From cc6c570bd7f18901a288be649dd7b9e422ac87a6 Mon Sep 17 00:00:00 2001
From: Andrew Simms <andrew.simms@nlr.gov>
Date: Mon, 13 Apr 2026 07:57:10 -0600
Subject: [PATCH 1/9] Package / Actions Cleanup - Continuation of #435 (#436)

This is a continuation and refinement of #435

Highlights:

## From #435

* Actions version updates:
  * checkout - v4 to v6
  * setup-python - v2 to v6
* cdip fixes

## Dependencies

### Module Dependencies

* Pin pandas below version 3.0
  * There are some subtle bugs related to underlying pandas changes that we should address and possibly fix that are out of scope of this PR.
* Refactor dependencies to move xarray, netcdf, and h5 dependencies into `all`
  * This helps standardize the versions for all modules, and behind the scenes xarray typically requires both netcdf and h5.

### Conda and Conda-Forge Dependency Definitions

* Move conda forge environment file into environment-dev.yml and create new conda-forge-build job to test the conda-forge specific no deps build

## Actions

### Linting

* Add filter to only run `black` on files that have changed
* Add Development Installation section to readme detailing pip, conda, and conda forge installation pathways

### Coveralls

* Pin coveralls action at v2
* Add a switch in main.yml to toggle reporting coveralls upload failures as test failures (recommended `fail-on-error: false` fix)
---
 .github/workflows/black.yml                   |  16 +-
 .github/workflows/main.yml                    | 274 +++++++++---------
 .github/workflows/pylint.yml                  |   4 +-
 .github/workflows/pypi.yml                    |   4 +-
 .github/workflows/test-wheel-build.yml        |   6 +-
 LICENSE.md                                    |   2 +-
 README.md                                     | 225 ++++++++++++--
 environment-dev.yml                           |  28 ++
 environment.yml                               |  23 +-
 .../data/dolfyn/{AQD_HR.PRF => AQD_HR.prf}    | Bin
 mhkit/utils/cache.py                          |   9 +-
 mhkit/utils/upcrossing.py                     |   4 +-
 pyproject.toml                                |  26 +-
 requirements-dev.txt                          |   4 -
 14 files changed, 414 insertions(+), 211 deletions(-)
 create mode 100644 environment-dev.yml
 rename examples/data/dolfyn/{AQD_HR.PRF => AQD_HR.prf} (100%)
 delete mode 100644 requirements-dev.txt

diff --git a/.github/workflows/black.yml b/.github/workflows/black.yml
index 96aaea347..a022a6634 100644
--- a/.github/workflows/black.yml
+++ b/.github/workflows/black.yml
@@ -8,17 +8,27 @@ jobs:
 
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
+
+      - name: Get changed Python files
+        id: changed-py-files
+        uses: tj-actions/changed-files@v47
+        with:
+          files: |
+            **.py
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        if: steps.changed-py-files.outputs.any_changed == 'true'
+        uses: actions/setup-python@v6
         with:
           python-version: "3.11"
 
       - name: Install Black
+        if: steps.changed-py-files.outputs.any_changed == 'true'
         run: |
           python -m pip install --upgrade pip
           pip install black
 
       - name: Check Black Formatting
-        run: black --check .
+        if: steps.changed-py-files.outputs.any_changed == 'true'
+        run: black --check ${{ steps.changed-py-files.outputs.all_changed_files }}
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index ba7925a8f..48c6f83ec 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -10,7 +10,25 @@ on:
       - main
       - develop
 
+# Global configuration for all jobs. Can be overridden at the job level if needed.
+env:
+  # Conda channels: Set conda forge as only channel and disable defaults channel
+  CONDA_MINICONDA_VERSION: latest
+  CONDA_AUTO_UPDATE_CONDA: true
+  CONDA_CHANNELS: conda-forge
+  CONDA_REMOVE_DEFAULTS: true
+  CONDA_USE_ONLY_TAR_BZ2: false
+  CONDA_ENVIRONMENT_FILE: environment-dev.yml
+  CONDA_ENVIRONMENT_NAME: mhkit-dev-env
+  # Coveralls: Set to false to ignore upload failures during outages.
+  #   Check status: https://status.coveralls.io/
+  COVERALLS_FAIL_ON_ERROR: true
+
 jobs:
+  # Set the operating system matrix for the following jobs/tests
+  # conda-forge-build
+  # pip-build
+  # hindcast-calls
   set-os:
     runs-on: ubuntu-latest
     outputs:
@@ -24,6 +42,8 @@ jobs:
             echo "matrix_os=[\"windows-latest\", \"ubuntu-latest\", \"macos-latest\"]" >> $GITHUB_OUTPUT
           fi
 
+
+  # This job decides if the hindcast test suite should run.
   check-changes:
     runs-on: ubuntu-latest
     outputs:
@@ -31,11 +51,11 @@ jobs:
       should-run-hindcast: ${{ steps.hindcast-logic.outputs.should-run-hindcast }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Check for changes in wave/io/hindcast
         id: changes
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@v4
         with:
           filters: |
             wave_io_hindcast:
@@ -56,45 +76,39 @@ jobs:
       PYTHON_VER: 3.11
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          python-version: ${{ env.PYTHON_VER }}
-          activate-environment: TESTconda
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare non-hindcast API data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/river/test_io_usgs.py
           pytest mhkit/tests/tidal/test_io.py
           pytest mhkit/tests/wave/io/test_cdip.py
 
       - name: Upload data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: data
           path: ~/.cache/mhkit
@@ -107,43 +121,37 @@ jobs:
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          activate-environment: TEST
-          python-version: ${{ env.PYTHON_VER }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare Wave Hindcast data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/wave/io/hindcast/test_hindcast.py
 
       - name: Upload Wave Hindcast data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit
@@ -156,49 +164,43 @@ jobs:
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          activate-environment: TEST
-          python-version: ${{ env.PYTHON_VER }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare Wind Hindcast data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/wave/io/hindcast/test_wind_toolkit.py
 
       - name: Upload Wind Hindcast data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit
 
-  conda-build:
-    name: conda-${{ matrix.os }}/${{ matrix.python-version }}
+  conda-forge-build:
+    name: conda-forge-${{ matrix.os }}/${{ matrix.python-version }}
     needs: [set-os, prepare-nonhindcast-cache]
     runs-on: ${{ matrix.os }}
     strategy:
@@ -210,50 +212,50 @@ jobs:
       PYTHON_VER: ${{ matrix.python-version }}
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          environment-file: environment.yml
-          activate-environment: TEST
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
           python-version: ${{ matrix.python-version }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e . --no-deps
+          pip install -e ".[all,dev]" --no-deps
+
+      - name: Download data from artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: data
+          path: ~/.cache/mhkit
 
       - name: Run pytest & generate coverage report
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           coverage run --rcfile=.github/workflows/.coveragerc --source=./mhkit/ -m pytest -c .github/workflows/pytest.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
-          flag-name: conda-${{ runner.os }}-py${{ matrix.python-version }}
+          flag-name: conda-forge-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   pip-build:
     name: pip-${{ matrix.os }}/${{ matrix.python-version }}
@@ -266,15 +268,22 @@ jobs:
         python-version: ['3.10', '3.11', '3.12']
 
     steps:
-      - uses: conda-incubator/setup-miniconda@v3
-
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
+      - name: Setup Python Virtual Environment
+        shell: bash
+        # The second command puts the venv bin directory on the PATH for
+        # subsequent steps in the job, which ensures that the correct Python
+        # version and installed packages are used.
+        run: |
+          python -m venv venv
+          echo "$PWD/venv/bin" >> $GITHUB_PATH
+
       - name: Set up Git repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Download data from artifact
         uses: actions/download-artifact@v4
@@ -284,35 +293,43 @@ jobs:
 
       - name: Install system dependencies
         if: runner.os == 'Linux'
-        run: sudo apt-get install -y libhdf5-dev libnetcdf-dev
+        run: |
+          # Update apt-get cache
+          sudo apt-get update
+          sudo apt-get install -y libhdf5-dev libnetcdf-dev
 
       - name: Update and install packages
-        shell: bash -l {0}
+        shell: bash
         run: |
           python -m pip install --upgrade pip wheel
-          pip install -e  ".[all,dev]"
+          pip install -e ".[all,dev]"
 
       - name: Reinstall h5py and netCDF4 with system libraries
         if: runner.os == 'Linux'
-        run: "pip install --force-reinstall --no-binary=:all: h5py netCDF4"
+        shell: bash
+        run: |
+          pip install --force-reinstall --no-binary=:all: h5py netCDF4
 
       - name: Install setuptools for Python 3.12
         if: matrix.python-version == '3.12'
-        run: pip install setuptools
+        shell: bash
+        run: |
+          pip install setuptools
 
       - name: Run pytest & generate coverage report
-        shell: bash -l {0}
+        shell: bash
         run: |
           coverage run --rcfile=.github/workflows/.coveragerc --source=./mhkit/ -m pytest -c .github/workflows/pytest.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: pip-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   hindcast-calls:
     name: hindcast-${{ matrix.os }}/${{ matrix.python-version }}
@@ -334,35 +351,29 @@ jobs:
         python-version: ['3.10', '3.11', '3.12']
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          environment-file: environment.yml
-          activate-environment: TEST
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
           python-version: ${{ matrix.python-version }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Download Wave Hindcast data from artifact
         uses: actions/download-artifact@v4
@@ -386,25 +397,25 @@ jobs:
       - name: Run hindcast pytest
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           coverage run --rcfile=.github/workflows/.coveragehindcastrc -m pytest -c .github/workflows/pytest-hindcast.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: hindcast-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   test-wheel-packaging:
     name: Test Built Wheel
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
@@ -465,10 +476,10 @@ jobs:
         python-version: ['3.12']
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
@@ -480,7 +491,10 @@ jobs:
 
       - name: Install system dependencies
         if: matrix.module != 'river' || matrix.module != 'power' || matrix.module != 'utils' || matrix.module != 'loads'
-        run: sudo apt-get install -y libhdf5-dev libnetcdf-dev
+        run: |
+          # Update apt-get cache
+          sudo apt-get update
+          sudo apt-get install -y libhdf5-dev libnetcdf-dev
 
       - name: Install MHKiT with optional dependency
         run: |
@@ -514,7 +528,7 @@ jobs:
           needs.prepare-nonhindcast-cache.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'skipped' &&
           needs.prepare-wind-hindcast-cache.result == 'skipped' &&
-          needs.check-changes.outputs.should-run-hindcast == 'false'    
+          needs.check-changes.outputs.should-run-hindcast == 'false'
         ) ||
         (
           needs.prepare-nonhindcast-cache.result == 'success' &&
@@ -527,10 +541,10 @@ jobs:
       matrix: ${{ steps.set-matrix.outputs.matrix }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
@@ -556,35 +570,29 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
-      - name: Set up Miniconda
+      - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v3
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          python-version: '3.12'
-          channels: conda-forge
-          activate-environment: TESTconda
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install notebook testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           conda install -y pytest coverage coveralls nbval jupyter utm folium
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Download non-hindcast data
         uses: actions/download-artifact@v4
@@ -622,7 +630,6 @@ jobs:
       - name: Run notebook
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           if [[ "${{ matrix.notebook }}" == "examples/metocean_example.ipynb" || "${{ matrix.notebook }}" == "examples/WPTO_hindcast_example.ipynb" ]]; then
             if [[ "${{ needs.check-changes.outputs.should-run-hindcast }}" == 'true' ]]; then
               jupyter nbconvert --to notebook --execute --inplace --ExecutePreprocessor.timeout=${{ matrix.timeout }} "${{ matrix.notebook }}"
@@ -639,7 +646,7 @@ jobs:
       [
         prepare-wave-hindcast-cache,
         prepare-wind-hindcast-cache,
-        conda-build,
+        conda-forge-build,
         pip-build,
         hindcast-calls,
       ]
@@ -647,14 +654,14 @@ jobs:
       always() &&
       (
         (
-          needs.conda-build.result == 'success' &&
+          needs.conda-forge-build.result == 'success' &&
           needs.pip-build.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'skipped' &&
           needs.prepare-wind-hindcast-cache.result == 'skipped' &&
           needs.hindcast-calls.result == 'skipped'
         ) ||
         (
-          needs.conda-build.result == 'success' &&
+          needs.conda-forge-build.result == 'success' &&
           needs.pip-build.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'success' &&
           needs.prepare-wind-hindcast-cache.result == 'success' &&
@@ -662,11 +669,10 @@ jobs:
         )
       )
     runs-on: ubuntu-latest
-    container: python:3-slim
     steps:
       - name: Coveralls Finished
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           parallel-finished: true
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml
index 27d52e520..6c85b7c67 100644
--- a/.github/workflows/pylint.yml
+++ b/.github/workflows/pylint.yml
@@ -8,10 +8,10 @@ jobs:
 
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
diff --git a/.github/workflows/pypi.yml b/.github/workflows/pypi.yml
index 9cc2d2e05..766251d91 100644
--- a/.github/workflows/pypi.yml
+++ b/.github/workflows/pypi.yml
@@ -19,11 +19,11 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.10'
 
diff --git a/.github/workflows/test-wheel-build.yml b/.github/workflows/test-wheel-build.yml
index 8186eff54..dd3ed5977 100644
--- a/.github/workflows/test-wheel-build.yml
+++ b/.github/workflows/test-wheel-build.yml
@@ -16,14 +16,14 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12']
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
diff --git a/LICENSE.md b/LICENSE.md
index 5b6698e8b..009012157 100644
--- a/LICENSE.md
+++ b/LICENSE.md
@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2019, Alliance for Energy Innovation, LLC under the terms of Contract DE-AC36-08GO28308, Battelle Memorial Institute under the terms of Contract DE-AC05-76RL01830, and National Technology & Engineering Solutions of Sandia, LLC under the terms of Contract DE-NA0003525. The U.S. Government retains certain rights in this software. 
+Copyright (c) 2026, Alliance for Energy Innovation, LLC under the terms of Contract DE-AC36-08GO28308, Battelle Memorial Institute under the terms of Contract DE-AC05-76RL01830, and National Technology & Engineering Solutions of Sandia, LLC under the terms of Contract DE-NA0003525. The U.S. Government retains certain rights in this software. 
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without
diff --git a/README.md b/README.md
index a95595db5..fcd51018c 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@
     </a>
 </p>
 
-MHKiT-Python is a Python package designed for marine renewable energy applications to assist in
+MHKiT-Python is a Python package designed for marine energy applications to assist in
 data processing and visualization. The software package include functionality for:
 
 - Data processing
@@ -33,55 +33,234 @@ See the [MHKiT documentation](https://mhkit-software.github.io/MHKiT) for more i
 ## Installation
 
 [MHKiT-Python](https://github.com/MHKiT-Software/MHKiT-Python) requires [Python (3.10-3.12)](https://www.python.org/).
-It is recommended to use the [Anaconda Python Distribution](https://www.anaconda.com/distribution/) (a fully featured Python installer with a GUI) 
-or [Miniconda](https://docs.anaconda.com/miniconda/#quick-command-line-install) (a lightweight installer with the ``conda`` command line utility).  
-Both will include most of MHKiT-Python's package dependencies. 
-MHKiT can be installed several ways:
 
-### Option 1: Install from Python
+See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.
+
+<details>
+
+<summary>Install with Anaconda/Miniconda (Recommended)</summary>
+
+### Install With Anaconda/Miniconda
 
-This option is recommended as a fast installation for MHKiT-Python users.
-To install MHKiT-Python using ``conda``, in an Anaconda Prompt:
+It is recommended to use the [Anaconda Python Distribution](https://www.anaconda.com/distribution/) (a fully featured Python installer with a GUI)
+or [Miniconda](https://docs.anaconda.com/miniconda/#quick-command-line-install) (a lightweight installer with the `conda` command line utility).  
+Both will include most of MHKiT-Python's package dependencies.
+
+This option is recommended for most MHKiT-Python users.
+To install MHKiT-Python using `conda`, in an Anaconda Prompt:
 
 ```bash
-	conda install -c conda-forge mhkit
+conda env create mhkit-env --python=3.11
 ```
 
-### Option 2: Clone Repository from GitHub
+```bash
+conda activate mhkit-env
+```
+
+```bash
+conda install -c conda-forge mhkit
+```
+
+Note: To use the above installed version of MHKiT-Python users must activate the `mhkit-env` environment each time, using `conda activate
+mhkit-env` in each new shell/terminal to use MHKiT.
+To avoid this, users can install MHKiT into their base conda environment, but this is not
+recommended as it may cause dependency conflicts with other software.
+
+Visual Studio Code has [instructions for using Python environments in VS Code](https://code.visualstudio.com/docs/python/environments) that support conda environment discovery.
+
+</details>
+
+<details>
+
+<summary>Clone Repository from GitHub</summary>
+
+### Clone Repository from GitHub
 
 This option is recommended for MHKiT-Python users who want access to example notebooks and developers.
+
+#### Step 1: Clone Repository
+
 Download and install your preferred version of [git](https://git-scm.com/).
 To clone MHKiT-Python:
 
 ```bash
-	git clone https://github.com/MHKiT-Software/MHKiT-Python
-	cd MHKiT-Python
+git clone https://github.com/MHKiT-Software/MHKiT-Python
+```
+
+```bash
+cd MHKiT-Python
 ```
 
+#### Step 2: Setup a Virtual Environment
+
+A virtual environment is a self-contained directory that contains a Python installation for a
+particular version of Python, plus a number of additional packages. Using a virtual environment
+allows you to manage dependencies for different projects separately, avoiding conflicts between
+packages and ensuring that your project has access to the specific versions of packages it needs.
+
+Use of a virtual environment is recommended to avoid dependency conflicts with other python
+packages (this environment must be activated in each new shell/terminal before using MHKiT).:
+
+##### Option A: Python `venv`
+
+Using Python venv (built into python) to create a virtual environment:
+
+###### Windows
+
+Note: A supported version of Python ([see installation for supported versions](#installation)) must be installed and added to the system PATH for venv to work in Git Bash or WSL. Use of Git Bash or WSL is recommended for Windows users to avoid issues with activating the virtual environment in Command Prompt or PowerShell.
+
+```sh
+python -m venv mhkit-env
+```
+
+```sh
+.\mhkit-env\Scripts\activate
+```
+
+Linux/MacOS:
+
+```bash
+python -m venv mhkit-env
+```
+
+```bash
+source mhkit-env/bin/activate
+```
+
+##### Option B: Conda (requires separate installation of Anaconda or Miniconda):
+
+```bash
+conda create -n mhkit-env python=3.11
+```
+
+```bash
+conda activate mhkit-env
+```
+
+#### Step 3: Install MHKiT-Python with pip
+
 To install a local, editable version of MHKiT-Python using [pip](https://pip.pypa.io/en/stable/):
 
 ```bash
-	pip install -e .["all"]
+pip install -e .["all,dev"]
 ```
 
-An [environment YAML file](https://github.com/MHKiT-Software/MHKiT-Python/blob/main/environment.yml) is also provided that can create the base environment required by MHKiT. 
+An [environment YAML file](https://github.com/MHKiT-Software/MHKiT-Python/blob/main/environment.yml) is also provided that can create the base environment required by MHKiT.
 MHKiT can then be installed into that environment using any of the provided methods.
 
-### Option 3: Module-specific Install from Python
+</details>
+
+<details>
+
+<summary>Module-specific Install using Pip</summary>
+
+### Module-specific Install using Pip
+
+A slim version of MHKiT-Python can be installed to reduce the number of dependencies and potential conflicts with other software.
+This installation utilizes pip's optional dependencies installation.
+
+Note: Use of a virtual environment is recommended to avoid dependency conflicts with other python.
+See Option 2 installation instructions for virtual environment setup.
 
-A slim version of MHKiT-Python can be installed to reduce the number of dependencies and potential conflicts with other software. 
-This installation utilizes pip's optional dependencies installation. 
 To install a single MHKiT module, e.g. the wave module, and its dependencies, use:
 
-	pip install mhkit["wave"]
+```bash
+pip install mhkit["wave"]
+```
+
+To install all MHKiT modules use:
+
+```bash
+pip install mhkit["all"]
+```
+
+Note: `pip install mhkit` does not install any MHKiT dependencies and will not work without installing dependencies separately.
+
+To install specific modules users must specify which module(s) they want to install with the optional dependencies installation syntax:
+
+```bash
+pip install mhkit "[<module>]"
+```
+
+Or multiple modules with:
+
+```bash
+pip install mhkit "[<module>,<module>]"
+```
+
+Supported modules are:
+
+- `dolfyn`
+- `wave`
+- `tidal`
+- `river`
+- `power`
+- `loads`
+- `mooring`
+- `acoustics`
+- `qc`
+- `all` (includes the above modules and their dependencies)
+- `dev` (includes development dependencies for contributing to MHKiT)
+- `examples` (includes dependencies for running MHKiT example notebooks)
 
-Note that ``pip install mhkit`` only installs the base MHKiT dependencies and not the entire software.
 To install all MHKiT dependencies use:
 
-	pip install mhkit["all"]
+```bash
+pip install mhkit["all"]
+```
 
 See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.
 
+</details>
+
+<details>
+
+<summary>Development Installation</summary>
+
+### Development Installation
+
+For developers contributing to MHKiT, there are three development installation strategies after
+cloning the repository locally:
+
+Note: Use of a virtual environment is recommended to avoid dependency conflicts with other python.
+See Option 2 installation instructions for virtual environment setup.
+
+**Pip development** (no conda):
+
+Setup and activate virtual environment using Python venv using [the instructions above](#python-venv) and then:
+
+Note: Developers can create multiple virtual environments by changing the name, `python -m venv <name>`, install isolated versions of MHKiT, and switch between them by activating the desired environment. This allows developers to test different versions of MHKiT and its dependencies without conflicts.
+
+```bash
+pip install -e ".[all,dev]"
+```
+
+**Conda development** (minimal conda + pip resolves deps):
+
+```bash
+conda env create -f environment.yml
+```
+
+```bash
+conda activate mhkit-env
+```
+
+```bash
+pip install -e ".[all,dev]"
+```
+
+**Conda-forge development** (all deps from conda-forge, mirrors production deployment):
+
+```bash
+conda env create -f environment-dev.yml
+conda activate mhkit-env
+pip install -e ".[all,dev]" --no-deps
+```
+
+The conda-forge option mirrors how users install MHKiT via `conda install -c conda-forge mhkit`, ensuring all dependencies come from the conda-forge channel. The `--no-deps` flag prevents pip from resolving dependencies, relying entirely on the conda-forge packages for dependencies. The conda-forge build and deployment happens in separate repository: [https://github.com/conda-forge/mhkit-feedstock] which is updated with each MHKiT release.
+
+</details>
+
 ## Copyright and license
 
 MHKiT-Python is copyright through the National Laboratory of the Rockies,
@@ -114,7 +293,7 @@ The GitHub platform has the Fork feature that facilitates code modification and
 
 ## Creating a branch
 
-The GitHub platform has the branch feature that facilitates code contributions and collaboration amongst developers. A branch isolates development work without affecting other branches in the repository. Each repository has one default branch, and can have multiple other branches. To create a branch of your forked MHKiT-Python repository, follow the steps below. More information about GitHub branches can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-branches)
+The GitHub platform has the branch feature that facilitates code contributions and collaboration. A branch isolates development work without affecting other branches in the repository. Each repository has one default branch, and can have multiple other branches. To create a branch of your forked MHKiT-Python repository, follow the steps below. More information about GitHub branches can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-branches)
 
 1. Navigate to your fork of MHKiT-Python (see instructions above)
 2. Above the list of files, click **Branches**.
@@ -128,13 +307,13 @@ The GitHub platform has the pull request feature that allows you to propose chan
 
 1. Navigate to the [MHKiT-Python main page](https://github.com/MHKiT-Software/MHKiT-Python)
 2. Above the list of files, click **Pull request**.
-3. On the compare page, click **Compare accross forks**.
+3. On the compare page, click **Compare across forks**.
 4. In the "base branch" drop-down menu, select the branch of the upstream repository you'd like to merge changes into.
 5. In the "head fork" drop-down menu, select your fork, then use the "compare branch" drop-down menu to select the branch you made your changes in.
 6. Type a title and description for your pull request.
 7. If you want to allow anyone with push access to the upstream repository to make changes to your pull request, select **Allow edits from maintainers**.
 8. To create a pull request that is ready for review, click **Create Pull Request**. To create a draft pull request, use the drop-down and select **Create Draft Pull Request**, then click **Draft Pull Request**. More information about draft pull requests can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-pull-requests#draft-pull-requests)
-9. MHKiT-Python adminstrators will review your pull request and contact you if needed.
+9. MHKiT-Python administrators will review your pull request and contact you if needed.
 
 ## Code Formatting in MHKiT
 
diff --git a/environment-dev.yml b/environment-dev.yml
new file mode 100644
index 000000000..958ff6e2c
--- /dev/null
+++ b/environment-dev.yml
@@ -0,0 +1,28 @@
+name: mhkit-dev-env
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python>=3.10,<3.13
+  - pip
+  - numpy>=2.0.0
+  - pandas>=2.2.2,<3.0
+  - scipy>=1.14.0
+  - xarray>=2024.6.0
+  - scikit-learn>=1.5.1
+  - h5py>=3.11.0
+  - h5pyd>=0.18.0
+  - netCDF4>=1.6.5
+  - hdf5>=1.14.3,<1.14.5.0a0
+  - statsmodels>=0.14.2
+  - requests
+  - beautifulsoup4
+  - numexpr>=2.10.0
+  - lxml
+  - bottleneck
+  - pecos>=0.3.0
+  - notebook
+  - matplotlib>=3.9.1
+  - fatpack
+  - nrel-rex
+  - cartopy
diff --git a/environment.yml b/environment.yml
index 884a2e01d..d484f58a8 100644
--- a/environment.yml
+++ b/environment.yml
@@ -3,26 +3,5 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python>=3.10,<3.13
+  - python=3.11
   - pip
-  - numpy>=2.0.0
-  - pandas>=2.2.2
-  - scipy>=1.14.0
-  - xarray>=2024.6.0
-  - scikit-learn>=1.5.1
-  - h5py>=3.11.0
-  - h5pyd>=0.18.0
-  - netCDF4>=1.6.5
-  - hdf5>=1.14.3,<1.14.5.0a0
-  - statsmodels>=0.14.2
-  - requests
-  - beautifulsoup4
-  - numexpr>=2.10.0
-  - lxml
-  - bottleneck
-  - pecos>=0.3.0
-  - notebook
-  - matplotlib>=3.9.1
-  - fatpack
-  - nrel-rex
-  - cartopy
diff --git a/examples/data/dolfyn/AQD_HR.PRF b/examples/data/dolfyn/AQD_HR.prf
similarity index 100%
rename from examples/data/dolfyn/AQD_HR.PRF
rename to examples/data/dolfyn/AQD_HR.prf
diff --git a/mhkit/utils/cache.py b/mhkit/utils/cache.py
index c4897c12c..78744dbf8 100644
--- a/mhkit/utils/cache.py
+++ b/mhkit/utils/cache.py
@@ -119,7 +119,11 @@ def _load_cache(file_extension, cache_filepath):
             )
         elif file_extension == ".pkl":
             with open(cache_filepath, "rb") as f:
-                data, metadata = pickle.load(f)
+                data_dict = pickle.load(f)  # some format of 'data' and 'metadata'
+                if isinstance(data_dict, tuple):
+                    # CDIP and WPTO hindcast call returns size 2 tuple
+                    return data_dict[0], data_dict[1]
+                data, metadata = data_dict["data"], data_dict["metadata"]
 
         return data, metadata
 
@@ -154,7 +158,8 @@ def _write_cache(data, metadata, file_extension, cache_filepath):
     if os.path.isfile(cache_filepath) and (
         cache_content is None or cache_content["data"] is None
     ):
-        return _load_cache(file_extension, cache_filepath) + (cache_filepath,)
+        data, metadata = _load_cache(file_extension, cache_filepath)
+        return data, metadata, cache_filepath
 
     # Store data in cache if provided
     if cache_content and cache_content["data"] is not None:
diff --git a/mhkit/utils/upcrossing.py b/mhkit/utils/upcrossing.py
index 7ab06a0ed..c48e18cc5 100644
--- a/mhkit/utils/upcrossing.py
+++ b/mhkit/utils/upcrossing.py
@@ -93,7 +93,9 @@ def upcrossing(t: np.ndarray, data: np.ndarray) -> np.ndarray:
 
     # eliminate zeros
     zero_mask = data == 0
-    data[zero_mask] = 0.5 * np.min(np.abs(data))
+    if any(zero_mask):
+        # avoid double counting zeros by making them small and positive
+        data[zero_mask] = 0.5 * np.min(np.abs(data))
 
     # zero up-crossings
     diff = np.diff(np.sign(data))
diff --git a/pyproject.toml b/pyproject.toml
index c0c7df262..d30cf3751 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,10 +21,16 @@ classifiers = [
 ]
 requires-python = ">=3.10"
 dependencies = [
+    # MHKiT-Python uses xarray everywhere, which leverages netcdf and h5 behind the
+    # scenes. xarray, netcdf4, and h5 dependencies should all be synced to avoid
+    # compatibility issues with individual modules.
+    "xarray>=2024.6.0",
+    "netCDF4>=1.7.1.post1",
+    "h5py>=3.11.0",
+    "h5pyd>=0.18.0",
     "numpy>=2.0.0",
-    "pandas>=2.2.2",
+    "pandas>=2.2.2,<3.0",
     "scipy>=1.14.0",
-    "xarray>=2024.6.0",
     "matplotlib>=3.9.1",
     "pecos>=0.3.0",
     "requests",
@@ -35,28 +41,22 @@ dependencies = [
 wave = [
     "scikit-learn>=1.5.1",
     "statsmodels>=0.14.2",
-    "netCDF4>=1.7.1.post1",
     "pytz",
     "NREL-rex>=0.2.63",
     "beautifulsoup4",
     "bottleneck",
-    "lxml"
+    "lxml",
 ]
 
 tidal = [
-    "netCDF4>=1.7.1.post1",
-    "bottleneck"
+    "bottleneck",
 ]
 
 river = [
-    "netCDF4>=1.7.1.post1",
     "bottleneck",
 ]
 
 dolfyn = [
-    "h5py>=3.11.0",
-    "h5pyd>=0.18.0",
-    "netCDF4>=1.7.1.post1",
     "cartopy",
 ]
 
@@ -91,11 +91,10 @@ dev = [
     "pytest-cov",
     "pre-commit",
     "coverage",
-    "coveralls"
+    "coveralls",
+    "black",
 ]
 
-
-
 # Install all optional dependencies
 all = [
     "mhkit[wave]",
@@ -119,7 +118,6 @@ examples = [
     "utm",
     "folium",
     "mhkit[all]",
-
 ]
 
 [project.urls]
diff --git a/requirements-dev.txt b/requirements-dev.txt
deleted file mode 100644
index 83e60c9dd..000000000
--- a/requirements-dev.txt
+++ /dev/null
@@ -1,4 +0,0 @@
-# requirements-dev.txt
-black
-pylint
-pytest

From ff2d805969deb291e34be7f78139f07a8ba3032b Mon Sep 17 00:00:00 2001
From: Emily Browning <63879572+browniea@users.noreply.github.com>
Date: Thu, 16 Apr 2026 11:53:07 -0800
Subject: [PATCH 2/9] D3D updates (#428)

Updates to `io/d3d.py` code

- Added new coordinate names for the latest version of Delft3D
- new `calculate_grid_convergence_index` function to calculate the grid
convergence index between two grid's results basted on the equation
[GCI]( https://www.grc.nasa.gov/WWW/wind/valid/tutorial/spatconv.html)
- Allows xarray or netCDF4 input

---------

Co-authored-by: akeeste <akeeste@sandia.gov>
Co-authored-by: Simms, Andrew <andrew.simms@nlr.gov>
---
 examples/Delft3D_example.ipynb   |  56 ++--
 mhkit/river/io/d3d.py            | 471 +++++++++++++++++++++++--------
 mhkit/tests/river/test_io_d3d.py |  91 +++++-
 3 files changed, 464 insertions(+), 154 deletions(-)

diff --git a/examples/Delft3D_example.ipynb b/examples/Delft3D_example.ipynb
index 8bb9e8702..c2342fb56 100644
--- a/examples/Delft3D_example.ipynb
+++ b/examples/Delft3D_example.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 18,
    "id": "030973b3",
    "metadata": {},
    "outputs": [],
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 19,
    "id": "258b202f",
    "metadata": {},
    "outputs": [
@@ -138,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 20,
    "id": "5e0dabc1",
    "metadata": {},
    "outputs": [
@@ -165,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 32,
    "id": "ebbdc284",
    "metadata": {},
    "outputs": [
@@ -180,14 +180,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\sterl\\AppData\\Local\\Temp\\ipykernel_21668\\3610353735.py:2: UserWarning: Warning: seconds_run not found. Closest time stampfound 60.0\n",
-      "  time_index = d3d._convert_time(d3d_data, seconds_run=seconds_run)\n"
+      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\river\\io\\d3d.py:87: UserWarning: Warning: seconds_run not found. Closest time stampfound 60.0\n",
+      "  time_index: int\n"
      ]
     }
    ],
    "source": [
     "seconds_run = 62\n",
-    "time_index = d3d._convert_time(d3d_data, seconds_run=seconds_run)\n",
+    "time_index = d3d.seconds_to_index(d3d_data, seconds_run=seconds_run)\n",
     "print(time_index)"
    ]
   },
@@ -204,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 22,
    "id": "197ab8f9",
    "metadata": {},
    "outputs": [
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 23,
    "id": "26e1daba",
    "metadata": {},
    "outputs": [
@@ -333,7 +333,7 @@
        "4      16.426020  3.0    1.000931"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -369,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 24,
    "id": "199785ce",
    "metadata": {},
    "outputs": [
@@ -379,13 +379,13 @@
        "Text(0.5, 1.0, 'Centerline Velocity at: 240.0 s')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 1200x500 with 1 Axes>"
       ]
@@ -426,7 +426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 25,
    "id": "26daf026",
    "metadata": {},
    "outputs": [
@@ -436,13 +436,13 @@
        "Text(0.5, 1.0, 'Velocity on Layer 2 at Time: 240.0 s')"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -487,7 +487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 26,
    "id": "baf1e542",
    "metadata": {},
    "outputs": [
@@ -613,7 +613,7 @@
        "[4000 rows x 3 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -638,7 +638,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 27,
    "id": "441f059a",
    "metadata": {},
    "outputs": [],
@@ -660,13 +660,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 28,
    "id": "d04fa7ad",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -711,7 +711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 29,
    "id": "857acdd2",
    "metadata": {},
    "outputs": [
@@ -923,13 +923,13 @@
        "[4000 rows x 8 columns]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -983,7 +983,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 30,
    "id": "941d76b7",
    "metadata": {},
    "outputs": [
@@ -1201,7 +1201,7 @@
        "[5760 rows x 9 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1256,7 +1256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 31,
    "id": "75433d08",
    "metadata": {
     "scrolled": true
@@ -1271,7 +1271,7 @@
     },
     {
      "data": {
-      "image/png": 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OHIG9vb3CZdapUwdHjx7Fm2++icaNGyMnJ0f2mqu7p6pnz56oW7cuAE7EQEQkj0QQ8x22REREpDGnTp2S9XqmpqbyfiMiqlVBQQEOHDiAPXv24M8//0RaWhrMzc3RrFkzDBs2DNOmTYODg0OlfRTpeX/55Zdx6NAhbTVbZXwILBERkYlYs2YNgKc9SAxGRKSIbdu2yUZMtGzZEgMHDkRubi4SExMxb948bN++HfHx8ZUebxEcHFxteXFxccjKykL37t213nZVsOeIiIjIBOzbtw8DBw5EeXk59u3bh1dffVXfTSIiA7Bp0yYkJiZi6tSpaNmypWx5RkYG+vfvj7///hujRo3Ctm3bai3r8ePHaNiwIYqLi3HlyhX4+flps+kqYTgiIiIyUnfu3EG3bt1QUFCAzMxMAMDrr7+OPXv26LllRGQMjh8/ji5dusDa2hq5ubmwsrKqcfv169dj4sSJ6NSpE44fP66jViqHEzIQEREZqbKyMqSlpSErKwseHh6YOnUqtm/fru9mEZGRCAgIAPD0kRIPHz6sdfutW7cCAP7v//5Pq+1SB3uOiIiIiIhIaefPn8fzzz8PS0tL5OXl1TgD5u3bt+Ht7Q0LCwtkZGSgXr16Omyp4thzRERERERESlu1ahUAoF+/frU+GuDHH3+EIAh49dVXRRuMAM5Wp1MVFRW4d+8eHB0dNf6QRiIiIiJSnyAIyMvLg7u7O8zMxNWPUFRUhJKSErXKEAShynWotbW10s8927dvHzZs2ABLS0ssXLiw1u0NYUgdwHCkU/fu3YOnp6e+m0FEREREtUhPT4eHh4e+myFTVFSEJl72yHxQoVY5Dg4OyM/Pr7Rs3rx5CA8PV7iMy5cvY8yYMRAEAcuXL5fde1Sd06dP4+LFi3BxccGAAQNUabbOMBzpkKOjIwAgqO4YWJjVPJsHEdWszKeR1uvI87bVeh2a9qSRuL7l1Bb7DPUuDnTN8VahTuqxuJmhk3qIjFlZRQmOPNoqu24Ti5KSEmQ+qMDR5PpwcFBtBFJ+voAeLz5Aeno6nJycZMuV6TW6e/cu+vXrh+zsbEybNg1hYWG17iPtNRoxYoTSPVS6xnCkQ9IuTAszK4YjIjWU+TbWyZuXhaWNDmrRjPzGT0ORuZ7boStF3oDDXcMJSBYWupn7iJ8tRJoj1lsgHBwkcHBU9Yuwp++bTk5OlcKRoh49eoQ+ffogLS0N48aNw4oVK2rdp7y8HP/73/8AAGPGjFG6Tl0T7VeMp06dwrJlyzB06FB4eHhAIpGodJJGRUXJ9q3pZ/PmzZX2CwkJqXH7devWaeqlEpESynwb66SePB/D6TWSBiNTY0ivW1fnk67+PojI9OTn5+PVV1/FxYsXMXToUKxfv16ha/M//vgDGRkZ8PLyQvfu3XXQUvWItudo4cKF2L17t9rlNGvWDMHBwXLX5eTkIDY2FgDQrVs3udv07dsXDRs2rLK8RYsWareNiEgdhhQOtEV6DAypF0nbynwbw+L6XX03g4iMSHFxMQYNGoTk5GT07dsX27dvh7m5YmMVpEPqxowZI9reuGeJNhx17twZbdq0QceOHdGxY0d4e3ujuLhY6XK6detWbfD59ttvERsbi65du6Jp06Zyt5k1axaCgoKUrpeINI+9Rv9iMKosv7GZ6ANSno8tHG/q5t4jIiJNKS8vx6hRo3Do0CF0794du3btgpWVYkN4CwoKEBMTA0D8s9RJiTYczZw5U+t1GMqUgkTE4ULPYjCSzxB6kXQVkNh7RESaEhERIQs4rq6umDRpktztVqxYAVdX10rLYmNjkZ+fj44dOxrMqCvRhiNtu3nzJhITE2FlZYWRI0fquzlEJBJi7jViKFKMIfQiEREZiuzsbNn/S0OSPOHh4VXC0bND6gyFyYYj6T9W//79UadOnWq327VrF3bu3Iny8nL4+PhgwIAB8Pf311UziYgAMBgpS8wBib1HRGRIwsPDlXoG0rP27dun2cbogMmHo9qG1K1Zs6bS7zNnzsR7772HVatWwcLCZA8fkU6Z+r1GDEaqMYRhdkREJC4m+YmbnJyMK1euoG7duujfv7/cbdq1a4d169bhypUrKCgowI0bN7B27Vq4uLjgm2++wccff1xrPcXFxcjNza30Q0SkDAYj9YnxGIo1iBMRmTrxfWLogLTXaOTIkdXOthEWFoZ33nkHfn5+sLW1hY+PDyZNmoSEhARYWVkhIiIC6enpNdazdOlSODs7y348PT01/lqIjFmZb2OT7jUS40U9GRZd/g0RERkDk/vkLSsrw08//QRAtVnqWrdujYEDB6KsrAx//PFHjdvOnj0bOTk5sp/awhQRPaXrCzoGI+MnxuOpy/OOIYmISDEmd9PMgQMH8ODBAzRt2hRdunRRqQw/Pz8AQEZGRo3bWVtbw9raWqU6iEwFL9iqEuOFvDEQ4yQNun72UW1/b5zAgYhMncmFI01MKSid0tDe3l4jbSIydmIOQGLrNWIw0i4xBiQxkfe3ysBERKbEpD6F8/PzsXv3bgCqh6Pi4mLExcUBANq3b6+xthEZKzEHI7FhMNINsR1nsQV0IiJTJq5PCDVERETA398fs2fPrnabXbt2oaCgAJ06dZINjZPn8uXL2LJlC4qLiystz8zMxJtvvon09HQEBASga9euGms/kTESezAS00Wp2C7YjR2Pt+LE/ndMRKRJoh1WFxcXh4ULF8p+LykpAQB06tRJtmzOnDmyqbizsrKQmppa431Aij7b6P79+xg7dizCwsLwwgsvwM3NDffu3cOpU6eQl5cHDw8P7NixAxKJROXXR2TsxH5BJaZgRPohpiF2ur73SFl8oCwRmQrRhqPMzEycOHGiyvJnl2VmZipcXkZGBg4dOgRLS0u88cYbNW7bvHlzTJ06FUlJSTh37hwePnwIa2trNG/eHAMGDEBYWBjq1Kmj+IshIqoBezH0hwFJcQxIRGQKJIIgCPpuhKnIzc2Fs7MzermGwsJM/vOViIwBe40Ux2AkDmIJSGIORwAnZyDTUFZRgoNZkcjJyYGTk5O+myMjvY48fbEBHBxV++zIz6tA+1b/iO61iQk/lYlIoxiMFMdgJB5i+bcQ0/kpj9j/vomI1CWOTwMiIhMjlotx+hf/TYiIiJ8ERKQxYv9WWSzfyvMinGoilvO0OmL/OyciUodoJ2QgIjJGYgxGBR76u9/G7o64jof030ff9yBxcgYiIv1gOCIijRD7t8li+DZe18FIn6FHUYq2UdchSkyz2BERke6I6ys7IiItYDAyfPp4Pfru5RPDeUtEZGoYjoiItIzBSDMKPCp0/toYkKon9t5iIiJVMBwRkVHT58VlfmMznV5c6yM86IOpBSQiItIdvuMTkdrE+g2yvoKRrkMRYLy9RdXRR0DSV0gSc+8REZGxYTgiIqOkz2Cka6YWjKRMaZgdAxIRkW4wHBERaYg+eotMNRg9y5R6kcRGrL3GRKQ5BQUFiI2Nxfjx49GiRQvY2NjA3t4eAQEBWLBgAfLz8xUqp1evXpBIJJBIJLhz546WW606vrsTkVrEeHGk62/ZOYxO/0xhNjv2HhGRPmzbtg1DhgxBZGQkzM3NMXDgQHTv3h03b97EvHnz0LFjRzx48KDGMqKiovDHH39AIpHoqNWqYzgiIlIDh9GJBwMSEZHmWVpaYuLEibh48SIuXryIHTt24LfffkNqairatWuHy5cvY+rUqdXun5mZienTp6NPnz5o0qSJ7hquIoYjIjIqurx4ZDASH1O6D0ksxNh7TESaExwcjO+++w4tW7astLxRo0ZYu3YtAGDXrl0oKSmRu//UqVNRUFCAb775Rutt1QTTfkcnIrWY8kUR7y8SN2MOSOw9IiKxCAgIAAAUFxfj4cOHVdb/9ttv2LZtGz799FP4+vrqunkqYTgiIqOhq4tG3l9kGIw5IBERicGNGzcAPB16V7du3Urrnjx5gvfeew/+/v6YMWOGPpqnEr6TExGJGIORehiQdMOUe5GJTNmqVasAAP369YO1tXWldXPnzsWtW7ewbt06WFlZ6aN5KrHQdwOIyDCZ6sWQLi9+GYw0o8CjAnZ3jCu05PnYwvFmob6bQUQGKjc3t9Lv1tbWVcJNbfbt24cNGzbA0tISCxcurLTu9OnTWLVqFYKDgxEYGKh2e3WJ4YiIjIIuhtQxGBkuXQak/MZmcLjLfz8i0o4DT/xhI1HtEr7oSRmAf+Dp6Vlp+bx58xAeHq5wOZcvX8aYMWMgCAKWL18uu/cIAMrLyzFhwgS4uLhgxYoVKrVTnxiOiEhpptprpCsMRtrBgKRdZb6NYXH9rr6bQUQKSE9Ph5OTk+x3ZXqN7t69i379+iE7OxvTpk1DWFhYpfVff/01/v77b2zYsAGurq4aa7OuMBwRESlAV71GDEbaZUxD7Di0johU5eTkVCkcKerRo0fo06cP0tLSMG7cOLk9Q3v27IFEIsGmTZuwefPmSuvu378PABgxYgSsra0xa9Ys9OvXT7UXoSUMR0SkFFPsNWIwMi66CkjsPSIiY5Kfn49XX30VFy9exNChQ7F+/XpIJBK52wqCgKNHj1ZbVlJSEgAgJCREG01VC8MRESlMrMHIGJ77wmCkW8bUgyQ2DEhExqe4uBiDBg1CcnIy+vbti+3bt8Pc3FzutkeOHKm2HG9vb6SlpSE9PR0eHh5aaq16GI6IyOAYQxgi06Dt3iN5fwscakdEmlReXo5Ro0bh0KFD6N69O3bt2mVQU3Mri+GIiAwKgxGR+LH3iMh4REREICYmBgDg6uqKSZMmyd1uxYoVBjkBw38xHBERkUni0DoiotplZ2fL/l8akuQJDw83inDETwUiUohY7zfSNl1MxsD7jYiISKzCw8MhCEKtP97e3rWWdevWLQiCINr7jQCGIyKiaunyoa+kH7oIpvmNzXR6LnHoKRGR6vjJT0QGQ5cXfZy+mzSNYZuISPz4Tk1E9Axdf8tPpsWUzi1THYpLRIbNdN6liYhqoesLV/YaiYOu/x1MKSARERkavkMTUa34DTCRZmk7IPG+IyIi1TAcEZFB0PbFHr/NN2366MXjOUdEJD58ZyYik6ePi1QOqSPA+AMSe52JyNDwIbBEZNKM/eKUFGdsD4XN87GF481CfTeDiEhpTZs21Ug5EokE169fV2ofhiMiqpEYvvnV1pA6fQUj9hrRs/Ibm8HhLs8JIiKpW7duaaQciUSi9D6i/Yrs1KlTWLZsGYYOHQoPDw9IJBKVXiAAeHt7y/aX93P58mW5+5WXl+Orr77C888/D1tbW7i5uWHkyJG4dOmSOi+NiESAPUYkj76CK89HIqLKQkJCUFFRofJPcHCwSvWKtudo4cKF2L17t0bLrO4gOTs7V1lWUVGBESNGICYmBi4uLujfvz+ysrIQHR2NuLg4HD58GC+++KJG20dExo+9RlQd9iAREemfaMNR586d0aZNG3Ts2BEdO3aEt7c3iouL1SozKipK4W0jIyMRExMDPz8/JCQkoEGDBgCAnTt3Yvjw4Rg9ejQuXboECwvRHkIiqga/pSdTIYb7jsp8G8Pi+l29toGIDMtXX32FVq1aqVXGW2+9hbZt2yq9n2iv7GfOnKnX+leuXAkA+OKLL2TBCACGDRuGgQMH4pdffsHu3bsxbNgwfTWRSOuM8X4jfQYj9hoZBn1OzMDeIyIiICwsTO0yevfujd69eyu9H78+lePmzZu4dOkSbG1t0b9//yrrhw8fDgDYs2ePrptGRERGjj2bRET6I9qeI21Yvnw5rl+/Dmtra7Ru3RpDhgyBm5tble3Onj0LAHjuuedgaWlZZX379u0BACkpKdptMJGJM6ZeIzIsxjSttxiG1hERacP169dx6dIlmJmZoVWrVvD29la7TJMKRzNmzKj0+4cffog1a9YgNDS00vLbt28DADw8POSWI12elpamhVYSkTHikDpShrENr+N9R0SkSY8fP8aECRMQExMDABAEARKJBKNGjcJ3330He3t7lcs2jq/FajFw4EDs2rULaWlpKCgowPnz5zFt2jQUFxdjwoQJVWbFy8/PBwDY2dnJLU96wPPy8mqst7i4GLm5uZV+iAyFGO43ItInYwq02npWGBGRPrzzzjvYv38/5s6di71792LHjh0YNGgQtm3bhmnTpqlVtkn0HK1evbrS761bt8aXX34Jf39/TJw4ETNnzsSgQYM0Xu/SpUsxf/58jZdLZAqM6WLOmC6yiYiItK2kpARWVlZy11VUVCA2NhZfffUVJk2aJFs+fPhwvPTSS4iOjsZ3332nct0m0XNUnfHjx6N+/fpITU2t9CReBwcHAEBBQYHc/Z48eQIAcHR0rLH82bNnIycnR/aTnp6umYYTkdJ4vxEREZFhaNWqFfbu3St3XVlZGUpLS1G/fv0q61xdXdV+9I9JXy2YmZnB19cXAJCRkSFb3qRJEwDAnTt35O4nXe7l5VVj+dbW1nBycqr0Q0T6oa/7N9hrZNiM6d9P372xHKpLRIpq1qwZBg0ahAEDBuDGjRuV1llZWeHFF1/EJ598gj///BNFRUV49OgR1qxZg/3796Nbt25q1W3S4QgAsrOzAaDSjVsBAQEAgPPnz6O0tLTKPqdPnwYAtGnTRgctJNI9fV/E6PsijoiIiPTnt99+Q3R0NC5cuIDWrVtj7ty5KCoqkq3/9ttvkZ+fj8DAQNjb28PNzQ1hYWFo3LgxVq1apVbdJh2OLly4gNTUVNjZ2cHf31+23MfHBy1btkRhYSHi4uKq7BcdHQ0AGDBggM7aSkSGx5h6HUwZ/x2JyJQVFBQgNjYW48ePR4sWLWBjYwN7e3sEBARgwYIFsonMnpWeno5vvvkGISEhaNmyJczMzCCRSHDkyBGF6x0yZAguXryIGTNmYMWKFfD395fNTteuXTtcu3YN3377LaZOnYqpU6fihx9+QGpqKlq0aKHW6zWacBQREQF/f3/Mnj270vJ9+/bh0KFDVbZPSUnBiBEjIAgCJkyYUOWmL+lMFzNmzMCDBw9ky3ft2oVffvlF1t1HRERkKNgrS0TK2rZtG4YMGYLIyEiYm5tj4MCB6N69O27evIl58+ahY8eOla6VAWDnzp2YPHkyNm3ahMuXL0MQBJXqtrGxwfz583HhwgW0adMGw4YNQ79+/XDlyhXY2dlh4sSJ+PLLL/Hll18iNDQUNjY2ar9e0YajuLg4dOrUSfZTUlICAJWWPdurk5WVhdTU1Er3DgFAcnIyXnnlFXh7e2PQoEEYNWoUXnrpJXTo0AGXLl1CUFAQli1bVqX+0NBQDBkyBFevXoW/vz9GjBiBl19+GcOHD4etrS22bt0KCwuTmOyPSKeM5eKNvQ3Ghf+emqHvIbtEpDxLS0tMnDgRFy9exMWLF7Fjxw789ttvSE1NRbt27XD58mVMnTq10j5NmzbF1KlT8eOPP+LKlSvo06ePWm3w8fHBL7/8gri4ONy4cQNt2rTBrFmzZJOkaZJor+4zMzNx4sSJKsufXZaZmVlrOX379kV6ejpOnjyJY8eOIScnB05OTujWrRtGjx6NcePGwdzcvMp+ZmZm+Pnnn7Fq1SpERkZi7969sLe3x7BhwzB//ny0atVKvRdIJFK8eCEybnk+tnC8WajvZhCRgQgODkZwcHCV5Y0aNcLatWvRpUsX7Nq1q9L02wMHDsTAgQNl20okEo205dVXX0WvXr2wfPlyLFmyBD/++CNWrFiBN954QyPlA4BEULWfi5SWm5sLZ2dn9HINhYWZ/LnbifRNn+FI271GuprOm70Mxsvujm7OIW3PrqjPcGRx/a7e6iZSRFlFCQ5mRcq+UBcL6XXkspOBsHFQrX+jKL8MszrGa+y1FRQUyCY1u3fvHho1aiR3u379+mH//v04fPgwgoKCFCr79u3bWLFiBc6cOYPs7Gw0adIEr7/+Ot5++21YWFggPT0d06ZNw86dOxEUFISIiAiNdF6IdlgdERGR2DD4EhH9SzrNtqWlJerWrauxcuPj4+Hv74+IiAg8ePAADg4O+OuvvzBlyhR06tQJRUVF8PT0xM8//4zff/8d9+/fR9u2bTF9+nTk5eWpVTfDERGRBvHimTRB272c+ry3j0N3ifQvNze30o+qD06VTpvdr18/WFtba6x9H330EaysrJCQkIDLly/j+PHjuHfvHmbPno2///4bkZGRsm1feeUVpKSkYMmSJfjhhx8qzUCtCtHec0REumfMQ+qINKXAo0Lrw+v09dBiIhK/+IfNYVmk2u0ZpU9KAMTD09Oz0vJ58+YhPDxcqbL27duHDRs2wNLSEgsXLlSpPdU5d+4cXnvtNXTt2lW2zNzcHDNmzMCSJUuQkpJSaXsLCwt89NFHGD16NGbMmKFW3QxHREQawl4jMiScmIHIdKWnp1e650jZXp/Lly9jzJgxEAQBy5cvR0BAgEbb5+7ujr///ht5eXlwdHSULY+PjweAau9tatSoEbZs2aJW3QxHRKR37DUiQ6OL3iMiIm1xcnJSeUKGu3fvol+/fsjOzsa0adMQFham4dY9fd7oBx98AH9/fwwaNAh16tTBlStXsHfvXri4uCA0NFTjdUoxHBERaQB7jUiT8hubGfXQujLfxpy1jsgAPXr0CH369EFaWhrGjRuHFStWaKWeKVOmoF69eli0aBG+//57VFRUwMbGBq+99hoWL15cZVigJjEcEREA479JWps3uDMYmSZj6D3i0DoiUlR+fj5effVVXLx4EUOHDsX69es19vwieUaNGoVRo0ahpKQEOTk5cHNz01pdzzLsd3UiMngcUkckn66ey0VEVJvi4mIMGjQIycnJ6Nu3L7Zv3w5zc3Od1G1lZaWzYAQwHBGRCWCvEWmLMfz78wsKIqpJeXk5Ro0ahUOHDqF79+7YtWsXrKxUmy3PEHBYHRHpDS/KyBgYw/A6feB9R0SGISIiAjExMQAAV1dXTJo0Se52K1asgKurKwAgIyMDQ4YMka27fPkyAGDSpEmyiSD69++POXPmyC1r4MCB6NWrFz744AOV271q1Sr88ccf+OWXX5Taj+GIiIz6fiP2GpEhM/aJGYhI/LKzs2X/Lw1J8oSHh8vCUXFxMU6cOFFlm0uXLsn+v6aHte7du1dWlqrOnDmDuLg4pfdjOCIivWCvERkTbfYe6SIgcWIGIqpOeHi40g+I9fb2hiAIatV7//59HD16VK39VcFwRERGi71GROLGoXVEVJ39+/dj//79Ku8vCIJKs+kxHBGZOGMeUqctDEYkD3uPiIg0Izg4WG91MxwRkc7pYkgdp0EmIiIyTBs3btRb3bx6ICJSAnuNqCbaPD90Efh5LyARmTqGIyLSKfYaERERkVjxCoKISEHsNSJFsPeIiMhwMRwRkc6w14hMBYO04jgpDBGJCa8iiEwYL0oUx4tdMiXsPSIiU8VwRGSidB2M2GtEpkZbgVpX57kuAxK/qCEiseCVBBFpnaF/C81eIzJVDEhEZGoYjohMkC4vQgw9GBGpw9B7j4iIxODWrVs6q4vvrkSkNboMRtq6WGSvEZk69h4Rkb41a9YM/fr1w86dO1FWVqbVuhiOiEyMri4+2GNEpF267D3i3zMR6ZOvry8OHDiAkSNHwsPDA7NmzcLVq1e1UhfDEREZPPYakZgZy3nEgERE+pKamorDhw9j1KhRyM3NxRdffAF/f3/07NkT//vf/1BSUqKxuhiOiEjjeBFFRKri0DoikicwMBBbt27FvXv3sGrVKjz33HM4cuQIRo8eDXd3d0ybNg2XLl1Sux6GIyIToouLDl0HI96YTobAWCZm4BcfRKRvLi4ueP/993H27FkkJSUhNDQUJSUlssDUvXt3bNmyBcXFxSqVz6sKIiI5jGUoFBERkbF68cUX8dFHH+HNN9+EIAgQBAHHjh1DSEgImjRpgoiICKXLZDgiIo3ht8pE1WPvERGRZhQVFWHLli3o0aMHWrVqhR9++AENGzbEJ598goMHD2LChAnIz89HWFgYFi5cqFTZDEdEZLA4EQORfmg7IPG+IyKSJyUlBe+//z7c3d0REhKCY8eO4eWXX8aOHTtw+/ZtLFq0CD179sR3332Hixcvon79+vj++++VqsNCS20nIpHR9sUGv00mql2BRwXs7vB7SSIiZfzwww9Yv349/vrrLwiCgHr16uHDDz/EO++8Az8/P7n7eHl5oXfv3vjxxx+VqovhiIjoGew1IkOU39gMDnd1e+7m+djC8WahTuskIt07deoUfv/9dyQnJyM5ORl3794FAAiCUO0+9+7dw5IlS/Dbb78hPT0d5ubmaNasGYYMGYKPPvoIjo6OSrVh4sSJAIAuXbrg3XffxYgRI2BtbV3rfm3atEF6erpSdTEcEZHa9NFrxFnqyFCx94iIDMnChQuxe/duhbe/evUqunbtiszMTHh7e+P1119HUVEREhMTsWDBAkRHRyMxMRHOzs4Klzl58mS88847eO6555Rq+0cffYSPPvpIqX347kxE9P+x14hIOdr8YoT3HRGJQ+fOnTFnzhz88ssvyMjIqLXHZubMmcjMzMSkSZNw7do17Ny5E3Fxcbh16xY6deqEixcvYuXKlUq14eOPP4a7u3ut22VnZ+P27dtKlf1fDEdEpBbea0SkPG0EcfamEpE2zJw5EwsWLMCAAQPQsGHDWrc/evQoAGDOnDkwNzeXLXd2dsaMGTMAACdPnlSqDT4+Pvj4449r3W7GjBlo2rSpUmX/l2jfSU+dOoVly5Zh6NCh8PDwgEQigUQiUbqcx48fY9u2bRg1ahR8fHxgZWUFR0dHvPTSS1i1ahVKS0vl7hcSEiKrU97PunXr1H2JRDpjbN/AauMikL1GRERE6lPkXqB69eopVab0GUaKbqsO0d5zpOz4xuqsWLECixcvhkQiQdu2bfHSSy8hMzMTx44dQ3JyMqKjo7F//37Y2dnJ3b9v375yU3KLFi3UbhsREZGh48QMRPSsPn36ICoqCgsXLsTq1atlvUc5OTn44osvAAChoaFaqTsrKwu2tuqNaBFtOOrcuTPatGmDjh07omPHjvD29kZxcbHS5djb22PGjBmYPHkymjRpIlt+9epV9OrVC3/++ScWLVqEJUuWyN1/1qxZCAoKUvVlEBk1YxlSx14j0gdOzFC7Mt/GsLh+V9/NICIlLF26FKdOncI333yDffv2oUOHDigqKsKxY8dgY2ODrVu34uWXX661HOnwPKn79+9XWSZVVlaG1NRU7N+/H61bt1ar/aINRzNnztRIObNnz5a73M/PD8uWLcNbb72F7du3VxuOiAyZsQ2nIyLTw4BEpHm5ubmVfre2tlZoOJwiGjZsiCNHjmDUqFE4cOAAbt26JVs3dOhQdOjQQaFygoKCKt1Ss3//fuzfv7/a7QVBgEQiwfTp01VuOyDicKQLAQEBAJ7OxU5kbBiMFMNeI9InY+k94tA6It1J/ccN5nY2Ku1bXlAEAPD09Ky0fN68eQgPD1e3aQCAlJQU9O/fH+bm5ti9ezd69OiBJ0+eIDo6GrNnz8aRI0eQmJhY6y0qY8eOlYWjTZs2wdfXF127dpW7rZWVFdzd3TFgwAC0b99erfabdDi6ceMGANQ488auXbuwc+dOlJeXw8fHBwMGDIC/v7+umkikEl0EI2MZUkdE4vfsexp7kYjUl56eDicnJ9nvmuo1Ki0txfDhw3Hv3j2cPHlSFlRcXFwQFhaG8vJyTJ8+HXPnzsVPP/1UY1lRUVGy/9+0aRO6deuGyMhIjbSzJiYdjlatWgUAGDRoULXbrFmzptLvM2fOxHvvvYdVq1bBwsKkDx+JDHuKlMdeIxIDY+k90hUOsyNSn5OTU6VwpClJSUm4evUqfH195fbgjBgxAtOnT6/23qHqVFTo7vPaZK/u161bh4MHD8LFxQWzZs2qsr5du3bo3LkzevbsCQ8PD9y/fx+//vorPvvsM3zzzTewsrLCV199VWMdxcXFlSaR+O/4TiJNYCgiMnwMSMr57/sewxKRONy5cwfA02caySNdnp2drbM2Kcskw1FCQgLCwsIgkUgQGRkp94m7YWFhlX738fHBpEmTEBgYiPbt2yMiIgLTpk2rMmbzWUuXLsX8+fM13n4yTQxBmsVeIyLN0ud9R/LeHxmYiHRPeqtKamoq8vLy4OjoWGm99OGv3t7eNZazYMECSCQSTJ48GXXr1sWCBQsUboNEIsGcOXOUa/iz+wvqPilJR2xsbFBcXKz2g53Onz+PHj16IDs7G6tXr8b777+vdBkjRoxAdHQ0Nm7ciJCQkGq3k9dz5OnpiV6uobAws1Kl+WSixBaM9H2/kSYeAstwRGKkbu+Rw139ntdim5SBAYlUUVZRgoNZkcjJydHK0DNV5ebmwtnZGU03faLWhAw3gpeo9dpquiYvKiqCl5cXHjx4gLFjx+L777+X3c9079499OvXD+fOncOnn36KRYsWVVuHmZkZJBIJLl26hObNm8t+VyQHSCQSlJeXq/TaABPrObp58yb69OmD7OxshIeHqxSMgKfTgANARkZGjdtpclpEMl1iC0bGgMGIyDTw/iQi9cXFxWHhwoWy30tKSgAAnTp1ki2bM2cO+vfvDxsbG3z33XcYMWIENm/ejD/++AMvvPACCgsLcfz4ceTl5aF9+/Zyb2l51saNGwEAjRo1qvS7LphMOMrIyEDv3r2RkZGBsLAwzJs3T+WypOMk7e3tNdU8IiIig7/3iFN6ExmfzMxMnDhxosryZ5dlZmbK/n/w4MFITk7GihUrcPToUezbtw9WVlbw8/PDyJEjMXXqVNja1jwCJTg4uMbftckkwlF2djb69u2L69evY9y4cbVOpFCT4uJixMXFAYDa86gT1UaMvUb6HlKnLvYaEZkW9h4RqSckJKTG20jkadeuHX788UftNEjLDPfrqf+IiIiAv78/Zs+eXWl5QUEB+vfvj3PnzmHkyJFYv359paftynP58mVs2bKl0v1CwNNU/OabbyI9PR0BAQHVPoiKiIhIVQzwRESKKSsrw7p16zBlyhR8/vnnGpkFT7Q9R8qMbwSArKwspKamVrkP6NNPP8Xx48dhbm4OCwsLjB8/Xm59zz5o6v79+xg7dizCwsLwwgsvwM3NDffu3cOpU6eQl5cHDw8P7Nixo9aQRWRs2GtERLUR49A69h4RGbYFCxZg/vz5OHz4MHr06AHg6bOPgoKCcPz4cQiCAIlEgvXr1+Ovv/6Ci4uLynWJNhwpO76xOtIEWV5ejm3btlW73bPhqHnz5pg6dSqSkpJw7tw5PHz4ENbW1mjevDkGDBiAsLAw1KlTR4lXQ6Q8MQ6pIyLdMPR7j4iINOn333+Hh4eHLBgBQHR0NBITE9GmTRtMnjwZv/76K2JjY7F27Vp8+umnKtdlMFN5GwPpFIycypsUIbZwJKZeI1Wm8mavERkaVcKRvqfyfpbYeo8ATu1NiuFU3uLTuHFjPP/88/jtt99ky9588038/PPPOH/+PFq2bAlBEODt7Y26devi77//Vrkufi1FJEJiC0ZEpHuGHujF9IUKERm2hw8fwtXVtdKy+Ph4+Pn5oWXLlgCePt+oY8eOuH37tlp1MRwRUa3EcpGT39iMvUZENVD1b4SISMxcXV1x9+6/Pb8XL17EP//8g6CgoErbWVlZyeYpUJVo7zkiMlWm2mvECzrtsHAvAACU3bPTc0tUY+FeYLBt1ydF/p7ENARPVzgxA5FhatmyJeLj4/H333+jXbt2WLlyJSQSCV577bVK2926dUv24FhV8WqEiMhISYPRf//fEFi4F8ja/Oz/ExGR6fnwww9RVlaGjh07wtXVFRs3boSPjw/69esn2yYnJwenTp1CQECAWnUxHBGRKJjit9jaJC9MMGCQFP/eiMiQvPbaa1izZg0aN26MwsJCdO3aFTExMbCy+neCs82bN6O0tBSvvPKKWnVxWB0RGT27O2Ymdd9RTSHIEIapVdd+Q2g7ERFpx+TJkzF58uRq10+YMAFjx46Fg4ODWvWw54iIRIPfZuuGmHuQamubmNtORET6Y2trC2dnZ5ibm6tVDsMREZERUTQ8iDFkiLFN+qSth8DySwgiouoxHBERkd4pE4wYooiITM/FixcREhKCpk2bwtbWFubm5nJ/LCzUu2uI9xwRkag43K3gtN4qUjY0iOUeHoYdIiKqyfHjx9GrVy8UFhYCAOrWrYuGDRtqpS6GIyKRsbh+12SfdUS6p++AxGCkWxxSR0SGaPbs2SgsLMTUqVPx2WefoW7dulqri+GIiMjE6SsgMRiRrvEBsESG6a+//kLbtm2xcuVKrdfFsStEJDr8dlv3GFSIiEisrKys4O/vr5O6GI6IiAiAbgOSunUxzBERmY5u3brh4sWLOqmL4YiITIK2pkUWC0MKC4bUVmPCHlkiMlRLlizBtWvXsHbtWq3XxXuOiESIkzKQvmj7/iMGIyIiUtbp06cxbtw4fPDBB9ixYwd69+4NDw8PmJnJ/+Jz7NixKtfFcEREosQpvfVHWwGJwYj0iZMxEBmukJAQSCQSCIKAhIQEJCQkQCKRVNlOEARIJBKGIyIi0ixNByQGI+Voehgoh9QRkapOnTqF33//HcnJyUhOTsbdu0+/aBAEQe724eHhmD9/frXlzZw5E8uWLVOqDXPnzpUbhrSB4YiIiOTSVEBiMCIiMlwLFy7E7t27ld6va9euaNasWZXlHTp0ULqs8PBwpfdRldrhKCcnB5mZmXj8+DFcXFzg5uYGZ2dnTbSNiIj0TN8Pia2JmNtGRGQsOnfujDZt2qBjx47o2LEjvL29UVxcXOt+EyZMQEhIiPYbqGFKh6OysjLExMQgLi4O8fHxuH37dpVtmjRpgsDAQLz++usYPHgwLCzYQUWkLE7KwPuOxEKsPT8MRkRE2jdz5kx9N6GSs2fPIjk5GVlZWWjdujUGDhwIACguLkZxcTGcnJzUKl/h1PL48WN8/vnniIyMRFZWFgRBgJmZGdzd3VG3bl04OTkhJycH2dnZuH37NjZv3owtW7bA1dUV48ePx4wZM+Di4qJWY4mIiKTYc6QY3m/EyRiIjEFqairGjRuHEydOyJYFBwfLwtG2bdswYcIExMXFoV+/firXo9BXsitWrICvry8+//xzODs747PPPsMff/yB7OxspKen4+zZs0hISEBKSgrS09Px+PFjHDx4EJ988gmcnJywbNky+Pr64ssvv1S5oURE6jL2Zx0RERGJxaFDhzB16lS8++67WLRoEU6dOqVyWenp6ejRoweSkpIwYMAAfPHFF1UmhBg5ciSsrKywc+dOtdqtUM/RjBkzMHDgQMyePRsvvfRSrds7OjqiZ8+e6NmzJxYuXIjjx49j2bJlmDFjBqZPn65Wg4lMCYfWERERkabl5uZW+t3a2hrW1tYarWPLli2Vfp8zZw6GDRuGqKgoODg4KFXWggULkJWVhR9++AGhoaEAgI8//rjSNvb29mjbtm2lniVVKBSOTp8+jbZt26pcSefOnbF7926cOXNG5TKIyDTxvqPaifWeIFINezg1i0PqyNiU37eDYGOj0r4VRU/fXzw9PSstnzdvnsZmhGvWrBlWrFiBV199FV5eXsjOzsbRo0cxY8YM7Ny5E+Xl5YiJiVGqzN9++w1t2rSRBaPqeHt748CBA+o0X7FwpE4w0kY5RERERESkmvT09EoTF2iy12jMmDGVfre3t8dbb72Fl19+Gc8//zxiY2ORlJSETp06KVzmgwcP0LVr11q3Ky0tRUGBel8Y8uspIpHjt56axW/ljQt7zWrGyRiISB4nJ6dKP5oeUidPo0aNMG7cOABPe4KUUa9ePbkzZP/XlStX0KhRI5XaJ6X2HNvl5eXIysqqcb7zJk2aqFsNERERkVL45RKRuPj5+QEAMjIylNqva9euiI2NxZkzZ6odiRYfH4/z58+r/Wwllb9C/f333/Hyyy/D3t4e7u7u8PHxkfvTtGlTtRpIRPyAp+qx58S4sGeTiIxZdnY2gKdD7ZTx0UcfQRAEDBo0CL/++ivKy8srrT906BD+7//+DxYWFpg6dapabVSp52jnzp144403UFFRAVdXV3h5eSk96wQRKYcz1xERKYZfKBGJjyAIsokY2rdvr9S+L730ElavXo2wsDC8/vrrsLOzg0Qiwc6dOxETE4Pc3FxIJBJ88803aNOmjVrtVCkcSWez+OGHHxASEgIzM37TRaQLphqQND1jnd0dMxR48F4MY8GHwRIRiUNmZiZ27NiBsWPHwtHRUbY8Pz8fH330EU6cOIGGDRti6NChSpc9adIktG/fHsuWLcOhQ4cgCALy8vJgY2ODvn374tNPP1Vo0obaqBSOrl27hsDAwFqn0yMiIiLFcEidZrDXiEiz4uLisHDhQtnvJSUlAFBptrk5c+agf//+ePLkCaZMmYJZs2ahY8eOaNSoETIzM3H69Gk8fPgQLi4uiI6Ohp2dal9oderUCbGxsRAEAVlZWbJRbObm5uq9yGeoFI4aNmwIV1dXjTWCiEjXjKH3iPcbUU04Ux0RaUJmZqbcB6s+uywzMxPA01nlZs6ciaSkJFy5cgWJiYkwNzeHj48PQkJC8OGHH6JxY+VHwBw9ehQNGzZE8+bNAQASiQRubm5Vtrt69SoyMjLQo0cPpeuQUikcjRgxAlu2bEFRURFsVHwIFRGpxlSH1hEZM/YaEZFYhYSEKDwDnKOjI5YtW6bxNgQFBWHcuHHYsGFDjdt98cUXiIyMrDJhgzJUejcODw+Hp6cnBgwYgOvXr6tcORGRPvGClMi4cEgdkfESBEEj29RGpZ4jOzs7HDx4EF26dIG/vz+8vb3RuHFjuRMzSCQS/PHHH2o3lIiIyBgxpBMRaca9e/fUnkFbpXB09+5d9OrVC1euXIEgCLh+/Xq1PUgSiUSlhp06dQq///47kpOTkZycjLt3n34bpGoizM7ORnh4OGJjY3H//n00bNgQQ4YMQXh4OFxcXOTuU15ejtWrVyMyMhLXrl2Dg4MDXn75ZcyfPx8tW7ZUqR1EJC7GcO8RERGRsdm8eXOl369du1ZlmVRZWRlSU1Nx8ODBShNFqEKlcDRt2jSkpqaiV69eeP/999G0aVONP+do4cKF2L17t0bKysrKQufOnXHt2jU0bdoUgwcPxoULF7Bq1Sr8+uuvOH78OOrWrVtpn4qKCowYMQIxMTFwcXFB//79kZWVhejoaMTFxeHw4cN48cUXNdI+ImWZ4n1Hmp7Om0gM2GtERCRfSEiIrJNFIpHg2LFjOHbsWLXbC4IAGxsbzJ07V616VQpHBw8ehJ+fH3799VeNTp33rM6dO6NNmzbo2LEjOnbsCG9vbxQXF6tU1tSpU3Ht2jUMHToUP/30Eywsnr7sDz74AGvWrMG0adMQFRVVaZ/IyEjExMTAz88PCQkJaNCgAYCnD8AdPnw4Ro8ejUuXLsnKIiLDxd4jw2eIzzrSZjAyxZnqeL8RkXGZO3cuJBIJBEHAggUL0LZtWwwaNEjutlZWVnB3d0efPn3QqFEjteqVCCqMU6tTpw769euH7du3q1W5MmxsbFBcXKz0sLqMjAx4eHjAwsICt2/floUcACguLoanpycePXqEe/fuoX79+rJ1rVq1wqVLlxATE4PBgwdXKnPQoEH45ZdfEB0djWHDhincltzcXDg7O6OXaygszKyUeh1E/6XLnqM8H1ud1VUTbfccGVpA4lTelRlSONJ2j5FYwpHjzUKd1cVwRJpSVlGCg1mRyMnJgZOTk76bIyO9jvT6fBHMVJwtuqKoCGkzPxPda6uNt7c3Ro4ciS+++ELrdan07typUyeDmaXut99+Q0VFBbp3714pGAGAtbU1BgwYgPLycuzbt0+2/ObNm7h06RJsbW3Rv3//KmUOHz4cALBnzx7tNp6IdIpDnEgXeJ4RESnn1q1bOglGgIrhaPHixTh37hzWr1+v6fZo3NmzZwEA7du3l7teujwlJaXKPs899xwsLS0V2odI1/gtqXYYyoUre40Mk6GcX0REpkqlG2bOnz+PcePG4d1338WPP/6I3r17VzuVNwCMHTtWrUaq4/bt2wAADw8Pueuly9PS0tTah4i0T1eTMvAeJNIGBiPt4ZdFRMbvwYMH+Oabb3D06FFkZGRUOxeBRCJRa4SbSuFIOnuEIAg4evQoEhIS5G4nCAIkEolew1F+fj6Ap89mksfe3h4AkJeXp9Y+8hQXF1f6h8vNzVWw1USkbwxIpEm6DEZiud+IiEhTLl26hMDAQDx8+FAjD3qtiUrhSDp7BNVs6dKlmD9/vr6bQUQqYkAiIiLSv48//hhZWVkYNmwYZs+ejebNm2v8MUJSKoWj8PBwDTdDe6QHrqBA/vj8J0+eAAAcHR3V2kee2bNnY9q0abLfc3Nz4enpqWDLiWpnis870jUGJFIHh9IREakvISEBLVq0wI4dO7TeQWP0D+lp0qQJAODOnTty10uXe3l5qbWPPNbW1rC2tlauwURUI308DFZ6gSumkFR2z46TMogYQxERkeYIgoC2bdvqZOSa0b97BwQEAABOnz4td710eZs2barsc/78eZSWliq0DxEZP7s7ZrzoFSkxPeNIn+eIKd5vxMkYiIzfCy+8oLOJ0BR6B3/jjTdw6dIltSq6cOECRo4cqVYZqujXrx/MzMyQkJCABw8eVFpXXFyMPXv2wNzcHK+99ppsuY+PD1q2bInCwkLExcVVKTM6OhoAMGDAAO02nkgkdPkgR0PAkETy8LyojO8bRKQp4eHhOHnypE6eMarQu/jBgwfx/PPPY+jQoYiNjUVJSYlChZeUlGDnzp0YNGgQAgICcPjwYbUaW5OIiAj4+/tj9uzZlZY3atQIo0aNQklJCSZNmoSysjLZuhkzZiAzMxNjxoxB/fr1K+0nvVdoxowZlULVrl278Msvv6BZs2YYNGiQ1l4Pkdg43iyU/eibWL4d1/fFsJh6S0yV9BxgKPqXWN4niMi4hIWFYejQoQgODsbWrVtx5MgRHD16VO6POhS65+jGjRtYtGgRIiIisHv3bjg6OqJTp07o2LEjWrRogTp16sDR0RF5eXl49OgRUlNTcfLkSZw4cQJ5eXmwtrbG9OnT8cknnyjcsLi4OCxcuFD2uzSQderUSbZszpw56N+/PwAgKysLqampyMjIqFLW119/jaSkJOzcuRP+/v544YUXcOHCBZw/fx5+fn5YuXJllX1CQ0Oxb98+xMTEwN/fH6+88gqysrIQHx8PW1tbbN26FRYWRn/LFpFcjjcLkedjq+9miIYY70kyJfoIiWIMQ/r+0oCBiIi0JSgoSPYYoS1btmDr1q01bl9eXq5yXQpd3Ts7O2P58uWYPn06NmzYgA0bNuDAgQM4cOCA3BujpPOP+/j4YObMmQgNDUWDBg2UalhmZiZOnDhRZfmzyzIzMxUqy9XVFcnJyQgPD0dsbCxiYmLQoEEDfPDBB5g/fz5cXFyq7GNmZoaff/4Zq1atQmRkJPbu3Qt7e3sMGzYM8+fPR6tWrZR6PUTaoq8Z66QXQgxJ/2JIMn5iDEViwGBERNo0duxYnT1GSCKo+CSlixcvIiEhASkpKXjw4AFycnLg7OyM+vXrIyAgAN27d0fLli013V6DlpubC2dnZ/RyDYWFmZW+m0NGRN/TeesrIOl61jpV6CIomfKsdbrqNTKEUKSPniN9hyJOxkDaUFZRgoNZkcjJyYGTk5O+myMjvY70+nwRzGxsVCqjoqgIaTM/E91rExOVx4W1atWKvSdEBIDD7GrC5yQZNkMIRYBpBiMiIm0wjHd9IhI9XihVT9sX2KY6MYO2X7ehBCN94N87ERkrzihARBqj6x4kfTwQVlXsQSJt0XWvEYMRkWk5deoUfv/9dyQnJyM5ORl37z4dzirvzpyKigocO3YMe/bswR9//IErV66gpKQEHh4e6N27N2bOnAkfH59a61ywYIHK7ZVIJJgzZ47K+zMcEZFGcYidfpTdszOpe4/Ya6QfDEZEpmfhwoXYvXu3QtveuHEDPXr0AAA0bNgQPXv2hLm5OZKTk/Hdd99h27Zt2LdvH7p161ZjOeHh4bLZ6RQl3Z7hiIj0NmNddXQZkNh7RJpmSMFI39N3E5Hx69y5M9q0aYOOHTuiY8eO8Pb2RnFxsdxtJRIJevfujVmzZuHll1+WzTBXXFyMd999F1FRURg9ejSuXbsGS0vLauucN2+eVl6LIlSerY6Ux9nqSJvEFI6kdNmDZCgBCdDuDHam0HukzV4jQwpGgG7Dkdh6jThTHWkLZ6urmY2NDYqLi5Xq1QGAwsJCNGrUCDk5OThy5AgCAwNVql/bDOtTgIjICBjaBTiJkykHIyIyPLa2tmjevDkA4N69e3puTfX4CU1EWqPLCyoOL3rKVGeu0wRDCq0MRkRkaCoqKpCWlgbg6f1IYsV7johIq3j/kXyGdP+RuoFLk0P9tBX+DCkY6RKDEZFxys3NrfS7tbU1rK2ttVrn9u3b8eDBA7i5uaFLly5arUsdKn0amJmZwcrKCitXrqxxu3HjxsHCgvmLSBc4/t7wGMIFuSbCiNh7swzh3+FZ7CUlMm22d81gd0e1H9u7T9/vPD094ezsLPtZunSpVtucnp6OqVOnAng6Tbe2g5g6VE4uZWVl+Pjjj3Hu3Dl8//331c44wfkeiEiXpBeOptyDpIlpvTUdaMQ61TiDERGZovT09EoTMmgzrDx58gRDhw5FVlYWBg8ejHfffVdrdWmCyp8K/fr1Q8eOHbFp0yYEBQXhwYMHmmwXERkRDs2pmZgu0Mvu2Wmtp0fdssXeA6VtDEb/Yk85kXqcnJwq/WgrHJWWlmLEiBH466+/0K1bN2zbtk0r9WiSyp/IDRs2RHx8PEaPHo3jx4/jxRdfxJkzZzTYNCIi1TncrTDpi0llg4Q2Q1F1dSlTnzbaJqZQWht9nMv8UoOI1FFRUYHg4GD8+uuvaNu2Lfbs2QNbW/E/JF6tTwZra2ts2bIFS5cuxZ07d9CtWzdER0drqm1ERGozlICkjQv16gLFs+FEl6GotrbUtI2mGUowMvWQT0SG6/3338f27dvRvHlz7N+/Hy4uLiqXtXnzZiQmJta6XVJSEjZv3qxyPYCGpvKeOXMmYmNjYWZmhjfeeAPh4eGaKJaIjIg+v4U2lAtMbQUksQSh2shrq6kHIyIiQ/TZZ5/hm2++QZMmTfD777+jfv36apUXEhKCH374odbtNmzYgHHjxqlVl8Y+IV5//XUkJSXB29sbCxcuxLBhw5Cfn6+p4omI1GYIF5uGcuFuqAzh+IohzHNIHRGp6quvvsLixYvRsGFDHDx4EE2aNNFZ3RUVFZBIJGqVodF5tlu1aoWTJ09i+PDhiImJUbtxRESaZgiz2RnSM5BIc/QdiIiI5ImLi8PChQtlv5eUlAAAOnXqJFs2Z84c9O/fH2fOnMH06dMBAD4+Pli8eLHcMidMmIBu3bppvK03btyoNAufKlQKR02aNIGrq6vcdXXr1sXvv/+O999/H+vWrWNAIiIZXT4QtjaGEJJIs8TcaySmYMReIyJ6VmZmJk6cOFFl+bPLMjMzAQCPHz+WPcbn+PHjOH78uNwyg4KCag1HCxYsqPT7mTNnqiyTKisrQ2pqKo4ePYrevXvXWG5tJIIWH0R0584dlJeXw8vLS1tVGJTc3Fw4Ozujl2soLMys9N0cMkJlvo313QSFiCUgSYk1ILH3SHPEGozEFIoAwwlGnMqbtKmsogQHsyKRk5Ojdi+EJkmvI/0/WAJzaxuVyigvLsLl1Z+I7rXJY2ZmBolEAkEQZP+tTf369bFv3z60b99e5Xo1Oqzuvzw8PLRZPBH9h8X1uwYRkMTUgwSItxeJw+s0Q4zBSGyhiIhIbDZu3AgAEAQBoaGh6NatG8aPHy93WysrK7i7u6NTp05qP7NJq+GIiMiQiDEkMSCpR2zBSMyhyFB6jYjINAQHB8v+f9OmTXj11VcrLdMWhiMi0gux9R49S2whiQHJ8Ik5FAEMRkQkbocPH9ZZXQxHRKQ30gsyhiTSBjH0GjEUaR7vNyIibWI4IiK9E3MvEiD/AlfXgYm9R8rRRzASexD6L0MMRkRkui5evIgvvvgCR48eRUZGhmxK8f+SSCQoKytTuR6GIyISBbH3Iv2XPgITA5JidBGMDC0IPYuhiIgMzfHjx9GrVy8UFj59/6pbty4aNmyolboYjohIVAwtJD2rugtmTYYmBqSaaSMYGXIQehZDEREZqtmzZ6OwsBBTp07FZ599hrp162qtLoYjIhKlZy/kDDEoPcvhbgUDkg4wGFXFQERExuCvv/5C27ZtsXLlSq3XxXBERKJnyL1J2sKApH2GHIwYiojImFhZWcHf318ndel/Kh8i0ihjnsnJ8WahwV70aeNCWwyzsYmFpo+FoQYjQ/4bISKqTrdu3XDx4kWd1MVPViIjZMwBCTDcC0BDveAWOwajpwzxb0IZFtfvGv17GxHJt2TJEly7dg1r167Vel0cVkdkpJ69iCjzbazHlmiP2KcAl4f3H2kWg9FTxhqMGIaICABOnz6NcePG4YMPPsCOHTvQu3dveHh4wMxM/mfA2LFjVa6L4YjIBBhzUGJAMt2AxGDEUEREpiEkJAQSiQSCICAhIQEJCQmQSCRVthMEARKJhOGIiBQnvegwtpBkaKQX4uqGJFMMRVLS166JkMRgpH8MRERUnblz58oNQ9rAcERERCbNEIMR8HT2RmMKSGW+jRmQiEiu8PBwndXFCRmITEyZb2P2GomIuhfmnLFOPYYajIwV35uISN/Yc0RkQnjhQcbG1MOhsfUeAexBIqKanT17FsnJycjKykLr1q0xcOBAAEBxcTGKi4vh5OSkVvmi/lQpLCzE3Llz0bx5c9jY2MDd3R2hoaG4e1fxN82oqChIJJJafzZv3lxpP+mNX9X9rFu3TtMvl0irjDUYGdpkDERUO/ZwE9F/paamokuXLmjfvj3effddfPbZZ4iNjZWt37ZtG+rUqYPffvtNrXpE23NUVFSEnj17IikpCY0aNcKgQYNw69YtbNy4EXv37kVSUhKaNm1aaznNmjVDcHCw3HU5OTmyg9qtWze52/Tt2xcNGzassrxFixaKvxgiFfDCwHSoO3udqc5WR8ZP0++D7JEiMkzp6eno0aMHMjMzMXDgQHTv3h0ff/xxpW1GjhyJSZMmYefOnejXr5/KdYk2HC1atAhJSUno3LkzDhw4AAcHBwDAypUrMX36dISGhuLIkSO1ltOtW7dqg8+3336L2NhYdO3atdqgNWvWLAQFBan6MogUxjBEpBx1h9TxfiPT89/3WYYlIsOwYMECZGVl4YcffkBoaCgAVAlH9vb2aNu2LU6cOKFWXaIcVldSUoKIiAgAwNq1a2XBCACmTZuGNm3aID4+HqdOnVKrnq1btwIA/u///k+tcohUIR02wuEjRKQODi1VHd+DiRRz6dIljB49Go0aNYK1tTW8vb0xZcoUZGVl6aT+3377DW3atJEFo+p4e3srdfuNPKIMR8eOHUNOTg58fX3Rrl27KuuHDx8OANizZ4/Kddy8eROJiYmwsrLCyJEjVS6HSFEMQ5pnTBeFnLWOSL/4Hk0k36FDh/DCCy9g27ZtcHFxweuvvw5ra2usXbsW7dq1w507d7TehgcPHih0S0tpaSkKCgrUqkuUw+rOnj0LAGjfvr3c9dLlKSkpKtch7TXq378/6tSpU+12u3btws6dO1FeXg4fHx8MGDAA/v7+KtdL4sMPQSLDwyF1pG26/Gzg8D4Sq4KCArz11lsoKCjA3LlzMX/+fACAIAiYMWMGVqxYgfHjx2P//v1abUe9evVw+/btWre7cuUKGjVqpFZdogxH0hfv4eEhd710eVpamsp1KDqkbs2aNZV+nzlzJt577z2sWrUKFhY1Hz7plIJSubm5AIAyn0aAhY0qzSYiI6buxAykGGMMRsY4pbcp4Zd04lJWVgToZrSY6O3atQv//PMPWrRogXnz5smWSyQSLFmyBNHR0Thw4ADOnj2LgIAArbWja9euiI2NxZkzZ9C2bVu528THx+P8+fMICQlRqy5Rfgrn5+cDAOzs7OSut7e3BwDk5eWpVH5ycjKuXLmCunXron///nK3adeuHdatW4crV66goKAAN27cwNq1a+Hi4oJvvvmmyk1g8ixduhTOzs6yH09PT5XaS0RVGdOQOiIiIjGS3t/fo0cPmJlVjg2Wlpbo2rUrAGD37t1abcdHH30EQRAwaNAg/PrrrygvL6+0/tChQ/i///s/WFhYYOrUqWrVJcpwpG3SXqORI0fCyspK7jZhYWF455134OfnB1tbW/j4+GDSpElISEiAlZUVIiIikJ6eXmM9s2fPRk5Ojuyntu2JiNTp1eB9R7Uzxl4jIiJtefLkCQBUewtKvXr1APx7S4y2vPTSS1i9ejXu3buH119/HS4uLpBIJNi5cyfq1KmD3r174969e4iIiECbNm3UqkuUn6TS2emqu6FK+g/l6OiodNllZWX46aefAKg2S530SbxlZWX4448/atzW2toaTk5OlX6IiGrDC/iaMQQSEemGm5sbgOpvZbl582aN6zVJ2kkxYMAASCQSCIKAvLw8FBcXo2/fvoiPj8fEiRPVrkeU9xw1adIEAKqd/UK63MvLS+myDxw4gAcPHqBp06bo0qWLSu3z8/MDAGRkZKi0PxER6Z6xh07ed0REipLeBy9lbW0Na2vrKtv16NEDS5YsQVxcHLKysuDq6ipbd/fuXfz+++8AVL/VRVmdOnVCbGwsBEFAVlYWKioq4OrqCnNzc43VIcqv36Q3dJ0+fVrueulyVbrNpEPqxowZo2LrgOzsbAD/3vtERLplCvcbqXohz14V+Yw9GBGR6bDPqIDDXdV+7DOevhd6enpWui9+6dKlcuvq06cP2rdvj/z8fLz66qtITk5Gfn4+jh8/jldffRVlZWUAUOV+JG2TSCRwc3NDgwYNNBqMAJGGo65du8LZ2RnXr1/HmTNnqqyPjo4GAAwYMECpcvPz82U3jKkajoqLixEXFweg+qnGiYg0gRf0VakS/ngciYgqS09Pr3Rf/OzZs+VuJ5FIsGvXLrRu3Rp//fUXXnrpJTg6OqJLly548OABwsPDAVR/T5IhEuWwOisrK0yZMgWLFy/G5MmTceDAAVkvzcqVK5GSkoLAwEB06NBBtk9ERAQiIiIwZMiQatPvrl27UFBQgE6dOsmGxslz+fJlnDx5EiNHjqzUxZiZmYmJEyciPT0dAQEBshk6iIi0hdN7ExGRpilzL7yXlxfOnDmDmJgYJCYmorCwEK1bt8bo0aOxa9cuAE/vydeknj17qryvRCKpdV6AmogyHAHAZ599hoMHDyIxMRF+fn7o3r070tLScOLECbi5uSEyMrLS9llZWUhNTa3xPiBFn210//59jB07FmFhYXjhhRfg5uaGe/fu4dSpU8jLy4OHhwd27NgBiUSi/gslIiKtMbVeI953RETaYGFhgREjRmDEiBGVlicmJgIAgoKCNFrfkSNHVN5X3etz0YYjGxsbHD58GEuXLsW2bdsQGxuLunXrIiQkBAsXLqz2AbHVycjIwKFDh2BpaYk33nijxm2bN2+OqVOnIikpCefOncPDhw9hbW2N5s2bY8CAAQgLCzOq7kMiQ2IK9xupy+6OGQo8TCsUEBGRbt2/fx/R0dGoV68ehg4dqtGypbPg6YNEEARBb7WbmNzcXDg7OyOo46ewsLDRd3OIDJKphiNlh9YZYzji/UaKYc8RkXrKyopw5ORi5OTkiOoxLNLryA4jFsHCUrXryLLSIpz6+TOlXtv58+fRrFkz2Nj8W+edO3cwbNgwJCcnIyoqCsHBwSq1R4xE23NERESkDlMMRkREmrZixQrExMSgffv2aNSoER48eIA///wTxcXFmDNnjlEFI4DhiIjIKHFonenifUdEpEmDBw/G/fv3cfbsWRw7dgx16tRBv379MHXqVI3fayQGDEdEZDBMdUgdwFnriIhIPwYPHozBgwfrtQ3KPMtIIpHInr+kCoYjIiISPWXvN+KQOiIi4+Hp6Sl3FrqKigrcv38fpaWlAJ5OO64uhiMiIiIjw6F1RGRMbt26Ve26iooKHDp0CGFhYXj++eexfft2teriGA0iIgOhbG+IKrO7ERERGRIzMzP06tULe/fuRVxcHD7//HP1ytNQu4iItMqU7zci5XBIHRGR6fHx8UGnTp0QGRmpVjkMR0REJGrsASMiIkXY2dkhPT1drTL4iUNEZEDYK0KKYm8rEZmStLQ0HD16FA0aNFCrHE7IQESix4s81Ul7XQzxmUfsMSIiIgDYvHlztevy8/Nx5coVbN26Fbm5uZg0aZJadTEcERGZgGeDhpiDkrqBiD1rlXHWOiIyBiEhIXKn8pYSBAEAMHbsWMyfP1+tuhiOiEjU2Gukef8NIPoOS+whIiKimsydO7facGRlZYVGjRqhR48eaNq0qdp1MRwRkWgxGOmGrnuVGIZ0i71HRGTowsPDdVYXwxERiRKDkX5oKygxEOkXAxIRkWIYjohIdBiMxIGBxrgwIBGRMUhMTERCQgLu3bsHAHB3d0e3bt3QtWtXjZTPcEREosJgRKQ9DEhEZKjOnTuHkJAQnDlzBsC/kzBI70UKCAhAVFQU2rRpo1Y9DEdEJBoMRkTax4BERIYmNTUVgYGBePz4MTw8PDB8+HB4e3sDePp8o507d+LMmTMICgpCYmIi/P39Va6L4YiIRIHBiEh3GJCIyJB88sknePz4MWbNmoUFCxbAwqJyhPniiy8wd+5cLF26FJ9++il27typcl0cUE5EesdgRKR7/LsjIkNx+PBhtG7dGkuWLKkSjADA3NwcixcvRuvWrXH48GG16mI4IiK94gUakf7w74+IDEFpaalC9xK1adMGpaWlatXFcEREesMLM9U43NXvQ1vJuPDvkIjELiAgANevX691u+vXryMgIECtuhiOiEgveEFGJB78eyQiMfv0009x8uRJREZGVrvNxo0bcfLkSXzyySdq1cUJGYhI53ghRiQ+nKSBiMTi6NGjlX63t7fHe++9h7fffhtRUVF444034OXlBeDpbHU7duzAn3/+iffeew8ODg5q1c1wREQ6xWBEJF4MSEQkBkFBQbLnFz1LEAT8+eefOHbsWJXlAPDtt9/i22+/RXl5ucp1MxwRkc4wGBGJHwMSEVUnMzMTn3/+Ofbs2YPbt2/D1tYW3t7eeOWVV7B8+XKN1TN27Fi54UgXGI6ISCcYjDQnvzFvFyXtkv69MiQRkdSpU6fQt29fPHz4EK1bt8agQYOQm5uLixcv4quvvtJoOIqKitJYWcpiOCKiGjHUEJkuTfz9M2ARGb7MzEz069cPhYWF2L17NwYOHFhpfXJyslbrX716Nezs7DBhwgSt1gNwtjoiqgGDkThxKm8yJHwfITJ88+bNQ1ZWFpYvX14lGAHAiy++qNX6p0+fjj179mi1DimGIyKSixc04sVhdWRo8nxs+Z5CZKAKCwuxdetW2NvbY9y4cXppQ8OGDWFjY6OTujisjogq4QUMEWkLJ3sgMjx//fUX8vLy0K1bN9ja2uLXX3/F77//jqKiIjRv3hwjR46Eu7u7VtvQt29f/PrrrygpKYGVlZVW62I4IiIADEVEpBuc7IFI/3Jzcyv9bm1tDWtra7nbXrx4EQBQv359DB48GLt37660/pNPPsGGDRswatQo7TQWwOLFi3HgwAGMHj0aq1evRqNGjbRWF8MRETEYEZHOMSQRqcbxViEsLASV9i0rKwIAeHp6Vlo+b948hIeHy90nOzsbAPDLL7/A3Nwca9euxYgRI1BQUICIiAisWLECwcHBaNmyJdq2batSu2oze/ZsBAQEYNeuXYiLi0P79u3RpEkTuUPtJBIJNmzYoHJdDEdEJoqBiIjEgCGJSPfS09Ph5OQk+726XiMAqKh4OglQWVkZFi9ejEmTJsnWLV++HGlpafj555+xfPly/Pjjj1pp77NTexcVFSExMRGJiYlyt2U4IiKlMRgRkdgwJBHpjpOTU6VwVBMHBwfZ/8ubkGHcuHH4+eefER8fr7H2/dfhw4e1VvZ/MRwRmQgGIiIyBAxJROLi5eUFALCzs4Obm1uV9d7e3gCABw8eaK0NgYGBWiv7vxiO9CDP2xYWlrqZjpCIiMgQ8Qsd0peyUglwUt+tEI927doBeDqld3FxcZUheI8ePQJQuYfJkIn6YRmFhYWYO3cumjdvDhsbG7i7uyM0NBR3795Vqhxvb29IJJJqfy5fvix3v/Lycnz11Vd4/vnnYWtrCzc3N4wcORKXLl3SxMsjIiIiIhK1Jk2aICAgAIIgyB06J10mDVGGTrQ9R0VFRejZsyeSkpLQqFEjDBo0CLdu3cLGjRuxd+9eJCUloWnTpkqVGRwcLHe5s7NzlWUVFRUYMWIEYmJi4OLigv79+yMrKwvR0dGIi4vD4cOHtf40YCIiIiIifZsxYwZGjx6Njz76CPv375dNpX3mzBl8+eWXAIB3331Xa/Wbm5srvK1EIkFZWZnKdYk2HC1atAhJSUno3LkzDhw4IOuqW7lyJaZPn47Q0FAcOXJEqTKfnemiNpGRkYiJiYGfnx8SEhLQoEEDAMDOnTsxfPhwjB49GpcuXYKFhWgPIRERERGR2t566y0cOHAAmzZtQqtWrdClSxcUFhYiMTERxcXFePvttzFixAit1e/p6QmJRFJleUVFBe7fv4/S0lIA/94fpQ5RDqsrKSlBREQEAGDt2rWVxjBOmzYNbdq0QXx8PE6dOqW1NqxcuRIA8MUXX8iCEQAMGzYMAwcOxLVr16o8BIuIiIiIyBht3LgR33//PXx9fXHkyBEkJyejffv2iIqKwvfff6/Vum/duoWbN29W+UlLS0NhYSEOHDiAli1b4qWXXsKNGzfUqkuU4ejYsWPIycmBr6+v3PGLw4cPBwDs2bNHK/XfvHkTly5dgq2tLfr376/z+omIiIiIxEQikeDtt9/GX3/9hSdPniA/Px+JiYnV3raiK2ZmZujVqxf27t2LuLg4fP7552qVJ8oxYWfPngUAtG/fXu566fKUlBSlyl2+fDmuX78Oa2trtG7dGkOGDJE7JaG0/ueeew6WlpYaq5+IiIiIiDTPx8cHnTp1QmRkJGbNmqVyOaIMR7dv3wYAeHh4yF0vXZ6WlqZUuTNmzKj0+4cffog1a9YgNDRUK/UXFxejuLhY9ntubq5S7SUiIuXkNzaDw90KfTeDiIj0wM7ODunp6WqVIcphdfn5+QCevkB57O3tAQB5eXkKlTdw4EDs2rULaWlpKCgowPnz5zFt2jQUFxdjwoQJVe4d0lT9S5cuhbOzs+zH09NTofYSEREREZHi0tLScPTo0UpzBahClD1HmrZ69epKv7du3Rpffvkl/P39MXHiRMycORODBg3SeL2zZ8/GtGnTZL/n5uYyIBGRWvIbi/I7LSIiIq3ZvHlztevy8/Nx5coVbN26Fbm5uZg0aZJadYkyHElnpysoKJC7/smTJwAAR0dHteoZP348PvvsM6SmpuLWrVvw9vbWaP3W1tZVniJMRERERETVa9q0KUaMGCGbXCEkJETuVN5SgiAAAMaOHYv58+erVbcow1GTJk0AAHfu3JG7Xrpc3bnMzczM4OvriwcPHiAjI0MWjnRVPxERERERVXbr1i1kZmbKfp87d2614cjKygqNGjVCjx490LRpU7XrFmU4CggIAACcPn1a7nrp8jZt2qhdV3Z2NoB/7yN6tv7z58+jtLS0yox1mqyfiIg0i5MyEBEZl/DwcJ3VJcrB6127doWzszOuX7+OM2fOVFkfHR0NABgwYIBa9Vy4cAGpqamws7ODv7+/bLmPjw9atmyJwsJCxMXFaa1+IiJl8H4jIiIi7RLlJ62VlRWmTJkCAJg8ebLsHh8AWLlyJVJSUhAYGIgOHTrIlkdERMDf3x+zZ8+uVNa+fftw6NChKnWkpKRgxIgREAQBEyZMgJWVVaX10okUZsyYgQcPHsiW79q1C7/88guaNWumlUkciIiIiIhIP0Q5rA4APvvsMxw8eBCJiYnw8/ND9+7dkZaWhhMnTsDNzQ2RkZGVts/KykJqaioyMjIqLU9OTsb8+fPh5eWFgIAA2NnZ4caNGzh9+jTKysoQFBSEZcuWVak/NDQU+/btQ0xMDPz9/fHKK68gKysL8fHxsLW1xdatW2FhIdrDR0RERERksM6cOYMFCxaotO/cuXNVrle0V/c2NjY4fPgwli5dim3btiE2NhZ169ZFSEgIFi5cWO0DWv+rb9++SE9Px8mTJ3Hs2DHk5OTAyckJ3bp1w+jRozFu3DiYm5tX2c/MzAw///wzVq1ahcjISOzduxf29vYYNmwY5s+fj1atWmn6JRMRkYbwviMiIsN29uxZnD17Vql9BEGARCJRKxxJBOncd6R1ubm5cHZ2RocRi2BhaaPv5hCRgeE9R8phOCIiVZSVFuHUz5/JvlAXC+l1ZFDHT2Fhodp1ZFlZEY6cXCy61/ZfZmZmaNasGbp27arS/hs3blS5btH2HBER0b8YjIiIyJR069atym00usBPWyIiIiIiIjAcERERERERAWA4IiIiI8WhiEREpCx+chAREREREYETMhARiR57QIiIyJRUVOhvtlF+4hIREREREYHhiIiIjBh73YiISBn81CAiEjFe3BMRkb6tXLkSQ4cOhZ+fH5ydnWFtbQ0vLy+MHTsW586d03fzNIqfukREIsVgpBk8jkRE6lmyZAl+/fVX1K1bF6+88gr69+8PGxsbbNmyBR06dMDevXv13USN4YQMRERERERUrd27d6NDhw6wsbGptPybb77B5MmTMWHCBNy5cwcWFoYfLfh1GhGRCLG3Q7N4PImIVNe1a9cqwQgAJk2aBF9fX/zzzz+4ePGiHlqmefy0ICISGV7Ia0d+YzMeWyIiDbO0tAQAWFlZ6bklmsFPCSIikeDFu27wGBMRacaWLVuQmpoKPz8/+Pn56bs5GmH4AwOJiAwcL9Z1T3rMHe7q70GDRESGZvny5bhw4QKePHmCS5cu4cKFC3B3d8f27dthbm6u7+ZpBMMREZEeMRjpF0MSEZmi3NzcSr9bW1vD2tq61v3279+PP/74Q/a7l5cXNm/ejA4dOmi8jfrCcEREpAcMReKS39iMAYmIDILFzQxYmKl4f09FCQDA09Oz0uJ58+YhPDy81t0PHjwIAHj8+DHOnTuHBQsWIDAwEIsWLcKnn36qWptEhuGIiEiHGIrEi71IRGQq0tPT4eTkJPtdkV6jZ7m4uKB79+7Yt28fOnfujDlz5qBPnz7o2LGjppuqc/yUJiLSAU62YDj4b0VExs7JyanSj7LhSMrS0hJvvPEGBEHAnj17NNxK/eC7PxGRlvFC2zAxJBER1c7V1RUAkJmZqeeWaAaH1RERaQEvqo3Hs/+WHHJHRFRZfHw8AMDX11fPLdEMhiMiIg1gGDINDEpEZGqOHTuGvLw89OnTB2Zm/74HlpaWYt26ddiyZQtsbW3xxhtv6LGVmsNwRESkIgYi08agRESm4OrVqxg3bhxcXV3RoUMH1KtXD1lZWTh37hwyMjJgY2ODqKioKjPgGSqGIyIiJTAQkTwMSkRkrAIDA/HJJ58gPj4eKSkpyMrKgpWVFby9vTF8+HB88MEHaNasmb6bqTEMR0RktDQRZBzuVjAQkVL+G5Q0dR4SEemDj48PFi9erO9m6AzDEREZFU0HGQYjUoemzh/2TBER6QbDkR48aWQGc2tecGkSLxZMGwMMmZL/nu98/zNdfO/TjvJiHldTxnBERsEYPiB4gaM4Y/j3JtIU9iqphu8jRCQPwxGRSBjqB7WuLsYM9fgQ6ZI+ghL/NonImDAcEZFaeGFEJE782yQiUh7fOYmIiIiIiMBwREREREREBIDhiIiIiIiICADDEREREREREQCGIyIiIiIiIgAiD0eFhYWYO3cumjdvDhsbG7i7uyM0NBR3795VuIzHjx9j27ZtGDVqFHx8fGBlZQVHR0e89NJLWLVqFUpLS+XuFxISAolEUu3PunXrNPUyiYiIiIhIBEQ7lXdRURF69uyJpKQkNGrUCIMGDcKtW7ewceNG7N27F0lJSWjatGmt5axYsQKLFy+GRCJB27Zt8dJLLyEzMxPHjh1DcnIyoqOjsX//ftjZ2cndv2/fvmjYsGGV5S1atFD7NRIRERERkXiINhwtWrQISUlJ6Ny5Mw4cOAAHBwcAwMqVKzF9+nSEhobiyJEjtZZjb2+PGTNmYPLkyWjSpIls+dWrV9GrVy/8+eefWLRoEZYsWSJ3/1mzZiEoKEgTL4mIiIiIiERMlMPqSkpKEBERAQBYu3atLBgBwLRp09CmTRvEx8fj1KlTtZY1e/ZsfP7555WCEQD4+flh2bJlAIDt27drsPVERERERGSIRBmOjh07hpycHPj6+qJdu3ZV1g8fPhwAsGfPHrXqCQgIAADcu3dPrXKIiIiIiMjwiXJY3dmzZwEA7du3l7teujwlJUWtem7cuAEAcu8pktq1axd27tyJ8vJy+Pj4YMCAAfD391erXiIiIiIiEh9RhqPbt28DADw8POSuly5PS0tTq55Vq1YBAAYNGlTtNmvWrKn0+8yZM/Hee+9h1apVsLAQ5eEjIiIiIiIViHJYXX5+PgBUO4Ocvb09ACAvL0/lOtatW4eDBw/CxcUFs2bNqrK+Xbt2WLduHa5cuYKCggLcuHEDa9euhYuLC7755ht8/PHHtdZRXFyM3NzcSj9ERERERCROogxH2paQkICwsDBIJBJERkbC3d29yjZhYWF455134OfnB1tbW/j4+GDSpElISEiAlZUVIiIikJ6eXmM9S5cuhbOzs+zH09NTWy+JiIiIiIjUJMpwJJ2drqCgQO76J0+eAAAcHR2VLvv8+fMYNGgQSkpKsGrVKgwZMkSp/Vu3bo2BAweirKwMf/zxR43bzp49Gzk5ObKf2sIUERERERHpjyhvmpFOu33nzh2566XLvby8lCr35s2b6NOnD7KzsxEeHo73339fpfb5+fkBADIyMmrcztraGtbW1irVQUREREREuiXKniPpFNunT5+Wu166vE2bNgqXmZGRgd69eyMjIwNhYWGYN2+eyu3Lzs4G8O+9T0RERERExqqwsBBz585F8+bNYWNjA3d3d4SGhuLu3bv6bprGiTIcde3aFc7Ozrh+/TrOnDlTZX10dDQAYMCAAQqVl52djb59++L69esYN24cvvrqK5XbVlxcjLi4OADVTzVORERERGQMioqK0LNnTyxcuBD5+fkYNGgQPD09sXHjRrRr1072aBxjIcpwZGVlhSlTpgAAJk+eLLvHCABWrlyJlJQUBAYGokOHDrLlERER8Pf3x+zZsyuVVVBQgP79++PcuXMYOXIk1q9fD4lEUmP9ly9fxpYtW1BcXFxpeWZmJt58802kp6cjICAAXbt2VfelEhERERGJ1qJFi5CUlITOnTvjypUr+Omnn3DixAl8+eWXyMzMRGhoqL6bqFGivOcIAD777DMcPHgQiYmJ8PPzQ/fu3ZGWloYTJ07Azc0NkZGRlbbPyspCampqlfuAPv30Uxw/fhzm5uawsLDA+PHj5dYXFRUl+//79+9j7NixCAsLwwsvvAA3Nzfcu3cPp06dQl5eHjw8PLBjx45aQxYRERERkaEqKSlBREQEAGDt2rWySdMAYNq0adi0aRPi4+Nx6tSpSp0Whky04cjGxgaHDx/G0qVLsW3bNsTGxqJu3boICQnBwoULq31A7H9J7w8qLy/Htm3bqt3u2XDUvHlzTJ06FUlJSTh37hwePnwIa2trNG/eHAMGDEBYWBjq1Kmj1usjIiIiIhKzY8eOIScnB76+vmjXrl2V9cOHD0dKSgr27NnDcKQLtra2WLBgARYsWFDrtuHh4QgPD6+yPCoqqlLwUYS7u7ta9yURERERERm6s2fPAqj+Pnvp8pSUFJ21SdtEec8RERERERHp1+3btwGg2hFb0uVpaWk6a5O2ibrnyNgIggAAKC8u0nNLiIiIiEge6XWa9LpNbMqEEqBCjX0B5ObmVlpe3bM58/PzAQB2dnZyy5M+1iYvL0+1BokQw5EOSU+cq9/VPkyQiIiIiPQnLy8Pzs7O+m6GjJWVFRo2bIgj97eqVY6DgwM8PT0rLZs3b57c21NMEcORDrm7uyM9PR2Ojo4mNdNdbm4uPD09kZ6eDicnJ303x2DxOGoOj6Xm8FhqBo+j5vBYao6pHktBEJCXlwd3d3d9N6USGxsb3Lx5EyUlJWqVIwhCletQeb1GAGSz0xUUFMhdL33cjqOjo1ptEhOGIx0yMzNTeJY9Y+Tk5GRSb67awuOoOTyWmsNjqRk8jprDY6k5pngsxdRj9CwbGxvY2NjorL4mTZoAAO7cuSN3vXS5l5eXztqkbZyQgYiIiIiIqggICAAAnD59Wu566fI2bdrorE3axnBERERERERVdO3aFc7Ozrh+/TrOnDlTZX10dDQAYMCAATpumfYwHJHWWVtbY968edWOZyXF8DhqDo+l5vBYagaPo+bwWGoOjyVZWVlhypQpAIDJkyfL7jECgJUrVyIlJQWBgYFG8wBYAJAIYp2nkIiIiIiI9KqoqAhBQUE4ceIEGjVqhO7duyMtLQ0nTpyAm5sbkpKS0LRpU303U2MYjoiIiIiIqFqFhYVYunQptm3bhvT0dNStWxf9+vXDwoULjW6yMYYjIiIiIiIi8J4jIiIiIiIiAAxHpIRTp05h2bJlGDp0KDw8PCCRSFR+mK23t7dsf3k/ly9f1nDrxaOgoACxsbEYP348WrRoARsbG9jb2yMgIAALFixAfn6+0mVmZ2cjLCwMXl5esLa2hpeXF6ZOnYrHjx9r/gWIiKaPpSmfl8DTm2uHDh0KPz8/ODs7y86lsWPH4ty5c0qXZ6rnpSaPo6mfk896+PAh6tevD4lEgmbNmqlUhqmek/+l7rHkeUnGjMPqSGGDBw/G7t27qyxX5RTy9vZGWloagoOD5a5funQpGjVqpHS5huCHH37A22+/DQBo2bIlnnvuOeTm5iIxMRF5eXnw9/dHfHw86tevr1B5WVlZ6Ny5M65du4amTZvihRdewIULF3DhwgU0b94cx48fR926dbX5kvRG08fSlM9LAHB1dcWTJ0/Qpk0bNG7cGABw4cIFXLlyBZaWlti1axdef/11hcoy5fNSk8fR1M/JZ4WEhGDz5s0QBAG+vr64du2aUvub8jn5X+oeS56XZNQEIgUtW7ZMmDNnjvDLL78IGRkZgrW1taDqKeTl5aXyvoYuKipKmDhxonDx4sVKy+/duye0a9dOACCMGjVK4fJGjx4tABCGDh0qlJaWypa///77AgAhODhYU00XHU0fS1M+LwVBEP7880+hsLCwyvK1a9cKAIQGDRpUOsdqYsrnpSaPo6mfk1IHDx4UAAgTJ04UAAi+vr5Kl2HK5+SzNHEseV6SMWPPEanMxsYGxcXFavUc8fSr7Pjx4+jSpQusra2Rm5sLKyurGrfPyMiAh4cHLCwscPv2bTRo0EC2rri4GJ6ennj06BHu3buncO+JsVD2WAI8L2vSrFkzXL9+HWfPnq31Seg8L6unzHEEeE4CT2fJev7552FtbY3Y2Fg0b95c6d4OnpNPaeJYAjwvybjxniMiEQkICADw9MP64cOHtW7/22+/oaKiAt27d6/0YQ88fXjfgAEDUF5ejn379mmlvWKm7LGkmllaWgKAQiGT52X1lDmO9NT8+fNx48YNrFu3Tnb8lMVz8ilNHEsiY2eh7waQaVu+fDmuX78Oa2trtG7dGkOGDIGbm5u+m6U3N27cAPD0AkqRse9nz54FALRv317u+vbt2yMyMhIpKSmaa6SBUPZYPovnZWVbtmxBamoq/Pz84OfnV+v2PC/lU/Y4PstUz8mUlBR8+eWXGDduHLp3745bt26pVA7PSc0dy2eZ6nlJxo3hiPRqxowZlX7/8MMPsWbNGoSGhuqpRfq1atUqAEC/fv1gbW1d6/a3b98GgGofwCZdnpaWpqEWGg5lj+WzTP28XL58OS5cuIAnT57g0qVLuHDhAtzd3bF9+3aYm5vXuj/Py6fUPY7PMsVzsqKiAhMmTICLiwu++OILtcoy9XNSk8fyWaZ4XpLx47A60ouBAwdi165dSEtLQ0FBAc6fP49p06ahuLgYEyZMkDsrnrHbt28fNmzYAEtLSyxcuFChfaRTVdvZ2cldb29vDwDIy8vTTCMNhCrHEuB5KbV//35s2rQJ0dHRuHDhAry8vLB9+3Z06NBBof15Xj6l7nEETPucXLNmDU6ePInly5ejXr16apVl6uekJo8lYNrnJZkAPU4GQQZOndnqqvP9998LAIQWLVpotFyxu3TpklCnTh0BgPD1118rvF/v3r0FAML69evlrv/9998FAELv3r011VTRU/VY1sRUz8vs7Gzh6NGjQq9evQQAwqJFixTaj+dlZaoex5oY+zmZlpYmODg4CIGBgZWW37x5U6UZ1kz5nNT0sayJsZ+XZBrYc0SiMn78eNSvXx+pqakaGQ9tCO7evYt+/fohOzsb06ZNQ1hYmML7Ojg4AHj6MFR5njx5AgBwdHRUv6EGQJ1jWRNTPC8BwMXFBd27d8e+ffvQoUMHzJkzBydPnqx1P56Xlal6HGti7Ofk5MmTUVJSgnXr1mmkPFM+JzV9LGti7OclmQbec0SiYmZmBl9fXzx48AAZGRnw9vbWd5O06tGjR+jTpw/S0tIwbtw4rFixQqn9mzRpAgC4c+eO3PXS5V5eXuo11ACoeyxrYmrn5X9ZWlrijTfewKlTp7Bnzx507Nixxu15Xsqn7HGsibGfk3v37oWLiwvefffdSsuLiooAPP0iJCgoCADwv//9Dw0bNqyxPFM+JzV9LGti7OclmQaGIxKd7OxsAP+OATdW+fn5ePXVV3Hx4kUMHToU69evh0QiUaoM6XTVp0+flrteulyR56kYMk0cy9qYynlZHVdXVwBAZmZmrdvyvKyeMsexNsZ+Tj5+/Bjx8fFy1xUVFcnWSS/ya2Lq56Qmj2VtjP28JOPHYXUkKhcuXEBqairs7Ozg7++v7+ZoTXFxMQYNGoTk5GT07dtXpdmrgKczsZmZmSEhIQEPHjyoUseePXtgbm6O1157TVNNFx1NHcuamMp5WRPpxZOvr2+t2/K8rJ4yx7Emxn5OCoIg9+fmzZsAnh4/6TJFeidM+ZzU9LGsibGfl2QaGI5IayIiIuDv74/Zs2dXWr5v3z4cOnSoyvYpKSkYMWIEBEHAhAkTjPYhieXl5Rg1ahQOHTqE7t27Y9euXbW+1uqOZaNGjTBq1CiUlJRg0qRJKCsrk62bMWMGMjMzMWbMGKN94rsmj6Wpn5fHjh2TPSjzWaWlpVizZg22bNkCW1tbvPHGG7J1PC+r0uRxNPVzUhU8JzWH5yWZKg6rI4XFxcVVmha5pKQEANCpUyfZsjlz5qB///4AgKysLKSmpiIjI6NSOcnJyZg/fz68vLwQEBAAOzs73LhxA6dPn0ZZWRmCgoKwbNkyHbwi/YiIiEBMTAyAp0NsJk2aJHe7FStWyIbgVHcsAeDrr79GUlISdu7cCX9/f7zwwgu4cOECzp8/Dz8/P6xcuVJ7L0bPNHksTf28vHr1KsaNGwdXV1d06NAB9erVQ1ZWFs6dO4eMjAzY2NggKioKnp6esn14XlalyeNo6uekKnhOag7PSzJVDEeksMzMTJw4caLK8meXKTKOvm/fvkhPT8fJkydx7Ngx5OTkwMnJCd26dcPo0aMxbtw4jQ+LEhPpeGwAsgt7ecLDw2UX9DVxdXVFcnIywsPDERsbi5iYGDRo0AAffPAB5s+fDxcXF000W5Q0eSxN/bwMDAzEJ598gvj4eKSkpCArKwtWVlbw9vbG8OHD8cEHH6BZs2YKl2eq56Umj6Opn5OaZqrnpKbxvCRjJxEEQdB3I4iIiIiIiPSN9xwRERERERGB4YiIiIiIiAgAwxEREREREREAhiMiIiIiIiIADEdEREREREQAGI6IiIiIiIgAMBwREREREREBYDgiIiIiIiICwHBERERKWLBgAczMzHDu3Dmt1jN48GA0aNAA+fn5Wq2HiIjoWQxHRESkkH/++QfLly/H8OHD8fzzz2u1rrlz5+LBgwf44osvtFoPERHRsySCIAj6bgQREYlfWFgYVq9ejdOnT6Ndu3Zar69fv35ISEjA7du3Ua9ePa3XR0RExJ4jIiKqVUFBATZt2oTnnntOJ8EIAMaMGSOrl4iISBcYjoiIjMxff/0FiUSCLl26VLvNkiVLIJFIMG/ePIXK/Pnnn5GTk4NRo0bJXS+RSODt7Y2ysjIsXLgQzZo1g62tLVq2bImNGzfKtjt06BBefvllODk5oU6dOhg7diwePnwot8zBgwfD1tYW69evV6iNRERE6uKwOiIiI9ShQwecPn0a58+fR+vWrSutEwQBzZo1w61bt3Dz5k00adKk1vJGjBiB6OhoHDt2TG7okkgk8PLyQvv27WUBqKCgAPHx8SguLkZkZCQcHR0xatQodOrUCQ0bNsTx48dx9+5ddOvWDUePHoVEIqlSbo8ePZCQkIDr16+jadOmqh8QIiIiBbDniIjICL377rsAILfX5Y8//sCNGzfQt29fhYIRACQkJMDCwqLGIXVpaWm4evUqrl69ipiYGOzfvx+//vorAODTTz/Fu+++i9jYWCQkJODnn3/GxYsX0bp1a/z55584cuSI3DJffPFFAEB8fLxC7SQiIlIHwxERkRF666234OTkhC1btqC4uLjSuh9++AEA8PbbbytU1oMHD/DPP//A09MTtra2NW779ddfw83NTfb7yy+/jHbt2iEjIwOvvvoq+vfvL1vn5OSEiRMnAqg+/Pj7+wMAzpw5o1BbiYiI1MFwRERkhOzt7TFmzBg8evQIO3fulC3PyspCTEwMGjZsiAEDBihU1oMHDwAAderUqXE7S0tLBAUFVVkuHQ7Xp0+fatdlZGTILbNu3boAgMzMTIXaSkREpA6GIyIiIyVvaN3mzZtRUlKCcePGwcLCQqFycnJyAACOjo41btewYUOYm5tXWe7g4AAAaNy4cbXr/tu7JeXk5AQAePz4sUJtJSIiUgfDERGRkXr++efRpUsXHDlyBFevXgUAbNiwARKJBBMmTFC4HGdnZwBAXl5ejduZmdX8kVLbenmkwczFxUXpfYmIiJTFcEREZMSkvUc//PADjh07hosXL+KVV15Raua3+vXrAwAePXqklTbWJDs7GwAq3cdERESkLQxHRERGbMSIEahXrx6ioqLwzTffAFB8Igap+vXro2HDhkhPT0dBQYE2mlmtS5cuAQDatm2r03qJiMg0MRwRERkxGxsbBAcH48GDB9i2bRvc3NwwePBgpcvp3r07ysvL8ffff2u+kTVITk4GAAQGBuq0XiIiMk0MR0RERu6dd96RPWA1ODgYVlZWSpchnYK7uucRaUN+fj7++usv+Pv78wGwRESkEwxHRERGrnnz5vDw8AAApSZieNbIkSPh7OyMbdu2abJpNYqJiUFRUZHSwwCJiIhUJREEQdB3I4iISHuOHz+OLl26IDAwUK2enw8//BBff/01/vrrL3To0EFzDaxG37598eeff+L27duoV6+e1usjIiJizxERkZFbvHgxAGDKlClqlTN79mw4ODhg6dKlmmhWjU6fPo0DBw5g+vTpDEZERKQz7DkiIjJCiYmJ2LBhA86fP4/k5GS0b98eJ0+eVOlZQ89asGABwsPDcfbsWTz//PMaam1VgwcPxvHjx3H9+nXZg2KJiIi0jeGIiMgIRUVFYdy4cXB0dESPHj2wdu1aeHl56btZREREosZwREREREREBN5zREREREREBIDhiIiIiIiICADDEREREREREQCGIyIiIiIiIgAMR0RERERERAAYjoiIiIiIiAAwHBEREREREQFgOCIiIiIiIgLAcERERERERAQA+H98iXOO0azeAwAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 1000x440 with 2 Axes>"
       ]
diff --git a/mhkit/river/io/d3d.py b/mhkit/river/io/d3d.py
index 7295d7e11..ac0f49f73 100644
--- a/mhkit/river/io/d3d.py
+++ b/mhkit/river/io/d3d.py
@@ -16,7 +16,8 @@
 from mhkit.utils import unorm
 
 
-def get_all_time(data: netCDF4.Dataset) -> NDArray:
+# pylint: disable=possibly-used-before-assignment
+def get_all_time(data: (netCDF4.Dataset, xr.Dataset)) -> NDArray:
     """
     Returns all of the time stamps from a D3D simulation passed to the function
     as a NetCDF object (data)
@@ -35,10 +36,18 @@ def get_all_time(data: netCDF4.Dataset) -> NDArray:
         simulation conditions at that time.
     """
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be a NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be a NetCDF4 object Dataset")
 
-    seconds_run = np.ma.getdata(data.variables["time"][:], False)
+    if isinstance(data, netCDF4.Dataset):
+        seconds_run = np.ma.getdata(data.variables["time"][:], False)
+
+    elif isinstance(data, xr.Dataset):
+        seconds_run = (
+            (data.time.values - data.time.values[0])
+            .astype("timedelta64[s]")
+            .astype(int)
+        )
 
     return seconds_run
 
@@ -64,6 +73,7 @@ def index_to_seconds(data: netCDF4.Dataset, time_index: int) -> Union[int, float
     return _convert_time(data, time_index=time_index)
 
 
+# pylint: disable=possibly-used-before-assignment
 def seconds_to_index(data: netCDF4.Dataset, seconds_run: Union[int, float]) -> int:
     """
     The function will return the nearest 'time_index' in the data if passed an
@@ -87,10 +97,11 @@ def seconds_to_index(data: netCDF4.Dataset, seconds_run: Union[int, float]) -> i
     return _convert_time(data, seconds_run=seconds_run)
 
 
+# pylint: disable=possibly-used-before-assignment
 def _convert_time(
-    data: netCDF4.Dataset,
+    data: netCDF4.Dataset or xr.Dataset,
     time_index: Optional[Union[int, float]] = None,
-    seconds_run: Optional[Union[int, float]] = None,
+    seconds_run: Optional[Union[int, float, np.datetime64]] = None,
 ) -> Union[int, float]:
     """
     Converts a time index to seconds or seconds to a time index. The user
@@ -118,8 +129,8 @@ def _convert_time(
         provided, returns the closest matching time_index.
     """
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be NetCDF4 object or xarray Dataset")
 
     if not (time_index or seconds_run):
         raise ValueError("Input of time_index or seconds_run needed")
@@ -153,27 +164,30 @@ def _convert_time(
     return converted_value
 
 
+# pylint: disable=unused-variable
 # pylint: disable=too-many-locals
 # pylint: disable=too-many-branches
 # pylint: disable=too-many-statements
+# pylint: disable=used-before-assignment
+# pylint: disable=possibly-used-before-assignment
 def get_layer_data(
-    data: netCDF4.Dataset,
+    data: Union[netCDF4.Dataset, xr.Dataset],
     variable: str,
     layer_index: int = -1,
     time_index: int = -1,
     to_pandas: bool = True,
 ) -> Union[pd.DataFrame, xr.Dataset]:
     """
-    Get variable data from the NetCDF4 object at a specified layer and timestep.
+    Get variable data from the NetCDF4 or xarray object at a specified layer and timestep.
     If the data is 2D the layer_index is ignored.
 
     Parameters
     ----------
-    data: NetCDF4 object
-       A NetCDF4 object that contains spatial data, e.g. velocity or shear
+    data: Union[netCDF4.Dataset, xr.Dataset]
+       A NetCDF4 or xarray Dataset object that contains spatial data, e.g. velocity or shear
        stress, generated by running a Delft3D model.
     variable: string
-        Delft3D outputs many vairables. The full list can be
+        Delft3D outputs many variables. The full list can be
         found using "data.variables.keys()" in the console.
     layer_index: int
          An integer to pull out a layer from the dataset. 0 being closest
@@ -199,8 +213,8 @@ def get_layer_data(
     if not isinstance(layer_index, int):
         raise TypeError("layer_index must be an int")
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be a NetCDF4 Dataset or xarray Dataset")
 
     if variable not in data.variables.keys():
         raise ValueError("variable not recognized")
@@ -208,9 +222,14 @@ def get_layer_data(
     if not isinstance(to_pandas, bool):
         raise TypeError(f"to_pandas must be of type bool. Got: {type(to_pandas)}")
 
-    coords = str(data.variables[variable].coordinates).split()
-    var = data.variables[variable][:]
-    max_time_index = data["time"].shape[0] - 1  # to account for zero index
+    if isinstance(data, netCDF4.Dataset):
+        coords = str(data.variables[variable].coordinates).split()
+        var = data.variables[variable][:]
+        max_time_index = data.variables["time"].shape[0] - 1
+    elif isinstance(data, xr.Dataset):
+        coords = list(data[variable].coords)
+        var = data[variable].values
+        max_time_index = data["time"].shape[0] - 1
 
     if abs(time_index) > max_time_index:
         raise ValueError(
@@ -218,8 +237,12 @@ def get_layer_data(
             f"max time index {max_time_index}"
         )
 
-    x = np.ma.getdata(data.variables[coords[0]][:], False)
-    y = np.ma.getdata(data.variables[coords[1]][:], False)
+    if isinstance(data, netCDF4.Dataset):
+        x = np.ma.getdata(data.variables[coords[0]][:], False)
+        y = np.ma.getdata(data.variables[coords[1]][:], False)
+    elif isinstance(data, xr.Dataset):
+        x = data[coords[0]].values
+        y = data[coords[1]].values
 
     if isinstance(var[0][0], np.ma.core.MaskedArray):
         max_layer = len(var[0][0])
@@ -229,7 +252,14 @@ def get_layer_data(
 
         v = np.ma.getdata(var[time_index, :, layer_index], False)
         dimensions = 3
+    elif isinstance(var[0][0], np.ndarray):
+        max_layer = var[0][0].shape[0]
 
+        if abs(layer_index) > max_layer:
+            raise ValueError(f"layer_index must be less than the max layer {max_layer}")
+
+        v = np.ma.getdata(var[time_index, :, layer_index], False)
+        dimensions = 3
     else:
         if not isinstance(var[0][0], np.float64):
             raise TypeError("data not recognized")
@@ -238,76 +268,148 @@ def get_layer_data(
         v = np.ma.getdata(var[time_index, :], False)
 
     # waterdepth
-    if "mesh2d" in variable:
-        cords_to_layers = {
-            "mesh2d_face_x mesh2d_face_y": {
-                "name": "mesh2d_nLayers",
-                "coords": data.variables["mesh2d_layer_sigma"][:],
-            },
-            "mesh2d_edge_x mesh2d_edge_y": {
-                "name": "mesh2d_nInterfaces",
-                "coords": data.variables["mesh2d_interface_sigma"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(
-            data.variables["mesh2d_waterdepth"][time_index, :], False
-        )
-        waterlevel = np.ma.getdata(data.variables["mesh2d_s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-
-    elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(data.variables["waterdepth"][time_index, :], False)
-        waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-    else:
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(data.variables["waterdepth"][time_index, :], False)
-        waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-
-    layer_dim = str(data.variables[variable].coordinates)
+    if isinstance(data, netCDF4.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["mesh2d_waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(
+                data.variables["mesh2d_s1"][time_index, :], False
+            )
+            coords = str(data.variables["mesh2d_waterdepth"].coordinates).split()
+
+        elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
+            coords = str(data.variables["waterdepth"].coordinates).split()
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
+            coords = str(data.variables["waterdepth"].coordinates).split()
+
+        layer_dim = str(data.variables[variable].coordinates)
+
+    elif isinstance(data, xr.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+            }
+            bottom_depth = data["mesh2d_waterdepth"].values[time_index, :]
+            waterlevel = data["mesh2d_s1"].values[time_index, :]
+            coords = list(data["mesh2d_waterdepth"].coords)
+        elif (
+            str(list(data[variable].coords))
+            == "['FlowElem_xcc', 'FlowElem_ycc', 'time']"
+            or str(list(data[variable].coords))
+            == "['FlowLink_xu', 'FlowLink_yu', 'time']"
+        ):
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+
+        layer_dim = " ".join(map(str, list(data[variable].coords)[0:2]))
 
     try:
         cord_sys = cords_to_layers[layer_dim]["coords"]
     except KeyError as exc:
         raise ValueError("Coordinates not recognized.") from exc
-    layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+
+    if isinstance(data, netCDF4.Dataset):
+        layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+    elif isinstance(data, xr.Dataset):
+        layer_percentages = cord_sys.values  # accumulative
 
     if layer_dim == "FlowLink_xu FlowLink_yu":
         # interpolate
-        x_laydim = np.ma.getdata(data.variables[coords[0]][:], False)
-        y_laydim = np.ma.getdata(data.variables[coords[1]][:], False)
-        points_laydim = np.array([[x, y] for x, y in zip(x_laydim, y_laydim)])
+        if isinstance(data, netCDF4.Dataset):
+            x_laydim = np.ma.getdata(data.variables[coords[0]][:], False)
+            y_laydim = np.ma.getdata(data.variables[coords[1]][:], False)
+            coords_request = str(data.variables[variable].coordinates).split()
+            x_wdim = np.ma.getdata(data.variables[coords_request[0]][:], False)
+            y_wdim = np.ma.getdata(data.variables[coords_request[1]][:], False)
+        elif isinstance(data, xr.Dataset):
+            x_laydim = data[coords[0]].values
+            y_laydim = data[coords[1]].values
+            coords_request = list(data[variable].coords)[0:2]
+            x_wdim = data[coords_request[0]].values
+            y_wdim = data[coords_request[1]].values
 
-        coords_request = str(data.variables[variable].coordinates).split()
-        x_wdim = np.ma.getdata(data.variables[coords_request[0]][:], False)
-        y_wdim = np.ma.getdata(data.variables[coords_request[1]][:], False)
+        points_laydim = np.array([[x, y] for x, y in zip(x_laydim, y_laydim)])
         points_wdim = np.array([[x, y] for x, y in zip(x_wdim, y_wdim)])
 
         bottom_depth_wdim = interp.griddata(points_laydim, bottom_depth, points_wdim)
         water_level_wdim = interp.griddata(points_laydim, waterlevel, points_wdim)
 
         idx_bd = np.where(np.isnan(bottom_depth_wdim))
-
         for i in idx_bd:
             bottom_depth_wdim[i] = interp.griddata(
                 points_laydim, bottom_depth, points_wdim[i], method="nearest"
@@ -332,7 +434,14 @@ def get_layer_data(
             z = [bottom_depth * layer_percentages[layer_index]]
     waterdepth = np.append(waterdepth, z)
 
-    time = np.ma.getdata(data.variables["time"][time_index], False) * np.ones(len(x))
+    if isinstance(data, netCDF4.Dataset):
+        time = np.ma.getdata(data.variables["time"][time_index], False) * np.ones(
+            len(x)
+        )
+    elif isinstance(data, xr.Dataset):
+        time = (data.time.values[time_index] - data.time.values[0]).astype(
+            "timedelta64[s]"
+        ).astype(int) * np.ones(len(x))
 
     index = np.arange(0, len(time))
     layer_data = xr.Dataset(
@@ -534,8 +643,10 @@ def variable_interpolation(
                 f"If a string, points must be cells or faces. Got {points}"
             )
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError(f"data must be netCDF4 object. Got {type(data)}")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError(
+            f"data must be netCDF4 or xarray Dataset object. Got {type(data)}"
+        )
 
     if not isinstance(to_pandas, bool):
         raise TypeError(f"to_pandas must be of type bool. Got: {type(to_pandas)}")
@@ -583,8 +694,12 @@ def variable_interpolation(
     return transformed_data
 
 
+# pylint: disable=possibly-used-before-assignment
 def get_all_data_points(
-    data: netCDF4.Dataset, variable: str, time_index: int = -1, to_pandas: bool = True
+    data: (netCDF4.Dataset, xr.Dataset),
+    variable: str,
+    time_index: int = -1,
+    to_pandas: bool = True,
 ) -> Union[pd.DataFrame, xr.Dataset]:
     """
     Get data points for a passed variable for all layers at a specified time from
@@ -616,8 +731,8 @@ def get_all_data_points(
     if not isinstance(time_index, int):
         raise TypeError("time_index must be an int")
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be NetCDF4 object or xarray Dataset")
 
     if variable not in data.variables.keys():
         raise ValueError("variable not recognized")
@@ -630,49 +745,110 @@ def get_all_data_points(
         raise ValueError(
             f"time_index must be less than the max time index {max_time_index}"
         )
-
-    if "mesh2d" in variable:
-        cords_to_layers = {
-            "mesh2d_face_x mesh2d_face_y": {
-                "name": "mesh2d_nLayers",
-                "coords": data.variables["mesh2d_layer_sigma"][:],
-            },
-            "mesh2d_edge_x mesh2d_edge_y": {
-                "name": "mesh2d_nInterfaces",
-                "coords": data.variables["mesh2d_interface_sigma"][:],
-            },
-        }
-
-    elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-    else:
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-
-    layer_dim = str(data.variables[variable].coordinates)
+    if isinstance(data, netCDF4.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+
+        elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+
+        layer_dim = str(data.variables[variable].coordinates)
+    elif isinstance(data, xr.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+            bottom_depth = data["mesh2d_waterdepth"].values[time_index, :]
+            waterlevel = data["mesh2d_s1"].values[time_index, :]
+            coords = list(data["mesh2d_waterdepth"].coords)
+        elif (
+            str(list(data[variable].coords))
+            == "['FlowElem_xcc', 'FlowElem_ycc', 'time']"
+            or str(list(data[variable].coords))
+            == "['FlowLink_xu', 'FlowLink_yu', 'time']"
+        ):
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+
+        layer_dim = " ".join(map(str, list(data[variable].coords)[0:2]))
 
     try:
         cord_sys = cords_to_layers[layer_dim]["coords"]
     except KeyError as exc:
         raise ValueError("Coordinates not recognized.") from exc
-    layer_percentages = np.ma.getdata(cord_sys, False)
+    if isinstance(data, netCDF4.Dataset):
+        layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+    elif isinstance(data, xr.Dataset):
+        layer_percentages = cord_sys.values  # accumulative
 
     x_all = []
     y_all = []
@@ -690,7 +866,7 @@ def get_all_data_points(
         depth_all = np.append(depth_all, layer_data.waterdepth)
         water_level_all = np.append(water_level_all, layer_data.waterlevel)
         v_all = np.append(v_all, layer_data.v)
-        time_all = np.append(time_all, layer_data.time)
+        time_all = np.append(time_all, np.asarray(layer_data.time))
 
     index = np.arange(0, len(time_all))
     all_data = xr.Dataset(
@@ -711,6 +887,7 @@ def get_all_data_points(
     return all_data
 
 
+# pylint: disable=too-many-lines
 def turbulent_intensity(
     data: netCDF4.Dataset,
     points: Union[str, pd.DataFrame, xr.Dataset] = "cells",
@@ -784,8 +961,8 @@ def turbulent_intensity(
             f"value of the max time index {max_time_index}"
         )
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be netCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be netCDF4 object or xarray Dataset")
 
     for variable in ["turkin1", "ucx", "ucy", "ucz"]:
         if variable not in data.variables.keys():
@@ -852,6 +1029,7 @@ def turbulent_intensity(
     return turbulent_data
 
 
+# pylint: disable=too-many-lines
 def list_variables(data: Union[netCDF4.Dataset, xr.Dataset, xr.DataArray]) -> List[str]:
     """
     List all variables in a DataArray, Dataset, or NetCDF4 Dataset.
@@ -886,3 +1064,52 @@ def list_variables(data: Union[netCDF4.Dataset, xr.Dataset, xr.DataArray]) -> Li
         "data must be a NetCDF4 Dataset, xarray Dataset, or "
         f"xarray DataArray. Got: {type(data)}"
     )
+
+
+# pylint: disable=too-many-lines
+# pylint: disable=superfluous-parens
+def calculate_grid_convergence_index(
+    fine_grid, coarse_grid, refinement_ratio, factor_of_safety=1.25, order=2
+):
+    """
+    Calculate the Grid Convergence Index (GCI) between two grid sizes.
+    https://www.grc.nasa.gov/WWW/wind/valid/tutorial/spatconv.html
+
+    Parameters
+    ----------
+    fine_grid: numpy.ndarray
+        Results from the finer grid.
+    coarse_grid: numpy.ndarray
+        Results from the coarser grid.
+    refinement_ratio: float
+        Refinement ratio between the grids.
+    order: int
+        Order of accuracy (default is 2).
+
+    Returns
+    -------
+    gci: float
+        Grid Convergence Index (GCI).
+    """
+
+    # Validate inputs
+    if not (np.issubdtype(type(refinement_ratio), np.number)):
+        raise TypeError("refinement_ratio must be a numeric values")
+    if not (np.issubdtype(type(factor_of_safety), np.number)):
+        raise TypeError("factor_of_safety must be a numeric values")
+    if not (np.issubdtype(type(order), np.number)):
+        raise TypeError("order must be a numeric values")
+    if not (
+        np.issubdtype(fine_grid.dtype, np.number)
+        and np.issubdtype(coarse_grid.dtype, np.number)
+    ):
+        raise TypeError("fine_grid and coarse_grid must contain numeric values")
+    if fine_grid.shape != coarse_grid.shape:
+        raise ValueError("fine_grid and coarse_grid must have the same shape")
+
+    # Calculate the approximate relative error
+    error = np.abs((fine_grid - coarse_grid) / fine_grid)
+
+    # Calculate the GCI
+    gci = (factor_of_safety * error) / (refinement_ratio**order - 1)
+    return gci
diff --git a/mhkit/tests/river/test_io_d3d.py b/mhkit/tests/river/test_io_d3d.py
index f41ba4962..810ba2bc8 100644
--- a/mhkit/tests/river/test_io_d3d.py
+++ b/mhkit/tests/river/test_io_d3d.py
@@ -10,7 +10,6 @@
 import netCDF4
 import os
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -26,6 +25,7 @@ def setUpClass(self):
 
         filename = "turbineTest_map.nc"
         self.d3d_flume_data = netCDF4.Dataset(join(d3ddatadir, filename))
+        self.d3d_flume_data_xr = xr.open_dataset(join(d3ddatadir, filename))
 
     @classmethod
     def tearDownClass(self):
@@ -33,24 +33,33 @@ def tearDownClass(self):
 
     def test_get_all_time(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         seconds_run = river.io.d3d.get_all_time(data)
+        seconds_run_xr = river.io.d3d.get_all_time(data_xr)
         seconds_run_expected = np.ndarray(
             shape=(5,), buffer=np.array([0, 60, 120, 180, 240]), dtype=int
         )
         np.testing.assert_array_equal(seconds_run, seconds_run_expected)
+        np.testing.assert_array_equal(seconds_run_xr, seconds_run_expected)
 
     def test_convert_time(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = 2
         seconds_run = river.io.d3d.index_to_seconds(data, time_index=time_index)
+        seconds_run_xr = river.io.d3d.index_to_seconds(data_xr, time_index=time_index)
         seconds_run_expected = 120
         self.assertEqual(seconds_run, seconds_run_expected)
+        self.assertEqual(seconds_run_xr, seconds_run_expected)
         seconds_run = 60
         time_index = river.io.d3d.seconds_to_index(data, seconds_run=seconds_run)
+        time_index_xr = river.io.d3d.seconds_to_index(data_xr, seconds_run=seconds_run)
         time_index_expected = 1
         self.assertEqual(time_index, time_index_expected)
+        self.assertEqual(time_index_xr, time_index_expected)
         seconds_run = 62
         time_index = river.io.d3d.seconds_to_index(data, seconds_run=seconds_run)
+        time_index_xr = river.io.d3d.seconds_to_index(data_xr, seconds_run=seconds_run)
         time_index_expected = 1
         output_expected = f"ERROR: invalid seconds_run. Closest seconds_run found {time_index_expected}"
         self.assertWarns(UserWarning)
@@ -60,13 +69,17 @@ def test_convert_time_from_tidal(self):
         Test the conversion of time from using tidal import of d3d
         """
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = 2
         seconds_run = tidal.io.d3d.index_to_seconds(data, time_index=time_index)
+        seconds_run_xr = tidal.io.d3d.index_to_seconds(data_xr, time_index=time_index)
         seconds_run_expected = 120
         self.assertEqual(seconds_run, seconds_run_expected)
+        self.assertEqual(seconds_run_xr, seconds_run_expected)
 
     def test_layer_data(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         variable = ["ucx", "s1"]
         for var in variable:
             layer = 2
@@ -77,10 +90,27 @@ def test_layer_data(self):
             layer_data_expected = river.io.d3d.get_layer_data(
                 data, var, layer_compare, time_index_compare
             )
-
             assert_array_almost_equal(layer_data.x, layer_data_expected.x, decimal=2)
             assert_array_almost_equal(layer_data.y, layer_data_expected.y, decimal=2)
             assert_array_almost_equal(layer_data.v, layer_data_expected.v, decimal=2)
+        for var in variable:
+            layer = 2
+            time_index = 3
+            layer_data_xr = river.io.d3d.get_layer_data(data_xr, var, layer, time_index)
+            layer_compare = 2
+            time_index_compare = 4
+            layer_data_expected_xr = river.io.d3d.get_layer_data(
+                data_xr, var, layer_compare, time_index_compare
+            )
+            assert_array_almost_equal(
+                layer_data_xr.x, layer_data_expected_xr.x, decimal=2
+            )
+            assert_array_almost_equal(
+                layer_data_xr.y, layer_data_expected_xr.y, decimal=2
+            )
+            assert_array_almost_equal(
+                layer_data_xr.v, layer_data_expected_xr.v, decimal=2
+            )
 
     def test_create_points_three_points(self):
         """
@@ -209,6 +239,32 @@ def test_variable_interpolation(self):
             np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
         )
 
+    def test_variable_interpolation_xr(self):
+        data_xr = self.d3d_flume_data_xr
+        variables = ["ucx", "turkin1"]
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points="faces", edges="nearest"
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points="cells", edges="nearest"
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+        x = np.linspace(1, 3, num=3)
+        y = np.linspace(1, 3, num=3)
+        waterdepth = 1
+        points = river.io.d3d.create_points(x, y, waterdepth)
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points=points
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+
     def test_get_all_data_points(self):
         data = self.d3d_flume_data
         variable = "ucx"
@@ -222,6 +278,19 @@ def test_get_all_data_points(self):
         size_output_expected = np.size(output_expected)
         self.assertEqual(size_output, size_output_expected)
 
+    def test_get_all_data_points_xr(self):
+        data_xr = self.d3d_flume_data_xr
+        variable = "ucx"
+        time_step = 3
+        output = river.io.d3d.get_all_data_points(data_xr, variable, time_step)
+        size_output = np.size(output)
+        time_step_compair = 4
+        output_expected = river.io.d3d.get_all_data_points(
+            data_xr, variable, time_step_compair
+        )
+        size_output_expected = np.size(output_expected)
+        self.assertEqual(size_output, size_output_expected)
+
     def test_unorm(self):
         x = np.linspace(1, 3, num=3)
         y = np.linspace(1, 3, num=3)
@@ -236,6 +305,7 @@ def test_unorm(self):
 
     def test_turbulent_intensity(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = -1
         x_test = np.linspace(1, 17, num=10)
         y_test = np.linspace(3, 3, num=10)
@@ -250,7 +320,7 @@ def test_turbulent_intensity(self):
         points = pd.DataFrame(test_points, columns=["x", "y", "waterdepth"])
 
         TI = river.io.d3d.turbulent_intensity(data, points, time_index)
-
+        TI_xr = river.io.d3d.turbulent_intensity(data_xr, points, time_index)
         TI_vars = ["turkin1", "ucx", "ucy", "ucz"]
         TI_data_raw = {}
         for var in TI_vars:
@@ -284,12 +354,16 @@ def test_turbulent_intensity(self):
         assert_array_almost_equal(
             TI.turbulent_intensity, turbulent_intensity_expected, decimal=2
         )
-
+        assert_array_almost_equal(
+            TI_xr.turbulent_intensity, turbulent_intensity_expected, decimal=2
+        )
         TI = river.io.d3d.turbulent_intensity(data, points="faces")
+        TI_xr = river.io.d3d.turbulent_intensity(data_xr, points="faces")
         TI_size = np.size(TI["turbulent_intensity"])
         turkin1 = river.io.d3d.get_all_data_points(data, "turkin1", time_index)
         turkin1_size = np.size(turkin1["turkin1"])
         self.assertEqual(TI_size, turkin1_size)
+        self.assertEqual(TI_size, np.size(TI_xr["turbulent_intensity"]))
 
         TI = river.io.d3d.turbulent_intensity(data, points="cells")
         TI_size = np.size(TI["turbulent_intensity"])
@@ -297,6 +371,15 @@ def test_turbulent_intensity(self):
         ucx_size = np.size(ucx["ucx"])
         self.assertEqual(TI_size, ucx_size)
 
+    def test_calculate_grid_convergence_index(self):
+        fine_grid = np.array([1.0, 2.0, 3.0])
+        coarse_grid = np.array([0.5, 1.5, 2.5])
+        refinement_ratio = 2.0
+        gci = river.io.d3d.calculate_grid_convergence_index(
+            fine_grid, coarse_grid, refinement_ratio
+        )
+        assert_array_almost_equal(gci, np.array([0.2083, 0.1042, 0.0694]), decimal=3)
+
 
 if __name__ == "__main__":
     unittest.main()

From 475c607944338f5695b10d130bd6e98249e56f45 Mon Sep 17 00:00:00 2001
From: James McVey <james.mcvey@pnnl.gov>
Date: Mon, 4 May 2026 11:16:41 -0700
Subject: [PATCH 3/9] NDBC Updates (#437)

Opening this to solve Issue #427

I changed the source code to return degrees instead of radians, which
was a simple fix. I also went ahead and updated the polar plots so that
zero degrees is at the top of the figure, and positive degrees runs
clockwise. We should update this in other polar plots in MHKiT too.

I also updated units to pass CF conventions, whereafter I noticed that
our tests for this code check that the units are the same as what NDBC
outputs. I'm not sure that's necessary. I also saw that we're not
actually testing the value output from the source code, which is
important.

---------

Co-authored-by: Simms, Andrew <andrew.simms@nlr.gov>
---
 examples/directional_waves.ipynb              | 609 ++++++++++++------
 examples/environmental_contours_example.ipynb | 127 ++--
 examples/extreme_response_MLER_example.ipynb  |  38 +-
 .../extreme_response_contour_example.ipynb    |  53 +-
 ...reme_response_full_sea_state_example.ipynb | 418 ++++++------
 mhkit/tests/wave/io/test_ndbc.py              |  72 ++-
 mhkit/wave/graphics.py                        |   3 +
 mhkit/wave/io/ndbc.py                         |  48 +-
 8 files changed, 836 insertions(+), 532 deletions(-)

diff --git a/examples/directional_waves.ipynb b/examples/directional_waves.ipynb
index 99d87dd75..7bc584b9b 100644
--- a/examples/directional_waves.ipynb
+++ b/examples/directional_waves.ipynb
@@ -41,7 +41,7 @@
    "metadata": {},
    "source": [
     "## Request Data\n",
-    "First, we will check if the buoy we're interested in–42012—has directional data. To do this we use the `wave.io.ndbc.available_data` function with any one of the 4 parameters used for the spread function. \n",
+    "First, we will check if the buoy we're interested in–42012, a buoy located in the Gulf south of Alabama—has directional data. To do this we use the `wave.io.ndbc.available_data` function with any one of the 4 parameters used for the spread function. \n",
     "We can see that this buoy does have directional data for the years 2009-2021."
    ]
   },
@@ -78,116 +78,130 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>346</th>\n",
+       "      <th>378</th>\n",
        "      <td>42012</td>\n",
        "      <td>2009</td>\n",
        "      <td>42012d2009.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>347</th>\n",
+       "      <th>379</th>\n",
        "      <td>42012</td>\n",
        "      <td>2010</td>\n",
        "      <td>42012d2010.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>348</th>\n",
+       "      <th>380</th>\n",
        "      <td>42012</td>\n",
        "      <td>2011</td>\n",
        "      <td>42012d2011.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>349</th>\n",
+       "      <th>381</th>\n",
        "      <td>42012</td>\n",
        "      <td>2012</td>\n",
        "      <td>42012d2012.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>350</th>\n",
+       "      <th>382</th>\n",
        "      <td>42012</td>\n",
        "      <td>2013</td>\n",
        "      <td>42012d2013.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>351</th>\n",
+       "      <th>383</th>\n",
        "      <td>42012</td>\n",
        "      <td>2014</td>\n",
        "      <td>42012d2014.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>352</th>\n",
+       "      <th>384</th>\n",
        "      <td>42012</td>\n",
        "      <td>2015</td>\n",
        "      <td>42012d2015.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>353</th>\n",
+       "      <th>385</th>\n",
        "      <td>42012</td>\n",
        "      <td>2016</td>\n",
        "      <td>42012d2016.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>354</th>\n",
+       "      <th>386</th>\n",
        "      <td>42012</td>\n",
        "      <td>2017</td>\n",
        "      <td>42012d2017.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>355</th>\n",
+       "      <th>387</th>\n",
        "      <td>42012</td>\n",
        "      <td>2018</td>\n",
        "      <td>42012d2018.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>356</th>\n",
+       "      <th>388</th>\n",
        "      <td>42012</td>\n",
        "      <td>2019</td>\n",
        "      <td>42012d2019.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>357</th>\n",
+       "      <th>389</th>\n",
        "      <td>42012</td>\n",
        "      <td>2020</td>\n",
        "      <td>42012d2020.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>358</th>\n",
+       "      <th>390</th>\n",
        "      <td>42012</td>\n",
        "      <td>2021</td>\n",
        "      <td>42012d2021.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>359</th>\n",
+       "      <th>391</th>\n",
        "      <td>42012</td>\n",
        "      <td>2022</td>\n",
        "      <td>42012d2022.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>360</th>\n",
+       "      <th>392</th>\n",
        "      <td>42012</td>\n",
        "      <td>2023</td>\n",
        "      <td>42012d2023.txt.gz</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>393</th>\n",
+       "      <td>42012</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>42012d2024.txt.gz</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>394</th>\n",
+       "      <td>42012</td>\n",
+       "      <td>2025</td>\n",
+       "      <td>42012d2025.txt.gz</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
        "        id  year           filename\n",
-       "346  42012  2009  42012d2009.txt.gz\n",
-       "347  42012  2010  42012d2010.txt.gz\n",
-       "348  42012  2011  42012d2011.txt.gz\n",
-       "349  42012  2012  42012d2012.txt.gz\n",
-       "350  42012  2013  42012d2013.txt.gz\n",
-       "351  42012  2014  42012d2014.txt.gz\n",
-       "352  42012  2015  42012d2015.txt.gz\n",
-       "353  42012  2016  42012d2016.txt.gz\n",
-       "354  42012  2017  42012d2017.txt.gz\n",
-       "355  42012  2018  42012d2018.txt.gz\n",
-       "356  42012  2019  42012d2019.txt.gz\n",
-       "357  42012  2020  42012d2020.txt.gz\n",
-       "358  42012  2021  42012d2021.txt.gz\n",
-       "359  42012  2022  42012d2022.txt.gz\n",
-       "360  42012  2023  42012d2023.txt.gz"
+       "378  42012  2009  42012d2009.txt.gz\n",
+       "379  42012  2010  42012d2010.txt.gz\n",
+       "380  42012  2011  42012d2011.txt.gz\n",
+       "381  42012  2012  42012d2012.txt.gz\n",
+       "382  42012  2013  42012d2013.txt.gz\n",
+       "383  42012  2014  42012d2014.txt.gz\n",
+       "384  42012  2015  42012d2015.txt.gz\n",
+       "385  42012  2016  42012d2016.txt.gz\n",
+       "386  42012  2017  42012d2017.txt.gz\n",
+       "387  42012  2018  42012d2018.txt.gz\n",
+       "388  42012  2019  42012d2019.txt.gz\n",
+       "389  42012  2020  42012d2020.txt.gz\n",
+       "390  42012  2021  42012d2021.txt.gz\n",
+       "391  42012  2022  42012d2022.txt.gz\n",
+       "392  42012  2023  42012d2023.txt.gz\n",
+       "393  42012  2024  42012d2024.txt.gz\n",
+       "394  42012  2025  42012d2025.txt.gz"
       ]
      },
      "execution_count": 2,
@@ -204,7 +218,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will ask for the data for 2021. To do this we use the `wave.io.ndbc.request_directional_data` function. We see that the spectrum is calculated over ~1hour which results in 8572 different timestamps. We also see there are 47 frequency bins."
+    "We will ask for the data for 2021. To do this we use the `wave.io.ndbc.request_directional_data` function. We see that the spectrum is calculated over ~1 hour which results in 8572 different timestamps. We also see there are 47 frequency bins."
    ]
   },
   {
@@ -230,39 +244,86 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "html[data-theme=dark],\n",
-       "body[data-theme=dark],\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -285,11 +346,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -297,7 +365,9 @@
        ".xr-sections {\n",
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -305,11 +375,15 @@
        "}\n",
        "\n",
        ".xr-section-item input {\n",
-       "  display: none;\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -317,6 +391,10 @@
        "  color: var(--xr-font-color2);\n",
        "}\n",
        "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
        ".xr-section-item input:enabled + label:hover {\n",
        "  color: var(--xr-font-color0);\n",
        "}\n",
@@ -338,7 +416,7 @@
        "\n",
        ".xr-section-summary-in + label:before {\n",
        "  display: inline-block;\n",
-       "  content: '►';\n",
+       "  content: \"►\";\n",
        "  font-size: 11px;\n",
        "  width: 15px;\n",
        "  text-align: center;\n",
@@ -349,7 +427,7 @@
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
+       "  content: \"▼\";\n",
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label > span {\n",
@@ -359,7 +437,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -369,6 +446,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -376,6 +454,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -421,15 +525,15 @@
        "}\n",
        "\n",
        ".xr-dim-list:before {\n",
-       "  content: '(';\n",
+       "  content: \"(\";\n",
        "}\n",
        "\n",
        ".xr-dim-list:after {\n",
-       "  content: ')';\n",
+       "  content: \")\";\n",
        "}\n",
        "\n",
        ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
+       "  content: \",\";\n",
        "  padding-right: 5px;\n",
        "}\n",
        "\n",
@@ -446,7 +550,9 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -457,6 +563,7 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -506,8 +613,15 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -520,6 +634,12 @@
        "  float: right;\n",
        "}\n",
        "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -579,78 +699,69 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 16MB\n",
        "Dimensions:    (date: 8572, frequency: 47)\n",
        "Coordinates:\n",
-       "  * date       (date) datetime64[ns] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
+       "  * date       (date) datetime64[us] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "Data variables:\n",
        "    swden      (date, frequency) float64 3MB 0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0\n",
        "    swdir      (date, frequency) float64 3MB 194.0 13.0 6.0 ... 167.0 159.0\n",
        "    swdir2     (date, frequency) float64 3MB 191.0 11.0 9.0 ... 169.0 106.0\n",
        "    swr1       (date, frequency) float64 3MB 0.16 0.26 0.21 ... 0.76 0.87 0.63\n",
-       "    swr2       (date, frequency) float64 3MB 0.99 0.93 0.9 ... 0.28 0.67 0.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a570ad58-2fe6-4c75-9054-8b4e5179aa77' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a570ad58-2fe6-4c75-9054-8b4e5179aa77' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>date</span>: 8572</li><li><span class='xr-has-index'>frequency</span>: 47</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9a5d80a8-3471-434e-8b89-0ef65c32ebda' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a5d80a8-3471-434e-8b89-0ef65c32ebda' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>date</span></div><div class='xr-var-dims'>(date)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01T00:40:00 ... 2021-12-...</div><input id='attrs-313cb012-7088-4776-b6b4-6087799bb91c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-313cb012-7088-4776-b6b4-6087799bb91c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec2ff83b-baef-43de-9f45-011bc4dcc930' class='xr-var-data-in' type='checkbox'><label for='data-ec2ff83b-baef-43de-9f45-011bc4dcc930' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>datetime</dd><dt><span>standard_name :</span></dt><dd>t</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:40:00.000000000&#x27;, &#x27;2021-01-01T01:40:00.000000000&#x27;,\n",
-       "       &#x27;2021-01-01T02:40:00.000000000&#x27;, ..., &#x27;2021-12-31T21:40:00.000000000&#x27;,\n",
-       "       &#x27;2021-12-31T22:40:00.000000000&#x27;, &#x27;2021-12-31T23:40:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-113d9e44-9203-40de-a87a-ce9b96db0295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-113d9e44-9203-40de-a87a-ce9b96db0295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38a32a2-2487-46a8-bac8-44dd586859d2' class='xr-var-data-in' type='checkbox'><label for='data-b38a32a2-2487-46a8-bac8-44dd586859d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
+       "    swr2       (date, frequency) float64 3MB 0.99 0.93 0.9 ... 0.28 0.67 0.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9c031c50-7cfd-453b-a761-a1ddd3da4ff7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9c031c50-7cfd-453b-a761-a1ddd3da4ff7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>date</span>: 8572</li><li><span class='xr-has-index'>frequency</span>: 47</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e0ddc0a6-3f38-4425-b433-d3b5c73bbe9c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0ddc0a6-3f38-4425-b433-d3b5c73bbe9c' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>date</span></div><div class='xr-var-dims'>(date)</div><div class='xr-var-dtype'>datetime64[us]</div><div class='xr-var-preview xr-preview'>2021-01-01T00:40:00 ... 2021-12-...</div><input id='attrs-60559a62-de99-415f-84ec-10868e9d0bc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60559a62-de99-415f-84ec-10868e9d0bc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2111a76e-dd0c-473c-b5dd-d330e4d17c69' class='xr-var-data-in' type='checkbox'><label for='data-2111a76e-dd0c-473c-b5dd-d330e4d17c69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>datetime</dd><dt><span>standard_name :</span></dt><dd>t</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:40:00.000000&#x27;, &#x27;2021-01-01T01:40:00.000000&#x27;,\n",
+       "       &#x27;2021-01-01T02:40:00.000000&#x27;, ..., &#x27;2021-12-31T21:40:00.000000&#x27;,\n",
+       "       &#x27;2021-12-31T22:40:00.000000&#x27;, &#x27;2021-12-31T23:40:00.000000&#x27;],\n",
+       "      shape=(8572,), dtype=&#x27;datetime64[us]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-0e80c0c8-2121-4469-98bc-bf4213bdb57d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e80c0c8-2121-4469-98bc-bf4213bdb57d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61e77607-a84c-4ce8-95b3-cf311831e31b' class='xr-var-data-in' type='checkbox'><label for='data-61e77607-a84c-4ce8-95b3-cf311831e31b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
        "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925, 0.1   , 0.11  , 0.12  , 0.13  ,\n",
        "       0.14  , 0.15  , 0.16  , 0.17  , 0.18  , 0.19  , 0.2   , 0.21  , 0.22  ,\n",
        "       0.23  , 0.24  , 0.25  , 0.26  , 0.27  , 0.28  , 0.29  , 0.3   , 0.31  ,\n",
        "       0.32  , 0.33  , 0.34  , 0.35  , 0.365 , 0.385 , 0.405 , 0.425 , 0.445 ,\n",
-       "       0.465 , 0.485 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5ed5387-ddaa-483c-926e-bad809afd09b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f5ed5387-ddaa-483c-926e-bad809afd09b' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>swden</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0</div><input id='attrs-18ec67a8-483c-47c7-a495-f3a124169895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18ec67a8-483c-47c7-a495-f3a124169895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cd658d3-400a-4135-8196-3865ad6f61d2' class='xr-var-data-in' type='checkbox'><label for='data-1cd658d3-400a-4135-8196-3865ad6f61d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz</dd><dt><span>long_name :</span></dt><dd>omnidirecational spectrum</dd><dt><span>standard_name :</span></dt><dd>S</dd><dt><span>description :</span></dt><dd>Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).</dd></dl></div><div class='xr-var-data'><pre>array([[0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.02],\n",
+       "       0.465 , 0.485 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2eea650-229b-439b-bb1c-282a8ff4ad2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2eea650-229b-439b-bb1c-282a8ff4ad2f' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>swden</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0</div><input id='attrs-acb6f8a6-3d12-4562-812e-39488f482e89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acb6f8a6-3d12-4562-812e-39488f482e89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a248ab18-28e7-419f-a14e-e48d3da2c0d8' class='xr-var-data-in' type='checkbox'><label for='data-a248ab18-28e7-419f-a14e-e48d3da2c0d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz</dd><dt><span>long_name :</span></dt><dd>omnidirectional spectrum</dd><dt><span>standard_name :</span></dt><dd>S</dd><dt><span>description :</span></dt><dd>Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).</dd></dl></div><div class='xr-var-data'><pre>array([[0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.02],\n",
        "       [0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.01],\n",
        "       [0.  , 0.  , 0.  , ..., 0.02, 0.02, 0.01],\n",
        "       ...,\n",
        "       [0.  , 0.  , 0.  , ..., 0.01, 0.01, 0.02],\n",
        "       [0.  , 0.  , 0.  , ..., 0.01, 0.01, 0.01],\n",
-       "       [0.  , 0.  , 0.  , ..., 0.01, 0.02, 0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>194.0 13.0 6.0 ... 167.0 159.0</div><input id='attrs-f3871019-520c-4696-827d-8487b1f723ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3871019-520c-4696-827d-8487b1f723ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b7070e3-81a5-40b8-acf1-ee1fdbb1a268' class='xr-var-data-in' type='checkbox'><label for='data-8b7070e3-81a5-40b8-acf1-ee1fdbb1a268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>mean wave direction</dd><dt><span>standard_name :</span></dt><dd>α1</dd><dt><span>description :</span></dt><dd>Mean wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[194.,  13.,   6., ..., 127., 125., 129.],\n",
+       "       [0.  , 0.  , 0.  , ..., 0.01, 0.02, 0.  ]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>194.0 13.0 6.0 ... 167.0 159.0</div><input id='attrs-14d3cda6-53f7-4b54-8e0c-f67d14163cec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d3cda6-53f7-4b54-8e0c-f67d14163cec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22588ac6-535f-46a7-9dbb-cdabc93a224e' class='xr-var-data-in' type='checkbox'><label for='data-22588ac6-535f-46a7-9dbb-cdabc93a224e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>mean wave direction</dd><dt><span>standard_name :</span></dt><dd>α1</dd><dt><span>description :</span></dt><dd>Mean wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[194.,  13.,   6., ..., 127., 125., 129.],\n",
        "       [179., 192., 205., ..., 134., 122., 138.],\n",
        "       [193., 356., 177., ..., 141., 128., 123.],\n",
        "       ...,\n",
        "       [ 26., 213.,  21., ..., 177., 179., 181.],\n",
        "       [194.,   7., 345., ..., 150., 176., 181.],\n",
-       "       [198., 199.,  29., ..., 173., 167., 159.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>191.0 11.0 9.0 ... 169.0 106.0</div><input id='attrs-96dcc3af-fcaf-4ed8-ad71-fd9375426a5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96dcc3af-fcaf-4ed8-ad71-fd9375426a5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42fbc38a-2e11-43a1-870e-69a07eceae29' class='xr-var-data-in' type='checkbox'><label for='data-42fbc38a-2e11-43a1-870e-69a07eceae29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>principal wave direction</dd><dt><span>standard_name :</span></dt><dd>α2</dd><dt><span>description :</span></dt><dd>Principal wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[191.,  11.,   9., ..., 132., 118., 120.],\n",
+       "       [198., 199.,  29., ..., 173., 167., 159.]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>191.0 11.0 9.0 ... 169.0 106.0</div><input id='attrs-a539b62a-ac22-4f33-aaf8-09d39153808d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a539b62a-ac22-4f33-aaf8-09d39153808d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1fdd91a-3b11-4d90-96a6-205257b6406f' class='xr-var-data-in' type='checkbox'><label for='data-f1fdd91a-3b11-4d90-96a6-205257b6406f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>principal wave direction</dd><dt><span>standard_name :</span></dt><dd>α2</dd><dt><span>description :</span></dt><dd>Principal wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[191.,  11.,   9., ..., 132., 118., 120.],\n",
        "       [197., 200., 197., ..., 106., 106., 117.],\n",
        "       [187.,   7., 188., ..., 147.,  75.,  53.],\n",
        "       ...,\n",
        "       [ 26., 200.,  22., ..., 179., 201., 184.],\n",
        "       [202.,  25.,  24., ..., 129., 178., 184.],\n",
-       "       [207., 204.,  26., ..., 178., 169., 106.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr1</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.16 0.26 0.21 ... 0.76 0.87 0.63</div><input id='attrs-74bb48ff-8fe0-4f87-8df9-5a1a99541fe6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74bb48ff-8fe0-4f87-8df9-5a1a99541fe6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-258e0fa1-c211-46f6-9202-a318bf0792be' class='xr-var-data-in' type='checkbox'><label for='data-258e0fa1-c211-46f6-9202-a318bf0792be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r1</dd><dt><span>standard_name :</span></dt><dd>r1</dd><dt><span>description :</span></dt><dd>First normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.16, 0.26, 0.21, ..., 0.74, 0.72, 0.72],\n",
+       "       [207., 204.,  26., ..., 178., 169., 106.]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr1</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.16 0.26 0.21 ... 0.76 0.87 0.63</div><input id='attrs-f09f27f9-fe17-47de-ba6e-48fd3b25a8e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09f27f9-fe17-47de-ba6e-48fd3b25a8e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4299d7ff-0489-4511-b4f3-6b56b512cd67' class='xr-var-data-in' type='checkbox'><label for='data-4299d7ff-0489-4511-b4f3-6b56b512cd67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r1</dd><dt><span>standard_name :</span></dt><dd>r1</dd><dt><span>description :</span></dt><dd>First normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.16, 0.26, 0.21, ..., 0.74, 0.72, 0.72],\n",
        "       [0.07, 0.41, 0.08, ..., 0.67, 0.71, 0.68],\n",
        "       [0.23, 0.27, 0.34, ..., 0.65, 0.6 , 0.41],\n",
        "       ...,\n",
        "       [0.34, 0.18, 0.25, ..., 0.69, 0.7 , 0.84],\n",
        "       [0.17, 0.36, 0.29, ..., 0.69, 0.87, 0.82],\n",
-       "       [0.34, 0.44, 0.69, ..., 0.76, 0.87, 0.63]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.99 0.93 0.9 ... 0.28 0.67 0.1</div><input id='attrs-8079fd66-9243-4863-b45e-9643d7e24e0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8079fd66-9243-4863-b45e-9643d7e24e0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea5b4ed-9f0a-4b61-bfdb-b6670c13a075' class='xr-var-data-in' type='checkbox'><label for='data-3ea5b4ed-9f0a-4b61-bfdb-b6670c13a075' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r2</dd><dt><span>standard_name :</span></dt><dd>r2</dd><dt><span>description :</span></dt><dd>Second normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.99, 0.93, 0.9 , ..., 0.21, 0.21, 0.29],\n",
+       "       [0.34, 0.44, 0.69, ..., 0.76, 0.87, 0.63]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.99 0.93 0.9 ... 0.28 0.67 0.1</div><input id='attrs-fdc5d48c-9afb-49fc-bab0-b98f9761f711' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdc5d48c-9afb-49fc-bab0-b98f9761f711' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-daf35db4-f4a6-4b1e-997e-6ddb6639be61' class='xr-var-data-in' type='checkbox'><label for='data-daf35db4-f4a6-4b1e-997e-6ddb6639be61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r2</dd><dt><span>standard_name :</span></dt><dd>r2</dd><dt><span>description :</span></dt><dd>Second normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.99, 0.93, 0.9 , ..., 0.21, 0.21, 0.29],\n",
        "       [0.98, 0.93, 0.88, ..., 0.12, 0.27, 0.13],\n",
        "       [0.99, 0.9 , 0.87, ..., 0.1 , 0.17, 0.32],\n",
        "       ...,\n",
        "       [0.94, 0.94, 0.92, ..., 0.19, 0.2 , 0.51],\n",
        "       [0.91, 0.87, 0.85, ..., 0.3 , 0.65, 0.5 ],\n",
-       "       [0.92, 0.91, 0.83, ..., 0.28, 0.67, 0.1 ]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea045dee-7b8b-4aae-9060-f4acccdec2e1' class='xr-section-summary-in' type='checkbox'  ><label for='section-ea045dee-7b8b-4aae-9060-f4acccdec2e1' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>date</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1c14c4d2-8726-40da-9d7b-a0526c5a2744' class='xr-index-data-in' type='checkbox'/><label for='index-1c14c4d2-8726-40da-9d7b-a0526c5a2744' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01 00:40:00&#x27;, &#x27;2021-01-01 01:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 02:40:00&#x27;, &#x27;2021-01-01 03:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 04:40:00&#x27;, &#x27;2021-01-01 05:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 06:40:00&#x27;, &#x27;2021-01-01 07:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 08:40:00&#x27;, &#x27;2021-01-01 09:40:00&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2021-12-31 14:40:00&#x27;, &#x27;2021-12-31 15:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 16:40:00&#x27;, &#x27;2021-12-31 17:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 18:40:00&#x27;, &#x27;2021-12-31 19:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 20:40:00&#x27;, &#x27;2021-12-31 21:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 22:40:00&#x27;, &#x27;2021-12-31 23:40:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;date&#x27;, length=8572, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a8c8ea4-7c2d-4f15-ac86-3b6f3af6ae28' class='xr-index-data-in' type='checkbox'/><label for='index-3a8c8ea4-7c2d-4f15-ac86-3b6f3af6ae28' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.02, 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
-       "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925,    0.1,   0.11,   0.12,   0.13,\n",
-       "         0.14,   0.15,   0.16,   0.17,   0.18,   0.19,    0.2,   0.21,   0.22,\n",
-       "         0.23,   0.24,   0.25,   0.26,   0.27,   0.28,   0.29,    0.3,   0.31,\n",
-       "         0.32,   0.33,   0.34,   0.35,  0.365,  0.385,  0.405,  0.425,  0.445,\n",
-       "        0.465,  0.485],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;frequency&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bbf14af5-cc5d-4b71-abb7-f95a7015f03a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bbf14af5-cc5d-4b71-abb7-f95a7015f03a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       [0.92, 0.91, 0.83, ..., 0.28, 0.67, 0.1 ]], shape=(8572, 47))</pre></div></li></ul></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 16MB\n",
        "Dimensions:    (date: 8572, frequency: 47)\n",
        "Coordinates:\n",
-       "  * date       (date) datetime64[ns] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
+       "  * date       (date) datetime64[us] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "Data variables:\n",
        "    swden      (date, frequency) float64 3MB 0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0\n",
@@ -705,39 +816,86 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "html[data-theme=dark],\n",
-       "body[data-theme=dark],\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -760,11 +918,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -772,7 +937,9 @@
        ".xr-sections {\n",
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -780,11 +947,15 @@
        "}\n",
        "\n",
        ".xr-section-item input {\n",
-       "  display: none;\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -792,6 +963,10 @@
        "  color: var(--xr-font-color2);\n",
        "}\n",
        "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
        ".xr-section-item input:enabled + label:hover {\n",
        "  color: var(--xr-font-color0);\n",
        "}\n",
@@ -813,7 +988,7 @@
        "\n",
        ".xr-section-summary-in + label:before {\n",
        "  display: inline-block;\n",
-       "  content: '►';\n",
+       "  content: \"►\";\n",
        "  font-size: 11px;\n",
        "  width: 15px;\n",
        "  text-align: center;\n",
@@ -824,7 +999,7 @@
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
+       "  content: \"▼\";\n",
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label > span {\n",
@@ -834,7 +1009,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -844,6 +1018,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -851,6 +1026,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -896,15 +1097,15 @@
        "}\n",
        "\n",
        ".xr-dim-list:before {\n",
-       "  content: '(';\n",
+       "  content: \"(\";\n",
        "}\n",
        "\n",
        ".xr-dim-list:after {\n",
-       "  content: ')';\n",
+       "  content: \")\";\n",
        "}\n",
        "\n",
        ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
+       "  content: \",\";\n",
        "  padding-right: 5px;\n",
        "}\n",
        "\n",
@@ -921,7 +1122,9 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -932,6 +1135,7 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -981,8 +1185,15 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -995,6 +1206,12 @@
        "  float: right;\n",
        "}\n",
        "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -1054,45 +1271,53 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (frequency: 47, direction: 180)&gt; Size: 68kB\n",
-       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))\n",
        "Coordinates:\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "  * direction  (direction) float64 1kB 0.0 2.0 4.0 6.0 ... 354.0 356.0 358.0\n",
        "Attributes:\n",
-       "    units:          m^2/Hz/deg\n",
+       "    units:          m^2/Hz/degree\n",
        "    long_name:      Elevation variance spectrum\n",
        "    standard_name:  spectrum\n",
-       "    description:    *Elevation variance (m^2)* spectrum (/Hz/deg).</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>frequency</span>: 47</li><li><span class='xr-has-index'>direction</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-93cccdeb-4324-42c0-b7ff-0e8989f778ee' class='xr-array-in' type='checkbox' checked><label for='section-93cccdeb-4324-42c0-b7ff-0e8989f778ee' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 ... 2.943e-05 7.353e-05 0.0001211 0.0001721</span></div><div class='xr-array-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "    description:    *Elevation variance (m^2)* spectrum (/Hz/degree).</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>frequency</span>: 47</li><li><span class='xr-has-index'>direction</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e8366115-b53c-411d-a541-f27c68d5ecc3' class='xr-array-in' type='checkbox' checked><label for='section-e8366115-b53c-411d-a541-f27c68d5ecc3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 ... -0.0006447 0.001686 0.004213 0.006937 0.00986</span></div><div class='xr-array-data'><pre>array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])</pre></div></div></li><li class='xr-section-item'><input id='section-941b7b31-c0db-4199-a45a-ee03a450b677' class='xr-section-summary-in' type='checkbox'  checked><label for='section-941b7b31-c0db-4199-a45a-ee03a450b677' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-fb644fc7-7c8b-494e-ac1a-9d6ff4cd9b8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb644fc7-7c8b-494e-ac1a-9d6ff4cd9b8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c6f6461-9147-47f9-b233-fa073ea29238' class='xr-var-data-in' type='checkbox'><label for='data-5c6f6461-9147-47f9-b233-fa073ea29238' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))</pre></div></div></li><li class='xr-section-item'><input id='section-64ee2d6a-6ec4-4f71-a1b4-d7d573421c11' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64ee2d6a-6ec4-4f71-a1b4-d7d573421c11' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-03018c68-6e9e-4ab5-a71e-fec0312698dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03018c68-6e9e-4ab5-a71e-fec0312698dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f902533d-6eb2-46d7-9653-db0ec2bbb5d2' class='xr-var-data-in' type='checkbox'><label for='data-f902533d-6eb2-46d7-9653-db0ec2bbb5d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
        "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925, 0.1   , 0.11  , 0.12  , 0.13  ,\n",
        "       0.14  , 0.15  , 0.16  , 0.17  , 0.18  , 0.19  , 0.2   , 0.21  , 0.22  ,\n",
        "       0.23  , 0.24  , 0.25  , 0.26  , 0.27  , 0.28  , 0.29  , 0.3   , 0.31  ,\n",
        "       0.32  , 0.33  , 0.34  , 0.35  , 0.365 , 0.385 , 0.405 , 0.425 , 0.445 ,\n",
-       "       0.465 , 0.485 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>direction</span></div><div class='xr-var-dims'>(direction)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-bc44332d-cc02-4629-aaa7-411b4c52cc1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc44332d-cc02-4629-aaa7-411b4c52cc1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8d7f712-ec94-409c-8820-6a1bd3bd12d5' class='xr-var-data-in' type='checkbox'><label for='data-f8d7f712-ec94-409c-8820-6a1bd3bd12d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>wave direction</dd><dt><span>standard_name :</span></dt><dd>direction</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
+       "       0.465 , 0.485 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>direction</span></div><div class='xr-var-dims'>(direction)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-ac269564-9ec0-45f3-a169-f26200eb4f51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac269564-9ec0-45f3-a169-f26200eb4f51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b84ae8e1-6373-461d-bae4-ab18524bbf2f' class='xr-var-data-in' type='checkbox'><label for='data-b84ae8e1-6373-461d-bae4-ab18524bbf2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>wave direction</dd><dt><span>standard_name :</span></dt><dd>direction</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
        "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
        "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
        "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
@@ -1106,40 +1331,31 @@
        "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
        "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
        "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
-       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-36041b6d-0acb-4ce7-8ceb-ef6debbe4390' class='xr-section-summary-in' type='checkbox'  ><label for='section-36041b6d-0acb-4ce7-8ceb-ef6debbe4390' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7c2fa4e1-9918-44c7-a18e-d54ef083e985' class='xr-index-data-in' type='checkbox'/><label for='index-7c2fa4e1-9918-44c7-a18e-d54ef083e985' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.02, 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
-       "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925,    0.1,   0.11,   0.12,   0.13,\n",
-       "         0.14,   0.15,   0.16,   0.17,   0.18,   0.19,    0.2,   0.21,   0.22,\n",
-       "         0.23,   0.24,   0.25,   0.26,   0.27,   0.28,   0.29,    0.3,   0.31,\n",
-       "         0.32,   0.33,   0.34,   0.35,  0.365,  0.385,  0.405,  0.425,  0.445,\n",
-       "        0.465,  0.485],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;frequency&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>direction</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cadb9cab-db81-48e5-96b4-c61d50695c25' class='xr-index-data-in' type='checkbox'/><label for='index-cadb9cab-db81-48e5-96b4-c61d50695c25' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,  18.0,\n",
-       "       ...\n",
-       "       340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0, 358.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;direction&#x27;, length=180))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5113910b-fbd9-468d-a599-890266222daa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5113910b-fbd9-468d-a599-890266222daa' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz/deg</dd><dt><span>long_name :</span></dt><dd>Elevation variance spectrum</dd><dt><span>standard_name :</span></dt><dd>spectrum</dd><dt><span>description :</span></dt><dd>*Elevation variance (m^2)* spectrum (/Hz/deg).</dd></dl></div></li></ul></div></div>"
+       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9be16afe-ef39-4f66-80ec-eaecda9855d6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9be16afe-ef39-4f66-80ec-eaecda9855d6' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz/degree</dd><dt><span>long_name :</span></dt><dd>Elevation variance spectrum</dd><dt><span>standard_name :</span></dt><dd>spectrum</dd><dt><span>description :</span></dt><dd>*Elevation variance (m^2)* spectrum (/Hz/degree).</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (frequency: 47, direction: 180)> Size: 68kB\n",
-       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))\n",
        "Coordinates:\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "  * direction  (direction) float64 1kB 0.0 2.0 4.0 6.0 ... 354.0 356.0 358.0\n",
        "Attributes:\n",
-       "    units:          m^2/Hz/deg\n",
+       "    units:          m^2/Hz/degree\n",
        "    long_name:      Elevation variance spectrum\n",
        "    standard_name:  spectrum\n",
-       "    description:    *Elevation variance (m^2)* spectrum (/Hz/deg)."
+       "    description:    *Elevation variance (m^2)* spectrum (/Hz/degree)."
       ]
      },
      "execution_count": 4,
@@ -1180,7 +1396,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1198,7 +1414,7 @@
    "metadata": {},
    "source": [
     "We now show a few other ways of plotting this directional spectra. \n",
-    "In the first plot below we set a minimum value of $0.3m^2/Hz$. \n",
+    "In the first plot below we set a minimum value of 0.3 $m^2/Hz$. \n",
     "In the second plot, we plot 3 contour lines with no fill. "
    ]
   },
@@ -1219,7 +1435,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1249,7 +1465,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1280,7 +1496,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x28112345fd0>]"
+       "[<matplotlib.lines.Line2D at 0x2c438c21b10>]"
       ]
      },
      "execution_count": 8,
@@ -1289,7 +1505,7 @@
     },
     {
      "data": {
-      "image/png": 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9+vfvD4VCgSFDhuD5559Hfn4+VqxYgaCgoArTAl26dMEXX3yB9957Dy1btkRQUBD69u2LN954Axs2bMBDDz2EsWPHokuXLigoKMDJkyfx66+/IiEhodrb1c1ZozRw4EBcvnwZ06ZNw549e7Bnzx79a8HBwXjggQf0zxcuXIihQ4eif//+ePLJJ3Hq1Cl8+umnmDhxItq0aaPf7+mnn8bBgwcxfvx4nD171qB3j6enJ4YPH65/fuLECWzYsAEAcOnSJeTk5OC9994DUDaSM2TIkGrj7969Ox577DHMmDEDaWlpaNmyJVavXo2EhAR88803+v2uXr2KoUOHQiaT4dFHH8W6desMztOhQwd06NCh2mu9/vrr2LBhA4YMGYKsrCx8//33Bq+XL7C/evUq1qxZAwD6URDd99WkSROMGjWq2mtVxtj3aunSpfj8888RHR0Nd3f3CnGOGDECHh4eACpvD3DfffdVuLavry8A4O677zb4/Ix9/4HK2wO4ubnh3XffxeTJk/HYY49hwIAB2L17N77//nu8//77BlPHkyZNwooVKzB48GBMnToVLi4uWLx4MYKDg/H6669Lfj+JamTtTI3I1uzcuVN06dJFKBQK0bx5c7F8+fJKO3Nv2LBBdOjQQbi6uoqmTZuKBQsWiG+//bbCiFJKSooYPHiw8PLyEgAMunTn5eWJGTNmiJYtWwqFQiEaNGggevToIRYtWqT/a70uAKjyUVlX8d9//11ERUUJpVIpGjVqJGbOnFkh3iZNmlR5zjtHQVauXFnlvmPGjDHqeygqKhJTp04VISEhQqlUirvvvrvCaF1cXFy13+usWbNqvE5MTEy15zD2elV1a69pRMnY92rMmDHVxln+/1FdnDV9/7r9KlvCxJj3X4jbIzaVfX9fffWVaN26tVAoFKJFixZiyZIlQqvVVtgvKSlJPProo8Lb21t4enqKhx56yKiu6hxRIlPIhKjknlAiIiIHk5CQgGbNmmHZsmV48skn4e3trb+Tsbi4GPn5+fjwww+xcOFCpKenm70xKtknLmFCRET1yksvvYTAwED9FCYALF++HIGBgVi4cKEVIyNbxBElIiKqF4qLiw3q7zp06KBvR5CUlGRwd2tMTEyt1h8kx8FEiYiIiKgKnHojIiIiqgITJSIiIqIqMFEiIiIiqgIbTkqk1Wpx48YNeHl5Vbk0BREREdkWIQTy8vIQFhYGudz4cSImShLduHGjwmKgREREZB+SkpLQqFEjo/dnoiSRbsHFpKQkg8UfiYiIyHbl5uYiPDxc8sLJTJQk0k23eXt7M1EiIiKyM1LLZljMTURERFQFJkpEREREVWCiRERERFQFJkpEREREVWCiRERERFQFJkpEREREVWCiRERERFQFJkpEREREVWCiRERERFQFJkpEREREVWCiRERERFQFJkpEREREVWCiRES1VqTWWDsEIiKLYKJERLUSdy4N7WZvxZr9CdYOhYjI7JgoEVGtHL56ExqtwL8JN60dChGR2TFRIqJayS5SAwDyikusHAkRkfkxUSKiWskuLEuQ8opLrRwJEZH5MVEiolrJKSpLlHI5okREDoiJEhHVCkeUiMiRMVEiolq5XaPERImIHA8TJSKqlZxbI0r5qlJotMLK0RARmRcTJSIymUYrkFtuJCmfo0pE5GCYKBGRyXKLDAu4WdBNRI7GrhOlefPm4e6774aXlxeCgoIwfPhwnD9/vsbj1q1bh4iICLi6uqJ9+/bYvHlzHURL5HiymSgRkYOz60Rp586dmDx5Mv755x9s374dJSUl6N+/PwoKCqo8Zt++fRg5ciQmTJiAo0ePYvjw4Rg+fDhOnTpVh5ETOYbsQrXBcxZ0E5GjkQkhHKb6Mj09HUFBQdi5cyd69epV6T5PPPEECgoKsHHjRv22e+65B1FRUVi+fHmN18jNzYWPjw9ycnLg7e1tttiJ7FHc+TSMW/mv/vlXo7qgf2SIFSMiIqqcqb+/7XpE6U45OTkAAH9//yr32b9/P/r162ewbcCAAdi/f3+l+6tUKuTm5ho8iKiM7o43HY4oEZGjcZhESavV4tVXX8W9996Ldu3aVblfSkoKgoODDbYFBwcjJSWl0v3nzZsHHx8f/SM8PNyscRPZs4pTb6xRIiLH4jCJ0uTJk3Hq1Cn8/PPPZj3vjBkzkJOTo38kJSWZ9fxE9iynyHAEKZcjSkTkYJytHYA5vPjii9i4cSN27dqFRo0aVbtvSEgIUlNTDbalpqYiJKTyugqlUgmlUmm2WIkcia4rtw5HlIjI0dj1iJIQAi+++CJ+//13/P3332jWrFmNx0RHRyM2NtZg2/bt2xEdHW2pMIkclq5Gycu17G8u1igRkaOx60Rp8uTJ+P777/Hjjz/Cy8sLKSkpSElJQVFRkX6f0aNHY8aMGfrnr7zyCrZs2YKPPvoI586dw+zZs3Ho0CG8+OKL1vgWiOyaro9SuJ87APZRIiLHY9eJ0hdffIGcnBz07t0boaGh+scvv/yi3ycxMRHJycn65z169MCPP/6Ir776Ch07dsSvv/6KP/74o9oCcCKqnK6Yu7F/WaLEESUicjR2XaNkTAuoHTt2VNj22GOP4bHHHrNARET1i35Eyd8NQMUlTYiI7J1djygRkXXpapTCOaJERA6KiRIRmUQIUW5ESVejxESJiBwLEyUiMkmBWgONtmz6m8XcROSomCgRkUl0hdwKZzkCvcp6jalLtVCVaqwZFhGRWTFRIiKTZN+qT/J1c4GX0hkyWdl21ikRkSNhokREJsm5VZ/k6+4CuVwGT0XZTbS8842IHAkTJSIyye0RJQUAducmIsfERImITKJb583H3QUA4O1W9l8mSkTkSJgoEZFJytcoAbdHlHjnGxE5EiZKRGSS8jVKAODtqhtRYqJERI6DiRIRmUTXldvX3bBGKbeIU29E5DiYKBGRSXQ1St76qTeOKBGR42GiREQmubNGydtNV6PEESUichxMlIjIJHfWKOlGlFjMTUSOhIkSEZmEfZSIqD5gokREJtHVKPGuNyJyZEyUiEiy4hINiku0AG43nORdb0TkiJgoEZFkuvokJ7kMXsqyBEl/15uKI0pE5DiYKBGRZLpEycfNBTKZ7NbXrFEiIsfDRImIJNMVcvvcag0AlO+jVAohhFXiIiIyNyZKRCRZduGtBXHLJUq6Ym6NVqBQrbFKXERE5sZEiYgky76jhxIAuLrI4Swvm4ZjLyUichRMlIhIspw7unIDgEwmYy8lInI4TJSISLLbPZQUBtt1676xlxIROQomSkQkWWXF3AB7KRGR42GiRESSVVajBABeSq73RkSOhYkSEUmWW0Wi5M1eSkTkYJgoEZFkVU+9cUSJiBwLEyUikkxXzO3jdkcxd7mmk0REjoCJEhFJphtRqlCjpC/m5ogSETkGJkpEJEmpRqsfMfKt4q43jigRkaNgokREkuSWS4LurFFiHyUicjRMlIhIEt06b15KZzg7Gf4I8dZNvXFEiYgcBBMlIpJE10PJ5476JOD2XW8cUSIiR8FEiYgkyamihxLAu96IyPEwUSIiSXKq6KEE8K43InI8TJSISBJdjZLvHT2UgNuJUoFaA41W1GlcRESWwESJiCQxpkYJAPI5/UZEDoCJEhFJom82WcnUm8JZDleXsh8rXMaEiBwBEyUikqS6Ym7gdkE3EyUicgRMlIhIkupqlIDyBd2ceiMi+8dEiYgkqa5GCWAvJSJyLEyUiEgS/dRbJTVKQPllTDiiRET2j4kSEUmi76NU5YiSbhkTjigRkf1jokRERhNC6KfeqqpR0q33xhElInIETJSIyGj5qlJ9I8ma7npjjRIROQImSkRkNF0PJaWzHK4uTpXuw7veiMiRMFEiIqPV1EMJKHfXm4ojSkRk/5goEZHRbnflrrw+CQC83VijRESOg4kSERktu6is2WRVd7wBgJfyVmfuIo4oEZH9Y6JEREarqYcSwD5KRORYmCgRkdF0U28+1SRK7KNERI6EiRIRGc24Ym5dosQRJSKyf0yUiMho+gVx3asr5i5LotSlWhSXaOokLiIiS2GiRERGM2bqzVPhDJms7GvWKRGRvWOiRERGyzZi6k0ul8FToWsRwDolIrJvTJSIyGg5RvRRAnjnGxE5DmdTDvr3338RFxeHtLQ0aLVag9cWL15slsCIyPbo+ihVN6IE8M43InIckhOlDz74ADNnzkTr1q0RHBwMma4YATD4mogcj+6ut+pqlIDbiRJHlIjI3klOlD7++GN8++23GDt2rAXCISJbVVyiQXFJ2QhydZ25AcBbt94bR5SIyM5JrlGSy+W49957LRELEdkw3WiSk1wGL2X1f2Ppp96KOKJERPZNcqL02muv4bPPPrNELERkw8q3Bqhpmv12MTdHlIjIvkmeeps6dSoGDx6MFi1aoG3btnBxMRyCX79+vdmCIyLboW82WUN9EsDu3ETkOCQnSi+//DLi4uLQp08fBAQEsICbqJ7Q9VCqqT4JALxu1SjxrjcisneSE6XVq1fjt99+w+DBgy0RDxHZqNs9lGpOlG4Xc3NEiYjsm+QaJX9/f7Ro0cISsRCRDbvdQ6n6ZpNA+WJujigRkX2TnCjNnj0bs2bNQmFhoSXiISIbZWwPJYB9lIjIcUieevvkk08QHx+P4OBgNG3atEIx95EjR8wWHBHZDmMWxNXR3/Wm4ogSEdk3yYnS8OHDLRAGEdk6YxbE1fFmHyUichCSE6VZs2ZZIg6T7Nq1CwsXLsThw4eRnJyM33//vdpEbseOHejTp0+F7cnJyQgJCbFgpET2T1/MLeGut3xVKYQQvDuWiOyW5BolW1JQUICOHTtKboB5/vx5JCcn6x9BQUEWipDIceiLud1qLubW3fWm0QoUqjUWjYuIyJIkjyjJ5fJq/zrUaOruh+KgQYMwaNAgyccFBQXB19fX/AEROTB9jZIRI0quLnI4y2Uo1QrkFpfAo4YlT4iIbJXkn16///67wfOSkhIcPXoUq1evxpw5c8wWmCVFRUVBpVKhXbt2mD17NteuIzKClD5KMpkM3m4uyCpQI6+4FKE+lo6OiMgyJCdKw4YNq7Dt0UcfRWRkJH755RdMmDDBLIFZQmhoKJYvX46uXbtCpVLh66+/Ru/evXHgwAF07ty50mNUKhVUKpX+eW5ubl2FS2QzSjVa5KnKCrON6aMElLUIyCpQs5cSEdk1s42H33PPPXjuuefMdTqLaN26NVq3bq1/3qNHD8THx2PJkiVYs2ZNpcfMmzfPbkbKiCyl/JptujvaasJeSkTkCMxSzF1UVIRPPvkEDRs2NMfp6lS3bt1w6dKlKl+fMWMGcnJy9I+kpKQ6jI7INugWxPVSOsPZybgfG95c742IHIDkESU/Pz+DYm4hBPLy8uDu7o7vv//erMHVhWPHjiE0NLTK15VKJZRKZR1GRGR7pCyIq6NfxoQjSkRkxyQnSkuXLjV4LpfLERgYiO7du8PPz89ccRklPz/fYDToypUrOHbsGPz9/dG4cWPMmDED169fx3fffQegLPZmzZohMjISxcXF+Prrr/H3339j27ZtdRo3kb2R0kNJx0u/MC5HlIjIfklKlEpLS3H16lWMHz8ejRo1slRMRjt06JBBA8kpU6YAAMaMGYNVq1YhOTkZiYmJ+tfVajVef/11XL9+He7u7ujQoQP++uuvSptQEtFtUnoo6XjrEyWOKBGR/ZKUKDk7O2PhwoUYPXq0peKRpHfv3hBCVPn6qlWrDJ5PmzYN06ZNs3BURI5HSg8lHf3UG+96IyI7JrmYu2/fvti5c6clYiEiG5UtoYeSjn5hXI4oEZEdk1yjNGjQILz55ps4efIkunTpAg8PD4PXhw4darbgiMg25EhYEFfndnsAjigRkf2SnChNmjQJALB48eIKr8lksjpdwoSI6oYuUfKRMqLEu96IyAFITpS0Wq0l4iAiG6bro2RaMTdHlIjIfkmuUfruu+8MlvTQUavV+tvwicixmNZH6VbDySKOKBGR/ZKcKI0bNw45OTkVtufl5WHcuHFmCYqIbIuUBXF1WKNERI5AcqIkhDDozK1z7do1+PhwiXAiR5StL+aWMPV2K6kqUGtQquGUPRHZJ6NrlDp16gSZTAaZTIb7778fzs63D9VoNLhy5QoGDhxokSCJyHq0WnG7RsmEu94AIF9VKinJIiKyFUYnSsOHDwdQtjbagAED4OnpqX9NoVCgadOmeOSRR8weIBFZV766FNpbfV2l3PXm4iSHq4scxSVa5BUzUSIi+2R0ojRr1iwAQNOmTfHkk09yoViiekJXn+TqIoeri5OkY71dXVBcokIu65SIyE5JrlFq27Ytjh07VmH7gQMHcOjQIXPEREQ2xJQeSjq3lzHhnW9EZJ8kJ0qTJ09GUlJShe3Xr1/H5MmTzRIUEdmO28uXSJ86u72MCUeUiMg+SU6Uzpw5g86dO1fY3qlTJ5w5c8YsQRGR7cguKivkltJDScfLleu9EZF9k5woKZVKpKamVtienJxscCccETkGUxbE1dFPvXFEiYjslOREqX///pgxY4ZB08ns7Gz897//xQMPPGDW4IjI+kxZEFfHmyNKRGTnJA8BLVq0CL169UKTJk3QqVMnAGUtA4KDg7FmzRqzB0hE1nW7h5IJNUr6Ym6OKBGRfZKcKDVs2BAnTpzADz/8gOPHj8PNzQ3jxo3DyJEj4eIi/S9OIrJtuqm32tz1xhElIrJXJhUVeXh44LnnnjN3LERkg7JrM/Wmu+tNxRElIrJPkmuUAGDNmjW47777EBYWhqtXrwIAlixZgj///NOswRGR9bGPEhHVZ5ITpS+++AJTpkzBoEGDcPPmTWg0GgCAn58fli5dau74iMjKcmrRR8lLyT5KRGTfJCdKy5Ytw4oVK/DWW28ZtAPo2rUrTp48adbgiMj6dH2UajX1xholIrJTkhOlK1eu6O92K0+pVKKgoMAsQRGR7TBHMTf7KBGRvZKcKDVr1qzStd62bNmCNm3amCMmIrIRxSUaqEq1AGo3opTLESUislOS73qbMmUKJk+ejOLiYgghcPDgQfz000+YN28evv76a0vESERWohtNcpLL4KmUfpOsbkRJXapFcYkGri5OZo2PiMjSJP/kmzhxItzc3DBz5kwUFhbiqaeeQlhYGD7++GM8+eSTloiRiKxEX5/k5gKZTCb5eE+FM2QyQIiyOiUmSkRkb0zqo/T000/j6aefRmFhIfLz8xEUFGTuuIjIBujrk0yYdgMA+a2RqLziUuQVlyDQS2nO8IiILM7kVWzT0tJw/vx5AIBMJkNgYKDZgiIi21CbHko63q4uyCsuZZ0SEdklycXceXl5GDVqFMLCwhATE4OYmBiEhYXhmWeeMVgol4js3+0eSqYnSreXMeGdb0RkfyQnShMnTsSBAwewadMmZGdnIzs7Gxs3bsShQ4fw/PPPWyJGIrKS2z2UpDeb1PF2ZS8lIrJfkqfeNm7ciK1bt+K+++7TbxswYABWrFiBgQMHmjU4IrKu2vRQ0rm9jAlHlIjI/kgeUQoICICPj0+F7T4+PvDz8zNLUERkG2qzIK7O7ak3jigRkf2RnCjNnDkTU6ZMQUpKin5bSkoK3njjDbz99ttmDY6IrMscNUq3lzHhiBIR2R/JU29ffPEFLl26hMaNG6Nx48YAgMTERCiVSqSnp+PLL7/U73vkyBHzRUpEdc4cNUq3lzHhiBIR2R/JidLw4cMtEAYR2aLa9lECbhdzc703IrJHkhOlWbNmWSIOIrJB5uij5MW73ojIjkmuUUpKSsK1a9f0zw8ePIhXX30VX331lVkDIyLrM2cfJd71RkT2SHKi9NRTTyEuLg5AWRF3v379cPDgQbz11luYO3eu2QMkIuso0WiRpyobBapVHyU3jigRkf2SnCidOnUK3bp1AwCsXbsW7du3x759+/DDDz9g1apV5o6PiKyk/AiQt6vJqx2VK+bmiBIR2R/JP/1KSkqgVJYtbPnXX39h6NChAICIiAgkJydXe2xubq7kAL29vSUfQ0S1l1lQdsebl9IZzk6S/6bS82YfJSKyY5ITpcjISCxfvhyDBw/G9u3b8e677wIAbty4gYCAgGqP9fX1hUwmM/paMpkMFy5cQPPmzaWGSUS1tOdiBgCgTWjt/li5vYRJCYQQkn4GEBFZm+REacGCBRgxYgQWLlyIMWPGoGPHjgCADRs26KfkqvPrr7/C39+/xv2EEHjwwQelhkdEZrL1dFlT2f6RwbU6j+6uN60ACtQaeCpNn8YjIqprkn9i9e7dGxkZGcjNzTVYsuS5556Du7t7tcc2adIEvXr1qnHkSad58+ZwcTH9bhsiMk1mvgr/JmQBAAZEhtTqXK4ucrg4yVCiEcgrLmGiRER2xaSfWE5OThXWdWvatGmNx125ckXSdU6dOiVpfyIyj9hzadAKoG2oN8L9q/8DqCYymQxeri7IKlAjr7gUoRWXiiQislmmV2jWUmJiIlQqVYXtWq0WiYmJVoiIiHS23Zp2q+1okg57KRGRvbJaotS0aVN07twZ8fHxBtvT09PRrFkzK0VFRAWqUuy6Vcg9oF3t6pN0vNmdm4jslNUSJQBo06YNunXrhtjYWIPtQggrRUREOy+kQ12qRZMAd7QO9jLLOdlLiYjsldUSJZlMhs8//xwzZ87E4MGD8cknnxi8RkTWsbXctJu5/i3eTpQ4okRE9sWoYu7ySUxNXn75ZaP2040avfbaa4iIiMDIkSNx8uRJvPPOO0Zfi4jMS12qxd/n0gAAA2rZFqC88r2UiIjsiVGJ0pIlS4w6mUwmMzpRKm/QoEHYt28fhg4dioMHD0o+nojMY//lTOQVl6KBpxKdwv1qPsBIul5KuUUcUSIi+2JUoiT1tn5jxMTEQKG4vdBm27ZtceDAATz88MOsUSKyEt202wNtgyGXm28K3Eu/jAlHlIjIvlit81tcXFyFbQEBAdi5c6cVoiEirVZg+5lUAOaddgMAbzfe9UZE9smkROnatWvYsGEDEhMToVarDV5bvHhxtccauzAuF8MlqltHk7KRnqeCl9IZPVo0MOu5edcbEdkryYlSbGwshg4diubNm+PcuXNo164dEhISIIRA586dazy+poVxdYtmajQaqaERUS3omkz2iQiCwtm8N8SyjxIR2SvJidKMGTMwdepUzJkzB15eXvjtt98QFBSEp59+GgMHDqzx+PJTbrqFb7/++ms0bNhQaihEZCZCCIO2AObmzRolIrJTkhOls2fP4qeffio72NkZRUVF8PT0xNy5czFs2DD85z//qfb4mJgYg+dOTk6455570Lx5c6mhEJGZXEjNR0JmIRTOcvRuHWj28/OuNyKyV5LH1z08PPR1SaGhoQZLkGRkZJgvMiKqM7rRpJ4tG8BDaf57PLzdOKJERPZJ8k/Ee+65B3v27EGbNm3w4IMP4vXXX8fJkyexfv163HPPPZaIkYgsTJco9Tfz3W46uhGlArUGpRotnJ2sunoSEZHRJCdKixcvRn5+PgBgzpw5yM/Pxy+//IJWrVrVeMdbVbhkCZH1JGUV4vSNXMhlQL82lkqUbv+oyVeVwtddUc3eRES2Q3KiVL6WyMPDA8uXL5d0/MMPP2zwvLi4GC+88AI8PDwMtq9fv15qaERkgm23eid1beqPAE+lRa7h4iSHm4sTiko0yCtmokRE9sPkYgS1Wo20tDRotVqD7Y0bN672OG9vb4MRpGeeecbUEIjIDCx5t1t5Xq7OKCrRIKeoBOEWvRIRkflITpQuXLiACRMmYN++fQbbje1/tGrVKqmXJCILycxX4VBCFgCgf1vLTLvpeLk6Iy1PxV5KRGRXJCdK48aNg7OzMzZu3IjQ0FDJ9UWNGzfG0KFDMWzYMPTp0wfOzlZbRYWo3os9mwatACLDvBHu727Ra5VNtxUgs0Bl0esQEZmT5Czl2LFjOHz4MCIiIky64Jo1a7BhwwZMmjQJ6enpGDBgAIYOHYrBgwfD19fXpHMSkWnqatoNAFoEeuDw1Zu4kJpv8WsREZmL5Ht027ZtW6t+STExMfjoo49w8eJF7N27F1FRUVi2bBlCQkLQt29fLF26FJcvXzb5/ERknHxVKXZfKvu3XBeJUuuQsvUbzyUbt94jEZEtkJwoLViwANOmTcOOHTuQmZmJ3Nxcg4cUkZGRmDFjBv755x8kJCRg5MiRiI2NRbt27dCuXTts2rRJanhEZKSd59OhLtWiSYA77gr2tPj1IkK8AADnU/Msfi0iInORPPXWr18/AMD9999vsL22i9mGhITg2WefxbPPPouCggJs27YNSqVlblUmIsNpt7roZaZLlBKzClGoLoW7gvWJRGT7JP+kKr+oraV4eHhgxIgRFr8OUX2lLtUi7lwaAGCAhbpx3ynAU4kGnkpk5KtwITUfUeG+dXJdIqLakJwo3bmorVQlJSV46623sH79evj7++OFF17A+PHj9a+npqYiLCzM5JEpIqrZvvgM5KlKEeilRKdwvzq7bkSIF/ZcUuF8Si4TJSKyCyaNfWdnZ+Obb77B2bNnAZTVGo0fPx4+Pj41Hvv+++/ju+++w9SpU5GdnY0pU6bgwIED+PLLL/X7CCFMCYuIjKTrxv1A22DI5XW3hFDrEC/suZSBs8msUyIi+yC5mPvQoUNo0aIFlixZgqysLGRlZWHx4sVo0aIFjhw5UuPxP/zwA77++mtMnToV7733Hg4dOoS///4b48aN0ydIXPuNyLL23brb7QELN5m8U2tdQXcKEyUisg+SE6XXXnsNQ4cORUJCAtavX4/169fjypUreOihh/Dqq6/WePz169fRrl07/fOWLVtix44d2LdvH0aNGiVpym3Xrl0YMmQIwsLCIJPJ8Mcff9R4zI4dO9C5c2colUq0bNmSncKpXkrLK2v62CzAo4Y9zavNrRYB51PzOHJMRHbBpBGl6dOnG3TUdnZ2xrRp03Do0KEajw8JCUF8fLzBtoYNGyIuLg7//vsvxo4da3QsBQUF6NixIz777DOj9r9y5QoGDx6MPn364NixY3j11VcxceJEbN261ehrEtm74hINCtVlf5D4e9bt4rStgj0hlwFZBWqk57NDNxHZPsk1St7e3khMTKzQmTspKQleXl41Ht+3b1/8+OOPFdoLhIWF4e+//0bv3r2NjmXQoEEYNGiQ0fsvX74czZo1w0cffQQAaNOmDfbs2YMlS5ZgwIABRp+HyJ5lFqgBAC5OMngp6/YWfVcXJzQN8MDljAKcT8lDkJdrnV6fiEgqySNKTzzxBCZMmIBffvkFSUlJSEpKws8//4yJEydi5MiRNR7/9ttv4/HHH6/0tYYNG2Lnzp349ttvpYZllP379+v7QOkMGDAA+/fvr/IYlUpVq6aaRLYmK78sUfL3UFilHlBXp3SOBd1EZAck/zm5aNEiyGQyjB49GqWlZauAu7i44D//+Q/mz59f4/FNmjRBkyZNqnw9LCwMY8aMkRqWUVJSUhAcbFi8GhwcjNzcXBQVFcHNza3CMfPmzcOcOXMsEg+RNegWpfX3sE5D19YhXvi/Uyk4x4JuIrIDkkeUFAoFPv74Y9y8eRPHjh3DsWPHkJWVhSVLlkjqpG0vhZwzZsxATk6O/pGUlGTtkIhqJevW1FuAR93WJ+lE6Au6OTpLRLbP5AIFd3d3tG/f3qRj1Wo1nnrqKfz666+mXt4kISEhSE1NNdiWmpoKb2/vSkeTAECpVHIpFXIoukTJ32qJUtnU28XUfGi0Ak512MeJiEgqoxKlhx9+GKtWrYK3tzcefvjhavddv359ta/n5+dj2LBhRhV+m1t0dDQ2b95ssG379u2Ijo6u81iIrCXTyolSY393uLk4oahEg4TMArQItPyCvEREpjJq6s3Hx0df9Ont7Q0fH58qH9XJyMhATEwMnJycsG7duloHn5+fr5/+A8pu/z927BgSExMBlE2bjR49Wr//Cy+8gMuXL2PatGk4d+4cPv/8c6xduxavvfZarWMhshe6Ym5rTb3J5TLcFVyWHLHxJBHZOqNGlFauXKn/ujYNGu+77z4EBQXhjz/+gIuLi8nn0Tl06BD69Omjfz5lyhQAwJgxY7Bq1SokJyfrkyYAaNasGTZt2oTXXnsNH3/8MRo1aoSvv/6arQGoXtGNKAV4Wm9KuXWIF45fy8G55Fw82D7UanEQEdVEco1S3759sX79evj6+hpsz83NxfDhw/H3339XeWx8fDxGjx4Nd3d3yYFWpnfv3tUWhVeW1PXu3RtHjx41y/WJ7NHtu96sM6IE3C7o5p1vRGTrJCdKO3bsgFqtrrC9uLgYu3fvrvbYtWvX4umnn0ZgYCCeffZZqZcmIjPQ3/VWx125y9MVdJ9PZaJERLbN6ETpxIkT+q/PnDmDlJQU/XONRoMtW7agYcOG1Z5jxIgR2LRpEx5++GF4eHjgqaeeMiFkIqqN8g0nrUXXdDIxqxCF6lK4K+q2QzgRkbGM/ukUFRUFmUwGmUyGvn37Vnjdzc0Ny5Ytq/E8ffr0wV9//YWhQ4cyUSKqY6pSDfJUZY1irVXMDZTVRzXwVCIjX4ULqfmICve1WixERNUxOlG6cuUKhBBo3rw5Dh48iMDAQP1rCoUCQUFBcHJyMupcXbp0QVxcnPRoiahWbhaUAACc5DJ4u9b+horaiAjxwp5LKpxLzmWiREQ2y+hESbfsiFarNcuF77rrLrOch4iMpyvk9nNXQG7lRo9liVIGC7qJyKaZXBhw5swZJCYmVijsHjp0aK2DIiLLsPbyJeXp6pTYS4mIbJnkROny5csYMWIETp48CZlMpr89X9eQUqPRGHWe4uJiLFu2DHFxcUhLS6swUnXkyBGpoRFRDay9fEl5t9d8y4MQQv8zhIjIlkhOlF555RU0a9YMsbGxaNasGQ4ePIjMzEy8/vrrWLRokdHnmTBhArZt24ZHH30U3bp14w9JojqQqbvjzYqtAXRaBXtCLitL3tLzVQjycrV2SEREFUhOlPbv34+///4bDRo0gFwuh1wux3333Yd58+bh5ZdfNrqZ48aNG7F582bce++9koMmItPY0tSbq4sTmjbwwOX0ApxLzmOiREQ2yai13srTaDT6BW0bNGiAGzduACgr9j5//rzR52nYsKFVFsYlqs+svSDunSJYp0RENk5yotSuXTscP34cANC9e3d8+OGH2Lt3L+bOnYvmzZsbfZ6PPvoI06dPx9WrV6WGQEQmyrp115stjCgBQOtgLmVCRLZN8tTbzJkzUVBQAACYO3cuHnroIfTs2RMBAQH45ZdfjD5P165dUVxcjObNm8Pd3b3CIrlZWVlSQyOiGtwu5rbegrjl6e98S821ciRERJWTnCgNGDBA/3XLli1x7tw5ZGVlwc/PT1JB9siRI3H9+nV88MEHCA4OZjE3UR2w1am3i6n5KNVo4ewkeZCbiMiiJCdKOTk50Gg08Pf312/z9/dHVlYWnJ2d4e3tbdR59u3bh/3796Njx45SQyAiE9nCgrjlNfZ3h5uLE4pKNEjILETLIE9rh0REZEDyn29PPvkkfv755wrb165diyeffNLo80RERKCoqEjq5YnIRKUaLbILy5YwsZURJblchrtY0E1ENkxyonTgwAH06dOnwvbevXvjwIEDRp9n/vz5eP3117Fjxw5kZmYiNzfX4EFE5nXzVpIkk5UtYWIrIoJ1iRL/3ROR7ZE89aZSqVBaWlphe0lJiaQRooEDBwIA7r//foPtug69xnb4JiLj6KbdfN1c4GTldd7K0xV08843IrJFkhOlbt264auvvsKyZcsMti9fvhxdunQx+jxxcXFSL01EtaBbENdWpt109L2UUpkoEZHtkZwovffee+jXrx+OHz+uHw2KjY3Fv//+i23btlV77IkTJ9CuXTvI5XLExMTUeK3Tp0+jdevWcHY2ee1eIrpFt3xJgKdttAbQ0Y0oXc0sRIGqFB5K/nsnItshuUbp3nvvxf79+9GoUSOsXbsW//vf/9CyZUucOHECPXv2rPbYTp06ITMz0+hrRUdHIzExUWqIRFQJW1q+pLwATyUCvcqStwscVSIiG2PSn25RUVH48ccfJR8nhMDbb78Nd3d3o/ZXq9WSr0FElbO1HkrlRYR4IT1PhfMpeejU2M/a4RAR6ZmUKMXHx2PlypW4fPkyli5diqCgIPzf//0fGjdujMjIyCqP69Wrl6T14KKjo+Hm5mZKiER0B1tbvqS81sFe2H0xgwXdRGRzJCdKO3fuxKBBg3Dvvfdi165deO+99xAUFITjx4/jm2++wa+//lrlsTt27KhNrERUC1k2PKLUmr2UiMhGSa5RevPNN/Hee+9h+/btUChu/8Dt27cv/vnnH7MGR0Tmoyvm9rexYm4AaBOqWxw3F0IIK0dDRHSb5ETp5MmTGDFiRIXtQUFByMjIMEtQRGR+tlrMDQAtgzwhl5U1xUzPU1k7HCIiPcmJkq+vL5KTkytsP3r0KBo2bGiWoIjI/Gx56s3VxQlNG3gAYONJIrItJq31Nn36dKSkpEAmk0Gr1WLv3r2YOnUqRo8ebYkYiaiWtFqBm4W2O6IElGs8yUSJiGyI5ETpgw8+QEREBMLDw5Gfn4+2bduiV69e6NGjB2bOnGmJGImolrKLSqC9VfrjZ6OJUutgXZ0SEyUish2S7noTQiAlJQWffPIJ3nnnHZw8eRL5+fno1KkTWrVqZakYiaiWdK0BvF2d4eIk+e+jOhERqlvzjYvjEpHtkJwotWzZEqdPn0arVq0QHh5uqbiIyIxsdfmS8nRTbxfT8lGq0cLZRhM6IqpfJP0kksvlaNWqlaRlSIjI+my5kFsn3M8d7gonqEu1SMgstHY4REQATKhRmj9/Pt544w2cOnXKEvEQkQXY8vIlOnK5DK2CWdBNRLZFcmfu0aNHo7CwEB07doRCoaiwxEhWVpbZgiMi87DlHkrlRQR74XhSNs6n5GJwh1Brh0NEJD1RWrp0qQXCICJLsoepN+B2QfdZjigRkY2QnCiNGTPGEnEQkQXZw9QbwDXfiMj2GJUo5ebmwtvbW/91dXT7EZHt0LUHCPC07USpbag35DIgMasQ++MzEd0iwNohEVE9Z1Qxt5+fH9LS0gCULWHi5+dX4aHbTkS2R78grofttgcAAF93BZ7u3gQAMGvDKZRotFaOiIjqO6NGlP7++2/4+/sDAOLi4iwaEBGZn70UcwPA1P6tselkMi6k5mP1vgRM7Nnc2iERUT1mVKIUExNT6ddEZPuEELcTJRufegMAH3cXvDkwAtN+O4El2y9gSMcwBHu7WjssIqqnjEqUTpw4YfQJO3ToYHIwRGR+uUWlKL210JutF3PrPNqlEX76NxFHE7Pxweaz+PjJTtYOiYjqKaMSpaioKMhkMgghIJPJqt1Xo9GYJTAiMo/MW4XcnkpnKJ2drByNceRyGd4d1g5DPt2DP4/dwJN3N2ZhNxFZhVHF3FeuXMHly5dx5coV/Pbbb2jWrBk+//xzHD16FEePHsXnn3+OFi1a4LfffrN0vEQkkb30ULpTu4Y+eOZWYfc7f7Kwm4isw6gRpSZNmui/fuyxx/DJJ5/gwQcf1G/r0KEDwsPD8fbbb2P48OFmD5KITGcvPZQqoyvsvpjGwm4isg7Ja72dPHkSzZo1q7C9WbNmOHPmjFmCIiLzsac73u6kK+wGgCXbLyA1t9jKERFRfSM5UWrTpg3mzZsHtVqt36ZWqzFv3jy0adPGrMERUe3Z69SbzqNdGqFTY18UqDV4f9NZa4dDRPWM5CVMli9fjiFDhqBRo0b6O9xOnDgBmUyG//3vf2YPkIhqR99s0g5aA1SmfGH3huM3MLIbC7uJqO5IHlHq1q0bLl++jPfeew8dOnRAhw4d8P777+Py5cvo1q2bJWIkolrQL19ipyNKAAu7ich6JI8oAYCHhweee+45c8dCRBZwu5jbtpcvqUn5wu5VexPwbC8WdhOR5RmVKG3YsAGDBg2Ci4sLNmzYUO2+Q4cONUtgRGQe9lzMXV75jt1L/7qAoVHs2E1ElmdUojR8+HCkpKQgKCio2tv/ZTIZG04S2Rh7L+Yur3zH7vc3ncUnI9mxm4gsy6gaJa1Wi6CgIP3XVT2YJBHZFiGEXfdRupOusFsmAzYcv4F98RnWDomIHJzkYm4ish8Fag3UpWWFz/awIK4x2jX0wdPdGwMAvtp12crREJGjM6mYOzY2FrGxsUhLS4NWa3j3ybfffmuWwIio9rJutQZwdZHDXWHSP3eb9HjXcHz/T9kUnDFrUBIRmUryiNKcOXPQv39/xMbGIiMjAzdv3jR4EJHtyNS3BrDvO97uFBHiDYWzHDlFJbiSUWDtcIjIgZnUcHLVqlUYNWqUJeIhIjNypELu8hTOckSGeeNoYjaOX8tG80BPa4dERA5K8oiSWq1Gjx49LBELEZmZIxVy3ykq3BcAcCwx26pxEJFjk5woTZw4ET/++KMlYiEiM3OUHkqV0SdKSdlWjYOIHJvkqbfi4mJ89dVX+Ouvv9ChQwe4uLgYvL548WKzBUdEtZOZf6tGyUHueCuvU7gfAOBMci6KSzRwdXGyckRE5IgkJ0onTpxAVFQUAODUqVMGr/HOEyLb4ijLl1Qm3N8N/h4KZBWocSY5F50b+1k7JCJyQJITpbi4OEvEQUQW4MhTbzKZDFHhvvj7XBqOJWYzUSIii2DDSSIH5qh3vemwTomILM2kGqVly5YhLi6u0oaTR44cMVtwRFQ7mbcaTvo7YI0SwESJiCxPcqI0YcIEbNu2DY8++ii6devGuiQiG+bIU28A0LGRLwAgMasQWQVqhx05IyLrkZwobdy4EZs3b8a9995riXiIyEyK1BoUlZQtVO2oCYSPuwuaN/DA5YwCHE/KRp+IIGuHREQORnKNUsOGDeHl5WWJWIjIjHTLlyic5PBUOs46b3fSTb8d5fQbEVmA5ETpo48+wvTp03H16lVLxENEZlK+kNuRp8ijGvsCYJ0SEVmG5D8zu3btiuLiYjRv3hzu7u4VGk5mZWWZLTgiMp0jL19Snm5E6XhSNoQQDp0UElHdk5wojRw5EtevX8cHH3yA4OBg/lAislFZt+54c8Su3OVFhHhD4SxHTlEJrmQUcIFcIjIryYnSvn37sH//fnTs2NES8RCRmTh6DyUdhbMc7cK8cSQxG8eSspkoEZFZSa5RioiIQFFRkSViISIzqi9TbwAQdWvdN9YpEZG5SU6U5s+fj9dffx07duxAZmYmcnNzDR7W8Nlnn6Fp06ZwdXVF9+7dcfDgwSr3XbVqFWQymcHD1dW1DqMlqhtZt+56c9QeSuWxoJuILEXy1NvAgQMBAPfff7/Bdl0RpUajMU9kRvrll18wZcoULF++HN27d8fSpUsxYMAAnD9/HkFBlfdU8fb2xvnz5/XPWWdFjijLgRfEvVOnWwXdZ5NzUVyigauLk3UDIiKHYfeL4i5evBjPPvssxo0bBwBYvnw5Nm3ahG+//RZvvvlmpcfIZDKEhITUZZhEda4+Tb018nNDgIcCmQVqnEnO5QK5RGQ2khOlmJgYS8RhErVajcOHD2PGjBn6bXK5HP369cP+/furPC4/Px9NmjSBVqtF586d8cEHHyAyMrLSfVUqFVQqlf65taYXiaTSL1/i4He9AWV//ESF+yL2XBqOJWYzUSIis5FcowQA2dnZ+OijjzBx4kRMnDgRS5YsQU5Ojrljq1FGRgY0Gg2Cg4MNtgcHByMlJaXSY1q3bo1vv/0Wf/75J77//ntotVr06NED165dq3T/efPmwcfHR/8IDw83+/dBZAm69gD1YUQJADpygVwisgDJidKhQ4fQokULLFmyBFlZWcjKysLixYvRokULHDlyxBIxmlV0dDRGjx6NqKgoxMTEYP369QgMDMSXX35Z6f4zZsxATk6O/pGUlFTHERNJpyrVIE9VCqB+FHMDtxtPMlEiInOSPPX22muvYejQoVixYgWcncsOLy0txcSJE/Hqq69i165dZg+yKg0aNICTkxNSU1MNtqemphpdg+Ti4oJOnTrh0qVLlb6uVCqhVDp+MSw5Ft20m7NcBm9Xlxr2dgy6EaXErEJk5qsQ4Ml/t0RUeyaNKE2fPl2fJAGAs7Mzpk2bhkOHDpk1uJooFAp06dIFsbGx+m1arRaxsbGIjo426hwajQYnT55EaGiopcIkqnOZt6bd/DwUkMvrx12dPm4uaB7oAQA4fi3busEQkcOQnCh5e3sjMTGxwvakpCR4eXmZJSgppkyZghUrVmD16tU4e/Ys/vOf/6CgoEB/F9zo0aMNir3nzp2Lbdu24fLlyzhy5AieeeYZXL16FRMnTqzz2IksRV/IXU+m3XT002+J2VaNg4gch+SptyeeeAITJkzAokWL0KNHDwDA3r178cYbb2DkyJFmD9CYeNLT0/HOO+8gJSUFUVFR2LJli77AOzExEXL57Xzw5s2bePbZZ5GSkgI/Pz906dIF+/btQ9u2bes8diJLqS/Ll9ypU7gv1h+5jmPX6v7mEiJyTJITpUWLFkEmk2H06NEoLS0rFnVxccF//vMfzJ8/3+wBGuPFF1/Eiy++WOlrO3bsMHi+ZMkSLFmypA6iIrKe+tRDqTzdUibHk7L1TXCJiGpDcqKkUCjw8ccfY968eYiPjwcAtGjRAu7u7mYPjohMU5+WLykvItQLSmc5copKcCWjgAvkElGtmdRHCQDc3d3Rvn17tG/fnkkSkY2pT8uXlOfiJEe7hj4A2CaAiMzD5ESJiGyX7q43/3rQlftO7KdERObERInIAdXXu94AdugmIvNiokTkgOrrXW9A2Z1vAHA2ORfFJRrrBkNEdo+JEpEDyqzHI0qN/NwQ4KFAiUbg9A0uYk1EtcNEicjBlGi0yCkqAVA/R5RkMhnrlIjIbJgoETmYm4Vlo0kyGeDrXv8SJeB2QfdxJkpEVEtMlIgcjK4+yc9dAad6ss7bnaIa+wLgiBIR1R4TJSIHk5Vffwu5dTo08gUAJGYVIjNfZd1giMiuMVEicjD1dfmS8nzcXNAi0AMAcPxatnWDISK7xkSJyMHU5x5K5enWfTuWmG3dQIjIrjFRInIwHFEqo6tTOso6JSKqBSZKRA6mvi6Ie6eoW3VKx5OyodUK6wZDRHaLiRKRg8lkMTcAICLUC0pnOXKLS3Els8Da4RCRnWKiRORg9F25PZVWjsS6XJzkaNfQBwCwZPsFLmdCRCZhokTkYFjMfduzPZvDSS7DxhPJGLniH6TnsVUAEUnDRInIwegXxPVkojSwXQhWj+sGb1dnHE3MxrBP9+BMLdZ/02oFhGC9E1F94mztAIjIfDRaoV/CpL7XKOnc16oB/ph8LyauPoTLGQV4dPk+LHkiCgMiQ4w+R0a+Cl/tuowf/rkKJ7kMrYK9cFewJ1oFeaFVsCfuCvZCkJcSMln97IRO5MiYKBE5kOxCNXQDHn71dJ23yjQP9MTvk+7F5B+PYM+lDLzw/WFM7d8ak3q3qDa50SVI3+1PQHGJVr/98NWbOHz1psG+3q7O+gSqQyNfPNalEZydOGhPZO+YKBE5EN20m4+bC1z4S9qAj7sLVo27G+9uPIPV+69i4dbzuJSWj3kPt4eri5PBvpUlSB3DffHK/S0R6uOGC6l5uJSWjwupebiYmo+EzALkFpfqE6ifDibhfEoeZg+NtMa3SkRmxESJyIFkspC7Ws5OcswZ1g4tg70we8Np/H70OhIyC/DVqK4I9FJWmSC92q8Vet8VqB99ahPqbXBeVakGl9MLcDEtH8eTsvHNniv4/p+rGNujKZo28Kjz75OIzIeJEpEDyWJXbqOMuqcJmjfwwKQfjuiLvPtHhuDnfxOrTZCqonR2QptQb7QJ9cbQjmGIT8/HjvPpWLj1PD57unNdfEtEZCEcmydyIFy+xHj3tiwr8m7ewAM3coqxal/ZKFLHcF+sHHc3/pjUA31aB5lUoP3moAjIZMCmk8k4mniz5gOIyGYxUSJyIFn5umaTTJSM0ayBB36fdC8Gtw/FPc39a50g6USEeOORzo0AAPP+7xxbChDZMU69ETmQhFtLdQTW867cUvi4u1hkemzKA3fhf8dv4OCVLMSeTUO/tsFmvwYRWR5HlIgcRIlGi7/PpQEom1Yi6wrzdcP4+5oBABZsOYdSjbaGIypKyirEkGV78Ma64yYdT0S1x0SJyEEcvJKFnKISBHgo0LWpv7XDIQAvxLSAr7sLLqbl49fD1yQdm1NUgrErD+Lk9RysO3wNczee4RQekRUwUSJyEFtPpwAA+rUJhpOcHaJtgY+bC17q2woAsHj7BRSqS406Tl2qxX++P4z49AL4eyggkwHf7b+KlXsTLBgtEVWGiRKRA9BqBbadTgUADGjHWhhb8sw9jRHu74a0PBW+2X2lxv2FEJj5x0nsi8+Eh8IJ30/ojjcHRgAA3t10BtvPpFo6ZCIqh4kSkQM4cT0HKbnF8FA4oUcL1ifZEqWzE6b2bw0A+HLXZWTkq6rd/4ud8Vh76BrkMuDTpzqjbZg3nuvVHCO7NYYQwMs/HcWp6zl1EToRgYkSkUPQTbv1bh1UYTkOsr4hHcLQvqEP8lWlWBZ7scr9Np64gQ+3nAcAzB4aiT4RQQAAmUyGucMi0bNVAxSVaDB+1b+4kV1UJ7ET1XdMlIgcgC5R6h/JaTdbJJfLMOPBsumzHw4k4kpGQYV9Dl+9iSlrjwMAxt/bDKOjmxq87uIkx2dPd8ZdwZ5Iy1Nh/Kp/ka8yruaJiEzHRInIzl1Ky8Pl9AK4OMn0IxBke3q0aIDerQNRqhVYtPW8wWuJmYV47rtDUJdq0a9NMN4a3KbSc3i7uuDbsXejgacS51Ly8NKPR9g2gMjCmCgR2bmtt4q4e7RoAG9XFytHQ9WpbGmTnMISjFt1EJkFarRr6I2Pn4yq9q7FRn7u+GZMV7i6yBF3Pp1tA4gsjIkSkZ3bdmvabUBkiJUjoZpEhHjjUd3SJpvPlbUB+KGsDUCojyu+GXM3PJQ1L5jQMdwXS5/oxLYBRHWAiRKRHUvOKcLxazmQyYAHuESGXZjS/y4oneU4mJCFx7/cr28D8M2YuxHs7Wr0eQa2C8GMQWwbQGRpTJSI7Jiud1KXxn4I9OL6bvYg1Of20ibHkrIN2gBI9WzP5niq++22AadvsG0AkbkxUSKyY1s57WaX/tO7Bfw9FACAOeXaAEglk8kwd+jttgFLtl8wZ5hEBCZKRHbrZoEaB65kAWBbAHvj7eqCtc/fg9Xju2HUHW0ApHJ2kmPWkLYAgLjz6UjPq76hJRFJw0SJyE7FnkuDRisQEeKFJgEe1g6HJGoZ5IWYuwLNdq6ocF9otAJ/HrtulnMSURkmSkR26naTSU67EfBol7K76X49fI3tAojMiIkSkR0qUmuw+2I6AGAAp90IZcukKJzlOJeSh9M3cq0dDpHDYKJEZId2XkhHcYkWjfzc0DZU+t1S5Hh83F3Q/1aLiF8PX7NyNESOg4kSkR0q32RSJqu6izPVL7rptz+PXYe6lEubEJkDEyUiO1Oi0eKvs2X9k9gWgMrr2SoQwd5K3Cwswd/n0qwdDpFDYKJEZGcOXM5CbnEpAjwU6NLEz9rhkA1xksswotPtom4iqj0mSkR2Rne32wNtg6tdPJXqp0e7NAQAxJ1PY08lIjNgokRkR7RagW1ndG0BeLcbVcSeSkTmxUSJyI4cv5aN1FwVPBRO6NGigbXDIRvFnkpE5sNEiciObLu1QnzviCC4ujhZORqyVfbWU0mjFVi09Txm/XkKyTlF1g6HyAATJSI7wkVwyRg+7i76/0dsvahboxV4fe0xfBp3Cav3X0WfRTvw0bbzyFeVWjs0IgBMlIjsxqW0PFxOL4DCSY4+rc2zRhg5Lt302x/HrkNVqrFyNJXTJUl/HLsBZ7kM7Rv6oLhEi2V/X0LvhXH44cBVlGrYD4qsi4kSkZ3Yerps2q1HywB4ubpYORqydfe1bIBgbyWyC0sQZ4M9le5Mkj59qhM2vHgvlj/TBU0D3JGRr8Zbv5/CoI93I+5cGmutyGqYKBHZCU67kRROchke7mybPZUqS5IGtguFTCbDwHYh2PZaDGYNaQtfdxdcTMvHuFX/4plvDuD0jRxrh071EBMlIjtwOT0fJ67lQCYD+rVhWwAyziO3EqW48+k201OpqiSpPIWzHOPubYadb/TB872aQ+Ekx95LmXho2R5MXXecBd9Up5goEdm4nKISPL/mMICy6ZRAL6WVIyJ70TLIE50aS++pdD27CKeu56BIbd7aJmOSpPJ83Fww48E2iH09BkM7hkGIstExFnxTXZIJTvxKkpubCx8fH+Tk5MDbm6u2k2WVaLQYu/Ig9l7KRIi3K/6YfC9CfFytHRbZkR8OXMVbv59C62AvbHm1Z7WLKBeXaLD0r4v4alc8tAKQyYBwP3fcFeyJVsFeaBXkibuCvdAi0BNuCmntKaQmSZU5lpSN9zedwb8JNwEADTwVeO2Bu/BE13A4O/Hvfqqeqb+/mShJxESJ6ooQAm/+dhK/HEqCu8IJ616IRmSYj7XDIjuTU1SCu9//C+pSLTa+dB/aNaz8/6FjSdmYuu44LqXlAwC8XZ2RW1z5iE35BKplkFdZIhXkhZZBlSdQ5kiSdIQQ2Ho6FfP/7ywSMgsBlI2cTe7TAg+2D4XSmf3FqHJMlOoIEyWqK1/siMeCLecglwErRnfF/axNIhO99NNR/O/4DYzt0RSzh0YavHbnKFIDTyU+GNEO/SNDkJGvwoXUPFxKy8eF1DxcSM3HxdQ83CwsqfQ6ugSqVVDZCJQugfpmz2WzJEnlqUu1+PHAVXwce1Efj7+HAk/cHY6nuzdGIz/3Wl+DHAsTpTrCRInqwqYTyZj84xEAwOwhbTH23mZWjojs2c4L6Rjz7UH4urvgwH/v14+6HE28iTd+PaEfRRoeFYbZQyPh666o9nxSEygAZk2SysspKsGa/Qn44UAiknOKAQByGdA3IhijopugZ8sGkHPxaAITpTrDRIks7UjiTYz86h+oSrWVjgAQSaXRCvSYH4vUXBWWP9MZvVsHYclfF7Bi12VoBRDopcT7w8tGkWojI1+Fi6n5uJiWhwupebe+zkehuhRLn4gye5JUXqlGi7/OpuH7f65iz6UM/famAe545p4meKxLOHzc2X+sPmOiVEeYKJElJWUVYvhne5FZoMb9EUH4anRXOPGvYTKDBVvO4Ysd8egY7osCVal+FGlEp4a3ehZVP4pUG1qtqNNRnUtp+fj+n6v47fA15N26M87VRY5hHRtiVHSTKuu0yLExUaojTJTIUnKKSvDIF/twKS0fkWHeWPt8NDyUztYOixzEpbR89Fu8U/880EuJD0a0xwNtHbf2rVBdij+O3sB3+xNwLiVPv71TY1+MuqcJHmwfysWl6xEmSnWEiRJZAtsAUF0Y9c0B7L6YUSejSLZECIHDV2/iu/1X8X+nklGiKfu15++hwONdy4q/w/1Z/O3omCjVESZKZG5sA0B1pUBVisx8NRoH1N+kID1PhV/+TTQo/pbJgL6tgzAqugl6tQpk8beDYqJUR5gokTldzy7CN7uv4Nu9VyCXAV+P6Yq+EY47FUJkK0o1WsSeS8Oa/YbF300C3HFfywaQV9OY05o8XZ0R4KFAgKcC/h7Kcl8r2EOqBqb+/mYBBFEdu55dhP87mYyNJ5JxLClbv33WkEgmSUR1xNlJjgGRIRgQGYL49LLi718PX8PVzEJczUy0dngm8VI6w/9W0hRwRxIV4Fm2zZ+JlWQcUZKII0r1ixAC17OLcDGtrE/MhVu3OydkFCDAQ4GWt5Z0aHWrsV7zQI9Ki0OrSo5kMuDupv4Y2S0cIzo1qsPvjIjuVKguxcYTybh200YX3RUCucWlyCxQI6tAhcx8NTIL1LhZoEapVvqvcn8PBVoGeqJV8K2fY7cahTbwVFS71I294tRbHWGiVPeuZhbgUlo+IkK9EebjKvkfcHahGhfT8nEju+YffkIAaXnF+oToUmoeCiQsDCqXAU0DPPQJlLvSCdtOp1aaHD3UIRQDI0MQ5M2ibSIynRACuUWlyChQIatAfSuBUiHrViKVVVD2PDO/7OusGhIrP3cXtArycrgEql4nSp999hkWLlyIlJQUdOzYEcuWLUO3bt2q3H/dunV4++23kZCQgFatWmHBggV48MEHjboWE6W6cTWzAJtOJmPzyWScup6r3x7srUTnxn7o1NgXnRv7oV1DH/0Iji4hut3ormwEKD1PVatYnOUyNA/00P/gaBXkhWYNPJBVoC67VlrZ9S6k5lW7Nla3pv4YzOSIiKxMl1gl3Sw06K5+KS0PV7MKUVVWUD6BaqUfTbefBKreJkq//PILRo8ejeXLl6N79+5YunQp1q1bh/PnzyMoKKjC/vv27UOvXr0wb948PPTQQ/jxxx+xYMECHDlyBO3atavxekyULKeq5MhJLkOzBh5IyCio8FeQi5MMLYO8kJGvqjYhaujrhkZ+bnB2qvkfs6+bwuAvqaYNPOBixMrkQgik56lw4VbSdDEtH5n5KtzXqgGTIyKyC8UlGlxKy5eUQPm6u6BFoCdcXWr+OWksZ7kcq8dXPeBhinqbKHXv3h133303Pv30UwCAVqtFeHg4XnrpJbz55psV9n/iiSdQUFCAjRs36rfdc889iIqKwvLly2u8nqUSJV0tTH1ToNIg9lwqNp1IxukbhslRdPMAPNg+FAMigxHgqUSRWoMT17JxJDEbRxNv4khiNjLyDZOjhr5ut6a9yoaKdUPGnmzcSERkMl0CdXsEvezrxGoSqNpQOMlx4f1BZj1nvbzrTa1W4/Dhw5gxY4Z+m1wuR79+/bB///5Kj9m/fz+mTJlisG3AgAH4448/Kt1fpVJBpbr9yzg3N7fS/WqrVCtw34I4i5zbXlSWHJXnpnBC9+YB6N48AEBZcnntZhHOJOciyEvJhIiIyEJcXZzQrqFPheVfdAnU1cxClGq1ZrueLbVnsOvfKhkZGdBoNAgONrylOjg4GOfOnav0mJSUlEr3T0lJqXT/efPmYc6cOeYJuAZKZ/MNW9oLuUyGLk38MLhDKPq3rZgcVUcmkyHc350ddYmIrKSqBMqR2HWiVBdmzJhhMAKVm5uL8PBws1/HxUmO8++Zd5iRiIiIaseuE6UGDRrAyckJqampBttTU1MREhJS6TEhISGS9lcqlVAqjR/lICIiIsdh13M9CoUCXbp0QWxsrH6bVqtFbGwsoqOjKz0mOjraYH8A2L59e5X7ExERUf1l1yNKADBlyhSMGTMGXbt2Rbdu3bB06VIUFBRg3LhxAIDRo0ejYcOGmDdvHgDglVdeQUxMDD766CMMHjwYP//8Mw4dOoSvvvrKmt8GERER2SC7T5SeeOIJpKen45133kFKSgqioqKwZcsWfcF2YmIi5PLbA2c9evTAjz/+iJkzZ+K///0vWrVqhT/++MOoHkpERERUv9h9H6W6xoaTRERE9sfU3992XaNEREREZElMlIiIiIiqwESJiIiIqApMlIiIiIiqwESJiIiIqApMlIiIiIiqwESJiIiIqApMlIiIiIiqwESJiIiIqAp2v4RJXdM1Ms/NzbVyJERERGQs3e9tqQuSMFGSKC8vDwAQHh5u5UiIiIhIqry8PPj4+Bi9P9d6k0ir1eLGjRvw8vKCTCZDbm4uwsPDkZSUxLXfrISfgfXxM7A+fgbWx8/Aump6/4UQyMvLQ1hYGORy4yuPOKIkkVwuR6NGjSps9/b25j8MK+NnYH38DKyPn4H18TOwrurefykjSTos5iYiIiKqAhMlIiIioiowUaolpVKJWbNmQalUWjuUeoufgfXxM7A+fgbWx8/Auiz1/rOYm4iIiKgKHFEiIiIiqgITJSIiIqIqMFEiIiIiqgITJSIiIqIqMFEywmeffYamTZvC1dUV3bt3x8GDB6vdf926dYiIiICrqyvat2+PzZs311GkjknK+3/69Gk88sgjaNq0KWQyGZYuXVp3gTo4KZ/DihUr0LNnT/j5+cHPzw/9+vWr8d8NVU/K+79+/Xp07doVvr6+8PDwQFRUFNasWVOH0Tomqb8LdH7++WfIZDIMHz7csgHWA1I+g1WrVkEmkxk8XF1dpV9UULV+/vlnoVAoxLfffitOnz4tnn32WeHr6ytSU1Mr3X/v3r3CyclJfPjhh+LMmTNi5syZwsXFRZw8ebKOI3cMUt//gwcPiqlTp4qffvpJhISEiCVLltRtwA5K6ufw1FNPic8++0wcPXpUnD17VowdO1b4+PiIa9eu1XHkjkHq+x8XFyfWr18vzpw5Iy5duiSWLl0qnJycxJYtW+o4csch9TPQuXLlimjYsKHo2bOnGDZsWN0E66CkfgYrV64U3t7eIjk5Wf9ISUmRfF0mSjXo1q2bmDx5sv65RqMRYWFhYt68eZXu//jjj4vBgwcbbOvevbt4/vnnLRqno5L6/pfXpEkTJkpmUpvPQQghSktLhZeXl1i9erWlQnRotX3/hRCiU6dOYubMmZYIr14w5TMoLS0VPXr0EF9//bUYM2YME6VakvoZrFy5Uvj4+NT6upx6q4Zarcbhw4fRr18//Ta5XI5+/fph//79lR6zf/9+g/0BYMCAAVXuT1Uz5f0n8zPH51BYWIiSkhL4+/tbKkyHVdv3XwiB2NhYnD9/Hr169bJkqA7L1M9g7ty5CAoKwoQJE+oiTIdm6meQn5+PJk2aIDw8HMOGDcPp06clX5uJUjUyMjKg0WgQHBxssD04OBgpKSmVHpOSkiJpf6qaKe8/mZ85Pofp06cjLCyswh8RVDNT3/+cnBx4enpCoVBg8ODBWLZsGR544AFLh+uQTPkM9uzZg2+++QYrVqyoixAdnimfQevWrfHtt9/izz//xPfffw+tVosePXrg2rVrkq7tbHLURERGmD9/Pn7++Wfs2LHDtEJKMomXlxeOHTuG/Px8xMbGYsqUKWjevDl69+5t7dAcXl5eHkaNGoUVK1agQYMG1g6n3oqOjkZ0dLT+eY8ePdCmTRt8+eWXePfdd40+DxOlajRo0ABOTk5ITU012J6amoqQkJBKjwkJCZG0P1XNlPefzK82n8OiRYswf/58/PXXX+jQoYMlw3RYpr7/crkcLVu2BABERUXh7NmzmDdvHhMlE0j9DOLj45GQkIAhQ4bot2m1WgCAs7Mzzp8/jxYtWlg2aAdjjt8HLi4u6NSpEy5duiTp2px6q4ZCoUCXLl0QGxur36bVahEbG2uQpZYXHR1tsD8AbN++vcr9qWqmvP9kfqZ+Dh9++CHeffddbNmyBV27dq2LUB2Suf4daLVaqFQqS4To8KR+BhERETh58iSOHTumfwwdOhR9+vTBsWPHEB4eXpfhOwRz/DvQaDQ4efIkQkNDpV281uXgDu7nn38WSqVSrFq1Spw5c0Y899xzwtfXV3+L4ahRo8Sbb76p33/v3r3C2dlZLFq0SJw9e1bMmjWL7QFqQer7r1KpxNGjR8XRo0dFaGiomDp1qjh69Ki4ePGitb4FhyD1c5g/f75QKBTi119/Nbg1Ny8vz1rfgl2T+v5/8MEHYtu2bSI+Pl6cOXNGLFq0SDg7O4sVK1ZY61uwe1I/gzvxrrfak/oZzJkzR2zdulXEx8eLw4cPiyeffFK4urqK06dPS7ouEyUjLFu2TDRu3FgoFArRrVs38c8//+hfi4mJEWPGjDHYf+3ateKuu+4SCoVCREZGik2bNtVxxI5Fyvt/5coVAaDCIyYmpu4DdzBSPocmTZpU+jnMmjWr7gN3EFLe/7feeku0bNlSuLq6Cj8/PxEdHS1+/vlnK0TtWKT+LiiPiZJ5SPkMXn31Vf2+wcHB4sEHHxRHjhyRfE2ZEEJIG4MiIiIiqh9Yo0RERERUBSZKRERERFVgokRERERUBSZKRERERFVgokRERERUBSZKRERERFVgokRERERUBSZKRGQWQgg899xz8Pf3h0wmw7Fjx6wdkk0aO3YsZDIZZDIZ/vjjD7Oee8eOHfpzDx8+3KznJqqvmCgRkVls2bIFq1atwsaNG5GcnIx27dpZOySbNXDgQCQnJ2PQoEH6bVUlTmPHjjU66enRoweSk5Px+OOPmylSInK2dgBE5Bji4+MRGhqKHj16VLmPWq2GQqGow6hsk1KpNHrFcykUCgVCQkLg5ubGBXCJzIQjSkRUa2PHjsVLL72ExMREyGQyNG3aFADQu3dvvPjii3j11VfRoEEDDBgwAABw6tQpDBo0CJ6enggODsaoUaOQkZGhP19BQQFGjx4NT09PhIaG4qOPPkLv3r3x6quv6vepbATG19cXq1at0j9PSkrC448/Dl9fX/j7+2PYsGFISEgwiHv48OFYtGgRQkNDERAQgMmTJ6OkpES/j0qlwvTp0xEeHg6lUomWLVvim2++gRACLVu2xKJFiwxiOHbsGGQyGS5dulS7N7USCQkJ+qm18o/evXub/VpEVIaJEhHV2scff4y5c+eiUaNGSE5Oxr///qt/bfXq1VAoFNi7dy+WL1+O7Oxs9O3bF506dcKhQ4ewZcsWpKamGkwXvfHGG9i5cyf+/PNPbNu2DTt27MCRI0ckxVRSUoIBAwbAy8sLu3fvxt69e+Hp6YmBAwdCrVbr94uLi0N8fDzi4uKwevVqrFq1yiDZGj16NH766Sd88sknOHv2LL788kt4enpCJpNh/PjxWLlypcF1V65ciV69eqFly5YS38WahYeHIzk5Wf84evQoAgIC0KtXL7Nfi4huqe1KvkREQgixZMkS0aRJE4NtMTExolOnTgbb3n33XdG/f3+DbUlJSQKAOH/+vMjLyxMKhUKsXbtW/3pmZqZwc3MTr7zyin4bAPH7778bnMfHx0esXLlSCCHEmjVrROvWrYVWq9W/rlKphJubm9i6dasQomxF9yZNmojS0lL9Po899ph44oknhBBCnD9/XgAQ27dvr/R7vn79unBychIHDhwQQgihVqtFgwYNxKpVq6p4l6peRR6AcHV1FR4eHgYPZ2fnSvcvKioS3bt3Fw899JDQaDRGXYOIpGONEhFZVJcuXQyeHz9+HHFxcfD09Kywb3x8PIqKiqBWq9G9e3f9dn9/f7Ru3VrSdY8fP45Lly7By8vLYHtxcTHi4+P1zyMjI+Hk5KR/HhoaipMnTwIom0ZzcnJCTExMpdcICwvD4MGD8e2336Jbt2743//+B5VKhccee0xSrDpLlixBv379DLZNnz4dGo2mwr7jx49HXl4etm/fDrmckwNElsJEiYgsysPDw+B5fn4+hgwZggULFlTYNzQ01OjaHplMBiGEwbbytUX5+fno0qULfvjhhwrHBgYG6r92cXGpcF6tVgsAcHNzqzGOiRMnYtSoUViyZAlWrlyJJ554Au7u7kZ9D3cKCQmpMGXn5eWF7Oxsg23vvfcetm7dioMHD1ZIBInIvJgoEVGd6ty5M3777Tc0bdoUzs4VfwS1aNECLi4uOHDgABo3bgwAuHnzJi5cuGAwshMYGIjk5GT984sXL6KwsNDgOr/88guCgoLg7e1tUqzt27eHVqvFzp07K4z06Dz44IPw8PDAF198gS1btmDXrl0mXctYv/32G+bOnYv/+7//Q4sWLSx6LSJiMTcR1bHJkycjKysLI0eOxL///ov4+Hhs3boV48aNg0ajgaenJyZMmIA33ngDf//9N06dOoWxY8dWmF7q27cvPv30Uxw9ehSHDh3CCy+8YDA69PTTT6NBgwYYNmwYdu/ejStXrmDHjh14+eWXce3aNaNibdq0KcaMGYPx48fjjz/+0J9j7dq1+n2cnJwwduxYzJgxA61atUJ0dLR53qhKnDp1CqNHj8b06dMRGRmJlJQUpKSkICsry2LXJKrvmCgRUZ0KCwvD3r17odFo0L9/f7Rv3x6vvvoqfH199cnQwoUL0bNnTwwZMgT9+vXDfffdV6HW6aOPPkJ4eDh69uyJp556ClOnTjWY8nJ3d8euXbvQuHFjPPzww2jTpg0mTJiA4uJiSSNMX3zxBR599FFMmjQJERERePbZZ1FQUGCwz4QJE6BWqzFu3LhavDM1O3ToEAoLC/Hee+8hNDRU/3j44Yctel2i+kwm7pzkJyKyQb1790ZUVBSWLl1q7VAq2L17N+6//34kJSUhODi42n3Hjh2L7Oxssy9fUtfXIKovOKJERGQilUqFa9euYfbs2XjsscdqTJJ0Nm7cCE9PT2zcuNGs8ezevRuenp6VFrATkWlYzE1EZKKffvoJEyZMQFRUFL777jujjvnwww8xc+ZMAGV3+ZlT165d9YsRV9Z+gYik49QbERERURU49UZERERUBSZKRERERFVgokRERERUBSZKRERERFVgokRERERUBSZKRERERFVgokRERERUBSZKRERERFVgokRERERUhf8HbNiB5/Wye8YAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1299,7 +1515,7 @@
     }
    ],
    "source": [
-    "data[\"swden\"].plot()"
+    "data[\"swden\"].plot(xscale=\"log\")"
    ]
   },
   {
@@ -1319,7 +1535,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1330,7 +1546,7 @@
    ],
    "source": [
     "spread = wave.io.ndbc.create_spread_function(data, directions)\n",
-    "wave.graphics.plot_directional_spectrum(spread, name=\"Spread\", units=\"1\")"
+    "wave.graphics.plot_directional_spectrum(spread, name=\"Spread\", units=\"1\", color_level_min=0.0)"
    ]
   },
   {
@@ -1359,7 +1575,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1371,7 +1587,7 @@
    "source": [
     "rho = 1025  # kg/m^3\n",
     "g = 9.81  # m/s^2\n",
-    "wave.graphics.plot_directional_spectrum(spectrum * rho * g, name=\"Energy\", units=\"J\")"
+    "wave.graphics.plot_directional_spectrum(spectrum * rho * g, name=\"Energy\", units=\"J\", color_level_min=0.0)"
    ]
   },
   {
@@ -1384,7 +1600,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -1398,12 +1614,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "15fd306e44580d8cf431083454c399b84f9cc4f7f2c761501397671836835f49"
-   }
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/environmental_contours_example.ipynb b/examples/environmental_contours_example.ipynb
index c97f2a634..524309692 100644
--- a/examples/environmental_contours_example.ipynb
+++ b/examples/environmental_contours_example.ipynb
@@ -83,31 +83,31 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1658</th>\n",
+       "      <th>1768</th>\n",
        "      <td>46022</td>\n",
        "      <td>1996</td>\n",
        "      <td>46022w1996.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1659</th>\n",
+       "      <th>1769</th>\n",
        "      <td>46022</td>\n",
        "      <td>1997</td>\n",
        "      <td>46022w1997.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1660</th>\n",
+       "      <th>1770</th>\n",
        "      <td>46022</td>\n",
        "      <td>1998</td>\n",
        "      <td>46022w1998.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1661</th>\n",
+       "      <th>1771</th>\n",
        "      <td>46022</td>\n",
        "      <td>1999</td>\n",
        "      <td>46022w1999.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1662</th>\n",
+       "      <th>1772</th>\n",
        "      <td>46022</td>\n",
        "      <td>2000</td>\n",
        "      <td>46022w2000.txt.gz</td>\n",
@@ -118,11 +118,11 @@
       ],
       "text/plain": [
        "         id  year           filename\n",
-       "1658  46022  1996  46022w1996.txt.gz\n",
-       "1659  46022  1997  46022w1997.txt.gz\n",
-       "1660  46022  1998  46022w1998.txt.gz\n",
-       "1661  46022  1999  46022w1999.txt.gz\n",
-       "1662  46022  2000  46022w2000.txt.gz"
+       "1768  46022  1996  46022w1996.txt.gz\n",
+       "1769  46022  1997  46022w1997.txt.gz\n",
+       "1770  46022  1998  46022w1998.txt.gz\n",
+       "1771  46022  1999  46022w1999.txt.gz\n",
+       "1772  46022  2000  46022w2000.txt.gz"
       ]
      },
      "execution_count": 2,
@@ -182,31 +182,31 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1658</th>\n",
+       "      <th>1768</th>\n",
        "      <td>46022</td>\n",
        "      <td>1996</td>\n",
        "      <td>46022w1996.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1659</th>\n",
+       "      <th>1769</th>\n",
        "      <td>46022</td>\n",
        "      <td>1997</td>\n",
        "      <td>46022w1997.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1660</th>\n",
+       "      <th>1770</th>\n",
        "      <td>46022</td>\n",
        "      <td>1998</td>\n",
        "      <td>46022w1998.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1661</th>\n",
+       "      <th>1771</th>\n",
        "      <td>46022</td>\n",
        "      <td>1999</td>\n",
        "      <td>46022w1999.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1662</th>\n",
+       "      <th>1772</th>\n",
        "      <td>46022</td>\n",
        "      <td>2000</td>\n",
        "      <td>46022w2000.txt.gz</td>\n",
@@ -217,11 +217,11 @@
       ],
       "text/plain": [
        "         id  year           filename\n",
-       "1658  46022  1996  46022w1996.txt.gz\n",
-       "1659  46022  1997  46022w1997.txt.gz\n",
-       "1660  46022  1998  46022w1998.txt.gz\n",
-       "1661  46022  1999  46022w1999.txt.gz\n",
-       "1662  46022  2000  46022w2000.txt.gz"
+       "1768  46022  1996  46022w1996.txt.gz\n",
+       "1769  46022  1997  46022w1997.txt.gz\n",
+       "1770  46022  1998  46022w1998.txt.gz\n",
+       "1771  46022  1999  46022w1999.txt.gz\n",
+       "1772  46022  2000  46022w2000.txt.gz"
       ]
      },
      "execution_count": 3,
@@ -547,7 +547,7 @@
        "      <th>Te</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>index</th>\n",
+       "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
@@ -615,7 +615,7 @@
       ],
       "text/plain": [
        "                          Hm0         Te\n",
-       "index                                   \n",
+       "date                                    \n",
        "1996-01-01 00:00:00  4.819627  14.856398\n",
        "1996-01-01 01:00:00  5.004158  14.961679\n",
        "1996-01-01 02:00:00  5.091169  14.244618\n",
@@ -719,7 +719,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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2+JzJuRNGCrmnBGZLSxj/99+9eG6zSneqLbLhoyfU4uJjauCxkRD7cPeK3FPCaDBZ7qsKpwkPXr4Ybyyvwf/+Yxt2dsbw9b9swu/e3Itvf3ABlkzzjPUQpwwT5Z4azPh02jhV8Oh0OvzlL3/BRRdddNB7mUwGF198MZqamvDKK68c0rG48847cddddx30+hNPPAG73T6SQxYEQRAGSV4DtgZ1eLlFhx1hldY0x53HymoNC7waZBJVEEaHXB54rV2H5/frkcjpoIOGFZUazp+eh0Wa0QsHiMfjuOqqqxAKhQ5pcwMT0LHIZDK47LLLsHv3bvz73/9GSUnJIbfTV8SitrYWPp/vsCdHOJhMJoOXXnoJZ511lpRxFEYEuaemJqlMDs9saMUjb+zDrs4YAMCg1+H8oyvxiVNmYGH10L+f5Z4SRoPJfF91RVP43vPb8cyGVgBUtvmuD87HyrllYzyyyc1EuafC4TBKS0sH5FhMqFQodip27NiBl19++bBOBQBYLBZYLAfXHTSZTOP6Io535PwJI43cU1ODYDyN367eh9+s3gtfNA2Acr+vOmE6Pn5yHaq9thHbl9xTwmgwGe+ryiITHrjyGHzk2E584y+b0BRI4FO/XYcLl1TjWxcuQKl07x5Vxvs9NZixjSvHIhqNYufOnd3P9+zZg/Xr16O4uBhVVVW45JJLsHbtWvz9739HLpdDW1sbAKC4uBhms1Q0EARBGK90hJP41Wu78fiaRsTTVA+22mPFdafU4/Lja+G2jt8fVUGYKrxvbhlevGkF7n1xOx757x78bUMLXtvRiW9duAAXLa2BTid5icKhGVeOxTvvvIPTTz+9+/nNN98MALj22mtx55134tlnnwUALF26tMd6L7/8MlauXHmkhikIgiAMkMauOH756i788Z0mpHN5AMD8Kjc+876ZOG9RlXQBFoRxht1sxDcvWIAPLq3G157ehPdaw7jpqQ146b12fOeiRSh2yESu0D/jyrFYuXLlIbtBjlM5iCAIgtCL7e0R/OKVXXh2Q0t3hadjZxThC6fPxsp5ZTLzKQjjnMXTvHjmC6fgoVd24YFVO/Dcpja8tSeAH16yCGccVTHWwxPGKePKsRAEQRAmNhv2B/Gzl3fixffau19bMbcMn185C8fXF4tDIQgTCJNBjxvOnIOV88px0x/WY2dHFJ947B1ceXwtvnn+AjgsYkYKPZE7QhAEQRg27+4L4P5/bcdrO3wAAJ0O+MDCSnxu5Wwskrr4gjChWTTNg7/fcCrueaEB//f6Hvz+rf34784u3Hf5Ehw7o3ishyeMI8SxEARBEIZMb4fCoNfhoqU1+OzKmZhd7hrj0QmCMFJYTQbcfsECnDm/HLf+cSMa/XFc9ss38eWz5+IzK2ZBLw1nBIhjIQiCIAyBd/cF8MCqHXh1eycAwKjX4ZJjp+Hzp89GbbE0HxWEycrJs0rxzy+dhm/+ZTOe3dCCHz7fgDd3+3HvZUukLK0gjoUgCIIwcMShEATBbTXhgSuW4pTZJbjjmS14dXsnznvgNTx45TKcOPPwPcaEyYs4FoIgCMJhWdcYwH3/6ulQXHwMORTTS8ShEISphk6nw+XHTcfS2iJ8/om12NkRxVW/ehM3njkXXzhjNgySGjUlEcdCEARB6JeGtgjueaEB/9pKVZ4Meh0uEYdCEIQDzKt04dkvnIJvPbMFf3y3Cff9azve2efHT65cBq9del5MNcSxEARBEA6isSuO+/61HX9d3wxNA/Q64OJjpuGGM+aIQyEIQg/sZiPuuXQJTppVgm/8ZTNe2+HDhT99HQ9fsxzzq9xjPTzhCCKOhSAIgtBNeziJn/x7B558az+yBxrbnb+oCjedNRezy51jPDpBEMYzHzlmGuZXufHp376D/f4EPvLzN/DDSxbjwiXVYz004QghjoUgCIKAYDyNX/xnF37zxl4kM3kA1Nju1rPnSR8KQRAGzPwqN/72hVNxw+/X4bUdPtzw+3XY3BzCVz5wlOgupgDiWAiCIExhYqksHv3vHvzy1d2IJLMAgGNnFOHWc+ZJdRdBEIaE127GY9cdjx++sA2//M9u/PLV3XivNSy6iymAOBaCIAhTkHQ2jyfW7MNPX94JXzQNADiq0oWvfGAeTp9XDp1OZhYFQRg6Br0Ot507H0dXe/CVP23Eazt8+Mgv3sCjHz8OM0ocYz08YZQQx0IQBGEKoWkantvUhh++sA37uuIAgLoSO246ay4uXFwt3XMFQRhRLlxSjdnlTnzysbexuzOGD//8DfzqY8fi2BnFYz00YRQQx0IQBGGK8O4+P777j61Y2xgEAJS5LPjS++fgsuW1MBn0Yzs4QRAmLfOr3Pjr50/BJ3/zDjY1h3Dlr9bgx5cuEVH3JEQcC0EQhEnOHl8MP/jnNjy/pQ0AYDMZ8D/vm4lPnTYTDov8DAiCMPqUu6146n9OxI1PrsdL77Xjht+vQ6M/js+tnCWpl5MI+UURBEGYpHRFU3hw1Q48vqYR2bwGvQ64/Lha3PT+uSh3W8d6eIIgTDHsZiMe+uix+N5zW/Hr1/fgnhcasNcXw90fWSRR00mCOBaCIAiTjGQmh0f+uwe/eHkXIimq9HT6vDLcdt58zK1wjfHoxo5UCsjnAb0esFjGejSCMDUx6HX45gULMKPEjm89S926/bE0fnb1MbCaDGM9PGGYiGMhCIIwScjnNfx1fTN+9EIDWkJJAMCCKje+cf58nDK7dIxHN3Ykk4DfD0QiQC4HGAyAywUUFwNWCdwIwphwzUl1qPba8LnH12LVtg587P/ewq+uXQ6PzTTWQxOGgcSdBEEQJgHv7gvgwz//L27+wwa0hJKo9lhx72VL8PcbTp3yTkVzMxAIUJTC46HHQIBeTybHeoSCMHU5c34FfvvJE+CyGvHWXj+uePhNdETkQzmREcdCEARhAtMaSuDGJ9fh4l+8gQ1NITjMBtx6zjz8+5aV+Mgx06Z8+Vi/n5yHoiLAbAZ0OnosKlKRDEEQxo7j64vx1KdPQqnTgq2tYVz60Go0HiiFLUw8xLEQBEGYgCTSOTzwrx0440f/wTPrW6DTAZctn4aXb12Jz58+W3KVQZqKSARw9NOLy+Gg91OpIzsuQRB6sqDajac/exJqi23Y1xXHxQ+9gW1t4bEeljAEBqWxePbZZwe9g7POOgs2m23Q6wmCIAgHo2ka/r6xFd//5zY0BxMAgOPqinDHBQuxaJpnjEc3vsjnSVNh6idl22QC4nFaThCEsWVGiQNPf+ZkfOyRt7CtLYIrH34Tv7v+BCyslu+1icSgHIuLLrpoUBvX6XTYsWMHZs6cOaj1BEEQhIPZ1BTCt/++BW/vDQAAqj1W3HbefFywuErqwPeBXk9C7UyG0p96k8nQ+3qJ3QvCuKDcbcVTnz4JH3tkDTY0hXD1r9fgd588AUfXiHMxURj012lbWxvy+fyA/ux2+2iMWRAEYUrREUniK3/agA/+7HW8vTcAq0mPm94/F6u+vBIXLqkWp6IfLBaq/hSL9f1+LEbvS+lZQRg/eOwm/Pb6E7BsuhfBeAZX/epNbGwKjvWwhAEyKMfi2muvHVRa00c/+lG43e5BD0oQBEEAMrk8fv3abpzxo//gD+80QdOAi5ZW4+VbVuLG98+BzSw6isPBJWUDASCdBjSNHgMBer24eKxHKAhCb9xWE/7fJ47HsTOKEE5mcfWv12D9/uBYD0sYAINKhXr00UcHtfFf/OIXg1peEARBIFbv6sK3nt2M7e1RAMCSaR7cceFCHDujaIxHNrGwWoGaGtXHIh6n9KeiIuljIQjjGZfVhN984nhc9+hbeHtvANf8eg0eO+BsCOMXaZAnCIIwjmgLJfHd57bibxtaAABFdhO++oGjcNny2ilfOnaoWK1AdbV03haEiYbTYsRj1x2PTzz2Ntbs8ePjj7yFJz51ohSqGMcMy7FIJpPYuHEjOjo6kO9VVuODH/zgsAYmCIIwlUhn83j0v3vw4KodiKVz0OmAj54wA18+ey689j6Ux8KgEWdCECYeDosRj153HK57lJyLjz2yBk/9z0mYW+Ea66EJfTBkx+L555/Hxz72Mfh8voPe0+l0yOVywxqYIAjCVOG/O32445nN2NVJKuNjpnvx7Q8dLZVQBEEQANjNRvzfx4/D1b9egw37g/jor9fgj585CTNK+mlSI4wZQy6yd8MNN+DSSy9Fa2vrQdWgxKkQBEE4PC3BBD7/+Fpc/es12NUZQ4nDjHsuWYw/feZkcSoEQRAKcFqM+M11x+GoShc6Iilc9as1aDnQy0cYPwzZsWhvb8fNN9+MioqKkRyPIAjCpCeTy+Oh/+zCmT/+D/6xqRV6HfDxk+vw71tW4lLRUgiCIPSJ127Gbz95AupLHWgOJvDRX6+BL5oa62EJBQzZsbjkkkvwyiuvjOBQBEEQJj9v7/Xj/Adfw/f/uQ2JTA7H1RXh7zechjs/uBAeWz8tooVxTyoFJBL0KAjC6FHmsuB315+AGq8Nu30xXPN/byGczIz1sIQDDFlj8dOf/hSXXnopXnvtNSxatAgmU88fxC9+8YvDHpwgCMJkIRBL4/v/3Ian3tkPACh2mPH18+bj4mNqpMHdBCaZVKVsczkqZetySSlbQRhNarw2PH79Cbj0l6uxtTWMz/z2XTx23fEwG4c8Xy6MEEN2LH7/+9/jxRdfhNVqxSuvvNLjh1Gn0w3JsXj11Vdxzz334N1330Vrayv+8pe/4KKLLup+X9M0fOtb38KvfvUrBINBnHLKKfjFL36BOXPmDPUwBEEQRhVN0/D02mbc/dxW+GNpAMAVx9Xia+ceJdWeJjjJJNDcTI8OB2AyAZkMNd9LJKh/hjgXgjA61JU68Nh1x+Gyh1bjjV1duPVPG3DfZUsllXSMGbJr941vfAN33XUXQqEQ9u7diz179nT/7d69e0jbjMViWLJkCX72s5/1+f4Pf/hDPPjgg3jooYewZs0aOBwOnHPOOUgmk0M9DEEQhFFjZ0cUVzz8Jm754wb4Y2nMq3DhT585Cd+/eLE4FZMAv5+ciqIiwGwGdDp6LCpSkQxBEEaPhdUePHTNsTDqdXhmfQt+8MK2sR7SlGfIEYt0Oo3LL78cev3IhZ3OPfdcnHvuuX2+p2ka7r//fnzzm9/Ehz70IQDA//t//w8VFRX461//iiuuuGLExiEIgjAckpkcfvbyTjz0n13I5DRYTXp86f1z8clT62EySKh+MpBKUfqTo59qlw4HvZ9KSf8MQRhNTptThh9cvBhf/uMG/PI/u1HtseHak+vGelhTliH/wl177bV46qmnRnIsh2TPnj1oa2vD+9///u7XPB4PTjjhBKxevfqIjUMQBOFQvLq9E+fc/yp+8u+dyOQ0nHFUOV666X34zPtmiVMxicjnSVNh6kdvbzLR+716xwqCMApcfOw03HrOPADAnX/bguc3t47xiKYuQ45Y5HI5/PCHP8QLL7yAxYsXHyTevvfee4c9uELa2toA4KDythUVFd3v9UUqlUKqoExHOBwGAGQyGWQyUkVgsPA5k3MnjBST5Z7qiKRw93MN+MfmA99VbgtuP+8onL2gHDqdbsIf30TiSNxT7DTE45T+1Jt0WjkfcuknB5Plu2qy8qlTpqPJH8Pv327CjU+ux+OfNGHJtPHdD2ii3FODGd+QHYtNmzZh2bJlAIDNmzf3eG88VTj53ve+h7vuuuug11988UXY7fYxGNHk4KWXXhrrIQiTjIl6T+U14I12Hf7WqEcyp4MOGlZUajhvegy5fe/in/vGeoRTl9G+p7q6LIjFzHA6D/7RjUZNcDjS2LVL6s9ONibqd9VU4DgDsMGrx3tB4BOPvIkvL8rBOwFSEcf7PRWPxwe87JAdi5dffnmoqw6JyspKANSYr6qqqvv19vZ2LF26tN/1brvtNtx8883dz8PhMGpra3H22WfD7XaP2ngnK5lMBi+99BLOOuusg6JUgjAUJvI9tbszhm88swXv7AsCABbVuPG/H1yAhdXy3TKWHKl7iqtCpVKA3a6qQsXjpKsYalWoVIqiHXq96DPGExP5u2oqsfLMLC7/1Rrs6IjhT+3FePwTx8FmNoz1sPpkotxTnO0zEAblWGzcuBFHH330gAXbW7Zswbx582A0Dtl/6aa+vh6VlZVYtWpVtyMRDoexZs0afPazn+13PYvFAksf38wmk2lcX8Txjpw/YaSZSPdUOpvHw6/uwoOrdiKdy8NuNuCWs+fh2pPrYJBSh+OG0b6nTCagrk71sYjHqY9FWdnQ+lhIT4yJwUT6rpqKFJtM+L9rj8eHfvY6NjWH8fVn3sNPrlw2rrJpejPe76nBjG1QFv+yZcvQ1taGsrKyAS1/0kknYf369Zg5c+aAlo9Go9i5c2f38z179mD9+vUoLi7G9OnT8aUvfQnf+c53MGfOHNTX1+P2229HdXV1j14XgiAIo8m6xgC+9vQmNLRHAADvm1uG7374aEwrktTKqYjVClRXDz/KID0xBGHkmF5ix0MfPRZX/3oN/r6xFXMrXPjimdLz7EgwKMdC0zTcfvvtA9YmpNPpQQ3mnXfewemnn979nFOYrr32Wjz22GP4yle+glgshk9/+tMIBoM49dRT8fzzz8Mq37aCIIwysVQWP3qxAY+9sReaRp2zv3XhAnxwSfW4ngkTjgzDTVkq7InBmM30FwjQ+9XVw9uHIEwlTphZgu9cdDS+9udNuPel7ZhT7sS5i6oOv6IwLAblWKxYsQINDQ0DXv6kk06CzWYb8PIrV66Epmn9vq/T6fDtb38b3/72twe8TUEQhOHySkMHvvGXzWgOJgAAH1lWg29esADFDmlydySY7JoD6YkhCKPDFcdPR0N7BI/+dy++/McNmF3uxJwK11gPa1IzKMfilVdeGaVhCIIgjD/8sTS+/bct+Ov6FgBAjdeGuz+yCO+bO7B0UGF4TBXNwUB6YsTj0hNDEIbCN86bj4a2CN7Y1YXP/O5dPPOFU+G0DF/7K/SNdGsSBEHohaZp+Ou6Zrz/3v/gr+tboNcBnzy1Hi/etEKciiMEaw4CAZql93joMRBQWoTJgl5PTlN/peIzGXp/gHVTBEEowGjQ48Erl6HSbcWuzhi++vTGQ2bHCMNDvqYEQRAKaAkmcN1jb+NLT62HP5bGUZUu/Plzp+D2CxbAIbNcgyaVIvFxapDtHAo1B2YzoNPRY1GRimRMFiwWisTEYn2/H4vR+5IGJQhDo9Rpwc+uPgZGvQ7/2NiKR/67d6yHNGmRX0lBEARQlOLJt/fj7n9sRSSVhdmgxxfPnI1Pr5gFs1HmYAoZiOZhOGlMU1FzUFxMDlgg0LMqVCxG56u4eKxHKAgTm2NnFOGb58/HnX97D997bisWT/PguDr5YI004lgIgjDl2e+P47Y/b8LrO30AgGXTvbjnksWYXS4iv0IG6iwMt3TqVNQcWK10Xnr3xCgqmnyaEkEYK649uQ7vNgbxtw0t+Pzja/GPL56GMtckmZ0YJ4hjIQjClCWf1/D4W434/nNbEUvnYDHqces583DdKfXS6K4XA3UWUimgpQUIh4GKCrX+YEqnFmoOzH0U3pqsmoOR6okhCELf6HQ6fP8ji7C1NYydHVHc/If1+M11x0Mv3/cjxpAcC5/Ph0ceeQSrV69GW1sbAKCyshInn3wyPv7xjw+4gZ4gCMJY0dgVx1ee3oA3d1Oy/nF1RfjBxYsxs8w5xiMbnxyuz0JLCxnGXV1AYyP9r2mA19tztn0gaUysOQgE+nYsYjEax2Q1uifrcQnCeMBhMeIXVx+DC3/6Ol7b4cOvX9+NT6+YNdbDmjQMer7n7bffxty5c/Hggw/C4/FgxYoVWLFiBTweDx588EEcddRReOedd0ZjrIIgCMMmn9fw6H/34Jz7X8Wbu/2wmQy488IFeOrTJ4lT0Q+H0zwYDMDOnUB7O0Uy7HZaNhQiJyMYVOJtk4nSnA6XxsTpP4EAkE6Tk5JO03PRHAiCMBzmVLhwxwULAQD3vNCATU2hMR7R5GHQEYsbbrgBl156KR566KGDus1qmobPfOYzuOGGG7B69eoRG6QgCMJIsMcXw1f+tAFv7w0AAE6cWYwfXrwE00vsfS4vKSnE4TQPsRilQ7ndKo0pnabz194O+HxAeTngdJLDMZA0JtEcCIIwmlx5fC1e3d6J57e04YtPrsPfbzhVKv+NAIM+gxs2bMBjjz12kFMBUO7aTTfdhGXLlo3I4ARBEEaCXF7DI6/vwY9ebEAqm4fDbMDXzpuPq4+f3mdu7VRpzDZQDqV5SKUoIuF0KgfMZAJ27aJz5XaTY6LTUQSjvR2YN29gjlqh5iBBTc9hs01tJ08QhJFBp9Ph+xcvwsamIPb4YvjWs1vwo0uXjPWwJjyDToWqrKzEW2+91e/7b731FioKFXuCIAhjyM6OCC556A1897mtSGXzOHV2KV64aQWuOXFGv07FUBuzDbVnw1hzuHEfqs9CPk+ve70HG/yaBhiNtAynPvUxJ3VIkknSbbS3k45j7156PFyDvExGPyGvRV9M1PtKEMY7XrsZ91+xDHod8Kd3m/DM+uaxHtKEZ9ARi1tuuQWf/vSn8e677+LMM8/sdiLa29uxatUq/OpXv8KPfvSjER+oIAjCYMjlNfzqtd2496XtSGfzcFmM+Mb583H5cbV9RlyZw4mU+6poNFEjHIcbd2EqWH99FsJhWtZ5QJ6SStHr06fT8qyvyGbpnNrt9P5AelAMpWxtMklOSEeHDXv3KqdovF+Lvpio95UgTCSOry/GF86YgwdX7cA3/7oZx9cXo8pjG+thTVgG7Vh8/vOfR2lpKe677z78/Oc/Ry6XAwAYDAYce+yxeOyxx3DZZZeN+EAFQRAGyh5fDF/+w3qsbQwCAFbOK8PdH16Eau+hfyyG0phtuD0bxopDjTsQoJSjTKanQVtSQlqHQs1DRQVFdThViaMTLhc5GzodPVZV0TnTNEqJGkgPisE6eXxM0ShgMuXhdtPr4/1a9MVEva8EYSLyxTNm49XtnVi/P4ivPr0Jv7nuuENOQAn9MySVyuWXX47LL78cmUwGPh81lCotLYWpP2WfIAjCESCf1/D/Vu/F95/fhmQmD6fFiDsuWIBLl08b0I/EUBqzDSXCMR7ob9z5PLB9OzkB9fV9G7QlJT1F7YXpY0YjRSeCQXp0uYDKSuWIDbQHxVCcPD4mrxcwGjXodDT+8X4t+mKi3leCMBExGvT40aVLcP6Dr+HV7Z148u39uPL46WM9rAnJsNoLmUwmVFVVoaqqSpwKQRDGlKZAHFf/eg3u/Nt7SGbyOHlWCV64aQUuO0zqUyGZDP1Fo/2/X2gUD8b4HU8catzBoBJraxpFHMxmMnA5NcdioYgGQM6GTkcOh82mtBANDaS96H3qYzFyNg6XBjUQJ6+wbO1EvRZ9MZmORRAmCrPLnbj1nHkAgO/8/T3s98fHeEQTkyHX1QqHw3j00UfR1taG+vp6LFmyBIsWLYLd3nfZRkEQhNFA0zT84Z39+N+/b0U0lYXNZMBt5x2Fj57Qtzi7Lwpz2QMBciyqqw9u7ta7MdtQIhzjgf7GnUrRsbvddE56j5sN2lCIzkVh7r/JRE6GywUsXkznMZOhZfJ5oLSUIhgD7UEx2O7bhceUzR68/Hi9Fn2Rz9O5ZOeutxM2kY5FECYS151Sjxe2tOHtvQF89emN+N0nT5Cu3INkyI7FRz7yEWzYsAHHHXcc/va3v6GhoQEAMGvWLCxZsgRPPfXUiA1SEAShL9rDSXzt6Y14uaETAHDsjCL86NIlqC/tZ6q3D3rnstfWAk1NwP79ZBRPm0YGXix2sFE8WON3vNDfuAurN+n1B4/bZCKHYf9+ikQU5v7v2UOOydy5qsxsMEiOSlcXGf2zZ9M6mnZ48fZgu28XHlNfAarxei16k0wCbW30ZzDQ8TmdPZ3ciXIsgjDRMOh1uOeSJTj3gdfwxq4u/G7NPnzspLqxHtaEYsiOxerVq/HKK6/guOOOAwCkUils2rQJ69evx4YNG0ZsgIIgCL3RNA3PbmjBHc9sQSiRgdmgx5fPnovrT5sJQz+zS/01u+srl722lozalhYyoquq+m7MNljjd7zQ37jZmQiHKcLQe9wcgXC5SLTNaJoydINB0lRYrfSYSgFlZeRgcIrPQCsc9VWJKhqlP5utp5NXeEzOPhqoj9drUUihk1tURGO2WChClEyq8zoRjkUQJip1pQ587dyj8K1nt+B7z23D6fPKUVss2TgDZciOxeLFi2E0qtUtFguWL1+O5cuXj8jABEEQ+qIrmsLtz2zGc5vaAABH17hx72VLMbfC1efyhyrZqdP1ncvORrHDQetXVaG7wlBv+ivD2leEYzzR17h1OjpHuRzNkPcmQA3LezhhgIp0uN3KgWCj12Kh9/x+VXLWaiUn5HAVjgq7b/t8ygm0WmmbLS3kRLhcPUviknBcB02jDuAjeS1Gsxt7oZNrs9F1iMepRG8sBnR20vGO5/tKECYD15w4A89tasWaPX7c/sxmPPpxqRI1UIbsWPzwhz/EHXfcgT/96U+wyLSJIAhHgBe3tOHrf9kEXzQNo16HL5wxG58/fTZMhr5zQg5XsrO4+NAaCafz0O8DPY3fwjKsfUU4hsvhjNrBGL39jXvGDDpfiQRtJ59X73NUoPf5KEybKkynYpqbVWpPKkXLcnpPInHoCkdsRAeDyiHMZICODmDzZtpXbS05gqWlVLHKaKQGeeEwjXkkrsVo95ToLdhm55bTyXI5um/Ly8nRlVKzgjB66PU6fPfDi3DeA6/hlYZO/GNTKy5YLGXYBsKQHYu6ujqEw2EsWLAAl19+OU488UQsW7YMtbW1Izk+QRAEhJMZ3PnsFvx5LXVFnVvhxI8vXYpF0zyHXO9wJTuDwZHRSFitZBiP1mz24aIu8TgdSzo9OKO3v3EnkxQN2LEDaG0l499mo4iEyUTbLy1V22EdgM+nohFMOEwVohwOGhOXo+X0npKSg8vG9sbvp3SroiJyUNjRcTppG8EgrZvNUk+N8nKgvDyBqioar802vOtxJHpK9CWoL0wny+XIweB0KEEQRpfZ5U58duUsPLBqB+7623s4bU4ZPDapgHo4huxYXHzxxWhvb8f73vc+vPHGG/jFL36BcDiM4uJiLFu2DC+++OJIjlMQhCnK6l1d+PIf1qMllIROB3x6xUzc9P65sJoMh1xvICU7UylyKGKxkdFIjEbwtj+jtq0N2LuXnnd1kVFdVkYGv8EwOKO3r3EnEvRXVEQz5MkkRQna2oCdO4Fly0jYztv2eqnUbC5Hzo6m0Tj37SOjua5OGc0mEzkAoZDSS/RX4ajwOvr99FzT6M/tpnXTaXrd5aJxtrYC4bAJ7e1K1D2c6MKR6ClxqEIAFgsdo80mgm1BOJJ87vRZ+NvGFuzujOEHz2/D3R9eNNZDGvcM2bHYvHkzVq9ejSVLlnS/tnfvXqxbtw4bN24ckcEJgjB1SWZy+PGLDfj163ugacD0YjvuvWwJltcNLLl8oKVgvV5adrxqJPoyavN5eq2zk4xRu53ej8fJuK+spOdDNXr9fnIiXC46Bx0d5AAYjXR+uLv1vHnAggW0/0SC0qisVjLy43E6/0YjMH06jbM3djtFG8zm/g1mvo58jbhzNzuMRqPSXfAYGxuBYNACi4X2MZzowkAc1K4u2s9wIiMTtRCAIExmLEYD7v7wIlzx8Jt4Yk0jPrKsZsC/QVOVITsWxx13HGKxWI/X6urqUFdXhw9/+MPDHpggCFOXra1h3PTUemxriwAArjiuFt+8YAGcloF/ZQ20FCwbhEdCIzFY+jNqg0F6r7iYIgIeT88oAFdmGorRm0rROvk8pRpxX490ms5ZSQltx2AgByOVAhYtokgJny9OrUqlaLlEglKiPL0y14xG2nZdXf9j0+spGtPURPszGCjlqrRUibb1ejp+Pl8U3cnCbFYN/oYaXTiUg5pM0jbb2ujccLrXUO+biVoIQBAmMyfOLMFly6fhD+804bY/b8JzN57Wr65PGIZjceONN+LOO+/EH/7wB3j7Kh8iCIIwSHJ5Db9+bTd+/OJ2pHN5lDjM+P7Fi3HWgorDr9yLwc4Aj6ZGYqj0ZdSGw2T4s5Yhm+0522+3k7EeDtMxDtbozedpeRZux+O0j0yGHA1No+cuF6VehcN0fguNdYtFdYXO5VTaWShE4yvUWdhsPfUaQM/roGl0PB0dtF2TiR59PnIibDZyovR62henjOl02kHHxg3+wmHazkCuc38OKvebiEbpfHq9A6t0dSiOZCEAQRAGzm3nzse/tnZgR0cUv3ljL64/beZYD2ncMmTH4pJLLgEAzJkzBx/+8IdxwgknYNmyZTj66KNh7utXXBAE4RA0BxP4yp+34K09fgDA++eX4/sXL0apc+gW/mBngMeDM1FIoVGbz1MkwucjYbXLRbPxvaswGY1ksLe0qE7XgzF6efY/n1fahXRanZtslt4zGFS/iFRKia97C80DAXqsrKR9R6P0mMuR0zBjhopk9CVSj8XoOKur6ZiiURpDVxct7/GQ4R0Mkuais5N6bJhMBzsWuRzpL5JJJUIvFMH35VT256By1IgjRXw+hxoZKXSmxqOTKwhTmSKHGbeeMw+3/XkTHvjXDly0rGZYv02TmSE7Frt378bGjRu7G+Ldfffd2Lt3L4xGI+bNmyc6C0EQBoSmaXirU4dv/HQ1oqks7GYD7rhgAS4/rnbYdcMn8gwwG5Zms9JZpFI0Q88pQMEgLRuPq3SpbJaMb6dzaEavxULpTj4f7VOnI8fGfqA/VDJJ+2ZnxWIhB4F1H72F5gYDsHs3pWzV1dH4OzooamCz0Vh37aLxRqM9141GlRNVXq6WjUTIgXK76ZhaW2kZm42OldKidEinVbQnmaR0qmiUxOhOZ08RvNNJ2+xL6N3bQWW9Ry6nyuYWwpGRw3UX53H1V/HLZhvw7SIIwihz2fJaPL5mHzY3h/GjFxrw/YsXj/WQxiXDKjdbV1eHD37wg92vRSIRrF+/XpwKQRAGRCCWxtee3oAXdhoAZHHMdC/uu3wpZpT0o5QdAqNdCnak6W1oZrPU/TuToX4NRiONv7OTjE+9ntbhNKNgkJYFaLlCo5c1D11dSivRF8XFZMjv36+E2GazKmfLDQO5eRtXK+IoQqHQ3OUikfe+fbQ9TrXifhOhEDkjsRi9NmeOigwYjWS4JxK0fjxO23O5VPWpWEw1jTOZ6K+xEejqsmH/fjp+r5fOSzCouqoDB4vgp03rW+jd20GNxchBKSvr20HlwgD9VboqvNajXcZWEISRwaDX4c4LF+KSh1bjqXf24+oTZhy25PlUZNCOhcvlwrJly3DsscfimGOOwTHHHIMFCxZAp9PB5XLhtNNOw2mnnTYaYxUEYRLxSkMHvvKnjeiIpKDXabjxjDn4/BlzYBwlUdx4diaYvgxNbo4GqJl6TuOyWmm5eJxe7+ykZc1mMtK5yzX3euBtcYSjurr/jtezZpHDYDBQhGHvXjK8a2pou8mk0jywod5f9SSrFaivpzK1bjcZ+oEAOS1OJzkn771Hhntbm+rVoNeToR0MqvS12lpyKFhgXlVFlak4+uB20zbzeR10Olq3q4vGVlLS09EqFMGHQhTd4SgIR3ZKSnqmKLEjxE5NNquqi/G5HGj/kyNRxlYQhJFjeV0xLlpajb+ub8G3nt2Mpz97snTk7sWgHYsf/OAHePfdd/Hvf/8bP/3pT5HP52Gz2bB48eIezkZhGVpBEAQmkc7h7ue24rdv7gMAzCx14CNVIfzPypmj5lRMFPoyNI1GMnzzeTLAy8qUqDkYVFWQKirI8LfZyMFwuchAZZFxKkXrc9pSKET/954V58hOJkNGe2kpRRG2baNZdE6J4vKx7OQUloXlrt2FzhxXiZo2jQzxVKqntqLQkeroUMfJjhCnBeXzZNCzI5HJ0P64W/isWXT+Nm7MQNOUtkTTevbdSKV6pphFIuQssPNhNJIj1NVFx2ow0PiSSdpWRQWNw2JRzf7YIRpIadiBlLEdaDqVIAhHjq+dOx8vvteOtY1B/HV9Mz68bNpYD2lcMWjH4nOf+1z3/4lEAg6HAzfccAP8fj/efPNN/PrXv0Y6nUaOp9gEQRAOsGF/EDc9tR67fVSq+uMn1+HL75+Ff7/0whiPbOzpz9DkcqpGI6UiFRrsXFLW66WIgNtNr7MGwGxWs/JsxIdCZPRWVNAyra20nXSaDGKfTxnc7DSUlgInnkjLd3bSNpNJNbvu96sysLGYcgi8XtqXx6OqRHGVJ7ud9pnP06w/OxWapjQYrCMxmZSzwuJtgI7BZiMdRiCgnBGrFSgqSmPaNBpXSQlFGXg9gLbX3q7Sp7hnRyiknC5Od3K7yYHZs4eOe9482i87PXY7HXdnp0rLOlxp2N4Vv3qn6g00nUoQhCNLpceKz58+G/e80IAf/LMBH1hYBZv50A1bpxJD1lgAgO3AFNKVV16JxYtJxJLNZvHee+8Nf2SCIEwacnkND/1nF+57aTuyeQ0VbgvuuWQJVswtQ4YFAVOc/volWCxkrAaDqgRsIdxxm50KQImN29uV4DiTIUOVdRfJJBnO+/eTIc/GtE6ntA3pNK2fzZJzUFJC48jnVdnXUIhm9VMpcgaiURpDIkHb44iHTqcqWSWTZIgnEsqY5qZ8dXXkDDgctF/eTlkZvc9Vn2w2JcB2OMjoLy2lMRVqTPJ5pQGJRlXaVjisjiuZpG05HHTMO3fStaivJyeBO4lz5IL7hFRW9kwxCwRIm1JVdXhtBFf8ikaVZoPPBY+F06kmij5IEKYKnzy1Hk+saURzMIHH3tiLz66cNdZDGjcMy7Hoc4NGY7eTIQiC0BxM4KYn1+OtvVRG9vzFVfjuRUfDa5ey1IUcqqGf10vRjEiEjGFNO3TZXBYbAzSbz9v2eJTGoK2NDGqDQc3kh8NkxM6ahe6u1Z2d5ETodMoB4fe4H8XOnVT5qbKSnrN2gqMPySQwezY5Jo2NJMS2WGjcvA2/n9bjErmsr+Cxeb00DoeDtut2q7SuQICch0yGtkHr6tHerlKdkkmV7sR9Nbg8LetVOBrT3k4OTXExpU8Bqqyv201OQCpF61RW0v+5HL3O6VCHg6MSDQ20fO/+Hu3t5GSxPqR3xSgRdQvC2GE1GXDzWXPx5T9uwM9f2Ykrj6+V37QDjLhjIQiCwPxtQwu+/pdNiCSzcJgNuOtDR+PiY2pE7NYHh2roZ7WqakgAGZ6HK5trtSo9Awu+ebabNRecx59IkGHOJVS5s3UoRM5GezsZ9vv2kcNSXq72o2m0jUyG0qqqqmhMhWk8PJvf0UGRBa7WNGeOihi4XOR4sCicu3rn87SP5mZaZsYMVZmpq0tFRWw2KidbWkpOjd9vQShEjkA2y70tVFSlq4uW41Szri4lkgdUWVkWk/NywMG9QywWinQYDMqx6R1Z6C/q0N9HIZ2m857PS8UoQRiPXLSsBr96bTe2tUXws5d34hvnLxjrIY0LBu1YXH/99Tj22GOxfPny7sjEkTIScrkc7rzzTvzud79DW1sbqqur8fGPfxzf/OY3xVARhHFENJXFHc9sxp/XNgMAltZ68cAVI1tGdriMx/SSQzX083jImOyvkVtfcE+KQEAtm0opjQPrA9jQbmujfba30+sWCzkvRiPtr6ODxsiC4lSKHIXNm8koZ+O8vl6t53LRMhw1yOdpTO3tFCGYNYv++HizWdVTorycHltayGmIxWh7Xi+dF27+V15ODgOXpdXpgHjcAJuNjtFqJQeDz62m0ThtNqoy1dhIEROHQ3UKdzrJGUkkVOqT00lOF0dUmGSS9supUoWRBaDvPhWcnlZXR2PkxoF6PV1rg4GOacYM5WhKxShBGD8Y9Dp89dyjcN2jb+M3b+zDtSfXYVqRfayHNeYM2rHYsWMH/vjHPyISicBopNXvuusurFy5EscccwyWLl0Ku310TuwPfvAD/OIXv8BvfvMbLFy4EO+88w6uu+46eDwefPGLXxyVfQqCMDjWNgbwpSfXo9Efh14HfOH02bjhzDkwjZOKT6EQGYfcLG88pZf019DPaCQjOJ3uqaU4FOw4ORxkGLe2kmHMs+qccuRwkFGcyZDhm0iQoZ3NKmE4942wWlWqjsdDxv7+/fQeOyi5HL1eVkbRi1RKlYYFyCGZMYPeb26ma1FVpZwQjpqUliqDmh2JYJBSrmbNUo6H202vt7XReHU6Ss3y+82IRJR4nB2ZdJqOwWCg5RIJ+r++XjlQej1tx2ymR0598nrJueIeGizw3r2bntfV0TFwZCEQUMv1jjoEAjQWPoZCRxeg688akd5IxShBGB+snFuGE2cW483dftz30g78+DKpiDpox+I///kPAHIw3n33XaxduxZr167FHXfcgWAwCIPBgLlz52LLli0jPtg33ngDH/rQh3D++ecDoCZ9v//97/HWW2+N+L4EQRgcubyGn728Ew+s2oFcXkON14b7Ll+K4+sPUx7nCJFM0sw3G5PcMdnpPHR6yZGObBQ29PP7yegPBskINZvJEJ05kxyNvsZV2GAvHlcGqKaRYc0N9SoqyLhnMTanPLW00P+lpbQO6xfCYdo+923IZGg/Tict6/Opc5rP03YtFnI8olHV2C+RoPW5K3hXF/3V1yuxOQu82ciPRsmYrqmhZcJhld7F43W7yUFh8XgwaOleb8cOlfrkdtM5cblozA0NNOb581WVp9JS2kYopKo/cbSltpZe48aBHMGYMaNnh3OzmbYNUBUpht9rb0e342M297yGiQRdb4ul714Y/VWMGo9ROEGYzOh0Onzt3Pm46Gf/xZ/XNeFTK+pxVOUAZ38mKUPWWMyZMwdz5szBFVdc0f3anj178M4772DdunUjMrjenHzyyXj44Yexfft2zJ07Fxs2bMDrr7+Oe++9t991UqkUUlznEED4wK9jJpORajRDgM+ZnDuhkKZAArc+vQnv7AsCAC5YVIm7LpwPt8102HvlSNxT3Hhu/34yjFlk7PdTek1FBRmk7e0qvaTQQGdj7UhGNsJhYNMm2n9xMRm/iQQZq9u2kSHucPQcF6C0CZxKE6PKvnA4yKhOp8lw1+noHHR2kgPR1kbHy7oKs5mMV26GxyVqQyHahtFIzgVnoWYyaox2Oy23YwdtnyMENhsdT0sLpUNxad2GBnIokknantNJyzU307mfM4ecIC7Jm07T/kwmGkdFherQ7fcDZnMWOp0O+XwWuRyNQ9NUj49QSFXg4jKybjedR6ezZ2neYFBpUIqKaNxcPpf7Z7hcSnjPpNPqXEejBxv67NB2dvbUrACqVwdXs+r90eAyvbkcvTfW9+pUQX7/hL5YWOnABxZW4Pkt7bjvxQb89MqlA153otxTgxmfTtM0bRTHMqLk83l8/etfxw9/+EMYDAbkcjl897vfxW233dbvOnfeeSfuuuuug15/4oknRi1lSxCmEu/6dPjDbj2SOR0sBg2X1uexvFTrV5Q6FnR1WRAKmZFIGGEyaTAY1NdePG6E3Z6By5VBJqNHUVEKuRwQDFqhaTpYrVkYDBpyOR2SSSNMphxKSpIwm0e3wcCuXS74fHaUlia7X8tk9AiFzOjstKKiIoaZM6M9xqXTaUinjXA6MwgEzIjHTbDbs8hmdYhGTXA40igvT6GlxYZkUg+bLQefz4Z4XI/mZhdCITNiMSPyeR2Mxhz0esBuz2LOnBDM5jwcjjQ6O23Q64F0Wodk0gS9XkMup0c2q4fZnEU2q0c6bUAyaTiQdqRHPq+H15uCyZSHTqeDyaQhkTBC0zTodBoyGT3s9iyczjTCYTOyWcOBFCIdDAYNdnsKbncONlsGZnMeFksO4bAJ8bgBBgNgt9NYYzHDgSiHhnjchJKSJFyuFBobXdA0HTRNd6DsbRoeTxr5vA7xuBEdHRbMmhVBTU0MJlPPn8SODis0TYPNlofBoEGv12C1ZuFyZQ5UvbJ3n2M26k0mDamUDj4flWQvKzv4ftE0IBQyw2Cgc9L7PotGDbBYNBQVpdAbvpYlJSmk03p0dVmRyRgO2gaQR3FxChZLHiaTNMQQhNGiJQ78cIMBGnT4yuIsasaPnHBEiMfjuOqqqxAKheA+TD7uhKoK9Yc//AGPP/44nnjiCSxcuBDr16/Hl770JVRXV+Paa6/tc53bbrsNN998c/fzcDiM2tpanH322Yc9OcLBZDIZvPTSSzjrrLNg6l1wX5hSRJJZ3PX3rXhmRysAYFmtBz+6ZBGmFw/OYR/teyqVAvbuJUOuvV31UlD7p2VKSyl/3uulWWqnk6IXXm/P2eZgkF4bDeEsp7JEo2SgLlumeivk86pxncFAM9rLl6tKUR0dNGNdW0vH2tREj9wzIp2mSEQup0TiBoOqQlVWBixcSGPIZGhZi0UJx1lXoNfTDHsySZGI0lJKQdLpVMO9fJ7eT6dpxpxF4Tx7brXSe1y6Vq+nCAz3rWDtgMejKjax/mTOHDr/DQ0UadA0VYbW7+dZ/iz279+KOXMWobjYCLOZthmLURpZZaXSb6TTtJ1586iKlt3eUwtRU6Ma/fHr3A+ktJRS1bikbWEfCrudIi6svegdsUinaZ3KShpX72iD3a76gxSOiffNaXstLeqeZJJJOretrXReKislgjESyO+fcCg25Tbguc3t2JirwafOG5jWYqLcU5ztMxAmlGNx66234mtf+1p3+tWiRYuwb98+fO973+vXsbBYLLD0kWxqMpnG9UUc78j5m9q8u8+PLz21Hvv9Ceh1wA1nzMENZ8yGcRgC7dG6p7JZ1Y2ZjUljwTcfG+ltbSqv3WwmozEWU6lTbJBxedR8fvh57GyMctdrrhwUiVDuPhvL8Tgt6/NRyo7XS86HTqca6jmd5FwYDGRsF2oh7HZatqWF3i8vp7+iImDXLtrHjBn0PBSi7en15JBxOpXdrlKB7HYaj9Go9A7sTOTzND5No22UlNB54spQdjuda9ZdlJWRQV9bC2zdSvtOp2mspaWq+7bHo0ruWq10ngpTmnI5GguLng2GLAAjAgET/H4y0lkoXRisDodp/xUVKlWsUDRfWkrXnzGb6boEAqrvh89Hy3AfCr5vABqb03nwtY9GVVdzl0ulX9ls6r5yuQ4W8peVKQeBK215POo+SCaVQ1JSos4PdyyXMrXDR37/hL648f3z8Nzmdjy/pR27uhKD0lqM93tqMGObUI5FPB6HvpeSzWAwIN9X2QxBEEacbC6Pn768Ez/5907k8hqmFdlw/+VLsbxufAi0+4Kbw/FMMlc0YrJZMtw0jWazeabY4VBaAS43CvQUzg5VLNtbYM1N6KqqVHQgGgU2blTGMB8Hi9Ct1p4OEu+fnSOuZMTai507ycmYPZv2mUjQMdXUkIEcDtMxWyxK78DHx9u3Wml87PBwfn86Tfvp6KBtc1laroQ0fTqdxz17VLfteJy2VVZGyzQ20msul2o4V+gkaRqNkXUYPF6ucBWN0p/BQNtpaSnCMccAc+fScu+8Q9vw+Wh/XNo2lyOnym5X/SryedWXo7/r6nDQmDnaw6V7jUblPLnd5LD0VT6Ym+K1tPTfAK9QyN/XfdZXt/ZgkJb3eFSPkcKKW1KmVhBGh3mVLpy/qAr/2NSKB1ftwM+vPnashzQmTCjH4sILL8R3v/tdTJ8+HQsXLsS6detw77334hOf+MRYD00QJj37/XF86an1eHdfAABw0dJqfPuio+G2jt9ZFqBn4zmvV6WJsBHY2UkGaV0dvc/pPtksGWxcRpXTc7gbNEc4BtsRmYXkySQZm1zFCGDhMc00FxcDW7Yow1vT6D2TiUTo9fUqDQpQKTSJBI2zUD0Xi5GxX15O2wiFVD8Mp5P2l0jQctQDgo7XZlMlacvKaDm9ns6Z16sqLcXj5DS0tdH7lZX0PkdNkkkyZrmPhNmsIhrsKLS20v7zedovoK4RO1GRCJ0jviYVFexEKEeQHYJQyNx9fbxeeo/Pvd+vHKS6OjouPoeFhjsb7X0Z9vk8jWfWLDqeYLBnL4rKSjqOmhoVjeKoQ1GRcmD5PjhUA7z+nJve3doLe5QAKlrH83FSplYQRpcvnjkH/9jUiuc2taGhLYJ5la7DrzTJmFCOxU9+8hPcfvvt+NznPoeOjg5UV1fjf/7nf3DHHXeM9dAEYVLzzPpmfPMvmxFJZeGyGPG/Fx2Ni5bVjPWwBgxrChIJ+j8WI0OQDemqKkqHYUOuMLJhNKpZdqCnzmEoHZF5/aIilffPqSwcHSkqUlWY9u2j9RwO5dBwzn9hozq/nxwHk4n+t1ppjH4/jY0dJa6Mxf+Hw+Qg+f3kPLABrmlqOxaL6qmQTNJ6RUWkWXE4aNxcNMRqpaiATkeGtddLfR4AGnsiQcty+lc4rAzjxkZVgpWrWnEvCXZa1q+nCAinonFjO67UlEyys5dHU5PqixGJ0HbcbrqmxcV0nc1mGkdlZU9jm53LpqaD9RNeL70G0PpWK61fuBw7cGazGluhc9LSou4DZrAN8Hp3a+eO4EYjnV/WXvBx9VemVhCEkaEwavGTf+/AT686ZqyHdMQZFcdCr9dj5cqVuOeee3DssSMXCnK5XLj//vtx//33j9g2BUHon94dtI+dUYT7L1+K2kEKtMea3o3nbDaVK89lPw0GtXxhZMNkUqVZOUXIaj3YIGRDnIXIfcHlUrnMaqEhCKiZeJuN/j/qKGDDBnIuNE0Z65WVykjs6KAIgtFIr5nNtK7BQMZlNEqGM5eR5Q7eHAHg8qs6nUqj0TRKD4rHaazs6FgstGwoROuGw+REcNSFZ82NRkq9ymbJCQiHaT+plGoGp9PRGKNRGid3tg4GVTpROk374WiKy0XHr2lkmHd0KD0M6w/sdnJ48nldt+aDj4Fn+DntzOslJwkgx5KjDRaL0ip0dZH+g/UToZDqseFy9ewzUeiYpNMqBa/3e73vg94URhb4Pukv3a6wWzuXAG5sVNoXg0E5o4VpgYIgjA5fOGP2gahFKxq74pheMrF+L4fLqDgWjzzyCPbu3YvPf/7zePPNN0djF4IgjDKbmkL44pPrsMcXg15HId4vnD48gfaRpPcM8aHy1dlpYHE3z0AHg2TAsvjWbqfZ78KCcsmkSoNJpciABshw7R256J0Tz2kqHEHg6EjhmCoqKBLB6U3c9M7nU2lEZWXKuOb8/aoqEl9XVqoGds3NZLQ2NalGdiUltJ/KStKYdHRQWlM2q1K/HA4al9VKjw4HpRt1dfUUHvt8av9sHHPEJRwmp8BkonUiEXrdZFJRC5erZ4TIbFbnq6KCnhuNdK45ClNbq4TMmQytazIBJSUJlJSo6AiPHaDnbW001mSSBOyRCF1Xh4POY1cXXddslpyP8nKVbtXWpkTnsZi6bwrvu3CYxtyXM9CXNqIQk4mOr7lZdUQvTLfjNDYuSsBOs89H1y8YJMewuJjWY2eI72tJgxKE0WN+lRsr5pbh1e2d+L/Xd+OuDx091kM6ogzZsWhsbERtbS10vYrVa5qGM844A9OnT8edd9453PEJgnCEyec1PPLfPfjB89uQyWmo9lhx/xXLxk0H7cNRKIzuS/9wuFlfTm9ix2PmTDLS7XYy5thw5X21talqR3a7SmPJ53umRaVSSpTMqT8WS8+0q8IKVrkcOSlz5pBRy9WHWC9hsdAs/IwZPcXonEoTj9PzUIjGUlamRM7cGbusjAx11pc4HLRv6glBjhh3/7bZVLdtTqfh2W+rlQzxTEYJn/l9jvxoGi0Xj6tu3cEgrefxkFHPnbXjcXVN7HY6Vq5wxJGJoiIy+FMpchQ4lYyrIQWDWve55pQhi4XOaVERHZ/BoIx0h0MJ4wHaV2Wl6lje0qLuIdZPlJTQNeGIV2GKHQvd2aAvpLc2ojfRqHJQC8vctrWRs+h0qmgE39vsNNfX0/nQNFXZqtAZKp4YH2NBmND8z4qZeHV7J/7wThO+9P65KHL08UGfpAzZsaivr0drayvKe7UM9fv9qK+vRy6XG/bgBEE4sviiKdzyxw14pYGsmnMWVuAHFy+G1z4xvhR7C6MPpX8ojFz0TpUqFNkWCrK5ozUbhIUVeABlxBYX0zb8fvq/0NEJBMgYnTGDtluYdsWdrjl9iWfcW1spysDVq/R6mhGPx2l7HJFhjEbaHvfAYIO8tpbGHAjQLL3VSlWTuOJVJkPrzppFzoteT45NezsZpj6fii4AqjIWp1TxeeM0LGpeR8tyKhNHEOx2Ms5ZLM6Rj1SK9sFOlsulUrpYTxIIkLNVXKwcRRZ8+/10LffsoTFNn07nLJ1W2pH2djLQy8roOfcu4Y7XTied80iE9mOz0bpmM53DQv1ETQ05HTt30j3mdNJr7DDG47ROofPHJY27unoeA9PSoqI0DOtbOjvpvE6b1vPeLi2lY6yuVo5jX2Ly8dS4UhAmKyfPKsHCaje2tITx2zf34YtnzhnrIR0xhuxYUMfUg7+hotEorFIkWxAmHK/v8OGmP6xHZyQFi1GP2y9YgKtPmN7n53y80DutqVAYzfQWxPY29Pua9e0vp71QLKtpPSvwAKqEqsVCBpzPRwaepilHx2AgMfPmzWT0cvrNnj2qDwMbsiUlNNYtW2hflZUqvWb3bjIsIxE1i85wyVWnk/bBs/qZDL1msdDYXC46Zj4/HR1kWLOuhFOLamrU8RQXK4H4zp1Ku5FI0DJsvCeTtB+jUfWOcLuVIxEKKY0CO4IsOOZme6wTsNvJcPZ4lJaAy+rW1vasmsXi8GjUhFxORW7icdpuLqeuMTscgYBqIMhOGwu9bTY17tZWOs+sDylMsysrU2WBNU0Z9sEgnavZs1W0gO8/n4+2WZjKFgjQ+KdP73nvdXTQuFi0X9hzhZ1VTq/S6foXk/cl3B5q2WRBEPpGp9Ph0ytm4sYn1+M3b+zFp1fMhNVkOPyKk4BBOxbcxVqn0+H222+HveBXNZfLYc2aNVi6dOmIDVAQhNElk8vj3pe246H/7IKmAXMrnPjJlceM6zJ5faU7mc0qT74vHI6+Df2+IhpsaPVVlpNTdNrayNBjY5E7InMHZDa+LRaa9WbxNZew3b6dZp+dThqX2UwpVw4HjSkYVNoAFlyzUWgwqNl9MqJ7jpXPCUcg8nmKAHR1kWHq8dCYYjElDE8kyFnhErNlZeTEdHWpCliBAL2+axdFhrgJXDBI+2QnTtPoj9OiXC56nsvReDweZfAbjXTOeAafu3nbbPScU5A4lYsNYL2etRTA/Pl0rvfsoW1GIoDZnO02uvn4k0k63+m06pfBvTK44zn3zOByubGYuu5+vypVy2J2jtgUFdEx9E6P4/O8fz+9ztfE6SRno6WFolHt7ZSSxvcvlxJOJsmp2LlTOYz5PJ0jvt6sZwF6plcdSkze3+dIOnQLwshw/qIqfPkPG9AVS+PqX6/B0589eayHdEQYtGOxbt06ABSx2LRpE8wFCaJmsxlLlizBLbfcMnIjFARh1Njvj+OG36/D+v1BAMBVJ0zH7ecvgM089JmV0Z797C/dqbWVDLC5cw/OW2dtQ1sbGaJVVT3HarerfghWqzK0crmes+WMTkfGYnMz7dPrpW1WVCiDrKuLDMbSUtoPN17jlCGbjbbR2qqqIpWXk3HX2Iju2XauzOR2qwgFaxD0ejKGNY3e5whANktjaW2l96mvgzp3LIzu6gLefFNVlGpvJwOZnRmPh7a3f78SEodCNN5UipaLRlUzPbdbXXOLhaIh8Tjtn9N6sllaNpFQx82CZLOZ0rBaWui9qioaYyhEY9Drab3CKIbZTPvN5Wg8s2bRmJxO8no4QpFI0HXiiAAfG1fgamtTRjs7Cek0jauw/0Z7O22HHUrW3bCD0js9LplUjuv27bTN2bNV5S425vm6zphB54h1KuzAskPGjkxHh2qix5Ewq/VgMTkTiyln6FCfo4GWTRYE4dAYDXpML7Fjd2cM7+4LIJfXYNCP3wyAkWLQjsXLL78MALjuuuvwwAMPwN3f9KAgCOOaZze04Bt/3oRIKgu31YgfXLwY5y6qGvL2jtTsZ+90J67KxIZ+Mkm6AK9Xpblwk7aWFjIkQyEynljIzLO44TAZVHY7vd/RQcdjtwMLFtCxcFOz2bPJIGtpIaOPS4PymPbsIUPN6yWjLRYDNm2ifRR2+A6FyABPJuk9r1dFJPx+1YSOezTEYkp7EInQ/u12cljsdjIquTxsOAy8+66KiLDGQdPovLBTw6k9kQg9nzaNzk1HhxJtsybD7abxslCZK1rpdKosL/evsFhoOTaG2eA1GNQyFRUq5UivV835olHlUHV20v49HjoGjjpVVtIy4TCdB7OZtkHnnHR+PPMfDitnhFPYOD0oHFb9PXw+KvNrMtG2uSJWSwtdt6IiVfGLoxNtbUoIHgpRdAWg42htpXPNkTBOd2pvVxEXLg7AlbvYQWDBv9dL54XF6Jzm1NZG6/L1KxST99Xpu1C4PZC0QenQLQjD48lPnYjj714FAHhjlw+nzSkb4xGNPkPWWDz66KMjOQ5BEI4Q8XQW33pmC/74bhMAYPmMIjxw5TLUeG1D3uaRmv3sXf+/MO3E5aJ8+44OGsuuXWoGmjsys6Hb2kpGqter+hPs20cGK4txfT6VvtTergSyHg8ZdskkjYFz8zs76bW6Otq+TkfjYYO7s5OMtVxOpRz5fKraEUco2GDlVKxolJwLgAy98nLaJ++Pox/ptBIP53I0JqdTGet6Pe2fHQjWIuj1KmJhsdA144Z3bW1UZYgNzpISFd1hZ4edCqNR9QUBaH2OzhQXkwGbz9Py2axalo1vm410BV4v/XGfDK6qZLfTNjRN3QcNDXTcrLlob1fRlHDYiooKVVUqmVRlbB0OGjNXsgqHaR2HQxnW3BTQalVN8GbNUnqRUIgiUul0zypTHF3gKlX8nCM9uZyK2tTVqQ7epaX0Opf11enonnS7lX6EU+fYyeQKWgaDqg7GWqPDFSEYaB8N0VwIwtApd1vxsZNm4P+t3offvblPHIvDsWrVKqxatQodHR3I91KEPfLII8MamCAII8+WlhBu+P067O6k3hRfOGMOvnjG8HtTHKnZz971/3unnfCMbWenMsKmTyfjnI3oeJyMQLdbbUfT6JGF1Wzc2WxkFBqNZIR2dgJHH93Toampoe0FArQuO1dz5yqRssFAM+JcqpYrM3F6Uk2NatzGAmZNUzPs3JAtk1FpWBYLGZZs0EejPQXWJSV0THPn0nnz+3s2qANUY77SUtof90zI5WisoZDq3WGxkOGbTqsyrzYb7VuvV8373G7lQGWzSv/idiutQyajNBZWK72eTpNTWFlJTiJXymJHoKJClVktKqLtRCL0vL1diZurq2l5iyWHdJoiR0VFKvWorEydD9aIJBJKW1JfT+fCYlERL+6VwQ5DVxdpHgIBVQ5Wp1O6ilhMpTBx93M+31zdCSCHatYsWt5uV529OZLGzhVrc8xmpQNxONR1MpnokZ2wwxUhGEgfjSPVoVuE48Jk56MnkmPx0nvtaAkmUD2MSbyJwJAdi7vuugvf/va3sXz5clRVVY3ryjGCMNXRNA2PvbEX33tuG9K5PCrdVtx/xVKcOLNk2NsejdnP/oyNTEaJldnIKqzKxHX7ucQmz+izYHn7djL+a2vp9XSatsNlRouKKNrBKTc8+81lU1lIyx2m2aFxOmmWPRxW43W5lJh3925VKjYaVd21TaaeDc3q62l5g0EZijYbRSm4YdqOHbQd7pztctH77EgEAqTRiMVUEzyAjsXtVj0lHA5aJpNRaTydnUr7wZWeWPBrt9M+W1pUJ2w2QNk54PKmHI0wm8l45pQpj4de44pT3OW7qIiM73CYtrVvn9KK8Pncu5fGduyx9BiJ0P7nzAHWraP1i4pUadpk0oBUSmkOZs2iMTqdZPTv3KmqSLHj4fUqR7Gjgwx0r1elGvH15IhORYWqcsXXPBpVkRabjdbL52k7nZ1q3IURq5IS2md5OS3LzhB3SAdUqhxA54QN/7IyWi+R6OnAH+qzdrg+GnxPjGaHbhGOC1OFuRUunDizGG/u9uOJNY245Zx5Yz2kUWXIjsVDDz2Exx57DNdcc81IjkcQhBHGH0vj1j9uwKptHQCAsxZU4IcXLx6xhj0jOfvZn7HB6TeRCBnO0SgZIBwdAMhI3bOHjFiPR5UO5cZ14bAScLNhXVREhiGXeGVnhSMfnDrDfw4HzVbbbDTLXwgLgdk5iUaVocSGflOTmnF2u1XDPq7IxBEfTaOogMFAy8XjtM3WVnqvvFwdE2sluAGdzUb/d3UpBysep+vA0RyAtp1K0Vg44sQ9JgA1m28yUcpOOk0GdTartAQsGOcUM07hYvF3YUdxjoSEQnS+9XoaYy5HzkE+T8exZw+tzxWpLBaKYvBxbNtGUSOrlY6TKypxyVV2JFlbwIJr7jnR0UFOCgvA2cjmhnOZDI3Z46Hr7feTMzJjBp2PREI5aBypsNnovrPZSIvT0qL0KewMNDbSPkpL1XnM51VVLq5StWOH0tVks/RXVkbngYsPcHNBr1eVpdXrB+7AF5ZNHojQe6QR4bgw1fjYSXV4c7cfT77diBvOnA2LcfKWnh2yY5FOp3HyyVOjdJYgTFTe2OXDl55cj45ICmajHt88fz6uOXHGiEYYR2r2k6MBvY2NtjZlRBUXU7ShqUnNnHPPiMZGNXtuMvVstMYlXt1uMtJYb7BvHxkxhYYbN2BjzQHnx3MefzhMBqGx17cn97AoLiYDuatLRUNSKdUsjcdYXExj49enT6ftb9lCRt/MmbT+pk1kGLOI1+mkbXZ00PlhTQZ3W2ahMFddKi5WqVMAGfKRCB0/H4PPR+fQ5aLtsnbC4VDpOyUlZCjv368cqFyOzh2nNrEDmc0qATFHQ1gYzQ5CIqFS0IJBFW1goTmfI+49wY3rQiEySlk3EQrRtQdoGyzUj0Qs3el4AB0Pl7/lcrY2mzovsZjq9eFw0LkoK6Nlliyha7t3L73HTQpjMXXcPPbZs+lcGY2qj0UuR+vU1dHxNDXRvebxqBQ2s5nurWiU7nGnk9YNhWh8rPXgaJ3bTQ4mM9j0pb66zfcn9B5pRDguTDXOWlCBCrcF7eEUnt/chg8trRnrIY0aQw50Xn/99XjiiSdGciyCIIwQ2Vwe977YgKt/vQYdkRRmlzvxzOdPwcdOqhsxp4JLeAJkhHG9/95wx+XDzX4WGhucLsNGIdfoN5vJ0KutJcM7n6eZ/pYW2g9XfNqxg4w81gdwyg9HDlgsyw4IV1vq7KT1mppUBIbTlioryTg2m5XIlnUJoRAdn81G6yaTtJ1164CNG8kYz+XoPPAsfzRK2+dIR3m5MvDmzAEWLiTjlKsncWpRJkPbbmykc8ZpS52dtG4uR0YuG9HsPPj9qmKSxaJ0KKwPicXoPLLYuLiYjrmsTBm4xcX0XkcH7YO1BCYTHRdXd2IjkXta8Hns6CCHKxJRKV+cSsSz7x4PXTerVYm1YzF1nJEIXd+dO1VvjvZ2FeWqrOTGdwYkk7Qf7urNTtf8+Sq1jcc8bRpFSUpK6FrMmkX32cKFKkWJI3MWCz3u2kXXAqDtGwx0rlpaaHuLFtH5Mxho2yze9nrV/VdRodbjqFNJCb1XVtazq3s6rYTzlZU9Z/XZgeemhoVVyvqCu81zw71QiB45BWu0IgaDSZ0UhMmCyaDHVcdT2PP3bzWO8WhGl0FFLLg5HgDk83k8/PDD+Ne//oXFixfD1CsP4t577x2ZEQqCMCjaQkl88cl1eGsPKUavOK4Wd1y4AHbzsGo1dNNXuhKnhAx19jOT0SMSURWFGK6KVFLSswkcd5o2GoGtW1X/Ba+XDD1O09E0MkZNJlq/pYX2wcZeWxt1wObGdMXFZBC2tpLRWFFBr3ElJYuFdBDFxbSfbJaMdY+HjNNAgIz1ykoyHLduJaciGFQ5+fG40kcYjbRvp5OWr6yk/z0e1ZnZ46HjY+eBZ5o571+no+vBURSnk857LqdE3eEwLcMz1Dwrz7P4HFFIJlUKFIvE29qUsxKP0/aMRjqHVquasdfplIbBYKDtcG8Iq1VpFFi3woJth4POXUeHSk0ClNjcaqVtcq8SjhYU9onI5egcAcpBaGvTuqMz9fV0flnrwI3murrU9lg4HwioEq5ms9LwcGQuGqX9ceUwLp3LmhnW9rS307VyOJSomp0Ds5mcFq48tm8fja2yku5jQ0GWhNdL56Gigs47j6+3o84C8dbWgWsWBiL0HmnGk3BcEI4klyyfhvtXbcebu/3Y74+jtth++JUmIIOyNLg5HsMdtjdv3tzjdRFyC8LY8PK2Dtz8h/UIxDNwWoy4+yOL8MElI5dT0F9uNEcrbDYyUvorc9kfrGHobWzw63a7qpRTCKfnWCxkrPn9ZLhVVND4OEWlq4sMLquVjCdOOwkE6JGNUU75KS5WqUYsSOamavk85du73aq8q8lEEQSfjwy1sjIyTN1uyrnnVBizWUUQTCY6jzyTzQY1z7jv3696P/BsO1cUSqdVPwZNU+Jhm005JlyWtLFRzQCHQkrrkEyqGXFNo/OTz9M2olFlAPMMezKptAklJXQ+2Jnbvl3pITRNjY2jFmz8G42q1wTPSLvdqudGPK6cD3aa3G61z8ZGpW/hhn6FJXr5GPi+zOdpTAYD3aOJhKroFIkowTlHnQDqYVFTo/bR1aV6UPj9dF3icXKaOPqTTFKkimf7AVqvuJhSo4JB1aW9tFSlQ9XUqPSzujo6znCYludeGFyMwGikc2E2K0eOj9PvV+mCHE0ZjGbhSFZjGg/CcUEYC2q8NpwyqxSv7/ThT+824aaz5o71kEaFQTkW3BxPEITxRSaXxz0vNODhV3cDAI6uceOnVx6DutJ+8g2GyOFyozm9YrCzn3q9KqdaaGzo9UrwyzPLDKdUxGLkRLAhyeVIeQY9HidjraqKjH7uEZDL0fa4IR6LqFmc7fGo2V/uzmw0kkHodJIBGo/Tc7+fHC52gNJpFQ1wOsl5YHF0S4vqPZHJ0PoWC+2vuZnGWFWlIgFcQchup23Z7cqB4hKu3OfBYKA0oZISSitirQeXveXyp5wuE4mo61VcrITb3KSuqIjG3dWlokeAqtbk9/dsesfrcTO3WEyVhWXBvM2mBOBcXpWrfbG2ZNcuVXUqn1dVlsrK1Mx9c7MSgXOUJZ0mgx8AEgkLiospjYm1J+m06mrOs/4lJeSgcEO+mTPJGeR7t61NNUoMh+mcJpM0Nk6Fs9uVk5tMqs8Ep7LNnk3Xme/FXI7enzaNli8pUeWP02mlHbHbaR/cl8TjofFxIQN24AFyKior+/5cjifNwlgLxwVhLLl0+bRux+LGM+eM9XBGhZHJjRAEYczY74/jht+vw/r9QQDAx0+uw23nHTXiVScGmhvNBtZAtqfSIvLdugMu5ZpIkDHFYt3qajJGbDbVNbuxUUUiOOWK12Vjb+tWMs6Ki5VomMuh7t1Lr3d20n5Yz8CpK3o9jdFspplmdjJCIdpuebkyIBMJ+mttpfdmzVL6iZISMiwNBjJoWbCtaWqsTicZlbt2UeO35mY10+5y0Z+m0Xi4EdvMmWSgs/Ygn6dz5PWqhmrNzcop42AyR094Vruyks7Dnj1k3LKxmkio5To7VfSCy9BydahgUHUDd7nIkOXjMxrJII7HlePI6UUcwchm6XyXlal7TKej8+H3qzK9gIpAALQe6SmUs8hOLTt1XC6W7zfuwB0K0bXgaAU7pm1t5GiwMJo1HUVFND52tLq6VHNFk4nOITe1q6pSDg+Xs9U0Vb0qm6Ux7N2rihKw+J/LFnP0j3tlcFqe1arSo1hH09ravyE+HpvdjaVwXBDGknMWVsJlNaI5mMCbu7tw3AzPWA9pxBmyY1GotyhEp9PBarVi9uzZ+NCHPoRi+YYQhFHj+c2tuPVPGxFJZuG2GnHPpUtwzsLKw684BEYqN7q3RiOfB7q6LN2z/Q0NPWfJOQJhsSiRNndIZm1ALEZGW2urynnPZskY1uvJKWHDkTtpswHK2+DqUry9zk41q88GIleVstmo7Gk0Ssarz0fHwukmXAK1ooKMp/Jy2n40Sv+Xl1M6DkcFeKadqxo1N6vjZONSr6f9d3SoDtpmMxnyXGKWe0LMnas6SvPr3KHablcVs7hbNaA0FlxulQ17bt5WmIfPVamqqlQPhWSS1rFaVQ8P7lPB22dno6iIjiWd7nl+ObLBx8TaB9YwcPNA1ivwulzOlsdGOgdTd5Qmk6FxctoUNx3s6qJrl8lQepvFopwo1oA0N6sKX6wzqaujcUYiqrQxO7h8HDZbz/uMnQDW1rDjyueZO3VzU0aPR0Uzpk1TmhKm0EmYaJoFjmwerkO4IEw2rCYDLlxSjSfWNOJP7zaJY1HIunXrsHbtWuRyOcybR80+tm/fDoPBgKOOOgo///nP8eUvfxmvv/46FixYMGIDFgQBSGZy+N5zW/Gb1fsAAMume/GTK5dhWtHoicEKc6N55rww3WkgudF9aTSoC7UZ27crIysSUakxnGfvdpPxxo3LXC4yKrlXABso7Kxwc7JZs8j455Qju10JhTntpqiItpfJ0Pj8ftXvoryc9svRAc7F5xQtFhnn87QtnpFnQ5JTUTweEuy2tND2IhFaLhCgvx07VBSgrIz2zU3RCjuNc8SipobOSWcnnYeqKlqnokIZuGyYc6pZLEZjZZ0DL9PRocrTcnoKa0F45t1gUA6QpinxeGUlzaCzMc2VqHI52hfrR7hrOBvnHFXhTtws1PZ4VISD1+XyqizW55Q8i0WlXgH0nO/LTEbf7WwUFdH91tlJy5aX0z3U3KxE7tx0jkXPfj9FxLjkMOtr2tvpXtLpaAysseHu7Pv301imT1frZrOqHDI7JezsJZM0rrIy+uN+INlszyjFQD6XE0mzMBbCcUEYD1xy7DQ8saYRz21uxTfPmzfWwxlxhuxYcDTi0UcfhdvtBgCEQiFcf/31OPXUU/GpT30KV111FW666Sa88MILIzZgQZjq7PHF8IUn1mJLSxgA8D/vm4lbzp4Hk2F0LQcWhe7Zo7oJc448p8f0lRtdaDgUajS4ck5HB9DebsfLL5OhPW+eMugdDmUk63Rk3B34uoGmqa7YgYBK0/F6yXD3+WgbnI5UV6cMbL9flT3lCEBzs5oV5zKkPOvPKTdclpZngDlv32hUM/NcHpWNds6zZyOU9RBcUUnTlDaDIyDxuDJ0ARW90OlUXwlOGwuHyRDO5+nR6+0p5uZeFrkcHQdXPuIIAxu47NSwfoBLlrIAmo8xn1fH2tFB+6qsVOks7AzwNmIxum41NcpR6uykZd1ularjcKjIDh9HPk/Xxu+nKAOnxplMSrDM6VZmsxJS53IAoHUb1SyY5lQ5QPXKAFSvknRadVz3++ke4hK4XGnJ66UUJquVnDmTicbPqWjc54LF13xPsPHPXcdZiK7X0/5276Ztut10r06bdmhDu/BzNZE1C+N1XIIwWiyr9WJmmQO7O2NYta0DfXxsJzRDdizuuecevPTSS91OBQB4PB7ceeedOPvss3HjjTfijjvuwNlnnz0iAxUEAXhmfTO+/udNiKVzKHaYce9lS7ByXvmo7rOwNCgbm5yWA5Dx1d5OqSSFmY+c8tTVpdKQQiFK7eDyp11dZBwmEkZUVtI+9u2j1+x2MuJsNlXhyWSifXD/Bs6ZLymhfQaD9FhRoToWc+Udi4Wch/37yahjQ27GDFo2laLx8Pomk0qt4vU5ktLeTttm3YHFQstyKdVwWPWFqK8nZ4kdjdJSOp62NlquslI1qHM66fiCQdoW5/kbDDS76/erjuKplOo0zVWaUikak06nUnySSTpmjkDY7TQWFlBzuhlHFThth685P3L/Bn5fpbEpjQTnyXM6WjqtNAHsILIDw8uxqJurY8VitI9C54W3U5gexl2+eaabIzDs+KRShu5+GXw9WHfR2ak0DHz8+/apfhmhEJ2/YFA5E9wYkPU9XMFK01Q/FINBRZs6O2k9o1FV5Coqom0Wir+5opnPR+l1ixbRPdufwd1fuWdANAuCMBHQ6XS4cHE1Hli1A//Y1IYPl4z1iEaWITsWoVAIHR0dB6U5dXZ2IhymmVSv14s0lxkRBGHIJNI53PnsFjz1DuVZnFBfjAevXIYK9+glI/c2YFhHMGOGMq64IhHrC3gGOJmktKCODlomkSBjnBuHGQz0Wi7HgmoT2tvJ4GxpURV6KirIEGdxcHU1bRtQ6SSpFBnWLFDmmeJwmLbBYvOmJjXOXI5mobnJWDBI++bUDNZTuN10/DqdMmhZ+5HJKGPTZlN57l1dKprAY9yxQzkAXBqVZ5LTaTI6DQb645nzSESda+7HEImoNCjucB0KqdKnzc20j5oalR7G1yOTIWOV06H0elUhi1ObOIWJdQlckYjL5XJakstF28hmlXPH9wI7Ldzvgs8/RRGUcDuVUlEYbjDIlab8ftX7go9z586ezoTJpHQKhSJzo5ErTuWRzdL9FAjQfcTi6K4u1WODnSY+L/v20X3Lzua6dXQ+y8uVroWvcy5Hr9fU0Hk3GOga8LljPUU2q6Jtzc3q3otEVAoaRyvY4evvM9lfuWfWtwyl3PNoIClO4xu5PmPLBYur8MCqHfjvri6cM8lkFsNKhfrEJz6BH//4xzjuuOMAAG+//TZuueUWXHTRRQCAt956C3PnTs46vYJwpNjeHsEXnliL7e1R6HTAF8+Ygy+eOQcG/ej1i+ltwLBeIJdTVYSKinoKoHn2l0XW+/erpnmsKYhGaVYWIAMzmyXDLJnUdzdus9lUhZ9IRM22hsMqTYhn8jkFhnPSPR4VWeAcfv7hZAeCZ65rakjkzBoGTuPhRnder0oxSibptWiUxs3LA2SgcppNPK5mo3lmntO5wmFg/Xo6Br0e3Q0BC0uQskHOuobdu5VBzqVbKypoGTYGODrB5UltNmD1ajJYeTyc9sQOBne95nPIla+4+lIqpRrEseiXoxhscLMAmYXXbEwXVmzi1DPWgbjdlD7Ejkg6rUTzXDqYH51O+uO0Lx4ToLQU6bSKbLBQnNPPLBatu3wrlx1mIXRREZ2zjg5V1cvtpv1ZLBTRCgaVM9nZScsYDErgDZATu3Sp6h/C1Zd8PiX0N5uVVmLPHjr3tbXKkWLH0uOh5bu66Hz2ZeyNVrnnkaSviMrhGvUJRw65PuODORUuzKtwoaE9go1+HS4Z6wGNIEN2LH75y1/ipptuwhVXXIHsgSLiRqMR1157Le677z4AwFFHHYVf//rXIzNSQZhiaJqGP77ThDue3YxkJo8ylwUPXL4UJ88uHbV98ixWW1tPA4ZTWLgUZjDYs2Y+N2nL52kbTU1kHIbDZKRxc7l0mhyLdJpSPoJB1hno4HarvPOyMjKM2BHQNPoxDIUo551TaDIZ1Wlap1PiYE0jA5IF1i4XOzBqtri0VIm/OcWmqUnNsPt8ZBA6nWS0NTXR69yYrLA/QUcHjZ1TT9jY5cZvqZQSWvPsNKfTsPHPjg2X9WXtgMWinA42mktKVE79jBl03vfuVc4bN8Jjslm1fqGjwIYFN9pj8XVhZS2DQaU9AcqRzOVUihugIlg8q8+vsxHOFbk4hY4dUZdLNYZzuZQTxtWZOOWIDXcWZBuNdL5YHwKocsBut9LGGI0qwpJI0HWaObNnqWDuWs3nlTU1Op1K0YrH6b1p09T9qdfTZ8Vq7dkckqticWUsLhnL55w/M+ykuVx0Px7uszmS5Z5Hg/4iKgNt1CeMLnJ9xhcXLK5Cw0sRrPON3iThWDBkx8LpdOJXv/oV7rvvPuzevRsAMHPmTDidzu5luDO3IAiDI5rK4ht/2YRn1rcAAE6bU4r7Ll+KUufoTEEWzmIlEqr0qc2m0k14Fp2FxoV18QsrzyQSSj/BKS6c4sEGYzxORjhrE8Jhc3cVHZ6NLyoio2/DBpXGY7GosqAskI5EVOO0eJz2y0Ytly6NRlXDvKoqlYbDqVic6sNNxLhnQiRC2yssu8rZnZpGRhxXJ9q1i46FZ59Zk8AdvDmCwhGP4mLqWM3VfLxe2i/rAgwGdSwGA20zGKRluIoQi8G9XtWzgscGKMObU5pYu2AwqLQnpUmgdQpLlxoMPcu5snjb66Vxc1oYG8mF0QNA7Y/PNc/6R6OqxG8goJxE1rBwWhN30Wbng6NTnBLFx8KN9LjCFKVj6bob57EjxPqXfftUlSmHg5yyZJLW6+xU9008rgywkhL6PxpVepLWVpWS5ffTGGbOpNfCYXIW3G51nmbPpjFyF3UufsCRNp9PldrtTX/lnnkyoLCPx1hxuIjKeGrUNxWR6zO+OH9xFX780nZsD+ngj6VR4e2nZvQEY9gN8pxOJxYvXjwSYxEEAcDm5hBu+P067PHFYNDr8OWz5+IzK2ZBP0qpT8kkpdwkEir9hBuz5XJKh+B0ktHsdiuRLFNYeYa7V4dCZIAGAqqWPhvBgNofGZx5mEz0A8dVf3hGP5+n1JGiItJpNDaS0TZ7NjkZsRgtu2OHqnbEYystVaLkGTNUtIIrUvGxcU+MVIqMc65oxF2WOa2JDVsuTZtOK6eqpITGwbN/gEoxam8ng5X7VFitylnh5ywyTiRo/5wKxhESo1GdR943O2zBoEohMpvpOTsC2az6n/UEDDsUrLPglCl2wtgw5xQj3i8b4XxueD+ASlfi6kccUeC+FSzGBsjJ4nPAkRFOJeP1eLyc7sZpTWyYM5zSxfodTdN19zLhFDu+1m1t1C/FZKIO6lw6t7OTrl9Jier5wR3Ey8qUiJt1IjwWXoYrU5WXq/2yLsZgIKfD4wE2b6ZlHQ6VEhgK0fb6qwbVu6xsMqkczUKno6ZmbCIWA42ojKdGfVMJuT7jj5llTsyvdGFrWwQvvteBa06uH+shjQiDcixuvvlm/O///i8cDke/DfKYe++9d1gDE4SphqZp+O2b+/Cdv29FOpdHtceKB69chuV1o1fSJZkE3nuPNBGcUsQlK7kSE6c9cUfqri5laLNxXFh5pjBVhqsN8Swzly0tLiYjm2ejUymtu1szl/HkJmVsgHV00PJ1dSo/vrpaldvk8rG8D27UlkrR8fl8tHwspgS83NuiuFg12WNRMpeSNZnIKOYoSyZDxltxMW3X7aaZPi47azarNBteXtNUBSc2HHlZNui7upShzqVd+TkbjuwAcHnUXbuUM8LN4EwmVXKVjX5u7sZi8t6z2zzzzw5IJtOzLwIb5LGY0gQcqNHRvT/eBkc1gJ46EC49m073TDkqLiZDmEvIsoi5tVVpTjgdip0qjr7w/vg+Y0eDKmDlu+9Fi0U1Pty/X10Pg0FVbDKZlB6GtR8mk2oWyM5EPE73J/e14MfyctpvIED3XX29Sn9ifYvZTPdgIqEcLHaW9HpyoPvr7cDVo7q6aJzcP8VuVz009Ho6LtYUHUlGqoGmMDrI9RmffGBhBba2RbBq2xR1LNatW4fMgYTZdevW9bucrr+SFoIg9EkokcFX/7QRz29pAwC8f34FfnTpYnjto1fhmiMVLS2qrCt3R+YfGE7P4eZllZWURmIwKOPVbqfIABsyJpOaseUSsdwhmQ0lTqnKZOgxFDJ1N6/jbfN+WZhstVKzu1BIVQkyGGj2mUu4VlYqA9PppLFyOk00Ssu2tJDhZ7fT+EIhVRWqrk5FNOrqgLffViVYOYoD0LGx9oIrUgGUjsV6CJ1Odb72+VR0gNOlvF7ahk6nyufydWHjn41SNjT5HPN4fD7VmI7PF1dlYgOfZ+OZQo0Fb4sf+ThYB5DPq0gJV9Pi6lGso+AZe06XYueE1+excflgt1s5NR0dKgLE5VdtNi5BrEr0skaE989jzedpuzodrWe3qygPC6DdbqV94HuPRdt8D3BqFkfiHA7VgNHnI+eHK0lxJMXjUcfJ4nWbje6N6dPpWNkp4HX4/p81i5wOLsXMqVZ2e9/CWh5nJELj4YjHjBm0fS5sUFmpUhGPdErLSDbqk4pFI89EbaQ42TnjqDLct2onVu/2I5HOwWY2HH6lcc6gHIuXX365z/8FQRg6G/YH8fkn1qIpkIDJoMNt587HdafUjbqD7verdCSuxGQyKZE1N/zimS7uYzF9uopu+P1KM1FSQgaYXk/LhMMUEeCymyyiLi4mAy0YBObMoRn8hoZ8t7PBM9ednSpVJB5XXaojEaWb2LuXKu1YLORc1NaqcqVbt9K43W5VRYhFytwcbdo0GhenulRUUEoVHzfrOjIZ1Z05HCaDUNPU+eMqSYEAHR/rVFhUzkYtG/6cssXRFDYkeTaxcNaQZ+fZqOZZdr4urJ9gzQmnGfFMe18zkHxrcQSDDWR2yrhpG0cDAFUxi3UGhSVo2aHgiEohnJrGvUC4KhVHGRIJlcbEx8GlXwvPQSpF59poVGl6fL8WRkt4DIXpWYUpWexEejwqMsOi9lRKpWPlcqpR3/TpZNDzteGoCzus3MgvmaT7tLy8Z8Sgd5M67jpdUqIMaE3rmZLI4+PPitdL9xZHqyIRuve54hT3CuGKY4NNaRmuMc+NDYfTqE8qFo0eI3F9hJFnXoUTRWYNgXQer+/04awFFWM9pGEzLI3Fa6+9hl/+8pfYvXs3/vjHP6Kmpga//e1vUV9fj1NPPXWkxigIkxJN0/DYG3tx93NbkclpmF5sx0+vWobF07yjvm/Ot2UHIZtVRi33aOAUG85550pKdjvpELhHBRtl3Ol61izartlM221tJUMum1XGdEkJMH8+rdfaCgB6LFjQUxPAzeQyGSXK5XSPri4ypDi9iKs2cfMxnY4MPu4T0d5OxzNzpkq14lz8eJyOhY3kPXuUgJcjN1xpiJfjBmgAPdrtqqmZ00nj8PlU9Sg2ktlwLXTceIadHZC+YKFyIqG2x6LqZFKJtAudCJ6BBHo6AYWds3nbvDzrEHqnRHFJWItFnRcWV7N+oDA9iSMebNizA8GRimyWrk1VFfcxUQ4G0LOqFDs6XIXKaFQicJeLzrfJROe8sFM4N9Hj+4g1H9EoOZGs4+AeJDzrz4J4/t/jUWWLq6pU5/LWVuVkp1K0HY7QRaN0v3CUq78mdWzE9ZWSyMUC2Nhm8T/3zqitVWVwCw3Cwaa0jKQxz071UBr1ScWi0Wc410cYHXQ6HY4u0vBauw7/3tY+tR2Lp59+Gtdccw2uvvpqrF27FqkDv5yhUAh33303nnvuuREbpCBMNsJJSn3652ZKffrAwkr88NLFcFtHtyoEG15s4Ho8qtOwx0PGRXu7MjI5XYebfDkcZNTv369y0NmQzOXodTYiw2HaZnGx6gXQ1kbrLFtGr+/bR0aYy5XuLuvJhmxZGf0AsriVy5YajTROjgJw7nlHB6WI8EwtG+But/oRZQN13z41k86z+vv3U3pVKETnIJejMQYCPRvgcSlW7hnBBi87BY2NqlQuG9qAqnjEEQZOl+LZdjbC+4NTqbgELM/Os+PFf4VRg8KSs4ByYHpHFQr3weej0IDnKk3RqNofbw/oeQ+wrqF3ZSc+Zv7jtCMWSbODwY4PGz1cWpaNe3YceFzssLDzxqVfc7ksXC7lQBsMdH+5XHRPcGdydmIMBhqHw0EOA2s9uHxvVRUJveNx0rbs3686jqfTtJ2SEvrjKFh1NTk1xcUqPat3RKCvlMRYjF5jjY7dTg6v3a6iPqxJ8vloHE6ncmb4fBwu+jDSxjz30WBHZTCN+qRi0egznOsjjB4LizW81g6s2tqBfF4btUItR4ohOxbf+c538NBDD+FjH/sYnnzyye7XTznlFHznO98ZkcEJwmRkc3MIn3t8LRr9cZgMOnz9vPn4+Mmjm/rUe1YyFCIHobKSflBYCNzVpQx27hFhNKqeAoEALcsGaDCoZs69Xvr/vfdovZoaMrhYZOpyKdHq+vVK9EpC7RR8PtWRmvfd3k7rc0dmNkQBMjhsNhV54Bl/vZ6WZcOYRblFRSplafduOhbuxMy9BrhjNhtnoRC9Fo2qfXAUgkvishEXDCrjtLNTOS6chtP7f9YK9BVFOBS8bmFFJ05/Ag6/nUM5FuwgsRNWGBEprArFsEPUOwLCjiigKlrxeuxosRieIyE8NtZrcOSKl+fjLTx3HGXjhnscZSBDP4eyMqXvYS0GO6GxmCosEAjQflpa6JqWlalStFytbN48Gk9pKW2/pYXuT+5E7nZTat+MGUo3wzP/h4oI9E5J5IgIR8ZyOXqvq4v2WVxMTk1rK9278bjSL/H1KC5Wx3yo6MNoGPOc5jWY1CqpWHTkGMr1EUaXOW4NDrMBHZEUNreEjkjWwmgyZMeioaEBK1asOOh1j8eDYDA4nDEJwqRE0zT87s19+N8DVZ9qvDb87OpjsLTWO6r7LZyV5NSk9nYyTgBKSTKZlHDbYlEVnMJh1WOhvJzW27OHfozYAGdDtbVVlYudNUuJtlta1Gx+SYlK2+H0EypPa4XBQNtm8TenOLHhylV1jjpKGf7t7aokKAuluSlZNKqiFry/jg5ajiMSDofSggQCJNhmbUIqpXL4ebaey6ay6JtL6brddKzpNHXz1ukocsEGazarKgCxwciVn1KpnulDh6Ow9OtA12F4edZqFKYqsVHPWgm+rvm8SlPifRZWYeLX+9oPVyfilCoeO8AlYdV2uD8Kj6FQ22M09tw2d8DmsXo8ZEDnckq87nZnUVystDmczsWCcaNRpWCl08qo5YgWn5fSUrV9bmZYVERjb2lRUZBFi0jvwAZ8SYm6vzlVijUQHBEoLT04JTEcVqWEDQb67PL6fj9pgHQ6+oxwqWVNo21zxaiSkp66pL6iD6NtzA9mHalYdOQRZ2L8YNQDp8wuwYvvdWDV1o6p61hUVlZi586dqKur6/H666+/jpkzZw53XP3S3NyMr371q/jnP/+JeDyO2bNn49FHH8Xy5ctHbZ+CMFwiyQxu+/Mm/H1jKwCq+vTjS5fAYx/9hjitrTSbbjRS7X4W6Xm91KBtzRoycJYsUaknFRWqtCUb5YWdrf1+mtXlCkptbZSSEQiobtuVlfS8q0sJXIuLVapTMqkq3SSThu6ULHYiWDDNlanYgGJjnJuZsfCcK5pw+g5HKuJxMs541jcSUWk63CsiHlfpWsXFqswsRxN4pt5sVs32WEvR2anExpkMHTvPjBc2oSvUObDBzkb2YB0ENtKHCoulmd4GG5dX5WgFpx4VOkcsiOcGeYUUPuf0No5AsHC00BlhsXjhOPg5ny+jsWekwmpVZXvtdjVjz4E/LlXMYm+LpWdqWiBAj263ch41jbZlNqt9xGKqkpjHQ9tob1fnxeGgzwuXlOUIjMlEnwt2YEMhVa3M66X71+frmZLo89Ej96Hg49q1iz6jsRjdX0cdRZ9hv5+Ox+GgKFw+T8fDzfv0eoqg9BV9GE/GvFQsEqY675tTihff68B/d/pw01lzx3o4w2LIjsWnPvUp3HjjjXjkkUeg0+nQ0tKC1atX45ZbbsHtt98+kmPsJhAI4JRTTsHpp5+Of/7znygrK8OOHTtQVBjHFYRxxnstYXz+ibXY44vBqNfha+cehU+eWj/qVZ+SSTIuGhroR3nvXjKiZ89Ws1W1taq067ZtqgpOaSkZU/k8rReNqllyNqz1evq/qYm2yzPAbW1kyGzbpqorsQCc06Jqa1VZUWr2Zeg2irhhGhuvvG02xjo6VGUiFntzrns+r3olAGq2mCtCBQLKODGZVC8BNhK5LGkspnpsFBrGnKJTWBmKdQ9c4YcNZjbMw+GeGhF2Kno3eBsMw3EqgIMjDL3h9K7CiAY7bazx4CgEcHDEhZcrdBYK07cKO4Cz9oL7dbDByw4EnzsuAOB00va4kSBfL7eb3ispofU5dY8jVgaDSplix5aPjY1rjsK53aoJnclE22XdEDu/nLrEKX3ccK+8nJzTXI4+G+XlygHiRnjJpIoq8PXwelWKYnGxihSFQsoZYmeJO7RbLOQscId7jopoGp2THTtou31FH8bamO+dijOcikWS1iNMdE6aRcr59fuDiKWycFiGVVtpTBnyyL/2ta8hn8/jzDPPRDwex4oVK2CxWHDLLbfghhtuGMkxdvODH/wAtbW1ePTRR7tfq6+fHA1FhMmHpml48u39uPPZLUhlqeHdT646BsfOGBlH+FA/ppz+xHn/nJbEjbRKSlSaSqFI1elU1YpaWpSGgcW1hWJcNtR5+c5OMnA4vaSri8ZSWqqiCuk0GWcdHcowjceBzk5rd5UeFuFySlIwqFJIjEbViyCRIIOJRbE8M8yVg3gZTpHhXgWFaU4ciSkpUVGHaFSdE71epZiwcJt1Gtxcj6Mo3HiPzx032GPHqi9x9limdhSWnO1NKtWz3Cv3WijsIVHonPSOuHCaV+HrHE0obPjHIm12KAob7PFzToNiXQ87BNwfIxZTehpNo3uAtEFad7Ssrk5tk50HvpdZhF/YdZwrRLE2J5GgiIDXS/vweGib771HaVM2m3IUkkn6HOzeTcdYVaXONafWsXaHHQGOUrDmY+9eOp5gkO7DhQuVM8t9RHisvG2PR+2bzzNXT1u4sGdDRGDsyo/2V4XKbh98xSIpTytMFmqL7KgttmG/P4G39vhx+lHlYz2kITNkx0Kn0+Eb3/gGbr31VuzcuRPRaBQLFiyAk6eTRoFnn30W55xzDi699FL85z//QU1NDT73uc/hU5/6VL/rpFKp7opVABA+0C42k8l0N/sTBg6fMzl3hyaWyuKOZ7fi2QOpT++bW4p7Lj4aRXbzsM9d4Y8pOxa9f0zb27naEhkaHAFgfUAwqKrX+HxkQHB1kGiUekBEoxRZAMio4bSkvXvpBz8SUWlO4TA9j0ToOafOcNlMTp/hRy5XW1MDlJdnEQqlYTRm0dpK43M4VBMygP6PROj/mTPp+AEyRDjNig1Wdjw4xzwapWXZIeptXHFfBc7tz2QozaukhMbY1UWvc8MzbkrHjg6L1gurNKVSPftKDDbV6UgwmKgHR20Gug6XeS2EZ8g5DY0dlEIRO6eecXSj0Enk2XN25DiVjR3sYFB16Aay0OnyyOez3VE2o5GuKWsL2LG1Wul+42pM4TBtx+ul5Z1Oeh4O0+eJy/4GAiqSEQyqHizhsNJ6cMGC3oa72UzRxOJiSlWKRMhJ0eupt0ogoPQTVquqpgZQiiFXj9qzR1Vw42heVRU9Z6eptVVFUvj+ZlwuGi+XTGZjnrVWLpe6n0ciIsATHtwxnD9/nZ30f0mJqvrW+7uNncGBbCscHp3ytPL7J4w0hffUSfXF2O9vxmvbO3DqrPGViTOYe16nacMNqh85rAe+JW6++WZceumlePvtt3HjjTfioYcewrXXXtvnOnfeeSfuuuuug15/4oknYLfbR3W8wtSkJQ48tt2A9oQOemi4YHoep1drGIkKcum0Hl1dVmQyBlitWRgMGnI5HaJRIwwGDaWlSZjNeXR02GAy5WE0aggEzOjqsqCjww6LJQeDQUMyqYfFkkNHhx3BoKnbYJw5MwSzGejstCEcNkGnA6ZPj8LrTcFqzSKf16GhwYvOThv0+hyam51IJg0wGmkDkYgJyaQJBkMOiYQBuZwOJhN/xehgNGahaXpomoZ02gCXKw2vNwOnM4No1IiODhsyGf2Bkq5ZTJ8eg06XRzBoQzarQacDKiricDjIUg+HTYhETIjFjEinjQB0MJvTSCbN0OtzsNmyiEQsyOV0MJtzADQABgDagTQbDbmcHgYDeRs6nQarNQOzOYd83oBg0AxAD4Mhh3xeB0CHXI4uZDJpPODQaLDZMtDrczAY9NDrNeh0eYTDFoTDJuRyhuFf+EmATqdB03TQ6fIwGvMHnAS6FwwGDTqdDvl8HqlU76T/PADyUvR62obJlANA62azetjtaRiNGvR6WtZmy6KyMo543IBUyginMwubLYtcTo9MRo9YzIhIxIhEwgSjMQ+bLXdgbBrM5gyyWT2KitKYMSMKvV6HZFIPjycFhyOPQMAMkymP2towdDoD9Po84nEjbLbcAcdSh5KSBNJpI1IpPWy2HDwe9aOcSOgRi5nQ0WFDTU0UFRVJ+P0mxOMGWK0a8nk9gkEzgkEjslnars2WhcmkIRQywWTKwemk+9/vNyGTMcLrTWHPHheyWR3mzAnDaNSQTBpgNudgseSRz2uoqopj1qzIQdclndYf+Nwakc/roNdrsFqzcLlozP29ZzYPPtzW1WVBLGaG03mwkRKNmuBwpFFSkkImo+92LEymvvcz0G0JwkRhrU+H3+wwoMau4StLxtdsVDwex1VXXYVQKAS3233IZYflWKxatQqrVq1CR0cH8r1i+o888shQN9svZrMZy5cvxxtvvNH92he/+EW8/fbbWL16dZ/r9BWxqK2thc/nO+zJEQ4mk8ngpZdewllnnQVTf6q/Kcyf1jbjrr9vRTKTR4XLgvsvX4zlw0x9Kpwt7OpSXXj5vWCQZjb59ZoamrErK1OpI+3t1OMhHKZZQa7B39ZGs5N79tCM4FFH0R+n9vj9FCHgak5NTSQkbW2lMbW10bI2m4oSAEqYXSim5dQjbqjG6R86XRapVAJFRTZEIsbuVCOjkY6B0zHCYdoWl8gFVGWgjg4aG6ce8QxyKtVTNMvC2kRCvQ+oWWVOveHxc+8OTaPtZLMqlx1Qs+vcuIx1A7yd5uae5VmnGlxtymRS17+wElRhpajCHh+F63M0il/nNCBAnW+nUwmpqSt3Fl5vAEVFRcjljHA66XqzDsjno3skEFCpcCxO54pn5eWUQlRXB2zaRJ+DBQvoPkskqPIZp17FYj2b8NXW0meD0504NSkYpIgfF05cuJDG1Nqq9Boej6o6xjoenY4iG2433VMAHU9Hh+rHoWn0WeHoCEdiUimKYpSXU8nc/iIOrAUyGmk/vSMCvaMZhRGBgUQ0Uik6du470xtOg6yrG1h52pHa1mCQ3z9hpCm8p8KpPE78wX8AAGu+thLFjj5u7jEiHA6jtLR0QI7FkFOh7rrrLnz729/G8uXLUVVVNepCVACoqqrCggULerw2f/58PP300/2uY7FYYOnjm8VkMskXwzCQ89eTeDqL2/+6BU+vbQIArJhbhvsuW4IS59B/1XrnD+dyZAhVVNCPfDJJRkUqRQaE3U4GTjBIRgnX1mejLp8H1q0jUTVXMGpro+24XGRcdXaS0VRVRUa9pikDyedTWgY2dsxmMkgKRbG8bS6jymlRnMPO6SxsdFKKgx7JpBFGI91TrG3IZOhYKitpjFwtinUXvIzFopqQNTUpQ5W1DfxnMtE5YsE65+/zWFh8XfjHaTgAjTudVgYtO1WcG895/pwqNnHiwaND4VcEi6RZ28DnsVBv0TtljOeruIoVL8P3EV8/1oDo9WRcUwd2A5JJI9xuGgQLlzm1ye+n+4dTswo7iXMPk2CQ/rhqE6cXFfbdyGZV7wdOv+PtGgzUbC8QIEOYU/24QtZbb6k+FUVFqvFdJEJGscNBnzmDgT4DvF2fj/Y9Zw4t19FBY7NalXPPeqPqalqOP4+9v7b70ilw1/Jcjr4HGLOZtsvaKi7IMBCNA/fa4H4iveGyxX2NsTf9bYsdHE6bG8i2hoL8/gkjjclkQqXdhKMqXdjWFsG7+8M4b1HVWA+rm8Hc70N2LB566CE89thjuOaaa4a6iUFzyimnoKGhocdr27dvx4wZM47YGAShNzs7Ivjs79ZiR0cUeh1w81lz8bmVs4fVPbOvjrjhcE8xdjBIP6SsQ2Bjt7SUjIvWVnIsAPqRnzuXtvXyyyQ47ehQpS4rKsi4iUbJuWhvp22wMNrnIweDG7JxTjfP1hbm37Njkc/3bJ7GQl3ug8DOBlXtoS8tdoK4AZ3RqErNlpYqB4iF1Owo7N6togZsXLABByjDlMcG9Nw+Ozis5SgcNx8HGzCF/R34dRaKs66Ay9NOdccCUBoJbmDIs+JcDQpQjkIhbByyk8qiZW4ix8/ZaWQdCFdxyuU0VFUp45d1H9GoagLIWoR0WkUMuHoUV0qzWsno7+igzuzc1yIUov00NdHnjEszcyQhm6VtctNGFoO3tys9k6bR/bZnD32e6+vJEQkG6TPH2oLCMr/ssNTW0vJ6PX1XNDTQOLhTPYueKyuVzqf3Oe6v83Z7O30PTJ/e9zV1OFTUh6M2h+vaPZJVqHpvK5lUkdvCMro1NSq6KAgTgePqismx2BcYV47FYBiyY5FOp3HyySeP5FgOy0033YSTTz4Zd999Ny677DK89dZbePjhh/Hwww8f0XEIAvPntU34xl82I5HJocxlwYNXLMNJs0qGvd2+OuJarZTqFAgo4WphrQSexdPraZZy3z4yEIqK1I++Xk/lZsNhMtaKiriPhErZYXH3/v09ewQEAmQwWa09RazcxKww5YcNQJ6ZZcNSr6f/2Sjn1CV+n1OnuGdESYlyKFwu1Y+Dm7txR2weSzZLx8LiXI6ssIHP+3E6VSlTdii4alAspvomcKSosLEcz6KzgcznjI8VkEZeDEci2NHjqEXvPhqF0QqOHnHDPoavEd9nHJECVOSK7xuqCpXC0qWUuhcK0T65hC6XJ+5dEpedGIDu+0iEChksXaoiFZzSxFGPjg56jwX/nLbHn1eO6HH/C4uFnAIeEzfY4+7vnPLE0TNNI+cAUJGBoiJKxeJJBS6f29KijHN+r6NDpUlyKVs2+PvrvO12U78MLuPbG3bWXC6Kbhau21/X7pGsQlW4LU7J5JQtrnyn15Pzw9XvBGEicMwML3775j6sbQyM9VCGzJAdi+uvvx5PPPHEqPWs6IvjjjsOf/nLX3Dbbbfh29/+Nurr63H//ffj6quvPmJjEAQASGZy+NYzW/DUO/sBUNfM+y9fhjLX8BN6++uIy8Zzezv9kOp0NCPn8dCPZzyu/jebydCxWlXdfS4bq9eToWGzqVQmn08Zx6yVYMPZ51Mz8tyXobUVBwTWZOiwMcCGnk6n6ulzSgXQsx5/KqVKYOp0um4HgPsTcOpLUZGKLOj19D73rGC48zXP7vJ2WQPB5PNKQ8GOGM8Cs66k0BDuDRvAfDzsVPXu1SAQvUvssvaksGxxf8VG2Onjc8pOCtCzFC6npLHjwY6jxxNHVRVFFDi6xc4koO4P7i6fzZJByk4POynBIEUqTj5ZpR21tJBzUF1Ns/p+v0pZyuXIweCKRpw+5/XS/isr1T7YeXA4VO8NTm3krvIWC63D92gqRRFGdhwA+jwsWECP/PmJRFRPF67oVhhN0On677zNEZZgkByR3sZ+NEqfoap+JlT769pdXDz4krL9wdvat4+2UVKiesw4nXTOEomDHRxBGM8cM528/C3NYaSyOViME6/4x6Aci5tvvrn7/3w+j4cffhj/+te/sHjx4oPyr+69996RGWEvLrjgAlxwwQWjsm1BGAi7OqP4/ONrsa0tAp0OuPHMObjhjDkwjETZJ/TdEZe7WwNkUPj9ataQy8ryzBz3IOC+FewMsEi1q4v+uLGX1arypGMxeuSUDhaSBgKqURkLanlcnI5iNisxNf9pGm2fDcTCPPbCUqOZjK47hYmjMSYTHQeXd62sJOOJZ7ybm8nBSSZVQ7tkUpU05f2bzWrfgNJNAMoxYrEnp0oN1DkoNJwLnSahb3pHfwx9/Gb2Pn/s/PH/hZEN7q3BJWi5Zwjl+2sIBOgePvpocggAclRTKfoMcPoa/3GUhO9TQDVNDIXISTEaSQTNs+BlZSqFLpmke4rv4b17KQLB2+Ju5XzfczSP+8Ww48znih1wHnsqRQZ1XwUNrVZVinnnTlqn0HEOBsngTqVof0VF/XfetljIEWlu7vt+5jK4/VWX769rt9VKTg1/33CBh6KiwfeesFopmslj5BLQHg+NnXvf9OXgjDbSsE8YKtOL7ShxmNEVS2Nzc3jE+l4dSQblWKxbt67H86VLlwIANm/e3OP1IyHkFoSx4Jn1zfj6nzchls6h1GnGA1cswymzS0d0H33lIrOeoqxMiYXjcSUQTiZpFpMbz7W307IVFeRUFFZ5CgbJkN64UdWN53Qiq1XVkE+n6XWeWQXU/+wUpNOqghNHIFiDwdoDNt7ZWGNDkB0UTjnhHHI28NhoZ20GO0ldXbRNn49mK3kdk4nGG48r8Wlhs7VCI4edDzaA2GkaTrSBjVthYHBfk0PRu5s3G+PsLBb2xGCnAmAtkhk7dtA9XajN4D4TuRwtx+vz/cC9Lbhho9FIjntnJ9179fW0LdYhsRictQ+zZinngnUI7DAUFam0Q01T4nCKsNAjR93Ky1VqX2kpvcfFGLq6VPGCQqxW+ky3tNCymkZGdmHXbxa987760zw4nbS9cFhFfDi6YLOp532tG40qQXxvjYPVShGEkTC+zWY6Nxwd7b2t/hyc0UIa9gnDRafTYdn0IvxrazvWNQYmv2Px8ssvj9Y4BGFck8zk8L9/fw+Pr2kEAJxQX4yfXLkM5e6R/7XonYvM3aB5lpJLpXIFmPZ2+rGvqKDXWltp+bIyMjA4j3rvXsoX9/tVuVd2TDSN9huNKqEsp1XwDzM7BTzzz1EH1i0UNogDlP6AjRL+cWfjkJ0BMgYy0DRjt9PCM8iA0lLs3aucHo5SsPCaIy/5PI25MFWmL+OVy8cmEmp2ebhIpGL04UiUqiam0na4mzqnRLW22rsrhk2bRu91dirD2OEgI5wLFHAqYWkprcPN8srL6bXiYlUpKpVS92k0Sp9Bm41Sg3h8Op3qhs2pidy8LZcjDVNbG+3b66Xt1taqlKBcjmbjq6qUM8NGc3s7PU6bdrBRns+rimdclhpQXb+DQfoOmDPn0JqHbJb0WDzZ0Du64PcfvC6LqFtalGMSjfZtWI/ETD5PwrBj2JvBCMKHS39C+P7E7ILQH8fM8B5wLIJjPZQhMWSNhSBMFRq74vjs4+9iS0sYOh3w+ZWz8aX3z4HRMHq/VoW5yGyIp1JkUEQiZOiUlKhZQb+fKiPxa0VFZLj4fGQMxWKqy3YqpQTYwaAScvMsMOeJh8MqasFRhEIxNIuwAeVk8P+sO+D8bXaKTCZlbHCkgJvMAcrZAGg8LLDllCg2ZDi1IxZTM8WD6XBdmMoljH+4FwZXiWLBfz6vrr/dTn+axhEGHfx+1V/C7aZ7hnVEfF/PnEkRgM5OpcdJp+ne0utpPZuNDHWLRXWOLytTJZ7ZSc9kyBFhATdHGLjvQzpN1ZuamuizsWQJrbttm6oK5XDQX1MTzew7nXSfer3KcA8EyHgPBOi7oqREaS5Y1N5fmpLZrCIKh9M8VFer9Mre0YXe6+ZyNGYWik+bRtdlJA3r3uMYSUH4cOlPCN+fmF0Q+oN1FusmqIBbHAtBOAQvvdeOm/+wHpFkFkV2E+6/YhneN7fs8CsOk8Jc5OZmchJYC8Czb8mkEjJbrWQYsQjb66Uf09271ax8aysZAJy2xGlOrIFg54BLW7LmgEP6vN/C/HCGy39yTndhOVYWk7rdKsWJjTHVGI02zukugJqNLux14HCoaAtrKBIJlaPOrxeKgrm3xEhEJYSxobBaGDsWXLUrnVZ9Wzg9isT8WnfkKxSie4ejG4V6iGRSGah83xfqN1io7HbTOPbsoeXb21XFJLud7sNolHrFBIOqB0VZGS1nNpPxP3MmfeY4qmGzAcuWqdl3jiIajeQw2Gy03VCIDFRuIBmPKyG51UrRhepq5byzTqo36bRK9Rqo5qEvw7z3uhwpra1VGgdgZAzrQ6UYjaQgfKj0V3CDKRSzA6OrvxB9x8RnQTV9sbSEkgjG0/Dax0+jvIEgjoUg9EE2l8c9Lzbgl//ZDQBYNt2Ln111DKq9o18UvfCHobiYjJTycpXrzB24NY2Mm0yGDJSiInIuQiHV+2HdOvpxyWbRLWRlA4rzu9ngSiSUeLWw9wSgctLZGAIOTv1hB6CwrCwbQbwud+6NRnvuI5czdv/PTcA4P5rF1iYTjTWZpD/efy6nehRw2lNhpSGuwCOOxcSFHVk2Kh0O5QAXiqz1epoppzQ8rbtXSSSiqpqxUw1QNIM1D6WldN+xw8vdvNnB5vuWdQWsr+AIgV5PTkBbGzkEtbVq9rqrC9ixg9L5EglKW+SO4VariiS2tNAkAn9G02nVy4InBKxWWi4cpu1zyWjWG3HaViBA3wVcgpWrvXGZatY/DEfzwOuGw6pKlMt18HL9VYkaCANJMRopQfhQ6avgRiEmE423qUmVpR5p/YXoOyYPbqsJ04psaAoksLU1MiIl7I8k4lgIQi86wkl84ffr8NYePwDgulPqcNu582E2jm6ibl8/DLGYMia2bSPDhHs6sLFUUaHElD6fSutgsTb/0Ofz9JwNJ9YocMM6dhioYd3Bgmfg0ALlwlQpTl3hCAiXteWKPTyzzAZPLpfvnl1mR6lwBpm7BnPjMq7exOscymngfHhh4sKfBy5xzAUDCnunsOPKvSpiMRNKS8nY5SaPwaBqoMflhjl6EImQEVZZqYxWo1FFAbhDvYqyqSZ9rP1wuZTjAygBeCCg7vV0WjnH3HyPNRPci8HtJmO6rU1ts7qa/lpaqDcHdxjncrk6Hf1vs5FzwU4293phg5YrqHGEgQ3P4cxucynfwVaJGggDTTEaKUH4UDhc879IhL6TgZ59hYabJsbHm07T/S36jsnD/Cr3AcciLI6FIExkVu/qwg2/XwdfNAWH2YAfXrIE5y8e/e6Xfc3KsWA5FKJlOKyfz1MKRFeXSuFwuaih1f79qlcF6w8CATWrzxGFwgZ1vUvCAqrs60Ap7JzMxj47IVySlt8vNMi42pNeTxYHNznj8Rcuy+lWyaRKhyl0fvpzHsSpmPiwY8ERNXYiuFxtYZpeKKTux6IiMrS5U7zfT2k6nPbHGgiulGYwUHSwvFx9bjjNjqOCLhd9zioq6P9cTqUCJZNKeJ1K0Wcyl6Pt5XLKsfd6VffuxkZVQIB7x3AvhmSSvgcsFppYaGoiZ8Nmo/2wWJ3L4ZaX0/cC97DhrtjZLDkkySRFUwarfzicwT6SXbV773egKUasuRgLDqf1aG2la1VRoV4bjv6i9ySUz0ePM2ao/Yu+Y2Izv8qNl95rx9bW8FgPZdAMy7F47bXX8Mtf/hK7du3Cn/70J9TU1OC3v/0t6uvrceqpp47UGAVh1MnnNTz06i786IUG5DVgXoULP//oMZhV1s8U3AjT16wcp/C0t6u0KE2jmS/uPp1IkPPR3Ex/gYAqxcrGDZe7ZEehsFxsYXdpLjvLBkRhs7fC3hUMi7wBlQZVaMSzroEjEwYDGUmFY1AN7GjFbFYZB2zoFea98zK8fuH+pCrTxITLn2raoZ1Z1lNwrxKuymS3q9n4QofWbs/A61VljI1GMua5keK0aXTPdHYq59fppNfr6+m+9PnoM8GRMpeLDHu+b2Mx+nzxmDi60NxM92xVFT2WlpLxz6WXC6N2fMz79qk+MFarOi7uQROJqF4xs2YpR6WkhJZta6NtsIGvooG0XCo1eP3DQNNrRktEPZAUoyNZTvZQ9Kf1CAToccaMvtcbbJpY70mowt4/bW0UcSu8NsNJQxPGjgVVlGqwtW0KORZPP/00rrnmGlx99dVYt24dUgdUSaFQCHfffTeee+65ERukIIwmoXgGN/9hPVZtoy5UHzmmBt+9aBFs5j66d40Cfc3KcQOvpiZVGYqNDO6mm0ioxm6JhJo57epSOd/xuIpCmExKP8FGGNAzOsERDDb0mL6alvEMJKcuFeoxOG2FnRdNU/npDNf+p+M1dW+Xx8tC7ML+ElzaVpg8cNSJ76e+jMTeKW9sbPL9w/caR+PsdiCfz6CoSFUQY0eEHxsb6XPD2+ASy9Goasg4fToZa6kURSk4bz8SIYeex8KOut2ulmH9QipFy7rd5BD4/bTNTEZFJtNp+qupUeeguZnG5vUqzURXl4rWeL00DtYrcefu6mp6j6N+mQyNa7D6h8GWTx0NEfVoRkJGOmWqPyE8V+saqTSx3pNQ3PHd66Xfh2CQ7t2hbl8YH8yvIgH39vYosrn8qFahHGmG7Fh85zvfwUMPPYSPfexjePLJJ7tfP+WUU/Cd73xnRAYnCKPNxqYgPvf4WjQFEjAb9fj2Bxfi8uNqj2iTx8JZuWSSIhRcSnLrVnp0OlVKxPTplPbw1lv0o1JcrASk3IOisNcEV5CxWFQEoHDWFFDGO//4HC4NimeFCyMWhWSzqgmdwaDG1nsbvV8rdHL4x7/3+311axYmNlwCtj/6i2ZwVC+bJcPdbiej1uMB0uksli2j1xoa6LPCFdKKi+kz4XCoxnlckrmkhD5zAH3uioro/ZISSjWqqiIjsqGBli8rU45LIkHRjvJy+mzxPvbvV44H96Bpa6P9cFGFmTPJ8eAqVOyUhMNkKJaWqjTIlhZax2gkZ4L7crAgmz+fRUWUhhMM0jH3NWvdn+E52PKpI9lVmxnpSMhoC5z7EsIDqiz4cJ2jviah2OnOZuneYg0an5Mj2ctDGDlqi+ywmw2Ip3PY2xXH7PIjkz0xEgzZsWhoaMCKFSsOet3j8SAYDA5nTIIw6miahsfXNOLbf3sP6Vwe04vt+PnVx+DoGs8RH0thmcnWVpol5IoxDgfNdra0oFuIyrP/3IGbm0N1dqpZ3cIyrzyjygLoQgOtd1+KgcKGHs8S93YseBaanZdCp+VwHM7IlOpOUwuzWaUzFcLONGt1APpMcCfskpI0ampUxAIgY5wNS4tFdZ8OBpXuYNcu2m4oRAa9TkfLLlmi0k3sdmD5cupez/vlKAWLwvV6JdyOxWjb27bR57i0lByS5mZlPPN9zQ5JPk8RilhMLccTED4fTTqUl6s0Qy66EI+TI8Mlc2MxSpHissxuN63HhnRfhudgtQ3MSHbVZkYqEjLQCMxIjL33eiPlHPWVGsb3cShE15bTWQE6Fr+fzpGkQU0s9Hod6koceK81jL2+2NRwLCorK7Fz507U1dX1eP3111/HzJkzhzsuQRg14uksvv7nTfjr+hYAwFkLKvCjS5fAY+snkXeUYcOioYEMBq7QwrNq3AOCy0VyQzyHg9ZjMXM6rRwJThkqNMgKK+gUMhxx8+HWlfC7MBw4takwRYq1A4zVqmbpubt0KASkUga0tpJglqMQs2ap7vTcqTseV5V6QiHaFxvper3qczF9Or323nsqva+oiMY1fTo9lpaqhpTxODkGBgONIRym9KtgUOXCFxXRPvx+MjqdTvoOaG5WqVQcaWFHpaqKPvvs3PNnPpVSzfKMRhrDrl3K2Whvp++L1lb6f+5cOld9GbbD1TYM1og9lDE/UpGQw0VguB/IaEQzDqW/4DLaA6G/1DBunsj3G1eJ6uxUFbtaWqT07ESjvvSAY9EVG+uhDIohOxaf+tSncOONN+KRRx6BTqdDS0sLVq9ejVtuuQW33377SI5REEaMnR1RfPZ372JHRxQGvQ5fOWcePr1i5pBTn0ZqZs7hoB94zqHOZsm46OigbTsc9IPK5TG5c7XdrirasGGSTKplubzrYKIRgjBeKIyksf6GZ9bNZjK+LRaVBsS9J+rqgGnT/NDpZiIcJsOrulpFA8JhFfFgQ6upiR75s2g00ufPYFCf7WnTaF1OJ+QqZXPnktPAzopeT84DOy1mMzkXrElqa6P1KyspusDGJXeP5yZ23G/CYKDJBY5O6PUkBu7sJOM3FqPHmTOVM8D6qlCIxsv793joe2bLFlre4zl41n+0tA29GWhq0nAjIYeLwBgMwM6dFEUayXKwheMvdI4CAXoEVEGAWOzwhn9/qWFWK91L+/bRtebHsjJydke6A7pwZKgrpQ6XU8ax+NrXvoZ8Po8zzzwT8XgcK1asgMViwS233IIbbrhhJMcoCCPCsxta8LWnNyKezqHMZcFPr1yGE2YOrT70SOfq8sxZZ6fq9+Dz0Y8Npxwkk6oMZVsbPdfp1IxmPk/LFnYn5lzrvrplC8JEoVB0zal/bKTH4yq9Raejz+Ds2QCQgctFnxnuIM89TXh9rirl89F+LBZy1NmZCIfpc819H4qKlH6Cy7x2dirHobGRPptcWMHppM9hLEaRhpkz6b22NhWhLC5WFalSKWUMxuP0efZ4lLNQVUWvOZ00Nu6g7XLR8RdWVONmeNksjbuqis5TLKYqx02b1tPQLDTczWZyQPpKoxlqladCBisO5+szFA4XgYnFaJ/cIR0Y+XKt7ByFQuTEulxDc2L6i34kEhQ54zSx3tdNSs9OPGaUkCe81xcf45EMjiE7FjqdDt/4xjdw6623YufOnYhGo1iwYAGc/ZU+EIQxIpXN4e5/bMVvVu8DAJw4sxgPXrkM5a6hTdsM5QfxoDH1mnlLp1WlGLdb1evP5VSVGhYu+3xkNLADwQ3kgIP7T3AgplBoLQjjnd7VoVicyn0eWHDN97TDQUbajBkUrTAYgI4OK/x++rw0NtJyZWXkGPBsvk5HUQmunMS9XXiWt6NDNa1LJMg4d7vJOHQ46L26OtpOOk1GWzRK3wFcjpmd/lCI/i8rU30NSkspPSscJgfFalXfAQBtt6yMIi7c8FLTaBwlJapRJkD74k7b/L3R1UWOCX9PuVz0PJcjB8pmU1GXwlQjnsyIx2msbrdKseJqbr2r2A02klAoKh/t3gt9RWB4zNksjcPp7DsCU6gnGQkBdOzA5PNQe1ocKjXM4VCd3/uKNEnp2YlFfSl9yPb4pkjE4vrrr8dHP/pRrFy5EgsWLBjJMQnCiNEUiOPzT6zDhv1BAMDnVs7CzWfNHVbptsFWSymkv0iHz6f6NiQSKseb00Cok7AyVrhuOW8TUD+ShUhzOGEiwn0i+P7N51UzOK4EBagUopoaMr41jWaDi4uBbFaPtjYyYAMBeo21FaxV4tx6Tj/M5VRzuVSKPnPhMBnrABniJ55IBubu3WScsWHe2EiGvc1Gy3Z20n44ihmJUJQiEFBi7EiEPvsOBxmDzc00RrudvkPcbjJ6zWbVCJP1HuwImUyqxG42Sw5FOKzSIUtKDk4hy2RoW5pGy/F3GjsO/J3CaZdbt9K2bTZyTGpqyIDt6qLl+PtoIJHbZJKOsaGBlo/FyKgv7K/hcNC27XaV7tYXA3VoClOI8nk6p9GomohpagLmzet7G4V6kuE6FkMVxfemv9QwLjs+Efp+CIdnRgl98bSEEkhlc7AYJ0ZJxCE7Fp2dnfjABz6AsrIyXHHFFfjoRz+KJUuWjOTYBGFYvNLQgS89tR7BeAZuqxH3Xb4UZ86vOPyKh2A4Pwz9ddfetAnYs0dFIdrbVSoFN9riiAX/kORyKiebG8ZJOUFhssCpRoAqRMA5/WYz3f8ejxIvWyxkgIZC9JmiNB4L/n975x0eV3H9/e/2vlpp1WXZllxxwxiMqYaAsak/WkixE0ooAUxoARJS6KE4QAi8AUIglACBEEJNQiCAIRBjCC40415kq7ftfe/7x/HZ2ZUlW73Y5/M8eqTdO3fu3NXdmXPmtHic3kskVA2Yxsbc4nTRqBJqdToSQFtaqD+jkc4Ph0mY3rEDWLWKrh2JKGsH18DwelUhyJYW+t56PEo45srZySQVq8vLU0pMtjXGbidLhtFImaQiERIkOcNbWxsJ53V1JJRzLIbXq1y9OP6qoYGulb2DzfFZNpsq8JefT2Nji00sRsHfXJBv61YaD2ewikZp3tI0FauxJ8stz4Hsbpafrywt0aiqv9DWpiy4nKQiW1npjSsq1wJZt46eI7YKcX2d7DS/2fQlnqSj4N/fBf86rjGDFRsjDA5FTgtsJgMiiRRq26MZC8Zwp9eKxSuvvIK2tja88MILePbZZ3Hvvfdi8uTJWLRoERYuXLhLtihBGCxSaQ2//fc6PPDuBmgaML0iDw8umoXKAnuf++7LwsC7guyqEInQol9fr/y0zWZVXbumhhZgzoHOKSW5uB1bNvhasgsl7C1wzAFAzzmgvnsGg8p0YzJRu2RSuSfp9SRwNzY6M8o7p4Jl1568PHJF4aBWvZ7iDdhtymhUdR/Y1dHno+/ljh3A5MkkyNrtJNwFg3RONErjYcuH2UzKBAuyySQJw4WFytrCVsr16+keuTp3Q4Ny1+J5orCQlASTiZSadJquz2NcvZoE46oqcgtraaHz8vNVdXB2A2MlJR5Xbl3BoLLO+P2q0GUkou6VrS+trep/xMHje7Lc8hxYUKAKYGZn8mpoUOm0rVZSyhIJ5TbFCSe764qaLdhz9jCu58NFRMvLSSFrbNy1uBzfG8eT7Km+D9OV4sP/74ES/AeqArowNOh0OpTmWbG5OYQG/z6gWABAfn4+LrroIlx00UXYvn07/vznP+OPf/wjbrjhBiQlDY0wBDQHY7jiuZX4cAPZ6L93yGj84qQpsJr6x4TY0x0hXtgSCRJaIhFVGXvFChIm4nFa0Px+5fpRV0evbTZaODkom5WHVIqOC8LeCLv1cWwQu0CxdYIVCf5+cPxFW5vKoNTYaIHFohIfZMcssbvP5MkkVPr9KhaivV2lh02nVe2LtWvptdWqCut5PCRwjx5NLlUc98HWlooKEpabm6kPgATZeFxtEmzfTgIfp8sF6Brr1tE9sTDf1kZjCgRyd/jdbuqH092GQqQAFRcDs2bR3w0N1K/Xq6p8OxzK9amyUn3uRqMqGMiFOTnrXHOzsq7U11OQvNebW5SNYxFaWugYC7HZ1l7OYOfzqcrUdjt9Fk4nHbdac12W6uqUdWlPrqgFBbsK9mYz9VVVperqsCUhGqV73LpVKQFcubynVcP3FIPHtUUGSvAfiArowtBR4rZkFIuRQp8UCyaRSOB///sfli9fji1btqAkOypJEAaJT7e2YvEzK1Hvj8JmMuCOM6bjtAMq+vUa3d0R0jQSNHhhCwZJiXC7acFatQp4/31abF0uWmB37KD2vEPLdSvsdqXQACodpSDsraRS9F3Q61VMhdFIghErHawI+P2qSJjTqTIzJZM22O20O9/SohQVvZ6EK52OhG4W3INBJTi3t9P3zmhUArHbrWrMhMM0B3BaWK6CnZ+vlBbOOGW3Ux+RiBIauVL311+rYG0WyCdNUsHqXHE7GqXXhYU05q1baf7ZtImER84std9+qhhmSQnNLZWVKnaDCwNWVFBfySTt1G/fTooIX5cLXAL0OfFnEA6TJUanU+l09XpSsliYDQbpb44Jq65W/7dsay8rCNkB5z6fUhJYIeT/g9FI911by1m/dsXhoP8hf77ZgnVLi4pn4TiYbHgDZ9MmFdMyahQpgj3J9LenGDyuTzJQgr/VSv9bdsVjq1NfKqALQ0eJm/5h+4xi8e677+LZZ5/Fiy++iHQ6jTPOOAOvv/46jjnmmP4anyDsEU3T8OR/t+C2v69BMq1hXJEDD3/vQEwocQ3I9fa0I2S30+IUiZCgY7VS9eyNG5Xf88cf08TvdtPOZFNTbqA279Ry8TveXeQsUIKwL8ACLgtjnEGNi9fpdEpQZUHWZOJaEwZEIsrCwcI5t7Hb6fvEmZFaWuh7Z7Eodxm/n4TdwkISvFtb6TvrdFL7cJhecy0Nu53Oq62l7zmnmuX4jXBY7e6HQqqoZXaQeDxOf5eV0Xh4vBYLWR54N3zCBKUQbd5M88WYMTRWVsQAasNpbh0OEpTZsmA0UnsunsdWBJuNPt9gUFkt2tvpXLs9d64Lh1WmqFhMzYWhEFl52tuBKVOoz2xrL9deYKsE1xYpLKRxR6PKmgGo2BMuQMgxEtmYTPQ/crno82PMZhW839ysLDR8nfp6lc2rooI+92i058kvuhODF4vRfXMq8d4W/OuMji5YAP2vCwtzP0th5MCKRb1v5Cz8vVYsKioq0NraiuOPPx6PPPIITjnlFFjEcU8YZMLxJK7/2+d4ZWcV7ZNmlOGuM2fAaekXY1yn7C7dHysVtbW0mK1fTwtWbS0tmuvXk0DCu511daRUcApCzuzCrg1AriIhSoWwr8GKtsGgFG7OGMXWQE7TGolQO/oO6RGJUDurVQnxnAihspK+s9mZlTi2govcMX4/fYdTKWVxYKE6maSNAw4y1unUrj3HgLCVgysisyVDp1NxBA6HKs7H8QzhsBJWYzESqjVN1bZgJQggS01NDfXHNToYdicqLKTzWZBm608iQffAloDmZjrOVhcuGMjCfDrNmbdU//y5cg2d8nIVEP7VV+SW1dHay8qF30+f7ejR1G9Dg4r1yH4O2E2J09R2FDk4ADtbqWAsFrK2sJsYn9vermJp8vLUPebl9TztbXdj8Mxm6r+/CqwCXbtghUL0/2TLnDCyyFgsAvuAxeKmm27CWWedBY/H04/DEYTus7k5hIv/9CnWNgRg0Otw/QmTcf4RVb2uot0TstP9seuSTkcTe20tLYDbtyv/Zr+fBJlAgASAUEiZ530+lfWGF2cgd7csmZRMHsK+C8dQsCBmMOTuyme75LAAqmnpTD2MdJqEOW6nafS9ZbcV3jF3OpVQz/2wD35zMwnB6TS1Z6UmElE70BxnYDTS9dxu5R7FVbM5CxHXpmAhE6Dx19XRtTk7XCBA84PfT+95PLsGErMbVn09jYWtEgwrX0YjteHaHEaj+mxranItpZyNq6mJ+mbrCEDn5uWpOh9cfDCRoD75uMlE42lqovsqK8u19qZS9Lk2Nalg/C1b6Lodd/05dW8sRnNrWVnnigVXLO+MwkKlLHi99L9sa6NxcMrbbHpa96GnMXj9uRfblzTowvClxE0PSYNvH1AsLrzwwv4chyD0iDe/rMeP/7IagVgSRS4LfrdwFg6uGtyotI5mZ66UDZDbU20tLZS86LJC4fMpiwX7iQO7L2CXbcEQhH0NVihYqeCsRqw4xOPKLSqZZNcj2k6PRlWNhmxlpK2Nvo8mk7KAJJMkYI4ZQ+d88YXalWc3xGyBMRZTMQgmE8UA6PXKdVGvJ4WAhWadTgn0kQj9DgRoB52LztXXk8C+bRsJv+PG0fFolITulhYKOmfLiU5HfxcX02uOy9I0tWPNQe4cQ5LtFpNO0zmcaraqijZBHA4S1NkKoNfTcU1T2ZWqq3NdnlwuUqbYPQyge+Qq5uXlytrb3ExzZDKpqo0nkxR3whmvXK7c+jxstWlvp2uWl6tihtn32ZVgbzDQOS6XckfjIHhWnrLpTfrXocjK1F/1MYThR6GT/mGt4ZETWNlnf5GvvvoK27ZtQ7xDNOn//d//9bVrQdiFZCqNe95ah4eWbgQAzB6bj98tnIVi9+DYeFnAYZcGNjuzCwBne9qxQ6VfZNcFDpLk4lyRSM+sEFLsTthXYaGfFQAOwmaBlxUMVhQo2DedSY2aSqnvYnaqVRb0o1mbgW63EpztdjqfXaMiERL2k0n6/gcCFD9QXk7X553+VEpZAzj+orlZuU5xFWyuuq3TKQGfXVYKCykA22xWY7BY1L1ypiNABZmPGUNKh05HAni2735dHSkrRUXqXmMxmpe2bKH7LisjxYrjC0pLldXEZFKBxdnuOw0NpIyk07lZoJhkUn32HC/D1t6iol1dmiZOJCVn1Sq6PrtgcRu9Hpg6le6tqYmEeFYwOBvU7gT7wsJcazP/L/or/etQZGXq7/oYwvDBZSUxPRAdOZlWe61YbNq0Caeffjo+//xz6HQ6aDulHnZDSe1u+1UQekFLMIbLs1LJ/uDwKlx/4mSY+lBFu7t0Zp2IRGhnj1NZRiLKhSEapd08DsTkHPcNDUq44AragiDsGa7ZwAI7C6uRiHIlZFce+m3I7HqzUMvV7Vlx0Otp9zseV/ViOLWz1UpCeShE333uo6mJrseBxqNGKVcqr5f6bmqiPjh1a1MT3QMXwPP5SNB3uZT7DWdBcrmUYsH3yKlmOTic40yKiqh9NErjnDGDgrq5cGC2777HQ9cPhZRFpaWF5iSrlSwebNHhIG6OZWBFKRymczmmpa1NKWIbNnQugGcX48tOwx2P0+eVLdBHo9RnRYVSZJxOla63rIzut7RUjZmDtdnNp7uCPcencIav/rIw7C4Gb6CyMklhvL0Xt5W0RX9k5AgLvVYsrrjiClRVVeHtt99GVVUVPv74Y7S0tODHP/4x7r777v4coyBgVU07Lnn6U9T5KJXsXd+cgf/bv28Oo7sLnMs+pmm5QXHsNtDaCqxZoyr0NjcrYQKgBZsr627apDJFRSIqp74gCN2DU8+yAAXQ95a/T5qmXGeoLgEpFuy6w65QXJsCULFLnNLV56PvdTpNgnh7uxLy+bqRiMoyNHZsbsyFyaRiK9rbSbCMRqmN3a6KznEdmqYmUkzGjVNpcLmqN1tIDAZ6j8fZ2Kh23oNBem0ykZJhMFCGqOxK1IzdTsI3F9ZkxcHrVS4yiYQSPu126p/jVljx6ExYBuhz4xgPVv7YAsNWAZ5nu9ph50DqsjJV64LT9/J8yUoF//95/HwPPRXsB8LCkB2D11/B2btDCuPtvbht9CWJJdOIJVOwGPunJtdA0mvFYtmyZXjnnXdQWFgIvV4PvV6PI444AnfccQcuv/xyrFy5sj/HKeyjaJqGZ5Zvwy2vfYV4Ko3qQgce/v6BmNiHVLJdVUXNXiCzj3FayKIiZXWoraVFl4MOYzGKq+DCV1wgyuEgAWLbNuqXi0tJ/UhB6D5skeA4Crb2sULBlZU5hSxlOtJldmpZ4fd66bjTSQIfV7/mwG+u48AVtq1WUhJGj1bZk3w++m63tKgU0GwhYEuI0UhCMltDNE2ls2WrAGc9isdJ+E2lVHwC7/CzcB4M0vsTJ5KlY8MGVecjlSLFY9w4mqO6qkTNaUfb2khJ4CxVDgcpJ1yhnAXTVEq9z8X7vF4S7M3mXYXlKVMo+xPXBjGb6T4421K2gN7ZDnt25W+OkykrU0oFp+ztmJujMzefngj2fbUw7O4agynIS2G8vROXxZhxAQ1Ek7A492LFIpVKweUi4a6wsBC1tbWYNGkSxowZg7Vr1/bbAIV9l2gihZ+/9AVeXLEdALBgagnuPmt/uKxdOJJ2p88uUvK1tdEPf4H5WEsL8PnnKitLSwvtym3ciEwqy7Y2WpC2blVxFlYr7UQ2NqoAbRZ4JFZCEHoGx1hwkchEQgmZ6bT6u7VV7YTze2xBjMVIoXC7lVXDYFDfT84cxfEL7KoTCqlMRayMGI303eZx8M55ezu9b7OpFKzRqBKuHQ51HyUlJLzm55P7UlOTsmwAdL7LpTI52e0qPWtVFV0jnaZ75sxULKRzil2/X8U0ALnCZyiklJ/mZhXYzJ9VXZ0KiOa+6+rodXX1rkKzx0MpZevq6LpsKeJNm2wBvbMddv4fGI10fl6euobNRu3Y+pPN7tx8uivY98bCsLsNqqFI6zoULljCwKPX6+A0GxGIJeGPJDLB3MOZXisW06ZNw+rVq1FVVYU5c+ZgyZIlMJvNeOSRR1BdXd2fYxT2Qba1hHHx05/iqzo/9DrguuMn44dzq/ucSnZ3KflYH540iX5zikn27WbXBXZF0OloYdyyRe2qsUmefYjZF5orBXOaTEEQegbHT2THJrEyYDarnWuOXzKZ0pkd83SavpOtrbRrz/EC7B7F1bHTaRW8zBW48/KUiw4XOGMFg6/J8QypFM0RHg9tLBQWqpo2VVWqDQd1s7WF74PdsUpLVaYfQLkB+XwkvBYXk6AYi6nK46wsccE5djfibEHslun1ktXV51OxX6NH0+uaGrp2MEjKTHGxKtrX0EB91tXROePG7Wq5sFrpPrsjoHfcYeeg+paW3NSvXFW9uZn676hA9KebT3f7iEZpHehsgyrbSjTYDLYLljA4uG0mUixGSAB3rxWLX/ziFwjtzK15yy234OSTT8aRRx4Jr9eL559/vt8GKOx7vPt1I654biX80SS8DjMe+O4BOGx8YZ/73V1KPp6I+W+LhRaOpiblbsEKBe+0NTTQ4stCCPsus4mf86OzciHB2oLQN3h3muMU+LvFsRc2m3qP3aY4NoMDvTlugAV8gL7DZjMJs2az2gAIh+k4p7O12WgOaWujNuxixLUfuLo1C/Qs2HGwM++L6HQ0n3Cwd329qvbd3k7CfVGRilvQ6aiv7MBlQAWkc0XytrbcGhWhEF1n40ZyVbJa6Z7y8lRNicZGFZ+ycSOwciX1Y7cr1zFA9ZlKkRW3tpYEaLt915367gizHXfY2dKk1+feI0D/l4aG3OKIQ+nmM9xrRogysXdhMZI2HU+OjF3JXisWCxYsyPw9fvx4fP3112htbUV+fv6gFCgT9j5SaQ2/fXs97n97PQBgZqUHD31vFsrybP3S/+5S8vHuDkCL7YYNwPLlKo87m7pLS1VmGc4Zn0wqiwUvvPE4/Yh1QhD6D1YWuBI3xzTpdMoFkVLNAu3t+kyxO7Z26PUq21AkQt9hFtjz8qgNBwtz1qhkUhXP0zQVMJ6XR4JkMEi77JGIqqrMcQLjxtHfDQ0qqJrHyulZOdNTMEi/i4tJaNY0ctsqLKTrh0K7FoXT6+n+3W61scEVnZublaVl61ZqP26c2lwxm5XS09BAlldWVJxOGkd9PW2uzJihYsm4iCfHi1gsne/Udze+IXuHvaKCxu3zqdgUgD6vMWOUlWZ3bj4DvVufSOgRCHRdhE9qRgj9jdFAMnUyNTIEil4rFmeffTa+8Y1vYO7cuRg3bhwAoECig4Re0h6O44rnVuG9dZSX8fuHjMEvTt6vXzMgdJWSj92WYjF6vXEj8OWXauewoIDeq6mhBYNdFlpalADAu6e8c5m9KAqC0DfM5tygaw7c5oBerkmRXf05kdBnLAiMx6N2t1mY532wSIR24TnwmF2fuFBcOk1zArslcf0JvjZnp2JhPj9fKTsGAwnfRqOK//B6qf3WrSQ0cxXosWPJjSo7XWx9vcqQxMpVIqGqUWuaCnzm2hS8sVFcTOfW1qp7zRaK+R7MZhoTKzQcCB8MUka7yZPpnlmp4srhBQV0r7xTz7UkehJ7wAI4W5pqa5XLFdfXGDeOlBCOdemoOAxWzAPHgkjNCGGwMO7c9UykR4ZQ0WvFwmw244477sD555+PiooKHHXUUTj66KNx1FFHYcKECf05xi658847cf311+OKK67AfffdNyjXFPqfL3b4cPHTn2J7WwRWkx63nz4dZ8wa1e/X6Rgw2NEfuaFB5bBPp1XaRE7l6PfTcbtdLWyRiMp9z65OolAIQv/C9VfZLUevV+5BJpNSEvi7R8dTSCZp91vTVA0JrjfDQdRsQeD4B7ZscJVtTsjAQd42GwnWbW2qDw4u51S2TicJs/X1KiC5pERtQuh0KnZDpyPlxemknw0b6PWECSoWJC+PAqbD4V0DcysqKCHFhg10DZ9PxY/Y7cqywpbVRILOY0WptZUE+VCIxuf10vW5wF5REbWrq1P/D7tdFQ9kAZqLALa35ybA6G7sQTRKCgxn0EunqQ/+fLnfigr6H3Q8t6ukHL2xpOwOLsgoNSOEwcK0r1gsHn30UQDAjh078P777+O9997DPffcgx/+8IcoKyvD9u3b+22QnfHJJ5/g97//PWbMmDGg1xEGlr9+uh0/e+lzxJNpjC6w4+HvHYgp5e4Bux67QNTX51bk5bSQW7bQbt/o0XSMBQnO4hIIqBSTeXm57gayQyUIA0s0mlsMD1DxC4ASOCkmQp9xYwLo+8rKB1eWZr94roYdDNL8wJmkWHBm1yZWOrLjpthlSqej9gYDuS+xayRnbeIsR7zj3dZG57Fb0pgxdHzrVuDjj0nYHzWKfioqyELg8ai5JrsI3qhRZEFtbKQfjjvgitVcn6KgQMWGcUA7u5aFQvRjNKrg8ZYWda3t2+neRo2ie+EaIKyEpVLUr9dLFgamu7EHtbV079ljSCTof9nYmBvsXlWVe27HmAf+jOx2UrJ6a0npDJMpDZeLnhWpGSEMBsadRYATqZGxa9lrxYLJz8+H1+tFfn4+PB4PjEYjioqK+mNsXRIMBrFo0SL84Q9/wG233Tag1xIGhkQqjdte/wpPLiPn32MnF+Peb81Enr33qWS7AwcM+nzKrWnHDlpAAWWNiETodSSi8swHArS4+nxqd45rXIhSIQiDA7seAcpayDvQLPzvbJkJwmbh2G6n87mPZFL95iQNXGtmZzZ1JJMqtatOp9wcuQYGj4V3wDklLqA2Mrj6NM8TXHyuqIgEaK6evWWLml/a2oDKSnrNNTWs1twU1ywgZ2eoYgtJtuWUrR7sTsXn5+dTDMX69XQNl0spWRUVZD347DO1O+/1KleycJjG09amUuvW1tJnxS5g2TgcNM9yjY5swTsWo7mVA+rjcZpb02l63dZGysWkSaqKeVmZirnguJGOVmj+n4TDvbekdEZBgRqX1IwQBpqMxWKECBq9Vix+9rOfYenSpVi5ciX2228/HHXUUfjpT3+KuXPnIj87VcIAsHjxYpx00kmYN2+eKBYjkKZADIufWYGPt7QCAK6cNwGXHzMBev3gBP2z60FJCQVUNjbSguZ0qkJbySTtOoZCqnZFOKyEhJYWpVhIsTtBGFw4KxT7ubMLIu9oUwpXQ8Zdil2Vsl9zMDK7WbFLFaeu1evVMbNZWTeZVIosm5pGc4FeTxYFm00J3ImEcucBaI5xueh9VnY2bCBB1GhUgjnv1E+dSufV1Kh6FB1dfgIBYN06uhdWUAwGej8UUtfkjFbptKqPsXkzuThxpfHiYvqc1q5VArzNRgpFfj71u3Ej9cMWhWiUlAW+ViKhKnCzsM41gJqalKXF4aB+udI4b/Q0N6tig8mkSpIRDALjx9PnzRaXiorcGLeGhtysWMkkjauujqwcY8eq/19fsjhJzQhhMDHslI1Se3uMxZ133omioiLceOONOOOMMzBx4sT+HFeXPPfcc1ixYgU++eSTbrWPxWKIcVQuAP9Ou3gikUBCcn/2GP7MevvZfbbdh8V/XoV6fwwOiwH3nDkdx+5XjFQqmbXTOLBw7vetW2mx4x0/ztSSTNLuGQsRDQ3UvrGRFhLemeIdQ6GvJDv8FgSCazx0hAO0s49nKxYGQxI6XRp6fTKTbtZoVBmkksncCtMOR667E1shWCHhWAoWeEtLaT7gHXjOFMfxCeEwCepuNwnEXGti1Cjqi62knFHJ7ydh1OFQmecaGkjpOPhgusctW1TWKg7STiToXINBFdADVJE+Tnlrs5Fw7fMp6wvXsPB6yTJSW0vHPR4a28aNZFEZN46uwxXFGxrIwhEIUFuvV2XDYhegUIgUBE4Tu2ULvZdIkBJhNtNnbLVS/waDOs6KAUDXSCbpc9yyhRSewkKVjSuZJAE/nVabP3l56v/KweA+n4ov6YjZTPM6u43tjuz1j2PvuOBidsyGiBZCd+mOTMVpZnVaesjk1p5cV6dpvQs1Xb16Nd577z0sXboU//nPf2A2mzMB3EcfffSAKBo1NTU46KCD8NZbb2ViK44++mjMnDmzy+Dtm266CTfffPMu7z/77LOw8+wlDAofNerwwiY9kpoOJTYN509KoaR/Msn2iERCjy+/9GDHDgeSSR3q6x1IpfRIJvXQNA0tLWbE4wYUFkZht6fQ2GjB9u0OhMNm6PVpmExphMMGxGID67YlCMLuMRhS0DQd0mnyQdbrAbM5CUCPeFwPvT6NZFIPkykJqzW183gKkYgRiYQeOp0OBkMaFksKqZQemqaDpmnQ6dSy6HCkYLfHAeig12uwWlNIpw3QtBRiMRNMpiTicQP0eh2s1iSSST0sljQKCiJIJAyIRvUIh40wGjWYTGlYLBp8PiN8PhP0eg02W2pnpicNHk8cHk8csZgBiYQO+fkxTJ7cjry8BNrazHC7E9Dr00il6P6SSR0iESMKCmI73bR08HjiCAZNCATMO+vrGOFyJXa6aaVgMKSxdasLLS1WaJoOLlcCLlcSen0agYAJkYgRPp95ZyB3DKWlYTgcKZjNCQSDZkQiBoTDBsTjRuTnx2AwAA5HAuXlIcTjBoTDJlgsKYTDBhgMafj9FkSjekQiJgSDhp1W4RSKiyM709bqYDan0NxsRSBghtWa2lmTJAmfzwJAQ3u7ZadVJY6KigDy8xOIRIwANEyY4EMgYERNjQt5eQkYDLkijc9nRjBoREFBFEVFUZhMucc1DQiHjSguDsNiGRmuJsK+xb2fG7A1qMMFk1KYXjA0VotwOIyFCxfC5/PB7d59HGyvFYuOrF69Gr/5zW/wzDPPIJ1OIzUAW7kvv/wyTj/9dBiynFhTqRR0Oh30ej1isVjOMaBzi0VlZSWam5v3+OEIu5JIJPDWW2/huOOOg6mrfHsdiCfTuOONtXh6eQ0A4NjJRfj1mdPhsvY5xKdX+HzAK68An35Ku2cNDbRT6HaT2b2hgQUU2uWqq6MdLQ7QTKVol3CEuDuOALItFUPzTAgjGw625grWmpaEmvaNmYxL0aiqNZNMqqBmdnXiTEQuF+2cx2K0I56Xp1yneAdc05TLTTBIVzIYyPe/okKlpDabqT0XyOMaEADNK16vsoawFcZiIZcak4ncf/bbj9oaDHQfyaSq57B5M425qEilim1uJqsIZ1iqrKTgcHbTaWoi9ymHQ7lhsStYWxvNg8kkWVgmTcrNiud0Up/t7ZSC1m5Xwel5eTR/cmVqu53Oq6+nz8jtVpmrOM7FYiErTShEFhqOi2ErRjRK55aXkwVk6lTqR9PoHqdOJUvJxx/TZ+1wKDcoTs+bTFL76upd3ZQ41fjYsd2zWPR0/ROE3dGdZ+rUB5fhq7oAHjt7FuZO6Hux4N7g9/tRWFjYLcWi16u4pmlYuXIlli5diqVLl+KDDz6A3+/HjBkzcNRRR/W2291y7LHH4vPPP89577zzzsPkyZPxk5/8ZBelAgAsFgssncwWJpNJJoY+0N3PrykQw6XPfIpPtrQBAK6aNxE/Omb8oMVTALnpBdk/l90TWlpUwN+OHbQI2e3Kv5rdn9ifOxpVLlNCf5IETUfynRQ6h91aOvvu8TFOqUrQM2UymXKEVKtVVePm2hfsnsPfe04H6/OpKttcUI4zw8Vi1BenkbVYVLwVF44rLqa5g2tMBAKkYLhc9Lq1lY4VF9M1QyE63+UiYTkep7HV1Kjif5zRimM3TCYVJ1ZcTC6eO3bQ+04njYOre6dSdF9cnI8DmrNdPK1WOpcz4nm9Sqni+hdcVNBmo/vgubGoiJSR7dtp3CYTKTesVPFnYbPRtdNpup7HQ/dWUUGfUWMjjYXrZnAl8oICGkN2Zr54nPoYPVoVCWSF0eulvpua6IfjZ7IJBlW/3aU38sNAF+4TRja7e6aSO2MrbOahk1t7ct1eKxYFBQUIBoPYf//9cdRRR+HCCy/EkUceCY/H09su94jL5cK0adNy3nM4HPB6vbu8Lww9K7e14ZKnV6DeH4XLYsR935mJY/crGbTrd1YwKRTKfY99rVtaSIhIJlXwdnaF3GyhRfxnBWHw4RgKhnelAbXD3RFWCKJREuxYIAVUDQyu4m2x0E44zwss9EajJOBy2ulYTNWw8fvpfM5QxBaB8nI6FgzSDj7XveAaGICqNcGVs00mujZnTAoGSdg1GFSxToeDBGQONPb7VbYmv19lrCorU8klJkyg89avJ4Gdk1ewYrFxo8p85/GQwsDB8bEYtWFlxGikudNioVgH/vyNxtw6HxwrwjEvxcUqDoOtO5wViy1LDgcpJevW0efhctF9tLVRX6kUKTEcG8PjZeWqsJDaFhfvKsBztfWOBQYHI4vTYBXuE/ZeOM2syTgyiqP0WrF4+umnceSRR4o7kdApf/mkBr94+QvEU2mMK3LgkbMPwriiHmwJ9ZHOCiYFg7Sb5/fTAmQy0cLT1KSCsINBWkjZLYBTUMbjKpOLIAhDT7a3bXZhu+zvKAdfcxYoFt4BdplSgh67KHHWJs5exPMEbzbw7jvXwwgGlcDu9ZK7Dbv5cNpYDugOh2ku0euVJYSVIpuNBGpOB9vaStYQh4ME6O3bVeA2B2WHQqqeDlteCwuVFYYC2VVK7JYWmv9GjVJpeAFldSgpoT5cLhL6s60hqRTNlXo9KTalpTTOpial1HEKVs6MxVYMDm7X6UhZam6m8el0SlHgjHycWSmVot+bNiHLrU1VHLdYVLpfrtHBWft4zo/HaTwWC1lDUqnBzeLUk8J9gtAVHLxtMuzlisVJJ53Un+PoNUuXLh3qIQhZxJNp3PL6l3j6o20AgPlTSnDPt/aHyzq45ruOBZPY37m1lbKLsL8w+wMHg7RIcyaReFwpFYBYKQRhuMGF6rLpqPin02qXmHeqWSlg10iHg35zxiLOEsU1H9iCwIU12V2SBXZ2r0qnSWDOdjHiCs0sQLMywC6YHg+NqaWF+udYkESC+uAUtokEzVtbtpBQX1GRa9XwepUQG4vR+PV6mv+iUVUbgq0KgQDFjhmNlJWpoYHacKxEaamyirBCwbUxRo+m/tnliK0yTifd46hRNJ7mZmqTl0fzLStVbBVi16C8PGW1icepf7+f7t9sJguEz0efeXs7XTs/nz6XSCS3GF12Cliu1QGQosQKU2mp+l8MtEtSx3UI6FuaW2HfJBQn06DD3IlZdhgikZJCv9EYiOLSp1fgf1vboNMBV8+biMXfGNx4CiC3YBJAEztX2jabaQFrbKSFjyvx8m4noKwTgiAMX7rKD2KxKHcmQO3Mc4VoFvizYzZYyOXaCbyxEAqpgGlNo/mipEQpIRz4y5YEvV6loK2ooPYeD8032cXabDaai9jFiHezbTba4U8mlXsVx0uwBaCpic4ZN44EeIuF2uj1ylWIXbUsFjonHFZWDA5Mt1qVBcbjoZ17i4X+ZquHy0WKQnMzXXP9euB//1MWHRbUq6tpvGz14VoZBgNd32Kh+9qxg+JFuI4QW2ucTjUvu1z02RcW0jmVlUpJSCToOlw3o6MbE7uh+Xx0HY5V6cxSMNBKRcd1qCMOBx2PxSTmQuiadFqDL0ICyUAXEO4vRLEQ+oVVNe344Z/+hwZ/DC6rEb/9zkwcM3nw4imy4V1KjjVqb6fJu6iIFvrWVlp02tpocWJLBQsKgiCMXNgiwbAVg4Vetl5kB4JzUT3OFBWLkZDP/bS00G+DITfWg12M+FwWqFOpXHdLTvoA0HtcM4OtHQUFqgJ3ZSW5bLKlIB4nIbuigl6z+5HTSULztm3UxuEgAb+9XSkhHGgej9O8ByhrAbsSNTaSgmO1knDv9apMVxxb5veroHG3m8YQDquigTx2LgzY3k73yMrW1q00v2a7YLEy5nbT/XNmrpYWurfiYuqPLUYGg6oplEqpKuCduRKFQjT2kqwlaLAtBR3XoY5kV0oXhK4IxJKZ+SbPJoqFsI/w0srt+MmLnyOeTGNCsROPnH0Qqgq72KYZBNivmKvCtrTQ4hMI0N9btiiXgVBILZBipRCEkQ8L+53BVg52Y2JLJQvAPp9SQJJJep8tGppG8wgH/XKqVC70xnFZ7PPPmZ5aW1UmqlSKrptMkmDsclFfbjellK2ro5iC9nZ6n60TiQS1YWVk+3ZqM2YMCdpGIwn3paUU/FxXR2NPpaionMVC16uoIOE6EqF+WPDljFNcfI6VK5dLuWkByqphMKhCfkYjteFga3aTMptpbh0zhqwgrIwYjfR3SQlZXTjuIRpVFc+zq3YzrIhwTAZbYPj/wAwXS0H2OpRdsZ1JJOg4W8oFoTN8YRJMbCYDLEZxhRL2clJpDUv+9TV+/94mAMC8/Upw33dmwmkZ2sfKYqEFavNmmrw3bKD3W1ro74YGWqxDIZWhhN0mBEEY2expBzjbOpkdc5FdbZsVCY6hYEtFMKhiNlhZAFR7jicIhVSsBWckisVUalmrVWUo8nrpWFMTXctsJuG7ro4UCI7d4DoOHOjNVbhtNhLqa2tJaLbZSGjnbFYcyzF+PF3b41EuVuxOBOQGP7e10b1wrAdbd/i6XOlbp6Nx+3w0v1ZU0P243So7EwevcxVy/gyya0qwK1pFhQrs5qxdwSApWzod1ZowmajN1q30OZWXk0LE1ovhYimwWOj/0tbWuWIRCuXGhwhCZ7RHyI3CM0LcoABRLIReEogmcc2Lq/DO140AgMXfGIcfHzdp0OMpsuHFiQP3WlpUfQqfD1izhhZqdltgIWEAajkKgjCM0OlUYTwWKA0Geo9rQ5jNyjoAKMG0Y1E9dktIJpUVgoPAXS4SWgsL6XdrKwn0RqOKc/D5VA0HnU7VcNi2jfqaPJk2QL7+mgRsh0PFfbH1w2ZT4+NinZxOt6CABHeuO1FURMJ+VZVyfwJIIN+0ScWdGQwksHOgtk5H8yUHaadSdD67jYXDNNe2t6vd90CAPguO2cgOpuZMTGVlu7owsXDNbk/Z5zQ3U9sxY6hNdrG9SIR+smMnhpOlgJU1Vq4GM82tsHeQia8YIW5QwAAoFvPmzcOmTZuwadOm/u5aGCY0RYCzHlmOjU0hWIx6LPnmDJw6s2LIxsPVsZuaaJFrbKQFSa8n68S2bZSrffNmWoR5UWEXKEEQ9g10uty/OY0puz/xLnm2AsGuQdnxGFzojc8xm6mv2loSFuNxEoA5/qK5WVW5ZkWluZnmI6+XBOqGBnp/xQoKkuZ6GfE49V9bS9dlod3lor+3bKE2Hg8pLaNG0T1EIjQv5ufTvPjJJ3SspISul22J4XgMkwmYOTO32F8oRP0Hg9Sez9++nc7hdLMVFeTCFAySIL18OTB/PikwPSkOxwHY7OqUStG9ms2q+J/BoGItQiFyI+N6EeXlw8dSYLV2rlwNdJpbYe+hNSQWC5x++ulobm7u726FYcKyTS2493MDwqkQStwWPPL9g7B/pWfIxtPeDnz1FS3iLS20ALIPczhMC+vWrbTgshDAx0WpEIR9A04nmw0rCmzFiEZJ2eCaDNmJHDg2ggOAAVUsk/vR6Uio5qKbZjNZDDhYORCgXXZA1Taw20kITibpp6AA+PBDmq+sVlVXhwv9xWIqSJxdqQBSWlpbab5jwTkaJeWFlYGmJrKCNDaqbFJ6PTBxIikUnDWPPwcuusdFRfV6UiaMRpUytq6OxjR2rEqLy5mk6uroeoccooT47PoaexLsLRaVNcpkorFs2ULHbDZV7LC5meb/8nIVOzGcLAXZipJU3hZ6Sp2Psj6U5dmGeCTdp98Vi8WLF/d3l8IwQNM0/Omjrbj5ta+QSuswY5Qbj549G8XuodtyiUZJqaitVfESkYiKrdDpKJCRC1Gx0pFI5GaNEQRh34KtDtmuT0zHDQcOXAZyNySyq31z8gejUbnYpNM0J23ZQu4/NTWqSF5NDQmaHg/NU/n5KjCca00kEspqwLUo2I2TM0VxMDfX5NA0ul5NjUplyylzZ80i620iQYqNxQIcfDBloWpsJPcpTSMh3eWifuNxskKw4tXcTMHgEyYoNySnk+7bbKbzuJ5FXp7K4mQ29676dLZbU1sbjaGsTClUOh1dhy0qNpuKBRlulgJRJoTeUNdOE1BZ3sgxb0mMhbBH4sk0bnrtSzy7nIreHVSYxhM/mA2nfWgf9Lo6WgQTCVIuEgmyWoRCKgCwtZUWX15gJEhbEITeBu5yjQZ2p0ynSajmgGFNo9c819hsykXKYlHB1KwM6HQq7bXDoYrUseLDGas41avZrILNk0m6TiCgMmHF4+p4IKBiFmpryQJRWEhuoRzo3dJCigLHPnCmpOZmVXiP6/yYTCTEr11LVmC9nuI3JkygdqxQADQXW63KZYyzUPW0+jQHQDc0qKxQyWRu/IvTSQoaF9RjxU4sBcLewI52sliUe/YBi8XVV1/d6fs6nQ5WqxXjx4/HqaeeigKJThrRtIbiuOTpT7F8cyt0OuCa4yagwr8GFtPQpj2LxWiRDgbJxL9jB/2t19Pi1dxM7gR+Py1eoZAoFYIgdE7H2hddwW24HgYHOQMk1GoazTcct5BKKUXCbFYB3vn5qhgfp8NmCwGgrBZcA8NoVHETTH29ErQ5Za3ZTH1FIipBBcdRbN1K7fx+sk7k5dH5LLSzEA+QUuL10t/JpBLSS0pUcblIBPj0UxozK0ceT+6YbTYVC9Hb6tMFBdQmFKLxsoLB6Wnz8lTdjbFjd1UeRJkQRjJ1PvrSl3v2AYvFypUrsWLFCqRSKUyaNAkAsG7dOhgMBkyePBkPPvggfvzjH+ODDz7AlClT+m3AwuDxdb0fFzz5P2xvi8BpMeL+787EkeMK8I9/rBnqoWVSMG7dSrtvbW3KFSEapd0rXrS4MJUgCEJn9NQ1kq0W2TUvsoO8OZ6rtVUpLZpGQm5xMQnbiQQJyRwoznFhnIGJFQK2bHCcB+/6GwxKceEUuXY7/TaZ1LlNTTRmn4/GWFSkqm5brfT6yy8pQ9Ts2XQu9wHQWDmTVCpF7QMBUiJcLspg5XQq5cTrJeuH2azclvpSU8JqJXctVi7YMs0F8rjauc1GFhlB2JuozbhC7QMWC7ZGPP7443DvjEjz+Xy44IILcMQRR+DCCy/EwoULcdVVV+Ff//pXvw1YGBze/boRlz27AqF4CmO8djx69kGYUOJCYhhUkYtGabduzRpg9WqV3SkYVAF9bK0QpUIQhIEgmVRKg3HnSsoWB65FwSla43ESntvbSTBPp2mOiseVgsIWBra6xmLqOMd22O0U85BIUL92OykO2YpFIkF9sBsWB2UnkyToc0Y8dpMCyAqxfTtZfjluobZWFaArKKCxezx0jVCIzh09miwezc2q2J/BQD9s4YhE+l5TIi+P0vY2NKiigBwzx5m8xoyhdoKwtxCJp9C2s0Be+b6gWPz617/GW2+9lVEqACAvLw833XQT5s+fjyuuuAI33HAD5s+f3y8DFQaPp5ZtwU2vfom0BhxSXYCHFh2IfEcnefuGgGiUFr+mJgo45KBF3v3jXb2GBlX8ThAEobdwDAULv+z+lO0+xRWjOZibBXm9PteC4PerdKk6nUr7Go+TYM4F3rhPjqtgrFYS7LODxg0GUkSCQeXCVF5O8yMrIw6HSn/LiS04QJv/5krd7Ka0bh317fFQu8JCer15s4q9yM8HZswg6zBbjeNxUijGj6cxcvA1x6dkxzr0pKYEZ3qKRlVAeSxGr93u3btTCcJIZGMTCTH5dhPctpETEt3rkfp8PjQ2Nu7i5tTU1AS/3w8A8Hg8iGfn7BOGNam0htv+/hUe/3ALAOCsA0fhV6dPh9k4CJWEugm7NrF/bX4+mcFNJnovFKLFlX2UBUEQegsrD7yBodcr60R2/QpApYFll6hkUrlmciG+VEpZEOx26pOrfxsMJDC3t9MmiclEiofXS0pDPK6K0lVXU1ufj66dStFufTJJ71sspIRkW06sVuWSxO5KVqvq12ikfrOLCDocuUUAOUCc3U7b2kjhKCtTcWzBIFlAuJ6HppEywpYZvV4FXEci3a8p0bEmBCtVJSVSE0LYO2HFYkKxC7rsIjzDnD65Qv3gBz/APffcg9mzZwMAPvnkE1xzzTU47bTTAAAff/wxJk6c2C8DFQaWUCyJy/+8Em/vrKR97YJJuPToccPiYebc57EYKRFmszKfp9PKHSCZpDbdMa0LgiB0B86KBKi4B65yzbERHAcBqErVvFPPgno8rlw1ObYilVJWAlZeuH4DH0ulaEdep1P1JNrbqS+LhYT65maVnIIVnlGjlIJhs9E57L5kNpPi4vVS+5oasjAUFpK11+NRgn8opFLnFhRQv62t6r5Y0XI41H1zcHsgoGp4sIuV2UzjZbemnuR3kUxPwr7E+gZSLMaXOId4JD2j14rF73//e1x11VX4zne+g+TOGc1oNOKcc87Bb37zGwDA5MmT8eijj/bPSIUBo84XwflP/A9f1flhNupx77f2x8kzBt6uvKfFIRolP1+u8BqP0++SEnInqKmhH6uVFjq/XwU/Sp0KQRD6SvY8wi5JPGexK47ZrOrkcHsO4GYrB7suZaeK5fSoFgsJ9DYbCe/Z1opkUu3KBwKqZgML61z3wu1WKWwrKsiSkEzSeRMmKEtLWxuNma0skQhd0+sFqqpoTFYrWUK4JgXXw2Crhaap9N5cV4NjKCIRGjenmm1uVnUlfD6qo2G1Up9Wq/rpKaJMCPsC6xsDAIAJxfuIYuF0OvGHP/wBv/nNb7Bp0yYAQHV1NZxO9QHMnDmzzwMUBpYvdvhw/pOfoMEfg9dhxh/OOQizRufv+cQ+EI12XizJ4VALs05HysOGDWqnS9Nol2vZMlqwYjGVeYV9eznVoyAIQn/AVgTekWchmwV5LlIH5MZddFQyOBUsWzcMBpWdiXf9TSZlbS0upr65YnQ4TO/zJgsXnWNLyKhRNE9ytiSOPeD6EsXFNGdu2EBF9CwWckOqrCQXKItFpb7NVhhYoeLaGGzN4OrgnAI3ElGWEKeTlJjmZhqP201jCofpXkwmsrQkErvPCCUI+zLrG3daLPYVxYJxOp2YMWNGf4xFGGT+/VUDLn9uJcLxFMYXO/H4ubNRWWAf0Gty8HV2saRAAPj8c5Uy0Gym95qa6LXHQwuU3U4L3ubN9DqVosVs+3a109exaq4gCEJ3YKUgWzng2hTsnpRO05yVPc9ku12yCxAf56BkTkfLigIrG6GQcnFyOEggLy2l+Y8rVrM7VSJBFgW2PrDrld1Of5eUUHXtpiaaD7kIXUMDMGkSXY9jNcaMofc8HlIsbDsTznAgtdNJikN2liV2+dI04IADqO/6erqHUIjasusVoLJBeb1qrA4H/fh8uZWyBUHIJZ5MY2sL7SZMKHYN8Wh6Ro8Ui6uvvhq33norHA5HlwXymHvvvbdPAxMGluzMT4eP9+LBRQciz9ZFTsB+hIOvuVhSNEoVtJuaaCFyuWgB+/RTWnwmTaL0jAYDZSn54ANyf8r2XQ4GaZETpUIQhN7S0dIA5LpVWiy5WYzY/adjBm62wvJvFqp1OpWOlt2pOCA6FKJjPh8pCGyh8HqVcB+Pk8DP2aR4o8VopOtwdimbjRSHQICUCrebNnOyMzaNG0d/b9tG829ZGbljmUyq0F00SuOx2+kaPh8dd7vJ3aqqSs3d7e10H1Yrze0ul5qfs12lGLt910rZgiAo1tYHkEpryLOZUOIeWSa9HikWK1euzNQxWLlyZZfthkPAr9A5mqbh1/9aiweXbgQAfPugStx2+jSYDAM/u3NO9exiSe3tZH2wWmnx+uILWqy2baOFLxRS+dk/+ghYv165FfAOHisZgiAI/QEL7Fy8jlO0ptPKMro7l0udLje2Ijt4m+MzspUUrlmRTitFxGZTu/6plHKZ4mDq4mJ1rUSC3JtKSkjg93pJuOfK1Js20XUOPJBec6xFURH1F4nQe9xfJEKuS6EQzbGhEM3RpaX0vk5HilZVFQVT8/1w2t10mvrQ68ny0rG+xO4qZQuCAKyqoS/k/pWeESdT90ixePfddzv9WxgZJFJp/PTFz/Hiiu0AgKuPm4gfHTN+0B5a9k3m3atYjCwYHMy4YQNV0jYYaMELBun4++8rtwGTiRasQED5AbOPryAIQn/AlgROkQooV6juuO6wS1S2csLVs2MxlcGJLRcAKRIOh6pgbTDQhko8TtaD7AJ6bP2IRmljJhymzRabjc7j4ndVVapoHrtLNTSQsO/x0HzKxfiKi6kfDqhuaaFzPB5SHrh2R12diovLTvPK7lQA9cf1NWKxXMtHMkmvpVK2IHTNypp2AMDMSs+QjqM39HibetmyZXj99ddz3nvqqadQVVWF4uJiXHTRRYhxyglh2BCKJXHBk//Diyu2w6DX4a4zp+PyYycMqibMO3jsOsCKhk5Hi2NTEy0+Hg+Z/BMJWkg3bAA++4x25LZsoRiL+noqANXSotwLBEEQ+gPe7MhWIjq+7gqdjuYvq1XFU3RUTgAVsM3vsdLBx9jKwcf4NRfOa2yk7EycES8Uovmwro5cSWtrab41mVSQ+NatNJ+2tdHxpibVdzqtCu1lL+GaRu1Z4eFYirY2FS/XEYtFuUOVltI5bLHmgoHjx0ulbEHoitUZxWLkfUl6HLx9yy234Oijj8bJJ58MAPj8889x/vnn49xzz8V+++2HX//61ygvL8dNN93U32MVeklzMIYfPPEJPtvug9Wkx4OLZuGYySUDft2O6WR5sWlrU761BgMtZA0NtHDb7bRAciXXHTtodysSocU2HqfFKhQa8OELgrCPk0opi0JHpSI7yDu7TXaqWI6jyHal0uuVZSH7GAv4breKh2CXKxbqCwqU0M/ZogwGsjawZWLbNhLmzWYS3MvLSfFgK4XRSO+nUvReMEivuRBeXR314/XSvWzfTgpIUZFy1eLq3G1tpNh0VvWaK2WzW5XHMzSVsqXmhTDS8EUS2NhEQs7+ozxDO5he0GPFYtWqVbj11lszr5977jnMmTMHf/jDHwAAlZWVuPHGG0WxGCZsaQ7hnMc/xtaWMAocZjx2zkE4YIjSyRYU0E97O+2c2e20QxYKkRUimaRzamtVQTzeieNsKjqdciMQBEEYaPT63AJ4AM1N2UpFdhu3m4ToeJzaORy0ccIxByaTco/iInepFFk5OFuUyUTzJsdo5OfnpqjlDFOcpnvUKDUurrbNsRJ+PykbZjPVtOCYNJOJfmpr6doWi0qMUVCgqorHYqSohMM0d5eWqs/B4VBWiI5C+1BXyt7dOiRVuoXhzOfbfQCAygIbvM6Rpw33WLFoa2tDSYna7X7vvfdwwgknZF7Pnj0bNTU1/TM6oU98scOHc/74MVpCcVQW2PDkeQejumhg8yF3lk42O+0hQDtizc004SeTtOg1N9OxdJp2x1palKVC0hEKgjBUJJMkNHNANm9scMwB/3CaVk5N63KRgsGWC70+N8sUZ0yy2agt98OxFk4nzZGRCPWZHa+RTO4aV8HxEZx+Nhymc7nehtutak1k155wu1WVbLZMsJLALlJGI/XLblJ83GSi63Q1Rw9VpezdrUORCCk8olwIw5WPN7cAAA6oHNhN4IGix4pFSUkJNm/ejMrKSsTjcaxYsQI333xz5nggEICpY245YdD535ZWnPfEJwhEk5ha7sbj581GsWvgZ9KO6WQBWlD8fmDlSvqdn68Wyq1bydQei9Gi5vOpoMRwWIrdCYIw9MTjynUpO0OT2ZwbN6HXKxcmk0nVjcgWzJNJZVFgYZvTbLMAzsHbDgedZ7fT3Oh0qpSwbJkwGlXxPLdbWTNY4He7KftStouWz6fS2ebn098tLdRXdkA1K0Q85o4bPdmZrbLpzA12MOlsHeqO+5YgDAc+2EA7rUeMH5nZDXqsWJx44on46U9/irvuugsvv/wy7HY7jjzyyMzxzz77DOPGjevXQQo94z/rm3DRU58ikkjh4LEFeOzcg+CyDryy11k62WiULBLbt9PfnN+9sVG5BiSTNNGzhSIapR9RKgRBGA5omsoUxa9ZqM6GLQIul1IeXC5lrTCbaXOF4yxsNpoPudp1NJprHRk3jhSC5mbqz2Qiyy9nrIpEqF+uhq1pqsioywVMnkwF8GpqVHrZkhLasff7Selhy0ZxMZ2XfU8WiyqWx3UzspWIUEhtFAHDw/2os3Uom925bwnCUOOPJrB6pyvU4RP2EcXi1ltvxRlnnIGjjjoKTqcTTz75JMxmc+b4H//4R8yfP79fByl0nze+qMflf16JeCqNoyYW4eHvHQib2bDnE/uBjulko1EqardjB/nmsuJQVEQLZ3s7WSm4kjYv3rz7JgiCMBRkB2Zz2lie38xmlYmOg7s5lapORzv+nJSCXXA69sEZpmw2lTrW7SYlIBolhcJup/OjUVUXgtPOcsG6dJoCrzWN+jCb6f38fIqnGDVKWQxYoQHodUkJ9cfxbiYTnbt5MxXYY0WAi+XV16ugcK4xZLWS0gAMH/ejjutQR/bkviUIQ8nyTa1IpTVUFTpQ4bHt+YRhSI8Vi8LCQrz//vvw+XxwOp0wdNiyeeGFF+B0Dqwfv9A5L63cjmte+AyptIYTppXit985AGbj4JU1zU4nm06TpaKhgRYZv592iTi+IpFQikddHS2WvHsmCIIwlGRXxeb0rhwDoWnKqqBpKq4BUBYDVkry80kA9/tVMLbNptyljEZq43QCEydSX2y1cLlU9jueFw0Gal9ZSX22tqoselwZ3OEApkwBpk5VgjwHiq9bp4r0RaPk/uRyUb0Lp5P637SJ2o0dq6wtVittCNlspHzwOLItEcPF/Sh7Hcra88zQlfuWIAwHPtzpBnX4eO8Qj6T39FixYPK6SEBdwNsXwqDyp4+24pcvfwEA+OaBo3DnGdNhHIRq2tlkp5PltIIOBy3AgQBZKDizSjBI7lD19fS+ZHoSBGEo6FhfB1AuMuymxDUkNE25MXGWOj43W3Gw2Wj+i8eVIsFtODharyeBnvfm7HaaJzmYm91BWblxOEiQN5lo999sJmF92zZSMkaPVgHj06YpF6qWFlI+YjGad202snIEAspSYjIpt61Jk8iK0dioXK6yK253FoQ9nNyPOqY170hH9y1BGE6M9PgKoA+KhTB8ePzDzbj5ta8AAOceNhY3nDwFev3gloCPxVTMRChEPr2cnaS9XZmmo1H6e/t2SnPo94tSIQjC0MGKBaCUhWyLBAc8Mzpd7q43Z2nS6WiOM5tJCPf5qJ3bTfMj/z1qFL3mzE06HVBdTRaGZBL4/HPacCksJAWA28ViKrtTKkVjLCtTrj0zZpBAnUjQ3Lp1K829nP7Wbqdrt7fTfTgcdH4oRErE6NH0vtVKCk8gQBYGruK9u8xOw839iGtotLXlumV1dN8ShOHEtpYwNjQGYdDrcEj1PmixEIYHT/53S0apuPiocfjJ8ZMGtZp2NEqL2PbtqgIs5073eul4YyOZ2TnN4bp11L69XapmC4IwtLBiwBYHdpGx20mojkRU8TqbTQnXnDrWaFTCql5Pc192kHdzM819+fnUtr1dKQ1tbeTWNGUKveaMT1u2kGVjv/1obO3ttFnj81FfiQRZH6xWVQdjyxZSLIqK6Hc6TWOy22kMFRXUf1ERzb91dTSORIKsGgAFcFutqo6GxUL3sHkz3RcrWh0Dsoeb+1HHGhrhcOfuW4IwnHjjyzoAwJyqAnjsnXyRRgiiWIxgnlq2BTe++iWAoVMqNm6kBS+ZVEGF7JPMhZhaWshc39REC1xNDS2U2a4HgiAI/YtKK8fWB4Oh8yKbPH9xATubjTZGWLDmWAcWuLlPi4WEVKdTxZIFg9Se07y2tVHf7Baan0+WgkCAftts1J7nw2CQ4i3YVYmVFJOJ2nM62nCYjnOaWh6Dy6WyR/GGTjRK13A6qS3HZeTnk0Lj89GcnE6T2xMrCn4/zfGtrSoInM/PDsgeju5HQ1VDQxB6yxtf1AMAjp9WuoeWw5sRpVjccccd+Nvf/oavv/4aNpsNhx12GO666y5MmjRpqIc26Pzpo6244RVSKn54VPWgKxUALTaNjcptIBKhxRigRW/DBjq2eTNlC+HFi1MkCoIg9BXOyhSP04/K6ETzYXaGp+yUsdlYrSRIsyuT1apqQqTTJOxz7YrsQnYFBSTMx2IqS5PFQv2wwlFQQK5IBQWUiSk/n9p++aWaLznt7KZNJITbbMr1yWoFxo9XsRpGI/XDVopwmCwNlZVkjQgEqM/ssXP8Rn6+CiTPz1dB5GYzjTESoTma62h89RVtDFVWqgJ94bAS0G02FZA9XN2PRJkQRgIN/ihWbGsHAMyfIorFoPHee+9h8eLFmD17NpLJJH72s59h/vz5+Oqrr+DoKmpsL+TZ5dsygdoXza3GT4+fPOhKRSxGpnTO286LYShEC1U8Tn7CjY0qE1QwqBY9QRCE/oArWBsMKjtTIrFrxWv+mwOQORDbaCQFwOlUx3mjhNPCcqE6h4OUgUSC5sB4nNrF4yTAFhVRe6+XdvCLi5W1Ij+fYhxSKRV3pmnKRbS1lYRxu10J7+EwWR44RfeWLTSPchVtgNqNHk3XsFppHuZsUTxWm40UBLZcmExkqTAaVbVtk4nGumWLUhI2b6Y+OFbDYlEWDq7WzQHZ4n4kCL3n32saAQAHjPagNG9kf1lGlGLxxhtv5Lx+4oknUFxcjE8//RRz584dolENLq9/Voufv/w5AOCCI6pw/QkDp1R0ZUKOx/XYsYOCA30+WjBqamgBa22lxamuTgVn19crdwBBEIT+hoOnHQ4SlkMhQNO0TO0IFpq5WjWfY7GQwMx1HAwGpQgAKo6iooIEak5QwYJ9IKCsGek0vTabSai221VKWVZE2tpobOk0Cdy1taQUsLDPwdWbNlFmJ72e4iEiEbq+16syQ4VCNK5YjCwKoRCN3WRSqWojERob3zcXxdPrVRVvk4k+B3a9CoeVdSE/n+7D7yelpLiY2trtKmFHtgVI3I8EoXe8+RUpFsdPHdnWCmCEKRYd8fmoOuG+kuL2/XVNuOr5VdA04HuHjMbPT9pvQJSK3VVPpUA/K/x+Wlza28kH9z//oYXMaKSFuL6edsKiUbWzJgiC0N9wXYZUiuYafm00JpFKmTJWCE7xyoJwdixAKqUsEsEgBTUXFJACsWGDUjpKS1WcBlsAWHBn4d1mI0FcpyPB3+kkhcLvJ8HcbqfzvF6VHYotCKkUvccB2j4fnc9uXvn51IfbTfOrzUZzLVtq/H7qi5Wn+nr6TNhqkEyS9djppPe8XnKBYsWotpZel5TQZpHZTMfcburb7yfrBispXCG8I6JMCEL3aY8Byza3AgBOmFY2xKPpOyNWsUin07jyyitx+OGHY9q0aV22i8ViiMVimdd+vx8AkEgkkBhBjv6ratrxwz/9D4mUhpOmleIXJ0xCcgBMAFw9NRajxYqLLnHgdSKRQDhshN2exPbtwJo1wBdfkLmefZ2DQXq9U+8ThD2Q7PBbEPYMKwkclJ39W69PIhYzQa9PZqpec0ByOq2UAE1TmZ3y80mwZ+WC6z3Y7aQYcPpsi4WOs9uT30/CuNmsavVw2u2NG0lJcblUmlmTiY6PGkV9+P1k4Q2HqY+iIhoLp3k1GOj6FRV0jKtvm0y0+eN00nvsilpfT+/X1qqNIS5+p9fTeLxeqq6drQCwxZkrhxuNqoI4B4T7fCoIPRyma7Kr2b4AywwjSXYQhjeJRAIfN+mgacBBYzwoc5uG5fPVkzHpNI3D2kYWl1xyCf75z3/igw8+wKhRo7psd9NNN+Hmm2/e5f1nn30Wdt7mGebUh4HffmlAOKnDpLw0LpqcxkAV1G5psSAUMsPpVA9RIqFHMGhEY6MNkYgBTmcC8bge4bAR27c7sG6dB+m0DqmUDj6fGcmkHu3tIzdVmiAIwxtWEnS6FDRND00DUikd9HoNJlMSyaQOgAE6nQadjmsspGEyadC09M5zdQA0WK0puFxxOJ1x+P0WGI0puFxJ2GwpWCxJbN/uQjyuR3l5GAaDhlDIgGTSCIMhjXgcCIWMsFpT0OsNiMd1MJtTsNtTSCb1SKc1pFJ67L9/M6qrgzCZ0vB44giHDYjHjdDp0mhstCIYNMFoTMNmS+20sGgoLY1C04BIxIDWVgvy8+Ow25NIJHRoazMjEjEindajsDCKVEoHkykNvV5DU5MVNTVOaBpQWhpBQUEURqMGiyWFgoIYYjE94nEDHI4UrNYkDAYNqZQOfr8ZPp8J5eUhWCwa2trM8PstiMf1SCb1MJlSSCT0yMuLIRQyw+2OYdw4P8zmQSpOIQh7IZoG3LbKgOaoDt8dl8IhxcNTJA+Hw1i4cCF8Ph/cbvdu245IxeKyyy7DK6+8gvfffx9VVVW7bduZxaKyshLNzc17/HCGA02BGM78/XLU+aKYMcqNp849CA5L/xua2F+2poZ2p9hNIBol6wMf//rrJNat+xolJZORTBoRDFLmEIOBdsjq6lRbQege2ZaKEWtEFQYJrjfBO+dc1C6VUm456XQSqVQKFosB4bAxUy2b4wlSKdrdd7lUpWyzWcVcAGSFYKtAPK5iG3bsoLaBgEoTazQqqwfHefj9dNxgAM48E5g9W8VyJBIUo7ZuHbVzOlXRO85MNXEixSz4fCo4urVVWSTGj1cxIZzdKRAgy3I8TnEXZWXqfnw+ssBwZiiXS6Wz1evVPXE2LJ77uYhpOKzSxhYXU40Nj2conoChI5FI4K233sJxxx0HU1fVAAWhB3y0sQnff2IlbCYDlv3kqAGR7/oDv9+PwsLCbikWw/MOukDTNPzoRz/CSy+9hKVLl+5RqQAAi8UCSycOnyaTadhPDNFECpf+eTXqfFFUFTrwxHlz4HH0ryUgO54iFCLFQNNo8bBayY84laKFr72dsz7pUFJixMaNpkzuc52O+kinpeid0BuSoOloeH8nhYGHszdl/wA0t8RiSojnNNesULDiwBmaAoE4dDoLjEZTpj1Acx7HTHDBN85kN348Cd87dpAAzzEILFjn5dF5TU0qCxW7CHERPSA3MNxmo/ciEbp2Ok2KxY4d1KfbrVLQptMk8EejNPd6PKSolJbSfMwZsCorqVq3ptG8HAxSBj5Nowrc8TgpFdkheG439Wsw0JgqK5U7GQdZ19bmpos1mVT/qRS5SU2YQH3vy1meRoL8IIwMXvmMgrZPnF4Cj9M2xKPpmp487yNKsVi8eDGeffZZvPLKK3C5XKivp2IieXl5sNmG7z+kN2iahuv++hlW1bQjz2bCH8+djYIBUCp27KDfvJC0tdGCFovRYsc50NvbaeEzGoHmZhtqamgR2rGDfji9YJZxSBAEoUdwrQi2SuTlqRSw8bjKNsRxA/G4ytDEKWWNRhLI9foY4nE78vJoftI0pVCw0Gw0qorX7e00l+l01Ka9nX5cLhKiORaDLSSscESjqjhdMEjHR4+m4zQOmittNlJcXC5K6drURHPr6NEkqCcSdB8NDfR3QwO9z9WwOb0tV/FmRam0lI653dRvZSX1zXEYjNFI/cdiKt6i455bx1oUFgu9p9ORkjVqFH1egiD0nWAsiX/uLIp35gEVQzya/mNEKRYPPfQQAODoo4/Oef/xxx/HueeeO/gDGkD+3zsb8OrqWhj1Ojy0aBaqCvu/TkdrKy2K+fnqPYeDFlM2/8di9PdXX9EOXmsrUFvrQDqtdtXa2qQ+hSAIPYd31Ll+AxeWSyRIgOZMTckkzT+A2mX3+5Vw7HJRm5IS5R5kNJKXr9VK/aZS1I6zLoVCym2Tj2/bRhsk+fkq+5NOpxQGtqCMGaPch0IhshZwMLPRSEHWHPhts9H5yaTK2hQO5yo5Viv9uFxqDua0tImEqnjd1kZWg44uSGwdMZlovE6ncn1iuK5HNEqfU2eZm7qqRVFSIrUoBKG/+csnNQjFUyi2ajhojGeoh9NvjCjFYgSGg/SK99Y14d5/rwMA3HLqNBw2vrDfrxGLkVJgNNLfbFJvbaW86a2tKkCyvp7aFhTQgpuXF0VtLe2K+f20+AiCIHQku+p1NtkuTnq92t1nywBneOIK183N6j2uDeHxkHAcjVI/7OJjtdJclkjoMxmaLBb6SSbpPKNRpYq12+k9riURj1M7t1tZTgA6v7RUuUFxLQqvF5mNFo77sFqpT6+X+q2upvPb2+k+4nE6npenYiQ4rs1gULEZwSDNsVzFm6/XmYCv15NiEolQ39EoKRd2O92vz0f353bvvgq21KIYWFKp1LDM+iMMLqm0hr+v2ooKlwELRqURi8WQzi4KM8iYTCYYeLLrIyNKsdgXqPNFMrUqFs0ZjYVzRvf7NdgFats2WnSSSVrw4nFa9NraaBGKxVRhJ7dbLTSBgAlNTbTAZi/2giAIDO/GJ5OqyjSgXI14DeMaDmYzCbEOhyoyx+mu02maqzSNBN9USsVGZNej8PtVwTqdTsuc43arWAy9XrkEeb1kXbDbSXA3GpUFtqCAxpBOq+vH49Q3WwO4andFBf3NaWqrqsiFic8tK6N74XSyNhvNw9n9AzSm2lra2Jk+nRSSYFD1y65KnREKkasSZZKiewsGVYyEzUaWlvLy7lkeRJnoXzRNQ319Pdrb24d6KMIwIJJI4eJZbhh0brjNGmpqagas2HF38Xg8KC0t7fM4RLEYRiRSaVz+55VoDcUxtdyNX548pd+vwUoF74KxRWLtWlp4OPja4aDFtbVVBQ5++SWdV1NjRyCgqt2KUiEIAqBcmyj9q1IeWKBPpVQchdms4h7SaZp/OtaD4BgBu53O1zSam/LylKuQ0UgCusOhBH8OcmaFprWVBHqnkzZU2ttJ8C8rU/Uj0mllMfH7lSuT1apcQ7madSql3KH0eqWgrF1LMROjRtF5ZjPdF7tnsSVD05Tlg92kNI0sw3V11EdFBd2Ly0U/bW30WVituQHWiQSNiy0NgHJl4mxXY8eSC5XERwwdrFQUFxfDbrcPuRApDC3bWkMwuFPId5hh1eJwOp3Qd1ZtchDQNA3hcBiNjRRIXlbWtyJ9olgMI3777/X4ZEsbnBYjfrdwFqym/jFLZcNxFXl5FBy4bh0thn4/7ZZx4SYWAFpalAl90yZSQnw+2u4aQqudIAjDEE2jnW62fmZniOPq1hxbYLWS4MvpWb1eEvyDQdrM4ErZOh2lZuXYA04iwYXZ2KLBKWFZsQgEEnA6c2M3OL0qWzw4SJsVBw7MtttJ6eACcJpGx7g/vm44TNc0m+kao0eTtWLcOOVCRHMmfQZ5efQeuyoFAnTfmkbtduwg5YBTzWbjcNAcXVpKikR2DARX1uZzxJVpeJFKpTJKhdfrHerhCENMJJ5ENG2A3mhEab4T4WAAVqt1yBQLAJkESI2NjSguLu6TW5QoFsOE1TXteHDpBgDAnWdOx9gBCNbmQGyjkRax9nbKIrJpEy2KnFklFKIF1W6nRauujhbicJgXVHlsBEFQmEwqNoJdjjqzZLLrEisNbClgwd/lojmmtJR+R6OqSjbHHSQSNHdxnADHJ5SVkYDNrj8Wi7J05OVRe86IkbIozgAAQ9NJREFUZLGo/jjzFLsN8VicTnVfHM/BAvq4cXQvvFFjt1M2poIC6sPvp7FoGh3jVLDl5VwZXFkYnE5lLTGZqO/Okhxy0LfZTGPek+IgysTwgWMqRkpRXmFgaQxQ+sw8uwlG/fCxXPHzmUgkRLEY6UQTKVzzwmqkNeCU/ctx8ozyAbkO79S1twObNwMbNpCCEQqpQMb6etoZc7s5tSy9l+0rLQiCwLCgrmk0j7BykY1Op7I8cYyFzUZKAW9iWCzkrhOPk6tPKkXCPkBzV0uLUhiMRpqPON4gFlMZl8xmEtYDgVQmS1IgQIJ7Xh4pLxaLcv8sLKQ5r6VFuRaxgsMxtiUl9DcXkKuspPGVlJBLVUUF9cOuXSz4s0Vh4kTqJ5Eg64XBQMpTtoUlkaBNnK7Wc85MlUjQuEVxGHmI+5MQSaTgi9DEUuQaXl/i/no+RbEYBjy4dCPWNwZR6DTj5v+bOmDX0etpodu4kSps19XRAsw+xJxBJRKhRTuZpMUsFMpd/ARB2Ldh5YCtDWyhyA7Q5jWKC9rZ7ST0p1LKNcjpJCGdrRLxuIohsNnoOG9uUHFOOo8VGVYyOAWtyURzFr2nZVLEcsraujpqU16u5jx2zSouVtaNkhJlEYhE6H23W1XIrq0lpWDiRGrLLkiJBN1nxc6U9B0tCruzMnBa2ra23ID0aJQ2g2pr1XwdDEr6V0EYiTT6KY1dns0Em8kwpJmgBoqhc+gSAAA1rWH8/r2NAICb/29avxfBy4aq0ZJi0dhIi3tzswpIbGmhdrEYLeRct4J33qJRsVgIgqCqTns8JOxyalgW8jlNLMcUcPAyZ0ICVEHNaJQUCpOJ5qDWVpqbgkGVLcrlIteiykpyeeJU2G43Cdf5+coi4XbTOfG4HokEtTMaqY9sYfzAA4Fp00gJKC6m+IgZM4CZM6m69NSpwLHHAscdR4XtOPudTqfi1DoqB6GQsohYLLtaFjp7LxseX1sbfSaRCG0C1dRQv5WVdG5bmypuKggDxfvvv49TTjkF5eXl0Ol0ePnll3dpo2kabrjhBpSVlcFms2HevHlYv359TpvW1lYsWrQIbrcbHo8H559/PoJsjuxAc3MzSktLcfvtt+9y7Fvf+hYOOeQQpAZZEHnxxRdx9NFHIy8vD06nEzNmzMAtt9yC1tbWHvUTiStrRYk7d1dg6dKl0Ol0e0XWMFEshpg7//k1Ysk0Dq324sTppQN6LZ+PftJpUija2ii+gtPLckCgz6cW/WRSgrQFYV/EuNOezbvrNhsJ7Xl5pEwUFZE7D8cSmM0qiNlmU/EJbL1gpSKZpHZc/bmujt7n9K2cPYmTR6RSdH1OQ8vuVByXkJen4r/iceo3Hs+tlcHjAkhA53FNmAAcdhj9zJxJysbYsSq+A1AbKmYzpX899FBSRBoaKKi8ro7mzbY2Gk9XNSK4GF8s1vVnzgXq8vOpXU0N9V1ZST+c5Sk/n8bVQ7lGEHpEKBTC/vvvj9/97nddtlmyZAnuv/9+PPzww1i+fDkcDgcWLFiAaJbWu2jRInz55Zd466238Prrr+P999/HRRdd1Gl/hYWFeOSRR3DzzTfj888/z7z/wgsv4PXXX8eTTz7Zb/UWmFQq1aXl4Oc//zm+/e1vY/bs2fjnP/+JL774Avfccw9Wr16NP/3pTz26TmOAPhOPzTQgyXm6Szw7q8YAIIrFELJyWxv+/nkd9DrghlOmDLj/ZUsLLbSVlbQobtlCVolgUGU9aW+nxS8aVTEZgiDsO3A8BFeDZhcmh4ME2vJyVYiNsyyZzcpikV3pOp1WSgCgApdZEYlE6LjFQgJ6KERCe1WVUhA4ToKVk0hE9afXkyISClGMRX19ttumHh6PGmsspuI58vJUv2xdSKVIKRg/nhQmj4fG1NhIbceOBSZPVp9JMEjFRNetIwUgP5+Ugo7uSdEouTFt2UKxbVu20OuurA0c1M3B6BMmqJTf2XBK8N0pKoLQF0444QTcdtttOP300zs9rmka7rvvPvziF7/AqaeeihkzZuCpp55CbW1txrqxZs0avPHGG3j00UcxZ84cHHHEEXjggQfw3HPPoba2ttN+/+///g8LFy7EOeecg0QigaamJixevBh33nknJk2ahFdeeQWzZs2C1WpFdXU1br75ZiSTycz59957L6ZPnw6Hw4HKykpceumlORaSJ554Ah6PB6+++iqmTJkCi8WCbdu27TKOjz/+GLfffjvuuece/PrXv8Zhhx2GsWPH4rjjjsOLL76Ic845J9P2oYcewrhx42A2mzFp0qRdlA6dTofH//gYrrzge5hcWYQJEybg1VdfBQBs27YNxx57LAAgPz8fOp0O5557LgAgFovh8ssvR3FxMaxWK4444gh88sknu9xLNi+//HKOPHnTTTdh5syZePTRR1FVVQXrAPtQSozFEPK7dykL1OkHjMJ+Ze5+67czP16/X7k61dVRDnVeoHl3LhjMjaOQeApB2Pvh+AQg151J0+hvjr3KjqHIyyOhlmtV2O1qRz47zSzHQMRiql92leI0sF4vHYtEqF+vV1WM5iQ6nGCCU75ardTe76f+jEayoBQUUFueu4qL1Tnl5dQfWyB4bly/nu7f4VDC+/jxpJBs3UqvfT5ShNhFyekkgZ/rAcViueczXDeIq3JzcHhbG42/M0WEMZnox+ns+jgX2BNGHpqmIZIY/J07m8nQb5uYmzdvRn19PebNm5d5Ly8vD3PmzMGyZcvwne98B8uWLYPH48FBBx2UaTNv3jzo9XosX768S6Xlt7/9LaZPn45bb70Va9aswbRp0/CjH/0I//nPf3D22Wfj/vvvx5FHHomNGzdmrB833ngjAECv1+P+++9HVVUVNm3ahEsvvRTXXXcdHnzwwUz/4XAYd911Fx599FF4vV4UFxfvMoZnnnkGTqcTl156aadjZIH+pZdewhVXXIH77rsP8+bNw+uvv47zzjsPo0aNwje+8Q1oOyfOh39zF35x86/wyP+7Dw888AAWLVqEzZs3o6KiAi+88ALOOussrF27Fm63O5P+9brrrsOLL76IJ598EmPGjMGSJUuwYMECbNiwAQVdmUc7YcOGDXjxxRfxt7/9rd8tPh0RxWKIWFPnx7/XNEKnAy79xrh+6ZNN49kLPpv/AwHaVdu4Efj4Y7VbptPRQhkO02+jPBGCsE+Q7SrEGxHZwj9bDFiZyC7GxvUcWChmAddsJuG+oUFtXHBmJJOJ+s9O58rns/tTLEZWgMJCOiccprmLA7NZGeB5rb5exR7YbCrTFAAYDGlYLBQ7UVlJfer15AbKNSD4HLa0+P30d3V1rvtVKKTmSPfOPSAOHi8tpT6bm3ctQMfpaPPz1XvsMtbWRse5qF1n/x9Or5sdzM1w/MgQpr4X+kAkkcKUG/416Nf96pYFsJv7Z6Gvr68HAJSUlOS8X1JSkjlWX1+/i9BuNBpRUFCQadMZbrcbjz/+OObPnw+Hw4HPPvsMOp0ON998M376059mrAXV1dW49dZbcd1112UUiyuvvDLTz9ixY3Hbbbfh4osvzlEsEokEHnzwQey///5djmH9+vWorq6GiSecLrj77rtx7rnnZhSQq6++Gh999BHuvvtufOMb38jEVZz6rYW46LyzYTbqcfvtt+P+++/Hxx9/jMMOOyyjJBQXF2cUllAohIceeghPPPEETjjhBADAH/7wB7z11lt47LHHcO211+52XNnE43E89dRTKCoq6vY5vUXEyCHiqWW0FXbitDKMK+piS6oHdLYzFgiQmZ5303w+2oGrqSHrhNtNC5PPp4QHsVIIwr6BppFAD+RWyNbpVOrYZFJldzIYVHAyoIKuLRYSyh0OFZvF1aW5pgX3mV0fIp2meYhjMbj6djBISks6rVw1efMjP58Ef4OBlACDQcVLcP0dj4frUiShaaRYFBWpGA9WiNxuYMqUXZWrcFgpHRywnUwqq0U0qu6JrT1Op7r37AxQgQB9Lp2R7crUVR0KrrjdmWIRCtHnIWlnhb2VY445BocccghmzpyJMWPGAABWr16NDz/8EL/61a8y7VKpFKLRKMLhMOx2O/7973/jjjvuwNdffw2/349kMplzHADMZjNmzJix2+uzpWFPrFmzZpeYkcMPPxy//e1vkU5rqPfRTu5BB8yE2UgTjsPhgNvtzlS77oyNGzcikUjg8MMPz7xnMplw8MEHY82aNd0aGzNmzJhBUSoAUSyGhEg8hddXk2/hojmj+6XP7EJN7LIQDqsc7pzGMRRSO2ac4SQWU8WtBEHYN8j+vnMsFVssE4lcpSBbiI7HSagHcgvIcQ2JhgaV+IEtINEoCeoclM3zT0uLCsC22ah/v18Vr+P0scmkqm/Brld6PblNWa0kXPt8yKSXLSsDWluTmQxKDocKNueU2mPGdF6IjudMr1cJ9kYjsG2bUhJ4/GVlNDaPR6XfZThGravNzu64MhUU0Fj5HrKtRrsLFBeGPzaTAV/dsmBIrttflJZSwpmGhgaUlZVl3m9oaMDMmTMzbToKz8lkEq2trZnzd4fRaIQxy5UiGAzi5ptvxhlnnLFLW6vVii1btuDkk0/GJZdcgl/96lcoKCjABx98gPPPPx/xeDyjWNhstj26hE2cOBEffPABEonEHq0WXdEUjCGeoi+515VbIFGn0/U53axer99FAUp0skPs6GqHYwAQI+oQ8O81DQjEkhiVb8Mh1d4+9xeLkRk+GFSpCTdupEBBXqDZZM4FrBwOWqg5rgJQO5OCIOybcPpXVjTSaWXVAFRtm0BA/fb5SOjesYMEYK5r4XKRAmA0qqKbJpOyPrDFQacjYdlqpbmJYydCIRXn4XCQEsBJJTi4nM/neY7Pb2kB0mldJjtUOk3XLy0llyiXa/cCPweec7XudesoNq2mhubahga6b45b45S72W5J2a5MndEdV6aOWaJ8PvrdVaC4MHLQ6XSwm42D/tOfSWKqqqpQWlqKt99+O/Oe3+/H8uXLceihhwIADj30ULS3t+PTTz/NtHnnnXeQTqcxZ86cHl9z1qxZWLt2LcaPH7/Lj16vx6effop0Oo177rkHhxxyCCZOnNhlkPieWLhwIYLBYI4LVTacGna//fbDhx9+mHPsww8/xOT99kNTQGVX0O+myrZ5p1kyO5UuB4Nn951IJPDJJ59gypQpAICioiIEAgGEQqFMm1WrVnXvBgcIsVgMAUvXNgEATppettsHrbuEw5RlhDO3GI206NfXK/eB+npaLCMRWtC4NgXvBGb7UguCIGTDFZ+zC9/ZbCQUx+NKIeEsS4CycnCgdiym6lkkEvQ7P58sCQAJ6TYbzWF+P/UbjdIPWynY2sEF8nw+pcSUltL5kQjPc/pMVe1EghQKnY7mxtZWNTd6PLkCerbAz9cwGilTVXOzskRw/IXVqu6lY82K/nBl4ixRuyuuJwgDQTAYxIYNGzKvN2/ejFWrVqGgoACjR4+GTqfDlVdeidtuuw0TJkxAVVUVfvnLX6K8vBynnXYaABK6jz/+eFx44YV4+OGHkUgkcNlll+E73/kOyrsKMNoNN9xwA04++WSMHj0a3/zmN6HX67F69Wp88cUXuO222zB+/HgkEgk88MADOOWUU/Dhhx/i4Ycf7tX9z5kzB9dddx1+/OMfY8eOHTj99NNRXl6ODRs24OGHH8YRRxyBK664Atdeey2+9a1v4YADDsC8efPw2muv4W9/+xuefvE1pDUNjm7EtIwZMwY6nQ6vv/46TjzxRNhsNjidTlxyySW49tprM5/5kiVLEA6Hcf7552fGaLfb8bOf/QyXX345li9fjieeeKJX99tfiMVikNE0DR9sIMXiyAn94+/W3k4LG5vKg0HaPdyxA/j8c+Cddyhge9s2tYuYSNDCyv7LYq0QBGFPcCxEdgaoVIpe+/1qs8LhoPdZKTCZSIDnCtusqLDFga0E7LLEhfE0TbkMJRIqxoKDrxMJVbGbU8/ytfV6DXY7WR0CAWDDBjqHlRCuAF5fn5v6NbvIHafAnTqViudNnUoKxowZNE67nRQina5zt6SOBe84Y9aeal50xp6K6wlCf/O///0PBxxwAA444AAAFJR8wAEH4IYbbsi0ue666/CjH/0IF110EWbPno1gMIg33ngjJ6XpM888g8mTJ+PYY4/FiSeeiCOOOAKPPPJIr8a0YMECvP7663jzzTcxe/ZsHHLIIfjNb36TicHYf//9ce+99+Kuu+7CtGnT8Mwzz+COO+7o9Wdw11134dlnn8Xy5cuxYMECTJ06FVdffTVmzJiRCSA/7bTT8Nvf/hZ33303pk6dit///vf4fw//AVMOPBQ6nQ4V+Z34XHagoqIiE5heUlKCyy67DABw55134swzz8T3v/99zJo1Cxs2bMC//vUv5O/MCFFQUICnn34a//jHPzB9+nT8+c9/xk033dTr++0PdFp3o1P2Evx+P/Ly8uDz+eDm9B6DSKM/ioNvfxt6HfDlzcfDZu6bv2MsRnnR29vpJxYjF6iGBlq8tm6lBd9iUf7Q4TCd09xMixwv4N2zWiQAJEHGrt75HApCLvJMjTQ4GJutB5xOlhUIi0XFRhQW0msW3tkN0+8nF6L8fFXsLj+fFAS/X1ktOMjb5VJWEi6oFwiQi1MoREI+u1tZrQkEg+tx8METUFlpQns7UFICzJqlxlJfT+NOJCiewutVsQsVFXSPX39NdSwKClQ8GhcQjcfp3JISYPbs3MxP2XSWra9jFXBhZJBIJPCPf/wDJ554Yo987qPRKDZv3jwoNQSEoSeZSmNdQxDJdBolbusuVbazSafT8Pv9cLvd0A9xirfdPac9kZ3FFWqQWd9IRVpGF9j7rFQAyixvsVBtitpatcgnk7QoBgK0+AEqy0k6netewDt/2ZliBEEQOsNmozkjnVZWBQ7U5jS1RqNyz2SXS5uNBHCTiTY30mllAeFUsFxJ22BQdTD0ehL2IxESyLk2hs1GCkFtrXJdAjgrVSqT0YmL/XE8mdVKVov2dtqAqa+nsXq9SuBni4zFQn1wutviYrqXVAoZhYXrbXSGuDIJwr5FnS+KZDoNq8mAIte+92UXxWKQ4bRjlQW7WYl6QDxOi3F9vXJFaGujnbdIhBZBzuRiMtF7BgMtvAC1B1QGF6OR3pOK24IgdIVOp4KpWejmWhBsHY3FVLVsg4GsCckkzS2cdpYDsSMR6pcz1TFOJykwrJywi5TJRP0WFJBgb7WqGI9Uii0paXi9KsbC6cwNlGblwuMhBaGyUs2LALW12VQ8WnaNCrOZ+tQ0uq/uKAqiTAjC3o8/kkBbOA4dgFH5Nuj3QT9zUSwGmWCMzAFua99dPqJRUioiEbJK8E5aUxMtevy6vJx+sz+w2UyLocdDblOBgCosxQGagiAIncHVuDlQm1O8Ggy5QcqsLLDlYdQoEvo5eQTHXPB8w7v5eXl0TiBAykQ6Ta5DOh29Nhiob5eLrB/JJDBpEm2sxGIU+0DF9RJwu8kK0dqqlJ6O6PUq61Q2HHwdCql0tpzlKpmkzZyiIko5KwiCkEilsb2NJj6v09JvhQhHGvvmXQ8h6X4MaeHaFZWVpDBwjAS7BMRitBByQLfdriwTnAbR5VIpJXk3jzOisE+xIAj7Huw2yQoEWzHZYsBxETxf5OWRoM91FriNptE8w21bW1UxPE4Kw3NQIEDXy89XygSnsOdjJhP1MXo0MHEiHfN6qV19Pc2FVO9CQ3ExbaLwmDtjd9mZuI4Efx4cpM4KzJQpEichCAIl5tneFsm4QJXuJq5ib0cUi0GGLRX+aN9KXGdXddU0sk5EoyqAG6D3vV5VSbatjRZvLobHgYqcCjIQUHniTSZaSNn6IQjC3g8HZQMqGJvf5/SqnMmJ4yjcblICsrMzlZSoVLTJJO3qc7yExaJcjoqKaL4ZO1YpJe3tlNHObKZ5jauAR6N0fksLzVn770+KBaeYDQbJKsKB41ZrGCUlpBywtbanheY4kNtmo/kxEqF7d7vpnkSpEAQBAJqDcQSiCeh1OowusPdLKYGRiigWg0yZh1airS3hPvWTXdWVUx36fLTQBoPA9u3K/SkapYW8vl75BY8ZQ4tsbS0txCwAWK3KV7qpSV1Pp1MFqCT+QhBGFizQswsTuyRlKw6A2ngwm1WWpWSSBHC9nuIUPB46lk6reIqSEhWLwAX2XC5qz3ER0SjNOWVlZG3ggO6CAnrNaWDjceCLL2i+GjVKWWItFpXRyeWifjkpRV6eCo4uKqLrrlzpx9ix9DdAcxpnZ+Lg8Pz8PWdnkuBrQRB2RySeRL2f4mfL8qyw9mN185GIKBaDzJQyStO1rTWM9nAcHnsnlZO6QXZVV7OZFvtolBa/8eNJUNi+nXbpOMCwuJh23OJxSgFZVUWLfFMTLbRGIy3QNhsJAK2tJEDwwq6Cu9MZxWbfSlYsCP0PC/ucqY2VeIaFWW7DLovptMrolm1lBNT8YDSS1bK0lDYcEgmaA1gpYHcnrk+RSJCgXV1N80A4TO/b7XQ+uwVZrTR3GI00T7hctLPPmZrYDdNup2vrdBQPFo0C48bR9bZsoblr7FhSBrhQndVK1+cK2U6nqtgdiSATN9HRAsGB4jzXWSzpHAWgrwqCKBOCIHQklU5jW2sEmqYhz2ZCgaN3Mt3ehCgWg4zHbsbEEifWNQTxzteNOGPWqF7107Gqa3b6xFSKFATe1UulyLUgkaCdwZIS5XPc3g6sW0d9Wq0kPHAaxeJiWoSbmuh1IkFtmpsj0OvNiEaVWxUXyWJXKr1eCUOMuFQJ+zqcOtVmo++f00l/s6sOJ1Dg2IZoVKVadTpJiAdU6lRWFAAlxIfDZGFIp2nzYN48Zbmsr1e1IZxOZaGMRmmOyM9Xgn9Jidrdr6ykuWT9eqqNE42SQM/W0LFjyQra2KiCoINBlca1qIgUllRKuUVNmaICvzkFbTxOY8/LI+UiHFYumgYDMq5NrIB0ZYEw7GbDUBQEQRD6A03TUNMaQSyZgsmgR4XHBp1kvxHFYig4fmop1jVswEsrd/RasQBUYCHv2lksqpBTfj69p9ORUsAVaIuLVfVWrp7LeeDz82mhDoVIkODsUW++SVW7OV1tKhWD3a6yqXA2mGSSxrJjB7W12ZSQwUHjPh9diwUoQLlpcDsu1icIA4lOpxRgrkNgNqsd/GRSJTXgStG7s9BxTILZTIK70ahqNHBRtOJiZXFwOGhXfscO2kmfOpWU+O3b6Xuk06kd+1Gj6DzaiafvpdVK4+GqzoCqPh2L0bnHHUeKgsuVW8V6+3Zqy+mlo1GKWZgwgfoPheg8nQ7YuJG+s5pGrpbTpinXoW3bqI3XqzI9RSL0vff7qY8pU5T1g5UfthZkF4/rzD3J4+nawrA7C4RsYgiCMNA0BGLwRxPQ6XQY47XDaBjaAnfDBVEshoBvHliJ//fuBvxnfTO+rPVhannenk/qBA4s7LgwZ+/qsfJgt5NwkZ0Okn2WDQa1a8ouE+wTHY8Dp50GfPwx7UaSkBRBeTkt+iUlwOTJKj5Drwe+/JIEE4AEmcJCSmvr85EQ5PEo9yq/X2WnApTFhTPBsMtVtsKRSilBymRSO52soJjNKmYklVIFAc1mlSqSBUTevRX2frhKNKcpLS0loZ0zp1VU0POxcSM9h4EAfTcMBvouNDaqYN9Egp5d9v3PzyfhmnfmW1vphzOreb303LvdKpVqWZkqUjlhAvVhtZLlorGRflh5Ly2lH07F2t5OrkWaBhx+OPVhMND4+LtTVsaF4uj7zdWeAeqztlZtHrDSY7WqOAgOsObMR5EIfV5cWyJb+WCLQjJJ42pspLlhyhQaG39uHQOeu+OetCcLg1ggBEEYbHyROBp3xlWM8tj22dSynSGfxBAw2mvHSTPK8drqWvzq72vwzAVzem0+29PCzMoDZ4XKViyYZJLiMrzeXB/ucBioqyPBpLKS3CDIpSqC2bOB6dNJqXC7lQsDuy00NtI57Oqx337A2rXAmjX0fjpNglkkQn0Gg9R2wgSVb97tJlcK9u1OJOg6HBzqcNC92+20A9veTn1YLPR3JEJ9xeNK6eKdZP5JJukY58dnIZLdMwwGun44rNzB+HNlVxRh8GFrQLZSyNYHtqBxbIDLRc8SxxBVVNDOe2kpuQq1ttKzmF2ozecjIXz6dHo2amvJBWjbNuXyxxYNu50sCpMnkxJdXU3PTCxGz8e2bdSuqIj6ra+n53b0aPrOHHggjSmdpuesulqleI3FqM9Ro3ILvEUi1FdLi7JQciFMjkOoqMiNy8ieF7pSFtrads2SxDEPvIHh8+VaFgB1zGKhz5g/e4DuYU9B0qIcCEL3GMwkAueeey6efPJJ3HHHHfjpT3+aef/ll1/G6aefDm3nDt3SpUvxjW98AwCg0+ngcrlQXV2N4447DldddRXKsoq93HTTTbj55pszr91uN2bMmIHbbrsNRx11VM71X3zxRTzwwANYuXIlUqkUqqur8c1vfhOXXXYZCrpK5baTWCyGOXPmYPXq1Vi5ciVmzpyZOaZpGu655x488sgj2Lp1KwoLC3HppZfi5z//eabN0qVLcfXVV+PLL79EZWUlfvGLX+Dcc88FAEQTKdx4y6/w73+8hi2b1sNus+Gwww7DXXfdhUmTJgEAWltbceONN+LNN9/Etm3bUFRUhNNOOw233nor8vJ6t5k8UhDFYoi4Zv5EvPllPf67sQV//XQ7zjqosk/97WmC6eg21Vm6xWz3KIAEg2yBYsoUUgr0+nqcfvpkVFSo/m02lZnF7QZWr6a/uSKv0UjXmD2bdjL9frJihELUb3s7teUdX1YIOGe8309j9/vpnJIS4JhjaDyaBnz2GcWK+Hz0k5+vrBE8EXMGHIeDBDWdjsY8ahQJlTU1dLy+npQovZ7GEwyS8uNw0H2UlpKwmkzSsVCIBEK2ksRi9ON0UttUio7zjjfHpexNZKcp5YDgnp2bzlifuBAaBzObTPQser3KCseZy5JJenZCIXrfaqX/Ke/gezy0q24wKEW0sJD6LC6mHfSxY2kcoRD97LefsorF4/S9mDULWLCAnr9Nm1TsEO/SW610TnExKekcM+Hz0fU++4yUE5uNjpeW0nkVFfT8h0KkrHi96vPjfisqdhXIOWVrSYn6fqZSu1osu2JPykLHc/e0gdHZMcmiJAj9R7bbIH/X2Qo5kGmPrVYr7rrrLvzwhz9Efn7+btuuXbsWbrcbfr8fK1aswJIlS/DYY49h6dKlmD59eqbd1KlT8e9//xsACeB33303Tj75ZGzfvj0jdP/85z/HXXfdhauuugq33347ysvLsX79ejz88MP405/+hCuuuGK3Y7nuuutQXl6O1atX73LsiiuuwJtvvom7774b06dPR2trK1o5gA3A5s2bcdJJJ+Hiiy/GM888g7fffhsXXHABysrKcMy847ClJYRPln2Isy+4CCd+4wikUin87Gc/w/z58/HVV1/B4XCgtrYWtbW1uPvuuzFlyhRs3boVF198MWpra/HXv/6125//SEQUiyFijNeBy4+dgF//ay1++coXmD4qD5NL3QN2va7cprJ3HTdtop3/QIBeu1wkdJeXK2tGKgXU14dRXNz5dSwWEtZsNuqvsZGuaTaTgMfZZtJpuk5LCwnn6bQKHPd4VIpKq5Um1GBQ1eFwOkl54bSZBgMpGbNmUaaZxkYVcM47sGPGkJLAAacWC70uLVWWi8MOo88iGgVWrACWLaPPw2ik3ehRo5C5b4+H2tbXk0LDc5LdTgI2C5qsRLCSxJYU9uXnzyEWU7vR3I4tM7wrz9mCWNhm4RNQhRFdLvp/ud3UL1uFuKI6B+umUtSer59IqIxE2alGWSjk+gKJhArQt9tVvA5XR2aFjqvBB4M0VqtVZTDiys38OSUSQHNzCC6XORNL4PfnFmErKyMBXdOU4B2P534O7FbncND/xmik91IpGtfEifT8cdByWRndAwu9nQnGrGTzfUajNA6/n94zm6k9WwNHjaJnl79zNpuq/7B9u1K8rVZ6lqqrVUY3/m7G44OTCrU35+7ueE9dmARB6B6cXIGTJvDGYFsbzVGdbT70F/PmzcOGDRtwxx13YMmSJbttW1xcDI/Hg9LSUkycOBGnnnoqDjjgAFxyySX44IMPMu2MRiNKS0sBAKWlpbjlllvw+OOPY926dZg9ezY+/vhj3H777bjvvvtyFIixY8fiuOOOQ3t7+27H8c9//hNvvvkmXnzxRfzzn//MObZmzRo89NBD+OKLLzLWhaqqqpw2Dz/8MKqqqnDPPfcAAPbbbz988MEHuPfe36B65mGIJ9N47Lm/YXyRMxNX8cQTT6C4uBiffvop5s6di2nTpuHFF1/M9Dlu3Dj86le/wve+9z0kk0kYjXuv+L333tkI4OKjxuGjTS34z/pmnP/E//CXiw9Fhcc2YNfrSpCIRkkJ2LqVBBqvl9r7/SQ0RyKkFNhs3Xf98XhI0Pf7VeC2u4PeZLOpzFMd02h2FHI6E346u4/SUlJW2L2J8+5zGl1AuTVxvAawqxA3dixl09m6ldoUFpIiEg6TMtHUpPzkS0qU8Mw76wAtBBs3Kjevykrlf8+WDk4VXFlJY2LXr6YmUpI4A09JCbVjl5kdO+iH79XtJuWpupo+C5uN3HxGjQK++op2zNln3+mk/lmA5XookQgtWhMmqJ39QABoaFDZjMJh1QdbCdjKFAyqlKYc3B+LUf+jR6tCZskkudg1Nal4ly++8GPq1HxUVdHueWsrXWPMGGDSJBX8y8puOk3jCgaVRYyvybFBrNBxMDG75XW1y9eZYNzxvY4F0zrLVpTdlr9vo0cDc+bQ3519H4YyFaooAIIwvGltpbkm22BgNtMPp4bnKvb9jcFgwO23346FCxfi8ssvx6hR3U84Y7PZcPHFF+Oqq65CY2MjijvZkYzFYnj88cfh8Xgygv4zzzwDp9OJSy+9tNN+PRwA1gkNDQ248MIL8fLLL8PO/phZvPbaa6iursbrr7+O448/HpqmYd68eViyZEnGvWrZsmWYN29eznnHzZ+PK6+8CpFECka9HlVeR06wts/nA4Ddumj5fD643e69WqkARLEYUgx6He7/zgE486H/YlNzCN97dDmevXAOyvIGTrkAdhUkWltJSGM3EqawkIS8xkaa0HozcXVUJroznu626Uzoy7audCWccbDtnoQ4t5t87Ds7t7o6dzcb2LWv6mrgoIPoOizs87HOFK7sXWu2MpjNShjmzF9s3QmFKFDW56PXmkaWAJuNBNmxY+kzmT4dmDuXXM+2bSMBnSuvaxoJxAUF9LmxopSthNXVKf95vo+2Njq3vFwtduEwPUfsCsZxMgUFKqCexzt6NMXcbN9OisfYsX7MmqUsJxMn0ljy8+kzMhhIoM8W3ktLu/4fDqRbTk+VgI4xT7tDhHxBELKJxWj+dTg6P+5wKKv3QM0fp59+OmbOnIkbb7wRjz32WI/OnTx5MgBgy5YtGcXi888/h3Nn5cpwOAyXy4Xnn38e7p2L4fr161FdXQ0T+y93E03TcO655+Liiy/GQQcdhC1btuzSZtOmTdi6dSteeOEFPPXUU0ilUrjqqqvwzW9+E++88w4AoL6+HiVcfXNnvwaHB8GAH/FoFONHF8KSVQQvnU7jyiuvxOGHH45p06Z1Orbm5mbceuutuOiii3p0TyMRUSyGmHyHGU9fMAdnPbwMm5tDOP13/8UTP5g9oG5R2cRitOvNee07woWxWlpI8NTrd23Tsb+h9qvu7nX7usvbHSGxqzadKVw9EVhtNrIUcHxAZ2472f1WVVHfhx5K/08ungZ0bVHie7DZcn17Y7HOd+j3pLDxuHi3n93mfD4gmYwjL0/FQVRU5FZT3p2S2BkD5ZYzHJ7vntLTMY/EexSEvRV2Qe5KxuYU0gOd3fCuu+7CMcccg2uuuaZH53GAd3aCmkmTJuHVV18FAAQCATz//PM466yz8O677+Kggw7KnNNTHnjgAQQCAVx//fVdtkmn04jFYnjqqacwceJEAMBjjz2GAw88EGvXrs1YTbLHX++LIhQjv+PRXvsuGaAWL16ML774IsfdKxu/34+TTjoJU6ZMwU033dSrextJiGIxDCj32PD8Dw/BuY9/gg2NQZz54H9x+xnTcerMij2f3Ec4sxHntO8Iu8Bwdd+uFIuhCizbG+mNMNddRQdQ1oju0pcd+u70Re51LTjsMFJuerLDP1iMxOe7p2MeifcoCHs7nOmOLdgdYSvvnjb9+srcuXOxYMECXH/99ZnsSN1hzZo1ACg+gjGbzRg/fnzm9QEHHICXX34Z9913H55++mlMnDgRH3zwARKJRI+sFu+88w6WLVsGS4eF46CDDsKiRYvw5JNPoqysDEajMaNUABRDAQDbtm3DpEmTUFpaioaGBmiahgZ/DE3BGFqamuByu1Gcn7sDd9lll+H111/H+++/36mbWCAQwPHHHw+Xy4WXXnqpx1aYkcgAP4oDw+9+9zuMHTsWVqsVc+bMwccffzzUQ+ozo/LtePHiw3BotReheApXPLcKP33xs4yWPFDo9SpINtnJpTg7j8m0e6Vixw5yj+F0kxaLKpYXjQ7oLQiDREd3rv7qy2IBnM4kPJ7ho0hkMxKf756OeSTeoyDsC3DtHa4N1ZFQiI4Pxtx555134rXXXsOyZcu61T4SieCRRx7B3LlzUVRUtNu2BoMBkZ1m94ULFyIYDOLBBx/stG1Xwdv3338/Vq9ejVWrVmHVqlX4xz/+AQB4/vnn8atf/QoAcPjhhyOZTGLjxo2Z89atWwcAGDNmDADg0EMPxdtvv40GfwyNAZr8Vn/0Pg479NDMOZqm4bLLLsNLL72Ed955Z5cAcIAsFfPnz4fZbMarr74K6z6yQzPiFIvnn38eV199NW688UasWLEC+++/PxYsWIDGxsahHlqfybOb8KfzD8blx4yHTgc890kN5v/mfby9pmHArmmxKBencHjX4xys6/V2PXFlB5aZzSqzUH6+2gUVhJHKSHy+ezrmkXiPgrCvwFbDtrbcxBSd1Z0ZSKZPn45Fixbh/vvv7/R4Y2Mj6uvrsX79ejz33HM4/PDD0dzcjIceeiinXTKZRH19fabtbbfdhq+++gqnnnoqAGDOnDm47rrr8OMf/xjXXXcdli1bhq1bt+Ltt9/GWWedhSeffLLT648ePRrTpk3L/LBVYty4cRlrwrx58zBr1iz84Ac/wMqVK/Hpp5/ihz/8IY477rhM+4svvhgbN23C9T+9Dps3rMM///IUXnnpRVx11VWZay1evBhPP/00nn32Wbhcrsz9sHLESkUoFMJjjz0Gv9+faZPqST72EciIUyzuvfdeXHjhhTjvvPMwZcoUPPzww7Db7fjjH/841EPrF4wGPa6ePwnPnD8Ho/Jt2NEewflP/g8XPfU/rG8IDMg1CwrIZz4apeBazt/f3EwuK8XFXU9cPQksE4SRxkh8vns65pF4j4KwL8HZ6DiGzedThScHMtVsZ9xyyy1IdxHQMWnSJJSXl+PAAw/EnXfeiXnz5uGLL77AlClTctp9+eWXKCsrQ1lZGWbOnIm//OUveOihh3D22Wdn2tx111149tlnsXz5cixYsABTp07F1VdfjRkzZuCcc87p9fj1ej1ee+01FBYWYu7cuTjppJOw33774bnnngMApNIabAVleOCJ57HsP0vxrQVH4pHf/RaPPvooFixYkOnnoYcegs/nw9FHH525l7KyMjz//PMAgBUrVmD58uX4/PPPMX78+Jw2NVw0ay9Fp/U2SmYIiMfjsNvt+Otf/4rTTjst8/4555yD9vZ2vPLKK7ucE4vFEMtaEf1+PyorK9Hc3JzJQDBcCceTeODdTXj8v1uRStO/Sd+7At17JJ3UIxUwIxGwIh03Qgcd9OY4DK4YjK449EY1kWialgnESif0SPhs0JuT6Kx4uKYB6bgRprwI9KYBji4TRizZz9RwYiQ+3z0d80i8x+4wXJ8pYWTTm+eq3GXATUcXo7h8FHTGTgIlekA8Kz7NPAxdR0c62QJxaZ4VhY6+/b/2eD1NQyAQgMvlGvL5KhqNYsuWLaisrNzFbcvv96OwsDCTMnd3jKjg7ebmZqRSqZw0YABQUlKCr7/+utNz7rjjjpzy8cybb77ZaY7j4cZ0ANdOB/5Ro8dnrXqkB0oNNKRh8EShd8aRTpAhS29KQ7dToci9ri5TZZnfTqd00Bl2HZyW0mXaDdjYhb0A9UwNJ0bi893TMY/Ee+wew/OZEkY6PX+utJ3fs/54HE1ZyoQ83gODQQe4TYA5FYXfPzgBZoHAwHik9IR4PI5IJIL3338fyQ5Bt+HOfOW7YEQpFr3h+uuvx9VXX515zRaL+fPnD3uLRTbnA/BHEoglh3bHMJFM4P333sfco+bCZKTsBvV1Ovh8uTUwGH6/tEymQKFzOnumhhMj8fnu6ZhH4j3ujuH+TAkjk94+V8l4DP6WeowudOwzAbwjFb1ON2CeIZ0x3CwWNpsNc+fO7dRi0V1GlGJRWFgIg8GAhobcYOaGhoZMefiOWCyWXVKPAYDJZBpxab+8w2C8iUQCbjNQnu/MfH4FdpU5xuGgDFKJBGWrGF0y+D6gwsiis2dqODESn++ejnkk3uPuGO7PlDAy6e1zFY0aEWrTw2w0wGw07PkEYZ+B41V0Oh30A50zeA/o9XrodLpO5eOePO8jKnjbbDbjwAMPxNtvv515L51O4+2338ahWWnAhMFlOAWWCUJ/MxKf756OeSTeoyAIgjD8GFEWCwC4+uqrcc455+Cggw7CwQcfjPvuuw+hUAjnnXfeUA9tn6anRdQEYSQxEp/vno55JN6jIAiCMLwYcYrFt7/9bTQ1NeGGG25AfX09Zs6ciTfeeGOXgG5haBBBRNibGYnPd0/HPBLvURBGAiMoCaewD9Jfz+eIUywAKqF+2WWXDfUwBEEQBEEQdgv7p4fDYdhstiEejSB0Dmd+6mtc2ohULARBEARBEEYCBoMBHo8HjY2NAAC73T7kGYCE4UE6nUY8Hkc0Gh2y4G1N0xAOh9HY2AiPxwODoW8JBkSxEARBEARBGEA4cyUrF4IAkFAfiURgs9mGXNn0eDxdZljtCaJYCIIgCIIgDCA6nQ5lZWUoLi5GIpEY6uEIw4REIoH3338fc+fOHdLU2CaTqc+WCkYUC0EQBEEQhEHAYDD0mwAnjHwMBgOSySSsVuteU3NnRNWxEARBEARBEARheCKKhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+sw+F2PBBUD8fv8Qj2RkkkgkEA6H4ff79xp/QGFokWdK6G/kmRIGAnmuhP5mpDxTLDN3p4jePqdYBAIBAEBlZeUQj0QQBEEQBEEQRgaBQAB5eXm7baPT9rEa8+l0GrW1tXC5XEOeM3gk4vf7UVlZiZqaGrjd7qEejrAXIM+U0N/IMyUMBPJcCf3NSHmmNE1DIBBAeXn5Hgv57XMWC71ej1GjRg31MEY8brd7WH8JhJGHPFNCfyPPlDAQyHMl9Dcj4Znak6WCkeBtQRAEQRAEQRD6jCgWgiAIgiAIgiD0GVEshB5hsVhw4403wmKxDPVQhL0EeaaE/kaeKWEgkOdK6G/2xmdqnwveFgRBEARBEASh/xGLhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+owoFoIgCIIgCIIg9BlRLIQ9ctNNN0Gn0+X8TJ48eaiHJYww3n//fZxyyikoLy+HTqfDyy+/nHNc0zTccMMNKCsrg81mw7x587B+/fqhGawwItjTM3XuuefuMncdf/zxQzNYYURwxx13YPbs2XC5XCguLsZpp52GtWvX5rSJRqNYvHgxvF4vnE4nzjzzTDQ0NAzRiIXhTneeqaOPPnqXueriiy8eohH3DVEshG4xdepU1NXVZX4++OCDoR6SMMIIhULYf//98bvf/a7T40uWLMH999+Phx9+GMuXL4fD4cCCBQsQjUYHeaTCSGFPzxQAHH/88Tlz15///OdBHKEw0njvvfewePFifPTRR3jrrbeQSCQwf/58hEKhTJurrroKr732Gl544QW89957qK2txRlnnDGEoxaGM915pgDgwgsvzJmrlixZMkQj7hv7XOVtoXcYjUaUlpYO9TCEEcwJJ5yAE044odNjmqbhvvvuwy9+8QuceuqpAICnnnoKJSUlePnll/Gd73xnMIcqjBB290wxFotF5i6h27zxxhs5r5944gkUFxfj008/xdy5c+Hz+fDYY4/h2WefxTHHHAMAePzxx7Hffvvho48+wiGHHDIUwxaGMXt6phi73b5XzFVisRC6xfr161FeXo7q6mosWrQI27ZtG+ohCXsRmzdvRn19PebNm5d5Ly8vD3PmzMGyZcuGcGTCSGfp0qUoLi7GpEmTcMkll6ClpWWohySMIHw+HwCgoKAAAPDpp58ikUjkzFWTJ0/G6NGjZa4SukXHZ4p55plnUFhYiGnTpuH6669HOBweiuH1GbFYCHtkzpw5eOKJJzBp0iTU1dXh5ptvxpFHHokvvvgCLpdrqIcn7AXU19cDAEpKSnLeLykpyRwThJ5y/PHH44wzzkBVVRU2btyIn/3sZzjhhBOwbNkyGAyGoR6eMMxJp9O48sorcfjhh2PatGkAaK4ym83weDw5bWWuErpDZ88UACxcuBBjxoxBeXk5PvvsM/zkJz/B2rVr8be//W0IR9s7RLEQ9ki2q8GMGTMwZ84cjBkzBn/5y19w/vnnD+HIBEEQuibbhW769OmYMWMGxo0bh6VLl+LYY48dwpEJI4HFixfjiy++kJhCod/o6pm66KKLMn9Pnz4dZWVlOPbYY7Fx40aMGzdusIfZJ8QVSugxHo8HEydOxIYNG4Z6KMJeAvuVdsys0tDQsFf4nArDg+rqahQWFsrcJeyRyy67DK+//jreffddjBo1KvN+aWkp4vE42tvbc9rLXCXsia6eqc6YM2cOAIzIuUoUC6HHBINBbNy4EWVlZUM9FGEvoaqqCqWlpXj77bcz7/n9fixfvhyHHnroEI5M2JvYvn07WlpaZO4SukTTNFx22WV46aWX8M4776Cqqirn+IEHHgiTyZQzV61duxbbtm2TuUrolD09U52xatUqABiRc5W4Qgl75JprrsEpp5yCMWPGoLa2FjfeeCMMBgO++93vDvXQhBFEMBjM2X3ZvHkzVq1ahYKCAowePRpXXnklbrvtNkyYMAFVVVX45S9/ifLycpx22mlDN2hhWLO7Z6qgoAA333wzzjzzTJSWlmLjxo247rrrMH78eCxYsGAIRy0MZxYvXoxnn30Wr7zyClwuVyZuIi8vDzabDXl5eTj//PNx9dVXo6CgAG63Gz/60Y9w6KGHSkYooVP29Ext3LgRzz77LE488UR4vV589tlnuOqqqzB37lzMmDFjiEffCzRB2APf/va3tbKyMs1sNmsVFRXat7/9bW3Dhg1DPSxhhPHuu+9qAHb5OeecczRN07R0Oq398pe/1EpKSjSLxaIde+yx2tq1a4d20MKwZnfPVDgc1ubPn68VFRVpJpNJGzNmjHbhhRdq9fX1Qz1sYRjT2fMEQHv88cczbSKRiHbppZdq+fn5mt1u104//XStrq5u6AYtDGv29Ext27ZNmzt3rlZQUKBZLBZt/Pjx2rXXXqv5fL6hHXgv0Wmapg2mIiMIgiAIgiAIwt6HxFgIgiAIgiAIgtBnRLEQBEEQBEEQBKHPiGIhCIIgCIIgCEKfEcVCEARBEARBEIQ+I4qFIAiCIAiCIAh9RhQLQRAEQRAEQRD6jCgWgiAIgiAIgiD0GVEsBEEQBEEQBEHoM6JYCIIgCIIgCILQZ0SxEARBEARBEAShz4hiIQiCIAxLjj76aFx55ZXDpp/+GIdOp4NOp8OqVav22P7cc8/NtH/55ZcHfHyCIAh9RRQLQRCEQSRbWMz+Of7444d6aL0m+57MZjPGjx+PW265Bclksk/9/u1vf8Ott97aT6PsHv/61786/f9k/7z55pu97v/CCy9EXV0dpk2btse2v/3tb1FXV9frawmCIAw2xqEegCAIwr7G8ccfj8cffzznPYvFMqDXjMfjMJvNA9Y/31MsFsM//vEPLF68GCaTCddff32v+ovH4ygoKOjnUe6ZuXPn5gjz06ZNw6WXXopLL700815RUVGv+7fb7SgtLe1W27y8POTl5fX6WoIgCIONWCwEQRAGGYvFgtLS0pyf/Px8AOQuc/nll+O6665DQUEBSktLcdNNN+Wcn06ncccdd6Cqqgo2mw37778//vrXv+a0Ofroo3HZZZfhyiuvRGFhIRYsWIBAIIBFixbB4XCgrKwMv/nNb3LchJ566il4vV7EYrGcvk477TR8//vf79Y9jRkzBpdccgnmzZuHV199tU/j7ejCFIvFcPnll6O4uBhWqxVHHHEEPvnkk5x+QqEQzj77bDidTpSVleGee+7Z7bg7YrPZMv+TVCqFlpYWHHnkkTn/K4PBAADYtm0bFi5ciPz8fBQUFGDRokVoa2vr0fX++te/Yvr06bDZbPB6vZg3bx5CoVCP+hAEQRguiGIhCIIwzHjyySfhcDiwfPlyLFmyBLfccgveeuutzPE77rgDTz31FB5++GF8+eWXuOqqq/C9730P77333i79mM1mfPjhh3j44Ydx9dVX48MPP8Srr76Kt956C//5z3+wYsWKTPuzzjoLqVQqoxAAQGNjI/7+97/jBz/4QY/uwWazIR6P92m8Hbnuuuvw4osv4sknn8SKFSswfvx4LFiwAK2trZk21157Ld577z288sorePPNN7F06dKce+wJK1euBADMmjVrl2MbNmzAgQceiPHjx+Ojjz7CW2+9hQ0bNuDaa6/tdv91dXX47ne/ix/84AdYs2YNli5dijPOOAOapvVqvIIgCEOOJgiCIAwa55xzjmYwGDSHw5Hz86tf/UrTNE076qijtCOOOCLnnNmzZ2s/+clPNE3TtGg0qtntdu2///1vTpvzzz9f++53v5t5fdRRR2kHHHBA5rXf79dMJpP2wgsvZN5rb2/X7Ha7dsUVV2Teu+SSS7QTTjgh8/qee+7RqqurtXQ6vdt7OvXUUzVN07R0Oq299dZbmsVi0a655ppej5ff47EFg0HNZDJpzzzzTOZ4PB7XysvLtSVLlmiapmmBQEAzm83aX/7yl0yblpYWzWaz5dxjd7n55pu1ysrKTo8dd9xx2g033JDz3l//+letqqqqy/6y70fTNO3TTz/VAGhbtmzZ7TgAaC+99FK3xy0IgjBUSIyFIAjCIPONb3wDDz30UM572fEEM2bMyDlWVlaGxsZGALRTHg6Hcdxxx+W0icfjOOCAA3LeO/DAAzN/b9q0CYlEAgcffHDmvby8PEyaNCnnnAsvvBCzZ8/Gjh07UFFRgSeeeCITnL07Xn/9dTidTiQSCaTTaSxcuBA33XRTr8fbkY0bNyKRSODwww/PvGcymXDwwQdjzZo1mTbxeBxz5szJtCkoKNjlHrvLihUrOrVWbN26FW+99RY++OCDHFerVCqFysrKbve///7749hjj8X06dOxYMECzJ8/H9/85jczbnGCIAgjDVEsBEEQBhmHw4Hx48d3edxkMuW81ul0SKfTAIBgMAgA+Pvf/46Kioqcdh0DwB0OR4/HdsABB2D//ffHU089hfnz5+PLL7/E3//+9z2ex8qS2WxGeXk5jEbjoIx3IFmxYgUuuOCCXd5fvXo1CgoKsHz58l2O2Wy2bvdvMBjw1ltv4b///S/efPNNPPDAA/j5z3+O5cuXo6qqqk9jFwRBGApEsRAEQRhBTJkyBRaLBdu2bcNRRx3V7fOqq6thMpnwySefYPTo0QAAn8+HdevWYe7cuTltL7jgAtx3333YsWMH5s2b161d+K6Upd6OtyPjxo3LxF+MGTMGAJBIJPDJJ59kArzHjRsHk8mE5cuXZ+6xra0N69at6/G1m5ubUVNT06nFwmQyIRAIoLy8HHa7vdf3BJDSePjhh+Pwww/HDTfcgDFjxuCll17C1Vdf3ad+BUEQhgJRLARBEAaZWCyG+vr6nPeMRiMKCwv3eK7L5cI111yDq666Cul0GkcccQR8Ph8+/PBDuN1unHPOOV2ed8455+Daa69FQUEBiouLceONN0Kv1+/i5rRw4UJcc801+MMf/oCnnnqq9zfah/F2xOFw4JJLLsmMf/To0ViyZAnC4TDOP/98AIDT6cT555+Pa6+9Fl6vF8XFxfj5z38Ovb7neUo44LszxWLOnDlwu904++yz8ctf/hIOhwMbNmzAG2+8gfvuu6/b11i+fDnefvttzJ8/H8XFxVi+fDmampqw33779Xi8giAIwwFRLARBEAaZN954A2VlZTnvTZo0CV9//XW3zr/11ltRVFSEO+64A5s2bYLH48GsWbPws5/9bLfn3Xvvvbj44otx8sknw+1247rrrkNNTQ2sVmtOu7y8PJx55pn4+9//jtNOO61H99af4+3InXfeiXQ6je9///sIBAI46KCD8K9//SsnJuHXv/41gsEgTjnlFLhcLvz4xz+Gz+fLHH/iiSdw3nnn7THz0sqVK1FSUoLy8vJdjhUUFOAf//gHfvKTn2Du3LnQNA0TJkzotpLEuN1uvP/++7jvvvvg9/sxZswY3HPPPTjhhBN61I8gCMJwQaftaXYVBEEQ9kpCoRAqKipwzz33ZHb9mWOPPRZTp07F/fffP0SjGxhuvPFGvPfee1i6dOmgX/voo4/GzJkze2TVAMhd6qWXXuoXJU8QBGEgkToWgiAI+wgrV67En//8Z2zcuBErVqzAokWLAACnnnpqpk1bWxteeuklLF26FIsXLx6qoQ4Y//znP7FkyZIhu/6DDz4Ip9OJzz//fI9tL774YjidzkEYlSAIQv8gFgtBEIR9hJUrV+KCCy7A2rVrYTabceCBB+Lee+/F9OnTM23Gjh2LtrY2/PKXv8Q111wzhKPd+9ixYwcikQgAYPTo0TCbzbtt39jYCL/fD4BSDg+3rFmCIAgdEcVCEARBEARBEIQ+I65QgiAIgiAIgiD0GVEsBEEQBEEQBEHoM6JYCIIgCIIgCILQZ0SxEARBEARBEAShz4hiIQiCIAiCIAhCnxHFQhAEQRAEQRCEPiOKhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+owoFoIgCIIgCIIg9BlRLARBEARBEARB6DOiWAiCIAiCIAiC0Gf+P1rKVLo7l6BKAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -762,7 +762,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -837,7 +837,7 @@
        "      <th>Tp</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>index</th>\n",
+       "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
@@ -905,7 +905,7 @@
       ],
       "text/plain": [
        "                          Hm0         Tp\n",
-       "index                                   \n",
+       "date                                    \n",
        "1996-01-01 00:00:00  4.819627  16.666667\n",
        "1996-01-01 01:00:00  5.004158  16.666667\n",
        "1996-01-01 02:00:00  5.091169  16.666667\n",
@@ -997,51 +997,51 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>7.529565</td>\n",
-       "      <td>1.595490</td>\n",
-       "      <td>0.182459</td>\n",
+       "      <td>6.746905</td>\n",
+       "      <td>1.523609</td>\n",
+       "      <td>0.092796</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>12.115343</td>\n",
-       "      <td>2.669366</td>\n",
-       "      <td>0.219278</td>\n",
+       "      <td>14.522477</td>\n",
+       "      <td>3.910731</td>\n",
+       "      <td>0.134162</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>16.567481</td>\n",
-       "      <td>2.636207</td>\n",
-       "      <td>0.073010</td>\n",
+       "      <td>10.760460</td>\n",
+       "      <td>2.055257</td>\n",
+       "      <td>0.179867</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>10.216278</td>\n",
-       "      <td>1.743338</td>\n",
-       "      <td>0.160776</td>\n",
+       "      <td>14.970050</td>\n",
+       "      <td>1.998624</td>\n",
+       "      <td>0.134551</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>13.455188</td>\n",
-       "      <td>4.738885</td>\n",
-       "      <td>0.041351</td>\n",
+       "      <td>8.404868</td>\n",
+       "      <td>1.898824</td>\n",
+       "      <td>0.211971</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>8.692400</td>\n",
-       "      <td>2.779776</td>\n",
-       "      <td>0.171362</td>\n",
+       "      <td>12.500668</td>\n",
+       "      <td>2.700447</td>\n",
+       "      <td>0.122227</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>19.900045</td>\n",
-       "      <td>2.707808</td>\n",
-       "      <td>0.018114</td>\n",
+       "      <td>19.891189</td>\n",
+       "      <td>2.952800</td>\n",
+       "      <td>0.018382</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>14.290462</td>\n",
-       "      <td>2.808907</td>\n",
-       "      <td>0.133650</td>\n",
+       "      <td>9.426510</td>\n",
+       "      <td>3.342735</td>\n",
+       "      <td>0.106045</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1049,14 +1049,14 @@
       ],
       "text/plain": [
        "          Tp       Hm0   weights\n",
-       "0   7.529565  1.595490  0.182459\n",
-       "1  12.115343  2.669366  0.219278\n",
-       "2  16.567481  2.636207  0.073010\n",
-       "3  10.216278  1.743338  0.160776\n",
-       "4  13.455188  4.738885  0.041351\n",
-       "5   8.692400  2.779776  0.171362\n",
-       "6  19.900045  2.707808  0.018114\n",
-       "7  14.290462  2.808907  0.133650"
+       "0   6.746905  1.523609  0.092796\n",
+       "1  14.522477  3.910731  0.134162\n",
+       "2  10.760460  2.055257  0.179867\n",
+       "3  14.970050  1.998624  0.134551\n",
+       "4   8.404868  1.898824  0.211971\n",
+       "5  12.500668  2.700447  0.122227\n",
+       "6  19.891189  2.952800  0.018382\n",
+       "7   9.426510  3.342735  0.106045"
       ]
      },
      "execution_count": 11,
@@ -1103,7 +1103,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1124,7 +1124,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -1138,12 +1138,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "15fd306e44580d8cf431083454c399b84f9cc4f7f2c761501397671836835f49"
-   }
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_MLER_example.ipynb b/examples/extreme_response_MLER_example.ipynb
index 3433d0f72..db3655b36 100644
--- a/examples/extreme_response_MLER_example.ipynb
+++ b/examples/extreme_response_MLER_example.ipynb
@@ -4,13 +4,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# MLER example\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g., 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "# Extreme Conditions Modeling - MLER Approach\n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g., 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different tools for estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave.\n",
     "This noteboook presents the MLER design wave. \n",
     "\n",
     "This example notebook shows users how to utilze the most likely extreme response (MLER) method.\n",
-    "This method is an alternative to running long (e.g., 3-hour) simulations for each sea state in which we wish to estimate the short-term extreme response.\n",
+    "This method is an alternative to running long (e.g., 3 hr) simulations for each sea state in which we wish to estimate the short-term extreme response.\n",
     "To accomplish this, a given RAO is combined with a wave spectrum corresponding to certain extreme sea states.\n",
     "MLER then generates the resulting wave profile that would cause the largest response for that degree of freedom.\n",
     "See full explanation and derivation of the MLER method in \n",
@@ -96,7 +96,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -109,7 +109,7 @@
     "Hs = 9.0  # significant wave height\n",
     "Tp = 15.1  # time period of waves\n",
     "pm = resource.pierson_moskowitz_spectrum(wave_freq, Tp, Hs)\n",
-    "pm.plot(xlabel=\"frequency [Hz]\", ylabel=\"response [m^2/Hz]\")"
+    "pm.plot(xlabel=\"frequency [Hz]\", ylabel=\"response [m^2/Hz]\", logx=True)"
    ]
   },
   {
@@ -121,7 +121,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -130,13 +130,13 @@
        "<Axes: xlabel='Frequency [Hz]', ylabel='[rad]'>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -146,7 +146,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -162,8 +162,9 @@
     "    y=\"WaveSpectrum\",\n",
     "    ylabel=\"Conditioned wave spectrum [m^2-s]\",\n",
     "    xlabel=\"Frequency [Hz]\",\n",
+    "    logx=True\n",
     ")\n",
-    "mler_data.plot(y=\"Phase\", ylabel=\"[rad]\", xlabel=\"Frequency [Hz]\")"
+    "mler_data.plot(y=\"Phase\", ylabel=\"[rad]\", xlabel=\"Frequency [Hz]\", logx=True)"
    ]
   },
   {
@@ -181,7 +182,16 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\wave\\resource.py:1185: RuntimeWarning: invalid value encountered in divide\n",
+      "  yi = xi * xi / np.power(1.0 - np.exp(-np.power(xi, 2.4908)), 0.4015)\n"
+     ]
+    }
+   ],
    "source": [
     "# generate parameters dict\n",
     "params = (\n",
@@ -233,7 +243,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -250,7 +260,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "mhkit_release",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -264,7 +274,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.2"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_contour_example.ipynb b/examples/extreme_response_contour_example.ipynb
index 0ee20f4c9..5591e6400 100644
--- a/examples/extreme_response_contour_example.ipynb
+++ b/examples/extreme_response_contour_example.ipynb
@@ -6,13 +6,13 @@
    "source": [
     "# Extreme Conditions Modeling - Contour Approach\n",
     "\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different methods of estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave. \n",
     "This noteboook presents the contour approach. \n",
     "\n",
     "The contour approach consists of the following steps: \n",
     "1. Sample the environmental contour for the return period of interest at N points near the maximum $H_s$.\n",
-    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3-hours) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
+    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3 hr) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
     "3. Select the sea state with the highest short-term expected value for the quantity of interest as the design sea state, and some metric (e.g. 95th percentile) of the distribution as the extreme/design response. \n",
     "\n",
     "**NOTE:** Prior to running this example it is recommended to become familiar with `environmental_contours_example.ipynb` and `short_term_extremes_example.ipynb` since some code blocks are adapted from those examples and used here without the additional description. \n",
@@ -99,7 +99,7 @@
    "metadata": {},
    "source": [
     "## 1. Sampling\n",
-    "The first step is to create the environmental contour for the return period of interest, which is 100-years in this case,\n",
+    "The first step is to create the environmental contour for the return period of interest, which is 100 years in this case,\n",
     "using the `wave.contours.environmental_contours`. See  `environmental_contours_example.ipynb` for more details on using this function. \n",
     "\n",
     "Next we choose 5 sample sea states along this contour. We choose 5 equally spaced energy period values, between 15-22 seconds, to sample the contour. We then obtain the significant wave height for each sample using the `wave.contours.samples_contour` function."
@@ -131,22 +131,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1fdc554ff50>"
+       "<matplotlib.legend.Legend at 0x2182a63c090>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -166,7 +166,7 @@
     "    data_label=\"bouy data\",\n",
     "    contour_label=\"100-year contour\",\n",
     "    x_label=\"Energy Period, $Te$ [s]\",\n",
-    "    y_label=\"Sig. wave height, $Hm0$ [m]\",\n",
+    "    y_label=\"Sig. Wave Height, $Hm0$ [m]\",\n",
     "    ax=ax,\n",
     ")\n",
     "ax.plot(te_samples, hs_samples, \"ro\", label=\"samples\")\n",
@@ -202,11 +202,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sea state 1/5. (Hs, Te) = (12.296107471329824 m, 15.0 s). Tp = 16.599299336182796 s\n",
-      "Sea state 2/5. (Hs, Te) = (13.015332686697155 m, 16.75 s). Tp = 18.535884258737457 s\n",
-      "Sea state 3/5. (Hs, Te) = (13.259537828803623 m, 18.5 s). Tp = 20.472469181292116 s\n",
-      "Sea state 4/5. (Hs, Te) = (12.922246639791062 m, 20.25 s). Tp = 22.409054103846774 s\n",
-      "Sea state 5/5. (Hs, Te) = (11.849171349367342 m, 22.0 s). Tp = 24.345639026401436 s\n"
+      "Sea state 1/5. (Hs, Te) = (12.296107428008783 m, 15.0 s). Tp = 16.599299336182796 s\n",
+      "Sea state 2/5. (Hs, Te) = (13.015332640851637 m, 16.75 s). Tp = 18.535884258737457 s\n",
+      "Sea state 3/5. (Hs, Te) = (13.259537785465055 m, 18.5 s). Tp = 20.472469181292116 s\n",
+      "Sea state 4/5. (Hs, Te) = (12.922246604002359 m, 20.25 s). Tp = 22.409054103846774 s\n",
+      "Sea state 5/5. (Hs, Te) = (11.849171325785678 m, 22.0 s). Tp = 24.345639026401436 s\n"
      ]
     }
    ],
@@ -247,7 +247,7 @@
     "Finally, we will choose the sea state with the largest expected value as the design sea state. \n",
     "We will then use the 95th percentile of the short-term extreme distribution as the extreme design response. \n",
     "\n",
-    "First we find the sampled sea state with the largest expected value, which is Hs = 12.24m, Te=15s. "
+    "First we find the sampled sea state with the largest expected value, which is Hs = 13.3 m, Te = 18.5 s. "
    ]
   },
   {
@@ -259,7 +259,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\Users\\sterl\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:2998: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
+      "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:3036: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
       "  dub = integrate.quad(fun, d, ub, **kwds)[0]\n"
      ]
     },
@@ -267,7 +267,20 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Design sea state (Hs, Te): (13.015332686697155 m, 16.75 s)\n"
+      "Design sea state (Hs, Te): (13.259537785465055 m, 18.5 s)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:3036: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.\n",
+      "  If increasing the limit yields no improvement it is advised to analyze \n",
+      "  the integrand in order to determine the difficulties.  If the position of a \n",
+      "  local difficulty can be determined (singularity, discontinuity) one will \n",
+      "  probably gain from splitting up the interval and calling the integrator \n",
+      "  on the subranges.  Perhaps a special-purpose integrator should be used.\n",
+      "  dub = integrate.quad(fun, d, ub, **kwds)[0]\n"
      ]
     }
    ],
@@ -287,7 +300,7 @@
    "metadata": {},
    "source": [
     "Next, we choose the 95th percentile of the short-term extreme distribution at this sea state as the extreme design response. \n",
-    "This gives an extreme design elevation of 14.1 meters."
+    "This gives an extreme design elevation of 18.7 meters."
    ]
   },
   {
@@ -299,7 +312,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Design (extreme) reponse: 14.134870969092166 m\n"
+      "Design (extreme) reponse: 18.71051873209217 m\n"
      ]
     }
    ],
@@ -313,7 +326,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -327,7 +340,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_full_sea_state_example.ipynb b/examples/extreme_response_full_sea_state_example.ipynb
index 76266e05e..b1007b429 100644
--- a/examples/extreme_response_full_sea_state_example.ipynb
+++ b/examples/extreme_response_full_sea_state_example.ipynb
@@ -5,13 +5,13 @@
    "metadata": {},
    "source": [
     "# Extreme Conditions Modeling - Full Sea State Approach\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different methods of estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave. \n",
     "This noteboook presents the full sea state approach. \n",
     "\n",
     "The full sea state approach consists of the following steps: \n",
     "1. Take $N$ samples to represent the sea state. Each sample represents a small area of the sea state and consists of a representative $(H_{s}, T_{e})_i$ pair and a weight $W_i$ associated with the probability of that sea state area. \n",
-    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3-hours) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
+    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3 hr) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
     "3. Integrate over the entire sea state to obtain the long-term extreme. This is a sum of the products of the weight of each sea state times the short-term extreme. \n",
     "\n",
     "See more details and equations in\n",
@@ -147,7 +147,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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ikpxUri7MEm5RgqNGiIohEKJCIBAIji/2+IM83dzFc61uemJxi4BM3L3pSzmpnOZKQj+MTDnDddNRlDAezya63etwd6/F69sB9H+UWq1TSU5eREryCSQnL8ZsniQj0AlmrGs+HA2aptLbu5uu7ndpaV5PVXUTkYiM2RxAp4shSalYzKvIylrCrFmLsR1CoE4EmqbxltvHgzVtfOCNi2q7TubbBRl8LT8dm+7wAeoCwWAIUTEEQlQIBALBsU9IUflXRw9/bOpKDKAgXk/iC9mpfCHbRa55kCjbIThccK7H00hb2/tYrC8SCKxDVcP9tttspaSknEhKylKSnYswGlNHemmCSUJvr5+amk3UN2ygq2sDitKD1dpLUpIHs1lHWuoqsrI+Q2rqSmR58iik/eLi7uoWdvTG3aIyjHquLcrii9mpIhWt4Ig5JkXF22+/zf3338+mTZtoaWnhn//8J+eeey4A0WiUm2++mRdffJF9+/bhdDo5/fTTuffee8k5AhukEBUCgUBw7NIcivD75i7+1NxFV19xMJ0EZ6Y6+VJOKqtcDnQjyN700dSnqhrB49mG272ebvc6AoE6AgEHWVmNmExhTMZMUlzLcKUsx+VahsmUOdqXKpgkhMMQi8Xw+Tbh9b5KR8erhMLNie16fRIZGZ8gK/MckpMXI0mTo8K6qmm80N7DPftaqA/FiyFOsZj44ZRsPpU+MdXJBccmx6SoeOmll1i7di0LFy7kc5/7XD9R4fF4OO+88/jqV79KeXk5brebq6++GkVR2Lhx47DPIUSFQCAQHFtomsZ7Hj+/bezgpU4PSt9TK8dk4JKcVL6QnUrmUQalhsNQUdlNILCeXt863D0bUJQDFhBFMWM2LWDOnNlk56zAZp0qBmUfUzRNw9e7k7a2f9PW9p9+dTJMpmyyMj9DdvZ52GxTJrCXB4ioKn9o7uLh2raEEF+WbOfu0lxm2CcgfZXgmOOYFBUHI0lSP1ExGB988AEnnHACdXV1FBQUDKtdISoEAoHg2CCgqPyzzc1vGzvY1Zc6E+DEZBtfyU3nrDTnsGIlDkUo1Ex7xyu0t79MdXU9vb1J2O1eIF5czpWyjBTXMiROIC3NPmmCcwWTA01TcPe8T2vrC7S3v9QvZW1y8hJycy4iPX31pAjK740pPN7QzuP17YRUDRm4LDeN64qzSBEF9ASHYLhj52P6V+TxeJAkieTk5InuikAgEAhGiaZQhN82dvJMS1ci8NoiS5yX5eKK3LSjnl0NBOro6HiZ9o5X8Hq3JdYnJRkxGOZgs64gO2cRrpTpxGJyIvuTa/LXmhOMM5Kkw5VyIq6UE5lWdjtdXWtoafk7nV1v0tOzgZ6eDej1yWRnf47cnAux2aZOWF/teh3XF2fzhexUbqtq4r8dHn7X1Mnz7W5+OCWbL2anjsh1UCDYzzFrqQiFQixfvpzp06fz9NNPD9lOOBwmHD4QUOf1esnPzxeWCoFAIJhkbPcFeKKhgxfa3QkXp0Kzkctz07go20XyUcym+v1VtLe/THvHy/T27j5oi0SycxEZGWeRnn4mkDPpUp8Kjj1CoRaaW/5Gc/OzhMMtifXJyUsoyL+ctLRTkaSJzcb0TrePH1U2URGIWwHn2C3cNy2PBUm2Ce2XYPJxXLs/RaNRPv/5z9PY2Mibb755yAu87bbbuP322wesF6JCIBAIJh5V03ij28cv69tZ23PAdWRFsp2v5adzWmrSiGdPQ6Fm2tr+TWvbv+jt3ZNYL0k6UpKXkp5xFulpZ2AypQ84djKnPhUcO2iaQlfX2zQ1/4XOzjcAFQCLpYD8vMvIzj4PvX7iBvFRVeOppk7ur23BG1ORgCvz0rixOBubXqSgFcQ5bkVFNBrlggsuYN++fbzxxhukph46bZ+wVAgEAsHkI6So/L3NzRMN7VQG4vdonQTnZqTwjfx05jisI2o3GvXQ3v4SrW3/oqfnffbXj5AkAy7XcjLSzyI9/XQMhkGKUQgEY0go1Exj459oav4zsVg8bkevd5CTcyH5eZdOaC2TjkiU26ua+VubG4inZr5vWj6np4pxkuA4FRX7BUVlZSVr1qwhPX3g7NLhEIHaAoFAMHG4ozGeaurkt42ddPZlorHrZL6ck8qVeelHVFtiP4oSorPrDVpbX6Cr6y00LZrYlpx8AlmZnyEj4xMYDMmjdRkCwYhRlAAtLf+gvuFJgsFaACRJT1bWuRQVfhOrtWjC+ramy8v1FY009KWgPTcjmTtLc0k3Hl12NcGxzTEpKnp7e6mqqgJg/vz5PPTQQ5xyyim4XC6ys7M577zz2Lx5M//5z3/IzDyQE9zlcmEcrFrRIAhRIRAIBONPWzjKLxva+UNzFwEl7gKSazJwZV46F+ekknSErhaapuH1bqW5+a+0tb/YL+uO3TaNzKxzyMr8tKhkLZi0aJpKV9eb1Nf/FnfPe31rZbIyP01h0Tex20onpF9+ReGnNa38pqEDFUjR67izNJfPZ6aINMofU45JUfHmm29yyimnDFh/6aWXctttt1FcXDzocWvWrGHVqlXDOocQFQKBQDB+1AXD/KK+nb+0dBPpe9zMspv5dkEmn05PPuLqvuFIJ62t/6S5+W8EAlWJ9fvrA2RlnYPdPm1Ur0EgGGs8ns3U1D5OV9eavjUS6emrKS76Ng7HzAnp01ZvgB/sbeDDvqrcn0p3cl9ZPqnGYzpxqGAEHJOiYjwQokIgEAjGnj3+II/VtfPPgzI5LU6ycXVRJqe5HEc046mqMbq63qS55Tm6ut5E0+JuU7JsJiPjE+Rkn0dy8gmTppKxQDBSvL4Pqa39BR0drybWZWScTcmU72O1Dj6xOpZEVY3H6tt4sLaVmAbpRj0PTcvnjDTnuPdFMHEIUTEEQlQIBALB2LHFG+DRujZe6vQk1p3icvDdwkyWOm1HJCYCgRqam/9KS+s/iUQ6EuuTkuaTk30emZmfRK93jGr/BYLJQG/vXmprH6et/b+AhiTpyM4+n+Li72A2ZY17f7b5Aly1qy6RVOFL2ancPjVHZIj6mCBExRAIUSEQCASjz0aPnwdqWnnT7QNAAs5Od/LdwkzKjyCTk6rG6Ox8naamp+l2r02sNxhSyc7+LNnZ502Yr7lAMN74evdQXf1Awi1Klk3k511GYeHXMRjG11oQVFTu3dfCrxrjAr/QbOSxmYUsdoq6Fsc7QlQMgRAVAoFAMHp8VEzoJPh8ZgpXFWRSZht+tbhQuJXmpmfjxcIibX1rJVJTV5KbcyGpqacgyyIDjeDjibvnA6qr78fj2QSAXp9EcfF3ycv90rj/X7zr9nH17nqawlF0EtxYnM23CzKQRRD3cYsQFUMgRIVAIBCMjIMLwu0I+XmwtpU13XExoZfgwiwX3y3MpNAyvGpxmqbS7V5HU9PTdHa+jqYpQNwqkZNzAbk5F2Gx5I3Z9QgExxKaptHVtYbq6gfo9e8FwGotoaz0ZlJTTx7XvnhjCjfsbeCf7T1A3MXx0RkFIvXscYoQFUMgRIVAIBAcGaEQdHeDzwfbPAF+39LB+xEfcpKCwaQdsZiIxXw0t/yNxsY/JfL0Q7ymRG7uF8lIX40sH3m9ipEiqmcLjiU0TaG5+Tmq9z1INNoNQFraaZRO/eG4BnNrmsafW7q5qbKRkKqRadTzy5lFLEuxj1sfBOODEBVDIESFQCAQDJ9QCJqaYEtHgD90t7OutxcUCV1I5uzcJG5cnMa0lOGNxAOBOhob/0Bzy98SdSV0OjvZWZ8lN/cL454K9mCxpCig04HDAS4XmIfvuSUQTAjRqJea2p/T2PgHNC2GJBnIz7+M4qLvoNePX5zD7t4gX9tZS2UgjAxcW5TFNUWZ6IQ71HGDEBVDIESFQCAQDJ83K4M8/GEn62LxbE46CT6TkcKVuWnYQiZSUiDnEPXlNE2jp2cD9Q1P0tn5OhB/5FitJeTnX0ZW5jnjOgDaz36xFAqBzQYGA0Sj4PfHBUVurhAWgmMDv7+aysq76Op+GwCzKYdp024nLe3U8euDovCjiib+0hq3nKxMcfDErEJSDKKmxfGAEBVDIESFQCAQHJ66YJh797by3DY/GDV0eo1PZ6Twtbw08vrcnCKRuOtQUdFAtyFFCdPW9m8aGp+kt3dPYn1q6kry8y7D5VoxoXUlmpvB7YaUlIHb9q8/lFgSCCYT++Mt9lbcTijUCEBG+icoK7sVkylj3PrxXGs31+9tJKiqFJiNPDWnmJl2y7idXzA2CFExBEJUCAQCwdC0hqM8XNvK0y1dREMSsRYjZxbY+XZhOlOs/afuNQ08HiguBkvfuCEaddPQ+CcaG/+Q8PeWZQvZ2Z8jP+9SbLaS8b6kAYTDUFsbF0LGQUI3DiWWBILJjKIE2FfzKA0Nv0PTFHQ6O1NLric39wvjJuJ39Qa5bEcN9aEIFlnm4en5nJs5iHoXHDMIUTEEQlQIBALBQNzRGI/Vt/O7xg6CavyxcLLdwcVyDuWplsMOvlW1gfqG39Lc/DdUNQiAyZRNft4l5ORcOO459Q9FMAg1NeB0wmBu34OJpfEgFosRCAQIBoMEAgECgQDhcJhIJNJvCYfDxGIxVFVFURQURUm81zQNWZaRJKnfotPpMBgMgy4Wi2XQxTjYly44JvD5drFnz4/w+rYD4HQuYOaMn45bILc7GuObO+sSqaa/lZ/Bj0qyRZzFMYoQFUMgRIVAIBAcwB9T+E1jB483tOONqQAsTrLxwynZLEuxH9ZNSG/YTTTyBG3tLwLx4x2OWRQWfI309LOQ5cnnUz3elgpFUfD5fHi93sTrwYvP5yMQCBCJRI7+ZKOIyWTC4XAMWFJSUhKLwSBSiE5WNE2hsfFPVO97EEXxI8tmppZcR17eJeNitVA0jZ/sa+EX9e2AiLM4lhGiYgiEqBAIBAKIqCp/aO7ikdo2OqMxAGbazPxwSjanpyYh9c0oDhbQHIloNLdsprPjGYymFzEa44Nhl+skCgu+RkrKiYnjJyujHVMRjUbp7u4esHR1deH1eofdjiRJWCwWrFYrFosFs9mM0WhMLCaTCaPRiF6vR6fTIcsyOp0u8V6SJDRNSyyqqiZeo9HogCUSiRAMBgcsqqoOq792u52UlBRcLhdpaWlkZGSQnp5OcnIysjxxMTOCA4RCzezefWOiQn1K8lJmzLhv3GrAPN/m5nt7GgiqKlOtJv40dwpFw0w/LZgcCFExBEJUCASCjzOapvHvDg8/2ddMbTAuBootRq4vzuacjORBq+LuT73q9Sq0d7xLa8szaGwjKcmDyaSQmfEpCgq+isMxY7wvZ8SMNPtTJBKho6ODtrY22tvbaWtrG5ZwkGWZpKQkkpKScDgciff7/7bZbFitVkwm04QPxjVNIxwO09vbi8/n67d4PB56enro7u4mHA4P2YbBYEiIjOzsbHJycsjKyhIuVROEpmk0NT1DZdU9qGoQnc5OWemPyM4+f1wmAHb1Bvny9n00haO4DDp+P2cKi53jn/VNMDKEqBgCISoEAsHHlQ88fm6vamKjNwBAhlHPD4qy+EJ2KgZ56IGFqsZoa/8PFRW/we+vQZI0zGYduTkXkp9/BRZL7nhdwqhyqDoVJpOGx+OhubmZtra2hIjo7u4esj2TyURqaioulyuxpKamkpKSgtVqnXCxMJpomkYwGMTtduN2u+nq6qKjo4OOjg46OztRFGXAMZIkkZ6eTk5ODjk5ORQUFJCRkXFcfS6TnUCgll27r8fj2QRAWuqpzJhxH0aja8zP3RaO8uUd+9juC2KSJX42vUAEcB8jCFExBEJUCASCjxv7AmHu3tfMfzvitSYsssy3CzL4Zn46Nr1uyONUNUJr6/PU1v2SYLAeAL0+ify8y8jPvwSD4fgYEITD4PP5aW1tpqOjkebmZpqamggEAoPub7PZyMjIIDMzM+Hu43K5sFqtk97tazxQFAW3252w6DQ3N9Pc3Exvb++AfU0mEwUFBYklNzcXvV743I8lmqZQ3/A7qqsfQtMimIyZzJr1ECkpS8f83H5F4du76ni5M27Z+2FxNt8tzBD/N5McISqGQIgKgUDwcaEzEuOh2lb+0NxJTAMZ+GJ2KtcVZ5FpGjrAVlHCtLQ8R13drwiFmwEwGFwU5F9BXt6X0Osd43QFY4OiKLS2tlJfX09DQwNNTU14PJ4B+8myTGZmJllZWf1EhN1un4BeH/t4vd6EwGhsbKSxsXFAcLper6ewsJCSkhJKSkrIyBADzrHC59vNhzu/SyCwD5AoLrqKoqKrxjy5gqJp3FHdzK8aOgC4KMvF/dPyD2ktFUwsQlQMgRAVAoHgeCeoqPxfYweP1rXhU+IBt6e5krhlajbTbUPnSFWUAE1Nf6Gu/jdEIvGMLUZjOoUFXyU39wvodNZx6f9oE41GaWpqoq6ujrq6ukEHswBpaWnk5uaSk5NDbm4umZmZIrvRGKIoCm1tbdTV1VFfX099fT1+v7/fPg6Hg5KSEqZOncrUqVMxizLno4qiBNhbcQctLc8BkOxczKxZD2E2j33lxyebOvlRRSMqcEZqEr+eVYRFJ1zhJiNCVAyBEBUCgeB4RdU0/t7m5t59LTSFowDMtlv4cUkOJ7mGti7EYn4aG/9IfcNvEwXrTKZsCgu/Tk72Beh0x1amllgsRkNDA/v27aO2tpampqYB2YzMZjP5+fkUFBSQl5dHdnb2cTNgDYdBVUGWj63ifZqm0dHRQXV1NVVVVdTV1RGLxRLbZVlmypQpTJs2jWnTpoln+CjS2vov9uy9GUXxo9cnM2vWg6Slrhrz877a6eFrO2sJqRpLnTZ+P6cYp0g5O+kQomIIhKgQCATHIxs9fm6ubGKrLx4HkGsycOOUbD6fmTJoRicARQnS2PQ0dXW/SogJi7mAwqJvkJ31WWT52MjUo6oqDQ3t7NtXS01NNc3NNf0GoxBPfVpYWEhhYeFxGyB8qMDzY1EvRaNR6uvrqa6uZu/evXR1dfXbnpuby8yZM5k9ezZO5+QprnisEgjU8uHOq/H5PgQkphRfTVHRt8e8psV7Pb1csmMf3pjKLLuZP88tIeMQ7pmC8UeIiiEQokIgEBxPNIci3LWvhX+0uQGw6WSuLszkq3npQ7oSqGqYpqa/UFv3SyKRuF+zxVJEcdFVZGZ+elIWrPsovb29VFZWsmdPLTt3ttDTo6CqErKsYTSGSU/XMW1aIcXFxRQWFpKSknJc++aPNEXusURHRwd79uxh7969NDY29ttWWFjInDlzmDlzJlbrsemmNxlQ1TAVlXfR1PQMAGlppzFr5oNjHke1szfIRduq6YjEKLIYeba8hEJRy2LSIETFEAhRIRAIjgcCisov69t5rL6doKoiARdlu/hhcfaQs3yqGqWl5W/U1P6CcLgFALM5j+Ki75CVde6kFhOaptHa2kpFRQUVFRU0NTURi+nxeh3EYnqsVpXCwlxycgpJTy8kJyeVvDzpmB9ID5fRLuY32fH5fOzevZsPP/yQ+vr6xHpZlikpKWH+/PlMmzYNnW7o7GaCoWlufo69FbeiqhEsliLmzvkldnvZmJ6zNhjmgq3V1IciZBj1PFtewgz70DFggvFjTETFv/71ryPuyBlnnIHFMnl+FEJUCASCYxlN03ihvYc7q5sTcRNLnDbuKM2l3DH4DK2qxmhre4F9NT8nFGoAwGTKoqjo2+Rknzdp3ZwikQg1NTUJIeHz+fptt1qnkppawuzZ8ZiIg1ORHo8D6aEIh6G2Nh4/MVhtuUgkvk9R0bEVYzFcenp62LlzJzt27KC1tTWx3mazUV5ezoIFC0hLS5vAHh6beL3b2bHj24TCzeh0VmbMuI/MjLMH7DeaMTxt4SgXbatmtz+Ey6Djr+UlzB7iviYYP8ZEVByp/6kkSVRWVjJlypQjOm4sEaJCIBAcq2zzBbi1sokNnniGnFyTgVtKcjgnI3lQ1x5NU2lr+w81tY8SCNQAYDSmUVT4TXJyvjApA7CDwSAVFRXs2rWL6urqfrERBoOBkpISysrKKCgopavLMWkH0pqiofZGUAIxtFAMNRhDDcXQQkq/91pUQVM0tJiKpmjQ96rFVFA0kABZAgkkWep7LyHJgE5GNsiEJD0NbhNJTgmdUUYy65AteiSLHp3FgGTW4YsZmDJNh9V6/LqAQdxFauvWrWzbtq1fXYyCggIWLlzIrFmzRB2MIyAS6ebDnVfjdq8DYErxNRQVXYUkSWMWw9MTjXHRtn1s9QVI0et4dl4Jc4WwmFDGTFS0traSkZExrP0dDgfbtm0TokIgEAiOgvZwlHtqWvhLSzcaYJElrirI5JsFGVgHiZvQNI2urjVUVd+P318BgMGQQmHB18jL+zI63eSxHgP4/X727NnD7t272bdvX79MTU6nk7KyMsrKyigqKkqkeA0GoaYGnE4YLFRC08DjgeJiGG1juRqMEesOEesOoXjCqL4ISt+i+qLx10AUxsm5OByTaPSYMOo0DLqBJ40qEhFFIi81ijXVgC7JiC7JhM5pQpdkRO8yo081o3dZkAzHR/C6oihUVlayefNmKisr2T/UsdlsLFq0iEWLFuFwHNv1VsYLVY1RXf1T6ht+C0BW5rkUF/+ElhbTmMXweGMKX9hWzSZvAKdex7PlJcxLEsJiohju2PmI5Pqll156RK5MX/rSl8TAXSAQCEZIVNX4XVMH99e00ttXb+LzmSn8aEo2OebBXZZ6PJuoqvopHs9GAPR6BwX5V5Kffxl6/eQp2ubz+di1axe7d++mrq6Og+e30tPTmTlzJjNmzCAzM3NQK4wsx2dGo9HBLRXRaHz7SBI8aZqG6o0QbQ8Q6wzGxUN3iJg7RKw7jBaKHb4RABlkiyFuNeizHsjm+CJZdMgmPZJRRtLLoJOQdDKSPv6KXo5bJgBN1UDVQNPQVOKKSdXiFo2oghZWiTZruLvBaoqihhW0YAw1ELeQeN0aScYIJhSULgWlKzR4fyXigsNlwZBmQZ9pxZBpxZBpQ3YYjqlAd51Ox/Tp05k+fTper5ctW7awceNGfD4fb731Fu+88w6zZs1iyZIl5OXlTXR3JzWyrKe09Cas1mL2VvyY1rbnqav3kZN9HxkZB4J4jMb44nbHLRhH43qYpNfxl/ISvrhtHx94/VywrYq/lJewIMk2ClckGCtEoLZAIBBMQta6fdxU2cRef3wAOM9h5a7SXBY5B3+o+v1VVFc/QEfnawDIson8vMsoLPw6BsPkSLcZDAbZvXs3O3bsoKampt+27OxsZsyYwcyZM4ft/360wcmaqqG4Q0TbAsQ6AkTbg3Eh0R5ACyuHPLdsN6BPMaNLMaFzGJEdRnR2I7okI7I9bg2QrYaEMBhrDpf9KSdDwRCJoHgjKN4wiieC4gmjeMJxq0tX6JDXLFv16DOsGHPsGHLtGPMd6NMs43Z9o4GiKOzevZsNGzbQ0NCQWF9UVMSKFSsoKSk5poTTRNDdvZZNm6+hsdGJw55K+bx7sFn7e6OMputhb0zh4u372ODx49DJ/Lm8ZMh7oGDsENmfhkCICoFAMJlpCUe4vaqZ59t7AHAZdPxoSg5fyHYNWm8iFGqhpuZRmlv+BqiATE72eRQXfxezOXtc+z4YkUiEiooKduzYQWVlZT/Xpry8vIRFImUwZXAYjiSNqqaoRNsCRJv9RJt7iTT3Em32o0WGGEjLoHdZ0Kdb0LvM6Fxm9ClxNyFdihnZOPmyCh2Nj7umaaj+aNwq0xUi2hGIi622ALGu4KCuXJJRhyHXhjHPgakwCWNREjr75Az6/yjNzc1s2LCBHTt2JH6T2dnZrFixghkzZhx3NUxGk87Oal555Q50+goMBjszpt9HcvKCxPbRdj30xxS+tGMf63viwuJv86cOmZRCMDaMi6gIhUJs376d9vb2AdVKP/OZz4y02TFFiAqBQDAZiagqv2ns5KHaVvxKPEXspblp3FCcRcogFWajUQ91dU/Q0Ph7VDUMQHr6mZRMuRabbeo4974/qqpSXV3N9u3b2bNnD9FoNLEtIyODOXPmMHv27BEJiY8y2EDabtNIUgLIbT4ijT4iTb1EW/3xwOePopcwpFnjrj7pFvQZcZcffaol7pZ0DDLaFbW1qBK34rT5iTb1xj/Ppl60qDpgX326BVOxE2NREqYpyeiTJ18ygIPxeDysX7+eTZs2JX6nqampnHzyycyZM0eIi0EIh6Gy0s2+mh8RDG5Blg1Mm3ZHogL3WCRJ8CsKX9oeFxYug45/zJ/KdNvkig07nhlzUfHyyy9zySWX0NnZObBRSUJRDm06niiEqBAIBJONd7p93FTZSGUgLg4WJVn5SVneoBlPFCVEY+MfqK37JbGYF4Bk52KmTr0ep3PBgP3Hk/2Zd7Zv394v/WtycjKzZ89mzpw5ZGZmjvp51WAMX7WPYK2PWKMXqdWLFhr4DJLMOgzZdoy5dgw5Now5dvTpViSdcHk5UjRFI9YRINLYS6TBS7jWS6wtMGA/fboFc2kKprIUTMVOZNPks/BAPFnA+++/z4YNGwiF4i6HaWlpnHLKKcJyMQjNzdDVFaKt7cd0db8NyEwtuY7s7HPHLJ1zb0zh/K3VbPEFyDTqeWFBKUWiQN64MOaiorS0lDPPPJNbb711TB4SY4UQFQKBYLLQFIpwW1Uz/+7oASDVoOeWkmwuyBro6hRPD/tvqqrvTxSus9nKmFpyPampqybMFzwYDPLhhx/ywQfbaWpqQZI09HoFi8XC7NmzmTt3Lnl5eaPaP6U3QnifJ7HE2gcOZiWDjDHfgbHAEY8ByLGjc5mFz/wYovijROriAiNS4yHS6OvvNqWTMBUmYZ6RimWmC33q5JtpDofDvP/++6xduzYhLjIzMzn11FMpKysTv58+9rseBgIx2toeoLPrBRRFT1rq1ykpuXjMCk+6ozE+t6WK3f4QeWYDL8wvJXeIpBWC0WPMRUVSUhJbtmyhpKRkxJ2cCISoEAgEE01U1fhVQzsP1rYRVFVk4PLcNK4vzsI5iKuTu+cDqip/gte3HQCTKZuSKd8nK+scJGn8Z35VVWXfvn1s2bKFHTsq6e01EomY0DSZ4uJ8Fi2axqJFJdjto1MPYDgiQpdqxlSQhLHAgbEgCUOWTVggJhg1GCNc3UOo0k2owo3iDvfbbsiyYp6ZimVmKoZc+6QasIdCId577z3WrVtHJBIB4jFAq1evJj8/f4J7NznY73ro9WrU1T9Fc/PTWK29TJ/+SebOuWnM7k0dkSjnbK5iXzBMicXE8wumkm40jMm5BHHGXFRcccUVLF++nK985Ssj7uREIESFQCCYSDb09HJ9RWMiq9MSp42flOUxyz5w1jYQqKWq+qd0dLwCgE5no6jwm+TnX45ONwbTgIfB5/OxZcsWNm/eTE9PD7GYHq/XQVJSOvPnT2POnOkYjbajzlWvRRXCNV5CFW5Cle5B3WoM2TZMU5wJ//1jJUD444qmacS6QoT2dBPa1UW41hPPK9CHLsWEtTwdS3kGhizrpBEYgUCAdevWsWHDhkTMxezZsznppJNwOidHVrWJJhKJx/C0tb1Ac8svAI201NMpKbkWWR6bQoOt4Qjf3lVHWyTGVKuJx2YUYtdPTte6YwGDwYBON/TnN+aiIhAIcP7555Oens6cOXMSBYn2893vfnckzY45QlQIBIKJoDsa467qZp5p6QbiWZ1+XJLLBVkpAwZQ0aiHmtrHaGz8I5oWBWRycy6keMo1mIzDS7c6Wuy3SmzatIm9e/cmknKYzWZychZRUDCX0tL0AddwJH7VmqYRaw8QqojPaof3eSDWPwjYkNUnIkqcGIuc6GxiZvJYRg1ECfYJjFCFGy1y4PvWZ1iwlmdgnZc+aVykvF4va9asobe3l8LCQnQ6HSaTCbNZuNQdjKIEiEbdAMiyBYNh4P1ttIipGu3RKIoGZlkizaAX38VRkJycTFZW1qCf4ZiLit/+9rd84xvfwGw2k5qa2q8TkiSxb9++I27z7bff5v7772fTpk20tLTwz3/+k3PPPTexXdM0fvzjH/Ob3/yGnp4eli9fzi9/+UtKS0uHfQ4hKgQCwXiiaRp/bXVze3UT3dF48PDF2S5uLskZkNVJVSM0Nj1NTc1jxGI9AKS6Tmbq1Bux26eNa799Ph9bt25l06ZN9PT0JNbn5+ezcOFCpk6dRVOTAZNp8OJzh8sAo0UVQlU9hHZ3E9rrRvH0d43RJRkxlaVgLkvBVJIsRMRxjBpRCO3pJrCtg9Ce7n5ZukxTnFgXZWKZnTbhaXxbWlro6urCbo+7au1f7Hb7iMTFwUkzRzsOfCzbPhzRqC8R96XT2TCbs5GkselESFGoD0VQNXDodeSYjq0ijZMBTdMIBAK0t7eTnJxMdvbAVORjUlH7YH70ox9x++23c+ONN45aVgS/3095eTlXXHEFn/vc5wZs/+lPf8qjjz7K73//e4qLi7nllltYvXo1u3btwjwWEUECgUBwFFT6Q1xf0cD6Hj8A021mflqWxwnJ/Stba5pGZ+f/qKy6l2CwFgCbrZTSqTeRmnryuPVX0zT27dvHxo0bB1glysvLWbBgQSIxRzAYT+FqGGKsbzBAINB/cKP4IoT2dBPc3U240t0/JalewlTsxNwnJPQZk8cFRjC2yEYd1rnpWOemo4ZiBHd2EdjaTriqJxFH0/NCNdZ56dgWZ2HMc4x7HxVFoaenh+zsbFwuF+FwGI/Hg6IoBINBFEXB6XQO8NoYDFWFWF9Rdk0DSYoP/PX6oxcAY9n2cDGbzZjNJoKhetACaFo7ZnPBmAgLM6AzmdkXDNOrgVvSkSMCt48YS19Bkfb2djIyMg7pCnUoRmypcLlcfPDBB2MWqC1JUj9LhaZp5OTkcO211/KDH/wAiOeXzszM5KmnnuKiiy4aVrvCUiEQCMaaoKLyaF0bj9W3E9U0LLLEtUVZfD0/A8NHKhD39lZQUXknbvc6AAyGVEqmfI/s7PPHzB/5o4TDYbZt28b777/fL034fqvEzJkzMX7EHBEOQ20th7VU5FoDqFVdhHZ3EWnonw1Il2zCPMOFZboLY7FzwmeiBZOLWE+YwKY2/Btb+wV5G/Md2JblYJ2TNm61REKhEDU1NRQVFSUGYJqm0dvbS29vL/uHUjabDYfDMeRkq6rG/zc0LT7Il6T4e1WNvzcaRz74H8u2R0Is5iMQrANNQ6+3Y7EUjpnFojsaoyEYD6jPMRtE4PYICAaD1NbWUlxcPGCifswtFZdeeinPPvssN91000ibOCJqampobW3l9NNPT6xzOp0sWbKE9evXD1tUCAQCwVjyZreXGysaqe17wJ2emsRPSnMp+Eg+9WjUw76an9HU9Cc0TUGWjeTnf4Wiwm+g19sHa3rU6e7u5v3332fLli2Ew/FBm9FoZN68eSxcuPCQ6cJNpni1Zre7v6jQNI1YR5DWjW7MDZ30hL39jjPk2bHMSMU8w4Uh2yasEYIh0SebSDqtAMcp+YT3efB/0Erww04iDT4iz+7F89992E7Iwr40G13S+NQr+Kirt8PhwGKx4PV6CYVC+P1+gsEgycnJg3pQxGLxgf7BE8GSFP9bUeLbBxPpw2Es2x4Jer0Dq6WIQLCOWKyXYLBuzISFy6Anqmq0hqM0h6IYJInkQTLpCYZmNO7FI/7EFUXhpz/9Ka+88gpz584dYPJ76KGHjrpzB9Pa2gow4CGXmZmZ2DYY4XA48bCEuNoSCASC0aYtHOXWqiZeaO8BINtk4K7SXM5Oc/a7WWuaQnPzX6ne9xDRaDxoOz39TEqn/hCLpWBY5zqaismaplFdXc37779PRUVFYn1qaionnHAC5eXlw3YndbniblDd3RrGQBClqovenW68rRFMeg27IwwmCVNJMpaZqVhmuNA5RbEqwZEhyRLmqcmYpyaj+CL432+ld0MLqjeC740GfG81Yp2XgWNlHoaMgQUjxxq9Xo/L5SIUCiVcorq7u7FYLDidzoTVQlUP/N8Ohiwffp+hGMu2jwa93t4nLGr7hEUDFkvBmEwmZBj1RDWNrkiM+lAEgyxhG6Ebj2BkjFhU7Nixg/nz5wPw4Ycf9ts2mWae7rnnHm6//faJ7oZAIDhOUTWNPzZ3cVd1Mz4lXnPiK3lp3FCcPSDFYU/PRioq7sDXuxOIx02Uld6Cy7V8WOfanxfe54vPPOp0cWuBy3X41K1DuThNnTqVJUuWUFJScsTxcTpfAPvuDnwb3HS1RlE0CZ2k4bSpZM1xkLKgAMvMVGSLmDEUjA46hzFuvViVR3BnF73rmonUeglsaiOwqQ3zzFQcq/IwFYy/e7PZbMZoNOLz+RIWi3A4jNPpPMhlauhBvST1j0E6Usay7aNBr7dhtRT2CQsvoVAjZvPoFsSE+Ngz12Qgomr4Ygq1wQilVhNGUQ193BjxnX7NmjWj2Y/DkpWVBUBbW1u/yPS2tjbmzZs35HE//OEP+f73v5/42+v1isI1AoFgVKgKhPjBngbe88QDscsdFu6fls9cR//Z0lCoharq+2hr+zcQdwsoLr6avNwvIcvD8/3dX8E2FAKbLR4IHY3G3Y+CwaFrQni9XjZs2MDGjRv7uTjNnz+fxYsXk5Z2ZClqFV+EwLYOAlvaiTb1ApAGOFJljFNd2Oek4ix3IZuFkBCMHZJOTgR3h+u9+N5qjKen7VuMxU6STi/AXJI8rv2SZRmn04nZbKanpwdFUXC73YRCIRwOJ5IkJwKoP8pQ64fL/hiKj7bxy1/+goceup+2tlbKy8v5+c9/zgknnHDItp577jluueUWamtrKS0t5b777uPss88+qK+Hz8Z5991389///petW7diNBrp6KgnGKwnGu0BJMzm3DERFoUWI5WBEGFFozYYocRqQncU51mzZg33338/GzZsIBgMUlRUxCc+8Qm+//3vk5ubOyr93h/LsGXLlkOOaSc7RyTftm/fnsgGMhx27txJbH8agqOkuLiYrKwsXn/99cS6/Q/LE088ccjjTCYTSUlJ/RaBQCA4GiKqyiO1rZz6/l7e8/ix6mTunJrLiwvL+gkKRQlTU/sL1r93Rp+gkMjJuYgTl75OQf7lwxYUELdQhELx2g9G44HAy5SUAxaMg2lra+P555/nkUceYe3atYTDYVwuV+Jh+IlPfGLYgkINx/BvaqPjtzto+ckGPP/ZFxcUMpinu3BdNI3i25eQf+UMUpZkCEEhGFdMBUmkfXkmmd9biHVRJugkIjUeOn+zg45fb48X2hvvPplMpKenY7fH46OCwSCdne3EYuEhLQb7XZNGMrG+/7iPtv3cc89y/fXf56abfsyGDZspLy9n9erVtLe3D9nWunXr+MIXvsBXvvIVtmzZwrnnnsu5557bzytlfzbOJ554gg0bNmCz2Vi9ejWhUCixTyQS4fzzz+eb3/wmAAZDEhZLfFI3GnUTDrcwwlxBh0QnSRRbTOikeNKMxlDkkOfRNG3IseqvfvUrTj/9dLKysvj73//Orl27eOKJJ/B4PDz44IOj3vfxQFGUIxrLHxHaESDLstbe3j7s/R0Oh1ZdXT3s/X0+n7ZlyxZty5YtGqA99NBD2pYtW7S6ujpN0zTt3nvv1ZKTk7UXXnhB2759u3bOOedoxcXFWjAYHPY5PB6PBmgej2fYxwgEAsF+NvX0ais37NYy39iiZb6xRbtoa5VWHwz320dVVa29/RXt3bUrtf+9PkX73+tTtA82nq95vDtGdM5QSNP27NG0mhpNa2oauNTUxLcHg6pWXV2t/fGPf9R+/OMfJ5bf/va32u7duzVFUYZ9TjWmaoFdnVrn07u0xpvf1RpueDuxtP1ii+Zb16TFfOHDNyQQjDPRnpDW/Xyl1nDTO4nfbPv/bddCdSN/7geDQW3Xrl1HNN7YTzgc1lpbW7WmpiatsbFJ6+jwan6/qoVCmhYOx/+/AwFNCwY17Qj+RQegKPE2AgEt0fbixSdoX//6txNtK4qi5eTkaPfcc8+Q7VxwwQXaJz/5yX7rlixZon3961/XNC1+f8vKytLuv//+xPaenh7NZDJpf/7znwe09+STT2pOp/Ogz6Nb83i2ax7Pdi0Uak2sf+uttzS9Xq+1tLT0O/7qq6/WVqxYkfj7nXfe0VasWKGZzWYtLy9P+853vqP19vYmtv/hD3/QFi5cqNntdi01I0M767zztR31jYnta9as0QDtxRdf1BYsWKAZDAZtzZo1A/rd0NCgGY1G7Zprrhn0c3K73Yn3f/vb37SZM2dqRqNRKyws1B544IF++xYWFmp33323dvnll2t2u13Lz8/XfvWrXyW2E8+Ll1hWrlypaVr8+7r99tu13NxczWg0auXl5dpLL7004FoO7sv+MXRNTY2maQc+/xdeeEGbMWOGptPpEtsO5lC/8eGOnY9oOknTNG655Ras1uEFQkUikSNpno0bN3LKKack/t7vtnTppZfy1FNPcf311+P3+/na175GT08PK1as4OWXXxY1KgQCwZjjjyncW9PC/zV2ohGviH1XaR6fzUjuZ8IPBGrYW3E73d3vAGAyZTG15AYyMz89YlO/qh66JoQsK+zZU8Wrr75DV1cjEHcDmDFjBsuWLSMvL2/Y54p2BPBvbCOwuQ3VF02s16dbsM6bXFWOBYLB0DtNpJwzFcfKPHxvNODf2Ea4soeOyh4sc9Jwri5Cn3Z0v2FN0wj2FbM8PDI2Zwo+r49gMEAw2oM3EMRuT0Kn0/erJaEOw7nDYtANei+R5bj1MhaL3zNCoQibN2/iuut+eFA6WZnTTz+d9evXD9n++vXr+7mNA6xevZrnn38eOPpsnEZjCqASCjUTDrcjSXqMxlROPvlkpkyZwh//+Eeuu+46AKLRKE8//TQ//elPAaiuruass87irrvu4ne/+x0dHR1cddVVXHXVVTz55JOJY+68806mTZtGZVMz1//gB3zjK1fwn//+t19GqBtvvJEHHniAKVOmkJKSMqCfzz33HJFIhOuvv37Q60hOTgZg06ZNXHDBBdx2221ceOGFrFu3jm9961ukpqZy2WWXJfZ/8MEHufPOO7npppv429/+xje/+U1WrlzJtGnTeP/99znhhBP43//+x6xZsxIpvH/2s5/x4IMP8qtf/Yr58+fzu9/9js985jPs3LnziAo/BwIB7rvvPv7v//6P1NRUMjIyhn3skXBEouLkk09m7969w97/xBNPTAQnDYdVq1Yd0kQlSRJ33HEHd9xxx7DbFAgEgqPljS4v11c00BiKD7LPy0zh9qm5pBoP3EIVJURt3S+pq/s1mhZBkowUFlxJYeE30OttR3V+WY4HZUej/VNCRiIRduzYwfvvb8HtDpKc3IPZrGfBggUsXboUl8s1rPbVsEJwRwf+D9qI1B3IkCfbDVjL07HOz8CQa59USTgEgsOhTzaT8rlSHKvy8b5eT2BzG8EdnQR3dWFfmo3j1IIRV2oPRhVm3vrKKPd4eOy6YzVW4+DDt/3CQlWhs7MTRVHIy8vs51KVmZnJnj17hmy/tbX1kJk2R5qN82CMxlRULUYk3E4o1IwkGTAYkvjKV77Ck08+mRAV//73vwmFQlxwwQVAPPnOxRdfzDXXXANAaWkpjz76KCtXruSXv/wlZrOZK664InGeKVOmoDz0MJ9csYy9nd2UZxxw+bzjjjs444wzhuxjZWUlSUlJg1aYPpiHHnqI0047jVtuuQWAsrIydu3axf33399PVJx99tl861vfAuCGG27g4YcfZs2aNUybNo309HQgnoVvfwwxwAMPPMANN9yQEGr33Xcfa9as4ZFHHuEXv/jFIft1MNFolMcff5zy8vJhHzMSjkhUvPnmm2PUDYFAIJh8dEVi3FrVxN/b3ADkmQ3cX5bPKan9Y7M6O99gb8UdhEINAKS6Tqas7MdYrUWj0o+P1oQIBoNs27aNzZs3EwwGCQbNuFw6zjjjZBYvXjwsa7KmaUTqffHc/9s70SJ9s64ymKe5sC3KxDzdhaQTmVMExzZ6lxnX+WXYV+TieamGcIWb3rXN+De1kXRqAfblOcfd73yksRnjycIFp1JXVwtonHjiAl566RUuu+wybr75Zt577z2WLl3KU089xQUXXIDNFp+Y2bZtG9u3b+fpp59OtKNpGqqqUlNTw4wZM9i0aRO33XYb27Ztw+12J+IHmhoacDocKH2T14sWLTpk/zRNG9ZEyu7duznnnHP6rVu+fDmPPPIIiqIkqlPPnTs3sV2SJLKysg4Z2+L1emlubmb58v7ZAZcvX862bdsO26+DMRqN/c4/VohoOoFAIPgImqbxjzY3t1Q10R1VkIGv5qVzfXEWtoPSxAaDjVRU3kln5/+AuKtTWemtpKefOeqz+i4XdHUFeOmlbezdu5lYLISqypjNGZx00jxOO206DsfhZ10VfzRepfiDVmIdwcR6fZoF66JMbAsyxq2QmEAwnhizbaRfMZtQhRvPizVEW/14XqzBv7GN5HNKjihTlMWgY9cdq0fcF03T8Pl68fvjGdQMBgPJycno9YcfllkMw6u9kJaWhk6no62trd/6tra2frPhHyUrK+uQx4w0G+dHefHFF4lEIoRCTRgMMYLBOlJTp/DpT3+aJ598kuLiYl566aV+E9q9vb18/etf57vf/e6A9goKCvD7/axevZrVq1fz9NNPk56eTn19PatXr0aLRQmrGh2RuMV5v1AZirKyMjweDy0tLYe1VgyHj9ZzkyTpqAOm96cBP9jLJxqNDtjPYrGMi6VZiAqBQCA4iKZQhOv2NvBGtw+AGTYzD07PZ0HSgQeQqoapq/8/amsfR1VDSJKegvwrKCq66qhdnQbD4/Gwbt063ntvKz6fgUjERHJyNosXL2DBglLS03WHrFOhaRqRBh/+91oIbO+AWPwBJBlkLHPTsS3OxFiY9LF0bzqaQoIT0a7g6DGXpWCamkxgUxuel2uItQfo/M0OLOXpJJ9dPKwCjZIkDemCNFxsphRCdgtutxtNU/F73KSkpIxanKjRaGThwoW8/vrrnHvuuQCoqsrrr7/OVVddNeRxJ554Iq+//nrCxQjgtddeS2TaPDgb534RsT8b5/5MT8OhsLAQAE0rIRCoQVECBIO1XHHFZVx88ZfJy8ujpKSk30z9ggUL2LVrF1OnTh20zR07dtDV1cW9996bKB+wceNGAHKMBpCgNza8gfx5553HjTfeyE9/+lMefvjhAdt7enpITk5mxowZrF27tt+2tWvXUlZWlrBSHI79MRSKciBOJykpiZycHNauXcvKlSv7tb0/JfB+t6mWlpZEXMjWrVuHdc6xQIgKgUAgID7wfrqlm9urmvApKkZJ4vtFmXyrIKNf8aSu7nepqLiNQKAGgOTkJUybdjt22/CD5oZLV1cXa9euZevWraiqiiTB9OmpLF26kpKSUvR6+ZADVjWsENjajv+9FqIt/sR6Q44N29JsrOXpyKaP52PgaAoJTkS7gtFFkiVsi7OwzErF81od/vdaCG7rILS7m6QzC7Evy0GSx15km81m0tPTcbvdRKNRuru7SUpKwmazjYrI//73v8+ll17KokWLOOGEE3jkkUfw+/1cfvnliX0uueQScnNzueeeewC4+uqrWblyJQ8++CCf/OQn+ctf/sLGjRv59a9/DcQF1TXXXMNdd91FaWkpxcXF3HLLLeTk5CTEC0B9fT3d3d3U19ejKEpisDt16tREqt14ezIWSyGBQDWqGuHkk6eTlJTEXXfdNSCG9oYbbmDp0qVcddVVXHnlldhsNnbt2sVrr73GY489RkFBAUajkZ///Od84xvf4MMPP+TOO+8EwKLXkWM6YC3ojSkkH+Kzy8/P5+GHH+aqq67C6/VyySWXUFRURGNjI3/4wx+w2+08+OCDXHvttSxevJg777yTCy+8kPXr1/PYY4/x+OOPD/t7ysjIwGKx8PLLL5OXl4fZbMbpdHLdddfx4x//mJKSEubNm8eTTz7J1q1bE+5fU6dOJT8/n9tuu427776bioqKCU11+/F8mggEAsFB1AfD/GBvA2+7464IC5OsPDy9gDLbgVFgKNRCZdVPaG9/EQCjMY3SqT86qqxOQ9HZ2cnbb7/Njh07EmbtoqIiTjrpJKZMmXLY80Xb/PS+10JgcztauG/mSy9jnZuGbWk2xnzHx9IqsZ+RFhKcqHYFY4dsNZByzlRsi7LoeaGKSL0Pz3/2EdzWQcp5pRgyR9/y+FH0ej1paWl4PB4CgQBer5doNIrT6TziKvcf5cILL6Sjo4Nbb72V1tZW5s2bx8svv9wvyLq+vr7feZYtW8YzzzzDzTffzE033URpaSnPP/88s2fPTuwznGyct956K7///e8Tf8+fPx+IF5NbtWpVv37Ksh6LpYhAoBpNC3HxxZ/j/vsf45JLLum339y5c3nrrbf40Y9+xEknnYSmaZSUlHDhhRcC8Zn7p556iptuuolHH32UBQsW8MADD/CZz3wGgDSDHrs+fq0NoQiZqorhEJ/xt771LcrKynjggQf47Gc/myh+96lPfSqRIWvBggX89a9/5dZbb+XOO+8kOzubO+64o1+Q9uHQ6/U8+uij3HHHHdx6662cdNJJvPnmm3z3u9/F4/Fw7bXX0t7ezsyZM/nXv/6VyPxkMBj485//zDe/+U3mzp3L4sWLueuuuzj//POHfe7RRNIOlW7pOMTr9eJ0OvF4PKIQnkDwMUfVNP7Q3MWd1c34FRWzLHFjcTZfzU9PVGBV1RiNjX9gX80jKIofkMnL+zIlU76HXu8Y1f4MJiZKS0s56aSTKCgoOOSxmqIR3NVF77pmIjUHin3pU83YlmRjXZg54kw3xxvNzfGB/iBZJBPrc3ImT7uC8UFTNfwftOJ5sSYuxnUSSafk41iVTzgWoaamhuLi4jFLY69pGn6/H683noHNYDDgcrmG7UJzPBCL9RII1PDtb/8Yt9vPf/4z+hm2FE2j0h8irGrY9TJTLKaP9STLfkKh0JC/8eGOnUdkqejs7OR3v/sd69evT6QPy8rKYtmyZVx22WUJHy+BQCCYrNQFw3xvTwPreuLWiSVOGw9Nz6fEeuBm6vXuYM/eH+Hz7QTAmTSfadPuwOGYOap9GUxMTJs2jZUrV5JzmFGoGozh/6CV3nXNKD3h+EoJzDNSsZ+YjakkeVzcOI4VwuG4a9JQMZo2W3x7OHxksRBj1a5g/JBkCfuSbCzTXbifryK0uxvv/+oJftiJ5bNFY39+ScJut6PX6xPuUB0dHaSmpg4I8j1e8fsVNm+u529/e5E///lRolEPBoNzVM+hkySKLCYqAiF6YyodkRgZpo/H5zvWHLGo+OCDD1i9ejVWq5XTTz+dsrIyIB71/+ijj3LvvffyyiuvHDZVl0AgEEwEqqbxu6ZO7q5uIaiqWGSZH5Vkc0VuGnLfbFUs1su+mkdoaPg9oKLXJzG15AZyci5AkkYvT+PRiIloR4Dedc0ENrWhReKBh7JVj21JNrYl2eiTxch1MBRFIxwIo0V68YWCRENhYuEQ0Uj8NRKK4HbHaEvzYTLEUFUFTVXRVBVVVdE0DZ1Oh6zTI+v18fd6A1HFQGtnEq5UAyarBaPFisFswWTpe28wEgjEg7cFkxud00TqJTMJbu+g51/VRFsDBJ/Zg3pW0iFraQ3Fwd/5cLyZ9sdZdHd3E4vF6OzsHNUA7snMOeecw/vvv8+VV36ZU089kWCoAVk2otONbsFNs04m12SgMRSlNRLFrpexfowsQmPFEbs/LV26lPLycp544okB5iJN0/jGN77B9u3bD1mtcSIR7k8CwceXfYEw39tTzwZPPGh5WbKdh6fnU2g5MADv6PgfeytuIxxuASAz8zOUlv4IkzFt0DZHwkjFhKZphKt66F3bTGhPd2K9PtOKY3ku1vnpSMNMN3m8EY2E6e3uii9dnfi6u+h1d+Hv6SHk8xD0+Qj6vPT2BGnvSUavi6KTB1ZEVlQdMcWAy9aOXjeM8sZ9xBQ93f6MIduV9FaMtlTy81WS0xzYklOwOVOwpbhISs8gOTMLR2o6shjYTCqU3gjuf1bRW9+N7xQbRYVF2DOdSPrDqwNVPVDdWtPoVzl7OOJCVVW6u7uJRCJAvILzcGrQHA9omkYwWEss1ossG7FaS5Dl0Q0D1jSNulAET1TBKEuU2cwJt9ePI6Ph/nTEosJisbBlyxamT58+6PY9e/Ywf/58gsHgoNsnGiEqBIKPH4qm8euGDu6raSGkath0MreU5HBJTmrCOhEKt1JRcQcdHXEfXrM5n+nT7iA19eRR60dPTw9vvfUWW7duTYiJsrIyVq1adWgxEVMJbGnH924TsbZAYr15ugv7ipy4i9Nx/jBUVQVfZyee9lZ62lrwtLXS0xZ/7+1oJ9TrG3ZbnoCLsJpEcjIYjCb0ZjMGoxG9yUxYSSI5WSMjNYIky8iyjNS3xN9LqIqKEouiKgpKLIYai6HEYrR1GfG4Qa91EwkFiQaDRELxZ2EwYsNi8OO0dg/ZL0mWSUpLx5mRhTMzi5TsXNLyC0nLL8TuSj3uv+PJiqZpuDc10hTtojA7H7PBhC7FhM46tMuMqkIkEhcTshwXFJoWXy9J8SKWwxEWmqbhdrsJhUIAOBwO7PaPR3V7VY0lMkLp9XYslqJRv+6YqlERCBFVNVIMOgosH18L74TEVGRlZfH+++8PKSref//9AaXbBQKBYKKo8If43p56Nnnjg/GTU+w8OL2AfHM8L7imKTQ2PUN19QMoSi+SpKMg/0qKi78zaib33t5e3nnnHTZu3JjIQz4cMaEGY/RuaKF3bROqL17QSDLKWBdmYl+WgyH9+Ju1jEWj9LQ00dXUQFdjPV2N8Vd3SzOqcmjLgd5kwuFKxZ6Sij01DbsrFZszBWtSEhZHEmZH/FUyOGjvshAOS/2yNPn98exM+7M0HWmticGyP0XCKj3uEGrEh9PahRrsxt/jxt/TE391d+Fpb8PT0YYSjcbft7fBh/0r5pqsNlLzC0nLKyCtoJCsqWWkF05B/zHxtZ9IJEnCOjsdXZUPySCDpqF0h9BCCrpk06AxS7FYXEQcbHiSpPjfihLf3lea4LDnTklJwefz0dvbi8/nQ1EUnE7ncS8s4hmhCvAHqonFeolE2jGZRnd8qZclCsxGqgNh3FEFhz5GikEkRh0pR/zJ/eAHP+BrX/samzZt4rTTTksIiLa2Nl5//XV+85vf8MADD4x6RwUCgeBIUDSNX9a3c39tK2FVw6GTuW1qLl/MdiUexj7fbvbsvRmvdysASUnzmD79bhz2wSdNjpRgMNhXtO69RJXT4uJiTj311ERhpsGIecL0vtuEf0MrWiQuQnROI/bludgWZyFbjo+HXsDrob2mmvbafbTXVNNRV4O7tRltiMADWafHmZFJcmYWzszsA68ZmdhT0zBZh5/b32g5UE8iEIgP9lJS4vUkIJ7J6UhrTewXJP3blcnMtuJyWTGbhx4QaapKb093XFT0WWG6mxvpaqiju7mRcMBP895dNO/d1e/zyCgqJmtqGVklZWRNLcOVk3fcDzYnCkknoXeZ0UVlFG8ENRBFiyroXGbkg9wOVfWAGB0MWT78Pv3OK0kkJSWh0+kSaWc1TSM5+fi3UOp0FsymXEKhRsLhdmTZgsEwul4mdr2OTJOetnCMxlAEm07uV5tIMHxGlFL22Wef5eGHH2bTpk2JWTedTsfChQv5/ve/zwUXXDDqHR0thPuTQHD8s9sd5vu76tncG0AyapzqcnD/tHxyzfurlgbYV/MoDQ2/Q9MUdDo7U0uuIzf3C0jS0fu0RyIRNmzYwNq1axNuC7m5uZx22mlMmTJlyOOirX58bzcS2NoBavzWrM+04jg5D2t5+rD8uCcrwV4frZV7aa7cS3tNFe21++jt7hp0X6PFSmpePql5BaTmxl9dufk40tKQ5dGNOfioNWKoWhMftWIcabtHQywaxd3SRFdDHZ0N9bTXVtNaVUHQ5x2wr9WZTN7MORTMmkv+rLmkZOcc9wPP8eCjriFqKEasOxT/P5Wkfu5Qqhr//g8VHqMo8d/FkY5dA4EAPT09AJhMJlJSUo66lsWxQCjUTCTShSTpsFpL0OlG101J0zSqAmECiopDL1P8MUwzOyExFQcTjUbp7OwEIC0t7ZhIeSZEhUBw/BIIajy+s4uHd3cQioHNIHHDrAyumJ6CxRJ/QHR1vcWevbcSCjUCkJH+CcrKbhkVs3osFmPTpk28/fbb+P3xYPD09HROO+00pk2bNuhDStM0IjUefG81EtrrTqw3TXFiX5mHuSzlmHu4qYpCZ0MdLZV7aK7YQ0vlXtwtTYPum5KdQ3pRCRlFU8gomkJaQSH2lImLHzhWak1omoa3o42Wqgpaq/bSUlVJ+74qYtFIv/3sKS7yZ82lqHwBxfMXYXGI595IGGzApSkqse5QosCkbDegc5rQNIlIJO7uNNjPWNPiy3DjKgbrS3d3PDbHaDTicrmOe2GhaSqBQA2KEkCnM2O1loxqJj6AkKJSEQihaZBnNpJqPD4swsNlwkXFsYgQFQLB8UllT4Sr3mpmY3cQyaxygsvKLYW5JClGzGZIT++moeEuWtteAMBkymb6tDtISzv1qM+tqirbtm3jzTffxOOJF55LSUnhlFNOYfbs2YM+8DVNI1ThxvdGA5G6vhlnCSyz03CcnIcxf3QL640l0XCI5r17aNi1g+a9u2itriQaDg3YLyUnj+ypZWSVlJJRVEJ6YRFGy+SJCwmHobY2PoM8mL97JBLfp6hoctaaiEWjtFbupX7ndhp2baelYg9K7EAciiTJZJdNp2ThCUxZsJjUvIJjTrBOFEMNuDRNi7tC+eJiTjLp0LvMRBU54Tr3UfavH05MxVCEw2G6u7vRNA2DwUBqaupxLyxUNYrfX4mmKRiNqZjNo6/u28NRWsJRZAnKbGZMx/lnejATKiq8Xi9PPvkkra2tFBcXU15ezpw5cyZ9ujMhKgSC4wtN0/hzSzc/XN9Gr1fCmqRxTWEmF2a7kCUpbtauXkNn5/0kJ1cAMvn5lzGl+Br0+iEqlR3BuSsrK3nttdfo6OgA4tlZVq5cyfz58wethKupGqFdXXjXNBBtihfeQy9hW5SF46Rc9KkjDw4fTZebQxENh2iu2EPjrh007NpBS2XFgCBqo8VKduk0skunk1M6jaypZZN+ljwYhJoacDqHnmH2eKC4GCyjmzZ/TIhGwjTv3U39h9uo2bKRjrqaftudGZlMXXwi05edTGZJqRAYh+BQAy4ANRgl1h3ui86W0bnMRDXdUWd/OhSRSISuri40TfvYWCyiUS/BYB0AFkvhqMdXaJpGdSCMX1E/dtW2J1RUnH766Wzbto3FixdTX1/P3r17ASgpKaG8vJxnn312JM2OOUJUCATHD63hKNfuaeB/rT5irQbmuczcNTM3UXciFGqjet8DtLe/RyRioqTESnn5nTiTyo/63E1NTbz22mvU1tYC8XTbK1as4IQTThjUFVRTNII7OvCuaUikhZWMMral2ThW5KFLGvm0ZSh0IDj4SAKLh4uqKDRX7qFu+xYadu6gtWpvvxlwAHtqGgUz55A7YzY5ZdNJzc1HOsYGOMe6peJweDvb2bd5I/s2baB+53aUvuQBAMmZ2UxbdjLTl59MWn7hBPZycnI4UQGgRhViXSGIxZWDnGxCNRhGXKdiOAxHWPziF7/g/vvvp7W1lfLycn7+859zwgknHLLd5557jltuuYXa2lpKS0u57777OPvssxPb//GPf/DEE0+wadMmuru72bJlC/PmzRudizoMB8dX2GylyPLIXe+rqqq4++67ExNDOTk5LF6yhM9+8ypmzl9ArtlAmvHoXfuLioq45ppruOaaa466rbFiQlLK7mf9+vW8+eabLF68GIib4nbs2MHWrVvZtm3bYY4WCASCkaNpGs+39/DDikZ6YgoGZL6al8nXprnQyxKaptLa+i9qah9DUfzo9QbS0y5j4YILsNnio8WRzup3d3fz+uuvs3PnTiCepGLp0qWsWLECyyDT14kaE282xAccxF0k7MtzsC/PRWc7ugfWUIHFbnd85n24gcUfxdvZTu22zdRu20z9jm2EA/5+2+2uVPJnzSV/1hzyZ87FmZF5zM/omUxxMeZ2Dy4q/P54TMWxKCgAktIymHfm2cw782yioRC12zezd/27VG/aQE9bCxv++Swb/vksaQVFzFixitmrTsfqTJ7obh8zyAYdhnRLIs5CdYfQOTX0NgMQ/98YbZ1tNBpJTU2lq6uLSCRCd3d3P2Hx7LPP8v3vf58nnniCJUuW8Mgjj7B69Wr27t1LRkbGoG2uW7eOL3zhC9xzzz186lOf4plnnuHcc89l8+bNzJ49GwC/38+KFSu44IIL+OpXvzq6F3UYTKYsYoofVQkRDDZgtRYf8t4TjUYHnejZuHEjp512GrNnz+ZXv/oV06dPx+fz8cILL/DzW27il/95meZwFIded0y5QQ11vePBiC0VJ554Io8//jjz588f7T6NKcJSIRAc23RGYtxY0cB/OuKxC3PtFh4oKcDUYcFkAkVpoLLqHjyeLQA4HLMoLPghen0JRUXxGcORzOr7/X7efvttPvjgA9S+lKfl5eWccsopJCcnD9hfi6r4N7bie6sRpScMgGzVY1+Ri/3EnFFLCztagcWxSITGPTup3bqJ2m2b6Wqs77fd7EiicM48CufMI3/mHJyZWce8iBiM0cr+dCwRCQWp3vQ+e9e9Tc2WTQlXNlmnZ+qiJcw5bTWFc+Ydc5an0WQ4lor9aJqG0hNG9cctQfsDuMfy/+WjFovU1HiygyVLlrB48WIee+wxIB7/lZ+fz3e+8x1uvPHGQdu68MIL8fv9/Oc//0msW7p0KfPmzeOJJ57ot29tbS3FxcWHtVT4/X6ys7P53e9+x3nnnZdY//zzz3PxxRfT2tqKw+GgoaGBa6+9lldffRVZljnppJP42c9+RlFREQAffPABN910E1u2bCEaDTNnzjQeeOBeli49PdGmJEk8/vjjvPTSS7z++utcd9113Hbbbf36o2kac+bMwWw28/777w+w7rjdbrpMFvwxleY9u7j/xutZv349VquVz3/+8zz00EPY7XYALrvsMnp6elixYgUPPvggkUiEiy66iEceeQSDwcCqVat46623Bpwf4O9//zu33norVVVVZGdn853vfIdrr72237X885//5Nxzz02sS05O5pFHHuGyyy5LfP5/+ctfePzxx9mwYQNPPPEEl1122ZDfxVBMqKXipz/9Kbfeeit/+9vfMB2r0zYCgeCY4uUODz/Y20BnNIZegmsKs7i6MBODLNEYiLF79z/o8fwCVY0gy2aKCr9OTs759PTocDjiguJIZ/Wj0Sjvvfce7777LuFwXByUlJRwxhlnkJWVNaCPWlTF/34L3jcbE8GbssOA46Q8bEuykU2jlxI1HI6LI9sQoSE2W3x7ODz47HrQ52Xf5g+o+uA9ardvJtZ3fdAX1Fs6jaJ5CyguX0jGlJJEOtdwOP4ZjnXsxkhRVQ0lqhKLKvHXiEosqqKpB+bQDp5PkyQJnV5GZ5DRG2RSnTIeWSYQlAkEpH41LI4lQTFca5zRbGHG8pXMWL6SUG8vFRveZccbr9JaVUHFhrVUbFhLUnomc045gzmnrcaWPIiC/bihaRANDLpJAnRWDUmLoXgiqG7Qgjr0KeZBC+UdMQbrgKCf/a5P3d3dRCIR3G43NpuNTZs28cMf/jCxnyzLnH766axfv37I5tevX8/3v//9futWr17N888/P+Iu22w2LrroIp588sl+omL/3w6Hg2g0yurVqznxxBN555130Ov13HXXXZx11lls374do9GIz+fj0ksv5ec//znhsJsHH7yfc865iL17d5GcfMDyctttt3HvvffyyCOPoNcPHOpu3bqVnTt38swzzwwah5KSkoJFUdnq7eLScz7N0qUn8sEHH9De3s6VV17JVVddxVNPPZXYf82aNWRnZ7NmzRqqqqq48MILmTdvHl/96lf5xz/+QXl5OV/72tf6WXU2bdrEBRdcwG233caFF17IunXr+Na3vkVqauoRi4Ibb7yRBx98kPnz5x9W9I4lIxYVRUVFeL1eZs6cyYUXXsjSpUuZP3/+IQs6CQQCwUjwxhR+VNnIc63xlKvTbGYenVFAuSOeGMLn201N7S20tHYSjZrJylzAtGk/QK/PpacnPhB0ueIWilCo/6y+0Rhf3O749v2z+vszOq1ZswavN56dKSsrizPOOIOSkpIBfdRifZaJNxpQvHExoXOacKzKw7YoE8kwuvUV4n2MW1uGsnQbDPECbAfXkutpbaFq43tUb9xA055daNqBjfYUF0XzFlJUvpDCOfMw983E7WesYzcGIxKKEfBGCHojBA5agr4I4WCMcCC+RIIxwoEo4WAMNTY6SQ2jioTepMds0WFP0mOy6jFa9JiteqxOI1anCZvThC3x3ojeOPrf85FyNN+T2W5n7mlnMfe0s+ioq2H766+w+901eDvaWPvXP/HeP/7C9BWrWPTJc0krKBqX6zmY8UpGcFiiAfjJ0CZACdD1LaPOTc1gHDiTYDKZcLlcdHV1EQqFaGtrQ1GURJHi/WRmZrJnz54hm29tbR30mNbW1qPq9pVXXsmyZctoaWkhOzub9vZ2XnzxRf73v/8BcVctVVX5v//7v4RV58knnyQ5OZk333yTM888k1NPPZCtT9M0Hn/8IXJyZvPaa//kvPO+mkgz+8UvfpHLL798yL5UVlYCMH360IVOzTqZd//xN8KhMLc88Wump6cye/ZsHnvsMT796U9z3333JT6nlJQUHnvsMXQ6HdOnT+eTn/wkr7/+Ol/96ldxuVzodDocDke/iaiHHnqI0047jVtuuQWAsrIydu3axf3333/EouKaa67hc5/73BEdMxaMWFR8/vOfp62tjZUrV7Ju3Tp++ctf4vV6cblczJ8/n1dffXU0+ykQCD6mrHX7+O7ueprCUSTgWwUZXFeUhVkno6phamp/QV3dr9C0GFlZaaSlXovV+ikiEQlFOTDDLEnDn9Vvbq7h5Zdfpq2tDQCn08mpp57KnDlzBsxqaYqKf1NbXEz0uTnpnEYcpxTExcQYFqyT5fiAMRodPAYgGgVZ1uioraZ+2zqqPnhvgFtTemExJYuWMnXREjKKS4Z00RiL2A1N0wj7Y3i7gvi6Qni7Qvi6Qvi6Q/i6gni7QkRDypE1+hFkvYS+zwoh6+LfRb9LlEBTQYmpKNH4ovZZNAw6DWJRwr4oYd/wzmdJMuJMs+BMt5CUZo6/pltJybJiPsr4meEwmt9TemExp13xDU7+0uVUbljH1lf/S0vFHna++T92vvk/CufOZ9Enz6WwfMGYu8JNhKA9FtlfEM/tdhMMBiesH9/4xjf405/+lPi7t7eXE044gVmzZvH73/+eG2+8kT/96U8UFhZy8sknA7Bt2zaqqqpwOPqn0w6FQlRXVwPQ1tbGzTffzJtvvkl7ezuKohAIBKivryccbsdsjg/aFy1adMj+Ddfzv6mygulz5mC0WGmNRMkzG1m+fDmqqrJ3796EqJg1a1a/bH/Z2dns2LHjkG3v3r2bc845p9+65cuX88gjj6AoyqDZA4ficNc7XoxYVHz44YesX7+e8vIDWVRqa2vZsmUL27dvH5XOCQSCjy8hReXemhZ+1dCBBhSajfx8RgEnJMdnzz2eLezafSOBQBUA6elnMq3sdkymjEFnM4PBw8/qNze72bDhf+zbFw/CNplMnHzyyYNmdNIUjcCWNrxvNKB0xwOwZYeRpFPzsS3OGpfq10MFFmuaRmdDHdve2UrH7nfAvzexTZJl8mfOpmTRUkoWLsGZMbyif0di5fkoiqLi7Qjibg3gbvX3vQboafUTGYZo0BtlrE4TVocxbiFIMmKxGzBZDZhsekwWffx9nyXBYNShM8ro9DLyCNxNVFVDianEwkrCGhIJxAgFokSCMUL+KAFPBL8nQsATxu8J4/dEUKIqwT6rSus+z4B2bckmUnNtuHLspObaSM2x48qxoRvF38rRfE9DYTCamHnSKcw86RSaK/aw6b/PU7lhHXXbt1C3fQupeQUs/dyFlJ24YtQrnsPYJSM4KgzWuMVgmCQyQyka6GUMqeaR3yMMh07db7FYUFWVSCSCTqejtraWE088MbG9ra1tUNfN/WRlZSUmVIZ7zEe54447+MEPfjBg/ZVXXskvfvELbrzxRp588kkuv/zyhCDt7e1l4cKFPP300wOOS09PB+DSSy+lq6uLn/3sZxQWFmIymTjxxKVEo1EikQ70+rggsQ01e9RHWVkZAHv27DlkbLAkSZj67iFdkRgp+sF/3x99PkiSlIi9OxqkvrToBxM9KGvbfg53vePFiEXF4sWLExVj91NUVERRURGf/exnj7pjAoHg48uu3iDf3lXHbn98sH5xtovbp+Zi1+tQlBD7ah6mvv53gIrRmMa0stvJyDgrcfxgbhGHmtUPBoOsXfs+H3ywA6fTjcEgsWjRIlatWjXgZq0pGoFt7fher09kc5LtBhyr8rEvyRoTN6dD4XLFB1bd3Rrhnnrqtm2g8oNNdLZ60ctRnNYuLBYTxfMXUnrCMornLRrg1nQ4hhu7EQppxIJhOht66Wjw0dnYi7vFj6c9mJj9Hwyr04jDZSYp1Ywj1YIjdf97M7ZkE0bz+Fa2lWUJ2ajDYNRhcQwv1a+maYQDMbydQTwdQbydQbwdQTydQTztQXrdYfw98aV+Z3fiOJ1eJi3fTmZxUnwpSiIpzTKimf+jjbEZDjll08kpuxFPexubX/oXO954la7Gev776P2s//tfOPHzF426uBgLoXTUSNKgLkhDIRvBYLIT7QxCTCXqkdCnmZHH6H5hs9lQVZW5c+fy2muvce655ybExuuvv85VV1015LEnnngir7/+er/0p6+99lo/YXI4MjIyBs0u9aUvfYnrr7+eRx99lF27dnHppZcmti1YsIBnn32WjIyMIYOB165dy+OPP55Ib9vQ0EBnZxc6XTzzXijUOKz+zZs3j5kzZ/Lggw9y/vkXov+IwOvp6SE5OZkZM2bw1FNPYY6ECBnNNIQiVL37LrIsM23atGGdC+IxL4rSfwJlxowZrF27dsD1lZWVJawU6enptLS0JLZXVlYSCAweyzMZGPGd+uqrr+a2227jr3/966CZTwQCgeBIUTSNJxo6uG9fCxFNI9Wg56Hp+axOcwL7rRPXEwjsAyAr61zKSm/BYEg+bNuDzeorisKOHTtYt24d3d0aZnOI6dOLOfPMMwc8EDW1r87E/+qJdcTdCmSbAcfKPGxLs5EnyJfe39VA3bq32frWFtqavKiajCypOCwKM5eWMefkSymevwijeeTV2gaL3dBUDU9nkK7mXroa/TTVBJEDbtSDgr0PRm/SkZIZdwNKybKRkmUlOcuKM92CfpyF2FggSRJmmwGzzUBG4cABUTgYo7vZT1dTb+K1q6mXcCBGW42XthpvYl+Lw0DO1GRyp6WQW5ZCSrZ1WCJjJDE2I8WZkckpl36VZed/kS0v/ZuN//0n3U0Noy4uxkMojReSXo6nnO0MokVVYh1B9OmWMRMWDoeD73znO3zzm99k7ty5nHLKKTz++OP4/f5+8QaXXHIJubm53HPPPUB8fLdy5UoefPBBPvnJT/KXv/yFjRs38utf/zpxTHd3N/X19TQ3x601+2uVZWVlHdKikZKSwuc+9zmuu+46zjzzTPLy8hLbLr74Yu6//37OOecc7rjjDvLy8qirq+Mf//gH119/PXl5eZSWlvLHP/6RRYsW4fV6ue6667BYLOj1TiTZgKpGDvu5qCrEYhJPPPEkn/zk6Zx00knceOOPmDVrOoFAL//+97959dVXeeutt7j44ov58Y9/zE1f/xpfuv4Gujo6ueu73+XLX/7ygLiTQ1FUVMTbb7/NRRddhMlkIi0tjWuvvZbFixdz5513cuGFF7J+/Xoee+wxHn/88cRxp556Ko899hgnnngiiqJwww03TFi62OEwYlGxP3q/tLSUz372syxZsoT58+cze/ZsjEdTe14gEHwsaQhF+M6uOt7zxC2gZ6Ym8eD0fNKNhkGsE+lMn3436WmnHdE59s/qt7VBe3st69e/RU9PN5GIkfR0B+efv5rZs6f2O0bTNEJ73XhfqSXaEu+bbNXHxcSJORMiJvw9bvaue5td77xJ277KxPqMZCsF5YuYtvREpi89OiFxMLIMSiRK3U4f7pZeOuq9dDb0Eg7GU4/GFImYKpPqiGA0SKRkWUnPd5CWbyc1x05ylhV7sml0Mt8co5gserJLnGSXOBPrNE3D0x6krdZLW62X9lovHQ0+gr4o1Vs6qN4Sr9JuSTKSW5ZM/nQXhbNTsSUPPnoeToyNTje6tRJMVhtLP38R8z/x6QHiYsPzz7HyS1dQVL5gxO2Pp1AaDySdjD7NQqwzhBZVxlxYXHbZZbS3t/PAAw9www03UF5ezssvv9xvQFxfX98vVmzZsmU888wz3Hzzzdx0002Ulpby/PPPJ2pUAPzrX//qJ0wuuugiAH784x8PSN/6Ub7yla/wzDPPcMUVV/Rbb7Vaefvtt7nhhhv43Oc+h8/nIzc3l9NOOy1hufjtb3/L1772NRYsWEB+fj4/+clP+MEPfoAkyVjMuQQCtQAoSmjQc6tqvIilpsEJJ5zAunUbuffeu/nmN79KV1cn2dnZLFu2jEceeSTRp1deeYWrr76aL646GZPFyunnnMPDP3vkkNf4Ue644w6+/vWvU1JSQjgcRtM0FixYwF//+lduvfVW7rzzTrKzs7njjjv6BWk/+OCDXH755Zx00knk5OTws5/9jE2bNh3RuceTEdepqK2tZfv27Ylid1u3bqW2tha9Xs+0adMmbVyFqFMhEEwuNE3juTY3P6poxKeoWHUyd07N5YvZLiRJOirrxEcJheDDDzt5/vmNVFd3ABJJSRpnnjmLs84qx2br/2AP13rwvFxLpDY+iyyZdDhOzsO+IgfZNL4uOdFQiKoP1rPr3Tep274FrW8UJckyxfMWMn3FKkoWLMZoObS/9XDYP9htruyhdZ+H1n0eaqqiBCIGrKYDlbT1ehlXrg2D00FhiYVZC224cmzHheVholCiKu31Ppr2ummqcNNS7UGJ9h8xpxc4KJqTStHcNNLzHf3E2mjVLRkp4YA/IS7CfS7SRfMWsvLiy0eULWqyVDk/kjoVw0FT1ISwQJbGVFioqkpXVxfRaBSdTkdaWtoRBQGPNn/84x/53ve+R3Nz86hPQgeDDUSjPciyCZttaiIb1H4ikQOB/h9l//qhuqRpGpWBMEFFxWXQkW+Z5KaxI2Q06lSMWFQMhs/nY+vWrWzfvp1vf/vbo9XsqCJEhUAweeiOxrhubwP/7StktyjJymMzCymymEbNOpE4V3eAf/xjA1u27MZgCKNpMrNnz2f27MVkZFj6BXtGWvx4X6kltKfP910vY1+WjWNl/lFXwD4SNFWlYdcOPnzzf1S9v55o+MDsW/bUacw4aRXTlp2MNcl5iFaGcR5No6ctQHNlD00VPTRVuAl4+rsRRGMyMVMSydkO8kps5JQkYUu1EgrJx21RuMlALKrQVuOlca+b+p3dtNd6+223Oo1MmZdO6aJMskuchCPSpCjeF+z1seEff2HLy/9FVWJIkszsU89g+QVfOuI6FxMtlGD0RQWMr7BQFIWOjg5UVe1XHG88CQQCtLS08JnPfIZzzz2Xu+++e9TPoaox/P4KNE3BZMrEZMo4aFtcVEjSgDIfQNx6oWlxUTGUNc8fU6gKxF08S20mrBMozkabCREVDoeD+fPns3DhQhYsWMCCBQuYOXPmMVNZVYgKgWBy8EaXl+/tqactEi9k94OiLK4qyEQvj651QlEUNm3axPPPb6CnR8ZiCTFlyhRWrlyJy+UCDgxMMkxBvK/VEdjWARogg21RFo7TCtA7R3dW6lD59r2dHex8K56209N+IAtLcmY2M05axYwVq0jJzj2q83s6gjTs7qa5wk1TRQ8Bb38RIeslsorj7jqZU5xkFSchGYwirecE4/eEqd/ZRe2OLhp2dRMNHwj+tCWbmLoog/w5mejtDnp7pQn/nnpaW3jnmaeo2BAPSDWYLSy/4EvMP+tTyMMckE2GKuejISoOdtHaP2jtJyx0EoZ065hljotGo3R2dqJpGjabDafz6CYjjpTbbruNu+++m5NPPpkXXnghUZF6tIlE3YSCjSBJ2Kyl6HTxG6yqxu+7h/rZKUr8fnwoF8G6YJieqIJVJzPVOraV0seTCREVjz/+OJs2bWLjxo3s2rULVVWxWCzMnTu3n9A4ONXsZEKICoFgYgkoKndUN/NUUycApVYTj80spNxhHXXrRF1dHS+++CJNTZ309CSTkeHk9NNPpqioqN9+wa4IXW83k1rXhEmOP/ktc9NIOqMQQ/rRuxMdLCA0bfB8+0mOKE0fbuDDNa9Su31LfEfAaLEyffnJzFp5Otml00b8AIuEYjRV9NCws4v6Xd14OvrnsNfpZbKmJJFTlkJuaTKZxUlDFnKbNAXIPuYoUZXGCjdVG9vYt6WjX3repHQLJYuzKVucjcNlmvDvqWnPLt784//RWlUBQEZRCad/9VtkTx1eBp2JrlNxNKIiHhgcf9W0+Cy5LINe33dPUNRE8DZ9wdySbmyERTAYxO2OFxFNTk7Gaj36+9tkQ9M0gsFaYrFedDobVmtxX4rXo7dUAERUlb3+EKoG+RYjLsP4usKOFRPu/hQMBrHZbNxwww10d3ezefNmPvzwQyKRyIDUWZMFISoEgoljizfAVbvqqA7GzcdfyU3j5pIcLDp5VK0TXq+XV199lQ8//BAAnc5OaemZLFs2C/1BecbVcIze91rofa8Vr18i3xkmeZYT5+oijLlHP4v20YFQLAa9vQcqfBsM0FbXwLY31lO3fR1mtQ6DLp6DPG/mbOaccialS5ZhMB35qEnTNDobe6nfGZ/Rbqn2oCoHbveyLJE5JYm86S5yy/pEhIiFOGaJRRXqd3ZTtbGNmu2dxCJ9MTcSFM5JY8aybArnpKIbo8HqcNBUlR1rXuWdp58i5O8FSaL8jLNZcdGXMduG9/82UYJ2pKLi4MBgWY5/H5oWXy9JBwawmqIS7Yinm5UM8WDusRIWXq+X3t5eANLS0o7L5DqqGqbXXwmahtmch9EY9507mpiKg2kLR2kNRzHIEtNsZnTHgbViwkUFgCzLbN26lblz5wIQi8XYtWtX4u/JhhAVAsH4o2gaj9W1c39tCzENsowGHpmRzypX0qhaJ2KxGOvXr+ftt99OFAhauHAhy5efSkeHLRHsqSkqga3t+N5pQvXHiCoSWoadWRfl4JyZPCrXPJjLRmMjtLZCijOEv/F9qje8TntdDQDBiI20ND3LP7WYWatOJyXryJ3EY1GFpr091GzvpHZ7J/6e/uldk9LMFMxMJX+mi7xpKRgtx8cMm6A/0bBC9eZ2dq1tpqXqQBE+a5KRWSflMHtlHtakiRtIBjw9vPXH37LrnTXxfjmTOeOrVzF18dIJ69PhGKmoOJJBrBZTiXYEQNGQjLq4sBiDjGmaptHd3U04HEaWZdLT0yc0cHusCIc7CIdbkSQ9dnsZkqQbtsg7HKqmsccfIqpqZJkMZJomb5rX4TIpRcVkR4gKgWB8aQxFuOqgVLGfyUjmvrI8Ugx6PN5t7Np1HYFANXB01omKigpefvllurvjwdV5eXmcffbZ5PRFcDY3xwvEWTrc+NY0JArX6VNMKAsLyTohmdzc0XuAfzS4NByGnVvaqN+8jj2btiErXSSZPciyjsK58ylZspL04tlMKdEd0QxswBuh7sNOard3Ub+7m9hBPvZ6o0zedBcFM13kz3SRnDG2rg7CLWry4W71s3ttC3veayHoiwttWS9RdkIW5afmk5Y3Nn7tw6H+w+3877eP426OFyybtfI0Trnsa5isk6M68MGMRFSMxN1G7Uszi6ohmfXoU81j4rOvqiodHR0oijJhgdtjjaap+P2VqGoEozENszkbOLw72nDpjsZoCEaQJZhhs6A/xlNmC1ExAoSoEAjGj+fb3Fxf0YA3pmLTyfykNI8LslLQtCg1tY9RV/cEmqYclXWiu7ubl19+mYqKuK+2zWbjjDPOYO7cuf1yr3srfez+SwO9tQGsBhWjXca8NA9tWgYWqzyqwZ4Hp8HUyTFqt29h2+tvsnNLJyZDEFXTYXZksOwT5cw5eTmWJCeaBh4PFBeD5TDlJbxdQfZt6aB6cwetNZ54UHkftmQTRXPTKJ6bRu605HFxaZpof3fB4VFiKvu2drDt9YZ+hfZyp6Uw/8wCCma6JmRQGYtGWffXP/HBv/8BmoYjNZ3V37yawjnzxr0vh2KkomIkgcFqWCHWGQANZLsBnXNsgoEPDtx2OBw4HI5RP8dEE435CAZqAQmbbSo63YHvbrDA+SNB0zQqAiFCika6UU+O+dh2IxsNUXHEtu8rr7yShQsXsmjRooSQGK8bkaIo3HbbbfzpT3+itbWVnJwcLrvsMm6++ebjTmELBMcyvTGFH1Y28lxrPCBwQZKVx/tSxfb27mXXruvw9e4EIDPz00wru+2IrRORSIR33nmHdevWoSgKsiyzZMkSVq5c2e+GGOsK4nmlluD2TlJjEjq7EW12DqZFWeit+jEZ/KoqeLu7adr2JnvWvknA04Oi6JDlDLKnzWHGsmU4smZQUCgnBMThCpN5O4NUbW6nenPHgLSi6QWOhJBIy7eP6/1wqMw8bne80KBINTs50OllShdlUrook9Z9Hrb+r4F9W9rj9TD2uskoSmLxJ4sonD2+M9Z6g4GTL76ckoVLePnxh+lpa+Fvd93MvNWf4uQvXY7BeGybvPa71wxlqRhsvWzSoUsxo3SHUHujSDoZnWP0B6wGgwGn00lPTw8+nw+j0YjpODMxGvQOonoHsZiPcLgFi6Uo8fs+2iKQkiSRbTJSEwjTGY2RZtRjHM3KkscgR2ypWLlyJVu3bsXn86HX64nFYnzuc59j1apVLFiwgHnz5o1ZNoGf/OQnPPTQQ/z+979n1qxZbNy4kcsvv5y7776b7373u8NqQ1gqBIKxZZPHz7d21VEXiiADVxdm8v2iLPSSSn39b6ne9zCaFsFgSGHatDvIzDj7iNrXNI3du3fz8ssv4/XGB9dTpkzhE5/4BOnp6Yn91EAU7xsN9K5vBkUDCazzM0g6swjFYhoTNx1N02jc/SHv//tFPni7Bp0URicrWBxJzFi+Ete0U1HkVKzW+Axmfv6B8w+Wb9/TEaB6cwdVm9rpqPcl1ksS5JQmM2V+BlPmpWFPmbhR+2SoISAYGd6uINtfb2TnO03E+grspRc4WPzJIormpo37ZF0kFOTtPz3Jttde7OtLEZ/63g9x5Rxd+uTRYDxiKgZs90VQPPG4KH2qGdkyNn77brebYDB43MZXKEoYv78S0LBYCjEYRm/sp2ka1cEw/phKikFHwTFcEG9C3Z8qKyvZtGkTmzdvTiw9PT3odDrKysrYuXPnSJo9JJ/61KfIzMzkt7/9bWLd5z//eSwWC3/605+G1YYQFQLB2KBoGj+ra+PB2lYUDXJNBn4xs5ClyXYCgTp27b4ej2cjAGmppzJ9+k8wmdIP02p/urq6eOmll6iqqgLA6XRy1llnMX369MQASIup9K5rxvtGA1ooXv3ZVJqM8xPFGHPGxn88Fo2yd93bbHrxBTpq49mrPAEXSfnlnLB6OcXzF6LTGwiF4oHaHR2QlQV5eQPz7UcDISreb6VqUzudDb2Jc0gS5JSlMHVhBlPmpU9ooO1+Jku1Y8HREfBG2PpaPTveakxkjUovcLDs81PJm3ZkhepGg9qtm3jxFw8R9HowmC2c+fXvMH3ZyePej4MZ6+xPg6FpGoonjNobBamvON4QaZ6PBlVV6ezsJBaLYTKZcLkmxhVuLAmFWolEOpBlIzZb6YBK20eDX1Go8sfFX5nNjGUCM6wdDRPi/rSf0tJSSktLueiiixLrampq2LhxI1u2bBlps4dk2bJl/PrXv6aiooKysjK2bdvGu+++y0MPPTTkMeFwmHD4QAaU/TObAoFg9KgPhvnO7no29AVjfzYjmXvL8kjS62hseoaqqntQlAA6nY2y0lvIzj7viB5a0WiUtWvX8s4776AoCjqdjuXLl7NixYpEOkRN0wjt7KLnxRqU7ngQtiHLivPsKZjLxmZg5O9xs+21F9n22ksEPD0A6I0mZp58CjNWfpqwrpBQCBQV5L5BhdkM6enxuAmPJz5TaTFF6alpZ/vzbTRX9iTal2SJvGnJlCzIoLh8cgiJg1HV+GyrYYgJVIMBAoH+vsuCyYc1yciyz09l/pkFbH29gR1rGumo9/HCw1sonJPKiZ8tIXWMBPlgFM1byCX3Pcp/f34/jbs+5L8/+ymNu3aw6pKvoj/G0p/Kclw47A8M3i8mdLrDBwZLkoTOaUKLqmhhhVhXCEPGkaea/cUvfsH9999Pa2sr5eXl/PznP+eEE044qI8yKSkpdHR0EA6H8fv9vPTSS9xyyy3U1tZSWlrKfffdx9lnH7AqX3bZZfz+97/vd57Vq1fz8ssvH1HfxguTKZ1o1I2qRohEuzEZ0wDYsmULP/nJT3j77bfxeDzk5+ezatUqrrvuOsrKyobVtk2nw2nQ4YkqtEWiFA1irZAkiX/+85+ce+65o3lZk45RzSdYXFxMcXEx559//mg2m+DGG2/E6/Uyffp0dDodiqJw9913c/HFFw95zD333MPtt98+Jv0RCATwzzY31+9twKeo2HUy95bl8fnMFMKRNrZt+yFd3W8DkJy8hJkz7sNiyT+i9quqqvjvf/+bKNg0ZcoUzj77bNLS0hL7RJp78fxnH+F98fSZssOI88xCrAszxyQlY9u+Kja/9C/2rnsbJRa3hthT05i/+lPMOW01Fns84PHgAOZAID6QyMqKx3AoMYXaHV3s3dhO094O1NgBo3FuWTKlizOZMj8dy/+zd9bhUVxtH75nfeOuhAgJkOAQnOIuxUq9lBaot1BK7W1LqRsF+tXlLdSpUCharLgXd4u72/ruzPfHkIVAAiEESHhzX9dcm4ycObMyc37nMbe6O4hSKORrstkqt1RcLk7kf5W6miVL766h66gmtOkbxr/LEzmyOYPkQ/mkHM4ntlswnW6NwrWWK8tXhZuPL+Nefottv//MzsW/cWDNSjJPnWTksy/h4RdwXfpQW5QLi5oEBguCgMpH56xhYS8wy6lmqzkp8+uvvzJt2jS++OILOnfuzNy5cxk0aBAnTpwgIODc+6hWq/Hw8KCkpIR169Zx11138c477zB8+HB+/vlnRo0axd69e2nZsqXzmMGDBzNv3jzn/3U1HsNms6FWq9FqAzGb07FactCovVm+fCVjx45l0KBB/PTTTzRp0oScnBx+//13XnnlFX799ddqnyNQo6bY5qDY5sCkEW+YtUKSJBwOByrVjUkXftXZn64nCxYs4Nlnn+WDDz6gRYsW7N+/n6lTpzJ79mzuv//+So+pzFIRFhbW4P7UQANXSandwYsn0/gjWx7sx3u48GlcOI11GrKzl3Li5KvY7SUoFBqaRD1LWNiEKzI5l5SU8Pfff3P06FEA3NzcGDx4MC1atHA+UB1lVkpWJ2PYnSVnQFIJuN/SCPfeYSi0tesmIIkip//dwd4VS0g7dti5PjimGe2HjiSmUzeUVdzIyweRAhL5qUWc3JnF6b25WE125z6+oa407RRETMdA3H3qT2RzQ0xF9alvWbKKso3sWHyGM/tyAVDrlHQeEUWr3qEoruOgKWn/HlZ88iGm0hJcPL0YOf0lQprGXrfzw9VV1K4NRJsDe44JJAmFmxqVV/X60LlzZzp27Mgnn3wityOKhIWF8eSTT/LCCy9U2Le8fsUDDzyA2Wxm1apVznttly5daNu2LV988QUgWyqKiopYvHhxtfqRlJREVFQUu3btIj4+3rl+7ty5zJkzh8TERBQKBYcPH+bZZ59l8+bNuLq6MnDgQObMmeOcRPr777958803OXz4MEqlkq5du/LRRx/RpEkT53kiIyNZsGABn332GTt37uSLL75gwoQJSJJ0NsWsBbvdlWbNOtOjRw8WLVp0UX+Liorw8vICYOPGjTz77LMcOHAAHx8f7r//ft58803nwL137960bt0ai0rNgnnz0Gg0PP7oI8ycOROAiIgIkpOTnW2Hh4eTlJQEwOeff86sWbNITU0lMjKSl19+mfvuu6/Ctezbt4+2bds6++Xt7c369evp3bs3GzZsoE+fPqxYsYKXX36ZQ4cOsXr1anr37l2tz+V8bqj7043g2Wef5YUXXnC6XLVq1Yrk5GTeeeedKkWFVquts+q5gQbqK7uLDTx+NJmUs8HYT0cE8nR4EKK9kMOHnyEndyUA7u6taBE3C1fX6Gq37XA42LlzJxs2bMBqtSIIAp07d6Z3797OG51kFynbmkHJPylIZ+sy6Fv74TkkElUtBy3brVaObv6Hf5cuojAzHQCFUknTLj1oP+RWgmOaXbYNq8HMiR2ZHNuWSUme2bnezVtLTMdAmnYKuqH1Aq4GHx85y1NhYcXsT+VxIj4+N7qHdYP6mCXLK9CFwQ+3IvNMMVt+P0VOUglbfj/Fse2Z9L67GUFRntelHxFtO3Dvu3NZ/P4b5CYn8ttrLzLgoSdp0evKU1DXFpIkYbKbrus5RQ8RR4EZXalcHE/pcunAbavVyp49e3jxxRed6xQKBf3792f79u0X7S8IAl5eXuzZs4eHHnqI0tJS5wBy0KBBFwmIDRs2EBAQgLe3N3379uXNN9/E19e30r5ERETQv39/5s2bV0FUzJs3jwkTJqBQKCgqKqJv375MmjSJOXPmYDKZeP7557n99tv5559/ADAYDEybNo3WrVtTVlbGjBkzGD16NPv376+QQvyFF17gww8/pF27ds7nhiAIaLVBmEzJrPx7KXl5eTz33HOV9rdcUKSnpzN06FAmTJjA999/z/Hjx5k8eTI6nc4pGgC+++47npz6ND/8s4GDu3Yy49GH6d69OwMGDGD37t0EBAQwb948Bg8e7AyEX7RoEVOmTGHu3Ln079+fZcuW8cADD9CoUSP69OlTab+q4oUXXmDWrFlERUXhXdkMz3WiXokKo9FY4UsDoFQqERscdhto4LpgFyXmJmczJ1kOxg7Tafg0tjGdvNzIy/uHY8dfxGrNQxBUREQ8TkT4oygU1c9YkpKSwrJly8jJyQHkAnbDhg0jOFguWiRJEuajZ+MmzhavU4e64TUiCm1E7Q5wzGVlHFizgr0rlzjjJbSurrTpP4S2g4fj7uN3yeMdNpHEg3kc25ZBytECZy0JtU5JdIcAmnUKIiTG65q4Z11PygPML3Tz8vauuzPwN4KCAllQnP+812jkpbBQ3l5XLTrBTTy57bkOHN2awfZFZ8hPK2Ph+3uI7R5MtzHR6FyvfTVhD78A7nz9fVZ+MpvTu7fz92dzyE9Locdd41Eorn+2IpPdROefO1/38wJs6b0OfaECQa1AcYk6NHl5eTgcDgIDAyusDwwM5Pjx45Ueo1Qqyc3Nxd/fn7KyMnQ6HRqNhsDAQLKyspz7DR48mDFjxhAZGcmZM2f4z3/+w5AhQ9i+fXuV2aMmTZrEI488wuzZs9Fqtezdu5dDhw7x119/AfDJJ5/Qrl073n77becx3377LWFhYc5Y2rFjx1Zo89tvv8Xf35+jR49WcM2aOnUqY8aMuagPKpU7SqULZ04nAdC8efMq3z+Azz77jLCwMD755BMEQaB58+ZkZGTw/PPPM2PGDOeYtHXr1rz52kySTBbCm0Tz+9dfsW7dOgYMGODMSujl5UVQUJCz7VmzZjFhwgQee+wxAKZNm8aOHTuYNWvWFYuK119/nQEDBlzRMdeCeiUqRowYwVtvvUXjxo1p0aIF+/btY/bs2Tz44IM3umsNNHDTk2yy8MTRFHaXyMHYYwO9eadpI1wwcuzYi2Rk/gaAi0s0LeJm4eHRqtptGwwG1qxZw/79+wHQ6/UMGDCAtm3bOm/a1kwDxUvPVIybGByBS7uAWh2Yl+TlsnfFXxxctwqbWZ6JdPP1I37YKFr1HYhGf+mU2XlpZRzbmsGJXVlYDOfcm0JivIjrHkxU+wDU1yCDy41Ep5MHxHU1VuBGY7HIgsu1ikLRrq7ydoul7r5vgkKgxS2hRLX1Z/uiMxzblsmxrZkkH8qnz73NiWh9aZFdG0iCngGPvohH8AL2LvmZ3UsWUpiZztCnnq339SyuBEGjBIeEo8CM4O9yTSYm1GezLxQVFVVI1V3O+Ul6WrVqRevWrWnSpAkbNmygX79+DBkyhM2bNwOyu8+RI0cYNWoUjz/+OIsWLeLOO+9k/vz59OnTh4iICAAOHDjA+vXrcXO72Gp75swZmjZtyqlTp5gxYwY7d+4kLy/POamckpJSQVScbw05n3JrRbnjv8NhrnS/co4dO0bXrl0rxLB0796dsrIy0tLSaNy4MYCzblt5bIVPYCAZ2dmXbfuhhx6qsK579+589NFHlzyuMqq63utNvRIVH3/8Ma+88gqPPfYYOTk5hISE8PDDDzNjxowb3bUGGrip+TO7kOfPBmO7lwdjB/lQWLSbnUenYzanAQKNwx4kKmpahaqll0IURfbt28fatWsxmeQBfPv27enXrx+uZ0dgDoONklVJ1zxuIjcliX+XLOT4tk2IDtmlyq9xBB1HjKFZt55VxksAWM12Tu3O5sjmjAr1JFy9tDTvGkTzrsF4BVyb+j11ibo6IL7R3ExZsvTuGvqOjyW2WzDrfzxOYZaR5Z8dpHmXIHrcHoP2Mi45NaFiLIqCkPi7UbhGsOvXuZzevYM/336Vkc++jM71+rkQ6lV6dt6987qd73x0ghZ7jgnJJuIotlTp8unn54dSqST7gsFtdnZ2hRnzCwkKCqK0tBRBELDb7ZSVlV32mKioKPz8/Dh9+jT9+vXjm2++cd7TywWKRqNh/PjxzJs3jzFjxvDzzz9XGECXlZUxYsQI3nvvvYvaL7dWjxgxgvDwcL7++mtCQkIQRZGWLVtitVor7O9alYIHVCpXmjWTLRSHD++gd+/RVe5bXcqvUa9U4KlWgiBgtNsvc9SlKZ9QOz/02WazVbrvpa73enJNRIVCoaB379588MEHdOjQodbadXd3Z+7cucydO7fW2myggQaq5sLK2B09XPkkrjFhWoHTZz4gOflLQEKna0Rc7Pt4e1ffHSAnJ4elS5eSmpoKyCb54cOHExYmZ4eSHBKGXZkUr0p21puo7biJ8mJ1u//6g8T9e5zrw1q0puOtY4lo0/6SWVby08s4vCmdEzuzsJllIaJQCkS29iO2ewhhcT4o6rl7UwNXz82YJSs42ovbX+rIriWJ7FubwvEdWaQeL6TPfc0Jb1G5X31NqCoWxS+mG13u92H3T2+Qduwwv818gTH/eR037+sTxCMIAi7qGzdRoPLRYc8zIRpsOLSVx1doNBo6dOjAunXrnKlMRVFk3bp1PPHEE1W23bVrV9avX88jjzzirLa9evVqunbtWuUxaWlp5OfnOwf/oaGVFyycNGkSLVu25LPPPnMWTy6nffv2LFy4kIiIiEqzF+Xn53PixAm+/vprbrnlFgC2bNlSZZ8uxdChY/H1fZEPP/yEW24ZctFEWHmgdmxsLAsXLkSSJOezYOvWrbi7u9OoUaNK2w7UyJ+FVZSwiCJahQK1Wo3j7GRVObGxsWzdurVCTPDWrVuJi4sDcFqIMjMzadeuHYDTml9XuSai4ttvvyUpKYnHH3+cHTt2XItTNNBAA9eYA6VGHj2STILJggKYFhHE1PBAzKbT/PvvM5SWyQUug4PG0rTpK6hU7tVq12azsW7dFrZu3Y4kOdDr1fTt25dOnTo5fXEticUU/XUGW5bsaqUOdsXr1iZoI2snbkKSJJIO7GXHn7+ScULOLiUICmI6d6PjiDEERVedn9xuc3Bmby5HNqWTeabYud4zQE+LW0Jp3iUIvXvdTQPbwPVHq5WzPBUWVi4qDAY51qK+WXpUaiXdxkYT2dafdd8dpTjHxLKPD9CmfxhdRzVBqbp6lXSpWBRoTv8n3mbbty+Tm5LEL688y20vvY538I2vwH2tUehUKNw1iKVWHEUWFBolQiXv97Rp07j//vuJj4+nU6dOzJ07F4PBwAMPPODcZ/z48YSEhPL22+8AMGXKFHr16sVnn31Gjx49+P3339mzZw9fffUVIFsUXnvtNcaOHUtQUBBnzpzhueeeIzo6mkGDBl2y37GxsXTp0oXnn3+eBx98EL1e79z2+OOP8/XXX3PXXXfx3HPP4ePjw+nTp1mwYAHffPMN3t7e+Pr68tVXXxEcHExKSspFGayqi4eHH5999h733vsYt946gqeffp7o6Gjy8vL47bffSElJYcGCBTz22GPMnTuXJ598kieeeIITJ07w6quvMm3atItifMvRKxWozs4l5VrtNNJpiIiIYN26dXTv3h2tVou3tzfPPvsst99+O+3ataN///4sXbqUP//8k7Vr18rt6PV06dKFd999l8jISHJycnj55ZdrdL3XixqLipSUFMLCwi6axZMkib59+9K4ceMKkfENNNBA/UCUJL5Oy+XNM5nYJMlZGbuzpytpad9z+sx7iKIFlcqL2OZvERAwuNptHz+exO+/ryU724QoehAV1Zhhw3oRGemJUgmOYgtFKxMx7ZdTWAp6FZ6DwnHtFFwrfsOSKHJ6z052/vkr2QlyVW6lWk3L3v2JHz4Gr6DgKo8tzjVyZFMGx7ZlYjbIJmhBIRDVxo8WvUJp1NT7qvrYEI9wc3MzZ8kKbuLJHS93YseiMxxcn8aBtalknipi4KSWePrrL99AFVQnFsWiCmf0Sx+w7MNXKMrKZMGrzzPulbfwCwuv8XnrC0oPDZLFgWR1YC+svH7FHXfcQW5uLjNmzCArK4u2bdvy999/O4O3RRGSk1OQJAUWi1yYLz6+Gz/++DMzZrzMSy+9RGRkJP/973+JioqSz6tUcvDgQb777juKiooICQlh4MCBvPHGG9XKtjlx4kS2bdt2UTxsSEgIW7du5fnnn2fgwIFYLBbCw8MZPHgwCoUCQRBYsGABTz31FC1btqRZs2b83//9X43SpwKMHXsvAQHuzJ79DXfffbez5EB5JiuQLS4rVqzg2WefpU2bNvj4+DBx4sTLDu61ZwVHgc1OkEbNhx9+yLRp0/j6668JDQ0lKSmJUaNG8dFHHzFr1iymTJlCZGQk8+bNq3A93377LRMnTqRDhw40a9aM999/n4EDB9boeq8HNa5ToVQqyczMrFA8BWTzVEBAwEVmnrpCdXPtNtDA/yK5VhtTjqXwT4EcFzDUz5MPm4fhIuZz9NjzFBTIgXc+PrcQF/seWm3gpZpzYjQaWbZsLVu2JGK3q/DyUjFgQB8iImIwGgW0KhHP5HSsW1KQrCII4NopCI+BEShrIbOMKDo4uWMrOxf9Rl5KEgAqrZY2/YcQP3w0bj6Vu2tIokTKsQIO/pNKypEC53o3by1xPUKI6x6Cq9fVKYD6VrugukiShLnMhsNkQbBZ0GBBtFjBcdbPuHzwIwhn/xZQ6LQIej0KrRZBp0OoT/5A1eBm/azPJ/FALuu+O4bFaEejU9LnvliiO9SsWJ3JBImJ4Ol57utyPpIkV6WPjATRUsjCd14lNykBF0+vWhcWN7pORVWcX79C6alFeQVWUlEEq1V+HxUK+T2WpHNVvzUaeX1ZWRklJSUIgkBAQECV2Z2qyxtvvMHvv//OwYMHr6qd2sBoTMZuL0Gt9kSvb1xr7UqSxCmjBZNDJFCrJkh77TOkXS03tE7F+f5l51OegqyBBhqoX2wqKOWJY8nkWO3oFAKvRYcyPsSX3NzV7Dj+H+z2IhQKLdHRL9Ao9L5qVXSVJImDBw+yatUqsrIU2O16Onduyi233HKu5kRqIalL0ikylRHkLqJp7I7XyGg0oVcfdOmw2zm+dSM7F/3mrDGh0etpN3gE7YeOxMWjcncqq9nOiR1ZHFyfRlG2UV4pQOM4H1r2DCW8pW+tFP+qL7ULJKsVe16evOTmnl3ycBQV4SgpQSwpweFcijEVWyk06jA69DhQosSBi8KIl7IYrcJ6+ROeRdBqUeh0KNzdUXp5ofT2RunthdLLC5W3N0ofX9QhwaiDg1EFBaN0qxvBilXxv5AlK7KNP3e87M7qb46QlVDMqq8Pk3UmjG5jm1zxb+ZKYlH0Xt6Me+Ut/njjZXKSzvD7Gy/9T1gsFGolSk8NjiILjhILgk55yTSz52O3yyLifI0gCPL/Doe8XaORg4CNRiN2u53S0lJnDYcrpaysjKSkJD755BOnJeBGo9UGYLeXYLMVo9GYq51k5HIIgoC/RkWKyUqe1U6ARoWimlXQ6zNXbKmYNm0aAB999BGTJ0/GxeVcoFJ50SqlUsnWrVtrt6e1RIOlooEGKmITJd5PzOSTlBwkoJmrji/iwonR2Tl58g0ysxYC4O7WgrgWH+LmGlOtdgsKCli2bBkJCQnY7UoUiigGD+5NRITs72wvMFGyLhXzyUJsDgGbVkPLO4Px7nz1KWLtNhtHNqxl119/UJIrZz7RubrRfuhI2g0ega6SlIUAxbkmDm1M49jWTGe1a41OSWy3EFr1CcXTv3YDM+tKNWrRYMCano4tLR1bejq2tDRsGelY09KxZ2biKCqqdlsWUUO2PRCrpEavMKHCjh0VZrU3Go1EsEshWsEi7yxJlOd2lEQRyWJBslZfdFyIwsMDdXAw6pAQNJGRaKMi0UQ1QdskCqXn9SnU1oCMwyGya0kie1fJlYTDYr0ZOKnlFde0uNLfiKms1CksatNiUVctFSBP3tjzzUhmO4JGicr/YjeoCym3UjgNhRe1KS/l1gqLxUJ+fj4gZ5XSVKbyLsOECRP45ZdfGDVqFD///PNVWzxqi3PWCi/0+rBaa1eSJA6WmUACF6WCGNe69b25kNqwVFyxqCgvyLFx40a6du1a4Yul0cjBKNOnTycmpnoDj+tNg6hooIFzJJssPHo0mb0l8mz8+BBfZkaHYi3dy5Gj0zGbUwGB8PBHiIp8CoXi8g8Sh8PBtm3b2LhxI3a7HaVSSdeufQkM7IyPjwrJ5qBsewZlOzLBLoFCwKVDIGKbUJo0V6GvuQs2DruNw+vXsGPRb5Tl5wHg4ulFh2GjaDtwaKU1JiRJIv1kEQf/SSXxYJ6zSJ1ngJ7WfcJo3jUIja72c1pYLJCUJM9UV/Z8tlrlfSIiamc2WxJF7FlZWBISsSYkYElMwJqYhDUhAfvZYoOXRK1G5eeHyt9fXvz8UPp4o3T3QOnpIVsTPDzJNntRYnfHJ1CLoNUiaDQIajWCIFRLKEkOB5LFgmg2I5lMiCYTjtJSHIVFsmWksBBHUSGOoiLsObnYsrKwZWUhFhdX3Sig9PVF26QJuthYdC1bomvZAk14+E3nYlXXOLM3h7Xzj2K3inj46xn6aCt8Q6pvhazKmlcei1KZNe9CYXHHzPfwCbm64O26LCoAJLuILdtYbTcoUZTvL5ca1zsc8r2n/CdSWFiIyWRCrVbj5+dXLWt1fcDuMGI0nAEE3NyaXVHB1stxvMyERZQfKq3dLy/2biQ3RFSU88ADD/DRRx/Vu4F5g6hooAGZxdmFPHu29oSnSsmHzcIY6udKYuL/kZT8BSCi04USF/ch3l4dq9VmamoqS5cudVbEjoyMZPjw4bi5+ZKUBGJKAeb1yTiK5dlobaQHHgPCkTxdrmoA7bDbObJxLTv+/JXSPDnI283bh44jb6NV34GotRcPAuw2Byd3ZXPwn1Ty0w3O9Y3jfGjdN4zGcT7XtNr1lfiLX6nQEo1GLCdPYj5+AvPxY1iOn8B88iSS0VjlMQpPTzShoahDQ1E3anT2NRR1cAiqAH+Unp6XHYBfb6F0Po4yA/asTGyZmdjS0mTxdOYMloQE7OdVAj4fhZsburg4dK1a4tIhHpf4Digbngu1Tl5aGSs+P0hpvhm1VsnASS2IaFX9Ynk1iUU5X1h4+Adw1+sfVBk7Vb0+1G1RAeAokzNBIQioA10qzQZVzpVaKkCeMMrJyUGSJLy8vCp4qtR3DIYEHA4DGo0fOl3VCTuuFJsocrRMLrAX5aLFXVU3rDOVcUNFRX2lQVQ08L+OweHgpZPpLMiSA487ebryWVw43o5UjhydRmnpYQCCgkbTrOmr1UoVazabWbduHbt37wbkVHiDBw+mdevWcgGlAjPHv08i+1AZnjoHSg8NHv3D0TX3rvYMdmWIDgdHN/3Djj8XUJwjuzm5evvQedQ4WvUdhKqSka3ZYOPwxnQOrk/FVCpncVJpFDTvGkyr3o3wCb4+fvm1NQB3lBkwHz6E6eAhzMeOYjl+AmtSktOtqAJqNZrGjWW3oMiocy5CkZG1Mpi+lkLpanCUGbAmJmI5dQrz0aOYDx/GfOwYksVScUeFAl1sLC6dOuHSqSMu8fEo3auXKrmBS2Mqs7Lqq8OknyxCUAj0vqcZcd2v7Ad/pbEoxuIiFrz6HIWZGfg1juCOme/WuEBefRAVkiRhzzMhWRwIWmWl2aDOx2o9J9IupHz9hfem0tJSSktLUSgUBAQEVJlWtb5hs5VgMiUjCArc3JojCLU3+E8zW8m32vFUKYlwqbtBVDdcVKxbt45169aRk5PjLJVezrffflvTZq8pDaKigf9lDpcaeeRoMqeNcu2JqRGBPN04kOzMnzl1+h1E0YxK5Unz5m8RGDCkWm2eOHGCZcuWUVoqZ4xq06YNAwcOxNXVFckuUro5ndJ/UjCZJLIMWlRtgwnoE4zWVXlZN4aqEB0Ojm3ZwI6FCyjKzgRkN6dOI8fResBg1JqLb9wleSYOrEvl6LZM7BY5O52bt5bWfcOI6x58TSoBX44r9ReXHA4sp89gOngA04EDmA8cxHL6dKUCQunvh65Zc3SxzdE2a46ueTM0EREIl6gMfrXcSEvFlSLZbFgSEjAfPoxp/36Mu3ZjTU6uuJNSib5dW9x798atVy800dF12n2hruNwiGz48TjHt8uWo04jIokfGnFN39PinCx+eeVZDEWFhDZvwdiXXq/0/nA56oOoAJBsIracs25Q3rpLZs+rbvaniseIzjGfu7s77nVYdJ8/LL2c9pEkCYPhFKJoQasNQqv1r7V+mBwiJw2ytSLWTYemjgqxGyoqXnvtNV5//XXi4+MJDg6+6KawaNGimjR7zWkQFQ38LyJJEv9Nz+P10xlYJYlgrZpPY8Pp4GLi2PHnyc/fCICPdw9i495Dpw26bJsGg4GVK1dy+LBs2fDx8WH48OHOXObmM0UULT6NPdcEgDbKE92gJpSqXWucUlMUHZzYtpntf/zizOak9/Ck061jaTNwaKVuTrkppexbnczpvblIZ31bfRu50W5AY6LjA1DWQhanmnI5f3EfNzOOYwcx7/0Xx8HdmA8eRKzEhUkdEoKuTWv0LVo4BYTKv/YeildCXQk+rwm27ByMu3dj3LUL486dF4kMdUgIbv374TF4CPq2bRriMWqAJEnsXJLAnpXye9uiZyg972x6TSvP5yQl8OvMF7CajER37MKIaS+iUFzZTHR9ERUAjlIrjmILKATUQa6XdOMURTnLkyjKgkIQ5AG4SlX1QNxoNFJUVFRrKWZrm5pcE4DVmo/ZnAGAu3tcrVorThvNGOwiAVoVwdq6WRz1hoqK4OBg3n//fe67776aHH7DaBAVDfyvkW+1M/V4CmvySwAY7OfB7OaNEYs3cfTY89hsBSgUGqKbPE+jRuMRhEsPlCRJ4tChQ6xcuRKTyYQgCHTr1o3evXujVqtxlFopXp6A8WwBO4WbGs9hUbi09XdOPlypG4MkipzatY2tv/1EQXoqADo3dzreOpa2g4ah0VX0pZEkiZSjBexbnUL6iULn+rBYb9oNCKdRrHedmXE+31/cVmbCevIo9iP7MR88iOFYAna7WCElq95Nha5VK/Rt2qBv0xp969Y3TEBURk0Ca+sq1rR0yjZuoGzjRow7dlbITKUKCsJj0CA8hg5Bd9bNr4Hqc2hDGpt+PQkSNGkfwICJcddU4KcePcTCt2fgsNmIHzGGXvc+ePmDzqM+iQpJkrBnG5HsIgo3NSqvy/f3Smf1c3NzsdvtuLq64lmHMqvVxPpSjiQ5KC09CoBS5YqrS1St9avIZifZZEUlCMS66epketkbKip8fX3ZtWsXTZo0qcnhN4wGUdHAzc75A/bdxlIeP5pMttWOViHwapMQxge5cebMe6Sl/wCAm1ssLeJm4+bW9LJtFxcXs2zZMk6dOgVAYGAgt956K6GhoUiihGFnJsWrkpDMDrmAXedgPAdFYFOoapSXX5Ikkg/uY8uC750VsHWubsSPGEO7wcMvyuYkOkRO/ZvDvtXJzuBrQSEQEx9A2wGN8Q+rW6Z6yWbDdPAghq1bKdi8G+ORY9isUCj6OFOyan29ULduj9isPZ5tmhPVPRy9a92aGbyQm7HIm2g0Yti+nZJVqyhb9w+i4VxwvyYqCq+xY/C89dY6JfDqOqf35LBm3hFEu0RUW38GTmqB8hLBxVfL8W2bWP7R+wAMeXwacT37VvvY+iQqAESzHXuebCVWBbig0NTuPcNsNlNQIMflBQQEoLqGbpVXQk3iRM6nrOw4omhDodDg6tq01iYLREnimMGMXZRorNfgra4b79f53FBR8fzzz+Pm5sYrr7xSk8NvGA2iooGblfMHclabxPzMXL4vykHh4aCpl4YvW0QQRjJHjkzFYJBFQVjYg0Q3mY5CcemRviiK7NmzhzVr1mC1WlEqlfTq1Yvu3bujVCqxppVSuOg0tvQyANShbniPikb0d6/x4DLj5HG2/PIdqUcPyW3q9HQYNor44aPQulQMpnbYRI5tz2Tf6mRK8mTfVbVWSVyPENr0C8Pdp+4MAqzJyZRt3Yph6zaMO3ZUGJwC5Pu2wNasC0FdmqNv2xZ1aKjzwVbX3Ycu5GYt8iZaLBg2b6ZkxUpK//kHySx/51AqcevZE++77sS1R48G96hqkHQoj5VfHkK0S0S28WPQ5JbXVFhsWfADOxf9ilKt5o5X3yU4plm1jqtvogLAnm9CNFW/dsWVkpeXh9VqxcXFpcYF8WqTmmS0urgNO2WG4yBJuLg0QaWqvQxXWRYb2RYbrioF0S517zt03UVFeeE7kAcZ3333Ha1bt6Z169ao1RWDgWbPnl3dZq8rDaKigZuR811ODCorLyemsbfQhGRWMDLUgw+6BWIs/JHTZ95DFK1oNH7ExX6Ar2/Py7adl5fH0qVLST7rX96oUSNGjhyJv78/oslO8aokDDszQQJBp8RzUASunYOxWIUaucHkpSSx5dcfOPPvTgCUKhVtBg6j8+jbL6qAbbM4OLI5nf1rUjCcTVOrd1fTum8YrXqF3pDg6wsRTSYM23dQtmkjhq3bsKWmVtiu9PLCtVs3XLt3Q9m2Cxn20HoR6NyAjKO0lJKVKyn+cxGm/fud6zXh4Xjfczeeo0c3ZJC6DMlH8ln5+SEcdpGIVr4MfqgVSvW1ERaSKPLXh29z5t8duHp5c8/bc3D3vXx62/ooKsprV3w+70vmfP0xWdlZtGnTho8//phOnTpVedyRI0eYMWMGe/bsITk5mTlz5jB16tSL9ju/IF5dsFZcWHujpKSEWbPeY9GihSQnJ+Hl5UVcXEsee+wxxo4dXaXIMplSsdmKUKu90esbXfa8EyZMoKioiMWLF19yP6socuxsetnmbjq0dWzSoTZExRV9A/bt21fh/7Zt2wI4AzXLafAtbaCB60tBgTx4PySV8sqxNIpsDty0CmbEBdNOktiz/VmUyiUA+Pn2JTb2XTSaS+dsdzgcbN++nQ0bNmC321Gr1fTv35+OHTsiCAKGfTkUL09ALJPTsrq0C8BzaKSz6FJ5n84P2NVo5KWwUN5+/ox7cU4W2377iaNbNoAkIQgKWvTuR9fb7sLDL6BC38wGG4c2pHHwnzTMBvn8bt5a2g5oTFyPENS1bOq/UmzZOZRt2EDZ+vUYtm+vmLpUrcalXTtcu3fHtXt3dHGxzhltkwkcibIAqwy1GozGiv7P1wpREjHajJRaSzE7zFgdVmyiDZtow+qwYnXIIk4QBBQoEATB+bdGqUGv0jsXnUqHXqVHpah7Jv+rRenujvftt+N9++1YEhIo+vU3iv78E2tyMtlvv0Pu3I/wGncbPg88gDro8gkQ/hcJb+HLsMdas/zzgyQdymf1t0cYNLnlNQneFhQKhj4xjV9eeZa81GSWfPgWd77+PkrVjZ+AqG0ElYI/Vi/muTf+w6fvfUTXAbfw0UcfMWjQIE6cOEFAQEClxxmNRqKiohg3bhxPP/10le1rtVo0Gg1Wq5WysrIbYq2wWq0VijCXx1AUFxfRp08PSkqKmTnzTeLjO6JUqti0aSMvvPAc/fv3rbK/arUPNlsRNnsRWjH4ioP6q0KjUOCmUlBmFym02QmqQcD2hddb12ioU9FAA/WUctcSmw1S0iW+yc7ip1x51ijWVcf7zcJwM/3LkaPvYTQaCQnJJS5uOo1C772s8M/KyuKvv/4iM1NO1xoVFcWIESPw9vbGnmeicPFpLKeLAFD56/EaFY2uiVeFvlU3tajdVMiOPxdwcO0qRIcdgKadu9PtjnvxDQ2rcJyxxMqBdSkc2piOzSynhfXw19NhUDjNugRdU7eJSyFJEuajRylbLwsJ85EjFbarQoLR9OiHvlsP3DrG4+JbeS2Ma5mS1eawkW/OJ9eYS54pj1xTLvmmfOdribWEUmupvNhKKbOWIVG7jwc3tRteWi950cmvPjofglyDCHYNJsg1iCDXIHx0PigukzCgLiMaDBQvXUrBDz9iPXNGXqlW4zVqJL4TJ6KJiLih/aurpB4rYNmnBxDtEnHdg+l9b/NrNklZnJPFjy8+jbmslA7DRtJ7/ORL7l8fLRUAnTt3pn1cWz56YxZKLy2Ci4qwsDCefPJJXnjhhcseHxERwdSpUyu1VIA8yM3Ly2PcuHG0adOGzz77zLktNzeX0NBQVq5cSb9+/bBYLLz00kv88ssvFBUV0bJlS9577z169+4NQH5+Pk888QSbNm2isLCQJk2a8J///Ie77rrL2Wbv3r1p2bIlKpWKH3/8kVatWrF+/frz+iO72k6d+hg//fQ9hw+fJOTs7FW5C67VWoZOp0OlUlFYWMiUKVNYunQpFouFXr168dFHHxESAqJo4bffNjB9+iv8+uuvTJ06ldTUVHr06MG8efMIDg5m5syZvPbaaxXek/Xr19O7d28OHTrElClT2L59Oy4uLowdO5ZX3nufAqUGtULgseFDaNu2LXPnznUeO2rUKLy8vJg/f77z/Z84cSKnTp1i8eLFjBkzxrmttrnulooGGmjgxnNhEGxqqYUZ+7M47VqGQgt3B/vwVJg36SmfcCTzDyQJ9LrWtG/3Of7+MZds22azsWnTJrZu3Yooiuh0OgYPHkybNm1AlChZn0rJuhSwi6BS4NEvDPdbGl1UuVUU5b5dasa9KN/Ill8XcXjtn9jPzuSHt25HjzvHE9SkYj8NxRb2rkrmyOYMHDZ5mt4nxJUOQ8KJbh+A4gakhZVEEdP+A5SuXk3p6tXYMjLObRQE9K1b49anN6pufTH4xlBWJmBwQGEeuFsqjyvRauWYk8LCykWFwSBbfioTFA7RQbYxm/SydNJK0+TXsjTSS9NJL0sn15Rbo+tUKVToVXo0Cg1qpRqNQoNGqUGlUCEgD/hESURCkl8lCYvDgsluwuwwY7KbECX5MyuzlVFmKyOtLO2S51Qr1DRyb0SERwSRnpHO10jPSDy1dSfTTFUoXF3xvvNOvO64A8OWreR/9RXG3bsp+v0Pihb+icewYfg/9SSasLDLN/Y/RFisDwMntmDVV4c5ujUTnZuGrqOvTTIYz4AgBj82lT/eeYcdf63EP7oNLbpV7RJ0IZIkIZlM16Rvl0PQVy8+wmq1smfPHp6fOh0AR4kVtYtscd6+fXut9EWj0aDVarn77rt5+eWXmTNnDtqzN6gff/yR0NBQ+vaVA+KfeOIJjh49yoIFCwgJCWHRokUMHjyYQ4cOERMTg9lspkOHDjz//PN4eHiwfPly7rvvPpo0aVLBXeu7777j0UcfZevWrRf1R6UCu13k998XcOed9xASElIh+5NKBRrNuQKIEyZM4NSpUyxZsgQPDw+ef/55hg0bxv79mwALdrsBo9HIrFmz+OGHH1AoFNx7771Mnz6dn376ienTp3Ps2DFKSkqYN28eIKdXNxgMDBo0iK5du7J7925ycnKYNGkSlqenMv3jz7CJEo5qzunPmjWLGTNm8Oqrr9b0Y7pu1FhUnB9fcT6CIKDT6YiOjmbkyJH4+PjUuHMNNNBARS5M17mxpJhXjmVSlKXG3U3LG738ucUzl2OHnsNglGdIA/zvJCjoETw8Lj21nZKSwpIlS8jLywMgLi6OIUOG4O7ujiW5hMI/T2HPlmskaKO98B4djcq38rLICoU8I2SzXTw4dthtHFi3np3LV+HGGVRKO8HRzehx1/00btm6wr6ViYmACA/ih4QT0crvkvnXrwWSw4Fp715KVslCwp6T49wm6PW49eiOW+8+uPXqicrP79znVVQxrqSwUHZ1qiyuxMdH3lZYWHksipunlVOFySQUJ5BQlCC/FieQVJyEVbRyKVSCCl+9L/56f/z0fvi5+MmvOj88dZ64q91x17jjpnHDQ+OBu8YdrfLqgjckScIm2jDYDBRbiimyFFFkKaLQXEiRpYg8Ux5ZhiyyjFlkGbLIM+VhE20kFieSWJzI+tT1FdoLdQsl1ieWON84Yn1jifWJxVd/aVe+K6E2g8sFQcDtlh643dID49695H/5FWUbN1KydCklK1fiffs4/B59tCFj1Hk0aRdA73uas/7H4+xdlYzOTU27AY1r/TxmM+iDOxPc8S4OrV/Pglm/cO9rkYTH+FcrQ5lkMnGifYda71d1aLZ3D4LL5QOI8/LycDgcBIWHIqgUSHYRR6mVwMBAjh8/Xmv9cXNzY8iQIbz88sssWrSIO++8E4D58+czYcIEBEEgJSWFefPmkZKS4rQcTJ8+nb///pt58+bx9ttvExoayvTp053tPvnkk6xatYrffvutgqiIiYnh/fffr7QvCgWUlORRWFhI06bNcThkMaFUXlynolxMbN26lW7dugHw008/ERYWxrJlmxgytAWSZMdms/HFF184s50+8cQTvP76685r1+v1WCwWgs5zb/zuu+8wm818//33uLrKlulPPvmEESNGMPW1N1B4+2Kvpqjo27cvzzzzTLX2vdHUWFTs27ePvXv34nA4aNZMzp5w8uRJlEolzZs357PPPuOZZ55hy5YtxMXF1VqHG2jgf5nyOAW9h8j7J7NYcLoEyaSgiU7LWKU/qmMb2K36AKXSgFrtTdOYlxGEbnh5VT1AslqtrFu3jp075cBoNzc3hg4dSlxcHKLZTuHi085AbIWrCs/hTSrUnKiMymbcJUnizJ7d7F78G1kZBvRqAwExwfS4azzR8V0qtFeZmAiK8qTT8MjrXmNCstsx7t5NyapVlK5Zi+NsYCLIM9JuffviPnAAbj16oNBXFFlXGlcC54LYCwogNbeQUwUJJJWeIdV6jFTHATIsCTgkR6V9VSlUhLiG0Mi9EaFuofLiHkojt0aEuIXgpfW67m5FgiCgUcrWDW9dJRXxLsAm2sgx5pBSkkJicSJJJUnO1yxDFullsuVlbcpa5zGN3BrRIbCDcwlzD7vi78i1ToPr0r49Ll9+genwEXLnzMGwdSuFP/9C0aLF+D74IL6TJl70/flfJa5HCKYyKzsWJ7Bt4Wk8/HQ0aVe5/39NOH9ypvvYMRSnHSMrMZm/Pp3HqKen0ThcVW9TH1eGIAgoPTXY882IZTZnEdCa8tNPP/Hwww87/1+5ciWxsbGMHTuWb775hjvvvJO9e/dy+PBhliyRY/kOHTqEw+GgadOKqcstFgu+vvKkgMPh4O233+a3334jPT0dq9WKxWLB5QIB1aHDpcWcIMjXp1Kde+5VFhN97NgxVCoVnTt3dq7z9fWlWbNmnDhxgltv7Q6Ai4u+QvmE4OBgcs6bUKqMY8eO0aZNG6egAOjevbtckTzhNEEdfLFL8nPxcsTHx192n7pCjUVFuRVi3rx5Tv+q4uJiJk2aRI8ePZg8eTJ33303Tz/9NKtWraq1DjfQwP8qFos84MlXWHhxTxrHUu1INiXjwj2501fFzh3/5d/d6YQ2CiQuLoSmTV/EbvORKzNXYTBMTk5m8eLFFBbKBeLatm3LoEGD0Ol0GA/lUbTkDGKpPPvt0iFQDsR2rV5A4/kz7iVZJ9izeAGZiUlY7TrcvfQMGT+aDoP6oTgvobih2MK+VSkc3pxeUUyMiKRR8+snJiRJwnzgAMXLllOycmVFIeHhgXu/frgPHIBr9+4oqgiaK/+8XCsPn8DVVd5uscgPvnxTPofyDnEo7xDHC45zPP84WSWFIClAEFGobc5j3dRuRHlGEeUVJb+e/TvENQRlLQUV3ijUCrVTEHUN6VphW4m1hBMFJziaf9S5JJckk1aWRlpZGn+d+QsAf70/HYM6ckujW+ge0v2yYqaqgn2XsijVFH3LFjT+7zcYduwkZ85szAcOkvfppxQt+pPA557HfdDAhmQnQPtB4RiKrRxan8baeUfx8NXj37h2smhVFPtqBkx+jIVvzaAs4zC7V67C7fZhl03bLOj1NNu7p1b6c6UI1RSffn5+KJVKsrOzEXQqBLUCySaSlZ5ZYVb9Srn11lsrDMRDQ0MBuOuuuxg4cKDTKtG3b1/Cw8MBKCsrQ6lUsmfPnosqcLu5ye5IH3zwAR999BFz586lVatWuLq6MnXqVKzWihZY16puqmfx9/fHy8uLEyeOX7aQ36VQq73PvqqQJIezwrYgCNUSA1WhUyjQKuTEFuYLsm7YbLaL9r/c9dYlaiwqPvjgA9asWVMhYMPT05OZM2cycOBApkyZwowZMxg4cGCtdLSBBv7XEUX4O7uYD3PTKctT4Cap+E/bIJpynMSEj3BxMeDtHYKX54O4ufYFScDbu/KZ1gutEx4eHowYMYKYmBjsRRbyfzuK+Zhc2EjldzYQO9qrWv08331EL6Sx4Zc/OLnnKKKkQKN1pceIvvS5YwgeXucejJWLCQ86DY+6rpYJS0ICxUuXUrJseYXUr0ovL9wHDMB94EBcO3dCqEb2jUvFldhEGwmlCexJOklW6k6OFu+pNM5AqRYI9winuU9z5xLjHYO//tKWopsVD40HHYM60jGoo3NdmbWM/bn72ZO9hz3ZeziUd4hcUy4rElewInEFAgKt/FvRI7QHvRv1prnPxcG/NbEoXS2uXToTsWABpatWkf3++9gzMkmfOhWXzp0JenUG2qjaq+ZbHxEEgR63RVOUbST1aAErPj/IbS/E4+p5dT5plYl9D78Aetx9P+v++znH/1lEZKtW+Po2vqT7myAI1XJBupFoNBo6dOjAunXrGDVqFEoPDdZcI+s3rOfxJ5+ocbvu7u64X5AmWZIkWrVqRZs2bfj000/5+eef+eSTT5zb27Vrh8PhICcnh1tuuaXSdrdu3crIkSO59957Abl0wcmTJ6/Y20WhUHDnnXfyww8/8OqrrzrdrcopK5MDtWNjY7Hb7ezcudPp/pSfn8+JEyeIi4tDqXRxCgmbvQSNuvLJCY1Gg8NR0XocGxvL/PnzMRgMTlGwdetWFAoFzZs3R1Ir8fbzJy0j03mMw+Hg8OHD9OnT54quty5RY1FRXFxMTk7ORR92bm4uJSUlAHh5eV2kMBtooIErx+gQeeFUGj8lloEALVSuPNfcF3vhT5zIks3Lrq4RxDZ/huDgCEQRgoOhsiQNF1on2rdvz8CBA9FqtJRuSadkdTKS1QFKAfdejfDo0xihGjnjz3cfKS0q5tCaZSTtXo1eXYKvm0BcrwF0ve0OfIPOmU0MxRb2rU7h8KZzYiIw0oNOIyIJi/W5LgNnW3Y2JctXULxsKZajx5zrBRcX3Pv1w3PEcFy7dkWoKuq8Cs6PK3EoTBzLP8aB3APsST/MqYLTmG02QIHGL8NphWji2YRW/q2I9Ykl1jeWZt7NcFHX7YHLjcZN40aP0B70CO0BgNlu5lDeIbamb2Vz+mZOFp7kYO5BDuYe5LP9n9HYvTGDIgYxOHIwMV4xWK3CFVmUahNBEPAYPBi3Xr3I/+a/5H/zDcadO0kcOQq/xx/Hd+KDV/y9u5lQKBUMmtSCP97bQ1G2kZVfHGLU0+1QXUXK6KrEfnR8FxL27CZh379s/Ol7Wnd6Hq22/r/306ZN4/777yc+Pp6OHTsy591ZGExGxo+7x7nP+PHjCQ0N5Z133gHkSaejR486/05PT2f//v24ubkRHR1d6XkEQUCr1XLXXXfx8ssv4+rqyujRo53bmzZtyj333MP48eP58MMPadeuHbm5uaxbt47WrVszbNgwYmJi+OOPP9i2bRve3t7Mnj2b7OzsGrnQv/XWW2zYsIHOnTvz1ltvER8fj1qtZvPmzbzzzjvs3r2bmJgYRo4cyeTJk/nyyy9xd3fnhRdeIDQ0lJEjR8puY0r5/mu3FVUpKiIiIli1ahUnTpzA19cXT09P7rnnHl599VXuv/9+Zs6cSW5uLk8++ST33XcfgYGBmB0inXr2YtZLL7Bk6TKaxkQze/ZsioqKrvha6xJX5f704IMP8uGHH9KxozxrtHv3bqZPn86oUaMA2LVr10X+cw000MCVcdxg4uEjyZwwmFG4qLhbF8BApZncpOcxmZIACAwchof7BHx8dPj4QHHxxQ/NyqwTt956K9HR0VjTy8hZdAxbmlwRWxPugfeYaNSB1TO7lruPlBWbObNzFYfXLcditmG1uxDYrAMjHxpFaPS5YEuzwca+1ckc/CcN+w0QE6LJROmaNRQtWoRxx045sTmASoVbjx54DB+Oe98+KGo4E2mymzhQcIC1SUfYnXiaM9Y9WC0CotEdh8UFRB+0Dh/iorzp3TqA+EYtaenXEg9NQ5rrq0Wn0jmtGVM7TCXLkMXW9K1sStvE1oytpJSm8PWhr/n60NdEeUbRP3gEbZSjaOJWeQG061EbRKHX4//kE3iOHk3W669h2LSZ3LlzKfn7b4LffBN9yxbX7uR1HK2LmmGPt+aPd/8lO7GEzb+dos+9zWvcXlVJJARBoOfd95N6/BRFmSnsXvIHfe65q+qG6gl33HEHubm5zJgxg6ysLNq2bsPSHxbi7+KDJEoICjmIWnGen1BGRgbt2rVz/j9r1ixmzZpFr1692LBhQ5Xncnd3Z9SoUbz66quMHTv2orSk8+bN48033+SZZ54hPT0dPz8/unTpwvDhwwF4+eWXSUhIYNCgQbi4uPDQQw8xatQoiouLr/i6fXx82LFjB++++y5vvvkmycnJeHt706pVKz744AM8PT2dfZoyZQrDhw/HarXSs2dPVqxY4Szo7BQV9jJE0YZCcbHQnDx5Mhs2bCA+Pp6ysjJnStlVq1YxZcoUOnbs6EwpW14YWqdUcMeE+zlx+BATJtyPWqXi6aefrtdWCriKOhVlZWU8/fTTfP/999jtcm55lUrF/fffz5w5c3B1dWX/2eqi5UXy6gINdSoaqC9IksQvWQW8dDINkygRoFExO7IxihMb2b59Ka6uBbi6amkc9jQaTTxaLQQFyQ/NC2sZJCUl8ddff11kndAo1JSsTaZsSzqIZytiD4nEtWPQFWVWSktzsHv1Dk6u/xVDcREA/o0j6TL2DlwC4vD2lt1HrGY7B9alsn9NCtazdSYCIz3oNDySsLhrKyYkScK0fz/Ffy6iZOVKxLIy5zZ9hw54jhiO+6BBqLwvH0x8IQ7RweH8w2xN38rOzJ0czDuIXbQjWjXYCgNwmFzxkEJp5hVLi4CmRLk3J9Q9GA8PAU/P2vXZb6BqjDYjG1I38HfS32xJ34JNtCHa1NjzG9G5UVtGNB1E5+DOFYr0Xe8q5pIkUbJsGdlvvY2jqAiUSvyffALfyZMRlPU7XuZqSD1WwJL/2w8S9H8gjmadax4TkJEhu7VV9lPfu34PuxZ8hJdbEfe8PYfASDlAt77WqbgQSZKw5xiRbCJKT62zWGltsW/fPuLj41m9ejX9+vWr1bZvFAbDGRwOI1ptEFpt7WVqy7bYyLLYcFcpiHK58d+p2qhTcdXF78rKykhISADkAlnlATd1lQZR0UB9oMzu4LmTafyZLYuA3t7uzInxIjfhFdLT15OcFIXF0o/Y2AfQ6bxxcwMvL3lgWv6wDAmRrRNr165l165dQEXrhPlUIYWLTuMoMAOgb+2H1/AmKD2u7CFzau8h/vxkESU5iSgVDtx9/ek06jaiO3RGUCiwWsFQ5sCQks6hf5Ixn63A7RvqRpeRUYS38r2mYsKWnUPxkr8oXrQY69l7FYC6USM8R4/Cc+QoNI1Cr7jdbEM22zK2sSV9Czsyd1BiLamwPcAlgE5BnWjj3RmPgs44ioNwdxdQKKjy82rg+lFqLWVdyjoWn17MjuPJOAweKF1L8dX5MjxqOLdG34q3zvuGfT72/Hyy3nyT0pV/A6CP70Doe++hDr3y7+rNws6lCfy7PAmVVsntL8bjHVSzANaqAvPL0zbvX/gBSXs2EhzdjLve+ABBobhpRAWAw2DDUWgGpYA6yLVW7r82m438/HyeeeYZTp48yV9//YW/v79zxr8+Y7XmYzZnoFDqcHO9dK2nK8HsEDlhMMsuza56VNc5RfpF/akLoqK+0SAqGqjrHCo18vCRZBJMFpQCvBAZzD0eqRw9OhWLJRNBUNMo9AVstvGYzQrc3ORB6vkPxdBQyMqqwjohKilanohxTzYASi8tXqOi0Te/spoyhVkZbPrxW45t30u+IQBPT+gw5FZa9BmA6uyDxOEQObU7mx0rM9BLpWhUIp4BejqPiCK6Q8A1qzMh2WyUrl9P0cKFGDZvcfquCHo9HgMH4jlmDC4d4xGuIDWIzWHj3+x/2Zq+la0ZWzlddLrCdneNO12Cu9AtpBudgzrTyL0RgiA4q2TDuTzp5894X++Z8AYu5nh2Et9vX8fq0xspJQuUdtS40CtgKOPiRtAlNuyGWJIkSaJkyRKyXn8D0WBA4e5O8Ftv4vE/mgBFFCWWfLSf9BOF+IS4ctsL8ahrGF9xqRTCdmM+86Y9gtVkYuDDT9Gq78CbSlRIkoQtywAOCaWHBuVlahhVhw0bNtCnTx+aNm3Kf//7X6KionBxccHLy+vqO3yDEUU7ZWXHAQlX16Yor7J2z/mcMJgxO0Qa6dT4am6sALvuomLatGm88cYbuLq6Vln8rpxyv7G6RoOoaKCuIkkS89LzmHk6A6skEapV81lcGP6F35GY+H+AiF4fTssWH+Hh0arKh6Kbm5UtWyq3TpgO51H412nEUhsI4NY1BI9BESi01X8wW4wGdvz5K3tXLEF02HFIGvzb3EaXW4fj6Sv/piRRIuFALvvWpFCYY8EuKggPk+g2MoLmXYNqVAG7OkXJbOnpFP7+O0ULF+LIzXOu17dvj9eY0bgPHoLSrfqzmyXWErakbWF96nq2pG+hzHbOZUohKGjp25Luod3pFtKNln4tK7jNlGMyQWIieHrKRZguRJLkGJjISGgoU3DjMJshO9fG6hPbWXTyL06VnECpM6ByLaVvk2480uYR4nxvTM0la2oqGdOfxXTgAAC+kybiP3UqgqrGYZH1FkOxhV/f2o2pxErLnqH0urvZVbVX1X1lz/LFbPj+G3TuHjw490sElfqmERUA9gIzolG2GqtD3WrVWmyxWMjPz0cQBAIDAyvEa9RXjMZE7PYytNpAtNraq5lyzgVKSZTLjZ1Vqg1RcUV3pH379jlz6O7bt6/K/f4XUx020MDVUGyzM+1EKstz5YC0QX4evBehJf3UIyQWyYHVQUGjaNb0NVQq2cVQp5NdMs5/KGZmJjFv3sXWCbVVQf4PRzEdkestqPz1eN/WFG149YW1KDo4tG41W3/7EVOJ3M/w1u3oPX4SVmU4hYWyMEo9WsDe1ckUZsnVtxVaHT0HB9NnTBAq9ZXPKl6uKJlkt1O2aROFCxbIVomz8yRKPz+8Ro/Gc8xotJGR1T5felk6G1I3sD51PXuy9mCX7M5tfno/eoT2oHtod7oGd8VT63nZ9i5VXRzk9Upl5cWZGrh+6HQQHqZmfEBP7ul2C/tz9/LLmfnO78L61PX0b9yfx9o+Rox37blAVAdNWBjhP/5Azuw5FMybR/43/8V0+Aihsz9EVVURmpsUV08tAx6IY8lH+zm8KZ2odv6Exdb8PahqgqLtoOEc+mc1+WkpbF3wAz3ufbDG56iLKD01TlEhltlqNbZCo9GgVCpxOByYzeaLitfVR1QqT+z2Muz2kloVFR4qJVkWG2UOBw5JQlnPx88N7k8NNHCD2Vdi5KEjSaSaragFgRlNQhipPcCx489jtxehVLrSrOlrBAePrrKNqmInmjRpgnFPNkXLEpHMdlAIuPeufprYcpIP7WfD99+Ql5IEgHdII3qPn0hk23i5gI8Z9mwuYtfKNEqyilEqJJQaNU06NqJVz0Aim9SsQu2lfJ+VJTm4bl+I+a9fsWdnO49x6doF7zvuxL1vn2rVkwA4XXia1cmrWZeyjpOFJytsi/aKpndYb/qE9aGlX8saVaS+VGBoQ0xF3SaxOJGvDn7F8oTlSEgICAyOHMwTbZ+gsUfjyzdQy5SsXEnGSy8jGY2oQ0II+/ILtDHXV+TUBTb+coLDG9Nx89Zy54zOaPW1b7VJPXqI3157EQSBO96YRaldvGksFQC2HCOS1YGgU6H2q10zaWlpKaWlpWg0Gvz8Ks+sVp8QRdtZFyhwc2uGQlE7IkySJI4ZzNhEiQi9Bk/1jbM+3vCYis2bN/Pll1+SkJDA77//TmhoKD/88AORkZH06NGjps1eUxpERQN1BUmS+G96Hq+dzsAmSYTrNHweG4JrzlzS0n4AwN29JS1bzMXFpeqZ9gvrTnTo0IEBAwagMkLhn6ewnC4CZBO399gYNCHVT6ZQmJnOxh+/5cy/srVE5+pG13F302bAUJRnXS/yM8rYsegMp/YVYjArsaMhplMwLW8Jxi9QXWnxvepy4WBcEkWMu3ZR9NcSsjYfwl0oJlCdi9LbG88xo/EeNw5NRMRl25UkidNFspBYnbSahOJzAdwKQUH7gPb0CetDn7A+hHmE1azz53G5wNCG7E91nzNFZ/h0/6esSV4DyJW/74u7j4daP4Sr+vpWvLWcOkXqE09gS05B4e5Oo4//D9cuXa5rH240VrOdX9/cRUmemebdguk3PvaanGf5/33A8a0bie56C00H3XpTiQrRJmLPNgDIAduq2jOXOhwOss9O9gQEBKC6CVz1DIYEHA4DWm0wWm3tCaU0s5V8qx0ftYowfe1m47oSbqioWLhwIffddx/33HMPP/zwA0ePHiUqKopPPvmEFStWsGLFipo0e81pEBUN1AVK7A6ePp7idHca5u/JW2EOkk9MpaxMLsDWOGwiTZpMr3JGxGazsX79erZt2wbI1omRI0cSFRlF2bYMSlYlIdlEUCnwHBCOW49QBGX1TKtmQxk7Fi5g39/LEB12BIWCtoOG0fW2u9G7yZVUywot7FqawPHtmUgSCAqBuB4htO4fgd5de8nYh+pQHuCs1YLSZqBkxUqK//wTW7pcedomqVC06EDLB/riN6wfistYJcqFxKqkVaxOXk1icaJzm1qhpltINwaED6BXo1546bxq3vEquJwbVwP1g+MFx5m7Zy5bM7YC4K/35+kOTzM8avh1df21FxaS9sSTmPbsAZWK4Ndfx2tM1dbMm5GMU0Usmr0XJBj+RBvCW/rW+jmKc7L4duoj6Dy96PHI08Q0a3bTiAoAW64RyeJA4a5BdZXVyi8kPz8fi8WCm5vbTTHeslrzMJszUSpdcHVtUmvtltgdJBotqBQCca66GxZCcENFRbt27Xj66acZP3487u7uHDhwgKioKPbt28eQIUPIysqqSbPXnAZR0cCN5mCpkcmHk0h2ujsFM1SxgZOnXkcUTajVPsTFfYCfb+8q28jIyGDRokXk5uYCci2YwYMHoyx2UPjHKayppQBoIj3xHhtTbdO2JIoc3rCWzb9854ybiGwXT697J+LbSJ6xt5js7F2VzMF1qc7CdVHt/OkyMqrGKR4rw2SCE5vTkFb/QemqlUgmEwCCiyseQ4fgMeJWzN4Rlw1wTitNY0XiCpYnLK9gkVAr1HQP6c7AiIH0DuuNu8a91vp+KaoTcN5A3UaSJDambeT93e+TWpoKQPuA9rzW7TUiPCOuWz9Ei4XMF/9DydlJvMAXX8Dn/vtr1FZ9/V5u+e0UB/5JxcNfz10zOtUobuty/DPvS07s2k7H+ybTol179DdRRgWH0SanFa/F9LLlmEwmCgsLUSqVBAQE1Pt424ouUM0rLYRXo3YliSNlJkQJYly1uNygejTXPVD7fE6cOEHPnj0vWu/p6Vnvy4w30MC1QJIk5mfk8+qpdKySRCOdms+bB6BLf4PjOcsB8PHuTlzcrCoDwRwOB5s3b2bTpk2IooirqysjRoygWXRTSjekUrI+FRwSglaJ59ArK2KXeeoE/8z7gqwzp+S+hDSi9/2TiWzbQT63XeTwxnT+XZGE2SAH+AU38aTrmGiCm1w+YLm6SKKIYfNmMr/7lYz1CWgUVtSCHXXjcLxuG4vHwIEoXFywWkFpqTzAuchcxOrk1SxLWMa+nHNJJdQKNd1DuzMw/PoKifOpTwO2BipHEAR6h/WmW0g3fjj6A18e/JK9OXu5beltPNH2Ce6Luw+l4toPDBRaLSGzPkAVHETBf78l+513EY1GfB95pNoDuPpuQet0aySn92RTkmti76oUOg2vflKG6tJlzB2c2b8Hh92O1Wi8qUSFQq/CoRDAISGZHQi1GJui1WoRBAGHw4HNZkNTzRi3uopCoUap1OFwmLHby9BorrxQaqXtCgLuKiXFNgcldscNExW1QY2/PUFBQZw+fZqIC/yXt2zZQlRU1NX2q0rS09N5/vnnWblyJUajkejoaObNm0d8fPw1O2cDDVwtpXYH00+k8ldOESBnd3ojpITUY+MoMaciCCqioqYR3ngyQhWBwDk5OSxatIjMzEzsdiXNm7di6NDBuBlEsj/ehz1bzraka+6D1+joapuyDUWFbP7lO45sWAuARq+n6213027wCJQqFZIocXpPDjv+OkNJnlwozzvIhS6jmhDZxq/WZp8cZWUU//knBT/9hC05BQAXZQD2Dv0IuXsILvHxFc5lMMixFuWDdLPdzMa0jSxLWMaW9C3YRTlrk4BA5+DODIsaRr/G/W6IkGjg5kSj1DCx1USGRg5l5vaZbMvYxod7PmR18mre7P4mUV7X7llYjqBQEDB9Oko3N3I/+j9yP/o/RKMR/2nTLvvbrCrWp7BQthTWh1gfjU5F93ExrP7mCHv/TqZZ5yA8/Wt30O/i6UWL3gMAMBYX4eHjU+9n3csRBAGFqxqx1IrDYENRi6JCoVCg1Woxm82YTKZ6LyoAlEp3HA4zDkcZUDuiAsBdKYuKUrtIUD2eeKrxt2fy5MlMmTKFb7/9FkEQyMjIYPv27UyfPp1XXnmlNvvopLCwkO7du9OnTx9WrlyJv78/p06dwruylCoNNFBHOFJmYuLeZKfP5MvNgxgsLub0wdlIkh2drhEtW8zF07NdpceLosj27dv5559/sFgERNGXLl0GEhXehDN/ZCAczMBLZ8fFU4XXrU3Qt/av1gPPYbezf9Vytv3+E1aTLEha9OrHLXdPwNVL/k2lnShk+5+nyUmW3alcPDR0GhFJbLfgGtWaqAxbZiYF3/9A0W+/IRrkoEGFuzteY8cSOvZuchVhmM2gtl0c4OztLbE761+WnFnC2uS1FepIxPrEMixqGIMjBhPoGlgrfW2ggcoIdgvmi/5fsPj0Yt7f/T6H8g5xx7I7+E/n/zAqetQ1H4AKgoDfo48i6PXkvPse+V9/g6DR4v/kE5c8rqBAFhTnP0I1GnkpLJS314esZNEdAji6JYO044Vs/u0kwx9vU+vnaNm7P8ePHMJut2ExlKFzqz+TE59++ikffPABWVlZtGnTho8//phOnTo5tytcVIilViSLHckh8t0P3/PAAw9UaKNcHFwpLi4uTlHh4eFxXcVYVlYWb731FsuXLyc9PZ2AgADatm3L1KlT6devX43aVKncsVpzsdtLkSRJtlr27k3btm2ZO3dujfvqdjZI3iiK9Tq1bI1FxQsvvIAoivTr1w+j0UjPnj3RarVMnz6dJ598sjb76OS9994jLCyMefPmOddFXkH++QYauJ5IksS8xAJm7M3CZBAIVLkwo4kb3sfe5Li0Fo3GTkDAMGKbv4VKVfkDqqCggMWLF5OSkoLdrsLbuyU9evTDyw7GP45gz7VgtKmQov0Ivi8cF9/q+XgmH9rP+vlfkZ8mWwQCo6Lp+8DDhDSVM6gUZhnY9ucZkg7KBeTUOiXtBzamTb/GqK+gUN6lMB05QsG8+ZSsXCn7XQCaJk3wue9ePEeMQOEqx2doznPPMBpl9wy7NpdVBUtZfmAhKaUpzjaDXYMZFjWMYZHDiPaOrpV+Xgvqq/96A1UjCAKjY0bTNaQrr257lW0Z25ixbQa7snbxSpdXcFFf+1z9vhMmIChVZL/1FnmfforCxQXfiZXXV7BY5N+UaxVhUK6u8naLpe5/RwVBoOedTVnwxi6SD+WTeryAsOa1W79Do9ej0cmfoaGoEK1r7RaMu1b8+uuvTJs2jS+++ILOnTszd+5cBg0axIkTJwgIkN1sFWolglqBZBMRTbKF18PDgxMnTjjbqem1lrtAiaKI1WpFW8tfJqvVWqkFJCkpie7du+Pl5cUHH3xAq1atsNlsrFq1iscff5zjx4/X6HxKpQuCoECSHDgcJlSq2vldaxUKNAoBqyhhcIh4qCp/ztpsNtTqG1t5+1LUeKpREAReeuklCgoKOHz4MDt27CA3N5c33nijNvtXgSVLlhAfH8+4ceMICAigXbt2fP3115c8xmKxUFJSUmFpoIFrjcHu4JH9KTy3LQtTqYIe/q583SIfIeUh0tJPkp8fTmTE+7Rs8VGlgkKSJHbv3s3nn39OSkoKGo2G7t1HMLDvcDyOF1D6y1EcBWa0nioi7ovCZUA0xZbL32hKcnNYMvtt/njzZfLTUtC7ezDgoSe5+60PCWkai7nMxuZfT7Lg9V0kHcxDoRBo1bsR977elfihkVctKCRRpGzjRpInPEDS2NsoWbYMHA5cunQh7KsviVq6BO8773QKCjhX5C80zEaCch2zzzzF+G39+fzoHFJKU3BRuTAmZgzzB8/n77F/M6X9lDorKMxmOU1uUpJcZTspSf6/BhOADdRRglyD+Lz/50xpPwWloGRZwjLuWHYHpwpPXZfz+9x3L/5PPw1AzgcfULjg10r3E0VZy1c1PlGr5e2ieK16Wrt4B7nSomcoADsWneFalOBS6/UIgoDNYsF6NnFEXWf27NlMnjyZBx54gLi4OL744gtcXFz49ttvK+yncJG/CKLxrNuoIBAUFORcAgOrtvZKkkR0dDSzZs2qsH7//v0oFAoyMjIA2XIwadIk/P398fDwoG/fvhw4WyUe4MyZM4wcOZLAwEDc3Nzo2LEja9eurdBmREQEb7zxBuPHj8fDw4OHHnqo0j499thjCILArl27GDt2LE2bNqVFixZMmzaNHTt2OPdLSUlh5MiRzgxVt99+uzMVLsDMmTNp27YtP/zwAxEREXh5efHggy9QWmrA4ShlwoQJbNy4kY8++ghBEBAEgaSkJAA2btxIp06d0Gq1BAcH88ILL2C3nyumGhERUcG64aZUcHuPLsycOdO5ThAEPv/8c2699VZcXV156623qvwc6gJX7Tyn0WiIi4urjb5cloSEBD7//HOmTZvGf/7zH3bv3s1TTz2FRqPh/ioyXrzzzju89tpr16V/DTQAcKzMxENHkjie4kBhU/JUnDc9rb+RdvIXAAIDowkKfBOdLpzKJn+Ki4tZsmQJZ86cASA8PJwhQ0aRe0SJ+fejCMXyw0zfyhfPAeEo9GqU1kvPKtqsFv5d8ie7/voDu9Uip4gdOIxu4+5B5+aGwy5yYH0qu5cnYjn7UIlo7Ue3MU1qJaOTaLVSsnQp+fPmYT0tXxdKJR5DhuDzwAT0LVpUeeypwlMsOr2IZWeWUWgpdK5vH9CeMTFjGBA+4LrMAl8t9d1/vcG6Un0UgoJJrSbRPqA9z256lqSSJO5dcS8f9PqAno0uTnBS2/g9/BCiwUD+V1+R9frrqIODcOvVq2Ifb8JK7/FDIji+LZOc5FLO7M0lukPtVT4GOUZA5+aO3WigKDsTn5CIWm2/uqg0impZDqxWK3v27OHFF190rlMoFPTv35/t27dX2FehV+EotiBZHUgOkbKyMsLDwxFFkfbt2/P222/Toor7tCAIPPjgg8ybN4/p06c718+bN4+ePXsSFxdHYWEh48ePx9PTk5UrV+Lp6cmXX35Jv379OHnyJD4+PpSVlTF06FDeeusttFot33//PSNGjODEiRM0bnyu0OSsWbOYMWMGr776aqX9KSgo4O+//+att97CtRJTnJeXFyC7FpcLio0bN2K323n88ce544472LBhg3P/M2fOsHjxYpYtW0ZhYSG33z6OOXP+y2uvPc9HH33EyZMnadmyJa+//joA/v7+pKenM3ToUCZMmMD333/P8ePHmTx5MjqdroJoOB+3s9YJ6wVKfubMmbz77rvMnTu3ztf7uKrerVu3jnXr1pGTk4N4wZtwoQquDURRJD4+nrfffhuQ09oePnyYL774okpR8eKLLzJt2jTn/yUlJYSFXX0xqwYaqIxfMvP5z8k0jGbwtbvwWis1bjkvknk2DV1w8G1ERjyBw6G9SARIksTBgwdZsWIFFosFlUpF//796dgunpxlqeT+nY+72oHCQ43n0Ej00eccodVq2TXowllFSZI48+9O1n/3NSW58uxLo7iW9H3gEfwbRyBJEgn7c9n252mKc2Sx4hvqRvfbogmLvXr3AUdREYULFlDw40848mRXKoWrK163347PffeirsJh22w3syppFb+d+I2DeQed6/31/tza5FZGRY+6rqk7a4P66r9e37MD3UjaB7bnjxF/MH3jdHZl7eLJf57kmQ7PcF/cfdfcdcb/6anY8/MoXvgn6U9PI/ynH9HFnisQp9XKn2NhYeWi4sJECPUBFw8NbQc0ZveyRHb8dYbItn4oayn2qxydmztlRgM2s52vpmys1bary0Mf9aqW1TgvLw+Hw3GRlSEwMPAi9x9BpUDQKpEsDmLCo/n2229p3bo1xcXFzJo1i27dunHkyBEaNWpU6bkmTJjAjBkz2LVrF506dcJms/Hzzz8za9YstFotu3btYt++fWRkZODmJhdgnTVrFosXL+aPP/7goYceok2bNrRpcy4e5o033mDRokUsWbKEJ544Fx/Ut29fnnnmmSqv+/Tp00iSRPPmzS/5/qxbt45Dhw6RmJjoHBd+//33tGjRgt27d9OxY0dAHnvOnz8fd3fZq+Dee+9hw4Y1OBwmPDzc0Gg0uLi4EBQU5Gz7s88+IywsjE8++QRBEGjevDkZGRk8//zzzJgxA0Ulat3t7HfVLoFdlFCdzdx49913XxTjUlepsah47bXXeP3114mPjyc4OPi6+BYGBwdfZBWJjY1l4cKFVR6j1Wpr3YevgQYuxOBw8OLJNH7LkmfSe3p5MF6bhjnpdcpEAyqVB01jXsLXV56lVCgqioCysjKWLVvmvNGHhoYyatQoPMo05P7fPozZFpRoUbfww29w+EUZOiqbVSzKzmL9/C9J2LsbADdfP3rfN5GmXXogCAK5KaVsXXiK9BNFAKhctHQcJgdh6/VX93u2ZedQMH8+hb/+imSUg8BVQUH4jB+P17jbULpXHkOSVJzEbyd/46/Tf1FilV0VVYKKXmG9GBMzhm4h3VAp6vZMTWXUV//1+m5dqQt467z5YsAXvLXjLRaeWsgH/35AQnECL3d5+Zp+lwVBIHjmTGwZGRi37yD1kUeJ+O031IHnZu99fOTPsbCw8krvPrUblnBdaNs/jMMb0yjOMXFiRxZx3WtXqavqsD/71aLQq3BYHHRuHU+P/ucsat26dSM2NpYvv/ySN954g7fffts5uQtw9OhRGjduzLBhw/j222/p1KkTS5cuxWKxMG7cOBQKBSdPnsRgMFQYeINcy6LcKl9WVsbMmTNZvnz52SyHdkwmEykpKRWOuVy2z+q6vh07doywsLAKE81xcXF4eXlx7Ngxp6iIiIhwCgqAkJBG5OXJz3qHw1hl2127dq0wNu7evTtlZWWkpaVVsLyUo1YonDEJZQ4HXmfvD/Upu2mN72hffPEF8+fP57777qvN/lyS7t27VwgcAjh58iTh4eHXrQ8NNHAhJw1mJh1O4qTRjAKYHuFP39Jv2HdsMxqNBR+f1jRr+ho63bmb6fki4Pjx4yxZsgSj0YhCoaB3795069SVsjUp5G7LAAlcfDSE3RqNydcbRSXZEs+fVbTbbOxe8ge7Fv2O3WZFoVQRP2I0XUbfgVqnw1BkYccSuRI2EoioiOjYmMiOjVCoVKSk1Hwm2pqaSv43/6X4zz+RbHItC23z5vhOfBCPwYMRKnkg20QbG1I38OuJX9mZudO5PsQ1hHHNxjEqehR+er8r60gdozr+65VZmm409dW6UtdQK9S82vVVojyjmPXvLBaeWkiRpYj3e76PRnnt0mwKajWNPvqIpLvvxnr6DOlTpxL+/XfO36FOJwvDCxMheHvXX0uURqei/aBwtv5xmr2rkmneNRhFNWv1VBevoGAKMzMYNbURvo3DUSqv70SHSlM964ufnx9KpbJCjABAdnb2RYN7AIVOhYNzLlDC2ZlztVpNu3btOH36NACPPPIIt99+u/O4kLM3gUmTJnHfffcxZ84c5s2bxx133IGLi+yaarFYCAgIYPHixfj6Vqx8Xu6ONH36dNasWcOsWbOIjo5Gr9dz2223YbVaK+xfmUvT+cTExCAIQo2DsS/kwsBoOfBc/ttuN9S4XYVCcZEAEs/GXBgcIl5nT3u5661L1PiXYLVa6datW2325bI8/fTTdOvWjbfffpvbb7+dXbt28dVXX/HVV19d13400EA5v2cV8NyJNEyiSIBGxZwoDW6pD5FfdhwXlwA8PSbTsuV4FBfMSBoM4OJi4e+//2bfPrk4W0BAAKNHj8bH5ELux/tx5MvRuy7xgXgNj8KKivT0S88qJh3Yyz/zvqAwUw6Ma9yyDX0ffATf0DBsVge7lyeyd3UKdoucbSm8bRCNOkSidtFf1Uy0+cRJ8r/+Wq7se/Zuq2/fHr9HHsb1llsqtWRmGbL44+Qf/HnqT3JNcmVwAYGejXpye7Pb6R7S/boUELse1Ef/9fpqXamrCILA+BbjCXUP5dmNz7IuZR1PrHuCuX3mXtOYIKWHB2GffUbi2Nsw7dtHzqxZBJ7nY1+eCOFmipmJ6xHCvyuSKM4xkbCv9mMrdK5uaPR6bGYzDqsBnVfdNOloNBo6dOjAunXrGDVqFCC78qxbt66CO1E5gkqBoFEiWR2IZjtKV/lm5XA4OHToEEOHDgXAx8cHn0rMWEOHDsXV1ZXPP/+cv//+m02bNjm3dezYkdxc+T4fGRmJspICb1u3bmXChAmMHj0akC0X5UHPV4KPjw+DBg3i008/5amnnrpoUF5UVISXlxexsbGkpqaSmprqtFYcPXqUoqKiy8YKlz/THA4DGo0Gx9kMhuWUe9GUp50tvz53d3enC5m/vz+ZmZnOY0pKSkg9e71GRx2bYaomNRYVkyZN4ueff75mNSkqo2PHjixatIgXX3yR119/ncjISObOncs999xz3frQQAMAJofIS6fS+DmzAIBbvN141e8oeSdfosxhRK32pUf3DzCbe1BcfLEIyM9PZ+XKRZSVyXEG3bp1o3ePXhjXppG7TZ4NUnpq8B4Tg66ZfPPWUfWsolrKY83n33ByxxYAXL196H3fRJp1k03Yp/7NZtvC05QVWgAIivKg+20xiDpPCgtrPhNt2r+fvK++puyff5zrXG+5Bb+HH8LlrMn2/MGKRiOxO2s3Px37iQ1pGxAl+cbpo/NhbMxYbmt6GyFuN9/U90X+6w47GPPBXATmYgzZZXir89DmZoCpEKxlYDOD3VTx1XF2xk4QQFAAwrm/VTrQuID67KJxBZ0XuPiAiy+4+smvboGg96bSLAHnUV+tK3Wdfo378Vn/z3jqn6fYnrmdR9c+yuf9P7+mwkLTuDEh775D2uNPUPDd9+jbtsVjyJAK+9R3IXE+Gp2KVn0a8e/yJPb8nUSTdv4ItWyt0Lt7YDObMZWW4uLpXWfTy06bNo3777+f+Ph4OnXqxNy5czEYDBV89MePH09oaCjvvPMOCp2S199/i86du9C8QwuKior44IMPSE5OZtKkSZc8l1KpZMKECbz44ovExMTQtWtX57ZBgwYRHx/Pgw8+yLvvvkurVq3IyMhg+fLljB49mvj4eGJiYvjzzz8ZMWIEgiDwyiuvXBSvW10+/fRTunfvTqdOnXj99ddp3bo1drudNWvW8Pnnn3Ps2DH69+9Pq1atuOeee5g7dy52u53HHnuMXr16VcPlqFxUmAgPD2fnzp0kJSXh5uaGj48Pjz32GHPnzuXJJ5/kiSee4MSJE7z66qtMmzbNGU/Rt29f5s+fz4gRI/Dy8mLGjBlOsWUSRcRrkMHsWnNFouL8gGdRFPnqq69Yu3YtrVu3vsg8NHv27Nrp4QUMHz6c4cOHX5O2G2igOpw2mpl8OIljBjMCMC3cl8HmT8k++TsA3l5daNFiDlptQIUgV6MRJMnO4cPbOXRoIyqVHU9PT0aNGkWw6E3+JwdxFMjWCdeOQXgOi0Shq/gTvXBWURLtHP1nCdt+/xmbxYwgKGg3ZATdxt2D1sWFvLRSNv96ioxTRQC4+WjpNiaa6A4BWK0CSUlXPhMtSRLG7dvJ+/IrjDvPuisJAu6DBuE7eZIzk1OFa7ea2ZK5kRXpv5Fi349CIw+OOwZ15PZmt9MvrB9q5U3iqyxJUJYDhYlQmARFqVCaiU9+HqZUK4VFxbja01ArrNhENQarCzqVBR+PTFBZrk8fNW7g2Qg8w+RXn0jwbw5+TcErHBSKemldqS90Ce7C1wO/5tE1j7I3Zy9T1k/hk36foFVeu5G9e79++E6eTP7XX5P5ygz0bdpUmSjhZqD1WVGRl1rG1j9P0+O2mFptX+fqRmleLnarFbvFgrqO+ordcccd5ObmMmPGDLKysmjbti1///13heDtlJQU50BX0KsoLCri0acfJys3G29vbzp06MC2bduqlelz4sSJvP322xcFFguCwO+//87MmTN5+OGHycvLIygoiJ49ezr7Mnv2bB588EG6deuGn58fzz//fI3LAERFRbF3717eeustnnnmGTIzM/H396dDhw58/vnnzj799ddfPPnkk/Ts2ROFQsHgwYP5+OOPq3EGAUFQIUl2nn76MSZOfIy4uDhMJhOJiYlERESwYsUKnn32Wdq0aYOPjw8TJ07k5Zdfdrbw4osvkpiYyPDhw/H09OSNN94gMTERBfJjxFQPrRWCdAXJnPv06VO9RgWBf86buaxLlJSU4OnpSXFxMR4eHje6Ow3UMxZlFzL9RCoGh4ifWsXsKAXuKU9jNJ4GFERGPkVkxGMIQkXTrsUC2dm5LFmymLy8dABat27N4P6DsKzPxLBdNoEqPbV4j41B1/TyVeLTjh1m3X8/Jy81GYCQprH0m/goARFRmMts7FySwJHN6UgSqNQK2g8Op92Axqg0Z2dCTHKtBE/PyietJQmKiyEyEvR6WUwYtmwl79NPMe3fL++kUuF56634TpqENupcIcryAN/0wjzWZS1lRfJflJiMiBY9Op3AmPjO3N/mDqK8oq7wE6hDWEoh9wTkHIO8E1BwVkQUJIKtcj9bs11LgdGLUqs7DkmF0sUDd08VPn4KdB5usgVB7wNaN9nyoNaDSgsqPah1UO5/L0mAdN6rKFsybAawGsFmkq0d5iIwFoAhT7aMGPNkS8ilUOnALwYCW5Kh7kGhvh3eMdFyP86j3MJ1E49Lrzn7c/bz0JqHMNlN9GzUk7l95qJWXDtxLdntJN97H6b9+3Hp1InG8+ch3MSq8NNHzo1DHv+i71W1ZTabSUxMJDIyEt1ZAVGckyVbKjw88fCvXRerG4UkSdiyDOCQUPnpL5rYuhybN2+mX79+pKamXpR1ymQyUVhYiFKpvGTdi/qC0ZSC3VaMVhuIVlt7n3+i0UKJ3UGITo2/5vpNtlX2HS+numPnK/q2rF+/vmY9baCBeo7ZITLjdDrfZ+QD0NXTlVf9DlB4cgZG0YJGE0DLFnPw9u5y0bGiKLJ//27WrFmD3W5Hr9czfPhwol0bUfDlUWfshGunIDyHXmyduBBjcRGbfprHkY3rANC5e9Dzngm07NUfSYJDG9LYuSTBWW8iukMA3cZG4+5T8SZR3ZloQZAo27yF3E8+wXxATu8qaLXoR9+J933j0TYKuch1YvOpI/yyZyW7ildjl+R+BHkEyhWHvYcQFuBOiNel3/M6g90Kuccg+4gsIHKPQ85xKE65xEGCbAHwjpBn/j2CwT0YnUcIIe7BWDTBiHp/FCrF9Xc7sZmgOF3uf1EqFKdC/hlZIOWfArsZsg5B1iF87H9iKgmm0OGKa0gj1OHtsAV3xeDdAZ2ne73MDlSXaBvQlk/7fcpjax9jU9omXt/+Oq93e/2audIIKhUh771LwugxGHftouC77/F9YMI1OVdd4Nan2rLk//YDUFpgvugeeLXo3DwwlZZiNpTi7ut3Uwg0QRBQaFWIRhuixVFtUWGxWMjNzWXmzJmMGzeuUtFQnonT4XDgcDgqjauoTygVeuwU43DUbiFEF6WCErsDg0PEv1ZbvvbUv9yMDTRwnUk2WZh0OIlDZSYE4Mkwb4aZ55J3egkAvj49iYubhUbje9GxJSUlLF68mISEBACaNGnCyGG3Iu4oIHfzQZDOxk7c1hRdzKWtE6Lo4ODaVWxZ8B0WgwEEgdZ9B9HjrvHo3T1IP1HI5t9Okp8uz5L7hrpyy+1NCW1WebuXy1NfViahPbGDzFfmYj54VkzodOjH3A2jJmDW+pNmAWWS3I6Hl53N2Wv47sAC9hzPR6GyIqjstPZvXSEdrPUyhfpuKA6bLBwy90PGPsjYD9mHz8UyXIhboOw25N8cfJuAd6TsSuTV+KKZ/fO5oZet1oNftLxciOiQrS25xyHzALr0vYQmH6Yg30RppgVjeiJKxR94a434NAlH16w7NBsKIe0a/KBqSMegjnzY+0Oe+ucpFp9eTIhbCI+2efSanU8THk7gc8+RNXMmuXPm4N6nN5qIiGt2vhtJWJwPoU29SD9ZxNGtGXQeUbuWUY1ej1KlwmG3YzEa0LlVniq7viHolGC0IZnt4Fm9u9Uvv/zCxIkTadu2Ld9//32l+ygUCtRqNTabDYvF4swMVV9RKuX+O8TaFRWuZ7Nu1cdg7Styf7oZaHB/auBKWJVXzJPHkimxi/iolcyKAK/UKZhMyQiCkiZRz9C48WQE4eIB1eHDh1m2bBlmsxmVSsXAgQNpE9ycwt9PYc+Rc1u7dAjEa0TUZWeDcpISWPP1J2SdPglAQEQT+k96jOCYZpTkm9i28Axn9uYAoHVV0XlEFC1uCUFxmcJPldUhsFolcjfsxvjr93glbEarsCLodHjfeSeu9zxIttW/wv4lRhN/HVvD8pQ/KdAeAgTE/MYMaNaZsTFjiPGp6Mt8oVvVDaU0C1J2yEvabnmG3lFJXIPWE4JaQUAsBDQH/1j5b5f/gal6SYKiZCwJexETt6FI2YS2pGJqb9yCoNkQaD4conrBzRIfcx357cRvvLHjDQDeueUdhkddu9hBSZJInTgJw7ZtuHbvTtg3X9fZQOOr5dS/2az+5ggunhrGv92txsXwqnINKc3Pw1BUiM7NHa/Ai9O01kckh4gtU56cUge7OlPL1gbFxcUYDAZcXFycqWTrK5LkoLT0KABubs1R1JLrokOSOFwqC5UWbnpnEbxrzXV3f2qggf8V7KLEO4mZfJoiD9Q7eLgw02cvpadewyRZ0WlDaNFyLl6eHS461mQysXLlSg6end0PCQlh9MhRaA+ZyF18EEQJhZsa7zEx6OMutm6cj81sZtsfP7Nn+WIkUUSjd6H7HffRdtBQRDvsWpbI3lXJOGwiggAteobSeUQUOrfq3dzOz1NfUiKRu34XxQt+QnV6P17KYnQuCrzvfhDfBx9A5edHRsa5ugUFpgIWnVjEkjNLKLWW4jC44+sbzt0dBtFJM44gT5+6FeArinLsQ8p2SNkpvxYlX7yf1gOC28iz7yFt5VfvyMtmS7ppEQTwjkDbIQI6jJHXFadB4iY4tRpOrYGyLNgzT15c/KDVbdDmTghu+7/7vl0htze7nbSyNOYdnsdr214jxiuGZj7Nrsm5BEEgaMYrJNw6EsPWrZSuXInH2XShNxtRbf3Ru6sxFltJPpRPVNvadSjRurphKCrEYjQgieLN4QKlVCCoFUg2EcnqQNBX75rOT9RU1dug0WgwGAzYztYxqs8IghKFQosoWnA4TLUmKpSCgFohYBMlzKKIWz1Krd4gKhpo4AKyLTYePpLEjmJ5pmZiiAdjLLMpSlwJgJ9ff+Ji30Ot9rro2MTERBYtWkRJSQmCIHDLLbfQrXk8xb+doSS9DAB9Kz+8RkWjdL30DShh327W/fdzSnJlYdO0Sw/63D8ZV28fEvblsvWP05SezRYVEuPFLXc0xa+R2xVfr1Yr4X5yIyVzv0B19Dj+iGg9VHjffS++Dz6I6myhovK6BQWOFL7d/Turk1dhE+V4iUbujRjd+nZuCexPs2gd+flVu1WdX6jvmiJJkHcKEjfKS9KWSoKUBQhsCY07Q1hnCO0gC4ibYGBwTfFsBG3vlhe7BRI3w4nlcGwpGHJh5xfy4t8c2t8P7e4BneeN7nWdZ0q7KZwsOMnWjK1MXT+VBcMX4Km9Nu+bJiIC34cfIu/jT8h65x3cevVCUY+KbFUXpUpB085BHFibyql/s2tdVKi1WqcLlNVkQnuTvIeCRolkExEtYqUFV89HFMFuP5uRUJLnERQKUKkuvpWWZwq12WyIoujMOlVfUSr1iKIFUTQBtef9olcosIkOTKKIGw2iooEG6iVbC0t55GgyuVY7rkoFbzUWCct4gCJzGoKgJib6BRo1uh9BECrUX1AobPzzzz9s374dAG9vb0aPGo13soK8zw6CXULQq/Ae1QR9a/9LuhqUFeSz/ruvnTUn3P386ffgozTp0ImibCNLPz5A6lG5Poabt5ZuY+UUsTVxXzDs3EXu3LmYzhbg07u54HP3vfg8+CCqC6Jw92bt55Nty/i36B/n5HOcbxx3NLuDbiHdUAhKiovl98THR84udalCfdeEolR5Bj1xo/xamllxu9pFFg6Nu8pColHHm2qwe0MKmKm0ENNfXoZ8AGf+gQO/wPHlcmzGqhdh/VuyAOn0cOWxHA0AoFQoefeWd7lz+Z2klaXx6rZXmdN7zjVzTfKdPJniv5ZgS0khf958/J94/Jqc50bTtGMgB9amknQwD5vFgVpbe4M0QRDQurphLC7CbCy7eUSFVgkGG5LVccn9RBGsVllMyM9C+W+HQ96m0VQUFkqlEoVCgSiK2Gw2Z/B2fUWp1GOzFdV6sLZeKVBir39pZa9KVGzevJkvv/ySM2fO8McffxAaGsoPP/xAZGQkPXr0qK0+NtDANUeUJD5NyeGdhExEoLmrjtd9dmNPfBOzZEeva0zLlh/h4dG6Qv0FhwMKCnLZtGk5RmMaKhV06NCBfh16UvZXEsXJco5tXTNvvMfGoPSo+gYqiSIH1qxk8y/fYTUZERQKOgwbRbfb7gaFmh1/nWHfmhREu4RSpaDdwMa0HxyOWnPlD0jTwYPkzp2LYZssggSdDu977sZ34sQKYkKURDakbuDbw9+yL+Mo1rwQFCoVXRt35K7md9LSr5VzX6v1nFuTVlt1oT4fn+pV6a4WdovsxnRqjeyKk3ey4nalFsI6yX7+kb1ld6ab0N//wu+kUikHz9fqe10dlCpoOlBeTEVw+A/Y+ZXsdrbrK3lpPhx6vyDHqDTgpFwQ6hVefNj7Q+5dcS/rUtax+PRiRseMvuJ2qiMsFRoNAU9PJf3paeR/+y3ed96Bys/vKq+k7uHf2B0Pfz0luSaSDuYR07F205lqXVwwFhdhNRorVFCu61zKXUmhUeIAJJsDSZSqLB5ot8si4vxEToIg/+9wyNvPt1gLgoBGo8FsNt8UokJx1owjirVbY0h39gMxi/Ur7LnGomLhwoXcd9993HPPPezbtw+LRX5Di4uLefvtt1mxYkWtdbKBBq4lRTY7Tx5LYU2+LADG+rtyn/1DDClrAAgIGEps87dRqdwrBDbr9SLHju1h06ZtmM0q3N0DuH1cb6KMbhR+fhjJJiJolHiNiMIlPvCSD5rc5ETWfP0JmafkANigJjEMeOhJ/MMjSTyQx5bfTjldnRq38OGWO5riFXDlmTPMJ06Q+9H/nauArVbjPW4cvo88jDrgXJ5th+hgVdIqvj70NaeL5ArfWq2aQbG9GRR4B60ah13U9oVuTRcW6qu12fPitLMiYg0kbKhYE0JQQEj7syKip+zSpL7R0eDXlsqC7W022UpkMsni7obU5dJ7QcdJED8REtbDzi/h5Co4vkxeYkdArxcgqOUN6FzdoTJB6O3egodin+KzI7N5d9e7xAfFE+Z+8W/ucu1UR1i6Dx6M7tt5mA8dIu+zzwiaMaOWr/DGIwgCMfEB7FmZzKl/s2tdVKh1egRBwGG347DZUFXm91mHqJa7klKQF4eEZHMgaC8eLoriuXt7ZSgUle+jVqudoqK+o1DIDzVRtCJJjotqVNUUvbJcVIj1SqjWWFS8+eabfPHFF4wfP54FCxY413fv3p0333yzVjrXQAPXmv0lRiYfSSLVbEWrEHgp1EZs1gQM1iwUCg0xMa8QGnKX8wddUCA/vFWqUpYsWUlqaiqCAC1bhtM+tjfCmkyK8s4AoI3yxPu2pqgukRvdZjGzfeEC9ixbhOhwoNHr6XHneNoMHEppvoXlnx4k+bBcG8PNR8st45oS2dbvim8w1qQkcj/+hJIVK5x2as+RI/F7/HE0jULP9cdhY2nCUv576L+klMp1GFzVrtzZ7E7uib0Hd4U/6elX5tZ01UJCFCFjrzwQPbkaco5U3O4WCNEDZPebqD7yYPY6c0Pcjs5S/p30Pi9zsEYjL4WF8vYbWqBOEKBJX3nJOQ6b3ofDf8rxF8eWQpu7oP9McL85MudcCZcShP08x7PVaysHinby2rbX+Hpg1RmarkZYCoJAwPTppNx/P4W//4Hvww+jvgkKk11ITHwge1Ymk3KkoNZdoBQKBWq9HqvRiMVoqNOiorruSoIgIKiVSA47kk2sMg92eTuVIQgVrSHlnB9XUd9RKFQIghJJciCKFmea2atFIwgoBBAlsIgSOuVNLipOnDhBz549L1rv6elJUVHR1fSpgQauOZIk8X1GPq+cSscqSYTrNLzusxtVyptYEXFxiaJly49xd2vuPKY8UDkj4yTr16/GYrGgUqno3bs30QSTv/g0BUYJVz8l/sPDcesaUqXJGCBx/x7WfvMZJbnZAMR06kafCQ+hd/fm3+XJ7F2VgsMuolAKtB3QmPghEVf8ILRlZJD72WcUL1osPzUA9yGD8X/ySbRR53K2m+1mFp5ayPwj88kyZAHgpfXi3th7uSv2Ljw05wLQrotbk8MmB1YfXwbHV0BpxrltgkKOhYgZIIuJoNY3LLD6RrsdlX8nq3LjdnWtYzVBAprDbd9Cz2dh43twZJEcf3Fsqbyuy6OXrO9xs3FpQahkSvPXeHT3SHZm7WR54vIq08xerbB07dwJl/h4jP/+S8G8+QS+8HwtXWHdwSfEFXcfHaUFZtJPFhLRqnbdvLR6F6xGI1aTCVevS9ccupFcibuSoFEgmUGyVu3XLwjnrB0XUtV6lUp1ti/2ejULXxUKhQ6Hw4DDUXuiQhAENAoFZoeIRRTR1WJa32tJjUVFUFAQp0+fJuKCojlbtmwh6rzBSgMN1DUMDgfPnUhjYbacCWigj56HHLOxpK8FIChoNM2avoZKVXGkZjJZWLNmCwkJ+xEECAgIYEifgSi2FVF8KhGlBIogD/wmh+PeuOobi6GokPXzv+LE9s0AuPv60/fBR4iO70zSoTw2/7qTkjzZ1alRc2963tkU76ArC/6z5+eT98WXFC1YgHR2Nsitd2/8pzyFLjb2XF9sBn498SvfHfmOArMc/O2n92NCiwmMazoOF/XF13HN3JqsRjizDo4tg5N/g7no3DaNG8QMlAutRferE/Uh6oLbkSjKAwF1FWEiarUs/CqbLbyhBMTCuPnQ9QlY+Ryk74G1r8K+H2Hkp3IQ/U1OdQShyhLKA80f4YsjH/HB7g+4JfSWi7JB1Zaw9H1osiwq5s/H6/ZxFSYdbgYEQaBxCx+ObM4g5WhBrYsKjU52s7RZTHVqoLxp0yY++OAD9uzZQ2ZmJr/+uoiRI0dVuu/57kqbNm1g2tSnOXLsKGEhjXj51VeYMGHCRfsrFOcmVC5EFCtPH65UKhEEAUmSsNvtTstFbVNSUsJ7773HwoULSUpKwsvLi5YtW/LYY48xevToWvuMHnnkBQoL8/jjj59rpb1ytAoBswOs9aicXI1FxeTJk5kyZQrffvstgiCQkZHB9u3bmT59Oq+88kpt9rGBBmqNUwYzEw8ncdJoRinAtGAHnXIfxGLNQqHQ0qzpa4SEjLvouPT0dH79dTEJCSIqlYIuXTrQwS+W0t+TEY0OUArouobi3iYEbWDlNypJkjiyYS0bf/gvZkMZgqCg/dARdLv9XsxlsOLzgyQeyAPA1VND93ExV5zVSTQYyJ83n4Jvv0U0ni2w17kz/lOn4NKunXO/EmsJPx39iR+P/UiJVY4lCXEN4cGWDzIqZhRa5eVVQq0ICZsZTq+FwwtlIWEzntvm4icXVIu9VY6RqGMz2HXB7UihkB/aNlvl6XtvWE2Q6tIoHiauhYMLYO1MyD8F3w6Cro9D35dv6niY6grC+5rfz+q0pSQUJ/DVwa94tuOzNWrncsLS9ZZbnH8njBxF7KGDV3I59YLGcb6yqDiSX+ttq7RaBIWA6BCx26yoNXXjfmUwGGjTpg0PPvggY8aMqdJ6AOfclRITExk2bBgPP/Qw8+Z8zfqtG5g0aRLBwcEMGjSowjEq1bnvoOw2JVsoRFH+W1XJKFMQBNRqNVarFZvNdlWiwmq1oqnk5ldUVESPHj0oLi7mzTffpGPHjqhUKjZu3Mhzzz1H3759a634XnkchSiaa6W9crRnPR0s5wVrV3W9dYUai4oXXngBURTp168fRqORnj17otVqmT59Ok8++WRt9rGBBmqFxdmFTDuRitEhEqBR8YrHEdwS36QMO15eUbRq+QlubhWLTYmiyNatW1m/fj2iKOLrG0y3jrfSKN1O8eYEANSBLniOaIJB44KHV+WD7aLsLNZ8/Qkph/YDckXsgQ8/iV9YFPvWpLBnZRJ2m4hCIdC6Xxgdh0WguUyV7fORbDaK/viD3E8/w5EnCxNdy5YETHsa127dnPuVWkv58eiP/HD0B0ptpQBEeEQwqdUkhkYNRV1LxXsuicMGCRtlIXF8GVhKzm3zbAyxw+UMQY27QB0t+lNX3I60Wtnd6obXBLkaFAo53WyzIbDqJdj/E2z/BE6vk60ZAc0v20R9pLqCUKtW81zH53hk7SP8cvwX7mp+F43cG11xO5cTloIg4NanD2Xr14PNhuRwIFQ2/VyPCW3ujUIhUJxjojjXhKd/7YlWQRBQa3VYTSZsZnOdERVDhgxhyJAhzv+r46705ZdfEBkZyYezP8SWYSA2phnbD+5mzpw5F4kKhUL+3vXr15dmzeKYM+cTpztVYWEuYWGhrFy5kn79+mGxWHjppZf45ZdfKCoqolmzZrzxxhsMGzYMgPz8fJ544gk2bdpEYWEhTZo04T//+Q933XWX83y9e/emZcuWqFQqfvzxR1q1asX69esvupb//Oc/JCUlcfLkSULOm91p2rQpd911l7NidGFhIVOmTGHp0qVYLBZ69erF//3f/xETEwPA/PnzmTp1Kr/++itTp04lNTWVHj16MG/ePIKDg5k5cyY//CDHFbu6RgKwfv16evfuzaFDh5gyZQrbt2/HxcWFsWPHMnv2bNzc3JzX0rZtW+bOnevs36hRo/Dy8mL+/PloBAVDWsVyx/0TyE9KZPHixYwZM4b58+dX9+O/7tRYVAiCwEsvvcSzzz7L6dOnKSsrIy4uzvlmNdBAXcEiirx2OoNv0+XBdiednvtKf6Ds1A5KpWD8/XsRGjL1Inen4uJi/vzzT5KT5arLcXFx9Gzei4QfssgqsOGiEfDqHoSuSyMMFkWlgcqi6GDviiVs/e1H7BYLKrWGruPuJn74aDLPlLDgzV0UZcuz8yExXvS8qym+IdX/DUmSROmq1eTOmYP1bD/VjRsT8PRU3AcPdlo5yqxl/HjsaMUFBgAA/HtJREFUR74/+j2lVllMRHtF83CbhxnQeADKaz14Fx2QvE0WEkf/AlPBuW0eodBiNLQcI2duqiNuA5eiLrkd3bCaILWN3htGfQZxo2DJk5B7DL7uA8NmQ9u7Lnt4feNKBGG3kG50Ce7CjswdfLzvY97r+V6N2rkcoXNmc6pnL8SSEgxbtuDWq9dVXGHdQ6tXERjpQeaZYjJOFV2VqJAkCbulYhpRQVBgt1owFhdfU1Gh0mpr7LpTbo24lLvSjh3b6d+//9lgbQWS1cHAvgOY9vwzlbapUMDkyZN44okn+H/2zjs8irKL4r/Zmmx6b4QkhBR671KlSZGiIIgIIiIKCCIqVhAFbBQrdoqKqAhYwQ+Q3rv0mhDSe9tk68z3xyQLgQAhbEiCOc+TZ7OzM++8Mzs7c88t5y5YMA+NRotCAcuXf0dQUBDdunUDYOLEiZw4cYIVK1bg5ubGypUreeCBBzh69CgREREYDAZatGjBiy++iKurK3/++ScjR44kPDyc1q1b2/a3dOlSnnrqKXbs2FHqfERRZMWKFYwYMaIEoSjGlXbq6NGjOXv2LL/99huurq68+OKL9OnThxMnTtgiKAUFBbz//vt8++23KBQKHnnkEaZNm8b333/PtGnTOHHiOFlZSXy6aDbOTpF4eXmh1+vp1asX7dq1Y9++faSmpjJ2rHyOykoKiiMVX32wkJmvv86MGTPKtF1lotykYuzYsTzyyCN06dKF+vXr23NONajBbeHKXP9UycS4Y7EcypMN98c9BBqenkmuPhOdo0jdiAl4ew0kL0/AbL6cB3/s2DH++OMPDAYDarWaPr3vIyzVnfwfzuArCeT56VB1i0QKdMVkLb1QOS0ulv999gHJ588CEFy/ET3GTcTBxYdN353m1C65INrRVUOHB+oS2frGsrNXo2DfPlLefx/DETlNQenpifeEp/EYMgShyLrIN+Wz/NRylh5faktzCncLZ3zT8fQM6YlCqOC8mJQTcGQ5/Psz5CdfXu7kIxuPDR+QZV+rbH5O6ahKaUcODneoeP5OIbInjN8Gq56QJYPXjIekw9BrTpWNXJUXZSWEgiAwtcVUhv4xlLUxa3myyZPUcatzy+PcDAoHB9wGDiBr2bdkr/zlriMVAH513Eg6n0NKTA712geUexyL0ciHox6048zKjmeWrkRdzh+2UikTixulKyUnJ+NXpAAmqAQkE/h6+5Cbm0thYSGOjteSscGDBzNx4kR+//1Xhg4dCshe/tGjRyMIAnFxcSxevJi4uDgCAwMpLCxk/PjxbN68mcWLFzNnzhyCgoKYNm2abcxJkybx999/89NPP5UgFREREbz77rvXPcb09HSysrKIjr5xlLOYTOzYsYP2RRH977//nuDgYNasWcOQIXIqtNls5rPPPiM8PByQydGsWbMAmaDodDoKCjT4+Xri7OyDQqFi6dKlGAwGli1bhlNRSPvjjz+mf//+vPPOO7bzeyMUk4pWnTrz7NSpKKqBw63cpCItLY3evXvj4+PDsGHDeOSRR2jSpIk951aDGtwSrlbi2ZuXx1sJ8eQ5mXDXKZnhcxbV0QXk6XV4e7tQL3q2Ld1Jq5UfyElJRo4cWcvhw4cBCAoK4v7O98HaVPKTEgDwbONLnf51MAuqUguVLWYze1atYO+vKxGtVrQ6Jzo98hgNu/TgzN5Udqzcg0EvF0836BREu4F10OrKnnZkOHOGtPkLyN+8GQBBp8Nr9Gg8x4xB6SzfvPRmPT+c+oElx5eQY8wBIMwtjKeaPEXPkJ4VG5nQp8PRlTKZSDpyebmDm1wf0fABCO0oN0qrpqhqaUcVVjxfWXD2hUdWwdb3YfMc2PMZZF6QlaO0LpU9O7vhVghhPa96dAnuIjejPPoNb93zVrnGuRncH3iQrGXfkrdpE5bMzBLNMO8G+NeRleySL+TeZM27E8XpSsV9KorJhFJ5VZ+KIgiqogXWy3n933//PU8++aTt/dq1a+nYsSMjR47km2++YejQoRw8eJBjx47x22+/AXD06FGsViuRkZG27SRJwmQyERAgkzur1cqcOXP46aefSEhIwGQyYTQa0elKCoa0aNHihscolbGw+eTJk6hUKtq0uSwM4eXlRVRUFCdPnrQt0+l0NkIBEBAQQGpq6hUjCUV/IEkmQMXJkydp0qSJjVCA3HJBFEVOnz5dJlKhEgQEoH7T5phFCW01kJUt91P9119/JSsri59//pnly5czf/58oqOjGTFiBA8//PA1qlA1qEFF4kolHgedxNKkVL68mI5oUFBPcOJF9yWoYn8hWR9EYGBrGtR/EZWqZJpRbm4iy5evRxDiUKsF7rnnHlqoI8lfFgsWCYVOhcfgCBwbyqohpdlsCadP8r/PPyQz4RIAdVu15d4xT2E2OfDbB0dIOJMNyPKGXUZEExDuVsoopcOcnEzahx+Rs2aNLU7tPnQIPk8/jcrHB4ACc4GNTGQb5X2FuoYyvsl4eof2rjgyYTHB2b/h8A/yq2iRlytUENkbmgyT1ZuqWLH17aAqph1VayJxNRRK6PKiXFOx6km5Y/qSvjByTZVQ/7IXboUQPt7wcTZf2syv539lcMRgmvs1L9c4N5xPVCQO9etjOHGCvA0b8CjyOt8t8A+T77mZifmYDJZbql27EiqtlmeWriyxTJIk0uJikEQRz6DgCkuBUt3mD72YWFyvo7a/vz8pKSlFO5M/SElOxtXVFUdHR+6///4ShnhQkNzraOzYsTRt2pT4+HgWL15Mt27dCAkJASA/Px+lUsmBAwdQKpWIokhaWhoAYWFyLcJ7773HBx98wMKFC2nUqBFOTk5MmTIFk8lUYv5O1ytmK4KPjw/u7u6cOnXq1k9OKbi6kLxYuarkMvk8iaK51NSy0qBQKK4Z58reHcWZC45OOsySdL1WIVUKt+Uq9PDwYNy4cYwbN474+Hh++OEHvvnmG15//XUsFou95liDGtwUxUo8opOZyWfi2ZOjBxU8ECLSLnEuBReP4+qqoXbwRKKiBqC4on+EKIrs2bOHHTt2YjBoCQlxY0i/PrjsKiT/XCwADlEeeDwQidL1slv6yoe3IBaw7YdlHP7fnyBJ6NzcuXfMeMKat+Xg33Ec/PtfRIuESq2gVb8wmnQPRlmK7nRpBoGo15Px9ddkfLMYySCrS7j07InPs1PQFt2MjVYjP53+ia+OfmWThg1xDeHJxk/SJ6xPxZGJlONwYCkc/blknURAU7n4tuGD4ORVMfuuZNx1aUdVFfUHgFst+H6oHPkqJhYud1eDtrLYiU19m9r+H7VuFEdHHS3XODeDS69eMqlYf/eRCid3Lc6eWvIzjaRezKNWVPl6SgiCUGoKkqOzKyZDIYKgKHeK0p3C9dIz27Vrx19//QVcjlRs2PwP7dq1A8DFxQUXl2sjho0aNaJly5Z8+eWXLF++nI8//tj2WbNmzbBaraSmptKxSGnM1dUVURTx9pYddTt27GDAgAE88sgjgPxsPnPmzC2n2CsUCoYNG8a3337LjBkzrqmryM/Px8HBgXr16mGxWNizZ48t/SkjI4PTp0/f0j41Gg3WokiOKMoEqF69eixZsgS9Xm8jQTt27EChUBAVJWdI+Pj4kJSUZBvHarVy7NgxunbtaltWbKmYq4msrF3yD8xmM/v372fPnj3ExsaWKaxTgxrYC8VKPOesBbxy5BIpJjMOCgXPeCcQmvYmJoWEKNahYcOXKNA3KtHcJzs7m7Vr15KYmIgoKoiKqsvQlg0Rf76E0WBBUCtw6xuGU5sAm9fg6jSrxNNHObj6a8SCi6iVEg279qDTI2PIiDfz41v7yEktBKB2Ay86D4/E1fvafNTSmqg566wot/9O3qfzsRR5dBxbtMDv+Wk4Nm0KgEW08Nv531h0ZJGtaV2wSzDjm4ynT1gfVIoKSDEy6eWmZQeWQPy+y8ud/aHxUJlM+Na77uZ3E+66tKOqiqAW8NhaWHY/pJ6QicWYdeBk314D1QGP1n+UZSeW4aZ1w2Q1oVHaX17SpUcP0hYsQL97N9bcXJSurjffqBrBJ9iF/EwjmYn6cpOK60GpVoOhEKvZdPOV7wDy8/M5d+6c7X1MTAyHDx/G09OT2rVrA/DSSy+RkJDAsmXLABg/fjwff/wxL7zwAo+NGs36NetY+fsq/vjjj5vur7gY2cnJiUGDBtmWR0ZGMmLECB599FHmzZtHs2bNOH36NFu2bKF169YMGjSIiIgIVq5cyc6dO/Hw8GD+/PmkpKSUq2539uzZbN68mTZt2jB79mxatmyJWq1m27ZtzJ07l3379hEREcGAAQN44okn+Pzzz3FxcWH69OkEBQUxYMCAMu8rNDSUdev+4uzZGPz8BPz83BkxYgQzZsxg1KhRzJw5k7S0NCZNmsTIkSNtNnK3bt2YOnUqf/75J+Hh4cyfP/+6zaPN4n+AVGzatInly5fzyy+/IIoigwcP5o8//rBV+tegBncCVqvEjwlZfJqRiBUIdVAzyeF3tCm/IAI+Pvfg7/ca3l6uZCku58GfPHmSDRs2YDKZUKvVtGvTneh0FdbfYwBQ13LG86Eo1D6X8zmvTLNSiLnsX/M9p/fsxWRxwN03mkHPDKN2VD12/HyO03tkI1/nqqHjQ5GEN/cptRC7tCZqOXsOcezjxRB7Cj9VDs4hwfhOm4ZLzx4IgoAoiay/uJ6PD31MbG4sAL46X55q8hQD6g6oGGnYpH9lInH058sysAoVRPeFZo9CnS7Vuk7idlBDJO4AfCLhsb9gSX+5n8X3D8Ko3++qGouy4NkWz7IuZh2phalsvrSZnqE97b4PbZ0wNHXDMZ07T/62bbgVSX7eLfDwd+LMwQyS4wqIsrPss7IoVcZ6RRpLZWL//v0lPN9Tp04FYNSoUTYVoqSkJOLi4mzrhIWF8eeff/Lss8/ywQcfEOQfyGfvfkyvHje/1oYPH86UKVNKyLYWY/Hixbz11ls899xzJCQk4OnpSfPmzRk4cCAAr776KhcuXKBXr17odDrGjRvHwIEDycnJueXj9vT0ZPfu3bz99tu89dZbXLx4EQ8PDxo1asR7772Hm5ubbU6TJ0+mX79+mEwmOnXqxF9//XVLvTOeeOIJ/vnnf3TpMpz8/AKbpOzff//N5MmTadWqVQlJ2WKMGTOGI0eO8Oijj6JSqXj22WdLfFcAQlGsorpEKgSprBUtVyEoKIjMzEx69+7NiBEj6N+/P9pq8GTNzc3Fzc2NnJwcXO8y78t/EXqrlalH41l5RI+gkejupWCwYQ6S4RyCoCQ09Gl8vIdjMgmEhsoqFxcuGNmwYTsXLvyLQiHi6xtEi9COqHal4yfk46oTcelaG9duwQhXpSglJhY1Nruwl20/LMWQn4cgKGh0by/qdhhI9qUczm07g1FvAQEadQqizcBwtI7XN7aLx/TwAGNcHOmffU7Bdrnbdp7Wn9DHB1N/4mAUGg2SJLEjcQcfHvyQk5lyIZm71p2xjcYyLHpYmZrW3RKM+bIM7IElkHjw8nKPMGgxCpqOkItqa1CDO4W0M3KDvMJMqNMVRqz8z5HZBQcW8M2xb+heuzsLui6okH2kvP2O3F17yBAC3pxVIfuoDBgMsOd/KWxYfgHfEFd6jmmAi8vNUxYNBgMxMTGEhYVdYyyXWC8/n+yUJNQODngFBVfAEdx5mJLywSqh8tWh0Nw4lTY2Npbw8HD27dtH8+bNb7huVlYWhYWF102nqk4wmbIwGOJRqZzR6cLsNm6ayUyiwYybWkmoY8Xa2De6xstqO5f7Tjxz5kyGDBlit46ENajBreJCgZExx2I4pTegclLxiCqXNjkvIUkmtFpfoiJn4ebWxGawa7WyR2bdutXExxdgsWhp1KANQdkB5PyWirNGJNPHBceBYWgbuyBcde80GiE1IYf9v31P3JHdAHgG1qLLyMfROAWw7efzxJ/Pw8vFin+IM11HROMXdmPiWpy65WDJIe2jZWSvWg1WCyiUuA0YQNCI0Vgd3TFLcDL1MAsPLuRAygEAdCodoxqM4tH6j+KssXN/mNRTsO9LOLICTPnyMoUa6vWHFqNl9aZqJgNbg7sEPpEykVjaHy5sgg0zoNfsyp7VHUWfsD58c+wbtsZvJdeUi6vG/g4yXZvWZC5Zgn7vHruPXVkojgoLWh0qhYgpV29T/issvCwpfjtQqmWzqqpEKuwBQalAslpLKEBdDbPZTEZGBq+++ipt27a9KaEAUCqLO1HfgYY+FQxFUaqxKNm3nlhdlN1w16c/PfHEE/acRw1qcEtYl5bDpJMXybOK+GqUTAv+G878Tp7ZAX+/VtSv/wqC4EFWlvyQ8PCQ2LVrNxs2bMBqtVKrlitdm/ci5y8ThampBLlacW3hjWOnEAosShISSj5gJEni5M4d/PLxGjClolAqaN67P4179uPUzlSObDwsd8RWamgzoC5t7gtCUUoh9tWwGkxkrvoL049fQb6cUqRr2w7vp59CGxqKJMHhuAssOP8RO9I2AKBRaHgo+iHGNhqLp4MdVXBEK5xeC3s/h5itl5d7hstEounD/8kc9hpUQdRqAYMWwU+Pyt23A5pC4yGVPas7hkiPSOq61+Vc9jm2XNpC//D+dt+HrmVLUCgwX4zDnJiIupQmYtUNxYIetes6olJKGPJNYLXg4aGSI9CZco3U7UBRFDUTrVYkSSp3k7oqhSJhE8l6feN/x44ddO3alcjISFauXHnd9UoMW+SYslqttz/HSoZQ5IWURPuSClXR9WOtJulPtx0zPnHiBHFxcddIft1///23O3QNanANLKLEOzFJfBQna0S3dFbwtHUWWv1BTD4OeHo8j5vboxQWKmxKPFqtnlWr1nD2rNyELioqinv9WhO3Kh2rXomfr4Bb37o4RsgGugOUeMDos7PY+PUiTu7ai6nAF9/gULo/9hiC0pu1i06QlawHwD/cg6b31aFRM8cy9ejK27yZS3Pmk3XWhEZhwik8HO8JT+PUqhUAKfoUvjy0hA0XtqP2TkCtUTKw7kDGNxmPv5O//U5qQSYcXAr7voYcWQoXQQFRfaD1OAjrVOldrmsKoWtwDeoPgHuehe0L4I8pENwKPEIre1Z3BIIg0DW4K+eyz7EtYVuFkAqliwsO0dEYTpyg8N9/qz2pKI4KOzmBRqNCo1ViMlopyDOhcVTh5CR/brzNGguFUilL9kggWi0oVRVQ33aHISgEJIAb2LVdunQpc3+IYhSTinJm4VcpCIJsTkuSfclkcWuK6kK7yk0qLly4wKBBgzh69GgJzd7iE3k3MM8aVC2kmyw8dSKWbVlyOs4Iz1x6Z05CIeWj0fjQvNlCPDzaljBAExIusHz5KptGds8u3Qk740zeX0noC7V41nPBe0AYSqeSCipOTpCbK5F2ehvbv1uEIT8PjUZJ+x69CW7Zh9gDiRzffgRJAgedmlb9w/AM9cHTU7jpA8kYE0PK22+j37IVAXDxikQ5fDK1h/ZEUCrJM+Wx/NRyVp1ZhSHPAaVTPvdFdGNi04mEuoXa74QmHoa9X8KxlWCRpWrReUHzUdByDLhXfj5waapYZcl/rsF/BN1eg4u74NJuWPM0jPrjP5OWd0/QPXx59Et2Ju7EKlorRDbaoUEDDCdOYDhxEtfeve0+/p2EKMr3kOL6W0dXDaa0QgpyTbj76lCrZVno283EEQQBpVKF1WJBtFjvClJB0U9KsnMKTrG9eDekPxWTCpl5iYB9fo+K/0qkYvLkyYSFhbFx40bCwsLYu3cvGRkZPPfcc7z//vv2nGMNasDBXD1jj8WSaDTjqBCY5raH6Ix3APDwaE+DBgvQaoqa0mllUrtp0ya2b98OgLe3N/e37IlqfSYmfTaiUoWuW218OvqW6FlRDJM+i/XfrEAfux61yoRPaB16PzWFnBx3fv38OFnpZjQqgYjm3jTrHYYoaHBwkMlIYWHpHnVrfj7pixaRuexbuUuaWo3XqEepPXo8yTnOpGeb+Sf5V5afWUZuYQGi0ZHGAVG80nM0zWvduqReqRCtcPov2PUJxO26vDygKbR5EhoMBnXVsNZLU8Uym+2b/1yDag6FUk6DWnQPXNwB+76CNuMqe1Z3BI19GuOicSHHmMPJzJM09G5o93041JeloQ1XdBeurlAoZKeE2Syr/+lcNeSkFVKYJ2dZmM3y5/bgpIJSCRYLoniXOFeLve52NmzvrkiFguIQlSSJtnSo24XS1qkbREmykYyqinKTil27dvHPP//g7e2NQqFAoVBwzz33MHfuXJ555hkOHTpkz3nW4D8KSZJYlpjBa2cTMEkSYQ5KnhM+wiNzIwChoROpE/ZMiR9wVlYWv/zyC/Hx8QA0b9qMtlIUpjUpiIDa3wn3wVGIhU4lelbIEQ6J8/t3sWvlcgryTXi7Kmg/dASNuw9k96+xnNp5GJVFgY+vjkY9Iwmo64lCCdoiZ1Ry8rUeda1GJOe330idNw9rWjoAzp074/fSdDShoUiSxPGM/7Fg11LiM3NAVBLsFs7TnUfSt2E7HB3tcBMx6eHwctj9KWRekJcp1NBgILR+Emq1rPQUp6tRnP/scYWMvEYj/9kr/7kGdwE860CPN+CvabDpLWj4wF3bcPFKqBQqmvk2Y2v8Vo6kHakYUlFPJhVGO3UmrkxotfI9uVhS3NFFvvEX5soF1Xr9ZUGP24XNWL4LPPAgpz8BsgPenuMKxQZz9ScVcLnTtiTZ70Qpr3gsW+9mUmG1Wm0SYN7e3iQmJhIVFUVISAinT5+22wRr8N9FoVXkxTOX+Ck5C4DurmZG5E9AY01GpXKjQf15eHuX1HQ+duwYv//+O0ajEa1WS99OvfDdK2FKkZvHOXcIxK13GIJagUuRlKsoQnY2pCVms/f3NSSdOY4kOVM3yoGRL00nN8OZH2cfoDDXBAI0vzeAtoPCkQQVoggmE6Snl+5Rzzx0CtXit5COyYpNmpAQfF+ajkuXLgAcTDnIvP3z+Df9X9BCYHAA4xqNZ2DE/TjdQIa2zMhLhr1fwP5voFA+jzi4Q6vH5XoJFzvWZtgRV+Y/lwZ75T/X4C5ByzGy7HHKMdg0G/rNv+kmdwMaeTdia/xW/k37lxH1Rth9fE1oKACWtDTEwkIUjtc27qxO8PSUo5xZWaDSqpEkyMs12QQ9PO2keyF7re+OtB7gcltnOxv/d1P6kwwFMvOy3/EIgoBCAFGSxbeqejJdua2Whg0bcuTIEcLCwmjTpg3vvvsuGo2GL774gjp16thzjjX4D+JioZHHj8VyLL8QBTDe4wLtM19AQMLFpSGNGn6Co2Mt2/omk4l169Zx8KDcSyE4OJjeIR2Q1qZjsUgonNV4DonEIeryU8PTU364nD4tEX/sICc3/4LZUIiIE1H3dKd979bs/O08CSdiAfDw19H1kWgC6rqXmGtW1rUedUV+JsYvviDh9224KPIIcNPh/fRTeDz6KAqNhpicGBYeWMg/l/4BwFHlyGMNHmNUg1Ho1DpuGyknZFWcoz+DtUhEwSMM2k2QVZw017HWqwiuzn++GvbKf67BXQKFEu57R+60fXApdJgMHiGVPasKR2OfxgAcTT9aIeMr3NxQODsj5udjTkhAW7duheznTsHBQU6bzMwEUVBiMKswFEUo7FmnJdxlkQoqJvvp7lDGugKCoECSsGukAkApCIiShPVGlfJVBOUmFa+++ip6vax6M2vWLPr160fHjh3x8vLixx9/tNsEa/Dfw4aMXCacuEiOxYqXWsHz2p8JzlwOQFDgcCIiXkN5RZO35ORkVq5cSXq6nFp0T5v2NE7yx7RBjk44RHvi8WAESueSxdgODoA5m32rVpN87gSSpMArKIyuIx7Akqdg3efHUUkGPF0FmvcOoeV9oSjVJRNur/aoS2YzWatWkbl4CVKBHkeFCkXX+wma8SjOwb7kGHNYtHc+P576EYtkQSEoeCDiAZ5u+jTejt4YjdevybgpJAlit8H2hXB+4+XlwW2h/URZzakCijkrAlfnP18Ne+Y/1+AuQeg9clf3C5vhiy7wYkwlT6jiEeURBUB8XjwGiwEHlX2LjARBQF2rFsZTpzDFx1d7UgHyfT8wEIJrSSS6GPB2N9o9jfJuS+u5HKqoGNw956n4gWTn2pPiUavBaSo3qejVq5ft/7p163Lq1CkyMzPx8PC469hnDe4MrJLEvNhk5semANDECSaYXsEp7wQKhZboqDcJCHgAkI15q1XiwIF9bN78ty0dr2+r7rhuLcSUnwMqBe59w3BqG1DqNXl0yw5++mgVoiETLxcVTe8bQN2WXTnw5wWSzueAVcApwJ0BE8IIrFN6c7krPeoFBw6SunAh5ouxAGgjowia/Aym4EZInhaWn1zOp0c+JceYA0DnWp2Z2mIqddzrYDDInbXLpXIkinBmHWyfD/H75GWCAurdD+0nyfUS1QxX5z9fDXvmP9fgLkKjoTKpKMyEpCMQ0KSyZ1Sh8HTwxEXjQp4pj7i8OCI9Iu2+D3VAAMZTp7CkpNp97MqEzkmBRiUiSBVQTF2FTKCZM2fyxhtvlFgWFRXFqZvUyfz888+89tprxMbGEhFel7denEmfPn0rcqp2R3JyMrNnz+bPP/8kISEBX19fmjZtypQpU7j33nvttp8uXbrQtGlTZs+eCNg/UmGLFNl31ApBuUnFo48+SteuXenUqRPh4eEAeNorIbEG/zlkmS08feIimzLzABjilkm/nMmopAIcHWvTqOGnuLjUs0mMpqYWsn79Ri5ejEGjcaRxwyB6uTfG+ldmUTG2Ds/h0aj9rk3zKczP459vPuPoll0Y9L4EhQXSbfSTpF1Sse6zf7GYrKhUClr2CSGoUSAeAdd/QigUIGZncGnBZxg3/S0vc/fAe9wTuPbpg9miYF/cAV48PpfYArnWqK57XZ5v9TztA9sDt6FyZLXA8VWwbT6kFamzqByg2Ug5zckzrPxfSBXAlfnPV54Xvd6++c81uIvQ9GH49Wn5/12fwOAvKnc+FQxBEAhzDePf9H+JyYmpEFKhdHMDwJqbY/exKxMqjRy1tZjsTyqEisoXKicaNGjAhg0bbO9Vqhubfjt37mT48OHMnTuXfv368d3Sbxky9mH2bNhBs06t7DYvezigTSYTmlI8T7GxsXTo0AF3d3fee+89GjVqhNls5u+//2bChAk3JVXlg634pNRPr8yGu5Uou1CsKoXcuVx9vbzgKoByJw9oNBrmzp1LREQEwcHBPPLII3z11Ve2BmN3Am+//TaCIDBlypQ7ts8a2B//5hXQc/8ZNmXm4aAQmO66g4HZT6CSCvDx7kGrlr/aCEVCApw4kcjKld+RlHQajUakef3ORJ1viH6nXIjs3D4Q3wnNSiUUMYcPsGzaBE7t2IJCAc169KbLmOnsX5vD7l8vYDFZ8Q9z4/5nmxHVLgi1Wrjuj1+yWND/+C2Z4x8hbcNOQMBt4CBCv/8Ot379uJQfz/QNs3jj4DRiC07jrnXn1Tav8nP/n22EAkqqHGk0sgiTRiO/LyZRJWA2yI3qPmoOq56QCYXGRW4ENuUo9H2/2hMKuJz/7OEhR6ZycuRXD48aOdkaXAeCAPe9K/+feLjKGHUViQDnAADSCtIqZHyFqyzIIubmVsj4Nah4qFQq/P39bX/e3t43XP+DDz6gd+/ePP/889SrV49Zr79Bs4ZNWPT156WuL0kSdevWvaadwOHDhxEEgXPnzgGQnZ3N2LFj8fHxwdXVle7du3P8+HHb+ufPn2fAgAH4+fnh7OxMq1atSpAhgNDQUN58800effRRXF1dGTeudAnpp59+GkEQ2Lt3Lw888ACRkZE0aNCAqVOnsnv3btt6cXFxDBgwAGdnZ1xdXRk6dCgpKSm2z2fOnEnTpk359ttvCQ0Nxc3NjWHDhpGXJztAR48ezZYtW/jggw9wdq6Lm1tjYmMvArBlyxZat26NVqslICCAF16Yjl5vwWSSBV5CQ0NZuHBhiXk3bdqUmTNn2t4LgsAPX37B5GFDCHBzZfbs2aUeb1VBuUnFV199xZkzZ7h06RLvvvsuzs7OzJs3j+joaGrVqnXzAW4T+/bt4/PPP6dx48YVvq8aVBx+TMqk/8GzXDKYqK1V8LbmAxrlzAcU1A1/kUaNFqFWuwKQni6ya9dB1q1bQWFhLh4e7jzYqifRR6Eg2UiuwhGvxxrgfn84wlW1DyZDIeu//JhVc2eQn5WJR0AQj8yeg19Ia1Z/cIqk8zmo1Ara3B9G73ENcfN2RK+XU3BKS7EpPHyYmCFDSZkzB1dDIi7RdXB+/yvcJz5Lvlriw72LGL3qWQ5m7kLrXMDI+iP5c/CfPBT9ECrFZS/RragcYcyHHR/AB43hz6mQfVFuVtftNXj2GHSfCc6+9vliqgiK859DQyEsTH4NDLx7CUVxTY3RWNkzqcZoMgyUWkg/DckVU8BcleDlIMvnZhgyKmR8pWtRpCLn7iIVolV2GytV9i/MstUIVJFU8LNnzxIYGEidOnUYMWIEcXFxN1x/165ddO/e/fICSaJH53vZfWBvqesLgsCYMWNYvHhxieWLFy+mU6dO1C2qxRkyZAipqamsXbuWAwcO0KxZMx566CGysmSHYH5+Pn369GHjxo0cOnSI3r17079//2vm+/7779OkSRMOHTrEa6+9ds18MjMzWbduHRMmTMCplIeru7s7IKtODRgwgMzMTLZs2cL69eu5cOECDz30UIn1z58/z5o1a/jjjz/4448/2LJlC2+//TYgE7B27drxxBNPcP78Ls6c+Yfg4FokJCTQp08fWrZsxd69R1i4cBFLl37Nu+++hSDIac5yUfcNvogifDxnNl379WfnwUOMGTPm5htUIm5bs9LDwwMvLy88PDxwd3dHpVLh4+Njj7ldF/n5+YwYMYIvv/ySt956q0L3VYOKgVmUmHEugW8S0pFMAvc4mXgkfxquqgQ0Gm8aNvgAD4+2tvWzsgr44Yf1JCRcQKmUiAyPoLU5HOt2+UHnGeWG9t46KEKvDYPGnzzGuk8XkJMqex+a3defJj0eYuuKC1w8mYxg1eBcy5Ouw8Pw8nO8YYqNJSuLtPnzyf55JSCro4RMnUpU/wdJyxT5+ejvfH98BXmWHJQ6Pd2imjC9/ZTrdsIuk8pRth5x+9ewf4GcKw7gWkuul2j+KGjsoBZVxXG3107UdA63IxzcILInnPxd/gu4ux1Png7yTSqjsGJIhVCUWiJZLBUyfmXBapGtOYWqfIa/JElI5tJz50WTVf7MLCFWRHqVWlHm1KE2bdqwZMkSoqKiSEpK4o033qBjx44cO3bM1hbgaiQnJ+Pn53d5gQS+3r6kpKaUuj7IHvvXX3+dvXv30rp1a8xmM8uXL7dFL7Zv387evXtJTU1FW3RDf/fdd1m9ejV//fUXDRo0oEmTJjRpcrkO6s0332T16tX89ttvTJw40ba8W7duPPfcc9edy7lz55Akiejo6Buem40bN3L06FFiYmIIDg4GYNmyZTRo0IB9+/bRqpWc6iWKIkuWLLGdr5EjR7Jx40Zmz56Nm5sbGo0GnU6Hn58PVmsBSqWKTz/9lODgYBYs+BhRFKhXL5qUlEReeeVFXnnldZRKmcxay3B59B86lIGPPEqIowZ3tR2k5isQ5Z7dyy+/zObNmzl06BD16tWjc+fOTJ8+nU6dOuFxpbZmBWDChAn07duX7t2715CKaog0k5knjsWyK60AMVfFYMUlWiUuIFvQoPXrTssWs3Bzu3xDi4uL44cf1nDxogKdDjq36EjQvyqsufmgFHDtGoyulT+5uUKJnEWLycSOn75j/x+rQZJw8fah15OTycnwZuU7h7GYRBx1CjoMqU1ggyDy9QI5ObJBd7XEoCSKZP/yCwnvfYQ5OxcFanwe7I/vtOdQeXqyL3kfcw7M4UzaRXBTUM8jjOntXqZ9UHtuhBuqHBn1mPf/gHL3chSOR0Flkht9dXxOLkhVlVLBXINqh5rO4RWAiCJSEbMFeKWyZ1OhcNHIho7erK/kmVQv2CIVyvJFKiSzSOLrO2+4TjapZJdr9BsjcFZ7BE3ZlPzuu+8+2/+NGzemTZs2hISE8NNPP/H444+XbYdXedPnzJnDnDlzbO9PnDhB7dq16du3L9988w2tW7e29YsaMmQIAEeOHCE/Px8vr5KNKQsLC7l4UU4Xys/PZ+bMmfz5558kJSVhsVgoLCy8JlLRsuWNxUfKqiZ18uRJgoODbYQCoH79+ri7u3Py5EkbqQgNDS1BwAICAkhNvbFwwcmTJ2nbth2SdDmFun37DuTn5xMfH0/t2rWL5io7F29UY9GoeXN53TIdVeWi3KTi7bffxsfHhxkzZjB48GAiI+1fIFYaVqxYwcGDB9m3b1+Z1jcajRivyCXIrckLrVQcyi3g8WMxJORZ0GaqGckG6ks/o9RZ8PMdgbf3k6Snq9FqQaMR2blzJxs3bsRsVuDpGUKPsBY47cxHFM0oPbR4DKyLJtAZk6mkxGjKhXOs/WQ+GfHyzahBl+606PsI23+OI/HsGQACI9zp8FA9XLwcUSjA2+fyj/tKz7jh5EkuvjaHpEMXKRB1qEIa4vvM09C2IYmk8vHWF1gbsxYAD2c3JjadyIORD5ZIc7oeSlU5MurhyPew72v0WRIeDtlofWtBpxeg0RBQVm1PRQ1uDTWdwysAdbrIr/H7wZALDq6VOp2KhFophznNorlidlA1MnjsDmtRlEFRAelPVRnu7u5ERkba6hxKg7+/f4m6AiSJ1PRU/HxlZ9/48eMZOnSo7ePAohvU2LFjGTlyJAsWLGDx4sU89NBD6HRyJD0/P5+AgAA2b95s285kMpGVlWVzRE+bNo3169fz/vvvU7duXRwdHXnwwQcxmUwl5ldaStOViIiIQBAEuxVjX10YLQhCmRv2SdL1CYNCobiGAJnN1/6OHXXy8VaHn2K5rZNDhw6xZcsWNm/ezLx589BoNHTu3JkuXbrQpUuXCiEZly5dYvLkyaxfvx6HMrru5s6de42cWg0qBz8kZTD9TDxGUaKWQckw86fUdjiAUulERMQb+Hh3A2RDKj5ez+7dq203viYNo6hzKZrsnYXgAA4NvHDvHYrCQb6EiyVG1Soru375id2/rEC0WtG5udPjiUkU5Aey6v1jWEwiKq2SFn3DCagfRJZeID23ZLpJMaEQCwpI+/gTkhb/QIrRG7PWl6AxD+EzdBCFVolv9q7mp/PLsLrGodQIDIkcwqRmk3B3cL+l82JTOUrR43RuBerDX2LW56M36XDw8sOz33PQ8oEaMnEXoqZzeAXBvbacIpgbL3fZDrlxxLA6Q62QDR6TaLrJmuVEkUe/Wlg0twBDvmy8OTqXT0lHUCsInFX6dZWZcAmz0Yi7XwDamxjA5d13eZGfn8/58+cZOXLkdddp164dGzdutIngSCJs3LaJtq3bALLSZ2lqn3369MHJyYlFixaxbt06tm7davusefPmJCcno1KpCC3q1G40GsnIyLCpUe3YsYPRo0czaNAg21xjY2Nv+Rg9PT3p1asXn3zyCc8888w1JCQ7Oxt3d3fq1avHpUuXuHTpki1aceLECbKzs6lfv36Z96fRaLBardg6aQsC9erV45dffgEkJElAEGDnzh24uLjY6o59fHxITk6yjZObm0tMzLX9dYppR3X4CZbbSinOfXvmmWcAObS1YMECJkyYgCiKRSfYvjhw4ACpqak0LwoFAVitVrZu3crHH3+M0WhEqSwZEnzppZeYOnWq7X1ubm6JUFcNKh4mUWTGuUQWJ8jN6Tqoc+mRPQ8XdSY6XRj1ouei013ufpudHc9vv/0PtToBBwcV3Vt0Jni/isKcXAwODtCpDk6tvRE0AibT5foHhTmZFTPfJ+mM7J2IbNOBNoPHsOOXBBKLVMmCIt1pN6Qe+SZHsnOun25i2beN5JlvYE5IINvsg6pDN6KnPY7ax4eDKQf56NBHXMy9iNXgQkOfNrzVdwINvBqU6/w4KAsJuvgNmRuXkZdjoUBUoPQMx6PTaDw79MfB6b9NJkwWkdQ8A8k5BrIKzGQXmMgpNJNTaCa7wIzeZMFkEeU/q4i5yAhSKRSolQJKhYBGpcTFQYW7oxo3RzXuOjU+LloC3R0JcnfExaFyJPpqOodXIPwbFpGK43c1qRAqWMRe1OcDoHQuPf++uqIgr4hUuJSTVAjCdVOQJIWEoFagdNSgKGOaUkVh2rRp9O/fn5CQEBITE5kxYwZKpZLhw4fb1nn00UcJCgpi7ty5AEyePJnOnTszb948+vbty/LF33Hg30N89slnN9yXUqlk9OjRvPTSS0RERNCuXTvbZ927d6ddu3YMHDiQd999l8jISGJiYli9ejX9+/enR48eREREsGrVKvr3748gCLz22mtljghcjU8++YQOHTrQunVrZs2aRePGjbFYLKxfv55FixZx8uRJunfvTqNGjRgxYgQLFy7EYrHw9NNP07lz55umWF2J0NBQ9uzZQ2xsHDqdmiCHUJ5++mkWLlzI1KmTePLJiZw7d5o335zB5MlTURSFLjp37sZ33y1h0KD+uLu78/rrr19jw16J6tADrtzWiiRJHDp0iM2bN7N582a2b99Obm4ujRs3pnPnzvacow333nsvR4+WVPN47LHHiI6O5sUXXyz1y9BqtbaioBrceaSZzIw9FsueHDnfd5TTETpmvEuqGISfX2eiIl9BqXQE5GKoffv2sW3bdgwGLeF1vBgQ1haHrXokyYJzkA6/wdHkqZ3Iy5MJgFIJ7u4Sycc38ef3izAbCtE46ug2ZjyCMoo1C09hNlhRaZW0HxROw05BJCUL1003SY/J4vg7H6LbukKek39tXMbMwqtTG7IsqXy2axabL20GwE3jxpgmT9IpoCd1nG/dc2QsMCMeXI5ix/s4FMYRqAZjnSjE9tNQNB6MVvffIBOSJJGaZ+RCmp6YdD0X0vK5lFVAUo6BpBwD6fnGClcGdXVQEe7rTLS/C9H+rtQLcKVxLTcc1BVrENR0Dq9A+NaXm0KmnqzsmVQoCi2FADiqHCtkfGuuLJ1ZLC17t6AwT47sOLrYtzZNkiTEIqeq4gYG4p1CfHw8w4cPJyMjAx8fH+655x52795dQlAnLi7OZugCtG/fnuXLl/Pqq6/y8ssvU7dOXX7+ajkNGza86f4ef/xx5syZw2OPPVZiuSAI/PXXX7zyyis89thjpKWl4efnR+vWrW1F4fPnz2fMmDG0b98eb29vXnzxxXKnrNepU4eDBw8ye/ZsnnvuOZKSkvDx8aFFixYsWrTINqdff/2VSZMm0alTJxQKBb179+ajjz66pX1NmzaNUaNG0apVPwoLDZw7d5Lw8Gj++usvnn/+edq0aYKHhyejRz/OSy+9aqujeP75l4iLi6Ffv364ubnx5ptvlhqpEIs8BlWfUoAglbM/uoeHB/n5+TRp0sSW9tSxY0ebVNedQnEnw6u1fq+H3Nxc3NzcyMnJwdX17s2zrQo4mKPn8eOxJBnNuCgFpqi/JbpwNSaTA1rtDMJCh6DVyj+TgoIC1q5dS2xsLFargrDgaPor/dAky2TEqY0/7v3qIBQZeUaj/KM06nPZtuwTzuzZAUBQdAO6jp7E/rWZxP4rR0YCwt24d3Q93Hx0GI0QG0tRzcbluUqSRO6ff5L4yVcYcw0EaZPxHzUM5ycmcT5Zw/+SV/LdqW8xWAwoBAX3h9/P6AajcdG4kpMjy506lvGZbigQydz1J3mbvsKamYhSIeLi7Ypn73E4tLq7ayYy9SZOJuVyIjGXE0m5nEnJIyZdT8FNFFI0SgV+blo8nbS4F0Ua3BzVuDuqcdKq0KgUqJUKNCoFmqLCS4soYbGKmEUJk0Uktyi6kVtoJrvQTHKOgcScQrILSs9FVysFmtRyp1WYJx0jvGkd6omqnEWdN0JiohwlK03fonh5da2pKP6dXl2ndEew/xv441mI6gvDl9/hnZcN9jg/S44tYd6BefSr04+5Hefad4JAwtSp5P61Fr+XX8bz0eunzFQ3LJ+5m6zkAnpPaEZgXY+bfgcGg4GYmBjCwsJumH4tWq2kxl4AwDcsvISxXl1hTi1AMllReTmicLzx82nbtm3ce++9XLp0qaSCVCnIy8sjLy8PR0fHChf4uRPIyzuOJIk4OUWiVF6+mEQRLBb5VZJkpWGFAlSqsjmMTuYXYhIlwnVanFUVR1RvdI2X1XYut/Xy3Xff0bFjxxrDvAalYnlSBtNPx2OSJOpoRZ6xvIZP4SnUak+aNf0Ag6E9WVnyTTw+Pp4//vgDvV6PUqmkZVgHIi6ARqNH0CrxeCACXeOSMsVaLVz89zDrPp1PflYmCqWS9kMfwTu4E39+eobCPDMKpUCb++vQtEdtFAqZvJSWbmK8GEfa++9TeOQwSglU4U0Ifns+ni3rszV2D69v/oYkQwyCykJD74Y80+wZ6nrIuttXF4jfEJKE4dhGEtZ8gSEpFidNAWoPF8wtJ5IV/iCFTlqCzOBQ+c6tEiiv4ZNTaObwpWwOXsziWEIOJ5JyScoxlLquUiEQ7OFImLcTYd7OhHrrCHBzJMDNAX83B7ycNBUW+s03WojPKuBsSj6nknM5nZzHv/E5pOYZ2X8xi/0Xs1i0+TzuOjXdon0Z0DSIe+p6o1TYZz53Y+fwKiGR61xk0ORfXwazsmDP85Nrkj25Tmr75+4DWFLlpnrK6nghXgeSJJGVZiI7X01GjhZjjP2uUWuR9K5CqbwrCAWAJBb5nm9wzzMajaSlpTFz5kyGDBlyU0IB2FKb7obzJEkSkiQfjyCUPB6FQnZilrejtq2mohqEKspNKvr27WvPeZQbVyoJ1KDyYRJFXjubwNJEWTO9sy6TR/RT0KHHxaUhjRstwsEhEIMBCgok/vnnEPv3b0GhEHFz9aaVU3NcjxpwdzGiDnbBa3g0Ks+Sd3iLycT2FUs58OevAHgE1qLHuCmc2SOyf53cndMryJnuj9XHu5ZziW2vTDdRYyJz+XKyln2LZDEjODjgOnIsjv0GY6yVy8vbXub3C79jtnjjSm2ebv0wPUN6ljBuiwvEb2psX9wFG98g89gFDAZ3PNxEaPk0NB+FRuuEhqqn9HMrho8kSZxP03PwYhYH4+S/s6n5paYthXrpqBfgSv0AV6L8Xajj40xtTx2aSlJhcdaqiPZ3Jdrflf5N5JMvSRJxmQXsjclk14UMNp1KJavAzKqDCaw6mECQuyNDWwYzsl0Ink63lz5R3Dm8+FwXFJQua1xdUGUkch2LjODi3i5VBPY+P2mFstHvq7u1xpdldRaYEhMA0NQKuqXxqzIyU02kZaqwiAq8/B1wcLTfNWq1yJFPpapy6rTsDUmSwFJkLCuvb9X+8MMPPP744zRt2pRly5aVaexiUnGjOoLqg8sPu6tJRTHKy53EogepshokQN29eRY1uONINZoZezyWvTl6BGCU7gD36ueiQCLA/wGiomahVBbfqQ3s2vU7hw5dxGLRUiekLi2yA3GK1ePuYsH73iDceoYgXJVukhYXy18fvU96XCwATXrcR93Wg/ln2QXys4wIAjTrGULrfmEoS1HIKJZwTdp5AuNnb2MuUpbQtW6Dz9Sp5Dn4sS1rLUuPziXHmIOAwPDmvRnoMwGV6CyTkVvxJKeehPUz4OzfGC0a8qx1cWr3ALR/HBxLhnurktJPWQyftIICdp5PZ+f5DHaezyAt79o20CFeOlrU9qBJsDsNAl2JDnDFWVv1bzuCIBDi5USIlxNDWgZjsYocuJjFn0eTWHMogYTsQhZsOMNnW87zSNvaPNk5HG/n8n9pxZ3DKzVdyE6oMhK5xZLOUtWqcrf3+UktkPXyy0oqbslZYDZjSZYjPeqgu4dUxJ4uxGxV4BeowlEnPyfsdY1aiyRBlVW8SVmZYb3CM3QDUjF69GhGjx59a0MX157cFZGKK1N47Xc8kiTZvoIbnP4qg7vkqq9BZeNgrp4xR2NJNplxUcJk1RLq6X9HEFRERrxGUNAIm4c/JSWFH3/8kczMTNzdFXSs35Jah7QojHk4+inxfKg+DlElLXVJFDm49ne2/bAEq9mMo6sb3cdOIuWiJ39+Khdiuno70H10fQLqul93nmJhIeavPiJ96QZMohonTx8CnnkKh073cir5Ep8feYEz4iYUGhNRHlHMaDeDRj6NSjyIy+RJzkuBzXPg4DLZqBGUiE1HYa39POogv1IrrqqS0k9pho/BamZfYgZbj2VzLD2NVGvJAjqtSkGTYHea1/agRYgHzWq735ahXZWgUipoU8eLNnW8eLlPPf4+nsyX2y5wLCGXL7fFsGLfJab2iGRk25DbqruorkSiGFVKIrfYW1iFSEVFnJ/E/EQA/HQ3Tze51SiJOSEBRBFBq0Xp7V22CVVxGI2QdMmARmXF1fva4vPbvUZtpOJuiVQUSwqryt7Fu6woJhV3Q6RCkuTvXRBUdj1PJTld1WcVNaSiBreNlcmZPHf6EkZRIlxrZZL5FXwMZ9FofIiM+ARX1xaYTPIN+siRI/z+++9YLBZcXV25L7ADLvtNgAVNuCueD0ejcit5J9dnZ7H2k/lc/PcQAHWat6J53zHsWJlAVnI8AA06BtL+gbpoHK5/Sev37iXp1dcwx8Xhp9Qg3vcQDqMmYHDQ8v3hb1l96VtwzMRJp2RC02mMqDfC1sCuzJ5kUwHs+gR2LASTLMVIvf5w70wULnVRxlZ9pZ9iw0enk4hJ17P9bDo7zqVzJD4HqyghWQWwKnHwUNIszJX24V60r+tNs9ruaCuwiKyqwEGtZEDTIO5vEsjmM2nM+99pjiXk8sbvJ1hzKIEPhzcjxKti8turOqqURG6RKhLKqsPU7H1+jFYjl/IuARDuHn7T9W81SmIoah6mLWomdjdAFCE7xYBSIeHufa26xu1eo2aTHLFVaarOdXc7kIqs2hulPpVrXEm6q0iFKBbV0pSh6e2twFqs/CSAohr8BmtIRQ3KDaskMedCEp/EyeH3jo4ZjCqYjCOFOGhbExj4IdnZPmRkgCRZ2L//H86e3YtKZaFO7TA6F0SjPCzL+jl3DMKtd+g16U4xhw+w9pP5FObmoNJo6fzIGKxSA/769ByiKKFz1dB1ZDShja7vRbPm60mbP4+s5T8AoPL3J/jNWTh37MiWmN3M3f0Ol/QXUbiZ6VKrCy+1eYlA59Jj39f1XIki/LsCNr4JebLnkKAW0HM2hMha3VpK6Z59Bcpcn1GBsFhFdp7N5OctWexLTCEpu2RhdZi3E23DvKjv40W/Dm74uP93byGCINA1ypdOET6s2BfHu+tOcyQ+h74fbmfBQ03pUf/mnuO7DVVKIregqJZCV3UKjO19fmJzYrFKVlw1rvg4+txw3fJESQwn5Ciwwy00AqvqUCggKzkPqyjgEaC75vPbuUYlScJS1P1ZVdoXXA0hmYvrKez7o72yl9ndQCokSSYVgmDfCJW1qJ5CVQ0IBdSQihqUE3kWK0+duMiGDDkFZpjjAfoWyPUT3t6PonN8iYICDU5OoNdn8+uvfxEfn4VK5ULPtlE0PesKhSYEByWeQ6JwbOBVYnyrxcz2Fd+y//dVAPjUDqXrY1M48HcuCadlub46zXzoOiIahxt0RNXv3ClHJxJlQ9996FB8X3ieHJWJl7a9xB8X/gDA382Xl1u/TLfa3W7dI3dhC/zvFUgu6qHiVhu6z4AGg695MlVFpR+zVWT3hQz+OprE38dTyMixYMlxBKUVrUZB8xAPOtT14p5wH4I8HTGZZMPDtWJk8asdlAqBEW1C6Brly5QVh9kbm8mT3+5n9qBGDG9du7Knd0dRXLNUJYhzgSwpfXXtUmXC3ufnVKYcSajrXvem963yREkMJ4tJRb2yTagaQK0SKUjPxWRR4h18rXrl7VyjVosFSRQRBOHuIRXFRdq30cW7NFwZpbgbomCXSYWdIxXVqJ4CKoBUdO/enQsXLnDhwgV7D12DSsSVaT+JViOPHr3A2QIjWgEmqH+gRcFKFAoNUZGzgCE2ff0LFy6wdu1aDAYDHh4ONHe/B/8dZnAxow5yxuvhaFReJa3T7JRk/vzgHZLPy12wm/bqS3Cj+/n7q/MYCyyoNAo6PhRJvfYB170ZWfPySH33XbJ/XgnIRYYBb72Jrm1b1sWuY+6euWQZsxAQeLjew0xsOhFnjXOpY10XGefh75flBlsAWjfo9By0fhLUpUuHVBWlH4tVZPu5dP46msT/TqSU6NXg6aqmXYQvzfx96NrYA91VhdVVIaJSFRHo7sjyJ9rw8uqj/LQ/npdWHUWnkVOl/kuoMsQ547z86hF6h3ZYNtjz/BxKlVNCm/g0uem6txolkSwWCg/J4zs0uHnTM6geQgMZiXq0CjM6nQpJLTtJ7HWNWoxyZFelqTgJ7DsOc8WQCkuR9O7dEKWAiiMVlmLlp2pyPdmdVAwaNIj09HR7D1uDSsLVSiGH8/N5Lf4S+U4m/HQik8XZhBoPo9H40rjxZzhomxAbC46OIjt27GL37t0A+Hr70lGqj3Deit6qRNXCG9+Bda65UZ3csYUNX36MqbAQBydn7n18Ikkx3qz/+jQAPrVd6Pl4A9z9rg1bFyN/61aSXp+BJTkZAI8RI/Cd+izpgp7pm56xdcSO8IhgVvtZNPQu2wPTBmM+bHtfrp2wmmSVmZaPQ+cXwcnrpptXltKPJEkcT8xl1cEEfjuSSHr+ZbUmLycNvRr606dhAG3qeGI1K+SCzgJQCVUjolIdoFIqeOeBxug0KpbsjGXaz0cI8XKiabB7ZU/tjqGqEGfSZacE3pF3aIdlgz3Pz8HUgwA092t+03VvNUpiOHECMT8fhavrTSMVVaIvSRmREpOLWiUSGaXF00uw6zVqMsikQl3VDrqckESpwiIVxaRCfb3QWTWDKMqOOXvXVJiLeoRo/qukYsKECfYesgaVhCuVQnQ6iV/SM3nvfDIWg4JIi4VnmIyvOglXl8Y0bvwZWq0fhYWQn1/Ipk1riYuLQxAUNI2MomGsD0KBBRwUaDrVwe0+L65MPTQbDPyz5HOObVoPQFB0fdoMfoqdq1LITkkEAZr1qE2b++ugvE4/A2u+npS355Kz8hcA1CG1CXzrLRxbtmTNuTW8t+898sx5qBQqxjUex9iGY1Erb+GGJklwdCWsfw3ykuRl4fdC77fB59YNlzvlyUvKKWTNoURWHYznbGq+bbmnk4Y+jfzp0yjgmm7RamUVMQyrIQRB4PV+9UnOMbDueDLP/niYP5+5B53mv5NtWukSuZIEKcfk/32i7uCOywZ7nJ/0wnRicmIAaOrTtEzb3EqURL97DwC61q0QbuBNrjJ9ScqIpHPZANSOcrX7NWo2yOIAaoe7Ize0mFCgEG7Y+K48MBepZN09pEJ20ikU9r3RmYoiFer/Kqmowd2DYqUQJzeRdy8k8XNKFqigi9dFeqR/hAIL/g0GEh0929Z/Ii4umcWLt5CbW4hK5UHr4Ib47weT1oqTvyNO/SMQnR0pup+gUEBO0gX+/OBdMhPjQRBoM2goDm4dWPdFLKJVwslNQ/fH6lMr+vIT7+oHQcH+/SS+OF2WQBQEPB99FJ8pk0myZjJl/ZPsStoFQEOvhszqMIsIj4hSx7kuko/CXy9A3E75vUco9JoLUfdVyTaXJovI/04ks2LvJXacT7c1odOoFPSo78fgZkF0ivRBfYPiu0o3DKsxFAqBdx5ozOFL2cSk6xn/3UGWjWld2dO646i06yU7DnIT5Chi4M29+JWF2zk/Wy5tAaCRdyPcHdzLtM2tREn0O3YA4NSm7Q3HrDJ9ScoASZS4dFIu4K8VLU/YXteoKIo25SeNtuqwqK1bt/Lee+9x4MABkpKSWL16NQMHDiyxjiRJzJgxgy+//JLs7Gw6dOjAokWLqBMQAshRitLSuT755BPee+89kpOTadKkCR999BGtW9/8PidJko1UqFSVa4aeO3eO2bNns379etLS0ggMDKRt27Y899xztGzZskxjSJKEKMkF+oJQei1NaGgoU6ZMYcqUKbc0v+JIhdrOpK6iUO5vc+rUqaUuFwQBBwcH6taty4ABA/CsyZOolihWCjGpLTx3Io4DOQUIwBDNDjoalmB10ODj8yzh4UNRFlUQHThwnO+/30xurg4nnSvdfeuiviCSa1FAHS/8hwaTo1eCHpKSwGKROLNrM//++S1aZRYe3p50fewZTu5SEr8pFoA6TX3o+sjlYuyrw+yCaMK04iukn79AKxhRBwUR+PZcHFq24MfTP7LgwAIKLYVolVomNp3II/UfQaVQlT1cX5AJ/7wFBxbLevdqHXScCu0mXbduojIRm67nh31xrNwfT4beZFveOsyTwc2CuK9RAG6Ot+YZqiES5YObTs2DLWrx8aZzbD2TRlJOIQFud4cHs8rjYhH5D2wGmuunSlZnFKdxdgnuckvblcVZYMnMpGDfPgCcu15//CrVl6QMSI/PpzDPjEqrxL+Om13HNhUWggRKtRplFfK+6/V6mjRpwpgxYxg8eHCp67z77rt8+OGHLF26lLCwMF577TV69erFv9sPokGJoL02UvXjjz8ydepUPvvsM9q0acPChQvp1asXp0+fxtf3xo0YRVGUO3VzZ0iF2WwuNSKyf/9+7r33Xho2bMjnn39OdHQ0eXl5/Prrrzz33HNs2bKlTONLkoViz51CYd/v3izdevrT9Y73TqDcSXKHDh3i66+/5osvvmDLli1s2bKFL7/8kq+//pqNGzcydepU6taty4kTJ+w53xrcIYginMktZNTJCxzIKUCngEmqb+lkXIJK6UTjRnPx93sISRIQRZH169fz/fdrMRigcX1nuqsisZ4FBIHAHgEoWodwLlZJdrY8viAWsvfnT9m/Zhn5hVpcw7rQYeSbbF9ZSPypLFQaBV1GRNH7yYYlCEVCguz90mpBm3qWtMlPEff9n6SYfdEOfIiwX9eQEe3PY+seY86eORRaCmnu25yV/VcyuuFoG6G4chw3N/k1K+tyGB9JgkPfwUctYP/XMqFoMBgm7oNOz1cpQmG2ivz5bxIjvtpNl/c38/mWC2ToTfi6aJnUrS7bXujKT0+2Y1jr2rdMKGpwe5jSPcL2//I9cZU4k/8YzqyVX8M6Ve48Kgj5pnxb9PVWSUUxtFpwdCzd2M/bsAFEEYcGDdDUqnXdMcqiKGW1Vo2GngBxJzIAqBXpft002vLCVKgHQOtYtUjsfffdx1tvvcWgQYNK/VySJBYuXMirr77KgAEDaNy4McuWLSMxMZE1v60BQKG5llTMnz+fJ554gscee4z69evz2WefodPp+Oabb0rdj16vx9XVlZUrV5aIUvz22284OTmRl5cHwKVLlxg6dCju7u54enoyYMAAYmNjbePs27ePHj164O3tjZubG507d+bgwYMl9iUIAosWLeL+++/HycmJ2bNnl3rco0ePJiIigm3bttG3b1/Cw8Np2rQpM2bM4Ndff7Wte/ToUbp164ajoyNeXl6MGzeO/PzLqcSjRz/Gww9P5qOPviUwMAgvLy8mTJhgO84uXbpw8eJFnn32WQRBKBH1+eWXX2jQoAFarZbQ0FDmzZtXYp5Rzo7888fvqK9QknR3d2fJkiUAxMbGIggCP/74I507d8bBwYHvv/++1O/gTqDcv6oBAwbQvXt3EhMTOXDgAAcOHCA+Pp4ePXowfPhwEhIS6NSpE88++6w951uDO4RNWbk8ffoiiQVmAjVWnhPfItK8FUfH2jRt8hUuLu1RKsFgKOD7779ny5bdmExaWkdH0Dk1FH9zIa4eArp+4Vjr+KJSCeTng04HGuslfp8/k5iDe1CroNuw+3ELHsivn8VRmGfGK8iZoS+3okHHIEwmgcJC2dNVHGZ3d7WS/+N3xI8fj3TxLO7eKjxenYV20gxWJa7lgd8e4GDqQRxVjrzc5mUW915MqFuo7diuDNdrNHL2kkYjvzcYIPPsOVjSF36dAIWZ4NsARv8JQxaD2/UfsDeC0YjtOOyFLL2JTzad4553/mHC8oPsOJeBIEDnSB8+H9mCHdO78VzPKII9q9ZD7r8ElVLBgy3ka+ZCur6SZ/MfgakAzsq1WdTrX7lzqSCsv7geo9VImFsYEe4RN9/gFpH39/8AcOnV64brXakoVRqqSkPPYpw/mAZAyA36GpUXxoICADS66nW/jYmJITk5me7du9uWubm50aZ1G3bvk+tqhKtIhclk4sCBAyW2USgUdO/enV27dpW6HycnJ4YNG8bixYsxFfXyUKvVLF68mAcffBAXFxfMZjO9evXCxcWFbdu2sWPHDpydnendu7dtm7y8PEaNGsX27dvZvXs3ERER9OnTx0ZKijFz5kwGDRrE0aNHGTNmzDXzOXz4MMePH+e5555DUcoF6u7uDshkqFevXnh4eLBv3z5+/vlnNmzYwMSJE69Y28q2bfuIjU1g06ZNLF26lCVLltgM/1WrVlGrVi1mzZpFUlISSUlyTeaBAwcYOnQow4YN4+jRo8ycOZPXXnvNtl1xjwq4eU3F9OnTmTx5MidPnqTXTX63FYlyx53ee+891q9fj6vrZZ1nNzc3Zs6cSc+ePZk8eTKvv/46PXv2tMtEa3Dn8E18Gq+eTcCsVVHPqOcx4ys4ocfDvQ1RUbNQq13JygKLJY1ly5aTlZWFSuXIPSGtCT8FgiDiEupM7cERWDQaRBFMJtlgTzuzk//9+g0WswknD0/uGT6OUzutxJ+LxyKqiGjrS7eH62IRlSQmXk5PslrlSIKHNYH4V2ZjOCYXYeo6dsRv2jTSFSLT/vcG/1p/Q6E208KvBW91eItaLiVJwA3D9eZCnI58Sd6u7zC6xcgepy4vQdun4FYKuq9ARaiinEvN45sdsaw6GI+hSO7P21nL8NbBDG0ZXEMiqhgGNg1i5YF4jifkVPZUbhvVor7mzDowF4B7bQhoWtmzqRCsObcGgAHhA+wuXWpOTERfZBi69rrx87tK9SW5CXLTC0mLy0MQ5LTa28WVdQEWkwlDQaH8XSiVNgO4oqBWq+32vScXqST6+ZVs1unr40NKaqpcT3FVPn96ejpWq/Wabfz8/DhV1IW9NIwdO5b27dsTFxeHp6cn2dnZ/PXXX2zYsAGQU6pEUeSrr76yHd/ixYtxd3dn8+bN9OzZk27dupUY84svvsDd3Z0tW7bQr18/2/KHH36Yxx577LpzOXtWVoeLjo6+7joAy5cvx2AwsGzZMpyKDIePP/6Y/v3788477+Dn54ckibi7u7Jw4ds4OQUTHR1N37592bhxI0888QSenp4olUpcXFzw9/e3jT1//nzuvfdeXnvtNQAiIyM5ceIE7733HqNHj8ZYFOJTCDfvUzFlypTrprfdSZSbVOTk5JCamkr9qzptpqWlkZsrN0Rzd3ev8B9XDewHqyQx81wCX8bLksC9fE5x76XPEPOV+IaNoG7d8VitKrKy4OLF0+zduxow4O7mTjd1K7KOKLAoJdza+OB2bwiCSkGxf6NQb+Lg2rUUXPgVtcpCrXoNqd95OLvXJGLQm3FwUNK4VwQd7/fGIl6rJpKbK5GwdhfxK7/A2xqPg5MOnylTcO3diy3xW5i/fwE5OeDs58CUlpMZWX8kCuFa78N1w/Wx22HDG6iz4yiwuiLW7QUD58iGSTlhT1UUSZLYdjadr7fHsOVMmm15g0BXHr8njL6NA9Cq7g6977sNdX3l/icXMwuQJKla6tdXJ8lQ9helXzQaWiVFFG4XMTkxHEw9iEJQ0K9Ov5tvcIvI/mUViCK6Nm3QhITcdP0q05fkJiiOUgRGuqNzvf3GdGazmTlz5tz2OOXByy+/jKaim+sVdV0rrZ6iLBg/fjzfffed7X1+fj6tW7emQYMGLF++nIkTJ7Jy5UpCQkLo1ElOUzxy5Ajnzp3DxcWlxFgGg4Hz5+W+MykpKbz66qts3ryZ1NRUrFYrBQUFxMXFlUizu1mRtXRFFOBGOHnyJE2aNLERCoAOHTogiiKnT58uIhUWoqPDUasvrxMQEMDRo0dvOvaAAQNKLOvQoQMLFy7EarVivEJO9mbPjbIWlVc0yk0qBgwYwJgxY5g3bx6tWrUC5Fy3adOm2ZQF9u7dS2Rk1dIIr0FJFHseC0Urk89fZH1Rh+xHNf/Q0/gJFl8nfH1n46TrT16eHIX4999tHD++DZXKQlitEDplRKJOETHpJOhYB/f2JUPLOakprF6whKS4NDycoUXfQaBswpYfLgLgEeBEh6HROLg4olBARkZJNRGrXk/2vIVY/j6OUdJibtyWqDcnUOjpxOw9s/kn7h8ki4pwj3rM6zuPBv51r3u81zSAKsiETbPhlNxZ2+wYhPLeV1Dc2w0cbs8gsYcqiihK/O9ECp9sOsfRIk+3IEDP+n6M6RBG6zDPammk3gzVwiNeRuiKHsqSBEaLiIO6epG/aiUZmnYGYreBoIAWoyt7NhWC707IhlqnoE74OfndZO1bg2SxkP2LLMntPnRImbapMn1JbgBJkji1W045qdvCvuesuqPYc56SkkJAQAAgn6+UlBQa12+EQnutmejt7Y1SqSQlJaXE8pSUFNt4s2bNYtq0addsO3r0aD755BMmTZrEsmXLeOyxx2zPsPz8fFq0aFFqTYCPjxxdGjVqFBkZGXzwwQeEhISg1Wpp164dBQUmTCYuKx1qnGzPkNJQbJueOnWKZs2a3ew0XReSJCFJVtRqFUrlZSEOQZDrTW8HhuLu7Fc9482l5Bs6XU8t4Q6j3KTi888/59lnn2XYsGG2JiYqlYpRo0axYMECQA4rffXVV/aZaQ3siis9j0kFJl48lcB5ayEO7gqecfuaFsY/UKncaNFsER4ebcjNhfx8A3/++SsJCSdRqaB1RDManfJEMIsoPbREPlGfNJxLeKzO7NvP+iXfI5ny8PNxpMX9k0k+LZASmwhAdFt/WvULIy9fSbFz4sr0pMLjx0me9SaWpEQc1T449huGy+C+7DMdYuHf75JuSEcpKBkYOopxbYcS4n/jNCVbuD5TQpP6F/zzJhRmAQpo9gj6BpPx8HPmdhUBb1cVxWIV+f3fRD7ddN7WW8JBrWBYq9qM6RBGbS+dbT93i/EN9vOIV6XzYjBZATmEraomsoBXojpJhrLrI/k1ohe4B1fuXCoAWYYsfjv/GwCPNnjU7uPnbfwHS3IySnd3XHr0KPN2VV1+OiU2l8xEPSq1goiWpSsT3erc1Wo1L7/8MhaTiYz4SwiCgHftEBR3oEO0PZV9wsLC8Pf3Z+PGjTRt2hSA3Mwc9h7az7iRj5caqdBoNLRo0YKNGzfanMiiKLJx40ZbrYGvr2+pKlAPPvggL7/8MkuWLOHEiROMGjXK9lnz5s358ccf8fX1LZFafyV27NjBp59+Sp8+fQC4ePES6emybLogXCYRxWnXGk3pxKJp06bUr1+fefPm8dBDD11TV5GdnY27uzv16tVjyZIl6PV6m+G+Y8cOFAoFUVFRSJIZKFZ+uv6Fo9FosFqtJZbVq1ePHUXSzVceX2RkJEqlEqPRgoe3N5kpybbPz549S0FR/U5VRLlJhbOzM19++SULFizgwoULANSpUwdnZ2fbOsUXaA2qFq70PJ43FjL1UALpWSLOZg0PJn1LQMAhFLXq0qrlZygUYSQmQnx8Nr/99hfZ2RnodO70r9+MsKPyj1Ab4Y7nsGiUTmo0RUZhTraVLb+v4cTmv9GqDIQ3CaLZfWP5Y2km+jwrTk4qOg4JJ7i+D3n5l8PkxelJKqVI5nc/kPH112C1oPIPoN6Lr5HmFsk3+1azw7QEhUMBtXShTGzwIo0DovArY+2dpzqFwg1vk3VmB06aAtS+0Zi7zUbv0tBu4fqyqKIUFFyrimK2ivxyIJ5PN58nLlO+cbhoVTzaPoQxHcLwcpZvWtUqHaWMsIdHvCqel4RsuSGWj4u2RIPB6oBqJRmadREOL5f/v6d6CYSU1aD94dQPGKwG6nnWo6WffdMdJEki44svAPB4eDiKcqTXVPo1cB2c3C47scJb+KLVlbwpl/eeIQgCGo0GY14uarUKrc4JB8eqJxmdn5/PuXPnbO9jYmI4fPgwnp6e1K5dG0EQmDJlCm+99RYRERGEhYXx6kuvEOAXwID+A2z1FPfeey+DBg2ykYapU6cyatQoWrZsSevWrVm4cCF6vf6GdQwAjo6O3Hfffbb621pXqIuNGDGC9957jwEDBjBr1ixq1arFxYsXWbVqFS+88AK1atUiIiKCb7/9lpYtW5Kbm8u0ac/j6OiIIJTMdlQo5KiFxVJ6vY8gCCxevJju3bvTsWNHXnnlFaKjo8nPz+f333/nf//7H1u2bGHEiBHMmDGDUaNGMXPmTNLS0pg0aRIjR47Ez88Pszm3aEAFQikp18UIDQ1l69atDBs2DK1Wi7e3N8899xytWrXizTff5KGHHmLXrl18/PHHfPrpp4AcqWjdqTOLP1tEz473YLVaefHFF6t0w8DbFgh2dnamcePG9phLDe4Qij2P+wtzmb43BYMBarkaGS7OR5VrpkDfjQD/KZhM7mRkwIULCfzzz+8YjXrcXF1o49ACYZeIwcWId5dA3PqE2W48Dg7g4ZLL5i/mkXT0KJ5OIm3u74ezTze2/xCLTlDgGeZKiwH1cHJ3xGgsGSY3GkHMyuDi63OxHN4LgHO3bvhOm0aimMXbm6ZxOiMLpU5Fb/+hjGk8Ch8Px7IZjZIE//6Ew9oXCMovJFPnTV7jyRQ0ewylRoOHHY3Pa9KsrsLVqiiiKPH7v4ksWH+G2AyZTHg6aXj8njBGtgvB1eHyTaRapaPcAm7XI15Vz8vBuGwA6geU7nmryigvOa4UbH0PRAvU6Qq121T2bMqEWzFosw3ZLDuxDIAxjcbYPe2xYNcuDMePIzg44PHII3YduzJhMlg4sz8VgPodSt5AbveeIUkShfmy6pCjS9X8fe/fv5+uXbva3hf3GBs1apRNZeiFF15Ar9czbtw4ufld63b8/u0v6NwvO4nPnz9Penq67f1DDz1EWloar7/+OsnJyTRt2pR169ZdU7x9JURRxGQyMWzYMFavXn2NKpNOp2Pr1q28+OKLDB48mLy8PIKCgrj33nttkYuvv/6acePG0bx5c4KDg5k5cw4vvXRtmhXIz1dR5LppUK1bt2b//v3Mnj2bJ554gvT0dAICAmjfvj0LFy60zenvv/9m8uTJtGrVCp1OxwMPPMD8+fOLjkl2GgncOEI1a9YsnnzyScLDwzEajUiSRPPmzfnpp594/fXXefPNNwkICGDWrFmMHj0aUZIwShJTZ7/Nu5OeomPHjgQGBvLBBx9w4MCBG+6rMiFIZa1WQb4Y33zzTZycnK7b/K4YxSe8qiE3Nxc3NzdycnKuG167m2E0QmwsrMnM4N1/0xD1Shp4ZDDYOA9HDLi7dSMw8GlcXbVIEly4cJI9e9YhiiK+Xj50NNVDkyaSY1YRMjCYun1KhjfTLsbw6/tvkZOagkqrpfvjzxB3ypMLh+Qiuej2AXQeFolVUpbqmcvftp1DU94hO1PEzcmMz+QpuNzXm/UX1/PBoQ/Q56jx8BR4q8ezdAzqXPYwe24S/DFFVoYBCGgCAz7F6NGwwsL1iYlFilUe135WvDwgQOKfU6m89/dpTiXLDycvJw1PdQnn4Ta10Wmu5f1lGdfe6SgVndZQfF1qtaWTMJNJXic09Pr7r4zzUhY88tUetp9LZ/p90YzvHH7nJ3AbsMf3ckeQeBi+6AJI8Ph6CK763cuvZ9AWFzhfbdDOPzCfxccWE+URxU/9fypViKK8kCSJuEdHUbBvHx4jR+L/yst2G7uy8e+mS2z78SzufjoentmmBBm7lXuGwWAgJiaGsLAwHIq+GIM+n+zkJBRKJT4hoTf0VFcXSFYRc5Isf632d0KwUz8PUZTPYVZWJqtXr2LmzJkkJibeVsG5KMr3nxtlnFmt8r2pomSNCwpisFjycXAIRKPxst+4Vitn9UaUAjRwdrwjtZOlXePFKKvtfEuRikOHDtkKRA4dOnTd9e7GwtG7BVarxKLYVL5NT0csVNPe+QJ9jJ+iQKRW0AgCAh4iP18ARNauPUhS0k60WpHwoDBaJQUjFIgonFTUuj8Cq49ribSH07u2sW7RQixGI25+/nQd/Rx7fsshKzkNhVKg40ORNOgYKBceXTUvyWol/ZNPSV+0CBerGkvd9rhMewUxzIPZe+bwT8xWRKMjTQKjmXf/VEK8bqHY7vhq+H0KGLJBqYHOL0KHyaBUU5F20M1UUWLzMpn06ykOXMwC5DSnJzvX4bEOYTiVUhwHdz4d5U6lE92uR7yqpukkZBey47zs3evbKODO7dhOqBaSoZIEa18AJGg0pFoQCri1yFxSfhI/nPwBgEnNJtmVUADot26lYN8+BI0Gr8dG23XsyoTVKnJ4/SUAmnSrVcI2scc9o7BI6dLRxeWuIBQAYqFcIyuolXYhFKIopyCJIqSm5nDp0iU+/vgTxo170i4KVoKArZ7ialxvub0gSRJWq5xZoFTaV8q9wCo/7HRKRbWyqW+JVGzatKnU/2tQPWAWJZ4/G8eKZD0g0EN5iC7W71AqVYSFTcXbqzNmM1gsRjZu3MCxY9n4+Ei0CGtExBk3BKuI2k+H0/0R4OxAfn5xaNHKjhXfsvfXlQCENG5Ggy6PsXHpJcxGK07uWnqPa4h/HbdS52XJzCRx2vPod+4EwG/4ICKnvsTWczHM+u0tUgtSUWkdGddmKE+3H4aTroyFcIZc2dg4Ij+MCWwGAxeBb73bPZVlwvVUUUzKQj7dcZo/TyTI66kVjG4fxvjOdXDX3fgmeyfTUe5kOtGtpotdjaqapvP5lvNIErQP96q2/UOqvGTowaVwaQ+onaDHrEqeTNlwqwbte/vfw2A10Ny3OZ1q2bdLuGS1kvq+3MXXY+QjqKtM1f3t49z+VPIyDTi6qIluV5LU3+49w2IyYSyQPfqOLqU/26ojikmFQnfb2fG2YmlJAoVC4sMP3+ejjxbSvv09TJ360g3VmcoChUL+K3Z4lbb/imy+KIqFSJKIIChRKOybW3slqahOuOWrZteuXWRkZJRoMrJs2TJmzJiBXq9n4MCBfPTRR2irasXWfxR6i5Wxx2PZlJmHSqdicO5GIiw7QeVOdPRLuDjL/UbS0vLYuXMdubmJqFRedAhqSfhJ+TIR6nhi7lCHixlKCuPlH6xWrefwL/NJPC533mzRbzAaXQf++TYWgKBId3qObXhdXfCCg4dIePZZLCkpCI6OBMycgabn/Szd+xsf7lmMyaDEx9GHV7o+Q/eGDcpuxMbthlXjIPuiLC95z1ToMv2Wm9jdbtrPlaooeoOVxTti+GrXOQrNVgQBhrYI5rmekfi6lu3Abtf4vhXcSdWf2/WI38nzUlZczNCzYq/sJZ3Y7foyx1UdVVoyNCsW/n5F/r/ry+BaPQziWzFodyXuYv3F9SgEBS+3ednuXsucNWswnj2Lws0N73Hj7Dp2ZUKSJA79Lw6Axl2DUV3VFfp27xkFOdkAaHVOqCq6Z8QdgmQRkYxFanUOt08qLBaZUMjn2cyzzz7H1KnT8PHxRRSF6xZR3wpUqsu/J4XicuRCFOX/Vbd/GNeFxSKTSqVSZ/8ap2JSUVXa0ZcRt3y6Z82aRZcuXWyk4ujRozz++OOMHj2aevXq8d577xEYGMjMmTPtPdcalBNpJjOP/HuBI3mFOChggvtH+BlOk61qRK2g6Tg7BWE2Q3x8Jps3/41CkYJW60L/0Hp4nZHAwYq6dRAZwUFkXBIQRfmBZzWmsX3JYkR9Av5ezvR+4kliT3hycYfsgW/aPZh2g8JRlMK0JUkic+lS2UNmsaAJC6PWhx+g9w/i2V/fZ+P57Si0hXSKasOzzV5AYXYhIaEM3nGrGba8A9vmgSTKzesGfQEh7W7pnNk77Wfr+RRm/nbcpgTUKtSDGf0b0DDo1jxcdyodpdiTqlLJXuqrSVVFpBPdjke8qqXpiKLEi7/8i8kq0jHCm/bhZZQmq6KokpKhohXWPA2mfKjdXu58X01QVoPWKBYye89sAIZFDSPKM8qu87BkZdmiFN7jx6N0u3s87rH/ppORkI9aq6Rh56BrPr+de4ZotVKYL6c+6dzd7TzzyoMt9UmjRFDfnjF7dYG0wWAAQKt1QBCEmxZRlxUKhfz9FadYFZMJpVJ+flWkTX459cm+PSIsomRrfOd4BySK7YlbJhWHDx/mzTfftL1fsWIFbdq04csvvwQgODiYGTNm1JCKKoKYAiPD/z1PbKEJD6XEVPEN6iiPog5tjK/P68TF+RAfD/n5CezcuQ5B0OOk8+ZedTT+uQaytBqErnXJ8fUiMe5yiNGSd4Fja5diKjSidq5Ly+H3c3RbFpmJGSjVCu59tB4RrUqvexALC0l65RVy/1oLgGuf+/Cf9SaXrGmM/3ki55My0DgXMLbRWIZGDbV5AG7qHc++BCsfg/h98vvGw6DPu+Bwaw9Ke6b9pOYamPHbcdYek3Wmg9wdealPNH0bBZTbs3E947v44Xi7PXCMRrkB4cWL8nEW3/Q1GnB1BUdH+X97pxPdrke8KqXpLN4Zy+4LmTiqlcwe2OjO7biCUelE4kpsmg0Xd8hpTwM/AUX1efiW1aD9/PiHXMy9iK/OlwnNJth9Hqnvv481KwttRASej4yw+/iVBdEqsmu13IG5UddaODiVHhIq7z2jICcbSZRQabVoHKqejGx5IEkSol6umVVc53zd+pjFRr1kIxUODvJNRBDs9/wofj5dOV5FO/jleoriSIV9SUVh0YFoFALqatbb6JZJRVZWVgnJsC1btnDffffZ3rdq1YpLly7ZZ3Y1uC0czStg2JELZJgtBKnNTDU/j790CQ+PdjRutAiVyoWAANi+/SQ7dmwCRAJ9/eluCsWrwICju5JaD0WQ6eDOyR3yzdfLC1LPHuDk+hUoFEZqhYcQ3OJh1n6bQoBbAW6eGvo81Ri/0NLVAcyJiVyaOBHjiZOgUuE3fToeIx5mQ9wGXtk8i6xUN7zcnJlxzyya+DYpse0NveNn18OqJ+RGdlo36L8AGj5QrvNmr07YK/ZdYu7ak+QZLCgVAuM61eGZbhE4am7P+Lna+M7Kkl9BNlSSk+WH4q1GVYqjM+npsuJPYqJ8Dtzd5fGKIxe+vpfJRXlv3NfzeN+OR7yqpOnsOp/BnL9OAjD9vmhbo8Ia2BGn18rRSID7PwTPOpU7n3LgZgZtjOkA352Uu2e/0f4NXDX2VSss2LePnF9WAeD/xhsIVVj7/lZxalcyWckFaJ1UNO8Vct31ynPPEK1W9EWpT87untWqiPZGkExWJIvs5lc42idnqDgVyWw2IxZ1h9Zo5Bt6RRRR38lMIau1AEmyIgjKEp207YH8oiZ51a2eAspBKvz8/IiJiSE4OBiTycTBgwd54403bJ/n5eVV6cYc/xXszc7nkaMXyLWIRGn0PGN8Bney8fPrT/1676JQaJAkiaNHd7Bv3wY8PZVE1o6g3aUgHK1GlD5avB9riNpXh5QNzs5QK0jk5NY/ObNjPQoFhDRqRkB0T/atjSe/UEV0lCtDpjbE2aN0K7DgwAHin5mMNSMDpacntT78AIcWzfnw0Id8dfQrRJOW+u4deLP783jrrpVmK7VwzmqBzXNh2/vy+4CmMHQpeISW67zZQxEkOcfAtJ+PsP2crPrTpJYbcwc3pn6g/YyCYuM7JwcuXZLJhIdH+aMqxdGZ3Fz5D+Sxjh2Tb/5ubjKZkCT52JOTwcdHfn8rKGtaWXk94pWdpnM2JY+nvz+AVZQY2DSQR9td36CpQTmRclyulwJoMx4aPVi58yknbmTQKnTZzNwwHYAHIh7gnqB77Lpva76exJflWhT3hx5C17yZXcevTJhNVvb+LjfkbXlfKNqbGMi3es8ozMtFEkVUGi3a2w0LVyHYohSOKlvfqdvBlUXUhYVy2q+Dg4ONhFV0EXVFw2KRPXkqlbPdiWW+RTZynKtZ6hOUg1T06dOH6dOn884777BmzRp0Oh0dO3a0ff7vv/8SHl69tNjvJhiNsCU9j3EnYjGoRJpos5homISOQmoHP07dutMRBAWiKLJ27Vr27ZNThdpGN6TJKW8Ei4i6ljPeoxqgdLkclxcwsGfVDySflqWEG3XtCYoGHFyXgCQKBIa7029SbZw9Sv8RZP30E8lvvgVmM9p69Qj++CNMvu5M2TSFTZdkJbGR9UfQz3MizqrSSek1hXP5qbByDMRuk9+3Ggs9Z4O6/C7p21UEWXs0iZdWHyW7wIyDWsELvaIZ1T4UZQWFMPV62dtzZb+h8hRTJyZCXJx87OfOQVqarNqRlyeTDIVCfvgqlTIxqFtXfn8rxdp3Uk2qMtJ0YtP1jPhqD1kFZhuRvFu8mFUGOQnw3YNgzJXrKHq8efNtqjBKM2jVGpGJG18mWZ9MiGsIz7d63u77TZkzB/OlS6gDA/Gd9pzdx69MHF4fhz7HhIuXA40617r5BkUoyz1DFEUK8/NQCQLOnndRlMIqIhYUqT45288prFLJsr6FhUZAwNHR8Y4VUVc0LFaZVChVLnYd1ypJFBQZGC526hFyJ3HLX+mbb77J4MGD6dy5M87OzixdurSE1vA333xDz5497TrJGtwcxR7gPy7mMON0EiZBSQv3dJ7STkGnKaRu+AuEhDwJgMViYdWqVZw4cQKALtHtqHtEBxI41PPEc3g0iitSdCRzDvtXLiXlUgoujkpaD3qItEveXDopN7QLbRFE404BuLpde4OVLBZS5r5N1vffA+DSuzeBc2aTJGYxae1IzmadRaPQMLP9TPqH97c1I7pp4VziYVjxMOQmyDnV939oF49leRVBCk1WZvx2jJ/2xwPQKMiNhcOaEu7jfO0gdoK9ejPk5MhEohjp6fL1pNHIx+ntLX8nCgXodJejFjrdrRVr30k1qTuNU8m5jP5mH6l5RqL8XFjyWOvbTnOrwVUw5MD3D0JeInhHwbDvQXV3qO5c+fv56ug3bEvYhlapZV7neTip7esNz/37f+SsWgWCQOC776B0sa9RVJnITingwNqLALQbGI7yNouNr4ZRr0dSu6LW6dDq7p4ohTVfjlIIGmWJZ//tQqEAi6UQQRBRKNQoFGqbGlRFF1FXJETRhGiVa0RUSvv+fvItVpDkegpNNTxBt0wqvL292bp1Kzk5OTg7O6O8Kjzz888/4+xccYZUDa5FsQf4t/hs3k5MwKqTaKtIZEDGQjLwo27rV/D3HwqAyWTip59+4ty5cygUCu6L6kzAIfnCdWrjj/uAuiVCn7lpqaye8zrWTDMqbTjNHxhN7FELGfGZoFDQsFsYPmFeBAdfa1iKej3xU6ei37IVAJ/Jz+A1fjyHUg/x7OZnyTRk4uXgxQfdPqCJj1w/UabCuWOrZNUXSyF4RcCw5eATaZdzWR5FkEuZBTz57QFOJOUiCPBU53CmdI9EYycvw/XC8vbqzZCRIV9DQUFyLUVhoXyeBUGOUri6ynUVWq38nTg5FXlUb6H3Q2U1p7sTaVC7zmcwbtl+8owWInyd+W5sGzyc7g5jt8rAkAvfD4HUE+DsD4+sBF1lN8iwPzZf2syHBz8EYHrr6XZXezJdvEjSa68B4PXEE+hatrTr+JUJSZLY8sNprBaR4Pqe1G3pa9fxMxMTMBsKAVdcvHzuniiFeLlAW+li/9R1g6EApVLExUWLViufs2poK5dAceqTUqlDobBvuCXfWhylqJ5OqXJ/tW5ubtcQCgBPT0+7dEmsQdmRmQk/XMxiTmo8okqii/YCQ41zEM1q1KoZpKcPJTYWLlwwsHjxD5w7dw6VSsWAut1shMKlWzDuA0sSivS4WH54bRpZifH4Bmjo+8QI/t1s4tKFAqyoad63LsH1vAgJudbDbElL4+Kjo9Bv2Yqg1RL00Yd4P/UUf1z4g8f/9ziZhkzqedZjRb8VNkIBl/OMPTxkgzAnR3718ICgABGHnbNlhSdLIdTtDk9stBuhKEZxfn9W1uXGPSaT/P5qRZDtZ9Pp//F2TiTl4uWk4fuxbXihd7RdCIXBIKclxcZCTMzl4ukiEY0SUZXSUJbeDEajTJScnGSCYDbL/5vNMqnQamVjXxDkCIXBII9ZTPbKmhNbFgJktdpPDeRm584ekCSJ73ZfZNQ3e8kzWmgd6snP49vh41KVJJLuAhhy4LvBcoM7B3cY8bMsFX2X4XTmaV7c+iISEkMih/BARPmEJq4HsaCA+EnPIObm4ti0KT4T7a8mVZk4szeF+FNZKNUKOg+PtKvRL0kS+36Tm7tqHXVoHKuP4tPMmTMRBKHEX3R0tO1zscCMoaCQZ157Dp9a/jg7O/PAAw+QkpJyw3ElSeL1118nICAAR0dHunfvztmzZ0usYzKZMBc9oHQ6R1udRVXCoUOHGDJkCH5+fjg4OBAREcETTzzBmTNnrruNxSIXHqpuIfVJEATWrFlz0/XyLHKRtnM1LNKG2yAVNagaMBrhm7OZLExJBKCn5gT3588jJ9MfP79XqFOnAwoFFBYWsHTprxw/no1CoWNgcFe8/pWrbN361sGtZ2iJm3D8yWOsmPkiWel5KNwa0njgK+z7Ix1DXiGOTmq6j4qkQUt3oqKgTp2SufDGCxeIHTYcw/HjKD08CFm6BJfu3Vl8bDEvb38Zi2ihR0gPlvRegr+T/zXHVJxnHBoKYWHya6CPAYc/RsPWd+WV2k2Eh3+6ZbnYsuCGxOaKvP+f919i1OK9ZBeYaVzLjd8n3WO3fgTF0aesLNmwd3OTX7OyLtclFEdV9PrSx9Dr5c9v5KEvLpYrVngqLspWKmUipdHI0Qo5N1bexsVFfjCUZfxi2IMAlRVlOXe3C73RwrM/HubVNccwWUX6Ngpg2eOtb9oRvQa3CEMOfDtYlol29IBRv0FA48qeld2RrE9m0j+TKLAU0Ma/DS+1ecnuRnHSa69jPHMGpbc3QR98gHAXOf8Kck3sWCkbtK36huLmY1/FtdO7tpF4+iQI1bMvRYMGDUhKSrL9bd++HSiSRc0zMe2Nl/hrwzp+/vlntmzZQmJiIoMHD77hmO+++y4ffvghn332GXv27MHJyYlevXrZpGMB8vPzAXB0dCzVCX2nYL7Og+ePP/6gbdu2GI1Gvv/+e06ePMl3332Hm5sbrxVF9K6GKJqxWOTjUqvta38YRVHuTyGUv0hbkiQsFotd53UrqCEV1RzfxKWx4EIKKCX6aQ7T37iAQr03IbWnE1K7NY6OkJeXz5o1K8nPj0etdqaTrgvuJ0VQgMeDkbh0LNkY6Nz+Pfwy+3Xyc01o/dvQsO+z7FmdgMpaSHi4kgFPRVK7rhO1a8vG/5WEouDgQWKHP4w5IQF17dqErvgBbZPGvLf/PeYfmA/AqPqjeL/z++jUN77xa7WybKlWyoHvHoATv4JCDQM+hV6zK1SXvlRic8Wxfr7lPM+v/BerKDGoWRA/PdmOQHf7ea+urD/QaORIgUYjvy+un4Fbi6qUhmJj38lJXt9kkl8dHeXzbzLJ+zabZWLh5CQb6QUFt9b7wR4EqKwo67krLw7GZdH/4+2sOZyIUiHwSp96fPxwMxzU1TNcXWWRkwDf3AcJ+2VC8ehvENDk5ttVM2QZsnhy/ZMk6ZMIdQ1lXpd5qBX2TUPJ+Pxzcv/8E1Qqai1cgNrPvqlBlQlJkvhn2UkK88x4BTnRtLt9o1iG/Hw2LfkCKOqera5+ZEylUuHv72/78/aWnV+i3kxOVjZLflzGvHnz6NatGy1atGDx4sXs3LmT3bt3lzqeJEksXLiQV199lQEDBtC4cWOWLVtGYmKizRtvsVhsBMPZ2ZnY2FgUCgX79+8vMdbChQsJCQlBLApTHzt2jPvuuw9nZ2f8/PwYOXIk6enptvXXrVvHPffcg7u7O15eXvTr14/z58/bPo+NjUUQBH744Uc6d+6Mg4MD3xfVdF6JgoICHnvsMfr06cNvv/1G9+7dCQsLo02bNrz//vt8/vnntnW3bNlC69at0Wq1BAXVYsaMhUiSBoVCfmB16dKFZ555hhdeeAFPT0/8/f1L9GoLDQ0FYNCgQQiCYHsPsGjRIsLDw9FoNDSIjuaPFctxVipQKQTbsRw+fNi2fnZ2NoIgsHnzZgA2b96MIAisXbuWFi1aoNVqbaSxMlBDKqoxvolPY+aFRFBI9FEcpZfxEyTRhVq13sTfvykA2dl5rFv3F1lZmTg7OdPPuxnCaQEjCrxG1MepZckGdad3bef3+XOwmE34RHeiQfexHPztAqLZjH+oK/0mNKROpGxZX20g5u/YwbnR4ynIMiA0bE7oih+gVgDTt03n2xPfAjCt5TSmtZqGQijjpZeXDIv7wsXtoHGBkaug2Z1r0mQjNlcYux9uPMvctacAeLJzHeYPbWJXg/JW6g/KGlW5HoqNfasVateWVaSu1A/39YUOHaBePdkgd3SUSUVZx78St0uAyoJbOXdlHa+wUH41mK3M/eskDy7ayYU0PX6uWn54oi1PdKpz1+RXVxkkH4OvukPqcbmGYtTvd2WEIt+Uz/gN47mQcwE/nR+f9/gcN619vZ85v/5K2sIPAPB/5eW7qo4C4NiWBC4ey0CpUtBjTAOUdlbM2bZ8CQU52bj6+qFxvOwIk5ufFVTKn3SLWt5nz54lMDCQOnXqMGLECOLi4mxRioNHD2M2m+nRs4dt/ejoaGrXrs2uXbtKHS8mJobk5GS6d+9uW+bm5kabNm1s2+iLDAStVotarSY0NJTu3buzePHiEmMtXryY0aNHo1AoyM7Oplu3bjRr1oz9+/ezbt06UlJSGDp0qG19vV7P1KlT2b9/Pxs3bkShUDBo0CBEUUQU5WcKwEsvTeeppyZz5MhJevTodc0x/P3336Snp/PCCy+UeozuRRGphIQE+vTpQ6tWrThy5AgLFrzBt9+u5v33vy6x/tKlS3FycmLPnj28++67zJo1i/Xr1wPYVDYXL15MUlKS7f3q1auZPHkyzz33HMeOHWPImMeZ8fR4jm7fVuqcboTp06fz9ttvc/LkSRo3rrx7ZbUS9Jo7dy6rVq3i1KlTODo60r59e9555x2iouxbzFYdsCQhnZfPJiBo4H6PQ3RIX4bS1YHwiPfIzamPSiWHHlet+huzOZNaQc70cGqB6oKJfKUKzxH1cWzgUWLMk9s3s/bj+UiSSN223dHVeYQ9v5xFkKwERrjRbWR91FrZeL66sDZt3RZOTHkDvdETbcvWBL76Epf0Cubsfo7daZtRKVS82eFN+tXpV/aDzIqFpf0hOw6cfOXizEr2VC7eEcP89XKu5fT7ohnf2f7yybdagH27vRmKi+MLC+WojFYrF28XFMjRCTc3mQA0aABRUfL65Yko3InmdPYqXr+6n8a+ixl8vvMUCYW5CCoY3CyIGf0b4Kar6cljd5zbCD+NAlOerPL0yMq7soaiwFzAxH8mciLjBJ4OnnzR8wsCne0rf6bftYvEV14FwPPxMXgMH27X8SsbGYn57PhFlq5rNzgcryD7isTE/nuIfzeuA6D9kBEYrnAeiGIhm7c0suv+yoounY+iVJYtxatNmzYsWbKEqKgokpKSeOONN+jYsSNHdh9EZ9WQkp6KRqOxGdHF8PPzIzk5udQxi5df2Qj5ym2sVisFBQUAOF3h4Rk7dizjx49n/vz5aLVaDh48yNGjR/n1118B+Pjjj2nWrBlz5syxbfPNN98QHBzMmTNniIyM5IEHStYaffPNN/j4+HDs2AkiIxva7u2TJk1h0KDBNvna4mdjMYrrP66sLykNn376KcHBwXz88cdIkpnAQDMvvfQUM2d+yBtvvI2iaNDGjRszY8YMACIiIvj444/ZuHEjPXr0wMfHB5CJir//5ZTv999/n9GjR/P0009jFkWGPT2JA3v28vnCBQy8guSVBbNmzaJHj1vbpiJQrSIVW7ZsYcKECezevZv169djNpvp2bOnjRH/V/BtYjrTz8jSpQ86HGKI5i0ctBAUuAAnXRMsFkhIyGfFiv9RWJiNr6+GnroWqGNMWJVKvAbXRRdZklAc37KRvz6ehySJNOzag/DWw9i24jyIVoLreXLvqMuEAkoW1qb++jcHJ71NrtERj46tiXz3VQQngefXzWbLsXNoRTc+6fbJLRKKi7CkiFB4hMHj/6t0QrHuWBJv/C7L8D7bPbJCCAWUv/6gtKhKabjS+w4lox0g11f4+sopX3XrQq1aMqFo2xYCAm4vRel6aWWCUHJO5YU9ajeurMlIKyjgjXWHefnXw8QmmnEVXfjkoZbMf6hpDaGwN0QRtr4vpzqa8iDkHnj877uSUOSZ8hi/YTwHUg7grHbms+6fUcfNvl3BC48cIX7iJLBYcO3TB9/n7q5+FGajlfVfH8dqFqndwJPGXcvek6IsMOTn8/eihQA06dGHgLr2FQS5U7jvvvsYMmQIjRs3plevXvz1119kZ2fz4/IVAHbrnn0l9Ho9I0aMICIiAm9vbxo0aADAwIEDUSqVrF69GoAlS5bQtWtXWzrQkSNH2LRpE87Ozra/YqO/OMXp7NmzDB8+nDp16uDq6mrbNiYmDkm6fG9v0aIlgiDf7yUJri4zKGu05+TJk7Rr1w5BEDCbswDo0KED+fn5xMfH29a7OjoQEBBAamrqTcfu0KEDADlFBdqt27Xj9KlTZZrblWhZRSKQ1SpSsW7duhLvlyxZgq+vLwcOHKBTp06VNKs7i19Ts3jhtHwhD3Y4zMDCt1A6aOnWdQYGQ1Pi4+HcuQL++WcPYCQgwIkeumhUsSYEtQJNr0i8G7qi1V72bJ/Ysp7NSz4ESaJx997UaTmEPz87iSRpqd3Qm64jIlFepURQbJzlrf2TEy++h8niRGDvdvi/NB0DZt7Y9SrH9IfQSN7MajaH9kE37thawsteGAdL+0FOHHiGw+g/wTWgok5pmRCTruf5n/8FYFS7EJ65t26F7as8srZlwc26WV8d7YCKk2MtHq9YpelmHbZvZdzbPXeZmZCYYWDN8YusPpSAySqiVgsM6xDE4Aah1PKrIRN2hyEHVj8Fp/+U3zcbCX3ngeruU9IqrqE4mXkSF40Li7ovop5XPbvuo/DYceLGPoGo16Nr04aAt+ciVDXZndtAcR1FRoIeR1cN3R6tZ/cUxI3fLCI/MwOPgEA6PzIG61WfKxSOdOl81Pb+yuhnRZ9qhaL89Xvu7u5EhEdwPuYCgkpBQEgQJpOJ7OzsEtGKlJSUEl71K1G8PCUlhYCAgBLbNGnSBL1ez3vvvYdWq8XBwQF1UehYo9Hw6KOPsnjxYgYPHszy5cv54IMPbNvn5+fTv39/3nnnnWv2Wbyf/v37ExISwpdffklgYCCiKNKwYUOMRlOJ835lhEShkL+fK59tkZEySTx16hTt2rW76XmTJAlTEakoTfVJfVV4XBAEW51IWVBMKhyusLWKoyBXEqDrFZ07VZHu7tWKVFyNnJwcQJax/S9gc2YuE0/EIQH3O55hcMGbKBUaGjf6HCen9iQkgEpVQEzMGhwcDOh0rrRQNiDzuBFclbj0isQt0hWd7rIhd3bfPrYtX4lW6UH7/p2IbDeQvz47ilKQqN/ag4Y9olAqr71Z6/Wg+ncLSbNepcDih1+/rvi/8CwmLLy67VUOpR7CUeXIm/e8Trhjw+v2H7jG0C1Mx+XPx/A0peDgWwdG/1HphEIUJZ798bBNNvTVfvUrPIe+TP06bgFl7WZ9JztRV1SH7ds5d0mZJt7/M45f/72EUZRv8m3rePFsj0jCvJ1sXcbt3U/jP42Eg/DLWMg8D0oN9HkfWoyq7FlVCFILUhn3v3Gczzkvpzz1+MLuvSgMp09z6fHHEfPycGzRguBFn6K4i5SeAA79L45zB1JRKAR6j2uIk5t9f4wntv7DqR1bEBQK7pvwHGoHB6xXycYJgoBSqUMUZS+4KF6uR5OkqtvcLS87lwsXzvPwwKEo3bW0bNkStVrNxo0bbalFp0+fJi4u7rrGdlhYGP7+/mzcuJGmTZsCkJuby549exg1ahSSJFG7dm28vb2veVaOHTuWhg0b8umnn2KxWEqoTDVv3pxffvmF0NBQVKW0287IyOD06dN8+eWXdOzYEeAKJavLtYBXozj96Ur07NkTb29v3n33XVvk5EoUk6x69erxyy+/YDbnIolmBEHJnj3/4uLiQq1aZY+OqdVqzGZrCWJTr149duzYwfCRI8m3yBM8vHsX9evXB7ClTSUlJdGsmeyYvbJouyqi2pIKURSZMmUKHTp0oGHDhtddz2g0YrwipyI3N/dOTM8uuNJrfNyg57GjsZgliXsdkxhS8AoKQUnDBh/h5dWxiCSY2LFjNRZLMsHBbrTVNcB43ESWRYVzpzr4N5EJRXGzs4yYI+z7+VNUCqjdqjfOoffx+ydHESSJ8GY+dHokkqRkoVTjzHp0H+a3nkOySui69yLwhcmIgsScXXM4lHoInVrH2x3fpoFXQ3JySs9hv8aolAowr36arOQ8Cj1bEfTQFzi4Xj/H+E40NgP4+cAlDl/Kxlmr4sPhzVDfAf1oe9cfVMVu1hU1p+udO51OTu0q7cGTmF3I4h0xfLc9npw0DYLGSqNabozvFE6rMA/bg/FWGv7V4CYQrbB9AWyeC6IFXGvBQ8sgqEVlz6xCcDrzNBM2TiClIAVfnS9f9vzS/ilPR49y6YlxWHNycGjSmODPP0Ohs6+8akXjZvf1uOMZ7Fojp8J0HBZJYF13u+4//dJF1n/1CQDtHhhOQMT1SV9xYXBx2o1CIf9fnBqs0VQ+sZg2bZrNu5+YmMjrL7+GUqlk2NBhKBxUuDm48fjjjzN16lQ8PT1xdXVl0qRJtGvXjrZt29rGiY6OZu7cuTYFoylTpvDWW28RERFBWFgYr732GoGBgXTp0gUAFxeXUp1v9erVo23btrz44ouMGTMGxyt6fkyYMIEvv/yS4cOH25SUzp07x4oVK/jqq6/w8PDAy8uLL774goCAAOLi4pg+fTpwmcyVhtIIh5OTE1999RVDhgzh/vvv55lnnqFu3bqkp6fz008/ERcXx4oVK3j66adZuHAhzzwzibFjHyQmJoOZM2cydepUWyThRigmnSEhoaxfv5FWrTrg6KjFx8eD559/nqFDhxLeqDH17unE7r/Xsmb1ajZs2ADIUrxt27bl7bffJiwsjNTUVF599dWb7rMyUW1JxYQJEzh27NhNpbPmzp3LG2+8cYdmZR9c7b2PMxqYGBNHgZNEW7dcHi2YggKR6Ki38fHpjtEI2dlWNm36g+TkZBwcHOj3//bOOz6KMn/875ntu8lueiUNQu9dRIoCAjawt5/lRD0L9nbnnd07ThTl0FO/p3d63Kl3NqxYEAUEBAHpPYEkENLbJtt3Z35/TBISCBDIQhJ83q/XvHZ36jOzM898Ps+nZY3EsN6J3yHR7bxs9Jl2YmMPKhTusu0s+ec8VDVEz5FnMHDS+Sx4ZRcGJAaOimXSDC2LRkvCmXnfJur+PBNTyIXx3POx3HE3gaDEK5te4sfCHzHIep458xn6xfXD7z+yD3szoTIUhM/ux1i5EWNMNFVTX6MylEpLMuWx3HjCSUhRefl7LRDw3ondiTab8XhOviIDbQ/AbqC9qlm3Z5uaXju3G6qrtZd/UVHz+yW3soY3f9zL5xsPEFRU1KBMdpKN287OZFyvw0fZwllP41dNVR58/FvYV5+yss90uOCl07JKNsCy/ct4aOlDuINushxZvDrhVbpEhjcGwLX6Z/bffjuK2425f3/S33gDXUR4A5dPJq3p1ysK6/jmza2gQp/RyfQdE96REL/Xw+cvziLo85ExYDAjL7niqOsHg5rA2rSkQIMffyikLW9vI9H+/fu5+uqrqaioID4unjOHjmTZp4tJ6nYwlfxLL72ELMtceuml+Hw+Jk+ezKuvvtpsPzt37mz0DgF4+OGHcblc3HrrrVRXV3PWWWfx/vvvN7o7mY7Scc+YMYOVK1dy0003NZufkpLCihUreOSRRzj33HPx+XxkZGQwZcoUZFlGkiT++9//cvfdd9OvXz969uzJvHnzGD9+fIvWiAYa6jEd2m9PmzaNlStXMmvWLK655hqcTidpaWmcc845PPvsswCkpqbyxRef8uCD9/HWW/8lJiaWGTNmtEq4b8hwqKrw3HNzePjh+3nrrTdISUll5848LrpoOnPnzuUvL7xA0QP3k5GZxVtvvdWomIEWiD5jxgyGDh1Kz549mT17Nueee+4xj91eSOrx5ibrAMycOZNPP/2UZcuWkZWVddR1W7JUpKWlUVNTg91uP9lNPW4OHb2vUQJc88seimsVekb4eCjyN9iNTrp1fYjMzNsAcLkU3nzzO/LzN6PX65jcfQKmtV5kSSVhWiaWAQnU1GhCVkkJ1JXl89W8P+H3eskYMIgzL7+Vha9vpa4mSHxmFDc82gtbRPMUqQ2CbXBfPkXXXUmopgbb2DGkvfIKReVGXvvpPT7Y9wayJPP4qMcZ20WLcamq0pSGQ0ecfT6tyrHJVN/pLpsDa/4OOhNcPh9//CB8Pi2Qt2nfdCSXmQbXlhN1mTkSS3eVccM/f8ZuMPHJzWcT8OpOuiITbjweraq0w9HyKL2qaqlos7K0QO/TqU0t3S+17hDfbizjq+0H2FZTgqTX3kSjusZy69iu9IiMp7paamZBaeBI97OglSghWP06fP8sBNxamujznoeBVx3Zd6ETo6oq72x/h+fXPo+iKoxMGsmc8XPCnja29vvvKbz3PlS/H+sZZ9DllVfQRXQMH+vW0Jp+PeD28tHsdbiqfSR3czDt3sHoDOHT7lVV5Yu5z7Fr1XIiYmK57rl5WO0H/yev18vevXvJysrCbDY3Wikk6ch9mKp2DGsFgKqoBEpcEFKRI43ow+wy5vf7G+tJxMXFYTyKNvXMM8/wwQcfsGnTprAd/1CrUYPloiH7U1v+B6+3GL+/DL0+Aqv16DJnU/z+gwryoTTM98shct0+ZAn6RFjQtWM/eOg93hSn04nD4Tim7NypLBWqqnLXXXexYMEClixZckyFArQcyUfTmDsaTUfvvSGF+3YUUKoGSI9RuaryT/hVE2mDbiQj47eN2yxZ8j27d+8EDIzsdjbVP4TwhkxEjEhEjk4gqvbgTe2sqmbx31/C7/WS0r0XY6+9jW/f3I63LkBcqo3Rl/dEbuEJMJkgVFPDgXtu10zr/fvTpb4q68baH/hf7nzUQCR3jbqFMalj8fuP7sPeLPXnnmWaQgEwZRakDsKgtuxmcqrdeH7cVYYalBmVloqnThdW3/9TRdOMSC318w2j7w3xX6fCCtPaNrX1Zdz0ftlb7uKT9YUs3FxEjSeA4tVjsBq4cGgst4zJYkCXKEBb3+sNXzyLoJ6iTfD53XBgvfY7YzRMfxWiM9u1WScLd8DNs6ue5fM9nwNwafdL+cMZfwh7YbvKf/+HklmzQFGImDCB1BfnIHeidx4cu18/sD/Aqv9swFXtIzrZxnl3DAirQgHw04fvsWvVcmSdngvueaSZQnEkmmYbOpSjjZy3ByGnD0Iq6GV0keE1n6iq2mjFsFgsR1Qo6urqyMvL45VXXmm0BIQLWdbul4b4lgZlQqdrW3yLqoYIBCoAMBhiW73doYHhLbVXUaCyPi2VQ69rV4UiXHQqpeLOO+/k3Xff5dNPPyUyMrIxV7LD4Wjml9dZaeoSoqoqT+YUsrnWg10ncWvoOeymYszmqaSn/6HRLWPjxo2sWbMcnS6KbknnElwewu3ToesRiyc1kZ07tYdq6FDQy16W/PNv1FbWEJOczJgb7uK7/+RSXuTFEWNi/LV90Fv0LT4EajBI4X334d+7F31SEl3+9gqyxcLuqt08sfYRDNEhpqX8hompF1BTc2z//0ahsroc49f1xWcGXgO9zgdaFirbw41nT7mLkEdPtxhHh4pHOB6OlRGpocJ0UdHJdydrbZtONMNVU3w+yC/y8ePeEhbvLGHrgYOm+yS7ifNGpXJuzxSGDzA3O86pqKfxq8JbA0tnw6rXQA2B2QGTntEyPHWEIdyTwJ6aPTyw5AFyqnOQJZn7htzHDX1vCGuCBzUYpOTPs6h6910AHJddSvKTTyK1EODakTlWv240hPji9R0oNR6iYk1ceNdAzLbwKmY7Vi7jpw+16zjx5jtI7dWnVds1jIYfyVLRUWRExRdCqdNGjfRRJiQ5vA3zeDwEAgEkSSIy8vDMSA3MnDmT9957j+nTpx/m+hQOGhSLcGbi8vsrUVUFWTa1mPXpaBxL6QyGVKrrsz7FGDrXc3skOtVZvPbaawDN/M3gYEXGzk7T0fs39pfxVXkNeglu079LjDcHq70HWZkPo6raXZqbu5+PPlqIougY0n8wyg8SFU495i5WYkclI8kH3UiKilS2ff4ytUU7CepTGXb5/SxZUM2uzX4MRitjzu+JTzERHdmyIFf2yiu4Vv6EZLWS9tqrGBIS8AQ93L/kfjxBD6MyRvL0xNsIBVrn/98oVL4/F6OnCuJ6wbhHGpe3JFSGq7DZ8eDxqKh+A5FHcE1uj3iEE+FIGZEqK7V4g6gorf2n0goT7gxXDdR4AizeXsKHPxexbJ0b1RBAkkCWYHR2HBcPSWVU1zhkSTpiEoFwxbP8qlFC8Mt8zdXJrblF0PdimPIcRCYefdtOzNd7v+aJlU/gDrqJs8Qxe+xshicND+sxQjU1FD74EK4ftcq7CQ8+QMyMGZ2ysvvR+vWAP8Syd7ZRus9FSqKBC+8eSGRMeDukA7u2882rcwEYev50+p/TOn/1hsDsI7m3HMmP/1SjKirBKi1zlWw1IJvDK/YpitKYACciIqLFrE0NvP3227z99tthPX5LhOuaq6qC36/1XUbj4TF2x+JYSmdNKISiglknYTsFCWBOBZ1KqeiE4R/HRcPo/bLSWl4t0Iqm3Gj9mfS67zEaY+ie/RySZMHvh4KCWv7xj2+oq4skPS0Tx+ZE3AEv/lgbMWen4g9IyLImmKemws/f/kzpmt3YrDD4opvZtlnP7nUlGHUKw87LotZvhWro2kIyEteqVVT8n+aelPzM05h7aznV56ydQ54zjwRLAi+MfQG9rD+utPIxNcvw7PmcqmA0tnP+hEFvJnAUt6lT5TLTgM8HcWYLStBDfnXLBRY7SzagI42+g6ZQNE1HfqqsMOG0CByo9vDd9hK+3VrCqj0VjUHXKhb6JEYxdVACk3onEhtx8AY9WhKBBoQicYLsXQZfPwol9Xn843rA5FnQfWL7tuskUuuv5S8//4XPcj8DYHjScGaPnU2cJa7V+2iNEuvdsYP9d91NYN8+JLOZlNnPYe/AgZvH4kj9esAfYvHb29i/24nRaOC82/oTmxLewPOK/QUs+MtTBAN+ug4Zztj/95vj2l6vP6gUteTH3xGMRqFqHwQV0MnoosLfoTmdThRFQafTdZhaCeEiEKhCVYNIsgGDIeq4tj2W0hlSVKpCQSQZ4oz6Tjkg0BId4JYXNGAygcvg5w9bDqCa4fzISgY530CSDPTu9RdCoSQsFigtVfjgg+/w+52kpERxlr0XW1f7CMhm+l7eBUu8vvHFpKqwd3sBa75diUmfxhnjxqM3p5C3SqsMnTE4heTsGBqShLjdmpDZQKi6mgMPPQyqStTll+E4X3NPWlG4gv/t/B8Az571LFHmJhu1BlXFvPwpUu1FVPa4i9qofrhrtAfQZoPY2MOFylPhMgPNs5B0tyUQqnOz4McKrhueRbS9+SPTmbIBHTr6HghoLk9Hul6nwgpzohaBkKKyaX81y3aV8932EjYX1jRbnp0QwQUDkjkjKZVIydZi0HW47hdBE/avg++fhj1LtN9mB4x/FIbPAJ3htLX8/Fz0M39c8UeKXEVISNzc/2buGHQHerl1r9jWZrSr/uQTip94EtXnw5CaSuq8v2Kpr1bcWWmpX29QKIpya1BlExfd3pPMPuFNrOIsL+PDPz+O11VHcveeXHDPI8hyC9LfUThZfvzhQvEEUNz1bk8x4Xd78vl8uN1uQCuq15oUq50FVVUPsVIc/7kdTel0KSECkoJegujTxPUJhFLRoQgoKo+XFOCUgnQN6ji76k+oMqR1uQuPpz8Ggza6umrVOqqq9mAy6ZkyaDz+L8qwm0xU9EnDq7fgqO+YfT4o3Ofh+/9+gUFyk94rm/QBo1n9yS4CAYVuvaxMvjoFvV7r2Fsq7FU6Zw7BsjKMXbuS+OijAPhDfmb9PAuAa3tfy6iUY1ejbGhPo0Cx73soXIvZbCHlkt9SE4Lyck2p8XqhuFgT+g59qZ4sl5kGDs1CcuHIeP6xtIADRSrPvJ/Ln67tgcVysGNuSTDt6IJT0zadTHey47kOrblOBRVufswpY/nuclbklOP0BhuXSRIMTY9mUp9EJvVJpGu8piU3/J8i6PokU7IVvv/TwYrYsgGG/QbG/x6sMZrQXHJq0kCfSjxBDy+vf5l/b/s3AF0iuvCns/7EkMQhrd5Ha4pAGkMuimfNoubDjwCwjR1D6uzZ6JqOAHVimvbrejnIj+9upzDXiaozce5NPek9JLwKhau6io/+9Bh1FeXEpKZx8SNPYDjBG/Fk+PGHAzWoEKzSMl/KkUZkU/jdnqqrqwGwWq2dKiFOawgEqlAUP5Kkw2hoYVSqFRxN6awOBZEkiDXoT4sA7QaEUtGBmJNXzFpvHfZEmZtdf0WpDoFlKsHgZdTWaoLXjh3FLF++HptNx7njxyMvqcCoU4kbGoM71k5trSbkGo3gdMLG73/AX1dFVJyVURdPI39zCb5KJ5JsYNDUbthsB3u/Q4XIqp9+ofh/nyNjIOOZp5Hrg+H/s/0/5DvziTXHMnPQzGOeV4ujcD8sICZowjzierz6BMpLtPUiI4/u13+yg2gPz0Ii88fLu3H3P7axeEMNsm4Xz1ybjQ7dYYLpqayfEQ5OljtZOK6DqqrsLXexNq+KtfmVrN5bSX6Fu9k6kWY9Z3aL5eyeCUzonUh85OEvNRF0fZIpXAc/vgg7vgRUkGQYeLUWHxWdAZy8yuntzYrCFTy76ln21+0H4LIel/HQsIewGo6v2NwxMx8t34by/H0E8gtAkoi7807i7rgdqSNIrmGi4Tndn+fj09d2UFXswWgycNFtmkIRzvvDXVPNB8/8gcoD+4mIjePSR5/GEtl2paUj/R2qqhKs9IKiIhl06OzhL5ZRW1tLKBRCluUOmZ6/Laiqgs+vuaAbjQlI0vFZsJrSktLpVUO4FQUkiDWeXmL46XU2nZj1Tjfz8ksAeCh+Jd10iwmYu5OUdA+qquXM93j8rFq1HL/fQFbWAOJ2WVA8XgyJVrpenIprK+zfD4mJmoktd0seezZswqgLMvKiizDqJHJ/LgJVYtj5qag6czOrRIMQ6fdDZaXK9ifewhNIxTFlItXJQ5G9ENK5eHPzmwDcO/ReIoxH93FtUaCoq6Nqyy945GRS+1x/3GliT1YQ7ZGykIzuEcNjl3Xl2Y9y+W5DNXlV63ngvGxG9YpqFEw7o+B0MtzJTvQ6ePwhthU5+SW/ijV5lazLr6LC5W+2jl6WGJIezVnd4zirexwDUh3oWxHcJoKuw4yqau5Ny1+CvUsPzu8zHc7+A8T3aLZ6R6zm3hbKPeXMXjObr/Z+BUCiNbFZbZ7j4WiZj9RgEN9H75I//3+kykVYU5NJ+ctfsI0c0dZT6JB4ql2s/PdGdG4fXVJMXHBHX7p0P75sO8fC7azhg2f+QMX+AiJiYrni8T9jj4sP6zE6AqFqH6o/BLKEPtYcdn99n8+Hy6XFGTocjtPK7QnA769AVQLIsgGjMTzm7KaXqNSjWdmj9DqMp9m1E0pFB8AbUrhnewEKcF5UiB6VzwOQlv4sqAdTmS5btgqv10lUlJH+8f0pWVFAgl3CcUFXjDaZrKyDo8SyHGDt14sx6N1kDxlCt/7d2LF4B3opQGRyNN0Hx1NX11x7drm0QmPl5VCxdDXkbsVuM5Dy2xsbhcLvaz6m1l9Lpj2Ti7pddMxza1GgqNiI0VRBlb4XRUpf/CeYJjbcguHRspBMH55CXJSRJ/63iwJ/NfcvLGPy/nhuHduVoRnRVFZKnVJwCrc7WWsEyOi4ENuKati8v4bNhU62FNawu7QW5ZA8DEa9zKAuUQzNjGZ4ZjQjsmKJaIMJXygSbSQUgO2fw8p5B2tNyHrofwWMvgcSeh22SUes5n6iBJUgH+36iL+u/yu1/lpkSeaaXtcwc/BMbIYTC1A9Up/jy8+n9Lnn8GzeQkiJxHbeVLKeeRSdI7xF8zoKxXtr+PKVTXhdAeKSLFx49yAc8eFNE19XWcFHf36c8n352KJjuOLxPxOd1AE75TYScgVQXA1xFGYkfXiF1lAoRFVVFaC5PZ0O6fyboigh/P4yAIzGxBOKpTganpBCTUBLI5tgDG9q5I6AUCo6APMKStjl9hJn0HGF5zEA4uKuRa8bdjC2obSUjRvXYDBYGTLobOSfS3AH9BiHJaBG2/B4tBfUiBGaz97yz35Cce/H7jByzpWTwFNN0a5ybBYdQyZ3obJSQqfT1m1aqA40oVD5+C0MUpDoS6/CmhCNFc168d66b8AIN/S9AfkYD9sRBYpSLUjclt6dmloJVaUxUPxQTmV2pWO5A43IiOOtmyP5YOcuFmwq4NttJXy7rYSe8Q7OSkxnQr94ojm8g+3IglM43YMO/b/9QYX9VW72lLnYU15HbrGH3GI3RaEKVN3hf2hchIlBaQ6GZcYwPDOafqkOTPoTNzsLwkRtCax7G9a9BbVF2jy9BYZcD2fOhKj0I27aHmmgTwYrC1fy/NrnyanOAaB3TG+eOPMJ+sa2LUj60D5H9fupfOcdqv79H9RggJDFQdId99LlpnPQmU8fv+um7FxdzA//3kEoqJCQEcn5dw7EGmZ3nariA3z47GM4y0oOKhTJqWE9RkdA8YUIVdenj7Ubw54+VlVVqqurURQFvV5/2rk9Afj9ZahqCFk2HXfGp9ZQ4tcUPodBh+U0SSPbFKFUtDMFHl9j+tj7ordhKNmGyZRE16yH2LdPe+mqqsqSJUsA6NevCym1ZiqrnQTMJpyZqZTtOagUOBwQG+WmatM/SXboGHDBDWRk2fjmDS21Y58z4+nV30p+vvYir67WjhEbqwmDxcWgK87Bt2M76A1EXXF5Y1sPBHaxr6Iae2Ik52Wdd8xzO6JA4a6vThkd35jD+VSliT0arXEHSk8yMWdIf247J5M3f9zLpxsL2X6gls3b9/D6yl30TIpkWEY0QzKiGZQWhd1i6PCCU1vcg0KKSlGNh4IKN7sPeNi4zU95wEVeuYuCSjfBJuYHVQXVr0fvgMQoE/1THfRLddC/fkq0m06btHqdHlWF/Wvg57/D1k9AqS+3bkvQArBH3Aq2Y6dKPdVpoMPNnpo9zFk7h2X7lwHgMDm4Y+AdXNHzilZndjoaTfuc0M7NlDz/PIG8PACsZ5yB8ab7ie+V1OFcJ8OBoqj8tCCXDYsKAMgcEMekm/pgDLMgXLI3l49nPYG7ppqoxGQu/cMzRCUmHXvDToYaVAhWeLTQJrO+sWr2smXLeP7551m3bh1FRUUsWLCA6dOnN99WVXniiSd44403qK6uZvTo0bz22mt07969cZ3Kykpuv/12Fi5ciCzLXHLJJbz88stEHGlEEPB6vTzwwAP897//xefzMXnyZF599VUSEztmnZpQyNeY8clkSmp8H/3www88//zzrF69Go/HQ2ZmJlOnTuX+++8nNbX1ymlTK0XiIVaKvLw8srKyWL9+PYMGDQrPCbUDQqloZ57JLcKrqIxymOha9icUILvbIxiNkY0v48LCPPbuLUSWjZw1fBTed/NwSjqq0hMpLpMba1FERGiuLD8sXoG7poaMrCSGTjiTPdvqKNjpRK+X6HlmKtXV2svs0Jd8gxLgX/wtALYzz0TfxI9lbdkqUHSMThnTqmDEIwoUiuZPGFCMWCzaMpfr5KaJhdYJza11B+qeGMlzlw3g9+f14qM1B/h4aTWbiirYVVLLrpJa3v1Ze1GmRVvoFmcnKzqSMwMWuidb6RJtxWzoeCPwh14TVVWp9QUpqfFSVOOl2OnVvju9HKjWFIl9VW4CIU1xUIMywRoL6EJIOm2e1agjKy6CrnFW0qMiSHFEcGY/G11izSK2oSNSVwqb/gfr/wNlOw7OTxupKRK9LwJ960eRT1Ua6HBT7Crm75v+zoLdCwiqQfSSnqt6XcVtA2/DYQqvC5JdqiLv/+az5/NvscgejNHRRN1xN/KIc7BYpNMyQ5nXFWDRP7ZSsK0SgKFTMxh5Ydewpzzdv20LC2Y/jd/jJj4ji0sffRpb1Ill8unIqIpKsNxTH5gta25P9QKxy+Vi4MCB3HTTTVxyySUtbj979mzmzZvHv/71L7KysnjssceYPHky27Ztw1yv0V599dXs37+f9957D6PRyJ133smtt97Ku/UV3Vvivvvu48svv+SDDz7A4XAwc+ZMLrnkElasWBH+i9AGVFUlGAwSCBwAVPT6iMbq2f/3f//HHXfcwQ033MBHH31EZmYmBQUFzJ8/nzlz5vDiiy+2+jglPm1wJqqdrRShUAhJkk5KLIxQKtqRX2pcfF5WjQzcbFyIoriIjOxPYuIFSJL2Mi4qUlm4cB1Op4NevfpQvNKPVCsRjLaRNSqK7j2aC8mKEmLjkqUEfZFMnX4R6Rl6Nn5bRFCRSekeh6qz4K07KCA3CM0lJQfzJ7t//gWAyAnnNGvvjrJckEMMSRrUqvM7okBhjcEXNFBZVEuMEZKTT27az+PJRnS87kBRViMzxmUytTvsLfSxq7qKdflVrM+vIr/Szb4qD/lFAWRzMf/ergUeSxIk2c2kxVhJcZiJizARF2kivv4zymLAZtITYdJjM+mwGfXIbXjZBkIKbl8Ilz+I2x/E5Qvh8gWp9QWpdvupdAWocvupdPmpcvmpcvupcgcocXpx+0PH3L9BJ5EWbSU91kq0Gkm0PoLemRa6xttIsh98uRUXa+srLtjr7PjZsX41hAKw+1tNkdj9baPSj94M/S6DEbdAyqAT3v3JTgMdTso95fxj8z94f+f7+BXteR3fZTwPDHuATEdmWI+lBgJUvfceZa/8DWu1F7/sQJ44nZibbsYQZT9tn43SfCffvLkVZ5kHvVHmnOt7031Y+Eeuty5dzKK/v0woGKRL735Mf/gxTNbTqzgb1AvEFR7UoAI6CX2spZlyNnXqVKZOnXrU7efOncsf//hHpk2bBsD8+fNJTEzkk08+4aqrrmLLli18++23LFy4kJEjRxIdHc3LL7/MeeedxwsvvEBKCwGDNTU1/OMf/+Ddd9/lnHM0WeKtt96id+/erFq1ijPOOOOwbZYtW8aECRPYt28fSU0qst57772sW7eOH+sryC9fvpzf//73rF27lri4OC6++GJmzZrVWHzv3//+N3/961/ZuXMnNpuNc845h7lz55KQkADAkiVLOPvss1m4cCF//OMf2bx5MwsXfsyIERmAhMmUgiRJ7N+/n7vvvpu7776bl156qbE9mZmZjB07tjGlLsBHH33E448/Tk5ODsnJydx111088MADjcszMjO56PrfsG9vLos/WUB0dDR//OMfufXWWwHIysoCYPDgwQCMGzeOJUuWoCgKzz77LH//+98pKyujd+/e/OUvf2HKlCnNzqWqqoqo+hTTGzZsYPDgwezdu5fMzEzefvtt7r33XubPn8/vfvc7du3aRU5ODpmZmUe8L04UoVS0Ez4fvLCzFNUvcUkXC9ayN1GA7tm/awwMslph164ScnN9RERIjBrRj4p/76W02gzZCfRJlTg0Rqpw+zZ8NYXIxli6jTgbg0HBmVdMbGSQ8RfGoo88KCSDJnBXV0NdnfbS99U4ce/0kWIwYqm/uRvYW16Czuyib2J2q8/zUIEiFILy0BDKSnth8OzH4FQxmSRiYzUBPtxpP08kG9GJuANp52kiyprE2d2TMBigrMbP5jwXBTVODgSq2FtVS0GlmzpfkKL60f/WYjXqMOlldLKMXpbQyRJ6nfYpobkhBRWVYEj7DCkKQUXFF1TwB9vmd+WwGEiym0l0mEmu/0xxmEmP0RSJZIcFXf1LrNn1rr83tWxi2n0WFaVdy86QHeu0RlFg3yrY8jFsXQDu8oPLUofB4P8H/S7Rite1kc6Q1rfCU8H8bfN5b8d7eIIeAIYlDuOuwXcdV82J1lK3bBklf3kO/549ANj79KL773+PftCI0zZDmaqqbPp+Pys/zkEJqUTGmJl6e3/i08Kb4UlRQix/bz5rPtNqemQPH8V5dz+IwRjeC6qqqpYWtB2wyjKSJKGqKqFKL6ovBFK9QnGcgdl79+6luLiYiRMPVrt3OByMHDmSn376iSuvvJLFixfjcDgYOnQoUVFRSJLExIkTkWWZ1atXc/HFFx+233Xr1hEIBJrtt1evXqSnp/PTTz+1qFSMHTuWrl278u9//5uHHnoIgEAgwDvvvMPs2bMByM3NZcqUKTz77LP885//pKysjJkzZzJz5kzeeuutxm2eeeYZevbsSWlpKffffz833ngjCxcubHa83/3ud7zwwgtkZWVgMGpWM6MpDp1Ou1c++OAD/H4/Dz/8cIvXrkGIX7duHVdccQVPPvkkV155JStXruSOO+4gNjaWG2+8UfufVJV/vzKPBx9/gheeeJwPP/yQ22+/nXHjxtGzZ09+/vlnRowYwXfffUffvn0x1o/E/vWvf2XOnDn83//9H4MHD+af//wnF110EVu3bm3mnnYs3G43zz33HG+++SaxsbGNCla4EUrFKaZh1Hx9sYdvtnqRZANjzT/h9UJc3GCiokY2rut2Q17eBuz2WjIz++De5SfkVUhOlvD1cBAIHL7/PevXIEshMgcNR2c0U7S7Eq8rgD3KQJceURTsOxhI21BkzufTFJjERCjeV0KpYqPANoSkYBRWt6YIBIPgVqvQ2ZxEm1pvPm4qUJSXw4EDENQPIN7hJs64E131T1Tpz2wULGNjw5v2sy3pLFs6/pEUjZYEJ4vOyIRBRmJiojGbtZz9qqpS6fJTUOmmoNJNidNLeZ2f8lofZXU+ymp9OD0B6nxBXP4QofqYBLc/1CqrwdEw6mSs9ZYPm0mHzaQnxmokymokxmYg2mZs/B1tNZBgN5NkN2Mxtt5V60gCJGgKRZPBp06RHeu0QlWh8BfY8pGmSNQeOLjMlgADr4JB17aYxamtdNS0voV1hby95W0W5CzAF9IKhQ2IG8DMwTM5I/mMsMf4eLdto/SlubjqR1x1MTHE33MPUZddiqTreC6R4cJbF2Dxv7aRt1mLp+s6OJ6z/18vzLbwZr/xud0sfPl59vyyBoCRF1/J6CuuPSk1PdyKQrdlm8O+39aQO7Y/VlkmVOVD8QRBAn2sGfk4+uoGiutNyIfGOSQmJlJcXExNTQ1FRUXExsYSExPT6DKj1+uJiYlp3L6l/RqNxkbB+9D9HokZM2bw1ltvNSoVn3/+OV6vlyuuuAKAWbNmce2113LvvfcC0L17d+bNm8e4ceN47bXXMJvN3HTTTY3769q1K/PmzWP48OHU1dU1iwF5+umnmTRpEl5vEX6/D1k2YDIeFLZ3796N3W4nOTn5aJeQF198kQkTJvDYY1qinR49erBt2zaef/55brzxRqqDIRTgrHPP5eG7Z2KUZR555BFeeuklfvjhB3r27El8vJbaODY2tpmV5oUXXuCRRx7hqquuAuC5557jhx9+YO7cufztb387aruaEggEePXVVxk4cGCrtzkRhFJxCmk6ivtpVSWSLcQERySe/M/xSon07fPbxpeY0wkFBR4KC3cRGRlg0qTesLgMu91H5OhUSmMlqqu1kb6Gl7OqquRvWo+i6sgcOABZhuI9NQB06RUDktwscLq6WnvJN2QpVFUwuKtI1hVRHJHNpk1gt2uCX0ICmCPr8Ov9KBzf6ExTgSI+HmJirJjqRsGGXFj1PMZrPqDKqQ+7YBnOdJatcaFqjeAkSRKxESZiI0wMTj+6cqaqmqWhzhfE5QsSCCmHWyNCKoqquSDpZAmDTtasGLKEXidj0ElEmPRYjXqMYU4teCQOvQ6BABQVHfkad+TsWJ2eUBAKfoKdX8GOL6A6HwBf0IhiTEDuPRXT4IsgaxzoTn56w47y/+6u2s0/t/yTr/Z+RUjVlPX+cf25dcCtjOsyLvx5/XNyKHv5FWq/+UabYTAQc911xN1+G7rI8I7UdzQKtlXw/fwduKp9yHqJsy7rTr9xqWG/xlVFhXz6wp+o2F+A3mDk3NvvoffocWE9RodBVQnV+FHcB1PHhjvTE0AwGMTt1oqO6nQ69PrwHqNv377k52t90pgxY/jqq6+48cYb+eMf/9joIvX2229zxRVXNLo2bdy4kU2bNvHOO+807kdVVRRFYe/evfTu3Zt169bx5JNPsnHjRqqqqlDqLUoFBQX06dOncbthw4YRDLqbBGenNEshq6pqq+7T7du3N7qONTB69Gjmzp1LIBikqD6WYsjAgY11KSRJIikpidLS0iPu1+l0cuDAAUaPHn3Yvjdu3HjMdjXFaDQyYMCA49rmRBBKxSmkYdTcbFdYtLMGSYLzo4ow1RTi86Wj053TKLyWlcGqVYXU1UUQGRlBdEQ01YV7MepU7ANj8Pu1QndNra91VZW4nTUEFTvZA7tjMkFZQR0AiZn2ZoHTqqq5PFmbxFsHg9pUq9qxW/zExUFaGuj12nyLP41qpYQSVwk9ontwPPh8mhtMbGx9fMUZd8C2z7T0ssvnYBv1SNgFy3ClszxeF6pwtV+SJMwGHWaDjriIDiKNHQdNr8PpkFa00+CrhZzvNEVi1zfgrW5c5CWGyuSLqU2fRqjLGeiMJiKtEBMA8+k7UA6AoiosL1zOO9vfYeWBlY3zRyWP4ub+NzM8aXjYBV3/vn2Uv/IKNZ9/od3gkoT9/POJv2smxoyMsB4r3LTVquT3BlnxUQ7bftQsYlGJVs69uW/Y3Z0AdqxYyrd/f4WA14MtOobpD/6RpOzje0cdL1ZZJnds/5N6jBZRVYx1QZQ6TVDVRZuRLcc3INC0r20YFS8pKWk2Il9UVETPnj0ByMjIoKysrNk+gsEglZWVzUbVm5KUlITf76e6urqZtaKkpKRxm4ULFxKod7loqHeRkJDAhRdeyFtvvUVWVhZfffVVY/ZLgLq6On77299y9913H3bM9PR0XC4XkydPZvLkybzzzjvEx8dTUFDA5MmT8fubF1S1Wi14vfsBMBiiMBiap8jt0aNHo6XmWNaKI1HqDxJQVCQgytz8QZIkqVHhOVEaLEeqejDTYqAFNxaLxXJKsisKpeIU0XTU/PtKJ3UhhRSTkRTXQiqALqlnUlGho6ZGE/jNZqiszEOSFBISstm3oQ6jH6zxJgyxFmxOrVCdsz7g1WCA4r0FePw2ErrEkpik3bx11ZpJPzLW3Cxw2mzWOpamAw9uN6gGTTqO9BVjNmvrNcRtZNh6sL9yFxvKNjCmy5jjOv/DBHxbLJz7NHxxL6z9JwZLLO4eN4dVsAxXOsvTrSLwqaazpxXt8KgqlO2EPT/A7kWQ9yOEmrw8rbHQYwrezPMpNJ2DV7F0mqrv4aDWX8unOZ/y7o532Ve7DwAJiYkZE5nRbwZ949pWa6IlfLm5VLz5D2o+/1wbkQEiJ00k7q67MPc4ucJuWzmexBZHYt+OSn6Yv4PaSi1urP/ZXRg1vRsGU3PNta2KS8DvY8nbb7Bp8dcAdOndj/PvfoiImNjj39lxIkkStlPssqaqKqEa30GFIsqE7jhdyAIBbYCvIZ17amoWSUlJLF68uDGVaVlZGWvWrOGaa64hIiKC8ePHU11dzbp16xg6dCgA33//PYqiMHLkyBaPM3ToUAwGA4sXL+bSSy8FYOfOnRQUFDBq1ChAU1Za4uabb+bqq6+mS5cudOvWrdlI/ZAhQ9i2bRvZ2S3Hdm7evJmKigr+8pe/kJaWBsDatWtbXNfnK0WnCyBJekymw5WGyy67jN/97nfMnj27WaB2Aw0KU+/evQ/LaLVixQq69+hBRUgTanSShHwUob4hhiIUOujmbLfbSUlJYcWKFYwbd9DqtmLFCkaMGAHQ6DZVVFREdL2QsmHDhiMe52QjlIpTRFOhemlpHapf4uy4SJzVPwOQlDSe0lKt805O1joPp7MQRdHRo0cSrm0ePF4dUV00f8BQCLKztU6+wXe9urwWi8FFeqYBSdIEhTqn9kIz27S/uiFw2unU9hEIaB2L2619mrskYZa9+IrLkAJeZPngW+SM9P4sO/ADX+76jpmDZh6X1tuiYNlzKlTsgZ/mEVgyF11ZNXLG3UB4Ch+FI53l6VQRuL3orGlFOzSuctizBHK/h9wfmsdHAMR0g17nQc/zIW0EyDoqD4C36tehHKuqypbyLXyc8zEL9yzEHdRcOCINkVzS/RKu7HUlaZFpYT+uZ9Mmyv/+d+q+W9w4z3bWWcTfcw+W/v3CfrxwcyKJLZpt7wqw6pNcttZbJyJjzUy4vjepPZu7eoZDcak8sJ8vXvoLZQV5IEmccfEVjLrsGuTTNDalRYUi4tjvyrq6OnJychoH7Pbu3cumTRuIiYkhLS0dRZG48857efbZZ+nevTtdunTh0UcfJTExkWnTphEZGUnv3r2ZMmUKt9xyC6+//jqBQICZM2dy1VVXNWZ+KiwsZMKECcyfP58RI0bgcDiYMWMG999/PzExMdjtdu666y5GjRrVYpB2UyZPnozdbufZZ5/l6aefbrbskUce4YwzzmDmzJncfPPN2Gw2tm3bxqJFi3jllVdIT0/HaDTy8ssvc9ttt7FlyxaeeeaZFo/j91dgtdoxm1ORW6g7k5aWxksvvcTMmTNxOp1cf/31ZGZmsn//fubPn09ERARz5szhgQceYPjw4TzzzDNceeWV/PTTT7zyyis8+dJfUVWw6mSONWaWkJCAxWLh66+/pkuXLpjNZhwOBw899BBPPPEE3bp1Y9CgQbz11lts2LCh0f0rOzubtLQ0nnzySf70pz+xa9cu5syZc4yjnTyEUnGKkGVtwGrfPpUVu/2EvAa6WHyUluqJtEciSb3xejWFQhNkXQQCTnQ6CwZDHAFXIS6/Hq/V0mhpSEnRPhtGe6p2VGI11eIjlrw8rbOurLPgrQvgqtNMYw2BtBaL1qGXlmoBtA6HtqxEjccUF01NqQd5zyZMfUc0nsPZmWN4ec0/2efM4Zv8b5iSOaXV539EwfLMO0Gnw7Xon0Rv/zumd7+Caa9AQu+wXPe2prMMhwtVRwtObQ86U1rRDom7EvathvwVsGcpFG9qvlxvhowzoevZ0GMKxDcfDf+1KMfV3mq+2PMFH+d8zO6q3QAoAQNdI3tzVZ8ruLjXea2qsXM8qIqCa8VKKt58E/fq1Y3zIydNJPbmm7Gc5MDIcHKiVllVVdm5qpiVH+fgqdWE3n5jUxl1SbfDitm1VXFRFYWNi75i6Tv/JOjzYbE7OG/mA2QODH+Wro6CqqpaULb7oMtTay0Ua9eu5eyzz278/cgj9wNw3XU38Oabb6PTwf33P4zH4+LWW2+lurqa4cOH8/7775OcnNw4ePjOO+8wc+ZMJkyYgCzLXHrppcybN69xv4FAgJ07dzbGYAC89NJLjes2LX53LGRZ5sYbb+TPf/4z119/fbNlAwYMYOnSpfzhD39gzJgxqKpKt27duPLKKwFt5P7tt9/m0UcfZd68eQwZMoQXXniBiy66qHEfinLQGmAwRB/m9tSUO+64gx49evDCCy9w8cUXNxa/u+CCC7j/fu1aDhkyhPfff5/HH3+cZ555huTkZH73xJNMvvpaJAm6mI+t/On1eubNm8fTTz/N448/zpgxY1iyZAl33303NTU1PPDAA5SWltKnTx8+++yzxsxPBoOB9957j9tvv50BAwYwfPhwnn32WS6//PJjHPHkIKlNHbF+BTidThwOBzU1Nae0xLzXC7/8ArsPBLi3JBdZB290KWHPzteJie5Gr17PUlsLcXGaoFVSUsrChV9gNlu44oqrqfg0h9p9HnpfnkL62NgWR3RWf/4Vn7z2ESn9hnPhHb/FYIAvX99C7jYXoy/OZNyFiY1B2QA1NbBvn9ahR0drgu/evVD+73cIff856aO70nXOnxvX9/vhrY3v8mHZCyRaE3n3vP8SbXG0Wgg50svE5QJz4fekrvotZqUUZD2Mmgln3QuWthcqasuomM8HeXktFwsE7Zr4fJCZebgwFo7RuNMJcT2Og9piyF95cCrdevg6if2h29nalD4KDJbD16nH49GebYdDs0geiqpq/UFWFoelqe7ohJQQq4tXs2D3AhYXLCZQX/1bH4zgzOgLGBd/AX1jBqDXS2G930J1ddQs+ISqd97BX18FG70ex0UXETvjJkzdurX9IKeQE+3rKg7UsfTdnRTlaElBopNtjLu6B6k9Wu67DxzQFIjoFhY3zD+SxcxZXso3r/2Vgi1akGpa3wGcN/OBU+Lu5PV62bt3L1lZWY0F4U4FqqISrPSiejWvg+NRKBpQFO3/k6QjP/+BQJDa2nJUVcFgMBAbG3tSiqO1lhkzZlBWVsZnn30W1v2qqorHU0Aw6ESWDdhs3ZGk8Fq3gorKDpeHkAqJJgNJppOfBCMcHO0eb63sLCwVp4jKSu1F5rL5wacj2S6jUw5gNntwubtRW6sJ2BUV2os/FPLg8RhQlAQtDatXwqRTiI5RiI5uuWPwqTEEFQOStwijURPiZFsEvoCXLesDRKVrLlMNL1WHQ3s5NBX0DAaInnwO/PgvQmsO4F6/Hmt9vQqXC67sNZ3lpV9RUFDFfR/N5Q9nPkqMw9CqF/VR89V3OwfzyB9g4cOw80tYMRfWvgWj7oDht2gxGCdIW9JZnqjrTltH405HOmpa0XYn6IPiLVC4DgrXwv41ULnn8PViu2vWiMyzoOt4iGh9nvHTLa5FVVU2lW9i4Z6FfJP3DRXeisZlvWJ6cUH6ZQwwTMWo2sP+/Pn27KXqnXeo+eQTFJcLADkigqhLLyHmxhsxnGBAZ3tzvFZZryvA2i/z2LxkP4qiojfKDD8/i4ET0tAdIdPciVrMVFVly5JFLPnXG/g9HvRGE2OuuYHBky84KeliOwpqSCFY4UX119ehiDEjW05MbFPVIz/foVCQqqpqZFnBaGxfhaKmpobNmzfz7rvvhl2hAPAHKggGnYCExZIedoUC4IDPT0gFs04iwfjrErN/XWfbTjR0pDExEAr4kWwhEmQL1dVu/H4T6ekmZFnrtA0GrdOurNQTChmw2XwYjVDp0WHw6diRo8Mdr2Vtajrq5vOBKSoNo95LZeF+XHUBysoNWGId6HVluMsqCARSKSmRmr1UDxX0UlOhPDWZfZOnEfjmI4r/MpvkV/+OV45EkkANWrm3z5P8bvXd/OJcysubDNzR5yE8HkOrXtRHFSzNXeDqd7WsNYuf0UZnl8yCH1+EfpfCiJshZUjLGlUrOFEB9kRcd0Rw95H5VSsSiqIpDIVr65WIdVC8uXlgNQASJPWDjNGaIpE+6riUiEM5XeJadlXt4qu9X/HV3q8orCtsnO8wOZiSOYVLul9Cn9g+LY6Gt+X5U3w+ahd9R/VHH+L+adXBfXbtSvT/uxbHRdPQRXTuas2tVTxVRWHDd/tZuzAPn1sbPc8aGMdZV3THHnt0M9eJuJNWlxTz/T9fY++GdQAk9+jFlNvvIyYl9YTOs7OgBhWC5fWVsmWtsJ1sOnEBWJIOBmc3JRgMUFlZjaoqjbUn2tNCMW3aNH7++Wduu+02Jk2aFNZ9B4NufF6tRobZnIROF15XSABnMERVQHOv6mI2HjU4+3REKBWngKYdqV+noIsJkmBXSZYq0OmKiI/zU1enCfRut5YqNhjUYzT6CQYDWmA1ZpL1tSh1fhRFe/k3HXVTVYiISSLCEYGntobta3cSmdyPHgPsbP9ewl/noyy/mszM6EY3lKYv1QZhwmKpN3/fewPb166man8FgSf/Qo85T+BTjHg8MDSrG8+YHuPxFY+ztOg7nEoF9/R6AovF3uoX9VGFl55Toftk2PaJZrEo2ggb39WmuB7Q7zJNyYhrfWXvtnC8FYF/Lf7rgmMQ8EDpdk1pKNmiWSNKtoDPefi61lhIHXpw6jIcLFFhbU5njGtRVIVtFdv4vuB7FhcsZk/NQQuORW/hnPRzOC/rPEYlj8JQX2cjrPVptm+n+sOPqPniC5Qazb0HSSJi/Hii/9+12M4885SkaTwVHEvxrKtTce4v5+f/5OAs06qOx6baOPOSbNL7ts6SfDwWs2AgwNrPP2b1x/8jGPCj0+sZfeV1DL1gOrLc+YOxmypOh8rwijdIsNILigo6GX2cGdlw4ucsy9rU4HbaQCCgpXwNhcBo1BEXF42unQPdm6aPDSeKEsTrLQBU9AYHBkP4XeYCisI+jzZAFGfUn/LsYB0BoVScAprVh2iYZwCzXsJgCODza3Ptdu3lXlwMkZE2AgEjNTUeIERErI6YUBBLnQuXSxMAoqMPjrrFxoLeIJM+YARbl/3A5h/XMPHGfugMOroNTWDL8hK2rzzA8HEObDb5qC9VsxnSekRg//vv2XvDTUibP8f9bDXBu+dgs2sS9BkpZ/D06Kd5etXTrC9Zz4NVt3PPgEe4KHZAeARlWYZ+l0Dfi2H/WljzBmz9BMp3wZI/a1N8b+g+EbInaSO5+vBkjWqJ43HdCVd9DEEnQQlpReXKd2t1V4q3aIpExW5QW/iT9WZIHgipwyB1iKZERGeesAWutRyvctxeBEIB1pSs4fuC7/lh3w+Uug8WhzLIBsakjmFq16mM6zIOi/7wkfG2Pn/B8nKcX31NzYIFeLdta5yvT04m6uKLcVxyCcYup+coeUuKp9+vkrOpmh3L9hGqqcSgV7DajYyc1pVeo5KR5dbft621mJXs3sR3/3iVqgNaDYH0fgOYMOMOYlK6hOtU2w1F0ZK2KMpBy4Esa+ndZRlCdX5C9angJaMOfawZSdd2y4Fef/DZkGVNoaiqqkZRNIUiPj6q3RWKk4WqKni8BShKAFk2YjGHv/iiqqrs8/oJqipmnURyJ4mjCDdCqTgFNO1II+p9TeuCIYzWOACczmoS4ml0gYqJgcREKz//7MPjCVJXV0FcdgRyGShFtYQCCoqi7adh1K2hqFzygAlsWLKC/dt3UF2UT3x6Bj1HJLF1VSXeyjp2/VTIgLPTWiXUOgb1JvtvL7B/5kzqlq2gLP8Ruv/5d5Cq+QyfkXIG886exxMrn+BAXRGPLnuMTcGR3HfGbcSYj3/Ys0WBXZIgbbg2nfc87FgIWz7SUmmWbdemlS+DMQIyRuNLGo3S5Qzk1IGYIsIvJbVGYTrd/NcF9QQ8UJGjKbZlu6B8p6ZIVORA0NvyNtY4zY0psR8kDdC+x/U4JdWrW6KjxrWUuctYcWAFKwq1qTZQ27jMqrdyVupZTEifwFldzsJuPHqCjRN5/kJ1ddQu+g7nF1/g+umng52jwUDkhAlEXXoptjNHIZ2mQlcDTRVPp1Mld0sNW5fso7a4Gps5hMUKgyZlMnhS+mFZnVrL0SxmAXcFq7/+F3t+/h4AqyOK8dffTK/R4a9y3h40BEw3xDfIsvY9FAJFUZHdPqjP8CRb9eiizEjHobQdDVnWnodgEDweHzU1NYCK2WwgNjYK/RHiYDo7qqri9RYRCrqQJBmLJeOkxFGUB4LUBhUkCdLNpl+d21MDQqk4RTR0pLYaA2pQosDjRx+TRl2dnejo7XTponWqVmvDqIVMZmYyO3fms3dvCWefHY9+qx6vM4gurxq5qya0Gwxa51xYqFXIDsgpmFInU7RlG0ve+5AL774bX8jI0Emp7Fqym/Xf5mOPtxGXGdP4Uj2agGEYPpr4l98g/75HCObsZO/Nt5Ny/0wiJ05AkiSyo7N549w3eGXN//FlzmI+3P4p3+Z9y2/638B1A67AZji2n3GrswKZHTDoam1yV9YX+/oOcr7DW1ND5boN1PpzCSn/QaeXiczIIiY7G3NGH02gi+95SoS508V//VeJrxaq8qByL1TtPfi9cg9Ua6bzFtGZIK67do8l9oOk/toUkXjSLRAnQnvfe4FQgPWl6xsViZ1VO5stjzHHcHba2ZyTfg4jk0di0rW+wa19/gxBF84ffsS58CvqlixBbVJt1zxwAI7zL8B+4QXoW0pTdBpjMqmEnFVs+jSfwt01SJJKbLRE/3GpDD43A6u9bRbhlixmIb+H3Ss/Z8+PHyEpLpAkBp17HqOvvA6zLSJMZ9b+BIOaEtFUN5UkkFHwV/iQgyEMOtA5TMgRhrArUpqFwkVdXQ06HZhMJmJioto1huJk4w9UEAhUAmA2p6HThX+w0R0KUeTTlMEUkwFLGCxLnRWRUvYU4vXCnpIgY5bsAkXi0wHRFOZOx2L2csYZyygvt6OqmnKgpZXN4csvVxAKRXHLLeej31VG8dJSopIN9L2vN5JOorYW8vMhPl57UYZCsD/PyRtP/RtPXZDhY7sw6bpLiIqCtV/kkLO2BL9q4qJbu9N3RNQRhXloLugr5cXsfeoF/Dk5xBkqsY46k/i778KYqrkBFBfDlvLNvJP7Bnuq8kEO4bDLXDf0fK4bePkRLRdHTTNrbl2WFq9boXDDdrx7N2Kr/BlD8RoCrhpcfitmvY9UexFmvU8T/BJ6a8JefE9txDg2G6IyQBde/Toc53Uq6Ggj1icVVQVvDTgLoaZQ+3QWNlEi8sBdfvR9mKMO3jtxPQ5+j0qH08DP+2QRUkLsrNrJmuI1jVNDQTrQKlz3ie3D6NTRjEkdQ/+4/ujacD2P9Pw5D1QT/OUnIjcsJPTzsmaKhLFrVxwXXoD9/PMxpqe36Xw7I4qismd9Geu/zac0X7MUyXqJvmNSGTolA5sj/B2Exx1i4+JFrF7wHkGXlsGrS59+jL/uZhK7npqYudbS1pSyR0rrqviChKp9qAqokoQlzojeGv7xXq2grhNXfcYyq9WKw+E4LSxARyIQcOLx5ANgMiVhMsWH/RghVWW3y4tPUXHodWRYjJ32moYjpaxQKtqBMct3sqvOy3NZacTunkl5eSmZGfcRG3s+wWB90bpK8PlCfPfde9TWuhk0aDT9evag7oMdxOk9xE9NI2JEMjvrB/h69mx+jC0/beLdOZ9g0HmZcs1IzrhoGl6PwsJ/7KQirwp7RIhBF/QmMTvuMKG3IUsENH8hV5T4yX/nS9Qv38VBBXod2C6YDhdcRy3RWhG9qBBLD3zHO1v/R0F5BZLBjzW2inOzx3J5z8sZljis2QPXlpzlR9yHqkJVPhxYT9WeXKLd60nxLgV/bcs70Bm1CsRx9QpGVAZEpWmCoiMNzCd2n3TkugwduW0nRCgArjKoK4G6MqgtOlx5qCmEgOvY+7LGajEO0VnaZ0z9Z1wPsMV3SMtDRyOkhNhVtUtTIErWsK5kHbWHPH8x5hhGp4xmdOpoRqWMOiGXyaPRcI9X7i7GufwnvKtXIG9fS5RUhUnWlAlDejqRkybiuOACTL16dVphoC0EAyF2ripm/aICakq1AGydQabPmckMmZJBRHT4OwRVUdj980pWvP8OlYX7AIhOTmXstb+h27CRHfJ/CIdS4fM1tVKohGr9jRWyJYMMdjNmqxx211hFUaiursbr1dw0IyMjiYiI6JDXOVyEQh7c7j31dTeiMZ+kOIo8jx9nMIRBluhhNaMPk7taeyCUihOgIygVz+0p4sXdpQz1RXGfZTWlZS9jt2fRr+/buN0ykqQJyF4vrFu3mUWLluP3O5g2bRoJzjrUFfnIBhndhb2plmykp2tB3oey8vNFfP/et1hMLgZOnMSIC6ZhtaqsW7CVbWtrcHqMDJuYxJBJaVisB3uxIykqoFkk/AX5eN59g7o169ERwq2LJPLss+lx0wWYMrQRvpAS4sfCH/nP2i/YE1iHIVobAe4S0YXJmZOZkjWFTGtP8vOlEyos10CrCzalK5jcew9m4mnwhT+aP3wDZoemYNi7aGk9IxIhMlH7jEg8OO8Ixcc6mjWgU1hRgj7wVDWf3BVQV1qvPDT9LNWWtxZLDDhSwV4/RWc0VyJOUIn8NVPnr2NT+SY2lm1kY9lGNpVtOkyJsBlsDE0cyvDE4YxMHknPmJ7IUvjdBBSfD/eatbiWL6du+Y/U7SpAQUZGwSgHMPfpQ+SkiURMmICpe/fTWrA6Gq5qH1uWFbJ1+QE8Tk3JMln19B/fhQFnd8ESGf7EF6qqkrN2FT+9/w5lBXkAmCPtnHnZ1QyYOBWdvuN6ZIfTUkFIIVTtRQ1osTuyzYAcYURFwmgMb7xdMBiksrKSYFBL/xsVFYXVGv5Uqh2JUMiH252LqobQ6WxYrZlIJ6GvKfb5KfEFkSTItpqwdvKYK6FUnAAdQanI9/gY/sVuQnU63hsRi3PHNYRCLnr1fIb4+InNRug9HoXXXvsXubm12O3dGHXGFFw/FGAorcYep8N6UU9SuppaFAJVFVZ8+i27Fr2JXg7SbdgwLrrnHtxeC++9sp9tP5ehk1Sik6yMvTiDzF42JAn21Gdt7Nr1cCG4QUhPTgb/Lz9TNO819q0vwij7MUhBrCNHYj//AiLOHIVfNeLzwY6yHNYp/+Xb/Z83c3lIM/Wgv+5CxmYPol98Xwxy83iH1lT5bXOlYEWBmn0HlYzqAi2TT80+qN4Hnsqj/JMavqARRZWRTTZMkTYtFag1RqsGfuhkdmhB5cYIMNrqpwgwRWgWk1Mg4ITDOnREVBUCbvC7tPgEfx346uo/m/52aZYjr7OJ4lCtXW9PlbaP40XWa5YEWzxEJmkKgyNVUwbtKeCo/zxK5WnBsVFUhTxnHhtLNzYqEbnVuaiHxJvYDDaGJAxheNJwRiSNoGdMT/TyyXHr8Ofl4fpRUyLcP69B9TYZKJBlrMOGETlxIpETzsGQenpmbmoNqqpSnFvDpiX72fNLGYqi/WcR0SYGTUyn9+jkEw7APtZx9/zyMyvff5fSvFwAjBYLQ86bztDzp3WKuIlwVNT2+1UCtUFwNURrS1r8hFnfaDFuaXCsLW2uqqpCVVVkWSY6OhpTRxjZaoIkSSxYsIDp06eHZX+K4sfl3oOqBNDpzFitXU9KYHZ1IEh+ffrYNIuRGEPHVYhbi1AqToCOoFT4fHDDov18V1vDyFgrf4j8nn373sRojGPI4P+gqo7GEXqvFzZtquS///0Ig6GOfv0GMKTPGHb+MxdvVRA10kSXSzOJSzUSFdV8hLlBAXAXfM/Sf71MKBDAGtuF7pPvwy31xFtRwaZFeXg9CkFFR88RcZwxJZlqpybcp6cfLogfKqS73Srbv9xK6PN38axcrp2fYqTOlopu1ARMw0YSTO5On74yUfFufq5Yxjd7v+HHwh/xeBX85SnIej82i5GB0cMZkjCMgQn96RabRiAghc9ScZR9HP3PqqtXMArAeUAbGa8rgboSvFWVVJZ6qa3wEAqG0MkKkcZaYqzVWgzH8SLrDyoZRpsWA6I3Nvmsn/Smw+fJOpBkbUI6+F2SmsyT8AUM5BVFYNIHMOoCoIa0lKhqCFQFv1/F55fJjC/HpPdry0J+zZoT9B37M+BuOY3qiSDJWgxDU6UsIkFTGhqsQw3fbQna8tM44LA9CCkh8p35bKvcxo6KHWyv3M72iu3NsjM1kBqRysD4gdqUMJCe0SdHiQAIFBbiWrMG989rcK9eTaCwsNlyfWIitjFnEXHWWdhGjULncJyUdnQW/J4gu9eWsGVZIeX76hrnJ2c76D++C10Hx6M7CcGlSijE7p9XsuazjyjZkwOAwWxhyNSLGHrBdCwRkWE/5smirUqFGlQIVPnwuRW8Xs3dyRhjwmSRURStqw6XlUJVVerq6qit1Z7Tmpoa5s6dy1dffUVJSQnR0dEMHDiQxx9/nNGjR7f9gG0gnEqFogRwu/egKH5k2YTV2hX5JPRBnpBCjtuLomr1KFLNJy+d/alEKBUnQEdQKjweWL7dx417cvCrKk92TSDtwN14PPnExo6nV88/UVYmY7drbipVVVBdvYcVK77FYAjQrdtw+ncbSMUne/HXBjA4DMSdn4UtyUJS0kHFoumoc3Hubj56fjb7CxRcvkgyh45l6NTJ6HV6fvmmgP07qvD4dUTYIH1ICln948nI0mMwNHfbOVRIbyrUU7KPsk+/IffztXirXZhlL6oKQUcKSWP6kjRhJNmT+2KJ0OMKuFi6bykLN2xg5c5cavw1KD4rKDLICtGRBnrH9mZUj65M6N+b7tHdjyignNSR9yPQzIXIqmJQagk4K3BVujCrVaQ6SjArFYe78HiqNcHbV1s/Wu+CoCe8jTsKnoCZvVXpOMzOI1t2vHayoguwGI7hFnYsGiwypobPyEN+R4DJ3rJFxxKtLRNKwinDG/Syp2YPOyt3NioPO6t24mnh/jTrzPSJ7cPAhIGNikScJe6ktEtVVQKFhZoC8fPPuNesOUyJkAwGrMOHYRt9FrYxZ/2q3ZoaaLBKbFtZRM7aEoJ+TdnXGWR6jEik//guxKedHKE+4POydcli1n65gJoSrYKx3mRi8JQLGXbBxVjtnU/JO1GlQlVVFFeAUI0fr0elvFqmTjEQ1BvQ6SQiIyEuDiIiwtPdhUIhqqur8fm0gS2r1cpFF12E3+9n1qxZdO3alZKSEhYvXkzfvn256KKL2n7QNhAupUJRgng8ewmFvEiyAZu1K7IcfmE/oCjkuH34FZUIvUxXi+m06WuEUnECdASlokEQf7e8jFcPlGCWJV7PVnHtugNVDRATfTOqOgOHQ8sEZbNpoxjr1+9gyZJ16PUhBg9OY0SfkRR9nI9U50c1yljO6ELKiGhiY5v7x4MWsHhgv4ev53/L/s0/EVL0GMxmzjz/THqeOYbSvDrWLSqkssSLx6cDnZ7BZ8WQNTAeS6SRiAiIitIUokOF9KZCfXExVFcGMeSux7V8OSU/bcMWKCfeUIEzFInDrtJ1bDa2s87CNno07ohU1q5T2FaUT17gF3bVbmJnaT4+ZwSy2YUlcwd6Wx1mnZmeMT3pG9uXvnF96RPThyxHFjpZ1y4xAmFVZJSQ5hbUoGQ0fA96tQDkoK/eWlD/2fR70Achn6YNqEqTTwVo8r1+mc8vk1cWi8mgaJYdWa9ZBOotHf6QAV/QRGZyHSYz2jK9WbOO6M2HfG/h02DRFAaDVSgEHZRAKECeM4/c6lx2V+8mpyqH3Jpc9tXuQ2nBymTRW+gZ3ZPesb3pHdObPrF96BrV9TB3xXCh+v14t2/Hs3Ejng0bcK/fQLCoqPlKOh2Wfv2wjhiBdcRwrEOHIp/mfuKtpa7Kx641xexYWURV8UE3wugkK73PTKH3mcmYI07Of+d21rDhmy/Z8M0XeGq1yvHmSDuDJ1/AoMnnd0plooETUSqUQIhQlQ/VH8LrhQMVegJmI5EOXWMtlYZU8uF4T/l8PqqqqlDq66w4HA4CgQDR0dEsWbKEcePGtbjdiy++yFtvvcWePXuIiYnhwgsvZPbs2UREaG5pb7/9Nvfeey//+c9/eOCBB9i3bx/nnXce8+fP54MPPuCJJ56gpqaG6667jpdeeqmxiF5mZiYzZsxg27ZtfPbZZ0RFRfHoo49y5513Nh77UKVi3759PPDAA3z77bfIssyYMWP461//SmZmJqBV3H744YfZunUrBoOBvn378p//zCc+QUEJeZEkHVZrN3THkYa6tYRUlVy3D09IwShLdO/kgdmHEg6lovM7gXVCGvKoXxaIY4PLxcqaOn6XZ+CFzD9QvfdJNm5aREpyDN26XYzHownJkgSDBvWitNTI9u0r2bVrJ1VV1QyfcjYxm4qoy3dTs6SA3QV16C9JJj5VT0yMpsDs369ZGGyRFkZfOo2aUb358eNvKCl0svTj79m8dBn9x41j3LVnsGG5i70bS/A4A2xeUULuuiLSekUTnx2PIzGSzEypMeVsAw01OEpK6gsaReiRBg0n2GM43Wb4cBz4hcDKJYR+XE2d00vFN0uoXbQIgKrEwYSyRzOwVy/6pY9CyrwEVQpQFMhhR9UO8pQEcpRl1AXqGv23G7DoLWRHZdMtqhvplh7EqT2I93cl2hiHokhYrdoIULgVCp9Py5pkO0IJjoaChEeqWH4Ysk6LtTCf/BeuCYisV4iMLShErnqFyHQMhaijBZ8LmqOqKpXeSgpqC8iryaOgtoB8Zz57a/aSV5NHUA22uF2UKYru0d3pHdOb3rG96RPThwx7RpvSux6rncHiYk2BWL8Bz8aNeLdta5bqFQC9/qASMXw41iGDkY/0AP4K8boC7Flfxq41xRTuqm4sp6I3ymQPS6TPmckkdTs56UNVVaU4ZxcbvvmCnT/9SKg+INiRkMjQCy6m3/iJGEztnfnh1KIqKkqdn1CtX/svJIka1UjQZiA25uB/oNNp76eqKm3g70Qt6qqqUltbS12d5tqm1+uJjo7GYDAQDAaJiIjgk08+4YwzzmgxpkKWZebNm0dWVhZ79uzhjjvu4OGHH+bVV19tXMftdjNv3jz++9//UltbyyWXXMLFF19MVFQUCxcuZM+ePVx66aWMHj2aK6+8snG7559/nkcffZSnnnqKb775hnvuuYcePXowadKkw9oRCASYPHkyo0aN4scff0Sv1/Pss88yZcoUNm3ahCzLTJ8+nVtuuYX33nsPv9/PqlUr8Xr3o4RikCQ9VmvWSVEoFFUlz6MpFDpJoqvFdFopFOFCWCraiYbR9ZK6IHfl7iU/6CNdb+Je3SYO7PiExMQDZGZchk53KyaTDoNB2yY/H8rL97Nt23cEAn50OgsXTxtBRrWFymXFOL06MlNDJF6UiadLPLm5UuPIudGoCbt2O+h0IdZ+/wvbfviOoLcSVZXRmyNI6nMWIycNQOdX+XlREUX7fKiqhCSp2BwWRk6wc/aF8UTGmFs8nx07tFEXnY5G60aDUK8EQ5T+kkNc3hKUn5dRs34bhd7ExiBvv2JAiorB2r8v9gG9kLv2gvRssvpaKfbls61iG1srtrKtYhvbK7Y3C/puIOi2YfamkmLKJs2eQmpkEllJ8fTtkkx2fBcijW0397c5OLydaYtl57RLRduJaVAcDtQdoKC2gAJnAXnOPPKd+RQ4C1qMe2ggwhBBt6huZEdla1O09hlrjj1ppvwGNybv1m14tx2cQhUVh62ri4rCMnAglkEDtc+BA4UScQgBf4i8TeXs+rmEgq0VKKGDr/Kkrg56jUqi+7BEjJaTFNfi97Fz5Y9s+OaLxngJgMSu3Rl24cX0GDkauZNnw2lKaywVqqqiekMEa3wQ1KwFkllPyGIif798UmL/AoEA1dXVBAJaalqr1Yrdbm9W0O6jjz7illtuwePxMGTIEMaNG8dVV13FgAEDWtznhx9+yG233UZ5uZa18e233+Y3v/kNOTk5dOvWDYDbbruNf//735SUlDRaNKZMmUJmZiavv/46oFkqevfuzVdffdW476uuugqn08nChQu169PEUvGf//yHZ599lu3btzf2Q36/n6ioKD755BOGDRtGbGxso9VFi6HYi6L4migUJyEFsqpS4PVTHQghS9DtNMj01BLCUtGJaRDeLJV6XpIyuH1LPvmeALOs/binlwGLdxalZfNRlBLi4x4iJsaGLGsdUnx8F6ZNm86iRcuorT3AosVfkJWVxRnTRhC5pArV5WTbP/PxxlQS7JtKYnYkkqRVLnW7tRHm+Hgdg8cNp+ewQdTmr2Trkq8p2l9B4S8LWbL7P2QN6MOY889GNmeTs66c/C1lBP0+1nzlZM/yHNK6R5I9NJFuQ+KJiDZjNkOXLtr+9Xrt/A7tHIOKDlvvniRO7Ynp3t9SV1qL/8ttGPesx7t5M9KOHajOEgIrSqhY8T2qCrVKJEo3megB3TmjTx/G9x2DafgMpOgo8mvzNdeN6lxyqnPYWZrPnlIfdf4gOaH15PjWQLEeZYsFyeDHEF1KbKSNNHsa6ZHpdInsQpI1iWRbMkm2JJJsSVgNx3ahkGUaTdctvSACAW15R/X+aamirU6nKZ5HUw6OpIxUVWmKVodIRXsaoaoqFd4KCusKKaororCukAN1Byh0ab8P1B3AG2o57kUJGJBUM8kRiWTFppBuTyfTnkmGPYPu0d1JtCaeVD9gxevFv2cPvpwcvDt2NioQitN5+Mo6HaaePbAMHIh10CAsAwdiyMg4bfyUw4nfEyR/awV7N5Sxd3MFQV+ocVlsqo3uwxPpPiwRe9zJG80oK8hj65JFbF36Pd46TXHV6fX0PHMsgyafT3J2C7nIfwUoAYVQjQ/VW28F1NVndrLoCXolQiGtz2wJg+Hgu7m1qKqKy+XCWf9MSZJEVFQUlhZGsi699FLOP/98fvzxR1atWsVXX33F7NmzefPNN7nxxhv57rvvmDVrFjt27MDpdBIMBvF6vbjd7sb0s1artVGhAEhMTCQzM7NRoWiYV1pa2uzYo0aNOuz33LlzWzynjRs3kpOTQ2Rk88E/r9dLbm4u5557LjfeeCOTJ09m4sQJjB07iOnTJ5CckoLVcnIsFKqqUuQLUB0IgQQZltNToQgXQqloR8xmzdwZG2vkk7QMbtyyhxy3lz+V9eCu5NlkVf2RQOB7dueUEh93F/HxvZEkbUQ5OjqKadPOY9++n9mwYTV79+5l584SzhzVBztp+JZWY66s5cCXezB0t2EbkYg9OQK/X8Lr1UbSLRZAMtBj1Diyhp1F3qb1bF22HNeBEvI3byR/80asdgddh4xg0nXDcVbZ2ba6ilC1j+I9Tor3OFn+wW7i0iLI6BdLRr84oqPt1NRILY62aO0+qGwYHJHYzxyJ6eyRxBu1/PK+XbvwbNqEd9t26nbkoiuuIlSwD+f+HJwLD4526KKjMWVn0z+7G8OyszFlX0lFn2yqekdSq9tHvjOffbX7OOA6QGFtIQUlTmpdXqqM5VSVVbGpbFOL/4ndaG+mZCTZkkiwJhBnjiPWEkucJY4oUxSRkTrNhagFpeLQ8+yINNx7x+PGVFmpKRRN40iMRm1qq/m+rXQ2dyx3wE2Zp4xSdyml7lLK3GWUeuo/6+eVukvxK/6j7kdCIt4aT1pkGpn2TJJNWUSFuhJNGgnWZCwG00m1JKl+P768PPw5OXh378afk4Nv1278+/a1KCFJBgOm7t0x9+2DuY82mXr0QO6IJr0OgqvGR96mcvZsKGf/zkqU4EGLRGSsmR7DE+k+PJHY1JOXltVbV8eOFUvZsuQ7Svbsbpxvj09gwMSp9D/n3E4dL9EW1JCiFbFzBepdnUCOMKKLNCLVu8eEeyDqUOuEyWTC4XCgP0qdD7PZzKRJk5g0aRKPPfYYN998M0888QTjx4/nggsu4Pbbb+dPf/oTMTExLF++nBkzZuD3+xuVCsMhGpEkSS3OU45HMzqEuro6hg4dyjvvvHPYsvh4rRr2W2+9xZ133soXX7zPRx99yTPPzOWbb77mzDN7nfBxj4SqqhT7A5T5NUUxzWzErhcKxdHolErF3/72N55//nmKi4sZOHAgL7/8MiNGjGjvZp0wJhN0Nxn58oxsZmzJY5nTy3MFcVyU/ipnV84iGCxi85a5RNimoNNNwWTSXsCJiXq6dTuT3r17snDhMkpLC9i4aSVrAzGMGDOALGcsupUeXHtr8Rc4MSRaMQ9IQIqPxmKRcLk0ITEQgNhYHekXDKPHsGG4qwrJXb2UnauW43bWsGXJIrYsWYQlKpHUvsMZclE2AW8Me9ZXULy3hvJ9dZTvq2PdV/nIJgPmxERiutjJ7OMgNslMMCg1utY0jcdoiC1pEM5lkwlL//5Y+vcHtPmRUjUxVVs1l4mtW/Fu20Zg/35CVVW416zBvWYNAH7FQGEgBXOUFVt6Er1TUxiQmoohdSiGLhfBgFScOgO62H0U+/IpqC3gQN0Bil3FFLmKKHGVUBuoxel34vQ72Vm184j/lyzJOORErO7u2OV4Ehw24iKiiNRFY1RiiIuIoJvdTMDp0BQQY+RJKfIVDlorgIc9jiRMdBR3rJASotpXTZW3iipfFZXeSu27t/67T/te5imjzF1GXaDu2DtFu9cSrAmk2FJIjUglOSKZ1IhUUiJSSLWlkmRLwqDTXuwny5Kkqiqh8nL8eXn48/O1KS8f3949+PPyIdhyfIYuKgpTdjamHj0alQhTt25I4UzEfxqiqiqVB1zkb6lg78Yyivc6aVoCxJFgoeugeLoOiicxy37SLDqhYJCCLRvZunQxOWt+IlQvwMo6Hd2GjqTv+IlkDR6KfJLibTo6qlKf1anWD/X1PiSzHp3DiGxofk0OfdcdSmsHog5NFStJEna7HavVetz3QZ8+ffjkk09Yt24diqIwZ86cRpep999//7j2dTRWrVp12O/evXu3uO6QIUP43//+R0JCwhFdbILBOnr2tNOjx008+ODtTJp0Pf/97weceeaYsLUZDioUpT6tf0sxG06LWhQnm053hf73v/9x//338/rrrzNy5Ejmzp3L5MmT2blzJwkJCe3dvDYRZdDzv4Hd+Iu5mL+uq+TTXB0/+p9kunEjXaLfw+P5GEn+nqSkS4mIGIvPJxMKgc0Wy29+M52Kit0sXvw9u3cHWP3LStYbDaQOHkR8VQqOoloCJW783+bhMRaTOMaOPjOOrCwzqakHOzOXC4LBVM68/BpGXnw5+7dvJWftKvI2/EJlaR2eqi8o+6USk81G5sChjL54MDpDJgdyfezbVonPHaBmzwEObCth7UI9ZpuBpK4OuvaOoNcQOyajFTjY+TUEeVdVtezfn5Aahdk8mogmubQVtxvfnr34c3Pw5eTgy8mlZmcBoTyQneV4t5bj3bql2bVVVXBZk+maradvViIDk5MxJHfDkHIWhh7JGJKTcVt0lLhLKHIVUewupqiuiBJ3CeWe8sapyluFoipUhYqokCoI1dkJldtA0YEcQmd2obM5kXMPjjDLkozdaCfKFIXD5Gj8tBvtRBgjiDBok81oI9IQ2WxehDECq/74XxjhRlEIu/m+rYRbiA4pIeoCdTj9Tmr9tdT6aw/77vQ5qQ3UNs5rUCRqfDWHFX87Fha9hURrIgnWBOKt8SRYtM94azyJ1kTiLdpng9JwLNpiSVJDIYKlpQQKC/Hv31+vOGhKRCAvH8V95GKEckQEpu7dNQWie3dM3bMxZWeji4tr9/u2s+B1Bdi3vZKCbZXs21qBq6a5hSoh007XQXFkDYwnOunk9QeqolC4Yxs7Vi5l16oVjRmcAOLTM+k7fhK9x4z/1VoloF7JdgUIOf0Qqo+bMMiNReyOxLHedYcmQDkUn89HTU1NY2Vso9FIVFTUUa0TABUVFVx++eXcdNNNDBgwgMjISNauXcvs2bOZNm0a2dnZBAIBXn75ZS688EJWrFjRGBMRDlasWMHs2bOZPn06ixYt4oMPPuDLL79scd1rr72W559/nmnTpvH000/TpUsX8vPz+fjjj3n44Ydxucr5v/97hfPOG09qagb5+XXs3p3D9dffELb2NlByiEIRbzw5GdNONzqdUvHiiy9yyy238Jvf/AaA119/nS+//JJ//vOf/O53v2vn1rUdvSzxx97JjIqKYObXJRwog39YBjA0shcTI+eTZPqJYGgt+/cPo3v3a8nOHoFOJ2MySaSm9qB792y+/XYnGzb8jNNZTk7BL2yo201qciY9LHHY90CgNsCB70uINBdhGGQhNCoBpXcsslF3SMdnIL3fIJJ7DmLA+T5Kczfj3reCwi2r8dQ62blyGTtXLgNJIiGjK9mDBhARm43PG0fJXi/7c2sJBXzU5tWybZ/Ktm/BZNWTmGknMctOYlcHiRl2kpP1VFdLrfbvl61WLP36YunXt3Fegg90OzxIpfuQSgsJ7C/EX7ifYOEB/IWFeMuqkOpq8G89gHP7Ly1ee8lqxZCcTEZyMtnJyRhSktEnDEGfkIA+LR59QgKqPYJqf00zRaPYWUW5q5JKXzkutZJqXzU1vhqqfdW4g24UVaHaV021r7r5AY+SI6GpyCBLMja9DZvBhkVvwaK3YNaZD37XmzHrzVh0Zm2+wVq/XJtvkk0YdUb0sg6jbMSgM2CUjehlA0bZgEE2YNBpn0adEYNkODzbTxAkBXwuMBpUmuZ3UFHx+0Hxq4S8KgGVZgK2inrwXNUm8+qvQdOr0LBfba7aOC+gBAiE/PiVAL6gl0AoyP6iEJVVKiabh2BFEL/ixx/yEwwFqHJKGHbUYo6uxBN04w648QQ9eIMe3EEPniaTN1D/eUh8gnQcOkJDJI7DaCfKGEWUOYooU/2nsf67KYpYSwxxljjiLPEH43eOdB/4VfA7adEOcMg2Ph9U7ZMxGVWCh8c9YwpA5W4/5j37kcsKCRwoJFB4gEBhIYEDBwgUFR3R4gCALGNITcWYkXFwysrE1L07+sSTG59xOuLzBKnYX8f+HZoiUZrnbPaX6g0yKT2iyOyvKRIR0SfP/OdzuygryCPn55/Y+dOP1FUevIGsjih6nHEW/cZPJCGr26/6f1aDCoovRKDcg06qFzB1Ejq7CdmqP+a1OZFYNlVVCYVC1NbW4vFo9WJkWcZut2OxWFr1f0RERDBy5EheeuklcnNzCQQCpKWlccstt/Doo49isVh48cUXee655/j973/P2LFjmTVrFtdff/1xX6OWeOCBB1i7di1PPfUUdrudF198kcmTJ7e4rtVqZdmyZTzyyCNccskl1NbWkpqayjnnnI3R6MbrrWb37r1cd93nVFZWk5yczJ133slvf/vbsLQVtLSxpU0UimSTUCiOh06V/anBv+/DDz9sVijlhhtuoLq6mk8//fSwbXw+X2MRGNAi2NPS0to9+9Ox8PlgW26It/aX8b/yCkKAZFCRG8StAKh+0CcFkA4xpwbL9ah1euSIEKCiBiRCtTJ4ZBSXDskWQp/qR2cPIRkP//tVv0TIqUN1y6BKIKlIVuWI64cL1S81+qSeyHGan3dzlDodUkQQfdxRBCfBUelI11f1SwSLDUhGkPQt3MNBqcnz0Wm6uBNG9UkEi41IVuWIGclUt4w+yY9kOv2vh0AQbrrI8GeHnvi0NCRj25Q8f5MYsDbuqkMztX8frr39Tv7fHXcee+VWc+oU22STgQTTr0eh+NVlfyovLycUCpGYmNhsfmJiIjt27Ghxm1mzZvHUU0+diuaFFUUBEzoe6ZvEZR4HrxWU8V2FE6X+gVL1oPp0qCiHDanKDpWQXyXk0iOZFTCoyA5QZAmdI4guPogcoQJyyw4bJtDFq6h+5RAh/wjrh4smneuJHEd21NeGcxm089apEJJQvTKSUUF2gCr9Ov1/w0FHur4qEqqqB32oxby+R3s+TkdUWUKVZVAkaEnJCkn16+h+FddDIAg3qtRgVZVoq2B7OisSLdO5LFx6SSLBpBcWihOgUykVJ8Lvf/977r///sbfDZaKjk7TbBHZVgtzeqXjDATx1weEBfzg8QVJSnViamEk1uuF6ioZV61ESAGdDFZrAJPVi8ncglDhCd8Ic8AXIBg4etaaBkIhBSWooIbJGd9nk3A69bhdOm0kSA/WxBB2exBTW0doQwohb8spPIET7DePf6OjmryPtOioZnIJFRVVDaEoCkFVQVGDh+xMAiP442WctQbcHh2qX0KWwRqpXV+jSWncRmqhIU2b0Gx5kwXN1zmILOuR0R3MXa6TKLKGMOgVDIbD/9dAQCJglUm2+jAa1cP212rC+S486v/W9gOVhYLU1uqItB1uSaqt1REZHyI+JtDm4wjajqzXoTd0jAEOnUGPsTOkTGtnlJBC0BMg3SRjMp+axBsSEpIkdVq3M6MkkWjU0dvWduFcOkUDVrIkoeuk17sj0KmUiri4OHQ6HSUlJc3ml5SUkJSU1OI2JpOpxQqSHZ2WskXYm2QeqHJDcpyBlNgjpGKMBOI7X6rNcPFrPe9TRUe4vgfqK4M3DUxuoGF+e6W4bQ/aUtRQIBAcnQbXELPBhNkgHqTWkJeX195NEJxiOmaeyyNgNBoZOnQoixcvbpynKAqLFy8+rMDK6UBD8FZVlVZxU1W1z6qq1mWLAE3gs1h+fYL1r/W8TxUd4fqG4/k4nWhQHKKjNaWvpkb7jI4WCoVAIBAITj6dylIBcP/993PDDTcwbNgwRowYwdy5c3G5XI3ZoE4nTrTysUDwa0A8H4dzIkUNBQKBQCAIB51OqbjyyispKyvj8ccfp7i4mEGDBvH1118fFrx9uiCEBIHgyIjno2XENRAITg6dKGGmQHBchOPe7nRKBcDMmTOZOXNmezfjlCKEBIHgyIjnQyAQnEwM9ZU/3W43FssRYhkFgk6Mu77IqeFIVW5bQadUKgQCgUAgEAhOFTqdjqioKEpLSwGtUFtnzcokEDRFVVXcbjelpaVERUWh0514pi2hVAgEAoFAIBAcg4Yskw2KhUBwOhEVFXXETKqtRSgVAoFAIBAIBMdAkiSSk5NJSEggEBA1XwSnDwaDoU0WigaEUiEQCAQCgUDQSnQ6XVgEMIHgdKNT1akQCAQCgUAgEAgEHQ+hVAgEAoFAIBAIBII2IZQKgUAgEAgEAoFA0CZ+dTEVDcU9nE5nO7dEIBAIBAKBQCDo2DTIzMcqkPerUypqa2sBSEtLa+eWCAQCgUAgEAgEnYPa2locDscRl0vqr6zmvKIoHDhwgMjISFG45gRwOp2kpaWxb98+7HZ7ezdHcBog7ilBuBH3lOBkIO4rQbjpLPeUqqrU1taSkpKCLB85cuJXZ6mQZZkuXbq0dzM6PXa7vUM/AILOh7inBOFG3FOCk4G4rwThpjPcU0ezUDQgArUFAoFAIBAIBAJBmxBKhUAgEAgEAoFAIGgTQqkQHBcmk4knnngCk8nU3k0RnCaIe0oQbsQ9JTgZiPtKEG5Ot3vqVxeoLRAIBAKBQCAQCMKLsFQIBAKBQCAQCASCNiGUCoFAIBAIBAKBQNAmhFIhEAgEAoFAIBAI2oRQKgTH5Mknn0SSpGZTr1692rtZgk7GsmXLuPDCC0lJSUGSJD755JNmy1VV5fHHHyc5ORmLxcLEiRPZvXt3+zRW0Ck41j114403HtZ3TZkypX0aK+gUzJo1i+HDhxMZGUlCQgLTp09n586dzdbxer3ceeedxMbGEhERwaWXXkpJSUk7tVjQ0WnNPTV+/PjD+qrbbrutnVp84gilQtAq+vbtS1FRUeO0fPny9m6SoJPhcrkYOHAgf/vb31pcPnv2bObNm8frr7/O6tWrsdlsTJ48Ga/Xe4pbKugsHOueApgyZUqzvuu99947hS0UdDaWLl3KnXfeyapVq1i0aBGBQIBzzz0Xl8vVuM59993H559/zgcffMDSpUs5cOAAl1xySTu2WtCRac09BXDLLbc066tmz57dTi0+cX51FbUFJ4ZerycpKam9myHoxEydOpWpU6e2uExVVebOncsf//hHpk2bBsD8+fNJTEzkk08+4aqrrjqVTRV0Eo52TzVgMplE3yVoNV9//XWz32+//TYJCQmsW7eOsWPHUlNTwz/+8Q/effddzjnnHADeeustevfuzapVqzjjjDPao9mCDsyx7qkGrFZrp++rhKVC0Cp2795NSkoKXbt25dprr6WgoKC9myQ4jdi7dy/FxcVMnDixcZ7D4WDkyJH89NNP7dgyQWdnyZIlJCQk0LNnT26//XYqKirau0mCTkRNTQ0AMTExAKxbt45AINCsr+rVqxfp6emirxK0ikPvqQbeeecd4uLi6NevH7///e9xu93t0bw2ISwVgmMycuRI3n77bXr27ElRURFPPfUUY8aMYcuWLURGRrZ38wSnAcXFxQAkJiY2m5+YmNi4TCA4XqZMmcIll1xCVlYWubm5PProo0ydOpWffvoJnU7X3s0TdHAUReHee+9l9OjR9OvXD9D6KqPRSFRUVLN1RV8laA0t3VMA11xzDRkZGaSkpLBp0yYeeeQRdu7cyccff9yOrT1+hFIhOCZN3QsGDBjAyJEjycjI4P3332fGjBnt2DKBQCA4Mk3d5vr378+AAQPo1q0bS5YsYcKECe3YMkFn4M4772TLli0ihlAQNo50T916662N3/v3709ycjITJkwgNzeXbt26nepmnjDC/Ulw3ERFRdGjRw9ycnLauymC04QGP9JDM6iUlJR0eh9TQceha9euxMXFib5LcExmzpzJF198wQ8//ECXLl0a5yclJeH3+6murm62vuirBMfiSPdUS4wcORKg0/VVQqkQHDd1dXXk5uaSnJzc3k0RnCZkZWWRlJTE4sWLG+c5nU5Wr17NqFGj2rFlgtOJ/fv3U1FRIfouwRFRVZWZM2eyYMECvv/+e7KyspotHzp0KAaDoVlftXPnTgoKCkRfJWiRY91TLbFhwwaATtdXCfcnwTF58MEHufDCC8nIyODAgQM88cQT6HQ6rr766vZumqATUVdX12zUZe/evWzYsIGYmBjS09O59957efbZZ+nevTtZWVk89thjpKSkMH369PZrtKBDc7R7KiYmhqeeeopLL72UpKQkcnNzefjhh8nOzmby5Mnt2GpBR+bOO+/k3Xff5dNPPyUyMrIxTsLhcGCxWHA4HMyYMYP777+fmJgY7HY7d911F6NGjRKZnwQtcqx7Kjc3l3fffZfzzjuP2NhYNm3axH333cfYsWMZMGBAO7f+OFEFgmNw5ZVXqsnJyarRaFRTU1PVK6+8Us3JyWnvZgk6GT/88IMKHDbdcMMNqqqqqqIo6mOPPaYmJiaqJpNJnTBhgrpz5872bbSgQ3O0e8rtdqvnnnuuGh8frxoMBjUjI0O95ZZb1OLi4vZutqAD09L9BKhvvfVW4zoej0e944471OjoaNVqtaoXX3yxWlRU1H6NFnRojnVPFRQUqGPHjlVjYmJUk8mkZmdnqw899JBaU1PTvg0/ASRVVdVTqcQIBAKBQCAQCASC0wsRUyEQCAQCgUAgEAjahFAqBAKBQCAQCAQCQZsQSoVAIBAIBAKBQCBoE0KpEAgEAoFAIBAIBG1CKBUCgUAgEAgEAoGgTQilQiAQCAQCgUAgELQJoVQIBAKBQCAQCASCNiGUCoFAIBAIBAKBQNAmhFIhEAgEAoFAIBAI2oRQKgQCgUAgEAgEAkGbEEqFQCAQCDok48eP59577+0w+wlHOyRJQpIkNmzYcMz1b7zxxsb1P/nkk5PePoFAIGgLQqkQCASCU0hTQbHpNGXKlPZu2gnT9JyMRiPZ2dk8/fTTBIPBNu33448/5plnnglTK1vHN9980+L/03T69ttvT3j/t9xyC0VFRfTr1++Y6/71r3+lqKjohI8lEAgEpxJ9ezdAIBAIfm1MmTKFt956q9k8k8l0Uo/p9/sxGo0nbf8N5+Tz+Vi4cCF33nknBoOB3//+9ye0P7/fT0xMTJhbeWzGjh3bTJDv168fd9xxB3fccUfjvPj4+BPev9VqJSkpqVXrOhwOHA7HCR9LIBAITiXCUiEQCASnGJPJRFJSUrMpOjoa0Fxk7r77bh5++GFiYmJISkriySefbLa9oijMmjWLrKwsLBYLAwcO5MMPP2y2zvjx45k5cyb33nsvcXFxTJ48mdraWq699lpsNhvJycm89NJLzVyD5s+fT2xsLD6fr9m+pk+fznXXXdeqc8rIyOD2229n4sSJfPbZZ21q76FuSz6fj7vvvpuEhATMZjNnnXUWa9asabYfl8vF9ddfT0REBMnJycyZM+eo7T4Ui8XS+J+EQiEqKioYM2ZMs/9Kp9MBUFBQwDXXXEN0dDQxMTFce+21VFVVHdfxPvzwQ/r374/FYiE2NpaJEyficrmOax8CgUDQERBKhUAgEHQw/vWvf2Gz2Vi9ejWzZ8/m6aefZtGiRY3LZ82axfz583n99dfZunUr9913H//v//0/li5deth+jEYjK1as4PXXX+f+++9nxYoVfPbZZyxatIgff/yRX375pXH9yy+/nFAo1KgMAJSWlvLll19y0003Hdc5WCwW/H5/m9p7KA8//DAfffQR//rXv/jll1/Izs5m8uTJVFZWNq7z0EMPsXTpUj799FO+/fZblixZ0uwcj4f169cDMGTIkMOW5eTkMHToULKzs1m1ahWLFi0iJyeHhx56qNX7Lyoq4uqrr+amm25i+/btLFmyhEsuuQRVVU+ovQKBQNCuqAKBQCA4Zdxwww2qTqdTbTZbs+lPf/qTqqqqOm7cOPWss85qts3w4cPVRx55RFVVVfV6varValVXrlzZbJ0ZM2aoV199dePvcePGqYMHD2787XQ6VYPBoH7wwQeN86qrq1Wr1arec889jfNuv/12derUqY2/58yZo3bt2lVVFOWo5zRt2jRVVVVVURR10aJFqslkUh988METbm/DvIa21dXVqQaDQX3nnXcal/v9fjUlJUWdPXu2qqqqWltbqxqNRvX9999vXKeiokK1WCzNzrG1PPXUU2paWlqLyyZNmqQ+/vjjzeZ9+OGHalZW1hH31/R8VFVV161bpwJqXl7eUdsBqAsWLGh1uwUCgaA9EDEVAoFAcIo5++yzee2115rNaxo/MGDAgGbLkpOTKS0tBbQRcrfbzaRJk5qt4/f7GTx4cLN5Q4cObfy+Z88eAoEAI0aMaJzncDjo2bNns21uueUWhg8fTmFhIampqbz99tuNgdhH44svviAiIoJAIICiKFxzzTU8+eSTJ9zeQ8nNzSUQCDB69OjGeQaDgREjRrB9+/bGdfx+PyNHjmxcJyYm5rBzbC2//PJLi1aK/Px8Fi1axPLly5u5V4VCIdLS0lq9/4EDBzJhwgT69+/P5MmTOffcc7nssssaXeEEAoGgMyGUCoFAIDjF2Gw2srOzj7jcYDA0+y1JEoqiAFBXVwfAl19+SWpqarP1Dg32ttlsx922wYMHM3DgQObPn8+5557L1q1b+fLLL4+5XYOiZDQaSUlJQa/Xn5L2nkx++eUXbr755sPmb9y4kZiYGFavXn3YMovF0ur963Q6Fi1axMqVK/n22295+eWX+cMf/sDq1avJyspqU9sFAoHgVCOUCoFAIOhE9OnTB5PJREFBAePGjWv1dl27dsVgMLBmzRrS09MBqKmpYdeuXYwdO7bZujfffDNz586lsLCQiRMntmr0/UiK0om291C6devWGG+RkZEBQCAQYM2aNY3B3N26dcNgMLB69erGc6yqqmLXrl3Hfezy8nL27dvXoqXCYDBQW1tLSkoKVqv1hM8JNIVx9OjRjB49mscff5yMjAwWLFjA/fff36b9CgQCwalGKBUCgUBwivH5fBQXFzebp9friYuLO+a2kZGRPPjgg9x3330oisJZZ51FTU0NK1aswG63c8MNNxxxuxtuuIGHHnqImJgYEhISeOKJJ5Bl+TDXpmuuuYYHH3yQN954g/nz55/4ibahvYdis9m4/fbbG9ufnp7O7NmzcbvdzJgxA4CIiAhmzJjBQw89RGxsLAkJCfzhD39Alo8/J0lDcHdLSsXIkSOx2+1cf/31PPbYY9hsNnJycvj666+ZO3duq4+xevVqFi9ezLnnnktCQgKrV6+mrKyM3r17H3d7BQKBoL0RSoVAIBCcYr7++muSk5ObzevZsyc7duxo1fbPPPMM8fHxzJo1iz179hAVFcWQIUN49NFHj7rdiy++yG233cYFF1yA3W7n4YcfZt++fZjN5mbrORwOLr30Ur788kumT59+XOcWzvYeyl/+8hcUReG6666jtraWYcOG8c033zSLQXj++eepq6vjwgsvJDIykgceeICamprG5W+//Ta/+c1vjplhaf369SQmJpKSknLYspiYGBYuXMgjjzzC2LFjUVWV7t27t1pBasBut7Ns2TLmzp2L0+kkIyODOXPmMHXq1OPaj0AgEHQEJPVYPatAIBAITktcLhepqanMmTOncbS/gQkTJtC3b1/mzZvXTq07OTzxxBMsXbqUJUuWnPJjjx8/nkGDBh2XNQM0F6kFCxaERcETCASCk4WoUyEQCAS/EtavX897771Hbm4uv/zyC9deey0A06ZNa1ynqqqKBQsWsGTJEu688872aupJ46uvvmL27NntdvxXX32ViIgINm/efMx1b7vtNiIiIk5BqwQCgaDtCEuFQCAQ/EpYv349N998Mzt37sRoNDJ06FBefPFF+vfv37hOZmYmVVVVPPbYYzz44IPt2NrTj8LCQjweDwDp6ekYjcajrl9aWorT6QS0tMIdLTuWQCAQNEUoFQKBQCAQCAQCgaBNCPcngUAgEAgEAoFA0CaEUiEQCAQCgUAgEAjahFAqBAKBQCAQCAQCQZsQSoVAIBAIBAKBQCBoE0KpEAgEAoFAIBAIBG1CKBUCgUAgEAgEAoGgTQilQiAQCAQCgUAgELQJoVQIBAKBQCAQCASCNiGUCoFAIBAIBAKBQNAmhFIhEAgEAoFAIBAI2oRQKgQCgUAgEAgEAkGb+P/csPiP1PbQVQAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -215,206 +215,206 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sea state 1/200. (Hs, Te) = (2.840183371772305 m, 10.181962895642807 s). Tp = 11.267563328978767 s\n",
-      "Sea state 2/200. (Hs, Te) = (2.435150836386068 m, 9.253557835748264 s). Tp = 10.240171762684351 s\n",
-      "Sea state 3/200. (Hs, Te) = (2.380182396284662 m, 9.145665731349082 s). Tp = 10.120776206888838 s\n",
-      "Sea state 4/200. (Hs, Te) = (2.6586225636340433 m, 9.245181682418751 s). Tp = 10.230902544257528 s\n",
-      "Sea state 5/200. (Hs, Te) = (2.489418873168824 m, 9.168527592693843 s). Tp = 10.146075598878438 s\n",
-      "Sea state 6/200. (Hs, Te) = (2.4554983906019254 m, 9.076055379984771 s). Tp = 10.043744002942633 s\n",
-      "Sea state 7/200. (Hs, Te) = (2.8264441787710775 m, 8.352759030940048 s). Tp = 9.243329829171866 s\n",
-      "Sea state 8/200. (Hs, Te) = (2.440636821165454 m, 8.454371440140704 s). Tp = 9.355776148944692 s\n",
-      "Sea state 9/200. (Hs, Te) = (2.2107044601389494 m, 8.139285537198479 s). Tp = 9.00709580097473 s\n",
-      "Sea state 10/200. (Hs, Te) = (1.773654332308055 m, 7.14357692017975 s). Tp = 7.905224775274031 s\n",
-      "Sea state 11/200. (Hs, Te) = (2.33221680310332 m, 9.019225599053808 s). Tp = 9.980855033283783 s\n",
-      "Sea state 12/200. (Hs, Te) = (1.4652901970781362 m, 7.467449653557229 s). Tp = 8.263628805151397 s\n",
-      "Sea state 13/200. (Hs, Te) = (2.37380465141513 m, 9.137972634616318 s). Tp = 10.11226287252288 s\n",
-      "Sea state 14/200. (Hs, Te) = (1.9418617270615008 m, 8.786718919588829 s). Tp = 9.72355850194371 s\n",
-      "Sea state 15/200. (Hs, Te) = (1.682708754224695 m, 9.005540858375955 s). Tp = 9.965711226160469 s\n",
-      "Sea state 16/200. (Hs, Te) = (1.461238938616968 m, 9.679214804474308 s). Tp = 10.711212258578739 s\n",
-      "Sea state 17/200. (Hs, Te) = (1.9389947758035828 m, 10.03218336557303 s). Tp = 11.101814312041364 s\n",
-      "Sea state 18/200. (Hs, Te) = (2.2114494380999004 m, 10.769142843100967 s). Tp = 11.917348376449572 s\n",
-      "Sea state 19/200. (Hs, Te) = (2.3798499882325825 m, 9.899703813443036 s). Tp = 10.955209795926086 s\n",
-      "Sea state 20/200. (Hs, Te) = (2.8107970520086796 m, 10.711433106791901 s). Tp = 11.853485630609148 s\n",
-      "Sea state 21/200. (Hs, Te) = (3.9450344430779625 m, 12.237764463240708 s). Tp = 13.542554368735527 s\n",
-      "Sea state 22/200. (Hs, Te) = (5.208290345944717 m, 12.779909428576214 s). Tp = 14.142502806282762 s\n",
-      "Sea state 23/200. (Hs, Te) = (5.064261814083509 m, 11.637831173755485 s). Tp = 12.878656218475125 s\n",
-      "Sea state 24/200. (Hs, Te) = (4.379521879521117 m, 10.312278693768631 s). Tp = 11.411773391733709 s\n",
-      "Sea state 25/200. (Hs, Te) = (3.5851473474648303 m, 9.202172592956305 s). Tp = 10.183307827579942 s\n",
-      "Sea state 26/200. (Hs, Te) = (3.685482708071981 m, 7.779449820330637 s). Tp = 8.608894415898781 s\n",
-      "Sea state 27/200. (Hs, Te) = (2.9763084662416763 m, 7.623162087670313 s). Tp = 8.435943292098646 s\n",
-      "Sea state 28/200. (Hs, Te) = (2.522737928991046 m, 7.032634458082821 s). Tp = 7.7824536327780285 s\n",
-      "Sea state 29/200. (Hs, Te) = (1.8248226200631286 m, 6.173217780864412 s). Tp = 6.831405987467631 s\n",
-      "Sea state 30/200. (Hs, Te) = (1.5073537401283845 m, 5.798538866794911 s). Tp = 6.416778824161261 s\n",
-      "Sea state 31/200. (Hs, Te) = (1.544648128528352 m, 6.991514600764015 s). Tp = 7.73694957809163 s\n",
-      "Sea state 32/200. (Hs, Te) = (1.1824969929468647 m, 6.59815195035135 s). Tp = 7.301646619300026 s\n",
-      "Sea state 33/200. (Hs, Te) = (1.0552074511072387 m, 7.163058124004591 s). Tp = 7.926783064188546 s\n",
-      "Sea state 34/200. (Hs, Te) = (0.8070976865959585 m, 7.601417023502728 s). Tp = 8.41187977015183 s\n",
-      "Sea state 35/200. (Hs, Te) = (0.43594988466745865 m, 8.895171963861962 s). Tp = 9.843574804997713 s\n",
-      "Sea state 36/200. (Hs, Te) = (1.1925410643512184 m, 9.872043847355096 s). Tp = 10.924600725477926 s\n",
-      "Sea state 37/200. (Hs, Te) = (1.8028237883891736 m, 10.88264042709196 s). Tp = 12.04294706782291 s\n",
-      "Sea state 38/200. (Hs, Te) = (2.0536026727829158 m, 11.313724254083688 s). Tp = 12.519993033371104 s\n",
-      "Sea state 39/200. (Hs, Te) = (2.9552188313626924 m, 13.585806588148326 s). Tp = 15.034324685343892 s\n",
-      "Sea state 40/200. (Hs, Te) = (3.6331136496492835 m, 13.97990050373177 s). Tp = 15.47043687676642 s\n",
-      "Sea state 41/200. (Hs, Te) = (5.144265805980378 m, 16.494051026966694 s). Tp = 18.252646017526228 s\n",
-      "Sea state 42/200. (Hs, Te) = (5.799748193230507 m, 13.531617551407685 s). Tp = 14.97435801590407 s\n",
-      "Sea state 43/200. (Hs, Te) = (5.880641596533005 m, 12.031691730764155 s). Tp = 13.314510170641965 s\n",
-      "Sea state 44/200. (Hs, Te) = (6.51238308153145 m, 12.003103839792574 s). Tp = 13.282874240000137 s\n",
-      "Sea state 45/200. (Hs, Te) = (5.580209865963464 m, 9.727880824002659 s). Tp = 10.765067046955512 s\n",
-      "Sea state 46/200. (Hs, Te) = (4.100873196672923 m, 7.9730435784224145 s). Tp = 8.823129131910912 s\n",
-      "Sea state 47/200. (Hs, Te) = (3.1340604795919393 m, 6.764084114821338 s). Tp = 7.485270463802562 s\n",
-      "Sea state 48/200. (Hs, Te) = (2.56485636049072 m, 5.9144283344779724 s). Tp = 6.545024421760062 s\n",
-      "Sea state 49/200. (Hs, Te) = (1.9133076193222602 m, 5.739115906958378 s). Tp = 6.351020190976688 s\n",
-      "Sea state 50/200. (Hs, Te) = (1.451516130573119 m, 5.529526324054767 s). Tp = 6.1190841760191725 s\n",
-      "Sea state 51/200. (Hs, Te) = (1.1108464969032716 m, 5.620177089281756 s). Tp = 6.219400121822961 s\n",
-      "Sea state 52/200. (Hs, Te) = (0.5408216661607194 m, 5.786678826645898 s). Tp = 6.403654267056419 s\n",
-      "Sea state 53/200. (Hs, Te) = (0.5380468022216697 m, 6.366389882593204 s). Tp = 7.045174090134016 s\n",
-      "Sea state 54/200. (Hs, Te) = (0.3365260257595956 m, 7.308686450335826 s). Tp = 8.087938276228511 s\n",
-      "Sea state 55/200. (Hs, Te) = (0.13904048508259811 m, 9.353861073536656 s). Tp = 10.351169327246874 s\n",
-      "Sea state 56/200. (Hs, Te) = (0.016222817409913045 m, 10.555122094632276 s). Tp = 11.680508745250528 s\n",
-      "Sea state 57/200. (Hs, Te) = (0.9853173366828838 m, 13.099921941116929 s). Tp = 14.496635038748579 s\n",
-      "Sea state 58/200. (Hs, Te) = (1.473244705812314 m, 14.122791226249372 s). Tp = 15.628562601795295 s\n",
-      "Sea state 59/200. (Hs, Te) = (2.75132120738797 m, 16.45603635813758 s). Tp = 18.210578226388876 s\n",
-      "Sea state 60/200. (Hs, Te) = (3.6161379238827065 m, 16.408517026993035 s). Tp = 18.15799238626064 s\n",
-      "Sea state 61/200. (Hs, Te) = (0.06168214841402529 m, 12.829541181563107 s). Tp = 14.197426294576688 s\n",
-      "Sea state 62/200. (Hs, Te) = (0.8144132100052286 m, 15.079313073296817 s). Tp = 16.68706876584456 s\n",
-      "Sea state 63/200. (Hs, Te) = (1.516942605361148 m, 16.537563949182438 s). Tp = 18.30079828558297 s\n",
-      "Sea state 64/200. (Hs, Te) = (3.5189950096049984 m, 17.443166728395703 s). Tp = 19.302956393038976 s\n",
-      "Sea state 65/200. (Hs, Te) = (5.142358500915479 m, 17.095909887023208 s). Tp = 18.918675042607017 s\n",
-      "Sea state 66/200. (Hs, Te) = (6.688164513590967 m, 15.49638894389953 s). Tp = 17.14861324731346 s\n",
-      "Sea state 67/200. (Hs, Te) = (7.38093521608525 m, 13.973338528525257 s). Tp = 15.463175264053787 s\n",
-      "Sea state 68/200. (Hs, Te) = (7.0401547336088806 m, 12.390922649193692 s). Tp = 13.712042273696882 s\n",
-      "Sea state 69/200. (Hs, Te) = (6.78506479000579 m, 11.942048671980722 s). Tp = 13.21530937289815 s\n",
-      "Sea state 70/200. (Hs, Te) = (5.429163429903464 m, 9.382949943110583 s). Tp = 10.38335965080746 s\n",
-      "Sea state 71/200. (Hs, Te) = (4.638215677462449 m, 7.951976580697559 s). Tp = 8.799815971820943 s\n",
-      "Sea state 72/200. (Hs, Te) = (3.844888983563724 m, 7.138788533096206 s). Tp = 7.899925850571548 s\n",
-      "Sea state 73/200. (Hs, Te) = (3.137219896709583 m, 6.146710336025804 s). Tp = 6.802072320033404 s\n",
-      "Sea state 74/200. (Hs, Te) = (2.0531097877647 m, 5.282256705596885 s). Tp = 5.8454506817841 s\n",
-      "Sea state 75/200. (Hs, Te) = (1.400213943382828 m, 4.84359372140781 s). Tp = 5.360017469633588 s\n",
-      "Sea state 76/200. (Hs, Te) = (1.0439873396686965 m, 4.8568106143709855 s). Tp = 5.37464354713959 s\n",
-      "Sea state 77/200. (Hs, Te) = (0.7636698181099354 m, 5.091330002497621 s). Tp = 5.634167382049754 s\n",
-      "Sea state 78/200. (Hs, Te) = (0.5164301455498969 m, 5.271200170082657 s). Tp = 5.833215298942646 s\n",
-      "Sea state 79/200. (Hs, Te) = (0.27764628706602273 m, 5.770502054768426 s). Tp = 6.385752728477266 s\n",
-      "Sea state 80/200. (Hs, Te) = (0.12019246831682381 m, 6.422497059929555 s). Tp = 7.107263412234976 s\n",
-      "Sea state 81/200. (Hs, Te) = (0.9435318150397511 m, 17.686766663680846 s). Tp = 19.57252894264383 s\n",
-      "Sea state 82/200. (Hs, Te) = (1.8095106472743567 m, 18.69492089098288 s). Tp = 20.688172529045467 s\n",
-      "Sea state 83/200. (Hs, Te) = (3.259242038934493 m, 18.12023589435014 s). Tp = 20.052214643504133 s\n",
-      "Sea state 84/200. (Hs, Te) = (4.553386977816094 m, 19.559176338719734 s). Tp = 21.64457485437285 s\n",
-      "Sea state 85/200. (Hs, Te) = (6.079815681228885 m, 17.580622913690455 s). Tp = 19.455068150726802 s\n",
-      "Sea state 86/200. (Hs, Te) = (7.756236359086145 m, 16.334746346569563 s). Tp = 18.0763562791551 s\n",
-      "Sea state 87/200. (Hs, Te) = (8.032314897416262 m, 13.853555311897695 s). Tp = 15.330620766170338 s\n",
-      "Sea state 88/200. (Hs, Te) = (7.437035773606835 m, 12.219920335227009 s). Tp = 13.522807700582689 s\n",
-      "Sea state 89/200. (Hs, Te) = (6.272689262948052 m, 10.341413873554192 s). Tp = 11.444014963098644 s\n",
-      "Sea state 90/200. (Hs, Te) = (5.680501796529699 m, 8.999952214580796 s). Tp = 9.959526721411192 s\n",
-      "Sea state 91/200. (Hs, Te) = (4.295403919706385 m, 7.407648031465147 s). Tp = 8.197451136758348 s\n",
-      "Sea state 92/200. (Hs, Te) = (3.802009467884611 m, 6.735058106015025 s). Tp = 7.45314970322185 s\n",
-      "Sea state 93/200. (Hs, Te) = (2.989442106573119 m, 5.947499898935134 s). Tp = 6.581622074956081 s\n",
-      "Sea state 94/200. (Hs, Te) = (2.1700845237542685 m, 4.95257206736844 s). Tp = 5.48061508201776 s\n",
-      "Sea state 95/200. (Hs, Te) = (1.6133443085967656 m, 4.56969222054859 s). Tp = 5.056912602874126 s\n",
-      "Sea state 96/200. (Hs, Te) = (1.2266847114435944 m, 4.571489478117535 s). Tp = 5.058901483965535 s\n",
-      "Sea state 97/200. (Hs, Te) = (1.1303877451521183 m, 4.660379638074873 s). Tp = 5.157269108843737 s\n",
-      "Sea state 98/200. (Hs, Te) = (0.4872278356806693 m, 4.633757768877119 s). Tp = 5.127808817130256 s\n",
-      "Sea state 99/200. (Hs, Te) = (0.4798540716715929 m, 4.8704655677404585 s). Tp = 5.389754391033024 s\n",
-      "Sea state 100/200. (Hs, Te) = (0.31668721479335277 m, 5.383362621384034 s). Tp = 5.957336505838085 s\n",
-      "Sea state 101/200. (Hs, Te) = (0.9159629695168572 m, 18.536545272385226 s). Tp = 20.51291090900176 s\n",
-      "Sea state 102/200. (Hs, Te) = (2.7901658222821446 m, 19.71513088475056 s). Tp = 21.817157267199796 s\n",
-      "Sea state 103/200. (Hs, Te) = (3.6108764062877143 m, 19.64828596034304 s). Tp = 21.74318533991013 s\n",
-      "Sea state 104/200. (Hs, Te) = (6.753018218293009 m, 19.628479599524695 s). Tp = 21.721267225777854 s\n",
-      "Sea state 105/200. (Hs, Te) = (7.585465267742793 m, 18.93939426620065 s). Tp = 20.958711644709915 s\n",
-      "Sea state 106/200. (Hs, Te) = (8.635760904114186 m, 17.1930692826929 s). Tp = 19.02619356874327 s\n",
-      "Sea state 107/200. (Hs, Te) = (9.05426230998776 m, 15.60503313558586 s). Tp = 17.268841077909393 s\n",
-      "Sea state 108/200. (Hs, Te) = (8.626994106919245 m, 13.664271430098866 s). Tp = 15.121155445270777 s\n",
-      "Sea state 109/200. (Hs, Te) = (8.249276423093754 m, 12.089069676425865 s). Tp = 13.378005750330896 s\n",
-      "Sea state 110/200. (Hs, Te) = (6.546720844163918 m, 9.609606714783245 s). Tp = 10.634182557445284 s\n",
-      "Sea state 111/200. (Hs, Te) = (4.6701612388987925 m, 7.257490338569866 s). Tp = 8.031283637291722 s\n",
-      "Sea state 112/200. (Hs, Te) = (4.247473885467209 m, 6.845251449907407 s). Tp = 7.575091856563489 s\n",
-      "Sea state 113/200. (Hs, Te) = (3.1407263408032344 m, 5.61649903202472 s). Tp = 6.21532991026395 s\n",
-      "Sea state 114/200. (Hs, Te) = (2.551617919566844 m, 5.052936353097902 s). Tp = 5.591680203450128 s\n",
-      "Sea state 115/200. (Hs, Te) = (1.8905541932864423 m, 4.58657204053238 s). Tp = 5.075592148517581 s\n",
-      "Sea state 116/200. (Hs, Te) = (1.5613774797899114 m, 4.417758226719366 s). Tp = 4.88877941334659 s\n",
-      "Sea state 117/200. (Hs, Te) = (0.8528945597991013 m, 4.288719454514684 s). Tp = 4.74598253295999 s\n",
-      "Sea state 118/200. (Hs, Te) = (0.7535671669252131 m, 4.366286078627602 s). Tp = 4.831819307103156 s\n",
-      "Sea state 119/200. (Hs, Te) = (0.3511622723387135 m, 4.5626616143918675 s). Tp = 5.04913239380011 s\n",
-      "Sea state 120/200. (Hs, Te) = (0.23409447683192347 m, 4.831684374307781 s). Tp = 5.346838348472796 s\n",
-      "Sea state 121/200. (Hs, Te) = (0.6567506058522764 m, 20.65466056484252 s). Tp = 22.85685956020476 s\n",
-      "Sea state 122/200. (Hs, Te) = (1.9109048595321103 m, 20.232119606821662 s). Tp = 22.38926730393905 s\n",
-      "Sea state 123/200. (Hs, Te) = (5.150072039646266 m, 21.75628304033487 s). Tp = 24.075936975282378 s\n",
-      "Sea state 124/200. (Hs, Te) = (8.216295742464304 m, 20.537645676815334 s). Tp = 22.72736854999455 s\n",
-      "Sea state 125/200. (Hs, Te) = (8.60693817012891 m, 18.967871991795526 s). Tp = 20.99022566414745 s\n",
-      "Sea state 126/200. (Hs, Te) = (9.398789015485178 m, 16.100608602045437 s). Tp = 17.817254778671455 s\n",
-      "Sea state 127/200. (Hs, Te) = (9.40047294257686 m, 15.347435783673259 s). Tp = 16.98377870773571 s\n",
-      "Sea state 128/200. (Hs, Te) = (8.79993692151442 m, 12.79158147602177 s). Tp = 14.155419326910422 s\n",
-      "Sea state 129/200. (Hs, Te) = (8.177600332494796 m, 11.910657841670044 s). Tp = 13.180571653648933 s\n",
-      "Sea state 130/200. (Hs, Te) = (6.949387711018023 m, 9.748680946742258 s). Tp = 10.78808487786111 s\n",
-      "Sea state 131/200. (Hs, Te) = (5.977891095364696 m, 8.28691724719266 s). Tp = 9.170467997355125 s\n",
-      "Sea state 132/200. (Hs, Te) = (4.51101544283036 m, 6.834717588605634 s). Tp = 7.563434875435892 s\n",
-      "Sea state 133/200. (Hs, Te) = (3.1807875598100446 m, 5.360130005515921 s). Tp = 5.9316268294942605 s\n",
-      "Sea state 134/200. (Hs, Te) = (2.5974274134022024 m, 5.0469024266918066 s). Tp = 5.5850029400776435 s\n",
-      "Sea state 135/200. (Hs, Te) = (1.7390452207300586 m, 4.245268668775884 s). Tp = 4.69789902636861 s\n",
-      "Sea state 136/200. (Hs, Te) = (1.6719550940091157 m, 4.273249097729748 s). Tp = 4.728862727419275 s\n",
-      "Sea state 137/200. (Hs, Te) = (1.2706497306606221 m, 4.121193500467361 s). Tp = 4.560594969105915 s\n",
-      "Sea state 138/200. (Hs, Te) = (0.7236083260991419 m, 3.953915214219135 s). Tp = 4.375481479380716 s\n",
-      "Sea state 139/200. (Hs, Te) = (0.5662113586554597 m, 4.165911158867419 s). Tp = 4.61008042226563 s\n",
-      "Sea state 140/200. (Hs, Te) = (0.22380262429040848 m, 4.428588430704851 s). Tp = 4.900764333201723 s\n",
-      "Sea state 141/200. (Hs, Te) = (0.9422263633698529 m, 21.68156229851667 s). Tp = 23.993249511278247 s\n",
-      "Sea state 142/200. (Hs, Te) = (2.6808185912102096 m, 22.65619752776177 s). Tp = 25.071800305533483 s\n",
-      "Sea state 143/200. (Hs, Te) = (5.284470291643777 m, 22.420384661431555 s). Tp = 24.810845081830916 s\n",
-      "Sea state 144/200. (Hs, Te) = (7.449969927903553 m, 21.84994192365026 s). Tp = 24.179581764592026 s\n",
-      "Sea state 145/200. (Hs, Te) = (9.184267967048088 m, 20.471169146791553 s). Tp = 22.653804295281518 s\n",
-      "Sea state 146/200. (Hs, Te) = (10.717866496341058 m, 17.115719729476954 s). Tp = 18.940597009586504 s\n",
-      "Sea state 147/200. (Hs, Te) = (10.671834020151834 m, 14.880105357839954 s). Tp = 16.46662153258152 s\n",
-      "Sea state 148/200. (Hs, Te) = (10.191452698929544 m, 13.818581919045513 s). Tp = 15.291918511719986 s\n",
-      "Sea state 149/200. (Hs, Te) = (8.37690632915727 m, 10.962421795675256 s). Tp = 12.131234722393874 s\n",
-      "Sea state 150/200. (Hs, Te) = (7.4694526641366625 m, 9.888932685570508 s). Tp = 10.943290250876458 s\n",
-      "Sea state 151/200. (Hs, Te) = (5.212528893273048 m, 7.249094730639045 s). Tp = 8.021992890014861 s\n",
-      "Sea state 152/200. (Hs, Te) = (4.063796625344188 m, 6.135879435017965 s). Tp = 6.790086628839425 s\n",
-      "Sea state 153/200. (Hs, Te) = (3.3787764210161813 m, 5.419027822055873 s). Tp = 5.996804328627211 s\n",
-      "Sea state 154/200. (Hs, Te) = (2.795945700731734 m, 4.958285027601677 s). Tp = 5.486937157818241 s\n",
-      "Sea state 155/200. (Hs, Te) = (1.9272686719719325 m, 4.228829976069561 s). Tp = 4.679707640973425 s\n",
-      "Sea state 156/200. (Hs, Te) = (1.568113495064289 m, 4.032997225028029 s). Tp = 4.462995210682322 s\n",
-      "Sea state 157/200. (Hs, Te) = (1.1822964652570693 m, 3.8685969019191884 s). Tp = 4.281066532399067 s\n",
-      "Sea state 158/200. (Hs, Te) = (0.7856775833759984 m, 3.797389763440326 s). Tp = 4.202267291966823 s\n",
-      "Sea state 159/200. (Hs, Te) = (0.3291798465609936 m, 4.03461070522861 s). Tp = 4.464780720070485 s\n",
-      "Sea state 160/200. (Hs, Te) = (0.15420429246200082 m, 4.3518582866098265 s). Tp = 4.81585322453894 s\n",
-      "Sea state 161/200. (Hs, Te) = (2.0790807412143555 m, 23.553887059988554 s). Tp = 26.065201455959503 s\n",
-      "Sea state 162/200. (Hs, Te) = (2.9005504155626443 m, 23.487521867586448 s). Tp = 25.99176040968044 s\n",
-      "Sea state 163/200. (Hs, Te) = (7.085064893935304 m, 23.617650072612047 s). Tp = 26.135762878167114 s\n",
-      "Sea state 164/200. (Hs, Te) = (10.008361591286254 m, 21.465144157914505 s). Tp = 23.75375687810255 s\n",
-      "Sea state 165/200. (Hs, Te) = (9.97460629881344 m, 20.66827347686875 s). Tp = 22.8719238803088 s\n",
-      "Sea state 166/200. (Hs, Te) = (12.515562162825644 m, 18.442195805046968 s). Tp = 20.408501905631287 s\n",
-      "Sea state 167/200. (Hs, Te) = (11.318704374242229 m, 15.379037771055806 s). Tp = 17.018750097614454 s\n",
-      "Sea state 168/200. (Hs, Te) = (9.831621741618951 m, 12.589522993573661 s). Tp = 13.931817378005688 s\n",
-      "Sea state 169/200. (Hs, Te) = (8.719753268757158 m, 11.001963549202046 s). Tp = 12.174992415931788 s\n",
-      "Sea state 170/200. (Hs, Te) = (6.697280646131268 m, 8.394469020363612 s). Tp = 9.289486935821916 s\n",
-      "Sea state 171/200. (Hs, Te) = (5.9260094336014575 m, 7.621869198633718 s). Tp = 8.434512555290185 s\n",
-      "Sea state 172/200. (Hs, Te) = (4.880617435847239 m, 6.717945332768991 s). Tp = 7.434212366849642 s\n",
-      "Sea state 173/200. (Hs, Te) = (3.876024525693232 m, 5.700254261167271 s). Tp = 6.308015118231136 s\n",
-      "Sea state 174/200. (Hs, Te) = (2.783776276233764 m, 4.665403840101326 s). Tp = 5.162828991067907 s\n",
-      "Sea state 175/200. (Hs, Te) = (2.232050172695443 m, 4.35064714713621 s). Tp = 4.8145129534282445 s\n",
-      "Sea state 176/200. (Hs, Te) = (1.4397061034565646 m, 3.8710858327287654 s). Tp = 4.283820832901415 s\n",
-      "Sea state 177/200. (Hs, Te) = (0.9917868156814885 m, 3.749108919277857 s). Tp = 4.148838746336396 s\n",
-      "Sea state 178/200. (Hs, Te) = (0.8379479685905803 m, 3.6939930215454 s). Tp = 4.08784639402683 s\n",
-      "Sea state 179/200. (Hs, Te) = (0.3649362767346382 m, 3.9015035570249985 s). Tp = 4.317481693615992 s\n",
-      "Sea state 180/200. (Hs, Te) = (0.26122851286335796 m, 3.8182178899126895 s). Tp = 4.2253161123619325 s\n",
-      "Sea state 181/200. (Hs, Te) = (1.85918793399297 m, 24.795749666965783 s). Tp = 27.43947139913466 s\n",
-      "Sea state 182/200. (Hs, Te) = (4.002691094113826 m, 24.82391450267687 s). Tp = 27.470639168382846 s\n",
-      "Sea state 183/200. (Hs, Te) = (8.434042106183172 m, 23.892405089109275 s). Tp = 26.439812262364136 s\n",
-      "Sea state 184/200. (Hs, Te) = (10.54951299048162 m, 22.368492149045327 s). Tp = 24.753419792070545 s\n",
-      "Sea state 185/200. (Hs, Te) = (12.438371651972409 m, 19.928667490533087 s). Tp = 22.0534611364409 s\n",
-      "Sea state 186/200. (Hs, Te) = (12.877658419178392 m, 18.405021605067592 s). Tp = 20.367364194095234 s\n",
-      "Sea state 187/200. (Hs, Te) = (12.20514433636702 m, 15.560744193082908 s). Tp = 17.219830050316762 s\n",
-      "Sea state 188/200. (Hs, Te) = (11.349999320223956 m, 13.573437147754268 s). Tp = 15.020636415762421 s\n",
-      "Sea state 189/200. (Hs, Te) = (8.943249528459614 m, 10.699541456942468 s). Tp = 11.840326093579028 s\n",
-      "Sea state 190/200. (Hs, Te) = (6.974694569119304 m, 8.532352187066413 s). Tp = 9.442071199656622 s\n",
-      "Sea state 191/200. (Hs, Te) = (6.794991647155438 m, 8.321004825044408 s). Tp = 9.208189991248899 s\n",
-      "Sea state 192/200. (Hs, Te) = (4.788840720460295 m, 6.38163862650819 s). Tp = 7.062048654450392 s\n",
-      "Sea state 193/200. (Hs, Te) = (3.2611200777648106 m, 4.933748144257159 s). Tp = 5.459784153057397 s\n",
-      "Sea state 194/200. (Hs, Te) = (2.863068054464451 m, 4.600269207998482 s). Tp = 5.0907497073727574 s\n",
-      "Sea state 195/200. (Hs, Te) = (2.3124781374766226 m, 4.192805730047 s). Tp = 4.639842491434172 s\n",
-      "Sea state 196/200. (Hs, Te) = (1.7972861360694252 m, 3.77507151907285 s). Tp = 4.177569477372569 s\n",
-      "Sea state 197/200. (Hs, Te) = (1.0994765211194881 m, 3.465224057093012 s). Tp = 3.8346860927085795 s\n",
-      "Sea state 198/200. (Hs, Te) = (0.8655202915109887 m, 3.438356041093707 s). Tp = 3.8049534100324585 s\n",
-      "Sea state 199/200. (Hs, Te) = (0.4625658856258066 m, 3.5756134401100295 s). Tp = 3.9568451868576466 s\n",
-      "Sea state 200/200. (Hs, Te) = (0.00764320162167542 m, 3.881423657080205 s). Tp = 4.29526087562771 s\n"
+      "Sea state 1/200. (Hs, Te) = (3.0519011698370164 m, 11.04583834537762 s). Tp = 12.223545140933947 s\n",
+      "Sea state 2/200. (Hs, Te) = (3.4454122915496477 m, 11.169309543379487 s). Tp = 12.36018083260262 s\n",
+      "Sea state 3/200. (Hs, Te) = (3.6662634602868733 m, 10.826118052470603 s). Tp = 11.980398280120792 s\n",
+      "Sea state 4/200. (Hs, Te) = (2.843537679463958 m, 9.454411623864956 s). Tp = 10.462440572801366 s\n",
+      "Sea state 5/200. (Hs, Te) = (3.2498724114450663 m, 9.102778237322505 s). Tp = 10.073316050147112 s\n",
+      "Sea state 6/200. (Hs, Te) = (2.5432758740513246 m, 9.068212764645198 s). Tp = 10.035065208302626 s\n",
+      "Sea state 7/200. (Hs, Te) = (2.4264778631768715 m, 8.911382062896639 s). Tp = 9.861513224074097 s\n",
+      "Sea state 8/200. (Hs, Te) = (2.3680978175067704 m, 7.789046740670324 s). Tp = 8.619514559460379 s\n",
+      "Sea state 9/200. (Hs, Te) = (2.2754848647911032 m, 7.730579014941564 s). Tp = 8.554813007401878 s\n",
+      "Sea state 10/200. (Hs, Te) = (2.2013893785282765 m, 8.531209614759113 s). Tp = 9.440806806340483 s\n",
+      "Sea state 11/200. (Hs, Te) = (2.2734303870548245 m, 8.840100909846239 s). Tp = 9.782632077639974 s\n",
+      "Sea state 12/200. (Hs, Te) = (2.1023284019631188 m, 8.616579481658642 s). Tp = 9.53527880467084 s\n",
+      "Sea state 13/200. (Hs, Te) = (1.4905589789833533 m, 8.267748616842887 s). Tp = 9.149255608485758 s\n",
+      "Sea state 14/200. (Hs, Te) = (1.2979444609623636 m, 8.430409347607648 s). Tp = 9.329259219166191 s\n",
+      "Sea state 15/200. (Hs, Te) = (2.132588467318634 m, 9.0814844673542 s). Tp = 10.049751939367129 s\n",
+      "Sea state 16/200. (Hs, Te) = (1.6432774588959944 m, 9.638029185709314 s). Tp = 10.665635430963668 s\n",
+      "Sea state 17/200. (Hs, Te) = (1.6876474061826714 m, 10.244402846851779 s). Tp = 11.336660625022391 s\n",
+      "Sea state 18/200. (Hs, Te) = (2.3000321378643753 m, 11.28775917735869 s). Tp = 12.49125956131476 s\n",
+      "Sea state 19/200. (Hs, Te) = (2.4146227608441593 m, 11.147740911966473 s). Tp = 12.336312554662857 s\n",
+      "Sea state 20/200. (Hs, Te) = (2.6103200843167143 m, 9.983394136743243 s). Tp = 11.047823177792889 s\n",
+      "Sea state 21/200. (Hs, Te) = (4.068731647379028 m, 13.47865291827843 s). Tp = 14.915746295934497 s\n",
+      "Sea state 22/200. (Hs, Te) = (3.6954884327563504 m, 11.566787354484731 s). Tp = 12.80003771033773 s\n",
+      "Sea state 23/200. (Hs, Te) = (4.480207105259814 m, 11.52005655504381 s). Tp = 12.748324475128467 s\n",
+      "Sea state 24/200. (Hs, Te) = (3.9561742254336414 m, 10.01673299203202 s). Tp = 11.084716620357161 s\n",
+      "Sea state 25/200. (Hs, Te) = (3.8531220807180997 m, 9.102625782286212 s). Tp = 10.073147340361595 s\n",
+      "Sea state 26/200. (Hs, Te) = (3.5663781572345914 m, 8.07240817659649 s). Tp = 8.933087979144979 s\n",
+      "Sea state 27/200. (Hs, Te) = (2.908241307240586 m, 7.952039998258466 s). Tp = 8.799886150959386 s\n",
+      "Sea state 28/200. (Hs, Te) = (2.464190314138586 m, 6.351176628326459 s). Tp = 7.028338799370605 s\n",
+      "Sea state 29/200. (Hs, Te) = (1.8859920748196535 m, 5.834077602503495 s). Tp = 6.4561066982983455 s\n",
+      "Sea state 30/200. (Hs, Te) = (1.7529151360331678 m, 6.187059223348201 s). Tp = 6.846723203936496 s\n",
+      "Sea state 31/200. (Hs, Te) = (1.1446025863887235 m, 6.175904417658782 s). Tp = 6.834379073358122 s\n",
+      "Sea state 32/200. (Hs, Te) = (1.2892599022789482 m, 7.0427301077881275 s). Tp = 7.793625680208137 s\n",
+      "Sea state 33/200. (Hs, Te) = (0.8966054052018009 m, 7.2246845535200235 s). Tp = 7.994980100891668 s\n",
+      "Sea state 34/200. (Hs, Te) = (0.6457634910721332 m, 8.242602318588398 s). Tp = 9.121428213024211 s\n",
+      "Sea state 35/200. (Hs, Te) = (1.1549727781983783 m, 9.080002152257277 s). Tp = 10.048111579900173 s\n",
+      "Sea state 36/200. (Hs, Te) = (1.2334407129813119 m, 10.628185539873787 s). Tp = 11.761362211790303 s\n",
+      "Sea state 37/200. (Hs, Te) = (1.2431677156081726 m, 11.406426838366153 s). Tp = 12.62257956308726 s\n",
+      "Sea state 38/200. (Hs, Te) = (1.1698012492327046 m, 12.996421545991407 s). Tp = 14.38209943607513 s\n",
+      "Sea state 39/200. (Hs, Te) = (2.618620581508073 m, 13.325913201158178 s). Tp = 14.746721476934301 s\n",
+      "Sea state 40/200. (Hs, Te) = (3.470102355731644 m, 14.741323374979535 s). Tp = 16.313042620850247 s\n",
+      "Sea state 41/200. (Hs, Te) = (5.692307434347409 m, 15.021145316541375 s). Tp = 16.62269916543804 s\n",
+      "Sea state 42/200. (Hs, Te) = (6.063254834692772 m, 14.912923656204937 s). Tp = 16.502938916465823 s\n",
+      "Sea state 43/200. (Hs, Te) = (6.480903322872717 m, 13.062850502306475 s). Tp = 14.45561104477273 s\n",
+      "Sea state 44/200. (Hs, Te) = (5.772781251171104 m, 11.063804638270845 s). Tp = 12.24342699918036 s\n",
+      "Sea state 45/200. (Hs, Te) = (4.817270478445196 m, 9.409534348102964 s). Tp = 10.41277848388365 s\n",
+      "Sea state 46/200. (Hs, Te) = (3.8173661650453172 m, 7.153726211432188 s). Tp = 7.916456183510652 s\n",
+      "Sea state 47/200. (Hs, Te) = (3.555645519825636 m, 7.0772788368068404 s). Tp = 7.831857993185889 s\n",
+      "Sea state 48/200. (Hs, Te) = (2.3757710877788805 m, 5.743160152018138 s). Tp = 6.355495633265744 s\n",
+      "Sea state 49/200. (Hs, Te) = (2.0006463135772363 m, 5.725278997544492 s). Tp = 6.3357079908934395 s\n",
+      "Sea state 50/200. (Hs, Te) = (1.5326631253318903 m, 5.450682138605642 s). Tp = 6.03183362700667 s\n",
+      "Sea state 51/200. (Hs, Te) = (1.0513428658700548 m, 5.250602616249876 s). Tp = 5.810421634831748 s\n",
+      "Sea state 52/200. (Hs, Te) = (0.5265157588947252 m, 5.743448169453037 s). Tp = 6.355814359106806 s\n",
+      "Sea state 53/200. (Hs, Te) = (0.4532800070739075 m, 6.025390228156072 s). Tp = 6.667817067631559 s\n",
+      "Sea state 54/200. (Hs, Te) = (0.3375768229335862 m, 7.7442235989089925 s). Tp = 8.569912376308078 s\n",
+      "Sea state 55/200. (Hs, Te) = (0.30102216405234467 m, 9.656746479427033 s). Tp = 10.686348361709246 s\n",
+      "Sea state 56/200. (Hs, Te) = (0.12542290090024186 m, 10.426998603044929 s). Tp = 11.538724732660175 s\n",
+      "Sea state 57/200. (Hs, Te) = (0.6729890509283177 m, 11.570361355358964 s). Tp = 12.803992771027009 s\n",
+      "Sea state 58/200. (Hs, Te) = (1.5175554651966627 m, 14.539941741525709 s). Tp = 16.090189686549614 s\n",
+      "Sea state 59/200. (Hs, Te) = (2.542385963739924 m, 14.83027643922333 s). Tp = 16.411479856867146 s\n",
+      "Sea state 60/200. (Hs, Te) = (3.843301514688319 m, 16.274667680028315 s). Tp = 18.009872027845976 s\n",
+      "Sea state 61/200. (Hs, Te) = (0.21703512911091222 m, 13.455423054650405 s). Tp = 14.890039665274477 s\n",
+      "Sea state 62/200. (Hs, Te) = (1.0647431724172083 m, 15.96883933443384 s). Tp = 17.67143627757849 s\n",
+      "Sea state 63/200. (Hs, Te) = (1.9266398513146878 m, 16.76677465034196 s). Tp = 18.554447421556524 s\n",
+      "Sea state 64/200. (Hs, Te) = (2.9446481669173643 m, 17.411128698164656 s). Tp = 19.267502469442523 s\n",
+      "Sea state 65/200. (Hs, Te) = (5.325927110106066 m, 17.28929200677703 s). Tp = 19.132675555410962 s\n",
+      "Sea state 66/200. (Hs, Te) = (6.358535119949946 m, 16.75931175233696 s). Tp = 18.546188829696494 s\n",
+      "Sea state 67/200. (Hs, Te) = (7.412694605997036 m, 14.620760342427937 s). Tp = 16.179625163103456 s\n",
+      "Sea state 68/200. (Hs, Te) = (6.912756247780623 m, 12.373393694903546 s). Tp = 13.692644383076056 s\n",
+      "Sea state 69/200. (Hs, Te) = (6.836728394398719 m, 11.960299344373112 s). Tp = 13.235505931173343 s\n",
+      "Sea state 70/200. (Hs, Te) = (5.355536467460859 m, 9.079058011369364 s). Tp = 10.047066774752572 s\n",
+      "Sea state 71/200. (Hs, Te) = (4.671151051589706 m, 8.180105150206973 s). Tp = 9.052267599315739 s\n",
+      "Sea state 72/200. (Hs, Te) = (3.4423336307698715 m, 6.6820931438917155 s). Tp = 7.394537619180891 s\n",
+      "Sea state 73/200. (Hs, Te) = (3.042300100254776 m, 6.127122298527252 s). Tp = 6.7803958068436145 s\n",
+      "Sea state 74/200. (Hs, Te) = (2.3786123268272035 m, 5.496412100399395 s). Tp = 6.082439315303118 s\n",
+      "Sea state 75/200. (Hs, Te) = (1.5041052101768 m, 4.9882001950273755 s). Tp = 5.5200418790709875 s\n",
+      "Sea state 76/200. (Hs, Te) = (1.1787130334573301 m, 4.923771573828079 s). Tp = 5.448743881130676 s\n",
+      "Sea state 77/200. (Hs, Te) = (0.7230899256428956 m, 5.085896456279929 s). Tp = 5.628154511374791 s\n",
+      "Sea state 78/200. (Hs, Te) = (0.6595252571108683 m, 5.241814253185951 s). Tp = 5.800696256886872 s\n",
+      "Sea state 79/200. (Hs, Te) = (0.4307357404436535 m, 5.7331571793437535 s). Tp = 6.344426144087493 s\n",
+      "Sea state 80/200. (Hs, Te) = (0.07857080829669981 m, 7.233311179831642 s). Tp = 8.004526497718864 s\n",
+      "Sea state 81/200. (Hs, Te) = (0.46027925182362306 m, 17.190680093637045 s). Tp = 19.023549644456015 s\n",
+      "Sea state 82/200. (Hs, Te) = (1.1980708521021082 m, 18.013198526276145 s). Tp = 19.93376495598297 s\n",
+      "Sea state 83/200. (Hs, Te) = (3.3456270989608847 m, 19.22345321864848 s). Tp = 21.27305695009685 s\n",
+      "Sea state 84/200. (Hs, Te) = (4.7172043745682934 m, 18.93499681508312 s). Tp = 20.95384533754884 s\n",
+      "Sea state 85/200. (Hs, Te) = (6.847539405620025 m, 17.01205239650382 s). Tp = 18.82587667015952 s\n",
+      "Sea state 86/200. (Hs, Te) = (7.7231278201867735 m, 16.002541319345347 s). Tp = 17.7087315666298 s\n",
+      "Sea state 87/200. (Hs, Te) = (7.629081235847672 m, 13.589062961401245 s). Tp = 15.037928252968927 s\n",
+      "Sea state 88/200. (Hs, Te) = (8.452363775230276 m, 13.697027484905862 s). Tp = 15.157403949191693 s\n",
+      "Sea state 89/200. (Hs, Te) = (6.786448289244335 m, 11.096803430725068 s). Tp = 12.279944121425705 s\n",
+      "Sea state 90/200. (Hs, Te) = (5.894927231129716 m, 9.486667762348933 s). Tp = 10.498135859343025 s\n",
+      "Sea state 91/200. (Hs, Te) = (4.358786891532466 m, 7.463316562369551 s). Tp = 8.259055043964198 s\n",
+      "Sea state 92/200. (Hs, Te) = (3.9467659355519693 m, 6.83220935253828 s). Tp = 7.560659211350037 s\n",
+      "Sea state 93/200. (Hs, Te) = (3.1553632519540327 m, 5.7986464312643555 s). Tp = 6.416897857149677 s\n",
+      "Sea state 94/200. (Hs, Te) = (2.4326564397131407 m, 5.386310322285478 s). Tp = 5.960598490479192 s\n",
+      "Sea state 95/200. (Hs, Te) = (1.9880614356841193 m, 4.766775125231435 s). Tp = 5.275008478132455 s\n",
+      "Sea state 96/200. (Hs, Te) = (1.293408716110891 m, 4.581909760591489 s). Tp = 5.070432776495719 s\n",
+      "Sea state 97/200. (Hs, Te) = (0.9616341076852011 m, 4.6589618685367205 s). Tp = 5.15570017678017 s\n",
+      "Sea state 98/200. (Hs, Te) = (0.666386186607189 m, 4.855002832015561 s). Tp = 5.372643019109433 s\n",
+      "Sea state 99/200. (Hs, Te) = (0.264660735105467 m, 5.103153352076978 s). Tp = 5.647251336638027 s\n",
+      "Sea state 100/200. (Hs, Te) = (0.12685463433629815 m, 5.661138705021298 s). Tp = 6.264729063219917 s\n",
+      "Sea state 101/200. (Hs, Te) = (1.1268237311741414 m, 18.301713991606317 s). Tp = 20.25304192745854 s\n",
+      "Sea state 102/200. (Hs, Te) = (1.845198442336088 m, 19.674565478195856 s). Tp = 21.77226677879343 s\n",
+      "Sea state 103/200. (Hs, Te) = (4.413499842939948 m, 20.172795771988145 s). Tp = 22.32361836446093 s\n",
+      "Sea state 104/200. (Hs, Te) = (6.483193116894594 m, 19.359981891388735 s). Tp = 21.424142303882665 s\n",
+      "Sea state 105/200. (Hs, Te) = (7.841572973402071 m, 18.519669560552952 s). Tp = 20.494235909520757 s\n",
+      "Sea state 106/200. (Hs, Te) = (8.790048122755998 m, 17.636792469179515 s). Tp = 19.51722650173635 s\n",
+      "Sea state 107/200. (Hs, Te) = (8.753396102235087 m, 14.14643164730843 s). Tp = 15.654723563501475 s\n",
+      "Sea state 108/200. (Hs, Te) = (8.426752536347962 m, 13.182638875844871 s). Tp = 14.58817124939662 s\n",
+      "Sea state 109/200. (Hs, Te) = (7.538945072970559 m, 10.89657968634219 s). Tp = 12.058372530277524 s\n",
+      "Sea state 110/200. (Hs, Te) = (6.52392465965872 m, 9.485481750157293 s). Tp = 10.496823394583998 s\n",
+      "Sea state 111/200. (Hs, Te) = (5.209202704421955 m, 7.9749237506419925 s). Tp = 8.825209768009335 s\n",
+      "Sea state 112/200. (Hs, Te) = (4.0540640761131765 m, 6.580592173706031 s). Tp = 7.282214620045882 s\n",
+      "Sea state 113/200. (Hs, Te) = (3.3049358170467524 m, 5.894452158235983 s). Tp = 6.522918386491186 s\n",
+      "Sea state 114/200. (Hs, Te) = (2.169848292969151 m, 4.7404643760311345 s). Tp = 5.245892478016787 s\n",
+      "Sea state 115/200. (Hs, Te) = (1.9534343747113685 m, 4.584560512331687 s). Tp = 5.073366151269149 s\n",
+      "Sea state 116/200. (Hs, Te) = (1.4832783753736873 m, 4.356627084101155 s). Tp = 4.821130471007753 s\n",
+      "Sea state 117/200. (Hs, Te) = (1.0598538682129985 m, 4.317024005381985 s). Tp = 4.777304913788158 s\n",
+      "Sea state 118/200. (Hs, Te) = (0.7258158734724787 m, 4.42511891003475 s). Tp = 4.896924892391318 s\n",
+      "Sea state 119/200. (Hs, Te) = (0.3218056251115961 m, 4.837161638335263 s). Tp = 5.352899598148494 s\n",
+      "Sea state 120/200. (Hs, Te) = (0.1529178499563497 m, 5.0948910210045915 s). Tp = 5.6381080761923466 s\n",
+      "Sea state 121/200. (Hs, Te) = (1.4617033785832907 m, 19.967713785536485 s). Tp = 22.09667054568959 s\n",
+      "Sea state 122/200. (Hs, Te) = (2.798041717936526 m, 21.495323765808678 s). Tp = 23.787154234454817 s\n",
+      "Sea state 123/200. (Hs, Te) = (5.259564944383678 m, 21.394671367392732 s). Tp = 23.675770281774085 s\n",
+      "Sea state 124/200. (Hs, Te) = (8.35812856579741 m, 20.660736018189226 s). Tp = 22.863582778118428 s\n",
+      "Sea state 125/200. (Hs, Te) = (8.439618161440924 m, 19.14134618167327 s). Tp = 21.18219566447295 s\n",
+      "Sea state 126/200. (Hs, Te) = (10.292141263188919 m, 18.299482065544524 s). Tp = 20.250572033538813 s\n",
+      "Sea state 127/200. (Hs, Te) = (9.289089256709273 m, 14.555275372180486 s). Tp = 16.107158188226222 s\n",
+      "Sea state 128/200. (Hs, Te) = (8.542968895321545 m, 12.324863083963992 s). Tp = 13.638939440545823 s\n",
+      "Sea state 129/200. (Hs, Te) = (7.468390108552663 m, 10.287748814954023 s). Tp = 11.384628138325445 s\n",
+      "Sea state 130/200. (Hs, Te) = (6.5707446111457015 m, 9.319715314854362 s). Tp = 10.313382949284977 s\n",
+      "Sea state 131/200. (Hs, Te) = (5.60872818188617 m, 8.051983881072617 s). Tp = 8.910486046136219 s\n",
+      "Sea state 132/200. (Hs, Te) = (3.991538414403644 m, 6.252186602100548 s). Tp = 6.91879446092924 s\n",
+      "Sea state 133/200. (Hs, Te) = (3.626524247915902 m, 5.902411884648774 s). Tp = 6.531726778581856 s\n",
+      "Sea state 134/200. (Hs, Te) = (2.6518984771001484 m, 5.066182973924612 s). Tp = 5.606339178403159 s\n",
+      "Sea state 135/200. (Hs, Te) = (1.8091038427854655 m, 4.457956383976893 s). Tp = 4.933263496351967 s\n",
+      "Sea state 136/200. (Hs, Te) = (1.2989406338592269 m, 3.994531032515327 s). Tp = 4.420427754426217 s\n",
+      "Sea state 137/200. (Hs, Te) = (1.0499593452251907 m, 4.193532941030377 s). Tp = 4.640647237620415 s\n",
+      "Sea state 138/200. (Hs, Te) = (0.6433991714660491 m, 4.216701883166105 s). Tp = 4.666286451341325 s\n",
+      "Sea state 139/200. (Hs, Te) = (0.35316386403086203 m, 4.501882113825003 s). Tp = 4.981872585572572 s\n",
+      "Sea state 140/200. (Hs, Te) = (0.2744545504333075 m, 4.488377393677282 s). Tp = 4.966927992760345 s\n",
+      "Sea state 141/200. (Hs, Te) = (0.8068170560899437 m, 21.216684038752813 s). Tp = 23.478805952031312 s\n",
+      "Sea state 142/200. (Hs, Te) = (3.069808490956658 m, 22.045232858515607 s). Tp = 24.39569461029022 s\n",
+      "Sea state 143/200. (Hs, Te) = (5.267494602662645 m, 22.51536680045854 s). Tp = 24.915954212317576 s\n",
+      "Sea state 144/200. (Hs, Te) = (8.574728268404309 m, 21.303061011945967 s). Tp = 23.574392434283755 s\n",
+      "Sea state 145/200. (Hs, Te) = (10.671063465675838 m, 19.060263176557495 s). Tp = 21.092467592940014 s\n",
+      "Sea state 146/200. (Hs, Te) = (10.876296838223272 m, 17.532968720866293 s). Tp = 19.402333069972638 s\n",
+      "Sea state 147/200. (Hs, Te) = (10.534388756527077 m, 14.801445206897775 s). Tp = 16.379574639826952 s\n",
+      "Sea state 148/200. (Hs, Te) = (9.779306267722461 m, 13.051496141467442 s). Tp = 14.443046082483523 s\n",
+      "Sea state 149/200. (Hs, Te) = (8.921235180657721 m, 11.717822520116258 s). Tp = 12.967176238644907 s\n",
+      "Sea state 150/200. (Hs, Te) = (7.273929502655918 m, 9.597743252685069 s). Tp = 10.62105421354321 s\n",
+      "Sea state 151/200. (Hs, Te) = (5.55737098699723 m, 7.627379062574176 s). Tp = 8.440609880680139 s\n",
+      "Sea state 152/200. (Hs, Te) = (4.408665215071578 m, 6.445613979770078 s). Tp = 7.132845057045867 s\n",
+      "Sea state 153/200. (Hs, Te) = (3.312948927456145 m, 5.3889083767085015 s). Tp = 5.963473549349823 s\n",
+      "Sea state 154/200. (Hs, Te) = (2.9187259448491996 m, 5.025725684161813 s). Tp = 5.561568334196267 s\n",
+      "Sea state 155/200. (Hs, Te) = (1.783850908447242 m, 4.109944171454214 s). Tp = 4.548146237131219 s\n",
+      "Sea state 156/200. (Hs, Te) = (1.3804145578511127 m, 3.948052538207203 s). Tp = 4.368993725111841 s\n",
+      "Sea state 157/200. (Hs, Te) = (1.101209720396516 m, 3.8107141547419805 s). Tp = 4.217012329279396 s\n",
+      "Sea state 158/200. (Hs, Te) = (0.6155862117958195 m, 3.848386306392394 s). Tp = 4.258701084071616 s\n",
+      "Sea state 159/200. (Hs, Te) = (0.525084466395597 m, 3.9369025968803957 s). Tp = 4.356654977534205 s\n",
+      "Sea state 160/200. (Hs, Te) = (0.09750512397836705 m, 4.300920721697868 s). Tp = 4.759484698710284 s\n",
+      "Sea state 161/200. (Hs, Te) = (1.8205359120028697 m, 23.730249683977565 s). Tp = 26.260367855113387 s\n",
+      "Sea state 162/200. (Hs, Te) = (3.976921009811278 m, 23.565594395719824 s). Tp = 26.07815702730834 s\n",
+      "Sea state 163/200. (Hs, Te) = (6.204240115221088 m, 22.723791210681824 s). Tp = 25.146600823935152 s\n",
+      "Sea state 164/200. (Hs, Te) = (10.125799848939408 m, 22.40066350074622 s). Tp = 24.78902125186606 s\n",
+      "Sea state 165/200. (Hs, Te) = (10.66793996073962 m, 21.6908578381681 s). Tp = 24.003536140955944 s\n",
+      "Sea state 166/200. (Hs, Te) = (12.060622651625676 m, 18.266815645632505 s). Tp = 20.21442272138141 s\n",
+      "Sea state 167/200. (Hs, Te) = (11.121735584154075 m, 15.855584181171377 s). Tp = 17.54610586488723 s\n",
+      "Sea state 168/200. (Hs, Te) = (10.998739267749489 m, 13.56417998032559 s). Tp = 15.01039224955217 s\n",
+      "Sea state 169/200. (Hs, Te) = (8.956292813877395 m, 11.186026584968262 s). Tp = 12.378680244425786 s\n",
+      "Sea state 170/200. (Hs, Te) = (6.621433952777892 m, 8.741275725438278 s). Tp = 9.673270156443893 s\n",
+      "Sea state 171/200. (Hs, Te) = (6.533492611294109 m, 8.37223466140765 s). Tp = 9.26488195049804 s\n",
+      "Sea state 172/200. (Hs, Te) = (4.835217043872919 m, 6.811976335865213 s). Tp = 7.53826895133469 s\n",
+      "Sea state 173/200. (Hs, Te) = (3.611112043718707 m, 5.53893766445577 s). Tp = 6.129498953117237 s\n",
+      "Sea state 174/200. (Hs, Te) = (2.833447601414693 m, 4.825371501732234 s). Tp = 5.339852397702617 s\n",
+      "Sea state 175/200. (Hs, Te) = (2.0009470208228026 m, 4.0628436045232785 s). Tp = 4.496023809838518 s\n",
+      "Sea state 176/200. (Hs, Te) = (1.5779173712229868 m, 3.847821538178794 s). Tp = 4.2580761002960745 s\n",
+      "Sea state 177/200. (Hs, Te) = (1.2643248630801083 m, 3.814335921677443 s). Tp = 4.221020248845238 s\n",
+      "Sea state 178/200. (Hs, Te) = (0.8497384887288895 m, 3.660673074170486 s). Tp = 4.050973875337359 s\n",
+      "Sea state 179/200. (Hs, Te) = (0.5569801970656724 m, 3.580383590440513 s). Tp = 3.9621239304052653 s\n",
+      "Sea state 180/200. (Hs, Te) = (0.15728439930305368 m, 3.9432178300420313 s). Tp = 4.363643540576057 s\n",
+      "Sea state 181/200. (Hs, Te) = (1.1422392525115137 m, 24.57816097776294 s). Tp = 27.198683413518285 s\n",
+      "Sea state 182/200. (Hs, Te) = (4.420537323675632 m, 24.662533773594717 s). Tp = 27.292052033107773 s\n",
+      "Sea state 183/200. (Hs, Te) = (7.755814565466879 m, 23.99477020392714 s). Tp = 26.553091541193766 s\n",
+      "Sea state 184/200. (Hs, Te) = (11.148663000514297 m, 22.117310762471593 s). Tp = 24.475457457176223 s\n",
+      "Sea state 185/200. (Hs, Te) = (12.473228354145467 m, 20.601270499596303 s). Tp = 22.797777048564743 s\n",
+      "Sea state 186/200. (Hs, Te) = (12.819497160322692 m, 18.09058901457892 s). Tp = 20.019406814723713 s\n",
+      "Sea state 187/200. (Hs, Te) = (13.145047626413522 m, 17.4098903839333 s). Tp = 19.266132126202617 s\n",
+      "Sea state 188/200. (Hs, Te) = (10.547709475660533 m, 12.521271889157314 s). Tp = 13.856289343856886 s\n",
+      "Sea state 189/200. (Hs, Te) = (9.943350925680063 m, 11.66905560140366 s). Tp = 12.913209793217327 s\n",
+      "Sea state 190/200. (Hs, Te) = (7.5242441111748075 m, 9.07975143213084 s). Tp = 10.047834128004949 s\n",
+      "Sea state 191/200. (Hs, Te) = (6.760594320713308 m, 8.273354886983919 s). Tp = 9.155459618901123 s\n",
+      "Sea state 192/200. (Hs, Te) = (5.109171994744844 m, 6.763731790622878 s). Tp = 7.484880574813655 s\n",
+      "Sea state 193/200. (Hs, Te) = (3.949044029389487 m, 5.6211544147327634 s). Tp = 6.220481649670304 s\n",
+      "Sea state 194/200. (Hs, Te) = (2.8239259484743475 m, 4.63068616046699 s). Tp = 5.1244097139673705 s\n",
+      "Sea state 195/200. (Hs, Te) = (2.344941275016907 m, 4.180452084450019 s). Tp = 4.626171700690346 s\n",
+      "Sea state 196/200. (Hs, Te) = (1.3703724180063444 m, 3.5598449780265367 s). Tp = 3.939395492044637 s\n",
+      "Sea state 197/200. (Hs, Te) = (0.9714898696699685 m, 3.4362402988581957 s). Tp = 3.802612087453428 s\n",
+      "Sea state 198/200. (Hs, Te) = (0.858186544460902 m, 3.4532722006476217 s). Tp = 3.821459929857905 s\n",
+      "Sea state 199/200. (Hs, Te) = (0.5908442916930283 m, 3.5489601073269093 s). Tp = 3.9273500769127194 s\n",
+      "Sea state 200/200. (Hs, Te) = (0.09805058620711124 m, 3.879098338016793 s). Tp = 4.292687631148663 s\n"
      ]
     }
    ],
@@ -475,7 +475,7 @@
     "Here, we will look at the survival function and the 100-year return level. \n",
     "\n",
     "The value of the survival function at a given return level (e.g. 100-years) \n",
-    "may be calculated using the `return_year_value` function. This gives a 100-year wave of about 11.1 meters.  "
+    "may be calculated using the `return_year_value` function. This gives a 100-year wave of about 11 meters.  "
    ]
   },
   {
@@ -487,7 +487,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "100-year elevation: 10.542254436353211 m\n"
+      "100-year elevation: 10.978019989377701 m\n"
      ]
     }
    ],
@@ -514,7 +514,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x2351c2b0850>]"
+       "[<matplotlib.lines.Line2D at 0x23482d13190>]"
       ]
      },
      "execution_count": 8,
@@ -523,7 +523,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -563,7 +563,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -577,7 +577,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/mhkit/tests/wave/io/test_ndbc.py b/mhkit/tests/wave/io/test_ndbc.py
index aa5b86a96..a3c1ee25b 100644
--- a/mhkit/tests/wave/io/test_ndbc.py
+++ b/mhkit/tests/wave/io/test_ndbc.py
@@ -11,7 +11,6 @@
 import unittest
 import os
 
-
 testdir = dirname(abspath(__file__))
 datadir = normpath(join(testdir, "..", "..", "..", "..", "examples", "data", "wave"))
 
@@ -100,8 +99,27 @@ def tearDownClass(self):
     # Realtime data
     def test_ndbc_read_realtime_met(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "46097.txt"))
+        cd = np.array(
+            [
+                180,
+                12.0,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                1001.0,
+                6.1,
+                10.9,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+            ],
+        )
         expected_index0 = datetime(2019, 4, 2, 13, 50)
         self.assertSetEqual(set(data.columns), set(self.expected_columns_metRT))
+        np.testing.assert_equal(data.iloc[-1].astype(float).values, cd)
         self.assertEqual(data.index[0], expected_index0)
         self.assertEqual(data.shape, (6490, 14))
         self.assertEqual(units, self.expected_units_metRT)
@@ -110,8 +128,26 @@ def test_ndbc_read_realtime_met(self):
     def test_ndbnc_read_historical_met(self):
         # QC'd monthly data, Aug 2019
         data, units = wave.io.ndbc.read_file(join(datadir, "46097h201908qc.txt"))
+        cd = np.array(
+            [
+                160.0,
+                2.7,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                1014.9,
+                14.5,
+                13.4,
+                np.nan,
+                np.nan,
+                np.nan,
+            ]
+        )
         expected_index0 = datetime(2019, 8, 1, 0, 0)
         self.assertSetEqual(set(data.columns), set(self.expected_columns_metH))
+        np.testing.assert_equal(data.iloc[-1].astype(float).values, cd)
         self.assertEqual(data.index[0], expected_index0)
         self.assertEqual(data.shape, (4464, 13))
         self.assertEqual(units, self.expected_units_metH)
@@ -127,14 +163,34 @@ def test_ndbc_read_spectral(self):
     def test_ndbc_read_cwind_no_units(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "42a01c2003.txt"))
         self.assertEqual(data.shape, (4320, 5))
+        cd = np.array(
+            [
+                [168.0, 6.1, np.nan, np.nan, np.nan],
+                [153.0, 5.6, np.nan, np.nan, np.nan],
+                [149.0, 4.8, np.nan, np.nan, np.nan],
+                [147.0, 4.1, np.nan, np.nan, np.nan],
+                [151.0, 4.1, 169.0, np.nan, np.nan],
+            ]
+        )
+        np.testing.assert_equal(data.tail().values, cd)
         self.assertEqual(units, None)
 
     def test_ndbc_read_cwind_units(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "46002c2016.txt"))
         self.assertEqual(data.shape, (28468, 5))
-        self.assertEqual(units, wave.io.ndbc.parameter_units("cwind"))
+        cd = np.array(
+            [
+                [303.0, 6.2, np.nan, np.nan, np.nan],
+                [306.0, 7.8, np.nan, np.nan, np.nan],
+                [302.0, 7.6, np.nan, np.nan, np.nan],
+                [293.0, 6.4, np.nan, np.nan, np.nan],
+                [287.0, 6.3, 307.0, 9.7, 1819.0],
+            ]
+        )
+        np.testing.assert_equal(data.tail().values, cd)
 
     def test_ndbc_available_data(self):
+        # Can't test data values because datafiles are periodically updating
         data = wave.io.ndbc.available_data("swden", buoy_number="46029")
         cols = data.columns.tolist()
         exp_cols = ["id", "year", "filename"]
@@ -158,14 +214,18 @@ def test__ndbc_parse_filenames(self):
         self.assertListEqual(fnames, self.filenames)
 
     def test_ndbc_request_data(self):
+        # Can't test data values because datafiles are periodically updating
         filenames = pd.Series(self.filenames[0])
         ndbc_data = wave.io.ndbc.request_data("swden", filenames, to_pandas=False)
         self.assertTrue(xr.Dataset(self.swden).equals(ndbc_data["1996"]))
 
     def test_ndbc_request_data_from_dataframe(self):
+        # Can't test data values because datafiles are periodically updating
         filenames = pd.DataFrame(pd.Series(data=self.filenames[0]))
         ndbc_data = wave.io.ndbc.request_data("swden", filenames)
-        assert_frame_equal(self.swden, ndbc_data["1996"])
+        assert_frame_equal(
+            self.swden, ndbc_data["1996"], check_column_type=False, check_dtype=False
+        )
 
     def test_ndbc_request_data_filenames_length(self):
         with self.assertRaises(ValueError):
@@ -221,9 +281,10 @@ def test_ndbc_date_string_to_datetime(self):
     def test_ndbc_parameter_units(self):
         parameter = "swden"
         units = wave.io.ndbc.parameter_units(parameter)
-        self.assertEqual(units[parameter], "(m*m)/Hz")
+        self.assertEqual(units[parameter], "m^2/Hz")
 
     def test_ndbc_request_directional_data(self):
+        # Can't test data values because datafiles are periodically updating
         data = self.directional_data
         # correct 5 parameters
         self.assertEqual(len(data), 5)
@@ -236,12 +297,14 @@ def test_ndbc_request_directional_data(self):
         self.assertEqual(len(data.frequency), 47)
 
     def test_ndbc_create_spread_function(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spread = wave.io.ndbc.create_spread_function(self.directional_data, directions)
         self.assertEqual(spread.shape, (47, 180))
         self.assertEqual(spread.units, "1/Hz/deg")
 
     def test_ndbc_create_directional_spectrum(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spectrum = wave.io.ndbc.create_directional_spectrum(
             self.directional_data, directions
@@ -250,6 +313,7 @@ def test_ndbc_create_directional_spectrum(self):
         self.assertEqual(spectrum.units, "m^2/Hz/deg")
 
     def test_plot_directional_spectrum(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spectrum = wave.io.ndbc.create_spread_function(
             self.directional_data, directions
diff --git a/mhkit/wave/graphics.py b/mhkit/wave/graphics.py
index b54c18413..f6d0bfd8c 100644
--- a/mhkit/wave/graphics.py
+++ b/mhkit/wave/graphics.py
@@ -935,6 +935,9 @@ def plot_directional_spectrum(
 
     a, f = np.meshgrid(np.deg2rad(spectrum.direction), spectrum.frequency)
     _, ax = plt.subplots(subplot_kw=dict(projection="polar"))
+    # Set 0 degrees to be at the top, and positive angles to be clockwise
+    ax.set_theta_zero_location("N")
+    ax.set_theta_direction(-1)
     tmp = np.floor(np.min(spectrum.data) * 10) / 10
     color_level_min = tmp if (color_level_min is None) else color_level_min
     color_level_max = np.ceil(np.max(spectrum.data) * 10) / 10
diff --git a/mhkit/wave/io/ndbc.py b/mhkit/wave/io/ndbc.py
index 5fbad8ef8..113873e96 100644
--- a/mhkit/wave/io/ndbc.py
+++ b/mhkit/wave/io/ndbc.py
@@ -57,7 +57,13 @@ def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
     metadata: dict or None
         Dictionary with {column name: units} key value pairs when the NDBC file
         contains unit information, otherwise None is returned
+
+    Notes
+    -----
+    NDBC documentation of measurement descriptions and units can be found here:
+    https://www.ndbc.noaa.gov/faq/measdes.shtml
     """
+
     if not isinstance(file_name, str):
         raise TypeError(f"file_name must be of type str. Got: {type(file_name)}")
     if not isinstance(missing_values, list):
@@ -710,9 +716,9 @@ def parameter_units(parameter=""):
         }
     elif parameter == "cwind":
         units = {
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WSPD": "m/s",
-            "GDR": "degT",
+            "GDR": "degT",  # degree True North
             "GST": "m/s",
             "GTIME": "hhmm",
         }
@@ -764,10 +770,10 @@ def parameter_units(parameter=""):
             "WWH": "m",
             "WWP": "sec",
             "SwD": "-",
-            "WWD": "degT",
+            "WWD": "degT",  # degree True North
             "STEEPNESS": "-",
             "APD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
         }
     elif parameter == "srad":
         units = {
@@ -777,13 +783,13 @@ def parameter_units(parameter=""):
         }
     elif parameter == "stdmet":
         units = {
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WSPD": "m/s",
             "GST": "m/s",
             "WVHT": "m",
             "DPD": "sec",
             "APD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
             "PRES": "hPa",
             "ATMP": "degC",
             "WTMP": "degC",
@@ -797,11 +803,11 @@ def parameter_units(parameter=""):
             "PRES": "hPa",
             "PTIME": "hhmm",
             "WSPD": "m/s",
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WTIME": "hhmm",
         }
     elif parameter == "swden":
-        units = {"swden": "(m*m)/Hz"}
+        units = {"swden": "m^2/Hz"}
     elif parameter == "swdir":
         units = {"swdir": "deg"}
     elif parameter == "swdir2":
@@ -812,13 +818,13 @@ def parameter_units(parameter=""):
         units = {"swr2": ""}
     else:
         units = {
-            "swden": "(m*m)/Hz",
+            "swden": "m^2/Hz",
             "PRES": "hPa",
             "PTIME": "hhmm",
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WTIME": "hhmm",
             "DPD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
             "ATMP": "degC",
             "WTMP": "degC",
             "DEWP": "degC",
@@ -834,7 +840,7 @@ def parameter_units(parameter=""):
             "WWH": "m",
             "WWP": "sec",
             "SwD": "-",
-            "WWD": "degT",
+            "WWD": "degT",  # degree True North
             "STEEPNESS": "-",
             "APD": "sec",
             "RATE": "mm/h",
@@ -859,7 +865,7 @@ def parameter_units(parameter=""):
             "WSPD20": "m/s",
             "T": "-",
             "HEIGHT": "m",
-            "GDR": "degT",
+            "GDR": "degT",  # degree True North
             "GST": "m/s",
             "GTIME": "hhmm",
             "DEP01": "m",
@@ -1026,7 +1032,7 @@ def request_directional_data(buoy, year):
 
     data_dict["swden"].attrs = {
         "units": "m^2/Hz",
-        "long_name": "omnidirecational spectrum",
+        "long_name": "omnidirectional spectrum",
         "standard_name": "S",
         "description": "Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).",
     }
@@ -1062,7 +1068,7 @@ def request_directional_data(buoy, year):
     return xr.Dataset(data_dict)
 
 
-def _create_spectrum(data, frequencies, directions, name, units):
+def _create_spectrum_dataarray(data, frequencies, directions, name, units):
     """
     Create an xarray.DataArray for storing spectrum data with correct
     dimensions, coordinates, names, and units.
@@ -1166,16 +1172,18 @@ def create_spread_function(data, directions):
 
     r1 = data["swr1"].data.reshape(-1, 1)
     r2 = data["swr2"].data.reshape(-1, 1)
+    # a1 = degrees CW from N, according to NDBC documentation
     a1 = data["swdir"].data.reshape(-1, 1)
+    # a2 degrees CW from N, according to NDBC documentation
     a2 = data["swdir2"].data.reshape(-1, 1)
-    a = directions.reshape(1, -1)
+    a = directions.reshape(1, -1)  # degrees
     spread = (
         1
         / np.pi
         * (0.5 + r1 * np.cos(np.deg2rad(a - a1)) + r2 * np.cos(2 * np.deg2rad(a - a2)))
     )
-    spread = _create_spectrum(
-        spread, data.frequency.values, directions, name="Spread", units="1"
+    spread = _create_spectrum_dataarray(
+        np.rad2deg(spread), data.frequency.values, directions, name="Spread", units="1"
     )
     return spread
 
@@ -1209,9 +1217,9 @@ def create_directional_spectrum(data, directions):
     spread = create_spread_function(data, directions).values
     omnidirectional_spectrum = data["swden"].data.reshape(-1, 1)
     spectrum = omnidirectional_spectrum * spread
-    spectrum = _create_spectrum(
+    spectrum = _create_spectrum_dataarray(
         spectrum,
-        data.frequency.values,
+        data["frequency"].values,
         directions,
         name="Elevation variance",
         units="m^2",

From d777688371423bdda5a0afcf81a94d772b4e8292 Mon Sep 17 00:00:00 2001
From: Andrew Simms <andrew.simms@nlr.gov>
Date: Tue, 9 Jun 2026 14:10:45 -0600
Subject: [PATCH 4/9] Feature: Add support for pandas 3 (#443)

## Pandas 3 Changes

* Updated pandas dependency to allow versions >=2.2.2 without an upper
limit in both `environment-dev.yml` and `pyproject.toml`, enabling
support for pandas 3.x.
* Added a new function `replace_pandas_missing_values_with_nan` in
`mhkit/wave/io/ndbc.py` to replace missing values with `NaN` in a way
that is compatible with both pandas 2.x and 3.x.


## Test Updates

* Increased `test_get_buoy_metadata` latitude and longitude assertions
delta tolerance to allow for a small amount real world buoy drift.
* Fix deprecation in `test_request_parse_workflow_multiyear`
(`mhkit/tests/wave/io/test_cdip.py`) by using `"D"` instead of `"d"` in
the `floor` method. Pandas deprecated `d` in 3.0+
https://github.com/pandas-dev/pandas/pull/58998. period aliases are
here:

https://pandas.pydata.org/docs/user_guide/timeseries.html#period-aliases
---
 .github/workflows/main.yml       | 25 +++++---------------
 environment-dev.yml              |  6 +++--
 mhkit/tests/conftest.py          |  7 ++++++
 mhkit/tests/wave/io/test_cdip.py |  9 ++++----
 mhkit/tests/wave/io/test_ndbc.py |  9 ++++++--
 mhkit/wave/io/ndbc.py            | 39 ++++++++++++++++++++++++++++----
 pyproject.toml                   | 10 +++++---
 7 files changed, 70 insertions(+), 35 deletions(-)
 create mode 100644 mhkit/tests/conftest.py

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 48c6f83ec..a58f39277 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -93,7 +93,7 @@ jobs:
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
@@ -138,7 +138,7 @@ jobs:
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
@@ -181,7 +181,7 @@ jobs:
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
@@ -229,7 +229,7 @@ jobs:
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
@@ -291,25 +291,12 @@ jobs:
           name: data
           path: ~/.cache/mhkit
 
-      - name: Install system dependencies
-        if: runner.os == 'Linux'
-        run: |
-          # Update apt-get cache
-          sudo apt-get update
-          sudo apt-get install -y libhdf5-dev libnetcdf-dev
-
       - name: Update and install packages
         shell: bash
         run: |
           python -m pip install --upgrade pip wheel
           pip install -e ".[all,dev]"
 
-      - name: Reinstall h5py and netCDF4 with system libraries
-        if: runner.os == 'Linux'
-        shell: bash
-        run: |
-          pip install --force-reinstall --no-binary=:all: h5py netCDF4
-
       - name: Install setuptools for Python 3.12
         if: matrix.python-version == '3.12'
         shell: bash
@@ -368,7 +355,7 @@ jobs:
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
@@ -587,7 +574,7 @@ jobs:
       - name: Install notebook testing dependencies
         shell: bash -l {0}
         run: |
-          conda install -y pytest coverage coveralls nbval jupyter utm folium
+          conda install -y pytest coverage nbval jupyter utm folium
 
       - name: Install mhkit
         shell: bash -l {0}
diff --git a/environment-dev.yml b/environment-dev.yml
index 958ff6e2c..3f845390b 100644
--- a/environment-dev.yml
+++ b/environment-dev.yml
@@ -6,14 +6,16 @@ dependencies:
   - python>=3.10,<3.13
   - pip
   - numpy>=2.0.0
-  - pandas>=2.2.2,<3.0
+  - pandas>=2.2.2
+  # Provides pyarrow storage for the default string dtype in pandas 3.0+
+  - pyarrow>=16.0.0
   - scipy>=1.14.0
   - xarray>=2024.6.0
   - scikit-learn>=1.5.1
   - h5py>=3.11.0
   - h5pyd>=0.18.0
   - netCDF4>=1.6.5
-  - hdf5>=1.14.3,<1.14.5.0a0
+  - hdf5>=1.14.3
   - statsmodels>=0.14.2
   - requests
   - beautifulsoup4
diff --git a/mhkit/tests/conftest.py b/mhkit/tests/conftest.py
new file mode 100644
index 000000000..1f49e55a4
--- /dev/null
+++ b/mhkit/tests/conftest.py
@@ -0,0 +1,7 @@
+"""Shared pytest configuration for the MHKiT test suite."""
+
+import matplotlib
+
+# Use the non-interactive Agg backend so figure/animation tests run headlessly
+# on every OS (Windows otherwise picks TkAgg and fails without Tcl/Tk).
+matplotlib.use("Agg")
diff --git a/mhkit/tests/wave/io/test_cdip.py b/mhkit/tests/wave/io/test_cdip.py
index 17d1bc2ad..dd5a798a5 100644
--- a/mhkit/tests/wave/io/test_cdip.py
+++ b/mhkit/tests/wave/io/test_cdip.py
@@ -7,7 +7,6 @@
 import pytz
 import os
 
-
 testdir = dirname(abspath(__file__))
 datadir = normpath(join(testdir, "..", "..", "..", "..", "examples", "data", "wave"))
 
@@ -130,18 +129,18 @@ def test_request_parse_workflow_multiyear(self):
         expected_index_final = datetime(year2, 12, 31)
 
         wave1D = data["data"]["wave"]
-        self.assertEqual(wave1D.index[0].floor("d").to_pydatetime(), expected_index0)
+        self.assertEqual(wave1D.index[0].floor("D").to_pydatetime(), expected_index0)
 
         self.assertEqual(
-            wave1D.index[-1].floor("d").to_pydatetime(), expected_index_final
+            wave1D.index[-1].floor("D").to_pydatetime(), expected_index_final
         )
 
         for key, wave2D in data["data"]["wave2D"].items():
             self.assertEqual(
-                wave2D.index[0].floor("d").to_pydatetime(), expected_index0
+                wave2D.index[0].floor("D").to_pydatetime(), expected_index0
             )
             self.assertEqual(
-                wave2D.index[-1].floor("d").to_pydatetime(), expected_index_final
+                wave2D.index[-1].floor("D").to_pydatetime(), expected_index_final
             )
 
     def test_plot_boxplot(self):
diff --git a/mhkit/tests/wave/io/test_ndbc.py b/mhkit/tests/wave/io/test_ndbc.py
index a3c1ee25b..bee861732 100644
--- a/mhkit/tests/wave/io/test_ndbc.py
+++ b/mhkit/tests/wave/io/test_ndbc.py
@@ -357,8 +357,13 @@ def test_get_buoy_metadata(self):
             metadata["provider"], "Owned and maintained by National Data Buoy Center"
         )
         self.assertEqual(metadata["type"], "3-meter foam buoy w/ seal cage")
-        self.assertAlmostEqual(float(metadata["lat"]), 36.785)
-        self.assertAlmostEqual(float(metadata["lon"]), 122.396)
+        # NDBC 46042 is a deployed buoy that drifts within its watch
+        # circle, so the NDBC output position can drift over time (observed
+        # lat 36.785 -> 36.787, lon 122.396 -> 122.408). Use a loose tolerance
+        # that tracks the buoy's nominal location without failing on real
+        # movement, while still catching large parsing errors.
+        self.assertAlmostEqual(float(metadata["lat"]), 36.785, delta=0.05)
+        self.assertAlmostEqual(float(metadata["lon"]), 122.396, delta=0.05)
         self.assertEqual(metadata["Site elevation"], "sea level")
 
     def test_get_buoy_metadata_invalid_station(self):
diff --git a/mhkit/wave/io/ndbc.py b/mhkit/wave/io/ndbc.py
index 113873e96..bbcc29d89 100644
--- a/mhkit/wave/io/ndbc.py
+++ b/mhkit/wave/io/ndbc.py
@@ -19,8 +19,40 @@
     convert_nested_dict_and_pandas,
 )
 
-# Set pandas option to opt-in to future behavior
-pd.set_option("future.no_silent_downcasting", True)
+
+def replace_pandas_missing_values_with_nan(data, missing_values):
+    """
+    Replace missing values with NaN without silently downcasting dtypes.
+
+    Parameters
+    ------------
+    data: pandas DataFrame
+        Data in which to replace missing values
+
+    missing_values: list of values
+        List of values that denote missing data
+
+    Returns
+    ---------
+    data: pandas DataFrame
+        Data with missing values replaced by NaN and object columns converted
+        to their best-fit dtypes
+
+    Notes
+    -----
+    pandas versions above 2.x do not silently downcast in ``replace`` and
+    dropped the ``future.no_silent_downcasting`` option. On pandas 2.x the same
+    forward-looking behavior is opted into so the result is identical across
+    supported pandas versions and no deprecation warning is emitted.
+    ``infer_objects`` then converts the resulting object columns explicitly.
+    """
+    pandas_major = int(pd.__version__.split(".")[0])
+    if pandas_major <= 2:
+        with pd.option_context("future.no_silent_downcasting", True):
+            data = data.replace(missing_values, np.nan)
+    else:
+        data = data.replace(missing_values, np.nan)
+    return data.infer_objects()
 
 
 def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
@@ -153,8 +185,7 @@ def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
         data.columns = data.columns
 
     # Replace indicated missing values with nan
-    data = data.replace(missing_values, np.nan)
-    data = data.infer_objects(copy=False)
+    data = replace_pandas_missing_values_with_nan(data, missing_values)
 
     if not to_pandas:
         data = convert_to_dataset(data)
diff --git a/pyproject.toml b/pyproject.toml
index d30cf3751..c9805d480 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,11 +25,16 @@ dependencies = [
     # scenes. xarray, netcdf4, and h5 dependencies should all be synced to avoid
     # compatibility issues with individual modules.
     "xarray>=2024.6.0",
-    "netCDF4>=1.7.1.post1",
+    "netCDF4>=1.6.5",
     "h5py>=3.11.0",
     "h5pyd>=0.18.0",
     "numpy>=2.0.0",
-    "pandas>=2.2.2,<3.0",
+    "pandas>=2.2.2",
+    # pandas 3.0+ uses a new string dtype by default and stores it using pyarrow
+    # when pyarrow is installed, otherwise a more limited numpy fallback. pandas
+    # keeps pyarrow optional, so we require it here to always get the reliable
+    # pyarrow storage. pyarrow 16.0.0 is the first version that supports numpy 2.
+    "pyarrow>=16.0.0",
     "scipy>=1.14.0",
     "matplotlib>=3.9.1",
     "pecos>=0.3.0",
@@ -91,7 +96,6 @@ dev = [
     "pytest-cov",
     "pre-commit",
     "coverage",
-    "coveralls",
     "black",
 ]
 

From b962f4c32aae660959957049d391d74d864c8b56 Mon Sep 17 00:00:00 2001
From: Andrew Simms <andrew.simms@nlr.gov>
Date: Wed, 10 Jun 2026 12:27:07 -0600
Subject: [PATCH 5/9] Feature: Add python 3.13 support (#445)

This PR verifies MHKiT-Python supports Python 3.13.

No python code changes were required.

README was updated to include Python 3.13

Actions were updated to include 3.13 in test matrices and for notebook
tests (single version)

Action versions for setup-miniconda and download-artifact were update
---
 .github/workflows/main.yml             | 38 +++++++++++++-------------
 .github/workflows/test-wheel-build.yml |  2 +-
 README.md                              |  2 +-
 environment-dev.yml                    |  2 +-
 4 files changed, 22 insertions(+), 22 deletions(-)

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index a58f39277..7ca82b44d 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -1,4 +1,4 @@
-name: Py 3.10, 3.11, 3.12 | Windows Mac Linux
+name: Py 3.10, 3.11, 3.12, 3.13 | Windows Mac Linux
 
 on:
   pull_request:
@@ -79,7 +79,7 @@ jobs:
         uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -124,7 +124,7 @@ jobs:
         uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -167,7 +167,7 @@ jobs:
         uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -207,7 +207,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     env:
       PYTHON_VER: ${{ matrix.python-version }}
 
@@ -215,7 +215,7 @@ jobs:
       - uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -237,7 +237,7 @@ jobs:
           pip install -e ".[all,dev]" --no-deps
 
       - name: Download data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
@@ -265,7 +265,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
       - name: Set up Python ${{ matrix.python-version }}
@@ -286,7 +286,7 @@ jobs:
         uses: actions/checkout@v6
 
       - name: Download data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
@@ -335,13 +335,13 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
       - uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -363,13 +363,13 @@ jobs:
           pip install -e ".[all,dev]" --no-deps
 
       - name: Download Wave Hindcast data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit/wave-hindcast
 
       - name: Download Wind Hindcast data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit/wind-hindcast
@@ -460,7 +460,7 @@ jobs:
       matrix:
         module:
           [wave, tidal, river, dolfyn, power, loads, mooring, acoustics, utils]
-        python-version: ['3.12']
+        python-version: ['3.13']
 
     steps:
       - uses: actions/checkout@v6
@@ -471,7 +471,7 @@ jobs:
           python-version: ${{ matrix.python-version }}
 
       - name: Download non-hindcast data
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
@@ -560,7 +560,7 @@ jobs:
         uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
           miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
           auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
@@ -582,21 +582,21 @@ jobs:
           pip install -e ".[all,dev]" --no-deps
 
       - name: Download non-hindcast data
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
 
       - name: Download Wave Hindcast data (if available)
         if: (needs.check-changes.outputs.should-run-hindcast == 'true')
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit/wave-hindcast
 
       - name: Download Wind Hindcast data (if available)
         if: (needs.check-changes.outputs.should-run-hindcast == 'true')
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit/wind-hindcast
diff --git a/.github/workflows/test-wheel-build.yml b/.github/workflows/test-wheel-build.yml
index dd3ed5977..46ecbbe82 100644
--- a/.github/workflows/test-wheel-build.yml
+++ b/.github/workflows/test-wheel-build.yml
@@ -16,7 +16,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
       - uses: actions/checkout@v6
diff --git a/README.md b/README.md
index fcd51018c..ebe2960ab 100644
--- a/README.md
+++ b/README.md
@@ -32,7 +32,7 @@ See the [MHKiT documentation](https://mhkit-software.github.io/MHKiT) for more i
 
 ## Installation
 
-[MHKiT-Python](https://github.com/MHKiT-Software/MHKiT-Python) requires [Python (3.10-3.12)](https://www.python.org/).
+[MHKiT-Python](https://github.com/MHKiT-Software/MHKiT-Python) requires [Python (3.10-3.13)](https://www.python.org/).
 
 See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.
 
diff --git a/environment-dev.yml b/environment-dev.yml
index 3f845390b..e624a7286 100644
--- a/environment-dev.yml
+++ b/environment-dev.yml
@@ -3,7 +3,7 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python>=3.10,<3.13
+  - python>=3.10,<3.14
   - pip
   - numpy>=2.0.0
   - pandas>=2.2.2

From 17ba78d5b9385faff7d2e5c17e3a01c39e04f4b4 Mon Sep 17 00:00:00 2001
From: Emily Browning <63879572+browniea@users.noreply.github.com>
Date: Mon, 29 Jun 2026 12:12:33 -0800
Subject: [PATCH 6/9] Updated ADCP examples  (#448)

Adding visualizations to match the [MHKiT_MATLAB ADCP
example](https://github.com/MHKiT-Software/MHKiT-MATLAB/blob/master/examples/acoustics_example.mlx)
and addressing several issues:

Qhull Error https://github.com/MHKiT-Software/MHKiT-Python/issues/444

D3D coordinate systems
https://github.com/MHKiT-Software/MHKiT-Python/issues/442
---
 examples/ADCP_Delft3D_TRTS_example.ipynb |  587 +-
 examples/adcp_example.ipynb              | 9557 ++++++++++++----------
 mhkit/river/io/d3d.py                    |   17 +-
 3 files changed, 5775 insertions(+), 4386 deletions(-)

diff --git a/examples/ADCP_Delft3D_TRTS_example.ipynb b/examples/ADCP_Delft3D_TRTS_example.ipynb
index 6347594ff..f9b2f7238 100644
--- a/examples/ADCP_Delft3D_TRTS_example.ipynb
+++ b/examples/ADCP_Delft3D_TRTS_example.ipynb
@@ -104,76 +104,28 @@
        " */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, white)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
-       "  );\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
        "}\n",
        "\n",
-       "html[theme=\"dark\"],\n",
-       "html[data-theme=\"dark\"],\n",
-       "body[data-theme=\"dark\"],\n",
+       "html[theme=dark],\n",
+       "html[data-theme=dark],\n",
+       "body[data-theme=dark],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, #111111)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
-       "  );\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
@@ -224,12 +176,10 @@
        ".xr-section-item input {\n",
        "  display: inline-block;\n",
        "  opacity: 0;\n",
-       "  height: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
-       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -238,7 +188,7 @@
        "}\n",
        "\n",
        ".xr-section-item input:focus + label {\n",
-       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label:hover {\n",
@@ -262,7 +212,7 @@
        "\n",
        ".xr-section-summary-in + label:before {\n",
        "  display: inline-block;\n",
-       "  content: \"►\";\n",
+       "  content: '►';\n",
        "  font-size: 11px;\n",
        "  width: 15px;\n",
        "  text-align: center;\n",
@@ -273,7 +223,7 @@
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label:before {\n",
-       "  content: \"▼\";\n",
+       "  content: '▼';\n",
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label > span {\n",
@@ -345,15 +295,15 @@
        "}\n",
        "\n",
        ".xr-dim-list:before {\n",
-       "  content: \"(\";\n",
+       "  content: '(';\n",
        "}\n",
        "\n",
        ".xr-dim-list:after {\n",
-       "  content: \")\";\n",
+       "  content: ')';\n",
        "}\n",
        "\n",
        ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: \",\";\n",
+       "  content: ',';\n",
        "  padding-right: 5px;\n",
        "}\n",
        "\n",
@@ -370,9 +320,7 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
-       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
-       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -383,7 +331,6 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
-       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -433,15 +380,8 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  border-top: 2px dotted var(--xr-background-color);\n",
-       "  padding-bottom: 20px !important;\n",
-       "  padding-top: 10px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in + label,\n",
-       ".xr-var-data-in + label,\n",
-       ".xr-index-data-in + label {\n",
-       "  padding: 0 1px;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -454,12 +394,6 @@
        "  float: right;\n",
        "}\n",
        "\n",
-       ".xr-var-data > pre,\n",
-       ".xr-index-data > pre,\n",
-       ".xr-var-data > table > tbody > tr {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -519,25 +453,17 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
-       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
-       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
-       "  color: var(--xr-font-color0);\n",
-       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
-       "  stroke-width: 0.8px;\n",
-       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 4MB\n",
        "Dimensions:              (time: 1227, time_gps: 1227, range: 47, beam: 4,\n",
        "                          dir: 4, x1: 4, x2: 4, earth: 3, inst: 3)\n",
        "Coordinates:\n",
        "  * time                 (time) datetime64[ns] 10kB 2010-08-10T14:28:15.55999...\n",
        "  * time_gps             (time_gps) datetime64[ns] 10kB 2010-08-10T22:28:17.2...\n",
-       "  * range                (range) float32 188B 0.57 0.82 1.07 ... 11.82 12.07\n",
+       "  * range                (range) float64 376B 0.57 0.82 1.07 ... 11.82 12.07\n",
        "  * beam                 (beam) int32 16B 1 2 3 4\n",
        "  * dir                  (dir) &lt;U3 48B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27; &#x27;err&#x27;\n",
-       "  * x1                   (x1) int64 32B 1 2 3 4\n",
-       "  * x2                   (x2) int64 32B 1 2 3 4\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
        "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
        "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
        "Data variables: (12/36)\n",
@@ -552,37 +478,32 @@
        "    speed_over_grnd_gps  (time_gps) float32 5kB 0.03549 0.03395 ... 0.1672\n",
        "    dir_over_grnd_gps    (time_gps) float32 5kB 115.5 94.08 ... 160.5 182.1\n",
        "    hdwtime_gps          (time_gps) datetime64[ns] 10kB 2010-08-10T14:28:15.5...\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.462 -1.462 0.0 ... -1.034 -1.034\n",
-       "    orientmat            (earth, inst, time) float32 44kB -0.9037 ... 1.0\n",
-       "Attributes: (12/39)\n",
-       "    firmware_ver:             10.16\n",
+       "    beam2inst_orientmat  (x1, x2) float64 128B 1.462 -1.462 ... -1.034 -1.034\n",
+       "    orientmat            (earth, inst, time) float64 88kB -0.9037 ... 1.0\n",
+       "Attributes: (12/38)\n",
        "    inst_make:                TRDI\n",
        "    inst_type:                ADCP\n",
        "    rotate_vars:              [&#x27;vel&#x27;, &#x27;vel_bt&#x27;]\n",
        "    has_imu:                  0\n",
+       "    prog_ver:                 10.16\n",
        "    inst_model:               Rio Grande\n",
        "    ...                       ...\n",
+       "    false_target_threshold:   50\n",
+       "    transmit_lag_m:           0.08\n",
        "    bandwidth:                0\n",
-       "    power_level:              128\n",
-       "    serialnum:                134877318\n",
-       "    source_program:           WINRIVER\n",
-       "    range_offset:             0.07\n",
-       "    fs:                       1.92</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-578127cd-b7cf-4d63-91f5-72d5d43d2429' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-578127cd-b7cf-4d63-91f5-72d5d43d2429' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1227</li><li><span class='xr-has-index'>time_gps</span>: 1227</li><li><span class='xr-has-index'>range</span>: 47</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3b3ff946-efbb-4554-ad63-3bd08aa87899' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b3ff946-efbb-4554-ad63-3bd08aa87899' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T14:28:15.559999942 .....</div><input id='attrs-6f699fd2-9283-4c36-a4f9-8affda9178d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f699fd2-9283-4c36-a4f9-8affda9178d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-748cabd6-4c0c-476c-a0ea-946e8174f704' class='xr-var-data-in' type='checkbox'><label for='data-748cabd6-4c0c-476c-a0ea-946e8174f704' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T14:28:15.559999942&#x27;, &#x27;2010-08-10T14:28:16.319999933&#x27;,\n",
+       "    sourceprog:               WINRIVER\n",
+       "    fs:                       1.92\n",
+       "    vel_gps_corrected:        0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6d7b2d91-33af-4019-b661-8abc3a85c065' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6d7b2d91-33af-4019-b661-8abc3a85c065' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1227</li><li><span class='xr-has-index'>time_gps</span>: 1227</li><li><span class='xr-has-index'>range</span>: 47</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a8aaf9c5-c9bc-408a-9759-254afd5048a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a8aaf9c5-c9bc-408a-9759-254afd5048a5' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T14:28:15.559999942 .....</div><input id='attrs-b89d9adb-1116-4bb4-b035-5c1b9291085c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b89d9adb-1116-4bb4-b035-5c1b9291085c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3383911-d7fe-442e-976a-87aba1b162b2' class='xr-var-data-in' type='checkbox'><label for='data-f3383911-d7fe-442e-976a-87aba1b162b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T14:28:15.559999942&#x27;, &#x27;2010-08-10T14:28:16.319999933&#x27;,\n",
        "       &#x27;2010-08-10T14:28:17.069999933&#x27;, ..., &#x27;2010-08-10T14:39:59.190000057&#x27;,\n",
        "       &#x27;2010-08-10T14:39:59.910000085&#x27;, &#x27;2010-08-10T14:40:00.630000114&#x27;],\n",
-       "      shape=(1227,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T22:28:17.200000047 .....</div><input id='attrs-645c471c-2cf9-4022-9054-79bc12763726' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-645c471c-2cf9-4022-9054-79bc12763726' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d99364c0-18c3-44cb-b839-8615ddedb585' class='xr-var-data-in' type='checkbox'><label for='data-d99364c0-18c3-44cb-b839-8615ddedb585' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time gps</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T22:28:17.200000047&#x27;, &#x27;2010-08-10T22:28:18.000000000&#x27;,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T22:28:17.200000047 .....</div><input id='attrs-2d596544-87b5-4104-95e8-df26dec1ce71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d596544-87b5-4104-95e8-df26dec1ce71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315278fa-15d7-45f1-b87a-cfbc7ffb5659' class='xr-var-data-in' type='checkbox'><label for='data-315278fa-15d7-45f1-b87a-cfbc7ffb5659' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T22:28:17.200000047&#x27;, &#x27;2010-08-10T22:28:18.000000000&#x27;,\n",
        "       &#x27;2010-08-10T22:28:18.599999904&#x27;, ..., &#x27;2010-08-10T22:40:00.799999952&#x27;,\n",
        "       &#x27;2010-08-10T22:40:01.400000095&#x27;, &#x27;2010-08-10T22:40:02.200000047&#x27;],\n",
-       "      shape=(1227,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.57 0.82 1.07 ... 11.82 12.07</div><input id='attrs-9dc6856a-64b6-432c-a221-71c0d9b2f0da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dc6856a-64b6-432c-a221-71c0d9b2f0da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-922d5d6d-b4d9-4676-80c5-08c0e1695166' class='xr-var-data-in' type='checkbox'><label for='data-922d5d6d-b4d9-4676-80c5-08c0e1695166' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.57,  0.82,  1.07,  1.32,  1.57,  1.82,  2.07,  2.32,  2.57,  2.82,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.57 0.82 1.07 ... 11.82 12.07</div><input id='attrs-63297499-24f6-439c-8ef7-45d1f9f862be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63297499-24f6-439c-8ef7-45d1f9f862be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e247d07e-b99d-4e7d-ba6f-7335b22e7a79' class='xr-var-data-in' type='checkbox'><label for='data-e247d07e-b99d-4e7d-ba6f-7335b22e7a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.57,  0.82,  1.07,  1.32,  1.57,  1.82,  2.07,  2.32,  2.57,  2.82,\n",
        "        3.07,  3.32,  3.57,  3.82,  4.07,  4.32,  4.57,  4.82,  5.07,  5.32,\n",
        "        5.57,  5.82,  6.07,  6.32,  6.57,  6.82,  7.07,  7.32,  7.57,  7.82,\n",
        "        8.07,  8.32,  8.57,  8.82,  9.07,  9.32,  9.57,  9.82, 10.07, 10.32,\n",
-       "       10.57, 10.82, 11.07, 11.32, 11.57, 11.82, 12.07], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-599765d6-77ae-4a61-a905-2324ac5d1f78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-599765d6-77ae-4a61-a905-2324ac5d1f78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-964ea246-25bb-44f0-901d-04ffbd82c4ac' class='xr-var-data-in' type='checkbox'><label for='data-964ea246-25bb-44f0-901d-04ffbd82c4ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27; &#x27;err&#x27;</div><input id='attrs-64de5b59-19c4-4851-b272-5ff3de8aed9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64de5b59-19c4-4851-b272-5ff3de8aed9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbbe2bd1-daae-44ea-94e2-d537e74eb20c' class='xr-var-data-in' type='checkbox'><label for='data-dbbe2bd1-daae-44ea-94e2-d537e74eb20c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>ship</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;, &#x27;err&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-b205455b-7133-47f7-85fe-ecca371d709c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b205455b-7133-47f7-85fe-ecca371d709c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9330cc18-117d-49b7-ba6a-d3a71969f4c0' class='xr-var-data-in' type='checkbox'><label for='data-9330cc18-117d-49b7-ba6a-d3a71969f4c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-1066768f-a31d-4528-a7e9-97f8496ef754' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1066768f-a31d-4528-a7e9-97f8496ef754' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56d38387-e9d7-4749-95f4-5a160110d81c' class='xr-var-data-in' type='checkbox'><label for='data-56d38387-e9d7-4749-95f4-5a160110d81c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-38d98e31-61ae-4207-b70d-6fabcb89b255' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38d98e31-61ae-4207-b70d-6fabcb89b255' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f82843d4-052d-4df7-a07a-220c972fe11e' class='xr-var-data-in' type='checkbox'><label for='data-f82843d4-052d-4df7-a07a-220c972fe11e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-c44f7188-bc78-4278-bf17-a7f81e65bea1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c44f7188-bc78-4278-bf17-a7f81e65bea1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a3d2fc-1128-4c10-a5ed-0e3c2fa7708f' class='xr-var-data-in' type='checkbox'><label for='data-04a3d2fc-1128-4c10-a5ed-0e3c2fa7708f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-86463766-f297-4ebf-8c1a-1f5100ba6d0f' class='xr-section-summary-in' type='checkbox'  ><label for='section-86463766-f297-4ebf-8c1a-1f5100ba6d0f' class='xr-section-summary' >Data variables: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>number</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.652e+03 3.653e+03 ... 4.904e+03</div><input id='attrs-97ddec0b-186d-4a85-8f26-ed11197cb843' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97ddec0b-186d-4a85-8f26-ed11197cb843' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c33d8902-2e4c-47f6-ba42-1eee9bc54c58' class='xr-var-data-in' type='checkbox'><label for='data-c33d8902-2e4c-47f6-ba42-1eee9bc54c58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([3652., 3653., 3654., ..., 4902., 4903., 4904.], shape=(1227,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>builtin_test_fail</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-b2e55464-b80c-4679-99e7-12c356690b22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2e55464-b80c-4679-99e7-12c356690b22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82a21a40-e3bd-4842-95ae-6bc74eadf327' class='xr-var-data-in' type='checkbox'><label for='data-82a21a40-e3bd-4842-95ae-6bc74eadf327' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Built-In Test Failures</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.466e+03 1.466e+03 ... 1.466e+03</div><input id='attrs-6fbd405f-7f47-43c5-9751-03b9666ef931' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fbd405f-7f47-43c5-9751-03b9666ef931' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0d08dc1-0342-42b5-ae7b-e49152c3710e' class='xr-var-data-in' type='checkbox'><label for='data-d0d08dc1-0342-42b5-ae7b-e49152c3710e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1466., 1466., 1466., ..., 1466., 1466., 1466.],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ba550007-9240-4057-9406-e444918287cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba550007-9240-4057-9406-e444918287cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69d6ab2b-06a0-40f2-b269-1b7ceeae35e2' class='xr-var-data-in' type='checkbox'><label for='data-69d6ab2b-06a0-40f2-b269-1b7ceeae35e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.1 -0.09 -0.21 ... 0.2 0.07 0.56</div><input id='attrs-bd690552-6634-4c77-9cdf-23167bb2efec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd690552-6634-4c77-9cdf-23167bb2efec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47d52669-fed0-4c63-8a27-466ae8f6b301' class='xr-var-data-in' type='checkbox'><label for='data-47d52669-fed0-4c63-8a27-466ae8f6b301' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.1 , -0.09, -0.21, ...,  0.2 ,  0.07,  0.56],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.33 3.32 3.33 ... 2.24 2.65 2.33</div><input id='attrs-8d2385a3-41bf-472e-a0c0-862100cf2c5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d2385a3-41bf-472e-a0c0-862100cf2c5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57ca0aa5-f45f-474c-bf3c-8490d40f796a' class='xr-var-data-in' type='checkbox'><label for='data-57ca0aa5-f45f-474c-bf3c-8490d40f796a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([3.33, 3.32, 3.33, ..., 2.24, 2.65, 2.33],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>154.6 154.5 155.0 ... 145.8 147.8</div><input id='attrs-8dd0c484-23c0-42ae-beeb-06c6c937fcb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8dd0c484-23c0-42ae-beeb-06c6c937fcb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-059aac28-3f57-48de-9c0b-5d09ab084401' class='xr-var-data-in' type='checkbox'><label for='data-059aac28-3f57-48de-9c0b-5d09ab084401' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([154.65, 154.49, 155.01, ..., 146.32, 145.75, 147.81],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>15.2 15.25 15.23 ... 15.21 15.22</div><input id='attrs-4617d5f5-9ccd-4b39-b273-6cc0df68d8da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4617d5f5-9ccd-4b39-b273-6cc0df68d8da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9883e43f-bc11-446d-b45c-20456e967c8e' class='xr-var-data-in' type='checkbox'><label for='data-9883e43f-bc11-446d-b45c-20456e967c8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([15.2 , 15.25, 15.23, ..., 15.2 , 15.21, 15.22],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-a4e2f45e-f579-462c-a1f2-3f6be538ec04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4e2f45e-f579-462c-a1f2-3f6be538ec04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a0f8759-a484-4206-ad9c-82731899e954' class='xr-var-data-in' type='checkbox'><label for='data-0a0f8759-a484-4206-ad9c-82731899e954' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>psu</dd><dt><span>long_name :</span></dt><dd>Salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_preping_wait</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-11cad2d2-671a-460b-8aee-db407f9afb43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11cad2d2-671a-460b-8aee-db407f9afb43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1bea08cd-80ec-41aa-8fbb-ffc75fc3ee7a' class='xr-var-data-in' type='checkbox'><label for='data-1bea08cd-80ec-41aa-8fbb-ffc75fc3ee7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Minimum Pre-Ping Wait Time Between Measurements</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ab02f46a-4482-40b1-a718-e0c75a36162d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab02f46a-4482-40b1-a718-e0c75a36162d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10a46c39-a816-438b-b58a-90309262c89a' class='xr-var-data-in' type='checkbox'><label for='data-10a46c39-a816-438b-b58a-90309262c89a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-f916e17c-0566-4775-9823-bdd787fb8b89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f916e17c-0566-4775-9823-bdd787fb8b89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f940130b-baa8-4ded-9871-a4aab5c8d1c7' class='xr-var-data-in' type='checkbox'><label for='data-f940130b-baa8-4ded-9871-a4aab5c8d1c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-405e2f6f-7b11-4a08-8537-8ab17ece385f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-405e2f6f-7b11-4a08-8537-8ab17ece385f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-180d019c-0ce7-4470-b3ab-ef7253e9a9e6' class='xr-var-data-in' type='checkbox'><label for='data-180d019c-0ce7-4470-b3ab-ef7253e9a9e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-41000da5-77e5-4aa9-82a2-198f45e78775' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41000da5-77e5-4aa9-82a2-198f45e78775' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-149a6432-df9b-40bc-bef6-f041e0bf878b' class='xr-var-data-in' type='checkbox'><label for='data-149a6432-df9b-40bc-bef6-f041e0bf878b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-bf175105-ef42-47b5-b53c-6f66438aeaea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf175105-ef42-47b5-b53c-6f66438aeaea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aac5104a-4b37-4268-84e8-52c7470d4b73' class='xr-var-data-in' type='checkbox'><label for='data-aac5104a-4b37-4268-84e8-52c7470d4b73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.057 -0.192 0.121 ... nan nan nan</div><input id='attrs-350671e0-1533-40cb-a5f3-8187f36b2c54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-350671e0-1533-40cb-a5f3-8187f36b2c54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4f334ad-743e-4fb3-80d3-3d9928096c82' class='xr-var-data-in' type='checkbox'><label for='data-e4f334ad-743e-4fb3-80d3-3d9928096c82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.057, -0.192,  0.121, ..., -0.01 , -0.629,  0.134],\n",
+       "       10.57, 10.82, 11.07, 11.32, 11.57, 11.82, 12.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c36e972d-5a02-49c0-b273-e3a8c00afec6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c36e972d-5a02-49c0-b273-e3a8c00afec6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f29fa75-a2f0-4cfc-ac97-3b52bf2ca12f' class='xr-var-data-in' type='checkbox'><label for='data-3f29fa75-a2f0-4cfc-ac97-3b52bf2ca12f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27; &#x27;err&#x27;</div><input id='attrs-aac781bb-f50f-4adc-ad84-150e31da3c7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aac781bb-f50f-4adc-ad84-150e31da3c7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38650e7d-abb9-4800-adcc-fa2a8ac73b87' class='xr-var-data-in' type='checkbox'><label for='data-38650e7d-abb9-4800-adcc-fa2a8ac73b87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>ship</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;, &#x27;err&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-286fb5f3-f0af-4d93-8205-7318c6458ec6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-286fb5f3-f0af-4d93-8205-7318c6458ec6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1ed3e68-0dd6-4d02-b1f1-a4980d2b5633' class='xr-var-data-in' type='checkbox'><label for='data-c1ed3e68-0dd6-4d02-b1f1-a4980d2b5633' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3879ad80-c86f-4594-b8a5-cb40d5a4b63f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3879ad80-c86f-4594-b8a5-cb40d5a4b63f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcd0881f-3ef4-4a17-a8e5-5f4d55d08393' class='xr-var-data-in' type='checkbox'><label for='data-bcd0881f-3ef4-4a17-a8e5-5f4d55d08393' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-0a8f6074-d3ef-499b-a88c-48004b7be006' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a8f6074-d3ef-499b-a88c-48004b7be006' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db51c26a-216c-4e9a-beb0-a1c7fe9974b8' class='xr-var-data-in' type='checkbox'><label for='data-db51c26a-216c-4e9a-beb0-a1c7fe9974b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-30e37be3-d64a-4a85-856b-03011399358d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30e37be3-d64a-4a85-856b-03011399358d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44bd9ef8-0eb2-4fc4-bd96-847b1f2200f9' class='xr-var-data-in' type='checkbox'><label for='data-44bd9ef8-0eb2-4fc4-bd96-847b1f2200f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-339cf7dd-d3c2-41ab-8025-8f1330a66b10' class='xr-section-summary-in' type='checkbox'  ><label for='section-339cf7dd-d3c2-41ab-8025-8f1330a66b10' class='xr-section-summary' >Data variables: <span>(36)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>number</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.652e+03 3.653e+03 ... 4.904e+03</div><input id='attrs-14f840b5-b23d-470f-a7c5-133072fec5ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14f840b5-b23d-470f-a7c5-133072fec5ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d77378e2-4e68-48bd-a5eb-18df53548120' class='xr-var-data-in' type='checkbox'><label for='data-d77378e2-4e68-48bd-a5eb-18df53548120' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([3652., 3653., 3654., ..., 4902., 4903., 4904.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>builtin_test_fail</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-c1e28a29-1ff6-4989-8e03-7bc31805f6f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1e28a29-1ff6-4989-8e03-7bc31805f6f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7e71b35-4eee-43e7-9b46-0fe5a300752d' class='xr-var-data-in' type='checkbox'><label for='data-d7e71b35-4eee-43e7-9b46-0fe5a300752d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Built-In Test Failures</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.466e+03 1.466e+03 ... 1.466e+03</div><input id='attrs-27216add-7b11-48b8-9b3b-abf2f3624540' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27216add-7b11-48b8-9b3b-abf2f3624540' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32f1a17a-76b4-4ff2-9279-53011f1bf335' class='xr-var-data-in' type='checkbox'><label for='data-32f1a17a-76b4-4ff2-9279-53011f1bf335' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1466., 1466., 1466., ..., 1466., 1466., 1466.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-5b7ba3ea-d932-4cda-9c63-d47d434c063b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b7ba3ea-d932-4cda-9c63-d47d434c063b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f6001da-bcb7-4b30-8ebe-60b33b89d3b5' class='xr-var-data-in' type='checkbox'><label for='data-3f6001da-bcb7-4b30-8ebe-60b33b89d3b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.1 -0.09 -0.21 ... 0.2 0.07 0.56</div><input id='attrs-287414d4-2558-4201-be9e-1933858384b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-287414d4-2558-4201-be9e-1933858384b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53b4dee0-4436-4132-a4db-d5d075c1771c' class='xr-var-data-in' type='checkbox'><label for='data-53b4dee0-4436-4132-a4db-d5d075c1771c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.1 , -0.09, -0.21, ...,  0.2 ,  0.07,  0.56], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.33 3.32 3.33 ... 2.24 2.65 2.33</div><input id='attrs-299d52aa-edd8-45ec-a40a-ac7e0f0583d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-299d52aa-edd8-45ec-a40a-ac7e0f0583d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe3ae63f-fa87-4c0e-8321-742a4714f6dc' class='xr-var-data-in' type='checkbox'><label for='data-fe3ae63f-fa87-4c0e-8321-742a4714f6dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([3.33, 3.32, 3.33, ..., 2.24, 2.65, 2.33], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>154.6 154.5 155.0 ... 145.8 147.8</div><input id='attrs-0b619233-76ea-4864-b694-9ba3a6827bd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b619233-76ea-4864-b694-9ba3a6827bd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2ef515e-47b4-4803-b8f5-d79dc40e6ba9' class='xr-var-data-in' type='checkbox'><label for='data-d2ef515e-47b4-4803-b8f5-d79dc40e6ba9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([154.65, 154.49, 155.01, ..., 146.32, 145.75, 147.81], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>15.2 15.25 15.23 ... 15.21 15.22</div><input id='attrs-34c846c1-7501-44e5-b389-dc8d19dc605a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34c846c1-7501-44e5-b389-dc8d19dc605a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2153147-f3f9-419e-b6c1-6b6833775565' class='xr-var-data-in' type='checkbox'><label for='data-c2153147-f3f9-419e-b6c1-6b6833775565' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([15.2 , 15.25, 15.23, ..., 15.2 , 15.21, 15.22], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-8671b2dd-742d-4ffc-beff-fb5f7ec97728' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8671b2dd-742d-4ffc-beff-fb5f7ec97728' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cc13546-7870-4cd2-ad21-2bcc293dc6b9' class='xr-var-data-in' type='checkbox'><label for='data-5cc13546-7870-4cd2-ad21-2bcc293dc6b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>psu</dd><dt><span>long_name :</span></dt><dd>Salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>min_preping_wait</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-9ed3d1c1-4a9c-4a44-8ead-88a7cb450d6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ed3d1c1-4a9c-4a44-8ead-88a7cb450d6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0053858-a8e7-4fc1-907d-55f97ae47f6e' class='xr-var-data-in' type='checkbox'><label for='data-b0053858-a8e7-4fc1-907d-55f97ae47f6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Minimum Pre-Ping Wait Time Between Measurements</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3b9bbd6f-45ba-45d1-9ac6-72bfe597e30e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b9bbd6f-45ba-45d1-9ac6-72bfe597e30e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb894a97-1b05-48fc-8c6a-bc26afaccb8c' class='xr-var-data-in' type='checkbox'><label for='data-cb894a97-1b05-48fc-8c6a-bc26afaccb8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-b51bb831-967b-4d4d-9e6a-bdfe4a521347' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b51bb831-967b-4d4d-9e6a-bdfe4a521347' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c81f7d1-61bb-4b97-b2c4-8b2396a53d8d' class='xr-var-data-in' type='checkbox'><label for='data-0c81f7d1-61bb-4b97-b2c4-8b2396a53d8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-7a205fc7-8d34-4d7a-bf03-f25b8bda668a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a205fc7-8d34-4d7a-bf03-f25b8bda668a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf187f74-4dda-4836-9177-e81d72b987d5' class='xr-var-data-in' type='checkbox'><label for='data-bf187f74-4dda-4836-9177-e81d72b987d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-97356e9f-7ceb-4f30-bc81-b7f5d271941f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97356e9f-7ceb-4f30-bc81-b7f5d271941f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c1fe7c2-9a48-427f-afac-e2dfc7472912' class='xr-var-data-in' type='checkbox'><label for='data-7c1fe7c2-9a48-427f-afac-e2dfc7472912' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_std</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-b69a02f5-b982-4d9b-9b5b-632874df04b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b69a02f5-b982-4d9b-9b5b-632874df04b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c764aac6-e484-4d48-a94a-4c4d3ee2b9c8' class='xr-var-data-in' type='checkbox'><label for='data-c764aac6-e484-4d48-a94a-4c4d3ee2b9c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.057 -0.192 0.121 ... nan nan nan</div><input id='attrs-e5f59eb9-dddf-45a9-9e75-be637e943018' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5f59eb9-dddf-45a9-9e75-be637e943018' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24a5b6a2-97bb-43fe-835b-5a04e659a473' class='xr-var-data-in' type='checkbox'><label for='data-24a5b6a2-97bb-43fe-835b-5a04e659a473' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.057, -0.192,  0.121, ..., -0.01 , -0.629,  0.134],\n",
        "        [-0.058, -0.131, -0.119, ...,  0.048, -0.146, -0.078],\n",
        "        [ 0.059,  0.406,  0.067, ..., -0.123, -0.524,  0.057],\n",
        "        ...,\n",
@@ -613,7 +534,7 @@
        "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
        "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
        "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
-       "      shape=(4, 47, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>224.0 229.0 225.0 ... 63.0 49.0</div><input id='attrs-4f37e2fe-ed0f-4d69-93b4-88f8608f406a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f37e2fe-ed0f-4d69-93b4-88f8608f406a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50afdb7d-af77-4499-a825-23388b176da8' class='xr-var-data-in' type='checkbox'><label for='data-50afdb7d-af77-4499-a825-23388b176da8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[224., 229., 225., ..., 228., 229., 227.],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>224.0 229.0 225.0 ... 63.0 49.0</div><input id='attrs-c18afc82-db7b-495a-89cd-719abb655ae2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c18afc82-db7b-495a-89cd-719abb655ae2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc8d642d-1523-4812-8219-e77a9384d24f' class='xr-var-data-in' type='checkbox'><label for='data-fc8d642d-1523-4812-8219-e77a9384d24f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[224., 229., 225., ..., 228., 229., 227.],\n",
        "        [222., 222., 221., ..., 222., 228., 226.],\n",
        "        [217., 215., 214., ..., 223., 219., 224.],\n",
        "        ...,\n",
@@ -643,8 +564,7 @@
        "        ...,\n",
        "        [ 51.,  57.,  52., ...,  61.,  92.,  49.],\n",
        "        [ 52.,  58.,  53., ...,  59.,  66.,  52.],\n",
-       "        [ 51.,  60.,  50., ...,  74.,  63.,  49.]]],\n",
-       "      shape=(4, 47, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>124.0 118.0 130.0 ... 16.0 8.0 21.0</div><input id='attrs-f567a3e8-0fac-4a0c-ba63-3880a9cfafab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f567a3e8-0fac-4a0c-ba63-3880a9cfafab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca3e4071-d4a1-46e7-a3a8-2ee3287fbbb3' class='xr-var-data-in' type='checkbox'><label for='data-ca3e4071-d4a1-46e7-a3a8-2ee3287fbbb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[124., 118., 130., ..., 125., 111., 133.],\n",
+       "        [ 51.,  60.,  50., ...,  74.,  63.,  49.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>124.0 118.0 130.0 ... 16.0 8.0 21.0</div><input id='attrs-3e90c35f-d26a-486d-be2c-328d842400e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e90c35f-d26a-486d-be2c-328d842400e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48645b6e-a061-489b-b898-b9bf90fabdbc' class='xr-var-data-in' type='checkbox'><label for='data-48645b6e-a061-489b-b898-b9bf90fabdbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[124., 118., 130., ..., 125., 111., 133.],\n",
        "        [128., 140., 128., ..., 118., 140., 120.],\n",
        "        [132., 119., 119., ..., 109., 116., 122.],\n",
        "        ...,\n",
@@ -674,8 +594,7 @@
        "        ...,\n",
        "        [ 19.,  13.,  17., ...,  18.,  23.,  11.],\n",
        "        [  7.,  25.,  16., ...,  26.,  23.,  27.],\n",
-       "        [ 13.,  25.,  13., ...,  16.,   8.,  21.]]],\n",
-       "      shape=(4, 47, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcnt_gd</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-1d21a950-b980-45d7-b2eb-5b092f6c9168' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d21a950-b980-45d7-b2eb-5b092f6c9168' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5de435e-8387-4b8d-b170-2f524765f536' class='xr-var-data-in' type='checkbox'><label for='data-e5de435e-8387-4b8d-b170-2f524765f536' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Percent Good</dd><dt><span>standard_name :</span></dt><dd>proportion_of_acceptable_signal_returns_from_acoustic_instrument_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
+       "        [ 13.,  25.,  13., ...,  16.,   8.,  21.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcnt_gd</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-f270e353-cd7e-4845-80fb-795282bb0c97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f270e353-cd7e-4845-80fb-795282bb0c97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c44e605-028a-4dfb-9e1f-1f2c7a4e1a1e' class='xr-var-data-in' type='checkbox'><label for='data-1c44e605-028a-4dfb-9e1f-1f2c7a4e1a1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Percent Good</dd><dt><span>standard_name :</span></dt><dd>proportion_of_acceptable_signal_returns_from_acoustic_instrument_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
        "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
        "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
        "        ...,\n",
@@ -705,53 +624,46 @@
        "        ...,\n",
        "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
        "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
-       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]]],\n",
-       "      shape=(4, 47, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dist_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.95 3.95 3.96 ... 1.93 1.95 2.0</div><input id='attrs-18d28ea0-92c5-476d-8ce2-18edc604e463' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18d28ea0-92c5-476d-8ce2-18edc604e463' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6fafaf1-cff5-4704-907f-0db346fb8b66' class='xr-var-data-in' type='checkbox'><label for='data-e6fafaf1-cff5-4704-907f-0db346fb8b66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Bottom Track Measured Depth</dd></dl></div><div class='xr-var-data'><pre>array([[3.95, 3.95, 3.96, ..., 2.65, 2.64, 2.6 ],\n",
+       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dist_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.95 3.95 3.96 ... 1.93 1.95 2.0</div><input id='attrs-895fef8d-813c-4a3c-9268-efb30dedf22a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-895fef8d-813c-4a3c-9268-efb30dedf22a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8919ef3-5561-49fd-b710-0601b711f922' class='xr-var-data-in' type='checkbox'><label for='data-c8919ef3-5561-49fd-b710-0601b711f922' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Bottom Track Measured Depth</dd></dl></div><div class='xr-var-data'><pre>array([[3.95, 3.95, 3.96, ..., 2.65, 2.64, 2.6 ],\n",
        "       [2.55, 2.56, 2.57, ..., 1.61, 1.59, 1.59],\n",
        "       [3.31, 3.32, 3.33, ..., 1.93, 1.95, 1.96],\n",
-       "       [2.87, 2.88, 2.88, ..., 1.93, 1.95, 2.  ]],\n",
-       "      shape=(4, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_bt</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.063 -0.004 0.039 ... 0.01 0.0</div><input id='attrs-0a14f9ef-3b14-4690-acae-a60c465076ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a14f9ef-3b14-4690-acae-a60c465076ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8688af7-56f3-44b9-b1f1-97077730fb2c' class='xr-var-data-in' type='checkbox'><label for='data-e8688af7-56f3-44b9-b1f1-97077730fb2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 6.3000e-02, -4.0000e-03,  3.9000e-02, ...,  2.3000e-02,\n",
+       "       [2.87, 2.88, 2.88, ..., 1.93, 1.95, 2.  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_bt</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.063 -0.004 0.039 ... 0.01 0.0</div><input id='attrs-80abbd51-3015-4834-9dd8-8ffaf8dfda6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80abbd51-3015-4834-9dd8-8ffaf8dfda6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-574068ae-0da5-4b1c-bc91-c3688eb6dbe0' class='xr-var-data-in' type='checkbox'><label for='data-574068ae-0da5-4b1c-bc91-c3688eb6dbe0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 6.3000e-02, -4.0000e-03,  3.9000e-02, ...,  2.3000e-02,\n",
        "         2.7000e-02,  0.0000e+00],\n",
        "       [-3.7000e-02,  1.9000e-02,  1.5000e-02, ..., -6.9000e-02,\n",
        "        -1.0100e-01, -1.5800e-01],\n",
        "       [ 9.0000e-03,  0.0000e+00,  8.0000e-03, ...,  0.0000e+00,\n",
        "        -1.7000e-02, -2.0000e-03],\n",
        "       [-1.0000e-02, -6.0000e-03, -3.2768e+01, ...,  7.0000e-03,\n",
-       "         1.0000e-02,  0.0000e+00]], shape=(4, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>231.0 243.0 242.0 ... 249.0 246.0</div><input id='attrs-ed1ddc5b-2f3a-4742-bac6-facf5e7402ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed1ddc5b-2f3a-4742-bac6-facf5e7402ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83911fb1-feeb-40b8-bf83-c3d4550b73eb' class='xr-var-data-in' type='checkbox'><label for='data-83911fb1-feeb-40b8-bf83-c3d4550b73eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[231., 243., 242., ..., 252., 255., 248.],\n",
+       "         1.0000e-02,  0.0000e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>231.0 243.0 242.0 ... 249.0 246.0</div><input id='attrs-dc8f1a58-468a-48fb-9ce3-469072691f60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc8f1a58-468a-48fb-9ce3-469072691f60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e64bec9f-0094-48df-a6d4-882bc827d1e9' class='xr-var-data-in' type='checkbox'><label for='data-e64bec9f-0094-48df-a6d4-882bc827d1e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[231., 243., 242., ..., 252., 255., 248.],\n",
        "       [229., 239., 246., ..., 249., 248., 254.],\n",
        "       [223., 237.,   0., ..., 249., 252., 251.],\n",
-       "       [248., 244., 250., ..., 248., 249., 246.]],\n",
-       "      shape=(4, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>40.0 40.0 36.0 ... 40.0 64.0 49.0</div><input id='attrs-93bc6915-f449-4344-ab4e-92149df0d5d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93bc6915-f449-4344-ab4e-92149df0d5d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-798c2c32-d456-4bb6-98e8-b36c003ae1dd' class='xr-var-data-in' type='checkbox'><label for='data-798c2c32-d456-4bb6-98e8-b36c003ae1dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[40., 40., 36., ..., 64., 66., 51.],\n",
+       "       [248., 244., 250., ..., 248., 249., 246.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>40.0 40.0 36.0 ... 40.0 64.0 49.0</div><input id='attrs-cd7acab0-bf1a-4c8f-bbdc-2a1b95d94abd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd7acab0-bf1a-4c8f-bbdc-2a1b95d94abd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-957042f8-d921-44f5-8265-96f209bb313c' class='xr-var-data-in' type='checkbox'><label for='data-957042f8-d921-44f5-8265-96f209bb313c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[40., 40., 36., ..., 64., 66., 51.],\n",
        "       [45., 38., 47., ..., 78., 78., 83.],\n",
        "       [40., 43., 36., ..., 55., 71., 71.],\n",
-       "       [55., 54., 52., ..., 40., 64., 49.]],\n",
-       "      shape=(4, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcnt_gd_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 100.0 ... 100.0 100.0 100.0</div><input id='attrs-1408b995-55a5-4be7-b140-1e5705f9c189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1408b995-55a5-4be7-b140-1e5705f9c189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-678b44f7-d6f3-4bc0-a050-af367c37baa0' class='xr-var-data-in' type='checkbox'><label for='data-678b44f7-d6f3-4bc0-a050-af367c37baa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Percent Good</dd><dt><span>standard_name :</span></dt><dd>proportion_of_acceptable_signal_returns_from_acoustic_instrument_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[  0.,   0., 100., ...,   0.,   0.,   0.],\n",
+       "       [55., 54., 52., ..., 40., 64., 49.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>prcnt_gd_bt</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 100.0 ... 100.0 100.0 100.0</div><input id='attrs-cb86b41f-5ea4-4967-81eb-12564b25b401' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb86b41f-5ea4-4967-81eb-12564b25b401' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18f9a8c2-1e08-436c-acd8-0708f743be19' class='xr-var-data-in' type='checkbox'><label for='data-18f9a8c2-1e08-436c-acd8-0708f743be19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Percent Good</dd><dt><span>standard_name :</span></dt><dd>proportion_of_acceptable_signal_returns_from_acoustic_instrument_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[  0.,   0., 100., ...,   0.,   0.,   0.],\n",
        "       [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
        "       [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
-       "       [100., 100.,   0., ..., 100., 100., 100.]],\n",
-       "      shape=(4, 1227), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>64.56 64.56 64.56 ... 64.56 64.56</div><input id='attrs-4955270e-8fce-45c7-a350-67eee8d83063' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4955270e-8fce-45c7-a350-67eee8d83063' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74a7d630-4ef4-4ee0-a26f-a11a9ec78455' class='xr-var-data-in' type='checkbox'><label for='data-74a7d630-4ef4-4ee0-a26f-a11a9ec78455' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([64.560905, 64.560905, 64.560905, ..., 64.56094 , 64.56094 ,\n",
-       "       64.56094 ], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-149.1 -149.1 ... -149.1 -149.1</div><input id='attrs-4304c44f-dfea-43b9-b5b6-e59f00833f93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4304c44f-dfea-43b9-b5b6-e59f00833f93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d23bdbd6-8fad-4a08-b5b3-91a02baaab04' class='xr-var-data-in' type='checkbox'><label for='data-d23bdbd6-8fad-4a08-b5b3-91a02baaab04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-149.06679, -149.06679, -149.06679, ..., -149.06682, -149.06682,\n",
-       "       -149.0668 ], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fix_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0</div><input id='attrs-48a1e437-d460-421d-9720-f09a8c23c220' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48a1e437-d460-421d-9720-f09a8c23c220' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80f8d7a4-e81a-41db-8f2f-1326bd2cb1e9' class='xr-var-data-in' type='checkbox'><label for='data-80f8d7a4-e81a-41db-8f2f-1326bd2cb1e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>GPS Fix</dd></dl></div><div class='xr-var-data'><pre>array([9., 9., 9., ..., 9., 9., 9.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_sat_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.0 9.0 9.0 9.0 ... 10.0 10.0 10.0</div><input id='attrs-953512d9-4ba2-47ef-9011-53c88a53fa55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-953512d9-4ba2-47ef-9011-53c88a53fa55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-beacc763-8095-4709-b13b-e5336494c2ac' class='xr-var-data-in' type='checkbox'><label for='data-beacc763-8095-4709-b13b-e5336494c2ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>count</dd><dt><span>long_name :</span></dt><dd>Number of Satellites</dd></dl></div><div class='xr-var-data'><pre>array([ 9.,  9.,  9., ..., 10., 10., 10.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hdop_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.9 0.9 0.9 0.9 ... 0.8 0.8 0.8 0.8</div><input id='attrs-aa04ea87-18a5-42f5-9dad-ff98e2d976a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa04ea87-18a5-42f5-9dad-ff98e2d976a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd8671b9-2d9e-4fa8-9cb8-e121e1af71e6' class='xr-var-data-in' type='checkbox'><label for='data-bd8671b9-2d9e-4fa8-9cb8-e121e1af71e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Horizontal Dilution of Precision</dd></dl></div><div class='xr-var-data'><pre>array([0.9, 0.9, 0.9, ..., 0.8, 0.8, 0.8], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>108.5 108.2 108.2 ... 108.6 108.6</div><input id='attrs-fcc07695-d8f4-4f7d-a4f9-58f1d8bbad58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcc07695-d8f4-4f7d-a4f9-58f1d8bbad58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31ac4442-7df8-46dd-bfa9-a8f100eb36c8' class='xr-var-data-in' type='checkbox'><label for='data-31ac4442-7df8-46dd-bfa9-a8f100eb36c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Elevation above MLLW</dd></dl></div><div class='xr-var-data'><pre>array([108.483, 108.196, 108.208, ..., 108.644, 108.629, 108.606],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtk_age_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.0 6.0 2.0 3.0 ... 6.0 2.0 3.0 3.0</div><input id='attrs-1ffe38ff-187d-4a46-96ca-ba105be74222' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ffe38ff-187d-4a46-96ca-ba105be74222' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35efa5b0-985c-424e-b510-667668d3e6f2' class='xr-var-data-in' type='checkbox'><label for='data-35efa5b0-985c-424e-b510-667668d3e6f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Age of Received Real Time Kinetic Signal</dd></dl></div><div class='xr-var-data'><pre>array([5., 6., 2., ..., 2., 3., 3.], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>speed_over_grnd_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.03549 0.03395 ... 0.1096 0.1672</div><input id='attrs-aab67b6c-2791-4215-be33-56398b668fb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aab67b6c-2791-4215-be33-56398b668fb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7500a405-dc71-4b65-8672-8959c959c1c3' class='xr-var-data-in' type='checkbox'><label for='data-7500a405-dc71-4b65-8672-8959c959c1c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Platform Speed over Ground</dd><dt><span>standard_name :</span></dt><dd>platform_speed_wrt_ground</dd></dl></div><div class='xr-var-data'><pre>array([0.03549382, 0.03395062, 0.03858025, ..., 0.11985596, 0.1095679 ,\n",
-       "       0.16718106], shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dir_over_grnd_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>115.5 94.08 6.931 ... 160.5 182.1</div><input id='attrs-01872462-a56d-402f-8d58-c0b320652190' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01872462-a56d-402f-8d58-c0b320652190' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-635a854c-72b9-49f5-b10a-bb6b13d2a24c' class='xr-var-data-in' type='checkbox'><label for='data-635a854c-72b9-49f5-b10a-bb6b13d2a24c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Platform Direction over Ground</dd><dt><span>standard_name :</span></dt><dd>platform_course</dd></dl></div><div class='xr-var-data'><pre>array([115.501,  94.077,   6.931, ..., 140.963, 160.468, 182.087],\n",
-       "      shape=(1227,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hdwtime_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T14:28:15.559999942 .....</div><input id='attrs-854f6af0-9af6-4929-85d8-b15d3e7b834c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-854f6af0-9af6-4929-85d8-b15d3e7b834c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-467689e9-7155-43f2-8079-ce0b5295f27e' class='xr-var-data-in' type='checkbox'><label for='data-467689e9-7155-43f2-8079-ce0b5295f27e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T14:28:15.559999942&#x27;, &#x27;2010-08-10T14:28:16.319999933&#x27;,\n",
+       "       [100., 100.,   0., ..., 100., 100., 100.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>64.56 64.56 64.56 ... 64.56 64.56</div><input id='attrs-db39bac2-fe9b-4c9a-af2e-c98d71d2ee7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db39bac2-fe9b-4c9a-af2e-c98d71d2ee7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd1af951-3824-4cda-acb9-21f8f0d3f7e4' class='xr-var-data-in' type='checkbox'><label for='data-cd1af951-3824-4cda-acb9-21f8f0d3f7e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([64.560905, 64.560905, 64.560905, ..., 64.56094 , 64.56094 ,\n",
+       "       64.56094 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-149.1 -149.1 ... -149.1 -149.1</div><input id='attrs-620a53c9-1848-496a-a49d-5ce6dc6bf703' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-620a53c9-1848-496a-a49d-5ce6dc6bf703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-717a3c0e-47b0-43fd-9c6f-2d1d742881ea' class='xr-var-data-in' type='checkbox'><label for='data-717a3c0e-47b0-43fd-9c6f-2d1d742881ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-149.06679, -149.06679, -149.06679, ..., -149.06682, -149.06682,\n",
+       "       -149.0668 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fix_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0</div><input id='attrs-6b40b289-2c64-4096-9e46-d30a2e1b99d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b40b289-2c64-4096-9e46-d30a2e1b99d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8c03e4c-52c1-446a-a918-c1a879f83ee1' class='xr-var-data-in' type='checkbox'><label for='data-f8c03e4c-52c1-446a-a918-c1a879f83ee1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>GPS Fix</dd></dl></div><div class='xr-var-data'><pre>array([9., 9., 9., ..., 9., 9., 9.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_sat_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.0 9.0 9.0 9.0 ... 10.0 10.0 10.0</div><input id='attrs-4dda8812-eda9-4368-88b0-585c2efcbe7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dda8812-eda9-4368-88b0-585c2efcbe7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-089b540a-42bc-4afc-b02d-86784a5db367' class='xr-var-data-in' type='checkbox'><label for='data-089b540a-42bc-4afc-b02d-86784a5db367' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>count</dd><dt><span>long_name :</span></dt><dd>Number of Satellites</dd></dl></div><div class='xr-var-data'><pre>array([ 9.,  9.,  9., ..., 10., 10., 10.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hdop_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.9 0.9 0.9 0.9 ... 0.8 0.8 0.8 0.8</div><input id='attrs-a431af50-9b0c-4355-841f-9c337fdda7e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a431af50-9b0c-4355-841f-9c337fdda7e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2ef31ae-4904-453b-92d4-140a4e8bcc47' class='xr-var-data-in' type='checkbox'><label for='data-b2ef31ae-4904-453b-92d4-140a4e8bcc47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Horizontal Dilution of Precision</dd></dl></div><div class='xr-var-data'><pre>array([0.9, 0.9, 0.9, ..., 0.8, 0.8, 0.8], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>108.5 108.2 108.2 ... 108.6 108.6</div><input id='attrs-7a572dd5-4605-4192-b0fb-6b8c7de5dd72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a572dd5-4605-4192-b0fb-6b8c7de5dd72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec72a9e5-0af6-4b96-8b6b-4579938af5e3' class='xr-var-data-in' type='checkbox'><label for='data-ec72a9e5-0af6-4b96-8b6b-4579938af5e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Elevation above MLLW</dd></dl></div><div class='xr-var-data'><pre>array([108.483, 108.196, 108.208, ..., 108.644, 108.629, 108.606],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rtk_age_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.0 6.0 2.0 3.0 ... 6.0 2.0 3.0 3.0</div><input id='attrs-c30d0faa-7b11-483e-8396-2cb00373924e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c30d0faa-7b11-483e-8396-2cb00373924e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76419494-ab4e-4540-9342-930f9af39666' class='xr-var-data-in' type='checkbox'><label for='data-76419494-ab4e-4540-9342-930f9af39666' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Age of Received Real Time Kinetic Signal</dd></dl></div><div class='xr-var-data'><pre>array([5., 6., 2., ..., 2., 3., 3.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>speed_over_grnd_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.03549 0.03395 ... 0.1096 0.1672</div><input id='attrs-79774f56-5e74-40be-95cf-ae0663283691' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79774f56-5e74-40be-95cf-ae0663283691' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ea5ee98-9639-4f85-9194-d95466091a41' class='xr-var-data-in' type='checkbox'><label for='data-8ea5ee98-9639-4f85-9194-d95466091a41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Platform Speed over Ground</dd><dt><span>standard_name :</span></dt><dd>platform_speed_wrt_ground</dd></dl></div><div class='xr-var-data'><pre>array([0.03549382, 0.03395062, 0.03858025, ..., 0.11985596, 0.1095679 ,\n",
+       "       0.16718106], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dir_over_grnd_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>115.5 94.08 6.931 ... 160.5 182.1</div><input id='attrs-f14dc8c1-0361-421c-a45b-beb58ab839ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f14dc8c1-0361-421c-a45b-beb58ab839ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-490f96ce-eefb-4525-af0a-0c32c73ea2df' class='xr-var-data-in' type='checkbox'><label for='data-490f96ce-eefb-4525-af0a-0c32c73ea2df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Platform Direction over Ground</dd><dt><span>standard_name :</span></dt><dd>platform_course</dd></dl></div><div class='xr-var-data'><pre>array([115.501,  94.077,   6.931, ..., 140.963, 160.468, 182.087],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hdwtime_gps</span></div><div class='xr-var-dims'>(time_gps)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-08-10T14:28:15.559999942 .....</div><input id='attrs-56c07c11-69c2-4231-b984-d793a2023031' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56c07c11-69c2-4231-b984-d793a2023031' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a45279e2-74ae-410c-88d6-cc48c1b17393' class='xr-var-data-in' type='checkbox'><label for='data-a45279e2-74ae-410c-88d6-cc48c1b17393' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-08-10T14:28:15.559999942&#x27;, &#x27;2010-08-10T14:28:16.319999933&#x27;,\n",
        "       &#x27;2010-08-10T14:28:17.069999933&#x27;, ...,\n",
        "       &#x27;2010-08-10T14:39:59.190000057&#x27;, &#x27;2010-08-10T14:39:59.910000085&#x27;,\n",
-       "       &#x27;2010-08-10T14:40:00.630000114&#x27;],\n",
-       "      shape=(1227,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.462 -1.462 0.0 ... -1.034 -1.034</div><input id='attrs-0113a027-7e0f-426c-a742-872ad1713938' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0113a027-7e0f-426c-a742-872ad1713938' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a03d6ad-4c2a-48c4-84f9-2644cd1a919d' class='xr-var-data-in' type='checkbox'><label for='data-9a03d6ad-4c2a-48c4-84f9-2644cd1a919d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.4619021 , -1.4619021 ,  0.        ,  0.        ],\n",
-       "       [ 0.        ,  0.        , -1.4619021 ,  1.4619021 ],\n",
+       "       &#x27;2010-08-10T14:40:00.630000114&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.462 -1.462 0.0 ... -1.034 -1.034</div><input id='attrs-383b1ef4-d125-4c38-8744-555b0889e331' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-383b1ef4-d125-4c38-8744-555b0889e331' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93fbfae1-d168-40e0-8696-3ffe4f73b2af' class='xr-var-data-in' type='checkbox'><label for='data-93fbfae1-d168-40e0-8696-3ffe4f73b2af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.4619022 , -1.4619022 ,  0.        ,  0.        ],\n",
+       "       [ 0.        ,  0.        , -1.4619022 ,  1.4619022 ],\n",
        "       [ 0.26604444,  0.26604444,  0.26604444,  0.26604444],\n",
-       "       [ 1.033721  ,  1.033721  , -1.033721  , -1.033721  ]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.9037 -0.9025 -0.9064 ... 1.0 1.0</div><input id='attrs-66663342-742c-4476-8963-b17dfc7bcc92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66663342-742c-4476-8963-b17dfc7bcc92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b36e2e53-263a-4699-b309-3d6dd3524d9a' class='xr-var-data-in' type='checkbox'><label for='data-b36e2e53-263a-4699-b309-3d6dd3524d9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.9037092 , -0.9025101 , -0.9063815 , ..., -0.8321477 ,\n",
+       "       [ 1.03372096,  1.03372096, -1.03372096, -1.03372096]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.9037 -0.9025 -0.9064 ... 1.0 1.0</div><input id='attrs-a599000d-d504-4ad6-bac1-c849e09d72a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a599000d-d504-4ad6-bac1-c849e09d72a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7151e22c-2c4a-49e1-ba32-0c5d6068cd63' class='xr-var-data-in' type='checkbox'><label for='data-7151e22c-2c4a-49e1-ba32-0c5d6068cd63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.90370917, -0.90251011, -0.90638149, ..., -0.83214772,\n",
        "         -0.8265897 , -0.84628606],\n",
-       "        [-0.4281468 , -0.43066862, -0.42246014, ..., -0.554554  ,\n",
+       "        [-0.42814681, -0.43066862, -0.42246014, ..., -0.55455399,\n",
        "         -0.56280506, -0.53272873],\n",
        "        [-0.        , -0.        , -0.        , ..., -0.        ,\n",
        "         -0.        , -0.        ]],\n",
        "\n",
-       "       [[ 0.4281468 ,  0.43066862,  0.42246014, ...,  0.554554  ,\n",
+       "       [[ 0.42814681,  0.43066862,  0.42246014, ...,  0.55455399,\n",
        "          0.56280506,  0.53272873],\n",
-       "        [-0.9037092 , -0.9025101 , -0.9063815 , ..., -0.8321477 ,\n",
+       "        [-0.90370917, -0.90251011, -0.90638149, ..., -0.83214772,\n",
        "         -0.8265897 , -0.84628606],\n",
        "        [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
        "          0.        ,  0.        ]],\n",
@@ -761,7 +673,7 @@
        "        [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
        "          0.        ,  0.        ],\n",
        "        [ 1.        ,  1.        ,  1.        , ...,  1.        ,\n",
-       "          1.        ,  1.        ]]], shape=(3, 3, 1227), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-715323bb-8a05-4f9d-9ed8-9c97206fb923' class='xr-section-summary-in' type='checkbox'  ><label for='section-715323bb-8a05-4f9d-9ed8-9c97206fb923' class='xr-section-summary' >Indexes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e5cbe076-06f8-4d0e-b075-481c131181e2' class='xr-index-data-in' type='checkbox'/><label for='index-e5cbe076-06f8-4d0e-b075-481c131181e2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2010-08-10 14:28:15.559999942&#x27;,\n",
+       "          1.        ,  1.        ]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-af3750cb-f986-452c-a36c-17c9bc7b65c4' class='xr-section-summary-in' type='checkbox'  ><label for='section-af3750cb-f986-452c-a36c-17c9bc7b65c4' class='xr-section-summary' >Indexes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b5224da7-74dc-4c8f-b372-1d442fe6cb2e' class='xr-index-data-in' type='checkbox'/><label for='index-b5224da7-74dc-4c8f-b372-1d442fe6cb2e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2010-08-10 14:28:15.559999942&#x27;,\n",
        "               &#x27;2010-08-10 14:28:16.319999933&#x27;,\n",
        "               &#x27;2010-08-10 14:28:17.069999933&#x27;,\n",
        "               &#x27;2010-08-10 14:28:17.799999952&#x27;,\n",
@@ -782,7 +694,7 @@
        "               &#x27;2010-08-10 14:39:59.190000057&#x27;,\n",
        "               &#x27;2010-08-10 14:39:59.910000085&#x27;,\n",
        "               &#x27;2010-08-10 14:40:00.630000114&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1227, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_gps</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2886a302-36d8-4d56-8351-9f96f18e870c' class='xr-index-data-in' type='checkbox'/><label for='index-2886a302-36d8-4d56-8351-9f96f18e870c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2010-08-10 22:28:17.200000047&#x27;,\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1227, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_gps</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7351e584-cbf5-4e5b-b97e-2ed8a1df6066' class='xr-index-data-in' type='checkbox'/><label for='index-7351e584-cbf5-4e5b-b97e-2ed8a1df6066' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2010-08-10 22:28:17.200000047&#x27;,\n",
        "                         &#x27;2010-08-10 22:28:18&#x27;,\n",
        "               &#x27;2010-08-10 22:28:18.599999904&#x27;,\n",
        "               &#x27;2010-08-10 22:28:19.400000095&#x27;,\n",
@@ -803,23 +715,23 @@
        "               &#x27;2010-08-10 22:40:00.799999952&#x27;,\n",
        "               &#x27;2010-08-10 22:40:01.400000095&#x27;,\n",
        "               &#x27;2010-08-10 22:40:02.200000047&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_gps&#x27;, length=1227, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0250f22b-7f25-4d4d-a112-eaaad29de8c5' class='xr-index-data-in' type='checkbox'/><label for='index-0250f22b-7f25-4d4d-a112-eaaad29de8c5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.5699999928474426, 0.8199999928474426, 1.0700000524520874,\n",
-       "       1.3200000524520874, 1.5700000524520874, 1.8200000524520874,\n",
-       "        2.069999933242798,  2.319999933242798,  2.569999933242798,\n",
-       "        2.819999933242798,  3.069999933242798,  3.319999933242798,\n",
-       "        3.569999933242798,  3.819999933242798,  4.070000171661377,\n",
-       "        4.320000171661377,  4.570000171661377,  4.820000171661377,\n",
-       "        5.070000171661377,  5.320000171661377,  5.570000171661377,\n",
-       "        5.820000171661377,  6.070000171661377,  6.320000171661377,\n",
-       "        6.570000171661377,  6.820000171661377,  7.070000171661377,\n",
-       "        7.320000171661377,  7.570000171661377,  7.820000171661377,\n",
-       "        8.069999694824219,  8.319999694824219,  8.569999694824219,\n",
-       "        8.819999694824219,  9.069999694824219,  9.319999694824219,\n",
-       "        9.569999694824219,  9.819999694824219, 10.069999694824219,\n",
-       "       10.319999694824219, 10.569999694824219, 10.819999694824219,\n",
-       "       11.069999694824219, 11.319999694824219, 11.569999694824219,\n",
-       "       11.819999694824219, 12.069999694824219],\n",
-       "      dtype=&#x27;float32&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-a60c54d3-df25-42a7-8ef8-2253c9892a87' class='xr-index-data-in' type='checkbox'/><label for='index-a60c54d3-df25-42a7-8ef8-2253c9892a87' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b5a9ace4-c990-46a0-abfd-93d43eade1ff' class='xr-index-data-in' type='checkbox'/><label for='index-b5a9ace4-c990-46a0-abfd-93d43eade1ff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;, &#x27;err&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-08b08bc7-5644-4126-858f-18dffc747812' class='xr-index-data-in' type='checkbox'/><label for='index-08b08bc7-5644-4126-858f-18dffc747812' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-a18de09c-9449-4985-b77e-86c4cdfb3f2b' class='xr-index-data-in' type='checkbox'/><label for='index-a18de09c-9449-4985-b77e-86c4cdfb3f2b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-444909e6-dced-4025-a032-e062865e9f49' class='xr-index-data-in' type='checkbox'/><label for='index-444909e6-dced-4025-a032-e062865e9f49' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-bf421842-96bc-4c53-9d66-2f033ee263fc' class='xr-index-data-in' type='checkbox'/><label for='index-bf421842-96bc-4c53-9d66-2f033ee263fc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-735e5954-b400-49c9-8606-fc374e7b760d' class='xr-section-summary-in' type='checkbox'  ><label for='section-735e5954-b400-49c9-8606-fc374e7b760d' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>firmware_ver :</span></dt><dd>10.16</dd><dt><span>inst_make :</span></dt><dd>TRDI</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;vel_bt&#x27;]</dd><dt><span>has_imu :</span></dt><dd>0</dd><dt><span>inst_model :</span></dt><dd>Rio Grande</dd><dt><span>beam_angle :</span></dt><dd>20</dd><dt><span>carrier_freq :</span></dt><dd>1200</dd><dt><span>beam_pattern :</span></dt><dd>convex</dd><dt><span>orientation :</span></dt><dd>down</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>n_cells :</span></dt><dd>47</dd><dt><span>pings_per_ensemble :</span></dt><dd>1</dd><dt><span>cell_size :</span></dt><dd>0.25</dd><dt><span>blank_dist :</span></dt><dd>0.25</dd><dt><span>profiling_mode :</span></dt><dd>12</dd><dt><span>min_corr_threshold :</span></dt><dd>64</dd><dt><span>n_code_reps :</span></dt><dd>4</dd><dt><span>min_prcnt_gd :</span></dt><dd>0</dd><dt><span>max_error_vel :</span></dt><dd>1.5</dd><dt><span>sec_between_ping_groups :</span></dt><dd>0.09</dd><dt><span>coord_sys :</span></dt><dd>ship</dd><dt><span>use_pitchroll :</span></dt><dd>yes</dd><dt><span>use_3beam :</span></dt><dd>yes</dd><dt><span>bin_mapping :</span></dt><dd>yes</dd><dt><span>heading_misalign_deg :</span></dt><dd>0.0</dd><dt><span>magnetic_var_deg :</span></dt><dd>0.0</dd><dt><span>sensors_src :</span></dt><dd>01011101</dd><dt><span>sensors_avail :</span></dt><dd>00011101</dd><dt><span>transmit_pulse_m :</span></dt><dd>0.3</dd><dt><span>water_ref_cells :</span></dt><dd>[0, 5]</dd><dt><span>false_target_threshold :</span></dt><dd>50</dd><dt><span>transmit_lag_m :</span></dt><dd>0.08</dd><dt><span>bandwidth :</span></dt><dd>0</dd><dt><span>power_level :</span></dt><dd>128</dd><dt><span>serialnum :</span></dt><dd>134877318</dd><dt><span>source_program :</span></dt><dd>WINRIVER</dd><dt><span>range_offset :</span></dt><dd>0.07</dd><dt><span>fs :</span></dt><dd>1.92</dd></dl></div></li></ul></div></div>"
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_gps&#x27;, length=1227, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-891ff25a-ac7b-4714-b15f-08e692a4e3ca' class='xr-index-data-in' type='checkbox'/><label for='index-891ff25a-ac7b-4714-b15f-08e692a4e3ca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([              0.57,               0.82, 1.0699999999999998,\n",
+       "       1.3199999999999998, 1.5699999999999998, 1.8199999999999998,\n",
+       "                     2.07,               2.32,               2.57,\n",
+       "                     2.82,               3.07,               3.32,\n",
+       "                     3.57,               3.82,               4.07,\n",
+       "                     4.32,               4.57,               4.82,\n",
+       "                     5.07,               5.32,               5.57,\n",
+       "                     5.82,               6.07,               6.32,\n",
+       "                     6.57,               6.82,               7.07,\n",
+       "                     7.32,               7.57,               7.82,\n",
+       "                     8.07,               8.32,               8.57,\n",
+       "                     8.82,               9.07,               9.32,\n",
+       "                     9.57,               9.82,              10.07,\n",
+       "                    10.32,              10.57,              10.82,\n",
+       "                    11.07,              11.32,              11.57,\n",
+       "                    11.82,              12.07],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e501e921-4b8a-4e5e-9e1e-a82e03320f62' class='xr-index-data-in' type='checkbox'/><label for='index-e501e921-4b8a-4e5e-9e1e-a82e03320f62' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dc25b894-3f88-4020-8f18-89058a9eac65' class='xr-index-data-in' type='checkbox'/><label for='index-dc25b894-3f88-4020-8f18-89058a9eac65' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;, &#x27;err&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-27b5548d-b305-4cab-a6cf-b55636ab86ae' class='xr-index-data-in' type='checkbox'/><label for='index-27b5548d-b305-4cab-a6cf-b55636ab86ae' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b0c8f78-78d0-4a6c-976d-bce594189813' class='xr-index-data-in' type='checkbox'/><label for='index-4b0c8f78-78d0-4a6c-976d-bce594189813' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-91a25934-41ef-4cc6-a82e-c2763c4ae1a2' class='xr-index-data-in' type='checkbox'/><label for='index-91a25934-41ef-4cc6-a82e-c2763c4ae1a2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c123edd-893d-497c-9ee0-12e8ff39da59' class='xr-index-data-in' type='checkbox'/><label for='index-0c123edd-893d-497c-9ee0-12e8ff39da59' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f17f6314-d80b-4c17-8466-88263ad9d34c' class='xr-section-summary-in' type='checkbox'  ><label for='section-f17f6314-d80b-4c17-8466-88263ad9d34c' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>inst_make :</span></dt><dd>TRDI</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;vel_bt&#x27;]</dd><dt><span>has_imu :</span></dt><dd>0</dd><dt><span>prog_ver :</span></dt><dd>10.16</dd><dt><span>inst_model :</span></dt><dd>Rio Grande</dd><dt><span>beam_angle :</span></dt><dd>20</dd><dt><span>freq :</span></dt><dd>1200</dd><dt><span>beam_pattern :</span></dt><dd>convex</dd><dt><span>orientation :</span></dt><dd>down</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>n_cells :</span></dt><dd>47</dd><dt><span>pings_per_ensemble :</span></dt><dd>1</dd><dt><span>cell_size :</span></dt><dd>0.25</dd><dt><span>blank_dist :</span></dt><dd>0.25</dd><dt><span>profiling_mode :</span></dt><dd>12</dd><dt><span>min_corr_threshold :</span></dt><dd>64</dd><dt><span>n_code_reps :</span></dt><dd>4</dd><dt><span>min_prcnt_gd :</span></dt><dd>0</dd><dt><span>max_error_vel :</span></dt><dd>1.5</dd><dt><span>sec_between_ping_groups :</span></dt><dd>0.09</dd><dt><span>coord_sys :</span></dt><dd>ship</dd><dt><span>use_pitchroll :</span></dt><dd>yes</dd><dt><span>use_3beam :</span></dt><dd>yes</dd><dt><span>bin_mapping :</span></dt><dd>yes</dd><dt><span>heading_misalign_deg :</span></dt><dd>0.0</dd><dt><span>magnetic_var_deg :</span></dt><dd>0.0</dd><dt><span>sensors_src :</span></dt><dd>01011101</dd><dt><span>sensors_avail :</span></dt><dd>00011101</dd><dt><span>bin1_dist_m :</span></dt><dd>0.57</dd><dt><span>transmit_pulse_m :</span></dt><dd>0.3</dd><dt><span>water_ref_cells :</span></dt><dd>[0, 5]</dd><dt><span>false_target_threshold :</span></dt><dd>50</dd><dt><span>transmit_lag_m :</span></dt><dd>0.08</dd><dt><span>bandwidth :</span></dt><dd>0</dd><dt><span>sourceprog :</span></dt><dd>WINRIVER</dd><dt><span>fs :</span></dt><dd>1.92</dd><dt><span>vel_gps_corrected :</span></dt><dd>0</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 4MB\n",
@@ -828,11 +740,11 @@
        "Coordinates:\n",
        "  * time                 (time) datetime64[ns] 10kB 2010-08-10T14:28:15.55999...\n",
        "  * time_gps             (time_gps) datetime64[ns] 10kB 2010-08-10T22:28:17.2...\n",
-       "  * range                (range) float32 188B 0.57 0.82 1.07 ... 11.82 12.07\n",
+       "  * range                (range) float64 376B 0.57 0.82 1.07 ... 11.82 12.07\n",
        "  * beam                 (beam) int32 16B 1 2 3 4\n",
        "  * dir                  (dir) <U3 48B 'X' 'Y' 'Z' 'err'\n",
-       "  * x1                   (x1) int64 32B 1 2 3 4\n",
-       "  * x2                   (x2) int64 32B 1 2 3 4\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
        "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
        "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
        "Data variables: (12/36)\n",
@@ -847,22 +759,22 @@
        "    speed_over_grnd_gps  (time_gps) float32 5kB 0.03549 0.03395 ... 0.1672\n",
        "    dir_over_grnd_gps    (time_gps) float32 5kB 115.5 94.08 ... 160.5 182.1\n",
        "    hdwtime_gps          (time_gps) datetime64[ns] 10kB 2010-08-10T14:28:15.5...\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.462 -1.462 0.0 ... -1.034 -1.034\n",
-       "    orientmat            (earth, inst, time) float32 44kB -0.9037 ... 1.0\n",
-       "Attributes: (12/39)\n",
-       "    firmware_ver:             10.16\n",
+       "    beam2inst_orientmat  (x1, x2) float64 128B 1.462 -1.462 ... -1.034 -1.034\n",
+       "    orientmat            (earth, inst, time) float64 88kB -0.9037 ... 1.0\n",
+       "Attributes: (12/38)\n",
        "    inst_make:                TRDI\n",
        "    inst_type:                ADCP\n",
        "    rotate_vars:              ['vel', 'vel_bt']\n",
        "    has_imu:                  0\n",
+       "    prog_ver:                 10.16\n",
        "    inst_model:               Rio Grande\n",
        "    ...                       ...\n",
+       "    false_target_threshold:   50\n",
+       "    transmit_lag_m:           0.08\n",
        "    bandwidth:                0\n",
-       "    power_level:              128\n",
-       "    serialnum:                134877318\n",
-       "    source_program:           WINRIVER\n",
-       "    range_offset:             0.07\n",
-       "    fs:                       1.92"
+       "    sourceprog:               WINRIVER\n",
+       "    fs:                       1.92\n",
+       "    vel_gps_corrected:        0"
       ]
      },
      "execution_count": 2,
@@ -988,7 +900,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1064,16 +976,7 @@
    "execution_count": 7,
    "id": "67f37e4f-a889-4676-9797-82d7c13fbe94",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\akeeste\\Documents\\Software\\GitHub\\MHKiT-Python\\mhkit\\dolfyn\\adp\\clean.py:90: UserWarning: The 'range_offset' is either already known or can be calculated from 'bin1_dist_m': 0.07000000029802322 m. If you would like to override this value with 0 m, ignore this warning. If you do not want to override this value, you do not need to use this function.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Adjust the range offset, included here for reference\n",
     "offset = 0\n",
@@ -1100,7 +1003,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x24186f3d5b0>"
+       "<matplotlib.collections.QuadMesh at 0x14bd1f07eb0>"
       ]
      },
      "execution_count": 8,
@@ -1109,7 +1012,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1215,7 +1118,7 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>400953.784848</td>\n",
+       "      <td>400953.813014</td>\n",
        "      <td>7.161133e+06</td>\n",
        "      <td>0.57</td>\n",
        "      <td>-0.094245</td>\n",
@@ -1224,7 +1127,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>400953.784848</td>\n",
+       "      <td>400953.813014</td>\n",
        "      <td>7.161133e+06</td>\n",
        "      <td>0.57</td>\n",
        "      <td>0.181185</td>\n",
@@ -1233,7 +1136,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>400953.784848</td>\n",
+       "      <td>400953.813014</td>\n",
        "      <td>7.161133e+06</td>\n",
        "      <td>0.57</td>\n",
        "      <td>-0.143789</td>\n",
@@ -1242,7 +1145,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>400953.784848</td>\n",
+       "      <td>400953.813014</td>\n",
        "      <td>7.161133e+06</td>\n",
        "      <td>0.57</td>\n",
        "      <td>-0.432847</td>\n",
@@ -1251,7 +1154,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>400953.784848</td>\n",
+       "      <td>400953.813014</td>\n",
        "      <td>7.161133e+06</td>\n",
        "      <td>0.57</td>\n",
        "      <td>-0.258352</td>\n",
@@ -1268,35 +1171,8 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>37885</th>\n",
-       "      <td>400989.041693</td>\n",
-       "      <td>7.161150e+06</td>\n",
-       "      <td>8.07</td>\n",
-       "      <td>0.074346</td>\n",
-       "      <td>1.819609</td>\n",
-       "      <td>0.084</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>39093</th>\n",
-       "      <td>400993.719096</td>\n",
-       "      <td>7.161153e+06</td>\n",
-       "      <td>8.32</td>\n",
-       "      <td>0.409135</td>\n",
-       "      <td>0.774590</td>\n",
-       "      <td>0.055</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>39094</th>\n",
-       "      <td>400993.719096</td>\n",
-       "      <td>7.161153e+06</td>\n",
-       "      <td>8.32</td>\n",
-       "      <td>0.230414</td>\n",
-       "      <td>0.237873</td>\n",
-       "      <td>0.038</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>39098</th>\n",
-       "      <td>400992.389563</td>\n",
+       "      <td>400992.412805</td>\n",
        "      <td>7.161152e+06</td>\n",
        "      <td>8.32</td>\n",
        "      <td>0.381595</td>\n",
@@ -1305,31 +1181,58 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>39101</th>\n",
-       "      <td>400991.707623</td>\n",
+       "      <td>400991.734048</td>\n",
        "      <td>7.161151e+06</td>\n",
        "      <td>8.32</td>\n",
        "      <td>0.058718</td>\n",
        "      <td>0.515059</td>\n",
        "      <td>0.152</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39102</th>\n",
+       "      <td>400991.079108</td>\n",
+       "      <td>7.161151e+06</td>\n",
+       "      <td>8.32</td>\n",
+       "      <td>0.520316</td>\n",
+       "      <td>1.154619</td>\n",
+       "      <td>0.084</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39103</th>\n",
+       "      <td>400991.079108</td>\n",
+       "      <td>7.161151e+06</td>\n",
+       "      <td>8.32</td>\n",
+       "      <td>0.194119</td>\n",
+       "      <td>1.282981</td>\n",
+       "      <td>0.123</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39104</th>\n",
+       "      <td>400991.049338</td>\n",
+       "      <td>7.161150e+06</td>\n",
+       "      <td>8.32</td>\n",
+       "      <td>0.203828</td>\n",
+       "      <td>0.322388</td>\n",
+       "      <td>-0.031</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>22018 rows × 6 columns</p>\n",
+       "<p>22009 rows × 6 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "               utm_x         utm_y  waterdepth  east_velocity  north_velocity  \\\n",
-       "0      400953.784848  7.161133e+06        0.57      -0.094245        0.214233   \n",
-       "1      400953.784848  7.161133e+06        0.57       0.181185        0.079026   \n",
-       "2      400953.784848  7.161133e+06        0.57      -0.143789        0.129486   \n",
-       "3      400953.784848  7.161133e+06        0.57      -0.432847        0.519561   \n",
-       "4      400953.784848  7.161133e+06        0.57      -0.258352        0.393507   \n",
+       "0      400953.813014  7.161133e+06        0.57      -0.094245        0.214233   \n",
+       "1      400953.813014  7.161133e+06        0.57       0.181185        0.079026   \n",
+       "2      400953.813014  7.161133e+06        0.57      -0.143789        0.129486   \n",
+       "3      400953.813014  7.161133e+06        0.57      -0.432847        0.519561   \n",
+       "4      400953.813014  7.161133e+06        0.57      -0.258352        0.393507   \n",
        "...              ...           ...         ...            ...             ...   \n",
-       "37885  400989.041693  7.161150e+06        8.07       0.074346        1.819609   \n",
-       "39093  400993.719096  7.161153e+06        8.32       0.409135        0.774590   \n",
-       "39094  400993.719096  7.161153e+06        8.32       0.230414        0.237873   \n",
-       "39098  400992.389563  7.161152e+06        8.32       0.381595        0.560519   \n",
-       "39101  400991.707623  7.161151e+06        8.32       0.058718        0.515059   \n",
+       "39098  400992.412805  7.161152e+06        8.32       0.381595        0.560519   \n",
+       "39101  400991.734048  7.161151e+06        8.32       0.058718        0.515059   \n",
+       "39102  400991.079108  7.161151e+06        8.32       0.520316        1.154619   \n",
+       "39103  400991.079108  7.161151e+06        8.32       0.194119        1.282981   \n",
+       "39104  400991.049338  7.161150e+06        8.32       0.203828        0.322388   \n",
        "\n",
        "       vertical_velocity  \n",
        "0                 -0.010  \n",
@@ -1338,13 +1241,13 @@
        "3                 -0.095  \n",
        "4                 -0.106  \n",
        "...                  ...  \n",
-       "37885              0.084  \n",
-       "39093              0.055  \n",
-       "39094              0.038  \n",
        "39098              0.104  \n",
        "39101              0.152  \n",
+       "39102              0.084  \n",
+       "39103              0.123  \n",
+       "39104             -0.031  \n",
        "\n",
-       "[22018 rows x 6 columns]"
+       "[22009 rows x 6 columns]"
       ]
      },
      "execution_count": 10,
@@ -1394,18 +1297,7 @@
    "execution_count": 11,
    "id": "7902c289",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\akeeste\\AppData\\Local\\Temp\\ipykernel_31724\\3234039020.py:7: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '[0. 0. 0. ... 1. 1. 1.]' has dtype incompatible with float32, please explicitly cast to a compatible dtype first.\n",
-      "  ADCP_points.loc[:,[\"utm_x\", \"utm_y\", \"waterdepth\"]] = (ADCP_points[[\"utm_x\", \"utm_y\", \"waterdepth\"]] - min_coords) / (max_coords - min_coords)\n",
-      "C:\\Users\\akeeste\\AppData\\Local\\Temp\\ipykernel_31724\\3234039020.py:9: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '[0.         0.         0.         ... 1.48387099 1.48387099 1.48387099]' has dtype incompatible with float32, please explicitly cast to a compatible dtype first.\n",
-      "  ADCP_ideal_points.loc[:,[\"utm_x\", \"utm_y\", \"waterdepth\"]] = (ADCP_ideal_points[[\"utm_x\", \"utm_y\", \"waterdepth\"]] - min_coords) / (max_coords - min_coords)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Remove duplicate points\n",
     "ADCP_points = ADCP_points.drop_duplicates(subset=[\"utm_x\", \"utm_y\", \"waterdepth\"])\n",
@@ -1497,7 +1389,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x440 with 2 Axes>"
       ]
@@ -1555,7 +1447,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x241a4281280>"
+       "<matplotlib.legend.Legend at 0x14bea62b640>"
       ]
      },
      "execution_count": 14,
@@ -1564,7 +1456,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1637,7 +1529,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x440 with 1 Axes>"
       ]
@@ -1710,7 +1602,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\akeeste\\AppData\\Local\\Temp\\ipykernel_31724\\3546222366.py:4: SettingWithCopyWarning: \n",
+      "C:\\Users\\ashly\\AppData\\Local\\Temp\\ipykernel_30240\\3546222366.py:4: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -1738,7 +1630,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\akeeste\\AppData\\Local\\Temp\\ipykernel_31724\\14157162.py:29: SettingWithCopyWarning: \n",
+      "C:\\Users\\ashly\\AppData\\Local\\Temp\\ipykernel_30240\\14157162.py:29: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -1861,7 +1753,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x440 with 2 Axes>"
       ]
@@ -1937,7 +1829,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1947,7 +1839,7 @@
     },
     {
      "data": {
-      "image/png": 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ZwXbBiRviAcICkUNEDPFeomsTghfvi1MKUUds8J6g6ByCB6/hoIMOUtsMsF/wOUNjA7ry8FlCGg2RMnRrugXbApGMzx26D9977z21/X379nX1mkLtW3z+UNOFNDU6/KZNm6bShLqJwg34zCFNiHqs3/72t6rLtanTfQqMniFNz86dOxGTVv/HI/PW7PD0uO4ddfnbG4tbenMICcju3bs9S5cuVf8nEpMnT1a/AbikpqZ62rVr5xk/frzn2Wef9dTV1fkti2XeeOMN9feTTz7pOfDAAz05OTme/Px8z5FHHumZP3++tWxJSYnn3HPP9RQXF3syMzM9gwYN8rzzzjvqvmnTpnkKCgr81o31mj/9WNfIkSPVY/v06eOZPn26p0ePHp4HHnjAcXtMbr31Vk/btm09ubm5nvPOO89zxRVXeA466CC/ZV544QW1/enp6Z6ioiLPYYcd5nn99det+w8//HC1b4Lx+eefe8aNG+fJyMjwFBYWeiZOnOgpLS1V9+E39fe//73aN926dfM899xznqFDh3puvvlmv+1/9NFHPUcddZRaR8+ePT2vvPKKdf+qVavUMgsWLLBuW7RokWfChAme7OxsT15enufQQw/1/PLLLwG3EfsZ+9tk+fLlnpNOOkltc1ZWlqdfv36eK6+80lNfX6/ux/8PPvigp2/fvp60tDT1mcBr++KLL/z2cceOHT2tWrUKuJ/0+/zf//7Xs99++6nXiM/WmjVr/JZ7//331X7EtmB/jR49Wn2+Qr3PJl999ZV6z/BeYj1Dhgzx25f1Ll5TsH2L78Itt9zi6dKli3o83ssZM2YEfa/wWcBtn332mXXbM8884+natavaxuOPP95z7733NvouuP1dcXv85iy/ZiLeZ/l9vmyrnDPNG64/ZURXuffUoS29SYQ4wll+8QuKkRE9Q8TLLYjCIJIVyGOJhAYRuiuvvJKO6i08y48pP+JnmQBg7kkIIcFANxfsGGAgiRTbSy+9pIrmYUfgFtQY4UAVKN1JSCJBQUUaCSrWUBFCQoHaHtTPoA0fZ/eof0GxPIqV3YIi+ED+W4QkGhRURMGidEJIOKBAGhEp0vIgXcqUactD2wTSyDahmrYJJAFg+SchJJ5+TyioiEMNFSNUJH7RLfF240lCCImmJhBE447PlB9R6LEzgMaeJJ6Bxw7GXGzbtk39+IVrSkgIIWZkCmIKY2vgYxaOi78dCirSuCidESoS58XQMLpEi/OaNWtaenMIIUlAYWGhNdg6UiioiIJdfiSRgFs2HL6Z9iOERAsi3dFEpjQUVMShy48pPxL/INVHY09CSLzA4oMkZPX2XbJsc0VYj2FROiGEEBI5FFRJRn29R055fKac+Og3UrW3QSSFW5TOlnRCCCHEPRRUSQYiTdsrq2V3TZ2UVO51LcIqbeKL42cIIYQQ91BQJRklu6qtv3e5jFBBTNkDUjT3JIQQQtxDQZVklFY1RKV2VdeFle5LT2ktrVt5b2MdFSGEEOIeCqokw0zzua2h0gXp+VmpkpnmbR1lpx8hhBDiHgqqJCOSCJUWVHmZaQ2CihEqQgghxDUUVElGyS5TUNWGlfLLz0yVzFTvR4LmnoQQQoh7KKiSjNJdEaT8qmusCFUGU36EEEJI2FBQJXOEam+4Kb9UyfBFqFiUTgghhLiHgiqJI1Thp/yMGipGqAghhBDXUFAlGTv8BFX4EarMNNZQEUIIIeFCQZVk7KgKv4ZKD0ZWNVSpOkJFQUUIIYS4hYIqydhRGX4NVbmfD5WuoWLKjxBCCHELBVUSgaiSKaLc1lA5+lAxQkUIIYS4hoIqSU09I/eh8goqRqgIIYQQ91BQJWlBOqhybZvQUEPFonRCCCEkfCioklhQhZ/ySzWMPSmoCCGEkKQQVBs2bJCzzjpLiouLJSsrSwYPHixz5851XPbiiy+WVq1ayYMPPuh3+44dO+TMM8+U/Px8KSwslPPPP18qKyv9llm8eLEceuihkpmZKd26dZO777670fqnT58u/fr1U8tgO9577z2JV0GF1B3YFWaXX0FWmjV6hik/QgghJAkEVWlpqRx88MGSlpYmM2bMkKVLl8p9990nRUVFjZZ94403ZNasWdK5c+dG90FM/fDDD/LRRx/JO++8I19++aVcdNFF1v3l5eUyYcIE6dGjh8ybN0/uueceueWWW+TJJ5+0lvn222/l9NNPV2JswYIFcuKJJ6rLkiVLJB4FVdeibPV/lQsfqpq6esvEkxEqQgghJDK8oYw45K677lLRomnTplm39erVyzGKdfnll8sHH3wgxx57rN99P/74o7z//vsyZ84cGTlypLrt4Ycflt/85jdy7733KgH2wgsvyN69e+XZZ5+V9PR0GThwoCxcuFDuv/9+S3g99NBDcvTRR8u1116rrt92221KoD3yyCPy+OOPO25/dXW1upjCrblc0ru1yZKlm8pVhMrj8ajIXah0H8jNgG0CndIJIYSQpIlQvf3220oEnXrqqdK+fXsZNmyYPPXUU37L1NfXy9lnn62EDoSQnZkzZ6o0nxZTYPz48dK6dWv57rvvrGUOO+wwJaY0EydOlGXLlqkomV4GjzPBMrg9EHfccYcUFBRYF4jD5prj180Xoar3hBZGusMvJz1FUlNaW7P8GKEihBBCkkBQrVy5Uh577DHp06ePij5dcsklcsUVV8jzzz/vF8VKTU1VtzuxefNmJcZMsHybNm3UfXqZDh06+C2jr4daRt/vxPXXXy87d+60LuvWrZPmsk3oUpRl3Raqjsr0oAJWhIo1VIQQQkjip/wQfUJkaerUqeo6IlSoWUKKbfLkyareCam4+fPnB01ptRQZGRnq0pyU+FzSi3MzJDs9RdkmqDqq3NCWCXBJB5ZTOiNUhBBCSOJHqDp16iQDBgzwu61///6ydu1a9fdXX30lW7dule7du6uoEy5r1qyRa665Rnr27KmW6dixo1rGpLa2VnX+4T69zJYtW/yW0ddDLaPvjxd0hKo4J12y070CqTKEdYI5xw9oY09GqAghhJAkEFTo8EMdk8ny5ctVNx5A7RTsDlBAri8oMkc9FVKEYOzYsVJWVqaiWZpPP/1URb/GjBljLYPOv5oar7AAKDjv27ev1VGIZT755BO/bcEyuD0eu/yKstMlNyPF1YBkPccPHX5myo8RKkIIISQJUn5XXXWVjBs3TqX8Jk2aJLNnz1ZWBtrOAN5UuJjAYgFRI4ghHdFCd96FF16oUoUQTZdddpmcdtpplsXCGWecIf/4xz+UJcJ1112n0opIJT7wwAPWeqdMmSKHH364sm1AJ+HLL7+s/LBMa4WWpr7eI6VVXlFYnNsQoQo1ILlh7Iw3QpVBp3RCCCEkeSJUo0aNUv5SL730kgwaNEhZFcC0E75S4QBbBBhyHnnkkcou4ZBDDvETQujA+/DDD2XVqlUyYsQIlTK86aab/LyqIOxefPFF9bihQ4fKa6+9Jm+++abarngBqbs6tPWJSGF2muToCFWIlJ/pkg44y48QQghJoggVOO6449TFLatXr250Gzr6IIaCMWTIEFWTFQzYN+ASr+h0X15GqmSkpkhOhrsaqsZdfoxQEUIIIUkToSIR1k/leP20cnwpv1ADkssbdfnR2JMQQggJFwqqJBNUbXyCCrYJ7nyo/Lv8rBqq2jrlsk4IIYSQ0FBQJamg0im/XS5TfnqgMtKFAFpqbx2jVIQQQogbKKiShB1VdkHli1BVu0z52WqoAAvTCSGEEHdQUCUJOyrtKT9dQxVel196SmvRxvMsTCeEEELcQUGVrBEqq4aqzl3KL8sbocIYH8s6gYXphBBCiCsoqJKthirbfQ0Vis61saeOUAGaexJCCCHhQUGVJJQGKEpXw5EDAGuEWp8ZqO7yAzT3JIQQQsKDgipJKLH5ULmxTdAF6a1bNaQIAc09CSGEkPCgoEqyCFVxGLYJpgcVaqc0NPckhBBCwoOCKglAJEkXn9ud0oMVpZfbOvw0GZagYoSKEEIIcQMFVRJQ6uvwS23dyjLodDMcWRekaw8qTUZqg1s6IYQQQkJDQZUElPg8qBCd0qk7y4eqpk7qfYXnoTyo7Ck/2iYQQggh7qCgSqIIla6fArm+GiqMkNkdIHVn96DSZDJCRQghhIQFBVUSeVAV+TyodKeerjMP1Omnu/wCRahYlE4IIYS4g4IqmUw9cxsEFVJ/OenBvah0l1/AGioWpRNCCCGuoKBKQpd0jS5MrwxQmG6l/ALVUNHYkxBCCHEFBVUyCSqjhgrkWAOSnSNNDWNnbDVUPmPPakaoCCGEEFdQUCWxoMr2RagC1VCF6vJjyo8QQghxBwVVMguqEDVUuii9UZcfi9IJIYSQsKCgSmJBlRti/EygCBWNPQkhhJDwoKBKIh+qxhEqdym/Rl1+NPYkhBBCwoKCKsGBC3ppVU2URem2GipGqAghhJCwoKBKcFAHVecbLVOY7R9pyvGl/JxsEyDEKn2Rq8ZdfixKJ4QQQsKBgirBKfHVT+VlpEpGqlcIaYINSIaYwliaoDVUTPkRQgghrqCgSnBK9dgZW7rP7PLb5ZDy0+m+9NTWVkRKQ2NPQgghJDwoqJIkQmWvn/KLUDkUpQdySfcTVEz5EUIIIa6goEqSCJWjoPJFqCodfKgCdfiZTumsoSKEEELcQUG1L0SoHGqoAnX4+RWlM+VHCCGEuIKCKokjVMFqqCqqnV3S/YvSGaEihBBC3EBBlaQu6aZtgpNTevluZ5f0SIvStXUDIYQQsi9CQZXg7NAu6dnhFqX7Un4ZDjVUPvsFiKSautCi6qOlW2Tgze/Lmws2BFwGvleTHp8pJz/2LcUXIYSQpIOCKsGp9BWXBytK3+VQlL61olr9X5zb+HEZvqJ0t2m/b1ZsV55VrwcRVD9trpDZq3fIvDWlsrFsd8h1EkIIIYlE43wPSSheu2Sc7N5bJymtWwVM+e2uqVNRIXOZDaVeUdOlKCtgDRWAUMrLdJd2nL+mVGrr6iU1pbFOn7N6R8Nzl+2Wbm2y3b1AQgghJAFghCoJyEpPUQaddvRwZKe0H0QN6FLYWFC1atUqrMJ0PZwZI25+3FThuMzsVTsaiTlCCCEkWaCgSmIginRUyj4gOZigCrcwvaTSK6gA0np2PB6P3+36uQkhhJBkgYIqiUGkSUepzE4/DFTWxp5OKb9wzT11hArMXlXS6P7VJVWyzVezBRihIoQQkmxQUCU5uZZ1Ql0jQVOUnWZ5VQWOUAUXVIg+6RoqMGd1qbrNZI6R7gMbd1JQEUIISS7iWlBt2LBBzjrrLCkuLpasrCwZPHiwzJ0717r/lltukX79+klOTo4UFRXJ+PHj5bvvvrPu//zzz1WUxukyZ84ctczq1asd7581a5bftkyfPl09V2ZmptqO9957TxIBK0Jl1FDpLrtA0SnQUEMVPOWHVKJOC6altFLi6pdtlX7LfOcTVMO7F6r/GaEihBCSbMStoCotLZWDDz5Y0tLSZMaMGbJ06VK57777lHDSHHDAAfLII4/I999/L19//bX07NlTJkyYINu2bVP3jxs3TjZt2uR3ueCCC6RXr14ycuRIv+f7+OOP/ZYbMWKEdd+3334rp59+upx//vmyYMECOfHEE9VlyZIlEu/oTj+zKF3XMHUuCCyo3EaodHQKAmxED+97M3tVqWOH30nDuljPb49iEUIIIYlM3Aqqu+66S7p16ybTpk2T0aNHKxEEsbT//vtby5xxxhkqKrXffvvJwIED5f7775fy8nJZvHixuj89PV06duxoXRDpeuutt+Tcc89VUSgT3GcuCyGneeihh+Too4+Wa6+9Vvr37y+33XabDB8+XIm5eCfHYUByMMsEu7lnqAiV6dQ+uldxozqqzTv3yNodVYLa+OOGdBbsdkS0thuF7IQQQkiiE7eC6u2331ZRpFNPPVXat28vw4YNk6eeeirg8nv37pUnn3xSCgoKZOjQoQHXWVJSogSVnRNOOEE9zyGHHKKWM5k5c6YSbiYTJ05UtweiurpaiTvz0hI4DUheH6LDzzT3DFWUbjm1Q1D1bGPVUWl0d9/AzgVSlJMu7fMy1HWaexJCCEkm4lZQrVy5Uh577DHp06ePfPDBB3LJJZfIFVdcIc8//7zfcu+8847k5uaq2qYHHnhAPvroI2nbtq3jOp955hklhLp27WrdhscilYgaqXfffVcJKqTzTFG1efNm6dChg9+6cB23B+KOO+5Q4k5fEG1rCZwGJGsx07UodMovZISqskFQDe9RKKmtW6mU3vrSKr9o1Sif2NIijtYJhBBCkom4dUqvr69XEaqpU6eq64hQoWbp8ccfl8mTJ1vLHXHEEbJw4ULZvn27imBNmjRJFaYj2mSyfv16JcxeffVVv9shvq6++mrr+qhRo2Tjxo1yzz33qKhVpFx//fV+60WEqiVElVOESqf8OgeLULk09tSWCRBUEG8DuxTIonVlqm6qa1G2zPHVU43uVWQ95/y1ZSxMJ4QQklTEbYSqU6dOMmDAAL/bUL+0du1av9vQ4de7d2856KCDVAQqNTVV/W8HtViok3IjksaMGSMrVqywrqOmasuWLX7L4DpuD0RGRobk5+f7XVqCHF1D5StKR5G5nuMXLOXn1tizxFdDVeQbzjymVxurML2saq8s21LhH6HyRcUYoSKEEJJMxK2gQoffsmXL/G5bvny59OjRI2RkC/VLJugog6D6wx/+4FdsHghEvCDoNGPHjpVPPvnEbxmkFnF7vJOtu/x8RembyvZYxp1OA5XDNfYs9QmqYt+6tHBCqk/XUu3fLkeKc721U12Z8iOEEJKExG3K76qrrlK2B0j5IY03e/ZsVXSOC9i1a5fcfvvtKuIE8YOU36OPPqq8q1DIbvLpp5/KqlWrlGWCHdRkoRsQKUXw+uuvy7PPPitPP/20tcyUKVPk8MMPV7VWxx57rLz88svKD0tvSzyTY/OhsjyoCrMadTo6dvmFsE2wIlSWoPKm9n7ZtktmLNmk/tbdf34RKqb8CCGEJBFxK6hQy/TGG2+oWqRbb71V2SY8+OCDcuaZZ6r7U1JS5KefflKCCGIK6Tw85quvvlIWCiZIAUKcwZjTCdggrFmzRqULscwrr7wip5xyinU/Hvviiy/K3//+d7nhhhtUofybb74pgwYNkkTxodKjZ3SHX7D6KbPLrzpEUbo9QlWYnS59O+SpVN9bCzf61U+Zz8sIFSGEkGQibgUVOO6449TFCXT1IZrkBoihQKDA3SxyDwSiXvbIVyJgFaX7uvx0ZChYh58ZoXJr7KkjVGB0rzZKUNXVexpHqHyCaufuGqmsrrVG4xBCCCGJTNzWUJEY2yb4IlQ6MhSsID0s24Qq/wgVGOUrTNfPYz5XXmaa5Gd6t4leVIQQQpIFCqokJ8cnqHSEys0cP7dF6bV19VJWVdM4QuUrTFd/G+KqUdrPZR1VxZ4a+XFTyxijEkIIIW6goEpydMoP6TW3c/xAhhWhCiyoynZ7xRRq2wuzGronOxZkSvc22X5dfyY63ajruUJx9auL5JiHvpLv1+90tTwhhBDS3FBQJTkNw5HrpL7eY9kmhIpQNRh71oesnyrISpPUFP+P0g2/6S8nHthZfntg50aP0ylAtym/JRu8QmrJRgoqQggh8QkrgpOcbG2bUF0r2yqrZW9dvRpU3DE/M+jjGow961wNRrZz9KCO6uJEONYJNXX1sqXcKwJptUAIISReYYQqydFddHA8X7vDO18PYsoeUYqkKN0SVD6XdLeEY52weece8TULsoidEEJI3EJBtY90+YHlvjEwodJ9IFOn/CKMUAXDGpDsIuJkii63NVeEEEJIc0NBleSkp7aWtBSvI/rPWypdWSaYRenBjD0jFlQ+QbelYo9K6QXDFF1M+RFCCIlXKKj2ocL0sCJU2im9CSJUbXMylNDzeLwpPbcRqs3le5RVAyGEEBJvUFDtA+T40n7LfRGqUGNn/Gb5NUGEqnXrVtK5wFsUvz5E1Mmsm4Lz+tYK/8HXhBBCSDxAQbUPdfptr6x2nfJrKEoPHKEqrYpMUJlRslCF5vbCdc4AJIQQEo9QUO0DZNvm5YWa42em/GrrPQHTbCWVjef4hV2YHkpQ+SJY6b6uRNZREUIIiUcoqPYBcn1u6Ro3Kb8MX8oP7KmtDxqhMuf4uaVLYXZIgeTxeCzBdWC3Qu/yjFARQgiJQyio9jHrhKLsNL/roZzSQbVD2g9ip8RXQ1UUpg8V6FyYGVIgYf3wz8JomxE9i0IuTwghhLQUFFT7ADm+Giq3HX66cBydeIEiVBhls9d3e3Fu09RQ6ehVh7xM6VkcOqJFCCGEtBQUVPuQbYLbgvRG5p4OESrd4YdIVpavgD0cuuqUX9luFe1yQkejIL6sFCEjVIQQQuIQCqp9TlB5hYkbtLlnMEGF+qlWyMmFSceCTJXKQ0pvu6+43Y6ORqHmy0oRlgYWYIQQQkhLQUG1D9kmAC1M3NBg7lkfUFBF0uEHkE5sn5cRNOpkRaiUoPJG1nbX1ElZVU1Ez0kIIYQ0FRRU+wA5RhG6G8uExuaegSNUkXhQ2dOPgeqozJQffLHa5gYXYIQQQkhLQUG1DxBpyi8zyDy/mAiqouCF5vr2Lr6omi5kD+WuTgghhDQ3FFT7ADkZ4Xf5mSk/xwhVVeSWCW7NPTfu1IIq209YhXJXJ4QQQpobCqp9AO07BYEEHyq3aHPPPQ4DkkuNovRI0QLJKeK0q7rWqpXSItCtuzohhBDS3IR2eHRBTU2NbN68WaqqqqRdu3bSpk2bWKyWxIi2Pp+oXm1zw+rIs4rSHVJ+lqlnFIKqaxtv5GnVdu/QZhMtmgqy0iTXl7K0BBVTfoQQQpJFUFVUVMh//vMfefnll2X27Nmyd+9e1c6OA3bXrl1lwoQJctFFF8moUaNiu8UkbDC25bbfDpShvvEtsbBNiEWEamhX7/b8sm2Xqsky67FMy4RGNVeMUBFCCEmGlN/9998vPXv2lGnTpsn48ePlzTfflIULF8ry5ctl5syZcvPNN0ttba0SVUcffbT8/PPPsd9y4hqI3LPH9pQhPgETdpdfE9gmAAioPu1z1d9zVu8IaJngtiuQEEIISagI1Zw5c+TLL7+UgQMHOt4/evRoOe+88+Txxx9Xouurr76SPn36RLutpJnJcFGUHk2ECozq1UZ+3lopc1btkIkDOzYSVKbNgxZUSDfu3lsnWYa/FiGEEJJwguqll15ytVxGRoZcfPHFkTwFiQMafKj8I1S1dfVWwXg0ESowplcbefG7tTLbHqGyLBMaBFV+Vqqqp6qsrlWCq7cvukUIIYQkfJcfIlHPPfecdX3NmjUyY8YM2blzZ7SrJi1Mg1O6f4SqbLdXTKG+vTDLfdegE6N6ehsYfthYroSSPUJl1lAhdclOP0IIIUkpqN577z3p16+f+rusrExGjBghJ554ogwYMECWLVsWi20kLYQ29rRHqHT9FDrwUlOi+whBMEEk1dV7ZP6aUut2XSdl983S11lHRQghJKkEFSJRXbp0UX//97//lY4dO0p5ebn8/ve/l+uvvz4W20haiAbbhLqYu6Tb035mYXpNXb1sKd/TKOUHzCHJhBBCSNIIqm7dusmqVavU39OnT5dzzjnHqp365ptvYrGNpIUIZOxpCaooXNLthengu1VeQbV55x6p93gHKNuL3rVrOlN+hBBCksrYEwLqiiuukOOPP14++eQTeeSRR9Tt9fX1UlnZ2LCRJA6BjD1jHaEa7RNUC9eVqXot7ZyO6FTr1q0cU36MUBFCCEkqQYW0Hgw9P/zwQ7nzzjuld+/elrVC9+7dY7GNpKVrqAJFqGIkqPZrm6Pc3LdX7pXF63c21E/Z0n3mbYxQEUIISSpBhc6rv/3tb+piglE0Z5xxRrSrJ/GQ8mviCBU+Q+j2m7Fks8xetUMVqIcSVJvL9yj7hmiL4gkhhJBYEPHR6KabbpJ58+YFvP/aa6+VG2+8MdLVkzhK+dmNPWMtqEz7BAgqp7EzmvZ5GZKW0kqJri0V1TF7fkIIIaRFBNX69evlmGOOUXP7LrnkEuU9hXl+JBkjVP6CqrQq9oJK11HNW1Mqa3dUOVomANRUdSpgHRUhhJAkEVTPPvusSuvBNT0vL0+uvPJKadu2rZx88snyr3/9S3bs8He+Jols7Omf8iupjH6On53+nfIlz+eCPnfNjoApP/N2elERQgiJF6IqQGndurUceuihcvfddysTz++++07GjBkjTzzxhHTu3FkOO+wwuffee2XDhg2x22LS4saepTGa42eS0rqVjOhZpP6uqfM0muNnolOBLEwnhBASL8S0ord///7yl7/8RflPrVu3TiZPnqwGI7ud/UfiU1CZxp7o6MRwYlAUIx8qex2VHmvTId9r4mlHpwK1vQIhhBDS0jRZi1S7du3k/PPPl7feekv+/Oc/R7QORLbOOussKS4ulqysLBk8eLDMnTvXuv+WW25RY29ycnKkqKhIxo8fr6JkJj179lRdZOYF9g4mixcvVpG2zMxMZVSKiJsdmJbiubAMtgMjd5KdjNTWjWwTqvbWyV5fCrA4N7aCSjumgw55mcrY04mujFARQghJdEFVWlpq1Udt27ZNXn/9dfnhhx9ivmF4noMPPljS0tJUwfvSpUvlvvvuU8JJc8ABBygj0e+//16+/vprJZ4mTJigtsvk1ltvlU2bNlmXyy+/3LoPY3LwmB49eqiuxXvuuUcJtSeffNJa5ttvv5XTTz9dCcQFCxaoWYW4LFmyRPaFCBVScNrKQHf4QWxl+e6PFYO7FlgiyqkgXcN5foQQQuKNVh7kcFzy9NNPy9SpUy1bhBdeeEGGDh0qX375pUyZMkUuuOCCmG3YX//6V5U6RMrQLRBHBQUF8vHHH8uRRx6pboPIQsE8Lk489thjykMLBfbp6enWc7/55pvy008/qeuYS7hr1y555513rMcddNBBcuCBB8rjjz/uuN7q6mp1MbcN0S/MPszPz5dEoGpvrQy46QP19/DuhdK6VSsVoVq6qVw6F2TKt9d793Es+f0TM9UImhOGdpZ/nj7McZlV23fJEfd+LqmtW8mB3Qr9OgDPHddTjhncKeD6P/xhs3y2bKvcfPxASzDa2b23Tm5+e4kcPaij/Lpfh6hez67qWrnl7R/kN0M6yRF920e1LkIIiUfu/WCZzFpZ4ncbfo8vOKSXTBjYURIdrS1CHb/DMvb85z//qaJRu3fvVi7omOGH1B6e5PDDD4+poHr77bdl4sSJcuqpp8oXX3yhBjD/6U9/kgsvvNBxeVg2IKqEFw2RZ4IU32233aa2GWajV111laSmel/6zJkzVfG8FlMAz3vXXXepKBkiYljm6quv9lsnloHoCsQdd9wh//jHPySRyUxNkba5GbK9slrmry3zu2//9rlN8pxHDeigBJUplOxgQHJhdpqUVdXI3DWlfveV764JKqju+WCZ/Ly1Ukb2aCMnj+jquMxbCzfIq3PXy5IN5VELqjcWbJDp89bLsi0VFFSEkKSjrGqvPPLZCsf7MOg+GQSVW8ISVBAhqGXCBSNmIKYARAxqk2LJypUrVfQIQuaGG25Qo2wwMxDCB8XuGkSNTjvtNKmqqpJOnTrJRx99pOwbNHjM8OHDpU2bNip1h1E5SPvdf//96n5Epnr16uX33B06dLDug6DC//o2cxncHgg8jynCdIQqkcAZxtuXHazGwfjd3gr1TsVN8pznHdxLeVIN6JQf1B/r7UsPUZEyzbbKarnxzSVBvakQjNWF7HNW7wgoqGAuGqsaLWtdLKAnhCQhOLHVZSAPnebNKqzYWiH3frhcdvru21cIS1ClpKTInj17VGE2okaaphiCjOHKI0eOtFKMw4YNUzVLSLGZguqII46QhQsXyvbt2+Wpp56SSZMmqcL09u290QBT1AwZMkQJsj/+8Y8qgpSRkSFNBdbdlOtvLmBR4ORY3pQibkjXwNEpTffibHUx03QQVBXVtbJzd40UZKU1ekxpVY3s9nUsaqHjBCJkAOuBL1ZuRmQTmiDg9POgMxLbmJUe27ozQghpSSr21Kr/C7PTVJkE+GFjlhJU5b779hXCKkpHbRIECawRTLGA6JBZxB0LEG0aMGBAI1uGtWvX+t2GDj9Ey1DT9Mwzz6goGv4PBHyyamtrZfXq1ep6x44dZcuWLX7L6Ou4L9gy+n7S8kCoaOf2QNEg8/aV23fJNofRNYhKmZGpaCJLiIZh5qC5bkIISSYq9nijUPmZDSex+m99375CWIIKqT2YeT744IOqbgqcc845kpubK6NGjYrphqHDD2ahJsuXL1fdeKEiW2YxuB1Es/AadARr7Nixqqi+pqbhjUfasG/fvlZHIZb55JNP/NaDZXA7iR+0g3og4WK/HWk/O3NskasNZd4xOJFgj4KxK5EQkmyU+0RTXmZqI0GFKRvVhu1OshORDxVc0CFMwL///e8mSfmhcHzWrFkq5bdixQp58cUXVRTs0ksvVfej6w61VVhmzZo1yvLgvPPOU95VKGQHKCaH+Fu0aJGqyUJXItYLbystllCkjqgbLBFQcP/KK6/IQw895JcqRAfj+++/r2wb0PkHWwX4YV122WUxf90kckKNpLELKqe032ybyNpQ1hBhChf7+hmhIoQkGzqtl2dEqHINcaVTgvsCEQmqa665Ro4//nhlhgkgVGbPnq26/2IFIl5vvPGGclkfNGiQ6tKDODrzzDOtei6IG8wOhB8VtqekpETZLAwcOFAtg7Tkyy+/rDoQcdvtt9+uBJWZnkTU7cMPP1QdiyNGjFCv7aabbpKLLrrIWmbcuHGWoEMH4WuvvaY6/LBdJH4INZJGp++08HIUVL7brGhXFCk/HQGLxboIISQe0YIp36hbxSgxXXu6LwmqiKptYYwJkfK///1PeUU9+uijypcKnX6oZ4LogEcT/j/mmGMi3rjjjjtOXZxAYTxMRYOB7j5EsEKBYvVQfleIeunIF4lPtOFnwBoqX/ruxGGd5dHPfpEfN5ercLUOT5dUVsuKrd5o6wkHdpbHPv8l4qjS1oo9qk4Lza/HD+0sj38R+boIISRegVWNPeWnr6OpR9+/LxDx6BmIEBhi7r///kq0VFRUKLdyGGginYaRM+i4I6S50JGg9QGEy0Zf+m5YtyLpUZwtsLSdt7rBx2qO7+8DOuTKoM4FvsdEJoLm+tbVr2O+9O+Up/6moCKEJG2EKtO/s7qhMJ0RKtf8/PPPfh10uGjCMGEnJGq6hhhJowUNIlmje7aRNSVVqmbqiH7t/VJ08MEKFe0KhU4dYj6h3i6m/Agh+0JRunld378vEFGEym5dEAht9olCcUKaq4YKdgh7fH5T5hgdPYcQYmmUbxCz2dWnBdWonm2saNeWij3WMOhIBJV3XV6/LFgo1NaFvy5CCIl/24RUR0G1L1kntI60YBzmmHAvDwRsFWC0icLt//73v9FsIyGuKMpOswY2b9rp352no1Z5GakqFI0IFVi0vkyJL+T6l2zYaUWoinPS1aBmBFk329YVChiCoj4LjOpVJO3yMtTcQQyY3uLgfUUIIclUlG5eZ8ovBEuXLlUdc0cddZQqDkd3HKwU8Dfm3+F+WBCgKPzuu++W3/zmN7HfckIcIqKIPqGwHOm1Xm1zGtkf6FQeaqja52XI1opqWbiuTEWh6j0i3dpkSacC7zKIUmEQM1KFpit7KOavKVVCDM/fPi9T3dapMFPW7dithJ2OfhFCSNKn/HYzQhWU4uJiNQsPM/EeeeQR6dOnjxr9ouupYG0AXyj4QFFMkXjworJbJkB86bQf0nNmis6+rnCLyfXomlE9ixqvi3VUhJAkosLBh8q8vi+Nn4mqKB1Dkk855RR1ISSe6qjsnX7aMsGcS4iC8XcXb1K1U3D01bc1rCszIhHUUNxe7NojixBCEhF2+cWwy4+QeCJQR50VofLdb0aj5q0plVrk+xpFqLLDHj+DeqzF68vU37pOS22XFnqMUBFCkgR08gfzodrXuvwoqEhS0ZCmq3L0oDLrl/p2yFOdKTok3TY3w6/uSosv/Vg3LFhbJjV1HumYn6nqsRqvi4KKEJIc7Kmpt05G8wMWpe87gipiY09C4hHLP6pRyq9xhKp161Z+EanRvYosqw+1bARpOqsWq1cb27p0tIuCihCSHOjoU+tWIjnp3g7rxkXp+07Kj4KKJBW6VglWB7ApAPB+ggcUsHfYwSLB+tsQV+ayEEH1vnWFwjQH9d+uhnosGt4SQpIBHX3C3L5Wxgmk6UtVUb3vRKiY8iNJRYe8DDWYE2k3GHx2LMhU3k8QV+kpraVdbobf8rrTz/43wGPxGwFLhe27qi0LBM3U936Up75aqSwS7NjFmRZ6u2vqpKyqRopy0oO+DojASU/MlMLsdHn2nFEBl0NR/c1v/yAPnz5Mxu7fUARPCGl5cPJ08X/mSdXeOpl2zihJTUmsGMbHS7fIX1//Xu49dYj8qq93ooSJLpewp/uauih9xveb5KpXF6qUo52XLjyoxX4LY/LuYrDwWWedJWPHjrVc0f/973+r2X6ENCf4wUL9kllHpQvS4QWFNJ/J4C4FMqhLvgztVqjm7pnA2LODT0TZ66gg0F78bq2jmBrYOV/6tM/1uy0zLUXVaLlN+63dUSXz15bJpz9tVUahgZixZJNsr6yWL5ZvC7lOQkjzgukMH/ywRb76ebv8sNFr9ptIfPDDZvX78vky59+XhoL0xoIqzxBUsY7Kz1iy2VFMJXyECi7oZ599tvKeWrBggVRXV1tO6VOnTpX33nsvFttJiGtQJwXRgo66ET0ahJWToWZaSmt55/JDg64L6UKIsgO7FVq3/7ipXLmro07g02t+pWoINEXZ6Y2Em14XfpywXYO6eIcvB8IUXXjuAoczQHO5Ut9YHUJI/GB+j1EOgBO3RNx+PbYrsAdVYymhb8PJJyJ0ORmpMd+uu04eLOP7d7A9r/NvZUJEqP7v//5PHn/8cTVmJi2t4YUcfPDBMn/+/GhXT0gU5p57/CJUpgeVWzoH6BrU5p0je3hHyxTnNlycxJR3uzJdR6jMbsBgnYH6vhIKKkLiDvO7q38zEnH7QwkquwcVyE5PUeUXTZH209t1QIc8v99eXJBZaCmifuZly5bJYYcd1uj2goICKSvz+vEQ0pLWCdbYmQgEVSCHcz1U2TTvdLsuN9YJ5vMFEmCo7cLoHFBaRUFFSLxh+s7NXb3DdXNLPIBt1SelgQRVeYDByABF6k3hRVVTVy9bAjQZtTRRC6qOHTvKihUrGt2O+qn99tsv2tUTErl1gu/HzMkyIex1GTVUqAdo6OYrcr+uMMbPmE7vgQTVpp3oGJSgP3iEkJbD/O6WVtXIim2VkiigPGFvXX2ICJWzqadG3x5LLyp0cEOXoslI16UmjaC68MILZcqUKfLdd98pRbpx40Z54YUX5M9//rNccsklsdlKQsLA7h+1obTKz608HPRjzB/GX7btUim2jNTWMriL+5qILkXuvajcRKjMZSioCIk/7CdP2qcuETBP6nZU7XUsLNceU05dfmYqMJZeVDrqByuaQOUVLUXUVWJ//etfpb6+Xo488kipqqpS6b+MjAwlqC6//PLYbCUhkdQ9+TyftCCJqobKJ8rMH8Vh3QvDytd3DqeGaqd/UboT5nrQCYhQOIrsCSHxgf4eD+laIIvX71S/HWcd1EMSAbM0AeUFu/bWKb+pSCJU5TGMUG2MIuPQ1ET964uo1N/+9jfZsWOHLFmyRGbNmiXbtm2T2267LTZbSEiEESr8AKwuqbLaa2GbEPa6fF9a+K3oHw+n4cdu6OpzS0c0affeuoDLoStmk5FiDBihst0OfytCSPygT4ZOPLCL+h+CKlGMfe0nck6dxMGK0pvKi8o6QS5IQkGlSU9PlwEDBsjo0aMlN9ffg4eQ5iQrPUWKfcaZuni8fV6GZKT6j0ZwA87ItGWBLtDUESq7eWco8rNSrTO8YFGqrRV7rPlYAAalGLoc6gePaT9C4oeqvbWqbgocN6STpLZupSxYEmVAuv03yqmTWEeeAlkV5OmUXwwjVE6D7pMm5Xf11VcHjFxlZmZK79695be//a20aRPewYeQaMCXDT8AulU5mi8fIl5IqaFrMCcjRf3Q4MdxeI/wPGXwncC6lm2pUOvobTP/tP9gdPX5ViHChkLMnsbgZqcfPAoqQuIH/T1G2qt9fqYM7lqghqfjhKxbG2+0OlkiVKGL0mtjt1065RdnHX4xEVQw84TfVF1dnfTt21fdtnz5cklJSZF+/frJ//t//0+uueYa1fWHCBYhzQHCwahZ0Om5SOqnrHUVZsnSTeXqB0a7lg/sUiDZ6eF/fVBHpQRVkLNU8wcDhe8ogsdtdkGlawnSUryjdiioCIkf7Ad+RLS1oDp5RFdJlO3Xvy8lwVJ+gYrSs3TKjzVUrkD0afz48aq7b968eeqyfv16Oeqoo+T0009Xo2hQqH7VVVfFZosJcYH+smGES6QdfhpEinTXy+xVpervMba5f+FuVzAvKtPmweoMtAkw0yOmb8c8qxOHEBKngsr3m6FP8hJl+/Xvi1OEqmH0jPPJpfanilWXn9lkFI8RqqgF1T333KMK0PPz8/1MPW+55Ra5++67JTs7W2666SYltAhpLuxftmhTfgACZvaqEvX3qDDrpxrWFdo6wUr5FWZZz222MJseMega7u+bQbijkoKKkHjBXuszskcbNWx95fZdqk4ynkHNk44+DersHZNlj1DhpK5yr9uUX01Mtmt75V6prq1X+7FTMhalY2bf1q1bG92OTr/ycu8wyMLCQtm7lz/2pPmwp/ii6QjR61qyYadKv4FRPYsiXJfPOiFIyk9Hr/C8elyNPaKlBRYGQbfP95rb0S2dkPjBSk35fj8KstOkbwdvtGfuam+kO17Rv09F2WlWhN4eoYKY0g2Lobr8ymNUQ6VPRNFk1JIjZpo05XfeeefJG2+8oVJ9uODv888/X0488US1zOzZs+WAAw6IxfYS4gr9IxCTCJXvsau2e8UUfhQLs9Oj2q4NrlN+zu7q5tkvhjEDzvMjJH5wmtCg037xbvBp1ikV5Tj/vuh0HxzLM9OcO6h1l1+sIlR2kZp0RelPPPGEqo867bTTpLbWq0JTU1Nl8uTJcv/996vrKE5/+umno99aQlow5Wf/UYwm5Yf26dq6ekm1GXGqGoFSsyg9xVGAmT8sxbnpAWscCCEtg9NQdvx2/GvmmrgXVGadkragsUfAGwrSA8uI/KzYdvlFM+g+IQQVPKeeeuopeeCBB2TlypXqNszwM72oDjzwwGifhpCwKMxOU9POq/bWqTx+oJC0G9rmpqvwMtyCwagoBBVC1bprZktFdSOxhi5CGJLqH40M35kf5vahZkGPWjDd3xmhIiS+wNQCnDTZG2K0d92Pm8vVd1173MUbpnDRvy/2LuKGgvTAryHPGj0TmwhVNHNZm4OYJSHXrl2rOv1Wr14tn376qbz99tvqQkhLAM8nfRYTbXhY+0dpwjX0NIEg6lgQuI5K/2BAxCGM3iEvQ1JaewXYtspqx5RfcY6vhoqCipC4YEu58wBf+FH1LM5WtUfz18RvHdV6hwi4XVCF8qAy78NJIiZARIv+fYymazuuI1SISp100kny/fffqwOPttXH3wD+VIS0BPgxWLG1Mib5dqwDNVTd22Rbgiiada3bsdvROsFM9wGkBFF4jh8SOCx3yPefB4jlinLSrB88fP/0d48Q0nTgu4bvMeoi7UN6NwQZ4IsOYYzEevf7TZJjzMbLSkuRgZ3z42Lgr/5twmvTESr7vNCKam/UKVj0P88QW5V7alVhfrK6pMckQjVlyhTp1auX6vSDRQLm+X355ZcycuRI+fzzz2OzlYREgP7SxeLLZ/eSiW5d2X4eWaFC2vq5zToq60zNiFDBRkGnCwkhTcv0eevlsHs+k2e/WdXovmAD2fVvyGvz1sukJ2Zal+Mf+Vqe/tpbNtPSNJzYZasGHH2OZs4L1d5SwSJUGakpypxYLR+DwvRoBt0nhKCaOXOm3HrrrdK2bVtp3bq1ckg/5JBD5I477pArrrgiNltJSARMGtlN/XidPDx6V+Kzx/aQQ3q3lYsO2y/qdfXv5G2dXriurNF91pmtYfNgNwM1PWLww4LZhZlp3q8yvagIaR5mfL/J+/+SzSEjzSYTB3WUg3sXy35tc6xLB5/1ycc/NrYgam6qa+tka0W1FWFDyUGhr9bLTPvpzr1ggiqW8/wqq2utSRVJ2+WHlF5envcAAVGFOiqMoOnRo4csW7YsFttISEQc2K1QXv3j2Jisa1CXAvnPBWNisq4xvYotx2TUFeAHS7NxZ+MIld27yvSI0eNvEKXC2Rvc0rsXx/+cMEISGXxvtZfU4vVlani5aR3g9D3WIEX2wgUH+d32y7ZKOfK+L9RJFgRNJIPcY8Um3wQGnKS18XX44X8MevYXVL4uvxANP/lZqcqIOFq3dH1CCff1YIXwLUnUEapBgwbJokWL1N9jxoxR7ujffPONilqh248Q0jhClZOeon6Qlm2uCHlma3dXd6ojaKijaihcJ4Q0DT9tLpeKaq9AQMMIZvSZoN4xnEgKolRoREEnMWaQtiRmfaaux9TCyhRUOuIUStzkxciLquF3L35PGKMWVH//+9+lvt7bTg4RtWrVKjn00EPlvffek3/+85+x2EZCkgoUmo/o6TzXy7GGymbuqc9+zbRgG18d1Y5dsRtCSghxxu4jZb8e7rw5CBc9zqqlPaqc6pQsQWV4UZW78KEy5/lF60XV0HkYXVNQXAuqiRMnyu9+9zv1d+/eveWnn36S7du3qyL1X//617HYRkKSjtG+0TXmjyfSBphV1ThC5V9D5RShauPrnmGEipCmR58I6ckH5okRuv9Mp3G3xIuLujVLtMhBUBk1mm58qPzHz8QoQhWn9VOgSYbhtGmDIZAt3/pJSLxinY2u3mFZjegfYaQDTcM/XUNV4SvKND1iNIxQEdI84PuqRc/Fh++v/p+3plRZCui02J6a8Af46t8ErCsWnk2R4hRda+Pglu7Gh8p/QHJsaqji1TIhZoLqk08+kRtuuEEuuOACNdfPvETDhg0b5KyzzpLi4mLJysqSwYMHy9y5c637b7nlFjXWJicnR4qKimT8+PHy3XffWffDZBQzBWHrgMfvv//+cvPNN/sNasYyEH/2y6xZs/y2Zfr06eq5MjMz1XYgpUlIpAztVqhM/7ZVVCtPGnu6zzwhQeG5/kHDWZrzGSQjVIQ0B/CjQyQZ0xNOGdFVnfzsrqmTHzaWRzXAt3+nfMnLSFXdbD9u8q6rJXCs0XSYxqBrokIXpaf5LZ+slgkxEVT/+Mc/ZMKECUpUIdVXWlrqd4kUPPbggw+WtLQ0mTFjhixdulTuu+8+JZw0GLj8yCOPKFPRr7/+Wnr27Km2Zdu2bep+pB9R34V5gz/88IMaj/P4448r8Wfn448/lk2bNlmXESNGWPd9++23cvrppytxtmDBAjX0GRd4bhESCegIGtqtQP09x3e2G2xOlZn22+hY48AIFSHNgY5OoYsY3+NRVvq+JKp5c+j2HeFb13ctmPZzqtF0mhda7jZCleG9P9ouv0RI+UVtmwCB8txzz8nZZ58tseSuu+6Sbt26ybRp06zbEGkyOeOMM/yuYxjzM888I4sXL5YjjzxSjj76aHXRoOsQVg6PPfaY3HvvvX6PRRSsY8eOjtvy0EMPqfVce+216vptt90mH330kRJzeP2ERAJqJuasLlU/npNGdQtayIrbvt+wU1aX7LI8YvxD8oxQEdIcIE1vjqDC9xj+UbNXlcpFh4VfkG6CdX2+bJs6yTr/EP/jXXOAeaHaNsEpQrUjgghVnk75+ZzVIwHdj1sqGm9X0kWokD4bN26cxBrMAYTb+qmnnirt27eXYcOGqSHMwbbjySeflIKCAhk6dGjA5Xbu3KlqvOyccMIJ6nlgSmqfQQjzUqQT7cX4uD0Q1dXVUl5e7nchxKlmQhe0Bhv8qW/Ty5oeMWaECl4xhJCmj1DpInLzewxBEs0A39HGunRtZXOCeaGYuIBoGUZeafQ0Bi2oIHBQJ+aqyy9Lp/xqo5qNiN2BFGpb37YkpaBC3dSLL74osQYzAhFJ6tOnj3zwwQdyySWXKOf1559/3m+5d955R3Jzc1VtE1J6iBzBYNSJFStWyMMPPyx//OMfrdvwWKQSUSP17rvvKkGFdJ4pqjZv3iwdOnTwWxeu4/ZAwCke4k5fEG0jxGREjyKBpydG0GzeuSdoSFunDxDR0suYdVY6QlViDFAmhMQWpNvhMYXv7fAeRZbpL+bwoWHk562VUaWmBnctUKNaUKv0y7Zd0txo/yyIKdi7NPK5q/LOCzXroXKNeYRBndJ9XYHRbFfngsazERM+5Xf11Vdbf6NGCZEh1CANGTJE1TzZ03CRgPUiQjV16lR1HREq1CwhxTZ58mRruSOOOEIWLlyo6rcQwZo0aZIqTEe0yV7gjrQdIl4XXnihdTvEl/l6Ro0apdze77nnHhW1ipTrr7/eb72IUFFUEfsPzYDO+bJkQ7lKI4RK+ZlniPb6DB2hQl2DOcCUEBI7dIQYIkoLCXzXhvcolG9WlKg6qmhSfnBIR20WygAQCevdPleak4b6TH+vJ2teaK13XqiONmWnp/gJr6bq8osm6hf3ggqF2SYHHnig+t9epB2NdUKnTp1kwIABfrf1799f/vvf//rdhg4/+F/hctBBB6mIFuqoIGg0EEgQXkhNQvyFAo7viHRpUFu1ZcsWv2VwPVDNFcjIyFAXQoIxumexElSzVpaoKFWgHw2zo8/pOjqN8HVDWBytze3z4tf8jpBET/fpNJ/5PVaCanVp1O39Y3q1UYIK4u2MMd2lOQkkBvW8UKT5UJhe7rJ+KlY+VIlQkB6xoPrss8+kqUGHn30W4PLly9WMwFCRLdQvmZEpiCl07aHAHQOcQ4GIFwSdZuzYsaqL8corr7Rug+DC7YREw+heRWpa/ftLNkttvUdSW7dyFEP2HxL7ddQ8oHAUEazSXTUUVIQ0o6Aa1cub/vtmxXarjjHSg/+oFjT4dLJM0Oh5oUhH7qp21+FnLqO7AiPBEqm+MVxJ2+XXVFx11VUqooSUH9J4s2fPVtElHWHatWuX3H777SotB/GDlN+jjz6qBBTSegB//+pXv1IiDF192k4B6OgSarLS09NVShG8/vrr8uyzz8rTTz9tLTtlyhQ5/PDDVa3VscceKy+//LLyw3IT7SIkGPqHWafyOvmmu9spzE5TdRrwuwnUko1hyVhPier08w4sJ4TEBny3UCMFtFWCZli3IklLaWV9j/OiGOA7vHuR+g2AeFlfWiVdm3F2XTCvJ9RR4X5EqDDA2Sw4D0a+bxlvIbv/EOnwtyu+TxSjLrRA8TUEiB3cBuuDSEEt0xtvvCEvvfSSGsAMq4IHH3xQzjzzTHV/SkqK8pk6+eSTlR/V8ccfLyUlJfLVV1/JwIEDrSgSCtERXeratasSXvpignUjgoVU31tvvSWvvPKKnHvuudb9EHYovIeAQgfha6+9Jm+++abaLkKioTg3Q/Zvl2NdN71f7Olzv/l+Dj94us4BESpCSNPUT6GuCd9be0pscBevr1y0qamcjFQZ1Dnf7zmbi4ZIUOPt13WaiFBpTyk3Eapco2g90jqqpK6hMoFpplOXH0TNaaedJtddd13E6z7uuOPUxQl09SGaFIxzzjlHXYKBAnezyD0QiHrpyBchsWR0r2KroyfYDwZ+5Fb4zpCdlrM6cehFRUjMmWOzS3D6Hs9fW+ZY4xgueI5F63cqb6uThnWV5sJpCoN9XigiVLo82k0ULqV1KyWq4ACP7sB2eeHVFptWFF3jPOUXdYQK1gH2iA9o166dchwnhISuo9J0DXJmq0UUMoKmR4yGbumENJ+hZ7DvcbTF09asT5/7enMA2wfMCw2U8jMjVDrSlO8iQmUuF0mECs+HdCFEXMeCzOSOUMEK4JtvvmnkYo7bOnfuHO3qCUl6cGarCTauQv9I2z1iInFLh5fMe99vVl5Y4f5Ifb5sqzozxWPDYdnmClm1vVKOHtT4BCwYmHeI5zx+aOeI6i+IO1Df8r9FG+WIfu2lrS2llQhgqDCKpQ87oF3AZXD/u4s3yVEDOkiRYYwbCkRX9Ky+QBGqET3aWJ22nWMkqBC53l5ZHdb7gW661+etV/YGJh3yM+Xk4V0Cdt/r6BRqMTE/NNDvCyJU2Rne76HbOrE8LLdzT6NOvxVbK+SjpVulPoiJKb7/kcxGTEhBBU8ndL/V1NTIr3/9a3Ubapb+8pe/yDXXXBOLbSQkqYFQ6tYmS9bt2C092zbUU9npUewNd/codl7GilC5cEv/5MetcumL8+XwA9rJ8+eNdr2tCL2f99wcKcxOl/k3HiXhcPlL82X5lkr5+OrDw/LXeeDj5fLid2tVF+Tpo5u3jXxfYvrcdXLjWz/I5LE95B+/Taz6UKSFzpk2W3bvrZO5fx+vPp9OvPDdGpn63k/yh4095NYwXuP8NaVSV+9R39VAYgnWJQN9vnLBvsdugNg7oEOu+r7MXb0jrJOQZ75aJQ998rPjfZjJd0Rff49GzZoSb9lBoCJ4M0JV50lzXUMVzIvqshcXyE+bK8QNgX73kkpQYb4disH/9Kc/qfEvur4JtVOmFxQhJDAP/n6YLFpXpjxoAjG+fweZcmQf9b8T4USolm3x/ojB/wrhdLdnfrN+KZF6j7fjCZ0+MCJ0CwQj2Fq+JyxBpevGMH6CNB0N+znxavAQ+dAH683lewIKKu24DXuDcNDF4cG+n+Cuk4fIVz9vD/gdDQdEwiCoUEcVjqBasc37PiKC3Lud93u2aH2ZEi4zfykJKKjmrvFOYRjStaG43jFCVbVXdIDcTZefuZzplo6pDlpMTRrZVVpJYN9KuKOfNqpb8gsqhA/RzXfjjTfKjz/+KFlZWcpck6aWhLgHP36hUmhId1111AEB77fOICsbBpgGQhd5VtfWy/cbylS6wg2mNw4OYBm57gQVIgfa8sGeigi5rb6DYFWYjyPhoT8Tu/ZG7hfUUphDe82/Ay0XbioNRpumR1QgBnYuUJdYgLTff2atldmrSyL6vlx4aC9LiL2xYL1c9coi63W4mVEYuEZzr6T7FFV+FBGqOb4xWojE3X1K4Pm7iUTUCcndu3dLVVWVmokHq4O8vDw1g+/DDz+MzRYSQlzRxndWjjNItz+6AGfAbjHbuMOZzYUZYJqqMA7YtXX1KuIAtJkgaRrWJ7BwDVdQAaTS3IBI7MJ1ZUHFRlOgn2vpxnK/2XmReEnpmqwfNux0/B55a8R2+i0bOAK+Vyqq3Tulm8uZryOQSeo+Lah++9vfyr/+9S/1d1lZmfJyggEmboewIoQ0D21y060fvFCT6vWPbjheNygOXbm9YWBrOB07KGQ1f7zdsqWiWtWuAAqqZopQJeB+NoWS+VkLtpzbE4nv1+9UafG2uemyX5S1UeHQqcBbW4mPv7ZjcNNYoIu4zU5D1EXhOuoQFzisCwX9eB7YJQSqEdMRKnQDaq+7cGuoyv0iVMEjYvukoJo/f74ceuih6m8YXnbo0EHWrFmjRNY///nPWGwjISSMCFVNnSeoaIHY0gZ++odNi5Zg2IVXOLO5zANZVbX7CIi5neGmCklkNUiJmPIzo7LBbEPM5dym0qx0X882Uc2njQTMCAzHPkHPA8XcvTa2Lkbt7q7tH8Lx2DLnhYJNO3eH3+UnDb8ZiFTpiBgFlQHSfUjzAaT5fve736l5eRhUDGFFCGke4NaM8TSh0h5lVTVWWgfT4nEghaVBKOyzxcKJUJnbE84B20xNhpMqJOFhCtdwBG+8gM4zTaCmDJxImJ9Dt6k0fSLREqkp7W01x2U0zUz32cWftmdxEmdW/VSQ16jnhQJ9/pWf5dKHKsu/hgoRN6wDEThE4pKFqAVV79691RiWdevWyQcffCATJkxQt2/dulXy8732+YSQ5kGflQYTVPpHFwW5uhDezRmw/tHFAGdQEWmEKoxIk5marEzAA32iYArXcFKy8YKZ5gtkG4LXhegt6JCfoQ7oSHUFA5Hbeb7i6ZaIpGgRhBoupPNcDzd2SNtpcYaUH1KYGqx34Xp3NWLwqDIJO0K1u8YvIpZM9VMxEVQ33XST/PnPf5aePXuq+qmxY8da0So9cJgQEn+CCs7rug1cd9wEAqH6Hzf7GxvqeV5uMLcnnAO2LpQGVQl4oE/ECBU6P9EMkGwRKv0ZRBT3kN7tXNUP/ripXLmH52WkSv9OzR8g6FmcrU589tbVy+L13hRZMKwRLQ6jY/Zvl6t+H7ydvQ3rWmzUiPUKUSOm54UCnFflpKdE1OU3e5U7G4p9TlCdcsopsnbtWpk7d668//771u1HHnmkPPDAA9GunhASBkVuBJWe11WYZZ0Bo04kWCE7ztJxN37g8cMcdoTK7PILQxj5paJYQ9VkrDf2M6hyEQ2J2whVgBoq/Z2AqNAHcnsa246+f0TPIpXyam6QtmvY1tBRZOtkySFChXVZdVTG6zaLw0PViOl5oTrq5LamLN+ooTIjYoxQOdCxY0cVjULtlGb06NHSr1+/WKyeEOKS4jAiVJ0LM5WJHzxl4MmzuqQq9ByzXm2segizYycUOwxvrF0RpvwSsVg6EVN+iVhHtSOMCBUElfaTWrRuZ9BUWkvWTzUuJi91/T4G6tTTJ1BmZM4sug+F7vQLp8PPPsuvISKWETIilmhEZOx59dVXy2233SY5OTnq72Dcf//9kW4bISRMdNGoGREKVmcBs9ADuxUqwYQz4EA/cKZnjE6vhNXlZ2yP27Z8RMzMA30itvMnCqZwTcQ6KvPzhZZ+fHbs0RNTUCHS2i4vQ1kMqAkF+zXM09RgHfGQmtIiaN7qHSoV6zTH002ESq3LJ5rMzl6M1fE+jxtB5R+hckue4UOlI22o6Wrursm4FFQLFixQs/v034FItp1FSLyDWV32iJCdjb6W5y6+mV2jehX5BFWp/H5U41l5OINf7AvRj+lVLF+t2BZll5+76Ae6EbW7OkBBcThjcohElFpNxI5K8/OOeiMIQvsB3xRUODZBXLz7/SYlLpwEFTzXcPKAz9vgAONYmoO+HfNUNAjftx83VQTcFswz1HYGqI90on+nPMnNSLU6ezGUWO2rjFTp1zE/rAiVW5d0oKPa0HCfL9sWsqNwnxJUn332mePfhJD4iFAFc0u3dwLhDPjRz34J6MuDriCIGXRGoc3ZqocIwyndrHFxW0Olz7bRWVTq69zCgT491XlOG4kMiNStPjNIiA0Ij10JlPKD4NciHefwqPVDlKqRoPJ9J3TjBiIyEFRIeV3msF4dnRrWrTCsmZWxBrVbiAx/+tNW+W5VSUBBta2yWn1PUerVMT/TcRlEt4b3KJIvl29TkSJf06OMdFkjFmmEKistRa0fUbH5a0tdjfFJRKI61auvr5dnn31WjjvuOBk0aJAMHjxYTjjhBGXqGcqpmRASe/TBwux6ss/U0/dpQTW8e6H6EcbwYn2Ga9JQtFqszuwDTY4PBM6cTYHnNnWnO/y6F+dIhi8qlWipqEQA7zl+rrGPu/kiG4mUXtWfLdh5dPIJiRKHOiodxdLfEV0zhJSXU1ejG7PL5kJva7CuRP19gZgKlhY0O3st+wKXr9EvQuXSgwrgd0NHtBClwm+Im4jYPiOoIJggni644ALZsGGDElMDBw5UZp7nnHOOnHTSSbHdUkJISPTBItD4DR31Qdhf/yDiTFMPdHXqemow/Svyr4fwzfMKBUZVmEbsblN+Vgt4YZbkZHi3lZ1+sceMWOr9nEgNADqVhw7XYt+wY6cIrb5Nf0eQSsNBHp/HpZu8liAm38WRoBptiKBAwQrTDsWNOMPr0wLNbY2YnsYQzhw/p4jWyB4t0zUZt4Lqueeeky+//FI++eQTVUf10ksvycsvvyyLFi2Sjz/+WD799FNrxh8hJD4iVLpWBgdPs8Yx0BlwTV29FaLXxbEFusvPpQ+VfVvc1udsNLoR4eieaJGTRME8EGenJ55wtWqjstMt25AShxpC/TnUaXEc0Ef6Pvf2EwnsE1ywzPDu3hOJlmRwlwI1Tgav9ZdtlSG/28FQnb2p3s5e7BNEJgd3KQxrXmi4XX725fVvSbIRsaCCgLrhhhvkiCOOaHTfr3/9a/nrX/8qL7zwQrTbRwiJQFAhHQcx5PYsVp8B2w8sP2wsVwdXzPHq0z7X70wT6Tc3qX0dGdAuy7q4PKzISQIe6BMFszMsNyPxhKtZbK5tQxwjVL7ldONGsM+9ToUN6pxvRe1aEgigYd2K/CJnAb8vISJUqrO3a4OAGta90HWjRzQRqnxjee3anmxELKgWL14sRx99dMD7jznmGBWtIoQ0HxA+OpLulPZr8KnJdPS6Wb6l0u9xDSMiiqS1b8X6hxEFpm4Ejo4WdGvj7Sp0e8BuEH/ZkuM70LOGKvaYwjVbp/wSqCjdFFQ6+uQUobVHqMzI7Nw1/qk07bsWT8aTus5JfyeDzfELva4GQRNOt505LzTSCFVGGBGxRCNi6b1jxw7p0KFDwPtxX2mpu4GOhJDYgBRFYba3UwtdTe1t3T4N0YgGcQNQe9K7fa6s2Fop5z8/Rwkz8JNvaLJZR4LUAwqAa+s9yosq1Bm8jha0y81QP6YYfYEaHZ2ecRM5aaihanpBhQPr3R8sU47wp4zoGvW67nz/J+nbIU9+Nzy6dTUV5oFYe4sF288vzV4rm8p2y1VHHRC1Nc5/Zq1Rqacrxx8QcBmksh78eLmce3Avx/EvpWaEyhd9sp9MIFqrmyh0FMueSjv7mdmSluJ9PQvWuZtt15yEcncPNsfPju7s1X+HA/YzPjPhdPkBvXw4EbF9RlDV1dVJamrgh6ekpEhtLc8mCWlu2udlqAPEmpKqRp00wQpXD+vTTgkqTIK3o2efAd3pBysDHKQ6FbiPIEAYVdfuDRnZQjeifpyKnFg1VE0fOfll2y557PNf1Jyyk4d3iUo0LNtSIU98sVIdxONVUFm1N0VZsnZHVdCidAjEW/+3VPmDnTS8a1RO1+j+xLrgG3Xy8K5+EUyTV+ask1fnrleNDfeeOjRw5MmIUNknBWiBhSCrPlkAOLCP27+tsiT4esV2v8dA/MdThApCBCcyG3fukfWlVdLV5yNnfx+d5vjZwVB0fIdb+dYbDvu1y1G/Iz2Knd+vQHT3vb+HHdDwW5JsRCyo8MVCN19GRkMbpUl1tbP9PyGkaRnWvUhFlpAamDiwo+uz2GsmHCAHdi+UatsoDhzoBnT2F2b5WV5vKDdeVKaggjDasSt06s7ejWh1nzVDyq/MF1FD9xfMRUNF0oKxvcK7rrLdzu7dLQ1EzcayPUYNVfCUH6KL2mx13Y6qqAQVomEQU3pdgQTVutIqa5lgEVCI1kDDwbUHFQSXTl1r7j5liPJl0s7hGkTDonnvYw0aBgZ1KZCF68pU84gpqNBJiyHOblN+eJ/f+NPByrcr3Bqx+yYNlV+27lLbEg5/PHw/GdKtQMbtn5wF6VEJqsmTJ4dc5g9/+EOkqyeERAgKPpGWsXfswWtnc3nDwdMOflhPGNrZ1XOE40VlCip9wA41K85M90GE5PiK0sOZAxgp5mvCdkRzUNV+SLreLB4KnE2QboOoUWaQBZmSHaIo3Rw3ZHdXDxezzsk++sbpJEA7/Aeq0SsKJqiMZexgply8Rg/tIAUJQYW030nDujbaR2j80J2aoUCKPxLa52WqS7hkpqXIEX3bSzIT8bd72rRpsd0SQkhM0DURSzaWqwOjPohvqahWB3bUiSAtGA15GQ3T48PxCbJSdyFqoewdS/pA79ZlPRrM1wSzxHDPxE3MWh4ItXgTVOt9QqZDfqakpbQO2U1pF5vRUOpWUPnu21S2R31+7f5F4USo9P2JCgrIn/xypaPNg5sOP9K0JGdlGCH7MIjq4GKOeTAjCp0KshqlPcJFm4KWhxGhwgHPbXG56UEFcqwIVXMIqtiJBvPAHs4w6ebC7l2k359AKVkzxWsOro46QhVgXfgMb97pjaqiCWJrhfdvR8Ge3SCoym22IaZXVSKDETG6zg/RxXA9qEjTQkFFSBJiOSsbZ7LhdAGFMz0+kghVpeuUn7dOpKGGqjlSfrFLa+nIiH298YI9EohC/GCCt7kjVBBQEFL27fUfa+Tdr+jw87MNMfa9JagMD6pEBB28/Trmqb/nGin9QN27pHmhoCIkCTHHS0TiUxMK7UVVEWmEKlRRepgH+lhiOsBHG4Xxj1DFX9ez/TMRyocqloLKjFAFEq72/W9/TkT9dDF5YXaaZRti3/fJEqEK+N0O4C9HmhcKKkKSOEKFAtbq2jq/4amxqLPQRemhuvxgf6C7whChynFZXG4WpYPmNJw0I0kxTfm56IhsbuxRS8spPYBwNdOWSMXZO+MijVCh0xDRpkbbZ9v/9ut6/+ZlpEpGqnfbneqozMaIRKdhrt+ORrVwbiwTSNNBQUVIErJ/uxwVEUKb+/frd/r71MQk5eeuy0+nvFAIj4NeqC6yQN2IoQ70sSSWURjzoO4mmtfc2IuZrVl+ASNUDYIKqbgtvvcp2n2DTkOzJkijTwKs7bVdN9PJGh2FSnZBtXRjufV+NNRQMeXXklBQEZKEwGpApwb0GI1YdgLBh8pNoXWpUTCMbcq1usgCiwunbkR9oG8OHyrzNeFAjChbpOzYVRPXRekbbCI7x7efIXCc5i3aB2JHU2Nm1peZURan9evPQaAIlSmoinLSGkXAkklQoSMTppoI6M1bUyp7aupkW4VXjLLLr2WhoCIkSdGzv9BiDVPJhjqLWNRQuYtQldgOZG5Sd3o7zW7EnGYcjmx/TZFGqbwF0/EboYLA09vUUEPljQQGEr32wvpoInh2awMncabXr6My9mXM+jxNm5yMRjVaySSogHWytGqHbPJ1QWKEjh5ATloGCipCkhQ9+2ve6lLZXrnXqmXqVJDZbF1+5pw1t8XlG8qqGnUjZjfjcORYiQaIFbPGKN66/LQ4QTG3bhaAF5Wes+ZU52YXhfaUXDhokaNHmDg1AOjb9GcZ180hxqYDuqaNLUKF5bWwTRZBZdZRmXVw8ebEv69BQUVIkoLRGXAmx0iKT3/aom5rl5ehHItj1eVnTwG5jVAFE0Z6FIoZSbMc1vfW+R1QmwL9mrCvoun00y7p9vXGC4FsNCzR6/Ae6bSltW9iEKHSxqn2damoqu+2ET3aWCIPY1bsDuh6KLJThAqf/5o6TyPhlegGn2DRup2yanul+ruLbbYfaX4oqAhJUtBCjiGo4I0FG2KW7vMvSg8vQqWLy4Ol7py6EbV/FSI+KLRvSvRr0n4/kdYJmek+c73xgr2TUmPVqzm8R9r6Idp9g7of/RkYrAWVTbhCOOllMJC3rU80mVGxoBEq3336M5iVliJZvs9RooOoHurKUOv27veb1G1daJnQ4lBQEZLE6NSA9qyJRYefKahw0EVXnusIlYvicnuhtPm4UI+NFrwWLSQQ4TO3J1z0jLl4raEKVFPXMCDZqYaq1n/fRBi909EpNB709Ykz+37WwglCClFVLfzM5YLWUPn2v/0zmDRNJ7bvNl3SWx4KKkKSGF28qrNkseoC0jVUodJ3jWuo3BSlVzXaVkTbEGFo6sJ087XoKEykokFHSFAsHI9dfpZwtX0mgllbaC8ta9+U+dc0ucUcF9PN9/yBPKe0UNCfBzMqVhrENsEeoUomQWWm/WL93SZJKqg2bNggZ511lhQXF0tWVpYMHjxY5s6da91/yy23SL9+/SQnJ0eKiopk/Pjx8t133/mtY8eOHXLmmWdKfn6+FBYWyvnnny+Vld6cs2bx4sVy6KGHSmZmpnTr1k3uvvvuRtsyffp09VxYBtvx3nvvNeErJyQ2DOlaYBUZx/IsFuvUQiFY5MXeXZUTwk8KB2enGio3j40F+rXgtfUozokuQqWLrtvkxGeEKkDKLydIR6VOW+qoEpYp841+CQfzc6HfZ+wfU3Ra3ko+odC5IKuRwHWKPunxMngOfJ6SMUJlRp819KBqeeJWUJWWlsrBBx8saWlpMmPGDFm6dKncd999SjhpDjjgAHnkkUfk+++/l6+//lp69uwpEyZMkG3btlnLQEz98MMP8tFHH8k777wjX375pVx00UXW/eXl5eoxPXr0kHnz5sk999yjhNqTTz5pLfPtt9/K6aefrsTYggUL5MQTT1SXJUuWNOMeISR8kCo5sGuhdT1WNVR+helBIi+6xkVHDXJCFJdjLlugbsSGdGHTRah0wTMicFpowGQ0WFozEKW2LrZESfk1zFusbWQDoW9rl5shbXMjL0w3u+7wvup2f1MsWdvnE1JaWJnP5xR90p81FKJje5M1QtW3Q55lXwI4dqbliVtBddddd6lo0bRp02T06NHSq1cvJXz2339/a5kzzjhDRaX2228/GThwoNx///1KICHiBH788Ud5//335emnn5YxY8bIIYccIg8//LC8/PLLsnHjRrXMCy+8IHv37pVnn31WreO0006TK664Qq1L89BDD8nRRx8t1157rfTv319uu+02GT58uBJzhCTSmWws6ywaxs+4SPn5ogahisv1QdSpG7FhQHLTR6hwoELRL2p8sK0wG404QuUTVDi4RzOqJZZgHNHWAGaQDR2V/vsZkUG9+TB21UXQkQgqXd+kU3WWWDIFlS1CZa+hQmG7rnczxRIKz3V6GFGqZPOg0sCjTaf0kRLvmE9B1dLEraB6++23ZeTIkXLqqadK+/btZdiwYfLUU08FXB6iCFGlgoICGTp0qLpt5syZKs2H9WggwFq3bm2lBrHMYYcdJunpDV+2iRMnyrJly1SUTC+Dx5lgGdweiOrqaiXuzAshLYEuXo11nUUoLyrT2FJHDUIVlzt5UGnCHZC8evsuOfrBL+X1+evFLfq14LXhgAVz0UB1VO8u3iQTH/hSVm3fFSJC5U35gcooolQQEL999Bv5x/9+kGjBHD6d2jQLuv1rqOocxSZEZkZqa0cR5Bb9udDPrd/vjTt3u66h0utIbd3KL1Jjn+eXrILK/G5DTKWmxO3hfJ8hbt+BlStXymOPPSZ9+vSRDz74QC655BIVOXr++ef9lkMaLzc3V9U2PfDAAyq117ZtW3Xf5s2blRgzSU1NlTZt2qj79DIdOnTwW0ZfD7WMvt+JO+64Q4k7fUG0jZCWYFTPIuneJlsO7FYoBb6RMbGgYfxMbcD0mY5o6EhEqOJyHTVxOtsOd0Dyq3PXyU+bK+Spr1a5e0HGa9GvrSEq4hV6Jk9++Yss21Ih7/na1u3oAzleCwRItIXpP2wsl0XryuTfM9dEHaXTc/MQCbSbQeYE6MTU245ULx7j1HUXbvRO2x3otKMpzuw1VPr5YFILcWmOnbG/hn1FUB09sKM60TjsgHYtvSkE+kLilPr6ehVZmjp1qrqOCBVqlh5//HGZPHmytdwRRxwhCxculO3bt6sI1qRJk1T0yS6kmpvrr79err76aus6IlQUVaQlQFTo46sPV2fysSSUF5U+aGI5OHCbxeWok3IqLtepIJ0idIpQuS1Kx1gO8NPmciXu3IjJhghVqt+BXhfKayA2lmwsD+oWbnkk5aSriFd1ZXVUgkpHvDCUeMHaMjmkj/fEMRJ0mlbXwTmmVvc6R6j0vrGiSpHUUGm7A9/7rNel5/lBMEE4mffh/cNnANsFEWcJJQezziJTUDl4VSULPdvmyPybjpJ0Rqfigrh9Fzp16iQDBgzwuw31S2vXrvW7DR1+vXv3loMOOkieeeYZFYHC/6Bjx46ydetWv+Vra2tV5x/u08ts2eJ1kdbo66GW0fc7kZGRoToLzQshLQW68vRcvFgRap6fPa2jCeZFZU8ROtdQhY5Q4YC8eP1O9Tdq3+et8Yor90Ij1S86YhdN89eWWvVQgSI0lot3TrrkZ7mbfeh29p0eeB0pZrTJTnaA1KqZDvWLKsUgQqWtG3SESq8TAkoLYRUVM5YLFnnSnzl8nuziLdnISE3hyJk4IW4FFTr8UMdksnz5ctWNFyqyhfolMHbsWCkrK1Pde5pPP/1ULYMidb0MOv9qahrOHJE27Nu3r9VRiGU++eQTv+fBMridkH2VhvEzNa4Kj90Io2At7uHUUC1cV6ZcpDXa/DAUWjTo19Y1gGjQ0a9AERqzYFpHqILtKzfoSIv3+UsiXo/aDlu0yc37Y4lNnziMqobKZsjZEAn0CSrDLd8UC2ZULJig0kINnye7eCNknxNUV111lcyaNUul/FasWCEvvviiKjq/9NJL1f27du2SG264QS2zZs0aJZrOO+885V2FQnYd0UJ33oUXXiizZ8+Wb775Ri677DLVyde5c2erUxAF6bBEgL3CK6+8orr6zHTdlClTVLcgbBt++uknZasAPyysi5B9lbwII1TBhFGwFnc3cwA1c3yCR0db9PVQ2NNaDbU9VQEFlX1gr1PBdKhoXrgRKqT89kYxgscebXLTTWk9JkOLTW/3IgTL7jDNVs36J1MooYYOHYhW/ZStOcGMigX7rOho1Lbyamuf2z+HhOwzgmrUqFHyxhtvyEsvvSSDBg1SVgUPPvig8pUCKSkpStycfPLJyo/q+OOPl5KSEvnqq6+U/YEGtggw5DzyyCPlN7/5jbJOMD2mUDD+4YcfyqpVq2TEiBFyzTXXyE033eTnVTVu3DhL0KGD8LXXXpM333xTbRch+yq6cLuiuiakG7azMGp8EA4WdbDa+V2k/HRK7Mwx3dX/SP+5OeiX24RGQ2fZHks04YC/YF2Z9RjUg8E/K1B0DhEWHfGKZp6fKahgOfH9hoZtiNgewhdtciN47VEtPFa/J2Z3XijM7k8tcvB+a6PYTWV7rIig3SPLjIpZkacgEapftnlNnJHtjmVDBiEJVZQOjjvuOHVxAl19r7/+esh1oKMPYigYQ4YMUUIsGIh66cgXISS0D5Uljmy1Kw0DkmvDElTZLovSYcI5b43X8uSkYV3lncWbZNPOPbJgXamM279tWEJDm4tq0YTt+n79ThUdKvaJJXTMIaJibrNdMFj7KgYRKogDlG/NXlUqI3r4u2W7RacenSJUgYYjW3VXRk0TzCSXb6lUAmf/drmuntvs/iz0CR/dNfjLtl1KTJkpPxOzeF0PS3aKPOn3YsXWSktgxbqGkJCEiVARQuIbnfoJFHUJ1IUVyPEcESDTQdtOTpCRKHZ7ASyDNBtmzmnzQzNNFwh7WgvmorAWAPogr+uxYJjaNUDRuj06Z0XzYhCh0kat0dRRmQamdqwRP41Sfo3rriKxTtC1YFiPORbJTOcFGotj1lAFqtEzPz9mHRshTQ0FFSGkSXyoAkWbAqWUKqpr1bgQp8eYhpOhaqjm+NJ9I3u28bpJ+wSIvj0cHyr/A32V33og1AIJCnt0Li8jdjVUEwd6u4vnrmnoNAwXe/G9mxoqHdUyHxNJYXqgz4XZ6RdocLN+PhiTai+tYBGqQNcJaQooqAghTeJDFejAGai4XBcZI7VnHzvjPwcwuCgxI0hgjO//+WvKpCbETD67D5V/p98eJWDmrS611h9IUNijcw0pv+h9qA7p3VbVLkGcwWMr5l1+RiTQLLZ3jlBlh+1FZXmN2T4XWpyu21FlObnbB/62z8tUhf7w4lpdUhWwe6+RoGKHH2kGKKgIIRERqi4okKAKVFweqr09Jz10UToKnucaESTQu12uFGanqTqoJRu83lSB0PVgfqLBEE0/bipXkTREnPp3yg9obml/7Q0pv8giVCiEx/MCpCCH9ygKq3sxYITKoVBbRwJrbfMWnToD9UBebcjphkBeY3o/o+Afzw3hpNOtGjjtd/I9p47OOflLoQDdLJlyMoolJNZQUBFCIkIfjFGgDd8l1xGqAMXloQwY9eOCpfxWbKtUxePoGBvcpaDRENlgdVR4Ddq7yi/l5ytMR8pPP35EzyJ1cA+Z8rOK0qPzoSrzdRHiOZFy01G3SA0+naJNmhxj3qJZr9aQDjWidzFM+XX2zU3UsxEhnPB67ejlNBDLdvA4XfCunosRKtIMUFARQiIiNz1VtOeiPfICiwJEhJxrqJxrdEJFqKzIVpCidC14hnUr8it4Ht0zdB2Vfg14TXhtmi5FOq21x69+KphbeKMIVZQ+VFYBdnaaTSCWNvLAirbLD2JEWxiY75FT3ZVOyW0u36O6K6MRVIE6+uyYyyFSCKdwJ8z1s4aKNAcUVISQiMCBXYscex2V7uRKS2lYJtSsOLt7dqBUFCJbgUSEFjy6fkqjr89ZXarSgk7o+iZsr9lib7Xql1ZZ69cRIn1wh0gwa7sCRqgiFFQ6TabF5pCuBWp+GwqzdUTHLRA+et87dfmBHMs6wRRUjef/tc/LUO8x0m96sHWkggpDpM2AlL1+yl7TFqp7z4xKUVCR5oCCihAS/fgZm1AwXaztc8a0MLIXl9vds+3k+A7y0FI6+mUCkaUjVHZBNbBzvkoZwgNp+dYKx/U7CQZTNCGViIG9iHwN7lpg1eroDj5zgLLd/iHaonT7SB4U7R/YrdB196KJmTJ1ilA5jZ9BMb+ODJppQgjPjlZK1F3aL9D7nJrSWokqTRdfrVSwCFUwocQIFWluKKgIITHv9AuWvssJUFwezNQTZBmdf05zAOEFBQNPFDMP6+4VG+bBekSIQu6GNJh/1AZRHDPKNqxboV+ayZ728zqB1zgWpaPeDAXm4eI0ZmVUr6Kw5hTahSPSemZaNNiA5EpDMOfa9o9VR+ayjmpHkEikKZbsKUCN6Z4eTCiZgo2CijQHFFSEkBgMSHZfYB6ouDyUoEI0JNgcQB2dGtSlwDIPNdF1R4EESKAIlXbx1tijX3brBEShdAeaFpSmIIukjsppaPToXsURRajs43XcRKj0NuO9S0vxP2zo1Fy0ESrvurJCpvzMZYIJJVOwUVCR5oCCihDSrBGqQMXluu4q2MFPe1g5Rajs9U12GuqodjjWYDl5UDlFSxoJKpt1gn7tSAXqCBAKvfXrjqTTzylCNbx7oao5WrcDkTn3XXZO1hB2rE5Mn+gtd7FvwhVUjFCRZCOuZ/kRQhJFUAWIUAVxPNfF5brGKlSECiBCtS3APD8dodKRKDuoOUIB9Zbyalm7o0p6FOf43R9MNGi/JQij4d2LbPf5CwpL/Niic0gdIioXSYTKad8gwjSwc4F8v2GnvLNokxzSp2FOIYSsrm0KxyW9sei1C6rGj9G1Tiu2VCqfLk1Gamvp1TbHr4bO7P50ilCZYknPUbSD+jHM8UM9m5sIVSCjWEJiDQUVISQG42fsEarqgAfNHFtxuU7PuRJUAcailFRWy8rtu5TlQSBBhYPq0K6FamQLuv3sgqphMLKTaPCmnwZ1zre2IVDKL1B0TomRnXtiJqgAXisE1e3v/djoMa9cdJCM2c+bFnTrQRVoQLKOajl1Bep9A0+sYx7yHzL/5wkHyGW/7uPY/amL+f3X5d2XbXMzgoogLKcEVRB/Kf3ZC2TDQUisYcqPEBLzCNXi9V5H8v3b5ToWl+ughU7doVhbryPYQTInwIDk1SW7LNPHAgejRw3czcGq7ZVhCY3jh3ZSEa5LftW70X12c89A0TltiBlJp18gQTVpVFfZr12OEiD6gsgQgNByotxFhMo+INnJJV2DYv+RPYr8tgHdj+D9Hzb7Lav3DUSOvftTC8RRPYtk8tgeQfaGyJljeijj1kMPaIjKBdqusw4Kvi5CYgUjVISQGNgmNIgE/K1TP/Z6I11cnp2WoqIf3pRShpT5IheoCdIHYycCDUhGh1+wuhs3w3ydhv9quhZly5uXHuy4Tu0Wrs0trQiVTfxoMRJo9mEwdGTHHm3p1zFfPr3mV3633fL2D/Lct6ut7bDTEIlLDbso3Sl6l5WeIq9dMs7vNtR0jb3jU1m6sVy9Xv3anYrr7c87/WL/dTkxaVQ3dQkG0pb27SKkKWGEihASMQ0jVRoEzrw1pYImtx7F2dLB8BUKNiDZTJOZppp2cizLBX9BpaNDpumjE4FGxajXYEWoAgs6J9rlNphbbqmoDhihChTNCwXqzEKN5THRz6sfYydYtElj76YMVl/mRKeCLOnWJkt9DvB5CFZcT0iyQEFFCIlpl5/2edLjXpywd/q5PdBaqShbyk932JlFzU7o+00TTk24okEDAQgBoSNfgWwBGiwmwotQQehhWLDbeiD9vIEiVMHqoew1VFrwuqm7sjO6Z2Nbh1ARKkISGQoqQkgMitJrG3fbBbAvcGrLD5Qma/w456L0DS5Tfvb0nEmwtFYoGiJfVQHtHxrc0sOLUGmBluOyWy1khKo6dITKLnjddAbaGe0zHp2zihEqsm9AQUUIiVmEak9NnVWQHsgPCuTYisv1qJZAc/ysx1lja/wjVDqFF2igrlN6DqLKrQ9VKMzIl1VAbosmBeqIDEWokTx29HL6cRH5UNmK0t1Etexo49GF68rU5wIwQkWSGQoqQkjE6AOsju7g4Lm3rl4Nze3extnp2qm4vKTSnWhwsk1AjZHbCJU9PedclB6+oNLPi+J4S1DlxqaGKpgRphN6OR0ps+Mm2pRjE7xuolp2ehZnq44/fB60yGaEiiQzFFSEkIjRB2UcpCFsrPqpXm0c2+LtwkgXl7uOUDnYJiB6omuqYJsQCsvZ3HAXx7ZrcRdOWkuji+ERKQsUoYq0y680wghVWVVNo7Sm9/nDd0p30xloB++/jlLOXlXi2muMkESFgooQEjFaJKBmGqIG5o6B7BKcusi0EAo2qibUHMD1ZVWWGEMLfyicrBOwHb6677C7/Mx1rtxWaYk9J6d0p7mHoQg3TVaYlWb5fJU5FMCHNctPd/lZg6PD2zfwlAKzV3vrqKz6MpptkiSEgooQEjGZaa1VTZKOpOgW+VCCyl5c7tYWwIpsGaNn3Kb7glknaMGA14LXFGkNlfbDcnICtyJUvvSZW0rDFCGpKa0tLy+nOqryMHyoquw+VGEKKl1HNW/1DhUtC5QOJSQZoKAihEQM0jpaKMxaWaKiMziYH9A+L+jj7F1kVuF1CNFgN5w0LRNCFaQ3FlR7HNJgaUFTlYGwz51zcgK315u5RdeXhSNCdDTLLqhQHA5Xerc+VHreYqSWEn075qnHIAL4w8Zyy8CVESqSjFBQEUKiQh9kP/lxq5XmCWbO6dRF5ra2xjzQaza49KBqnPLzpgpBpIJBAzuDdnkZ1nWn16G7/CCoIFKaKkJlLmsXVFrMQes5zdKzC1ekQVGLVVPniWj/YJi0nq340dItVlrVbT0YIYkEBRUhJCp0GujLn7ep/wMNJzbJMYrLlRN4AO+mwKnCurAtE5xSflrYROKzZMcUdE6vQ4sRWDbYbR+CEYnVQKAIlX6duempQUUv5i1qtL0EFs/x7f9w0J8HPdcP+yEthYceknzwU00IiQotFLRICFU/ZS8ur6iutSIgoURDbgxqqDoVetNze2rqpbSqJmIncDvm2BunCAxESqpPxIST9iuNqaBy9zrVvEXfe7R55x5r34eKPDqhPw8rtlaGZf9ASKJBQUUIiQrz4AzRMKhLQcjHmMJoh69GKNuFE7hOFUK81fvyR7oWym2EKiO1IT2nxVhDF1vkgsoUdE6iwVtvpt3S3Rem74ihoNLP68YNXqf9NvkEVSTdj2BwlwK/Qn+m+0iyQkFFCIkKM002vEehq3SOHo6M1F2gUS1O5Bgpp6qaOlVkvb2yOixBZR8V49f5FkXKz3z+QMX14XpRVdfWWRYRzRmhMuvVdMovkpE8ID21tRzYrdC6zggVSVYoqAghUWFGLtzUT9mLy3WEyo1gQKRDZ51gCqo7/BDdKsxOi8jZ3N7l11Q1VKZVgVsvqtJdNVZxdzhiTz+/rk3ThOMnpevVNvsMUKOJ3mn7BLcDnglJRCioCCFRYR5oR7sVVBFGqJA2y9GF6Xvr/ArSw7E76GrM3vNPhUWR8nMhqPIywpvn12AnkRZW/ZJOq2nLBU2Dn5SLCJUvvapTftFE78zPBT2oSLJCQUUIiQqdCkLB9bDuXmfsUORYXX61AUe1uLFcsDyoXBak26NJOuUXiwiVuQ0BBVWYXlSRjmopDhChahgA7b6GaotO+UURoUIqWBfk04OKJCsUVISQqGiT4z04D+la4Gr0i724vMRXA+VWNOQYLuu6qNytB1Ugt/RYFKVDcGiHcgyHdlwmK8wIlU8QhZsm08vDcsH0vHLjkq7JSbcXpUe+b5A+1M0Kpl8XIclE5N8QQggRkfH9O8h5B/eSY4d0cv0Y3eVn1jG57f5qGD9TJ+vD9KCyR5N0yi8WPlRIOd5+0iBlD9C7fW5sIlQ+sRlqJI8dvTxc0bGf9D5zM8dPo20TGgYjR75vwI3HDZB3Fm+UowZ0iGo9hMQrFFSEkKjAwfmm4weE9ZiMVG9xOZwPtKBy2/1leljplF/XCFN+SKkh7RhObVEwjhvSOej9+WF2+e3w+WSFG6GCfQX2cXWtd36eFlRhdfk1mkUY3b4Z0aNIXQhJVpjyI4Q0O2Zx+TrfCJjwI1S1Ybuka5Ca06NXIMrCidxEg+VD5bLLb8cuX4QqzBoq7N9iB+sEndp0E4nTRemapt43hCQ6FFSEkBZB11FhVlwkESpEWzZpU88wI1TmYxAha0hrNW3QPtwIlbZNiMQMs8hBUIUTodK2CZpo0qGE7AtQUBFCWgR7SsmtaND1V6u275Laeo/qHmuf5x0nEw46qrVuR5U1NqepozBasLmtoSrxRajC7fIzH+MnqKrdR+LMOjfvY1ghQkgwKKgIIS1Cji0C4j5C5X3cz1u8s+E6FmQq48tw0XVUP22uaDbRoIVMeZgRqlgJKp1qLHARidORQE20RemEJDtxLag2bNggZ511lhQXF0tWVpYMHjxY5s6dq+6rqamR6667Tt2Wk5MjnTt3lj/84Q+yceNG6/Gff/65qiVwusyZM0cts3r1asf7Z82a5bct06dPl379+klmZqZ6zvfee6+Z9wYhyYV5wA7HCVzX9izfWhFR/ZQ95ffjpnKrkNvN2JxoCLfLD7YHUQsqn/UC7BP0GJtwfKg0jFARkqCCqrS0VA4++GBJS0uTGTNmyNKlS+W+++6ToiJvl0hVVZXMnz9fbrzxRvX/66+/LsuWLZMTTjjBWse4ceNk06ZNfpcLLrhAevXqJSNHjvR7vo8//thvuREjRlj3ffvtt3L66afL+eefLwsWLJATTzxRXZYsWdKMe4SQ5MJMKYXjBK4P9Lr2KpL6KVOILfNFqJpDMGjRqIvDgwEBpI05IxJUvs5APdoHac0630BpN+LVHqGioCIkOHH7DbnrrrukW7duMm3aNOs2CCFNQUGBfPTRR36PeeSRR2T06NGydu1a6d69u6Snp0vHjh2t+xHVeuutt+Tyyy9vNKYCUTBzWZOHHnpIjj76aLn22mvV9dtuu009N57v8ccfj9lrJmRfQg9IDtcWQM8B1EQbocIIm+ZKaWlRsssnboKlKpGe0wIokvl3esSLjlDpNCNqzjATMdwaKhalE5KgEaq3335bRZFOPfVUad++vQwbNkyeeuqpoI/ZuXOnEkqFhYUB11lSUiLnnntuo/sQ2cLzHHLIIWo5k5kzZ8r48eP9bps4caK6PRDV1dVSXl7udyGEOAujcCIw9u6ziAWV7XHNEYExU22VIdJ+WghhP2WmuXOgd4xQ+dKGZoefm7mH5n5OT2kd0TYQsi8Rt4Jq5cqV8thjj0mfPn3kgw8+kEsuuUSuuOIKef755x2X37Nnj6qpQmouPz/fcZlnnnlGCaGuXbtat+Xm5qpUImqk3n33XSWokM4zRdXmzZulQwd/d19cx+2BuOOOO1QUTV8QbSOEOB+wwxFUdn+kSFN+7XIzlFBoTp+l9FQIk9auCtO1B1Wkw4R112SpT1BZHlQuI3Hmfma6j5DQxO23pL6+XkWopk6dqq4jQoWaJaTYJk+e7LcsUnmTJk1SNQcQYU6sX79eCbNXX33V7/a2bdvK1VdfbV0fNWqUKmy/5557/OqxwuX666/3Wy8iVBRVhDSQaxywwxNUsYlQoWarU2GmrCmpiolLulsg3PbUVLsQVDVRDRPWXZO6sD0cDyr7fmaHHyEJHKHq1KmTDBjgP86if//+qj7KSUytWbNG1TUFik6hFgt1Um5E0pgxY2TFihXWddRWbdmyxW8ZXA9UcwUyMjLUtpgXQohzDVU0Kb9wByMHEmPN5QSe77LTz4pQRVCQbkaodu6ukdq6+gY3+AyXESpjPzNCRUgCCyp0+KFrz2T58uXSo0ePRmLq559/Vl16EExOIHIFQQVbBXQNhmLhwoVK0GnGjh0rn3zyid8yEG+4nRDSvDVUZiqqbW56VLU9phhrapf0Rl5Uu91FqCJxSQeFWWmiS6VKq2qkPEw3eKQmdc08C9IJCU3cnnZcddVVyvYAKT+IptmzZ8uTTz6pLlpMnXLKKcoy4Z133pG6ujqrpqlNmzaqw0/z6aefyqpVq5Rlgh3UZGFZpBQB7BeeffZZefrpp61lpkyZIocffriqtTr22GPl5ZdfVn5YelsIIeFjppTCElRG5CTSdJ/T45tLNOj0mdsIVbhz/DSpKa3VzELYS8B+QY+7cRuJ0/MWK6prGaEixAVx+y1BLdMbb7yhapFuvfVWZZnw4IMPyplnnmmZfurC8QMPPNDvsZ999pn86le/8itGhziDMacTsEFAyjA1NVUt88orryixpsFjX3zxRfn73/8uN9xwgyqUf/PNN2XQoEFN9OoJSX4iL0pPjbog3enxzSUaGsw9mzZCpfcrBBU6/ax5hWEIR8xbpKAixB1x/S057rjj1MWJnj17qlSeGyCGAoECd3uRuxOwb8CFEBIbzNRdOD5LpuFk54IEjFD5xIlOwTVVhEoXtK+UXUpQ6RRjOOIoR4neaqb8CEnkGipCyL4ToSoOwxogI7W1MqeMSYTKryi9ec4vtTgJGaHyOcFHYurpNM8v3C4/HaHyPoaCipBQUFARQuJg9Ix70YDaHh2liraGCrYJmuYSDVrQ6EHFISNUEfpQNRZU4flQgRyf6GXKj5DQUFARQlqEdnkZavRKh/yMsDv1OvlSfb3b50a1DRmpKdKrbY5vnQ3iqilBoTjQc/qcQDlDiW8GX5ucjJgIKqvLLwxxpPdJtJFAQvYFeNpBCGkRcLD/z/ljpDA7/MjQo2cOl/WlVbJfu+gEFXjqDyNkY9ke6dYmW5oDLQY37twdcBkUkmOYcbRCzylCFU4k7m/HDpCJAzvKkf3aR7wNhOwrUFARQlqMsfs7e8eFApGpaKNTDevKU5fmQkd7IOICsaHMK7ba5oYfvXMSVIiG6RRjOAXmiCIeM7jBk48QEhim/AghpBnRggpRo6q9znVU60u9gqqLUeMVCdpyAenDhggVz6MJaQooqAghpBlBhEiLmo2+SJQdfXu0tUvacmFbZbXs8qUQOZePkKaBgooQQpoZ3Z2oI1GBUn7RdjHq7sltFd6OQcAIFSFNAwUVIYQ0M1ooBaqj2mCl/KKMUNksFzCfLy2FP/uENAX8ZhFCSDOjU3kbyqqCRqjM4c2RkJWWooxQNXQ8J6TpoKAihJBmRkeedCSqqWqoYIJqjq5huo+QpoOCihBCmhkdedKRKJPde+ukZJfX1LNrYfTeWOZwZY6QIaTpoKAihJBmJpgXlRZZGM2TnxV9REl7UQF2+BHSdFBQEUJIM9PVF6HaXL5HauvqA9RPZaqUXSwFFVN+hDQdFFSEENLMwAE9PaW11NV7lKhyrJ+KsiDdMULFlB8hTQYFFSGENDOtW7eSTj4XdHvaz7JMiNFA4jY+L6pwByMTQsKDgooQQlqy089mndBg6hmbYc1tDC8qpvwIaTooqAghJI6sE/R11FDFPELFonRCmgwKKkIIiSPrBH29a6xSfixKJ6RZoKAihJAWdUtvqKFCx58uUo9Zys8UVBmMUBHSVFBQEUJIC1onbChtqKHaUlGtOv/SUlpJ+7yMmDwPfagIaR4oqAghpEUjVLvF4/H41U91LMhUnYCxoDA7XbSdFVN+hDQdFFSEENICQDSBPTX1ssM3aibWHlQgpXUrGdg5X/IyUmNWl0UIaQxPVwghpAXISE1Rab2tFdXKi6o4NyPmlgma1y4eJ3tq6jjLj5AmhBEqQghp8bSft45qfYxNPTWZaSkq9UcIaTooqAghpIXQqT0tpBoiVLHxoCKENB8UVIQQ0sKCSo+f2dhEKT9CSNNDQUUIIXGQ8kOnX6zn+BFCmg8KKkIIafF5frultKpGdtfUqeudfB2AhJDEgYKKEEJaevxM6W4rOtU2N0MVkRNCEgsKKkIIaSF0ag/RqRXbKvxuI4QkFhRUhBDSQuRnplnu5XNWl/qNpCGEJBYUVIQQEgd1VLNX7fBeZ4SKkISEgooQQuJAUK3YWqn+78yCdEISEgoqQghpQewRqS5F9KAiJBGhoCKEkBbEPgg5loORCSHNBwUVIYTEVYSKgoqQRISCihBC4sCLCuRmpEq+r+uPEJJYxLWg2rBhg5x11llSXFwsWVlZMnjwYJk7d666r6amRq677jp1W05OjnTu3Fn+8Ic/yMaNG/3W0bNnT2nVqpXf5c477/RbZvHixXLooYdKZmamdOvWTe6+++5G2zJ9+nTp16+fWgbP+d577zXxqyeE7AuYNglI9+E3ihCSeMStoCotLZWDDz5Y0tLSZMaMGbJ06VK57777pKioSN1fVVUl8+fPlxtvvFH9//rrr8uyZcvkhBNOaLSuW2+9VTZt2mRdLr/8cuu+8vJymTBhgvTo0UPmzZsn99xzj9xyyy3y5JNPWst8++23cvrpp8v5558vCxYskBNPPFFdlixZ0kx7gxCSrMAZPT3F+1PMdB8hiUvcxpbvuusuFS2aNm2adVuvXr2svwsKCuSjjz7ye8wjjzwio0ePlrVr10r37t2t2/Py8qRjx46Oz/PCCy/I3r175dlnn5X09HQZOHCgLFy4UO6//3656KKL1DIPPfSQHH300XLttdeq67fddpt6bjzf448/HvPXTgjZd2jdupV0LsyU1SVVLEgnJIGJ2wjV22+/LSNHjpRTTz1V2rdvL8OGDZOnnnoq6GN27typwuWFhYV+tyPFh7Qh1oEIVG1trXXfzJkz5bDDDlNiSjNx4kQV7UKUTC8zfvx4v3ViGdweiOrqahX9Mi+EEBKsjsqspyKEJBZxK6hWrlwpjz32mPTp00c++OADueSSS+SKK66Q559/3nH5PXv2qJoqpOby8/Ot2/GYl19+WT777DP54x//KFOnTpW//OUv1v2bN2+WDh06+K1LX8d9wZbR9ztxxx13qCiaviDaRgghTpw4rIt0b5Mtv+7XvqU3hRCSbCm/+vp6FaGCAAKILqFmCSm2yZMn+y2LAvVJkyaJx+NRIszk6quvtv4eMmSIikRBWEHwZGRkNNn2X3/99X7PjQgVRRUhxIlJI7upCyEkcYnbCFWnTp1kwIABfrf1799f1Uc5iak1a9aouiYzOuXEmDFjVMpv9erV6jpqq7Zs2eK3jL6u664CLROoLgtArGFbzAshhBBCkpO4FVTo8EMdk8ny5ctVN55dTP3888/y8ccfqzqpUKDgvHXr1qouC4wdO1a+/PJLtS4NhFnfvn2tjkIs88knn/itB8vgdkIIIYSQuBVUV111lcyaNUul/FasWCEvvviisjK49NJL1f0QQKeccorypUKnXl1dnappwgVdewBF4w8++KAsWrRI1WRhOawX3lZaLJ1xxhkqDQhLhB9++EFeeeUV1dVnpuumTJki77//vrJt+Omnn5StAp73sssua6G9QwghhJC4whPH/O9///MMGjTIk5GR4enXr5/nySeftO5btWqVB5vvdPnss8/UMvPmzfOMGTPGU1BQ4MnMzPT079/fM3XqVM+ePXv8nmfRokWeQw45RD1Ply5dPHfeeWejbXn11Vc9BxxwgCc9Pd0zcOBAz7vvvhvWa9m5c6faNvxPCCGEkMTA7fG7Ff5paVG3L4CidHT7wdqB9VSEEEJIch2/4zblRwghhBCSKFBQEUIIIYRECQUVIYQQQkiUUFARQgghhEQJBRUhhBBCSJRQUBFCCCGERAkFFSGEEEJIlFBQEUIIIYRECQUVIYQQQkiUpEa7AuIObUgPx1VCCCGEJAb6uB1qsAwFVTNRUVGh/u/WrVtLbwohhBBCIjiOYwRNIDjLr5mor6+XjRs3Sl5enrRq1Sqmyhkibd26dZwR2Mxw37cc3PctB/d9y8F93zJAJkFMde7cWVq3DlwpxQhVM4E3oWvXrk22fny5+AVrGbjvWw7u+5aD+77l4L5vfoJFpjQsSieEEEIIiRIKKkIIIYSQKKGgSnAyMjLk5ptvVv+T5oX7vuXgvm85uO9bDu77+IZF6YQQQgghUcIIFSGEEEJIlFBQEUIIIYRECQUVIYQQQkiUUFARQgghhEQJBVWC8+ijj0rPnj0lMzNTxowZI7Nnz27pTUoq7rjjDhk1apRyuG/fvr2ceOKJsmzZMr9l9uzZI5deeqkUFxdLbm6unHzyybJly5YW2+Zk5c4771RTBq688krrNu77pmPDhg1y1llnqX2blZUlgwcPlrlz51r3o5/ppptukk6dOqn7x48fLz///HOLbnMyUFdXJzfeeKP06tVL7df9999fbrvtNr85ctz38QkFVQLzyiuvyNVXX63aaOfPny9Dhw6ViRMnytatW1t605KGL774Qh2wZ82aJR999JHU1NTIhAkTZNeuXdYyV111lfzvf/+T6dOnq+UxYuh3v/tdi253sjFnzhx54oknZMiQIX63c983DaWlpXLwwQdLWlqazJgxQ5YuXSr33XefFBUVWcvcfffd8s9//lMef/xx+e677yQnJ0f9/kDkksi566675LHHHpNHHnlEfvzxR3Ud+/rhhx+2luG+j1Ngm0ASk9GjR3suvfRS63pdXZ2nc+fOnjvuuKNFtyuZ2bp1K04TPV988YW6XlZW5klLS/NMnz7dWubHH39Uy8ycObMFtzR5qKio8PTp08fz0UcfeQ4//HDPlClT1O3c903Hdddd5znkkEMC3l9fX+/p2LGj55577rFuw/uRkZHheemll5ppK5OTY4891nPeeef53fa73/3Oc+aZZ6q/ue/jF0aoEpS9e/fKvHnzVKjXnBeI6zNnzmzRbUtmdu7cqf5v06aN+h/vAaJW5vvQr18/6d69O9+HGIEI4bHHHuu3jwH3fdPx9ttvy8iRI+XUU09Vqe5hw4bJU089Zd2/atUq2bx5s9++x6wzlB1w30fHuHHj5JNPPpHly5er64sWLZKvv/5ajjnmGHWd+z5+4XDkBGX79u0q196hQwe/23H9p59+arHtSmbq6+tV/Q5SIYMGDVK34YctPT1dCgsLG70PuI9Ex8svv6zS2Uj52eG+bzpWrlyp0k4oKbjhhhvU/r/iiivU/p48ebK1f51+f7jvo+Ovf/2rlJeXq5ODlJQU9Tt/++23y5lnnqnu576PXyioCAkjUrJkyRJ1tkiannXr1smUKVNU7RqaLkjznjwgQjV16lR1HREqfPZRswNBRZqOV199VV544QV58cUXZeDAgbJw4UJ1Ite5c2fu+ziHKb8EpW3btursxd7RhOsdO3Zsse1KVi677DJ555135LPPPpOuXbtat2NfI/1aVlbmtzzfh+hBSg8NFsOHD5fU1FR1QeE5inHxN87Iue+bBnSPDRgwwO+2/v37y9q1a9Xfev/y9yf2XHvttSpKddppp6nOyrPPPls1X6DjGHDfxy8UVAkKQu8jRoxQuXbzrBLXx44d26LblkygPRli6o033pBPP/1UtTKb4D1AJ5T5PsBWAQcevg/RceSRR8r333+vztD1BVETpD7039z3TQPS2nZ7ENT09OjRQ/2N7wEO3ua+R5oKHWfc99FRVVWl6mFNcPKM33fAfR/HtHRVPImcl19+WXV2PPfcc56lS5d6LrroIk9hYaFn8+bNLb1pScMll1ziKSgo8Hz++eeeTZs2WZeqqiprmYsvvtjTvXt3z6effuqZO3euZ+zYsepCYo/Z5Qe475uG2bNne1JTUz2333675+eff/a88MILnuzsbM9//vMfa5k777xT/d689dZbnsWLF3t++9vfenr16uXZvXt3i257ojN58mRPly5dPO+8845n1apVntdff93Ttm1bz1/+8hdrGe77+ISCKsF5+OGH1QElPT1d2SjMmjWrpTcpqcA5h9Nl2rRp1jL4EfvTn/7kKSoqUgedk046SYku0vSCivu+6fjf//7nGTRokDpp69evn+fJJ5/0ux/t+zfeeKOnQ4cOapkjjzzSs2zZshbb3mShvLxcfcbxu56ZmenZb7/9PH/729881dXV1jLc9/FJK/zT0lEyQgghhJBEhjVUhBBCCCFRQkFFCCGEEBIlFFSEEEIIIVFCQUUIIYQQEiUUVIQQQgghUUJBRQghhBASJRRUhBBCCCFRQkFFCCGEEBIlFFSEEOKCc845R0488cSW3gxCSJyS2tIbQAghLU2rVq2C3n/zzTfLQw89pIZlE0KIExRUhJB9nk2bNll/v/LKK3LTTTfJsmXLrNtyc3PVhRBCAsGUHyFkn6djx47WpaCgQEWszNsgpuwpv1/96ldy+eWXy5VXXilFRUXSoUMHeeqpp2TXrl1y7rnnSl5envTu3VtmzJjh91xLliyRY445Rq0Tjzn77LNl+/btLfCqCSGxhIKKEEIi5Pnnn5e2bdvK7Nmzlbi65JJL5NRTT5Vx48bJ/PnzZcKECUowVVVVqeXLysrk17/+tQwbNkzmzp0r77//vmzZskUmTZrU0i+FEBIlFFSEEBIhQ4cOlb///e/Sp08fuf766yUzM1MJrAsvvFDdhtRhSUmJLF68WC3/yCOPKDE1depU6devn/r72Weflc8++0yWL1/e0i+HEBIFrKEihJAIGTJkiPV3SkqKFBcXy+DBg63bkNIDW7duVf8vWrRIiSeneqxffvlFDjjggGbZbkJI7KGgIoSQCElLS/O7jtor8zbdPVhfX6/+r6yslOOPP17uuuuuRuvq1KlTk28vIaTpoKAihJBmYvjw4fLf//5XevbsKamp/PklJJlgDRUhhDQTl156qezYsUNOP/10mTNnjkrzffDBB6orsK6urqU3jxASBRRUhBDSTHTu3Fm++eYbJZ7QAYh6K9guFBYWSuvW/DkmJJFp5aH1LyGEEEJIVPCUiBBCCCEkSiioCCGEEEKihIKKEEIIISRKKKgIIYQQQqKEgooQQgghJEooqAghhBBCooSCihBCCCEkSiioCCGEEEKihIKKEEIIISRKKKgIIYQQQqKEgooQQgghRKLj/wMIg2ZyTKHe1gAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2029,7 +1921,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "64e7f82b-3632-41f4-a5be-9421a817b3d4",
    "metadata": {},
    "outputs": [
@@ -2062,10 +1954,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "id": "69a3a77d-2a2a-4944-8923-05159d52ad8d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([400960., 400980., 401000., 401020., 401040., 401060., 401080.,\n",
+       "        401100.]),\n",
+       " [Text(400960.0, 0, '400,960'),\n",
+       "  Text(400980.0, 0, '400,980'),\n",
+       "  Text(401000.0, 0, '401,000'),\n",
+       "  Text(401020.0, 0, '401,020'),\n",
+       "  Text(401040.0, 0, '401,040'),\n",
+       "  Text(401060.0, 0, '401,060'),\n",
+       "  Text(401080.0, 0, '401,080'),\n",
+       "  Text(401100.0, 0, '401,100')])"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x440 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Plot Delft3D interpolated Data\n",
     "fig, ax = plt.subplots(figsize=(10, 4.4))\n",
@@ -2113,7 +2035,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "id": "d01e3d76-daab-4597-8b5d-5b588f6c81c2",
    "metadata": {},
    "outputs": [],
@@ -2135,7 +2057,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "id": "147f4bf3-7ad3-4cb0-8c08-fd946557e2f8",
    "metadata": {},
    "outputs": [],
@@ -2165,10 +2087,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "id": "bf78c6e0-c4cd-421e-b9c0-3465d05c6dd3",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.32240335443242324"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Calculate and priont the Mean Absolute Error\n",
     "MAE = np.sum(L1_Magnitude * error_filter) / len(L1_Magnitude[L1_Magnitude < 1000])\n",
@@ -2177,10 +2110,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "id": "0acdaf51-d08e-4d9e-8070-4d2e5477b456",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([400960., 400980., 401000., 401020., 401040., 401060., 401080.,\n",
+       "        401100.]),\n",
+       " [Text(400960.0, 0, '400,960'),\n",
+       "  Text(400980.0, 0, '400,980'),\n",
+       "  Text(401000.0, 0, '401,000'),\n",
+       "  Text(401020.0, 0, '401,020'),\n",
+       "  Text(401040.0, 0, '401,040'),\n",
+       "  Text(401060.0, 0, '401,060'),\n",
+       "  Text(401080.0, 0, '401,080'),\n",
+       "  Text(401100.0, 0, '401,100')])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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C5HihvOHCdWUyF61z4TqpLXPROheuK5e5aJ0L1ykTF5SbV2RkJIYNGyZvz58/X8VqTCuzA6LkQjbSASHTYVdEOXZFyFqwK2I8TtFyXAwclpGSkoJixYrJ25cuXbKLqVdkGnz7cmBcK6IM14qQteBaEdPgFC3HwOBhWe7u7vL1L7/8EuXKlVOxGtNTfh4Q/h4CDCAEdkWMwa4IWQt2RYzHroj9YehQR9myZeXr3bp1w5AhQ1Ssxjx0QoJOKFgDouAx9ohvVaSHYUQZdkXIWrArYhrsitg2Bg/1fPDBB7h69SoAwM/PDxs2bFC5IvPQKeyA8DwgGfj2RLniFC1lGEbIWrArYjx2RWwHQ4f69u/fjyVLlsjbjx8/VrEasmZ8W6KXYldEOU7RImvArohpsCtinRg8rMODBw/QpEkTeTs+Pt6uF53rhAY6BUe0UvIYe8S3IjIIuyLKsCtC1oJhxHjsiqiPocP6ZD1P26+//op8+fKpWI35aSFBq+CcHkoeY4/49kOKsCuiHLsiZC04Rct4DCOWxeBhnU6cOAGdLuOzwFtvvYVmzZqpXJH5sQNiHL7tkNHYFVGGXRGyFuyKmAanaJkHQ4f1q1u3rnx98+bNKlZCtoJvNWQy7Ioox64IWQt2RYzHrohpMHjYhh07dsjXZ8+erXf+D3umhbLpVFrTl2KT+BZDZsGuiDLsipC1YFfENNgVMQxDh20RQqB9+/by9kcffaReMRbGKVjG4dsKmRW7IsqxK0LWgl0R47Er8mIMHrYp63SrefPm2fVRr/5LKzTQKggTSh5jjzgKZDFpXhr5QnnnEZMqX4jUpEn/90LKucTrBxJH5RynkS9ke7RaLbp27SpvDx8+XMVqLE9Agk7BRSg8CtbSpUsRGhoKd3d31K5dG3/++ecL779w4UKULVsWHh4eCAkJwahRo5CcnKzotc2B/+pJFQwiyjCIkLVgEDFeZhBxtDDC0GEfZs+eLV+fOnUqnJ3ZIjWXTZs2ITw8HFOmTEFERASqVKmC5s2bIzo6Osf7b9iwAePGjcOUKVNw6dIlrFy5Eps2bcKECRMsXHnu+NtCquIULWW4VoSsBdeKmIa9rxVh4LAvcXFx+Pjjj+XtMWPGqFiNOoydghUXF6e3383NDW5ubjk+Zv78+Rg4cCD69esHAFi2bBl27dqFVatWYdy4cdnu/8cff6B+/fro3r07ACA0NBTdunXDyZMnDa7XXPgXgawGuyLKsCtC1oJdEePZW1eE3Q775OvrK1+/cOECPD09VaxGHTohKb4AQEhICHx9feXLrFmzcnyd1NRUnD59Gk2bNpX3aTQaNG3aFMePH8/xMfXq1cPp06flaVo3btzA7t270apVKxOPgnL8voqsDrsiyrArQtaCXRHTsNWF6wwc9u2NN96Qrw8bNgwVK1ZUsRr1aKGBVsH3+JmPiYyMhI+Pj7w/t+5HTEwMtFotgoOD9fYHBwfj8uXLOT6me/fuiImJweuvvw4hBNLT0zF48GCrmoLFvxJk1dgVUYZdEbIW7IqYhrV3Rbig3DFMnToVR44cAQC4uLhg8eLFKldku3x8fPQuuQUQJQ4ePIiZM2fiyy+/REREBLZu3Ypdu3Zh+vTpJnsNY/G7KbIJ7Ioow64IWQt2RUzD2roiDByOY8OGDfjkk0/k7efPn6tXjBXIOp3K0McZIjAwEE5OTnj48KHe/ocPH6JgwYI5PmbSpEno1asXBgwYAACoVKkSEhMTMWjQIEycOBEajfr/btWvgMhAPJyvMuyKkLVgV8Q01OqKsNvheGbPno0ePXrI248ePYKTk5OKFalPB43iiyFcXV1Ro0YN7Nu379/X1umwb98+1K1bN8fHJCUlZQsZmf+/hBAG/qTmwe+hyKbxjOuGY1eErAW7IqZhqa4IA4fjSUlJQVBQEOLj//0lO3/+PAIDA1WsyjpohQStgg6IkseEh4ejT58+qFmzJmrVqoWFCxciMTFRPipW7969UaRIEXkhe5s2bTB//nxUq1YNtWvXxrVr1zBp0iS0adPGaoIj/+STXeAULWV4tnWyFgwjpmHqw/kydDiuefPmZTu8bnR0NIKCglSqyHF17doVjx49wuTJkxEVFYWqVatiz5498sL0O3fu6HU8Pv74Y0iShI8//hj37t1DUFAQ2rRpg08//VStHyEbSVhLL8YC4uLi4Ovri9jYWL0jD9iCOj3mqV2CzckpiLjGcd7Hy7wsjKTlU3YWV9KX7sFxfJmXBRGt6dZs2rWXhZE03+x/Kxk8DHf141Fql2ASR44c0TvSFQCEhYVh//79kCTL/N2y5s9rmbW9d/htuOVzMfjxKQlpWP7GFqv82SyJ3zOR3WJXRBl2RchasCtiGnmdosXQ4dgePHiAwoULZ9t//vx5vPrqqypUZN2E0ECn4ESEQsFj7BFHgRwCF60bLnPROheukzXgwnXTyGnhOheUO7a0tDQ0aNAgW/hYtWoVhBAMH7nQQlJ8IXZAbMaJ9aPVLsHmNas3Q+0SbJbbs38/+aUpaDlTds5JDjP71aScU/4dt/ii/NCsVNYQkuq4s0Ac3tSpU/UOrQsAffr0werVqy023YocEwMIEeUqPYew4f5ECwDQuvHDnzHSPPnmboiswUPel6RCIXZE/P8nAHtZu0B5t3fvXrRo0UJvX+HChXH58mV4e1vBCWZsgE4Yfk6PzMcRAwgR/UdOoSMnTin/rqthGCFzyCl0kHEE3/UdWkxMTI5Hsbp48SLKly+vQkW2S6dwDYiSx9gjjgIRAcgIHnkNH//llKLTCyRExnBOEQwfJiacGT4c3bZt27KFjx9++AFCCIYPBXSQFF+IAYTIoWWGDqXB478ygwjDCBkqM3QweJhOZuhg8KCZM2eiY8eO8nb37t2h0+nQuXNnFasiR8Y/S0QOxlRh42UyQwinZ1FuGDbMg4GDsvr6668xceJEefvs2bOoUqWKihXZB0ueCd0e8c8UkYOwVPD4L64Vof9i8DA9hg7KyZYtW/Dee+/J21FRUfLZs8k4XANiHP7JIrJjaoWO3LAr4rgYOsyDwYNys2bNGvTr10/evnPnDsOHCekgKTsKFteAAGAAIbJL1hY8/otdEcfB4GF6DB30Mt988w0GDhwob1+5cgUhISEqVkSkz2be+du2bYtixYrB3d0dhQoVQq9evXD//n21yyKyGqZeUG4pXLRuf7ig3Dy4oJxeRgiBdu3a6YWP3bt3o0yZMipWZZ+EwiNgCXZAANhQB6RRo0aYMGECChUqhHv37mHMmDHo1KkT/vjjD7VLI1KVrQWO3LArYvsYOEyPgYPy6ty5c6hatarevtu3b6NYsWLqFGTndELhFCwuQgdgQwFk1Kh/z9RavHhxjBs3Du3bt0daWhpcXOzjAxhRXtlL6MgN14rYDoYO82DwoLxKT09H7dq1ERERobc/Li6OZzU3Iy5CN45NjsKTJ0+wfv161KtX74XhIyUlBXFxcXoXIltmi1OsjMHzilgvTrEyPZ63gwz1ww8/wMXFRS98rFixAkIIhg+yajb1Z27s2LFYsmQJkpKSUKdOHfz8888vvP+sWbMwdepUC1VHZB6OFDhehF0R9TFwmAcDBxnqyZMnCAgI0NtXokQJXL58Ga6uripV5Vg4Bcs4qr6Tjxs3DpIkvfBy+fJl+f4ffvghzpw5g19//RVOTk7o3bs3hMj9DXH8+PGIjY2VL5GRkZb4sYhMwtG6HXnFrojlsdtheux2kFJjx47NFj6OHTuGGzduMHxYkJIF6JkXUrkDMnr0aPTt2/eF9ylZsqR8PTAwEIGBgShTpgzKly+PkJAQnDhxAnXr1s3xsW5ubnBzczNlyURmxcBhGHZFzIeBwzwYOEipCxcuoFKlSnr7evfujTVr1kCS+KHW0tgBMY6qfwqDgoIQFBSk6LE6XcYHj5SUFFOWRKQKBg/j8AhapsPgYXoMHWSM2NhYVK5cGXfu3NHbf/fuXRQpUkSlqoiMYxPv1CdPnsSSJUtw9uxZ3L59G/v370e3bt1QqlSpXLsfRNbOVs/bYe04PctwPG+HeXCKFSkVHR2N8PBwSJKE/Pnz64WPpUuXQgjB8KGyzA6IkgvZyCJ0T09PbN26FVOmTEFiYiIKFSqEFi1a4OOPP+YUK7I5DByWwa7IyzFwmB4DBynx7NkzfP3115gwYQK0Wm2O96lVqxaOHDnCdR5WglOwjGMTfyorVaqE/fv3q10GkWIMHeriWpF/MXSYB4MHKXHmzBlUr179hfcpXLgw/vnnH3h6elqoKsoLBhDj8N2YyEw4xcr6OOoRtDjFyjx4JCsyxpgxY3IMH9WqVcPu3buh0+kghMC9e/cYPsju8M8mkYkxcNgGR5iixcBhHgwcZAytVgtPT0+kpqbK+7p164YVK1bAy8tLxcrIEAJQdEhd/lXOwD+jRCbA0GHb7GmKFkOHeTB0kClcuXIF5cqV09v38OFDFChQQKWKSClOwTKO7b/bEqmIU6zsiy1P0eIUK/PgFCsyBa1Wi4EDB+qFjzp16kAIwfBho3gULOPwzyqRgRg4HIMtdEUYOMyDgYNM6fz586hcubLevq+//hoDBw5UqSIi9fHPLFEeMXg4JmtcK8LgYXoMHWRqaWlp6NatG7Zs2aK3Pzo6WvFJmMl6cAqWcazj3ZTISvFIVpSVmtOzeCQr8+AUKzK1mJgY1K9fH66urnrhY+rUqdDpdAwfdoJTsIzDP7tEOWDgoBexZFeEgcP0GDjIXDZv3owuXbpk23/58mWULVtWhYrIXISQIBSECSWPsUfsgBD9P3Y7SAlzdEXY7TAPdjvInObNm6cXPgIDA3H9+nUIIRg+iP6Df4rJ4TFwkCmYoivCwGF6DBxkCevWrcOYMWPk7YMHD6Jhw4YqVkTmpoOk6DwgSh5jj/inmRwSQweZkyFH0GLoMA8GD7KU5cuXY/DgwfJ2REQEqlWrpmJFZAlchG4c/okmh8LgQZb0oq4Ig4fpMXSQJQkh0LRpU+zfv1/et3//foYPB8E1IMbhn2tyGFoPZ0hagfR8TmqXYtPSPbh0zBhO/x88PO6lyPt0rhxTJZ77uwNg8CDLO3r0KBo0aKC378qVKyhTpoxKFZGlsQNiHP7ZJofjnKCVrzOMkCU4vaTboUnN6JQwiBjG72pqtn0JRdjlJPOJjY1FuXLlEBUVJe/z8fHBw4cP4e7urmJlRLaF73bk0JwTtHqBhMiUnFLES8NHVppUnXwhZfLdS0O+e2lql0F2Jjo6GqVLl0b+/Pn1wse2bdsQGxvL8OGAMqdgKbkQOyBEANgVIdMxJHC8CLsixskaQtgVIaW2bt2Kt99+O9v++vXr49ChQ3By4vuFoxIKp2AxgGQwOIDcvHkTR44cwe3bt5GUlISgoCBUq1YNdevW5TcAZBcYRkgJUwWP/8raDWEYUSYzjDCIUF5otVoMGzYMy5Yty3Zb5cqV8fvvv/Ns5gQBQCj4s8/Dj2TIcwBZv349vvjiC5w6dQrBwcEoXLgwPDw88OTJE1y/fh3u7u7o0aMHxo4di+LFi5uzZiKLyQwjDCKUE3OFjtywK2IcdkXoRaKjo9GyZUtERERkuy08PByfffYZnJ05cYQcQ1paGlq0aIFly5ahdOnSJn/+PP1LqlatGlxdXdG3b19s2bIFISEherenpKTg+PHj2LhxI2rWrIkvv/wSnTt3NnmxRGphV4SysnTw+C92RYzHrghlevr0KV599VXcv38/221HjhzB66+/rkJVZO10kCDZ8YkIXVxc8Pfff5vt+fP0zjV79mycPHkSQ4cOzRY+AMDNzQ1hYWFYtmwZLl++jJIlS5q8UCJrwYXrjilzQbna4eO/uGjdOJmL1rlw3fFotVq0atUK/v7+euEjNDQUd+/ehRCC4YNy5QiL0Hv27ImVK1ea5bnz1AFp3rx5np8wICAAAQEBigsishXsijgGawscueH0LOOxK+I4Fi9ejOHDh+vtq1+/Pvbs2YN8+fKpVBXZEp2QINn5eUDS09OxatUq/P7776hRowa8vLz0bp8/f77i51Y8mTE6OhrR0dHQ6fS/eatcubLiYohsFdeK2BdbCR054fQs43GtiP3666+/UKtWLb19+fLlQ2RkJPLnz69OUURW6sKFC6hevToA4OrVq3q3SZJxQcrgAHL69Gn06dMHly5dgvj/5f+SJEEIAUmSoNVyago5LnZFbJstB4+csCtiPHZF7MOzZ89QuHBhPH/+XG//qVOnUKNGDZWqIlsmhMKjYNnQ28yBAwfM9twGB5B3330XZcqUwcqVKxEcHGx0AiKyV+yK2AZ7Cx05YVfEeOyK2K7vv/8e3bt319u3dOlSDB06VKWKyB4oXc9hS2tAzMngAHLjxg1s2bIFr7zyijnqIbI77IpYJ0cIHjlhV8R47IrYBiEE3n33XaxZs0be99Zbb2H79u08gSAZzVECyLNnz7By5UpcunQJAFChQgX0798fvr6+Rj2vwe9ATZo0wblz54x6USJHxSNoqctaj2SlhsyjZ/EIWsrxCFrWKykpCQEBAXrhIyIiAj/99BPDB1EenTp1CqVKlcKCBQvw5MkTPHnyBAsWLECpUqVyPF+OIQzugHzzzTfo06cPLly4gFdffRUuLvrfALVt29aogogcAbsilsXA8WLsihiPXRHrceLECdStW1dvX0xMDI/QSSblCEfBGjVqFNq2bYsVK1bIJ+FMT0/HgAEDMHLkSBw+fFjxcxscQI4fP45jx47hl19+yXYbF6ETGY5rRcyDocNwXCtiPK4VUdfbb7+NrVu3yttVq1bF8ePH4e7urmJVZI8cYRH6qVOn9MIHADg7O+Ojjz5CzZo1jXpug99hPvjgA/Ts2RMPHjyATqfTuzB8ECmXOT2LU7SMwylWpsHpWcbj9CzLiYmJgSRJeuFjy5YtOHPmDMMHmUVGAFFyIkK1K887Hx8f3LlzJ9v+yMhIeHt7G/XcBgeQx48fY9SoUQgODjbqhYkodwwihuHaDvPhWhHjca2I+QghMHXqVAQFBentT0pKQseOHVWqisg+dO3aFf3798emTZsQGRmJyMhIbNy4EQMGDEC3bt2Mem6Dp2B17NgRBw4cQKlSpYx6YSJ6Oa4VeTEGDsviWhHjca2IaQghsHjxYowYMUJv/0cffYTPPvtMparIkTjCUbDmzp0LSZLQu3dvpKenAwBcXFwwZMgQzJ4926jnNjiAlClTBuPHj8fRo0dRqVKlbIvQhw8fblRBRJQzrhXJwNChPgYR43GtiHI5ndcDyDhNQIkSJVSoiByR+P+LksfZgrS0NLRs2RLLli3DrFmzcP36dQBAqVKl4OnpafTzKzoKVr58+XDo0CEcOnRI7zZJkhhAiMzMUbsiDB7Wh4vWTYNhJG+SkpJQvHhxxMTE6O3fuXMn2rRpo1JV5KjsvQPi4uKCv//+GwDg6emJSpUqmfT5DQ4gN2/eNGkBRKScvXdFGDpsB7sipsEpWjnT6XTw8vLS23fw4EE0bNhQpYqI7F/Pnj2xcuVKo6db5cTgAEJE1seeuiIMHbaNXRHTYFdEX9YD3wQGBuL27dsmmQZCpJi9z8FCxjk/Vq1ahd9//x01atTI9iXA/PnzFT93nt4dZs+ejefPn+fpCU+ePIldu3YpLuhlUlJSULVqVUiShLNnz5rtdYhsla0eQYtHsbI/PHqWaTj6EbSaNWsmT7vy9fVFVFQUwwepT9EheCVA4RSspUuXIjQ0FO7u7qhduzb+/PPPF97/2bNneP/991GoUCG4ubmhTJky2L17t0GveeHCBVSvXh3e3t64evUqzpw5I1+M/Qyepw7IxYsXUaxYMXTu3Blt2rRBzZo15UPepaen4+LFizh69Ci+++473L9/H99++61RRb3IRx99hMKFC+PcuXNmew0ie2ALXREGDsfArohpOGJXZOTIkfj999/l7adPn0KSbGMOPdk3S56IcNOmTQgPD8eyZctQu3ZtLFy4EM2bN8eVK1dQoECBbPdPTU1Fs2bNUKBAAfz4448oUqQIbt++jfz58xv0ugcOHDC82DzK0zvBt99+i99//x1paWno3r07ChYsCFdXV3h7e8PNzQ3VqlXDqlWr0Lt3b1y+fBlvvPGGWYr95Zdf8Ouvv2Lu3Ll5un9KSgri4uL0LkSOyNpOcshuh+NiV8Q0HKEr8sUXX+CLL76Qt9PT0xk+yG789/NpSkpKrvedP38+Bg4ciH79+qFChQpYtmwZPD09sWrVqhzvv2rVKjx58gTbt29H/fr1ERoaioYNG6JKlSp5ri8tLQ1NmjTBP//8Y/DPlhd5/iqqSpUqWLFiBR4/fozTp09j8+bNWLFiBfbu3YuHDx/i1KlTGDx4sNnOOPrw4UMMHDgQ69aty3PrddasWfD19ZUvISEhZqmNyJaoFUR4skDKiic4NA17Pcnh5s2bMXLkSHk7NjYWTk7W2cklx6TsLOj/HjkrJCRE7zPqrFmzcnyd1NRUnD59Gk2bNpX3aTQaNG3aFMePH8/xMTt37kTdunXx/vvvIzg4GK+++ipmzpwJrTbv7/1Zj4JlDgYvQtdoNKhatSqqVq1qhnJyJoRA3759MXjwYNSsWRO3bt3K0+PGjx+P8PBweTsuLo4hhOj/WWqKFgMHvQyPoGUa9nIErV9++QVdunSRt2/cuAEfHx8VKyLKgdL1HP//mMjISL3fazc3txzvHhMTA61Wq3cgBiDjwAyXL1/O8TE3btzA/v370aNHD+zevRvXrl3D0KFDkZaWhilTpuS5VLs9Cta4ceNeesbSS5cu4ddff0V8fDzGjx9v0PO7ubnl+j+UiP5l6sP5MnSQElwrYhq2ulbk3LlzaN68OR4+fCjvO3z4ME8uSFbJ2DUgPj4+ZgvWOp0OBQoUwNdffw0nJyfUqFED9+7dw5w5cwwKIOY8CpaqAWT06NHo27fvC+9TsmRJ7N+/H8ePH88WJmrWrIkePXpg7dq1ZqySyHEY2xVh8CBTYVfENGyhK7JixQoMGjQo2/5NmzahQYMGKlREZD0CAwPh5OSkF8yBjKUJBQsWzPExhQoVgouLi960xfLlyyMqKgqpqalwdXXN02tnHgULAK5evap3m7HrsVQNIEFBQfLRtF5k0aJFmDFjhrx9//59NG/eHJs2bULt2rXNWSKRw8prV4Shg8yJQcQ0rLErEhsbm+NReapXr46DBw/C29vb8kUR5ZWFzgPi6uqKGjVqYN++fWjfvj2AjA7Hvn37MGzYsBwfU79+fWzYsAE6nQ4aTcbfzqtXr6JQoUJ5Dh+AFRwFS23FihXDq6++Kl/KlCkDAChVqhSKFi2qcnVE9i23I2hxQTlZEhetm441LFo/evRotvCxYcMGCCFw+vRphg+yesYuQjdEeHg4VqxYgbVr1+LSpUsYMmQIEhMT0a9fPwBA79699ZYpDBkyBE+ePMGIESNw9epV7Nq1CzNnzsT7779vsp/fWDwTOjkMnQsP32gsTYoObik6aN1t4rsLslOZIcTlcRJSgvOpXI3tUiOE3L9/Hw0aNMCNGzfkfe3bt8fWrVt5iF2yPRb6Dq5r16549OgRJk+ejKioKFStWhV79uyRF6bfuXNH7nQAGUfY2rt3L0aNGoXKlSujSJEiGDFiBMaOHZun12vVqhW+//57+Pr6Asg4IfngwYPlLw0eP36MBg0a4OLFi4p/JkkIw5bQJCYmYvbs2di3bx+io6Oh0+l/G5X1j4q1iYuLg6+vL2JjY3lEDQcU1uLFBzyg3GnS/v0zIZz+/ZCQ7skgopTXTZ6XyBT2nJuudgmUB0+ePEGdOnWynVNg165daNWqlUpVkbWy5s9rmbUV+3oyNB6Gn3pC9zwZdwZNs8qfLZOTkxMePHggn+TQx8cHZ8+eRcmSJQFkrD8pXLiwQYf1/S+DOyADBgzAoUOH0KtXLxQqVIjfWBDZsazBIyfOSRlfQDCIGE7n+e88XE1SqoqVEJnXvHnzMGbMGL195cqVQ0REBDw8PFSqisg4SqdTKXmMpf23N2FgryJPDA4gv/zyC3bt2oX69eubvBgiUt/LQkdOMoMIwDCiRGYYYRAhezNgwACsXLlS3i5TpgzWrVuHWrVqqVgVkQlYaBG6vTI4gPj5+cHf398ctRCRipQEj5wwjCjHrgjZk1GjRumFj7Nnz6JKlSoqVkRkStL/X5Q8zrpJkpRthpOpZzwZHECmT5+OyZMnY+3atfD09DRpMURkWaYKHbnhFC3l2BUhW7Z06VIsXLhQ3k5ISMh2EjMisk5CCPTt21c+/15ycjIGDx4s/xtOSUkx+jXyFECqVauml3yuXbuG4OBghIaGwsVF/3jiERERRhdFROZj7tCRE3ZFlGNXhGzNli1b9M5PwPBBdsmOp2D16dNHb7tnz57Z7tO7d2+jXiNPASTzxCdEZLvUCB45YVdEOXZFyNqtW7dO74PJ/fv3GT7IPtlxAFm9erXZXyNPAWTKlCnmroOIzMBaQkdO2BVRjl0Rskbjx4/H7Nmz5e0rV66gUKFCKlZEZEZCyrgoeRwZfib0kiVL4vHjx9n2P3v2TD4+MBGpS5MmrDp8/Jdzkk4vkFDe6Txd9QIJkRo6duyoFz5u3LiBMmXKqFgREVkzgxeh37p1K8cTj6SkpODu3bsmKYqIDGdLgSM37Ioox64IqaVx48Y4cOCAvP3s2TP5DMpE9kqIjIuSx5EBAWTnzp3y9b179+r9cdFqtdi3bx9KlChh2uqI6KXsIXjkhGFEOa4VIUtp2bKlXvhIS0uDs7PB320S2R47XgNiCXn+K5G5EF2SpGyr411cXBAaGop58+aZtDgiypm9ho7ccOG6MuyKkLmkpqaiWrVquHjxoryP4YMcigOsAenTpw/69++PN954w+TPned3c51OB51Oh2LFiiE6Olre1ul0SElJwZUrV/DWW2+ZvEAi+petre0wtcy1IlwvYjiuFSFTiIyMRP369eHm5qYXPlJSUhg+yKFIQvnFVsTGxqJp06YoXbo0Zs6ciXv37pnsuQ3+a3Hz5k2TvTgRvZwjB44XYVdEGXZFyBBCCPz55594//33cfr06Wy3e3p64unTp3B1zT3carVapKWlmbNMsjEuLi5wcnJSuwx6ie3bt+PRo0dYt24d1q5diylTpqBp06bo378/2rVrl+1cgIZQ9HXFvn37sGDBAly6dAkAUL58eYwcORJNmzZVXIgl8Q8h2QIGj7zhWhHluFaEcrNv3z4MGzYMly9fzvF2Pz8//Pzzz6hXr16uzyGEQFRUFJ49e2amKsmW5c+fHwULFtQ70bVNcZA1IEFBQQgPD0d4eDgiIiKwevVq9OrVC/ny5UPPnj0xdOhQlC5d2uDnNTiAfPnllxgxYgQ6deqEESNGAABOnDiBVq1aYcGCBXj//fcNLsLSzpw5YzNhiRwLQ4dx2BVRhl0RyqTValG5cmW96VWZfHx8sH79erRu3TpPHxozw0eBAgXg6elpux80yaSEEEhKSkJ0dDQA2O65YhxgDUhWDx48wG+//YbffvsNTk5OaNWqFc6fP48KFSrg888/x6hRowx6PoMDyMyZM7FgwQIMGzZM3jd8+HDUr18fM2fOtIkAsn79egYQsioMHqbFrohy7Io4rvj4ePj4+OjtK1SoEFasWIEWLVoYNGVGq9XK4SMgIMDUpZKN8/DwAABER0ejQIECtjkdywE6IGlpadi5cydWr16NX3/9FZUrV8bIkSPRvXt3+W/Ftm3b8O6775o/gDx79gwtWrTItv/NN9/E2LFjDX06VaxZs8Yip5knehGGDstgV0QZdkUcy82bN7OdTDguLg7e3t6Kni9zqrOnp6fRtZF9yvzdSEtLs80A4gAKFSoEnU6Hbt264c8//0TVqlWz3adRo0bInz+/wc9t8Dty27ZtsW3btmz7d+zYYVNHwUpPT1e7BHJQjn4kK7XwCFrK8Qha9uncuXOoUqUKJEnSCx8VK1aEVqtVHD6y4rQryo3N/24IIy42YsGCBbh//z6WLl2aY/gAMtbyKDlAlcEdkAoVKuDTTz/FwYMHUbduXQAZa0COHTuG0aNHY9GiRfJ9hw8fbnBBlnLmzBm89tprapdBDoKBw7pwipYy7IrYPp1Oh+XLl2Po0KE53t6uXTts2bIFGg3/XRC9kANMwWrYsCHc3Nyy7RdCIDIyEsWKFVP83AYHkJUrV8LPzw8XL17UW6SWP39+rFy5Ut6WJMmqA8ju3bsZQMisGDpsA6doKcO1IrbnzJkzqF69erb9Hh4e+PTTTzFkyBC4u7urUBmRDXKAReglSpTAgwcPUKBAAb39T548QYkSJaDVahU/t8OeB2TOnDmYMmWK2mWQHWLwsE3siijDrohtePfdd7Otffzqq68waNAgdjvyQJIkbNu2De3bt7fo6x48eBCNGjXC06dPFc2zJzKGECLHqXIJCQlGf1mh+LSlqampuHnzJkqVKmWTZz9NTEyEVqvlwicyCYYO+8KuiDIMI9YnOjoawcHBevu++uorvPfee7Y/B9+CHjx4AD8/P7XLUCw0NBQjR47EyJEj5X1r1qzByJEjeZ4WhZSe1dwWzoQeHh4OICN4T5o0Se9gElqtFidPnsx1TUheGZwckpKS8MEHH2Dt2rUAgKtXr6JkyZL44IMPUKRIEYwbN86ogizp3LlzObajifKKwcO+sSuiHKdoqW/ZsmUYMmSI3j5jjmzliFJTU+Hq6oqCBQua9XW0Wi0kSWI3ypbY8RqQM2fOAMjogJw/fx6urv9+ueTq6ooqVapgzJgxRr2Gwb/p48ePx7lz53Dw4EG99kvTpk2xadMmo4qxtIMHD6pdAtmgzKNYMXw4Fh5BS5nMI2jxKFqWc/fuXUiSpBc+Pv74YwghVA0fQggkJiZa/CJE3v9Wh4WFYdiwYRg5ciQCAwPRvHlzABnfBG/fvh0AUK9evWynHXj06BFcXFxw+PBhAEBKSgrGjBmDIkWKwMvLC7Vr19b7zLFmzRrkz58fO3fuRIUKFeDm5oY7d+7kWtexY8dQuXJluLu7o06dOrhw4YLe7Vu2bEHFihXh5uaG0NBQzJs3T+9nun37NkaNGgVJkiBJEg4ePIh+/fohNjZW3vfJJ58AAJ4+fYrevXvDz88Pnp6eaNmyJf75559stf/8888oW7YsPD090alTJyQlJWHt2rUIDQ2Fn58fhg8fbtQaAVLPgQMHcODAAfTp0we//PKLvH3gwAHs3bsXy5cvV3T286wM7oBs374dmzZtQp06dfTatxUrVsT169eNKsbSvvnmG7nNRPQyDBwEsCtiDHZFzCMlJQUnTpzA2rVrczzH1bVr11CqVCkVKtOXlJSEfPnyWfx1ExIS4OXllef7r127FkOGDMGxY8dyvL1Hjx74/PPPMXv2bPlz0KZNm1C4cGE0aNAAADBs2DBcvHgRGzduROHChbFt2za0aNEC58+flz+4JSUl4bPPPsM333yDgICAbAt9s/rwww/xxRdfoGDBgpgwYQLatGmDq1evwsXFBadPn0aXLl3wySefoGvXrvjjjz8wdOhQBAQEoG/fvti6dSuqVKmCQYMGYeDAgQAAf39/LFy4EJMnT8aVK1cAQP5/07dvX/zzzz/YuXMnfHx8MHbsWLRq1QoXL16Ei4uLXPuiRYuwceNGxMfHo2PHjujQoQPy58+P3bt348aNG3j77bdRv359dO3aNc9jT9bFnOfMMziAPHr0KMd/JImJiTYzn9TFxQVpaWm4dOkSdDodW56UK4YOehGGEWW4VsQ0li9fjsGDB+d6e5cuXbBx40abeW+2FqVLl8bnn3+e6+1dunTByJEjcfToUTlwbNiwAd26dYMkSbhz5w5Wr16NO3fuoHDhwgCAMWPGYM+ePVi9ejVmzpwJIOMEfF9++SWqVKny0pqmTJmCZs2aAcgISEWLFsW2bdvQpUsXzJ8/H02aNMGkSZMAAGXKlMHFixcxZ84c9O3bF/7+/nBycoK3t7feVDJfX19IkqS3LzN4HDt2DPXq1QMArF+/HiEhIdi+fTs6d+4s1/7VV1/JwbZTp05Yt24dHj58iHz58qFChQpo1KgRDhw4YLcBRILCNSAmr8S0wsPDMX36dHh5eb30S/r58+crfh2DA0jNmjWxa9cufPDBBwD+PZHMN998I58XxNqNHDkSc+bMAQBcuHABlStXVrkisjYMHmQoLlxXhl0Rw127du2F0x9GjhyJSZMmwd/f34JVvZynpycSEhJUeV1D1KhR44W3BwUF4c0338T69evRoEED3Lx5E8ePH8fy5csBAOfPn4dWq0WZMmX0HpeSkoKAgAB529XVNc+fP7J+vvL390fZsmVx6dIlAMClS5fQrl07vfvXr18fCxcuNPhgO5cuXYKzszNq164t7wsICNB7PSBjTLN21YKDgxEaGqrX4QoODkZ0dHSeX9vm2OlheM+cOYO0tDT5urkYHEBmzpyJli1b4uLFi0hPT8cXX3yBixcv4o8//sChQ4fMUaPJNWvWTA4gBw4cYAAhAAwdZBrsiijDrsjLCSHQunVr/PLLL3r7P/30UwwaNAiBgYEqVZY3kiQZNBVKLXmpsUePHhg+fDgWL16MDRs2oFKlSqhUqRKAjClfTk5OOH36dLYP/1k/oHt4eNhsdypzKlYmSZJy3KfT2fG6OTtdhH7gwIEcr5uawe+Or7/+Os6ePYv09HRUqlQJv/76KwoUKIDjx4+/9FsDa5G1TmPaR2QfuKCczIUL15XhovXs9uzZA41Goxc+Zs6cCSEEJkyYYPXhw960a9cOycnJ2LNnDzZs2IAePXrIt1WrVg1arRbR0dF45ZVX9C5Kj6Z14sQJ+frTp09x9epVlC9fHgBQvnz5bOtVjh07hjJlysgByNXVNduC8Jz2lS9fHunp6Th58qS87/Hjx7hy5QoqVKigqHayXbNmzcKqVauy7V+1ahU+++wzo55b0Qk8SpUqhRUrVhj1wmrKet6SO3fu5HqiFbJfDBxkSeyKKMOuSMa36UFBQUhOTpb3eXl5ISoqSpUF3ZTBy8sL7du3x6RJk3Dp0iV069ZNvq1MmTLo0aMHevfujXnz5qFatWp49OgR9u3bh8qVK6N169YGv960adMQEBCA4OBgTJw4EYGBgfJJEUePHo3XXnsN06dPR9euXXH8+HEsWbIEX375pfz40NBQHD58GO+88w7c3NwQGBiI0NBQJCQkYN++fahSpQo8PT1RunRptGvXDgMHDsTy5cvh7e2NcePGoUiRItmmeTk8O+2AZLV8+XJs2LAh2/6KFSvinXfeyXY0OEMY/E4YGxuLH3/8EXPnzsW8efOwbds2xMXFKS7AGmSd10j2jd0OUhu7Iso4Yldk4sSJ8Pb21gsfe/bsQUJCAsOHFejRowfOnTuHBg0aoFixYnq3rV69Gr1798bo0aNRtmxZtG/fHn/99Ve2++XV7NmzMWLECNSoUQNRUVH46aef5HMzVK9eHT/88AM2btyIV199FZMnT8a0adPQt29f+fHTpk3DrVu3UKpUKQQFBQHIOJzw4MGD0bVrVwQFBckL71evXo0aNWrgrbfeQt26dSGEwO7du7NNsXJ0mSciVHKxFVFRUShUqFC2/UFBQXjw4IFRzy0JAw6Q/d1332HYsGHZAoevry+WLVtm9Uc6iIuLg6+vL2JjY9GgQQP8/fffAIA5c+YYfUIVsn5hLT6D28MktcuwC5qUNLVLsGkJZfxwZPuHapdh81pUmYQ956arXYbJnTx5EnXq1NHb17p1a/z00082061PTk7GzZs3UaJECb1zhhFletHvSNbPaz4+PipVmLPM2kJnfAqNgt9tXXIybn080Sp/tv8qXbo0pkyZgp49e+rtX7duHaZMmYIbN24ofu48d0AiIiLQr18/tG/fHmfOnMHz58+RlJSEU6dOoU2bNujVqxfOnTunuBBL27t3r3z9ww/5QcARMHwYSZPlQkbJd/Wp2iXYBXsLHwkJCQgMDMwWPm7evImff/7ZZsIHEdmHgQMHYuTIkVi9ejVu376N27dvY9WqVRg1apR8Thml8rwGZPHixWjfvj3WrFmjt7969er49ttvkZSUhC+++CLHxSrW6L8LwbgOhCgXDBxEZjdhwgTMmjVLb9/q1av1ptEQkRVxgDUgH374IR4/foyhQ4ciNTVjHZ67uzvGjh2L8ePHG/Xcef5ocezYMbz33nu53j548GAcPXrUqGJeJDQ0FJIk6V1mz55tsue/evWqyZ6LyOax20FkdkIIHDhwAJIk6YWPxo0bIz09neGDyIo5whoQSZLw2Wef4dGjRzhx4gTOnTuHJ0+eYPLkyUY/d547IPfv3892Up2sypQpg3v37hld0ItMmzZNr+Xj7e1t1POdOnUKNWvWBAB0794dp0+fNur5iGweAweR0XI6+ZsQAn///Td+++03XLp0CSdOnMDFixezPfbWrVsoXry4pUolIqXs9ESEOcmXLx9ee+01kz5nngNIUlLSCxeSubm56R2pwxy8vb0NOoZ2SkoKUlJS5O3/Lp7Pej6QiIgI4wskskUMHURGEUJg8uTJmDFjhuLnWLx4MYYNG2bCqqyDAce5IQfD3w3b8OzZM6xcuVI+YmyFChXQv39/+Pr6GvW8Bp0HZO/evbm+4LNnz4wqJC9mz56N6dOno1ixYujevTtGjRqld06P/5o1axamTp2a5+fnOhByKAweREbbtGkT3nnnHcWPHzlyJD799FN4enqasCr1ZR6yNSkpCR4eHipXQ9YoKSnjwDA2e3hfB1gDcurUKTRv3hweHh6oVasWAGDBggWYOXMmfv31V1SvXl3xcxsUQPr06fPC28354X348OGoXr06/P398ccff2D8+PF48ODBC89kPn78eISHh8vbcXFxCAkJ0bvP5s2b0blzZwDAV199haFDh5rnByCyBgwdRCaRkpKCAgUKZOusV6pUCSEhIfj7779x7949+Pj4oHHjxujYsSPatm1r9YfdNBUnJyfkz58f0dHRAABPT09+wUcAMr7sTUpKQnR0NPLnz59tuqKtULqew5bWgIwaNQpt27bFihUr5C/809PTMWDAAIwcORKHDx9W/NwGnQfE1MaNG/fSU7lfunQJ5cqVy7Z/1apVeO+995CQkAA3N7c8vV5ux5XO+keRLUH71bzaFLVLUI+Jg4fmOc8DYqxfLs5UuwRS6PLlyyhfvrzevuPHj2c7fK6jE0IgKirKIjMkyPbkz58fBQsWzDGY2sJ5QEpOnqn4PCA3pk2wyp/tvzw8PHDmzJlsn8MvXryImjVryl0sJQzqgJja6NGjX3qUj5IlS+a4v3bt2khPT8etW7dQtmxZo+oYNGgQvv76awCQT4pDZPPY7SAyuQULFuh11uvVq4fDhw/b7Le45iRJEgoVKoQCBQogLY1fWtC/XFxc+G/GBvj4+ODOnTvZAkhkZKTRB4JSNYAEBQUhKChI0WPPnj0LjUaDAgUKGF3H3Llz5QDSsWNHnDlzxujnJFINgweRyQkhULJkSdy6dUvet3btWvTu3Vu9omyEk5MTP2yS/VF6SF0bmmjTtWtX9O/fH3PnzkW9evUAZJyW48MPP0S3bt2Mem5VA0heHT9+HCdPnkSjRo3g7e2N48ePY9SoUejZsyf8/PyMfn5vb28UL14ct2/fxtmzZ3H37l0ULVrUBJUTWQhDB5HZxMbGIn/+/Hr7IiMj+T5B5MgcYBH63LlzIUkSevfujfT0dAAZ3ashQ4YYfS4+m/jY4ubmho0bN6Jhw4aoWLEiPv30U4waNUruWphC1jO4T5s2zWTPS2Q2PFkgkdldvHhRL3yUKlUKOp2O4YPI0QkjLjbC1dUVX3zxBZ4+fYqzZ8/i7NmzePLkCRYsWJDn9de5Meiji1arxeHDhy2+oKx69eo4ceIEnj17hufPn+PixYsYP3680T98VmFhYfL1FStWICoqymTPTWRSDB1EFvHbb7+hYsWK8vb48eNx7do1Hs2JiByKp6cnKlWqhEqVKpnskOEGTcFycnLCm2++iUuXLmVrR9s6jUaDjz/+WD6R1OzZs7Fw4UJ1iyLKxMBBZDZCCAghoNH8+w/tv4dl37FjB9q2batGeURkhez1MLxZD7LxMi86FcbLGLwG5NVXX8WNGzfs8khRQ4cOlQPIF198gYkTJypeJE9kEgweRCal1WqxefNmjB07Fnfu3MnTYyIiIlCtWjUzV0ZEpL68HojJ2E6wwQFkxowZGDNmDKZPn44aNWrAy8tL73ZrP6bxixQqVAhr1qyRDw08cOBAbN++XdWayAExdBCZTGJiIlauXIlZs2YpmlrLxeZElCM7XYR+4MABi7yOwR91WrVqhXPnzqFt27YoWrQo/Pz84Ofnh/z585vkiFRqy3pIxR07duDRo0cqVkMOhWs7iIx25coVvPfee5AkCZIkIV++fBgxYkSO4cPPzw/jxo3D/PnzMWLECL3bOnTogPT0dIYPInJoR44cQc+ePVGvXj3cu3cPALBu3TocPXrUqOc1uANiqWSkFkmSEBkZiZCQEABASEgIkpOTVa6K7BYDB5Fi6enp2Lp1K+bOnYu//vrrpfcPCgrC+PHjMWDAgBxPorVw4UIIIZCQkGD0SbaIyL7Z6xqQrLZs2YJevXqhR48eiIiIQEpKCoCMQ5PPnDkTu3fvVvzcBgeQhg0bKn4xW1G0aFG0bt0au3btQkpKCk6cOIE6deqoXRbZEwYPIoNdvXoV06dPx3fffZen+9etWxdjxoxBu3bt8nwiPEmSGD6IKG9sKEwoMWPGDCxbtgy9e/fGxo0b5f3169eX10wrpehjkLnaMdZkx44d8vW6devKJ2AhUozn7SBSZMeOHZAkCWXLln1h+Bg6dCiuXr0qH9Xqjz/+QMeOHXkWbiIyPQc4D8iVK1fwxhtvZNvv6+tr9Ck5DP4otGXLFjRv3hweHh45tmPshZOTE1asWCFvN2jQQMVqyKYxdBAp8uDBA0iShPbt22e7rXbt2vjmm2+QlJQkB46lS5eidOnSli+UiBxO5hQsJRdbUbBgQVy7di3b/qNHj6JkyZJGPbfBH4sy2zErVqyAi4uLvL9+/fqIiIgwqhhrM2DAAAQEBAAATpw4gT179qhcEdkMdjuIFBNCYODAgShcuLDe/qlTpyIlJQVCCJw4cQL9+/eHh4eHSlUSEdm3gQMHYsSIETh58iQkScL9+/exfv16jBkzBkOGDDHquQ1eA2LOdow1un//vnzG9ZYtWyIxMdFkZ4EkO8TAQWSUkydPZltzN2LECCxYsIBnICci62Gnh+HNaty4cdDpdGjSpAmSkpLwxhtvwM3NDWPGjMEHH3xg1HMbHEAy2zGhoaF6+03RjrFGrq6uOHr0KF5//XUAgJeXF4Swod8eMj+GDiKjJSUloUSJEoiOjtbbHxMTI3eiiYishSMcBUuSJEycOBEffvghrl27hoSEBFSoUAH58uUz+rkN/uhkznaMtapfvz569eolbxub+shOcIoVkUnMnDkTXl5eeuFj7dq1EEIwfBCRdbLwIvSlS5ciNDQU7u7uqF27Nv788888PW7jxo25rqXLzYULF/S2XV1dUaFCBdSqVcsk4QNQ8PFp3Lhx6N69O5o0aYKEhAS88cYbGDBgAN577z27/mD+7bffyteXLFmS5//xZGe4toPIZG7evCl/w5bpjTfeQHp6ut5JYYmIHNmmTZsQHh6OKVOmICIiAlWqVEHz5s2zdYz/69atWxgzZozBB1KqXLkyateujRUrViA+Pt6Y0nNl8MeozDeLJ0+e4MKFCzhx4gQePXqE6dOnm6M+qxIbGytfr127tnwEMHIADB1EJiOEQK9evbJN27127RoOHTrEw+YSkfWzYAdk/vz5GDhwIPr164cKFSpg2bJl8PT0xKpVq3J9jFarRY8ePTB16lSDl0gcOnQIFStWxOjRo1GoUCH06dMHR44cMbzwFzD4I9W7776L+Pj4bO2YxMREvPvuuyYtztr4+PjonfXR3d1dxWrI7NjtIDK5yMhIaDQavfN5zJgxA0IIlCpVSsXKiIjyztjD8MbFxeldcvtSOzU1FadPn0bTpk3lfRqNBk2bNsXx48dzrW/atGkoUKAA+vfvb/DP1qBBA6xatQoPHjzA4sWLcevWLTRs2BBlypTBZ599hqioKIOf878M/mi1du1aPH/+PNv+58+f601TslctW7ZEmzZt5O0JEyaoWA2ZBUMHkVkcOXIExYoV09sXGxurNwWLiMgmGNkBCQkJga+vr3yZNWtWji8TExMDrVaL4OBgvf3BwcG5BoGjR49i5cqVeuezU8LLywv9+vXDoUOHcPXqVXTu3BlLly5FsWLF0LZtW6OeO88fs+Li4hAbGwshBOLj4/VS29OnT7F7924UKFDAqGJsxc6dO+Xrs2bNwt9//61iNWQS7HYQmdWvv/6qdwj3OXPmQAgBHx8fFasiIlJHZGQkYmNj5cv48eNN8rzx8fHo1asXVqxYgcDAQJM8JwC88sormDBhAj7++GN4e3tj165dRj1fng/Dmz9/fkiSBEmSUKZMmWy3S5KEqVOnGlWMLYmJiZH/x1apUgVpaWlwdjb4qMakNgYOIrPbtWsX3nrrLXn76NGjqF+/vooVEREZycjzgPj4+OTpC5jAwEA4OTnh4cOHevsfPnyIggULZrv/9evXcevWLb3ZOjqdDgDg7OyMK1euGDzd9fDhw1i1ahW2bNkCjUaDLl26KJralVWePzEfOHAAQgg0btwYW7Zsgb+/v3ybq6srihcvnu2stfYsICAAmzdvRufOnQEAfn5+ZjtSAACELp1ntud2FGUzrzB0GE3ry7NPK5VUyLHGbvv27ejQoYO8febMGVStWlW9goiITMBS5wFxdXVFjRo1sG/fPvlQujqdDvv27cOwYcOy3b9cuXI4f/683r6PP/4Y8fHx+OKLLxASEpKn171//z7WrFmDNWvW4Nq1a6hXrx4WLVqELl26wMvLy7AfIgd5DiANGzYEkHHYxJCQEGg0/BTXqVMnNGjQAEeOHEFCQgJmz56NcePGqV0W5cDzgQbpfjxogKk4PU9XuwSb4mihI9PmzZvRpUsXefv8+fN49dVXVayIiMhELHgm9PDwcPTp0wc1a9ZErVq1sHDhQiQmJqJfv34AgN69e6NIkSKYNWsW3N3ds/2dzZ8/PwDk+e9vy5Yt8fvvvyMwMBC9e/fGu+++i7Jly778gQYweM5Q8eLFAWSctfbOnTtITU3Vu71y5cqmqcxGHDp0SA5j48ePR4cOHUz+P4mU8XzAkEzqctTgAQAbNmxAjx495O1Lly6hXLlyKlZERGSbunbtikePHmHy5MmIiopC1apVsWfPHnlh+p07d0zaGHBxccGPP/6It956y2yHRTc4gDx69Aj9+vXDL7/8kuPtWq3W6KJsSebZ4DOnn5UrVw5arZYdIhUxeJCaHDl0ZFqwYAHCw8Pl7X/++QevvPKKihUREZmWpaZgZRo2bFiOU64A4ODBgy987Jo1awx6rawHWzIXgz+pjRw5Es+ePcPJkyfh4eGBPXv2YO3atShdurRFCrZGhQoV0vufGxoaqlotjsrzgUa+EKkhqZCHw4YPIQTOnj2LSZMmQZIkvfBx8+ZNhg8isj8WPBGhPTK4A7J//37s2LEDNWvWhEajQfHixdGsWTP4+Phg1qxZaN26tTnqtHp9+vTB3LlzceHCBURGRmL//v1o3Lix2mXZPQYOUpOjBo5MERER2LRpE7Zs2YLr169nu/3+/fsoVKiQCpUREZmZBdeA2CODA0hiYqJ8vg8/Pz88evQIZcqUQaVKlRAREWHyAm3JuXPn5LlyTZo0QXp6utnmzjkyhg5Sm6MHj4cPH+Kdd97Jte3fqlUrbNu2Da6urpYtjIiIbILBn+TKli2LK1euAMg4/8Xy5ctx7949LFu2zOG/6dJoNNiwYYO8ndtcPVKGU6xITZlTrBw5fKSnp6NmzZooWLBgjuGjSJEimDx5Mn766SeGDyKya5IRF1IQQEaMGIEHDx4AAKZMmYJffvkFxYoVw6JFizBz5kyTF2hrunXrJl9ftmwZ/vnnHxWrsX1c20Fqc/TQkWn9+vVwcXHB6dOn9fa///772LBhA27fvo27d+9i6tSpPAgHEdk/rgEBAJw8eVLR4/I8BevmzZsoUaIEevbsKe+rUaMGbt++jcuXL6NYsWImPeW7LTt37hyqVKkCAHjzzTdx8+ZNlSuyPQwcpCYGjn9FR0fLh3rMVLx4cZw9e1Y+tjwRkaOx9FGwrFXnzp1x584dgx+X5wBSqlQpFC9eHI0aNULjxo0RFhaGokWLwtPTE9WrVzf4he1Z5cqV8corr+DatWu4desWhBCQJDbd8oLBg9TE4KFv0KBBWLFihd6+EydOoHbt2ipVRERElpb1hLJZCSHw5MkTRc+Z5wCyf/9+HDx4EAcPHsT333+P1NRUlCxZEo0bN0ajRo3QqFGjbN+SObIdO3agYsWKAIC//voLtWrVUrki68XQQWpi6MguIiICNWrU0Ns3ZMgQfPnllypVRERkZRzoKFi///471q1bh3z58untF0Lg8OHDip4zzwEkLCwMYWFhAIDk5GT88ccfciBZu3Yt0tLSUK5cOfzvf/9TVIi9qVChgnx95cqVDCA5YPAgNTF4ZCeEQKdOnbB161a9/dHR0QgKClKpKiIiK2WDYUKJsLAweHt744033sh2W+XKlRU9p8GH4QUAd3d3NG7cGK+//joaNWqEX375BcuXL8fly5cVFWHvVq5cieXLl6tdhlVg6CA1MXTk7uHDhyhYsKDevnXr1umt+yMiogyOtAbkv19KZfXbb78pek6DPg2mpqbi8OHDmDp1Kho1aoT8+fNj8ODBePr0KZYsWcLF1v9RokQJAIBWq1W5EvXxSFakJh7J6sX27duXLXwkJiYyfBARUTb//PMPGjZsaNRz5PkTYePGjeHn54ehQ4ciOjoa7733Hq5fv44rV65gxYoV6NWrF4oVK2ZUMfamf//+apegKh5Cl9TE83bkzbRp09C0aVN5e+bMmRBCwNPTU8WqiIisnAMfhjc1NRVHjx416jny/MnwyJEjCAgIQOPGjdGkSRM0a9bM4ice3LVrF2rXrg0PDw/4+fmhffv2Fn19Q/Xp00e+nnnyRkfA0EFqYejIu8ePH0OSJEyZMkXed/LkSYwfP17FqoiIbEPmFCwlFzIggDx79gxff/01PD098dlnn6Fw4cKoVKkShg0bhh9//BGPHj0yZ53YsmULevXqhX79+uHcuXM4duwYunfvbtbXNFbRokXl6ytXrlSxEvNjt4PUxNCRd0lJSQgLC8t23qaYmBgeLIOIKK/suAMyePBgrFixAqdOnUJqaqpZXiPPi9C9vLzQokULtGjRAgAQHx+Po0eP4sCBA/j888/Ro0cPlC5dGhcuXDB5kenp6RgxYgTmzJmjN60p65GmcpKSkoKUlBR5Oy4uzuS15dU333yDzz//XLXXNxcGDlILA4dh/vzzzxzP39GmTRvs2LGD5yoiIiIAwPnz57F+/XokJibCxcUFFSpUQPXq1VGjRg1Ur14dGo3xn/0UHQULyAgk/v7+8Pf3h5+fH5ydnXHp0iWjC8pJREQE7t27B41Gg2rVqiEqKgpVq1bFnDlz8Oqrr+b6uFmzZmHq1KlmqSmv/Pz88PTpUzx9+lTVOkyJoYPUxOCRdzqdDh9//DFmzZqV7bagoCBcvnwZ/v7+KlRGRGTb7PkoWMeOHYMQAleuXEFERIR82bZtG549ewYARn9plecAotPpcOrUKRw8eBAHDhzAsWPHkJiYiCJFiqBRo0ZYunQpGjVqZFQxublx4wYA4JNPPsH8+fMRGhqKefPmISwsDFevXs31DXT8+PEIDw+Xt+Pi4hASEmKWGnMzYMAAzJkzx6KvaS4MHqQWhg7DJCcno02bNvj999+z3dauXTusW7cO3t7eKlRGRGQn7PxEhJIkoVy5cihXrpzekocbN27g9OnTOHPmjFHPn+cAkj9/fiQmJqJgwYJo1KgRFixYgLCwMJQqVUrxi48bNw6fffbZC+9z6dIl6HQ6AMDEiRPx9ttvAwBWr16NokWLYvPmzXjvvfdyfKybmxvc3NwU12cK7777rhxA7t69q7cuxBYwdJCaGDwMEx0djd69e2Pv3r3Zbtu8eTM6deqkQlVERHbIzgNIbkqWLImSJUuic+fORj1PngPInDlz0KhRI5QpU8aoF8xq9OjR6Nu37wvvU7JkSTx48ACA/poPNzc3lCxZEnfu3DFZPeZQrlw5+fratWsxceJEFavJOwYPUgtDh+GEEAgPD8fChQv19vv6+uL8+fMW7/wSERG9SJ4DSG5dBmMEBQUhKCjopferUaMG3NzccOXKFbz++usAgLS0NNy6dQvFixc3eV3msnLlSqsOIAwdpCYGD2ViY2ORP39+vX2enp64fPkygwcRkZnY8xoQS1C8CN2SfHx8MHjwYEyZMgUhISEoXry4PK3J2BaQJWg0Guh0Oqs9UzyDB6mFocM4165dQ+nSpfX2RUREoFq1aipVRETkIBx0Cpap2Mwnzzlz5uCdd95Br1698Nprr+H27dvYv38//Pz81C7tpazxjOg8bwepieftMF5ERIRe+OjWrRt0Oh3DBxGRBUhCKL6QDQUQFxcXzJ07Fw8fPkRcXBx+++03VKxYUe2y8mTAgAHydbUPx8vQQWrhWcpN59dff0WNGjXk7XXr1mHDhg08lwcREdkEfhK1gNdee02+vn79eou/PrsdpCaGDtP66quv0Lx5c3n7119/Rc+ePVWsiIjIAdnxmdAtgZ9ILSDrt5LffPONxV6XoYPUwm6HefTr1w9Dhw6VtyMiItCsWTMVKyIickyZi9CVXMhGFqHbk3Pnzpn1+Rk4SE0MHOYhhEBoaKjeYcfv3r2LIkWKqFgVEZED4yJ0o/DTqoV06dLFrM/Pbgephd0O83ry5Ak0Go1e+Hj+/DnDBxER2Sx+YrWQrEfCSkpKMslzcm0HqYmhw/w2b96MgIAAebtw4cLQ6XRwd3dXsSoiIuIULOPwk6uFNG3aVL6+ZcsWo56LoYPUxuBherGxsdi6dSu+++47DBgwAJIk6XVOP/roI9y7d49HuiIisgZchG4UrgGxEI3m38CwcuVK9OrVy7DH+6fI15P9TVaWQxEnGdqUcnmaLF/fe+oT9QqxMzqdDlOnTsW0adNeeL9z586hcuXKFqqKiIhehmdCNw4DiAoOHTqkdgkOx/ukB4CUl96P9GUNHmRau3fvRuvWrV94n0GDBmHZsmXsehARWRsuQjcKA4gFNW/eHHv37lW7DIeRETrIUAwd5vfGG2/gyJEjevuGDx+OZs2awc/PD9WqVYOnp6dK1REREZkXA4gFDRgwQA4g6enpcHbm8JsDg4cyDB7mJ4SAq6sr0tPT5X27d+9Gy5YtVayKiIiU4HQq5fgJ2ILatm0rX9+9e7feNhmHoUMZhg7LEULorQUDMg6nyyNaERHZICEyLkoeRzwKliW5urrK11euXKliJfbD+6QHw4eBXJ4myxeyDJ1Opxc+QkJCIIRg+CAislE8DK9x2AFRyc6dO9UuwWYxcCjDwKGO+Ph4+Pj4yNvFixfHrVu31CuIiIhIZeyAWFidOnXULsEmZXY6GD4Mw26Hum7duqUXPmrWrMnwQURkD3geEKMwgFhY1jOiC84DfCmGDmUYOtT38OFDlChRQt7u0KED/vrrLxUrIiIiU5F0yi/EAGJxXbt2la8fPnxYxUqsF7sdyrDbYT3S0tJQsGBBebtLly7YsmWLihUREZFJsQNiFAYQC/P29pavcyG6PoYOZRg6rM/rr78uX69Vqxa+//57nkyQiIjo/zGAqGjdunVql6A6djuUYbfDek2cOBF//vmnvH306NFsh98lIiLbxqNgGYdHwVJB+fLlcenSJbXLUBUDhzIMHNbtp59+wsyZM+XtxMREuLi4qFgRERGZBc8DYhR+LaeCrAvRHQm7Hcqw22Ebrl+/rndy0UePHsHT01PFioiIyFzYATEOA4gKevXqJV8/e/aseoVYAEOHcgwdtiM9PR2vvPKKvH3u3DkEBgaqWBEREZH1YgBRQYECBeTr9roQnaFDGXY7bJOHx7+/66tXr0blypVVrIaIiMyOR8EyCgOIyuwpgLDboRxDh+0aOXIk0tPTAQBhYWHo27evugUREZHZcQqWcbgIXSWFChXCgwcP8Pz5c7VLMRoDhzIMHLbv119/xRdffCFvHzhwQMVqiIjIYrgI3SjsgKhkwIABapdgFHY7lGO3wz5cvHgRzZs3l7fj4uJUrIaIiMh2MICopF+/fvL169evq1iJYRg6lOHaDvty//59VKxYUd4+ffq03klGiYjIvnEKlnEYQFRSokQJ+frq1atVrOTl2O1QhqHDPkVHR6NIkSLy9ubNm1G9enUVKyIiIovjInSjMIBYgW+++UbtEnLE0KEMQ4f9SklJQXBwsLw9adIkdOrUScWKiIhIDeyAGIeL0FXk5eWFxMREPHz4UO1SZAwcyjBwOIYWLVrI1998801MmzZNxWqIiIhsEzsgKrKWM6JzipVy7HY4jgULFuDgwYPy9s8//6xeMUREpC6dUH4hBhA1ZQ0ganRBGDqU4doOx3Lnzh3Uq1cP4eHh8r6HDx/CxcVFxaqIiEhVXANiFAYQFWU9W7KlTkjIbodyDB3278mTJ5gzZw58fX0hSRIkSULx4sVx/Phx+T5nzpxBgQIFVKySiIjUJkHhGhC1C7cSXANiJSZOnIgJEyaY7fkZOJRh4HAMWq0W3bp1w+bNm194v0ePHiEwMNBCVREREdkndkBU1rlzZ/l6bGysSZ+b3Q7l2O2wf8+fP8f+/fvRvXt3ODs7Zwsfnp6e6NWrF37++WekpKRACMHwQUREGTLPhK7kQrYRQA4ePChPh/jv5a+//lK7PKNMnjxZvr5q1SqTPCdDhzJc2+E4bt68iaJFi6JJkyb4/vvv9W67evUqhBBITEzEt99+i9atW8PV1VWlSomIyBpZ+jC8S5cuRWhoKNzd3VG7dm38+eefud53xYoVaNCgAfz8/ODn54emTZu+8P5qsIkAUq9ePTx48EDvMmDAAJQoUQI1a9ZUuzyjZD2bcnh4OITCZMxuh3IMHY4lNTUVJUuWxJMnT/T2HzlyBEIIlC5dWqXKiIjIZlhwEfqmTZsQHh6OKVOmICIiAlWqVEHz5s0RHR2d4/0PHjyIbt264cCBAzh+/DhCQkLw5ptv4t69e4a/uJnYRABxdXVFwYIF5UtAQAB27NiBfv36QZJsezmPJEl488035e1jx47l+bEMHcqx2+G43Nzc9LY3bNgArVaL119/XaWKiIiIcjd//nwMHDgQ/fr1Q4UKFbBs2TJ4enrmOnNm/fr1GDp0KKpWrYpy5crhm2++gU6nw759+yxcee5sIoD8186dO/H48WP069fvhfdLSUlBXFyc3sUatW/fXr7+1VdfvfT+DB3KMXQ4tjFjxsjXq1evjuTkZHTr1g0ajU3+KSQiIpVIQii+AMj2+TQlJSXH10lNTcXp06fRtGlTeZ9Go0HTpk31jtD4IklJSUhLS4O/v7/xP7iJ2ORRsFauXInmzZujaNGiL7zfrFmzMHXqVAtVpVxYWJh8fcOGDVi4cCGCgoL07nOjW5YjZHWzUGF2qNGbn6ldAqnk0qVLmDdvnrx9+vRpFashIiKbpvv/i5LHAQgJCdHbPWXKFHzyySfZ7h4TEwOtVovg4GC9/cHBwbh8+XKeXnLs2LEoXLiwXohRm6pf+40bNy7XxeWZl/8O7t27d7F37948nUV8/PjxiI2NlS+RkZHm+lGMUq5cORQsWFDeXr16tYrV2LfnQc54HmSTuZuMoNPpUKFCBXk7JiZGxWqIiMjWGdsBiYyM1PuMOn78eLPUOXv2bGzcuBHbtm2Du7u7WV5DCVU/iY0ePRp9+/Z94X1Kliypt7169WoEBASgbdu2L31+Nze3bPO9rZEkSQgLC8PGjRsBAMuXL8eYMWM4LcSMsoYQj0fpKlZCllC1alX5+po1axAQEKBeMURE5PB8fHzg4+Pz0vsFBgbCyckJDx8+1Nv/8OFDvS+vczJ37lzMnj0bv//+u97Jr62BqgEkKCgo21SjFxFCYPXq1ejduzdcXFzMWJnlNWrUSA4gN27cwG+//YbmzZurXJVjyAwjDCL2aeHChTh//jwAoGjRoujTp4/KFRERkc1TeEQrQx/j6uqKGjVqYN++ffKa4cwF5cOGDcv1cZ9//jk+/fRT7N271yqPGGtTX7Hv378fN2/exIABA9QuxeSyrgMBgGXLlqlTiAPLnJ7FKVr24+TJkxg1apS8fevWLfWKISIi+2HBExGGh4djxYoVWLt2LS5duoQhQ4YgMTFRPhhT79699aZwffbZZ5g0aRJWrVqF0NBQREVFISoqCgkJCSb78Y1lU5+0Vq5ciXr16qFcuXJql2JypUuXRuHChXH//n0AwE8//YS7d+++dKE9mQe7Irbv7t27qFOnjrx98+ZNODk5qVgRERHZC6UnFVTymK5du+LRo0eYPHkyoqKiULVqVezZs0demH7nzh29aftfffUVUlNT0alTJ73nyW2huxpsKoBs2LBB7RLMRpIktGvXTj4Mr1arxTfffGM1vyiOimtFbFNcXJzeEUa+++47hIaGqlcQERGREYYNG5brlKuDBw/qbdtCt9+mpmDZuzlz5uhNxZo6dSrS0/mh11pwepZtSEtL01tkPmTIEPTo0UPFioiIyO5YcAqWPWIAsSJeXl7YtWsXGjRoIO97//33VayIcsK1ItZLCIHmzZvLwb18+fJYunSpylUREZG9kXTKL8QAYnU8PT2xd+9eefvrr78227GhyXgMItZlwoQJOHDggLwdEREBSZJUrIiIiOwSOyBGYQCxQh4eHnj27Jm8PXv2bIwZM0a9guil2BVR34kTJzB79mx5+8GDB1Z10iUiIiLKwABipXx9fREXFydvz5s3D8OHD1exIsorBhHL02q1qFu3rrx9+vTpl56giYiISDFhxIVs6yhYjsbb2xvx8fHw9vYGACxevBipqak8R4iN4BG0LCdr+Fi8eDGqV6+uYjVERGTvJCEgKZhOpeQx9ogBxMrly5cPiYmJ8PLyAgAsX74cqampWLVqlcqVkSEYRsznzJkz+OuvvwAABQoUeOGZYYmIiExC6XoOBhAAnIJlEzw9PZGUlCRvr169Gh06dFCxIjIGp2iZVtZux927d1WshIiIHIYAoFNwYf4AwABiMzw8PJCcnCxvb9++HZIk4caNGypWRcbgwnXjTZw4Ub7+9ddfw8XFRcVqiIiIKC8YQGyIm5sbUlJS9PaVKlUKHTt2RGpqqt7+q1evok+fPmjWrBk++OADLF68GDExMZYslwzAIGK4uLg4zJw5U94eOHCgitUQEZEjyVwDouRCXANic1xdXSGEwLx58+RD827btg1ubm65Pub3338HAAwfPhze3t749ttv0a5dO54fwQpxrUjeBQcHy9dv376tYiVERORwBBSuATF5JTaJHRAbNXr0aDx+/Njgx8XHx6NDhw7QaDSoW7cunj59aobqyBTYFcndvn375CmJb731FooVK6ZyRURE5FB4IkKjMIDYMH9/fwghkJCQgBkzZsj7Q0NDsW/fPgghIITAs2fPsHXr1myHJj1x4gT8/f1RqFAhnDhxAoL/KKwS14roE0KgadOm8vbOnTtVrIaIiIgMxQBiB7y8vDBx4kQ5cNy8eRONGzeWb/f19UWHDh1w+vRpCCFw584dFC5cWL49KioKdevWhUajwZdffonY2Fg1fgzKAwYRoHfv3vL1HTt2cCohERFZnpIjYGVeiAHEEYWEhODevXuIiYlBvXr19G57//33kT9/fnh5eeHzzz9HQkKCSlXSizhqVyQqKgrfffedvN22bVsVqyEiIkfFRejGYQBxYAEBATh27Bju3LmT7bwiSUlJGDt2LLy9vSFJEl577TXcuXMnT8+beYjgzEvbtm1x/vx5c/wIBMfqihQqVEi+rmQNFBERkUlwDYhRGEAIISEh2Lp1K/73v/9h0qRJKFGiRLb7nDp1CsWLF4enpyfu37+f7XatVosRI0ZAkqRsYeann35C5cqV0bNnT7P9DGT/XZEff/xRvv7+++/D399fxWqIiIhIKQYQklWoUAHTpk3DjRs3IIRAeno6Vq1ahXz58sn3ef78OYoUKQJJkjBo0CDs27cPFStWhLOzMxYtWqT3fCVLltTbXr9+PRYvXmyRn8XR2VsQ0el06Ny5s7y9ZMkSFashIiKHxw6IURhAKFdOTk7o168f4uPjkZycjLfeekvv9hUrVqBp06a4ePGi3v7ffvsNQghcv35dPkpXpuHDh+P48eMWqZ/spyuSNXzs27dPxUqIiIjAAGIkBhDKEzc3N/z0009ITk5G3759s91etmxZ3L9/P9shUoGMo3RlXT9Sr149REdHm7tk+g9bDSKnT5/G1q1b5e2sR3gjIiJSBY+CZRQGEDKIm5sbVq9eDSEEEhMTcfHiRWi1Wly+fFlvgfB/hYSE4MCBA/J2cHAwkpKSLFEy/YctdUWePXuGmjVryttPnjxRsRoiIiIyBQYQUszT0xPly5eHRpO3X6OwsDB8/vnn8raXlxc7ISqz5jAihECVKlXk7ZkzZ8LPz0/FioiIiDLwMLzGYQAhi/rwww8xYMAAeTs4ODjbGhJShzUFkZUrV0Kj0ehN3fvwww9VrIiIiCgLrgExCgMIWdyKFSvQvXt3ebtixYrYs2ePihVRVmp1RR4/fozGjRtDkiS9kAoAkZGRcHa2jnBEREQEnVB+IQYQUsd3332Hli1bytstW7bE22+/rWJFlBNLBJGNGzdCkiQEBgbqrRMCgFWrVkEIgaJFi5q1BiIiIrIcfqVIqpAkCTt27MCMGTMwbdo0AMDWrVshSRIOHDiAsLAws7zuifWjzfK8ZJgHDx6gU6dO+OOPP7Ldli9fPhw+fBjVqlVToTIiIqI8UDqdilOwALADQipycXHB1KlTsy1Eb9SoESRJwpYtW6DT8Xh1tioyMhITJ05E79690ahRI3h4eECSJEiShMKFC2cLH6NHj0ZaWhri4+MZPoiIyMopXf/BAAKwA0JWICgoCEIILFq0CCNGjJD3d+rUKcf7Dxs2DPPmzYOrq6ulSiQDJCYmokqVKrh+/fpL7xsQEID9+/ejcuXKFqiMiIjIRNgBMQo7IGQ1hg8fDp1Oh9mzZ7/wfkuWLIGbmxumT59uocoor6ZMmYJ8+fK9MHw0bNgQO3bsgE6nQ0xMDMMHERGRg5GEcJwoFhcXB19fX8TGxsLHx0ftcuglHj58iH379mHXrl24ceMGzp49i+Tk5Gz3S0pKgoeHhwoVUqYzZ86gevXqevuKFSuGGTNmoHTp0ihdujT8/f0hSZJKFRIRka2w5s9rmbU1LT4Mzho3gx+frkvB77eXWOXPZkmcgkVWKzg4GN27d9c7ZC8A3L59G6GhofK2p6cnLl68iPLly1u4QkpJSUHFihWzdTxu3LiBEiVKqFQVERGRmQldxkXJ44hTsMj2FC9eHEIIdOnSRd5XoUIF7NixQ8WqHM+CBQvg7u6uFz6WL18OIQTDBxER2TeeiNAoDCBkszZt2oTNmzfL2+3bt8e8efNUrMgxnD9/HpIkITw8XN5XrVo1pKamYtCgQSpWRkRERLaAU7DIpnXq1AkXLlzAq6++CgAYM2YMkpOTMXHiRJUrs30PHz7EggULcPz4caSkpMDZ2RnHjh3Ldr///e9/qFChggoVEhERqUSn8JC6PBM6ABvqgFy9ehXt2rVDYGAgfHx88Prrr2c7azI5pooVK+qdS+Tjjz/G119/rWJFtuv+/fsICwuDJEkoWLAgPvvsMxw+fBgnT57MFj7mzJkDIQTDBxEROR5OwTKKzQSQt956C+np6di/fz9Onz6NKlWq4K233kJUVJTapZEVCAoKwuPHj+Xt9957j2tCDLBu3TpIkoQiRYrg0KFDL7zvgAEDkJKSgjFjxlioOiIiIisjoDCAqF24dbCJABITE4N//vkH48aNQ+XKlVG6dGnMnj0bSUlJuHDhgtrlkZXw9/fH3bt35e327dvnOGWI/nXs2DFIkoTevXvr7Xdzc8PWrVuRlpYGIYTeZcWKFTwJJBERESlmEwEkICAAZcuWxbfffovExESkp6dj+fLlKFCgAGrUqJHr41JSUhAXF6d3IftWpEgRXLp0Sd5+/fXXcebMGRUrsl5jx47F66+/rrdvzpw50Gq1SE5ORocOHeDszGViRERE2XAKllFsIoBIkoTff/8dZ86cgbe3N9zd3TF//nzs2bMHfn5+uT5u1qxZ8PX1lS8hISEWrJrUUq5cOfzxxx/ydvXq1XHu3DkVK7Iuz58/R6dOnfD555/L++bOnQshBMaMGQONxib+LBAREalHp1N+IXUDyLhx4yBJ0gsvly9fhhAC77//PgoUKIAjR47gzz//RPv27dGmTRs8ePAg1+cfP348YmNj5UtkZKQFfzpSU926dfHrr7/K21WrVsXevXtVrEh9Qgjs3LkTxYsXx5YtW+T99+/fx+jRo1WsjIiIyMawA2IUSQj1RuLRo0d6C4dzUrJkSRw5cgRvvvkmnj59qnfa+tKlS6N///4YN25cnl4vLi4Ovr6+iI2N1Xsesl+7du3CW2+9JW+PGzcOs2bNUrEidVy7dg0jRozA7t279fZHR0cjKChIpaqIiIiys+bPa5m1NQ3qD2eN4esh03Wp+P3RSqv82SxJ1QneQUFBefrwk5SUBADZpoZoNBro2MqiF2jdujVOnz4trxWaPXs2Zs+ejcTERHh6eqpcnfmdP38e/fv3x19//ZXttiNHjjB8EBERKaG0m8EOCAAbWQNSt25d+Pn5oU+fPjh37hyuXr2KDz/8EDdv3kTr1q3VLo+sXPXq1bN12ry8vLBixQqo2AA0CyEExo4dK09hrFy5crbw4eTkhMWLF2dbgE5ERER5pBPKL2QbASQwMBB79uxBQkICGjdujJo1a+Lo0aPYsWMHqlSponZ5ZAP8/f0hhECrVq3kfYMGDYKHhweuXr2qYmWms3r1amg0Gr3F5ZlcXV3x2Wef4ddff0VUVBSGDRumQoVERET2QQid4gupPAXLEDVr1nT4RcRkvF27duHPP/9E7dq1AWQcqrls2bLo1KkTli5digIFCqhcYc5SUlJw6NAhHD16FB06dEC1atXk23Q6HQoUKJCtyzNjxgwMHDjQan8mIiIickw20QEhMqVatWohMTERDRo0kPf9+OOPCA4OhiRJWLp0qYrV/Ss+Ph7vvPMOJEmCu7s7mjdvjunTp6N69ery9LGoqCg4OTnphY/ff/8dQghMnDiR4YOIiMgchMLpV3Y29VspBhBySJ6enjh8+DDWrVuX7bZhw4ZhwIABqh3gYPv27ZAkCT4+Pti0aVOO9xk0aBA0Gg0KFSok76tatSp0Oh2aNGliqVKJiIgcEw/DaxQGEHJoPXv2hBACKSkpmDlzprx/5cqVGDBggEVr2bVrFyRJQocOHbLd9uWXX+Lzzz9H5cqVc3zs3LlzcebMGUiSZO4yiYiIiCciNAoDCBEyFmmPHz8eUVFR8r7Vq1fn2CExh9OnT+udrwQARowYgZSUFAghMGTIEHz44Yc4d+4cbt++jVWrVsl1X758mScSJCIiIpuh6okILc2aT2xD1uP06dOoWbOmvN2lSxd069YNycnJuHDhApo1a4aGDRua7PVu3ryJkiVLyttdu3bF2rVr4ebmZrLXICIishXW/Hkts7Ym+brDWVJwIkKRin0JG6zyZ7MkdkCI/qNGjRqYN2+evP3DDz+gQ4cO6NatGz799FOEhYVhxIgRJnmtw4cP64WP+fPnY+PGjQwfREREVkzodIovxABClKNRo0blugAcABYtWiSfW0QJrVaLadOm6XVSlixZglGjRil6PiIiIrIgLkI3is2cB4TIkiRJQpcuXVCrVi3Mnz8ftWvXRlhYGA4fPozu3bsDAJ4+fQqNRoO0tDQ4O+f9n9K9e/dQtGhRvX0TJkzA+++/b9KfgYiIiMxEJwBJQZhgAAHADgjRC4WGhmLRokXo0aMHihQpgm7dukEIgeLFi8v3cXFxQVxc3EufKz09Hb17984WPkaOHInp06ebvHYiIiIia8QAQqTArVu30K5dO3nb19cX0dHRud63atWqcHFx0TuqVtu2bXHv3j0sWLAAGg3/KRIREdkMIQChU3BhBwRgACFSbPv27Rg3bpy8HRwcjHXr1kGr1eL58+eYP38+JElCiRIlcO7cOb3H3r9/Hzt27EDhwoUtXTYREREZSeiE4gsxgBAZZdasWViwYIG83bt3bzg7O8PT0zPbuTmKFSuGf/75B0IIvTOYExERkY1R1P34/wsxgBAZa+TIkdi2bVuuty9evBg6nQ63b9/GK6+8YsHKiIiIyB4sXboUoaGhcHd3R+3atfHnn3++8P6bN29GuXLl4O7ujkqVKmH37t0WqjRvGECITKB9+/aIiIhAt27dULlyZXTq1An/+9//IITAsGHDIEmS2iUSERGRiVhyCtamTZsQHh6OKVOmICIiAlWqVEHz5s1zXXv6xx9/oFu3bujfvz/OnDmD9u3bo3379rhw4YKxP7bJONSZ0GNjY5E/f35ERkY69NkniYiIiKxVXFwcQkJC8OzZM/j6+qpdjp7MM6G/jlZwhovBj09HGo5id7bPom5ubrmehLh27dp47bXXsGTJEgCATqdDSEgIPvjgA721qJm6du2KxMRE/Pzzz/K+OnXqoGrVqli2bJnBNZuDQ50H5PHjxwCAkJAQlSshIiIioheJj4+3ugDi6uqKggUL4miU8ilN+fLly/ZZdMqUKfjkk0+y3Tc1NRWnT5/G+PHj5X0ajQZNmzbF8ePHc3z+48ePIzw8XG9f8+bNsX37dsU1m5pDBRB/f38AwJ07d6zuF9reZX6bwe6TOjj+6uHYq4djry6Ov3psfeyFEIiPj7fKI0W6u7vj5s2bSE1NVfwcQohsU7Nz637ExMRAq9UiODhYb39wcDAuX76c42OioqJyvH9UVJTimk3NoQJI5rkWfH19bfIfpD3w8fHh2KuI468ejr16OPbq4virx5bH3pq/KHZ3d4e7u7vaZdg0LkInIiIiIrJCgYGBcHJywsOHD/X2P3z4EAULFszxMQULFjTo/mpgACEiIiIiskKurq6oUaMG9u3bJ+/T6XTYt28f6tatm+Nj6tatq3d/APjtt99yvb8aHGoKlpubG6ZMmZLrPDsyH469ujj+6uHYq4djry6Ov3o49vYlPDwcffr0Qc2aNVGrVi0sXLgQiYmJ6NevH4CMkyAXKVIEs2bNAgCMGDECDRs2xLx589C6dWts3LgRp06dwtdff63mj6HHoQ7DS0RERERka5YsWYI5c+YgKioKVatWxaJFi1C7dm0AQFhYGEJDQ7FmzRr5/ps3b8bHH3+MW7duoXTp0vj888/RqlUrlarPjgGEiIiIiIgshmtAiIiIiIjIYhhAiIiIiIjIYhhAiIiIiIjIYhhAiIiIiIjIYhhAiIiIiIjIYhhADMADhqmHY09E5Dj4N19dHH8yNwaQPMj8hyhJksqVOB6OPRGR4+DffHVx/MlSHOpM6EokJCRg6tSpiIyMRIkSJdCsWTM0btxY7bIcAsdePQkJCVi8eDFu376NGjVqoHr16qhRo4baZTkMjr96OPbq4d98dXH8yZJ4IsIXSExMRJUqVVC6dGnky5cPcXFxOHjwIGbNmoXw8HC1y7NrHHv1JCQkoGrVqggJCYFWq8Xz589x//59zJkzB927d1e7PLvH8VcPx149/JuvLo4/WRo7IC+wbNky+Pn5Yfv27XBzc8Pjx4/x3XffYfTo0YiNjcXUqVPVLtFucezV8/nnn6NQoULYvXs3PDw8cPHiRaxZswY9e/ZEUlISBgwYoHaJdo3jrx6OvXr4N19dHH+yNAaQF4iOjoaPjw/c3NwAAAEBARgxYgR8fHzQv39/FClSBIMGDVK5SvvEsVfP3bt3UahQIXh4eAAAKlSogIkTJ8LT0xODBw+Gv78/OnbsqHKV9ovjrx6OvXr4N19dHH+yOEG5+vbbb4W3t7e4cOFCttumTp0qChUqJC5evKhCZfaPY6+euXPnilKlSonbt2/r7X/06JEYPHiwqFWrlrh7965K1dk/jr96OPbq4d98dXH8ydJ4FKwsnj9/jmPHjsnbdevWRZ06dfDZZ5/hxo0bAP49QsTbb78NFxcXeT+ZFsdePTVq1ICfnx+++eYbPHr0SN4fGBiITp064datW3jw4IGKFdo3jr/l6HQ6vf/WqlWLY28hfL+1Lhx/sjQGkP8XFxeHhg0bYtWqVbh+/ToA4JVXXkHnzp1x8eJFzJ07F1evXpUPTffKK68gf/78iI+PV7Nsu5CQkIDw8HB069YN77//PlJTU/HKK6+gU6dOHHszS0pKwrfffotvv/0WP//8MwAgLCwM7dq1w3fffYfVq1fj/v378v2rVauG/Pnz49mzZypVbF+Sk5Px22+/YceOHTh58iSAjPFv1aoV1q9fz/E3o/j4eLz++uv45ZdfoNFkvBU2aNAAbdq04dibGd9v1cX3XLIK6jZgrENiYqKoUKGCaN++vYiNjRU6nU7v9oULF4patWqJli1biqNHj4rIyEjx9ddfCz8/PxEREaFS1fYhLi5OlC1bVjRp0kQMGjRIBAYGil69esm3z507V9SuXZtjbwZxcXGidOnSonr16iIkJET4+/uLNm3aiAcPHgghhBg3bpwoU6aMGDp0qDh//ryIi4sTy5cvF0FBQWzFm0BsbKyoXr26qF27tvDx8RE1atQQixYtkm8fM2aMKFu2LMffTObMmSMkSRJeXl7ip59+0rtt9OjR/N03E77fqovvuWQtGECEEN9//71o2rSp/Ifw22+/FXPnzhXTpk0Tjx8/FkIIsX37dtGxY0chSZIoX768KFiwoNi4caOaZdu89PR00aFDB/H222/L+1atWiW6dOmi96a0bds20aFDB469CWm1WvHOO++IVq1aidTUVHHv3j1x9OhRERoaKqpVqyauXr0qhBBi/vz5olGjRsLJyUlUr15d+Pn5cexNIDExUVSvXl107txZREdHizNnzoiRI0eKtm3biidPnsj3mz9/vmjcuDHH3wy2bdsmunbtKiZNmiScnZ3Fzp079W7/6quv+LtvBny/VQ/fc8ma8ChYAG7fvg0hBCRJQrdu3XD+/HkEBQXh77//xo8//ogFCxagXbt2aNWqFc6fPw9JkuDl5YUyZcrwrKFGSE5ORkxMjN6RNR4+fIgrV66gdevW8PDwwKhRo9C+fXu0adMG586d49ibiEajQWxsLF5//XW4uLigcOHCKFy4ME6dOoW6deuiZ8+eOHjwIEaNGoWuXbvi4sWLAIDg4GBUqlRJ/vdCyixbtgz58+fHl19+icDAQAQFBSEmJgatW7fGw4cP4efnBwAYNWoUevTogb///hsAx9+UQkNDcePGDcyZMwdRUVF4++23cezYMVy8eBFOTk4YPHgwOnTogPPnzwPg2JsK32/Vw/dcsiYMIADc3Nyg0Whw4cIF3LlzBz///DOKFi0KAGjcuDE+/PBDnDhxAi4uLqhevbreY/kPUTmNRoPbt2/jt99+Q8OGDXHw4EF8/PHHGDRoECpWrIhvv/0WQ4YMwZ49e1CkSBGOvQkJIRATE4MrV67I+9LS0hAQEIBDhw6hRo0aGDZsGFauXCmHEzINrVYLPz8/NG3aFPnz55f3v/baayhcuDCSk5Pl+zk5OaFAgQJo2rSpStXaL39/f+h0OuTLlw8LFy6Ev78/6tatC51OJ6/H4dibHt9v1cP3XLIqarVerMnNmzeFp6enqFevnmjRooVISkoSWq1WCJExX9LDw0P8+OOPKldpn3755Rfh5eUlwsLChK+vr5g+fbre7Z6enmL+/PkqVWffNm3aJAoUKCBWr14t70tJSRFCZEyLKFOmjLh+/Xq2OdpkvFu3bonnz58LIYQ8vunp6aJMmTLi5MmT8v3+97//qVKfPUtPT5evN23aVB7v8ePHC1dXV+Hk5CT27t0rhBD83TcDvt+qi++5ZC0c7ihYKSkpuHr1Ks6ePYv09HQAGa34SZMm4Z9//sHjx4/h6uoKjUYDnU6H5ORklC9fHkFBQSpXbvuyjn1aWhoAoEWLFoiMjMSmTZtQuXJl+dvG58+fIy4uDlWqVEFwcLCaZduF5ORknD59GocOHZK/YW/cuDHatGmDr776Cps2bQIAuLq6AgCCgoKQkJAAZ2dnfutlApnjf/DgQSQnJ6N48eJwd3eHTqeDJEkQQiA2NhZPnz6V/2189913qFq1Ki5duiRPfSDD/fd338nJSe/2u3fvYsmSJVi4cCFWr16N4cOHo0WLFvj555/5u2+knP7u8P3WcnIaf77nkrVwqClYcXFxaNGiBZKSkhAfHw9nZ2fMmzcPTZo0wbvvvovo6GgsXLgQQ4cOxezZs6HRaLBv3z7ExMTIc7JJmdzGvk6dOggMDERycjKioqJw4sQJ1KlTBx4eHtixYwdu3bqFMmXKqF2+Tcs85GViYiKePHkCDw8PTJ8+HZ07d8ZHH32Ejz/+GJ9//jliYmLw/vvvQ6vV4t69e/D19eUHMBP47/h7enpi2rRpaN68OQoVKgQgY0qcs7MznJyc4Ofnhy1btqBPnz5Yt24dypcvr/JPYLtyG/umTZuiaNGiaNmyJUaMGIFnz55h48aNaNu2LVq1apVjUCHD5Db27dq1w8CBA/l+a2Yv+93ney6pTuUOjMU8f/5c1KxZU/Ts2VNcuHBBXLt2TXTq1El4e3uLGTNmiGfPnonHjx+LhQsXCm9vb1G8eHFRpUoVERAQIDZt2qR2+TYtt7H39fUVM2bMEJGRkUIIIT755BNRoEAB0aRJE9GjRw/h5+cnfvjhB5Wrt22pqamiSZMmonPnzuLKlSvi1q1b4r333hMlS5YUY8aMEU+fPhXXrl0T4eHhwtPTU1SqVEmEhYUJLy8v/t6bQG7jX6pUKTFmzBhx69Yt+b5arVbUqVNHDBgwQGg0GvHdd98JITKmAXEqkOFeNvYPHz4Ux44dE9WqVRO7d+/We2xaWpoQglOwlHrZ353o6Gjx7Nkzvt+ayct+969duyaEyHjPDQoK4nsuqcJhAsjRo0dFrVq15A+7Qgjx119/CS8vLxEaGioWLFgg74+MjBQrVqwQmzdvFqdOnRJC8I3IGC8a+5IlS8pjf+vWLfHtt9+KFi1aiPDwcPH7778LITj2xoiOjhbly5cX27Zt09s/e/ZsUaFCBTFhwgSRnJwskpKSxJkzZ8SECRPEokWLxOHDh4UQHHtjvWj8X331VTFx4kT50KPR0dHCw8NDSJIkNm/eLIRg+DDGi8a+YsWKYsKECUIIoXfYYzKNvIx9fHy8EILvt+aQl787SUlJ4v79+3zPJdU4zBSsu3fv4tKlS3pzS319fdGmTRsIITB58mR07twZRYoUQdGiRTFgwAC9x3MqinJ5HfvixYujV69e6NGjByRJkufGk3JpaWnQ6XRISEgAkDEn2N3dHWPHjkVaWhq+/PJLhIWFoVmzZqhatSqqVq2qbsF25mXjv2zZMjRs2BDNmjWDu7s7Bg0ahNatW6NZs2Y85KWRDPnd1+l08tnQyXgvG/uvvvpKHnu+35peXsY/8+8O33NJLZJwkN+2qKgohIWFoWHDhpg1axaSk5PRuHFjNGjQACtWrEC1atXQtm1bTJ06Ve1S7U5exr5NmzaYNm0aj7FvBm+//TYuXbqE//3vf5AkCSkpKXBzcwMAdOjQAdHR0Th27JjKVdovQ8Y/ISEB+fLlY/gwEf7uq4djr66Xjf/Dhw/xxx9/qFwlOTKH+crHz88P4eHhOHToEF555RVUq1YNZcqUwYoVKwAAAQEBePTokcpV2qe8jH1MTAwAfuAyJZ1OBwBYuHAh0tLS0KxZMwAZx+HPPNJSs2bNkJycjNTUVNXqtFeGjH9KSgoAIF++fAAgfxtJyvB3Xz0ce3XldfxTUlI4/qQqhwkgbm5u6Nu3L/bv349Vq1bhu+++w86dOwFknPArMDAQpUqVAgC2IE2MY6+OzCklRYoUwaJFi3Dt2jU0atQI8fHxcHFxAQDExMTAy8sLqampHHsTM2T809LSOP4mxN999XDs1cXxJ1thl1OwMqfx5GU6T1paGtatW4fw8HDs2rUL9evXt1CV9oljb53S0tJw5MgRfPDBB4iPj0e9evXg7e2NtWvXYtOmTejQoYPaJdo1jr96OPbq4diri+NP1syuAohWq5XnOnp4eLz0/v/88w+WLFmC7777Dl9++SW6du1qgSrtE8defVqt9qXnLkhNTcW0adNw584duLi4oEuXLmjevDnX3pgAx189HHv1cOzVxfEnW2U3ASQ+Ph6DBg1CZGQkvLy80Lx5c4SHh7/0catXr0bJkiXRsGFDLvxUiGOvnsTERGzduhW9evUCgBcezee/bzZZu1UAx14Jjr96OPbq4diri+NP9sAu1oAkJSXhtddeQ3JyMpo3b44KFSpg4sSJ6NSpE27evKl338wFWpmLsfr164eGDRvKt/Mfo2E49upJTExE/fr10adPH3z66acAMub/Zo5zVjqdDpIk4fnz5/K+rG9AHHvDcfzVw7FXD8deXRx/shd2EUB++eUXaDQarFq1CpMmTcKCBQtw7NgxHDp0CEOGDMG9e/cAZPzD02g0OHHiBL766isA0PtHy3+MhuPYqyMtLQ0jR46Et7c3PvjgA6xfvx7Tpk0DkPObkUajwfHjxzFp0iQ5APK8B8px/NXDsVcPx15dHH+yJ3bxmxgXF4eUlBT4+fkByPhHWr16dRw/fhynT5/GhAkTAPz7IXffvn0YOXIkLl26xH+MRuLYq+P58+fQarXo168fPvzwQ7zzzjv4/vvv5fPY5PRmdPnyZcyfPx9//fWXGiXbFY6/ejj26uHYq4vjT3bFhGdVV825c+eEs7OzWLdunbwvNTVVCCHE/v37hYeHh9iyZYt8m1arFb169RJr1661eK32hmNveVqtVgghxOPHj0ViYqIQQoi7d++KKVOmiHLlyokpU6bI901PTxc6nU7e/uCDD8TUqVP19pFhOP7q4dirh2OvLo4/2RtntQOQKZQrVw5DhgzBggULEBQUhObNm8PFxQVCCLz22muoUKECrly5It9fo9GgefPmaNy4sYpV2weOveVldo78/f0BZBwFpUiRInjvvfcAAJs2bYIkSZgyZQoWLlyIx48fY8aMGdBoNOjYsSPKly/PKW9G4Pirh2OvHo69ujj+ZG9sLoAkJCRg8uTJSEhIgEajwejRo1G6dGkMHDgQt27dwsyZM6HVatGqVStIkoR8+fIhKCgI6enpAP49ZF2PHj1U/klsD8dePTmNfbFixeDm5iYf0aRQoULym9GPP/6Iw4cP48CBA1izZo385hUWFqbiT2G7OP7q4dirh2OvLo4/2TUVuy8GS0hIECVKlBBhYWGiR48eomLFiqJYsWJiwYIFIjk5Wfz555+iY8eOomTJkmLevHni4MGDYvHixcLDw0McOnRI7fJtGsdePTmNfWhoqJg/f76Ijo4WQvzbnhdCiPv374uwsDAhSZLYvn27EEKw9W4Ejr96OPbq4diri+NP9s6mAsj06dPFG2+8obfv/fffFxUqVBCffPKJSElJEdeuXRMzZswQfn5+okyZMqJcuXLihx9+UKli+8GxV09uY//qq6+KyZMni5iYGL3bli9fLiRJElu3bhVCZLwJ8Y1IOY6/ejj26uHYq4vjT/bOpg5DlJycDJ1Oh+TkZGi1WgDAkiVL0KZNG3z//ffYuHEjSpUqhYkTJ+L69es4fPgw9u/fj86dO0NkhC2VfwLbxbFXT25j37p1a/z444/4+eefAWQc6jgpKQm//fYbNm3ahA4dOvBkUybA8VcPx149HHt1cfzJ7qmRegyRNcHPmDFDlCpVSiQkJAghhEhOTpZv69mzpyhZsqRISkqyeI32imOvHkPGvlSpUnpjn3k7vwFTjuOvHo69ejj26uL4kyOx6gASHx8vxo0bJ06cOCGEEOL58+eiaNGiokOHDvJ9nj9/LoTImC/p7+8vvvvuO1VqtTcce/UYM/Z88zEex189HHv1cOzVxfEnR2O1U7CEEBg1ahQ+//xzrFy5EidPnoS7uzu+/vprHDp0SD6Skru7OwAgMTERhQoVkk+IR8px7NVj7NhLksS2uxE4/urh2KuHY68ujj85IqsNIJIkwdPTE6VLl8aFCxewZMkSnDlzBi1btsTSpUtx+PBhNGrUCBcuXMC1a9ewd+9ePHjwAAULFlS7dJvHsVcPx15dHH/1cOzVw7FXF8efHJEkhPWtDhZCQJIkfP/993j06BHKlSuHcePGoWLFivjiiy+wa9culCpVCsOGDUN0dDScnZ2RlpaGefPm4Z133lG7fJvGsVcPx15dHH/1cOzVw7FXF8efHJVVnogws5Xo4+OD5cuX4+DBg3j8+DEWL16Mpk2b4uzZs7h8+TIiIiJw4MABuLm5wc/PD+XLl+fRH4zEsVcPx15dHH/1cOzVw7FXF8efHJVVBhAg41uB4sWLIyUlBQDQrVs37Ny5E5s3b0ZYWBgSExMBAI0aNdJ7HP8hGo9jrx6Ovbo4/urh2KuHY68ujj85IqteA1KuXDm4uLjg2bNnmDFjBnbu3Inw8HAkJydj5syZOH36tNpl2iWOvXo49uri+KuHY68ejr26OP7kiKy2AwIA6enpcHZ2RqtWrfD3339j48aNaNOmDTZs2IA5c+bA2dmqy7dpHHv1cOzVxfFXD8dePRx7dXH8yeFY4li/xliyZIkIDQ0V27dv19t///59lSpyHBx79XDs1cXxVw/HXj0ce3Vx/MmRWOVRsLJKTEzEo0ePEBoaCuDfI0Zk/pfMh2OvHo69ujj+6uHYq4djry6OPzkSqw8gRERERERkP6x2EToREREREdkfBhAiIiIiIrIYBhAiIiIiIrIYBhAiIiIiIrIYBhAiIiIiIrIYBhAiIiIiIrIYBhAiIiIiIrIYBhAiIiIiIrIYBhAiIge1cuVKvPnmm0Y9R0xMDAoUKIC7d++aqCoiIrJ3DCBERAqEhYVh5MiR2favWbMG+fPnBwCEhoZCkqRcL3379gUAefvEiRN6z5WSkoKAgABIkoSDBw+atP7k5GRMmjQJU6ZMMep5AgMD0bt3b6Ofh4iIHAcDCBGRmfz111948OABHjx4gC1btgAArly5Iu/74osv5PuGhIRg9erVeo/ftm0b8uXLZ5bafvzxR/j4+KB+/fpGP1e/fv2wfv16PHnyxASVERGRvWMAISIyk6CgIBQsWBAFCxaEv78/AKBAgQLyPl9fX/m+ffr0wcaNG/H8+XN536pVq9CnT58XvsajR49QsGBBzJw5U973xx9/wNXVFfv27cv1cRs3bkSbNm309vXt2xft27fHzJkzERwcjPz582PatGlIT0/Hhx9+CH9/fxQtWjRbUKpYsSIKFy6Mbdu2vXxQiIjI4TGAEBFZgRo1aiA0NFTulNy5cweHDx9Gr169Xvi4oKAgrFq1Cp988glOnTqF+Ph49OrVC8OGDUOTJk1yfdzRo0dRs2bNbPv379+P+/fv4/Dhw5g/fz6mTJmCt956C35+fjh58iQGDx6M9957L9uaj1q1auHIkSMKfnIiInI0DCBERFbi3XffxapVqwBkrCVp1aoVgoKCXvq4Vq1aYeDAgejRowcGDx4MLy8vzJo1K9f7P3v2DLGxsShcuHC22/z9/bFo0SKULVsW7777LsqWLYukpCRMmDABpUuXxvjx4+Hq6oqjR4/qPa5w4cK4ffu2gT8xERE5IgYQIiIr0bNnTxw/fhw3btzAmjVr8O677+b5sXPnzkV6ejo2b96M9evXw83NLdf7Zk7zcnd3z3ZbxYoVodH8+9YQHByMSpUqydtOTk4ICAhAdHS03uM8PDyQlJSU53qJiMhxMYAQESng4+OD2NjYbPufPXumt7bDEAEBAXjrrbfQv39/JCcno2XLlnl+7PXr13H//n3odDrcunXrpa8jSRKePn2a7TYXFxe9bUmSctyn0+n09j158iRP3RoiIiIGECIiBcqWLYuIiIhs+yMiIlCmTBnFz/vuu+/i4MGD6N27N5ycnPL0mNTUVPTs2RNdu3bF9OnTMWDAgGwdiqxcXV1RoUIFXLx4UXGd/3XhwgVUq1bNZM9HRET2iwGEiEiBIUOG4OrVqxg+fDj+/vtvXLlyBfPnz8f333+P0aNHK37eFi1a4NGjR5g2bVqeHzNx4kTExsZi0aJFGDt2LMqUKfPS6VvNmzfPto5DqaSkJJw+fdrokxoSEZFjYAAhIlKgZMmSOHz4MC5fvoymTZuidu3a+OGHH7B582a0aNFC8fNKkoTAwEC4urrm6f4HDx7EwoULsW7dOvj4+ECj0WDdunU4cuQIvvrqq1wf179/f+zevTvHaWSG2rFjB4oVK4YGDRoY/VxERGT/JCGEULsIIiKyvM6dO6N69eoYP368Uc9Tp04dDB8+HN27dzdRZUREZM/YASEiclBz5swx+kzrMTEx6NixI7p162aiqoiIyN6xA0JERERERBbDDggREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVkMAwgREREREVnM/wEA2+5hObE3OgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1000x440 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Set the min and max error values\n",
     "max_plot_error = 1\n",
@@ -2228,7 +2191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "id": "1d10a637-2105-40de-8f22-e8b46b5c2d16",
    "metadata": {},
    "outputs": [],
@@ -2253,10 +2216,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "id": "e71c17c4-93f7-4ad2-8b66-bff1b7da0519",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.1466436957034881"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "MSE = np.sum(L2_Magnitude * error_filter) / np.size(L2_Magnitude[L2_Magnitude < 1000])\n",
     "MSE"
@@ -2264,10 +2238,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "id": "3921f31e-1f0e-45a6-9394-c7e42e1ebb2d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\ashly\\AppData\\Local\\Temp\\ipykernel_30240\\3877048929.py:20: UserWarning: Adding colorbar to a different Figure <Figure size 1000x440 with 3 Axes> than <Figure size 1000x440 with 1 Axes> which fig.colorbar is called on.\n",
+      "  cbar = plt.colorbar(contour_plot_L1)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(array([400960., 400980., 401000., 401020., 401040., 401060., 401080.,\n",
+       "        401100.]),\n",
+       " [Text(400960.0, 0, '400,960'),\n",
+       "  Text(400980.0, 0, '400,980'),\n",
+       "  Text(401000.0, 0, '401,000'),\n",
+       "  Text(401020.0, 0, '401,020'),\n",
+       "  Text(401040.0, 0, '401,040'),\n",
+       "  Text(401060.0, 0, '401,060'),\n",
+       "  Text(401080.0, 0, '401,080'),\n",
+       "  Text(401100.0, 0, '401,100')])"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x440 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Create a contour plot of the error\n",
     "# Plotting\n",
@@ -2312,10 +2324,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "id": "de8f93fc-8254-4181-817c-dae48b39456b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.8787287797274143"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# L inf\n",
     "L_inf = np.nanmax(L1_Magnitude * error_filter)\n",
@@ -2345,7 +2368,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python_310",
    "language": "python",
    "name": "python3"
   },
@@ -2359,7 +2382,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.10.15"
   }
  },
  "nbformat": 4,
diff --git a/examples/adcp_example.ipynb b/examples/adcp_example.ipynb
index d476e0d21..9bbcb220e 100644
--- a/examples/adcp_example.ipynb
+++ b/examples/adcp_example.ipynb
@@ -1,4186 +1,5541 @@
 {
-  "cells": [
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "# Analyzing ADCP Data with MHKiT\n",
-        "\n",
-        "The following example illustrates a straightforward workflow for analyzing Acoustic Doppler Current Profiler (ADCP) data utilizing MHKiT. MHKiT has integrated the DOLfYN codebase as a module to facilitate ADCP and Acoustic Doppler Velocimetry (ADV) data processing.\n",
-        "\n",
-        "Here is a standard workflow for ADCP data analysis:\n",
-        "\n",
-        "1. **Import Data**\n",
-        "\n",
-        "2. **Review, QC, and Prepare the Raw Data**:\n",
-        "   1. Calculate or verify the correctness of depth bin locations\n",
-        "   2. Discard data recorded above the water surface or below the seafloor\n",
-        "   3. Assess the quality of velocity, beam amplitude, and/or beam correlation data\n",
-        "   4. Rotate Data Coordinate System\n",
-        "\n",
-        "3. **Data Averaging**: \n",
-        "    - If not already executed within the instrument, average the data into time bins of a predetermined duration, typically between 5 and 10 minutes\n",
-        "\n",
-        "4. **Speed and Direction**\n",
-        "\n",
-        "5. **Plotting**\n",
-        "\n",
-        "6. **Saving and Loading DOLfYN datasets**\n",
-        "\n",
-        "7. **Turbulence Statistics**\n",
-        "    1. Turbulence Intensity (TI)\n",
-        "    2. Power Spectral Densities\n",
-        "    3. Instrument Noise\n",
-        "    4. TKE Dissipation Rate\n",
-        "    5. Noise-corrected TI\n",
-        "    6. Reynolds stresses\n",
-        "    7. TKE Production\n",
-        "    8. TKE Balance \n",
-        "\n",
-        "\n",
-        "Begin your analysis by importing the requisite tools:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 1,
-      "metadata": {
-        "scrolled": true
-      },
-      "outputs": [],
-      "source": [
-        "from mhkit import dolfyn\n",
-        "from mhkit.dolfyn.adp import api"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "##  1. Importing Raw Instrument Data\n",
-        "\n",
-        "One of DOLfYN's key features is its ability to directly import raw data from an Acoustic Doppler Current Profiler (ADCP) right after it has been transferred. In this instance, we are using a Nortek Signature1000 ADCP, with the data stored in files with an '.ad2cp' extension. This specific dataset represents several hours of velocity data, captured at 1 Hz by an ADCP mounted on a bottom lander within a tidal inlet. The list of instruments compatible with DOLfYN can be found in the [MHKiT DOLfYN documentation](https://mhkit-software.github.io/MHKiT/mhkit-python/api.dolfyn.html).\n",
-        "\n",
-        "We'll start by importing the raw data file downloaded from the instrument. The `read` function processes the raw file and converts the information into an xarray Dataset. This Dataset includes several groups of variables:\n",
-        "\n",
-        "1. **Velocity**: Recorded in the coordinate system saved by the instrument (beam, XYZ, ENU)\n",
-        "2. **Beam Data**: Includes amplitude and correlation data\n",
-        "3. **Instrumental & Environmental Measurements**: Captures the instrument's bearing and environmental conditions\n",
-        "4. **Orientation Matrices**: Used by DOLfYN for rotating through different coordinate frames.\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {
-        "scrolled": true
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Indexing data/dolfyn/Sig1000_tidal.ad2cp... Done.\n",
-            "Reading file data/dolfyn/Sig1000_tidal.ad2cp ...\n"
-          ]
-        }
-      ],
-      "source": [
-        "ds = dolfyn.read(\"data/dolfyn/Sig1000_tidal.ad2cp\")"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "There are two ways to see what's in a Dataset. The first is to simply type the dataset's name to see the standard xarray output. To access a particular variable in a dataset, use dict-style (`ds['vel']`) or attribute-style syntax (`ds.vel`). See the [xarray docs](http://xarray.pydata.org/en/stable/getting-started-guide/quick-overview.html) for more details on how to use the xarray format."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 3,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/html": [
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-              " *\n",
-              " */\n",
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-              "\n",
-              "html[theme=\"dark\"],\n",
-              "html[data-theme=\"dark\"],\n",
-              "body[data-theme=\"dark\"],\n",
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-              "  --xr-background-color-row-even: #111111;\n",
-              "  --xr-background-color-row-odd: #313131;\n",
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-              "\n",
-              ".xr-wrap {\n",
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-              "\n",
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-              "\n",
-              ".xr-header {\n",
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-              "  padding-bottom: 6px;\n",
-              "  margin-bottom: 4px;\n",
-              "  border-bottom: solid 1px var(--xr-border-color);\n",
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-              "\n",
-              ".xr-header > div,\n",
-              ".xr-header > ul {\n",
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-              "  margin-top: 0;\n",
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-              "\n",
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-              ".xr-array-name {\n",
-              "  margin-left: 2px;\n",
-              "  margin-right: 10px;\n",
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-              "\n",
-              ".xr-obj-type {\n",
-              "  color: var(--xr-font-color2);\n",
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-              "\n",
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-              "\n",
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-              ".xr-section-inline-details {\n",
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-              "\n",
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-              "  margin-bottom: 5px;\n",
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-              "\n",
-              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-              "  display: contents;\n",
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-              "\n",
-              ".xr-array-wrap > label {\n",
-              "  grid-column: 1;\n",
-              "  vertical-align: top;\n",
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-              "\n",
-              ".xr-preview {\n",
-              "  color: var(--xr-font-color3);\n",
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-              "\n",
-              ".xr-array-preview,\n",
-              ".xr-array-data {\n",
-              "  padding: 0 5px !important;\n",
-              "  grid-column: 2;\n",
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-              "\n",
-              ".xr-array-data,\n",
-              ".xr-array-in:checked ~ .xr-array-preview {\n",
-              "  display: none;\n",
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-              "\n",
-              ".xr-array-in:checked ~ .xr-array-data,\n",
-              ".xr-array-preview {\n",
-              "  display: inline-block;\n",
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-              "\n",
-              ".xr-dim-list {\n",
-              "  display: inline-block !important;\n",
-              "  list-style: none;\n",
-              "  padding: 0 !important;\n",
-              "  margin: 0;\n",
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-              "\n",
-              ".xr-dim-list li {\n",
-              "  display: inline-block;\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
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-              "\n",
-              ".xr-dim-list:before {\n",
-              "  content: \"(\";\n",
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-              "\n",
-              ".xr-dim-list:after {\n",
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-              "\n",
-              ".xr-dim-list li:not(:last-child):after {\n",
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-              "  padding-right: 5px;\n",
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-              "\n",
-              ".xr-has-index {\n",
-              "  font-weight: bold;\n",
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-              "\n",
-              ".xr-var-list,\n",
-              ".xr-var-item {\n",
-              "  display: contents;\n",
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-              "\n",
-              ".xr-var-item > div,\n",
-              ".xr-var-item label,\n",
-              ".xr-var-item > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-even);\n",
-              "  margin-bottom: 0;\n",
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-              "\n",
-              ".xr-var-item > .xr-var-name:hover span {\n",
-              "  padding-right: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-var-list > li:nth-child(odd) > div,\n",
-              ".xr-var-list > li:nth-child(odd) > label,\n",
-              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-odd);\n",
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-              "\n",
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-              "\n",
-              ".xr-var-preview {\n",
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-              "\n",
-              ".xr-index-preview {\n",
-              "  grid-column: 2 / 5;\n",
-              "  color: var(--xr-font-color2);\n",
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-              "\n",
-              ".xr-var-name,\n",
-              ".xr-var-dims,\n",
-              ".xr-var-dtype,\n",
-              ".xr-preview,\n",
-              ".xr-attrs dt {\n",
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-              "  overflow: hidden;\n",
-              "  text-overflow: ellipsis;\n",
-              "  padding-right: 10px;\n",
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-              "\n",
-              ".xr-var-name:hover,\n",
-              ".xr-var-dims:hover,\n",
-              ".xr-var-dtype:hover,\n",
-              ".xr-attrs dt:hover {\n",
-              "  overflow: visible;\n",
-              "  width: auto;\n",
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-              "\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  display: none;\n",
-              "  background-color: var(--xr-background-color) !important;\n",
-              "  padding-bottom: 5px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-              ".xr-var-data-in:checked ~ .xr-var-data,\n",
-              ".xr-index-data-in:checked ~ .xr-index-data {\n",
-              "  display: block;\n",
-              "}\n",
-              "\n",
-              ".xr-var-data > table {\n",
-              "  float: right;\n",
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-              "\n",
-              ".xr-var-name span,\n",
-              ".xr-var-data,\n",
-              ".xr-index-name div,\n",
-              ".xr-index-data,\n",
-              ".xr-attrs {\n",
-              "  padding-left: 25px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs,\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  grid-column: 1 / -1;\n",
-              "}\n",
-              "\n",
-              "dl.xr-attrs {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  display: grid;\n",
-              "  grid-template-columns: 125px auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt,\n",
-              ".xr-attrs dd {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  float: left;\n",
-              "  padding-right: 10px;\n",
-              "  width: auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt {\n",
-              "  font-weight: normal;\n",
-              "  grid-column: 1;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt:hover span {\n",
-              "  display: inline-block;\n",
-              "  background: var(--xr-background-color);\n",
-              "  padding-right: 10px;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dd {\n",
-              "  grid-column: 2;\n",
-              "  white-space: pre-wrap;\n",
-              "  word-break: break-all;\n",
-              "}\n",
-              "\n",
-              ".xr-icon-database,\n",
-              ".xr-icon-file-text2,\n",
-              ".xr-no-icon {\n",
-              "  display: inline-block;\n",
-              "  vertical-align: middle;\n",
-              "  width: 1em;\n",
-              "  height: 1.5em !important;\n",
-              "  stroke-width: 0;\n",
-              "  stroke: currentColor;\n",
-              "  fill: currentColor;\n",
-              "}\n",
-              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 83MB\n",
-              "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-              "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-              "                          x1: 4, x2: 4)\n",
-              "Coordinates:\n",
-              "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-              "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-              "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-              "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
-              "  * beam                 (beam) int32 16B 1 2 3 4\n",
-              "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
-              "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-              "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-              "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-              "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-              "  * x1                   (x1) int32 16B 1 2 3 4\n",
-              "  * x2                   (x2) int32 16B 1 2 3 4\n",
-              "Data variables: (12/38)\n",
-              "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-              "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-              "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-              "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-              "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-              "    ...                   ...\n",
-              "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
-              "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
-              "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-              "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-              "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-              "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-              "Attributes: (12/34)\n",
-              "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
-              "    inst_model:            Signature1000\n",
-              "    inst_make:             Nortek\n",
-              "    inst_type:             ADCP\n",
-              "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
-              "    n_cells:               28\n",
-              "    ...                    ...\n",
-              "    proc_idle_less_12pct:  0\n",
-              "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
-              "    coord_sys:             earth\n",
-              "    fs:                    1\n",
-              "    has_imu:               1\n",
-              "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2bb93856-6493-4446-9b87-27cea014a081' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2bb93856-6493-4446-9b87-27cea014a081' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-44ab80c1-468d-4c4c-bfd8-da385ad2911b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44ab80c1-468d-4c4c-bfd8-da385ad2911b' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-b1f3c94e-ecd6-47a7-9b10-f64197ef1000' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1f3c94e-ecd6-47a7-9b10-f64197ef1000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0639fea1-589f-4696-98e4-db209d804809' class='xr-var-data-in' type='checkbox'><label for='data-0639fea1-589f-4696-98e4-db209d804809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
-              "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
-              "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-df1333fa-8090-4b73-90a1-370ef194f0d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df1333fa-8090-4b73-90a1-370ef194f0d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bc8ccde-7a5f-478c-a30e-602041272b6a' class='xr-var-data-in' type='checkbox'><label for='data-5bc8ccde-7a5f-478c-a30e-602041272b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
-              "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
-              "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-f266a94c-6400-4611-b6cc-540c71e6f4f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f266a94c-6400-4611-b6cc-540c71e6f4f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3d7efda-a3b4-4fdf-a0ac-47fa75f7d90b' class='xr-var-data-in' type='checkbox'><label for='data-f3d7efda-a3b4-4fdf-a0ac-47fa75f7d90b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-390d0180-57eb-4119-b0c0-5b41d0402e28' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390d0180-57eb-4119-b0c0-5b41d0402e28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f61bff6-c013-498b-970d-d4673831eee5' class='xr-var-data-in' type='checkbox'><label for='data-5f61bff6-c013-498b-970d-d4673831eee5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-7f44c1f4-69b3-4068-9911-0419633c6f89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f44c1f4-69b3-4068-9911-0419633c6f89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f6dd975-0fde-4e31-9eb0-bf06af4dc611' class='xr-var-data-in' type='checkbox'><label for='data-8f6dd975-0fde-4e31-9eb0-bf06af4dc611' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-94007066-9746-4038-8627-4e4cbdeebe51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94007066-9746-4038-8627-4e4cbdeebe51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a776caf-27ad-490d-9198-a303fe3db364' class='xr-var-data-in' type='checkbox'><label for='data-6a776caf-27ad-490d-9198-a303fe3db364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-e523f6b1-bdc3-4fbe-87ee-36a3c64207a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e523f6b1-bdc3-4fbe-87ee-36a3c64207a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d72a7f1b-9e73-4cda-884f-9df8be1c801b' class='xr-var-data-in' type='checkbox'><label for='data-d72a7f1b-9e73-4cda-884f-9df8be1c801b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-40c67b12-a0b6-47ed-afdc-dbec63068d92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40c67b12-a0b6-47ed-afdc-dbec63068d92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-007855ee-909e-4285-9c39-c36252088294' class='xr-var-data-in' type='checkbox'><label for='data-007855ee-909e-4285-9c39-c36252088294' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-a13fb84b-25d1-48ff-838d-4c490f163ac5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a13fb84b-25d1-48ff-838d-4c490f163ac5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8e30837-ea9d-4cdf-86a0-be81d160c31b' class='xr-var-data-in' type='checkbox'><label for='data-b8e30837-ea9d-4cdf-86a0-be81d160c31b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-b065e21f-114d-46c5-b868-fe13351035e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b065e21f-114d-46c5-b868-fe13351035e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33f36f6d-3af7-4fc4-b563-86f1121a7203' class='xr-var-data-in' type='checkbox'><label for='data-33f36f6d-3af7-4fc4-b563-86f1121a7203' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-977e242d-bfc2-4800-9149-e7762c892688' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-977e242d-bfc2-4800-9149-e7762c892688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a82d0ad-2e37-4d7c-adfe-d3b0cba5aa75' class='xr-var-data-in' type='checkbox'><label for='data-8a82d0ad-2e37-4d7c-adfe-d3b0cba5aa75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c996444d-d6fd-4594-9a5f-9717e2605adb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c996444d-d6fd-4594-9a5f-9717e2605adb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ae7b00f-61dc-4a25-aaea-da2285f28319' class='xr-var-data-in' type='checkbox'><label for='data-5ae7b00f-61dc-4a25-aaea-da2285f28319' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aba501e5-2078-4cac-811c-1a57021b8eed' class='xr-section-summary-in' type='checkbox'  ><label for='section-aba501e5-2078-4cac-811c-1a57021b8eed' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-cd161dc4-2187-41ac-9b00-be6b10bc8bbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd161dc4-2187-41ac-9b00-be6b10bc8bbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f2afe60-12d6-49fd-b1dd-14df2c4dab76' class='xr-var-data-in' type='checkbox'><label for='data-0f2afe60-12d6-49fd-b1dd-14df2c4dab76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-c884fa59-ec0b-4529-8400-537d38bd77c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c884fa59-ec0b-4529-8400-537d38bd77c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd474941-9a8d-4e30-b7d3-7f958b6dc3a2' class='xr-var-data-in' type='checkbox'><label for='data-dd474941-9a8d-4e30-b7d3-7f958b6dc3a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-227176fc-19c4-40d5-8f74-df756d306f3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-227176fc-19c4-40d5-8f74-df756d306f3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3398794a-de4e-4e9b-bd3d-dee74335344a' class='xr-var-data-in' type='checkbox'><label for='data-3398794a-de4e-4e9b-bd3d-dee74335344a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-c135a21c-5db2-487b-ad1f-1faff443d5db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c135a21c-5db2-487b-ad1f-1faff443d5db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c21e291-655d-4ff6-be10-951b9c9bc7a9' class='xr-var-data-in' type='checkbox'><label for='data-7c21e291-655d-4ff6-be10-951b9c9bc7a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
-              "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
-              "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-b957bb42-48dc-425f-b414-290a166595ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b957bb42-48dc-425f-b414-290a166595ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cf8d694-3813-4297-bae1-ed46db2b4ea8' class='xr-var-data-in' type='checkbox'><label for='data-5cf8d694-3813-4297-bae1-ed46db2b4ea8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
-              "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
-              "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
-              "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
-              "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
-              "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-63d7dc22-a222-4368-8d64-edd3a7fb6ce9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63d7dc22-a222-4368-8d64-edd3a7fb6ce9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fcd37e5-2bb0-44a4-87ab-07894fc1d27e' class='xr-var-data-in' type='checkbox'><label for='data-5fcd37e5-2bb0-44a4-87ab-07894fc1d27e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-7230bc27-e7dd-4a81-bc58-ec377dfba2f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7230bc27-e7dd-4a81-bc58-ec377dfba2f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-956e2170-d3fa-4b3f-91f8-b755c892f600' class='xr-var-data-in' type='checkbox'><label for='data-956e2170-d3fa-4b3f-91f8-b755c892f600' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-2b195a2d-ca32-41c9-bbc7-a257d1a55275' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b195a2d-ca32-41c9-bbc7-a257d1a55275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43653780-016c-44e0-bb3f-c525c0c403cd' class='xr-var-data-in' type='checkbox'><label for='data-43653780-016c-44e0-bb3f-c525c0c403cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-0309ea33-451b-4d67-9839-d11061c65111' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0309ea33-451b-4d67-9839-d11061c65111' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8613093-89dc-48c6-b2a9-ee53b27f95b1' class='xr-var-data-in' type='checkbox'><label for='data-c8613093-89dc-48c6-b2a9-ee53b27f95b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-608fbc04-d386-4fa1-8e43-de8db4cc6cb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-608fbc04-d386-4fa1-8e43-de8db4cc6cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d316239-ef9e-4482-83b0-e7264fc944a8' class='xr-var-data-in' type='checkbox'><label for='data-8d316239-ef9e-4482-83b0-e7264fc944a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-98644f44-ab34-4c0b-a749-8d40015b89b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98644f44-ab34-4c0b-a749-8d40015b89b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-199e8e9d-f69f-4bff-9f1d-881ed213794c' class='xr-var-data-in' type='checkbox'><label for='data-199e8e9d-f69f-4bff-9f1d-881ed213794c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
-              "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
-              "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
-              "        ...,\n",
-              "        [-0.169, -0.013, -0.124, ..., -0.062,  0.091, -0.009],\n",
-              "        [-0.16 , -0.043, -0.111, ...,  0.012,  0.089,  0.021],\n",
-              "        [-0.158, -0.057, -0.13 , ..., -0.055,  0.104,  0.013]],\n",
-              "\n",
-              "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
-              "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
-              "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
-              "        ...,\n",
-              "        [ 0.305,  0.377,  0.283, ..., -0.198, -0.229, -0.121],\n",
-              "        [ 0.328,  0.33 ,  0.294, ..., -0.161, -0.292, -0.103],\n",
-              "        [ 0.31 ,  0.314,  0.226, ..., -0.219, -0.292, -0.049]],\n",
-              "\n",
-              "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
-              "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
-              "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
-              "        ...,\n",
-              "        [ 0.034, -0.061, -0.024, ..., -0.014,  0.086,  0.01 ],\n",
-              "        [ 0.032, -0.04 , -0.027, ..., -0.014,  0.063, -0.01 ],\n",
-              "        [ 0.004, -0.037, -0.018, ..., -0.001,  0.059,  0.021]],\n",
-              "\n",
-              "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
-              "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
-              "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
-              "        ...,\n",
-              "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
-              "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
-              "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
-              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-c32c85ac-0276-4d5f-8f1d-cbd90cec0e3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c32c85ac-0276-4d5f-8f1d-cbd90cec0e3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9723746f-29e5-49fd-85c4-09b3642f16b6' class='xr-var-data-in' type='checkbox'><label for='data-9723746f-29e5-49fd-85c4-09b3642f16b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
-              "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
-              "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
-              "        ...,\n",
-              "        [54.5, 55.5, 54.5, ..., 50. , 50. , 49.5],\n",
-              "        [53.5, 54.5, 54.5, ..., 46.5, 47. , 46.5],\n",
-              "        [53. , 54. , 53. , ..., 45. , 46. , 44.5]],\n",
-              "\n",
-              "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
-              "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
-              "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
-              "        ...,\n",
-              "        [57. , 58.5, 58. , ..., 53.5, 52. , 52.5],\n",
-              "        [55.5, 56.5, 55.5, ..., 50. , 49. , 49. ],\n",
-              "        [52.5, 54. , 54. , ..., 47.5, 47.5, 47. ]],\n",
-              "\n",
-              "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
-              "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
-              "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
-              "        ...,\n",
-              "        [56.5, 56.5, 57. , ..., 47.5, 47. , 48. ],\n",
-              "        [56. , 55.5, 56.5, ..., 46.5, 47. , 47. ],\n",
-              "        [54.5, 54. , 55.5, ..., 45. , 45.5, 45.5]],\n",
-              "\n",
-              "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
-              "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
-              "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
-              "        ...,\n",
-              "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
-              "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
-              "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]],\n",
-              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-6cf257b5-82cd-4e7a-a64f-b3c347885ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cf257b5-82cd-4e7a-a64f-b3c347885ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81ea19f2-bf29-4aa6-a618-9941b95035be' class='xr-var-data-in' type='checkbox'><label for='data-81ea19f2-bf29-4aa6-a618-9941b95035be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
-              "        [ 74,  92,  96, ..., 100,  97, 100],\n",
-              "        [100, 100,  99, ...,  99, 100, 100],\n",
-              "        ...,\n",
-              "        [ 99, 100, 100, ...,  96,  96,  99],\n",
-              "        [ 99,  97, 100, ...,  94,  97,  96],\n",
-              "        [ 98, 100, 100, ..., 100, 100,  98]],\n",
-              "\n",
-              "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
-              "        [ 94, 100, 100, ...,  96, 100,  93],\n",
-              "        [ 99,  95,  97, ...,  98,  98, 100],\n",
-              "        ...,\n",
-              "        [100, 100, 100, ...,  98,  99, 100],\n",
-              "        [ 99, 100,  99, ...,  97,  94,  94],\n",
-              "        [ 96,  99,  96, ...,  97, 100,  97]],\n",
-              "\n",
-              "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
-              "        [ 99, 100,  99, ...,  96,  88,  98],\n",
-              "        [ 97, 100,  98, ..., 100,  99,  97],\n",
-              "        ...,\n",
-              "        [100, 100,  99, ...,  97,  94,  95],\n",
-              "        [100, 100, 100, ...,  96, 100, 100],\n",
-              "        [100, 100, 100, ...,  96,  95,  94]],\n",
-              "\n",
-              "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
-              "        [100,  93,  93, ...,  96,  96,  97],\n",
-              "        [100, 100, 100, ..., 100, 100,  97],\n",
-              "        ...,\n",
-              "        [100,  99,  96, ...,  98, 100, 100],\n",
-              "        [100, 100, 100, ...,  94,  93,  95],\n",
-              "        [100,  98,  99, ...,  98,  98,  96]]],\n",
-              "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-81e10eb9-2350-4e6c-8f48-13d67572014c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81e10eb9-2350-4e6c-8f48-13d67572014c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d233e24a-daa2-474f-ad1a-512b7641dc17' class='xr-var-data-in' type='checkbox'><label for='data-d233e24a-daa2-474f-ad1a-512b7641dc17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
-              "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-              "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
-              "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-              "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
-              "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
-              "\n",
-              "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
-              "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-              "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
-              "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-              "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
-              "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
-              "\n",
-              "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
-              "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
-              "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
-              "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
-              "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
-              "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-17f5fa72-a0bb-4b54-b694-f4903158ec8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17f5fa72-a0bb-4b54-b694-f4903158ec8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3859ed97-6d64-4f02-b4cf-bfed1a1a9664' class='xr-var-data-in' type='checkbox'><label for='data-3859ed97-6d64-4f02-b4cf-bfed1a1a9664' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
-              "        -0.00292969, -0.00195312],\n",
-              "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
-              "         0.00097656,  0.00097656],\n",
-              "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-              "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-fd7a2f23-54b3-48d5-bf91-aee8beac0a22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd7a2f23-54b3-48d5-bf91-aee8beac0a22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e6ffbf6-25c3-484d-b5e7-aef6638ab46e' class='xr-var-data-in' type='checkbox'><label for='data-2e6ffbf6-25c3-484d-b5e7-aef6638ab46e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
-              "         0.6247864 ,  0.62490845],\n",
-              "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-              "        -0.03564453, -0.03561401],\n",
-              "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
-              "        -0.04360962, -0.04360962],\n",
-              "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-4ca0ab12-bd84-4097-b895-e57e3fc5de6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ca0ab12-bd84-4097-b895-e57e3fc5de6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c2d82bb-5a17-4f7e-b60c-be48ad57a5e7' class='xr-var-data-in' type='checkbox'><label for='data-0c2d82bb-5a17-4f7e-b60c-be48ad57a5e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-baf3a83f-5067-483c-b593-c804797724f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baf3a83f-5067-483c-b593-c804797724f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c853c46c-dd38-401f-91d9-dd5a664ea07a' class='xr-var-data-in' type='checkbox'><label for='data-c853c46c-dd38-401f-91d9-dd5a664ea07a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-a3d36048-7a04-447f-bca2-3dc7664d54d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3d36048-7a04-447f-bca2-3dc7664d54d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c06619e-5cea-454c-a150-7d12c1a7adc2' class='xr-var-data-in' type='checkbox'><label for='data-5c06619e-5cea-454c-a150-7d12c1a7adc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
-              "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
-              "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-37b68fe2-0af0-480d-9d75-c671620f8b77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37b68fe2-0af0-480d-9d75-c671620f8b77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02b2768b-9263-4783-ba00-4ba49ef9dae1' class='xr-var-data-in' type='checkbox'><label for='data-02b2768b-9263-4783-ba00-4ba49ef9dae1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
-              "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
-              "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
-              "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
-              "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
-              "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-e627ec10-d8cd-429d-b603-1d9a35e02e36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e627ec10-d8cd-429d-b603-1d9a35e02e36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afdfad8b-d9e3-41af-9619-c2178b544fdb' class='xr-var-data-in' type='checkbox'><label for='data-afdfad8b-d9e3-41af-9619-c2178b544fdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-437c65d8-caa7-4bc7-85ac-2e54a22e1402' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-437c65d8-caa7-4bc7-85ac-2e54a22e1402' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c857bb51-3bb7-4320-8d3a-493531d3d019' class='xr-var-data-in' type='checkbox'><label for='data-c857bb51-3bb7-4320-8d3a-493531d3d019' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-5c3f5314-b091-4990-8617-32819e546950' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c3f5314-b091-4990-8617-32819e546950' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0253f787-a52b-4f5c-b911-d1e23b9a3c36' class='xr-var-data-in' type='checkbox'><label for='data-0253f787-a52b-4f5c-b911-d1e23b9a3c36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-8ba34c98-f026-466e-9c04-ca734c6dfd9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ba34c98-f026-466e-9c04-ca734c6dfd9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-505f74df-75de-4ab9-9b6f-e2c4b1c4a275' class='xr-var-data-in' type='checkbox'><label for='data-505f74df-75de-4ab9-9b6f-e2c4b1c4a275' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
-              "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
-              "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
-              "       ...,\n",
-              "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
-              "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
-              "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
-              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-e56774a7-c9e7-476f-97ad-72b4a06d9caf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e56774a7-c9e7-476f-97ad-72b4a06d9caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5006da4b-9fac-45f3-93cf-093f338a4b03' class='xr-var-data-in' type='checkbox'><label for='data-5006da4b-9fac-45f3-93cf-093f338a4b03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
-              "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
-              "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
-              "       ...,\n",
-              "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
-              "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
-              "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]],\n",
-              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-404c4618-f62e-4504-b6c3-1859e03b4f70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-404c4618-f62e-4504-b6c3-1859e03b4f70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfe891f4-9f91-4567-8f93-109fc59a7b74' class='xr-var-data-in' type='checkbox'><label for='data-bfe891f4-9f91-4567-8f93-109fc59a7b74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
-              "       [ 97,  94,  98, ...,  97,  95,  97],\n",
-              "       [100, 100, 100, ...,  93, 100,  96],\n",
-              "       ...,\n",
-              "       [100, 100, 100, ..., 100, 100,  98],\n",
-              "       [100, 100, 100, ...,  99, 100,  98],\n",
-              "       [100, 100, 100, ...,  99,  94, 100]],\n",
-              "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-1a470afd-e700-413c-b637-a244630e9ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a470afd-e700-413c-b637-a244630e9ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19fe9666-50f5-495e-8450-dc6b3f76616f' class='xr-var-data-in' type='checkbox'><label for='data-19fe9666-50f5-495e-8450-dc6b3f76616f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
-              "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-              "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
-              "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-              "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
-              "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
-              "\n",
-              "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
-              "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-              "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
-              "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-              "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
-              "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
-              "\n",
-              "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
-              "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
-              "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
-              "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
-              "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
-              "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-a74a7f13-0d52-4f16-82b1-ee206ae6d5bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a74a7f13-0d52-4f16-82b1-ee206ae6d5bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f20d95-68d7-474a-8595-d5c5021028ea' class='xr-var-data-in' type='checkbox'><label for='data-b3f20d95-68d7-474a-8595-d5c5021028ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
-              "        -0.00195312, -0.00390625],\n",
-              "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
-              "         0.        ,  0.00097656],\n",
-              "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-              "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-26443951-1c72-4ee5-bfc4-bd88dbb72a68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26443951-1c72-4ee5-bfc4-bd88dbb72a68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cd4a141-939b-4e48-927f-83fafb7cb2e4' class='xr-var-data-in' type='checkbox'><label for='data-7cd4a141-939b-4e48-927f-83fafb7cb2e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
-              "         0.6247864 ,  0.62490845],\n",
-              "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-              "        -0.03564453, -0.03561401],\n",
-              "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
-              "        -0.04360962, -0.04360962],\n",
-              "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-7ec6af9a-2255-46c2-850c-93e145634ac2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ec6af9a-2255-46c2-850c-93e145634ac2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61005fbb-7dfb-4d0b-9523-6eb3492ca550' class='xr-var-data-in' type='checkbox'><label for='data-61005fbb-7dfb-4d0b-9523-6eb3492ca550' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-4e977b39-1909-48dd-8c7e-e02ad7a96c22' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e977b39-1909-48dd-8c7e-e02ad7a96c22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baa95071-3866-471b-b363-0ef3d4385487' class='xr-var-data-in' type='checkbox'><label for='data-baa95071-3866-471b-b363-0ef3d4385487' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-93757c98-db60-44da-bdfb-1318145581a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93757c98-db60-44da-bdfb-1318145581a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d6e07b5-4397-4172-8c7b-25483bd9111e' class='xr-var-data-in' type='checkbox'><label for='data-2d6e07b5-4397-4172-8c7b-25483bd9111e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-318ea917-1899-4a34-abc4-5c37c5c15fc5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-318ea917-1899-4a34-abc4-5c37c5c15fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b729943f-bf76-445a-ba63-1bf020bd6fb8' class='xr-var-data-in' type='checkbox'><label for='data-b729943f-bf76-445a-ba63-1bf020bd6fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-e6c5b282-4fac-44ca-8c0f-2b06b9941da7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6c5b282-4fac-44ca-8c0f-2b06b9941da7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45c11eaf-5ea8-491f-a07a-6202abbd36f5' class='xr-var-data-in' type='checkbox'><label for='data-45c11eaf-5ea8-491f-a07a-6202abbd36f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-eba533fc-3add-4203-8fe9-58c745d4a428' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eba533fc-3add-4203-8fe9-58c745d4a428' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66aeb13a-c38a-492a-af64-001423f96b88' class='xr-var-data-in' type='checkbox'><label for='data-66aeb13a-c38a-492a-af64-001423f96b88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-              "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-a4b40bd9-d7cb-4510-8ce3-3b2a91e29acc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4b40bd9-d7cb-4510-8ce3-3b2a91e29acc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e4a129a-fc0f-42eb-9338-20dbed6475ad' class='xr-var-data-in' type='checkbox'><label for='data-9e4a129a-fc0f-42eb-9338-20dbed6475ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-f7999b95-d36b-45ad-b566-08589acee982' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7999b95-d36b-45ad-b566-08589acee982' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-042bdbd3-5f68-4ce3-8795-e9b64b6ae1c1' class='xr-var-data-in' type='checkbox'><label for='data-042bdbd3-5f68-4ce3-8795-e9b64b6ae1c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-              "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-36b40b6e-6419-46de-bbb3-b61ce161e810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36b40b6e-6419-46de-bbb3-b61ce161e810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-699e6c95-2bd9-4c71-8390-2bda2c0a5771' class='xr-var-data-in' type='checkbox'><label for='data-699e6c95-2bd9-4c71-8390-2bda2c0a5771' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
-              "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
-              "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-              "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85c4917d-66c8-479f-b4e2-15d04b2bf964' class='xr-section-summary-in' type='checkbox'  ><label for='section-85c4917d-66c8-479f-b4e2-15d04b2bf964' class='xr-section-summary' >Indexes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2de81dd7-2cb8-44e4-904b-7daf8ca0d950' class='xr-index-data-in' type='checkbox'/><label for='index-2de81dd7-2cb8-44e4-904b-7daf8ca0d950' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:01.501100063&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:02.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:03.501100063&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:04.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:05.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:06.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:07.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:08.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:09.500999927&#x27;,\n",
-              "               ...\n",
-              "               &#x27;2020-08-15 15:36:30.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:31.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:32.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:33.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:34.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:35.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:36.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:37.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:38.500999927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:39.500999927&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2afce65d-6462-4849-aa74-76741c2965b9' class='xr-index-data-in' type='checkbox'/><label for='index-2afce65d-6462-4849-aa74-76741c2965b9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:01.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:02.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:03.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:04.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:05.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:06.438400030&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:07.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:08.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 00:20:09.438499927&#x27;,\n",
-              "               ...\n",
-              "               &#x27;2020-08-15 15:36:30.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:31.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:32.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:33.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:34.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:35.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:36.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:37.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:38.438499927&#x27;,\n",
-              "               &#x27;2020-08-15 15:36:39.438499927&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f033e9d7-d4fd-4979-8ac4-bfb33ff92fd8' class='xr-index-data-in' type='checkbox'/><label for='index-f033e9d7-d4fd-4979-8ac4-bfb33ff92fd8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-de7c4065-0bf4-4f6d-b14f-69449fc8b193' class='xr-index-data-in' type='checkbox'/><label for='index-de7c4065-0bf4-4f6d-b14f-69449fc8b193' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9137ad8f-4782-432a-8947-4b73692e8655' class='xr-index-data-in' type='checkbox'/><label for='index-9137ad8f-4782-432a-8947-4b73692e8655' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0263034c-e555-4e21-b001-f590f8e161ea' class='xr-index-data-in' type='checkbox'/><label for='index-0263034c-e555-4e21-b001-f590f8e161ea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-92be0ebb-9e9c-46f7-85f7-7ccca83a0541' class='xr-index-data-in' type='checkbox'/><label for='index-92be0ebb-9e9c-46f7-85f7-7ccca83a0541' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-cb6b149f-ce38-46e6-9fae-b4424b15f76d' class='xr-index-data-in' type='checkbox'/><label for='index-cb6b149f-ce38-46e6-9fae-b4424b15f76d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c06b0f97-0474-48a9-bd9d-0ed657f86896' class='xr-index-data-in' type='checkbox'/><label for='index-c06b0f97-0474-48a9-bd9d-0ed657f86896' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-36cb7aef-fbb6-4ed0-9ce5-1363e63f39ec' class='xr-index-data-in' type='checkbox'/><label for='index-36cb7aef-fbb6-4ed0-9ce5-1363e63f39ec' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4602e62a-bc1a-49ec-bfd7-afd8f4f8498a' class='xr-index-data-in' type='checkbox'/><label for='index-4602e62a-bc1a-49ec-bfd7-afd8f4f8498a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-dea9ba20-680e-4e92-8a42-2918492d10cb' class='xr-index-data-in' type='checkbox'/><label for='index-dea9ba20-680e-4e92-8a42-2918492d10cb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e4c8d97d-a580-46d6-8a37-d465412da7bf' class='xr-section-summary-in' type='checkbox'  ><label for='section-e4c8d97d-a580-46d6-8a37-d465412da7bf' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
-            ],
-            "text/plain": [
-              "<xarray.Dataset> Size: 83MB\n",
-              "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-              "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-              "                          x1: 4, x2: 4)\n",
-              "Coordinates:\n",
-              "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-              "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-              "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-              "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
-              "  * beam                 (beam) int32 16B 1 2 3 4\n",
-              "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
-              "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
-              "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
-              "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
-              "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
-              "  * x1                   (x1) int32 16B 1 2 3 4\n",
-              "  * x2                   (x2) int32 16B 1 2 3 4\n",
-              "Data variables: (12/38)\n",
-              "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-              "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-              "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-              "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-              "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-              "    ...                   ...\n",
-              "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
-              "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
-              "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-              "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-              "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-              "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-              "Attributes: (12/34)\n",
-              "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
-              "    inst_model:            Signature1000\n",
-              "    inst_make:             Nortek\n",
-              "    inst_type:             ADCP\n",
-              "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
-              "    n_cells:               28\n",
-              "    ...                    ...\n",
-              "    proc_idle_less_12pct:  0\n",
-              "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
-              "    coord_sys:             earth\n",
-              "    fs:                    1\n",
-              "    has_imu:               1\n",
-              "    beam_angle:            25"
-            ]
-          },
-          "execution_count": 3,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
-      "source": [
-        "# print the dataset\n",
-        "ds"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "A second way provided to look at data is through the *DOLfYN view*. This view has several convenience methods, shortcuts, and functions built-in. It includes an alternate – and somewhat more informative/compact – description of the data object when in interactive mode. This can be accessed using"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 4,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<ADCP data object>:  Nortek Signature1000\n",
-              "  . 15.28 hours (started: Aug 15, 2020 00:20)\n",
-              "  . earth-frame\n",
-              "  . (55000 pings @ 1Hz)\n",
-              "  Variables:\n",
-              "  - time ('time',)\n",
-              "  - time_b5 ('time_b5',)\n",
-              "  - vel ('dir', 'range', 'time')\n",
-              "  - vel_b5 ('range_b5', 'time_b5')\n",
-              "  - range ('range',)\n",
-              "  - orientmat ('earth', 'inst', 'time')\n",
-              "  - heading ('time',)\n",
-              "  - pitch ('time',)\n",
-              "  - roll ('time',)\n",
-              "  - temp ('time',)\n",
-              "  - pressure ('time',)\n",
-              "  - amp ('beam', 'range', 'time')\n",
-              "  - amp_b5 ('range_b5', 'time_b5')\n",
-              "  - corr ('beam', 'range', 'time')\n",
-              "  - corr_b5 ('range_b5', 'time_b5')\n",
-              "  - accel ('dirIMU', 'time')\n",
-              "  - angrt ('dirIMU', 'time')\n",
-              "  - mag ('dirIMU', 'time')\n",
-              "  ... and others (see `<obj>.variables`)"
-            ]
-          },
-          "execution_count": 4,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
-      "source": [
-        "ds_dolfyn = ds.velds\n",
-        "ds_dolfyn"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 2. Initial Steps for Data Quality Control (QC)\n",
-        "\n",
-        "### 2.1: Set the Deployment Height\n",
-        "\n",
-        "When using Nortek instruments, the deployment software does not factor in the deployment height. The deployment height represents the position of the Acoustic Doppler Current Profiler (ADCP) within the water column. \n",
-        "\n",
-        "In this context, the center of the first depth bin is situated at a distance that is the sum of three elements: \n",
-        "1. Deployment height (the ADCP's position in the water column)\n",
-        "2. Blanking distance (the minimum distance from the ADCP to the first measurement point)\n",
-        "3. Cell size (the vertical distance of each measurement bin in the water column)\n",
-        "\n",
-        "To ensure accurate readings, it is critical to calibrate the 'range' coordinate to make '0' correspond to either the seafloor or sea surface. This calibration can be achieved using the `set_range_offset` function. \n",
-        "\n",
-        "For those using a Teledyne RDI ADCP, the TRDI deployment software will prompt you to specify the deployment height/depth during setup in order to automatically calculate water depth. If there's a need for calibration post-deployment, the `set_range_offset` function can be utilized in the same way as described above to override the initially specified value."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a2a9fdc10>"
-            ]
-          },
-          "execution_count": 5,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "ds[\"vel\"][1].plot()"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "# The ADCP transducers were measured to be 0.6 m from the feet of the lander\n",
-        "api.clean.set_range_offset(ds, 0.6)"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "So, the center of bin 1 is located at 1.2 m:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 7,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
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-              ".xr-section-summary-in:checked + label:before {\n",
-              "  content: \"▼\";\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:checked + label > span {\n",
-              "  display: none;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary,\n",
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-              "  padding-top: 4px;\n",
-              "  padding-bottom: 4px;\n",
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-              "\n",
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-              "  grid-column: 2 / -1;\n",
-              "}\n",
-              "\n",
-              ".xr-section-details {\n",
-              "  display: none;\n",
-              "  grid-column: 1 / -1;\n",
-              "  margin-bottom: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-              "  display: contents;\n",
-              "}\n",
-              "\n",
-              ".xr-array-wrap {\n",
-              "  grid-column: 1 / -1;\n",
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-              "  grid-template-columns: 20px auto;\n",
-              "}\n",
-              "\n",
-              ".xr-array-wrap > label {\n",
-              "  grid-column: 1;\n",
-              "  vertical-align: top;\n",
-              "}\n",
-              "\n",
-              ".xr-preview {\n",
-              "  color: var(--xr-font-color3);\n",
-              "}\n",
-              "\n",
-              ".xr-array-preview,\n",
-              ".xr-array-data {\n",
-              "  padding: 0 5px !important;\n",
-              "  grid-column: 2;\n",
-              "}\n",
-              "\n",
-              ".xr-array-data,\n",
-              ".xr-array-in:checked ~ .xr-array-preview {\n",
-              "  display: none;\n",
-              "}\n",
-              "\n",
-              ".xr-array-in:checked ~ .xr-array-data,\n",
-              ".xr-array-preview {\n",
-              "  display: inline-block;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list {\n",
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-              "  list-style: none;\n",
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-              "  margin: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list li {\n",
-              "  display: inline-block;\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list:before {\n",
-              "  content: \"(\";\n",
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-              "\n",
-              ".xr-dim-list:after {\n",
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-              "\n",
-              ".xr-dim-list li:not(:last-child):after {\n",
-              "  content: \",\";\n",
-              "  padding-right: 5px;\n",
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-              "\n",
-              ".xr-has-index {\n",
-              "  font-weight: bold;\n",
-              "}\n",
-              "\n",
-              ".xr-var-list,\n",
-              ".xr-var-item {\n",
-              "  display: contents;\n",
-              "}\n",
-              "\n",
-              ".xr-var-item > div,\n",
-              ".xr-var-item label,\n",
-              ".xr-var-item > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-even);\n",
-              "  margin-bottom: 0;\n",
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-              "\n",
-              ".xr-var-item > .xr-var-name:hover span {\n",
-              "  padding-right: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-var-list > li:nth-child(odd) > div,\n",
-              ".xr-var-list > li:nth-child(odd) > label,\n",
-              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-odd);\n",
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-              "\n",
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-              "  grid-column: 1;\n",
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-              "\n",
-              ".xr-var-preview {\n",
-              "  grid-column: 4;\n",
-              "}\n",
-              "\n",
-              ".xr-index-preview {\n",
-              "  grid-column: 2 / 5;\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-var-name,\n",
-              ".xr-var-dims,\n",
-              ".xr-var-dtype,\n",
-              ".xr-preview,\n",
-              ".xr-attrs dt {\n",
-              "  white-space: nowrap;\n",
-              "  overflow: hidden;\n",
-              "  text-overflow: ellipsis;\n",
-              "  padding-right: 10px;\n",
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-              "\n",
-              ".xr-var-name:hover,\n",
-              ".xr-var-dims:hover,\n",
-              ".xr-var-dtype:hover,\n",
-              ".xr-attrs dt:hover {\n",
-              "  overflow: visible;\n",
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-              "  z-index: 1;\n",
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-              "\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  display: none;\n",
-              "  background-color: var(--xr-background-color) !important;\n",
-              "  padding-bottom: 5px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-              ".xr-var-data-in:checked ~ .xr-var-data,\n",
-              ".xr-index-data-in:checked ~ .xr-index-data {\n",
-              "  display: block;\n",
-              "}\n",
-              "\n",
-              ".xr-var-data > table {\n",
-              "  float: right;\n",
-              "}\n",
-              "\n",
-              ".xr-var-name span,\n",
-              ".xr-var-data,\n",
-              ".xr-index-name div,\n",
-              ".xr-index-data,\n",
-              ".xr-attrs {\n",
-              "  padding-left: 25px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs,\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  grid-column: 1 / -1;\n",
-              "}\n",
-              "\n",
-              "dl.xr-attrs {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  display: grid;\n",
-              "  grid-template-columns: 125px auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt,\n",
-              ".xr-attrs dd {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  float: left;\n",
-              "  padding-right: 10px;\n",
-              "  width: auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt {\n",
-              "  font-weight: normal;\n",
-              "  grid-column: 1;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt:hover span {\n",
-              "  display: inline-block;\n",
-              "  background: var(--xr-background-color);\n",
-              "  padding-right: 10px;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dd {\n",
-              "  grid-column: 2;\n",
-              "  white-space: pre-wrap;\n",
-              "  word-break: break-all;\n",
-              "}\n",
-              "\n",
-              ".xr-icon-database,\n",
-              ".xr-icon-file-text2,\n",
-              ".xr-no-icon {\n",
-              "  display: inline-block;\n",
-              "  vertical-align: middle;\n",
-              "  width: 1em;\n",
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-              "  stroke-width: 0;\n",
-              "  stroke: currentColor;\n",
-              "  fill: currentColor;\n",
-              "}\n",
-              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt; Size: 224B\n",
-              "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])\n",
-              "Coordinates:\n",
-              "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-              "Attributes:\n",
-              "    coverage_content_type:  coordinate\n",
-              "    units:                  m\n",
-              "    long_name:              Profile Range\n",
-              "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-27183307-48d8-4334-9d4f-9e05d7a24cc7' class='xr-array-in' type='checkbox' checked><label for='section-27183307-48d8-4334-9d4f-9e05d7a24cc7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-0182f8e5-1c9b-476b-af6c-5e3eaa33364e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0182f8e5-1c9b-476b-af6c-5e3eaa33364e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-8ce42991-ade4-4c8c-b8e4-ef266c967ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ce42991-ade4-4c8c-b8e4-ef266c967ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-127f377e-0b3a-46b3-9028-0af3c4ab733e' class='xr-var-data-in' type='checkbox'><label for='data-127f377e-0b3a-46b3-9028-0af3c4ab733e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e8bb7c5-5914-419d-a3aa-7e595f1cc63d' class='xr-section-summary-in' type='checkbox'  ><label for='section-8e8bb7c5-5914-419d-a3aa-7e595f1cc63d' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-eeb0489d-3509-4e51-8c17-c60ea011f3f3' class='xr-index-data-in' type='checkbox'/><label for='index-eeb0489d-3509-4e51-8c17-c60ea011f3f3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
-              "                      2.7,                3.2,                3.7,\n",
-              "                      4.2,  4.699999999999999,  5.199999999999999,\n",
-              "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
-              "        7.199999999999999,  7.699999999999999,                8.2,\n",
-              "                      8.7,                9.2,                9.7,\n",
-              "                     10.2,               10.7,               11.2,\n",
-              "                     11.7,               12.2,               12.7,\n",
-              "                     13.2,               13.7,               14.2,\n",
-              "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c09138d-d003-4599-bca4-cd197af81125' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c09138d-d003-4599-bca4-cd197af81125' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
-            ],
-            "text/plain": [
-              "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
-              "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])\n",
-              "Coordinates:\n",
-              "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-              "Attributes:\n",
-              "    coverage_content_type:  coordinate\n",
-              "    units:                  m\n",
-              "    long_name:              Profile Range\n",
-              "    description:            Distance to the center of each depth bin"
-            ]
-          },
-          "execution_count": 7,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
-      "source": [
-        "ds.range"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 2.2. Discard Data Above Surface Level and Surface Interference\n",
-        "\n",
-        "To reduce computational load, we can exclude all data at or above the water surface level, including that affected by surface interference. Since the instrument was oriented upwards, we can utilize the pressure sensor data along with the function `water_depth_from_pressure` to find the water depth. However, this approach necessitates that the pressure sensor was calibrated or 'zeroed' prior to deployment. If the instrument is facing downwards or doesn't include pressure data, the function `water_depth_from_amplitude` can be used to detect the seabed or water surface.\n",
-        "\n",
-        "It's important to note that Acoustic Doppler Current Profilers (ADCPs) do not measure water salinity, so you'll need to supply this information to the function. If `water_depth_from_pressure` is called after `set_range_offset`, \"depth\" represents the distance from the water surface to the seafloor. Otherwise, it indicates the distance to the ADCP pressure sensor.\n",
-        "\n",
-        "After determining the \"depth\", you can use the `remove_surface_interference` function to discard data in depth bins at or above the actual water surface. Be aware that this function will generate a new dataset."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 8,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "api.clean.water_depth_from_pressure(ds, salinity=31)\n",
-        "ds = api.clean.remove_surface_interference(ds)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 9,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a2aba1090>"
-            ]
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-          "execution_count": 9,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "ds[\"vel\"][1].plot()"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 2.3: Apply an Acoustic Signal Correlation Filter\n",
-        "\n",
-        "After removing data from bins at or above the water surface, we typically apply a filter based on acoustic signal correlation to the ADCP data. This helps to eliminate erroneous velocity data points, which can be caused by factors such as bubbles, kelp, fish, etc., moving through one or multiple beams.\n",
-        "\n",
-        "You can quickly inspect the data to determine an appropriate correlation value by using the built-in plotting feature of xarray. In the following example, we use xarray's slicing capabilities to display data from beam 1 within a range of 0 to 10 m from the ADCP.\n",
-        "\n",
-        "It's important to note that not all ADCPs provide acoustic signal correlation data, which serves as a quantitative measure of signal quality. Older ADCPs may not offer this feature, in which case you can skip this step when using such instruments."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 10,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a7fe4a9d0>"
-            ]
-          },
-          "execution_count": 10,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "%matplotlib inline\n",
-        "ds[\"corr\"].sel(beam=1, range=slice(0, 10)).plot()"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "It's beneficial to also review data from the other beams. A significant portion of this data is of high quality. To avoid discarding valuable data with lower correlations, which could be due to natural variations, we can use the `correlation_filter`. This function assigns a value of NaN (not a number) to velocity values corresponding to correlations below 50%.\n",
-        "\n",
-        "However, it's important to note that the correlation threshold is dependent on the specifics of the deployment environment and the instrument used. It's not unusual to set a threshold as low as 30%, or even to forgo the use of this function entirely."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 11,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "ds = api.clean.correlation_filter(ds, thresh=50)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 12,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a2abaa990>"
-            ]
-          },
-          "execution_count": 12,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "ds[\"vel\"][1].plot()"
-      ]
-    },
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analyzing ADCP Data with MHKiT\n",
+    "\n",
+    "The following example illustrates a straightforward workflow for analyzing Acoustic Doppler Current Profiler (ADCP) data utilizing MHKiT. MHKiT has integrated the DOLfYN codebase as a module to facilitate ADCP and Acoustic Doppler Velocimetry (ADV) data processing.\n",
+    "\n",
+    "Here is a standard workflow for ADCP data analysis:\n",
+    "\n",
+    "1. **Import Data**\n",
+    "\n",
+    "2. **Review, QC, and Prepare the Raw Data**:\n",
+    "   1. Calculate or verify the correctness of depth bin locations\n",
+    "   2. Discard data recorded above the water surface or below the seafloor\n",
+    "   3. Assess the quality of velocity, beam amplitude, and/or beam correlation data\n",
+    "   4. Rotate Data Coordinate System\n",
+    "\n",
+    "3. **Data Averaging**: \n",
+    "    - If not already executed within the instrument, average the data into time bins of a predetermined duration, typically between 5 and 10 minutes\n",
+    "\n",
+    "4. **Speed and Direction**\n",
+    "\n",
+    "5. **Plotting**\n",
+    "\n",
+    "6. **Saving and Loading DOLfYN datasets**\n",
+    "\n",
+    "7. **Turbulence Statistics**\n",
+    "    1. Turbulence Intensity (TI)\n",
+    "    2. Power Spectral Densities\n",
+    "    3. Instrument Noise\n",
+    "    4. TKE Dissipation Rate\n",
+    "    5. Noise-corrected TI\n",
+    "    6. Reynolds stresses\n",
+    "    7. TKE Production\n",
+    "    8. TKE Balance \n",
+    "\n",
+    "\n",
+    "Begin your analysis by importing the requisite tools:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "from mhkit import dolfyn\n",
+    "from mhkit.dolfyn.adp import api\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##  1. Importing Raw Instrument Data\n",
+    "\n",
+    "One of DOLfYN's key features is its ability to directly import raw data from an Acoustic Doppler Current Profiler (ADCP) right after it has been transferred. In this instance, we are using a Nortek Signature1000 ADCP, with the data stored in files with an '.ad2cp' extension. This specific dataset represents several hours of velocity data, captured at 1 Hz by an ADCP mounted on a bottom lander within a tidal inlet. The list of instruments compatible with DOLfYN can be found in the [MHKiT DOLfYN documentation](https://mhkit-software.github.io/MHKiT/mhkit-python/api.dolfyn.html).\n",
+    "\n",
+    "We'll start by importing the raw data file downloaded from the instrument. The `read` function processes the raw file and converts the information into an xarray Dataset. This Dataset includes several groups of variables:\n",
+    "\n",
+    "1. **Velocity**: Recorded in the coordinate system saved by the instrument (beam, XYZ, ENU)\n",
+    "2. **Beam Data**: Includes amplitude and correlation data\n",
+    "3. **Instrumental & Environmental Measurements**: Captures the instrument's bearing and environmental conditions\n",
+    "4. **Orientation Matrices**: Used by DOLfYN for rotating through different coordinate frames.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 2.4 Rotate Data Coordinate System\n",
-        "\n",
-        "After cleaning the data, the next step is to rotate the velocity data into accurate East, North, Up (ENU) coordinates.\n",
-        "\n",
-        "ADCPs utilize an internal compass or magnetometer to determine magnetic ENU directions. You can use the set_declination function to adjust the velocity data according to the magnetic declination specific to your geographical coordinates. This declination can be looked up online for specific coordinates.\n",
-        "\n",
-        "Instruments save vector data in the coordinate system defined in the deployment configuration file. To make this data meaningful, it must be transformed through various coordinate systems (\"beam\"<->\"inst\"<->\"earth\"<->\"principal\"). This transformation is accomplished using the `rotate2` function. If the \"earth\" (ENU) coordinate system is specified, DOLfYN will automatically rotate the dataset through the required coordinate systems to reach the \"earth\" coordinates. Setting `inplace` to true will modify the input dataset directly, meaning it will not create a new dataset.\n",
-        "\n",
-        "In this case, since the ADCP data is already in the \"earth\" coordinate system, the `rotate2` function will return the input dataset without modifications. The `set_declination` function will work no matter the coordinate system."
-      ]
-    },
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file data/dolfyn/Sig1000_tidal.ad2cp ...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds = dolfyn.read(\"data/dolfyn/Sig1000_tidal.ad2cp\")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are two ways to see what's in a Dataset. The first is to simply type the dataset's name to see the standard xarray output. To access a particular variable in a dataset, use dict-style (`ds['vel']`) or attribute-style syntax (`ds.vel`). See the [xarray docs](http://xarray.pydata.org/en/stable/getting-started-guide/quick-overview.html) for more details on how to use the xarray format."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 13,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Data is already in the earth coordinate system\n"
-          ]
-        }
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 83MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
+       "Coordinates:\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
+       "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
+       "Data variables: (12/38)\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    ...                   ...\n",
+       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+       "Attributes: (12/34)\n",
+       "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
+       "    inst_model:            Signature1000\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
+       "    n_cells:               28\n",
+       "    ...                    ...\n",
+       "    proc_idle_less_12pct:  0\n",
+       "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
+       "    coord_sys:             earth\n",
+       "    fs:                    1\n",
+       "    has_imu:               1\n",
+       "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f28a974d-02c1-4c0e-b0aa-35a34cb04614' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f28a974d-02c1-4c0e-b0aa-35a34cb04614' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-73f6a664-08f3-4fbb-9c79-c107bd2e17a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73f6a664-08f3-4fbb-9c79-c107bd2e17a5' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-2bf135d0-099b-454c-92c3-0fc84896aa43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bf135d0-099b-454c-92c3-0fc84896aa43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b43dbf41-e9ef-4950-984f-d8f6138b0ddb' class='xr-var-data-in' type='checkbox'><label for='data-b43dbf41-e9ef-4950-984f-d8f6138b0ddb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+       "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
+       "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
+       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-603893bf-5abc-410a-8c19-ef29f6982588' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-603893bf-5abc-410a-8c19-ef29f6982588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c572de15-bf56-4083-bb69-eb0ea27440df' class='xr-var-data-in' type='checkbox'><label for='data-c572de15-bf56-4083-bb69-eb0ea27440df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+       "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
+       "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
+       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-2a25848e-bb35-49a4-b9fb-672be8314b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a25848e-bb35-49a4-b9fb-672be8314b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d260546b-dc09-4642-9764-acbe5209a5bb' class='xr-var-data-in' type='checkbox'><label for='data-d260546b-dc09-4642-9764-acbe5209a5bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-6c42074c-a1d8-4c94-8018-7c1e5846fcbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c42074c-a1d8-4c94-8018-7c1e5846fcbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fb7f816-ba22-412a-a090-0d23c8c09ee0' class='xr-var-data-in' type='checkbox'><label for='data-7fb7f816-ba22-412a-a090-0d23c8c09ee0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-8f9f0671-99ea-4543-a37b-d94c1ac426d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f9f0671-99ea-4543-a37b-d94c1ac426d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5acdfbec-8b28-4849-8321-02b4f256cc65' class='xr-var-data-in' type='checkbox'><label for='data-5acdfbec-8b28-4849-8321-02b4f256cc65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-fe64bed1-065d-4572-820c-a546674bc23b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe64bed1-065d-4572-820c-a546674bc23b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91cb97d1-6a16-4001-9fe4-7c770edad6a5' class='xr-var-data-in' type='checkbox'><label for='data-91cb97d1-6a16-4001-9fe4-7c770edad6a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-a282b85b-1f3d-41db-9220-93b48867f2a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a282b85b-1f3d-41db-9220-93b48867f2a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37a55f67-7a4c-4fe9-8eb4-4e30a9092209' class='xr-var-data-in' type='checkbox'><label for='data-37a55f67-7a4c-4fe9-8eb4-4e30a9092209' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-a9a65575-08ac-4c58-94a7-e351c187dcff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9a65575-08ac-4c58-94a7-e351c187dcff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27ad0f22-1689-4e27-85a9-03077cf5af87' class='xr-var-data-in' type='checkbox'><label for='data-27ad0f22-1689-4e27-85a9-03077cf5af87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-69f85873-b714-4894-bcdf-1e1100f23400' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69f85873-b714-4894-bcdf-1e1100f23400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81d1c39c-d2f5-46d2-8b2d-13206e10bed1' class='xr-var-data-in' type='checkbox'><label for='data-81d1c39c-d2f5-46d2-8b2d-13206e10bed1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-a14bc8fc-bfb6-4a07-ae07-0c00765ca633' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a14bc8fc-bfb6-4a07-ae07-0c00765ca633' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bd0f72c-78f5-4b0b-af0b-0b8a580840cb' class='xr-var-data-in' type='checkbox'><label for='data-3bd0f72c-78f5-4b0b-af0b-0b8a580840cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-cc997752-660a-4a7e-92db-5dc162d10c73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc997752-660a-4a7e-92db-5dc162d10c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fccb9774-d78a-413b-b35e-56e61fa4fc88' class='xr-var-data-in' type='checkbox'><label for='data-fccb9774-d78a-413b-b35e-56e61fa4fc88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-18671300-7253-40b7-b0f9-f82e20574edb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18671300-7253-40b7-b0f9-f82e20574edb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55b56463-9c00-4b38-a15f-b5bc9114fc0f' class='xr-var-data-in' type='checkbox'><label for='data-55b56463-9c00-4b38-a15f-b5bc9114fc0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b40bdc2f-5ba2-43b8-88e0-ab62a460bc56' class='xr-section-summary-in' type='checkbox'  ><label for='section-b40bdc2f-5ba2-43b8-88e0-ab62a460bc56' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-11d0c1f6-a1d8-414c-83fe-3e3c06a05ca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11d0c1f6-a1d8-414c-83fe-3e3c06a05ca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c481825-6aa6-41dc-9aa8-05b64183f645' class='xr-var-data-in' type='checkbox'><label for='data-3c481825-6aa6-41dc-9aa8-05b64183f645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-276d2650-d81c-4c34-9775-78a2e2e1e367' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-276d2650-d81c-4c34-9775-78a2e2e1e367' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41ff6085-7e2b-4f24-9fd7-bb2485b84cf1' class='xr-var-data-in' type='checkbox'><label for='data-41ff6085-7e2b-4f24-9fd7-bb2485b84cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-5d688586-aa74-4f0d-ad5e-fbd7d9488d60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d688586-aa74-4f0d-ad5e-fbd7d9488d60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47260f77-e611-4f40-8321-6331a6f1564a' class='xr-var-data-in' type='checkbox'><label for='data-47260f77-e611-4f40-8321-6331a6f1564a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-e6322c76-1557-4aa8-815e-7930d416ce20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6322c76-1557-4aa8-815e-7930d416ce20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3394cdc-3ef0-47f7-9e63-fb198b8e9f1c' class='xr-var-data-in' type='checkbox'><label for='data-b3394cdc-3ef0-47f7-9e63-fb198b8e9f1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+       "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
+       "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-14a9fcb0-6690-4c66-9888-93437bec3f33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14a9fcb0-6690-4c66-9888-93437bec3f33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f26e634c-ad73-4b8e-8d60-0a562215bfed' class='xr-var-data-in' type='checkbox'><label for='data-f26e634c-ad73-4b8e-8d60-0a562215bfed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+       "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
+       "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
+       "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
+       "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
+       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-ce4bd203-6f47-4d75-877f-b2d6458ffa2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce4bd203-6f47-4d75-877f-b2d6458ffa2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff83154-4207-4313-9bea-3642e3d9693a' class='xr-var-data-in' type='checkbox'><label for='data-8ff83154-4207-4313-9bea-3642e3d9693a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-638397a6-8e5b-4462-b526-34e79ade8cdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-638397a6-8e5b-4462-b526-34e79ade8cdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a687b8c7-daa8-4804-9913-5308745abcff' class='xr-var-data-in' type='checkbox'><label for='data-a687b8c7-daa8-4804-9913-5308745abcff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-d5e19c7f-ae28-4acf-9f57-8ccf921b9bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5e19c7f-ae28-4acf-9f57-8ccf921b9bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b22bf5-0482-46ba-add2-be69c364880c' class='xr-var-data-in' type='checkbox'><label for='data-d1b22bf5-0482-46ba-add2-be69c364880c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-6343e252-273c-431b-823b-eb2bde09e714' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6343e252-273c-431b-823b-eb2bde09e714' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3397a186-35a2-46ac-a040-b32afaf9a17e' class='xr-var-data-in' type='checkbox'><label for='data-3397a186-35a2-46ac-a040-b32afaf9a17e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-5bc2999c-15fc-4cb5-94a4-67caadb4c7af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bc2999c-15fc-4cb5-94a4-67caadb4c7af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7569e9e-c73e-4915-9ec2-524b7fab94ff' class='xr-var-data-in' type='checkbox'><label for='data-a7569e9e-c73e-4915-9ec2-524b7fab94ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-7fe81551-7fd9-44c5-8f10-a69e53b22908' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fe81551-7fd9-44c5-8f10-a69e53b22908' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48264037-1850-4629-940b-afe003baed01' class='xr-var-data-in' type='checkbox'><label for='data-48264037-1850-4629-940b-afe003baed01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+       "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
+       "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
+       "        ...,\n",
+       "        [-0.169, -0.013, -0.124, ..., -0.062,  0.091, -0.009],\n",
+       "        [-0.16 , -0.043, -0.111, ...,  0.012,  0.089,  0.021],\n",
+       "        [-0.158, -0.057, -0.13 , ..., -0.055,  0.104,  0.013]],\n",
+       "\n",
+       "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
+       "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
+       "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
+       "        ...,\n",
+       "        [ 0.305,  0.377,  0.283, ..., -0.198, -0.229, -0.121],\n",
+       "        [ 0.328,  0.33 ,  0.294, ..., -0.161, -0.292, -0.103],\n",
+       "        [ 0.31 ,  0.314,  0.226, ..., -0.219, -0.292, -0.049]],\n",
+       "\n",
+       "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
+       "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
+       "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
+       "        ...,\n",
+       "        [ 0.034, -0.061, -0.024, ..., -0.014,  0.086,  0.01 ],\n",
+       "        [ 0.032, -0.04 , -0.027, ..., -0.014,  0.063, -0.01 ],\n",
+       "        [ 0.004, -0.037, -0.018, ..., -0.001,  0.059,  0.021]],\n",
+       "\n",
+       "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
+       "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
+       "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
+       "        ...,\n",
+       "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
+       "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
+       "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
+       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-6a311971-8539-4391-959b-5a2e29c55984' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a311971-8539-4391-959b-5a2e29c55984' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72821c48-0bc3-4a04-a089-cc29f3bd3eeb' class='xr-var-data-in' type='checkbox'><label for='data-72821c48-0bc3-4a04-a089-cc29f3bd3eeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+       "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
+       "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
+       "        ...,\n",
+       "        [54.5, 55.5, 54.5, ..., 50. , 50. , 49.5],\n",
+       "        [53.5, 54.5, 54.5, ..., 46.5, 47. , 46.5],\n",
+       "        [53. , 54. , 53. , ..., 45. , 46. , 44.5]],\n",
+       "\n",
+       "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
+       "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
+       "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
+       "        ...,\n",
+       "        [57. , 58.5, 58. , ..., 53.5, 52. , 52.5],\n",
+       "        [55.5, 56.5, 55.5, ..., 50. , 49. , 49. ],\n",
+       "        [52.5, 54. , 54. , ..., 47.5, 47.5, 47. ]],\n",
+       "\n",
+       "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
+       "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
+       "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
+       "        ...,\n",
+       "        [56.5, 56.5, 57. , ..., 47.5, 47. , 48. ],\n",
+       "        [56. , 55.5, 56.5, ..., 46.5, 47. , 47. ],\n",
+       "        [54.5, 54. , 55.5, ..., 45. , 45.5, 45.5]],\n",
+       "\n",
+       "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
+       "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
+       "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
+       "        ...,\n",
+       "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
+       "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
+       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]],\n",
+       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-56aad773-9465-4433-bb11-a09cfcd4df6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56aad773-9465-4433-bb11-a09cfcd4df6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8543c267-4dac-4f97-8328-ebb8ff57392b' class='xr-var-data-in' type='checkbox'><label for='data-8543c267-4dac-4f97-8328-ebb8ff57392b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+       "        [ 74,  92,  96, ..., 100,  97, 100],\n",
+       "        [100, 100,  99, ...,  99, 100, 100],\n",
+       "        ...,\n",
+       "        [ 99, 100, 100, ...,  96,  96,  99],\n",
+       "        [ 99,  97, 100, ...,  94,  97,  96],\n",
+       "        [ 98, 100, 100, ..., 100, 100,  98]],\n",
+       "\n",
+       "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
+       "        [ 94, 100, 100, ...,  96, 100,  93],\n",
+       "        [ 99,  95,  97, ...,  98,  98, 100],\n",
+       "        ...,\n",
+       "        [100, 100, 100, ...,  98,  99, 100],\n",
+       "        [ 99, 100,  99, ...,  97,  94,  94],\n",
+       "        [ 96,  99,  96, ...,  97, 100,  97]],\n",
+       "\n",
+       "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
+       "        [ 99, 100,  99, ...,  96,  88,  98],\n",
+       "        [ 97, 100,  98, ..., 100,  99,  97],\n",
+       "        ...,\n",
+       "        [100, 100,  99, ...,  97,  94,  95],\n",
+       "        [100, 100, 100, ...,  96, 100, 100],\n",
+       "        [100, 100, 100, ...,  96,  95,  94]],\n",
+       "\n",
+       "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
+       "        [100,  93,  93, ...,  96,  96,  97],\n",
+       "        [100, 100, 100, ..., 100, 100,  97],\n",
+       "        ...,\n",
+       "        [100,  99,  96, ...,  98, 100, 100],\n",
+       "        [100, 100, 100, ...,  94,  93,  95],\n",
+       "        [100,  98,  99, ...,  98,  98,  96]]],\n",
+       "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-9b9c2cc3-8d21-4715-9999-c6d82daf0381' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b9c2cc3-8d21-4715-9999-c6d82daf0381' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-370f5f57-f122-4594-b089-ec9ae3c4b3aa' class='xr-var-data-in' type='checkbox'><label for='data-370f5f57-f122-4594-b089-ec9ae3c4b3aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+       "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
+       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+       "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
+       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
+       "\n",
+       "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
+       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+       "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
+       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+       "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
+       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
+       "\n",
+       "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
+       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
+       "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
+       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
+       "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
+       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-777fa3a5-705e-4db6-8040-d98d483332a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-777fa3a5-705e-4db6-8040-d98d483332a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1832c48-85c6-4601-9fd1-5a6d47409bb7' class='xr-var-data-in' type='checkbox'><label for='data-f1832c48-85c6-4601-9fd1-5a6d47409bb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+       "        -0.00292969, -0.00195312],\n",
+       "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
+       "         0.00097656,  0.00097656],\n",
+       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+       "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-b3df1677-f6ee-4361-9744-d264f633c86d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3df1677-f6ee-4361-9744-d264f633c86d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0922c989-b7fb-402e-b5da-d2bb0d2c1cf7' class='xr-var-data-in' type='checkbox'><label for='data-0922c989-b7fb-402e-b5da-d2bb0d2c1cf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+       "         0.6247864 ,  0.62490845],\n",
+       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+       "        -0.03564453, -0.03561401],\n",
+       "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
+       "        -0.04360962, -0.04360962],\n",
+       "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
+       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-369b7ac7-3c76-4829-bd5a-e24553418a5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-369b7ac7-3c76-4829-bd5a-e24553418a5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca75ac4f-4c6f-4bf2-9533-9288632ae70f' class='xr-var-data-in' type='checkbox'><label for='data-ca75ac4f-4c6f-4bf2-9533-9288632ae70f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-9f0ad4f2-aaa7-42b0-917b-c9f7c5b115c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f0ad4f2-aaa7-42b0-917b-c9f7c5b115c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ce54ca4-b578-404d-84f7-cbf3032c8853' class='xr-var-data-in' type='checkbox'><label for='data-7ce54ca4-b578-404d-84f7-cbf3032c8853' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-6e7cb7a1-075d-4116-af50-af4ebeb85739' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e7cb7a1-075d-4116-af50-af4ebeb85739' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d97d916-ae98-48c8-a287-d25c690a0daf' class='xr-var-data-in' type='checkbox'><label for='data-4d97d916-ae98-48c8-a287-d25c690a0daf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+       "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
+       "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-f403d93b-53cf-4afb-8397-8afdcf14e667' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f403d93b-53cf-4afb-8397-8afdcf14e667' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8492deda-94a2-4ba0-9972-e35a250f6ed3' class='xr-var-data-in' type='checkbox'><label for='data-8492deda-94a2-4ba0-9972-e35a250f6ed3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+       "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
+       "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
+       "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
+       "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
+       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-8753e491-8667-4bdc-85f3-06c43ba85c61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8753e491-8667-4bdc-85f3-06c43ba85c61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3643a4a9-9e2e-427e-893c-d7c598d80254' class='xr-var-data-in' type='checkbox'><label for='data-3643a4a9-9e2e-427e-893c-d7c598d80254' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-193f34be-d8d4-4977-a71f-bb63445659b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-193f34be-d8d4-4977-a71f-bb63445659b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ae9e849-6118-49a4-b4db-ebbc4bcf4eac' class='xr-var-data-in' type='checkbox'><label for='data-1ae9e849-6118-49a4-b4db-ebbc4bcf4eac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-bac83806-7e0d-4f0c-ae41-d3838df691c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bac83806-7e0d-4f0c-ae41-d3838df691c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03de88eb-7398-4de1-90b2-529099f32800' class='xr-var-data-in' type='checkbox'><label for='data-03de88eb-7398-4de1-90b2-529099f32800' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-62c5f014-9241-42d8-ad8b-134f3b0c2f25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62c5f014-9241-42d8-ad8b-134f3b0c2f25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97cfe342-8196-4402-ba27-a1c80696ed1e' class='xr-var-data-in' type='checkbox'><label for='data-97cfe342-8196-4402-ba27-a1c80696ed1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+       "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
+       "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
+       "       ...,\n",
+       "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
+       "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
+       "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
+       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-4cc9ef2a-f41a-4ab0-9776-aa0ad0ea04d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4cc9ef2a-f41a-4ab0-9776-aa0ad0ea04d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acdc68ed-ef5f-4caa-a112-66b2593f4492' class='xr-var-data-in' type='checkbox'><label for='data-acdc68ed-ef5f-4caa-a112-66b2593f4492' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+       "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
+       "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
+       "       ...,\n",
+       "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
+       "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
+       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]],\n",
+       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-76a59e93-8a68-4c75-9552-dc6c6546a3b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76a59e93-8a68-4c75-9552-dc6c6546a3b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b472c615-dea5-49b7-a2ee-7540f0a413d1' class='xr-var-data-in' type='checkbox'><label for='data-b472c615-dea5-49b7-a2ee-7540f0a413d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+       "       [ 97,  94,  98, ...,  97,  95,  97],\n",
+       "       [100, 100, 100, ...,  93, 100,  96],\n",
+       "       ...,\n",
+       "       [100, 100, 100, ..., 100, 100,  98],\n",
+       "       [100, 100, 100, ...,  99, 100,  98],\n",
+       "       [100, 100, 100, ...,  99,  94, 100]],\n",
+       "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-c18e2035-c4f9-45f7-ac74-820e5d113539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c18e2035-c4f9-45f7-ac74-820e5d113539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-056471b0-c180-4158-8790-a13facc490cc' class='xr-var-data-in' type='checkbox'><label for='data-056471b0-c180-4158-8790-a13facc490cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+       "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
+       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+       "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
+       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
+       "\n",
+       "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
+       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+       "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
+       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+       "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
+       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
+       "\n",
+       "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
+       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
+       "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
+       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
+       "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
+       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-939e8beb-5806-47c7-bbac-a5b77d8d2d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-939e8beb-5806-47c7-bbac-a5b77d8d2d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c11138d-4e5f-4e3c-b8f3-bac261b7e7cb' class='xr-var-data-in' type='checkbox'><label for='data-3c11138d-4e5f-4e3c-b8f3-bac261b7e7cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+       "        -0.00195312, -0.00390625],\n",
+       "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
+       "         0.        ,  0.00097656],\n",
+       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+       "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-9b0ac6e1-bea8-4307-9dc7-9863e4b221ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b0ac6e1-bea8-4307-9dc7-9863e4b221ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f43d76ae-75fc-43b6-97f7-e76dcaa21183' class='xr-var-data-in' type='checkbox'><label for='data-f43d76ae-75fc-43b6-97f7-e76dcaa21183' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+       "         0.6247864 ,  0.62490845],\n",
+       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+       "        -0.03564453, -0.03561401],\n",
+       "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
+       "        -0.04360962, -0.04360962],\n",
+       "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
+       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-7509e529-273f-4169-9c6c-138a57766fde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7509e529-273f-4169-9c6c-138a57766fde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e92d63e-8f07-41a5-b463-5e374259309c' class='xr-var-data-in' type='checkbox'><label for='data-0e92d63e-8f07-41a5-b463-5e374259309c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-53521fd9-798b-4a9c-b11c-d52775a96263' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53521fd9-798b-4a9c-b11c-d52775a96263' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f11ec6fb-60b9-4bd8-b625-51f371434f74' class='xr-var-data-in' type='checkbox'><label for='data-f11ec6fb-60b9-4bd8-b625-51f371434f74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-a8944bce-70c7-436a-91bb-c4abb1fd9507' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a8944bce-70c7-436a-91bb-c4abb1fd9507' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bcf6f94-248e-459c-b751-fabed7292479' class='xr-var-data-in' type='checkbox'><label for='data-7bcf6f94-248e-459c-b751-fabed7292479' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-6757c338-4e8c-4dc9-b50e-1bbe018e9825' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6757c338-4e8c-4dc9-b50e-1bbe018e9825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e3b3997-2deb-4ece-ba76-3daf7370642f' class='xr-var-data-in' type='checkbox'><label for='data-0e3b3997-2deb-4ece-ba76-3daf7370642f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-0c05add4-068c-49a7-9ac2-3704a77417e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c05add4-068c-49a7-9ac2-3704a77417e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df4fa6f3-587c-4280-a100-85a4e60f465e' class='xr-var-data-in' type='checkbox'><label for='data-df4fa6f3-587c-4280-a100-85a4e60f465e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-331cc7f8-0610-4c67-9d3e-515fc3d73aee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-331cc7f8-0610-4c67-9d3e-515fc3d73aee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-561108d0-676b-4d20-96ef-3b87a24bcc0b' class='xr-var-data-in' type='checkbox'><label for='data-561108d0-676b-4d20-96ef-3b87a24bcc0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+       "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-0f345601-b07b-474e-a2a0-49a2ec0708f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f345601-b07b-474e-a2a0-49a2ec0708f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cfc3192-7bda-4cec-a282-6c400ee02a2e' class='xr-var-data-in' type='checkbox'><label for='data-4cfc3192-7bda-4cec-a282-6c400ee02a2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-45ec3d74-0628-4889-a8fb-529b86508120' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45ec3d74-0628-4889-a8fb-529b86508120' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5daaec6-28f0-4f8d-93a6-a5b68f6598c3' class='xr-var-data-in' type='checkbox'><label for='data-c5daaec6-28f0-4f8d-93a6-a5b68f6598c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+       "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-8c09064d-3cdc-41fc-a42f-590b2be4e59d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c09064d-3cdc-41fc-a42f-590b2be4e59d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e624ebaf-c843-4311-9779-b513fd032d37' class='xr-var-data-in' type='checkbox'><label for='data-e624ebaf-c843-4311-9779-b513fd032d37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+       "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
+       "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
+       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b62067c6-93e4-4617-b952-0abf39e01c72' class='xr-section-summary-in' type='checkbox'  ><label for='section-b62067c6-93e4-4617-b952-0abf39e01c72' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
       ],
-      "source": [
-        "dolfyn.set_declination(ds, 15.8, inplace=True)  # 15.8 deg East\n",
-        "dolfyn.rotate2(ds, \"earth\", inplace=True)"
+      "text/plain": [
+       "<xarray.Dataset> Size: 83MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
+       "Coordinates:\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
+       "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
+       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
+       "Data variables: (12/38)\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    ...                   ...\n",
+       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+       "Attributes: (12/34)\n",
+       "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
+       "    inst_model:            Signature1000\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
+       "    n_cells:               28\n",
+       "    ...                    ...\n",
+       "    proc_idle_less_12pct:  0\n",
+       "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
+       "    coord_sys:             earth\n",
+       "    fs:                    1\n",
+       "    has_imu:               1\n",
+       "    beam_angle:            25"
       ]
-    },
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# print the dataset\n",
+    "ds"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A second way provided to look at data is through the *DOLfYN view*. This view has several convenience methods, shortcuts, and functions built-in. It includes an alternate – and somewhat more informative/compact – description of the data object when in interactive mode. This can be accessed using"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "To rotate into the principal frame of reference (streamwise, cross-stream, vertical), if desired, we must first calculate the depth-averaged principal flow heading and add it to the dataset attributes. Then the dataset can be rotated using the same `rotate2` function. We use `inplace=False` because we do not want to alter the input dataset here."
+     "data": {
+      "text/plain": [
+       "<ADCP data object>:  Nortek Signature1000\n",
+       "  . 15.28 hours (started: Aug 15, 2020 00:20)\n",
+       "  . earth-frame\n",
+       "  . (55000 pings @ 1Hz)\n",
+       "  Variables:\n",
+       "  - time ('time',)\n",
+       "  - time_b5 ('time_b5',)\n",
+       "  - vel ('dir', 'range', 'time')\n",
+       "  - vel_b5 ('range_b5', 'time_b5')\n",
+       "  - range ('range',)\n",
+       "  - orientmat ('earth', 'inst', 'time')\n",
+       "  - heading ('time',)\n",
+       "  - pitch ('time',)\n",
+       "  - roll ('time',)\n",
+       "  - temp ('time',)\n",
+       "  - pressure ('time',)\n",
+       "  - amp ('beam', 'range', 'time')\n",
+       "  - amp_b5 ('range_b5', 'time_b5')\n",
+       "  - corr ('beam', 'range', 'time')\n",
+       "  - corr_b5 ('range_b5', 'time_b5')\n",
+       "  - accel ('dirIMU', 'time')\n",
+       "  - angrt ('dirIMU', 'time')\n",
+       "  - mag ('dirIMU', 'time')\n",
+       "  ... and others (see `<obj>.variables`)"
       ]
-    },
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_dolfyn = ds.velds\n",
+    "ds_dolfyn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One way to visualize this data is to plot the velocity in a histogram. This will highlight any outliers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 14,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "ds.attrs[\"principal_heading\"] = dolfyn.calc_principal_heading(ds[\"vel\"].mean(\"range\"))\n",
-        "ds = dolfyn.rotate2(ds, \"principal\", inplace=False)"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1200 with 4 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vel = ds[\"vel\"]\n",
+    "\n",
+    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+    "labels = vel.coords[vel_dim].values\n",
+    "\n",
+    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
+    "\n",
+    "if len(labels) == 1:\n",
+    "    axes = [axes]\n",
+    "\n",
+    "for ax_i, label in zip(axes, labels):\n",
+    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+    "    values = values[np.isfinite(values)]\n",
+    "\n",
+    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+    "    ax_i.set_ylabel(\"Count\")\n",
+    "\n",
+    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Initial Steps for Data Quality Control (QC)\n",
+    "\n",
+    "### 2.1: Set the Deployment Height\n",
+    "\n",
+    "When using Nortek instruments, the deployment software does not factor in the deployment height. The deployment height represents the position of the Acoustic Doppler Current Profiler (ADCP) within the water column. \n",
+    "\n",
+    "In this context, the center of the first depth bin is situated at a distance that is the sum of three elements: \n",
+    "1. Deployment height (the ADCP's position in the water column)\n",
+    "2. Blanking distance (the minimum distance from the ADCP to the first measurement point)\n",
+    "3. Cell size (the vertical distance of each measurement bin in the water column)\n",
+    "\n",
+    "To ensure accurate readings, it is critical to calibrate the 'range' coordinate to make '0' correspond to either the seafloor or sea surface. This calibration can be achieved using the `set_range_offset` function. \n",
+    "\n",
+    "For those using a Teledyne RDI ADCP, the TRDI deployment software will prompt you to specify the deployment height/depth during setup in order to automatically calculate water depth. If there's a need for calibration post-deployment, the `set_range_offset` function can be utilized in the same way as described above to override the initially specified value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 3. Average the Data\n",
-        "\n",
-        "As this deployment was configured in \"burst mode\", a standard step in the analysis process is to average the velocity data into time bins. \n",
-        "\n",
-        "However, if the instrument was set up in an \"averaging mode\" (where a specific profile and/or average interval was set, for instance, averaging 5 minutes of data every 30 minutes), this step would have been performed within the ADCP during deployment and can thus be skipped.\n",
-        "\n",
-        "To average the data into time bins (also known as ensembles), you should first initialize the binning tool `ADPBinner`. The parameter \"n_bin\" represents the number of data points in each ensemble. In this case, we're dealing with 300 seconds' worth of data. The \"fs\" parameter stands for the sampling frequency, which for this deployment is 1 Hz. Once the binning tool is initialized, you can use the `bin_average` function to average the data into ensembles."
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x400 with 6 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    ds[\"vel\"][i].plot(ax=ax)\n",
+    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The ADCP transducers were measured to be 0.6 m from the feet of the lander\n",
+    "api.clean.set_range_offset(ds, 0.6)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So, the center of bin 1 is located at 1.2 m, with a constant a 0.5m bin size. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 15,
-      "metadata": {
-        "scrolled": true
-      },
-      "outputs": [],
-      "source": [
-        "avg_tool = api.ADPBinner(n_bin=ds.fs * 300, fs=ds.fs)\n",
-        "ds_avg = avg_tool.bin_average(ds)"
-      ]
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "      Statistic  Value\n",
+      "0           min    1.2\n",
+      "1           max   14.7\n",
+      "2  mean spacing    0.5\n",
+      "3   max spacing    0.5\n",
+      "4   min spacing    0.5\n"
+     ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 16,
-      "metadata": {},
-      "outputs": [
-        {
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-              "  margin-right: 10px;\n",
-              "}\n",
-              "\n",
-              ".xr-obj-type {\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-sections {\n",
-              "  padding-left: 0 !important;\n",
-              "  display: grid;\n",
-              "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
-              "}\n",
-              "\n",
-              ".xr-section-item {\n",
-              "  display: contents;\n",
-              "}\n",
-              "\n",
-              ".xr-section-item input {\n",
-              "  display: inline-block;\n",
-              "  opacity: 0;\n",
-              "  height: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-section-item input + label {\n",
-              "  color: var(--xr-disabled-color);\n",
-              "}\n",
-              "\n",
-              ".xr-section-item input:enabled + label {\n",
-              "  cursor: pointer;\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-section-item input:focus + label {\n",
-              "  border: 2px solid var(--xr-font-color0);\n",
-              "}\n",
-              "\n",
-              ".xr-section-item input:enabled + label:hover {\n",
-              "  color: var(--xr-font-color0);\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary {\n",
-              "  grid-column: 1;\n",
-              "  color: var(--xr-font-color2);\n",
-              "  font-weight: 500;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary > span {\n",
-              "  display: inline-block;\n",
-              "  padding-left: 0.5em;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:disabled + label {\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in + label:before {\n",
-              "  display: inline-block;\n",
-              "  content: \"►\";\n",
-              "  font-size: 11px;\n",
-              "  width: 15px;\n",
-              "  text-align: center;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:disabled + label:before {\n",
-              "  color: var(--xr-disabled-color);\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:checked + label:before {\n",
-              "  content: \"▼\";\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:checked + label > span {\n",
-              "  display: none;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary,\n",
-              ".xr-section-inline-details {\n",
-              "  padding-top: 4px;\n",
-              "  padding-bottom: 4px;\n",
-              "}\n",
-              "\n",
-              ".xr-section-inline-details {\n",
-              "  grid-column: 2 / -1;\n",
-              "}\n",
-              "\n",
-              ".xr-section-details {\n",
-              "  display: none;\n",
-              "  grid-column: 1 / -1;\n",
-              "  margin-bottom: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-              "  display: contents;\n",
-              "}\n",
-              "\n",
-              ".xr-array-wrap {\n",
-              "  grid-column: 1 / -1;\n",
-              "  display: grid;\n",
-              "  grid-template-columns: 20px auto;\n",
-              "}\n",
-              "\n",
-              ".xr-array-wrap > label {\n",
-              "  grid-column: 1;\n",
-              "  vertical-align: top;\n",
-              "}\n",
-              "\n",
-              ".xr-preview {\n",
-              "  color: var(--xr-font-color3);\n",
-              "}\n",
-              "\n",
-              ".xr-array-preview,\n",
-              ".xr-array-data {\n",
-              "  padding: 0 5px !important;\n",
-              "  grid-column: 2;\n",
-              "}\n",
-              "\n",
-              ".xr-array-data,\n",
-              ".xr-array-in:checked ~ .xr-array-preview {\n",
-              "  display: none;\n",
-              "}\n",
-              "\n",
-              ".xr-array-in:checked ~ .xr-array-data,\n",
-              ".xr-array-preview {\n",
-              "  display: inline-block;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list {\n",
-              "  display: inline-block !important;\n",
-              "  list-style: none;\n",
-              "  padding: 0 !important;\n",
-              "  margin: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list li {\n",
-              "  display: inline-block;\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list:before {\n",
-              "  content: \"(\";\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list:after {\n",
-              "  content: \")\";\n",
-              "}\n",
-              "\n",
-              ".xr-dim-list li:not(:last-child):after {\n",
-              "  content: \",\";\n",
-              "  padding-right: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-has-index {\n",
-              "  font-weight: bold;\n",
-              "}\n",
-              "\n",
-              ".xr-var-list,\n",
-              ".xr-var-item {\n",
-              "  display: contents;\n",
-              "}\n",
-              "\n",
-              ".xr-var-item > div,\n",
-              ".xr-var-item label,\n",
-              ".xr-var-item > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-even);\n",
-              "  margin-bottom: 0;\n",
-              "}\n",
-              "\n",
-              ".xr-var-item > .xr-var-name:hover span {\n",
-              "  padding-right: 5px;\n",
-              "}\n",
-              "\n",
-              ".xr-var-list > li:nth-child(odd) > div,\n",
-              ".xr-var-list > li:nth-child(odd) > label,\n",
-              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-              "  background-color: var(--xr-background-color-row-odd);\n",
-              "}\n",
-              "\n",
-              ".xr-var-name {\n",
-              "  grid-column: 1;\n",
-              "}\n",
-              "\n",
-              ".xr-var-dims {\n",
-              "  grid-column: 2;\n",
-              "}\n",
-              "\n",
-              ".xr-var-dtype {\n",
-              "  grid-column: 3;\n",
-              "  text-align: right;\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-var-preview {\n",
-              "  grid-column: 4;\n",
-              "}\n",
-              "\n",
-              ".xr-index-preview {\n",
-              "  grid-column: 2 / 5;\n",
-              "  color: var(--xr-font-color2);\n",
-              "}\n",
-              "\n",
-              ".xr-var-name,\n",
-              ".xr-var-dims,\n",
-              ".xr-var-dtype,\n",
-              ".xr-preview,\n",
-              ".xr-attrs dt {\n",
-              "  white-space: nowrap;\n",
-              "  overflow: hidden;\n",
-              "  text-overflow: ellipsis;\n",
-              "  padding-right: 10px;\n",
-              "}\n",
-              "\n",
-              ".xr-var-name:hover,\n",
-              ".xr-var-dims:hover,\n",
-              ".xr-var-dtype:hover,\n",
-              ".xr-attrs dt:hover {\n",
-              "  overflow: visible;\n",
-              "  width: auto;\n",
-              "  z-index: 1;\n",
-              "}\n",
-              "\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  display: none;\n",
-              "  background-color: var(--xr-background-color) !important;\n",
-              "  padding-bottom: 5px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-              ".xr-var-data-in:checked ~ .xr-var-data,\n",
-              ".xr-index-data-in:checked ~ .xr-index-data {\n",
-              "  display: block;\n",
-              "}\n",
-              "\n",
-              ".xr-var-data > table {\n",
-              "  float: right;\n",
-              "}\n",
-              "\n",
-              ".xr-var-name span,\n",
-              ".xr-var-data,\n",
-              ".xr-index-name div,\n",
-              ".xr-index-data,\n",
-              ".xr-attrs {\n",
-              "  padding-left: 25px !important;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs,\n",
-              ".xr-var-attrs,\n",
-              ".xr-var-data,\n",
-              ".xr-index-data {\n",
-              "  grid-column: 1 / -1;\n",
-              "}\n",
-              "\n",
-              "dl.xr-attrs {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  display: grid;\n",
-              "  grid-template-columns: 125px auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt,\n",
-              ".xr-attrs dd {\n",
-              "  padding: 0;\n",
-              "  margin: 0;\n",
-              "  float: left;\n",
-              "  padding-right: 10px;\n",
-              "  width: auto;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt {\n",
-              "  font-weight: normal;\n",
-              "  grid-column: 1;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dt:hover span {\n",
-              "  display: inline-block;\n",
-              "  background: var(--xr-background-color);\n",
-              "  padding-right: 10px;\n",
-              "}\n",
-              "\n",
-              ".xr-attrs dd {\n",
-              "  grid-column: 2;\n",
-              "  white-space: pre-wrap;\n",
-              "  word-break: break-all;\n",
-              "}\n",
-              "\n",
-              ".xr-icon-database,\n",
-              ".xr-icon-file-text2,\n",
-              ".xr-no-icon {\n",
-              "  display: inline-block;\n",
-              "  vertical-align: middle;\n",
-              "  width: 1em;\n",
-              "  height: 1.5em !important;\n",
-              "  stroke-width: 0;\n",
-              "  stroke: currentColor;\n",
-              "  fill: currentColor;\n",
-              "}\n",
-              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
-              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-              "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
-              "Coordinates:\n",
-              "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
-              "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
-              "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
-              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
-              "  * beam            (beam) int32 16B 1 2 3 4\n",
-              "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-              "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-              "  * q               (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-              "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
-              "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-              "Data variables: (12/38)\n",
-              "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
-              "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
-              "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
-              "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
-              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
-              "    ...              ...\n",
-              "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
-              "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-              "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
-              "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
-              "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
-              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
-              "Attributes: (12/41)\n",
-              "    fs:                        1\n",
-              "    n_bin:                     300\n",
-              "    n_fft:                     300\n",
-              "    description:               Binned averages calculated from ensembles of s...\n",
-              "    filehead_config:           {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;...\n",
-              "    inst_model:                Signature1000\n",
-              "    ...                        ...\n",
-              "    has_imu:                   1\n",
-              "    beam_angle:                25\n",
-              "    range_offset:              0.6\n",
-              "    declination:               15.8\n",
-              "    declination_in_orientmat:  1\n",
-              "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-40afcbec-82fa-4ea2-8864-207bc81a7a2f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-40afcbec-82fa-4ea2-8864-207bc81a7a2f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6a2d51fd-0c35-44ba-9e74-4c2f260aa17a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a2d51fd-0c35-44ba-9e74-4c2f260aa17a' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-8c6cc862-7bbd-406d-95d2-977701a314a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c6cc862-7bbd-406d-95d2-977701a314a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3388b96d-e832-465d-ba2d-8a2ee5e60b51' class='xr-var-data-in' type='checkbox'><label for='data-3388b96d-e832-465d-ba2d-8a2ee5e60b51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
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-              "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
-              "       &#x27;2020-08-15T01:02:30.001023769&#x27;, &#x27;2020-08-15T01:07:30.001024723&#x27;,\n",
-              "       &#x27;2020-08-15T01:12:30.001034259&#x27;, &#x27;2020-08-15T01:17:30.001035451&#x27;,\n",
-              "       &#x27;2020-08-15T01:22:30.001024961&#x27;, &#x27;2020-08-15T01:27:30.001025438&#x27;,\n",
-              "       &#x27;2020-08-15T01:32:30.001025676&#x27;, &#x27;2020-08-15T01:37:30.001031875&#x27;,\n",
-              "       &#x27;2020-08-15T01:42:30.001029014&#x27;, &#x27;2020-08-15T01:47:30.001030683&#x27;,\n",
-              "       &#x27;2020-08-15T01:52:30.001033067&#x27;, &#x27;2020-08-15T01:57:30.001029014&#x27;,\n",
-              "       &#x27;2020-08-15T02:02:30.001028299&#x27;, &#x27;2020-08-15T02:07:30.001020908&#x27;,\n",
-              "       &#x27;2020-08-15T02:12:30.001016378&#x27;, &#x27;2020-08-15T02:17:30.001012802&#x27;,\n",
-              "       &#x27;2020-08-15T02:22:30.001014709&#x27;, &#x27;2020-08-15T02:27:30.001018524&#x27;,\n",
-              "       &#x27;2020-08-15T02:32:30.001022577&#x27;, &#x27;2020-08-15T02:37:30.001020193&#x27;,\n",
-              "       &#x27;2020-08-15T02:42:30.001002311&#x27;, &#x27;2020-08-15T02:47:30.001003503&#x27;,\n",
-              "       &#x27;2020-08-15T02:52:30.001002550&#x27;, &#x27;2020-08-15T02:57:30.001000165&#x27;,\n",
-              "       &#x27;2020-08-15T03:02:30.001000642&#x27;, &#x27;2020-08-15T03:07:30.001000404&#x27;,\n",
-              "       &#x27;2020-08-15T03:12:30.000999450&#x27;, &#x27;2020-08-15T03:17:30.001003026&#x27;,\n",
-              "       &#x27;2020-08-15T03:22:30.001004695&#x27;, &#x27;2020-08-15T03:27:30.001004219&#x27;,\n",
-              "       &#x27;2020-08-15T03:32:30.001001834&#x27;, &#x27;2020-08-15T03:37:30.001005887&#x27;,\n",
-              "       &#x27;2020-08-15T03:42:30.001003742&#x27;, &#x27;2020-08-15T03:47:30.001000642&#x27;,\n",
-              "       &#x27;2020-08-15T03:52:30.001000404&#x27;, &#x27;2020-08-15T03:57:30.001001834&#x27;,\n",
-              "       &#x27;2020-08-15T04:02:30.001001834&#x27;, &#x27;2020-08-15T04:07:30.001001358&#x27;,\n",
-              "       &#x27;2020-08-15T04:12:30.001004695&#x27;, &#x27;2020-08-15T04:17:30.001001358&#x27;,\n",
-              "       &#x27;2020-08-15T04:22:30.001009464&#x27;, &#x27;2020-08-15T04:27:30.001006603&#x27;,\n",
-              "       &#x27;2020-08-15T04:32:30.001002550&#x27;, &#x27;2020-08-15T04:37:30.001004695&#x27;,\n",
-              "       &#x27;2020-08-15T04:42:30.001004934&#x27;, &#x27;2020-08-15T04:47:30.001004934&#x27;,\n",
-              "       &#x27;2020-08-15T04:52:30.001004457&#x27;, &#x27;2020-08-15T04:57:30.001002788&#x27;,\n",
-              "       &#x27;2020-08-15T05:02:30.001008749&#x27;, &#x27;2020-08-15T05:07:30.001017570&#x27;,\n",
-              "       &#x27;2020-08-15T05:12:30.001015186&#x27;, &#x27;2020-08-15T05:17:30.001005887&#x27;,\n",
-              "       &#x27;2020-08-15T05:22:30.001001358&#x27;, &#x27;2020-08-15T05:27:30.001011610&#x27;,\n",
-              "       &#x27;2020-08-15T05:32:30.001020431&#x27;, &#x27;2020-08-15T05:37:30.001011848&#x27;,\n",
-              "       &#x27;2020-08-15T05:42:30.001020908&#x27;, &#x27;2020-08-15T05:47:30.001013517&#x27;,\n",
-              "       &#x27;2020-08-15T05:52:30.001021146&#x27;, &#x27;2020-08-15T05:57:30.001010656&#x27;,\n",
-              "       &#x27;2020-08-15T06:02:30.001004219&#x27;, &#x27;2020-08-15T06:07:30.001012563&#x27;,\n",
-              "       &#x27;2020-08-15T06:12:30.001021862&#x27;, &#x27;2020-08-15T06:17:30.001018524&#x27;,\n",
-              "       &#x27;2020-08-15T06:22:30.001016139&#x27;, &#x27;2020-08-15T06:27:30.001016616&#x27;,\n",
-              "       &#x27;2020-08-15T06:32:30.001012325&#x27;, &#x27;2020-08-15T06:37:30.001016378&#x27;,\n",
-              "       &#x27;2020-08-15T06:42:30.001021862&#x27;, &#x27;2020-08-15T06:47:30.001023769&#x27;,\n",
-              "       &#x27;2020-08-15T06:52:30.001024007&#x27;, &#x27;2020-08-15T06:57:30.001014709&#x27;,\n",
-              "       &#x27;2020-08-15T07:02:30.001006126&#x27;, &#x27;2020-08-15T07:07:30.001019477&#x27;,\n",
-              "       &#x27;2020-08-15T07:12:30.001013994&#x27;, &#x27;2020-08-15T07:17:30.001016855&#x27;,\n",
-              "       &#x27;2020-08-15T07:22:30.001019239&#x27;, &#x27;2020-08-15T07:27:30.001024961&#x27;,\n",
-              "       &#x27;2020-08-15T07:32:30.001011610&#x27;, &#x27;2020-08-15T07:37:30.001024484&#x27;,\n",
-              "       &#x27;2020-08-15T07:42:30.001018524&#x27;, &#x27;2020-08-15T07:47:30.001029968&#x27;,\n",
-              "       &#x27;2020-08-15T07:52:30.001009464&#x27;, &#x27;2020-08-15T07:57:30.001014232&#x27;,\n",
-              "       &#x27;2020-08-15T08:02:30.001011610&#x27;, &#x27;2020-08-15T08:07:30.001028299&#x27;,\n",
-              "       &#x27;2020-08-15T08:12:30.001027107&#x27;, &#x27;2020-08-15T08:17:30.001024723&#x27;,\n",
-              "       &#x27;2020-08-15T08:22:30.001022577&#x27;, &#x27;2020-08-15T08:27:30.001018047&#x27;,\n",
-              "       &#x27;2020-08-15T08:32:30.001019477&#x27;, &#x27;2020-08-15T08:37:30.001017808&#x27;,\n",
-              "       &#x27;2020-08-15T08:42:30.001018762&#x27;, &#x27;2020-08-15T08:47:30.001015186&#x27;,\n",
-              "       &#x27;2020-08-15T08:52:30.001020431&#x27;, &#x27;2020-08-15T08:57:30.001026630&#x27;,\n",
-              "       &#x27;2020-08-15T09:02:30.001021146&#x27;, &#x27;2020-08-15T09:07:30.001016378&#x27;,\n",
-              "       &#x27;2020-08-15T09:12:30.001025676&#x27;, &#x27;2020-08-15T09:17:30.001024246&#x27;,\n",
-              "       &#x27;2020-08-15T09:22:30.001026630&#x27;, &#x27;2020-08-15T09:27:30.001017570&#x27;,\n",
-              "       &#x27;2020-08-15T09:32:30.001015901&#x27;, &#x27;2020-08-15T09:37:30.001016139&#x27;,\n",
-              "       &#x27;2020-08-15T09:42:30.001018762&#x27;, &#x27;2020-08-15T09:47:30.001014709&#x27;,\n",
-              "       &#x27;2020-08-15T09:52:30.001016378&#x27;, &#x27;2020-08-15T09:57:30.001024961&#x27;,\n",
-              "       &#x27;2020-08-15T10:02:30.001021146&#x27;, &#x27;2020-08-15T10:07:30.001022100&#x27;,\n",
-              "       &#x27;2020-08-15T10:12:30.001017808&#x27;, &#x27;2020-08-15T10:17:30.001013994&#x27;,\n",
-              "       &#x27;2020-08-15T10:22:30.001018762&#x27;, &#x27;2020-08-15T10:27:30.001021385&#x27;,\n",
-              "       &#x27;2020-08-15T10:32:30.001016855&#x27;, &#x27;2020-08-15T10:37:30.001021385&#x27;,\n",
-              "       &#x27;2020-08-15T10:42:30.001015186&#x27;, &#x27;2020-08-15T10:47:30.001020193&#x27;,\n",
-              "       &#x27;2020-08-15T10:52:30.001021623&#x27;, &#x27;2020-08-15T10:57:30.001021862&#x27;,\n",
-              "       &#x27;2020-08-15T11:02:30.001018047&#x27;, &#x27;2020-08-15T11:07:30.001021146&#x27;,\n",
-              "       &#x27;2020-08-15T11:12:30.001011848&#x27;, &#x27;2020-08-15T11:17:30.001015901&#x27;,\n",
-              "       &#x27;2020-08-15T11:22:30.001014232&#x27;, &#x27;2020-08-15T11:27:30.001015663&#x27;,\n",
-              "       &#x27;2020-08-15T11:32:30.001012325&#x27;, &#x27;2020-08-15T11:37:30.001004457&#x27;,\n",
-              "       &#x27;2020-08-15T11:42:30.001018524&#x27;, &#x27;2020-08-15T11:47:30.001023292&#x27;,\n",
-              "       &#x27;2020-08-15T11:52:30.001009464&#x27;, &#x27;2020-08-15T11:57:30.001002311&#x27;,\n",
-              "       &#x27;2020-08-15T12:02:30.001004695&#x27;, &#x27;2020-08-15T12:07:30.001007556&#x27;,\n",
-              "       &#x27;2020-08-15T12:12:30.001012086&#x27;, &#x27;2020-08-15T12:17:30.001007080&#x27;,\n",
-              "       &#x27;2020-08-15T12:22:30.001011371&#x27;, &#x27;2020-08-15T12:27:30.001014471&#x27;,\n",
-              "       &#x27;2020-08-15T12:32:30.001016378&#x27;, &#x27;2020-08-15T12:37:30.001012563&#x27;,\n",
-              "       &#x27;2020-08-15T12:42:30.001015901&#x27;, &#x27;2020-08-15T12:47:30.001010417&#x27;,\n",
-              "       &#x27;2020-08-15T12:52:30.001009464&#x27;, &#x27;2020-08-15T12:57:30.001010894&#x27;,\n",
-              "       &#x27;2020-08-15T13:02:30.001016855&#x27;, &#x27;2020-08-15T13:07:30.001020908&#x27;,\n",
-              "       &#x27;2020-08-15T13:12:30.001018762&#x27;, &#x27;2020-08-15T13:17:30.001018762&#x27;,\n",
-              "       &#x27;2020-08-15T13:22:30.001018047&#x27;, &#x27;2020-08-15T13:27:30.001013517&#x27;,\n",
-              "       &#x27;2020-08-15T13:32:30.001015424&#x27;, &#x27;2020-08-15T13:37:30.001009225&#x27;,\n",
-              "       &#x27;2020-08-15T13:42:30.001011133&#x27;, &#x27;2020-08-15T13:47:30.001008749&#x27;,\n",
-              "       &#x27;2020-08-15T13:52:30.001019477&#x27;, &#x27;2020-08-15T13:57:30.001022338&#x27;,\n",
-              "       &#x27;2020-08-15T14:02:30.001019716&#x27;, &#x27;2020-08-15T14:07:30.001026868&#x27;,\n",
-              "       &#x27;2020-08-15T14:12:30.001021623&#x27;, &#x27;2020-08-15T14:17:30.001034021&#x27;,\n",
-              "       &#x27;2020-08-15T14:22:30.001024961&#x27;, &#x27;2020-08-15T14:27:30.001032352&#x27;,\n",
-              "       &#x27;2020-08-15T14:32:30.001023292&#x27;, &#x27;2020-08-15T14:37:30.001024484&#x27;,\n",
-              "       &#x27;2020-08-15T14:42:30.001044034&#x27;, &#x27;2020-08-15T14:47:30.001032352&#x27;,\n",
-              "       &#x27;2020-08-15T14:52:30.001019239&#x27;, &#x27;2020-08-15T14:57:30.001032829&#x27;,\n",
-              "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
-              "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
-              "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
-              "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-d4114ee4-4fd2-4656-a755-e1677ad95cbf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4114ee4-4fd2-4656-a755-e1677ad95cbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07f9c86c-b27f-44bc-a342-95d51837989d' class='xr-var-data-in' type='checkbox'><label for='data-07f9c86c-b27f-44bc-a342-95d51837989d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-3ff426e7-7498-47ac-b74d-288024071044' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ff426e7-7498-47ac-b74d-288024071044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea33e978-7438-4f80-9375-612b056787b0' class='xr-var-data-in' type='checkbox'><label for='data-ea33e978-7438-4f80-9375-612b056787b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-358893ed-0b0c-41bf-8c7c-493855cc2ee4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-358893ed-0b0c-41bf-8c7c-493855cc2ee4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da36c9fa-4417-4a9b-8660-d95c849a25e7' class='xr-var-data-in' type='checkbox'><label for='data-da36c9fa-4417-4a9b-8660-d95c849a25e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3e6e203d-6844-430c-817a-055331cd2e13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e6e203d-6844-430c-817a-055331cd2e13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-834b2c68-401c-4879-bae7-bfd0f58002ba' class='xr-var-data-in' type='checkbox'><label for='data-834b2c68-401c-4879-bae7-bfd0f58002ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-24652350-689b-4f90-91ca-12b788f20e20' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24652350-689b-4f90-91ca-12b788f20e20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5585fda-1e78-4e83-a0e6-3c5a5eda53be' class='xr-var-data-in' type='checkbox'><label for='data-c5585fda-1e78-4e83-a0e6-3c5a5eda53be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-f0203aca-7838-436a-88d3-fe64978fe082' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0203aca-7838-436a-88d3-fe64978fe082' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d33f4c6b-3f93-4b82-97ce-4cd4e91aebd8' class='xr-var-data-in' type='checkbox'><label for='data-d33f4c6b-3f93-4b82-97ce-4cd4e91aebd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-9a254a54-000c-4a40-8c99-d7d9d1ebf2a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a254a54-000c-4a40-8c99-d7d9d1ebf2a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed47564f-b71a-4934-b7ae-18f156b1af82' class='xr-var-data-in' type='checkbox'><label for='data-ed47564f-b71a-4934-b7ae-18f156b1af82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-0f8d92ee-d75c-4067-96be-8ccf57a9b599' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f8d92ee-d75c-4067-96be-8ccf57a9b599' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8ee951d-8ed4-4b8a-8d8d-cdc25ea61095' class='xr-var-data-in' type='checkbox'><label for='data-d8ee951d-8ed4-4b8a-8d8d-cdc25ea61095' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
-              "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
-              "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
-              "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T01:02:29.938493013&#x27;, &#x27;2020-08-15T01:07:29.938492536&#x27;,\n",
-              "       &#x27;2020-08-15T01:12:29.938490867&#x27;, &#x27;2020-08-15T01:17:29.938497781&#x27;,\n",
-              "       &#x27;2020-08-15T01:22:29.938496112&#x27;, &#x27;2020-08-15T01:27:29.938498497&#x27;,\n",
-              "       &#x27;2020-08-15T01:32:29.938496589&#x27;, &#x27;2020-08-15T01:37:29.938497781&#x27;,\n",
-              "       &#x27;2020-08-15T01:42:29.938495635&#x27;, &#x27;2020-08-15T01:47:29.938497066&#x27;,\n",
-              "       &#x27;2020-08-15T01:52:29.938498735&#x27;, &#x27;2020-08-15T01:57:29.938496112&#x27;,\n",
-              "       &#x27;2020-08-15T02:02:29.938496589&#x27;, &#x27;2020-08-15T02:07:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T02:12:29.938497304&#x27;, &#x27;2020-08-15T02:17:29.938496828&#x27;,\n",
-              "       &#x27;2020-08-15T02:22:29.938496112&#x27;, &#x27;2020-08-15T02:27:29.938496828&#x27;,\n",
-              "       &#x27;2020-08-15T02:32:29.938496112&#x27;, &#x27;2020-08-15T02:37:29.938497304&#x27;,\n",
-              "       &#x27;2020-08-15T02:42:29.938495159&#x27;, &#x27;2020-08-15T02:47:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T02:52:29.938490867&#x27;, &#x27;2020-08-15T02:57:29.938492059&#x27;,\n",
-              "       &#x27;2020-08-15T03:02:29.938489675&#x27;, &#x27;2020-08-15T03:07:29.938488245&#x27;,\n",
-              "       &#x27;2020-08-15T03:12:29.938485622&#x27;, &#x27;2020-08-15T03:17:29.938485622&#x27;,\n",
-              "       &#x27;2020-08-15T03:22:29.938488245&#x27;, &#x27;2020-08-15T03:27:29.938485145&#x27;,\n",
-              "       &#x27;2020-08-15T03:32:29.938486099&#x27;, &#x27;2020-08-15T03:37:29.938482046&#x27;,\n",
-              "       &#x27;2020-08-15T03:42:29.938489437&#x27;, &#x27;2020-08-15T03:47:29.938489437&#x27;,\n",
-              "       &#x27;2020-08-15T03:52:29.938485860&#x27;, &#x27;2020-08-15T03:57:29.938491582&#x27;,\n",
-              "       &#x27;2020-08-15T04:02:29.938488006&#x27;, &#x27;2020-08-15T04:07:29.938491106&#x27;,\n",
-              "       &#x27;2020-08-15T04:12:29.938492059&#x27;, &#x27;2020-08-15T04:17:29.938487052&#x27;,\n",
-              "       &#x27;2020-08-15T04:22:29.938489675&#x27;, &#x27;2020-08-15T04:27:29.938491582&#x27;,\n",
-              "       &#x27;2020-08-15T04:32:29.938491106&#x27;, &#x27;2020-08-15T04:37:29.938493251&#x27;,\n",
-              "       &#x27;2020-08-15T04:42:29.938489675&#x27;, &#x27;2020-08-15T04:47:29.938492059&#x27;,\n",
-              "       &#x27;2020-08-15T04:52:29.938491582&#x27;, &#x27;2020-08-15T04:57:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T05:02:29.938491106&#x27;, &#x27;2020-08-15T05:07:29.938499212&#x27;,\n",
-              "       &#x27;2020-08-15T05:12:29.938491821&#x27;, &#x27;2020-08-15T05:17:29.938493490&#x27;,\n",
-              "       &#x27;2020-08-15T05:22:29.938495397&#x27;, &#x27;2020-08-15T05:27:29.938490390&#x27;,\n",
-              "       &#x27;2020-08-15T05:32:29.938493967&#x27;, &#x27;2020-08-15T05:37:29.938493728&#x27;,\n",
-              "       &#x27;2020-08-15T05:42:29.938491582&#x27;, &#x27;2020-08-15T05:47:29.938493013&#x27;,\n",
-              "       &#x27;2020-08-15T05:52:29.938495159&#x27;, &#x27;2020-08-15T05:57:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T06:02:29.938493013&#x27;, &#x27;2020-08-15T06:07:29.938496589&#x27;,\n",
-              "       &#x27;2020-08-15T06:12:29.938494920&#x27;, &#x27;2020-08-15T06:17:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T06:22:29.938493728&#x27;, &#x27;2020-08-15T06:27:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T06:32:29.938492536&#x27;, &#x27;2020-08-15T06:37:29.938495159&#x27;,\n",
-              "       &#x27;2020-08-15T06:42:29.938496112&#x27;, &#x27;2020-08-15T06:47:29.938497304&#x27;,\n",
-              "       &#x27;2020-08-15T06:52:29.938496112&#x27;, &#x27;2020-08-15T06:57:29.938493728&#x27;,\n",
-              "       &#x27;2020-08-15T07:02:29.938497304&#x27;, &#x27;2020-08-15T07:07:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T07:12:29.938492059&#x27;, &#x27;2020-08-15T07:17:29.938493490&#x27;,\n",
-              "       &#x27;2020-08-15T07:22:29.938493967&#x27;, &#x27;2020-08-15T07:27:29.938497304&#x27;,\n",
-              "       &#x27;2020-08-15T07:32:29.938494443&#x27;, &#x27;2020-08-15T07:37:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T07:42:29.938495635&#x27;, &#x27;2020-08-15T07:47:29.938493967&#x27;,\n",
-              "       &#x27;2020-08-15T07:52:29.938492298&#x27;, &#x27;2020-08-15T07:57:29.938489675&#x27;,\n",
-              "       &#x27;2020-08-15T08:02:29.938493013&#x27;, &#x27;2020-08-15T08:07:29.938493728&#x27;,\n",
-              "       &#x27;2020-08-15T08:12:29.938497066&#x27;, &#x27;2020-08-15T08:17:29.938497781&#x27;,\n",
-              "       &#x27;2020-08-15T08:22:29.938495159&#x27;, &#x27;2020-08-15T08:27:29.938492774&#x27;,\n",
-              "       &#x27;2020-08-15T08:32:29.938495397&#x27;, &#x27;2020-08-15T08:37:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T08:42:29.938494920&#x27;, &#x27;2020-08-15T08:47:29.938494682&#x27;,\n",
-              "       &#x27;2020-08-15T08:52:29.938494443&#x27;, &#x27;2020-08-15T08:57:29.938491821&#x27;,\n",
-              "       &#x27;2020-08-15T09:02:29.938497066&#x27;, &#x27;2020-08-15T09:07:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T09:12:29.938495397&#x27;, &#x27;2020-08-15T09:17:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T09:22:29.938498020&#x27;, &#x27;2020-08-15T09:27:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T09:32:29.938495159&#x27;, &#x27;2020-08-15T09:37:29.938498735&#x27;,\n",
-              "       &#x27;2020-08-15T09:42:29.938493728&#x27;, &#x27;2020-08-15T09:47:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T09:52:29.938500642&#x27;, &#x27;2020-08-15T09:57:29.938496589&#x27;,\n",
-              "       &#x27;2020-08-15T10:02:29.938497781&#x27;, &#x27;2020-08-15T10:07:29.938500881&#x27;,\n",
-              "       &#x27;2020-08-15T10:12:29.938504457&#x27;, &#x27;2020-08-15T10:17:29.938501358&#x27;,\n",
-              "       &#x27;2020-08-15T10:22:29.938507556&#x27;, &#x27;2020-08-15T10:27:29.938496112&#x27;,\n",
-              "       &#x27;2020-08-15T10:32:29.938495635&#x27;, &#x27;2020-08-15T10:37:29.938500165&#x27;,\n",
-              "       &#x27;2020-08-15T10:42:29.938496112&#x27;, &#x27;2020-08-15T10:47:29.938493251&#x27;,\n",
-              "       &#x27;2020-08-15T10:52:29.938493728&#x27;, &#x27;2020-08-15T10:57:29.938492536&#x27;,\n",
-              "       &#x27;2020-08-15T11:02:29.938492774&#x27;, &#x27;2020-08-15T11:07:29.938492774&#x27;,\n",
-              "       &#x27;2020-08-15T11:12:29.938493967&#x27;, &#x27;2020-08-15T11:17:29.938494443&#x27;,\n",
-              "       &#x27;2020-08-15T11:22:29.938496589&#x27;, &#x27;2020-08-15T11:27:29.938496112&#x27;,\n",
-              "       &#x27;2020-08-15T11:32:29.938495397&#x27;, &#x27;2020-08-15T11:37:29.938493967&#x27;,\n",
-              "       &#x27;2020-08-15T11:42:29.938493013&#x27;, &#x27;2020-08-15T11:47:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T11:52:29.938493967&#x27;, &#x27;2020-08-15T11:57:29.938498735&#x27;,\n",
-              "       &#x27;2020-08-15T12:02:29.938496589&#x27;, &#x27;2020-08-15T12:07:29.938498020&#x27;,\n",
-              "       &#x27;2020-08-15T12:12:29.938494443&#x27;, &#x27;2020-08-15T12:17:29.938495159&#x27;,\n",
-              "       &#x27;2020-08-15T12:22:29.938495635&#x27;, &#x27;2020-08-15T12:27:29.938497066&#x27;,\n",
-              "       &#x27;2020-08-15T12:32:29.938493967&#x27;, &#x27;2020-08-15T12:37:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T12:42:29.938496112&#x27;, &#x27;2020-08-15T12:47:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T12:52:29.938494443&#x27;, &#x27;2020-08-15T12:57:29.938496589&#x27;,\n",
-              "       &#x27;2020-08-15T13:02:29.938494205&#x27;, &#x27;2020-08-15T13:07:29.938494205&#x27;,\n",
-              "       &#x27;2020-08-15T13:12:29.938492536&#x27;, &#x27;2020-08-15T13:17:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T13:22:29.938493251&#x27;, &#x27;2020-08-15T13:27:29.938495397&#x27;,\n",
-              "       &#x27;2020-08-15T13:32:29.938494920&#x27;, &#x27;2020-08-15T13:37:29.938497066&#x27;,\n",
-              "       &#x27;2020-08-15T13:42:29.938497304&#x27;, &#x27;2020-08-15T13:47:29.938494920&#x27;,\n",
-              "       &#x27;2020-08-15T13:52:29.938493490&#x27;, &#x27;2020-08-15T13:57:29.938492774&#x27;,\n",
-              "       &#x27;2020-08-15T14:02:29.938496112&#x27;, &#x27;2020-08-15T14:07:29.938489675&#x27;,\n",
-              "       &#x27;2020-08-15T14:12:29.938489913&#x27;, &#x27;2020-08-15T14:17:29.938494443&#x27;,\n",
-              "       &#x27;2020-08-15T14:22:29.938495397&#x27;, &#x27;2020-08-15T14:27:29.938492774&#x27;,\n",
-              "       &#x27;2020-08-15T14:32:29.938491582&#x27;, &#x27;2020-08-15T14:37:29.938493251&#x27;,\n",
-              "       &#x27;2020-08-15T14:42:29.938492536&#x27;, &#x27;2020-08-15T14:47:29.938492774&#x27;,\n",
-              "       &#x27;2020-08-15T14:52:29.938491106&#x27;, &#x27;2020-08-15T14:57:29.938495635&#x27;,\n",
-              "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
-              "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
-              "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
-              "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-d5375742-8ba6-436b-b6d3-12a79f5c02df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5375742-8ba6-436b-b6d3-12a79f5c02df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5dcd2ea-cf12-4db4-bf1d-7f1fc9630097' class='xr-var-data-in' type='checkbox'><label for='data-d5dcd2ea-cf12-4db4-bf1d-7f1fc9630097' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a932f57a-5d21-4646-bc9d-3c6f245535a4' class='xr-section-summary-in' type='checkbox'  ><label for='section-a932f57a-5d21-4646-bc9d-3c6f245535a4' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-0e9bf684-5b1f-4b1f-b9bd-c62e5914a05e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e9bf684-5b1f-4b1f-b9bd-c62e5914a05e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a887c99f-97d9-4fcf-a09d-d5a3c45c3342' class='xr-var-data-in' type='checkbox'><label for='data-a887c99f-97d9-4fcf-a09d-d5a3c45c3342' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
-              "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
-              "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
-              "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
-              "       1500.6763, 1500.2716, 1500.1096, 1499.8009, 1499.5637, 1499.3373,\n",
-              "       1499.2163, 1499.0955, 1498.9806, 1498.8579, 1498.7637, 1498.6821,\n",
-              "       1498.6133, 1498.5066, 1498.5637, 1498.7421, 1498.8367, 1498.984 ,\n",
-              "       1498.9717, 1498.9644, 1499.0553, 1499.21  , 1499.2789, 1499.2766,\n",
-              "       1499.265 , 1499.2623, 1499.3181, 1499.2903, 1499.3444, 1499.2922,\n",
-              "       1499.2983, 1499.195 , 1499.2087, 1499.212 , 1499.2494, 1499.2227,\n",
-              "       1499.1742, 1499.1772, 1499.1937, 1499.2306, 1499.2719, 1499.3043,\n",
-              "       1499.4073, 1499.3677, 1499.4554, 1499.5647, 1499.6683, 1499.7489,\n",
-              "       1499.8341, 1499.8446, 1499.8396, 1499.9257, 1499.781 , 1499.8274,\n",
-              "       1499.7506, 1499.8904, 1499.7473, 1499.7411, 1499.7415, 1499.7079,\n",
-              "       1499.508 , 1499.7562, 1499.5327, 1499.4186, 1499.4877, 1499.1946,\n",
-              "       1499.1821, 1499.466 , 1499.5144, 1499.7024, 1499.8877, 1499.8373,\n",
-              "       1499.8597, 1500.1703, 1500.0886, 1500.082 , 1500.0476, 1499.9003,\n",
-              "       1499.8434, 1498.8927, 1497.6433, 1496.299 , 1495.386 , 1495.2273,\n",
-              "       1494.9376, 1494.7117, 1494.9341, 1495.1063, 1495.0103, 1494.7747,\n",
-              "       1494.5977, 1494.4548, 1494.4042, 1494.3356, 1494.229 , 1494.0669,\n",
-              "       1493.7662, 1493.4755, 1493.3303, 1493.1544, 1492.8477, 1492.7877,\n",
-              "       1492.8064, 1493.0189, 1493.5558, 1494.0146, 1494.7506, 1495.2681,\n",
-              "       1496.2244, 1496.8036, 1497.5472, 1498.0507, 1498.3839, 1498.663 ,\n",
-              "       1498.8971, 1499.136 , 1499.3384, 1499.535 , 1499.5739, 1499.5245,\n",
-              "       1499.4437, 1499.4467, 1499.5509, 1499.6014, 1499.5997, 1499.5935,\n",
-              "       1499.525 , 1499.4967, 1499.4364, 1499.4977, 1499.503 , 1499.5526,\n",
-              "       1499.5083, 1499.5023, 1499.474 , 1499.4028, 1499.436 , 1499.4973,\n",
-              "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
-              "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
-              "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
-              "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-e389d35a-f683-44a6-99bd-93380cd821b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e389d35a-f683-44a6-99bd-93380cd821b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a25e171-6518-412c-9a9c-35b718000676' class='xr-var-data-in' type='checkbox'><label for='data-9a25e171-6518-412c-9a9c-35b718000676' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
-              "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
-              "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
-              "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
-              "       14.572268 , 14.502767 , 14.376032 , 14.268402 , 14.178566 ,\n",
-              "       14.055    , 14.005532 , 13.911533 , 13.838566 , 13.7688675,\n",
-              "       13.7339325, 13.696598 , 13.661633 , 13.626367 , 13.597433 ,\n",
-              "       13.572568 , 13.552067 , 13.520534 , 13.538133 , 13.592899 ,\n",
-              "       13.620734 , 13.665668 , 13.661699 , 13.658334 , 13.686766 ,\n",
-              "       13.7354   , 13.754033 , 13.754901 , 13.7525   , 13.751934 ,\n",
-              "       13.767399 , 13.760633 , 13.776802 , 13.761433 , 13.7625   ,\n",
-              "       13.731066 , 13.7371   , 13.737367 , 13.748701 , 13.741634 ,\n",
-              "       13.726335 , 13.726666 , 13.7323   , 13.743701 , 13.756766 ,\n",
-              "       13.766968 , 13.797334 , 13.7852   , 13.812601 , 13.847366 ,\n",
-              "       13.878734 , 13.903067 , 13.928333 , 13.931099 , 13.930567 ,\n",
-              "       13.957533 , 13.912533 , 13.9264   , 13.9032   , 13.947433 ,\n",
-              "       13.902601 , 13.900833 , 13.900665 , 13.890833 , 13.830032 ,\n",
-              "       13.9046335, 13.8364   , 13.801933 , 13.8241   , 13.735    ,\n",
-              "       13.732666 , 13.818233 , 13.8298   , 13.888301 , 13.944167 ,\n",
-              "       13.928867 , 13.9361   , 14.0331   , 14.008999 , 14.006901 ,\n",
-              "       13.992832 , 13.946533 , 13.9282   , 13.643267 , 13.266466 ,\n",
-              "       12.865967 , 12.595367 , 12.5469   , 12.462267 , 12.3959   ,\n",
-              "       12.461133 , 12.512366 , 12.482166 , 12.411167 , 12.3605995,\n",
-              "       12.3201   , 12.303568 , 12.284267 , 12.252732 , 12.203699 ,\n",
-              "       12.118533 , 12.031001 , 11.988433 , 11.939434 , 11.8505   ,\n",
-              "       11.8341   , 11.837234 , 11.8984995, 12.0561   , 12.189    ,\n",
-              "       12.403767 , 12.5546   , 12.837867 , 13.010934 , 13.233933 ,\n",
-              "       13.384068 , 13.485199 , 13.565999 , 13.639567 , 13.711732 ,\n",
-              "       13.774034 , 13.829665 , 13.838365 , 13.829668 , 13.8013   ,\n",
-              "       13.805167 , 13.833833 , 13.855499 , 13.857698 , 13.844232 ,\n",
-              "       13.831333 , 13.816167 , 13.802168 , 13.811266 , 13.820599 ,\n",
-              "       13.834399 , 13.828466 , 13.826566 , 13.810034 , 13.792601 ,\n",
-              "       13.800402 , 13.820232 , 13.830032 , 13.8446665, 13.8607   ,\n",
-              "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
-              "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
-              "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
-              "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-2a458a4b-e91c-4f24-9662-4a6f05dc33e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a458a4b-e91c-4f24-9662-4a6f05dc33e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-455ce3f4-c117-4153-b79f-fd02f0721f52' class='xr-var-data-in' type='checkbox'><label for='data-455ce3f4-c117-4153-b79f-fd02f0721f52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
-              "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
-              "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
-              "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
-              "       9.218047 , 9.186557 , 9.157551 , 9.123754 , 9.09348  , 9.059697 ,\n",
-              "       9.026804 , 8.994499 , 8.95571  , 8.92198  , 8.886473 , 8.853367 ,\n",
-              "       8.813594 , 8.782229 , 8.74448  , 8.708926 , 8.674907 , 8.637604 ,\n",
-              "       8.602573 , 8.560874 , 8.524677 , 8.48187  , 8.4449835, 8.400766 ,\n",
-              "       8.365373 , 8.322662 , 8.28713  , 8.248011 , 8.21333  , 8.178404 ,\n",
-              "       8.14623  , 8.109827 , 8.072543 , 8.039574 , 7.9980125, 7.963136 ,\n",
-              "       7.926347 , 7.8918767, 7.8531103, 7.824253 , 7.7964296, 7.7649107,\n",
-              "       7.7383432, 7.7130632, 7.6841335, 7.65858  , 7.633538 , 7.609003 ,\n",
-              "       7.592057 , 7.573613 , 7.5537395, 7.533187 , 7.5146875, 7.497063 ,\n",
-              "       7.48256  , 7.472039 , 7.454433 , 7.4437304, 7.4306965, 7.422947 ,\n",
-              "       7.4138427, 7.4127507, 7.407543 , 7.4021435, 7.40189  , 7.4006333,\n",
-              "       7.401152 , 7.3961263, 7.4010367, 7.4031525, 7.414211 , 7.4199567,\n",
-              "       7.4243903, 7.4346695, 7.4523306, 7.4677606, 7.47785  , 7.4955306,\n",
-              "       7.507134 , 7.52034  , 7.540297 , 7.5592594, 7.583973 , 7.6029363,\n",
-              "       7.623276 , 7.6508303, 7.67267  , 7.6968994, 7.7202635, 7.7465167,\n",
-              "       7.7706933, 7.795326 , 7.820833 , 7.8509097, 7.8781033, 7.9117236,\n",
-              "       7.9442267, 7.9752865, 8.007596 , 8.042522 , 8.077546 , 8.108029 ,\n",
-              "       8.1417265, 8.17497  , 8.210143 , 8.243827 , 8.281553 , 8.317181 ,\n",
-              "       8.35565  , 8.390187 , 8.42794  , 8.465797 , 8.50642  , 8.54146  ,\n",
-              "       8.581511 , 8.618688 , 8.65223  , 8.69048  , 8.72701  , 8.758973 ,\n",
-              "       8.795943 , 8.832204 , 8.870703 , 8.8993225, 8.936847 , 8.969017 ,\n",
-              "       9.001257 , 9.036253 , 9.063161 , 9.095617 , 9.1287565, 9.157017 ,\n",
-              "       9.187741 , 9.216694 , 9.244237 , 9.274386 , 9.300383 , 9.32181  ,\n",
-              "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
-              "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
-              "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
-              "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-6675907a-764b-4c6d-9b2b-1bfce60030a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6675907a-764b-4c6d-9b2b-1bfce60030a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f35fda8-28ce-4760-a49c-abf3e3fe2445' class='xr-var-data-in' type='checkbox'><label for='data-7f35fda8-28ce-4760-a49c-abf3e3fe2445' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
-              "         3.60746217e+00,  3.56795740e+00,  3.58543777e+00,\n",
-              "         3.56357908e+00,  3.57667398e+00,  3.60632110e+00,\n",
-              "         3.56949067e+00,  3.57479167e+00,  3.59876704e+00,\n",
-              "         3.60281253e+00,  3.59981132e+00,  3.59064198e+00,\n",
-              "         3.59985065e+00,  3.58579111e+00,  3.57373047e+00,\n",
-              "         3.56544852e+00,  3.58114982e+00,  3.58714032e+00,\n",
-              "         3.55944085e+00,  3.58880138e+00,  3.53171992e+00,\n",
-              "         3.53358531e+00,  3.49057865e+00,  3.49481201e+00,\n",
-              "         3.49612260e+00,  3.45677161e+00,  3.42318940e+00,\n",
-              "         3.46062589e+00,  3.41326380e+00,  3.41770315e+00,\n",
-              "         3.41921234e+00,  3.43796873e+00,  3.42292237e+00,\n",
-              "         3.41392589e+00,  3.38415337e+00,  3.38218069e+00,\n",
-              "         3.43648434e+00,  3.38592434e+00,  3.34218621e+00,\n",
-              "         3.38532996e+00,  3.37350154e+00,  3.37754154e+00,\n",
-              "         3.35902476e+00,  3.34339881e+00,  3.35676146e+00,\n",
-              "         3.35692763e+00,  3.32560086e+00,  3.27195191e+00,\n",
-              "         3.19083190e+00,  2.95882225e+00,  2.40057945e+00,\n",
-              "         2.16090226e+00,  1.92318320e+00,  1.78795314e+00,\n",
-              "         1.62216699e+00,  1.56376326e+00,  1.46418226e+00,\n",
-              "...\n",
-              "        -1.96982498e+02, -1.97061203e+02, -1.96969849e+02,\n",
-              "        -1.97076538e+02, -1.97007187e+02, -1.97028168e+02,\n",
-              "        -1.97006195e+02, -1.97027512e+02, -1.97029175e+02,\n",
-              "        -1.96980515e+02, -1.97019150e+02, -1.96939850e+02,\n",
-              "        -1.96979843e+02, -1.97032181e+02, -1.97038193e+02,\n",
-              "        -1.96942871e+02, -1.96959534e+02, -1.96986191e+02,\n",
-              "        -1.97056839e+02, -1.97049850e+02, -1.97026855e+02,\n",
-              "        -1.97041199e+02, -1.97016525e+02, -1.97084503e+02,\n",
-              "        -1.97077499e+02, -1.97032166e+02, -1.97061508e+02,\n",
-              "        -1.97079834e+02, -1.97101852e+02, -1.97092865e+02,\n",
-              "        -1.97062164e+02, -1.97118851e+02, -1.97044510e+02,\n",
-              "        -1.97032166e+02, -1.97112183e+02, -1.96995499e+02,\n",
-              "        -1.97103195e+02, -1.97131195e+02, -1.97147202e+02,\n",
-              "        -1.97079849e+02, -1.97053513e+02, -1.97125504e+02,\n",
-              "        -1.97132843e+02, -1.97114838e+02, -1.97074829e+02,\n",
-              "        -1.97085831e+02, -1.97115845e+02, -1.97091156e+02,\n",
-              "        -1.97044174e+02, -1.97063873e+02, -1.97090515e+02,\n",
-              "        -1.97129501e+02, -1.97007523e+02, -1.97017838e+02,\n",
-              "        -1.97019165e+02, -1.97129166e+02, -1.97051849e+02,\n",
-              "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-5660f62f-4bc7-4437-9336-fc2125a12873' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5660f62f-4bc7-4437-9336-fc2125a12873' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae198a49-8e0c-43e2-84cf-05b46db4c47b' class='xr-var-data-in' type='checkbox'><label for='data-ae198a49-8e0c-43e2-84cf-05b46db4c47b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
-              "        -1.2613868 , -1.2610568 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
-              "        -1.2618904 , -1.258823  , -1.2596216 , -1.258702  , -1.2583325 ,\n",
-              "        -1.2578007 , -1.2583394 , -1.2576339 , -1.2579147 , -1.2534361 ,\n",
-              "        -1.2568558 , -1.2559422 , -1.2557042 , -1.2571892 , -1.2556211 ,\n",
-              "        -1.2540294 , -1.2548382 , -1.2532483 , -1.2525105 , -1.2511989 ,\n",
-              "        -1.2522614 , -1.2561746 , -1.2530836 , -1.2531874 , -1.2519903 ,\n",
-              "        -1.2518218 , -1.2511966 , -1.2544034 , -1.2561861 , -1.2536184 ,\n",
-              "        -1.2504781 , -1.2535783 , -1.2560768 , -1.2559297 , -1.257113  ,\n",
-              "        -1.2519604 , -1.2501055 , -1.2515699 , -1.2483989 , -1.2508361 ,\n",
-              "        -1.2479837 , -1.2430646 , -1.2314413 , -1.2083213 , -1.1935245 ,\n",
-              "        -1.1852744 , -1.1747023 , -1.1735051 , -1.1686733 , -1.1616861 ,\n",
-              "        -1.1579937 , -1.1570411 , -1.1541711 , -1.1540251 , -1.1536013 ,\n",
-              "        -1.1516274 , -1.147889  , -1.1449583 , -1.1449729 , -1.14322   ,\n",
-              "        -1.1418625 , -1.1392603 , -1.1384715 , -1.136121  , -1.1344364 ,\n",
-              "        -1.132704  , -1.1329331 , -1.1329101 , -1.130972  , -1.1331373 ,\n",
-              "        -1.1304799 , -1.1283726 , -1.1294136 , -1.132449  , -1.1283008 ,\n",
-              "        -1.1297874 , -1.1291262 , -1.1277461 , -1.1284393 , -1.1265595 ,\n",
-              "        -1.1229205 , -1.1222471 , -1.1207403 , -1.1196108 , -1.1196036 ,\n",
-              "        -1.1186633 , -1.1185873 , -1.1168755 , -1.1150851 , -1.1146263 ,\n",
-              "...\n",
-              "         9.716357  ,  9.717475  ,  9.7163725 ,  9.718897  ,  9.715463  ,\n",
-              "         9.711327  ,  9.713148  ,  9.713642  ,  9.712924  ,  9.715384  ,\n",
-              "         9.715974  ,  9.716772  ,  9.718337  ,  9.714473  ,  9.717203  ,\n",
-              "         9.714393  ,  9.71425   ,  9.713914  ,  9.711695  ,  9.708918  ,\n",
-              "         9.711455  ,  9.70863   ,  9.711487  ,  9.71433   ,  9.710337  ,\n",
-              "         9.711295  ,  9.7138815 ,  9.70997   ,  9.713227  ,  9.717092  ,\n",
-              "         9.713419  ,  9.719773  ,  9.71832   ,  9.716453  ,  9.717108  ,\n",
-              "         9.715989  ,  9.7141695 ,  9.711615  ,  9.71741   ,  9.715814  ,\n",
-              "         9.71428   ,  9.717347  ,  9.712972  ,  9.7162285 ,  9.713419  ,\n",
-              "         9.712238  ,  9.714361  ,  9.716245  ,  9.713563  ,  9.718161  ,\n",
-              "         9.713195  ,  9.715207  ,  9.71591   ,  9.713914  ,  9.7165    ,\n",
-              "         9.7136755 ,  9.717347  ,  9.719837  ,  9.718688  ,  9.713898  ,\n",
-              "         9.717618  ,  9.715941  ,  9.710864  ,  9.71433   ,  9.717777  ,\n",
-              "         9.716262  ,  9.716644  ,  9.719199  ,  9.718911  ,  9.715112  ,\n",
-              "         9.714042  ,  9.710752  ,  9.714153  ,  9.716006  ,  9.715191  ,\n",
-              "         9.716421  ,  9.718177  ,  9.717875  ,  9.718033  ,  9.713227  ,\n",
-              "         9.714537  ,  9.714841  ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
-              "         9.715717  ,  9.711741  ,  9.710465  ,  9.712621  ,  9.71337   ,\n",
-              "         9.715622  ,  9.715989  ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
-              "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-cc0755d1-eac2-491e-928f-87d0c37109ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc0755d1-eac2-491e-928f-87d0c37109ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-567a13b3-7eb6-4554-92ac-a39a2c00f691' class='xr-var-data-in' type='checkbox'><label for='data-567a13b3-7eb6-4554-92ac-a39a2c00f691' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
-              "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
-              "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
-              "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
-              "       16.466002, 16.476501, 16.464167, 16.464666, 16.462667, 16.460833,\n",
-              "       16.462164, 16.460167, 16.459501, 16.459002, 16.454332, 16.449501,\n",
-              "       16.444332, 16.4325  , 16.422   , 16.412834, 16.400167, 16.397667,\n",
-              "       16.385334, 16.382334, 16.380499, 16.383333, 16.381332, 16.379833,\n",
-              "       16.382   , 16.379168, 16.380499, 16.378834, 16.374832, 16.384499,\n",
-              "       16.374166, 16.373333, 16.377167, 16.376   , 16.38    , 16.370333,\n",
-              "       16.376501, 16.382   , 16.3775  , 16.3815  , 16.378   , 16.3785  ,\n",
-              "       16.378   , 16.383667, 16.374668, 16.3845  , 16.353   , 16.372334,\n",
-              "       16.377668, 16.378168, 16.372334, 16.372665, 16.363167, 16.367167,\n",
-              "       16.372833, 16.363333, 16.355165, 16.367002, 16.368334, 16.372665,\n",
-              "       16.360834, 16.367834, 16.367   , 16.360834, 16.358   , 16.342833,\n",
-              "       16.341167, 16.328001, 16.317   , 16.305332, 16.295   , 16.2915  ,\n",
-              "       16.279333, 16.281166, 16.280834, 16.276167, 16.279333, 16.279333,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-              "       16.275   , 16.278334, 16.276834, 16.271   , 16.2725  , 16.27    ,\n",
-              "       16.265165, 16.268333, 16.268   , 16.264   , 16.268   , 16.268   ,\n",
-              "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.268   ,\n",
-              "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.263334,\n",
-              "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
-              "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
-              "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
-              "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-0ea2a008-c7ed-404d-82e3-22b0a9cf1efd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ea2a008-c7ed-404d-82e3-22b0a9cf1efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bbdbfa5-d964-49a4-9ac2-26a5234ec875' class='xr-var-data-in' type='checkbox'><label for='data-7bbdbfa5-d964-49a4-9ac2-26a5234ec875' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
-              "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
-              "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
-              "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
-              "       20.25    , 20.25    , 20.163334, 20.      , 20.      , 20.      ,\n",
-              "       19.766666, 19.75    , 19.75    , 19.726667, 19.553333, 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.606667, 19.746666, 19.75    , 19.75    , 19.75    ,\n",
-              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-              "       19.556667, 19.5     , 19.5     , 19.5     , 19.626667, 19.75    ,\n",
-              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-              "       19.75    , 19.75    , 19.75    , 19.54    , 19.413334, 19.233334,\n",
-              "       19.      , 18.91    , 18.75    , 18.746666, 18.5     , 18.5     ,\n",
-              "       18.5     , 18.5     , 18.366667, 18.25    , 18.25    , 18.25    ,\n",
-              "       18.25    , 18.2     , 18.      , 18.      , 18.      , 18.      ,\n",
-              "       17.873333, 17.75    , 17.75    , 17.75    , 17.863333, 18.      ,\n",
-              "       18.      , 18.17    , 18.25    , 18.44    , 18.513334, 18.75    ,\n",
-              "       18.783333, 19.      , 19.      , 19.196667, 19.25    , 19.25    ,\n",
-              "       19.25    , 19.433332, 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
-              "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-              "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-404cc268-b828-4be2-9f0e-f5ea092a8e62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-404cc268-b828-4be2-9f0e-f5ea092a8e62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae2d2613-dfc7-49eb-90ec-4cc77daf5d9c' class='xr-var-data-in' type='checkbox'><label for='data-ae2d2613-dfc7-49eb-90ec-4cc77daf5d9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-07b270e1-76b1-4d7a-bb68-bd0976704d2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07b270e1-76b1-4d7a-bb68-bd0976704d2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f5c59a0-1323-4827-b779-7dc9bc5a7064' class='xr-var-data-in' type='checkbox'><label for='data-9f5c59a0-1323-4827-b779-7dc9bc5a7064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "...\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355693e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-80f9429f-e37d-463a-b260-bc3dce95522f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80f9429f-e37d-463a-b260-bc3dce95522f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc2060a2-f49a-4655-9ed5-6966a6b9a0c8' class='xr-var-data-in' type='checkbox'><label for='data-dc2060a2-f49a-4655-9ed5-6966a6b9a0c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
-              "         -0.18383324, -0.17606331],\n",
-              "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
-              "         -0.19696543, -0.20011853],\n",
-              "        [ 0.26504937,  0.28428233,  0.31169885, ..., -0.2103943 ,\n",
-              "         -0.21627884, -0.21236075],\n",
-              "        ...,\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan]],\n",
-              "\n",
-              "       [[ 0.02619691,  0.04430203,  0.04002393, ...,  0.05932099,\n",
-              "          0.06400961,  0.07232199],\n",
-              "        [ 0.06181316,  0.07802678,  0.06236525, ...,  0.0768801 ,\n",
-              "          0.08184617,  0.0892335 ],\n",
-              "        [ 0.08793733,  0.10133781,  0.08016948, ...,  0.08136398,\n",
-              "          0.08639657,  0.10118616],\n",
-              "...\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan]],\n",
-              "\n",
-              "       [[-0.00417333, -0.01056667, -0.01045333, ..., -0.02584564,\n",
-              "         -0.02752333, -0.02575667],\n",
-              "        [ 0.01358667,  0.00760333,  0.00634667, ..., -0.01625333,\n",
-              "         -0.01776333, -0.01595   ],\n",
-              "        [ 0.01556187,  0.00811371,  0.00740333, ..., -0.00842   ,\n",
-              "         -0.01147667, -0.01189667],\n",
-              "        ...,\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan],\n",
-              "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-835a0dc2-bd02-46dc-b855-d47c12c9c279' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-835a0dc2-bd02-46dc-b855-d47c12c9c279' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d2b5c66-6ad4-4add-af31-56e1b8ffedc7' class='xr-var-data-in' type='checkbox'><label for='data-1d2b5c66-6ad4-4add-af31-56e1b8ffedc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
-              "         81.68667 ],\n",
-              "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
-              "         77.528336],\n",
-              "        [72.81167 , 73.391304, 74.26833 , ..., 74.525   , 74.39667 ,\n",
-              "         74.253334],\n",
-              "        ...,\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan]],\n",
-              "\n",
-              "       [[80.706665, 80.93833 , 81.255   , ..., 82.19833 , 82.225   ,\n",
-              "         82.17    ],\n",
-              "        [76.80666 , 76.996666, 77.44833 , ..., 78.38333 , 78.41167 ,\n",
-              "         78.06    ],\n",
-              "        [74.31834 , 74.64667 , 75.903336, ..., 75.16333 , 75.26833 ,\n",
-              "         74.875   ],\n",
-              "...\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan]],\n",
-              "\n",
-              "       [[80.185   , 80.55    , 80.885   , ..., 81.888336, 81.945   ,\n",
-              "         81.85833 ],\n",
-              "        [75.78    , 76.291664, 76.76833 , ..., 77.97667 , 78.03833 ,\n",
-              "         77.87666 ],\n",
-              "        [72.67725 , 73.55666 , 74.44334 , ..., 74.75833 , 74.665   ,\n",
-              "         74.47    ],\n",
-              "        ...,\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan],\n",
-              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-286a83dd-1148-46cb-9de7-e2ae8ece0f95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-286a83dd-1148-46cb-9de7-e2ae8ece0f95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d168c9-4293-4ab6-a0b1-2e9f011125be' class='xr-var-data-in' type='checkbox'><label for='data-d3d168c9-4293-4ab6-a0b1-2e9f011125be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
-              "         92.06333 ],\n",
-              "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
-              "         96.03333 ],\n",
-              "        [97.166664, 96.246666, 95.94    , ..., 96.45333 , 97.206665,\n",
-              "         97.263336],\n",
-              "        ...,\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ]],\n",
-              "\n",
-              "       [[93.333336, 93.61    , 93.31333 , ..., 91.6     , 91.49    ,\n",
-              "         91.14667 ],\n",
-              "        [96.57    , 96.39    , 96.12666 , ..., 96.27    , 96.56333 ,\n",
-              "         96.44334 ],\n",
-              "        [97.37666 , 97.09333 , 96.87666 , ..., 96.17333 , 97.30334 ,\n",
-              "         97.32667 ],\n",
-              "...\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ]],\n",
-              "\n",
-              "       [[92.78333 , 93.223335, 92.63    , ..., 92.22    , 92.34    ,\n",
-              "         92.61    ],\n",
-              "        [96.75    , 96.34333 , 96.34    , ..., 96.53    , 96.69    ,\n",
-              "         96.27333 ],\n",
-              "        [96.346664, 97.05    , 97.24    , ..., 96.66333 , 96.89333 ,\n",
-              "         97.41    ],\n",
-              "        ...,\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ],\n",
-              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-f571b318-e797-496a-b128-02af5fbd8d46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f571b318-e797-496a-b128-02af5fbd8d46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cb3b78f-ae14-4dba-b173-83f31056980d' class='xr-var-data-in' type='checkbox'><label for='data-2cb3b78f-ae14-4dba-b173-83f31056980d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
-              "          5.81927113e-02,  5.85613623e-02,  5.85512854e-02],\n",
-              "        [ 9.98300374e-01,  9.98323679e-01,  9.98248577e-01, ...,\n",
-              "          9.98254061e-01,  9.98234987e-01,  9.98234689e-01],\n",
-              "        [-1.05408905e-03, -1.34927384e-03, -1.13080605e-03, ...,\n",
-              "         -8.26976204e-04, -8.38353124e-04, -8.28948745e-04]],\n",
-              "\n",
-              "       [[-9.89950538e-01, -9.89953220e-01, -9.89922285e-01, ...,\n",
-              "         -9.91938353e-01, -9.91944909e-01, -9.91939366e-01],\n",
-              "        [ 5.68153895e-02,  5.63202463e-02,  5.76671995e-02, ...,\n",
-              "          5.77317439e-02,  5.80984168e-02,  5.80891557e-02],\n",
-              "        [-1.29125342e-01, -1.29299909e-01, -1.28952131e-01, ...,\n",
-              "         -1.12354711e-01, -1.12130061e-01, -1.12175331e-01]],\n",
-              "\n",
-              "       [[-1.28852651e-01, -1.29014045e-01, -1.28667876e-01, ...,\n",
-              "         -1.12116747e-01, -1.11889169e-01, -1.11934915e-01],\n",
-              "        [ 8.45469162e-03,  8.69723968e-03,  8.63243733e-03, ...,\n",
-              "          7.35414820e-03,  7.39390310e-03,  7.38611678e-03],\n",
-              "        [ 9.91627276e-01,  9.91604209e-01,  9.91649806e-01, ...,\n",
-              "          9.93667483e-01,  9.93692815e-01,  9.93687749e-01]]],\n",
-              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-f5f72cc0-816a-4bd5-91a4-3554e0011ccd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5f72cc0-816a-4bd5-91a4-3554e0011ccd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53b865f0-230e-4714-ba59-680e4cf00b61' class='xr-var-data-in' type='checkbox'><label for='data-53b865f0-230e-4714-ba59-680e4cf00b61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
-              "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
-              "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
-              "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
-              "         0.00054653,  0.00055442,  0.00072552,  0.00056834,  0.00065792,\n",
-              "         0.00086152,  0.00080709,  0.00096736,  0.00085591,  0.00094166,\n",
-              "         0.00090368,  0.00095632,  0.00094047,  0.00091472,  0.00092718,\n",
-              "         0.00097144,  0.00090388,  0.00098592,  0.00099217,  0.00104627,\n",
-              "         0.00101094,  0.00108953,  0.00094413,  0.0010326 ,  0.00105636,\n",
-              "         0.00098609,  0.00101084,  0.00101927,  0.00101796,  0.00096841,\n",
-              "         0.00102785,  0.00113951,  0.00098156,  0.00111134,  0.00100472,\n",
-              "         0.00104199,  0.00104198,  0.00100612,  0.00103637,  0.00099132,\n",
-              "         0.00102272,  0.00102712,  0.00100425,  0.0010416 ,  0.00097589,\n",
-              "         0.00090605,  0.00108258,  0.00090169,  0.00096689,  0.00081777,\n",
-              "         0.0009423 ,  0.00087804,  0.00102183,  0.00083111,  0.0009242 ,\n",
-              "         0.00094747,  0.00110261,  0.00097415,  0.00097692,  0.00113317,\n",
-              "         0.00105406,  0.00104935,  0.00102722,  0.00093711,  0.00103575,\n",
-              "         0.00095867,  0.0009583 ,  0.00104538,  0.00100466,  0.00095809,\n",
-              "         0.00101549,  0.00097118,  0.00090704,  0.00094464,  0.00096578,\n",
-              "         0.00105039,  0.00093799,  0.00100518,  0.00088882,  0.00095506,\n",
-              "...\n",
-              "        -0.00263344, -0.00258787, -0.00256183, -0.00256183, -0.00250324,\n",
-              "        -0.00268227, -0.00268227, -0.00259113, -0.00262693, -0.00257485,\n",
-              "        -0.00259113, -0.00252602, -0.00267576, -0.00253904, -0.00256509,\n",
-              "        -0.00242511, -0.00249998, -0.00250975, -0.00252277, -0.00261066,\n",
-              "        -0.00257485, -0.00265298, -0.00264647, -0.00261391, -0.00260089,\n",
-              "        -0.00270181, -0.0027604 , -0.00278318, -0.00288084, -0.00274412,\n",
-              "        -0.00280272, -0.00289386, -0.0030729 , -0.0029492 , -0.0029199 ,\n",
-              "        -0.00302407, -0.00299803, -0.00296222, -0.00288084, -0.00299477,\n",
-              "        -0.00304034, -0.00298175, -0.00296222, -0.00296873, -0.00305337,\n",
-              "        -0.00302081, -0.00299803, -0.00304034, -0.0030729 , -0.0029199 ,\n",
-              "        -0.00295571, -0.00287433, -0.00287433, -0.0028548 , -0.00275714,\n",
-              "        -0.00271157, -0.0027018 , -0.00278644, -0.0026074 , -0.00264972,\n",
-              "        -0.00273761, -0.00259764, -0.00258787, -0.00256834, -0.00263344,\n",
-              "        -0.00255207, -0.00265623, -0.00261391, -0.00255207, -0.00249673,\n",
-              "        -0.00258787, -0.00256183, -0.00253579, -0.00264321, -0.00268553,\n",
-              "        -0.00255858, -0.00264321, -0.00262693, -0.0025423 , -0.00256834,\n",
-              "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
-              "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
-              "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
-              "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-45a6a8d5-3fef-4a8f-866f-3a995f2a7b59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45a6a8d5-3fef-4a8f-866f-3a995f2a7b59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0994d618-54bb-41b5-a0d3-170b89de0800' class='xr-var-data-in' type='checkbox'><label for='data-0994d618-54bb-41b5-a0d3-170b89de0800' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
-              "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
-              "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
-              "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
-              "         0.6253574 ,  0.6254711 ,  0.6251542 ,  0.6249595 ,  0.62512624,\n",
-              "         0.62510735,  0.62479544,  0.6250753 ,  0.624999  ,  0.6248949 ,\n",
-              "         0.6248343 ,  0.6245227 ,  0.6248399 ,  0.624795  ,  0.6250311 ,\n",
-              "         0.62494355,  0.6249766 ,  0.6244582 ,  0.62417775,  0.6244494 ,\n",
-              "         0.6248647 ,  0.6245337 ,  0.62416995,  0.6242157 ,  0.62425923,\n",
-              "         0.6247039 ,  0.6248129 ,  0.6246122 ,  0.6248121 ,  0.6246928 ,\n",
-              "         0.6245991 ,  0.6248212 ,  0.6247573 ,  0.6243741 ,  0.6243043 ,\n",
-              "         0.6244282 ,  0.6243682 ,  0.6240724 ,  0.62418926,  0.6241515 ,\n",
-              "         0.6239765 ,  0.62391806,  0.62415963,  0.62387216,  0.6239287 ,\n",
-              "         0.62390673,  0.6236841 ,  0.62378633,  0.6236643 ,  0.6235926 ,\n",
-              "         0.62364197,  0.6237233 ,  0.62374234,  0.62387735,  0.62402254,\n",
-              "         0.62393117,  0.62393445,  0.62373453,  0.62396324,  0.62340415,\n",
-              "         0.62373024,  0.62379295,  0.62355286,  0.6231889 ,  0.62350035,\n",
-              "         0.6232749 ,  0.6232579 ,  0.6233172 ,  0.6232117 ,  0.62328154,\n",
-              "         0.6234021 ,  0.62359464,  0.6235321 ,  0.62355274,  0.62340564,\n",
-              "         0.6233349 ,  0.6232732 ,  0.62326413,  0.62335676,  0.6233057 ,\n",
-              "...\n",
-              "         0.77982664,  0.7798403 ,  0.77980125,  0.7798833 ,  0.7798343 ,\n",
-              "         0.77974474,  0.7795985 ,  0.77965385,  0.77964175,  0.7797572 ,\n",
-              "         0.7798193 ,  0.77987343,  0.77987754,  0.7798154 ,  0.7798561 ,\n",
-              "         0.77976704,  0.77973217,  0.77971977,  0.77958   ,  0.7794924 ,\n",
-              "         0.77951276,  0.77934176,  0.77977145,  0.77983665,  0.7796758 ,\n",
-              "         0.77951133,  0.77975136,  0.7796223 ,  0.7795445 ,  0.7798783 ,\n",
-              "         0.7796854 ,  0.78009176,  0.77983886,  0.77976817,  0.7798124 ,\n",
-              "         0.77966744,  0.77980477,  0.77957195,  0.7797228 ,  0.7795519 ,\n",
-              "         0.77965647,  0.7795511 ,  0.7795689 ,  0.77951413,  0.77942085,\n",
-              "         0.7791843 ,  0.7793043 ,  0.7793574 ,  0.7790914 ,  0.77922   ,\n",
-              "         0.7788722 ,  0.77907705,  0.7790985 ,  0.778842  ,  0.7789314 ,\n",
-              "         0.77889466,  0.7789852 ,  0.7792381 ,  0.77916646,  0.7788889 ,\n",
-              "         0.77894676,  0.7789039 ,  0.7785506 ,  0.7786492 ,  0.7788344 ,\n",
-              "         0.7786969 ,  0.77884805,  0.7789083 ,  0.77894056,  0.7786727 ,\n",
-              "         0.77858806,  0.7783844 ,  0.7785528 ,  0.7787677 ,  0.77864134,\n",
-              "         0.77870125,  0.7787834 ,  0.7788154 ,  0.7788442 ,  0.7785659 ,\n",
-              "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
-              "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
-              "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
-              "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-80807e6c-4ad1-4cb5-a7b4-432d16d0cb72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80807e6c-4ad1-4cb5-a7b4-432d16d0cb72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d10a642e-69bf-4c03-a5c3-06929c1a6332' class='xr-var-data-in' type='checkbox'><label for='data-d10a642e-69bf-4c03-a5c3-06929c1a6332' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
-              "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
-              "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
-              "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
-              "       13.       , 12.941335 , 12.800002 , 12.631333 , 12.598    ,\n",
-              "       12.411335 , 12.400001 , 12.230666 , 12.199998 , 12.119332 ,\n",
-              "       12.       , 12.       , 12.       , 11.957999 , 11.800002 ,\n",
-              "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.800002 ,\n",
-              "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.834001 ,\n",
-              "       11.999333 , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.104667 , 12.193999 , 12.199998 , 12.199998 ,\n",
-              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.086667 ,\n",
-              "       12.113999 , 12.192665 , 12.032667 , 12.078666 , 12.03     ,\n",
-              "       12.       , 12.111999 , 12.199998 , 12.199998 , 12.199998 ,\n",
-              "       12.202665 , 12.219333 , 12.274    , 12.367333 , 12.203999 ,\n",
-              "       12.217332 , 12.199998 , 12.199998 , 12.119332 , 11.845334 ,\n",
-              "       11.496667 , 11.219998 , 11.       , 10.952001 , 10.800002 ,\n",
-              "       10.800002 , 10.800002 , 10.800002 , 10.751334 , 10.599999 ,\n",
-              "       10.599999 , 10.599999 , 10.599999 , 10.5546665, 10.400001 ,\n",
-              "       10.400001 , 10.334666 , 10.2      , 10.2      , 10.191999 ,\n",
-              "       10.029333 , 10.       , 10.009334 , 10.198667 , 10.243333 ,\n",
-              "       10.415334 , 10.599999 , 10.772668 , 11.       , 11.186666 ,\n",
-              "       11.398002 , 11.528    , 11.599999 , 11.746667 , 11.800002 ,\n",
-              "       11.876667 , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       , 12.000667 , 12.006    ,\n",
-              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.001333 , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.024667 , 12.173999 , 12.199998 ,\n",
-              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-              "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-da38a2c5-c0d7-45bf-ace1-9a9ae7cc141c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da38a2c5-c0d7-45bf-ace1-9a9ae7cc141c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90901631-17a9-41e8-b887-81a76cadf770' class='xr-var-data-in' type='checkbox'><label for='data-90901631-17a9-41e8-b887-81a76cadf770' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
-              "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
-              "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
-              "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
-              "       244.98334, 244.94   , 244.86333, 244.82666, 244.79333, 244.84666,\n",
-              "       244.76666, 244.73334, 244.82666, 244.75   , 244.86333, 244.83   ,\n",
-              "       244.84334, 244.91333, 244.96666, 245.08   , 245.25333, 245.30667,\n",
-              "       245.4    , 245.51   , 245.61333, 245.61   , 245.65666, 245.76666,\n",
-              "       245.73   , 245.79666, 245.83333, 245.85333, 245.81   , 245.85667,\n",
-              "       245.90334, 245.89333, 245.90666, 245.90334, 245.89333, 245.90666,\n",
-              "       245.93   , 245.91333, 245.91667, 245.92334, 245.92334, 245.92   ,\n",
-              "       245.96   , 245.95   , 245.94333, 245.96   , 245.94667, 245.97   ,\n",
-              "       245.95   , 245.93666, 245.93   , 245.95667, 245.94   , 245.95667,\n",
-              "       245.95   , 245.95334, 245.96666, 245.98   , 245.96666, 245.97   ,\n",
-              "       245.97   , 245.98   , 245.97333, 245.97   , 245.98666, 245.97667,\n",
-              "       245.97667, 245.98334, 245.97667, 245.99333, 245.97667, 245.98334,\n",
-              "       245.99667, 245.99667, 245.99   , 245.97333, 245.98334, 245.98666,\n",
-              "       245.97   , 245.99667, 245.98666, 245.98   , 245.85667, 245.44667,\n",
-              "       244.92334, 244.41667, 244.16333, 244.00667, 244.06   , 244.07333,\n",
-              "       243.87334, 243.77333, 243.75   , 243.69   , 243.76334, 243.79666,\n",
-              "       243.55   , 243.5    , 243.37666, 243.20334, 242.92334, 242.87666,\n",
-              "       242.83   , 242.83333, 243.07666, 243.41   , 243.88333, 244.20334,\n",
-              "       244.40334, 244.45334, 244.48666, 244.41   , 244.38   , 244.43333,\n",
-              "       244.6    , 244.72333, 244.90666, 244.9    , 244.97667, 245.03667,\n",
-              "       245.22667, 245.36   , 245.4    , 245.42   , 245.48334, 245.62666,\n",
-              "       245.67   , 245.71333, 245.75667, 245.77   , 245.84   , 245.87   ,\n",
-              "       245.87666, 245.89   , 245.87666, 245.94333, 245.93   , 245.91333,\n",
-              "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
-              "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
-              "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
-              "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-2aa34c31-3361-49b7-a9c5-8ab6c267b27f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aa34c31-3361-49b7-a9c5-8ab6c267b27f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-731bdd99-c0c2-4995-8df5-99a7b6b8cba5' class='xr-var-data-in' type='checkbox'><label for='data-731bdd99-c0c2-4995-8df5-99a7b6b8cba5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
-              "         3.6116719e+00,  3.5757926e+00,  3.5947008e+00,  3.6243417e+00,\n",
-              "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830538e+00,\n",
-              "         3.6165168e+00,  3.5789921e+00,  3.5747981e+00,  3.5690453e+00,\n",
-              "         3.5796013e+00,  3.6261466e+00,  3.6063533e+00,  3.6014795e+00,\n",
-              "         3.6353865e+00,  3.6033041e+00,  3.6023455e+00,  3.5552027e+00,\n",
-              "         3.5689840e+00,  3.5028169e+00,  3.5047083e+00,  3.5002160e+00,\n",
-              "         3.4591196e+00,  3.4518204e+00,  3.4781299e+00,  3.4272485e+00,\n",
-              "         3.4080899e+00,  3.4372404e+00,  3.4341383e+00,  3.3986638e+00,\n",
-              "         3.4168522e+00,  3.4093900e+00,  3.3794670e+00,  3.3934760e+00,\n",
-              "         3.4050257e+00,  3.4207287e+00,  3.3710022e+00,  3.3771679e+00,\n",
-              "         3.3508575e+00,  3.3733418e+00,  3.3524203e+00,  3.3316767e+00,\n",
-              "         3.3258898e+00,  3.3680136e+00,  3.2842207e+00,  3.1945534e+00,\n",
-              "         3.0031645e+00,  2.4369471e+00,  2.1365104e+00,  1.9519800e+00,\n",
-              "         1.7708881e+00,  1.6470156e+00,  1.5729071e+00,  1.4625059e+00,\n",
-              "         1.3881445e+00,  1.3379683e+00,  1.3052688e+00,  1.2468668e+00,\n",
-              "         1.2023062e+00,  1.1269653e+00,  1.1022494e+00,  1.0541168e+00,\n",
-              "         1.0267943e+00,  9.7805512e-01,  9.2956728e-01,  9.2703992e-01,\n",
-              "         9.1599506e-01,  8.9450091e-01,  8.5012424e-01,  8.2220656e-01,\n",
-              "         7.9883534e-01,  7.8205061e-01,  7.3997599e-01,  7.3860037e-01,\n",
-              "...\n",
-              "        -1.9736919e+02, -1.9725951e+02, -1.9730052e+02, -1.9728384e+02,\n",
-              "        -1.9724889e+02, -1.9722919e+02, -1.9715518e+02, -1.9727151e+02,\n",
-              "        -1.9724452e+02, -1.9721884e+02, -1.9717354e+02, -1.9723384e+02,\n",
-              "        -1.9719716e+02, -1.9714218e+02, -1.9723254e+02, -1.9710817e+02,\n",
-              "        -1.9708250e+02, -1.9709784e+02, -1.9708986e+02, -1.9712950e+02,\n",
-              "        -1.9721385e+02, -1.9720052e+02, -1.9717422e+02, -1.9710918e+02,\n",
-              "        -1.9715718e+02, -1.9714487e+02, -1.9715251e+02, -1.9714418e+02,\n",
-              "        -1.9714218e+02, -1.9706715e+02, -1.9705818e+02, -1.9705084e+02,\n",
-              "        -1.9708583e+02, -1.9708820e+02, -1.9714618e+02, -1.9709253e+02,\n",
-              "        -1.9707854e+02, -1.9714384e+02, -1.9717952e+02, -1.9718620e+02,\n",
-              "        -1.9718388e+02, -1.9716652e+02, -1.9712685e+02, -1.9720485e+02,\n",
-              "        -1.9718315e+02, -1.9713019e+02, -1.9714951e+02, -1.9724086e+02,\n",
-              "        -1.9716119e+02, -1.9719583e+02, -1.9724786e+02, -1.9716052e+02,\n",
-              "        -1.9725883e+02, -1.9720285e+02, -1.9717485e+02, -1.9725154e+02,\n",
-              "        -1.9714687e+02, -1.9711821e+02, -1.9714719e+02, -1.9711786e+02,\n",
-              "        -1.9714052e+02, -1.9714351e+02, -1.9715118e+02, -1.9712117e+02,\n",
-              "        -1.9710718e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
-              "        -1.9706255e+02, -1.9714519e+02, -1.9712418e+02, -1.9705786e+02,\n",
-              "        -1.9708685e+02, -1.9711749e+02, -1.9707716e+02, -1.9707919e+02,\n",
-              "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-8a8419d8-2c69-41fe-8e75-29534c04e382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a8419d8-2c69-41fe-8e75-29534c04e382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26ead8e4-f4aa-4e9f-9c2b-b791e066a12a' class='xr-var-data-in' type='checkbox'><label for='data-26ead8e4-f4aa-4e9f-9c2b-b791e066a12a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
-              "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
-              "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
-              "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569212 , -1.2552022 ,\n",
-              "        -1.2558354 , -1.2547812 , -1.2564313 , -1.2570257 , -1.2564919 ,\n",
-              "        -1.2552761 , -1.2551885 , -1.254373  , -1.2521615 , -1.253256  ,\n",
-              "        -1.2520183 , -1.2556639 , -1.2544196 , -1.2537049 , -1.2514051 ,\n",
-              "        -1.251719  , -1.2501887 , -1.2550075 , -1.2560523 , -1.2542702 ,\n",
-              "        -1.2513357 , -1.2537422 , -1.25587   , -1.2554086 , -1.2568508 ,\n",
-              "        -1.2513126 , -1.251984  , -1.2514541 , -1.2487588 , -1.249171  ,\n",
-              "        -1.2487395 , -1.2432916 , -1.2308283 , -1.2085198 , -1.1925628 ,\n",
-              "        -1.1850357 , -1.175814  , -1.1718632 , -1.1669031 , -1.1620393 ,\n",
-              "        -1.1585126 , -1.1573663 , -1.1550487 , -1.1537894 , -1.1520277 ,\n",
-              "        -1.1507337 , -1.1474868 , -1.1443372 , -1.1442864 , -1.1430473 ,\n",
-              "        -1.1418384 , -1.141045  , -1.1385593 , -1.1344901 , -1.134764  ,\n",
-              "        -1.1317551 , -1.1333026 , -1.1325271 , -1.1293766 , -1.1324316 ,\n",
-              "        -1.1310244 , -1.1295373 , -1.1287975 , -1.1317044 , -1.1290994 ,\n",
-              "        -1.1286312 , -1.1276112 , -1.1271322 , -1.128308  , -1.1257491 ,\n",
-              "        -1.1227695 , -1.1230273 , -1.119395  , -1.1190095 , -1.1182653 ,\n",
-              "        -1.1186818 , -1.1167871 , -1.1160123 , -1.1153725 , -1.1143075 ,\n",
-              "...\n",
-              "         9.716884  ,  9.718464  ,  9.717347  ,  9.717715  ,  9.714792  ,\n",
-              "         9.714857  ,  9.712732  ,  9.712222  ,  9.713994  ,  9.715383  ,\n",
-              "         9.71674   ,  9.716182  ,  9.717108  ,  9.716772  ,  9.715446  ,\n",
-              "         9.714425  ,  9.7126045 ,  9.713626  ,  9.7121105 ,  9.711023  ,\n",
-              "         9.711408  ,  9.709459  ,  9.712988  ,  9.7141695 ,  9.710418  ,\n",
-              "         9.713371  ,  9.713164  ,  9.711615  ,  9.713355  ,  9.714377  ,\n",
-              "         9.714473  ,  9.719391  ,  9.71805   ,  9.71583   ,  9.716421  ,\n",
-              "         9.71658   ,  9.71583   ,  9.71334   ,  9.7177305 ,  9.716677  ,\n",
-              "         9.71476   ,  9.716166  ,  9.713404  ,  9.715751  ,  9.715623  ,\n",
-              "         9.712237  ,  9.714856  ,  9.7166605 ,  9.713179  ,  9.7175865 ,\n",
-              "         9.710929  ,  9.71484   ,  9.715895  ,  9.712062  ,  9.71591   ,\n",
-              "         9.714346  ,  9.716932  ,  9.718177  ,  9.718816  ,  9.713802  ,\n",
-              "         9.717826  ,  9.715128  ,  9.711727  ,  9.713515  ,  9.718353  ,\n",
-              "         9.716836  ,  9.716278  ,  9.717762  ,  9.718656  ,  9.714761  ,\n",
-              "         9.713004  ,  9.710816  ,  9.71409   ,  9.716276  ,  9.713579  ,\n",
-              "         9.716166  ,  9.718401  ,  9.716804  ,  9.718209  ,  9.71428   ,\n",
-              "         9.714553  ,  9.715957  ,  9.7148075 ,  9.717874  ,  9.716309  ,\n",
-              "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
-              "         9.715256  ,  9.714936  ,  9.7148075 ,  9.711726  ,  9.711886  ,\n",
-              "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-c1489d78-e4f8-4ed9-a39b-16d34eef0607' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1489d78-e4f8-4ed9-a39b-16d34eef0607' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-979eb0b5-c11d-4941-91e7-eaed1428ac1b' class='xr-var-data-in' type='checkbox'><label for='data-979eb0b5-c11d-4941-91e7-eaed1428ac1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-52723004-2e23-4fbc-95bf-e29b29e5059f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52723004-2e23-4fbc-95bf-e29b29e5059f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dabc074-db2c-43f3-a21f-ba8e89d48e8c' class='xr-var-data-in' type='checkbox'><label for='data-4dabc074-db2c-43f3-a21f-ba8e89d48e8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355693e+09, 1.05355686e+09, 1.05355693e+09,\n",
-              "       1.05355699e+09, 1.05355686e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355693e+09,\n",
-              "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
-              "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355693e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "...\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-ac1abc66-620f-46c9-9a93-3075662d1ab6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac1abc66-620f-46c9-9a93-3075662d1ab6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7234876-f33b-4775-8583-4d0c8554cecb' class='xr-var-data-in' type='checkbox'><label for='data-f7234876-f33b-4775-8583-4d0c8554cecb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
-              "        -0.02035667, -0.01573333],\n",
-              "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
-              "        -0.00658667, -0.00238   ],\n",
-              "       [ 0.02739334,  0.01897667,  0.01496333, ...,  0.00196667,\n",
-              "        -0.00096667,  0.00083946],\n",
-              "       ...,\n",
-              "       [        nan,         nan,         nan, ...,         nan,\n",
-              "                nan,         nan],\n",
-              "       [        nan,         nan,         nan, ...,         nan,\n",
-              "                nan,         nan],\n",
-              "       [        nan,         nan,         nan, ...,         nan,\n",
-              "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-1207ec72-09c2-4b85-ac67-d272dcc3b499' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1207ec72-09c2-4b85-ac67-d272dcc3b499' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d3b874-816d-4bc9-b9c1-cac5234ab087' class='xr-var-data-in' type='checkbox'><label for='data-d3d3b874-816d-4bc9-b9c1-cac5234ab087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
-              "        81.745   ],\n",
-              "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
-              "        78.045   ],\n",
-              "       [73.58833 , 74.355   , 75.083336, ..., 75.265   , 75.098335,\n",
-              "        74.92976 ],\n",
-              "       ...,\n",
-              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "              nan],\n",
-              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "              nan],\n",
-              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-03ad1167-0875-4cf7-975a-6bbb0d2a724a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03ad1167-0875-4cf7-975a-6bbb0d2a724a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ed62442-4022-403a-b87a-5c6c1de5cf10' class='xr-var-data-in' type='checkbox'><label for='data-8ed62442-4022-403a-b87a-5c6c1de5cf10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
-              "        92.61667 ],\n",
-              "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
-              "        96.57667 ],\n",
-              "       [97.19    , 97.32333 , 97.136665, ..., 96.08667 , 97.16    ,\n",
-              "        96.96667 ],\n",
-              "       ...,\n",
-              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "         0.      ],\n",
-              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "         0.      ],\n",
-              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-5e4433c1-a5c9-42b2-9362-7d86df0c9815' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e4433c1-a5c9-42b2-9362-7d86df0c9815' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83522526-79fc-4223-8c0c-267c8e027356' class='xr-var-data-in' type='checkbox'><label for='data-83522526-79fc-4223-8c0c-267c8e027356' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
-              "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
-              "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
-              "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
-              "        [-1.26286745e-01, -1.26509830e-01, -1.26157105e-01, ...,\n",
-              "         -1.09885700e-01, -1.09676003e-01, -1.09719723e-01]],\n",
-              "\n",
-              "       [[ 9.76216435e-01,  9.76112664e-01,  9.76405323e-01, ...,\n",
-              "          9.76383269e-01,  9.76462007e-01,  9.76460576e-01],\n",
-              "        [-2.14884892e-01, -2.15368673e-01, -2.14055121e-01, ...,\n",
-              "         -2.14541376e-01, -2.14190111e-01, -2.14200497e-01],\n",
-              "        [-2.69518793e-02, -2.67608669e-02, -2.67287735e-02, ...,\n",
-              "         -2.34543420e-02, -2.33496260e-02, -2.33698264e-02]],\n",
-              "\n",
-              "       [[-1.05265796e-03, -1.35056104e-03, -1.13043608e-03, ...,\n",
-              "         -8.24717747e-04, -8.40478169e-04, -8.31306970e-04],\n",
-              "        [-1.29126370e-01, -1.29302278e-01, -1.28952518e-01, ...,\n",
-              "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
-              "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
-              "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
-              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-d7173144-8398-40be-bd9d-dde1b7389737' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7173144-8398-40be-bd9d-dde1b7389737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb4b2283-0ff2-44f1-b251-ed0b82c4cbce' class='xr-var-data-in' type='checkbox'><label for='data-bb4b2283-0ff2-44f1-b251-ed0b82c4cbce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
-              "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
-              "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
-              "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
-              "         0.00056599,  0.00061758,  0.00068752,  0.00066373,  0.00073918,\n",
-              "         0.00085721,  0.00084523,  0.0009018 ,  0.00089635,  0.00084324,\n",
-              "         0.00086276,  0.00089614,  0.00096862,  0.00108153,  0.00095481,\n",
-              "         0.00098828,  0.00098117,  0.00097845,  0.00099421,  0.00095727,\n",
-              "         0.00108126,  0.00108415,  0.00096381,  0.00100037,  0.00098756,\n",
-              "         0.00103554,  0.00096841,  0.00107755,  0.00104051,  0.0009601 ,\n",
-              "         0.00106976,  0.0010707 ,  0.00102194,  0.0009954 ,  0.00100513,\n",
-              "         0.0010245 ,  0.00102471,  0.00096594,  0.0010335 ,  0.00105437,\n",
-              "         0.00105971,  0.00095506,  0.00102042,  0.00097918,  0.00088768,\n",
-              "         0.0009018 ,  0.00096684,  0.00101125,  0.00096008,  0.0008592 ,\n",
-              "         0.00082965,  0.00095935,  0.00094485,  0.00081024,  0.00092011,\n",
-              "         0.00098175,  0.00094213,  0.00095046,  0.00099598,  0.00104662,\n",
-              "         0.00101681,  0.0010222 ,  0.00099111,  0.001044  ,  0.00103549,\n",
-              "         0.00097536,  0.00099907,  0.00097684,  0.00104176,  0.00094763,\n",
-              "         0.0009761 ,  0.00097227,  0.00089143,  0.00096118,  0.00097306,\n",
-              "         0.00096506,  0.00094653,  0.00092565,  0.00091383,  0.0009503 ,\n",
-              "...\n",
-              "        -0.00262043, -0.00258136, -0.00261717, -0.00257811, -0.00261066,\n",
-              "        -0.00255532, -0.00266274, -0.00254881, -0.00255858, -0.00259764,\n",
-              "        -0.00258462, -0.00252602, -0.00258787, -0.00256183, -0.00260415,\n",
-              "        -0.00251626, -0.00250975, -0.00243488, -0.00254881, -0.00264321,\n",
-              "        -0.00260089, -0.00263996, -0.0026367 , -0.00271157, -0.00256183,\n",
-              "        -0.00271808, -0.00277993, -0.00284178, -0.00276365, -0.00277016,\n",
-              "        -0.00279946, -0.00295896, -0.00294594, -0.00302732, -0.00302407,\n",
-              "        -0.00301756, -0.00298501, -0.00291339, -0.00296548, -0.00294269,\n",
-              "        -0.00311196, -0.00294594, -0.0030143 , -0.00297198, -0.00296873,\n",
-              "        -0.002985  , -0.0030729 , -0.0030143 , -0.00306638, -0.00288084,\n",
-              "        -0.00289386, -0.00281899, -0.00278644, -0.0028255 , -0.00276365,\n",
-              "        -0.00277993, -0.002666  , -0.00267576, -0.002666  , -0.00268227,\n",
-              "        -0.00268878, -0.00263019, -0.00254881, -0.00262368, -0.00263019,\n",
-              "        -0.00260415, -0.00257811, -0.0026074 , -0.00249673, -0.00254881,\n",
-              "        -0.00258787, -0.00263019, -0.00255532, -0.00269204, -0.00258136,\n",
-              "        -0.00259113, -0.00272133, -0.00258462, -0.00263019, -0.00261066,\n",
-              "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
-              "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
-              "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
-              "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-b39bd1a7-c5aa-4350-abf6-a52d0d9b0342' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b39bd1a7-c5aa-4350-abf6-a52d0d9b0342' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2805d9de-f37e-4513-91bb-60faa10fcdd8' class='xr-var-data-in' type='checkbox'><label for='data-2805d9de-f37e-4513-91bb-60faa10fcdd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
-              "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
-              "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
-              "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
-              "         0.6253524 ,  0.6254653 ,  0.62515104,  0.62495625,  0.62512195,\n",
-              "         0.6251015 ,  0.624793  ,  0.6250713 ,  0.6249948 ,  0.62489176,\n",
-              "         0.6248301 ,  0.62451917,  0.6248372 ,  0.62479085,  0.62502736,\n",
-              "         0.6249378 ,  0.62497205,  0.62445515,  0.62417245,  0.6244453 ,\n",
-              "         0.6248608 ,  0.62453014,  0.62416404,  0.6242139 ,  0.62425303,\n",
-              "         0.62470126,  0.6248098 ,  0.62460905,  0.62480783,  0.6246901 ,\n",
-              "         0.6245936 ,  0.6248162 ,  0.624754  ,  0.62437105,  0.62430066,\n",
-              "         0.6244233 ,  0.6243633 ,  0.62407166,  0.6241861 ,  0.6241456 ,\n",
-              "         0.6239719 ,  0.62391376,  0.62415487,  0.6238682 ,  0.6239241 ,\n",
-              "         0.62390107,  0.6236789 ,  0.6237806 ,  0.6236614 ,  0.62358916,\n",
-              "         0.6236376 ,  0.62371755,  0.6237382 ,  0.6238726 ,  0.6240171 ,\n",
-              "         0.6239264 ,  0.623931  ,  0.6237308 ,  0.62395936,  0.6234018 ,\n",
-              "         0.6237265 ,  0.6237913 ,  0.6235492 ,  0.62318647,  0.62349266,\n",
-              "         0.62327045,  0.6232548 ,  0.6233126 ,  0.6232084 ,  0.6232786 ,\n",
-              "         0.62339824,  0.62359285,  0.6235284 ,  0.6235471 ,  0.6234016 ,\n",
-              "         0.6233313 ,  0.6232729 ,  0.6232614 ,  0.62335205,  0.6232998 ,\n",
-              "...\n",
-              "         0.7798304 ,  0.77984285,  0.7798039 ,  0.7798881 ,  0.77983624,\n",
-              "         0.779747  ,  0.7796003 ,  0.7796562 ,  0.77964693,  0.77976   ,\n",
-              "         0.77982175,  0.77987325,  0.7798803 ,  0.77981853,  0.7798599 ,\n",
-              "         0.77976817,  0.7797355 ,  0.7797223 ,  0.77958274,  0.7794968 ,\n",
-              "         0.77951866,  0.7793451 ,  0.77977306,  0.7798404 ,  0.7796792 ,\n",
-              "         0.77951556,  0.7797541 ,  0.7796244 ,  0.77954704,  0.779882  ,\n",
-              "         0.7796897 ,  0.78009367,  0.77984214,  0.77977324,  0.77981466,\n",
-              "         0.77967215,  0.77980614,  0.7795769 ,  0.77972573,  0.77955645,\n",
-              "         0.7796588 ,  0.77955323,  0.7795721 ,  0.7795167 ,  0.7794243 ,\n",
-              "         0.77918714,  0.77930677,  0.7793621 ,  0.77909505,  0.7792217 ,\n",
-              "         0.7788761 ,  0.7790808 ,  0.7791028 ,  0.7788446 ,  0.7789332 ,\n",
-              "         0.7788981 ,  0.7789904 ,  0.779241  ,  0.7791693 ,  0.77889454,\n",
-              "         0.7789502 ,  0.77890694,  0.7785553 ,  0.77865255,  0.7788394 ,\n",
-              "         0.7787025 ,  0.7788493 ,  0.77891165,  0.7789452 ,  0.77867603,\n",
-              "         0.7785905 ,  0.7783878 ,  0.77855736,  0.778772  ,  0.7786441 ,\n",
-              "         0.77870494,  0.77878624,  0.77881914,  0.77884936,  0.77857053,\n",
-              "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
-              "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
-              "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
-              "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-ac9904c0-7c54-436e-ae3f-01105ec4b6ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac9904c0-7c54-436e-ae3f-01105ec4b6ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0044892b-bf52-4cea-a990-44d519ed1609' class='xr-var-data-in' type='checkbox'><label for='data-0044892b-bf52-4cea-a990-44d519ed1609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-530600cd-d334-468f-b609-aa2995780efd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-530600cd-d334-468f-b609-aa2995780efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4201c682-780a-4c9b-bcdb-91bea8d76fa6' class='xr-var-data-in' type='checkbox'><label for='data-4201c682-780a-4c9b-bcdb-91bea8d76fa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-e880d741-352f-4824-8fdf-574661b1157a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e880d741-352f-4824-8fdf-574661b1157a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97f17196-9934-41d3-84eb-09808b171b41' class='xr-var-data-in' type='checkbox'><label for='data-97f17196-9934-41d3-84eb-09808b171b41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-5421ce6b-1e96-439f-8a08-d278b40a3c44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5421ce6b-1e96-439f-8a08-d278b40a3c44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc9df836-e7c1-47d7-a6dc-665c75d077b6' class='xr-var-data-in' type='checkbox'><label for='data-cc9df836-e7c1-47d7-a6dc-665c75d077b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-e6d26a7e-dbf1-4e8b-b5c5-e7e625fbf25b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6d26a7e-dbf1-4e8b-b5c5-e7e625fbf25b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49a0c93a-7544-4e43-a887-660a21e44663' class='xr-var-data-in' type='checkbox'><label for='data-49a0c93a-7544-4e43-a887-660a21e44663' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
-              "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
-              "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
-              "       0.12      , 0.12333333, 0.12      , 0.11      , 0.11      ,\n",
-              "       0.11666667, 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11333334,\n",
-              "       0.12      , 0.11666667, 0.11666667, 0.11666667, 0.11333334,\n",
-              "       0.12      , 0.11666667, 0.11      , 0.12333333, 0.13333334,\n",
-              "       0.13333334, 0.13      , 0.13333334, 0.12666667, 0.13333334,\n",
-              "       0.13      , 0.13      , 0.15333334, 0.13333334, 0.15333334,\n",
-              "       0.14333333, 0.13666667, 0.11666667, 0.13666667, 0.13333334,\n",
-              "       0.13666667, 0.14666666, 0.14      , 0.15666667, 0.13333334,\n",
-              "       0.13333334, 0.15      , 0.15      , 0.12666667, 0.13666667,\n",
-              "       0.15      , 0.13      , 0.13666667, 0.13      , 0.13666667,\n",
-              "       0.13666667, 0.14333333, 0.13666667, 0.12666667, 0.13666667,\n",
-              "       0.12333333, 0.12333333, 0.13333334, 0.12      , 0.11666667,\n",
-              "       0.11      , 0.11      , 0.11666667, 0.12333333, 0.11      ,\n",
-              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-              "       0.11      , 0.20333333, 0.22666667, 0.22      , 0.22      ,\n",
-              "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
-              "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
-              "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
-              "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-ee6c7c13-5318-4806-ad24-22ffe79846c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee6c7c13-5318-4806-ad24-22ffe79846c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d46d7a3-9016-4cc3-aaa6-71f6a1560d55' class='xr-var-data-in' type='checkbox'><label for='data-1d46d7a3-9016-4cc3-aaa6-71f6a1560d55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
-              "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
-              "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
-              "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
-              "       3.3772287, 3.3739138, 3.3298807, 3.368963 , 3.357279 , 3.3420138,\n",
-              "       3.3332636, 3.2887158, 3.3332634, 3.3267972, 3.3609293, 3.34788  ,\n",
-              "       3.3524635, 3.2797818, 3.2383478, 3.2774158, 3.3357968, 3.2894654,\n",
-              "       3.237099 , 3.2444148, 3.250231 , 3.3133483, 3.3285973, 3.3003979,\n",
-              "       3.3281136, 3.3106983, 3.2960656, 3.3239977, 3.3058155, 3.231132 ,\n",
-              "       3.2188826, 3.2362165, 3.2269833, 3.1857452, 3.2025456, 3.1971133,\n",
-              "       3.1716278, 3.1624265, 3.196963 , 3.1550453, 3.162944 , 3.158162 ,\n",
-              "       3.1250577, 3.1385927, 3.1210082, 3.1101758, 3.116926 , 3.1283762,\n",
-              "       3.1307604, 3.149876 , 3.1709106, 3.1579425, 3.157861 , 3.1293783,\n",
-              "       3.1623626, 3.0823452, 3.1290247, 3.1371257, 3.103561 , 3.0512455,\n",
-              "       3.0958426, 3.0634787, 3.061212 , 3.0691292, 3.0543785, 3.0647104,\n",
-              "       3.0809944, 3.1082118, 3.099077 , 3.1025605, 3.0808105, 3.070144 ,\n",
-              "       3.061945 , 3.0596778, 3.0728438, 3.0654464, 3.082978 , 3.0888774,\n",
-              "       3.090909 , 3.1166098, 3.1326916, 3.1294093, 3.1606429, 3.0821111,\n",
-              "       3.0704782, 3.099461 , 3.1288106, 3.0858114, 3.1094916, 3.1244771,\n",
-              "       3.0631604, 3.098195 , 3.0228472, 3.0709112, 3.0849445, 3.0772102,\n",
-              "       3.10411  , 3.0789108, 3.122175 , 3.0939767, 3.126108 , 3.1068432,\n",
-              "       3.1269426, 3.124676 , 3.133493 , 3.1521947, 3.1957629, 3.174427 ,\n",
-              "       3.1647441, 3.2137322, 3.1900635, 3.2544334, 3.2174487, 3.2122307,\n",
-              "       3.2605999, 3.244882 , 3.2509172, 3.234432 , 3.1874464, 3.200428 ,\n",
-              "       3.251467 , 3.2418153, 3.24985  , 3.3141315, 3.2959988, 3.2620163,\n",
-              "       3.2882996, 3.2601004, 3.2490656, 3.242116 , 3.2917488, 3.306215 ,\n",
-              "       3.3455298, 3.3139143, 3.274265 , 3.2986312, 3.2870982, 3.271833 ,\n",
-              "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
-              "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
-              "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
-              "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-c5a9fc28-31a5-4b78-bf31-d79210ec1dd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5a9fc28-31a5-4b78-bf31-d79210ec1dd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-549b7c47-68e6-4efb-a142-3cdbc96f31c2' class='xr-var-data-in' type='checkbox'><label for='data-549b7c47-68e6-4efb-a142-3cdbc96f31c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
-              "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
-              "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
-              "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
-              "       -0.04223333, -0.0388    , -0.05338333, -0.0568    , -0.0611    ,\n",
-              "       -0.0627    , -0.07021666, -0.05368333, -0.0487    , -0.0493    ,\n",
-              "       -0.05311666, -0.06443334, -0.04586667, -0.04441666, -0.04498333,\n",
-              "       -0.03575   , -0.03521667, -0.07056666, -0.07609999, -0.0662    ,\n",
-              "       -0.04191666, -0.06681666, -0.06818333, -0.07636666, -0.07111666,\n",
-              "       -0.05511666, -0.0493    , -0.05571667, -0.04891667, -0.04571667,\n",
-              "       -0.04198333, -0.00336667,  0.08048334,  0.25323334,  0.22161667,\n",
-              "        0.19196668,  0.15959999,  0.11676668,  0.09488333,  0.07456666,\n",
-              "        0.05981667,  0.06043334,  0.06175001,  0.05643333,  0.04858334,\n",
-              "        0.06248334,  0.06495   ,  0.07498333,  0.06741667,  0.07038333,\n",
-              "        0.06546666,  0.06541666,  0.06608333,  0.07325   ,  0.0566    ,\n",
-              "        0.054     ,  0.061     ,  0.0511    ,  0.05655   ,  0.02896667,\n",
-              "        0.02978333,  0.04755   ,  0.01526667,  0.00998333,  0.0108    ,\n",
-              "        0.00458333,  0.00831667,  0.00378333, -0.00401667, -0.00796667,\n",
-              "        0.00555   ,  0.01133333,  0.00541667, -0.0047    , -0.0019    ,\n",
-              "       -0.00158333, -0.01193333, -0.00146667, -0.00791667, -0.00841667,\n",
-              "       -0.00898333, -0.00903333, -0.002     ,  0.00205   ,  0.00393333,\n",
-              "       -0.00233333,  0.01098333, -0.01495   , -0.01253333,  0.0059    ,\n",
-              "        0.01675   , -0.0048    ,  0.00353333,  0.00155   , -0.01018333,\n",
-              "        0.00053333, -0.0111    , -0.01913333, -0.02155   , -0.02396666,\n",
-              "       -0.01793333, -0.02523333, -0.0194    , -0.02291666, -0.02203333,\n",
-              "       -0.0282    , -0.02571667, -0.03851666, -0.0208    , -0.03573333,\n",
-              "       -0.02388333, -0.03908334, -0.04381667, -0.031     , -0.04036666,\n",
-              "       -0.02826666, -0.04583333, -0.0394    , -0.03658333, -0.04336667,\n",
-              "       -0.04073333, -0.05656667, -0.0553    , -0.05688334, -0.04293333,\n",
-              "       -0.05556666, -0.05011667, -0.02433333, -0.03963333, -0.04716667,\n",
-              "       -0.05826667, -0.05943333, -0.06553333, -0.04911667, -0.04304999,\n",
-              "       -0.023     , -0.03935   , -0.03393333, -0.04798333, -0.05141667,\n",
-              "       -0.04823333, -0.05695   , -0.05431667, -0.07600001, -0.0419    ,\n",
-              "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
-              "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
-              "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
-              "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-6c2edf8f-5c91-42ea-89ad-21b62c2beb53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c2edf8f-5c91-42ea-89ad-21b62c2beb53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c567dd3-4ec1-4bd5-ac93-c615acab80af' class='xr-var-data-in' type='checkbox'><label for='data-0c567dd3-4ec1-4bd5-ac93-c615acab80af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
-              "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
-              "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
-              "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
-              "       -7.3838835, -7.3748665, -7.3916   , -7.391783 , -7.3853164,\n",
-              "       -7.377949 , -7.3945003, -7.3738666, -7.373867 , -7.369084 ,\n",
-              "       -7.372767 , -7.3854327, -7.3678336, -7.3722672, -7.3625836,\n",
-              "       -7.3666334, -7.360083 , -7.3809   , -7.3875995, -7.3742666,\n",
-              "       -7.3516665, -7.369966 , -7.387017 , -7.386867 , -7.379284 ,\n",
-              "       -7.361167 , -7.3493667, -7.3615665, -7.344417 , -7.350366 ,\n",
-              "       -7.3399496, -7.300467 , -7.236433 , -7.0768504, -6.997516 ,\n",
-              "       -6.949867 , -6.899017 , -6.8814178, -6.8526497, -6.8263836,\n",
-              "       -6.813383 , -6.8076496, -6.78375  , -6.781251 , -6.7671165,\n",
-              "       -6.7577667, -6.7516494, -6.728033 , -6.72715  , -6.716767 ,\n",
-              "       -6.708234 , -6.69495  , -6.6866503, -6.6791   , -6.6603007,\n",
-              "       -6.659384 , -6.6542172, -6.659967 , -6.6461835, -6.667401 ,\n",
-              "       -6.6473837, -6.6366506, -6.6365337, -6.649917 , -6.6360173,\n",
-              "       -6.638784 , -6.6400666, -6.62885  , -6.628683 , -6.617567 ,\n",
-              "       -6.6096334, -6.59625  , -6.589217 , -6.5807333, -6.5850334,\n",
-              "       -6.5764165, -6.5684667, -6.5721836, -6.55585  , -6.5561   ,\n",
-              "       -6.5420327, -6.5459166, -6.5430665, -6.5388503, -6.5341506,\n",
-              "       -6.5321503, -6.52225  , -6.539833 , -6.5372   , -6.528584 ,\n",
-              "       -6.5262337, -6.5375338, -6.5275497, -6.51875  , -6.5324664,\n",
-              "       -6.525267 , -6.548233 , -6.5326   , -6.5178337, -6.5193667,\n",
-              "       -6.505567 , -6.5125165, -6.4989333, -6.508083 , -6.49675  ,\n",
-              "       -6.50315  , -6.4925   , -6.485383 , -6.492067 , -6.4811997,\n",
-              "       -6.4708   , -6.4739504, -6.472566 , -6.4622664, -6.4698668,\n",
-              "       -6.4504333, -6.4621997, -6.4667   , -6.45215  , -6.4554167,\n",
-              "       -6.454716 , -6.461316 , -6.4738665, -6.473217 , -6.458534 ,\n",
-              "       -6.46535  , -6.4565167, -6.4414663, -6.4526324, -6.4590497,\n",
-              "       -6.4487834, -6.4628167, -6.46505  , -6.4660163, -6.4543834,\n",
-              "       -6.4556837, -6.4339333, -6.443283 , -6.4565334, -6.4484835,\n",
-              "       -6.4508667, -6.4604836, -6.4581666, -6.4554834, -6.4470496,\n",
-              "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
-              "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
-              "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
-              "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-6950b35b-71bd-4e77-af5a-edfa6d09ff1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6950b35b-71bd-4e77-af5a-edfa6d09ff1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b5fb35a-3179-4627-941c-9092dcc52a7d' class='xr-var-data-in' type='checkbox'><label for='data-9b5fb35a-3179-4627-941c-9092dcc52a7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
-              "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
-              "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
-              "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
-              "       1023.23627, 1023.24646, 1023.2652 , 1023.2814 , 1023.2947 ,\n",
-              "       1023.3131 , 1023.32043, 1023.33435, 1023.3452 , 1023.3554 ,\n",
-              "       1023.3606 , 1023.366  , 1023.37103, 1023.37616, 1023.38043,\n",
-              "       1023.38403, 1023.3869 , 1023.3915 , 1023.38855, 1023.3802 ,\n",
-              "       1023.3759 , 1023.3691 , 1023.3694 , 1023.3698 , 1023.3653 ,\n",
-              "       1023.3579 , 1023.3548 , 1023.35455, 1023.3548 , 1023.35455,\n",
-              "       1023.3522 , 1023.3529 , 1023.3504 , 1023.3525 , 1023.3523 ,\n",
-              "       1023.3569 , 1023.35583, 1023.35565, 1023.35364, 1023.35455,\n",
-              "       1023.35675, 1023.3567 , 1023.35565, 1023.35364, 1023.35144,\n",
-              "       1023.3499 , 1023.3452 , 1023.347  , 1023.3427 , 1023.3374 ,\n",
-              "       1023.3326 , 1023.32874, 1023.3249 , 1023.3244 , 1023.3244 ,\n",
-              "       1023.3202 , 1023.3271 , 1023.32477, 1023.3281 , 1023.3215 ,\n",
-              "       1023.3281 , 1023.3284 , 1023.3283 , 1023.3299 , 1023.33887,\n",
-              "       1023.3277 , 1023.3379 , 1023.343  , 1023.33966, 1023.35315,\n",
-              "       1023.35333, 1023.34064, 1023.33875, 1023.33   , 1023.3218 ,\n",
-              "       1023.32404, 1023.32294, 1023.30853, 1023.3122 , 1023.3125 ,\n",
-              "       1023.3147 , 1023.3218 , 1023.32446, 1023.3674 , 1023.42395,\n",
-              "       1023.4842 , 1023.5248 , 1023.5321 , 1023.545  , 1023.555  ,\n",
-              "       1023.5453 , 1023.53784, 1023.5425 , 1023.5531 , 1023.56085,\n",
-              "       1023.5671 , 1023.5697 , 1023.5727 , 1023.5777 , 1023.5851 ,\n",
-              "       1023.598  , 1023.61127, 1023.61774, 1023.6253 , 1023.63873,\n",
-              "       1023.6415 , 1023.64105, 1023.6321 , 1023.6085 , 1023.58875,\n",
-              "       1023.55664, 1023.53424, 1023.4919 , 1023.4661 , 1023.4329 ,\n",
-              "       1023.4105 , 1023.3956 , 1023.38354, 1023.3727 , 1023.36206,\n",
-              "       1023.3528 , 1023.34467, 1023.34357, 1023.345  , 1023.34937,\n",
-              "       1023.34894, 1023.3448 , 1023.3418 , 1023.3417 , 1023.3436 ,\n",
-              "       1023.3458 , 1023.3482 , 1023.3505 , 1023.34937, 1023.348  ,\n",
-              "       1023.34607, 1023.3471 , 1023.3476 , 1023.3501 , 1023.3529 ,\n",
-              "       1023.35187, 1023.34894, 1023.3476 , 1023.3455 , 1023.3432 ,\n",
-              "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
-              "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
-              "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
-              "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-69c71a5f-e445-4ea7-8f0c-4ea2adeba256' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69c71a5f-e445-4ea7-8f0c-4ea2adeba256' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c304da2-da73-4cf8-8348-f522cbcc6fc6' class='xr-var-data-in' type='checkbox'><label for='data-1c304da2-da73-4cf8-8348-f522cbcc6fc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
-              "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
-              "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
-              "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
-              "        9.90408  ,  9.8704815,  9.843054 ,  9.8099   ,  9.782674 ,\n",
-              "        9.751141 ,  9.722181 ,  9.688391 ,  9.658139 ,  9.624396 ,\n",
-              "        9.591585 ,  9.559362 ,  9.5206785,  9.487036 ,  9.4516325,\n",
-              "        9.418625 ,  9.378983 ,  9.347703 ,  9.310125 ,  9.274782 ,\n",
-              "        9.240932 ,  9.203833 ,  9.168937 ,  9.127398 ,  9.091378 ,\n",
-              "        9.048801 ,  9.012082 ,  8.96804  ,  8.932783 ,  8.890241 ,\n",
-              "        8.854867 ,  8.815892 ,  8.781367 ,  8.746559 ,  8.714514 ,\n",
-              "        8.678216 ,  8.641088 ,  8.608247 ,  8.566862 ,  8.532115 ,\n",
-              "        8.495453 ,  8.461118 ,  8.42251  ,  8.39378  ,  8.36608  ,\n",
-              "        8.334696 ,  8.308269 ,  8.283072 ,  8.254289 ,  8.228873 ,\n",
-              "        8.203963 ,  8.179552 ,  8.162701 ,  8.144332 ,  8.124536 ,\n",
-              "        8.104092 ,  8.085614 ,  8.068075 ,  8.053603 ,  8.043172 ,\n",
-              "        8.025586 ,  8.014922 ,  8.00194  ,  7.9942083,  7.985075 ,\n",
-              "        7.9840665,  7.978806 ,  7.97339  ,  7.9731627,  7.971814 ,\n",
-              "        7.972329 ,  7.9674144,  7.9723177,  7.9744887,  7.9855638,\n",
-              "        7.991272 ,  7.9956956,  8.006041 ,  8.023605 ,  8.038973 ,\n",
-              "        8.049008 ,  8.066569 ,  8.078107 ,  8.090951 ,  8.110414 ,\n",
-              "        8.1288595,  8.1531725,  8.172004 ,  8.192166 ,  8.219532 ,\n",
-              "        8.241356 ,  8.265544 ,  8.288776 ,  8.314842 ,  8.338862 ,\n",
-              "        8.363347 ,  8.388729 ,  8.418659 ,  8.4457035,  8.479128 ,\n",
-              "        8.511397 ,  8.542225 ,  8.57435  ,  8.609074 ,  8.643846 ,\n",
-              "        8.674181 ,  8.707741 ,  8.740917 ,  8.776131 ,  8.809834 ,\n",
-              "        8.847663 ,  8.883326 ,  8.921983 ,  8.956591 ,  8.994466 ,\n",
-              "        9.032357 ,  9.072943 ,  9.107945 ,  9.147928 ,  9.18505  ,\n",
-              "        9.218539 ,  9.25671  ,  9.293107 ,  9.324933 ,  9.361722 ,\n",
-              "        9.397845 ,  9.436231 ,  9.464766 ,  9.502145 ,  9.534171 ,\n",
-              "        9.566268 ,  9.601108 ,  9.627889 ,  9.660232 ,  9.6932535,\n",
-              "        9.72142  ,  9.752015 ,  9.780852 ,  9.808266 ,  9.838272 ,\n",
-              "        9.864178 ,  9.885547 ,  9.914127 ,  9.934637 ,  9.957427 ,\n",
-              "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
-              "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
-              "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
-              "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-6f8b823e-8ebc-4098-ac88-ef9e421e2501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f8b823e-8ebc-4098-ac88-ef9e421e2501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aee946c4-df3b-4a9d-9731-0c3b3e11590c' class='xr-var-data-in' type='checkbox'><label for='data-aee946c4-df3b-4a9d-9731-0c3b3e11590c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
-              "        0.04634431],\n",
-              "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
-              "        0.03873245],\n",
-              "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
-              "        0.04237254],\n",
-              "       ...,\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan],\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan],\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan]], shape=(28, 183), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39822272-7344-4f67-9029-9ac3bdaf315f' class='xr-section-summary-in' type='checkbox'  ><label for='section-39822272-7344-4f67-9029-9ac3bdaf315f' class='xr-section-summary' >Indexes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-22f50f61-d724-40f0-ba78-70482d1b5863' class='xr-index-data-in' type='checkbox'/><label for='index-22f50f61-d724-40f0-ba78-70482d1b5863' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:30.001030683&#x27;,\n",
-              "               &#x27;2020-08-15 00:27:30.001019239&#x27;,\n",
-              "               &#x27;2020-08-15 00:32:30.001010656&#x27;,\n",
-              "               &#x27;2020-08-15 00:37:30.001015901&#x27;,\n",
-              "               &#x27;2020-08-15 00:42:30.001019954&#x27;,\n",
-              "               &#x27;2020-08-15 00:47:30.001018524&#x27;,\n",
-              "               &#x27;2020-08-15 00:52:30.001013994&#x27;,\n",
-              "               &#x27;2020-08-15 00:57:30.001026630&#x27;,\n",
-              "               &#x27;2020-08-15 01:02:30.001023769&#x27;,\n",
-              "               &#x27;2020-08-15 01:07:30.001024723&#x27;,\n",
-              "               ...\n",
-              "               &#x27;2020-08-15 14:47:30.001032352&#x27;,\n",
-              "               &#x27;2020-08-15 14:52:30.001019239&#x27;,\n",
-              "               &#x27;2020-08-15 14:57:30.001032829&#x27;,\n",
-              "               &#x27;2020-08-15 15:02:30.001021146&#x27;,\n",
-              "               &#x27;2020-08-15 15:07:30.001027345&#x27;,\n",
-              "               &#x27;2020-08-15 15:12:30.001029014&#x27;,\n",
-              "               &#x27;2020-08-15 15:17:30.001026630&#x27;,\n",
-              "               &#x27;2020-08-15 15:22:30.001026153&#x27;,\n",
-              "               &#x27;2020-08-15 15:27:30.001022577&#x27;,\n",
-              "               &#x27;2020-08-15 15:32:30.001030683&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-68d0fa06-2aea-4d10-accd-011823a35690' class='xr-index-data-in' type='checkbox'/><label for='index-68d0fa06-2aea-4d10-accd-011823a35690' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e234f08d-8c57-434a-a27b-ceaea3df8e75' class='xr-index-data-in' type='checkbox'/><label for='index-e234f08d-8c57-434a-a27b-ceaea3df8e75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9f63e293-4cea-4995-829a-d6f2ce67b99d' class='xr-index-data-in' type='checkbox'/><label for='index-9f63e293-4cea-4995-829a-d6f2ce67b99d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
-              "                      2.7,                3.2,                3.7,\n",
-              "                      4.2,  4.699999999999999,  5.199999999999999,\n",
-              "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
-              "        7.199999999999999,  7.699999999999999,                8.2,\n",
-              "                      8.7,                9.2,                9.7,\n",
-              "                     10.2,               10.7,               11.2,\n",
-              "                     11.7,               12.2,               12.7,\n",
-              "                     13.2,               13.7,               14.2,\n",
-              "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-34366b69-9c8f-4bf6-989d-1da3a72d15ab' class='xr-index-data-in' type='checkbox'/><label for='index-34366b69-9c8f-4bf6-989d-1da3a72d15ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-36fbb1ab-b6cc-4322-b1c4-be9a69d327bd' class='xr-index-data-in' type='checkbox'/><label for='index-36fbb1ab-b6cc-4322-b1c4-be9a69d327bd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-235eb738-3773-4f61-a25e-957043df7788' class='xr-index-data-in' type='checkbox'/><label for='index-235eb738-3773-4f61-a25e-957043df7788' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-77db153b-8d36-4e42-8aa1-a218f8b28f07' class='xr-index-data-in' type='checkbox'/><label for='index-77db153b-8d36-4e42-8aa1-a218f8b28f07' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-42bff68f-07ca-47ad-82d7-da6c885d3a03' class='xr-index-data-in' type='checkbox'/><label for='index-42bff68f-07ca-47ad-82d7-da6c885d3a03' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:29.938495159&#x27;,\n",
-              "               &#x27;2020-08-15 00:27:29.938490867&#x27;,\n",
-              "               &#x27;2020-08-15 00:32:29.938487529&#x27;,\n",
-              "               &#x27;2020-08-15 00:37:29.938496828&#x27;,\n",
-              "               &#x27;2020-08-15 00:42:29.938495397&#x27;,\n",
-              "               &#x27;2020-08-15 00:47:29.938496589&#x27;,\n",
-              "               &#x27;2020-08-15 00:52:29.938497781&#x27;,\n",
-              "               &#x27;2020-08-15 00:57:29.938495397&#x27;,\n",
-              "               &#x27;2020-08-15 01:02:29.938493013&#x27;,\n",
-              "               &#x27;2020-08-15 01:07:29.938492536&#x27;,\n",
-              "               ...\n",
-              "               &#x27;2020-08-15 14:47:29.938492774&#x27;,\n",
-              "               &#x27;2020-08-15 14:52:29.938491106&#x27;,\n",
-              "               &#x27;2020-08-15 14:57:29.938495635&#x27;,\n",
-              "               &#x27;2020-08-15 15:02:29.938493013&#x27;,\n",
-              "               &#x27;2020-08-15 15:07:29.938493967&#x27;,\n",
-              "               &#x27;2020-08-15 15:12:29.938494920&#x27;,\n",
-              "               &#x27;2020-08-15 15:17:29.938493251&#x27;,\n",
-              "               &#x27;2020-08-15 15:22:29.938486099&#x27;,\n",
-              "               &#x27;2020-08-15 15:27:29.938484191&#x27;,\n",
-              "               &#x27;2020-08-15 15:32:29.938490390&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2a0b257d-1e4d-415d-9dca-9988fdbf08bb' class='xr-index-data-in' type='checkbox'/><label for='index-2a0b257d-1e4d-415d-9dca-9988fdbf08bb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
-              "                      2.7,                3.2,                3.7,\n",
-              "                      4.2,  4.699999999999999,  5.199999999999999,\n",
-              "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
-              "        7.199999999999999,  7.699999999999999,                8.2,\n",
-              "                      8.7,                9.2,                9.7,\n",
-              "                     10.2,               10.7,               11.2,\n",
-              "                     11.7,               12.2,               12.7,\n",
-              "                     13.2,               13.7,               14.2,\n",
-              "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cea8b836-b914-44c4-b99f-da6161f6f2c3' class='xr-section-summary-in' type='checkbox'  ><label for='section-cea8b836-b914-44c4-b99f-da6161f6f2c3' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, 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&quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
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-            "text/plain": [
-              "<xarray.Dataset> Size: 379kB\n",
-              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-              "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
-              "Coordinates:\n",
-              "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
-              "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
-              "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
-              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
-              "  * beam            (beam) int32 16B 1 2 3 4\n",
-              "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
-              "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
-              "  * q               (q) <U1 16B 'w' 'x' 'y' 'z'\n",
-              "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
-              "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-              "Data variables: (12/38)\n",
-              "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
-              "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
-              "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
-              "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
-              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
-              "    ...              ...\n",
-              "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
-              "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-              "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
-              "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
-              "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
-              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
-              "Attributes: (12/41)\n",
-              "    fs:                        1\n",
-              "    n_bin:                     300\n",
-              "    n_fft:                     300\n",
-              "    description:               Binned averages calculated from ensembles of s...\n",
-              "    filehead_config:           {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"...\n",
-              "    inst_model:                Signature1000\n",
-              "    ...                        ...\n",
-              "    has_imu:                   1\n",
-              "    beam_angle:                25\n",
-              "    range_offset:              0.6\n",
-              "    declination:               15.8\n",
-              "    declination_in_orientmat:  1\n",
-              "    principal_heading:         11.1898"
-            ]
-          },
-          "execution_count": 16,
-          "metadata": {},
-          "output_type": "execute_result"
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+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt; Size: 224B\n",
+       "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])\n",
+       "Coordinates:\n",
+       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
+       "Attributes:\n",
+       "    coverage_content_type:  coordinate\n",
+       "    units:                  m\n",
+       "    long_name:              Profile Range\n",
+       "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;range&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0025dbc2-44e5-46bc-869d-1190c9602df2' class='xr-array-in' type='checkbox' checked><label for='section-0025dbc2-44e5-46bc-869d-1190c9602df2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-96787b9e-7530-4068-862d-b28bdb67e527' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96787b9e-7530-4068-862d-b28bdb67e527' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-39f56f30-fd1a-4676-84cb-9afcfd108d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39f56f30-fd1a-4676-84cb-9afcfd108d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b45e0c4-31f4-4b55-b573-dfb44456c555' class='xr-var-data-in' type='checkbox'><label for='data-5b45e0c4-31f4-4b55-b573-dfb44456c555' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fb59eb1-0655-463e-9953-677ac4364339' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8fb59eb1-0655-463e-9953-677ac4364339' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
       ],
-      "source": [
-        "ds_avg"
+      "text/plain": [
+       "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
+       "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])\n",
+       "Coordinates:\n",
+       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
+       "Attributes:\n",
+       "    coverage_content_type:  coordinate\n",
+       "    units:                  m\n",
+       "    long_name:              Profile Range\n",
+       "    description:            Distance to the center of each depth bin"
       ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 4. Calculate Speed and Direction\n",
-        "\n",
-        "Two additional variables that might be of interest, which are not automatically provided, are the magnitude of the horizontal velocity (referred to as `U_mag` or speed) and its direction (`U_dir`). These can be accessed via \"shortcut\" functions through the keyword `velds`, as demonstrated in the subsequent code block.\n",
-        "\n",
-        "For a comprehensive list of these \"shortcut\" functions, you can refer to the [DOLfYN documentation](https://dolfyn.readthedocs.io/en/latest/apidoc/dolfyn.shortcuts.html)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 17,
-      "metadata": {
-        "scrolled": true
-      },
-      "outputs": [],
-      "source": [
-        "ds_avg[\"U_mag\"] = ds_avg.velds.U_mag\n",
-        "ds_avg[\"U_dir\"] = ds_avg.velds.U_dir"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## Plotting"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "Plotting can be accomplished through the user's preferred package. Matplotlib is shown here for simplicity, and flow speed and direction are plotted below with a blue line delineating the water surface level."
-      ]
-    },
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "range_da = ds[\"range\"]\n",
+    "spacing = range_da.diff(\"range\")\n",
+    "\n",
+    "range_stats = pd.DataFrame(\n",
+    "    {\n",
+    "        \"Statistic\": [\"min\", \"max\", \"mean spacing\", \"max spacing\", \"min spacing\"],\n",
+    "        \"Value\": [\n",
+    "            float(range_da.min().values),\n",
+    "            float(range_da.max().values),\n",
+    "            float(spacing.mean().values),\n",
+    "            float(spacing.max().values),\n",
+    "            float(spacing.min().values),\n",
+    "        ],\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "print(range_stats)\n",
+    "ds.range"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.2. Discard Data Above Surface Level and Surface Interference\n",
+    "\n",
+    "To reduce computational load, we can exclude all data at or above the water surface level, including that affected by surface interference. Since the instrument was oriented upwards, we can utilize the pressure sensor data along with the function `water_depth_from_pressure` to find the water depth. However, this approach necessitates that the pressure sensor was calibrated or 'zeroed' prior to deployment. If the instrument is facing downwards or doesn't include pressure data, the function `water_depth_from_amplitude` can be used to detect the seabed or water surface.\n",
+    "\n",
+    "It's important to note that Acoustic Doppler Current Profilers (ADCPs) do not measure water salinity, so you'll need to supply this information to the function. If `water_depth_from_pressure` is called after `set_range_offset`, \"depth\" represents the distance from the water surface to the seafloor. Otherwise, it indicates the distance to the ADCP pressure sensor.\n",
+    "\n",
+    "After determining the \"depth\", you can use the `remove_surface_interference` function to discard data in depth bins at or above the actual water surface. Be aware that this function will generate a new dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "api.clean.water_depth_from_pressure(ds, salinity=31)\n",
+    "ds = api.clean.remove_surface_interference(ds)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 18,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.colorbar.Colorbar at 0x25a2de98c50>"
-            ]
-          },
-          "execution_count": 18,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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-            "text/plain": [
-              "<Figure size 1000x600 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
+     "data": {
+      "text/html": [
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+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
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+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
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+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
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+       "html[data-theme=\"dark\"],\n",
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+       "  );\n",
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+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 84MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
+       "Coordinates:\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+       "  * range_b5             (range_b5) float64 224B 1.2 1.7 2.2 ... 13.7 14.2 14.7\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
+       "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
+       "Data variables: (12/40)\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    ...                   ...\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+       "    water_density        (time) float32 220kB 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth                (time) float32 220kB 10.28 10.28 10.28 ... 10.16 10.16\n",
+       "Attributes: (12/35)\n",
+       "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
+       "    inst_model:            Signature1000\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
+       "    n_cells:               28\n",
+       "    ...                    ...\n",
+       "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
+       "    coord_sys:             earth\n",
+       "    fs:                    1\n",
+       "    has_imu:               1\n",
+       "    beam_angle:            25\n",
+       "    range_offset:          0.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3b60b78a-3f53-4327-82a3-47a9d97f6e5a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3b60b78a-3f53-4327-82a3-47a9d97f6e5a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3f52280c-ae51-4cbf-8f2d-6ff8e1f0fe68' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f52280c-ae51-4cbf-8f2d-6ff8e1f0fe68' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-d32184a9-e33e-415d-a267-542d575c5d56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d32184a9-e33e-415d-a267-542d575c5d56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c042bb9-eec0-4f21-a04d-80f9c3b639a9' class='xr-var-data-in' type='checkbox'><label for='data-3c042bb9-eec0-4f21-a04d-80f9c3b639a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+       "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
+       "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
+       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-10c3d059-5fe5-4ed8-b774-8ecde1198f83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10c3d059-5fe5-4ed8-b774-8ecde1198f83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f4aefa7-2f3b-4387-a78d-fb6723e950a4' class='xr-var-data-in' type='checkbox'><label for='data-0f4aefa7-2f3b-4387-a78d-fb6723e950a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+       "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
+       "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
+       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-5123f094-c771-40ba-a455-89a460000c29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5123f094-c771-40ba-a455-89a460000c29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f100808e-89c5-4611-974e-89ef10c1e3be' class='xr-var-data-in' type='checkbox'><label for='data-f100808e-89c5-4611-974e-89ef10c1e3be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-d2b47560-9f68-4ddb-9a71-3ae9f877d158' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2b47560-9f68-4ddb-9a71-3ae9f877d158' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ca236a9-821c-46ff-9074-9bddcaa9797b' class='xr-var-data-in' type='checkbox'><label for='data-1ca236a9-821c-46ff-9074-9bddcaa9797b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c439419b-bb03-4daa-9197-a89297d44810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c439419b-bb03-4daa-9197-a89297d44810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-528c857c-7fe8-424c-96b7-5d14b78688a6' class='xr-var-data-in' type='checkbox'><label for='data-528c857c-7fe8-424c-96b7-5d14b78688a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-f1876829-2a3b-4840-9014-19e6e4fd0fc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1876829-2a3b-4840-9014-19e6e4fd0fc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dcce187-8c0c-4dd4-b3fc-6db7314b2437' class='xr-var-data-in' type='checkbox'><label for='data-0dcce187-8c0c-4dd4-b3fc-6db7314b2437' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-aeb36c82-1db9-4419-a089-2f58994b6a0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aeb36c82-1db9-4419-a089-2f58994b6a0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d01d9df4-a49c-4a85-b93f-74a933c67353' class='xr-var-data-in' type='checkbox'><label for='data-d01d9df4-a49c-4a85-b93f-74a933c67353' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-9468b964-5319-40c6-9699-6a3dbed6dcc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9468b964-5319-40c6-9699-6a3dbed6dcc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e43fe00-ab16-4cba-8535-8c975cc836bc' class='xr-var-data-in' type='checkbox'><label for='data-2e43fe00-ab16-4cba-8535-8c975cc836bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-ad5d3f7c-a552-483c-a8a2-dfcabfad2057' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad5d3f7c-a552-483c-a8a2-dfcabfad2057' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11104ddf-2608-4dbe-a625-314637bc4e76' class='xr-var-data-in' type='checkbox'><label for='data-11104ddf-2608-4dbe-a625-314637bc4e76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-f405fe50-ee5c-4064-b0fe-fcac0cea48ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f405fe50-ee5c-4064-b0fe-fcac0cea48ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88b0b5d0-6b0e-4181-a479-40472eabdfdb' class='xr-var-data-in' type='checkbox'><label for='data-88b0b5d0-6b0e-4181-a479-40472eabdfdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-e00a9ca5-e0f8-49da-89ce-f4c7b4e16384' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e00a9ca5-e0f8-49da-89ce-f4c7b4e16384' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c82fe9d4-d230-49cf-89ea-fb7df701c364' class='xr-var-data-in' type='checkbox'><label for='data-c82fe9d4-d230-49cf-89ea-fb7df701c364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-2bf2d2de-3964-4652-b831-2d5fee0968e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bf2d2de-3964-4652-b831-2d5fee0968e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83556ad2-333b-4d99-9c32-d8f485a2ef34' class='xr-var-data-in' type='checkbox'><label for='data-83556ad2-333b-4d99-9c32-d8f485a2ef34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da3721f7-23f0-41c7-befb-6a8e5d98d95f' class='xr-section-summary-in' type='checkbox'  ><label for='section-da3721f7-23f0-41c7-befb-6a8e5d98d95f' class='xr-section-summary' >Data variables: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-04b9eee2-42a0-4d5e-a5d0-de155c7b5c8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04b9eee2-42a0-4d5e-a5d0-de155c7b5c8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b05b2969-59cc-44c3-b89f-d4699f952d17' class='xr-var-data-in' type='checkbox'><label for='data-b05b2969-59cc-44c3-b89f-d4699f952d17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-9b5a6f5d-a7e6-45a6-9f2c-78360b5409ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b5a6f5d-a7e6-45a6-9f2c-78360b5409ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9859d01e-5e61-4d51-9e26-010178406e63' class='xr-var-data-in' type='checkbox'><label for='data-9859d01e-5e61-4d51-9e26-010178406e63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-e360df77-6724-4a52-9fae-09981e6dae73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e360df77-6724-4a52-9fae-09981e6dae73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-210923cc-88d8-4b0e-b8dc-4eb97348da0f' class='xr-var-data-in' type='checkbox'><label for='data-210923cc-88d8-4b0e-b8dc-4eb97348da0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-8a7a903a-315c-4813-a33b-c1632e40fbc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a7a903a-315c-4813-a33b-c1632e40fbc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96153423-1386-4f28-90bc-0bd9ab38e2a5' class='xr-var-data-in' type='checkbox'><label for='data-96153423-1386-4f28-90bc-0bd9ab38e2a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+       "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
+       "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-9ed21429-a052-4aa8-815a-950403f7096b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ed21429-a052-4aa8-815a-950403f7096b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64c500dd-9770-449a-8680-ccf78a2d64b0' class='xr-var-data-in' type='checkbox'><label for='data-64c500dd-9770-449a-8680-ccf78a2d64b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+       "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
+       "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
+       "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
+       "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
+       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-6ce9ff5b-9dfb-4f40-b945-955d259824d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ce9ff5b-9dfb-4f40-b945-955d259824d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc3cca79-0257-4108-80db-6152c622a3d7' class='xr-var-data-in' type='checkbox'><label for='data-cc3cca79-0257-4108-80db-6152c622a3d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-98553162-8a44-4687-b531-88b59e511042' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98553162-8a44-4687-b531-88b59e511042' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-facb0350-434c-40d8-80ec-e03b7a36b532' class='xr-var-data-in' type='checkbox'><label for='data-facb0350-434c-40d8-80ec-e03b7a36b532' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-7058c137-8eb9-439f-9a9c-0a1bb3e7dd69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7058c137-8eb9-439f-9a9c-0a1bb3e7dd69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33e065bd-98a4-4713-bf62-adb0604678d7' class='xr-var-data-in' type='checkbox'><label for='data-33e065bd-98a4-4713-bf62-adb0604678d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-7bcdef99-2f89-4fd7-9b7a-d7a70bc15cac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bcdef99-2f89-4fd7-9b7a-d7a70bc15cac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0237d5dc-01db-489e-ade7-2917e695935e' class='xr-var-data-in' type='checkbox'><label for='data-0237d5dc-01db-489e-ade7-2917e695935e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-3d316c65-e7b9-4c3b-b6fb-82f11f6bf5ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d316c65-e7b9-4c3b-b6fb-82f11f6bf5ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c38da9c-25a1-4552-b304-7a478e4d0fc5' class='xr-var-data-in' type='checkbox'><label for='data-6c38da9c-25a1-4552-b304-7a478e4d0fc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 0.008 ... nan nan nan</div><input id='attrs-5eb905c4-9c12-48f9-90ee-048dc17c61f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eb905c4-9c12-48f9-90ee-048dc17c61f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef4d0a60-551a-4545-8c7b-64f1af4ed635' class='xr-var-data-in' type='checkbox'><label for='data-ef4d0a60-551a-4545-8c7b-64f1af4ed635' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+       "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
+       "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
+       "        ...,\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
+       "\n",
+       "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
+       "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
+       "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
+       "        ...,\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
+       "\n",
+       "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
+       "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
+       "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
+       "        ...,\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
+       "\n",
+       "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
+       "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
+       "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
+       "        ...,\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
+       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 80.5 ... nan nan nan</div><input id='attrs-3a562ab9-056c-4a92-b02c-d12df5163082' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a562ab9-056c-4a92-b02c-d12df5163082' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fa31852-2f6d-4bb3-ae20-b9dd4edea08b' class='xr-var-data-in' type='checkbox'><label for='data-9fa31852-2f6d-4bb3-ae20-b9dd4edea08b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+       "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
+       "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
+       "        ...,\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
+       "\n",
+       "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
+       "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
+       "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
+       "        ...,\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
+       "\n",
+       "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
+       "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
+       "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
+       "        ...,\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
+       "\n",
+       "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
+       "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
+       "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
+       "        ...,\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]],\n",
+       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 87 ... 0 0 0 0 0 0</div><input id='attrs-519d184f-8ef3-45d7-b919-9e3120f09459' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-519d184f-8ef3-45d7-b919-9e3120f09459' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7f62e0a-8031-4949-984f-8c851c9ef55f' class='xr-var-data-in' type='checkbox'><label for='data-e7f62e0a-8031-4949-984f-8c851c9ef55f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+       "        [ 74,  92,  96, ..., 100,  97, 100],\n",
+       "        [100, 100,  99, ...,  99, 100, 100],\n",
+       "        ...,\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
+       "\n",
+       "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
+       "        [ 94, 100, 100, ...,  96, 100,  93],\n",
+       "        [ 99,  95,  97, ...,  98,  98, 100],\n",
+       "        ...,\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
+       "\n",
+       "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
+       "        [ 99, 100,  99, ...,  96,  88,  98],\n",
+       "        [ 97, 100,  98, ..., 100,  99,  97],\n",
+       "        ...,\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
+       "\n",
+       "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
+       "        [100,  93,  93, ...,  96,  96,  97],\n",
+       "        [100, 100, 100, ..., 100, 100,  97],\n",
+       "        ...,\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0],\n",
+       "        [  0,   0,   0, ...,   0,   0,   0]]],\n",
+       "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-fac58596-809d-4cd2-842d-938f8aa3b158' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fac58596-809d-4cd2-842d-938f8aa3b158' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c97b617-4b4a-4164-a3f1-a73476706a9c' class='xr-var-data-in' type='checkbox'><label for='data-3c97b617-4b4a-4164-a3f1-a73476706a9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+       "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
+       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+       "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
+       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
+       "\n",
+       "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
+       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+       "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
+       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+       "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
+       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
+       "\n",
+       "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
+       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
+       "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
+       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
+       "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
+       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-f36da3b8-6c54-471a-977b-a2b10de919ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f36da3b8-6c54-471a-977b-a2b10de919ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43b7c30c-4401-4da9-a124-fcc8d894aa8a' class='xr-var-data-in' type='checkbox'><label for='data-43b7c30c-4401-4da9-a124-fcc8d894aa8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+       "        -0.00292969, -0.00195312],\n",
+       "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
+       "         0.00097656,  0.00097656],\n",
+       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+       "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-ea338374-0cc4-47a6-9dd3-24e7a1907d42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea338374-0cc4-47a6-9dd3-24e7a1907d42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f238500-68d7-47bb-a9f9-614c1bbdb632' class='xr-var-data-in' type='checkbox'><label for='data-3f238500-68d7-47bb-a9f9-614c1bbdb632' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+       "         0.6247864 ,  0.62490845],\n",
+       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+       "        -0.03564453, -0.03561401],\n",
+       "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
+       "        -0.04360962, -0.04360962],\n",
+       "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
+       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-49e97b68-5f8b-4e1a-b389-b7cf4c92156b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49e97b68-5f8b-4e1a-b389-b7cf4c92156b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f25b32ea-65d7-4c86-950d-3cb3f06879af' class='xr-var-data-in' type='checkbox'><label for='data-f25b32ea-65d7-4c86-950d-3cb3f06879af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-208a71ef-adba-43f9-a333-ca1de21ca2b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-208a71ef-adba-43f9-a333-ca1de21ca2b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cf8e297-7cf9-4173-8e1f-a242c5c4275a' class='xr-var-data-in' type='checkbox'><label for='data-6cf8e297-7cf9-4173-8e1f-a242c5c4275a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-988dff58-bb78-4b41-b1fc-2145643890a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-988dff58-bb78-4b41-b1fc-2145643890a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28973660-cf4b-4d55-8108-3e0425072873' class='xr-var-data-in' type='checkbox'><label for='data-28973660-cf4b-4d55-8108-3e0425072873' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+       "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
+       "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-15d6f924-114e-4bf5-be69-8f81b4640295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15d6f924-114e-4bf5-be69-8f81b4640295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7986dd8-1046-4e66-acb4-1672df68237d' class='xr-var-data-in' type='checkbox'><label for='data-f7986dd8-1046-4e66-acb4-1672df68237d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+       "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
+       "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
+       "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
+       "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
+       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
+       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-c7ccfee5-07eb-4fd7-bfb8-7be1b0262b62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7ccfee5-07eb-4fd7-bfb8-7be1b0262b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a141cd7-21aa-48f5-9dc7-3c1a46a6469d' class='xr-var-data-in' type='checkbox'><label for='data-5a141cd7-21aa-48f5-9dc7-3c1a46a6469d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-c18b3666-f050-4de7-b8d1-3df520752621' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c18b3666-f050-4de7-b8d1-3df520752621' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42765d09-47dd-49ed-a8c5-9aa5b63de351' class='xr-var-data-in' type='checkbox'><label for='data-42765d09-47dd-49ed-a8c5-9aa5b63de351' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-2297a980-4a57-41c7-97a4-a0d166f7cd2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2297a980-4a57-41c7-97a4-a0d166f7cd2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32b27170-8cb1-42a9-a1a3-116a4f2dd113' class='xr-var-data-in' type='checkbox'><label for='data-32b27170-8cb1-42a9-a1a3-116a4f2dd113' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... nan nan nan</div><input id='attrs-14ccc856-4363-425d-944d-65678f7370b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14ccc856-4363-425d-944d-65678f7370b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9305015-3a1d-40be-b68d-e6a0dc00cada' class='xr-var-data-in' type='checkbox'><label for='data-c9305015-3a1d-40be-b68d-e6a0dc00cada' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+       "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
+       "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
+       "       ...,\n",
+       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
+       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
+       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 80.5 ... nan nan nan</div><input id='attrs-e7b1334d-b840-4797-a987-e2141dd2cef4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7b1334d-b840-4797-a987-e2141dd2cef4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e71dd98-e434-4165-b485-bbc4c3c9bce9' class='xr-var-data-in' type='checkbox'><label for='data-0e71dd98-e434-4165-b485-bbc4c3c9bce9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+       "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
+       "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
+       "       ...,\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
+       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 100 ... 0 0 0 0 0 0</div><input id='attrs-1f747258-8108-4ae0-9c50-202c7e96b587' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f747258-8108-4ae0-9c50-202c7e96b587' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cd3b67b-c20e-45dc-8c6b-bb769c506bf2' class='xr-var-data-in' type='checkbox'><label for='data-6cd3b67b-c20e-45dc-8c6b-bb769c506bf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+       "       [ 97,  94,  98, ...,  97,  95,  97],\n",
+       "       [100, 100, 100, ...,  93, 100,  96],\n",
+       "       ...,\n",
+       "       [  0,   0,   0, ...,   0,   0,   0],\n",
+       "       [  0,   0,   0, ...,   0,   0,   0],\n",
+       "       [  0,   0,   0, ...,   0,   0,   0]],\n",
+       "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-6aa40778-97f4-43c9-ae4c-f41d70238179' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aa40778-97f4-43c9-ae4c-f41d70238179' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8026d2f-c8d4-4aee-b62b-eaf6ca504e0a' class='xr-var-data-in' type='checkbox'><label for='data-c8026d2f-c8d4-4aee-b62b-eaf6ca504e0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+       "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
+       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+       "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
+       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
+       "\n",
+       "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
+       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+       "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
+       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+       "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
+       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
+       "\n",
+       "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
+       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
+       "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
+       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
+       "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
+       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-3e99d3c9-0836-45b6-8c19-5a576c25383e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e99d3c9-0836-45b6-8c19-5a576c25383e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b20520f-b4ac-42f0-9873-501e3df0f90a' class='xr-var-data-in' type='checkbox'><label for='data-5b20520f-b4ac-42f0-9873-501e3df0f90a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+       "        -0.00195312, -0.00390625],\n",
+       "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
+       "         0.        ,  0.00097656],\n",
+       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+       "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-cc7659cd-127d-486e-ad9b-4b48e25bccbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc7659cd-127d-486e-ad9b-4b48e25bccbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbbae1d3-38b0-44e0-bf12-c4fa3b75e199' class='xr-var-data-in' type='checkbox'><label for='data-cbbae1d3-38b0-44e0-bf12-c4fa3b75e199' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+       "         0.6247864 ,  0.62490845],\n",
+       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+       "        -0.03564453, -0.03561401],\n",
+       "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
+       "        -0.04360962, -0.04360962],\n",
+       "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
+       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-b97d1d40-0461-49a0-bdfc-858bf0e2107b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b97d1d40-0461-49a0-bdfc-858bf0e2107b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23eb80ae-40f4-458c-86de-996156fedae8' class='xr-var-data-in' type='checkbox'><label for='data-23eb80ae-40f4-458c-86de-996156fedae8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-db59adea-502a-4e93-b075-862d98d07eca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db59adea-502a-4e93-b075-862d98d07eca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb33cc15-3200-45c2-801c-97bd960b6d6e' class='xr-var-data-in' type='checkbox'><label for='data-eb33cc15-3200-45c2-801c-97bd960b6d6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-ec918346-f32c-49af-a738-a2176994dfcd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec918346-f32c-49af-a738-a2176994dfcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14c6370c-8658-4a0f-89d1-f8414e1af492' class='xr-var-data-in' type='checkbox'><label for='data-14c6370c-8658-4a0f-89d1-f8414e1af492' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-01031b8b-3f17-4723-9007-125ece6930f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01031b8b-3f17-4723-9007-125ece6930f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85e56225-bd35-4432-aa43-b40cff669b8d' class='xr-var-data-in' type='checkbox'><label for='data-85e56225-bd35-4432-aa43-b40cff669b8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-97a64000-ff17-4b02-9bd3-3910113c801e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-97a64000-ff17-4b02-9bd3-3910113c801e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bba3ff1c-4b69-4066-ac3c-d43a5be0bc21' class='xr-var-data-in' type='checkbox'><label for='data-bba3ff1c-4b69-4066-ac3c-d43a5be0bc21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-50cb20ba-8ec8-4267-81cb-d7ef32bb0b4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50cb20ba-8ec8-4267-81cb-d7ef32bb0b4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7783dd55-36bd-42bd-888d-994093bed229' class='xr-var-data-in' type='checkbox'><label for='data-7783dd55-36bd-42bd-888d-994093bed229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+       "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-2a60a58f-c1cb-4eb8-8c3c-58a6a6500ec7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a60a58f-c1cb-4eb8-8c3c-58a6a6500ec7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b80099b0-39db-4ae0-8da0-e5b94f8cdf41' class='xr-var-data-in' type='checkbox'><label for='data-b80099b0-39db-4ae0-8da0-e5b94f8cdf41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
+       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-ee7339f8-c6b7-4eb1-a036-bbc09bd2e808' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee7339f8-c6b7-4eb1-a036-bbc09bd2e808' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a88c998-b634-4f80-b754-68f424c8f2e4' class='xr-var-data-in' type='checkbox'><label for='data-6a88c998-b634-4f80-b754-68f424c8f2e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+       "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-0e526501-0f6f-4ee2-9d4a-e25e81ded0bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e526501-0f6f-4ee2-9d4a-e25e81ded0bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-795ecf6d-5e93-45c9-a54e-6a4ab24ec042' class='xr-var-data-in' type='checkbox'><label for='data-795ecf6d-5e93-45c9-a54e-6a4ab24ec042' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+       "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
+       "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
+       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-016e0ef0-2457-44cb-b074-88412c61be7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-016e0ef0-2457-44cb-b074-88412c61be7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea536dce-62be-4334-8a4f-ec284ea5ea34' class='xr-var-data-in' type='checkbox'><label for='data-ea536dce-62be-4334-8a4f-ec284ea5ea34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2412 , 1023.2412 , 1023.2412 , ..., 1023.40265, 1023.40265,\n",
+       "       1023.40265], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.28 10.28 ... 10.16 10.16</div><input id='attrs-acaba087-0262-4545-8841-a7c3b4528202' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acaba087-0262-4545-8841-a7c3b4528202' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c149786-bee8-4e55-91c6-288e974957ba' class='xr-var-data-in' type='checkbox'><label for='data-9c149786-bee8-4e55-91c6-288e974957ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.276234, 10.281216, 10.281216, ..., 10.158169, 10.156177,\n",
+       "       10.158169], shape=(55000,), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d3aa7b58-2604-474f-b39a-1f7654920867' class='xr-section-summary-in' type='checkbox'  ><label for='section-d3aa7b58-2604-474f-b39a-1f7654920867' class='xr-section-summary' >Attributes: <span>(35)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd></dl></div></li></ul></div></div>"
       ],
-      "source": [
-        "%matplotlib inline\n",
-        "from matplotlib import pyplot as plt\n",
-        "import matplotlib.dates as dt\n",
-        "\n",
-        "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
-        "# Plot flow speed\n",
-        "t = dolfyn.time.dt642date(ds_avg[\"time\"])\n",
-        "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_mag\"], cmap=\"Blues\", shading=\"nearest\")\n",
-        "# Plot the water surface\n",
-        "ax.plot(t, ds_avg[\"depth\"])\n",
-        "\n",
-        "# Set up time on x-axis\n",
-        "ax.set_xlabel(\"Time\")\n",
-        "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
-        "\n",
-        "ax.set_ylabel(\"Altitude [m]\")\n",
-        "ax.set_ylim([0, 12])\n",
-        "plt.colorbar(label=\"Speed [m/s]\")"
+      "text/plain": [
+       "<xarray.Dataset> Size: 84MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
+       "Coordinates:\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+       "  * range_b5             (range_b5) float64 224B 1.2 1.7 2.2 ... 13.7 14.2 14.7\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
+       "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
+       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
+       "Data variables: (12/40)\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    ...                   ...\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+       "    water_density        (time) float32 220kB 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth                (time) float32 220kB 10.28 10.28 10.28 ... 10.16 10.16\n",
+       "Attributes: (12/35)\n",
+       "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
+       "    inst_model:            Signature1000\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
+       "    n_cells:               28\n",
+       "    ...                    ...\n",
+       "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
+       "    coord_sys:             earth\n",
+       "    fs:                    1\n",
+       "    has_imu:               1\n",
+       "    beam_angle:            25\n",
+       "    range_offset:          0.6"
       ]
-    },
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Visualizing the Depth from the ADCP pressure sensor. This measurement includes any previously applied range offsets. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 19,
-      "metadata": {
-        "scrolled": false
-      },
-      "outputs": [
-        {
-          "data": {
-            "image/png": 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X5x6RwQEclfYcna/JSU5Oxosvvoh27doBAN5//31cd9112LZtG7p06eLWb/GpU6fi22+/xZIlSxAVFYWHH34Yo0ePRmZmJoxG/f4wL4km0q8lSZKiJ0cIgcTEREydOhWPPfYYAFumGBcXh5deegn33HOPW3FLSkpgNptRXFxsH0LaVxRV1GDn8WJsP1aE7dm2R2F5jcN88eGBuKR1K/RvG4WBGTFIiQzWobZERETkC4oranHsdAWOnrYlMHvzSrAntwRZheVOOwJMfgakRgYjMiQAEcG2npakiGC0iQlBm5gQpEeHNKlri5v6779z9Vv57D0ICTRpFre8qhpXz/i/C9ruyMhI/Otf/8Idd9xx3t/ixcXFiImJwYcffoiJEycCAHJzc5GSkoIffvgBI0aM0GzbGqvp7I0qWVlZyM/Px/Dhw+3TTCYTBg0ahA0bNjhNcqqrq1FdXX+xWUlJSYPz+YKI4ABcmRGDKzNiANgSv+zTldiWfQbbs4uw9egZ7M4tQX5JFb7bkYfvduQBANKignFlRjSuaBeD/m2jYA7idT1EREQtUVFFzdkRYIuwI6cYO48XI6+4yun8ceEmtIsNRZvo0LMJTCjaxoTwnoDeIqDx6Wq2/9S/f00mE0wm18mUxWLBf//7X5SXl6N///5u/RbPzMxEbW2tYp7ExER07doVGzZsYJLTkPz8fABAXFycYnpcXByOHj3qdLk5c+Zg9uzZXq2bXiRJQmpUMFKjgnFdzyQAQGWNBduzi/B71mn8evAUth47g6OFFThaeAwfbToGo0FCj2Tz2WQpGj1TIuDH4auJiIianYqaOuw6XoI/sovwx9mk5tjphi/AjwkzIS0yGKmRwWgXF2of9CgqVLteBXKDl67JSUlJUUyeOXMmZs2a1eAiO3fuRP/+/VFVVYXQ0FAsW7YMnTt3xoYNGwC4/i2en5+PgIAAtGrVymGec7/l9dJkk5xz1NeaCCFcXn/yxBNPYNq0afbXJSUlDm90cxIUYET/tlHo3zYKDw3LQFl1HTYdKsS6Ayex7uApHD5Zjq3HirD1WBFe/fkAwkx+6N82CldmROPKjBikRQXzeh4iIiIfU2ex3abij5xi7Mi2JTQHCkphbeD3cuuoYHRLjkCPZDO6JZnRJcmMUFOT/wnYIgiLFULDG5eei5Wdna04Xc1VL06HDh2wfft2FBUV4csvv8SkSZOwZs0ae3ljf4u7O4+3Ndk9PD7edlF+fn4+EhLq70tTUFDgkFHKudMd15yFmvwwrHOcfUS340WVWH/gJNYeOIVfD55CUUUtVuw5gRV7TgAAklsF4erOcRjXMwndk82675BERETUsJKqWqzdfxI/7y3Aqn0FKGpgRLP48EB0TzajR0oEuieb0T0pgrejaMq81JMTHh7u9jU5AQEB9oEHLrnkEmzevBmvvvqq/TocV7/F4+PjUVNTgzNnzih6cwoKCjBgwABNNslTTTbJSU9PR3x8PFauXIlevXoBAGpqarBmzRq89NJLOtfOdyRFBGFi31RM7JsKi1Vgd24x1h04hXUHTiLz6BnknKnE4l+PYPGvR9AmOgRjeiRiWKc4dEkM57m3REREOsovrsLGw6eQefQMMo8WYV9+iaKnJjzQDz1SItAjOcKe2MSFB+pXYWo8nYeQbjiEQHV1tVu/xfv06QN/f3+sXLkSEyZMAADk5eVh165dePnlly+4LhdC1ySnrKwMBw8etL/OysrC9u3bERkZidTUVEydOhUvvPACMjIykJGRgRdeeAHBwcG4+eabday17zIaJHRPjkD35AjcN6QdyqvrsOFQIb75Ixcr9+Tj8KlyvPrzAbz68wFEh5owuEMMRnSJx6D2MQjw43U8RERE3lRTZ8XGw4VYu/8k1h04if0nyhzmaRMTgqs7xWFopzj0TuV1tr5OWAVEQ+cYXkC8xnjyyScxatQopKSkoLS0FEuWLMHq1avx448/QpKk8/4WN5vNuPPOO/Hwww8jKioKkZGRmD59Orp164Zhw4Zptl2e0DXJ2bJlC4YMGWJ/fe5amkmTJuG9997Do48+isrKStx77732GxCtWLHCZ++R09SEmPxwdec4XN05DmXVdVi+Kx8r9uRj/YFTOFVWjS8yc/BFZg7MQf64pls8xnRPRN/0SPjzgEpERKSJsuo6rNl3Est352PVnwUora6zlxkkoFuSGX1bR6JPWiv0TmvFnprmRueenBMnTuDWW29FXl4ezGYzunfvjh9//BFXX301ALj1W3zevHnw8/PDhAkT7DcDfe+993S9Rw7QhO6T4y1NfZz0pqi6zoItR87gp70n8P2OPBSU1g/JHWbywxUZ0RjSIRZXdYpFNEdhISIiapS84kr8tLcAP+05gY2HChU32owJM+GqDrEY2D4Gl7eLQkRwgI419V1N/fffufotf3wSQgK1e4/Lq2ow4sX3m+x2X0xN9poc0o/Jz4jL20Xj8nbRePrazvjtcCG+3p6LlXtP4HR5Df63Kx//25UPgwT0bxuFa7slYmTXeESG8EBMRESkJoTA7twSrNxzAj/tPYHducp7mKRFBWNEl3iM6BKHXimteE1sCyIgoGV/g0Cz7rtoFCY55JLRIGFAu2gMaBeNOVaBHceLsXpfAX7eW4Cdx4vx68FC/HqwEDO+3oUBbaMwpnsihneJ41+eiIioRauus2DjoUL8tPcEft5boLgBpyQBvVNbYVinOFzdORZtY0I5umkLJSwCwqJhkqNhLF/HJIfcZjBI6JkSgZ4pEZg6rD2OFVbg+515+G5HLnbnlpwdte0Unlwm4cqMaFzbPRFXd46DOYhDVxIRUfN3urwGv/xZgJ/3nsDa/SdRXmOxlwX5GzGwfTSGdYrDkI483ZvOaoKjqzUXTHLIY6lRwfj74Lb4++C2yDpVju935OK7HXn4M78Uq/adxKp9JxFgNGBg+2hc2z0BwzrFISyQCQ8RETUfp8qq8eOufHy/Iw+/ZRUqhniOCzdhaKc4XN0pDv3bRiHQX98LsakJYpLjNUxySBPp0SG4/6oM3H9VBg4WlOH7HbYengMFZbaLK/cWIMDPgMHtY+wJTwjvtkxERD7odHkNlu/Ox3c7crHxkDKx6ZwQjmGdbYlN16RwnoZGLgmh8TU5THLs+CuTNNcuNhQPDcvAQ8MysP9EKb47m/AcPlmOFXtOYMWeEzD5GXBVx1iM7p6IIR1jEBzAXZGIiJquoooarNh9At/uyMWGQ4WwyDKb7slmXNstAdd0S0BKZLCOtSSfYxWAhvfJ0TSWj+MvS/Kq9nFhmHZ1GP4xLAN/5pfae3iOFFbYR2kL8jdiaKdYjO6egMEdYtmdT0RETUJxZS1W7jmB73bkYv2BU6iT/YDskhiO0d0TcW23BKRGMbEhz7TUs9V69+7dqPklScI333yDpKQkt5dhkkMXhSRJ6JQQjk4J4Xh4eHvszi3Bdzvy8P3OXGSfrjzb25OHkAAjhnWOw7XdEjCwfQwTHiIiuqhKq2yJzfc78rD2wEnUykar6pQQjtHdbT026dEhOtaSmo0WmuVs374dDz/8MEJDQ887rxACL774Iqqrq887rxyTHLroJElC1yQzuiaZ8djIDth5vNiW8OzIw/GiSny9PRdfb89FeKAfxvdOxi2XpaJdbNj5AxMREXmgrLoOP+89ge925GHN/pOoqau/OWeHuDBcezaxaRd7/h9kRI3RkoeQfuSRRxAbG+vWvK+88kqj4zPJIV1JkoTuyRHonhyBJ0Z1xLbsInx/NuHJL6nCexuO4L0NR3BZm0hM7JuC4Z3jOWABERFdsIqaOvy8twDf78jDqn0FqJYlNm1jQmynonVPQPs4/pGNvKiF9uRkZWUhJibG7fn37NmDxMTERq2DvxapyZAkCb1TW6F3ais8dU0nrDt4Ch9tOoqf957ApsOnsenwaQT578KILnEY1ysJV7SLhp/RoHe1iYjIRwghsPnIGXz6+zH8b1ceqmrrE5v06BCM7p6Aa7snoENcGEdFo4vCluNoObqaZqG8Ki0trVHzp6SkNHodTHKoSTIYJAxqH4NB7WOQW1SJz7dk46ttx3GksAJfbc/FV9tzER0agDE9EjG+VzKH6SQiIqcOnyzDij0n8N8t2Th0stw+PS0qGNd2S8Do7onolMDEhnQgzj60jOcjjh075tZ8qampHsVnkkNNXmJEEKYOa4+HhmZge3YRvtp2HN/uyMOpshos/vUIFv96BG1jQnB9ryRc1zOJw3cSERF2HS/G19uP4+e9BTh8qj6xCQ4wYmyPREzsm4KeKRFMbEhXLfk+Oa1bt27w8yeEsE+XJAl1dXUexWeSQz5DkiT0Sm2FXqmt8PTozlh34CSWbcvFit35OHSyHP9esR//XrEfl7aOxN8uS8WorgkI8OPpbERELUVJVS2+3p6LJb8fw+7cEvt0f6OEy9pEYVTXBIztmYhQXttJTYUAYD3vXI2L5yO2bdvW4HQhBJYsWYLXXnvNrdHXnOGnnHySv9GAqzrG4aqOcSitqsWPu/Lx1fbj2HCoEL8fOY3fj5zGs6F7cfOlKfjrJSns3SEiaqaEENhy1HadzQ8766+zCTAaMLxLHEZ1TcDA9tEIC/TXuaZEjoTVCmHVLsvRMpa39ejRw2HaTz/9hMcffxz79+/Ho48+iunTp3scn0kO+bywQH/89RJbMpNXXInPNmfjk9+OoaC0Gq/9chCv/XIQ3ZLMGNUtHqO7JfKmbUREzUBhWTWWbj2OJZuPKa6zyYgNxY2XpmJ8ryS0CgnQsYZE59dCB1dzkJmZiccffxzr1q3DXXfdhR9++MHt4aWdYZJDzUqC2Xb9zn1D2mH57nx8+vsxbDxUiJ3Hi7HzeDFe/nEf+qVHYsIlKbimWwKCAnizUSIiX1FrseLXg6fw3y05WLEn336jziB/I8b0SMDEvqnoncrrbMiHtPAs5+DBg3jqqafw5ZdfYsKECdizZw/atGmjSWwmOdQs+RsNGN09EaO7J+JUWTWW787HDzvzsOFQIX7LOo3fsk5j1je7MaZnIiZekoLuyWZ+KRIRNUEWq8Cmw4X4bkcuftyVjzMVtfay7slm3Ng3FWN6JPB0NPJJwmp7aBnPV9x7771YtGgRhgwZgi1btqBnz56axpeELw3D4IGSkhKYzWYUFxcjPDxc7+qQznKLKvFlZg4+z8xG9ulK+/SO8WH46yUpGNsjETFhJh1rSEREAHC0sBz/3ZKDLzJzkF9SZZ8eFRKAa7snYGLfFHRJNOtYQ2rKmvrvv3P1WzZpPEICtEvQy2tqcf37S5vsdssZDAYEBgaiY8eOLufbunWrR/HZk0MtSmJEEB4YmoH7hrTDpsOF+HxLNv63Kx9/5pfi2e/24Pnv9+CKjBiM65mIkV3jERzAjwgR0cVSVWvB8t35WPJ7NjYeLrRPjwj2x6iuCRjdPQH90iN5I2hqNlryENIzZ870anz25FCLV1xZi2+2H8fSbcex7ViRfXqoyQ/X9UzETZemomsS/1pIROQtBwtK8env2fhyaw6Kzp6OJknAlRkxmHhJCoZ1joXJj9dQkvua+u+/c/Vbeuv1mvfkjP9wWZPd7ouJf6amFs8c5I9b+7fGrf1b48ipcny9PRdLt+XgaGEFPv7tGD7+7Ri6JoXjpktTMbZHIs/7JiLSQFWtBT/szMOnvx/D5iNn7NMTzIGYcEkKJvRNQVJEkI41JPI+YRUQVg17cjSM5euY5BDJtI4OwUPDMvDAVbbT2T7dnI3lu/Kx63gJnlq2C899txdjeiTgpktTeadsIiIP/JlfgiW/Z2Pp1hyUVNnuZG40SLiqYyxuujQFg9rHwmjgsZVahpY88IC3MckhaoDBIGFAu2gMaBeN0+U1WLo1B5/+brsXw+dbcvD5lhx0jA/DjX1TcH2vZJiD2btDRORMRU0dvtth67WRnxacFBGEG/va7nMWbw7Ur4JEetH4mhxfG0Lam5jkEJ1HZEgA7rqyDe68It1+V+3vd+Thz/xSzPp2D+b8709c2y0BN16air6tW7F3h4jorN25xfj092P4elsuSqttvTZ+BglXd47DjZem4sp20TCw14ZaMnH2oWU8AsAkh8htkiShb+tI9G0diZmju+Cr7cfx6e/H8Gd+KZZusw1c0DYmBLf1b42/XpLMkdmIqEUqq67Dt3/kYsnvx/BHTrF9elpUMCb2TcFf+iQjNoy9NkRAi78XqIOqqioEBmpzfOCvMCIPmIP9MWlAa9zWPw1/5BTj09+O4dsduTh0shwzv9mNuSv345bLUjGpf2vEhvPLnIiaNyEEdh639dp8sz0X5TUWAIC/UcKILvG46dJU9G8TxV4bIgcaZzk+2JVjtVrx/PPP480338SJEyewf/9+tGnTBjNmzEDr1q1x5513ehSXSQ7RBZAkCT1TItAzJQJPj+6Er7Ydx6L1WThSWIH/rDqE/1tzGEM7xWJi3xQMzIjhvR2IqFkpqarF19ttvTa7c0vs09tEh+DGS1NwQ+9kRIXyBstEzrAnB3juuefw/vvv4+WXX8bdd99tn96tWzfMmzePSQ6R3sICbUNR39wvDSv3nMA76w5jy9EzWL77BJbvPoH48EDcclkqbr2sNQcqICKfJYTAtuwiLPn9GL79Iw+VtbZemwA/A67pGo8bL01Fv/RIXp9I5AZhERAGDYeQtvhelvPBBx/grbfewtChQzFlyhT79O7du+PPP//0OC6THCKNGQ0SRnaNx8iu8diXX4rPNmdj2bYc5JdU4d8r9uON1Ydw06WpuPPKdCSYeQ8IIvINxRW1WLYtB0s2Z+PP/FL79IzYUNx4aSrG90pCq5AAHWtI5HvYkwMcP34c7dq1c5hutVpRW1vrcVwmOURe1CE+DP8c0xmPjeqAH3bm4f/WHMaf+aV4Z30WFm84goEZ0fhLnxQM7RSLQH/ezZuImhaLVWDjoUJ8uTUHP+zMQ3Wd7SYcJj8DRndPxE2XpqBPGkeVJPIUkxygS5cuWLduHdLS0hTT//vf/6JXr14ex2WSQ3QRmPyMuL5XMsb1TMLq/Sfx5upD+C3rNFbtO4lV+04iPNAPEy5Jwe1XpPMO30Sku0Mny/DfLTn4attx5JdU2ad3jA/DTZemYlzPJJ52S6QFDiGNmTNn4tZbb8Xx48dhtVqxdOlS7Nu3Dx988AG+++47j+O2mCTn2L5DCAsNtb1w8QcnCc4vDBewOp9Pkv8VXnW7WVlaLdRlyhXYpXXKcD4f+SxJkjCkQyyGdIjFoZNlWLo1B0u3HkdecZW9d+eabgm464p0dE8286+jRHTRVNVa8L9defj0t2z8fuS0fbo5yB9jeiTght7J6JkSweMSuTQ2ZpjidZ2o/91TIyzKMtkPn1pVmVVWpv7lJN8DLZLyV70QtuTbIurcrbKuhMY3A9X0xqIXyZgxY/DZZ5/hhRdegCRJ+Oc//4nevXvj22+/xdVXX+1x3BaT5BA1NW1jQvHIiI6YdnUHrN1/Eu+sP4xfDxbi2z9y8e0fuegQF4a/9EnGdb0SeU8JIvKaP/NLsOT3bCzdmoOSKtsPQ4MEXNUxFn/pk4whHWNh8uPptETewNPVbEaMGIERI0ZoGpNJDpHOjAYJQzrGYkjHWOzOLcaidVn4bmce9p0oxfM/7MWLP/6JoR1jcWv/NFzelncHJ6ILV1FTh+/+yMOnm49h27Ei+/SkiCDc2DcFf70kBfFm/nGFyOt4uprXMMkhakK6JJoxd2JPzBzbBd/tyMUXmTnYdqwIK/acwIo9J9A6Khg390vFuF5J7N0hokY5d8POJZuz8c32XJRV23pt/AwSru4chxsvTcWV7fiHFKKLyWoBrBreQs9qOf88TY3BYHB5GqzF4tlGMckhaoLMQf74W780/K1fGvafKMXHm45i6dbjOFJYgRd++BMv/u9PDGwfg+t7JWF453gEBfBUEiJqWPbpCny9/TiWbTuOQyfL7dNbRwVjYt9U/KVPMmLCeMNOIj3wdDVg2bJlite1tbXYtm0b3n//fcyePdvjuExyiJq49nFhmH1dVzw6siO+3p6LLzKzsfVYEVbvO4nV+04i1OSHa7rFY3zvZFzaOpJ/hSUiFFXU4Pudefhq23FsPnLGPt3kZ8DwLvG4qW8KLmsTxeMFkd6Y5eC6665zmPaXv/wFXbp0wWeffYY777zTo7hMcoh8RIjJDzf3S8XN/VKRdaocy7bmYOm248g5U4nPt+Tg8y05SIoIwvW9knB97yS0jQnVu8pEdBFV1Vrwy58FWLbtOFbvK0Dt2TufSxIwoG0UxvVMwsiu8QgL5NDPRE0Fcxzn+vXrh7vvvtvj5ZnkEPmg9OgQTBveAVOHtceWo2ewdGsOvt+Rh+NFlXh91UG8vuogeqRE4IbeSRjTPZF3ISdqpqxWgd+yTuOrbcfxw648lFbVD5vbOSEc43olYmyPJA4iQNREMclpWGVlJRYsWIDk5GSPYzDJIfJhBoOES9MjcWl6JGaN7YKf9p7A0q3HsWb/SfyRXYQ/sovw7Hd7MKRDLMb3TuJQsETNgBACf+aX4uvtufh6u+0+W+ckmgNxXa8kjOuZhA7xYTrWkojcwSQHaNWqlWLgASEESktLERwcjI8++sjjuExyiJqJQH8jRndPxOjuiThZWo1v/sjFsm052HW8xD4627mb+o3vnYxevKkfkc8QQmB7dhF+3J2P5bvycaSwwl4WFuiHa7slYFyvJF6XR+RjhACEi/vEexLP18yfP1/x2mAwICYmBv369UOrVq08jsskh6gZigkz4c4r0nHnFenYl1+Kpdty8NW24zhRUo2PNh3DR5uOIT06xHb9Tq8kpEQG611lImrA0cJyLN16HEu35SD7dKV9eoCfAYPbx2B87yQM7hCLQH/20BL5opbek1NXV4cjR47gjjvuQEpKiqaxmeQQNXMd4sPwxKhOeHRER2w8VIilW3Pwv135yDpVjrkr92Puyv24rE0kJg9Ix9Wd42DkX4GJdFVcWYvvd+Rh6dYcbDlaPzJaSIARV3WKw8gu8RjcIQYhJn6FE/m6lp7k+Pn54d///jcmTZqkfWzNIxJRk2Q0SLgiIxpXZETj2XF1+HFXPpZuy8GGQ4XYdPg0Nh0+jeRWQZg8oDX+2icF5mCOwER0sVTVWrB630l8+0cuVu49gZo62/krBgm4IiMG43slYXiXOAQH8GubqDlp6UkOAAwdOhSrV6/G5MmTNY3LoyVRCxRi8sMNfZJxQ59k5BZV4uPfjuLj344h50wlnvt+L17+cR+u7hyHG/okYWBGDPyMGt6OmYgA1Cc2P+zMw897T6C8pv6u3h3iwnBDnyRc1zMJceEcGY2o2RJnH1rG8zGjRo3CE088gV27dqFPnz4ICQlRlI8dO9ajuExyiFq4xIggPDKiI+4fkoGvth/H+xuO4M/8Uny/Mw/f78xDTJgJ43om4i99UjhaE9EFcpXYJEUEYVTXeIzrlYQuieEcGISoBWBPDvD3v/8dADB37lyHMkmSYLFYHKa7g0kOEQEAggKMuOnSVNzYNwW7c0vw5dYcfL09FydLq/H2uiy8vS4L3ZLMuKF3Esb2TEIk771D5Jay6jqs+rMAP+7Kx6p9BahQJTbXdIvHNd0S0JMjHhK1PBonOb7Yk2O1aji8nAyTHCJSkCQJXZPM6JpkxhOjOmH1vgJ8uTUHP+8twM7jxdh5vBjP/7AXV3WMxV/7pGBwB57ORqRWXFGLn/aewP925WPtgZP2a2wAJjZEVM9qtT20jOdrPvjgA0ycOBEmk0kxvaamBkuWLMFtt93mUVwmOUTkVICfAcO7xGN4l3icLq/BN9uP44uttnvvLN99Ast3n0CCORA3XZqKiX1TeO0AtWiFZdVYsceW2Gw4eAp11vo/qaZHh2Bk13iM6hqPbklmJjZEBICnqwHA7bffjpEjRyI2NlYxvbS0FLfffjuTnPMRwgpx9m5LEur/6iysqvP8DLK9Q/UlJOTpsaTei2SvHfawhvc44WJPPLL7T8VryVBfZ2tdtXJmN78sDX7KDNkgyUbPktR/iXe+PUJYZHOptsHFHa2sllrZbMp2t9bW3//BUlPuNEaH/lc5LSPvigwJwOTL0zH58nT8mV+CL7bk4MutOcgrrsLclfvx6s8HcFmbSAzrFIdhneJ47x1qEU6UVOHHXfn43648/J51GrK8Bh3iwmyJTbd4dIgLY2LTRPWPHKB4Lf8WU38zui4TsjLn77X6m19yUeZsPvW86vW52tOMDjV3Mp9qf/WTLWdV1VQ+pzq+QRZHUtXMIIvjWNbwc0C57erfUnWS9ew8PtKlwYEHIIRo8PiYk5MDs9nscdwWk+QQkXY6xofj6dGdMX1EB/y4Kx8f/3YUm4+cwa8HC/HrwULM/nYP2seFYlinOAztFIeeKRG8/w41C7UWK/7ILsKGQ4VYva8AW48VKcq7JZntPTZtYkL1qSQR+Qy9e3LmzJmDpUuX4s8//0RQUBAGDBiAl156CR06dLDPM3nyZLz//vuK5fr164dNmzbZX1dXV2P69On49NNPUVlZiaFDh2LhwoVITk52uu5evXpBkiRIkoShQ4fCz68+LbFYLMjKysLIkSMbt0EyTHKIyGOB/kaM65WEcb2SkHWqHD/vPYGVe05gy9Ez2H+iDPtPlGHh6kOICgnAVR1jMbRTHK7MiOZNDMlnWK0Ce/NLsOFgITYcOoXfs04rRkQDgD5prTCqazxGdIlnDyYRNYreSc6aNWtw3333oW/fvqirq8NTTz2F4cOHY8+ePYqhnEeOHInFixfbXwcEKAcfmjp1Kr799lssWbIEUVFRePjhhzF69GhkZmbCaDQ2uO5x48YBALZv344RI0YgNLT+D0MBAQFo3bo1brjhhsZtkAx/aRCRJtKjQ3DXlW1w15VtUFRRg9X7TuKnvSewZt9JFJbX4L+ZOfhvZg4C/AwY0DYKQzvFYVinWCSYg/SuOpGdEAJHCivw68FT2HDoFDYeKsSZilrFPK2C/TGgbTQGtIvC0I5xiDfzWjQi8oy3kpySkhLFdJPJ5HBhPwD8+OOPiteLFy9GbGwsMjMzMXDgQMXy8fHxDa6zuLgYixYtwocffohhw4YBAD766COkpKTgp59+wogRIxpcbubMmQCA1q1bY+LEiQgM1PZYyiSHiDQXERxg7+GpqbNi85HT+GnvCfy09wSyT1di9b6TWL3vJGZ8BXRJDMeg9jG4ol00eqe1QqB/w3/xIfKW/OIqbDh0Cr8eLMTGQ6eQW1ylKA8JMOLS9Ehc3i4a/dtGoVN8OAw8/ZKINOCtJCclJUUxfebMmZg1a9Z5ly8uLgYAREZGKqavXr0asbGxiIiIwKBBg/D888/bBwrIzMxEbW0thg8fbp8/MTERXbt2xYYNG5wmOedMmjTpvPXyBJMcIvKqAD8DLm8XjcvbReOfozvjQEGZLeHZcwLbsouwO7cEu3NLsHD1IQT6G3BpehSu7mQ7tS0xgr08pL2iihpsOmy7fuzXQ6dw+KRysJMAowG9UiNwebtoDGgbhR4pEfDnMOlE5AXeGkI6Ozsb4eHh9ukN9eKoCSEwbdo0XHHFFejatat9+qhRo/DXv/4VaWlpyMrKwowZM3DVVVchMzMTJpMJ+fn5CAgIQKtWrRTx4uLikJ+fr82GeYBJDhFdNJIkoX1cGNrHheHewe1wqqwaa/adxK8HT2H9wVMoKK3G2v0nsXb/Scz4eje6JIZj4Nlenj7s5SEPnSytxu9Zp/F7ViF+yzqNP/NLFeWSZBswYEDbaFzeLgqXpEUiKID7GhF5n4DGPTln/w8PD1ckOe64//77sWPHDqxfv14xfeLEifbnXbt2xSWXXIK0tDR8//33GD9+vPO6OBk17WJhkkNEuokONeGGPsm4oU8yhBDYf6IMq/YV4Kc9J5B57Iy9l+eN1YcQ4GdA39atMKBtNK5oF42uSWaO2EYNOlNeg7UHTmLTYVtSo+6pAYB2saG4vG0UBrSLxmXpUTAH+zcQiYjIu/QeeOCcBx54AN988w3Wrl3rckQ0AEhISEBaWhoOHDgAAIiPj0dNTQ3OnDmj6M0pKCjAgAEDnIXxOiY5RNQkSJKEDvFh6BAfhimD2qKwrBqr953Er4dO4deDp3CipNo+RPW/lu9DeKAf+reNOntKUTTaxoTwPiQtVGlVLXYdL0Hm0dNYte8kth07o7hfjSTZhj3vlx6JfumR6JseiejQ85+6QUTkbXonOUIIPPDAA1i2bBlWr16N9PT08y5TWFiI7OxsJCQkAAD69OkDf39/rFy5EhMmTAAA5OXlYdeuXXj55ZcbvQ1aYZJDRE1SlKqX59DJsrNJzilsPFyIkqo6LN99Ast3nwAARIcGoHOiGZ0TwtEpIQxdEsORHh3K3p5mpqrWgt25JdiRU4SdOcX4I6cIh0+VO3yxd4wPw5UZ0bisje30M/bUEFFTpHeSc9999+GTTz7B119/jbCwMPs1NGazGUFBQSgrK8OsWbNwww03ICEhAUeOHMGTTz6J6OhoXH/99fZ577zzTjz88MOIiopCZGQkpk+fjm7dutlHW3NdZ4EvvvgCq1atQkFBAayqi5SWLl3auI06i0kOETV5kiShXWwY2sWGYdKA1qizWLErtwS/HrT18mw5cganymrs1/OcE+hvQIe4MHRONKN7shndksxoHxeGAD9eRO4rqmot2HrsDDYeKsSGQ4X4I7sIdVbHb/GkiCB0TzbjyowYDO4Qw0EriMgn6J3kvPHGGwCAwYMHK6YvXrwYkydPhtFoxM6dO/HBBx+gqKgICQkJGDJkCD777DOEhYXZ5583bx78/PwwYcIE+81A33vvPaf3yJF76KGH8NZbb2HIkCGIi4vT7KwMSQgtm7bpKSkpgdlsxo7ftiDs7E2GJKn+B46wKm/qJhlkP35UjSxkmaXDGyCL6biHNdzELpteVSavl7WuWrVu93YGg5/y9AyDJPvLpqT+0Sdbv6ouQlhkc6m2QTgfIsRqqZXNpmx3a22l/bmlxvH8+XM69L/KaRm1XFW1FuzNK8GevBLsybX9/2deKSprLQ7zBhgN6JQQhq5JtsSn69nEh6Nn6a+q1oI/80uxM6cIO48XY+fxEuw/UQqLKqmJDg1A9+QIdE82o0dyBLolm3n6GXmsf6TymgH5t5j6qOC6TMjKnH8vq7/5JRdlzuZTz6ten6tfBUaHmjuZT/Xbwk+2nFVVU/mc6vgGWZw61W8Ei6xFa1RlDr8vFGUNxwCAOsn2o9oi6vDHmd9QXFzc6AvwL4Zzv09f7nYtgoza9TRXWmrx6M7vm+x2NyQyMhIfffQRrrnmGk3jsieHiHxeoL8RvVJboVdq/QWPFqvA0cJy7Mkrwa7jJdh1vBg7copQUlWHP3KK8UdOMT7+zTZvgJ8BnRPC0S3JjG5ne3wyYkPhx8RHcxarQH5JFbJPV9geZyqRc7oCe/NLceBEaYO9NHHhJvRvE4UBbW33qUluFcTrr4ioWdC7J6cpMJvNaNOmjeZxm3SSU1dXh1mzZuHjjz9Gfn4+EhISMHnyZDz99NMwGPjjg4icMxoktIkJRZuYUIzungjA1nt67HSFrZcgpxg7coqxK7cYpVV12J5dhO3ZRfblz53q1jYmFG1iQtAmJhRJEUFIMAciOtTEm0GeR1WtBTlnKvFnfn3vWtapcuQWVaLW4vxbODIkwJZsyhLOBHMgkxoiarZ8MC/R1KxZszB79my8++67CArS7lTjJp3kvPTSS3jzzTfx/vvvo0uXLtiyZQtuv/12mM1mPPTQQ3pXj4h8jCRJSIsKQVpUiD3xsVoFjtoTnyLsyCnG7twSlFXX9/io+RkkJLcKQqeE8LMDHYQjOTIICeFBCA/yazE/yGstVmSdKse+/FLb40Qpsk9XIL+kCkUVtU6X8zNISGoVhJRWwUiJDEJyq2C0jQlBt+QIJDKhIaIWhD05wF//+ld8+umniI2NRevWreHvrzx9b+vWrR7FbdJJzsaNG3Hdddfh2muvBQC0bt0an376KbZs2aJzzYiouTAYJKRHhyA9OgRje9QnPlmF5difX4rDp8pxqKAMWYXlyCuqQkFpFeqsAkcKK3CksAL/26W8m3OgvwEJ5iDEhZvO/h+I+HAT4s1BiDcH2nuCmvqob1arQHlNHcqq61BSWYcTJVXIL65CbnGlPbE5dLLMZa9McIAR7ePCbMlgYjgyYkOREhmM+PDAJr/9REQXA5McYPLkycjMzMQtt9yi6cADTTrJueKKK/Dmm29i//79aN++Pf744w+sX78e8+fPd7pMdXU1qqvrL8wvKSm5CDUloubEYJDQNiYUbWNCHcrqLFYUlFbj8Mly7Mkrxt68UvyZX4q84koUVdSiqtbWu5F1yvkAGkaDhNgwE2LDA2EyGiBJtmkBfgaEBfoj1OSH8EA/hJr8EBboh9BAf5j8bPNJkM7+f27MEflrCQYJCA6wLRdi8oNRklBZa0FlrQVV5/6vsaCqzoLCshrkFlUht6gS+SVVKK2qRVl1Hcqq6lBe4zhoQ0NCTX5oHxeKDvHh6BAXivSYUCSYAxEXHojwwJbTq0VE5AkmOcD333+P5cuX44orrtA0bpNOch577DEUFxejY8eOMBqNsFgseP7553HTTTc5XWbOnDmYPXv2RawlEbUkfkYDEiOCkBgRhCsyohVlVbUW5BdXIb+kCidKqpBXbOv9OPf8REkVCkqrYbEK5BXbpjV1fgYJYYF+th6psz1Rya2C0fHsjVuTIjgIABGRp5jkACkpKV4ZCa5JJzmfffYZPvroI3zyySfo0qULtm/fjqlTpyIxMRGTJk1qcJknnngC06ZNs78uKSlBSkrKxaoyEbVggf5GtI4OQevoEKfzWKwCp8qqkV9sS3jqLFZYhIBV2JKk0ipbT8q5XpXSqjqUVtehutZiuzhV2IZWFcJ2saoQ4uz/ttdWq0BFTR3Kqy0oq66DVQgE+RsR6G9EoL8Bgf5GBPkbERRgRHiQP5LPJmzx5kCYg/ztvUchJltPkq0HiUkMEZE3WIXtoWU8X/PKK6/g0UcfxZtvvonWrVtrFrdJJzmPPPIIHn/8cdx4440AgG7duuHo0aOYM2eO0yTHZDLBZGrgfgnCar+Hi/z+NPJ7vgBQDoKv/mKXjeHukClLzu8rowoiX8hpmVDfb0b2Uljr1Ct3sT4ZY4BybbI6Sw7j07t45eJeOK7u/SNJshtCGdT3Aaovk1Tjxct/YB3YskG1QlldVPf6keTt4nAfICcx1PO6KvOQfFsBoG2vSy44JvkOo0FCXLjtdC4iX9RPdV8ZZ9T3OZHc/K5ydT8YxzLnpe6m5o73tJF9NzrEdF6mnM/V2l18T7pYytW86uXk63d8H1zEdPEHDaHYdufrU99Dx+iiLq7u9SMvc3VfHnVbC+ncbz3nv1WaEvbkALfccgsqKirQtm1bBAcHOww8cPr0aY/iNukkp6KiwmGoaKPRCKvVN3ZcIiIiIiJn2JMDl9faX4gmneSMGTMGzz//PFJTU9GlSxds27YNc+fOxR133KF31YiIiIiILgh7cuD07KwL1aSTnAULFmDGjBm49957UVBQgMTERNxzzz345z//qXfViIiIiIguiIC2NwP1wRwHAGCxWPDVV19h7969kCQJnTt3xtixY2E0Gs+/sBNNOskJCwvD/PnzvdaNRURERESkF/bkAAcPHsQ111yD48ePo0OHDhBCYP/+/UhJScH333+Ptm3behT3wq+iJiIiIiKiRjuX5Gj58DUPPvgg2rZti+zsbGzduhXbtm3DsWPHkJ6ejgcffNDjuE26J4eIiIiIqLmyALBomJi4dxvnpmXNmjXYtGkTIiMj7dOioqLw4osv4vLLL/c4LpMcIiIiIiId8HQ12+1fSktLHaaXlZUhICCggSXcw9PViIiIiIh0IjR8+KLRo0fj//2//4fffvvNdoNrIbBp0yZMmTIFY8eO9TgukxwiIiIiIh3wmhzgtddeQ9u2bdG/f38EBgYiMDAQl19+Odq1a4dXX33V47g8XY2IiIiISAct/XQ1IQSKi4vx6aefIjc3F3v37oUQAp07d0a7du0uKDaTHCIiIiIiHVjPPrSM50uEEMjIyMDu3buRkZFxwYmNHE9XIyIiIiLSQUs/Xc1gMCAjIwOFhYXax9Y8IhERERERnZdVCM0fvubll1/GI488gl27dmkal6erERERERHpoKWfrgYAt9xyCyoqKtCjRw8EBAQgKChIUX769GmP4jLJISIiIiLSQUsfeAAA5s+f75W4THKIiIiIiHSg9f1tfCXHmTZtGp599lmEhIQgPT0dAwYMgJ+ftmkJr8khIiIiItKBVWj/8AULFixAWVkZAGDIkCEen5LmSovpyRHCAiEsZ19JsgLV2YuSLO9T9fnVL9/QClydBeneHiesLmIYhGw+F/VwGV+1nHxbJXW+67yNhOy1JElQFsrmVceUzyuUy0mG+l3RYPBzWqamrIvznF0yKmMI+Xvr0C7yuhmdxnTYPlfb7sLhP7a5NZ9w0Qetfh/k8zq8R94g1bdTm+7dvb8+oiakf+QAxWvh5Ll6ilX10ZQd5h2WM8qOyeoy+Wv1p11yMp+a43LuHTdczyW5eOVZTHWZkE1xte2NITl5DgAGF1FdLed8Ts8p1+eqXqr3Qfad4PJ7pRF1kbeLq68cx3rKvqvUMWXfo0L1O0T5Pqh+o0iWs//7xtUpLbUnp3Xr1njttdcwfPhwCCGwceNGtGrVqsF5Bw4c6NE6WkySQ0RERETUlGg9IpqvjK72r3/9C1OmTMGcOXMgSRKuv/76BueTJAkWi2d/3GeSQ0RERESkA6HxKWY+kuNg3LhxGDduHMrKyhAeHo59+/YhNjZW03UwySEiIiIi0kFLPV3tnNDQUKxatQrp6emaDzzAJIeIiIiISAfi7D8t4/maQYMGeSUukxwiIiIiIh1oPSKar4yudjEwySEiIiIi0kFLP13Nm5jkEBERERHpQAjhcihvT+KRDW8GSkRERESkAwuE5g9f8c477+Dw4cNei8+eHCIiIiIiHQih7bDPvtSR89BDD6GqqgpJSUkYMmQIhgwZgquuugqpqamaxGeSQ0RERESkA+vZh5bxfEVRURE2bdqENWvWYNWqVbjvvvtQVVWFtLQ0XHXVVfbEJzEx0aP4THKIiIiIiHTQkoeQ9vf3x5VXXokrr7wSTz/9NGpra7Fp0yasWrUKq1evxqefforq6mrU1dV5FJ9JDhERERGRDlry6WpqFosFNTU1qK6utic36enpHsdjkkNEREREpAMrBKwa9r5oGcvbqqqqsGHDBqxevRq//PILtmzZgjZt2mDgwIG4//77MWjQII9PVQPcTHJKSkoaHTg8PLzRyxARERERtRQt+T45ERERiIuLw9ixY/HQQw9h0KBBiI2N1Sy+W0lOREQEJElyO6gkSdi/fz/atGnjccWIiIiIiJozqwAsGp5jZvWhLKdHjx7Yvn071qxZA0mSYDAYMHjwYERFRWkS3+3T1b744gtERkaedz4hBK655poLqhQRERERUXPXkgce+O2331BeXo5169Zh1apVePnll3HTTTehffv2GDx4MAYNGnRBvTtuJTlpaWkYOHCg25lVmzZt4O/v71GFiIiIiIhagpZ8uhoAhISEYOTIkRg5ciQAoLS0FOvWrcPKlStx9913o6yszLujq2VlZTUq6K5duzyqDBERERFRSyGEgNDwdDUtY11MVqsVmzdvxurVq7Fq1Sr8+uuvKC8vR1pamscxW87oarIx+oSQ3SpJqG6b5OLaI2F1foslV9csKXY4xfqUO6KwWurjGYyqsobnawwhlMtJov7tFy5vH6X6wMgqI4Ryu+VtK0kG5frkbSQptw8G2XJ+JufLOVRNuDefan0SZG1hVH8M5HFcHSxU61Os3/1r2KBqJ6ezqUPKdwp1W8N5mTfI2/7wH9tVhbL1O3zenNdNHlN90HZZZpCvT/X+yRvRocx5PYWr/czN/dPt+QBIBuc94da6KvmMyrKacvtz/9Bo5Spkx69Tm79UlO1etNn+/Of91YqyfTVn7M+j/LoqyvKtO+3Pg6ytFGVVUv1y/kJZzwDUfx5roTwuBUr1n8ca4f6xTpJ95lyNLuTqk+nq025RlRpdRHL7CKLeBV0s6arMXa62XVKVup7Xvfkas353j7SO9XT1XrtXO/VcjdkmPZdzN0Zj9hZ39xFXp0Sp210+p0FVpnjtYuXq5Vyt32i1z+QTWvLNQDdv3my/J8769etRVlaG5ORkDB48GK+99hqGDBmC1q1bexzfoyTn999/x+rVq1FQUACr6of/3LlzPa4MEREREVFL0ZKvyenXrx8SEhIwePBgzJ07F4MHD0a7du00i9/oJOeFF17A008/jQ4dOiAuLk7xV83GjMBGRERERNSSteRrcvbu3YsOHTp4LX6jk5xXX30V7777LiZPnuyF6hARERERtQwWIWDQ8DoaLYej9rbY2FgsWLAAkyZNcri/ZnFxMT744IMGy9zV6JP1DQYDLr/8co9WRkRERERENsIL/3zF66+/jrVr1zaYxJjNZqxbtw4LFizwOH6jk5x//OMf+M9//uPxComIiIiIqP50NS0fvuLLL7/ElClTnJbfc889+OKLLzyO3+gkZ/r06di3bx/atm2LMWPGYPz48YoHERERERGdn1UIzR+NMWfOHPTt2xdhYWGIjY3FuHHjsG/fPsU8QgjMmjULiYmJCAoKwuDBg7F7927FPNXV1XjggQcQHR2NkJAQjB07Fjk5OS7XfejQIWRkZDgtz8jIwKFDhxq1PXKNTnIeeOABrFq1Cu3bt0dUVBTMZrPiQURERERE56d3T86aNWtw3333YdOmTVi5ciXq6uowfPhwlJfX35Lg5Zdfxty5c/H6669j8+bNiI+Px9VXX43S0lL7PFOnTsWyZcuwZMkS+3DQo0ePhsXi/FYARqMRubm5Tstzc3NhMHh+G4xGDzzwwQcf4Msvv8S1117r8UqJiIiIiFo6vYeQ/vHHHxWvFy9ejNjYWGRmZmLgwIEQQmD+/Pl46qmn7Gdsvf/++4iLi8Mnn3yCe+65B8XFxVi0aBE+/PBDDBs2DADw0UcfISUlBT/99BNGjBjR4Lp79eqFr776CpdddlmD5cuWLUOvXr0atT1yjU6PIiMj0bZtW49XSEREREREtqTEquHjXJJTUlKieFRXV5+nJjbFxcUAbL/3ASArKwv5+fkYPny4fR6TyYRBgwZhw4YNAIDMzEzU1tYq5klMTETXrl3t8zTk/vvvxyuvvILXX39d0eNjsViwYMECzJs3D/fdd5+bLemo0UnOrFmzMHPmTFRUVHi8UiIiIiKilk4AEELDx9m4KSkpistJ5syZc/66CIFp06bhiiuuQNeuXQEA+fn5AIC4uDjFvHFxcfay/Px8BAQEoFWrVk7nacgNN9yARx99FA8++CAiIyPRq1cv9O7dG5GRkZg6dSqmTZuGv/zlL262pKNGn6722muv4dChQ4iLi0Pr1q3h7++vKN+6davHlSEiIiIiainO9cBoGQ8AsrOzFUMzm0ym8y57//33Y8eOHVi/fr1DmSRJitdCCIdpau7M8/zzz+O6667Dxx9/jIMHD0IIgYEDB+Lmm2/GpZdeet46u9LoJGfcuHEXtEIiIiIiIvLeNTnh4eGNuonmAw88gG+++QZr165FcnKyfXp8fDwAW29NQkKCfXpBQYG9dyc+Ph41NTU4c+aMojenoKAAAwYMOO+6L7300gtOaBrS6CRn5syZmleCiIiIiKil0freNo2NJYTAAw88gGXLlmH16tVIT09XlKenpyM+Ph4rV660DwJQU1ODNWvW4KWXXgIA9OnTB/7+/li5ciUmTJgAAMjLy8OuXbvw8ssvX/A2earRSQ4REREREV04vUdXu++++/DJJ5/g66+/RlhYmP0aGrPZjKCgIEiShKlTp+KFF15ARkYGMjIy8MILLyA4OBg333yzfd4777wTDz/8MKKiohAZGYnp06ejW7du9tHW9OBWkhMZGYn9+/cjOjraraCpqalYt24d0tLSLqhyRERERETNld49OW+88QYAYPDgwYrpixcvxuTJkwEAjz76KCorK3HvvffizJkz6NevH1asWIGwsDD7/PPmzYOfnx8mTJiAyspKDB06FO+99x6MRuMFbM2FcSvJKSoqwv/+9z+3b/ZZWFjo8uY/REREREQtnVVoPPCAaFws4cb8kiRh1qxZmDVrltN5AgMDsWDBAixYsKBR6/cmt09XmzRpkjfrQURERETUoujdk9OcuZXkWK1Wb9fD64S1DsJad/ZV/XB2Qqi2zVJX/1xS3UZIOO+dUibC6uHyhGw+2YxWZTxFXVSZtWSUxVTXWbEm1XLybZVvGwBh8G9wPtsE+fpU65CtX1K3kSKEi5iqMslQvytK6m2X5O+XuszF+pzNCADC9ZCGbsVp5F9LnMeUtaGL99blNjSmzGH/VCzoosyV+pgOu4Ri/S5uzaVuT1kgSVLXS3JaJkn1XeMC6s+s1OBT23L163NYm2Idqn1XscGqITZl65fXS70WAeX7LhlkdXE4FsiG7VftLwb/QKd1UbSvajmj7JvA6OJzVGk5o5wgm9WCWmdFDsclq2LbVdVUxFC3p/P909Nz2l0tJTl57jif83o6Luc8krLN3D9GNaZu7i7n7vpcxXfVuo7LCRdlja9XQ6+14Dqmq7ZWvrvOyhqzHxs8XJ9ivvMM7+tefNV3sWpe+efdVY+F8z3Cscwg/35QHSMNZ49vwtPv+YtM72tymoJevXo1uC9KkoTAwEC0a9cOkydPxpAhQxoVt9E3AyUiIiIiogsnvPDwNSNHjsThw4cREhKCIUOGYPDgwQgNDcWhQ4fQt29f5OXlYdiwYfj6668bFZejqxERERER6YA9OcCpU6fw8MMPY8aMGYrpzz33HI4ePYoVK1Zg5syZePbZZ3Hddde5HZc9OUREREREpIvPP/8cN910k8P0G2+8EZ9//jkA4KabbsK+ffsaFZdJDhERERGRDni6mm1ktg0bNjhM37BhAwIDbdeaWq1WmEymRsXl6WpERERERDqwQuMhpH0wzXnggQcwZcoUZGZmom/fvpAkCb///jveeecdPPnkkwCA5cuXo1evXo2K61GSc+jQISxevBiHDh3Cq6++itjYWPz4449ISUlBly5dPAlJRERERNTi+F5aoq2nn34a6enpeP311/Hhhx8CADp06IC3334bN998MwBgypQp+Pvf/96ouI0+XW3NmjXo1q0bfvvtNyxduhRlZWUAgB07dmDmzJmNDUdERERE1ELxhDUA+Nvf/oaNGzfi9OnTOH36NDZu3GhPcAAgKCjIfuqauxqd5Dz++ON47rnnsHLlSgQEBNinDxkyBBs3bmxsOCIiIiKiFokpjk1RUZH99LTTp08DALZu3Yrjx497HLPRp6vt3LkTn3zyicP0mJgYFBYWelwRIiIiIqKWREie35+8wXjahbpoduzYgWHDhsFsNuPIkSO46667EBkZiWXLluHo0aP44IMPPIrb6J6ciIgI5OXlOUzftm0bkpKSPKoEERERERG1PNOmTcPkyZNx4MABxSlpo0aNwtq1az2O2+gk5+abb8Zjjz2G/Px8SJIEq9WKX3/9FdOnT8dtt93mcUWIiIiIiFoS4YV/vmbz5s245557HKYnJSUhPz/f47iNTnKef/55pKamIikpCWVlZejcuTMGDhyIAQMG4Omnn/a4IkRERERELQmvybHdJ6ekpMRh+r59+xATE+Nx3EYnOf7+/vj444+xf/9+fP755/joo4/w559/4sMPP4TRaPS4Is4cP34ct9xyC6KiohAcHIyePXsiMzNT8/UQEREREV1MAvXX5Wjy0HuDPHDdddfhmWeeQW1tLQBAkiQcO3YMjz/+OG644QaP43p8M9C2bduibdu2Hq/YHWfOnMHll1+OIUOG4H//+x9iY2Nx6NAhREREeHW9RERERETkff/+979xzTXXIDY2FpWVlRg0aBDy8/PRv39/PP/88x7HdSvJmTZtmtsB586d63Fl1F566SWkpKRg8eLF9mmtW7fWLD4RERERkV40H11Nw1gXS3h4ONavX49ffvkFW7duhdVqRe/evTFs2LALiutWkrNt2zbF68zMTFgsFnTo0AEAsH//fhiNRvTp0+eCKqP2zTffYMSIEfjrX/+KNWvWICkpCffeey/uvvtup8tUV1ejurra/rqhc/yIiIiIiPRmu45Gu5PMfPF0tXOuuuoqXHXVVZrFcyvJWbVqlf353LlzERYWhvfffx+tWrUCYDut7Pbbb8eVV16pWcUA4PDhw3jjjTcwbdo0PPnkk/j999/x4IMPwmQyOR3Jbc6cOZg9e7am9SAiIiIi0poEQIJ23S++0pHz2muvuT3vgw8+6NE6JCFEo5K+pKQkrFixAl26dFFM37VrF4YPH47c3FyPKtKQgIAAXHLJJdiwYYN92oMPPojNmzdj48aNDS7TUE9OSkoKtq9fi7DQ0LNT63cBIayK5SVJNhaDpBqXQVjcrLl6F6tvYkVzW5Xx5HWRVOuWjP71i9VWOl2z+q8B8g+OwT9IUSZ/LUmqOstfq/YQq6XGaT3l22CQ1VkdU1iV7Q7ZclZLrWox+fvlfHd12AYn6z4byPm8rijaRaO/l8jbULU/Ol23ev2NKXN5CPR0m+TtotoGV++LYtWqdSv2LXW9JKdlklQ/AIpw+My6u5z6fZDPq9we5WdAWSZfvzy+OqZ6ffLPjnqfF9Y6+QunZUZTmLLMUl92avMXirI/P6gfzOXnvTWKsj3Vp+3PgyXlvdCKpRz78wBrqKKsTiqrr4vq/Al/1LdFHZTbECjV/+2tTr19bu6fruZyfnR2Pa9FNafBxedIXk9X8dVl8j1JvQca5d9bjficuvrx5OmPIats/a7iu6qnejnhZkzXdVFy9R65G7MxMZwfJZTb5Op7ujHvrau6uYppVP+2USzX8HMAMLoYq8ooO86r6yVvT4vqeGZVfFZUxzr5fEJ9vJacllWh7uy66rC1aAuKi4sRHh7utO56KSkpgdlsRvdWfWE0eHyJvAOLtQ47zmxustt9Tnp6uuL1yZMnUVFRYb/uvqioCMHBwYiNjcXhw4c9WkejW7WkpAQnTpxwSHIKCgpQWlrqUSWcSUhIQOfOnRXTOnXqhC+//NLpMiaTCSaTyWG6ta4W1jrbl7f8R4niBwMA+JnkC7lfWVc/yGTJjPzHjOMPMBfh3Z1R/aNAvq0ufhBB9QNMMsiXUx90nf84c/cngzy+rS7ydavq4jIJkH3BOfyIbHjdtqXkPz6dH7hdJcECLhJkF3Ec55N/GalKXPyAhuTiK9VVmcc8+4Hpql2UM553gpO1OE/QHSM4T3Lkn+FG/VVNvj51QqfYr9V/EHDxo05eF0n1xa+IqTyESwbVHxac1TMgUFGkyInVP1BkL2uF8g8sQrZJVjg/nllVmyffdvX+ov7B4oxWp2R4+uPaxZ6kiuP8h5tjTPm+61mCcDF4+ldn5fY5lnoW07sa09Za1MXTpNFVXVz9ichV8uCYhMsSCxd1cfjF4KLa7tbTqDq2KtpJ1WT+Zw9MUuMHENaJxhfl+EhfTlZWlv35J598goULF2LRokX2S2H27duHu+++u8H757ir0XvA9ddfj9tvvx1ffPEFcnJykJOTgy+++AJ33nknxo8f73FFGnL55Zdj3759imn79+9HWlqapushIiIiIrrYJC88fM2MGTOwYMECe4IDAB06dMC8efMu6B6cje7JefPNNzF9+nTccsst9vGs/fz8cOedd+Jf//qXxxVpyD/+8Q8MGDAAL7zwAiZMmIDff/8db731Ft566y1N10NEREREdPFpnZr4XpqTl5dnzynkLBYLTpw44XHcRvfkBAcHY+HChSgsLMS2bduwdetWnD59GgsXLkRISIjHFWlI3759sWzZMnz66afo2rUrnn32WcyfPx9/+9vfNF0PEREREdHFJglJ84evGTp0KO6++25s2bLFfjrzli1bcM8991zQMNIeX+kUEhKC7t27e7xid40ePRqjR4/2+nqIiIiIiC4u9uS8++67mDRpEi699FL4+9uuLa2rq8OIESPwzjvveBy30UnOkCFDXI5i9csvv3hcGSIiIiKilkI6+0/LeL4mJiYGP/zwAw4cOIC9e/dCCIFOnTqhffv2FxS30UlOz549Fa9ra2uxfft27Nq1C5MmTbqgyhARERERtRQSDJqOBOc7o8o5ysjIQEZGhmbxGp3kzJs3r8Hps2bNQllZWYNlRERERESk1FJ7cqZNm4Znn33W7ev5n3jiCTzyyCOIjIx0ex2apXu33HIL3n33Xa3CERERERE1cy1zEOlXX30VFRUVbs//n//8B0VFRY1ah2a3WN24cSMCAwPPPyMREREREQEa9+T4SpIjhED79u1dXucvV15e3uh1NDrJUd/wUwiBvLw8bNmyBTNmzGh0BYiIiIiIWqaWObra4sWLG71MXFxco+ZvdJITHh6uyLoMBgM6dOiAZ555BsOHD29sOCIiIiKiFqmlXpNzMQYra3SS895773mhGkRERERELUtLTXIuhkYPPNCmTRsUFhY6TC8qKkKbNm00qRQRERERUXNnG0LaqOHDd4eQ1lqje3KOHDkCi8XiML26uhrHjx/XpFJERERERM0de3K8x+0k55tvvrE/X758Ocxms/21xWLBzz//jNatW2taOSIiIiKi5opJjve4neSMGzcOACBJksPFQv7+/mjdujVeeeUVTStHRERERNRc2U5X0+4UM187Xa2urg6BgYHYvn07unbtqmlst5Mcq9UKAEhPT8fmzZsRHR2taUWIiIiIiFqWljmE9Dl+fn5IS0tr8FKYC47d2AWysrI0r8RFYa2FsNbanktG+2QhlI0qWS2yMquyTHKRHcvjqG5sJKx1DS9iVa1bvpysjg7U9ZDVU1ItJyBkVaxVLucXUF8mVHW0yncNoSwTstfqmzjJy1QfNHkXqioiJIN8m5S7paJdrM4/vMoYtns41cdQtZnsrW3Ucop6GVSvZdsnhNN5HW98JXstnLenZFDvE+pWdJd8HcoYym1vzIFSvg1W57M1JqKL9buup4v3QfZeu3qPIDWmbaUGn6rXp/6sSK6Wc7nf1e8HDvuEm++Zus386w8FDn8DlDdFHaqVhUL+mVa1p2yjrKoy+Wuruq093a0VIZzXxXFe56/ky2n1s8HTOM4/tepjqwYNqDN1G13sLXL3dB/1fN5ue/X6XH3GXC2nKGvUcd451+uof+5w3HWxZxsUnz9lfKPk/DvHevYoJnykR6Ol9+QAwNNPP40nnngCH330ESIjIzWL61aS89prr+H//b//h8DAQLz22msu533wwQc1qRgRERERUXNmkIwwuPrDdmPjQZs/NF5Mr732Gg4ePIjExESkpaUhJCREUb5161aP4rqV5MybNw9/+9vfEBgYiHnz5jmdT5IkJjlERERERG7gwAP11/1rza0kR36Kms+erkZERERE1KQY4MFtK88Tz7fMnDnTK3Eb3RLPPPMMKioqHKZXVlbimWee0aRSRERERETNneSFf2TT6CRn9uzZKCsrc5heUVGB2bNna1IpIiIiIqLmToIBkqThw0d6ciIjI3Hq1CkAQKtWrRAZGen04alGj64mhGhwNI4//vhD0xERiIiIiIias5Z6Tc68efMQFhYGAJg/f75X1uF2ktOqVStIkgRJktC+fXtFomOxWFBWVoYpU6Z4pZJERERERM2NLcXRcghp30hyJk2a1OBzLbmd5MyfPx9CCNxxxx2YPXs2zGazvSwgIACtW7dG//79vVJJIiIiIqLmRvMhpDWMdbEUFxdj5cqVOHLkCCRJQps2bTB06FCEh4dfUFy3k5xzWVZ6ejoGDBgAf3//C1oxEREREVHL1rJHV/voo49w//33o6SkRDHdbDbjzTffxMSJEz2O7VZLlJSU2B+9evVCZWWlYpr8QURERERE56fpoANnH75i69atuP322zFu3Dhs27YNlZWVqKiowJYtWzBmzBjceuut+OOPPzyO71ZPTkRERIODDcidG5DAYrF4XBkiIiIiopZD62GffeOaHABYsGABxo0bh/fee08xvXfv3vjggw9QUVGBV199Fe+++65H8d1KclatWuVRcCIiIiIiapgEbYd99pUhpAHg119/xcKFC52WT5kyBffee6/H8d1KcgYNGuRWsO3bt3tcESIiIiKilkTrU8w8ibV27Vr861//QmZmJvLy8rBs2TKMGzfOXj558mS8//77imX69euHTZs22V9XV1dj+vTp+PTTT1FZWYmhQ4di4cKFSE5Odrre3NxctG/f3ml5+/btcfz48UZvzzkX3KrFxcVYuHAhevfujT59+lxoOCIiIiKiFkHywr/GKi8vR48ePfD66687nWfkyJHIy8uzP3744QdF+dSpU7Fs2TIsWbIE69evR1lZGUaPHu3yMpaKigoEBgY6LTeZTKiqqmr09pzT6JuBnvPLL7/g3XffxdKlS5GWloYbbrgBixYt8rgiREREREQtiST5QZI8/jneQDxro5cZNWoURo0a5XIek8mE+Pj4BsuKi4uxaNEifPjhhxg2bBgA26hpKSkp+OmnnzBixAincZcvX664LY1cUVGRexvgRKNaNScnB++99x7effddlJeXY8KECaitrcWXX36Jzp07X1BFiIiIiIhaEkmSND5dzdaTox7x2GQywWQyeRx39erViI2NRUREBAYNGoTnn38esbGxAIDMzEzU1tZi+PDh9vkTExPRtWtXbNiwwWWSc74bgZ5v4DNX3G7Va665Bp07d8aePXuwYMEC5ObmYsGCBR6vmIiIiIioJbMlOdo+ACAlJQVms9n+mDNnjsd1HDVqFD7++GP88ssveOWVV7B582ZcddVVqK6uBgDk5+cjICAArVq1UiwXFxeH/Px8p3GtVut5HxcyarPbPTkrVqzAgw8+iL///e/IyMjweIVERERERAR462ag2dnZCA8Pt0+9kF4c+Q05u3btiksuuQRpaWn4/vvvMX78eKfLnbu9jF7cTnLWrVuHd999F5dccgk6duyIW2+99YLuQnqxWa21sFpqAQCSJMsKVV2EwlpX/xwCqkLZYsqms1pr68sko3Ix0XAW6vDGy+riquvSoUz2Wl5/NXU9hMX5vDA6LxKivl0kSTgtcyDbXslhNqnBpw5FBhcVU7Wnsm6qMnkc9dvgqi5ucrjwT/5Ste2K91O9PsUmeHqgcLWc+22mqozziI3pdncZ0nmjuTpoKobPVFdFvg86xJR9jtRvkpvU77uQnRvtcFyAq/OmZccC9ToMLo4TsnUIofx8y+c1mIIVZf6m+rWoayVkFagTNcqYstqpt0deb4tBdZyQHYrUbW110fZC8Vw4LXO9pPN9Rx3DVUzP9hDvL+c4n6sl3TumOB4JZN8BjWhPF4dB1fvp/rHO0/Z0P777a7jwlm4cd+vmOJ97tVEvJf9sqj+nLt9bN5tQvS8Z5cdBF1X2Ux3ohf17zDfuF+Ot0dXCw8MVSY6WEhISkJaWhgMHDgAA4uPjUVNTgzNnzih6cwoKCjBgwACv1MEdbrdq//798fbbbyMvLw/33HMPlixZgqSkJFitVqxcuRKlpaXerCcRERERUbPSFEZXa6zCwkJkZ2cjISEBANCnTx/4+/tj5cqV9nny8vKwa9cu30hyzgkODsYdd9yB9evXY+fOnXj44Yfx4osvIjY2FmPHjvVGHYmIiIiImh/JoP2jkcrKyrB9+3b7/S6zsrKwfft2HDt2DGVlZZg+fTo2btyII0eOYPXq1RgzZgyio6Nx/fXXAwDMZjPuvPNOPPzww/j555+xbds23HLLLejWrZt9tDU9XFD/WIcOHfDyyy8jJycHn376qVZ1IiIiIiJq9gwGo+aPxtqyZQt69eqFXr16AQCmTZuGXr164Z///CeMRiN27tyJ6667Du3bt8ekSZPQvn17bNy4EWFhYfYY8+bNw7hx4zBhwgRcfvnlCA4OxrfffgujsfH10YomA3MbjUaMGzdOcXdUIiIiIiJywcPeF5fxGmnw4MEur6levnz5eWMEBgZiwYIFTWrkZe3uPkRERERERG6TYFAOmKNBPF/QqlUrt0deO336tEfrYJJDRERERKQD+b1ttIrnC+bPn+/1dTDJISIiIiLSgyRpfLqabyQ5kyZN8vo6fKNPi4iIiIiomTnXk6PlwxcdOnQITz/9NG666SYUFBQAAH788Ufs3r3b45hMcoiIiIiIdCAZjJo/fM2aNWvQrVs3/Pbbb1i6dCnKysoAADt27MDMmTM9jsskh4iIiIhID03gPjl6e/zxx/Hcc89h5cqVCAgIsE8fMmQINm7c6HFcXpNDRERERKQLSePraHzvdLWdO3fik08+cZgeExODwsJCj+P6XrpHRERERNQMSJJB84eviYiIQF5ensP0bdu2ISkpyeO4vtcSRERERETNgSRp//AxN998Mx577DHk5+dDkiRYrVb8+uuvmD59Om677TaP4zLJISIiIiLSAXtygOeffx6pqalISkpCWVkZOnfujIEDB2LAgAF4+umnPY7La3KIiIiIiPSgde+LD/XkjBs3DnfddReuueYafPzxx3j22WexdetWWK1W9OrVCxkZGRcUn0kOEREREZEOJIMBkkG73hdJ+E5PTmVlJcaNG4fY2FhMnjwZd9xxB/7yl79oFt93WoKIiIiIqDkxSIDBoOHDd3pyli9fjiNHjuDvf/87Pv/8c3To0AEDBw7EBx98gMrKyguO32J6coSlFsJSa3shO19RMvor54Oof261KIPIugAlVdPJ55WMLm7EJD9XUlhV4WXLqW7mJBnr1yesdS7Cq95S2bxCKLfHVRxVUOVreb2F8sOkuNOuw+dMXqYuFLK5VOuTzSugajNXMYWQlaljCjglDyNczOewnIt6KtaviinfHx0azcU2qOMoiuTLNeKA5+lyivdMue2uY7q5Plfvg8NyijdQNav8c6Wqp+J9aMT7rlif6vOgeK18/1xtruv9xfk+r7zTtXJ9ArJjVECgosw/sH45o6u3QVIdQ+THS8mqnru+JkJ5PLPKl3NYynnbW918Xxxj1lO/t0JV6qzMcc3O69KYvUcLruvpnHxr1W2r3pOV63NW4v57qz7Wqd8Vd7ma0xvvg6t6WhXb53w5V/uSY7s4L3M2n+21e8dvIZxvkSS5+jw4X87VZ1hdojxaq4/X8vlctItqU01nf58ZL/YH0VMt+HQ1AEhOTsaMGTMwY8YMrFq1Cu+++y7uvfdePPDAA7jxxhtxxx13oF+/fh7FbjFJDhERERFRUyJJkkNCeaHxfNWQIUMwZMgQlJaW4pNPPsGTTz6JRYsWoa7OzT/KqzDJISIiIiLSQwvvyVE7fPgw3nvvPbz33nsoLi7GsGHDPI7FJIeIiIiISA9MclBZWYn//ve/WLx4MdauXYvU1FTcdddduP3225GSkuJxXCY5RERERER6kAwNXHN7gfF8xIYNG7B48WJ8/vnnqKmpwbhx47B8+fIL6r2RY5JDRERERKQHowGSUcvExHeSnCuuuAI9evTA888/j7/97W9o1aqVpvGZ5BARERER6aEFn662ZcsW9O7d22vxmeQQEREREelC4yTHzeHDmwJvJjgAkxwiIiIiIn204J4cb2OSQ0RERESkA8kgQTJoeJ8cDWP5OiY5RERERER6YE+O1zDJISIiIiLSg8Fge2gZjwAwySEiIiIi0ocEbccK8JGOnF69ekFys9dp69atHq3Dp5KcOXPm4Mknn8RDDz2E+fPn610dIiIiIiLPGSTbQ8t4PmDcuHFeX4fPJDmbN2/GW2+9he7du+tdFSIiIiKiC9dCr8mZOXOm19fhEyfulZWV4W9/+xvefvttze+GSkRERESkCwn1iY4mD703qOnwiSTnvvvuw7XXXothw4add97q6mqUlJQoHkRERERETY0kSZo/fI3FYsG///1vXHrppYiPj0dkZKTi4akmn+QsWbIEW7duxZw5c9yaf86cOTCbzfZHSkqKl2tIREREROSBc9fkaPnwMbNnz8bcuXMxYcIEFBcXY9q0aRg/fjwMBgNmzZrlcdwmneRkZ2fjoYcewkcffYTAwEC3lnniiSdQXFxsf2RnZ3u5lkREREREHmCSg48//hhvv/02pk+fDj8/P9x0001455138M9//hObNm3yOG6THnggMzMTBQUF6NOnj32axWLB2rVr8frrr6O6uhpGo1GxjMlkgslkcoglrFYIq8X2QpbaqXcFSZLFk6we1VuSlLmjkL2W5Gs0+CuXM9a/lgzKt0aS/JyWAUI+p9N6WevqlEtZap3Oa28rVb1sdalfhxDCaZm6LvJtVy6lmldyWnKeC+qcL6heSrh70qqHxwp1d7Fi29XVlM+rak/5vOqY8rZ32D6X2+6CJI+pWp98Nofl5Nug3v9d1MVl+8rW6OJ9V9fT5byyz6J6H3D1ykmtHOd0eI9kn30XZa7fFXXN5Mup/04lOZlPtQ6hPLYFBNcf9yyqqhhlb1Kd0aIoE4qYzv9mJqneaKvs2GpVLWaVVcDgsA+62gtFA8/OvpYfdlWFVvn+qfr8WRXrUH02FW2trol79XT8jLnYBpdlrl453warosT95eSv1d+SrupiVbSZek73vsccPynO20VeN1fHQdffKs7fI1fHSFesqjmNiu9G51HUZfL1O8Z0Xi+rcN5mindd/XmQFTq+7+5uvWfLqd8jg4u/0Z+b1+rynW1CWujAA3L5+fno1q0bACA0NBTFxcUAgNGjR2PGjBkex23SSc7QoUOxc+dOxbTbb78dHTt2xGOPPeaQ4BARERER+Q6NkxxfSe5kkpOTkZeXh9TUVLRr1w4rVqxA7969sXnz5gY7LtzVpJOcsLAwdO3aVTEtJCQEUVFRDtOJiIiIiHyKAdpePNKkL0Rp2PXXX4+ff/4Z/fr1w0MPPYSbbroJixYtwrFjx/CPf/zD47hNOskhIiIiImq2eLoaXnzxRfvzv/zlL0hJScGvv/6Kdu3aYezYsR7H9bkkZ/Xq1XpXgYiIiIjowjHJwdq1azFgwAD4+dnSkn79+qFfv36oq6vD2rVrMXDgQI/i+mCnFhERERFRMyB54eFjhgwZgtOnTztMLy4uxpAhQzyO63M9OUREREREzYLRYHtoRT1kpQ8QQjR4E9PCwkKEhIR4HJdJDhERERGRHrTuffGhnpzx48cDsN1iYfLkyYqR1CwWC3bs2IEBAwZ4HJ9JDhERERGRHlrwNTlmsxmArScnLCwMQUFB9rKAgABcdtlluPvuuz2OzySHiIiIiEgPLbgnZ/HixQCA1q1bY/r06Rd0alpDmOQQEREREelAkqQGr0e5kHi+ZubMmV6J63tXJxERERERNQcGSfuHjzlx4gRuvfVWJCYmws/PD0ajUfHwFHtyiIiIiIj00IJPVztn8uTJOHbsGGbMmIGEhATNeqOY5BARERER6UHr3hcf7MlZv3491q1bh549e2oal0kOEREREZEeWvDoauekpKRACKF5XF6TQ0RERESkBwm2X+NaPXwvx8H8+fPx+OOP48iRI5rGZU8OEREREZEe2JODiRMnoqKiAm3btkVwcDD8/f0V5adPn/YoLpMcIiIiIiI9cOABzJ8/3ytxW0ySYxuHvIGz81TTDH4B9ueWWotyXmF1Ht8gG+JOlUVLUn2ZZKzPTiWDsvklg0G2jKpMNoSeJJQZrqJeDhl8/TmOkkVZZrXWwRn5yBbqdhPyMvXQfvIy9SdNUeawRqd1Ucylfg8U2+t829Vl7h8D1OeIShdc5nLbJeGsxHEpF3+tcbmc4pWrbWhMm7naBk/fBxfn58rP3W3oc22Pr16D/DPm2fm/kss2U5UoitTHBdlrh2OLi5aRH08k9bvp/HMrb0+/4AhFSUhSqP15gFSpKDPKYhpV1bTK1i9U7al414WLvU5VZpWVGlTtYFW8dP/9E7J5rS4+N0JdJNvP1GWSvMxFHEl1nrm8zOBwDnp9oVW9f7q5uVaHzXO+oHz96uXU9VZEdLF9rsj3EYfNc9Euzo8gDW2vrEwWx/FY0HD885XKPwKO3zgu2kz+3rqYz9Pfpw77IESDzwFA/svGoT1drMPo4nvMIpyvTxlfWab+jLvL1bet8exn3NVnvUlhTw4mTZrklbi8JoeIiIiISA9aXo9z7tFIa9euxZgxY5CYmAhJkvDVV18pyoUQmDVrFhITExEUFITBgwdj9+7dinmqq6vxwAMPIDo6GiEhIRg7dixycnLcroPFYsGXX36J5557Ds8//zyWLVsGi8Vy/gVdYJJDRERERKSHJnAz0PLycvTo0QOvv/56g+Uvv/wy5s6di9dffx2bN29GfHw8rr76apSWltrnmTp1KpYtW4YlS5Zg/fr1KCsrw+jRo91KVA4ePIhOnTrhtttuw9KlS/HFF1/glltuQZcuXXDo0KFGb885LeZ0NSIiIiKiJsVL1+SUlJQoJptMJphMpgYXGTVqFEaNGtVgmRAC8+fPx1NPPYXx48cDAN5//33ExcXhk08+wT333IPi4mIsWrQIH374IYYNGwYA+Oijj5CSkoKffvoJI0aMcFnlBx98EG3btsWmTZsQGRkJACgsLMQtt9yCBx98EN9//73bmy/HnhwiIiIiIh3YrhnX9gHY7j1jNpvtjzlz5nhUv6ysLOTn52P48OH2aSaTCYMGDcKGDRsAAJmZmaitrVXMk5iYiK5du9rncWXNmjV4+eWX7QkOAERFReHFF1/EmjVrPKo3wJ4cIiIiIiJ9eKknJzs7G+Hh4fbJznpxzic/Px8AEBcXp5geFxeHo0eP2ucJCAhAq1atHOY5t7wrJpNJcerbOWVlZQgICGhgCfewJ4eIiIiISA+SFx4AwsPDFQ9Pkxx7NdWjeQrhcpRXd+cBgNGjR+P//b//h99++w1CCAghsGnTJkyZMgVjx471uM5McoiIiIiI9CChfhhpTR7aVi8+Ph4AHHpkCgoK7L078fHxqKmpwZkzZ5zO48prr72Gtm3bon///ggMDERgYCAuv/xytGvX7oLuocMkh4iIiIhID0ZJ+4eG0tPTER8fj5UrV9qn1dTUYM2aNRgwYAAAoE+fPvD391fMk5eXh127dtnncSUiIgJff/019u/fjy+++AL//e9/sW/fPixbtgwREREe153X5BARERER6cFL1+Q0RllZGQ4ePGh/nZWVhe3btyMyMhKpqamYOnUqXnjhBWRkZCAjIwMvvPACgoODcfPNNwMAzGYz7rzzTjz88MOIiopCZGQkpk+fjm7dutlHW3Nl7dq16NixI9q1a4d27drZp9fW1mLjxo0YOHBg4zcKTHKIiIiIiPSj8SlmjbVlyxYMGTLE/nratGkAgEmTJuG9997Do48+isrKStx77704c+YM+vXrhxUrViAsLMy+zLx58+Dn54cJEyagsrISQ4cOxXvvvQej0Xje9Q8ePBhxcXFYunQp+vfvb59++vRpDBkyxOObgjLJISIiIiLSgXzYZ63iNdbgwYMhhHAZc9asWZg1a5bTeQIDA7FgwQIsWLCg0esHgBtvvBFDhw7FwoULMXnyZPt0V/U6HyY5RERERER6aAKnq+lNkiQ88cQTuPLKKzFp0iTs2LEDr7zyir3MUxx4gIiIiIhID14aQtqXnOutGT9+PNauXYsvvvgCo0aNQlFR0QXFZZJDRERERKQHTYePPvvwYb169cLvv/+OoqIiDB069IJiMckhIiIiItKBZNT+4WsmTZqEoKAg++v4+HisWbMGQ4cORWpqqsdxeU0OEREREZEeeE0OFi9e7DDNZDLh/fffv6C4THKIiIiIiPSg9SlmPnK62o4dO9C1a1cYDAbs2LHD5bzdu3f3aB1McoiIiIiI9NBCe3J69uyJ/Px8xMbGomfPnpAkSTFc9LnXkiTxPjnnIxn9IRn9HaYbjAEO89nLrMpGtVpq5AsqlxPW+ucGVbNK9Zc+Gfzq1ydJfqrZZJdIqTJxSXaSpUG1HcJqhVMuzs0Ullqn65PXWUh1qiJXu40sjsNfE1x98tz8VErqy8g0iOl6hZqUCaclyjJ1qeR0Pq2OY55FcTVqveQQ0wvvg+yly3ZR7S/K98H998hlXbSYV/VZkX+iHfZ4xbzub5+8Lgb/QEVJQGykLP4p1VL1yxmFcn1WSVZToWpP2awGq7KszlhfU6NVeZCSx1TfHkHItrAxnwf56g2qoC4/m672MzffWuFiPqsqiLxuQrVG9bxOY7o8ojhfv3p9ruotn9MgqT9Hzo8OivfBzXqpY6r3a/X2yhlcbJ+cpN7PXBx45S/VP7tc7S/ynVndtkLxvrt6x5xvg8P+4uKzApdlztcmPy5Z1R9O2efW1XecRbWc8j1ShZRFcvW+q8sMZ18bNPqW9LYW2pGDrKwsxMTE2J97Q4tJcoiIiIiImpQW2pOTlpYGAKitrcWsWbMwY8YMtGnTRtN1cHQ1IiIiIiI9tPAhpP39/bFs2TKvxGaSQ0RERESkA8mg/cPXXH/99fjqq680j8vT1YiIiIiI9NBCT1eTa9euHZ599lls2LABffr0QUhIiKL8wQcf9CgukxwiIiIiIh1IkqQaUObC4/mad955BxEREcjMzERmZqaiTJIkJjlERERERD7H9/ISTXF0NSIiIiKiZkTr62h88ZocuXNDqmvRI+XjTUFERERE5KMkLzx80AcffIBu3bohKCgIQUFB6N69Oz788MMLismeHCIiIiIiHUgGCZJBw2tyNIx1scydOxczZszA/fffj8svvxxCCPz666+YMmUKTp06hX/84x8exWWSQ0RERESkB46uhgULFuCNN97AbbfdZp923XXXoUuXLpg1axaTHCIiIiIiX6L1/Tt9cHA15OXlYcCAAQ7TBwwYgLy8PI/j8pocIiIiIiI98JoctGvXDp9//rnD9M8++wwZGRkex2VPDhERERGRDtiTA8yePRsTJ07E2rVrcfnll0OSJKxfvx4///xzg8mPu5jkEBERERHpgVkObrjhBvz222+YN28evvrqKwgh0LlzZ/z+++/o1auXx3GZ5BARERER6YA5jk2fPn3w0UcfaRqTSQ4RERERkQ5a8s1AS0pK3JovPDzco/hMcoiIiIiIdNCSe3IiIiIguaiwEAKSJMFisXgUv8UkOQb/EBgDQgAAQtQ3lsHPpJhPMvjLntcpYwghK3PedJLRX/laHsMvwEkJIEl+TkpU1OuWrPXPZXW0xalP6eXbZptQ63Q5AausSLlzSZKsjST1Nsj/hKD+c4KLHdlpiZr7n15XMeVR3J3vfPO6Ws4qW1JSlQqXZc6532be52obXLW16zL33mvX7XBx27Nx2yd/7nyfsKrKDLLPlTqmq/0Mss+0wT9IGTMk1P7cT1Kvr/61nyqm7AjisDbJapSVGRVlRmv9McwglMcli6FKVmZVlFkl+XPl1huEi+OLfDmnczVuH3A1r7xururlaq+wqhaThPM1yme1qg678mZybDPnZcr5lJWRz+uiWlBvulBsr/N2UW+rPI5BVSbfXqFqT/mshkbUU87iokxdZJG1i0NzSg3P5xipEXuhbAPVMeXtpN7nXf2hX37cqFMtKd8P1G0tCfe6D6yq5eSvPf/8NaVvQw+04PvkrFq1yv5cCIFrrrkG77zzDpKSkjSJ32KSHCIiIiKipkSSJJe9GZ7E8xWDBg1SvDYajbjsssvQpk0bTeIzySEiIiIi0oPGp6v5Uk+OtzHJISIiIiLSCxMTr2CSQ0RERESkg5Y88EBDtDzdjkkOEREREZEODAbbQ8t4vmL8+PGK11VVVZgyZQpCQkIU05cuXepRfCY5RERERER6aMFdOWazWfH6lltu0TQ+kxwiIiIiIh204BwHixcv9mp8JjlERERERDpoyUmOtzHJISIiIiLSAZMc72GSQ0RERESkAyY53sMkh4iIiIhIB5LB9tAyHtkwySEiIiIi0oEkSZreG0bLWL6uSed7c+bMQd++fREWFobY2FiMGzcO+/bt07taREREREQX7Nzpalo+yKZJJzlr1qzBfffdh02bNmHlypWoq6vD8OHDUV5ernfViIiIiIguCJMc72nSp6v9+OOPiteLFy9GbGwsMjMzMXDgQJ1qRURERER04TjwgPc06SRHrbi4GAAQGRnpdJ7q6mpUV1fbX5eUlHi9XkREREREjcUkx3ua9OlqckIITJs2DVdccQW6du3qdL45c+bAbDbbHykpKRexlkRERERE7uHpat7jM0nO/fffjx07duDTTz91Od8TTzyB4uJi+yM7O/si1ZCIiIiIyH0GSYLBoOGDWY6dT5yu9sADD+Cbb77B2rVrkZyc7HJek8kEk8nkMN3gHwiDf5DthbDYp0tGf8V8ksEoK1M1j2zwcYNqOSFbzmAMUC0neyr5y56rd0T3ck4Jkup1/XJCEqq5618b/JT1slpq6uey1iljygdaVw+6rihT1UXefqoy4eT5hRCySOp2sWqwFvU75GlE4ebWO67PszWq28JZTPV8rsrcpa6zpCiDR2Wu1+d8OVf7hKv31uBhuzi+X/XzqvdHg6qmzuMol7O6uX6rqsygPBApyvzC608BDjS6ajPn65aE8jghof5YYFR91Rhk88rnA4A6qcr+3OJwPKtfzmhV1dMgO66r6yKfVxVTSFZZkfNjsHy+sxOcxjRa67fXql5OUTHlchZZWwv1vmtwHkfxvgjnx12jVdnW8jaT11lN/S4YZRNcbZ+kqov8tUN7ytpCuPjwW1Rl8vdMvT4h2z7H5Zyvw8Vbq57T6XIO22CVfTZdBHW3Xuq1qz4OqFPsS86PIQaH9TmvZ52of88cPpuyl66OE+rjoEW42GBZGPVy7hzntfgNcDHwdDXvadJJjhACDzzwAJYtW4bVq1cjPT1d7yoREREREWmGeYl3NOkk57777sMnn3yCr7/+GmFhYcjPzwcAmM1mBAUF6Vw7IiIiIiLPsSfHe5r0NTlvvPEGiouLMXjwYCQkJNgfn332md5VIyIiIiK6IBx4wHuadE+OcHWuJhERERGRDzNI2g4WwIEH6jXpJIeIiIiIqLni6Wre06RPVyMiIiIiaq4MBu0fjTFr1ixIkqR4xMfH28uFEJg1axYSExMRFBSEwYMHY/fu3Rq3gncwySEiIiIi0kFTuCanS5cuyMvLsz927txpL3v55Zcxd+5cvP7669i8eTPi4+Nx9dVXo7S0VMNW8A6erkZEREREpINzvSdaxmssPz8/Re/NOUIIzJ8/H0899RTGjx8PAHj//fcRFxeHTz75BPfcc88F19eb2JNDRERERKQDb/XklJSUKB7V1dVO63DgwAEkJiYiPT0dN954Iw4fPgwAyMrKQn5+PoYPH26f12QyYdCgQdiwYYNX20ULTHKIiIiIiHRgkLR/AEBKSgrMZrP9MWfOnAbX369fP3zwwQdYvnw53n77beTn52PAgAEoLCy0358yLi5OsUxcXJy9rCnj6WpERERERDrw1uhq2dnZCA8Pt083mUwNzj9q1Cj7827duqF///5o27Yt3n//fVx22WVnYyorKITQ9BQ7b2FPDhERERGRDrx1ulp4eLji4SzJUQsJCUG3bt1w4MAB+3U66l6bgoICh96dpohJDhERERGRDoySpPnjQlRXV2Pv3r1ISEhAeno64uPjsXLlSnt5TU0N1qxZgwEDBlzopnsdT1cjIiIiItKDxqeroZGxpk+fjjFjxiA1NRUFBQV47rnnUFJSgkmTJkGSJEydOhUvvPACMjIykJGRgRdeeAHBwcG4+eabNay0dzDJISIiIiLSgbeuyXFXTk4ObrrpJpw6dQoxMTG47LLLsGnTJqSlpQEAHn30UVRWVuLee+/FmTNn0K9fP6xYsQJhYWHaVdpLmOQQEREREenAIEkwaJjlNDbWkiVLXJZLkoRZs2Zh1qxZF1ArfTDJISIiIiLSgd49Oc1Zi0ly/AKC4RcQAgCwWuvs0yWDcuwFg1TfJMLgryiTDPLnyuUk2UmQkmR0WgZZmVVVRwHR8DIqkmq8CPkOLcliqBn8ghSvjZb6drBanN8kymF7ZA2hLlN+ulRDDsqeW1X1FC7q7bzkfHO6iCmcz2VQVFu5DVbhXm3U755wUSZvC4N6fW7uE47rd689DZJyPots+xpz8aKrZvH2MJNCtXLlX7Gc72fq9lTugwanZa62Rr0fy+e1OnzinY/7Ip9XXU/5Uupml++fjn/Nq39t8FOOsmOKbW1/HuznvF3U+6cyuvJYYJR9vRgR4GI5Zcxaa/1yFkOdosxoqS8zqNYnWeTzqttMdtwVFkWZkOrb2iiUx3whex+Ew/tXvw55DAAwiPp6SsLxSO9sOSH7PBqtfqoyZb0bjggYhNHpfA7HEGv9a8dtd3Wsk30eXHz4XX3GhLouwtVRUt5mqs+YqP9EqLfdKmtel0duh5jyVau2QXLx2bQaGpwPACyG+vfPaHXe1urtc3XMqpPFVG97nUFWT9XGy98zoX4bZM+tDseQ+pgW9ZDCkG2fUP8+kkdwtb8o1cg+q+r9UX4sMjocS22v69z8vtabBI2THO1C+bwWk+QQERERETUlWoyIpo5HNkxyiIiIiIh0YJDUZ5BceDyyYZJDRERERKQDXpPjPUxyiIiIiIh0YEtytMtMmOTUY5JDRERERKQDnq7mPUxyiIiIiIh0wNPVvIdJDhERERGRDvS+GWhzxiSHiIiIiEgHBgkw8nQ1r2CSQ0RERESkA0mSNB54gFnOOUxyiIiIiIh0wIEHvIdJDhERERGRDtiT4z1McoiIiIiIdGA4+9AyHtkwySEiIiIi0gF7cryHSQ4RERERkQ54TY73MMkhIiIiItKB0SDBqGFmomUsX8ckh4iIiIhIB9LZh5bxyIZJDhERERGRDgySBIOG19FoGcvXMckhIiIiItKBJNkeWsYjmxaT5KS0b4Pw8HC9q0FE1AS0dloy+9BY5Wsv14SIyBtKSkpgNpv1rsZ5SdC2J0fiCWt2LSbJISIiIiJqSnhNjvcwySEiIiIi0gGvyfEeJjlERERERDrgENLewySHiIiIiEgH0tl/WsYjGyY5REREREQ6MEi2h5bxyIZJDhERERGRDiRJgqTl6Gq8JseOSQ4RERERkQ4MZx9axiMbJjlERERERDpgT473MMkhIiIiItKBUZJg1DAx0TKWr2OSQ0RERESkB417csAkx45JDhERERGRDji6mvcwySEiIiIi0gHvk+M9THKIiIiIiHQgSdqeYcaz1eoxySEiIiIi0gF7cryHSQ4RERERkQ54TY73MMkhIiIiItKBQZJgkLS7haeB56vZMckhIiIiItIBr8nxHiY5REREREQ64DU53sMkh4iIiIhIB9LZh5bxyIZJDhERERGRDiRJgqThOWZaxvJ1THKIiIiIiHTAnhzvYZJDRERERKQD9uR4D5McIiIiIiIdGCDBoGH/i5axfB2THCIiIiIinTAt8Q4mOUREREREOuB9cryHSQ4RERERkS449IC3MMkhIiIiItIBUxzvYZJDRERERKQD6ew/LeORDZMcIiIiIiIdsCfHe5jkEBERERHpgD053mPQuwLuWLhwIdLT0xEYGIg+ffpg3bp1eleJiIiIiIiaqCaf5Hz22WeYOnUqnnrqKWzbtg1XXnklRo0ahWPHjuldNSIiIiIij0leeJBNk09y5s6dizvvvBN33XUXOnXqhPnz5yMlJQVvvPGG3lUjIiIiIqImqElfk1NTU4PMzEw8/vjjiunDhw/Hhg0bGlymuroa1dXV9tfFxcUAgJKSEu9VlIiIiIiajHO/+4QQOtfEtfKyMk17X8rLyjSM5tuadJJz6tQpWCwWxMXFKabHxcUhPz+/wWXmzJmD2bNnO0xPSUnxSh2JiIiIqGkqLS2F2WzWuxoOAgICEB8fj36D+mkeOz4+HgEBAZrH9TVNOsk5R5KUOa4QwmHaOU888QSmTZtmf221WnH69GlERUU5XaYlKikpQUpKCrKzsxEeHq53dXwe21NbbE9tsT21xfbUFttTW2xPGyEESktLkZiYqHdVGhQYGIisrCzU1NRoHjsgIACBgYGax/U1TTrJiY6OhtFodOi1KSgocOjdOcdkMsFkMimmRUREeKuKPi88PLxFHwS1xvbUFttTW2xPbbE9tcX21BbbE02yB0cuMDCQyYgXNemBBwICAtCnTx+sXLlSMX3lypUYMGCATrUiIiIiIqKmrEn35ADAtGnTcOutt+KSSy5B//798dZbb+HYsWOYMmWK3lUjIiIiIqImqMknORMnTkRhYSGeeeYZ5OXloWvXrvjhhx+Qlpamd9V8mslkwsyZMx1O7SPPsD21xfbUFttTW2xPbbE9tcX2JLKRRFMfW4+IiIiIiKgRmvQ1OURERERERI3FJIeIiIiIiJoVJjlERERERNSsMMkhIiIiIqJmhUmOj1q4cCHS09MRGBiIPn36YN26dQCA2tpaPPbYY+jWrRtCQkKQmJiI2267Dbm5ueeNuXPnTgwaNAhBQUFISkrCM888A/W4FGvWrEGfPn0QGBiINm3a4M033/TK9l1sztpT7Z577oEkSZg/f/55Y7I9nbfn3r17MXbsWJjNZoSFheGyyy7DsWPHXMZkezbcnmVlZbj//vuRnJyMoKAgdOrUCW+88cZ5Y7bE9ly7di3GjBmDxMRESJKEr776SlEuhMCsWbOQmJiIoKAgDB48GLt37z5v3JbYloDr9uR3UeOdb/+U43cRkRsE+ZwlS5YIf39/8fbbb4s9e/aIhx56SISEhIijR4+KoqIiMWzYMPHZZ5+JP//8U2zcuFH069dP9OnTx2XM4uJiERcXJ2688Uaxc+dO8eWXX4qwsDDx73//2z7P4cOHRXBwsHjooYfEnj17xNtvvy38/f3FF1984e1N9ipX7Sm3bNky0aNHD5GYmCjmzZvnMibb03l7Hjx4UERGRopHHnlEbN26VRw6dEh899134sSJE05jsj2dt+ddd90l2rZtK1atWiWysrLE//3f/wmj0Si++uorpzFbanv+8MMP4qmnnhJffvmlACCWLVumKH/xxRdFWFiY+PLLL8XOnTvFxIkTRUJCgigpKXEas6W2pRCu25PfRY13vv3zHH4XEbmHSY4PuvTSS8WUKVMU0zp27Cgef/zxBuf//fffBQCHH+1yCxcuFGazWVRVVdmnzZkzRyQmJgqr1SqEEOLRRx8VHTt2VCx3zz33iMsuu8zTTWkS3GnPnJwckZSUJHbt2iXS0tLO+8XC9nTenhMnThS33HJLo2KyPZ23Z5cuXcQzzzyjKO/du7d4+umnncZsye15jvpHpNVqFfHx8eLFF1+0T6uqqhJms1m8+eabTuOwLW1c/Sg/h99F7nPWnvwuInIfT1fzMTU1NcjMzMTw4cMV04cPH44NGzY0uExxcTEkSUJERIR92uTJkzF48GD7640bN2LQoEGKm4eNGDECubm5OHLkiH0e9XpHjBiBLVu2oLa29sI2TCfutKfVasWtt96KRx55BF26dGkwDtvT5nztabVa8f3336N9+/YYMWIEYmNj0a9fP4fTMtieNu7sn1dccQW++eYbHD9+HEIIrFq1Cvv378eIESPs87M9zy8rKwv5+fmKbTaZTBg0aJDi2Mq29By/iy4Mv4uIGodJjo85deoULBYL4uLiFNPj4uKQn5/vMH9VVRUef/xx3HzzzQgPD7dPT0hIQGpqqv11fn5+gzHPlbmap66uDqdOnbqwDdOJO+350ksvwc/PDw8++KDTOGxPm/O1Z0FBAcrKyvDiiy9i5MiRWLFiBa6//nqMHz8ea9assc/P9rRxZ/987bXX0LlzZyQnJyMgIAAjR47EwoULccUVV9jnZ3ue37ntPt+xlW3pGX4XXTh+FxE1jp/eFSDPSJKkeC2EcJhWW1uLG2+8EVarFQsXLlSUzZkzx62Y6unuzOOLnLVnZmYmXn31VWzdutXlNrI9lZy1p9VqBQBcd911+Mc//gEA6NmzJzZs2IA333wTgwYNAsD2VHP1eX/ttdewadMmfPPNN0hLS8PatWtx7733IiEhAcOGDQPA9myM8x1b2ZaNx++iC8fvIqLGY0+Oj4mOjobRaHTotSkoKFD8Jaa2thYTJkxAVlYWVq5cqfjLWUPi4+MbjAnU/9XH2Tx+fn6IioryeJv0dL72XLduHQoKCpCamgo/Pz/4+fnh6NGjePjhh9G6dWuncdmeDbdndHQ0/Pz80LlzZ0V5p06dXI6uxvZsuD0rKyvx5JNPYu7cuRgzZgy6d++O+++/HxMnTsS///1vp3Fbanu6Eh8fDwDnPbY2tBzb0jl+F2mD30VEjcckx8cEBASgT58+WLlypWL6ypUrMWDAAAD1XyoHDhzATz/95NZBqn///li7di1qamrs01asWIHExET7AbR///4O612xYgUuueQS+Pv7X+CW6eN87Xnrrbdix44d2L59u/2RmJiIRx55BMuXL3cal+3ZcHsGBASgb9++2Ldvn6J8//79SEtLcxqX7dlwe9bW1qK2thYGg/JQbjQa7b1mDWmp7elKeno64uPjFdtcU1ODNWvW2I+tDWFbOsfvIu3wu4jIAxd3nAPSwrkhZRctWiT27Nkjpk6dKkJCQsSRI0dEbW2tGDt2rEhOThbbt28XeXl59kd1dbU9xuOPPy5uvfVW++uioiIRFxcnbrrpJrFz506xdOlSER4e3uAwk//4xz/Enj17xKJFi5rFMJOu2rMhDY1ow/asd772XLp0qfD39xdvvfWWOHDggFiwYIEwGo1i3bp19hhsz3rna89BgwaJLl26iFWrVonDhw+LxYsXi8DAQLFw4UJ7DLanTWlpqdi2bZvYtm2bACDmzp0rtm3bZh/t68UXXxRms1ksXbpU7Ny5U9x0000OQ0izLeu5ak9+FzXe+fZPNX4XEbnGJMdH/ec//xFpaWkiICBA9O7dW6xZs0YIIURWVpYA0OBj1apV9uUnTZokBg0apIi5Y8cOceWVVwqTySTi4+PFrFmz7ENMnrN69WrRq1cvERAQIFq3bi3eeOMNb2/qReGsPRvS0BcL21PpfO25aNEi0a5dOxEYGCh69OjhcE8XtqeSq/bMy8sTkydPFomJiSIwMFB06NBBvPLKK4q2YXvarFq1qsFj46RJk4QQtmGkZ86cKeLj44XJZBIDBw4UO3fuVMRgW9Zz1Z78Lmq88+2favwuInJNEkJ121siIiIiIiIfxmtyiIiIiIioWWGSQ0REREREzQqTHCIiIiIialaY5BARERERUbPCJIeIiIiIiJoVJjlERERERNSsMMkhIiIiIqJmhUkOERERERE1K0xyiIh82KxZs9CzZ0+9q0FERNSkSEIIoXcliIjIkSRJLssnTZqE119/HdXV1YiKirpItSIiImr6mOQQETVR+fn59uefffYZ/vnPf2Lfvn32aUFBQTCbzXpUjYiIqEnj6WpERE1UfHy8/WE2myFJksM09elqkydPxrhx4/DCCy8gLi4OERERmD17Nurq6vDII48gMjISycnJePfddxXrOn78OCZOnIhWrVohKioK1113HY4cOXJxN5iIiEgjTHKIiJqZX375Bbm5uVi7di3mzp2LWbNmYfTo0WjVqhV+++03TJkyBVOmTEF2djYAoKKiAkOGDEFoaCjWrl2L9evXIzQ0FCNHjkRNTY3OW0NERNR4THKIiJqZyMhIvPbaa+jQoQPuuOMOdOjQARUVFXjyySeRkZGBJ554AgEBAfj1118BAEuWLIHBYMA777yDbt26oVOnTli8eDGOHTuG1atX67sxREREHvD7/+3dLY5iQRiG0ZcmGBIw/Dk8AQULIcHi2ACrQrAMQLMDCAbFBkDdtJtJZ8Z0unvIFOe4uqLy2edWKvXsAQD4XuPxOG9vv/9hDQaDTCaTX+t6vZ5Op5Pb7ZYkOR6POZ1OabVaH/Z5PB45n8//ZmgA+EYiB6AwjUbjw7pWq/31W1VVSZKqqjKbzbLZbP7Yq9fr/dygAPBDRA7Ai5tOp9lut+n3+2m3288eBwC+zJ0cgBe3XC7T7XYzn89zOBxyuVyy2+2yXq9zvV6fPR4AfJrIAXhxzWYz+/0+w+Ewi8Uio9Eoq9Uq9/vdyQ4A/yWPgQIAAEVxkgMAABRF5AAAAEUROQAAQFFEDgAAUBSRAwAAFEXkAAAARRE5AABAUUQOAABQFJEDAAAUReQAAABFETkAAEBR3gEjBNo9qqPcSAAAAABJRU5ErkJggg==",
-            "text/plain": [
-              "<Figure size 1000x600 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
-        "# Plot flow direction\n",
-        "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_dir\"], cmap=\"twilight\", shading=\"nearest\")\n",
-        "# Plot the water surface\n",
-        "ax.plot(t, ds_avg[\"depth\"])\n",
-        "\n",
-        "# set up time on x-axis\n",
-        "ax.set_xlabel(\"Time\")\n",
-        "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
-        "\n",
-        "ax.set_ylabel(\"Altitude [m]\")\n",
-        "ax.set_ylim([0, 12])\n",
-        "plt.colorbar(label=\"Horizontal Vel Dir [deg CW from true N]\");"
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x249c4ff40e0>]"
       ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## Saving and Loading DOLfYN datasets\n",
-        "Datasets can be saved and reloaded using the `save` and `load` functions. Xarray is saved natively in netCDF format, hence the \".nc\" extension.\n",
-        "\n",
-        "Note: DOLfYN datasets cannot be saved using xarray's native `ds.to_netcdf`; however, DOLfYN datasets can be opened using `xarray.open_dataset`."
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds[\"depth\"].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Updated water velocity plots with data above the surface removed. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 20,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "# Uncomment these lines to save and load to your current working directory\n",
-        "# dolfyn.save(ds, 'your_data.nc')\n",
-        "# ds_saved = dolfyn.load('your_data.nc')"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x400 with 6 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    ds[\"vel\"][i].plot(ax=ax)\n",
+    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.3: Apply an Acoustic Signal Correlation Filter\n",
+    "\n",
+    "After removing data from bins at or above the water surface, we typically apply a filter based on acoustic signal correlation to the ADCP data. This helps to eliminate erroneous velocity data points, which can be caused by factors such as bubbles, kelp, fish, etc., moving through one or multiple beams.\n",
+    "\n",
+    "You can quickly inspect the data to determine an appropriate correlation value by using the built-in plotting feature of xarray. In the following example, we use xarray's slicing capabilities to display data from beam 1 within a range of 0 to 10 m from the ADCP.\n",
+    "\n",
+    "It's important to note that not all ADCPs provide acoustic signal correlation data, which serves as a quantitative measure of signal quality. Older ADCPs may not offer this feature, in which case you can skip this step when using such instruments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 7. Turbulence Statistics\n",
-        "\n",
-        "The next section of this jupyter notebook will run through the turbulence analysis of the data presented here. There was no intention of measuring turbulence in the deployment that collected this data, so results depicted here are not the highest quality. The quality of turbulence measurements from an ADCP depend heavily on the quality of the deployment setup and data collection, particularly instrument frequency, samping frequency and depth bin size.\n",
-        "\n",
-        "Read more on proper ADCP setup for turbulence measurements in: Thomson, Jim, et al. \"Measurements of turbulence at two tidal energy sites in Puget Sound, WA.\" IEEE Journal of Oceanic Engineering 37.3 (2012): 363-374.\n",
-        "\n",
-        "Most functions related to turbulence statistics in MHKiT-DOLfYN have the papers they originate from referenced in their docstrings.\n",
-        "\n",
-        "### 7.1 Turbulence Intensity\n",
-        "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this can be simply calculated as `<raw dataset>.velds.I`, but be aware that this will be a conservative estimate. Another function, `turbulence_intensity`, is capable of subtracting instrument noise from this parameter and is discussed below. The noise-subtracted TI is more accurate and typically 1-2% lower than the non-noise-subtracted estimation.\n",
-        "\n"
+     "data": {
+      "image/png": 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Q0Jmtlsf81q4CdT2AP0Ol6l9cc37akS+H99giu3fvlry8vDrLM655+HJlyqLukp3rqvH6xQVBGdFraZ3nkxKnqjhp67L2UpRdJl6HIyJOwjlwy/phcmWrmTIwMxwOov6jfheERHKdIqv82VJgZEqmw6+W+dVfLI2dITONHIdbdoT8sj5QT9q6ixgnERHZ3H9+nye7gpkyINMpBz9+ufx01eNSaPjMmEhfPzIc4etGO3euGTtNL/HKURn5kuFwq2tJY2emLN5ZnPRxEmOkFHmKnFavXj312rlzp8yYMUMN/F0Z3OWEFxERUbriGExUFcZJRESU7jgGUxp3MKEzCTdQdevWTVauXCnXX3+9dO/eXS6++OJEZouIiChp4dG7NX38bni9hN+wTERERJR0cRJjpBTpYMJtcjfffLP88ccf0qhRIznzzDPl3nvvFY/Hk8hsERERJa2g4VCvWNYjIiIiSmWxxEmMkVKkg+mss85SLyIiIqqeoDjVq6aCvIOJiIiIUlwscRJjpBR5ihwREREREREREdlfUgzyTURERNUTMpzqVVOhxD80loiIiCjp4iTGSPHDDiYiIiIb4U/kiIiIiOIXJ/EncvHDDiYiIiIbCcU4GCXWIyIiIkplscRJjJHihx1MREREKf74Xb0eERERUSqLJU5ijBQ/7GAiIiKykaDhVK9Y1iMiIiJKZbHESYyR4ofRJhERERERERER1QrvYCIiIrKRkDjUK5b1iIiIiFJZLHESY6T4YQcTERGRjfAnckRERETxi5P4E7n4YQcTERFRij9+V69HRERElMpiiZMYI8UPO5iIiIhsJGQ41CuW9YiIiIhSWSxxEmOk+GEHExERkY3gUbqxfNPGR/ASERFRqoslTmKMFD8p0cH0l8xwD2ULV45sDhaqf1/Mby6X5G2Rrp4c8RsBaegO7yreN3E5xeNwq3nazlCxNHRmm8tgPj43LK+b7dy5avqMjYsito3t5TjckuPMjFi3Kpg/t8wjAzL85nJ629Hr6s96n7TCUKm5PbyHZQGnNHWWyepAnnT3FMhSf654JCg7QjlyVOZ2OadN/9oWMxGlkTf/mGe2iRDdDlk/o60qMwKqXbK2pYDPBaGgakM1a1un27PK2mBMy3F4pdDwRaRZGZ3OCn+hdHBnyqZgidpmdH7WBQrMvOBagHnTS7wyKMsnm4M+EfGaecO8uaUhaeAqlYGZ2bLCL/JnqFQ2BL3Sye0Ujzjlpi295JrMebUub6K65HG4xOtwSOPy2EFDHPRsh/cjYhC8ENc0drtlbaBUDvKWSkNnOBjCMj08e84nvQ7OvXbqtMmV59Z9HXG+R6ssTqoq/rHS57ZuG/R5PbvUIbnOMunj9Ua0BfpcR1poQxb56qnlenqc0m3qFTLmuE/lsc9PkcP6rJL8o7bVpniJKI18uGGBigWsMZBmjVfQZrV0uSXD4VbT+0wbK6vPeFa1X4gf9N9yOg20bda2LzpWKjQCkuFwRqyr28IFPp9q2/TyiF3CbXc4L9Y2E2n5JaQ+W6cjv7gmmH+XugOywl8si69+SuaWOmVAZrZ8UJwtR2RsVfuu/45+dGcHGZKzWHKd4b/FO7t3yCfFraV3xgYVZ/1nZ3e53LNsPxwZShYp0cFERESULkKGU71iWY+IiIgolcUSJzFGih92MBEREdlIUBzqFct6RERERKksljiJMVL8sIOJiIjIRngHExEREVH84iTewRQ/7GAiIiKykWCM37RhPSIiIqJUFkucxBgpftjBREREZCO8g4mIiIgofnES72CKH474SURERBGCwaDcdttt0rFjR8nKypLOnTvL3XffLYZhmMvg/e233y4tW7ZUy5x44omyYsUKliQRERGlNMZJVWMHExERkY0EDWfMr+p64IEH5KmnnpInnnhCfvvtN/X5wQcflMcff9xcBp8fe+wxefrpp2X+/PlSr149OeWUU6S0tLSO9pyIiIho7+o6RgLGSVXjT+SIiIhsxBCHhGIYgwnrVdc333wjp59+ugwdOlR97tChg7zxxhvy3XffhdMyDJk4caLceuutajl4+eWXpXnz5jJt2jQ555xzapw/IiIiokTESTWJkYBxUtV4BxMREVEa3cGUn58f8SorK6uwjSOPPFJmzpwpy5cvV58XLVokX3/9tQwePFh9XrNmjWzevFn9LE6rX7++9OvXT+bNm7ffyoKIiIjIqq5jJGCcVDXewURERGQjIcOhXrGsB23bto2YPn78eLnjjjsipt10000qsOrevbu4XC411sC9994r5513npqPziXAHUtW+KznxQPGdJo1a5Zs3bpVQqFQxDyM/0RERERU2zipJjESME5K0g4mBKw4YK+++qoKSFu1aiUXXXSRuuXe4ah58ExERJTqguJUr1jWg/Xr10teXp45PSMjo8Kyb7/9trz22mvy+uuvS48ePWThwoUyduxYdZ0eOXKk7A/PPfecXH755dKkSRNp0aJFRFyA9+xgIiIionjESTWJkYBxUpJ2MOnBsV566SUVwP7www9y8cUXq9vsr7nmmkRmjYiIKCUhcLIGT5W5/vrr1bdzeiylQw45RH7//XeZMGGC6mBChw9s2bJFPUVOw+fevXvHJZ/33HOPumvqxhtvjEt6RERERLWNkYBxUpKOwWQdHAsDiP7tb3+Tk08+2RxElIiIiCq/9TuWV3UVFxeL0xkZIuCncvpnah07dlSdTBinScNP6vA0uf79+8flkO3cuVNGjBgRl7SIiIgoPdR1jASMk5K0g2lfg2NFwyBb0QNvERERpZOQOGN+Vdepp56q7h766KOPZO3atTJ16lT5z3/+I8OHD1fz8RM1/GQOdxm9//778ssvv8iFF16ofkI3bNiwuOwnOpc+/fTTuKSVLhgnERFRuqvrGAkYJyXpT+T2NThWNNyaf+edd+73fBIRESWLoOFQr1jWq67HH39cbrvtNrniiivUANvoOPrnP/8ZMe7RDTfcIEVFRTJq1CjZtWuXHHXUUTJ9+nTJzMyUeOjSpYvKw7fffqt+oufxeCLm86f0FTFOIiKidBdLnFTT5RknJWkHU00Hx7r55ptl3Lhx5md0TkWP9E5ERJTKavsUuerIzc2ViRMnqldVcBfTXXfdpV514dlnn5WcnByZM2eOekVvmx1MFTFOIiKidFebp8hVF+OkqjkMwzAkQdA5hLuYrrzySnMabrfHU+WWLl26z/XRwYQBwXcu7yR5uS5Z4S+Uli63FBoBaeHKMZcrDJVKhsMtHodb/EZA/VsdO0PF0tCZHTHNuj7SzXHu+aY2Om2sD0gD82Bv20b+u3pyItL51V8sPTzZZl42BwvNfcP2/RKKyKN1O9Z01gUKpJ07N2KfML/Q8EWsf/yvp8kXPd43P2N7jZ2Z8meo1NxudLno/TzirXGy8tynVb4W+bxywfTRMmPof2RhWWtZUNRBWnp3y8c96ler7InSzYyNi8zzHeemPucqO09122M9x/F+ecBnrq+n6zZDT8O/c8s8MjDTqJBOVe0jzvElvkwZkOmMaE91WxC9vm43dFrWtlCzbquyttZqSmF9OShjk7R3OVX7bk17+MqT5e3OH1faLuM9WPdxeolXTevt3aHKBcv8HgzJhwU9ZVSDnyXH4VXlvTEocoDbK5uCJartRBvqdTgkw+FUedXtNfY1uzhLGh6wWnbv3l2tgSFjpa95o+aMEG9O5N081eEr9Muzx06p83xS8oiOk1CPW7qy1LmAuv91WZ4MyvJVGi9YWWMLHXvgXLF+xnmh2we9rF4X55RePlp03GJdV7Oe1zqvj+7sIGMarjXn4Vxc6Guk9ic6/ej09LToNgyQzoB3r5NVI55Rn7u/cLksvfSpSssFbtrSS+5utiAiPWubpt/r9dHOA9rqp3e3llxniby8ob8sX9VSDrjs+2ofW6J0jJMA11+fONU1Wp93UGaExwgE/TdLZef/3NKQtHUXySJfczk1u7jS5aqKhyqLqazL4fzW+apsPeTVU/5TLN1uYp7PMCLal8q2j/3OdYb3LTquwvKIV3KdLrNNs/7tFs0ar1W2jG63Ll53tDzbdpZaFvvW2Bkyt1/Z38gn/Po3+fLgaeZ1oSAUVPs1f0ehHNljU1LHSYyRUuQOpn0NjkVERESRguJQr5qKZZ1kob8Lw51LRERERPGMk+wcIyVbnJTQQb73NTgWERERpa+XX35Zjb+UlZWlXj179pRXXnkl0dkiIiIiSriXkzBOSugdTNUZHIuIiIj2CBk1HytAr2cn+MIJMcJVV10lAwYMUNPwpNnRo0fL9u3b5dprr010FomIiCgF4iS7xUjJHCcltIOpOoNjERER0R4hw6leNRXLOon+Euqpp56SCy+80Jx22mmnqYeC3HHHHexgIiIiorjESXaLkZI5TkpoBxMRERHVTEgc6lVTsayTSJs2bZIjjzyywnRMwzwiIiKieMRJdouRkjlOsl9XHRERURoLGo6YX3bSpUsXefvttytMf+utt6Rr164JyRMRERElt3SIkZI5TuIdTERERDaSLj+Ru/POO+Xss8+WL7/80hxbYO7cuTJz5sxKAyoiIiKidPmJ3J1JGifZrySJiIgo5Z155pkyf/58adKkiUybNk298P67777j02aJiIgorZ2ZpHES72AiIiKy29gCsTxFzobjC/Tp00deffXVRGeDiIiIUjhOsmOMlKxxEjuYiIiIbMSIcZBvrJfs8vPzJS8vz3y/N3o5IiIiotrESXaIkewSJ7GDiYiIyEbwrVxMdzDZYADLhg0bqiefNGvWTBo0aCAOR8U8G4ahpgeDwYTkkYiIiFIrTrJDjGSXOIkdTERERDaSyoN8f/HFF9KoUSP1ftasWYnODhEREdlMKg/y/YUN4iR2MBEREdlIKt/BdOyxx5rvO3bsKG3btq3w7Ry+mVu/fn0CckdERETJLpXvYDrWBnGSPbrqiIiIKK0gcNq2bVuF6Tt27FDziIiIiNJVxySNk3gHExERkd2ejhLDYJR2e0KKHkMgWmFhoWRmZiYkT0RERJR6cZLdYqRkjpPYwURERGQjqfwTORg3bpz6F0HTbbfdJtnZ2eY8DFg5f/586d27dwJzSERERMkqlX8iZ4c4yWGg68um8Gi++vXry5qlLaVd/RxZ4S+Uli635DjDPXZ+IyAex54+tJ2hYikzQtLClVMhLSwLWH5zsFAaOzPVe+t0a3qFoVJzO3r9QsMnOQ5vRLqY1tCZba6Lf5cHfHKA26s+I52L1/5VpnT6XC0/u9QhAzONCunrbfx12enyYbf3VLoFoaC0c+eq/doeDElXT47MLQ1J34xQRH4xH3nQ/1rzYi2fysoiGvIFi3xe6eX1VchjZeWu90Vvv6pt7K18rX71F0sPTzgdnSaOGY4r0tgULFHloud7xCl+Ccn8sgZqWr+MXXJOm/6Vpk3p4Ynf58qGYK54JCgDMsO/FEbd+a7MKQd5S9V5rM9d0PVL1z+cv2sDpdLE5axQp/++ZpC83nF6lecP6vW6QIGqo9a6bGXdHt7/GXJKe1e4HoP1fI62wOeTps4y8xzQ27ppSy+5v/kilYdNwYDZVup0XitoJKfX2yhvF7aXs3J+l4zy/Ov9wPzzcnfs9VzV79EOWctVt6t6n6LbWz0dbTjaMT1fs7ZjgPR1+4P1V/mzxS8u1XZifxs5PRXanH1BOlDZ9cHahi7xZUoDV6mqAzNLs+WEzGLZlu+Ttt03yO7du+v0kbD6mjd4+mXiqRd5rakOf5FPPhn0XJ3ns7aOO+449e+cOXOkf//+4vXu2Ve879Chg/zrX/+Srl27JjCX9qDrzM7lnSQrx5A/Q6Uqvok+ryqLl9AORp97VtHTq4pbqoozKptu9ejODjKm4doK6WO7gPzNLfOo897K2qZEb7PMCJhp6P3bV74w7Zgbr5J5Dz5d5b5XBvlFO1pZeqDzUlV7qOOZy1aeIzO6f1TlfqFtv7Xp/Iiyt8ZESBftYq7TZcbAuiwKjYD4DEO1mV+X5cmgLJ9MKawvzx/QYa/7RmngizbyjzZfy4nZm8y/MeCIn0bIO4e8aF5nR6w+0Yx59N8IiFVQ1/TfUlXR13wr698uVjjfsLxPnGbcZD13ov/WsdJth/5bbW9/C1b2d4l1uvXc0ucwpuU4wjEV4rpWLpHVAbd0cgdUXjAt1xFU56D+m0Uvr1UWD+q/Ca3LNHZWnnddljr+wjYyHOEYtdP0S2XGCY+aMWtV7de+2mXMR+yrj1n09cN6PK1/F6OcQkUeaXjA6qSOk+wSI9khTuIdTERERDaS6ncw6aeiXHzxxfLoo48mfaBHREREySPV72CaleRxEjuYiIiIbCTVO5i0SZMmJToLREREZDOp3sGU7HESO5iIiIgoKf3www/y9ttvy7p168Tn80XMe/fddxOWLyIiIqJE+yEJ46TwIBlERERkC4blCSk1edltwMU333xTjjzySPntt99k6tSp4vf75ddff5UvvvhCjbFAREREFI84yW4xUjLHSexgIiIisuGt37G87OS+++6TRx55RD744AM1aCXGGVi6dKmcddZZ0q5du0Rnj4iIiJJQOsRIyRwnsYOJiIjIRtKlg2nVqlUydOhQ9R6BU1FRkXok77XXXivPPvtsorNHRERESSgdYqRkjpPYwURERGQj6dLB1LBhQykoKFDvW7duLYsXL1bvd+3aJcXFkY+wJiIiIoJ0iJGSOU7iIN9EREQ2ki5PkTvmmGPks88+k0MOOURGjBghY8aMUeMKYNoJJ5yQ6OwRERFREkqXp8gdk6RxUrU6mMaNG1fjhG+99VZp1KhRLHkiIiKiKhiGQ71qKpZ1EumJJ56Q0tJS9f7//u//xOPxyDfffCNnnnmmijHsjrEVERFRcsRJdouRkjlOqlYH08SJE6V///7qt33V8fXXX8tVV13FDiYiIiKKifVLKqfTKTfddFNKlSRjKyIiIkq1OKnaP5HDo++aNWtWrWVzc3OrtVyHDh3k999/rzD9iiuukCeffLK6WSMiIkob+pG6sayX7PLz86u9bF5enthdXcRWRERE6SyWOMkOMZJd4qRqdTBNmjRJ6tevX+1En3nmGWnevPk+l/v+++8lGAyanzEw1UknnaR+Q0hERETpNQZTgwYN1BNQ9sYwDLWMNX6wo7qKrYiIiNJZKo/B1MAGcVK1OphGjhxZo0T//ve/V2u5pk2bRny+//77pXPnznLsscfWaHtERETpIpXHYJo1a5aki7qKrYiIiNJZKo/BNMsGcVKtniJXWFgooVAoLrdi+Xw+efXVV9Wgl1X1ypWVlalXLLeIERERpYJUvoOJXzDVLrZinEREROkule9gOtYGN+I4a7rCmjVrZOjQoVKvXj11a3fDhg3VC7dr4d9YTZs2TXbt2iUXXXRRlctMmDBBbVO/2rZtG/P2iIiI7PzNXCwvu/nqq6/k/PPPlyOPPFI2bNigpr3yyivqYSKpJF6xFeMkIiJKd+kSIyVrnFTjO5iwA/hd34svvqjGAtjXbwCr64UXXpDBgwdLq1atqlzm5ptvjnisL+5gYicTERFR6nnnnXfkggsukPPOO09+/PFH8w7m3bt3y3333Scff/yxpIp4xVaMk4iIiNLDO0kaJzkMRDQ1kJOTIwsWLJBu3brFLRN4klynTp3k3XffldNPP73a66GDCd/07VzeSfJyXfKrv1h6eLLVPL8REI8j3H9WGCqVHGdmhfU3BwulsTPTXM7Kun5lnytbv7JlrHaGiqWhM5y/6HSRVgtXTkTa+vMHxdkyKCtf1gZKpasnJ2K7K/yF0sFdcR/0PmObOQ6v/BkqjUg/ehtY7pLVw2RMm89kYKZRIT9W6wIF0tKVpd5bt9vljdHy2zlPmNOv2thXnmj1nTywo4uMa7i0Qh71vlvLDfnwiDPieGEfsd+VlXll+1xZunp7Om/6WOh/rfP0sssDPjnA7ZWDvrxUVhz7UqXbWuDzSZ7DJy1dbslwuGVumUc6ufOlnTs34nijbrZyScTxv23rwTIo72cZkOmUrnNGmtvAtgsNX0Q56DKIziemY9vwgy9LHTtr2SIP24Mh2RrMls6eYnVMcfwKDJdazishlS72o6fHqbaL5XOdIj7DEK/DIRkOp6pDSA/70dgZUscAUCexbHTd1cfo0Z0dZEzDtWqbZYZDlvqbSS/vFlU+1mOit2vNp65rWNa639HHVddVvSz2eWNwz75Vdv5b24ro+ljZPF03dTlYl9fzdD3aFCxR+ZhbGpIGrlKVlnXZ2aUOOdxbovJkrdtYRp+nOOePytyutof0KjvfsMyp2cUV6iSmg56ny8f6L46pSk+cqt4iXZynb63pIz/2eUvlcUCGX01HuvBqQWc5ImuN9PF6K5SNtYyt+6E/f1fmlL4ZISlTdTug5kW3h9bytbY/WB/rWY+h3p61/CpjbQtA56vTp5fK6pNfUNOqSiO6Ply87mj5V8sZUmq4JdMRUNNwjHH+btxdLG27b1AX9Lp8Yoe+5h32v3HiqpdR4/WDRWXy49/+U+f5jJdDDz1Urr32WrnwwgvVE9QWLVqkYoWffvpJfSG1efNmSRV1EVtVFidVdQ3V5ynqc7To67L13NXXK93+Wa+v2t7iCQ3xwq3NvzCXw3kJuL4A8hzdDkRDu6DbF9DXnejzW+fZ2p5bYb1cp0tO+Oli1R5aYwu0ITkOd4X26OuyPOmXsUulCZVdo6qKTW7a0ktubDqvQnwYXY7RZa1Z04q+TgHarmfbzoq4XlWWT30c7m4xW20DcUFrly8iFvU4AjIoy2fut75+aNZYxdp+6s/6uoUyQTmi3HR6VZWPjjl1DKx1//oC+fQv/1VxykJfI+ns3iELy1rL0VkbzDxjO/BnyCm5jqCKfUaPu1YOv+UH2eXPljtbfazSPmTuxTLvyGdkiS9TZhUeJLc2War2772iVnJWzlb5z87uclT2cnUdQ5xXanjU9nQdxTUVMUyGw1Dp6eN07aY+cm3T2WbMA7pc79lyvJzb6FvZGGgoB2VsUjEiYhfAe8DnqbsPU/lBWartOYJqG/p8sMZHen+RH+s5qeuwrovTS7xyVEa++CWk8m0t18qOA95jv3t5i+Tvp18mr7/3XEQMXVU8BtF1AHk55JOr5JfBT6j6o8/F6HYE5YR4A2l9VdJezsvdERGf9fruXFnU9w1z20h3UzBQISatDGLTKxqsjPi7SpdZdDlYITZCGVjbP2uMAfq46L/drMfGGoPt7XzX52j03wLYDvKMv/ui4yxrmxbdPkTHUZX97VlZ22E1pbC+9Mv8Q7WN1u3oY4q2V19bomNe/G2SXxCUhgesTuo4yW4xUjLHSTX+idwRRxwh69evj/uTVPCYXtweTkRERFVDNzK+Gqrxy2aFumzZMjnmmGMqTEfwiJ/Up5K6iK2IiIjSUUxxktjPsiSNk2r8E7nnn39eRo8erX7jd/DBB4vH44mY37Nnzxqlh4Es0cGEp6m43bUac5yIiCjlhcSh/otlPTtp0aKFrFy5Ujp06BAxHeMK4Bu6VBLv2IqIiChdxRIn2S1GSuY4qcY9Otu2bZNVq1bJxRdfbE7DWAH4pR3+DQbL7++sps8//1zWrVsnl1xySU2zQkRElHZiHYzSbgNYXnbZZTJmzBg1LhHii40bN8q8efPkX//6l9x2222SSuIdWxEREaWrWOIku8VIyRwn1biDCR1B+L3fG2+8EZdBvk8++WQVQBEREVH1HqXriCEQsssjeLWbbrpJ3eV8wgknSHFxsboNPCMjQwVOV199taSSeMdWRERE6SqWOMluMVIyx0nuWAbkfv/996VLly51kyMiIiJKa7hjZ+7cuXLllVfK9ddfr24BLywslIMOOkgNiJ1qGFsRERFRKsRJNe5gOv7449UI5exgIiIi2v/0gJSxrGcXLpdL3eH822+/SYMGDVTAlMoYWxERESUuTrJTjJTscVKNO5hOPfVU9Ti8X375RQ455JAKA1Gedtpp8cwfERERpeEYTBjsevXq1dKxY0dJdYytiIiI4iNdxmA6OEnjpBp3MOEpJ3DXXXdVmMeBKImIiOpWunQw3XPPPWocgbvvvlv69Okj9erVi5ifl5cnqYKxFRERUXykSwfTPUkaJ9W4gwkDSREREVFipMsg30OGDDHvjLYOep2KT1ZjbEVERBSna2qaDPI9JEnjpBp3MBEREVHipMMYTDBr1qxEZ4GIiIhsJh3GYErmOKlaHUyPPfaYjBo1SjIzM6uV6NNPPy3nnXee5Obm1jZ/RERElGb8fr/6KT7iia5du0oqYmxFREREqRYnOauzEAb1LigoqHaiN9xwg2zbtq02+SIiIqIqv5lzxPCyT3HiASI///yzpDLGVkRERMkSJ9nrSHiSOE6q1h1M+B3fCSecIG539X5RV1JSUtt8ERERURoP8n3++efLCy+8IPfff7+kIsZWREREdXF9TY9Bvs9P0jipWj1G48ePr1Gip59+ujRq1CjWPBEREVEV8CVbLF+02ezLOQkEAvLiiy/K559/XunTUf7zn/+InTG2IiIiSo44yW4xUjLHSXXSwURERER1I13uYFq8eLEcdthh6v3y5csj5lmflmJXjK2IiIjiL13uYFqcpHESnyJHRERkJ/vpFqYNGzbIjTfeKJ988okUFxdLly5dZNKkSXL44YeHkzMM1Uny3HPPya5du2TAgAHy1FNPxW2wyWR9OgoRERElsf10CxPjpFoM8p3s/EZQ/EZADnB7ZYW/UE3zOMJ9Z5ie48w031v/beHKUcvtDBVLYahUTdsc3LO+Xs6aHmB5vPT61nX0fOtyWkNntvoXedRp6/WRFvJgzdu6QHhg9VOzi9VyXT3haZinYRrmDRp2vrktpOGXkLlNzM+xlIdmTQfLTe3yqfTyFqnPGQ5nOB0jIB8UZ5vr/eovlnbuXJVmoeGLKJOFZ0+MKIMnWn2n9u3GRitlecAn00u8EXnANGsZ6Hzo46WXxT5a86y3gXX0PuM91kPZ6vnWY4Z0rJ/1sdD/bgqWRKSLfevhCZfdzAFPyIv5zcUK20KafbxelT+d51xnmfoXxwlpzy51qOOKtApCwYg0rmz8rfjFpba34tiXzH35M1Sq1t0R8pvHQJcB5um6ieU3BHPVcoVGQA73lpj1WO8L0lnqbybNXMXycVFn8/ghP6/s6K/SxfaxH//d1cXM21v5B0uB4VL1QNchlG2uI6imlZWXZ65T5PuyZioNfVxR12aWZqv8jWm4Vk1v6cqSli63HJW5XbwOh5qG9FDuuh4hLwd5S1X6GvKqj92fln3T57m1Hq8PhG8LRX7RFiBv+lghL0OXDzbPSew/6HSs9aOxM3zu6LLUyoxQRLtgrbc4tlge05BnGJDpNLej6xUMzDTkyV0HR6SN+oJ1sS9IX53z4oxIT+dzbmk4f1gGn/V5oOsgph+RsdWsT77yUQuRtm5rNgbD5ZThcJv7jfN0/mGvqfSRRxxjXX5HPXytjK6/QfIc4WOl6x/yjeX1tjEN6RWEs2iWE8oC6WE5vY/63NNp/Wd7X7N8dXuoz2d9butt6O1Z2wbdXurjqs49w6fqvM6H3vayk55R/2IZaxpH/DRCrWttt3EM8blN5k5Vr3CutHKF52G/wmWUIalm586dqsMIg0iig2nJkiXy73//Wxo2bGgu8+CDD6onoeEJJvPnz1e3Zp9yyilSWhp57sTDH3/8oV4Ue5yk45bK4PzomxGqECdAjsNrXvP0uWu91uhzGe/1tQ8W+MLthXWbyIM1fX2uIV6Ijm3wauzMVC/dDuj8RecRcC20poG2U5/fenndRunrmjVPOgbDepj/Y5+3ZPjKk83t6jYE7WZE+TgzZVCWL6IckM4Rt11utmd7jkP4WnPTll5mLHh/80VqXX2NsJa7tV3Dep8Xt6x0363r6P26Z3t3teykdl+p9hf7iW3ofdfxr/WY4DhgPj739DjN2BGOy9yh9tO81pcfF2v5WttT3X6OWH2iuZy+biFdXW7W2FfvpzUuz3W6zBgY+dex5NKjXlGxBcr3hMxiNf/E7E3qsy5bxBP4HI4JXCo/7z/6iCza0VqVC+IceKffMzL0lwtUDHJrk6XhMpGQDKn3Rzg//nry0vaj1HvEyW9t6ycZDkPFGaif4XyKyg+uO/p4PtJygSzyNZdrN/Ux96+TOyAbgl5p6C6WCz4eLb0zNsi2YD0VYyB/iEGwPl74fGPjxWo97IOu14ifEffp8tJxEfYVL2td1McKMA+xEMqrsuuodR1rzAzhuCAkn3zwmizyheMtxCm3bQ3HM6irf4bC10TEeShD5ElfQxHv6b/J1gx9XuUf+6Hro7Vd0bA+0johe51a1xpTLer7hnnO6OO1NZhtxjzWem39+wiG5/6itq33HcdQ13vrclgPMYRuc1AGiJ+sy1jjR/y7yOeN+NtNz0PZ6Bhse3BPkKTTWR0IL4cysJaJPk5YF9OauMKxobVdwWe9PuB81zGzzh/KB/uDuEfnSaeh2/Xov5uwrH4/Ime32TZa43Fdv6x/n+n8jvrjSJlf3Fl93hVKvfGZGSeleAcTERFR2ojpCXIOtV51PfDAA9K2bVt1x1Lfvn2lY8eOcvLJJ0vnzp3Nu5cmTpwot956qxp3sWfPnvLyyy/Lxo0bZdq0aXHZzVAopB7BW79+fWnfvr16NWjQQO6++241j4iIiKiCOo6RgHFS1djBREREZLvH78b2gvz8/IhXWVn4zkur999/X/0UbsSIEdKsWTM59NBD1U/htDVr1sjmzZvlxBNPNKehI6hfv34yb968uOzn//3f/8kTTzyhno7y008/qdd9990njz/+uNx2221x2QYRERGllrqOkYBxUh10MPl8Plm2bJkavZyIiIj2j1juXrIOeIk7k9AZpF8TJkyosI3Vq1eb4ynNmDFDLr/8crnmmmvkpZdeUvPRuQTNm0f+fBif9bzawraef/55tW3cIYXXFVdcoTq6Jk+eLKmIsRUREVHt1HWMBIyT4jjINwb6vPrqq80gEyOWd+rUSU1r3bq13HTTTTVNkoiIiKorhlu5zfUwXtn69ZKXl2dOzsioOIYUfoKGO5hwxxDgDiY8rQTjLY0cOXK/HKsdO3ZI9+7dK0zHNMxLJYytiIiIEhgn1SBGAsZJcbyD6eabb5ZFixbJ7NmzJTNzz2DMuE3+rbfeqmlyREREtB9/IofAyfqqLHhq2bKlHHTQQRHTDjzwQFm3bp1636JFC/Xvli1bIpbBZz2vtnr16qV+IhcN0zAvlTC2IiIiio+6jpGAcVIc72DC4J3oSPrLX/4iDseensEePXrIqlWrapocERER1fXjd/V61YQnyOFn8Fa4YxkDbQMG/UZH0syZM6V3795qGsYqwNPk8JO2eMBT6oYOHSqff/659O/fX03D+E74dvHjjz+WVMLYioiIKIFxUg2XZ5wUxzuYtm3bpgb8jFZUVBTR4URERET2dO2118q3336rfiK3cuVKef311+XZZ5+VK6+8Us3H9X7s2LFyzz33qIEuf/nlF7nwwgulVatWMmzYsLjk4dhjj1WdWsOHD5ddu3ap1xlnnKE6vo4++mhJJYytiIiI7INxUhzvYMKYDB999JEacwl0pxIG4tTfMBIREVHdsA5GWdP1quuII46QqVOnqp9u3XXXXeqOpYkTJ8p5551nLnPDDTeoL5dGjRqlOn+OOuoomT59esTP52sLHVb33nuvpDrGVkRERImLk2q6POOkOHYw4dvMwYMHy5IlS9QT5B599FH1/ptvvpE5c+bUNDkiIiKqqVh+IldDf/3rX9WrKviCCZ1PeMXTihUr5Pbbb5dnnnkmYqBN2L17t/oJHu6cwgNGUgVjKyIiojhinCSJipNq/BM5fEO5cOFC1bl0yCGHyKeffqp+ModxEfr06VM3uSQiIqJaPX43lrueEuGhhx5SjwmO7lwCPDIY87BMKmFsRUREFB+pHCPZIU6q8R1M0LlzZ3nuuefikoENGzbIjTfeKJ988ol6TG+XLl1k0qRJ6nZxIiIi2v+DfCcS7oZ+9dVXq5x/1llnyd///ndJNfGMrYiIiNLWfhjkO5HmJHmcVOMOJjwlpqpb5fEYP6/XW+20du7cqUZgP+6441QHU9OmTdWt8Q0bNqxptoiIiNIEvmWL5Zs2e3w7t27dukofJqI1adJEPUkulcQztiIiIkpvscRJ9oiR7BAn1biDqUGDBnt9WlybNm3koosukvHjx4vTufdf4D3wwAPqFi7csaRhIFEiIiJKT7i9e9WqVdK+fftK5+OpdpXdFm5n8YytiIiIKHXVT/I4qcZRyuTJk9VTXW655RaZNm2aeuF969at5amnnlJPk3nsscfk/vvv32daeLQxfgo3YsQI1Qt36KGH7vX28LKyMvUtn/VFRESUlrd+x/KygWOOOUYef/zxKucjxjj66KMllcQrtmKcREREaS+FYyQ7xEk1voPppZdekn//+9/qt33aqaeeqgb8xhNfZs6cKe3atVOPFUZwtDerV69WgdO4cePUst9//71cc8016lbwkSNHVlh+woQJcuedd9Y0y0RERKkjxcdguvnmm6V///7yt7/9TW644Qbp1q2bmr506VJ58MEHZcaMGerJtakkXrEV4yQiIkp7KT4G081JHifV+A4mZBZ3GkXDNDxJTj8NBb8N3JdQKCSHHXaYejwv1sc3dJdddpk8/fTTVRYmHlGsX6k2BgMREdE+4Uknsb5sAPHA//73P/nyyy9VANWoUSP1OvLII+Wrr76St99+W8UOqSResRXjJCIiSnspHCPZIU5yGIZRo/66Aw44QM4444wKt2nfdNNNMnXqVFm2bJn88MMPcvrpp6snxO0Nfjd40kknyfPPP29Owx1N99xzzz7XBfxEDr9B3Lm8k2TlGFJmBCTHmSkr/IXS1ZMjO0PF0tCZXeX6lc0vDJWqNPa1nJ6e4/CKx+E21wXr+n4jYM6PXt6aNpYrNHzmdqz52BwslByHW3aE/NLOnauW/TNUKi1cOfJaQSM5L3dHlXl7u7CZDKn3h0r30Z0dZEzDtRHrW/et+wuXyy+XPB6Rv8r241d/sbR3Oavcz+j19HGxwj5h+9b3Oi/Y9wyHWzYFS6SlK0stE522XgfL+iUUcXysedHbtx4XPf+YxcPk44PerDBdi05bH5Po5azHENvaFAxvr4M7nK61fmC/cJyt9cBaFroeRNcTlHkPT7ZatrEzM2IepmU4nOIRp8pvmRFS9eW4RRfIrF6vmGW5OpAnj/5xkkzt8qm5LZ0/vU9TCuvLQRmb1LawzVYukbcKusqwnGVqu/qY6LqK5Ufk7DbLAXR5XbWxrzzR6jsz/+CVkDo3o8sb9fiE7HVqP5B/XR5Vlbn1WOu8RJ+n0fWqsmNsXU7PWxcoUOeZLmvreVlZGtHL4fPM4nZyVs7WCuvqtgn7q8/LwxacLfMPey2izgLOUZ+Bds1hlpnVAp9P+kQN/Du71CG9vEXqmI2uv6HK9iu6zmk4vth3rIPjYK1r0eeVfo99Ql23HgfrMbSWG2A9XZ/x7wHuPXVdl0/0NiqrB9jO9mC4PkW3HSg7sOahsnOnKqgDXgyu7Ah/B6PLb3qJV/pl7JLVAbe0dvlU+shz89IsaXjAavXFR13+5l1f89o8cac4syLb1OoIlZTKH1eNr/N8xktJSYlMnz5djSWAUAXxx8knnyzZ2VVf1+0qnrFVZXVm67L20jjPq+prE5dzr7FRZed1VSprX6PbyOj4Rqdvbdes19vK4jC9rcraln2xxjx4vzZQqsog+jpr3W50W2PNu25nILpNtLat0XnQZaOv8TpP+jpqLYPqXKusedbXrejt6fe6bbfOu2d7d7m1yVKzbUa+dPwQXf56O3uL3azHCfEIWMtT7zdg39G+Wvf1g+JsOTU7HCtEi46frfun910f5z9DTnV9seYdcdmGYK4MyPCbxw3TH9h+uFzWaJ5aH9fPgZmGmfbc0pAMyAzvh36Pazeu7fpYQ0FIzLqMvCBG0uWt63n08dTXEuv+Y13Eaa1dBWZ6uEY2du45JkjPJ0513bTGitHXTpTDQl8jOSGzWM3HvmHfredn9HlZWb2qjF4OMUgnd6DCsQd9bdbL6zKPrpcHfDxa1gzd8zdgVfV3WlFjGVbvzyqv38hvoRFQ9VHXS/23U/R+VPV3ibVcMB/nIuyt/asqNrWWh44LEX/ov0d0Xq3rR59bqFcZDsOs29blkJa1TNGm6WWtbbe1vaxqemVtlnV7127qIw+2mC8/+0PSzR2qUG76bwXsZ3Sd0LEejs+OgoB07L4pqeMku8VIyRwn1fgncg8//LAaMwlPfTviiCPUNAQ9uCULPWmAn7qdffbZ+0wLT5BD0GS1fPnyKgesIiIiSnsp/hM5LSsrS4YPHy7pIJ6xFRERUVpL8Z/IJXucVOMOptNOO00FPBgTAJ1BMHjwYDUgZYcOHdTnyy+/vFppXXvttepWLvxEDuMOfPfdd/Lss8+qFxEREVE6iGdsRURERGSbDibo2LFjtZ4Sty/4lg63fmPMgLvuukulO3HiRDnvvPNqnTYREVFKinWsABuNL5CO4hVbERERpbVY4iTGSIntYNq1a5e622jr1q1qoG6rCy+8sEZp/fWvf1UvIiIi2jeHEX7VVCzr0P4Tz9iKiIgoXcUSJzFGSmAH0wcffKDuMCosLFQDYDkce3oH8Z5BEBERUR1KkzGY0gljKyIiojhJkzGYUqaD6brrrpNLLrlEjZuU6BHKiYiI0k4K/0QOT4CpLrs85aU6GFsRERHFSQr/RC7fBnFSjTuY8Hjca665hp1LREREiZDCdzA1aNAg4s7oyuBRvFgmGAxKqmBsRUREFCcpfAdTAxvESTXuYDrllFPUo3M7depUNzkiIiKitDRr1ixJR4ytiIiIKBXipBp3MA0dOlSuv/56WbJkiRxyyCHi8XgqPGqXiIiI6kgK38F07LHHxiWdRo0a1Wh5fNP3448/Svv27SURGFsRERHFSQrfwXRsHOKkuo6RatzBdNlll6l/77rrrko3nkq3rBMRESWdFO5gqkxxcbGsW7dOfD5fxPSePXvu9YlsEydOlPr16+8zfdxKfsUVVyQ0fmFsRUREFCcp3MEUjziprmOkGncwRT86l4iIiPajFB7k22rbtm1y8cUXyyeffFLp/H0FO+ecc440a9asWtu6+uqrJZEYWxEREcVJCg/yHa84qS5jJGeNliYiIqKEchixv+xk7Nix6lu2+fPnS1ZWlkyfPl1eeukl6dq1q7z//vv77LCpbuAEBQUFHFuSiIgoBaRDjFSbOKmuY6Qa38EERUVFMmfOnEpvxcIT5oiIiKiOpMlP5L744gt577335PDDDxen06l++3/SSSepx+5OmDBBjVuUShhbERERxUGa/ETuiySNk2rcwfTTTz/JkCFD1G/9EAxhkKjt27dLdna26gljBxMRERHVFmIM/Q1bw4YN1a3gBxxwgHrACAabrCl8A4fxI2fPnq1uGx8wYICMHz9emjRpkvCDxdiKiIiIEhUnxTNGqvFP5K699lo59dRTZefOnepWrG+//VZ+//136dOnjzz88MM1zgARERFRtG7dusmyZcvU+169eskzzzwjGzZskKefflpatmwZ00Da+ELszjvvVEHT6tWr5bzzzkuKgmdsRURERImKk+IZI9X4DqaFCxeqzOM2LJfLJWVlZeo3eQ8++KCMHDlSzjjjjJgyQkRERPuGYShjGSvAbsNXjhkzRjZt2qTeI9gZNGiQvPbaa+L1emXy5Mn7XP+RRx5R4xPgCbfw/fffy/Lly1XsogOzv/zlL5IMGFsRERElLk6yW4xU2zipLmOkGt/B5PF4VOcS4JYsjMMEeMzd+vXrJVE8DrfkODNlhb9QOrgzzek7Q8Xmv5i3LlBgziszwk/EKwyVit8IqPdIA/RymNfQmR2xLaSj07XCunr9zcFCM19I+1d/sRSEgvJnqDQiDY841bJYDtvBdJ2WTqOFK0f8EpJ27tzwOg63NC7fznm5O1T6XV8dbS4PSAvLYT62C2MarlXLFho+yXA4ZYHPp5bT+7700qfkhfz26jPSwr7DAzu6qLR0ObZ3OSWjfL90GR302lXmtjEdLyy7POCTwvLl9L5hXo7DLbNLHeo99k/nWe87tof9xb9628gTXnodpI9lrccH074rc0aUP/Kq89Bp+qVqGpb78uBp8mpBZ3M9vR1zPyRkls+oP45U29JlYj3+OQ6vWsZTvp2l/maSUd6q6W3B4d9cpo4/0sQxmFsaUmWr99967LAPVj084X3EslhX0/uJdTYFA+pfnd73h06RWaWNzLJs7SqQtzt/bK5bVp5npHHtpiPVPgyr96c0dobU+1au8L4dnb1CfIYhawOl0tKVZdZhrNc7Y0NEOeCcmlIYfuTlE62+U/+i7r+5s698WLDnUZkoR6SnnZWzVeX7rYKu8mcovO+oH9bzwOrp3a1VuaIsos9PDemhzmG+PgbYpq6HmIa01flVXhb4d4m/sbm+Pi9VfTACal11nMvLANNwLmHa/LIGajrWw/5Y2xi9/a6ecL3tnfmHKi+k92Oft9T6Ol+63gCOm6+8jdDbw3uk0cfrjagHmDYw01D5HV1/g3l+ahevO9pMQ5ex3hZeOFdxfDF/ezCk2hjUEThswdlmnnQbAsgz9kmXE+ZVdTys+6XrM+qY9fzW5aOX1fsVXQ8wDdvB8jC1sKM8urOD2Xas8ofPA93G6DZDH2MrXQ+wL3jhvES5Y3lsw9pGDsryqWNqLXvkYUuwSBLydJRYXjZy/vnny0UXXaTe4y5p3C2NAAixxtlnn73P9VetWiX9+vVTPz8DjEuA8Qjwzd7jjz8uF154oZxyyimSDOo6tvI4wgGjOl8rCf2s1zQVU1jOa+sy1ngJ9HzrNVSfu9br8NHf/SNie/rc1du1Xst1LIcYJXpb0ddLXEN1nvX1RrO2qXo95AXb1jGSlY7fNOwrrmc6NlNtX6hUXedxHbRei3VaejtYDnED9k9fX/RySG96SZ657Iic3eF1VGwUbls2BUtUGtYywLVGp4H8YL7OM9osvc/W7enl9XxAu4583dpkqXlN0/lCu480dQynt434Qu8frr8RcVh5nvVxQDrWeFjXDV3meKn2WJxqH3ReT80uluklkWnpeoRlkW8zNreUvbf8jyNMQ7q4vui6p68fiMm6ewrM7R/x0wg1/famC1XZ6P3ENUNfJwZkOtW/qGN4j7QQU+PYY3pB+UO1UZ9w3UDeF/maq/m5TpdavonLKcNXnqzyruMG6Jexy6zvWB7rYh3Eabnlpye2UWqEy0rHn6sCjSTXEYyIffT5ai1rrHNURr5ZtogNrPVB7y/KVZepNc6PPhf0dVTXLZRvJ3fAbEtw3mHeIl89lS/sgzpXyo+vtf7DPdu7q31YM/R585jr81Wvg20gXSw3J7+bmoZytsZD1r/dEKdiHuIbpKXLLRrS+cGXVSGex3R9/HV7FB3PYFndDobPixL1721bDzbzhDTAWpd1nKjOcVUfw3XLmq6K78vTxXmIY7o6kBdR5nr/rGWJ+oNl9d+I1rYb6ejtoC7q6dZ21Premif9/pGWC9R63dwhlX8cE7RLOnbC+TZq7WnqPWIjpK+PkY71sM8NnFmyX6VBjFTbOKkuY6Qa38F06KGHqoxjdPJjjz1Wbr/9dnU71SuvvCIHHxw+wYiIiKiOpMkg39Ew1uNhhx1W7eWfeOIJ9TP+Sy65RI477jg14OWrr74qn332mRpfYMSIEXLVVXu+HEkkxlZERERxkiaDfNcmTqrLGKnGHUz33XefGgQK7r33XtW7dfnll6sOpxdeeCGmTBAREVE1pUkHEwIc3OI9c+ZM2bp1q3qsbvTTU/YFt3fjS7EHHnhA+vfvLw899JC88847kmwYWxEREcVJmnQwBWsZJ9VVjFTjDiY8Bk/DbdzTp0+vdSaIiIioevAL3JjGYDLsN7YAAifcso07pPU4ATXldrvl//7v/+Sss86S0aNHy0svvaS+uWvRooUkC8ZWREREiYuT7BYjxStOqosYqcYdTFXBo/Dwc7kPP/wwXkkSERFRmnrzzTfl7bffliFDhsS0/qJFi+Qf//iHLF26VHr27Ckvvvii+pZv0qRJcuSRR8r111+v7sBOZoytiIiIKN5xUl3GSDUa5HvGjBnyr3/9S2655Rb16DpApoYNGyZHHHFEhduyiIiIqI5u/Y7lZSN4CkqXLuFBnGOBcQWOPvpodfs3xhLAN3Nw8cUXy/z582Xu3LnqlvBEY2xFREQUR2kQI9U2TqrLGKnaHUwYX2nw4MHqNiz8Tg+/2cNAUNgwbqFavHixfPzxnidUERERUR1Ikw6m6667Th599FExjNgyjsftXnHFFdK9e3e5+uqrZc2aNea8pk2bqhjmzjvvlERibEVERBRnaRAj1TZOqssYqdo/kUPm0bGE26Uw+BN6uv773//KL7/8Im3atIlp40RERFQz6TIG09dffy2zZs2STz75RHr06CEejydi/rvvvrvX9QcOHCijRo2Sc845Rw10OWDAgArLnHzyyZJIjK2IiIjiK13GYPq6FnFSXcZI1e5gWrVqlepUgjPOOEMNCIWRxtm5REREtB8ZjvArlvVspEGDBjJ8+PCY13/55ZfV027fe+896dWrl9x0002SbBhbERERJUGcZLMYqbZxUl3GSNXuYCopKZHs7Gz1HiOUZ2RkSMuWLeOWESIiIqqGWG/lttm3cxhoMlY///yzeqLKww8/XK3lf/31V+nWrZv68mx/YmxFRESUBHGSzWKk2sRJdR0j1SiSev755yUnJ0e9DwQCajymJk2aRCxzzTXX1CRJIiIiorg69NBDZfPmzWocgerAeJILFy6UTp067fcjwdiKiIiIUiVGqnYHU7t27eS5554zP2Ng71deeSViGdzZVJMOpjvuuKPC4FHoHcOT6YiIiCh9x2BCAIS4IhqmZWZmqienXHTRRXLcccdVWAYDXt52223mndf74vP5JBHqIrYiIiJKZ+kyBtOhMcZJdR0jVbuDae3atVIXMCDV559/vidD+/n2dCIiIltJk5/IDRo0SJ566ik55JBDpG/fvmoaHqeLW7sRMC1ZskROPPFENYjl6aefHrHuMcccI8uWLav2tvDtXFZWluxvdRVbERERpa00+YncoBjjpLqOkRLem4MOJXxjR0RERNUQ4x1Mdguetm/frh7Bi2/ZrO655x75/fff5dNPP5Xx48fL3XffXaGDafbs2fs5t0RERGTbOMlmMVJt4qS6jpGckmArVqyQVq1aqd/0nXfeebJu3boqly0rK5P8/PyIFxERUVp+MxfLy0befvttOffccytMxyN1MQ8wvybfwqU6xklERJT20iBGSuY4KaEdTP369VMDhU+fPl3d3rVmzRo5+uijpaCgoNLlJ0yYIPXr1zdfbdu23e95JiIiSqg06WDC+AHffPNNhemYhnkQCoXM98Q4iYiIKB1ipGSOkxL6E7nBgweb73v27Kk6nNq3b6963C699NIKy998880ybtw48zPuYGInExERUeq5+uqrZfTo0bJgwQI54ogjzLEF8NS1W265RX2eMWOG9O7dO8E5TR6Mk4iIiNLD1UkaJzkMDCOeRFA4GIwKdyvtCzqYcCfT0t+aS0aOQz4u6i6j629Q8/xGQDyO6vWfWZf91V8sPTyVj6g+tzQkfTNCFdLdGSqWhs7sCu83BwulhStHpQ+V5acwVCo5zky1zNpAqeQ6Ra2jp6/wF0pXT06l+Zle4pVBWT5zm3odnY8chzdim9b51mmFRkAaOzMr5E/nqbLtY16h4TP3tbLyrGr/rWWky0lv35pHrDe3zCMDM42Idazb1mnjM+hlkI5fQlIQCko7d26l5Te71KHStm4T07p7ClS+o8vQmgfUk/Yup1l22H6ZEZIch1ttF6LLvyrR9UrnR2/Pur86T9by1Hn+M+SUA9x7tqmPA+pQS5dbvi7Lk87uHebx1Mdngc8nfbxes8zmlzVQ9Qr72NgZklX+bDnIWyoecUqGw20e2wyHU7YHQ/Lyzr/IlY2/VZ+tx+iIh66Wc//xmdzYaGVEeevtYntID/7EPuP4R9VFvc7e6P2MrpPW6Ui/sjpuLW+9PMqjtctnLl9ZW2KdFl2fddli/TIjoMpUz9fHwnoe6nKoahvRZaC3Zy3H6PPa2m5E12N9nKPPQRznAZnOiHqJz1h/Y1BUXaiqnQDrdGy/iSuclq7D0ef3ukCBeW5i+77yS1GZ4VB518cN+1hZOWMbHdzhc09Pjy6rvbVTer+i23vka4m/sToHkF4vb1FE+x7OY0jVd/y70NdIjgyUSMMDVsvu3bslLy9P6oq+5nW+5T5xxfBtVLC0VFbdd0ud5zOeXnvtNXniiSfM27vxpFkEVH//+9/V55KSEvNpKVR1ndm6rL3k5TqrvKZXBvVdX0Ot7ZS1TdHnP0Rfw6JZ24p9taGabq+qcz2trK3W7aR1n6JjNOu61jTwHm14Ze1zdfKh21B9vYzeR+u2qroOVJY3tFFehyMi768UtJYh9VZVaKMxb3nAJ6WGW/IcPtVmRpd7dPrRZba3/UT56OsnWLdtTV+35db32GeIritVxYx7ix33dex1bG9dTsfQer41foKrNvaVJ1p9p8q7kdMjL+zuLmMaro34OwHxQk+P0zwvdD41ff7odaLLFvnZFCxRy2A9XFN0/Kn3tfOUf8qqEc+o91MK68tBGZvEKyF1jbVem6znpDVG1nUG+xBdx6LLFOlnOv1yRMZWM5/WctLHBnXKeu3Uf0ugniNWtMYYur7iWOHYI1bVx0LH+NZ0rHGhjqOsfxdEx7jR+6LLP7rOWJevLH7S5Y9YVNfL6LT0e+vx21t8aN2W/lfHHjgndd2JLmfruRHdVuo6Yq3XiIcyHIa0dGWZcf+GYK4Zv2DbOsbW61rPH+vfa9Hth8pPVByFetLKvdOMGfX692zvLrc2WSofFGfLoKx8mVbUWHpnhP8ub16alfRxkh1jpGSNk2K6g2nVqlUyadIk9e+jjz4qzZo1k08++UQ9bhdPhYtVYWGhSvOCCy6IOQ0iIiJKDRibEa+qJOLJb3WlrmIrIiIiSk3nJWGcVOMxmObMmaMehTd//nz1yDt0CsGiRYvUKOU18a9//Uulh8f04reCw4cPF5fLVelgVURERJQ+YzClk3jGVkRERGmNMVJC1biD6aabblKPvvvss8/E6w3/VAeOP/54+fbbb2uU1h9//KE6k3Ar11lnnSWNGzdWaTRt2rSm2SIiIkoLePRurK9k16hRI/XYXWjYsKH6XNUrlcQztiIiIkpnqRoj2SVOqvFP5H755Rd5/fXXK0zHrdx6Z6vrzTffrOnmiYiIyCaBUE098sgjkpsbHptr4sSJki7iGVsRERGlPcZJ9ulgatCggWzatEk6duwYMf2nn36S1q1bxzNvRERElEZGjhxZ6ftUx9iKiIiIUiFOqvFP5M455xy58cYbZfPmzWpE8lAoJHPnzlXjKV144YV1k0siIiJKizGYAoGAlJWVRUzbsmWL3HnnnXLDDTfI119/LamGsRUREVGcpHCMZIc4qcYdTPfdd590795d2rZtqwahPOigg+SYY46RI488Um699da6ySURERGl/BhMcNlll8k111xjfi4oKJAjjjhCnnzySZkxY4Ycd9xx8vHHH0sqYWxFREQUH6kcI9khTqrxT+Qw+ORzzz0nt912myxevFh1Mh166KHStWvXuskhERER7RHrN202CZ5wV/QTTzxhfn755ZclGAzKihUrpH79+uou6oceekiGDBkiqYKxFRERUQLjJJvESHaIk2p8B5PWrl07lWk8/Y2dS0RERKl7B9P999+vfhY/duxYc1ppaalceeWV6gmwOTk5cuaZZ6pbtGtrw4YNEXHFzJkzVdoImvSYA7/++qukIsZWRERE9ruDiXFSDe9gGjdunFTXf/7zn2ovS0RERMl9B9P3338vzzzzjPTs2TNi+rXXXisfffSRTJkyRXX+XHXVVXLGGWeob9ZqIzMzU0pKSszP3377rfomzjofd0/bHWMrIiIi+9/BxDgphg4mPCGuOvDtJhEREaVGBxM6cs477zz10/h77rnHnL5792554YUX5PXXX5fjjz9eTZs0aZIceOCBqkPoL3/5i8Sqd+/e8sorr8iECRPkq6++UndF6W3AqlWrpFWrVmJ3jK2IiIjs3cHEOCnGDqZZs2ZVZzEiIiJKcvn5+RGfMzIy1Ksy+Anc0KFD5cQTT4zoYFqwYIH4/X41XcMDQPATr3nz5tWqg+n222+XwYMHy9tvvy2bNm2Siy66SFq2bGnOnzp1qgwYMEDsjrEVERGRfWMkYJwUh0G+iYiIKHFiHStAr4OnwFqNHz9e7rjjjgrLv/nmm/Ljjz+qW7+jbd68WQ1M3aBBg4jpzZs3V/Nq49hjj1UdWJ9++qm0aNFCRowYUeEOp759+9ZqG0RERJSaYomTahojAeOkWnQwYUyFyZMnS15ennq/N++++251kiQiIqIE/ERu/fr16nquVfbNHJYZM2aMfPbZZ2rMo/0NP7XDqzKjRo2SVMDYioiIKLl+IledGEkvxzipFh1MGLxTj6+EAudYS0RERPbsYMJ13Bo8VQZ3EG3dulUOO+wwcxoegfvll1+qR+POmDFDfD6f7Nq1K+IuJoyXhLuOaN8YWxERESVXB1N1YiRgnFTLDqbhw4eb32DiTiYiIiKy50/kquOEE06QX375JWLaxRdfrMZZuvHGG9Ut5B6PR2bOnClnnnmmmr9s2TJZt26d9O/fv+aZS0OMrYiIiJLrJ3LVxTipak6pZhCEbynB5XKpbzWTSXNXPWnnzpXR9Teoz34jIB6HW6aXeGWBzyeFoVJzOqwLFMgK/55HHP9ZPh/TeniyzemzSx0Ryw3IdKp0NwcLzTR/9RdLjsNrpo33WgtXjloW6+C1M1SsXlY5znDHXaHhk66eHMlwOFVaenoHd6aZl2iDsnzq34bOcJ6xjs4vpiHN27YerNLDdnWaGvYB07DNtwubVVq2yBPWRRqj/jjS3M8yI2BuF/M7T/mnej+3NKT2FWWM/Qd8Xh7Ycxz0ejqvjZ2Zahm9Dy/mNze308tbpMrQCsvqNJAP7KdO95SlQ9X7jPL0UC9Ap4dy1MdhYKZhlgvm4zUgw7/n2Di8alvIN+YhfV0WqCc7Qn5zHzEvx+GWRb49x1/vE2Af9Laj9fL6zDqo0peQ2ibSRP2CjcFween6pdPGtFxnmTqG7V2Rp7Ouc7pc27p3qeOJdbAPOu99vF5zGaSPeqXLHMug3iMvX5flqXoSrvPh7ec6RVpn7JTndx6ulsF62CaO98IbnpIbG62UD4rDxwrl/fTu1ipNbP/3YMjM5z1bjlfHDPM2BUsijr+V9XzUx1Wfk9OKGpvHCOf9sT+frfKK+oF0dXmgbupjovdbpwOtXXuWjz6OWF+f09Z6Yp2v6/TM0nCZWY8jyj/6PMR+Iz29z6DzjXqActN1ULUNDq/ajj5+SE/vi04j3wi3SZi+PRg+J802ypkpS3zhPOhp+jgPX3mymQd8BuQf9d1aJta86vbNrL9GQB7acrJaT5+nmK/qb3lZW89NvS/43MjpMeso1lnqz1XLRx93XZa6LdDlHl1f9Pzoc0+fX42d4ToIV20Mj+mDfOBcwTZR9lhOt6Ev7z5IyoyQyq8+7rodTsg3c7G8qik3N1cOPvjgiFe9evWkcePG6j3uvrn00ktl3LhxarBqfJOHDih0LtVmgO90sj9jK4/DZZ43aB+t5zDOh+jrLKDut3RlRbRTerq1fbS2AXpZnC+IB3Q7hG3oZaK3peKV8msgoI1GHgFtBubjGom09HLWNPS06PbJep2zbkvDPL3vKgabM9Jsq3R62H50+2zdBvbTmndrPnQbiu3odgTLWq8j1nbZmn89HXGsXk5f69BG6evoozs7qOmX5G0x22jdlmFZxEhov3t6nGabqbeh86SXxbUX0O6qa1Co1MzvxeuONtt3637q69nawJ7jq5fRxxXTdVnr99ge6sknxc3Ve7yqKmNcw6KPnS5Xfbx0Gen4Rs+3si6Hfcl0+NV71NMD3OFytl5L724xW733OhxqP8c0XKs+47qBWAbroVxRd5A28odpgOsErhEFhkulqa81iNV0nUUa2CaOJ+IkvX+4Xul4CvlYNeIZdTzwuZN3mxl7WWMPvP/7mkHhtA1fxLU3nJ/wPuCzzqOuAzjf8B7/npi9SQZl5Zv1C3p7d6jt6zqI9FFe0X9LYB21385M85iBrq86FkOsqv9WsF6z9d8+mK5jYvy7LOA0/waytjPW+objWRAKqs8fF7Ux4wJdDtg3ax0xy628/mI68o7YDTE4XijvcGzvNWMGbGNKYf2I9ie63uJc0NvBdpEmFJQXiY49EHvruoPlP9zZ2yxPnBvWvw9B749OR/8tAi1d4XqkywTnuo5fkH44tt5zruvzQ6etzxW0F7p+6DKeW+apcO6NyNlttm/WdnZso4Uqn8dl7lCfP9vVQ+UFL78RPj77TR3HSMA4qZYdTE2bNlWPHQbDMPgTOSIiojT3yCOPyF//+ld1B9MxxxyjfhrHcRirj7EVERFR6nokTeOkav1EbvTo0XL66aerjiW89ja+AsZoICIiIvv+RK4ys2eHv9HX8NP5J598Ur3qAp5eFwqFpF+/fhHT58+fr+74Ofzww8XOGFsRERHZ8ydylWGcVIMOJjya75xzzpGVK1fKaaedJpMmTarwaGIiIiJK/kG+7eLKK6+UG264oUIH04YNG+SBBx5QHU12xtiKiIgouQb5tpMrkzROqlYHE2BgT7zGjx8vI0aMkOzsyN9jEhER0X6QJh1MS5YsiXiKnXbooYeqeamAsRUREVGcpUkH05IkjZOq3cGkoYMJtm3bpp4YA926dVNjCRAREVHdwnCnjhjXs5OMjAzZsmWLdOrUKWL6pk2bxO2ucfiS1BhbERERJS5OsluMlMxxUrUG+bYqLi6WSy65RFq1aqUGq8IL7/E0GcwjIiIiez9FLhmcfPLJcvPNN8vu3bvNaXjq2i233CInnXSSpBLGVkRERHGSBjFSMsdJNe5guvbaa2XOnDny/vvvqx3A67333lPTrrvuurrJJREREaWVhx9+WNavXy/t27eX4447Tr06duwomzdvln//+9+SShhbERERUSrESTW+d+qdd96R//3vfzJw4EBz2pAhQyQrK0vOOusseeqpp+KdRyIiIkrwU+T2t9atW8vPP/8sr732mixatEjFGRdffLGce+654vF4JJUwtiIiIrL3U+T2t9ZJGie5Y7mNu3nz5hWmN2vWjD+RIyIiqmtpMsg31KtXT0aNGiWpjrEVERFRnKTJIN/JGifVuIOpf//+ajDKl19+WTIzM9W0kpISufPOO9U8IiIiqmM2DYT2BT+/Hzx4sPrmDe/35rTTTpNUwdiKiIgojhgnSaLipBp3ME2cOFEGDRokbdq0kV69eqlpuCULnU0zZsyIOSP333+/GqRqzJgxahtERESUXj+RGzZsmBo7AHdF431VHA6HBINBSRV1FVsRERGlm1T+idwwG8RJNe5gOuSQQ2TFihXqt35Lly5V0/A7v/POO0/97i8W33//vTzzzDPSs2fPmNYnIiJKGyn8E7lQKFTp+1RXF7EVERFRWkrhn8iFbBAn1aiDye/3S/fu3eXDDz+Uyy67LC4ZKCwsVAHUc889J/fcc09c0iQiIiJ7w0/xzz77bMnIyIiY7vP55M0335QLL7xQUkFdxFZERESU2l5O0jjJWZOFMSZCaWlpXDNw5ZVXytChQ+XEE0/c57JlZWWSn58f8SIiIkrHW79jedkJnoSye/fuCtMLCgrUvFQRz9iKcRIREaW7dIiRkjlOqlEHk+4QeuCBByQQCNR64+hZ+/HHH2XChAnVWh7L1a9f33y1bdu21nkgIiKy5a3fsbxsxDAMNYZAtD/++EPFAKkkXrEV4yQiIkp7aRAjJXOc5I5lvKSZM2fKp59+qsYMwKPxrN59991qpbN+/Xo1oPdnn31mPo1uXzAI+Lhx48zPuIOJnUxERJROUnmQbzj00ENVwITXCSecIG73nlAFA1auWbNGDYidSuIVWzFOIiKidJfKg3zbIU5yGOj6qoF93W41adKkaqUzbdo0GT58uLhcrogCQUE5nU51m7d1XmXQwYTeuZ3LO0lebnjZe7Z3l1ubhAfI1ApD4VvPc5yZsjlYKC1cORHzdoT80s6dKztDxWpaQSioPmuYHj2tMr/6i6WHJ1st7xGn2h5MKawvR2dtMLfrN8LfUE4rahwxXcN8j8NtbrelK0vWBkplQzBXunsK1PLWZRo6s83POr+Yhn1DHqzzrOUBvwdDKs/WeYVGQHyGsdf9xXKbggHp6tmTd70d679lRkClhzzr/OAYXLpqhLzQeYoUhERynVKhDKzmloaks6c4Yhmk0diZKQd9eamsOPYllXaGw23upzUPL+S3l7NzV6gysZpd6pCBmYYs8Pmkj9cbMW+Fv1Dt2/QSrwzK8kWUK+Z9V9pOzsvdYW7ntYJG6vO6QIE6XmAtc2uerGXol1BEXdHrYzmdh+h1df3CuqgfXocjok7octdp6vJa5c+WvhmhCvnSZdzAVarqAupxe5dTHbccpCch+by4pYzI2W1uA+nBnyGnWsdaTrp+nbn8THmi81vmPujjj/yXGSF1/FCvrccfx6SXt0hyHF5zH/R5sDqQp44XPLCji9zYaKWZll7f+lkfL+uxi/5Xw2e9zWUBp6oPOr+A43t6vY3mvGg4VtiPDEf4plCdB11PUWbWehZdX1H+AzKdKh9vFXSV0fU3ROQRx6SxM1xm0XXcSrdvOj86D/p8xvSWLrc6tta0rO2iTtfanlnbE+tn1A2dR+xfnsOn0re2O7q9w7HWdUGnobdr3VfrNBwTvZ6uY9H5i9533Y5/XdpETs0urlAvdFlXts/WvOl8A+bh3JxacIiMabg2or5DfkFQGh6wWt2mnJeXJ3VFX/N6XnyfuLzV+2LGKugrlZ8n3VLn+aytO++80/z3uuuuk5ycPW2/1+uVDh06yJlnnqnep4p4xVb7ipNQj63Xdut5gPZ3QIa/Qhujl7Gec9Z0MN0rIXWeRsdY1lgFrG2JdRmc57rtgOi2XS8XfW2zpqW3hbaokzsQ0cZjXqHhi2hnrG2gdZlFvnrmtcbaNuj5uB7lOl0qf1+VtFbXRtBtS2V5quyag+u49TpgXQZpnPbbWTK522tqW2gLrXm1Xk+wjU3BEmnk9KjtIh8TN54sUzp9bh4fHLfoNi06ZrPCNfatNX1k/mGvRcxDHnX5RB/HyuqMrieVbSv62lLVMdZx0XdlTlW+ejm9H7rse3l9FWIqDflBPIPp1tjKCvn4wZelYpAlvkzzmmwte2ynmas4oq5ar38d3JkyszRb2rp3Sa5jT9yCdB7Y1l/ubrZALb884DPPJR0/6jgN6SN/0cfFGr9gH1U5WK7B0eWP+v2nijWc5v5EHyvMryz+xvpYLzpu1ueljilwbFDv9N8SKFuUwc/+kKqf+nN0nbPm1Xr8UVdbufa0EzrOLTBclf6tAtb4T9PHzFpPosvTGidZ5+n8RMdpWvT5pM9vbFO3D9Y2Nrqcsd0mroplG133K/u7Rm9PHyP8DWX9OwHQlur09fmHth10uxZ9rK3nqk4rOj7X5TJ85ckytcunEWlUdk5Zzx2UWdvSjKSPk+wSI9khTqrxHUyxBjnR0Nv2yy+/VAiwMNDljTfeuM/OJSIiorSUwk+Rg/Hjx6t/ESCdc845FQavTEXxiq2IiIjSXgo/Rc4OcVK1x2DCY/AwPsCAAQPkiCOOkJtuuklKSkpi3nBubq4cfPDBES/cEt64cWP1noiIiNLX8ccfL9u2bTM/f/fddzJ27Fh59tlnJVXEO7YiIiKi9HB8ksZJ1e5guvfee+WWW25Rt2C1bt1aHn30UTUoJREREe0/6fIUub///e8ya9Ys9X7z5s3qabMInv7v//5P7rrrLkkFjK2IiIjiKx1ipGSOk6rdwfTyyy/Lf//7X5kxY4YaP+mDDz6Q1157TX37Fi+zZ8+WiRMnxi09IiKilJMmT5FbvHix9O3bV71/++231eDX33zzjYo9Jk+eLKlgf8RWREREaSUNYqRkjpOq3cG0bt06GTJkiPkZPWQYkHvjxo11lTciIiKK4sBjaWN82Ynf7zfHFfj888/ltNNOU+8xVuOmTZskFTC2IiIiiq90iJGSOU6qdgdTIBCQzMzI0dg9Ho/aMSIiItpP0uQOph49esjTTz8tX331lXz22WfmI3fxxRbGa0wFjK2IiIjiLA1ipGSOk6r9FDnDMOSiiy6KGKW8tLRURo8erQbn1t59993455KIiIiUWMcKsNv4Ahj8evjw4fLQQw/JyJEjpVevXmr6+++/b94SbneMrYiIiBIfJ9ktRkrmOKnaHUzIdLTzzz8/3vkhIiKivYn1mzabBU8DBw6U7du3S35+vjRs2NCcPmrUKMnOzpZUwNiKiIgoCeIkm8VIyRwnVbuDadKkSXWbEyIiIiILl8sVETRBhw4dUqaMGFsRERFRKsVJ1e5gIiIiosRLl5/IdezYUT1MpCqrV6/er/khIiKi5JcuP5HrmKRxEjuYiIiI7CRNfiI3duzYiM94qMhPP/0k06dPl+uvvz5h+SIiIqIkliY/kRubpHESO5iIiIhsJF3uYBozZkyl05988kn54Ycf9nt+iIiIKPmlyx1MY5I0TnImbMtERES0/x6/a8PgqTKDBw+Wd955J9HZICIiomSUxjFSMsRJvIOJiIjIZuz4TVu8/O9//5NGjRolOhtERESUpBgnNUpY2bODiYiIiJLOoYceGjF4pWEYsnnzZtm2bZv897//TWjeiIiIiBLp0CSNk9jBREREZCeGEX7Fsp6NDBs2LOKz0+mUpk2bysCBA6V79+4JyxcRERGlWJxksxgpmeMkh4GuLpvKz8+X+vXry87lnSQv1yXrAgXSzp0rm4OF0sKVI9NLvNIvY5c0dGZHrOc3AuJxuGWFv1BautyS48yMmF8YKlX/LvJ5ZUCmU3aGis00MA/LYxsZDqeajvQKDZ96r/MAWA8wXa9XGaS1yp8tBUamHJWRLxkOt8pfVZBujsMrm4Ilkut0mXmz5lMvg3R0PrQyI6TKR5eTNT2dd+yT9meoVC1n3X/8i3yuDZRKV0+OubzOt56vp+m8VVYOmKfzpNfDOtZyxfRlAaf08XrlV3+x9PBkm2liPxo7M9U6L+Y3l22BXLmywWK1HZ0G6PKItsDnk9Yun2wIelX60WWJNC/I3aDWteYf2z366ytlxbEvmfv8SXFzOTprg1k3dH3Q6emy1mWKtIfUW2UeB71NfWzg0Z0d5ML6S9T77cGQKm99jLBvG4OiygPb3xQMSK5TzHWtkBdrfbGeLwUhUeke+M358s1fnq1wzsDc0pA6H7BdXfdAL/tBcbacmr2nrs0udcjATEPtV0EoKGWGQ1YFGkln9w61LZx/uu7oOuIRZ0T9stap6OMSvf7Tu1vL6PobKuRbr2fNq4a6tC1YTwZk+NXnMiMgfgmp+pjjiGwb9P7rstd5th4TlGlLV5ZZb61lr8+t6PX1ctb6rusA6pE+N/Syut3CsW7icprbt56b2AfUM2v56W3iOHXybJcD3HvmY960osbS1J2vjhny+0b+oXJjo5XmunPLPNLLW1ShvbG2NdbyxjG31n3kq9AIRLSb1jLANr0Oh9pXfY6D9ZzT62j6PNF1LZr1PIo+7jp9LLPUnyu5zjJ1/mMbqAe6nUfbrI+7FZbT5/G63YXSsfsm2b17t+Tl5UldX/MO/9s94vZUfj3Zm4C/VH743611nk9K3jgp+nzV18/oNqsqe4tlcE4sD/jEKyHxiVMaO0PmvMrOQ8Rog7J8lcZY0bDM6Uv+Ll8ePE19RjvYwR2+7u9NdBur2zvrv9blrNN0m4zy0m1CdBsULbqtr6yMrOtbYy3dHlYVq+g2B9emnp9fKT+f+KT84MtS1y/rfujrqHW/rOlGx2vWPFhjCvW5/Fqsr/mLfPVUW2uNu6qCa2YzV7EZk1jju+h4Fdc5nZ6+9iG/iDGtMY0uP7ThqF8+w5BGTk+FOqPjAyzX3uWsUE5g3Qd9fVLtefkxjI739HUY11x97QXkD8dkR8ivrmHwZ8ipzgNY6m8mjZyF0jcjFLF/gDJAjDem4dpKy0IfG31+4jPKBHT8o+dNKawvI3J2m3m1lreOj6KPvXXfoul9tW7LWmdQJ6xlr6ch1sO5qfOFbV+a97v6jLqJ+CT6nLQeM/03GOi6p7eDeL2bO6TeW2NOHf9ifcQD3T0FEfVTl4U+f94raiXn5e6I2Nfo9g/lEh0H7u38t/69oeO26HmIi8J1Zk8sbl0P06zxif77RKeFfM4va6Dazei8W/+W0ue7tq92sirWcyQ6NtLb0dvEebPI11yOyNhaoeyxTn5BUBoesDqp4yTGSPHDO5iIiIjsJNbBKG34dVIwGJRp06bJb7/9pj736NFDTjvtNHG5wh3cRERERLWOk2wYIyVrnMQOJiIiIhtxhMKvWNazk5UrV8qQIUNkw4YN0q1bNzVtwoQJ0rZtW/noo4+kc+fOic4iERERpUCcZLcYKZnjpIr3/RMREVHqPX7XZt/OXXPNNSo4Wr9+vfz444/qtW7dOunYsaOaR0RERFRBGsRIyRwn8Q4mIiIiSjpz5syRb7/9VhpZHrXbuHFjuf/++2XAgAEJzRsRERFRIs1J0jiJHUxEREQ24jDCr1jWs5OMjAwpKCioML2wsFC85Q9kICIiIqptnGS3GCmZ4yT+RI6IiMiOj9+N5WUjf/3rX2XUqFEyf/58wQNv8cI3daNHj1YDWBIRERFVkAYxUjLHSexgIiIisuE3c7G87OSxxx5TYwv0799fMjMz1Qu3fHfp0kUeffTRRGePiIiIklA6xEjJHCfxJ3JERER2EutglDYLnho0aCDvvfeeekqKfvzugQceqAInIiIiorjFSTaLkZI5TmIHExERkY2kyxhMGgKlRAdLREREZA/pMgZTssZJCf2J3FNPPSU9e/aUvLw89cLtXZ988kkis0RERERJ4Mwzz5QHHnigwvQHH3xQRowYkZA8ERERESWDM5M0TkpoB1ObNm3UY/QWLFggP/zwgxx//PFy+umny6+//prIbBERESWvNBnk+8svv5QhQ4ZUmD548GA1j4iIiKiCNIiRkjlOSuhP5E499dSIz/fee6+6qwmjn/fo0SNh+SIiIkpW6fITuaoes+vxeCQ/Pz8heSIiIqLkli4/kStM0jgpaZ4iFwwG5c0335SioiL1UzkiIiLay+CVsbxs5JBDDpG33nqrwnTECgcddFBC8kRERERJLg1ipGSOkxI+yPcvv/yiOpRKS0slJydHpk6dWmWBlJWVqZfGbzCJiCjdpMsdTLfddpucccYZsmrVKvUTepg5c6a88cYbMmXKlERnLykxTiIionSXLncw3ZakcVLC72Dq1q2bLFy4UObPny+XX365jBw5UpYsWVLpshMmTJD69eubr7Zt2+73/BIRESVUyIj9ZSP4Gf20adPU43evuOIKue666+SPP/6Qzz//XIYNG5bo7CUlxklERJT20iBGSuY4KeF3MOF3g/qxen369JHvv/9eHn30UXnmmWcqLHvzzTfLuHHjIu5gYicTERFRaho6dKh6RVu8eLEcfPDBCclTMmOcRERElD6GJmGclPA7mKKFQqGIn8FZZWRkSF5eXsQL/EZQ/dvOnSubg4XSwpWjPg/K8klDZ7YUhkrVy28EZGeouHydgHT15EiOM9P8rGFaoRGQAZlOc3n8i2V+D4ZUWlBmhMr/DajtYNvIg+YRp5q+wl8oGQ63SgPrYjn9L+Y1dmaqbSG/WO5nfzhd7Vd/sVpW53N1wC1/hkrNbSFdpJPjCA/yhWWxXY/DrZbHe/3SecbygHyoMjJ8Znq6LLA+XjkOt7nOpmB4nl/C6TRxhasQ1tfrIj8ow+UBn1ofsA1dtjqPep9AHzPMfyG/vbyY39ycp/bNmSl9vF61Tg9PeVoOr4z640hVfmsD4WNyQe4GubHRSnX89D7qfdd5wT7PLnWovJ6ydKhKF9vX6et11gUK1LKX5G1R6+p86DLPcDhlxbEvqXWQFspkcPYWlRbKGcugTPGvroeAY4cy1Wnjva5nWmPLdsY0XGvWpVyn5dgZPhn3xymyK5hpbh91WpelXl8b+PlYlcaUwvqywBc+3sh7QUjUevDbka/KxmC4jKaXeM1tYTnUUdD1E8ttD+6pq6dmh7eFckN+enmL1HFEWWBb2AbquN4W9gXL6eOyyFdPle9rBY3U8dP1T9dHpIv8631COnNLQ2oZnCPdMzaadVCvo//Fesgr9sfaBqAuDcw0VBooT2z/P9v7qjJEeWJZvJD+Qd5S9a8+N3S6LV1ulTeUF/ZT5VucZh3HdjAd8/EeZY86gHV0+WH6pmCJWk/nD8cF6au8lJ/HmIf91sca03R5Iu/IH/7V9R3b0W0XPmPb+jjp8tXv+2X+YR7LXKcrfB6FStU6qv5kGipdpIW86/bGem7p8sE03Z7othH5wr7ozyhvHD9dJ63tmT7HAW0itqfroi4vLIf0MB15s9Z5vFDeuuz0NLzH8khfn+tYBuvj/NeQV+QN83S9R5uhz2Fdnvpca+DMkv0qTcZgilZQUCDPPvus9O3bV3r16pXo7CSlquKkXaES1bbifEO7ADgHcK1BXdbXaD09ui010y+/dgH+1ddJnFdIB+cW2iT8i/MD6VuvSVa4Huh4RW9HX2N1e2K9jn958DT1/undrdU2sB/WOAJ5wT5a98N67UX+0A7o/UfcgPMc29btGdphLKPTRRut4iBnppqurzc6fes1Vrf1+FeXiXbTll5qed1W6mXwWbX95XkLx2kBtSzyFhE3Gj5VlsjL6pNfUP/q6xe2hXYU62M6YiO9/9Y8qnbM8Jn7ofcJLx3LHuD2yj3bu6tyRlqY19KVpcpCt7XIB6ZHx3LWGBdtJ44TYiUrzEdaOF76WmKNeTYEveZ1Beuv8ofrJvKLY4dyQR6RB5S3Pjb62nTb1oPN62JjZ0h+8GVJd0+Bmb7+F+vruoDYVtdTXP+sdRFpWuvwqkAjFddgG4iBMW9HyC+NnB5Z6Gukrt3Ybr7hVXHOcZk7xC8udZxRLlj+nOUj5PPilqosLqy/RF2vMK8gFFTr4xhhf/Wx0X9LYLpPwuWq5yMWw76PyNmt0tAxu46jkP/R9TeY54A+BljH+jeTrq/6vNfxhS5Lva4+d7C/KDcs+8COLvJdmVO8Dod0cIfjfxxX5Afb1vuA9sNaJ1XsVf73md6OhuOG44Pjof/2wHVaHxfEMsg/6j1iogyHodJp7SqoUOf0OqhneH9e7g6zzUFe9N9G+rzUbSOW1WWl2zidd0zHcbPuC/YNf6NhXZ0WYD90XIRzSbdLOk3d/uJYWeMfHZdgutqGOOWEzD3ns4qtytuuJb49ba01LrO2WSgrvZ/WNPTn6L9PdXq67dLnGvZPt1dYRv9NgWOi2wZN/72o/1bfb9IwRkqmOMmd6G/a8Bi9du3aqQJ5/fXXZfbs2TJjxoxEZouIiChpOWIcKwDr2REetfv888/Lu+++K61atVLjDTz55JOJzhYRERGlSJxk1xgpGeOkhN7BtHXrVrnwwgvVOEwnnHCC+nkcOpdOOumkRGaLiIgoeRlG7K8ajOVzxBFHSG5urjRr1kz9ln/ZsmURy+DhHFdeeaU0btxYPaTjzDPPlC1btsRlFzdv3iz333+/dO3aVUaMGKHGXcTdzRhrANORNyIiIqIK6jhGAsZJSdrB9MILL8jatWtV0IjOJgxIxc4lIiKifT8dJZZXdc2ZM0d1Hn377bfy2Wefid/vl5NPPlmKiorMZa699lr54IMP1JNKsPzGjRvVt2bxGLQSXzz9/PPPMnHiRJXu448/Xut0iYiIKPXVdYwEjJOSeJBvIiIiqoFYxwqowTrTp0+P+Dx58mR1J9OCBQvkmGOOkd27d6svifDTdv1o3EmTJsmBBx6oOqX+8pe/SKw++eQTueaaa9STZXEHExEREVGdxkk1XJ5xko0G+SYiIqKqOQwj5pd+Aqv1VdWDNazQoQSNGoUHUUZHE+5qOvHEE81lunfvrsZUnDdvXq0O39dff63GZcSTZfv16ydPPPGEbN++nVWCiIiI9ml/x0jAOGkPdjARERGlkbZt26oxjfQL4wjs6+muY8eOlQEDBpiPvMUYSV6vVxo0aBCxbPPmzdW82sDdT88995xs2rRJ/vnPf8qbb76pBq1EPvBzPXQ+ERERESU6RgLGSZHYwURERGQnoVq8RGT9+vXqmzb9whNd9wZjMS1evFh19OxP9erVk0suuUTd0fTLL7/Iddddpwb4xk/1TjvttP2aFyIiIrKJ/RgjAeOkSOxgIiIiSqOfyOXl5UW8MjIyqtzWVVddJR9++KHMmjVL2rRpY05v0aKF+Hw+2bVrV8TyeIoc5sUbBv1+8MEH5Y8//pA33ngj7ukTERFRathfMRIwTqqIHUxERER2HLwylld1N2EYKmiaOnWqfPHFF9KxY8eI+RgfyePxyMyZM81py5Ytk3Xr1kn//v2lrrhcLhk2bJi8//77dbYNIiIisrE6jpHUJhgnVYlPkSMiIrITfMtW/k1bjderJtzujSfEvffee5Kbm2uOq4TxCLKystS/l156qYwbN04N/I1v+a6++mrVuVSbJ8gRERER7fc4qYbLM06qGjuYiIiIbMRhhF+xrFddTz31lPp34MCBEdMnTZokF110kXr/yCOPiNPplDPPPFM9ZeWUU06R//73vzXPGBEREVEC46SaLs84qWrsYCIiIqIKt37vS2Zmpjz55JPqRURERJQuGCdVjR1MREREdrIffiJHREREZEv74SdyVDV2MBEREdmIIxR+xbIeERERUSqLJU5ijBQ/7GAiIiKyE97BRERERBS/OIl3MMUNO5iIiIjsJIbH6ZrrEREREaWyWOIkxkhx45QUsDLgk9mlDtkcLJQWrhyZXuIVvxGQFf5C9a9fQlJoBMzlPQ63/BkqVe+xzLpAgfpcGCpVy+8MFat05paGJMfhVa+Gzmy1Xg9PtkoL8xs7M9WyP/iyVFpflbQOb88IqLxgu5DrFCkzAiqNHGemWneRz6v+7erJkbWBUvnVX6zWwTb6eL1mXpEWtgnIp56PdbG8StPhVenofcpxuFXe9b4iDdD75TMMtTzeIz/Yb6SDssAym4IlUmj4zHWwDNLAOnjp9PQ+oezLjJDaj/D0kNo+8o08Av5F+vo9yg7bR/qLfPXUv5iPeZfm/S6X5G0p3xevNHE5zTLFvlnd1fJTlVfkC2WI/UU6GQ6nmoZ5mI70dRlif7p7CtS8Gd0/kimF9dV8nS+932WGQzLK0/ugOFult8Dnk9cKGsn2YEgKQkGVNrb1XZlTTdsUDKh9X+XPVp91HUIa2C7KS5c76ke4vPfUTdD7geOCdZFn1BdMx7od3JkqPaQ1qd1X0sxVbB4vTMd62Bcsj/XxL6we9ILKz4ic3WYd03UBy6AcoLEzJDtCfumXsUvNw/mk6yLSxbrrA/Uk1xGUVYFG4bpuBFQ9gHbuXFUXsP84jsizXhd03US5YT+xf5h/uLdElUf3jM2q/LA8Xtg37Ne2UIaaj/3W9WlAplO9R10bmBm+MuiywHZ0/cf+YV9autwqX1gH54tKv/y813VzQO5ys3xRfqjPB7jD7YA+FzF/z3641T4PyvKZeQbsd0FozzmI+XjfyR1Q01u6stSxxPIoL6SBOqHri673eP3sD6l8Ii/6vLDS20T+UJ667cN2dJng+GQ6Auo449hhOb0PUGC41DHAeth3QN1s7fKpcx3TUf/RPiDv1rLV508rV/gcsx5nXRa6rJEPdQ44vOr4YV3USeQL558+vrpNxPZQNigrtS/l7RzKAvP1+TB0+WA1Hevj3NTHA/nUZTazNHwe6zR0uWE/kG+9PD73zQipc13vC+oXykO3Jfp8wectwSLZnxyGEfOL0lMDZ5acl7tD1fOXdvdW9RZtMM5tXadR/1HXcX7C3DKPaid1+47l1PkhkW0fPuO80tcAnF+4ZmI9HZfgPabjXNWxAKbp6wPyoen2C+0Z0tVtCqZjG6Prb1DvsS5e+nxGG4Z9xDUL0zBPn8M6tgO9f0gbbRDaX91OeB3hfdD0ful4C2ngGqnjBWt7hXQwX1+DcL3R7m++yLyuIW/YHq6zKG+UYTi+8cqjOzuYcWIvr0/FRyhnHZtoOk9635BPtKOAvPyn1RfmOro9n1bUWLVj2A7y0N7lVPN0+WI7+tp4Y+PFKhbTcRnaYR3/6eOnYxJdnjpe1DGujil1HIL9tZY/Yizsu47J8S/yg2skykVfQxq4wtfqbcF66jOOmb4mXbWxb3m8FlJxWK7TJXc3W2yWDep4L2+4fV4e8Jl50WWi41DE6foc+LiojRkTAPKo6x/Ww7VlQzCcDtJT11rDpfa9t3eHWvbPUDjBpf5cNR3ljnRQBihvxJ44Xti+TnNZwKmWyXAYapqOoXX9Dv8tEZL1gQbmdVzHP9j3cDztNWN27DvOBaR505ZeKg1cw1HW2C7KGzE10td1QMcj+ry1sl4nw/F1uN7BjY1WquOCmBLrIm86DZST2TYYPpUG9k/HDqh3+vzDNlBGusywD4jZvittp5bV57D1PcrRU/7n7Av57cUnTjNG0jGU9bzEZ9Qt1Ad9fuDcBOTj92C4DUSZ6jqk/85Qf0M4vObfmzhueh+xDczXMRPKUf+NhVhMx8G6DDBPlx8gXbQ/yFt0e4V6jXR0WWF7qI+oZzpmQfkjXayn5+t9RB3BZ5SVah8Nn1nHkb7+Gxj7inyh7UBspese6rGOb1EH9d9/Oo84Z3W7pMtYl4u1jdmfGCMlVkp0MBERERERERERUeLwJ3JERER2wjGYiIiIiOIXJ/Eu77hhBxMREZGdIGaK5Ylw/IUcERERpbpY4iTGSHHDDiYiIiIbiXU8JY7BRERERKkuljiJMVL8sIOJiIjIdk9HieGrNn47R0RERKkuljiJMVLcsIOJiIjITjgGExEREVH84iSOwRQ3fIocERERERERERHVCu9gIiIishMMXOmIcT0iIiKiVBZLnMQYKW7YwURERGQjHOSbiIiIKH5xEgf5TpGfyE2YMEGOOOIIyc3NlWbNmsmwYcNk2bJlicwSERGRPcYWiOVFRERElMoYI6VvB9OcOXPkyiuvlG+//VY+++wz8fv9cvLJJ0tRUVEis0VERJS82MFEREREFN84iez/E7np06dHfJ48ebK6k2nBggVyzDHHJCxfRERESYtPkSMiIiKKX5zEDqbUfIrc7t271b+NGjVKdFaIiIiIiIiIiMhug3yHQiEZO3asDBgwQA4++OBKlykrK1MvLT8/fz/mkIiIKAnwKXJUBcZJRESU9vgUuYRKmjuYMBbT4sWL5c0339zroOD169c3X23btt2veSQiIkqWp6PE8qLUxjiJiIjSHWOkxEqKDqarrrpKPvzwQ5k1a5a0adOmyuVuvvlm9TM6/Vq/fv1+zScREVHCcZBvqgLjJCIiSnsc5DuhHIaRuK80semrr75apk6dKrNnz5auXbvWaH38RA53Mu1c3knWZ5ZJriMoXodDWrhyZIW/UDIchjRyesQvIWnozFbTunpy5IPibDkqc7vML2sgnd07JNcp0tiZKcsDPllS1lKG1ftT/gyVqnR+9RdLYyfusxPJcbil0Aio6ZuDhRGfNUzX8/8MOeUAt1fKjIDsCPmlwHCJV0IqD9blddoZjvAvFmeWZktb9y7ZFcyUg7ylUhAKSktXlngcbtkZKhaPOGVZwCmZjoC0comUGeH8FYREpe03AmpZ/Fto+NR8nacNQa90c4ckx5mp0vq4qI2clbNV1gZKpYM7Uy2/xJcpAzKdsi5QoMoTsD4+f1XSXobU+0PlYVMwYJYd1tseDKnPWBZph/MUVMcA20N+UMbrAw2kX8YuNR/rYLvILxSGSmWRz6u2P73Eq8qhhyfb3Bccs6auQslz+NS+YvkffFkyIMNv7ivygzL/pLi5DM7eIr8HMS2kjkd7l1MdM7xH2WFfl/layvCcNWpdHAddtsgn6odPnGp9n2FIO3euygvKC1DHygyHWXZIA2WM9XHsAfuMupnrdKntNXCVqmPbzFUsLV1uVT9RTmAtK2wD+6jLEmnrY4y6jG3OLfOIR4LSNyOktr864DaPL+hjiPWauJzqPACkaX0/tbCjXJK3xayTKMNpRY3l6KwNZv3W67xW0EhOyF4nq/zh9XGsMO283B1mfdbr6HMO62Lf/eJS0w/3lph1EGlOKawvvTM2mPVpU7DEPJeteUW5/OwPSR+v1zw3sTzOV3189H6jLFFHsX18xjmEdLEM0sxxhI8P1kUaug7qc1hvD9Ot+6HrrbXu4/jh+OrjlOEI991jG5iP8wX1DsdBH3McK9RjHEfkwUqfb9a6hTLQxwaml+RJI2ehaiOQH92uIM84dmjHkPcFPp90cgciyhD1prunoEJbZj2XUe91HdZlhHnYJxwD1HGcT9gXvX9IT9ddnBvrA/VkY6ChHJSxSUoNtxSEMmRgpqG2ibL4uPBgOTtvsdqGPm+tbSqOMc5/7INe13qMrHVA7yu0dvnM64A+T3XdsB5XpHPd+r/K5Pafq23rcxF1RZc50sS+4hzWaej6MLc0pOr/A+vbyC19Z6kvPvLy8qSu6GveiZ3HituVUeP1A8Ey+XzVxDrPJyUPXWe++bWl9GjgNq8Ns0sd0tpVoK4Lui1Em3JqdrF5fuq2U19D0OaBbjcW+hpJb+8Odf6hTcF1GG1DachtxhA4Z3AtP8jzZ8Q5aI2VsL6Oe3A+o/3U12OdX5yzoM9LnHu9vD6zjdfp6XMbbQOu8Tr2QxuANlq31Xq6vi6ibcc2cV3DtRnTNwbFPO8Ra+i2yXpNwnaX+nNVe6rbMMR7aLuRht4P3U5ar/eAuNC6z7pdQ6wIet8wH9eMnp7wQdDxgd5vHE+Uv54OyCfW+b6ko5yfu6pCXIB9zXQG1PVhka+eqg86hgPkY2FpG+mesVldc3U+QOdVlwumo7xQ5ro+6ZgIdQfXse/KnOqYISYDxEGdPcWq/Dq582WJv7GqJyg7HecsLGttxgaI21BW+jiDPtY6xgNcM5AvbAfvkc6GYPgYoc4OygpfJ7A/+nhb4xTEUzqmwLVAX89QD7At2BasF3Et0/nD9nAstgXyVPyEaYgl/wzkqBgJ87AeYqbT621Ucf9Zq4bIK53eV8cH9RrXdOv1Wl8XdRnreBTlBDpGQLlbywP7hvMQZYHtYBl97FAnUU91jK/3VcdBKDPsk05Dxwk6HX0eIT/6OFr/9tKxi6ZjL+QF+6nruP6bBeWt64m+NmN7OL+/K20nfTPXRZwPVvqc0ecqyrCtu0jlD2Wi43VdTqreiNMsb5wDaLNQ7rpe6zipl7fI/LtC/w2m6WOk90mfczrO1/ER4PzCcdexqC5nbB/Loj7pmEwfd2tca/17DNOwbzruQxqoszi/dF3WedL/6jZL/6vbSd1GIGZC+esytv4NYv2b0nosdR0BlA+WR3yLY2atky/kt5fR9TdIfkFQGh6wOqnjJMZIKTIGE34W9/rrr8t7770nubm5snnzZjUdFSMrKyuRWSMiIkpOfIocERERUfziJA4jkBo/kXvqqadUT+bAgQOlZcuW5uutt95KZLaIiIiSWHngVNMX1iMiIiJKaYyR0vYOpgT+Oo+IiIiIiIiIiFKhg4mIiIhqiD+RIyIiIopfnMQbX+KGHUxERER2Eorx525qPSIiIqIUFkucxBgpbtjBREREZCd4cmj500NrvB4RERFRKoslTmKMFDfsYCIiIrIT/kSOiIiIKH5xEn8iFzfsYCIiIrIT/kSOiIiIKH5xEn8iFzfO+CVFRERERERERETpiHcwERER2Ql/IkdEREQUvziJP5GLG3YwERER2Ym68zuGJ8LxIXJERESU6mKJkxgjxQ07mIiIiOyEdzARERERxS9O4h1MccMOJiIiIjsJ4dG7oRjXIyIiIkphscRJjJHihh1MREREdsI7mIiIiIjiFyfxDqa44VPkiIiIiIiIiIioVngHExERkZ3wDiYiIiKi+MVJvIMpbhyGYd/SzM/Pl/r168uURd3lyMa71bSvSlrLidmbZH5ZA2nr3qWmLSxtI43dhdLZvUN93hDMlU7ufMl1umRjUGRbsJ6UGh7pl7FLFvnqiUeC0sBVam6n1HBLpiMg6wMNJNdRKs1cxbI1mC0HeUulzAjJn6HwjWC5jqCsDuRJU1eRel9mOMRXfpNYK1c4re3BkKwKNJJMh19tp7OnWFq4cuRXf7FKvyCYpfKPdDF9hb9Q8g2vdHIH1LpI76virnJC9jK1H8g39nNXMFOlX2Bkmmkjn1ge89q6i2R9oJ7aXkFIVB6WlbaS4bm/qOlYD3QZYT72FVAWKKNtgTw5KGOTmuaVkGQ4DLWPKAtsq4nLKUt8mSotrPtLWVs5OnuF2i9AvlA2PTzZMrvUUaGckU+9LSzX2BmSmcXtpG/mOrWvWB774XU4ZJU/WzKdAdkWzFHpho+TR/yGWzyOgPr31Oxi2RkqFo845fdgSKWv97+DO1OmFTWWXFeJ9PbukA1Br5SG3NI3IyRvFzaT3pl/mNtv7dkprV0F5n7iXyy3KVii8uIrP4XwvrEzU372h6QglCEDMvzicbjVvuL98oBP7fsCn0/yHD5VfqgvyDfykONwy6ZgQO0rlkc6rV0+leb0kjy1X0dl5MsPvixVf/XxXOhrpNZHmQzIdKo6g+Ony2BzsNDc57WBcHljH3CcsMxxmTskx5kpHxRnywZ/Qxldf4P4jYDK+9zS8O+Xsb/flTnVMb0073eZWZqttom6P7+ko1ySt0Xt12pfU+nk3SYbAw2kk2e7qifYn8O9JZKh9q/EPC9QLw7y/CnzS9vIiJzdKt+oQ58Xt1TbRF3DebM64FblgG3hmCz156p8Dqn3hxSEgrItlKHOT11vcL6ifJf6m8kRGVvV8jh++tzv7ilQZV1oBMJ13R8+rsgTzluUK+oW0kA56fe5TlHnJOoUzkVAfvV7zNd51MdSnyN62ygHTEe6qOvYP90G5TrL1H6gnv5Q0kmG5CxWaWY4nPJ1aRPJdZZIL2+RattwfqH9Ued8KJxnpIf8Az7jXAm3Ca6ItkvnBWWCfUZ5LS1rISdkr1P1BDBdl7U+F9G24pjo8wj5wr7rfcGx/q60nTp3sD84X1HH0KYNq/enqj/YPo5LI2ehWgfng277/gzkqHWRPtZbVNJO/pr7sywpaym9MzZIV0+OTCmsL5lOv1p/rb+JuTzS1ccWx+DzwoMkw+lX7Y+ug6gzHTzbVdkenrVa/BJulAdmGmY9R5nhuoA6eHTWBnlpd28Z1eBntZ+6fUN9QFuBc2FYzjJVZs1Ls6ThAatl9+7dkpeXJ3V9zTux0cXidnprvH4g5JPPd0yq83xS8tB1ZufyTlKcXaLaO9R9nCs4v/U5g/ME1whc/3RboOMHfa7i/EN8gjgJ7QfOCbTPuA7rthznDdo/XHORJmA5xDS4VqI91LEL4g20kTjn9PyvStrL6fU2qnYS9LJov3S7g/NzcPYW8UtInZtYRrefaANxTUCemroK1bkKur3EOYz90e0Y9l23+7ods17r8S/yiHYU66Ds0A5ju7q9s8Z71tgIkIaG9qWR0yPLAk75vqSjdPBuU9dR7DfyrPOq4zW0g4jvVvvD7T/igkLDFxFnYdkl/sYqHRzPglCWdPdsjbge6eMLaH97ebeo/OG4fFzURsVY+lji2o31rcctvF74WgBIE3nWZYbrGK5LOJ66fddtMupJS1e4PqAOIR5BfrBPiGlQb9q5c2V6iVcGZflkXaBA5Q0xDGJyXB8RY5yYvVKVHeIf5APHAvHOozs7yJiGa9V1BPnA/qD+IqZDHIa4tZV7p2wMNFTXr/Yup6pb2Lcch1fFObimYz9R53GdAR17o06h7LA8YskdIb95rLEPg7LyVRqIf7A95E1fz/VnrI/jYY3R8BmxG46hzhtgHx7Y1l9ubTpflRnyi3qujwPqP+i4CPFh9D7o+A51B2VeGCpVdQ7xGa6lqJ84dr28PpXWIp/XjBf030XIB+oZzhGUJc4nHF/kG58RE6G9QFyr9w91BHUU13rreaLPAdQJXS8B6+E4I0bQxwbli/qMvCMu0LGtXhd0fdZ/X6G80Y59Xxau27odQj6b4jgYLnWOIkbXZa7PddRNlC/2FaxxmT6vdZyn67Nus/R5qP/W1PuEOoTjgTQQiyCWQ13C+Y308Tcp2o1XdvSXG5vOM/+OxP7Ozj9QLm00Vz4uPFiauPMlz1WqzifYEcpRcbX+exLtMOo3/o7RfwfpcwOQN30O6TgK5yfSQNyH+oOy1fuM8+HKDcfI35vMM8913eahfLHsMl9L6eTdquIp3W7ov2uxLZx/R2f9bv5tg7LBccV5+/nmTjKh//SkjpMYI8UP72AiIiKyEcMIqVcs6xERERGlsljiJMZI8cMOJiIiIjvBXZOhGG4+tu8Ny0RERER1FycxRoobdjARERHZiQqC2MFEREREFJc4iR1MccOnyBERERERERERUa3wDiYiIiI7CYVEHDGMp8QxmIiIiCjVxRInMUaKG3YwERER2Ql/IkdEREQUvziJP5GLG3YwERER2YgRCokRwx1MfEIKERERpbpY4iTGSPHDDiYiIiI74R1MRERERPGLk3gHU9ywg4mIiMhO8OhdB58iR0RERBSXOIkdTKnxFLkvv/xSTj31VGnVqpU4HA6ZNm1aIrNDRESU/BAEYTDKGr9i6JQiIiIiSvk4iTFSSnQwFRUVSa9eveTJJ59MZDaIiIiIiIiIiMiuHUyDBw+We+65R4YPH57IbBAREdmGETJiftUUvgDq0KGDZGZmSr9+/eS7776rk30iIiIiiof9FSMB46Qk62AiIiKiGorp53Hlrxp46623ZNy4cTJ+/Hj58ccf1R3Hp5xyimzdupWHjIiIiJLTfoiRgHFSCnQwlZWVSX5+fsSLiIgoneyvO5j+85//yGWXXSYXX3yxHHTQQfL0009Ldna2vPjii3W2b1Q7jJOIiCjd7a87mBgnpcBT5CZMmCB33nlnhenFhUEp8IZ7HYtLglIQDElxWVAK3eFpJWUBKXbt+VwUDEoB3jsdUhgMfy4znFLgC0mRLygeCYnbtacXs9QIScARkuJAUJyOkBS6QlIUDKltlhkhKdSLOkJSFAhKFtZ1hMRnOMRXPqvAFf63EHkLBCXoCG+nwBOSbOTNH55ejLwFw+nq6YVGSOUX6yK9kpKAeq/zjf1CftT+G3vSRj6xvMorlgmEt4f8YlulZQEpkPB0rKfyV15Gel8BZYFtYVqhLzzNKyHxOQy1j0gf28pwiRT5wmlh3RJfOJ9YD5AvlE2+JyhFpY4K5Yx09LawnNcZCu+rPzxNlZc7JF6HQ4r8IQk4Q6q8kC6gLPyGQzyOoPo3H2UZCqlKHi6vPfuf7w5JcVFQXK5w3cH8slBI8n0hKSkKb1Nvv8gdNI+5/hfL4TghL77yQeHw3uMMhfMbCqplkBfsK94XBsL7jjJE+aD8UF9U3fOGJIS6VX5c1fL+kBS4QipN1GuklV9eR63HsxifvSFVJvl+w6xLZhkE9+wz8qDLGsdJLeMPScgZlOLioJQEApLvxHSd9/C+qe2WiTqm+TgXSsvLLSRSUopp4f1CXgq94e0XekKqnqj98YYkwxEuM31eYBmV/9Kg5Bvhuo46hHyouogydonKM8oB28IxKfKH84lji1dhKHx+6nqD8xXlW+wPhs9pf/j4mee+J1zWReXfVKDc9LkSPofDdQtpoJz0e3TH45xU2yw/35Bf/R7zdR71sdTniN42ykHXRdR1tX/lbZDDqfcjJKWlAXXeI02fQ1QZOZ3hMkfbhvzoNg/5QZ7VuVR+zqq6UX4uFxqOiLZL50XvM8oLx1XXE8B0Xdb6XEQdxDHR5xHyZd0XHGu0tdbzFXUM52g+8lgmaps4LhnO8DrqfCivryVBvW54vdJSvxRKeVvuCy+Lth51FeujDujlw+dl+NhiH0qLAhJyhtsfXQexfJE7XLYoH395u4NzRtdzfV1AHSwIhKS00B+ue8E97RvqA9oKVWbl7X9WWbjgjP00QGTAKIvpm7ZA+V5HfzmTkZGhXlY+n08WLFggN998sznN6XTKiSeeKPPmzYs575SYOCm/MCQlOF/94bqPcwXntz5ncJ7gGoHrn24LdPygz1UVayENtPPl13y0zypuKW/Lcd7o9g9pApZDTINrZThm2BO7oI3EOafnq+uJpY3Vy6o2r7zdwfmZj7ZZ9lwzdfuJNhDXBOQJecS5Crq9xDkcjjP2xAO63dftmPVar9pJh6HaUXxWZVfejuv2zhrvWWOjcP73nKdoX9yIEQLh62axJ9ymY7+RZzOv5dd3tIMoI7SZaP/VddgIRcRZWFZd61QMEJTiUPjaa70e6eMLelnkD8elpDi8D+axLL92W4+b2o/yawEgTeRZlxmuYzrm1u27bpPxb355G4o6pOsWlkOMgWOQ7w6q60s+YoJAOG8qPkAcFAyXFdZD2aHuZek4zG9IaWFArR+Ol8L7o7aBehEKx61o93X8ml9+zca+oZ6qPKDsy9ty5BF07I06hbLD8oglsawZw/iR53Aa6toY0nkL10f9WZW9UyJiNHxGvKRiFUtsjX0oK/RLfmZ5mbnQbofzB6j/Kn+BPfFh9D7oayiOh7rG4nwKhLeH7YRjz5CKR/Q5oeMF/XcR8qGm4xxBejiW6voYLj/kW8eUe/avvI6WScR5os8BFX+U10tVj2TP3z362GA/UK6qLgX2xLZ6XZVOeX3Wf1/paz/qoIqRytshbDsTdRHnIo6jw2GWuT7XUTdRvthXsMZl+rzWcZ4ZN5W3Wfo81H836X1S9Vy1YeFYBPUIL5zfSF+3GzjOBZl7jhv2F9Nw/mG9EndA3OXxjjp3y89t/fckzgWsg79j9N9B+txQyxt7ziEdR6myRfr4uxLL+vecwzgffIU+KcrYc66bbZ66XoSkxB+QIk84njLbjfK/87Atdf4Fwn8L6zYexxV5LSsKJH2cVJMYCRgn7YWRJJCVqVOn7nWZ0tJSY/fu3eZryZIlaj2+WAasA6wDrAOsA4muA+vXr6/T62RJSYnRokWLWuUxJyenwrTx48dX2NaGDRvUvG+++SZi+vXXX2/07du3TveTYsc4ie1gottBvlgGrAOsA3aNk6obIwHjpKrZ6g6m6B7EnJwcWb9+veTm5orDUd6tbwPoGW3btq3Ke15enqQS7pv98JjZE49b8sB3JAUFBdKqVas63Q4G2l6zZo361qw2eY2+Xlb2zRzZUyrESWzb7InHzZ543OzJbsfNLnESY6T4SGgHU2FhoaxcudL8jAqxcOFCadSokbRr126f6+N2/TZt2ohdoUGwQ6MQC+6b/fCY2ROPW3KoX7/+ftkOgie86lqTJk3E5XLJli1bIqbjc4sWLep8+xQfdo6T2LbZE4+bPfG42ZOdjhvjpPSR0EG+f/jhBzn00EPVC/C0Gry//fbbE5ktIiKitOb1eqVPnz4yc+ZMc1ooFFKf+/fvn9C8ERERESUS46QkvYNp4MCB+22wLyIiIqo+fOkzcuRIOfzww6Vv374yceJEKSoqUk+VIyIiIkpnjJMqZ6sxmFIFxkcYP358So57wX2zHx4ze+Jxo7p29tlny7Zt29RdxZs3b5bevXvL9OnTpXnz5ix8qjNs2+yJx82eeNzsKZWPm50wTqqcAyN9VzGPiIiIiIiIiIgoucdgIiIiIiIiIiIi+2MHExERERERERER1Qo7mIiIiIiIiIiIqFbYwURERERERERERLXCDibaLy666CIZNmzYfi/tyZMni8PhUK+xY8fu9+3He18aNGhQJ2l36NBBPYKciIiI9j/GSbXHOImIKPHYwUS1pjtwqnrdcccd8uijj6oLfyLk5eXJpk2b5O67707I9u3g+++/l1GjRiU0D19++aWceuqp0qpVK1Vvpk2bVmGZLVu2qCAcy2RnZ8ugQYNkxYoV5vy1a9dWWQ+nTJliLrdu3ToZOnSoSqNZs2Zy/fXXSyAQ2GcekUb37t0lMzNTDjnkEPn4448j5r/77rty8sknS+PGjdU2Fy5cWK1937Fjh5x33nmqrqIT8dJLL5XCwkJzfmlpqdpvbNPtdieks5aIiGLDOMn+GCcxTiKi6mEHE9UaOm/0C3fB6A4d/frXv/4l9evXr7O7b6oT2LVo0UJyc3MTsn07aNq0qepsSaSioiLp1auXPPnkk5XONwxDdaysXr1a3nvvPfnpp5+kffv2cuKJJ6p1oW3bthF1D68777xTcnJyZPDgwWqZYDCoOpd8Pp9888038tJLL6nOz9tvv32v+cOy5557rur8wbaRF7wWL14csQ9HHXWUPPDAAzXad3Qu/frrr/LZZ5/Jhx9+qDrbrB1+yHNWVpZcc801an+JiMg+GCfZH+MkxklEVE0GURxNmjTJqF+/foXpI0eONE4//XTz87HHHmtcddVVxpgxY4wGDRoYzZo1M5599lmjsLDQuOiii4ycnByjc+fOxscffxyRzi+//GIMGjTIqFevnlrn/PPPN7Zt21bj/Dz55JNGly5djIyMDJXOmWeeac4LBoPGfffdZ3To0MHIzMw0evbsaUyZMiVi/cWLFxtDhw41cnNzVV6POuooY+XKleb6d955p9G6dWvD6/UavXr1Mj755BNz3TVr1hg49d555x1j4MCBRlZWltrGN998UyHvbdu2VfOHDRtmPPzwwxH7snDhQrU+to98HHbYYcb3339faTmEQiFj/PjxKj3kqWXLlsbVV19tzm/fvr3xyCOPmJ+Rv+eee05tF9tHWb333nvVLgPA+t27d1dl3K1bN1Xm1YXtT506NWLasmXL1HRsV0NZN23aVG2rKr179zYuueQS8zPqlNPpNDZv3mxOe+qpp4y8vDyjrKysynTOOusstb9W/fr1M/75z39WWFYf459++mmf+7pkyRK1rPXYob44HA5jw4YN+zyXiIjIPhgnMU7SGCcxTiJKRbyDiRIGd440adJEvvvuO7n66qvl8ssvlxEjRsiRRx4pP/74o/qp0QUXXCDFxcVq+V27dsnxxx8vhx56qPzwww8yffp09ZOps846q0bbxbq4E+Suu+6SZcuWqXSOOeYYc/6ECRPk5ZdflqefflrdVXLttdfK+eefL3PmzFHzN2zYoJbPyMiQL774QhYsWCCXXHKJ+RMr/Bzw3//+tzz88MPy888/yymnnCKnnXZaxE+54P/+7//U3V34GdUBBxyg7o7RacyfP1/dKXPVVVep+ccdd5zcc889Fe56adOmjbptG3m46aabxOPxVLrP77zzjjzyyCPyzDPPqHzg52f4udXe4M4flC32YciQIWp7+ClXdcrgtddeU3cE3XvvvfLbb7/JfffdJ7fddps65rEqKytT/+LnaZrT6VR5+PrrrytdB/lC+aEstXnz5ql9b968uTkNxyg/P18d76pgvei7h7AeptcG1sfdfYcffrg5DdvBvqEeEBFRemKcxDipJhgnEVFSSHQPF6XvN3O440ULBALqrqQLLrjAnLZp0yZ1Z8e8efPU57vvvts4+eSTI9Jdv369WgZ3t1Q3P7hzCHer5OfnV1i+tLTUyM7OrnA30aWXXmqce+656v3NN99sdOzY0fD5fJVus1WrVsa9994bMe2II44wrrjiioi7W55//nlz/q+//qqm/fbbb+oztjVkyJCINM4+++yIfcGdQ5MnTzaq49///rdxwAEHVJnnyu5guvXWW83PuLMM0/SdWPsqA9x99vrrr0dMw/Hr379/zHcwYVvt2rUzRowYYezYsUPdbXT//ferZaPrhXb55ZcbBx54YMS0yy67rMLyRUVFKp3oO+asPB5PhX3CXVm4A642dzChruDYRMOdWf/9738rTOcdTERE9sU4iXESME5inESUqngHEyVMz549zfcul0sNjGy9q0bfYbJ161b176JFi2TWrFlqPB39woDLsGrVqmpv96STTlJj93Tq1EndIYW7bfRdUitXrlTvsYx1O7ijSW8Dd8QcffTRld4thLtgNm7cKAMGDIiYjs+4k6eq/W/ZsmXEvmLZfv36RSzfv3//iM/jxo2Tf/zjH+pul/vvv3+vZYA7w0pKStQ+X3bZZTJ16tR9DmptzV+9evXU2Fo6f3srA4xDhLzgriFrGeIOrJocp2jYFgbRXr58uTRq1EiNGYX6gLGVcLdPNOzv66+/HnH3UnVgAHBrvnH3VbyMHj06Im0iIqKqME5inFQTjJOIKBm4E50BSl/RnRMYjNs6DZ8hFAqpf/FULTxlrLIBlHUHTXVgsG/8BG/27Nny6aefqp9y4Ul3+KmZfnLXRx99JK1bt45YDz/FAgy2HA9729fqQJ7//ve/q7x+8sknMn78eHnzzTdl+PDhFZbF4Nf4OeDnn3+uBpK+4oor5KGHHlI/+6vqZ3WVHR+dv72VgS7D5557rkInGToSa6NPnz6qc2v37t1qkG4MuoltWH9epv3vf/9TnYUXXnhhxHQM+I6fZVrhp5Z6Hp5QZ336Gzqz9Dy9nHU9TK8u/CwTP4uMzo/uuNPQ+YefI9YkbSIiSi2Mkxgn1RTjJCJKNN7BRLZx2GGHqTFyOnToIF26dIl44Q6bmsCj3nHnz4MPPqjGGMLj7TGW0EEHHaQ6knAXS/Q20Emjv1H86quvxO/3V0gXd/mgg2Lu3LkR0/EZaVfXgQceWGH8nW+//bbCchi7CWNEoaPsjDPOkEmTJlWZJjqF0EH32GOPqc41jP3zyy+/SCz2Vga48wxlgKe9RZdhx44dJR7wVEJ0LmE8KYypdfrpp1dY5oUXXlBjX2G56DvBsN/WTh10uuHY4RihbljzrDuYsN7MmTMj0sJ60XeW7U2zZs0i0tbpYnwxjBeloS6iMy+6g46IiKgqjJMYJ2mMk4goUXgHE9nGlVdeqe6KwWDYN9xwg/rDHz9pw107zz//fLXvjsFj4NH5gUGqGzZsKB9//LH6Y75bt27q7ibcYYJOG0zDI+dxtww6iNABMXLkSDXw9uOPPy7nnHOO3Hzzzeoijs6fvn37qjSuv/56dTdR586dpXfv3qrTB3fE4Kd41YVByPGzOgwUjs6TGTNmqMHIrT//wnb+9re/qU6bP/74Q92BdeaZZ1aa3uTJk9Wj7tFhgZ+Wvfrqq6rDCT8VjMW+ygADhGMfMH3QoEFq4El0BO3cuVP9tK+qO59wPLU1a9aocsNxbteunZo2ZcoU1WGEz+gkGjNmjAwbNkwNCG+FdL788kt1bKNhWXQk4eeR6GDcvHmz3Hrrrap+6bvUKoNtHXvssWoA96FDh6p6h3169tlnzWVw1xE6J/EzScBdY4A7kaq6GwmdiSgj/HQRA8uj0w7li7JFR522ZMkSddcWtlFQUGDeZYU6RkRExDiJcRLjJMZJRAmX6EGgKH0HrxwzZsxeB5qubLDn5cuXG8OHDzcaNGhgZGVlGd27dzfGjh1rhEKhaufnq6++Uttv2LChSqNnz57GW2+9Zc5HWhMnTjS6deumBnbGYMunnHKKMWfOHHOZRYsWqYGiMSA4Bts++uijjVWrVql5wWDQuOOOO4zWrVur9Xv16mUOjl3VANA7d+5U02bNmmVOe+GFF4w2bdqoPJ566qnGww8/bO4LBrg+55xzjLZt2xper1cNLH7VVVcZJSUllZYDyrBfv35qcHMMpv6Xv/zF+Pzzz6ss+8oG2ca2UZ7VKQN47bXXjN69e6v8oayPOeYY49133zWqgn3HdqNfqDvao48+qsoE5YoBvzEQOcoiGgYhR9ngWFRm7dq1xuDBg1XZNmnSxLjuuusMv99v7Mvbb7+tBuTGPvXo0cP46KOPIuajfCrbh/Hjx+813T///FMN7J6Tk6OO0cUXX2wUFBRELINjVFnaRERkH4yTGCdpjJMYJxGlIgf+l+hOLqK6gjt3xo4dq36CRERERESMk4iIqG5wDCZKefiJG57YdeONNyY6K0RERERJhXESERHFC+9gopSGsWr0k78aNGggTZo0SXSWiIiIiJIC4yQiIoondjAREREREREREVGt8CdyRERERERERERUK+xgIqKE6NChgzgcDvXiIOxEREREjJOIyN7YwUSUJJ588knV6ZKZmSn9+vWT7777zpxXWloqV155pTRu3FgNWH7mmWeaY0vtzZQpU6R79+4qzUMOOUQ+/vjjiPl4iOTtt98uLVu2lKysLDnxxBNlxYoV+0x39uzZcthhh0lGRoZ06dJFPa2vJvsD33//vbzzzjv73BYRERER4yQiouTHDiaiJPDWW2/JuHHjZPz48fLjjz9Kr1695JRTTpGtW7eq+ddee6188MEHqsNozpw5snHjRjnjjDP2muY333wj5557rlx66aXy008/ybBhw9Rr8eLF5jIPPvigPPbYY/L000/L/PnzpV69emq76NCqypo1a2To0KFy3HHHycKFC2Xs2LHyj3/8Q2bMmFHt/YGmTZtKo0aNallyRERElOoYJxER2YRBRAnXt29f48orrzQ/B4NBo1WrVsaECROMXbt2GR6Px5gyZYo5/7fffjNw+s6bN6/KNM866yxj6NChEdP69etn/POf/1TvQ6GQ0aJFC+Ohhx4y52NbGRkZxhtvvFFlujfccIPRo0ePiGlnn322ccopp1Rrf6xmzZql9mPnzp1Vbo+IiIjSG+MkxklEZA+8g4kowXw+nyxYsED9PE1zOp3q87x589Q8v98fMR8/e2vXrp2ar+HnaHfccYf5GfOs6wDuItLr4E6kzZs3RyxTv3599XM2a7oDBw6Uiy66qNrp7mt/iIiIiBgnMU4iotTDDiaiBNu+fbsEg0Fp3rx5xHR8RgcQXl6vVxo0aFDpfK1z587SpEkT8zPmVZWmnq+n7S1ddGRhjKZ9pZufny8lJSX73B8iIiKi6mKcRERkH+5EZ4CI4mPmzJl1UpQvv/xynaRLREREtL8wTiIiqnu8g4kowXDXkcvlqvBUOHxu0aKFeuFnZ7t27ap0flUwr6o09Xw9LR7p5uXlqSfR7Wt/iIiIiKqLcRIRkX2wg4kowfDztz59+kR8sxYKhdTn/v37q3kejydi/rJly2TdunVqflUwL/rbus8++8xcp2PHjqrDx7oMfuaGp8nVJt197Q8RERFRdTFOIiKykUSPMk5EhvHmm2+qp7dNnjzZWLJkiTFq1CijQYMGxubNm1XxjB492mjXrp3xxRdfGD/88IPRv39/9bI6/vjjjccff9z8PHfuXMPtdhsPP/yweurc+PHj1dPofvnlF3OZ+++/X23nvffeM37++Wfj9NNPNzp27GiUlJSYy1xwwQXGTTfdZH5evXq1kZ2dbVx//fUq3SeffNJwuVzG9OnTq70/Gp8iR0RERPvCOIlPkSMie2AHE1GSQOcQOpG8Xq96HO+3335rzkOHzxVXXGE0bNhQde4MHz7c2LRpU8T67du3V51IVm+//bZxwAEHqDR79OhhfPTRRxHzQ6GQcdtttxnNmzdXHUInnHCCsWzZsohljj32WGPkyJEVOoZ69+6t0u3UqZMxadKkGu2PNR30c+9k4ERERESMkxgnEZGtOfC/RN9FRUTpafbs2XLcccfJzp07Kzwlj4iIiCidMU4iIrvhU+SIKCF69Oghq1evZunT/7N3H2BOVGsfwN/ULewusPRepCkKKgIXsKBiARvKhw0VyxV7w2u9InbU61VsFzvYFVSwg4KgggqKggLSUZCOlO2bTTLf8z/hDJNsFnazWTaT/H8+kWQy5ZwzZ868OzlzhoiIiBgnEVESYA8mIqoVf/75p5SVlan37du3F6eTzxwgIiIiYpxERHbFC0xERERERERERFQt7DJARERERERERETVwgtMRERERERERERULbzARERERERERERE1cILTEREREREREREVC28wERERERERERERNXCC0xERERERERERFQtvMBERERERERERETVwgtMRERERERERERULbzARERERERERERE1cILTEREREREREREVC28wERERERERERERLzAREREREREREREtYc9mIiIiIiIiIiIqFp4gYmIiIiIiIiIiKqFF5iIiIiIiIiIiKhaeIGJKEFMmDBBHA5H2Ktx48Zy7LHHyueffy52VFxcLJdddpkcfPDBUrduXcnKypLu3bvLk08+KWVlZbWdPCIiIrKBZIyRIs2ePdvM27Zt22o7OUREMXHHthgR1ZT77rtP2rVrJ4ZhyObNm1VQNWjQIPn444/l1FNPtd0FpsWLF6v0t23bVpxOp3z33Xdy0003ydy5c+Wtt96q7SQSERGRTSRTjGQVDAbluuuukzp16khhYWFtJ4eIKGa8wESUYAYOHChHHHGE+Rk9gJo0aSJvv/227YKn3Nxc+eGHH8KmXXnllao30zPPPCOPP/64NG3atNbSR0RERPaRTDGS1QsvvCDr1q2Tf/7zn6qXNxGRXfEWOaIEV69ePcnIyBC3213u166xY8dK165dJT09XQVYV1xxhezYsSNsvg8//FBOOeUUad68uaSlpckBBxwg999/vwQCgbD5+vfvr25l+/XXX+WYY46RzMxM6dChg7z33nvq+6+//lp69+6t0tK5c2eZPn16zHlCbybYuXNnzOsgIiKi1JYMMdL27dvlrrvuUr2zkB8iIjvjBSaiBLNr1y517/3WrVvV7WVXXXWVFBQUyAUXXBA2HwKlW265Rfr166d+7brkkkvkzTfflJNOOilsfCN0H8fYRyNHjlTz9ejRQ+6++265/fbby20bgRd+AUSQ9Oijj6pg69xzz5V3331X/Ytu6A8//LDqvv1///d/kp+fX6k8+Xw+lSf8Ojd58mR57LHHpE2bNio4IyIiIkrVGGnUqFGqNzfSTERkewYRJYTx48cbOCQjX2lpacaECRPC5v3222/Vd2+++WbY9KlTp5abXlRUVG5bV1xxhZGZmWmUlJSY04455hi17FtvvWVOW7p0qZrmdDqNH374wZw+bdo0NR1proy33347LE9HHHGE8euvv1ayZIiIiCiVJWuMtHDhQsPlcqllYPTo0WrZrVu3VrpsiIgSCXswESWYZ599Vr788kv1euONN9QTUnBP/gcffGDOM2nSJDWO0QknnKB+ydMv/PKGX+Jmzpxpzovu2hp+TcN8Rx11lBQVFcnSpUvDto1l8Suchm7e6K594IEHql/sNP1+9erVlcoT8oD8IN0Yg8nj8XAQSyIiIkrpGOn6669X40qdeOKJrAlElBQ4yDdRgunVq1fYAJbnnXeeHHbYYXLttdeqrtler1dWrFihuonjEb3RbNmyxXyPLuS4t/+rr76SvLy8sPmwDquWLVuqx+NaIUhr1apVuWkQOZZBRTD2AV6AbuMPPfSQCvyQDw7yTURERKkWI+HWOjxZd9GiRfvMNxGRXfACE1GCczqd6hc6jA2AoAkDVmLwSgROGE8gmkaNGpmDaGMwypycHDV4JAavxGCXP//8s9x2221qPVYulyvq+iqajscExwIXmf7973+rwTU55gARERGlWoyEMaKGDh2qLor98ccfZpoAY1Zi/EoMPk5EZCe8wERkA36/X/2LgSwBQRCeUILBK63duyPNmjVL/v77b9V1/Oijjzanr1mzRmpTcXFx1F8HiYiIiFIhRsJFpLfeeku9Ih1++OHSvXt3WbBgwX5JCxFRvHAMJqIEh6edfPHFF+oXLtznD2effbZ6hC4epRst0NK/gOlf1ay/ouEXsf/973/7Je0YyyDaL3gvvfSS+tfazZ2IiIgoVWIkPFU38nXOOeeo71577TV54okn9ks6iIjiiT2YiBLM559/bg4siXEC8MsWun3jkbnoxg3o0o1by8aMGaN+3cLgkBg4G/NhcEt0FcdtaH379pX69evL8OHD1UCSGDvg9ddfj/nWtqrCAJzPPfecDB48WNq3b68G0Jw2bZoanPO0006T4447br+kg4iIiOwvmWIkxEaRdI8lDPzdsGHD/ZIOIqJ44gUmogRz9913m+8xFkCXLl1k3Lhx5cYqwoUbPBHl+eeflzvvvFPcbre0bdtWLrjgAtUtHBo0aCCffPKJ3HzzzWoQSwRS+P7444+Xk046qcbzcuSRR6oBLN9++23ZvHmzSiOeuvL444/LddddV+PbJyIiouSRTDESEVEychj76zI9ERERERERERElJY7BRERERERERERE1cILTEREREREREREVC28wERERERERERERNXCC0xERERUzjfffKOe9ti8eXP1dKUpU6aEfY8hHDHgbrNmzSQjI0MGDBigntJktX37dhk2bJh6ulO9evXksssuk4KCApY2ERER2RrjpOh4gYmIiIjKKSwslO7du8uzzz4btXQeffRReeqpp9TTmubOnSt16tRRT14qKSkx58HFpcWLF8uXX36pntaEYGzEiBEsbSIiIrI1xknR8SlyREREtFfowTR58mQZPHiw2XsJPZvweO9//etfatquXbukSZMmMmHCBDn33HPl999/l4MOOkh+/PFHOeKII9Q8U6dOlUGDBslff/2lliciIiKyO8ZJe7jFxoLBoGzYsEGys7PVTiUiItrfcLElPz9fXTBxOmu2YzB6B/l8vmqlNfJ8mZaWpl5VsWbNGtm0aZO6LU6rW7eu9O7dW77//nt1gQn/4rY4fXEJMD/KCD2ezjzzzJjzQZXDOImIiGqbXeKkeMVIqR4n2foCEy4utWrVqraTQUREJOvWrZOWLVvWaNDUrk2WbNoSiHkdWVlZ5cZAGj16tNxzzz1VWg+CJkCPJSt81t/h38aNG4d973a7JTc315yHahbjJCIiShSJHifFK0ZK9TjJ1heY0HMJjpRB4hZPbSeHiIhSkF/KZLZ8Zp6Tagp+kUPQ9Of8tpKTXfVfAPPyg9Kmxx8qwMOg21osv8yRPTBOIiKi2maHOIkxUvzY+gKT7sKGi0tuBy8wERFRLTDCz0k1LSvboV5VFZTQMri4ZL3AFIumTZuqfzdv3qyeIqfh86GHHmrOs2XLlrDl/H6/erKcXp5qFuMkIiKqdTaIk+IZI6V6nMSnyBEREdlIwAjG/IqXdu3aqeBnxowZ5rS8vDw1ZkCfPn3UZ/y7c+dOmT9/vjnPV199pcYFwhgERERERPFW2zFSqsdJtu7BRERElGqCYqhXLMtVBcYhWLlyZdiAlQsWLFBjA7Ru3VpuvPFGeeCBB6Rjx44qkBo1apQawFM/ae7AAw+Uk08+WS6//HJ57rnnpKysTK699lo1sCWfIEdERESJEifFElcxToqOF5iIiIhsJKj+i225qvjpp5/k2GOPNT+PHDlS/Tt8+HCZMGGC3HrrrVJYWCgjRoxQv8AdeeSRMnXqVElPTzeXefPNN9VFpeOPP149FWXIkCHy1FNPxZB6IiIiopqJk2KJrBgnRecw8Dw+m0I3Mzzur7+cwTGYiIioVviNMpklH8quXbvict/+vs5565a2iHmQ71Zd1td4OilxME4iIqLaZoc4iTFS/HAMJiIiIiIiIiIiqhbeIkdERGQj+2sMJiIiIiK72V9jMFF0vMBERERkIwiCArzARERERBSXOIkXmOKHF5iIiIhshD2YiIiIiOIXJ/ECU/zwAhMREZGNBAxDvWJZjoiIiCiZxRInMUaKH15gIiIishE8SLfqD9ONbRkiIiKiZI+TGCPFD58iR0RERERERERE1cIeTERERDYSiHGQ71iWISIiIkr2OIkxUvzwAhMREZGNBIzQK5bliIiIiJJZLHESY6T44QUmIiIiG+EYTERERETxi5M4BlP88AITERGRjQTFIQFxxLQcERERUTKLJU5ijBQ/vMBERERkI0Ej9IplOSIiIqJkFkucxBgpfniBiYiIyEYCMfZgimUZIiIiomSPkxgjxY8zjusiIiIiIiIiIqIUxB5MRERENsIeTERERETxi5PYgyl+eIGJiIjIRoKGQ71iWY6IiIgomcUSJzFGih9eYCIiIrIR9mAiIiIiil+cxB5M8cMLTERERDYSEKd6VX05IiIiouQWS5zEGCl+eIGJiIjIRowYb5HDckRERETJLJY4iTFS/PApckREREREREREVC3swURERGQjHIOJiIiIKH5xEsdgSpIeTPn5+XLjjTdKmzZtJCMjQ/r27Ss//vhjbSaJiIgooQUMZ8wvIiIiomTGGCmFezD985//lEWLFsnrr78uzZs3lzfeeEMGDBggS5YskRYtWtRm0oiIiBJSUBwSjOH3oaAYNZIeIiIiIjvHSYyR4qfWfs4sLi6W999/Xx599FE5+uijpUOHDnLPPfeof8eNG1dbySIiIrJF1+9YXkRERETJjDFSivZg8vv9EggEJD09PWw6bpWbPXt2bSWLiIgoocV6u1vAYA8mIiIiSm6xxEmMkZLgAlN2drb06dNH7r//fjnwwAOlSZMm8vbbb8v333+vejFFU1paql5aXl7efkwxERERUeJinERERES1qVZH/MTYS4ZhqPGW0tLS5KmnnpLzzjtPnM7oyRozZozUrVvXfLVq1Wq/p5mIiKj2xxaI7UXJjXESERGlOsZItcth4ApPLSssLFS9kZo1aybnnHOOFBQUyKefflqpX+ZwkWnLsjbSIMerppUZfvE4Qh2zrt3QS55pPi9sHZsCBdLUlaXeLy4rkuYukfrOzLB5dgSLzGnW93BS8+5xzTsREe1/0zYsNM8H+Dc/KNLRkyWzShzSL63MPI9MLfbKyRk+WevPl3X+OlLPVSKd3F5Z7vdJA2dQLZ+XH5D6nVbLrl27JCcnp8bSjHMeflyZtLCLZGa7qrx8UX5AhnZfWuPppNpTUZy0Y3l7ybHUmRVlBeITp3T17IlvED8B6j5in1IjqD43cKZLgeFTsVBkTKSX08cL3p/aokeN55OIiGo2RoI5JUHp7vXJxoBfsp2iYh7d5uvzQUGwRJb5Q51DGjlL5cXtfeTy3O+l1Aj9qLWgtIWcZGxP+DiJMVKSPEVOq1Onjnrt2LFDpk2bpgb+jga9nPAiIiJKVRyDiSrCOImIiFIdx2BK4QtMuJiEDlSdO3eWlStXyi233CJdunSRSy65pDaTRURElLDw6N2qPn43tFytd1gmIiIiSrg4iTFSklxgQje5O+64Q/766y/Jzc2VIUOGyIMPPigej6c2k0VERJSwAoZDvWJZjoiIiCiZxRInMUZKkgtMZ599tnoREREREREREZF9JcQYTERERFQ5AXGqV1UFeIscERERJblY4iTGSPHDC0xEREQ2EjSc6lX15TgGExERESW3WOIkxkjxwwtMRERENsIeTERERETxi5PYgyl+eIGJiIjIRoIxDkaJ5YiIiIiSWSxxEmOk+OEFJiIioiR//K5ejoiIiCiZxRInMUaKH0abRERERERERERULezBREREZCMBw6lesSxHRERElMxiiZMYI8UPLzARERHZSFAc6hXLckRERETJLJY4iTFS/PACExERkY2wBxMRERFR/OIk9mCKH15gIiIiSvLH7+rliIiIiJJZLHESY6T44QUmIiIiGwkaDvWKZTkiIiKiZBZLnMQYKX54gYmIiMhG8CjdWH5p4yN4iYiIKNnFEicxRoqfpLjA5HG41L9lhl82BoqltTtbFpcVyTPN58nUYq+cnOGTHcEiNY/PMMzlunoy1TJ62dC63FLfmWnOg/f4rsDwqffTNiw0v9PrnF7UTIZm7TKnY36sJ5KejuWs26hoftgUKJCmriw1z9/BEvV+vs8nPbzesDQft/h0+arrR+rznJKgpDv90s3jVN9hHcNb9YuxdIkoFVnbuoJgiWQ501W72sntLdde6XZK020c/vWIU17e1UXOzP5Ntc0QbT1o1zq7g5LmcJvtrd729mCZZDtd5rTINnRFWYF09OzZvp4HrPNFyg+KNHWJzChqLYPq/KXa1BauEvE4slSeshxuOTkjNC+2f4CnSBb4cmVnoEQO8oqU7j6d9P7xbBF5OIZSJqodzVxu+TMQDDu+9XEX7Xiqv/tYtR5P+jjEcazjGLyitR2RsU5kPGT9t9QIhrUnmo7nItsb6zYitzOrxCH90w0zPmzmyjC/QzvU3CWy0FdHxrTvFqeSJaJkhzYu2t9u1nbm17Kg+ltNw99m/dKdYTEQ/q5DnIG4B7C+yPZsb9BWN3SF1rkhIGqd5685WSa1n67ay95pO8vFQJHtZ2T6I/PU3etT6WnrCP0dak0f4jssg889dmd1R9AvtzX8SX7y5UgLV746lzR0bZTNeaG/WSk1JMUFJiIiolQRNJzqFctyRERERMksljiJMVL88AITERGRjQTEoV6xLEdERESUzGKJkxgjxQ8vMBEREdkIezARERERxS9OYg+m+OEFJiIiIhsJxPhLG5YjIiIiSmaxxEmMkeKHF5iIiIhshD2YiIiIiOIXJ7EHU/xwxE8iIiIKEwgEZNSoUdKuXTvJyMiQAw44QO6//34xLE9ixfu7775bmjVrpuYZMGCArFixgiVJRERESY1xUsV4gYmIiMhGAoYz5ldlPfLIIzJu3Dh55pln5Pfff1efH330UXn66afNefD5qaeekueee07mzp0rderUkZNOOklKSkpqKOdEREREe1fTMRIwTqoYb5EjIiKyEUMcEoxhDCYsV1nfffednHHGGXLKKaeoz23btpW3335b5s2bF1qXYcjYsWPlrrvuUvPBa6+9Jk2aNJEpU6bIueeeW+X0EREREdVGnFSVGAkYJ1WMPZiIiIhSqAdTXl5e2Ku0tLTcNvr27SszZsyQ5cuXq88LFy6U2bNny8CBA9XnNWvWyKZNm9RtcVrdunWld+/e8v333++3siAiIiKyqukYCRgnVYw9mIiIiGwkaDjUK5bloFWrVmHTR48eLffcc0/YtNtvv10FVl26dBGXy6XGGnjwwQdl2LBh6ntcXAL0WLLCZ/1dPGBMp5kzZ8qWLVskGAyGfYfxn4iIiIiqGydVJUYCxkkJeoEJASt22BtvvKEC0ubNm8vFF1+sutw7HFUPnomIiJJdQJzqFctysG7dOsnJyTGnp6WllZt34sSJ8uabb8pbb70lXbt2lQULFsiNN96oztPDhw+X/eHFF1+Uq666Sho2bChNmzYNiwvwnheYiIiIKB5xUlViJGCclKAXmPTgWK+++qoKYH/66Se55JJLVDf766+/vjaTRkRElJQQOFmDp2huueUW9eucHkvpkEMOkT///FPGjBmjLjDhgg9s3rxZPUVOw+dDDz00Lul84IEHVK+p2267LS7rIyIiIqpujASMkxJ0DCbr4FgYQPT//u//5MQTTzQHESUiIqLoXb9jeVVWUVGROJ3hIQJuldO3qbVr105dZMI4TRpuqcPT5Pr06ROXXbZjxw4ZOnRoXNZFREREqaGmYyRgnJSgF5j2NTgWERERhQuKM+ZXZZ122mmq99Cnn34qf/zxh0yePFkef/xxOfPMM81b1HDLHHoZffTRR/Lbb7/JRRddpG6hGzx4cFx2GS4uffHFF9z9REREVGk1HSMB46QEvUVuX4NjRcIo7taR3LEsERFRKgkYDvWKZbnKevrpp2XUqFFy9dVXqwG2ceHoiiuuCBv36NZbb5XCwkIZMWKE7Ny5U4488kiZOnWqpKenSzx06NBBpeGHH35Qt+h5PJ6w73krfXmMk4iIKNXFEidVdX7GSQl6gamqg2Nh7Id77723VtJKRESUDE+Rq4zs7GwZO3aselUEvZjuu+8+9aoJL7zwgmRlZcnXX3+tXpHb5gWm8hgnERFRqqvOU+Qqi3FSxRyGYRhSS/AYQPRiuuaaa8xp6G6Pp8otXbq0Ur/MYR07lreXjCxDPI7Q9bIdwSIpNYLSwJkuEwsay6A6f0l9Z2bYutb686W1O7vSaS0z/OpfvQ18xnv9r3VatGWjzYP3pYZfspzpYesrMHxmekdtOVi6ZGyQYdnb1edNgQJp6spS880oyZSTM3xRt6Ndu6GXPNN8nswpCUq/dKcqG73ugmCJuW1r3iLTBo9s7yDX1FskBYZfbV+vB+vtlRYst6x1X6h9ZwRlfcArd7btWekyJ0oln6yfL8v9PmnjcprHnT5G9b+gj1fdTkRri6zHOdqMv4NOaeAMqmMXFpcVSVfPnmX1fGkOp1oOy2c5vGHrfSWviQyqs8pch2ZtP9CuZjtdstrvlh5er5kWsLbB2BbaZ71tLJfr9EiZBM35rMtZt6HTo9ehyyJym5Hbi0y3TjuWfWRrH3m4yUJzmnU7WNfskoaSF0iXLmmbpIXLp9al14nvXYVpUr/Tatm1a1elBoaMFc55eAjGiK+HijcrvDdPZfgKyuSFYybVeDqp9uwtTsrJdlUYp+wNlvk7WBL1GNrbMpHtEdqxNIdbHXO6fbF+XxHr9zq+08detDZCtynNXBlh8dTePLmjrdxQ/4+wtsKabmv7G1l++nsse+zcK+W9ni+o9tW6nHVZa3liG/nBgGo3ka/hrfpVuoyJUs07f30f1hZEHtsfF2VKF88W6egJHcN7OwYRb+k4aG/txHyfT8UWej4N8+v24pK1R8n41t+q7fdM22K2Ic/taiGX5fypttXcFb2tsqZNr39vbZZeHqx/p+n2Ndp3+Fvtj7KGcnzm2qgxnDX/Ff3Nam17I/+GxnfPbj9cLqr3o2p3kd9Obq9q55aWZUv/dEPy8gMJHycxRkqSHkz7GhwrEh4TWNGjAomIiCg56d/C0HOJKsY4iYiIKPUYCRQn1eog3/saHIuIiIjCBcQR88tuXnvtNTX+UkZGhnp169ZNXn/99dpOFhERESWoVImREjVOqtUeTJUZHIuIiIj2CBpVHytAL2cn+MEJMcK1114r/fqFbh3Ck2avvPJK2bZtm9x00021nUQiIiJKgjjJbjFSIsdJtXqBqTKDYxEREdEeQcOpXlUVyzK1CT9CjRs3Ti666CJz2umnn64eCnLPPffwAhMRERHFJU6yW4yUyHFSrV5gIiIioqoJikO9qiqWZWrTxo0bpW/fvuWmYxq+IyIiIopHnGS3GCmR4yT7XaojIiJKYQHDEfPLTjp06CATJ04sN/3dd9+Vjh071kqaiIiIKLGlQoyUyHESezARERHZSKrcInfvvffKOeecI9988405tsCcOXNkxowZUQMqIiIiolS5Re7eBI2T7FeSRERElPSGDBkic+fOlYYNG8qUKVPUC+/nzZvHp80SERFRShuSoHESezARERHZbWyBWJ4iZ8PxBXr06CFvvPFGbSeDiIiIkjhOsmOMlKhxEi8wERER2YgR4yDfWC7R5eXlSU5Ojvl+b/R8RERERNWJk+wQI9klTuIFJiIiIhvBr3Ix9WCywQCW9evXV08+ady4sdSrV08cjvJpNgxDTQ8EArWSRiIiIkquOMkOMZJd4iReYCIiIrKRZB7k+6uvvpLc3Fz1fubMmbWdHCIiIrKZZB7k+ysbxEm8wERERGQjydyD6ZhjjjHft2vXTlq1alXu1zn8Mrdu3bpaSB0RERElumTuwXSMDeIke1yqIyIiopSCwGnr1q3lpm/fvl19R0RERJSq2iVonMQeTERERHZ7OkoMg1Ha7QkpegyBSAUFBZKenl4raSIiIqLki5PsFiMlcpzEC0xEREQ2ksy3yMHIkSPVvwiaRo0aJZmZmeZ3GLBy7ty5cuihh9ZiComIiChRJfMtcnaIkxwGLn3ZFB7NV7duXVm3tIVkZIvUd2bKWn++tHZnl5u3zPBLqeGXjQG/NHO5JcuZLgXBEvUvvvM49lxr058j/90RLJIsh1fNY53/2g295OGm36h1WbelP1eUljSH21wP1o30V8SarxVlBdLRk2Wuy5oerGfUpv7yRLPvzGmR+bCyloF1PfN9PunmcZab37qcNf3WMkI+ntzRVq6ut7Lc8vr7Qx+9ShbcOk5Nw7w31P8jLJ26/PQ0nU5rGf4dLJGmrixzv0TbVwWGT21v1JaD5f7Gi2RToEAtc1Lz7hWWNSW/F9fOVsfTSUtPkfc7vW/WLdQztBFt3ekVHpv7qvuPbO8gt+WuLHfcWpfT8y4uK5JObq9Zl610XdXLQbTj0Xrc6Hn0stb0W4//aN8jLV094fm0lsslf5wqk9pPj1qe1uPRmibrusokWK6NiyxbtG0NXc6waUjX5UsulGvaz5Rh2dvLbRt5gQbO9LD2489AUBo4g1HLNc0R2kZF+1a3G7odBOQvPyiq7UU6twQy5SBviXjEKaUFTmnc+U/ZtWtXjT4SVp/zBk69XDx1Queiqigr9MnnJ79Y4+msrmOPPVb9+/XXX0ufPn3E692TV7xv27at/Otf/5KOHTvWYirtQdeZpb83kY71cmRqsVdOzvCp73CsTCxoLGdnbQlr76znTj3NepxY25po518rTMO6So3yx+LeRJ7zrSLTY23PrO+t6Yls37AOpGmBL9csj8rQ69f5spbRQl8d6Z9uhKUvWnypl4uMu6zzTyqoK0dlrJcslGtE22nN474gvjoz+zfzPKTXby2POSVB6e71qfJmjETaq+vmmOdK63GzxJcuB3iKysUQVvpcOq/UKf3Sy4/GYq2HiIGscRH+nVtaT1q5d0q2IyDNXBmyMVCs6nC0tkivp7krNG1bIKjO06jLOH6i/Z0XrY15YFsXOTZriToWdKyml9PHxXO7WsiuQIYZ41nTgPUV7D6mMa+ONXTbZz1u38zPlTPqbAj7uzFaHGiFuOOzgoPlorpLJD8YMI9pXSbWtknnNTKOw3sdl2K+qcU50jNtyz7bE8z7h79ElWuX2RfK932fl9klDeW0zCJzvbNKHKr9wznm+PQimVPqkX5pZea+DRa4Ez5OskuMZIc4iT2YiIiIbCTZezDpp6Jccskl8uSTTyZ8oEdERESJI9l7MM1M8DiJF5iIiIhsJNkvMGnjx4+v7SQQERGRzST7BaZEj5N4gYmIiIgS0k8//SQTJ06UtWvXis8XfivTBx98UGvpIiIiIqptPyVgnFT+xlgiIiJKWIblCSlVedltwMV33nlH+vbtK7///rtMnjxZysrKZPHixfLVV1+pMRaIiIiI4hEn2S1GSuQ4iReYiIiIbNj1O5aXnTz00EPyxBNPyMcff6wGrcQ4A0uXLpWzzz5bWrduXdvJIyIiogSUCjFSIsdJvMBERERkI6lygWnVqlVyyimnqPcInAoLC9UjeW+66SZ54YUXajt5RERElIBSIUZK5DiJF5iIiIhsJFUuMNWvX1/y8/PV+xYtWsiiRYvU+507d0pRUVEtp46IiIgSUSrESIkcJ3GQbyIiIhtJlafIHX300fLll1/KIYccIkOHDpUbbrhBjSuAaccff3xtJ4+IiIgSUKo8Re7oBI2TKnWBaeTIkVVe8V133SW5ubmxpImIiIhS3DPPPCMlJSXq/b///W/xeDzy3XffyZAhQ1SMYXeMrYiIiCjZ4qRKXWAaO3as9OnTR93bVxmzZ8+Wa6+9lheYiIiI4swwHOoVy3J2Yv2Ryul0yu233y7JhLEVERFRYsRJdouREjlOqvQtcnj0XePGjSs1b3Z2dqXma9u2rfz555/lpl999dXy7LPPVjZpREREKUM/UjeW5RJdXl5epefNyckRu6uJ2IqIiCiVxRIn2SFGskucVKkLTOPHj5e6detWeqXPP/+8NGnSZJ/z/fjjjxIIBMzPGJjqhBNOUPcQEhERUWqNwVSvXj31BJS9MQxDzWONH+yopmIrIiKiVJbMYzDVs0GcVKkLTMOHD6/SSs8///xKzdeoUaOwzw8//LAccMABcswxx1Rpe0RERKkimW+RmzlzpqSKmoqtiIiIUlky3yI30wZxUrWeIldQUCDBYDAuXbF8Pp+88cYbatDLiq7KlZaWqlcsXcSIiIiSQTL3YOIPTNWLrRgnERFRqkvmHkzH2KAjjrOqC6xZs0ZOOeUUqVOnjuraXb9+ffVCdy38G6spU6bIzp075eKLL65wnjFjxqht6lerVq1i3h4REREltm+//VYuuOAC6du3r6xfv15Ne/3119XDRJJJvGIrxklERESp49sEjJOq3IMJGcB9fa+88ooaC2Bf9wBW1ssvvywDBw6U5s2bVzjPHXfcEfZYX/Rg4kUmIiJKJcl8i5zV+++/LxdeeKEMGzZMfv75Z7MH865du+Shhx6Szz77TJJFvGIrxklERJTqkvkWOTvESQ4DEU0VZGVlyfz586Vz585xSwSeJNe+fXv54IMP5Iwzzqj0crjAhF/6tixrIw1yvGpameGXUsMvWc50KQiWSJkEpb4z01xmU6BAmrqyzM+Y3+Nwy45gUdh8WBbr2BfMB9Z5I7eh16W3pf8FbDfL4S03XVtRViAdPaF1zSkJSr90p7lMgeEz06zTv7isSDq5vfJ3sESlQa9zVolD+qcbZvp8hiGt3dlR02hdb0VpRVq6e32y0OeVXmnBsHRHlmVkvvT31vVpD2zrItfk/qy+1+WoyzjN4Vb5Al2+kWUa+e9af76ZT709rKPB7v2lt21NI97r7ypKu65nSJP1+1fymsigOqskzeGUx7f1kmsa/KDeg7VMtI+LMuW0zKK91rfINKDsdZnj/QGeIvk76JTmrtA2sC6ka2JBYxmWvd2sQ5MK6srQrF1mHVgf8EoPr1fl6bVdB8lFdZeo5VFXPBJQ67XWIdQtbMNaX1FXIvNmPQYj97Guw9g+0tzVk6nS91nBwXJD/T/U+4YuZ7my0mnQx7Q1DX/4S8xjRM+LdG0IiFq/zi/yEnlsRjPf51PlEq3sK0vnwyPOcvsV69THpzU9elt6f0X7LlJk+9Xt8avk15HjwuqTPlY/LGwuZ2dtUftmY8AfVmaYv8DwS35Q1HTrMay3gfQA0nT75u7ycJOF5fIztdgrx6cXmXVPH0uatS2JbLsi2w3UN73/dBp1u67zppfRdf7XsqC57yoqK+u6NN0+XrL2KBnf+ltzunUfYBmUW7ZT5OZ1p8ozrT8z070tzy9dDtysTug1+cQOfc47/L2R4qqTVuXlA4Wl8vP/PV7j6YyXww47TG666Sa56KKL1BPUFi5cqGKFX375Rf0gtWnTJkkWNRFbWevMjuXtJSfbFfadPl5BH8N7a2+s8UhFdBtdagTV+iKP673FWta2BI5bfLp81fWjcvNVZG/HuHX7Om26jbGe8/dGn7/2tt1o80Q771jLAWl9YGtvs019ZHsHuS135V63E+2zzjPinlLDEbavdBqixTfR4mDEMpfmbK5yuVvrSlt3upp+wPRLZNWA8ea8kefsaOvTrHEW0qfP65HnEExH7ItzP+KDI368UH7q+bpaDuf09m6c3wLSzJWhltH1rMvLV8nSy8aZeXhyR1sVi8Dh88+Rn3u8G5a2nr8Mle8OfVu93xgoFq/DoeJJbBf1CnTcqstNnzt0nq3nVMyL888R3uKwmGlKYQMzXtPLRB6jat2WeD2SNf7Ce+TfWi8i432d1p98GdLFkx9WZ6Odj3VMPmjBZaqcdIyo43fEvigT/Kvj5s7TrpD5Jz5tbjNyvdHqgjUu0n/j6PJD2VvrHtq0A9zb1byR7ZW1vuv9pfOo9wXWn+0IqL8b9vb3UGTsoNNija+scSvov5d0/Y9sd6LFQpF53FsMa41zsQzqp/XvPD0P6HVU1Kbrdiwyz/pvlkj6GCwx3JLjCP1dkOYw5LPCLnJO9gqVn7z8gNTvtDqh4yS7xUiJHCdV+Ra5nj17yrp16+L+JBU8phfdw4mIiKhi+KkAPw1V+WWzQl22bJkcffTR5aYjeMQt9cmkJmIrIiKiVBRTnCT2syxB46Qq/zT/0ksvyZVXXqnu8Tv44IPF4/GEfd+tW7cqrQ8DWeICE56m4nZXa8xxIiKipBcUh/ovluXspGnTprJy5Upp27Zt2HSMK4Bf6JJJvGMrIiKiVBVLnGS3GCmR46QqX9HZunWrrFq1Si655BJzGsYKwJ12+DcQCFRpfdOnT5e1a9fKpZdeWtWkEBERpZxUGYPp8ssvlxtuuEGNS4T4YsOGDfL999/Lv/71Lxk1apQkk3jHVkRERKkqVcZgujxB46QqX2DChSDc7/f222/HZZDvE088UQVQREREVLlH6TpiCITs8ghe7fbbb1e9nI8//ngpKipS3cDT0tJU4HTddddJMol3bEVERJSqYomT7BYjJXKc5I5lQO6PPvpIOnToUDMpIiIiopSGHjtz5syRa665Rm655RbVBbygoEAOOuggNSB2smFsRURERMkQJ1X5AtNxxx2nRijnBSYiIqL9Tw9IGctyduFyuVQP599//13q1aunAqZkxtiKiIio9uIkO8VIiR4nVfkC02mnnaYeh/fbb7/JIYccUm4gytNPPz2e6SMiIqIUHIMJg12vXr1a2rVrJ8mOsRUREVF8pMoYTAcnaJxU5QtMeMoJ3HfffeW+40CURERENStVLjA98MADahyB+++/X3r06CF16tQJ+z4nJ0eSBWMrIiKi+EiVC0wPJGicVOULTBhIioiIiGpHqgzyPWjQILNntHXQ62R8shpjKyIiojidU1NkkO9BCRonVfkCExEREdWeVBiDCWbOnFnbSSAiIiKbSYUxmBI5TqrUBaannnpKRowYIenp6ZVa6XPPPSfDhg2T7Ozs6qaPiIiIUkxZWZm6FR/xRMeOHSUZMbYiIiKiZIuTnJWZCYN65+fnV3qlt956q2zdurU66SIiIqIKf5lzxPCyT3HiASK//vqrJDPGVkRERIkSJ9lrT3gSOE6qVA8m3Md3/PHHi9tduTvqiouLq5suIiIiSuFBvi+44AJ5+eWX5eGHH5ZkxNiKiIioJs6vqTHI9wUJGidV6orR6NGjq7TSM844Q3Jzc2NNExEREVUAP7LF8kObzX6cE7/fL6+88opMnz496tNRHn/8cbEzxlZERESJESfZLUZK5DipRi4wERERUc1IlR5MixYtksMPP1y9X758edh31qel2BVjKyIiovhLlR5MixI0TuJT5IiIiOxkP3VhWr9+vdx2223y+eefS1FRkXTo0EHGjx8vRxxxRGh1hqEukrz44ouyc+dO6devn4wbNy5ug00m6tNRiIiIKIHtpy5MjJOqMch3ovM4XFIQLDE/pzlC182ynOlS35lpTi8z/NLUlSWbAgXl1mGdTy+71h8a2HxHsMhcZkVZQbn58AI9D7ZhpdNTYPjMdOp1Y7seh1tNx79II97jhfcdPVlqm4vLiqRfulNt48jnblbzZjm8Zvp0+rt6MuXvYIlKA9ZRavjVevqnG2o+lWaHW1q7Q0/409vRecB6sa4zV55oftZp1mmdVeJQaUG+GruK1DRr/pEurBPpxkt/j+1jOnR840rJDwbCygnfXZP7s/kZeZhUUFelbXuwzJyG1+2bu6t1I686nVi//leXtc4nyk+nH8vjX50uvbx1/+KzTjvSpfODdSCfWD/yr5fT8/gMt3xb3EI84pS7Gy1Q29oWCKrl8L0uA/3vaZm794kzPax8dJ3DZ+RRT8e/B3j2lHkrd6H4DEOyHQEpNYJh5dnCs0OtZ5U/V0ZtOVgOStuo9t2TO9qqdPXwhvbTEl+6XF1vpZnG7t5CtV9XlYU+6zJA3cK+RXqQNlWG4pQLVg4x04ZyxvSFPq/0XTgkrH53/Hq4Srs+Dtu4nCp9qOMN3XlmupEPTMe69HqxjjklQVVO2CbSoPf3QxsHhh3/uq52coeOD+sxiX/1vtLHg7X+QXv3nu+sdcSanmjLWY8B5AlpQDno/Qn6OEfZ4j323St5TcxtYV1t3em765IRtox1PdiPOv+6zLDMryPHhbU5mNYrLag+D8vertoDlKHP0vRj/ZiGsmnmcpfL1x/+UNk22D0P8nhjwznmfPqYwvy903aqz9iW/k6/lvt9YfvH2q7of3Vbh7yhvln3lW6j9L/6eLROa+HyhR1DVtZ9qefX+UT7iGNkfOtv1TQcI7qeIp1YF9qgbKfIAl+uTGgzXdVD1XY6vNLEFd4lORns2LFDXTDCIJK4wLRkyRL573//K/Xr1zfnefTRR9WT0PAEk7lz56qu2SeddJKUlIQfj/Hw119/qRfFznps4P3JGT7z+LTGLdZjxdq2ol2zTtfHp7UN1HFXmsMZFg9EHo84ftGWWI9FHbvgO7Rx0w76YE/aJXR+s8ZvWK/1szXdkfNqSFv+7lMl2phoy0XmUUPcg/OQlYrZDJ8Z02Ee63egyxb5unZDLzMd5nldgmFt6oh64YO2vpkfPuSELnMd76DNRF5/8mWoeRH36H2FWEm3Zfh3TqlHfi0Lqnzoc47OP2IVfO7y8lVyac5mNc26f3RsCh1mXqz+7TL7QjMd1vQ1dDnN9a4aMN78DtPwHebHPtblYmU9b6hz/u4YAunDed0a82JbeI99ifkwD0zr8aLaL4BYB/WwmSvDXD/KA2U16+L/qPXhPIf0nJOzSM0z3+eTn3u8W67c3zp4vFovzqVeh0P+DjplanGOWefxwvpwztXl9Ub+Aeb+QF4nFjRW+wzzYjs4//wZCKp9iLh4Y6BYhmbtCjtuXs9vEbY/kV7r3wHRIE1Ip35vrRd7/h4IHZ86fyjv/GCG+jvBOl8DZzBsPkAaUI4oJ33OxvqQx/UBr9om4ga9r5De1Se/LNOLmpnrnl5wkJleXQ9QDvrYRZuAMkpzhP6G0fsZdCyv6ya+PzItT52nAXm1/s1lzmv4VJqQR2wT+UE6dZyr/27Q5atjP5SlLg+dPv23lTUtecaeMlVl7ExX9QFtw7xSp0rXA9u6mHVc72fEcfibx9o2RP49ic/qb5xgSbnjRu8bzIO0Ih86nY9s76DyoeM4DWnB+lDGeps4LvTfm/rvDyyLNuOZtcea7bMuC+sxiBgMxzfWm+10yeCsZfJZYUuzDJMN46Qkv8BERESUMmJ6gpxDLVdZjzzyiLRq1Ur1WOrVq5e0a9dOTjzxRDnggANCSTAMGTt2rNx1111q3MVu3brJa6+9Jhs2bJApU6bEJZvBYFA9grdu3brSpk0b9apXr57cf//96jsiIiKicmo4RgLGSRXjBSYiIiLbPX43thfk5eWFvUpLS8tt46OPPlK3wg0dOlQaN24shx12mLoVTluzZo1s2rRJBgwYYE7DhaDevXvL999/H5d8/vvf/5ZnnnlGPR3ll19+Ua+HHnpInn76aRk1alRctkFERETJpaZjJGCcVAMXmHw+nyxbtkyNXk5ERET7Ryy9l6wDXqJnEi4G6deYMWPKbWP16tXmeErTpk2Tq666Sq6//np59dVX1fe4uARNmoRu8dTwWX9XXdjWSy+9pLaNHlJ4XX311epC14QJEyQZMbYiIiKqnpqOkYBxUhwH+cZAn9ddd50ZZGLE8vbt26tpLVq0kNtvv72qqyQiIqLKiqErt7mciKxbt05ycnLMyWlpaeVmxS1o6MGEHkOAHkx4WgnGWxo+fPh+2Vfbt2+XLl26lJuOafgumTC2IiIiqsU4qQoxEjBOimMPpjvuuEMWLlwos2bNkvT0PYP/oZv8u++GD4hHREREiXWLHAIn6yta8NSsWTM56KA9A7DCgQceKGvXrlXvmzZtqv7dvDk0GLCGz/q76urevbu6RS4SpuG7ZMLYioiIKD5qOkYCxklx7MGEwTtxIekf//iHOBx7rgx27dpVVq1aVdXVERERUYLBE+RwG7wVeixjoG3AoN+4kDRjxgw59NBD1TSMVYCnyeGWtnjAU+pOOeUUmT59uvTp00dNw/hO+HXxs88+k2TC2IqIiMg+GCfFsQfT1q1b1YCfkQoLC8MuOBEREVENMKrxqqSbbrpJfvjhB3WL3MqVK+Wtt96SF154Qa655hr1Pc73N954ozzwwANqoMvffvtNLrroImnevLkMHjw4Ltk85phj1EWtM888U3bu3KleZ511lrrwddRRR0kyYWxFREQUJzUcIwHjpDj2YMKYDJ9++qkacwn0RSUMxKl/YSQiIqKaYR2MsqrLVVbPnj1l8uTJ6tat++67T/VYGjt2rAwbNsyc59Zbb1U/Lo0YMUJd/DnyyCNl6tSpYbfPVxcuWD344IOS7BhbERER1V6cVNX5GSfF8QITfs0cOHCgLFmyRD1B7sknn1Tvv/vuO/n666+rujoiIiKqqir+0haLU089Vb0qgh+YcPEJr3hasWKF3H333fL888+HDbQJu3btUrfgoecUHjCSLBhbERERxRHjJKmtOKnKt8jhF8oFCxaoi0uHHHKIfPHFF+qWOYyL0KNHj5pJJREREVXr8bux9HqqDf/5z3/UY4IjLy4BHhmM7zBPMmFsRUREFB/JHCPZIU6qcg8mOOCAA+TFF1+MSwLWr18vt912m3z++efqMb0dOnSQ8ePHq+7iREREFCGGsQLM5WwAvaHfeOONCr8/++yz5fzzz5dkE8/YioiIKGXFEifZJEayQ5xU5QtMeEpMRV3l8Rg/r9db6XXt2LFDjcB+7LHHqgtMjRo1Ul3j69evX9VkERERURJYu3Zt1IeJaA0bNlRPkksm8YytiIiIKHmtTfA4qcoXmOrVq7fXp8W1bNlSLr74Yhk9erQ4nXu/A++RRx5RXbjQY0nDQKJERERUEZyDY+nKbY/u3+jevWrVKmnTpk3U7/FUu2jdwu0snrEVERFRaoslTrJHjGSHOKnKUcqECRPUU13uvPNOmTJlinrhfYsWLWTcuHHqaTJPPfWUPPzww/tcFx5tjFvhhg4dqq7CHXbYYXvtHl5aWqp+5bO+iIiIUkqsj9+1Sffvo48+Wp5++ukKv0eMcdRRR0kyiVdsxTiJiIhSXhLHSHaIk6rcg+nVV1+V//73v+rePu20005TA37jiS8zZsyQ1q1bq8cKIzjam9WrV6vAaeTIkWreH3/8Ua6//nrVFXz48OHl5h8zZozce++9VU0yERFR8kjyMZjuuOMO6dOnj/zf//2f3HrrrdK5c2c1fenSpfLoo4/KtGnT1JNrk0m8YivGSURElPKSfAymOxI8TqpyDyYkFj2NImEaniSnn4aCewP3JRgMyuGHH64ez4vl8Qvd5ZdfLs8991yFhYlHFOtXso3BQEREtE940kmsLxtAPPDee+/JN998owKo3Nxc9erbt698++23MnHiRBU7JJN4xVaMk4iIKOUlcYxkhzjJYRhGla7XderUSc4666xy3bRvv/12mTx5sixbtkx++uknOeOMM9QT4vYG9w2ecMIJ8tJLL5nT0KPpgQce2OeygFvkcA/ilmVtpEGOV3YEi6S+M1N9V2b4xePY00FrU6BAmrqy1PuCYIlsD5ZJM1eGmgfzFhg+2RAQ6eT2hi2HdWY59kzDslnO9LB06HXr7ev1gV52VolD+qcbYenS67KmW4u2nUjW7ZUa/r3OP7XYKydnhNKkVVRGWO9CXx05wlssaQ63WUbWfytaz+KyIunqib4PsF6Ito8iy+DJHW3lhvp/lPsO70uNoLkv90aXC/Jg9TfK1uEOyxumQQNnern8VbQvVpQVSEfPnnRY61Fzl6h0pjmc5j6KLKNjL79c1p1fJiuPnVDhdvQ+wb9Im5kmw6fWi3VhW5HbiLaf9Doi82813+eTzu6gSgfmx3wFhl/yg6Hv27rT5deyoLRw+cx9YC2Htf58yXa6ZHpRMxmatatcOjAv1hG5XZ3/ZX6n5Dh8an16v2A7WG9rd3bYfkUao20bPOKUS/44VSa1nx5Wh6ztQEX0tiLbE6RF7wPrsTCpoK4MrvO3uTzStjHgV+my5jeyHlvrO9a13O8zjx39vW5/9P7el/YfXy6rT3tR5QHtG+gytB6b0crB+n20NOp0WuvYH/4SlU+0Lwe4t6v3WDfqi96Hke0Hygd1CtvX7ZJeVzOXW+1XpMUrQbWOaO263kco34YuZ9Q2YV/tqm5L/g465duijnJl3fVh6dRlp49hzI9jW5dR+ykjZNkZ/1Pz/53nk8ad/1Q/fNTkPe/6nNfymXvFmbH380M0weIS+eva0TWezngpLi6WqVOnqrEEEKog/jjxxBMlM3Pfx4LdxDO2ilZndixvLznZrrDjQrfx+hwZrV3eG33Oqyju0qztd0XrQfuH+EuvL/L8qtO7t/bbGmdtDBSb7TjodtQaz80pCUq/dGeFcQ3oNs46HfPqtOwtJtpX3KRZv0MbpVnjgciyjra9vUF6l5Zlq/Kp7LI6jfvKS7Q21jqfPh9Z4z29HyqKC63xrT6HVSTyvBAN6pNPnGaMH21elBHae8QPyAPO7Yhj9Hn8+MX/J98cPCUsxreee6yxiS4HxFQ9vKG/T/R6o6VN1zHMlx8MiNfhCMszzpWg43isX59Ho5W/zo/+3nrcP7K9g9yWu1L2RscD0c6j1mMNkMd0h1/NH7n/IvX8Zaj8eNgk83vk6/j0orC/YSLPwypfEXUf3yEWbe8OzYP6BFgO5YlYYtTmfvJEs/lm+e7t78JoUJbR4mRdf6cW58hpmUXl/n7SdRvtS2NX6HvEKTp+sNbtyPg4sq3Rf8PoMn1kax+5usFss+5Gi4+wP7p5Qv1HIveFruN7+9uxon130tJTZFqXT6O2AdZ6p+M63b5qefkBqd9pdULHSXaLkRI5TqryLXKPPfaYGjMJT33r2bOnmoagB12ycCUNcKvbOeecs8914QlyCJqsli9fXuGAVURERCkvyW+R0zIyMuTMM8+UVBDP2IqIiCilJfktcokeJ1X5AtPpp5+uAh6MCYCLQTBw4EA1IGXbtm3V56uuuqpS67rppptUVy7cIodxB+bNmycvvPCCehERERGlgnjGVkRERES2ucAE7dq1q9RT4vYFv9Kh6zfGDLjvvvvUeseOHSvDhg2r9rqJiIiSUqxjBdhofIFUFK/YioiIKKXFEicxRqrdC0w7d+5UvY22bNmiBuq2uuiii6q0rlNPPVW9iIiIaN8cRuhVVbEsQ/tPPGMrIiKiVBVLnMQYqRYvMH388ceqh1FBQYEaAMvh2HN1EO8ZBBEREdWgFBmDKZUwtiIiIoqTFBmDKWkuMN18881y6aWXqnGTanuEciIiopSTxLfI4QkwlWWXp7xUBmMrIiKiOEniW+TybBAnVfkCEx6Pe/311/PiEhERUW1I4h5M9erVC+sZHQ0exYt5AoGAJAvGVkRERHGSxD2Y6tkgTqryBaaTTjpJPTq3ffv2NZMiIiIiSkkzZ86UVMTYioiIiJIhTqryBaZTTjlFbrnlFlmyZIkccsgh4vF4yj1ql4iIiGpIEvdgOuaYY+Kyntzc3CrNj1/6fv75Z2nTpo3UBsZWREREcZLEPZiOiUOcVNMxUpUvMF1++eXq3/vuuy/qxpOpyzoREVHCSeILTNEUFRXJ2rVrxefzhU3v1q3bXp/INnbsWKlbt+4+14+u5FdffXWtxi+MrYiIiOIkiS8wxSNOqukYqcoXmCIfnUtERET7URIP8m21detWueSSS+Tzzz+P+v2+gp1zzz1XGjduXKltXXfddVKbGFsRERHFSRIP8h2vOKkmYyRnleYmIiKiWuUwYn/ZyY033qh+ZZs7d65kZGTI1KlT5dVXX5WOHTvKRx99tM8LNpUNnCA/P59jSxIRESWBVIiRqhMn1XSMVOUeTFBYWChff/111K5YeMIcERER1ZAUuUXuq6++kg8//FCOOOIIcTqd6t7/E044QT12d8yYMWrcomTC2IqIiCgOUuQWua8SNE6q8gWmX375RQYNGqTu9UMwhEGitm3bJpmZmepKGC8wERERUXUhxtC/sNWvX191Be/UqZN6wAgGm6wq/AKH8SNnzZqluo3369dPRo8eLQ0bNqz1ncXYioiIiGorTopnjFTlW+RuuukmOe2002THjh2qK9YPP/wgf/75p/To0UMee+yxKieAiIiIKFLnzp1l2bJl6n337t3l+eefl/Xr18tzzz0nzZo1i2kgbfwgdu+996qgafXq1TJs2LCEKHjGVkRERFRbcVI8Y6Qq92BasGCBSjy6YblcLiktLVX35D366KMyfPhwOeuss2JKCBEREe0bhqGMZawAuw1fecMNN8jGjRvVewQ7J598srz55pvi9XplwoQJ+1z+iSeeUOMT4Am38OOPP8ry5ctV7KIDs3/84x+SCBhbERER1V6cZLcYqbpxUk3GSFXuweTxeNTFJUCXLIzDBHjM3bp166Q2eBwu2REsipjmljLDb35u6sqS+T6fDF09QLKc6dLanS1H3XGt+q7A8El9Z6Y0d4mUGn61HF5YZ5bDq9YFmIZlNwUKzHnwwrpXlBWodehtg3XZ/umhWq4/r/Xnq3Vheb1cQbDETC++iwbbaf/FZWo5z+7dh3WmOdxhZTCpYM9jB7HekzPCx8rSrPlIczhV3pAepLdMQk8MfGR7B7WNxWVFYeWqy8G6nq6ezLByt77HekuNPU8hvGljX7UO/Z21DG6o/4da9pK1R6nvsO/0fChvvT1ruXR4+0rzM8oCadXl+HewxCx7LI/pmGatH3jpdVnzaN0X1m129ITm17D+Jb508UpQtgWCan3WOqHTnO0Ijeg/88UX5dU+r1jK321uX28L65hTEloX6qnOA9aL71FnsS3UpxklmWbaMZ9eD+B7rAN5xr/bg2VqHpQrympWiUPN38PrVd8B6gPShPmR14Yup/zhL1Hz4DtdFvNKWqt14OV1OKT3GzeLz3Cp75FmpF/Puz6QbebBampxaLvdPM6w/af3STNXRlg5633S1p1uzp/r9KhywQvfT2o/XU23HmMNnOnmcaK/s8L+zjdCDSuW0fNa04L3qKc6H0OzdpnTddqauULf5RnesPZA7+vPCluqf3FM6WX1sYN1Y15sO3TM+NVnK8yHtkynWR83H5/8pHpfuvtJGNZ0Y/2RrGWBeqvXo9sBTMc0fZzqvODzxkCxeQwcn15kvtfbi2yTdb1E+eh5dLuE6Vhe71ekVa8P6cD2UIf19tF+Y/2YR7cJuj1CPUZ9xnTUK5121Z7vXr86rh1eWVqWrY6hy3L+VNP0+vW+1Mcw1vv4tl6qjLBurOvWYz9V8zy3q4XaR7XydJRYXjZywQUXyMUXX6zeo5c0eksjAEKscc455+xz+VWrVknv3r3V7WeAcQkwHgF+2Xv66afloosukpNOOkkSQU3HVmVGIOx40nBM6PqOYx11G8eQ9biPjE90u4llsD608bpN1G2Yng/rw/GK99b1afq4xjFvPTfo4z8yjrPS63szP1e1pSpu2d3OYJs6v3jh3IV/cU7S+TnIW2LOH7ktPQ3p0Nux5lHHIdFiIj3N2p7gM9oOa9npF3xclGnuD7x0PGBNjz4PoMys+8ITJf5DWvQ0tINIL8oH5aTPyZHp1+eUg5++KiyN1vKw7le4fXP3sDgQhv3RX82vyw37wppGxIHWWCbyXItytsZO0WIzvT+ssB3Mg/xZ04N/ESs0cO7Zrq4fSCPqj96nSJuOzfW5HXUA57uJB76hPs8rdYbiDEeoXPV2EF8hbtbxPSCm0edyvd6evwxVaUd9gC2BPed+He9Yz2k6hscL7wt2bycrIs7T9Ueznot1eWKdt+WuNN/r2DqyzHA86vOoLntreaMu6X2GmBDz63qp58MyqHs6DfBxt/Fhfy8hT9aYTu9zFXvsjnnxL2ImvU49D7aL9eBvIXzGeVhvG+t7otl8c/9F1mFAHButXlnLIVq8ipgb00/LLCq3rlGb+qt6gHW2cheqbeOFetXJ7VXHn/47yLpu5Bd1VO9z698w+lhCXu9vPF/VD12euhyxH3W8jTqHZXQ6MI+1juuYRsWWu8vd2qZE+5sUpnX5NCwOs6Yd68F3+Dss21Gi8tkvPfR3gm7bfi8rlv0qBWKk6sZJNRkjVbkH02GHHaYSjtHJjznmGLn77rtVd6rXX39dDj744JgSQURERJWUIoN8R8JYj4cffnil53/mmWfUbfyXXnqpHHvssWrAyzfeeEO+/PJLNb7A0KFD5dprQz801TbGVkRERHGSIoN8VydOqskYqcoXmB566CE1CBQ8+OCD6urWVVddpS44vfzyyzElgoiIiCopRS4wIcBBF+8ZM2bIli1b1GN1I5+esi/o3o0fxR555BHp06eP/Oc//5H3339fEg1jKyIiojhJkQtMgWrGSTUVI1X5AhMeg6ehG/fUqVOrnQgiIiKiyLEFEDihyzZ6SOtxAqrK7XbLv//9bzn77LPlyiuvlFdffVX9cte0adOEKXDGVkRERLS/46SaiJGqfIGpIngUHm6X++STT+K1SiIiIoqAgStjGuTbZr/OvfPOOzJx4kQZNGhQTMsvXLhQ/vnPf8rSpUulW7du8sorr6hf+caPHy99+/aVW265RfXATmSMrYiIiGo+TrJbjFTdOKkmY6QqDfI9bdo0+de//iV33nmnenQdIFGDBw+Wnj17luuWRURERDXU9TuWl43gKSgdOnSIeXmMK3DUUUep7t8YSwC/zMEll1wic+fOlTlz5qgu4bWNsRUREVEcpUCMVN04qSZjpEpfYML4SgMHDlTdsHCfHu7Zw0BQ2DC6UC1atEg+++yzmBJBRERElZQiF5huvvlmefLJJ8UwYks4Hrd79dVXS5cuXeS6666TNWvWmN81atRIxTD33nuv1CbGVkRERHGWAjFSdeOkmoyRKn2LHBKPC0voLoXBn3Cl63//+5/89ttv0rJl6PGRREREVLNS5Ra52bNny8yZM+Xzzz+Xrl27isfjCfv+gw8+2Ovy/fv3lxEjRsi5556rBrrs169fuXlOPPFEqU2MrYiIiOIrVW6Rm12NOKkmY6RKX2BatWqVuqgEZ511lhoQCiON8+ISERHRfmQ4Qq9YlrORevXqyZlnnhnz8q+99pp62u2HH34o3bt3l9tvv10SDWMrIiKiBIiTbBYjVTdOqskYqdIXmIqLiyUzM1O9xwjlaWlp0qxZs7glhIiIiCoh1q7cNvt1DgNNxurXX39VT1R57LHHKjX/4sWLpXPnzurHs/2JsRUREVECxEk2i5GqEyfVdIxUpUjqpZdekqysLPXe7/er8ZgaNmwYNs/1119flVUSERERxdVhhx0mmzZtUuMIVAbGk1ywYIG0b99+v+8JxlZERESULDFSpS8wtW7dWl588UXzMwb2fv3118PmQc+mqlxguueee8oNHoWrY3gyHREREaXuGEwIgBBXRMK09PR09eSUiy++WI499thy82DAy1GjRpk9r/fF5/NJbaiJ2IqIiCiVpcoYTIfFGCfVdIxU6QtMf/zxh9QEDEg1ffr0PQnaz93TiYiIbCVFbpE7+eSTZdy4cXLIIYdIr1691DQ8ThdduxEwLVmyRAYMGKAGsTzjjDPClj366KNl2bJlld4Wfp3LyMiQ/a2mYisiIqKUlSK3yJ0cY5xU0zFSrV/NwQUl/GJHRERElRBjDya7BU/btm1Tj+DFr2xWDzzwgPz555/yxRdfyOjRo+X+++8vd4Fp1qxZ+zm1REREZNs4yWYxUnXipJqOkZxSy1asWCHNmzdX9/QNGzZM1q5dW+G8paWlkpeXF/YiIiJKyV/mYnnZyMSJE+W8884rNx2P1MV3gO+r8itcsmOcREREKS8FYqREjpNq9QJT79691UDhU6dOVd271qxZI0cddZTk5+dHnX/MmDFSt25d89WqVav9nmYiIqJalSIXmDB+wHfffVduOqbhOwgGg+Z7YpxERESUCjFSIsdJtXqL3MCBA8333bp1Uxec2rRpo664XXbZZeXmv+OOO2TkyJHmZ/Rg4kUmIiKi5HPdddfJlVdeKfPnz5eePXuaYwvgqWt33nmn+jxt2jQ59NBDazmliYNxEhERUWpI1DjJYWAY8QSCwsFgVOittC+4wISeTOuWthB/nYC0dmeb35UZfvk7WCJNXVnq86ZAgfl+TklQ+qWHd96aVeKQ/ulG2PIeh9v8V1tcViRdPZlSECyRLGfoauCOYJHUd2aqbaQ5nOq9prd70tJT5NWO76r3ev4VZQXS0ZNVbpuA9ZdJULIcXjMdyA/W7xGn+g7/Ig06TVbW+bEtrC/N4TbXpc0p9Uh3b6GcseR8+ebgKea2AeuOTKM135Flo9erp0V+b52vwPCpdEVbptTwh+XPmnZreUemx5p2LK/zbf0ey04uaCdHZayqsOwj911k/mBiQWM5O2tLubQjX0t86XKQt0Q2BEQ6ub3l0q23deyl/5SZr7wUtv+ibRPzYj80dDlVfdBlB1OLvXKAe3tYXiJhnXDzulPl3Mbz5Mj0bVJqBM3tjNpysMzZ2l6+6vqRSqOuX9Z5cMz0SguqtGB9DbBfjNATBSraF9bjSudjrT9f1vnrSLrTL1sDWXJ8elFYuWPdfwed0twl5Y4pa9no+az13lq+1vplrfP6vbUM9Tyv5DWRM7PWmMdctGPJWia6Xv7hL6mw/LHf2rrTzfUh/2inIverdb3Ix7ZAUE1HGvHZ2g7gX13Wukys80DfhUPk6KYr5eEmC822RJeHtV2ITOsqf660cu8MK1drvcexie1aj8F9wbw4Ftqg/lrqh16vbqetaUP+UabRjkuUYa7TY+YfLls1VD7t9HnY/rTS5VRRux6ZJl23rWX6yPYOcmr2r2Flg2MXx3hxgUPqd1otu3btkpycHKkp+px3wJ0PiSuGX6MCJSWy6qE7azyd8fTmm2/KM888Y3bvxpNmEVCdf/756nNxcbH5tBSquM7sWN5ecrJdapq1LY08B+N4zQ/uiaf0OTnaeT+y3bF+jmwjIttdaxqs8+r147x0d6MFYfEPzjsVnU8j1xNNRce91ZM72soN9csPvG5ts5u53GHxnz4v63JD3oZdeoNMnfB82PasadZlOqmgrgyu83fUMtOf9Tas7S/aVH2e3FvedTlHxhaR27Cev63nDD092nx6n1rrQOR+taY7siwrSlNkWc0rdaqYfb7PJz283rAYJPIcqWPAAsOv1m2NnUDP8/KuLnJOziKzTqEtb+AMnYfx/Z+BoGrbUe+yHKH9rc/ny/0+dR6wxjeIA3S90OcoxAdYHrGKXreGZbt48uXb4hYyNGuXiuVOzvCpvOntWf9eQZo2Bvxq+zpGtp7TdT502UY7PqKVMej4I9rfNTpmsdYnvS2kuZGrQO2TaPtWzxf595W1jmHbkfGItU2KbGOitVfWYwDz6n3xeVETOSpjveQHJWo8EZm3aOu3rhf1Tccm0eq2NR7TMSvKIFQfy8eckSL/3opsi5Fer8Oh6oeu39Zls50SFudE0nUMUN+t7YdOf2RZRcZO1nmt27d+/rgoUzwOvxnf62OwOF+kVZf1CR0n2TFGStQ4KaYeTKtWrZLx48erf5988klp3LixfP755+pxu3gqXKwKCgrUOi+88MKY10FERETJAWMz4lWR2njyW02pqdiKiIiIktOwBIyTqjwG09dff60ehTd37lz1yDtcFIKFCxeqUcqr4l//+pdaHx7Ti3sFzzzzTHG5XFEHqyIiIqLUGYMplcQztiIiIkppjJFqVZUvMN1+++3q0XdffvmleC3dIo877jj54YcfqrSuv/76S11MQleus88+Wxo0aKDW0ahRo6omi4iIKCXg0buxvhJdbm6ueuwu1K9fX32u6JVM4hlbERERpbJkjZHsEidV+Ra53377Td56661y09GVW2e2st55552qbp6IiIhsEghV1RNPPCHZ2aExJ8aOHSupIp6xFRERUcpjnGSfC0z16tWTjRs3Srt27cKm//LLL9KiRYt4po2IiIhSyPDhw6O+T3aMrYiIiCgZ4qQq3yJ37rnnym233SabNm1SI5IHg0GZM2eOGk/poosuqplUEhERUUqMweT3+6W0tDRs2ubNm+Xee++VW2+9VWbPni3JhrEVERFRnCRxjGSHOKnKF5geeugh6dKli7Rq1UoNQnnQQQfJ0UcfLX379pW77rqrZlJJREREST8GE1x++eVy/fXXm5/z8/OlZ8+e8uyzz8q0adPk2GOPlc8++0ySCWMrIiKi+EjmGMkOcVKVb5HD4JMvvviijBo1ShYtWqQuMh122GHSsWPHmkkhERER7RHrL202CZ7QK/qZZ54xP7/22msSCARkxYoVUrduXdWL+j//+Y8MGjRIkgVjKyIiolqMk2wSI9khTqpyDyatdevWKtF4+hsvLhERESVvD6aHH35Y3RZ/4403mtNKSkrkmmuuUU+AzcrKkiFDhqgu2tW1fv36sLhixowZat0ImvSYA4sXL5ZkxNiKiIjIfj2YGCdVsQfTyJEjpbIef/zxSs9LREREid2D6ccff5Tnn39eunXrFjb9pptukk8//VQmTZqkLv5ce+21ctZZZ6lf1qojPT1diouLzc8//PCD+iXO+j16T9sdYysiIiL792BinBTDBSY8Ia4y8OsmERERJQdcyBk2bJi6Nf6BBx4wp+/atUtefvlleeutt+S4445T08aPHy8HHniguiD0j3/8I+ZtHnroofL666/LmDFj5Ntvv1W9ovQ2YNWqVdK8eXOxO8ZWRERE9sY4KcYLTDNnzqzMbERERJTgPZjy8vLCJqelpalXNLgF7pRTTpEBAwaEXWCaP3++lJWVqekaHt8s+EcAAGLaSURBVACCW7y+//77al1guvvuu2XgwIEyceJE2bhxo1x88cXSrFkz8/vJkydLv379xO4YWxERESVWD6aqxEjAOCkOg3wTERFR7Yl1rAC9DJ4CazV69Gi55557ys3/zjvvyM8//6y6fkfatGmTGpi6Xr16YdObNGmivquOY445Rl3A+uKLL6Rp06YydOjQcj2cevXqVa1tEBERUXKKJU6qaowEjJOqcYEJYypMmDBBcnJy1Pu9+eCDDyqzSiIiIqqFHkzr1q1T53Mt2i9zmOeGG26QL7/8Uo15tL/hVju8ohkxYoQkA8ZWREREidWDqTIxkp6PcVI1LjBh8E49vhIKnGMtERER2fMCE87j1uApGvQg2rJlixx++OHmNDwC95tvvlGPxp02bZr4fD7ZuXNnWC8mjJeEXke0b4ytiIiIEusCU2ViJGCcVM0LTGeeeab5CyZ6MhEREZE9b5GrjOOPP15+++23sGmXXHKJGmfptttuU13IPR6PzJgxQ4YMGaK+X7Zsmaxdu1b69OlT9cSlIMZWREREiXWLXGUxTqqYwzCMfRany+VSYyo0atRIvcegm40bN5bahkG48AvgjuXtJSfbJYvLiqSrJ9P8viBYIhsDfunoyVKfrd9vChTISfMvl4W93lafdwSL1L+r/W7p4fWW21aZ4RePwx323jptRVmBuR29vvrOPWnR6SmToJq+1p8vrd3Z5b7PcqaX28avZUGVJuv7aOkrMHzlthmZfqQry+E1010ZI/7qK7c0+UJ84pQGzqA0dWWZ+dPl5hGnSjvysMzvNNOI7ZYafvUdyjzN4VTLYb7Tfz9bvur6kZpHrcPhlke2d5CR9Zeq9wd+d4H83vcNczmYXtRMBmZulu3BMvE6HNLAmW6uv/0HI2T1WS9EzYN125quD3rf6TxFphnbiFZekfUN3szPlVLDIwMyV6r9++SOtnJ1vZVq+ds3d5e7Gs019zG2h3JLc7hlY6DYrA+R60Ua/g7uKXsNyy/xpUs9V4lMLzhILqu7VP4MBNWyer9sCEi5NEajt4m8/+EvkbbudPk7WKLyjn9XlWVKY1eRmg7L/T7xSlCaudyqTmM7SB/KGHkCnU8rlHVDV/h+QP4A25pX6pSDvCXmfogsd0yzlpW1HLG9aMcdlkEeUHbW4y7a+mFWiUP6pZWVO8atZaThO+txG1meWFf/dKNcuqx1zJoP6zzWtOJ9M1eGuU+wrG7b9tX26PVgPuw/pBnTcPygTKzHX0V0u6G3j3mx33yGEbbuOaUeVXaYTx+z0drByH1lTZveX9GOO308QmQ9mFrslZMzfGpdWwKh+op/W7kL1Xx6vdZ2QO8fmFMSlF5pwb3uF2t9sE7Pyw9I/U6r1ZPVKvOrV3XPeV2uf0hcaVW/bS1QWiJLn7oz5nT2799fjX80duxY9fmqq66Szz77zLyF/rrrrlPTv/vuuyqvOxXtj9jKGidlZBlm/dXtrj6noG7j+NXHQ2SMUlF7GY11XmxHb8P63hpDWNsI6+fI7/TykW0upmc53OY5W7+P3M7c0nqqjdDp0+uJbEMrc66P1qZHa6+s52zdfiFWg8h2Jdq5JNo6rJ/1ucG67WjxpRW2g7gDrMtFxoeR5wadvmgxsPWcdvAP58szh75t1iXr+nW+o63Dun1r+er8RH6P8/7s0hw5Pr0oLI2RebOes/V0vd3IGA/LFxj+sDLW54d+6c6wfWCNLZCebYGgOX+2MxTTWM9TiA+HZW+XYX/0lwltpoeVvY69EB+VGkHJD0rUOmmtI5MK6srQrF1m2aE8EBfoOC1y36BcIuuoNe6Nth8itxmtXljpstHtS2TcjWUR5+Fci+Wjxd/WdKNM8LfH1kCdcvUpEurJt8Vt5KiMP80yjxYTWtMZ+X6+z6f+ftlXGext3boOIW7v5Paaf5thOmL05i6Rd/M7ypV114fVw7Hb+snVDWZLrtNj/q2oy0HXWexH63fW9OsYyLrM3tKq50Ec1N6dV2FsHLm/9bqsx0Q0+pzS3Vuo6maw0JPwcVJ1YyRgnBRScc2wQPCDxw4DrkfxFjkiIqJa7vodyyuOnnjiCTn11FNVD6ajjz5a3RrHcRgrj7EVERFRDUiAGCmV46RK/Rx15ZVXyhlnnKEuLOG1t/EVMEYDERER2fcWuWhmzZoV9hm3zj/77LPqVRPw9LpgMCi9e/cOmz537lzV4+eII44QO2NsRUREZM9b5KJhnFSFC0x4NN+5554rK1eulNNPP13Gjx9f7tHERERElPiDfNvFNddcI7feemu5C0zr16+XRx55RF1osjPGVkRERIk1yLedXJOgcVKlB+LBwJ54jR49WoYOHSqZmfse14WIiIjiLEUuMC1ZsiTsKXbaYYcdpr5LBoytiIiI4ixFLjAtSdA4qfIjPe+GC0ywdetW9cQY6Ny5sxpLgIiIiGqWY/crluXsJC0tTTZv3izt27cPm47BsN3uKocvCY2xFRERUe3FSXaLkRI5TqrUIN9WRUVFcumll0rz5s3VYFV44f1ll12mviMiIqLkH+S7pp144olyxx13qCe6aDt37pQ777xTTjjhBEkmjK2IiIjiJAVipESOk6p8gemmm26Sr7/+Wj766COVAbw+/PBDNe3mm2+umVQSERFRSnnsscdk3bp10qZNGzn22GPVq127drJp0yb573//K8mEsRURERElQ5xU5b5T77//vrz33nvSv39/c9qgQYMkIyNDzj77bBk3bly800hERES1/BS5/a1Fixby66+/yptvvikLFy5UccYll1wi5513nng8HkkmjK2IiIjs/RS5/a1FgsZJ7li6cTdp0qTc9MaNG/MWOSIiopqWIoN8Q506dWTEiBGS7BhbERERxUmKDPKdqHFSlS8w9enTRw1G+dprr0l6erqaVlxcLPfee6/6joiIiGqYTQOhfcHt9wMHDlS/vOH93px++umSLBhbERERxRHjJKmtOKnKF5jGjh0rJ598srRs2VK6d++upqFLFi42TZs2LeaEPPzww2qQqhtuuEFtg4iIiFLrFrnBgwersQPQKxrvK+JwOCQQCEiyqKnYioiIKNUk8y1yg20QJ1X5AtMhhxwiK1asUPf6LV26VE3DfX7Dhg1T9/3F4scff5Tnn39eunXrFtPyREREKSOJb5ELBoNR3ye7moitiIiIUlIS3yIXtEGcVKULTGVlZdKlSxf55JNP5PLLL49LAgoKClQA9eKLL8oDDzwQl3USERGRveFW/HPOOUfS0tLCpvt8PnnnnXfkoosukmRQE7EVERERJbfXEjROclZlZoyJUFJSEtcEXHPNNXLKKafIgAED9jlvaWmp5OXlhb2IiIhSset3LC87wZNQdu3aVW56fn6++i5ZxDO2YpxERESpLhVipESOk6p0gUlfEHrkkUfE7/dXe+O4svbzzz/LmDFjKjU/5qtbt675atWqVbXTQEREZMuu37G8bMQwDDWGQKS//vpLxQDJJF6xFeMkIiJKeSkQIyVynOSOZbykGTNmyBdffKHGDMCj8aw++OCDSq1n3bp1akDvL7/80nwa3b5gEPCRI0ean9GDiReZiIgolSTzIN9w2GGHqYAJr+OPP17c7j2hCgasXLNmjRoQO5nEK7ZinERERKkumQf5tkOc5DBw6asK9tXdavz48ZVaz5QpU+TMM88Ul8sVViAoKKfTqbp5W7+LBheYcHVux/L2kpPtkk2BArl744nyQsvv1Pssh1uynOmyI1gkHnGq9wXBEimToNR3ZprrWVxWJF09ez6XGX7xOMKvvWGaZv0u2rwrygqkoydLpSHN4VTb0vMhLVkOr7kM5mnqylLpQvqs69TrqSysG9vCOgHr1dMi06rf6+13Hn+VLLtknJkOPd26TOR3FW0fy5QafjM/KF+vBKWtO13+DpaoZdf68yXb6QorG6tJBXVlaNausHLRMC3N4Y5antbPmG9jwC8NXaF9oNeF7b2e30I6ezdKd69PTRv2R3+Z0GZ62H5p4ExXn637A3nA+4+LMuW0zCIzTXr+eaVOKROXHOEtVtOtZYA6ptc1tdgrJ2f4wso1sh5G5g3fd3J75Q9/iVkvrPta0+Vv3b5m3a51fmxjVolDpVsvg3X7DENau7PD5kM5NHO5pcDwm/Vbw37V8+v9CD7DJcOyt6vvSw2H5Ble6eZxlqtbMKckKI1dRWq/bQsE1bb0sav3X2R9sdYJ7fbN3eX+xvPLzauPSw1lDBsDxSpt2MdW0eqELo8Cwxd2fFnnx+c5pR7pn76nicU6/g46pbkrtN2X89rIlXXXl9vnWK9us7Ae7PM0R2hfoPx1nbaWN5bdEBBVRyKP84qOVWv7ANdu6CXPNJ9nbjOyHatonda2Sq8z2rEbrV2J9n0krN8nTjNvkel+Ja+JnJ31p/zkyzDL29pmW/dTZBlYj2vrNJ13nR4cf3OL20l77xa1DWs+g4Ueqd9pteqmnJOTIzVFn/O6XfKQuLyV+2HGKuArkV/H31nj6ayue++91/z35ptvlqysPXXC6/VK27ZtZciQIep9sohXbLWvOAn08RftGLXS86Huo82ynq/1ecDaNlvta93R2o1SI2gebzgP9EoLhp2Do7UR1nZXn0Mj24eq0nEiWM/BkXmLPAfo6fi393M3yeKrx1V4bqwM3aaj7HXZ6G1WJm3W71Bu6wNe6ewOhn2v02WN36KdPyqKJXUadblb92G0OEqnEfGDdT/qc7j52VKuSGOu01PuHK9jPGs89G1xCxU76nqB89iWQKb0S3eGbTeyflZ0TrR+by3vvguHyH86T1J1VO8PvZzON+JdawwVbZ1Dfj9X+jVaLfc3XhSWBh2X/FoWNPeZLt/8oJSLayP3i44DI8+JmBZZ9tY6j7gj8m8kfTyiDPW/mvVvCWucMN/nkx6W9vnN/Fw5O2uLWRcgsm2JjLEit6Hrgo6DsN+tf29Y/55Cvlu48s15IteJspxbWk+OTMszyzbyb4nIssB6sE9B/31prTvWstQxvY5ZdHlY95fOu471tMi/BaxlYP0bVpeFtV5HHqe6nK3xYWR9jRa76s+RdUpP13+jWesq9oM+RvXfGtY22VWYlvBxkl1iJDvESVXuwRRrkBMJV9t+++23cgEWBrq87bbb9nlxiYiIKCUl8VPkYPTo0epfBEjnnntuucErk1G8YisiIqKUl8RPkbNDnFTpMZjwGDyMD9CvXz/p2bOn3H777VJcHOqlEYvs7Gw5+OCDw17oEt6gQQP1noiIiFLXcccdJ1u3bjU/z5s3T2688UZ54YUXJFnEO7YiIiKi1HBcgsZJlb7A9OCDD8qdd96pumC1aNFCnnzySTUoJREREe0/qfIUufPPP19mzpyp3m/atEk9bRbB07///W+57777JBkwtiIiIoqvVIiREjlOqvQFptdee03+97//ybRp09T4SR9//LG8+eab6te3eJk1a5aMHTs2busjIiJKOinyFLlFixZJr1691PuJEyeqwa+/++47FXtMmDBBksH+iK2IiIhSSgrESIkcJ1X6AtPatWtl0KBB5mdcIcOA3Bs2bKiptBEREVEEBx5LG+PLTsrKysxxBaZPny6nn366eo+xGjdu3CjJgLEVERFRfKVCjJTIcVKlLzD5/X5JT494upLHozJGRERE+0mK9GDq2rWrPPfcc/Ltt9/Kl19+aT5yFz9sYbzGZMDYioiIKM5SIEZK5Dip0k+RMwxDLr744rBRyktKSuTKK69Ug3NrH3zwQfxTSUREREqsYwXYbXwBDH595plnyn/+8x8ZPny4dO/eXU3/6KOPzC7hdsfYioiIqPbjJLvFSIkcJ1X6AhMSHemCCy6Id3qIiIiIpH///rJt2zbJy8uT+vXrmyUyYsQIyczMTIoSYmxFREREyRQnVfoC0/jx42s2JURERLRvsXbltuGvcy6XKyxogrZt20qyYGxFRESUAHGSDWOkRI2TKn2BiYiIiGpfqtwi165dO/UwkYqsXr16v6aHiIiIEl+q3CLXLkHjJF5gIiIispMU6cF04403hn3GQ0V++eUXmTp1qtxyyy21li4iIiJKYCnSg+nGBI2TeIGJiIjIRlKlB9MNN9wQdfqzzz4rP/30035PDxERESW+VOnBdEOCxknOWtsyERER7b/H79oweIpm4MCB8v7779d2MoiIiCgRpXCMlAhxEi8wERERkW289957kpubW9vJICIiIko479VynMRb5IiIiGzGjl25q+qwww4LG7zSMAzZtGmTbN26Vf73v//VatqIiIgocTFO+l+tlT0vMBEREdmJYYResSxnI4MHDw777HQ6pVGjRtK/f3/p0qVLraWLiIiIkixOslmMlMhxksPAT4I2lZeXJ3Xr1pUdy9tLTrYr7Lsywy8eh1tWlBVIR09W1O8i7QgWSZbDG/W7yGULgiWStnu+v4Ml0sCZrv5t6spS8xQYPqnvzDSX2xQoUN9huSxnujl9vs8njZyl4nU45O+gU7wSlGYutyzzO6Wbx6m2hXRZ1wWLy4qkqyfTTI9evzW/ehr+RfownzXvOg/3bT1U7m+8KGz91nRiGZ03vQzyh7LS05HGo+b9U37p/Zpa/1p/vmQ7XeIRZ1h+sS6oqPyt+Xxkewe5LXelTC32yskZPrXtMgmqeTDv7JKGclpmkZoX+faJU5WJLhtrPqxloNcbLU2R7//wl0hbd3rY/rSWIdab5nCa380pCUqvtKCaH3lHercFgpK2+zI6ygQwP8pocv4hMiBriXRyh+pdZL1F+jcGQmlq6HJKqRE0t4fvFvq8Us9VIs1dIvnBgLR2Z1dYZ61lALdv7i4PN1kYNi+2i+1g/br+6HwuLcuW9u48VVd9xp78bAiIWd7Wbc4oyTT3m64Ds0occoS32NyPuox1ncV+XeJLl4O8JeaxGDmPtW6jvPulO8vtl8i6ZD1uUZ6RbYKuKzpdVthPYC1bfYwjjYDjwFoP9Pbxr64HyJdOqzVNep6ffBnSP31Pc6yPIb0e7Hvr/rMuj+/0vrIujzTrtOj5I4/ByDZE14MFpS1kaNausPSWGn7zeEJ+rWl6YFsXua3BIjVPgeE316Xbj/UBr/TwhsoLy68qy1TlocsS9aiBM5QPfQxPKqhrpkFP0+2BzpfOp96WPmatedTl8VlhF7my7nr1Ges5yPN32H61Hs+6PKzrnFjQWIZlbze3qefZsKtIWnVZL7t27ZKcnByp6XPeEf/3gLg9e9rVyvKXlchP791V4+mkxKHrzJqlzaRZTnq5thTHEc5RaPfRDuH8bj2/6ePYGh9Z21fr+VZ/znbsORfp73HMNHNlRI2NorWd0ei2Cu3C4Dp/q/c4p6DdRPttbXcQWyGGAr1NnQZruxAZk0XmuyKRy+l06+nWc5NuLyLjC2tZYpt9P7tJVp/2Ylga+i4cIt91jz6Oht532J94D9YYdm/nRLTx2U4xY8TI/EabZo07reUK127oJVmu0rCYQm8f+0K3/dZ2W5/frDFmtLLV230zP1fOztoiGwPFYXVJpwfnHus53Hoe1nGFtYz0Od9arwHLYP81dhWZxwo+61hrbmk9dQ6KrPvW+o84CTFTd2+huY9wzjk+vUiW+31mzIf9cOnIm+Wrp55Vnz8uypTu3s3muVunx1qmyDfivXzDZZ4zrWWAsrPGkvp8qOueLt+K/uax1lfrd9bPkXGw3ne63mNaFur57hhYp8G6nyNjUut69b9IC8rS2g7pWDfy7xls67PCltIlbVO5+mYV7e9CLP9nIKj2Xa7To8rHOp/O177KAPsf+yQ/KJJnhGIezKfrrDVv+riwxok6lkO7hrpjjfl1OvH3If5utMZ31vLTx6aOzaOlWdcBa/xkPe6s5wVr/GjdDuqxtf7rbWMf4+/ZyGMjLz8g9TutTug4iTFS/LAHExERkZ3EOhilDX9OCgQCMmXKFPn999/V565du8rpp58uLlf4j0pEREREMcdJNoyREjVO4gUmIiIiG3EEQ69YlrOTlStXyqBBg2T9+vXSuXNnNW3MmDHSqlUr+fTTT+WAAw6o7SQSERFREsRJdouREjlO4lPkiIiIUuHxuzb7de76669XwdG6devk559/Vq+1a9dKu3bt1HdERERE5aRAjJTIcRJ7MBEREVHC+frrr+WHH34Ie9RugwYN5OGHH5Z+/frVatqIiIiIatPXCRon8QITERGRjeCZAbE8ftduj+xNS0uT/PzQIPtWBQUF4t09iCsRERFRdeMku8VIiRwn8RY5IiIiOz5+N5aXjZx66qkyYsQImTt3ruCBt3jhl7orr7xSDWBJREREVE4KxEiJHCfxAhMREZENf5mL5WUnTz31lBpboE+fPpKenq5e6PLdoUMHefLJJ2s7eURERJSAUiFGSuQ4ibfIERER2Umsg1HaLHiqV6+efPjhh+opKfrxuwceeKAKnIiIiIjiFifZLEZK5DiJF5iIiIhsJFXGYNIQKNV2sERERET2kCpjMCVqnMRb5IiIiCjhDBkyRB555JFy0x999FEZOnRoraSJiIiIKBEMSdA4qVYvMI0bN066desmOTk56oX7Bz///PPaTBIREVFiS5FBvr/55hsZNGhQuekDBw5U3xERERGVkwIxUiLHSbV6i1zLli3l4Ycflo4dO6pRz1999VU544wz5JdffpGuXbvWZtKIiIgSUqrcIlfRY3Y9Ho/k5eXVSpqIiIgosaXKLXIFCRon1WoPptNOO01ddcMFpk6dOsmDDz4oWVlZ6vF6REREtJfBK2N52cghhxwi7777brnp77zzjhx00EG1kiYiIiJKcCkQIyVynJQwg3wHAgGZNGmSFBYWqlvloiktLVUvjb9gEhFRqkmVHkyjRo2Ss846S1atWiXHHXecmjZjxgx5++23VbxA5TFOIiKiVJcqPZhGJWicVOsXmH777Td1QamkpET1Xpo8eXKFV9zGjBkj9957735PIxERUcIIGqFXLMvZCHo5T5kyRR566CF57733JCMjQ43bOH36dDnmmGNqO3kJiXESERGlvFjiJJvFSIkcJ9X6BabOnTvLggULZNeuXapghg8fLl9//XXUi0x33HGHjBw5MqwHU6tWrfZziomIiGh/OOWUU9Qr0qJFi+Tggw/mTojAOImIiCh1nJKAcZLDwOjaCWTAgAFywAEHyPPPP7/PeXGBqW7durJmaTOZ62ohQ7N2md8VBEtke7BMWruz1XtIc7jlD3+JdPRkyVp/vjRzZYjHEbrGtqKsQE2HN/NzZVj2dnNd+K6tO10KDJ/Ud2aqaTuCRZLl8JrTsI0sZ7r5HabN9/mkszuotovtlBl+9a/+Ptoy1vf4d0NApJPbq5bbFCiQBs50We73SVdPaF6sU+cJ71XeDZ94xCllEjTXiW39GQiq5bCeLIc7bNvIC+h1LS4rkjYup5pHp1tvX+dFbwvb0PNY02+dBnNKgtIv3anW09QVSu/fwRJznYD9ku10SX4woPbdrBKH9E831DKg87/OX09OzvCpfBUYfrU+7Kd5Ja3VvsP7LYFMtb2pxV41r94uHLf4dHm+01tqvyLP2U4xv9PlqvP5yN8Hy0X1flTTkaaKYP1/B53ilaA0dDml1Aiq6Xq9keUI+nOaw6nKDOWu97e1fljrNaahjLVtgaDaZ9b9o8tR73981mlH2QCWidwn1n3Vyl2o1oG6Yd2PmNdnGJJvuFQdmV2aIwd5/lbH08ZAscwtaSmHpq1X6+/5y1D58bBQF02kecjv58rdB3ys9mlkncF2Sg2/Om69DofKC/bNKn+utHLvlOYuKXfcRO6vyO90HUP56jqutxl5PGqjthws9zdeFLZ+6zGpWeu4bmM2BvyqTqEcSg2Hqge6Luty7ZUWlBklmXJkWp55jFrLQu8L7CddL63tk04P2oYGzqD6/rldLWRw1jLzuIp2jOp27ckdbWVQ1iKzzmAZpOsgb4m5r63tiq4jusysZRhZPoA6jHYG884rdZrLRu4r/PtrWegY6eH1hi2H7/V2rcdyVei86X1mbV/RPup6EtlO4TP2z/HpRarsdJlgORzTWCf2N/Y19g+OhXrFmVK/02r1QwmeiFpT9Dmv74B7xe0JPwYqw19WIt9NH13j6awp+fn5qtv3Sy+9JPPnz1e31lPl6syO5e0lUKdUHQcPbOsi/6z/k6q7um3SbWfk8RDZPupzLtpnHB+gjxF9nra2Q6CPbes6cSzp8571/GRtZyYWNFZtFpbfGqgj2c5S1VZU1J5ExiB626DjGbDGIDjnYLo1X9b1IW25To/6Lj/UXKnjXqc98txpbSOtabK+t56nIssd6dXnOiudp0vWHiXDG89W59BI1vOo2i8R+xPvrXFsJN2u4RymPhs+s82LJtp519pO4v1CXx0pMTzqfKdj4cj9b2WtQzo2wrw6ZsL5XKcnMtbUbTfiBV3fMM8SX7qKZxBXWGMtPQ/Sj3Ox2m/iDEunNX16X+u/L1AvrPGGnh/zrSoLnbMiz92gp0XWiVCZh/ZdtLJBLKtjLWvcHxk76HREO66ssYHedzq/1uNCrx9/x+CYi3aexDw61tXbRVnrc7W1LkTuY2v+ou1H63GJsgbEVJFxEOq7TquOgRFXpDtwLIe2ret9ZCyrYwHs+8h0on5geV0XreWn048YDHVI1yW9X60xXOTfGJjmE2dYrBNZ7yP3l34POq+6Pug4BenXdU6nR+cBZYLy1PsZ+/TH4nZyZd31Yfsl8u9ana7r/hwsk9pPD5vXmsaK2hTr33iwNc8nrbqsT+g4ye4xUiLFSbU6yHc0wWAwbJwlIiIi2sNhGV+gSi+bFiIetXvRRRdJs2bN5LHHHlPjDPBhIERERBS3OMnGRflNgsVJztruyo0C+eOPP9RYTPg8a9YsGTZsWG0mi4iIKHGh43GsryqM5dOzZ0/Jzs6Wxo0by+DBg2XZsmVh82DsxGuuuUYaNGigxlAcMmSIbN68OS5Z3LRpkzz88MPqKbNDhw5Vv0jixyeMNYDpSBsRERFROTUcIwHjpAS9wLRlyxZ1tQ3jMB1//PHy448/yrRp0+SEE06ozWQRERElrJh6L1XxiSoYCxEXj/AL2JdffillZWVy4oknqie9ajfddJN8/PHH6kklmH/Dhg3qaSbxGLQSccGvv/4qY8eOVet9+umnq71eIiIiSn41HSMB46QEHeT75Zdfrs3NExER2Q+CoFhGT6zCMlOnTg37PGHCBNWTCff0H3300WqMApzD33rrLfPRuOPHj5cDDzxQXZT6xz/+IbH6/PPP5frrr5errrpK9WAiIiIiqtE4qYrzM06y0RhMREREJDU6CKb1VZlxD3FBCXJzc9W/uNCEXk14MIfWpUsXad26tXz//ffVSt/s2bPVQJU9evSQ3r17yzPPPCPbtm2r1jqJiIiIaiJGAsZJe/ACExERkY04DCPmF7Rq1UqNaaRfGEdgXw/fuPHGG6Vfv37mI28xRpLX65V69eqFzdukSRP1XXWg99OLL74oGzdulCuuuELeeecdad68uUoHbtfDxSciIiKiaPZnjASMk8LxAhMREZGdBKvxEpF169apX9r0Cw/Y2BuMxbRo0SJ1oWd/qlOnjlx66aWqRxMeBHLzzTerAb5xq97pp5++X9NCRERENrEfYyRgnBSOF5iIiIhSqAdTTk5O2CstLa3CbV177bXyySefyMyZM6Vly5bm9KZNm4rP55OdO3eGzY+nyOG7eMOg348++qj89ddf8vbbb8d9/URERJQc9leMBIyTyuMFJiIiIjsOXhnLq7KbMAwVNE2ePFm++uoradeuXdj3GB/J4/HIjBkzzGnLli2TtWvXSp8+faSmuFwuGTx4sHz00Uc1tg0iIiKysRqOkdQmGCcl5lPkiIiIqIrwK9vuX9qqvFwlobs3nhD34YcfSnZ2tjmuEsYjyMjIUP9edtllMnLkSDXwN37lu+6669TFpeo8QY6IiIhov8dJVZyfcVLFeIGJiIiIwowbN079279//7Dp48ePl4svvli9f+KJJ8TpdMqQIUPUU1ZOOukk+d///seSJCIioqTGOKlivMBERERkIw4j9Ipluap0/d6X9PR0efbZZ9WLiIiIyK5xUlXnZ5xUMV5gIiIispP9cIscERERkS3th1vkqGK8wERERGQjjmDoFctyRERERMksljiJMVL88AITERGRnbAHExEREVH84iT2YIobXmAiIiKykxgep2suR0RERJTMYomTGCPFjVOSQD1nhgzN2iWbAgUytdgrZYZfspzp0tqdLTuCRfKTL0PNV2D4pKErlOVsp0s8DreaF6+Onix5ckdb9d2w7O3qXyxbECxR32He+s5MNS+m4z3gX8yD7cGKsgLzuxYun5qO7a7156t1aFimwPCr6Xo9enmrrp7Q9FklDklzONU6Orm9MqckqNIBSB/gu1LDLy/s7Ka2m+XwqjLBC5+9ElTbberKMtOL8tLbxvJYF9art4v0If2A5QDrw7yYjm3M9/nUe6QR6ce0xWVF8newRJUXton19Et3mtuHP/yh90gzlsMr33Cp9JQaDrWd/umGmt7AmW7mH2k7OcOn1p3mcMvfQaeat6073dx3yEevtKCap3faTpUebEuX2VddP1Lz63nxHdKI+TAPtoN1wl0Nl0ozV4aqM0g/0oPvMC9gG9gfWQ63KmPYEBCVXkzDejGPLm9sa7nfp/I9asvBu+fzqu+QtzmlntB6d+8vvFC2aj27148ywssjTtkSyFT7wGcYZpmj7uP7N/Nzzc+6biG/eGE69om1bHSd7+71mftiXml4M5EfFPE6HCqvGwN+tS9ynR5VZignHIu6Hn136NvqX6QdeUS5d/Hkq/zo+o7t5QcDu49Rv2wNpoXVR6wf5aLzY627un7p/aW/08cpyljXN9RR1DnMr7/DeytMv7vRAvUv1qH3M7Yd2seh4wUv5AHbRR5QD7HtNIehtoOyQ9pLjaAqe73/Ud5YBnmCuaX1wtKA7en0on7iPdaPdgvzIc96/6NMUL+Qvivrrjf3oS4LfYzqdgvHBtZ1Q/0/xCehYwbLIx9Il24HMH1joFilXx+3HxdlmsfD3xHp1W2eThvSpdOBY1DXO8wbmb4eXq96IQ1YDvNi/VgXtqvrK96jjuv6ifmQb91uTCqoq9ahj2/8i/LAdpC2bYE96cBn7C9Nt8tYZujqAWr72D+6fcP3us1HO4SywL5GuvAZ+3dzoFD2J4dhxPyi1PR7WbFqb3BMnFP3J3V8oO4Cjil9TOi4CMeUptsvNe/uNhXz4fjQy+AYQXuC73Bs6vVge7pNwEsfk5gP/2KaNR1oZ7EszpFn1NkgD2zrIm1cThULoK3AutEWaKqdU/GUT32HbVrjKWwbMVPa7vnw/dKy0PZwrGM60oR/kSac7/T6AOc2/Z0+d+q069hEt0ugz9/Wtkifb3S8p+LCYIlKL86haLvw/Yi/+qq06tgN6792Qy9VJkt86Wra+NbfqrLQsG4diyz01VHnOBX/7T4X6nLAOvT5AOdR637V5zss08zlVmWqY17kVccf+nyo84r1qf3uTFdtNvYVznmIRXQs2MhVqNpTzIM8YjuIW0DnSZ+vdbut0xyKD4Oyqgwxod/cJ5hPr1/XU6wD+/NQ73a1z63nSkBMiX2F9WGbzV17yg/7F2nCvLNLc9T5D+28PneCjpN0HLbOX0ctp+NGbA9xH5ZDjNTYVWSWsxX2w41rhprpRVliv2Odep8hprXG7zq/R6blqdgL5bA+EPr7RscgoM95+rjUIs+9v5btuW9IHReWGB/f4zPqOd538zjN+ok049jTx7f+28OMPcRpxpSv5DUxy16n31qO2A/6s24HdH1SbYszVDdAxZsOh5kmvJAmnU/9d52uJ+kOv2ozsB2kGdNUvLy7rHRcjTTg+MN32GfWYwp1CNPWB0Lb0GnB+lCPsK8xj27fQJfHt8UtzM+huNit4nxAvI7YWcdAer1Iq6771r/v8C/qOOZFfcE6dVken16k2kl9nKLs8d3OQKgeIV1o67DsMn8o9sT3aEcRM+pt419sQ5eRPkZ0Gia1n2625XihDuh4S2//uV0tQnUnWKL+xd/TpbvLSstyhmL7/YUxUu1KigtMRERERERERERUe3iLHBERkZ1wDCYiIiKi+MVJ7OUdN7zAREREZCeImWJ5IhzvkCMiIqJkF0ucxBgpbniBiYiIyEZiHU+JYzARERFRsoslTmKMFD+8wERERGS7p6PE8FMbf50jIiKiZBdLnMQYKW54gYmIiMhOOAYTERERUfziJI7BFDd8ihwREREREREREVULezARERHZCQaudMS4HBEREVEyiyVOYowUN7zAREREZCMc5JuIiIgofnESB/lOklvkxowZIz179pTs7Gxp3LixDB48WJYtW1abSSIiIrLH2AKxvIiIiIiSGWOk1L3A9PXXX8s111wjP/zwg3z55ZdSVlYmJ554ohQWFtZmsoiIiBIXLzARERERxTdOIvvfIjd16tSwzxMmTFA9mebPny9HH310raWLiIgoYfEpckRERETxi5N4gSk5nyK3a9cu9W9ubm5tJ4WIiIiIiIiIiOw2yHcwGJQbb7xR+vXrJwcffHDUeUpLS9VLy8vL248pJCIiSgB8ihxVgHESERGlPD5FrlYlTA8mjMW0aNEieeedd/Y6KHjdunXNV6tWrfZrGomIiBLl6SixvCi5MU4iIqJUxxipdiXEBaZrr71WPvnkE5k5c6a0bNmywvnuuOMOdRudfq1bt26/ppOIiKjWcZBvqgDjJCIiSnkc5LtWOQyj9n7SxKavu+46mTx5ssyaNUs6duxYpeVxixx6Mk1a2EXOahyQHcEiqe/MVP96xCl/BoLS1ZMpi8uKxCtB8e2+noZpZYZf/vCXSEdPlpp/iS9d+qU7ZUVZgeQZXmnh8onPMKS1O1vNuzFQLF6HQxo406XA8EmWwyu3buottzX+Wk3D981cGWba/g6WSFNXlpkm2BQoUNNgarFXDvVuNz8jjbAzEEoHvj8+vUitx7pN/a/H4VbLYP4ycUl7d+h2wdX+HOmfbqht5QdF1geypV9amcwp9ajpSI9eHnlF/p/b1UIGZy2Tb4tbqHUcmrZeTddpauAMyt9Bp3Rye1WZNXO5ZZnfKfnBNOnuLVT5m+/zSQ+vV2aVOMQjAZUHlBvSDyjLbKdLNgREtgbqqGlIz5ySoBzgKTLLASYV1JUBmRvNdCLNoPdpieFW20L6G7pC+7TUCO4ud6fav2v9+bunO9Q8WNfjO7rIeTm/qDJ6b3tPuarRLFUv2rrTZV6pU3qlBaXU8EuB4TfTg3JcVZYp9Vwl0twlkh8MqDoB2D7MK2ktw7K3m/M2dhWpupbtCKg6odeNvMDHRZnSM22LSivygrqW5nCqsoE2LqcqX+QRUI7Y76v9bmnv9qu8Li3LVmV/24YBckXjWWo6lkcadX3TkC5sC+v9yZehyl2Xna73ug6i7LBPMA3LZTnckuVMV9NuWTZUXj3oVVWnsG2UxTp/HWnlLgwrk3d3HSG3NVgkEwsay6A6f8kjW/vIjQ3nqHqM+rDAlysnZ/hUnWnkDN3yimMLZQBIE8pwSyBT8o10dRyo/R9RfthHeN/es02lWx9ryAfKAeWEeVAXkD7dDqQ5DFUv9LGP+XCs6Hqij129HsB01H3AfNsCQbU8WNsblDHKS5eFXifqVZkE5bPClqquYJ/q/Oh9hPxbt4N0oq6irFEmB3lD0zXMq8sFaVjoq6OOdZ1+bGO53yfr/PWkd9pOVX9Qp6zzYluo/1gH9kdnd1ClX7cfyKNut5CfbCeOgd3tr+GVbh5nuTZJ10FrntA+6rYUxwOOJ9R9tCFIB+j2WMO8M0oyJd1RJkd4iyXN4Vb5wb6OrN847vTxi3LGPp1S0FmurLteCoIl8uzOg+W23JWqfUJ5Yn/p41znT+8TzG8tAxzLaAPB2i6gvUQ7hW15Cr3SuPOf6oePnJwcqSn6nDfggBvF7Uqr8vL+QKlMXzW2xtNJiUPXmR3L20tOtss8n6D9Rrurj2fdHqJt059xLOB40m0Yjgs9DfMhFsBxtD4QaotKgm51HGL9OMZ0W4j1Yns4H+p2T8civ5aFtpfj8Kn2Beecl3d1kRvq/xGWD7RPOFeCPldgG9uDZWq9OtbAdzoO1OdE3VaijbG2yUifPm/oeAjnC8QqOv36M0wvaia90/9S573uXp/ato5rsB38q9snpDfd4TfjEb3OhT6vasuxTewLpANtG9pInJfQ7ut5rbEIYP6pxTmyvqy+HJK2zjx36/2m04/9qs9hiNuwzGmZRWHxLaDd1Od6/RnxGM7VaKcB3+v1W8+ROI/jvILPaJd1nIh/sQ/QLuq4BjEfYlScz7Kdpeq8vzWYptp/a7wKuk4h/ahrumzyDZeKdxEboIxwPkEZ69hHx/VIiz4P63LH9zjfYF5rDKfLTscKKB/EN9FiZZwnUa+x33SMhDgdsYw+B+k6AcgfjgeUJ46P2YWd5JycRWbdtcYQet9iWzoexz4A/TeANR2YpmNdbBvxIM6jSB8gjyjrFq58cxuYT/8tgTygbNV2d58vkS4sh/KK/FtD/72E41OX09KyxnJs+na1r7Dv8B3ShBhLx5b42wRlqfOnz/E6r/qYs6ZNH9dYr843yhv7XW9fz2/9+wB0PvT+1PUa03RcifM5yg353xjwq7Qi39hfui7p+qP3s459QmUrZsyE+pXr9Kh59d9jOk7TbZA1bdZjWZcJ6PZS7w8s+2Z+rhya/pc6frEtHU9hPsyD/KCtRX1HmSN9iEmGZoXGMtZ/Sx2Vsd6sK/pvK+vfCsibLhNrDITjzhqj6mNNt1u6XoD++1LHUjqGQvkh1tNx90/b68nQ7ksTOk5ijJQkYzDhtri33npLPvzwQ8nOzpZNmzap6agYGRl7LtYQERHRbnyKHBEREVF0fIpc6t4iN27cOHUls3///tKsWTPz9e6779ZmsoiIiIiIiIiIyC49mGrx7jwiIiKbMkK/zsWyHBEREVFSiyVOYoyUFBeYiIiIqIp4ixwRERFR/OIkdnyJG15gIiIispOgEdsvbWo5IiIioiQWS5zEGClueIGJiIjITvDUzN1PzqzyckRERETJLJY4iTFS3PACExERkZ3wFjkiIiKi+MVJvEUubniBiYiIyE54ixwRERFR/OIk3iIXN874rYqIiIiIiIiIiFIRezARERHZCW+RIyIiIopfnMRb5OKGF5iIiIjsRPX8juGJcHyIHBERESW7WOIkxkhxwwtMREREdsIeTERERETxi5PYgylueIGJiIjIToJ49G4wxuWIiIiIklgscRJjpLjhBSYiIiI7YQ8mIiIiovjFSezBFDd8ihwREREREREREVULezARERHZCXswEREREcUvTmIPprhxGIZ9SzMvL0/q1q0ra5Y2k/xMpzR3icwtrSe903ZKfjAg6/x1ZIO/vhyVsV6aurJkRVmBWm6VP1fNsyEgsjVQRxq5CqWT2yt/B0vU92kOp8wuaSg907aIzzDE63DI0rJsaeHKly2BTKnnKlHLdfHky/qAV3IcPskzvFISdEuZuKTE8Ei2o0Rt+9C09WoZaOUulIW+JtLFs0WynSKryjKlsatI0hyG5BsuNQ/SMbU4R82D5dKdfjUd27Ausz6QLdnOUrXNAzxF8nfQKV4Jqnle3XWonJr9q/rczOWWjQG/mo58oVyWlDVQ6zzAvV18EloO/zZwhu5VzQ9KWD7bu/NUGWD5UiOovgc9z+Rdh8s5dX8yP+8MpEu+ka7KQEMakXY4yFui1oOyRb71fjvUu10W+HLD0vXy9n5yYe73ap7PClvKoel/qTShjA/y/K2Wx/awfqQL+2G1r5E0d+9Q28L+QPqRZ6QHn1FuPbxe2REsUnVgdVlDVd4oU0B9wDa2+nNkQOZGlVYN9QDWl9WXXulrzbq0xBdKQ5bDLX8GgrLOX0/SHWXSL63MrFffFreQg9I2qny1dafLvFKnKifMd4S3WMokKFmOUD3UZYU6szWYpvKEuqTrGcoZsh0B+ba4jbTw7DDrA75Dnk7LLJK1/nxp7Q6leVOgQB0HmFZqOMw8oW4gbThO9L/IB+rNgtJQmlE3sOwreU3k0pzN6ljS+7urJ9MsS7yH+T6ftHD51PsGznQpMHyyLRA0t4f93MhVIJ3dQSkw/Grfoa7iPerZar9b7SOkFVD/UCY4HjAd28dxg7xhntV+HDP55vGK4wH7EOWPbWP/oN6hfJf7fVJiuFVZ4Viy1mVAfdLbQZnpfY56lOv0SJYzXWaVhMpPH+tYT0OXU5UBltfrauNyykKf1/yM43tOqcdcDvAdyhdtSbrDr5YHrBP1ZEphA2nv3araAJ1WfQyh3LCPUDdQHqgrmA/Hj26jZhS1VnVVl9eckqA6DlDPUX+wDLaLNKCMUY8B+xvzIn1LSpupbWg4VnAMbPPnSJqzTBq4ClS9mVLQWXpmrJH8YJrKI47lGUWd5ajMFWodjdx5srS0uZpng7+eZDuLJT+Yof5F+4q8YD26DdLl8NqOf8jIhvPMNhvHps4z2vleaUH5w18iN64ZKic2+l0GZC0x2wXUCeT79s3d5eoGs1VbgLYG+xXH3ezSHLUvcCy2cu9U6/dIQNUB1GHMh7z87c+SBu4Cc57u3kKVHhzPv+2oK0O7L5Vdu3ZJTk6O1PQ5b0DuJeJ2equ8vD/ok+nbx9d4Oilx6Drz0+ImkpXtVO0v6jSOfxwjOL5wrPVLd8ristCxr6ejHdGfcTzguO6fbqj2HrEEzr/6eNHneH3coI0HnKfRPmN7aGNwPsCxquMZtC86dsFxj2Masp0udc7A9B9LG6t4DPQyaE9wbkIbps9neh04L+M4RXs7oyTTTAPacPyLPOAcgvMp2kvMj7YK28a69HRVfpZzro6VAO/R5nvEKduDZaodQhmgHUc5Ib84z+B9KG2lYW24bm/0PJhfrx/lrWOVRs5S1WZhXmuspuMnLA/t3X4zVtH7F2WDeb4t6ijHZy6Tjp5QHIz2G+2tPhdj3Vgnzr0LfXVkta+xDMhcKc1cGep8Obe4nQyqs8qcV+9z5AFlizLTMRvWresDzsP6HIPzKeB8resN9ge28WtZUJ2DAOmwxrPY37qs9DSkE+o7M9U5CrA9TEeceFTGn2b9AV2m+jyM9QDKA+d41BmkG+eVoVm7VP1GrIAYDfW5m8cpHofbjAdQfz4uylQxFo4ZxD2IebAPkKZJBXVVDKrjN+QN82A6zm+oz83dO80Y6d28g+WIjNXqPdL4SX43GVHvVxUHYR6kD3UN+UFeEA8jpgGUzckZPlUOOp7R+dXHIo457EdAfUE6EXPrGHVjoFjVX2wbxwzm1WVkPRZ0jKPrCtoA7HuUHWINlA3+1X+n6DSjvuuywLoQ12Cfo25ju4hndOykYxMdv+H4xflZx/jfFh+g6iKgPuJcrvK8+3hAfcO+1+vTdQNlgNgL9R55wrb1fPq40nlGunEc6DZLrx/z6xgdabHWK10m2C/4jHJGjJPrLFBlgXqL/axjkz/KGkqp4VHHGcpAx3ujtvRQcQrKFZ91vIj2yRpz6xhb/81hbbPRNuYH081jGO0t8qzrMY5B7IulpU2lrWebWefquopVO6G3g/LA++3BLPl4+6FyS5MvZGlZY+nu3azibNRj5A91sMxwq7+j5pW0Vn+nLShpKcOyt6vjA3UKx1LjkgLpcuDmhI6TGCPFD3swERER2YhhBNUrluWIiIiIklkscRJjpPjhBSYiIiI7QcfjYAydj+3bYZmIiIio5uIkxkhxwwtMREREdqKCIF5gIiIiIopLnMQLTHHDp8gREREREREREVG1sAcTERGRnQSDIo4YxlPiGExERESU7GKJkxgjxQ0vMBEREdkJb5EjIiIiil+cxFvk4oYXmIiIiGzECAbFiKEHE5+QQkRERMkuljiJMVL88AITERGRnbAHExEREVH84iT2YIobXmAiIiKyEzx618GnyBERERHFJU7iBabkeIrcN998I6eddpo0b95cHA6HTJkypTaTQ0REREREREREdrvAVFhYKN27d5dnn322NpNBRERkH/iVDU87qfIrhl5PREREREkfJzFGSooLTAMHDpQHHnhAzjzzzNpMBhERkW0YQSPmV1XhB6C2bdtKenq69O7dW+bNm1cjeSIiIiKKh/0VIwHjpAS7wERERERVFFPvpd2vKnj33Xdl5MiRMnr0aPn5559Vj+OTTjpJtmzZwl1GREREiWk/xEjAOCkJLjCVlpZKXl5e2IuIiCiV7K8eTI8//rhcfvnlcskll8hBBx0kzz33nGRmZsorr7xSY3mj6mGcREREqW5/9WBinJQEF5jGjBkjdevWNV+tWrWq7SQRERElXQ8mn88n8+fPlwEDBpjTnE6n+vz999/XUMaouhgnERFRytsPPZgYJ1XMLTZyxx13qO762q5du6R169aSXxCUgoBIvkukqDQg+b6g5AeDUugPSpE/IPn+oGS6AlJQFqo4apovtExhICAZrqDkuUPLgM8hUlQSmsdnGOJ1OKSwLCAFrqAUBoLiVv8GJN+DdQTF6QhKgRGU0mBQyvALouFU07CdAl9oGch3B6XIF5ACT1Bd2issC6p1+hyGFBgONQ/SUVQcmgfL+Z2hZbE+6zLYvsMZ2qZKR1DEK6F5SgrKpECC6nOeK5RGTEe+kMeisoBaZ4E7KD4JLaf+3b0trCssn+6gKgMsX2qEtgV6HrU9p7VsglJkBEJp3g1pRNrVe29QrQdli3yb+827u3ws6SrFuj1BNU9xkV/tQ6QJZazybTjU9nQZYD9gHYXu0LbKdLmXhdKDzyi3PG9AlQXqAL4LlXeoXFAf8F7Vk0AorRrqART7Q2nRdakQdc4TlCDqAvLvD0jAEZC83XVR1TvsV9/u/eIOSmGpqHJS83mD4pfQ8qru6rJyI1+7y8W3p56hnBVHUIpL/FLo3lMf8B3ylId958e2QmlGXnAcYJpvd30LVa5Q2jBd/2vmo3R3mp2hZYsL/JLnCB1Len/nefaUJd6rOoR8706jB3UD9Wb3caC2h/zsPu7Ud0FRdRXvUc8K/Lv3kT+0TOgYDB0PmI7t47hB3jBPIfaDZ8/xGqrDofLHOtX+8e7Olz8oJbvLEWmw1mX9Xm8HZab3OfaF2xmUoDMghSWh8tPHOtaT5pLdbcqedeW5RG3b/Kz2e6j+6uMD36F8UT5+x572QpdPUWFACryhdkanTx9DyKfeR6odCYbmw/Gj26jiYn9YeRWWGOo4QD1H/cEy2C7SgDLGMoD9jXlVfdq9DfM4CATUMVDi90vQ6ZciZ2g/FBf6VfkWBkN5xLGstr+7LqGeFvtC8+AYcToDUhQM/Yv8qnbAH8qXtRzQDuSn7WmzdduKPKGdx37GOv2FpVKS4VfHiW4XUCeQb7UOtDFlobYG+xXHHbap2msj1PZg/R4J1QHUYcyHvBQH/FLk2jMP1oH04Hguwhs1puT+GSDSjz1oxLgc6mFE79+0tDT1stq2bZsEAgFp0qRJ2HR8Xrp0aSzJplqMkwr0iVvFEaG4B8eIjmvyygwzRtLT0Y7ozzgecFxjPrT3qs1X59/Q8aLP8fq4QRsParo/tD20MTgf4FjV8Yxq/3bHLkgijulQOh1m7KLjOpWW3cuYbZLDcj7bvQ7VPrh3t5+I5XanAW04/tV5RTthxmqIOxyGWpeeDtZzro6VAO/R5iOI1vGmjglRTsgvzjN4Dzg/W9tw3d7oeTIs68f3OlZJd4baLMxrjdV0/ITlVTm798Qqev+q9t1wmG0wzs86hlLnPn0uxrqxTgfOVwEpLvOrc18dxI9o10v8odhx97x6nyMPoTbWYcZs1vqgqtzucwzOpyqd/j31BmlW20C92V026lxoiWexv3VZ6WlIJ7jUuThUX1Q6HKE4UcUNuv4gpo84x6v1oB1E7IK6vjteQD3IQ56CoVgBMZqKBTwiHseeeAD1p6goFGMh7apcEWO4gypNOB8gBtXxG/KGeTBdxVmou/h+d3pKCvyq/oCOqfN3l736Nyi744vQ/s/fHVcAyibPHyoHHc/o/Opj0TzmsC0jlC6kwYxRkS//7ngOafbvLuvd9V/XWx3j6LqCcsK+17EGyka3A3tiot3n4t1lgXWpbZSF6rY6bnafS3W91zE40objF8vo+qTrosq7L3QeVnnefTygvoX2/Z4YAsuqOBTljvI0QtvW85nH1e48I904DnSbpdeP+XWMrtoqS73ac/zs/rsIf4v4A5KGst99rGE/69gE8VMp/v7ZXfY63tNxCsrVGi+Gjrs9MbeOsXWsbm2zsW+LjfBjGNs167GKsYIqFkM91XXO6wq1E2ae1PEcVDGar8AnBZl74ifE2dgO8oc6WIZ2E/FmaSjexL95svv42P33TkFpMOHjpKrESMA4aS+MBIGkTJ48uUrLrFu3Ti3HF8uAdYB1gHWAdaC26wDOSTWpuLjYaNq0abXSmJWVVW7a6NGjy21r/fr16rvvvvsubPott9xi9OrVq0bzSfHDOIntYm23i3yxDFgHWAfsEidVNkYCxkkVq9UeTAUFBbJy5Urz85o1a2TBggWSm5urfnHbl+bNm8u6deskOztbHA5Lj4wEhyujuL0Pac/JyZFkwrzZD/eZPXG/JQ78RpKfn6/OSTUJT3LDeRLdsquT1sjzZbRf5ho2bCgul0s2b94cNh2fmzZtGvP2af+yY5zEts2euN/sifvNnuy23+wSJ1U2RgLGSRWr1QtMP/30kxx77LHmZ92te/jw4TJhwoR9Lo/xIFq2bCl2hQbBDo1CLJg3++E+syfut8SAcQH3BwRPeNU0r9crPXr0kBkzZsjgwYPVtGAwqD5fe+21Nb59ig87x0ls2+yJ+82euN/syU77jXFS6qjVC0z9+/ffb/diEhERUeXhRx/84HPEEUdIr169ZOzYsVJYWKieKkdERESUyhgnJcEg30RERLR/nHPOObJ161a5++67ZdOmTXLooYfK1KlTyw38TURERJRqGCdFxwtMtQD3co4ePbrCezrtjHmzH+4ze+J+o/0Bt8Pxljjan9i22RP3mz1xv9lTMu83u2GcVJ4DI31HmU5ERERERERERFQpzsrNRkREREREREREFB0vMBERERERERERUbXwAhMREREREREREVULLzDF4Nlnn5W2bdtKenq69O7dW+bNm6emb9++Xa677jrp3LmzZGRkSOvWreX666+XXbt27XOdkyZNki5duqh1HnLIIfLZZ5+FfY+hsvAkn2bNmql1DxgwQFasWLHf8haZloEDB4rD4ZApU6YkTd6+//57Oe6446ROnTqSk5MjRx99tBQXF+91nbNmzZLDDz9cDbLXoUMHmTBhQpW3W5P5wpOfLrzwQmnatKnKF9L6/vvv73OdiZCvb775Rk477TRp3rx51LoWa71J9LyVlZXJbbfdpo4V7DPMc9FFF8mGDRtsn7dIV155pZpn7NixtsgbEaV2nMQYyX4x0r62wTgp8fYbY6QQxkhkWxjkmyrvnXfeMbxer/HKK68YixcvNi6//HKjXr16xubNm43ffvvNOOuss4yPPvrIWLlypTFjxgyjY8eOxpAhQ/a6zjlz5hgul8t49NFHjSVLlhh33XWX4fF41Pq0hx9+2Khbt64xZcoUY+HChcbpp59utGvXziguLt4vebN6/PHHjYEDB2JweGPy5MlJkbfvvvvOyMnJMcaMGWMsWrTIWLp0qfHuu+8aJSUlFa5z9erVRmZmpjFy5EiVt6efflrlderUqZXebk3n64QTTjB69uxpzJ0711i1apVx//33G06n0/j5558TOl/w2WefGf/+97+NDz74IGpdi6Xe2CFvO3fuNAYMGKDqH+rh999/b/Tq1cvo0aPHXtdph7xZ4fvu3bsbzZs3N5544glb5I2IUjdOYoxkvxipMttgnJR4+40xEmMksjdeYKoi/KF3zTXXmJ8DgYD6Awkn3WgmTpyoGuGysrIK13n22Wcbp5xySti03r17G1dccYV6HwwGjaZNmxr/+c9/wv4ITUtLM95++21jf+btl19+MVq0aGFs3LixUheY7JI3pAkBa1XceuutRteuXcOmnXPOOcZJJ51U6e1W177WX6dOHeO1114LWyY3N9d48cUXEzpfkSLrWqz1xg55i2bevHlqvj///DMp8vbXX3+pdgR/qLRp02afF5gSMW9ElFpxEmMk+8VIldkG46TE3G8aYyTGSGQ/vEWuCnw+n8yfP191u9acTqf6jNurokG3b3Qldrvd5jR0Kb3nnnvMz1jWuk446aSTzHWuWbNGdeG1zlO3bl3VJbWi7dZE3oqKiuT8889X3WJxy1U0dszbli1bZO7cudK4cWPp27evNGnSRI455hiZPXt22Hr69+8vF198caXzFkt9iWe+APl599131W0JwWBQ3nnnHSkpKVF5SdR8VUZl640d81ZRO4JbyerVq2f7vKEe4rbNW265Rbp27Rp1HrvmjSjVJWucxBjJfjFSZbfBOCnx9ltVMUay3z6j5MYLTFWwbds2CQQC6uRqhc8IbKLNf//998uIESPCph9wwAHSsGFD8zOW3ds69b+V3W5N5e2mm25SJ+IzzjijwvXYMW+rV69WnxHMXn755TJ16lR17/nxxx8fNn4DxorA2A77ylteXp4al6Cq9SXe+YKJEyeqMX0aNGig7qW/4oorZPLkyeqe+kTNV2VUtt7YMW+RcEEQYzKdd9556o8wu+ftkUceUX9IYtyVitg1b0SpLlnjJMZI9ouRKrvfGCcl3n6rCsZI9ttnlPz2/FxEcYWD+pRTTpGDDjoo7Fc4mDFjhu1K+6OPPpKvvvpKfvnll73OZ8e8oUcF4OLLJZdcot4fdthhKi+vvPKKjBkzRk177bXXxG5GjRolO3fulOnTp6tgHQMun3322fLtt9+qQVLtmq/KsnvecHEQ+wu9xMeNG2f7vOEXtCeffFJ+/vln1SOrInbMGxGlbpzEGMm+7TbjJHvuN2CMRJSY2IOpCvAHusvlks2bN4dNx2frLWP5+fly8sknS3Z2tuot4vF49rpeLLu3dep/97XdmswbLi6tWrVK3aKD3ge6K/uQIUPCbreyY970LzcIcq0OPPBAWbt2bZXzhl4meIJNZetLTeUL++uZZ55RF8nwS2P37t1l9OjRcsQRR6jbHBM1X5URa72xQ94iA6c///xTvvzyy7DeS3bNGy5s4pZU/NKt2xHk7+abb1a3xNg5b0SUvHESYyT7xUiV2W+MkxJzv1UGYyT77TNKHbzAVAVer1d69OgR9ssaer/gc58+fcxf5E488UQ1L37RwuM79wXLRv5ahz8o9TrbtWunGgDrPNgOxg3S89R03m6//Xb59ddfZcGCBeYLnnjiCRk/fryt84Y/bPFI9WXLloUtt3z5cmnTpk3MeatMfanJfGHMLH2ftRVOMrrXViLmqzJirTd2yJs1cMLtB+h9hlsc98UOecPYS5HtCI49jMc0bdo0W+eNiJI3TmKMZL8YqTLbYJyUmPttXxgj2W+fUYqp7VHG7QaP5sRTSSZMmKAe3zlixAj1aM5NmzYZu3btUk81OeSQQ9Tjd/GkNf3y+/3mOo477jj12E/r43fdbrfx2GOPGb///rsxevToqI/fxXY+/PBD49dffzXOOOOMuD5+d195q+yTHeyaNzzFKicnx5g0aZKxYsUK9US59PR0tR+1Cy+80Lj99tvLPcr1lltuUXl79tlnoz7KtSplGs98+Xw+o0OHDsZRRx1lzJ07V+UF+8HhcBiffvppQucL8vPz1VML8UJde/zxx9V7/SS1ytQbO+YN+w2P127ZsqWxYMGCsHaktLTU1nmLJtpT5BI1b0SUunESYyT7xUj72gbjpMTcb4yR9mCMRHbEC0wxQNDTunVr9VhdPKrzhx9+UNNnzpyp/qCK9lqzZk1YY4HgKPIxvZ06dVLrxONBrRcA9CN4R40aZTRp0kQ16scff7yxbNmy/Za3yl5gsnPe8HhV/FGPE2ufPn2Mb7/9Nuz7Y445xhg+fHjYNOzzQw89VK2zffv2xvjx46u83ZrM1/Lly42zzjrLaNy4scpXt27djNdee80W+aroeNJprUy9sWPe0FZU1I5gOTvnrbLBU6LmjYhSO05ijGS/GGlf22CclHj7jTHSHoyRyI4c+F9t96IiIiIiIiIiIiL74hhMRERERERERERULbzARERERERERERE1cILTEREREREREREVC28wERERERERERERNXCC0xERERERERERFQtvMBERERERERERETVwgtMRERERERERERULbzARESUAsaMGSM9e/aU7Oxsady4sQwePFiWLVsWNk9JSYlcc8010qBBA8nKypIhQ4bI5s2bze8XLlwo5513nrRq1UoyMjLkwAMPlCeffLLctmbNmiWHH364pKWlSYcOHWTChAmVTucVV1whLpdLJk2aJPvTgw8+KH379pXMzEypV69e1HkcDke51zvvvLNf00lERETxxzhp7xgnUWXxAhPtFxdffLH6g3Z/wx+2+g/BG2+8UewMeanoD9/qatu2rYwdO7ZG1k2J4euvv1YXj3744Qf58ssvpaysTE488UQpLCw057npppvk448/Vhd3MP+GDRvkrLPOMr+fP3++ujj1xhtvyOLFi+Xf//633HHHHfLMM8+Y86xZs0ZOOeUUOfbYY2XBggXquPvnP/8p06ZN22cai4qK1AWbW2+9VV555RXZn3w+nwwdOlSuuuqqvc43fvx42bhxo/mqjXaNiJIP46TqY5xE1cE4ae8YJ1GlGUTVhGq0t9fo0aONnTt3Gjt27NjvZT1+/HgjJyfH2Lhxo5GXl2fYGfJSt27dGln3li1bjMLCQqM2ff3118app55qNGvWTNWbyZMnl5tn06ZNxvDhw9U8GRkZxkknnWQsX77c/H7NmjUV1sOJEyea8/3555/GoEGD1DoaNWpk/Otf/zLKysr2mUaso3PnzkZaWppx8MEHG59++mnY9++//75xwgknGLm5uWqbv/zyS6Xy/vfffxvnn3++kZ2drfbxpZdeauTn55vfFxcXq3xjmy6XyzjjjDOMeOxzpBHlDjhGPR6PMWnSJHOe33//Xc3z/fffV7ieq6++2jj22GPNz7feeqvRtWvXsHnOOeccta/2ZcKECcY//vEPlZbMzExj7dq1Yd8fc8wxxg033BA2DWWBstE2bNig9m16errRtm1b48033zTatGljPPHEE0Z1j7OK6iUR0d4wTto/GCcxTmKcxDiJah97MFG1WX/NRy+YnJycsGn/+te/pG7dujXW+2Zf0HupadOm6tYgiq5Ro0bq1qDahJ403bt3l2effTbq94jR0Vtk9erV8uGHH8ovv/wibdq0kQEDBpi9cHDrlrXu4XXvvfeq270GDhyo5gkEAqqHDX6J+e677+TVV19Vv3refffde00f5sXtYZdddpnaNtKC16JFi8LycOSRR8ojjzxSpbwPGzZM9QhCz6JPPvlEvvnmGxkxYoT5PdKMW9Kuv/56ld942LVrl/o3NzfX7J2EXk3W9Xfp0kVat24t33///V7Xo9cBmDcyjSeddNJe16G9/PLLcsEFF6j2AvurKrfWaRdddJHqeYXb9N5//3154YUXZMuWLRIv6AXWsGFD6dWrl+plFfrbkYioYoyT7I9xEuMkxkmVwziJ2IOJ9suvR+hhYO11gZ4I1157reqNUK9ePaNx48bGCy+8YBQUFBgXX3yxkZWVZRxwwAHGZ599Frae3377zTj55JONOnXqqGUuuOACY+vWrVVOz7PPPmt06NBB9UTBeoYMGWJ+FwgEjIceekj1fkAviG7duoX16oBFixYZp5xyiupxgrQeeeSRxsqVK83l7733XqNFixaG1+s1unfvbnz++efletmgt0v//v1VLxps47vvviuX9latWqnvBw8ebDz22GNheVmwYIFaHttHOg4//HDjxx9/jFoOwWBQ9STD+pAm9AC67rrrzO8je3ggfS+++KLaLraPsvrwww8rXQaA5bt06aLKGL1+UOaVFa2nyLJly9R0bFdDWaMHErZVkUMPPVT1CNJQp5xOp+oNpY0bN071dCstLa1wPWeffbbKr1Xv3r2NK664oty8eh9XpgfTkiVL1LzWfYf64nA4jPXr1+/zWIoFyg156devnzkNPX1QNyL17NlT9UqKZs6cOYbb7TamTZtmTuvYsaM6fqzQ0wt5LCoqqjBN6ImGHlT6eMb+b9eunaq7le3BpHtcWctyxYoValo8ejDdd999xuzZs42ff/7ZePjhh1XdfvLJJyu1XiKivbUxjJMYJzFOio5xUgjjJLIL9mCiWoOeI+gJMG/ePLnuuuvU2CcYAwUD7f78889qfJgLL7xQjcsCO3fulOOOO04OO+ww+emnn2Tq1KlqAOKzzz67StvFsugJct9996lBjrGeo48+OmyQv9dee02ee+451asE49KgVwXuzYb169er+TGA8VdffaV+0bj00kvF7/er7zHo8X//+1957LHH5Ndff1W9N04//XRZsWJFWDowfg16d2Gcmk6dOqneMXodc+fOVT1lrr32WvU9xrN54IEHyvV6admypfz4448qDbfffrt4PJ6oeUZPjieeeEKef/55lY4pU6bIIYccstdyQs8flC3yMGjQILW97du3V6oM3nzzTdUjCAMC/v777/LQQw/JqFGj1D6PVWlpqfo3PT3dnOZ0OlUaZs+eHXUZpAvlh7LU0JMGeW/SpIk5DfsoLy9P7e+KVKdnzt5gefTuO+KII8xp2A7yhnpQE/DrEnpeVWeAaix/xhlnyOjRo9WxWlmoG+hRpl/ffvutmo7eQChPtAmAOofeUahflYXj2e12qwHGNQwyXr9+ffPzlVdeGbb9qkAd7tevn2qDbrvtNjVW1H/+858qrYOIqLIYJzFOqgrGSfHDOIlxElVDbV/hotT9ZQ49XjS/3696JV144YXmNIybZB3/5f777zdOPPHEsPWuW7dOzYPeLZVND3oOobdKtDGZSkpK1Ngvkb2JLrvsMuO8885T7++44w7Vs8Ln80XdZvPmzY0HH3ywXC8QjFVj7d3y0ksvmd8vXrxYTUMPDMC2MI5M5Dg21ryg5xDGrKmM//73v0anTp0qTHO0Hkx33XWX+Rk9yzBN98TaVxmg99lbb70VNg37r0+fPjH3YMK2WrdubQwdOtTYvn276m2EXiSYN7JeaFdddZVx4IEHhk27/PLLy82P8aewnsgec1boXROZJ/zaiB5w1enBhLqCfRMJPbP+97//xb0H0zXXXGO0bNnSWL16ddj0GTNmqDRHjpWGMn/88cfDpqG+It933nlnufUfddRR5XoZvfLKK+qYAxx36FWkX+jVhOMfverQawtjTOkX0oOxqTSM9XT99deHrRvHie7BNGXKFNWjCj20rOrXr2/W782bN4dtvzpjeHzyyScqjWg3iIgqg3ES4yRgnMQ4yYpxEiUT9mCiWtOtWzfzPR5LjkejW3vV6B4mevwUPCJ95syZYb0PMEYMrFq1qtLbPeGEE9TYPe3bt1c9pNCjQveSWrlypXqPeazbQY8mvQ30iDnqqKOi9hZCLxiM/4JeDlb4jJ48FeW/WbNmYXnFvL179w6bv0+fPmGfR44cqZ7Ohd4uDz/88F7LAD3DiouLVZ4vv/xymTx5stnbqCLW9NWpU0eNraXTt7cywDhESAt6DVnLED2wqrKfImFbH3zwgSxfvlyN+YMxo1AfMFYPevtEQn7feuutsN5LlbF27dqwdKP3VbxUp/dMdeG6HXrEYd+jV1C7du3Cvu/Ro4cq4xkzZoT1CEJ5WOseenmhR93w4cNVD7VImNe6DsDYUnodGAsNvYr0C2NLffbZZ5Kfn6/GtkLd0q+3335b7XP0XtRjYGAsE+vYVNYxsDp37qzqNdaj4ZjesWOH+RlPwbNuvzqQRvSOQi86IqJ4Y5zEOKkqGCdVD+OkEMZJVF3uaq+BKEaRFycwGLd1Gj5DMBhU/xYUFMhpp50WdQBlfYGmMvAHLm7BwyDAX3zxhbqV65577lG3mmEb8Omnn0qLFi3CltN/ROIP4njYW14rA2k+//zzVVo///xzdasSbnk688wzy82Lwa9xsWD69Onqj/2rr75a3dqD2/4quq0u2v7R6dtbGegyfPHFF8tdJMOFxOrARRD8UY9bpzBINy44YBvW28u09957T10sxKDPVhjwHbdlWuFWS/1d8+bN1TY0PYA1vtPzWZfD9MrCbZm4LTIyPZGDUOMiCW5HrMq6K9PdGxfcMEA6joFNmzap6RhQG/sT/+JiHC5cIs+4oIhbV3Fh6B//+IeaFxdzcJsqbmXDfHod2K/YF/oi2jPPPKNuH8Ntk7iYNXHiRFVP9za4NwZexyDvVgcddJC6RRUXgZF+bPv/27v/0Jq/OI7jx4b5UcxM8yMzm6Su38qMwlAS8jM//hAihD9m8qOE/UdIspb5Q7R/bBalReR3Yoz5HZaM+QOJJv6YLDvfXqc+t3tnd7tsvnc/no+67HPP557P55x7b529d877ZGZmurpSUlLMwYMH/cEnUcBZAVclSD9y5Ij7DG/evNm1z/uOhaJAmvpc/ytw5X0GFIRSMLCoqMi93+oLLdPU90jBx9rvJwA0FcZJjJP+FOOkv8c4iXESmkikp1Ch7U79rr2Mpq6txAOXSmk5jpJFh7OdfEP3E0jLv7SsRkvntHxHiXvz8vJCnp+VlfVXS+S0NCnU8iktS9Jz165dC7lEbsmSJfW2ReWzZ8+24Xj58qW7XmlpacglcrWXqOna6s9w+0AJkf9WuNvBK+GhEnYHJpkO/IwFJm+vneRbS6U8R48edUu46lvqpCTfs2bNCnpOS/6aKsn3/fv3/c+pPU2d5DvUNtneeypVVVVuKaeWlGmp6Lx589xSVY8SxddVhz4/gfQ5VnJ1JQ1PTk4OukZtSrau79+pU6dCLnMcNWqU+1mfNx3HxcW5JXp79uwJSvIt79+/tzNmzHDfY92XljXq3Nzc3Hr7R3XU1TbvO6nloWqTEtprOa+S96vO2svxAKA+jJMYJwnjJMZJjJPQWhFgQosZOOmXbeWlWbhwoS0pKXE7ll24cMHtOqccLuHeT1FRkdv5Sb/8v3371uW5UcDB251sx44dtmfPni6/ka6hIMzhw4f9+Y4+f/7syufPn+92q1KQQwEpBW1EbVCwIj8/3z23bds2l79H54UbYFLeKd3T/v373euys7PdbnteW5S3RgErna82aGcrrecPtduX+kE5n7QL3+vXr11+Je0Op7b8TYCpoT7Qrm6qX/2s/FhPnjxx68uVCyqU79+/uz7RQ9dX3h/9XFFR4T9HQQi1WW1Qvh3dt+6hNuXWUYAmcPc+jz4rQ4cOdXmYtBOfPkP6XCmvVH28HdO0m59yZSnYovdVfer58uWLu2dv1zR9BnQcGKSpi3ZGVBDl7t277r3UTmxezq/AvEeqS0FE7R7o9RXq5+Vpu3z5Ml0FIOIYJzFOEsZJjJOaC8ZJaGoEmNBiBk6iQIZmVSjYogDGkCFDbEZGRtBW5g3dz82bN931NUtDdQwfPtwWFBT4y1XXoUOH3GwpBRAUfJg+fbq9ceOG/5zHjx+7AIVmeSjZthIbK+ghmtGgGT79+vVzr9dMh8BARzgBJjl27JhLxqx7VFBBgQ2vLUpwrRlL/fv3d7NE9JewjRs3uhkodVEfpqamusCXZl+MGzcu6BfuPw0wNdQH3rb33l9n1NcTJ060Z86csaGo7XXNIAmcnaKAlfpE/ark0wqUqS9qU7BIfRNqdomCcprlor6Nj4+3mzdvDmtmnAJcSsitNvl8PhdICqT+qasNCkbVR4EpBZQ0O0bv0cqVK13ALZDeo7rqhv0tWfnZs2ddEnMFBSdMmGCTkpJCzrYDgP8T4yTGSR7GSYyTIoFxEv61dvqnqZbbAc3NiRMnTEZGRlCeFgCt18WLF13epfLycpdravz48ebQoUMusT8AIBjjJKBtYZyEf40k32j1lBBaSXqVvK+uBOEAWg8lINcDABAexklA28E4Cf8aM5jQqmnrc2/nr9jYWBMfHx/pWwIAAGgWGCcBAJoSASYAAAAAAAA0SlTjXg4AAAAAAIC2jgATgIhISkoy7dq1cw+SsAMAADBOAtCyEWACmomcnBwXdOnUqZNJTU01JSUl/rIfP364JOU9e/Z0CcsXLFjgzy1Vn8LCQjNkyBBX57Bhw8z58+eDyrWJ5K5du0yfPn1M586dzbRp08yrV68arPf69etm9OjRJiYmxgwaNMjtQvMn7ZF79+6Z06dPN3gtAAAAxkkA0PwRYAKagYKCApOZmWl2795tHjx4YEaMGOF2efj06ZMr37RpkykqKnIBoxs3bpj379+b+fPn11vn7du3zdKlS82qVavMw4cPzdy5c93j2bNn/nP27dtnDh8+bHJzc83du3dN165d3XUV0ArlzZs3ZubMmSY9Pd08evTIZGRkmNWrV7ttT8Ntj/Tq1cvExcU1sucAAEBrxzgJAFoICyDixo4dazds2OA//vXrl+3bt6/ds2eP/fr1q+3QoYMtLCz0l7948cLq61tcXByyzkWLFtmZM2cGPZeammrXrl3rfq6pqbG9e/e2+/fv95frWjExMfbkyZMh6926dav1+XxBzy1evNhOnz49rPYEunbtmmtHZWVlyOsBAIC2jXES4yQALQMzmIAI+/nzpyktLXXL0zxRUVHuuLi42JVVV1cHlWvZW2Jioiv3aDlaVlaW/1hlga8RzSLyXqOZSB8/fgw6p3v37m45W2C9kydPNitWrAi73obaAwAAwDiJcRKA1ocAExBhnz9/Nr9+/TIJCQlBz+tYASA9OnbsaGJjY+ss96SkpJj4+Hj/scpC1emVe8/VV68CWcrR1FC93759M1VVVQ22BwAAIFyMkwCg5Wgf6RsA0DSuXLnyT7oyLy/vn9QLAADwf2GcBAD/HjOYgAjTrKPo6OjfdoXTce/evd1Dy86+fv1aZ3koKgtVp1fuPdcU9Xbr1s3tRNdQewAAAMLFOAkAWg4CTECEafnbmDFjgv6yVlNT447T0tJcWYcOHYLKy8rKzLt371x5KCqr/de6S5cu+V8zcOBAF/AJPEfL3LSbXGPqbag9AAAA4WKcBAAtSKSzjAOwNj8/3+3eduLECfv8+XO7Zs0aGxsbaz9+/Oi6Z926dTYxMdFevXrV3r9/36alpblHoClTptjs7Gz/8a1bt2z79u3tgQMH3K5zu3fvdrvRPX361H/O3r173XXOnj1rnzx5YufMmWMHDhxoq6qq/OcsW7bMbt++3X9cXl5uu3TpYrds2eLqzcnJsdHR0fbChQtht8fDLnIAAKAhjJPYRQ5Ay0CACWgmFBxSEKljx45uO947d+74yxTwWb9+ve3Ro4cL7sybN89++PAh6PUDBgxwQaRAp06dsoMHD3Z1+nw+e+7cuaDympoau3PnTpuQkOACQlOnTrVlZWVB50yaNMkuX778t8DQyJEjXb3Jycn2+PHjf9SewHoU565k4AQAABgnMU4C0KK10z+RnkUFoG26fv26SU9PN5WVlb/tkgcAANCWMU4C0NKwixyAiPD5fKa8vJzeBwAAYJwEoBVgBhOAiKioqDDV1dXu5+TkZBMVxZ4DAAAAjJMAtFQEmAAAAAAAANAoTBkAAAAAAABAoxBgAgAAAAAAQKMQYAIAAAAAAECjEGACAAAAAABAoxBgAgAAAAAAQKMQYAIAAAAAAAABJgAAAAAAAEQOM5gAAAAAAADQKASYAAAAAAAAYBrjP/a6zW3fMQWeAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1200x800 with 8 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "fig, axes = plt.subplots(2, 2, figsize=(12, 8), sharex=True, sharey=True)\n",
+    "\n",
+    "for i, ax in enumerate(axes.ravel()):\n",
+    "    ds[\"corr\"].isel(beam=i).sel(range=slice(0, 10)).plot(ax=ax)\n",
+    "    ax.set_title(f\"Beam {int(ds['beam'].isel(beam=i).values)}\")\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It's beneficial to also review data from the other beams. A significant portion of this data is of high quality. To avoid discarding valuable data with lower correlations, which could be due to natural variations, we can use the `correlation_filter`. This function assigns a value of NaN (not a number) to velocity values corresponding to correlations below 50%.\n",
+    "\n",
+    "However, it's important to note that the correlation threshold is dependent on the specifics of the deployment environment and the instrument used. It's not unusual to set a threshold as low as 30%, or even to forgo the use of this function entirely."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = api.clean.correlation_filter(ds, thresh=50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Updated velocity plots filtered for beam correlation. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 21,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a3bd609d0>"
-            ]
-          },
-          "execution_count": 21,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "# Turbulence Intensity\n",
-        "ds_avg[\"TI\"] = ds_avg.velds.I\n",
-        "ds_avg[\"TI\"].plot(cmap=\"Reds\", ylim=(0, 11))"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1500x400 with 6 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    ds[\"vel\"][i].plot(ax=ax)\n",
+    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.4 Rotate Data Coordinate System\n",
+    "\n",
+    "After cleaning the data, the next step is to rotate the velocity data into accurate East, North, Up (ENU) coordinates.\n",
+    "\n",
+    "ADCPs utilize an internal compass or magnetometer to determine magnetic ENU directions. You can use the set_declination function to adjust the velocity data according to the magnetic declination specific to your geographical coordinates. This declination can be looked up online for specific coordinates.\n",
+    "\n",
+    "Instruments save vector data in the coordinate system defined in the deployment configuration file. To make this data meaningful, it must be transformed through various coordinate systems (\"beam\"<->\"inst\"<->\"earth\"<->\"principal\"). This transformation is accomplished using the `rotate2` function. If the \"earth\" (ENU) coordinate system is specified, DOLfYN will automatically rotate the dataset through the required coordinate systems to reach the \"earth\" coordinates. Setting `inplace` to true will modify the input dataset directly, meaning it will not create a new dataset.\n",
+    "\n",
+    "In this case, since the ADCP data is already in the \"earth\" coordinate system, the `rotate2` function will return the input dataset without modifications. The `set_declination` function will work no matter the coordinate system."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.2 Power Spectral Densities (Auto-Spectra)\n",
-        "\n",
-        "Other turbulence parameters include the TKE power- and cross-spectral densities (i.e the power spectra), turbulent kinetic energy (TKE, i.e. the variances of velocity vector components), Reynolds stress vector (i.e. the co-variances of velocity vector components), TKE dissipation rate, and TKE production rate. These quantities are primarily used to inform and verify hydrodynamic and coastal models, which take some or all of these quantities as input.\n",
-        "\n",
-        "The TKE production rate is the rate at which kinetic energy (KE) transitions from a useful state (able to do \"work\" in the physics sense) to turbulent; TKE is the actual amount of turbulent KE in the water; and TKE dissipation rate is the rate at which turbulent KE is lost to non-motion forms of energy (heat, sound, etc) due to viscosity. The power spectra are used to depict and quantify this energy in the frequency domain, and creating them are the first step in turbulence analysis.\n",
-        "\n",
-        "We'll start by looking at the power spectra, specifically the auto-spectra from the vertical beam (\"auto\" meaning the variance of a single vector direction, e.g. $\\overline{u'^2}$, vs \"cross\", meaning the covariance of two directions, e.g. $\\overline{u'w'}$). This can be done using the `power_spectral_density` function from the `ADPBinner` we created (\"avg_tool\"). We'll create spectra at the middle water column, at a depth of 5 m, and use a number of FFT's equal to 1/3 the bin size."
-      ]
-    },
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data is already in the earth coordinate system\n"
+     ]
+    }
+   ],
+   "source": [
+    "dolfyn.set_declination(ds, 15.8, inplace=True)  # 15.8 deg East\n",
+    "dolfyn.rotate2(ds, \"earth\", inplace=True)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To rotate into the principal frame of reference (streamwise, cross-stream, vertical), if desired, we must first calculate the depth-averaged principal flow heading and add it to the dataset attributes. Then the dataset can be rotated using the same `rotate2` function. We use `inplace=False` because we do not want to alter the input dataset here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds.attrs[\"principal_heading\"] = dolfyn.calc_principal_heading(ds[\"vel\"].mean(\"range\"))\n",
+    "ds = dolfyn.rotate2(ds, \"principal\", inplace=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Updated velocity histograms and contour plots for rotated velocity. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 22,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "rng = 5  # m\n",
-        "vel_up = ds[\"vel_b5\"].sel(range_b5=rng, method=\"nearest\")  # vertical velocity\n",
-        "U = ds_avg[\"U_mag\"].sel(\n",
-        "    range=5, method=\"nearest\"\n",
-        ")  # flow speed, for plotting in the next block\n",
-        "\n",
-        "ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n",
-        "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 2\n",
-        ")"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1200 with 4 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vel = ds[\"vel\"]\n",
+    "\n",
+    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+    "labels = vel.coords[vel_dim].values\n",
+    "\n",
+    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
+    "\n",
+    "if len(labels) == 1:\n",
+    "    axes = [axes]\n",
+    "\n",
+    "for ax_i, label in zip(axes, labels):\n",
+    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+    "    values = values[np.isfinite(values)]\n",
+    "\n",
+    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+    "    ax_i.set_ylabel(\"Count\")\n",
+    "\n",
+    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "In the auto-spectra, we're primarly looking for three components: the energy-producing region, the isotropic turbulence region (so-called \"red noise\"), and the instrument noise floor (termed \"white noise\"). \n",
-        "\n",
-        "The block below organizes and plots the power spectra by the corresponding ensemble speed, averaging them by 0.1 m/s velocity bins. Note that if an ensemble is missing data that wasn't filled in, a power spectrum will not be calculated for that ensemble timestamp."
+     "data": {
+      "image/png": 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8qXb//ffr99KnuTS063rSTOod1lWfQEQVLiKqIIVCIfr+978fzZgxI6quro5SqZT+/etf/7p7mnQ6HX3lK1+J6urqpMlWNHnyZB3/2GOP6ec//elPa1z2yy+/HB166KFRY2NjFIvFdL7DDz88euSRR7qnaWlpiY499tho1KhRUVVVVbTffvtF77zzjk57zDHHdE9300036bqef/75Xus455xzdPyyZct6jZd55bes6rDDDtPp77zzzu5xxWIxSiaTkeu6US6X6zV913pnz56tn1966aXoyCOPjCZNmqS/qampKfrc5z4XvfDCC6ut6ze/+U204447RolEQrft9OnTox/84AfRwoUL17FHiIiIyufFF1+MbNuOTj311F7jfd+PPv7xj0fjxo3TWLwmH3zwQXTcccdFm2yySRSPx6OGhoZor732iv75z3/2mk7i9u67767xTmJmV/xeW4zucvfdd0ef/OQnNV7LsOWWW0bf/OY3o5kzZ3ZP89Zbb0X77LOP5hEkr3DCCSdEr776qi5XYvRHxf099tgj2mabbVYbL/mMAw888CO3HxERUaV6+OGHNV4ahhHNnz9/te9nzZoVHX300VFzc3PkOE40fvx4Ldv++c9//shyeJef/vSnOp9pmr3KzV3zrWnoWc4nouHHkH8Gu3KeiIiIiIiIiIiIiGhjYR/jRERERERERERERDSisGKciIiIiIiIiIiIiEYUVowTERERERERERER0YjCinEiIiIiIiIiIiIiGlFYMU5EREREREREREREIworxomIiIiIiIiIiIhoRLExzIVhiIULF6K6uhqGYQx2coiIBlUURejo6MC4ceNgmuW5N5rP51EsFvs1j+u6iMfjZVk/DT+M3URE/8XYTZWAsZuI6L8YuyvHsK8Yl0rxiRMnDnYyiIiGlPnz52PChAllqRRvTFQhi6Bf8zU3N2P27NmsHKc1YuwmIlodYzcNZYzdRESrY+we+oZ9xbi0FO86GGtqagY7OUREg6q9vV1vFnZdGzeUtBSXSvGjMR5uH3vnKiLELYsX6LxsNU5rwthNRPRfjN1UCRi7iYj+i7G7cgz7ivGu7lOkUpwV40REva+N5ZIwLLhG3yrGrcgAIu4JWjvGbiKitV8by4Wxm8qJsZuIaO3XxnJh7C6/YV8xTkREA880AKuPMV+rz1kxTkRENKgYu4mIiCoLY3f5sWKciIg2mGUYOvRpWvBFyERERIONsZuIiKiyMHaXHyvGiYhog1n9aDFucXsTERENOsZuIiKiysLYXX596xCWiIiIiIiIiIiIiGiYYItxIiLaYHyki4iIqLIwdhMREVUWxu7yY8U4ERFtMD7SRUREVFkYu4mIiCoLY3f5sWKciIg2GO9cExERVRbGbiIiosrC2F1+rBgnIqINZvTjpRV9fEcnERERDSDGbiIiosrC2F1+rBgnIqINxjvXRERElYWxm4iIqLIwdpcfK8aJiGiDsa8zIiKiysLYTUREVFkYu8uPFeNERFSmAN23TlIsbm8iIqJBx9hNRERUWRi7y6+vXcIOiCeeeAIHHXQQxo0bB8MwcN9996112pNOOkmnueKKKzZqGomIqO93rvs6UOVi7CYiGh4Yu0cOxm4iouGBsXuYVYxnMhnMmDED11xzzTqnu/fee/HMM89oBToREQ3dvs76OlDlYuwmIhoeGLtHDsZuIqLhgbF7mFWM77///rjgggtwyCGHrHWaBQsW4NRTT8Vtt90Gx3E2avqIiKhvzH60FpdpqXIxdhMRDQ8DHbv700q5y+OPP44ddtgBsVgMm266KW6++eb1+3HUC2M3EdHwwHL3COtjPAxD/L//9//w/e9/H9tss02f5ikUCjp0aW9vH8AUEhGR4NuxqQtjNxFRZRjo2N3VSvm4447DoYce+pHTz549GwceeKB2oSmNoh555BF8/etfx9ixY7Hffvv1e/3Ud4zdRESVgeXuEVYxfvHFF8O2bXzrW9/q8zwXXXQRzjvvvAFNFxER9ca3Y1MXxm4iosow0LFbWinL0FfXXXcdpk6dil/+8pf6eauttsKTTz6Jyy+/nBXjA4yxm4ioMrDcPcy6UlmXF198EVdeeaU+PieP3vXVmWeeiba2tu5h/vz5A5pOIiLiS0CohLGbiKhyDLUXeD399NPYZ599eo2TluIyngYOYzcRUeUYarF7OBiyFeP//ve/sXTpUkyaNElbjcswd+5cfPe738WUKVPWOp/0R1dTU9NrICKigcWXgBBjNxHR8I/d0k1lz6FnF5YbavHixRgzZkyvcfJZ1pPL5cq2HuqN5W4iosrBcvcI6kpF+hZfU4sBGX/ssccOWrqIiGjNj1j3+XHsiFtwuGLsJiIa3rF74sSJvcafc845OPfccwcgdbSxMHYTEVUOlruHWcV4Op3G+++/3+uFK6+88goaGhq0pXhjY2Ov6R3HQXNzM7bYYotBSC0REa2N2Y8XeMm0VLkYu4mIRm7slm4qez6RK0/rlouU85YsWdJrnHyW9SUSibKtZyRi7CYiGh5Y7h5mFeMvvPAC9tprr+7Pp59+uv5/zDHHaN/iREQ0DF8CwnrxisbYTUQ0cmP3QHZVueuuu+Jvf/tbr3EPP/ywjqcNw9hNRDQ8sNw9zCrG99xzT0RR35+pnzNnzoCmh4iI1k/P/kf7Mm1/PfHEE7jkkkv0BVGLFi3Cvffei4MPPnit0z/++OO9brx2kXmlRRqtP8ZuIqLhYaBj90e1Uj7zzDOxYMEC3HLLLfr9SSedhKuvvho/+MEPcNxxx+HRRx/FXXfdhQceeKDf66beGLuJiIaHgY7dI9GQ7WOciIgqx0Dfuc5kMpgxY4YWlA899NA+zzdz5sxeLduampr6v3IiIqJhaKBj90e1Upab1fPmzev+furUqVoJftppp+HKK6/EhAkTcOONN+p7poiIiIgtxgcCK8aJiGjI37nef//9degvqQivq6vr93xERETD3UDH7o9qpbymrjNlnpdffrnf6yIiIhoJ2GK8/MwBWCYREY3Al4D0ZxDt7e29hkKhUPZ0bbfddhg7diw+85nP4D//+U/Zl09ERDSSYjcRERENHsbu8mPFOBERbTDDMvo1iIkTJ6K2trZ7uOiii8q2J6Qy/LrrrsPdd9+tg6xLWqG99NJLZVsHERHRSIvdRERENHgYu8uPXakQEdEGMy0Dptm3QnNXq7P58+f36v87FouVbU9sscUWOnTZbbfdMGvWLFx++eW49dZby7YeIiKikRS7iYiIaPAwdpcfK8aJiGjDWSYMs48PIRml/kalUrxnxfhA23nnnfHkk09utPURERENt9hNREREg4ixu+xYMU5ERBvMMPv+mLWBwWl19sorr2gXK0RERFQZsZuIiIj+i7G7/FgxTkRE5Xmkq4+Fa3M9CtfpdBrvv/9+9+fZs2drRXdDQwMmTZqEM888EwsWLMAtt9yi319xxRWYOnUqttlmG+Tzedx444149NFH8dBDD/V73URERMPRQMduIiIiKi/G7vJjxTgREW0weRS7r49jG1H/H8d+4YUXsNdee3V/Pv300/X/Y445BjfffDMWLVqEefPmdX9fLBbx3e9+VyvLk8kktt12W/zzn//stQwiIqKRbKBjNxEREZUXY3f59bFTOSIioo9uddbXob/23HNPRFG02iCV4kL+f/zxx7un/8EPfqAtzHO5HFasWIHHHnuMleJEREQbMXYTERFR5cXua665BlOmTEE8Hscuu+yC5557rk/z3XHHHTAMAwcffDAqCSvGiYhog0kfpf0ZiIiIaHAxdhMREVWWgY7dd955pz6dfc455+Cll17CjBkzsN9++2Hp0qXrnG/OnDn43ve+h0996lOoNKwYJyKiDVYKvGYfB1aMExERDTbGbiIiosoy0LH7sssuwwknnIBjjz0WW2+9Na677jrtmvR3v/vdWucJggBHHXUUzjvvPEybNg2VhhXjRES04cGEj2MTERFVFMZuIiKiyjKQsbtYLOLFF1/EPvvs89/1maZ+fvrpp9c63/nnn4+mpiYcf/zxqER8+SYRERERERERERHRMNPe3t7rcywW02FVy5cv19bfY8aM6TVePr/zzjtrXPaTTz6J3/72t3jllVdQqdhinIiINpi8ZMMw+zgY7EqFiIhosDF2ExERDf/YPXHiRNTW1nYPF110UVnS0tHRgf/3//4fbrjhBowaNQqVii3GiYhog5mWqUOfpo14T5aIiGiwMXYTEREN/9g9f/581NTUdI9fU2txIZXblmVhyZIl6Ek+Nzc3Y1WzZs3Sl24edNBB3ePCMNT/bdvGzJkzsckmm2CoY8U4ERFtsP689dqI2GKciIhosDF2ExERDf/YLZXiPSvG18Z1Xey444545JFHcPDBB3dXdMvnU045ZbXpt9xyS7z++uu9xp111lnakvzKK6/UluqVgBXjRES0wVi4JiIiqiyM3URERJVloGP36aefjmOOOQY77bQTdt55Z1xxxRXIZDI49thj9fujjz4a48eP1+5Y4vE4Pvaxj/Wav66uTv9fdfxQxopxIiLaYHwcm4iIqLIwdhMREVWWgY7dRxxxBJYtW4af/OQnWLx4Mbbbbjs8+OCD3S/knDdvHkxzeHWNyopxIiLacP24cw12pUJERDT4GLuJiIgqy0aI3aeccsoau04Rjz/++Drnvfnmm1FpWDFOREQbzDQMmKbR52mJiIhocDF2ExERVRbG7vJjxTgREW0wwzJ16NO04fB69IqIiKgSMXYTERFVFsbu8mPFOBERbTDTMnTo07QhW4wTERENNsZuIiKiysLYXX6sGCcioo37dmxWjBMREQ06xm4iIqLKwthdfqwYJyKiDcZHuoiIiCoLYzcREVFlYewuP1aMExHRBjOt0mNdfZo25AYnIiIabIzdRERElYWxu/xYMU5ERBvMMA0d+jotERERDS7GbiIiosrC2F1+JgbRE088gYMOOgjjxo2DYRi47777ur/zPA8//OEPMX36dKRSKZ3m6KOPxsKFCwczyUREtAamacK0+jiYgxp6aAMxdhMRDQ+M3SMHYzcR0fDA2F1+g1o7kclkMGPGDFxzzTWrfZfNZvHSSy/h7LPP1v/vuecezJw5E5///OcHJa1ERPTRLwHp60CVi7GbiGh4YOweORi7iYiGB8buYdaVyv7776/DmtTW1uLhhx/uNe7qq6/GzjvvjHnz5mHSpEkbKZVERFTWl4D0cToamhi7iYiGB8bukYOxm4hoeGDsHuF9jLe1tWmXK3V1dWudplAo6NClvb19I6WOiGjkMkxTh75OSyMHYzcR0dDE2E1rw9hNRDQ0MXaXX8XUTuTzee1z/Mgjj0RNTc1ap7vooou0tXnXMHHixI2aTiKikajP/Yt3DjQyMHYTEQ1djN20JozdRERDF2P3CG0xLi/iPPzwwxFFEa699tp1TnvmmWfi9NNP79VinJXjREQDrB9dqci0lW59nkZa103d4Yixm4hoiGPs/kiM3WvHcjcR0SBg7C577LYrpWA9d+5cPProox/5A2OxmA5ERLSRH+myRk5XKtKll3Tt1Vcy7bvvvotp06ZhJGDsJiIa+hi7P2L7MHavc/uw3E1EtPExdpc/dtuVULB+77338Nhjj6GxsXGwk0RERIPQ19kTTzyBSy65BC+++CIWLVqEe++9FwcffPA653n88cf1CaI333xTnxw666yz8LWvfa1s++/Pf/4zGhoaPnI6edrpgAMOwEjB2E1EVBlGYj+ljN1rxthNRFQZGLvLX+4e1IrxdDqN999/v/vz7Nmz8corr2hFw9ixY/GlL30JL730Ev76178iCAIsXrxYp5PvXdcdxJQTEdHqb8e2+rRRDCvo98bLZDKYMWMGjjvuOBx66KEfOb3EkwMPPBAnnXQSbrvtNjzyyCP4+te/rrFlv/322+CdN3nyZOy+++59vmErd6wdx8FwwNhNRDQ8DHTsHmoYu1nuJiKqdIzd5S93D2rF+AsvvIC99tqr+3NX3+DHHHMMzj33XNx///36ebvttus1n7Qe33PPPTdyaomIaN0Buo+tztajj/H9999fh7667rrrMHXqVPzyl7/Uz1tttRWefPJJXH755WWpGJeK9/544403MFwwdhMRDQ8DHbuHGsZulruJiCodY3f5y92DWjEuldvS1H1t1vUdERENHaZp6tDXadf0Asty9lX59NNPY5999uk1TirEv/Od75Rl+SMZYzcR0ciN3VSZGLuJiIYHxu7yYw6HiIjKdue6r4OQfr9ra2u7h4suuqhse0K63hozZkyvcfJZKuNzuRw2hiVLluD888/fKOsiIiLaGLF7uGPsJiKioYyxu/yxe2TkcIiIaMgF6Pnz56Otra17OPPMM4fVXpLK+fPOO2+wk0FERLRGLFyvjrGbiIiGMsbu8sfuQe1KhYiIhgfDMPUN2X2dVtTU1OgwEJqbm/XOcU/yWdaXSCTKso7XXnttnd/PnDmzLOshIiIaKrG70jF2ExFRJWPsLn+5mxXjREQ07F4Csuuuu+Jvf/tbr3EPP/ywji8XeTG0YRhrfB9G13j5n4iIaCgaarF7Y2DsJiKiSsbYXf5yNyvGiYhoyAfodDqN999/v/vz7Nmz8corr6ChoQGTJk3SblgWLFiAW265Rb8/6aSTcPXVV+MHP/gBjjvuODz66KO466678MADD6BcZN2/+MUvsPfee6/x+zfffBMHHXRQ2dZHRERUTiOxcM3YTURElYyxu/zlblaMExHRBjMtU4e+TttfL7zwAvbaa6/uz6effrr+f8wxx+Dmm2/GokWLMG/evO7vp06dqpXgp512Gq688kpMmDABN954I/bbbz+Uy4477oiFCxdi8uTJa/y+tbV1ja3JiYiIRkLsHooYu4mIqJIxdpe/3M2KcSIi2mCGafS9n1Kz/4857bnnnusMdlI5vqZ5Xn75ZQwUaZWeyWTW+r20ZL/pppsGbP1ERERDOXYPRYzdRERUyRi7y1/uZsU4ERHRejjkkEPW+X19fb22aCciIqKhgbGbiIioshwywOXu4fFMHBERDYm+zvo6DFf/+c9/UCgUBjsZREREH4mxu4Sxm4iIKgVjd/lj9/CtnSAioo2GAbpk//3315eAEhERDXUbI3Zfc801mDJlCuLxOHbZZRc899xz6+wWzTCMXoPMN9AYu4mIqFKw3F3+2M2uVIiIaIMZhtn3fkqN4XtPli/bJCKiSjHQsfvOO+/Ul2Vfd911Wil+xRVX6EuwZ86ciaampjXOU1NTo9//d70D37c5YzcREVUKlrvLH7v7VDEuGZr+Ouuss9DQ0LA+aSIiogpjWBZMy+rztDTwGLuJiGgwY/dll12GE044Accee6x+lgryBx54AL/73e9wxhlnrHk9hoHm5uYRu+MYu4mIaF1Y7i6/PlWMy939XXfdFa7r9mmhTz75JE455RRWjBMRjRD9ecx6OPcxfv3112PMmDEYChi7iYhosGJ3sVjEiy++iDPPPLN7nGma2GefffD000+vdb50Oo3JkycjDEPssMMOuPDCC7HNNttgIDF2ExFRpWC5u/yxu89dqdx7771rfeRtVdXV1RuSJiIiqjAM0CVf+cpX0N7ejvvuuw9bbLEFttpqq0HdL4zdRERUztgtMa6nWCymw6qWL1+OIAhWK7TK53feeWeN65C4Ka3Jt912W7S1teHSSy/FbrvthjfffBMTJkwYsB3J2E1ERJWC5e7yx+4+5YRuuukm1NbWVuRddyIiGnjSR2l/huHk8MMPx9VXX61/53I57LTTTjpOCvZ33333oKWLsZuIiModuydOnKjlwq7hoosuKttGlieUjz76aGy33XbYY489cM8992D06NFatiw3xm4iIqpELHdfXfZyd59qJ4455pg1tgRYV819KpVa70QREVFlGclvx37iiSfwqU99qruFtrwIpLW1Fb/61a9wwQUXDFq6GLuJiKjcsXv+/Pnamrtr6NlVSk+jRo2CZVlYsmRJr/Hyua99iDuOg+233x7vv/9+2XckYzcREVUilrs/VfZy9wbVTkgfcNJ0vedAREQjj2EafQ/SpoHhRCoGul42/eCDD+KLX/wikskkDjzwQLz33nsYahi7iYhofWN3TU1Nr2Ftjafk3VQ77rgjHnnkke5x0m+4fJaW4X0hXbG8/vrrGDt2bNl3GGM3ERFVIpa7G8pe7u53xfjs2bN1pdIiXB6fq6+v16Gurk7/JyKikWckP9Ilj5XLi8QymYwG6H333VfHt7S0IB6PYyhg7CYioo0du08//XTccMMN+P3vf4+3334bJ598ssbKY489Vr+XblN6tjg///zz8dBDD+GDDz7ASy+9hK9+9auYO3cuvv71r5d95zF2ExFRJWK5++myl7v7/PLNLpJBkebq8mIU6UfcMIZXyz8iIuo/w7R06Ou0w8l3vvMdHHXUUaiqqsLkyZOx5557dj+mPX36dAwFjN1ERLSxY/cRRxyBZcuW4Sc/+QkWL16sfYdLQbbrXVTz5s2D2aPCXQq2J5xwgk4rDa6kxflTTz2Frbfeuuw7j7GbiIgq0cYod19zzTW45JJLNB7PmDEDV111FXbeeec1Tis3wG+55Ra88cYb+lli94UXXrjW6Ydi7O53xfirr76KF198Ud/6SUREpCTo9jXwDrOK8f/93//FLrvsogX8z3zmM92F/GnTpg1qH+M9MXYTEdFgxO5TTjlFhzV5/PHHe32+/PLLddgYGLuJiKgiDXDsvvPOO/WJr+uuu07LuFdccQX2228/zJw5E01NTWuM5UceeSR22203bbV98cUXa0vuN998E+PHj0clxO5+V4x//OMf15eusGKciIi6SVDq62PWw6wrla474zL0JN2ODRWM3UREtBrGbsZuIiKqLAMcuy+77DJ9equr2zOpIH/ggQe015Azzjhjtelvu+22Xp9vvPFG3H333fpOEekyrRLK3f2uGJcfedJJJ2HBggX42Mc+pm8L72nbbbfdoAQREVHlMSxLh75OSxsXYzcREa2KsXtoY+wmIqKNGbuLxaL2ENLz/R/SKnufffbRd2r1RTabhed5aOh8SWYl6HfFuPQTN2vWrO67B0L6GZd+x+V/eXs4ERGNMCO4K5VKwNhNRESrYewe0hi7iYioHLG7vb291+hYLKbDqpYvX651ul3vAukin995550+rfKHP/whxo0bp5Xpw7Zi/LjjjsP222+PP/7xj3z5JhER9XikyxqxXakMdYzdRES0GsbuIY2xm4iIyhG7J06c2Gv0Oeecg3PPPbfsG/fnP/857rjjDu13XPobH7YV43PnzsX999+PTTfddGBSREREFccwTR36Oi1tXIzdRES0KsbuoY2xm4iIyhG75T2RNTU13ePX1FpcjBo1CpZlYcmSJehJPjc3N2NdLr30Uq0Y/+c//1lxXWz3u2L805/+NF599VVWjBMR0X8Z/XikS6YdZvL5PF577TUsXboUYRj2+u7zn/88BhtjNxERrYaxm7GbiIiGfeyWSvGeFeNr47quvthSXpx58MEH6zgp28rnU045Za3z/eIXv8DPfvYz/OMf/8BOO+2ESit397ti/KCDDsJpp52G119/HdOnT1/t5Zv9ScgTTzyBSy65RDt3X7RoEe69997ujS+k33Jp4n/DDTegtbUVn/jEJ3Dttddis80262+yiYhoII3gfkoffPBBfeO29Mm2qqHy7g3GbiIiWg1jN2N3J5a7iYgqxADH7tNPPx3HHHOMVnDvvPPOuOKKK5DJZLrfMynl3vHjx+Oiiy7SzxdffDF+8pOf4Pbbb8eUKVOwePFiHV9VVaVDJZS7+10xftJJJ+n/559//gYnRDbujBkztP+0Qw89dI13HX71q1/h97//PaZOnYqzzz4b++23H956662K6q+GiGi4G8mPY5966qk47LDDNEOw6otKhgrGbiIiWhVjN2N3F5a7iYgqw0DH7iOOOEJf/ixlW6nk3m677bRCuqucO2/ePJg9liuNl4vFIr70pS8NeD/mA1Xu7nfF+KpN1TfE/vvvr8OayF1ruTNx1lln4Qtf+IKOu+WWW/TH33ffffjyl79ctnQQEdEGGsGtzqTPNbmzPlQrxQVjNxERrYaxm7Gb5W4iosqyEWL3KaecstauU+TFmj3NmTMHlV7uHrLN9mbPnq13J/bZZ5/ucbW1tdhll13w9NNPD2raiIhoLW/H7tMwZEPPepG746tmEEYqxm4iogrC2D3Ye2BIYOwmIqogjN0otz61GJfuTE488cQ+d19y3XXX4aijjkJ1dfV6J6yrX5pV7wTI567v1qRQKOjQpb29fb3TQEREfWNYlg59nXZ9XHPNNfpeCokB0g3XVVddpf2ercnNN9/c3Q9az7dvy8s6yu3qq6/WR7r+/e9/r/HdG9/61rcwGBi7iYhosGP3UMXY/V8sdxMRVQ7G7sPKXu7uU8W4vGzzyCOP7HPF+A9+8APsu+++G1Qxvr6kA/jzzjtvo6+XiGhE0zvXfWwJvh4txu+88059bEpuvMqTQ9LVlrxzYubMmWhqalrjPPLmbfm+53swBsIf//hHPPTQQxojpeV4z/XI34NVMc7YTUREgxm7hzLG7g3HcjcR0SBg7Ea5y919qhiX/r733ntv2HbfuiTP5XLYUM3Nzd19yIwdO7Z7vHyWzt/X5swzz9TKk54txidOnLjB6SEiosHr6+yyyy7DCSec0N0KXCrIH3jgAfzud7/DGWecscZ5JDh2xZKB9OMf/1hvyEo6er6IZLAxdhMR0TqN4D7GGbv/i+VuIqIKwtiNcpe7+1TTLW8T7Q95WWZDQwM2xNSpUzVIP/LII90V4VLJ/eyzz+Lkk09e63zyqLwMRES08RimpUNfp+0Pecv1iy++qDc+u0gglHdQrOudE+l0GpMnT9YXT+6www648MILsc022/Rr3X1Nn7y9eyhVigvGbiIiGqzYPdQxdv8Xy91ERJWDsfuIspe7B6RivK+k0uL999/v9eKPV155RSvVJ02ahO985zu44IILsNlmm2nAPvvsszFu3DgcfPDBA5IeIiJaT0Y/HseWadfwDoi13dhcvnw5giBY4zsn3nnnnTWuYostttDW5Ntuuy3a2tpw6aWXYrfddsObb76JCRMmoJyOOeYY7erlRz/6EYYSxm4iIip37B4uGLtZ7iYiqkiM3Sh3ubtvfaMMkBdeeAF77bVX9+euLlAkoyIvTpO+yjOZjL74s7W1FZ/85Cfx4IMP9rmvcyIiGrp3rlft5koqcs8999yypGfXXXfVoYtUim+11Va4/vrr8dOf/hTlJJX2v/jFL/CPf/xDK+JXfQmIdAMznDB2ExENDyO51RljN8vdRESViLH7F2Uvdw9qxfiee+6pfaCujfQPe/755+tARERD/SUgfe2ntNTqbP78+fqCzC5r6wZr1KhRsCxL3zHRk3zuax/iEjS33377Xk8plcvrr7+uyxZvvPFGr+8G6oWfg4mxm4ho5Mbu4YKxuzeWu4mIKgRjN8pd7h7UinEiIhq5b8eWSvGeFeNr47oudtxxR33nRFdXWtJvuHw+5ZRT+twyTArBBxxwAMrtscceK/syiYiIhmLsHi4Yu4mIqCIxdpcdK8aJiGiDGZalQ1+n7S/paku62dppp52w884744orrtCuto499lj9/uijj8b48eNx0UUX6Wd50uh//ud/sOmmm2pXXJdccgnmzp2Lr3/96/1eNxER0XA00LGbiIiIyouxu/zMDXmT98yZM+H7fnlTRERElUcexe7P0E9HHHGEvkDzJz/5Cbbbbjt9UbO8c6LrhZzz5s3DokWLuqdvaWnBCSecoP2KSytxedHnU089ha233rosP/fQQw9d7eWh63LUUUdh6dKlGGyM3UREtLFi91DD2E1ERBWPsbvs5e5+V4xns1kcf/zxSCaT2GabbbQyQpx66qn4+c9/3t/FERER9Yl0myKtvguFAp599lnssssu3d89/vjj+tLmLpdffnn3tIsXL8YDDzzQ3Q94Ofzf//0fli1bppXjHzW0tbXhL3/5C9Lp9KDtacZuIiIa6Ri7iYiIKsv/bYRyd78rxs8880y8+uqrWgkRj8e7x++zzz648847+7s4IiIaDkbYnWt5cfTmm2+O+vr6jxwaGhq025fBxNhNRESrYexm7CYiosrC2I1yl7v73cf4fffdpxXg0ndrz7d+SuvxWbNm9TsBRERU+QzT1KGv047El3ZJH+iDhbGbiIhWxdj90Ri7iYhoKGHsLn/s7nfFuDRhb2pqWm281Mr3rCgnIqIRxOhHS3CZtsLtscceqCSM3UREtBrG7iGNsZuIiFbD2F12/W62t9NOO2lfrV26KsNvvPFG7LrrruVNHRERVQaJBYbZx4E3UTc2xm4iIloNY/eQxthNRESrYewuu363GL/wwgux//7746233oLv+7jyyiv176eeegr/+te/yp9CIiIa+roqvfs6LW1UjN1ERLQaxu4hjbGbiIhWw9hddv2unfjkJz+JV155RSvFp0+fjoceeki7Vnn66aex4447lj+FREQ05EWG2a+BNi7GbiIiWhVj99DG2E1ERKti7B4CLcbFJptsghtuuKH8qSEiosrEO9dDHmM3ERH1wtg95DF2ExFRL4zdZdfvZnvt7e1rHDo6OlAsFsufQiIiqpC+zvoxDCPnnHMO5s6di6GMsZuIiFbD2D2kDwrGbiIiWg1jNwa9Yryurg719fWrDTI+kUhg8uTJWkkQhmHZE0tEREOUafZvGEb+7//+T1t07b333rj99ttRKBQw1DB2ExHRahi7GbuJiKiyMHaj3OXuftdO3HzzzRg3bhx+9KMf4b777tNB/h4/fjyuvfZanHjiifjVr36Fn//852VJIBERDX0jua8zee/G888/j2222Qbf/va30dzcjJNPPlnHDRWM3UREtCrGbsZuIiKqLIzdz5e93G1EURT1Zwapmf/GN76Bww8/vNf4u+66C9dffz0eeeQR3HrrrfjZz36Gd955B0PhEbTa2lqsfP7vqEnGYdgOYMdKFTOZFp0mCgL930zVICrmgTBAmOmAEU+Wvi/mYSZSCDpaYZgWzNpGBMsWwP3Ulwf1txHRyPXUnBVwTBOOZSDlWMj5IWK2AauzmxLHNGCbBtoKASwTqI1ZOn55SxumTx2PtrY21NTUlO0au+Lt51BTXdW3eTrSaNxq57KlYSjxPA9/+ctfcNNNN+Ef//gHttxySxx//PH42te+pttpsFRq7F7x1jNIjd8MRlBEZLkInCTMKIAReDBCX2N56CZhennkzRiSmSUI4zUwC+nuGzCRm+zRH5+BWNXg7QciGrn8hTP1OhY5Mb0eGV4eYaIOMC0YuTbkEo1wLUMKZzD8AopWDG5YRHvowMt2YPzYZsbuAcLYXd7YvWDRYjSmYojsmMZvPd4LHYjsOIp2Am7ko2jYCMIICXilfWC6iKWXwKtuhp1vRRivRcaPkC6GGGtl4dY1lSmVREQfrSObQ3UyoX8XMh3wDBs2QuRDA0EEpKyoVBaxXPgRIJWqcm1D4CFyEogMAx1tbRjTzNhdCbG73832nnrqKWy//farjZdxTz/9dPcbtOfNm9ffRRMRUaW/BKSvwzAl95olSMs7N+Rv6Wrs6quvxsSJE3HnnXcOWroYu4mIaDWM3Yqxm4iIKgZjd9ljd79rJ2Qlv/3tb1cbL+PkO7FixQpNFBERjRAjPEC/+OKLOOWUUzB27FicdtpperP47bffxr/+9S+899572hL7W9/61qClj7GbiIhWw9jN2E1ERJWFsRvlLnfb/d0Hl156KQ477DD8/e9/x8c//nEd98ILL+ij13/+85/1s/TvcsQRR/R30UREVKHkcbG+9h0u0w4n06dP1xi477776k3igw46CJZV6rqmy5FHHqn9oA0Wxm4iIloVYzdjNxERVRbG7nfKXu7ud8X45z//ea0AkD5J3333XR23//7760s4p0yZop+l83MiIhpB+tMSfJi1GJd+u4877jh9CfXajBo1CmEYYrAwdhMR0WoYuxm7iYiosjB2o9zl7n5XjIupU6fi5z//+frMSkREw5G0Au9rS/Bh1mK8q0+zVeVyOVxyySX4yU9+gqGAsZuIiHph7F7tgGDsJiKiIY2xG+WO3etVMd7a2ornnnsOS5cuXa0m/uijj16vhBARUQUbwXeuzzvvPJx00klIJpO9xmezWf1uqFSMM3YTEVEvjN2M3UREVFkYu1Hucne/K8b/8pe/4KijjkI6nUZNTQ2MHi3/5G9WjBMRjTzSv3jf+xg3h12L8Z6xsMurr76KhoYGDAWM3UREtCrGbsZuIiKqLIzdRtnL3f2uGP/ud7+rfaleeOGFq9XSExHRCCWV3ebIajEu3adIhbgMm2++ea/K8SAI9AaytCQfChi7iYhoNYzdjN1ERFRZGLtR7nJ3vyvGFyxYgG9961uVVykeBjDiVYBfKA1OAkY8haiYh2zSyPN0MsN2EGbyMNw4EIYIs+2wahsB0wJ8D5FssTCAv3A2zFcfQphuhRlPwV+2AM6kzRF2tPZabdC2AvCL8JYvgV3XAHvsFPgLZiHIdOj3hZYOpKZNQ2HRAjhVKfjZHIJ8EYZlIrNoBULPh+nYiDfWIFZfjbDoo9iRgR2PISh6iMIQyfFjkfzi9wZlsxINB0fc/Bxc28SHy7P6uaEmpv8HYYSka2FJax4fm1inn2U6+T9d8FGbcGCbho5b2lHAhPoEquK2fp8rBjpepjENA0nHwspcEem8r+Mn15euoSuyRTSlXFS5NsIogmOZiFkm0kVf55tQE4cXhsh6gU4j6wuiSJcnXMvUbsYsw9BBvkvYJqII8CW9lgHHNFDwI1gGkJB/BsIIfKTriiuu0NbicrNYHt2qra3t/s51XX0h9a677oqhoFJjd+QkNP4a2QyQsGHnW3Wc4WUB04YR+jCLpWMqHuQQuUkYxSwQhYAT1/hrty1AkGrszETa8JbNg5lZiTBValVgFDqAZfMRTtkOhl/UeQtVY5CY9wIQr0YUS+l0QXUTlhUtNIWtCGV5UQi7bSHCRC3CWDXslnkI3RTcURPgLZ5Vmq/zvLCXzERQOw7Biw8ifsDJyD/0W0TZdiQOPm2QtzBR5QrffwbemC1htS3QcxhNk/WaIPn3oHo07NaFpTy/XEtiVXp9iEwbkRODlVmBIFEPs5jR7+X8FM7itxEm6xHGUrA6lsGvnwjDz8NaOgvBmM1gt3yo3+k1xjBh5toQVI/RaeT6Edlu6Xqwcq4u08y26DUsjFXp9UfnkzTI9cvL6/d+7VjYUQjTAEy/gMhy9XcEhiuPJMExgUwQDcxGZOxm7B4AlmnACCQ4AznDRSLyEDlJPa4lHws/hC35U4RAECGyHLheRs8fydPKORQZBvJ+qHnjIF6DQkerLrPoVpemNUy0I47aKKsxNqwapfE4clMw08v1PBfFeD2WZn2Mj4doDx2MrkliQUsGVa6JrBci6ZiaX26sTmLuijSKQYTmKhsrcwHGJC3kgwjJYisiO46inUB1MjEQm4xoRFnaltHrRHWYRRCrQms+QHXnOVkXdmBRWIWGhAXXzyGU2B2hVE4OCgjsOKzQK8Vzw9DvvDBCotiGDrsGVZBYHEM8kdA8fyE1GhJB3bCIoulqOV0qVXVdcQtmUKoHlPicN1zEoyICK6bXqlw+r9cE13JQFY8jm8vDMiPEESI0LFjwNQ1SvDY0kSGMKEQUhUh7hl4/BgRjN8pd7u53xfh+++2HF154AdOmTVvvlRIR0TAzAgP0Mccc0/1Sy9122w2O42CoYuwmIqLVMHYzdhMRUWVh7Ea5y939rhg/8MAD8f3vfx9vvfUWpk+fvlqCPv/5z5czfUREVAlGWIBub2/X92yI7bffXt+ELcOadE03mBi7iYhoNYzdjN1ERFRZGLtR7nJ3vyvGTzjhBP3//PPPX+07eSRB+nchIqKRRR9l6/PLNweoO5eN3L/4okWL0NTUhLq6ujW+fLPrpZxDIS4ydhMR0aoYuxm7iYiosjB2G2Uvd/e7YjwMQ2ws8qPOPfdc/OEPf8DixYsxbtw4fO1rX8NZZ521xkoIIiIaJCPszvWjjz7a/eZr+XuoxyTGbiIiWg1j95A+KBi7iYhoNYzdKLd+V4xvTBdffDGuvfZa/P73v8c222yjfZsfe+yx2tG6vESMiIiGCKkY7mvl8HpWIl9zzTW45JJL9EbpjBkzcNVVV2HnnXde6/R/+tOfcPbZZ2POnDnYbLPNNKYccMABKIc99tij++8999yzLMscLhi7iYgqBGM3dWLsJiKqEIzdQ6NiPJPJ4F//+hfmzZuHYrH0xuku5aywfuqpp/CFL3xB+0YV8qbRP/7xj3juuefKtg4iIhr6d67vvPNOnH766bjuuuuwyy674IorrtAXSs6cOVO7M1lT/DjyyCNx0UUX4XOf+xxuv/12HHzwwXjppZfwsY99DOV00003oaqqCocddthqFfPZbLb7JZ2DjbGbiIh6Yexm7O7EcjcRUYVg7Ea5y939rp14+eWXsemmm2qFwymnnIILLrgA3/nOd/CjH/1IKyrKabfddsMjjzyCd999Vz+/+uqrePLJJ7H//vuvdZ5CoaAvRes5EBHRwJL+xfsz9Ndll12m/WTLU0Nbb721VpAnk0n87ne/W+P0V155JT772c/qy6K32mor/PSnP8UOO+yAq6++GuUmle+jRo1abbxU2F944YUYChi7iYhoVYzdjN1dWO4mIqoMjN2jyl7u7nftxGmnnYaDDjoILS0tSCQSeOaZZzB37lzsuOOOuPTSS1FOZ5xxBr785S9jyy23hOM42H777bUS/qijjlpnBYV0tdI1TJw4saxpIiKiddy57usArHYTU25srok8mfTiiy9in3326R5nmqZ+fvrpp9c4j4zvOb2QFuZrm35DyNNTU6dOXW385MmT9buhgLGbiIhWw9i92iZh7Ga5m4hoSGPsRrljd7+7UnnllVdw/fXXa6WEZVlakTFt2jT84he/0Gbrhx56KMrlrrvuwm233aaPwEsf47JuqRiXl3CurYn8mWeeqY/bd5HKFqkcN2wHUT4NJGpgBEXAdhC2LoUxajyCOW/CrCm9RC0q5qXGBfA9hMU8DNtFVMjDSNUg7GiBWdsImJbOb1iWfhfZbmn58ncYIOxohZmqhlXbiDDTjuys9+DWVeny/SXzEQUBwqIPwzIR5CUtLmqPvwAdt5yr03TMW4KaqWP1ezeRhCHpAeC1Z+HnC0g01et8pmWhmM3DcFwsu/w0eJk82ucsglud1L8TjbWI1Veh9f0FcGtSyK9oQ9X40eiYtxRW3NG/ozBErK4Ko0+7HLO/9/8Qeh5aP1iBHf/yMF49fH/MuOvvePngfVEzuQHxhlqMP+f6su1fonXZ45ePo31lDm7MRntLDo3N1fC9AF7Bh5twYFml8yIIQsQSNjLtBR1XVRdHy5I0nJgNyzax2aQ6zFrQBtux9HM+4+k8pmmgWPCx2dR6LG3NY2xDQseFYYSiHyJXDODaJpKuhVE1MRSDEOm8h6q4gyCMdN22acAPIyRMQ8d1DTK/kP9XZooYUx1DGJXGy/dVMRs5L0BNzEaVa8M0DHhhhLhtwuzsflvGyWdhmQaSjlX6vVEExzRgGQYyxQBx+79djcm8UWQgXQyRckwd51oGikEpva5jdv89MG/H7lvf4V3TrXrj8pxzztEXLq9q+fLl+jLmMWPG9Bovn9955501rkP6IV/T9DK+3OQO9WuvvabdffUkTzk1NjZiKKjY2B0GKJouYnYM8PKI4tUwc21AGCCK2UAUwvDzOk/kJEsZRctG5MR1eiP0NZ6bhQyCVCMiOwandYHOF8ZrYC//AJETK81vx/V/o5iD4+dKCUmvQFg1CoZfgBF4CCKJ/y7MXAtg2ro8M9uiaZL5oqrRKKTbYBomrPQyXafhFRA5CU2L5CEyf7wA9phJMGoaUfjnTbDqmzRPgTCEEYvDm/eujrPqR2uewZqyDYqvPgFnuz0RLXhP8xnurl9E4fHbdDsYiZQmNfv6i4g1N8PddncUnv07nD0Oh9O8CdK3nY+qo35Stv1LtC7+wpmI5r8Nc0zpeijnZ1DTDKdpCnL5PKx8O6yWDxEmamEseg9o3qQ0zby3YSZrYNaOKn1XyCByE6U8exDoNP6SebAmbIFw8WyY4zZBlGnX88xoX4ZI8spRKfbK/HItkP/tsZsheOtxwAkQOgmYXg5R6JSuC16udN46MRiFDp03WLkYph1DVNMMtC3W9cs5DL9Yum60LQeaa0vriaVg+EVElqPpC5P1MIqZ0oawnFJ5QdKRrO9+UspKL0dgx2CgiMhNwsh36DaRtOa8EK4RAGYIBEXEYlWAb2geYKAwdjN2D0TslryxnlupBBIItC2e4ecQxGsQRdDjHlUxmMUMsnYVil6EGjk/5RwppPVcNWRCAFWuBTPwkDdjSKWXwTFLGV8556oTCaT9JGqSdaXzPwrhGTY0qocholgVCkGEpqSNyACKXoiObE7z9JJflrx3FEVoyQcoBhnNPycdA9XJBJZlOxBPJBDm8noeG8UsbDeJeSvTGBOLEJgO8n6I2tZZsCZOR7FtOXJ2SpcXs020FQKMSs/TNEn+QuLxotYMLANobHkP/qipiEwb7uK3sbRxKzTmFmt+I7BKeRITEbJ+hIbq5ICd/0Rdiss/hDtqAoorF6IYr4cUFxN+BgUnBYlAUn6szi2VgmYptkm+MzkaK3I+xqVsjZUL8yakCDwpBbT4JqocOQ9CjHJDZEILtSvfQ3b05lp+lrgm/wdOlZ7rcr4kHRNpL0RdafG6zlgxi6KVQMwIkfENuJGv5wYCT/PhppdHGq6mUc41Ob/kXC1aMZgSr504WvMBRiUszTNbltHdo6eUyfU6I2UKy0EBtl67pC5Qrg1CytExqRoMI7RlcogHOeSNOBypU/BDpExTN4nlS51gDJ7pwgkD5EMD1XaESBI0ABi7Xyt7ubvfFePSclsK1l2VAVIrL4+pS+vs+fPno5zkEfiuVuNi+vTp2jpdWoWvLUDHYjEdiIho45FMQWcZpk/TCokZNTU13eMr9dotXYvJ+zWqq6ux++676zh5D8e3v/3t7vg12Bi7iYhoVYzdjN1dWO4mIqoMjN3fKnu5u98V49KdyfPPP4/NNtsMe+yxB37yk59oa75bb7217C80k87Tuyrhu0hLtzAstQghIqKhQVrEy9DXaYVUivesGF8b6b9brv1LlizpNV4+Nzc3r3EeGd+f6TeE9F8+Z84c7L333rDtUliVOHX00UcPmT7GGbuJiGhVjN2M3V1Y7iYiqgyM3XPKXu7udx/jsrKxY8fq3z/72c9QX1+Pk08+GcuWLdPHtMtJ+jKXdTzwwANa6XDvvffqC9gOOeSQsq6HiIiGLtd19T0W8jLmLhIA5fOuu+66xnlkfM/pxcMPP7zW6Tc0fXfeead26yKPId9zzz2YNWuWvhhUvhsKGLuJiGhjYuzecIzdRES0MbkjtNzd7xbjO+20U/ff0pXKgw8+iIFy1VVX4eyzz8b//u//YunSpdrH2Te+8Q1tpU5EREOHtAHva+/l69PLufRhKV1oSQzaeeedccUVVyCTyeDYY4/V7+Uu8fjx47WrLSGPU8lTTb/85S9x4IEH4o477sALL7yA3/zmNxgom2++uT5NJYw+9re+sTB2ExHRqhi7Gbu7sNxNRFQZGLtR9nJ3v1uMr81LL72Ez33ucygn6TdGKj+kX/FcLqd3Ai644IIh0wKPiIhK5B0l/Rn664gjjsCll16qN0a32247fSmU3JjtesGmvO9i0aJF3dPvtttu+gIpqQifMWMG/vznP+O+++4re5dfXW655RZ9D0YikdBh22231S7GhjrGbiKikYuxm7G7C8vdRESVgbH7lrKXu/vVYvwf//iHNomXiumvf/3rmDZtmjZhlxdk/uUvf8F+++23QYkhIqLKFEWRDn2ddn2ccsopOqzJ448/vtq4ww47TIeBJl18ydNNkrZPfOITOu7JJ5/ESSedpO/gOO200zCYGLuJiGhNGLsZu4mIqLIwdp9d9nJ3nyvGf/vb3+KEE05AQ0MDWlpacOONN2plwKmnnqot+d544w1stdVW65UIIiKqbP1pCb4+LcaHMnn8+Nprr9XuXLp8/vOfxzbbbINzzz13UCvGGbuJiGhtGLsZu4mIqLIwdl9b9nJ3n7tSufLKK3HxxRdrLfxdd92l///617/G66+/juuuu46V4kREI1zUx2G4kS5cpOuWVcm4nt27DAbGbiIiWhfG7t4Yu4mIaKhj7C5v7O5zxbj07931SPqhhx4K27ZxySWXYMKECeu9ciIiGh4Guq+zoWzTTTfVG8arkjdmd70UZLAwdhMR0dowdjN2ExFRZWHsvqvs5e4+d6UiL79MJpPdb/2MxWIYO3YsKoblwoglgSgEjM77AWEAo5hD5BURFfOIYglEQQDDshD5HqzqOkSFfPe0sF0Ytoso067TwCxNF/lFmNX1ugxhmKZ+J4PhuAg8D342D7e6Ht6yJbCrqmC6NsKij8DzdZ7W3/wIplPaHcmxDSi2ZxDki4jVVem8TiqBYkcG6QXL9W+ZVpYbq6uG37oSfr6I3LIWJEfX6zLDzuUGRR+x+mr9OwoiREGIRFMdCq0dOk6WX2zPYt6ZxyK9YAXc6jjshI35Zx0PyzHx8sH7opgprUfSI9OtfHchLNeC5VhY+tZyjJk+GlvddD/eOvogtH3YrusZvXVTabPHXUy7/Ha8fuQB+jlel0TL7JVwUw7i9Qn4OQ+LX1mKmonVqJ1Up+le/s4KuFUudnn4sY16iNCanfznV1Eds/H2onZ8fGoD3lnUjoZUDAduMwbPzG3B87I/bRPTRldhZaaIoh9gdHUc7y3pQEdHQU85J2aV+sIKI/heiDCMEPohTLt0LvpeAL8YwLJN2I6l08l3pmnAdi0dZ7umLqdretvp+t6GVwh0Hidp6XdOzNZ5LNtArujrcmX9gR/CK5TOjXzBR1VdHJZpIJcuItFcDds20d6aRyIuy/SRcGNIuDbSeU+HqriDuoSDpR0FXW5W1mEaOlTFbN0O6bzMZ6Et66E26SAII3x958m49aUPu6fNeQGq3NL5HrNNFIIQcduEF4Q63gtD/c40DGTl91ilNy27lgEvjJAphnBtA3HHRBBKcIxgmYBMpf8bBoIoghEBQST9kJX2paTFW8/+vYdCX2dD1Xnnnaddij3xxBPdfZ395z//wSOPPLLGCvONqeJjd+hr5s/wC4DlAH5B/w5qmmF4OcC0YXh5BFWjYRY6YGZbEMarEZk2EKuC2bEEYdUoGMUMQjcJu2MpIicOo5CBEfqaHzAkjkvcFoGv+QSjmC3lEZK1Op2Za4OfaoRtGpqmKFYNBB6MwAMWva/x3tr+syjm8zCL2dI624qax7CyLYgk7VEIs6oOqSPPQvHfd2jew95khi4/jKU0HUZQhGE7MJsm6XpgO0AQaFrMgvyGOMK2FVjyi1NRt9PHEWY74NQ3Icxn4NbXwWpsRrF5S5jVTwNzX4c393U4Y6fAf/EBePPfhdU4Flb9aER1zbo84S+dr/kae8Km8D54Q3+LmaqB+6kvo/j03bo+Wb8zZStYW++J4K3HEXa0IsxlAL+IMN2q+SN79HiEmXZNgz1j38E9bkj5C95GmKiF4RX0fzk/nOZN4C96r3RMSn44DBDFUnq8yfd6ToS+niOyP+VYiCwXyLXrsRklanTZusx4delc8nIIq5tg5Dtgejl4HS3AtB1gyfnme7qO8N3/wBz3MfixGlhyXMvpnc/AMEw9FuXc0Px3tg2RLEuWW8ggknWEWT3mdJ7FszXfHTpJQPPuKZi5DMzaRkReQT/LNcLMrERQPwHB7JdKvyNRA0MyJDKYZuf1w5ILo15HIicJu3U+Ijdeml+2RaYFqBun56X+5sCHKWUDOcfl+iLnkNm5vWTdlovISQCWjchN6DRy7THzbXpNKl1zDP1fr1nFjKYpkvl9oMa1EUs2IJ/N6DXGlOueYaIYRJpHGAiM3YzdA8GRUBmvKZWfJabKMS5xVcYJ00TBDxGPyfktx34pnyvnnV83QefJ+nLcG5p3lXhr2TYiO6bnROAmYeVaYbUvRipRi8iOa5xGsh6uV4ptQtbrOjGkvVBbA0reuDqZQFs+rflxxzQQNyX/Co3vkodOOSaembsSY6tcLG7LoM6BLluuoZJmyzDgGRbszmcgI8PEvJVpjG+bh+f9idi+OYXFaU+/letCIPkBv4Bi61LErCokbQNhqkGvQcuiKozzC2jNB2iU67Fhwi6msSxMoDZmah5eFNJtOr3kd8JkveY9ZFuY6eV4pVCH6aPjsDqWIJsag+pFr8Ibs6Vet9JWFarzyxGkGuHDRCyzDJHtotWsRn1uMQo14xBvnQd73BYI5rwCa8p2A3I8UP8Ul3+ocUSOBz3mwwCxmgY9Hs3OsqMcu056qZ4rrfEmPTZlvBzjNVJ2LrTr/k+ZgZ4/K8MYGswC0kZcy5JyXGcDQ8uWwnGTKLSvhGG5em5I5lvWLaefrCuSI1ryxVGIQI5fv6DrdE1Dz9WkZSPlAG0FyUNn4Ng1cCIfKcfSzzlUozpRi/ZCiIZEqTwvq856oZ571a6FhNeBWomb+SISrqHlWrlWxEzA6lgGNzUGRjYLw3JK+f2Uqcd5YJTyFBLL45aBMFEPCwYCidPFrGajNa/tJrUOIudHcEwg4ZgIYcBw4pqOpGNovO2+3sgivTzScHU7JGxDY7xfDNHhATk/hBO3YUQRktV1yOdysI3SumRHSX7IH6AiL2P3EWUvd/fr5ZvSr3hVVZX+7fs+br75ZowaNarXNN/61rfWOzFERFSZpCo/7Me0w8kXv/hFPPvss7j88stx33336Th558Zzzz2H7bfffrCTx9hNRERrxNjN2E1ERJWFsfvZspe7+1wxPmnSJNxwww3dn5ubm3Hrrbf2mkZao7FinIho5JHWNn1tCD7MGoyrHXfcEX/4wx8w1DB2ExHR2jB2M3YTEVFlYezesezl7j5XjM+ZM6esKyYiouFjpL0du729vc/T1tR0Pjo8CBi7iYhobRi7146xm4iIhiLG7vLH7n51pUJERLQmI62vs7q6On1K6qN+p/b3Lp3bERERDTGM3WveJozdREQ0VDF2lz92s2KciIg22Ejr6+yxx/hyYCIiqmyM3URERJWFsbv8WDFOREQbTNqA97mP8WGwvffYY4/BTgIREdEGYewmIiKqLIzd5WcOwDKJiGiECaOoX8Nw8+9//xtf/epXsdtuu2HBggU6Tl5Q/eSTTw520oiIiNaIsZuxm4iIKgtj97/LXu5mxTgREZXnznU/huHk7rvvxn777YdEIoGXXnoJhUJBx7e1teHCCy8c7OQRERGtEWM3YzcREVUWxu79yl7uXq+uVGbNmoWbbrpJ/7/yyivR1NSEv//975g0aRK22WYbDElhgMhyYfh5RMU8okStjo68ApwJmyDMdMBwEzDM0r0C+RyFAcxEqvRdGMCqHw3DjQO+B7OqTv82U9WIchmY9SmE+Qwiz9P5DdMqLb+QQ2raNESZdpjxJEzXhhGLw0qk4M2fj3hdtaYtKHpwqpOleVo74OeLsFNxhJ4PL5NH1UQXwbIWWI6t07XPWQQnFe+eLyz6sOIxXb5Tk0SQL8DPF3QZURCielITcktbYMVdxOqrkFvaimJHVpeh68jmkF2eg+VYMC0DEy/4LT789B6oGpNCGEQ6ryxblhWriSGzJINR0yfAf3ExCu0FvHHUgXBSMThxG7mWvKY/CiIsn7kMHYfvr8tsn9+BYtrTeWObNei6vUwRlmvCz/no+LANtZPr0bhZA1o+aMWzn9kLY3aYpOte+V4Llr6/EuOmN+m0o7YeDTvhws8VUezIwzANeBkPtVNHwa1JaTolDbIO+c35Fe2IggBV40fr50JrWre15drILFqB1NhGVE+diPTcBUg01cNKJFFsaYVbXweYJoorVsKwTJiOrd/ZzZMQyn5PpGDEk3pMGbYLw3ZgNI5H5CZgppfD3PwT8D98E0HdBJiZlbAyK+DXTwBMG75bBS+M4IcRgjBCWyFEQ8KCvM4viIBFaQ9eEMG1DbTmfFidt7GyXgjTANLFAF5Q6q25reCj4Ieocm20FTw0xB08O6cFSddCVbx0midcCwnHQrrgo+iHOsh3liwMwOLWPDoKvk4j6RlbF0c6X5oWMej/Mr4hFcPVX9xW53nsveXI5X2gcx0T6hN4ZtYK1CZdnd6yTcRits4X+CHyOQ+2Y8ErePC9AImqmM7nxmz4xQCRvGJZzx8DoR/q/zKfG7NgWSay6SIy7QXUNpbOlXjCQbq90P0SRK8gywCCzu0SBIZu3+qUi9a2vK5bz+8oQrI6pp+Xthf0f9c24fuhpkHSq+vuTE9V3NHtJJ9rkw7eWNCGXDHAZmOq8cGytI6X77u2kWw32ZbNdXEdd+tLH3ZfiuR72cZeGMILTbTnPST1c4SYZerfgIV00dd0xmwTtmmgNe8hbpvIFAM4pom8F6I6ZiEv28cy4QdA3DJ0OdIg2+38O4gimDBgm9Dt5HzECyPX+xIblYa+TjucXHDBBbjuuutw9NFH44477uge/4lPfEK/GyoqMnabNmJGCEhMjUIYXh6RacPsWKpfR3YMRjEDM+8ijFXDzLUBYQgj9IGgqNOH8WoYhgmrkAYCD1gyG6hr6pzfgRGF8BfMgjlpWxiBBzPfgTBhluJ96Os4w8vBzLWipmoMkAfMzApNh17rUzUwnBjCd/+DaOKOujxImrItiOw4IsNE5CZL6Y4l4L/4QCn/UNOAKF4NFDIwvAK85q10ubDfQ9S6FEbtKFgTNtd0OhM3h984BVYhC7tpPMb84CoU/31HKV8Si8MMAxiJFMx4CivyAWo7WuFM2UpjkuRlCu++DKtxrMYte9w0BMl6GL4HWBbCjtbStk7VIf/hfNTsfbB+bP3Nj5Da/n90Gdn3PoA9dioK/7wJsX2Ohffgb3T5Mo/39nM6vUxn1TYiymdR/M9d8BfPQ2ynz8Cf/YamMWxboetyN99OY2cUhohqm2G0LEDkFWHUNiFySjEBS+fCrK5D5CQQtS5BmG7VZXsL58CZtDn8idvBeOXvpfVu/j+w2hcjWLkYZvNUhE4SRlAsHS9RCK9xGtyFr8OXOFyQfVsLq2MZIqdz/0ahzmMW0giqRyNyUxqvRaG6GU5QkIunHgOSjzTz7TCzrXpcyf73Ew16HS4EEWpjFuxCO9rMKr32Nngtpfym5kEdTWcUS3Uepz6M9mWICnkYdU2lYynXhsj3dLtI+oOaZjhL30OQatTjyR81Dc6iNzWNfsMk2CvmlI4h+b2mjWL9ZLit83XZoexjN6XHoP5ey9HzRY97w9TfI+dJ9zHqJAEr0502zdfUjNJzpGv/+isWw25ySueRHdNzRdIp+WQkZX/F9HjWdVi2rhMxE2GqEU7zJjCWfwgz5SJ0q0rnqGmVzheJC+lW2M1T4C+eA2PUFERtS3X98tui5R/quuUYkONCt6efh5GqQWDaCIt5IF4Ns5iD0XXexVIwJC2GCbO6HtHKRXqewnJL60s16DaTc06OCdnHkr83HBdRrgNGoraUp5f0yb6SczbfVrqeeAVNvx5nsm38AsJkXel/KUt0ntNS5pB1yLmPruPMy5YubcWMjpf9BC8Pw8+i4FTDbFsOMwq7j7UwVgUYpTzCQGDsZuweEFGIop2AgxD50EDcjmBIvI4irMgFaLJcFIMICXgohg4sw9CKHsswS9fuUMo9LtLFEI4JvT4XjTjiBbnW1MMsZoHAh1lM6zVQr0VyrZJ5i1m9nsq5L59jXgbLvRiqXMlfR8jl86hyJWfceQ4YFtoLHmpjpqZDLOooYEpdTFsQSvqr9DwvIh6LsMQLMMr2sLhoa147ilUjYcs1NIbdGwysDCNd1+KMV7pOyLVu/pswJm6DIFmFDi9CTbxGr4/JwEBY3YRq10IUxWAUOhAkGzA+Hkc6m9PlF1cuRJhsgJ1eruXIKFZVurZGIZwxU1G/rAORYSCM12BFzkeV1FPk2/UabDmGTifxw0yN0nFGMYdkdS0i1MI2oNeg1nQWVZ3xV7aPlCmlLFrtter07amxqA5lmxdhBD7mG/WYYOewLEqhGISYWPgQufopOn8s3wKrbTFmV22Ghril+1W2j+XnETpxmH5B81Whk9Dps4GBFIpoCR2Myi5EpmaCHhsypBxDjxEpU0s8lH1lBQX9LHFFr88SW1s/RFA7rvManCpNF3r6WcrbEo9jxY7/xkCpE5LYIjEg24IVdj0anFIs0uu19uFs6DI0XsrxbNiQzZkP5MlXIGV4CCUOFrMI3SSsfLumJ23X6LZLOSbsYlrHdVhVSFkRfJhwix16bObslJbn5ZiTbRg3I023iQimbKeOJRrLYBd1n7dlct3Hp2ybmBzeMl1mBcwEUBsvld8LxUi3kayjGEZwLDlOS51Sy+8vFuUFhaXtLsfX0qyPxoQNNyjCrW9GsXWpliNtlH6z7EBZnm26uo2t9DKkIwepmIugEGr5VytpTalniLTv68iMI2YZMLJtSMSqdJ5EXQ2MXAHxRKk8Ld87kY+slIULARoStp4DtlwLnLguN2kbiKK4bvOqwCv9ZsvW31Y6x0vbQ8q3CduAkckjitdovZ3ETTmO5SjLeCHg+HqsyL6RaXUbdpaVZbmWAZ1PvpeLg/wn01h2HK4+7QzN5wWmoeXvtkKg+1iOCTnHZf/I/nRl23fmawYSY/d1ZS9397vF+L/+9S9Mnz4dzz77LO655x6k06UKxldffRXnnHPOeieEiIgqWFTqY7wvw3BrMj5z5kzsvvvuq42vra1Fa2tnpeMgY+wmIqLVMHavtkkYu4mIaEhj7Ea5Y3e/K8bPOOMMrYl/+OGH4bqlVhfi05/+NJ555pn1TggREVWuEFG/huGkubkZ77///mrjpZ+zadOmYShg7CYiolUxdjN2ExFRZWHsfr/s5e5+V4y//vrrOOSQQ1YbL49kL1++fL0TQkRElauvrcW7W40PIyeccAK+/e1v65NU8jjfwoULcdttt+F73/seTj75ZAwFjN1ERLQqxm7GbiIiqiyM3d8ue7m7332M19XVYdGiRZg6dWqv8S+//DLGjx+/3gkhIqLKNZL7OpPW2GEYYu+990Y2m9VuVWKxmAboU089FUMBYzcREa2KsZuxm4iIKgtjd1j2cne/W4x/+ctfxg9/+EMsXrxYa+ilMuA///mPJkQ6QCciopFnJN653mmnnfSlmx0dHfjxj3+MlStX4o033tBuxZYtW4af/vSnGCoYu4mIaFWM3YzdRERUWRi7f1z2cne/K8YvvPBCbLnllpg4caK+eHPrrbfWWvrddtsNZ5111gYlhoiIKtNI7OtsxowZ+MEPfoCxY8fqjeGnnnpKY+LOO++MqqoqDCWM3UREtCrGbsZuIiKqLIzdR5e93N3vinF54eYNN9yAWbNm4a9//Sv+8Ic/4J133sGtt94Ky7I2OEFERFR5RuKd69/+9rf69NQ111yDefPm6SNdm266qVZCL1iwAEMJYzcREa2KsZuxm4iIKgtj97yyl7v7XTHeZdKkSTjggANw+OGHY7PNNtvghBARUeUKo6hfw3CRTCbxta99DY8//jjeffdd7bLk+uuvx5QpU3DggQfinnvuwVDC2E1ERF0Yuxm7iYiosjB2P172cnefXr55+umn93mBl1122XonhoiIKlMQloa+TjscbbLJJrjgggu0j7O7774b3/jGN/Dggw8iCIJBSQ9jNxERrQtjN2M3ERFVFsZulL3c3aeK8ZdffrlPC5OXcQ5ZUQAj9BEV8/rR8PKIbAfwiwgyHTDiSUC+9z0gDBCFAQzTBMxS9zBRIQ8zkSp9rhkFo5jXZRluHJHnldYRhjAsC2ExhGE7Ok+Yz+pXfjYHszoPP5OHXe/ocgyr1GDfX7EYlusg9PxS2iwTQb6IRFMd2mYtQGJ0vX4XBiHsVFzXOfbMa9By7Rlom7MIdiKm05d+ZggnFdd5cstadLwdd1Fsz2Krm+7HwgtOhhV3ddogX4Dp2ih2ZGA6DgzLQHJsA6onNuHVw/eHE7eRXZ5DvD6uaQqLPgLP13Fd8+db8giKIba7+wHMO/NY1EwdizdueQaZJRmkxqTgZTzMePTvePngfTX9ft7X6cUHD72HsTs0Y6+Xn8Vj2++i4zQ9SzuQXZFF/dQ6FFo6EKurgp3oQC6INI2BF8BybU1z2J6Fn/N1vCfLzheR93z9/fkFy5Bf0YbaTcaXdk/n9vWzef3by+T/uw9yRXjt7Sh2ZBFvrEXb+3MRr6tGkMvCSlXBdErbyY7HYMViCDPtuv8j09T9EbQsgzN2Smm/+nkgCgE7hvD9Z2A4CcSqauGll8OcthOMpXMQxUr9IDmmAT+MEHQ2oM15IWrjFnKFEOmiD0eOQRjwQtlmJpZni3qHcGx1DAU/hBdA562PO5jXlkPMNhHkIixOF5DzAh1EVbx0qgdRBMs0sCJdRF3S0XHpvI/apKPpSDgWquM2PmzJIZDXHQM6fdcy5O+ka+HEu16Ba5lorHKR6Fx20Q+71yfzyrSyxfM5D6YcP0GIIAiRqonpNPlsEaZpIPBDFL1A/3ZiNizbhO2YaF/ZeZzJ7ywEyGc9RGGk3/legHjK0XXI58CPEE+6unyv4MMvBgjNEG7CgS3TuBbaTUPXIctJ1sRgWgZc10I2U4TR+eyMzN/cXIW2dBGWZeq2kG0yd0UGjVUxtGaLGFsb198qaREJt3PbhhFc29RtV5dwusfVJ0vnm07rWJrmYhAi6Viojdm6n2W/dZFD0gvkmIgwKunCMgz9W6aX3yLHhCPHe1B6I7V8lu9lXYZhQnZXPohgd1Y+u6aBQhAhYZqIZDoMjP60BB9OLcZXJS3Hb7rpJg3Qtm3jhBNOGLS0DIfYHdkuzGKm9LdpaxyXQa6xQU0z9OT1cjDzHXKxAIIizNBHKNfmYg6RE9dpjKAII9em1+gwn4EZS8EopGGkVyKqaihdu4s52RilIQoR2XFEKxbADAOEuQyiUS5cPwfDK+g0Zr4NkZuC4cQQxlIwCxmYUQCrfRGCmrGAaSNyYqV0yN9W6bqAsZvCyrUhTNSWflO+A1GmHbYT07SaEzeDv3gO0DQZRsdyGG4C4bgtSnElUQPYDvJ/uxb22KkwYnHNs5i1jTBWLNY8TMYLUV/biKBtBcxJW8NK1GDuLX/EJt/dB7nn/4lg+8/AzLUhqBoFyHayHXiL5sDe2kRQLOVn/PoJSGy6JczqevgLZqH+5J9rPJNlhrOeQ9jRCn/hbNibzIA7ZUsU57wDs36M/sZg1qu6DHfax/RZT3vyVjC8HLxcBs6ULWE4LvyGybCWz0b04duwP/55+Atnwsi2IEzW6bxmLK7rCCdPgrF4NsxkDYx4Sn+rmJcBptiu5t2CRC3wwUswU9VA21JEE2cAhTSs9HL4jVOwogCMSdTCCDzdp5JXk98teT7hjdoUduuHCJP1us/MzEqEVaNgppfDLXboNGGsWveVHotyzKVXwIil9JizM8uBWINej61Q1hGDa8h1Xi7oNoqGDdcIYXUs1e+s1oW6fKOY0XyipkXOQzn+JO/pJhDJvpZjIbOydNz0OEflWDTtmB7TpRNDfo+t6etaf5ho0uXLdjecuB5rsF39HcHslwD5LDpWIGzeXI/BrutA6Cb0fIq8IoxqB0GqEdbid0vrTVYjTLdq/sdqHFfKN1suDMlDFkrbJvJL6bLaFuv6C+++AutTk+AtngXTzyOSfSH5JDn23bj+HeUznfnpAqzGsQhiKUTpVpijJpby7qYFq7axlAb5f9QUGH4BRiyJyEnAkO0m56Vf6N5Oks+XfWpkVuhbLeRcMbKtpXz+uK1LaZV9Kenw5NxvRFDbDCvTomlB+1LN42ne3iuUzicnAcSrS9sr5yNyE6XvwzyC6jGwOpaU9oVs32xL6ViTa08UInSSiOR3aR4xKp33kr5CGpGbBLxQ84RGMavXva7rnJltQXWiFmHUub/LjLG7hLG7vOSYlytKuwfU2gEieUhdzrcohCf51SALN5FE3nDhWoDdmXeVc8SHCSeKELMA3zYQswxESGr+1gj8zrxAALMgcb8zVyvXr0DGZfTcCurGlWK/xNqqUbACA1WuiXQx0PJT3Ix0nmIQaZ68KmairRAiZhuQ7LOUZ1ZkA9TFrdL3kidwk7DaF2NUaiyMwkoEqEXOjzSf4XRm4zWfkUigLr8UK60GvfZKOiO51nlZ1Jgelns2gnhcY3W1YyCMV5fmlWtYp6VtGdR5LbrOKFYNK98Op3kT+K/OghlfBr9+EjyYMFqXIm4ltQznWg5yXoRg2QJEE7eDvfwDmPH6Ur1GvAbtxQD1bkq3ixOVri9WepmuQ36H/MZFrRk0OCHygYl6o4DIScLKrCil1Qx1+8vyQhNw65oQrEyjSnagZ2sMjAc5dDh1qDOX6fXMtQykvRDFQoDR6QWA5I2EXBMNS2OWJfuzkEVg1Hbnk6rtCK0RkIiKCJ04jM7taHSmX+JG0Yohll2hsU23n1xT49UoRCZc2R8SFwppwC2VueW46e7LUY5PiReOqXHCy0s/jyFCOwYz8JCHDdOIANPRa6Qcnw5KscCyE0iERV2eHD8JiVEyaXoZ/IYpkIJWXGaQJDgJPZ7tCMgGQFXQoel3a0ehmM1pmTDrhbAM+d6AY0WwvQyKTgqxWLXG8TDVqMdqPCwAVkzLcnHLKMVGib+hj3Qx1DLiaCODdiT1txXcatRJT9SmgSiS/RMiHxrI+YGem6mkrceN3bmfJHbpcSfbVz7KueRWa/qcWAxFL0TCS+t2WpkLEMRMPZdrY1bn+uUYLP1u2TeSX5Y8UGDHtcIxbpuaP5H1yfFWn56PoGo0QsT0GJL1xM0AHX6ApJ+FF0uhEBpIZltgVI8r5XVkv0meWvLnsWrdx2mrCkW/tO4wVlXK+6XknC/ANl2kozhGJ4HAcbX8Lus3O8vWUoci26BU3xLB9HJI2CmEVhJOGKCodTCRXntkuycduU4EcEwLCdssrTMCWoomamOddSZ+iKxTo2V7I5tGhAQGAmN3+WN3nyrGH3vssfVeARERDX8SoCWT0ddph5MPP/wQN998sw4ffPABPvWpT+HXv/41DjvsMCQSA5Mh6gvGbiIiWhfGbsZuIiKqLIzdN5e93L3efYwTERH9N0D3p7+zgd1uK1euxFFHHYWamhrU1dXh+OOPRzqdXuc8e+65p7aY7DmcdNJJ65znrrvuwmc/+1lMnToV1157rb5zQ/o7+9e//oWjjz56UCvFiYiIKil2byyM3UREVMkYu68te7m7Ty3GDz30UK2Rl0oG+XtdhtqLxoiIaGT1dSaV4osWLcLDDz8Mz/Nw7LHH4sQTT8Ttt9++zvnk8avzzz+/14s11+WrX/2qvujj3nvv1ZdRm51dIgwVjN1ERFQpsXtjYewmIqJKxth9QNnL3X2qGK+tre3ue1Aqxzdmf6QLFizAD3/4Q/z9739HNpvFpptuqv3I7LTTThstDUREVBl9nb399tv64o3nn3++O05cddVVWnF96aWXYty4cWudVyrCm5ub+9WFSlNTE4Yqxm4iIqqE2L0xMXavHcvdRERDH2N3+fWpYvyQQw5BPB7Xv6Xl+MbS0tKCT3ziE9hrr720Ynz06NF47733UF9fv9HSQEREH630EpO+FZq7pmtvb+81PhaL6bAhnn76ae0+pefN03322UfvKj/77LMaz9bmtttuwx/+8AetHD/ooINw9tlnr7PV+FCuFBeM3UREVO7YXekYu9eM5W4iosrA2D2IFeOLFy/WimnLsvQR9Y2Rqbj44osxceJEbSHeRfpyJSKiyifX957OOeccnHvuuRu0TIlVq8YneUt1Q0ODfrc2X/nKVzB58mRtUf7aa6/pk0ozZ86s6O7BGLuJiIgqC2M3ERHRxtWnjlmkQvyZZ57Rv6Mo2mhdqdx///3a6k/eMCoVHdtvvz1uuOGGdc5TKBS0FWLPgYiIBlbY/SKQPgyd88yfPx9tbW3dw5lnnrnW5Z9xxhmrvRxz1eGdd95Z7/RLH+T77bcfpk+frn2U33LLLdp3+KxZs1CpGLuJiKjcsZsGFmM3ERGtC2P3IFWMn3TSSfjCF76grcWl8kEeM5e/1zSU0wcffIBrr70Wm222Gf7xj3/g5JNPxre+9S38/ve/X+s8F110kfar2jWs2iKRiIjKLwijfg1d76zoOayrG5Xvfve72n/4uoZp06ZpfFq6dGmveX3fx8qVK/vVf/guu+yi/7///vvr/t1BgCeeeAKtra0Yahi7iYio3LF7OGDsXh3L3URElYGxu3VwulKRR9u//OUvawXB5z//ee3aRPpwHWhhGGqL8QsvvFA/S4vxN954A9dddx2OOeaYNc4jLQ5PP/307s/SYlwrx41Spb1hOwhzGZh+AZq9s93SeMtCZLlAmAHM0rRhpgNmdb3OI+Miz4OZiiOS730PRrwK6GiFmapGFAaIvKJOZ9U2lj7nM0AY6BCFIQw3Divu6jRBy1IYVum+hNee1f+jzte92/FS5ZDlOIg31MJybZ02LPrdaV1w3jeQGtuIKRf/Hh+ec4JuK8ux4WVyiBWrdLp8SwamYyP0fMTqqtH6mx+h0JpGkC+imCkiDEJ0zFsKtzqly3fiNhKNNcgsWK7z106uR9vcFsy46+/d23PmiYci35KHl/dhuSt1XKG9oOPdmhTijg3LsRB4Iey4i+qxVXj54H1RPaEOLR+0IlYbQ3ZlTpf58FY76vzPffbTiNXE4KYc+LkiWue2I92Sx4T/SXX/3mK6iIaaGEzTQFAM4GXymubqSWOw8r134FQ5aNh0lI738z5S40ejmPG6t2mhtQOGaeo8pmsjt6Jdx8k22+zaP2PJL07VaWWQafxMHmF1UrdfYelynUf2i3xnxOKwR48v7cNUjR4fZrzUD3FUzOv+NgwfkWkDxTyMMID/4ZswfQ/e4lmyY4EoLPUNFUbwwgiuVXoKIx9EqI5KT2ZUx2xkioFOk3QstOQ81MZtbbVjGoZ+tjuPIXkBw4KVOdTFHaQcS7dTQvZDGCFbDDC6JgbLNNAQd/CV7SfgB395U+fLFQO4tqnfiZhtoiPv67wyTuYVHQUfTTVxnVbG/ebw7fDte1/XaRKuhbash2IQoi7h6DRL2/M6Xr4v+qH+nc37iMUdJOM20q15xBIO/GIAJ2bjmbP2wa4XPqLrcuM2vEIANya/NdLfKkzLQBgaiKdc+F4AvxiiYAUIOwtquXQB1Q0JBH6IIAhhO6Xz2A8jTUPgRzCt0rSyfSzbRKajiHjK0XnSeU/nkd+ZzvuIwggFP0TStVAdt9GR9/T3yO9rrHJ1O7RmS+Pk84ctOd2eojXn6TaUaeU3eGGo6ZR9LtNMaUjCC0ppcUxTf2Oyc3/J30EU6n62DAMhIpgwSsd+FMGxDD1ebNOAdPcpy5Z9HloRip3LjNuGpkt+u5wCshyvc9kD9byPHLN9fTGXTLs+Lahk+Ci77rqrVlK/+OKL2HHH0jXm0Ucf1WtkV2V3X7zyyiv6/9ixY9c5ndwQ3nfffbVifmPExf4YFrE78BA5CRiFDKzMCoSJWkSGCSP09VprFtr0u8hN6LgoVg2jmIFZyABBUf/X2J5pBRpr9TuN55arfxtuQq/Vck03si0IUw1ygYCVXgYYJiLb0fhtJlKALKuYg+HnAdNG8O6LMLf+xH9/hGEilLyG78GUtMZSCKtGw0wv03Rr+qoaEM5+FUZ9E5CsR5ishxEUgUw7zGwrwmSdLkfyEaGbgoHlCFKNgGHAal9SmjYKYY+dCrOmAcHyhbBGTwD8gqbRqh+t570p80v+JArhz3oNtZuMh98wCVZ9k67T8gvIJRpL8aWYh93YDCMKEW+sRVTIInJL8VfSK3mfjlvORXKvL2q+Rn5LdtESJE0TjpfTNMv4yInptgxWLIYzaXMEbSsQbfEp2O/9B9HoybAaMzBTNQjlt+bbdP/5i+bAWDgTWDYXUd0YuTiUfmNn3skIfFiNzQiqRiNaOb87f/bakg5sMmpcKc4aJszqOiBRo8eB7grJ4+XTQOjr9VCPFy+LMF6LoGoUzEKH7sNI4rEetD4QmIBl6/Y108s1HUYmj6B6jE4v+0O/y6wEUvW6bsPLAU5pnY4JHedJDA8jaFgPfMQKbVgaVWF01ShNV1DbLCeJbm/JP6qgqL/RkmNEjiPZ94Gn+x0dyxGOmlZKgxOHHUvoNHJeRLEUIjum08rfus9sV9Ml54sc52auTfe5pF3Gy3R6DHfmiWUby2/Vbbl0NtA0FWHbCj2GoiDQ7aTbfeymCN55Vo8hXU8xB6TqpIZR88tGXTOM1sUwkrU6r2xzf8l8mMlqGIW0rlN/c8fS0v7oWI4gn4FpuQhblpXy5okUjER16fyUbeQXEVk2DBnvOIj8zmMjivR3y29qDyzUuXE9P/0Vi2A1ji39VjlXi7LPq2Hk03ocR4W8HisyXn+/bG8npv+bcv7HazSvrtccWYZpaqssOa4kfxe1LgWaEpq+rm0q5Hoh6ZH5dJxen3y9lhheQddhFtIIDbN0XYlXw+xYovtGj0G5pvkF2MW0Xpf0elHM6L408x1aXtHrWAXG7qGKsXtgY3dgOigEpfJNm2+i1vT0OmLKcY0EIjepZZ4a14QpR7icy8UIKbmmxmqRN2OIhz6qjBCGxBe79K4zOU8yfoRquZ7LeWLlAC9fOneDop6X5uJZMBK1CKtGAbEUPNOFZYTIeSFqY6UY0u4Bllk6ntPFUPPZ7YUA9ZJG6V5v+wl4c1E7pJhVJXls1CJ0ErCzLRo33VETkF7YhuaUDaOQRSxeo9dKvZbKzzFtjInbiNISV1y9tgVulV6rXcvRPHmVayLrhUgk6uBn/NL1yHJgFrOwzbjG6JgJtBdDNKSXoSh5A8eFXz1G8xqGrihEUeONgSJsGIZX2hFSzqwZg7Z8gGQhrdenguEibTqoDjpK11G5FslgOQg9wBu1Caol/9C+GEV3DJzlb6M4cQedxpFyouQnqptgFdJIRSaKKxfCD6vR0DZLr09tUnZLJmH5oV67JjdWoS2TQ71RwPIwptdCKQPLtVaPN7capsQXuWTGa1FvWAjtuu79XAxcGFGxtO+jsPsaKN9J3HLDYilmy3VVlifXZMNEXOK/4SCQ+VKNsEKvtB6JY5JfyKyAV90Mq5ApxXWN34buG1O2i2khZpau7RKHYDqIJ1L6W1Lti+A0TkNoxzSvlZMybhTqOmT/ZwMDrYUAY6scmIGnx37SKVViJhwTUWRrLFzclkHCNlH0QqRsQ49p+azXYolHhoFCajRcJ67HVNGthluUfEtMy3pSRkwh0H0XJOp1PvkNkk+M10zTbdueD9EYN2G3L9bzI27H0VYItfwoy8j7EWr9VuTMWv0tcmZI2bFgpZArBKg1bZ1ezmE5XmUeSbvVvhi1neWx+rgFx5Byp4fIjGlstYy4Tms5Sdh+HmYUaBplGbFsK9yaZs0fGe1Ldb9E8WbUmEW0GY7G3YaEDchPlXoJI9R4KWnQfJHE1c4yQNqIoyosIDBcTX88LOi+C2WfBwW0BTaqLANBGOr1Jxe4SMBDYMT0miPxzLVM3TeWl4VtS94qpmmTekJdDyz9LNeylBWV/pfMnmwrA93lbjmXhVxjkpJ/6Hy8Ss6DID8wcZOx++2yl2n7VDEuttxySx2kD1jp2mRdLyQrF6mQ2HrrrXuN22qrrXD33XevdZ5yvLyNiIj6R/IGnfmDPk07UCRGfPazn8UJJ5yghTnP83DKKadoBbH0Hy4WLFiAvffeW7tL2XnnnbW7lNtvvx0HHHAAGhsbtY/x0047Dbvvvju23Xbbj1znxz72MW1pNRTfgcHYTUREQz12DwbG7t5Y7iYiqgyM3R+Uvdzd54rxLlIxLpYtW6YvJhNbbLFFn1ry9dcnPvGJ7nV0effdd/UFaURENHSE/Wh11tfp1tdtt92mleFS+W2aJr74xS/iV7/6Vff3UlkusSWbLbUadF0X//znP3HFFVcgk8loayeZ56yzzurT+i644AJ873vfw09/+lNtpZ5KlVqgdJFuYgYbYzcREQ3l2L2xMXb3xnI3EVFlYOz+XtnL3f2uGJeKBKlwuPXWW7V/tq7H0Y4++mhcddVVZW1JLi32dtttN32k6/DDD8dzzz2H3/zmNzoQEdHQ0Z/+Rwe6n9KGhgZtAb42U6ZM6fVIuFSE/+tf/1rv9UlLcyHdlfR8OXXXy6q7YuVgYuwmIqKhHLs3Nsbu3ljuJiKqDIzdKHu5216foCkVCPfff7/eWRZPPvmkvhRTXo4mL8ssl49//OO49957tf+y888/X5vLS4u+o446qmzrICKiDTeS71w/9thjGOoYu4mIaFWM3UMbYzcREa2Ksbv8+l0xLv17//nPf8aee+7Z6457IpHQVt3lrBgXn/vc53QgIqKhayT3dbbHHntgqGPsJiKiVTF2D22M3URENJRj98qVK3HqqafiL3/5S3cXpldeeSWqqqrWOr108fnQQw9h3rx52iX3wQcfrF2j1NbWDlq5u/QK1X4+jj1mzJjVxjc1NXX310pERCPzznVfh+Hm3//+N7761a9q91/yck8hXY7JE1VDAWM3ERGtirGbsZuIiCrLUIrdRx11FN588008/PDD+Otf/4onnngCJ5544lqnX7hwoQ6XXnop3njjDdx888148MEHcfzxxw9qubvfFeO77rqr1vDn8/nucblcDuedd55+R0REI08YRv0ahhNp0bXffvvpk1MvvfQSCoWCjm9ra9N3ZAwFjN1ERLQqxm7GbiIiqixDJXa//fbbWql94403YpdddsEnP/lJfe/kHXfcoZXfa/Kxj31My84HHXQQNtlkE3z605/Gz372M21x7vv+oJW7+10xLn18/+c//8GECROw99576yAvLnvqqae0yTwREY08EnODPg7DrF4cF1xwAa677jrccMMNcByne7y8h0MC9lDA2E1ERKti7GbsJiKi4R+729vbew1dFcob4umnn0ZdXR122mmn7nH77LOPdqny7LPP9nk5UqldU1MD27YHrdzd7z7Gp0+fjvfeew+33XYb3nnnHR135JFHahN6qbUnIqKRZyS/BGTmzJnYfffdVxsv/aS1trZiKGDsJiKiVTF2M3YTEdHwj93SmLkn6QXk3HPP3aB0LF68WLvU7kkqtxsaGvS7vli+fLn2L76u7lc2Rrm7Xy3GPc/T5u5z587FCSecgF/+8pc6fP3rXx/6leKmhciJ6f8IQyDwYNSNgWE7MKvrANsFChkYblynkfGGI0MMke+V/k6kSn8HHsJMOyLT1umt2kZExTzMVI1OF4WBrkOXBej/hmnqvFaqSqcNPV/HFVo6dJowCODU1yPIFxEUPfj5InIr2lA9aQySzY06rZ1wdYg8D+PPuR6mY+O9k78EL5NHWPRgp+Jon7cCxY4svGwegReW/s7kdXl1J16IeGMNDMtEMeMhXp9CsT2j42RZsZqYpiWzeEX3ZkuOSuLVw/fHK1/cDy8fvC8s10YYhKidUI1cSx5V46oQFAOsfH8FnFQcURgivazU17wVdzHnmQXw8j6iIIRhGXDiNtyko8tq3m4MCu1FeGmvMz1x5FZkkFueRS6IYMddXeayNxbAy3hIjkrAqXLhplx0LEojLJaWK8uXNHR82KrzZJfnYFom8i15/a2a5mKAIO/pdi+0pOG1Z1BoL+hvmfPDY3T7epmcDlYspsuVaeX3yDj5XraR/B0FAYKWpQhalsmOKx0Xxbzu99L/ISI71r3vo1gVzGIOsCyY+Q4YfgHwi3AQwjAMRJ138iwTcC0DxSCCZRoIOm/vdRQC/b/KtVHwQ/27Le/DNA39O+cFWJ71UJt0YBoGMl6A2piNsXVxXY5wbRPpvI+EY+HG5+aiKm7r8GFLTr93TBONVW73eoPOC6gsuzHl6nx1CUe/q47b+NrtL+l3uWKApGshly6iLVss7XfT0KHoh0i4lg46X9KBZZfSEwQhbMfsvlB/8uLHkKqJIa7TmDDM0kU8FneQrInB90KEnW+OiMIIXsGH7ZoYUxfX7+TvrseEsu0FnUbEEqV7f3VJBzW1MbiuVdovhoFkwtH5JH2+F8C1LU23/FZNf6H0KM+KTFHTL7+nLumiLet1b6emmpiO78j7GFsb12ktw4BrmYjZpv6v53cY6f5KOhZqEw6WZ2U6wOtMp/zWtrynf8s+lmVUuRa8MESmGOj/sk/iltn9vexa2wISjqnHjoyTZer2LR0mpW3Quc2FrM/pPCbKTdLXn2E4aW5uxvvvv7/aeOnnbNq0aRhslRy7zUKmFK+9LIxCWuOvMEIfVscSGIUOvbZGTul3GMUMYNoIYyn9HCbr5YTXa27kxOUCAiOeRCTfmzYiw4QRFGHWNur/pYtPWIrTrcsA39N5w1ymlJ58h05jFHMIVizWeSKvAKN9GaJsW+malmnRaSRNmma/dG1E6Ot4My7rtgCZ144hjFdr/kBiRRSrRsvorYFUPSLLRlTbXFpvthVhvKaUPr8AY9R4Xa+kW/Iiwmps1nRLHLEmbK55E79xGoJlC1Cz9ZbIunVwttkVoeXAaFmg0zmWAXv0eNhjJulv1fxMLgOrY6nOJ9tI1lF99LkInaTmcyS9NR/fTafVbR74cMZvIhd2hLFqFJavLOV7HAeml4MRS+h2D9tXIqgeU9q+sWr9jRJDg5pmmIkUJBhGbgKhmwJqmxDmS9tcto3sx678muad/BBe0+YIqpt02bo9ZZvbcYROQrerpKEQq0XKinS8EYWw2xZqzJV9I8eIxuMo1ONMvtdjJ1mPsGoUvIbJCBO1MIpZuHVNMIsZ+PE6hMm60rHSuU6ZJmkbyAeRLs/1c3rtlzghnyM3hbq4haJhd6bV1u0Cyy2lI1lX2v92rPR7ZLmdx2rkJvXYMzuWAm1LYQYeoqoGTavh5UrHWOc5Icem7lsv331s6/Evy5FjJPSRMeKadtlnki+R/IqZb9N9avh5PabNzAqExXxpe7qJ0rlT24zIcjVtYbpV92GwYlEpH9x1/qRXAtWjELYth1ldr99FhRyifKa0nTUNpfyRLEvy11Z1ne7vsKOldAzUNpXyT5aj88oxL8eKIemQ7SLHm+2UzmP5/b6n8UTP17YVpXyZntuWLqP7nJV9Vl86l8JUQ2mbyfko20Z+5/IFei2JOueRfSpD13VF2GOnwUxVl9Yt524sBau9dA2Q7WfK/FKWkG2bbencXjZgO7of9Poj1yKZv5D+7/Y1zdK1QLaXXA/kWJfzRq9ZydL26rxODQTGbsbugWD5+e4WjTVuKS+c72yPl7BNPd5Tjol0MZDSkJ6TMpVce53IR9brPDc745tcn4ScM1VmoOeG4RVK1ws5h+Q6nmsrfZZyeOf1Qs5/KVc5JjTeVYWlMqrEv+U5H+3FUhlLppH4nfFC/e7qp2ejOmZqGqVspeW30IeR79Br+8qO0nI0ux1FsFsXaFollmje3nYRN6NSjJCYkqwrnf9BETWmh5gJLMtKuUy2QViq5Iql9Jon1w+JKZJdbymEWp4onaxFoLoR7Ygj74dwwqJeZ0YnbVheKT05rzOPY9rosGuQ8yNYk2foNVjKA5I02dZFK6ax0k+N0u/itgFnxWzdDlG8GnHLQJSo0XyWPWEbJGUDyjVK4qflaHkjTNTDNY3S9byQQVshgJVrRSKSa1cC+VwOMSMsxVbdGVbpWlbMIIxVIda+sLTuIAcfZulaZMcRj4rIWwlNg8QjXW7rQr2my3VaYkaQaoS9Yo7GV71uSpzwCzq95hfleIgCXZ8eP3JNlZghMT5eo8enxkLJmxgWql0TRSdVij0yjVGK77IvZNt6S2brb5F9aeZaYEtMBvT4kPxFYJau8ynDQ3OqswVrGOh2k+NHjhnZz7I+mb65NtVdHvM66wHsYhq2HFGBr8eh/i3TOwk9j2RfyCyyTG0JbMchZ43kE+K2Cds0dDu0F0NdpuxTie+6v+3OPLJRSnPOD0vbtW2xLs+RpEShnlt6jsr+RmkZK/N+d/lS42Q+g4bMh6VjojP9VvsizSOFblKXL+eADF15Lz1HOxMgx6ic45KHkHNK0q3nlmHo+VUMQvg1zbp8+X1+rAZ+GCGXaETecGEW03rMSRqDWJX+FjlnS9eJgu7n9tApbbOwVGZvCR1dTzpy9Joj28WTZMl1R2Y1SttU47Dsus64m0JRzyG5ZhWizjJ9BF1nV0k2kvK5HPNyPBgefNk3YaT5VM2TDlCRd31i9/z587Vldtdw5plnrnX5Z5xxRmmfrGPoaiS9IaTl+oEHHoitt966z5X0A1Xu7leLcWmq3rNvcSIiItGfPsyGWx/jUtn87W9/G7/73e80oyB9qsmjZd/73vdw9tlnD3byGLuJiGiNGLsZu4mIaPjHbumqRIa++O53v4uvfe1r65xGKqGlknrp0tKNoi7ST/jKlSv1u3Xp6OjAZz/7WVRXV+Pee+/t1S3KYJS7+92Vyje/+U1cfPHF2sF6X/qAISKi4U/aGHQ26u/TtMOJ3FUPw1DfuZHNZvXxrlgspgH61FNPxVDA2E1ERKti7GbsJiKiyjLQsXv06NE6fJRdd91Vuy958cUXseOOO+q4Rx99VMvF8jLOdbUUlxdoSnn5/vvvRzxe6mljMMvd/a7Zfv755/HII4/goYce0j5LU6nS48pd7rnnnvVODBERVaaR3E+p3K3+8Y9/jO9///v6aFc6ndZHwqqqqjBUMHYTEdGqGLsZu4mIqLIMldi91VZbaatvacUtL8SU7jtPOeUUfPnLX8a4ceN0mgULFmgl9i233IKdd95ZK8X33XdfrdT+wx/+0P0yUCGV8ZZV6gprY5e7+9XHuJC3jn7xi1/UGn75sdLJec+BiIhGnpHcT+lxxx2nj4O5rquBWYK+BOdMJqPfDQWM3URENJRjtzx6fdRRR+mj3hKzjj/+eC3wrsuee+65Wr+nJ510Up/Wx9hNRESVaCjF7ttuuw1bbrmlVn4fcMAB+OQnP4nf/OY33d9LZbm8MFMqwsVLL72EZ599Fq+//jo23XRTjB07tnuQftAHK3b3u8X4TTfdtN4rIyKi4Un6L+t6YWxfph1Ofv/73+PnP/+59pHWUy6X07vj0gfaYGPsJiKioRy7pVJ80aJFePjhh7Ugfeyxx+LEE0/E7bffvs75pKXa+eef3/05mUz2aX2M3UREVImGUuxuaGhYZ5yeMmWKvqS05w3tnp/7a6Bid58rxqUfl0suuUT7gCkWi3pH4JxzzkEi8d83thMR0cgU9CNA93W6oU4e+5LALoPcue7ZP1oQBPjb3/6GpqamQU0jYzcREQ312P3222/jwQcf1G6/dtppJx131VVXaeuzSy+9tPuR7DWRivCPeslXT4zdRERUyYZK7N6YBjp297li/Gc/+xnOPfdc7LPPPloZfuWVV+obSIdCSzgiIhpcIzFAy6PeXY9ub7755qt9L+PPO+88DCbGbiIiKmfs7uoLtIu89EqGDfH0009rTO2qFBdS5jRNUx+5PuSQQ9b5GLf0UyqV4wcddBDOPvvsdbYaZ+wmIqJKxnL35mUvd/e5Ylyapf/617/GN77xDf38z3/+EwceeCBuvPFGzbQQEdHIFYR9r/CWaYeDxx57TO9af/rTn8bdd9+tj5J1kX7PJk+evM5WbhsDYzcREZUzdk+cOLHXeHmCWBpPbYjFixev1tLLtm2Nq/Ld2nzlK1/pjrWvvfYafvjDH2pfpvfcc89a52HsJiKiSsZy991lL3f3uWJ83rx5+jhbz7v4Uiu/cOFCTJgwAUNd5OWljT0iOw7DcRCFIWCaiHwPhu0AdgxRMafjDScGw3ZhmBYQdH3vwnATiPJpRJYDmBYMP4/QL+ryzao6wPcQFfOIPA/WqGaEuYxOJ/PayQSMeApoWwGzvgn+goUwXVvX52VyCDwfCc+DYZkI5HO+AD9T+l6mC/JFhEGIQmsasbpWdPziVMQba3W+mqY6FFrScKuTqBpbCyvuotiegWkZiIIQpmPr5/lnHQ87FUf77MUwTUPH51syukxRaC/ovFEQISwGyCzt0PTMuOvveOGAvbHT3x7BzBMPheVaaPuwQ5c9afep+OCh9xBHHLmlLXA3GY9YtavLyi5tQy6IUNWU0rTbcRthECGdLmKsa+nnlg9a9f+qpiS8jAcv75em8UMU2nMwMwVYjgXTtTBmRjO8TAFOlaPLbP+wDX6+qL8zLIaI18dRM3Ussisy+ntqJ9eibW6b/s7ACxCvS+o2S3+4DPnWLNIL02jYfBwKrR3ImybijTXwMnn42dL+KLZnkZowFommev2tdk0N8iva4LW2/ve4KuRLx0KyRo8Xv2UpDDcOS44Z0wbCAJBHPgxTB9id/5smjCiEa1nI+b2PVccEsl7U/RbhpGPBC0NYJtBW8DGpNo6OQgDHNBCzLVgG0Jr3YJmGTu9apo5PuBZitqnjpdDj2ibSxQAtOQ8NVS7asqV5ZDqZT6bJFgNUx22syBSRKwawDAOja2I67dwVWUxzU6hNOviwJQvLtPTvd5cEiCcdXZbMJ/N35H3UJR0kXBuLWnO67qIfIpsuYlR9AoZp6CDz2Y4F3wt0Gtk+BVmvbep4qXSsSjpYDiBR5SLTXkAsYSPdmkcURij4of6fTDhY4YU6jwxOzMaoxgQWL06jzbGQdC1df2OVC39cNezO9cg1TNLZkSliQn0CRT9AW85DVdxGoeDrfLJdurah/O+Hkf4u1y69MVnSLb9ZtoX8vbS9oOM3G1OlfXq1y3KSLhJOaTtLmptSMazIFlETd3QfeWGE8dVxpIulg0HHBRHitqmBT9Yr+0J0vUTDNg05tCCj875Ma6CraCubUr6TeeXv0nFlwAHQNkCttUfines99thD/589e7ZWFAzFm8SVHruFWUhr7I5iVUDoA24KIZKAYWocNvIdMOw4zGwLwkStXmPNQgZmMYeguhqRxO9kLYxiVq+7qBmFyHJhFDIwvBxCiflyvZZrupsE0suBVD2Qy8BomoRo+QK9ZodOAtaKeXqtj2rHwKofDUPSEwaIvKLmA9x8i8YAFDIIRk2F1bYQYbJe12sUc5o+K5ECEjWA5SKSE1h+RzyJyLIROXHIma6/w0kC2Rb49RM1sybr8kdNg5FrK6W15V1YYzcBsq0IRk2BWegAOlYg50UInaQus6UQoqF+dPe2DKpGwyqkEWbaYUQRikEE6RAvnLYTrJXzYI+ZBLO6Dn68WmObTO9M2hzhrOeAqtH6G/1EPaxpOwDvPougdlxpe1u2/j7ZTnE5F2oaYCRSCAul/IXsP81zyXL9oi5X8lf2+E0QWC68sdvAnvsiTDeBoKYZRuuHsOqbEMlvknkMU8eH778Gf6tPoXm5ASu9DEGqEYEVg1U9Clg6F0jU6nGg64yl4EY+zI6luj0NLwbT92DnW0v7WaaxXPgw4ViO5u0iJwEzs0L3QxSvQ+Sm4CyZiaJ8lv0fFGDm2kr7tJjR5ebgIBEUEUUWzHy7LtuMAo3vkZuA4RewwjdQGzP1t8s20G3mZQHJK0j+QNIv+6d6DMzMytIx7ecBzynlK1ONsDIr9FgL47U6jwxhvEZ/rx6Hcq7IMe7lYASepl3Ol8iOwSikYXo5JOOl88MIPYSSp132IcxYSpcp+8+IxRHGq2G6cd02erzIvm/eBJBjOBaH1Ty1dCwu/ADp2smoMhcAi2fBqG9GUDsWtpdD0LIUZqoOVuNYzXOHcqzHq2G88yTMiXEYXr50Dkq+WOLo5tvDm/O27k+rY1np2JiwKQLJbwu/UDon21YgTDWUzpnQ1/x697Et65TzyE2Uto1cL6IIYdtyhNl2GJv/D4yWzgrWoAgz36H5NP29qWotD4SGhaBlGVA3HpHhwIzaNA9vtnXodpRjSveXXI8sF2F1k24XPb79oh4Xsp1R6ND0yTT6OwO/lKZEHSwpV8jvicLSsZRq1H0YmTZiqWoUAg9W+yLdf7oMN6nXLjP337znYMdueTmWvCCzy7pai59xxhm4+OKLP7IblfUlfZB3mT59ur68S7r7nDVrFjbZZJM1zsPYPfDkelrlmJrvDWHADn2YVkzPBwTQa2WQGKV5WWEERbh6vkcoGjZcK0IhMhAPCzDk3ErUlZYrscB0YEnctRw9l+Q80XNIyuFybWgYq9cMvUbHUiiGEWpcC6Ys20nBNQwtD6ULIRwpQwLoKPqa55a8tuS545aJuGVoPLZCT6//oVxLg6KWu+qqkvDDDNoKIRpNC17VWDhtC3S9rmXAzLbpdVyuM4HkMaIQoZtEEK+BlWtFe+gg64X6t2nXIOGYMLMZtDl1qJZ8QscSGMl61LsS/UO9Tlhti+E3TkGNGWBJwUDKDpAz41JY1PS5npS3LBjjNtNt0lYwtQyQzeVhJ2rhmgY6iiFqYyktNyRXvodc0xa6T2JSZ2DHkfZCVBmh7CKt14AbIZj/OoK6TRC6Ml+IuB1DbZgFPCDpxOHHJ8Bu/RDNKQfwS2VwuZ75EeDIfpB8gGy/WJXGJqNlISB5h1jpGifXQtsA2iVtRqkMVUSEOuT0O9mest0lNkvM0+PFL5TyS35B82aQmC55M73uhxor20P5/QaqghyKbjXcYrYUxzrjomxTOV6kDBaHj1xkwZZ8iuR9QjluAT9Vyj+5MR/ZwEC1V0qfFL7kcihpy0cxxKJA960psavQruuzJMZbMT3u9JgwgNAoxbx8Lqf5ryCSzSxlfENjiOekELPd0vSFdoSxzj6UI5Riv5YDofOaRqhpSHQsQZicpPPI7467hv5uOXYLVi2S6WU6Xc4L0Yx2LPZqUPQjyO5CpgUJrwNuXROyMDTNsWIbsvEGLPNdWGYEU85fhMj5ncdh62KNdU7kwyhIbIyX8g+FNIp2CjEjhJSGZBvmrYSeL3aiHjHZL9L1lRXBgw3zw1lwp21f6ms69JGKmzDb0sjHm2CbpfypRJyucmxa6npsQ/MlhpeFnVmBFYlmpJzSPtR9K3mLWJWuUza45oesKr0WSXpXFDvrSuI1cIIInmFrOuX4glmKY44BXZ7Tmc+A4eo1wOw8pqUeQM4XIf8FMBCYMTidpXD5V645tTEL8Et1BQOB5e6JZS9397li3Pf9Xv24CMdx9OUoREQ0so3EAN1F7lALedu2VETLezh62nbbbQcpZYzdRERU3tgtleI9K8bX5bvf/S6+9rWvrXOaadOmaTco0kXnqmXPlStX9qv/8F122UX/f//999daMd6FsZuIiCoRy90oe7m7zxXjcjdHMjY9WwXk83mcdNJJSKVKd7/Euh5dIyKi4WkovR17Y1u2bBmOPfZY/P3vf1/j9/JCkMHC2E1ERIMVu0ePHq3DR9l1113R2tqKF198ETvuuKOOe/TRR/UF0l2V3X3x/9s7D3BLijL9vx1PvDlMHoYhSxIQEEygKKBrFkUxIIoRFUUR14gLC4IBUYyrAv8VWRO6iuIqAioiIohkFEEYmDxzw8md6v98X99zmQszwwxzU8+8v+c5957TXV391Vfhra5Tp+rWW2/V/zJz/ImgdhNCCMkifO5+86Q/d2/xwPib3vSmxx17/etf/6RuSgghZPtCl3jZ0lln8rO57YhTTz1VH+hlg7AjjjgCV1xxBVatWoWzzjoLn/vc52bUNmo3IYSQ2a7de+21F4455hicfPLJ+NrXvqa/SD7llFNw/PHHj68Z+sgjj+gyKbJ3xiGHHKLLpVx22WW6XFhfX5+uMf7+978fz372s7doxhi1mxBCSBaZLdo9E0yVdm/xwPh3vvOdJ30TQggh2zc78k+6ZFbbT3/6UzztaU/T9c7k59nPf/7z9afm55xzjm5UPVNQuwkhhGRBu7/73e/qYLgMfouWvvKVr8SFF144fl4Gy2VjTfn5dHuzrd/85je44IILUKvVdK8PueZjH/vYFt2P2k0IISSLzCbtnm6mSru3eGCcEEII2RQ7skDLA/ng4KC+7+np0Z9n77777roR2C233DLT5hFCCCGzXrt7e3t1BvimWLJkSbpR2xgyEH7dddc96ftRuwkhhGSR2aTd081UaffkbuVJCCFkh0R26d6a1/bEHnvsobPYhP333x9f//rX9Sff8nPwLVnnlBBCCJkJqN3UbkIIIdmC2n3vpD93c8Y4IYSQbWZH/ub6fe97H1asWKHvP/nJT+o6qfKTcPmZ98UXXzzT5hFCCCEbhdpN7SaEEJItqN0rJv25mwPjhBBCtqvdsc8++2xceeWVuPXWW1UkZYOOJ0J+ni3i+s1vflPDP+MZz8BXv/pV7Lbbbpu85oEHHsDOO+88YSPqgw46CA8++CDuueceLF68GP39/ZOWLkIIIWR71e7pgtpNCCEky1C7J/+5e4dZSsXy8rCSCHAcwPVh+QUYywaSGHA8JJX1sLycfja2CyuXB1wPsB1Ypc70uGXDhAHM8CpYfh4maMKyHY3fLpRgFUowcZzer9Axdj69h5xDFGh88ZpHYPsugtEact0dGt7vKCJu1BHWGojDCLbnImq29H9z3YiGz3d3IKo10nONAK2hChzPRXFun8YR1ZsoDPTAxMlYnHm4eR+2YyPX04HWcAVxM0BjqIlcVw5JGMHxHQz9/RG1sznaQmuoCtt3UFlRhYkNvLyLe9/2Cq18d5zwInilvF5T7C+gNRqk6ZNvWAouWqMNrL3tfjieA8u2UFtdx/ydujS+uBmi0JNHrtNHqeCiKTZ0l+GVvNRfjo2gFiKshoijBCNhoteHzQgjD46gY14ZnTvPS9PSmdNrWqMt7PWd/x2PQ96HteZ4notv3LyL1nBV/4tf66uHYJJE7QtqgfrKyef0/uJjib/y0CrNx+b6EVieh6jWRFCpIWnW4XeW4HV2wpJylMRI6pUx+9NyYkmZ2RDHgxU107Jn2bDiCHZYB2xXy1MjTFD2bDgW4FgWZOlEy7LgOxYKng3JylYcIzEGYWxw/P4LYFsWHNtC0XNQD2OUfRe+Y+sxT9IVJxhtho970JHzI60Qg+Uc+ot+WkYcG3k3LcPVZoQgSvS67oKn4WUX4/XVAOW8q5/lfH8pvVbCFSRvE4Ni3kVvKQfftbGwp4ilA2UNU86l3711F329Xmzfqa8EP+dqPmuYoqef641Q45e4oiBBsexjoL+ox9r2+zkHcWQQhTFajdTefMlTO0qdOczrzmvexnGidrhemraugo+FvUXM7SpgyWBqm+vamNdbgO86KBa8CWmSeHM5F11FH70lH+W8h8HOPApemt52uiTc0oGS+qcz52JOZ15tGOzMaX7atoWSn56TPBYk3/qLHnJuWnc6pD6N2ek5NppRAsuC5n+YGDh2apeUDSkHedfW895Y/gRxms/N6NH8Fj+7tqXh2ueTKd6ZWnfH3orXVBIEAY477ji8853v3OJrzjvvPN3kS36GJbtcl0olHH300Wg2H21THssuu+yiA+MnnXQS/vu//xsPP/ywHi8WizjwwAM5KD4JxOV+WFFL21HjF2GFLRjHhd2qwuQ7YBwf0ZpHVLflfeKXYPwCEjlnu0AcAiaBvfRpsIIaEIUwXg5WWEfcNRdJqRdw/FTfm1VYQR1JuR9G+gy5POKOOYhH1ul10o6L9ie1USS5DthdfbCChmqB3dGr9kobnzRqaV/DsmE3KxqX4nho5Hr0+qh/aZo+qdtuHu7+L9DwSCJI7TC5kt4v7pynOiFpRRyofcbNpf6ojSLuWTjmpwG1ycoVUfZtJMUe7Zf05Gy13+7ogUiChKnYRe2H1CKDNfUIdveAHtP05fKIBnbBalPW9LlDyxDP3UN9awdV2KUOVEIDuzmqfSTjpnqgtgOaPndgAeJSH0znYJoH+Y5UB/08rFZVevPwl90Cp7YOTu9cLK9FGEm89Lz40xjNv6R3ESyTwLgenNEVqQ9cH1WnjJ2lrQ/qarO0k5LHJgowWpyjx+qlOeNlyBS60vOqwQEQR+pD6ZOJn+riXy+PpNSHxPHU5obfpe2UFTY0r7RfGNQQOzm9Rq+XuN08inFdj3fl7LRfKfkkZS5sql+M42l7rG2++EvSV+5H4pf1enVfZS1g25BmPO0vWFqWpKxbux6s/tEyI/2EXHqdJWXLGeunSrkQG6X8uPk0rUENSaEHVhxq2rQetCqwohBo1dL/tq22yktIKsOIexYD83bVMqi2SZnoXqj+dzq607yOQ9idvRhqxkgKXYjXrdB6FeXS/nIysg5R1wLtQ1n50qP+dz1Y6x+GWb8CrTl7aj5L/dZ+cq6Q+tQvan5rn/nuP2h6tY47btoX90ta/sR/cm9f+hblbi13EofWOWkLJJ9yJS0Xcl7bArEtl/a75dpkaBXizrnp52K3liUp46khCRJ5VvAKWp7FV5oOr6D/1dfS7kh91H6djQg2Gm5Jw0g7pMclrKYx0vd6L0l32BprPyIkYme+A+Gah9I2qGMOkkJ3akeUlqd2HduetXu6oHZPPVLmpc9aDRP9L2Vf+sWqM9IfjkNI99RzLDhJqNfIs4+E0+cKz0ZL+sMSPmql9cyytF43ogRNO22D5ZlK6rw+V3XNhRl7Ltc2WuqM46Pg2mpDM077zDYMGpFBybeRcy105dJ+eWfO0eUJ5N7Sz5fwXtRQXbCra7UfbqLU7ujhO9VeCSs60b6n1H19nhP9b4wg7hxMbXN8WGEzfc4Lm3ofsSv1C9DjpO2A6L3f1a/ttgaWTWdluMaytd2Qtq9h0mcR6VMUTIBaaDDUSuCu+xfmlz2Mdu6k9koQeVZwg6pqRUdzbfosEgXo8NK88FsjaX9iLN86fVs1RNIWzHuK6r60mSU7ht0c0TDiS0mn6KkcV9ukzyFxj7WJ0h6KryVuOS/Pps3O+em5sX6D+ET8pH2XONDnPNWzqIlqEKeaFTTUFkm79MecyirVSWm35VjdKaIeW6k9Y31FvaftqO4W3fThyw8qgOi85aTt9thzuCA+am4wV3SklY7lqI1jz592dY2mT+yUV7tfZyUx8ibQPHKao2PaW9frpH33YrGppfkteSY+b409kEn5kuPysRYm6jstO9LfknGB6hrVFPGf5FuSK2v5kHrh2UAZQepzfe5Ln/0k7V15B3bUgiRdTideUe8tfRDRz1Zk0FNw9JzpXZjmz9BKrG1E434U21zHQs6R+pHa0JN3tGwkA0vH9cyKAqyNJU897V9oHdZnXVvrSTVI4CJBAgt2fSgt05aNSpDA7ujWciP1WuKV/oT0tbXManrSZ9uclWidL7iWhpE0BPlU3wUpZ3nHQtMpaHxSL0pm7NnNsrWNkXyQPJc4JD+lbJR9Z7zcq67rs7Kl5VzOSzlLtD4Dse3pZwkv9U3SJOkbe8TW8lqPDBJpp8YGWCWpNePp/acCavd/T/pzN2eME0II2a4488wz9f+W/pxKZotfcMEF+NjHPoaXvvSleuzSSy/FnDlz8JOf/ATHH3/8JnfFvvbaa/X1ve99Twfkly5diuc+97k48sgj9SVxEEIIIWR2QO0mhBBCssVvp/i5mwPjhBBCdui1zuRn1StXrsRRRx01fqyrqwuHHnoobrjhhk0OjB9xxBH6EmRm+R//+Mdxwb7kkksQhiH23HNP3HnnndOWFkIIIWRH0O4nC7WbEEJIlqF2Nyf9uZsD44QQQmZEoEdHRyccz+Vy+ppuZFBceOy3zPK5fe6JyOfz+o31M5/5TP3G+pe//KXuki1rnhFCCCGzkR3x4XpDqN2EEEKyBrU7P+nP3ZlaY/zcc8/VdYhOPfXUmTaFEELIRgR6S1/CokWLdGZ2+3XOOeds0qdnnHGGtv+be83EILT8jOt3v/udLt8iwtzd3Y13vOMdGBoawpe//GWdjb6jQ+0mhJDtR7u3B6jdTwy1mxBCZifU7jMn/bk7MzPGb7rpJv0WYL/99ptpUwghhDyGWDdMam/x+cRhhWXLlqGzs3P8+OZmi5922mk48cQTNxuvrDP2ZJg7N918bdWqVZg3b974cfn81Kc+dZPXyTfVslGnbMD5nOc8B29/+9tx2WWXTYhjR4faTQgh25d2Zx1q9xND7SaEkNkLtfs5k/7cnYmB8Wq1ihNOOAHf/OY3cdZZZ820OYQQQh5DshWzySSsIIPiGw6Mb46BgQF9TQUysC2D41dfffX4QLgs8yKD3u985zs3ed3vf/97FWN5yJY1S2VwvK+vb0pszCLUbkII2f60O+tQuzcPtZsQQmY31O4jJv25OxNLqbz73e/Gi170ogkboxFCCJk9zKafdD300EO49dZb9X8cx/peXvKw10Y257jiiiv0fXuJLvni9X//939x++23441vfCPmz5+Pl73sZZu8z/DwML7xjW+gWCziM5/5jIbfd999ccopp+CHP/wh1qxZgx0ZajchhMxuZpN2TxfU7s1D7SaEkNkNtfszk/7cPetnjF9++eW45ZZb9CddW0Kr1dJXm8du7kYIIWTyiRLA2sKHZgk7lXziE5/Q3anbHHDAAfr/mmuu0Zndwr333ouRkZHxMKeffjpqtRre9ra36UOzbOZx1VVX6cZcm6JUKuGYY47Rl1CpVPCHP/xB73PeeefpL51222033HHHHdjRoHYTQsjsZzZp93RB7d401G5CCJn9ULsx6c/ds3pgXNaffd/73odf//rXmx2c2BDZvE02QSOEEDK931zbW/hwPdWzzi6++GJ9bQ5jJtogs8Y//elP62tbHrZ7e3v11dPTA9d1cffdd2NHg9pNCCHZYDZp90xB7U6hdhNCSDagdmPStXtWL6Vy8803Y/Xq1TjwwAM1ofK67rrrcOGFF+p7+Yn8Y/nIRz6iswDbLxH5caKWLMijbxO/AMsksFwPxvEfDVPshhUHMI0a7EJJz0kYK1cErEfd5XR0p2/k+ijUt1a+rNdYjqPXOV19sPIlWH5e40iaddhj14W1BrxSQf8LcTOA5aTxmziBSRKU5vUhqjXheJ4ek/O57g4kYQTbdxFtcI18nnP6lxDWmxrW9j0N1xyuI5bwtq1h5ZqgFiCohmisqyKohfpezvklH/WV6/T60mAJxcEyqqtrqK6oIKyGsNv3jxM4noNcp4/KI0OoDjX12rAWor62jo75ZRT7i/BLHmzH0vjknrIWkuPLdTm4eVfTPPpwBXEQo2unHv0v4QrdOQSJ0TBhNcAjyytwfBvhaB2FwW44no04jBE1I1z/zGehNRrA9m38833Ho7luBK3RFlpD6ZIJEl/bd2EtwOgDK+CV8mgONREHCdxSHqW5vXo+CSIUBnuw/p5l6r+w1hz3rcTnlDpSH8pyDLaDuNWCnS+meduowbJt2B09sEsdSGqjMI6XlhEpN1LWogCwbS0bxs0hsRzkXRut2EAeNSwLCGKDKDH63oYFyV7PttOXY+H3969DyXdQ1peL3oKHouegEcYo51zYtoVGEKMz78GxrfHymncdbUA7fBf1MEYrStBfzmGwM4fEGFRbkYbvyLsoSNx5F9VmhI6ci0W9RQRRgr0XdGqYnoIH33X0ffshqX2vajPEQGcO3UUPw/UQQZxg/0XdGOzIoa+cg2VbGpcMQnZ35ZHERs93l300a2k9Evtl0DKOEyzsKaKv7KOrr6jnerry6OnJw0j58Bw9tmROh9qRK4jtLnZamK5ZLdctnldGFMYo+o7aIP/ndeU1jfVagN5STj+Lvb1lH+X8WJ6N0VfykXNtFDwHXQVP0yM+m9ed189dRQ879aT+CROjvpS45RUbM55vcjznOugv+ujMuRC3SX3oLbiaj7mxehzGiYZt+1X+i29LnvgbsC0L/ljYRpRoeRHX14IY3lgeyL+d+spoxWlbJ+O/OTfNK/G7xDEV7Ig/6UqSBH/+85/1W+pjjz1Wd8Y+/PDD8ZWvfEXXLL/oootw//33Y0djUrW73X7GEZBE+h62C+PlYbXGlsZJYiTlfj1nN0dg3Pz4ddLWCvEDt8B4RZh8B6zhlbBbNRi/hKTYA4jmezmYMIBxXH0JpnsurKCetun1Snor6RuUOuE0hmC5PqLl9wOlnnHbxC7TrGtfwwobMH4BcT5tk+Sz1Fu7f2H6uVXT+jhqfEQr/qHXN3I9cG1L9aJiF9Gw8yh4Nqp2EUm+C0mhC1YSpf2XXEHvKxq0rCpp9TU90oaMmBxMrozIAJbnwx5cnN4zlnbZIKkMY7QVp++LPWhGBsZ2gXKf+kXu6ez/XE2P+q9rLpJcB6L+nfVz9Tc/gL1oTzwclwD1ma+2jLRi2PN30XQHPTvBqaxGIv2qoeWqj2HHXO0TyT3kmmDe3tp2jrSSVEejJhqWr3llt/NX8mIsfnfvw1UzpV0Ufwr5uKH+cHrnanrGr5FyEIeI/DIQR7DDBqK+JarDVdPWZwuNyCAp9Wk5cqprNZy0o9UgLWuat2M2uI31sIIa4o45adkZQ5rVWmj02nbZS8Z8F9g+fOkLjZkmfYO1oYu4cy6MZcMKW9p/kP+SLsljyQuNX/6XetHlJqg7aT/079U0jLyX+2kccahGJH5JfShlRMs3LCS5EoxlaZxW2EyvzZU0vPRZ5fNQZMMUurRsJ46XhkkizQPTNSetW40RxCPrYFxP+0BWZz/qoUHD64AzsEDTVgsTwPHgLdlL647WDbGzMYLEL8KWfnGxCyYKNN/jrgWpH/yxvnLYQtS9EMmDdyKev1d6TNLj+oCUl3/dgyRXhvGLaR9r1QPaX0wW7aP9cclbSa/WkaCuaXZ6BhE98k+1C3OWpPW41AfjFTQ9kp9SRtVOC0gGd9Hr7PowrCiEXV2r6UUcax2UcoLGKKxmJbXBGD0utntJkMZR7NE4pBwLdn3oUZscT8NKnJrXXkHLqrRn0vZIXjqjK/RZRNomqV9W1NJ8ngqo3dTuqdJuafIKrj2xXbZsSPdUNEK0LowNYtvT8NJHTdtTS5+FOn0bdm0d4vKAtmFyTLRVB4Ta9UzuY6X1Pu4YhNMcHesPGG3vpB0TjXAtoBkb1MMErUTeJyh7qW3t+FZWA/TmHT0mfWrHsuBUVsGWeju6Fk7U1LYz51iIe1JNLUjE8hyUhNoeS52WY9KuiS4pUTCmYTGa8gwUhyh6toazgoY+Z2i6gwbKvo1g7cNpvyeso2XEX6k+S/9FNFl0YoFdQWC52lZ05mx05RygNoSyHae+KfWp/1RbRW9tF83SgN5X2hRJV9SzML1Pq6Z5If4TWwInp2kUP4hv7VZF80jaKekbrGvEsIOaXltNHNjSH2pW9BpNRxykbaW0fc2Ktl+VIIFvIm0Ho/l76zG7OartsoSX68V2LTei3eqPuo7XeBa0T6Q65hXS52TR2EIPiuEoynE11Tzxsfg8STS9ortyHy13jq99KiduaRzi18AtwB1ZjtEgLdeSdslDb6xcVsMEHcUCHGmb3TxE3rSfZ7uI8t3Q5Iq9jo/l1TAdM1IttvV6aePtxrD6U8qSlnfL1b5FaNJnfslvuZ+8RCelCki+S3hEISQaSbcL+WmPrWVYkLSNY9n62W0Oq07KtbGT0+u0je+ar/0mwX34Ni0D3TlHj0k5CbySnmtFRvNV7Ch5aZmS/pHUx+EgfeaUfo1omGi21DHpZ0r5izvnqb1CJbK0vkl/cH0zQgRb9V70WfRW+uniA9X3VlWfl0Mnp3VTKLnp/eQS8Y9WIamTY2kW/0v8Ur+lLZHDcmnOStS/Us9CtzDe3ow0Y/Vpuyyob8fqrPR99Zk0idWH0mpJX9dKYrVHylkJgdb99vOz2CT5LPWs3VakYwW2thXt5k7SpWUVUwO1+9hJf+6e1TPGn/e85+larxvy5je/WdeG/fCHPwzHSQfGNiSXy+mLEELI9LEjfnMtgizLr4gYH3nkkfjCF76gS7Xssssu2JGhdhNCSDagdlO721C7CSEkG1C7j5z05+5ZPTDe0dGBffbZ53FT5mX30cceJ4QQMnPsiLtjn3/++Togvvvuu8+0KbMKajchhGQDajdpQ+0mhJBsQO2efGb1wDghhJBsoEu17GAzxt/+9rfPtAmEEELIk4baTQghhGQLavfkk7mB8WuvvXamTSCEEPIYZF14Wft9S3jsxpdk+4faTQghsw9qN9kc1G5CCJl9ULsnn8wNjBNCCJmdP+lKdrClVAghhJAsQ+0mhBBCsgW1e/LhwDghhJDJ+eZ6C2eCc8Y4IYQQMvNQuwkhhJBsQe2efDgwTgghZJuRZVS2eCkVzhgnhBBCZhxqNyGEEJItqN2TDwfGCSGEbDP8SRchhBCSLajdhBBCSLagdk8+NnYkHA9IYiBXghVHsIIGjFfQU1auABO25OsXwHrULVYSpW/iUP+5+78AiEJYuTxMowa73K1xmqAJJJH+t4sdQH0YcH1Ynq/nrWJneu92vLYN23Phd5ZgOTaCSh1JEMHN5xDVmvA7SigtGIDtu4jDEMN/XwYn72vYOAjhdxThyLkg0vBRM8DDnzwZSRAirDcRjtaQ6y7rvVbcvAJJkuh7Oa6u8CWeGLZjoTSnhMaaIZg4gVsqjB8PKk2Y2Oh7t+AiqAV6/yRIEIdpWuRcOz7LsdAalTBpnBKPm5frQji+o3H99ef3odBfgF/2ND3j33jFiZ6X+HOdufG4G0NN9BY8VJZXUV8zNHYvB0lsUF/bwD/uXouOeWV079SVpq+W2hxUasj3dcHLuwhrDYS1AF7JR9wMNcx4Pji25oHQXDeqeSJxix8122sVtIYqGs7u7FObKw+tQlwZhtvZBROFaXlp563rIalVYHf0wpIyE4dpubJd+c0LjP5P9JxtYritUb1MJtB6toUEBkXPxkgrhmsDHTkXYZKg6Dnj7x3LgmfbyLs2ck5aVgueg5xraxwLugpoRTGqzQhRYnTX4sGSj8FyTsOUfRdl39E4C76j14/U0/S2okTDy7Vzu/OoBzG68i66ih4c20I5n36XNtiRUzvkWEfeRXfRR3fRw7yuAnoKnobxJQGAXiNxCQODJfSVfeQKLvZf1I1WI9Rzcr3rOXpuYW8Rft7FkjkdaISx3qO/r6DxSDj53DOnjM6utJxombAtlEppeVrQU0R/fxGVZoQ953ViTk9B07m4v6jngyhBXzmnVT0NL/5KNI5qM0Sf+Kozr7bIPeVaeS/nJc1zOnKY25HHYGdOj402Qz2mafVdzYuBUg6VVgSpHl05F7EBwjjRY+LPnryHsuSnlDVj0F/0UQ3Stsa2LFRakm4pEzZqQYwwMXBtC0Esy5WkZUXLrwW1Sa6R8HJeysQDaytpHozVT8kJ37FRDxOkOT75iD+35kXIlmBFqbam7wOYXGm8ABnXV12386W0DbYdEQgkflG1PSl0Abatx4yXg8l3AHEAy88jKfYgcXPaNif5Ln1Z3XPSmzp+eg/5b9mwC6lG2PVhmGYd8cg66ZFq3KL3VthAUhnWuKygnsZh2zBqS1nrrBnrV2jdFZ2Q/giAoWasP4e0WjW1Sd7nJGgSa/0Npb4YoBomMH4RTSvtU8SFHjh9c9Vu45fQkLa72KsaEyQmvXZgV217/F33U9+IHowaX9uTqN5AZy5tDezGCHryjtoV9S1BLXGwph7B+Gn/KMp1Isp36/u6363tWvnQI5GUBxBLVoivxPeWjbxjwbj58fYp7lmIuDyAZHAXWF4O6xsR7M5e1Af3QNw1F6Nh6pPuvKP9JelDSTsm8SW5Mlr9u2kaJe6K142oZ7Ge7xV7RU+TCHZ9SO9hGhXVTvGB6FiS79By4MQt9Z3VrOhnk+vQNMBxNY+0LEneRU0tI0mupJqsxy1by13o5LSsJYUeTZ8VtWCFaV9C8twOm+pzI/kqeWD7cFrVtFyJRrsWmlECv3sQdthAK05Qjwws6Q9I3zFXVj9Wg0RtcUdXwgpqMG4OQ7Gr5UXcInm/p7UWgSvpKCHOlTWOsH+p1geJS17iDyk4TtRU++2opWmTvofUBSmzcceA1gVJY9mzNS5n4e6aFvGLLWVS6pBlo2VstcvpGdTPUlaFtfUAD40GQN8C9UvelfzPIe6cC3h5zce41AfUhmDHoR4X/zq9czWPtD8kvpR6vvRAjfdfoyHsnffXfrrd1YcRpxP23J31frndn6rxS75Luu0OKY+W2iT9eLFPrtP8lHZD8izfAW/x7rBaFb2mVewD5BkgDuEOLoDdrMCKQvVfU/JE+mfNEcTl/vE6YLcqaqvYZ8UBUOhM89rL632c2rrxNsuPW2n/r10JpI3JldSn7byWOJJ8Z9omSf2XOOV/FOg14jNJg5QfsU/SLH6aCqjdZCpIvDxqYQKRPHlekbZXdErqajy27J5oXUue/Swg8Uuqf6LLeUTabmo8+Q7VKLkk51haB9t9W22LVAMLaRsgdUXqWVDTNiUpdGv9a9hpmy3tXF/RRd4EWFD29JlI4m1EJtWdsecJ1Th/bO6gtK9uQfXJbqbPbH59nd6jYAKUEKTPdjIWYNlaVyU+O6ghqazXsQZp87Xu5zs0vNhZiGqwrLS9tKTuBzVtR4rhKPz+hemz5Vi/YVU9Sn0w9gyZr66Cs/LvGG0lqsOiG/IsITorWlGqrcJQ4qHLDrGgw4UzslzjluvK4XDarrQqiAvd2m7HXfPT56DKavWD5Jsr+Za0EHctgFn9EFbWwrQ9l+dKeZ6VfCz2qq8sfc514CJB1Smr/olmFDx7rG1L0CHjBK0KQstF0ymM95Xks7vmn9pmOkMPpX05x0NXzhnr4/loJVAtsuWaJH0ulPxUH0v/wCQILNFzL21DndRPEk6PtdLyILY34Ok5KUOiHdI2lzxbfSgaJeElnJQG37bQaDaRSL8h34FOSJnqUh0bDVI7RMcjA0QyDCAFWYhDlKxwrA3v1Gc9G0b7YH5zSPsDa+uRlsdcc0h1R+TQnbcbvKFlaRkbXqY+Ff9KGY1gwwrr2vcR22uhgV1bh4KUYTen/TrpC1U7FqgZ1SDWvJT6JeHkvWcD8ZzdUAlilGwZZ7DURj+ooO516hiExCFpzAUV9UPZt7FexhP0eRVYVxddlf5SS+OVciDHG25J66bkkYR3hx5S2x8eaeozquq91I8oRJLr0LGOaM0jeo30G8XOnBS6MaRfKMekrjYTC/15S++jfT/tm1kwXh79fqL9YymTUuZytTWaD1IWJV+l7qd9p0TbpOaYH6SOSl2RPkuXE6W+Hqvf4mvNxnbf3Xa0XEhf0jeR+l/yQspPfqxvJ4iP10S+9nOl7Gsb59qa71MBtXvy4YxxQggh2wzXOiOEEEKyBbWbEEIIyRbU7smHA+OEEEK2Gf6kixBCCMkW1G5CCCEkW1C7Jx8OjBNCCNlmuAkIIYQQki2o3YQQQki2oHZPPhwYJ4QQsu3Imnxbuo7aFK23RgghhJCtgNpNCCGEZAtq96SzY22+SQghZErQjX+24kUIIYSQmYXaTQghhGSL2aTd69evxwknnIDOzk50d3fjLW95C6rV6havlX7sscfqZsQ/+clPMJNwYJwQQsjkbAKSbOGLA+OEEELIjEPtJoQQQrLFbNLuE044AXfeeSd+/etf4+c//zl+97vf4W1ve9sWXXvBBRfooPhsgEupEEII2Wa41hkhhBCSLajdhBBCSLaYLdp9991346qrrsJNN92Epz3taXrsS1/6El74whfis5/9LObPn7/Ja2+99VZ87nOfw1/+8hfMmzcPMw1njBNCCNlmkuTRHbKf+EWHE0IIITMNtZsQQgjZ/rV7dHR0wqvVam2zHTfccIMun9IeFBeOOuoo2LaNG2+8cZPX1et1vO51r8NFF12EuXPnYjbAgXFCCCGT85OurXgRQgghZGahdhNCCCHbv3YvWrQIXV1d469zzjlnm+1YuXIlBgcHJxxzXRe9vb16blO8//3vx+GHH46XvvSlmC3sMAPjxvFgHB9wvfSzl09PWLb8vgCIAiBXSs/5BQ2XNGowtgvYLkyhE1YSIfnnn9PrXB9JvQLEIUwcwyp26WG73A2TxLD8PCzbhmk1YOUKsHJ5WPkSYDuIWy24hRzcYkHDCLnusn7O9XahtKAfJk5gux68cknf5/s6EYzWEDUDBJU6kjCC7bnwO0uIQ7EhgVfK63HHc+GWCjBJgu5d5iEOEiRBGkau796pC52L+5DrzKE42IniQA+cfA7F/mJqS2cBtu/AstP1fpqjLZQGiyj0pf6prKjCL3mwHBtxEMP3HAS1EB0LexA2I5QHU5vjMEGxv4CoESGJDbp37sH8nbpQW1XXuJvrKhpfa7SFsNZCHMb6ecUDw2nWOBaiZoQ4SmA7ttrZGq7ovRzP1rgLjoVcp4+uXRagMNCD8oIBtS0OIjh5X+0RxA/in65d5uv/fE8ehZ68+qqxbkR9WV8zNJb+HNx8LvVnkF7vdxZheT5aQxXYvou4GaT5mcRahuyObsRDa2DZDizXg5FypeWsoGG0HDnOeHm0WlXYQS0tSraFepggTAyCOH3FCSBNWJwY5BwHsTHwbAtFz0HZt+E5FlbVAoRJglacoKfgwdlgfSbPseHYFvaY24GuoqebLuRcG7Zl6bVC0bNR8l2UfRcLegroLfvYqb+IIEqwutJCZ86F76bpkLirkheJwepaoP/VL46NgvgjSVDwHdSDGIPlnL4f7MyjEcT66i54mNeVxwv3m4fheqjfXkoYyduReohyzkWpw8fcrgJ6Sz6Wzu3AYEdOXxJ/R15eHhb2FNS+3rGyWq2Hmk65V1/Zx7pq+s3nXvM61a/zu/LjaejwXQw3Quw+p6z2e7nUr31FX8OKb8V+iX/vBZ0Y6MhjQVcBBy/qVh+KDbvNLWs4Qc7ds6KitkuaF3Tm1afi43kdOZTGwuVcB70FD9Ugxpyyj1YkeRarD8T3YkPetcfy1tX8GSx7WgZyrqXnHBuIEqNlRLJZ3C8v0bkEBj0FR9NQcG0VP/GJ5Fm7gXcdC0GcoOBaSGvZ5CPN6Na8CNmicuWXAcdHXOqD8Yva3oqWJ/kOPS5abnf1wW4M63tpe+2gjqasFOd4SPJdaHklWCZJ+wF+SdtlaZOl3TVuDiZXhlNdiyRX1nsmfkkLaSLtt2h8qwkrXwSq65DURrWNR2WtansSNFXXLc+DaVZhRS3AtmGFLY3DeDm4jfVI/CKSQhfKppmmReqvXxjvrMblflS8bq3XldDodY0wgWcDo0GMvGOprWJzs3M+TL4DJgxgpEFwHHTnHTw8GqJenosoBpZXIySWgzwimK45iDsGtI14pBJou5DbeQ+Nf15ZfNSR2tAxJ+2jGGg7U/c6EfUsRi1M1Ab1k522SaZ3IVbERW1TokKv+j4Z60NJuv3e+bCjFtaYEqw4RLM8B1HXfDRjg3BgV4y2EjT8Lv3s2xY6kfoRhU6MBglapQH9/M/hFqq53nF/VCILcwoWKtKvKXSpn9WPfkk1eFg0v92/G2Nt6MJuVRHO2SMtP6LHAKJ8N4aDBCKJWn7cPAJbylRR/aw6J2Wo2KPplrIl/UArDmA3R1Xbneqa1HduXttyCSuIjmv4OIAXNfSYdKlalWFYQV0/S1svZUzKjXFczV+5Tu4hZbVtq+S92CLmyLm4c2762S+pne17ii+ssKH3/VfT1TKiGSn9EcvGyqQIK2rC5DqQlHq1biTFbrQ658OLU+2MexbCrg/BHXlEfT4Sp3ata0RodswFOvrQ7FmCsHcnjV/6FaI1SXlA415bjxD17oSoc66mU8p6UurTPrFdW5f2h6QOSr9afNKqwlt7v5ZByc8afAwWXS13cm1j8dMw0opTsTMJ7Lk7YzSUulOCcf3UF8bAigIklSG1T+qfxFUvzdH6K+2EVZA092mcofg4DmG1ajA98zV94le7WdGy0G4npJ/fLs9SNtSf+jzhI+5drOetxoj6P+6cA5NL0yX9u3YfUPJDbBGft9sdPZdE42IoZQ9xlJZ/eYB1fa0/2q7EodartCyFUyIa1G4yFdhxqG276E4zSlST9dFB6pP0XQs92v73egmsJIbdHNG2zmlVtZ2QvrS0z4LWMXkOSgIY20HBijVebQ/L/Vo/VbflmdokqmVS77T9M4m2UxLWlTY4ShA7OY3fdywNIv3j9Y0QA0Vf7ZE2e2Fn2qbHnfO0/20a6TObtIuiMdp+SNsR1rWdl/i1rXVcrG9GSHIdsLrnwG6MaP3Vum+7aX13PW07Sp6tfZMElvpD2isrbOpYg1wnbbRowtySp+2L4A49rPGED/9T9XcYBdV/SdtQbgB22NR0i4+lLRc9t4eXp9og7ZO0NWNtmrfuAU2DUIyqel2xshzrGzHCMb1JvDzikXXIyYNIEmseyLOGtplxiFooPpoLPHgbnMpq1TnRp7wJNC+txiisoKHtuLSxflhDsbZK+1wSXzVMgNoQknK/+k90xBldmT6rSn+usjotT/XhVH9NAk/uIf2RoYe1DOn4jrS34stCt/pN23jVhrE+wlgYjSuo6TknCRHke1TD5Nla2+axPllJHApguBlrvHqdtO2SryZJtdoYLRtSllwHaMBTn1uP3JPeT/oilo0SAs1j8bH0LwqejSAxKNnSr+pAV87Wshg/+Lc0P6SsSN8jV1Z/SfnM1daoHyU/5d5514Id1rWMCmXPTnVYntelf6TP7mlYu1XRci6uln5PXyHtA2n5kzQ5vuajDUv9L+VZyq9n0jEQQezty9toREbL/ohd1rCxV9T8lPxVDfQKmFOUchagt+Dq+IRtpD6n8UhfQJCy6y/dR/1TjOvj/pY8Hmql/tUy0xhJbWuOaD9E/CT9Xun7iB2jsQO5UtoObStEbx1f06zP17bBgNiTRBqflF3xoaRd2ygTaT9HhXBMt6W/10zS9qEWWwit9HqJV+uQ9GO8oqZL7Cy6FirSTwEw4MeabolX+hpilvRpZ4t2L1u2DCMjI+Ovj3zkI5uM/4wzztDytLnXPffc86Rs/9///V/89re/1fXFZxNcY5wQQsg2IwP91hauYSZhCSGEEDKzULsJIYSQ7V+7Ozs79bUlnHbaaTjxxBM3G2bp0qW6DMrq1ekXWG2iKML69es3uUSKDIr/85//1CVYNuSVr3wlnvWsZ+Haa6/FTMCBcUIIIdvNJiCEEEII2TKo3YQQQki2mGrtHhgY0NcTcdhhh2F4eBg333wzDjrooPGB7yRJcOihh25yNvpb3/rWCcf23XdffOELX8CLX/xizBQcGCeEELLN8OGaEEIIyRbUbkIIISRbzBbt3muvvXDMMcfg5JNPxte+9jWEYYhTTjkFxx9/PObPn69hHnnkETzvec/DpZdeikMOOURnkm9sNvnixYux8847Y6bgwDghhJBtRtaxl/X2tjQsIYQQQmYWajchhBCSLWaTdn/3u9/VwXAZ/LZtW5dEufDCC8fPy2D5vffei3o93WNntsKBcUIIIdsVZ599Nq688krceuut8H1ff+L1RMg6apdccsmEY0cffTSuuuqqKbSUEEIIIYQQQgjJHr29vbjssss2eX7JkiUwTzA4/0TnpwMOjBNCCNluftIlBEGA4447Ttc9+9a3vrXF18lPwb7zne+Mf87lclNkISGEEDLzzCbtJoQQQsgTQ+2efDgwTgghZJuRb3q3+OF6ir8VPvPMM/X/xRdfvFXXyUD4pnbQJoQQQrY3ZpN2E0IIIeSJoXZPPhwYJ4QQss3Ig3WylbPORkdHHzcwPZOztK+99loMDg6ip6cHz33uc3HWWWehr69vxuwhhBBCZpt2E0IIIWTmoHZPPjZ2EIzrA44DK2zBSiJYQQPGL0ipAlo1WIWO9Lh8FscUSkCSAJYNRC0NL/8lvFXqhOUXYJe7kdQq6Q2iFkwUwgRNvdY0a/rZ6ZsHu9gBy/Vg+XkgCmB7rr5MEsPt7ITfWYKbz8EqlGD3DMIrFeCW8vpekHMmTu0SkiDSz/JyvPS7DTfvo7FuFJZj6/FgtKbhaivXwS24yPd1IQ4iRM1Iw8o9ywsG4BULaKwbQaGvU+Mpze1FrrsDHQt6YDs2OuaVUejJ63VCa7iq8Xcu7oPtWCjP60LH/DJMbDQuL+/C9p007GgLhb6ShvNLHrxSXo8X+wsan5P3NPzAU/oRNiME1VDDrmnFWFBwEdRCNIea6FnShaAWoDVc0fRGjQidiwfRs7QbA3PLcAue2uR3FjX9+Z48wloLtUfWoHunLk17vq8TfkcJuZ4ywloT5YX9KM8vw8n7E3zbfi/x2J6n521/4vdH4hfLtjU/TZLA1Edgub7mp93RDbieBIKxbFhxABMGsKJmWp7kHn5JvuaDcXxYQR05K4HvWIgTM/4/NgaOZT26uYIFfbWiRM8LvQUXvQVPP9uWhb6ij668h5ybVuulfSV05V2U8y5iA3TlXDTCGDknPb+6FqDoOfAcS//3lXzkXQe+a+v7noKHou/ouT36S+gv59BV8DSe4UaIhb0FBOJ3x4Zj22qHHFtbDzQO+SzhHduCZ9tY0FvQ+1ZbEcrF9HixI4fVoy29bl53QW0f7Mxh6UAJvWVfwxQ8B10FH3vO69C0PGO3fo2nu+jBHytr4ivfdTDYmcdO/UUNt8tgWc8VfBc79RXx8HADQZRoesS+pXM70F3w1L9yH/HtSDXA6kpLj8ux3fqKGr5D0lwP0T3m31YUo+jZGKkH4+WiHsYIE4NmFGOw5CPnOmq7hLUtoOw7yDmOhhlpRljUVZiwGYbkeUfOQXfehS/pdsVvFrpyDvKOrWUj71oo+zbyTnoujI2ek/RLrkoZkbxuv9e2QZqwOE3jlH9zvRUvYdGiRejq6hp/nXPOOZgpZBkV2S376quvxmc+8xlcd911OPbYYxHH8YzZRKQBjJDkSjB+EXHHIJJ8R9quunltP6UdlWPGy8N4BRg3/WJFinuSK6MWj7Wj+S6Etq/xiK5brarWKWO7qMKHyZWQFHtSzRekfRZdl36CfOwZhIlj1WlL2ncpF4VOmEZNbZA2Xz5bYRNOVx/icj9CtwC7VYPximiECaJ8dxrOdrUdELtrUQJVBttGZ33VWHuZmtBtamhEqRYEsUFiSfvgYLSVYH3kAn0LsLIaIupagJJnj+kGMFB09P1oECO0XDR6lmDE7ca6RqxthutYcPY4RO/R4RrE5QE0ogRRrhOJ4yESDUpEe4BI2pN205FEqIUJvNEVCHp2UlukHbRNWkfs+rC2P0mpD63KMEZiFyXP0jwR++v5Xm2/pJ8l9xD/t6LUnutXx4jn7TXeB6sEifpf2rc1jQgr0ak+k/TJ8fWNGHGpD3Z9CFGhFyORDadnQNMn/bRAlofw0rwT+43jomVsVBMHdbmnbamPxNViU5LvRODk4En8YV3bX4kDSQwrbOgGR+L/2PY2KCOepk20XtpyaWetZgWIA+QcS/uUiZx3c3CRwLIsLbsanyz5JLZ6eb2HlGdT6NI2XspFa3APtV/8IRor/up0JFwOdquicUnZLjkGTbgazni5tI8qfU/LQuSXUTWepl1sLHs2op7FWua1rtiOlnk/rMFuDOPh0VD7qJL+JNehrzAB1voDWhbE53Kt2CJNuHE89IsOOxYqTln90l900bB8VINE7zvi96Jp55CU+2EFtbG62KmfNW/W3I+oez7i7oXaL2rF0v8ZK26Wo30bKdtJsVttDgZ2w1ArzXvEEeqlOVpW5V7SJ5O6IDYK6xtpv1V8FnXNxxp0oO53ox6Kj5qIOwdhDS2HyZW1Dy9+l7QlhW7Nk/VWCVarhqh7gcYh7Y342W6MpO2MlOPuBXpc0i7tgN0c0bqvfUApf9LWBPU0zfnO9DkjibRNsMN6aqvkf74DSaFLfSo0Gw31V7utS53lzhrtJuQJSWKUEMCOWiiO9WelrZA6Iboh7bg+r5hE67qU75bW5bRdbfdhk0KPhsnV1yEQDZciKPUwbGr77w0tSzu80gfwS1gTpc9Wor1WnLZpShxo/NKeimaJPq6ohtq+yDF5TpHHI2nj7eYoip6l7ai0FQWE+oynbZi091K3Rcul3ZW2UvoOcTB+TPrwdm2d9kGkD2EPL9f2WdpWe/0yII7hVNfAkc/1IbiN9VrX4+4FsNf+C8nwGjRv/i1qkUGXqaMQjGhbIWGSynrVWKFkmupTd2SFtj3yDFGT/oxfVF2TtqqMINXWOBhrnwYQwVatkrZlXQsIDbStEw2vlOal+hw14K66V/0s/R7pl0ia7Opa9HrJeBuYNiIJTFPaQQuFpImCCTT+xJe+W0nbvEor7SdI3jijK9Uf0u6Jr9Rv8gxdW682Rd0LVSOrbifg5rTs6LWtMQ2BBTuoI+5ZqH0kid83aXsvNthBTXVH0qsaLW2o7ahuqm1hU+OQ/pEUJydupf0cacfdnPpRymc1TLSvoLoq/nJcvUZe8mwmWix6Jf0i+Szxy/1lnMjoA1mQ+sh2UA2k/NQ1f5xWVctxYLnaJ5H7CM5O++t4VctP+7SSf8JIK+0PSZ9D9Kvg2XrPqHuR9nlU0+U51ClqOqQf0e3Jc2k6ZpCUBzDXqqb9L0mO3DyJ8fBooPVGynhXztY+FmrDCPt2Vv8gDvX6kpv2H9zhh7WOSPnr8CytY7bc2UqfQ7XPMlav40IP1tQjzO/wtX7XQgMrClRnJfxwK4Y9uFj7L9qvCWro9G2YRgUPjrS0zyEv8Yfcs+J1j/Xb0mzWfBlDyof4aF1DxvfSMiLkmkMYDtP8lToqfQXpd0n74+i4TKx9XrFX2wop63Gg/XWxV/px4hNPypZlq43SJ5a+kzhS+pSCHJMyk7OhbZQ0c5Ku/Nh4jPhuKqB2Tz6cMU4IIWRG1jpbtmwZOjvTL+WEzc0WP+OMM3TAenPcfffd2HPPPfFkOP7448ff77vvvthvv/2wyy676Cxy2WWbEEII2d7gOqWEEEJItqB2Tz4cGCeEELLN6E+xt3BgvP2zbRkU33BgfHOcdtppOPHEEzcbZunSpZgsJK7+/n7cd999HBgnhBCyXfJktJsQQgghMwe1e/LhwDghhJBtRn5mKq8tDbu1DAwM6Gu6ePjhh7Fu3TrMmzdv2u5JCCGEbE/avTWcffbZuPLKK3HrrbfC930MDw8/sU3G4JOf/CS++c1vavhnPOMZ+OpXv4rddtttSm0lhBBCZorZpN3bC7N6jXFZb/bggw9GR0eHboj2spe9DPfee+9Mm0UIIWQTAr2lr6nkoYce0gdr+S9rhMt7eVWr1fEwsuTKFVdcoe/l+Ic+9CH86U9/wr/+9S9dZ/ylL30pdt11Vxx99NHM662E2k0IIdlgNml3EAQ47rjj8M53vnOLrznvvPNw4YUX4mtf+xpuvPFGlEol1e1mszmltm6vUL8JIWT2M5u0e3thVg+My+Zn7373u3Ww4te//jXCMMQLXvAC1GqPLqxPCCFk5tGNaLdYoB/d8HYq+MQnPoEDDjhAZ5HJoLe8l9df/vKX8TDyJevISLqxjeM4uO222/CSl7wEu+++O97ylrfgoIMOwu9///vNrntONg61mxBCssFs0u4zzzwT73//+3Wfjy2y3RhccMEF+NjHPqZfZsveILKJ9vLly/GTn/xkSm3dXqF+E0LI7Gc2aff2wqxeSuWqq66a8Pniiy/WmeM333wznv3sZ8+YXYQQQiZi4lhfW8KWhnuyiFbIa7M2yK7sYxQKBfzqV7+aUpt2JKjdhBCSDWaTdm8tDzzwAFauXImjjjpq/FhXVxcOPfRQ3HDDDRM21SZbBvWbEEJmP1nW7tnKrB4Yfyzt2X29vb0zbQohhJANMGYr1jozFOgdCWo3IYRsP9o9Ojo64bj8smomfl0lg+LCnDlzJhyXz+1zZNugfhNCyOyDz9072FIqG5IkCU499VTdVGWfffbZZLhWq6Udtg1fhBBCphaudUY2BrWbEEK2L+1etGiRzsxuv2Rd6k1xxhlnwLKszb7uueeeaUwxmUz95nM3IYRMP3zu3oFnjMta43fccQf+8Ic/bDacdM5kjTpCCCHTB3fHJhuD2k0IIduXdi9btgydnZ3jxzc3W/y0007DiSeeuNl4ly5diifD3Llz9f+qVaswb9688ePy+alPfeqTipNsnX7zuZsQQqYfPnfvoDPGTznlFPz85z/HNddcg4ULF2427Ec+8hH92Vf7JZ03xbKBKITxcul7kwBxDMsksOz0s7Fdfclxkyunl0VNmKAJ06gAtoOkNgrL9WAsG1ahBLujG1auADgeLC8Hy8/DKnRoWMW204IbhXB6BsbtdEpl2IWSvvfKJViODRMGei/bd/VzMrIOUb2hn+XVWDMMv6OoC+h7pQJaw1W93u8oIWoGY8m002vDCLnuDrh5H8X+QnqfUh6WbSEOI/0s/+trhvS4W8yjOK9X42kNV1AY7EHYjJDv60Dv7vPRsbAHtpMWl1xnTu/ftVOX3ntw30Hke/LI9ZRhORaqyyvwO4uIgxhxM9Tw5QUDiJsBOuaVUZpT0jjlmLw3sYFf8lCaU9T4d+0vosuzYduWxjuw94BeJ3Tvvgi9e8xFWG+gvKBPr3c8V+8nNFYPaXxdO89FEiea/ly32GWjOLcXbj6nPpRjYpftOHB8F9177aLHxRdCvi/t8Et+yjVJEMHKp/cQX7nFwngemzDUMiHlazzfxx4eknwHLMfR/1IWpOxJ2dFyKGXOL8JKIiQG8B0bjmVBVj4OIoPYGHi2jZxrw7MtdPoOip6DIDHwHQuVVow4AUZaETp8R8PkHBtdOVf/y7HFXXns0luCYwFdeRdl38Gcso96mGBpTxGeY2mccry/6KOn4KGr6GFBbwGLuwpY0ldEnBiEscFgyVdbYgPsNifNj7zrYLe5ZcRJgmozwtK+ksbXV/Th2NZ4eS96kgYbD6ypIYhi7DWvU+Pt7S2gI++iM+/hsF360Fv2Ma8zj517i+gqeOnn7rz6YqQeouA7ep/BzjzKeQ879ZfUlqWDJew5rwNLB0royLlYPdpCKPXEsdFX8lH2Xb324fV1rKkHWNhTQDnn4oBF3Xpu6UBZ0yZlTuKQfOgr+1hbD/W4+KbairCoK49WlGi4MDEY6MhresXfPXkP9TDGnHIOa+sBEmP0OvGXhMm7af1J/e2m17m2HrcsaBnQ+iV1KEw0PwXJb0m/fPJtC7I0tsSZwKDgpde6toWRVrqxhnyW83K9/Jf4xf+SJolL7J4K+M01mRLtFhxftVoKvxUFMH4JTaeAJFeG1aoiKfbACptpWC8PKw7gJ4H+L7mW1h0J40UNBH4HkmK3tr1SJyKpT4mBEQ0P6khyHUjkCmmfC10I8j2w+hfCOD7s0thAkO3A8nwYLw+nqw+Q9l/afvkvuDkk+c60nha6NO51jVjr8ZrAwXqrhGqQALaLgmsjiA2SfJeGFZqxgRU00PA60IzSei1tQi1M4NTXoxrGWs/XdyxR3Yi9osYjuiBxSdtbaUX6PkoMHqmEqAYxGlGCvqKrx8OeRRhqxRgKgJWhj/WNGMurISxj9D4rqy08NBpgdT3SNkM0475WUa+Vm0t8xfoavZcdNtQ/4le1N4kQODltn1bJ9SZt1+5Z19T7rI7zar/YJTbJsRseHMJ9DR9xsQct0b/EIOpZrPeWdm9NLVKdakQGxs1pWzticuqzVbVQ27940f7ariZ+Se0UmyQfRf9MrkN93ggT9YktBoz5Ou9YqsOic/I/KvTq9QNFF4mXR8vv0ONO3ILbHE77im4atxWHMPkO1W1pZ6WcSvn0TDRmZ4LhEBpO0mTX1ql90i6LnxEHML0L076mZaPkGLVVzjVLA0gcD7aJ1U6575qWhbqXlsM19Uj7FJKehlvCsNMFp7YOUe9iLWtuaxSjrVjLktig5ch4sFsVxB1zVEsqXrfeN+yYi+WVFqyopXVFTmp/GMDaRgSRI8kLuU4kRPJNyvhOGNJyJ341XgG55hBGpWyP1Vs5l0eENcWFMI/8I607YV1Piz+k71T3u1Ezad3ptVvocA3qkdF7jLRizTe9b6FLy6TYvaKeAK6Ph0dDdOZsxMVe7Yu76/4F4+ZRtfLozKX9sbA8iLjcr/VG64uB2rre6YKVLyHxCkg6BmG1aqqloZOD3RjRNFlhAyur4Vg9HntGqA9r3kf57jSdcahlXvty+S7tm0l+qx+1v5dP2ykvr+VGy4/jaVsjbZSUE0WeFfyiTNOFHdTSY/KsIWFyZZh2/3IWaLcMim/42tzA+MDAAPbcc8/Nvnzff1K277zzzjo4fvXVV48fk18K33jjjTjssMOeVJxk6/R7U9otZVwa+tjJwVgWnLCOvAn0mLTJ8l/qmJyXtkXC56xE2yAp/3JOtECuFW2WuuFZ0HgSqTP6HB+mdSnfqfXICmoY8GNtG1RP40CfvUTX7PpQqo+JNMi2aqa02WXP1jakp+Dqe0faYr+oGlFwLb1ObRpYDKxdhqQ8oPVbaBlb2whp86Xdljpst2roLaRtp1Mf0vbIdPRrm5IUeoB8B6J/3ann7VZV7ZN2W5D7mM4BHTOQ42UrHG8fErGpMQIzZxfto8iYgnwuWDGc6ppxLZB+vtWsaPsqPnDXP6hpiLoWwBpeqVoi+pSUehF1zUPetbTdk7BR/86q6fJZ2jMZb1DtW7i7Pq8k5X7YzYra04CnOlH202dbu7M3/S/+SiLti2keWWncfUVPNV2OhYO7wwpb2h8rWSFQ7Nb2UX028oiGUa0fe44W7U0LVaL+kDyU/9J2qx8bI5r34j/VZNvVZyBpY6XdbFhp+9Lhpe27tM0Sh5QHSauUQSlv4lfpE9phUzVZyoj6XsqW9CUqa1Q/2s+3cb5Ty5CUE3keF/9r+y75HTZVXwO3oOW0yw61rLRiA7u6RvtAo620Xye2yr5Hrcqw2qy2jPUJJY1SX+R/rdCv+SqvrlyaLs3zYh88JKqVftxCMzJqb09rDVzHwohVVM1zK6thj5Vduzmajil4Y2NRJtV500i1x62t1WukDyO/6pFyE5cHVP9HjQ+nsgpxqU/rp73uQfT7CUZjB7GbVw0UH/fkHfTmnbTvaqf9cKk/2scVvxa6UKwsR2il9UXKmPSHpG9e8qQ/m4z3d6SNkPZAfCHxS79CyoD0MaR/PBrEWn+l/qlmSp+9VUNJ+mVhA97KuzFgN7BstJX2CR1P+6nij2J1pfaholK/5rX0z+T+knbJ11ripPoseSvP5WP9MTkvZaQy1ueRfotv0jE2yVPpw0h5ERunAj5372AzxqWReM973oMrrrgC1157rXaAnoiZWueOEEJ2ZNq7Y29pWLL9Qu0mhJBsMJu0+6GHHsL69ev1fxzHuPXWW/X4rrvuinI5nZAhA+kyS/nlL3+5DtjIUh9nnXUWdtttN31O/PjHP4758+fjZS972ZTaur2ytfrN525CCNmxtXt7wZ3tP+G67LLL8NOf/hQdHR3jG6nIenaFQvotISGEkJknEXHeQoHWsGS7hdpNCCHZYDZp9yc+8Qlccskl458POOAA/S+zlo844gh9f++9945vCCmcfvrpqNVqeNvb3obh4WE885nPxFVXXYV8Pp2BSrYO6jchhMx+ZpN2by/M6oHxr371q/q/3Rlq853vfOcJ16sjhBAyfXCtM9KG2k0IIdlgNmn3xRdfrK/N2iBr6WyAzBr/9Kc/rS+y7VC/CSFk9jObtHt7YVYPjD+280MIIWR2QoEm42WB2k0IIZmA2k0mlAfqNyGEzHqo3TvYwDghhJCMIJsW21v4jXTMb64JIYSQGYfaTQghhGQLavekw4FxQggh24wxW77WmYYlhBBCyIxC7SaEEEKyBbV78uHAOCGEkG1Gd7zm7tiEEEJIZqB2E0IIIdmC2j35cGCcEELINqMbe3ATEEIIISQzULsJIYSQbEHtnnxs7CgkEYxfAGRWo0kA24EVBzBeDsYvAbar7+UYLAvGcQE7dY+R9XBtB7Bs2IUSjJvX95ZfgHF8oNCZ/o9DWLk8kuowLNfTa63eebBLnUAUwuoahJUv6We7owfR6AiSZh1JFMIt5WHlCjCtBizbhu3YMFGgcUSNlh7zO4pwfBe25yKo1FCc2wvbd5GEkZ7zinl4pQIsx0ZhsAeFwW4UBnpQHizB7yzqMYm3NLdP43DzPjqXzNPj+b4uJEEIEyfp9X1dKA126Dn53LvnEnidJX2/6BmLkesuI9eZ089eKY+eXebCkfgWdqB3jzkIa00U+4vo3HmuvuIwQq67A50Lu/S6jsVzkO/rRLG/ANt31B4JX+wrYMmRO2G35y1Bkhg9JvbOOXAJwlpL7Ssv6Fe/OJ6Lrp26kMSJ2t9YPYzi3D707LVY0z7/mfupf3I9HQhG63B8D15HEeVFc/X+kv7aynV6rdMziK5dFiBqBuqT0uIF4/eRe8q3cpJntuOojyXPJK+dvrkwQRNJs6blpZ3v7fJimQSWn9fyZQUNLSd2cwRw/LSsJVEa3EpfsudNLUzguxbiBHAdoBpECBODoWaMvJeWSfncW/Dg2MCcko+dugtY1JVHV95FR87Ra3oKqS1510ZsAM+2UfZdfY20QhQ9R1+Lu/J6TN4nxqAz52JeR16vleskzpXVFlpxggUdeezZX8J+cztR8B10yCvnYr9F3egt+7h/XQ22Zem1gx05zOvOY7geIuc6ao9c01XwsctgWcPss6ALS/qKaoNjAUt6i6iHMXKujcGSj7nlnB6LE4O53Xm9Vz2INZ5n7NKHpQMlfV/yXXTmPQyWc1hdaWFNpYmReqi2SPj+oqfpWjpY1rTtO68THfn0e0FJ8x5zOjT9z917DnYfLGO4GWJhdwGtKEYrSvRcwXPgSHxhrP/l2NN26lHbJQ71ed5Dl9gYJppe8b1np2HFl5Kvks/yWcL7joVQTgDYqSuPkuegveWwY1twbUvvJf8lLjkWG4OcxANLr5cyI//L/qPNudjTjBL9L+fkFlJWyl5qz1QgdWRrXoRsCa1cJyBtpei1m0OSK8NYNgrBiLavimXDeHkYvwhju0AcwYpDtHJdaCVAKzaoJY62y64F1EtztP0dDWI9J+2NxJEUe1CJLD0e9Oyk91vfjNEa3AMm3wHjFWAv2S/tG9gO7GYFSdAEasOA6HWSIO4YgHE82PUh5CTasIlmktbPIDbadreitJavMSVt26S9qMWWpkfeDzfj1JZWnLZhogmOpccfjDrwyGgLlVZ6TF6iDY0oQTVIsLIW6f/uvDemJwbDzUjTmbZlNpZXAj033IhQcC0NL9fLKzTAUCPCnFIOV96zGkONWM/La00t0GtXuf0YaSVolgbw93VNJH4JzugKJOUBvc96uwPLRkNNWxQDa+pRmvaxtm40SMbTLW3ZspEm+su5tB3Jd6g+VcMETmWVHit5NtbWA207RQJX1BP0FV2N52F3UNu0ldUAkV9GT8HBaAiNW/p6ieVASklguZpW8b9lWdo2StuadywtI5JflSBJ+3EW0IjS83YcqiZLmVNsF1HXPC0L8kWgHk9iJGPtsKbBdhHbHmrG0/uJr6UsSRu+trwYw16PHpf2WPqfSb5DfWekTNWHNA7Ji2Zk0AgTLcuSxuZY+VlTjzV90sZbSaT60C4jiVfEkMnpPeN8J1bVQiSlPkSxwbpGuoSV1arBilrqA8mXUeSxshZiTtlH3DkXw04X7MYIGoW+tNyO+UK0J/aKmg+aTjcHu7oWBddGkBis9fq0HklYyae6U0xdVlun90n2PlLrqfSFRvP9Wu9aiw/SMiq+Xx97en3L2PpZ4hWXDpZc1CODpuXDty2sqYXoLbiIcp1Y3OWp76VsR4uequUnKfXq/eRlt6pw4paWQSnXThKqb6UNEN9KPdO6n+9Aq3M+io6BH9YQ9S9F2XcQdy9AYazfZbwiapGBCeU5QepzAjtqoVKah1a+J217xspJ1S5quajYRe33BcU+WFJecmk7YgpdMLly2nb5xdRvY+VdbJK4okJvel/pL0bN9FllCqB2k6kgkiEGeW6G0fYejqdtmZbtxCB2ctpuyHnZ8FPaS9HBwO/QMNLOSNtrGaNtWMPOQ6XT8VQbtT9Q6kOrPAehW0DieEjyXXoPaRskjrrfDUv6AzIGMNZ2NYyjnwthBYMFB50e1D7RgjGJUu3ozjvaHsg9pC3VZ7b+RfrcJnpnhY3xNt+urEZouVpP5VptI10fiFraV5A6L/Va7it4i3bTeKWNiHqXaJuobfLYeISVl/YjgV1bj6bMYTQJnFZV/Rl3zU91zM/ruIXqkF9Q7ZDbilaLrdIXcGrrYNavUF+p/V2DKFVXqK3S7kib1FlbkfY1GiNpG+tYmF92NR/iodXqx0bfrijWVmkYaV/F1wUrhtWqal6mz7OpTkbdC2CPtWV22AAqa/X9nJILZ3Sl+k38ET1yH7wk0DSaXAlOcxTh8n+lmmg56K6v0P6K+EQ1tXv+eDolzfJf4uu1W0hyJe3vKWPjOKJv4m/RAbFV2tEElt5T9Fn8KmkVjZe2vP1UIs9ZTTsdGxLN03RELQTdi5DkO7VfJ0i8qu1jYcQPWswbQ2n/wCTISR8tbqVtvvQLWzU8ONLSPMw7NgajdejNO1rOVSO9vNYBSbexrNSXYQOuY2G13a39USmXUk7zcQNrG7GG1WstR/Va7lMJYlhBTeuCjCWI5omx4nspZ5JG6Uvv1OUhV12Fht+V+lP6PJ29sMMm7KCm/UHRv86cjblWVe3r9GVMwaBZnqNlWHWtay68FXfqcSdqqnZKf0b8kR95GHk3fVaV+ze8DhSSpj7rah+6Y1B913BLWnaljM8reyg11o5rryD9JUmrZyIMtcaW43R9LbtyXPJSwksZlLZF+tNS7iVNUb5bfS7lSPsncUvbp/VjfaKwc57+l76f2DLSirWfKC8Z+5D+aOjktFxImtY1Ir2+z2qob5OxciD5MhSl/RctUyb1veTPVEDtnnw4Y5wQQsg2w2+uCSGEkGxB7SaEEEKyBbV78uHAOCGEkG2GAk0IIYRkC2o3IYQQki2o3ZMPB8YJIYRsM0kS60/qtljMCSGEEDKjULsJIYSQbEHtnnw4ME4IIWSbkbX4YcVbHpYQQgghMwq1mxBCCMkW1O7JhwPjhBBCthljYt0QZ4vDEkIIIWRGoXYTQggh2YLaPflwYJwQQsg2o8ujbOmMcS6lQgghhMw41G5CCCEkW1C7Jx8OjBNCCNlmKNCEEEJItqB2E0IIIdmC2j35cGCcEELINkOBJoQQQrIFtZsQQgjJFtTuyWe7Hxg3xuj/0WoNsGxYUQArasG4Yfrfj4E4hpVESPwYdqum54zjAtUa7MRBUq/B8kJYQQIkEYyXxinXGMsGbEduBCusw0QhTBjAjqHvgZzGE9fqcCpVRLUGknoTVmwjbLRg2da4rY7XgGk1YYImas1Aw8WtEFGjpefjVgCTGMRBBCdJ4FoWGq0ASaOFejPQMEkUwXJsRHK82ULQDFANQhSaLYRj79EK4IyFteNEw6PeRKUVavhGEMJvtFAJQiTNII1LPrfSe0RBCLvZ0riSVoCgFcJzHMRyLAzV5jAIUYuiR69pBbBtG0EQIg4jFBotmDjW8LKqgsTZDCOEYQQEIaIwRD2KgNiMxyH3yzVbam9l7J5iq2XbGB2zT9JjJwk8x0Kr4Wu4gqRN0tFowXNsWLaDJAo1faH4tNFCUGug1mihNeZHu95EvdlCXG+i1Uh951dreh/HGNhRBL9WT8uB7cBE6XVupZaWF6eqZQKOA6tZQ2LysBtVxCYPK2wgMUUtSzCJlsFKlFbFWpggcCxUgxiRYyOBQa0ewQocOJaF2Bj4joUgNmiGaTprzRiFxEv9nBjUghj1ags1K0BigHqUoN4IUXVC1JoRqmihUaugVrFQb4Wo2gFqtRCObaFeD9BoRXAjT8NrOD9Go9pE7NrwIw9+5Go8zVoV9cRHK07QrAdo76dYzyVohjFa9Rrc2EVLfFktoC7HalUEco+ajWYtQKsVoVFNULdDvYcdumg0Q9SNr3G1ogS2bSGoV9GsWXBDia+KME7QqHpo1lqwQhvGlRINGEfibSFsSHgXDU/sqKJWqaBRrWs89Woenm3p8XrVRuLaaDQjhI6FZq2Oej7ROBqRB9t3UIt9hMbotWk8Nc2bXOzpddVigno10PTZlqXxxQZIjEHVtDQvql6U/nfGfB24mk9V46FWDTX/xCYte1IdwwS50NX8a8QJfNsaPy+fJS+q0h5Z0OPyWfK53ZpIOWljtRyNR47ZUo8qlQlt46QRh9jiGGNpGwnZNO3yWalUkPPSJXqS0NH207g52K0qYLtA1Ez/C7YLYzuwghrghmh5cVr25Y8UO0u03UcrAcKggopttP5I2xc1KohjD9UobWfhO3CSEJWWBT904VeqsII6jJ+oplthAsuLEYm2ezURMQB5beOdahVJYBBbo3CkDQ19NKO07a4EaTsh+i0ESaLteT5yYZIGKibU9n80jFCJfLQXJxKbkrE2tlZpoWoFyEUOogR6fehaqFZDuLaFxLO1DZH/ch8JL21ntRWjYvn6eTQfoVapYzQfolqNNH4xadTyUa00kXiOtvHVSh526KARJqg1IkSuhYrx0YwNRhNXw47mAriVKpIkj2oQwAkcVJtxer4aIfIs2C0HtUoTuTjNK4lH2jCxu1YVTWqgWnEwGrRQqziqM6NWBdXERS50UKvWURlNNC9rkSijtLGAI22gpjHAaClGpR7CSPvYijFqHCSWoz6PPRuh9CeCGMZz9L6SD9IOt6TNrlRRCUZRdAMkfoRKPUIuctMyENmwvbTPZ8UR4lwCO2rBrqVtaRI5aDqh2pKrp+VI7tuMEoSJSbsCOdHzsfwH1H+SP1ImpVxJ2Y0DaHkxoaXlLnJtSLMfI0ANvr6vtGLVWuPZqNZDjNoOmnA1fyRNca2CSlhM0695Xceoa6MSunpPL3SARkVtDp2c5oGUmUoYq3/EZ5UQ8CpVVHOjmr5qpaX5Jlo/anwEcZLWK8douIo3qteLLnqmigoMYi8t35ZlIapXUHF8FFsxrLCp9bMSl7TeaZ1oxIikb2NbcJ0QTTun6RT/j+dPYjR8pSnlNsRoIUq1T+qFSduL0Iq1ny11sN2n8qMKEvFnIGUowKjvoVqTsutpXKNBFZEzCrtZQZCz4CKBHTa1HZFybrcqqLRycJwItqQjKsCSPv3oKBrGQYgQNeNpX8yP5dkih0qQqK2xaY71w5oI3VDjtqTPZ7tpWZI2Qz878gAwZntB47DiELEbwA1qMJalnyvyHEPtJhnSbs9EWt4jA30vZT7xQm1jEj9tm23fTtvDsQ5ky7HgxS00RItqEUat9PlGwkhbJfFImwxpk+NQ2zFB6pyVxFp/Iz+BE9bRsAPEzbS9k/Za6q+0o9JWSFuU5KTxSNBMRAvSeittkIwPNHwLOSvRvkYc2siJxoUWksjV5zkh9EbhNCuwWhW0MIqgUtWxhoY9ilxQhStthVtJ67mMLfixaqUVB0hiT+t+kvjajkZeBSICtuhBtYag3oRXqaCeFBG2KoDj630je1T7MHG1hmS0AuNFGqf0bZr2qGqXtGtVdxSjtSqSag2mUtHzjnyW5yKMwg+qOu7hVFLNcFrpvaRNlmcv8bU855rRUfVxTvROxjxEv+WZNg5hNSuotlwkVghH7KlUEI+lR59zJV/k/n4VlWRUtUd8G7mjsMfilnZV8i2RZ7laHXalgtAUNe2SVtFEzT/xSxJp/0quFx2RuOSc/G8FDnJhXX0ofg5tH14SoGn5CJCWQ9FgJ24hdnKqzdp/MJG25S15cPMd7QdJn0qukXImz96wQ71GbIpR1DZZyov0K0QPVUObsT6LaV8ogL6k3ZeyLG26lAHpR9acUYx6UvYdjCYVtOKcXiue9aJUy6UOSFlU/7VqqCBEJDaZtK8o9omuVAIPxTj9HLipLYFtUGkkGLXrWnalXyM6WfBS3yWxj6odjeuS5Gs9LmgfuGocjFaqCPOjGlbKsfQLRN9yrYrWA+lbSFdU0q6a53iaZrtWQyU3Ckd85QbqR61T9Soa1qi+91BHwzMI4gYqoYdRyctcqqXSV5B7SfhKaxSFROyxUYik75H2lyqtBL6foFo3GI0trcMVGb/T9iFRXQ+k/Fijqp0yLhcmefWjJ+UokP6MwahjaZkWvxelr257Wh6k7KfjKAmidp8xjLUf7QaOPttr29aMNB/8sK6+lP699HmkPy6+liZQ+mPtz9KX3rBtnDT43D3pWGbSc2l28fDDD2PRokUzbQYhhMwqli1bhoULF25zPM1mEzvvvDNWrly5VdfNnTsXDzzwAPL5tNNCyIZQuwkh5PFQu8lshtpNCCGPh9o9+9nuB8aTJMHy5cvR0dGh30bNJKOjozpILxWjs7MTs5ms2JoVO7Nka1bsFGjr1iNNvszkmT9/vv6KYzKQwfEgSH81saX4vs9BcbJJqN3bd5uYFTsF2kqfzoaySu0mWYDavX3rTFbsFGgrfTobyiq1Ozts90upyMDPZMyKnEykcs52McmarVmxM0u2ZsVOgbZuHV1dXZPqf5n1zZnfZDKhdu8YbWJW7BRoK30602WV2k1mO9TuHUNnsmKnQFvp05kuq9TubDA50wUJIYQQQgghhBBCCCGEkIzAgXFCCCGEEEIIIYQQQgghOxQcGJ9GcrkcPvnJT+r/2U5WbM2KnVmyNSt2CrSVEMJ2JnttYlbsFGgrfZqVskoIeRS23ZMPfbpj+zUrdmbNVjI72O433ySEEEIIIYQQQgghhBBCNoQzxgkhhBBCCCGEEEIIIYTsUHBgnBBCCCGEEEIIIYQQQsgOBQfGCSGEEEIIIYQQQgghhOxQcGCcEEIIIYQQQgghhBBCyA4FB8ZnKVnaEzUrtmbFzqzZSgghJHttd1ZszYqdWbOVEEJI9trurNiaFTuzZishZGrgwPgsotlsIooifW9ZFmYzWbG1VqthZGQEYRjOajuzZmtWOxRZsTNrthKyI5MVPcySrVnSwyzZmlWdyYqdWbOVkB2ZrOhhlmzNkh5mydas6kxW7MyarWRq4MD4LOGOO+7Av/3bv+FZz3oWDjjgAPz3f/83li1bhtlIVmwVO5/3vOfhOc95DnbffXecddZZuOuuuzAbyZKty5cvx5/+9Cf86le/QrVa1WPSoUiSBLOJrNiZNVsJIdnTwyzZmiU9zJKtWdGZrNiZNVsJIdnTwyzZmiU9zJKtWdGZrNiZNVvJ9GEZfj0y49x///046KCDcNxxx+Hggw/G7373O/z5z3/GYYcdhtNOOw377rsvZgtZsfXBBx9UO1/zmtfg2GOPxXXXXae2FotFnH322Tj88MMxW8iSrbfddhte+MIXoq+vD7fffjue/vSn4yUveQk+/OEPjwuKbc/8921ZsTNrthJCsqeHWbI1S3qYJVuzojNZsTNrthJCsqeHWbI1S3qYJVuzojNZsTNrtpJpRgbGycxy/vnnm+c///kTjn3jG98wz3rWs8yrXvUqc/fdd5vZQlZsvfTSS9WmOI7Hj/385z83L3nJS8zTnvY0c+ONN5rZQlZsXbdundlrr73MBz/4QfPII4+Yhx56yJx88snm4IMPNm95y1tMkiQarv2fdm4/PiWEZFcPs2RrVvQwS7ZmRWeyYmfWbCWEZFMPs2RrVvQwS7ZmRWeyYmfWbCXTD78OmQXEcYxHHnlE17lqc/LJJ+tLjl988cW6DtZsICu2BkGAe+65BytXrhw/9qIXvQjvfe97MXfuXHz+85/HqlWrMBvIiq1in9j6xje+EfPnz8eiRYtw3nnn4fjjj8fNN9+MU089VcPN9DptWbEza7YSQrKph1myNSt6mCVbs6IzWbEza7YSQrKph1myNSt6mCVbs6IzWbEza7aS6YcD4zNIexWbBQsWqODdd999+rm9ucYb3vAG/WnHf/3Xf2Ht2rUzaWpmbG3bucsuu6C3txd//OMfJ6wXJeuJyc/Rfv/73+Ohhx7CTJIlW4VSqaT5LT9Batvf3d2Nt73tbWqn2P+zn/1sps3MjJ1Zs5UQki09zJKtWdLDLNmaJZ3Jip1Zs5UQki09zJKtWdLDLNmaJZ3Jip1Zs5XMADMwS32HR36eseHPdwT5Sc8+++xj1q9fr5/DMBw/N2/ePPOlL31pRvyWFVuDINDXhrz85S83CxYsMLfccsvjwu+yyy7m4x//uJkJsmTrhgwPD5sjjzzSvOxlLzOrV6+ecK5SqZgDDzxQf44002TFzqzZSsiOTlb0MEu2ZkkPs2RrFnUmK3ZmzVZCdnSyoodZsjVLepglW7OoM1mxM2u2kumHM8anmbvvvlt/qiO7S5977rm46qqr9Pjll1+u32AdddRR+tMo13X1eKVSwbx58/SnPbR149x555046aSTdGfp97znPbjkkkv0+I9//GMsWbIEr3rVq/QbwPa37GEY6jfwCxcunHafZsnW4eFhnaGwevVq3bG5q6tLf270y1/+Ep/85Ce1bLYpl8v6M7R//OMf47bTzuz6lBAyEWr3jq2HWbI1KzqTFTuzZish5FGo3Tu2HmbJ1qzoTFbszJqtZBYwA4PxOyx33XWX6e7uNscdd5x53etep99K7b333ubcc8/V8/fee6/Zf//9zc4772y++tWvmiuuuMKcccYZpq+vz9x///20dSOIz8SnJ510kjn11FPNS1/6UjMwMGDe+9736vlGo2GOOOII/Ub99NNP1w1L3v/+9+s1f//736fVp1my9W9/+5vZd999za677mqWLFliXvGKV5hbb71Vz/30pz81uVzOnHjiieaee+4Zv+b1r3+9Of74400URbQzwz4lhEyE2r1j62GWbM2KzmTFzqzZSgh5FGr3jq2HWbI1KzqTFTuzZiuZHXBgfJqQn0W9733vM6997WvHd7qVRvdTn/qUDnx/+tOf1mPyU583vvGN5oADDtAB8kMOOWSjP/OhrSlnnnmmeeELXzj+s7M1a9aYb33rWyafz5t3vOMd426SLxiOPfZYs8cee5jnPe955q9//eu0+jRLtj788MNm7ty52jn485//bL785S+rPZ2dneZ3v/udhvnNb35j+vv7zTOe8QztVEi5LpfL5rbbbqOdGfYpIWQi1O4dWw+zZGtWdCYrdmbNVkLIo1C7d2w9zJKtWdGZrNiZNVvJ7IED49PIi170Ip0tviGrVq0y55xzjlm4cKHOEm+zcuVKPTc0NGRmgqzYKt/0yVpRG9Jqtcxll11misXihDXC5JthsbFarZqZICu2XnPNNeaggw4ya9euHT/2z3/+05xwwgnambjhhhvGv9j54he/qOn68Ic/bO68807amXGfEkKyq4dZsjUrepglW7OiM1mxM2u2EkKyqYdZsjUrepglW7OiM1mxM2u2ktkDB8ankfPOO0830JCf9mzIsmXLdKH/Y445ZkIFnkmyYquIm2yScf311z9uA4WzzjpLl6t5bBpmiqzYKkv42LZtli9fPuG4fH7Na16jv2S47777Jpxr/wpiOsmKnVmzlRCSTT3Mkq1Z0cMs2ZoVncmKnVmzlRCSTT3Mkq1Z0cMs2ZoVncmKnVmzlcweuPnmNPK0pz0NDz/8MC677DKsX79+/Lhs8PCa17wGv/71r/HQQw9hNpAVW/fee2/dmFQ207j33nsnbKBw7LHH4p577pkVdmbJ1sMPPxwHH3wwvvjFL2J0dHT8uGwC+4EPfAD9/f26UYkQx7H+tyyLdm4HPiWEZFcPs2RrVvQwS7ZmRWeyYmfWbCWEZFMPs2RrVvQwS7ZmRWeyYmfWbCWzBw6MTzHtyiYceeSReN/73oezzjoLX/va17B8+fLxc3vssQee8pSnYCbJiq0b2rnffvvh7W9/O6666ip8+ctfxm233TZ+brfddlNbkySZIUuzZWubwcFB3b37//7v//CjH/0IjUZj/NwhhxyiNl5//fX62XEc2rkd+ZQQki09zJKtWdLDLNmaNZ3Jip1Zs5UQkh09zJKtWdLDLNmaNZ3Jip1Zs5XMHtyZNmB7RyqbLFnzhz/8Ac961rNU9KTR/tSnPoVly5bhJS95Cfbdd19ceOGFGB4e1m+yaOvGET/Kt3ltn0pD96pXvQpveMMbtIE799xz8eCDD+qxAw44AJdeeql2LGayM5EVW6VMiq1im23b+MxnPoP7778fn//851Gv1/HmN78ZxWJRwy5ZsgTz58+nnduJTwkhj4faPXlQu6eOrOhMVuzMmq2EkIlQuycPavfUkRWdyYqdWbOVzFJmei2X7ZkwDPX/SSedZHbddVfzhz/8Yfzc//t//888//nP191v99lnH7N48WJzyy23zIh9QnvH5tlo6+rVqx+37tNHP/pRs2DBAvPjH/94/NgvfvEL3TyhVCqZvffe2+y+++7T7tONkRVbxcdi69VXXz1+TGw84IADzHOf+1zdAEbKR0dHh7nrrrto53bkU0LIo1C7Jwdq9/SQFZ3Jip1Zs5UQkkLtnhyo3dNDVnQmK3ZmzVYy++DA+CQim2Lcfffd4zvdtpGNHd7xjnc8bvdoEZ7bb7/d3HzzzbrD9HRyzz336O67//jHP2a1rXLPPfbYw1x00UXjg/fCgw8+aD71qU+Z9evXP2636Ycfftjcf//9075Jiex2/IUvfMF84AMfML///e9NvV4ft/XMM8+cVbZujP/7v/8zc+fOVb/K7twbfjHyxje+0Rx22GHmFa94hfnb3/42o3b+5je/mZV2rlu3TutJFmwlhDwKtXvyoXZPH9TubYPaTUg2oXZPPtTu6YPavW1Qu8lkY8mfmZ61vj1w++23461vfStGRkYwNDSky2PImlZt2j/rmGkku5vNpq679Je//EXX3vr3f/93LFq0aNzG9k+nZhrZFEM2T5CfvsgSNIsXL97oT2ZmS/4fddRROOigg3SDD/HlT37yE+y///6zKv+Fv//97/jWt76F1atX46lPfSpe+MIX6lprwtVXX40DDzwQPT09jysHrVZL/e2607MC0wMPPKA+lM1oZD0w2XymzbXXXqu+nQ12CvJTrec///k44YQT8I53vGPCz7Nmm62EkEehdk8+1O6pgdo9+VC7Cckm1O7Jh9o9NVC7Jx9qN5kSJn2ofQdEZl/39/ebM844Q2eL/+pXvzJLly41H/nIRzYa/sILLzQ//OEPzUzy7//+7+bNb36zKRQK5rWvfa154IEHZpWtMjv8bW97m9rY/vy73/3OfPvb39ZZ7Y+d0f75z3/enH/++WYmWL58udlrr710VnAURXrsKU95ivnKV76y0fAzaeudd95purq6zDHHHGNe+cpX6vujjjrKfO1rX9to+H/9619mJrjtttvMwoULzfOe9zxz+OGHG9u2zXnnnbfJ8DNlZxvxn2VZ+lOts88+26xYsWLW2koISaF2Tz7U7qmB2j01ULsJyR7U7smH2j01ULunBmo3mQo4ML6NVCoV8+pXv9q8613vmiAu73nPe8xLXvKSjf7sY+edd9aBSbl2umkvR/K+971PlyeRBjuXy+myDrVaTQds2wN3M2mrDDA/85nPNJdccol+fs5znmMOOuggHcjdZZddzNvf/nbz0EMP6bnh4WEd3D3iiCMet1zJdCDrscva63//+9/Hj73mNa8xH/zgB83rX/96Hcxv2yoD+jNlqyzdIvacfPLJ48dkKR2x9elPf7r54he/OCH8Zz/7WbX1L3/5y7TaKeVP1rk//fTTx8vrt771LTNnzpwJPp5pOzdElkJ505veZM466ywzf/588x//8R+P+/JmtthKCKF2TxXU7smH2j11ULsJyRZ87p4aqN2TD7V76qB2k6lgdqztkHFKpdL4khmCLJnxzGc+U5eCCIIAYRjqcfkiore3F7/97W9x0UUXoVwuz5jNxxxzDG655RY85SlPwe9//3v8z//8D/bee29ccMEFuuyHILZec801M2KrLC8xMDCA4eFhfOITn0Aul1Mb165di/e85z36E7rvfOc7amtXVxcuvfRS/L//9/90uYrpRpbOWbVqFf75z3/q0hjnn38+fvzjH+v7devW4atf/aoeq1ar6O7unjFbfd9XO9tLeUh53HXXXXHeeedhzz33xA9/+EP8/Oc/Hw/f39+v5XfOnDnTZqPk5+WXX652yRI/7eVnDj74YHieN142N2Qm7Hws4ss//vGParMsT/SNb3wDl1xyCV7xilfgox/96KyylRCSQu2efKjdkw+1e+qgdhOSPajdkw+1e/Khdk8d1G4yJUzJcPsOgMxkbe9+veHSCLIbrvA///M/Zt99951wTbVaNTNla3uJjw03fJBNLdsbRB577LG6XIX839wyENNpp8xql5nYJ5xwgvn6178+IazMxpblS4IgGPf5TNoqs+oHBgZ06Q+Zgf/LX/5y/Ny5555rFi9erJtwzhRiq/hKlqZ51ateZZrNpvqtPSNbNg6VjSBl9viGjIyMTLut1113nS5LtCFi55IlS8w111yz0Wtmws7H8oIXvGB8SSJZ9qVUKukvHGRppdlmKyE7KtTuqfEptXtqoHZPPdRuQmY/1O6p8Sm1e2qgdk891G4y2XDG+JPgrrvuwhvf+Eaddf3ud78bd9xxx4QNIQWZ6brh7NbTTjsNxx9//Pj56bb16KOPxjvf+U5ceeWVatdhhx2GnXfeGYVCASeddJLOwP72t7+ts8dlxusjjzwyY3bK/X/3u9/h7LPP1hnWl112GR588MEJ4V/wghfoN7G1Wm3aNwrd0NaTTz5ZZwr/8pe/xG9+8xv18T777KMznKMo0vDPfvaz1VbZ9HS6aZc3mQkgM67f9KY34YorrsDXv/519ZuUUwmzdOlSnHPOOfjBDzC/OygAAB9JSURBVH6AO++8c7zsdnZ2TqudbX+JLcKGewOLve1fX7Q3Cl25cuW02vlYWzdEZoJLuRVkA1bxudSvv/3tb1i+fPl4uOm0lRDyKNTuyYfaPTVQu6fOp4+F2k3I7IbaPXU+5XP35ELtnnyo3WS64MD4ViIDXocffrhWUhn8vP766/GpT30K73//+/W867r6v1gsjg+MyvIKspyGLKkgg2UzZesNN9ygtp5++um6NIkMlA4ODuIXv/iFDpbKoKm8v/HGG6d1sPmxdsr93/e+96mtssyHDOLL0iO/+tWvdCBckPcyaC4DztPJY2296aab8K53vQsf+tCHsN9++2HevHmo1+vo6+sbLwuyrIrYKkvDTPcu2LI0zooVK8aPPec5z8FnPvMZLa//9V//pcfaZbKjowN77LGH/kSxvYTJTNnZHhCXcij1qNFoqJ3tQWWpU89//vM3urTKdNvaHqw/9NBD1W/vfe979YuSW2+9Vd9LOZblYab7SzFCyKNQuycfavfUQO2eHp9SuwmZ/VC7p96nfO6eHKjdkw+1m0wrkz4HfTtGlp7493//d91ss83o6KhuuPfUpz51wqaGP/7xj3VDQwnv+765+eabZ42tssSLLKnx0Y9+1LzoRS8yf/7zn/V8++dUjUZjxu2UzQsPPPBA85a3vMXcdtttuhHnwoULzf77729e/OIXm+7ubnPrrbdOm51P5FOx65RTTtENF3fbbTdz+OGHm49//ONqf19f37TbKptq9vb2GsuyzEc+8hGzZs2a8XOyyeqZZ56p5z72sY+ZW265RTdaleVLZNPL1atXzwo7N/ypn5RJ2XRVNq389Kc/rcuUtMvtbLFVNlmVc/PmzTM33XTT+PHPfOYzG900lBAyPVC7p8+n1O5tg9o9+VC7Cckm1O7p8ym1e9ugdk8+1G4y3XBgfCs58cQTzbOf/ewJx0RQPvvZz5qnPe1p5pxzzhlfY1wGyXp6enQwbzbZev7555sjjjjCvPe97zWPPPLI466b7jW7N+fTgw8+2Fx44YV67Jvf/Kb5xCc+oWt233vvvdNq4+ZslR3SxVYZyP/c5z5n7rjjDnPkkUfqmt3HHXecufPOO6fVRlnL/qSTTlJbL7roIi2HH/rQhyYMeMtg8yWXXGLmzp1rFixYYPbcc08zf/78af0CZ1N2bmxwXDjggAO0PMgXTRsOPM8WW6VMyhcNf/3rX/Vze/12QsjMQ+2eXp9Su7ceavfkQ+0mJNtQu6fXp9TurYfaPflQu8lMwIHxLaQ9WCyDtM94xjPMPffcM+H8+vXrdca4zBRutVrmvvvuM8961rN0tvNss1VmB7/1rW9V+2RQd7b79JBDDnnc5qGz1VY51x4QlXIgr+lGNlSVwdvLL798wpc0jx0cF2SzSNnsUjYLffjhh2eNnRsOOEveS5mVjSwdx5mROrWltsps/DYzsSksIWQi1O7Jh9o9NVC7p9en1G5CZi/U7pnzKZ+7tw5q9+RD7SYzAQfGtxIZ8O7v79fZo+1B5bbQPPTQQ9rhlkFGGRyVb7uyYOtMsyV2/uIXv5gVA45bYuvPf/5zM9M8tuzJQ6HY9sEPfnD8YTAMQ/Pggw+a2Wrn2rVrx+0Um6+66iqdjT8bbW1/4SD1/v77758hCwkhm4LaPflQuycfavf0+pTaTcjshto9Mz7lc/fWQe2efKjdZLrhwPiT4Le//a3J5XLm3e9+94QZJytWrNC1pq+//nqTFVv/+Mc/mtlAVuzMmq0y27rd2fne9743PlNKltB5//vfb17xileo8Mz07OYnsvPlL3/5hNnYs92ns8VWQsijULt3bD3Mkq3U7pnxKbWbkNkHtXvH1sMs2UrtnhmfUrvJZMCB8SfJ//7v/2ojLZVRZp/cddddunmhbLy3bNkyM5vIiq1ZsTNrtoqYtJd3EVs9zzN77LGHcV13fD3s2WynLJ8ym+zMkk8JIdltu7Nia1bszJqtWdEZajchZKrJUtudFVuzYmfWbKV277g+JdnGkj8gT4pbbrkFH/jAB/Cvf/0LruvCcRxcfvnlOOCAA2adR7Nia1bszJqt7WpuWRae97zn4dZbb8W1116LfffdF7OJrNiZNVsJIdlsu7Nia1bszJqtWdGZrNiZNVsJIdlsu7Nia1bszJqtWdGZrNiZNVtJNuHA+DYyOjqK9evXo1KpYN68eejv78dsJSu2ZsXOrNkaxzE+9KEP4YILLlAx2W+//TAbyYqdWbOVEJLNtjsrtmbFzqzZmhWdyYqdWbOVEJLNtjsrtmbFzqzZmhWdyYqdWbOVZA93pg3IOp2dnfrKAlmxNSt2Zs1WYe+999Zv3Ge7kGTFzqzZSgjJXtudFVuzYmfWbM2SzmTFzqzZSgjJXtudFVuzYmfWbM2SzmTFzqzZSrIFZ4wTsgMhP0OSnyDNdrJiZ9ZsJYQQkj2yojNZsTNrthJCCMkeWdGZrNiZNVtJtuDAOCGEEEIIIYQQQgghhJAdCnumDSCEEEIIIYQQQgghhBBCphMOjBNCCCGEEEIIIYQQQgjZoeDAOCGEEEIIIYQQQgghhJAdCg6ME0IIIYQQQgghhBBCCNmh4MA4IYQQQgghhBBCCCGEkB0KDowTQmYd55xzDg4++GB0dHRgcHAQL3vZy3DvvfdOCNNsNvHud78bfX19KJfLeOUrX4lVq1aNn//b3/6G1772tVi0aBEKhQL22msvfPGLX3zcva699loceOCByOVy2HXXXXHxxRdvsZ1vf/vb4TgOfvCDH2A6Ofvss3H44YejWCyiu7t7o2Esy3rc6/LLL59WOwkhhOw4ULs3D7WbEELIbIPavXmo3TsGHBjfzjjxxBN1EHG6kcHE9uDbqaeeiiwjadnUYOO2smTJElxwwQVTEvf2xHXXXaeD3n/605/w61//GmEY4gUveAFqtdp4mPe///342c9+poPSEn758uV4xSteMX7+5ptv1kH1//7v/8add96Jj370o/jIRz6CL3/5y+NhHnjgAbzoRS/CkUceiVtvvVXL7lvf+lb86le/ekIb6/W6DjSffvrp+Pa3v43pJAgCHHfccXjnO9+52XDf+c53sGLFivHXTLQNhJAnhtq97VC7Zx5q9+ahdhOyfUHt3nao3TMPtXvzULt3EAzJDJJdm3t98pOfNMPDw2ZoaGjabfvOd75jOjs7zYoVK8zo6KjJMpKWrq6uKYl79erVplarmZnkuuuuM//2b/9m5s2bp+XmiiuueFyYlStXmje96U0aplAomKOPPtr8/e9/Hz//wAMPbLIcfv/73x8P9+CDD5oXvvCFGsfAwID54Ac/aMIwfEIbJY499tjD5HI5s88++5jLLrtM4xbbhUsvvdRYlmXK5bIe/+tf/2ruvvtufX/DDTdsMt6TTjrJzJkzx3R0dGge77vvvmavvfYaP99oNMySJUs0XsdxzEtf+tJNxnXxxRebpz/96VrnisWieeihhyacf85znmPe9773TTgm8Ylf2yxfvlz9k8/n9b7f/e53zU477WS+8IUvmG0tq5vKW0LI9ELtnh6o3dRuajchZLKgdk8P1G5qN7WbzAY4YzxDbDjzU2Ydd3Z2Tjj2wQ9+EF1dXVM22/mJkNnic+fO1eUvyMYZGBjQ5S9mEpl1vf/+++Oiiy7a6HnpC8rM4vvvvx8//elP8de//hU77bQTjjrqqPEZ27I8yYZlT15nnnmmLmly7LHHapg4jnU2tnzL+sc//hGXXHKJzgr4xCc+sVn7JKwsgfKWt7xF7y22vPGNb9Rzvb29+v+uu+5SO+WnTW323HNPLF68GDfccMMm4/7lL3+pS7DILPSf//zn+Mc//qF2tpH3Mqs/iiJN7+b41re+hde//vVa5yTNW7MESxtJl8x0l+VcfvSjH+Eb3/gGVq9ejclCZt339/fjkEMO0VntaT+fEDKdULuzD7Wb2r0h1G5Ctn+o3dmH2k3t3hBqN9ksMz0yTyb321WZjbrhLFeZtXrKKafozNXu7m4zODhovvGNb5hqtWpOPPFE/YZul112Mb/4xS8mxHP77bebY445xpRKJb3m9a9/vVmzZs1W23PRRReZXXfdVWf+SjyvfOUrx8/FcWz+8z//U2fKyozZ/fbbz/zgBz+YcP0dd9xhXvSiF+kMX7H1mc98prnvvvvGrz/zzDPNggULjO/7Zv/99ze//OUvHzer+Uc/+pE54ogjdNay3OOPf/zj42xftGiRnn/Zy15mPvvZz05Iy6233qrXy/3FjgMPPNDcdNNNG/VDkiQ6c1/iE5tkxvV73vOe8fOPnQ0s9n3zm9/U+8r9xVc//elPt9gHgly/5557qo9llrX4fEvZ2Kzie++9V4/LfduIr2XGt9xrUzz1qU/VGdltpEzZtq2zz9t89atf1V8WtFqtTcbz6le/WtO74b2l7M6dO3f8mMysFv+281hmjAsHH3ywOf300zcar1wjYb/0pS+NH5OyI8ceeeSR8WNXXnmlHjvhhBM2OWNcZs97njdeJ8SHO++8s+b/ls4Yb89w37As/eMf/9BjkzFj/NOf/rT5wx/+YG655RZz7rnnavn44he/uEXxEkKmBmo3tbsNtZvavTGo3YTMPqjd1O421G5q98agdmcfzhjfAZCZujJr9M9//jPe85736LrEsj6xbN53yy236NrNb3jDG3TNZGF4eBjPfe5zccABB+Avf/kLrrrqKt3U8NWvfvVW3Veufe9734tPf/rTunGixPPsZz97wkYPl156Kb72ta/pGtCyZrTMwJV1roRHHnlEw8umiL/97W91zeiTTjpJZ/MKspHi5z73OXz2s5/FbbfdhqOPPhoveclLdBbwhsja0jKbXtaQ3n333XU2cjuOG2+8UWcmn3LKKXpe1po+66yzJlx/wgknYOHChbjpppvUhjPOOAOe5200zTLr9wtf+AK+/vWvqx0/+clPsO+++27WTzLTWnwraXjhC1+o91u/fv0W+eC73/2uzsCWmdN33303/vM//xMf//jHNc+fLK1WS//n8/nxY7Ztqw1/+MMfNnqN2CX+E1+2kZnbkvY5c+aMH5M8Gh0d1fzeFHLdhrO1ZdazjOFvyy8h7rjjDt0oU9Iked1GZu/LLx2kHGyMZcuW6Sz49uv3v/+9HpfZ15IWqVeC5NvIyIjm0ZYidcJ1Xd34s41s/tnT0zP++R3veMeE+28NUg6e8YxnaD3+8Ic/rGuhn3/++VsVByFk5qB2U7u3Bmr3o1C7CSEzBbWb2r01ULsfhdpNZpSZHpknU//NtcwwbhNFkc4Cf8Mb3jB+TNYF33Bt5v/4j/8wL3jBCybEu2zZMg0js4m31B6ZqS2zgze25niz2dR1mR87e/stb3mLee1rX6vvP/KRj+gs3CAINnrP+fPnm7PPPnvCMZkx/K53vUvft2cT/9d//df4+TvvvFOPyWxdQe4lazxvyGte85oJaZGZ2rKe9Jbwuc99zuy+++6btHljM8Y/9rGPjX+WmfxyrD3z/Yl8ILP9Zf3tDZH8O+yww570jHG51+LFi81xxx1n1q9fr7O7ZcaxhH1suWjzzne+c8Ja3cLJJ5/8uPCyvrrE89hfKGyIzMRup+nd7363Wbhwof4yQH5x0Obqq6/WeP72t79NmDEudn/+85+fEJ/kuVwrdUHyZkOe9axn6Uz9r3zlK+PHvv3tb2u5lbokZUNmcbdf9Xpd65D8EkDWOJd1yNsvseN1r3vdeDxHHnmkee973zvhfhJfe8b4T37yE+O6rs6I35Cenp7xMrJq1aoJ99+Wdfl+/vOfq41S9wghMwO1m9otULup3dRuQrIDtZvaLVC7qd3U7u0XzhjfAdhvv/3G3zuOg76+vgmzmNszettrG//tb3/DNddcM2GmqqzfLPzzn//c4vs+//nP17Wply5dqjPSZXZze1b6fffdp+8lzIb3kRnk7XvIDORnPetZG52dLbOOZW1mmRG7IfJZZk5vKv3z5s2bkFYJe+ihh04If9hhh034/IEPfABvfetbdRbzueeeu1kfyEz8RqOhaT755JNxxRVXjM/u3hQb2lcqlXTt+LZ9m/OBrPcttsgs7Q19KDPetyafHovc68c//jH+/ve/65reMqtayoOsoy0zxx+LpPeyyy6bMFt8S3jooYcm2C2z3dvImL3M7Bb/ySzs9szsNgcddJDaef3110+YgS1xSv61Z1qL7XvvvTfe9KY36S8jHouElTXQN0TWH2+XAbmHzOJuvwqFAn7xi1+gUqno+ueSP+3X9773PfWb/OKiva6drE+44frlMnO9zR577KFlQ+JpI/ViaGho/PPg4OCE+28LYqPMRpeZ/4SQ2Q+1m9q9NVC7qd2EkJmH2k3t3hqo3dRuMjtwZ9oAMvU8dlBVlo7Y8Jh8FpIk0f/VahUvfvGL8ZnPfOZxcbUHlrcE2YRTlmqRjQX/7//+T5f8+NSnPqVLksg9hCuvvBILFiyYcF174E4GISeDzaV1SxCbX/e616mtsnnjJz/5SVx++eV4+ctf/riwsimlDND+5je/0QHWd73rXbp8hSwPs6nlVzaWP237NueDtg+/+c1vPm5wX74A2RZk4FkGUmV5EBk4lkFeucfTnva0x4X94Q9/qF9ytDfIbCMbscryPRsiS/K0z82fP1/v0aa9saac+8pXvqKDyLL5p5QjGeiXL3RkEF58IhteykB8e9kb2Yzzy1/+sg5oP/3pT9cvJmRZHflCRgbE5csNGbheuXIl1qxZo+kR5AuP8847T8unLKMjg/Df//73Na8l/KY23ZRNRWUD0w15ylOeossByRdAsvyLLEck95W4dtllF3z+858fHzQX5Msm+bLlbW97G7761a9qOTjttNM0fe1yuinkCwBZbkf+y4B7248yeC5fCPzsZz9TX4svZPkYKYvyxYMsKUQIyQbUbmr31kLtpnYTQmYWaje1e2uhdlO7ySxgpqesk6n/SddjNwB87HIej11S49///d91E8cwDLfZng2RZUJk6QhZYkWWV5HNAC+99NJNhv/Upz71pJZSkeU3hMduzCgMDQ3psWuuuWaTS6kcf/zxm02LnH/xi19stoR77rlH73fzzTdvcimVxy5lIvcWf26pD2SzhyfLxu6/qc0mZSPNX/3qV487J2Vsw01VH7v5piwH0ubrX/+6LlOyueU8ZPNNsWtjr7ZfhEajoZvCynHZvPXlL3+5LgvURjZB3VgcsgxKG0mPHNt77711M8+lS5eO3+OxdUmQjUSlDH//+9/f5JIyBxxwgL6XPJPPvb29upTLOeecM2HzTWH58uXm2GOP1bogZUOWkJGwX/va1zbpn7ZtG0tbu1zLUjyyGaps1ipLJ8nGtBLnY5dtIYRML9RuardA7aZ2U7sJyQ7Ubmq3QO2mdlO7t184MJ5RplKgH3nkETMwMGBe9apXmT//+c/mvvvuM1dddZU58cQTdX3lLbXnZz/7mfniF7+oA9P/+te/dB1nGSi944479PxHP/pR09fXp+t3yz1k8PjCCy8cX8977dq1ev4Vr3iFuemmm3RwVgbSZbBZkDTIIOvll1+uxz784Q/r+tQSbksHxmVddbHp/PPP1+u+9KUvme7u7vG0yJrSMtAu4SUNf/jDH3R9sdNPP32TfpA1zW+//Xbzz3/+U9cPlzWsJS1PZmD8iXwgO2NL/OJnWf/9tttu0zWyZa3zTVGpVNQn8pL7y5rc8v7BBx8cDyMDv5JmSYOshS12iw2PRda9lrW222uib4iUlX322UfXGb/11lu1DEm5knXTN8f111+vg8+f/exndS14GeCWfBWftlm3bp3afOWVV2oapAzI5w0HxjfGMcccowPXN954o+blbrvtNr6m/YZrkktc8uXHEUccMe6r6aC9lv9vfvObabkfIWR6oXZTuwVqN7WbEJIdqN3UboHaTe0m2y8cGM8oUynQggzAygxcGSSWgdc999zTnHrqqSZJki225/e//73eXzYTlDj2228/8z//8z/j5yWuCy64QGeny8CnDJoeffTR5rrrrhsPI5srysCqbNQpm2DKZokyWCvI7FeZUb1gwQK9XmbFbjhAuyUD48K3vvUt3eBRbJTBUBmQbadFNp6UGeKLFi3SGcXyTfEpp5yis5U3hvjw0EMP1QF7man79Kc/fcIg59YOjD+RD4Tvfve7OjtY7BNfP/vZzzY//vGPzaaQtG9stvGGM5lloF18In6VDS1lgF988VhkkFt8s6mZyPJlgsyIFt/29/eb0047bYt+iSAD87JRpqRJZnPLAPiGiH82lgYZRN8cMqAuA+Eyk1ry6M1vfrN+UbAhkkcbi3sqkE1Ef/rTn5r7779fvxB4xjOeYZYsWbLJXwgQQrINtZva3YbaTe0mhGQDaje1uw21m9pNtk8s+TPTy7mQ7HPxxRfj1FNPnbCGMiFk8/zqV7/SdcXvv/9+XUv98MMPxwUXXKCb1hJCyFRD7SZk66F2E0JmEmo3IVsPtZtsDm6+SSYN2ahRNv6TjQc3tnEnIWQiRx99tL4IIWSmoHYTsnVQuwkhMw21m5Ctg9pNNgdnjJNJoVKpYNWqVfq+u7sb/f399CwhhBAyi6F2E0IIIdmC2k0IIZMLB8YJIYQQQgghhBBCCCGE7FDYM20AIYQQQgghhBBCCCGEEDKdcGCckO2cJUuWwLIsfXFzVEIIIWT2Q+0mhBBCsgW1m5BswoFxssNx0UUXqWjl83kceuih+POf/zx+rtls6uahfX19upHoK1/5yvG10zfHD37wA+y5554a57777otf/OIXE84bY/CJT3wC8+bNQ6FQwFFHHYV//OMfTxjvtddeiwMPPBC5XA677rqr7kK+NekRbrrpJvzoRz96wnsRQgghsxVqNyGEEJItqN2EkExgCNmBuPzyy43v++bb3/62ufPOO83JJ59suru7zapVq/T8O97xDrNo0SJz9dVXm7/85S/m6U9/ujn88MM3G+f1119vHMcx5513nrnrrrvMxz72MeN5nrn99tvHw5x77rmmq6vL/OQnPzF/+9vfzEte8hKz8847m0ajscl477//flMsFs0HPvABjfdLX/qS3ueqq67a4vS0ueaaa4xU96GhoW3wHiGEEDL9ULup3YQQQrIFtZvaTUhW4MA42aE45JBDzLvf/e7xz3Ecm/nz55tzzjnHDA8P64D2D37wg/Hzd999tw4o33DDDZuM89WvfrV50YteNOHYoYceat7+9rfr+yRJzNy5c835558/fl7ulcvlzPe+971Nxnv66aebvffee8Kx17zmNeboo4/eovRsCAfGCSGEZBVqNx+uCSGEZAtqN7WbkKzApVTIDkMQBLj55pt1GZM2tm3r5xtuuEHPhWE44bwsj7J48WI930aWLfnUpz41/lnObXiNcPTRR49f88ADD2DlypUTwnR1demyJxvGe8QRR+DEE0/c4nifKD2EEEJI1qF2E0IIIdmC2k0IyRIcGCc7DGvXrkUcx5gzZ86E4/JZBq7l5fs+uru7N3q+zS677IL+/v7xz3JuU3G2z7ePbS5eGYCXNcifKN7R0VE0Go0nTA8hhBCSdajdhBBCSLagdhNCsoQ70wYQkjWuvvrqKYn30ksvnZJ4CSGEkB0dajchhBCSLajdhJDpgDPGyQ6DzPJ2HAerVq2acFw+z507V1/ys6/h4eGNnt8Ucm5TcbbPt49NRrydnZ0oFApPmB5CCCEk61C7CSGEkGxB7SaEZAkOjJMdBlkm5aCDDprwzXOSJPr5sMMO03Oe5004f++99+Khhx7S85tCzj322+xf//rX49fsvPPOOlC9YRhZDuXGG2/cpnifKD2EEEJI1qF2E0IIIdmC2k0IyRQzvfsnIdPJ5ZdfbnK5nLn44ovNXXfdZd72treZ7u5us3LlSj3/jne8wyxevNj89re/NX/5y1/MYYcdpq8Nee5zn2u+9KUvjX++/vrrjeu65rOf/ay5++67zSc/+UnjeZ65/fbbx8Oce+65ep+f/vSn5rbbbjMvfelLzc4772wajcZ4mDe84Q3mjDPOGP98//33m2KxaD70oQ9pvBdddJFxHMdcddVVW5yeNtdcc42R6j7E3bEJIYRkDGr30ExnASGEELJVULup3YRkBQ6Mkx0OGdSWwW/f980hhxxi/vSnP42fk4Hqd73rXaanp0cHpV/+8pebFStWTLh+p5120sHvDfn+979vdt99d41z7733NldeeeWE80mSmI9//ONmzpw5OpD9vOc9z9x7770TwjznOc8xb3rTmx43oP3Upz5V4126dKn5zne+s1Xp2TAeDowTQgjJKtRuQgghJFtQuwkhWcCSPzM9a50QMrVce+21OPLIIzE0NITu7m66mxBCCJnlULsJIYSQbEHtJiR7uDNtACFkatl7771x//33082EEEJIRqB2E0IIIdmC2k1INuGMcUK2cx588EGEYajvly5dCtvmnruEEELIbIbaTQghhGQLajch2YQD44QQQgghhBBCCCGEEEJ2KDh1lBBCCCGEEEIIIYQQQsgOBQfGCSGEEEIIIYQQQgghhOxQcGCcEEIIIYQQQgghhBBCyA4FB8YJIYQQQgghhBBCCCGE7FBwYJwQQgghhBBCCCGEEELIDgUHxgkhhBBCCCGEEEIIIYTsUHBgnBBCCCGEEEIIIYQQQsgOBQfGCSGEEEIIIYQQQgghhOxQcGCcEEIIIYQQQgghhBBCCHYk/j/fujA+x0beQAAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1500x400 with 6 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    ds[\"vel\"][i].plot(ax=ax)\n",
+    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Average the Data\n",
+    "\n",
+    "As this deployment was configured in \"burst mode\", a standard step in the analysis process is to average the velocity data into time bins. \n",
+    "\n",
+    "However, if the instrument was set up in an \"averaging mode\" (where a specific profile and/or average interval was set, for instance, averaging 5 minutes of data every 30 minutes), this step would have been performed within the ADCP during deployment and can thus be skipped.\n",
+    "\n",
+    "To average the data into time bins (also known as ensembles), you should first initialize the binning tool `ADPBinner`. The parameter \"n_bin\" represents the number of data points in each ensemble. In this case, we're dealing with 300 seconds' worth of data. The \"fs\" parameter stands for the sampling frequency, which for this deployment is 1 Hz. Once the binning tool is initialized, you can use the `bin_average` function to average the data into ensembles."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "avg_tool = api.ADPBinner(n_bin=ds.fs * 300, fs=ds.fs)\n",
+    "ds_avg = avg_tool.bin_average(ds)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dateframe, velocity histogram, and contour plot for 5 minute averaged velocity. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 33,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "[Text(0.5, 0, 'Frequency [Hz]'),\n",
-              " Text(0, 0.5, 'PSD [m2 s-2 Hz-1]'),\n",
-              " (0.01, 1),\n",
-              " (0.0005, 0.1)]"
-            ]
-          },
-          "execution_count": 33,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
+     "data": {
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+       "<defs>\n",
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+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
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+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
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+       "html[data-theme=\"dark\"],\n",
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+       "  );\n",
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+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
+       "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
+       "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
+       "Coordinates:\n",
+       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+       "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
+       "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
+       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * beam            (beam) int32 16B 1 2 3 4\n",
+       "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * q               (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+       "Data variables: (12/38)\n",
+       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+       "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
+       "    ...              ...\n",
+       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+       "Attributes: (12/41)\n",
+       "    fs:                        1\n",
+       "    n_bin:                     300\n",
+       "    n_fft:                     300\n",
+       "    description:               Binned averages calculated from ensembles of s...\n",
+       "    filehead_config:           {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;...\n",
+       "    inst_model:                Signature1000\n",
+       "    ...                        ...\n",
+       "    has_imu:                   1\n",
+       "    beam_angle:                25\n",
+       "    range_offset:              0.6\n",
+       "    declination:               15.8\n",
+       "    declination_in_orientmat:  1\n",
+       "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-94cd68dd-7aac-478a-80b1-3a6f39b8452a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-94cd68dd-7aac-478a-80b1-3a6f39b8452a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3bbb6d59-0298-4fdb-a533-98ba028cbc81' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3bbb6d59-0298-4fdb-a533-98ba028cbc81' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-83f5cfe5-8633-46aa-ae9d-9ed27402e9a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83f5cfe5-8633-46aa-ae9d-9ed27402e9a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4595c08c-025a-4bd3-9186-a759a86a2e83' class='xr-var-data-in' type='checkbox'><label for='data-4595c08c-025a-4bd3-9186-a759a86a2e83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
+       "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
+       "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
+       "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
+       "       &#x27;2020-08-15T01:02:30.001023769&#x27;, &#x27;2020-08-15T01:07:30.001024723&#x27;,\n",
+       "       &#x27;2020-08-15T01:12:30.001034259&#x27;, &#x27;2020-08-15T01:17:30.001035451&#x27;,\n",
+       "       &#x27;2020-08-15T01:22:30.001024961&#x27;, &#x27;2020-08-15T01:27:30.001025438&#x27;,\n",
+       "       &#x27;2020-08-15T01:32:30.001025676&#x27;, &#x27;2020-08-15T01:37:30.001031875&#x27;,\n",
+       "       &#x27;2020-08-15T01:42:30.001029014&#x27;, &#x27;2020-08-15T01:47:30.001030683&#x27;,\n",
+       "       &#x27;2020-08-15T01:52:30.001033067&#x27;, &#x27;2020-08-15T01:57:30.001029014&#x27;,\n",
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+       "       &#x27;2020-08-15T06:12:30.001021862&#x27;, &#x27;2020-08-15T06:17:30.001018524&#x27;,\n",
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+       "       &#x27;2020-08-15T08:12:30.001027107&#x27;, &#x27;2020-08-15T08:17:30.001024723&#x27;,\n",
+       "       &#x27;2020-08-15T08:22:30.001022577&#x27;, &#x27;2020-08-15T08:27:30.001018047&#x27;,\n",
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+       "       &#x27;2020-08-15T08:52:30.001020431&#x27;, &#x27;2020-08-15T08:57:30.001026630&#x27;,\n",
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+       "       &#x27;2020-08-15T09:12:30.001025676&#x27;, &#x27;2020-08-15T09:17:30.001024246&#x27;,\n",
+       "       &#x27;2020-08-15T09:22:30.001026630&#x27;, &#x27;2020-08-15T09:27:30.001017570&#x27;,\n",
+       "       &#x27;2020-08-15T09:32:30.001015901&#x27;, &#x27;2020-08-15T09:37:30.001016139&#x27;,\n",
+       "       &#x27;2020-08-15T09:42:30.001018762&#x27;, &#x27;2020-08-15T09:47:30.001014709&#x27;,\n",
+       "       &#x27;2020-08-15T09:52:30.001016378&#x27;, &#x27;2020-08-15T09:57:30.001024961&#x27;,\n",
+       "       &#x27;2020-08-15T10:02:30.001021146&#x27;, &#x27;2020-08-15T10:07:30.001022100&#x27;,\n",
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+       "       &#x27;2020-08-15T10:22:30.001018762&#x27;, &#x27;2020-08-15T10:27:30.001021385&#x27;,\n",
+       "       &#x27;2020-08-15T10:32:30.001016855&#x27;, &#x27;2020-08-15T10:37:30.001021385&#x27;,\n",
+       "       &#x27;2020-08-15T10:42:30.001015186&#x27;, &#x27;2020-08-15T10:47:30.001020193&#x27;,\n",
+       "       &#x27;2020-08-15T10:52:30.001021623&#x27;, &#x27;2020-08-15T10:57:30.001021862&#x27;,\n",
+       "       &#x27;2020-08-15T11:02:30.001018047&#x27;, &#x27;2020-08-15T11:07:30.001021146&#x27;,\n",
+       "       &#x27;2020-08-15T11:12:30.001011848&#x27;, &#x27;2020-08-15T11:17:30.001015901&#x27;,\n",
+       "       &#x27;2020-08-15T11:22:30.001014232&#x27;, &#x27;2020-08-15T11:27:30.001015663&#x27;,\n",
+       "       &#x27;2020-08-15T11:32:30.001012325&#x27;, &#x27;2020-08-15T11:37:30.001004457&#x27;,\n",
+       "       &#x27;2020-08-15T11:42:30.001018524&#x27;, &#x27;2020-08-15T11:47:30.001023292&#x27;,\n",
+       "       &#x27;2020-08-15T11:52:30.001009464&#x27;, &#x27;2020-08-15T11:57:30.001002311&#x27;,\n",
+       "       &#x27;2020-08-15T12:02:30.001004695&#x27;, &#x27;2020-08-15T12:07:30.001007556&#x27;,\n",
+       "       &#x27;2020-08-15T12:12:30.001012086&#x27;, &#x27;2020-08-15T12:17:30.001007080&#x27;,\n",
+       "       &#x27;2020-08-15T12:22:30.001011371&#x27;, &#x27;2020-08-15T12:27:30.001014471&#x27;,\n",
+       "       &#x27;2020-08-15T12:32:30.001016378&#x27;, &#x27;2020-08-15T12:37:30.001012563&#x27;,\n",
+       "       &#x27;2020-08-15T12:42:30.001015901&#x27;, &#x27;2020-08-15T12:47:30.001010417&#x27;,\n",
+       "       &#x27;2020-08-15T12:52:30.001009464&#x27;, &#x27;2020-08-15T12:57:30.001010894&#x27;,\n",
+       "       &#x27;2020-08-15T13:02:30.001016855&#x27;, &#x27;2020-08-15T13:07:30.001020908&#x27;,\n",
+       "       &#x27;2020-08-15T13:12:30.001018762&#x27;, &#x27;2020-08-15T13:17:30.001018762&#x27;,\n",
+       "       &#x27;2020-08-15T13:22:30.001018047&#x27;, &#x27;2020-08-15T13:27:30.001013517&#x27;,\n",
+       "       &#x27;2020-08-15T13:32:30.001015424&#x27;, &#x27;2020-08-15T13:37:30.001009225&#x27;,\n",
+       "       &#x27;2020-08-15T13:42:30.001011133&#x27;, &#x27;2020-08-15T13:47:30.001008749&#x27;,\n",
+       "       &#x27;2020-08-15T13:52:30.001019477&#x27;, &#x27;2020-08-15T13:57:30.001022338&#x27;,\n",
+       "       &#x27;2020-08-15T14:02:30.001019716&#x27;, &#x27;2020-08-15T14:07:30.001026868&#x27;,\n",
+       "       &#x27;2020-08-15T14:12:30.001021623&#x27;, &#x27;2020-08-15T14:17:30.001034021&#x27;,\n",
+       "       &#x27;2020-08-15T14:22:30.001024961&#x27;, &#x27;2020-08-15T14:27:30.001032352&#x27;,\n",
+       "       &#x27;2020-08-15T14:32:30.001023292&#x27;, &#x27;2020-08-15T14:37:30.001024484&#x27;,\n",
+       "       &#x27;2020-08-15T14:42:30.001044034&#x27;, &#x27;2020-08-15T14:47:30.001032352&#x27;,\n",
+       "       &#x27;2020-08-15T14:52:30.001019239&#x27;, &#x27;2020-08-15T14:57:30.001032829&#x27;,\n",
+       "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
+       "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
+       "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
+       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-ee9453dd-0e1f-4609-800f-b7785def0997' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee9453dd-0e1f-4609-800f-b7785def0997' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e987dc0-2769-47d7-9980-0cffd6452fb4' class='xr-var-data-in' type='checkbox'><label for='data-7e987dc0-2769-47d7-9980-0cffd6452fb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-823e073a-d75c-463c-a4df-34580897ee81' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-823e073a-d75c-463c-a4df-34580897ee81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aab03f98-74f0-4e0d-adac-6d2c5c9837ed' class='xr-var-data-in' type='checkbox'><label for='data-aab03f98-74f0-4e0d-adac-6d2c5c9837ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-9e796c46-5807-46ff-bcee-dd007ae9a509' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e796c46-5807-46ff-bcee-dd007ae9a509' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88900068-2151-4243-8ce7-50c91e53ffcf' class='xr-var-data-in' type='checkbox'><label for='data-88900068-2151-4243-8ce7-50c91e53ffcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-129a6633-70c5-4877-971e-cbae6aef4cd1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-129a6633-70c5-4877-971e-cbae6aef4cd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-274de313-22c3-46a9-89be-05e30df2f539' class='xr-var-data-in' type='checkbox'><label for='data-274de313-22c3-46a9-89be-05e30df2f539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-07471bd2-3fff-4550-ab2c-3f3f935b6b8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07471bd2-3fff-4550-ab2c-3f3f935b6b8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ea841b9-c6fd-4485-ade0-d809c64b4430' class='xr-var-data-in' type='checkbox'><label for='data-6ea841b9-c6fd-4485-ade0-d809c64b4430' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-41aafcf3-92b7-41ed-91fe-e8fd7e853019' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41aafcf3-92b7-41ed-91fe-e8fd7e853019' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c331539-ea72-4303-9589-b1a9a3d1b226' class='xr-var-data-in' type='checkbox'><label for='data-8c331539-ea72-4303-9589-b1a9a3d1b226' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-96ef30a6-3706-45d0-b9ff-4bcc47822f51' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96ef30a6-3706-45d0-b9ff-4bcc47822f51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00da1e9-f04e-4fc0-b8c7-58f069ddffbb' class='xr-var-data-in' type='checkbox'><label for='data-f00da1e9-f04e-4fc0-b8c7-58f069ddffbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-ae39105f-724b-4ffb-ad5e-72022d2c834a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae39105f-724b-4ffb-ad5e-72022d2c834a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67133c30-1d3c-442b-b10a-a21e9ef43c2f' class='xr-var-data-in' type='checkbox'><label for='data-67133c30-1d3c-442b-b10a-a21e9ef43c2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
+       "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
+       "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
+       "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T01:02:29.938493013&#x27;, &#x27;2020-08-15T01:07:29.938492536&#x27;,\n",
+       "       &#x27;2020-08-15T01:12:29.938490867&#x27;, &#x27;2020-08-15T01:17:29.938497781&#x27;,\n",
+       "       &#x27;2020-08-15T01:22:29.938496112&#x27;, &#x27;2020-08-15T01:27:29.938498497&#x27;,\n",
+       "       &#x27;2020-08-15T01:32:29.938496589&#x27;, &#x27;2020-08-15T01:37:29.938497781&#x27;,\n",
+       "       &#x27;2020-08-15T01:42:29.938495635&#x27;, &#x27;2020-08-15T01:47:29.938497066&#x27;,\n",
+       "       &#x27;2020-08-15T01:52:29.938498735&#x27;, &#x27;2020-08-15T01:57:29.938496112&#x27;,\n",
+       "       &#x27;2020-08-15T02:02:29.938496589&#x27;, &#x27;2020-08-15T02:07:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T02:12:29.938497304&#x27;, &#x27;2020-08-15T02:17:29.938496828&#x27;,\n",
+       "       &#x27;2020-08-15T02:22:29.938496112&#x27;, &#x27;2020-08-15T02:27:29.938496828&#x27;,\n",
+       "       &#x27;2020-08-15T02:32:29.938496112&#x27;, &#x27;2020-08-15T02:37:29.938497304&#x27;,\n",
+       "       &#x27;2020-08-15T02:42:29.938495159&#x27;, &#x27;2020-08-15T02:47:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T02:52:29.938490867&#x27;, &#x27;2020-08-15T02:57:29.938492059&#x27;,\n",
+       "       &#x27;2020-08-15T03:02:29.938489675&#x27;, &#x27;2020-08-15T03:07:29.938488245&#x27;,\n",
+       "       &#x27;2020-08-15T03:12:29.938485622&#x27;, &#x27;2020-08-15T03:17:29.938485622&#x27;,\n",
+       "       &#x27;2020-08-15T03:22:29.938488245&#x27;, &#x27;2020-08-15T03:27:29.938485145&#x27;,\n",
+       "       &#x27;2020-08-15T03:32:29.938486099&#x27;, &#x27;2020-08-15T03:37:29.938482046&#x27;,\n",
+       "       &#x27;2020-08-15T03:42:29.938489437&#x27;, &#x27;2020-08-15T03:47:29.938489437&#x27;,\n",
+       "       &#x27;2020-08-15T03:52:29.938485860&#x27;, &#x27;2020-08-15T03:57:29.938491582&#x27;,\n",
+       "       &#x27;2020-08-15T04:02:29.938488006&#x27;, &#x27;2020-08-15T04:07:29.938491106&#x27;,\n",
+       "       &#x27;2020-08-15T04:12:29.938492059&#x27;, &#x27;2020-08-15T04:17:29.938487052&#x27;,\n",
+       "       &#x27;2020-08-15T04:22:29.938489675&#x27;, &#x27;2020-08-15T04:27:29.938491582&#x27;,\n",
+       "       &#x27;2020-08-15T04:32:29.938491106&#x27;, &#x27;2020-08-15T04:37:29.938493251&#x27;,\n",
+       "       &#x27;2020-08-15T04:42:29.938489675&#x27;, &#x27;2020-08-15T04:47:29.938492059&#x27;,\n",
+       "       &#x27;2020-08-15T04:52:29.938491582&#x27;, &#x27;2020-08-15T04:57:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T05:02:29.938491106&#x27;, &#x27;2020-08-15T05:07:29.938499212&#x27;,\n",
+       "       &#x27;2020-08-15T05:12:29.938491821&#x27;, &#x27;2020-08-15T05:17:29.938493490&#x27;,\n",
+       "       &#x27;2020-08-15T05:22:29.938495397&#x27;, &#x27;2020-08-15T05:27:29.938490390&#x27;,\n",
+       "       &#x27;2020-08-15T05:32:29.938493967&#x27;, &#x27;2020-08-15T05:37:29.938493728&#x27;,\n",
+       "       &#x27;2020-08-15T05:42:29.938491582&#x27;, &#x27;2020-08-15T05:47:29.938493013&#x27;,\n",
+       "       &#x27;2020-08-15T05:52:29.938495159&#x27;, &#x27;2020-08-15T05:57:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T06:02:29.938493013&#x27;, &#x27;2020-08-15T06:07:29.938496589&#x27;,\n",
+       "       &#x27;2020-08-15T06:12:29.938494920&#x27;, &#x27;2020-08-15T06:17:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T06:22:29.938493728&#x27;, &#x27;2020-08-15T06:27:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T06:32:29.938492536&#x27;, &#x27;2020-08-15T06:37:29.938495159&#x27;,\n",
+       "       &#x27;2020-08-15T06:42:29.938496112&#x27;, &#x27;2020-08-15T06:47:29.938497304&#x27;,\n",
+       "       &#x27;2020-08-15T06:52:29.938496112&#x27;, &#x27;2020-08-15T06:57:29.938493728&#x27;,\n",
+       "       &#x27;2020-08-15T07:02:29.938497304&#x27;, &#x27;2020-08-15T07:07:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T07:12:29.938492059&#x27;, &#x27;2020-08-15T07:17:29.938493490&#x27;,\n",
+       "       &#x27;2020-08-15T07:22:29.938493967&#x27;, &#x27;2020-08-15T07:27:29.938497304&#x27;,\n",
+       "       &#x27;2020-08-15T07:32:29.938494443&#x27;, &#x27;2020-08-15T07:37:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T07:42:29.938495635&#x27;, &#x27;2020-08-15T07:47:29.938493967&#x27;,\n",
+       "       &#x27;2020-08-15T07:52:29.938492298&#x27;, &#x27;2020-08-15T07:57:29.938489675&#x27;,\n",
+       "       &#x27;2020-08-15T08:02:29.938493013&#x27;, &#x27;2020-08-15T08:07:29.938493728&#x27;,\n",
+       "       &#x27;2020-08-15T08:12:29.938497066&#x27;, &#x27;2020-08-15T08:17:29.938497781&#x27;,\n",
+       "       &#x27;2020-08-15T08:22:29.938495159&#x27;, &#x27;2020-08-15T08:27:29.938492774&#x27;,\n",
+       "       &#x27;2020-08-15T08:32:29.938495397&#x27;, &#x27;2020-08-15T08:37:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T08:42:29.938494920&#x27;, &#x27;2020-08-15T08:47:29.938494682&#x27;,\n",
+       "       &#x27;2020-08-15T08:52:29.938494443&#x27;, &#x27;2020-08-15T08:57:29.938491821&#x27;,\n",
+       "       &#x27;2020-08-15T09:02:29.938497066&#x27;, &#x27;2020-08-15T09:07:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T09:12:29.938495397&#x27;, &#x27;2020-08-15T09:17:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T09:22:29.938498020&#x27;, &#x27;2020-08-15T09:27:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T09:32:29.938495159&#x27;, &#x27;2020-08-15T09:37:29.938498735&#x27;,\n",
+       "       &#x27;2020-08-15T09:42:29.938493728&#x27;, &#x27;2020-08-15T09:47:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T09:52:29.938500642&#x27;, &#x27;2020-08-15T09:57:29.938496589&#x27;,\n",
+       "       &#x27;2020-08-15T10:02:29.938497781&#x27;, &#x27;2020-08-15T10:07:29.938500881&#x27;,\n",
+       "       &#x27;2020-08-15T10:12:29.938504457&#x27;, &#x27;2020-08-15T10:17:29.938501358&#x27;,\n",
+       "       &#x27;2020-08-15T10:22:29.938507556&#x27;, &#x27;2020-08-15T10:27:29.938496112&#x27;,\n",
+       "       &#x27;2020-08-15T10:32:29.938495635&#x27;, &#x27;2020-08-15T10:37:29.938500165&#x27;,\n",
+       "       &#x27;2020-08-15T10:42:29.938496112&#x27;, &#x27;2020-08-15T10:47:29.938493251&#x27;,\n",
+       "       &#x27;2020-08-15T10:52:29.938493728&#x27;, &#x27;2020-08-15T10:57:29.938492536&#x27;,\n",
+       "       &#x27;2020-08-15T11:02:29.938492774&#x27;, &#x27;2020-08-15T11:07:29.938492774&#x27;,\n",
+       "       &#x27;2020-08-15T11:12:29.938493967&#x27;, &#x27;2020-08-15T11:17:29.938494443&#x27;,\n",
+       "       &#x27;2020-08-15T11:22:29.938496589&#x27;, &#x27;2020-08-15T11:27:29.938496112&#x27;,\n",
+       "       &#x27;2020-08-15T11:32:29.938495397&#x27;, &#x27;2020-08-15T11:37:29.938493967&#x27;,\n",
+       "       &#x27;2020-08-15T11:42:29.938493013&#x27;, &#x27;2020-08-15T11:47:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T11:52:29.938493967&#x27;, &#x27;2020-08-15T11:57:29.938498735&#x27;,\n",
+       "       &#x27;2020-08-15T12:02:29.938496589&#x27;, &#x27;2020-08-15T12:07:29.938498020&#x27;,\n",
+       "       &#x27;2020-08-15T12:12:29.938494443&#x27;, &#x27;2020-08-15T12:17:29.938495159&#x27;,\n",
+       "       &#x27;2020-08-15T12:22:29.938495635&#x27;, &#x27;2020-08-15T12:27:29.938497066&#x27;,\n",
+       "       &#x27;2020-08-15T12:32:29.938493967&#x27;, &#x27;2020-08-15T12:37:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T12:42:29.938496112&#x27;, &#x27;2020-08-15T12:47:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T12:52:29.938494443&#x27;, &#x27;2020-08-15T12:57:29.938496589&#x27;,\n",
+       "       &#x27;2020-08-15T13:02:29.938494205&#x27;, &#x27;2020-08-15T13:07:29.938494205&#x27;,\n",
+       "       &#x27;2020-08-15T13:12:29.938492536&#x27;, &#x27;2020-08-15T13:17:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T13:22:29.938493251&#x27;, &#x27;2020-08-15T13:27:29.938495397&#x27;,\n",
+       "       &#x27;2020-08-15T13:32:29.938494920&#x27;, &#x27;2020-08-15T13:37:29.938497066&#x27;,\n",
+       "       &#x27;2020-08-15T13:42:29.938497304&#x27;, &#x27;2020-08-15T13:47:29.938494920&#x27;,\n",
+       "       &#x27;2020-08-15T13:52:29.938493490&#x27;, &#x27;2020-08-15T13:57:29.938492774&#x27;,\n",
+       "       &#x27;2020-08-15T14:02:29.938496112&#x27;, &#x27;2020-08-15T14:07:29.938489675&#x27;,\n",
+       "       &#x27;2020-08-15T14:12:29.938489913&#x27;, &#x27;2020-08-15T14:17:29.938494443&#x27;,\n",
+       "       &#x27;2020-08-15T14:22:29.938495397&#x27;, &#x27;2020-08-15T14:27:29.938492774&#x27;,\n",
+       "       &#x27;2020-08-15T14:32:29.938491582&#x27;, &#x27;2020-08-15T14:37:29.938493251&#x27;,\n",
+       "       &#x27;2020-08-15T14:42:29.938492536&#x27;, &#x27;2020-08-15T14:47:29.938492774&#x27;,\n",
+       "       &#x27;2020-08-15T14:52:29.938491106&#x27;, &#x27;2020-08-15T14:57:29.938495635&#x27;,\n",
+       "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
+       "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
+       "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
+       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-f53e9720-6d63-4f51-8a7a-f8bf4ed3af70' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f53e9720-6d63-4f51-8a7a-f8bf4ed3af70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7e9300c-f075-4671-b07c-6ee5e31d03ca' class='xr-var-data-in' type='checkbox'><label for='data-b7e9300c-f075-4671-b07c-6ee5e31d03ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b67361b7-a489-4710-b7cb-1eaa91d2b631' class='xr-section-summary-in' type='checkbox'  ><label for='section-b67361b7-a489-4710-b7cb-1eaa91d2b631' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-63952b1d-c12b-4529-9de6-757bb7fc4022' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63952b1d-c12b-4529-9de6-757bb7fc4022' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b9837e3-8b6d-4623-b540-df60aaa29fd6' class='xr-var-data-in' type='checkbox'><label for='data-6b9837e3-8b6d-4623-b540-df60aaa29fd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
+       "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
+       "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
+       "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
+       "       1500.6763, 1500.2716, 1500.1096, 1499.8009, 1499.5637, 1499.3373,\n",
+       "       1499.2163, 1499.0955, 1498.9806, 1498.8579, 1498.7637, 1498.6821,\n",
+       "       1498.6133, 1498.5066, 1498.5637, 1498.7421, 1498.8367, 1498.984 ,\n",
+       "       1498.9717, 1498.9644, 1499.0553, 1499.21  , 1499.2789, 1499.2766,\n",
+       "       1499.265 , 1499.2623, 1499.3181, 1499.2903, 1499.3444, 1499.2922,\n",
+       "       1499.2983, 1499.195 , 1499.2087, 1499.212 , 1499.2494, 1499.2227,\n",
+       "       1499.1742, 1499.1772, 1499.1937, 1499.2306, 1499.2719, 1499.3043,\n",
+       "       1499.4073, 1499.3677, 1499.4554, 1499.5647, 1499.6683, 1499.7489,\n",
+       "       1499.8341, 1499.8446, 1499.8396, 1499.9257, 1499.781 , 1499.8274,\n",
+       "       1499.7506, 1499.8904, 1499.7473, 1499.7411, 1499.7415, 1499.7079,\n",
+       "       1499.508 , 1499.7562, 1499.5327, 1499.4186, 1499.4877, 1499.1946,\n",
+       "       1499.1821, 1499.466 , 1499.5144, 1499.7024, 1499.8877, 1499.8373,\n",
+       "       1499.8597, 1500.1703, 1500.0886, 1500.082 , 1500.0476, 1499.9003,\n",
+       "       1499.8434, 1498.8927, 1497.6433, 1496.299 , 1495.386 , 1495.2273,\n",
+       "       1494.9376, 1494.7117, 1494.9341, 1495.1063, 1495.0103, 1494.7747,\n",
+       "       1494.5977, 1494.4548, 1494.4042, 1494.3356, 1494.229 , 1494.0669,\n",
+       "       1493.7662, 1493.4755, 1493.3303, 1493.1544, 1492.8477, 1492.7877,\n",
+       "       1492.8064, 1493.0189, 1493.5558, 1494.0146, 1494.7506, 1495.2681,\n",
+       "       1496.2244, 1496.8036, 1497.5472, 1498.0507, 1498.3839, 1498.663 ,\n",
+       "       1498.8971, 1499.136 , 1499.3384, 1499.535 , 1499.5739, 1499.5245,\n",
+       "       1499.4437, 1499.4467, 1499.5509, 1499.6014, 1499.5997, 1499.5935,\n",
+       "       1499.525 , 1499.4967, 1499.4364, 1499.4977, 1499.503 , 1499.5526,\n",
+       "       1499.5083, 1499.5023, 1499.474 , 1499.4028, 1499.436 , 1499.4973,\n",
+       "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
+       "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
+       "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
+       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-95a9e011-df19-4e04-a3e8-3b06c28ec021' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95a9e011-df19-4e04-a3e8-3b06c28ec021' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6c6987d-f6a0-48a7-96cc-2f19ae146351' class='xr-var-data-in' type='checkbox'><label for='data-e6c6987d-f6a0-48a7-96cc-2f19ae146351' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
+       "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
+       "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
+       "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
+       "       14.572268 , 14.502767 , 14.376032 , 14.268402 , 14.178566 ,\n",
+       "       14.055    , 14.005532 , 13.911533 , 13.838566 , 13.7688675,\n",
+       "       13.7339325, 13.696598 , 13.661633 , 13.626367 , 13.597433 ,\n",
+       "       13.572568 , 13.552067 , 13.520534 , 13.538133 , 13.592899 ,\n",
+       "       13.620734 , 13.665668 , 13.661699 , 13.658334 , 13.686766 ,\n",
+       "       13.7354   , 13.754033 , 13.754901 , 13.7525   , 13.751934 ,\n",
+       "       13.767399 , 13.760633 , 13.776802 , 13.761433 , 13.7625   ,\n",
+       "       13.731066 , 13.7371   , 13.737367 , 13.748701 , 13.741634 ,\n",
+       "       13.726335 , 13.726666 , 13.7323   , 13.743701 , 13.756766 ,\n",
+       "       13.766968 , 13.797334 , 13.7852   , 13.812601 , 13.847366 ,\n",
+       "       13.878734 , 13.903067 , 13.928333 , 13.931099 , 13.930567 ,\n",
+       "       13.957533 , 13.912533 , 13.9264   , 13.9032   , 13.947433 ,\n",
+       "       13.902601 , 13.900833 , 13.900665 , 13.890833 , 13.830032 ,\n",
+       "       13.9046335, 13.8364   , 13.801933 , 13.8241   , 13.735    ,\n",
+       "       13.732666 , 13.818233 , 13.8298   , 13.888301 , 13.944167 ,\n",
+       "       13.928867 , 13.9361   , 14.0331   , 14.008999 , 14.006901 ,\n",
+       "       13.992832 , 13.946533 , 13.9282   , 13.643267 , 13.266466 ,\n",
+       "       12.865967 , 12.595367 , 12.5469   , 12.462267 , 12.3959   ,\n",
+       "       12.461133 , 12.512366 , 12.482166 , 12.411167 , 12.3605995,\n",
+       "       12.3201   , 12.303568 , 12.284267 , 12.252732 , 12.203699 ,\n",
+       "       12.118533 , 12.031001 , 11.988433 , 11.939434 , 11.8505   ,\n",
+       "       11.8341   , 11.837234 , 11.8984995, 12.0561   , 12.189    ,\n",
+       "       12.403767 , 12.5546   , 12.837867 , 13.010934 , 13.233933 ,\n",
+       "       13.384068 , 13.485199 , 13.565999 , 13.639567 , 13.711732 ,\n",
+       "       13.774034 , 13.829665 , 13.838365 , 13.829668 , 13.8013   ,\n",
+       "       13.805167 , 13.833833 , 13.855499 , 13.857698 , 13.844232 ,\n",
+       "       13.831333 , 13.816167 , 13.802168 , 13.811266 , 13.820599 ,\n",
+       "       13.834399 , 13.828466 , 13.826566 , 13.810034 , 13.792601 ,\n",
+       "       13.800402 , 13.820232 , 13.830032 , 13.8446665, 13.8607   ,\n",
+       "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
+       "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
+       "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
+       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-3afeb9ef-5d73-4f4c-b904-34b07796c1de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3afeb9ef-5d73-4f4c-b904-34b07796c1de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30163c0a-6f68-479b-b273-e60ae4eaa390' class='xr-var-data-in' type='checkbox'><label for='data-30163c0a-6f68-479b-b273-e60ae4eaa390' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
+       "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
+       "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
+       "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
+       "       9.218047 , 9.186557 , 9.157551 , 9.123754 , 9.09348  , 9.059697 ,\n",
+       "       9.026804 , 8.994499 , 8.95571  , 8.92198  , 8.886473 , 8.853367 ,\n",
+       "       8.813594 , 8.782229 , 8.74448  , 8.708926 , 8.674907 , 8.637604 ,\n",
+       "       8.602573 , 8.560874 , 8.524677 , 8.48187  , 8.4449835, 8.400766 ,\n",
+       "       8.365373 , 8.322662 , 8.28713  , 8.248011 , 8.21333  , 8.178404 ,\n",
+       "       8.14623  , 8.109827 , 8.072543 , 8.039574 , 7.9980125, 7.963136 ,\n",
+       "       7.926347 , 7.8918767, 7.8531103, 7.824253 , 7.7964296, 7.7649107,\n",
+       "       7.7383432, 7.7130632, 7.6841335, 7.65858  , 7.633538 , 7.609003 ,\n",
+       "       7.592057 , 7.573613 , 7.5537395, 7.533187 , 7.5146875, 7.497063 ,\n",
+       "       7.48256  , 7.472039 , 7.454433 , 7.4437304, 7.4306965, 7.422947 ,\n",
+       "       7.4138427, 7.4127507, 7.407543 , 7.4021435, 7.40189  , 7.4006333,\n",
+       "       7.401152 , 7.3961263, 7.4010367, 7.4031525, 7.414211 , 7.4199567,\n",
+       "       7.4243903, 7.4346695, 7.4523306, 7.4677606, 7.47785  , 7.4955306,\n",
+       "       7.507134 , 7.52034  , 7.540297 , 7.5592594, 7.583973 , 7.6029363,\n",
+       "       7.623276 , 7.6508303, 7.67267  , 7.6968994, 7.7202635, 7.7465167,\n",
+       "       7.7706933, 7.795326 , 7.820833 , 7.8509097, 7.8781033, 7.9117236,\n",
+       "       7.9442267, 7.9752865, 8.007596 , 8.042522 , 8.077546 , 8.108029 ,\n",
+       "       8.1417265, 8.17497  , 8.210143 , 8.243827 , 8.281553 , 8.317181 ,\n",
+       "       8.35565  , 8.390187 , 8.42794  , 8.465797 , 8.50642  , 8.54146  ,\n",
+       "       8.581511 , 8.618688 , 8.65223  , 8.69048  , 8.72701  , 8.758973 ,\n",
+       "       8.795943 , 8.832204 , 8.870703 , 8.8993225, 8.936847 , 8.969017 ,\n",
+       "       9.001257 , 9.036253 , 9.063161 , 9.095617 , 9.1287565, 9.157017 ,\n",
+       "       9.187741 , 9.216694 , 9.244237 , 9.274386 , 9.300383 , 9.32181  ,\n",
+       "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
+       "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
+       "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
+       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-2fb56565-ef29-4887-835e-41ad0b301dd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fb56565-ef29-4887-835e-41ad0b301dd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9195dd1f-c8d4-46c5-b7db-5eb6171eac67' class='xr-var-data-in' type='checkbox'><label for='data-9195dd1f-c8d4-46c5-b7db-5eb6171eac67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
+       "         3.60746217e+00,  3.56795740e+00,  3.58543777e+00,\n",
+       "         3.56357908e+00,  3.57667398e+00,  3.60632110e+00,\n",
+       "         3.56949067e+00,  3.57479167e+00,  3.59876704e+00,\n",
+       "         3.60281253e+00,  3.59981132e+00,  3.59064198e+00,\n",
+       "         3.59985065e+00,  3.58579111e+00,  3.57373047e+00,\n",
+       "         3.56544852e+00,  3.58114982e+00,  3.58714032e+00,\n",
+       "         3.55944085e+00,  3.58880138e+00,  3.53171992e+00,\n",
+       "         3.53358531e+00,  3.49057865e+00,  3.49481201e+00,\n",
+       "         3.49612260e+00,  3.45677161e+00,  3.42318940e+00,\n",
+       "         3.46062589e+00,  3.41326380e+00,  3.41770315e+00,\n",
+       "         3.41921234e+00,  3.43796873e+00,  3.42292237e+00,\n",
+       "         3.41392589e+00,  3.38415337e+00,  3.38218069e+00,\n",
+       "         3.43648434e+00,  3.38592434e+00,  3.34218621e+00,\n",
+       "         3.38532996e+00,  3.37350154e+00,  3.37754154e+00,\n",
+       "         3.35902476e+00,  3.34339881e+00,  3.35676146e+00,\n",
+       "         3.35692763e+00,  3.32560086e+00,  3.27195191e+00,\n",
+       "         3.19083190e+00,  2.95882225e+00,  2.40057945e+00,\n",
+       "         2.16090226e+00,  1.92318320e+00,  1.78795314e+00,\n",
+       "         1.62216699e+00,  1.56376326e+00,  1.46418226e+00,\n",
+       "...\n",
+       "        -1.96982498e+02, -1.97061203e+02, -1.96969849e+02,\n",
+       "        -1.97076538e+02, -1.97007187e+02, -1.97028168e+02,\n",
+       "        -1.97006195e+02, -1.97027512e+02, -1.97029175e+02,\n",
+       "        -1.96980515e+02, -1.97019150e+02, -1.96939850e+02,\n",
+       "        -1.96979843e+02, -1.97032181e+02, -1.97038193e+02,\n",
+       "        -1.96942871e+02, -1.96959534e+02, -1.96986191e+02,\n",
+       "        -1.97056839e+02, -1.97049850e+02, -1.97026855e+02,\n",
+       "        -1.97041199e+02, -1.97016525e+02, -1.97084503e+02,\n",
+       "        -1.97077499e+02, -1.97032166e+02, -1.97061508e+02,\n",
+       "        -1.97079834e+02, -1.97101852e+02, -1.97092865e+02,\n",
+       "        -1.97062164e+02, -1.97118851e+02, -1.97044510e+02,\n",
+       "        -1.97032166e+02, -1.97112183e+02, -1.96995499e+02,\n",
+       "        -1.97103195e+02, -1.97131195e+02, -1.97147202e+02,\n",
+       "        -1.97079849e+02, -1.97053513e+02, -1.97125504e+02,\n",
+       "        -1.97132843e+02, -1.97114838e+02, -1.97074829e+02,\n",
+       "        -1.97085831e+02, -1.97115845e+02, -1.97091156e+02,\n",
+       "        -1.97044174e+02, -1.97063873e+02, -1.97090515e+02,\n",
+       "        -1.97129501e+02, -1.97007523e+02, -1.97017838e+02,\n",
+       "        -1.97019165e+02, -1.97129166e+02, -1.97051849e+02,\n",
+       "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-a899fa25-7d18-4765-afe3-04bc22fe5d71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a899fa25-7d18-4765-afe3-04bc22fe5d71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b02d62d4-7b2a-4b71-b7be-ca78eb28e340' class='xr-var-data-in' type='checkbox'><label for='data-b02d62d4-7b2a-4b71-b7be-ca78eb28e340' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
+       "        -1.2613868 , -1.2610568 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
+       "        -1.2618904 , -1.258823  , -1.2596216 , -1.258702  , -1.2583325 ,\n",
+       "        -1.2578007 , -1.2583394 , -1.2576339 , -1.2579147 , -1.2534361 ,\n",
+       "        -1.2568558 , -1.2559422 , -1.2557042 , -1.2571892 , -1.2556211 ,\n",
+       "        -1.2540294 , -1.2548382 , -1.2532483 , -1.2525105 , -1.2511989 ,\n",
+       "        -1.2522614 , -1.2561746 , -1.2530836 , -1.2531874 , -1.2519903 ,\n",
+       "        -1.2518218 , -1.2511966 , -1.2544034 , -1.2561861 , -1.2536184 ,\n",
+       "        -1.2504781 , -1.2535783 , -1.2560768 , -1.2559297 , -1.257113  ,\n",
+       "        -1.2519604 , -1.2501055 , -1.2515699 , -1.2483989 , -1.2508361 ,\n",
+       "        -1.2479837 , -1.2430646 , -1.2314413 , -1.2083213 , -1.1935245 ,\n",
+       "        -1.1852744 , -1.1747023 , -1.1735051 , -1.1686733 , -1.1616861 ,\n",
+       "        -1.1579937 , -1.1570411 , -1.1541711 , -1.1540251 , -1.1536013 ,\n",
+       "        -1.1516274 , -1.147889  , -1.1449583 , -1.1449729 , -1.14322   ,\n",
+       "        -1.1418625 , -1.1392603 , -1.1384715 , -1.136121  , -1.1344364 ,\n",
+       "        -1.132704  , -1.1329331 , -1.1329101 , -1.130972  , -1.1331373 ,\n",
+       "        -1.1304799 , -1.1283726 , -1.1294136 , -1.132449  , -1.1283008 ,\n",
+       "        -1.1297874 , -1.1291262 , -1.1277461 , -1.1284393 , -1.1265595 ,\n",
+       "        -1.1229205 , -1.1222471 , -1.1207403 , -1.1196108 , -1.1196036 ,\n",
+       "        -1.1186633 , -1.1185873 , -1.1168755 , -1.1150851 , -1.1146263 ,\n",
+       "...\n",
+       "         9.716357  ,  9.717475  ,  9.7163725 ,  9.718897  ,  9.715463  ,\n",
+       "         9.711327  ,  9.713148  ,  9.713642  ,  9.712924  ,  9.715384  ,\n",
+       "         9.715974  ,  9.716772  ,  9.718337  ,  9.714473  ,  9.717203  ,\n",
+       "         9.714393  ,  9.71425   ,  9.713914  ,  9.711695  ,  9.708918  ,\n",
+       "         9.711455  ,  9.70863   ,  9.711487  ,  9.71433   ,  9.710337  ,\n",
+       "         9.711295  ,  9.7138815 ,  9.70997   ,  9.713227  ,  9.717092  ,\n",
+       "         9.713419  ,  9.719773  ,  9.71832   ,  9.716453  ,  9.717108  ,\n",
+       "         9.715989  ,  9.7141695 ,  9.711615  ,  9.71741   ,  9.715814  ,\n",
+       "         9.71428   ,  9.717347  ,  9.712972  ,  9.7162285 ,  9.713419  ,\n",
+       "         9.712238  ,  9.714361  ,  9.716245  ,  9.713563  ,  9.718161  ,\n",
+       "         9.713195  ,  9.715207  ,  9.71591   ,  9.713914  ,  9.7165    ,\n",
+       "         9.7136755 ,  9.717347  ,  9.719837  ,  9.718688  ,  9.713898  ,\n",
+       "         9.717618  ,  9.715941  ,  9.710864  ,  9.71433   ,  9.717777  ,\n",
+       "         9.716262  ,  9.716644  ,  9.719199  ,  9.718911  ,  9.715112  ,\n",
+       "         9.714042  ,  9.710752  ,  9.714153  ,  9.716006  ,  9.715191  ,\n",
+       "         9.716421  ,  9.718177  ,  9.717875  ,  9.718033  ,  9.713227  ,\n",
+       "         9.714537  ,  9.714841  ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
+       "         9.715717  ,  9.711741  ,  9.710465  ,  9.712621  ,  9.71337   ,\n",
+       "         9.715622  ,  9.715989  ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
+       "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-de29e6fa-0f56-4d87-b171-ef3a1091f762' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de29e6fa-0f56-4d87-b171-ef3a1091f762' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5546337-3ff6-4986-a386-f2b1901fbdcd' class='xr-var-data-in' type='checkbox'><label for='data-f5546337-3ff6-4986-a386-f2b1901fbdcd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
+       "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
+       "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
+       "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
+       "       16.466002, 16.476501, 16.464167, 16.464666, 16.462667, 16.460833,\n",
+       "       16.462164, 16.460167, 16.459501, 16.459002, 16.454332, 16.449501,\n",
+       "       16.444332, 16.4325  , 16.422   , 16.412834, 16.400167, 16.397667,\n",
+       "       16.385334, 16.382334, 16.380499, 16.383333, 16.381332, 16.379833,\n",
+       "       16.382   , 16.379168, 16.380499, 16.378834, 16.374832, 16.384499,\n",
+       "       16.374166, 16.373333, 16.377167, 16.376   , 16.38    , 16.370333,\n",
+       "       16.376501, 16.382   , 16.3775  , 16.3815  , 16.378   , 16.3785  ,\n",
+       "       16.378   , 16.383667, 16.374668, 16.3845  , 16.353   , 16.372334,\n",
+       "       16.377668, 16.378168, 16.372334, 16.372665, 16.363167, 16.367167,\n",
+       "       16.372833, 16.363333, 16.355165, 16.367002, 16.368334, 16.372665,\n",
+       "       16.360834, 16.367834, 16.367   , 16.360834, 16.358   , 16.342833,\n",
+       "       16.341167, 16.328001, 16.317   , 16.305332, 16.295   , 16.2915  ,\n",
+       "       16.279333, 16.281166, 16.280834, 16.276167, 16.279333, 16.279333,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+       "       16.275   , 16.278334, 16.276834, 16.271   , 16.2725  , 16.27    ,\n",
+       "       16.265165, 16.268333, 16.268   , 16.264   , 16.268   , 16.268   ,\n",
+       "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.268   ,\n",
+       "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.263334,\n",
+       "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
+       "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
+       "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
+       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-7246ebc5-63f8-46e8-a0eb-6e66b537fdeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7246ebc5-63f8-46e8-a0eb-6e66b537fdeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b2b71af-ff51-449a-a230-50c42525f9e8' class='xr-var-data-in' type='checkbox'><label for='data-5b2b71af-ff51-449a-a230-50c42525f9e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
+       "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
+       "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
+       "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
+       "       20.25    , 20.25    , 20.163334, 20.      , 20.      , 20.      ,\n",
+       "       19.766666, 19.75    , 19.75    , 19.726667, 19.553333, 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.606667, 19.746666, 19.75    , 19.75    , 19.75    ,\n",
+       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+       "       19.556667, 19.5     , 19.5     , 19.5     , 19.626667, 19.75    ,\n",
+       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+       "       19.75    , 19.75    , 19.75    , 19.54    , 19.413334, 19.233334,\n",
+       "       19.      , 18.91    , 18.75    , 18.746666, 18.5     , 18.5     ,\n",
+       "       18.5     , 18.5     , 18.366667, 18.25    , 18.25    , 18.25    ,\n",
+       "       18.25    , 18.2     , 18.      , 18.      , 18.      , 18.      ,\n",
+       "       17.873333, 17.75    , 17.75    , 17.75    , 17.863333, 18.      ,\n",
+       "       18.      , 18.17    , 18.25    , 18.44    , 18.513334, 18.75    ,\n",
+       "       18.783333, 19.      , 19.      , 19.196667, 19.25    , 19.25    ,\n",
+       "       19.25    , 19.433332, 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
+       "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+       "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
+       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-cb14a4c6-5017-4bda-ac21-2fcc0f72702e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb14a4c6-5017-4bda-ac21-2fcc0f72702e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae80c9f2-edee-4981-90d7-b281d205f328' class='xr-var-data-in' type='checkbox'><label for='data-ae80c9f2-edee-4981-90d7-b281d205f328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-cc0cf513-bd59-407d-adc4-aec84aade42c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc0cf513-bd59-407d-adc4-aec84aade42c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a0b89f6-b56d-405b-9bc5-d0c028b38012' class='xr-var-data-in' type='checkbox'><label for='data-0a0b89f6-b56d-405b-9bc5-d0c028b38012' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "...\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355693e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-8c6a894f-c99f-4c61-8e63-9b0744f354b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c6a894f-c99f-4c61-8e63-9b0744f354b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbec152b-b3d5-455e-801a-5671c162591a' class='xr-var-data-in' type='checkbox'><label for='data-dbec152b-b3d5-455e-801a-5671c162591a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
+       "         -0.18383324, -0.17606331],\n",
+       "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
+       "         -0.19696543, -0.20011853],\n",
+       "        [ 0.26504937,  0.28428233,  0.31169885, ..., -0.2103943 ,\n",
+       "         -0.21627884, -0.21236075],\n",
+       "        ...,\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan]],\n",
+       "\n",
+       "       [[ 0.02619691,  0.04430203,  0.04002393, ...,  0.05932099,\n",
+       "          0.06400961,  0.07232199],\n",
+       "        [ 0.06181316,  0.07802678,  0.06236525, ...,  0.0768801 ,\n",
+       "          0.08184617,  0.0892335 ],\n",
+       "        [ 0.08793733,  0.10133781,  0.08016948, ...,  0.08136398,\n",
+       "          0.08639657,  0.10118616],\n",
+       "...\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan]],\n",
+       "\n",
+       "       [[-0.00417333, -0.01056667, -0.01045333, ..., -0.02584564,\n",
+       "         -0.02752333, -0.02575667],\n",
+       "        [ 0.01358667,  0.00760333,  0.00634667, ..., -0.01625333,\n",
+       "         -0.01776333, -0.01595   ],\n",
+       "        [ 0.01556187,  0.00811371,  0.00740333, ..., -0.00842   ,\n",
+       "         -0.01147667, -0.01189667],\n",
+       "        ...,\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan],\n",
+       "        [        nan,         nan,         nan, ...,         nan,\n",
+       "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-dcef319d-3809-4efc-ac3d-4bdfe1b0f3a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcef319d-3809-4efc-ac3d-4bdfe1b0f3a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d35a990-7c06-46e7-9f16-aa3349287c64' class='xr-var-data-in' type='checkbox'><label for='data-7d35a990-7c06-46e7-9f16-aa3349287c64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
+       "         81.68667 ],\n",
+       "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
+       "         77.528336],\n",
+       "        [72.81167 , 73.391304, 74.26833 , ..., 74.525   , 74.39667 ,\n",
+       "         74.253334],\n",
+       "        ...,\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]],\n",
+       "\n",
+       "       [[80.706665, 80.93833 , 81.255   , ..., 82.19833 , 82.225   ,\n",
+       "         82.17    ],\n",
+       "        [76.80666 , 76.996666, 77.44833 , ..., 78.38333 , 78.41167 ,\n",
+       "         78.06    ],\n",
+       "        [74.31834 , 74.64667 , 75.903336, ..., 75.16333 , 75.26833 ,\n",
+       "         74.875   ],\n",
+       "...\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]],\n",
+       "\n",
+       "       [[80.185   , 80.55    , 80.885   , ..., 81.888336, 81.945   ,\n",
+       "         81.85833 ],\n",
+       "        [75.78    , 76.291664, 76.76833 , ..., 77.97667 , 78.03833 ,\n",
+       "         77.87666 ],\n",
+       "        [72.67725 , 73.55666 , 74.44334 , ..., 74.75833 , 74.665   ,\n",
+       "         74.47    ],\n",
+       "        ...,\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan],\n",
+       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-e8e09ea2-5181-492c-9abb-4dae602329d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8e09ea2-5181-492c-9abb-4dae602329d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8efeaaf4-1cc0-461c-90da-afcc0082ce62' class='xr-var-data-in' type='checkbox'><label for='data-8efeaaf4-1cc0-461c-90da-afcc0082ce62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
+       "         92.06333 ],\n",
+       "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
+       "         96.03333 ],\n",
+       "        [97.166664, 96.246666, 95.94    , ..., 96.45333 , 97.206665,\n",
+       "         97.263336],\n",
+       "        ...,\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ]],\n",
+       "\n",
+       "       [[93.333336, 93.61    , 93.31333 , ..., 91.6     , 91.49    ,\n",
+       "         91.14667 ],\n",
+       "        [96.57    , 96.39    , 96.12666 , ..., 96.27    , 96.56333 ,\n",
+       "         96.44334 ],\n",
+       "        [97.37666 , 97.09333 , 96.87666 , ..., 96.17333 , 97.30334 ,\n",
+       "         97.32667 ],\n",
+       "...\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ]],\n",
+       "\n",
+       "       [[92.78333 , 93.223335, 92.63    , ..., 92.22    , 92.34    ,\n",
+       "         92.61    ],\n",
+       "        [96.75    , 96.34333 , 96.34    , ..., 96.53    , 96.69    ,\n",
+       "         96.27333 ],\n",
+       "        [96.346664, 97.05    , 97.24    , ..., 96.66333 , 96.89333 ,\n",
+       "         97.41    ],\n",
+       "        ...,\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ],\n",
+       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-9b2c757c-c921-4588-8c5b-3a44841f1715' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b2c757c-c921-4588-8c5b-3a44841f1715' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f51a2dc2-78d5-40bf-b90c-b2d939d5d5a2' class='xr-var-data-in' type='checkbox'><label for='data-f51a2dc2-78d5-40bf-b90c-b2d939d5d5a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
+       "          5.81927113e-02,  5.85613623e-02,  5.85512854e-02],\n",
+       "        [ 9.98300374e-01,  9.98323679e-01,  9.98248577e-01, ...,\n",
+       "          9.98254061e-01,  9.98234987e-01,  9.98234689e-01],\n",
+       "        [-1.05408905e-03, -1.34927384e-03, -1.13080605e-03, ...,\n",
+       "         -8.26976204e-04, -8.38353124e-04, -8.28948745e-04]],\n",
+       "\n",
+       "       [[-9.89950538e-01, -9.89953220e-01, -9.89922285e-01, ...,\n",
+       "         -9.91938353e-01, -9.91944909e-01, -9.91939366e-01],\n",
+       "        [ 5.68153895e-02,  5.63202463e-02,  5.76671995e-02, ...,\n",
+       "          5.77317439e-02,  5.80984168e-02,  5.80891557e-02],\n",
+       "        [-1.29125342e-01, -1.29299909e-01, -1.28952131e-01, ...,\n",
+       "         -1.12354711e-01, -1.12130061e-01, -1.12175331e-01]],\n",
+       "\n",
+       "       [[-1.28852651e-01, -1.29014045e-01, -1.28667876e-01, ...,\n",
+       "         -1.12116747e-01, -1.11889169e-01, -1.11934915e-01],\n",
+       "        [ 8.45469162e-03,  8.69723968e-03,  8.63243733e-03, ...,\n",
+       "          7.35414820e-03,  7.39390310e-03,  7.38611678e-03],\n",
+       "        [ 9.91627276e-01,  9.91604209e-01,  9.91649806e-01, ...,\n",
+       "          9.93667483e-01,  9.93692815e-01,  9.93687749e-01]]],\n",
+       "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-b485eef9-a704-4048-8ddb-75f9f1d992a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b485eef9-a704-4048-8ddb-75f9f1d992a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ded8637c-a800-4d74-b9aa-9f557aa69155' class='xr-var-data-in' type='checkbox'><label for='data-ded8637c-a800-4d74-b9aa-9f557aa69155' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
+       "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
+       "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
+       "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
+       "         0.00054653,  0.00055442,  0.00072552,  0.00056834,  0.00065792,\n",
+       "         0.00086152,  0.00080709,  0.00096736,  0.00085591,  0.00094166,\n",
+       "         0.00090368,  0.00095632,  0.00094047,  0.00091472,  0.00092718,\n",
+       "         0.00097144,  0.00090388,  0.00098592,  0.00099217,  0.00104627,\n",
+       "         0.00101094,  0.00108953,  0.00094413,  0.0010326 ,  0.00105636,\n",
+       "         0.00098609,  0.00101084,  0.00101927,  0.00101796,  0.00096841,\n",
+       "         0.00102785,  0.00113951,  0.00098156,  0.00111134,  0.00100472,\n",
+       "         0.00104199,  0.00104198,  0.00100612,  0.00103637,  0.00099132,\n",
+       "         0.00102272,  0.00102712,  0.00100425,  0.0010416 ,  0.00097589,\n",
+       "         0.00090605,  0.00108258,  0.00090169,  0.00096689,  0.00081777,\n",
+       "         0.0009423 ,  0.00087804,  0.00102183,  0.00083111,  0.0009242 ,\n",
+       "         0.00094747,  0.00110261,  0.00097415,  0.00097692,  0.00113317,\n",
+       "         0.00105406,  0.00104935,  0.00102722,  0.00093711,  0.00103575,\n",
+       "         0.00095867,  0.0009583 ,  0.00104538,  0.00100466,  0.00095809,\n",
+       "         0.00101549,  0.00097118,  0.00090704,  0.00094464,  0.00096578,\n",
+       "         0.00105039,  0.00093799,  0.00100518,  0.00088882,  0.00095506,\n",
+       "...\n",
+       "        -0.00263344, -0.00258787, -0.00256183, -0.00256183, -0.00250324,\n",
+       "        -0.00268227, -0.00268227, -0.00259113, -0.00262693, -0.00257485,\n",
+       "        -0.00259113, -0.00252602, -0.00267576, -0.00253904, -0.00256509,\n",
+       "        -0.00242511, -0.00249998, -0.00250975, -0.00252277, -0.00261066,\n",
+       "        -0.00257485, -0.00265298, -0.00264647, -0.00261391, -0.00260089,\n",
+       "        -0.00270181, -0.0027604 , -0.00278318, -0.00288084, -0.00274412,\n",
+       "        -0.00280272, -0.00289386, -0.0030729 , -0.0029492 , -0.0029199 ,\n",
+       "        -0.00302407, -0.00299803, -0.00296222, -0.00288084, -0.00299477,\n",
+       "        -0.00304034, -0.00298175, -0.00296222, -0.00296873, -0.00305337,\n",
+       "        -0.00302081, -0.00299803, -0.00304034, -0.0030729 , -0.0029199 ,\n",
+       "        -0.00295571, -0.00287433, -0.00287433, -0.0028548 , -0.00275714,\n",
+       "        -0.00271157, -0.0027018 , -0.00278644, -0.0026074 , -0.00264972,\n",
+       "        -0.00273761, -0.00259764, -0.00258787, -0.00256834, -0.00263344,\n",
+       "        -0.00255207, -0.00265623, -0.00261391, -0.00255207, -0.00249673,\n",
+       "        -0.00258787, -0.00256183, -0.00253579, -0.00264321, -0.00268553,\n",
+       "        -0.00255858, -0.00264321, -0.00262693, -0.0025423 , -0.00256834,\n",
+       "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
+       "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
+       "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
+       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-ecc277c0-5ffc-479d-8499-8da5fe58c508' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecc277c0-5ffc-479d-8499-8da5fe58c508' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69e77445-8f9a-4232-803d-89f14e29e3ff' class='xr-var-data-in' type='checkbox'><label for='data-69e77445-8f9a-4232-803d-89f14e29e3ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
+       "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
+       "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
+       "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
+       "         0.6253574 ,  0.6254711 ,  0.6251542 ,  0.6249595 ,  0.62512624,\n",
+       "         0.62510735,  0.62479544,  0.6250753 ,  0.624999  ,  0.6248949 ,\n",
+       "         0.6248343 ,  0.6245227 ,  0.6248399 ,  0.624795  ,  0.6250311 ,\n",
+       "         0.62494355,  0.6249766 ,  0.6244582 ,  0.62417775,  0.6244494 ,\n",
+       "         0.6248647 ,  0.6245337 ,  0.62416995,  0.6242157 ,  0.62425923,\n",
+       "         0.6247039 ,  0.6248129 ,  0.6246122 ,  0.6248121 ,  0.6246928 ,\n",
+       "         0.6245991 ,  0.6248212 ,  0.6247573 ,  0.6243741 ,  0.6243043 ,\n",
+       "         0.6244282 ,  0.6243682 ,  0.6240724 ,  0.62418926,  0.6241515 ,\n",
+       "         0.6239765 ,  0.62391806,  0.62415963,  0.62387216,  0.6239287 ,\n",
+       "         0.62390673,  0.6236841 ,  0.62378633,  0.6236643 ,  0.6235926 ,\n",
+       "         0.62364197,  0.6237233 ,  0.62374234,  0.62387735,  0.62402254,\n",
+       "         0.62393117,  0.62393445,  0.62373453,  0.62396324,  0.62340415,\n",
+       "         0.62373024,  0.62379295,  0.62355286,  0.6231889 ,  0.62350035,\n",
+       "         0.6232749 ,  0.6232579 ,  0.6233172 ,  0.6232117 ,  0.62328154,\n",
+       "         0.6234021 ,  0.62359464,  0.6235321 ,  0.62355274,  0.62340564,\n",
+       "         0.6233349 ,  0.6232732 ,  0.62326413,  0.62335676,  0.6233057 ,\n",
+       "...\n",
+       "         0.77982664,  0.7798403 ,  0.77980125,  0.7798833 ,  0.7798343 ,\n",
+       "         0.77974474,  0.7795985 ,  0.77965385,  0.77964175,  0.7797572 ,\n",
+       "         0.7798193 ,  0.77987343,  0.77987754,  0.7798154 ,  0.7798561 ,\n",
+       "         0.77976704,  0.77973217,  0.77971977,  0.77958   ,  0.7794924 ,\n",
+       "         0.77951276,  0.77934176,  0.77977145,  0.77983665,  0.7796758 ,\n",
+       "         0.77951133,  0.77975136,  0.7796223 ,  0.7795445 ,  0.7798783 ,\n",
+       "         0.7796854 ,  0.78009176,  0.77983886,  0.77976817,  0.7798124 ,\n",
+       "         0.77966744,  0.77980477,  0.77957195,  0.7797228 ,  0.7795519 ,\n",
+       "         0.77965647,  0.7795511 ,  0.7795689 ,  0.77951413,  0.77942085,\n",
+       "         0.7791843 ,  0.7793043 ,  0.7793574 ,  0.7790914 ,  0.77922   ,\n",
+       "         0.7788722 ,  0.77907705,  0.7790985 ,  0.778842  ,  0.7789314 ,\n",
+       "         0.77889466,  0.7789852 ,  0.7792381 ,  0.77916646,  0.7788889 ,\n",
+       "         0.77894676,  0.7789039 ,  0.7785506 ,  0.7786492 ,  0.7788344 ,\n",
+       "         0.7786969 ,  0.77884805,  0.7789083 ,  0.77894056,  0.7786727 ,\n",
+       "         0.77858806,  0.7783844 ,  0.7785528 ,  0.7787677 ,  0.77864134,\n",
+       "         0.77870125,  0.7787834 ,  0.7788154 ,  0.7788442 ,  0.7785659 ,\n",
+       "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
+       "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
+       "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
+       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-2a830c4a-30b3-44a0-bf5d-015ab205796c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a830c4a-30b3-44a0-bf5d-015ab205796c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2451ce69-7a5d-4d87-91a9-a73a177b0ae6' class='xr-var-data-in' type='checkbox'><label for='data-2451ce69-7a5d-4d87-91a9-a73a177b0ae6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
+       "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
+       "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
+       "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
+       "       13.       , 12.941335 , 12.800002 , 12.631333 , 12.598    ,\n",
+       "       12.411335 , 12.400001 , 12.230666 , 12.199998 , 12.119332 ,\n",
+       "       12.       , 12.       , 12.       , 11.957999 , 11.800002 ,\n",
+       "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.800002 ,\n",
+       "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.834001 ,\n",
+       "       11.999333 , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.104667 , 12.193999 , 12.199998 , 12.199998 ,\n",
+       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.086667 ,\n",
+       "       12.113999 , 12.192665 , 12.032667 , 12.078666 , 12.03     ,\n",
+       "       12.       , 12.111999 , 12.199998 , 12.199998 , 12.199998 ,\n",
+       "       12.202665 , 12.219333 , 12.274    , 12.367333 , 12.203999 ,\n",
+       "       12.217332 , 12.199998 , 12.199998 , 12.119332 , 11.845334 ,\n",
+       "       11.496667 , 11.219998 , 11.       , 10.952001 , 10.800002 ,\n",
+       "       10.800002 , 10.800002 , 10.800002 , 10.751334 , 10.599999 ,\n",
+       "       10.599999 , 10.599999 , 10.599999 , 10.5546665, 10.400001 ,\n",
+       "       10.400001 , 10.334666 , 10.2      , 10.2      , 10.191999 ,\n",
+       "       10.029333 , 10.       , 10.009334 , 10.198667 , 10.243333 ,\n",
+       "       10.415334 , 10.599999 , 10.772668 , 11.       , 11.186666 ,\n",
+       "       11.398002 , 11.528    , 11.599999 , 11.746667 , 11.800002 ,\n",
+       "       11.876667 , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       , 12.000667 , 12.006    ,\n",
+       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.001333 , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.024667 , 12.173999 , 12.199998 ,\n",
+       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+       "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
+       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-2f827c3d-1b05-44f9-af16-7d6e6e5751ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f827c3d-1b05-44f9-af16-7d6e6e5751ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-205c009a-da96-4bd6-b2a8-2b72ee9626d5' class='xr-var-data-in' type='checkbox'><label for='data-205c009a-da96-4bd6-b2a8-2b72ee9626d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
+       "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
+       "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
+       "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
+       "       244.98334, 244.94   , 244.86333, 244.82666, 244.79333, 244.84666,\n",
+       "       244.76666, 244.73334, 244.82666, 244.75   , 244.86333, 244.83   ,\n",
+       "       244.84334, 244.91333, 244.96666, 245.08   , 245.25333, 245.30667,\n",
+       "       245.4    , 245.51   , 245.61333, 245.61   , 245.65666, 245.76666,\n",
+       "       245.73   , 245.79666, 245.83333, 245.85333, 245.81   , 245.85667,\n",
+       "       245.90334, 245.89333, 245.90666, 245.90334, 245.89333, 245.90666,\n",
+       "       245.93   , 245.91333, 245.91667, 245.92334, 245.92334, 245.92   ,\n",
+       "       245.96   , 245.95   , 245.94333, 245.96   , 245.94667, 245.97   ,\n",
+       "       245.95   , 245.93666, 245.93   , 245.95667, 245.94   , 245.95667,\n",
+       "       245.95   , 245.95334, 245.96666, 245.98   , 245.96666, 245.97   ,\n",
+       "       245.97   , 245.98   , 245.97333, 245.97   , 245.98666, 245.97667,\n",
+       "       245.97667, 245.98334, 245.97667, 245.99333, 245.97667, 245.98334,\n",
+       "       245.99667, 245.99667, 245.99   , 245.97333, 245.98334, 245.98666,\n",
+       "       245.97   , 245.99667, 245.98666, 245.98   , 245.85667, 245.44667,\n",
+       "       244.92334, 244.41667, 244.16333, 244.00667, 244.06   , 244.07333,\n",
+       "       243.87334, 243.77333, 243.75   , 243.69   , 243.76334, 243.79666,\n",
+       "       243.55   , 243.5    , 243.37666, 243.20334, 242.92334, 242.87666,\n",
+       "       242.83   , 242.83333, 243.07666, 243.41   , 243.88333, 244.20334,\n",
+       "       244.40334, 244.45334, 244.48666, 244.41   , 244.38   , 244.43333,\n",
+       "       244.6    , 244.72333, 244.90666, 244.9    , 244.97667, 245.03667,\n",
+       "       245.22667, 245.36   , 245.4    , 245.42   , 245.48334, 245.62666,\n",
+       "       245.67   , 245.71333, 245.75667, 245.77   , 245.84   , 245.87   ,\n",
+       "       245.87666, 245.89   , 245.87666, 245.94333, 245.93   , 245.91333,\n",
+       "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
+       "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
+       "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
+       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-ae0eb9cf-4aef-4228-821f-8ce74f6dc8bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae0eb9cf-4aef-4228-821f-8ce74f6dc8bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9483a782-9e95-4403-9163-7f1a77ac2ebd' class='xr-var-data-in' type='checkbox'><label for='data-9483a782-9e95-4403-9163-7f1a77ac2ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
+       "         3.6116719e+00,  3.5757926e+00,  3.5947008e+00,  3.6243417e+00,\n",
+       "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830538e+00,\n",
+       "         3.6165168e+00,  3.5789921e+00,  3.5747981e+00,  3.5690453e+00,\n",
+       "         3.5796013e+00,  3.6261466e+00,  3.6063533e+00,  3.6014795e+00,\n",
+       "         3.6353865e+00,  3.6033041e+00,  3.6023455e+00,  3.5552027e+00,\n",
+       "         3.5689840e+00,  3.5028169e+00,  3.5047083e+00,  3.5002160e+00,\n",
+       "         3.4591196e+00,  3.4518204e+00,  3.4781299e+00,  3.4272485e+00,\n",
+       "         3.4080899e+00,  3.4372404e+00,  3.4341383e+00,  3.3986638e+00,\n",
+       "         3.4168522e+00,  3.4093900e+00,  3.3794670e+00,  3.3934760e+00,\n",
+       "         3.4050257e+00,  3.4207287e+00,  3.3710022e+00,  3.3771679e+00,\n",
+       "         3.3508575e+00,  3.3733418e+00,  3.3524203e+00,  3.3316767e+00,\n",
+       "         3.3258898e+00,  3.3680136e+00,  3.2842207e+00,  3.1945534e+00,\n",
+       "         3.0031645e+00,  2.4369471e+00,  2.1365104e+00,  1.9519800e+00,\n",
+       "         1.7708881e+00,  1.6470156e+00,  1.5729071e+00,  1.4625059e+00,\n",
+       "         1.3881445e+00,  1.3379683e+00,  1.3052688e+00,  1.2468668e+00,\n",
+       "         1.2023062e+00,  1.1269653e+00,  1.1022494e+00,  1.0541168e+00,\n",
+       "         1.0267943e+00,  9.7805512e-01,  9.2956728e-01,  9.2703992e-01,\n",
+       "         9.1599506e-01,  8.9450091e-01,  8.5012424e-01,  8.2220656e-01,\n",
+       "         7.9883534e-01,  7.8205061e-01,  7.3997599e-01,  7.3860037e-01,\n",
+       "...\n",
+       "        -1.9736919e+02, -1.9725951e+02, -1.9730052e+02, -1.9728384e+02,\n",
+       "        -1.9724889e+02, -1.9722919e+02, -1.9715518e+02, -1.9727151e+02,\n",
+       "        -1.9724452e+02, -1.9721884e+02, -1.9717354e+02, -1.9723384e+02,\n",
+       "        -1.9719716e+02, -1.9714218e+02, -1.9723254e+02, -1.9710817e+02,\n",
+       "        -1.9708250e+02, -1.9709784e+02, -1.9708986e+02, -1.9712950e+02,\n",
+       "        -1.9721385e+02, -1.9720052e+02, -1.9717422e+02, -1.9710918e+02,\n",
+       "        -1.9715718e+02, -1.9714487e+02, -1.9715251e+02, -1.9714418e+02,\n",
+       "        -1.9714218e+02, -1.9706715e+02, -1.9705818e+02, -1.9705084e+02,\n",
+       "        -1.9708583e+02, -1.9708820e+02, -1.9714618e+02, -1.9709253e+02,\n",
+       "        -1.9707854e+02, -1.9714384e+02, -1.9717952e+02, -1.9718620e+02,\n",
+       "        -1.9718388e+02, -1.9716652e+02, -1.9712685e+02, -1.9720485e+02,\n",
+       "        -1.9718315e+02, -1.9713019e+02, -1.9714951e+02, -1.9724086e+02,\n",
+       "        -1.9716119e+02, -1.9719583e+02, -1.9724786e+02, -1.9716052e+02,\n",
+       "        -1.9725883e+02, -1.9720285e+02, -1.9717485e+02, -1.9725154e+02,\n",
+       "        -1.9714687e+02, -1.9711821e+02, -1.9714719e+02, -1.9711786e+02,\n",
+       "        -1.9714052e+02, -1.9714351e+02, -1.9715118e+02, -1.9712117e+02,\n",
+       "        -1.9710718e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
+       "        -1.9706255e+02, -1.9714519e+02, -1.9712418e+02, -1.9705786e+02,\n",
+       "        -1.9708685e+02, -1.9711749e+02, -1.9707716e+02, -1.9707919e+02,\n",
+       "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-46b1204c-9611-4b1c-ac05-95b954782894' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46b1204c-9611-4b1c-ac05-95b954782894' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c86a487e-4d9c-46fd-ad8a-56fc4ee29a89' class='xr-var-data-in' type='checkbox'><label for='data-c86a487e-4d9c-46fd-ad8a-56fc4ee29a89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
+       "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
+       "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
+       "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569212 , -1.2552022 ,\n",
+       "        -1.2558354 , -1.2547812 , -1.2564313 , -1.2570257 , -1.2564919 ,\n",
+       "        -1.2552761 , -1.2551885 , -1.254373  , -1.2521615 , -1.253256  ,\n",
+       "        -1.2520183 , -1.2556639 , -1.2544196 , -1.2537049 , -1.2514051 ,\n",
+       "        -1.251719  , -1.2501887 , -1.2550075 , -1.2560523 , -1.2542702 ,\n",
+       "        -1.2513357 , -1.2537422 , -1.25587   , -1.2554086 , -1.2568508 ,\n",
+       "        -1.2513126 , -1.251984  , -1.2514541 , -1.2487588 , -1.249171  ,\n",
+       "        -1.2487395 , -1.2432916 , -1.2308283 , -1.2085198 , -1.1925628 ,\n",
+       "        -1.1850357 , -1.175814  , -1.1718632 , -1.1669031 , -1.1620393 ,\n",
+       "        -1.1585126 , -1.1573663 , -1.1550487 , -1.1537894 , -1.1520277 ,\n",
+       "        -1.1507337 , -1.1474868 , -1.1443372 , -1.1442864 , -1.1430473 ,\n",
+       "        -1.1418384 , -1.141045  , -1.1385593 , -1.1344901 , -1.134764  ,\n",
+       "        -1.1317551 , -1.1333026 , -1.1325271 , -1.1293766 , -1.1324316 ,\n",
+       "        -1.1310244 , -1.1295373 , -1.1287975 , -1.1317044 , -1.1290994 ,\n",
+       "        -1.1286312 , -1.1276112 , -1.1271322 , -1.128308  , -1.1257491 ,\n",
+       "        -1.1227695 , -1.1230273 , -1.119395  , -1.1190095 , -1.1182653 ,\n",
+       "        -1.1186818 , -1.1167871 , -1.1160123 , -1.1153725 , -1.1143075 ,\n",
+       "...\n",
+       "         9.716884  ,  9.718464  ,  9.717347  ,  9.717715  ,  9.714792  ,\n",
+       "         9.714857  ,  9.712732  ,  9.712222  ,  9.713994  ,  9.715383  ,\n",
+       "         9.71674   ,  9.716182  ,  9.717108  ,  9.716772  ,  9.715446  ,\n",
+       "         9.714425  ,  9.7126045 ,  9.713626  ,  9.7121105 ,  9.711023  ,\n",
+       "         9.711408  ,  9.709459  ,  9.712988  ,  9.7141695 ,  9.710418  ,\n",
+       "         9.713371  ,  9.713164  ,  9.711615  ,  9.713355  ,  9.714377  ,\n",
+       "         9.714473  ,  9.719391  ,  9.71805   ,  9.71583   ,  9.716421  ,\n",
+       "         9.71658   ,  9.71583   ,  9.71334   ,  9.7177305 ,  9.716677  ,\n",
+       "         9.71476   ,  9.716166  ,  9.713404  ,  9.715751  ,  9.715623  ,\n",
+       "         9.712237  ,  9.714856  ,  9.7166605 ,  9.713179  ,  9.7175865 ,\n",
+       "         9.710929  ,  9.71484   ,  9.715895  ,  9.712062  ,  9.71591   ,\n",
+       "         9.714346  ,  9.716932  ,  9.718177  ,  9.718816  ,  9.713802  ,\n",
+       "         9.717826  ,  9.715128  ,  9.711727  ,  9.713515  ,  9.718353  ,\n",
+       "         9.716836  ,  9.716278  ,  9.717762  ,  9.718656  ,  9.714761  ,\n",
+       "         9.713004  ,  9.710816  ,  9.71409   ,  9.716276  ,  9.713579  ,\n",
+       "         9.716166  ,  9.718401  ,  9.716804  ,  9.718209  ,  9.71428   ,\n",
+       "         9.714553  ,  9.715957  ,  9.7148075 ,  9.717874  ,  9.716309  ,\n",
+       "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
+       "         9.715256  ,  9.714936  ,  9.7148075 ,  9.711726  ,  9.711886  ,\n",
+       "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-66d06c2c-bd2e-4996-b5b5-ba589e57b5fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66d06c2c-bd2e-4996-b5b5-ba589e57b5fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5ddc8ed-095e-4d98-b4e4-696af069547d' class='xr-var-data-in' type='checkbox'><label for='data-c5ddc8ed-095e-4d98-b4e4-696af069547d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-15c9c44d-d3c5-4a48-8ce4-6d873cffbb20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15c9c44d-d3c5-4a48-8ce4-6d873cffbb20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3efbacfb-7d62-4858-b87c-821787f8223e' class='xr-var-data-in' type='checkbox'><label for='data-3efbacfb-7d62-4858-b87c-821787f8223e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355693e+09, 1.05355686e+09, 1.05355693e+09,\n",
+       "       1.05355699e+09, 1.05355686e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355693e+09,\n",
+       "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
+       "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355693e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "...\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-297b8fbf-740d-4abd-9031-0598d65507a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-297b8fbf-740d-4abd-9031-0598d65507a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a67f119-6cdb-46e7-a66e-d907e680773a' class='xr-var-data-in' type='checkbox'><label for='data-2a67f119-6cdb-46e7-a66e-d907e680773a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
+       "        -0.02035667, -0.01573333],\n",
+       "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
+       "        -0.00658667, -0.00238   ],\n",
+       "       [ 0.02739334,  0.01897667,  0.01496333, ...,  0.00196667,\n",
+       "        -0.00096667,  0.00083946],\n",
+       "       ...,\n",
+       "       [        nan,         nan,         nan, ...,         nan,\n",
+       "                nan,         nan],\n",
+       "       [        nan,         nan,         nan, ...,         nan,\n",
+       "                nan,         nan],\n",
+       "       [        nan,         nan,         nan, ...,         nan,\n",
+       "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-538241e5-a10c-4c59-8268-c21f482db45c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538241e5-a10c-4c59-8268-c21f482db45c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5027d2b2-8a7b-431b-9ba2-4cefabf900e8' class='xr-var-data-in' type='checkbox'><label for='data-5027d2b2-8a7b-431b-9ba2-4cefabf900e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
+       "        81.745   ],\n",
+       "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
+       "        78.045   ],\n",
+       "       [73.58833 , 74.355   , 75.083336, ..., 75.265   , 75.098335,\n",
+       "        74.92976 ],\n",
+       "       ...,\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-a65f35cd-777d-4e00-b3a4-2b3b223bfae8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a65f35cd-777d-4e00-b3a4-2b3b223bfae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f69b5dac-a215-4e37-a4cc-a214d0c865c6' class='xr-var-data-in' type='checkbox'><label for='data-f69b5dac-a215-4e37-a4cc-a214d0c865c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
+       "        92.61667 ],\n",
+       "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
+       "        96.57667 ],\n",
+       "       [97.19    , 97.32333 , 97.136665, ..., 96.08667 , 97.16    ,\n",
+       "        96.96667 ],\n",
+       "       ...,\n",
+       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "         0.      ],\n",
+       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "         0.      ],\n",
+       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+       "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-4bec0e51-ca20-4b23-9298-9aa49c02fed7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bec0e51-ca20-4b23-9298-9aa49c02fed7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd70347f-70ee-4b01-9d6c-7d045c455cb2' class='xr-var-data-in' type='checkbox'><label for='data-cd70347f-70ee-4b01-9d6c-7d045c455cb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
+       "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
+       "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
+       "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
+       "        [-1.26286745e-01, -1.26509830e-01, -1.26157105e-01, ...,\n",
+       "         -1.09885700e-01, -1.09676003e-01, -1.09719723e-01]],\n",
+       "\n",
+       "       [[ 9.76216435e-01,  9.76112664e-01,  9.76405323e-01, ...,\n",
+       "          9.76383269e-01,  9.76462007e-01,  9.76460576e-01],\n",
+       "        [-2.14884892e-01, -2.15368673e-01, -2.14055121e-01, ...,\n",
+       "         -2.14541376e-01, -2.14190111e-01, -2.14200497e-01],\n",
+       "        [-2.69518793e-02, -2.67608669e-02, -2.67287735e-02, ...,\n",
+       "         -2.34543420e-02, -2.33496260e-02, -2.33698264e-02]],\n",
+       "\n",
+       "       [[-1.05265796e-03, -1.35056104e-03, -1.13043608e-03, ...,\n",
+       "         -8.24717747e-04, -8.40478169e-04, -8.31306970e-04],\n",
+       "        [-1.29126370e-01, -1.29302278e-01, -1.28952518e-01, ...,\n",
+       "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
+       "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
+       "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
+       "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-bc7b5757-d49e-4310-8739-c8fe662b1c7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc7b5757-d49e-4310-8739-c8fe662b1c7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fa91cc2-2039-4555-a442-bb831c9e93b0' class='xr-var-data-in' type='checkbox'><label for='data-7fa91cc2-2039-4555-a442-bb831c9e93b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
+       "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
+       "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
+       "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
+       "         0.00056599,  0.00061758,  0.00068752,  0.00066373,  0.00073918,\n",
+       "         0.00085721,  0.00084523,  0.0009018 ,  0.00089635,  0.00084324,\n",
+       "         0.00086276,  0.00089614,  0.00096862,  0.00108153,  0.00095481,\n",
+       "         0.00098828,  0.00098117,  0.00097845,  0.00099421,  0.00095727,\n",
+       "         0.00108126,  0.00108415,  0.00096381,  0.00100037,  0.00098756,\n",
+       "         0.00103554,  0.00096841,  0.00107755,  0.00104051,  0.0009601 ,\n",
+       "         0.00106976,  0.0010707 ,  0.00102194,  0.0009954 ,  0.00100513,\n",
+       "         0.0010245 ,  0.00102471,  0.00096594,  0.0010335 ,  0.00105437,\n",
+       "         0.00105971,  0.00095506,  0.00102042,  0.00097918,  0.00088768,\n",
+       "         0.0009018 ,  0.00096684,  0.00101125,  0.00096008,  0.0008592 ,\n",
+       "         0.00082965,  0.00095935,  0.00094485,  0.00081024,  0.00092011,\n",
+       "         0.00098175,  0.00094213,  0.00095046,  0.00099598,  0.00104662,\n",
+       "         0.00101681,  0.0010222 ,  0.00099111,  0.001044  ,  0.00103549,\n",
+       "         0.00097536,  0.00099907,  0.00097684,  0.00104176,  0.00094763,\n",
+       "         0.0009761 ,  0.00097227,  0.00089143,  0.00096118,  0.00097306,\n",
+       "         0.00096506,  0.00094653,  0.00092565,  0.00091383,  0.0009503 ,\n",
+       "...\n",
+       "        -0.00262043, -0.00258136, -0.00261717, -0.00257811, -0.00261066,\n",
+       "        -0.00255532, -0.00266274, -0.00254881, -0.00255858, -0.00259764,\n",
+       "        -0.00258462, -0.00252602, -0.00258787, -0.00256183, -0.00260415,\n",
+       "        -0.00251626, -0.00250975, -0.00243488, -0.00254881, -0.00264321,\n",
+       "        -0.00260089, -0.00263996, -0.0026367 , -0.00271157, -0.00256183,\n",
+       "        -0.00271808, -0.00277993, -0.00284178, -0.00276365, -0.00277016,\n",
+       "        -0.00279946, -0.00295896, -0.00294594, -0.00302732, -0.00302407,\n",
+       "        -0.00301756, -0.00298501, -0.00291339, -0.00296548, -0.00294269,\n",
+       "        -0.00311196, -0.00294594, -0.0030143 , -0.00297198, -0.00296873,\n",
+       "        -0.002985  , -0.0030729 , -0.0030143 , -0.00306638, -0.00288084,\n",
+       "        -0.00289386, -0.00281899, -0.00278644, -0.0028255 , -0.00276365,\n",
+       "        -0.00277993, -0.002666  , -0.00267576, -0.002666  , -0.00268227,\n",
+       "        -0.00268878, -0.00263019, -0.00254881, -0.00262368, -0.00263019,\n",
+       "        -0.00260415, -0.00257811, -0.0026074 , -0.00249673, -0.00254881,\n",
+       "        -0.00258787, -0.00263019, -0.00255532, -0.00269204, -0.00258136,\n",
+       "        -0.00259113, -0.00272133, -0.00258462, -0.00263019, -0.00261066,\n",
+       "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
+       "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
+       "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
+       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-249663e1-6f7d-4320-b41d-dd342f1539e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-249663e1-6f7d-4320-b41d-dd342f1539e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62887a06-1b0e-4cba-a74c-c54451e0a3d8' class='xr-var-data-in' type='checkbox'><label for='data-62887a06-1b0e-4cba-a74c-c54451e0a3d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
+       "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
+       "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
+       "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
+       "         0.6253524 ,  0.6254653 ,  0.62515104,  0.62495625,  0.62512195,\n",
+       "         0.6251015 ,  0.624793  ,  0.6250713 ,  0.6249948 ,  0.62489176,\n",
+       "         0.6248301 ,  0.62451917,  0.6248372 ,  0.62479085,  0.62502736,\n",
+       "         0.6249378 ,  0.62497205,  0.62445515,  0.62417245,  0.6244453 ,\n",
+       "         0.6248608 ,  0.62453014,  0.62416404,  0.6242139 ,  0.62425303,\n",
+       "         0.62470126,  0.6248098 ,  0.62460905,  0.62480783,  0.6246901 ,\n",
+       "         0.6245936 ,  0.6248162 ,  0.624754  ,  0.62437105,  0.62430066,\n",
+       "         0.6244233 ,  0.6243633 ,  0.62407166,  0.6241861 ,  0.6241456 ,\n",
+       "         0.6239719 ,  0.62391376,  0.62415487,  0.6238682 ,  0.6239241 ,\n",
+       "         0.62390107,  0.6236789 ,  0.6237806 ,  0.6236614 ,  0.62358916,\n",
+       "         0.6236376 ,  0.62371755,  0.6237382 ,  0.6238726 ,  0.6240171 ,\n",
+       "         0.6239264 ,  0.623931  ,  0.6237308 ,  0.62395936,  0.6234018 ,\n",
+       "         0.6237265 ,  0.6237913 ,  0.6235492 ,  0.62318647,  0.62349266,\n",
+       "         0.62327045,  0.6232548 ,  0.6233126 ,  0.6232084 ,  0.6232786 ,\n",
+       "         0.62339824,  0.62359285,  0.6235284 ,  0.6235471 ,  0.6234016 ,\n",
+       "         0.6233313 ,  0.6232729 ,  0.6232614 ,  0.62335205,  0.6232998 ,\n",
+       "...\n",
+       "         0.7798304 ,  0.77984285,  0.7798039 ,  0.7798881 ,  0.77983624,\n",
+       "         0.779747  ,  0.7796003 ,  0.7796562 ,  0.77964693,  0.77976   ,\n",
+       "         0.77982175,  0.77987325,  0.7798803 ,  0.77981853,  0.7798599 ,\n",
+       "         0.77976817,  0.7797355 ,  0.7797223 ,  0.77958274,  0.7794968 ,\n",
+       "         0.77951866,  0.7793451 ,  0.77977306,  0.7798404 ,  0.7796792 ,\n",
+       "         0.77951556,  0.7797541 ,  0.7796244 ,  0.77954704,  0.779882  ,\n",
+       "         0.7796897 ,  0.78009367,  0.77984214,  0.77977324,  0.77981466,\n",
+       "         0.77967215,  0.77980614,  0.7795769 ,  0.77972573,  0.77955645,\n",
+       "         0.7796588 ,  0.77955323,  0.7795721 ,  0.7795167 ,  0.7794243 ,\n",
+       "         0.77918714,  0.77930677,  0.7793621 ,  0.77909505,  0.7792217 ,\n",
+       "         0.7788761 ,  0.7790808 ,  0.7791028 ,  0.7788446 ,  0.7789332 ,\n",
+       "         0.7788981 ,  0.7789904 ,  0.779241  ,  0.7791693 ,  0.77889454,\n",
+       "         0.7789502 ,  0.77890694,  0.7785553 ,  0.77865255,  0.7788394 ,\n",
+       "         0.7787025 ,  0.7788493 ,  0.77891165,  0.7789452 ,  0.77867603,\n",
+       "         0.7785905 ,  0.7783878 ,  0.77855736,  0.778772  ,  0.7786441 ,\n",
+       "         0.77870494,  0.77878624,  0.77881914,  0.77884936,  0.77857053,\n",
+       "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
+       "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
+       "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
+       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-a7e823ec-24f5-4377-8a95-1a95da2b173e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7e823ec-24f5-4377-8a95-1a95da2b173e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92536e33-550f-4745-bbf1-ee46c2c42b1b' class='xr-var-data-in' type='checkbox'><label for='data-92536e33-550f-4745-bbf1-ee46c2c42b1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-611825d7-5271-4d27-a72d-ff4b5e390601' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-611825d7-5271-4d27-a72d-ff4b5e390601' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b3bd447-85f3-4be3-84d1-3031537131a9' class='xr-var-data-in' type='checkbox'><label for='data-6b3bd447-85f3-4be3-84d1-3031537131a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4448bbd9-b593-40b2-b58c-072b98492615' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4448bbd9-b593-40b2-b58c-072b98492615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673aba38-c31c-4c3c-9918-8990d37228a2' class='xr-var-data-in' type='checkbox'><label for='data-673aba38-c31c-4c3c-9918-8990d37228a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ff482eee-9029-43c4-93f5-66e8228b90cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff482eee-9029-43c4-93f5-66e8228b90cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31618f71-8540-44d9-85ff-e6866de2fed7' class='xr-var-data-in' type='checkbox'><label for='data-31618f71-8540-44d9-85ff-e6866de2fed7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-b3c849c7-37f8-4509-bd76-c64ecac873aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3c849c7-37f8-4509-bd76-c64ecac873aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3a64d6c-df81-491b-a306-b02af38afc75' class='xr-var-data-in' type='checkbox'><label for='data-d3a64d6c-df81-491b-a306-b02af38afc75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
+       "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
+       "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
+       "       0.12      , 0.12333333, 0.12      , 0.11      , 0.11      ,\n",
+       "       0.11666667, 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11333334,\n",
+       "       0.12      , 0.11666667, 0.11666667, 0.11666667, 0.11333334,\n",
+       "       0.12      , 0.11666667, 0.11      , 0.12333333, 0.13333334,\n",
+       "       0.13333334, 0.13      , 0.13333334, 0.12666667, 0.13333334,\n",
+       "       0.13      , 0.13      , 0.15333334, 0.13333334, 0.15333334,\n",
+       "       0.14333333, 0.13666667, 0.11666667, 0.13666667, 0.13333334,\n",
+       "       0.13666667, 0.14666666, 0.14      , 0.15666667, 0.13333334,\n",
+       "       0.13333334, 0.15      , 0.15      , 0.12666667, 0.13666667,\n",
+       "       0.15      , 0.13      , 0.13666667, 0.13      , 0.13666667,\n",
+       "       0.13666667, 0.14333333, 0.13666667, 0.12666667, 0.13666667,\n",
+       "       0.12333333, 0.12333333, 0.13333334, 0.12      , 0.11666667,\n",
+       "       0.11      , 0.11      , 0.11666667, 0.12333333, 0.11      ,\n",
+       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+       "       0.11      , 0.20333333, 0.22666667, 0.22      , 0.22      ,\n",
+       "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
+       "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
+       "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
+       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-b8a3d627-053f-4298-ac79-4a0c3c3d1f55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8a3d627-053f-4298-ac79-4a0c3c3d1f55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25036bcc-c32c-45ef-8197-8c0061ffc31e' class='xr-var-data-in' type='checkbox'><label for='data-25036bcc-c32c-45ef-8197-8c0061ffc31e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
+       "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
+       "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
+       "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
+       "       3.3772287, 3.3739138, 3.3298807, 3.368963 , 3.357279 , 3.3420138,\n",
+       "       3.3332636, 3.2887158, 3.3332634, 3.3267972, 3.3609293, 3.34788  ,\n",
+       "       3.3524635, 3.2797818, 3.2383478, 3.2774158, 3.3357968, 3.2894654,\n",
+       "       3.237099 , 3.2444148, 3.250231 , 3.3133483, 3.3285973, 3.3003979,\n",
+       "       3.3281136, 3.3106983, 3.2960656, 3.3239977, 3.3058155, 3.231132 ,\n",
+       "       3.2188826, 3.2362165, 3.2269833, 3.1857452, 3.2025456, 3.1971133,\n",
+       "       3.1716278, 3.1624265, 3.196963 , 3.1550453, 3.162944 , 3.158162 ,\n",
+       "       3.1250577, 3.1385927, 3.1210082, 3.1101758, 3.116926 , 3.1283762,\n",
+       "       3.1307604, 3.149876 , 3.1709106, 3.1579425, 3.157861 , 3.1293783,\n",
+       "       3.1623626, 3.0823452, 3.1290247, 3.1371257, 3.103561 , 3.0512455,\n",
+       "       3.0958426, 3.0634787, 3.061212 , 3.0691292, 3.0543785, 3.0647104,\n",
+       "       3.0809944, 3.1082118, 3.099077 , 3.1025605, 3.0808105, 3.070144 ,\n",
+       "       3.061945 , 3.0596778, 3.0728438, 3.0654464, 3.082978 , 3.0888774,\n",
+       "       3.090909 , 3.1166098, 3.1326916, 3.1294093, 3.1606429, 3.0821111,\n",
+       "       3.0704782, 3.099461 , 3.1288106, 3.0858114, 3.1094916, 3.1244771,\n",
+       "       3.0631604, 3.098195 , 3.0228472, 3.0709112, 3.0849445, 3.0772102,\n",
+       "       3.10411  , 3.0789108, 3.122175 , 3.0939767, 3.126108 , 3.1068432,\n",
+       "       3.1269426, 3.124676 , 3.133493 , 3.1521947, 3.1957629, 3.174427 ,\n",
+       "       3.1647441, 3.2137322, 3.1900635, 3.2544334, 3.2174487, 3.2122307,\n",
+       "       3.2605999, 3.244882 , 3.2509172, 3.234432 , 3.1874464, 3.200428 ,\n",
+       "       3.251467 , 3.2418153, 3.24985  , 3.3141315, 3.2959988, 3.2620163,\n",
+       "       3.2882996, 3.2601004, 3.2490656, 3.242116 , 3.2917488, 3.306215 ,\n",
+       "       3.3455298, 3.3139143, 3.274265 , 3.2986312, 3.2870982, 3.271833 ,\n",
+       "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
+       "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
+       "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
+       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-f62001ed-6467-4693-967f-e4902c176c26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f62001ed-6467-4693-967f-e4902c176c26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5929ec33-17f1-4434-97f7-63721111aae1' class='xr-var-data-in' type='checkbox'><label for='data-5929ec33-17f1-4434-97f7-63721111aae1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
+       "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
+       "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
+       "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
+       "       -0.04223333, -0.0388    , -0.05338333, -0.0568    , -0.0611    ,\n",
+       "       -0.0627    , -0.07021666, -0.05368333, -0.0487    , -0.0493    ,\n",
+       "       -0.05311666, -0.06443334, -0.04586667, -0.04441666, -0.04498333,\n",
+       "       -0.03575   , -0.03521667, -0.07056666, -0.07609999, -0.0662    ,\n",
+       "       -0.04191666, -0.06681666, -0.06818333, -0.07636666, -0.07111666,\n",
+       "       -0.05511666, -0.0493    , -0.05571667, -0.04891667, -0.04571667,\n",
+       "       -0.04198333, -0.00336667,  0.08048334,  0.25323334,  0.22161667,\n",
+       "        0.19196668,  0.15959999,  0.11676668,  0.09488333,  0.07456666,\n",
+       "        0.05981667,  0.06043334,  0.06175001,  0.05643333,  0.04858334,\n",
+       "        0.06248334,  0.06495   ,  0.07498333,  0.06741667,  0.07038333,\n",
+       "        0.06546666,  0.06541666,  0.06608333,  0.07325   ,  0.0566    ,\n",
+       "        0.054     ,  0.061     ,  0.0511    ,  0.05655   ,  0.02896667,\n",
+       "        0.02978333,  0.04755   ,  0.01526667,  0.00998333,  0.0108    ,\n",
+       "        0.00458333,  0.00831667,  0.00378333, -0.00401667, -0.00796667,\n",
+       "        0.00555   ,  0.01133333,  0.00541667, -0.0047    , -0.0019    ,\n",
+       "       -0.00158333, -0.01193333, -0.00146667, -0.00791667, -0.00841667,\n",
+       "       -0.00898333, -0.00903333, -0.002     ,  0.00205   ,  0.00393333,\n",
+       "       -0.00233333,  0.01098333, -0.01495   , -0.01253333,  0.0059    ,\n",
+       "        0.01675   , -0.0048    ,  0.00353333,  0.00155   , -0.01018333,\n",
+       "        0.00053333, -0.0111    , -0.01913333, -0.02155   , -0.02396666,\n",
+       "       -0.01793333, -0.02523333, -0.0194    , -0.02291666, -0.02203333,\n",
+       "       -0.0282    , -0.02571667, -0.03851666, -0.0208    , -0.03573333,\n",
+       "       -0.02388333, -0.03908334, -0.04381667, -0.031     , -0.04036666,\n",
+       "       -0.02826666, -0.04583333, -0.0394    , -0.03658333, -0.04336667,\n",
+       "       -0.04073333, -0.05656667, -0.0553    , -0.05688334, -0.04293333,\n",
+       "       -0.05556666, -0.05011667, -0.02433333, -0.03963333, -0.04716667,\n",
+       "       -0.05826667, -0.05943333, -0.06553333, -0.04911667, -0.04304999,\n",
+       "       -0.023     , -0.03935   , -0.03393333, -0.04798333, -0.05141667,\n",
+       "       -0.04823333, -0.05695   , -0.05431667, -0.07600001, -0.0419    ,\n",
+       "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
+       "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
+       "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
+       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-0629cd39-673d-4d21-998a-2ab00fc8783c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0629cd39-673d-4d21-998a-2ab00fc8783c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94dd308d-41fb-47db-887f-d873e67e2fa4' class='xr-var-data-in' type='checkbox'><label for='data-94dd308d-41fb-47db-887f-d873e67e2fa4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
+       "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
+       "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
+       "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
+       "       -7.3838835, -7.3748665, -7.3916   , -7.391783 , -7.3853164,\n",
+       "       -7.377949 , -7.3945003, -7.3738666, -7.373867 , -7.369084 ,\n",
+       "       -7.372767 , -7.3854327, -7.3678336, -7.3722672, -7.3625836,\n",
+       "       -7.3666334, -7.360083 , -7.3809   , -7.3875995, -7.3742666,\n",
+       "       -7.3516665, -7.369966 , -7.387017 , -7.386867 , -7.379284 ,\n",
+       "       -7.361167 , -7.3493667, -7.3615665, -7.344417 , -7.350366 ,\n",
+       "       -7.3399496, -7.300467 , -7.236433 , -7.0768504, -6.997516 ,\n",
+       "       -6.949867 , -6.899017 , -6.8814178, -6.8526497, -6.8263836,\n",
+       "       -6.813383 , -6.8076496, -6.78375  , -6.781251 , -6.7671165,\n",
+       "       -6.7577667, -6.7516494, -6.728033 , -6.72715  , -6.716767 ,\n",
+       "       -6.708234 , -6.69495  , -6.6866503, -6.6791   , -6.6603007,\n",
+       "       -6.659384 , -6.6542172, -6.659967 , -6.6461835, -6.667401 ,\n",
+       "       -6.6473837, -6.6366506, -6.6365337, -6.649917 , -6.6360173,\n",
+       "       -6.638784 , -6.6400666, -6.62885  , -6.628683 , -6.617567 ,\n",
+       "       -6.6096334, -6.59625  , -6.589217 , -6.5807333, -6.5850334,\n",
+       "       -6.5764165, -6.5684667, -6.5721836, -6.55585  , -6.5561   ,\n",
+       "       -6.5420327, -6.5459166, -6.5430665, -6.5388503, -6.5341506,\n",
+       "       -6.5321503, -6.52225  , -6.539833 , -6.5372   , -6.528584 ,\n",
+       "       -6.5262337, -6.5375338, -6.5275497, -6.51875  , -6.5324664,\n",
+       "       -6.525267 , -6.548233 , -6.5326   , -6.5178337, -6.5193667,\n",
+       "       -6.505567 , -6.5125165, -6.4989333, -6.508083 , -6.49675  ,\n",
+       "       -6.50315  , -6.4925   , -6.485383 , -6.492067 , -6.4811997,\n",
+       "       -6.4708   , -6.4739504, -6.472566 , -6.4622664, -6.4698668,\n",
+       "       -6.4504333, -6.4621997, -6.4667   , -6.45215  , -6.4554167,\n",
+       "       -6.454716 , -6.461316 , -6.4738665, -6.473217 , -6.458534 ,\n",
+       "       -6.46535  , -6.4565167, -6.4414663, -6.4526324, -6.4590497,\n",
+       "       -6.4487834, -6.4628167, -6.46505  , -6.4660163, -6.4543834,\n",
+       "       -6.4556837, -6.4339333, -6.443283 , -6.4565334, -6.4484835,\n",
+       "       -6.4508667, -6.4604836, -6.4581666, -6.4554834, -6.4470496,\n",
+       "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
+       "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
+       "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
+       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-f29e11ee-40ef-48ea-8152-093e958ca80e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f29e11ee-40ef-48ea-8152-093e958ca80e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43a2aeb-935a-406f-843a-629a2e3b816f' class='xr-var-data-in' type='checkbox'><label for='data-a43a2aeb-935a-406f-843a-629a2e3b816f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
+       "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
+       "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
+       "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
+       "       1023.23627, 1023.24646, 1023.2652 , 1023.2814 , 1023.2947 ,\n",
+       "       1023.3131 , 1023.32043, 1023.33435, 1023.3452 , 1023.3554 ,\n",
+       "       1023.3606 , 1023.366  , 1023.37103, 1023.37616, 1023.38043,\n",
+       "       1023.38403, 1023.3869 , 1023.3915 , 1023.38855, 1023.3802 ,\n",
+       "       1023.3759 , 1023.3691 , 1023.3694 , 1023.3698 , 1023.3653 ,\n",
+       "       1023.3579 , 1023.3548 , 1023.35455, 1023.3548 , 1023.35455,\n",
+       "       1023.3522 , 1023.3529 , 1023.3504 , 1023.3525 , 1023.3523 ,\n",
+       "       1023.3569 , 1023.35583, 1023.35565, 1023.35364, 1023.35455,\n",
+       "       1023.35675, 1023.3567 , 1023.35565, 1023.35364, 1023.35144,\n",
+       "       1023.3499 , 1023.3452 , 1023.347  , 1023.3427 , 1023.3374 ,\n",
+       "       1023.3326 , 1023.32874, 1023.3249 , 1023.3244 , 1023.3244 ,\n",
+       "       1023.3202 , 1023.3271 , 1023.32477, 1023.3281 , 1023.3215 ,\n",
+       "       1023.3281 , 1023.3284 , 1023.3283 , 1023.3299 , 1023.33887,\n",
+       "       1023.3277 , 1023.3379 , 1023.343  , 1023.33966, 1023.35315,\n",
+       "       1023.35333, 1023.34064, 1023.33875, 1023.33   , 1023.3218 ,\n",
+       "       1023.32404, 1023.32294, 1023.30853, 1023.3122 , 1023.3125 ,\n",
+       "       1023.3147 , 1023.3218 , 1023.32446, 1023.3674 , 1023.42395,\n",
+       "       1023.4842 , 1023.5248 , 1023.5321 , 1023.545  , 1023.555  ,\n",
+       "       1023.5453 , 1023.53784, 1023.5425 , 1023.5531 , 1023.56085,\n",
+       "       1023.5671 , 1023.5697 , 1023.5727 , 1023.5777 , 1023.5851 ,\n",
+       "       1023.598  , 1023.61127, 1023.61774, 1023.6253 , 1023.63873,\n",
+       "       1023.6415 , 1023.64105, 1023.6321 , 1023.6085 , 1023.58875,\n",
+       "       1023.55664, 1023.53424, 1023.4919 , 1023.4661 , 1023.4329 ,\n",
+       "       1023.4105 , 1023.3956 , 1023.38354, 1023.3727 , 1023.36206,\n",
+       "       1023.3528 , 1023.34467, 1023.34357, 1023.345  , 1023.34937,\n",
+       "       1023.34894, 1023.3448 , 1023.3418 , 1023.3417 , 1023.3436 ,\n",
+       "       1023.3458 , 1023.3482 , 1023.3505 , 1023.34937, 1023.348  ,\n",
+       "       1023.34607, 1023.3471 , 1023.3476 , 1023.3501 , 1023.3529 ,\n",
+       "       1023.35187, 1023.34894, 1023.3476 , 1023.3455 , 1023.3432 ,\n",
+       "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
+       "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
+       "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
+       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-a229de0a-42e4-4718-8da1-7173c1238db9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a229de0a-42e4-4718-8da1-7173c1238db9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27910dde-2db5-4d77-818f-4dad1e0be671' class='xr-var-data-in' type='checkbox'><label for='data-27910dde-2db5-4d77-818f-4dad1e0be671' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
+       "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
+       "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
+       "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
+       "        9.90408  ,  9.8704815,  9.843054 ,  9.8099   ,  9.782674 ,\n",
+       "        9.751141 ,  9.722181 ,  9.688391 ,  9.658139 ,  9.624396 ,\n",
+       "        9.591585 ,  9.559362 ,  9.5206785,  9.487036 ,  9.4516325,\n",
+       "        9.418625 ,  9.378983 ,  9.347703 ,  9.310125 ,  9.274782 ,\n",
+       "        9.240932 ,  9.203833 ,  9.168937 ,  9.127398 ,  9.091378 ,\n",
+       "        9.048801 ,  9.012082 ,  8.96804  ,  8.932783 ,  8.890241 ,\n",
+       "        8.854867 ,  8.815892 ,  8.781367 ,  8.746559 ,  8.714514 ,\n",
+       "        8.678216 ,  8.641088 ,  8.608247 ,  8.566862 ,  8.532115 ,\n",
+       "        8.495453 ,  8.461118 ,  8.42251  ,  8.39378  ,  8.36608  ,\n",
+       "        8.334696 ,  8.308269 ,  8.283072 ,  8.254289 ,  8.228873 ,\n",
+       "        8.203963 ,  8.179552 ,  8.162701 ,  8.144332 ,  8.124536 ,\n",
+       "        8.104092 ,  8.085614 ,  8.068075 ,  8.053603 ,  8.043172 ,\n",
+       "        8.025586 ,  8.014922 ,  8.00194  ,  7.9942083,  7.985075 ,\n",
+       "        7.9840665,  7.978806 ,  7.97339  ,  7.9731627,  7.971814 ,\n",
+       "        7.972329 ,  7.9674144,  7.9723177,  7.9744887,  7.9855638,\n",
+       "        7.991272 ,  7.9956956,  8.006041 ,  8.023605 ,  8.038973 ,\n",
+       "        8.049008 ,  8.066569 ,  8.078107 ,  8.090951 ,  8.110414 ,\n",
+       "        8.1288595,  8.1531725,  8.172004 ,  8.192166 ,  8.219532 ,\n",
+       "        8.241356 ,  8.265544 ,  8.288776 ,  8.314842 ,  8.338862 ,\n",
+       "        8.363347 ,  8.388729 ,  8.418659 ,  8.4457035,  8.479128 ,\n",
+       "        8.511397 ,  8.542225 ,  8.57435  ,  8.609074 ,  8.643846 ,\n",
+       "        8.674181 ,  8.707741 ,  8.740917 ,  8.776131 ,  8.809834 ,\n",
+       "        8.847663 ,  8.883326 ,  8.921983 ,  8.956591 ,  8.994466 ,\n",
+       "        9.032357 ,  9.072943 ,  9.107945 ,  9.147928 ,  9.18505  ,\n",
+       "        9.218539 ,  9.25671  ,  9.293107 ,  9.324933 ,  9.361722 ,\n",
+       "        9.397845 ,  9.436231 ,  9.464766 ,  9.502145 ,  9.534171 ,\n",
+       "        9.566268 ,  9.601108 ,  9.627889 ,  9.660232 ,  9.6932535,\n",
+       "        9.72142  ,  9.752015 ,  9.780852 ,  9.808266 ,  9.838272 ,\n",
+       "        9.864178 ,  9.885547 ,  9.914127 ,  9.934637 ,  9.957427 ,\n",
+       "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
+       "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
+       "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
+       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-7cc0e12c-ac1d-465f-b919-ff4396f1f4fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cc0e12c-ac1d-465f-b919-ff4396f1f4fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c229b4ba-1f27-4846-9eb7-379c42e5b345' class='xr-var-data-in' type='checkbox'><label for='data-c229b4ba-1f27-4846-9eb7-379c42e5b345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
+       "        0.04634431],\n",
+       "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
+       "        0.03873245],\n",
+       "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
+       "        0.04237254],\n",
+       "       ...,\n",
+       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+       "               nan],\n",
+       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+       "               nan],\n",
+       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+       "               nan]], shape=(28, 183), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ce677c8-4493-441f-8813-1154a1999004' class='xr-section-summary-in' type='checkbox'  ><label for='section-3ce677c8-4493-441f-8813-1154a1999004' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
       ],
-      "source": [
-        "import numpy as np\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "\n",
-        "plt.rcParams.update({\"font.size\": 18, \"font.family\": \"Times New Roman\"})\n",
-        "\n",
-        "\n",
-        "def plot_spectra_by_color(auto_spectra, U_mag, ax, fig, cbar_max=4.0):\n",
-        "    U = U_mag.values\n",
-        "    U_max = U_mag.max().values\n",
-        "\n",
-        "    # Average spectra into 0.1 m/s velocity bins\n",
-        "    speed_bins = np.arange(0.5, U_max, 0.1)\n",
-        "    time = [t for t in auto_spectra.dims if \"time\" in t][0]\n",
-        "    S_group = auto_spectra.assign_coords({time: U}).rename({time: \"speed\"})\n",
-        "    group = S_group.groupby_bins(\"speed\", speed_bins)\n",
-        "    count = group.count().values\n",
-        "    S = group.mean()\n",
-        "\n",
-        "    # define the colormap\n",
-        "    cmap = plt.cm.turbo\n",
-        "    # define the bins and normalize\n",
-        "    bounds = np.arange(0.5, cbar_max, 0.1)\n",
-        "    norm = mpl.colors.BoundaryNorm(bounds, cmap.N)\n",
-        "    colors = cmap(norm(speed_bins))\n",
-        "\n",
-        "    # plot\n",
-        "    for i in range(len(speed_bins) - 1):\n",
-        "        ax.loglog(auto_spectra[\"freq\"], S[i], c=colors[i])\n",
-        "    ax.grid()\n",
-        "\n",
-        "    # create a second axes for the colorbar\n",
-        "    cax = fig.add_axes([0.8, 0.07, 0.03, 0.88])\n",
-        "    # cax, _ = mpl.colorbar.make_axes(fig.gca())\n",
-        "    sm = mpl.colorbar.ColorbarBase(\n",
-        "        cax,\n",
-        "        cmap=cmap,\n",
-        "        norm=norm,\n",
-        "        spacing=\"proportional\",\n",
-        "        ticks=bounds,\n",
-        "        boundaries=bounds,\n",
-        "        format=\"%1.1f\",\n",
-        "        label=\"Velocity [m/s]\",\n",
-        "    )\n",
-        "\n",
-        "    # Add -5/3 slope line\n",
-        "    m = -5 / 3\n",
-        "    x = np.logspace(-1, 0.5)\n",
-        "    y = 10 ** (-3) * x**m\n",
-        "    ax.loglog(x, y, \"--\", c=\"black\", label=\"$f^{-5/3}$\")\n",
-        "    ax.legend()\n",
-        "\n",
-        "    return ax, sm\n",
-        "\n",
-        "\n",
-        "# Set up figure\n",
-        "fig, ax = plt.subplots(1, 1, figsize=(6, 5))\n",
-        "fig.subplots_adjust(left=0.2, right=0.75, top=0.95, bottom=0.1)\n",
-        "\n",
-        "# Plot spectra by color\n",
-        "plot_spectra_by_color(ds_avg[\"auto_spectra_5m\"], U, ax, fig, cbar_max=2.0)\n",
-        "# Set axes\n",
-        "ax.set(\n",
-        "    xlabel=\"Frequency [Hz]\",\n",
-        "    ylabel=\"PSD [m2 s-2 Hz-1]\",\n",
-        "    xlim=(0.01, 1),\n",
-        "    ylim=(0.0005, 0.1),\n",
-        ")"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance."
+      "text/plain": [
+       "<xarray.Dataset> Size: 379kB\n",
+       "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
+       "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
+       "Coordinates:\n",
+       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+       "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
+       "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
+       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * beam            (beam) int32 16B 1 2 3 4\n",
+       "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * q               (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+       "Data variables: (12/38)\n",
+       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+       "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
+       "    ...              ...\n",
+       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+       "Attributes: (12/41)\n",
+       "    fs:                        1\n",
+       "    n_bin:                     300\n",
+       "    n_fft:                     300\n",
+       "    description:               Binned averages calculated from ensembles of s...\n",
+       "    filehead_config:           {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"...\n",
+       "    inst_model:                Signature1000\n",
+       "    ...                        ...\n",
+       "    has_imu:                   1\n",
+       "    beam_angle:                25\n",
+       "    range_offset:              0.6\n",
+       "    declination:               15.8\n",
+       "    declination_in_orientmat:  1\n",
+       "    principal_heading:         11.1898"
       ]
-    },
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_avg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.3 Instrument Noise\n",
-        "\n",
-        "The next thing we want to do is calculate the instrument's Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
-        "\n",
-        "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8."
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1200 with 4 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vel = ds_avg[\"vel\"]\n",
+    "\n",
+    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+    "labels = vel.coords[vel_dim].values\n",
+    "\n",
+    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
+    "\n",
+    "if len(labels) == 1:\n",
+    "    axes = [axes]\n",
+    "\n",
+    "for ax_i, label in zip(axes, labels):\n",
+    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+    "    values = values[np.isfinite(values)]\n",
+    "\n",
+    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+    "    ax_i.set_ylabel(\"Count\")\n",
+    "\n",
+    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 24,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "ds_avg[\"noise_5m\"] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra_5m\"], pct_fN=0.9)"
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x400 with 6 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+    "\n",
+    "for i, ax in enumerate(axes):\n",
+    "    ds_avg[\"vel\"][i].plot(ax=ax)\n",
+    "    ax.set_title(ds_avg[\"vel\"].coords[\"dir\"].values[i])\n",
+    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+    "\n",
+    "plt.tight_layout()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. Calculate Speed and Direction\n",
+    "\n",
+    "Two additional variables that might be of interest, which are not automatically provided, are the magnitude of the horizontal velocity (referred to as `U_mag` or speed) and its direction (`U_dir`). These can be accessed via \"shortcut\" functions through the keyword `velds`, as demonstrated in the subsequent code block.\n",
+    "\n",
+    "For a comprehensive list of these \"shortcut\" functions, you can refer to the [DOLfYN documentation](https://dolfyn.readthedocs.io/en/latest/apidoc/dolfyn.shortcuts.html)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "ds_avg[\"U_mag\"] = ds_avg.velds.U_mag\n",
+    "ds_avg[\"U_dir\"] = ds_avg.velds.U_dir"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plotting"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plotting can be accomplished through the user's preferred package. Matplotlib is shown here for simplicity, and flow speed and direction are plotted below with a blue line delineating the water surface level."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.4 TKE Dissipation Rate\n",
-        "\n",
-        "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, the frequency range of the isotropic cascade, and the instrument's noise."
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar at 0x249c4fdac30>"
       ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "code",
-      "execution_count": 25,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "# Frequency range of isotropic turubulence cascade in same units as PSD frequency vector\n",
-        "f_rng = [0.1, 0.5]\n",
-        "# Dissipation rate\n",
-        "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
-        "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
-        ")"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "from matplotlib import pyplot as plt\n",
+    "import matplotlib.dates as dt\n",
+    "\n",
+    "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
+    "# Plot flow speed\n",
+    "t = dolfyn.time.dt642date(ds_avg[\"time\"])\n",
+    "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_mag\"], cmap=\"Blues\", shading=\"nearest\")\n",
+    "# Plot the water surface\n",
+    "ax.plot(t, ds_avg[\"depth\"])\n",
+    "\n",
+    "# Set up time on x-axis\n",
+    "ax.set_xlabel(\"Time\")\n",
+    "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
+    "ax.lines[-1].set_label(\"Water surface\")\n",
+    "ax.legend(loc=\"upper right\")\n",
+    "ax.set_ylabel(\"Altitude [m]\")\n",
+    "ax.set_ylim([0, 12])\n",
+    "plt.colorbar(label=\"Speed [m/s]\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "We have just found the spectra and dissipation rate from a single depth bin at an altitude of 5 m from the seafloor, but typically we want the spectra and dissipation rates from the entire measurement profile. If we want to look at the spectra and dissipation rates from all depth bins, we can set up a \"for\" loop on the range coordinate and merge them together:"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
+    "# Plot flow direction\n",
+    "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_dir\"], cmap=\"twilight\", shading=\"nearest\")\n",
+    "# Plot the water surface\n",
+    "ax.plot(t, ds_avg[\"depth\"])\n",
+    "\n",
+    "# set up time on x-axis\n",
+    "ax.set_xlabel(\"Time\")\n",
+    "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
+    "\n",
+    "ax.set_ylabel(\"Altitude [m]\")\n",
+    "ax.set_ylim([0, 12])\n",
+    "plt.colorbar(label=\"Horizontal Vel Dir [deg CW from true N]\");"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Saving and Loading DOLfYN datasets\n",
+    "Datasets can be saved and reloaded using the `save` and `load` functions. Xarray is saved natively in netCDF format, hence the \".nc\" extension.\n",
+    "\n",
+    "Note: DOLfYN datasets cannot be saved using xarray's native `ds.to_netcdf`; however, DOLfYN datasets can be opened using `xarray.open_dataset`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Uncomment these lines to save and load to your current working directory\n",
+    "# dolfyn.save(ds, 'your_data.nc')\n",
+    "# ds_saved = dolfyn.load('your_data.nc')"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 7. Turbulence Statistics\n",
+    "\n",
+    "The next section of this jupyter notebook will run through the turbulence analysis of the data presented here. There was no intention of measuring turbulence in the deployment that collected this data, so results depicted here are not the highest quality. The quality of turbulence measurements from an ADCP depend heavily on the quality of the deployment setup and data collection, particularly instrument frequency, samping frequency and depth bin size.\n",
+    "\n",
+    "Read more on proper ADCP setup for turbulence measurements in: Thomson, Jim, et al. \"Measurements of turbulence at two tidal energy sites in Puget Sound, WA.\" IEEE Journal of Oceanic Engineering 37.3 (2012): 363-374.\n",
+    "\n",
+    "Most functions related to turbulence statistics in MHKiT-DOLfYN have the papers they originate from referenced in their docstrings.\n",
+    "\n",
+    "### 7.1 Turbulence Intensity\n",
+    "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this can be simply calculated as `<raw dataset>.velds.I`, but be aware that this will be a conservative estimate. Another function, `turbulence_intensity`, is capable of subtracting instrument noise from this parameter and is discussed below. The noise-subtracted TI is more accurate and typically 1-2% lower than the non-noise-subtracted estimation.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 26,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "import xarray as xr\n",
-        "\n",
-        "spec = [None] * len(ds.range)\n",
-        "e = [None] * len(ds.range)\n",
-        "n = [None] * len(ds.range)\n",
-        "\n",
-        "for r in range(len(ds[\"range\"])):\n",
-        "    # Calc spectra from each depth bin using the 5th beam\n",
-        "    spec[r] = avg_tool.power_spectral_density(\n",
-        "        ds[\"vel_b5\"].isel(range_b5=r), freq_units=\"Hz\"\n",
-        "    )\n",
-        "    \n",
-        "    # Calculate doppler noise from spectra from each depth bin\n",
-        "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
-        "    \n",
-        "    # Calc dissipation rate from each spectra\n",
-        "    e[r] = avg_tool.dissipation_rate_LT83(\n",
-        "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
-        "    )\n",
-        "\n",
-        "ds_avg[\"auto_spectra\"] = xr.concat(spec, dim=\"range\")\n",
-        "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
-        "ds_avg[\"dissipation_rate\"] = xr.concat(e, dim=\"range\")\n",
-        "\n",
-        "del spec, n, e  # save memory"
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x249daa0dd30>"
       ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "Now that we have a profile timeseries of dissipation rate, we need apply some quality control (QC). Since we can't look at each individual spectrum to ensure we can see the isotropic turbulence cascade, we want to QC the output from `dissipation_rate_LT83` to make sure what was calculated actually falls on a f^(-5/3) slope. We can do this using the function `check_turbulence_cascade_slope`, which uses linear regression on the log-transformed LT83 equation (ref. to Lumley and Terray, 1983, see docstring) to calculate the spectral slope for the given frequency range. \n",
-        "\n",
-        "In our case, we're calculating the slope of each spectrum between 0.2 and 0.5 Hz. We'll use a cutoff of 20% for the error, but this can be lowered if there still appear to be erroneous estimations from visual inspection of the spectra."
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Turbulence Intensity\n",
+    "ds_avg[\"TI\"] = ds_avg.velds.I\n",
+    "ds_avg[\"TI\"].plot(cmap=\"Reds\", ylim=(0, 11))"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.2 Power Spectral Densities (Auto-Spectra)\n",
+    "\n",
+    "Other turbulence parameters include the TKE power- and cross-spectral densities (i.e the power spectra), turbulent kinetic energy (TKE, i.e. the variances of velocity vector components), Reynolds stress vector (i.e. the co-variances of velocity vector components), TKE dissipation rate, and TKE production rate. These quantities are primarily used to inform and verify hydrodynamic and coastal models, which take some or all of these quantities as input.\n",
+    "\n",
+    "The TKE production rate is the rate at which kinetic energy (KE) transitions from a useful state (able to do \"work\" in the physics sense) to turbulent; TKE is the actual amount of turbulent KE in the water; and TKE dissipation rate is the rate at which turbulent KE is lost to non-motion forms of energy (heat, sound, etc) due to viscosity. The power spectra are used to depict and quantify this energy in the frequency domain, and creating them are the first step in turbulence analysis.\n",
+    "\n",
+    "We'll start by looking at the power spectra, specifically the auto-spectra from the vertical beam (\"auto\" meaning the variance of a single vector direction, e.g. $\\overline{u'^2}$, vs \"cross\", meaning the covariance of two directions, e.g. $\\overline{u'w'}$). This can be done using the `power_spectral_density` function from the `ADPBinner` we created (\"avg_tool\"). We'll create spectra at the middle water column, at a depth of 5 m, and use a number of FFT's equal to 1/3 the bin size."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rng = 5  # m\n",
+    "vel_up = ds[\"vel_b5\"].sel(range_b5=rng, method=\"nearest\")  # vertical velocity\n",
+    "U = ds_avg[\"U_mag\"].sel(\n",
+    "    range=5, method=\"nearest\"\n",
+    ")  # flow speed, for plotting in the next block\n",
+    "\n",
+    "ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n",
+    "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 2\n",
+    ")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the auto-spectra, we're primarly looking for three components: the energy-producing region, the isotropic turbulence region (so-called \"red noise\"), and the instrument noise floor (termed \"white noise\"). \n",
+    "\n",
+    "The block below organizes and plots the power spectra by the corresponding ensemble speed, averaging them by 0.1 m/s velocity bins. Note that if an ensemble is missing data that wasn't filled in, a power spectrum will not be calculated for that ensemble timestamp."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 27,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "# Quality control dissipation rate estimation\n",
-        "slope = avg_tool.check_turbulence_cascade_slope(\n",
-        "    ds_avg[\"auto_spectra\"], freq_range=f_rng\n",
-        ")\n",
-        "\n",
-        "# Check that percent difference from -5/3 is not greater than 20%\n",
-        "mask = abs((slope[0].values - (-5 / 3)) / (-5 / 3)) <= 0.20\n",
-        "\n",
-        "# Keep good data\n",
-        "ds_avg[\"dissipation_rate\"] = ds_avg[\"dissipation_rate\"].where(mask)"
+     "data": {
+      "text/plain": [
+       "[Text(0.5, 0, 'Frequency [Hz]'),\n",
+       " Text(0, 0.5, 'PSD [m2 s-2 Hz-1]'),\n",
+       " (0.01, 1),\n",
+       " (0.0005, 0.1)]"
       ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "If we plot the dissipation rate below in a colormap, we can see that the profile map has a lot of missing data. One of the reasons is that the 1 Hz sampling rate doesn't provide enough information needed to make dissipation rate estimations, and the other part is that turbulence measurements push the boundaries of what ADCPs are capable of.\n",
-        "\n",
-        "Also, 1x10^-4 to 3x10^-4 $m^2/s^3$ is reasonable for a dissipation rate estimate for the 1 - 1.5 m/s current speeds measured here. They can be a magnitude greater for faster flow speeds, typically increase closer to the seafloor, and depend heavily on bathymetry and regional hydrodynamics."
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "\n",
+    "plt.rcParams.update({\"font.size\": 18, \"font.family\": \"Times New Roman\"})\n",
+    "\n",
+    "\n",
+    "def plot_spectra_by_color(auto_spectra, U_mag, ax, fig, cbar_max=4.0):\n",
+    "    U = U_mag.values\n",
+    "    U_max = U_mag.max().values\n",
+    "\n",
+    "    # Average spectra into 0.1 m/s velocity bins\n",
+    "    speed_bins = np.arange(0.5, U_max, 0.1)\n",
+    "    time = [t for t in auto_spectra.dims if \"time\" in t][0]\n",
+    "    S_group = auto_spectra.assign_coords({time: U}).rename({time: \"speed\"})\n",
+    "    group = S_group.groupby_bins(\"speed\", speed_bins)\n",
+    "    count = group.count().values\n",
+    "    S = group.mean()\n",
+    "\n",
+    "    # define the colormap\n",
+    "    cmap = plt.cm.turbo\n",
+    "    # define the bins and normalize\n",
+    "    bounds = np.arange(0.5, cbar_max, 0.1)\n",
+    "    norm = mpl.colors.BoundaryNorm(bounds, cmap.N)\n",
+    "    colors = cmap(norm(speed_bins))\n",
+    "\n",
+    "    # plot\n",
+    "    for i in range(len(speed_bins) - 1):\n",
+    "        ax.loglog(auto_spectra[\"freq\"], S[i], c=colors[i])\n",
+    "    ax.grid()\n",
+    "\n",
+    "    # create a second axes for the colorbar\n",
+    "    cax = fig.add_axes([0.8, 0.07, 0.03, 0.88])\n",
+    "    # cax, _ = mpl.colorbar.make_axes(fig.gca())\n",
+    "    sm = mpl.colorbar.ColorbarBase(\n",
+    "        cax,\n",
+    "        cmap=cmap,\n",
+    "        norm=norm,\n",
+    "        spacing=\"proportional\",\n",
+    "        ticks=bounds,\n",
+    "        boundaries=bounds,\n",
+    "        format=\"%1.1f\",\n",
+    "        label=\"Velocity [m/s]\",\n",
+    "    )\n",
+    "\n",
+    "    # Add -5/3 slope line\n",
+    "    m = -5 / 3\n",
+    "    x = np.logspace(-1, 0.5)\n",
+    "    y = 10 ** (-3) * x**m\n",
+    "    ax.loglog(x, y, \"--\", c=\"black\", label=\"$f^{-5/3}$\")\n",
+    "    ax.legend()\n",
+    "\n",
+    "    return ax, sm\n",
+    "\n",
+    "\n",
+    "# Set up figure\n",
+    "fig, ax = plt.subplots(1, 1, figsize=(6, 5))\n",
+    "fig.subplots_adjust(left=0.2, right=0.75, top=0.95, bottom=0.1)\n",
+    "\n",
+    "# Plot spectra by color\n",
+    "plot_spectra_by_color(ds_avg[\"auto_spectra_5m\"], U, ax, fig, cbar_max=2.0)\n",
+    "# Set axes\n",
+    "ax.set(\n",
+    "    xlabel=\"Frequency [Hz]\",\n",
+    "    ylabel=\"PSD [m2 s-2 Hz-1]\",\n",
+    "    xlim=(0.01, 1),\n",
+    "    ylim=(0.0005, 0.1),\n",
+    ")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.3 Instrument Noise\n",
+    "\n",
+    "The next thing we want to do is calculate the instrument's Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
+    "\n",
+    "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 28,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x25a30084250>"
-            ]
-          },
-          "execution_count": 28,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Statistic</th>\n",
+       "      <th>Value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>mean</td>\n",
+       "      <td>0.024059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>std</td>\n",
+       "      <td>0.007032</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>min</td>\n",
+       "      <td>0.013010</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>max</td>\n",
+       "      <td>0.046780</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
       ],
-      "source": [
-        "ds_avg[\"dissipation_rate\"].plot(cmap=\"turbo\", ylim=(0, 11))"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.5 Noise-Corrected Turbulence Intensity\n",
-        "\n",
-        "Now that we've calculated the noise floor for each ping, we can recalculate TI and include subtracting instrument noise using the `turbulence_intensity` function. If we subtract this from the non-noise corrected function, we can see there's a large difference\n",
-        "at slower slow speeds, but the average difference is about 0.008 (0.8%). Notice this will also remove measurements where noise is \n",
-        "high."
+      "text/plain": [
+       "  Statistic     Value\n",
+       "0      mean  0.024059\n",
+       "1       std  0.007032\n",
+       "2       min  0.013010\n",
+       "3       max  0.046780"
       ]
-    },
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_avg[\"noise_5m\"] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra_5m\"], pct_fN=0.9)\n",
+    "\n",
+    "noise_stats = pd.DataFrame({\n",
+    "    \"Statistic\": [\"mean\", \"std\", \"min\", \"max\"],\n",
+    "    \"Value\": [\n",
+    "        float(ds_avg[\"noise_5m\"].mean().values),\n",
+    "        float(ds_avg[\"noise_5m\"].std().values),\n",
+    "        float(ds_avg[\"noise_5m\"].min().values),\n",
+    "        float(ds_avg[\"noise_5m\"].max().values),\n",
+    "    ]\n",
+    "})\n",
+    "\n",
+    "noise_stats\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.4 TKE Dissipation Rate\n",
+    "\n",
+    "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, the frequency range of the isotropic cascade, and the instrument's noise."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Frequency range of isotropic turubulence cascade in same units as PSD frequency vector\n",
+    "f_rng = [0.1, 0.5]\n",
+    "# Dissipation rate\n",
+    "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
+    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We have just found the spectra and dissipation rate from a single depth bin at an altitude of 5 m from the seafloor, but typically we want the spectra and dissipation rates from the entire measurement profile. If we want to look at the spectra and dissipation rates from all depth bins, we can set up a \"for\" loop on the range coordinate and merge them together:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "\n",
+    "spec = [None] * len(ds.range)\n",
+    "e = [None] * len(ds.range)\n",
+    "n = [None] * len(ds.range)\n",
+    "\n",
+    "for r in range(len(ds[\"range\"])):\n",
+    "    # Calc spectra from each depth bin using the 5th beam\n",
+    "    spec[r] = avg_tool.power_spectral_density(\n",
+    "        ds[\"vel_b5\"].isel(range_b5=r), freq_units=\"Hz\"\n",
+    "    )\n",
+    "    \n",
+    "    # Calculate doppler noise from spectra from each depth bin\n",
+    "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
+    "    \n",
+    "    # Calc dissipation rate from each spectra\n",
+    "    e[r] = avg_tool.dissipation_rate_LT83(\n",
+    "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
+    "    )\n",
+    "\n",
+    "ds_avg[\"auto_spectra\"] = xr.concat(spec, dim=\"range\")\n",
+    "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
+    "ds_avg[\"dissipation_rate\"] = xr.concat(e, dim=\"range\")\n",
+    "\n",
+    "del spec, n, e  # save memory"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have a profile timeseries of dissipation rate, we need apply some quality control (QC). Since we can't look at each individual spectrum to ensure we can see the isotropic turbulence cascade, we want to QC the output from `dissipation_rate_LT83` to make sure what was calculated actually falls on a f^(-5/3) slope. We can do this using the function `check_turbulence_cascade_slope`, which uses linear regression on the log-transformed LT83 equation (ref. to Lumley and Terray, 1983, see docstring) to calculate the spectral slope for the given frequency range. \n",
+    "\n",
+    "In our case, we're calculating the slope of each spectrum between 0.2 and 0.5 Hz. We'll use a cutoff of 20% for the error, but this can be lowered if there still appear to be erroneous estimations from visual inspection of the spectra."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Quality control dissipation rate estimation\n",
+    "slope = avg_tool.check_turbulence_cascade_slope(\n",
+    "    ds_avg[\"auto_spectra\"], freq_range=f_rng\n",
+    ")\n",
+    "\n",
+    "# Check that percent difference from -5/3 is not greater than 20%\n",
+    "mask = abs((slope[0].values - (-5 / 3)) / (-5 / 3)) <= 0.20\n",
+    "\n",
+    "# Keep good data\n",
+    "ds_avg[\"dissipation_rate\"] = ds_avg[\"dissipation_rate\"].where(mask)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we plot the dissipation rate below in a colormap, we can see that the profile map has a lot of missing data. One of the reasons is that the 1 Hz sampling rate doesn't provide enough information needed to make dissipation rate estimations, and the other part is that turbulence measurements push the boundaries of what ADCPs are capable of.\n",
+    "\n",
+    "Also, 1x10^-4 to 3x10^-4 $m^2/s^3$ is reasonable for a dissipation rate estimate for the 1 - 1.5 m/s current speeds measured here. They can be a magnitude greater for faster flow speeds, typically increase closer to the seafloor, and depend heavily on bathymetry and regional hydrodynamics."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 29,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'TI Difference')"
-            ]
-          },
-          "execution_count": 29,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
-        "\n",
-        "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
-        "plt.title(\"TI Difference\")"
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x249c4a40f50>"
       ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.6 Reynolds Stress Components\n",
-        "\n",
-        "The next parameters we'll find here are the Reynolds normal and shear stresses (-$\\overline{u_iu_j}$). Since we're using the vertical beam on the ADCP, we can directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
-        "\n",
-        "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the normal and shear stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. \n",
-        "\n",
-        "Both of these functions will give comparable results, but `stress_tensor_5beam` takes into account instrument tilt, and `stress_tensor_4beam` does not. Both will throw a tilt warning if tilt is greater than 5 degrees.\n",
-        "\n",
-        "#### Quick 5-beam ADCP lesson before we dive in:\n",
-        "\n",
-        "There are a couple caveats to calculating Reynolds stress tensor components:\n",
-        "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unknowns, 5 knowns)\n",
-        "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
-        "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly (\"coupled ADCPs\")\n",
-        "  4. Measurements close to the seafloor can be suspect due to increased vertical flow. ADCPs operate under the \"assumption of homogeneity\", which means that they can only accurate measure consistent horizontal currents with relatively little vertical motion.\n"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_avg[\"dissipation_rate\"].plot(cmap=\"turbo\", ylim=(0, 11))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.5 Noise-Corrected Turbulence Intensity\n",
+    "\n",
+    "Now that we've calculated the noise floor for each ping, we can recalculate TI and include subtracting instrument noise using the `turbulence_intensity` function. If we subtract this from the non-noise corrected function, we can see there's a large difference\n",
+    "at slower slow speeds, but the average difference is about 0.008 (0.8%). Notice this will also remove measurements where noise is \n",
+    "high."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "As an example, we'll calculate the Reynolds stresses from the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs: the raw dataset in \"beam\" coordinates, the instrument Doppler noise, the ADCP's orientation and its beam angle. It outputs both the normal stress (\"tke_vec\") and the shear stress (\"stress_vec\") vector. Note, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically."
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'TI Difference')"
       ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "code",
-      "execution_count": 30,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\adp\\turbulence.py:422: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
-            "  warnings.warn(\n"
-          ]
-        }
-      ],
-      "source": [
-        "dolfyn.rotate2(ds, \"beam\", inplace=True)\n",
-        "ds_avg[\"tke_vec\"], ds_avg[\"stress_vec\"] = avg_tool.stress_tensor_5beam(\n",
-        "    ds, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
-        ")"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
       ]
-    },
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
+    "\n",
+    "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
+    "plt.title(\"TI Difference\")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.6 Reynolds Stress Components\n",
+    "\n",
+    "The next parameters we'll find here are the Reynolds normal and shear stresses (-$\\overline{u_iu_j}$). Since we're using the vertical beam on the ADCP, we can directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
+    "\n",
+    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the normal and shear stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. \n",
+    "\n",
+    "Both of these functions will give comparable results, but `stress_tensor_5beam` takes into account instrument tilt, and `stress_tensor_4beam` does not. Both will throw a tilt warning if tilt is greater than 5 degrees.\n",
+    "\n",
+    "#### Quick 5-beam ADCP lesson before we dive in:\n",
+    "\n",
+    "There are a couple caveats to calculating Reynolds stress tensor components:\n",
+    "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unknowns, 5 knowns)\n",
+    "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
+    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly (\"coupled ADCPs\")\n",
+    "  4. Measurements close to the seafloor can be suspect due to increased vertical flow. ADCPs operate under the \"assumption of homogeneity\", which means that they can only accurate measure consistent horizontal currents with relatively little vertical motion.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As an example, we'll calculate the Reynolds stresses from the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs: the raw dataset in \"beam\" coordinates, the instrument Doppler noise, the ADCP's orientation and its beam angle. It outputs both the normal stress (\"tke_vec\") and the shear stress (\"stress_vec\") vector. Note, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "There is one other important thing to note on Reynolds stress measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the stress transported by larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue, though on its own it may not be particularly useful."
-      ]
-    },
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\dolfyn\\adp\\turbulence.py:407: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "dolfyn.rotate2(ds, \"beam\", inplace=True)\n",
+    "ds_avg[\"tke_vec\"], ds_avg[\"stress_vec\"] = avg_tool.stress_tensor_5beam(\n",
+    "    ds, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is one other important thing to note on Reynolds stress measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the stress transported by larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue, though on its own it may not be particularly useful."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.7 TKE Production\n",
+    "\n",
+    "Though it can't be found from this deployment, we'll go over how to estimate the TKE shear production rate. Note that we're assuming here that the buoyancy production is negligible and we're in a well-mixed tidal channel. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
+    "\n",
+    "It is possible to estimate production rates from either an ADV or an ADCP aligned with the flow direction (so \"X\" would align with the principal flow direction). The following estimation for shear production rates takes into account both along- and cross-stream shear:\n",
+    "\n",
+    "$P = -\\overline{u'w'}\\frac{du}{dz} - \\overline{v'w'}\\frac{dv}{dz}$\n",
+    "\n",
+    "Note that the signs can get tricky but are important here. We found the Reynolds shear stresses -$\\overline{u'w'}$ and -$\\overline{v'w'}$ above using the Reynolds stress equations. If ADV data is available, those estimations are preferred because the ADV's point measurement does not have the assumptions that ADCP measurements have.\n",
+    "\n",
+    "The velocity shear components can be found from the aptly named functions `dudz` and `dvdz` in ADPBinner. These functions, which are useful alone in their own right, approximate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"approximate\" is also used here for velocity shear.\n",
+    "\n",
+    "The velocity shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation. If using ADV data, take the mean again of the \"range\" dimension."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.7 TKE Production\n",
-        "\n",
-        "Though it can't be found from this deployment, we'll go over how to estimate the TKE shear production rate. Note that we're assuming here that the buoyancy production is negligible and we're in a well-mixed tidal channel. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
-        "\n",
-        "It is possible to estimate production rates from either an ADV or an ADCP aligned with the flow direction (so \"X\" would align with the principal flow direction). The following estimation for shear production rates takes into account both along- and cross-stream shear:\n",
-        "\n",
-        "$P = -\\overline{u'w'}\\frac{du}{dz} - \\overline{v'w'}\\frac{dv}{dz}$\n",
-        "\n",
-        "Note that the signs can get tricky but are important here. We found the Reynolds shear stresses -$\\overline{u'w'}$ and -$\\overline{v'w'}$ above using the Reynolds stress equations. If ADV data is available, those estimations are preferred because the ADV's point measurement does not have the assumptions that ADCP measurements have.\n",
-        "\n",
-        "The velocity shear components can be found from the aptly named functions `dudz` and `dvdz` in ADPBinner. These functions, which are useful alone in their own right, approximate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"approximate\" is also used here for velocity shear.\n",
-        "\n",
-        "The velocity shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation. If using ADV data, take the mean again of the \"range\" dimension."
-      ]
-    },
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Vertical shear gradients\n",
+    "upwp_ = ds_avg[\"stress_vec\"][1]\n",
+    "vpwp_ = ds_avg[\"stress_vec\"][2]\n",
+    "\n",
+    "# Find shear velocity and and ensemble-average it\n",
+    "ds.velds.rotate2(\"principal\", inplace=True)\n",
+    "dudz_raw = avg_tool.dudz(ds[\"vel\"], orientation=\"up\")\n",
+    "dudz = avg_tool.mean(dudz_raw.values)\n",
+    "\n",
+    "dvdz_raw = avg_tool.dvdz(ds[\"vel\"], orientation=\"up\")\n",
+    "dvdz = avg_tool.mean(dvdz_raw.values)\n",
+    "\n",
+    "# Calculate Production\n",
+    "P = -upwp_ * dudz - vpwp_ * dvdz\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 7.8 TKE Balance \n",
+    "We can plot the production rates and the ratio of production rates to dissipation rates to get an understanding of the TKE balance.We always expect production to be greater than 0, though negative values can give us an indication of uncertainty. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates are possibly high because our stress components aren't aligned with the flow (1.3x10^-3 $m^2/s^3$ is quite large), but if this weren't the case, we would conclude that TKE is produced (kinetic energy is lost to turbulence) but not dissipated (turbulent energy is lost to entropy) here."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
     {
-      "cell_type": "code",
-      "execution_count": 31,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
-            "  warnings.warn(\n"
-          ]
-        }
-      ],
-      "source": [
-        "# Vertical shear gradients\n",
-        "upwp_ = ds_avg[\"stress_vec\"][1]\n",
-        "vpwp_ = ds_avg[\"stress_vec\"][2]\n",
-        "\n",
-        "# Find shear velocity and and ensemble-average it\n",
-        "ds.velds.rotate2(\"principal\", inplace=True)\n",
-        "dudz_raw = avg_tool.dudz(ds[\"vel\"], orientation=\"up\")\n",
-        "dudz = avg_tool.mean(dudz_raw.values)\n",
-        "\n",
-        "dvdz_raw = avg_tool.dvdz(ds[\"vel\"], orientation=\"up\")\n",
-        "dvdz = avg_tool.mean(dvdz_raw.values)\n",
-        "\n",
-        "# Calculate Production\n",
-        "P = -upwp_ * dudz - vpwp_ * dvdz\n"
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'TKE Balance')"
       ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
     },
     {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "### 7.8 TKE Balance \n",
-        "We can plot the production rates and the ratio of production rates to dissipation rates to get an understanding of the TKE balance.We always expect production to be greater than 0, though negative values can give us an indication of uncertainty. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates are possibly high because our stress components aren't aligned with the flow (1.3x10^-3 $m^2/s^3$ is quite large), but if this weren't the case, we would conclude that TKE is produced (kinetic energy is lost to turbulence) but not dissipated (turbulent energy is lost to entropy) here."
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
       ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-      "cell_type": "code",
-      "execution_count": 32,
-      "metadata": {},
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "Text(0.5, 1.0, 'TKE Balance')"
-            ]
-          },
-          "execution_count": 32,
-          "metadata": {},
-          "output_type": "execute_result"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 2 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "# Remove estimations below 0\n",
-        "P = P.where(P > 0)\n",
-        "# Plot production rate\n",
-        "P.plot(cmap=\"turbo\", ylim=(0, 11))\n",
-        "plt.title(\"TKE Production\")  # remove bogus title\n",
-        "\n",
-        "\n",
-        "# Plot difference between production and dissipation rate\n",
-        "plt.figure()\n",
-        "balance = P - ds_avg[\"dissipation_rate\"].values\n",
-        "balance.plot(ylim=(0, 11))\n",
-        "plt.title(\"TKE Balance\")"
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
       ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": []
-    }
-  ],
-  "metadata": {
-    "kernelspec": {
-      "display_name": "work",
-      "language": "python",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.11.10"
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
+   ],
+   "source": [
+    "# Remove estimations below 0\n",
+    "P = P.where(P > 0)\n",
+    "# Plot production rate\n",
+    "P.plot(cmap=\"turbo\", ylim=(0, 11))\n",
+    "plt.title(\"TKE Production\")  # remove bogus title\n",
+    "\n",
+    "\n",
+    "# Plot difference between production and dissipation rate\n",
+    "plt.figure()\n",
+    "balance = P - ds_avg[\"dissipation_rate\"].values\n",
+    "balance.plot(ylim=(0, 11))\n",
+    "plt.title(\"TKE Balance\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Updated_MHKiT",
+   "language": "python",
+   "name": "python3"
   },
-  "nbformat": 4,
-  "nbformat_minor": 4
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
 }
diff --git a/mhkit/river/io/d3d.py b/mhkit/river/io/d3d.py
index ac0f49f73..ce4d99f95 100644
--- a/mhkit/river/io/d3d.py
+++ b/mhkit/river/io/d3d.py
@@ -388,7 +388,7 @@ def get_layer_data(
     elif isinstance(data, xr.Dataset):
         layer_percentages = cord_sys.values  # accumulative
 
-    if layer_dim == "FlowLink_xu FlowLink_yu":
+    if layer_dim in ("FlowLink_xu FlowLink_yu", "mesh2d_edge_x mesh2d_edge_y"):
         # interpolate
         if isinstance(data, netCDF4.Dataset):
             x_laydim = np.ma.getdata(data.variables[coords[0]][:], False)
@@ -421,13 +421,13 @@ def get_layer_data(
     waterdepth = []
 
     if dimensions == 2:
-        if layer_dim == "FlowLink_xu FlowLink_yu":
+        if layer_dim in ("FlowLink_xu FlowLink_yu", "mesh2d_edge_x mesh2d_edge_y"):
             z = [bottom_depth_wdim]
             waterlevel = water_level_wdim
         else:
             z = [bottom_depth]
     else:
-        if layer_dim == "FlowLink_xu FlowLink_yu":
+        if layer_dim in ("FlowLink_xu FlowLink_yu", "mesh2d_edge_x mesh2d_edge_y"):
             z = [bottom_depth_wdim * layer_percentages[layer_index]]
             waterlevel = water_level_wdim
         else:
@@ -651,6 +651,17 @@ def variable_interpolation(
     if not isinstance(to_pandas, bool):
         raise TypeError(f"to_pandas must be of type bool. Got: {type(to_pandas)}")
 
+    # Avoid Quhall errors by filling in bad sigma values
+    if "mesh2d_interface_sigma" in data.variables:
+        sigma = data["mesh2d_interface_sigma"].values
+        sigma = np.clip(sigma, -1.0, 0.0)
+
+        data["mesh2d_interface_sigma"] = xr.DataArray(
+            sigma,
+            dims=data["mesh2d_interface_sigma"].dims,
+            attrs=data["mesh2d_interface_sigma"].attrs,
+        )
+
     data_raw = {}
     for var in variables:
         var_data_df = get_all_data_points(data, var, time_index=-1, to_pandas=True)

From 272e2a05918f56fae991b7c8fa207f8ad2524038 Mon Sep 17 00:00:00 2001
From: James McVey <james.mcvey@pnnl.gov>
Date: Mon, 29 Jun 2026 14:05:20 -0700
Subject: [PATCH 7/9] Update Acoustics Module (#447)

Enhancements:
- Adds ability to convert sound spectral densities to millidecade format
(https://doi.org/10.1121/10.0003324)
- Adds reader for WISPR (Wideband Intelligent Signal Processing and
Recording) system for hydrophones
- Updates the export_audio function to input voltage timeseries and
allow resampling to speed up recordings

Bugfixes
- Refactors band-averaging for spectral density levels and sound
pressure levels. This refactor avoids losing information at frequencies
located at band boundaries, and conducts all of the band-averaging
immediately after the PSD calculation.

The jupyter notebook has been updated with these changes as well.
---
 examples/acoustics_example.ipynb              | 390 +++++----
 .../data/acoustics/WISPR_230825_003936.dat    | Bin 0 -> 29990912 bytes
 mhkit/acoustics/__init__.py                   |   8 +
 mhkit/acoustics/analysis.py                   | 779 ++++++++++--------
 mhkit/acoustics/io.py                         | 243 +++++-
 mhkit/acoustics/spl.py                        | 111 +--
 mhkit/acoustics/spsdl.py                      | 462 +++++++++++
 mhkit/tests/acoustics/test_analysis.py        | 134 ++-
 mhkit/tests/acoustics/test_io.py              |  56 +-
 mhkit/tests/acoustics/test_metrics.py         |  75 +-
 10 files changed, 1662 insertions(+), 596 deletions(-)
 create mode 100644 examples/data/acoustics/WISPR_230825_003936.dat
 create mode 100644 mhkit/acoustics/spsdl.py

diff --git a/examples/acoustics_example.ipynb b/examples/acoustics_example.ipynb
index 0b53d6670..fc3101bac 100644
--- a/examples/acoustics_example.ipynb
+++ b/examples/acoustics_example.ipynb
@@ -56,12 +56,13 @@
      "text": [
       "<xarray.DataArray (time: 30720000)> Size: 246MB\n",
       "array([0.31546374, 0.30229832, 0.32229963, ..., 0.08506887, 0.07291618,\n",
-      "       0.06278893])\n",
+      "       0.06278893], shape=(30720000,))\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 246MB 2024-06-01T05:31:14 ... 2024-06-01T0...\n",
       "Attributes:\n",
       "    units:        Pa\n",
       "    sensitivity:  1.413e-09\n",
+      "    gain:         0\n",
       "    resolution:   9.89e-07\n",
       "    valid_min:    -2123.837353\n",
       "    valid_max:    2123.837353\n",
@@ -72,13 +73,13 @@
    ],
    "source": [
     "P = acoustics.io.read_hydrophone(\n",
-    "    \"data/acoustics/RBW_6661_20240601_053114.wav\", \n",
-    "    peak_voltage=3, \n",
-    "    sensitivity=-177, \n",
-    "    gain=0, \n",
+    "    \"data/acoustics/RBW_6661_20240601_053114.wav\",\n",
+    "    peak_voltage=3,\n",
+    "    sensitivity=-177,\n",
+    "    gain=0,\n",
     "    start_time=\"2024-06-01T05:31:14\"\n",
     ")\n",
-    "# `P` is returned as an xarray DataArray, which allows easy handling of labeled multi-dimensional arrays. \n",
+    "# `P` is returned as an xarray DataArray, which allows easy handling of labeled multi-dimensional arrays.\n",
     "# In this case, the array represents sound pressure in Pascals (Pa) over time because the calibrated sensitivity was passed.\n",
     "print(P)"
    ]
@@ -98,14 +99,23 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\io.py:460: UserWarning: no explicit representation of timezones available for np.datetime64\n",
+      "  start_time = np.datetime64(metadata[\"icrd\"])\n"
+     ]
+    }
+   ],
    "source": [
     "# Pressure output\n",
     "P = acoustics.io.read_iclisten(\"data/acoustics/RBW_6661_20240601_053114.wav\")\n",
     "# Voltage output\n",
     "V = acoustics.io.read_iclisten(\n",
-    "    \"data/acoustics/RBW_6661_20240601_053114.wav\", \n",
-    "    sensitivity=None, \n",
+    "    \"data/acoustics/RBW_6661_20240601_053114.wav\",\n",
+    "    sensitivity=None,\n",
     "    use_metadata=False\n",
     ")"
    ]
@@ -123,8 +133,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "P = acoustics.io.read_soundtrap(\"data/acoustics/6247.230204150508.wav\", sensitivity=-177)\n",
-    "V = acoustics.io.read_soundtrap(\"data/acoustics/6247.230204150508.wav\", sensitivity=None)"
+    "P = acoustics.io.read_soundtrap(\"data/acoustics/6247.230204150508.wav\", sensitivity=-177, gain=0)\n",
+    "V = acoustics.io.read_soundtrap(\"data/acoustics/6247.230204150508.wav\", sensitivity=None, gain=0)"
    ]
   },
   {
@@ -192,6 +202,8 @@
     "    return calibration[\"Analog Sensitivity\"]\n",
     "\n",
     "sensitivity_curve = read_calibration_file(\"data/acoustics/6247_calibration.csv\")\n",
+    "# Add gain if any\n",
+    "sensitivity_curve = sensitivity_curve + V.attrs[\"gain\"]\n",
     "print(sensitivity_curve)"
    ]
   },
@@ -254,7 +266,11 @@
      "output_type": "stream",
      "text": [
       "<xarray.DataArray 'freq' ()> Size: 8B\n",
-      "array(48000.)\n"
+      "array(48000.)\n",
+      "Attributes:\n",
+      "    units:                  Hz\n",
+      "    long_name:              FFT Frequency Vector\n",
+      "    coverage_content_type:  coordinate\n"
      ]
     }
    ],
@@ -284,7 +300,7 @@
     "fmax = 48000\n",
     "\n",
     "# Create high resolution spectrogram\n",
-    "kwargs={\"cmap\": \"inferno\", \"vmin\": 0, \"vmax\": 100}\n",
+    "kwargs = {\"cmap\": \"inferno\", \"vmin\": 0, \"vmax\": 100}\n",
     "fig, ax = acoustics.graphics.plot_spectrogram(\n",
     "    spsdl, fmin, fmax, **kwargs\n",
     ")\n",
@@ -310,7 +326,7 @@
    "source": [
     "# Uncomment to save new file\n",
     "filename = \"sound1.wav\"\n",
-    "#acoustics.io.export_audio(filename, P, gain=1)"
+    "# acoustics.io.export_audio(filename, P, gain=1, resample_multiplier=1)"
    ]
   },
   {
@@ -342,7 +358,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -381,9 +397,30 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Window Aggregating\n",
+    "### Window Averaging\n",
+    "\n",
+    "If desired, one can do a couple different types of time-averaging the SPSDLs, though this isn't required by the IEC-40. There are two main supported functions in MHKiT, `time_average` and `time_summation`, which both take the SPSDL and a time window as inputs\n",
     "\n",
-    "If desired, one can group a series of measurements into blocks of time, though this isn't required by the IEC-40. In the following block, we'll take our 5 minutes of measurements, `time_aggregate` them into 30 second intervals, and find the median, 25% and 75% quantiles of each interval. We then plot the stats of the median parameters."
+    "`time_average` finds returns the spectral average of the SPSDLs in each specified window. This is useful for say, finding the average 30 second SPSDL every hour. In this case, the original SPSD bin_length was 30 seconds, and the time window to input to `time_average` is 1 hour.\n",
+    "\n",
+    "`time_summation` returns the spectral sum of the SPSDLs in each specified window. This is equivalent to recalculating the SPSDs for a new bin_length. For example:\n",
+    "\n",
+    "```python\n",
+    "spsd = acoustics.sound_pressure_spectral_density(V, fs=V.fs, bin_length=1, fft_length=V.fs)\n",
+    "spsdl = acoustics.sound_pressure_spectral_density_level(spsd)\n",
+    "spsdl_30 = acoustics.time_summation(spsdl, window=30)\n",
+    "```\n",
+    "\n",
+    "is equivalent to\n",
+    "\n",
+    "```python\n",
+    "spsd_30 = acoustics.sound_pressure_spectral_density(V, fs=V.fs, bin_length=30, fft_length=V.fs)\n",
+    "spsdl_30 = acoustics.sound_pressure_spectral_density_level(spsd_30)\n",
+    "```\n",
+    "\n",
+    "But, note that error will be introduced in the former because of memory rounding errors.\n",
+    "\n",
+    "In the following block, we'll take our 5 minutes of 1-second resolution data and find the average SPSDL in every 30 second window using the `time_average` function."
    ]
   },
   {
@@ -392,16 +429,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "\n",
     "# Time average into 30 s windows and take the median parameter value\n",
     "window = 30\n",
-    "spsdl_time = acoustics.time_aggregate(spsdl, window, method=\"median\")"
+    "spsdl_30s = acoustics.time_average(spsdl, window)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can then using the `plot_spectra` function in the graphics submodule to plot the median and quantiles of the first 30 s window."
+    "We can then using the `plot_spectra` function in the graphics submodule to plot the median and quantiles of the 30 s window averages."
    ]
   },
   {
@@ -422,7 +460,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -433,11 +471,11 @@
    ],
    "source": [
     "# Plot medians and quantiles\n",
-    "fig, ax = acoustics.graphics.plot_spectra(spsdl_time.median(\"time_bins\"), fmin, fmax, label=\"Median\")\n",
+    "fig, ax = acoustics.graphics.plot_spectra(spsdl_30s.median(\"time_bins\"), fmin, fmax, label=\"Median\")\n",
     "ax.fill_between(\n",
-    "    spsdl_time[\"freq\"],\n",
-    "    spsdl_time.quantile(0.25, \"time_bins\"),\n",
-    "    spsdl_time.quantile(0.75, \"time_bins\"),\n",
+    "    spsdl_30s[\"freq\"],\n",
+    "    spsdl_30s.quantile(0.25, \"time_bins\"),\n",
+    "    spsdl_30s.quantile(0.75, \"time_bins\"),\n",
     "    alpha=0.5,\n",
     "    facecolor=\"C0\",\n",
     "    edgecolor=None,\n",
@@ -455,9 +493,13 @@
    "source": [
     "### Frequency Band Analysis\n",
     "\n",
-    "Frequency band analysis can be completed by grouping the data into specific frequency bands, called \"band aggregating\" here. In other words, instead of aggregating by the time dimension, we aggregate by the frequency dimension. The `band_aggregate` function operates by taking the SPSDL and grouping it based on a specified octave and octave base.\n",
+    "Frequency band analysis can be completed by grouping the data into specific frequency bands, which we can do by taking the SPSD and grouping it based on a specified octave and octave base. There are a number of built in functions to convert the SPSDs to specified bands, notably:\n",
+    "1. Third octaves (band = 3, bands per division = 2) (`convert_to_third_octave(spsd)`)\n",
+    "2. Decidecades (band = 10, bands per division = 10) (`convert_to_decidecade(spsd)`)\n",
+    "3. Millidecades (band = 10, bands per division = 1000)  (`convert_to_millidecade(spsd)`)\n",
+    "4. Custom bandwidth (`convert_to_custom_band(spsd, band, bands_per_division)`)\n",
     "\n",
-    "In the following codeblock, we use the same plotting function as above, but do so by creating the decidecade frequency bands (10th octave, octave base 10 => $10^{1/10}$). We'll calculate the median and quantiles of each sample, then take the median of each of those parameters. For the IEC-40, one will calculate these parameters for each device operating state (current energy converters) or wave state matrix (wave energy converters)."
+    "In the following codeblock, we create the decidecade frequency bands (10th octave, octave base 10 => $10^{1/10}$) and then plot using the same graphics function as before, displaying the median and quantiles of the dataset. For the IEC-40, one will calculate these parameters for each device operating state (current energy converters) or wave state matrix (wave energy converters)."
    ]
   },
   {
@@ -466,91 +508,42 @@
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "[(20.0, 80.0), Text(0, 0.5, 'Decidecade SPSDL [dB rel 1 uPa$^2$/Hz]')]"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:96: UserWarning: `fmax` = 48000 is greater than the Nyquist frequency. Settingfmax = 39810.71705534977\n",
+      "  warnings.warn(\n"
+     ]
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 600x500 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "octave = [10, 10]  # [octave, octave base]\n",
-    "spsdl10 = acoustics.band_aggregate(spsdl, octave, fmin, fmax, method=\"median\")\n",
-    "\n",
-    "# Plot medians and quantiles\n",
-    "fig, ax = acoustics.graphics.plot_spectra(spsdl10.median(\"time\"), fmin, fmax, label=\"Median\")\n",
-    "ax.fill_between(\n",
-    "    spsdl10[\"freq_bins\"],\n",
-    "    spsdl10.quantile(0.25, \"time\"),\n",
-    "    spsdl10.quantile(0.75, \"time\"),\n",
-    "    alpha=0.5,\n",
-    "    facecolor=\"C0\",\n",
-    "    edgecolor=None,\n",
-    "    label=\"Quantiles\"\n",
-    ")\n",
-    "ax.legend(loc=\"upper right\")\n",
-    "ax.set_axisbelow(True)\n",
-    "ax.grid()\n",
-    "ax.set(ylim=(20, 80), ylabel=\"Decidecade SPSDL [dB rel 1 uPa$^2$/Hz]\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The plot above shows significant spread in sound measurements at higher frequency due to the vessel noise, but less so at lower frequency. This mirrors what we can see in the sound pressure density level figure we first plotted.\n",
-    "\n",
-    "Boxplots for each frequency band can also be created instead of simple line plots. We can use the aggregate methods to apply plotting functions, like matplotlib's native boxplot. In this case, we'll supply the \"map\" function and an iterable of the custom function inputs (the figure axes we want to use to plot)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x24648eb2b50>,\n",
-       "  <matplotlib.axis.XTick at 0x246000ac350>,\n",
-       "  <matplotlib.axis.XTick at 0x246000752d0>,\n",
-       "  <matplotlib.axis.XTick at 0x24601842f90>,\n",
-       "  <matplotlib.axis.XTick at 0x24601ce0e10>,\n",
-       "  <matplotlib.axis.XTick at 0x24606034f90>],\n",
+       "[[<matplotlib.axis.XTick at 0x238f3fa2910>,\n",
+       "  <matplotlib.axis.XTick at 0x238f619e4d0>,\n",
+       "  <matplotlib.axis.XTick at 0x238f6132590>,\n",
+       "  <matplotlib.axis.XTick at 0x238f5710250>,\n",
+       "  <matplotlib.axis.XTick at 0x238f638b290>,\n",
+       "  <matplotlib.axis.XTick at 0x238f6395350>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
        "  Text(3.0, 0, '3'),\n",
        "  Text(4.0, 0, '4'),\n",
        "  Text(5.0, 0, '5')],\n",
-       " (1.0, 4.8),\n",
+       " (1.6532125137753437, 4.7160033436347994),\n",
        " (20.0, 100.0),\n",
-       " Text(0.5, 0, 'log(Frequency) [Hz]'),\n",
-       " Text(0, 0.5, 'Decidecade SPSDL [dB re 1 uPa$^2$/Hz]')]"
+       " Text(0.5, 0, 'log(Frequency) [Hz]')]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
-       "<Figure size 700x500 with 1 Axes>"
+       "<Figure size 1000x400 with 2 Axes>"
       ]
      },
      "metadata": {},
@@ -558,33 +551,42 @@
     }
    ],
    "source": [
-    "def boxplot(x, ax):\n",
-    "    # Use the median of the coordinate we're grouped in\n",
-    "    freq = x[\"freq\"].median()\n",
-    "    x = x.mean(\"freq\")\n",
-    "    # Create boxplots\n",
-    "    ax.boxplot(\n",
-    "        x.values,\n",
-    "        whis=(1, 99),\n",
-    "        showfliers=False,\n",
-    "        positions=[np.log10(freq.values)],\n",
-    "        widths=0.04,\n",
-    "        flierprops={\"marker\": \".\", \"markersize\": 2},\n",
-    "    )\n",
-    "    return x\n",
+    "decidecade_spsd = acoustics.convert_to_decidecade(spsd)\n",
+    "decidecade_spsdl = acoustics.sound_pressure_spectral_density_level(decidecade_spsd)\n",
     "\n",
-    "fig, ax = plt.subplots(figsize=(7, 5))\n",
-    "acoustics.band_aggregate(\n",
-    "    spsdl, octave, fmin, fmax, method={\"map\": (boxplot, [ax])}\n",
+    "# Plot medians and quantiles\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
+    "fig, ax[0] = acoustics.graphics.plot_spectra(decidecade_spsdl.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
+    "ax[0].fill_between(\n",
+    "    decidecade_spsdl[\"freq\"],\n",
+    "    decidecade_spsdl.quantile(0.25, \"time\"),\n",
+    "    decidecade_spsdl.quantile(0.75, \"time\"),\n",
+    "    alpha=0.5,\n",
+    "    facecolor=\"C0\",\n",
+    "    edgecolor=None,\n",
+    "    label=\"Quantiles\"\n",
+    ")\n",
+    "ax[0].legend(loc=\"upper right\")\n",
+    "ax[0].set_axisbelow(True)\n",
+    "ax[0].grid()\n",
+    "ax[0].set(ylim=(20, 100), ylabel=\"Decidecade SPSDL [dB rel 1 uPa$^2$/Hz]\", xscale=\"log\")\n",
+    "\n",
+    "# Boxplots\n",
+    "ax[1].boxplot(\n",
+    "    decidecade_spsdl.values,\n",
+    "    whis=(1, 99),\n",
+    "    showfliers=True,\n",
+    "    positions=np.log10(decidecade_spsdl[\"freq\"].values),\n",
+    "    widths=0.04,\n",
+    "    flierprops={\"marker\": \".\", \"markersize\": 1.5},\n",
     ")\n",
     "xticks = np.linspace(0, 5, 6)\n",
-    "ax.set(\n",
+    "ax[1].set(\n",
     "    xticks=xticks,\n",
     "    xticklabels=xticks.astype(int),\n",
-    "    xlim=(1, 4.8),\n",
+    "    xlim=(np.log10(45), np.log10(52000)),\n",
     "    ylim=(20, 100),\n",
     "    xlabel=\"log(Frequency) [Hz]\",\n",
-    "    ylabel=\"Decidecade SPSDL [dB re 1 uPa$^2$/Hz]\",\n",
     ")"
    ]
   },
@@ -592,12 +594,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The \"map\" function will also allow one to conduct further frequency band analysis than the simple statistical methods that xarray offers. In the following block of code, we find the empirical quantile function (the empirical version of the cumulative distribution function, CDF) of each decidecade frequency band and plot the decidecade band centered nearest to 160 Hz. "
+    "The plot above shows significant spread in sound measurements at higher frequency due to the vessel noise, but less so at lower frequency. This mirrors what we can see in the sound pressure density level figure we first plotted."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The built-in python `map` and the xarray `groupby` function also allow one to conduct further frequency band analysis than the simple statistical methods that xarray offers. In the following block of code, we find the empirical quantile function (the empirical version of the cumulative distribution function, CDF) of each decidecade frequency band and plot the decidecade band nearest to 160 Hz. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -608,13 +617,13 @@
        " Text(0.5, 0, 'SPSDL [dB re 1 uPa$^2$/Hz]')]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 400x400 with 1 Axes>"
       ]
@@ -638,19 +647,73 @@
     "    x.values = np.reshape(x_sorted, shape)\n",
     "    return x\n",
     "\n",
-    "\n",
-    "octave = [10, 10]  # 1/10th octave at base 10\n",
-    "cdfs = acoustics.band_aggregate(spsdl, octave, fmin, fmax, method={\"map\": quantile_function})\n",
+    "# Calculate CDFs for each frequency bin by grouping by frequency and applying the quantile function\n",
+    "cdfs = decidecade_spsdl.groupby(\"freq\").map(quantile_function)\n",
     "# Plot\n",
     "fig, ax = plt.subplots(figsize=(4, 4))\n",
-    "ax.plot(cdfs.sel(freq_bins=160, method=\"nearest\").values, cdfs[\"probability\"].values)\n",
+    "ax.plot(cdfs.sel(freq=160, method=\"nearest\").values, cdfs[\"probability\"].values)\n",
     "ax.set(\n",
-    "    title=f\"{np.round(cdfs['freq_bins'].sel(freq_bins=160, method='nearest').values, 2)} Hz\",\n",
+    "    title=f\"{np.round(cdfs['freq'].sel(freq=160, method='nearest').values, 2)} Hz\",\n",
     "    ylabel=\"Exceedance Probability\",\n",
     "    xlabel=\"SPSDL [dB re 1 uPa$^2$/Hz]\",\n",
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above chart says that in the band centered at 158.5 Hz, the spectral density levels are above 62 dB re 1 uPa2/Hz for 50% of the time."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Millidecade Bands\n",
+    "It is becoming best practice to store passive acoustic data long-term in millidecade bands. These bands preserve resolution at low frequencies and effectively compresses data at high frequencies. See \"Martin et al 2021 - Hybrid millidecade spectra, a practical format for exchange of long-term ambient sound data\" for more details.\n",
+    "\n",
+    "To do this, we convert the SPSDs to the millidecade band using `convert_to_millidecade` after calibrating the original 1 second SPSDs. Note any bin_length of time can be used, depending on your storage capacity. If we plot the millidecade SPSDLs, there is little visual difference between the original resolution SPSDL plotted above. In this case, the noise is reduced because of the band-averaging."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:96: UserWarning: `fmax` = 48000 is greater than the Nyquist frequency. Settingfmax = 47973.34486365695\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "millidecade_spsd = acoustics.convert_to_millidecade(spsd)\n",
+    "millidecade_spsdl = acoustics.sound_pressure_spectral_density_level(millidecade_spsd)\n",
+    "\n",
+    "# Create high resolution spectrogram\n",
+    "kwargs = {\"cmap\": \"inferno\", \"vmin\": 0, \"vmax\": 100}\n",
+    "fig, ax = acoustics.graphics.plot_spectrogram(\n",
+    "    millidecade_spsdl, fmin, fmax, **kwargs\n",
+    ")\n",
+    "ax.xaxis.set_major_formatter(mdates.DateFormatter(\"%H:%M:%S\"))\n",
+    "ax.xaxis.set_major_locator(mdates.MinuteLocator(interval=2))\n",
+    "ax.xaxis.set_minor_locator(mdates.MinuteLocator())"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -711,7 +774,7 @@
     "\n",
     "#### Cumulative SPL\n",
     "\n",
-    "Running the code block below, we can see our cumulative SPL start out at 86 dB and then peak at 125 dB as the boat drives by. If you haven't listened to the audio track, this peak SPL of 125 dB rel 1 uPa (underwater) is equivalent to 99 dB rel 20 uPa (air). For reference, the OSHA time limit for workers experiencing 100 dB rel 20 uPa of sound is 2 hours. Vessel traffic can be quite loud and is one of the largest contributors to noise in the marine environment."
+    "Running the code block below, we can see our cumulative SPL start out at 86 dB and then peak at 125 dB as the boat drives by. For a relevant comparison to in-air sound, this peak SPL of 125 dB rel 1 uPa (underwater) is equivalent to 99 dB rel 20 uPa (air). For reference, the OSHA time limit for workers experiencing 100 dB rel 20 uPa of sound is 2 hours. Vessel traffic can be quite loud and is one of the largest contributors to noise in the marine environment."
    ]
   },
   {
@@ -722,7 +785,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x24601c66a90>]"
+       "[<matplotlib.lines.Line2D at 0x238f69c8410>]"
       ]
      },
      "execution_count": 19,
@@ -731,7 +794,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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SC5O5u+SqW3OqkxVLql677mKhee+BEOYmCZMQQhgpq6icIk2l4bn5u+SqWpisIWFykxYm0TxIwiSEEEa6fMA3QHq+eVtXsgqru+QsN+C7mmGmXIEkTKJpk4RJCCGMlFTVHeflbA9YoEuuqLpLzrxLodSmeqbchQLpkhNNmyRMQghhpKSqGkx9WvoA+i4yTaX5ptVfLNTPkrOqFibpkhNNnCRMQghhpOoZcl3DvFBXTauf9vk+3t182izvn1VkPYO+/dxlDJNoHiRhEkIII1UnTJG+LgR56FtYdp/N5o318Rw9n9/g73+x0DrKCsClQd8yS040dZIwCSGEERRF4VxV0cpIH2dDxe1qb29qmFamA+dy2Z2QTaVWZ1UtTNVdctnF5VRqdXUcLUTjJQmTEEIYIae4nEJNJSoVhHk7M75LMABjOgaiUsH64xc4nlZg0vcsq9By32d7uOfTv/h6bzKaSh1ezvaG1i1L8nFxwNZGhaJcqkAuRFNksoTp0KFD2Nramup0Qghhlaq744I9nHC0t+Wfw1vxyz/6896UboxsFwjAb0fTTfqex9LyKSnXolPgxV9OADCmYxB2tpb/zmtjc6nat8yUE02ZSf+1KYpiytMJIYTVqV5DLsLHGQBHe1vaB3ugUqno3cIbgBPppm1hOpx6aVxUeaW+22tc52CTvseNCPLUt3SdzSqycCRCNJx6r9o4YcKEa+7Pz89HpVLdcEBCCGHNLh/w/Xftgj0ATN4ld3nCBBDo7kjPSG+TvseN6BnpzcHkPHYnZHN711BLhyNEg6h3C9P//vc/ysrK8PDwqPXh6urakHEKIYRVqC5aGVnVwnS5NkFuAKTll5FXYrrxPIdS8wAY0MoPgIk9w7CxsZ4vqNX1qHaeyZaeBtFk1buFqW3bttxxxx08+OCDte6Pi4vj559/NllgQghhjaqXRYnwubKFyd3RnjBvJ1JySjmeXkDflr43/H6FZRWcvah/zzcndiazQEPrQLcbPq8p3RTpjZ2NivN5paTklBJeSzIpRGNX7xam7t27Exsbe9X9arWa8PBwkwQlhBDWSFEUEquqfEfV0iUH0C7IHTBdt9yRqrpOIZ5O+LqqaRfsjq0VtS4BuKjt6BruCcDOhCzLBiNEA6l3C9OHH36IVnv10v9t27YlMTHRJEEJIYQ1yi4up7CsEoBw79pbUdoFefDHsQscN9HA7+rxS51CPUxyvobSt6Uv+5Jy+WT7WcorddzbO8LqEjshbkS9W5jUajXOztLMKoRovt6pKkoZ7e+Ko33tZVTaBZu2hWnP2WwAukd4meR8DWV4uwBUKjibVcyCn46x4XiGpUMSwqQsX8RDCCGs3In0ApZujOeL3ecAWDC23VWPrU6YzmQWUVZxYwvyVmh17E3MAS4NrLZWHUI82Dx7EKM76GtR/X5UEibRtDTqhGn79u2MHTuW4OBgVCoV69atq7F/zZo1jBw5El9fX1QqFXFxcVecY9CgQahUqhqPyZMnm+cChBBWLyWnhFve/pOlG/WtS/f1juDmGL+rHh/s4Yi3iwOVOoWTGYU39N6HU/MpLtfi6WxP20D3GzqXOUT5uvBA/ygANp/MpEKWShFNSKNOmIqLi+ncuTPvvvvuVff369ePV1555ZrnmTFjBunp6YbHRx991BDhCiEaob2JOegUfSK0YGw7nr/16q1LACqVio4h+vFGR6rKAVyv3VUDqPu08LGqMgLX0i3cCx8XBwrKKg2tY0I0BfUe9G2NRo8ezejRo6+6/7777gMgKSnpmudxdnYmMDCw3u+r0WjQaDSG5wUFpi1SJ4SwHoerkp7RHYOY3i+qXq/pHOrBtviLVxScNNauBP34pb5W3h13OVsbFUPb+vPd/lQ2HL9Av+gbL60ghDW47hamM2fO8Mcff1BaWgo07mVRVq1aha+vL+3bt2fOnDkUFl67GX3x4sU1inaGhYWZKVIhhLnFXccstY6hnsClkgDX40xmIfuTcgHrH7/0d0PbBgCw44yUGBBNh9EJU3Z2NsOGDaNVq1aMGTOG9HT9IpMPPfQQs2fPNnmADe2ee+7h66+/ZuvWrTz//POsXr26zmVg5s+fT35+vuGRkpJipmiFEOZUXqnjRNVst85VSVB9VCdX8RcKKSmvNPp9izSVPLLiAOVaHX1b+tDSr3GtpNChqksyKatYxjGJJsPohOmf//wndnZ2JCcn1ygzMGnSJH7//XeTBmcOM2bMYNiwYXTo0IHJkyfzww8/sHHjxjqLdLq7u9d4CCGanlMZhZRrdXg42RsW262PAHdHAtzV6JTrKy+wfGciCReLCXR35K3JXRvdOp3BHo64ONhSqVMMldGFaOyMTpjWr1/Pq6++SmhozQUWY2JiOHfunMkCs5Ru3bphb2/P6dOnLR2KEMLCqtdw6xTqYXTS0jHEE4DY5Fyj37e6K++hm6Pwc1Mb/XpLU6lUtPTXt4qdvlBk4WiEMA2jE6bi4uJaC1hmZWWhVje+f9h/d+zYMSoqKggKCrJ0KEIICztSNX7JmO64agNa6Qc7/3I4vc5jFUVBq7s0DvRMpj7JaBVgXWvGGSO6KmGqvhYhGjujE6YBAwbw5ZdfGp6rVCp0Oh2vv/46gwcPNmlwdSkqKiIuLs5QXykxMZG4uDiSk5MByMnJIS4ujuPHjwNw6tQp4uLiyMjQF1RLSEhg0aJF7N+/n6SkJH799VfuuusuunbtSr9+/cx6LUII63MuR9+dFBNg/BiiMR2DsLVRcSg137D+XG0qtDpGv/UnY9/ZQXmljgqtjnPZJQCGVprGKMZfn+ydloRJNBFGlxV4/fXXGTRoEPv376e8vJy5c+dy7NgxcnJy2LlzZ0PEeFX79++vkaTNmjULgKlTp7J8+XJ++uknpk+fbthfXZBywYIFLFy4EAcHBzZt2sRbb71FUVERYWFh3HLLLSxYsABb29qXPRBCNB8XC/XlQ/zdHI1+ra+rmv7RvmyLv8i6g+f55/BWtR4Xf6HQUODy58NpdAr1pFKn4OxgS7CH8e9rLapbmCRhEk2F0QlTu3btOHz4MB988AG2trYUFxczYcIEHn/8cbN3Yw0aNOia5QymTZvGtGnTrro/LCyMbdu2NUBkQoimoDphut5xRLd1DdYnTHHneWpoTK3FJ49eVnrgsx2JPDkkBoCWfq6NbrD35WKqEqazF4vQ6hRZiFc0ekYlTBUVFYwYMYKPPvqIF154oaFiEkIIiyur0FJQpi8JcL0J04h2gbipj3Euu4St8ZkMaRNwxTFHz1+aRXcsrYBVe/STZ6IbcXccQJi3Mw52NmgqdaTmlhDh42LpkIS4IUaNYbK3t+fo0aON+luPEELUR1aRvnXJwc4Gd8frWxTBRW3H3b3CAfh4+9laj6meEVfd/fbnaX2xx5Z+jTvBsLVRGepHnUi/sTX1hLAGRg/6vv/++/nss88aIhYhhLAahu44V/UNfUmc1jcSOxsVf53NMcy6q1ap1XEiXd/C9PpdnXGwu/SR3NhbmAC6hnsCsCcx27KBCGECRn9tKi8v59NPP2XDhg306NEDF5ea34LefPNNkwUnhBCWcqPjl6oFezpxa6cg1sWl8cmfZ3n77q7odApzVx/mZEYBmkodrmo7+rTwYVrfSENLVFNImPq19OWrPcnsOiMJk2j8jE6Yjh49Srdu3QCIj4+vsU+66oQQTcXFItMkTAAP3dyCdXFp/HIknWdGtyGnqJwfDqQa9rcKcMXGRsXjg6L5+VAaNjaqJjHmp3oNvFMXCsksLLuu2YZCWAujE6YtW7Y0RBxCCGFVTNXCBPq11fq29GFXQjbLdiTi5eJQY3+PSG8APJztWT9rILYqFfa21702utXwdnGgXZA7x9ML2J2QzfguIZYOSYjr1vj/RQohRAO4fAyTKcwY0AKAr/cmG6p/P9Q/iicGR/NQ/yjDca5qO5wcmk4duH7R+lamnWeyLByJEDdGEiYhhKiFKVuYAAa18qNdkDvF5VqOVw30vr9PJHNGtsbfvel2VfWL1i8R8+fprGvWzRPC2knCJIQQtTDlGCbQj/GcPeJSte9IH2fCfa5cl7Op6d3CB0d7G9LzywwVzYVojCRhEkKIWpi6hQlgSBt/uoR5AnBzjJ/JzmvNHO1t6ddS38q0+WSmhaMR4vpJwiSEEH+jKIrJxzCBvpXpzYmduadXOE8MiTbZea3dkLb+AGw6ccHCkQhx/YyeJZednY2Pj34QX0pKCp988gmlpaWMGzeOm2++2eQBCiGEuRVqKtFU6gDTtjABtPBz5aXbO5r0nNZuSBt9wnQwJY+sIg2+JkxChTCXercwHTlyhMjISPz9/WnTpg1xcXH07NmTJUuW8PHHHzN48GDWrVvXgKEKIYR5VLcuuTna4WjfdGasWUqQhxPtg91RFJj40W5OZhTU/SIhrEy9E6a5c+fSsWNHtm3bxqBBg7j11lsZM2YM+fn55Obm8sgjj/DKK680ZKxCCGEWDTF+qbl76faOBLirOXuxmJnfxFk6HCGMVu+Ead++fbz00kv079+fN954g7S0NB577DFsbGywsbHhySef5OTJkw0ZqxBCmEVmA4xfau66hHnyvyf6o1LByYxCMgvKLB2SEEapd8KUk5NDYGAgAK6urri4uODt7W3Y7+XlRWGhTBkVQjR+0sLUMPzdHWkb6A7AnsQcC0cjhHGMmiX397XiZO04IURTJAlTw+nVQv9Fe0+iLMgrGhejZslNmzYNtVr/AVJWVsajjz6Ki4t+gUiNRmP66IQQwgIkYWo4vaK8WbYziT1npYVJNC71TpimTp1a4/m99957xTH333//jUckhBAWZqjyLWOYTO6mKH1ZmtOZRWQXafCReywaiXonTMuWLWvIOIQQwmpIC1PD8XZxoFWAK/EXivgxLo0HLlt4WAhrJpW+hRDibyRhalj39o4A4LU/TvLvH4/y0Bf7ZNacsHr1amGaMGFCvU+4Zs2a6w5GCCEsTatTyCmWhKkh3dsrgg3HL/Dn6Sy+3H0OgFCvBP45vBUHzuUwuLW/TCoSVqdeLUweHh6Gh7u7O5s2bWL//v2G/QcOHGDTpk14eHg0WKBCCGEO2cUadArYqMDHRRKmhmBjo+KNuzrTJcyTzlWLEf9wIJUxb/3JA8v38/vRDMsGKEQt6tXCdPn4pWeeeYaJEyfy4YcfYmurXzJAq9Xy2GOP4e7u3jBRCiGEmVR3x3m7qLG1kVaOhhLg7si6x/uh0ykMe3MbZ7OKKdJUArAzIYvRHYMsHKEQNRk9hunzzz9nzpw5hmQJwNbWllmzZvH555+bNDghhDA3Gb9kXjY2KsOYpmpJWSUWikaIqzM6YaqsrOTEiRNXbD9x4gQ6nc4kQQkhhKVIwmR+k3qGMaytP0Pb+ANwIr0ARVEsHJUQNRlVuBJg+vTpPPDAA5w5c4bevXsD8Ndff/HKK68wffp0kwcohBDmJDWYzM9FbcenU3tSVqGl3b9/J7u4nItFGvzdHC0dmhAGRidMb7zxBoGBgSxZsoT09HQAgoKCmDt3LrNnzzZ5gEIIYU7SwmQ5jva2RPm6kHCxmBPphZIwCatidJecjY0Nc+fO5fz58+Tl5ZGXl8f58+eZO3dujXFNQgjRGEnCZFltg/STh06mF1g4EiFquqHCle7u7jIzTgjRpOQUlwPg4+Jg4Uiap+qE6YQkTMLK1Cth6tatG7m5ufU+af/+/Tl//vx1ByWEEJZSWKaf2u7hZG/hSJqnNoFuAJzMKLRwJELUVK8xTHFxcRw6dAhvb+96nTQuLg6NRnNDgQkhhCUUlFUA4OZo9BBPYQLVLUxnMovQVGpR28lQD2Ed6t0lN3ToULp06VKvR2lpaUPGbLB9+3bGjh1LcHAwKpWKdevW1di/Zs0aRo4cia+vLyqViri4uCvOodFoePLJJ/H19cXFxYVx48aRmppqlviFENanoFSfMLlLC5NFBHk44u5oR6VOISGz2NLhCGFQr69QiYmJRp84NDTU6NcYq7i4mM6dOzN9+nTuuOOOWvf369ePu+66ixkzZtR6jpkzZ/K///2Pb775Bh8fH2bPns2tt97KgQMHZBC7EM2MoigUVHXJuTtKwmQJKpWKtkHu7EnM4UR6Ae2CZZyssA71SpgiIiLqPsgCRo8ezejRo6+6/7777gMgKSmp1v35+fl89tlnrFixgmHDhgGwcuVKwsLC2LhxIyNHjqz1dRqNpkaXY0GBDE4UoikordCi1ekLJro7SZecpVQnTCczCkjMKsbd0Q4fqYslLOyGZsk1dgcOHKCiooIRI0YYtgUHB9OhQwd27dp11dctXry4xoLEYWFh5ghXCNHACkr1rUu2Niqc7KWF2VLaBukHfq8/foGRS7Zz2/s7KavQWjgq0dw164QpIyMDBwcHvLy8amwPCAggI+Pqq2XPnz+f/Px8wyMlJaWhQxVCmEH1gG93RztUKll411LaBOq74c5ll1Cu1ZGSU8rnO40fGiKEKTXrhOlqFEW55oelWq021KCSWlRCNB0y4Ns6tApww+ZvH8EfbEkgu2rZmgqtrFsqzK9ZJ0yBgYGUl5dfUWMqMzOTgIAAC0UlhLCUQhnwbRWcHGyJ9HUB9HWZ2gW5U6ipZO3B83y8PYG2z//OjtNZALJIrzCbZp0wde/eHXt7ezZs2GDYlp6eztGjR+nbt68FIxNCWILUYLIefVv6APDowJaM7RwMwL6kHL7fn0qlTuHdLaf5eHsCrZ//nd0J2ZYMVTQT9fpU8PLyqnd/fk5Ozg0FZIyioiLOnDljeJ6YmEhcXBze3t6Eh4eTk5NDcnIyaWlpAJw6dQrQtywFBgbi4eHBgw8+yOzZs/Hx8cHb25s5c+bQsWNHw6w5IUTzYeiSkxYmi/vXmLbcfVM47YM9OHBO/3dl15lsCjX6VsC/zuZw4FwuFVqFFX8l0acqwRKiodQrYVq6dGkDh3F99u/fz+DBgw3PZ82aBcDUqVNZvnw5P/30E9OnTzfsnzx5MgALFixg4cKFACxZsgQ7OzsmTpxIaWkpQ4cOZfny5VKDSYhmyFCDSUoKWJyzgx3tgz0A6BDigYOdjSFZqlah1XfHbTl5kdJyLU4O8rktGo5KkQ7gG1ZQUICHhwf5+fkyAFyIRmzxbyf4aNtZHuwfxfO3trN0OOIyEz/czd4kfUtTm0A3TmYUYqMCT2cHcorL+fDebozqEGThKEVjY8zf7+saw5SQkMBzzz3H3XffTWZmJgC///47x44du57TCSGEVaiuwyRdctanR+Sl8i//HN6KZ8e0ZenkrtzRLQSA345evRSMEKZgdMK0bds2OnbsyJ49e1izZg1FRUUAHD58mAULFpg8QCGEMBdDHSbpkrM6PSP1i7+rVNArypsZA1owrnOwoVXpt6MZHEnNt2SIookzOmGaN28e//nPf9iwYQMODg6G7YMHD2b37t0mDU4IIcxJygpYr94tfOgV5c29vSLwdL70t6dbuCdD2vhTXqnj4RX7uVioucZZhLh+RidMR44c4fbbb79iu5+fH9nZMrVTCNF4Vc+Sk7IC1sfJwZZvH+nDi7d1qLFdpVKxdHIXWvi6kJ5fxjOrD0ttJtEgjE6YPD09SU9Pv2L7wYMHCQkJMUlQQghhCZe65KSFqTFxd7Tng3u742Brw+aTmXy7T5arEqZndMI0ZcoUnnnmGTIyMlCpVOh0Onbu3MmcOXO4//77GyJGIYQwCxn03Xi1DnRj9ohWALzy+0m0OmllEqZldML00ksvER4eTkhICEVFRbRr144BAwbQt29fnnvuuYaIUQghzKJQBn03ag/2j8LJ3pa8kgoSs4osHY5oYoz+VLC3t2fVqlUsWrSIgwcPotPp6Nq1KzExMQ0RnxBCmEVZhRZNpX5RVzdpYWqU7Gxt6BDizr6kXA6l5BPt72bpkEQTYnTCtG3bNgYOHEjLli1p2bJlQ8QkhBBmVz1DTqUCN7W0MDVWHUM82ZeUy5Hz+dzRPdTS4YgmxOguueHDhxMeHs68efM4evRoQ8QkhBBmVz3g21Vth41N/dbOFNanc5h+OZXDqXmWDUQ0OUYnTGlpacydO5c///yTTp060alTJ1577TVSU1MbIj4hhDALWXi3aegYok+YjqUVUKHVd7FKmQFhCkYnTL6+vjzxxBPs3LmThIQEJk2axJdffklkZCRDhgxpiBiFEKLBZReVA+Dt4lDHkcKaRfq44OZoh6ZSx+kLRXyzN5m2//6dracyLR2aaOSuay25alFRUcybN49XXnmFjh07sm3bNlPFJYQQZpVdrK8Q7esqCVNjZmOjMrQy/XIkjZd+PUFZhY7lu5IsG5ho9K47Ydq5cyePPfYYQUFBTJkyhfbt2/Pzzz+bMjYhhDCbrKoWJl9XtYUjETdqaNsAAN7bkmAYzL/zTJZhnJoQ18PohOlf//oXUVFRDBkyhHPnzrF06VIyMjJYuXIlo0ePbogYhRCiwVWvQebrJglTYze9bySj2gcanrs42FKhVdhyUrrlxPUzeu7s1q1bmTNnDpMmTcLX17chYhJCCLPLKtInTD4yhqnRs7FRsWRSF2x/OISfqxoXtS3vbUngtyMZjO8iS3iJ62N0wrRr166GiEMIISyqetC3n7QwNQlODra8N6UbAEfP5/PelgS2xV+kUqvDztaGhItFLNkQz9yRbQj3cbZwtKIxuK4xTCtWrKBfv34EBwdz7tw5AJYuXcqPP/5o0uCEEMJcqluYZAxT09MuyB0ne1tKK7Qk55QA8PG2s/x8OJ2P/0ywcHSisTA6Yfrggw+YNWsWY8aMIS8vD61WC4CnpydLly41dXxCCGEWkjA1XTY2KqL9XQGIv6BfY+7UhUJAX69JiPowOmF65513+OSTT3j22WextbU1bO/RowdHjhwxaXBCCGEOFVoduSX6GVQ+UlagSYqpSpjOZBaiKApnMvWJ08n0QrQ6KWwp6mZ0wpSYmEjXrl2v2K5WqykuLjZJUEIIYU65xfrxSzYq8HKWhKkpig7QJ0ynM4tIyy+jSKMvN1BaoSUxq8iSoYlGwuiEKSoqiri4uCu2//bbb7Rr184UMQkhhFldrOqO83ZRYyvryDVJrfzdAH2XXHxGYY190i0n6sPoWXJPP/00jz/+OGVlZSiKwt69e/n6669ZvHgxn376aUPEKIQQDepS0UppXWqqYqpamBIuFnEio2aCdDytQMoNiDoZnTBNnz6dyspK5s6dS0lJCVOmTCEkJIS33nqLyZMnN0SMQgjRoLIKZcB3Uxfq5YzazgZNpY7NJ/QFLEM8nTifVyotTKJerquswIwZMzh37hyZmZlkZGSQkpLC5MmT2b59u6njE0KIBndphpy0MDVVtjYqWvrpW5n2n8sFYHyXYACOpeWjKDLwW1zbDS2+6+vri7+/PwBnzpxh8ODBJglKCCHMKbtY1pFrDlpVdctVG9s5GAc7G3JLKgyz5oS4mhtKmIQQoinIknXkmoWJPcMIcNf/Pw7xdCLG35VeUd4AbIu/aMnQRCNg9Bim6zVr1iyjX/Pcc8/h7e3dANEIIcQlmYWyjlxz0LelL3/NH0pSdglezvbY2dowqLU/f57OYuupizx0cwtLhyismNkSpqVLl9KnTx8cHOr3gbRjxw6eeOIJSZiEEA0uMUtfQy7S18XCkYiGplKpiLrs//Og1n68+DPsTcyhWFOJi9psfxZFI1Pv34yffvrpmvsTExPrPMfatWsNY57q4ubmVq/jhBDiRpSUV3I+rxSAaD/XOo4WTU0LXxdCvZxIzS3lsx2JTOkVXutYtmJNJV/tSeb2biEy1q2ZqnfCdNttt9V5jEp19YJvy5Ytw8PDo75vx0cffURAQEC9jxdCiOtx9qK+dcnbxQEv6ZJrdlQqFUPa+PPl7nO8uSGeL3YlsXPeEBztbVEUhdTcUkK9nHhr02k+3n6WkxmF/HdiZ0uHLSyg3gmTTqe7oTeaOnWqUcdPmTLlht5PCCHqI+GifnZUSz/pjmuunhwSg52NDd/uSya7uJxjafl0j/Dm+/2pzF19mNnDW/HL4XQAtp7KRKdTsJGK8M1Oo54lt337dsaOHUtwcDAqlYp169bV2K8oCgsXLiQ4OBgnJycGDRrEsWPHahwzaNAgVCpVjYcU4BSi+UioamFqKd1xzZafm5p/j21Hn5a+AMSeywPgf4fTAHh782lDt212cTlHzudbJE5hWRZJmLRaLW+88QY33XQTgYGBeHt713jUV3FxMZ07d+bdd9+tdf9rr73Gm2++ybvvvsu+ffsIDAxk+PDhFBbWXEdoxowZpKenGx4fffTRDV2fEKLxqG5hivaXhKm56x7hBUBsci7llTr2J+kLXFZoaxa13HpKShA0RxZJmF544QXefPNNJk6cSH5+PrNmzWLChAnY2NiwcOHCep9n9OjR/Oc//2HChAlX7FMUhaVLl/Lss88yYcIEOnTowBdffEFJSQlfffVVjWOdnZ0JDAw0POoaa6XRaCgoKKjxEEI0LpVaHWl5pSRkVnfJScLU3HUL9wT0CVNcSh6lFdoa+/tH61ugtsZnmjs0YQUskjCtWrWKTz75hDlz5mBnZ8fdd9/Np59+yr///W/++usvk7xHYmIiGRkZjBgxwrBNrVYzcOBAdu3adUU8vr6+tG/fnjlz5lzRAvV3ixcvxsPDw/AICwszScxCCPN5du1R+r6ymZNVK9dLwiQ6hXpiZ6PiQoGGHw6kADCsbQAt/FwI8nBk4bj2AMSl5JFW1UUnmg+LJEwZGRl07NgRAFdXV/Lz9f3Bt956K7/88ovJ3gO4YqZdQECAYR/APffcw9dff83WrVt5/vnnWb16da0tVpebP38++fn5hkdKSopJYhZCmM+vR9JrPA/xcrJQJMJaODnY0jbIHYDv9qcCMLiNH788eTObZw8i2t+V3i28URT49M+6S+mIpuW6Eqa8vDw+/fRT5s+fT05ODgCxsbGcP3++Xq8PDQ0lPV3/YRUdHc369esB2LdvH2q1aetb/L3UgaIoNbbNmDGDYcOG0aFDByZPnswPP/zAxo0biY2Nveo51Wo17u7uNR5CiMZDURR0ly222qeFD7Yy60lwaRxTtT4tfHBysMXJwRaAxwZFA/D13mSyqxZtFs2D0SVNDx8+zLBhw/Dw8CApKYkZM2bg7e3N2rVrOXfuHF9++WWd57j99tvZtGkTvXr14qmnnuLuu+/ms88+Izk5mX/+85/XdSF/FxgYCOhbmoKCggzbMzMzr1nfqVu3btjb23P69Gm6detmkliEENaloKyS4nL9+JTfZ95MiKe0Lgm9Rwa2oFyrI7NAQ+dQD1r8rav25hhfOoS4c/R8ASv+OsfMYa0sFKkwN6MTplmzZjFt2jRee+21GtW4R48eXe/aSa+88orh5zvvvJOwsDB27txJdHQ048aNMzakWkVFRREYGMiGDRvo2rUrAOXl5Wzbto1XX331qq87duwYFRUVNZIsIUTTkp6vH3/i5WxPm0BpIRaXBHk48fLtHa+6X6VS8VD/Fsz8No51B8/z1NCYaxZtFk2H0QnTvn37ap12HxISUmNs0NV8//33rFu3joqKCoYNG8bDDz9Mr1696NWrl7GhUFRUxJkzZwzPExMTiYuLw9vbm/DwcGbOnMnLL79MTEwMMTExvPzyyzg7OxsSu4SEBFatWsWYMWPw9fXl+PHjzJ49m65du9KvXz+j4xFCNA7VA3aDpWVJXIdh7QJQ29mQlF3CsbQCOoTUfxUL0XgZnTA5OjrWOo3+1KlT+Pn5XfO1H3/8MY8++igxMTE4OjqyevVqEhMTWbx4sbFhALB//34GDx5seD5r1ixAX1V8+fLlzJ07l9LSUh577DFyc3Pp1asX69evN7SMOTg4sGnTJt566y2KiooICwvjlltuYcGCBdja2l5XTEII63c+rwzQtyYIYSxXtR1D2vjz29EMfj6cLglTM6FSFEWp+7BLHn74YS5evMh3332Ht7c3hw8fxtbWlttuu40BAwawdOnSq762Y8eO3Hbbbbz44osALF++nCeffLLOafzWrqCgAA8PD/Lz82UAuBCNwGu/n+T9rQlM7RPBC+M7WDoc0Qj9fDiNJ746SKiXE3/OHSzdco2UMX+/jZ4l98Ybb3Dx4kX8/f0pLS1l4MCBREdH4+bmxksvvXTN1549e5bp06cbnt93331oNJp6deUJIYSpSJecuFFD2vjj7GBLam4puxOyLR2OMAOju+Tc3d3ZsWMHmzdvJjY2Fp1OR7du3Rg2bFidry0tLcXV9dKMA1tbW9RqNSUlJcaGIYQQ1y2tuktOEiZxnZwd7LijWygr/jrHZzsS6VtVBVw0XUYlTJWVlTg6OhIXF8eQIUMYMmSI0W/46aef1kiaKisrWb58Ob6+l37Z/vGPfxh9XiGEqK+0qllyIZ6OFo5ENGbT+0Wy4q9zbDqZydmLRVeUIBBNi1EJk52dHREREWi12roPrkV4eDiffPJJjW2BgYGsWLHC8FylUknCJIRoMFqdQka+voVJuuTEjWjh58rQNv5sOpnJy7+e5OP7umMjBVCbLKO75J577jnmz5/PypUr8fb2Nuq1SUlJxr6dEEKYVFaRhkqdgq2NCn83aWESN2bmsFb8eTqLjScu8MrvJ/nXmLZXPfaJr2I5kV7AT0/0x0Vt9J9fYWFG/x97++23OXPmDMHBwURERODi4lJj/7WWFKm2aNGiq+5TqVQ8//zzxoYlhBD1kpRVDECAm1qWQxE3rGOoB6/f1Ymnvonj4+1n6RnpzfB2V64mcSQ1n58P65cEO5SSJ2OeGiGjE6bbbrvtht907dq1NZ5XVFSQmJiInZ0dLVu2lIRJCNFgfjuqn5XbPdK4FnIhrmZ8lxCOns/nkz8Tmb/mCD0ivPBycahxzMq/zhl+zigoM3eIwgSMTpgWLFhww2968ODBK7YVFBQwbdo0br/99hs+vxBC1EZTqWVdnH6R8Du7h1o4GtGUzB7Rmi2nLnIms4gnvo7ls6k9cbTXF0DOLCjjx0OXFqevLmshGhej6zA1FHd3dxYtWiStS0KIBrP5RCZ5JRUEuKvpL10iwoQc7W1ZOqkLzg627DyTzaMrD1BeqePFn4/T79XNlFXoDMeel4SpUTI6YbKxscHW1vaqjxuRl5dHfn7+DZ1DCCGuprp1aUK3UBm/JEyuQ4gHy6b1xNHehq2nLjL2nR18tiORCq1CuyB37u8TAVxamkc0LkZ3ydU2/ujgwYN88cUXvPDCC/U6x9tvv13juaIopKens2LFCkaNGmVsSEIIUS9HUvVfyAa39rdwJKKp6tXChw/u6c6DX+zj1AX9sl8LxrZjer8odp3J4svd56RLrpEyOmEaP378FdvuvPNO2rdvz7fffsuDDz5Y5zmWLFlS47mNjQ1+fn5MnTqV+fPnGxuSEELUqbCsgrSq+kutA9wsHI1oyga38eeF8R144adjTOoZxrS+kcClul/nc0tRFEXWn2tkTFYIolevXsyYMaNexyYmJprqbYUQol7OZBYB4O+mxsPZ3sLRiKbuvt4RTOgaUqPeUqCHvu5XaYWWvJKKK2bSCetmkkHfpaWlvPPOO4SGyqwTIYR1On1BnzDFBMjyFcI8/l6c0tHeFj83NSADvxsjo1uYvLy8ajQjKopCYWEhzs7OrFy50qTBCSGEqcRXjSeJ8ZfuOGE5wZ5OXCzUcD6vlA4hHpYORxjB6IRpyZIlNRKm6vFHvXr1wsvLy6TBCSGEqZyu6pJrJeOXhAWFeDpyKEVqMTVGRidM06ZNa4AwhBCiYZ2uamFqJV1ywoJCqgZ+S8LU+Bg9hun3339nx44dhufvvfceXbp0YcqUKeTm5po0OCGEMIXLZ8hJl5ywpOqZcik5kjA1NkYnTE8//TQFBQUAHDlyhFmzZjFmzBjOnj3LrFmzTB6gEELcqOrxSzJDTlhaCz99C+eZi0UWjkQYy+guucTERNq1awfA6tWrGTt2LC+//DKxsbGMGTPG5AEKIcSN2h6fBUDXcE/LBiKavTaB+hbOxKxiNJVa1HY3tkKGMB+jW5gcHBwoKSkBYOPGjYwYMQIAb29vQ8uTEEJYkw3HLwAwvF2ghSMRzZ2/mxoPJ3u0OoWEzGJLhyOMYHTC1L9/f2bNmsWLL77I3r17ueWWWwCIj4+XOkxCCKtzPq+U4+kF2KhgcGs/S4cjmjmVSmWoNH/qgjQyNCZGJ0zvvvsudnZ2/PDDD3zwwQeEhIQA8Ntvv8k6cEIIq7PphL51qXuEFz6uagtHIwS0ruqWO5Uh45gaE6PHMIWHh/Pzzz9fsf3v68MJIYSlVWp1/HAgFYBhbQMsHI0Qeq0MCZO0MDUmRrcwxcbGcuTIEcPzH3/8kdtuu41//etflJeXmzQ4IYS4ER9sTeBwaj6uajvGdwmxdDhCAJcWf46/IC1MjYnRCdMjjzxCfHw8AGfPnmXy5Mk4Ozvz/fffM3fuXJMHKIQQ1+PsxSKWbjoNwKLx7Q0LnwphadUJ0/m8UgrKKiwcjagvoxOm+Ph4unTpAsD333/PgAED+Oqrr1i+fDmrV682dXxCCHFdtpy6iFan0KeFD7d3ldYlYT08nO0J89YXsFz86wkURbFwRKI+jE6YFEVBp9MB+rIC1bWXwsLCyMrKMm10QghxnQ6cywHg5la+Nda/FMIaLLi1PSoVfL03hWU7kywdjqgHoxOmHj168J///IcVK1awbds2Q1mBxMREAgJkUKUQwvIURWFfkn6pph4R3haORogrDWsXwHO36ItAv7H+FJkFZRaOSNTF6IRp6dKlxMbG8sQTT/Dss88SHR0NwA8//EDfvn1NHqAQQtTHL4fTmfvDIYo0laTklHKxUIODrQ2dQj0sHZoQtXqgXyRdwz0pKdfy+h+nLB2OqIPRZQU6depUY5Zctddffx1bWynxLoQwjTnfH2J3Qja//KM/ns4O1zxWp1P4949HyS4uJ9TL2bAifIcQdxzt5XNJWCeVSsXzt7Zjwvu7+CE2lccGRxPl62LpsMRVGN3CBJCXl8enn37K/PnzycnRjxM4fvw4mZmZJg1OCNE8lVVoWXfwPOfzStlf1bV2LYdS88gu1pc1Wb4riW3xFwHoGSndccK6dQv3ok8LHxQFdpy+aOlwxDUYnTAdPnyYmJgYXn31Vd544w3y8vIAWLt2LfPnzzd1fNe0fft2xo4dS3BwMCqVinXr1tXYrygKCxcuJDg4GCcnJwYNGsSxY8dqHKPRaHjyySfx9fXFxcWFcePGkZqaasarEEL83fH0Aip1+plDiVl1r7e16cSlL2s5xeX8dCgNgN4tfBomQCFMqG9L/e/p7rPZFo5EXIvRCdOsWbOYPn06p0+fxtHxUl2T0aNHs337dpMGV5fi4mI6d+7Mu+++W+v+1157jTfffJN3332Xffv2ERgYyPDhwyksLDQcM3PmTNauXcs333zDjh07KCoq4tZbb0Wr1ZrrMoQQf3MoJc/w89n6JEwn9QlTz0gvw7aHB7RgkKwdJxqBPlUJ019nc6TEgBUzegzTvn37+Oijj67YHhISQkZGhkmCqq/Ro0czevToWvcpisLSpUt59tlnmTBhAgBffPEFAQEBfPXVVzzyyCPk5+fz2WefsWLFCoYNGwbAypUrCQsLY+PGjYwcObLWc2s0GjQajeF5QYGUtxfCFI6ezyc5p4S4yxKmpDoSprS8Uk6kF6BSwfv3dGf98QxaBbhJd5xoNDqFeuJob0NOcTnxF4oMa80J62J0C5Ojo2OtCcKpU6fw87Oeb3OJiYlkZGQwYsQIwza1Ws3AgQPZtWsXAAcOHKCioqLGMcHBwXTo0MFwTG0WL16Mh4eH4REWFtZwFyJEM1Gp1TFt2T4eWxXLb0cuffmqq0vui91JAHQP98LPTc09vSIkWRKNioOdjaH8xV9nsynSVPLKbyc5cK7u8XvCfIxOmMaPH8+iRYuoqNCXc1epVCQnJzNv3jzuuOMOkwd4vapbu/5eGyogIMCwLyMjAwcHB7y8vK56TG3mz59Pfn6+4ZGSkmLi6IVofv46m0NWkb7ltlyrM2zPKCijpLyy1tdk5JexvKro3/8NatngMQrRUKq75f53KI2XfjnBh9sSePKrWMordXW8UpiL0QnTG2+8wcWLF/H396e0tJSBAwcSHR2Nm5sbL730UkPEeEP+XuFXUZQ6q/7WdYxarcbd3b3GQwhxfTSVWvJKyvnlSFqN7ZE+zng52wOQlFVSY5+iKPzvUBqPrjyAplJHjwgvhrTxN1vMQpja2E7BONnbsv9cLl/vTQYgLb+M1bEyCclaGD2Gyd3dnR07drB582ZiY2PR6XR069bNMAbIWgQGBgL6VqSgoCDD9szMTEOrU2BgIOXl5eTm5tZoZcrMzJQinEKYyb2f7uFQSj52tvovKQ8PaMHynUmM7hjEnrPZ5CbnkZhVTLvgS19Mvj+QytwfDgNgb6ti/pg2svyJaNTCfZx5YXx7w+91oLsjGQVlvLflDHd2D8Xe9rqqAAkTMur/QGVlJXZ2dhw9epQhQ4YwZ84c5s6da3XJEkBUVBSBgYFs2LDBsK28vJxt27YZkqHu3btjb29f45j09HSOHj0qCZMQZlBYVsG+pFzKtTpKyrX4ujowd2Rr4hYMZ+7I1kRWFfFLyr40jklTqWXphngAJvYI5benBtBdlj8RTcBd3UN5eEALbor0ZvVjffF1VZOaW8r6YxcsHZrAyBYmOzs7IiIirGbKfVFREWfOnDE8T0xMJC4uDm9vb8LDw5k5cyYvv/wyMTExxMTE8PLLL+Ps7MyUKVMA8PDw4MEHH2T27Nn4+Pjg7e3NnDlz6Nixo1UmgUI0NSfSL5X4cLCz4b7ekdjZ2mBX9W26RVXClJBZZDjuqz3JpOWXEejuyKLxHaSSt2gyVCoV/xrT1vB8Us9Q3tuSwPcHUrilU9A1XinMweguueeee4758+ezcuVKvL0t+61u//79DB482PB81qxZAEydOpXly5czd+5cSktLeeyxx8jNzaVXr16sX78eN7dLUzaXLFmCnZ0dEydOpLS0lKFDh7J8+XJZ5kUIMzh6Ph+AYW0D+PDeboZEqVr7EP06cL8fy+Dp/FL83Rz5ZPtZAJ4cGi3JkmjS7uwexntbEtgef5GM/DICPRzrfpFoMCrFyCpZXbt25cyZM1RUVBAREYGLS811b2JjY00aYGNQUFCAh4cH+fn5MgBcCCPM/u4Qq2NTeWpoDP8c3uqK/YqicNeHu9l/LpdbOwVx903h3PPpHtwd7dj77DBJmESTd9eHu9iXlMvcUa15bFC0pcNpcoz5+210C9P48eNlcKUQwiSOpelbmNoH1/5BpVKpeGF8e8a+s4OfD6dzMkPfhXdr52BJlkSzcGf3UPYl5fLH0QxJmCzM6IRp4cKFDRCGEKK5KavQcrpqbFKHqq632rQP9mDGgBZ8tO0sZ6qOv6NbqFliFMLS+rTwBfTj/TSVWtR28kXBUuo9S66kpITHH3+ckJAQ/P39mTJlCllZWQ0ZmxCiCYu/UIhWp+DlbE9QHWMznh7R2rBAaaSPM93CPc0QoRCWF+bthJezPeVaHScvmyQhzK/eCdOCBQtYvnw5t9xyC5MnT2bDhg383//9X0PGJoRowqoX2G0f7FFnN7+drQ3vTenGtL6RvHJHJxkWIJoNlUpFx1BPAA6n5lk0luau3l1ya9as4bPPPmPy5MkA3HvvvfTr1w+tViszyoQQRtt0MhO4tCREXbxcHFg4rn1DhiSEVeoS6sH2+IscSs3nPksH04zVu4UpJSWFm2++2fD8pptuws7OjrS0tGu8SgghrlSkqWTXmWwARrQLqONoIZq3TlUtTNWtssIy6p0wabVaHBwcamyzs7OjsrL2RTGFEOJqtsdfpFyrI9LHmWh/V0uHI4RV6xSmnxRx5mIR2VULVAvzq3eXnKIoTJs2DbVabdhWVlbGo48+WqMW05o1a0wboRCiydlwXL/Uw/B2ATIeSYg6+Ls5EuzhSFp+Gb0Xb+KZUW146OYWlg6r2al3wjR16tQrtt17770mDUYI0fRVaHVsrhq/NLxdoIWjEaJxmD+mLf9df4qk7BK+3pssCZMF1DthWrZsWUPGIYRoJvYl5ZBfWoG3iwPdI7wsHY4QjcLYzsH0jPSm9+JNJGWXUF6pw8Gu3qNqhAnI3RZCmFV1d9yQNv7Y2kh3nBD1FeCuxlVth1ankJRdbOlwmh1JmIQQZqMoCuuP6RMmmR0nhHFUKpVhkkR11XthPpIwCSHM5kR6IefzSnG0t+HmGD9LhyNEoxNTlTCdviAJk7lJwiSEMJv/HdbXbesf7YeTgxS8FcJYhhami5IwmZskTEIIsyiv1PH9/hRAvwK7EMJ4MQHVLUyyrpy51WuW3E8//VTvE44bN+66gxFCNF3rj2eQVVSOv5uaoW39LR2OEI1StJ8bAGezitHqFJk4YUb1Sphuu+22Gs9VKhWKotR4Xk2r1ZomMiFEk/L13mQAJvUMw95WGreFuB4hXk442ttQVqEjJaeESF+Xul8kTKJen1o6nc7wWL9+PV26dOG3334jLy+P/Px8fv31V7p168bvv//e0PEKIRqh0nItf53NAaQ7TogbYWujonWAvpWpegFrYR71LlxZbebMmXz44Yf079/fsG3kyJE4Ozvz8MMPc+LECZMGKIRo/I6nF6DVKfi6qgn3drZ0OEI0apN6hnMo9Qif/nmW+3pHSAFLMzH6LickJODh4XHFdg8PD5KSkkwRkxCiiTmSmgdAp1APWTtOiBt0R/cQ/N3UpOeXse7geUuH02wYnTD17NmTmTNnkp6ebtiWkZHB7Nmzuemmm0wanBCiaTh8Ph+AjiFXftkSQhhHbWfLjKq15L6tmnkqGp7RCdPnn39OZmYmERERREdHEx0dTXh4OOnp6Xz22WcNEaMQopE7kqpPmDqFSsIkhCn0j/EFpOK3ORk9hik6OprDhw+zYcMGTp48iaIotGvXjmHDhklTuxDiCsWaShKqiuxJC5MQphHpo58dl19aQW5xOV4uDhaOqOkzOmECfRmBESNGMGLECFPHI4RoAhIuFrHgx2M8Nrgl9rY26BQIdHfE393R0qEJ0SQ4OdgS6O5IRkEZidnFkjCZwXUlTJs2bWLTpk1kZmai0+lq7Pv8889NEpgQonE5lpbPc+uO8o+hMfywP5UdZ7IoLq9kWFv9IrsdpHVJCJOK9HUmo6CMpKxiuoV7WTqcJs/ohOmFF15g0aJF9OjRg6CgIOmGE0KgKAoLfzrGweQ8nv7+MHkl5QAcTM4jPa8MgOHtpLq3EKYU5evCX2dzSMoqtnQozYLRCdOHH37I8uXLue+++xoiHiFEI7QrIZt9SbkAZBVpauzLKCjD0d6GMR2DLBGaEE1W9TimxOwSC0fSPBg9S668vJy+ffs2RCxCiEbqrY2nAQwViAF6RFzqIhjZPhA3R3uzxyVEU1a9LMq5bGlhMgejE6aHHnqIr776qiFiEUI0QvklFexN0i97smx6T27pFETvFt4sndyF6nVB7+gmy6EIYWpRVQlTYlZxjfVdRcMwukuurKyMjz/+mI0bN9KpUyfs7Wt+a3zzzTdNFpwQwvqdyCgAIMTTiWBPJ96b0s2wb9H4DqTnl9I/2tdS4QnRZIV7O6NSQWFZJTnF5fi4qi0dUpNmdMJ0+PBhunTpAsDRo0dr7JMB4EI0PyfS9QlTu2D3K/bd2zvC3OEI0Ww42tsS7OHE+bxSkrKLJWFqYEYnTFu2bGmIOIQQjVR1wtQ26MqESQjRsEI89QlTRr6m7oPFDWkWSxwXFhYyc+ZMIiIicHJyom/fvuzbt8+wf9q0aahUqhqP3r17WzBiIRqP49UtTEFudRwphDA1Lxf9sJicqlIeouEY3cI0ePDga3a9bd68+YYCaggPPfQQR48eZcWKFQQHB7Ny5UqGDRvG8ePHCQkJAWDUqFEsW7bM8BoHB6maKkRdKrU64i/olz1pFySFKYUwN++qCt+5xZIwNTSjE6bq8UvVKioqiIuL4+jRo0ydOtVUcZlMaWkpq1ev5scff2TAgAEALFy4kHXr1vHBBx/wn//8BwC1Wk1gYGC9zqnRaNBoLjV/FhQUmD5wIRqBs1nFlFfqcFXbEerlZOlwhGh2vJz1CVOOJEwNzuiEacmSJbVuX7hwIUVF1rdqcmVlJVqtFkfHmmtYOTk5sWPHDsPzrVu34u/vj6enJwMHDuSll17C37/2ysSLFy/mhRdeaNC4hbBWmkotP8alsetMFqeqWpfaBLphYyOTPoQwN0MLk3TJNTiTjWG69957rXIdOTc3N/r06cOLL75IWloaWq2WlStXsmfPHtLT0wEYPXo0q1atYvPmzfz3v/9l3759DBkypEYr0uXmz59Pfn6+4ZGSkmLOSxLCopbtTGLuD4dZF5dmGPDdPVLWsRLCEqSFyXyua/Hd2uzevfuKVhxrsWLFCh544AFCQkKwtbWlW7duTJkyhdjYWAAmTZpkOLZDhw706NGDiIgIfvnlFyZMmHDF+dRqNWq1TN8UzdNfZ7MBuKVTEMPbBmBjo2JoG1knTghLkBYm8zE6Yfp7AqEoCunp6ezfv5/nn3/eZIGZUsuWLdm2bRvFxcUUFBQQFBTEpEmTiIqKqvX4oKAgIiIiOH36tJkjFcK6KYrCoZQ8AB6+uQWdwzwtGo8QzZ2XYdB3hYUjafqMTpg8PGrOhLGxsaF169YsWrSIESNGmCywhuDi4oKLiwu5ubn88ccfvPbaa7Uel52dTUpKCkFBslioEJc7l11CbkkFDnY2UndJCCvgLV1yZmN0wnT51PvG4o8//kBRFFq3bs2ZM2d4+umnad26NdOnT6eoqIiFCxdyxx13EBQURFJSEv/617/w9fXl9ttvt3ToQliVuKrWpfbB7jjYNYsybkJYteo6TKUVWkrLtTg52Fo4oqbruscwHThwgBMnTqBSqWjXrh1du3Y1ZVwmlZ+fz/z580lNTcXb25s77riDl156CXt7eyorKzly5AhffvkleXl5BAUFMXjwYL799lvc3KQQnxCXq06YukhXnBBWwVVth72tigqtQm5JOU4OUt6joRidMGVmZjJ58mS2bt2Kp6cniqKQn5/P4MGD+eabb/Dz82uIOG/IxIkTmThxYq37nJyc+OOPP8wckRCN00FJmISwKiqVCi9nBzILNeQUlxPsKQlTQzG6Tf3JJ5+koKCAY8eOkZOTQ25uLkePHqWgoIB//OMfDRGjEMKCcovLOZyax3tbznAkNQ+ArmFSRkAIayEz5czD6Bam33//nY0bN9K2bVvDtnbt2vHee+9Z/aBvIUT95ZdW8N/1p/hmXwrllTrD9rtvCifcx9mCkQkhLie1mMzD6IRJp9Nhb29/xXZ7e3t0Ol0trxBCNEYfb0/gy93nAPB3U+PuZM9D/aOY1DPMwpEJIS4n68mZh9EJ05AhQ3jqqaf4+uuvCQ4OBuD8+fP885//ZOjQoSYPUAhhGacyCgGYNbwVTw6Jvuai20IIy6meKZdTIrWYGpLRY5jeffddCgsLiYyMpGXLlkRHRxMVFUVhYSHvvPNOQ8QohLCAhIvFAPSI8JJkSQgrVl2LSVqYGpbRLUxhYWHExsayYcMGTp48iaIotGvXjmHDhjVEfEIIC9BUaknOKQGgpb+rhaMRQlxLdbXvHBn03aCuuw7T8OHDGT58uCljEUJYieTsErQ6BVe1Hf5usm6iENZMxjCZR7275Pbs2cNvv/1WY9uXX35JVFQU/v7+PPzww2g0GpMHKIQwv4SLRQC08HOR7jghrJyvq/5LTUZ+mYUjadrqnTAtXLiQw4cPG54fOXKEBx98kGHDhjFv3jz+97//sXjx4gYJUghhXtXjl1r6SXecENau+t/puZySGiVAhGnVO2GKi4urMQvum2++oVevXnzyySfMmjWLt99+m++++65BghRCmMfOM1mMWrqdL3YlAdDSz8WyAQkh6hTgrsZNbYdWp5CUXWzpcJqseidMubm5BAQEGJ5v27aNUaNGGZ737NmTlJQU00YnhDAbnU7hhf8d42RGIZmF+u51aWESwvqpVCrD5IzTF4osHE3TVe+EKSAggMTERADKy8uJjY2lT58+hv2FhYW1FrQUQjQOW05lEv+3D1uZISdE4xBTnTBlFlo4kqar3gnTqFGjmDdvHn/++Sfz58/H2dmZm2++2bD/8OHDtGzZskGCFEI0vA+2JgAwsn0ANir9zJsIWQJFiEYhJqA6YZIWpoZS77IC//nPf5gwYQIDBw7E1dWVL774AgcHB8P+zz//XNaSE6KRysgvY/+5XGxUsGh8B54d0w6VCtR2tpYOTQhRD9FVLUwJkjA1mHonTH5+fvz555/k5+fj6uqKrW3ND9Lvv/8eV1dpvheiMTqRUQDoxywFuDtaOBohhLFi/N0AOHuxmEqtDjtboxfyEHUw+o56eHhckSwBeHt712hxEkI0HifS9QlTmyB3C0cihLgeIZ5OONrbUK7VcSJdxjE1BElBhRCcrPqAbRvkZuFIhBDXw8ZGRasA/b/f8e/t4K2Npy0cUdMjCZMQzdBfZ7O5//O9vLflDJmFZYYWpraB0sIkRGP13C3t6BruiU6BlXvOWTqcJue615ITQjRO5/NKeXTlAfJKKtgef5EvdyeRVaRfg6qtdMkJ0WjdFOXNygd70WHhH1ws1JBVpDEsmyJunLQwCdGMlFVoeeKrWPJKKmgT6EaIpxMXCjRodQqezvYEuMuHqxCNmYvajghvfTmQkzKWyaQkYRKimdBUanlkxQEOJufh5mjHJ/f34Nlb2hr2tw10l4V2hWgC2lR1rZ+smv0qTEMSJiGasNzicn44kEqFVse7m8+wLf4ijvY2fDa1J2HezoxqH0iHEP2Hq3THCdE0VP9bPp4uCZMpyRgmIZqwl389wfcHUknLK+V/h9IA+M9tHbkpyhvQz6xZMrELH247y/R+kRaMVAhhKm2qZrtKl5xpScIkRBOlKApbTl0E4POdieSVVOBga8OoDoE1josJcOO/EztbIkQhRANoV9XCdCaziAqtDnspYmkScheFaKLiLxSRVaQBIK+kAoDeLX1wVcv3JCGaslAvJ1zVdpRrdSRclKVSTEU+OYVoYlYfSGVd3HmCPK5c4mRYW38LRCSEMCeVSkWbQDf2n8vlZHqhYRC4uDHSwiREE/LWxtPM/v4Qf57O4rv9qQD0buFt2D+0bYClQhNCmFH1wO8TMvDbZKSFSYgmYl9SDks2xgPg5mhHYVklAPNHt2XZzkT83R0J8XSyZIhCCDOpHvh9IkMGfpuKJExCNHJ7E3PwdrHnw60JAEzsEcrdN4Uz6aO/CPRwpGOIB0snd7VwlEIIc5IWJtOThEmIRuxMZiGTPt6NrUpFpU5BpYL/GxRNlK8Lm+cMxNHeFhsbKUYpRHPTOsANlQpZIsWEZAyTEI3Yz4fTURSo1CkAjO4QSJSvCwChXs7yISlEMyVLpJhes0iYCgsLmTlzJhERETg5OdG3b1/27dtn2K8oCgsXLiQ4OBgnJycGDRrEsWPHLBixEPXz65F0AMZ0DGRoG3/mjWpbxyuEEM2FLJFiWs0iYXrooYfYsGEDK1as4MiRI4wYMYJhw4Zx/vx5AF577TXefPNN3n33Xfbt20dgYCDDhw+nsFCycmG9zmQWEn+hCHtbFYtv78Rn03oS7uNs6bCEEFaiehzTF7uTeHD5Pi4UlFk4osatySdMpaWlrF69mtdee40BAwYQHR3NwoULiYqK4oMPPkBRFJYuXcqzzz7LhAkT6NChA1988QUlJSV89dVXlg5fiKv64YA+4e8X7YuHs72FoxFCWJu2VTPlUnJK2XQyk3+tOYKiKBaOqvFq8oO+Kysr0Wq1ODrWLOLn5OTEjh07SExMJCMjgxEjRhj2qdVqBg4cyK5du3jkkUeuOKdGo0Gj0RieFxRIc6e4McnZJbg72eHp7FDr/uwiDfd9tpdKnY7eLXxQAV/sPgfAbV1CzBipEKKxGNTanym9wlEUhdUHzrPpZCY/H05nbOdgS4fWKDX5hMnNzY0+ffrw4osv0rZtWwICAvj666/Zs2cPMTExZGRkABAQULOgX0BAAOfOnav1nIsXL+aFF15o8NhF07c/KYcXfz7OodR87GxUjGgfwOIJnVgbm8r7WxPwcLLnju6hXCgoM6w8Hn/h0lIHjwxowfgu8uEnhLiSg50NL9/eEYBAdyeWbIzn7U2nJWG6Tk0+YQJYsWIFDzzwACEhIdja2tKtWzemTJlCbGys4RiVqubUa0VRrthWbf78+cyaNcvwvKCggLCwsIYJXjRpi387yaHUfGxt9GUBfj2SgZvanl+OpFOkqSSzUMMrv52k+ldx9vBWFGoqySwoo1+0L3d2D73q76kQQlSb0iucJRvjOXOxiNJyLU4OtpYOqdFpFglTy5Yt2bZtG8XFxRQUFBAUFMSkSZOIiooiMFC/cntGRgZBQUGG12RmZl7R6lRNrVajVst0bVE3nU5h5Z5zdI/won2wR419iqJwqqoK77rH+nE+r4RHV8by7f4UAFoFuHJrp2De3BCPokC/aB+eHBpj9msQQjR+fm5qfF0dyCoqJ/5CIZ3DPC0dUqPT5Ad9X87FxYWgoCByc3P5448/GD9+vCFp2rBhg+G48vJytm3bRt++fS0YrWgK1h+/wL9/PMZT38RdsS8tv4wiTSV2NipaB7oxsn0gnUMvJVWPDGjJP4bGMGdEKyJ9nHn+1nZmjFwI0dRImYEb0ywSpj/++IPff/+dxMRENmzYwODBg2ndujXTp09HpVIxc+ZMXn75ZdauXcvRo0eZNm0azs7OTJkyxdKhi0ZuV0IWAGcyi0jOLqmxL/6CvnUpytcFBzsb/e/i8FYAhHg6GcYZPDEkhq1PD5YVx4UQN6RNYNX6clLI8ro0iy65/Px85s+fT2pqKt7e3txxxx289NJL2Nvrp2LPnTuX0tJSHnvsMXJzc+nVqxfr16/Hzc3NwpGLxm7P2RzDz1vjM7m/T6Th+emqhKlVwKXfs8Gt/Vn5YC/CvJ1wsGsW32eEEGbSJqhmC9Oes9msiT3Pv8a0ldIk9dAsEqaJEycyceLEq+5XqVQsXLiQhQsXmi8o0eTlFJdz6sKlb3JbT12skTBVz3aLCXCt8br+Mb5miU8I0bxUtzCdzCjUr3Dxv+OcSC/A313N7BGtLRyd9ZOvsEI0kL2J+tYlN7X+e8muhCzKKrS8tfE0o5ZuZ/0xfUmL1gHSkimEaHjR/q7Y2qjIK6kgNjmPE1WlStbEnkenk4KWdWkWLUxCmMuFgjLe33KGX46kU16pA2Bcl2A2ncgko6CMR1YcYFv8xRqviZGESQhhBo72trTwdeF0ZhFLNsQbtp/PK+Wvs9n0jZbW7WuRFiYhTESrU7j30z18sfscWUXlFJRVAtCnpQ8zh+nLAfw9WQKIlPXfhBBmMqCVHwA7zugnpFS3gP9wINViMTUWkjAJYSI/H07jdGYRHk72LJvWk4Vj2zFreCtGdwhi8k3hvHFXZxxsbegf7ctzt7QFoGu4J3a28s9QCGEeTw2Lwd/tUh3B58fqy5X8fCSdjHxZnPdapEtOiOuwas85dp3J5qXbO+Dp7KAfm7TpNAAPD2jB4Db+V7zmzu6hjOoQiLO9LSoVtA50I8rXxdyhCyGaMXdHe168rQOPrDhAqwBX7uoeyvf7U9iXlMuH2xJYOK69pUO0WpIwiWYlJaeEgrKKK6puG0OrU3jl15MUaiqp1OnoGOLBpzsSySupwNPZnvv7RFz1ta7qS//kbo7xu+4YhBDieo1sH8jq/+tLkIejvv7bsFbc8+kevtqbzPguwbQJdKe0Qou3S+2LgTdXkjCJZkNRFCZ//BeZhWXsmjcUP7frW97mRHoBhRr9+KQ/jl3gj2MXAAjycOTF8R1wc5R6JkII69Y9wsvwc9+WPtwU5c3exBxuf38XNirQKfDVjF70jvKhsKxS6jQhY5hEM5JRUMb5vFIqtJfWcDNGkaaStKrZJHCptcjDyZ43J3ZmxzNDGNau9vUHhRDCWqlUKt6d0pUJ3UIMyRLAr0fSWbrpNJ0XrWfH6SzLBmkFpIVJNBvVNUcAErOLjSoQqSgK9322h2PnCwj1dgLgiSHRdI/wIsrXBV9XWYxZCNF4+bs58ubELvxrTFs2Hr/AvDVH+OtsDkVVs31/OnSeQA9Hvt2XzD+GxjTLlnRpYRLNxuXrJyVlFV/z2EqtjtUHUjmfVwrAwZQ8DibnUa7Vcfai/rW9W/jQM9JbkiUhRJPh66pmRPtAQL8GZkaBfubc7rPZPL/uKJ/8mciXu89ZMkSLkYRJNBuXtzDVlTCtjk1l9veHuPXtPzlwLpev9yTX2O/iYEuHYFkMVwjR9Hi7ONDqb0s2peSU8leifjjCoZS8Gvs2HL/AqKXbOZ5WQFMmCZNoNk5eNm4pMfvaCdOmE5kA5JZUMOmj3ayLOw/AhK4hgL74m9RPEkI0Vb2ifK7YplSNbTpyPt+wTVOp5d8/HuVkRiGrY5t28Uv5xBfNQlmFlrMXiwzPU3JKqNTqaj22vFLHrgT9N6lu4Z5U6hQqtArR/q78d2Jnvn+0D69M6GSWuIUQwhJuivI2/Dy+S3CNfen5ZWQW6rvq1sSeJ72q4KW0MAnRCJ2+UFij2fj0hSJ0Cng52+NgZ0OFViEtr4wKrY5v9yVzoeBShdvY5FyKNJV4uzjww6N9Wf1/fXmgXxT/vaszKpWKnpHeMsVWCNGkDYjxI8jDkaFt/JnQLdSwvbocy9Hz+Wh1Ch9sTTDsO5FRgKI03UV8ZZacaHJKyiu588PdlJZr2TZ3EK5qOz7fmQhA2yB3LhZqOJ1ZRGJ2MWsPnmfJxnhu6RTEe1O6AbC9ar23m2N8sbFR0T3Cq0bNEiGEaOo8nO3ZPX8oiqJvYR/dIZAoXxcyCspYE3uew6n5eDk7kJxTgpujHSXlWvJKKsgoKCPIw4mTGQXY29rQ0s+17jdrJCRhEmZXodXx6IoD+LmpeeUO03dtbTh+gfzSCkA/FumbfckcPa9vKr6tSwgbTlzgdGYR8RmFrPgrCYDdCdkoioJWp7D+uL4Q5cBWUolbCNG8qVQqHOxUfHBvdwCW70xkTex5jqTm42hvC0CfFj4kZRcTf6GIE+kFVFQqjHtnJ6jg/Sndmkx9OkmYhNkdOZ/PppP6QdXzRrfB09m05ffXHjxv+PndzWfIKCjDVW3HB/d24+YYP85UjWX6dMdZsorKAcgpLifhYhG/HcngTGYRbo52DG595XpwQgjRnHUM1S8rdTBFX2YF9OOdnBxsqxKmQjaeyDTse2TlAVY8cBN9o+tf985ayRgmYXYHk/MMP5+8jorb15JVpOHPyyrSVtcQGdcl2LB224Cq/14o0ACgUumPXb4rybCA7qLx7fGSdZSEEKKGjiGe+Lg4kFNcbvis7d3Ch7ZB+jIrW09l8sN+/Wy5zmGeaHUKn+9MMrz+l8PpbKhqxW9sJGESZhebnGv4+XqWKAH9TLY/julbg77fn8L0ZXs5kprPb0fS0eoUOoV64H/ZWnGTeoQZfu4f48uy6T1pE+hGSz8X7uutXyx35V/JVOr0ffW3dQm5zqsTQoimy8HOhsk3Xfo8dVPb0TbI3ZAw7UvKpVyro2ekF69VDbnYHn+RgrIKNp+8wONfxfLoygNkF2ksEv+NkC45YXZxf2th+nZfMs4OdgxvF8Bt7+3E0d6WHx7tc806Rx9vT+CN9fFXbLepai4a0zGIsxeL+G5/Km0C3ehU1YxcbXBrf0OX2/b4i4bKtQ52Njx3aztU1c1OQggharinVwQfbE1Ap0CPSC9sbVR0DPHAyd6W0gotge6OLBjbnlYBrkT7u3Ims4jv9qXw0fazAGh1CtviLzKhWyiVWh2HUvOJCXDF3cqXW5GEqRF4b8sZDibn8d49XVHb2Vo6nGtKyirm9fWnaBfkzuODowFIzi7hq73JjO0chK+r2rDcCMCG4xl8vTcZlQpmDWtl6KJbf/wCYzoGXfV9/jh2qUm3+h/proRsbG30ic6AGD+GtPHn1IUiZg1vdc0EqFuEl2HByQf6RRHi6XRD90AIIZqyYE8nRncI4pcj6Qyomhzj7eLAj0/0o0hTSedQT8Nn8a2dgli68TT/+eVEjXNsOaVPmJbvSuI/v5zAwc6G6f0imTeqjdV+YZWEycqVVWh5a+NpyrU69ifl0q8eA+dOXyjkeHoB4zoHm/UXb+PxCzzxdSxlFTp+P5rB/X0icHO0Z9HPx9l44gIfb0+gR4S+GJqr2o4iTaVh0LWiwJsbL7UYLd+ZVCNh2nkmix1nsigt13J71xBDpdk/5w4m0MORQa9vNSRivq5q2gS6YWOj4sfH+9UZt6vajhk3t+BoWj6PDW5psvshhBBN1St3dGRUh0BGdwg0bGsV4HbFcdUJE0C4tzMPD2jBc+uOsj3+IpVaHTvP6MdBlVfq+GjbWQbE+NXr75wlSMJk5Q5dNhMhMau4Xr9Is78/xOHUfNR2NozqcPVWmutVPf3+8i4zRVF4+dcTlFXoY9XqFHYnZDOotT+7E/T/IHQK7E3KAWB0h0DWxZ2nQqtcdg79f+1sVOxNymHxbyfoGuZJfmkFz6w+YjjuhwP6AYUdQtwJ83YGYHAbP1b+pV/vrbp+kjHmj2lr1PFCCNGcuTnaM7ZzcJ3HRfu7sXRSF4rLK7mzeyh2Nja8sf4UeSUVxKXkcayqOni7IHeOpxfw4bYEq02YZNC3ldubmGP4ObGOBWMBdDrF0K216m8LxtZHhVZHSk7JNY9ZsiGetv/+nQPnLsW2LymXs1nFODvYGtZb23Emi4PJuRSXa/F1deCHR/swrG0Afm5q7u4Vbiho5uZoR6SPPvHpF+3DLZ30Sd5H287y6MpYQ7I0vF0AjvY2FGkqgZp1koa0uVQC4OYY6/zHJoQQzdFtXUO4p1cEajtbbG1UhpnK3+5LIbNQg0oFb03ugq2Nij9PZ3EkNb+OM1qGJExWrrpFBuqXMKXll1JeqW/l+fN0Vq3JT2aBfkmQahVaHfklFWh1CtOW7eXm17aw52x2recv1lTy2Y5EKrQKn+1INGz/Zp8+ORvbKZgR7fVNtDtOZxmmnfaL9qVHpDefTu3BvmeH0S3ci3ZVsypu6RjEs7e0I8zbiX8MieH5W9sxc1gMk3uGGWa63dU9lI/u7c7jg6IN7zmw1aUkqW9LXzyd7VHb2dBfEiYhhLBaQ9vqP7vXVNXMa+nnSkyAG+OqWqw+3J5w1ddaknTJWbFKrY4D5y5NwU/MKib+QiHJ2SVXrZz696Tqo+0JPDKgJV/tTWZIG3+cHWwZ9+5OWvi68Pm0noR5O/Ps2iN8tz+VzqEeHKrK7L/bn0qvFleuVv3z4TSKy7UAbDyeyXtbzrBsZxLZxfopopNuCqOlnys2KjibVWxYvbq6BtLlHh8SjbPaln8MicHf3ZHhl13TzGGtDPcgKbuYln6uqFQqZgxowZZT+qKXXcM9DcdXz6wrq9Dh7+Z47RsrhBDCYga38cfeVmUYktE+WP/l+ZGBLVh78Dy/HUknMauYKF8XS4Z5BWlhsmLH0gooKdfiUDVWKDmnhGmf7+WhL/dzLK32JsukqoTJs2px2JV/JTPg9S18sDWBJ786yPf7U9HqFE5nFnH7+zs5lpZvqIx96LJm0PXHMwwtVZf7em+K4edyrY7X/zhFVpEGRYEeEV50DfPEw8mezmGeAIZVrGvrJmvp58p/buuIv/vVExw7Wxui/d0Mg9cd7W1Z81g/1jzWD/u/lR2I9nejQ4hHbacRQghhJdwd7el92RfyDsH6z+02ge4MaeOPToGPq0oQABSWVTDn+0NkXrZIuiVIwmTFqscv9Y/xxcneFq1OIa0qAYlLyatxbFaRhkMpeZytSpju6h7KwrHtcLK3NQymzigoY9Uefb0hT2d7sorKeXD5fiq0CiGeTnQL9+SJwdH4uakpLKtkx5mLNd7j6Pl84lLysLNR8ejAS7PJ7r4pjD/nDubbR/oYEptHB7Yk3NsZDyd77uweSsA1kiIhhBDNS/XQDbjUwgTwf4P0f1tWH0glr6ScrCINd3/yFz8cSOWxVbEoinLFucxFuuSs2NC2/tjYqAjzciI9v4wT6QWGfSfTL1XITsoqZuJHu8ks1BDkoU9MonxdmdIrnFEd9AUc/ziWwRe7z1GhVXBV2/HelG7c8+kew9IhU3qFG+omFZZV8MXuc/x8KJ0hbQIoKa/E0c6Wt6uWDbmlUxAPD2jBz4fTaOnnygvjOuBgVzP3Htk+kJGX/YMQQgghqo1oF8CCH49ia6OiffClnoGekd60DXLnRHoBvxxJZ8Xuc5zMKMTHxYGF49pbtEaTJExWrIWfKy2qZpL9GJdWM2HK0P+cWVjGPZ/uIbNQP4aougss0lc/6yzQw5FAD0fcnez5oqqa9bC2/vSL9qVPCx92Vw3uHtvp0vTQsZ2D+WL3OdbGncfPXc2K3efwcnbgfF4pKhU8OSQabxcH/pw7GMBqi4wJIYSwTgHujnw6tQcqVHg416zwfWunIE6kF/DKbycpLKvEy9me7x/tY/h7aCnSJddI/H3w28n0QhRF4cWfT3A+rxTvvy0U28K35i9W+2B3w/Igt1VN+//n8FbY2qjo29KH8Kpp/QDdI7y4+6YwFEU/tb+kXGsoCnlrp2Ci/fXFyVQqlSRLQgghrsuQNgEMvqwkTLXqL/CFZfoSMg/2j7J4sgTSwtRoVM8IG94ugK2nMinUVPL9/lT+dygNGxV8Mf0mHlmxn7T8MpzsbQlwV9d4vUql4pP7e3D6QpFh2v1NUd5smjUQH1eHK459YVwHEjKL2ZuUw9Q+Ebio7TiUmsfcka3Ncr1CCCGap3AfZ8OsbVe1Hff1ibR0SEAzaGGqrKzkueeeIyoqCicnJ1q0aMGiRYvQ6S7NAJs2bZqhtaT60bt3bwtGfaUhbfz5akYv/juxs6Hg49zVhwG4r3cEHUM9uL2bvuUo0tel1pafAHfHK2oURfq64FbLgocOdjasmtGLrXMG8cL4Dswd1YZVD/U2VNYWQgghGso9vSMAeGRACzycrGNR3ibfwvTqq6/y4Ycf8sUXX9C+fXv279/P9OnT8fDw4KmnnjIcN2rUKJYtW2Z47uDgUNvpLEalUtG3pT7ZaRvkbqjmHeThyKwR+lafqX0jOZSSzx3dQ0zynva2NkRaWR0MIYQQTd9d3UPpH+1rmMhkDZp8wrR7927Gjx/PLbfcAkBkZCRff/01+/fvr3GcWq0mMLBxzOpq6XcpifnvxM6G7NvfzZGVD/WyVFhCCCGESahUKoI9nSwdRg1Nvkuuf//+bNq0ifj4eAAOHTrEjh07GDNmTI3jtm7dir+/P61atWLGjBlkZmZe9ZwajYaCgoIaD3Ma1zmECB9n5o1uY2h1EkIIIUTDUSmWrAJlBoqi8K9//YtXX30VW1tbtFotL730EvPnzzcc8+233+Lq6kpERASJiYk8//zzVFZWcuDAAdRq9RXnXLhwIS+88MIV2/Pz83F3d79iuxBCCCGsT0FBAR4eHvX6+93kE6ZvvvmGp59+mtdff5327dsTFxfHzJkzefPNN5k6dWqtr0lPTyciIoJvvvmGCRMmXLFfo9Gg0WgMzwsKCggLC5OESQghhGhEjEmYmvwYpqeffpp58+YxefJkADp27Mi5c+dYvHjxVROmoKAgIiIiOH36dK371Wp1rS1PQgghhGiamvwYppKSEmxsal6mra1tjbICf5ednU1KSgpBQUENHZ4QQgghGoEm38I0duxYXnrpJcLDw2nfvj0HDx7kzTff5IEHHgCgqKiIhQsXcscddxAUFERSUhL/+te/8PX15fbbb7dw9EIIIYSwBk0+YXrnnXd4/vnneeyxx8jMzCQ4OJhHHnmEf//734C+tenIkSN8+eWX5OXlERQUxODBg/n2229xc3OzcPRCCCGEsAZNftC3ORgzaEwIIYQQ1sGYv99NfgyTEEIIIcSNkoRJCCGEEKIOkjAJIYQQQtRBEiYhhBBCiDpIwiSEEEIIUQdJmIQQQggh6iAJkxBCCCFEHSRhEkIIIYSoQ5Ov9G0O1bU/CwoKLByJEEIIIeqr+u92fWp4S8JkAoWFhQCEhYVZOBIhhBBCGKuwsBAPD49rHiNLo5iATqcjLS0NNzc3VCrVVY8rKCggLCyMlJQUWUKlAcl9Nh+51+Yh99l85F6bh7XcZ0VRKCwsJDg4GBuba49SkhYmE7CxsSE0NLTex7u7u8s/RDOQ+2w+cq/NQ+6z+ci9Ng9ruM91tSxVk0HfQgghhBB1kIRJCCGEEKIOkjCZkVqtZsGCBajVakuH0qTJfTYfudfmIffZfORem0djvM8y6FsIIYQQog7SwiSEEEIIUQdJmIQQQggh6iAJkxBCCCFEHSRhEkIIIYSogyRM9bB9+3bGjh1LcHAwKpWKdevW1dg/bdo0VCpVjUfv3r3rPO+RI0cYOHAgTk5OhISEsGjRohrr2WzduvWK86pUKk6ePGnqS7QalrrXABqNhmeffZaIiAjUajUtW7bk888/N+XlWQ1L3efazqtSqWjfvr2pL9FqWPJ3etWqVXTu3BlnZ2eCgoKYPn062dnZprw8q2HJ+/zee+/Rtm1bnJycaN26NV9++aUpL83qNMS9LisrY9q0aXTs2BE7Oztuu+22Wo/btm0b3bt3x9HRkRYtWvDhhx+a6KrqJpW+66G4uJjOnTszffp07rjjjlqPGTVqFMuWLTM8d3BwuOY5CwoKGD58OIMHD2bfvn3Ex8czbdo0XFxcmD17do1jT506VaMSqp+f3w1cjXWz5L2eOHEiFy5c4LPPPiM6OprMzEwqKytNc2FWxlL3+a233uKVV14xvKayspLOnTtz1113meCqrJOl7vWOHTu4//77WbJkCWPHjuX8+fM8+uijPPTQQ6xdu9Z0F2glLHWfP/jgA+bPn88nn3xCz5492bt3LzNmzMDLy4uxY8ea7gKtSEPca61Wi5OTE//4xz9YvXp1rcckJiYyZswYZsyYwcqVK9m5cyePPfYYfn5+V43DpBRhFEBZu3ZtjW1Tp05Vxo8fb9R53n//fcXDw0MpKyszbFu8eLESHBys6HQ6RVEUZcuWLQqg5Obm3mDUjZM57/Vvv/2meHh4KNnZ2TcadqNjzvv8d2vXrlVUKpWSlJRkbNiNkjnv9euvv660aNGixuvefvttJTQ09Lpib0zMeZ/79OmjzJkzp8brnnrqKaVfv37XFXtjY6p7XZ/Xz507V2nTpk2NbY888ojSu3fv634vY0iXnIls3boVf39/WrVqxYwZM8jMzKyxf9q0aQwaNMjwfPfu3QwcOLBG0a6RI0eSlpZGUlJSjdd27dqVoKAghg4dypYtWxryMhqFhrjXP/30Ez169OC1114jJCSEVq1aMWfOHEpLS81xSVapIX+nq3322WcMGzaMiIiIhriERqMh7nXfvn1JTU3l119/RVEULly4wA8//MAtt9xijkuySg1xnzUaDY6OjjXO4+TkxN69e6moqGiwa7F2xt7r+ti9ezcjRoyosW3kyJHs37/fLPdaEiYTGD16NKtWrWLz5s3897//Zd++fQwZMgSNRmM4JigoiPDwcMPzjIwMAgICapyn+nlGRobhNR9//DGrV69mzZo1tG7dmqFDh7J9+3YzXJV1aqh7ffbsWXbs2MHRo0dZu3YtS5cu5YcffuDxxx83w1VZn4a6z5dLT0/nt99+46GHHmqgq2gcGupe9+3bl1WrVjFp0iQcHBwIDAzE09OTd955xwxXZX0a6j6PHDmSTz/9lAMHDqAoCvv37+fzzz+noqKCrKwsM1yZ9bmee10fV/v/UVlZaZ57bZZ2rCaEWpof/y4tLU2xt7dXVq9efdVjhg8frjz88MM1tqWmpiqAsnv37qu+7tZbb1XGjh1rVMyNlTnv9fDhwxVHR0clLy/PcMzq1asVlUqllJSUXP9FNAKW+p1++eWXFR8fH0Wj0VxX3I2ROe/1sWPHlKCgIOW1115TDh06pPz+++9Kx44dlQceeOCGr8PamfM+l5SUKNOnT1fs7OwUW1tbJTg4WJk7d64CKBcuXLjha7F2prrXl7tal1xMTIzy8ssv19i2Y8cOBVDS09PrG/J1kxamBhAUFERERASnT5++6jGBgYFXfOuubrL8ewZ9ud69e1/zvM2Nqe51UFAQISEheHh4GI5p27YtiqKQmpraAJE3Lqb+nVYUhc8//5z77ruvzsGgzY2p7vXixYvp168fTz/9NJ06dWLkyJG8//77fP7556SnpzfcBTQSprrPTk5OfP7555SUlJCUlERycjKRkZG4ubnh6+vbcBfQiNTnXtfH1f5/2NnZ4ePjc0Pnrg9JmBpAdnY2KSkpBAUFXfWYPn36sH37dsrLyw3b1q9fT3BwMJGRkVd93cGDB6953ubGVPe6X79+pKWlUVRUZDgmPj4eGxsbQkNDGyz+xsLUv9Pbtm3jzJkzPPjggw0VcqNlqntdUlKCjU3Nj3hbW1uAK6bFN0em/p22t7cnNDQUW1tbvvnmG2699dYr7n9zVZ97XR99+vRhw4YNNbatX7+eHj16YG9vf0PnrpcGb8NqAgoLC5WDBw8qBw8eVADlzTffVA4ePKicO3dOKSwsVGbPnq3s2rVLSUxMVLZs2aL06dNHCQkJUQoKCgznmDdvnnLfffcZnufl5SkBAQHK3XffrRw5ckRZs2aN4u7urrzxxhuGY5YsWaKsXbtWiY+PV44eParMmzdPAerdrNkYWepeFxYWKqGhocqdd96pHDt2TNm2bZsSExOjPPTQQ2a9fnOx1H2udu+99yq9evUyy7VamqXu9bJlyxQ7Ozvl/fffVxISEpQdO3YoPXr0UG666SazXr+5WOo+nzp1SlmxYoUSHx+v7NmzR5k0aZLi7e2tJCYmmvPyzaoh7rWi6LuRDx48qIwdO1YZNGiQ4T2qnT17VnF2dlb++c9/KsePH1c+++wzxd7eXvnhhx/Mct2SMNVD9fT+vz+mTp2qlJSUKCNGjFD8/PwUe3t7JTw8XJk6daqSnJxc4xxTp05VBg4cWGPb4cOHlZtvvllRq9VKYGCgsnDhwhrTr1999VWlZcuWiqOjo+Ll5aX0799f+eWXX8xxyRZjqXutKIpy4sQJZdiwYYqTk5MSGhqqzJo1q8mOX7Lkfc7Ly1OcnJyUjz/+uKEv0ypY8l6//fbbSrt27RQnJyclKChIueeee5TU1NSGvmSLsNR9Pn78uNKlSxfFyclJcXd3V8aPH6+cPHnSHJdsMQ11ryMiImo97+W2bt2qdO3aVXFwcFAiIyOVDz74oKEv10ClKNI2K4QQQghxLdLBKoQQQghRB0mYhBBCCCHqIAmTEEIIIUQdJGESQgghhKiDJExCCCGEEHWQhEkIIYQQog6SMAkhhBDCoqZNm8Ztt91m6TCuSRImIYQQwsotXryYnj174ubmhr+/P7fddhunTp2qcYyiKCxcuJDg4GCcnJwYNGgQx44dM+zPycnhySefpHXr1jg7OxMeHs4//vEP8vPza5xn3LhxhIeH4+joSFBQEPfddx9paWnXjG/r1q2oVKorHs8995zpbkIt6rrmvx87evRoVCoV69atM/q9JGESQjRb1R/yeXl5lg5FiGvatm0bjz/+OH/99RcbNmygsrKSESNGUFxcbDjmtdde48033+Tdd99l3759BAYGMnz4cAoLCwFIS0sjLS2NN954gyNHjrB8+XJ+//33K9Z0HDx4MN999x2nTp1i9erVJCQkcOedd9YrzlOnTpGenm54zJs3z3Q3oRZ1XfPlli5dikqluv43M1tNcSGEsLCBAwcqTz31lOG5RqNR0tPTr1hSRAhrl5mZqQDKtm3bFEVRFJ1OpwQGBiqvvPKK4ZiysjLFw8ND+fDDD696nu+++05xcHBQKioqrnrMjz/+qKhUKqW8vPyqx1Qvl5Kbm1vr/tTUVGXixImKp6en4u3trYwbN67GentTp05Vxo8fryxcuFDx8/NT3NzclIcffljRaDRXfU9jrjkuLk4JDQ1V0tPTFUBZu3btVc97NdLCJIRothwcHAgMDLyxb51CWEB1N5q3tzcAiYmJZGRkMGLECMMxarWagQMHsmvXrmuex93dHTs7u1r35+TksGrVKvr27Yu9vf11xVpSUsLgwYNxdXVl+/bt7NixA1dXV0aNGkV5ebnhuE2bNnHixAm2bNnC119/zdq1a3nhhReuet76XnNJSQl333037777LoGBgdd1DSBdckKIZmLatGls27aNt956yzC+Yvny5TW65JYvX46npyc///yzYZzHnXfeSXFxMV988QWRkZF4eXnx5JNPotVqDecuLy9n7ty5hISE4OLiQq9evdi6datlLlQ0eYqiMGvWLPr370+HDh0AyMjIACAgIKDGsQEBAYZ9f5ednc2LL77II488csW+Z555BhcXF3x8fEhOTubHH3+sV2yhoaG4uroaHtnZ2XzzzTfY2Njw6aef0rFjR9q2bcuyZctITk6u8e/EwcGBzz//nPbt23PLLbewaNEi3n77bXQ6Xa3vVd9r/uc//0nfvn0ZP358va7hampPKYUQool56623iI+Pp0OHDixatAig1sGhJSUlvP3223zzzTcUFhYyYcIEJkyYgKenJ7/++itnz57ljjvuoH///kyaNAmA6dOnk5SUxDfffENwcDBr165l1KhRHDlyhJiYGLNep2j6nnjiCQ4fPsyOHTuu2Pf31lJFUWptQS0oKOCWW26hXbt2LFiw4Ir9Tz/9NA8++CDnzp3jhRde4P777+fnn39GpVLRvn17zp07B8DNN9/Mb7/9Znjdn3/+iZubm+G5l5cXBw4c4MyZMzW2A5SVlZGQkGB43rlzZ5ydnQ3P+/TpQ1FRESkpKezYsaNGYvfbb79ha2tb5zX/9NNPbN68mYMHD15xjcaShEkI0Sx4eHjg4OCAs7OzoVn+5MmTVxxXUVHBBx98QMuWLQG48847WbFiBRcuXMDV1ZV27doxePBgtmzZwqRJk0hISODrr78mNTWV4OBgAObMmcPvv//OsmXLePnll813kaLJe/LJJ/npp5/Yvn07oaGhhu3Vv9MZGRkEBQUZtmdmZl7RAlNYWMioUaNwdXVl7dq1tXa1+fr64uvrS6tWrWjbti1hYWH89ddf9OnTh19//ZWKigoAnJycarwuKioKT0/PGtt0Oh3du3dn1apVV7yPn59fndesUqkYN24cvXr1MmwLCQkhPT29zmvevHkzCQkJV8R0xx13cPPNNxvVEiwJkxBCXMbZ2dmQLIG+eT8yMhJXV9ca2zIzMwGIjY1FURRatWpV4zwajQYfHx/zBC2aPEVRePLJJ1m7di1bt24lKiqqxv6oqCgCAwPZsGEDXbt2BfRdxdu2bePVV181HFdQUMDIkSNRq9X89NNPODo61uu9Qf87DRAREWFU7N26dePbb7/F398fd3f3qx536NAhSktLDUnYX3/9haurK6GhodjY2FzRQlWfa543bx4PPfRQjdd17NiRJUuWMHbsWKOuQxImIYS4zN+/batUqlq3VY+r0Ol02NracuDAAUMXQbXLkywhbsTjjz/OV199xY8//oibm5thjI6HhwdOTk6oVCpmzpzJyy+/TExMDDExMbz88ss4OzszZcoUQN+yNGLECEpKSli5ciUFBQUUFBQA+pYeW1tb9u7dy969e+nfvz9eXl6cPXuWf//737Rs2ZI+ffpcV+z33HMPr7/+OuPHj2fRokWEhoaSnJzMmjVrePrppw0tZeXl5Tz44IM899xznDt3jgULFvDEE09gY1P7cOv6XHNgYGCtA73Dw8OvSDrrIgmTEKLZcHBwqDFY2xS6du2KVqslMzOTm2++2aTnFqLaBx98AMCgQYNqbF+2bBnTpk0DYO7cuZSWlvLYY4+Rm5tLr169WL9+vaFl5sCBA+zZsweA6OjoGudJTEwkMjISJycn1qxZw4IFCyguLiYoKIhRo0bxzTffoFarryt2Z2dntm/fzjPPPMOECRMoLCwkJCSEoUOH1mhxGjp0KDExMQwYMACNRsPkyZNZuHDhNc9d1zWbkkqpbmsTQogm7uGHHyYuLo7vvvsOV1dXDh8+zNChQ8nNzcXT05Ply5czc+bMGoUsFy5cyLp164iLizNsmzZtGnl5eYZqwffeey87d+7kv//9L127diUrK4vNmzfTsWNHxowZY96LFEI0CCkrIIRoNubMmYOtrS3t2rXDz8+P5ORkk5x32bJl3H///cyePZvWrVszbtw49uzZQ1hYmEnOL4SwPGlhEkIIIYSog7QwCSGEEELUQRImIYQQQog6SMIkhBBCCFEHSZiEEEIIIeogCZMQQgghRB0kYRJCCCGEqIMkTEIIIYQQdZCESQghhBCiDpIwCSGEEELUQRImIYQQQog6SMIkhBBCCFGH/wfr9h/ZLjmYBgAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -757,9 +820,9 @@
     "\n",
     "The last stat that IEC-40 requests are the decidecade SPLs, where the SPL is calculated for each decidecade frequency band. Note that the IEC-40 labels these as synonymous the third-octave SPLs; while for some applications this may be true, mathematically they have different definitions. \n",
     "\n",
-    "To explain, a true octave is a frequency band where the upper frequency is double (i.e., base 2) that of the lower frequency. Third octaves are often measured because mammals to have evolved to interpret sound at this bandwidth. The true one-third octave is a frequency band where the upper frequency is 2^(1/3) = 1.25992 times the lower frequency. The decidecade band referenced by the IEC-40 refers to the one-tenth octave of base 10, where the upper frequency is 10 times that of the lower frequency. Mathematically this means the decidecade band has a bandwidth of 10^(1/10) = 1.25892. So, when reporting frequency analysis, it is important to note both the octave and its bandwidth.\n",
+    "To explain, a true octave is a frequency band where the upper frequency is double (i.e., base 2) that of the lower frequency. Third octaves are often measured because mammals to have evolved to interpret sound at this bandwidth. The true one-third octave is a frequency band where the upper frequency is 2^(1/3) = 1.25992 times the lower frequency. The decidecade band referenced by the IEC-40 refers to the one-tenth octave of base 10, where the upper frequency is 10 times that of the lower frequency. Mathematically this means the decidecade band has a bandwidth of 10^(1/10) = 1.25892. In general, when reporting frequency analysis, it is important to note both the octave and its bandwidth.\n",
     "\n",
-    "We can calculate the SPL in each decidecade band using the function `decidecade_sound_pressure_level`. This function uses the same calculation as `sound_pressure_level` above and runs it on each tenth octave band. It returns 1 SPL in each frequency band every timestamp, so our boxplots show 5 minutes worth of SPL measurements in each decidecade band. You'll notice a similar spread as in the SPSDL boxplots, especially in the upper quantile. Boats are loud."
+    "We can calculate the SPL in each decidecade band using the function `decidecade_sound_pressure_level`. This function uses the same calculation as `sound_pressure_level` above and runs it on each tenth octave band. It returns 1 SPL in each frequency band every timestamp, so our boxplots show 5 minutes worth of SPL measurements in each decidecade band. You'll notice a similar spread as in the SPSDL boxplots, especially in the upper quantile."
    ]
   },
   {
@@ -767,15 +830,23 @@
    "execution_count": 20,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:96: UserWarning: `fmax` = 48000 is greater than the Nyquist frequency. Settingfmax = 39810.71705534977\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x24600155790>,\n",
-       "  <matplotlib.axis.XTick at 0x246001a3c90>,\n",
-       "  <matplotlib.axis.XTick at 0x24603434350>,\n",
-       "  <matplotlib.axis.XTick at 0x246001d7290>,\n",
-       "  <matplotlib.axis.XTick at 0x24602e809d0>,\n",
-       "  <matplotlib.axis.XTick at 0x24602e81b10>],\n",
+       "[[<matplotlib.axis.XTick at 0x238fa9ff050>,\n",
+       "  <matplotlib.axis.XTick at 0x238f0048150>,\n",
+       "  <matplotlib.axis.XTick at 0x238f6c6fa10>,\n",
+       "  <matplotlib.axis.XTick at 0x238f6d1ec90>,\n",
+       "  <matplotlib.axis.XTick at 0x238f24eef90>,\n",
+       "  <matplotlib.axis.XTick at 0x238f6c886d0>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -794,7 +865,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x400 with 2 Axes>"
       ]
@@ -808,7 +879,7 @@
     "spl10 = acoustics.decidecade_sound_pressure_level(spsd, fmin, fmax)\n",
     "\n",
     "# Plot the decidecade sound pressure level\n",
-    "fig, ax = plt.subplots(1,2, figsize=(10, 4), constrained_layout=True)\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
     "fig, ax[0] = acoustics.graphics.plot_spectra(spl10.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
     "ax[0].fill_between(\n",
     "    spl10[\"freq_bins\"],\n",
@@ -858,15 +929,23 @@
    "execution_count": 21,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:96: UserWarning: `fmax` = 48000 is greater than the Nyquist frequency. Settingfmax = 41285.092962955234\n",
+      "  warnings.warn(\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x246064476d0>,\n",
-       "  <matplotlib.axis.XTick at 0x24606434350>,\n",
-       "  <matplotlib.axis.XTick at 0x24606421e50>,\n",
-       "  <matplotlib.axis.XTick at 0x246061d4350>,\n",
-       "  <matplotlib.axis.XTick at 0x24606460e10>,\n",
-       "  <matplotlib.axis.XTick at 0x24606462ed0>],\n",
+       "[[<matplotlib.axis.XTick at 0x238f24af010>,\n",
+       "  <matplotlib.axis.XTick at 0x238f3bde790>,\n",
+       "  <matplotlib.axis.XTick at 0x238f406a590>,\n",
+       "  <matplotlib.axis.XTick at 0x238f4036e10>,\n",
+       "  <matplotlib.axis.XTick at 0x238f4441bd0>,\n",
+       "  <matplotlib.axis.XTick at 0x238f4443c90>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -885,7 +964,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x400 with 2 Axes>"
       ]
@@ -899,7 +978,7 @@
     "spl3 = acoustics.third_octave_sound_pressure_level(spsd, fmin, fmax)\n",
     "\n",
     "# Plot the decidecade sound pressure level\n",
-    "fig, ax = plt.subplots(1,2, figsize=(10, 4), constrained_layout=True)\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
     "fig, ax[0] = acoustics.graphics.plot_spectra(spl3.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
     "ax[0].fill_between(\n",
     "    spl3[\"freq_bins\"],\n",
@@ -946,7 +1025,7 @@
     "The National Marine Fisheries Service (NMFS) publishes auditory weighting functions for five groups of marine mammals. These weighting functions are designed to try to emulate the auditory sensitivity of each group to better predict auditory injury thresholds. They are mathematically equivalent to band-pass filters. A link to the latest recommendations from NMFS is [here](https://www.fisheries.noaa.gov/national/marine-mammal-protection/marine-mammal-acoustic-technical-guidance-other-acoustic-tools).\n",
     "\n",
     "The SEL function `sound_exposure_level` has a few inputs. One is the pressure spectral density (PSD) in Pa^2/Hz, found from `sound_pressure_spectral_density`. The 'n_bin' input to that function should be the same length of time as you want to calculate SEL for. If you would like to calculate the 24 hr SEL, you need 24 hours worth of data - the best way to do this and save computer RAM would be to calculate the PSD from each 1-5 minute individual file and then concatenate the PSD from each file together.\n",
-    "Set \"group=None\" to calculate the standard SEL. Set \"group\" to \"LF\" for 'low frequency' cetaceans; \"HF\" for 'high frequency' cetaceans; \"VHF\" for 'very high frequency' cetaceans; \"PW\" for phocid pinnepeds; and \"OW\" for otariid pinnepeds.\n"
+    "Set `group=None` in `sound_exposure_level` to calculate the standard SEL. Set `group` to 'LF' for \"low frequency\" cetaceans; 'HF' for \"high frequency\" cetaceans; 'VHF' for \"very high frequency\" cetaceans; 'PW' for phocid pinnepeds; and 'OW' for otariid pinnepeds.\n"
    ]
   },
   {
@@ -961,12 +1040,12 @@
       "<xarray.DataArray 'sel' (time: 1)> Size: 4B\n",
       "array([136.9158], dtype=float32)\n",
       "Coordinates:\n",
-      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996493339\n",
+      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
       "Attributes:\n",
       "    units:             dB re 1 uPa^2 s\n",
       "    long_name:         Sound Exposure Level\n",
       "    weighting_group:   None\n",
-      "    integration_time:  300 s\n",
+      "    integration_time:  300\n",
       "    freq_band_min:     50\n",
       "    freq_band_max:     48000\n",
       "\n",
@@ -1006,7 +1085,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Compare this to the 5 minute SPL:"
+    "Compare the above-printed SEL values for each group to the 5 minute SPL:"
    ]
   },
   {
@@ -1021,12 +1100,13 @@
       "<xarray.DataArray (time: 1)> Size: 4B\n",
       "array([112.14459], dtype=float32)\n",
       "Coordinates:\n",
-      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996493339\n",
+      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
       "Attributes:\n",
-      "    units:          dB re 1 uPa\n",
-      "    long_name:      Sound Pressure Level\n",
-      "    freq_band_min:  50\n",
-      "    freq_band_max:  48000\n"
+      "    units:            dB re 1 uPa\n",
+      "    long_name:        Sound Pressure Level\n",
+      "    time_resolution:  300\n",
+      "    freq_band_min:    50\n",
+      "    freq_band_max:    48000\n"
      ]
     }
    ],
@@ -1039,7 +1119,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can look at the specific marine mammal auditory weighting and noise exposure functions as well using `nmfs_auditory_weighting`, given a frequency vector and one of the mammal groups. It outputs the weighting function and the exposure function (the inverse of the former) in units of dB. To convert back to a unitless magnitude, use `10 ** (<func> / 10)`. The exposure function shows the SEL in dB at and above which temporary or permanent hearing damage can occur to an individual in the specified group. The minimum value in the exposure function is the known or estimated injury level for a given group."
+    "We can look at the specific marine mammal auditory weighting and noise exposure functions as well using `nmfs_auditory_weighting`, given a frequency vector of the data and one of the mammal groups. It outputs the weighting function and the exposure function (the inverse of the former) in units of dB. To convert back to a unitless magnitude, use `10 ** (<func> / 10)`. The exposure function shows the SEL in dB at and above which temporary or permanent hearing damage can occur to an individual in the specified group. The minimum value in the exposure function is the known or estimated injury level for a given group. Below is plotting the sensitivity curves and injury level for the \"low frequency\" cetaceans group."
    ]
   },
   {
@@ -1062,7 +1142,7 @@
     "# Calculate weighting and exposure functions\n",
     "weight_func, exp_func = acoustics.nmfs_auditory_weighting(spsd_300s[\"freq\"], group=\"LF\")\n",
     "\n",
-    "fig, ax = plt.subplots(1,2, figsize=(7,4), subplot_kw={\"xscale\": \"log\"}, constrained_layout=True)\n",
+    "fig, ax = plt.subplots(1, 2, figsize=(7, 4), subplot_kw={\"xscale\": \"log\"}, constrained_layout=True)\n",
     "ax[0].plot(spsd_300s[\"freq\"], weight_func, label=\"Weighting Function\")\n",
     "ax[0].axhline(y=0, color='k', linestyle='--', label=\"Highest Sensitivity\")\n",
     "ax[0].set(ylabel=\"Transmission [dB]\", ylim=(-50, 20))\n",
@@ -1071,12 +1151,12 @@
     "ax[1].plot(spsd_300s[\"freq\"], exp_func, label=\"Exposure Function\")\n",
     "ax[1].axhline(y=exp_func.min(), color='k', linestyle='--', label=\"Highest Sensitivity\")\n",
     "ax[1].fill_between(spsd_300s[\"freq\"], exp_func, np.ones_like(exp_func)*300, color='red', alpha=0.2, label=\"Injury Region\")\n",
-    "ax[1].set(ylabel=\"Exposure Level [dB]\", ylim=(exp_func.min()-20, exp_func.min()+50))\n",
+    "ax[1].set(ylabel=\"Exposure Level [dB]\", ylim=(exp_func.min() - 20, exp_func.min() + 50))\n",
     "ax[1].legend(loc=\"lower right\")\n",
     "\n",
     "for a in ax:\n",
     "    a.grid()\n",
-    "    a.set(xlabel=\"Frequency [Hz]\", xlim=(10,48000))"
+    "    a.set(xlabel=\"Frequency [Hz]\", xlim=(10, 48000))"
    ]
   },
   {
diff --git a/examples/data/acoustics/WISPR_230825_003936.dat b/examples/data/acoustics/WISPR_230825_003936.dat
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HcmV?d00001

diff --git a/mhkit/acoustics/__init__.py b/mhkit/acoustics/__init__.py
index 0c84970f0..605eb2dba 100644
--- a/mhkit/acoustics/__init__.py
+++ b/mhkit/acoustics/__init__.py
@@ -18,11 +18,19 @@
 from mhkit.acoustics import io, graphics
 from .analysis import (
     minimum_frequency,
+    create_frequency_bands,
     sound_pressure_spectral_density,
     apply_calibration,
+    convert_to_third_octave,
+    convert_to_decidecade,
+    convert_to_millidecade,
+)
+from .spsdl import (
     sound_pressure_spectral_density_level,
     band_aggregate,
     time_aggregate,
+    time_summation,
+    time_average,
 )
 from .spl import (
     sound_pressure_level,
diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index 7c297ee88..5bfe1ae9c 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -7,47 +7,59 @@
 
 The following functionality is provided:
 
-1. **Frequency Validation and Warning**:
+1. **Type Validation**:
+
+   - `_check_numeric`: Validates that a value is of numeric type (int or float).
+
+2. **Frequency Validation and Warning**:
 
    - `_fmax_warning`: Ensures specified maximum frequency does not exceed the Nyquist frequency,
      adjusting if necessary to avoid aliasing.
 
-2. **Shallow Water Cutoff Frequency**:
+3. **Shallow Water Cutoff Frequency**:
 
    - `minimum_frequency`: Calculates the minimum frequency cutoff based on water depth and the
      speed of sound in water and seabed materials.
 
-3. **Spectral Density Calculations**:
-
-   - `sound_pressure_spectral_density`: Computes the mean square sound pressure spectral density
-     using FFT binning with Hanning windowing and 50% overlap.
+4. **Calculation of Frequency Bands**:
 
-4. **Calibration**:
+    - `create_frequency_bands`: Generates frequency bands based on specified octave divisions,
+      minimum and maximum frequency limits, and the chosen base
+      (e.g., 2 for octaves, 10 for decades).
 
-   - `apply_calibration`: Applies calibration adjustments to the spectral density data using
-     a sensitivity curve, filling missing values as specified.
+5. **Sound Pressure Spectral Density Calculation**:
 
-5. **Spectral Density Level Calculation**:
+    - `sound_pressure_spectral_density`: Computes the mean square sound pressure spectral density
+      using FFT binning with Hanning windowing and 50% overlap.
 
-   - `sound_pressure_spectral_density_level`: Converts mean square spectral density values to
-     sound pressure spectral density levels in dB.
+6. **Calibration**:
 
-6. **Spectral Density Aggregation**:
+   - `apply_calibration`: Applies calibration adjustments to the spectral density data using
+     a sensitivity curve, filling missing values as specified.
 
-   - `band_aggregate`: Aggregates spectral density data into fractional octave bands using
-     specified statistical methods (e.g., median, mean).
+7. **Band-Averaged Spectral Density**:
+
+    - `_get_band_table`: Generates a table of frequency bands for logarithmically
+      spaced divisions with optional linear spacing at lower frequencies.
+    - `_band_power_spectral_density_v3`: Pre-computes bin indices and weights for band averaging.
+    - `_band_mean_power_spectral_density_v2`: Computes the mean power spectral density
+      within specified bands.
+    - `_convert_to_band_spectral_density`: Generic function to convert spectral density
+      to custom banded spectral densities.
+    - `convert_to_millidecade`, `convert_to_decidecade`, `convert_to_third_octave`:
+      Convenience functions to convert spectral density to millidecade, decidecade,
+      and third-octave banded spectral densities, respectively.
+    - `convert_to_custom_bands`: Convert spectral density to custom band spacing with
+      user-specified parameters.
 
-   - `time_aggregate`: Aggregates spectral density data into specified time windows using
-     similar statistical methods.
 """
 
-from typing import Union, Dict, Tuple, Optional
+from typing import Union, Optional
 import warnings
 import numpy as np
 import xarray as xr
 
 from mhkit.dolfyn import VelBinner
-from mhkit.dolfyn.time import epoch2dt64, dt642epoch
 
 
 def _check_numeric(value, name: str):
@@ -90,6 +102,47 @@ def _fmax_warning(
     return fmax
 
 
+def create_frequency_bands(octave, base, fmin, fmax):
+    """
+    Calculates frequency bands based on the specified octave, minimum and
+    maximum frequency limits.
+
+    Parameters
+    ----------
+    octave: int
+        Octave to subdivide spectral density level by.
+    base : int, optional
+        Octave base. Set to 2 for the true octave band; set to base 10 for
+        the decidecade octave band. Default: 2
+    fmin : int, optional
+        Lower frequency band limit (lower limit of the hydrophone). Default is 10 Hz.
+    fmax : int, optional
+        Upper frequency band limit (Nyquist frequency). Default is 100,000 Hz.
+
+    Returns
+    -------
+    octave_bins: numpy.array
+        Array of octave bin edges
+    band: dict(str, numpy.array)
+        Dictionary containing the frequency band edges and center frequency
+    """
+
+    bandwidth = base ** (1 / octave)
+    half_bandwidth = base ** (1 / (octave * 2))
+
+    band = {}
+    band["center_freq"] = 10 ** np.arange(
+        np.log10(fmin),
+        np.log10(fmax),
+        step=np.log10(bandwidth),
+    )
+    band["lower_limit"] = band["center_freq"] / half_bandwidth
+    band["upper_limit"] = band["center_freq"] * half_bandwidth
+    octave_bins = np.append(band["lower_limit"], band["upper_limit"][-1])
+
+    return octave_bins, band
+
+
 def minimum_frequency(
     water_depth: Union[int, float, np.ndarray, list],
     c: Union[int, float] = 1500,
@@ -324,387 +377,439 @@ def apply_calibration(
     return spsd_calibrated
 
 
-def sound_pressure_spectral_density_level(spsd: xr.DataArray) -> xr.DataArray:
+def _get_band_table(
+    freq: np.ndarray,
+    bands_per_division: int,
+    base: int,
+    use_fft_res_at_bottom: bool,
+):
     """
-    Calculates the sound pressure spectral density level from
-    the mean square sound pressure spectral density.
+    Returns a three column array with the start, center, stop frequencies for
+    logarithmically spaced frequency bands such as millidecades, decidecades,
+    or third octaves base 2. These tables are passed to
+    `band_squared_sound_pressure` to convert square spectra to band
+    levels. The squared pressure can be converted to power spectral
+    density by dividing by the band_widths.
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
-        Mean square sound pressure spectral density in Pa^2/Hz
+    freq : np.ndarray
+        Array of frequency values in Hz from the FFT.
+    bands_per_division : int
+        The number of bands to divide the spectrum into per increase by
+        a factor of 'base'. A base of 2 and bands_per_division of 3
+        results in third octaves base 2. Base 10 and bands_per_division
+        of 1000 results in millidecades.
+    base : int
+        Base for the band levels, generally 10 or 2.
+    use_fft_res_at_bottom : bool
+        In some cases, like millidecades, we do not want to have
+        logarithmically spaced frequency bands across the full spectrum.
+        When True, bands at lower frequencies use linear spacing (equal
+        to the FFT bin size), and transition to log spacing at the band
+        where the bandwidth exceeds the FFT bin size and the frequency
+        space between band center frequencies is at least the FFT bin size.
 
     Returns
     -------
-    spsdl: xarray.DataArray (time, freq)
-        Sound pressure spectral density level [dB re 1 uPa^2/Hz]
-        indexed by time and frequency
-    """
+    bands : np.ndarray
+        Three column array where column 1 is the lowest frequency of the
+        band, column 2 is the center frequency, and column 3 is the highest
+        frequency.
 
-    # Reference value of sound pressure
-    reference = 1e-12  # Pa^2 to 1 uPa^2
+    Originally created by Bruce Martin, JASCO Applied Sciences, Feb 2020:
 
-    # Sound pressure spectral density level from mean square values
-    lpf = 10 * np.log10(spsd.values / reference)
+    Martin, S. Bruce, et al. "Hybrid millidecade spectra: A practical format
+        for exchange of long-term ambient sound data." JASA Express Letters
+        1.1 (2021).
 
-    spsdl = xr.DataArray(
-        lpf.astype(np.float32),
-        coords={"time": spsd["time"], "freq": spsd["freq"]},
-        attrs={
-            "units": "dB re 1 uPa^2/Hz",
-            "long_name": "Sound Pressure Spectral Density Level",
-            "time_resolution": spsd.attrs["bin_length"],
-        },
+    Converted to Python and refactored by MHKiT Team, June 2026.
+    """
+
+    band_count = 0
+    linear_bin_count = 0
+    log_bin_count = 0
+    max_linear_bin_hz = 0
+
+    fft_bin_size = freq[1] - freq[0]
+    bin1_center_freq = freq[0]
+    max_freq = freq[-1]
+
+    # Generate the log-spaced bands
+    _, band_dict = create_frequency_bands(
+        octave=bands_per_division,
+        base=base,
+        fmin=freq[0],
+        fmax=freq[-1],
     )
 
-    return spsdl
+    # For millidecades and similar
+    if use_fft_res_at_bottom:
+        # Find the first band where the bandwidth is greater than the FFT bin size
+        # and the frequency space between band center frequencies is at least the FFT bin size
+        band_count = np.where(np.diff(band_dict["center_freq"]) >= fft_bin_size)[0][1]
+        center_freq = band_dict["center_freq"][band_count]
+
+        # Now keep counting until the difference between the log spaced
+        # center frequency and new frequency is greater than .025
+        max_linear_bin_hz = np.ceil(center_freq / fft_bin_size)
+        while (max_linear_bin_hz * fft_bin_size - center_freq) > 0:
+            band_count += 1
+            max_linear_bin_hz += 1
+            center_freq = bin1_center_freq * base ** (band_count / bands_per_division)
+
+        if (fft_bin_size * max_linear_bin_hz) > max_freq:
+            max_linear_bin_hz = max_freq / fft_bin_size + 1
+
+        linear_bin_count = int(max_linear_bin_hz / fft_bin_size - 1)
+
+    # Count the log space frequencies
+    log_bin_count = len(np.arange(band_count, band_dict["center_freq"].size, 1))
+
+    # Generate the linear frequencies
+    bands = np.zeros(((linear_bin_count + log_bin_count), 3))
+    if linear_bin_count:
+        bands[:linear_bin_count, 1] = (
+            np.arange(0, linear_bin_count * fft_bin_size, fft_bin_size)
+            + bin1_center_freq
+        )
+        bands[:linear_bin_count, 0] = (
+            np.arange(
+                -fft_bin_size / 2,
+                linear_bin_count * fft_bin_size - fft_bin_size / 2,
+                fft_bin_size,
+            )
+            + bin1_center_freq
+        )
+        bands[:linear_bin_count, 2] = (
+            np.arange(
+                fft_bin_size / 2,
+                (linear_bin_count + 1) * fft_bin_size - fft_bin_size / 2,
+                fft_bin_size,
+            )
+            + bin1_center_freq
+        )
+
+    # Trim log spaced bands to start the first band after the linear bands if they exist
+    idx = np.where(band_dict["center_freq"] > max_linear_bin_hz)[0]
+    bands[linear_bin_count:, 1] = band_dict["center_freq"][idx]
+    bands[linear_bin_count:, 0] = band_dict["lower_limit"][idx]
+    bands[linear_bin_count:, 2] = band_dict["upper_limit"][idx]
+
+    if log_bin_count > 0:
+        bands[-1, 2] = max_freq
+
+    return bands
 
 
-def _validate_method(
-    method: Union[str, Dict[str, Union[float, int]]],
-) -> Tuple[str, Optional[Union[float, int]]]:
+def _band_power_spectral_density_v3(freq_fft, freq_table):
     """
-    Validates the 'method' parameter and returns the method name and its argument (if any)
-    for an xarray.core.groupby.DataArrayGroupBy method.
+    Sums squared sound pressures to determine in-band totals.
+    The band edges are normally obtained from a call to ``get_band_table``.
 
     Parameters
     ----------
-    method : str or dict
-        The aggregation method to validate. It can be either:
-          - A string representing one of the supported methods without additional arguments,
-            e.g., 'mean', 'sum'.
-          - A dictionary with a single key-value pair where the key is the method name and
-            the value is its argument, e.g., {'quantile': 0.25}.
-
-        Supported methods are:
-          - 'all'
-          - 'any'
-          - 'assign_coords' (requires coordinate argument)
-          - 'count'
-          - 'cumprod'
-          - 'fillna'
-          - 'first'
-          - 'last'
-          - 'map' (requires custom function argument)
-          - 'max'
-          - 'mean'
-          - 'median'
-          - 'min'
-          - 'prod'
-          - 'quantile' (requires a quantile between 0 and 1)
-          - 'reduce' (requires custom function argument)
-          - 'std'
-          - 'sum'
-          - 'var'
-          - 'where' (requires condition argument)
+    freq_fft : np.ndarray
+        1D array of center frequencies produced by the FFT call [Hz].
+    freq_table : np.ndarray
+        Nx3 array of band edges where column 0 is the lower limit [Hz],
+        column 1 is the center frequency [Hz], and column 2 is the upper
+        limit [Hz].
 
     Returns
     -------
-    method_name : str
-        The validated method name in lowercase.
-    method_arg : float, int, or None
-        The argument associated with the method, if applicableotherwise, None.
-
-    Raises
-    ------
-    ValueError
-        - If the method name is not supported.
-        - If the 'quantile' method is provided without an argument or with an invalid argument.
-        - If the 'method' dictionary does not contain exactly one key-value pair.
-        - If 'method' is of an unsupported type.
-    TypeError
-        - If the key in the 'method' dictionary is not a string.
-
-    Examples
-    --------
-    >>> _validate_method('mean')
-    ('mean', None)
-
-    >>> _validate_method({'quantile': 0.75})
-    ('quantile', 0.75)
-
-    >>> _validate_method('quantile')
-    ValueError: The 'quantile' method must be provided as a dictionary with the quantile value,
-        e.g., {'quantile': 0.25}.
-
-    >>> _validate_method({'quantile': 1.5})
-    ValueError: The 'quantile' method must have a float between 0 and 1 as an argument.
-
-    >>> _validate_method({'unsupported_method': None})
-    ValueError: Method 'unsupported_method' is not supported.
-        Supported methods are:
-        ['median', 'mean', 'min', 'max', 'sum', 'quantile', 'std', 'var', 'count']
+    full_pts : dict
+        Dictionary where keys are band indices and values are arrays of FFT bin
+        indices that fall fully within the band.
+    partial_pts : dict
+        Dictionary where keys are band indices and values are arrays of FFT bin
+        indices that partially overlap the band.
+    weights : dict
+        Dictionary where keys are band indices and values are arrays of weights
+        for the partial bins, proportional to the fraction of the bin that falls
+        within the band.
+
+    Notes
+    -----
+    Full bins (entirely within a band) are summed
+    directly; partial bins (overlapping a band edge) are weighted
+    proportionally to the fraction of the bin that falls within the band.
+    The result is then divided by each band's bandwidth to return mean PSD.
+
+    Original code by Bruce Martin, JASCO Applied Sciences, Feb 2020:
+
+    Martin, S. Bruce, et al. "Hybrid millidecade spectra: A practical format
+        for exchange of long-term ambient sound data." JASA Express Letters
+        1.1 (2021).
+
+    Updated to use FFT-generated frequencies as input to handle time-resolved
+    spectral processing with a fundamental FFT frequency of 10 Hz by
+    Brian Polayge, University of Washington, 2025.
+
+    Converted to Python.
+    Split into two functions to pre-compute bin indices and weights in
+    ``_band_power_spectral_density_v3``, then compute band averaged PSD
+    in ``band_mean_power_spectral_density_v2``.
+    MHKiT Team, June 2026.
     """
 
-    allowed_methods = [
-        "all",
-        "any",
-        "assign_coords",
-        "count",
-        "cumsum",
-        "fillna",
-        "first",
-        "last",
-        "map",
-        "max",
-        "mean",
-        "median",
-        "min",
-        "prod",
-        "quantile",
-        "reduce",
-        "sum",
-        "std",
-        "sum",
-        "var",
-        "where",
-    ]
-    if not isinstance(method, (str, dict)):
-        raise TypeError("'method' must be a string or a dictionary.")
-    if isinstance(method, str):
-        method_name = method.lower()
-        if method_name not in allowed_methods:
-            raise ValueError(
-                f"Method '{method}' is not supported. Supported methods are: {allowed_methods}"
-            )
-        if method_name == "quantile":
-            raise ValueError(
-                "The 'quantile' method must be provided as a dictionary with "
-                "the quantile value, e.g., {'quantile': 0.25}."
-            )
-        method_arg = None
-    elif isinstance(method, dict):
-        if len(method) != 1:
-            raise ValueError(
-                "'method' dictionary must contain exactly one key-value pair."
-            )
-        method_name, method_arg = list(method.items())[0]
-        if not isinstance(method_name, str):
-            raise TypeError("Key in 'method' dictionary must be a string.")
-        method_name = method_name.lower()
-        if method_name not in allowed_methods:
-            raise ValueError(
-                f"Method '{method_name}' is not supported. Supported methods are: {allowed_methods}"
-            )
-        if method_name == "quantile":
-            if not isinstance(method_arg, (float, int)) or not 0 <= method_arg <= 1:
-                raise ValueError(
-                    "The 'quantile' method must have a float between 0 and 1 as an argument."
-                )
-    else:
-        raise ValueError(
-            f"Unsupported method type: {type(method)}. Must be a string or dictionary."
+    fft_bin_size = freq_fft[1] - freq_fft[0]
+
+    # Pre-compute full and partial bin indices for each band.
+    # This is band-invariant across time windows, so it is done once.
+    full_pts = {}
+    partial_pts = {}
+
+    for j in range(freq_table.shape[0]):
+        f_lo = freq_table[j, 0]
+        f_hi = freq_table[j, 2]
+
+        # FFT bins whose extent falls entirely within the frequency band
+        full_mask = (freq_fft - fft_bin_size / 2 >= f_lo) & (
+            freq_fft + fft_bin_size / 2 <= f_hi
+        )
+        full_pts[j] = np.where(full_mask)[0]
+
+        # FFT bins that overlap the frequency band at all (full or partial)
+        overlap_mask = ((freq_fft >= f_lo) & (freq_fft <= f_hi)) | (
+            (freq_fft + fft_bin_size / 2 > f_lo) & (freq_fft - fft_bin_size / 2 < f_hi)
         )
-    return method_name, method_arg
+
+        # Partial bins = overlapping minus fully-contained
+        partial_pts[j] = np.setdiff1d(np.where(overlap_mask)[0], full_pts[j])
+
+    # Compute fractional weights for partial bins
+    weights = {}
+    for j in range(freq_table.shape[0]):
+        weights[j] = np.zeros(partial_pts[j].size)
+
+        for k, idx in enumerate(partial_pts[j]):
+            bin_lo = freq_fft[idx] - fft_bin_size / 2
+            bin_hi = freq_fft[idx] + fft_bin_size / 2
+
+            if bin_lo < freq_table[j, 0]:
+                # Bin extends below the band's lower edge
+                weights[j][k] = (
+                    fft_bin_size - (freq_table[j, 0] - bin_lo)
+                ) / fft_bin_size
+
+            elif bin_hi > freq_table[j, 2]:
+                # Bin extends above the band's upper edge
+                weights[j][k] = (
+                    fft_bin_size - (bin_hi - freq_table[j, 2])
+                ) / fft_bin_size
+
+    return full_pts, partial_pts, weights
 
 
-def _create_frequency_bands(octave, base, fmin, fmax):
+def _band_mean_power_spectral_density_v2(
+    input_spsd, freq_table, full_pts, partial_pts, weights
+):
     """
-    Calculates frequency bands based on the specified octave, minimum and
-    maximum frequency limits.
+    Sums squared sound pressures to determine in-band totals, then divides by
+    the band widths to return mean power spectral density.
+    The band edges are normally obtained from a call to ``get_band_table`` and
+    the full and partial bin indices and weights are obtained from a call to
+    ``band_power_spectral_density_v3``.
 
     Parameters
     ----------
-    octave: int
-        Octave to subdivide spectral density level by.
-    base : int, optional
-        Octave base. Set to 2 for the true octave band; set to base 10 for
-        the decidecade octave band. Default: 2
-    fmin : int, optional
-        Lower frequency band limit (lower limit of the hydrophone). Default is 10 Hz.
-    fmax : int, optional
-        Upper frequency band limit (Nyquist frequency). Default is 100,000 Hz.
+    input_spsd : np.ndarray
+        2D array of sound pressure spectral density values with dimensions (time, freq).
+    freq_table : np.ndarray
+        Nx3 array of band edges where column 0 is the lower limit [Hz],
+        column 1 is the center frequency [Hz], and column 2 is the upper
+        limit [Hz].
+    full_pts : dict
+        Dictionary where keys are band indices and values are arrays of FFT bin
+        indices that fall fully within the band.
+    partial_pts : dict
+        Dictionary where keys are band indices and values are arrays of FFT bin
+        indices that partially overlap the band.
+    weights : dict
+        Dictionary where keys are band indices and values are arrays of weights
+        for the partial bins, proportional to the fraction of the bin that falls
+        within the band.
 
     Returns
     -------
-    octave_bins: numpy.array
-        Array of octave bin edges
-    band: dict(str, numpy.array)
-        Dictionary containing the frequency band edges and center frequency
+    out_spsd : np.ndarray
+        2D array of band-averaged sound pressure spectral density values with dimensions
+        (time, band), where 'band' corresponds to the center frequencies in 'freq_table'.
+
+    Notes
+    -----
+    Full bins (entirely within a band) are summed
+    directly; partial bins (overlapping a band edge) are weighted
+    proportionally to the fraction of the bin that falls within the band.
+    The result is then divided by each band's bandwidth to return mean PSD.
+
+    Original code by Bruce Martin, JASCO Applied Sciences, Feb 2020:
+
+    Martin, S. Bruce, et al. "Hybrid millidecade spectra: A practical format
+        for exchange of long-term ambient sound data." JASA Express Letters
+        1.1 (2021).
+
+    Updated to use FFT-generated frequencies as input to handle time-resolved
+    spectral processing with a fundamental FFT frequency of 10 Hz by
+    Brian Polayge, University of Washington, 2025.
+
+    Converted to Python.
+    Split into two functions to pre-compute bin indices and weights in
+    ``_band_power_spectral_density_v3``, then compute band averaged PSD
+    in ``band_mean_power_spectral_density_v2``.
+    MHKiT Team, June 2026.
     """
 
-    bandwidth = base ** (1 / octave)
-    half_bandwidth = base ** (1 / (octave * 2))
+    fft_bin_size = input_spsd["freq"].values[1] - input_spsd["freq"].values[0]
+    input_spsd = input_spsd.values
+    out_spsd = np.zeros((input_spsd.shape[0], freq_table.shape[0]))
+
+    # Accumulate band-squared pressure; vectorised over the time (row) axis
+    for j in range(freq_table.shape[0]):
+        # Contribution from fully-contained FFT bins
+        if len(full_pts[j]) > 0:
+            out_spsd[:, j] = np.sum(input_spsd[:, full_pts[j]], axis=1) * fft_bin_size
+
+        # Contribution from partial FFT bins
+        if len(partial_pts[j]) > 0:
+            out_spsd[:, j] += (
+                np.sum(
+                    input_spsd[:, partial_pts[j]] * weights[j][np.newaxis, :], axis=1
+                )
+                * fft_bin_size
+            )
 
-    band = {}
-    band["center_freq"] = 10 ** np.arange(
-        np.log10(fmin),
-        np.log10(fmax * bandwidth),
-        step=np.log10(bandwidth),
-    )
-    band["lower_limit"] = band["center_freq"] / half_bandwidth
-    band["upper_limit"] = band["center_freq"] * half_bandwidth
-    octave_bins = np.append(band["lower_limit"], band["upper_limit"][-1])
+    # Take means
+    band_widths = freq_table[:, 2] - freq_table[:, 0]
+    out_spsd /= band_widths
 
-    return octave_bins, band
+    return out_spsd
 
 
-def band_aggregate(
-    spsdl: xr.DataArray,
-    octave: Tuple[int, int] = None,
-    fmin: int = 10,
-    fmax: int = 100000,
-    method: Union[str, Dict[str, Union[float, int]]] = "median",
+def _convert_to_band_spectral_density(
+    spsd: xr.DataArray, bands_per_division: int, base: int, use_fft_res_at_bottom: bool
 ) -> xr.DataArray:
     """
-    Reorganizes spectral density level frequency tensor into
-    fractional octave bands and applies a function to them.
+    Convert sound pressure spectral density to banded spectral density based on
+    the specified base and bands per division.
 
     Parameters
     ----------
-    spsdl: xarray.DataArray (time, freq)
-        Mean square sound pressure spectral density level in dB rel 1 uPa^2/Hz
-    octave: [int, int]
-        Octave and octave base to subdivide spectral density level by. Set to
-        octave base to 2 for the true octave band; set to base 10 for
-        the decidecade octave band.
-        Default = [3, 2] (true third octave)
-    fmin: int
-        Lower frequency band limit (lower limit of the hydrophone). Default: 10 Hz
-    fmax: int
-        Upper frequency band limit (Nyquist frequency). Default: 100000 Hz
-    method: str or dict
-        Method to run on the binned data. Can be a string (e.g., "median") or a dict
-        where the key is the method and the value is its argument (e.g., {"quantile": 0.25}).
-        Options: [median, mean, min, max, sum, quantile, std, var, count]
+    spsd: xr.DataArray
+        DataArray with frequency dimension.
+    bands_per_division: int
+        The number of bands to divide the spectrum into per increase by a factor
+        of 'base'. A base of 2 and "bands_per_division" of 3 results in third
+        octaves base 2. Base 10 and "bands_per_division" of 1000 results in
+        millidecades.
+    base: int
+        Base for the band levels, generally 10 or 2.
+    use_fft_res_at_bottom: bool
+        In some cases, like millidecades, we do not want to have logarithmically
+        spaced frequency bands across the full spectrum, instead we have the option
+        to have bands that are equal 'fft_bin_size'. The switch to log spacing is
+        made at the band that has a bandwidth greater than 'fft_bin_size' and such
+        that the frequency space between band center frequencies is at least
+        'fft_bin_size'.
 
     Returns
     -------
-    out: xarray.DataArray (time, freq_bins)
-        Frequency band-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz]
-        indexed by time and frequency
+    xr.DataArray
+        DataArray with frequency dimension converted to banded spectral density.
     """
 
-    # Type checks
-    if not isinstance(spsdl, xr.DataArray):
-        raise TypeError("'spsdl' must be an xarray.DataArray.")
-    if octave is None:
-        octave = [3, 2]
-    if not isinstance(octave, list) and not isinstance(octave, tuple):
-        raise TypeError("'octave' must be a list or tuple of two integers.")
-    for val in octave:
-        if not isinstance(val, int) or (val <= 0):
-            raise TypeError("'octave' must contain positive integers.")
-    _check_numeric(fmin, "fmin")
-    _check_numeric(fmax, "fmax")
-    if fmax <= fmin:  # also checks that fmax is positive
-        raise ValueError("'fmax' must be greater than 'fmin'.")
-
-    # Value checks
-    if ("freq" not in spsdl.dims) or ("time" not in spsdl.dims):
-        raise ValueError("'spsdl' must have 'time' and 'freq' as dimensions.")
-
-    # Validate method and get method_name and method_arg
-    method_name, method_arg = _validate_method(method)
-
-    # Check fmax
-    fn = spsdl["freq"].max().values
-    fmax = _fmax_warning(fn, fmax)
-
-    octave_bins, band = _create_frequency_bands(octave[0], octave[1], fmin, fmax)
-
-    # Use xarray binning methods
-    spsdl_group = spsdl.groupby_bins("freq", octave_bins, labels=band["center_freq"])
-
-    # Handle method being a string or a dict
-    if isinstance(method, str):
-        func = getattr(spsdl_group, method.lower())
-        out = func()
-    else:
-        method_name, method_arg = list(method.items())[0]
-        func = getattr(spsdl_group, method_name.lower())
-        if isinstance(method_arg, (list, tuple)):
-            out = func(*method_arg)
-        else:
-            out = func(method_arg)
+    # Get bands
+    bands = _get_band_table(
+        freq=spsd["freq"].values,
+        bands_per_division=bands_per_division,
+        base=base,
+        use_fft_res_at_bottom=use_fft_res_at_bottom,
+    )
+    full_pts, partial_pts, weights = _band_power_spectral_density_v3(
+        freq_fft=spsd["freq"].values,
+        freq_table=bands,
+    )
+    band_spsd = _band_mean_power_spectral_density_v2(
+        input_spsd=spsd,
+        freq_table=bands,
+        full_pts=full_pts,
+        partial_pts=partial_pts,
+        weights=weights,
+    )
+    out = xr.DataArray(
+        band_spsd,
+        coords={"time": spsd["time"], "freq": bands[:, 1]},
+        dims=["time", "freq"],
+        attrs=spsd.attrs,
+    )
+
+    return out
+
+
+def convert_to_millidecade(spsd: xr.DataArray) -> xr.DataArray:
+    """Convert sound pressure spectral density to millidecade spacing."""
+
+    out = _convert_to_band_spectral_density(
+        spsd=spsd, bands_per_division=1000, base=10, use_fft_res_at_bottom=True
+    )
+    return out
 
-    # Update attributes
-    out.attrs["units"] = spsdl.units
 
+def convert_to_third_octave(spsd: xr.DataArray) -> xr.DataArray:
+    """Convert sound pressure spectral density to third octave spacing."""
+
+    out = _convert_to_band_spectral_density(
+        spsd=spsd, bands_per_division=3, base=2, use_fft_res_at_bottom=False
+    )
     return out
 
 
-def time_aggregate(
-    spsdl: xr.DataArray,
-    window: int = 60,
-    method: Union[str, Dict[str, Union[float, int]]] = "median",
+def convert_to_decidecade(spsd: xr.DataArray) -> xr.DataArray:
+    """Convert sound pressure spectral density to decidecade spacing."""
+
+    out = _convert_to_band_spectral_density(
+        spsd=spsd, bands_per_division=10, base=10, use_fft_res_at_bottom=False
+    )
+    return out
+
+
+def convert_to_custom_bands(
+    spsd: xr.DataArray,
+    bands_per_division: int,
+    base: int,
+    use_fft_res_at_bottom: bool = False,
 ) -> xr.DataArray:
     """
-    Reorganizes spectral density level frequency tensor into
-    time windows and applies a function to them.
-
-    If the window length is equivalent to the size of spsdl["time"],
-    this function is equivalent to spsdl.<method>("time")
+    Convert sound pressure spectral density to custom band spacing based on specified
+    parameters.
 
     Parameters
     ----------
-    spsdl: xarray.DataArray (time, freq)
-        Mean square sound pressure spectral density level in dB rel 1 uPa^2/Hz
-    window: int
-        Time in seconds to subdivide spectral density level into. Default: 60 s.
-    method: str or dict
-        Method to run on the binned data. Can be a string (e.g., "median") or a dict
-        where the key is the method and the value is its argument (e.g., {"quantile": 0.25}).
-        Options: [median, mean, min, max, sum, quantile, std, var, count]
+    spsd (xr.DataArray): DataArray with frequency dimension.
+    bands_per_division (int): The number of bands to divide the spectrum into
+        per increase by a factor of 'base'. A base of 2 and
+        "bands_per_division" of 3 results in third octaves. Base 10
+        and "bands_per_division" of 1000 results in millidecades.
+    base (int): Base for the band levels, generally 10 or 2.
+    use_fft_res_at_bottom (bool): In some cases, like millidecades, we do not want
+        to have logarithmically spaced frequency bands across the full
+        spectrum, instead we have the option to have bands that are equal
+        'fft_bin_size'. The switch to log spacing is made at the band that
+        has a bandwidth greater than 'fft_bin_size' and such that the
+        frequency space between band center frequencies is at least
+        'fft_bin_size'.
 
     Returns
     -------
-    out: xarray.DataArray (time_bins, freq)
-        Time-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz]
-        indexed by time and frequency
+    xr.DataArray: DataArray with frequency dimension converted to custom banded spectral
+        density.
     """
 
-    # Type checks
-    if not isinstance(spsdl, xr.DataArray):
-        raise TypeError("'spsdl' must be an xarray.DataArray.")
-    if not isinstance(window, int):
-        raise TypeError("'window' must be an integer.")
-    if not isinstance(method, (str, dict)):
-        raise TypeError("'method' must be a string or dictionary.")
-    if "time" not in spsdl.dims:
-        raise ValueError("'spsdl' must have 'time' dimension.")
-
-    # Value checks
-    if window <= 0:
-        raise ValueError("'window' must be a positive integer.")
-
-    # Ensure 'time' coordinate is of datetime64 dtype
-    if not np.issubdtype(spsdl["time"].dtype, np.datetime64):
-        raise TypeError("'spsdl['time']' must be of dtype 'datetime64'.")
-
-    # Validate method and get method_name and method_arg
-    method_name, method_arg = _validate_method(method)
-
-    window = np.timedelta64(window, "s")
-    time_bins_lower = np.arange(
-        spsdl["time"][0].values, spsdl["time"][-1].values, window
-    )
-    time_bins_upper = time_bins_lower + window
-    time_bins = np.append(time_bins_lower, time_bins_upper[-1])
-    center_time = epoch2dt64(
-        0.5 * (dt642epoch(time_bins_lower) + dt642epoch(time_bins_upper))
+    out = _convert_to_band_spectral_density(
+        spsd=spsd,
+        bands_per_division=bands_per_division,
+        base=base,
+        use_fft_res_at_bottom=use_fft_res_at_bottom,
     )
-
-    # Use xarray binning methods
-    spsdl_group = spsdl.groupby_bins("time", time_bins, labels=center_time)
-
-    # Handle method being a string or a dict
-    if isinstance(method, str):
-        func = getattr(spsdl_group, method.lower())
-        out = func()
-    else:
-        method_name, method_arg = list(method.items())[0]
-        func = getattr(spsdl_group, method_name.lower())
-        if isinstance(method_arg, (list, tuple)):
-            out = func(*method_arg)
-        else:
-            out = func(method_arg)
-
-    # Update attributes
-    out.attrs["units"] = spsdl.units
-
-    # Remove 'quantile' coordinate if present
-    if method == "quantile":
-        out = out.drop_vars("quantile")
-
     return out
diff --git a/mhkit/acoustics/io.py b/mhkit/acoustics/io.py
index 8ba1ef98a..868a74621 100644
--- a/mhkit/acoustics/io.py
+++ b/mhkit/acoustics/io.py
@@ -44,6 +44,7 @@
 import struct
 import wave
 from pathlib import Path
+from datetime import datetime
 import numpy as np
 import pandas as pd
 import xarray as xr
@@ -239,6 +240,7 @@ def read_hydrophone(
             attrs={
                 "units": "Pa",
                 "sensitivity": np.round(sensitivity, 12),
+                "gain": gain,
                 # Pressure min resolution
                 "resolution": np.round(peak_voltage / max_count / sensitivity / 1e6, 9),
                 # Minimum pressure sensor can read
@@ -255,6 +257,7 @@ def read_hydrophone(
             coords={"time": time[:-1]},
             attrs={
                 "units": "V",
+                "gain": gain,
                 # Voltage min resolution
                 "resolution": np.round(peak_voltage / max_count, 6),
                 # Minimum voltage sensor can read
@@ -487,51 +490,257 @@ def read_iclisten(
     return out
 
 
+def _read_wispr_metadata(f: io.BufferedIOBase) -> Dict[str, Any]:
+    """
+    Reads the metadata from the WISPR .dat file and
+    returns the metadata in a dictionary.
+
+    Parameters
+    ----------
+    f: io.BufferedIOBase
+        Opened .dat file for reading metadata.
+
+    Returns
+    -------
+    metadata: dict
+        A dictionary containing metadata such as sampling_rate,
+        adc_vref, gain, etc.
+    """
+
+    # Read metadata off wispr file header and store in dictionary
+    metadata = {}
+    for row in f.readlines():
+        try:
+            row = row.decode().strip().split("=")
+        except UnicodeDecodeError:
+            break
+        if len(row) == 2:
+            key, value = row
+            if "'" in value:
+                value = value.replace("'", "")
+                dtype = str
+            else:
+                dtype = np.float32
+            metadata[key.strip()] = dtype(value.strip().rstrip(";"))
+        elif "WISPR" in row[0]:
+            metadata["version"] = row[0].split(" ")[-1]
+
+    if "file_length_sec" not in metadata:
+        metadata["file_length_sec"] = (
+            metadata["file_size"]
+            * 512
+            / metadata["sample_size"]
+            / metadata["sampling_rate"]
+        )
+
+    return metadata
+
+
+def read_wispr(file_path):
+    """
+    Read WISPR .dat file and return xarray DataArray with voltage time series.
+
+    Parameters
+    ----------
+    file_path : str
+        Path to WISPR .dat file.
+
+    Returns
+    -------
+    xr.DataArray
+        DataArray containing voltage time series and metadata.
+    """
+
+    def read_24bit_data(filename, is_signed=True, endian="<"):
+        """
+        Reads 24-bit data from a binary file into a 32-bit NumPy array.
+
+        Parameters
+        ----------
+        filename : str
+            The path to the binary file.
+        is_signed : bool
+            True if the data is signed 24-bit PCM, False if unsigned.
+        endian : str
+            Byte order, '<' for little-endian, '>' for big-endian.
+
+        Returns
+        -------
+        np.ndarray
+            A 32-bit integer NumPy array containing the data.
+        """
+        # Read the raw data as bytes
+        with open(filename, "rb") as f:
+            raw_bytes = f.read()
+
+        # Ensure the file size is a multiple of 3 bytes
+        if len(raw_bytes) % 3 != 0:
+            raise ValueError("File size is not a multiple of 3 bytes (24 bits)")
+
+        # Convert raw bytes into a 1D numpy array of 8-bit integers (uint8)
+        data_int8 = np.frombuffer(raw_bytes, dtype=np.uint8)
+
+        # Reshape the 8-bit array into N rows of 3 bytes each
+        data_3bytes = data_int8.reshape(-1, 3)
+
+        # Create an empty array to hold the final 32-bit integers
+        # Use the appropriate dtype based on 'is_signed'
+        dtype_str = f"{endian}i4" if is_signed else f"{endian}u4"
+        data_int32 = np.zeros(len(data_3bytes), dtype=dtype_str)
+
+        # Use vectorized slicing to copy the 3 bytes into the lower 3 bytes of the 32-bit array
+        data_int32.view(np.uint8)[:, :3] = data_3bytes
+
+        # Handle signed data sign extension if necessary
+        if is_signed and endian == "<":
+            # If little-endian and the original 24-bit number was negative, the
+            # most significant byte (index 2) will have the sign bit set.
+            # We correct this by shifting and logical ORing.
+            data_int32 = (data_int32 << 8) >> 8
+
+        return data_int32
+
+    with open(file_path, "rb") as f:
+        metadata = _read_wispr_metadata(f)
+
+    # Clean up metadata
+    start_time = np.datetime64(datetime.strptime(metadata["time"], "%m:%d:%y:%H:%M:%S"))
+    fs = int(metadata["sampling_rate"])
+    peak_voltage = int(metadata["adc_vref"])
+    bits_per_sample = int(metadata["sample_size"] * 8)
+
+    # Read binary data from wispr file
+    # Data is recorded in 16 or 24-bit by the ADC, saved in 32-bit format by the microcontroller,
+    # and finally converted to 16-bit within the WISPR code before being written to file.
+    with open(file_path, "rb") as f:
+        # skip header lines
+        f.seek(512)
+        # read binary data (datatype determined by bits per sample)
+        if bits_per_sample == 24:
+            # 24-bit data is stored as 24-bit signed integers in little-endian format
+            data = read_24bit_data(file_path, is_signed=True, endian="<")
+        else:
+            data = np.fromfile(f, dtype=np.int16, offset=0)
+
+    # Normalize and then scale to peak voltage
+    max_count = 2 ** (bits_per_sample - 1)
+    # Use 64 bit float for decimal accuracy
+    raw_voltage = data.astype(float) / max_count * peak_voltage
+
+    # Set time
+    end_time = np.datetime64(start_time) + np.timedelta64(
+        int(metadata["file_length_sec"] * 1000), "ms"
+    )
+    time = pd.date_range(start_time, end_time, data.size + 1)
+
+    # metadata attributes are hardcoded in wispr .dat file
+    out = xr.DataArray(
+        raw_voltage,
+        coords={"time": time[:-1]},
+        attrs={
+            "units": "V",
+            # Voltage min resolution
+            "resolution": np.round(peak_voltage / max_count, 9),
+            # Minimum voltage sensor can read
+            "valid_min": -peak_voltage,
+            # Voltage at which sensor is saturated
+            "valid_max": peak_voltage,
+            "fs": fs,
+            "filename": Path(file_path).stem,
+            # Gain setting in header is in 6 dB intervals
+            "gain": int(metadata["gain"]) * 6,
+            "peak_voltage": peak_voltage,
+            "file_length_sec": metadata["file_length_sec"],
+            "instrument_id": metadata["instrument_id"],
+            "sfw_version": metadata["version"],
+            "location_id": metadata["location_id"],
+        },
+    )
+    return out
+
+
 def export_audio(
-    filename: str, pressure: xr.DataArray, gain: Union[int, float] = 1
+    filename: str,
+    pressure: xr.DataArray,
+    peak_voltage: Union[int, float] = None,
+    gain: Union[int, float] = 1,
+    resample_multiplier: int = 1,
 ) -> None:
     """
-    Creates human-scaled audio file from underwater recording.
+    Creates an audio file from an underwater recording.
 
     Parameters
     ----------
     filename : str
         Output filename for the WAV file (without extension).
     pressure : xarray.DataArray
-        Sound pressure data with attributes:
-            - 'values' (numpy.ndarray): Pressure data array.
+        Sound pressure or voltage data with attributes:
             - 'sensitivity' (int or float): Sensitivity of the hydrophone in dB.
             - 'fs' (int or float): Sampling frequency in Hz.
+            - 'peak_voltage' or 'valid_max' (int or float): Peak voltage of the analog-to-digital
+               converter.
+    peak_voltage : int or float
+        Peak voltage of the analog-to-digital converter.
     gain : int or float, optional
         Gain to multiply the original time series by. Default is 1.
-
-    Returns
-    -------
-    None
+    resample_multiplier : int, optional
+        Multiplier for resampling the pressure to speed up the recording,
+        which is useful for listening to low frequency sound. Default is 1 (no resampling).
     """
 
     if not isinstance(filename, str):
         raise TypeError("'filename' must be a string.")
     if not isinstance(pressure, xr.DataArray):
         raise TypeError("'pressure' must be an xarray.DataArray.")
-    if not hasattr(pressure, "values") or not isinstance(pressure.values, np.ndarray):
-        raise TypeError("'pressure.values' must be a numpy.ndarray.")
     if hasattr(pressure, "sensitivity"):
         _check_numeric(pressure.sensitivity, "pressure.sensitivity")
     else:
         raise AttributeError("'pressure' must have a 'sensitivity' attribute.")
     if hasattr(pressure, "fs"):
         _check_numeric(pressure.fs, "pressure.fs")
+        fs = pressure.fs
     else:
         raise AttributeError("'pressure' must have a 'fs' attribute.")
+    if "peak_voltage" in pressure.attrs:
+        peak_voltage = pressure.attrs["peak_voltage"]
+    elif "valid_max" in pressure.attrs:
+        peak_voltage = pressure.attrs["valid_max"]
+    else:
+        if peak_voltage is None:
+            raise AttributeError(
+                "'pressure' must have a 'peak_voltage' attribute or 'peak_voltage' must be "
+                "provided."
+            )
+        _check_numeric(peak_voltage, "peak_voltage")
     _check_numeric(gain, "gain")
-
-    # Convert from Pascals to UPa
-    upa = pressure.values.T * 1e6
-    # Change to voltage waveform
-    v = upa * 10 ** (pressure.sensitivity / 20)  # in V
+    _check_numeric(resample_multiplier, "resample_multiplier")
+
+    # To resample
+    if resample_multiplier > 1:
+        total_time = pressure.time[-1] - pressure.time[0]
+        # Shorten time coordinate based on 10x speed up
+        new_time = pd.date_range(
+            start=pressure["time"][0].values,
+            end=pressure["time"][0].values + (total_time.values / resample_multiplier),
+            periods=pressure.size + 1,
+        )[:-1]
+        pressure = pressure.assign_coords({"time": new_time})
+
+        # Resample to keep sampling frequency unchanged
+        resample_time = pd.date_range(
+            start=pressure["time"][0].values,
+            end=pressure["time"][-1].values,
+            periods=pressure.size // resample_multiplier + 1,
+        )[:-1]
+        pressure = pressure.interp(time=resample_time)
+
+    if pressure.attrs["units"] == "Pa":
+        # Convert from Pascals to microPa and change to voltage waveform
+        pressure = (pressure.T * 1e6) * 10 ** (pressure.sensitivity / 20)
+
+    v = pressure.values
     # Normalize
-    v = v / max(abs(v)) * gain
+    v = v / min(max(abs(v)) * gain, peak_voltage)
     # Convert to (little-endian) 16 bit integers.
     audio = (v * (2**16 - 1)).astype("<h")
 
@@ -539,5 +748,5 @@ def export_audio(
     with wave.open(f"{filename}.wav", mode="w") as f:
         f.setnchannels(1)  # pylint: disable=no-member
         f.setsampwidth(2)  # pylint: disable=no-member
-        f.setframerate(pressure.fs)  # pylint: disable=no-member
+        f.setframerate(fs)  # pylint: disable=no-member
         f.writeframes(audio.tobytes())  # pylint: disable=no-member
diff --git a/mhkit/acoustics/spl.py b/mhkit/acoustics/spl.py
index 3be616c9b..c553d8dbf 100644
--- a/mhkit/acoustics/spl.py
+++ b/mhkit/acoustics/spl.py
@@ -19,7 +19,12 @@
 import numpy as np
 import xarray as xr
 
-from .analysis import _check_numeric, _fmax_warning, _create_frequency_bands
+from .analysis import (
+    _check_numeric,
+    _fmax_warning,
+    _get_band_table,
+    _band_power_spectral_density_v3,
+)
 
 
 def _argument_check(spsd, fmin, fmax):
@@ -126,13 +131,7 @@ def sound_pressure_level(
     return out
 
 
-def _band_sound_pressure_level(
-    spsd: xr.DataArray,
-    octave: int,
-    base: int = 2,
-    fmin: int = 10,
-    fmax: int = 100000,
-) -> xr.DataArray:
+def _band_sound_pressure_level(spsd: xr.DataArray, octave: int, base: int):
     """
     Calculates band-averaged sound pressure levels from the
     mean square sound pressure spectral density (SPSD).
@@ -145,63 +144,62 @@ def _band_sound_pressure_level(
         Octave subdivision (1 = full octave, 3 = third-octave, etc.)
     base: int
         Octave base subdivision (2 = true octave, 10 = decade octave, etc.)
-    fmin : int, optional
-        Lower frequency band limit (lower limit of the hydrophone).
-        Default is 10 Hz.
-    fmax : int, optional
-        Upper frequency band limit (Nyquist frequency).
-        Default is 100,000 Hz.
 
     Returns
     -------
     out: xarray.DataArray (time, freq_bins)
         Sound pressure level [dB re 1 uPa] indexed by time and frequency of specified bandwidth
-    """
 
-    # Type checks
-    if not isinstance(octave, int) or (octave <= 0):
-        raise TypeError("'octave' must be a positive integer.")
-
-    # Argument checks
-    fmax = _argument_check(spsd, fmin, fmax)
+    Notes
+    -----
+    Assumes constant spacing in FFT frequency vector.
+    """
 
     # Reference value of sound pressure
     reference = 1e-12  # Pa^2, = 1 uPa^2
+    # Frequency vector
+    freq = spsd["freq"].values
+
+    # Get bands
+    bands = _get_band_table(
+        freq=freq,
+        bands_per_division=octave,
+        base=base,
+        use_fft_res_at_bottom=False,
+    )
+    full_pts, partial_pts, weights = _band_power_spectral_density_v3(
+        freq_fft=freq, freq_table=bands
+    )
 
-    _, band = _create_frequency_bands(octave, base, fmin, fmax)
+    input_spsd = spsd.values
+    out_sp = np.zeros((input_spsd.shape[0], bands.shape[0]))
 
-    # Manual trapezoidal rule to get Pa^2
-    pressure_squared = xr.DataArray(
-        coords={"time": spsd["time"], "freq_bins": band["center_freq"]},
-        dims=["time", "freq_bins"],
-    )
-    for i, key in enumerate(band["center_freq"]):
-        # Min and max band limits
-        band_range = [band["lower_limit"][i], band["upper_limit"][i]]
-
-        # Integrate spectral density by frequency
-        x = spsd["freq"].sel(freq=slice(*band_range))
-        if len(x) < 2:
-            # Interpolate between band frequencies if width is narrow
-            bandwidth = band_range[1] / band_range[0]
-            # Use smaller set of dataset to speed up interpolation
-            spsd_slc = spsd.sel(
-                freq=slice(
-                    None,  # Only happens at low frequency
-                    band_range[1] * bandwidth * 2,
-                )
+    # Integrate band-squared pressure by frequency; vectorised over the time (row) axis
+    for j in range(bands.shape[0]):
+        # Contribution from fully-contained FFT bins
+        if len(full_pts[j]) > 0:
+            out_sp[:, j] = np.trapezoid(
+                input_spsd[:, full_pts[j]], freq[full_pts[j]], axis=1
             )
-            spsd_slc = spsd_slc.interp(freq=band_range)
-            x = band_range
-        else:
-            spsd_slc = spsd.sel(freq=slice(*band_range))
 
-        pressure_squared.loc[{"freq_bins": key}] = np.trapezoid(spsd_slc, x)
+        # Contribution from partial FFT bins
+        if len(partial_pts[j]) > 0:
+            out_sp[:, j] += np.trapezoid(
+                input_spsd[:, partial_pts[j]] * weights[j][np.newaxis, :],
+                dx=freq[1] - freq[0],
+                axis=1,
+            )
 
     # Mean square sound pressure level in dB rel 1 uPa
-    mspl = 10 * np.log10(pressure_squared / reference)
-
-    return mspl
+    out_spl = xr.DataArray(
+        10 * np.log10(out_sp / reference),
+        coords={
+            "time": spsd["time"],
+            "freq_bins": bands[:, 1],
+        },
+        dims=["time", "freq_bins"],
+    )
+    return out_spl
 
 
 def third_octave_sound_pressure_level(
@@ -227,9 +225,13 @@ def third_octave_sound_pressure_level(
     mspl: xarray.DataArray (time, freq_bins)
         Sound pressure level [dB re 1 uPa] indexed by time and third octave bands
     """
+
+    # Argument checks
+    fmax = _argument_check(spsd, fmin, fmax)
+
     octave = 3
     base = 2
-    mspl = _band_sound_pressure_level(spsd, octave, base, fmin, fmax)
+    mspl = _band_sound_pressure_level(spsd, octave, base)
     mspl.attrs.update(
         {
             "units": "dB re 1 uPa",
@@ -238,6 +240,7 @@ def third_octave_sound_pressure_level(
         }
     )
 
+    mspl = mspl.sel(freq_bins=slice(fmin, fmax))
     return mspl.astype(np.float32)
 
 
@@ -265,9 +268,12 @@ def decidecade_sound_pressure_level(
         Sound pressure level [dB re 1 uPa] indexed by time and decidecade bands
     """
 
+    # Argument checks
+    fmax = _argument_check(spsd, fmin, fmax)
+
     octave = 10
     base = 10
-    mspl = _band_sound_pressure_level(spsd, octave, base, fmin, fmax)
+    mspl = _band_sound_pressure_level(spsd, octave, base)
     mspl.attrs.update(
         {
             "units": "dB re 1 uPa",
@@ -276,4 +282,5 @@ def decidecade_sound_pressure_level(
         }
     )
 
+    mspl = mspl.sel(freq_bins=slice(fmin, fmax))
     return mspl.astype(np.float32)
diff --git a/mhkit/acoustics/spsdl.py b/mhkit/acoustics/spsdl.py
new file mode 100644
index 000000000..70b41f024
--- /dev/null
+++ b/mhkit/acoustics/spsdl.py
@@ -0,0 +1,462 @@
+"""
+1. **Spectral Density Level Calculation**:
+
+   - `sound_pressure_spectral_density_level`: Converts mean square spectral density values to
+     sound pressure spectral density levels in dB.
+
+2. **Spectral Density Aggregation**:
+
+   - `band_aggregate`: Aggregates spectral density levels into fractional octave bands using
+     specified statistical methods (e.g., median, mean).
+
+   - `time_aggregate`: Aggregates spectral density levels into specified time windows using
+     similar statistical methods.
+"""
+
+import warnings
+from typing import Union, Dict, Tuple, Optional
+import numpy as np
+import xarray as xr
+
+from mhkit.dolfyn.time import epoch2dt64, dt642epoch
+from .analysis import _check_numeric, _fmax_warning, create_frequency_bands
+
+
+def sound_pressure_spectral_density_level(spsd: xr.DataArray) -> xr.DataArray:
+    """
+    Calculates the sound pressure spectral density level from
+    the mean square sound pressure spectral density.
+
+    Parameters
+    ----------
+    spsd: xarray.DataArray (time, freq)
+        Mean square sound pressure spectral density in Pa^2/Hz
+
+    Returns
+    -------
+    spsdl: xarray.DataArray (time, freq)
+        Sound pressure spectral density level [dB re 1 uPa^2/Hz]
+        indexed by time and frequency
+    """
+
+    # Reference value of sound pressure
+    reference = 1e-12  # Pa^2 to 1 uPa^2
+
+    # Sound pressure spectral density level from mean square values
+    lpf = 10 * np.log10(spsd.values / reference)
+
+    spsdl = xr.DataArray(
+        lpf.astype(np.float32),
+        coords={"time": spsd["time"], "freq": spsd["freq"]},
+        attrs={
+            "units": "dB re 1 uPa^2/Hz",
+            "long_name": "Sound Pressure Spectral Density Level",
+            "time_resolution": spsd.attrs["bin_length"],
+        },
+    )
+
+    return spsdl
+
+
+def _validate_method(
+    method: Union[str, Dict[str, Union[float, int]]],
+) -> Tuple[str, Optional[Union[float, int]]]:
+    """
+    Validates the 'method' parameter and returns the method name and its argument (if any)
+    for an xarray.core.groupby.DataArrayGroupBy method.
+
+    Parameters
+    ----------
+    method : str or dict
+        The aggregation method to validate. It can be either:
+          - A string representing one of the supported methods without additional arguments,
+            e.g., 'mean', 'sum'.
+          - A dictionary with a single key-value pair where the key is the method name and
+            the value is its argument, e.g., {'quantile': 0.25}.
+
+        Supported methods are:
+          - 'all'
+          - 'any'
+          - 'assign_coords' (requires coordinate argument)
+          - 'count'
+          - 'cumprod'
+          - 'fillna'
+          - 'first'
+          - 'last'
+          - 'map' (requires custom function argument)
+          - 'max'
+          - 'mean'
+          - 'median'
+          - 'min'
+          - 'prod'
+          - 'quantile' (requires a quantile between 0 and 1)
+          - 'reduce' (requires custom function argument)
+          - 'std'
+          - 'sum'
+          - 'var'
+          - 'where' (requires condition argument)
+
+    Returns
+    -------
+    method_name : str
+        The validated method name in lowercase.
+    method_arg : float, int, or None
+        The argument associated with the method, if applicableotherwise, None.
+
+    Raises
+    ------
+    ValueError
+        - If the method name is not supported.
+        - If the 'quantile' method is provided without an argument or with an invalid argument.
+        - If the 'method' dictionary does not contain exactly one key-value pair.
+        - If 'method' is of an unsupported type.
+    TypeError
+        - If the key in the 'method' dictionary is not a string.
+
+    Examples
+    --------
+    >>> _validate_method('mean')
+    ('mean', None)
+
+    >>> _validate_method({'quantile': 0.75})
+    ('quantile', 0.75)
+
+    >>> _validate_method('quantile')
+    ValueError: The 'quantile' method must be provided as a dictionary with the quantile value,
+        e.g., {'quantile': 0.25}.
+
+    >>> _validate_method({'quantile': 1.5})
+    ValueError: The 'quantile' method must have a float between 0 and 1 as an argument.
+
+    >>> _validate_method({'unsupported_method': None})
+    ValueError: Method 'unsupported_method' is not supported.
+        Supported methods are:
+        ['median', 'mean', 'min', 'max', 'sum', 'quantile', 'std', 'var', 'count']
+    """
+
+    allowed_methods = [
+        "all",
+        "any",
+        "assign_coords",
+        "count",
+        "cumsum",
+        "fillna",
+        "first",
+        "last",
+        "map",
+        "max",
+        "mean",
+        "median",
+        "min",
+        "prod",
+        "quantile",
+        "reduce",
+        "sum",
+        "std",
+        "sum",
+        "var",
+        "where",
+    ]
+    if not isinstance(method, (str, dict)):
+        raise TypeError("'method' must be a string or a dictionary.")
+    if isinstance(method, str):
+        method_name = method.lower()
+        if method_name not in allowed_methods:
+            raise ValueError(
+                f"Method '{method}' is not supported. Supported methods are: {allowed_methods}"
+            )
+        if method_name == "quantile":
+            raise ValueError(
+                "The 'quantile' method must be provided as a dictionary with "
+                "the quantile value, e.g., {'quantile': 0.25}."
+            )
+        method_arg = None
+    elif isinstance(method, dict):
+        if len(method) != 1:
+            raise ValueError(
+                "'method' dictionary must contain exactly one key-value pair."
+            )
+        method_name, method_arg = list(method.items())[0]
+        if not isinstance(method_name, str):
+            raise TypeError("Key in 'method' dictionary must be a string.")
+        method_name = method_name.lower()
+        if method_name not in allowed_methods:
+            raise ValueError(
+                f"Method '{method_name}' is not supported. Supported methods are: {allowed_methods}"
+            )
+        if method_name == "quantile":
+            if not isinstance(method_arg, (float, int)) or not 0 <= method_arg <= 1:
+                raise ValueError(
+                    "The 'quantile' method must have a float between 0 and 1 as an argument."
+                )
+    else:
+        raise ValueError(
+            f"Unsupported method type: {type(method)}. Must be a string or dictionary."
+        )
+    return method_name, method_arg
+
+
+def band_aggregate(
+    spsdl: xr.DataArray,
+    octave: Tuple[int, int] = None,
+    fmin: int = 10,
+    fmax: int = 100000,
+    method: Union[str, Dict[str, Union[float, int]]] = "median",
+) -> xr.DataArray:
+    """
+    Deprecated. Reorganizes spectral density level frequency tensor into
+    fractional octave bands and applies a function to them.
+
+    Parameters
+    ----------
+    spsdl: xarray.DataArray (time, freq)
+        Mean square sound pressure spectral density level in dB rel 1 uPa^2/Hz
+    octave: [int, int]
+        Octave and octave base to subdivide spectral density level by. Set to
+        octave base to 2 for the true octave band; set to base 10 for
+        the decidecade octave band.
+        Default = [3, 2] (true third octave)
+    fmin: int
+        Lower frequency band limit (lower limit of the hydrophone). Default: 10 Hz
+    fmax: int
+        Upper frequency band limit (Nyquist frequency). Default: 100000 Hz
+    method: str or dict
+        Method to run on the binned data. Can be a string (e.g., "median") or a dict
+        where the key is the method and the value is its argument (e.g., {"quantile": 0.25}).
+        Options: [median, mean, min, max, sum, quantile, std, var, count]
+
+    Returns
+    -------
+    out: xarray.DataArray (time, freq_bins)
+        Frequency band-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz]
+        indexed by time and frequency
+    """
+    warnings.warn(
+        "The 'band_aggregate' function is deprecated and will be removed in a future release. "
+        "Please use one of the following alternatives instead to convert the SPSD to the "
+        "appropriate band before calculating the SPSDL using "
+        "'sound_pressure_spectral_density_level':\n"
+        "- For third octaves, use 'mhkit.acoustics.convert_to_third_octave' function.\n"
+        "- For decidecades, use 'mhkit.acoustics.convert_to_decidecade' function.\n"
+        "- For millidecades, use 'mhkit.acoustics.convert_to_millidecade' function.\n"
+        "- For custom band aggregation, use 'mhkit.acoustics.convert_to_custom_bands.'",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+    # Type checks
+    if not isinstance(spsdl, xr.DataArray):
+        raise TypeError("'spsdl' must be an xarray.DataArray.")
+    if octave is None:
+        octave = [3, 2]
+    if not isinstance(octave, list) and not isinstance(octave, tuple):
+        raise TypeError("'octave' must be a list or tuple of two integers.")
+    for val in octave:
+        if not isinstance(val, int) or (val <= 0):
+            raise TypeError("'octave' must contain positive integers.")
+    _check_numeric(fmin, "fmin")
+    _check_numeric(fmax, "fmax")
+    if fmax <= fmin:  # also checks that fmax is positive
+        raise ValueError("'fmax' must be greater than 'fmin'.")
+
+    # Value checks
+    if ("freq" not in spsdl.dims) or ("time" not in spsdl.dims):
+        raise ValueError("'spsdl' must have 'time' and 'freq' as dimensions.")
+
+    # Validate method and get method_name and method_arg
+    method_name, method_arg = _validate_method(method)
+
+    # Check fmax
+    fn = spsdl["freq"].max().values
+    fmax = _fmax_warning(fn, fmax)
+
+    octave_bins, band = create_frequency_bands(octave[0], octave[1], fmin, fmax)
+
+    # Use xarray binning methods
+    spsdl_group = spsdl.groupby_bins("freq", octave_bins, labels=band["center_freq"])
+
+    # Handle method being a string or a dict
+    if isinstance(method, str):
+        func = getattr(spsdl_group, method.lower())
+        out = func()
+    else:
+        method_name, method_arg = list(method.items())[0]
+        func = getattr(spsdl_group, method_name.lower())
+        if isinstance(method_arg, (list, tuple)):
+            out = func(*method_arg)
+        else:
+            out = func(method_arg)
+
+    # Update attributes
+    out.attrs["units"] = spsdl.units
+
+    return out
+
+
+def time_aggregate(
+    spsdl: xr.DataArray,
+    window: int = 60,
+    method: Union[str, Dict[str, Union[float, int]]] = "median",
+) -> xr.DataArray:
+    """
+    Deprecated. Reorganizes spectral density level frequency tensor into
+    time windows and applies a function to them.
+
+    If the window length is equivalent to the size of spsdl["time"],
+    this function is equivalent to spsdl.<method>("time")
+
+    Parameters
+    ----------
+    spsdl: xarray.DataArray (time, freq)
+        Mean square sound pressure spectral density level in dB rel 1 uPa^2/Hz
+    window: int
+        Time in seconds to subdivide spectral density level into. Default: 60 s.
+    method: str or dict
+        Method to run on the binned data. Can be a string (e.g., "median") or a dict
+        where the key is the method and the value is its argument (e.g., {"quantile": 0.25}).
+        Options: [median, mean, min, max, sum, quantile, std, var, count]
+
+    Returns
+    -------
+    out: xarray.DataArray (time_bins, freq)
+        Time-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz]
+        indexed by time and frequency
+    """
+    warnings.warn(
+        "The 'time_aggregate' function is deprecated and will be removed in a future release. "
+        "Please use one of the following alternatives instead to convert the SPSD to the "
+        "appropriate time-aggregated form before calculating the SPSDL using "
+        "'sound_pressure_spectral_density_level':\n"
+        "- For time-averaged SPSDLs, use the 'mhkit.acoustics.time_average' function.\n"
+        "- For time-summed SPSDLs, use the 'mhkit.acoustics.time_summation' function.\n"
+        "If you are using this function for a different purpose, please reach out to the MHKiT "
+        "developers to discuss how we can support your use case with a more specific function.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+    # Type checks
+    if not isinstance(spsdl, xr.DataArray):
+        raise TypeError("'spsdl' must be an xarray.DataArray.")
+    if not isinstance(window, int):
+        raise TypeError("'window' must be an integer.")
+    if not isinstance(method, (str, dict)):
+        raise TypeError("'method' must be a string or dictionary.")
+    if "time" not in spsdl.dims:
+        raise ValueError("'spsdl' must have 'time' dimension.")
+
+    # Value checks
+    if window <= 0:
+        raise ValueError("'window' must be a positive integer.")
+
+    # Ensure 'time' coordinate is of datetime64 dtype
+    if not np.issubdtype(spsdl["time"].dtype, np.datetime64):
+        raise TypeError("'spsdl['time']' must be of dtype 'datetime64'.")
+
+    # Validate method and get method_name and method_arg
+    method_name, method_arg = _validate_method(method)
+
+    window = np.timedelta64(window, "s")
+    time_bins_lower = np.arange(
+        spsdl["time"][0].values, spsdl["time"][-1].values, window
+    )
+    time_bins_upper = time_bins_lower + window
+    time_bins = np.append(time_bins_lower, time_bins_upper[-1])
+    center_time = epoch2dt64(
+        0.5 * (dt642epoch(time_bins_lower) + dt642epoch(time_bins_upper))
+    )
+
+    # Use xarray binning methods
+    spsdl_group = spsdl.groupby_bins("time", time_bins, labels=center_time)
+
+    # Handle method being a string or a dict
+    if isinstance(method, str):
+        func = getattr(spsdl_group, method.lower())
+        out = func()
+    else:
+        method_name, method_arg = list(method.items())[0]
+        func = getattr(spsdl_group, method_name.lower())
+        if isinstance(method_arg, (list, tuple)):
+            out = func(*method_arg)
+        else:
+            out = func(method_arg)
+
+    # Update attributes
+    out.attrs["units"] = spsdl.units
+
+    # Remove 'quantile' coordinate if present
+    if method == "quantile":
+        out = out.drop_vars("quantile")
+
+    return out
+
+
+def time_average(spsdl, window):
+    """
+    Reorganizes spectral density level frequency tensor into time windows and takes the
+    spectral average of all of the inputs along the time dimension. This is effectively
+    time-averaging the original SPSDs.
+    Note: 'window' must be larger than the original 'bin_length' of the SPSD
+
+    Parameters
+    ----------
+    spsdl: xarray.DataArray
+        Sound pressure spectral density level with dimensions (time, freq)
+    window: int
+        Time in seconds to group spectral density level into.
+
+    Returns
+    -------
+    xarray.DataArray
+        Time-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz] indexed
+        by time and frequency
+    """
+
+    def spectral_average(x):
+        # Convert value in decibels to absolute magnitude, still relevant to original units
+        magnitude = 10 ** (x / 10)
+        # Sum energy in each time bin
+        summed_magnitude = magnitude.sum("time")
+        # Take average
+        average_magnitude = summed_magnitude / magnitude["time"].size
+        # Convert back to decibels
+        result = 10 * np.log10(average_magnitude)
+
+        return result
+
+    return time_aggregate(spsdl, window, method={"map": spectral_average})
+
+
+def time_summation(spsdl, window):
+    """
+    Reorganizes spectral density level frequency tensor into time windows and takes the
+    spectral sum of each window. This is the equivalent of recalculating the SPSD using
+    `mhkit.acoustics.sound_presssure_spectral_density` with 'bin_length=window' instead
+    of the original 'bin_length'.
+    Note: 'window' must be larger than the original 'bin_length' of the SPSD
+
+    Parameters
+    ----------
+    spsdl: xarray.DataArray
+        Sound pressure spectral density level with dimensions (time, freq)
+    window: int
+        Time in seconds to group spectral density level into.
+
+    Returns
+    -------
+    xarray.DataArray
+        Time-summed sound pressure spectral density level [dB re 1 uPa^2/Hz] indexed
+        by time and frequency
+    """
+
+    def spectral_sum(x):
+        # Convert value in decibels to absolute magnitude, still relevant to original units
+        magnitude = 10 ** (x / 10)
+        # Sum energy in each time bin
+        summed_magnitude = magnitude.sum("time")
+        # Convert back to decibels
+        result = 10 * np.log10(summed_magnitude)
+
+        return result
+
+    return time_aggregate(spsdl, window, method={"map": spectral_sum})
diff --git a/mhkit/tests/acoustics/test_analysis.py b/mhkit/tests/acoustics/test_analysis.py
index b60f5f91f..2e78e6adb 100644
--- a/mhkit/tests/acoustics/test_analysis.py
+++ b/mhkit/tests/acoustics/test_analysis.py
@@ -6,7 +6,6 @@
 
 import mhkit.acoustics as acoustics
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -26,6 +25,46 @@ def setUpClass(self):
     def tearDownClass(self):
         pass
 
+    def test_frequency_bands(self):
+        _, third_octaves = acoustics.create_frequency_bands(3, 2, fmin=1, fmax=48000)
+        _, decidecades = acoustics.create_frequency_bands(10, 10, fmin=1, fmax=48000)
+        millidecades = acoustics.analysis._get_band_table(
+            self.spsd["freq"][:460].values,
+            bands_per_division=1000,
+            base=10,
+            use_fft_res_at_bottom=True,
+        )[:, 1]
+
+        cd_third_octaves_head = np.array(
+            [1.0, 1.25992105, 1.58740105, 2.0, 2.5198421, 3.1748021, 4.0]
+        )
+        cd_third_octaves_tail = np.array(
+            [16384.0, 20642.54648148, 26007.97883545, 32768.0, 41285.09296296]
+        )
+        cd_decidecades_head = np.array(
+            [1.0, 1.25892541, 1.58489319, 1.99526231, 2.51188643, 3.16227766]
+        )
+        cd_decidecades_tail = np.array(
+            [19952.62314969, 25118.8643151, 31622.77660168, 39810.71705535]
+        )
+        cd_millidecades = np.array(
+            [454.0, 455.0, 456.03691595, 457.08818961, 458.14188671, 459.19801284]
+        )
+
+        np.testing.assert_allclose(
+            third_octaves["center_freq"][:7], cd_third_octaves_head, atol=1e-5
+        )
+        np.testing.assert_allclose(
+            third_octaves["center_freq"][-5:], cd_third_octaves_tail, atol=1e-5
+        )
+        np.testing.assert_allclose(
+            decidecades["center_freq"][:6], cd_decidecades_head, atol=1e-5
+        )
+        np.testing.assert_allclose(
+            decidecades["center_freq"][-4:], cd_decidecades_tail, atol=1e-5
+        )
+        np.testing.assert_allclose(millidecades[-6:], cd_millidecades, atol=1e-5)
+
     def test_sound_pressure_spectral_density(self):
         """
         Test sound pressure spectral density calculation.
@@ -135,7 +174,7 @@ def test_spsdl(self):
             td_spsdl["time"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
-    def test_averaging(self):
+    def test_averaging_deprecated(self):
         td_spsdl = acoustics.sound_pressure_spectral_density_level(self.spsd)
 
         # Frequency average into # octave bands
@@ -197,6 +236,95 @@ def test_averaging(self):
             td_spsdl_50["time_bins"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
+    def test_averaging(self):
+        # Third Octaves
+        third_octave_spsd = acoustics.convert_to_third_octave(self.spsd)
+        td_spsdl_to = acoustics.sound_pressure_spectral_density_level(third_octave_spsd)
+        # Decidecades
+        decidecade_spsd = acoustics.convert_to_decidecade(self.spsd)
+        td_spsdl_dd = acoustics.sound_pressure_spectral_density_level(decidecade_spsd)
+        # Millidecades
+        millidecade_spsd = acoustics.convert_to_millidecade(self.spsd)
+        td_spsdl_md = acoustics.sound_pressure_spectral_density_level(millidecade_spsd)
+
+        # Time average into 30 s bins
+        lbin = 30
+        td_spsdl_avg = acoustics.time_average(td_spsdl_to, lbin)
+        td_spsdl_sum = acoustics.time_summation(td_spsdl_to, lbin)
+
+        cd_spsdl_dd = np.array(
+            [
+                [65.93822, 62.86854, 60.797012, 62.410725, 60.77913],
+                [68.95052, 65.88085, 63.982758, 65.66743, 61.178196],
+                [59.101044, 56.03137, 63.76194, 66.764084, 67.23888],
+                [52.0443, 48.974625, 46.74791, 48.29464, 53.098785],
+                [56.053894, 52.98422, 57.43947, 60.282322, 57.38807],
+            ]
+        )
+        cd_spsdl_md_head = np.array(
+            [
+                [61.725582, 60.458782, 61.02544, 62.104874, 53.694523],
+                [64.73789, 63.71548, 56.60307, 55.591457, 65.14299],
+                [54.88841, 64.81213, 68.54643, 66.962105, 57.269337],
+                [47.831665, 46.342693, 55.266895, 59.975372, 62.875645],
+                [51.84126, 58.33038, 56.425198, 55.835743, 55.486942],
+            ]
+        )
+        cd_spsdl_md_tail = np.array(
+            [
+                [33.43558, 44.184784, 33.868732, 34.39551, 34.410404],
+                [33.27611, 45.362965, 33.23099, 34.436787, 36.571167],
+                [33.29176, 45.027763, 34.02678, 35.329945, 36.35523],
+                [33.95818, 44.993164, 34.119263, 34.288776, 35.93025],
+                [34.140266, 45.39091, 33.197502, 34.189434, 35.96681],
+            ]
+        )
+
+        cc = np.array(
+            [
+                "2023-02-04T15:05:23.49998",
+                "2023-02-04T15:05:53.49998",
+                "2023-02-04T15:06:23.49998",
+                "2023-02-04T15:06:53.49998",
+                "2023-02-04T15:07:23.49998",
+            ],
+            dtype="datetime64[ns]",
+        )
+        cd_spsdl_avg = np.array(
+            [
+                [62.4551, 59.374382, 58.97122, 61.07321, 59.783104],
+                [61.14534, 58.064617, 57.62369, 59.71631, 59.29018],
+                [62.43891, 59.358192, 59.07586, 61.207146, 60.29722],
+                [61.163094, 58.08237, 59.036198, 61.416603, 60.38328],
+                [62.242744, 59.162025, 57.95079, 59.82794, 58.536304],
+            ]
+        )
+        cd_spsdl_sum = np.array(
+            [
+                [77.22632, 74.14559, 73.74243, 75.84442, 74.55432],
+                [75.91655, 72.83583, 72.394905, 74.487526, 74.06139],
+                [77.21013, 74.1294, 73.84707, 75.97836, 75.06843],
+                [75.9343, 72.853584, 73.80741, 76.18781, 75.154495],
+                [77.01396, 73.93324, 72.72201, 74.59916, 73.30752],
+            ]
+        )
+
+        np.testing.assert_allclose(td_spsdl_dd.head().values, cd_spsdl_dd, atol=1e-5)
+        np.testing.assert_allclose(
+            td_spsdl_md.head().values, cd_spsdl_md_head, atol=1e-5
+        )
+        np.testing.assert_allclose(
+            td_spsdl_md.tail().values, cd_spsdl_md_tail, atol=1e-5
+        )
+        np.testing.assert_allclose(td_spsdl_avg.head().values, cd_spsdl_avg, atol=1e-5)
+        np.testing.assert_allclose(
+            td_spsdl_avg["time_bins"].head().astype("int64"), cc.astype("int64"), atol=1
+        )
+        np.testing.assert_allclose(td_spsdl_sum.head().values, cd_spsdl_sum, atol=1e-5)
+        np.testing.assert_allclose(
+            td_spsdl_sum["time_bins"].head().astype("int64"), cc.astype("int64"), atol=1
+        )
+
     def test_fmax_warning(self):
         """
         Test that fmax warning adjusts the maximum frequency if necessary.
@@ -224,7 +352,7 @@ def test_validate_method(self):
         """
         Test the validation of the 'method' parameter in band_aggregate or time_aggregate.
         """
-        from mhkit.acoustics.analysis import _validate_method
+        from mhkit.acoustics.spsdl import _validate_method
 
         # Valid method string
         method_name, method_arg = _validate_method("median")
diff --git a/mhkit/tests/acoustics/test_io.py b/mhkit/tests/acoustics/test_io.py
index 8d4642a4b..90ca1201d 100644
--- a/mhkit/tests/acoustics/test_io.py
+++ b/mhkit/tests/acoustics/test_io.py
@@ -6,7 +6,6 @@
 
 import mhkit.acoustics as acoustics
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -255,6 +254,61 @@ def test_calibration(self):
             td_spsd["time"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
+    def test_wispr(self):
+        file_name = join(datadir, "WISPR_230825_003936.dat")
+        td = acoustics.io.read_wispr(file_name)
+
+        # Check time coordinate
+        cc = np.array(
+            [
+                "2023-08-25T00:39:36.000000000",
+                "2023-08-25T00:39:36.000020000",
+                "2023-08-25T00:39:36.000040000",
+                "2023-08-25T00:39:36.000060000",
+                "2023-08-25T00:39:36.000080000",
+            ],
+            dtype="datetime64[ns]",
+        )
+        # Check data
+        cd = np.array([-0.00167847, -0.00167847, -0.00152588, -0.00183105, -0.00106812])
+
+        np.testing.assert_allclose(td.head().values, cd, atol=1e-6)
+        np.testing.assert_equal(td["time"].head().values, cc)
+
+    def test_read_wispr_metadata(self):
+        from mhkit.acoustics.io import _read_wispr_metadata
+
+        file_name = join(datadir, "WISPR_230825_003936.dat")
+
+        with open(file_name, "rb") as f:
+            metadata = _read_wispr_metadata(f)
+
+        expected_metadata = {
+            "version": 1.2,
+            "time": "08:25:23:00:39:36",
+            "instrument_id": "PERI_1",
+            "location_id": "PWSPNE",
+            "volts": 15.77,
+            "blocks_free": 20.98,
+            "file_size": 58575,
+            "buffer_size": 16896,
+            "samples_per_buffer": 8448,
+            "sample_size": 2,
+            "sampling_rate": 50000,
+            "gain": 0,
+            "decimation": 16,
+            "adc_vref": 5.0,
+            "file_length_sec": 299.904,
+        }
+
+        # Assertions to check if metadata matches expected values
+        for key, expected_value in expected_metadata.items():
+            self.assertIn(key, metadata)
+            if isinstance(expected_value, float):
+                self.assertAlmostEqual(metadata[key], expected_value, places=6)
+            else:
+                self.assertEqual(metadata[key], expected_value)
+
     def test_audio_export(self):
         file_name = join(datadir, "RBW_6661_20240601_053114.wav")
         P = acoustics.io.read_iclisten(file_name)
diff --git a/mhkit/tests/acoustics/test_metrics.py b/mhkit/tests/acoustics/test_metrics.py
index b41085f08..5c679acc5 100644
--- a/mhkit/tests/acoustics/test_metrics.py
+++ b/mhkit/tests/acoustics/test_metrics.py
@@ -6,7 +6,6 @@
 
 import mhkit.acoustics as acoustics
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -60,68 +59,82 @@ def test_spl(self):
         )
         cd_spl10_head = np.array(
             [
-                [68.88561, 75.65294, 68.29522, 75.80323, 82.53724],
-                [62.806908, 69.76993, 62.64113, 73.26091, 83.27883],
-                [71.73166, 68.541534, 68.056076, 75.438034, 84.268715],
-                [70.84345, 68.65471, 63.4681, 72.818085, 77.38771],
-                [69.23148, 74.04387, 64.49707, 74.146164, 79.52727],
+                [63.707756, 73.40367, 71.83326, 74.295204, 82.49378],
+                [61.048367, 68.54169, 63.2604, 71.18353, 82.87061],
+                [67.130325, 69.02487, 69.4047, 74.431915, 83.363075],
+                [66.81117, 68.42907, 65.77348, 71.172745, 75.995766],
+                [66.638435, 73.6602, 65.55014, 72.049995, 79.03914],
             ]
         )
         cd_spl10_freq_tail = np.array(
-            [19952.62315, 25118.864315, 31622.776602, 39810.717055, 50118.723363]
+            [15848.931925, 19952.62315, 25118.864315, 31622.776602, 39810.717055]
         )
         cd_spl10_tail = np.array(
             [
-                [80.50317, 80.87118, 83.18715, 81.44459, 73.96579],
-                [81.933586, 81.51899, 83.47768, 81.85002, 74.25242],
-                [81.261314, 81.41166, 83.528534, 81.81753, 74.15244],
-                [81.70521, 81.42419, 83.45481, 81.4712, 73.85561],
-                [80.90549, 81.397545, 83.36795, 81.5738, 74.3497],
+                [82.50739, 80.50211, 80.871185, 83.187004, 82.15865],
+                [83.363846, 81.93087, 81.5197, 83.476814, 82.54627],
+                [83.13403, 81.25866, 81.41169, 83.52817, 82.50404],
+                [83.35105, 81.70449, 81.42432, 83.45459, 82.16487],
+                [83.0968, 80.904686, 81.39755, 83.36778, 82.327],
             ]
         )
-        cd_spl3_freq_head = np.array([10.0, 12.59921, 15.874011, 20.0, 25.198421])
+        cd_spl3_freq_head = np.array([10.079368, 12.699208, 16.0, 20.158737, 25.398417])
         cd_spl3_head = np.array(
             [
-                [68.88561, 75.65294, 68.29522, 75.80323, 82.53724],
-                [62.806908, 69.76993, 62.64113, 73.26091, 83.27883],
-                [71.73166, 68.541534, 68.056076, 75.438034, 84.268715],
-                [70.84345, 68.65471, 63.4681, 72.818085, 77.38771],
-                [69.23148, 74.04387, 64.49707, 74.146164, 79.52727],
+                [63.88229, 73.85718, 71.21643, 75.30319, 82.05813],
+                [61.557175, 68.491905, 63.157738, 73.00873, 83.248314],
+                [67.5524, 68.75996, 69.92572, 74.80283, 84.11074],
+                [67.03263, 68.281166, 66.243065, 72.29833, 77.29135],
+                [67.13636, 73.57136, 65.761345, 73.54653, 79.427895],
             ]
         )
         cd_spl3_freq_tail = np.array(
-            [20480.0, 25803.183102, 32509.973544, 40960.0, 51606.366204]
+            [16384.0, 20642.546481, 26007.978835, 32768.0, 41285.092963]
         )
         cd_spl3_tail = np.array(
             [
-                [80.37833, 81.21788, 83.5725, 80.37073, 72.06452],
-                [81.848434, 81.772064, 83.928505, 80.70311, 72.164345],
-                [81.13474, 81.67803, 83.96902, 80.6636, 72.07929],
-                [81.532005, 81.694954, 83.796875, 80.38368, 71.94872],
-                [80.70353, 81.6905, 83.76083, 80.53248, 72.248276],
+                [82.13845, 80.43939, 81.25442, 83.51936, 80.834045],
+                [83.07329, 81.89704, 81.748245, 83.87166, 81.16063],
+                [82.843, 81.24031, 81.632744, 83.92745, 81.09888],
+                [83.10067, 81.60538, 81.68111, 83.73491, 80.842834],
+                [82.74249, 80.793686, 81.695526, 83.699776, 81.01264],
             ]
         )
 
-        np.testing.assert_allclose(td_spl.head().values, cd_spl_head, atol=1e-6)
-        np.testing.assert_allclose(td_spl.tail().values, cd_spl_tail, atol=1e-6)
+        np.testing.assert_allclose(
+            td_spl.head().values, cd_spl_head, atol=1e-6, rtol=1e-6
+        )
+        np.testing.assert_allclose(
+            td_spl.tail().values, cd_spl_tail, atol=1e-6, rtol=1e-6
+        )
+        np.testing.assert_allclose(
+            td_spl["time"].head().astype("int64"), cc.astype("int64"), atol=1
+        )
+
         np.testing.assert_allclose(
             td_spl10["freq_bins"].head().values, cd_spl10_freq_head, atol=1e-6
         )
-        np.testing.assert_allclose(td_spl10.head().values, cd_spl10_head, atol=1e-6)
+        np.testing.assert_allclose(
+            td_spl10.head().values, cd_spl10_head, atol=1e-6, rtol=1e-6
+        )
         np.testing.assert_allclose(
             td_spl10["freq_bins"].tail().values, cd_spl10_freq_tail, atol=1e-6
         )
-        np.testing.assert_allclose(td_spl10.tail().values, cd_spl10_tail, atol=1e-6)
+        np.testing.assert_allclose(
+            td_spl10.tail().values, cd_spl10_tail, atol=1e-6, rtol=1e-6
+        )
+
         np.testing.assert_allclose(
             td_spl3["freq_bins"].head().values, cd_spl3_freq_head, atol=1e-6
         )
-        np.testing.assert_allclose(td_spl3.head().values, cd_spl3_head, atol=1e-6)
+        np.testing.assert_allclose(
+            td_spl3.head().values, cd_spl3_head, atol=1e-6, rtol=1e-6
+        )
         np.testing.assert_allclose(
             td_spl3["freq_bins"].tail().values, cd_spl3_freq_tail, atol=1e-6
         )
-        np.testing.assert_allclose(td_spl3.tail().values, cd_spl3_tail, atol=1e-6)
         np.testing.assert_allclose(
-            td_spl["time"].head().astype("int64"), cc.astype("int64"), atol=1
+            td_spl3.tail().values, cd_spl3_tail, atol=1e-6, rtol=1e-6
         )
 
     def test_nmfs_weighting(self):

From dd25feb87620e411133f24b6f51bf00871619a56 Mon Sep 17 00:00:00 2001
From: James McVey <james.mcvey@pnnl.gov>
Date: Wed, 8 Jul 2026 09:04:41 -0700
Subject: [PATCH 8/9] Refactor DOLfYN PSD Scripts to use Scipy.Signal.Welch
 (#452)

This refactor solves a DOLfYN structural problem between its binning
architecture and the traditional sliding-window architecture of Welch's
algorithm. Because DOLfYN was using slices of bins to compute each PSD
segment, it was impossible to ensure data overlap between one bin and
the next, meaning the industry-standard 50% overlap cannot be
accomplished. This PR removes the bin structure from the PSD computation
and ensures overlap using a "step" argument, which is also now built
into the bin structure to properly average dimensions for the PSD.

In doing this, DOLfYN's custom PSD code, which was a custom
implementation of Welch's algorithm without the ability to overlap FFT
segments, has been replaced with scipy.signal.welch. This has one
breaking change, in that NaN's are no longer tolerated in the PSD
calculation.

To avoid breaking changes, the DOLfYN code will default to an overlap of
0%. This ensures array shapes will remain the same. On the other hand,
since it's new, the Acoustics module will default to 50%.

The second breaking change is that the PSD code now renames the input
time dimension to "time_psd". In this way, if a different overlap is
used, and the PSD is saved into dataset with an averaged "time"
dimension, the PSD will not follow the xarray default and go to nan.

Finally, I removed the float32 datatypes in certain functions since
sometimes we do need float64 precision. Removing custom code means
fft.py no longer exists, and tools/misc.py was renamed to tools.py
---
 examples/acoustics_example.ipynb              |   144 +-
 examples/adcp_example.ipynb                   | 10135 +++++++---------
 examples/adcp_waves_example.ipynb             |   404 +-
 examples/adv_example.ipynb                    |   142 +-
 .../data/dolfyn/test_data/BenchFile01_avg.nc  |   Bin 89659 -> 87168 bytes
 .../data/dolfyn/test_data/BenchFile01_func.nc |   Bin 12274 -> 12790 bytes
 .../dolfyn/test_data/Sig1000_tidal_bin.nc     |   Bin 108658 -> 109732 bytes
 .../dolfyn/test_data/vector_data01_bin.nc     |   Bin 48122 -> 49540 bytes
 .../dolfyn/test_data/vector_data01_func.nc    |   Bin 17278 -> 17976 bytes
 mhkit/acoustics/analysis.py                   |    61 +-
 mhkit/acoustics/sel.py                        |     5 +-
 mhkit/acoustics/spl.py                        |    18 +-
 mhkit/acoustics/spsdl.py                      |    71 +-
 mhkit/dolfyn/adp/clean.py                     |     2 +-
 mhkit/dolfyn/adp/turbulence.py                |    46 +-
 mhkit/dolfyn/adv/api.py                       |     2 +-
 mhkit/dolfyn/adv/clean.py                     |     2 +-
 mhkit/dolfyn/adv/turbulence.py                |   239 +-
 mhkit/dolfyn/binned.py                        |   319 +-
 mhkit/dolfyn/io/nortek.py                     |     2 +-
 mhkit/dolfyn/time.py                          |     2 +-
 mhkit/dolfyn/{tools/misc.py => tools.py}      |     4 +-
 mhkit/dolfyn/tools/__init__.py                |     2 -
 mhkit/dolfyn/tools/fft.py                     |   316 -
 mhkit/dolfyn/velocity.py                      |   138 +-
 mhkit/tests/acoustics/test_analysis.py        |   135 +-
 mhkit/tests/acoustics/test_io.py              |    60 +-
 mhkit/tests/acoustics/test_metrics.py         |    86 +-
 mhkit/tests/dolfyn/base.py                    |     2 +-
 mhkit/tests/dolfyn/test_analysis.py           |    49 +-
 mhkit/tests/dolfyn/test_shortcuts.py          |     5 +-
 mhkit/tests/dolfyn/test_tools.py              |    86 +-
 32 files changed, 5692 insertions(+), 6785 deletions(-)
 rename mhkit/dolfyn/{tools/misc.py => tools.py} (98%)
 delete mode 100644 mhkit/dolfyn/tools/__init__.py
 delete mode 100644 mhkit/dolfyn/tools/fft.py

diff --git a/examples/acoustics_example.ipynb b/examples/acoustics_example.ipynb
index fc3101bac..a627a740d 100644
--- a/examples/acoustics_example.ipynb
+++ b/examples/acoustics_example.ipynb
@@ -152,7 +152,16 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:250: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=48000 samples, pct_overlap=0.5).\n",
+      "  psd = binner.power_spectral_density(\n"
+     ]
+    }
+   ],
    "source": [
     "# Create mean square spectral densities using 1 s bins.\n",
     "spsd = acoustics.sound_pressure_spectral_density(V, fs=V.fs, bin_length=1)"
@@ -286,7 +295,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -358,7 +367,7 @@
     },
     {
      "data": {
-      "image/png": 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b8bnPfQ5//vOfS46u1NfX4+6778bKlSvxox/9CL/+9a9xxx13+I5Zt24dHn74YTz22GN47LHHsHTpUnzve98DAPzoRz/Ccccdh0svvRQ7duzAjh07MHPmzGGv+8QTT+DCCy/E1772NaxcuRK//OUvcffdd+Pmm28GAPz1r3/FHXfcgV/+8pdYs2YNHn74YRx66KEl3VOlKJtcNTU1YceOHXnbly1bhunTp1elU/saOvtz2Ng1tKe7MW5huwRWRK58sCscj3GzWjB63KOO8fEmRBgJ1qxZA0opDjzwwND9Bx54IHp6erBz586S2vv2t7+N448/Hm1tbTjnnHPw3//93/jLX/7iO4YQgrvvvhuHHHIITjrpJHz+85/H008/DQBobGxEPB5HKpVCa2srWltbYRjGsNe9+eabcfXVV+Oiiy7C3LlzsWjRInz3u9/FL3/5SwDA5s2b0draio9+9KOYNWsWPvjBD+LSSy8t6Z4qRdnk6oILLsA3v/lNtLe3Q9M0EELwwgsv4KqrrsK//du/jUYf9wlE6lXlcAiFNU4KDu8OPLd6J666/230Z8uvCjBecpnGSz8jRBjP4IqVmgJUDH/9619x4oknorW1FXV1dbj22muxefNm3zFtbW2or68Xv0+dOhWdnZ0j6ucbb7yBG2+8EXV1deI/rn6l02l8+tOfRiaTwdy5c3HppZfioYce8oUMRwNlk6ubb74Zs2bNwvTp0zE4OIiDDjoIJ598Mo4//nh8+9vfHo0+7hPY1pPB1p6oDmEl6BnKVUQk9lb82/+9iv/vre34ydNryj53vAiAEbWKEGHkmDdvHjRNw8qVK0P3v//++5g0aRKampqgaVpeeFDNp3r55Zfxmc98BmeccQYee+wxLFu2DN/61rdgWZbvnFgs5vudizQjASEEN9xwA9566y3x3/Lly7FmzRrU1NRg5syZWLVqFX72s58hmUzisssuw8knn+zrf7VRthVDLBbDH/7wB9x4441YtmwZCCE44ogjMH/+/NHo37iA5RIYtgtC2TdqTQNS8fJdLl7b2I0ZzalR6OHei+4hC+f//CVMrk/g1W99dE93Z0xhR1+27HPGiyI0XhLvqwVK6bhaKRVhfKClpQWLFi3C//t//w9XXHGFL++qvb0df/jDH/CVr3wFAMurVlOC1qxZg3RaCgIvvPACZs+eLRLgAWDTpk1l9ykej8N1y1ukdOSRR2LVqlWYN29ewWOSySQ+/vGP4+Mf/zi+8pWv4IADDsDy5ctx5JFHlt3HUlA2A1i6dClOOeUU7Lfffthvv/1Go0/jDne9uBl6wk+KZk9I4cMHTEZDMlbgrHxs7Eqjoz+LKQ011e7iXovXvXBq50BuD/dk7CFeSQ3LccJZxgkHjBBhzOOnP/0pjj/+eJx++um46aabMGfOHKxYsQJf//rXsWDBAlx33XUAgA9/+MP46U9/imOPPRaEEHzzm9/0qVDz5s3D5s2b8ac//QlHH300Hn/8cTz00ENl96etrQ2vvPIKNm7ciLq6OkyYMGHYc6677jqcffbZmDlzJj796U9D13W88847WL58OW666SbcfffdcF0XxxxzDFKpFO69914kk0nMnj277P6VirI/fRctWoRZs2bh6quvxrvvvjsafdorsKk7jd+/sglvbekty8fqpXXRistyYCju9uMlGXt3wTTKVzrGjXI1TvpZLeyJ24389/YNzJ8/H6+99hrmzp2Lf/mXf8Hs2bNxxhlnYMGCBXjhhRdQV8fq4P7whz/EzJkzcfLJJ+OCCy7AVVddhVRKigqf+MQncMUVV+CrX/0qDj/8cLz44ou49tpry+7PVVddBcMwcNBBB2HSpEl5OVthOP300/HYY49hyZIlOProo3Hsscfi9ttvF+SpqakJv/71r3HCCSdg4cKFePrpp/Hoo4+OqkGqRsv8C+rq6sKf/vQn/PGPf8RLL72EQw45BBdeeCEuuOACzJgxY7T6OSbR39+PxsZGfOf+l1FX3wRdY/HjniELT73fge29LCwztbEGHz1wCibUlpYU+K9Hz8S0puTwB0bAs6s6cfFdrwEA3r3hdNQlKio6MKqwbRuLFy/GmWeemZdvMBpou/pxAMAFx8zCLeeVt9z4vlc244JjZo1Gt6qK9TsHMXcvLH5e6F0hhO72MlkDWRv1NaP/vu4NyGaz2LBhA+bMmYOamtGPPBBC0N/fj4aGBuh6BQr1MPjOd76D22+/HU8++SSOO+64qrc/1lHsefJ5v6+vDw0NDQXbKPupTJw4EV/96lfxwgsvYN26dfjXf/1X/O53v0NbWxs+/OEPl38XewFiug5D10RORHNtHJ86cgZO3X8SYoaGHX1Z3PfKZizf1ldSey9G6lVFSOdGd/XHeEMlYcHxogiNZ5EyUoQijHXccMMN+PGPf4xXXnllxMnm+ypG9DV/zpw5uPrqq3HYYYfh2muvxdKlS6vVr3EPTdOwcEYT2ibW4h/vd2LTrjSWrt6JuRNrUTuMurKlO40t3WnMnBAltw8H1YJhKHJq98GsQOkYDxM/6+PY72c1sW/dbYSxgC984Qt7ugvjGhXriS+88AIuu+wyTJ06FRdccAEOPvhgPPbYY9Xs216BhpoYPnHYNExtrIFLKJZt6S3pvCj3qjTkVHIVKVc+mBUoVyOZxHcXMRsH/K8oxkv/x0k3I0QYkyj70/d//ud/MGfOHHz4wx/Gpk2bcOedd6K9vR2///3vccYZZ4xGH8c9NE3DUbObAQDLt/YhV0Kh4W29mci1vQSoRZvT41i5qtRRvRjigYT2UuwLRmJxsLtCdeMldFkIlfR+PCiKESJEkCibXD377LO46qqrsG3bNjz++OO44IILfCsGxgra2tpE4Uf1P+7ZQSnF9ddfj2nTpiGZTOJDH/oQVqxYMWr9mTOxFi21cVguwdtbo9yrasGnXFl+5Wo8rR6slsO8So6CylVwfELPH8GQ7S7SQzF+1J8I+xYiErx3oBrPsWxy9eKLL+IrX/kKJk6cOOKLjyZee+01Ufhxx44dWLJkCQDg05/+NADgtttuw+23346f/vSneO2119Da2opFixaJ6tzVhqZpOKqNqVdvbektSano6M9iS3fk2l4MKrlK5/zK1c5x5H1VLeVKrbEYtGIYLCFsOhKCtNvI1V4wf5X74b2nbjkiC6WBr+xUTTUjjF/w5ziS1d0VJbTfe++9+MUvfoENGzbgpZdewuzZs3HnnXdizpw5+MQnPlFxZ6qJSZMm+X7/3ve+h/322w+nnHIKKKW488478a1vfQvnn38+AOCee+7BlClTcN999+FLX/rSqPRpweR6vLRuF/qzDlZs78fhM5uGPWdHXzZKbC+CnCMJVVCZ2dGXQWvj+DBkrVbhabWdWGCJdik5aSOZS6N5uDRQSoFx4LbuuNEDLRWGYaCpqUnUyEulUqPqqE8IgWVZyGazo2LFsK+CUop0Oo3Ozk40NTWVVDS6EMomVz//+c9x3XXX4fLLL8fNN98sbOqbmppw5513jhlypcKyLPz+97/HlVdeCU3TsH79erS3t+O0004TxyQSCZxyyil48cUXC5KrXC6HXE6qIf39/QAAlxAQUlq+z5GzmvDs6i68uakHB0+t85lghmFb9yDsGfVFj9mXkVZqCg5kLF+tqK3dQzhk6p73QuJ9KlbHKpO1YNdU/ofMkc6oah3xXXMwMD5hsF2n6DEuoQXf2ZzlwBjZAuSSYDkEtl28n2MZjktAFOsWFYXeFdslANm9k6hl27BtRGV3SkRLSwtc10VHR8eoX4tSimw2i5qamuj5jAIaGhrQ0tIS+hlT6udO2Z+EP/nJT/DrX/8a5557Lr73ve+J7UcddRSuuuqqcpvbLXj44YfR29uLiy++GACrmQQAU6ZM8R03ZcqUorWQbr31Vtxwww152zdu2Ih4sjR1KUaBuK5hIOfg+XfWYXpt8eO3rKfQty4rqe19Ee9t0sGj28uWr8DEblY1wCbAazs1kE1j59s3D02HYWcGmFQF39ieHMD/rFeuXInFPSyPkFJg6xCwaRiu+d42DYv73yu43yGAWWCOz7pAFfjhsHAIsDMLrNmDgu5IxCeXsHOLfa8KvivFxn20MGgDtea4ENnGFDRNG5HiEWHPwnXdouHwUkO/ZZOrDRs24IgjjsjbnkgkMDQ0Nle3/fa3v8UZZ5yBadOm+bYHGf9wxVGvueYaXHnlleL3/v5+zJw5E21z2lBbX9ipNYihRC9eXN+NrbkETjlsxrDfPE45oW1Yb6x9FW88/j6wnZVHmNk2D2cuYgXEO/qz6H63A2ceP3q1o0qFbdtYsmQJFi1aVDCGv6ZzEPMnj1xl29KTBt78JwDggAMOxJkntAFgie4rdvTj0OmNxc9/bgPOPHlOwf1Z20VNLHzi2F2O3jmHYNOuISyYsucU3WIK3nCwXQJD00Id1wu9KzmHILGb2dWuwRyaU/Hd7gwfYXiU8pkSYXTAI1bDoewZe86cOXjrrbfyCh7+7W9/w0EHHVRuc6OOTZs24amnnsKDDz4otrW2tgJgCtbUqVPF9s7Ozjw1S0UikUAikcjbbug6dL30byoLZzbh9c296Enb2LAri3nDTKrdGRdNdbu3HA6lFJRizH+w2kqq0pBNxAfNoJ2BTUaWkFhtxGKxgv0h0KvSV9OQbWi6bNMlFIZhDnsN9ZwwWERDLBb+sWHYu2e8iebCNAuP5e6A5pKKfMQAAHphcsURfFeI5iJmhn/GDPelsFLohotYLDbmPwP2ZRT7TIkwOih1vMv+dPj617+Or3zlK/jzn/8MSileffVV3Hzzzfif//kffP3rXy+7o6ONu+66C5MnT8ZZZ50lts2ZMwetra0+6d2yLCxduhTHH3/8qPcpYRo4bAZTEEopidPRv/tXveUcgjWdg7v9uuVC9QwbyMqE7d60Dcsh48aOoVqrBamyrky9dUppSav5hvO5corsH63VgsE+jYXE+ZG8VpRWd/XfaI1HsWcdIUKE4ihbufrCF74Ax3HwjW98A+l0GhdccAGmT5+OH/3oR/jMZz4zGn2sGIQQ3HXXXbjoootgmvJWNU3D5ZdfjltuuQXz58/H/PnzccsttyCVSuGCCy7YLX07oLUBr23swbaeDCyHIF5E8u8cyO6WPqmwXIK3tvRg/9axnUyvWjGoVgO9aZZ0mLXdcRFSdQmtSnFeSgv8jNImdOYhVVgJKUa+Ro1cUQodgRD+HvYP393XLza0YeNTteuOSqsRIuz9qGjWufTSS3HppZeiq6sLhBBMnjwZQ0NDeO6553DyySdXu48V46mnnsLmzZtxySWX5O37xje+gUwmg8suuww9PT045phj8OSTT6K+fveQieZUDA01JvqzDrb2pDF3UuHQYEf/HiBXDsH23iza+7J5dgb9WRvdgxZmTUjt8ZCBz4pBIVd9GQvA+CFXDqFwqzBJqgQnSHZK9SwiFDAKdMMt0sZoCR1jUUAZC+oZx2h1ZQzdYoQI4w4jypCcOHEiJk+eDABYu3YtTj311Kp0qlo47bTTQCnFggUL8vZpmobrr78eO3bsQDabxdKlS3HIIYfstr5pmoa2iWyp4IZdxRcCDOVcDGTzl3+u2zl6YTvuGL5sc0/evu29GTy0bBt+88/1vvIzewJZO7y2IFeuMmX2jxC6R0KJhJQWthsOagsqmaK0NELAjitCoIqMzWgZTu5plSoMI/IDA63qWI3W+zqSUkgRIuzriNzH9iDaWhi52tiVHvbDNizv6o1NPaNWrJiTqzWdg3nO3j1DjLgM5Vys2F7ayonRQlhtwZzjip9V8lUKhiwHi5fvqF4HS4RDKEgV0q7U18iXcwVasgJU7Lg9oVyFXXJPK0djqb7heMkrjBBhX0JErvYgZjYnYegaBnMOdg1ZRY/tDIQGB7I2tvdm0DlKJV6407dLKNYFEtt707Kvy7f27tESGVknn1z1paXKV66yZjlkj5TNcSktSlxKR3hYcDhFSp5NiypFxSby0VKYxhCPERhJlyq5n2LnjFbieanvTIQIEfIRkas9CNPQMbOZWSxs7CoeGuwIJLWv7hgApfmkq1rIKYpPkMD1ZiR56Unb2NKdGZU+lAJVmeIhQLV/ZZMrl/gIG4dTZDVfNSYg161OOJIUUK7Cfi+EYrdTrI+jl3M19ib4kTzzaq8WHK3w3VgMx0aIMF5QcqbvI488UnT/hg0bRtyZvRlHzGrCss29edvbWmqxcVcaG3YN4ai2CQXPD4YFV7UzNWn0lCtJMLoG/dfoSftVtre39mJWy56xy1YT2jOectXrU67Ki7VZDoHlkLyVe70ZGxPr8j3O+DWS8ZE5Mru0Onk4/tWCAeWqhMlyuNysouRqmHysSr2YwsjVnuZbI+Ez7H6qtxDEqdJKUw7e1p4e4wgRxjNKJlfnnnvusMdENY7Cccr+k3DkrGZs7BpCT9qfmN42sRZYvRM7+rJF3a8zlou+tI3GVAw9Q5ZYQThaKwlVi4NdgznxgZu2HJ+qBQyvuo0m1L5kHVa2oE9RrlZ3DGDhzEY0lOgcbjkElLK2UnH559GbLkau3JGTqyol0tMCYUGgdEJSTCkqtq+4XUD+CsRSCVdwWMbEpD9iclXu5YoT12raMVDl37Ew1BEijEeUHBYkhAz7n+vu2ZVjYw2aBiw6aAqOnNUMAJjenK/uNCZjmJCKg1Jgc3fxmkU8NLiqY0BsG8g6QrGpJiyFXNkuFWpVkBwC7JuzevzuhEoCKWW/9yvkqi9j44l328tuL6h4cWuHMJS7IjEMLqlOzlXxhPbi7XOlq9hRxbxOi7UfRhxLD1OGKFfj2OeKlLhys/S+VDcky5/jWAzHRogwXhDlXI0SdE3Dxw5pxSFKLbcZzeElbNomMtI1bN6Vp1Ktah/wbR8Nk9EgWdrphQZ7CiTeh+Up7Q4E+zmYczBk+Vc3buvNoD/EyiK0PZeTK//98BWSYaiGHQWho7FasDwrBr6/XJIUdr1S9pWq1O1tc3y1k8RJie77EaIE/Qi7DxG5GgWYuoazFk7FAa3+Ys7TC5Erbsmwq7glQ0d/Dp0DWXQHCM5o5F1ZAYmCr6DjZWWC/dxTfle5AKnLWG6edQSlwOoAIS0ETtaCapSaJB/ESJWrwZyDbb2ZqkyQQUIlfkbpSsRwbuCF95XXZqn9yQtvjoFg1Yh8rqq8WrBUD7Pyr0n3OmIbIcLuQkSuRgGnHjA5tBhzQ00MDcn83J9pTUnEDR0Z20VHEaLUOZDNU62A4fOutveWv5ovT7ny+rWhaxC/fn49/vjqFp+xaTAPa3fAdomY0Hku70DWRs4m2N6bwe9f3oStPSzUOlzIlcNy8pWrnOMiYxX2Eys3aT6Izv4scnb16yD6E9qHpyQi16ZC5arQeezaYWHBUslVWJslnTpqGJEVA6pLEMshzmW1GxGrCBEqRkSuqozpzUkcPK2h4P6w0KCha5g1YfjQYM4meGdrfqHnziKFnbO2i0ff3p6n8AyHXAFy9d6OfjiEYudgDn95fatYSbgnlCu1j/Vewjr3C3tw2TbsGrLw2DvMEDSo9hWCFZJzlbVJUS+hkd47v4+qOLQXzLkqr/xNIRQv3Fy4T2H7Sg4LjgGlKojRCC9V2iYh1R0h3o2xN+oRIowfROSqijB0DR85YHLRFVDTm4bJuxqmFE5Y4nhfxi44wS/b3Iu05WJNR36pnLCSOoWuk/bCbe0KkRvMOXho2TZkbHfE6k0lyCn3XF/DVvb1DFmwXakC5bwQ5mDOgV0sG9sDD4eqbbf3ZfG7lzbh7wUS46tFrkZztWApoaP+jIX1OwdhFSHilawkJAVsJqrhu7WvYFjVMVKuIkQYUyibXF188cV47rnnRqMv4x5HzmpGS4Hl+hwFk9q9vKuO/lxezlApCHMVtxyCt7b0AgBW7vCXqdk1mMMfX91cMNF7ycoOvLRul+9De/3OQbESb8GUOkxIxZG2XDy/ZuceSWjnpCRmaMI2oSdt54UAuwYtUJrvzxXeJrsPNY/qe397Dxu6hvDl37+RdzyldMTE0qqicuVTq2jhfWG45J7X8eg7O/DLpesLt19BQnuhJf2lml8Gmx0Lk/5Iu1DNexitZHZSIJwbIUKE4VE2uRoYGMBpp52G+fPn45ZbbsG2bdtGo1/jDg3JGI6ZW9gElKMpFRcqi4rahImpjTUAgPd3lF+vLyzvavm2XqGqbO/N+MrCvLKhG0M5F4+8tT1P0elL2/jn2i68urEbXYOSkKzukHUGJ9Yl8NGDWNHu93YM4PWNPWX3eaTg5CphGkjF2avcl7GxaZefXPG8q2Ir/jg40RlS7C02F3GgdwiFM8JlfpzQVSPlSiXDvkmXDq9ucJPbR97eXvCYcpPW+fawfdUp97NnMLKE9kK5aZX3paphQa+10UqUjxBhX0DZ5OqBBx7Atm3b8NWvfhX3338/2tracMYZZ+Cvf/0rbLu05e57I07dfxJiRmnDWSg0yHO13t3eX7bMH1wx6LgEb27qFb9TCrzXzkjbrsEcVnteWTsHcnhyRYfvXNXT6f12SfS29WQEuapLmJjamMRhM5jVxN0vbiirvyp6S1CUwsCJY9zUkYzLsCBvrynF8rD42JSSd/Xy+l0+hQ5A0eLYjkthuyObgfhigKrkXCk/+8KCZRVursxuoSC5QvjsX/LqxRFSh9EoDzOWFB2Kkd1joc+ayN4hQoTKUVHOVUtLC/7rv/4Ly5Ytw6uvvop58+bh85//PKZNm4YrrrgCa9asqXY/xzTaWlKYOyl/dWAhFLJkmD+5HjFDQ1/GxrYyV/gFawy+vbUvL7z4nqeIvbKh2zcRru4Y8NXOU0nIqvYBn6mgSq4A4INzmFrX0Z+rOPdoR19lPl1SudKR9Jzte9IW+rOsj9Ma2Thzk9ViRqAAG8OHlm3Ho+/swC5FsQv6ZqlwCClad7AUVDXnqlBCOwVK1Tcq9bIqRDiYshKSczWCYStn3h+oIMw+fAeq32TRyxUltSNz96/UeqP860RkLcK+gxEltO/YsQNPPvkknnzySRiGgTPPPBMrVqzAQQcdhDvuuKNafRzzOGFeS1nHzwhxageYArP/lHoAwIrt5YUGezM2co6LLd1p/OX1LXhu9c78Y9I2lm/tE6qViqGcJEY9qmpjudjaw4gepVSoOHVeaDOplOsp1agziB19lRV+5knnCVNHbUKSK56o3+qFWdPeccEVkEGoIdD1XYMiXDecclVsBV0p4NepxtwTtF8QP6P0sGOxcF01w4KV+m6VO0yjkuxd9RYrb5NiZMS80JmlhgUj0hQhQj7KJle2beOBBx7A2WefjdmzZ+P+++/HFVdcgR07duCee+7Bk08+iXvvvRc33njjaPR3TKK+xLp1HBNq40gVqEV38DQWZlvTOehbsTYcKAX+9OoW/PWNrdjWU5is/OP9ztAPzEFFnQmG6Xho0HKICIFx5UrTNMRN9hoNZCtTCLb3jky5qokZqPXCgp0DORDKfK8meYsLuHI1XImeXkXZ2tKdRn+G3c9w1gTlKlfByaiaCe2+sKDSrXIMIavpws76FK5plW7FsPdgNIjISAl+oRqUpARvtAgRIoSj5MLNHFOnTgUhBJ/97Gfx6quv4vDDD8875vTTT0dTU1MVurf3YnpzMtQeYUpDAi11cewatPB+xwAOm9FUcpul5BQVmgDTOZVcMeUnYerIOQRrOwdx6v5EhAQTpu7LL0uYOiyHVESuXEKxa9CC4xKYJeascfAwZE1MR61H9vgY1NfEkPLUrIzFCjoPNwGppX229rCSOZPqi6/+dIjfA2sw5wjiWQhpyxX9ZW3wsGvR00qCPyzob7BU8laU9FSwi/lchYQFS1au8o8rZ9ofHffySs7xEsUruV6RfS4ZWfkb4WtFWSFt/rtbwEIjQoQIw6Ns5eqOO+7A9u3b8bOf/SyUWAFAc3MzNmyoPMF5X0Ch0KCmaTh4KktsX1lmaLAcDOUcbFI8tdT8rD4vLDijOYmGGhO2S7Gxaygv34ojIZSr8sOCPWkLhNJhQ3ZhUFcL1npKIM+VakzGkPJCli6l+Mkza/F8SKhUxS6FXHUPWWIcVKQD+VfBhPZdg8OXIgrmwvGJsTo5V7KNPBPREtsolgtVjNQUTmgvFBYsrT+hKw3LGKtiR1ZacHykmk61rRhG0l4hEu6WaE5a6rXHAk8bC32IsG+gbHL1zDPPhK4KHBoawiWXXFKVTu0LKLRiEAAOmNoAQ9PQOZDLS1SvFv7xficefms7NniO8GrOFQ+HxU0dcyYy/63tvVlJrrx8K67q8LBgb7oCcuURmkrIFfeiSsUNoQRxFaihxoRp6Ih7ahilwOICJqAcqvLnEIptPRmfs33M0PKS74NhwZ607Vu5FZbkH1T4XEJBCAWpQuVm6vtZzb8qPSRVNOeqaBcLJbSHBwYrVUVGmsCtohRj2fA+VHaOGnLL31/peFR0WsHzxQIWMnq1BUdjBWeECGMJZZOre+65B5lMfk5PJpPB7373u6p0al/AxLo4amLheVfJmIH9JjNSs2J7P1xCsaU7jaWrd+LJle1Ysb2v4uRxDk4SuAeUuiKOK1AJwxBJ4e392Tzl6pQFk5CMG0iY7D5KLTGjYpcgV+WvNOShzFTczMth4zUckwVy28LQG/DB2tyd9hHGmpiBHYH8MMdlYUE+MWZt15e/9uamnryJJKjwvbejH798bj1+9sy6kvtaCIULN48sdCTbKbKvwE5SQDYbyfxalnJV5L4r9doayUhSWv51ix1OMTISpPpaAey5UErFv8X7VdmFI5uHCHs7Ss656u/v95JiKQYGBlBTUyP2ua6LxYsXY/LkyaPSyb0RmqZhWlMN1u8ML3dz8LRGrO4YxMod/Xi/Y8AXvnhvB1vt15SM4eg5E3DQ1MK1DMOQthyh+nR45WzUFXEDOTb5x00drQ3sOe8cyKG5lhGWuoSJWRNSmDkhhcZkTFGuyidXnJBVUviZrwJMxg3hc8XBjVpTcSM0vBeGnoBVw9butM/vyiU0b2UjV8pcQmEaGnIOwWDWQYO3yGFzdxptE2p85wSVq7+8vhUAsHRN8bBlSSiUc0VHZn0gmilqxVB4R9i+Uifm0QwLVm7cWf6JFIAGj+hWUbkpZHVR+HjqK9EV7ArvG18EQQiFrmu+83w/V9Bnl9LyE34jRBhHKPn9bmpqgqZp0DQNCxYsyNuvaRpuuOGGqnZub8eM5lRBcjXTy3fqzzoAoUjGDMyZWIvahIGtPRm092fRm7GxZGWH2FcqVIWpcyALQqnPkXwwK805G5MxJGMGMrYrnM/rEiZOmDcRANBQExM5V5WEBdv7M3h8+Q7UJUxcevLcss5N52RYMBlQAfnqweD24MSiIpjIv7U3I2oNAiyEtDOQU8XDSg6hMA1mD8EVPkopdg1ZeSFPNedK9TOLl5nQHwZ1oqs056oYinGCQoShkLJSan+CxIGiPOWn6KEVk6sKz/P+L4wcVvp8CuW0lXy+kmhPiFz4wZt0KYUOLXAOUKSEasF+Roiwr6BkcvXMM8+AUooPf/jDeOCBBzBhgiz1Eo/HMXv2bEybNm1UOrm34sCp9XhpXVeow7emaThr4VRs3JXGjKYkWhtroCufZjnHxfNrurBiez/+vqIdnzl6JppT8ZKuqxpk2i5F95DlW73GVay4qUPTNExpSGDjrjTSHgGbOSElwoWNSYVclagQqVi+tR9rOwfx59e3lE2uBj2FLRk38sKCPByoqjeGpsFyiQhjBsEVrskNCWzpznhFoOX5tkuRtVxkbVeEdIM2CpZLhPVDziGefYWfXKlhwdXt0nOMj+NIUGi1YKEVexVcoew9hZSVSn2ugHKVq2J93n1TvliNh0JKHlAmX5HnltUPPzHyE3KWz1aqxxVrj2typaMaKmqECGMZJZOrU045BQCwYcMGzJo1q+C3/wilIxU3ccj0RlHTLYjJ9TWYXF8Tui9hGjh1/8noHrKwoy+Lx97egX85egZ60zZe39iDrT1pfOyQVsxuyVe0dgVyozr6s5hYl4BLKAxdE/lXXElpbazBRqVeH6+BCMAXFuwvk1w5LhGhxOAqvFLAk/BTMTMvt4qTLbWosksZOSpErnj/m5JxbAEr9RP0sCKUhfU4ueKqFP+2n7MlmeL/Blek9aZtMdH6lbGRT/R+QhVQfKpArioyES2wb3c5tFfSDg+FFUIlRFWEBQsQFwpamKIMc7mRPFtKZBvEywej8Ptc5b1LYntluXOlkNpiKnOECGMdJZGrd955B4cccgh0XUdfXx+WL19e8NiFCxdWrXP7Ao5qm4DlW/sqMgE0dA1nHToVf3ptC7rTFu59eZNv1d9bW3oLkCsW2qpLmBjMOejoz+HgaSypvaEmJpQXrqTwvCsOtXxPQ9JEwmBEo9wyI0M5V1wrY5Wf0M7Da7UJv3KlaTIcOLk+gXZlxWVfxkZjAYWPLxLgNQmHLNdHfgA24Qwo/ldCueLkylOrAKmuBElTxnbRl7HRlIrDUfaNtAA0EFAhVBPRMmoLFm1/mMTq8HPCk+lLVY3CjiqL3BTtczhISCjMd94IcrUKmarurhzv4lFSCtel4plxm4c8tUtRq8rxK2PtaLvtXiNE2FMoiVwdfvjhaG9vx+TJk3H44Yd7fxzhoSzXray+3L6KuoSJg6c34O0tfRWdX5swcdbCqfjrG1sxlHOhAZjdksLGXWls7cnkmXNSStHthQUPnFqP1zb2oMMjH0M5Rq54+C8eQq4MXfP93piMIRFjxw2WuYJx0HJEUnq2koR2S0loV3KrkjFDfOM9br8WmIaGNz11sCdtY1aBakU80bzRW2mYzjl5xMgl1JeQzlc5ciJlOS5yrl/NUsOCG7sGsXxrH3b0ZdCUivvIm+NNaqV8Wy+krPh9rqofFqykcDMppNSUFXbyn1ethPZCGK55dXdegnjBZ8MICqGAUUVyQenIgptByw6uXEn1ShKpsPcz+ByDx6jhUHnNEvpVQV7XsG1Wt7kIEQqiJHK1YcMGTJo0Sfwcobo4qm0C3t3WX7F3T2tDDT5+2DRs68ngoGkNaKgx8X8vbMRgzsGWnowv2T1tucg6BBqAA1ob8NrGHnQN5uC4RORaZR0/uUrEDDSnYuhJ26hLmMLmAGBO6FzhGsyVR6yHco5QrLKOW3YYYEhYMRi+sKCqYtXEDJw0fxLebx9A2nLzVjTaLkHM0EGINDLlK/0ytgs7ENLLJ1d+lSpMuVIJ1Jk//ifSlotJ9Ql875MLfe1TMEIWM4Yfg4ztd3lX2+AIJrRXRbkqtq/M9ksmVyHbqrXYrlA4bTgiSgPEVX1tcw4pagHCyFB5rGE4+lSWkBfIkeLn8iZ4zpXtEKFacSWP36cIC6KwZ1exv2W+8rzoMaXfUoQIYw4lkavZs2eH/hyhOmioieGA1vqyizWrmDUhhVkTpOt728QU3t3Wj41dQz5yxfOtGpMxNKfkSsCuQUuEFLmKFFcSrFsbawS5Uh3aDV1TwmjlhQUHspJcUcompULeX2EQylXMREqxYghrI27oSMNFX8bfx/a+LGZOSAlCCUgfL0KZg7wKHhbkEETKmyxUcmU5LrqHLJ+RKO/zm5t7AOSbWHKyNxyyBciVOiMFizhXI+equBVDgbBggdWCI0loL+deiocywzFc34LE1d9mkXGAVjjnSuE8o1l2Jr+/EjyhXU1sZ9tZvc4wlLJyM2hIWsrdEUphVJziH45Kku8jRKgEFZmIPv744+L3b3zjG2hqasLxxx+PTZs2VbVz+xI+OGeCbzXgSDHHy7XasGvI90HNy7O01MXFSkCAmYQO5RzkHFcoLgllkp/lletpqYsLh3aOiYECyaViKCfDgvz34eC4RCSZqw7tqloVZmnAiWJfwMuKm6mmlb6n4gZMbyYJWi+4hPqOFQntLiNWLqGCXP3l9a249+VNuOelzSH3ka9qAaWXY8kUKOqtkoK8sGBVyusU3lew+QIhyZGEKcu5lUpK9gyvIkuyGha2rKRPwfBceRjJWFKRD0Upy/3jpW9E3lWB9gmlAV+s/JWGUhnj+4bvazmFxstBpIZF2F0om1zdcsstSCZZQvNLL72En/70p7jtttswceJEXHHFFVXv4L6CplQc+7fWVa29mRNSMHQNA1nH52vFf55Qy5K6p3j5Ux2eA/ugEvKKKcrV/q31+OSR03HivImoCxh2TvaSu7O2W9Y37kElLAj4CU4hDFkutvRkxPUARoZUG4NYiKUB398fMPBs78/CJVT0w9A1HDarSeSRdQ0ElSu/2qRaMfD+c8L0fy+wEPrza3fl9ccm/hWFwfaGQ6EctWLqQHXCgsWISiHFJnxSqzhrilbR56oAhhsrNY+s1OalClTA96uYGjbMRcoLC+b/TihX1tgCDIdwUhW418C/hPpra5ICY0KRT7iGUyRHwyYjSqSPsLtQNrnasmUL5s2bBwB4+OGH8alPfQr/8R//gVtvvRXPP/981Tu4L+HotglVS+CMGTpmeKv6NigFmnlYsKWWESKVXKUtV3g9xQzNp6RpmoYZzSk0p+J5ybqTvTYILY0gcfRnbZ8CUyysyGsQpi0HG7oGAUj1Jhk3fLkbYTlLsri0/xpZy0VPWobuYoaGQ6Y1ot4LuXUO+MvduIT6yZWSvM7tJDhBCipoOeVeXW9CCibMB5WsQmpeWM1CoHDOVdZ2sbl7aMTqVdEQW4F9hdSKkTi0B3Phip5fdF+hTpfep6ACV/R6tPDigqI2GsXaLNbRAu0F9zmEiH65hHhqI1M7eZgw/Fyp8vHzacj1gkpgQSIeonhVE7vT1yzCvo2yyVVdXR127WLfxJ988kl89KMfBQDU1NSE1hyMUDpa6hKYO6l66hUPDW7sYh5V3DGcXYspV1x16knb6ElbIscoXsDQMhgS5G1wbhMkL8XQNeAPuQ0VSYjf4tVATFuucLXnJXNqA0paWFiQl8cJ1vXLuQTdQ5YgajFDx6T6BJo8u4bOQB+D39R5HwihgvBwchXMnWrvl23xlYRBpSr4ezDnC2DPsSC5KjBBf+uhd3H3i5vwp9e2hJ5XKor6XBXJNQo7r1SeF3ZYe7UKmhfow/A5V6oHVPmXDFVthu9W0TZLP9b/jgSVKZf4Q4WMXPkVSLUNdawKOc8LSwf4Va9i9zEq5CriVhF2E8omV4sWLcK///u/49///d+xevVqnHXWWQCAFStWoK2trdr92+dw5KymqrXV5iWyb+/LsILCOQeWQ6Bp0stJzS/q6Muie0gWbQ5DXUgSdVMqLvKztvWm8/YXQlcgnylIfDhyjitqIKZzLgayDp5fvdOXc6UiYRrQNBn6BJgXFgBf2BOQ5WqE/YR3H83euTsH8nOuVJNQPkG4IWHBIEFVCQGfhILeVvzcrGJRETRYZX0InyXUuU2dvF7d2A0A+P3LI8uLLK6AFD2zzOOLH1dq+JSdX6TPZW5X+1RYfalsBqfKLeWH7kaHFVAeDqSSUHGlSipZhRdDqMqV2m8/SZJhRg7LJcOOcaVFtSNEGAsom1z97Gc/w3HHHYedO3figQceQEsLMw1644038NnPfrbqHdzXMKNZlpYZKRqTMUxIxUEp8PaWXmz1cpWak3GYOnv0mqYJwtQ1ZAmrgnKUq4ZkDAlvhR5XyYZD1nbRH1i5V6jAcm/aFqVuONF4eb3MY+LL3s85bCoaakwsnNGI4/ebiGPmyhJN/B4HA2E2y2Wr+zhR4/fd6N3nrsF85SpMdXJchVw5BITQPOVKDYEKDyzHP4Hw33lbDiF5aqATCE36oSgKIYcUswgoBYVDf4UTkHlOT9g5QZQStuSqyUjCisPtG4lyNVwYstBY+RSlvH0F2qMyJFcMxcJtPN+KK1hcqVKT2vkpQWVKzR+zvC8bwfujyr/ck2u4nKti5HUkiPhahN2FsguTNzU14ac//Wne9qhoc/Vw5KxmLF6+oyptzZlYi+7NFl7e0C22TajzO5TXJUz0ZmwMZG0RBitErupDlKtUzBDHb+4ujVwN5py8FW99BQo/dw9ZwkOLkw5VueE2DF84YQ7mtNRC0zQ0JE00JeV9cu8qNa+LUrayL+cQZAOu9I3eucEEeK5c8XM5CKUYyjp4b0c/pjbWhPpVqccL9/Y85Yrfp4MJtczBPRgCdAgt6OZeLBcIyC9kXS4KrxorTEgKhcHCQ4UhRYKrnCczXGkb3o9i8JOH0kmepvHwWgixLBITK9Qdke80nA9Wgbb8KwUpXO8/VcEiyn6ikB9+Pt+mkrC86wf2ccWsGMpaEUpL88iLcq4i7C6UTa4AoLe3F6+++io6OztBlA95TdPw+c9/vmqd21cxf3Id6mvMsvKXCuHI2U2wXILtfRl0D1qgkLYKHFyNGsw5IgxWjnKl6xpqvOO395aWdzeYdfKsG4JEhqNnyBKJ3ZJc8bwmDYY3UZq6Jj5gE6YhQp8A0Oj9rCpXlsuSeHO2m+dK36icq8L1Jhrb9atHDqF4ecMuPLmyAwBwzZkHCnWQ9RcgATIGwFf+BpDWDhnLFeGUPJd4l6JnyA71xAqbRNX6iCMtDl1M6Sk+sYbl1wxDMIa5JicrQGmESe0rJ3CVJrSrik1+CK/4uVy1CXMyF07oed0Jb9Qh4SpY/jVl2367DpUo8QR24iNZhLHBUJJMIcN3fu8v9RqeWqV8H+AJ9Fyd4uPgayMsJyuERI2mJ1iECJWibHL16KOP4nOf+xyGhoZQX1/ve9EjclUd6LqGI2Y14bnVXSNuKxU38eEDJgNgysmQ5aAp6ScOImSm2DaEJYWrxwbBw027PNPM4cxA1TwnjkI5Vz1pGxmL+W9x5YkTG/U6KplJmDpqYsy5PWO5wourV1HHOJGxXBkW5O01FSBX/LuEQ4g4n22nPtUua7s+5WrQAVIKSZJ1B4MmolT0yXYpHJcVglaJlE0INnenkbHdPHIV5nOl5q7kyshVCkMhNaF4DlKBIs3DhMbU84v9DrB7LFQLMEhk/BN46CklWDFIwph36LBzPfWUPkAVNwvlyxVrM6gk5V2J5peeCb4jVBAn1i/HpXBcplw5hPlYsbBh/qpBSuQXhLBr8b5RqhBwSoct2l1I7awUom8hpLaSdqp1XIS9F2V/jf3v//5vXHLJJRgYGEBvby96enrEf93d3cM3EKEkHDK9saB6VCnipo7mVDzvj17NR+Kr0wopHPWJcNLBw005xxXGnMWwbudgfliwQM5Vt9cn1RfL9mYiNcxlKjMV7z8nkq0Nklxt8qwpeJguZxNkPNImziukXCm5UioxcglFjSn7snxbn2+cByy/zQKhFKvaB/LDgg5PlmehP4ewiU5VMTfsHMKajgFYISsGw8KC6rZSXfQLe1YVCgsWV1DClauw65bSu/zzi5l+Blcr+iwPipxTDP4VdqV3mhONMHuDYiaiha5Qih9XsL3guPE8MEIZSVXDgY6rJLeTcEVNvGfIf+dUg1FXeUdk3lx+e+WNZ3kMrBr1NSNEKAVlz97btm3D1772NaRSqeEPjlAxEqaBQ6Y37pZrqWHBfk89CiN2mhYeFgSAlEfQcjbBjgKhwVXtAwDYCrwNXUMiOZ2rZP0KueIfmoRQ9A5JcsXJAQ91qQnahhIWSgQUKL5IIG05eM1bOacqV5y8cOWqOeXPS+PgH85cWeJQVTUAeH/HgI98DTj+nCtCgPU7B/PCgpZDsLFryFOr2ORmE+Ibm0//8iUsfrcdz63JVzb9CoW3TdlYyMIB8BcFCZIVbhBbLERX1KYhZF+pru0FLR5CVLpCCFvRFmzD34+izfnOCyMcRc9FeDivEAEqBYz8hIfRgn2iRG7nZIrCI3yEkSDeP0K5ysbIfh4hpFIZpJS3LffLfC1//zg5pb621FCr9MsqtXRTKas3I2oVYXehbHJ1+umn4/XXXx+NvkQI4IhZTVUtiVMIqnKVtcJtBABmeWAUyGup9UiO5RBs7cmgoz+LzbtkmKxzIIu/v9uOLd1pvLaxG5TKcjncc2tAyYdat5MZhW7uTouVdf0ZW/hKcRUo5QsL5itXPDF9aiMzVCUUWN85BMclinLlCnLFlTDVxkEFD7E5hPgT1Km/LM5QzvERpyE7X7nKOm5emK4vY+PJle1IWy5slzD1yqWC9KpJ/8u39uX1L8znKphjUwjqu+YEDsxYLC9NJb0qipVI4ZNr2PZKtwUxHLErVhaoHMgxLa9/gF+tUZWrsBV/pYRC1XNZ++H9DNb1U1VGpkzJPvF/1fqCrke4/LUGw9Sqwrl1FH4XeH5sGGFXiXqp41AqCr2LESJUG2XnXJ111ln4+te/jpUrV+LQQw9FLOYPn3z84x8vqZ1HHnmk3Etj0aJFovTOvoCGmhg+cuBkvLC2a1jn8+nNSTSn4nh3W/6EOxw4uUrnXKFsqOSqLmFiMOegrkBIUG0j5xJs683gvlc2w9A1fOGENtTXxLC2cxCEUjy+fIcgSLyuYGtDDXb0ZUWyuUsoXtvYg3mT67GqY0BcQ/Wc4sQlTLkydE3kIjV6YcGmVBw1po6sQ9CftbGtN4OcV6w55+WiAQq5KqBcpb1Vi7ZDfWTJIdSXoJ91XJ9y1ZPT0KoQKQqm8uUCSlLnQBaUAt1DOZH7krFdMYG9tF6qVcOuaAs5rpjVgabJk4LKleUSdKctuSSf+nOc1BVleQnHKDTp5qOUsA0N/AswJbNQUrtKAEq+RoFjeHFx9X7zzx22eR9RoZSNfXGH9uGeNSNDBjRBWHibXHniz4aH/HRo0sOKQkli50ql6nPF3nH+scBfDzUM6BLZfnA81LAghcyp4j/L4+Tz4urVcF8v+eXCvoeqxJW/37uDW4nrRdhnUTa5uvTSSwEAN954Y94+TdPguqWVPzn33HPLuq6maVizZg3mzp1b1nnjHYdMb8T8KXV4Y1MPlm3uDTVPbKmL4+OHTUN/1q6IXKXiBnSNfWCKnCslUfpfjp6JDV1DaO8rvBKwvoaHBZUSL4TirS29OGn+JKzr9ErWqLUEPaIyZ2Itlm3pRdojV/0ZG+19WXQOZIWCBfjd0jlxUd3ZOaFS88V4v1JxA6mEiaxjYchysaZjEJO9PCzLIcJclJO1QsrVS+t3YcGUOi8s6K8xqKpQWdv15VN15fKNL7O2m1fuZkt3GjOaU9g1aGFrTxp/f3cHXtvUg6tOWwAAaFfy2QpZGQR/LpoorUBX2FVQubIcgl2DliBnwXZUpSE4qahKRKG+BtspF7bLyG6Nnr+QQqx4K+MahYbJdhm5olQhPOWqX6B54xtsxiY0lKiGn5P/TFTC4obcv0MoDF3mWlGwkCAnU7bLQ4VKIWcKGGJRgHcukTUIqXdBl1DxRUcltvxYTZNhP0KpR540rw3ep+pQIP4+SkI+etQqSmKPoKLssCAhpOB/pRIrjvb29qLtqf+Vm+O1bds2XHjhhWhpaUEqlcLhhx+ON954Q+ynlOL666/HtGnTkEwm8aEPfQgrVqwo6xq7CwnTwPH7TcTFx7fh6LYJPrWmLmHi3COmoyZmYHJ9jagVWAwxQ8NhMxvxmQ/OxMXHt+FLp+wnlCduh8CVqwm1cTQmYzh8ZhMWHdRasE1+fpBALN/Wh87+LLoG/WVcLIcIYrF/az0AabPAE9ufWtkpVC4A6OzPYsnKDixZ2SG2pxL5ypWqujXUxGDoGhKmLpzc05aD5dv68OI6ZkTqECp8tPgxTclYwW+eazsH88KCacvxEaWsTUT9QADIuVqe4zRzzPdv4671A1kHG3el8dc3t2HTrjSeXdWF3rTlt5IIIdq+8A/h22jo/iDU+w0qVzxEKdSwwKWpOsEG+xTog29HcFMZSpC63SU0j6iql/HnXJU2HoXaKtTP4DGh+6gMUwZXG/pUxWLtFxgjf1hREi5C8vOZOFniqhYnXFxh4l5u/Hzu76ZaiKjETRwrVDLZF6JcR96/7LeqgvHf5b9BBa/wOKj3FzxezdvaXdYNkUXEvo2KfK44stksamoqcxO/6KKLygrxXXjhhWhoaCjp2J6eHpxwwgk49dRT8be//Q2TJ0/GunXr0NTUJI657bbbcPvtt+Puu+/GggULcNNNN2HRokVYtWoV6uvry72d3YLahIkT50/EsXMnYE3nIFZu78dJCyYKg0wAOHR6IzqK1F07ZHojTpjXIow3ORqSMZ/PFCcos1skqS2UbwUA9V74LReY4HI2CTVE5SQhbuiiTE/OIcg5snh08D52DVpYuaPft01VrnjOVUJZtVdXYyJh6j4neq6YZQI5UoA0JDUMHTWmkbeiEWB2E3y14JrOASzf2ofPHTvLV0w4Y7s+dcKl+YSlL23nWTGo56xXVDtNA7b3Zn15XLzgtGpH4Z/UylOu/P0gXnvs23jWJiAkPxwk24U4PhjICRpIiu0hW8NUpVLUBocQUFLY/qMQoSpHyVAJikjILpkg+q9P8sheMJQaPL9Qn+TPagFlvtlxKQzD/+4JogNOjqinThGRo8VXCRKPtPL3khNlngQvjvPeb66Aq/3j+VVsBSxTtYRNCKHQDEnOOBEulMMXNlZh4CFipoypXmK7JywYIULZypXruvjud7+L6dOno66uDuvXrwcAXHvttfjtb39bcjt33XVXWSTm5z//OSZOnFjSsd///vcxc+ZM3HXXXfjgBz+ItrY2fOQjH8F+++0HgP2B3nnnnfjWt76F888/H4cccgjuuecepNNp3HfffSX3aU/BNHQcOLUBn/zADEyu95PbBa11BS0cZrek8NEDJ+cRK0DmJnHwFXyzveLPw6HRI3hhakpPiPM6J1f1SVNc23ZZeK6QJUOYjUAiJu/VEOTKv43XCeTkKqwdvk2tU6gqhJ/94Ezxc3tfFpbLcqoWL2/Hlp4MHn+n3aec5BziM++0XGDZlt7ANd28nCtVEVLJpe0S7BzM+a4xmHN8qwiB4Dd7r01lBi5Wry1M9eKhzvb+jGf8SEPbUXNkwtsOIVIhQlPYyrDgqWEr4IKrLoPn+8nF8MpVOGmCGGB16i+FoMnVcdwzSlFaClyzXOEj7L5yriv8qqhynFCseD6VS5FzmBrremSLq0c5h+X88fdZECbKiJf0wfK+HFAZZgS8sacsDC5sHogkeLyvPP/L8Ugez48qTGILkyX1XtXfg+Pkb6+87aUiUrD2TZStXN1888245557cNttt4n8KwA49NBDcccdd+CLX/xi2Z348Ic/jFNOOQXf+c53fNt7enrwyU9+Ev/4xz/Kau+RRx7B6aefjk9/+tNYunQppk+fjssuu0z0d8OGDWhvb8dpp50mzkkkEjjllFPw4osv4ktf+lJou7lcDrmczPvp72cqim3bsO1wQrC7oQPYryWJFQGFpy5h4qP7T4TjhPscNSf9r0LMAEAJptSZJd1bXZwRm5ztgpDhw8ODWRYmbErGkPC4kO0S9Axl0T2YDW1jKJffj7q4IftH2LVNjfr63FTDjuErGodyTl77PN+rxtTEuTUKcTtyZiMaa0z88vkN6M3YeH39LkzycrYAloCuEstMzvGpUKv7daC/13fN1R39yHpJ9aaueZ5WcvxytnxWg1kbXf0ZWMrzo5SiayCD5qQkgbay3yUEtm3DsuRYuK4cm2ACuDrpZC0Ltm0gnbUBYiKdtREzdbiuC8uykMs5sBWhyLJsb58NBMi9bTvef/7n5zj521h/NV+/bO843t/BTA6EuLBtB7pn+521bFgxDWGvquM4yFmAbeviGvznsD4AgOXk/007LoHtuLBt1ifLsmDC9O5N6a/SvtjmEthe0XTHcWB77du655dGdFi2LfpveZ8pfBzUfqrPjV3LgQGKnGWjxvCUJ0KhUR05ywb1vgjkTJaXaNk24jpFlrrIeednLSCbY0qqbTvI2Q4c14Xl2NCgwbJsVi0grsGyNaRzFlIxDdmchZxtI5ezkclZ0DUgphEQorO/R8ruxSGsf5mcARADtmPDskxoAKipQ6c6ckpVAoARe9vWQLx4ta5rLFxJ2NiGeZsZuibyyFzN+7Jn6Eyh0zTkbBsxjUAjbqjTe9AxnxmPyu3F8qrU58JVvOD51QJ/F8bKvLMvodQxL5tc/e53v8OvfvUrfOQjH8GXv/xlsX3hwoV4//33y20OAPDss89i+fLlWLZsGf7whz+gtpapJZZlYenSpWW3t379evz85z/HlVdeif/5n//Bq6++iq997WtIJBL4t3/7N7S3twMApkyZ4jtvypQp2LRpU8F2b7311tAais8888yY8v3qzQFrOuWHu65RfHASxTNPrSx4TrZPhypkbtm4EVOSFEueWFXSNdf3A4AJy6VY8f5aDFcfeFM/AOjQcgN4/eV/AjCRtRw88fSz2DigYcDO/zDaOsTOmZigmF1PsWVQw4SBtVi8eC0Alny7ZpuOzHYKbJEfvJsHgcw6YKiH3eP27gGsWdMPmwAdGaA1CfQOagA0rH1/BRZ3v8vayxngIYh333kbXVlgSo2O9oyG+/75Pk5spQC8PK50BlkX4vjtHZ3IWRqKhTBe39SL5jgLcxggcKCha1cP1rjMh6s9ze4XALbu6MDSdDv6LU1s6+rqwpPPPId/msAUL8L+Tqcm+jQwOIjFixejz2LPBgCG0hk8+vhiGBrgED8PIkTe79P/eAYTa4ABG0gawPIeDYYG7MoCi3tXYsgB6hSxs88C1vRpoJtpkFuhIwMM2kBHIKVxebeG3Ab/BNlvsXbVCPSmAWBbPXu+hs7aW9Ol4+/p1eD8d3saaIwBtSELWjsyQEIHmhLyGg3eeoXODDA5JDthZwaYFNjuEiBHgJQJvNeroWMlRY0BZBx2XUpZ+FZtX6gylP0HADuzwKCtYUc9O58/B94XSoGlS59DvTIO3Tlggtd/QuX2tAPsSANxne2vjckcJ0MDei3WtkvYvpjO2kro7OdeC8i4QI3B2nIJsC2tYXOc9bNvM3vbGhMULgHqY0B9nL0HjXGgKwsMOhq21lH05li/kiZgauy6mtdHh7JxaYrLPjQn2PGGxrZlXU9l9O7PIkCDMga6Jt8B/jzUPy/NO4arWRpYGzFdPpshR9572MILdRv/Xd0ePEaF+lwIZdcPnl9tLFmyZHQajlAQ6XRp9XPLJlfbtm3DvHnz8rYT71typXjqqafwpS99CcceeyweffRRtLW1VdwWIQRHHXUUbrnlFgDAEUccgRUrVuDnP/85/u3f/k0cN9w3lyCuueYaXHnlleL3/v5+zJw5E6eeeipaWloq7u9ogL6yGYM5F7NbUjiwtd6XOxWG5U+sxuv/3Ch+P2DBfjhh3kQcNbu5pOut6RzE3etfRV/GQcOU6ZjZXDyfbvvqLqC/Hwe2TcMZixbg5reegwsNCz9wDMiWPq/uH8XidzugacAZB09B3+ZeoKcHk5rrcfyBk1GbMPHFE9rkPVOKDc+swxGzmnDSPBlC3t6bwbSmJDY8uw6vP70OA7aG6bNn49nVu7CuZwi5WC100wJsGyd88EicdhAj3f+35RV0eF5SR3/gSGzoGoLWNIDHlndgSKvBtP1mA+vWAACSySQyacv7xAfqGpuB9EB47EuBHosDlo1UTRy5tI2GpkbMn8/6TtoHgO6dAIDmCS2Y3dbMyve0bwEANDZPwAGHsfv/iFfiaOiNrfjjOkaiU6lanHnmicwx/43nAACxRAInnno8mlNxpC3HFyK+4uUnRfzkxJNOwdxJtdjRl0Vj0oT+/k6Yho5tvRl87LjZ6ElboqQQAOzoy6J2Yw9OP2iyMHDlWNs5iO60hQ+2TfBtJ+/swMcOafWpVF2DOTQlYzCV1apvbenF4TObkLNdJGIGVncMYGBFBz520hxxrZVeweww89d1O4eQihuY6hnJdg7kMLme9X1D1xDmTMwPfW/cNYS2QEjccgjSloumVAz1a7pwyPQGNNTE0J+10ZyKC+WiazAnxoaHhCyHiNDcpl1ptPdn8cG2CaivMZFzCBKmjg1dQ5jRGMeTTy7BKSefjClNtSLUzd9hAL7VeL1pG6s7B5CKmZjamMCE2rgIz8V0DTv6s56aw1TiZNzAlp40UnETNaaO9v4cBrI2kjED/Vm2KKO+YxBT6hPY0pPB/Cl10DVgUl0COYdgamMNWmrj2LhrCFMba7C5O4PutIVDpzViR18WCVNHbcJAMmYgZujQdQ29aQuWS9Del8PUxhokTB3t/VlMbayBrmmImzpSMQO9XojbdglMXUPGJphUn4ChsZWsuq7BcohIe7A8JRDgRIbVGeWrEg1dQ9piOYmOpyT1ZWzUxk3UxPSCn/+F/lWPCYNPUfTuYTSVqyVLlmDRokV5dkgRRhc8YjUcyiZXBx98MJ5//nnMnj3bt/3+++/HEUccUW5zAlOnTsXSpUtxySWX4Oijj8b999+PAw88sOK2DjroIN+2Aw88EA888AAAoLWVrXprb2/H1KlTxTGdnZ15apaKRCKBRCKRtz0Wi425F/yTR81CbdwsuZgt/+AGWDK7YZjYb3JDyfdVWxPHxLoE+jIOdg3ZmN1SV/T4IS+ZfMaEWjTWskmPUmDnkAOHatB1Ax39WazvSnvHU2QsNlGlEjHouoFEzMzrX8w0UZuI+7ZPadIRixmYUFeDSfUJ7BzIYWtvDut2sjI4azqHRK7VhLoacW69slAgmYjBNE3U1rDJO2sTdA7IFZCskLNUYSyvNttw4OewJHwbxLt3AHCVr+UuBXSd6VschALb+ixMa5R91hUrAgr2bhqmGiqkyLkaO96Bb5zU1BDNMBCLxUA1C5phQtMNQNOg6zpc6NAN/9gbpgPTNGDGYogFyJVumDAM4jt+e28GV9y/HItXdOLX/3aU0o7L2lDIlWGya9lUQyxmQtNN6Lr/WppuIGaG/x2apiHaYL+74md1u/+c/LZcuIhRNna6YcAwTJimiZjJxtFxCUxDh6G0L6wrNALNI1emacIwTMS899eFi1hM9pEq/RLebaYtn7FCrmIxCl03YZgGdNOEabLzNUJg6joMwwGlgGFq4pmaRgyGYcCMGTAMB4ZJAV0HNJZvpWk6oOvQdJ39rGmAboB4/TJME9ANGGYMumFB1w1QXQfVdBimAc1g/YGueeNBoFEC6DaoprNzDRNUM6AbOnRDhxkzoVs8Cc1l90McNla6BsMjV3ys+PPQNc1HsExDF2FRU9dgEA2maYgse8OgMGMmYjEjj/BwclQquQqSJpVcUY0gZoweueIYi3PP3o5Sx7tscvWd73wHn//857Ft2zYQQvDggw9i1apV+N3vfofHHnus7I4CUkFKJBL4wx/+gJtuugkf+9jH8M1vfrOi9k444QSsWuUPZ61evVoQwjlz5qC1tRVLliwRhJCHIL///e9XdM2xBpUYlIKpKrkydMQMDZPq84lkIcRNHZPqE1i3cwhdih9VIQx5K/ZmNad86snGXUNidY9aCLknbYlyOZwImSHFpQ1dy1NO+Go6XdMwa0IKOwdyvrYBmbjdpCgfapHqmKFD16QjfMZyBUEEgJ2D/nvOOaRMciXzSN7Z2oumVNxn5cDzUNTE7Tc39+LEeROFCgMEVwZ6/6qrFomsUxi0J1B7y/dZDktYVo9NW25eUjBPjA7L3WXL+v3b/vwaU9+WrOzw7whpQ014ZveVfxHuyxSEWttObCshwbikcivD/K5ul8nbsj/B44MGr+rKuHwrCT7Be0nyFCJJXGznqplLkNB08e7wlXjcdoEQChteHUtP9bHFsQAoW5zhECKeM08+93LVmV0Dz3VyucM7EPd4jeutQLRcIlYLOi7z2gJVVgvytiH74BIK3ShMTsSKQC1/e1A4VhcSDIfhwnmsnXDixMZXG7VwYISxj7JXC55zzjn485//jMWLF0PTNFx33XV477338Oijj2LRokUVdSL4Qfbtb38bf/jDH/DDH/6wovauuOIKvPzyy7jllluwdu1a3HffffjVr36Fr3zlKwAYmbv88stxyy234KGHHsK7776Liy++GKlUChdccEFF1xzvmKr4YyVMHcm4Wda3rbihY5IXCgkSjTDw1YIzJ6Q8R3V2rYGMVFlUAtSbtoUPFrdfiIWocjFDK1h02tQ1TGvyQkP9OZ+1BJ+8VPPQ+pogudLECkKXUvSm/d5dKrKWW3CyrUuYgiDy1X981ePanYN4ZtVOPLRsmy8hnk+MTmC22DVk+Sde5aphhZu5XxFrU3GMD3RWkCtvGb6rTH79WTuPOBabsBySv6y+2Njl0w5voieF7ytnu6GEKOzYQj/nX7Ew1JVq/FhB2tT2xT7/72r7nAipKzCD1w8zHVUPpmDvZB5ho1Ss9uPtczJEPELGLRK4WSgjQ0Sc7xDqrX6V3lbSJ0uSNL4S0HKJz9eKk3NWu1CW1+G1CvnqQN4HxzuOr1hUiaL6vCRJDPPWkuao1DuPO9MXI8HymfjJsPqsgseHlZwqlcBF2HtRkc/V6aefjtNPP71qndiwYQMmTZrk2/bJT34SBxxwQEV1DI8++mg89NBDuOaaa3DjjTdizpw5uPPOO/G5z31OHPONb3wDmUwGl112GXp6enDMMcfgySefHLMeV6ONupoYauMGhiwXcVMXK+tKRczUMdFTULq9Cb+QLxahssjxDC83qyZmwHalEaftEuzolVYEPWkrzy4hTLkydR2tBYxUdV3D5Dq2rztthdZtbFQIVYNiT8Ekfkay+Mq+oDEqwNzydw1aGAyxe+CwXOJTqgDpzaWuOBzIyhxGbssQVlBZnXjDiEPQioETNNtHyvzgbfKJkC29Z+PVn7HRUutXNcVEFzJ1OSHKVaFyTnwiDAMnB8LPSblWmB8ZAC93L/8ahX4TWwuRrpAxHf6cgGs5JwwKT3YUdbDg5B8SXmKqmKf8eISHKzgUnExLciP64zFDTm4oNFZuiVBBqHi/uUEr3yd9qDhxYmqV43qkCESSE0gi5QhCpQmVzCUUjiY9tRxP4XI9ZYuTJ6HUqfYbyphyvyz1WVCN+t4Vroq5riwPFDauQcUqTKESliGaJhPfvUHXlPGPsO+ibHJFKcUbb7yBjRs3QtM0zJ07F4cffviIYsrB/C2Ogw8+GAcffHBFbZ599tk4++yzC+7XNA3XX389rr/++ora39tQE9NRV2MKcpVKlPdqxA0d9Qlm2JlzCLqHrNCwYk/aQs5hE54GYJqXZFwTMzCQdYSqsr034/sm36MoV5xcxUJCBftNrhO+VkGYuiaSbTO2m+fVFDM01CghyqByxd/xZJz1tXMg36x1akMNdg1aRWtBWg7x+Wmx+88nimq5n86BHHoCKhXAFEBXUbOC376BALnyJkMAvrBjkCzwNsUESCh0jU1t/VlHJI6r9erY7/n3a7t0GIKj9jl/G7/lYmFByyGhbfZ6HmuF6vYVVhiUsRG5OPl9UtsOEa4EySAeEZBtKIWbwZ6JeIyKKqb2kys4YYqJbJUCVPMpa9xZ3VdsWSFKfFyZsiTL2nAyknNcOK4J1yNIjHTxUB67f5tIR3dKJOHjSpfq8u4QHZSyZ1ZjGnA1tVA0KyvFCRA3KxVjqY67op4RhfxzUkeprIrAx6KUUL367IrF9Wjg3wgRVJQ1gz7zzDP44he/iE2bNok/bE3TMGfOHPzf//0fTj755LIuXmrWfanO7BEqRzJmoC5hogM5JIzylSvugj6pLoGtvRnsHMzlkavuIQv3vbpZfMClEgbiXg4TL5jM8yy29LA6hs2pGHrSNroGcyIvihM/U88nJEfOairYR8NbvTOpPpGXcwUgz3y1sUZVrnSxzDrpEcHO/vzwJw8rhpmpBvuioiaWP96dgdy1jv4sjAChHMr5lSt19hE5V8puPokB8NU+DM7TnIDxSdh2iEgy78/YPhXJNDSRyxJm5hkMZRaDVCr8fWZ9lHk+wT7bhIqi46oSsXMgh1TcyHMNH7YfvrYJEoGahcGQFD8uCSM0dBRWzNhHyrThx4mEKCzc/ZyCl68BXEpE3iKllBmDKu76XJHioUJCKUAkkWZ9Y8c6hMJyWRssF4t4+VNE5pJ5ZEwUZqbsOfJ8LJfIsCEvRs79rFxKoXFDUcr+/jO26z0zT/0iUtFUR5G/94Tmk13ifXlTzUp99xuC/Fy2wuD3yc9TibVQECPs0yg552rt2rU4++yz0dbWhgcffBDvvfceVq5cifvvvx8zZszAmWeeKdzaS0VTUxOam5sL/sf3Rxh9JOOGSOCOm3qoi3sxaN6Sah4a7OjPYudAzlfe5Z9ru3zfHOsTkrw0eCamfZ7SsL2XkauDpzUCkGEkXQNqPBJkhihXxRL5OaEplKivls0BgMaUbEvTIMKIPO8qLA+mUMHnIMwAuaoLUQqD37ITMSMvQTdtOXmlTeTPkpSo+/kk7hRRrhxFueKTHldUBnOOkgPmvwa30PC1FaZcFZl88kvreESOSjVDtuP1wyUKuZLnWi7JS8D356gF+5XfMU6Ufa7sIeqXrRznb5OTAzlj08C1g8pSPmQOUCGFjCtUnNxwRUy6oksyJ3KkiP8YnrclS9GwJHYWfiZCxcx5Cx2Il6PF86xsQmTOFZGEillREFG30CaqWkVFQrzjUuHkzt+9sGLkQEDJpP7nzgmdmovF+xs2vsF6hHwMxO/B9xf5z5m3o+6L3Nn3XZQ8g95555049thj8fTTT/u2H3DAATjvvPPw0Y9+FHfccQd+8pOflHzxZ555RvxMKcWZZ56J3/zmN5g+fXrJbUSoDmpMA3Mm1uK99gHMmpBCbaI85QpgYTWe1P7O1j68s7UP+02qxdkLp2FLdxobuoZ8tcdU4nXErGa8u60fG3YN4cCp9UIV2m9SLV7b2C1Uq2RcLqEOCwsWAyc00xpr8EbI/mSssHKVthxoGiNmQSLUlIwJj56gzxLPYwvCCIQbGmqG/1N0CEF/NuBo7ikBHEEipf4r2imQHK9CTFxEkiZZtJeIhPRg/cKc48J2KeKmvD/bJWxJfwngE39wG79GXniLMhNKni/E+6R7CoTjUrjERW3CEOE9t8Bkza8l8mfA74lAzcTkhIL1QfYnLOQkVRwqjg8qXnzylm3679s3Dr5cIOo7Vm0D4ndJMtScLq4cWS6r52nqulChVFWGh/eyjou4oYvQXs5xYRMlR8ulgkxR6g87yqR1KnLAeDkdSilcPi6U9cfmiyh4iNL7T9c03+pPovRVfS84kWSmo2roUL5DfAx8SmDIs+PXCgsPhpJc7xHxcVNzsiLsWyiZXD377LO49dZbQ/fx1XfXXHNNWRc/5ZRTfL8bhoFjjz0Wc+fOLaudCCOHrmtY0FqPWRNS0DQtLyeoFMQNHVObalhJC2/bup1D6B6y8PyaLgCssHRzKo5nV+/EMXOlqeRJ81pw70ubsLk7jW1evlUqbqAxGUNzKo52L6HbX6i5vMWuhnf8zAnhhqpB5aombmB6UxK2S3DwtEas3DGAY+e24I1N3VixXYa0axOmIFfB8N6cibVIxnW8trEXAPvg/eJJc/DEu+2+4+pKsM54Ye2uvLqLPEzDEVQzgBBVipOrosoVFf9S6qlPgEhQ5vUiVfWA0nCbBjVvZjhQwJfoLc6nUiVRmyeUwoAGmxClL2zfQ8u24rf/3ID/+sgCz1yTkS4eXtQ0zTd2lkMEAVevESyuHVQyhiNF6k4f/6Iy1Mnvk58ftkpN5FMVUsYg2+KzOScaQZsGApnsbjkEekzzFebmV3CILMqco0SoV1mb2TNwBSx/BaFUScXqP5cRM16ihie1a+DKGfvXcmTokJNtSXTkfcuEd8/XSrk/liPIyuW4lCWxc4KnkjW1TUkuqW97gNN6+/xkTuR7Uf9zKEW4Gk0frAh7DiXPTps3b8ahhx5acP8hhxxStHRMhLGPpGKsV25YEADipoHmVBz/cvRM/MtRM9DmucI/+vZ27BzMIW7qOGZOCw6b2YRLT5qD0w9uFecumFKPuoQJl1C8soGVf5nelISmaZg/WRqSqmG3sLBgMfDFhbGQVYaAv1AzAExtrMEnj5yO311yNGpiBnSNFbg+Z+E0cYyu+cOMwXDftKakT83616Nn4qxDp+blXNWXoFyFFbTm3/I5gsQjuA1QQ36SNARzpTKe2sbCRHJC4pMmX9UZtEcYzDnhRC3Qh2J5L2FhQU6qfAqMcqyjmLbybVf8+W28u60fD7y5VUzeALxkbPj6D7AVh2G94mPDSQ9VZ11IdU/cg+9nfw6T2g/1NAr4lKXwsfGHolSS51OalOMZWSFiDNU+sf1EqH4iZwqS2Nj8XMKUJj7OlkOYAkUU1YorVISHJKln9SBJmO3y5HaP3Dk8J0yuKmSqGMlX3KifVvL7U4tB8+08J852ObFSVjmGDDCF+i57z4NKssivr/aDv5OqwsVDx77nUOB5FkIUStw7UPIMOjg4WLR+XiqVKrnmToSxiWTMQC/YBF5bEblipIVbIRw5qxkbd6WFqvPBtgmCwKTipk/lScQMzJ1Yi3e29bFyLZCu8UfObsb8KXXoHMhhWqPf7LQcGIrS9YnDpuGx5Ttw2IxGvLm5F4BMqueY0ZyCaeiIm9KENGZo2G9yHT58wGSs7RzEgil1mDupDr1pCwdNbUBtjekLfbY21iCj2DKYuoaYoeeRq4YyTV95zTLLJXAJwWDOQV3CDOSn8H8DSpKX19IzJMlaMNy4azDHcl+UfCn1G75YVaYQOAognXNFSEQ4WcNPCtSk+jCEhQVFPhD17+c/BhU8FYNZxxc2UpU0lWAO5RxvIYeW119ff5T78U++vE/5/VCTqlXbCqE6qcoSJKn1XTPQrPq7DOdR2X9N83mU+RPopd0BIx4sazyoiqmEWg3zcaWQq01cXeQKJ99uC0JGxPXYuQQu0WC5rvccZH4WI11EXJcrYlQZW/4eBH2zVM8t8R/1t+2I90/zqbuu8rMG9ndCY4qSqGlsdKiyTXk+4n2Akt+W9yZE2FdQ1gy6cuVKUfQ4iK6urqp0KJJH9xxUspOqIOcquNpuRnNS+D411Jg4bEajb79q9hkzdMyfUod3trFafroGXz3E+ppYXrJ62Aq7YlDznNom1uIrH9oPQ5YryFWwvbjJPLN4+EDXmLdWKm7i0OmNOHS6vJ9PHD7d66eJuKkja7NJe1J9Aj2Dsk3T0EPJlapczZyQxJbujK/fQcJRlzCZdYXDJos1HQM4YlazSOoGCitXlkuwvTeDLsXsNWjqabvMTkM1pgwqIiqx4P8OeQn2at4VVVQFAL4+BqG2qd6H9FZSQi7wX7+YVYOqMPDwD6D5jmUVABLieA4nMFHm94+PT/h11XPVSVklrdzdPNjX4DiAyoUZkqJJ8uUSVvaFajKEy4mRjwgr21ioT/erW1SeDwAaJ0tEqkAukaTJJUF1SPpjESpDfbZLYDsaXG91IkuMRz4RUgiTDP9pvhEWx3vvqEqO+H3LJHyZ88W/MHh8SZJuRaFU7yMMnCyLn9W/EyrD6cEcuWh+23dQFrn6yEc+EvqyVVo/6bzzzvOdk81m8eUvfxm1tf6CqQ8++GBZ7UaoDJxcxE29YOisGOKBMJ2maThp3kQ8u3onPrRgUp7pp5rjFDd1zGhO4VNHzoBDCCbUxoct4VNuXliQ0GiaJsrZAOGKQ32NKc7TwJQrrch1a+Mm4oYkV/U1JhxHkgnTc6MP9kUNLTbUxPCFE6bg/te3AgAm1sWxcZdfFebkqr0/i4GsI0w0eVkhwE9KVDiEoidtodsjVI63ok6F5RJ09GeFIqGOD5/Q1MmYq1VDOUdMrCrU33g+jegnob4amME8e6FceNdT98vVimr+F0LhS3imvG2lj9RPgoLnBfuj/q6eE6Yw8Zwx3j+hxAAI5l5RX1u8vh3brhYuVq/DyZJLKQwvN0v2lQbGhzJSQdhKQZHfFNJ5zg94GJiHEUVSOpH/OoHwG1eLCPW8sgKkySCa54Em86+4Gsp/dkSulKL6UakCcvIFQFTdVIkjb18SJraike83PDWKE1z1XFVtpNDEc4SSq0X58zckaVUJm3zPI1K1r6FkcrVhw4aqX7ypqcn3+4UXXlj1a0QoHTxkV67HFUdQuQKA2S21uOi42pCjZckXQIb4pjcnQ48NQzBHajjwHK36GlPU11MndTtkVk4lZPFrTQNiuo6YLsNyYddgpJG7yZuw4pK4GF5YUDXwBOCrD5hzCBpqYrjkhDYAzMIiSK7qa0zsYCIfXt/YjZMXsAoHQ5a/SHN/xg4lV29v6RMWA46X+6LCdij6MjarC+ht8xMcmeDO9lHv+q6YwJJgz0dVTfjvPgWCytV9fL8KObH6z6UUPsLi5k1oEL/zSZOPC28ljwQKskjl6kLlGCrOV4mYJEVh/eftWi5h+Wu8zwqZ4IRL3JfXZ+bmbwhS4RAC3Xud/LlIUk2iOpvK+fiw9uTvLmGGprbrDxlKUuMPe0J516Xbu1SC+Nir+U+2R4o0l6mgOVuajHIiZupU2FfwlYMsdMdIHCdEahgP1P+MeL4WIO0gaKAvlhcy5oRQ7bOhOL/z58rzt9T3jl9efZ/kQgsZKqYesRXPEkG1snDh5wh7F0omV4Vc1EeC1tZWnHvuuTjmmGOq3naE8sH9oypJZgeAuDE82eGlYwB/WLDc/CkASMXK6ycP7x3Q2oDXNnbn7XeDkgmYOsb5V8zQBdFKxgyh9qhEy9R1H8msTRjQqVTguCqYC6xAU1W9jGhXE20GkVSeEaVM0djWmxGKGcAmh6zj5oXhXJflaEmyRH2GogA35STIWK5PReHX45Oy5RBRuw5gNf4IpVDEOtE/2TbxSVkuoeACIqWyiLY8X1ESiOyHWhBaDWEVVq7k9ajys7iO71hJ4lQSo/7O7yl4PXUy5X3j24GQnDJIQsB/94cIZS6T4zKnfNEOlY2oSiV7dTTRjkMIbJepNA5h+22X5z5JAuFP3odQd4h3Ds+jUr2xuOrm8n+9cB8rT8NIDc/R4s+St6Nr8PriV7Vsl3qWBjJhHoZ87wCIcCL7PJFqF6X5OVyOuL4MQZq64mRPpXqoqmQijGhQuFTqT0EyprajaQGi5el/fF+EfQPlz2hVRHt7O8455xxMnToV//Ef/4HFixcjlxu+6G+E0YFINq8g3woIV66CaErFhGKl5jjpSvHmUlETL+/1NXVWH/CgaX7H/1meNcOHFkzOOycZM0Sulnp/akiyUalBaOr+wtF1XuL+Ka0EFx83yyNoQM72Ewhd03DgVOamdHRbs2/VYdiqyCmK0pWKG4xc9WT8BJEyRSobuFZOWVmnJiWrsB0XOUHMJGnh6gdXRPozLMeqP+uIiZspF373d5Xg5Wx/qRo/wWEhSxU8H0l12wYYCVVDciKEGSQ7XrsyednfttpPVdEqZGXB1RFO7vJWk0EhUoQGJnAlJEghJmeitgM1kVwm8VMlNwnwr1KkkKoaawsiD4mTBMshgvzwtrlzO79fTrLVO5ZKESNkfEUo6wvrh1g5qDx/vpLVUfZxUuZ6xNz2zrVdIlccutx2QypPvB/qvXGFjI+f7chxVEOTrvdFQc27UhUwCmW1pHfzQSVOvF/i+QQ9tCThFbluJJ9Yl4Jyjo0wdrFHydVdd92Fjo4O/OUvf0FTUxOuvPJKTJw4Eeeffz7uvvvuqiXJRygNfLVcJSsFgdLIVSpuCjKSCBwfdn7c1EO3MxJTfs7VpPoEmlMxH3n5+GHTcNFxs3FIIOGe9VfaU6jqmqoctdQpVgyG5gt31iVMmLqGpMlCebrGEtSD5XFMXcNHD5yCLxzfhtkttb6QZ9DeAWB5WNOa2KpMm1BYrsvqJSoTLqEsVLKjL+M7N6fISj1pW6gIKixvRWHWUdUhOWHzc7JeLk2/tyLUcVmCcr9iG0EBrx0qrq9OIBRSraM0f3JxOZnjydtU3gdf7ccVC9XsVG2fT8y8PUEYFBLFCBgfO0+VIH5FiU+yfHz5sbzvoi9irFV3dz9Z49fjZEO2xy5mE+KbvNXQHeAlTUMlY1yBUtUdGRZkREQhCdQLv0HmMQXHPkgYVdNamdAOUWyZq5l8tZ8owsxVJfCwIEHOZV5ZLCeLiDFgJqVEJL07rqImEX9iPneld72/AU60eP4XJ1QO4flXMixMlHtWbSZUYusjveL5+ld9qiRL1lUMKFrIB39WEZnaO7FHyRXgJT2fdBJuu+02vP/++3j11Vdx7LHH4te//jWmT5+Ok08+GT/4wQ+wbdu2Pd3VvR5cSarEQBQozTE9FTeE7UCQHIUl0SdMPc8iASg/3wpgRO34/SZC0zTf6jxD19CUiiMWEn6rTciE9kLK1UTFeytm6D4SVp+M+eoB6roGU9fzwnCGrkHXNDR4xFMNzSZC7j9uGpjRxBQ32yWwHIKM5eR5XvVlLKzvGvKdm1NUpJ0DOfCEYhW2S4QyxPeoYUE+6XHi43jlcbhywU1Ge9MWKKXI2bIGYtb2EyCXEJFcT5X/V8u1qBMe37+1J+NTrkQIKUiuvEmUEzGf0hAYL46sTXzKkgo1MVwlZKId+PvLJ3BVAZLHSrKhji+/F66SSFWIEQF1fHK2i5xNBHGSNf4CeUTUr+Yw8i3JFwkZCxroKy/eDEiDUZ4LxttVSRxLOCcKAWHXsRSPLL6KkKtnjkfchXWDK/O1ZFK7VKj4MZajWELwVYJe8r3jKWkUkshSqCHm/HZ5W5xw8f0AQMVCANULTn7xkO+qEnJUfg6Dz0MtwrhHZRLFKOLAAw/EgQceiG984xvYuXMnHnnkETzyyCMAgKuuumoP927vBidXtSF17kpBUIkKQyphiryFRGx45aomZsDQtTwDzUrI1bxJdSJnqiEZEwSAI7iCj1+HO4ar5E8lVz7lKqCo1SUMX7u6pkHXgY8eOAUPLWNfGE6eP9GXWA/AV35oelN+kn9NTBdk1nYJetI2S5RXlStQtPflMJBxfOdmbSKedVqxTlDRl7aR9erHqRMt/5mHckToh7BiwVwZGMyxsd3akwEFRFJxzMjPqcrZRNblUyYwQlmiO1cQgisf+zK2UvdP5gORAvOTqrhQsEk+J5Q5lViw1W1iwgyuXgyZ5FXwcSIK8ZKU0J/bQz2ywSdmACCA7375ZK8mvwOSyH75928iZmi4+wsfFGTAUPKyuDrnUjlGNVT3CBxfBUh9+UBUHQ/lZ94vfn1VxeGExCUENiFe4WRNEhVwIsYItQadETVNqqmqOsVVQ068CFeyCMs7I2yQlRAh8RmWcqLNtnuLATRNbFcVRlWlEqRQIaHqffLVgLZC4FTFUKcBaw2Rc+VPZve/MxGpGi1s6BrCmo4B9GVsrO8awjdO33+3LCQYc+RKxaRJk/DFL34RX/ziF/d0V/YJSIPPCnOuSkhoT8UNoezkhQVDlKuamBEaFqukjyqBCTPtDFPeUjEDaU/pUcmfSqCaa2Miqd30cqrU65g+csXCr/Mm1+HKRQvQM2Th00fNzLtHVa1rTMaw36RarNspFaiJdQnRH9ulyFgudvRlMZiTRIpSoL0/m6dK5RxJrmTOlZ9B9KQt5GwiknMB/yTrEiI8injODe8yU71Ye4M5R3yT5/1Qw5IAI3s8LOkjIeJabCK0vBwnPg9xUqgqMQ6hvn7yceBJ4Wp7rkeiABnKyfsP+VYL3MKA54CJSVQhhex/mgy5if/U/hNf/9Rwoy+BX5eTtap8ZGxXFDq3vTCuJAJSmeGr3zRNFl2uVYiEIAWKqaYYO98YSjWKesSME1CeXM6fc84mSJi6d6w/X0/T5T26lAIuWxyga8z/ipEjeS2etG5SaTAaN3RfiFqDNJJ1XPauJIhcuchJVszQvdB1Pmniqp9qTspJL4V/kYEgfArBVseIF7ymyvPgNSvDpnVKo2T30cKpP3jW9/uHD5iMo9smhB9cRZREro444oiSmd6bb7457DGZTAbd3d15BZpXrFiBgw8+uKTrRKg+kiIsOLKcKyOwfF1FKm6gNm5C1/JzpsKuWxPTw1fLlblSMAgeFtQ1aSQZ9OHi27hu5FvdGFjpmDBZUnmQoCXjMqxo6jp0TYNp6JhUl0B/1oZLYogZ+bUcg+rh2Qunob0viz+/vkXs58dwYsJKkvhJ0lDWziNOOdsFvPCjSPwNKFdcneFL+gFONqRqYbnE9w2fE0TLJcJ3i+fgECKvkXP8Ce1Z2/UlLaskhW9zKZWlWBRy5RIqrsW9pIJvHidsPCzIVRT/6jyqkEh/H4SLO+WhMZ6gLSdYtpv6QmC8HULz2+RjyO9N7bM6SfPri2R+ypO+SZ7alHMkETF0TiSlL5kOzctNkiG8Yupb8HmoYwVAPFfRR4WkOITAJGwBCX+X+Aj7cpQohQtGDnXFH4q3xcmzeg0ZepOKpga54pCHVF0qk+V5GNvQIcaQ54ARCqFmua4kWbb3fnPlj5NQDZoIXQry5SsDJU1S1fvRoSl2DvnvqKb8zI5hP0V2DdXFb55fP3bI1bnnnlu1C/71r3/FFVdcgQkTJoBSil//+tfCiuHzn/98SeQswujA0DXETb3i1YIxg+UNnXFIKx57Z4fYPqE2ju4hllOTiptoSMZCQ4ANyRByZRqIhRxbSVhQBTconTOpFus6mYV6mEIGyHCgX7mSPxu6hpqYjppYvvO64eVY8T5zO4jWxhpBCjRNJr47hCJmaOKaNTFDrLRT255YlxBk2FbDbIEP7TDvLlXJEpNR4NNe/ZYeTODm29WacCrpydlE9Dlns3wwldz0pi1fPzO2g/6ssID05R55WwQpUAken2j5/buUOYjnhVgUFYofRwlAdBm2k4RIts0JAF/ZKYw0qZy4HeLvb3BCVcdP3QbIwsMyGV1JLAcVRIkrNFw94cpMsB4kN8cUITgCYcBJKQUBUw3twKpBRngAvciflCCenqpEqfSV4iqQWuTZcSksjYiizKpqR7z2CNW8PC/vXkHkcXw8+WpAL8eJeIohJzY870/X2XUsR4apOSHLOTJxXhBbl8Ix5POxXeK7Lh9H21HyqQh/xyWJ5AqWSxk5dAkF1ZQvLd4XFJ1qeZKVakgaYffhiRUdu+U6JZGr73znO1W74E033YQ333wTkyZNwuuvv46LLroI3/rWt3DBBRdEcecxgJqYMaLVgifOn4j5U+qRiHWISWlWS0qQq9q4gYYaE8lYPmEKc2RPxPTQMjeVhi6D5+8/pR7bejLI2u6whaDVsKVKrkydKVepuBGalM9JUU1MB/U+Yac21mBbL1vFp2kaNE1DYyqGXYMWEqYhikyn4pJcqf07br8WPL9mJwD48qXyVJuA8sC3caiJu75jFELA6w4Gk7d5LosaUgGYgsL7PJhzxAo+Tur6ArluWZuI/DeVBPmUK5JfgJibTfIcLjbZ5udccaIirBUI9bbx8QjmlSkEh1IRarVdAkPXRC4Qv29BROG3XuC5OVnbVcJPfuWK94eHqPj98+NYErYm7S8gQ288L4mDEwiurNlEFld2CaBrVCxSkGqSVCR5H4Jjp7ICSmVCvVqrT/bdS5R3WEiZK8O8XfWZEsjrc3VJqDecwBK2apBQKv61XeZSr+ZkxaCzpHZu6UB4/7j3GsBtIzhRcpUxlJYOkjCpdRnBFSoqCZ7/iwVTtFxCQXV/WBfe7xoFdApZo1CMcWDMqX/MI5QPl1C8vbUXh0xr3GN92O05V7ZtY9Ik5iZ91FFH4bnnnsP555+PtWvXRvLnGEBzKhaa2F0K6hImPjC7GQDLE+q0mWfZ7AkpvOXV70slTJiGjglKEjiHuoKPoyZmhK8WLLOuYBBcnaurMdHWksL77QMFlSuOeIGwIFeuGgMWDxx8WzJmIOs5oU9tSiK2lVmsczWrMemRq5gutqn32ZSM4di5EzCtMYm6hCkIos9TKnDt/AwkfwiIk4Fg0rb6a69CfFTwMGRwos85LMxnuwRpyxGqgCAT1N+HjOXKhHa17wppUZfSq/5Tjksl+fMInEo4OFTSJcqceMnQqjElvx4nC64rbSr4BKl6R4nQHmHEhRMO3n8KvjqTglKZnM/P4eOiEitOxBhpJtA0XSECfvVLfU58tRw/lj8fHqYzdM2nMPHVbqw9/3sbVA85RJ4UpA2CbEOSx5zjMtXWkGHYvOdKpR2BCGdqfJEGC226rsyDooJkqTl2nkO7RgTR4v3hIb2sQ4SqRKgurqWSXfUZ83Ycl+eVyfB2wjBgE+mZxY8jhPpIlKpoGUSDozFXfE6c+VgZYkwYG1e/XBRCWDJ8NHeycVi8fAcOnNqAB97cip89sw5nLZy6x/pTNrlyXRd33HEH/vKXv2Dz5s2wLL/hX3d3vvO1ismTJ+Odd97BwoULAQAtLS1YsmQJLrroIrzzzjvldidClTFBsRUoF+ofeGMyhs7+HDQNmNGcgq6x5F5ey08t98IRSq5MI1S5GmlYkKtzqZiBxhRTzMJyu1QUSmjnKwSbkrFhlCsDOZcpOnUJU7QnVk+aMtGf90UN0WqahmPmtIhnxO/Bl2eVz67yPoxVIiFdsfM/sDlE0nfgGMuzgBAJ3t45WZtNOANZxzOuZMfbjpzA1PazjisT2hX1RFU5etO28DFS9/MQFP+d16Lz3ws8s0qZcyVVG1l/jm9zCdetpJcUb8enehDqFQFm52Y93y2RX0Rl+7oGcT3V6V1eTyEo3nPL2i4M3RT5Qy6RYUTZn3zlynIJaogO05BjRJhUJAiBUMuUcF+QYAGezYPjivedUPkeqCFnrv7xfVz1gStJnLxHeQ43DnXVe4esoSj6KsgLJ6PU97xdqgljUg1SXWSlnQhMQ/OIr1w56Li6TGJXlEie0M7zCQVZ49fyxo57fvEVipTw3DHNGyfv2eqA4alauqbxKj6hqqD8GxiOYkUI4h/vd+Ir9y0DIBcnPa6kp6j4+7s7cPy8iaELm6qFsn2ubrjhBtx+++34l3/5F/T19eHKK6/E+eefD13Xcf311w97/r333ovJk/1O2PF4HH/84x+xdOnScrsTocqYGKIoVQJuFMpJREOSOZXzFXth5CrsRa+J6aFEqtLQJUcyZkDTGHmp8xLDhw0LhihXzFqBKVfNqbjXRljeFUUykJPFw4xcpYqJVZSGWHGYiueTS96ETGhnH8RdgznsGvJXOKAIDxVyqMnCKlQeVajMS1C54iQh57DQU3/GhqWELFUCpV4tY7mwiVx9JvOe+D1QdA9Zwj+J7xehGxFeg7dIIF+9sh2Zo6ROqBTS+JT7KcnQngwJZb2yPmyi95Qnb9w4QZImlHwMparFiRWh0nKBr7rzkT1I0pRzZDiVkwVV7WEJ9P7xJZQRouD1eN/UPCGA+id05L8rv3huPX6xdD3SXs1KtmpTjhsfe/VfETYl/nAx26/0n6rkDz5DVz7WfPUnHwPHSzIXdguECpLDrTVsn42C34OLJ6Jzk1FwEkQVNdIr18M9uHjeGieMvF1u/cDb49cIhgsl4ZYEWv0SoRIplWzz5xKhNLy1pbfkY7/8+zdxyV2vjV5nUIFy9Yc//AG//vWvcdZZZ+GGG27AZz/7Wey3335YuHAhXn75ZXzta18rev6MGTMK7mtubsbf//73PDXs4x//eLndjFAhRqJcqeDkihOmplRMFEsGgMkNNXnn1MQMxE3d515eKCyolpypBLquob4mhoSpkKvhlCsjn1zxTXXK6r0gRTN1DU1xL6E97ShtsCO54BdTLCqEcalhYHpzUiTds+PZPk4weQjuD69szuuz+iHO4VeuvDydQHK0egwnSMEAY9YmYuWZ6oeVzjGla+OuId+zFCsCA7lbOc/ReyjnObcHJh3qkRuxYstrkhMF3i6hFH1pG821cZ8Sxyc4Tu7UcBg8BcLUJUnlYTM+ofI+Wg4roszJAp9EfdcgcvLMeLlWPL+LheW4OSj1hSV1pSgxm4RlMWOu7EgrCjVHS3lOjiRP0gZAkgaq9JnfIwcndeL3wDuzcyCH2S2m77mo4T5HGQdOIni/ueIm9vPn6v1HvJtx+Y2D50Zxkub31uKkRyVERJMr/ADdR3AcL9+Mk1H+hYAXn3Y8IsXJsCS1RLjki9ClYnjKDUr5ikZd11j4lWji/pknF2BovH1NqFaCKPuHWilAjlDsa4SrP2vj3J+9gI8d3IpvfOyAqrX7+qaeqrUVhrLJVXt7Ow499FAAQF1dHfr6WN7I2WefjWuvvbaiTqxfvx7nnXceli9fDk2TXit8EnFdt9jpEaqIlroqkyvv36Zk3JfXU1fAqLS+xsSuQUmuE7F8h/a4Ga5mlYuJ3r3yvtQOs0oyEbJa0PAIWWMqhpqY38STwzQ0NMcpkjG5WhCQvmBczRPkKqaLPK2YoaG1oQZbutOCqPA2amtkf4dyfqNQDlUJktskMpYrcld8x3jkY/m2PhzQWo+EaeR9qOccF5ZDsHMw51Nkujz1LG3JcB/AyEtHfxZrOgbxj/c7ZR9sV5TSUSdsqVzJlVrqZEQ9YsTDlhQQbQS9tFhf2JmcEKpKAqH+MB0FVzU4EWL16bhRK1Wuz9UpQjwSCE4aFPVKmTCZVQJXrrxraJKYSOInc4JcIsOLal/V142bWvKFBjUxqSQ5hMKETKqXeWHlzdSib5AhZb4dkPfLlSj1PEBu8xuWyn6qkUlC2bPSvGcWh66UtVGVQq/Is9cfTqRUBdPV2HhZ3tgwYmWA57HZLhHFrLki5yqkjquUqlqqqlMst4r1ydT96h0BYOr5Y6SODR8PkQgfQrqK5VbtzXlX9760Cet3DuH/PbsO3/jYAUzpdl00JP1zVcYeWzyh7LDgjBkzsGMHi2POmzcPTz75JADgtddeQyJRWUjpv/7rvzBnzhx0dHQglUphxYoVeO6553DUUUfh2WefrajNCJWh3Hp9hcDJFf+3KRVDbQmEKBgarIkZqFESvAFJ2EaKSV4ItDZhIhHTQ1crqlA/vGKG51nlkaCmZFy4yX/4ABb25gnnjTUxJE12L2opG54XwFvlSlbClCTMNFhIVb1nHhasU0KjOwcKFDxXlCAOddIbyDqhOVeEUry7rQ/PrtqJXyxdH9p01naRcwh2DVr+sKC3SlSGnxgcl2Aga+P+N7b62rED4UU1XCImbyWHiU/uXKkQ6hiFKNCrKmYU7IOXE0jb8+HiRIgTQ54f5iiWD+rkOmTJgsV+RcjvBq72U6g4irITLPjMt0vvJZnwroYbZVhQXt+/WpCKPLg8805FRXJ4jlAgLKj+G4QgtAgm5Mv7AqSJq5q/Rn33Ka+j/ucGxpsrWnys+DsiXdElCXIIT/Rn7x5fJahaQ/hULkp9yf88jOgoKpRNeH4W8SlVariRK1Mq2VJd3dXnxlVS9Xmz8feTKfXn/MT1cDK8tytZwRD/whuewMIbloh6pADw/b+/j988v2F3d60oylauzjvvPDz99NM45phj8F//9V/47Gc/i9/+9rfYvHkzrrjiioo68dJLL+Ef//gHJk2aBF3Xoes6TjzxRNx666342te+hmXLllXUboQ9h4aamFcrj71iTal4XgmbMAST2mtMVji5JqYj7f0xjTQkyDHJy/tKxQ1BtMpBXAnfNaVYMrsG4OIT2rBscw9Omj8RACODMZ3leYUZkebnXKlhQUb66hMmujwCxY9Xidrid9tD+xjCrbD43XZ8Km4i67iY0pAQBEsFoRTt/dmi989zrrKKiaeKYJkbl1Bs781vM2u7gKbB5b5RoGJ1n+WwBCfbCwNRflNeezmHIK4kyvOCweq1CaG+nCteN5H1mZ2nU034IfmS2PkxhJmVqqqPSxiZYaFFWQtPXYWm5hRxIuG4nns5YxRe/pKSe6UQDW5pwK+raxBJ4PyeOXjyNjfOVENwjkuF5xRriwC67iNNKiiAdTsHEUQ+KZT/EsqsBvh4qfUQg21Lw0ypoBGlba72EcJCfnzlpOsq5EUhM1TjIUC5SpCTIj5+lFLhQRU0JHVcAl3XfCFDns9laJpIcA+SLJcQ7z8Konukz9B8qzTZ+OgKodJCxsT/paKYoriXc6lhwRXoDV1DOGhaAwDg58+u25NdCkXZ5Op73/ue+PlTn/oUZs6ciRdeeAHz5s2rODfKdV3U1dUBACZOnIjt27dj//33x+zZs7Fq1aqK2oywZ6HrGupqTKlcJWPoKqFmoaoecVNTgOUrVZtc8eR9TdMwu6W27PMTpi6S4HnSOXd5P3h6IybWy7yyuA4kY7qPXHE1irfBc778yhUrMi3yuTS5+rAUyww+oQfx1ze3etfUcNDUxjxyRcNYWQC86C8nV0E7h6BbvEuoKNCsIm27qIkZSh08ePlFvMYfBPFxCUVv2sKmXUPYb1Itco6LuMPGjZMxh1D0KNfhk7DIuSLcKkAXKguhmlC05OpBvyLDyJlUzvj1KDw/L0caVfpMM6kkGJTKyYFPttKvSVUwpOKieWSFebGZSikcKvLNAEbaLKG0+FUQfo9caeO+V+q7ESRYj4WstFIVFVVFVMNZ/F3gBCh4Dc2jVpxoyPwj/7EihEmZukTBc9ZUN3hPHfVsJtQVf8GQoZ9cyVwunkdlejYNwkbBI11U10SCu7rfl/+lKFe2q1Yv0MS7z5U83dBEv/iz0aGBaooi6I2B6vulklIMs328Yyjn4N1tfRU7qWtidItja08aM5pTFV1jOJRFrmzbxn/8x3/g2muvxdy5cwEAxxxzjHBYrxSHHHII3nnnHcydOxfHHHMMbrvtNsTjcfzqV78S14kw/tCYjPnCg6Ws8FOVqxrFaFRdMVctctWUku3Mbin/DyxYeFqFqWu+1YcxnRFEX03CVFwcCyhhwRgjbVwNq4ubMi8sbop2Q1wf8kBB0ZvJJzQcDqHY3pvJc/vmYZ1i4GQlq5S68e0PKFc2oejoy1eucjxRnMhcKE6S4ClRllLY9/t/XwWXUpy9cCo+UBPzfKRkyM0lBP1KsWpuEqmadtouhaZJAsRJVtZzl6dUruYDZL24tGfCyUM0lktgaBoytouuwRymNNT4wnGUUmQsIogwV6Qk8ZJJ7aJgMScJom9qOFGurONGmfKZQShyQi0LJJILpYlQ2FCVI4j+FYPss0eMFLVFbcefOxRC3HmOkdchNeyrHscTxW2HAKYu1SlBaHj4WIaR1RI4VGkHAKv26JFinqzuEOIt2qA++wWuUAmiS+QKQUtROfk1NY/cml75LxlClrYMfFEDISxHSrwL6vh446d5tSnD7Rr2bv3qs79+Ge9s7cP15xw0qtd5ZtVOfP7Y2aPSdlk5V7FYDA899FDVO/Htb38bxJNPb7rpJmzatAknnXQSFi9ejB//+MdVv16E3YOW2rggBbquYWpj/grBINTcIpWIqMSsWuRKzaEKs4YYDrVxs6DxKLNf8JOruKH7nOUbkzFRaxBQyuwYOgxNw9TGJFthqGtiHBuT0uRV17Rhv7EO5Vy8vL649xxXdlQE8ttDwfOabDf8gz643XEJbv3b+3nH8YlPhP6oLO8iFSwi1QZvYtnYNYScIx3auaeUS1hJHXEvkA7g7Di1JItCsLyJdijneIqSl7AOiEmdKBM1UyKIIGUZyxVqjqhLRxWjS0jrC06isrYrbAQEsYIMrYncLspdxGVOGN8u7tN3LwEyxUkckQn2QWVxS3caz67aKfKcfFDVJ5q3KVQd5cSKhpwbbFb2mW+X9y7Cwi6zgeDhNkf5V44pFatB1ULfag4Y8d6nnC0XAHA1LOfk2yqoShXh76YaHqQ8B4wqhEy+K8IHSxBo7x1S+saNbeVzV8eMFhxfvn9vwzuewfIDb24btxWCKsq5evjhh3HllVdWrROnn366+Hnu3LlYuXIluru70dzcvNeugNgXMKM56Xt+zSXYPDQpxElVrj4wuxlrOwdBKEVDiNnoSFHJe1abMPNICYeuab6wXUxnIUO1ILPhhU7NwGrBuKmjJm5gUn1cLALgY9GQjIkPU0NnhXGLfbZu7UmXdC9hOVf6MGMStjJShajFR1iuUKGx4jMsrx1H4SUmEwITulCy+Lf+YB+ku7ZUGDK2ktBOZX4MP85ymUklJ04y5MQcvXmOTbBt4YMFrkwAmsbCjMLKweWleiS5kDlSsk4gb0OoJZDhO65ccRVL9bkSpVoI9Y0Ht23g1+Hn8nFS+8EtAlT88VVWFNzUNZw0f1KBRyWvGVRbgtuCIUFfO5wEQlHDggqOQgyZxQFELhQvUs0VOhCp+AlfKe93nnOlQ44H88RyBWmVRErmSQU9rdQFBqJgtbJd04iXBK+J4wzdHzLUdQrDe046lYn/cgGEQrS0oGpFPRd3Of57Ia/Kw2hygGsffhcfPXAypjYmq9522bPUvHnz8N3vfhcvvvgiPvCBD6C21p+rMpzPVamYMGH0q1ZHGF3MnFB+qK3WMx21HOILBbY21uD4eS14e0tv1ZSrkaI2YRS0QDCV4suAXGodtHtQk+LVhPaGmhiSMZlrZRrMnqExGcOAV+7F0LVhcws2dA2VdC/5JqIsyXsk4Mnud724EbMnpLB/a0Pocbz3vKyI7RDkHNdTXaSKwnNpfOdSinWdgxjMOWhIxrwkdxdDufxl2Vyo4SSKKwQOITCpWhqGkxepvolJVVEZxKQKwAIRpVKGLEd6JbmqzxMVqhMUQsHvg/VNEjmRI0WpIBjEO5nnXQUVRtVvyhd+JJKQ8esRaKGT8+ubegqqBT5FRXnvwtoJEmH1vKDmWih0qK6MdAi3R5ArBsU9avyeGSnh23lbsj2e90YECVZ9z/g4CUWJyGurBEtNqucqFV9taOqSkMVNFtLkjvAxA6A8ROjZQ1C+2FVXnz2FRjWfNYWfavm3R6gc1z68Ar+56Kiqt1s2ufrNb36DpqYmvPHGG3jjjTd8+zRNK4tcpdNpfP3rX8fDDz8M27bx0Y9+FD/+8Y8xceLEcrsVYQwirGxNKWhMxrBzIJd3/tFtEypOcBwN1CVM7NLD85mCyhVHbSCpP27I8GFcUa4AuQIRYLYNh89qQlxJojd0Vkoj7NN1/yn1WNUxgC09mWHvY0t3Gg8u2+bbxvJDSv/YdgnFms4BzGhOiRAmpcCq9gFYDsGazsG8MBSHuqKNh12yNgkNe/q8k7xzfu+Zp85oSsIwdORsAr+iw/soc6iEskRZSC9uGEKJkEn1ri8E53hFoillk7Jckg9QV66cS1uuWOXHw5mGdyfcaZyTBjXEyMeCkybWNxcxQ5fKhiBl0ndJjA1lqwVlDTt1n0zk5uNYLGfvtY09hXeGQM3dGso5cAgVq3FLPS+oxKiqFiHMq8pxCWxX91kiiPMp8saIEJazRShbychXD/KQourobhLqFX72q4X8Z0f5jz07vx+WC7VqALciMdgiA4fCNb32dO6H5dWuJF6elkLqw8aCIygA83vfG4M8tkt85tOlwirwWROGnpBFNtVA2eRqw4YNVbv4d77zHdx999343Oc+h2Qyifvuuw//+Z//ifvvv79q14gw/tCUYuSqpUpu8aOF2kTxnKtYiON7MKm/JmYI2Tum+FwBfkPXuKEjYTIfLR6uM4rkXJ28YCJWdQyUdB9BYgUwUrBrqPQPnTc39+DFdbtQlzDxxRPnyB1KBwdzxa04GFmASBo2dA26YhcA5E8sal7XkOWiIamLPK0gsrYs3my5nuM72L3ynBie18TzqDh5Id4+4YWlTu6eWsJX/hFv4tY1Tawg5BfmJWq4giJChAopECoVNGRtV5ABnrTNj2Mu5fmKIwgnkkqiOXjOEXfJr0zxCCach+E3/2RzxGUf2i/vy4Q4t8DVKSjSloPXNvZg4YxGTG1MCgVJ1yUpYl5dsh+8NUK82n5E5shplHoKkCbIFjda5UXDeQ6aWnibE1IAPsXKcaU9BleubB5KJNIhnytdfPWgSwhcz5JBKpLcbkKqlMLvzOuzqsDxAlG+HDhPC9wb8X77AN5vL+1zbKyhbBPRG2+8Eel0fh5HJpPBjTfeWFZbDz74IH7729/iV7/6FX70ox/h8ccfx8MPPxw5su/jaPKcd6eElMgZS6hLmAWNRw09XLkKblPd5+OeMWlcFHBWikMbOgshapqwbNALEDuAjV0pVg2FsKMvW9Y3Ru6JNBgIk6o9eHx5YS8uQHo9cVLjEIrBrONzW1fDlyu29wMaDWmH5JEw3jdpJCpDa5wk8RAhD/3xnBy+wk+EiFyKV9bvwuqOAV8+DVO7iDCX5GoXVzf4PQJyNZ0ogqxsd6nMkeJEzxZ5PjJc5RCCrgFJgKlyLy6RDvB8H9sP7zp+FbBUFBIExHWUWb9nyAoluWGkTE3aXrKyA29t6cXvXtrkW+3Ic82EQSjhKyIVdVIZe57DJO7dI7Ki5iFhz9hyZfFxXrdQ1MukUq0S4UHld0GmvYR7QcKUNqTru6zHqNpMSHKttgtx32J8lHuhvrHbO5PaxzsqKtw8OJhvLpdOp3HDDTeU1daWLVtw0kknid8/+MEPwjRNbN++vdxuRdiL0JSKQdOAyQ3VKSI9WmhMxnD0nObQfYamCQf2YkgpSpZp6L4kfhUxQ2PkS1d8rjStYCjA1LXQmowjQV/Gxp9f24I3N+eHjEr5bH95/a7Q7fxcx8u56svYIsepJ20Lx3fAbz0QvK4ILyrhIhWqY7zjSq8oQYAoVfJvZK0+fh2+QuyVDbvw8oZu/Pr5DT5ixtt1CQvPCRWDUl8iOV8Jx9vk986vQ4FAMjtEojNPgOYk4/9ekJEEopzjEmUVJQ+9QSkVRIczXQg8I3GN0s9SSc/qjgE8+vZ25fqBY5XfO5VqAzLc5zdaJYFxl6sLmW0HJ1F8PGWtRYhVgzwxXpqCqqFeJa+OShWK+I6Dj3iJsB71rza0lHfB9ciZmljPr0Op2mf+fvJxh7I9/wtF0ecwzogXIaWH9MYyyiZXhWoYvf3222Unobuui3jcH/oxTROOU36MNcLeg8ZkDE3JWNVK8YwWamJGwT4WUq6CSMb9f4KFwigxrlwp7aohwiB0XctTkUYCQimefr8D7f1ZPL+mK29/oc9vNXBpDJMUkrUJfrl0PZ5a2eERGYLOAb8vVjBvy0euvH/FCrLAdkrV4sxEKDdqjg3Pp1FznPh1+bbOQTn5B3N/eGhJlFERagYRidS8T3wSBuWWDzQwyVIfeRNqjLJd9fNi7XI1ThqcBsc4bOyGw8od/Xh1Y2FLj47+LBYv34G+dH7o13EJ/vZuO9Z3DeXlcklyVBicuIjVe0T+zsmGIGFEmrGq1yDiOpIsu8Rv9yEXLXD1U443J2DcoFWuHFVrEfqVUN5vVrbHr3Zxk1dRs1CQMyht8YoF8j74f3zM1He0HPjDu2OHfL26oRtH3fz0nu5GVVByzhW3RdA0DQsWLPARLNd1MTg4iC9/+ctlXZxSiosvvthXkzCbzeLLX/6ybxXigw8+WFa7EcY3mlIxtJbgiTWWYej+1YKFkIz5/wQLrYSMGczdndrUR67OO2I6/vTalrzjC+WCVQpCaOjEKfYXmh6VbhRcgeadu6p9AMu3MX8bbs7ZPejP+wp6Z/n0F6GABZLxlR85ueEhJkrlknuxAk0hL/yYwZwjwmrqXOS4LMeHU2w1HGi5Um3hJFiUQyHSd0ntF6EUxGvH1OVEy/b5E7bZseokKcNfwfqKfL+qkBV8ZiFY2zmItZ2DmNNSG5qozt9BNTmYUIo3NvXg2dU7xbaM5eKtLb2IGRoOntboO1aDhqGcIyoxiH6DGdLqGnzPi+dPCTIKxTMqJKtLhNX4cYrdBh9jy3vAwrqCsGwmfhxXBXmOlEuYyqg+P06+xIpUr//MdFSHoSiaUFQrw8vb4/5o1EviF0a2lC2MIJQygxLveasu7uPduuiSu18r+UvhP97vwPSmJBpTY2P1eBAlk6s777wTlFJccskluOGGG9DYKP8w4vE42tracNxxx5V18Ysuuihv24UXXlhWGxH2PtQlTExvGp2SBLsLJZOrQDHrpgIfFIauoSZmIOcQQZwMXcPRbRPQlIrlFVceSb5VGHhhY46dAzkxyVLqJ17qh7zai0JfkPl21fjTdghg6HnWC0HLCF87/BiXolCNcH4P0g2e5814kySR4SU1LJOxXBGaU7/pO4QgRjVQb828ms/DCZzlEqFw8rAj9caJEwEe7hQEiXh+SJAr30BZPy0lbyeY2Mycv9l1co400RT9LWD4Wir+vqK9qKN1r/IerGofwNueGSRH95CFlTv6AbC/c152ilIAGsV93spPcU9sB7tfjat3Up3kKXcUUqFSlSzRTsDIgBNQ29W994Armwr5pJQ9V00qlDwMaGh8UYBUEsOIsAw9S2NcU1csJPi9aIBOqO/ajHAqZNCl0E0v0V7cF1crJcGvBGOFmJUTdv7Bk6vx+PJ2/O2/Thr+4CIYLeWuZHLFidCcOXNwwgknwDRHbuR41113jbiNCHsfNE3DvMl1e7obIwJzXi8hLBjIi+LJ/GGoS5gYzDk+h/baRHhocjgD0HJBPOLB8efXtuCrH54HANi0K+0zCB3IOj6n/VKhTvyWy1bbBT/38uwcfOEfPrGF51wBsqCzS/yeUrz8DF8Jxp3X+SU40eJJ1GqfiSl1Et6mLVaUMVIa81Y9qpMvpbJEkBr6o2CkTXN1pl75+qH4bZFgYrPXC8ruM+wVEMoVKgsndZexgrRrMP/YAWXF6HNruvD5QE3PISt/MZNQ2Th5IkEfK2XsvOeYT6zUcBojTWoeFCcyzBRW8+W2cXVJWDMQVh8QkP5hjrKf94kTLL4CVi2nE3Rx1zQK15V1CPlqWa5O+cgelXdFCIWm55PHfQXveUR9LKLsnKuhoSE8/XR+TPSJJ57A3/72t6p0KkKEoKIz3mCWHBYsTbkC2JgYmj/nKlWgXqNZSuHBMjCUc3wf3aqiFFwqXchjpuCyfK8p1bOJl48JYldgwqYl/KyiP8MmdzXkJ8KCVM2p4ROkStggcrI4HK/eIO8qD0hZrrrii692U0vwsPZyDvdVkvdNvetkbVfJAZMTrKhDSPLvkotZjpdPpAbHuNWEeuzuhu3Ii3YPWejoz681qYLdj1wVKG0M8kkTUFj5CG7mRMhnRAqlLJJyDr8mI81SwRKkinJbDOrrn/DDompiOxHHBNUwHk5Wi0oTQsU7pa5AZIoVxDXD7jHCnkXZ8tPVV1+N733ve3nbKaW4+uqrccYZZ5TdieEsHK677rqy24wQYU+ChQVLSWj3k6vhFB9dh2jX0DXh+H7hMbOwrTeDZ1ax/BazQuXK8IrOBvGHVzZ7Jqdy37LNPVi5oz9PoQgaW3JQSlEbN0LVieB5jkvhGPn9CMvHke3Ln/0rquTP/Z67vY84CRWBkaKExleEyfb5sv6gKsIJElV+Z6Ee5mlEqQz/sURrf794GRe+PWsTqXBpSjKz12dO+ngCtAo+fDzUxFe8qeMjyeLoTMYFSxx5CBLvP722BecfMR0zmpMIU14EydGon+wIQsFVPSquz4lSGPkKtsvJklqHUaeaQlj8zv2OIMhEjDMn6ODjrTjLc0VL+nPx5Hgi8rnEClbdv3LVdglMXZfhTkJBNIVcUUnS/c95bIT4SsWe7u+bm3vROZDF5Prq5vmWTa7WrFmDgw7Kr1R9wAEHYO3atRV1IlgM2rZtbNiwAaZpYr/99ovIVYRxB71E5Yp7WnEMVzfR0DURBkyYOuIGNxxNYEpDjSBXIf6lJSEZMwomlAYnxudCVg0CfmKjzrWWS/LKngByElTPs12CmJt/E0HiVyhfohBxyHjkjIdjuCIgLRoI4oYmVnNRbxbjE1jQ5oETlvU7B1l+DOXtyBWHYiWi4r/FJ0xLCQsCkqg5LoVpyhthE7iazM3uZWZz0ufCT8ESw9X8H7lPCY0pys+exoPLtmHRgVNw0LQC5ZE8xsLqaPrVIU6kOHgC+XDEUVXE+H88f0tdgcd/DhaDdqnsC8+7ylPZeBiReqsKCcvv4jlzrPagJq/ByZenblkOhRbTRD/4Qg2W2M7DloAeINERysel97yO/++rJ1a1zbLJVWNjI9avX4+2tjbf9rVr1+bVGSwVy5Yty9vW39+Piy++GOedd15FbUaIsCdh6lpFK/aG+wZnaBpMzwurJmb48roSClGrdLVgTRFyVSr6MrYohOoL9TkUYc4VWZvg5fW70KAYsnJX63LgI3UFFJScQmZEWFAJsQXrzPHHIawRQmaxF9d14YW1uzB3Yi3283IFxUoyIlf3qcSMq2DBBHlJGtTEd3Y8d/7mru8OIfjA7GZBrjjZgEZDyRW/bnCsxgJWdw4UIVcQBcqFiiPG0Y9iwllQNaQUwvFckk6WHM7VFEJlqJc9A+8ZEtkfylUlhezxMLLMq4IgVjGii7w5EE70CQxXE7lZXJFyXfnOyNxAAIZUKA11PAp+2ZDq0FixXkhbDmpMY8Rle9LWyC1nggsvqoGyv99+/OMfx+WXX45169aJbWvXrsV///d/4+Mf/3jVOtbQ0IAbb7wR1157bdXajBBhdyFh6qMideu65jMajRm6yNOKKeRKD0hXB02tx/lHTh+2/UImpuXgiRUd4md1EucmnUE8s6oTr2zoxpL35HlDObuklW2+cIiyvdAky5UiSqXbuOqwrpInlWRyImYHvKMomN0AAKzvGhJ+WGr+DVfJ1JAinxh57UK+nV/fVZQlVVXj7fFJuxCcEHIVnFOrMclSSguaw27rHb6uJYdLKB54Y2tI+/I6wpdM+Zkf41PkqP/cYFscXLFSr8GJbFC5ktYMTH0Uzuq8b1QuRhDEjcpQsPC9ItIzS5iPElngW3WhV98hl68yVZ494ddHcbKs3t9YQedAFgdd9wQ+86uXR9zW9//2fhV6VH2U/Un6v//7v6itrcUBBxyAOXPmYM6cOTjwwAPR0tKCH/zgB1XtXG9vL/r6ymeU119/vfDk4v+1traK/ZRSXH/99Zg2bRqSySQ+9KEPYcWKFdXseoR9HJUWrR4Ouqb5Vgc2p2KiBI+qXAU/bM8/ckbRlYgc1XZ1DypIYcpPWJmdIcstarsQCh/RCp9I1NWGQq0iUpHiy/LFz1SZhL3zgxO7Gursz9iKkuE3uvQZQkKGemQOjZeoDr+dgAwb+T2c+D4OvpJPqHGBsQ4qNA5htfUGssVrPhbD6o5BvLKhsLloqdjak8HWEDKmpuRLMgMU4t0izyrk+Yt2hMIkVUKxHeFkhCtTPFysPh9JeKhQLIFg8j1AiKyN6BKVfHNipXppUZ9Sxa0jVNNa6nWWE+5CfS+0PW98diP5+ptXCuvVjd246v638dCyrV4fym/rnpc2VbNrocjaLp5d1YmsXXppvorCgi+++CKWLFmCt99+G8lkEgsXLsTJJ59cblMCP/7xj32/U0qxY8cO3HvvvfjYxz5WUZsHH3wwnnrqKfG7YchJ47bbbsPtt9+Ou+++GwsWLMBNN92ERYsWYdWqVaivr6/sJiJEUFANBSgMcVP35WlNqI0LUhVXSFeQ1OialjfhzG5JYdMuf53Qaq/SHCa/uSD4t3gA6E1bqEuYoSsggyqSuK5yYceleOq9DsydWOurV+kLtwifKVW1gNjGj1UJEocqUP71jW04e+FUoYRxtUoQLWUi54qFqUvLCZurW8q1c4raRpT9PL+HY8l7HSK0FiReYaAU+NXzzB9twZTKrE/6R0DMSgGlAJSQIM+7Uscx//jw+w4bDpkjxbLV5HZ2PC8bzpXEoComzqfKClOvDaFYUv+qQRH2IxTQ2ftpEwqNK1quJFYxQ64OFQqW8twdj/mLMSlSzD04BmMl5/2BN7fhgTe34bwjZuzRfrywtgsnzJuYtz1tOTjyu0uQtQk+ftg03HTWfiW1V5FZlaZpOO2003DyyScjkUiMOPxxxx13+H7XdR2TJk3CRRddhGuuuaaiNk3T9KlVHJRS3HnnnfjWt76F888/HwBwzz33YMqUKbjvvvvwpS99qaLrRYigYrRK96QCypKmaYJc+ZUr/3nBFKyDpjbgM0fPxHWP+BXbaituYUpVKeBEYkdfBn95fStaauO4MMS80l/GQ25X1ZRN3YxArtjejw/ObRHb+VJ5HqIBICZa3neplnj7SWDFX+D+VnUM4CxMFTlWqq9V1nJ9kzJ39k6Yurgmy6fyE0X127KqsKn/BqEmZYeNT3Df6o78erGF0D1k4e8r2nH4jCa8u636uSphUFUnruypGMw5eGtLLxZObyzo2B2mZgVDtexfv5KlaQpJ9vLwgueIhQsKIeNeWmpYWJTQoSz/yqQsyd32zIEFiaLcJkIXbTiEQnOZUz2hmkhoZwW62VU1SBIq7puOr9WDewqf+80r2Pi9s/K2X/PgclE26pG3t48euSKE4Oabb8YvfvELdHR0YPXq1Zg7dy6uvfZatLW14Ytf/GK5TWLDhg1lnzMc1qxZg2nTpiGRSOCYY47BLbfcgrlz52LDhg1ob2/HaaedJo5NJBI45ZRT8OKLL0bkKkJVkBgl5UoPSVTnSpZq/RAkNbruN+RcdNAUTG9O5rVVLXK1tSeNB97cVvH5/VkbTak43tvBPLR2lWBeScHykn6+dF1BxSwsedz1QjHBeoJc/ZKqBJiK4msvXwHgoSaXEIW05SfoUwrkHBepuCGUM0c5hvstqfYGIv/KC5naTuHQaTFaS1G4kPZweGJFO3YO5Hw5cqMJlZCyHzSpKnrbHntnOzr6c1jTMYBLTpxTUniJqXt+0sXUKS2PiHLVkbKDxBlEIc+ir5o/VMiVJm7LoJqHAnxxgj8UqPpgUa8NVkaJqV287zwpXthuhHAo/gVBC2wbaxhLOWEq/r+3tld0Xtnk6qabbsI999yD2267DZdeeqnYfuihh+KOO+6oiFxVG8cccwx+97vfYcGCBejo6MBNN92E448/HitWrEB7O4v1TpkyxXfOlClTsGlT8dhtLpdDLieLtvb3M3dY27Zh26Mrj0cYXzBBxDsR/Lfq19IoCHGhKR+Ztu3PYyKu66s2T4iLRAiPSigEjX1DrqxPIyFWAMvJ+MLxs+G4UrXJWnae672r7CfExfJtvUX7bDsuCGHnWI4Dx3VhORoyORuuy0weHZcdYzkOcpYOx3WRJi4c14GmaXAVAqT2T+2T4wJZi+13vaT1TM4WbbuOV74FGnrTOViOAw0acrYDAkb4HJ31xXGI6LPtuHBdF1nLgeu4eY71/DgAcBz/7ypyFqk4VyrnlJ53MlIQ4rJwHa8DA7ByNA5/59n70NHPPpf7sw6IS0JVKg3+0LjjKLlT8NQdCsBTkKABVPNWDkJ6VumefQIoQHi9Q00SI14KyXEpYjrgOi4cUOjQkdMpCGHeVTmLLUixXIKc5cLUCHIOqwmZs2zm0g6CbEIHoRSZnAXH0BEzNJiecmVZNjSDwNBMWAZbJaxBEn5NYysQNbDUAEKp+JeH2VWlLuzL22jADfm7YZ+PxT9wRnueLaX9UvtQNrn63e9+h1/96lf4yEc+4ivUvHDhQrz//tjI2leNTA899FAcd9xx2G+//XDPPffg2GOPBZC/5L0U6fTWW2/FDTfckLf9mWeeQSo1vmvhRaguHAIELKywZMmSUbnWxgFgTa8OewcFvApjy956S/wMACtWrEBHRgNfw7JmzVrEugiCHwHdO9vFMU1xiu5c2N9Ega/IVURvxsb7q1ahp08X1/rl8xvxgRYCdR3OH17ZLPZv3boNO7Na0b4tf3cF1vRpqI8BU1IUNgHiOpAygV6LhVt2xCj6LQ0Jg6LWBLIuu+OcV55kVx9EH1avXg3XkX0EgNVrViOuAzEdsAnP1wG2xYCsA1hE84r0AqbGSGzWa7szzib79evXQ9coEgZrwyFsf9KksFygMwH05IDOAflMAfZcOUydivOCsFz5rpSLnGVjtJ8/B78fzZcTxYpav9utI2FQzKkH1DFYvWZ1gf7531tDk4ngKnvjXyp8JMXbSyhEAWmqbOe1Bvl+gB3Dn5+ps2cdN+T+lMHOsylguUCNyT43bAI0xplaGjcomhOs3X4LMLx2Ut6f7fP//CccAtQYbJuhe/1W7tpV7iXYZ95PPjq7iVthZbuG4Pu3ePHf4LoGir1bixcvRoXZTCWBtR+E/3pPPvlkSW2V3ctt27Zh3rx5edsJIWNWvamtrcWhhx6KNWvW4NxzzwUAtLe3Y+rUqeKYzs7OPDUriGuuuQZXXnml+L2/vx8zZ87EqaeeipaWliJnRtiXYds2lixZgkWLFiEWq34F9xXb++G834mjZjfjF++/AQA4dOFCYK3Mp1p46KFY3TEAtG8BAMyfPw8fPmgKbl/+kq+tGdOn442uHQCAVCqF7lz+Cq6DpzVgxfaBvO0ccVP3FXmuFPPmz8f72XYgI5Pu12cSAOTnjEPlB/H06dMx2DEIDBTum9kyEys2MZn/G6fPR9YmqI0bqEuY2DlowSUETckYvvfEauiahm+duT8ylgvbpUKx6VzXDQz0AgDmz1+Af3ZtQtaVSuH8+fNREzOQMHVkbSJWBDbUmLBcgozlwtSZGhEzdJiGhiHP9qE5aeLtFe9h7ty5iJkGahMmsrZUqOprYshYLibVJ9A5kEPfph6gd5dybfnZnPj/2zvzOCmqc/0/55yq6p6ejZlhG/ZVFBGQRUVFwAW3GI2amBgXotfo1RgNV41eY4Jeo0lcb6LRmChqEqMxRpPrLxpREVGjgmgURUR2kEXWGZitu+r8/jjn1NLdM9M99CzA+/UzznR11anT1cX0M+/7nue1RLNRpi21TcCGTOuDXDBCsCMwryccdWJg2F7fhFVr1gJgmD5uCF5ctyJ0zPCsYzEwJF3Xj9gIzv32MuZ5/YMfQDGCxOJMpWdl9HnoAnvzfvpF91D7FDkCTSnVJzBmcyRs5evEGUNp3IJgDE2up+7DmGrM3pD0UF0eR2PKRUnMQp9ucbiexJe1TbAEgyM4im1g/vw3MOnIoyAZR2ncRnmRBUcoCxgzRc6UkOYsU7JYgmfULLZX5GpnfRK3vbAUZ4ytxqQhVdj2zhr8ZWVaMGbAoWh6+6MWxznllFNw1b9yEzdt4ZRTTsnYln6+cElRS+Qtrg4++GDMnz8fAwcOjGx/+umnceihh+Y7XIfQ2NiIJUuWYPLkyRg8eDB69+6NOXPm+PNtamrCvHnz8POf/7zFcWKxGGKxWMZ227bb5UOT2Ldor/ukpMhBIuYg7gRjMy5gC+avuLMsEfG+4lwgEc+0Znh/bVCg3Nyv2dYsHQpVO8G5wMot0dWMLbZXYTxj/3RWbwvE4u4mCUcIcC4gGQfnHBIM9SmzUlGiMSXBuQA8V31PQ2ZZncW5AONcfwfmLN6ArXVNuPCIgWBMgHOAcQYu9XfOgrGZ/uAX6njOOTiX4FpE+o+5mm96tD08RzWH7NfhnVXbW7xOXQXzesJF5IypCE/6PoaUp1pPpV+bjTUNeGrBWowb0A2Th/dQPTpDbXXMOcKHmXeX86BQPSz01mytw/trd+CEg3qiOGZDIki7AcF7wAUDYxySafHD1b9RMICDASkATD1mXN1XrlT7gwkwLvX+DFxwcKGLALiABAfjAsKy1X3DzOpgHYVjnt/InYUyrGaVqnm97Smu7n7+U/z1/S/w1/e/wKqfnRpZvW+4+s8tCysA7f45m8v4v30jN+uHvMXVT37yE5x//vlYv349PM/DX//6VyxduhSPP/44nn/++XyHaxeuueYanHbaaRgwYAA2b96MW2+9FTU1NbjwwgvBGMPVV1+N2267DcOHD8fw4cNx2223IZFI4Nxzz+3sqRNE3sQsgZKYiFgVTBxUif8+5SDc9+rnOOaAHlnD/bbgwV/kmo3hRrpZjrlsypBWV5YlczD/zIXdWZziWzIWVbYFLdcDhfsgvrh4A04b0wdAdNXdpxtCkS9mWskEm8J1X00pL2s5gV/Q7El8vEHVZq7YshuDugddLIKl/cHxJvrx6qdfYnNtEy4+elCkuDrsTG4K59tCW1dxdgXUqr3mn//DO6uxqzGFod1LELM5hvUowaDuxXhTt2tatGYHJg/vkVHdk74CUEWgQiEq8xwLIlR/fV/VFr68ZDNOH9s3o6jceJj5P0sJFwA8dV9Jxny7BuNjldI2JOax+ffkSQnpSqQE00am2kYEgUmpDKU+ZbpS9Odv7iMW2d6ed8TabS3/0bM38evXlre+E9pgInraaafhqaeewj/+8Q8wxvDjH/8YS5Yswf/93//hhBNOyHuiLbF27VpcdNFFeR+3bt06fOtb38KIESNw5plnwnEcvP3223607brrrsPVV1+Nyy+/HBMmTMD69evx0ksvkccVsVfiWBzFMQu2YPj5WYfgwfPGYXD3YhzStxznHTEQAyoTYIxl/PKMWRxnj++Hvt0C76ejQz4v6TGZkpiFmCXUX/x7yJXTMksL0slm2JdewB1m486GVgvww6vxtu5qwsufbMKiNdsjAvP5jzb4P0sZmDYGG4MfTfPddHzrhjRh5PcYNOaSEmniSQ3/8YZafLmrEZ9t3pWxOtE8DvsuZaOrrr4qBM2ZxALKlFZK4PMvd+HjL2rwt39/odLUWVZ15ny+LPuGr+/O+mRk32xfZoVgxPNK9xEM2zWYe06JyMBcNLyCULXPMW2WlAiTnrk24XY4wXzD29Lvu45mfzCGaFNl2IknnogTTzyx0HPJYNu2bXjsscfwyCOP5HXck08+2eLzjDHMmjULs2bN2oPZEUTXIKbFlcVV7cWAShUdCYsgzljGL1NbcIzsU4aBVcUYVJXAM4vW4fYzR2PiT5X5bvovQPNHcKoFgZMr/ataXwDCs0SEWkoLvp3D6rfGUD5pR30SO+qTWPxFDQ4d0C3rh41xzo5sC+uszOAAgKCtSliU1dSnsGjNDsxduhl9u8Vx9vj+oYLq0Jihn5MpLzIv8/r9D8gWXmv661m5ZTfWba/DUcO6Y+uu1q0tuhLpryVfYZBNlOfTX7G1PXfUZ683NjYK6v3SFhLaKyvlST+i7LfB8bJ/ZyyINkoZ2Igo1374vQrDASlfhEtA6mibTDNYNbtLM1fZen9TIjfaXHa/cOFCLFmyBIwxHHTQQRg/fnzeY/z9739v8fkVK1a0+DxBECotmHAEHIuBM+Z/2FuhghsGoDQe/efuWByCM3CmnN6nHNADPUpDNYVpv2M5YxCcoSLRehud1sgmnNJpj9/xm2sbs253vezREM/L9sEebPCa+dg1y/vD+4Z9odbvUOnX9OhT2CEeAF75dDO6l8b8ptYmLWrm2mJPOSjX6YWrt+PIoVV4a7kqfO9eEtvj5txdiSfeWdPqPvneS5tqGsAZQ8+y4N9DetowjBsqjI/4ZoWOMSlCJZBVxEmaZsoIek2qiJQXMR5lTDVx5tz0wtRmqp5KM5oOAJ7U9XlmRSMz95iqA2OSRebD9B9dvocXUTDyFlcm5fbmm2+iW7duAFQPwCOPPBJ/+tOf0L9//5zHOuOMM/Sb2/zbSiqaIFomZnEkHIEix4LFmS9cjLZyLFVUe+mUoXh92ZeYMrwHABXZMvtznlkAnI7gDJZg6JfFfDRfutq/6myO5mZ75rbgZynhuzeHCcRP8+dcu60O/SujEbz0SFZdk4tnF63HhUcO8ucTjkKGpze8Z7SFzZe1jViom0obYQUAtXuZsEq5HjbVNqK6PJ5VlH+5K7tgDrNtdxM2heoJt+1uQmVx9j8SGlMunlygVtV+/9hhGQa8hlwCX+m7mNWJnKnFJhY3UWUlmFwtdJKuEUtqPoKp2kgB5reGcqXpIsD8+9f1JARXqiqImKk/AiTCoh/K2kILLFffV+p1RW2JupLD+2W/f69dxy/ka8275uqiiy5CMpnEkiVLsG3bNmzbtg1LliyBlDJvA9Hq6mo888wz8Dwv69eiRYvynR5B7HdwztCvIoGELWAJ5qcaTOQqZnFwxlBeZOOnZxyCr47tq45jDIJzf2m4+Z0yopeqPRyl+9QZTj2kGrZeobandVecA+cdPqDZ54d0L+7QmpDm2shs2dWY+cdf6OGjb61CfTPNXFsrOP/bv7/Qw4UiHVniB+kpp3BELDx8VZpYaGimuL8lV/euyAuLN+Iv763DOyva3iD6mUXrIwstfv/2amzc2ZB137BYbq7w35Oy2a4BWYVY6DjT/NlP+5mfXc+PXJo0X8rzVONmL6j9S3rKbNQ4tHsy3K8wFCWTCO1jImcy8ryZW3vXYGUIljYKmBc/3liA2TTPzD//O/L48X+tavNYeYur+fPn44EHHsCIESP8bSNGjMCvfvUrzJ8/P6+xxo8f36KAai2qRRCEomdpDEWO0D43apsRQLYIluwLHvQi5Ew7OmuxJPQ+15x4AM49bAAO7lseOUe/iiJ/pVy+vxoz6rfAcNjg5r3hVmzZjUVrtud5lrbjSYmP1u/E+u1RX6/H/rUaC9JsC5pLBYYx9VAtRa6MoIsUHWdJQ4ZZvH4nHnljpZ/ejAqz9ElkH8NEs/YWVmzZDQD4YO2OAo+bfdVr+F5t7r14ZclmbWCbG+HUWzjKZESWuV9kSDCZur2U5yHpu7+rryadPjRNnn2RJmXoeP2lxZkMCS9Pp8FNrVX6691fP3effT/aWeLHf/u4mT1bJ++04IABA7KahaZSKfTt2zevsa699lrs3r272eeHDRuGuXPn5jtFgtjvYIwhbgvYViCkrJC4Mj8LzvxehCbNZxydjcdNRcJBj9IYHBH920vtz/X5MudwyeTB+O38lVnn9x9HD8aqbXVYvXU3vnZoPzAGtNbbevEXNbm89IKwbls9Xv10c9bn/rViKw4bXOk/bu1zJ5xaaMuHVEtHvKLn+Pd/f4Ezxrb8+7a5yMzexOqtzX8+tAcpz8P2uiAiZSI9TJuFvr92B/qUF+GTDbndm9F6uiDN7EeSJIOnrRSgU3YmkgUEESsjqlIewF0JDglPN4YGN88bwRbcd1IXwnN9TiYB6UWL4019lt83U7ZPveP+Rt7i6he/+AWuvPJK3H///Rg/fjwYY1i4cCGuuuoq3HnnnXmNNXny5BafLy4uxpQpU/KdIkHst4RrrkzkyhJBGs+xuI5WKUFm6YJ2zoLIlfnFGrNFpL+gxRlsbiJXYZtq4CujqxFrQS31q0ygJG5jZHUZLj56MF78eCOGdC/J8NnqLHY25N5dIlfBpGpd8iPXFWzZol476pIRYTf/8y15nr3r8Vwbm+bmQriof932Omzd1YSlm2qxISRKpVT7WZxh1dbdmL+s+WuqCs6bVyVB+k0JKIsLXxQZAZe+yjScDky5UvcKVLVapuYKnvKWS7mqsbNr+t3os6rzBa15AkuIwDjVNJfmEhn1VuZ7V6m72lvIW1zNmDEDdXV1OPzww2FZ6vBUKgXLsnDRRRdFfKm2bWt7jpwgiPyxBfd/r/qCKhS5cgSHJbgvpISuoWIsbN2gvsdMOlH/ghX6WACYMqIH5nyiVr+dPrYPBlUVoyRbJ2hN9xIHuxpTaEpJXeMFxG2B608+ELf+vyWFvARtIp8Sstbkjwz95e/lIBwjqw8lkE/SNTz60k21qCpxMHFQZbP7782EU6Crt+65KeWSDbWABI4a1r3ZRuNNKQ+PvLkKADBhYEWL4z385kp856hBkVW66TV0vpiCWeGn/kzxI1d6dz9ylVabJTwJySQEtLhyJSRTKwuTngfm6ui0UO14mDYcNedWq2JD82ASDMzvpSjT5po+97YKrMyygH2fvMXVvffe2w7TIAiiEDi6eB0InMTTI1dCt1wBEIlcmW1GaDiWEmGu/pVrcdVWBADGDajAoKoEimzh/8LtXR5dRXhg71J8ulG5nVcWO1i/ox5NKdNYVgk6x+KIWTziP9XVaS26JP3vuS1vj6aOsh+xZVdjRsF65GSat5Zv3WfFVVinvruqMH+4L9lYi7pmFiQAwPa6kDloK2PVNbnYXNOI3mVx7GpKYcuuRvQqi6PYsUIRonBtlVoJKThLW8kn/VWhqoDdFKtLpJgyrWWm8N2TYBx+ZIsz5ctmC3Us9xhSXtD+xtUqypMmXcj82izzB1d6alBGft5/IliL1+/co+PzFlcXXnjhHp2QIIj2w6T8APhpOlVzpf6adgSHLVhEgDHGwHlQo2V+eToWx49POwj/8/wSTB/ZC4Iz2DpyVRwTaEhGf32UxCycOroa/+9D5XAeXjYft4U+1lXnMysUAXzrsAH4x0cbmvWg6ggyOwS2QA41VwCLpHdyHrqZ3f/4zhr//YlOJfOAXY2pjHq5fYJ2yh63ZKgaLnBuqTtAmOf+vR5rdQ9LwRi+d+wwKMMEpq02pN+f0JUAN7VTIUzdlKe9royPFdf7MX2sSu95fiF70vXAGZB0ubJ8kMbJPdpf0KxGhLFx8ADJg8eCRfsO7o98+3fv7NHxOf8L9DwPqVTUH2XTpk24+eabcd111+GNN97Yo4kQBLHn2IL7EaiYpYSUiVYBUeNQQKUQjBWDL7hCx4/pV4GrjhuOMf276ciVFldO5t9lRY7A8Qf19CMsQ3sEffRswf1jGYJf2pwri4gjhjS/crCtfHVMdUHHM870rX3ERlMrrY/70fqd+NsH65F0vRZjXdlq07KN//AbK/Hb+fueAXN72Vzmaqj64brWIxlNrucLK6DlHo6mBZLpORh8BVEuU3NlvpK61Y0pXDdpQ9cNVgdGW+So58K1W/53NyiCDxfRG0w0DcjtPt5XMP1Jdzbjup8rOYuriy++GJdffrn/uLa2FhMnTsT999+Pf/7zn5g2bRr+8Y9/7NFkCILYM2JWUHMVsziqSmKIW8JPEaqC9kBsWZxrYRXUXJXELH9fU4tlcZVaLHYEimMCJdrt3RZBpMwWaqxvHTYAlx4zBKXxoMO8Lbi/StEU0zMGP2XSHn8gD+9ZgjH9uuW0b2sf3Cu27ML9ry3HojXbWy1oD39Y5xK5eumTTVi1tQ7vr9mR01zDNDd6V1gkUGg8Cbyzcitq81h80NH8LUsB/o66pmABQpojvzIVzRQxEiZaFVg3GNsFV4ZMRE2xu3Z0N35XSdfzhVaT7kuoHN/hC6qk50W8sEwdmBF2ah6hnwt4S3XliNixd84ryDg5pwXffPNN3Hffff7jxx9/HKlUCsuWLUN5eTl++MMf4o477sApp5yS03gzZ87MeZJ33313zvsSxP5MzBLwdA0JYwx9uhUhZgeCy0SPjJASXFsxMAaTSUrEBBiDrqcCLB0NszhHSdxCdXmRH90qciw0JF00pTztsaU9s7jA7pDIsATzo2iMBecsiVlZ012FgHOOymK79R3RvImo4aWPVfF+S6vFDJ98UYOjhnX3oxC50pwZaYvsexqqRd5esQ1v74GZaGfw2L9Wo3d5HN+aGDXNDQsqU+ekEnNRvylTW2XuUUvoiJXezrmKYqmUINMF7eqx8Yr0ELj7G3d4zwsK6U1q0PMAzoP71hwfWItkCqNc6rC6sphKZ/2O+tZ3yoGcxdX69esxfPhw//Err7yCs846C+Xl5QBULdbs2bNzPvH777+f0377S/EcQRSCmM39sDYA9O1WhKaUlyEeTBTJ1F+F04JxW8DiDMWxUHQKxoBUYGz/bvh8szJgLLKF/5eyJQI7BwCRZek252BQXlxAUG9VErcgOG8XjSBY7pVULy/J7nFlyKUXoiESmWhFXW3YGfwiX7e9DkBuxejrttfjf19Zhr7d9rwVEdH+bNzZkBG1Ci988LfJwFMLCKfsVF0Vk0DSBQQLTEaNtYLrqdV/JirlKsWl2uZwU0sFSK78vFKe56cSpUkxSgl4DFwv/A3f9YHw03Vf+/Bnc2t/bOVCzuIqHo+jvj74RfD222/jjjvuiDy/a1d2x9tskDkoQRQeJ+TGDihX9Y07G1DX5GbsB+gIlrZG8KNZTNVWlcQs7G5KwRYcrif9lYXV5XGs2LIbjKnUY8rjGFxarNOCwTnCLXIsnT6M2/q8IkgLtlfkyuKFyzfm8zmyeZduyixbT6X8eeE6/2fTlHln8/XVGRTqr+x0Dh3QrU1pSiI3JKRy+AT8gnXzp4BJEzIENVVh01GzDtX0ITTHm5pAx+JIuSpVyMB9oeBJCckAgSDFaOq2UronoetKMKEamZt0faSGEPuHjcIt/9d2Z3ZDzjVXY8aMwe9//3sAqgXOpk2bcOyxx/rPL1++HH369NnjCREE0XZ4yIEdUFGoAZUJv+bKYPYpdiw4ulYqnCq0BEdp3AID81cgGkFkaRElmDqXo4VYLFQ4D8C3bQCCVYlFOnJlcQaGoNi+PYqVbYvntwqwBfJJ75mCZlPDkvM59PclOzr/46vzZ7DvI81/abdIuKBdaruGoBYq6BkoYRo3q/us0fX8+qrGlErVh+utzJcSXqYGS30lU15QuxUqqvc9spC7ee6+wGP/Wr3HY+Qsrm666Sbce++9GDp0KE488UTMmDED1dXBapxnn30WRx11VJsnMn/+fJx33nmYNGkS1q9Xy19///vf0ypEgsgTI2AMnGc2Wjb9Bau7xRHXtVUmmsUZgyMYihzl0O5YHOVFdmAqCiWsOGdIOAKOxVFkCxQ5IiLiRMhMUaUFg7mZVYqmDquqOFbw61Csa8c6k3w+j3w37HaaSz7syymfzmJNK8an6Q28zb0TWC6E0ndmpaEWR66nolEmIpV0PSRdVfie8oJVhMauwQ1tc7Wo8kWbbo8TFnNhp/ZCUKg/eroyOYuradOm4b333sP3v/99zJ49G7/97W8jz48dOxY/+MEP2jSJZ555BieeeCKKiorw/vvvo7FR+d3U1tbitttua9OYBLG/Eo5cGdJTb8YDK2YJJBwBzpSYMvtaOprFmFpR2KssjsoSJ+SVo2q0KoodxCzV07DIFr6flqVXGBq4FlPdEo5+Xoktx+LolrAxpEcxvnZoX1w+dWjBrkNJzCrYr/C2FJubdE2umOtP7Jts2aU+1974fAveXbkNUgJrt9XhlU83+ym9dIGlhJMXiST5dVKAnxpMuR5cz0PS9dCY8vy0oKvrqpKuF0SsjH2DB113pdrn+NGtkF2DDEWuzHc/spbHvb3vS6lM8jIRHTlyJEaOHJn1ue9+97ttnsStt96KBx98EBdccAGefPJJf/uRRx6JW265pc3jEgShaC5yBUBHqBgS2ruK6/YZSkipVX7KMytYdehYanVhRcLBtl1NEJz5hfCASh2GRZ5JA1bo1XuCA9BRscqEgx11SUwaWoWyeG6r+3IhZolOi8A0Jl08sWAN4q11pw4xuLv2BesKoSui4CRdiZ31Sby3ejsAYOKgSr/tTtzmOHyw8noLO6N7UILI4sYWIYheGaHFtOgy9huNKRcuN55y0h/TkxKMcS3YlPgydX5+g2geFHNzBoiQqajB06sD90fBlA95O7S3B0uXLsUxxxyTsb2srAw7duzo+AkRxD5GuN8ZACRiwT/9It2gORGKnJiUoEkLCh5dUVgWtyE4R7Gj04HcWDCo522hzEGPGlaFId1LUByzIDhDt6IgcgWoVGR5wvb7oRVSCykB2DkfAYu/qEFNfQo1yM2gEgB2N7pq5eXe0wmIyIN/rdiKbonsfzzU1Kv7pDHl+itqAeCpheuwuzGFS48ZEo0Y6Zorz5NgzHhfeWBgaEx6kJbxk1PjCKbc4VMIVhN6XiDIfHElAY9LeK4EZxy2MBGzoODeeEXIjHL3/as9Tmt0iR4J1dXV+PzzzzO2v/HGGxgyZEgnzIgg9i3SRUa4yXLCURGecJTF9AzkTNkvCK5sFszvzbIiGxUJGzFbRIrhTc2VLTiKHIEJAytx2hi10MWxmB8xEzqSZZzbVRF94f4aPqBXCRxLRIrqO5I3Pm/dDyudj9bvxLxlW1Hndv6H0z7ZPqcL8OLijVm3Mwa8sWwLHpy3Aiu+3OWn477YUY+d9UlsqlEpxVVbduM3r6/Acr2PaXvjeVLXWHlIGjd3/TilGz8b+wVXSmytbcQ/PvoCuxpTcPX2pOv5KcFk2Hg0XH+lxZmKorXdWHR/0F9d4l/QpZdeiquuugrvvPMOGGP44osv8Mc//hHXXHNNxBWeIIi2kS4yEqH2NQnHAmfKI8tg6n8EZ35kShmBqn3itkDvsjiKbKEd3E2tlf4umE7LBY2gjRu8eV4VtOuVioxpqweGqSN6ROY6tEcxJg/vjq9P6JfTa515wgE4eVS1XuW4d/0W/2h9TWdPAQAwfmA39K8gD61C05IWeW+NShf+/d8bMp7zpFoB+PR761DbkMKzH6h9lBGoikCZmqrAmkGiSddfmQJ3VfDu4af/WIIH5q3AA6997m83YixceyURGJgGdV8y75qr/ZEukRa87rrrsHPnTkybNg0NDQ045phjEIvFcM011+B73/teZ0+PIPZ60iNXxaG0YCIm4HkyEq0Ir+oriQkIziM+VpwBvcvjfsowI3LFuW7FEwicsiIbJjtpCtpNOtESSqAxBhx/UE8M61GC372xUs3PsXDYoMqcq2KLYwJ1jW6khyKRH3Fb4JyJ/XHnS5919lT2WcLipLXb1PUkFqzKdKaXociVqyvek3rxiHrI4HoeBDcpRXWm7XWqhdC7K7cFokxKNKWk72vneMHYHgOYRKT5dHjWraUD97Y/cgpBmyJXO3bswO9+9zvccMMN2LZNveGLFi3yLRTyIZlMYtq0abjwwguxZcsWvPvuu3j77bfx5Zdf4n/+53/aMj2CINJIr7kqDtVXFTsWYpaIOKoXxwJxVRq3tbEog20Fdg0mimUL5tdrGYHGdA0XD0WuyuJWpDk003YOQqcfTWF9zAp6FyokOGcYUJnA8Qf1xDkT+rf4WhkYYjb3U49E/qjej3Tt2pNXPg11BUi71LPfXInlXwam3BKZjYTDqTlXSrg66pRMi0KZqJUxC026UUf4Jtf1U4dqVaE6Lhz18jxtB4FQFKvwl2SfIu/I1Ycffojjjz8e5eXlWLVqFS655BJUVlbi2WefxerVq/H444/nNZ5t21i8eDEYY0gkEpgwYUK+UyIIohXSI1dWKEqlVvpFxVf3kpj/XMIRSHlJvzYKQKTOKm4L9ChV+9vafNQXS5yFBBWPRLjMjCzBUBK3UOQINLkeuiUcbNzZ4M/lo/U1OHV0H3DGMHl4D9iC45lF65ptTqyc40XkfER+mMhHmP4VRVi7vX0c4fdHPv4iSAFv1jVVhpqGFJ7/MJwezFQzyjwU4NI4ravtTSkXghsDUGPxoP7QUNtlZIymlG6vo20ZGlPK+sESTK8qlLB0W5xwax6pg1emZU86LUWz9od/lXlHrmbOnIkZM2Zg2bJliMfj/vaTTz4Zr7/+epsmccEFF+Dhhx9u07EEQbROay1m0n8JlhdpywRt0WBxFakKR6aMaCqyhR/FciyO7iUxv7VNkS54BwKHdzWfYGWg4AwDKxNB7ZVgkSiamb+JljkWx58uOQITBlU0+3riOnL1jQn9UBq3cM7ElqNdRBTjyn/EkKDXYV+qwWo3Ntc2trpP+p8Spu7Jr4XSRqN+AXuofirpqhSfKVAPYzywmlLKqT3lSRXNCh1jjgubkRqvLSI7eUeuFixYgN/85jcZ2/v27YuNG7OvhGiNpqYm/O53v8OcOXMwYcIEFBcXR56/++672zQuQRCKdLHSGkZs8VCkKuxbxRnz66fChfCOxRG3ORqSHhKOUEaevqAKoljhlJ3gyrZhV2MKRY5AY5oXQcwKDE2NaDqgdynOGNsXC1epIuDwonAGpiNXDD1K4/ju5ME4cVQ1Fq7ahuVf7s7rOuyvmMba3z5sILolHGzd1YSjhnXH2ysy636IzkGmfXelhLKPY/C0wOJcR5n0PymWxTrBiC+1mlDC0o3eXVtqoeUhZnGdTuS6YF6d2USnmoteGfaHSFU6eYureDyOmprMFS1Lly5Fjx49shzROosXL8a4ceMAAJ99Fi2gpLw/QXQefhovTZyJkFAKt9txLI6YLdCY8mALjuKQuDKRKUCvXgx58Jg+gAlHIOXKSNPYXmVxvzi9yBYqFaI9fL52aB88+/4XuOjowXhYF8AzJn0RxjkD56oQ/8IjB2Hjzgb8+rXl7XfB9hEEVymhkiILh/Qth+vJiPFsvlicNZvGJVqnIelhV2PUMy1c9yR1U2dXAoJHewcCUAXpUP8Gw++DhI5caSsGzwOaUkqJNaZceJ7lCzUJACywa/AYoG4JI7Do/Q2Tt7g6/fTTccstt+DPf/4zACV+1qxZg+uvvx5nnXVWmyYxd+7cNh1HEET7YkSVSLNy4KG0YNj00BEcPUpiaGhyYesoVriInfs1V9xPTwjtAG/6G6p6LIYbTj4Q//xkEy6cNBA1DSkwpvZrcj3f0HTy8B4Y278CvcrivrgCGIpjlr+60US+BA+K8NuD7x83HL98ZVm7jd+RmOsbt1Ra14P038eWmDSkCv9asTVj+39OHYpfvZrpZUjkxrPvZy4WC4RVWpNwL6itcnWUiTEJBvXvwQ3XXMnAQFSlAZXYAgNSnvq3ZlrjKFHG/X6Gges7C5mKIlKXpc6RKbr2h5hJ3r9p7rzzTnz55Zfo2bMn6uvrMWXKFAwbNgylpaX46U9/2h5zJAiikwgLozCMhd3YQw2aBUdViYMiR8DRBqF+bVVIoKl2OHq7rqUykSZT7zOsVwn+c8pQ9KtM+JGymKXqvoz9A2eqGD88P8aAbkWObxPhmLSiPuMNJx9Y6MsEADh0QLd2Gbcz4Oa9EMyPEjYnrkb2KfN/HtW3LOs+1eVUr1V4ou+HlIHHldRF7qY+KmjU7PnRLHNMUq8MTLrKS8v1VO1VUq8WDMSX2hY2Gw33HwRoBWGYvCNXZWVleOONN/Dqq69i0aJF8DwP48aNw/HHH98e8yMIohMJrw5MJ5v7OYMSSypyxHyTUCAq0ARnSHlBzZU5hylaZ1Ar/ppSHiy9YpEzFfFypdT7Mf9DXwjVPqfJ9TC0R4nvweW60u+TaNqBVJXEcOLBvfDPjzcV9FrZvP2iYh3F6H7lGFiZgMUZPB4YuzJ9vbPRszSGT/TPFlcLDkxqyZBLwLBfRRHG9CvH8i9349ONtXv4SvYTwo2VQ2lCI4hMKtD0JPSkqZcKjvuypgG/+OdSTBpaha+O6YMmXQhvWx7qk0psNaY8HaUKxBZngeeVDFVzZYtU7Y+iKy9xlUqlEI/H8cEHH+DYY4/Fscce217zIgiiC9BczVX4uTCMBfYNjCm/KbNXWKBZnKEpbRzBlTBzQmk8QEXDTGG8LRhcT6U3BDffVS3Xr789DrUNSZTFbZTELHCuxF7M5v7Pvijbw+vSrcjGjjTfIauTWu0Ukm8dNsBPo3pSGUpyzmDJzBWchn7dgqhUcyIqXZzbgkX8ljgDzjtiIJpSHgZ3LyFxlQO7QyVYYVuET77YiV2NKUwcVOnbM0gg60pBAJizZBMaUx5eW/olTjmkGk0pDxIqmtWYdFWq0FKCizH4Hli2UH+8CMYArqJdFzzyLiYMqsAPT4pGh/eHNGA6ef2pZVkWBg4cCNd122s+BEF0QbIJqWyRGsaU03qxbq/TvTjmL0qJpu5CKwfNykS9AtEWHDGb+3VYtmC6MN70ItQRrlAz6ZK4hYpiB92KHf8XuUlLVhbHQo2noRtE79lv+69P6Ie7vj4a3z58AABg/MAK2IJj6gGtL+rpytZbRtzGtb2GLVTKNWbxZu08WCQiybMK1/T753vThmUUyBuh3JWvT1di/kYOCYnPNtXgreVbVFE7JP7fRxsx77MteHnJZtQ1pqLWCbrGykciEsny9OpA0zrH1Fs16R6FyZTarmqxlAgz4875ZBMWrt6OB+etaHXu+4O5b95x7B/96EcRZ3aCIPZ9somR5iIZQjAktMN73I76WUXHjI5jBJAtmO+dZQRSXPtlORZXvRA5gyWCyFVZ3PLrsYIUoC5iN8KKM1+gtVac3ass1uLzRbaAYwl0L4nhimlDcefXRyNmcRw6oHnvLUNVcctjdyaCq2sf8wUW03VrIsPl3xC+ks0JsPT3vntpDNelRTcsznU7pL0/vdpR/GnBOvy/jzbinZXbcM/Ly/D55sDV/YO1O3Df3OVIuZ5fF+VJGS1oByI1WEktmvw6K72KsEnXWjWkXP9nsyLR1F81uUEqmBYOtkFc/fKXv8T8+fPRp08fjBgxAuPGjYt8tYWtW4PVJWvXrsWPf/xjXHvttZg/f36bxiMIovNQNVK64iBUCJ0u0NIFjolCOdrCwbFU/Y4SV0pIWZyhe4njn8cILmMuyhgQ/mwWWoSZCJipz2otcFVZ7ODaE0c0+/yhAyr8+SuT1WjxfkucOrp36zt1EOPSivAtoZz147aAzYNIYczifosjQDXTNiRCq0UtwXHCyF4AgIGVCX+74Ayj+5YDAIb3LIHQixPCmEUK7bigc59jy66myOOoq7ti9dY6/HPxRsx+cxWSbnoBetQI1ESqknp1YFPKQ2PK9UVXUketUq4qcE95EtIzhfPBOIvX78Tj/1oVEW6Gix9dgCfeXbOnL73Lk3dB+xlnnFGwk3/00Uc47bTTsHbtWgwfPhxPPvkkTjrpJOzevRucc9xzzz34y1/+UtBzEgTRvphmzADQUne/9CCHWqGm0o1FjvBd4W3BEbcEGNTjIv0hr9pz6GJ2SzWbNX0KI/MR2vmdBwItvM+Q7sVYsSVqLnpo/24oK4r+ejxtTDX+79/qw6tbwkZ9UpVHCL260cnRB6qsyMlpv45gSI9iLFqzw39scY6yuI3GlAdL22JYXAmrRMzCT88YhY+/2Il+FQksWrMdUgIVxcHrcQTDqL7lGFldispiB//4aCN6l8dhcY6TD+mNA6tL0b9Crf5M/9w1q07DERCiMHy4ficA4Il3VuPbRwyMPBcWQJ7xy/I8NDHmvxdJ/T3FlEFpY0rZoSRdD47gWrAF43z1/jcBqE4Pp4/tGzlfpKfiPkze4uonP/lJwU5+3XXX4ZBDDsEf/vAH/OEPf8BXvvIVnHLKKfjd734HALjyyivxs5/9jMQVQexFhPsWtrSEP327EUa2pWq2jD2DIzg8vVrQsYJ6LotzpIRETAuwlJB+zU54aJtzP8LlF8qHnj99bF+s216HjzfU4BPd7+2YA3pge100KjC4qhhj+pWjNG7rJtNqPkasWTx7bVo64abZuRKzOBpThRcd6Sk4weFHlExK0NYRxCJbRbSG9CiBlMDBfcpVg++QSIo7ArLJRVHcgSUEjjuol59mtAXHgb3L4EkJS2SaitqCwZMM+8C6gC7FR1pYAcAXOxvw1vItwZMSGfe560lsrm1Az7IYEq4AYyqi5XlqgUPKU9EsO9R70KxGTGfpRpWm3B/f0rzFVSFZsGABXn31VYwePRpjx47FQw89hMsvvxxc/4O/8sorccQRR3TmFAmC2EOaS5Wl12xxvVrQ0nU/lrZyiNnc7zfo6NVrgPowTnnqwz9mcaRcqVOA0XiZbal9imyh04PRomvGgD7dinBgdakvrtKjW2o/hqkjesLW0RzBOcqLbEgooegx2axdQZiSeP6/dgtZw9KjxMGXOp2Uzb9MpVfVtbY4h6Mjg5YIUrCq7Qn8+jZDzOJoTHqIW8J/zziPClvpmZWeUbFoIpGOnb/4JJpnWagOCwDe/Dwow2lMeZHUoutJLN6wE8998AUGVSVw+bRhANS/GVXArlKAjUkPMcvzexZmW4Vo2LizYb+swco7u805hxCi2a982LZtG3r3VvUHJSUlKC4uRmVl0Ci0oqICtbW0JJcg9lYYcl+GbWqujPGnqcGJ28L/cI6n1feoD3+uegkK5tdVhVGrFwWKHDVmRcKOiqvQ+Q1CG2gaTJ0XoNOXOmplCsCNRinKQRjYbVgOd+TQqryPaY7imIWKhI3uJQ666QbdANCnW9yvl4tZHImYpdOowXW2tcDiIf+rcC2drVOJCUf4Kw1NejcQyMEigzBKsDIkbOGvwiTal5QnI211Vm3djec++EL/XIddDSlsqmnAfa9+jsXrd+oidlV31ZSSWP5lLd5ZsRXJVHaB9cC85Zj0s1f3m1RgmLz/hHr22Wcjj5PJJN5//3089thjuPnmm/OeQHqRK/USJIh9h7DlQmsIbcVgafFiolhAUMcVTrtZWgCZYnahoy3pacGYjsTELIEiWwTF9v4c1XeeJhKcUHrzrHH9/J+5rt8y5yrRNhHK16t1cVUUy+/X7lnj+mJQVQKvffZlTvtfMGkgHv/XagBAdXkcG3Y2RJ7njOG8IwaiTDfLDo4bBEsLqJSnhSpXXmWOZewYlGCS0lzz6LkTjsDuRheOxeFJ+K775lgAfiRLJDO9rzypIpBDe5TkdY2IwvCnd9dGHt/y/Cf+z59sqMFdXx+DHfVNmPPJJhx/UC/M/PO/AQAPXTA+avFAtK23YDpnn302Dj74YDz11FO4+OKL8xpvxowZiMXU0uSGhgZcdtllKC5WK1EaGxvznR5BEF2IvCJXadEQi3M/esRY0BbHoOo/pL86kPPsNgum0LzIESiOWRmr1NQfdDIydnofQmP5YIrmVYpMzbesyPIbTbcWubrlqwfnXVNUXV4EzjkunDQQj2nR1BxfHVMdSfVlE7ZDe5ZogcgiUbTKYke/X4GQNYI1ZonI6k0Jz29DFP5ILXYsbOdJv3dkzOL+qkPBA7Gd7X2yOIcnACk92HvQJBoAyuIWahpSre9I5EXS9fDom6uwdns9Fq3e4W9ftmlXm2oJ92UKtuj18MMPx8svv5zXMRdeeCF69uyJ8vJylJeX47zzzkOfPn38xz179sQFF1xQqCkSBNHBtFTQnk44MsWZ8ssKR6oEj648TE8DWrr4Or2mykSgSuMWSuPKNiEsCMJ9CsPbwpGrcC9F03PPpLHK4rZ/bGs1Vwf0LkVZ3M7YftKo5u0ZzGrEYb1K8f1jh7U4/ojeZZHofzgD+Z0jB+GscX39FKNKwYb7Qhpxq1N0oRStv2rTFlrEBunBsJms2eaEzEfNwgRbcP046CVpKC+y/fdOpIm+tnDR0YP36HgiOx+t34m12+sBABtrgohoyvUyVn/u7xSkoL2+vh6/+tWv0K9fv9Z3DjF79uxCnJ4giC5KS1YM6YTTeSayItIET6S+h3N4QvrbhK7viVsisp+JXJXELG1Amml86aY5g1tcCYmDepdiy64m9CyLgTOGbbubwJk6t1lBp9rFICc7hoQj0JCWDhvSvRixZsydfvWtQ7H8y11gYH5heUsoMRs8nj6yN554dw0OG1yBXuVxHNC71O8LxzlDn/J4cJ2Eqh1TtW/SjzI5VlBrFbdVJEowgSahluP3r0xgeE+VxotZykLDsTiYC799jhGwMUst23csJdD+c8pQvPjxRlxwxEDYPOhnaDVzPXKlubuuV1kMm2ooI9JW/vhOdn+qlBc1JyXaIK4qKioiv7iklKitrUUikcAf/vCHgk6OIIi9n1zrKDljkVY4pl7HYGWJXHmS+4W0TAsc28r0uQJUys5EUFiaaFMRp/A2IGYL/Nf0A7B4fQ0E5yiJCdQ1uUr46ehLImZFVijGW0gLMihxFbdFpDehBHBI3zL87d9fROfNGSoSjp8ONSnTbBzStxyebmhdZAe/1gdUFeGSyYNRGrdDqU5PR94YDupThu8cNQgDq4p1etNYWZhonor8meiVaczsetKP3JXGLfzktJFYsWW3v6JQpSa576LviGDhgYSEI1SacUTvUgyoSqhm0X6aV83tpIN7YdnmXVj+5e6sr7kl9jDwReSJ6ylTUSIgb3F1zz33RMPOnKNHjx44/PDDUVFRkfM4M2fOzHnfu+++O685EgTRRWC511yFU3PGliHS7DnNAV3oYuvGpPqlHo5yhU9p0lZ+O5y0cSxtguiEUnpC1wgJXffFGRC3hF9nFHYut0UQ9SqL2xjVpwyLtaWD4fSxfdC3WxEcoewgjjmgO/7+78BNO+4IDKhMYM22uoxrYuk0p0kPnnfEADzxzppIGuaGkw/EglXbwZlqVP39Y4fpVZbCv27KhoLB85j/OmIWx9QRPVFV7KAx5SHlen7kythRxG3hG7DagmlzUWX2qcScQK02erVFMLbgDI0pJTo5h98v0pMqwhe3BOqEC8fjiGmbDMtjsFwlqg+sLsO4gRW47R+ftnrvpNNca6aepRS5ag9MKxwiIG9xNWPGjIKc+P333488fu+99+C6LkaMUC0nPvvsMwghMH78+D0+1+23347//u//xlVXXYV7770XgIq43XzzzXjooYewfft2HH744bj//vtx8MEH7/H5CIJQ5FVzxYJIlUlbhQWTlZYW5Ey1akm5KgKkarJMAXwwbviD1tQRhcc1ab1uCQeThlSiJG6jxLHQkHLBmPFkYog7wk89GiFoIjqmVqnIESjN4mNVErN8OwLGgNH9ukXElcU5vjGhH+586bPItTMRMiml//oOqi7D9ScdiEfeXOXXvdiWEYGqfUyRY6HI5r6lRBCJYn7NmBFKggXF+37KUO+vBJkRZ1pY6e3FjgUwFeGzuLo+Fue+6ShnQF2TEqkWV1ErW6cFY5Zy2rcbVRQspq02pASaUp7//gjO0adbHF/siK54bPVe4gzHHdgzwwKgyCmsteMph/TGPz7aWNAx90ZcTyLpkrgKk3di+8UXX8Qbb7zhP77//vsxduxYnHvuudi+fXvO48ydO9f/Ou200zB16lSsW7cOixYtwqJFi7B27VpMmzYNp556ar5TjLBgwQI89NBDGD16dGT7L37xC9x999247777sGDBAvTu3RsnnHAC+WoRRAGJJttaJiyC/Nqr0G+o9HojzoASx/L3ZVrgtFTlVawbSocDGzEdRWEMOH5kb3xldLUvREyvO4sr/yUjNowNREK36eFMndWIhHTMCkVLF+n3KotHnjdmm2FMk2nB1Pkdv0ciz9jXCB5j/mkLU9zP9LHB6zE1TeGidUswf26msN2kIX1RxoKid1PgHtN1Z5bgSOi0q18IL4wY5eAciPtO7cbeIWi0HbeV2DKNus15HMHQp1tRs+9nczAAEwdX4pLJ0cL29PUG4d6KXzu0T6vjCsYwfmCQoTliSOH8x/ZmHn5jJf73lWWdPY0uRd7i6tprr0VNjQp5f/TRR5g5cyZOOeUUrFixIq9UX5i77roLt99+eyStWFFRgVtvvRV33XVXm8YEgF27duHb3/42fvvb30bGllLi3nvvxY033ogzzzwTo0aNwmOPPYa6ujo88cQTbT4fQRBRjODJlyByESpgTytyNjVZYTFjfmquNqlHaczs4G+LWcEquGJHoCLhRMSVERNFjog4mCvDS8tPu1nGGyvLqS3O/VV4phg+/fWKtDkzqDoxk9qLO8Kv20p/fSaqJXRakDEWtP3RtU7mtTAGxLWrPTfRMW0Uagvmv2dG2BrfscBCIfAYUxEp7hexG4EmGINt6VWDof2M2PIjWVqoGkFlxJ+t5+ZYvNli/3TC18+IwarimL9tQGUict1G9yvHiQf3xiWTB+M/Jg/GwKpitMYPpg/HUUOrUBKzcMSQSvJlJJol7xjpypUrMXLkSADAM888g9NOOw233XYbFi1ahFNOOaVNk6ipqcGmTZsyUnKbN2/eo0jSFVdcgVNPPRXHH388br311shr2LhxI6ZPn+5vi8VimDJlCt566y1ceumlWcdrbGyMeG8ZkZlMJpFMJts8T2Lfxtwb++M9kkqmVMogmd+HkPRcJJNJuCkXSabTDXqbwXNTSCYZXDflb0+lUkhxiSTLXlzrMIlkMokRPYMPUg7llcWkB0cAHB6k50J6KUjPBYMEpAeHq3kJWEgmk/BSKXBIuCkGFxxMevA8D7FQeMS0mjm0f5kqzPZc1YfNc0MvVsLzXEBmztnmHiwmkZISxTaDlB6k56n9Q4YSnutCShdSAhZjet4cTEJHviRSSU+d3/MgmASDh1RKvUbPSwGehICnr7sHL6Wuq/RS8DwgmZSQbgpMempceIAEXD0Ghxof0oXrpsCE0PNg8NwUuPRU2xyp3jsOF4J5YFJfbzBAj8Okp3r+SA+HD67Am8u3ZlybdIb0SGDZ5t36knrwpIwI8tNH98aitTsj151BIqGjaKZ2ryUsBjgxgf86fih2N3ngWd4zggDaIK4cx0FdnSq6fPnll30fqsrKSl9s5MvXvvY1fOc738Fdd93l9xJ8++23ce211+LMM89s05hPPvkkFi1ahAULFmQ8t3GjypH36tUrsr1Xr15YvXp1s2PefvvtWV3o586di0Qi0aZ5EvsPc+bM6ewpdDiNLuBJoCjP3zSuFgUpDzBBniYXCPsUNrhAXAA1TUCZ7k6zO6n2sVsJdiRSwKn9GaoTEh8tWgCbA0kPqHcZ1tgSq+Nq/NoksG43Q5kN7CyR+HQnQ7kDJFdJ7Eqq6JLF1VfKU2MM8BhKLI6BpRLDy+pRVg0s/XAhVtYyvLJzCSSAz2sYAPVidu/ejQ///W/sTsHfBgCjuqXw1uuvYdlOBk8COxISn+1k2BwDdjQB9Q0cJkz21ptv4LOdDDZX17ouBRRb6jrUp4C4pd6LhKXmCKifNyUktjUCZTZ03zjg8yLA9dTrL7bVca5UYzW5wJZGwGaAB6V/VhUB25vUfqtjwJcNarxiS82TMaDcUe+T1MeUOWqsHU1Ag8uweakEg5q3K4G6FMO63cAmG6h3gQndgYVbWlqJKdFUVwuTjPl0ySeQAGIc+NogoCEFrFi+DNtqmb/Pzp07sGTJdjS68N//8PXPxmefLgGg9m/U16e1Y4j9k7zF1dFHH42ZM2fiqKOOwrvvvounnnoKgCpAz9fnyvDggw/immuuwXnnnef/BWpZFi6++GLccccdeY+3du1aXHXVVXjppZcQj8eb3S89pKuakTb/F/YNN9wQSX3W1NSgf//+mDZtGqqqKPdOZCeZTGLOnDk44YQTYNuZBpL7MnVNKXhSFXS3BdeTfmqwMeVF3NXrm1wUOQJbdzWiqkSlf3bUJVHkiAwX9nQaki6OaUhhd1MKtQ0plMYtbN+dxK7GFKpKHFSXx7G70cWWXY1YsrEWPUpimDCwAqWfb0HvsjgmDqrAtt1Nfnosbgk0pjw0pFwcsLUO3QdtV3VFgqNfRRG6FdkoWr0dpx4xAK4nsWDVdjz06SIAQElJMcaOHYpdjSn8ddUSf45nHHkwTh7VG91WbIPrSRzQqwT28q3o160IG3Y24INda7Bzi/pD95jJkxFbtR1FNkdZ3Ma2uiZUJBwUOwI76pMoiVloSLoojlloSnlK8BTZGNy9GBt3Nih3dqYcuPtXJOB6ErsbUygrstGQdJHyVBSoKeVizbZ6xG0B11MqrX9FApt3NaIx6aJ3WRyrt9Whe0kM3YpsbN7VCIszVCYcbKtrguupHnRVxQ7qkx421TSgPuliSPdiMAC1jSm4HrBtdxM+/3IXyuI2ahtScNdux8ItGzLeR0P3khgqK4qwepeKTB0y6mBIqWrs4pbA9vokdjWkULd6O5bs2AIAqOhWgdGjqlFTn0Lc5mhMefjH2s/9MS8+aiAefjP4Y/uc8X1xcN8yeJ6EYwnUJ11UFTv44+cftnwTE/slef/Gu++++3D55ZfjL3/5Cx544AH07dsXAPDCCy/gpJNOatMkEokEfv3rX+OOO+7A8uXLIaXEsGHD/DY4+fLee+9h8+bNkZWGruvi9ddfx3333YelS5cCUBGs6upqf5/NmzdnRLPCxGIxv1VPGNu297sPTSJ/9sf7xNE+VLbdNnFlhf7gYdyLmEt6jMO2BOIx6V9XxwYcW7TaPkUygUaPocljKI4LxGyBeAxISoZuxXHEHAdJmULM8WBbFsqLY4jHbBTHHZQUObBtG44tIXS9UswRkNyFxzhKimJqDtoHy7EtxBwblmWpcV0PMSe4DzjnsG0LRWDoX1HkO2DbloV4zEFxXNkkFMUcxGwLcceGZSXxjQn98eSCtTh7fD84jo2YbSFmC5QUOahLShQ5NkoTNpo8oDhuw7Y8tfKPu6qGLGbDsW3EHBcxR7nMW54H27bBPQlHMti2DckEhOepujEuEHNSiNnC99VS5/bAuEA85qAollJzjVkoSkplz+DYSLjBkv2Y40AyF8VxCcZTcGzlw9Xkqful2AWK9GtqdCUGVLb8WcAYAw+7zVuWmpvNUeRY2J2UEEJChFsacYaYbcNKStiWgIcgxdezNIYhPUv9x327FWFUv26I2QIpVyJuc7hgSMT2r3/PRO7k/RtvwIABeP755zO233PPPXmN8+GHH2LUqFGRfxDFxcUZq/oMH3/8MUaMGAHLan3Kxx13HD766KPItu985zs48MAD8cMf/hBDhgxB7969MWfOHBx66KEAgKamJsybNw8///nP83odBEE0j1q9tyfHh2wU0lbImUL2SFQsR1+twIlcF2tztcrQFG2bomxjbGpWASYc4dfxGJuJYLWiGsMWDAnHgqujPaYXoZm+KZQPz8Wc47gDe+DRf63xxzPtZySkXp1o+Y2oq7sV4fvHDcfAqmJ/pWLM5qhIOCqqpn24Eo7ltwRijMGSXL8O5jfHNo74jv79any1zHX3JPPnY1YgRk1XGRxw//nwtTANm9U4ADdF71ytEkx53HffV7VvulWOLRCzOXijMlP9zylD8MC8FS2+p/5tYDy5uBrHTmuVBBjfs2D+ggMXHzUIr3y6Gd+Y2D/S1scsWFAO867+WcKxOCYP7475y7a0ftMR+xV5i6tFixbBtm0ccsghAIC//e1vmD17NkaOHIlZs2bBcZycxjn00EOxceNG9OjRI6f9J02ahA8++ABDhgxpdd/S0lKMGjUqsq24uBhVVVX+9quvvhq33XYbhg8fjuHDh+O2225DIpHAueeem9N8CILIjVx9rlojPWXv9xQU0Q/BXM5m+hQyLcbMaj7fx4oFAoAbOwGmxI1Z6WdctXxxpc+sVsMxFdnhgV+XOSdniDi5G8d3wTlE2MhUf7ib89lC2R6Uxm1lFmoJNKZcX5gUOQJFtkBJ3PJ7IzoWR1mR7V8bizNISJToiAvjiLzOcD/FqBDRj3nIPT/0vBFovkmrPsaITCNOXM+N+GbFbYGGpOevUDSCLjBo1cXmKY6qkliGr5QtGJKuxKDuxRFxJfSqTn/1oW+fEby+kdVlfmsfru+BA6vLcGB1mW5OLdG7LI6NNQ0YN6DCX+kouNTeYGrcK6cNQ/cSB+u212PioEp0L4nhluc/yeEuJPZl8hZXl156Ka6//noccsghWLFiBb75zW/ia1/7Gp5++mnU1dX5Jp2tIaXETTfdlHMheFNTU75TbZHrrrsO9fX1uPzyy30T0ZdeegmlpaWtH0wQRE4wpgqY24P0SBYAPzrTGqZvnvmQNy1yBDcWD/DNQs2HPGOq+bMvjFgQrVJjRsUK80KGo5yFIl4qAmawdLRHSoYiKyy6TASG68J5hiKHoySuUl4xWxlwChY4yFtagHGm7AxUj0QliOqbgOKYpUWNajVjDETNGOFLF4jGQEiqCJcSKpwz/73lnEEgcNVX7YCgI1xBFKsppU1NoSNXloAlUpGonrlmqm+j8COJnDGMG1ChmgdvU6nTm04dibdXbMX4gRV4OWQYany4zFiWME7zwQs8uE+pHpvr+0H6RqxKRAHfP24YVm/djcE9SvzoV8rTIlJH6kriNiYP76Gc6htTqG8KrQQFMLAygdVpzvvEvk/e4uqzzz7D2LFjAQBPP/00jjnmGDzxxBN488038c1vfjNncXXMMcf4tU+5MGnSJBQV5W8mZ3jttdcijxljmDVrFmbNmtXmMQmCaJ1CRa5ywXyo57SvicL43lWB6DJu8YIzFMcEHN2vsDhmIW41kxbUX+YDmrOgpU/YBNSk8AwiJLx6lsUwuNTDmKF9dV8+7RXFGYq1y3vMUmIoJjgauQfOlTN83Ba+B5WJXClzUbV/UngojVvaEV0AKTdwwhdRcWWiecF1DaKCthVE45hJq+lxmP+a1Xb12oNrZSJEZp6Aak8ktFAz57V4YCoajiRKLxqZ7FtRhGkH9kRjyNUdgO+cb8Sy8eEa3a8cf9c9HC2hit3D742JUFq6jU95kYMDq4UvBs11VSlHoV3u1fsXt9WihkYWFVczjhqEm/+PIln7G3mLKyklPL1K5OWXX8ZXvvIVAED//v2xZUvueed0sUMQxL4HQ9tMRNt+vtx7GYbbvFicIWYJP4VlPkiDlJL60I1ZKnJkjg9/Zzpi4zu7a1Hlix0riFw5FkdFwsb2uiQmD+/hiwmLM4yulDjz0D6oSyp7ApO6MhEcS6gUoNluIkBxm0MC/n4x3f7G4Wq743K/zilmcSRdz4/QGaGT3ZAVYDKICBpndyOmzHHGgNQYmiqhK6M9H01dla53UqlTdbwHVSDPuKqBS+h2Q6rvYNIXZP0rE1ijI1eObrWT8mQkLehYpo+hDPWClJg0pArXTh+B4rjlH2vc6YHARNURqn4t6XrwpBGpKq3oyUA0R01QuU5Fchw2qALvrtqOCyYNRLFDVg37I3mLqwkTJuDWW2/F8ccfj3nz5uGBBx4AoIw5W1ppRxDE/keuNVAFPV+O6spEakykqcgRSLqeLwxMiitmCb8nYEnMUlEfwE+TsfB4CAReuI+fCAkYQAmUHxx/AOpTLo4aWoXGlIdiR/hRn5glYFnBB33cUalBI/RMy5mYFbTfUX0WpS+6jCu7SXmaPoKmx5+VCrf4UZGj5qKMGfVV3ES6grBdRGyGrgWg/K3UNQkiWAwMLgvqvIIFBiYdq9oNmRY5YAw2Z5g0pEpZYwyq9CN5jSkPxx7YC68v24Lq8jhiWjglXU8dr9O7jsUxcXAltu5q9BtI25zryKGn3lumomkxi6NRi6mYzQEJ2JyBWaYAXzvuayEWtznqmpTIvGDSIMw4ahBSHuC6ZDS6P5K3uLr33nvx7W9/G8899xxuvPFGDBs2DADwl7/8BUceeWTBJ0gQxN6LESAdd77cz2Wiag43Pft0ek4PEdTqKL8qhmghup8q81NpOpKjBUHSVVEbx18xyH0xIjhDr/I4+lckYAm1is7S9T8cai7Ftu2n4WJC+ILNErpYm6kaLHN947ZAE/P8vn6moNukOW3hwTSb5gyR1ZAmchS+es29bUasBTVrQaTPvLbwNQGg3dDNf6E+kF50QYLfm1BfNwlle2AJBpEKaqeOHt4DPUpjOkIlYAsXRw2rwkPnj0e3hO37ckkdZbI5ByzdoigU7TLRJlswSAQF8KZ43dTame+CmQiWiUbqlY16nLit/K9itkBlsY0vaxvhMh6+fDhqWBWGdC/B799enfO9Sux95C2uRo8enWFzAAB33HEHhKDwJ0EQAW3tLdj28+W3L2fMLxC3/d566nnzQa/6+2U2ZDbWDeFIGYP6UI47qv7GpKTMUn+DYKqoPZzKUyIu6ONnRIzpz8dYsJLRjBnnKjoFFgg/k6KzeLR+THlcAUJqcRQqtudMLTwwDaEZY5C6Wl29vmBVgsU5XBmYu6pzhiNXoVSpPo/rKRf1cITLzDVc62UaUHOuehO6XpDm5Fq0+osMdDq0wXZhNylhM7JPGXbWJ9GU8vyaMTuU9jOWFzFLgLmu/5zFOaT0In0Nja2E4Dpyad47/X7FbO5HNS1fpHE/QmbsJMrj0Y/ZEw/ujQ076lu+OYm9nrwbNwPAjh078Lvf/Q433HADtm3bBgD45JNPsHnz5laOJAhif8JEKTrsfHmcyqSgYpbwxYylI1RA4PWU0IXk6WNnS3kyppotGwFkVu2Z+hx/P11TZCJQkZodBj9ywhj8CBQQrvVRURMzd0Cd1zRZTjiWX0hv0nFmPiYlZ+Zu6olyfZ+skABU14lF0qMsJJhCWcOI9YV/HYBQRCuUFmRmxZ5uCM2NL1ZQa+ZYJh0nMhpEF8cs2FZgl2BW+pnIV9zm/vgWV8fGTY2XXmVpCfXe2dqB38wlZgnffd9vUi2ConkjsMxcHEvguhNHAFALGVRz7+i1/u4xzVsMTR9J5TZ7I3lHrj788EMcd9xx6NatG1atWoVLLrkElZWVePbZZ7F69Wo8/vjj7TFPgiD2QkwkpKPIJy3IWWA8acSHERpAkO6K60hENvGR/vpMNMxf1ccDU810bytHKJsBz/NgCxXNKolZsHlgKspYYH0ABDYRgeeSqrUyaU1TrxS3VfSFh46T5jVzlS4zLvZGuGUKxebrr4xIM0eZCJj5Of19YGmCLnwOVdCui9p1RIxzBpsBQFAwHrOFb4thCw5LqHopRz9nUnZmYYLpY2hEpSnwN8aqKU9qk1GuU4CqeL7IFki6Ul93D54+FkklLKUEgoUO4cJ2HvHmMisOLcEwtGcJrj95BCoSMQjOUJrWDqqquHl/yKkjeuKlTzY1+zzRNck7cjVz5kx85zvfwbJlyyJ9+04++WS8/vrrBZ0cQRBEPuSXFgw+7lkoehSOwJjVf1YWkZjtXCotGERVBFfF0Yyp6IfBpJ1MJMfWRdcq+gS/ABuAv7oOCISLxbmOqqjidgC+2DICI5xyC9dWGTFlIk9h49CcrlvoZxMZC28Lp/kCoRr9Hh4rM7UaFS+m9skXWVZQJ2Vc6E3ReiDETFF/ENEKe16ZCJM5nnMlfs3qSxMtM8eZfYNUIQ8inTy0QjMSuTLjqPn2ryhGeZENizN0L43h7HH9cMqo3rhk8hC/N2Y2YjpNSexd5B25WrBgAX7zm99kbO/bty82btyY5QiCIIiOIZ/PIM6C4mwgKMoO1xIZYZItipMtSmbqhcqLbDSmXCV4dL2OsWJQ59YRLQQf5ubDWQkv+GnEcMrNCDLjt2TEGZPwLQ0AtbqNsaA+yhxjirJdJv2/rIM6q+avVUT8ZLkm4Z/D3l/R65Vt3CC9GowbRLpsLY6KHFUoblZBJrQHlrl2ppUP149V30MZ+H3pqJ7NOVKeWkFoBJCybIhaXkgJCMHg6F6IRiiZ12fEsb9ggAd1bTE7iFo6Wvg5giMpPFiCIekyxBjHYUMqUexYqGlIwhYMPzltJOqaXNzxz6j/o2Nx3HL6wZjzySbM+4za7Owt5C2u4vE4ampqMrYvXbo051Y2BEEQ7UE+9V2m/UoYf9m/2QdoNr7fkoAoi1vYuiuIvngyahwKhFagcfWhb8xMbfPBLYJ0nTmXScnFdWRGymDVo8VVBAaAn1JkTE2fM+bbIQR1UG0Ph4QFka5T9/HTjOlRKv+Y9OhVlnSridQhMPR0dCowZgVpQd+nTAsoCfi9HJMpD55kfkTLRK08qYrlzSKFmKUsOMy94FjK+T7sFm9nie4FbYACrzDpR9KEaurtqebejsXRlNKpQkstDki50o+cWZyjf0UCMZvjV986FOu212Hb7iaUxCxYnKFnaRxnj++PSUO742cvfNqm94zoWPJOC55++um45ZZbkEwmAah/KGvWrMH111+Ps846q+ATJAiCyJV80yfpLXTSI1cAIiaYYbJHYoL0nSW4X+eTHrkCgJK45RfNW0LVHqkIFnwDUvWagihRes/DqJFnMFfzoe8beiIacUovLA/PPRcynOlZ2nPNHJdVkJpIVXjMUBTLFJebKJSf0vOFjekPaKJXeoUlD2qijEBiTEekBPdTeSYdrIrc9TlFIMbCAiu8wtJvGRRyb7d0DZhtKU8um6tVjf7qTl03Fq7JMgX3xsqhZ2kMB/Yuw7QRPTGwqjhiHzGiVyl+c974nN8novPIW1zdeeed+PLLL9GzZ0/U19djypQpGDZsGEpLS/HTn/60PeZIEASRE3u6MtF8kIbHa86nK3uq0IyjPmSL9ao984EdHKtW9xmz0rDjt2C64bNfpxSMbyJTJoKVXvPkR3x4sILPFy4IxOeeOuebQ/O93pmF7kF/x8i4ofmZ4v6glioQRsYR3qThTF9AznRLHx61rjDjGT8rk+4ztVGWTi/aoVqrsFA1otfUr5n31u/PyJWXlqkTM4sPTGrSCCvVdieoHUu3cYjZ4deq5mGEZXnCbuvbRnQgeacFy8rK8MYbb+DVV1/FokWL4Hkexo0bh+OPP7495kcQBNFhZKz+Q/O1SNmiZOZ4VSDNkYiJkBAKWTGAwRJAUwq6rx+D6SNo86jICwsYMwZjSItsSYQbUBtxwvRzZpzwSsi2pgXTfa/SbRyYOUHWY3M7hy8CtSgNiwxTwG7piGDYzV0dy4Ionm6lY8SUcY9PeUEkyuIMrmcihdxPr3qeHktHsZgMzT/UtkdC+mlcT5qiepOO5DryFETI1OpFhIrfhW/vELMEPClVDZh+rcpWI1j5GLc5Du1fjvfX7szjXSM6mrzEVSqVQjwexwcffIBjjz0Wxx57bHvNiyAIotNprjgbaDlqYywSYhb3BVp6epEhKL420RFbMBSJIPKUOZ9g/HC7GSOUgv6F0dqq9JH2LL6nx2hJQMmsT2UlUuPmiz9lYqq8r4J0rR/lsZgf3WM6nao6GcqIqLRYEBE0qUYjhkyRu6mxEsIYmAbF/zZUvRxjDALqPZSQcL2QE70MolmSqx6GQerW1GPxUApQiSvjoeVHqXQky/U8PxJniuNNzZx5LdXlcRJXXZy8xJVlWRg4cCBc1219Z4IgiL2ctkZ4TBSKQYsAGRSom3GlVFGZlBsUeqsPYvhRmYxxTWorFNniISEVTiXaPFNoBeffM3nV2vHNC9Icx/bd4dWXESaOCJpVG2Flonyc6R6GoXOZ1KitWwypfZQMs7lqr2PrlXyCBe+ROc7jDMzT15grHy6OoA+j0ZEm+igEYHlRM9So/UOQikw4nhbX2nrC0mlecDgW9MIF4QtmRwateNLrAomuR941Vz/60Y8izuwEQRD7Mm35HFPpLB4RPeleWUwXY6dHbmzefMTML1hngaCIFIKn7RfelpG6KxDZxspaj8ayxdDSIleh7+ExwnVVQq+sDNc9GQNRv2DfHGeuFw/28RcFaJEWrskK11H5j3nw/ln+trR99X5+TZYpjNfvr6mvMoXs5vWYr6AZt7afMFE6ERVkRmBm810juhZ511z98pe/xOeff44+ffpg4MCBKC4ujjy/aNGigk2OIAiiMzEfoPnCwPwVD4SAgwAALJlJREFUbGqcwLdKPa8wqaNAhAEOD4rQM+ajP1SD2iv12ESpzPkswYPegGjOp6vjyWrGmmU/E7wSjMFj0q9dMqlBI3pMzVW4P2Ig0IIUI2cM4DJU4K9TfAwApC+aGNc9FnUUzOIMKS+IggGA5+8fzN9flam9tUzE0wqlGn07CR6kAAXnsIUaP6Zb7EhIeF7gk2WsIsxbaFsM00b0wLMfbPCv12VThuDBeSsAANedOAL/WLwBuxpSWLW1bg/fMaKt5C2uTj/99D0OKRMEQewNZEup5Xpcutu7aGYcE1Ex+7UUlPCL3NNyDi0ZgbYkXgpBIT8Oss8/sEQwJqHGXsHEwsKiLTyGeZ3pkUCVrpWQkgHcRJjU9fcg/ZovwZnveSU4g/R0WjA0vrJiCM5jIl7mMRBaoRhqi2S5OgKl6/KUNxnAwJFyZcgNngHgfqG78cQ6vIeHd75UN0LYr21U33KM6d8NtQ1JXPYHCnZ0FnmLq1mzZrXDNAiCILoezbmz53Qcb763YmQFYDMGldnHVd+b9d5KSzFK7c6efb8CqasW5pD5XG7b0p/3vao4R4oHK/UAhNJzzTvDq9V/mQILTIJJBsZlxA6C6XGllL4wYzCiDHC96P5cizLARLHUE+Y4U3elIlQq5ObXjukomDFBDZuXipBXlyslPC8olo9bwfsXFpdh/y6i88j56tfV1eGKK65A37590bNnT5x77rnYsoWs+AmC2Hdpa1CGIbtoyuW4lsRGNu+rFsdrozhsL5qrxcq2LXwtwiv4/GJ2I15C0UUWGSOoR8tWw2aiToFwCmq9/G2h4wFd2I5Mo9TwNrXCMXjevAemTsy0xLH83olB/ZhJNxqzUlsE7vO+7xZTQm1giRJXZh+DY+q4BEdJLLf4yelj+2RsG9G7NKdjiezk/K//Jz/5CR599FGceuqp+OY3v4k5c+bgP//zP9tzbgRBEJ1KW3VJq9EYNC/czId6y8fvuWAqlOhqL/HmpzoRiCDjYeVHq/y6qizzaubn8P4sNFb6vixNSAViLS0CFhJ2Eef60LgmJRh21w+iUyxwftevyaSKjW2DKZS3tZO/LRh6xoH/PWc0HjhvHOxQzjmmTUjjFsePvnKQv726PO7/PKpvGbqXOP7jQVWJjOt37fQD8KNTD8rYTuRGzmnBv/71r3j44YfxzW9+EwBw3nnn4aijjoLruhBCtHI0QRDE3kdbhUMuxzWXIjPRkXyP3RdoLorFIbXgQCRNB1/YtBzRS69lM0lRM0Zz1gbhqFj4WJFFYJkaNjM/GTIdFSZNHBJcEUsFicgxptm3WZkovUDcmX6IggEDKhKQnGP99gZ/LqYJuGNxHNS7LDLvb07sj8Vf7MRVxw3HB2t34P65yzGmXzkGVkUXpt30lYNgCY7eIUFG5EfO4mrt2rWYPHmy//iwww6DZVn44osv0L9//3aZHEEQxL5ISyKg5efV9/1tKX64UDxca+VJqQVHtH4sXFPGGAOTMuT6rp5jobHBW7jmZgw9TiCC1AEy5MkVXiSQHvUyvQgj0Syu6qy80IEmPSi1/xVnDB5XhfRhmwih3ecZj9p8mPShHbICAYA+FUWYdmBPnDamDxyL48ih3dGvIoG+5UUojgv89ykHIeEIDKhM+OcJdxUg8iNnceW6LhzHiWyzLAupVKrgkyIIgtiXaT3t19z24IN5f8GIE84DoRJEr4wYzR7xau6xKfYH4Fs47NEcWbB4IEjrykg0S+pViIIDEhLcRKP0qxSMwdXu8Z4Mitu5Dq+lCzPBtNms7olosEPNrcO3ielNaGqyGIC+3YpQ5KgWTaP6qCiXSVEyAE0WR3mRjZ31yT27QPshOYsrKSVmzJiBWCzmb2toaMBll10W8br661//WtgZEgRB7Gc03yzafN+PxJWpdQo9Nk2bfSf3HMYxVgvRsbOLs3BUKirKosKs1bmHzi3DqUsZjcABUkfi4G+TLNS/UK9aDFs7cKZSgJIps1GDiYg5Fo9cF86AhC18s1IGhpQn4QhlbeFY2upBqFWZpi3TPeeMwc1//wSrt5FnVj7kLK4uvPDCjG3nnXdeQSdDEARBtJyi2p+IRpiCaJWJyGQL4GWPYrW8H0NUUEX2kTLjukfrrQKBli66gmL3YJxwnZepsWLSCK0gUuevOmTBWH5aWDBYTEWjUmAYP6gSo/uVY2Blwi+eT08dc6b6XcZtLcQswPHMSkS1zZWBoaqAEmjCY7jhlAPJMytPchZXs2fPbs95EARBEJrmIlNtcYvf2zHXwjdQbeES5BrR4wyqIXPOc8hxxxbPGRVhYeHF0mvGoHsWaqPUcEqQAb5lgyU4OFSa775vjYusqLREEAkz541ZAo4QKi3JJFJCR644gwQD94JWQYAxwvVQ5ORtibnfQ1eMIAhiL2E/1FY+JhXIIHMSUbkLJ5YZrWrDONmO94UUQqsBYb4YwMLnTashMzVc5is0pqm5CvofMr9noYk8WZwj5Xn++D1LY8rdngOccXAmYQupBBoDOFNtdoxFhCdVZMz8TOQHiSuCIIi9hP2p1iqdcOSn0LQ2ZHO1WW0d34hESBYVTmZfqX5gMtgWrjsDoAWR+sHiDNKIJC2ubKGiUfecMwYvLt6IGUcO8lcSmjGFaTYt1MpLKYMm1ilXqvorxpByPRD5QeKKIAiC2Gtoy0LJ5orQC63TWl0FGopehVvmpJvCGoFlivCZjL5uE/1SFhUqrSf0uGEne1tyHDO8ByYN6Y6k62V4awmu7BosweB5DC6XfqseiaDZuC04vjGhH/68cF0hLtN+AYkrgiAIossTTosh7ee2iKT2jgHmYrfBwg8yjocyF0Xm6ws71duWEkBmwaBpEu3bOXgMrnRhQbm7GwNU10OkpQ7j8AvhBWMAB5JaqFmC4bwjBmLqiB54asE6jO3fDY7Fccc/l7b9Au3jkEMYQRAE0eXJV0BlS8Vl+7kjSLdzSN+ef12X+m5Sg6bI3UStTE2X8sEKBJelo1x+3RZnft9GU69laWsGzpVwM8fZgqNXWRyXTRmKiYMqcXCfMtz59dF7dF32ZXKKXP3973/PecCvfvWrbZ4MQRAEQXQ0nVHL5kemGIMMb0N4RaFu+dOMWarvfcWUy7txcVcWDqqmSzDAZUHzaIszuFI1/7G0cLIEh+tKeHoVImMM0JEtBoYm4cH1AEcIAB5SrgfOOCqLo8biREBO4uqMM86IPG5pdYXruoWZGUEQBEF0MoXSXVFj0ujYbXGI17XsfhsgZTaKjLEZVK9C6cE3JQUAF1LVaukUo8vgN4y2OIPLVEqRM2i3d4mUJ+FJBs44kq5ELOvMCCDHtKDnef7XSy+9hLFjx+KFF17Ajh07sHPnTvzjH//AuHHj8OKLL7b3fAmCIIj9kEJHl/ZkuILPpYUxW1qpaBpShz3AzF5+BEtHqIQI0oDmOSv0mLGg9Q3XUS7bP0YVuYdb6zhWplEpEZB3QfvVV1+NBx98EEcffbS/7cQTT0QikcB3v/tdLFmypKATJAiCIIh9ibBQynR1D9VntXJ82KJBsrTn9P+Mf5bKQkq/tY4Ag6fFFKBSgK6nPLk4h450MX91oyW4H2ETXAIpD66gsu3myFtcLV++HOXl5Rnby8vLsWrVqkLMiSAIgiD2CXIyPG1ml3BqL/PJLP5Y6efVKUi/zQ6C5teMAVwGNVoAwPyCeB0RY4Cnm0k7QvUb9CSD6wGw+B43vN6XyVt2Tpw4EVdffTU2bNjgb9u4cSP+67/+C4cddlhBJ0cQBEEQrbG3m6u2Zf4mleiLJQRf0efDRe7mOfWfCAkrf6UhCzy1OAu5vodShiY1yClw1Sx5X5pHHnkEmzdvxsCBAzFs2DAMGzYMAwYMwIYNG/Dwww+3xxwJgiAIYp8gHyHV0r5GAIVXGGbb39g1cD8iFU4pZol4ISq2TCsdY8lgoliW/k5kJ++04LBhw/Dhhx9izpw5+PTTTyGlxMiRI3H88cfv9X89EARBEERHskdpwyw/h1cgMr3B2DpE+hUiVAAffmysGPQKRADKYJQzJBH4aVmCwfI4fnXuobjyifcBAMUxgd2N5BgAtNGhnTGG6dOnY/r06YWeD0EQBEEQIdqUNmSBxUM4WgVEVxSGPbUEQs8z3f8QodWExqpBcHgSsLjEyOoy2IIh6aqfF6za3ubXuS/RJnH1yiuv4JVXXsHmzZvhedGGjo888khBJkYQBEEQ7UluUaOOy8gU8lxMu5QagWVMS81zDMp4FEiLgJnaLBlsF9qagXNASFN7pXsSSoaHzh+PFxZvxAkje2HBqvcK9hr2ZvJOmN58882YPn06XnnlFWzZsgXbt2+PfBEEQRBEZ7M/lKn4KbxmHoe3A0HkiYX29ZtDI/huyIh4aZFlCuHN94FVxfjOUYNRVRLD3d8Y0z4vdi8j78jVgw8+iEcffRTnn39+e8yHIAiCIIgCka0uK+t+ochWOmFRJkSo0F2nBwEVBXM9juE9Swsz8b2cvCNXTU1NOPLII9tjLgXjgQcewOjRo1FWVoaysjJMmjQJL7zwgv+8lBKzZs1Cnz59UFRUhKlTp+Ljjz/uxBkTBEEQHUlXj2zlO79su/spviz7tBThyrY9qNPSdg3hhs9CRbBswWFbXfu6dhR5i6v/+I//wBNPPNEecykY/fr1w89+9jMsXLgQCxcuxLHHHovTTz/dF1C/+MUvcPfdd+O+++7DggUL0Lt3b5xwwgmora3t5JkTBEEQRG601dahRXPS0D7hNGPggaU9snio9orziE0D0Ya0YENDAx566CG8/PLLGD16NGzbjjx/9913F2xybeW0006LPP7pT3+KBx54AG+//TZGjhyJe++9FzfeeCPOPPNMAMBjjz2GXr164YknnsCll17aGVMmCIIgiIKQq+hqSWSZVYTh54NVg0ZkaT8sqdKFNoJ2Ovs7eYurDz/8EGPHjgUALF68OPJcVwyzuq6Lp59+Grt378akSZOwcuVKbNy4MWIjEYvFMGXKFLz11lstiqvGxkY0Njb6j2tqagAAyWQSyWSy/V4EsVdj7g26R4jWoHuFyIX0+yTcnzD9c9gXSGG/q7Tn0jH7mOelBDwGpFIeGGPwGOB6qqeO57qq7srz4LkehN/HMODcif3wxIJ1e/KS9zryFldz585tj3kUnI8++giTJk1CQ0MDSkpK8Oyzz2LkyJF46623AAC9evWK7N+rVy+sXr26xTFvv/123HzzzRnb586di0QiUbjJE/skc+bM6ewpEHsJdK8QuWDuk7BGSo9xRKwYspBNX4WNSAEllBgAVwb1V562akhJtd3T3zkDJARMvOvyg1Jgu1cDvovW/kGbfK72BkaMGIEPPvgAO3bswDPPPIMLL7wQ8+bN85/Ppu5bi7zdcMMNmDlzpv+4pqYG/fv3x7Rp01BVVVXYF0DsMySTScyZMwcnnHBCRhqdIMLQvULkQvp9Yj6/sn2OhSNXzZEewUqPXJltSdeDYMpaNOVJcAakXAlPSiRdCdfzYAmOH783119F+LUTp2DLriZsSXyBpxauL8Cr3zvIW1xNmzatxTfp1Vdf3aMJFQrHcTBs2DAAwIQJE7BgwQL87//+L374wx8CUM2mq6ur/f03b96cEc1KJxaLIRaLZWy3bZt+ERKtQvcJkSt0rxC5YO6TlsQV0HrwIFdxxbgHrsUV85TQ4kIZlVpSwnUlhGC44+wx+OEzH+LaE0cg7jiIOxJfHdtvvxJXeZf1jx07FmPGjPG/Ro4ciaamJixatAiHHHJIe8yxIEgp0djYiMGDB6N3796RsHtTUxPmzZvX5S0mCIIgCKI59qTuuaVjgxWDLOhLCBaxejCO7QzAUcO647Vrp+LU0dXKnkFwdEvYuPjoQW2e395G3pGre+65J+v2WbNmYdeuXXs8oULw3//93zj55JPRv39/1NbW4sknn8Rrr72GF198EYwxXH311bjtttswfPhwDB8+HLfddhsSiQTOPffczp46QRAEQeRFa6Kq0IvNws2fBWOQTAJSCS0JlS50LA7PU6sJHYuDM+CIIVV4+I1VkbG+c9Qg/Gv5Vny6cd+yQipYzdV5552Hww47DHfeeWehhmwzmzZtwvnnn48NGzagvLwco0ePxosvvogTTjgBAHDdddehvr4el19+ObZv347DDz8cL730EkpLyVmWIAiC2D8J2y9kfb6Zn9WxZjsD56o1TkoLLVtwCG0yms7kYd0xqCqBn/z9kz1/AV2Igomrf/3rX4jH44Uabo94+OGHW3yeMYZZs2Zh1qxZHTMhgiAIguiiRA1GWbPPZdtu+hNKBLYNFlcpQ7Nm0ESubBGMlXAESuMW4raA4Pue8Wje4soYbxqklNiwYQMWLlyIm266qWATIwiCIAii6xBpn5O2nYFBSiWylHN7UGAvmGqRE45cPTrjMMQdjqQrYe2DxqN5i6vy8vLIY845RowYgVtuuSVizEkQBEEQxL6JL7RkILTUNuXSbtKDxsXd4gwDq4oxsroMRY5ASVzAsTjqmzxYgsQVZs+e3R7zIAiCIAhiLyBs+5Bu88Ah/TY5zFNtciyuhFbM4njsoonwPIldTS5szpGyJEpi+57lZptf0XvvvYclS5aAMYaRI0fi0EMPLeS8CIIgCILoQkT6DYYaOkd63TAGxqQWVSoNaAlVgyV1cbvLJGwuwblq+tyvIrPDyZDuxVixZXd7v6R2I29xtXnzZnzzm9/Ea6+9hm7dukFKiZ07d2LatGl48skn0aNHj/aYJ0EQBEEQewkMQerQNHP2WCDKhGB6BaGE62UWtH91TB/c+8qyjppuwcm7RP/KK69ETU0NPv74Y2zbtg3bt2/H4sWLUVNTg+9///vtMUeCIAiCIDqYtvhjpRuMMqZSgwyqyF0wVZNlc/XdEtwXXwBw2KAK3HDygTh6ePcCvpKOJ+/I1YsvvoiXX34ZBx10kL9t5MiRuP/++6mgnSAIgiD2YZq3ZlDfpQx+VisGATCdSpQqisUlg+AeGGOwJUOSMzw6YyLe+HwLTjmkGsUxC0nX88e++OhBGeajXZ28xZXneVl7Xtm2Dc/zshxBEARBEMT+Ajf1WPp/UuptOlfGmBJZjDF4Utk0DOlRgqE9S9CQdLU4CxJrAyqLMXVED7y29MuOfiltJu+04LHHHourrroKX3zxhb9t/fr1+MEPfoDjjjuuoJMjCIIgCKJrE/G/8nsPhoreERS/mzQhN2lBrgrfhfbBUmlCHrFnsATDlccOw7CeJR34qvaMvMXVfffdh9raWgwaNAhDhw7FsGHDMHjwYNTW1uJXv/pVe8yRIAiCIIguTNTlPbQd4V6EzLdpELr+inMGzqF/Vu7utmARY1GLMyQcC0cMqezAV7Rn5J0W7N+/PxYtWoQ5c+bg008/hZQSI0eOxPHHH98e8yMIgiAIogsTboWT3puQMZ0XhHJsMJIpXWQxDnCmolSCMTTKoMzIsbgWXHtPm5w2+1ydcMIJfiNkgiAIgiCIdFTdlUkPypAQU4LLrBg0Xlme/m4JhnMm9sfabXUYN6ACTDu/p3PEkEq4nsSCVdvb+6XkRc4y8J133sELL7wQ2fb4449j8ODB6NmzJ7773e+isbGx4BMkCIIgCGLvwq+90nrI1GH5P7NwDRbAufqyhRJRgjNcM30E7v3mWDiWqska0y/afm9YzxJ8/7jh+MEJB+CQvtHnOpucI1ezZs3C1KlTcfLJJwMAPvroI1x88cWYMWMGDjroINxxxx3o06cPZs2a1V5zJQiCIAiiCxN1cc98LvIYLFg5CAapW+ekXAlwDiklJNQqQy6BMf274X/PGYteZTHsbEiid1kRXCmRciWG9ijGR+t3ZsxneK8SLNu0q91eb3PkHLn64IMPIqsBn3zySRx++OH47W9/i5kzZ+KXv/wl/vznP7fLJAmCIAiC2DvIFFGZKwo5Y+D+ykIW2qYK27l+LBiDI7j/3KEDKlDdrQj9K4pR5Ag4gkNwYFQzkau7vj6m/V5oC+Qcudq+fTt69erlP543bx5OOukk//HEiROxdu3aws6OIAiCIIi9msBUNKipYlDiyZPSF1bhn8EBz1OpQs8DBFd1WK6nyuIdS4ktKVSMaMLAiqzntkXnFMHnfNZevXph5cqVAICmpiYsWrQIkyZN8p+vra3Nai5KEARBEMS+SUstcrI9x9KeM985izq724IriwauVhKKUBTLFhwWV1+29sdyLJF1DuEi+JNG9W7DK2wbOUeuTjrpJFx//fX4+c9/jueeew6JRAKTJ0/2n//www8xdOjQdpkkQRAEQRB7H6YGK92mgUX2MdtUetDV+5mehIIBHpfgPHB+ty1Vk2UzDk96aC5AZQuOX5x1CJZ/uRtnje+HFxdvbIdXmUnO4urWW2/FmWeeiSlTpqCkpASPPfYYHMfxn3/kkUeotyBBEARBEFlRUao0HywYzyvlhxV2cZfmZy26bM791KHFGaRUqURbMDBwjOpThsVf1PhjGwf4wwZXYUz/iogxaXuTs7jq0aMH5s+fj507d6KkpARCRENwTz/9NEpK9h5reoIgCIIgOp5sUSzOAC9k3xAWWR6kimpxCS5ZSHxJMMlgKpzu+PoYvLFsC44aVoXXln6JScOqfFsHV8oONSHN20S0vDx7RX5l5d5jS08QBEEQRNcg6EGofma60bPHAksH0/zZiK4UV+sMvZDtQ1WJg6+N6wspgbMn9INgDClPRbpsl8OxurC4IgiCIAiCKBQmW8f9Inf1WDCmkoiSAUzqx9K3aABT/ldShk1LlQCTUFYPUo8rhMzq8N5ekLgiCIIgCKKgtLSKUD3f/DZm7BpCdViuL6D06kJu7BuCqJbU6UMJqeq0uBI5jKnaKxJXBEEQBEHsc7Rm3WBWFrJgo/om1f9MqZZJEVqMQ0I1eRZMFbxzqIiX0EXxRliRuCIIgiAIYp+gtShW+j6mqD1U864NSIO0oFlJyBhUkTvU6kDXU99TnkoDelIGzu8dp61IXBEEQRAE0fGkrxoMtoe+y2Ajh3JnD68kVAQCCjxoBm32Mf0LeQ4ir1B0ji88QRAEQRD7LZFIVS6RLf3d9CMMrxwULCq4GJgvtsw2I65+f9FhOG1Mdfu8qBAkrgiCIAiC6DJEhRd8Z/bwc/7qQATpQbM9/HwgsNS2kX3KcN2JB7b7ayBxRRAEQRBEp5BL1Cq8r7FbMK7uxnqB6XWEQYQrSAOq7boAnnNYguG4g3oW+qVEIHFFEARBEMReCYNKCwJZolppES3OmN8M+sZTD2rXeZG4IgiCIAiiy+MLprTH0eeD6JbaFo5uKWElGEOJY2Fs/27tNldaLUgQBEEQRJeguUL3dGsGlnYMCzWEjvhkhfZlutjdEhyAh5JY+0kgilwRBEEQBLFXEE79hUm3WVApwWAVoV+TpW0Z2ttUlMQVQRAEQRBdnmwrAgFkRKnSJZMRWeYYwRg4Zzh7fL92myuJK4IgCIIguhS5riIM11MF20I/p30Pe19VFtuFmGpWSFwRBEEQBNGlycV0NLw6MH1fHvrOdSPnA3qV4uA+Ze0yXxJXBEEQBEHsVaQLrHw723DGYAuOB88bX8BZhcZvl1EJgiAIgiA6mNbSicq1PdjXFhxHD6sq+DxIXBEEQRAE0eXJpw6r+eeC71yvHLzpKwcXYnoRyOeKIAiCIIi9jszUYKaoCjyulE9WuACe6YbOCUcUfG4krgiCIAiC2G8IVg6qL0sU3u+K0oIEQRAEQezz8DTTUNP8mTOGvt2KCnuugo5GEARBEATRxUhvpWO+G6f2owpc1L5Piqvbb78dEydORGlpKXr27IkzzjgDS5cujewjpcSsWbPQp08fFBUVYerUqfj44487acYEQRAEQRSKXIrfTUscoVcNFpJ9UlzNmzcPV1xxBd5++23MmTMHqVQK06dPx+7du/19fvGLX+Duu+/GfffdhwULFqB379444YQTUFtb24kzJwiCIAgiH3JZHZi+v1ktaExF03sT7in7ZEH7iy++GHk8e/Zs9OzZE++99x6OOeYYSClx77334sYbb8SZZ54JAHjsscfQq1cvPPHEE7j00ks7Y9oEQRAEQbSBXG0a0o9hTILxzH6Ee8o+Ka7S2blzJwCgsrISALBy5Ups3LgR06dP9/eJxWKYMmUK3nrrrWbFVWNjIxobGzPG3bZtW3tNndgHSCaTqKurw9atW2Hb7dfLitj7oXuFyAW6T3JHSplVeEkpAQCuJ5HyJBrrauA11rU6ntnHHN8c+7y4klJi5syZOProozFq1CgAwMaNGwEAvXr1iuzbq1cvrF69utmxbr/9dtx8880Z2w844IACzpggCIIgiK5MbW0tysvLm31+nxdX3/ve9/Dhhx/ijTfeyHguXc02p3ANN9xwA2bOnOk/3rFjBwYOHIg1a9a0eJG7AhMnTsSCBQu69PhtHSOf43LZt7V9Wno+23M1NTXo378/1q5di7Ky9mkSWij2hvukreN09H3S2j50r7T/+PQ7pfNp7/ukUOfIdQwpJWpra9GnT58W99unxdWVV16Jv//973j99dfRr18/f3vv3r0BqAhWdXW1v33z5s0Z0awwsVgMsVgsY3t5eXmXv8GFEO06x0KM39Yx8jkul31b26el51t6rqysjO6TAo3flnE6+j5pbR+6V9p/fPqd0vm0931SqHPkM0YuwZR9crWglBLf+9738Ne//hWvvvoqBg8eHHl+8ODB6N27N+bMmeNva2pqwrx583DkkUd29HQ7hCuuuKLLj9/WMfI5Lpd9W9unpefb+zq3N3vDfdLWcTr6PmltH7pX2n98+p3S+XTE/DvzXmkOJlurytoLufzyy/HEE0/gb3/7G0aMGOFvLy8vR1GRcmH9+c9/jttvvx2zZ8/G8OHDcdttt+G1117D0qVLUVpamtN5ampqUF5ejp07d3b5vx6IzoPuEyJX6F4hcoHuk67PPpkWfOCBBwAAU6dOjWyfPXs2ZsyYAQC47rrrUF9fj8svvxzbt2/H4YcfjpdeeilnYQWoNOFPfvKTrKlCgjDQfULkCt0rRC7QfdL12ScjVwRBEARBEJ3FPllzRRAEQRAE0VmQuCIIgiAIgiggJK4IgiAIgiAKCIkrgiAIgiCIAkLiiiAIgiAIooCQuGonvva1r6GiogJnn312Z0+F6MKsXbsWU6dOxciRIzF69Gg8/fTTnT0logtSW1uLiRMnYuzYsTjkkEPw29/+trOnRHRx6urqMHDgQFxzzTWdPZX9ErJiaCfmzp2LXbt24bHHHsNf/vKXzp4O0UXZsGEDNm3ahLFjx2Lz5s0YN24cli5diuLi4s6eGtGFcF0XjY2NSCQSqKurw6hRo7BgwQJUVVV19tSILsqNN96IZcuWYcCAAbjzzjs7ezr7HRS5aiemTZuWlyEpsX9SXV2NsWPHAgB69uyJyspKbNu2rXMnRXQ5hBBIJBIAgIaGBriuC/q7mGiOZcuW4dNPP8Upp5zS2VPZbyFxlYXXX38dp512Gvr06QPGGJ577rmMfX79619j8ODBiMfjGD9+PObPn9/xEyU6nULeKwsXLoTneejfv387z5roaApxn+zYsQNjxoxBv379cN1116F79+4dNHuiIynEvXLNNdfg9ttv76AZE9kgcZWF3bt3Y8yYMbjvvvuyPv/UU0/h6quvxo033oj3338fkydPxsknn4w1a9Z08EyJzqZQ98rWrVtxwQUX4KGHHuqIaRMdTCHuk27duuHf//43Vq5ciSeeeAKbNm3qqOkTHcie3it/+9vfcMABB+CAAw7oyGkT6UiiRQDIZ599NrLtsMMOk5dddllk24EHHiivv/76yLa5c+fKs846q72nSHQR2nqvNDQ0yMmTJ8vHH3+8I6ZJdDJ78jvFcNlll8k///nP7TVFoovQlnvl+uuvl/369ZMDBw6UVVVVsqysTN58880dNWVCQ5GrPGlqasJ7772H6dOnR7ZPnz4db731VifNiuiK5HKvSCkxY8YMHHvssTj//PM7Y5pEJ5PLfbJp0ybU1NQAAGpqavD6669jxIgRHT5XonPJ5V65/fbbsXbtWqxatQp33nknLrnkEvz4xz/ujOnu11idPYG9jS1btsB1XfTq1SuyvVevXti4caP/+MQTT8SiRYuwe/du9OvXD88++ywmTpzY0dMlOpFc7pU333wTTz31FEaPHu3XVvz+97/HIYcc0tHTJTqJXO6TdevW4eKLL4aUElJKfO9738Po0aM7Y7pEJ5Lr5w/R+ZC4aiOMschjKWVk2z//+c+OnhLRRWnpXjn66KPheV5nTIvoYrR0n4wfPx4ffPBBJ8yK6Iq09vljmDFjRgfNiEiH0oJ50r17dwghMv5K2Lx5c8ZfE8T+Dd0rRC7QfULkCt0rew8krvLEcRyMHz8ec+bMiWyfM2cOjjzyyE6aFdEVoXuFyAW6T4hcoXtl74HSglnYtWsXPv/8c//xypUr8cEHH6CyshIDBgzAzJkzcf7552PChAmYNGkSHnroIaxZswaXXXZZJ86a6AzoXiFyge4TIlfoXtlH6MSVil2WuXPnSgAZXxdeeKG/z/333y8HDhwoHceR48aNk/Pmzeu8CROdBt0rRC7QfULkCt0r+wbUW5AgCIIgCKKAUM0VQRAEQRBEASFxRRAEQRAEUUBIXBEEQRAEQRQQElcEQRAEQRAFhMQVQRAEQRBEASFxRRAEQRAEUUBIXBEEQRAEQRQQElcEQRAEQRAFhMQVQRBEF2TGjBlgjIExhueee66gY7/22mv+2GeccUZBxyYIgsQVQRAdRFgshL/CfdSIKCeddBI2bNiAk08+2d/WnNiaMWNGzkLpyCOPxIYNG/CNb3yjQDMlCCIMNW4mCKLDOOmkkzB79uzIth49emTs19TUBMdxOmpaXZZYLIbevXsXfFzHcdC7d28UFRWhsbGx4OMTxP4ORa4IgugwjFgIfwkhMHXqVHzve9/DzJkz0b17d5xwwgkAgE8++QSnnHIKSkpK0KtXL5x//vnYsmWLP97u3btxwQUXoKSkBNXV1bjrrrswdepUXH311f4+2SI93bp1w6OPPuo/Xr9+Pc455xxUVFSgqqoKp59+OlatWuU/b6JCd955J6qrq1FVVYUrrrgCyWTS36exsRHXXXcd+vfvj1gshuHDh+Phhx+GlBLDhg3DnXfeGZnD4sWLwTnH8uXL9/zCprFq1aqsUcKpU6cW/FwEQWRC4oogiC7BY489Bsuy8Oabb+I3v/kNNmzYgClTpmDs2LFYuHAhXnzxRWzatCmSyrr22msxd+5cPPvss3jppZfw2muv4b333svrvHV1dZg2bRpKSkrw+uuv44033kBJSQlOOukkNDU1+fvNnTsXy5cvx9y5c/HYY4/h0UcfjQi0Cy64AE8++SR++ctfYsmSJXjwwQdRUlICxhguuuiijIjdI488gsmTJ2Po0KFtu2At0L9/f2zYsMH/ev/991FVVYVjjjmm4OciCCILkiAIogO48MILpRBCFhcX+19nn322lFLKKVOmyLFjx0b2v+mmm+T06dMj29auXSsByKVLl8ra2lrpOI588skn/ee3bt0qi4qK5FVXXeVvAyCfffbZyDjl5eVy9uzZUkopH374YTlixAjpeZ7/fGNjoywqKpL//Oc//bkPHDhQplIpf5+vf/3r8pxzzpFSSrl06VIJQM6ZMyfra//iiy+kEEK+8847Ukopm5qaZI8ePeSjjz7a4vU6/fTTM7YDkPF4PHIdi4uLpWVZWfevr6+Xhx9+uPzKV74iXdfN6RwEQewZVHNFEESHMW3aNDzwwAP+4+LiYv/nCRMmRPZ97733MHfuXJSUlGSMs3z5ctTX16OpqQmTJk3yt1dWVmLEiBF5zem9997D559/jtLS0sj2hoaGSMru4IMPhhDCf1xdXY2PPvoIAPDBBx9ACIEpU6ZkPUd1dTVOPfVUPPLIIzjssMPw/PPPo6GhAV//+tfzmqvhnnvuwfHHHx/Z9sMf/hCu62bse/HFF6O2thZz5swB55SsIIiOgMQVQRAdRnFxMYYNG9bsc2E8z8Npp52Gn//85xn7VldXY9myZTmdkzEGKWVkW7hWyvM8jB8/Hn/84x8zjg0X29u2nTGu53kAgKKiolbn8R//8R84//zzcc8992D27Nk455xzkEgkcnoN6fTu3TvjOpaWlmLHjh2RbbfeeitefPFFvPvuuxnikSCI9oPEFUEQXZJx48bhmWeewaBBg2BZmb+qhg0bBtu28fbbb2PAgAEAgO3bt+Ozzz6LRJB69OiBDRs2+I+XLVuGurq6yHmeeuop9OzZE2VlZW2a6yGHHALP8zBv3ryMiJLhlFNOQXFxMR544AG88MILeP3119t0rlx55plncMstt+CFF15ol7ougiCah2LEBEF0Sa644gps27YN3/rWt/Duu+9ixYoVeOmll3DRRRfBdV2UlJTg4osvxrXXXotXXnkFixcvxowZMzJSX8ceeyzuu+8+LFq0CAsXLsRll10WiUJ9+9vfRvfu3XH66adj/vz5WLlyJebNm4errroK69aty2mugwYNwoUXXoiLLroIzz33HFauXInXXnsNf/7zn/19hBCYMWMGbrjhBgwbNiySziw0ixcvxgUXXIAf/vCHOPjgg7Fx40Zs3LgR27Zta7dzEgQRQOKKIIguSZ8+ffDmm2/CdV2ceOKJGDVqFK666iqUl5f7AuqOO+7AMcccg69+9as4/vjjcfTRR2P8+PGRce666y70798fxxxzDM4991xcc801kXRcIpHA66+/jgEDBuDMM8/EQQcdhIsuugj19fV5RbIeeOABnH322bj88stx4IEH4pJLLsHu3bsj+1x88cVoamrCRRddtAdXpnUWLlyIuro63Hrrraiurva/zjzzzHY9L0EQCibTixEIgiD2YqZOnYqxY8fi3nvv7eypZPDmm29i6tSpWLduHXr16tXivjNmzMCOHTsK3vqmo89BEPsjFLkiCIJoZxobG/H555/jpptuwje+8Y1WhZXh+eefR0lJCZ5//vmCzmf+/PkoKSnJWsRPEMSeQwXtBEEQ7cyf/vQnXHzxxRg7dix+//vf53TML37xC/zoRz8CoFZHFpIJEybggw8+AICsVhcEQewZlBYkCIIgCIIoIJQWJAiCIAiCKCAkrgiCIAiCIAoIiSuCIAiCIIgCQuKKIAiCIAiigJC4IgiCIAiCKCAkrgiCIAiCIAoIiSuCIAiCIIgCQuKKIAiCIAiigJC4IgiCIAiCKCD/H8a3gNRM4RksAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -369,12 +378,12 @@
    ],
    "source": [
     "import random\n",
-    "samples = random.sample(range(spsdl[\"time\"].size), 30)\n",
-    "spsdl_clip = spsdl.isel(time=samples)\n",
+    "samples = random.sample(range(spsdl[\"time_psd\"].size), 30)\n",
+    "spsdl_clip = spsdl.isel(time_psd=samples)\n",
     "\n",
-    "spsdl_median = spsdl_clip.median(\"time\")\n",
-    "spsdl_q25 = spsdl_clip.quantile(0.25, \"time\")\n",
-    "spsdl_q75 = spsdl_clip.quantile(0.75, \"time\")\n",
+    "spsdl_median = spsdl_clip.median(\"time_psd\")\n",
+    "spsdl_q25 = spsdl_clip.quantile(0.25, \"time_psd\")\n",
+    "spsdl_q75 = spsdl_clip.quantile(0.75, \"time_psd\")\n",
     "\n",
     "# Plot medians and quantiles\n",
     "fig, ax = acoustics.graphics.plot_spectra(spsdl_median, fmin, fmax, label=\"Median\")\n",
@@ -399,22 +408,24 @@
    "source": [
     "### Window Averaging\n",
     "\n",
-    "If desired, one can do a couple different types of time-averaging the SPSDLs, though this isn't required by the IEC-40. There are two main supported functions in MHKiT, `time_average` and `time_summation`, which both take the SPSDL and a time window as inputs\n",
+    "If desired, one can do a couple different types of time-averaging the SPSDLs, though this isn't required by the IEC-40. There are two main supported functions in MHKiT, `time_summation` and `time_average`, which both take the SPSDL and a time window as inputs\n",
     "\n",
-    "`time_average` finds returns the spectral average of the SPSDLs in each specified window. This is useful for say, finding the average 30 second SPSDL every hour. In this case, the original SPSD bin_length was 30 seconds, and the time window to input to `time_average` is 1 hour.\n",
+    "`time_summation` represents the total accumulated spectral energy within each window and is proportional to N times the window-averaged SPSDL, where N is the number of input bins per window.\n",
     "\n",
-    "`time_summation` returns the spectral sum of the SPSDLs in each specified window. This is equivalent to recalculating the SPSDs for a new bin_length. For example:\n",
+    "`time_average` returns the energy-averaged SPSDLs in each specified window. This is equivalent to recalculating the SPSDs for a new bin_length. For example:\n",
     "\n",
     "```python\n",
     "spsd = acoustics.sound_pressure_spectral_density(V, fs=V.fs, bin_length=1, fft_length=V.fs)\n",
+    "spsd = acoustics.apply_calibration(spsd, sensitivity_curve, fill_value=fill_Sf)\n",
     "spsdl = acoustics.sound_pressure_spectral_density_level(spsd)\n",
-    "spsdl_30 = acoustics.time_summation(spsdl, window=30)\n",
+    "spsdl_30 = acoustics.time_average(spsdl, window=30)\n",
     "```\n",
     "\n",
     "is equivalent to\n",
     "\n",
     "```python\n",
     "spsd_30 = acoustics.sound_pressure_spectral_density(V, fs=V.fs, bin_length=30, fft_length=V.fs)\n",
+    "spsd_30 = acoustics.apply_calibration(spsd_30, sensitivity_curve, fill_value=fill_Sf)\n",
     "spsdl_30 = acoustics.sound_pressure_spectral_density_level(spsd_30)\n",
     "```\n",
     "\n",
@@ -429,8 +440,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "# Time average into 30 s windows and take the median parameter value\n",
+    "# Time average into 30 s windows\n",
     "window = 30\n",
     "spsdl_30s = acoustics.time_average(spsdl, window)"
    ]
@@ -460,7 +470,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -518,12 +528,12 @@
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x238f3fa2910>,\n",
-       "  <matplotlib.axis.XTick at 0x238f619e4d0>,\n",
-       "  <matplotlib.axis.XTick at 0x238f6132590>,\n",
-       "  <matplotlib.axis.XTick at 0x238f5710250>,\n",
-       "  <matplotlib.axis.XTick at 0x238f638b290>,\n",
-       "  <matplotlib.axis.XTick at 0x238f6395350>],\n",
+       "[[<matplotlib.axis.XTick at 0x168e9168710>,\n",
+       "  <matplotlib.axis.XTick at 0x168e9169b90>,\n",
+       "  <matplotlib.axis.XTick at 0x168e9246050>,\n",
+       "  <matplotlib.axis.XTick at 0x168e9106cd0>,\n",
+       "  <matplotlib.axis.XTick at 0x168e991e050>,\n",
+       "  <matplotlib.axis.XTick at 0x168e989dbd0>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -541,7 +551,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x400 with 2 Axes>"
       ]
@@ -556,11 +566,11 @@
     "\n",
     "# Plot medians and quantiles\n",
     "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
-    "fig, ax[0] = acoustics.graphics.plot_spectra(decidecade_spsdl.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
+    "fig, ax[0] = acoustics.graphics.plot_spectra(decidecade_spsdl.median(\"time_psd\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
     "ax[0].fill_between(\n",
     "    decidecade_spsdl[\"freq\"],\n",
-    "    decidecade_spsdl.quantile(0.25, \"time\"),\n",
-    "    decidecade_spsdl.quantile(0.75, \"time\"),\n",
+    "    decidecade_spsdl.quantile(0.25, \"time_psd\"),\n",
+    "    decidecade_spsdl.quantile(0.75, \"time_psd\"),\n",
     "    alpha=0.5,\n",
     "    facecolor=\"C0\",\n",
     "    edgecolor=None,\n",
@@ -623,7 +633,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 400x400 with 1 Axes>"
       ]
@@ -643,7 +653,7 @@
     "    # calculate the proportional values of samples\n",
     "    p = 1.0 - np.arange(len(x)) / (len(x) + 1)\n",
     "    # recreate dataarray\n",
-    "    x = x.assign_coords({\"time\": p}).rename({\"time\": \"probability\"})\n",
+    "    x = x.assign_coords({\"time_psd\": p}).rename({\"time_psd\": \"probability\"})\n",
     "    x.values = np.reshape(x_sorted, shape)\n",
     "    return x\n",
     "\n",
@@ -691,7 +701,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 2 Axes>"
       ]
@@ -785,7 +795,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x238f69c8410>]"
+       "[<matplotlib.lines.Line2D at 0x168e7181dd0>]"
       ]
      },
      "execution_count": 19,
@@ -794,7 +804,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -841,12 +851,12 @@
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x238fa9ff050>,\n",
-       "  <matplotlib.axis.XTick at 0x238f0048150>,\n",
-       "  <matplotlib.axis.XTick at 0x238f6c6fa10>,\n",
-       "  <matplotlib.axis.XTick at 0x238f6d1ec90>,\n",
-       "  <matplotlib.axis.XTick at 0x238f24eef90>,\n",
-       "  <matplotlib.axis.XTick at 0x238f6c886d0>],\n",
+       "[[<matplotlib.axis.XTick at 0x168e6f5ad90>,\n",
+       "  <matplotlib.axis.XTick at 0x168e7170e10>,\n",
+       "  <matplotlib.axis.XTick at 0x168e9f0ebd0>,\n",
+       "  <matplotlib.axis.XTick at 0x168e7416690>,\n",
+       "  <matplotlib.axis.XTick at 0x168e74387d0>,\n",
+       "  <matplotlib.axis.XTick at 0x168e743a8d0>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -865,7 +875,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x400 with 2 Axes>"
       ]
@@ -880,11 +890,11 @@
     "\n",
     "# Plot the decidecade sound pressure level\n",
     "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
-    "fig, ax[0] = acoustics.graphics.plot_spectra(spl10.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
+    "fig, ax[0] = acoustics.graphics.plot_spectra(spl10.median(\"time_psd\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
     "ax[0].fill_between(\n",
     "    spl10[\"freq_bins\"],\n",
-    "    spl10.quantile(0.25, \"time\"),\n",
-    "    spl10.quantile(0.75, \"time\"),\n",
+    "    spl10.quantile(0.25, \"time_psd\"),\n",
+    "    spl10.quantile(0.75, \"time_psd\"),\n",
     "    alpha=0.5,\n",
     "    facecolor=\"C0\",\n",
     "    edgecolor=None,\n",
@@ -940,12 +950,12 @@
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x238f24af010>,\n",
-       "  <matplotlib.axis.XTick at 0x238f3bde790>,\n",
-       "  <matplotlib.axis.XTick at 0x238f406a590>,\n",
-       "  <matplotlib.axis.XTick at 0x238f4036e10>,\n",
-       "  <matplotlib.axis.XTick at 0x238f4441bd0>,\n",
-       "  <matplotlib.axis.XTick at 0x238f4443c90>],\n",
+       "[[<matplotlib.axis.XTick at 0x168e8276290>,\n",
+       "  <matplotlib.axis.XTick at 0x168e8274410>,\n",
+       "  <matplotlib.axis.XTick at 0x168e8502a90>,\n",
+       "  <matplotlib.axis.XTick at 0x168e82a1810>,\n",
+       "  <matplotlib.axis.XTick at 0x168e85ebfd0>,\n",
+       "  <matplotlib.axis.XTick at 0x168e8599950>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -964,7 +974,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x400 with 2 Axes>"
       ]
@@ -979,11 +989,11 @@
     "\n",
     "# Plot the decidecade sound pressure level\n",
     "fig, ax = plt.subplots(1, 2, figsize=(10, 4), constrained_layout=True)\n",
-    "fig, ax[0] = acoustics.graphics.plot_spectra(spl3.median(\"time\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
+    "fig, ax[0] = acoustics.graphics.plot_spectra(spl3.median(\"time_psd\"), fmin, fmax, fig=fig, ax=ax[0], label=\"Median\")\n",
     "ax[0].fill_between(\n",
     "    spl3[\"freq_bins\"],\n",
-    "    spl3.quantile(0.25, \"time\"),\n",
-    "    spl3.quantile(0.75, \"time\"),\n",
+    "    spl3.quantile(0.25, \"time_psd\"),\n",
+    "    spl3.quantile(0.75, \"time_psd\"),\n",
     "    alpha=0.5,\n",
     "    facecolor=\"C0\",\n",
     "    edgecolor=None,\n",
@@ -1033,14 +1043,22 @@
    "execution_count": 22,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\acoustics\\analysis.py:250: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=14400000 samples, pct_overlap=0.5).\n",
+      "  psd = binner.power_spectral_density(\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<xarray.DataArray 'sel' (time: 1)> Size: 4B\n",
-      "array([136.9158], dtype=float32)\n",
+      "<xarray.DataArray 'sel' (time_psd: 1)> Size: 4B\n",
+      "array([139.87512], dtype=float32)\n",
       "Coordinates:\n",
-      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
+      "  * time_psd  (time_psd) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
       "Attributes:\n",
       "    units:             dB re 1 uPa^2 s\n",
       "    long_name:         Sound Exposure Level\n",
@@ -1051,12 +1069,12 @@
       "\n",
       "\n",
       "Data variables:\n",
-      "    sel      (time) float32 4B 136.9\n",
-      "    sel_lf   (time) float32 4B 136.1\n",
-      "    sel_hf   (time) float32 4B 133.6\n",
-      "    sel_vhf  (time) float32 4B 128.5\n",
-      "    sel_pw   (time) float32 4B 135.1\n",
-      "    sel_ow   (time) float32 4B 132.7\n"
+      "    sel      (time_psd) float32 4B 139.9\n",
+      "    sel_lf   (time_psd) float32 4B 139.1\n",
+      "    sel_hf   (time_psd) float32 4B 136.6\n",
+      "    sel_vhf  (time_psd) float32 4B 131.4\n",
+      "    sel_pw   (time_psd) float32 4B 138.0\n",
+      "    sel_ow   (time_psd) float32 4B 135.7\n"
      ]
     }
    ],
@@ -1097,10 +1115,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<xarray.DataArray (time: 1)> Size: 4B\n",
-      "array([112.14459], dtype=float32)\n",
+      "<xarray.DataArray (time_psd: 1)> Size: 4B\n",
+      "array([115.10391], dtype=float32)\n",
       "Coordinates:\n",
-      "  * time     (time) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
+      "  * time_psd  (time_psd) datetime64[ns] 8B 2023-02-04T15:07:37.996495008\n",
       "Attributes:\n",
       "    units:            dB re 1 uPa\n",
       "    long_name:        Sound Pressure Level\n",
@@ -1129,7 +1147,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x400 with 2 Axes>"
       ]
diff --git a/examples/adcp_example.ipynb b/examples/adcp_example.ipynb
index 9bbcb220e..d6b021ed5 100644
--- a/examples/adcp_example.ipynb
+++ b/examples/adcp_example.ipynb
@@ -1,5541 +1,4764 @@
 {
- "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Analyzing ADCP Data with MHKiT\n",
-    "\n",
-    "The following example illustrates a straightforward workflow for analyzing Acoustic Doppler Current Profiler (ADCP) data utilizing MHKiT. MHKiT has integrated the DOLfYN codebase as a module to facilitate ADCP and Acoustic Doppler Velocimetry (ADV) data processing.\n",
-    "\n",
-    "Here is a standard workflow for ADCP data analysis:\n",
-    "\n",
-    "1. **Import Data**\n",
-    "\n",
-    "2. **Review, QC, and Prepare the Raw Data**:\n",
-    "   1. Calculate or verify the correctness of depth bin locations\n",
-    "   2. Discard data recorded above the water surface or below the seafloor\n",
-    "   3. Assess the quality of velocity, beam amplitude, and/or beam correlation data\n",
-    "   4. Rotate Data Coordinate System\n",
-    "\n",
-    "3. **Data Averaging**: \n",
-    "    - If not already executed within the instrument, average the data into time bins of a predetermined duration, typically between 5 and 10 minutes\n",
-    "\n",
-    "4. **Speed and Direction**\n",
-    "\n",
-    "5. **Plotting**\n",
-    "\n",
-    "6. **Saving and Loading DOLfYN datasets**\n",
-    "\n",
-    "7. **Turbulence Statistics**\n",
-    "    1. Turbulence Intensity (TI)\n",
-    "    2. Power Spectral Densities\n",
-    "    3. Instrument Noise\n",
-    "    4. TKE Dissipation Rate\n",
-    "    5. Noise-corrected TI\n",
-    "    6. Reynolds stresses\n",
-    "    7. TKE Production\n",
-    "    8. TKE Balance \n",
-    "\n",
-    "\n",
-    "Begin your analysis by importing the requisite tools:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "from mhkit import dolfyn\n",
-    "from mhkit.dolfyn.adp import api\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pandas as pd\n",
-    "import numpy as np"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "##  1. Importing Raw Instrument Data\n",
-    "\n",
-    "One of DOLfYN's key features is its ability to directly import raw data from an Acoustic Doppler Current Profiler (ADCP) right after it has been transferred. In this instance, we are using a Nortek Signature1000 ADCP, with the data stored in files with an '.ad2cp' extension. This specific dataset represents several hours of velocity data, captured at 1 Hz by an ADCP mounted on a bottom lander within a tidal inlet. The list of instruments compatible with DOLfYN can be found in the [MHKiT DOLfYN documentation](https://mhkit-software.github.io/MHKiT/mhkit-python/api.dolfyn.html).\n",
-    "\n",
-    "We'll start by importing the raw data file downloaded from the instrument. The `read` function processes the raw file and converts the information into an xarray Dataset. This Dataset includes several groups of variables:\n",
-    "\n",
-    "1. **Velocity**: Recorded in the coordinate system saved by the instrument (beam, XYZ, ENU)\n",
-    "2. **Beam Data**: Includes amplitude and correlation data\n",
-    "3. **Instrumental & Environmental Measurements**: Captures the instrument's bearing and environmental conditions\n",
-    "4. **Orientation Matrices**: Used by DOLfYN for rotating through different coordinate frames.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
+  "cells": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Reading file data/dolfyn/Sig1000_tidal.ad2cp ...\n"
-     ]
-    }
-   ],
-   "source": [
-    "ds = dolfyn.read(\"data/dolfyn/Sig1000_tidal.ad2cp\")"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There are two ways to see what's in a Dataset. The first is to simply type the dataset's name to see the standard xarray output. To access a particular variable in a dataset, use dict-style (`ds['vel']`) or attribute-style syntax (`ds.vel`). See the [xarray docs](http://xarray.pydata.org/en/stable/getting-started-guide/quick-overview.html) for more details on how to use the xarray format."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Analyzing ADCP Data with MHKiT\n",
+        "\n",
+        "The following example illustrates a straightforward workflow for analyzing Acoustic Doppler Current Profiler (ADCP) data utilizing MHKiT. MHKiT has integrated the DOLfYN codebase as a module to facilitate ADCP and Acoustic Doppler Velocimetry (ADV) data processing.\n",
+        "\n",
+        "Here is a standard workflow for ADCP data analysis:\n",
+        "\n",
+        "1. **Import Data**\n",
+        "\n",
+        "2. **Review, QC, and Prepare the Raw Data**:\n",
+        "   1. Calculate or verify the correctness of depth bin locations\n",
+        "   2. Discard data recorded above the water surface or below the seafloor\n",
+        "   3. Assess the quality of velocity, beam amplitude, and/or beam correlation data\n",
+        "   4. Rotate Data Coordinate System\n",
+        "\n",
+        "3. **Data Averaging**: \n",
+        "    - If not already executed within the instrument, average the data into time bins of a predetermined duration, typically between 5 and 10 minutes\n",
+        "\n",
+        "4. **Speed and Direction**\n",
+        "\n",
+        "5. **Plotting**\n",
+        "\n",
+        "6. **Saving and Loading DOLfYN datasets**\n",
+        "\n",
+        "7. **Turbulence Statistics**\n",
+        "    1. Turbulence Intensity (TI)\n",
+        "    2. Power Spectral Densities\n",
+        "    3. Instrument Noise\n",
+        "    4. TKE Dissipation Rate\n",
+        "    5. Noise-corrected TI\n",
+        "    6. Reynolds stresses\n",
+        "    7. TKE Production\n",
+        "    8. TKE Balance \n",
+        "\n",
+        "\n",
+        "Begin your analysis by importing the requisite tools:"
+      ]
+    },
     {
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-       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
-       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, white)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       "html[theme=\"dark\"],\n",
-       "html[data-theme=\"dark\"],\n",
-       "body[data-theme=\"dark\"],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, #111111)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "  line-height: 1.6;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-obj-name,\n",
-       ".xr-group-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name::before {\n",
-       "  content: \"📁\";\n",
-       "  padding-right: 0.3em;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name,\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
-       "  margin-block-start: 0;\n",
-       "  margin-block-end: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: inline-block;\n",
-       "  opacity: 0;\n",
-       "  height: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "  border: 2px solid transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:focus + label {\n",
-       "  border: 2px solid var(--xr-font-color0) !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: \"►\";\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: \"▼\";\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-top: 4px;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box {\n",
-       "  display: inline-grid;\n",
-       "  grid-template-columns: 0px 20px auto;\n",
-       "  width: 100%;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-vline {\n",
-       "  grid-column-start: 1;\n",
-       "  border-right: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "  width: 0px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-hline {\n",
-       "  grid-column-start: 2;\n",
-       "  grid-row-start: 1;\n",
-       "  height: 1em;\n",
-       "  width: 20px;\n",
-       "  border-bottom: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-contents {\n",
-       "  grid-column-start: 3;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: \"(\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: \")\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: \",\";\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  border-color: var(--xr-background-color-row-odd);\n",
-       "  margin-bottom: 0;\n",
-       "  padding-top: 2px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "  border-color: var(--xr-background-color-row-even);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  border-top: 2px dotted var(--xr-background-color);\n",
-       "  padding-bottom: 20px !important;\n",
-       "  padding-top: 10px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in + label,\n",
-       ".xr-var-data-in + label,\n",
-       ".xr-index-data-in + label {\n",
-       "  padding: 0 1px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > pre,\n",
-       ".xr-index-data > pre,\n",
-       ".xr-var-data > table > tbody > tr {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
-       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
-       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
-       "  color: var(--xr-font-color0);\n",
-       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
-       "  stroke-width: 0.8px;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 83MB\n",
-       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-       "                          x1: 4, x2: 4)\n",
-       "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
-       "  * beam                 (beam) int32 16B 1 2 3 4\n",
-       "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
-       "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-       "  * x1                   (x1) int32 16B 1 2 3 4\n",
-       "  * x2                   (x2) int32 16B 1 2 3 4\n",
-       "Data variables: (12/38)\n",
-       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-       "    ...                   ...\n",
-       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
-       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
-       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-       "Attributes: (12/34)\n",
-       "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
-       "    inst_model:            Signature1000\n",
-       "    inst_make:             Nortek\n",
-       "    inst_type:             ADCP\n",
-       "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
-       "    n_cells:               28\n",
-       "    ...                    ...\n",
-       "    proc_idle_less_12pct:  0\n",
-       "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
-       "    coord_sys:             earth\n",
-       "    fs:                    1\n",
-       "    has_imu:               1\n",
-       "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f28a974d-02c1-4c0e-b0aa-35a34cb04614' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f28a974d-02c1-4c0e-b0aa-35a34cb04614' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-73f6a664-08f3-4fbb-9c79-c107bd2e17a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-73f6a664-08f3-4fbb-9c79-c107bd2e17a5' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-2bf135d0-099b-454c-92c3-0fc84896aa43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bf135d0-099b-454c-92c3-0fc84896aa43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b43dbf41-e9ef-4950-984f-d8f6138b0ddb' class='xr-var-data-in' type='checkbox'><label for='data-b43dbf41-e9ef-4950-984f-d8f6138b0ddb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
-       "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
-       "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-603893bf-5abc-410a-8c19-ef29f6982588' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-603893bf-5abc-410a-8c19-ef29f6982588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c572de15-bf56-4083-bb69-eb0ea27440df' class='xr-var-data-in' type='checkbox'><label for='data-c572de15-bf56-4083-bb69-eb0ea27440df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
-       "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
-       "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-2a25848e-bb35-49a4-b9fb-672be8314b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a25848e-bb35-49a4-b9fb-672be8314b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d260546b-dc09-4642-9764-acbe5209a5bb' class='xr-var-data-in' type='checkbox'><label for='data-d260546b-dc09-4642-9764-acbe5209a5bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-6c42074c-a1d8-4c94-8018-7c1e5846fcbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c42074c-a1d8-4c94-8018-7c1e5846fcbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fb7f816-ba22-412a-a090-0d23c8c09ee0' class='xr-var-data-in' type='checkbox'><label for='data-7fb7f816-ba22-412a-a090-0d23c8c09ee0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-8f9f0671-99ea-4543-a37b-d94c1ac426d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f9f0671-99ea-4543-a37b-d94c1ac426d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5acdfbec-8b28-4849-8321-02b4f256cc65' class='xr-var-data-in' type='checkbox'><label for='data-5acdfbec-8b28-4849-8321-02b4f256cc65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-fe64bed1-065d-4572-820c-a546674bc23b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe64bed1-065d-4572-820c-a546674bc23b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91cb97d1-6a16-4001-9fe4-7c770edad6a5' class='xr-var-data-in' type='checkbox'><label for='data-91cb97d1-6a16-4001-9fe4-7c770edad6a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-a282b85b-1f3d-41db-9220-93b48867f2a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a282b85b-1f3d-41db-9220-93b48867f2a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37a55f67-7a4c-4fe9-8eb4-4e30a9092209' class='xr-var-data-in' type='checkbox'><label for='data-37a55f67-7a4c-4fe9-8eb4-4e30a9092209' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-a9a65575-08ac-4c58-94a7-e351c187dcff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9a65575-08ac-4c58-94a7-e351c187dcff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27ad0f22-1689-4e27-85a9-03077cf5af87' class='xr-var-data-in' type='checkbox'><label for='data-27ad0f22-1689-4e27-85a9-03077cf5af87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-69f85873-b714-4894-bcdf-1e1100f23400' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69f85873-b714-4894-bcdf-1e1100f23400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81d1c39c-d2f5-46d2-8b2d-13206e10bed1' class='xr-var-data-in' type='checkbox'><label for='data-81d1c39c-d2f5-46d2-8b2d-13206e10bed1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-a14bc8fc-bfb6-4a07-ae07-0c00765ca633' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a14bc8fc-bfb6-4a07-ae07-0c00765ca633' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bd0f72c-78f5-4b0b-af0b-0b8a580840cb' class='xr-var-data-in' type='checkbox'><label for='data-3bd0f72c-78f5-4b0b-af0b-0b8a580840cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-cc997752-660a-4a7e-92db-5dc162d10c73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc997752-660a-4a7e-92db-5dc162d10c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fccb9774-d78a-413b-b35e-56e61fa4fc88' class='xr-var-data-in' type='checkbox'><label for='data-fccb9774-d78a-413b-b35e-56e61fa4fc88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-18671300-7253-40b7-b0f9-f82e20574edb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18671300-7253-40b7-b0f9-f82e20574edb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55b56463-9c00-4b38-a15f-b5bc9114fc0f' class='xr-var-data-in' type='checkbox'><label for='data-55b56463-9c00-4b38-a15f-b5bc9114fc0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b40bdc2f-5ba2-43b8-88e0-ab62a460bc56' class='xr-section-summary-in' type='checkbox'  ><label for='section-b40bdc2f-5ba2-43b8-88e0-ab62a460bc56' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-11d0c1f6-a1d8-414c-83fe-3e3c06a05ca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11d0c1f6-a1d8-414c-83fe-3e3c06a05ca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c481825-6aa6-41dc-9aa8-05b64183f645' class='xr-var-data-in' type='checkbox'><label for='data-3c481825-6aa6-41dc-9aa8-05b64183f645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-276d2650-d81c-4c34-9775-78a2e2e1e367' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-276d2650-d81c-4c34-9775-78a2e2e1e367' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41ff6085-7e2b-4f24-9fd7-bb2485b84cf1' class='xr-var-data-in' type='checkbox'><label for='data-41ff6085-7e2b-4f24-9fd7-bb2485b84cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-5d688586-aa74-4f0d-ad5e-fbd7d9488d60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d688586-aa74-4f0d-ad5e-fbd7d9488d60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47260f77-e611-4f40-8321-6331a6f1564a' class='xr-var-data-in' type='checkbox'><label for='data-47260f77-e611-4f40-8321-6331a6f1564a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-e6322c76-1557-4aa8-815e-7930d416ce20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6322c76-1557-4aa8-815e-7930d416ce20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3394cdc-3ef0-47f7-9e63-fb198b8e9f1c' class='xr-var-data-in' type='checkbox'><label for='data-b3394cdc-3ef0-47f7-9e63-fb198b8e9f1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
-       "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
-       "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-14a9fcb0-6690-4c66-9888-93437bec3f33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14a9fcb0-6690-4c66-9888-93437bec3f33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f26e634c-ad73-4b8e-8d60-0a562215bfed' class='xr-var-data-in' type='checkbox'><label for='data-f26e634c-ad73-4b8e-8d60-0a562215bfed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
-       "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
-       "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
-       "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
-       "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
-       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-ce4bd203-6f47-4d75-877f-b2d6458ffa2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce4bd203-6f47-4d75-877f-b2d6458ffa2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff83154-4207-4313-9bea-3642e3d9693a' class='xr-var-data-in' type='checkbox'><label for='data-8ff83154-4207-4313-9bea-3642e3d9693a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-638397a6-8e5b-4462-b526-34e79ade8cdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-638397a6-8e5b-4462-b526-34e79ade8cdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a687b8c7-daa8-4804-9913-5308745abcff' class='xr-var-data-in' type='checkbox'><label for='data-a687b8c7-daa8-4804-9913-5308745abcff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-d5e19c7f-ae28-4acf-9f57-8ccf921b9bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5e19c7f-ae28-4acf-9f57-8ccf921b9bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b22bf5-0482-46ba-add2-be69c364880c' class='xr-var-data-in' type='checkbox'><label for='data-d1b22bf5-0482-46ba-add2-be69c364880c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-6343e252-273c-431b-823b-eb2bde09e714' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6343e252-273c-431b-823b-eb2bde09e714' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3397a186-35a2-46ac-a040-b32afaf9a17e' class='xr-var-data-in' type='checkbox'><label for='data-3397a186-35a2-46ac-a040-b32afaf9a17e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-5bc2999c-15fc-4cb5-94a4-67caadb4c7af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bc2999c-15fc-4cb5-94a4-67caadb4c7af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7569e9e-c73e-4915-9ec2-524b7fab94ff' class='xr-var-data-in' type='checkbox'><label for='data-a7569e9e-c73e-4915-9ec2-524b7fab94ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-7fe81551-7fd9-44c5-8f10-a69e53b22908' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fe81551-7fd9-44c5-8f10-a69e53b22908' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48264037-1850-4629-940b-afe003baed01' class='xr-var-data-in' type='checkbox'><label for='data-48264037-1850-4629-940b-afe003baed01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
-       "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
-       "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
-       "        ...,\n",
-       "        [-0.169, -0.013, -0.124, ..., -0.062,  0.091, -0.009],\n",
-       "        [-0.16 , -0.043, -0.111, ...,  0.012,  0.089,  0.021],\n",
-       "        [-0.158, -0.057, -0.13 , ..., -0.055,  0.104,  0.013]],\n",
-       "\n",
-       "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
-       "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
-       "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
-       "        ...,\n",
-       "        [ 0.305,  0.377,  0.283, ..., -0.198, -0.229, -0.121],\n",
-       "        [ 0.328,  0.33 ,  0.294, ..., -0.161, -0.292, -0.103],\n",
-       "        [ 0.31 ,  0.314,  0.226, ..., -0.219, -0.292, -0.049]],\n",
-       "\n",
-       "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
-       "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
-       "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
-       "        ...,\n",
-       "        [ 0.034, -0.061, -0.024, ..., -0.014,  0.086,  0.01 ],\n",
-       "        [ 0.032, -0.04 , -0.027, ..., -0.014,  0.063, -0.01 ],\n",
-       "        [ 0.004, -0.037, -0.018, ..., -0.001,  0.059,  0.021]],\n",
-       "\n",
-       "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
-       "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
-       "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
-       "        ...,\n",
-       "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
-       "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
-       "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
-       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-6a311971-8539-4391-959b-5a2e29c55984' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a311971-8539-4391-959b-5a2e29c55984' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72821c48-0bc3-4a04-a089-cc29f3bd3eeb' class='xr-var-data-in' type='checkbox'><label for='data-72821c48-0bc3-4a04-a089-cc29f3bd3eeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
-       "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
-       "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
-       "        ...,\n",
-       "        [54.5, 55.5, 54.5, ..., 50. , 50. , 49.5],\n",
-       "        [53.5, 54.5, 54.5, ..., 46.5, 47. , 46.5],\n",
-       "        [53. , 54. , 53. , ..., 45. , 46. , 44.5]],\n",
-       "\n",
-       "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
-       "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
-       "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
-       "        ...,\n",
-       "        [57. , 58.5, 58. , ..., 53.5, 52. , 52.5],\n",
-       "        [55.5, 56.5, 55.5, ..., 50. , 49. , 49. ],\n",
-       "        [52.5, 54. , 54. , ..., 47.5, 47.5, 47. ]],\n",
-       "\n",
-       "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
-       "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
-       "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
-       "        ...,\n",
-       "        [56.5, 56.5, 57. , ..., 47.5, 47. , 48. ],\n",
-       "        [56. , 55.5, 56.5, ..., 46.5, 47. , 47. ],\n",
-       "        [54.5, 54. , 55.5, ..., 45. , 45.5, 45.5]],\n",
-       "\n",
-       "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
-       "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
-       "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
-       "        ...,\n",
-       "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
-       "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
-       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]],\n",
-       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-56aad773-9465-4433-bb11-a09cfcd4df6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56aad773-9465-4433-bb11-a09cfcd4df6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8543c267-4dac-4f97-8328-ebb8ff57392b' class='xr-var-data-in' type='checkbox'><label for='data-8543c267-4dac-4f97-8328-ebb8ff57392b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
-       "        [ 74,  92,  96, ..., 100,  97, 100],\n",
-       "        [100, 100,  99, ...,  99, 100, 100],\n",
-       "        ...,\n",
-       "        [ 99, 100, 100, ...,  96,  96,  99],\n",
-       "        [ 99,  97, 100, ...,  94,  97,  96],\n",
-       "        [ 98, 100, 100, ..., 100, 100,  98]],\n",
-       "\n",
-       "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
-       "        [ 94, 100, 100, ...,  96, 100,  93],\n",
-       "        [ 99,  95,  97, ...,  98,  98, 100],\n",
-       "        ...,\n",
-       "        [100, 100, 100, ...,  98,  99, 100],\n",
-       "        [ 99, 100,  99, ...,  97,  94,  94],\n",
-       "        [ 96,  99,  96, ...,  97, 100,  97]],\n",
-       "\n",
-       "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
-       "        [ 99, 100,  99, ...,  96,  88,  98],\n",
-       "        [ 97, 100,  98, ..., 100,  99,  97],\n",
-       "        ...,\n",
-       "        [100, 100,  99, ...,  97,  94,  95],\n",
-       "        [100, 100, 100, ...,  96, 100, 100],\n",
-       "        [100, 100, 100, ...,  96,  95,  94]],\n",
-       "\n",
-       "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
-       "        [100,  93,  93, ...,  96,  96,  97],\n",
-       "        [100, 100, 100, ..., 100, 100,  97],\n",
-       "        ...,\n",
-       "        [100,  99,  96, ...,  98, 100, 100],\n",
-       "        [100, 100, 100, ...,  94,  93,  95],\n",
-       "        [100,  98,  99, ...,  98,  98,  96]]],\n",
-       "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-9b9c2cc3-8d21-4715-9999-c6d82daf0381' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b9c2cc3-8d21-4715-9999-c6d82daf0381' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-370f5f57-f122-4594-b089-ec9ae3c4b3aa' class='xr-var-data-in' type='checkbox'><label for='data-370f5f57-f122-4594-b089-ec9ae3c4b3aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
-       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-       "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
-       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-       "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
-       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
-       "\n",
-       "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
-       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-       "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
-       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-       "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
-       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
-       "\n",
-       "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
-       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
-       "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
-       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
-       "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
-       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-777fa3a5-705e-4db6-8040-d98d483332a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-777fa3a5-705e-4db6-8040-d98d483332a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1832c48-85c6-4601-9fd1-5a6d47409bb7' class='xr-var-data-in' type='checkbox'><label for='data-f1832c48-85c6-4601-9fd1-5a6d47409bb7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
-       "        -0.00292969, -0.00195312],\n",
-       "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
-       "         0.00097656,  0.00097656],\n",
-       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-b3df1677-f6ee-4361-9744-d264f633c86d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3df1677-f6ee-4361-9744-d264f633c86d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0922c989-b7fb-402e-b5da-d2bb0d2c1cf7' class='xr-var-data-in' type='checkbox'><label for='data-0922c989-b7fb-402e-b5da-d2bb0d2c1cf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
-       "         0.6247864 ,  0.62490845],\n",
-       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-       "        -0.03564453, -0.03561401],\n",
-       "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
-       "        -0.04360962, -0.04360962],\n",
-       "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-369b7ac7-3c76-4829-bd5a-e24553418a5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-369b7ac7-3c76-4829-bd5a-e24553418a5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca75ac4f-4c6f-4bf2-9533-9288632ae70f' class='xr-var-data-in' type='checkbox'><label for='data-ca75ac4f-4c6f-4bf2-9533-9288632ae70f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-9f0ad4f2-aaa7-42b0-917b-c9f7c5b115c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f0ad4f2-aaa7-42b0-917b-c9f7c5b115c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ce54ca4-b578-404d-84f7-cbf3032c8853' class='xr-var-data-in' type='checkbox'><label for='data-7ce54ca4-b578-404d-84f7-cbf3032c8853' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-6e7cb7a1-075d-4116-af50-af4ebeb85739' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e7cb7a1-075d-4116-af50-af4ebeb85739' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d97d916-ae98-48c8-a287-d25c690a0daf' class='xr-var-data-in' type='checkbox'><label for='data-4d97d916-ae98-48c8-a287-d25c690a0daf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
-       "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
-       "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-f403d93b-53cf-4afb-8397-8afdcf14e667' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f403d93b-53cf-4afb-8397-8afdcf14e667' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8492deda-94a2-4ba0-9972-e35a250f6ed3' class='xr-var-data-in' type='checkbox'><label for='data-8492deda-94a2-4ba0-9972-e35a250f6ed3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
-       "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
-       "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
-       "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
-       "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
-       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-8753e491-8667-4bdc-85f3-06c43ba85c61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8753e491-8667-4bdc-85f3-06c43ba85c61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3643a4a9-9e2e-427e-893c-d7c598d80254' class='xr-var-data-in' type='checkbox'><label for='data-3643a4a9-9e2e-427e-893c-d7c598d80254' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-193f34be-d8d4-4977-a71f-bb63445659b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-193f34be-d8d4-4977-a71f-bb63445659b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ae9e849-6118-49a4-b4db-ebbc4bcf4eac' class='xr-var-data-in' type='checkbox'><label for='data-1ae9e849-6118-49a4-b4db-ebbc4bcf4eac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-bac83806-7e0d-4f0c-ae41-d3838df691c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bac83806-7e0d-4f0c-ae41-d3838df691c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03de88eb-7398-4de1-90b2-529099f32800' class='xr-var-data-in' type='checkbox'><label for='data-03de88eb-7398-4de1-90b2-529099f32800' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-62c5f014-9241-42d8-ad8b-134f3b0c2f25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62c5f014-9241-42d8-ad8b-134f3b0c2f25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97cfe342-8196-4402-ba27-a1c80696ed1e' class='xr-var-data-in' type='checkbox'><label for='data-97cfe342-8196-4402-ba27-a1c80696ed1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
-       "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
-       "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
-       "       ...,\n",
-       "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
-       "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
-       "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
-       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-4cc9ef2a-f41a-4ab0-9776-aa0ad0ea04d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4cc9ef2a-f41a-4ab0-9776-aa0ad0ea04d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acdc68ed-ef5f-4caa-a112-66b2593f4492' class='xr-var-data-in' type='checkbox'><label for='data-acdc68ed-ef5f-4caa-a112-66b2593f4492' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
-       "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
-       "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
-       "       ...,\n",
-       "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
-       "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
-       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]],\n",
-       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-76a59e93-8a68-4c75-9552-dc6c6546a3b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76a59e93-8a68-4c75-9552-dc6c6546a3b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b472c615-dea5-49b7-a2ee-7540f0a413d1' class='xr-var-data-in' type='checkbox'><label for='data-b472c615-dea5-49b7-a2ee-7540f0a413d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
-       "       [ 97,  94,  98, ...,  97,  95,  97],\n",
-       "       [100, 100, 100, ...,  93, 100,  96],\n",
-       "       ...,\n",
-       "       [100, 100, 100, ..., 100, 100,  98],\n",
-       "       [100, 100, 100, ...,  99, 100,  98],\n",
-       "       [100, 100, 100, ...,  99,  94, 100]],\n",
-       "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-c18e2035-c4f9-45f7-ac74-820e5d113539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c18e2035-c4f9-45f7-ac74-820e5d113539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-056471b0-c180-4158-8790-a13facc490cc' class='xr-var-data-in' type='checkbox'><label for='data-056471b0-c180-4158-8790-a13facc490cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
-       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-       "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
-       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-       "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
-       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
-       "\n",
-       "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
-       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-       "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
-       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-       "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
-       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
-       "\n",
-       "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
-       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
-       "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
-       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
-       "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
-       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-939e8beb-5806-47c7-bbac-a5b77d8d2d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-939e8beb-5806-47c7-bbac-a5b77d8d2d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c11138d-4e5f-4e3c-b8f3-bac261b7e7cb' class='xr-var-data-in' type='checkbox'><label for='data-3c11138d-4e5f-4e3c-b8f3-bac261b7e7cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
-       "        -0.00195312, -0.00390625],\n",
-       "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
-       "         0.        ,  0.00097656],\n",
-       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-9b0ac6e1-bea8-4307-9dc7-9863e4b221ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b0ac6e1-bea8-4307-9dc7-9863e4b221ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f43d76ae-75fc-43b6-97f7-e76dcaa21183' class='xr-var-data-in' type='checkbox'><label for='data-f43d76ae-75fc-43b6-97f7-e76dcaa21183' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
-       "         0.6247864 ,  0.62490845],\n",
-       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-       "        -0.03564453, -0.03561401],\n",
-       "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
-       "        -0.04360962, -0.04360962],\n",
-       "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-7509e529-273f-4169-9c6c-138a57766fde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7509e529-273f-4169-9c6c-138a57766fde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e92d63e-8f07-41a5-b463-5e374259309c' class='xr-var-data-in' type='checkbox'><label for='data-0e92d63e-8f07-41a5-b463-5e374259309c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-53521fd9-798b-4a9c-b11c-d52775a96263' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53521fd9-798b-4a9c-b11c-d52775a96263' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f11ec6fb-60b9-4bd8-b625-51f371434f74' class='xr-var-data-in' type='checkbox'><label for='data-f11ec6fb-60b9-4bd8-b625-51f371434f74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-a8944bce-70c7-436a-91bb-c4abb1fd9507' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a8944bce-70c7-436a-91bb-c4abb1fd9507' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bcf6f94-248e-459c-b751-fabed7292479' class='xr-var-data-in' type='checkbox'><label for='data-7bcf6f94-248e-459c-b751-fabed7292479' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-6757c338-4e8c-4dc9-b50e-1bbe018e9825' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6757c338-4e8c-4dc9-b50e-1bbe018e9825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e3b3997-2deb-4ece-ba76-3daf7370642f' class='xr-var-data-in' type='checkbox'><label for='data-0e3b3997-2deb-4ece-ba76-3daf7370642f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-0c05add4-068c-49a7-9ac2-3704a77417e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c05add4-068c-49a7-9ac2-3704a77417e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df4fa6f3-587c-4280-a100-85a4e60f465e' class='xr-var-data-in' type='checkbox'><label for='data-df4fa6f3-587c-4280-a100-85a4e60f465e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-331cc7f8-0610-4c67-9d3e-515fc3d73aee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-331cc7f8-0610-4c67-9d3e-515fc3d73aee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-561108d0-676b-4d20-96ef-3b87a24bcc0b' class='xr-var-data-in' type='checkbox'><label for='data-561108d0-676b-4d20-96ef-3b87a24bcc0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-       "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-0f345601-b07b-474e-a2a0-49a2ec0708f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f345601-b07b-474e-a2a0-49a2ec0708f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cfc3192-7bda-4cec-a282-6c400ee02a2e' class='xr-var-data-in' type='checkbox'><label for='data-4cfc3192-7bda-4cec-a282-6c400ee02a2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-45ec3d74-0628-4889-a8fb-529b86508120' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45ec3d74-0628-4889-a8fb-529b86508120' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5daaec6-28f0-4f8d-93a6-a5b68f6598c3' class='xr-var-data-in' type='checkbox'><label for='data-c5daaec6-28f0-4f8d-93a6-a5b68f6598c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-       "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-8c09064d-3cdc-41fc-a42f-590b2be4e59d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c09064d-3cdc-41fc-a42f-590b2be4e59d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e624ebaf-c843-4311-9779-b513fd032d37' class='xr-var-data-in' type='checkbox'><label for='data-e624ebaf-c843-4311-9779-b513fd032d37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
-       "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
-       "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b62067c6-93e4-4617-b952-0abf39e01c72' class='xr-section-summary-in' type='checkbox'  ><label for='section-b62067c6-93e4-4617-b952-0abf39e01c72' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "scrolled": true
+      },
+      "outputs": [],
+      "source": [
+        "from mhkit import dolfyn\n",
+        "from mhkit.dolfyn.adp import api\n",
+        "import matplotlib.pyplot as plt\n",
+        "import pandas as pd\n",
+        "import numpy as np"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "##  1. Importing Raw Instrument Data\n",
+        "\n",
+        "One of DOLfYN's key features is its ability to directly import raw data from an Acoustic Doppler Current Profiler (ADCP) right after it has been transferred. In this instance, we are using a Nortek Signature1000 ADCP, with the data stored in files with an '.ad2cp' extension. This specific dataset represents several hours of velocity data, captured at 1 Hz by an ADCP mounted on a bottom lander within a tidal inlet. The list of instruments compatible with DOLfYN can be found in the [MHKiT DOLfYN documentation](https://mhkit-software.github.io/MHKiT/mhkit-python/api.dolfyn.html).\n",
+        "\n",
+        "We'll start by importing the raw data file downloaded from the instrument. The `read` function processes the raw file and converts the information into an xarray Dataset. This Dataset includes several groups of variables:\n",
+        "\n",
+        "1. **Velocity**: Recorded in the coordinate system saved by the instrument (beam, XYZ, ENU)\n",
+        "2. **Beam Data**: Includes amplitude and correlation data\n",
+        "3. **Instrumental & Environmental Measurements**: Captures the instrument's bearing and environmental conditions\n",
+        "4. **Orientation Matrices**: Used by DOLfYN for rotating through different coordinate frames.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "scrolled": true
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Reading file data/dolfyn/Sig1000_tidal.ad2cp ...\n"
+          ]
+        }
       ],
-      "text/plain": [
-       "<xarray.Dataset> Size: 83MB\n",
-       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-       "                          x1: 4, x2: 4)\n",
-       "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
-       "  * beam                 (beam) int32 16B 1 2 3 4\n",
-       "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
-       "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
-       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
-       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
-       "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
-       "  * x1                   (x1) int32 16B 1 2 3 4\n",
-       "  * x2                   (x2) int32 16B 1 2 3 4\n",
-       "Data variables: (12/38)\n",
-       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-       "    ...                   ...\n",
-       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
-       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
-       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-       "Attributes: (12/34)\n",
-       "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
-       "    inst_model:            Signature1000\n",
-       "    inst_make:             Nortek\n",
-       "    inst_type:             ADCP\n",
-       "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
-       "    n_cells:               28\n",
-       "    ...                    ...\n",
-       "    proc_idle_less_12pct:  0\n",
-       "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
-       "    coord_sys:             earth\n",
-       "    fs:                    1\n",
-       "    has_imu:               1\n",
-       "    beam_angle:            25"
+      "source": [
+        "ds = dolfyn.read(\"data/dolfyn/Sig1000_tidal.ad2cp\")"
       ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# print the dataset\n",
-    "ds"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "A second way provided to look at data is through the *DOLfYN view*. This view has several convenience methods, shortcuts, and functions built-in. It includes an alternate – and somewhat more informative/compact – description of the data object when in interactive mode. This can be accessed using"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "<ADCP data object>:  Nortek Signature1000\n",
-       "  . 15.28 hours (started: Aug 15, 2020 00:20)\n",
-       "  . earth-frame\n",
-       "  . (55000 pings @ 1Hz)\n",
-       "  Variables:\n",
-       "  - time ('time',)\n",
-       "  - time_b5 ('time_b5',)\n",
-       "  - vel ('dir', 'range', 'time')\n",
-       "  - vel_b5 ('range_b5', 'time_b5')\n",
-       "  - range ('range',)\n",
-       "  - orientmat ('earth', 'inst', 'time')\n",
-       "  - heading ('time',)\n",
-       "  - pitch ('time',)\n",
-       "  - roll ('time',)\n",
-       "  - temp ('time',)\n",
-       "  - pressure ('time',)\n",
-       "  - amp ('beam', 'range', 'time')\n",
-       "  - amp_b5 ('range_b5', 'time_b5')\n",
-       "  - corr ('beam', 'range', 'time')\n",
-       "  - corr_b5 ('range_b5', 'time_b5')\n",
-       "  - accel ('dirIMU', 'time')\n",
-       "  - angrt ('dirIMU', 'time')\n",
-       "  - mag ('dirIMU', 'time')\n",
-       "  ... and others (see `<obj>.variables`)"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "There are two ways to see what's in a Dataset. The first is to simply type the dataset's name to see the standard xarray output. To access a particular variable in a dataset, use dict-style (`ds['vel']`) or attribute-style syntax (`ds.vel`). See the [xarray docs](http://xarray.pydata.org/en/stable/getting-started-guide/quick-overview.html) for more details on how to use the xarray format."
       ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ds_dolfyn = ds.velds\n",
-    "ds_dolfyn"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "One way to visualize this data is to plot the velocity in a histogram. This will highlight any outliers."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x1200 with 4 Axes>"
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+              "<defs>\n",
+              "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+              "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "</symbol>\n",
+              "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+              "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "</symbol>\n",
+              "</defs>\n",
+              "</svg>\n",
+              "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+              "\n",
+              ":root {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, white)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              "html[theme=\"dark\"],\n",
+              "html[data-theme=\"dark\"],\n",
+              "body[data-theme=\"dark\"],\n",
+              "body.vscode-dark {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, #111111)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              ".xr-wrap {\n",
+              "  display: block !important;\n",
+              "  min-width: 300px;\n",
+              "  max-width: 700px;\n",
+              "  line-height: 1.6;\n",
+              "}\n",
+              "\n",
+              ".xr-text-repr-fallback {\n",
+              "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-header {\n",
+              "  padding-top: 6px;\n",
+              "  padding-bottom: 6px;\n",
+              "  margin-bottom: 4px;\n",
+              "  border-bottom: solid 1px var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-header > div,\n",
+              ".xr-header > ul {\n",
+              "  display: inline;\n",
+              "  margin-top: 0;\n",
+              "  margin-bottom: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-obj-type,\n",
+              ".xr-obj-name,\n",
+              ".xr-group-name {\n",
+              "  margin-left: 2px;\n",
+              "  margin-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name::before {\n",
+              "  content: \"📁\";\n",
+              "  padding-right: 0.3em;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name,\n",
+              ".xr-obj-type {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-sections {\n",
+              "  padding-left: 0 !important;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+              "  margin-block-start: 0;\n",
+              "  margin-block-end: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input {\n",
+              "  display: inline-block;\n",
+              "  opacity: 0;\n",
+              "  height: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input + label {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "  border: 2px solid transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label {\n",
+              "  cursor: pointer;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:focus + label {\n",
+              "  border: 2px solid var(--xr-font-color0) !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label:hover {\n",
+              "  color: var(--xr-font-color0);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary {\n",
+              "  grid-column: 1;\n",
+              "  color: var(--xr-font-color2);\n",
+              "  font-weight: 500;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary > span {\n",
+              "  display: inline-block;\n",
+              "  padding-left: 0.5em;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in + label:before {\n",
+              "  display: inline-block;\n",
+              "  content: \"►\";\n",
+              "  font-size: 11px;\n",
+              "  width: 15px;\n",
+              "  text-align: center;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label:before {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label:before {\n",
+              "  content: \"▼\";\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label > span {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary,\n",
+              ".xr-section-inline-details {\n",
+              "  padding-top: 4px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-inline-details {\n",
+              "  grid-column: 2 / -1;\n",
+              "}\n",
+              "\n",
+              ".xr-section-details {\n",
+              "  display: none;\n",
+              "  grid-column: 1 / -1;\n",
+              "  margin-top: 4px;\n",
+              "  margin-bottom: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box {\n",
+              "  display: inline-grid;\n",
+              "  grid-template-columns: 0px 20px auto;\n",
+              "  width: 100%;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-vline {\n",
+              "  grid-column-start: 1;\n",
+              "  border-right: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "  width: 0px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-hline {\n",
+              "  grid-column-start: 2;\n",
+              "  grid-row-start: 1;\n",
+              "  height: 1em;\n",
+              "  width: 20px;\n",
+              "  border-bottom: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-contents {\n",
+              "  grid-column-start: 3;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap {\n",
+              "  grid-column: 1 / -1;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 20px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap > label {\n",
+              "  grid-column: 1;\n",
+              "  vertical-align: top;\n",
+              "}\n",
+              "\n",
+              ".xr-preview {\n",
+              "  color: var(--xr-font-color3);\n",
+              "}\n",
+              "\n",
+              ".xr-array-preview,\n",
+              ".xr-array-data {\n",
+              "  padding: 0 5px !important;\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-array-data,\n",
+              ".xr-array-in:checked ~ .xr-array-preview {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-array-in:checked ~ .xr-array-data,\n",
+              ".xr-array-preview {\n",
+              "  display: inline-block;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list {\n",
+              "  display: inline-block !important;\n",
+              "  list-style: none;\n",
+              "  padding: 0 !important;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li {\n",
+              "  display: inline-block;\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:before {\n",
+              "  content: \"(\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:after {\n",
+              "  content: \")\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li:not(:last-child):after {\n",
+              "  content: \",\";\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-has-index {\n",
+              "  font-weight: bold;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list,\n",
+              ".xr-var-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > div,\n",
+              ".xr-var-item label,\n",
+              ".xr-var-item > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-even);\n",
+              "  border-color: var(--xr-background-color-row-odd);\n",
+              "  margin-bottom: 0;\n",
+              "  padding-top: 2px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > .xr-var-name:hover span {\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list > li:nth-child(odd) > div,\n",
+              ".xr-var-list > li:nth-child(odd) > label,\n",
+              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-odd);\n",
+              "  border-color: var(--xr-background-color-row-even);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name {\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dims {\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dtype {\n",
+              "  grid-column: 3;\n",
+              "  text-align: right;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-preview {\n",
+              "  grid-column: 4;\n",
+              "}\n",
+              "\n",
+              ".xr-index-preview {\n",
+              "  grid-column: 2 / 5;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name,\n",
+              ".xr-var-dims,\n",
+              ".xr-var-dtype,\n",
+              ".xr-preview,\n",
+              ".xr-attrs dt {\n",
+              "  white-space: nowrap;\n",
+              "  overflow: hidden;\n",
+              "  text-overflow: ellipsis;\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name:hover,\n",
+              ".xr-var-dims:hover,\n",
+              ".xr-var-dtype:hover,\n",
+              ".xr-attrs dt:hover {\n",
+              "  overflow: visible;\n",
+              "  width: auto;\n",
+              "  z-index: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  display: none;\n",
+              "  border-top: 2px dotted var(--xr-background-color);\n",
+              "  padding-bottom: 20px !important;\n",
+              "  padding-top: 10px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in + label,\n",
+              ".xr-var-data-in + label,\n",
+              ".xr-index-data-in + label {\n",
+              "  padding: 0 1px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+              ".xr-var-data-in:checked ~ .xr-var-data,\n",
+              ".xr-index-data-in:checked ~ .xr-index-data {\n",
+              "  display: block;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > table {\n",
+              "  float: right;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > pre,\n",
+              ".xr-index-data > pre,\n",
+              ".xr-var-data > table > tbody > tr {\n",
+              "  background-color: transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name span,\n",
+              ".xr-var-data,\n",
+              ".xr-index-name div,\n",
+              ".xr-index-data,\n",
+              ".xr-attrs {\n",
+              "  padding-left: 25px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs,\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  grid-column: 1 / -1;\n",
+              "}\n",
+              "\n",
+              "dl.xr-attrs {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 125px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt,\n",
+              ".xr-attrs dd {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  float: left;\n",
+              "  padding-right: 10px;\n",
+              "  width: auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt {\n",
+              "  font-weight: normal;\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt:hover span {\n",
+              "  display: inline-block;\n",
+              "  background: var(--xr-background-color);\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dd {\n",
+              "  grid-column: 2;\n",
+              "  white-space: pre-wrap;\n",
+              "  word-break: break-all;\n",
+              "}\n",
+              "\n",
+              ".xr-icon-database,\n",
+              ".xr-icon-file-text2,\n",
+              ".xr-no-icon {\n",
+              "  display: inline-block;\n",
+              "  vertical-align: middle;\n",
+              "  width: 1em;\n",
+              "  height: 1.5em !important;\n",
+              "  stroke-width: 0;\n",
+              "  stroke: currentColor;\n",
+              "  fill: currentColor;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+              ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+              ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+              "  color: var(--xr-font-color0);\n",
+              "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+              "  stroke-width: 0.8px;\n",
+              "}\n",
+              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 83MB\n",
+              "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+              "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+              "                          x1: 4, x2: 4)\n",
+              "Coordinates:\n",
+              "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+              "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+              "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+              "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+              "  * beam                 (beam) int32 16B 1 2 3 4\n",
+              "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
+              "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+              "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+              "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+              "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+              "  * x1                   (x1) int32 16B 1 2 3 4\n",
+              "  * x2                   (x2) int32 16B 1 2 3 4\n",
+              "Data variables: (12/38)\n",
+              "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+              "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+              "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+              "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+              "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+              "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+              "    ...                   ...\n",
+              "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+              "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+              "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+              "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+              "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+              "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+              "Attributes: (12/34)\n",
+              "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
+              "    inst_model:            Signature1000\n",
+              "    inst_make:             Nortek\n",
+              "    inst_type:             ADCP\n",
+              "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
+              "    n_cells:               28\n",
+              "    ...                    ...\n",
+              "    proc_idle_less_12pct:  0\n",
+              "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
+              "    coord_sys:             earth\n",
+              "    fs:                    1\n",
+              "    has_imu:               1\n",
+              "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-81ec53bd-3a1b-4f28-aa47-0f11989aa6e7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-81ec53bd-3a1b-4f28-aa47-0f11989aa6e7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-53f8ec61-a299-4e10-85cf-26d603f8c4e9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-53f8ec61-a299-4e10-85cf-26d603f8c4e9' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-e42e1c9b-5ccd-487b-b356-b871d8d7e2ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e42e1c9b-5ccd-487b-b356-b871d8d7e2ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acc85947-3e1d-4a94-90a4-943a780120ef' class='xr-var-data-in' type='checkbox'><label for='data-acc85947-3e1d-4a94-90a4-943a780120ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+              "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
+              "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
+              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-fa788832-b958-46a0-b06c-51639711ae84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa788832-b958-46a0-b06c-51639711ae84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a672fdd3-ad71-4c3c-98fc-3f05ccfff241' class='xr-var-data-in' type='checkbox'><label for='data-a672fdd3-ad71-4c3c-98fc-3f05ccfff241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+              "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
+              "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
+              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-32866ab0-8a8c-4bb9-bc9d-24f77c5d7df4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32866ab0-8a8c-4bb9-bc9d-24f77c5d7df4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81bdd9c1-4516-4510-822a-f1eec1c945ad' class='xr-var-data-in' type='checkbox'><label for='data-81bdd9c1-4516-4510-822a-f1eec1c945ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-12842eed-1613-496e-821a-5d1541fc4bff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12842eed-1613-496e-821a-5d1541fc4bff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce3dd45c-e68b-4d81-b564-61b824e2dc81' class='xr-var-data-in' type='checkbox'><label for='data-ce3dd45c-e68b-4d81-b564-61b824e2dc81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-cb0a43fa-8adb-4ac8-a8d5-7e35157383bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb0a43fa-8adb-4ac8-a8d5-7e35157383bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c1cd77d-081b-4ed6-b5db-50a9b9e071a2' class='xr-var-data-in' type='checkbox'><label for='data-5c1cd77d-081b-4ed6-b5db-50a9b9e071a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-f5892753-f981-4c23-a778-ebd210d48e92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5892753-f981-4c23-a778-ebd210d48e92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acb5a6fe-f764-4342-8a0c-94343969b1e6' class='xr-var-data-in' type='checkbox'><label for='data-acb5a6fe-f764-4342-8a0c-94343969b1e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-785924bf-9c21-4cc9-809a-70cf6c734ba3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-785924bf-9c21-4cc9-809a-70cf6c734ba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c1ae45c-1270-4c5f-994c-72f97fdabb00' class='xr-var-data-in' type='checkbox'><label for='data-3c1ae45c-1270-4c5f-994c-72f97fdabb00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-409e3aaf-0fab-4df5-8eba-4995d2cda650' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-409e3aaf-0fab-4df5-8eba-4995d2cda650' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a80cea2-fd1d-4467-900b-1007fe495d45' class='xr-var-data-in' type='checkbox'><label for='data-5a80cea2-fd1d-4467-900b-1007fe495d45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-d276d6f5-ebd7-4155-8782-10ce43695d76' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d276d6f5-ebd7-4155-8782-10ce43695d76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f12b0fe8-c2a5-4a90-a545-d32a83711cbd' class='xr-var-data-in' type='checkbox'><label for='data-f12b0fe8-c2a5-4a90-a545-d32a83711cbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-7e5d997e-66a5-4e62-b249-8ff38533779d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e5d997e-66a5-4e62-b249-8ff38533779d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adf10e73-fa2c-4781-93b9-f409aa3a32cc' class='xr-var-data-in' type='checkbox'><label for='data-adf10e73-fa2c-4781-93b9-f409aa3a32cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-995c7fea-fd95-41f1-8d22-e7ce5573d205' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-995c7fea-fd95-41f1-8d22-e7ce5573d205' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b843242-5150-432d-985a-4854ab2f1cc5' class='xr-var-data-in' type='checkbox'><label for='data-1b843242-5150-432d-985a-4854ab2f1cc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-e3e8bca9-d09c-42b5-9fe2-31507904fbae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3e8bca9-d09c-42b5-9fe2-31507904fbae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8477bd9-931e-4f6a-983d-518154bf8742' class='xr-var-data-in' type='checkbox'><label for='data-a8477bd9-931e-4f6a-983d-518154bf8742' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ef77866-dedc-4b00-8753-7058bf1cbae3' class='xr-section-summary-in' type='checkbox'  ><label for='section-5ef77866-dedc-4b00-8753-7058bf1cbae3' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-89f75bdf-299d-49a0-87bb-3293ae60d785' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89f75bdf-299d-49a0-87bb-3293ae60d785' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc8eb6f2-f1a4-45c2-bc7d-76d3fcd8f924' class='xr-var-data-in' type='checkbox'><label for='data-dc8eb6f2-f1a4-45c2-bc7d-76d3fcd8f924' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-5e5460c1-d999-4af5-b1c6-525598b7b74b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e5460c1-d999-4af5-b1c6-525598b7b74b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e946f9e-fcca-4de2-b4b2-3c01470eb1c5' class='xr-var-data-in' type='checkbox'><label for='data-5e946f9e-fcca-4de2-b4b2-3c01470eb1c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-57626b14-7200-462d-858f-3ddd8cc01b37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57626b14-7200-462d-858f-3ddd8cc01b37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a0a5d65-ea40-4f12-97df-86c6319a0607' class='xr-var-data-in' type='checkbox'><label for='data-0a0a5d65-ea40-4f12-97df-86c6319a0607' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-a7db5f59-dace-41e6-b9e0-2cd7835d1858' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7db5f59-dace-41e6-b9e0-2cd7835d1858' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af8e8c3f-5a17-42a5-b49d-e7bedb8efc6f' class='xr-var-data-in' type='checkbox'><label for='data-af8e8c3f-5a17-42a5-b49d-e7bedb8efc6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+              "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
+              "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-b26d0197-c857-4e64-9576-134e32211e49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b26d0197-c857-4e64-9576-134e32211e49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e38243d-d17e-430a-b0d2-412f9a5ac190' class='xr-var-data-in' type='checkbox'><label for='data-9e38243d-d17e-430a-b0d2-412f9a5ac190' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+              "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
+              "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
+              "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
+              "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
+              "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-39ff53ef-2f04-4858-8a84-75acc246cf12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39ff53ef-2f04-4858-8a84-75acc246cf12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-929cdaf4-5581-4a3b-9ada-5386e99e77b9' class='xr-var-data-in' type='checkbox'><label for='data-929cdaf4-5581-4a3b-9ada-5386e99e77b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-72c7027a-5f58-4110-ba3c-c0b41b3fedba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72c7027a-5f58-4110-ba3c-c0b41b3fedba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99ebbf73-ab56-40fb-8e47-fbfda5950247' class='xr-var-data-in' type='checkbox'><label for='data-99ebbf73-ab56-40fb-8e47-fbfda5950247' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-632e1657-6d21-4b98-85f2-05b0ae4589a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-632e1657-6d21-4b98-85f2-05b0ae4589a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72454d35-24e0-4216-a1ec-c02893477705' class='xr-var-data-in' type='checkbox'><label for='data-72454d35-24e0-4216-a1ec-c02893477705' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-51409b14-ca96-43cf-836f-2c535e2c6da1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51409b14-ca96-43cf-836f-2c535e2c6da1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd90441f-d8dc-4319-9d2b-0c14300b265f' class='xr-var-data-in' type='checkbox'><label for='data-dd90441f-d8dc-4319-9d2b-0c14300b265f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-a80d9153-009e-4079-9f37-e1163989bb0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a80d9153-009e-4079-9f37-e1163989bb0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-237361cc-1982-41b0-a180-62035c9179d3' class='xr-var-data-in' type='checkbox'><label for='data-237361cc-1982-41b0-a180-62035c9179d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-7922cfcd-9b23-49f4-a504-c920129082d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7922cfcd-9b23-49f4-a504-c920129082d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8bb45e9-0b12-4fdb-891f-55596038d293' class='xr-var-data-in' type='checkbox'><label for='data-b8bb45e9-0b12-4fdb-891f-55596038d293' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+              "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
+              "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
+              "        ...,\n",
+              "        [-0.169, -0.013, -0.124, ..., -0.062,  0.091, -0.009],\n",
+              "        [-0.16 , -0.043, -0.111, ...,  0.012,  0.089,  0.021],\n",
+              "        [-0.158, -0.057, -0.13 , ..., -0.055,  0.104,  0.013]],\n",
+              "\n",
+              "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
+              "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
+              "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
+              "        ...,\n",
+              "        [ 0.305,  0.377,  0.283, ..., -0.198, -0.229, -0.121],\n",
+              "        [ 0.328,  0.33 ,  0.294, ..., -0.161, -0.292, -0.103],\n",
+              "        [ 0.31 ,  0.314,  0.226, ..., -0.219, -0.292, -0.049]],\n",
+              "\n",
+              "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
+              "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
+              "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
+              "        ...,\n",
+              "        [ 0.034, -0.061, -0.024, ..., -0.014,  0.086,  0.01 ],\n",
+              "        [ 0.032, -0.04 , -0.027, ..., -0.014,  0.063, -0.01 ],\n",
+              "        [ 0.004, -0.037, -0.018, ..., -0.001,  0.059,  0.021]],\n",
+              "\n",
+              "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
+              "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
+              "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
+              "        ...,\n",
+              "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
+              "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
+              "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
+              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-1cce2e02-84e8-4a8c-9c55-216b0c1813ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cce2e02-84e8-4a8c-9c55-216b0c1813ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37fdc4b9-d265-4cdd-b317-f12501c9a1dd' class='xr-var-data-in' type='checkbox'><label for='data-37fdc4b9-d265-4cdd-b317-f12501c9a1dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+              "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
+              "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
+              "        ...,\n",
+              "        [54.5, 55.5, 54.5, ..., 50. , 50. , 49.5],\n",
+              "        [53.5, 54.5, 54.5, ..., 46.5, 47. , 46.5],\n",
+              "        [53. , 54. , 53. , ..., 45. , 46. , 44.5]],\n",
+              "\n",
+              "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
+              "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
+              "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
+              "        ...,\n",
+              "        [57. , 58.5, 58. , ..., 53.5, 52. , 52.5],\n",
+              "        [55.5, 56.5, 55.5, ..., 50. , 49. , 49. ],\n",
+              "        [52.5, 54. , 54. , ..., 47.5, 47.5, 47. ]],\n",
+              "\n",
+              "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
+              "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
+              "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
+              "        ...,\n",
+              "        [56.5, 56.5, 57. , ..., 47.5, 47. , 48. ],\n",
+              "        [56. , 55.5, 56.5, ..., 46.5, 47. , 47. ],\n",
+              "        [54.5, 54. , 55.5, ..., 45. , 45.5, 45.5]],\n",
+              "\n",
+              "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
+              "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
+              "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
+              "        ...,\n",
+              "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
+              "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
+              "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]],\n",
+              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-078587be-cb12-48d8-8f59-60af8f024b03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-078587be-cb12-48d8-8f59-60af8f024b03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfbaeb67-c258-4989-b26f-b4d8469a1d0b' class='xr-var-data-in' type='checkbox'><label for='data-cfbaeb67-c258-4989-b26f-b4d8469a1d0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+              "        [ 74,  92,  96, ..., 100,  97, 100],\n",
+              "        [100, 100,  99, ...,  99, 100, 100],\n",
+              "        ...,\n",
+              "        [ 99, 100, 100, ...,  96,  96,  99],\n",
+              "        [ 99,  97, 100, ...,  94,  97,  96],\n",
+              "        [ 98, 100, 100, ..., 100, 100,  98]],\n",
+              "\n",
+              "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
+              "        [ 94, 100, 100, ...,  96, 100,  93],\n",
+              "        [ 99,  95,  97, ...,  98,  98, 100],\n",
+              "        ...,\n",
+              "        [100, 100, 100, ...,  98,  99, 100],\n",
+              "        [ 99, 100,  99, ...,  97,  94,  94],\n",
+              "        [ 96,  99,  96, ...,  97, 100,  97]],\n",
+              "\n",
+              "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
+              "        [ 99, 100,  99, ...,  96,  88,  98],\n",
+              "        [ 97, 100,  98, ..., 100,  99,  97],\n",
+              "        ...,\n",
+              "        [100, 100,  99, ...,  97,  94,  95],\n",
+              "        [100, 100, 100, ...,  96, 100, 100],\n",
+              "        [100, 100, 100, ...,  96,  95,  94]],\n",
+              "\n",
+              "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
+              "        [100,  93,  93, ...,  96,  96,  97],\n",
+              "        [100, 100, 100, ..., 100, 100,  97],\n",
+              "        ...,\n",
+              "        [100,  99,  96, ...,  98, 100, 100],\n",
+              "        [100, 100, 100, ...,  94,  93,  95],\n",
+              "        [100,  98,  99, ...,  98,  98,  96]]],\n",
+              "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-ff07934e-45ae-4c2c-961b-a85b40b3539a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff07934e-45ae-4c2c-961b-a85b40b3539a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78941838-129b-4353-b752-23cb80dfca22' class='xr-var-data-in' type='checkbox'><label for='data-78941838-129b-4353-b752-23cb80dfca22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+              "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+              "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
+              "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+              "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
+              "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
+              "\n",
+              "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
+              "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+              "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
+              "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+              "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
+              "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
+              "\n",
+              "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
+              "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
+              "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
+              "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
+              "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
+              "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-4c8f371b-ac52-4627-ad0b-76a98449312c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c8f371b-ac52-4627-ad0b-76a98449312c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-664e805e-0512-4971-9d9f-2aa2049c0269' class='xr-var-data-in' type='checkbox'><label for='data-664e805e-0512-4971-9d9f-2aa2049c0269' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+              "        -0.00292969, -0.00195312],\n",
+              "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
+              "         0.00097656,  0.00097656],\n",
+              "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+              "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-87b050ee-7b51-4e85-8e6f-b4e8041d9e29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87b050ee-7b51-4e85-8e6f-b4e8041d9e29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b157de7-db08-482a-8b9c-a82881ceb8d2' class='xr-var-data-in' type='checkbox'><label for='data-2b157de7-db08-482a-8b9c-a82881ceb8d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+              "         0.6247864 ,  0.62490845],\n",
+              "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+              "        -0.03564453, -0.03561401],\n",
+              "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
+              "        -0.04360962, -0.04360962],\n",
+              "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
+              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-d8c7f300-eac5-4983-a1cb-ead8cfe7a07d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8c7f300-eac5-4983-a1cb-ead8cfe7a07d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e7a12c8-c6b3-4e63-9cbc-1029e0cd2664' class='xr-var-data-in' type='checkbox'><label for='data-8e7a12c8-c6b3-4e63-9cbc-1029e0cd2664' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-17d3f828-6bf8-42d7-95dc-d0ec54024e20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17d3f828-6bf8-42d7-95dc-d0ec54024e20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a99f0b77-fad9-4a57-9a96-e9d64cf3cb26' class='xr-var-data-in' type='checkbox'><label for='data-a99f0b77-fad9-4a57-9a96-e9d64cf3cb26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-ce00e77f-a9fb-4f2d-a2c9-1306c030bd7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce00e77f-a9fb-4f2d-a2c9-1306c030bd7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e523d55c-3ba6-4b87-8d81-ece057246d23' class='xr-var-data-in' type='checkbox'><label for='data-e523d55c-3ba6-4b87-8d81-ece057246d23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+              "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
+              "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-6ccedab4-36b1-4b7e-bc45-3fc7bdb5460d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ccedab4-36b1-4b7e-bc45-3fc7bdb5460d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7532ee4d-1bf1-4411-9778-62abb3cf4e48' class='xr-var-data-in' type='checkbox'><label for='data-7532ee4d-1bf1-4411-9778-62abb3cf4e48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+              "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
+              "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
+              "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
+              "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
+              "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-dcb8313f-29b4-4677-9632-c9a8672b6a2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcb8313f-29b4-4677-9632-c9a8672b6a2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97e25bcf-f74d-49a9-9645-53f59e999a90' class='xr-var-data-in' type='checkbox'><label for='data-97e25bcf-f74d-49a9-9645-53f59e999a90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-36f37d07-284c-4962-82f9-aa1ca988f69e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36f37d07-284c-4962-82f9-aa1ca988f69e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22465ebd-cb51-4601-a41a-db3d8614fce1' class='xr-var-data-in' type='checkbox'><label for='data-22465ebd-cb51-4601-a41a-db3d8614fce1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-f593b7ed-d879-40e7-9204-c712b2e64ae3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f593b7ed-d879-40e7-9204-c712b2e64ae3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7257c562-4a3f-468d-8aeb-d88c260156b8' class='xr-var-data-in' type='checkbox'><label for='data-7257c562-4a3f-468d-8aeb-d88c260156b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-84a5f01d-2a76-4630-a7a4-7b0af48e020d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84a5f01d-2a76-4630-a7a4-7b0af48e020d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4150f7e4-3eb8-4419-b82e-691c84ed83a5' class='xr-var-data-in' type='checkbox'><label for='data-4150f7e4-3eb8-4419-b82e-691c84ed83a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+              "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
+              "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
+              "       ...,\n",
+              "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
+              "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
+              "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
+              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-00f899f1-2a21-4e4e-9382-fe689b9939c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00f899f1-2a21-4e4e-9382-fe689b9939c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b7a263-e67a-42c6-9409-3ee4929d4fa8' class='xr-var-data-in' type='checkbox'><label for='data-f0b7a263-e67a-42c6-9409-3ee4929d4fa8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+              "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
+              "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
+              "       ...,\n",
+              "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
+              "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
+              "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]],\n",
+              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-a716bd46-ca3d-42c6-84b2-b914fd21f50e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a716bd46-ca3d-42c6-84b2-b914fd21f50e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf2fcc9c-9b7c-4214-83ea-67350f1bc34c' class='xr-var-data-in' type='checkbox'><label for='data-cf2fcc9c-9b7c-4214-83ea-67350f1bc34c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+              "       [ 97,  94,  98, ...,  97,  95,  97],\n",
+              "       [100, 100, 100, ...,  93, 100,  96],\n",
+              "       ...,\n",
+              "       [100, 100, 100, ..., 100, 100,  98],\n",
+              "       [100, 100, 100, ...,  99, 100,  98],\n",
+              "       [100, 100, 100, ...,  99,  94, 100]],\n",
+              "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-87378697-fc85-40f9-99e1-0e9cbc99c76b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87378697-fc85-40f9-99e1-0e9cbc99c76b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87ff3fbb-4771-4957-b291-48c4aa8669f3' class='xr-var-data-in' type='checkbox'><label for='data-87ff3fbb-4771-4957-b291-48c4aa8669f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+              "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
+              "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
+              "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
+              "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
+              "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
+              "\n",
+              "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
+              "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
+              "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
+              "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
+              "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
+              "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
+              "\n",
+              "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
+              "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
+              "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
+              "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
+              "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
+              "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
+              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-fec42e91-87c5-4202-80e7-3426ce4d8669' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fec42e91-87c5-4202-80e7-3426ce4d8669' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af786cbd-befd-49dd-aaa6-213153ca8626' class='xr-var-data-in' type='checkbox'><label for='data-af786cbd-befd-49dd-aaa6-213153ca8626' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+              "        -0.00195312, -0.00390625],\n",
+              "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
+              "         0.        ,  0.00097656],\n",
+              "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
+              "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-1d0e8b83-9e37-4b6b-88ac-e7617f742970' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d0e8b83-9e37-4b6b-88ac-e7617f742970' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99ca2ceb-85b5-411d-b360-d3cce4b1b114' class='xr-var-data-in' type='checkbox'><label for='data-99ca2ceb-85b5-411d-b360-d3cce4b1b114' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+              "         0.6247864 ,  0.62490845],\n",
+              "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
+              "        -0.03564453, -0.03561401],\n",
+              "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
+              "        -0.04360962, -0.04360962],\n",
+              "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
+              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-5a065413-6b6a-41dc-9809-49b03ff14282' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a065413-6b6a-41dc-9809-49b03ff14282' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dd6d596-251a-4cbd-a9c7-a185a37a40d7' class='xr-var-data-in' type='checkbox'><label for='data-0dd6d596-251a-4cbd-a9c7-a185a37a40d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-94e5f453-580f-46d5-a3e1-c98f66e188b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94e5f453-580f-46d5-a3e1-c98f66e188b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-558f4719-a032-456c-a850-1f6bf832b8d5' class='xr-var-data-in' type='checkbox'><label for='data-558f4719-a032-456c-a850-1f6bf832b8d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-4fa2a0c1-2971-41a3-9c65-f76fff37b088' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4fa2a0c1-2971-41a3-9c65-f76fff37b088' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8002079f-244a-4ceb-8cc3-0b3ff11bfe21' class='xr-var-data-in' type='checkbox'><label for='data-8002079f-244a-4ceb-8cc3-0b3ff11bfe21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-a83d3d94-1a3a-4cb2-a31d-3416574e0700' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a83d3d94-1a3a-4cb2-a31d-3416574e0700' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c03baa61-7f7b-4589-aa87-ace245eed6b6' class='xr-var-data-in' type='checkbox'><label for='data-c03baa61-7f7b-4589-aa87-ace245eed6b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-ab267b70-1cc2-4e4a-a1d8-7d0d77c03942' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab267b70-1cc2-4e4a-a1d8-7d0d77c03942' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-039441bd-4caa-42f0-8319-9dd547513069' class='xr-var-data-in' type='checkbox'><label for='data-039441bd-4caa-42f0-8319-9dd547513069' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-012d6206-c1ce-4d14-b3b8-fd268838cb12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-012d6206-c1ce-4d14-b3b8-fd268838cb12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0042280-4de0-412b-8c61-d5327fb12280' class='xr-var-data-in' type='checkbox'><label for='data-b0042280-4de0-412b-8c61-d5327fb12280' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+              "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-5ff03634-faa3-4fe4-a27c-aa2ebc0178da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ff03634-faa3-4fe4-a27c-aa2ebc0178da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9179fff0-3844-46c7-ae3c-a97d407114fe' class='xr-var-data-in' type='checkbox'><label for='data-9179fff0-3844-46c7-ae3c-a97d407114fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-3c2323c0-917d-466e-aab9-9a4404e55101' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c2323c0-917d-466e-aab9-9a4404e55101' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43541028-b402-464d-9d1b-39fec6098a51' class='xr-var-data-in' type='checkbox'><label for='data-43541028-b402-464d-9d1b-39fec6098a51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+              "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-4a5dc191-1b80-40d2-a8e0-c030a91ba634' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a5dc191-1b80-40d2-a8e0-c030a91ba634' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aaa67dd1-de49-4d21-b267-80967ce2edeb' class='xr-var-data-in' type='checkbox'><label for='data-aaa67dd1-de49-4d21-b267-80967ce2edeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+              "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
+              "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
+              "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a052cbed-5b22-47f3-a394-0968cd5f6c80' class='xr-section-summary-in' type='checkbox'  ><label for='section-a052cbed-5b22-47f3-a394-0968cd5f6c80' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
+            ],
+            "text/plain": [
+              "<xarray.Dataset> Size: 83MB\n",
+              "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+              "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+              "                          x1: 4, x2: 4)\n",
+              "Coordinates:\n",
+              "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+              "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+              "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+              "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+              "  * beam                 (beam) int32 16B 1 2 3 4\n",
+              "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
+              "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
+              "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
+              "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
+              "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+              "  * x1                   (x1) int32 16B 1 2 3 4\n",
+              "  * x2                   (x2) int32 16B 1 2 3 4\n",
+              "Data variables: (12/38)\n",
+              "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+              "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+              "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+              "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+              "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+              "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+              "    ...                   ...\n",
+              "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+              "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+              "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+              "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+              "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+              "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
+              "Attributes: (12/34)\n",
+              "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
+              "    inst_model:            Signature1000\n",
+              "    inst_make:             Nortek\n",
+              "    inst_type:             ADCP\n",
+              "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
+              "    n_cells:               28\n",
+              "    ...                    ...\n",
+              "    proc_idle_less_12pct:  0\n",
+              "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
+              "    coord_sys:             earth\n",
+              "    fs:                    1\n",
+              "    has_imu:               1\n",
+              "    beam_angle:            25"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "# print the dataset\n",
+        "ds"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "vel = ds[\"vel\"]\n",
-    "\n",
-    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
-    "labels = vel.coords[vel_dim].values\n",
-    "\n",
-    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
-    "\n",
-    "if len(labels) == 1:\n",
-    "    axes = [axes]\n",
-    "\n",
-    "for ax_i, label in zip(axes, labels):\n",
-    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
-    "    values = values[np.isfinite(values)]\n",
-    "\n",
-    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
-    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
-    "    ax_i.set_ylabel(\"Count\")\n",
-    "\n",
-    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 2. Initial Steps for Data Quality Control (QC)\n",
-    "\n",
-    "### 2.1: Set the Deployment Height\n",
-    "\n",
-    "When using Nortek instruments, the deployment software does not factor in the deployment height. The deployment height represents the position of the Acoustic Doppler Current Profiler (ADCP) within the water column. \n",
-    "\n",
-    "In this context, the center of the first depth bin is situated at a distance that is the sum of three elements: \n",
-    "1. Deployment height (the ADCP's position in the water column)\n",
-    "2. Blanking distance (the minimum distance from the ADCP to the first measurement point)\n",
-    "3. Cell size (the vertical distance of each measurement bin in the water column)\n",
-    "\n",
-    "To ensure accurate readings, it is critical to calibrate the 'range' coordinate to make '0' correspond to either the seafloor or sea surface. This calibration can be achieved using the `set_range_offset` function. \n",
-    "\n",
-    "For those using a Teledyne RDI ADCP, the TRDI deployment software will prompt you to specify the deployment height/depth during setup in order to automatically calculate water depth. If there's a need for calibration post-deployment, the `set_range_offset` function can be utilized in the same way as described above to override the initially specified value."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1500x400 with 6 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "A second way provided to look at data is through the *DOLfYN view*. This view has several convenience methods, shortcuts, and functions built-in. It includes an alternate – and somewhat more informative/compact – description of the data object when in interactive mode. This can be accessed using"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
-    "\n",
-    "for i, ax in enumerate(axes):\n",
-    "    ds[\"vel\"][i].plot(ax=ax)\n",
-    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
-    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# The ADCP transducers were measured to be 0.6 m from the feet of the lander\n",
-    "api.clean.set_range_offset(ds, 0.6)"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "So, the center of bin 1 is located at 1.2 m, with a constant a 0.5m bin size. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<ADCP data object>:  Nortek Signature1000\n",
+              "  . 15.28 hours (started: Aug 15, 2020 00:20)\n",
+              "  . earth-frame\n",
+              "  . (55000 pings @ 1Hz)\n",
+              "  Variables:\n",
+              "  - time ('time',)\n",
+              "  - time_b5 ('time_b5',)\n",
+              "  - vel ('dir', 'range', 'time')\n",
+              "  - vel_b5 ('range_b5', 'time_b5')\n",
+              "  - range ('range',)\n",
+              "  - orientmat ('earth', 'inst', 'time')\n",
+              "  - heading ('time',)\n",
+              "  - pitch ('time',)\n",
+              "  - roll ('time',)\n",
+              "  - temp ('time',)\n",
+              "  - pressure ('time',)\n",
+              "  - amp ('beam', 'range', 'time')\n",
+              "  - amp_b5 ('range_b5', 'time_b5')\n",
+              "  - corr ('beam', 'range', 'time')\n",
+              "  - corr_b5 ('range_b5', 'time_b5')\n",
+              "  - accel ('dirIMU', 'time')\n",
+              "  - angrt ('dirIMU', 'time')\n",
+              "  - mag ('dirIMU', 'time')\n",
+              "  ... and others (see `<obj>.variables`)"
+            ]
+          },
+          "execution_count": 4,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "ds_dolfyn = ds.velds\n",
+        "ds_dolfyn"
+      ]
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "      Statistic  Value\n",
-      "0           min    1.2\n",
-      "1           max   14.7\n",
-      "2  mean spacing    0.5\n",
-      "3   max spacing    0.5\n",
-      "4   min spacing    0.5\n"
-     ]
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "One way to visualize this data is to plot the velocity in a histogram. This will highlight any outliers."
+      ]
     },
     {
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-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, white)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       "html[theme=\"dark\"],\n",
-       "html[data-theme=\"dark\"],\n",
-       "body[data-theme=\"dark\"],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, #111111)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "  line-height: 1.6;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-obj-name,\n",
-       ".xr-group-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name::before {\n",
-       "  content: \"📁\";\n",
-       "  padding-right: 0.3em;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name,\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
-       "  margin-block-start: 0;\n",
-       "  margin-block-end: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: inline-block;\n",
-       "  opacity: 0;\n",
-       "  height: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "  border: 2px solid transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:focus + label {\n",
-       "  border: 2px solid var(--xr-font-color0) !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: \"►\";\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: \"▼\";\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-top: 4px;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box {\n",
-       "  display: inline-grid;\n",
-       "  grid-template-columns: 0px 20px auto;\n",
-       "  width: 100%;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-vline {\n",
-       "  grid-column-start: 1;\n",
-       "  border-right: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "  width: 0px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-hline {\n",
-       "  grid-column-start: 2;\n",
-       "  grid-row-start: 1;\n",
-       "  height: 1em;\n",
-       "  width: 20px;\n",
-       "  border-bottom: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-contents {\n",
-       "  grid-column-start: 3;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: \"(\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: \")\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: \",\";\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  border-color: var(--xr-background-color-row-odd);\n",
-       "  margin-bottom: 0;\n",
-       "  padding-top: 2px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "  border-color: var(--xr-background-color-row-even);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  border-top: 2px dotted var(--xr-background-color);\n",
-       "  padding-bottom: 20px !important;\n",
-       "  padding-top: 10px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in + label,\n",
-       ".xr-var-data-in + label,\n",
-       ".xr-index-data-in + label {\n",
-       "  padding: 0 1px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > pre,\n",
-       ".xr-index-data > pre,\n",
-       ".xr-var-data > table > tbody > tr {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
-       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
-       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
-       "  color: var(--xr-font-color0);\n",
-       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
-       "  stroke-width: 0.8px;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt; Size: 224B\n",
-       "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])\n",
-       "Coordinates:\n",
-       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-       "Attributes:\n",
-       "    coverage_content_type:  coordinate\n",
-       "    units:                  m\n",
-       "    long_name:              Profile Range\n",
-       "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;range&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0025dbc2-44e5-46bc-869d-1190c9602df2' class='xr-array-in' type='checkbox' checked><label for='section-0025dbc2-44e5-46bc-869d-1190c9602df2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-96787b9e-7530-4068-862d-b28bdb67e527' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96787b9e-7530-4068-862d-b28bdb67e527' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-39f56f30-fd1a-4676-84cb-9afcfd108d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39f56f30-fd1a-4676-84cb-9afcfd108d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b45e0c4-31f4-4b55-b573-dfb44456c555' class='xr-var-data-in' type='checkbox'><label for='data-5b45e0c4-31f4-4b55-b573-dfb44456c555' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fb59eb1-0655-463e-9953-677ac4364339' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8fb59eb1-0655-463e-9953-677ac4364339' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 800x800 with 4 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
       ],
-      "text/plain": [
-       "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
-       "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])\n",
-       "Coordinates:\n",
-       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-       "Attributes:\n",
-       "    coverage_content_type:  coordinate\n",
-       "    units:                  m\n",
-       "    long_name:              Profile Range\n",
-       "    description:            Distance to the center of each depth bin"
+      "source": [
+        "vel = ds[\"vel\"]\n",
+        "\n",
+        "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+        "labels = vel.coords[vel_dim].values\n",
+        "\n",
+        "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 2 * len(labels)), sharex=True)\n",
+        "\n",
+        "if len(labels) == 1:\n",
+        "    axes = [axes]\n",
+        "\n",
+        "for ax_i, label in zip(axes, labels):\n",
+        "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+        "    values = values[np.isfinite(values)]\n",
+        "\n",
+        "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+        "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+        "    ax_i.set_ylabel(\"Count\")\n",
+        "\n",
+        "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+        "plt.tight_layout()"
       ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "range_da = ds[\"range\"]\n",
-    "spacing = range_da.diff(\"range\")\n",
-    "\n",
-    "range_stats = pd.DataFrame(\n",
-    "    {\n",
-    "        \"Statistic\": [\"min\", \"max\", \"mean spacing\", \"max spacing\", \"min spacing\"],\n",
-    "        \"Value\": [\n",
-    "            float(range_da.min().values),\n",
-    "            float(range_da.max().values),\n",
-    "            float(spacing.mean().values),\n",
-    "            float(spacing.max().values),\n",
-    "            float(spacing.min().values),\n",
-    "        ],\n",
-    "    }\n",
-    ")\n",
-    "\n",
-    "print(range_stats)\n",
-    "ds.range"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 2.2. Discard Data Above Surface Level and Surface Interference\n",
-    "\n",
-    "To reduce computational load, we can exclude all data at or above the water surface level, including that affected by surface interference. Since the instrument was oriented upwards, we can utilize the pressure sensor data along with the function `water_depth_from_pressure` to find the water depth. However, this approach necessitates that the pressure sensor was calibrated or 'zeroed' prior to deployment. If the instrument is facing downwards or doesn't include pressure data, the function `water_depth_from_amplitude` can be used to detect the seabed or water surface.\n",
-    "\n",
-    "It's important to note that Acoustic Doppler Current Profilers (ADCPs) do not measure water salinity, so you'll need to supply this information to the function. If `water_depth_from_pressure` is called after `set_range_offset`, \"depth\" represents the distance from the water surface to the seafloor. Otherwise, it indicates the distance to the ADCP pressure sensor.\n",
-    "\n",
-    "After determining the \"depth\", you can use the `remove_surface_interference` function to discard data in depth bins at or above the actual water surface. Be aware that this function will generate a new dataset."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "api.clean.water_depth_from_pressure(ds, salinity=31)\n",
-    "ds = api.clean.remove_surface_interference(ds)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
+    },
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-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
-       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
-       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
-       "  color: var(--xr-font-color0);\n",
-       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
-       "  stroke-width: 0.8px;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 84MB\n",
-       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-       "                          x1: 4, x2: 4)\n",
-       "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-       "  * range                (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-       "  * range_b5             (range_b5) float64 224B 1.2 1.7 2.2 ... 13.7 14.2 14.7\n",
-       "  * beam                 (beam) int32 16B 1 2 3 4\n",
-       "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
-       "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-       "  * x1                   (x1) int32 16B 1 2 3 4\n",
-       "  * x2                   (x2) int32 16B 1 2 3 4\n",
-       "Data variables: (12/40)\n",
-       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-       "    ...                   ...\n",
-       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-       "    water_density        (time) float32 220kB 1.023e+03 1.023e+03 ... 1.023e+03\n",
-       "    depth                (time) float32 220kB 10.28 10.28 10.28 ... 10.16 10.16\n",
-       "Attributes: (12/35)\n",
-       "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
-       "    inst_model:            Signature1000\n",
-       "    inst_make:             Nortek\n",
-       "    inst_type:             ADCP\n",
-       "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
-       "    n_cells:               28\n",
-       "    ...                    ...\n",
-       "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, ...\n",
-       "    coord_sys:             earth\n",
-       "    fs:                    1\n",
-       "    has_imu:               1\n",
-       "    beam_angle:            25\n",
-       "    range_offset:          0.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3b60b78a-3f53-4327-82a3-47a9d97f6e5a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3b60b78a-3f53-4327-82a3-47a9d97f6e5a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3f52280c-ae51-4cbf-8f2d-6ff8e1f0fe68' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f52280c-ae51-4cbf-8f2d-6ff8e1f0fe68' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-d32184a9-e33e-415d-a267-542d575c5d56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d32184a9-e33e-415d-a267-542d575c5d56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c042bb9-eec0-4f21-a04d-80f9c3b639a9' class='xr-var-data-in' type='checkbox'><label for='data-3c042bb9-eec0-4f21-a04d-80f9c3b639a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
-       "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
-       "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-10c3d059-5fe5-4ed8-b774-8ecde1198f83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10c3d059-5fe5-4ed8-b774-8ecde1198f83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f4aefa7-2f3b-4387-a78d-fb6723e950a4' class='xr-var-data-in' type='checkbox'><label for='data-0f4aefa7-2f3b-4387-a78d-fb6723e950a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
-       "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
-       "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-       "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-5123f094-c771-40ba-a455-89a460000c29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5123f094-c771-40ba-a455-89a460000c29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f100808e-89c5-4611-974e-89ef10c1e3be' class='xr-var-data-in' type='checkbox'><label for='data-f100808e-89c5-4611-974e-89ef10c1e3be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-d2b47560-9f68-4ddb-9a71-3ae9f877d158' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2b47560-9f68-4ddb-9a71-3ae9f877d158' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ca236a9-821c-46ff-9074-9bddcaa9797b' class='xr-var-data-in' type='checkbox'><label for='data-1ca236a9-821c-46ff-9074-9bddcaa9797b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c439419b-bb03-4daa-9197-a89297d44810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c439419b-bb03-4daa-9197-a89297d44810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-528c857c-7fe8-424c-96b7-5d14b78688a6' class='xr-var-data-in' type='checkbox'><label for='data-528c857c-7fe8-424c-96b7-5d14b78688a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-f1876829-2a3b-4840-9014-19e6e4fd0fc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1876829-2a3b-4840-9014-19e6e4fd0fc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dcce187-8c0c-4dd4-b3fc-6db7314b2437' class='xr-var-data-in' type='checkbox'><label for='data-0dcce187-8c0c-4dd4-b3fc-6db7314b2437' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-aeb36c82-1db9-4419-a089-2f58994b6a0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aeb36c82-1db9-4419-a089-2f58994b6a0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d01d9df4-a49c-4a85-b93f-74a933c67353' class='xr-var-data-in' type='checkbox'><label for='data-d01d9df4-a49c-4a85-b93f-74a933c67353' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-9468b964-5319-40c6-9699-6a3dbed6dcc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9468b964-5319-40c6-9699-6a3dbed6dcc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e43fe00-ab16-4cba-8535-8c975cc836bc' class='xr-var-data-in' type='checkbox'><label for='data-2e43fe00-ab16-4cba-8535-8c975cc836bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-ad5d3f7c-a552-483c-a8a2-dfcabfad2057' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad5d3f7c-a552-483c-a8a2-dfcabfad2057' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11104ddf-2608-4dbe-a625-314637bc4e76' class='xr-var-data-in' type='checkbox'><label for='data-11104ddf-2608-4dbe-a625-314637bc4e76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-f405fe50-ee5c-4064-b0fe-fcac0cea48ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f405fe50-ee5c-4064-b0fe-fcac0cea48ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88b0b5d0-6b0e-4181-a479-40472eabdfdb' class='xr-var-data-in' type='checkbox'><label for='data-88b0b5d0-6b0e-4181-a479-40472eabdfdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-e00a9ca5-e0f8-49da-89ce-f4c7b4e16384' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e00a9ca5-e0f8-49da-89ce-f4c7b4e16384' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c82fe9d4-d230-49cf-89ea-fb7df701c364' class='xr-var-data-in' type='checkbox'><label for='data-c82fe9d4-d230-49cf-89ea-fb7df701c364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-2bf2d2de-3964-4652-b831-2d5fee0968e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bf2d2de-3964-4652-b831-2d5fee0968e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83556ad2-333b-4d99-9c32-d8f485a2ef34' class='xr-var-data-in' type='checkbox'><label for='data-83556ad2-333b-4d99-9c32-d8f485a2ef34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da3721f7-23f0-41c7-befb-6a8e5d98d95f' class='xr-section-summary-in' type='checkbox'  ><label for='section-da3721f7-23f0-41c7-befb-6a8e5d98d95f' class='xr-section-summary' >Data variables: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-04b9eee2-42a0-4d5e-a5d0-de155c7b5c8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04b9eee2-42a0-4d5e-a5d0-de155c7b5c8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b05b2969-59cc-44c3-b89f-d4699f952d17' class='xr-var-data-in' type='checkbox'><label for='data-b05b2969-59cc-44c3-b89f-d4699f952d17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-9b5a6f5d-a7e6-45a6-9f2c-78360b5409ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b5a6f5d-a7e6-45a6-9f2c-78360b5409ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9859d01e-5e61-4d51-9e26-010178406e63' class='xr-var-data-in' type='checkbox'><label for='data-9859d01e-5e61-4d51-9e26-010178406e63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-e360df77-6724-4a52-9fae-09981e6dae73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e360df77-6724-4a52-9fae-09981e6dae73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-210923cc-88d8-4b0e-b8dc-4eb97348da0f' class='xr-var-data-in' type='checkbox'><label for='data-210923cc-88d8-4b0e-b8dc-4eb97348da0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-8a7a903a-315c-4813-a33b-c1632e40fbc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a7a903a-315c-4813-a33b-c1632e40fbc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96153423-1386-4f28-90bc-0bd9ab38e2a5' class='xr-var-data-in' type='checkbox'><label for='data-96153423-1386-4f28-90bc-0bd9ab38e2a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
-       "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
-       "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-9ed21429-a052-4aa8-815a-950403f7096b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ed21429-a052-4aa8-815a-950403f7096b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64c500dd-9770-449a-8680-ccf78a2d64b0' class='xr-var-data-in' type='checkbox'><label for='data-64c500dd-9770-449a-8680-ccf78a2d64b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
-       "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
-       "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
-       "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
-       "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
-       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-6ce9ff5b-9dfb-4f40-b945-955d259824d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ce9ff5b-9dfb-4f40-b945-955d259824d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc3cca79-0257-4108-80db-6152c622a3d7' class='xr-var-data-in' type='checkbox'><label for='data-cc3cca79-0257-4108-80db-6152c622a3d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-98553162-8a44-4687-b531-88b59e511042' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98553162-8a44-4687-b531-88b59e511042' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-facb0350-434c-40d8-80ec-e03b7a36b532' class='xr-var-data-in' type='checkbox'><label for='data-facb0350-434c-40d8-80ec-e03b7a36b532' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-7058c137-8eb9-439f-9a9c-0a1bb3e7dd69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7058c137-8eb9-439f-9a9c-0a1bb3e7dd69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33e065bd-98a4-4713-bf62-adb0604678d7' class='xr-var-data-in' type='checkbox'><label for='data-33e065bd-98a4-4713-bf62-adb0604678d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-7bcdef99-2f89-4fd7-9b7a-d7a70bc15cac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bcdef99-2f89-4fd7-9b7a-d7a70bc15cac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0237d5dc-01db-489e-ade7-2917e695935e' class='xr-var-data-in' type='checkbox'><label for='data-0237d5dc-01db-489e-ade7-2917e695935e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-3d316c65-e7b9-4c3b-b6fb-82f11f6bf5ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d316c65-e7b9-4c3b-b6fb-82f11f6bf5ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c38da9c-25a1-4552-b304-7a478e4d0fc5' class='xr-var-data-in' type='checkbox'><label for='data-6c38da9c-25a1-4552-b304-7a478e4d0fc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 0.008 ... nan nan nan</div><input id='attrs-5eb905c4-9c12-48f9-90ee-048dc17c61f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eb905c4-9c12-48f9-90ee-048dc17c61f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef4d0a60-551a-4545-8c7b-64f1af4ed635' class='xr-var-data-in' type='checkbox'><label for='data-ef4d0a60-551a-4545-8c7b-64f1af4ed635' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
-       "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
-       "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
-       "        ...,\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
-       "\n",
-       "       [[ 0.243,  0.204,  0.234, ..., -0.163, -0.135, -0.18 ],\n",
-       "        [ 0.272,  0.248,  0.236, ..., -0.254, -0.169, -0.204],\n",
-       "        [ 0.257,  0.294,  0.333, ..., -0.299, -0.226, -0.273],\n",
-       "        ...,\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
-       "\n",
-       "       [[ 0.016,  0.012,  0.01 , ...,  0.009,  0.006, -0.018],\n",
-       "        [ 0.01 ,  0.011, -0.013, ...,  0.002, -0.027,  0.009],\n",
-       "        [ 0.01 ,  0.009,  0.023, ..., -0.018, -0.002, -0.024],\n",
-       "        ...,\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
-       "\n",
-       "       [[ 0.003, -0.007,  0.046, ..., -0.032, -0.008, -0.029],\n",
-       "        [ 0.017,  0.033,  0.035, ..., -0.016, -0.022, -0.034],\n",
-       "        [ 0.016, -0.012,  0.005, ...,  0.002, -0.045, -0.026],\n",
-       "        ...,\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]]],\n",
-       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 80.5 ... nan nan nan</div><input id='attrs-3a562ab9-056c-4a92-b02c-d12df5163082' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a562ab9-056c-4a92-b02c-d12df5163082' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fa31852-2f6d-4bb3-ae20-b9dd4edea08b' class='xr-var-data-in' type='checkbox'><label for='data-9fa31852-2f6d-4bb3-ae20-b9dd4edea08b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
-       "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
-       "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
-       "        ...,\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[81.5, 80. , 80.5, ..., 82. , 81.5, 82. ],\n",
-       "        [76. , 77. , 76.5, ..., 79. , 77.5, 77.5],\n",
-       "        [73.5, 74. , 73. , ..., 75.5, 74.5, 74.5],\n",
-       "        ...,\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[80.5, 79.5, 80. , ..., 81.5, 82.5, 81.5],\n",
-       "        [76. , 75.5, 75. , ..., 77. , 78.5, 77. ],\n",
-       "        [72. , 73.5, 72. , ..., 74. , 75. , 73.5],\n",
-       "        ...,\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "\n",
-       "       [[80. , 81. , 80. , ..., 81. , 81. , 81.5],\n",
-       "        [75.5, 75.5, 74.5, ..., 76.5, 76.5, 77.5],\n",
-       "        [73. , 72.5, 73. , ..., 75.5, 74.5, 74. ],\n",
-       "        ...,\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]],\n",
-       "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 87 ... 0 0 0 0 0 0</div><input id='attrs-519d184f-8ef3-45d7-b919-9e3120f09459' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-519d184f-8ef3-45d7-b919-9e3120f09459' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7f62e0a-8031-4949-984f-8c851c9ef55f' class='xr-var-data-in' type='checkbox'><label for='data-e7f62e0a-8031-4949-984f-8c851c9ef55f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
-       "        [ 74,  92,  96, ..., 100,  97, 100],\n",
-       "        [100, 100,  99, ...,  99, 100, 100],\n",
-       "        ...,\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
-       "\n",
-       "       [[ 94,  90,  89, ...,  91,  92,  90],\n",
-       "        [ 94, 100, 100, ...,  96, 100,  93],\n",
-       "        [ 99,  95,  97, ...,  98,  98, 100],\n",
-       "        ...,\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
-       "\n",
-       "       [[ 92,  93,  93, ...,  93,  97,  89],\n",
-       "        [ 99, 100,  99, ...,  96,  88,  98],\n",
-       "        [ 97, 100,  98, ..., 100,  99,  97],\n",
-       "        ...,\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0]],\n",
-       "\n",
-       "       [[ 87,  97,  87, ...,  91,  87,  90],\n",
-       "        [100,  93,  93, ...,  96,  96,  97],\n",
-       "        [100, 100, 100, ..., 100, 100,  97],\n",
-       "        ...,\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0],\n",
-       "        [  0,   0,   0, ...,   0,   0,   0]]],\n",
-       "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-fac58596-809d-4cd2-842d-938f8aa3b158' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fac58596-809d-4cd2-842d-938f8aa3b158' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c97b617-4b4a-4164-a3f1-a73476706a9c' class='xr-var-data-in' type='checkbox'><label for='data-3c97b617-4b4a-4164-a3f1-a73476706a9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
-       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-       "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
-       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-       "        [-1.22870505e-03, -1.20262802e-03, -1.17563456e-03, ...,\n",
-       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04]],\n",
-       "\n",
-       "       [[-9.67970312e-01, -9.68004048e-01, -9.67982769e-01, ...,\n",
-       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-       "        [-2.15024590e-01, -2.14734554e-01, -2.14924574e-01, ...,\n",
-       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-       "        [-1.29278094e-01, -1.29190803e-01, -1.29239410e-01, ...,\n",
-       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01]],\n",
-       "\n",
-       "       [[-1.26469478e-01, -1.26385525e-01, -1.26422524e-01, ...,\n",
-       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01],\n",
-       "        [-2.68291458e-02, -2.68030688e-02, -2.68616974e-02, ...,\n",
-       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
-       "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
-       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-f36da3b8-6c54-471a-977b-a2b10de919ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f36da3b8-6c54-471a-977b-a2b10de919ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43b7c30c-4401-4da9-a124-fcc8d894aa8a' class='xr-var-data-in' type='checkbox'><label for='data-43b7c30c-4401-4da9-a124-fcc8d894aa8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
-       "        -0.00292969, -0.00195312],\n",
-       "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
-       "         0.00097656,  0.00097656],\n",
-       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-ea338374-0cc4-47a6-9dd3-24e7a1907d42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea338374-0cc4-47a6-9dd3-24e7a1907d42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f238500-68d7-47bb-a9f9-614c1bbdb632' class='xr-var-data-in' type='checkbox'><label for='data-3f238500-68d7-47bb-a9f9-614c1bbdb632' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
-       "         0.6247864 ,  0.62490845],\n",
-       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-       "        -0.03564453, -0.03561401],\n",
-       "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
-       "        -0.04360962, -0.04360962],\n",
-       "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-49e97b68-5f8b-4e1a-b389-b7cf4c92156b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49e97b68-5f8b-4e1a-b389-b7cf4c92156b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f25b32ea-65d7-4c86-950d-3cb3f06879af' class='xr-var-data-in' type='checkbox'><label for='data-f25b32ea-65d7-4c86-950d-3cb3f06879af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-208a71ef-adba-43f9-a333-ca1de21ca2b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-208a71ef-adba-43f9-a333-ca1de21ca2b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cf8e297-7cf9-4173-8e1f-a242c5c4275a' class='xr-var-data-in' type='checkbox'><label for='data-6cf8e297-7cf9-4173-8e1f-a242c5c4275a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-988dff58-bb78-4b41-b1fc-2145643890a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-988dff58-bb78-4b41-b1fc-2145643890a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28973660-cf4b-4d55-8108-3e0425072873' class='xr-var-data-in' type='checkbox'><label for='data-28973660-cf4b-4d55-8108-3e0425072873' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
-       "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
-       "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-15d6f924-114e-4bf5-be69-8f81b4640295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15d6f924-114e-4bf5-be69-8f81b4640295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7986dd8-1046-4e66-acb4-1672df68237d' class='xr-var-data-in' type='checkbox'><label for='data-f7986dd8-1046-4e66-acb4-1672df68237d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
-       "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
-       "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
-       "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
-       "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
-       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
-       "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-c7ccfee5-07eb-4fd7-bfb8-7be1b0262b62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7ccfee5-07eb-4fd7-bfb8-7be1b0262b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a141cd7-21aa-48f5-9dc7-3c1a46a6469d' class='xr-var-data-in' type='checkbox'><label for='data-5a141cd7-21aa-48f5-9dc7-3c1a46a6469d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-c18b3666-f050-4de7-b8d1-3df520752621' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c18b3666-f050-4de7-b8d1-3df520752621' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42765d09-47dd-49ed-a8c5-9aa5b63de351' class='xr-var-data-in' type='checkbox'><label for='data-42765d09-47dd-49ed-a8c5-9aa5b63de351' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-2297a980-4a57-41c7-97a4-a0d166f7cd2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2297a980-4a57-41c7-97a4-a0d166f7cd2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32b27170-8cb1-42a9-a1a3-116a4f2dd113' class='xr-var-data-in' type='checkbox'><label for='data-32b27170-8cb1-42a9-a1a3-116a4f2dd113' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-       "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... nan nan nan</div><input id='attrs-14ccc856-4363-425d-944d-65678f7370b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14ccc856-4363-425d-944d-65678f7370b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9305015-3a1d-40be-b68d-e6a0dc00cada' class='xr-var-data-in' type='checkbox'><label for='data-c9305015-3a1d-40be-b68d-e6a0dc00cada' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
-       "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
-       "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
-       "       ...,\n",
-       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
-       "       [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
-       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 80.5 ... nan nan nan</div><input id='attrs-e7b1334d-b840-4797-a987-e2141dd2cef4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7b1334d-b840-4797-a987-e2141dd2cef4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e71dd98-e434-4165-b485-bbc4c3c9bce9' class='xr-var-data-in' type='checkbox'><label for='data-0e71dd98-e434-4165-b485-bbc4c3c9bce9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
-       "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
-       "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
-       "       ...,\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
-       "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 100 ... 0 0 0 0 0 0</div><input id='attrs-1f747258-8108-4ae0-9c50-202c7e96b587' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f747258-8108-4ae0-9c50-202c7e96b587' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cd3b67b-c20e-45dc-8c6b-bb769c506bf2' class='xr-var-data-in' type='checkbox'><label for='data-6cd3b67b-c20e-45dc-8c6b-bb769c506bf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
-       "       [ 97,  94,  98, ...,  97,  95,  97],\n",
-       "       [100, 100, 100, ...,  93, 100,  96],\n",
-       "       ...,\n",
-       "       [  0,   0,   0, ...,   0,   0,   0],\n",
-       "       [  0,   0,   0, ...,   0,   0,   0],\n",
-       "       [  0,   0,   0, ...,   0,   0,   0]],\n",
-       "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-6aa40778-97f4-43c9-ae4c-f41d70238179' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aa40778-97f4-43c9-ae4c-f41d70238179' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8026d2f-c8d4-4aee-b62b-eaf6ca504e0a' class='xr-var-data-in' type='checkbox'><label for='data-c8026d2f-c8d4-4aee-b62b-eaf6ca504e0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
-       "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
-       "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
-       "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
-       "        [-1.26507595e-01, -1.26426160e-01, -1.26425594e-01, ...,\n",
-       "         -1.10033900e-01, -1.10009573e-01, -1.09963998e-01]],\n",
-       "\n",
-       "       [[ 9.76198971e-01,  9.76259708e-01,  9.76250350e-01, ...,\n",
-       "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
-       "        [-2.15024590e-01, -2.14829564e-01, -2.14924574e-01, ...,\n",
-       "         -2.14874983e-01, -2.15436578e-01, -2.15052128e-01],\n",
-       "        [-2.68766508e-02, -2.68536285e-02, -2.68591940e-02, ...,\n",
-       "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02]],\n",
-       "\n",
-       "       [[-1.19058788e-03, -1.16700679e-03, -1.17257237e-03, ...,\n",
-       "         -1.16243958e-03, -1.02279335e-03, -9.55920666e-04],\n",
-       "        [-1.29325598e-01, -1.29241347e-01, -1.29241914e-01, ...,\n",
-       "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
-       "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
-       "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-3e99d3c9-0836-45b6-8c19-5a576c25383e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e99d3c9-0836-45b6-8c19-5a576c25383e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b20520f-b4ac-42f0-9873-501e3df0f90a' class='xr-var-data-in' type='checkbox'><label for='data-5b20520f-b4ac-42f0-9873-501e3df0f90a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
-       "        -0.00195312, -0.00390625],\n",
-       "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
-       "         0.        ,  0.00097656],\n",
-       "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-cc7659cd-127d-486e-ad9b-4b48e25bccbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc7659cd-127d-486e-ad9b-4b48e25bccbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbbae1d3-38b0-44e0-bf12-c4fa3b75e199' class='xr-var-data-in' type='checkbox'><label for='data-cbbae1d3-38b0-44e0-bf12-c4fa3b75e199' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
-       "         0.6247864 ,  0.62490845],\n",
-       "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
-       "        -0.03564453, -0.03561401],\n",
-       "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
-       "        -0.04360962, -0.04360962],\n",
-       "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-b97d1d40-0461-49a0-bdfc-858bf0e2107b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b97d1d40-0461-49a0-bdfc-858bf0e2107b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23eb80ae-40f4-458c-86de-996156fedae8' class='xr-var-data-in' type='checkbox'><label for='data-23eb80ae-40f4-458c-86de-996156fedae8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-db59adea-502a-4e93-b075-862d98d07eca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db59adea-502a-4e93-b075-862d98d07eca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb33cc15-3200-45c2-801c-97bd960b6d6e' class='xr-var-data-in' type='checkbox'><label for='data-eb33cc15-3200-45c2-801c-97bd960b6d6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-ec918346-f32c-49af-a738-a2176994dfcd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec918346-f32c-49af-a738-a2176994dfcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14c6370c-8658-4a0f-89d1-f8414e1af492' class='xr-var-data-in' type='checkbox'><label for='data-14c6370c-8658-4a0f-89d1-f8414e1af492' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-01031b8b-3f17-4723-9007-125ece6930f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01031b8b-3f17-4723-9007-125ece6930f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85e56225-bd35-4432-aa43-b40cff669b8d' class='xr-var-data-in' type='checkbox'><label for='data-85e56225-bd35-4432-aa43-b40cff669b8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-97a64000-ff17-4b02-9bd3-3910113c801e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-97a64000-ff17-4b02-9bd3-3910113c801e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bba3ff1c-4b69-4066-ac3c-d43a5be0bc21' class='xr-var-data-in' type='checkbox'><label for='data-bba3ff1c-4b69-4066-ac3c-d43a5be0bc21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-50cb20ba-8ec8-4267-81cb-d7ef32bb0b4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50cb20ba-8ec8-4267-81cb-d7ef32bb0b4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7783dd55-36bd-42bd-888d-994093bed229' class='xr-var-data-in' type='checkbox'><label for='data-7783dd55-36bd-42bd-888d-994093bed229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-       "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-2a60a58f-c1cb-4eb8-8c3c-58a6a6500ec7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a60a58f-c1cb-4eb8-8c3c-58a6a6500ec7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b80099b0-39db-4ae0-8da0-e5b94f8cdf41' class='xr-var-data-in' type='checkbox'><label for='data-b80099b0-39db-4ae0-8da0-e5b94f8cdf41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
-       "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-ee7339f8-c6b7-4eb1-a036-bbc09bd2e808' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee7339f8-c6b7-4eb1-a036-bbc09bd2e808' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a88c998-b634-4f80-b754-68f424c8f2e4' class='xr-var-data-in' type='checkbox'><label for='data-6a88c998-b634-4f80-b754-68f424c8f2e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-       "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-0e526501-0f6f-4ee2-9d4a-e25e81ded0bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e526501-0f6f-4ee2-9d4a-e25e81ded0bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-795ecf6d-5e93-45c9-a54e-6a4ab24ec042' class='xr-var-data-in' type='checkbox'><label for='data-795ecf6d-5e93-45c9-a54e-6a4ab24ec042' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
-       "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
-       "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-016e0ef0-2457-44cb-b074-88412c61be7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-016e0ef0-2457-44cb-b074-88412c61be7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea536dce-62be-4334-8a4f-ec284ea5ea34' class='xr-var-data-in' type='checkbox'><label for='data-ea536dce-62be-4334-8a4f-ec284ea5ea34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2412 , 1023.2412 , 1023.2412 , ..., 1023.40265, 1023.40265,\n",
-       "       1023.40265], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.28 10.28 ... 10.16 10.16</div><input id='attrs-acaba087-0262-4545-8841-a7c3b4528202' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acaba087-0262-4545-8841-a7c3b4528202' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c149786-bee8-4e55-91c6-288e974957ba' class='xr-var-data-in' type='checkbox'><label for='data-9c149786-bee8-4e55-91c6-288e974957ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.276234, 10.281216, 10.281216, ..., 10.158169, 10.156177,\n",
-       "       10.158169], shape=(55000,), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d3aa7b58-2604-474f-b39a-1f7654920867' class='xr-section-summary-in' type='checkbox'  ><label for='section-d3aa7b58-2604-474f-b39a-1f7654920867' class='xr-section-summary' >Attributes: <span>(35)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd></dl></div></li></ul></div></div>"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "And the raw velocity profile data:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1500x400 with 6 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
       ],
-      "text/plain": [
-       "<xarray.Dataset> Size: 84MB\n",
-       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
-       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
-       "                          x1: 4, x2: 4)\n",
-       "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
-       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
-       "  * range                (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-       "  * range_b5             (range_b5) float64 224B 1.2 1.7 2.2 ... 13.7 14.2 14.7\n",
-       "  * beam                 (beam) int32 16B 1 2 3 4\n",
-       "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
-       "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
-       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
-       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
-       "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
-       "  * x1                   (x1) int32 16B 1 2 3 4\n",
-       "  * x2                   (x2) int32 16B 1 2 3 4\n",
-       "Data variables: (12/40)\n",
-       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
-       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
-       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
-       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
-       "    ...                   ...\n",
-       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
-       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
-       "    water_density        (time) float32 220kB 1.023e+03 1.023e+03 ... 1.023e+03\n",
-       "    depth                (time) float32 220kB 10.28 10.28 10.28 ... 10.16 10.16\n",
-       "Attributes: (12/35)\n",
-       "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
-       "    inst_model:            Signature1000\n",
-       "    inst_make:             Nortek\n",
-       "    inst_type:             ADCP\n",
-       "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
-       "    n_cells:               28\n",
-       "    ...                    ...\n",
-       "    rotate_vars:           ['vel', 'accel', 'accel_b5', 'angrt', 'angrt_b5', ...\n",
-       "    coord_sys:             earth\n",
-       "    fs:                    1\n",
-       "    has_imu:               1\n",
-       "    beam_angle:            25\n",
-       "    range_offset:          0.6"
+      "source": [
+        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+        "\n",
+        "for i, ax in enumerate(axes):\n",
+        "    ds[\"vel\"][i].plot(ax=ax, vmin=-1.5, vmax=1.5, cmap=\"RdBu_r\")\n",
+        "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+        "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+        "\n",
+        "plt.tight_layout()"
       ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ds"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Visualizing the Depth from the ADCP pressure sensor. This measurement includes any previously applied range offsets. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x249c4ff40e0>]"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 2. Initial Steps for Data Quality Control (QC)\n",
+        "\n",
+        "### 2.1: Set the Deployment Height\n",
+        "\n",
+        "When using Nortek instruments, the deployment software does not factor in the deployment height. The deployment height represents the position of the Acoustic Doppler Current Profiler (ADCP) within the water column. \n",
+        "\n",
+        "In this context, the center of the first depth bin is situated at a distance that is the sum of three elements: \n",
+        "1. Deployment height (the ADCP's position in the water column)\n",
+        "2. Blanking distance (the minimum distance from the ADCP to the first measurement point)\n",
+        "3. Cell size (the vertical distance of each measurement bin in the water column)\n",
+        "\n",
+        "To ensure accurate readings, it is critical to calibrate the 'range' coordinate to make '0' correspond to either the seafloor or sea surface. This calibration can be achieved using the `set_range_offset` function. \n",
+        "\n",
+        "For those using a Teledyne RDI ADCP, the TRDI deployment software will prompt you to specify the deployment height/depth during setup in order to automatically calculate water depth. If there's a need for calibration post-deployment, the `set_range_offset` function can be utilized in the same way as described above to override the initially specified value."
       ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# The ADCP transducers were measured to be 0.6 m from the feet of the lander\n",
+        "api.clean.set_range_offset(ds, 0.6)"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ds[\"depth\"].plot()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Updated water velocity plots with data above the surface removed. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1500x400 with 6 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "So, the center of bin 1 is located at 1.2 m, with a constant 0.5 m bin size."
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
-    "\n",
-    "for i, ax in enumerate(axes):\n",
-    "    ds[\"vel\"][i].plot(ax=ax)\n",
-    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
-    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 2.3: Apply an Acoustic Signal Correlation Filter\n",
-    "\n",
-    "After removing data from bins at or above the water surface, we typically apply a filter based on acoustic signal correlation to the ADCP data. This helps to eliminate erroneous velocity data points, which can be caused by factors such as bubbles, kelp, fish, etc., moving through one or multiple beams.\n",
-    "\n",
-    "You can quickly inspect the data to determine an appropriate correlation value by using the built-in plotting feature of xarray. In the following example, we use xarray's slicing capabilities to display data from beam 1 within a range of 0 to 10 m from the ADCP.\n",
-    "\n",
-    "It's important to note that not all ADCPs provide acoustic signal correlation data, which serves as a quantitative measure of signal quality. Older ADCPs may not offer this feature, in which case you can skip this step when using such instruments."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1200x800 with 8 Axes>"
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "      Statistic  Value\n",
+            "0           min    1.2\n",
+            "1           max   14.7\n",
+            "2  mean spacing    0.5\n",
+            "3   max spacing    0.5\n",
+            "4   min spacing    0.5\n"
+          ]
+        },
+        {
+          "data": {
+            "text/html": [
+              "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+              "<defs>\n",
+              "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+              "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "</symbol>\n",
+              "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+              "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "</symbol>\n",
+              "</defs>\n",
+              "</svg>\n",
+              "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+              "\n",
+              ":root {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, white)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              "html[theme=\"dark\"],\n",
+              "html[data-theme=\"dark\"],\n",
+              "body[data-theme=\"dark\"],\n",
+              "body.vscode-dark {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, #111111)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              ".xr-wrap {\n",
+              "  display: block !important;\n",
+              "  min-width: 300px;\n",
+              "  max-width: 700px;\n",
+              "  line-height: 1.6;\n",
+              "}\n",
+              "\n",
+              ".xr-text-repr-fallback {\n",
+              "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-header {\n",
+              "  padding-top: 6px;\n",
+              "  padding-bottom: 6px;\n",
+              "  margin-bottom: 4px;\n",
+              "  border-bottom: solid 1px var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-header > div,\n",
+              ".xr-header > ul {\n",
+              "  display: inline;\n",
+              "  margin-top: 0;\n",
+              "  margin-bottom: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-obj-type,\n",
+              ".xr-obj-name,\n",
+              ".xr-group-name {\n",
+              "  margin-left: 2px;\n",
+              "  margin-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name::before {\n",
+              "  content: \"📁\";\n",
+              "  padding-right: 0.3em;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name,\n",
+              ".xr-obj-type {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-sections {\n",
+              "  padding-left: 0 !important;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+              "  margin-block-start: 0;\n",
+              "  margin-block-end: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input {\n",
+              "  display: inline-block;\n",
+              "  opacity: 0;\n",
+              "  height: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input + label {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "  border: 2px solid transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label {\n",
+              "  cursor: pointer;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:focus + label {\n",
+              "  border: 2px solid var(--xr-font-color0) !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label:hover {\n",
+              "  color: var(--xr-font-color0);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary {\n",
+              "  grid-column: 1;\n",
+              "  color: var(--xr-font-color2);\n",
+              "  font-weight: 500;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary > span {\n",
+              "  display: inline-block;\n",
+              "  padding-left: 0.5em;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in + label:before {\n",
+              "  display: inline-block;\n",
+              "  content: \"►\";\n",
+              "  font-size: 11px;\n",
+              "  width: 15px;\n",
+              "  text-align: center;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label:before {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label:before {\n",
+              "  content: \"▼\";\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label > span {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary,\n",
+              ".xr-section-inline-details {\n",
+              "  padding-top: 4px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-inline-details {\n",
+              "  grid-column: 2 / -1;\n",
+              "}\n",
+              "\n",
+              ".xr-section-details {\n",
+              "  display: none;\n",
+              "  grid-column: 1 / -1;\n",
+              "  margin-top: 4px;\n",
+              "  margin-bottom: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box {\n",
+              "  display: inline-grid;\n",
+              "  grid-template-columns: 0px 20px auto;\n",
+              "  width: 100%;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-vline {\n",
+              "  grid-column-start: 1;\n",
+              "  border-right: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "  width: 0px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-hline {\n",
+              "  grid-column-start: 2;\n",
+              "  grid-row-start: 1;\n",
+              "  height: 1em;\n",
+              "  width: 20px;\n",
+              "  border-bottom: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-contents {\n",
+              "  grid-column-start: 3;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap {\n",
+              "  grid-column: 1 / -1;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 20px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap > label {\n",
+              "  grid-column: 1;\n",
+              "  vertical-align: top;\n",
+              "}\n",
+              "\n",
+              ".xr-preview {\n",
+              "  color: var(--xr-font-color3);\n",
+              "}\n",
+              "\n",
+              ".xr-array-preview,\n",
+              ".xr-array-data {\n",
+              "  padding: 0 5px !important;\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-array-data,\n",
+              ".xr-array-in:checked ~ .xr-array-preview {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-array-in:checked ~ .xr-array-data,\n",
+              ".xr-array-preview {\n",
+              "  display: inline-block;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list {\n",
+              "  display: inline-block !important;\n",
+              "  list-style: none;\n",
+              "  padding: 0 !important;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li {\n",
+              "  display: inline-block;\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:before {\n",
+              "  content: \"(\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:after {\n",
+              "  content: \")\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li:not(:last-child):after {\n",
+              "  content: \",\";\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-has-index {\n",
+              "  font-weight: bold;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list,\n",
+              ".xr-var-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > div,\n",
+              ".xr-var-item label,\n",
+              ".xr-var-item > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-even);\n",
+              "  border-color: var(--xr-background-color-row-odd);\n",
+              "  margin-bottom: 0;\n",
+              "  padding-top: 2px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > .xr-var-name:hover span {\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list > li:nth-child(odd) > div,\n",
+              ".xr-var-list > li:nth-child(odd) > label,\n",
+              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-odd);\n",
+              "  border-color: var(--xr-background-color-row-even);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name {\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dims {\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dtype {\n",
+              "  grid-column: 3;\n",
+              "  text-align: right;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-preview {\n",
+              "  grid-column: 4;\n",
+              "}\n",
+              "\n",
+              ".xr-index-preview {\n",
+              "  grid-column: 2 / 5;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name,\n",
+              ".xr-var-dims,\n",
+              ".xr-var-dtype,\n",
+              ".xr-preview,\n",
+              ".xr-attrs dt {\n",
+              "  white-space: nowrap;\n",
+              "  overflow: hidden;\n",
+              "  text-overflow: ellipsis;\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name:hover,\n",
+              ".xr-var-dims:hover,\n",
+              ".xr-var-dtype:hover,\n",
+              ".xr-attrs dt:hover {\n",
+              "  overflow: visible;\n",
+              "  width: auto;\n",
+              "  z-index: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  display: none;\n",
+              "  border-top: 2px dotted var(--xr-background-color);\n",
+              "  padding-bottom: 20px !important;\n",
+              "  padding-top: 10px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in + label,\n",
+              ".xr-var-data-in + label,\n",
+              ".xr-index-data-in + label {\n",
+              "  padding: 0 1px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+              ".xr-var-data-in:checked ~ .xr-var-data,\n",
+              ".xr-index-data-in:checked ~ .xr-index-data {\n",
+              "  display: block;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > table {\n",
+              "  float: right;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > pre,\n",
+              ".xr-index-data > pre,\n",
+              ".xr-var-data > table > tbody > tr {\n",
+              "  background-color: transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name span,\n",
+              ".xr-var-data,\n",
+              ".xr-index-name div,\n",
+              ".xr-index-data,\n",
+              ".xr-attrs {\n",
+              "  padding-left: 25px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs,\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  grid-column: 1 / -1;\n",
+              "}\n",
+              "\n",
+              "dl.xr-attrs {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 125px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt,\n",
+              ".xr-attrs dd {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  float: left;\n",
+              "  padding-right: 10px;\n",
+              "  width: auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt {\n",
+              "  font-weight: normal;\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt:hover span {\n",
+              "  display: inline-block;\n",
+              "  background: var(--xr-background-color);\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dd {\n",
+              "  grid-column: 2;\n",
+              "  white-space: pre-wrap;\n",
+              "  word-break: break-all;\n",
+              "}\n",
+              "\n",
+              ".xr-icon-database,\n",
+              ".xr-icon-file-text2,\n",
+              ".xr-no-icon {\n",
+              "  display: inline-block;\n",
+              "  vertical-align: middle;\n",
+              "  width: 1em;\n",
+              "  height: 1.5em !important;\n",
+              "  stroke-width: 0;\n",
+              "  stroke: currentColor;\n",
+              "  fill: currentColor;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+              ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+              ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+              "  color: var(--xr-font-color0);\n",
+              "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+              "  stroke-width: 0.8px;\n",
+              "}\n",
+              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt; Size: 224B\n",
+              "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])\n",
+              "Coordinates:\n",
+              "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
+              "Attributes:\n",
+              "    coverage_content_type:  coordinate\n",
+              "    units:                  m\n",
+              "    long_name:              Profile Range\n",
+              "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;range&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b85c62e4-be8a-440b-addf-22e99b3732b2' class='xr-array-in' type='checkbox' checked><label for='section-b85c62e4-be8a-440b-addf-22e99b3732b2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-c504fe3a-f4c7-4797-a5b9-5ac1ab74105a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c504fe3a-f4c7-4797-a5b9-5ac1ab74105a' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-f9d5a0fa-ba71-4745-bd36-a3c8d5328790' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9d5a0fa-ba71-4745-bd36-a3c8d5328790' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff13e2db-7742-4ad3-841b-8f28d39417e1' class='xr-var-data-in' type='checkbox'><label for='data-ff13e2db-7742-4ad3-841b-8f28d39417e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e6e1bd8b-24b8-4ca5-a70a-da5da99210a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e6e1bd8b-24b8-4ca5-a70a-da5da99210a0' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
+            ],
+            "text/plain": [
+              "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
+              "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])\n",
+              "Coordinates:\n",
+              "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
+              "Attributes:\n",
+              "    coverage_content_type:  coordinate\n",
+              "    units:                  m\n",
+              "    long_name:              Profile Range\n",
+              "    description:            Distance to the center of each depth bin"
+            ]
+          },
+          "execution_count": 8,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "range_da = ds[\"range\"]\n",
+        "spacing = range_da.diff(\"range\")\n",
+        "\n",
+        "range_stats = pd.DataFrame(\n",
+        "    {\n",
+        "        \"Statistic\": [\"min\", \"max\", \"mean spacing\", \"max spacing\", \"min spacing\"],\n",
+        "        \"Value\": [\n",
+        "            float(range_da.min().values),\n",
+        "            float(range_da.max().values),\n",
+        "            float(spacing.mean().values),\n",
+        "            float(spacing.max().values),\n",
+        "            float(spacing.min().values),\n",
+        "        ],\n",
+        "    }\n",
+        ")\n",
+        "\n",
+        "print(range_stats)\n",
+        "ds.range"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "%matplotlib inline\n",
-    "fig, axes = plt.subplots(2, 2, figsize=(12, 8), sharex=True, sharey=True)\n",
-    "\n",
-    "for i, ax in enumerate(axes.ravel()):\n",
-    "    ds[\"corr\"].isel(beam=i).sel(range=slice(0, 10)).plot(ax=ax)\n",
-    "    ax.set_title(f\"Beam {int(ds['beam'].isel(beam=i).values)}\")\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "It's beneficial to also review data from the other beams. A significant portion of this data is of high quality. To avoid discarding valuable data with lower correlations, which could be due to natural variations, we can use the `correlation_filter`. This function assigns a value of NaN (not a number) to velocity values corresponding to correlations below 50%.\n",
-    "\n",
-    "However, it's important to note that the correlation threshold is dependent on the specifics of the deployment environment and the instrument used. It's not unusual to set a threshold as low as 30%, or even to forgo the use of this function entirely."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ds = api.clean.correlation_filter(ds, thresh=50)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Updated velocity plots filtered for beam correlation. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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Fs2HlOBER1aQSsmaVAyvHiYiIGglznIiIqHmNdo5fdNFFOProo3HkkUdiq622wpVXXql9glxzzTVrnScMQxxyyCE488wzMWfOHDQbVo4TEVFtwcFmVYiIiJoWc5yIiKh5jWaOe56Hxx57DHvttde/X8809fHDDz+81vnOOussTJw4EZ/5zGfQjNghJxEREREREREREdE4NDg4uNrjRCKhwxstW7ZMrwKfNGnSauPl8fPPP7/GZT/44IP44Q9/iCeeeALNileOExFRTaSDDcOscjBGvwOQPfbYo7JObxj222+/kWmOOOKINz3/oQ99iHueiIhazobIcSIiImqcHJ8+fTo6OjpGhvPOO68u65LL5fDpT38aV111FXp7e9GseOU4ERHVxLRMHaqaNjbXuwMQadtMKsYvvvhi7QDkhRde0Fu13uiWW27R27+G9fX1aachH//4x1ebTirDr7322pHHa/qlnIiIaLwb7RwnIiKixsrx+fPno729/S3Lwr29vbAsC4sXL15tvDyePHnym6Z/6aWXtCPO/ffff2RcFEX617ZtLcNvvPHGaHSsHCcioprU0uu1Eb+9DkCEVJLffvvt2gHISSed9Kbpu7u7V3t84403aochb6wclxOANQU6ERFRKxntHCciIqLGynGpGF+1cnxtXNfFTjvthHvuuQcHHnjgSGW3PD7++OPfNP0WW2yBp59+erVxp5xyil5Rfskll+gV682AleNERDTqYVxtG2fDHYCcfPLJNXUAsipp7+zggw9GJpNZbfx9992nV553dXXhAx/4AM4++2z09PRUtUwiIqLxgpXjREREzWu0c/yEE07A4Ycfjp133hlz587VO7nz+fzIxWuHHXYYpk2bpk2zSDOo22yzzWrzd3Z26t83jm9krBwnIqJRv43rjb8Yn3766TjjjDPq0gHIqqRt8meeeUYryN/YpMpBBx2E2bNn661f3/jGN7DvvvtqhbvcNkZERNQq2KwKERFR8xrtHP/kJz+JpUuX4rTTTsOiRYuwww474I477hgpo8+bN08vYBtPWDlORES1qeGXaqz8pbraNs7eLqkU33bbbfUX7lXJleTD5PnttttO2z6Tq8n33HPPUVkXIiKi8ZLjRERE1Do5fvzxx6+xGRUhZeh1ue6669BsxldVPxERjTrTMGCaVQ7G6m2cDQ/16gBkVXKrl7Q3/pnPfOYt38OcOXP0tV588cWa3jsREVEr5jgRERE1BuZ4/bFynIiIamJYZk1DLVbtAGTYcAcgu+666zrn/X//7/+hXC7j0EMPfcvXee2119DX14cpU6bUtH5ERETNbjRznIiIiEYXc7z+2KwKERHVxLQMHaqaNhrdDkDe2KSK9Kj9xk42h4aGcOaZZ+JjH/uYXn0ubY6feOKJ2GSTTbDPPvvUvH5ERETNbLRznIiIiEYPc7z+WDlORESj1zv2ehSq16cDkBdeeAEPPvgg7rrrrjctT5ppeeqpp/CjH/0I/f39mDp1Kvbee29861vfGrW2z4mIiFo1x4mIiGj0MMfrj5XjRERUk1puszYic4N0ALL55psjjuM1Tp9KpXDnnXeu13oQERGNNxsix4mIiGh0MMfrj5XjRERUE9Oq3MpV1bQRNy4REVEjYY4TERE1L+Z4/bFynIiIamKYhg7VTktERESNgzlORETUvJjj9Tem98k98MAD2H///bX9V8MwcNttt4085/s+vv71r2PbbbdFJpPRaaQTttdff30sV5mIqOVJe9+mVeXwhrbBaXxhjhMRNR/mOA1jjhMRNR/meP2Naa1FPp/H9ttvj8svv/xNzxUKBTz++OM49dRT9e8tt9yiHa4dcMABY7KuRES0egcg1Q40fjHHiYiaD3OchjHHiYiaD3N8nDWrsu++++qwJh0dHbj77rtXG/f9738fc+fOxbx58zBjxowNtJZERLTeHYBUOR01J+Y4EVHzYY7TMOY4EVHzYY63eJvjAwMD2vxKZ2fnWqcpl8s6DBscHNxAa0dE1BoM09Sh2mmJhjHHiYjGHnOc1hdznIho7DHH669pai1KpZK2Qf6pT30K7e3ta53uvPPO06vOh4fp06dv0PUkIhrvqm5vfOVAJJjjRESNgTlO64M5TkTUGJjjLXrluHTO+YlPfAJxHOOKK65Y57Qnn3wyTjjhhNWuHGcFORFRHdXQrIpM2wrW5y6ldf3QO94wx4mIGkiL5Tgz+u1jjhMRNRDmeN3L2nazBPGrr76Ke++99y3fYCKR0IGIiEbxNq5q2xxvkWZVpLkvafarWjLtP/7xD8yZMwfjHXOciKi1cvyBBx7ABRdcgMceewwLFy7ErbfeigMPPHCd89x33316gdOzzz6rFzadcsopOOKII1APzOi3hzlORNRYWq083rkBytp2MwTxP//5T/zhD39AT0/PWK8SEVHLYxtna/bzn/8c3d3db3l8yF1QH/7wh1viOGKOExG1Xo7n83lsv/32OOqoo3DQQQe95fQvv/wy9ttvPxx77LG44YYbcM899+Czn/0spkyZgn322Qf1wIxeP8xxIqLG04rl8Z+Pcll7TCvHh4aG8OKLL652YvTEE0/oG5aTof/8z//E448/jt/85jcIwxCLFi3S6eR513XHcM2JiFq9d2yrymlDtIKZM2di9913r/pHXPkV23EcNDvmOBFR8xntHN933311qNaVV16J2bNn47vf/a4+3nLLLfHggw/ie9/7Xl0qx1s1o6vBHCciaj6tVh6fuQFyfEwrxx999FG8//3vH3k83Fb44YcfjjPOOAO/+tWv9PEOO+yw2nxyFfkee+yxgdeWiIj+HcZV/lI9DtoqrYb8uFuLZ555BuMBc5yIqPk0Wo4//PDD2GuvvVYbJ5XiX/7yl+uy/FbN6Gowx4mImk+j5fho2xA5PqaV41LBLZe8r826niMiorFhmqYO1U5L4xdznIioNXL8jZ1a1rOfJ7k7eNKkSauNk8fymsViEalUqi6vQ2/GHCciaj4sj9cfay2IiGi9fqmudqCKxYsX46yzzuLmICKipstx6SSzo6NjZDjvvPPG1V5kRhMRUbNgebz+Oc5aCyIiqgnDeP2vjDvzzDN5tBERUdPl+Pz58zEwMDAynHzyyXVbn8mTJ2uhdlXyuL29fYNdNc6MJiKiZsHyeP1zfEybVSEiouZjGDX0jm20zm+wTz311Dqff+GFFzbYuhAREdUzx6WiWobRsOuuu+K3v/3tauPuvvtuHV8vzGgiIhovWrE8/tQol7VZOU5ERDVptQ5AqiWdRxuGscb+MobHy18iIqLxnONDQ0N48cUXV+tI64knnkB3dzdmzJihV50vWLAA119/vT5/7LHH4vvf/z5OPPFEHHXUUbj33ntx88034/bbb0e9MKOJiGi8aMXy+A6jXNZm5TgREdWkFcO4GlLo/853voM999xzjc8/++yz2H///Tf4ehEREW3IHH/00Ufx/ve/f+TxCSecoH8PP/xwXHfddVi4cCHmzZs38vzs2bO1IvwrX/kKLrnkEmy00Ua4+uqrsc8++9RtxzGjiYhovGjF8nj3KJe1WTlOREQ1MS1Th2qnXR+XX345LrjgAm07bPvtt8dll12GuXPnrnFaKWgfeeSRq41LJBIolUojj+WX5NNPPx1XXXUV+vv78e53vxtXXHEFNt10U9TLTjvthNdffx0zZ85c4/Pyumv6pZuIiGg85fgee+yxzryT3F7TPH/7298wWpjRREQ0XmyI8nijGe0cHx9biYiINhjDNLSNs+qG2m9tuummm/QqM6nMfvzxx7VyXK4eW7JkyVrnkXZQ5Uq04eHVV19d7Xn5lfnSSy/FlVdeiUceeQSZTEaXuWoF+tslt4XPmjVrrc/LreTXXntt3V6PiIioEXO8ETGjiYhovGCO17+szSvHiYiooVx00UU4+uijR64Glwptud36mmuuwUknnbTGeaR9scmTJ6/xOfkF+eKLL8Ypp5yCj3zkIzpO2jmdNGkSbrvtNhx88MF1We+PfvSj63y+q6tLbyknIiKiDYsZTURE1Lw+OsplbV45TkRE69XGWbVDLTzPw2OPPYa99trr30Flmvr44YcfXmfnX3KL1fTp07UCXNocW7UjMGmeZdVldnR0YJdddlnnMuvhT3/6E8rl8qi+BhERUaPkeDNhRhMRUTNijtc/x8fv2Q4RETVMGA8ODq42rC3Eli1bhjAM9aruVcljqeBek80331yvKv/lL3+Jn/zkJ4iiCLvtthtee+01fX54vlqWWS/77rsvFixYMKqvQUREVAsWqiuY0URE1IyY4/XPcVaOExFRTQyj2nZKTZ1WyBXdcrX28HDeeefVbavvuuuuOOyww7DDDjvgfe97H2655RZMmDABP/jBD8Z8z7IDTiIiGg85Ph4xo4mIqBkxx+uf41W1OS4do9VK2nbt7u5en3UiIqIGZlgWTMuqeloxf/587TRzWCKRWOP0vb29sCwLixcvXm28PF5bm+Jv5DgOdtxxR7z44ov6eHg+WcaUKVNWW6ZUqLcC5jgREb2dHKexxRwnIqJhzPH6q6pyXDoykyvzXNetaqEPPvggjj/+eFaOExGNQ7W0QTo8nVSMr1o5vjaSMzvttBPuueceHHjggTpOmkmRx5Ir1ZBmWZ5++ml8+MMf1sezZ8/WCnJZxnBluDTt8sgjj+C4447DaJKr19/YnMtYYI4TEdHbyfHxqFEyuhrMcSIiGsYcr3+OV1U5Lm699VZMnDixqmnb2trezjoREVELh7FcHSU9Te+8886YO3euFgjz+TyOPPJIfV6aUJk2bdpI0yxnnXUW3vWud2GTTTZBf38/LrjgArz66qv47Gc/W1kHw8CXv/xlnH322dh00021svzUU0/F1KlTRyrgR8t//dd/aUX8bbfdpm2jb7nllhgrzHEiIhIsVDdeRleDOU5ERII5Xv8cr6py/Nprr9U2Ysfjr/BERFSb4XZIq522Vp/85CexdOlSnHbaadphplztfccdd4zkyrx582CustwVK1bg6KOP1mm7urr0yvOHHnoIW2211cg0J554olawH3PMMVqB/p73vEeXmUwmUW+f+MQnsPvuu+uV7sViUSv5X3nlFW0T7cYbb8THPvYxbGjMcSIi2lA53sgaMaOrwRwnIqJhzPHd657jVZ3tyBV8a2sfdm2195lMhkcuEdE4tCF6x5awk6u/y+WyNn+yyy67jDx333334brrrht5/L3vfW9kWqkgv/3227XN8dXW2TD0CnN5vlQq4fe//z0222wzjIYHHngA733ve0eu8pKglgr5Sy+9VK9eHwvMcSIi2pA53qgaMaOrwRwnIqJhzPH31j3H39bZztDQkF7CvupARETjm2Ea1QeyaaDVDAwMjPS5IVeny6/X6XQa++23H/75z3+ikTDHiYhaTyvneDNldDWY40RErYc53l33HK+5cvzll1/WF5Urw6WpFbmFXYbOzk79S0RErXEbV7VDq5k+fToefvhhbcZFAnvvvfceaf5lNJpxqRVznIiotbVyjjd6RleDOU5E1NqY4w/XPcer7pBz2KGHHqqXrV9zzTXa/qvcqk5ERK3DMC0dqp221Ujnn4cccgiy2SxmzpyJPfbYY+RW7m233XasV485TkTU4lo5xxs9o6vB8jgRUWvbEDl++eWX44ILLtBmSbfffntcdtllmDt37hqnveqqq3D99dfjmWee0cfSB9i555671ukbMcdrrhx/8skn8dhjj2lPoERE1IIkYKsN2XFWqK7G5z//eW0jXToO/eAHPzjSeeicOXMaoj1T5jgRUYtr4Rxv9IyuBnOciKjFjXKO33TTTTjhhBNw5ZVXamZefPHF2GefffDCCy9g4sSJb5pe+gT71Kc+hd12202v3j7//PP1iu5nn30W06ZNQzPkeM2V4+985zsxf/58Vo4TEbUqCaBqb7MeZ7djV0t+LZdhVdIkWSNgjhMRtbgWz/FGzuhqMMeJiFrcKOf4RRddhKOPPhpHHnmkPpZK8ttvv11bEDnppJPeNP0NN9yw2uOrr74av/jFL3DPPffgsMMOQzPkeM2V4/Imjz32WCxYsADbbLMNHMdZ7fntttvuba0QERE1NsOydKh2WmoszHEiotbGHG9uzHEiotY2mjnueZ62FnLyySePjJOrs/faay/ts6MahUIBvu+PdIDdDGquHF+6dCleeumlkV8QhLQ7Lu2Qy98wDOu9jkRE1Eha+Hbs8YA5TkTU4pjjTY05TkTU4tYjxwcHB1cbnUgkdHijZcuWab2u9DG5Knn8/PPPV/WSX//61zF16lStUB+3leNHHXUUdtxxR/zsZz9jh5xERC17G5fVsrdjNzvmOBFRi2OONzXmOBFRi1uPHJ8+ffpqo08//XScccYZdV+1b3/727jxxhu1HXJpf3zcVo6/+uqr+NWvfoVNNtlkdNaIiIgammGaOlQ7LTUW5jgRUWtjjjc35jgRUWtbnxyXviPb29tHxq/pqnHR29sLy7KwePFirEoeT548Gety4YUXauX473//+6ZrcrvmyvEPfOAD2kM2K8eJiFqUUcNtXDJtCyqVSnjqqaewZMkSRFG02nMHHHAAxhJznIioxbV4jjdyRleDOU5E1OLWI8elYnzVyvG1cV1XO7uUzjQPPPBAHSdZKY+PP/74tc73ne98B+eccw7uvPNO7Lzzzmi2HK+5cnz//ffHV77yFTz99NPYdttt39QhZy0r8sADD+CCCy7Qxt4XLlyIW2+9dWTjC2nHXC71v+qqq9Df3493v/vduOKKK7DpppvWutpERFQvbKt0ne644w7tlVvaa3ujRuibgzlORNTiWjjHGz2jq8EcJyJqcaOc4yeccAIOP/xwreSeO3cuLr74YuTz+ZG+JyVHp02bhvPOO08fn3/++TjttNPw05/+FLNmzcKiRYt0fDab1aEZcrzmyvFjjz1W/5511llve0Vk426//fbabtpBBx20xl8eLr30UvzoRz/C7Nmzceqpp2KfffbB3//+96Zqu4aIaDzh7djr9oUvfAEf//jH9QThjR2ZNALmOBFRa2vlHG/0jK4Gc5yIqLWNdo5/8pOf1M6fJSulonuHHXbQSunh3Jw3bx7MVZYrFzF7nof//M//HPV2zUcrx2uuHH/jJetvx7777qvDmshV4/LrxCmnnIKPfOQjOu7666/XN3/bbbfh4IMPrtt6EBFRDVr4irNqSHts8mt7oxa6meNERC2uhXO80TO6GsxxIqIWtwFy/Pjjj19rMyrS2eaqXnnlFTR7jjfspQAvv/yy/kKx1157jYzr6OjALrvsgocffnhM142IqKUN945d1dCwMTNq5BfzN54wtCLmOBFRg2rhHGdGV485TkTUoJjjqLeqrhyXpk2OOeaYqpsyufLKK3HIIYegra1tvVdsuI2aN/4aII+Hn1uTcrmsw7DBwcH1XgciInozw7J0qEa1040n3//+9/VWrz/+8Y9r7Jvji1/84gZfJ+Y4ERFtyBy//PLLtW8pKbdJM5qXXXaZtlu6Jtddd91IO6bDEomEdrjVChldDeY4ERENa+Xy+PdHKcerqhyXDjg/9alPVV05fuKJJ2Lvvfd+W5Xj60sahD/zzDM3+OsSEbXWL9VVXkk2zq44q8bPfvYz3HXXXZqZcgW59McxTP4/FgVv5jgREW2oHL/pppv0lme5YEru+pWmMqXfqBdeeAETJ05c4zzt7e36/LBVs3O8Z3Q1mONERDSihcvjPxulHK+qclza/95zzz1h29U1UV4sFvF2TZ48eaQ9mSlTpoyMl8fSGPzanHzyyXoytuqV49OnT3/b60NERCu1cFul1fjmN7+pP9KedNJJq3VUMpaY40REtKFy/KKLLsLRRx89cjW4VJLffvvtuOaaazQb10QKtMPlv1bL6Gowx4mIaEQLl8e/OUo5XlVtt/QwWgvpQLO7uxtvx+zZs/UE6Z577hmpDJeK7kceeQTHHXfcWueTW/BkICKi0WGYlg7VTttqpKdu6eG7kQrdzHEiItoQOS4Z+Nhjj+kFS8MkD6UfqXX1GzU0NISZM2dqZ5PveMc7cO6552LrrbduiYyuBnOciIiGtXJ53BulHB+VyvFqyUnQiy++uFqnH0888YRWrM+YMQNf/vKXcfbZZ2PTTTfVyvJTTz0VU6dOxYEHHjgq60NERFUwariNS6ZtMYcffrjeUv6Nb3wDjYI5TkREbyfH39iP09ouSFq2bBnCMFxjv1HPP//8Gl9i880316vKt9tuOwwMDODCCy/EbrvthmeffRYbbbTRuM/oajDHiYhoRAuXxw8fpRyvrp2UUfLoo4/i/e9//8jj4eZQ5M1KxyzSdnk+n9fOQPv7+/Ge97wHd9xxR9VtnxMRUXP+Ul1LR15XXXUVrr/+ejzzzDP6eKeddtIrzlad/ogjjsCPfvSj1eaT9k8lU+pNKgW+853v4M4779SC/hs7CZHbzccL5jgRUWvk+BubqZTK2jPOOKMu67PrrrvqMEwqxrfcckv84Ac/wLe+9S3UUytldDWY40REzaeVrxwPRynHx7RyfI899tD209ZG2p4766yzdCAiokbqAMRqmI68pCMO6TRaCtPy4+n555+vnULLFWfTpk0bme5DH/oQrr322pHHo9UE19NPP40dd9xR/z9cYT/aHYyNFeY4EVFr5Pj8+fO108y3ytDe3l5YlqX9RK1KHlfbprgUdCVHV73DuF5aKaOrwRwnImpCo1web2SjleNjWjlORERNaJR7x661I68bbrhhtcdXX301fvGLX2ifFYcddthqBfkN0dnXH/7wh1F/DSIiog2Z41Ixvmrl+Nq4rqt3cEkGDzeFKe2Iy+Pjjz++6qvCpPD74Q9/GPXGjCYioqY3yuXxRjZaOT6+thIREY06w7JqGtanIy/puKuWjrxWVSgU4Pv+mzqGlivM5cpzadtUOnbu6+urad2IiIjGg9HMcSF3f0mTZ9Kc2XPPPaeZK01lDv/oLT9cr9php9wlfNddd+Ff//oXHn/8cRx66KF49dVX8dnPfrau75uIiGg8GO0cb0XrXTkuFRhyi3sQBPVdIyIiamxyC1ctw8qOvFYdyuXyGhe9ro68pP3xanz961/XzptXrWCXJlWkXXK5ck2aXbn//vux77776mvVw0EHHfSmzsrW5ZBDDsGSJUswlpjjREQtaj1yvBaf/OQntVPN0047DTvssAOeeOIJ7eNjONvnzZuHhQsXjky/YsUKvWNM2hmXq8UlTx966CFstdVWLZvR1WCOExG1qFHO8UazIXK85spxuSLvM5/5DNLpNLbeems9uRFf+MIX8O1vf7vWxRERUQuQjrw6OjpGhvPOO29UXkdy6MYbb8Stt966WufNBx98MA444ABsu+22epv3b37zG/z1r3/Vq8nr4Ze//CWWLl36ph8B1jQMDAzg17/+NYaGhjAWmONERDTapAkVufpbfgx/5JFHtA+RYZK911133cjj733veyPTyg/h0pTacHuirZbR1WCOExFRK/nlBsjxmivH5Ra4J598Uk9qVq14kCv0pBM1IiIa59bjl2rpyEuCanhY9XbqenXkJVepSeW43JotPVevy5w5c/S16tXZl3Quvdlmm6Grq+stB2nuRW4vHyvMcSKiFtdiV5w1U0ZXgzlORNTimOOod47X3CHnbbfdppXg73rXu1brCVSuIn/ppZdqXgEiImouhmnqUO20G6Ijr+985zs455xzcOedd2LnnXd+y9d57bXXtM3xKVOmYKw6Bpk2bRrGAnOciKi1rU+ON7NmyuhqMMeJiFobc7z+OV5z5bhcyi4dmr2R1MyvWllORETjlFHDlWQy7Xp05HX44YdrJffcuXNx8cUXv6kjLwm74aZZpA1xadf0pz/9KWbNmjXSNnk2m9VBbqk688wz8bGPfUyvPpcfck888URssskm2GeffVAP73vf+9AsmONERC1ulHO80TRTRleDOU5E1OKY43VX86UAUlkh7cANG64Qv/rqq7HrrrvWd+2IiKjxyPe+YVY5GKPekdcVV1yhnVL953/+p14JPjzIMoQ00/LUU09pm+NyW7X0myFXp//xj39EIpFAq2GOExG1uFHOcRpdzHEiohbHHK+7mq8cP/fcc7Hvvvvi73//O4IgwCWXXKL/lx7F77///vqvIRERNZbhAnO1064HaUJlbc2ovLETzVdeeWWdy0qlUtrcClUwx4mIWtwGyHEaPcxxIqIWxxyvu5rPdt7znvfoVXxSMb7ttttqx2fSzMrDDz+sV+IREdH4FhtmTQM1FuY4EVFrY443N+Y4EVFrY443wJXjYuONN8ZVV11V/7UhIqLGx1+qmx5znIiohTHHmx5znIiohTHH667mS/oGBwfXOORyOW3zlYiIWqGNsxqGFnP66afj1VdfRaNijhMRtbgWzvFGz+hqMMeJiFoccxxjXjne2dmJrq6uNw0yXtp1nTlzpp50RFFU95UlIqIGYJq1DS3ml7/8pV7Rteeee+KnP/0pyuUyGglznIioxbVwjjd6RleDOU5E1OKY46h3jtd8tnPddddh6tSp+MY3voHbbrtNB/n/tGnTcMUVV+CYY47BpZdeim9/+9t1WUEiImosbONs3aRfjr/+9a/Yeuut8aUvfQmTJ0/Gcccdp+MaAXOciKi1tXKON3pGV4M5TkTU2pjjf617jhtxHMe1zCC185/73OfwiU98YrXxN998M37wgx/gnnvuwY9//GOcc845eP7559EIt511dHTguVdex5TeTgyUQzhm5fbArGvCCytvP+9H6EhYyJVD2JaBrGNCnhkohZBr4IfnESnbQGc2PWbviYhax8L+PKZ0ZrBoIK/fX5MzDpIIgChE0XBRDGJ9vlTII4AJ2wBKYYxUVMJgbggTN5qJgYEBtLe31+37tO+5v6C9LVvdPLkh9Gw5t27r0Gx838evf/1rXHvttbjzzjuxxRZb4DOf+QyOOOII3ZZjoVlzvO++m9ExY2MYoaft7IXLF8FMZWAkM4gG+nTaOPBhZtoQ5vphuknEUajTiCifQ+yVEOUHYU+aAXvHD43xOyOiVvD0wgF4QQzXNiClLtcyRu6ItgwDUsSY09uGfy3LwTYNLXNIuSRlm8gNDmLLWVOZ4y2U0eM5x5e89iqcjl4kbBNhFOs5qx8DCT+P2LQR2wl9LM/J+W23E8HwiwiT7TpuyI+QtAyk/UEMWO2Y0J7G0sGC/iUiGm3FUglBFFe+vySvw7KWx0XSjGGEPmBaQByhZLhImMDygUFMmzKZOd4EOV7zpQAPPfQQdtxxxzeNl3EPP/zwSA/a8+bNq3XRRETUTB2AVDu0MPn9WUJb+uSQ/0szZN///vcxffp03HTTTWOyTsxxIqIWxxxv2IyuBnOciKjFMcfrnuM111rIi/zwhz9803gZJ8+Jvr4+XSkiIhqHGMZv6bHHHsPxxx+PKVOm4Ctf+Yr+gPzcc8/h/vvvxz//+U+9muuLX/wixgJznIioxbV4jjdyRleDOU5E1OKY46h3jtu17oMLL7wQH//4x/G73/0O73znO3Xco48+qrds/fznP9fH0tbLJz/5yVoXTURETSA2jKrbIJVpW822226rmbj33nvrD8f7778/LMtabZpPfepT2kbaWGCOExG1tlbO8UbP6Gowx4mIWhtz/Pm653jNleMHHHCAnlBIe2b/+Mc/dNy+++6rHXPOmjVLH0tj6ERENE7VciXZOLzi7K1IG6BHHXWUdlS9Nr29vYgi6dFiw2OOExG1uBbO8UbP6Gowx4mIWhxzHPXO8Zorx8Xs2bPx7W9/e31mJSKiZidXkVV7Jdk4u+KsGsPtnb1RsVjEBRdcgNNOOw1jjTlORNTCWjjHmyGjq8EcJyJqYcxx1DvH16tyvL+/H3/5y1+wZMmSN9XGH3bYYeu1IkRE1CRa+Jfqapx55pk49thjkU6nVxtfKBT0uUYoeDPHiYhaWAvneDNkdDWY40RELYw5jnrneM2V47/+9a9xyCGHYGhoCO3t7TBWuZpA/s/KcSKi8U3aKa2+rdLxVaiu9qq0VbNx2JNPPonu7m6MNeY4EVFra+Ucb/SMrgZznIiotTHHjbrneM2V41/96le1nbZzzz33TTX1RETUAqSgbLbmFWfrIrdpS4Fbhs0222y1wncYhvqjslytNtaY40RELa4Fc7xZMroazHEiohbHHEe9c7zmyvEFCxbgi1/8YtNVjIdxjI5MCgU/jzbXRM6LMORF6EhYGCiHSNkmcuUQYQz4fgTHNJCxDaQcE14YI4xiDDcgkzVNvLBksLLcCLqM13MeMq6F2Z0uFg35+ty8gTLSjoWCH2KznhRs00DKNvS1u1zAh4l5A742F9SbslAMYiwrBHBtA4uHPEzKuth2SgeeXTiIgbKPCWkX/1pRRHfKgb+yOZtSEOEDm0wYs+1K1KxeXpZD1rUQRLF+LuX7oBTGmJ4GhiILPW1p/Zy78rl1TP3rRfJdACRtA65lYGkh0GW1ufI5j9CZtHQ5PQkgF8hnPdTnHBP6+ZbnIsToTdnIWDGWlOKVr28iile/oinjGBj0Kp/zBSvy6EjId1SEhBEhNmxIFMi6ZOX7rFCEZVgYKIXotX1EcOHbKSCufE/VXQvfxrUuF198se4/+QFZbunq6OgYec51Xe20etddd8VYa9YcN1JpGHE0cvyZmXbExTziMEQc+DAzbYBp6WMzmUEceDBsF3G5BCOV0YqguFzUaQ3HQfTinxEsXQBEITDcRJzt6DINx0Xw+sv6GDJ9ph2Gm0TslWDINKU8wnwO2UNOQ+76MxD5ASIvQFAqw23PICiWEZY85BctR2ZyN9JTehDkS/oSVtLV6f18EXYygTiM0HUc+3EhqtWHr3xIz8870w4WLM5jq9ld+liGbMLGUDlAyrV02qIXoujJYxvdGVen0c+jaWCg6GNmT+X7cEJbAs8vzCHtWjqvDDJNT9rVc4bXBkvoTrk6bW/agWOZSFgmhrwAHUkbpuS3ayHvhbBWFtqkDOKYpmZ9Oai8rry8tbJMJ1ku5yRCzi0KK8shcn5gjlZz3y2Y482S0eM5x6XQm7BNmF4BpuWgGFlIwUfkpFAIDaTjCG4cIbZsPWeOTRtxok3L4vJZyKwslwvZl97y15FJdcNf/DLKbZPhhGX4VgLpRc8i6JkFRAFiN4NibGk5PNk/D6XOGXAiD2ZxAP2JXj1H78ymUR5cjkEk0VcM0J209PM+P+fpa3UlLLQ7QDKdQXloQNdL/i/n34lCH9zejcZ4wxI1n0KxBC+M4Fqm5qQbB0AcwRp4HVF2AsJEFlZpEJGbQQCZpjKfZGPCMmCvrJ1b4VXKw27kIbITsHNLEDtJxJaL0E5Wlh15MIIyYicF37DRVwwxMWNr/V9nnEeQaIczuBBRtle/L1JGiMhy9PkOO0IJtuayGYdwowADoa3TyHeaH1W+m5YVA/QmHc1MQ7574hhBbGCwPEqdOzPHUe8cr7lyfJ999sGjjz6KOXPmrPeLEhFRE2vBMK7G4YcfPtJJ1m677QbHcdCImONERC2uBXO8WTK6GsxxIqIWxxxHvXO85srx/fbbD//zP/+Dv//979h2223ftEIHHHBAPdePiIgaTQuG8VsZHBzUfjjEjjvuqL1ly7Amw9ONFeY4EVGLa7Ecb6aMrgZznIioxTHHUe8cr7ly/Oijj9a/Z5111puek6YApK0XIiIav2LDqKEjr9G6J7zx2jJduHAhJk6ciM7OzjV29jXcZM5Y5yRznIiotbVajjdTRleDOU5E1NqY40bdc7zmyvFouF3ODUDe1BlnnIGf/OQnWLRoEaZOnYojjjgCp5xyyhpPaoiIaANosV+qq3HvvfeO9I4t/2/kjGKOExG1uBbL8WbK6Gowx4mIWhxzHPVWc+X4hnT++efjiiuuwI9+9CNsvfXW2tb5kUceqQ2vSyckREQ0BqRQWW3Bcj0LoJdffjkuuOAC/WF0++23x2WXXYa5c+eudfr/9//+H0499VS88sor2HTTTTU/PvzhD6/2S/Lpp5+Oq666Cv39/Xj3u9+t+SLT1sP73ve+kf/vsccedVnmeMAcJyJqQE2Y428HM3r9MceJiBoQc7wxKsfz+Tzuv/9+zJs3D55X6cV5WD0rrR966CF85CMf0XbVhPQ++rOf/Qx/+ctf6vYaRETUWL9U33TTTTjhhBNw5ZVXYpdddsHFF1+snU+98MILekv0mrLiU5/6FM477zz8x3/8B37605/iwAMPxOOPP45tttlGp/nOd76DSy+9VH9slc64pAAuy5T+M5LJJOrp2muvRTabxcc//vE3FfwLhcJIp2BjiTlORNTCmjDHWymjq8EcJyJqYcxx1DvHaz7b+dvf/oZNNtlET2COP/54nH322fjyl7+Mb3zjG3riU0/Sk/g999yDf/zjH/r4ySefxIMPPoh99913rfOUy2XtdGXVgYiI6kfaKa1lqNVFF12k7WnKnUJbbbWVFq7T6TSuueaaNU5/ySWX4EMf+pB2Fr3lllviW9/6Ft7xjnfg+9//fmV941jzSZrkkh9ct9tuO1x//fV4/fXXcdttt6HepHDf29v7pvFSIXDuuedirDHHiYhaW7PleCtldDWY40RErY053lv3HK/5bOcrX/kK9t9/f6xYsQKpVAp//vOf8eqrr2KnnXbChRdeiHo66aSTcPDBB2OLLbaA4zjau7hUxB9yyCHrPOGRZleGh+nTp9d1nYiIWt7wL9XVDsCbfrSUHzLXRO5Geuyxx7DXXnuNjDNNUx8//PDDa5xHxq86vZAr1Ianf/nll/W27lWnkXyQq9nWtsy3Q+6qkqvT32jmzJn63FhjjhMRtbgmy/FWyuhqMMeJiFoccxz1zvGam1V54okn8IMf/EBPcizL0hOjOXPm6C3rcvn6QQcdhHq5+eabccMNN+itddLmuLy2VI5Lx5xru1T+5JNP1tv4hsnJm1SQh3GM5bkC/ChGwa90Kir/z/sREpaBchjrY8s0EIRAyjZRjmIsL4ZwLQOdSQu5cohiEGPIizBYCuFYBlzL1OUlbBP9JR9x7CKMgYFSqK8p0o6ly5b5zFTl/wEsfW3LrKyHLDdlG+hIWpV5oxgmDPz48dfwvlmd8CMLfUVflyWv9fyiPDbtSWNCxsWNTy5AwQ/xr6V5ZJM2ZnSmdJrbnnwd79l0AtpcC5v2ZDBvoIhyEKEn7WJS1sVLywu67i/35XHg1pNx0X0v4UNbT8L8/iI+MKcXtz+/WJdX9ELdLie9vz5t8xKtTaFYGmnaMohivD7kY0a7i/5SqJ9TL4rRHeWwKM7q5zLjmPDDGCnH1Oll1kX5AL0pC6nYwytFE/IxnNXuVD7zMbCsEKA7ZcORz/rK74A210baMVEMQgyGlk5bHlyOOLb1NYb8CNm0Xfls+wHaEw4SpRWI4jZYBmAaQBTHeG3QR0/agukXASONhGXqc9prchTp98iSfICifu9Y8MJAly/kT+WbyUA5iOGFMs7AoBci61j6Wd10YhtKxSIiGDBNG1kE8GDr+5btlnEMGH4Jse3CiTyUy7lR7B27ujZIh6d74w+V0v63dLj8RsuWLdPOmCdNmrTaeHn8/PPPr/E1pOJ7TdPL+OHnh8etbZp6kl+tn3rqKW0KbFVy91NPTw/GWrPmOKIQkZuCMbgUhptElB+E1dGDOPABGeR480qIoxBWWyeMRBLhQB8M29HPiD4fRbAnTEMchogH+hAX84hLeV1G6oAvwvvTzTqdLN9IZQDTAiyrsgw3qdMiMmEkM4gHB1C87XuwMlmUFyyE25aBl8vDyWZQ6huoPB7MIz2xE2YyDdML9Pli3wCcTBKGaSIolRF5AV445iB0bzkTqYldeO0PjyM9oUufK/cPoXe7jeENFjC0YCmy0yYgLHnaGVscRrocGV774/OYsssmiPwAQclDYeFybHX9r/HK1w/X/VxYukJfb/P/u6Vu+5ZoTXY56244CRthGKEwWIbtmPq4OOQhmXZGnhtcVkCqzUUi5WBgWQG909oQeJHe6TOhN41lfUU4CQuua6En62LB0nzls2kasCwT+cEyLNvUaXOlYKTlj6GSr+e63RkXXj6EF4SY2ZNBZ8pBwQvx2ooCsgkby/NldKRdpExL50m58jfQc3c5h5bHXhDBtU0sH/IwOZvQ5cr/u1OulgFyXoiOhAHfiODICf1Kcg5vGQaSjgkvkPKFPF/JdplMnpNxiCTLK/kteS/nGEEYI4zkfcYjyxoNzZbjrZTR4znH5RzVDCt57Rk2klIOjl24fh4eUkjaFmwvjzDRjraEBSP0tALIMmwti1qlQdjJdhjFEtx0OxACVuQjthz9/NiWg8Tg6wjbJkrg67xGOQc31Q0zDmGWKufFK0IbXYmsnqPbpoFcoQjLScNd+Xnzwkr5QOoEBsq+1gu0JWzMWz6E7uTKc+x8Dm4cwQh9LFiRR09CPtIry/lRjKzhwyjlsNTqwoR4AHGiDUZxAHCSKNoZZJe+AH/S5jCCMhb7NqaWF8LrnI7lxQBZ10S6tBxeukffl5R53EXPI0q2wZm8cd32LdGaLB0soCMcBEwb5tBSDHXMRNKM9ViF5WAoqtRjZVeWYdNWjL4y0JM09TO7qGxpmTcV5AG/hCjTg1IoZdsYnXEekZvRZdlxBMswMRQnkbENlGIbyagIIwqAKIARxyg6bUgYQNGv1JU5cYDYthHE0GXETgquFcONA/0seoYLy0kilO+JWOrTYq0/ELKsZOwhNqDrZ3oFdFgWYiTghZF+f8jV2JLRsWFr3Z989kLTQQKxzleOTKRKOYR2l37H+KaLspTVXRM9aVvrFJNxoNtIvgNi2PAk70cBc/ypuud4zZXjcgW3BPHwyYXUzMvtb3IV3vz581FPcmvd8NXjYtttt9Wr1OXq8LWFcSKR0IGIiEaH/OCw8re/qqYVkg/t7e0j48fz97Q0Oyb9b7S1tWH33XfXcdJPx5e+9KWRPBtLzHEiotbWyjne6BldDeY4EVFrY45/se45XnPluDRt8te//lV7EZeev0877TS9QuDHP/5x3TtMkcbUhyvih8mv43LFFBERjQ25Sl6GaqcVUqBetVC9NtIOqHzPL168eLXx8njy5MlrnEfGr2v64b8ybsqUKatNs8MOO6DepK3UV155BXvuuSdsuxKzkluHHXZYQ7RnyhwnImptzZbjrZTR1WCOExG1Nub4K3XP8ZrbHJcXG65cOOecc9DV1YXjjjsOS5cu1du76knaNpfXuP322/Uk5tZbb9UOXj760Y/W9XWIiKgxuK6rfVhIZ8zDJOzk8a677rrGeWT8qtOLu+++e2R6aVtUCtirTiO3+D7yyCNrXebbfQ833XST3j4utyLfcssteOmll7QjMnlurDHHiYiomXK8lTK6GsxxIiIaLW6L5njNV47vvPPOI/+XZlXuuOMOjJbLLrsMp556Kj7/+c9jyZIl2rbZ5z73Ob1anYiIxoZcQ1ZtK6jr01qqtFMpTWdJ3sydOxcXX3wx8vk8jjzySH1efhWeNm2aNrEl5BYquZPpu9/9Lvbbbz/ceOONePTRR/F///d/+ry0+S7tY5599tl615NUlku2SKYceOCBGC2bbbaZvt7wOjQK5jgRUWtrthxvpYyuBnOciKi1McdR9xyv+crxtXn88cfxH//xH6gnaUNGTqaknfFisai/BkjlRrP8qk9ENB5Jvya1DLX65Cc/iQsvvFB/CJVmT6TzJ/khdrizLunrYuHChSPT77bbbtpRlBSit99+e/z85z/HbbfdtlpTXyeeeCK+8IUv4JhjjsE73/lODA0N6TKTySRGw/XXX6/9ZKRSKR222247bX6skTHHiYhaQzPmeKtndDWY40RErYE5fn3dc7ymK8fvvPNOvTReKqc/+9nPaq/Ycim7dJr561//Gvvss8/bWhkiImp8cRzrUO206+P444/XYU3uu+++N437+Mc/rsPayK/JZ511lg6jTZr/kivTZf3f/e5367gHH3wQxx57rPbR8ZWvfAVjhTlORETNmOOtkNHVYI4TERFz/NS653jVleM//OEPcfTRR6O7uxsrVqzA1VdfrScXciWeXB3wzDPPYMstt+RRSkQ0ztVyJdn6XHHW7KRJsCuuuEJvGx92wAEHYOutt8YZZ5wxZgVv5jgREbV6jjdqRleDOU5ERII5fkXdc7zqZlUuueQSnH/++VoTf/PNN+vf//3f/8XTTz+NK6+8khXjREQt2M7ZWw2tSG4Vl1vE30jGrXob+YbGHCciolbP8UbN6Gowx4mIaBhzvL45XnXluLT3PXyr20EHHQTbtnHBBRdgo402Wu8XJyKi5jPabZw1u0022UR/RH4j6VV7uNOQscAcJyKiVs/xRs3oajDHiYhIMMdvrnuOV92sinSImU6nR9puTSQSmDJlStMcma5pouBHCKIYoWkgjGJkHRMD5RC9aRvlMEYQAZZZGRblfUh/p2Ecw4+g83krzw6LQQTHMlAKImRdC14YwzIM+GGMQS/Ux0vyZTiWiYRtYkXRRzmw4csywhgTUxb6ShE6EqY+lvWSzlVXlEMEIbCs4KEcRhgo+zp/xjEx5Jl4bbCM/9hyEp5eOIAtejPIeQGmtyeweKiMpG3puu0xpwddKRsvLCtgu+md6EjamNaWRMEPUQ4iTGtPwjQMDJQChDF0/ad2JDGzw8XMnjReWpZHyrXw0ooCvCBCZ8qBZRr6/2//4Z/44CYT9Lm/ze/X6T61/VTMHyzhN88uRmfaQTZp4wNzenD1n+dhtzndKIURtpqQRca18POnFuK9c3pw34vLsNXkNn1O1mmoHKAr5eAfi4eww0YdeHl5Ad/cc7MxPmJI5ApF/azIMbC8GGJmTxalYhFG6CE2bRhRgGW+rceyfDqKfoSu8lLMN3v0M9HmmvpZeWTBELabmEYxiJF2TOS8EBPSti5zWSFAe8LChLSFdDCEINEOK/IRxhakmUs5RjoSln62hOGXADurryWfYflcmkGkASHrKfPId1RkJ5H0AmTdym+A8pkzjcovrPI3ku8FA3AtQ9dLPuvy2Zf2u+RzF5pplHIlRLDgyndGDP2smjDgyNyGia6khQU5H90pW59POQZy5Qid2RSWDwVw5IUgn2HoMpO2LCce6U25HMToSMjrR7pSsq1TjonYqqyfTJa0TF1Hme/lZTn9npLtLeO8UL5jKuss7921TERmG1KGCfghonR307Zx1szOPPNMbW7sgQceGGkH7U9/+hPuueeeNRbIN5Rmz3Ejkan8JwoReyUYbhJxFCHKD8IwLcB2AdOEmUxXngt8WB09iH1PBzOVQZTPwbAdXUwchTASSV2eCB67HYYuw0JUzOt0spyoEMKU5eQHYabbEPYt0vmCfAlWKo2wWICfL8FOJmA6NoJCEYZpwsvl0bXZdJiuDcNxEfkBIi/AlJMvx5ILvwQrWelcPCh5sFOuzl9Y2Ifl/1wOty29cpku2jbfDCuefKayDSwTfqGoz4lkTzvsdBKJdhduexqFhcthmiY6Np6K5z97IBKdbQjDCJEXItmTxt8O3BttG3Vik+/fjNdOPxqDLy/CwGuDSLYnMGH7mfp4xb/6dXmFviI22X97FBb1IZZlhBGKfXmkejKw5D3JF6bsDi/Qv/klObTP6NH3ufzFZZh7x70b/iChNznm5icwUPCQTTpwbVPP5ya2JfDcwkHNDc27KEbBC/VxcWXWilLRRynvw3YtBF6Izt40giBCYchDLHmVdVEYLOsxVi4GaO9O6Xzlkq/nmhJFhmkg8EMk0w7yg2X0TnMBrzJehHIe2J9Hz5Ss5oUp2Sbn2QlL57NsEzk5Zw1iHdeRddGfK+tzHd0pXWcRSQgD6C/4en4q55Yy35TOFPry3mrbZKDojcxX9EM9xx8qBfq68neYnNOKCe0JpBxLz8070g4sA0g7lm63toSl5/+S946WNUIkbRN+FKHTslHyAyQsS89l5Hwo50V418xuPLtwUOeJEMOMDf1ONhCjFMawTSl/QF/n33ujvlo5xxs1o1shx2MnidgwYVjyOTJgRD4KgYmEV0AqnYEZhwiT7VoG1zK7ndDydtqKUPANZKMAZujrObhWDKW6YPhSLvF1+VIuMctDCHrnwFoxD1GyQ88L5Bw6hAnHScD18+h0UrBWLEbUNlO/C+TzWZSck++kqHIOLvMkbAMdcLQsLtPM6M6inOvX1ynaGaT8Af1/e8KE6eWARJuW7TuCfgw5negorkC2uwdxWHnfXroHCT+PlJ+DEVRyXMpUJmxE6S7Y5UEk7CxS8BG7aTiRh9BwK98fbkpfK5z/NML2KSg7GX2tNr8fZjkPLHkZ3ma7a91Gl6xPOYfYSek5TmgntawhZYfF+QCzyvMQdM9CZFhYUQqRsqUMYcCJAxjFAUSZHsSGgdQodVpP1ZPjrWQmkESg+zJykloGlv0lx3JsJ2Dm+/SzJWSfh1YCSwuBHr/yOWs3PD0GpLRuBGXk4SJjhjALK1DOTECyfx787pkwohCF0NDjIYZbOX5SHmzTgOkNadk/NB1YcaTHnpNcWZ6NDZhGpMdnbLlI2ZHmm65beQjlCEiaMSLJunwOvtsGV04Q5PPqFRC6CUgJO4winUc/t/K8vo6BZOQhaSfkU6LvVY7PEDbcWD6skrE2EIY6vZDvENMvYSBytN5B8z6MkYQHz3Q1s2X7yWvJOhulHBLZXv3MyXeJK+UA09H3Ld+z8l0gi5DvHtnKbu9G6M71y0m5rtPK0w89J5DBs2xkZZtbCf1Oc1aW++uNOf7Juud4TR1ySjvj2WxW/x8EAa677jr09vauNs0Xv/jF9V4ZIiJqfHLqEdUwbav52Mc+hkceeQTf+973cNttt+k46ZPjL3/5C3bccccxXTfmOBERtXKON3JGV4M5TkREzPFH6p7jVVeOz5gxA1ddddXI48mTJ+PHP/7xatPILyusHCciGt/kIrJqLyQbZxecVW2nnXbCT37yEzQS5jgREYlWz/FGzOhqMMeJiEgwx3eqe45XXTn+yiuv8CgkIqKW7h17bQYHB6uetr29HWOBOU5ERK2Y482Q0dVgjhMRkWCO1z/Ha2pWhYiIqJXbOFubzs7Okbbk17UttO06aRePiIhojLRajjOjiYhoPGGO17+szcpxIiKqSSu3cbY2f/jDH8Z6FYiIiKrSajnOjCYiovGEOV5/rBwnIqKayDVkVbdV2iLb9n3ve99YrwIREVFVWi3HmdFERDSeMMfrzxyFZRIR0TgWxXFNQyv64x//iEMPPRS77bYbFixYoOOkE+sHH3xwrFeNiIhaXKvnODOaiIiaGXP8j3Uva7NynIiIav+luoah1fziF7/APvvsg1QqhccffxzlclnHDwwM4Nxzzx3r1SMiohbXyjnOjCYiombHHN+n7mXt9WpW5aWXXsK1116rfy+55BJMnDgRv/vd7zBjxgxsvfXWaETSOHsplM5nKj27yv8tUwYDXhhjeTGEbQEFXxpxr8xT9Cut7HWnKpvJNQ28NFDC7K4kwggY8kJMb0/AC0NEiJF2LARhjKxrImGbKAcRlhU8/RvGMV7PldGVTCMfyOsCA+UI5SCGH8WwpOH4CMh5AdoSFqJSZXmDJR9px0S7a+rfW59ZiBkdKV2ekL/dKVdfb5lrYUXRR2fSxibdaf3/lGwCQ16ArGvDNA2dfkZHAn99PYcgjFD0K6+fjMqY3JHEooES+oY8dKYcdGdd5MoBtujNoq/gYVZXCq5tIGmb6Mt7CHMx/rWiiH+tKOi6zOxO6/rLNp3Zm8Z/7bgRfvPcYmzU5mLeYGX5S4bKmNyZRCmMdJ3STgxT3nsMdKQd2JaJlGvhmkfnYUmujG0mt6MjYet7KAUR/r44hxldaX2/G3el8Up/Ae/aqAN/fm0A/1peQDZh4wNzujF/oIztJqZx6/PLMKUtgYkZF5t2J/Hbfy7HrM4UulMOnl06pPtGtuvG3Wl0JCzM7m3DkoE8Xh/y0Zuy8dBrg9isJ43ZnQl0ZFL6fmT6WZ3JyvaPANsEHNOoNP4fx3AtQ4+d9oSFhPw/iJG0DQyWI/QkgFdyoR6DkzM2HKtysCUKfTDiCFG6C4gjmIUV8NsmwwpKiJwk+kuhvn9Z5pBXOZ5Stqn7LuuYKPgROpKWHsfPLyugN+1i694EjCjAYGjpOq18KSwY8jFUjjC93UHWtbC0EKAzaSHlDWAp2nRdZblyLMt7lXVMlAdgGFmUikVdv9BKoBhEyKLSoZONSNc/tCwYoY+UayLvR+huS+s8k7KuLivvBwiiyjEXRjF6UpaukzxeXgqRSsix4mF21tDPx+IhT99fygFy5QjdKQuxk4QZA8PdLOhnMYz0mEitfJOyPSzD1HVsk3UJYuS8UJc3vUM+E5F+F9jymfAjpGwDC4dCdCRMfd1us7K9Mo6lvyDK8Sn7QL4r2hImVnhAj2HqdpVBtoFpAPLqg+UQyJp6DLgJS58rBtDvBTkGZHrZBkK+N2Qd5XvAtKGfHdkWMsgxJeuXsKGvO0z35crn5Jgb7ihLtqdMFkQGDERI2wnEpj8q36et1jt2rc4++2xceeWVOOyww3DjjTeOjH/3u9+tzzWCZsxxCWcj8GG4SUS5fhiJJBB4ladSGRi2A6ujB1E+hziKEPseDMsC5P+BB7Nroj4vzGwn4nIBQT4Hq2siwoE+xIGP2CtV5nNcxLYLI5FCtHQBrAnT9P/yXHHpciR7OmAlXZhtnTAcB3bfgC7XTiZQ7q+8vjzvZFLwBvPwli7R8aZj4/Wzj0PkBzDyJRiWibDkoWPjaXDa0/ByeaS6kvByBViODTuTwtCLLyIOI12mjDdME6UVRWQmtiHIl3SwU44uR+b3Bovo3W4OIi9EHIa6TkNL8ojCCKXBMjqTCTx35AFomzFptc2bm7d4ZDpdL0/mdZGa0IXBVxbq/2W8rLtu3zDSaZxMAk4mCTfj6nh5j0ExwIvHfwL5JTldtpO0kZ7SjeKSFeh/dQATtpqky1ry9EJs8fFd9bX9QrGybxxHt1nPNrOx9G//RHbaBCQ6swhKnq5Dbv5i9Gw9Byv+MR+T3rmV7o/i0n7d3rItOjebDqd3EkqvzUdi6jQ9RoxkBkHfImQPOQ2F//cdmB09uh0h+1j234RpiIp5YMJMGF4l5+JEBkboIZYvZ8PUIUq2IbaTKBqunkcK+f6W72jJJ8kWuZJnoBzquZKc98n5neSo5I+cN0oWyvmZnOPJIgbKle/ppGXilb4CXu3LY2ZPBptOzGLhYAleEOl52RZT2vR8af7yAlzb1PH9BR9eGGFKR1L/L9qSNs7ed0t8+ieP6nLkvGig4GluyLp4QYhcKdBpl60oYvaUdoRRhIIX6jKDoHLua9smDNOAaZsYXF7UPPO8UM8lZSiXA1iyHuXKsizbgJu0EUUxvLwHV8JLPpuSV44Fr+jDSVgIvEintd3K9TkyzjAtBJLFWRf5wTIGB8rItLnwSgECP5Tg07+JlI20a6EviOAkbGzUncary/I6Tzrr6vuUbSPvNeVY+leyUbbBaysK6Mkm9DXlfXakXX1uZk8aRS8c2aYyiAltCSzPe3pOKiSX9Xw+ivV8Q/bFgBdgimGgN+1gebGy/WW8r+cKts5T2c8yr5z3QI+Lvy8arGwzE5A+oyKjci4g+S7ndnKOIP/k+Bg+36+3Vs7xZsjocZvjcjwZFmwvj5JlIWNEaHdtxKGtn4GEUzmftQ1oOULOpW3LQMaMYBoWolSXlm3C7AS4WjMUwSwOIEp1VM7Fh5bB8IvwDRtOoR+xk0ZsJuAYlbJ/5KQRuRmdRr7T5dzd9EsI4Wr7vX2FcOTzKmUJOdeWc3VZl0mJGH25ArKmnNvLuXsEuB1ImXblMyI5EUdal9AZeoADRMkOPZ+XB4VQvpcMfX2zuOLf28PNIBsZiHWGEB3ecs0mRAGMwEOQmqjlSUPWs30SjHIenpPReeU7RqaRbRAnUpoxMq2812y+D0HXDFj5JTBSHWiT8pGRrpRbZBtIuROmlvvSVoxkOo1CsQQrkcWgFyHlmFjYn0evtxRLnAmacUYU6v5zcos0G58uZrHT9E682jeEmT1ZlPOVzLfnP4F/de+AGRlomXaF24POOI/YSel7lHFS5g3tpK5zd/41fU6m6zB9xHZCt6WVW4JCdjKSYVHHDfpAhx3p/guT7TBDX6crwkEmvxixm0KUaEOs+wiVY8oy4ARFGFKmTlXK2fK8HGdOHOhjKbvKfrAGFyFsn6zHWGQ5+l5SyST6hwrI5hbA75oOMyhX2qQyrcq8pRziRBax5aAcm1p+lONX9kHKCEfKzWYcIoA5Ui+QWvGK7odyZgJyXmU95TnZzrlyiO7C68i3b4SELFfLlA6soLwyHyplU91Ooa/7Qo6P2E0jshOaw1LuFD1taSzPAa58PhBpvUJKyqse0BWUtdzryvEQhej3pexbqZepvHugnOyCGxQr+05yKyzDMFytx5D1cOMAhpeHk+zU8+1hll+Ab6fgSN2GfDxCH0Hk6LmVkO0lzHwfOuTzq8eirCFgpP+9n6S07FsJPX8x/HLlXMxy4Mk2czM6nWxv2RaGX0Ay9mCUfQRuVgrQ+pzsTz2fc1JaVpePpBN58EwXMF24yTZYheW6P2T76XqFPtK2jWBl/sn8w/u9WCrBkHL2ykrDtFM5N5B9I+/BlC0jx7kZ6vrmVtYp1v27lDmOeud4zVeO33///dh2223xyCOP4JZbbsHQ0JCOf/LJJ3H66aev94oQEVGTkBOyKodxd8lZFV544QXsvvvubxrf0dGB/v5+jDXmOBFRi2vhHG/0jK4Gc5yIqMUxx1HvHK+5cvykk07S2vi7774bruuOjP/ABz6AP//5z+u9IkRE1BzkKppahlYzefJkvPjii28aL22gzZkzB2ONOU5E1NpaOccbPaOrwRwnImptzPEX657jNVeOP/300/joRz/6pvFyK9eyZcvWe0WIiKg5VHu12chVZy3m6KOPxpe+9CW9w0qavnn99ddxww034Gtf+xqOO+64sV495jgRUYtr5Rxv9IyuBsvjREStjTn+pbrneM1tjnd2dmLhwoWYPXv2auP/9re/Ydq0aeu9IkRE1BxauY2zaq/oiqIIe+65JwqFgt6+nUgkNLC/8IUvjPXqMceJiFpcK+d4o2d0NVgeJyJqbczxqO45XvOV4wcffDC+/vWvY9GiRVpLLycXf/rTn3RFpEF0IiIa31r5l+p12XnnnbWTr1wuh29+85tYvnw5nnnmGW1ybOnSpfjWt76FRsAcJyJqba2Y482S0dVgjhMRtTbm+DfrnuM1V46fe+652GKLLTB9+nTtjHOrrbbSmvrddtsNp5xyyttaGSIianyt3MbZumy//fY48cQTMWXKFP2x+KGHHtKMnDt3LrLZLBoFc5yIqLW1Yo43S0ZXgzlORNTamOOH1T3Ha64cl044r7rqKrz00kv4zW9+g5/85Cd4/vnn8eMf/xiWZb3tFSIiosbWSL9Uyy/GhxxyCNrb2/U248985jP6w+26ppfbrTbffHOkUinMmDEDX/ziFzEwMLDadHJn1BuHG2+8cZ3r8sMf/lDvqrr88ssxb948vdVrk0020ULsggUL0CiY40REra2RcnxDaZaMrgZznIiotTHH59U9x2uuHB8mFQof/vCH8YlPfAKbbrrp214RIiJqDlEc1zSMJqkYf/bZZ3H33XfrD7YPPPAAjjnmmLVOLx12yHDhhRfqbVjXXXcd7rjjDq1Uf6Nrr71W+9gYHg488MC3XJ90Oo0jjjgC9913H/7xj3/orc8/+MEPMGvWLOy333645ZZb0CiY40REramRcnxDaqaMrgZznIioNTHH76t7jlfVIecJJ5xQ9QIvuuii9V4ZIiJqfGFUGaqddrQ899xzWrH917/+VdsSFZdddpn+cCuV31OnTn3TPNtssw1+8YtfjDzeeOONcc455+DQQw9FEASw7X/HolyJPnny5PVeP1n22Wefre2fyWt+7nOf0/UNwxAbGnOciIgaLcfHUiNldDWY40RENIw5jrrneFWV43/729+qWpjcdt6obMtA0jLgRzFyXqi9u5pGBFlj25Rb5gHLMBAiRtaxsLwUIONY2pZPGMXwwhihzmMgiGIkbRMdCRuWCX3sWgb6g0iX70UxJmUSmDdQRNqxsCTvVZYdxSgFEToSDrxyZYfJ/C4MhHGsy3mlv4gZHUl9raxbaabGDH34ETAh4+IDm0zAi0tzeHxhAVOyCX1PCdtE0Q+RTdoYKAf63pK2gTldaXQkK7u44IcYKAWY1ZmCZRqYlHExb6AExzQwUPQxBFfXNeVa6Bvy4IcxZnam8PySIWzcnUJfwUN3ykGuHOo2mNKRRK4U6LJl3Se2J7DjlHbc9uwipGwTO07twPu+ex9O2m9LpBxT55vekcKCwRKefz2HXWZ3j1yJ0pVyMFjyMbs7jSCMsFFHSv/2Zlx0p2zdZrI9JmVdPPyyj0I21Pc85AWY1p7UbSi8IMLEbhflIMaSoTKWtSWwcXda36O8N9kujmXotiiHke5DeU9px9Rt8Y7JWTy7cBCdSUu/bIpBjN60o+83YQJPLOjHRu0J3Y5ClievLcuXaTsSBvryIToSFqakTfT7lWOnMq2BjGPouP5SgJkdiZFlyH5PWDYiJwWEPozQA4zKm4rthC5DlinHYN6PkLLl9WT9IiQsU483+ewV/Ujfy5S2BBK2gSCWY9tG4EdoN30MRQ4so7K+09sd3aZy3MvxL+sA00bSrHxG5Hj1EKMcxrr/YjeDuARdphNHWFqMdb6sDeSDCNnIRsJ2UCqHyNgJXdeMY2Jhfx5TOjPwlpWxtBAgiOS4NvV9u5aJBTlf349lGVhRDhFlk3AtH0vLhq5r1pXPWOWzI7KGjyVxpT0pGSPbveBH+jmV5RpRqMtLWJV9snI23S4yTpYn20ymHSiFOq/sXxsRbFP2Z+Wz6K6cX8hfWRfZzpOzNhYNBbo8L9GGUhDr8SLbX7aHbLfp7SbKsanLkiXIfCnTqBx/ZmWby/zZdApOzkd30sJrOR9hbCAMY33OGT6mw8q6xEblO0iWmXVMPXZNVL4zhqeR9zHkh7oOun1M+f4ane/kWq4kG55ucHBwtfHSo7QMb8fDDz+sFdjDFeNir732gmmaeOSRR/DRj360quVIkyrSLMuqFePiv//7v/HZz34Wc+bMwbHHHosjjzyy5pyTq9PkCnQJbFn+0UcfjbEwHnL8jaJ8DoabhCHHen4QlptEHEWAacJwEojzg4DjAlFJp4+9EgzHqcw7uBxGKgMjkRwZ5PnKvC5gOzDbOhHl+hGWPFgrlsBIVqa3UwmYqQyCQgmG7SDyfbjtGQTFsr6+IcHgy9e4ifzCPliujcgL4LZl4OXyiPyV2VnydNpEZxbeYAHJng4UlvTrc4nONniDeX2+vGIIdsrFFlffhle+fjgKSwZWztcG07F1efJasoyg5MEvBfByBbjtqcrr+AFKK0pom5JFqiu5cvlZxGGE3MIhJNsTiOQcx6ucl5iWCTtlI7coj9z8xejeYpb+lWUn2hPITO5B33Ovwcv7ujwvV4KTSSIKI/j5yv/bpmZRWpFH5IW6LMMyUF6RQxzGCIrBv6ebkkVQKuvrBkUPYclHdlov/HwZuXlLdL2z06DbtX32FCx76iV9r6HnY2hBH9ITX0d6cg8WPvx39GwzCx0bT8PQgqXoWPndEixfCiuVBpCHmUyjdMf/AVGIuJSHNWkGwoE+fazHR6kAqzigOSyZZ/glGH4RSGQQW66shI6T/8s5lm7bGCivbJN5OKcKfuWvZKljVr6vlxU8PR+TcZJD5SBCKYzQX/T13KUj5cBcmXXdmYSOK6w8ryt6oY6X7JZpJAc0C5I2+vIeOlOVYzrtWnpeJs9d9MeXkE06KKycN+VWvtuGyoGOH85VOT8IowgT2pI6rb7ukIdEyoZXrhyn8ppREMFI2bBsE4Ef6nNOwoZfDuAmKssul3zEcQzLMnWe4e8TeZzOuijlPaTbEigVPJ1Xt7mcb9gmosCDaRnoybpYsXgIpm3qaZCbtHWZK1aU4CQq58QdaRcLTEPX0bVNHfyEBcM09Py1I+1oHst7lXPFJYMlZCdkMVDw0Zl2dXvK62QTtp7/yjxy7ju0ctvJoNtiZY1wZfvJuXwZvWkX7cnKeaGcF3z6HRvh9/9cqvvYjyL0uHJuFeu5pu4zOU4MQL6WZJwsW8i+1O8hPRcy9FzCsSuvJff0Sm7Ky8v5TG6ULtpenxwfjxolo1slx+U7VAUeklK48kOUECMTBrBsA6Y3hNBpgxMHSFqVc2n5fMj3dNK2UY6AZBxV/oZF+LaUay3ETgqeFyEjyzb/fS4nZapYzgcMA6moCLM8hLKUj+yEfpcPbyn5zhByTi/lK513ZbMFJT/Sz+nrkXyGI7SZRQSJds03mTYVBZDZDa8Aw3IwIZ2A0e9XvheyE/W8vwQbUqzvL4VaBtGEMkyYxRWInTQyxX5EyXZ9H4ZkjVfQ9xxle9EWFBDZGVgzt0e05BVYhRVwsr0oGa7WA8ROUt+jvG/JpE6/H0GqW9+fWc4hSncBlgOjnMPisouMbaKUnQQ3DnQ7W46jr+etyMF3O+CbCdiI9fkVpRht7ZOQiWLNrXRY1Pdo5pfruq0o+SjLeVJswetfAtgJGFKWlXMjxFhaNjEh2Q4jNhCbLnzDhiv7rX0KrMjH4ryUf4AuO6HvV8qcZn4QYXaClmMMv4AhL0LSsVAIK2XUFYGJnlIOpuXCtxJwYq9SlyP72mzT7SrztMtWt1JwSyswYHeiLZmAEVTON8zCCgy53XDMCKGVgBWFMKIAcSKDUihlXBtuaVC3YVGaMbJMhO2TtU5meLv2Rxl0yPd2tlePEyuQc8gEnEjWw9ayv2/acMIi7HAIYSKLgeLK8ywDSDophJkeLStK2U/KdFJXIDkg70fqBeQjEsQmpKRrSC4ksihKeRlAxooRmQ4sv4g41YFIjqdyTpcjnxnNY9PA0sGCvp5s50RuEQptU5GMyghjB0ZQ0uMRvosAJpJWpVwpry91ELItBr0Ik1FCtHLfCsm5pOHDM10YXl7HVeolbC2HyvuJkYATVD6jQRjr9o3goJzo0GNLthFMq3JuFZR1KFhZPQbkWJDpzThGOyIMBklYRozYSCKVTSPvRfr+8oFsB2l724CdX1bZv/K59goomWmtP5P3kA7LelzIazqhh9BwUYKLsi/lfwOuKa8ZVc71Vpa/k/L5k+1rAqZfQuRUzp/l/4XI0joJ2UayvfV7wK7U1STNULdlaKWQjAMgKI+cM9Ybc7z+OV5V5fgf/vCH9X4BIiIaX7TgXmOhWjpxXtXpp5+OM844422th7QdOnHixNXGSSh2d3frc9VYtmyZ/tr8xqZYzjrrLHzgAx/QW7DvuusufP7zn9e2zKV98rfy2muvaXMtMvzrX//Ce9/7Xvzv//4vPv7xj2s752OBOU5ERG8nx8eLRszoajDHiYhoGHP8urrneFWV40RERP8O4+oLy8NX78+fP1+vzh62rqvGTzrpJJx//vlv2aTK2yVXs0vbZNLL9Rsr6k899dSR/++4447I5/O44IIL1lk5fvPNN+Oaa67BPffco5X2hx9+OI466ijtKISIiKiZc3y0DHeU/etf/1rv/PrYxz6GSy65BNls5U7BNdljjz1w//33rzZObqe+8sor1zoPM5qIiMaLRsrxDWW0c7yqyvGDDjpIa+WlYkP+vy7N1pEJERGNfhtnkh+rVo6vy1e/+lXtMGtdpKkTaQ98yZIlq42XdsOloP1WbYXncjl86EMfQltbG2699VY4K5vbWJtddtlFrzAvl8trrdiXdsulsl2WJ+2eSyG/UTDHiYioEdsqlY61pdNr6Vjb931twkzu5vrpT3+6zvnk1mm5y2uY3Om1Lo2c0dVgjhMRUSPm+IYy2jleVeV4R0fHSPtlUrmxIdsyW7BgAb7+9a/jd7/7HQqFgv4qIG3KrNrGLBERbTij3cbZhAkTdHgru+66K/r7+/HYY49hp5120nH33nsvoijSyux1XTG+zz77aCX3r371KySTlXbk1uWJJ55AV1fXOq94l1u139jMS6NgjhMRUaO1Vbo+HWuvWhleS6fZjZzR1WCOExFRo+X4hjTaOV5V5bh0ajZceSBXkG8oK1aswLvf/W68//3v18pxqSz55z//qRUUREQ0NsIa2iqtdrr1seWWW+rV33L1mNxKLVecHX/88Tj44INHCtTyA+uee+6J66+/HnPnztWK8b333lt/bP3JT36ij4c7C5WMsSxLb+1evHgx3vWud2n2ydVs5557Lr72ta+tc30audDNHCcioreT443WsfYNN9ygOS4V5Pvvv782h7auq8cbOaOrwRwnIqJGK49vSKOd41VXjkvnZsMVB3Lr24Y4wZA2Z6UTN7lSfNjs2bNH/XWJiKg5SOFYKsSlAny4rdJLL7105HmpMH/hhRe0Mlw8/vjjWuAWb2yf7OWXX8asWbO0iZXLL78cX/nKV7Q3dJnuoosuelu9X4815jgREb0djdSx9n/9139h5syZ+kP4U089pXcZS9aP5+Y9meNERERjXDkuleJ//vOf9Vd5qSjYUM2qyO3ucuu79Doqna5MmzYNn//859dZQSHtwcow7I1XORAR0dsT1dCxx2g3cSYF6HW1SyqV3ZJbq3biterjNZGr0WUYT5jjRET0dnK8kTrWljbJh2277baYMmWK/kj+0ksvYeONN8Z4xBwnIqJGLI+PF1W1YH7sscfiIx/5iF41LhXjcvua/H9NQz3961//whVXXIFNN90Ud955J4477jh88YtfxI9+9KO1znPeeedpm2zDwxuvciAiorcnjOKahlYShiEeeOABbQu9kTDHiYjo7eT4cMfaw8O6KselY22p/F7X8HY71l7VcD8jL774YlNmdDWY40RE1Orl8XAUc7yqK8flljlpw1VOOA444ABt5kTahxtt0qmatEEnbb2KHXfcEc8884y2LXv44YevcZ6TTz4ZJ5xwwmpXjksFufTQ6lqVK969KEbWMRFEMYb8CI4ZwgsjWKaJjG3qdI5pwDaBIT+GZRgY8iL4UYyOpI1SEGNZwdO2e0y4SDsm5EJEaeh+oByiFERoc20U/BBZ18aszhRKYQTHMvS1TcTI+xE6EhaWFkKYhoEwivR1ykEEP4zhh5EuM4wBozgAy+xExjHxm+cWY3ZnCkU/xIqSDyCJjdoTcExTX2/BYEnXyzZNTMg4WJr3dX2mtifQnXL0uf5SiIFygC16M/o4YZtIWAYmZxO6jI5pDjbuTmNhrqwfpIFSiPakgzbXwmuDZX39v85bgTkTM9h+cgZPLRrEtI4UhrwAHWkHvSkLAyUH9391D9z74lJ4YWW7vdJfRG/awUDRQzkIMeTFun2WF8tI2hYmtyXw96VD2HWjLvhRhGUFX9+X6RhIOxYmZhxkk/8+ZOcNlDClLYFyEKMr5eg4eV+yXWW7TW938MKyPDbvzaDdNXU9upKV6WT/ynbPuhaGvFDHl8IYacfQfejahh4HU9sS+rccyTwmcl6ASVlXt8XSQoDulIWUHCgIdZ8mbANymAWyl+MIhinHkuylAMsDE22uqcuR7VqM5ZgEkraB2MzAKOcQ20kdEFd+3/NjwEGEfCDHo6wz0JawYJmRHody3GZME51JE4NepMf0Rm0O+sshikGsj1O2ASMow3ZcfSyfAtkW8rwcu0sLPqa1uYgtB2Eo01e21fAgx0bSduCFPnJehG4rhGs5+n5LbgJJK9QfzazCcpTjdoSZHthljBzjy3OV5iyWFQL0pm24kafLG/TkcyfHnxz3sR7vfYUArmnoe1ySD1AOZbtaSK787Bqhr9ui3bX0y2tR3sf0Nkc/R8tLIaZkZWsF+j5le/WXfHQlLWSjIThmUpfXV5R966Ajaek2LAYRCqEByzR0nWXfCrm6WD4fnUn5LEfoke1uyDQhLBMIIkPnlWNJXs9cOc+gF6Nb9hUM/c6QdZX9LZ/t4V9tZT++tnxIt7+Q5cpryV9ZlnxmJcLkedlGcozIa2VtOQYjPSZX/bVYpjGMGF12hIHA1Pcir2dF8h1Rf/I+q+3Y462u0h5v5EdiadNcCv4bIierNR5yPLZc2cCInRRg52FmKlcwxsU8EIWIS3nEYQgjkULslwHb0eeMRFLOpPT/Zlsn4ijS/8cDJRimBcNNyorCbO9GNNSPKLcC9qQZgGkh7FsEwzIReyWdLi6X4GQz+pxhmogKOXgr+uG0pfWxny/q8oOiByvpwm2vtH8bhSEs19FxlccR4jCCl8vrNKW+AaR6OnT9Rbk/h0RnGyzHhpcrwC+UMHjtafq4tKKEZFdS500lXV2O256BnUmufH5A18XOpBCWKnfS2XLusqKE4ooSpr2nF7l5ixGUPHhDnq6Ln/d1OU7SRnZiRuc5YOEzeOlLB6PYN4Atrr4NT3xsH90WiU4PifYECsuKKKKEtilZRH6ARU8sQdecTphWQdfPXLmuXt6Hm3F0HtO1kOioVKjJ65uWZLyN0A9Q6i/qdH6hiFDypW8AfinQaSedeBly15+BIF/U+WQbR2Gs2zksebBTjr53u70d8YKlCApFXa5sRytfgunauu3NVOW9yX6MoxAIZFkholy/7mM5bsK+hbCmbYbYdoHcMsTJNsAwK7ksf00LESrf2fIdLyQH5DtZxrUlTCzNR/o9L+d9cj6zUUcSuXKAzXrS+EdfQc+p/IKH9oSNQQSa5XIeI+c4CwdKmNmT1nGSHUOlAD1ZF4PlAK5t6jTLhzzM6EnDtSrf9yLlWugv+vpX5pM8ETLvQNFHZ8rBklwZV/zn9vjMjX+rzJN1kSsFmNljaWZ6cqw4JtIpB8VSgOKQh2TGge3K8W7ALwfwyiHiKEYUREDC0ufygyVdXiiZmLBQLplItVWOdR0fRki3JfRcwUnYOq/8P92e0GWZtotlr+ew2fROHSevK/vXzVjwvBC2a8J2LH1vry0vIPAjTJ6YwfKhsr6/XK6s559Fr/L5kW0yXBCU/+u2lPUF0LbyPFKe78m4KKwyj2wLT87hkza6U5X1l2Xq9pT3H8a6T8vyfhwLtz6zEG0JW8sYw/S81TA0IyXLdR9JxqOyT+RYkcy25VQjruS/ZLysrsRlDCnEDrcPWjnva8YcH+2OtdfUabaQK8ibMaNbJcejRBb61eQkK+VoJ4VQygC2WymnR/KZAEqxjYRdOb/V48+00C9lkCiH2M0gYQKG58EzknBtF2a+D+2ZHkRGF8zyENxCH6J8DkaqHbGThhGFMIISYFbOu+3+1xBmJyBpmzBKJYS2q68l5/fyV8j3hnyW5bMehEBXwtTvyRguzDjU83vNAA9wZNVTHTC8PGzkdX4pU8hn24llOSacWPLMxGA5wgTLRWzasJe9jGDCxgjbJsEsDQCWA/glIPQRuyldnpzz5IMY5h9vRLzjvjDzy2GUcig6XVr2SLkZGP5rujzdXsk2Xa/k0FKEkleJSob5yS54Ax4yNirrYBRhFgeQz05DNijByi2FNaEDA+XKeseGlGVDvDzgaVlLGF5B912U7tL1TTsZJNo6UcoPwiwtRdAzR8/Vgp5ZyMSVOpXYTsCRckoYwIMLx7R13zv5PsDswSYT2hC9+Kwuc4WU5UJf89aLTMiryrSyTCsCOhIG+oqVfWn4BVhOErJz5PtU3r9sOzOOkEm0IzLSMKMYcaINjtSnxBF8KwFbDrJkGyz5vl25LpZhohhbSMt2Gv7+ddvg+pV9aZf6dTtK+d6JAoTJdqQlu4aWAqlOfY/DZXfPrGSHfJcr2QdmQr/fZbtKnkjZWo752LTgyLmIWckJyRkz9LVpqSF0A0GsZVCpq5HlS+lSM82PYNgxjKByjlSCjZSX02lk30rZV8rZ+XKIqSnAN+zKuYJR2Se6CWQdLBcJo3Ju40QebNl3sdSnRMhpGdis1HOElc+N1BXIOgflEJ6zMuPlOHFSWJYPkHUsTIgHYKS6EMSV/VeWei05Z3BS6DQq9RWJuIiinUXSsnW/GOW8Hu+yirJ9PDMBS/aVrqqBlHxXrDynkdySuo3lpQgTEpbWDcjnS5cTelr/EluVnF9ZzNbXNv2i1vVYpguJX6kHkW0h5yJ67Mi5nuwuv4TYqLw3yy9U9q2c88exbhtZN1dWJTZR9COkbUPr6JygiLSTghGWK8dlFCMfWsjGZQyWK+cZ9daq5XFrFHO8qspxscUWW+gg7ctJMyfr6vCkXuQEZ6uttnpTB2y/+MUv1jpPPTqHISKitZNyw8qyw1uqdrrxZJttttE7nxqtjwzmOBERNVKOr0/H2tJ0ijSn9uEPfxg9PT3a5rj0EbL77rtju+22a9qMrgZznIiIGinHx8Jo5XjVlePDpHJcLF26VDs+EZtvvnlVVwfU6t3vfvfIawz7xz/+oR2wEBHR2Ihq+KW62unGk7PPPhtf+9rX8K1vfUuvhMtkKlerDlu1zdaxwBwnImptjZTjtXas7boufv/73+Piiy9GPp/XK5JlnlNOOWVcZHQ1mONERK2tkXJ8QxutHK+5clxOTOQE5sc//rG29zJ8afthhx2Gyy67rK5XlMtVALvttpvexvWJT3wCf/nLX/B///d/OhAR0diope2y8dTGWbXkajYhtz2v2oH1cIfWw9k5VpjjREStrZFyvNaOtaUy/P777x+3GV0N5jgRUWtrpBzf0EYrx+31qbCWE5Jf/epXemW3ePDBB7WjTOl8RTrQrJd3vvOduPXWW7XdsrPOOksvm5erBA455JC6vQYREdWmlX+prsYf/vAHNDLmOBFRa2vlHG/0jK4Gc5yIqLUxx+uv5spxae/75z//OfbYY4/Vau5TqZRe3V3PynHxH//xHzoQEVFjaOU2zqrxvve9D42MOU5E1NpaOccbPaOrwRwnImptjZLjy5cvxxe+8AX8+te/Hmka7ZJLLkE2m13r9NI02F133YV58+Zp89wHHnigNpHS0dExpjm+sg/X2m7jmjRp0pvGT5w4caQtOCIiGv+/VFc7tKI//vGPOPTQQ7VpMOlMTEhzZHKn1VhjjhMRtbZWz/FGzuhqMMeJiFpbo+T4IYccgmeffRZ33303fvOb3+CBBx7AMcccs9bpX3/9dR0uvPBCPPPMM7juuutwxx134DOf+cyY53jNleO77rqr1vSXSqWRccViEWeeeaY+R0RE41sUxTUNrUau6Npnn330jqrHH38c5XJZxw8MDGgfGmONOU5E1NpaOccbPaOrwRwnImptjZDjzz33nFZsX3311dhll13wnve8R/uhvPHGG7UCfE222WYbzeH9998fG2+8MT7wgQ/gnHPO0SvPgyAY0xyvuXJc2vz+05/+hI022kh7FZdBOkZ56KGH9PJ5IiIa3yRfwyqHcVamrroH7SuvvBJXXXUVHMcZGS/9dEiAjzXmOBFRa2vlHG/0jK4Gc5yIqLWtT44PDg6uNgxXKq+vhx9+GJ2dndh5551Hxu21117avMojjzxS9XKkUru9vR22bY9pjtfc5vi2226Lf/7zn7jhhhvw/PPP67hPfepTejm91NwTEdH41sodgFTjhRdewO677/6m8dKOWn9/P8Yac5yIqLW1co43ekZXgzlORNTa1ifH5aLmVUmLIGecccZ6r8OiRYu0ee1VSQV3d3e3PleNZcuWaXvj62qKZUPleE1Xjvu+r5e+v/rqqzj66KPx3e9+V4fPfvazDV8xng9CeGGsv5zIsVHwI/hRDBMG0o6JUhDBMgwUgxg5L9T/e1GMjoSFYlCZVhR8WU7lsYwa9CIkLQOvDpSQdW1dTnvCRoRYH/tRhIW5Ml4bKGGgFGCwFKIcyS84MfpLITKOBT+MkfdCndYxZX0sWKaBwXJlXJyqNEw/5EXoTtm6DinHwlA5QGeUw5Ssi4kZB9PaE5jVldL3Vw5i2KaBiVkHbQlLx23clUDGtfBKfxEJy8TivIdZnQk4lgkn8jC1PQHTMDCrM6XbRExoS8C1DfQVPKRsQ9dP3uPkjiRmdab1cdEL0Zt2kCuH2Kg9iVIYY3LWwSm/ew5T2xK63vKeDt5+GjbtyeB9m03Q/TC9I4Wsa2FGRwobd6cxoyMJL4iQcU19j7Js+SvbU95f1jHh2iYGSz427krr+sn8edmXYYyUayFpmWhzTXQkbbhxoO9t0VAZCduEtcrR3p12sFF7QredvIY8tyTv6fKW5j3d/5YBLB7ydFtUjpcI5SBCwjKQcUxkXRMp28SSfADDMCBHSMY29dgIoljnT9oGUkaIEmzdH+WVvSHIsSXHkWlA113EThpGHMEIPcC0YRhAKYhRiirrIseL/LVKgzBQWbYcJxGAnB/re5R5Uno8V9ZBHss0YbJdt2cWnq6njLNN6DRyTOnuNmTdAdcyKsuW9bcqr2HGoR6z4crPgfyV6YS8L9k+9orX9DNWjk1dV/nsyHbqbkvDsQxdvyACSoar8w0fSzKtHFuyPWVTyF9ZL9mOCctCd1I+g7FOE5uV3/Pkfcnry76Sz6CQ/WSVh3QdZJ3EtLZE5bPqZpAP5PP174NAppP1ls9Kzov0cy77XbaFHDuyHdtcS9dTjmFhhWUsL/o6nbyGzCPLkedlHWWq3pSl6ybDopyn08j7kun0GDYN/b8sv901dT45/mTTyvuS52Q7yXrL51beiryWzCfLSch2APRYksfyvuV14zjGikCOc0P3j8wjx91o0GOhhqHVTJ48GS+++OKbxksbaHPmzMFYauYcRxwhttzK96RT+R4xTBNmpg2GaSEul2AkUkAUIs4P6jRmRw8gz5UKiKMQ4UAf4nIRhpusLFO+EywHZrYTsVeCmcwAtqvz6PJtB3EY6bLjqPK6/lBe5zcsE1F+EG5HG8KSBz9fhGlZcDIpfa7UNwi3LQM7mdDng1JZ/x/JOcRgAXYmCT9faaIuO20C8ov64OUKSLQnYDk2AlmeY8PJVNa1/cizdLk7//YexPL9vjLUyv05FJf06+s57RkYloHCoj5db9NxVr52gNJgGYOv5RD5Acr9QwhLlatFIvn+WlFCKAEAoP/VAYR+iN9M3RblFXmd/sXjP4HQi+APeTpfojOLdG8KhWVF/b+8D9k+dspGsiup621aJro3nwRvyNPpFj2xGPnFeX0NWY+BVwd0W8jy4zDU8V7eR+QFug1kuaFXGf/3w/ZHqW9At2dQrEyT7Kwcr4UlK+C2pZGbv1j3obxvO5uFl6u8lmx3WR8ZHxXzgOzTwKvsW5k+8HV/y7GBwJP7VIFCPwz5f7YHRhjosaeHoJOEEfojhQz5I9/1oZzXRdBskO9fyTz5Pk/apubY8oKv50iSHzKvxKecb8l3uJxD6aEo5x3mvwch53py3iOPe9IuOhKO/n9Wb0bPq9qSle/44enltYdKAf7nfZvoOUbarRzHsgw5R5LhmJufgBeEOq0cR+HKQZYh6+IVA31sSpbIsS/HmnxM5HhfOd5J2DBtU/8m046eA9mOpc/JIPPo+re56OhOobMtgTkbtcMvB0hnXbgpG5n2JKIwhlcO4SZseEUf/QUPlpzLmLL9Vm6DpI0wiJBN2iPvZ/j24AltSRS8ELkVRWy08rxQppFxw9tRtpHsFznWsol/Z6K8R5lOpm9L2LptJrYn9HW6s66e83WnXF2G/JXzS/2suvbI+amcY0oGD58fSt4NeYHuY1fOrU1Tjw/ZPZX9W3lt+SuZPlzWkLcj08l5mRxH8n851+xIWno+NBpaOccbOaPHfY5LrkYh4JdQlLKVXNUo30V2slKuiAI9D5bPTMKslHXku8AzbK20kOkMv4h8EOv5gHzHSplJFIK4UoaS79h8n37P6+uFHszCCpjlvJYjbKMyzogCmIgRJdqQMStlLCkTyHrIuslnUcpoUqaXz7t8X8u5d+QkYQ0t1c+FrCvCQMthsl5eskvLc1Eio+UZKY8N+oCDCJHlaJm1Xd5Y6CF2U3r+IVkj6+4lOmD1vwZraBnMUg5xok2fM0o5XTf3vQejKEvKdGsOLS+GWuY2igOIkm36XqU8ko8sJOPKe49tV6cV8r43T/vYqDur66bbppRD2ooRpbpgBGUkhhbrtm/z++EsfVHfu+RXprgMeT9GmOmB1f86wvbJmpXyveatWKT7SfeNbNNyDoZXxEA50joI2VaaUXFUycagBEceJrJaTiwViwizExBlerTMJ9tFyr5SromyE3SfmKUB/Y514qBSPnIzms1GXNnnsh2Uk1x5DEUwV75v2e5yeiP7R75PTS+vx47MkQ8rmW2WBrWcKsel7Nes4WvZUNbZ7l+AINmpy5L34Ru27ncZdNvKOabUA9iJkfKXHD/yHS7bR6YZPm+Q/SjlPzmOdN/GlXKzbDct20mOmM7IulbK8pVyue5PybKVeSGfCQ1nPX+o7Ev5LGScSvlUtpvWE1iV8wY5rqJ0l563yD6Q9ZfPg+kXYeYWwxp4XeuoZLwco/K6w8eD7EM5915cjHWd5TiWsrKuk5yXB2X9vOh6BJ4uR9erOFCps7AMfZ+yn2RXmfk+XadAPj7znqssx83o81KLptvRgD4vZe8hP9K/VuRXyrkxtJ7B9Ar62Zbtp8twUnoeJ58d2c4ybUo+C4Y5Uocg70/K3u1WqPs8GRYr3xv63RRgCK7uQ12mfD5DX/e5vEfZn5L/sg+kjJ22DV1n+Zzr94zsHzlPjCvrL8f78HHTKDk+f/58vUp7eDj55JPXuOyTTjpJj4F1DcMXSr8dcvX6fvvth6222qqmSvrRyvGaak7kkvVV2xonIqLWU0vbZeOtrdJqSGH1S1/6Eq655ho9eZA21+S2s6997Ws49dRTx3TdmONERNTKOd7IGV0N5jgREa1PjkvTJTK8la9+9as44ogj1jmNVEJLJfWSJUtWGy/thi9fvlyfW5dcLocPfehDaGtrw6233rpa8yhjleM1X1b43//93zj//PO10fVq24QhIqLxQ65zHL5Io5ppW4382h5FkfbJUSgU9LavRCKhgf2FL3xhrFePOU5E1OJaOccbPaOrwfI4EVFrG80cnzBhgg7VdA4tzZg89thj2GmnnXTcvffeqxkrHXSu64px6VBTsvdXv/oVksmVd/SOcY7XXLv917/+Fffccw/uuusube8sk8ms9vwtt9yy3itDRESNr5XbKq2G/IL9zW9+E//zP/+jt3wNDQ3p7WLZbBaNgDlORNTaWjnHGz2jq8EcJyJqbY2Q41tuuaVe/S1XcksHmdLs1/HHH4+DDz4YU6dO1WkWLFigldjXX3895s6dqxXje++9t1Zq/+QnPxnpHFRIhbxlVZrQG4scr7lyXHoj/djHPva2XpSIiJpXLW2Qjre2Sqtx1FFH4ZJLLtHbxCSoh+Xzef01W24BG0vMcSKi1tbKOd7oGV0N5jgRUWtrlBy/4YYbtEJcKsBN09S64ksvvXTkeakwlw40pTJcPP7443jkkUf0/5tssslqy3r55Zcxa9asMcvxmivHr7322vV6ISIiGh+k3bLhzlmrmbbV/OhHP8K3v/1tDexVFYtF/dV8rAvezHEiotbWyjne6BldDeY4EVFra5Qc7+7uxk9/+tO1Pi+V3dLB7rA99thjtceNlONVV45Lmy4XXHCBtgnjeZ7+MnD66ac3Ra/YRERUP2ENYVztdOOB3BImYS+DdDKyavtpYRjit7/9LSZOnDhm68ccJyKiVs3xRs/oajDHiYhIMMdzdc9xs9oJzznnHHzjG9/QdlymTZuml7FLZyBERNSaYVztMJqkN+xDDjlEe96W24w/85nPaLtj6yK/WEtbZasOxx577GrTzJs3D/vttx/S6bSGrLRpJr1vr4u8vvx6LsvbbLPN0NXVNTL09vbqLWBjmZvMcSIiarQc31AaPaOrwRwnIiLBHN+s7jle9ZXjcnn6//7v/+Jzn/ucPv7973+vFQdXX321ti1DREStIYyqv5JMph1NUjG+cOFC3H333dqm2ZFHHoljjjlmnbd3Cek45Kyzzhp5LJXgq/7yLPk2efJkPPTQQ7r8ww47DI7j4Nxzz13rMv/whz/oFWkf+MAH8Itf/EIL4cNc18XMmTNHOicZC8xxIiJqtBzfUBo9o6vBHCciIsEc/0Xdc7zqynG5iu7DH/7wyOO99tpLf3l//fXXsdFGGzX8EZqwTFimgRXFAO2uhYFyiIRtIO0YOj7tWLAMIOWa6CuEsMzKATcURfCCGK4NuJaBzqQNyzCw3PAxtS2BlC3LBRzTQMEP4UfRymUZGCgHmJJNIGmb8KMYS/Ke9hQ7tc2FNLOztOjhlRVF9KRdTGlLoBxEmNyWQMKu/NiwcKgMxzSxuGzo478vHcLcae3oKwS6rr1tCSD2df27khb+0VdGwrL0fUmj+xYMBCEwuzOp08t6ZB1T10/Wd8lASW8d6E078EwX/cUCulKOrrdMI/9fMFDUabeZ2AbTgI7PuKY+XlHy9cTatU2UggjbTspiWUHGATkvxLtmdet2iBDDD2Pc/9IyTMq62Lw3q9uqI2nrOt3/ynK8Y0oHJmdspFZuu46Eo9tSnl+a9zCjI6Hvc9PeDDqSDiZlbCzI2RjyQizMlTGjI4UJmYQutxzK68lZv6/vTZ7viIbguW26PFlWyjHx6OtDmNbmYpPutO6Pxfly5VixTWQcEx1JS9+vF8YIohi9KRuuZer2sPwCupMpXaeelIW+Yqh/ZTqZP4wBKUtIucMzbD2GZPuVgnjkeOhIVI7DNtdCZDmw/CJiJwUz3wcj9IEoQGx1wI8MtDly7FnwI2ApMuiwDJiGocsp+BFc00DGsVGUtpb8CFm38hryPtw4QCm09fU9w4UXBuhIyPEZ63uTaWS5CddBHAd6HCYtQ9cz70eYgAA+bOQ9X5fZm3TglSP9TCVMYCCOMeRHmGgn9HXlcyKfCVmOLNvrXwLXSuq2KAaRHjOL8wHmdDj6GsuLvn6O5JhNWMCQF6E7ZaPdNbFoqIwYLkqhvCcbRlBCEFYqMeU46U27urxpbbL9CohNR5cl+2GgLMuRbRYjgoGMbSKZ+fcPeTL++WUFbNaT0v1gGMCrhRJmtCcQug5sA5g/WNZ11w4vohiGn4cfVr42pUg53FyWbCd5Ldn2si3lWVn+hIyLoh8j7QClMIZRrmxX2UayvLQcA/kAtll5LOT/8nmVdZZx3spjRbZt3o91X8t4Wb7sJ3mvcrgPBBHaXFOnl3cpx+B4v43rueeewx133IG//vWv2HnnnXXcZZddpll14YUXrjMcpTJcKr/X5K677sLf//53/RF40qRJ2GGHHfCtb30LX//613HGGWdo+K7J+973vpHORKZPn95wPxw3e44bcQQYJmLDhOEmAdMG4ghxMVd5PpWBYTuIrQxMN4ko2QbDKwKpdsQrlsDq6EHs+zASlebgosHlMNNtiP2yzhv1DcLsmoi4lIeRSCLKDyLK9cNub4fhuDBTGQRLXqusjGnBdGzEUQQ/V4BhmTAtq/LXsWHJSQOA/n/MR9eWM4HBPBKdbSj35+Bkkhh8eSGspIu+5/vQvcVMlPuH4OeLiMMIVtLR50p9OdgpF8W+QYSlMl47/WgEJQ+PfnhPZCZlEHkB/EIJdiaFFS8vR7Kn0u5eeaCMQl8eGcusrI9rI92Tgl8KYFgGCkv6EXohDMtDKPmRdeEkK+sbhTHiMIY35KN9ehtCP0RxyQpsesXP8dj+H9RprGQCdtJFUAx0Pi9X0MflAQ+J9gT8vIdMZxaRH+j7slM2Bl4dxECujOzUrE5TWFbQ+dO9Kdi6vASWPrsMbVMrvcy7GQem68Bc+R76/rkcE3c2EfoBSitK+pq6zy1TX1teS7ZN5TVz8AcHdZnyfG7eYqQn9+h+srtTeozk5i2AM6MEs70HceAjDjyYyTSiYh72pOmVcbYLszigx1mUyOrxZ3gFRJkezV85fywFIYb8EKZ8X6/sGEnO2CRPJPc1C8NQz5GGs1+ybN8tJuGnf3sNjuZl5RxPZJM2ZvakMbsno+dfybSl36ETVp4bSq56mqM+OjpTOv1ry4vozrooenLuWsmH0+98Xs9XCl6oj+XcSs7VOlPOymlcXY7uT9NArhRgo660Tl9K2PC8EKmkjWxHEn45lI8ZkhkHobx+OUAi6SAMI2wxpR1D5QB9i3JwEjZsx9LxlmUi8CJMmpDGQMHHZpPakCsHMExDh86OJHJ5D6W8r/OYks+Ohf4hD22ZyvdrImFjSmcKRS/A4EAZcyZk8fzCQRRLAVw5WQCwxdQ2HSfSbuU9am6uPNdIrfwcyntMphy0yfZaESNlVsoEsk1fW1HQ9y7zLh/y0JF29PxX59P9GOn56lAZsOV9hREiU85TK+eIcp4+vG/kvET2dVoDuLJ97VjWCXp+aps2AjnXsQ3dP3JOhJXnErK+clzZZuU4knkkPkerD61GyfENqdEzuhVyvByv3OamqZ8Q+cykpayABJwohBEGSKZMWJGvZQ/HADJSVjcMtDtAbCQ0fzPyvRk5Ol3kpGCYNtJWLCf3iNKdMKRMVSogSrTp97hOU8ohynQjNgw9j4jcDIIYsA0ToWHBtSI9ny8HsX43y2dWXve1gTKmtSf1HFvKe1Z5CFb/Agw6EzAp/wqidFel/Vyj8r1ilAqI7SQSrz0BY9r2KMhNh/KaceU7RT/XThooDiBsn4wo1YG0qaUKmOW8bp7YSVTeg+SQlAtTPQhffhxe9+bI+sVKDpWBCWkbRn8ZYcdU2Ev+qWXFbFTQ9xb2LUI8ZWudP2ybVHnfpo2F/Xl0JUz9v+ZaHMFa/gqC3jmwls9DaPfqNov7F8OdMlvLWmbfc2ifMQFGWIYRBfBldSduBmtpCWYph0SyDWF6sj5X2c498Acr32/m0n/BlW1kubo/40QbrKGl+t66/KXIWxORSndhIE6gIw5g+GV4luSnAcMvwbXSei5npNqRjyz0yincUIgo3Q6zuEK3WcpO6vaHX9L9kZT6B8OB51e+l1NSqCsFSBkhCnYWqdAD4CALDyUjofNIebo99FFEhE7H1nIXfBOwHM30CJa229xfCnU7O7apx1VoOpXcCSv5a4Y+hvxK7rRFeZSdDJJDi5FzJ1TKaWGMrBnCCMrIB7GuwxBcZM0AvmnDCsv6XrS8t7LsLPUHjg1dNlCpD7DlSctGQg4v3dCW1h0MlyWlzinrWFqubjc8xG4aJTMBUw7EZCciL4TfMQ12eVCPAb97lhZuK+V4OV5jmIV+lJwJuu/keCmFPvzYQjGIEZouXL9QOTePIy0DyzlPbxQiGRaxPErATVbOS+U7SjMnhm4Dc3let4N89uNyCabsj9BHp5uCEXpIW1Lm92DKfoV8B8i5v4tCEOv5itS5SDlfzqvCrByXnpzAInZT+tkzigNYYnRiciLU/ZsMPZ3GchMI5RxXznXlXL08BM/JwIk8fX/6GZY6NNl+bkaP51jqaGR7GAl4YaTbVkh9kOS5LMsxgdisrGtlH+kJNRw7gYIl9RZSQ1N/zPHpdc/xqivH5XbyVdt0EXIVnVypR0REraNRwvjhhx/W26SHK8aHC4oSlNIL9kc/+tF19qz9k5/8RCvI999/f5x66qkjV4/LcrfddlutGB+2zz774LjjjsOzzz6LHXfccZ3rJb9aC+mVWwqy0k/HqrbbbjuMBeY4ERE1Uo6PhUbN6Gowx4mISDDHUfccr7pyXH49OuKII5BIyO9TFaVSSdtpzWQyI+NuueUWHq1EROPY+vSOLR1hrUqyZNU8WR+LFi16U6cbtm3rLVby3Nr813/918htV0899ZReEf7CCy+M5JfMu2rFuBh+vK7lDlu6dKk27/K73/1ujc9Lsy1jgTlORETrm+PjRaNmdDWY40REJJjjR9Y9x6uuHD/88MPfNO7QQw/lkUlE1GKGm5mpdlohtzCv6vTTT9cmStbkpJNOwvnnn/+WTaqsL2mTfJhcIT5lyhTsueeeeOmll7Dxxhvj7fryl7+M/v5+vXpdOv+89dZbsXjxYpx99tn47ne/i7HCHCciovXN8fGiUTO6GsxxIiISzPH+uud41ZXj1157LY9CIiJar9u45s+fj/b29pHx67pq/Ktf/areqbQuc+bM0SZRlixZ8qZbjpcvX77W9sTXZJdddtG/L774olaOy7x/+ctfVptGAldUs9x7770Xv/zlL7W5F2niRa5S/+AHP6jv/7zzztPOPscCc5yIiFr9duxGzehqMMeJiEgwx39Z9xyvunKciIhofcNYwmrVyvF1mTBhgg5vZdddd9Wrvx577DHstNNOI4XeKIpGKryr8cQTT+hfuYJ8eLnnnHOOVrwPN9ty99136/pvtdVWb7m8fD4/Ml9XV5fewr3ZZpvpVeqPP/541etFREQ0Glq5UM2MJiKiZsccn1j3snbzddNNRERjKojimobRsuWWW+JDH/oQjj76aL3S+09/+hOOP/54HHzwwdqeuFiwYAG22GKLkSvBpemUb33rW1qh/sorr+BXv/oVDjvsMOy+++4jnXfsvffeWgn+6U9/Gk8++STuvPNOnHLKKfjv//7vqtpJ33zzzbUNc7H99tvjBz/4ga7HlVdeOVIBT0RE1Oo5PhaY0URE1OyY4y/UvazNK8eJiKhpf6m+4YYbtEJc2gyX26o+9rGP4dJLLx153vd9raiW3qyF67r4/e9/j4svvlivHpO20GUeqfweZlkWfvOb3+C4447Tq8il02lp5/Oss86qap2+9KUvYeHChSNtq0sFvqynvPZ1111X921ARETUrDm+oTGjiYio2THHF9a9rM3KcSIiatresbu7u/HTn/50rc/PmjUL8SqdiUll+P333/+Wy5W2y37729/WtC4vv/wyZs+evVpn1dLcy6uvvornn38eM2bMQG9vb03LJCIiGs85vqEwo4mIaLxgjte/rN0yzaoMlkPIuZ0JA1EcI+2YsAwDYVy5JUEM+RGGvAiuZaAURFg4VIZpAK5toL8YwAtjGAaQ90O0uTY6EhaStgGpd5HeYv0owtS2BGzTQEfCxKSMi85U5fcHP4zgWAb8KIZjQl+j4EcohREKfgg/jJF0THQkHF03ef3ZnSlMzLi6fnICm3VtXXZn0sbG3Wk4pimfCiwvBnCDor6vlGPqegpZjryHLhdI2CYsv4AJaRtdSQfdaQczOpIoBpVpZbmVeSz9K9N3JGxsPiGr6zLkBbqtTMNAQtc9xJKhMrKuhYltCZ1PtsGszoS+r8VDnr6+vN+hcoQVJR/TOxKYnYkxOeti6wlpTG9PYFLGQdK2dNvIuszqTKEzaaE7ZSHjVtbl6SU5nS4LD1v0ZjEp62KiWdBpc+UA5TBCNmHq4+kdKSwvhth6YhawHLQnbPQVPF2OrrttouDH6A4H9D2lbAPT2hx9flImAcuQfRVjRSnQ46MtYWGgHGJJ3tf1kv0dAfDslO4XIwphmQYsE1hSCDBQrhw/bcEgykGMhAldjoyTZcv7si3oPpIPn2yjciD7MESYbAdCH1GyHVGyDYZX1P3ZboUwQk/XQ5bT61SORdnfna6JMFr5BRnHaHdlHU2dTo4ZeU3Dy+t6yDyp2EPKNnVbbtTm6POyP2XfyXrI6+m2yvfpcaOfjThCOYx13eW9GKGvy2pPmDqdYxr6XsP2Sfq6pl/C0rwPL5L3GMPKLdb5ZBslbAN9xRDtrol8UPk8yTaWz0FWPpNmZVvZ3hA6khY27kqhtPIY7YlzKCc6dPvJWsr2kOXJ59YuDwKGfB5CTIgHdLvKZ1DI+xWy3GIQYXIiHPnMyzaT9V+YKyPvhbotZXPKesvnWo4f2UYyXj4icaINU9oSelz///bOA86Sotr/v443T94cWJYsQQHJqCAg6QmioigGRAEVVBRFTCg+fUQTyjM9Ffgrj2fCLIoEQUSSkoPgAgub08zcfDvU/3NOzx13YHeZhdmZe2d+38+nZ+7trq46daq6Tp261VUDtSS8xCv1qL8m8SZyyfMkdUXynPeTfAlhs0xkzcsgKXdB9CP3ig5052kDlcvVcpSyi/X5yHlJvL5jIy3tVGS0LESGrXrzqvPm87slZ3slMo7+mCrIZp4yOH7yySfjhz/8IZ555hk9n81msccee3BgfCyIGjDpAozja9tk3BSsbCes6fNHBNPrtgsj7YI8Y93TAdeH5XmwbBuWn9HzdqFL2w3Bcv3kv5+GqZb1uwkbsDM5/W6CBkyjBq+jA3FxHaJaAyaK9bA9F3EUwUn7CMs1/R8Hof6X6/LfyWQRlGtoDFbg+C5qawdgSxsehEm6TmLzolqA/JxpsH1Hw4blKuJGiHp/EVGtDjfjwnLsobSqcNOJ3CaO0Rgsw3Zs1AfrcHMZpLoKeji+Ay/tol4UmSMNE1YD2NLepl1EQYTK6op+9/Keyix4OV/Teux9b8S6Rf0IaqHKILI0yoHeF5QbGsZyLL2vUQqGdSNySLphNUTOdeDnPDiejfyMHFKdKaS7skj1dGp8Eo+Ek+t+RxalZ1arDKKz5v8kHVvL0MulVY+278JJpxA3IlRXrlM9SNpuLg03m1bdSRnKfZDyLHTB78jBBAGsVDop71pF75Nw0bpVgO3ArhVhwgCmUVUbrDqWOmG7sM1Q2y39OWmrJeo4aY8F6ZuIfRF7LKoUG9CZdrXvJH2PXz20XNtp6Tv5ro1Cyh3qmzqYVkjptYyUmRgMsX9ZP3GCpJ/nOxioBPq9VAux4+wCGmGMaiPS/lhn1tM4s76jR7EWojfvD88wWtCb1etyfuG0vMrWlfX0PonPkX5OFOs1+d/RmYKfceFInQli7Uu5vo1s3sdAtaFpZvIp+CkHhawHI8twBJEeWp/DGA8sGVA7J9fku6Q3ozuD8mBd0/NTLry0A2vIVqZSSd85n3JVr6mMq3mpNyJkpL6GRu1sX9bXOF3pg8YGhXRyn/yXPFalnzd0TfT2zLqq6m67GXkMVIPh/nVP3sfCnkQvczozSLlJf6cj7SE/FKfYfSkjKRvpL63fX5bzUjZi7pr2PukbJp+lryPhh74qYteleMUvkT7EcBNnkrSkH9OMZ7LbcdnjY//991db2dXVNap75Efvc889V1+fzmQyOPTQQ/HYY49t8h7a6IlH+rbGdmC8rPZjpb8t1d9DjFCehqCq9T+wXPU9xAUIpA9uIlQiC3Z1nV4T+y8+k2BX1iFV6FL/RPxibacdH87c7dUHQjxkY4OqVBz9bPwcrLCe+PZRA04c6LPckUr8NPEdpL0W37w742m77ZnEb7RqRUQdM/W5EDshfQ15bq2glviGQV39RDkfw0J26PkWP1z679LmWEEFxk0ncoV1OMWVsIMqYj+T9Fs0HykYL+mrpBHCMtLu2Oof1v3CsE6d0io4g8vVbhUbkd4veRLbJnqSfMt3t7gSVpjYUysO9ZzxUmiIPlc9Das6gKh77r/bLSdpB8WPMfkepBrFpN811K8SH2R6zkOc6UQpEF81UL1L3MNtYG0Qpl6DVS9qQ1iPk3KQPEvYONc7bDebvovIJae0DTQxZvqJrKVGhBySayaVQ+xnk7J0U7Brg/o5znZrPRKdiD+acy2tO2K3pDyk7ojc4jOK/yt+rJSHnFf/LKxpHZA6KnJJ3CJD02+UOiD6kGvaNub79H+qskZ9u0436TuJ3qpBUobyv4mMkYhetC4Ojb+4/U9r2lXjwK8PDPVfHWSjio5dSXrPRv1JeygNx9f8yfiB+KmW2Nqh/kfOs3XcqWanELgZ9RfF/3TLqxPfXfIg9w2VqbjO4ldbJok/7Jmv6dvVARhLxrcc+FFdfVEZH2rWTy1LY9Aj/ZzCbLgDS1R2Qfx+tcHStxvq04Rds7Vs5HF0p89RHZetdFJ34ij5L32N6lotK/WTh+yrpCP5fXh1RfUkYWPxBeSeKEzqdizjOGookDYNbQdEVolHnm2RQ8ObWOuThNP2Q9oVaVOiQOtoUxaRX+pus47quE4caBslMjXHT6SayfMUOx7K8BFI/uxkTGay2/HxYkvb8SkzOE4IIYRsSWQzUFl+ZdGiRboOusw+32677XDaaafh6quvxooVK1gAhBBCyHo0Gg0cf/zxupTZaLnooot0CTVZX/T222/X5c8OP/xw1GrJ4B9tNCGEEDK5uGEL+9pcVoUQQshmMZXXONsUBx10kB6COOh//etfcdNNN+lxxRVX6Prnsjnogw8+ONGiEkIImcK0kh0/77zz9P9o1wmVWZGyb4jsFXLsscfquSuvvBIzZszAL37xC92Ue0PQRhNCCJkstJIdHy+2tB3n4DghhJDNYioa480lnU7j1a9+NQ488EAcfPDB+P3vf687act6aIQQQki72fHBwWTpgiapVEqPiVg7fPny5bqUSpPOzk7ss88+uO222zY6OL4+tNGEEELamanuj6e3gK/dVsuqXHDBBbqO0plnnjnRohBCCKa6MR7tMdVeD7/55pt1JpwYalk/9b3vfS/WrVuHb3zjG+rUT2VoxwkhpD3tuGxoLYPQzeP888+fENllYFyQmeLrI9+b1zYGbfSLh3acEEImnqnqjze2oK/dNjPH77zzTv0lYLfddptoUQghZEoTyQYmcTzqsFMF+fVa1j6VjUJe9apX6fpnV111lW4YRmjHCSGkne34008/jY6OjuHzm5o1fs455+DCCy/cZLwPP/ywvv48XtBGv3jojxNCSGswFf3xV29hX7stZo6XSiWceOKJ+O53v4vu7u6JFocQQqY08Wb8Si1hpwq33HILent71XAfcsghOOywwzgwPgTtOCGEtLcdl4Hx9Y9NDY6fddZZOvi9qWPhwoUvSPaZM2fq/2dvvCXfm9c2BG30i4N2nBBCWoep6I/fsoV97bYYHD/99NNx9NFHj1hbjhBCyMQwVV/jej76+/vxne98B9lsVmfMzZ49G7vuuivOOOMM/PSnP8WqVaswVaEdJ4SQqWPHp02bprPCN3X4vv+CZJcZYzIIfv311w+fk/XQZTbZfvvtt9H7aKNfHLTjhBDSOkxFf7x/C/vaLb+sytVXX42///3v+hrXaKjX63o0efbmMYQQQl4cYQxYozSyEnaqkMvlcMQRR+ghFItF/OUvf8GNN96Iiy66SN+A2m677fDAAw9gKkE7TgghrUUr2fHFixdj7dq1+j+KItxzzz16ftttt0U+n9fPMpgua5wfd9xxw/tPfeELX1CbKoPln/nMZ9RJft3rXrfRdGijXzi044QQ0lq0kh0fL7a0HW/pwXFZ2+5DH/oQrrvuOt2NdDRIx0kWZyeEELJlkF+f7Sm8O/bmGPCenh49ZEkw13X1VfKpBO04IYS0Hq1kx88991xcccUVw9933313/S/O7kEHHaSfH330UQwMDAyHOfvss1Eul3HqqafqTLIDDzwQ11577aj9RYE2enTQjhNCSOvRSnZ8ohhrO97Sy6rcfffdWLlyJfbYYw/NqBx//vOfcemll+pnmV3wbD7xiU9o56l5iEEXMp6NepT8ZBIZIOfZ6E47cCwgiA3qYQzPtmCG6k2xHun3vGdj6WAd8ztT+j/t2JBoOobudW0LlgX0ZDxs25OBY1nw5YIo17I0/KxCCnnfRWfKRRAZrK1F8O0kjCDpV4II/dUQ9ShCxrWxrhogMgaObel3kaXgO6iGMbKerfJlPQdxthu1MIYVh9iqM3k9sTvl6DnJ7+pKA3Zlnd4nVIJYddHhO1jQlUbGteDZNhqRQSHlqBwvmZZHqRFhVsHHDn059GVcjS+PBmbkXFRDg860i3IQwS2vxvRcCn1ZH9UgVn11pmz0ZD2kXfnsaJ6WDNYwLetied2BawN9GUkrxvT+xzQfO/amtUxWlhvojAbRkXJgw1Jdrxqsw4ZB5KY1bolH8pRyLdWP6GpmzsNuM7IoNUKsKNchz79VHUjKOeMBcQi3uhY534FjA8bPYZvuLFzEyARFzXfet9E/pFcpJ9W/ldQB0YfoSOSRepOUG7CiapCygZ60g96Mq2UTxgbG8bUeWEEVsUleZZGZLlJueS/Jm5SIlIOEk/Kx4gh2bRCwHcCyYdIFeEPVROITRA5nYClypqblABNr/RE9SL1uRLHKXazHyPsO0raBVS/DihpJnSyvURml0ko97PCTJkD0JPeLnGmpv44Lp7RK657T/wxEDN+x8ejqMtw1T2JVOdD7rChAd8rWvMepAnKOgXFTqs911QhWWAfK/VrmUi/leehKO+hLWyhEJU1f6pbU796sq7rrdGMY24UfVrWMpVx2yAaqEykP0V2Hl+hFykP1XCvCOJ4+B1YUwosbqhNBykdltSzVlYSVfEq5vmRaDrXI4KUzc/ocPLCyqOcl71LnFq2roh4ZlVnKO7I9TU8OeY6COEavVdVnXeIWeaVuy3fRs8gn5ySfUu7SXoiem+2D1KVaFGudnJ5zkXWTNkjukXalHhp9RuUe+Z6UsdQlCWNrAy7yC0vWlVWPpca/fxper5kZU6bia1yjIY5j3HHHHfrL9ZFHHqm7Z++///747//+b30F/LLLLsOiRYswlRhLOy7I8y3tnjzrJqjDOK6272btMlh+GiYMYMn1qAErqOlnaTsQR4gH1sBEEYyXGZlgHMFyPT3ks93ZCyvXkXwudMPKduh306jBcn1E1Qqicgnu0IxGISzX4HfkYDk2wlodtTWDCGsN+B1ZuNkMolrSBrtpXw8nnYJl2+jZtlev2Z4Lv5BFWAs1nNwv34NyFdU1JcRRrOHDagN+zkfciGDiGLk501BZuQ5BKUB1dRFRLUCqw4eJDOJGoPfk50xDHBm4GRd92/dgxb1LNA3bsZHqSMF2LAysranstu+gPlBHFMSIGhFSXQW4uQzqg1VNL9uXRdQIUVo2oPE1SgGm776Nypjty6Cyugo/72nebd9FfbCBoBYi1emrLZTvZqhNkPidtA8TJ3VA0rccC6mODIJyTeULqyEcz9W04kaI/Jw+ZLrTqK0dQG5Wr+pNztfWDKA+WNd0RbcSrzdnG60Tbi4ZLCs9k7xqaYJEL5bnIS4XEa1aAhM0YCqDek1lkbow9N/yUlrntN4FdbVramuM0fZWbI0c8VD7LBRSrtpisQHSF+pOexom5ST9uabNkM8NtYHSX3L1v/QXm+flvmmFFGblU3jr7nM1bjmf8R21AfJZ7GJPzkelEWl7u7aU1LX5fVlNszfvJ32E2Oh9Qn8lyafv2shqvyi5HoUx+roz6CikUEi7yOV8vd9PuShkE514KRddhRRc14bvOtp/7uhK63mRJwoNLNuC6zkopD105n1UayFWFWsIgwjTu9KaVmfWR74rPRTWRjrra/qSblMekW2r3hxSvpPIF8Uqs2l21gEsmJ5HJu+jM+tpvnpyKWw3o6DhpxXS2i/qynqY251FZ8bD9I6U6mF6IYWBaqByNO3UQunzZr3ENxjyGUQW6dNImckhfddeuUfK1xit13JeohBb3oyr2VeQ8mmKK58zzY6dlKWsAwqj/7V9sJN7wqFmUeuTmfx2/PLLL9cyffbRHBgX5PtJJ500/F36dJ///OexfPly1Go1/OlPf8L222+/yXRooyfejic+awSrXtJnS1wZbU/Duva3xYeQei/PWcpJnjl5HuW69oWjEK4FhNIDFl/JdgEvjVKlijJ8GD8LK2xoPHGmExD/ybKTvoDjwXgpOLVBGC8Nq1HRfvLa0EXVOLCjQOu6+JTit4hPKn5Qb8ZTvzB2knY8KkzX+MT3i3O9aPgFlNVJCOAhVt9cHvMo16u+RIwkn4GbgbhgWfGVvKx27KUPI76Z+H6iE7tRBaqDSd8GwEDkIs5P0/wby1Z9SH78uKHpi+/dePw+tU+SJ/FhBLu8Vm2c+Gwiz6qGo32aiteB3ngAtaH5kWLTaqFBXEt8xTDVMaTvBuD6mJlzUfBtlUGfQy+j8flRXdsr8VFiP6dlJr65XRuAtfYZBE5KfUspH6trOip+FwLbRxohEDZUN1p+lq3+kvi/6biOhuWqzytpSrtpXF91ExVm6NiA6EjKRMtYrnvZJC5p0wrTYQdVeFEdkchrWajH0HOiNsmb6K85BiMym0yntrmJb2VpXcxbgdo1yZ/oTOSUz7aJtA6Ib9305UQGqRvis0s8kl/xFSVPpSBGOXb0c5zuUBsh8Yh9r3oFjVfTDepJ/8CVcJ1JudSLqpsOJ9J+hoaTPkhDfD2oflJWMqbT9PGlfuvYR/+T6rPL8yP1UvIlepfnS+qLxh+HWnZSjuo3Or769Ha9OFQvquj2k/LWfAZ1uMWVKrszsET7MpI/TTsO4RRXqE/cgZrWH9GDyCl1Q3xasXFOvYR0VE3a4ky31hWxz9IPg+1qX0n0a4U1VOFpfVF9xNHwOEzTx3XCmo5jiT5E3061X+uBK2MWtaI+lzJ+IO2A1jM3rc+Iju1E9cQ/jiPU/aTcJB9SB43tIBtVtNzkuxVUVBcyPiE6FP1J+yP9P5FVdCyHyFW1krEaaQOafUNtBwy07k52Oz5ebGk73tIzx2WR9fvvv3/EuXe96136at3HP/5xOM5zK5psDrOpDWIIIYS8OPhL9YYRAy0z2cQ4H3zwwfjKV76izv0222wzZasc7TghhLQeU9GO00a/MGjHCSGk9aAdP3jMfe2WHhwvFArYZZddnjN1XnYoffZ5Qggh47s79mjDThUuvvhiHRR/vtlrUwnacUIIaT2moh2njX5h0I4TQkjrQTs+9rT04DghhJDWQ5cJmmIzzkbDaaedNtEiEEIIIc/LVLTjtNGEEEImC7TjY0/bDY7fdNNNEy0CIYRMaXQ90FE6y+uvDUuIQDtOCCETC+04eTHQjhNCyMRCOz72tN3gOCGEkIl/jSueYq9jE0IIIZMF2nFCCCGkfaEdH3s4OE4IIWTzf6ke5YxwzhwnhBBCWgvacUIIIaR9oR0fezg4TgghZLOQJVVGvawKZ44TQgghLQXtOCGEENK+0I6PPRwcJ4QQslnwNS5CCCGkfaEdJ4QQQtoX2vGxx8YUIe/ZaEQGkTHIeTbyfvJdyLg2Uq4N17aQci0UUjam5Tw959gWPMfScAP1UK93ph34tgXfsVANY6QdC55toy/jYlbeRXfaQSM2KDXC4fQLKQelRoS11Qae6q/hX+tqeGxNWa8N1gKNO4hjVIJYX5EoN0JkPRudKXcoHaPy5NykyHqznspRiSzM60jBeBlYloUwNpjbk0dHyoFjWdiuJwfLxFrQ8l/icWxonD0ZB0EM9GVd1MMYtTBGT8bD/A4PSwZrmJlL0o4BLOhOwzie5kPy15vxMKuQRpzrxdyOFLozjupqWSlUOWbmJJ6U5ifrOQiiWOWZkXVU/0JX2tH/czpSWF2NsK4WYWY+JT+D6e67MQwynq2f7XoRQWywthahJy7Crg5gdt7D/csGsUNfTsNIMc3vzGh6kkcrrGv5TM+lYNfLgONjbSVAb8bF2tDVcHZtAIilXG0M1CNISUuatmXBj+oqo3zvy3oqq5S/hPHDKoqNSPUjspUasdatUpDEEXlZrU+ic6lnUtPSCJH3HdSjGJYFrUPlIFa9dfg21tSBKD8Ndnmt6sCqFTUP8tntf0b1JvFEXXO1vCXtADZm5yUvNjzb0rqYqq3D04M1reOSvpRR7Ka0nsPx9LyxXf1uN8qa11poVG6RtRwahOkuTVvyZNw0clag9VL0a9YsQWwMPAuwogZCA9V3LbZgB1XV08pyQ/XmlFYhWrVEZe90pSxcdMYljdsprlC5Zxd8LRN3YBnWVELYlXWwy2u0jHtQRcqK4a54FMbxYZsIa6oBnOJKzWtnykHasWH8DFZUDezSKlhLH1EdrqqEmi9jWVq30q6leXZWP4G+tKV1U8pInhl9hh0L8zozqA+1C/UY2KorrWGauI2Syiw1WOqj5NFYtpajNxSX1KUV5UB1OS3ratzynIkupepr2TuW/pejJ+3qs5GO64iRnJfvUQwUpAwtud9ofUk5lsoj9T2pc4lcEp/UK7kmn+W65K+Zl7HGxJt3bEnWrl2LE088ER0dHejq6sK73/1ulEqljYZ/8sknVacbOn7yk58Mh9vQ9auvvnrLZoZsEuOJfTBJpbJsIJXT9kk+27mO5Fwcqa0ytbJ+1ra0UQZcH3ahC1bndFhxCEgb1DsTJgxgokj/w03aecv1YPkZ/e50T4NT6IKd74LlpzUO23PhpFJorOuHk8nCcmykpvchqjUQN0I0BitI93bAL2Q1vjgMEAUhqitWwUQxvFwGbtpHHISwHVvvMXGs3x3PQRzFWPvPpQjKNRSXrIMlz3VHTsME5Tps34ElbVY2o/FHtUDvcTMevFwKuRk5/S73e7m0prn60TVw0y5SHSkEZZEn0jiE2mBd2xdH2jONx0VuehaV1VUMLl4Nx3Mx+ExRZcv2JnKYyOh3iae6ZhCZ3jyyfVn9Lp8b5QDV1UVEjQj1wQYsO7Gr6e40GqVA05W81/tLGHxymerH8ZO+QWZ6t6Yp1AfriIfSczO+yuekPf0v5SD3izyizyb5OX3JByl/KU/HhtM7KzlVLWuZan0KAsQDa2B5SX3RMHEEO1dQeyP1yaRyQBTACurJPfJdI7W1bkn7LlVS2lzpb0gfodnsVoIkfbEJgtgI6UNpH8VKvmtfw7XVrjTDdaZdpF0bvTlf+2R6r2Ph94+swLKBGg7btg8ZP+k/yX+JT+jN+3hmXVXjk0NkaoRJA9w51IepNiLYtoXpHanh65VGpOclLt93sP2MArabUdDvs7oyyKc9bDe/a1i++bPy6M2n9Nqy/iq6sp6mN7cnq/2Zvt6kXqYyrp6XNBzXxsr+GmzXRsZPynag0kB3TwZRGCPbkUIm76MyWEexFqpsQT1ET95H1nc0jUWrShpW0pD2eOG0PFKOjc6Mh67O9HB+xNbm0y4WTsvpvRJeju1m5rHH/C5NO+e7qpNGGKmeJa9SblImy0p1rK0Fqid9vmKjOp6e81HwHdWD9GmlTy8Ekdh9C91pT221lHHOd7ReiC0Xsp41/FmeNbkmZW8jOeQFK5FRSPoRUo+M9lvsLeSptZIdJ1OHpt9k0gXtozcxbtImGdfXvrKQPCNG27/Yz2q7GafyqK3XtxU/RvrhngkTf912tH0W/0d8A/GrrEZV74tTOdjiWzUq6mOYTCeywaD2nTNW8jzLZ/GJ1e92xG7JOSDvu/rcapqVdSqvX1mDONOp5+YUPPWJ5FrspVEM5CF31KcSn0lu9cIqukwZxnZghTWYVB5W2NDDeGlYUQDTqMLUa9q3EV9mXT1KbJGb0vglLnUU4kj9KrEV0mexS6vVN5w1+Djsekn7S6ZrJlBeh5Lbob686EP8EWfpw+pbRZkuhL0LkHEtuNIfcnxtdyRs1DFjuD1S/7hRQdUrqG8kcYv80maJ7RL/T31721H/UftblvgsidySbjYs6blY+md+FnZtEKvDxC6JvyR+oYSV9nQwO0P9fZEFcQyrOqA6FR9OdOaENVSyiR2XeOomqTCheGfS5wsq6psGtq91RsNFAZyorm206EzqjJStpClIXrQJlv6Gnfhu8r3hpBDletWnkrpmSR/TdlRnHmI4QQU5NLQ8tA0Xv3uooohuxE/0ojoabkZ9Zam6bnWt+nBSH5tLT/om1LibDW6U7RmWbZY1iGlmAJHtAbardTMf9Gt9STWKCFMdcOJAr4vPj9VPwysuV/ml/EQHDctVOyN+YV3qZLoDJakMRvzXZPxB6hfChuZdxjGeLiXXpW8TzN9D6+hja2uwSmv1XH8tSsYpolBllf6K9K/TA89oXdI6ZyW2T+J0BpfpcynPgbtusdY/1XNnL6x6Wav18lKAaqobvmOr7NpfN7GOE0l+cp6l5Sf1Qa5L2oNiiy1b2wh5HuN8n9Yz9Z/lcQnrSd6GdG0FVfWnk7ICnHoJcaqgfb2qOuwNDSc6krZDniv15S03qSMSh9RXSd78W8fNtkPqh7Rz0p8YbvOG7P9YQzs+9nDmOCGEkLZd40wGxpctW4brrrsOQRDgXe96F0499VRcddVVGww/b948Db8+3/nOd3DxxRfjyCOPHHH+Bz/4AY444ojh7zL4TgghhLQ7rWTHCSGEELJ50I6PPRwcJ4QQ0pavcT388MO49tprceedd+LlL3+5nvv617+Oo446Cpdccglmz579nHscx8HMmTNHnLvmmmvwpje9Cfl8fsR5GQx/dlhCCCGk3WkVO04IIYSQzYd2fOyZMsuqEEIIGdsNQEZ7bCluu+02HcBuDowLhx56KGzbxu233z6qOO6++27cc889uhzLszn99NPR19eHvffeG9///vc5e44QQsikoFXsOCGEEEI2H9rxsYczxwkhhGwem+MsD4UbHBwccTqVSunxYli+fDmmT58+4pzruujp6dFro+F73/sedtppJ+y///4jzn/+85/Hq1/9amSzWfzxj3/E+9//fl3L/IMf/OCLkpkQQghpRztOCCGEkBaBdnzM4cxxQgghm4VsNrM5R3Ot787OzuHj/PPP32j855xzzkY3zWwejzzyyIsutWq1qmuTb2jW+Gc+8xkccMAB2H333fHxj38cZ599tq5LTgghhExFO04IIYSQ1qBV7PjatWt1D7COjg59o1v8aplQNtp102XPL/Htf/GLX2Ci4cxxQgghm78BSLx5G3k9/fTTajSbbGrW+FlnnYWTTjppk/EuXLhQ1wNfuXLliPNhGKqRHs1a4T/96U9RqVTwjne843nD7rPPPvjP//xP1Ov1Fz3jnRBCCGk3O04IIYSQ1qBV7PiJJ56IZcuW4brrrkMQBHjXu96FU089VSegPR9f/epXdWC8VeDgOCGEkM1ic9YgbYaTgfH1B8c3xbRp0/R4Pvbbbz/09/fruuF77rmnnrvhhhsQx7EOZo9mSZVjjjlmVGnJuuTd3d0cGCeEEDIl7TghhBBCWoNWsOMPP/wwrr32Wtx5553De4B9/etfx1FHHYVLLrkEs2fP3qRv/aUvfQl33XUXZs2ahVaAg+OEEEI2izgGrFEaWQm7pZC1wo844giccsop+Na3vqW/Vp9xxhk44YQTho3xkiVLcMghh+DKK6/UjTWbPP7447j55pvxu9/97jnx/vrXv8aKFSuw7777Ip1O6y/h//Vf/4WPfvSjWy4zhBBCyBSz44QQQggZHzs+1nuA3XbbbbqUSnNgXDj00ENh2zZuv/12HHfccRu8T97cfutb34rLLrtsVG97jxdcc5wQQsjmv8a1GceW5Ec/+hF23HFHHQCXX6kPPPBAfOc73xm+LgPmjz76qBrh9fn+97+PuXPn4jWvec1z4vQ8T421zEx/2ctehm9/+9v48pe/jM9+9rNbNC+EEELIVLPjhBBCCNnydnxz9gAbDcuXL8f06dNHnHNdFz09PXptY3z4wx/G/vvvj2OPPRatxJQZHI9iwLUtdKUd/T5Yj/X7jJyHNdUQjmUh7ViqEM9O1r1Ju4l6PNuGYwHzO9MaJuPa6Eg5yCBAs78YGYNyECMygO9YkBjmd2Y0Pbnftix0pFzMKqThORYqQaT3SLq9WR/rqoGGi2KDIDYaVtKc15n8ktOIDLKeg3IYw7GT9ORczhIZDKywjrRr6WL7qwYrmJX39PMu3RaM66PDA6xGBdOyLrpTDnpRRqq2DsVGpPHLWj9daRfTc77ma0FXRs93phzNY4fvoD8AMkFR85T1bPRkPKyoRPAdGz1pB/MKHmpRjFWVEGFsMC1lkHItjWO73hxWV0OERmSXX7lC5P1Ev/KDl+RH9LbTtCxMqoAuU9bvcu+c7gwQh6gEsZ5rpDoR5XqRXfM4tpuWx0umZZHxbE1zRt7D3IIP37ZgmVh1OTPvI852o2hn0Z3xkHEtDDYiFFI2rCiEFdRVDimLnoyLDt/Wsi/BR4edlLF8zzpG64YUuV0vqQ4Kvg2nuELTkdykHVvz58SBlp+xbDi2pXWtWU/kvhm55KUNyY9cy/tSTwA7qCLOdCZlEotsFVhRgCg/TXVZ8B3Y5TVDddogFZS17FI24ER1rQd2vYxpOV/rR2R7cEqrYEcB/P6nEac7ND/GdtAZDcIurYIT1jSf/fVo5JpPVlI+JpXDusjV8sqLznrnYE5HCmtqsepVCKOkPjrrnoFdG8B2vVnVs5Sb0zsTnXYAZ91iuAPLVF+at+qgPgsz436IekROqYPGcYGn7oddWad1dl0DMI2avA+k+dtlWgZWWENfxtH7RC7j51S3VhjA8nwEHbP0Gehz6okehp61emhg6lU4xZVYV4/0em/GRamR1K2dp2WRcizNl9RjedarYYz+mtRzC3Uvh+60g0ZstI5JfRA5pZ6WG0mbIvVQylPSFdnk+RD9StshdaEHVVTDpL47lbX6/IquAicFUb+Uj9QFiUfqkhmSXfLqmVDLXa5JGJFNZJBztdCgPvRd9Kplt4X8WRNv3rElEeMra5oVi0UMDAzooHc+nx++vmDBAtXhQQcdNOI+mQm+ePFi/WX72chs9H/84x8ap2woIq99nXbaaRsMS8aP2MvAeClYYUPbVvksbbEZasON7cJyvaQNsR21AYp8tm1Yfjr5bmLE1TJM0EiudfQBcZS0MxK80K3xS1tiZztgZXJA2BgSItLrcp/f24PyM8vgpH1E5RKiRgDbd5HuTZYPctM+TBQjboR6+B05hLUGav1FBOUq0r2diIIQjWJZw9meC0vaBd9BWuyetK3VEOnuHHp22krjCGshHC+xH0GlimCwgjiKkelOaxyWYyM3sxe2Y8PEMer9JRQXr0CqI+lL5GcV4HgO1jy2TsO6aReeHKmkbyThJC4346Fnu26Ns7JynZ63xU515FBbV0WjHCDV4es9lWVrETVCld3PeRqv7VioraupvPK5MDuPVKeP0tISyivLiCOjckeNCH4hi7gRId0leTCqP7km6Qm5mT3I9mVQXrYG1ZX9cDM+gnJN9VlbM4DGYPLDl6Qf1RrIzpqBsFzTsgoHBxNdBA2kuvMIihVYqQz8WXNhZ3KIqhWtC1Y6ByudTcrY9YF6WeuAVhepd+nCcN2RtlqvWTZcKS8r6deI/Ze2WtpdG3LeQiBlEEpfJKmLhZSr/S7pz8k90k+b25nR/k0QGe0bShsufRWJT8I1ohgryw0NP6OQ0v6k79pIuQ46s57Gq30oN+lvzOxKY1l/TdOS63JO4sqnXQ0j8lQbETK+o9+36s1hWkdK7Ujz3PSOFHryPhZOy+nRmfHQmfWRznoaXr7P6kxjbk8W/ZVA792qN9FfIe2ia1oOs3symvb0jjR2m9elZZrN+4jiGE8tLQ6HTWU8OK6NfNZDviut9/TmfaQznspcrIVY0V/T9KXelGoh0jkPO85MykRkbcqx46wOlaUv52PrnkQekV9kE31kPEfj78t6qoOd53Rifm8WA5UAnSlX+7Ciq4LvIo6N9gm36cmpzutRjM60q2UiSDlJ/zXl2lre0g9thAaz8slzkfdsDSN9AelDis3Xvrv03Yb66/JdXI2mHRc7Xw3E5if2W+4Vez/Z7TiZOnhxA8ZNa39e/R7LUl8ltpJnE46vbZ08V251LQLxEWXpAAPk44r6D+KnioshdljtfhwisFz1iSSg8dIwflZ9A6teApzkmY3TnYgKM4Y+F9CwXCCSMQAgdjy4qxchZ2qQ6i4+tfjxKrNtYaAe6Oe8SfoJ0s+QPEj6kidv7VOIOmZpv8NuVBLfvFFWn88Lq9pWwPFgVwfUJ7PqZTS8nIZRmR0/8XtsW/sicWG65k/HJKIGrKCKqGMmvKiu4deZFBAF6vuZMEBj0YNJP8ZLad5VjyJPKotSEGOGFyZpWICVKai+RebQz8OvrYNJ5VHvmI1M/2J0+XbSz+qYrnIvKzVUbvGFxO9I8u+rDyO+UjYsaXtnl9dqu2aqZZTEpmshAXGuV8N7g8v0u5SXU1qtvo/4ePXIwC6t1vONIX9G8i2+mdhe8StFZ26tHzU7pUemukZ9bdGLjruEdfj1ATT8AuJMt5aJH5S1LjX1JzZbq5jcFwXINvq1cZPySVmx5lX8ZCnD/kasNtyDlGdZ/XzpCwgii9TbEDZqTiZpIMXfrw1qWElX6vYMP4I7uDxJA7H6lNqe267qRuqnjl90JLNmJZ91Y6MSJb6k+Oql2EnGKex/L/agfY5sD4zjqZ8tdkTqr44DSF57ZmldcId0KD6nZ0Ftv5yT8FK3pG5GXhYD9aSRl7o83NeR/qD4pkjsmOjLuCm1jUjl9JzEJX666F6eKy2HRgVxKqfxyNiAPLuS14xpAOV+fcZExrBrrl4bbMSIB9Yg7JkPK46wuhKq3UutfBS5h/+k4w/6zLtD4yXFJeiNB1Q+GRORui56rfsFzd+/x1AipBFqXZJ8NftuflRHnCponZMyaw4Yu+sW6385HWZ6tJ5IPZM8W7ViMr4ifS/pTw6NlYgeNX92MrYjcco4itQPKSMZaxLVilxbakXtF2LHZQ8w8Zebxyc+8YkNxn3OOedofjZ1PPLIIy9I7l/96le6DKqsN95qcFkVQgghm4UMGoz+NS7OOCOEEEJaCdpxQgghZGrZ8dHuAXbWWWfhpJNO2mSYhQsX6pIoK1euHHE+DEOsXbt2o8ulyMD4v/71L12OZX3e8IY34BWveAVuuukmTBQcHCeEENJ2G4AQQggh5IVBO04IIYS0L1vSjk+bNk2P50OWIO3v78fdd9+NPffcc3jwO45j7LPPPhudlf6e97xnxLldd90VX/nKV/Da174WEwkHxwkhhGwWdKoJIYSQ9oV2nBBCCGlfWsGO77TTTroc6SmnnIJvfetbutfXGWecgRNOOAGzZ8/WMEuWLNG9wa688krsvffeOqN8Q7PK58+fj6233hoTCQfHCSGEbBaypqA1ygXNJSwhhBBCWgfacUIIIaR9aRU7/qMf/UgHxGUAXPbnkuVRLr300uHrMmD+6KOPolJJ9ghqZTg4TgghhBBCCCFk3PniF7+I3/72t7r5te/7+or28yFroV5xxRUjzh1++OG49tprt6CkhBBCCFmfnp4eXHXVVdgYCxYsGN78dGM83/XxgoPjhBBC2u41LkIIIYS0vx1vNBo4/vjjde3S733ve6O+T17l/sEPfjD8PZVKbSEJCSGEkNailez4ZIGD44QQQjYL+XV31Ma4RX4JJoQQQkjr2fHzzjtP/19++eWbdZ8Mhm9o3VJCCCFkstNKdnyyYE+0AIQQQtoLMcTxKA/+Uk0IIYS0FpPBjt90002YPn06dthhB7zvfe/DmjVrJlokQgghZFyYDHa81Zgyg+OeDUTGIJIKYpJfT2wrOZdybLgO4MgJABnXhu9Y8GwblgVMz3uwLAu9GQ+NaGTFSjkWghiYnnPR4UTwhuKQ/xnPQtq1UEjZem9PxkPBdxBEBrMKyat/QRSjGkToy3oI4hjzOtOohgZZz8GKcgDftuBY0Di60o7GG0ZG5evLOKhZPrKeDas6oHnrTicvA8ji/B0pB+avP0WU6YKxHVhhHbaJUA5iWEENK9GBvGdjRs5DwU3izPu2hutMu/DrA6iGseposBFhVSXUuN3iSs3Xjr0ZuLaFbTMNZBAgV1mJtZUgybtrwS6uxAwv1PgXdKX1fD0SfSfXnGo/jJfCylJd8yn6E4xlwy6vwbyCj46UjeUDNZhUQXXfk3ZULsvECDvn4KCtOpGT/McR0rbRNAopB7MzQJTrRbEeqiwDVlbzJ/JKEUoZd6Yc1HLTEGe7tZzXVgOEcaKH3qyDWmhgRYHqX8JacYi11QipoIw4lYf8AOeFVUSZbmQ8W+uB6El0aGwXWccAVlKXJN7ByIFjSb2ykDc1NGuS1EUnqmv9M24KVliDcXwgDvV++e+ufQo90YDqHXEEu1FOwtuulrvb/wysRhlWUAGiBrql7I1JyjqsIbDc5L+Tgr/uKTiVtUAUIuqaq/mS9KJY9GKpvKKPOF3AtKwL46bR5QGZuIaZOQ/Fvu21LCSs3Oc3iuhMO1oP5R6nfylmF/ykXBpVWOm85kvyYlcHND6rXoZJ5ZEaKsucayEuJWtMWlEIy09r+PjBW1QeE0UaLvKyqnMrqKvc0wce1+vN5zbsmQ/TMQ1BbJCyAeeJu5CprkE9NEgvuSeJv2cWYDuYnfdgV9ahAzUtP3m+ZuVcrR+i10oQa/6lkcx6FlKWPKux5l3qq5SvPM8m04nutKPPb1/GVZ1LHRBKjVjrhORb6l5TVmkmpB4YP4eUa0OK1UUMO6xrGKnLKVfqqlHZJD6tu7an8snnwUaseW7aOn12raTspJ5J+Ygettgv1ZtxEDImSHto4uSz7cBuVJPPqZy2RWJPNFgYwHK9JGwUwIQB4HiIy4OwokbShmZysHMdsLyUtiUSH+JY2xpkOpJ4pB2Ko+Sa68PUyv8+J4e0DTN7YTm2Hl4ug6jWQGbGNDieh3RvJ6IgRFBO5IyDxIZKmOZnL5eG7bnITO8ajke+p7oKGsaXdspzsfQv92lcct1J+6isriZh4hhuxtOOr8QlNIplFGblkZ3WrZ8lfKrDh+M7GmfPdt163fFcmChGoxyga2EXCrPzSHXlk3DSbjlJO+b4LmzHwtx95+lGO27aRXFpCfXBBvycN5SnAFEjgp/zETdChNUQQS1EqiOFjrkFdG3djb4dejWsyO6lXWS605pWbc0g6oN1/Sz3WLaNwvwZ8AvZpKg9F7npBeRmJbqW+Lu2n4ewWkdtXRm9u++EUPTem9O8wrbhd+WTOuK7yEzrhpVKw02n4BWyMNWkHE3YgNvVA7vQrXXB6ZmJuFGDqVe1/ojNif281jurVlR7JnVKbVAcal9J+mMqo9hMJP2HzpT0B2Ltx0k/UtrxnOhU+gxiO+S8hkvszWAt6WdUgkivyX/pJ0r7XQtjzCqk1c5LmI60h5Xlxr+/p1ztR0qb35nxML2QQiOM9ZD4F/RkUaqFGu/MQhqVRoRSPal70zvS2v+c25PB9HwK+bSLrXpz6Mn7GKgEqEp/Ju1qXFv1ZVFthOjpSKEu/cLYoDPrYeG0HAppF11ZDxnfQdZ3MKszo06Y/Be55nZnMKsrDddzsO2cTiycltf6lE97mFZI6zWtt2GMo3efjV3mdGLnOZ3Yqi+nMghdeR++Y8NPu6hVA722oCuj/SCRMeM5aktFlq16s8inXNjSF/Ud9OZ8lSMpD9GTr33wYi3ES2d1YGY+hZmdaS2T7rSnupBzEr6QcjG3I6VlJL6CfJdNrfqyProznpa74NrP3fBK7LE+G8ZgXS3SuiH9LOkrqR2VZ2sozFDXQPUqtlzyKvdpf2DoOWwFOz44ODjiqNfrmChkSZUrr7wS119/PS688EL8+c9/xpFHHolI2nDSskSO+AMWYj+nz4gTB9rWqd9hgIaX0+dB/CbY8rxB+8RyXa6prXd8WEEVVr2IEnzts4svIu2z+DoSt9p/6TOI7RafSj7LcxlU1LcTe+9Jf7m6Tp8z6a+HfQth10vqv6j/LS6YgV6flvPVhxbEBxN74JTXwK4Nqi9hl1arzTGSnpdBp5v0VcRncAaX6f/Y8dQfclcvUvuSyFNX/038XvFbxS9w+majJi/3mxi9GVd9CPWb/KzGFXVM1/6/+ou2C7vQhfqSxdoHkvjknNgsb9XjiFOiT0vjlzSl/Ql7F6ivEj30V7iNksqP8jr1RURXzsBSTUvyIW3c6kqg16VcelDFgNulaYtcOnZiYh27CB//h/oyZvYOkNxJ+GJoJfYzaqh8Yj8QNlSuNdVIfS/xaeJyUctU2kjxdUVOPe+mMNC5tZa16Fx8u85cBk5pteZJZZe2N11QOSR9p7hCy1j0kAlFb7nEp44CDDW1WB16Wr+kXgRuRnUj5RznetS2i98ryPhJnCqoLyjjE2r760U0oiQtqTdS7g0nlfjwtSIqzlDfpbw2KeOwBqe0CpmgqGMgolcZB5DrMqYgutZ82K7WE6n7Uu/ED9Uxq6F6I2Um+ZBxDrkmstfT3VhSDGA3KloeJePpuMRgbhYG6rH6khKn1Fm5T3QrdUeew0dXV9VmqT8/NP5QNh6eHGjAK61UOcTvzVsBrHoJa0NXy8v4Gb1PnhPVkZtCaMR+SX2uIs50a1nIcy19HMmDPnd+Bkbqp59DObK0vglS30WvIqPYcZFHykDoMWX9n/cdFBuxloFTXKX1SMaoGm5Gr4uc0k5AnnXpW698TPvpYkeTCiLjWYnvIGnn7QhVK+lXVN1cEsZ2tA5ImyRxSd2R9gNeGrGX1ud/oB7pmJPkT54riTKErXVBylZlMY4+FzouERtkrGhYV2MN/fGxZ8oMjhNCCBnbNc5GexBCCCGkve34vHnz0NnZOXycf/75G43/nHPOGfrBfuPHI4888oLlP+GEE3DMMcdg1113xete9zr85je/wZ133qmzyQkhhJDJDv3xsYdrjhNCCNksZJbq8JT10YQlhBBCSFvb8aeffhodHcmbNc+3AeZZZ52Fk046aZPxLly4EGOFxNXX14fHH38chxxyyJjFSwghhLQi9MfHHg6OE0II2SxMHOkx2rCEEEIIaW87LgPj6w+Ob4pp06bpMV4888wzuub4rFmzxi1NQgghZKKgPz7FllWR1/X22msvFAoF3XBFXpt79NFHJ1osQgiZ0jSN8WgPMnWhHSeEkNajlez44sWLcc899+h/WTNcPstRKpWGw+y444645ppr9LOc/9jHPoa//e1vePLJJ3Xd8WOPPRbbbrstDj/88C0q61SEdpwQQlqPVrLjk4WWHhyXzVVOP/107fxcd911CIIAr3nNa1AuJ4vzE0IIGX+MbFw4amM8tIEimZLQjhNCSOvRSnb83HPPxe67747PfvazOvAtn+W46667hsPI5KiBgQH97DgO7rvvPl1zfPvtt8e73/1u7Lnnnrjllls2udQLeWHQjhNCSOvRSnZ8stDSy6pce+21I75ffvnlOoP87rvvxitf+coJk4sQQqYyJor0GG1YMnWhHSeEkNajley4+HdybFIG8+/10TOZDP7whz9sUZnIv6EdJ4SQ1qOV7PhkoaUHx59Nc8ZAT0/PRItCCCFTFmM2Y61SQ2NM/g3tOCGETDy04+SFQjtOCCETD+34FB4cj+MYZ555Jg444ADssssuGw1Xr9f1aDI4ODhOEhJCyNSAG4CQFwLtOCGEtAa04+SFQDtOCCGtAe34FFtzfH1k7fEHHngAV1999fNuGtLZ2Tl8zJs3b9xkJISQqQA3ACEvBNpxQghpDWjHyQuBdpwQQloD2vEpOjh+xhln4De/+Q1uvPFGzJ07d5NhP/GJT+jrXs3j6aef1vORkcxa+l9wbAu+YyGKDTpTNnrSLqphrOcbUYyUY+v5KAa6Uw4iY+DayX05z0JK7nVSyNkRPDlvWRrvYCPSz30ZBwXf0XN5z0YMg76sj0DSS7tYWw1Q8F10ZzxkPAeVQOKxMVgPkXEt2LaF2QVf0wtiIOfZ6PAlB0DWs7FV3tH/QloEkzX4rEjPSb5iJPnzt30pnNogLFmI33YBy0Zf1oVxXOR9G11pB249mV3fk3ZUvjhVwMy8B9guZIm/rpSDjGur/mBiWI1kQ9S+tIXeFNCPDErGQ1SYgZdMy6oM2dpaWBI2qMDvfxop11L9ivyeY8GulzQu4VULujEj58Eur0EjMvBWPQ5rYAViY+DHDczuygBxhHW1EJ1OCGdwBaKOmZqXTquOxQMB7HoR7rrF6HECjdOqDqBqp1GsR6oH0WkqKCPtSvkaPXL9T6IcxHCKK7SMpuc9uLaFjGcjLeVrDKxGBdXQoNvXd1e0TjiDy2CFNa07kZeFSRfQbdU1DSl70ZndKCOEjcBJNgaqhUbzL/qVuiOyyWfbgqZZhafxxY4n0zJg3JTq32pUYVcHYFwfzsp/IdUo6rXQzyf12k1DqrSEsetlPeJ0p5at1J0kUAQvbgDlfpSkMlk2jJ8DHBerGzactYtVf5I3qc+ip6roZXBFoss4hFNeo2WWsmKVV+ppIzaqB4QNDVePTCJ3dRAzUgZdwTpEnTMRpwsIDLRMpe7Ej9+t8cG2YVfWwa4NwK6uQ7jsSRRSNqx6EZixNayogXDZE1qfrFQGVr0Et9afyNQow0g+1i6DH9W1bPoaq1Cy0oiz3Yle1y1GtG4VrLCOnowD06jBkUeluEbTyK76J+y1T6s+9FmxLU2zMy7BCqrYtjuFTFDU9OY4ZTjFlSqL1BmpI6qzaBDG8WDDoDfjaZlK3bGjQJ/ZUiPSeKWu50xN44r9HBwL+kyJbNnKKhjLQmw5+l3qh8gk9wuSntQpabucOECHE+lnuT82yTqcYWw0vPwPhxo5+Sf52hLQGJOJsOPyfKhdclx95o2XSv6ncoDtwK4VAWlDh+yx2jzHg6mWYapFIAyAKADcVLKJTaOGuNQPU69oO2als7BzHYkQ9XLSBvfM0vvtTA5293TYhW7Y2YKmpzK5PuJGCNv1YDm2fjZDbWJz8xs3k4Kb8VFfl7QntufCRDHq/UVYtg03ndL/giPX4hhhuZrEb1uwfQ+NcgAvl0a2N4dGsYJUh49UV2IHstO6UZiV1/Ql7lRXAXEUD333ND4/5yM3s1fvKcyfgc6tulHrr+j9HXML6F7YDTf975cJLcfS76mOFKJGqOk76RSctA/bsRHWQmS600h3p1Fdl7RtJjLITO/StOU+SbNRaqC8oqJpuhkX+dl5zD9groaTMCJPVGsg05fV+PycB8f34HdkVe6BlWX9LnG62bSmP+egPeEXsshM60Gmr6BlU1ldRaa3U/UaDg7qOVMra3n4M2bBznchrNXhdE9HtG4lrExOba2VzsFyPdiFLq0Hlu0grhRhwkDrj9g/qU9S17S+WUk5WbWi2otmWys1TvpI0gYL0p9LrhntF6Sdob6ZAeZ2pGDLOddG1nPgObb2BaWPOD3n6/9SI9R+ofSDZuVTKKRcbNWV0e8DtQA9GemUSH/KRi2KNR4h4zso1ULsPKdD4/RsCzvP7oDr2Ei5ySFh+isBFk7LYW53Bo1QbJqD+Z0ZFIbqQD2M4bu2ptuT8zVtZyhPEkdX1tM+RrURYYcZBWzVm9Pvkn+5d5uZBfTkfe1Pd2Y9DFQCuM2+qu+gtzuDNaU6evM+enIppFKu3r/bzA48s66KvnwKXRlP81ANIhy803TNU2feh+s5mF5IdBhEMXrSHl4yq4BKI0r69FlPrz3dX9Xvki/Rg+hIdC4ySd9Q0pb+uNCb9bVsxIbnfWdYn+VGsiyYyCFhJT6JS/qxUj5SttLfSsrTwvSclzzHtvSJkv6S+BCdKUftvpyXPoHcJ9ea9acWSX8w+S7h5F5B+8TNvtwYQztOJsKOS39ZkLY1NTQKIf+lrhc8S/0U8WflWZM2WOu/Zasf6+LfG8qJ/2HctD5H6otIWy12XOyvtNPiY8YRik5e/VPF9fW69Ns1jqiBKD9Nn0F5fqvGQZzpVB9IUpK+vvS/5b8gfp34W3KfyXTCBPXETkQB4myX+p7qJ4d19SMkrTRCvbfDasDtXwJ7xWMwq58BogZcebRFVttJ7InjIezbGmH3XGTCsvZvJP/iPzmlVbDqZRgvo76hnI+yPahEFpzeWcjtcaD2WaKu2Zo/6RcZx4fdqCbjCtUBOP1LYBmDKJ30c6I1y9W3Ehninnnq19irFmlfSmyc+GfZqKJpxdMWYm0tQpTKY6AeoZrq1vj7MtInk7beqM8lvpf6jZalbbr4KFI+FTePMNOjbZ34zXGuV+WS+7QN7exTn1t8UdF/pr5O/WbxpwpRIqPaYstCePdv/13RLBmrMYgyXepTBrDVD2yWsfYD1TFP7LnoPLCSMZDhtnCofylpadlVB7C6JmMFscYtZZPUszoadlKH5HvdSNufjA8Ick1FEntgS8fAgvGzei5Od6gs+aA/8fVF57keIKghcDNJ/9ayVS7Rkeh8bTVS386k8ojdVOIXRqGeF1sVil9oyRiH+KQlLS8dS8j1Yl0tUjsi1+S2hpdDpjGAdHmVjmmIbzmvM6W+e4eX1G3RUQ4N+NJ3XPHY8JiI1AWp79KH6U3bqHUvwOxUhFJj6Hm0xa4a9eHj/DQdA5H6Js9V87k2qQKC6dshmrWT9sNFzkooY2tD9i0O0fAL2KrT135EVJiu/TGpE1LnpS5IfdG+d5z4waprJL6uHJKHWJ6PejHps8l4SWQQe2lU0j0abylOxro0SakWJkLaNLSNiDNdSZskfoIU61B/r+7ltG5I3eqWADL+4Kb0XpFfx+pgD9d3kU10I30hQdLcQmacdnyqDY5LBRNDfM011+CGG27A1ltv/bz3yC7lHR0dIw5CCCGTc3fsL37xi9h///2RzWbR1dU1OvmNwbnnnotZs2bpxl6HHnooHnvssRFh1q5dixNPPFFtiMT77ne/G6VSaQvlYvJCO04IIa1HK9lx0trQjhNCSOtBOz7FBsfl1a0f/vCHuOqqq1AoFLB8+XI9qtVkRhUhhJDxJ46jzTq2JI1GA8cffzze9773jfqeiy66CJdeeim+9a1v4fbbb0cul8Phhx+OWi2ZASvIwPiDDz6I6667TmdK3XzzzTj11FO3UC4mL7TjhBDSerSSHSetDe04IYS0HrTjU2xDzm9+85v6/6CDDhpx/gc/+AFOOumkCZKKEEKmNq20Ach5552n/y+//PLRyWMMvvrVr+LTn/40jj32WD135ZVXYsaMGfjFL36BE044AQ8//DCuvfZa3HnnnXj5y1+uYb7+9a/jqKOOwiWXXILZs2dvwRxNLmjHCSGk9WglO05aG9pxQghpPWjHp9jguAxiEEIIaX9jPDiY7G2w/hJYcow3TzzxhL6BJEupNJHNm/fZZx/cdtttOjgu/2UplebAuCDhbdvWmebHHXfcuMvdrtCOE0JI60Gnmoy6rtAfJ4SQloN2fIotq0IIIaQFiSKYUR4SVpg3b54OQjeP888/f0JEl4FxQWaKr498b16T/9OnTx9x3XVd9PT0DIchhBBCppIdJ4QQQkiLQDs+tWaOE0IIaT2MiXS38FGHBfD000+P2CB5U7PGzznnHFx44YWbjFeWPtlxxx1HLTMhhBBCXrgdJ4QQQkhrQDs+9nBwnBBCyGbvjj1qp1rCAjowvv7g+KY466yznndfiYULF+KFMHPmTP2/YsUKzJo1a/i8fH/Zy142HGblypUj7gvDEGvXrh2+nxBCCJlKdpwQQgghrQHt+NjDwXFCCCGbha4jvgU38po2bZoeW4Ktt95aB7ivv/764cFwWQ9d1hJ/3/vep9/3228/9Pf34+6778aee+6p52644QbEcaxrkxNCCCHtzJa244QQQgjZctCOjz1TZs1x37GQ9Ww0IoPutIPOlIMgMnBtC9XQwLMB37YQxAaWZek9Mk+iJ+MgiAHHsjAz7w3H4VpALBuURAGyUUXvN5YNz7Zgw8AK63pOYgpjg76MiyCOsaArg3oYY2Y+hbzvYHouhfmdGdiWhc60q+kInSlX4yo1Yk0v5VgYbMSYnQHSrg1jO0gVlyMTFDW8FYewGmV0xiVkGgNwy6uRahRhbBcVNw+7XoTxUggNkOlfDLs6oHn3wiqMm4LdKCNfXIKtCh6MZaG590rKTfQzI2VQC2NEmS7EuV7URGerHodTWoXuxhrk7QjPlEJ0VVegV1ZL8NIwjgfEMezKOmRcGz1pB1nHwEMMKwrgDCxXuSV8avVjiNMdGkb+S4c9VV4Fb+VjeOnMgspYrEf6PXj0Ltil1SjBh7t2Mbbq9GA1qohTBdi1QWSLS2EHVWTiGrKeo/Kl1z0JBDUUfAcZ14JtAXa9rPUAq55CT8bVPDsWVC9p26gsdm1Aw8OyYYU1OLaF2Muq/uQeJ6rrZ5FP6PBtPYeoAc+E8CtrEMVG8yj/pR66Q2nkh+pSZKR+2sh4ttYVwe1/BsbxAakPJtbPJt+jaUnenKCCdFTVuibxRtnuYTksEyM/8JTWpYJnIU4X4AwsBTLJrF2pp4KU3ZpqCNiO1hPRkxVUYTUqKqeUgZSV6E3KJMpP03oidWZW3tf6KUjd8iwgb2owflbjc1cvgjuwVHVsBTX4YRVWOg84HuJqGaZWQrz0X1r+Zu0yOCv/Bcv1MH31g4jz07Q81/zqf5E66M2JzB3T9ZmSPEo5RN3ztP6FO7wCZfhwBpdp/Zd66JTXID24FFjxBJxCF+yggpwoPduF6VkXcc88mFQBcSoPy0/DLq9RXeXsSONw+pdqPXKkvAeWoTfrah7sRgmlINZnOW8FQBSqDt01T8IprtB6InUvG5a0zKRuhTFQlzIuzEDkZZEZeAZW1EjqkTGw6mUYLw27UYHbKGn55awAgQFSlTVaR0TP8jxL3YgdD5Ht6eZIcvSm/92EyzMm7ZeWHaBth7QbW+qX6s05tiSLFy/GPffco/+jKNLPcpRKpeEwsvzKNddco5+lfT/zzDPxhS98Ab/61a9w//334x3veAdmz56N173udRpmp512whFHHIFTTjkFd9xxB2699VacccYZulmnhCMThLSF0sYFdX1W1z8vNsV4maStls9hALge4lI/7M4+WJmCftc6WSsB6YK2VYKVysLUa7A8P7lPjEEqB0j75KVgZXLabkl7Iu2UleuA5Xka3i50wc3ntYNqey5s34WdySXx2jbctA8n7et3+e/4bnKkfaS6CsjN6tVrtTWDMFGs5xzPhdeRQ2Z6NzrmT4dfyMLPechM69b4O7eZg2kvXQg3nYKXTWtcHQtmaXpeLgM3l0ZuVo/KU1szoOe7t50GryOLoFzT8+neTsSRQRwbZKd3Im5Eek9UayDTm9frft5T+Wv9VZWxa5s5mn6qO4c5eydvXWT7srAdCzP23hG5GTnkZkocATLTu/R+wct7muf8nF50bzMTtu+g3l9EZXUVhfkzNE6RX+SZucdcWI6N7Iw+eNkMCr1ZVNcMaDg3k4KXS6MxUEQcJLara7t5sLId6NyqG+neDg3nTZuhbTtcX+OOy0UgDOAXcnqP1Amxb3a2AKd7mpap2EctWz89XM5Gvoc1GNcHbFfrmbT7ck7srNQ117G0nySWW/43W1zXke+2mvAmacfS9lz6cNI38Ya+d2c8bbvleyGVnB+oh2hEMXqynp7rTku7n8TTl/W1/yh9xjWVBgq+i4XdWe1Him3ZcUZB+5hyXs51DPUnezIe8mlXz/fmfczpzKAn5+s9gsSZ8ZNnYlZXGjnPwax8CvM6M+hMe5jbncH0jjR819Z45L7OrIf5nWnst3WP5mOXOZ1YVaxh5zkdmF5IoSvjafhpHSlM70gh4zl4+dwu7LtNL7bqzen9c3symNWVwcE7TcfKUh35lIvpOR87zipgZiGNhdNyaISxxi/3vGXf+ejJ+1hWqqtcrtQXz9H4hW26s9qHFvmkfyR5lzj7sp72t3pzvpbBVj1ZeLaNJcWa9v2kfx9GMXJSP6NY4xVdSZhZhUSf3WlXP0s/vjPlaflI/0H6cuJDSN9OdJ52kv6dqFbkEHsttkfCSp/AsZM+ofQbpFzFbmu3S2y5Z0O6gmL/pV40hvqFk9mOk6lDDAuB7SNyUurXiv9RDAyWlwP1Pzv8xCeR50Da2HW1CPUYqMWWHrGX1rY4yvYg9rPaN5Y+PcRncn31Q6QPXfU71Q+V/r8VVPQQP9Gk8urTVDO9aNg+GqlObSPkMZPnVx5I+S9jBXnP0XEAuZbz7KSttB2EPQu0LxJ3z9U8ibwig/hIltiIobSiwjRY9SLibLf6O5IfsUdWzywYN42nigFMKoewZ776CeKfrYuSeYviR6m/EAcwXbMQTN8ecb5P5RO/xl/7BOyglrQPuS7ti1i1YpKG5ajfAsdBXFyb6D3XA1QH1WezoyBpm3pnan9J0hYZETYQ9y1IfE/xDd205k3aNPFVxK/xVz2mukmbBoyfQWr5Q+rbbeWV4R10gvbPosJ0FBsRfBNq2lHnHGSDQfj9T2u7pv6t2kxb2z1v7VOaTtgxU31M8bvcdc9oOnZxpV4Tf0vQPL/kEPVtJS/im7qIUZXBGokzKKuOxGcUanZK/UQpj6KTx+pqBL9RTNpbqTeiG6kvbk59LNFB0DlHZRPfXFpfSV/ssvhxUjekjkldSMd1jUfqo46pSO02sdanZvrit4aZnkSfXgbGy8KplxL/1/ER5fvgxQ3UOucmfVlj1HZIuYtNEv8vctM6BuLWBzV83rfV3qh/aRK/T/Qgh8itdVJsXUbsF9DhQcvQrhV1XMMZXK5yb1V9UtOSMSXRocgnYzYSn+maqfZKxsrkmQksV+WRZ7HYSMZ2VpTr+ixJvGuqEXqry7Xf7PQv0edDZOtATctpVT0ZS6k4WfWxJQ3t89RWa32Ra35QVruoNtPPan9c0hZ5pf8keWuOZ4naZ+c9vUeH44bMpOhddBw3n8ehMa0MAs2rtAfyLIsvLWNSgYykSDlIXXc8HScTPQyKK6DllVGZ1oU2VlVC9Ddiba+k/ELY2heQ66sr0mcbKjt5fCzomIH44lsS2vGxhzPHCSGEtO0v1eeeey6uuOKK4e+77767/r/xxhtx0EEH6edHH30UAwMDw2HOPvtslMtlnHrqqTpD/MADD8S1116LdDo9HOZHP/qRDogfcsghsG0bb3jDG3DppZdu0bwQQgghU82OE0IIIWTzoB0fezg4TgghpG2N8eWXX67HJmVoTrkcQmYSfP7zn9djY/T09OCqq64aMzkJIYSQVqGV7DghhBBCNg/a8bGHg+OEEEI2iziOYNGpJoQQQtoS2nFCCCGkfaEdH3s4OE4IIWSzkLWRYUWjD0sIIYSQloF2nBBCCGlfaMfHHg6OE0II2SyM2YzXsSUsIYQQQloG2nFCCCGkfaEdH3s4OE4IIWTz1zgb7cxxrlVKCCGEtBS044QQQkj7Qjs+9nBwnBBCyGZBY0wIIYS0L7TjhBBCSPtCOz72cHCcEELIZkFjTAghhLQvtOOEEEJI+0I7PvZM+sFxY4z+LxaL8EKDUiPCoOXruVoYw3cs1EID1wbKjRiydZyVcvRzZAxSoYtiNVk+wA0c/V+qR4BvIzSAF1ZhGYOKE6JhG1QiC5FrwQrrqFo+XNtCNYjh2BZKxQZsy0K5GiITe6iUyijHDcSejUqphpIXoh7GSEUuKqUqioMxykGMyLVhpWwUaxEyKYPI9mBZgFsswtRjhCnAL5YQBzZg2fKkAHEIOD6cYglFfxBhUNTzjYaDRrGkn2vOoMoP24EVNmDXSgjtQRjL0rQ8q4YiAsh+er4fo1SMMJhqwKkVUTQRspJmmKQZhw6KVWAwLiIyadhBDVajBGO7cEWG7KCWhehIEHmNyOp6CLxBeMUSQmsQZasBUy3CLpURZ4sqf9kZxGA6QLlYxSBKaJSrcIpFFMMM7GIJ1fQgUqUijOPBkrxHgZZJFHkoF4FBlGE1KogbQNFzEbgWitUQg8US6oOD8KQcBgdRKgcYNJ6WlRVHCGEjENkxqOVtS74tA79ehBUFaLiDcKK6npe0pOylrFN+pOmZlIFVK6IRenARo1iNkY1FRqN1R2hERtPzbEvrm5CS/Mv9jgcpaCuoJXkL61qmgqSn9dsLUGzEWiZOpYQIGT0v6Yt8NozqSuSVMi7ag/BqRcSxr+VSEt0GJYTOIOxGGcaVcDXUo5TmPcgMwq4m9cy4Kdh1KVMHxdCH8WyYsAi7WkLoDsIKqslzUioDoa3yxpGnskj8UsZaB8tV1Xlcrmj5mVIZVhAjlPNSD7yk3Iu1uv4PmvcOIeVoxSHsSglBalD1jqG4I2dQ8xV7ESyRI45hZUoI/CSOQW8QplIERLdRAKdU1voaWINw4gBWvaRpxpGjz5PE1chInEXNe1IXHC13DVstaRryHBQdH5mgCNMAjFtH5KRQKgWqJydlI4al9V7Sa9g+LCnr0pBu5Rk0BsZJmmS5LvVA6k6pEcOLiijVXYSicyP1JkYQGa2X0j5JOxb78gyGCNb7bNXLI9rBMSMKMOoYo2Bs0yZTjmb9HSyVYfwi7HJJ2ykj9ieKtB206+WknRyqb0brfkrbFxu+tg9xOWlrdL38yAXknnoVtnERlyrJSkG2AwSWhpe44sCCVS4jLFfgpiV8HXFQQ1SpJbYzMIgrIktD0w2rdfiVGmrVOhyxebU6gkoNlVoDrmUhrCXhyvUAfr0Bz7FRrzeQ9C6AqN5AoxHArSfhbNuG69goNQLYtQaq9QBRrQHbseG5LqpD8Qn1egDPdTR8rd6A77l6n1Vr6DVJW76j1kAchigF0ucIkaoHqDcChPUGIrnu2HCkrxIECBsBKkPhBqt11GsNVOoBqkEAx8QIgghxEKFYrWt80m6XhuKS+8thiED6B3pfA04coyppiA6Gwkv+7SjW+13JQ7UOT+yMxBFFeq9sOhRV6whqdbi2jbBW1zIQPYstKWo+62jIvZUqLNsGnAhhpQY7BPxSBRUpm3IVpl6Dk67ADi11LOJyVdt6qVNaRzwPVoCk7I20z27St4rD4X6W2CDjRdpHEiphrOUrdjx2pbwi1EOjfbVaEMMNXITS34yMhhHbX25Eekh7rvqIPcRDDav0CWvlOkpFD1FstB8WutJXLKFsGqjUApSNj1q5iGrso+xGqJZLqJUbqGSM9ilKVgOVUn24ftiBi1q5hKobol6uoJoxqAYhavUQFS9COfL0uhs5aIQxqtKvsQOIqZF+aL1SQqPSQN0ONIz0XVTuoo1KI0S1VEe9XENQFTl8zbPcU0uFGq5RLaFhfJRLRU2nLuVXjjR/DQlXtjQ9+VwppVGtBaiYhoaN3eSaxFctWajJNS9CSmSsBgijGLVyFXXJS8mHZVmqm3pF+o5plU/yV6mFGke5mEG1VEUpHaNaLqKCBsoQfVVRKhqUy4HGK9eFII7h2TaMb6NUC1GuiR/gwJf+vu+oPZbylXTDofZKfAy7njzZkke5Vg1j7RNIvZDPnsgZGTQcC7b0b+TwbBTrESxP+g1AqVgc0Q6OGbTjZIL88diYxB9uJP50KTAo1UMMwtc+rvgugXRxozqKoYfYl77vkI8kPnEcab9ZEL8rtiP1cdT/tWzUvUjb0pSVfBc/RogDJ/Gv5LlzAkgTJq2YyBLEBo4FeFEdZfjwHAvFeqw+o7R1xVqIXOzBLRXV5xXscvHf/Q7tD9RgvFBthqY1lK7i+LDqRWDI9xG/oWSnMBiVEKuP1VA/qig2PComvkzoIBL/RH2HjKYhaaq/ZruIMIhi7CEl9qteUf/CBDZCP4Yn4WqJjzU4OAhTS3zraLCofaZy7Kjt07iHfEpJX3w36U/Fkas6jeIUyqUAgxmgGIcYrJTUl4ytQP07uT9MD+pnK2po/yz0B1Gs2xgMgKL4g3YwFG8JNWsQroXEp7IT/cq4hNWoopEVX7SC2A81T+XcIBpSX0In0UdDytBG5DbgiV8WVBH7YlPTw75gbLKJTyXtm+OhZqe0/Q3FhoRi82Kk7SoavlE5xJbXhobDxJdyykWEkY+KjL94ttprDzECJP0iabvF544aYlNrqn/LqqvMUi/Vb7QH4QQV2DpeIONDyXiBkToQ1jWc1kc/0rpoh3UEtg+/UUKcMiiWQwyGQLFhIxUn8sizYpuKpiv9B8mTIPVUxqzEz5TxiKpvIWUDpVKIdOQOj73ElqM+qPZzpO8S5WCJr21E547KJP0dqV9F28eglE80qOUToYHASelzIGmLDv1GEeWiwWDahlMuoeQO6hiQ+LROs37DxWAj0YvUnVTKoGocRNUiymE6iU98culnufIMuSjZoeYp1SjBKldgBpNxhmI4CJNyhsePBq1BNFwbbqOs9V3sbd2xknEt6aM1yjJwh2IcwGkkfnsxdFVP0rZIWdom0nL1LLG9yXcZ+5F6IWMr0jZJ/RCZ65HRfp70heRe2IGWmehCfHPxuaXPI30nkV+Kp9iINKzYfOn3rN8Ojhm042OOZca8lFqLZ555BvPmzZtoMQghZMJ4+umnMXfu3BcdT61Ww9Zbb43ly5dv1n0zZ87EE088gXQ6/aJlIFMP2nFCyFSHdpy0M7TjhJCpDu146zPpB8fjOMbSpUtRKBR01sZEIr/cykC9PBgdHR1oVSgn9dmq9ZN1c/OQ5l1m6cyePVtnoI4FMkDeaPx7tupo8H2fA+PkBUM7vvmwrZx6+mwHGQXKuXnQjpPJAO345sO2curpsx1kFCjn5kE73j5M+mVVZEBoLGZMjiXS2LVyg9eEclKfrQrr5ujp7OwcU93L7G/OACfjCe34C4dt5dTTZzvIKFDO0UM7Ttod2vEXDtvKqafPdpBRoJyjh3a8PRibqYSEEEIIIYQQQgghhBBCSBvBwXFCCCGEEEIIIYQQQgghUw4Ojo8jqVQKn/3sZ/V/K0M5qc9WhXWTEMI2iG0lbQ/tI/sbhBD6EhMPfTPqslVpl7pJWodJvyEnIYQQQgghhBBCCCGEEPJsOHOcEEIIIYQQQgghhBBCyJSDg+OEEEIIIYQQQgghhBBCphwcHCeEEEIIIYQQQgghhBAy5eDgOCGEEEIIIYQQQgghhJApBwfHW5R22Ce1HWQUKCchhBDaHdpH9jcIIYTQfxx/6I8TQlodDo63ELVaDWEY6mfLstCKtIOMQrlcxsDAAIIgoJxbCHZypqY+CSHtbR/bRU7a8S1Pu9gdykkIGQ/axT62i5y041se2sepqU+yZeDgeIvwwAMP4D/+4z/wile8Arvvvjt++MMf4umnn55osdpOxqachxxyCF71qldh++23xxe+8AU89NBDaDXaRU5h6dKl+Nvf/oY//OEPKJVKw52xOI7RSlBOQshE0E72sV3kbAf72C5yCrSPU1OfhJDJZx/bRc52sI/tImc72R3KSdoVy/DnkQln0aJF2HPPPXH88cdjr732ws0334w77rgD++23H8466yzsuuuuEy1iW8goPPXUUyrnm9/8Zhx55JH485//rLJms1l88YtfxP77749WoF3kFO677z4cddRR6O3txf333499990XxxxzDD7+8Y8PG2Tbnvjf2SgnIWQiaBf72C5ytot9bBc5BdrHqalPQsjkso/tIme72Md2kbOd7A7lJG2NDI6TieXiiy82hx122Ihz3/nOd8wrXvEK88Y3vtE8/PDDZqJpBxmFK6+8UmWKomj43G9+8xtzzDHHmJe//OXm9ttvN61Au8i5Zs0as9NOO5mPfvSjZsmSJWbx4sXmlFNOMXvttZd597vfbeI41nDN/5RzcuiTEDL57GO7yNku9rFd5GwXu0M5CSETRbvYx3aRs13sY7vISfs4NfVJxp+J/3mJIIoiLFmyRNfIbnLKKafoIecvv/xyXbNrImkHGYVGo4FHHnkEy5cvHz539NFH44Mf/CBmzpyJL3/5y1ixYgUmmnaRU+QTWd/xjndg9uzZmDdvHi666CKccMIJuPvuu3HmmWe2xHp3lJMQMlG0i31sFznbxT62i5y0j1NTn4SQyWcf20XOdrGP7SJnu9gdyknaHQ6OTyDNFW3mzJmjRu7xxx/X780NNt7+9rfr6zL/8z//g9WrV1PGUehym222QU9PD/7617+OWH9L1hKTV9BuueUWLF68eEJ02U5yNsnlclof5RWppvxdXV049dRTVU6R/9e//vVEi0k5CSHjTjvY8HaUs9XtY7vI2YR2fGrqkxAy+exju8jZ6vaxXeRsN7tDOUnbMwGz1ac88orG+q/vCPJKzy677GLWrl2r34MgGL42a9Ys8/Wvf31c9dYOMgqNRkOP9TnuuOPMnDlzzN///vfnhN9mm23MZz7zGTPetIucz6a/v98cfPDB5nWve51ZuXLliGvFYtHsscce+hrSREM5CSHjRbvYx3aRs13sY7vI+WxoH6emPgkh7W8f20XOdrGP7SJnu9odyknaHc4cH2cefvhhfVVHdpm+4IILcO211+r5q6++Wn8RPPTQQ/W1KNd19XyxWMSsWbP01R7KOJIHH3wQJ598su4u/YEPfABXXHGFnv/5z3+OBQsW4I1vfKP+ktr8VT0IAv3Ffe7cueNa5u0ip9Df36+zEVauXKm7YHd2duprW7///e/x2c9+Vutjk3w+r6+ePfbYY8OyU8721CchZPLY8HaSs13sY7vI2U52h3ISQiaCdrGP7SJnu9jHdpFToH2cmvokLcBEj85PJR566CHT1dVljj/+ePPWt75Vf+XbeeedzQUXXKDXH330UfPSl77UbL311uab3/ymueaaa8w555xjent7zaJFiyjjeoiuRJcnn3yyOfPMM82xxx5rpk2bZj74wQ/q9Wq1ag466CD9Bf3ss8/WzUo+/OEP6z3//Oc/x63M20VO4d577zW77rqr2Xbbbc2CBQvM61//enPPPffotV/+8pcmlUqZk046yTzyyCPD97ztbW8zJ5xwggnDkHK2qT4JIZPHhreTnO1iH9tFznayO5STEDIRtIt9bBc528U+toucAu3j1NQnaQ04OD5OyCtRH/rQh8xb3vKW4Z1vpbH93Oc+p4bs85//vJ6TV33e8Y53mN13310N3t57773B13ymqoxNzjvvPHPUUUcNv2q2atUq873vfc+k02nz3ve+dzicdBSOPPJIs8MOO5hDDjnE/OMf/6CcG+CZZ54xM2fO1I7AHXfcYb7xjW+o3jo6OszNN9+sYf70pz+Zvr4+c8ABB2gHQupJPp83991337jplHISQiaCdrGP7SKnQDs+ttA+Tk19EkIml31sFzkF2vGpaXcoJ5mscHB8HDn66KP1F+D1WbFihTn//PPN3Llz9ZffJsuXL9dr69atG08R20JGQX7hk7W31qder5urrrrKZLPZEeuDya/BImOpVKKcG+HGG280e+65p1m9evXwuX/961/mxBNP1B8cbrvttuHO2de+9jXV/8c//nHz4IMPjqtOKSchZKJoF/vYLnLSjo8ttI9TU5+EkMlnH9tFTtrxqWl3KCeZrHBwfBy56KKLdBMNebVnfZ5++mndROGII44Y0RhOBO0goyCD4LJJxq233vqcTSm+8IUv6Otnz87DRNAucsrreLZtm6VLl444L9/f/OY364yExx9/fMS15myG8YRyEkIminaxj+0iZ7vYx3aRk/ZxauqTEDL57GO7yNku9rFd5GwXu0M5yWSFG3KOIy9/+cvxzDPP4KqrrsLatWuHz8tGD29+85tx3XXXYfHixeMpUlvKKOy888664YhspvHoo4+O2EThyCOPxCOPPEI5N4P9998fe+21F772ta9hcHBw+Lxs7PKRj3wEfX19ukmJEEWR/rcsa+wKlHJOiD4JIZPPPraLnLTjYwvt+NTUJyFk8tnHdpGTdnxq2h3KSSYrHBzfwjQbLuHggw/Ghz70IXzhC1/At771LSxdunT42g477ICXvOQlW1qctpXx2XLutttuOO2003Tn7m984xu47777hq9tt912Kmscx5RzlEyfPl137/7jH/+In/3sZ6hWq8PX9t57b9Xlrbfeqt8dx5kQvVJOQsh40472sV3kpB0fW2jHp6Y+CSGTzz62i5y041PT7lBOMllxJ1qAyY40XLJ8zV/+8he84hWvUEMnRuVzn/scnn76aRxzzDHYddddcemll6K/v19/GaSMIxH9ya+iTV2KsXjjG9+It7/97WokLrjgAjz11FN6bvfdd8eVV16pnYiJ6ji0i5xSD0VWkc22bVx44YVYtGgRvvzlL6NSqeBd73oXstmshl2wYAFmz55NOSeBPgkhk8uGt4OctONT2+5QTkLIRNHq9rFd5KQd3zLQPk5NfZIWZaLXdZnMBEGg/08++WSz7bbbmr/85S/D1/7f//t/5rDDDtPdhXfZZRczf/78cdthuilXc0fsVpRRWLly5XPW0frUpz5l5syZY37+858Pn/vd736nG1Lkcjmz8847m+23337cd+t+Nu0ip+hXZL3++uuHz4mMsvP5q1/9at34RepGoVAwDz30EOWcJPokhLSvDV9fNoF2fMtAOz417WO7yEkIeX5ox1889Me3PO1idygnmexwcHwMkY0xHn744eGdhJvIBg/vfe97n7OLtBib+++/39x999260/R48Mgjj+iuxo899ljLyihImjvssIO57LLLhh1/4amnnjKf+9znzNq1a0eEr9fr5plnnjGLFi0a1w1KZAfpr3zlK+YjH/mIueWWW0ylUhmW87zzzmsZOTfGH//4RzNz5kzVabVaHTHw8453vMPst99+5vWvf7259957J1TOP/3pTy0n55o1a/T5aHU5CSGTx4YLtONjC+34+NCK9pF2nJDJBe342EJ/fHygP/7CoR0nY4klfyZ69vpk4P7778d73vMeDAwMYN26dbpshqyH3aT5asdEIcVcq9V0Hau77rpL1+v+5Cc/iXnz5g3L1nxdaqKRzTRlowd57UVeKZs/f/4GX5dphTI/9NBDseeee+qmoKLHX/ziF3jpS1/aEmW+Pv/85z/xve99DytXrsTLXvYyHHXUUbo2u3D99ddjjz32QHd393PqQL1eV1277viswPTEE0+oDmUTGllbTTadaXLTTTepbltBTnk967DDDsOJJ56I9773vSNeyWolOQkhk8OGC7TjYw/t+NhDO04ImQhox8cW+uNjD/3xsYX+OBlzxnSofYois7j6+vrMOeecozPO/vCHP5iFCxeaT3ziExsMf+mll5qf/vSnZiL45Cc/ad71rneZTCZj3vKWt5gnnniipWSUWeKnnnqqytj8fvPNN5vvf//7Onvv2TP3vvzlL5uLL7543OVcunSp2WmnnXQGVBiGeu4lL3mJ+e///u8Nhp8oOYUHH3zQdHZ2miOOOMK84Q1v0M+HHnqo+da3vrXB8E8++aSZCO677z4zd+5cc8ghh5j999/f2LZtLrrooo2Gnyg5BdGdZVn6utsXv/hFs2zZspaUkxAyuWy4QDs+NtCOjz2044SQiYB2fGyhPz720B8fe+iPk7GGg+MvkmKxaN70pjeZ97///SMMygc+8AFzzDHHbPDVj6233loHKuXe8aK5NMmHPvQhXapEGuhUKqWvspbLZR24bQ7iTZSMggw0H3jggeaKK67Q76961avMnnvuqQO622yzjTnttNPM4sWL9Vp/f78O8h500EHPWb5kSyNrz8o6s//85z+Hz735zW82H/3oR83b3vY2HcxvyikD+hMlpyzjIvKccsopw+dkSR2Rdd999zVf+9rXRoS/5JJLVNa77rprXOWUuidr+p599tnDdfV73/uemTFjxggdT7ScTeS173e+853mC1/4gpk9e7b5z//8z+f8cNMKchJCJocNb8ol0I6PDbTjYwvtOCFkIqAdH3voj48t9Me3DPTHyVjTGms+tDm5XG54KQ1BXr0+8MAD9dXSRqOBIAj0vPwY0dPTgxtuuAGXXXYZ8vn8uMt6xBFH4O9//zte8pKX4JZbbsH//d//Yeedd8ZXv/pVfW1cEBlvvPHGCZFRlpyYNm2a7sJ97rnnIpVKqYyrV6/GBz7wAX1l7gc/+IHK2tnZiSuvvBL/7//9P13CYjyR1+5XrFiBf/3rX7pUxsUXX4yf//zn+nnNmjX45je/qedKpRK6uromTE7f91XO5tIeUge33XZbXHTRRdhxxx3x05/+FL/5zW+Gw/f19WmdnTFjxrjJKGV59dVXq1yy1E9z6YK99toLnucN18v1mQg510f0+Ne//lXllSWKvvOd7+CKK67A61//enzqU59qGTkJIZPLhgu042MD7fjYQTtOCJlIaMfHFvrjYwv98S0D/XEy5oz5cPsUQWZwNXfAXn/ZBNnFV/i///s/s+uuu464p1QqjbuMzSU/1t/wQTa6bG4ceeSRR+ryFfJ/U0tDjKecMitOZmWfeOKJ5tvf/vaIsDIzW5YzaTQaw7qeKDll5uC0adN0GRCZhf/73/9++NoFF1xg5s+frxtzThQiq+hJlqh54xvfaGq1muqsOftQNiGTDbBkFvn6DAwMjLusf/7zn3VJg/URORcsWGBuvPHGDd4zEXKuz2te85rhZYlk+ZdcLqdvOMiSDK0kJyGkPW24QDu+ZfVJOz520I4TQsYT2vGx1yf98bGH/viWhf44GUs4c/wF8NBDD+Ed73iHzt46/fTT8cADD4zYLLI582z9Ga9nnXUWTjjhhOHr4yXj4Ycfjve973347W9/q/Lst99+2HrrrZHJZHDyySfrTOzvf//7OotcZsAuWbJkXOTbkJyS/s0334wvfvGLOtv6qquuwlNPPTUi/Gte8xr99bVcLo/r5qHry3nKKaforOHf//73+NOf/qT63WWXXXSmcxiGGv6Vr3ylyimboI43zTomv/rLzOt3vvOduOaaa/Dtb39bdSZ1U8IsXLgQ559/Pn7yk5/gwQcfHK6vHR0d4ypnU18ii7D+HsEib3PWZnPz0OXLl0+YnOsjM0qlvgqyIavoW56re++9F0uXLh0ON15yEkImjw1fX07a8bHXJ+342EA7TgiZCGjHt4w+6Y+PHfTHxxb642Q84OD4ZiKDYPvvv78+oDIYeuutt+Jzn/scPvzhD+t113X1fzabHR4olaUXZJkNWW5BBtDGW8bbbrtNZTz77LN1mRIZMJ0+fTp+97vf6aCpDJ7K59tvv31cB5yfLaek/6EPfUhllWU/ZCBfliL5wx/+oIPhgnyWgXMZeJ4oOe+88068//3vx8c+9jHstttumDVrFiqVCnp7e4fLX5ZYETlliZjx3gVblshZtmzZ8LlXvepVuPDCC7WO/s///I+ea9bDQqGAHXbYQV9HbC5nMlFyNgfFpQ7Ks1OtVlXO5uCyPEeHHXbYBpdZGU85m4P1++yzj+rsgx/8oP5Qcs899+hnqb+yTMx4DqIRQisPxsMAAB2/SURBVCaPDd+QnLTjY6tP2vEXD+04IWQioB3fsvqkP/7ioT8+ttAfJ+PGmM5Dn+TI69af/OQndfOuJoODg7op38te9rIRmx7+/Oc/1w0PJbzv++buu++ecBnlFXFZYuNTn/qUOfroo80dd9yh15uvUFWr1XGRcVNyysaGe+yxh3n3u99t7rvvPt2cc+7cuealL32pee1rX2u6urrMPffcM+Fyij5FpjPOOEM3Ytxuu+3M/vvvbz7zmc+o7L29veMqZ3OjzZ6eHmNZlvnEJz5hVq1aNXxNNl0977zz9NqnP/1p8/e//103lpOlTGQjzJUrV7aEnOu/2if1UTZhlc0sP//5z+uyJc062wpyyqarcm3WrFnmzjvvHD5/4YUXbnATUULIxNIONvz55KQdH1t90o6/MGjHCSETAe34+OiT/vgLh/742EJ/nIwnHBzfTE466STzyle+csQ5MSKXXHKJefnLX27OP//84fVKZeCsu7tbB/daQcaLL77YHHTQQeaDH/ygWbJkyXPuG+81vDely7322stceumleu673/2uOffcc3Ud70cffXRcZdyYnLIzusgpA/lf+tKXzAMPPGAOPvhgXcP7+OOPNw8++OC4yihr4Z588skq62WXXaZ172Mf+9iIQW8ZcL7iiivMzJkzzZw5c8yOO+5oZs+ePa6DPhuTc0MD5MLuu++udUEGp9YfgG4FOaUuyg8N//jHP/R7cy13Qkjr0g42fFNy0o6PnT5px18YtOOEkImEdnz89El/fPOgPz620B8n4w0Hx0dJc+BYBmwPOOAA88gjj4y4vnbtWp11JrOH6/W6efzxx80rXvEKnf3cKjLKTOH3vOc9Kpc4ha2uy7333vs5G4q2opxyrTkwKmUvx3gjG6zKIO7VV189YmDn2QPkgmwiKRtnyQaizzzzTMvIuf7As5S71FfZ4NJxnHF9jjZHTpmRP1E/LhFCJpcNH42ctONjq0/a8c2HdpwQMhHQjk+MPumPjx7642ML/XEy3nBwfDMRh7mvr09nlTYHmJvGZfHixTqAJoOOMlgqv3a1sowTzWjk/N3vfjfhg4+jkfM3v/mNmWieXd9kYFdk++hHPzo8oBsEgXnqqadMq8q5evXqYTlF5muvvVZn5beanM0fHOQ5X7Ro0YTIRwiZnDZ8c+ScaGjHxxba8fHTJ+04Ie0J7fj465P++OihHR9baMfJeMLB8RfADTfcYFKplDn99NNHzCJdtmyZrl956623mlaX8a9//atpBSjn2COzrpudmv/93/8dnvEsS+l8+MMfNq9//evV0Ez0TOfnk/O4444bMTO7lfXZCnISQiaPDRdoH6emPgXa8fHXJ+04Ie0D7fj46rNV7GO7yCnQjo+/PmnHyYuFg+MvkF/96lfaOMuDKDNRHnroId3cUDbne/rpp00r0A4yCpRz7BHj0VzqRcre8zyzww47GNd1h9fIbmU5ZSmVdpCz1fRJCBkdtDtjC/U5de0O7TghZCKg3aE+W3l8Q6Adn5r6JO2LJX9AXhB///vf8ZGPfARPPvkkXNeF4zi4+uqrsfvuu7eMRttBRoFyjj3NR9uyLBxyyCG45557cNNNN2HXXXdFK0E5CSETAe0O9dnK/SKB9nFq6pMQMjpox8cW6nPq2h3KSQjAwfEXyeDgINauXYtisYhZs2ahr6+v5epVO8goUM6xJ4oifOxjH8NXv/pVNca77bYbWhHKSQiZCGh3qM9W7hcJtI9TU5+EkNFBOz62UJ9T1+5QTjLVcSdagHano6NDj1amHWQUKOeWYeedd9aZAK1qiJtQTkLIeEO7Q322A7SPU1OfhJDnh3Z8bKE+p7bdoZxkKsOZ44RMcuQ1KXmVq9WhnIQQQgjtI/sbhBBCJhP0c6emPkl7wcFxQgghhBBCCCGEEEIIIVMOe6IFIIQQQgghhBBCCCGEEELGGw6OE0IIIYQQQgghhBBCCJlycHCcEEIIIYQQQgghhBBCyJSDg+OEEEIIIYQQQgghhBBCphwcHCeEEEIIIYQQQgghhBAy5eDgOCFkQjn//POx1157oVAoYPr06Xjd616HRx99dESYWq2G008/Hb29vcjn83jDG96AFStWDF+/99578Za3vAXz5s1DJpPBTjvthK997WvPSeumm27CHnvsgVQqhW233RaXX375qOU87bTT4DgOfvKTn2A8+eIXv4j9998f2WwWXV1dGwxjWdZzjquvvnpc5SSEEDI1oR3fNLTjhBBCWhna8U1DOz414OD4JOCkk07SAcXxRgYWmwNxZ555JtoZycvGBh5fLAsWLMBXv/rVLRL3ZODPf/6zDnz/7W9/w3XXXYcgCPCa17wG5XJ5OMyHP/xh/PrXv9aBaQm/dOlSvP71rx++fvfdd+vA+g9/+EM8+OCD+NSnPoVPfOIT+MY3vjEc5oknnsDRRx+Ngw8+GPfcc4/W2fe85z34wx/+8LwyVioVHWw+++yz8f3vfx/jSaPRwPHHH4/3ve99mwz3gx/8AMuWLRs+JqJNIIS8MGjHXzy04xMH7fimoR0nZPJDO/7ioR2fOGjHNw3t+BTBkJZGimhTx2c/+1nT399v1q1bN+6y/eAHPzAdHR1m2bJlZnBw0LQzkpfOzs4tEvfKlStNuVw2E8mf//xn8x//8R9m1qxZWm+uueaa54RZvny5eec736lhMpmMOfzww80///nP4etPPPHERuvhj3/84+FwTz31lDnqqKM0jmnTppmPfvSjJgiC55VR4thhhx2M7/sa54UXXqjnpX57nqfxHHbYYaanp2c43dtuu22j8b3//e83Bx98sFmzZo1561vfqvHatm1OPvlkUywWNcyb3/xmjVPyvcsuuxjHccyxxx77nLguv/xys++++6os2WzWLF68eMT1V73qVeZDH/rQiHMSj8TbZOnSpaqXdDptFixYYH70ox+ZrbbaynzlK18xL7aObqxMCSETD+34+EA7TjtOO04I2RLQjo8PtOO047TjZCLhzPEWZ/2ZoDL7uKOjY8S5j370o+js7Nxis56fD5k1PnPmTF0Sg2yYadOm6ZIYE4nMwn7pS1+Kyy67bIPXpd8nM40XLVqEX/7yl/jHP/6BrbbaCoceeujwDG5ZsmT9uifHeeedp8ucHHnkkRomiiKdnS2/rv71r3/FFVdcobMAzj333E3KJ2FlWZR3v/vdmr4gs78feOABnRUus8m32WYbHHjggbjwwgv1utS72267baNxDgwMoKenByeeeKLOJn/JS16iy7HcfPPNOPXUUzXM4Ycfjttvv12XYvngBz+o+d0Q3/ve9/C2t71NnzXJ6+Ysx9LkHe94h854l6Vdfvazn+E73/kOVq5cibFCZt/39fVh77331tntSV+eEDLR0I63P7TjtOMC7TghUxPa8faHdpx2XKAdJ5tkQofmyZj8miqzU9ef7SqzWM844wydydrV1WWmT59uvvOd75hSqWROOukkk8/nzTbbbGN+97vfjYjn/vvvN0cccYTJ5XJ6z9ve9jazatWqzZbnsssuM9tuu61JpVIazxve8Ibha1EUmf/6r//SmbMyg3a33XYzP/nJT0bc/8ADD5ijjz7aFAoFlfXAAw80jz/++PD95513npkzZ47OBH7pS19qfv/73z9ndvPPfvYzc9BBB+nsZUnjr3/963Nknzdvnl5/3eteZy655JIRebnnnnv0fklf5Nhjjz3MnXfeuUE9xHGsM/glPpFJZl5/4AMfGL7+7NnBIt93v/tdTVfSF1398pe/HLUOBLl/xx13VB3LbGvR+WjZ0CzjRx99VM9Luk1E1zLzW9LaGC972ct0JnYTqVMyO1tmoTf55je/qW8Y1Ov1jcbzpje9SfMracr/Aw44wOyzzz7mtNNO0xnWotdnl/HOO+9szj777A3Gd+uttxrXdVV2CStlt91222ndk/piWZZZsmSJ+e1vf6vXK5XKBp8lQWbPy8z15rMgutt666213Ec7c/zhhx8elqPJY489pufGYub45z//efOXv/zF/P3vfzcXXHCB1ouvfe1ro4qXEDJ+0I7TjjehHacdXx/acULaA9px2vEmtOO04+tDO97+cOb4JEVm7Mos0jvuuAMf+MAHdL1iWbdYNvb7+9//rms6v/3tb9e1lIX+/n68+tWvxu6774677roL1157rW54+KY3vWmz0pV7ZQbu5z//ed1UUeJ55StfOWKzhyuvvBLf+ta3dDavrCUtM3JlnSthyZIlGl42TLzhhht01vDJJ5+MMAz1umyy+KUvfQmXXHIJ7rvvPp35e8wxx+Cxxx4bIYfMOpZZ9bK29Pbbb6+zkptxyExhmaF8xhln6HVZg/oLX/jCiPtltvHcuXNx5513qgznnHMOPM/bYJ5lFvBXvvIVfPvb31Y5fvGLX2DXXXfdpJ5kxrXoVvJw1FFHaXpr164dlQ5+9KMf6Uxs2Rji4Ycfxn/913/hM5/5jJb5C6Ver+v/dDo9fM62bZXhL3/5ywbvEblEf6LLJjKTW/I+Y8aM4XNSRoODg1reG0Puk1nbMvtZZovL+t5y36Zmhm8Muf/YY4/FZz/7Wc2DvFXx8pe/fPi6pCPnpR6sj+hVjt/85jc6G/6WW27R8zILW2SR50mQ8pJZ6VI2o0WeBdd1dTPQJrIhaHd39/D39773vZpu89gcpPwPOOAAfX4//vGP69roF1988WbFQQhpLWjHacc3B9px2nFCSGtBO047vjnQjtOOkwlmokfnyZb5pVpmGjcJw1Bng7/97W8fPifrhK+/ZvN//ud/mte85jUj4n366ac1jMwqHq08MmNbZglvaA3yWq2m6zU/exb3u9/9bvOWt7xFP3/iE5/QWbmNRmODac6ePdt88YtfHHFur7320vWl159V/D//8z/D1x988EE9J7N3BUlL1n5eH1l7ev28yIxtWWd6NHzpS18y22+//UZl3tDM8U9/+tPD32VGv5xrzoB/Ph3IrP+rrrpqxDkpv/322+8FzxyXtObPn2+OP/54s3btWp3lLTOQJeyz60WT973vfWannXYace6UU055TnhZb13iefabCusjM7Nl7e+5c+eaRYsW6TmZDS9vHlx//fV6f3Nd/WYZz5w503z5y18eEY+UtdzzyU9+Ur9LXZGyEV7xilcMz+6WGfH//d//bb7//e9rfRWkzh533HHmkEMO0VndMptcnh15E0Bmmst65M1D0pd1zJvI2uYf/OAHR8gidaw5c/wXv/iFzmSXmfHr093dPVw3VqxYoek2jxezDt9vfvMblVGeOUJI60A7Tjsu0I7Tjj8ftOOEtCa047TjAu047fjzQTvefnDm+CRlt912G/7sOA56e3tHzGZuzuxtrnl877334sYbbxwxc3XHHXfUa//6179Gne5hhx2ma1UvXLhQZ6bLTNzm7PTHH39cP0uY9dORmeTNNGQm8ite8YoNztKW2ceyZrPMkF0f+S4zqDeW/1mzZo3Iq4TdZ599RoTfb7/9Rnz/yEc+gve85z06y/iCCy7YpA5kRn61WtU8n3LKKbjmmmuGZ3lvjPXly+VyupZ8U75N6UDW/xZZZLb2+jqUme+bU07PRtL6+c9/jn/+85+6TreskS71QdbXllnWz0bye9VVV42YNT4aFi9ePEJumfUu4/WyVrm8dSCzsbfeeusR9+y5554q3/XXXz/i/PLly0eUm8zE33nnnbFu3Tp9w+DZSNhnx3HdddcNxyHr5ks5iFwyq1vWIf/d736HYrGoa7BLuTSP//3f/1V9yRsXzXXsZD3CJpIfmcHeZIcddtA6IfE0kedBZG0yffp0Tbd5vBhERpmVLjP/CSHtCe047fjmQDtOO04IaS1ox2nHNwfacdpxMrG4E5w+2UI8e2BVNs5c/5x8F+I41v+lUgmvfe1rhzc7XJ/m4PJokAFGWbZFNh384x//qMt/fO5zn9PlSSQN4be//S3mzJkz4r7mIJ4MSI4Fm8rraBCZ3/rWt6qsv//973WJDlnq47jjjntOWNmoUpbN+NOf/qSDre9///t1SQtZKmZjS7FsqHya8m1KB00dfve7333OAL/8CPJikEFoGVSVJUNkQ00Z8JU01l+SpMlPf/pT/aFDNrVYH9kkU5byWR9Znqd5bfbs2ZpGExmIl6VUZIBc9C31Rwa9hWeeeUbvkU0wZRBefrCQ8E0dSIdz33331c8yEC0D67KciiwrIkg88sND80cHWbbkG9/4hi63s2bNGh2o/vGPf6xlvDFkI07ZYFQ2M10f2dxTlgSSH39EflmSSOSTuGTj0C9/+cvDA+eC/NAkP7TIRqDf/OY3tfzPOussLetm/dzUDwqy5I78l0H3pv5kAF0G8n/961+rjkUXsiyO1EH50UHySQhpX2jHacc3F9rx50I7TgiZKGjHacc3F9rx50I7TsaNiZ66TrbMa1zP3hzw2Ut7PHt5DVmGQjZ2DILgRcuzPrJkiCwnIcutyLIVslHglVdeudHwn/vc517Qsiqnn376iCU3/vGPfwxfl+U45NyNN9640WVVTjjhhE3mRa6/9rWvNaPhkUce0fTuvvvujS6r8uxlTSRt0edodSAbPrxQNpT+hpCNKGVzzT/84Q/PuSZ1bP2NVp+9IacsEdLk29/+ti5dsrElPkSeDR3yuppsyClUq1VdOkeWIZFNTOX6ddddNxyHbIi6oThEV/L/rrvu0nBSByReOSfl0tT5hp4l2VRU6u6Pf/zjjS4rs/vuu+tnKSv53tPTo8u6nH/++SM25BSWLl1qjjzySH0GJG1ZGkfCfutb39pkOUgcG8pbsz7LcjyyMaps3CrLJ8kmtRLns5dwIYRMPLTjtOMC7TjtOO04Ie0J7TjtuEA7TjtOOz754OB4G7EljfGSJUt0HeY3vvGN5o477jCPP/64ufbaa81JJ52k6y6PVp5f//rX5mtf+5oOTj/55JO6rrMMlj7wwAN6/VOf+pTp7e3V9bwlDRlAvvTSS4fX9169erVef/3rX2/uvPNOHaCVwXQZcBYkDzLQevXVV+u5j3/847petYQb7eC4rLMuMl188cV639e//nXT1dU1nBdZa1oG2yW85OEvf/mLDqieffbZG9WDrHF+//33m3/961+6nrgM4EpeXsjg+PPpQHbGlvhFz7Ie/H333adrZ8va5xujWCyqTuSQ9GWtbvn81FNPDYeRQWDJs+RB1sgWuUWGZyPrYcsa3M010tdH6souu+yi647fc889WoekXsk66pvi1ltv1YHoSy65RNeGl8FuKVfRaZM1a9aozL/97W81D1IH5Lusn78pjjjiCB3Evv3227Ust9tuu+E17tdfq1zikh9ADjrooGFdbUmaa/r/6U9/2qLpEEJaB9px2nGBdpx2nBDSntCO044LtOO042TywcHxNmJLGmNBBmFlQ0IZKJbB1x133NGceeaZJo7jUctzyy23aPrNGb677bab+b//+7/h6xLXV7/6VZ2lLoOfMnB6+OGHmz//+c/DYe69914dXJXNO2VjTNlIUQZsBZkNKzOr58yZo/fLLNn1B2lHMzgufO9739PNH0VGGRCVQdlmXmQzSpkpPm/ePOP7vv4yfMYZZ+js5Q0hOtxnn3100F5m7u67774jBjw3d3D8+XQg/OhHP9LZwiKf6PqVr3yl+fnPf242huR9Q7OP15/ZLIPtohPRq2zOKYP8ootnIwPdopuNzUyWHxRkhrTotq+vz5x11lmjeiNBBudl80zJ084776yD4Osj+tlQHmQgfVPIoLoMhsvMaimjd73rXfpjwfpIGW0o7rFENhb95S9/qRuOyo8BBxxwgFmwYMFG3xAghEw+aMdpx5vQjtOOE0LaD9px2vEmtOO042RyYcmf8VvEhUwmLr/8cpx55pkj1lYmhGyYP/zhD7rO+KJFi3Rt9f333x9f/epXdQNbQgiZCGjHCRk9tOOEkFaDdpyQ0UM7TjYFN+QkLwrZvFE2BZRNCTe0mSchJOHwww/XgxBCWgnacUJGB+04IaQVoR0nZHTQjpNNwZnj5AVTLBaxYsUK/dzV1YW+vj5qkxBCCGkTaMcJIYSQ9oV2nBBCxgYOjhNCCCGEEEIIIYQQQgiZctgTLQAhhBBCCCGEEEIIIYQQMt5wcJyQSciCBQtgWZYe3DCVEEIIaS9oxwkhhJD2hXackPaCg+NkSnDZZZepgUqn09hnn31wxx13DF+r1Wq6oWhvb69uLvqGN7xheC31TfGTn/wEO+64o8a566674ne/+92I68YYnHvuuZg1axYymQwOPfRQPPbYY88b70033YQ99tgDqVQK2267re5Cvjn5Ee6880787Gc/e960CCGEkHaAdpwQQghpX2jHCSEtjSFkknP11Vcb3/fN97//ffPggw+aU045xXR1dZkVK1bo9fe+971m3rx55vrrrzd33XWX2Xfffc3++++/yThvvfVW4ziOueiii8xDDz1kPv3pTxvP88z9998/HOaCCy4wnZ2d5he/+IW59957zTHHHGO23nprU61WNxrvokWLTDabNR/5yEc03q9//euazrXXXjvq/DS58cYbjTzi69atexHaI4QQQiYW2nHacUIIIe0L7TjtOCGtDgfHyaRn7733Nqeffvrw9yiKzOzZs835559v+vv7dVD7Jz/5yfD1hx9+WAeVb7vtto3G+aY3vckcffTRI87ts88+5rTTTtPPcRybmTNnmosvvnj4uqSVSqXM//7v/2403rPPPtvsvPPOI869+c1vNocffvio8rM+HBwnhBAyGaAdp1NNCCGkfaEdpx0npNXhsipkUtNoNHD33XfrkiZNbNvW77fddpteC4JgxHVZKmX+/Pl6vYksYfK5z31u+LtcW/8e4fDDDx++54knnsDy5ctHhOns7NQlUNaP96CDDsJJJ5006nifLz+EEELIZIJ2nBBCCGlfaMcJIe0AB8fJpGb16tWIoggzZswYcV6+y+C1HL7vo6ura4PXm2yzzTbo6+sb/i7XNhZn83rz3KbilUF4WZP8+eIdHBxEtVp93vwQQgghkwnacUIIIaR9oR0nhLQD7kQLQEg7cP3112+ReK+88sotEi8hhBBC/g3tOCGEENK+0I4TQrYknDlOJjUy29txHKxYsWLEefk+c+ZMPeRVr/7+/g1e3xhybWNxNq83z41FvB0dHchkMs+bH0IIIWQyQTtOCCGEtC+044SQdoCD42RSI0um7LnnniN+aY7jWL/vt99+es3zvBHXH330USxevFivbwy59uxfr6+77rrhe7beemsdrF4/jCyNcvvtt7+oeJ8vP4QQQshkgnacEEIIaV9oxwkhbcFE7whKyJbm6quvNqlUylx++eXmoYceMqeeeqrp6uoyy5cv1+vvfe97zfz5880NN9xg7rrrLrPffvvpsT6vfvWrzde//vXh77feeqtxXddccskl5uGHHzaf/exnjed55v777x8Oc8EFF2g6v/zlL819991njj32WLP11lubarU6HObtb3+7Oeecc4a/L1q0yGSzWfOxj31M473sssuM4zjm2muvHXV+mtx4441GHvF13B2bEEJIG0M7vm6ii4AQQgh5wdCO044T0upwcJxMCWRgWwbAfd83e++9t/nb3/42fE0Gq9///veb7u5uHZg+7rjjzLJly0bcv9VWW+kA+Pr8+Mc/Nttvv73GufPOO5vf/va3I67HcWw+85nPmBkzZuhg9iGHHGIeffTREWFe9apXmXe+853PGdR+2ctepvEuXLjQ/OAHP9is/KwfDwfHCSGETAZoxwkhhJD2hXacENLKWPJnomevE0LGnptuugkHH3ww1q1bh66uLqqYEEIIaSNoxwkhhJD2hXackPbBnWgBCCFjz84774xFixZRtYQQQkgbQjtOCCGEtC+044S0F5w5Tsgk5KmnnkIQBPp54cKFsG3uvUsIIYS0C7TjhBBCSPtCO05Ie8HBcUIIIYQQQgghhBBCCCFTDk4nJYQQQgghhBBCCCGEEDLl4OA4IYQQQgghhBBCCCGEkCkHB8cJIYQQQgghhBBCCCGETDk4OE4IIYQQQgghhBBCCCFkysHBcUIIIYQQQgghhBBCCCFTDg6OE0IIIYQQQgghhBBCCJlycHCcEEIIIYQQQgghhBBCyJSDg+OEEEIIIYQQQgghhBBCphwcHCeEEEIIIYQQQgghhBCCqcb/B8j7joqXKt/wAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 1500x400 with 6 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 2.2. Discard Data Above Surface Level and Surface Interference\n",
+        "\n",
+        "To reduce computational load, we can exclude all data at or above the water surface level, including that affected by surface interference. Since the instrument was oriented upwards, we can utilize the pressure sensor data along with the function `water_depth_from_pressure` to find the water depth. However, this approach necessitates that the pressure sensor was calibrated or 'zeroed' prior to deployment. If the instrument is facing downwards or doesn't include pressure data, the function `water_depth_from_amplitude` can be used to detect the seabed or water surface.\n",
+        "\n",
+        "It's important to note that Acoustic Doppler Current Profilers (ADCPs) do not measure water salinity, so you'll need to supply this information to the function. If `water_depth_from_pressure` is called after `set_range_offset`, \"depth\" represents the distance from the water surface to the seafloor. Otherwise, it indicates the distance to the ADCP pressure sensor.\n",
+        "\n",
+        "After determining the \"depth\", you can use the `remove_surface_interference` function to discard data in depth bins at or above the actual water surface. Be aware that this function will generate a new dataset."
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
-    "\n",
-    "for i, ax in enumerate(axes):\n",
-    "    ds[\"vel\"][i].plot(ax=ax)\n",
-    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
-    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 2.4 Rotate Data Coordinate System\n",
-    "\n",
-    "After cleaning the data, the next step is to rotate the velocity data into accurate East, North, Up (ENU) coordinates.\n",
-    "\n",
-    "ADCPs utilize an internal compass or magnetometer to determine magnetic ENU directions. You can use the set_declination function to adjust the velocity data according to the magnetic declination specific to your geographical coordinates. This declination can be looked up online for specific coordinates.\n",
-    "\n",
-    "Instruments save vector data in the coordinate system defined in the deployment configuration file. To make this data meaningful, it must be transformed through various coordinate systems (\"beam\"<->\"inst\"<->\"earth\"<->\"principal\"). This transformation is accomplished using the `rotate2` function. If the \"earth\" (ENU) coordinate system is specified, DOLfYN will automatically rotate the dataset through the required coordinate systems to reach the \"earth\" coordinates. Setting `inplace` to true will modify the input dataset directly, meaning it will not create a new dataset.\n",
-    "\n",
-    "In this case, since the ADCP data is already in the \"earth\" coordinate system, the `rotate2` function will return the input dataset without modifications. The `set_declination` function will work no matter the coordinate system."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data is already in the earth coordinate system\n"
-     ]
-    }
-   ],
-   "source": [
-    "dolfyn.set_declination(ds, 15.8, inplace=True)  # 15.8 deg East\n",
-    "dolfyn.rotate2(ds, \"earth\", inplace=True)"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To rotate into the principal frame of reference (streamwise, cross-stream, vertical), if desired, we must first calculate the depth-averaged principal flow heading and add it to the dataset attributes. Then the dataset can be rotated using the same `rotate2` function. We use `inplace=False` because we do not want to alter the input dataset here."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ds.attrs[\"principal_heading\"] = dolfyn.calc_principal_heading(ds[\"vel\"].mean(\"range\"))\n",
-    "ds = dolfyn.rotate2(ds, \"principal\", inplace=False)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Updated velocity histograms and contour plots for rotated velocity. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "api.clean.water_depth_from_pressure(ds, salinity=31)\n",
+        "ds = api.clean.remove_surface_interference(ds)"
+      ]
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x1200 with 4 Axes>"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Visualizing the depth from the ADCP pressure sensor, and this depth includes any previously applied range offsets. We can plot the water depth along with the cleaned velocity profiles:"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "vel = ds[\"vel\"]\n",
-    "\n",
-    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
-    "labels = vel.coords[vel_dim].values\n",
-    "\n",
-    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
-    "\n",
-    "if len(labels) == 1:\n",
-    "    axes = [axes]\n",
-    "\n",
-    "for ax_i, label in zip(axes, labels):\n",
-    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
-    "    values = values[np.isfinite(values)]\n",
-    "\n",
-    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
-    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
-    "    ax_i.set_ylabel(\"Count\")\n",
-    "\n",
-    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1500x400 with 6 Axes>"
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1500x400 with 6 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+        "\n",
+        "for i, ax in enumerate(axes):\n",
+        "    ds[\"vel\"][i].plot(ax=ax, vmin=-1.5, vmax=1.5, cmap=\"RdBu_r\")\n",
+        "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+        "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+        "    ax.plot(ds[\"time\"], ds[\"depth\"], color=\"black\", label=\"Depth\")"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
-    "\n",
-    "for i, ax in enumerate(axes):\n",
-    "    ds[\"vel\"][i].plot(ax=ax)\n",
-    "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
-    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 3. Average the Data\n",
-    "\n",
-    "As this deployment was configured in \"burst mode\", a standard step in the analysis process is to average the velocity data into time bins. \n",
-    "\n",
-    "However, if the instrument was set up in an \"averaging mode\" (where a specific profile and/or average interval was set, for instance, averaging 5 minutes of data every 30 minutes), this step would have been performed within the ADCP during deployment and can thus be skipped.\n",
-    "\n",
-    "To average the data into time bins (also known as ensembles), you should first initialize the binning tool `ADPBinner`. The parameter \"n_bin\" represents the number of data points in each ensemble. In this case, we're dealing with 300 seconds' worth of data. The \"fs\" parameter stands for the sampling frequency, which for this deployment is 1 Hz. Once the binning tool is initialized, you can use the `bin_average` function to average the data into ensembles."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "avg_tool = api.ADPBinner(n_bin=ds.fs * 300, fs=ds.fs)\n",
-    "ds_avg = avg_tool.bin_average(ds)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Dateframe, velocity histogram, and contour plot for 5 minute averaged velocity. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
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-       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
-       "</symbol>\n",
-       "</defs>\n",
-       "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
-       "\n",
-       ":root {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, white)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       "html[theme=\"dark\"],\n",
-       "html[data-theme=\"dark\"],\n",
-       "body[data-theme=\"dark\"],\n",
-       "body.vscode-dark {\n",
-       "  --xr-font-color0: var(\n",
-       "    --jp-content-font-color0,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
-       "  );\n",
-       "  --xr-font-color2: var(\n",
-       "    --jp-content-font-color2,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
-       "  );\n",
-       "  --xr-font-color3: var(\n",
-       "    --jp-content-font-color3,\n",
-       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
-       "  );\n",
-       "  --xr-border-color: var(\n",
-       "    --jp-border-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
-       "  );\n",
-       "  --xr-disabled-color: var(\n",
-       "    --jp-layout-color3,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
-       "  );\n",
-       "  --xr-background-color: var(\n",
-       "    --jp-layout-color0,\n",
-       "    var(--pst-color-on-background, #111111)\n",
-       "  );\n",
-       "  --xr-background-color-row-even: var(\n",
-       "    --jp-layout-color1,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
-       "  );\n",
-       "  --xr-background-color-row-odd: var(\n",
-       "    --jp-layout-color2,\n",
-       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
-       "  );\n",
-       "}\n",
-       "\n",
-       ".xr-wrap {\n",
-       "  display: block !important;\n",
-       "  min-width: 300px;\n",
-       "  max-width: 700px;\n",
-       "  line-height: 1.6;\n",
-       "}\n",
-       "\n",
-       ".xr-text-repr-fallback {\n",
-       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-header {\n",
-       "  padding-top: 6px;\n",
-       "  padding-bottom: 6px;\n",
-       "  margin-bottom: 4px;\n",
-       "  border-bottom: solid 1px var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-header > div,\n",
-       ".xr-header > ul {\n",
-       "  display: inline;\n",
-       "  margin-top: 0;\n",
-       "  margin-bottom: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-obj-type,\n",
-       ".xr-obj-name,\n",
-       ".xr-group-name {\n",
-       "  margin-left: 2px;\n",
-       "  margin-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name::before {\n",
-       "  content: \"📁\";\n",
-       "  padding-right: 0.3em;\n",
-       "}\n",
-       "\n",
-       ".xr-group-name,\n",
-       ".xr-obj-type {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-sections {\n",
-       "  padding-left: 0 !important;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
-       "  margin-block-start: 0;\n",
-       "  margin-block-end: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input {\n",
-       "  display: inline-block;\n",
-       "  opacity: 0;\n",
-       "  height: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input + label {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "  border: 2px solid transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label {\n",
-       "  cursor: pointer;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:focus + label {\n",
-       "  border: 2px solid var(--xr-font-color0) !important;\n",
-       "}\n",
-       "\n",
-       ".xr-section-item input:enabled + label:hover {\n",
-       "  color: var(--xr-font-color0);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary {\n",
-       "  grid-column: 1;\n",
-       "  color: var(--xr-font-color2);\n",
-       "  font-weight: 500;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary > span {\n",
-       "  display: inline-block;\n",
-       "  padding-left: 0.5em;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label {\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in + label:before {\n",
-       "  display: inline-block;\n",
-       "  content: \"►\";\n",
-       "  font-size: 11px;\n",
-       "  width: 15px;\n",
-       "  text-align: center;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:disabled + label:before {\n",
-       "  color: var(--xr-disabled-color);\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label:before {\n",
-       "  content: \"▼\";\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked + label > span {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary,\n",
-       ".xr-section-inline-details {\n",
-       "  padding-top: 4px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-inline-details {\n",
-       "  grid-column: 2 / -1;\n",
-       "}\n",
-       "\n",
-       ".xr-section-details {\n",
-       "  display: none;\n",
-       "  grid-column: 1 / -1;\n",
-       "  margin-top: 4px;\n",
-       "  margin-bottom: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box {\n",
-       "  display: inline-grid;\n",
-       "  grid-template-columns: 0px 20px auto;\n",
-       "  width: 100%;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-vline {\n",
-       "  grid-column-start: 1;\n",
-       "  border-right: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "  width: 0px;\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-hline {\n",
-       "  grid-column-start: 2;\n",
-       "  grid-row-start: 1;\n",
-       "  height: 1em;\n",
-       "  width: 20px;\n",
-       "  border-bottom: 0.2em solid;\n",
-       "  border-color: var(--xr-border-color);\n",
-       "}\n",
-       "\n",
-       ".xr-group-box-contents {\n",
-       "  grid-column-start: 3;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap {\n",
-       "  grid-column: 1 / -1;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 20px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-array-wrap > label {\n",
-       "  grid-column: 1;\n",
-       "  vertical-align: top;\n",
-       "}\n",
-       "\n",
-       ".xr-preview {\n",
-       "  color: var(--xr-font-color3);\n",
-       "}\n",
-       "\n",
-       ".xr-array-preview,\n",
-       ".xr-array-data {\n",
-       "  padding: 0 5px !important;\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-array-data,\n",
-       ".xr-array-in:checked ~ .xr-array-preview {\n",
-       "  display: none;\n",
-       "}\n",
-       "\n",
-       ".xr-array-in:checked ~ .xr-array-data,\n",
-       ".xr-array-preview {\n",
-       "  display: inline-block;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list {\n",
-       "  display: inline-block !important;\n",
-       "  list-style: none;\n",
-       "  padding: 0 !important;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li {\n",
-       "  display: inline-block;\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:before {\n",
-       "  content: \"(\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list:after {\n",
-       "  content: \")\";\n",
-       "}\n",
-       "\n",
-       ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: \",\";\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-has-index {\n",
-       "  font-weight: bold;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list,\n",
-       ".xr-var-item {\n",
-       "  display: contents;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > div,\n",
-       ".xr-var-item label,\n",
-       ".xr-var-item > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-even);\n",
-       "  border-color: var(--xr-background-color-row-odd);\n",
-       "  margin-bottom: 0;\n",
-       "  padding-top: 2px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-item > .xr-var-name:hover span {\n",
-       "  padding-right: 5px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-list > li:nth-child(odd) > div,\n",
-       ".xr-var-list > li:nth-child(odd) > label,\n",
-       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
-       "  background-color: var(--xr-background-color-row-odd);\n",
-       "  border-color: var(--xr-background-color-row-even);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name {\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dims {\n",
-       "  grid-column: 2;\n",
-       "}\n",
-       "\n",
-       ".xr-var-dtype {\n",
-       "  grid-column: 3;\n",
-       "  text-align: right;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-preview {\n",
-       "  grid-column: 4;\n",
-       "}\n",
-       "\n",
-       ".xr-index-preview {\n",
-       "  grid-column: 2 / 5;\n",
-       "  color: var(--xr-font-color2);\n",
-       "}\n",
-       "\n",
-       ".xr-var-name,\n",
-       ".xr-var-dims,\n",
-       ".xr-var-dtype,\n",
-       ".xr-preview,\n",
-       ".xr-attrs dt {\n",
-       "  white-space: nowrap;\n",
-       "  overflow: hidden;\n",
-       "  text-overflow: ellipsis;\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name:hover,\n",
-       ".xr-var-dims:hover,\n",
-       ".xr-var-dtype:hover,\n",
-       ".xr-attrs dt:hover {\n",
-       "  overflow: visible;\n",
-       "  width: auto;\n",
-       "  z-index: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  display: none;\n",
-       "  border-top: 2px dotted var(--xr-background-color);\n",
-       "  padding-bottom: 20px !important;\n",
-       "  padding-top: 10px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in + label,\n",
-       ".xr-var-data-in + label,\n",
-       ".xr-index-data-in + label {\n",
-       "  padding: 0 1px;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data,\n",
-       ".xr-index-data-in:checked ~ .xr-index-data {\n",
-       "  display: block;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > table {\n",
-       "  float: right;\n",
-       "}\n",
-       "\n",
-       ".xr-var-data > pre,\n",
-       ".xr-index-data > pre,\n",
-       ".xr-var-data > table > tbody > tr {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "\n",
-       ".xr-var-name span,\n",
-       ".xr-var-data,\n",
-       ".xr-index-name div,\n",
-       ".xr-index-data,\n",
-       ".xr-attrs {\n",
-       "  padding-left: 25px !important;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs,\n",
-       ".xr-var-attrs,\n",
-       ".xr-var-data,\n",
-       ".xr-index-data {\n",
-       "  grid-column: 1 / -1;\n",
-       "}\n",
-       "\n",
-       "dl.xr-attrs {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  display: grid;\n",
-       "  grid-template-columns: 125px auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt,\n",
-       ".xr-attrs dd {\n",
-       "  padding: 0;\n",
-       "  margin: 0;\n",
-       "  float: left;\n",
-       "  padding-right: 10px;\n",
-       "  width: auto;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt {\n",
-       "  font-weight: normal;\n",
-       "  grid-column: 1;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dt:hover span {\n",
-       "  display: inline-block;\n",
-       "  background: var(--xr-background-color);\n",
-       "  padding-right: 10px;\n",
-       "}\n",
-       "\n",
-       ".xr-attrs dd {\n",
-       "  grid-column: 2;\n",
-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "\n",
-       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
-       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
-       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
-       "  color: var(--xr-font-color0);\n",
-       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
-       "  stroke-width: 0.8px;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
-       "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-       "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
-       "Coordinates:\n",
-       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
-       "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
-       "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
-       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
-       "  * beam            (beam) int32 16B 1 2 3 4\n",
-       "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * q               (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
-       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-       "Data variables: (12/38)\n",
-       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
-       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
-       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
-       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
-       "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
-       "    ...              ...\n",
-       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
-       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
-       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
-       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
-       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
-       "Attributes: (12/41)\n",
-       "    fs:                        1\n",
-       "    n_bin:                     300\n",
-       "    n_fft:                     300\n",
-       "    description:               Binned averages calculated from ensembles of s...\n",
-       "    filehead_config:           {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;...\n",
-       "    inst_model:                Signature1000\n",
-       "    ...                        ...\n",
-       "    has_imu:                   1\n",
-       "    beam_angle:                25\n",
-       "    range_offset:              0.6\n",
-       "    declination:               15.8\n",
-       "    declination_in_orientmat:  1\n",
-       "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-94cd68dd-7aac-478a-80b1-3a6f39b8452a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-94cd68dd-7aac-478a-80b1-3a6f39b8452a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3bbb6d59-0298-4fdb-a533-98ba028cbc81' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3bbb6d59-0298-4fdb-a533-98ba028cbc81' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-83f5cfe5-8633-46aa-ae9d-9ed27402e9a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83f5cfe5-8633-46aa-ae9d-9ed27402e9a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4595c08c-025a-4bd3-9186-a759a86a2e83' class='xr-var-data-in' type='checkbox'><label for='data-4595c08c-025a-4bd3-9186-a759a86a2e83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
-       "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
-       "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
-       "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
-       "       &#x27;2020-08-15T01:02:30.001023769&#x27;, &#x27;2020-08-15T01:07:30.001024723&#x27;,\n",
-       "       &#x27;2020-08-15T01:12:30.001034259&#x27;, &#x27;2020-08-15T01:17:30.001035451&#x27;,\n",
-       "       &#x27;2020-08-15T01:22:30.001024961&#x27;, &#x27;2020-08-15T01:27:30.001025438&#x27;,\n",
-       "       &#x27;2020-08-15T01:32:30.001025676&#x27;, &#x27;2020-08-15T01:37:30.001031875&#x27;,\n",
-       "       &#x27;2020-08-15T01:42:30.001029014&#x27;, &#x27;2020-08-15T01:47:30.001030683&#x27;,\n",
-       "       &#x27;2020-08-15T01:52:30.001033067&#x27;, &#x27;2020-08-15T01:57:30.001029014&#x27;,\n",
-       "       &#x27;2020-08-15T02:02:30.001028299&#x27;, &#x27;2020-08-15T02:07:30.001020908&#x27;,\n",
-       "       &#x27;2020-08-15T02:12:30.001016378&#x27;, &#x27;2020-08-15T02:17:30.001012802&#x27;,\n",
-       "       &#x27;2020-08-15T02:22:30.001014709&#x27;, &#x27;2020-08-15T02:27:30.001018524&#x27;,\n",
-       "       &#x27;2020-08-15T02:32:30.001022577&#x27;, &#x27;2020-08-15T02:37:30.001020193&#x27;,\n",
-       "       &#x27;2020-08-15T02:42:30.001002311&#x27;, &#x27;2020-08-15T02:47:30.001003503&#x27;,\n",
-       "       &#x27;2020-08-15T02:52:30.001002550&#x27;, &#x27;2020-08-15T02:57:30.001000165&#x27;,\n",
-       "       &#x27;2020-08-15T03:02:30.001000642&#x27;, &#x27;2020-08-15T03:07:30.001000404&#x27;,\n",
-       "       &#x27;2020-08-15T03:12:30.000999450&#x27;, &#x27;2020-08-15T03:17:30.001003026&#x27;,\n",
-       "       &#x27;2020-08-15T03:22:30.001004695&#x27;, &#x27;2020-08-15T03:27:30.001004219&#x27;,\n",
-       "       &#x27;2020-08-15T03:32:30.001001834&#x27;, &#x27;2020-08-15T03:37:30.001005887&#x27;,\n",
-       "       &#x27;2020-08-15T03:42:30.001003742&#x27;, &#x27;2020-08-15T03:47:30.001000642&#x27;,\n",
-       "       &#x27;2020-08-15T03:52:30.001000404&#x27;, &#x27;2020-08-15T03:57:30.001001834&#x27;,\n",
-       "       &#x27;2020-08-15T04:02:30.001001834&#x27;, &#x27;2020-08-15T04:07:30.001001358&#x27;,\n",
-       "       &#x27;2020-08-15T04:12:30.001004695&#x27;, &#x27;2020-08-15T04:17:30.001001358&#x27;,\n",
-       "       &#x27;2020-08-15T04:22:30.001009464&#x27;, &#x27;2020-08-15T04:27:30.001006603&#x27;,\n",
-       "       &#x27;2020-08-15T04:32:30.001002550&#x27;, &#x27;2020-08-15T04:37:30.001004695&#x27;,\n",
-       "       &#x27;2020-08-15T04:42:30.001004934&#x27;, &#x27;2020-08-15T04:47:30.001004934&#x27;,\n",
-       "       &#x27;2020-08-15T04:52:30.001004457&#x27;, &#x27;2020-08-15T04:57:30.001002788&#x27;,\n",
-       "       &#x27;2020-08-15T05:02:30.001008749&#x27;, &#x27;2020-08-15T05:07:30.001017570&#x27;,\n",
-       "       &#x27;2020-08-15T05:12:30.001015186&#x27;, &#x27;2020-08-15T05:17:30.001005887&#x27;,\n",
-       "       &#x27;2020-08-15T05:22:30.001001358&#x27;, &#x27;2020-08-15T05:27:30.001011610&#x27;,\n",
-       "       &#x27;2020-08-15T05:32:30.001020431&#x27;, &#x27;2020-08-15T05:37:30.001011848&#x27;,\n",
-       "       &#x27;2020-08-15T05:42:30.001020908&#x27;, &#x27;2020-08-15T05:47:30.001013517&#x27;,\n",
-       "       &#x27;2020-08-15T05:52:30.001021146&#x27;, &#x27;2020-08-15T05:57:30.001010656&#x27;,\n",
-       "       &#x27;2020-08-15T06:02:30.001004219&#x27;, &#x27;2020-08-15T06:07:30.001012563&#x27;,\n",
-       "       &#x27;2020-08-15T06:12:30.001021862&#x27;, &#x27;2020-08-15T06:17:30.001018524&#x27;,\n",
-       "       &#x27;2020-08-15T06:22:30.001016139&#x27;, &#x27;2020-08-15T06:27:30.001016616&#x27;,\n",
-       "       &#x27;2020-08-15T06:32:30.001012325&#x27;, &#x27;2020-08-15T06:37:30.001016378&#x27;,\n",
-       "       &#x27;2020-08-15T06:42:30.001021862&#x27;, &#x27;2020-08-15T06:47:30.001023769&#x27;,\n",
-       "       &#x27;2020-08-15T06:52:30.001024007&#x27;, &#x27;2020-08-15T06:57:30.001014709&#x27;,\n",
-       "       &#x27;2020-08-15T07:02:30.001006126&#x27;, &#x27;2020-08-15T07:07:30.001019477&#x27;,\n",
-       "       &#x27;2020-08-15T07:12:30.001013994&#x27;, &#x27;2020-08-15T07:17:30.001016855&#x27;,\n",
-       "       &#x27;2020-08-15T07:22:30.001019239&#x27;, &#x27;2020-08-15T07:27:30.001024961&#x27;,\n",
-       "       &#x27;2020-08-15T07:32:30.001011610&#x27;, &#x27;2020-08-15T07:37:30.001024484&#x27;,\n",
-       "       &#x27;2020-08-15T07:42:30.001018524&#x27;, &#x27;2020-08-15T07:47:30.001029968&#x27;,\n",
-       "       &#x27;2020-08-15T07:52:30.001009464&#x27;, &#x27;2020-08-15T07:57:30.001014232&#x27;,\n",
-       "       &#x27;2020-08-15T08:02:30.001011610&#x27;, &#x27;2020-08-15T08:07:30.001028299&#x27;,\n",
-       "       &#x27;2020-08-15T08:12:30.001027107&#x27;, &#x27;2020-08-15T08:17:30.001024723&#x27;,\n",
-       "       &#x27;2020-08-15T08:22:30.001022577&#x27;, &#x27;2020-08-15T08:27:30.001018047&#x27;,\n",
-       "       &#x27;2020-08-15T08:32:30.001019477&#x27;, &#x27;2020-08-15T08:37:30.001017808&#x27;,\n",
-       "       &#x27;2020-08-15T08:42:30.001018762&#x27;, &#x27;2020-08-15T08:47:30.001015186&#x27;,\n",
-       "       &#x27;2020-08-15T08:52:30.001020431&#x27;, &#x27;2020-08-15T08:57:30.001026630&#x27;,\n",
-       "       &#x27;2020-08-15T09:02:30.001021146&#x27;, &#x27;2020-08-15T09:07:30.001016378&#x27;,\n",
-       "       &#x27;2020-08-15T09:12:30.001025676&#x27;, &#x27;2020-08-15T09:17:30.001024246&#x27;,\n",
-       "       &#x27;2020-08-15T09:22:30.001026630&#x27;, &#x27;2020-08-15T09:27:30.001017570&#x27;,\n",
-       "       &#x27;2020-08-15T09:32:30.001015901&#x27;, &#x27;2020-08-15T09:37:30.001016139&#x27;,\n",
-       "       &#x27;2020-08-15T09:42:30.001018762&#x27;, &#x27;2020-08-15T09:47:30.001014709&#x27;,\n",
-       "       &#x27;2020-08-15T09:52:30.001016378&#x27;, &#x27;2020-08-15T09:57:30.001024961&#x27;,\n",
-       "       &#x27;2020-08-15T10:02:30.001021146&#x27;, &#x27;2020-08-15T10:07:30.001022100&#x27;,\n",
-       "       &#x27;2020-08-15T10:12:30.001017808&#x27;, &#x27;2020-08-15T10:17:30.001013994&#x27;,\n",
-       "       &#x27;2020-08-15T10:22:30.001018762&#x27;, &#x27;2020-08-15T10:27:30.001021385&#x27;,\n",
-       "       &#x27;2020-08-15T10:32:30.001016855&#x27;, &#x27;2020-08-15T10:37:30.001021385&#x27;,\n",
-       "       &#x27;2020-08-15T10:42:30.001015186&#x27;, &#x27;2020-08-15T10:47:30.001020193&#x27;,\n",
-       "       &#x27;2020-08-15T10:52:30.001021623&#x27;, &#x27;2020-08-15T10:57:30.001021862&#x27;,\n",
-       "       &#x27;2020-08-15T11:02:30.001018047&#x27;, &#x27;2020-08-15T11:07:30.001021146&#x27;,\n",
-       "       &#x27;2020-08-15T11:12:30.001011848&#x27;, &#x27;2020-08-15T11:17:30.001015901&#x27;,\n",
-       "       &#x27;2020-08-15T11:22:30.001014232&#x27;, &#x27;2020-08-15T11:27:30.001015663&#x27;,\n",
-       "       &#x27;2020-08-15T11:32:30.001012325&#x27;, &#x27;2020-08-15T11:37:30.001004457&#x27;,\n",
-       "       &#x27;2020-08-15T11:42:30.001018524&#x27;, &#x27;2020-08-15T11:47:30.001023292&#x27;,\n",
-       "       &#x27;2020-08-15T11:52:30.001009464&#x27;, &#x27;2020-08-15T11:57:30.001002311&#x27;,\n",
-       "       &#x27;2020-08-15T12:02:30.001004695&#x27;, &#x27;2020-08-15T12:07:30.001007556&#x27;,\n",
-       "       &#x27;2020-08-15T12:12:30.001012086&#x27;, &#x27;2020-08-15T12:17:30.001007080&#x27;,\n",
-       "       &#x27;2020-08-15T12:22:30.001011371&#x27;, &#x27;2020-08-15T12:27:30.001014471&#x27;,\n",
-       "       &#x27;2020-08-15T12:32:30.001016378&#x27;, &#x27;2020-08-15T12:37:30.001012563&#x27;,\n",
-       "       &#x27;2020-08-15T12:42:30.001015901&#x27;, &#x27;2020-08-15T12:47:30.001010417&#x27;,\n",
-       "       &#x27;2020-08-15T12:52:30.001009464&#x27;, &#x27;2020-08-15T12:57:30.001010894&#x27;,\n",
-       "       &#x27;2020-08-15T13:02:30.001016855&#x27;, &#x27;2020-08-15T13:07:30.001020908&#x27;,\n",
-       "       &#x27;2020-08-15T13:12:30.001018762&#x27;, &#x27;2020-08-15T13:17:30.001018762&#x27;,\n",
-       "       &#x27;2020-08-15T13:22:30.001018047&#x27;, &#x27;2020-08-15T13:27:30.001013517&#x27;,\n",
-       "       &#x27;2020-08-15T13:32:30.001015424&#x27;, &#x27;2020-08-15T13:37:30.001009225&#x27;,\n",
-       "       &#x27;2020-08-15T13:42:30.001011133&#x27;, &#x27;2020-08-15T13:47:30.001008749&#x27;,\n",
-       "       &#x27;2020-08-15T13:52:30.001019477&#x27;, &#x27;2020-08-15T13:57:30.001022338&#x27;,\n",
-       "       &#x27;2020-08-15T14:02:30.001019716&#x27;, &#x27;2020-08-15T14:07:30.001026868&#x27;,\n",
-       "       &#x27;2020-08-15T14:12:30.001021623&#x27;, &#x27;2020-08-15T14:17:30.001034021&#x27;,\n",
-       "       &#x27;2020-08-15T14:22:30.001024961&#x27;, &#x27;2020-08-15T14:27:30.001032352&#x27;,\n",
-       "       &#x27;2020-08-15T14:32:30.001023292&#x27;, &#x27;2020-08-15T14:37:30.001024484&#x27;,\n",
-       "       &#x27;2020-08-15T14:42:30.001044034&#x27;, &#x27;2020-08-15T14:47:30.001032352&#x27;,\n",
-       "       &#x27;2020-08-15T14:52:30.001019239&#x27;, &#x27;2020-08-15T14:57:30.001032829&#x27;,\n",
-       "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
-       "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
-       "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-ee9453dd-0e1f-4609-800f-b7785def0997' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee9453dd-0e1f-4609-800f-b7785def0997' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e987dc0-2769-47d7-9980-0cffd6452fb4' class='xr-var-data-in' type='checkbox'><label for='data-7e987dc0-2769-47d7-9980-0cffd6452fb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-823e073a-d75c-463c-a4df-34580897ee81' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-823e073a-d75c-463c-a4df-34580897ee81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aab03f98-74f0-4e0d-adac-6d2c5c9837ed' class='xr-var-data-in' type='checkbox'><label for='data-aab03f98-74f0-4e0d-adac-6d2c5c9837ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-9e796c46-5807-46ff-bcee-dd007ae9a509' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e796c46-5807-46ff-bcee-dd007ae9a509' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88900068-2151-4243-8ce7-50c91e53ffcf' class='xr-var-data-in' type='checkbox'><label for='data-88900068-2151-4243-8ce7-50c91e53ffcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-129a6633-70c5-4877-971e-cbae6aef4cd1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-129a6633-70c5-4877-971e-cbae6aef4cd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-274de313-22c3-46a9-89be-05e30df2f539' class='xr-var-data-in' type='checkbox'><label for='data-274de313-22c3-46a9-89be-05e30df2f539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-07471bd2-3fff-4550-ab2c-3f3f935b6b8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07471bd2-3fff-4550-ab2c-3f3f935b6b8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ea841b9-c6fd-4485-ade0-d809c64b4430' class='xr-var-data-in' type='checkbox'><label for='data-6ea841b9-c6fd-4485-ade0-d809c64b4430' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-41aafcf3-92b7-41ed-91fe-e8fd7e853019' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41aafcf3-92b7-41ed-91fe-e8fd7e853019' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c331539-ea72-4303-9589-b1a9a3d1b226' class='xr-var-data-in' type='checkbox'><label for='data-8c331539-ea72-4303-9589-b1a9a3d1b226' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-96ef30a6-3706-45d0-b9ff-4bcc47822f51' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96ef30a6-3706-45d0-b9ff-4bcc47822f51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00da1e9-f04e-4fc0-b8c7-58f069ddffbb' class='xr-var-data-in' type='checkbox'><label for='data-f00da1e9-f04e-4fc0-b8c7-58f069ddffbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-ae39105f-724b-4ffb-ad5e-72022d2c834a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae39105f-724b-4ffb-ad5e-72022d2c834a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67133c30-1d3c-442b-b10a-a21e9ef43c2f' class='xr-var-data-in' type='checkbox'><label for='data-67133c30-1d3c-442b-b10a-a21e9ef43c2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
-       "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
-       "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
-       "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T01:02:29.938493013&#x27;, &#x27;2020-08-15T01:07:29.938492536&#x27;,\n",
-       "       &#x27;2020-08-15T01:12:29.938490867&#x27;, &#x27;2020-08-15T01:17:29.938497781&#x27;,\n",
-       "       &#x27;2020-08-15T01:22:29.938496112&#x27;, &#x27;2020-08-15T01:27:29.938498497&#x27;,\n",
-       "       &#x27;2020-08-15T01:32:29.938496589&#x27;, &#x27;2020-08-15T01:37:29.938497781&#x27;,\n",
-       "       &#x27;2020-08-15T01:42:29.938495635&#x27;, &#x27;2020-08-15T01:47:29.938497066&#x27;,\n",
-       "       &#x27;2020-08-15T01:52:29.938498735&#x27;, &#x27;2020-08-15T01:57:29.938496112&#x27;,\n",
-       "       &#x27;2020-08-15T02:02:29.938496589&#x27;, &#x27;2020-08-15T02:07:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T02:12:29.938497304&#x27;, &#x27;2020-08-15T02:17:29.938496828&#x27;,\n",
-       "       &#x27;2020-08-15T02:22:29.938496112&#x27;, &#x27;2020-08-15T02:27:29.938496828&#x27;,\n",
-       "       &#x27;2020-08-15T02:32:29.938496112&#x27;, &#x27;2020-08-15T02:37:29.938497304&#x27;,\n",
-       "       &#x27;2020-08-15T02:42:29.938495159&#x27;, &#x27;2020-08-15T02:47:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T02:52:29.938490867&#x27;, &#x27;2020-08-15T02:57:29.938492059&#x27;,\n",
-       "       &#x27;2020-08-15T03:02:29.938489675&#x27;, &#x27;2020-08-15T03:07:29.938488245&#x27;,\n",
-       "       &#x27;2020-08-15T03:12:29.938485622&#x27;, &#x27;2020-08-15T03:17:29.938485622&#x27;,\n",
-       "       &#x27;2020-08-15T03:22:29.938488245&#x27;, &#x27;2020-08-15T03:27:29.938485145&#x27;,\n",
-       "       &#x27;2020-08-15T03:32:29.938486099&#x27;, &#x27;2020-08-15T03:37:29.938482046&#x27;,\n",
-       "       &#x27;2020-08-15T03:42:29.938489437&#x27;, &#x27;2020-08-15T03:47:29.938489437&#x27;,\n",
-       "       &#x27;2020-08-15T03:52:29.938485860&#x27;, &#x27;2020-08-15T03:57:29.938491582&#x27;,\n",
-       "       &#x27;2020-08-15T04:02:29.938488006&#x27;, &#x27;2020-08-15T04:07:29.938491106&#x27;,\n",
-       "       &#x27;2020-08-15T04:12:29.938492059&#x27;, &#x27;2020-08-15T04:17:29.938487052&#x27;,\n",
-       "       &#x27;2020-08-15T04:22:29.938489675&#x27;, &#x27;2020-08-15T04:27:29.938491582&#x27;,\n",
-       "       &#x27;2020-08-15T04:32:29.938491106&#x27;, &#x27;2020-08-15T04:37:29.938493251&#x27;,\n",
-       "       &#x27;2020-08-15T04:42:29.938489675&#x27;, &#x27;2020-08-15T04:47:29.938492059&#x27;,\n",
-       "       &#x27;2020-08-15T04:52:29.938491582&#x27;, &#x27;2020-08-15T04:57:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T05:02:29.938491106&#x27;, &#x27;2020-08-15T05:07:29.938499212&#x27;,\n",
-       "       &#x27;2020-08-15T05:12:29.938491821&#x27;, &#x27;2020-08-15T05:17:29.938493490&#x27;,\n",
-       "       &#x27;2020-08-15T05:22:29.938495397&#x27;, &#x27;2020-08-15T05:27:29.938490390&#x27;,\n",
-       "       &#x27;2020-08-15T05:32:29.938493967&#x27;, &#x27;2020-08-15T05:37:29.938493728&#x27;,\n",
-       "       &#x27;2020-08-15T05:42:29.938491582&#x27;, &#x27;2020-08-15T05:47:29.938493013&#x27;,\n",
-       "       &#x27;2020-08-15T05:52:29.938495159&#x27;, &#x27;2020-08-15T05:57:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T06:02:29.938493013&#x27;, &#x27;2020-08-15T06:07:29.938496589&#x27;,\n",
-       "       &#x27;2020-08-15T06:12:29.938494920&#x27;, &#x27;2020-08-15T06:17:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T06:22:29.938493728&#x27;, &#x27;2020-08-15T06:27:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T06:32:29.938492536&#x27;, &#x27;2020-08-15T06:37:29.938495159&#x27;,\n",
-       "       &#x27;2020-08-15T06:42:29.938496112&#x27;, &#x27;2020-08-15T06:47:29.938497304&#x27;,\n",
-       "       &#x27;2020-08-15T06:52:29.938496112&#x27;, &#x27;2020-08-15T06:57:29.938493728&#x27;,\n",
-       "       &#x27;2020-08-15T07:02:29.938497304&#x27;, &#x27;2020-08-15T07:07:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T07:12:29.938492059&#x27;, &#x27;2020-08-15T07:17:29.938493490&#x27;,\n",
-       "       &#x27;2020-08-15T07:22:29.938493967&#x27;, &#x27;2020-08-15T07:27:29.938497304&#x27;,\n",
-       "       &#x27;2020-08-15T07:32:29.938494443&#x27;, &#x27;2020-08-15T07:37:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T07:42:29.938495635&#x27;, &#x27;2020-08-15T07:47:29.938493967&#x27;,\n",
-       "       &#x27;2020-08-15T07:52:29.938492298&#x27;, &#x27;2020-08-15T07:57:29.938489675&#x27;,\n",
-       "       &#x27;2020-08-15T08:02:29.938493013&#x27;, &#x27;2020-08-15T08:07:29.938493728&#x27;,\n",
-       "       &#x27;2020-08-15T08:12:29.938497066&#x27;, &#x27;2020-08-15T08:17:29.938497781&#x27;,\n",
-       "       &#x27;2020-08-15T08:22:29.938495159&#x27;, &#x27;2020-08-15T08:27:29.938492774&#x27;,\n",
-       "       &#x27;2020-08-15T08:32:29.938495397&#x27;, &#x27;2020-08-15T08:37:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T08:42:29.938494920&#x27;, &#x27;2020-08-15T08:47:29.938494682&#x27;,\n",
-       "       &#x27;2020-08-15T08:52:29.938494443&#x27;, &#x27;2020-08-15T08:57:29.938491821&#x27;,\n",
-       "       &#x27;2020-08-15T09:02:29.938497066&#x27;, &#x27;2020-08-15T09:07:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T09:12:29.938495397&#x27;, &#x27;2020-08-15T09:17:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T09:22:29.938498020&#x27;, &#x27;2020-08-15T09:27:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T09:32:29.938495159&#x27;, &#x27;2020-08-15T09:37:29.938498735&#x27;,\n",
-       "       &#x27;2020-08-15T09:42:29.938493728&#x27;, &#x27;2020-08-15T09:47:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T09:52:29.938500642&#x27;, &#x27;2020-08-15T09:57:29.938496589&#x27;,\n",
-       "       &#x27;2020-08-15T10:02:29.938497781&#x27;, &#x27;2020-08-15T10:07:29.938500881&#x27;,\n",
-       "       &#x27;2020-08-15T10:12:29.938504457&#x27;, &#x27;2020-08-15T10:17:29.938501358&#x27;,\n",
-       "       &#x27;2020-08-15T10:22:29.938507556&#x27;, &#x27;2020-08-15T10:27:29.938496112&#x27;,\n",
-       "       &#x27;2020-08-15T10:32:29.938495635&#x27;, &#x27;2020-08-15T10:37:29.938500165&#x27;,\n",
-       "       &#x27;2020-08-15T10:42:29.938496112&#x27;, &#x27;2020-08-15T10:47:29.938493251&#x27;,\n",
-       "       &#x27;2020-08-15T10:52:29.938493728&#x27;, &#x27;2020-08-15T10:57:29.938492536&#x27;,\n",
-       "       &#x27;2020-08-15T11:02:29.938492774&#x27;, &#x27;2020-08-15T11:07:29.938492774&#x27;,\n",
-       "       &#x27;2020-08-15T11:12:29.938493967&#x27;, &#x27;2020-08-15T11:17:29.938494443&#x27;,\n",
-       "       &#x27;2020-08-15T11:22:29.938496589&#x27;, &#x27;2020-08-15T11:27:29.938496112&#x27;,\n",
-       "       &#x27;2020-08-15T11:32:29.938495397&#x27;, &#x27;2020-08-15T11:37:29.938493967&#x27;,\n",
-       "       &#x27;2020-08-15T11:42:29.938493013&#x27;, &#x27;2020-08-15T11:47:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T11:52:29.938493967&#x27;, &#x27;2020-08-15T11:57:29.938498735&#x27;,\n",
-       "       &#x27;2020-08-15T12:02:29.938496589&#x27;, &#x27;2020-08-15T12:07:29.938498020&#x27;,\n",
-       "       &#x27;2020-08-15T12:12:29.938494443&#x27;, &#x27;2020-08-15T12:17:29.938495159&#x27;,\n",
-       "       &#x27;2020-08-15T12:22:29.938495635&#x27;, &#x27;2020-08-15T12:27:29.938497066&#x27;,\n",
-       "       &#x27;2020-08-15T12:32:29.938493967&#x27;, &#x27;2020-08-15T12:37:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T12:42:29.938496112&#x27;, &#x27;2020-08-15T12:47:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T12:52:29.938494443&#x27;, &#x27;2020-08-15T12:57:29.938496589&#x27;,\n",
-       "       &#x27;2020-08-15T13:02:29.938494205&#x27;, &#x27;2020-08-15T13:07:29.938494205&#x27;,\n",
-       "       &#x27;2020-08-15T13:12:29.938492536&#x27;, &#x27;2020-08-15T13:17:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T13:22:29.938493251&#x27;, &#x27;2020-08-15T13:27:29.938495397&#x27;,\n",
-       "       &#x27;2020-08-15T13:32:29.938494920&#x27;, &#x27;2020-08-15T13:37:29.938497066&#x27;,\n",
-       "       &#x27;2020-08-15T13:42:29.938497304&#x27;, &#x27;2020-08-15T13:47:29.938494920&#x27;,\n",
-       "       &#x27;2020-08-15T13:52:29.938493490&#x27;, &#x27;2020-08-15T13:57:29.938492774&#x27;,\n",
-       "       &#x27;2020-08-15T14:02:29.938496112&#x27;, &#x27;2020-08-15T14:07:29.938489675&#x27;,\n",
-       "       &#x27;2020-08-15T14:12:29.938489913&#x27;, &#x27;2020-08-15T14:17:29.938494443&#x27;,\n",
-       "       &#x27;2020-08-15T14:22:29.938495397&#x27;, &#x27;2020-08-15T14:27:29.938492774&#x27;,\n",
-       "       &#x27;2020-08-15T14:32:29.938491582&#x27;, &#x27;2020-08-15T14:37:29.938493251&#x27;,\n",
-       "       &#x27;2020-08-15T14:42:29.938492536&#x27;, &#x27;2020-08-15T14:47:29.938492774&#x27;,\n",
-       "       &#x27;2020-08-15T14:52:29.938491106&#x27;, &#x27;2020-08-15T14:57:29.938495635&#x27;,\n",
-       "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
-       "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
-       "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-f53e9720-6d63-4f51-8a7a-f8bf4ed3af70' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f53e9720-6d63-4f51-8a7a-f8bf4ed3af70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7e9300c-f075-4671-b07c-6ee5e31d03ca' class='xr-var-data-in' type='checkbox'><label for='data-b7e9300c-f075-4671-b07c-6ee5e31d03ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
-       "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b67361b7-a489-4710-b7cb-1eaa91d2b631' class='xr-section-summary-in' type='checkbox'  ><label for='section-b67361b7-a489-4710-b7cb-1eaa91d2b631' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-63952b1d-c12b-4529-9de6-757bb7fc4022' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63952b1d-c12b-4529-9de6-757bb7fc4022' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b9837e3-8b6d-4623-b540-df60aaa29fd6' class='xr-var-data-in' type='checkbox'><label for='data-6b9837e3-8b6d-4623-b540-df60aaa29fd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
-       "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
-       "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
-       "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
-       "       1500.6763, 1500.2716, 1500.1096, 1499.8009, 1499.5637, 1499.3373,\n",
-       "       1499.2163, 1499.0955, 1498.9806, 1498.8579, 1498.7637, 1498.6821,\n",
-       "       1498.6133, 1498.5066, 1498.5637, 1498.7421, 1498.8367, 1498.984 ,\n",
-       "       1498.9717, 1498.9644, 1499.0553, 1499.21  , 1499.2789, 1499.2766,\n",
-       "       1499.265 , 1499.2623, 1499.3181, 1499.2903, 1499.3444, 1499.2922,\n",
-       "       1499.2983, 1499.195 , 1499.2087, 1499.212 , 1499.2494, 1499.2227,\n",
-       "       1499.1742, 1499.1772, 1499.1937, 1499.2306, 1499.2719, 1499.3043,\n",
-       "       1499.4073, 1499.3677, 1499.4554, 1499.5647, 1499.6683, 1499.7489,\n",
-       "       1499.8341, 1499.8446, 1499.8396, 1499.9257, 1499.781 , 1499.8274,\n",
-       "       1499.7506, 1499.8904, 1499.7473, 1499.7411, 1499.7415, 1499.7079,\n",
-       "       1499.508 , 1499.7562, 1499.5327, 1499.4186, 1499.4877, 1499.1946,\n",
-       "       1499.1821, 1499.466 , 1499.5144, 1499.7024, 1499.8877, 1499.8373,\n",
-       "       1499.8597, 1500.1703, 1500.0886, 1500.082 , 1500.0476, 1499.9003,\n",
-       "       1499.8434, 1498.8927, 1497.6433, 1496.299 , 1495.386 , 1495.2273,\n",
-       "       1494.9376, 1494.7117, 1494.9341, 1495.1063, 1495.0103, 1494.7747,\n",
-       "       1494.5977, 1494.4548, 1494.4042, 1494.3356, 1494.229 , 1494.0669,\n",
-       "       1493.7662, 1493.4755, 1493.3303, 1493.1544, 1492.8477, 1492.7877,\n",
-       "       1492.8064, 1493.0189, 1493.5558, 1494.0146, 1494.7506, 1495.2681,\n",
-       "       1496.2244, 1496.8036, 1497.5472, 1498.0507, 1498.3839, 1498.663 ,\n",
-       "       1498.8971, 1499.136 , 1499.3384, 1499.535 , 1499.5739, 1499.5245,\n",
-       "       1499.4437, 1499.4467, 1499.5509, 1499.6014, 1499.5997, 1499.5935,\n",
-       "       1499.525 , 1499.4967, 1499.4364, 1499.4977, 1499.503 , 1499.5526,\n",
-       "       1499.5083, 1499.5023, 1499.474 , 1499.4028, 1499.436 , 1499.4973,\n",
-       "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
-       "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
-       "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
-       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-95a9e011-df19-4e04-a3e8-3b06c28ec021' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95a9e011-df19-4e04-a3e8-3b06c28ec021' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6c6987d-f6a0-48a7-96cc-2f19ae146351' class='xr-var-data-in' type='checkbox'><label for='data-e6c6987d-f6a0-48a7-96cc-2f19ae146351' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
-       "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
-       "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
-       "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
-       "       14.572268 , 14.502767 , 14.376032 , 14.268402 , 14.178566 ,\n",
-       "       14.055    , 14.005532 , 13.911533 , 13.838566 , 13.7688675,\n",
-       "       13.7339325, 13.696598 , 13.661633 , 13.626367 , 13.597433 ,\n",
-       "       13.572568 , 13.552067 , 13.520534 , 13.538133 , 13.592899 ,\n",
-       "       13.620734 , 13.665668 , 13.661699 , 13.658334 , 13.686766 ,\n",
-       "       13.7354   , 13.754033 , 13.754901 , 13.7525   , 13.751934 ,\n",
-       "       13.767399 , 13.760633 , 13.776802 , 13.761433 , 13.7625   ,\n",
-       "       13.731066 , 13.7371   , 13.737367 , 13.748701 , 13.741634 ,\n",
-       "       13.726335 , 13.726666 , 13.7323   , 13.743701 , 13.756766 ,\n",
-       "       13.766968 , 13.797334 , 13.7852   , 13.812601 , 13.847366 ,\n",
-       "       13.878734 , 13.903067 , 13.928333 , 13.931099 , 13.930567 ,\n",
-       "       13.957533 , 13.912533 , 13.9264   , 13.9032   , 13.947433 ,\n",
-       "       13.902601 , 13.900833 , 13.900665 , 13.890833 , 13.830032 ,\n",
-       "       13.9046335, 13.8364   , 13.801933 , 13.8241   , 13.735    ,\n",
-       "       13.732666 , 13.818233 , 13.8298   , 13.888301 , 13.944167 ,\n",
-       "       13.928867 , 13.9361   , 14.0331   , 14.008999 , 14.006901 ,\n",
-       "       13.992832 , 13.946533 , 13.9282   , 13.643267 , 13.266466 ,\n",
-       "       12.865967 , 12.595367 , 12.5469   , 12.462267 , 12.3959   ,\n",
-       "       12.461133 , 12.512366 , 12.482166 , 12.411167 , 12.3605995,\n",
-       "       12.3201   , 12.303568 , 12.284267 , 12.252732 , 12.203699 ,\n",
-       "       12.118533 , 12.031001 , 11.988433 , 11.939434 , 11.8505   ,\n",
-       "       11.8341   , 11.837234 , 11.8984995, 12.0561   , 12.189    ,\n",
-       "       12.403767 , 12.5546   , 12.837867 , 13.010934 , 13.233933 ,\n",
-       "       13.384068 , 13.485199 , 13.565999 , 13.639567 , 13.711732 ,\n",
-       "       13.774034 , 13.829665 , 13.838365 , 13.829668 , 13.8013   ,\n",
-       "       13.805167 , 13.833833 , 13.855499 , 13.857698 , 13.844232 ,\n",
-       "       13.831333 , 13.816167 , 13.802168 , 13.811266 , 13.820599 ,\n",
-       "       13.834399 , 13.828466 , 13.826566 , 13.810034 , 13.792601 ,\n",
-       "       13.800402 , 13.820232 , 13.830032 , 13.8446665, 13.8607   ,\n",
-       "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
-       "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
-       "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
-       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-3afeb9ef-5d73-4f4c-b904-34b07796c1de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3afeb9ef-5d73-4f4c-b904-34b07796c1de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30163c0a-6f68-479b-b273-e60ae4eaa390' class='xr-var-data-in' type='checkbox'><label for='data-30163c0a-6f68-479b-b273-e60ae4eaa390' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
-       "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
-       "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
-       "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
-       "       9.218047 , 9.186557 , 9.157551 , 9.123754 , 9.09348  , 9.059697 ,\n",
-       "       9.026804 , 8.994499 , 8.95571  , 8.92198  , 8.886473 , 8.853367 ,\n",
-       "       8.813594 , 8.782229 , 8.74448  , 8.708926 , 8.674907 , 8.637604 ,\n",
-       "       8.602573 , 8.560874 , 8.524677 , 8.48187  , 8.4449835, 8.400766 ,\n",
-       "       8.365373 , 8.322662 , 8.28713  , 8.248011 , 8.21333  , 8.178404 ,\n",
-       "       8.14623  , 8.109827 , 8.072543 , 8.039574 , 7.9980125, 7.963136 ,\n",
-       "       7.926347 , 7.8918767, 7.8531103, 7.824253 , 7.7964296, 7.7649107,\n",
-       "       7.7383432, 7.7130632, 7.6841335, 7.65858  , 7.633538 , 7.609003 ,\n",
-       "       7.592057 , 7.573613 , 7.5537395, 7.533187 , 7.5146875, 7.497063 ,\n",
-       "       7.48256  , 7.472039 , 7.454433 , 7.4437304, 7.4306965, 7.422947 ,\n",
-       "       7.4138427, 7.4127507, 7.407543 , 7.4021435, 7.40189  , 7.4006333,\n",
-       "       7.401152 , 7.3961263, 7.4010367, 7.4031525, 7.414211 , 7.4199567,\n",
-       "       7.4243903, 7.4346695, 7.4523306, 7.4677606, 7.47785  , 7.4955306,\n",
-       "       7.507134 , 7.52034  , 7.540297 , 7.5592594, 7.583973 , 7.6029363,\n",
-       "       7.623276 , 7.6508303, 7.67267  , 7.6968994, 7.7202635, 7.7465167,\n",
-       "       7.7706933, 7.795326 , 7.820833 , 7.8509097, 7.8781033, 7.9117236,\n",
-       "       7.9442267, 7.9752865, 8.007596 , 8.042522 , 8.077546 , 8.108029 ,\n",
-       "       8.1417265, 8.17497  , 8.210143 , 8.243827 , 8.281553 , 8.317181 ,\n",
-       "       8.35565  , 8.390187 , 8.42794  , 8.465797 , 8.50642  , 8.54146  ,\n",
-       "       8.581511 , 8.618688 , 8.65223  , 8.69048  , 8.72701  , 8.758973 ,\n",
-       "       8.795943 , 8.832204 , 8.870703 , 8.8993225, 8.936847 , 8.969017 ,\n",
-       "       9.001257 , 9.036253 , 9.063161 , 9.095617 , 9.1287565, 9.157017 ,\n",
-       "       9.187741 , 9.216694 , 9.244237 , 9.274386 , 9.300383 , 9.32181  ,\n",
-       "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
-       "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
-       "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
-       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-2fb56565-ef29-4887-835e-41ad0b301dd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fb56565-ef29-4887-835e-41ad0b301dd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9195dd1f-c8d4-46c5-b7db-5eb6171eac67' class='xr-var-data-in' type='checkbox'><label for='data-9195dd1f-c8d4-46c5-b7db-5eb6171eac67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
-       "         3.60746217e+00,  3.56795740e+00,  3.58543777e+00,\n",
-       "         3.56357908e+00,  3.57667398e+00,  3.60632110e+00,\n",
-       "         3.56949067e+00,  3.57479167e+00,  3.59876704e+00,\n",
-       "         3.60281253e+00,  3.59981132e+00,  3.59064198e+00,\n",
-       "         3.59985065e+00,  3.58579111e+00,  3.57373047e+00,\n",
-       "         3.56544852e+00,  3.58114982e+00,  3.58714032e+00,\n",
-       "         3.55944085e+00,  3.58880138e+00,  3.53171992e+00,\n",
-       "         3.53358531e+00,  3.49057865e+00,  3.49481201e+00,\n",
-       "         3.49612260e+00,  3.45677161e+00,  3.42318940e+00,\n",
-       "         3.46062589e+00,  3.41326380e+00,  3.41770315e+00,\n",
-       "         3.41921234e+00,  3.43796873e+00,  3.42292237e+00,\n",
-       "         3.41392589e+00,  3.38415337e+00,  3.38218069e+00,\n",
-       "         3.43648434e+00,  3.38592434e+00,  3.34218621e+00,\n",
-       "         3.38532996e+00,  3.37350154e+00,  3.37754154e+00,\n",
-       "         3.35902476e+00,  3.34339881e+00,  3.35676146e+00,\n",
-       "         3.35692763e+00,  3.32560086e+00,  3.27195191e+00,\n",
-       "         3.19083190e+00,  2.95882225e+00,  2.40057945e+00,\n",
-       "         2.16090226e+00,  1.92318320e+00,  1.78795314e+00,\n",
-       "         1.62216699e+00,  1.56376326e+00,  1.46418226e+00,\n",
-       "...\n",
-       "        -1.96982498e+02, -1.97061203e+02, -1.96969849e+02,\n",
-       "        -1.97076538e+02, -1.97007187e+02, -1.97028168e+02,\n",
-       "        -1.97006195e+02, -1.97027512e+02, -1.97029175e+02,\n",
-       "        -1.96980515e+02, -1.97019150e+02, -1.96939850e+02,\n",
-       "        -1.96979843e+02, -1.97032181e+02, -1.97038193e+02,\n",
-       "        -1.96942871e+02, -1.96959534e+02, -1.96986191e+02,\n",
-       "        -1.97056839e+02, -1.97049850e+02, -1.97026855e+02,\n",
-       "        -1.97041199e+02, -1.97016525e+02, -1.97084503e+02,\n",
-       "        -1.97077499e+02, -1.97032166e+02, -1.97061508e+02,\n",
-       "        -1.97079834e+02, -1.97101852e+02, -1.97092865e+02,\n",
-       "        -1.97062164e+02, -1.97118851e+02, -1.97044510e+02,\n",
-       "        -1.97032166e+02, -1.97112183e+02, -1.96995499e+02,\n",
-       "        -1.97103195e+02, -1.97131195e+02, -1.97147202e+02,\n",
-       "        -1.97079849e+02, -1.97053513e+02, -1.97125504e+02,\n",
-       "        -1.97132843e+02, -1.97114838e+02, -1.97074829e+02,\n",
-       "        -1.97085831e+02, -1.97115845e+02, -1.97091156e+02,\n",
-       "        -1.97044174e+02, -1.97063873e+02, -1.97090515e+02,\n",
-       "        -1.97129501e+02, -1.97007523e+02, -1.97017838e+02,\n",
-       "        -1.97019165e+02, -1.97129166e+02, -1.97051849e+02,\n",
-       "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-a899fa25-7d18-4765-afe3-04bc22fe5d71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a899fa25-7d18-4765-afe3-04bc22fe5d71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b02d62d4-7b2a-4b71-b7be-ca78eb28e340' class='xr-var-data-in' type='checkbox'><label for='data-b02d62d4-7b2a-4b71-b7be-ca78eb28e340' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
-       "        -1.2613868 , -1.2610568 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
-       "        -1.2618904 , -1.258823  , -1.2596216 , -1.258702  , -1.2583325 ,\n",
-       "        -1.2578007 , -1.2583394 , -1.2576339 , -1.2579147 , -1.2534361 ,\n",
-       "        -1.2568558 , -1.2559422 , -1.2557042 , -1.2571892 , -1.2556211 ,\n",
-       "        -1.2540294 , -1.2548382 , -1.2532483 , -1.2525105 , -1.2511989 ,\n",
-       "        -1.2522614 , -1.2561746 , -1.2530836 , -1.2531874 , -1.2519903 ,\n",
-       "        -1.2518218 , -1.2511966 , -1.2544034 , -1.2561861 , -1.2536184 ,\n",
-       "        -1.2504781 , -1.2535783 , -1.2560768 , -1.2559297 , -1.257113  ,\n",
-       "        -1.2519604 , -1.2501055 , -1.2515699 , -1.2483989 , -1.2508361 ,\n",
-       "        -1.2479837 , -1.2430646 , -1.2314413 , -1.2083213 , -1.1935245 ,\n",
-       "        -1.1852744 , -1.1747023 , -1.1735051 , -1.1686733 , -1.1616861 ,\n",
-       "        -1.1579937 , -1.1570411 , -1.1541711 , -1.1540251 , -1.1536013 ,\n",
-       "        -1.1516274 , -1.147889  , -1.1449583 , -1.1449729 , -1.14322   ,\n",
-       "        -1.1418625 , -1.1392603 , -1.1384715 , -1.136121  , -1.1344364 ,\n",
-       "        -1.132704  , -1.1329331 , -1.1329101 , -1.130972  , -1.1331373 ,\n",
-       "        -1.1304799 , -1.1283726 , -1.1294136 , -1.132449  , -1.1283008 ,\n",
-       "        -1.1297874 , -1.1291262 , -1.1277461 , -1.1284393 , -1.1265595 ,\n",
-       "        -1.1229205 , -1.1222471 , -1.1207403 , -1.1196108 , -1.1196036 ,\n",
-       "        -1.1186633 , -1.1185873 , -1.1168755 , -1.1150851 , -1.1146263 ,\n",
-       "...\n",
-       "         9.716357  ,  9.717475  ,  9.7163725 ,  9.718897  ,  9.715463  ,\n",
-       "         9.711327  ,  9.713148  ,  9.713642  ,  9.712924  ,  9.715384  ,\n",
-       "         9.715974  ,  9.716772  ,  9.718337  ,  9.714473  ,  9.717203  ,\n",
-       "         9.714393  ,  9.71425   ,  9.713914  ,  9.711695  ,  9.708918  ,\n",
-       "         9.711455  ,  9.70863   ,  9.711487  ,  9.71433   ,  9.710337  ,\n",
-       "         9.711295  ,  9.7138815 ,  9.70997   ,  9.713227  ,  9.717092  ,\n",
-       "         9.713419  ,  9.719773  ,  9.71832   ,  9.716453  ,  9.717108  ,\n",
-       "         9.715989  ,  9.7141695 ,  9.711615  ,  9.71741   ,  9.715814  ,\n",
-       "         9.71428   ,  9.717347  ,  9.712972  ,  9.7162285 ,  9.713419  ,\n",
-       "         9.712238  ,  9.714361  ,  9.716245  ,  9.713563  ,  9.718161  ,\n",
-       "         9.713195  ,  9.715207  ,  9.71591   ,  9.713914  ,  9.7165    ,\n",
-       "         9.7136755 ,  9.717347  ,  9.719837  ,  9.718688  ,  9.713898  ,\n",
-       "         9.717618  ,  9.715941  ,  9.710864  ,  9.71433   ,  9.717777  ,\n",
-       "         9.716262  ,  9.716644  ,  9.719199  ,  9.718911  ,  9.715112  ,\n",
-       "         9.714042  ,  9.710752  ,  9.714153  ,  9.716006  ,  9.715191  ,\n",
-       "         9.716421  ,  9.718177  ,  9.717875  ,  9.718033  ,  9.713227  ,\n",
-       "         9.714537  ,  9.714841  ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
-       "         9.715717  ,  9.711741  ,  9.710465  ,  9.712621  ,  9.71337   ,\n",
-       "         9.715622  ,  9.715989  ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
-       "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-de29e6fa-0f56-4d87-b171-ef3a1091f762' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de29e6fa-0f56-4d87-b171-ef3a1091f762' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5546337-3ff6-4986-a386-f2b1901fbdcd' class='xr-var-data-in' type='checkbox'><label for='data-f5546337-3ff6-4986-a386-f2b1901fbdcd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
-       "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
-       "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
-       "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
-       "       16.466002, 16.476501, 16.464167, 16.464666, 16.462667, 16.460833,\n",
-       "       16.462164, 16.460167, 16.459501, 16.459002, 16.454332, 16.449501,\n",
-       "       16.444332, 16.4325  , 16.422   , 16.412834, 16.400167, 16.397667,\n",
-       "       16.385334, 16.382334, 16.380499, 16.383333, 16.381332, 16.379833,\n",
-       "       16.382   , 16.379168, 16.380499, 16.378834, 16.374832, 16.384499,\n",
-       "       16.374166, 16.373333, 16.377167, 16.376   , 16.38    , 16.370333,\n",
-       "       16.376501, 16.382   , 16.3775  , 16.3815  , 16.378   , 16.3785  ,\n",
-       "       16.378   , 16.383667, 16.374668, 16.3845  , 16.353   , 16.372334,\n",
-       "       16.377668, 16.378168, 16.372334, 16.372665, 16.363167, 16.367167,\n",
-       "       16.372833, 16.363333, 16.355165, 16.367002, 16.368334, 16.372665,\n",
-       "       16.360834, 16.367834, 16.367   , 16.360834, 16.358   , 16.342833,\n",
-       "       16.341167, 16.328001, 16.317   , 16.305332, 16.295   , 16.2915  ,\n",
-       "       16.279333, 16.281166, 16.280834, 16.276167, 16.279333, 16.279333,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
-       "       16.275   , 16.278334, 16.276834, 16.271   , 16.2725  , 16.27    ,\n",
-       "       16.265165, 16.268333, 16.268   , 16.264   , 16.268   , 16.268   ,\n",
-       "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.268   ,\n",
-       "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.263334,\n",
-       "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
-       "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
-       "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
-       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-7246ebc5-63f8-46e8-a0eb-6e66b537fdeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7246ebc5-63f8-46e8-a0eb-6e66b537fdeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b2b71af-ff51-449a-a230-50c42525f9e8' class='xr-var-data-in' type='checkbox'><label for='data-5b2b71af-ff51-449a-a230-50c42525f9e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
-       "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
-       "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
-       "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
-       "       20.25    , 20.25    , 20.163334, 20.      , 20.      , 20.      ,\n",
-       "       19.766666, 19.75    , 19.75    , 19.726667, 19.553333, 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.606667, 19.746666, 19.75    , 19.75    , 19.75    ,\n",
-       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-       "       19.556667, 19.5     , 19.5     , 19.5     , 19.626667, 19.75    ,\n",
-       "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-       "       19.75    , 19.75    , 19.75    , 19.54    , 19.413334, 19.233334,\n",
-       "       19.      , 18.91    , 18.75    , 18.746666, 18.5     , 18.5     ,\n",
-       "       18.5     , 18.5     , 18.366667, 18.25    , 18.25    , 18.25    ,\n",
-       "       18.25    , 18.2     , 18.      , 18.      , 18.      , 18.      ,\n",
-       "       17.873333, 17.75    , 17.75    , 17.75    , 17.863333, 18.      ,\n",
-       "       18.      , 18.17    , 18.25    , 18.44    , 18.513334, 18.75    ,\n",
-       "       18.783333, 19.      , 19.      , 19.196667, 19.25    , 19.25    ,\n",
-       "       19.25    , 19.433332, 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
-       "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
-       "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-cb14a4c6-5017-4bda-ac21-2fcc0f72702e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb14a4c6-5017-4bda-ac21-2fcc0f72702e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae80c9f2-edee-4981-90d7-b281d205f328' class='xr-var-data-in' type='checkbox'><label for='data-ae80c9f2-edee-4981-90d7-b281d205f328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-cc0cf513-bd59-407d-adc4-aec84aade42c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc0cf513-bd59-407d-adc4-aec84aade42c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a0b89f6-b56d-405b-9bc5-d0c028b38012' class='xr-var-data-in' type='checkbox'><label for='data-0a0b89f6-b56d-405b-9bc5-d0c028b38012' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "...\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355693e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-8c6a894f-c99f-4c61-8e63-9b0744f354b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c6a894f-c99f-4c61-8e63-9b0744f354b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbec152b-b3d5-455e-801a-5671c162591a' class='xr-var-data-in' type='checkbox'><label for='data-dbec152b-b3d5-455e-801a-5671c162591a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
-       "         -0.18383324, -0.17606331],\n",
-       "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
-       "         -0.19696543, -0.20011853],\n",
-       "        [ 0.26504937,  0.28428233,  0.31169885, ..., -0.2103943 ,\n",
-       "         -0.21627884, -0.21236075],\n",
-       "        ...,\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan]],\n",
-       "\n",
-       "       [[ 0.02619691,  0.04430203,  0.04002393, ...,  0.05932099,\n",
-       "          0.06400961,  0.07232199],\n",
-       "        [ 0.06181316,  0.07802678,  0.06236525, ...,  0.0768801 ,\n",
-       "          0.08184617,  0.0892335 ],\n",
-       "        [ 0.08793733,  0.10133781,  0.08016948, ...,  0.08136398,\n",
-       "          0.08639657,  0.10118616],\n",
-       "...\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan]],\n",
-       "\n",
-       "       [[-0.00417333, -0.01056667, -0.01045333, ..., -0.02584564,\n",
-       "         -0.02752333, -0.02575667],\n",
-       "        [ 0.01358667,  0.00760333,  0.00634667, ..., -0.01625333,\n",
-       "         -0.01776333, -0.01595   ],\n",
-       "        [ 0.01556187,  0.00811371,  0.00740333, ..., -0.00842   ,\n",
-       "         -0.01147667, -0.01189667],\n",
-       "        ...,\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan],\n",
-       "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-dcef319d-3809-4efc-ac3d-4bdfe1b0f3a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcef319d-3809-4efc-ac3d-4bdfe1b0f3a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d35a990-7c06-46e7-9f16-aa3349287c64' class='xr-var-data-in' type='checkbox'><label for='data-7d35a990-7c06-46e7-9f16-aa3349287c64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
-       "         81.68667 ],\n",
-       "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
-       "         77.528336],\n",
-       "        [72.81167 , 73.391304, 74.26833 , ..., 74.525   , 74.39667 ,\n",
-       "         74.253334],\n",
-       "        ...,\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan]],\n",
-       "\n",
-       "       [[80.706665, 80.93833 , 81.255   , ..., 82.19833 , 82.225   ,\n",
-       "         82.17    ],\n",
-       "        [76.80666 , 76.996666, 77.44833 , ..., 78.38333 , 78.41167 ,\n",
-       "         78.06    ],\n",
-       "        [74.31834 , 74.64667 , 75.903336, ..., 75.16333 , 75.26833 ,\n",
-       "         74.875   ],\n",
-       "...\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan]],\n",
-       "\n",
-       "       [[80.185   , 80.55    , 80.885   , ..., 81.888336, 81.945   ,\n",
-       "         81.85833 ],\n",
-       "        [75.78    , 76.291664, 76.76833 , ..., 77.97667 , 78.03833 ,\n",
-       "         77.87666 ],\n",
-       "        [72.67725 , 73.55666 , 74.44334 , ..., 74.75833 , 74.665   ,\n",
-       "         74.47    ],\n",
-       "        ...,\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan],\n",
-       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-e8e09ea2-5181-492c-9abb-4dae602329d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8e09ea2-5181-492c-9abb-4dae602329d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8efeaaf4-1cc0-461c-90da-afcc0082ce62' class='xr-var-data-in' type='checkbox'><label for='data-8efeaaf4-1cc0-461c-90da-afcc0082ce62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
-       "         92.06333 ],\n",
-       "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
-       "         96.03333 ],\n",
-       "        [97.166664, 96.246666, 95.94    , ..., 96.45333 , 97.206665,\n",
-       "         97.263336],\n",
-       "        ...,\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ]],\n",
-       "\n",
-       "       [[93.333336, 93.61    , 93.31333 , ..., 91.6     , 91.49    ,\n",
-       "         91.14667 ],\n",
-       "        [96.57    , 96.39    , 96.12666 , ..., 96.27    , 96.56333 ,\n",
-       "         96.44334 ],\n",
-       "        [97.37666 , 97.09333 , 96.87666 , ..., 96.17333 , 97.30334 ,\n",
-       "         97.32667 ],\n",
-       "...\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ]],\n",
-       "\n",
-       "       [[92.78333 , 93.223335, 92.63    , ..., 92.22    , 92.34    ,\n",
-       "         92.61    ],\n",
-       "        [96.75    , 96.34333 , 96.34    , ..., 96.53    , 96.69    ,\n",
-       "         96.27333 ],\n",
-       "        [96.346664, 97.05    , 97.24    , ..., 96.66333 , 96.89333 ,\n",
-       "         97.41    ],\n",
-       "        ...,\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ],\n",
-       "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-9b2c757c-c921-4588-8c5b-3a44841f1715' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b2c757c-c921-4588-8c5b-3a44841f1715' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f51a2dc2-78d5-40bf-b90c-b2d939d5d5a2' class='xr-var-data-in' type='checkbox'><label for='data-f51a2dc2-78d5-40bf-b90c-b2d939d5d5a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
-       "          5.81927113e-02,  5.85613623e-02,  5.85512854e-02],\n",
-       "        [ 9.98300374e-01,  9.98323679e-01,  9.98248577e-01, ...,\n",
-       "          9.98254061e-01,  9.98234987e-01,  9.98234689e-01],\n",
-       "        [-1.05408905e-03, -1.34927384e-03, -1.13080605e-03, ...,\n",
-       "         -8.26976204e-04, -8.38353124e-04, -8.28948745e-04]],\n",
-       "\n",
-       "       [[-9.89950538e-01, -9.89953220e-01, -9.89922285e-01, ...,\n",
-       "         -9.91938353e-01, -9.91944909e-01, -9.91939366e-01],\n",
-       "        [ 5.68153895e-02,  5.63202463e-02,  5.76671995e-02, ...,\n",
-       "          5.77317439e-02,  5.80984168e-02,  5.80891557e-02],\n",
-       "        [-1.29125342e-01, -1.29299909e-01, -1.28952131e-01, ...,\n",
-       "         -1.12354711e-01, -1.12130061e-01, -1.12175331e-01]],\n",
-       "\n",
-       "       [[-1.28852651e-01, -1.29014045e-01, -1.28667876e-01, ...,\n",
-       "         -1.12116747e-01, -1.11889169e-01, -1.11934915e-01],\n",
-       "        [ 8.45469162e-03,  8.69723968e-03,  8.63243733e-03, ...,\n",
-       "          7.35414820e-03,  7.39390310e-03,  7.38611678e-03],\n",
-       "        [ 9.91627276e-01,  9.91604209e-01,  9.91649806e-01, ...,\n",
-       "          9.93667483e-01,  9.93692815e-01,  9.93687749e-01]]],\n",
-       "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-b485eef9-a704-4048-8ddb-75f9f1d992a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b485eef9-a704-4048-8ddb-75f9f1d992a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ded8637c-a800-4d74-b9aa-9f557aa69155' class='xr-var-data-in' type='checkbox'><label for='data-ded8637c-a800-4d74-b9aa-9f557aa69155' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
-       "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
-       "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
-       "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
-       "         0.00054653,  0.00055442,  0.00072552,  0.00056834,  0.00065792,\n",
-       "         0.00086152,  0.00080709,  0.00096736,  0.00085591,  0.00094166,\n",
-       "         0.00090368,  0.00095632,  0.00094047,  0.00091472,  0.00092718,\n",
-       "         0.00097144,  0.00090388,  0.00098592,  0.00099217,  0.00104627,\n",
-       "         0.00101094,  0.00108953,  0.00094413,  0.0010326 ,  0.00105636,\n",
-       "         0.00098609,  0.00101084,  0.00101927,  0.00101796,  0.00096841,\n",
-       "         0.00102785,  0.00113951,  0.00098156,  0.00111134,  0.00100472,\n",
-       "         0.00104199,  0.00104198,  0.00100612,  0.00103637,  0.00099132,\n",
-       "         0.00102272,  0.00102712,  0.00100425,  0.0010416 ,  0.00097589,\n",
-       "         0.00090605,  0.00108258,  0.00090169,  0.00096689,  0.00081777,\n",
-       "         0.0009423 ,  0.00087804,  0.00102183,  0.00083111,  0.0009242 ,\n",
-       "         0.00094747,  0.00110261,  0.00097415,  0.00097692,  0.00113317,\n",
-       "         0.00105406,  0.00104935,  0.00102722,  0.00093711,  0.00103575,\n",
-       "         0.00095867,  0.0009583 ,  0.00104538,  0.00100466,  0.00095809,\n",
-       "         0.00101549,  0.00097118,  0.00090704,  0.00094464,  0.00096578,\n",
-       "         0.00105039,  0.00093799,  0.00100518,  0.00088882,  0.00095506,\n",
-       "...\n",
-       "        -0.00263344, -0.00258787, -0.00256183, -0.00256183, -0.00250324,\n",
-       "        -0.00268227, -0.00268227, -0.00259113, -0.00262693, -0.00257485,\n",
-       "        -0.00259113, -0.00252602, -0.00267576, -0.00253904, -0.00256509,\n",
-       "        -0.00242511, -0.00249998, -0.00250975, -0.00252277, -0.00261066,\n",
-       "        -0.00257485, -0.00265298, -0.00264647, -0.00261391, -0.00260089,\n",
-       "        -0.00270181, -0.0027604 , -0.00278318, -0.00288084, -0.00274412,\n",
-       "        -0.00280272, -0.00289386, -0.0030729 , -0.0029492 , -0.0029199 ,\n",
-       "        -0.00302407, -0.00299803, -0.00296222, -0.00288084, -0.00299477,\n",
-       "        -0.00304034, -0.00298175, -0.00296222, -0.00296873, -0.00305337,\n",
-       "        -0.00302081, -0.00299803, -0.00304034, -0.0030729 , -0.0029199 ,\n",
-       "        -0.00295571, -0.00287433, -0.00287433, -0.0028548 , -0.00275714,\n",
-       "        -0.00271157, -0.0027018 , -0.00278644, -0.0026074 , -0.00264972,\n",
-       "        -0.00273761, -0.00259764, -0.00258787, -0.00256834, -0.00263344,\n",
-       "        -0.00255207, -0.00265623, -0.00261391, -0.00255207, -0.00249673,\n",
-       "        -0.00258787, -0.00256183, -0.00253579, -0.00264321, -0.00268553,\n",
-       "        -0.00255858, -0.00264321, -0.00262693, -0.0025423 , -0.00256834,\n",
-       "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
-       "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
-       "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
-       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-ecc277c0-5ffc-479d-8499-8da5fe58c508' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecc277c0-5ffc-479d-8499-8da5fe58c508' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69e77445-8f9a-4232-803d-89f14e29e3ff' class='xr-var-data-in' type='checkbox'><label for='data-69e77445-8f9a-4232-803d-89f14e29e3ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
-       "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
-       "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
-       "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
-       "         0.6253574 ,  0.6254711 ,  0.6251542 ,  0.6249595 ,  0.62512624,\n",
-       "         0.62510735,  0.62479544,  0.6250753 ,  0.624999  ,  0.6248949 ,\n",
-       "         0.6248343 ,  0.6245227 ,  0.6248399 ,  0.624795  ,  0.6250311 ,\n",
-       "         0.62494355,  0.6249766 ,  0.6244582 ,  0.62417775,  0.6244494 ,\n",
-       "         0.6248647 ,  0.6245337 ,  0.62416995,  0.6242157 ,  0.62425923,\n",
-       "         0.6247039 ,  0.6248129 ,  0.6246122 ,  0.6248121 ,  0.6246928 ,\n",
-       "         0.6245991 ,  0.6248212 ,  0.6247573 ,  0.6243741 ,  0.6243043 ,\n",
-       "         0.6244282 ,  0.6243682 ,  0.6240724 ,  0.62418926,  0.6241515 ,\n",
-       "         0.6239765 ,  0.62391806,  0.62415963,  0.62387216,  0.6239287 ,\n",
-       "         0.62390673,  0.6236841 ,  0.62378633,  0.6236643 ,  0.6235926 ,\n",
-       "         0.62364197,  0.6237233 ,  0.62374234,  0.62387735,  0.62402254,\n",
-       "         0.62393117,  0.62393445,  0.62373453,  0.62396324,  0.62340415,\n",
-       "         0.62373024,  0.62379295,  0.62355286,  0.6231889 ,  0.62350035,\n",
-       "         0.6232749 ,  0.6232579 ,  0.6233172 ,  0.6232117 ,  0.62328154,\n",
-       "         0.6234021 ,  0.62359464,  0.6235321 ,  0.62355274,  0.62340564,\n",
-       "         0.6233349 ,  0.6232732 ,  0.62326413,  0.62335676,  0.6233057 ,\n",
-       "...\n",
-       "         0.77982664,  0.7798403 ,  0.77980125,  0.7798833 ,  0.7798343 ,\n",
-       "         0.77974474,  0.7795985 ,  0.77965385,  0.77964175,  0.7797572 ,\n",
-       "         0.7798193 ,  0.77987343,  0.77987754,  0.7798154 ,  0.7798561 ,\n",
-       "         0.77976704,  0.77973217,  0.77971977,  0.77958   ,  0.7794924 ,\n",
-       "         0.77951276,  0.77934176,  0.77977145,  0.77983665,  0.7796758 ,\n",
-       "         0.77951133,  0.77975136,  0.7796223 ,  0.7795445 ,  0.7798783 ,\n",
-       "         0.7796854 ,  0.78009176,  0.77983886,  0.77976817,  0.7798124 ,\n",
-       "         0.77966744,  0.77980477,  0.77957195,  0.7797228 ,  0.7795519 ,\n",
-       "         0.77965647,  0.7795511 ,  0.7795689 ,  0.77951413,  0.77942085,\n",
-       "         0.7791843 ,  0.7793043 ,  0.7793574 ,  0.7790914 ,  0.77922   ,\n",
-       "         0.7788722 ,  0.77907705,  0.7790985 ,  0.778842  ,  0.7789314 ,\n",
-       "         0.77889466,  0.7789852 ,  0.7792381 ,  0.77916646,  0.7788889 ,\n",
-       "         0.77894676,  0.7789039 ,  0.7785506 ,  0.7786492 ,  0.7788344 ,\n",
-       "         0.7786969 ,  0.77884805,  0.7789083 ,  0.77894056,  0.7786727 ,\n",
-       "         0.77858806,  0.7783844 ,  0.7785528 ,  0.7787677 ,  0.77864134,\n",
-       "         0.77870125,  0.7787834 ,  0.7788154 ,  0.7788442 ,  0.7785659 ,\n",
-       "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
-       "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
-       "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
-       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-2a830c4a-30b3-44a0-bf5d-015ab205796c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a830c4a-30b3-44a0-bf5d-015ab205796c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2451ce69-7a5d-4d87-91a9-a73a177b0ae6' class='xr-var-data-in' type='checkbox'><label for='data-2451ce69-7a5d-4d87-91a9-a73a177b0ae6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
-       "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
-       "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
-       "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
-       "       13.       , 12.941335 , 12.800002 , 12.631333 , 12.598    ,\n",
-       "       12.411335 , 12.400001 , 12.230666 , 12.199998 , 12.119332 ,\n",
-       "       12.       , 12.       , 12.       , 11.957999 , 11.800002 ,\n",
-       "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.800002 ,\n",
-       "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.834001 ,\n",
-       "       11.999333 , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.104667 , 12.193999 , 12.199998 , 12.199998 ,\n",
-       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.086667 ,\n",
-       "       12.113999 , 12.192665 , 12.032667 , 12.078666 , 12.03     ,\n",
-       "       12.       , 12.111999 , 12.199998 , 12.199998 , 12.199998 ,\n",
-       "       12.202665 , 12.219333 , 12.274    , 12.367333 , 12.203999 ,\n",
-       "       12.217332 , 12.199998 , 12.199998 , 12.119332 , 11.845334 ,\n",
-       "       11.496667 , 11.219998 , 11.       , 10.952001 , 10.800002 ,\n",
-       "       10.800002 , 10.800002 , 10.800002 , 10.751334 , 10.599999 ,\n",
-       "       10.599999 , 10.599999 , 10.599999 , 10.5546665, 10.400001 ,\n",
-       "       10.400001 , 10.334666 , 10.2      , 10.2      , 10.191999 ,\n",
-       "       10.029333 , 10.       , 10.009334 , 10.198667 , 10.243333 ,\n",
-       "       10.415334 , 10.599999 , 10.772668 , 11.       , 11.186666 ,\n",
-       "       11.398002 , 11.528    , 11.599999 , 11.746667 , 11.800002 ,\n",
-       "       11.876667 , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       , 12.000667 , 12.006    ,\n",
-       "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.001333 , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.024667 , 12.173999 , 12.199998 ,\n",
-       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-       "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
-       "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-2f827c3d-1b05-44f9-af16-7d6e6e5751ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f827c3d-1b05-44f9-af16-7d6e6e5751ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-205c009a-da96-4bd6-b2a8-2b72ee9626d5' class='xr-var-data-in' type='checkbox'><label for='data-205c009a-da96-4bd6-b2a8-2b72ee9626d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
-       "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
-       "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
-       "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
-       "       244.98334, 244.94   , 244.86333, 244.82666, 244.79333, 244.84666,\n",
-       "       244.76666, 244.73334, 244.82666, 244.75   , 244.86333, 244.83   ,\n",
-       "       244.84334, 244.91333, 244.96666, 245.08   , 245.25333, 245.30667,\n",
-       "       245.4    , 245.51   , 245.61333, 245.61   , 245.65666, 245.76666,\n",
-       "       245.73   , 245.79666, 245.83333, 245.85333, 245.81   , 245.85667,\n",
-       "       245.90334, 245.89333, 245.90666, 245.90334, 245.89333, 245.90666,\n",
-       "       245.93   , 245.91333, 245.91667, 245.92334, 245.92334, 245.92   ,\n",
-       "       245.96   , 245.95   , 245.94333, 245.96   , 245.94667, 245.97   ,\n",
-       "       245.95   , 245.93666, 245.93   , 245.95667, 245.94   , 245.95667,\n",
-       "       245.95   , 245.95334, 245.96666, 245.98   , 245.96666, 245.97   ,\n",
-       "       245.97   , 245.98   , 245.97333, 245.97   , 245.98666, 245.97667,\n",
-       "       245.97667, 245.98334, 245.97667, 245.99333, 245.97667, 245.98334,\n",
-       "       245.99667, 245.99667, 245.99   , 245.97333, 245.98334, 245.98666,\n",
-       "       245.97   , 245.99667, 245.98666, 245.98   , 245.85667, 245.44667,\n",
-       "       244.92334, 244.41667, 244.16333, 244.00667, 244.06   , 244.07333,\n",
-       "       243.87334, 243.77333, 243.75   , 243.69   , 243.76334, 243.79666,\n",
-       "       243.55   , 243.5    , 243.37666, 243.20334, 242.92334, 242.87666,\n",
-       "       242.83   , 242.83333, 243.07666, 243.41   , 243.88333, 244.20334,\n",
-       "       244.40334, 244.45334, 244.48666, 244.41   , 244.38   , 244.43333,\n",
-       "       244.6    , 244.72333, 244.90666, 244.9    , 244.97667, 245.03667,\n",
-       "       245.22667, 245.36   , 245.4    , 245.42   , 245.48334, 245.62666,\n",
-       "       245.67   , 245.71333, 245.75667, 245.77   , 245.84   , 245.87   ,\n",
-       "       245.87666, 245.89   , 245.87666, 245.94333, 245.93   , 245.91333,\n",
-       "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
-       "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
-       "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
-       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-ae0eb9cf-4aef-4228-821f-8ce74f6dc8bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae0eb9cf-4aef-4228-821f-8ce74f6dc8bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9483a782-9e95-4403-9163-7f1a77ac2ebd' class='xr-var-data-in' type='checkbox'><label for='data-9483a782-9e95-4403-9163-7f1a77ac2ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
-       "         3.6116719e+00,  3.5757926e+00,  3.5947008e+00,  3.6243417e+00,\n",
-       "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830538e+00,\n",
-       "         3.6165168e+00,  3.5789921e+00,  3.5747981e+00,  3.5690453e+00,\n",
-       "         3.5796013e+00,  3.6261466e+00,  3.6063533e+00,  3.6014795e+00,\n",
-       "         3.6353865e+00,  3.6033041e+00,  3.6023455e+00,  3.5552027e+00,\n",
-       "         3.5689840e+00,  3.5028169e+00,  3.5047083e+00,  3.5002160e+00,\n",
-       "         3.4591196e+00,  3.4518204e+00,  3.4781299e+00,  3.4272485e+00,\n",
-       "         3.4080899e+00,  3.4372404e+00,  3.4341383e+00,  3.3986638e+00,\n",
-       "         3.4168522e+00,  3.4093900e+00,  3.3794670e+00,  3.3934760e+00,\n",
-       "         3.4050257e+00,  3.4207287e+00,  3.3710022e+00,  3.3771679e+00,\n",
-       "         3.3508575e+00,  3.3733418e+00,  3.3524203e+00,  3.3316767e+00,\n",
-       "         3.3258898e+00,  3.3680136e+00,  3.2842207e+00,  3.1945534e+00,\n",
-       "         3.0031645e+00,  2.4369471e+00,  2.1365104e+00,  1.9519800e+00,\n",
-       "         1.7708881e+00,  1.6470156e+00,  1.5729071e+00,  1.4625059e+00,\n",
-       "         1.3881445e+00,  1.3379683e+00,  1.3052688e+00,  1.2468668e+00,\n",
-       "         1.2023062e+00,  1.1269653e+00,  1.1022494e+00,  1.0541168e+00,\n",
-       "         1.0267943e+00,  9.7805512e-01,  9.2956728e-01,  9.2703992e-01,\n",
-       "         9.1599506e-01,  8.9450091e-01,  8.5012424e-01,  8.2220656e-01,\n",
-       "         7.9883534e-01,  7.8205061e-01,  7.3997599e-01,  7.3860037e-01,\n",
-       "...\n",
-       "        -1.9736919e+02, -1.9725951e+02, -1.9730052e+02, -1.9728384e+02,\n",
-       "        -1.9724889e+02, -1.9722919e+02, -1.9715518e+02, -1.9727151e+02,\n",
-       "        -1.9724452e+02, -1.9721884e+02, -1.9717354e+02, -1.9723384e+02,\n",
-       "        -1.9719716e+02, -1.9714218e+02, -1.9723254e+02, -1.9710817e+02,\n",
-       "        -1.9708250e+02, -1.9709784e+02, -1.9708986e+02, -1.9712950e+02,\n",
-       "        -1.9721385e+02, -1.9720052e+02, -1.9717422e+02, -1.9710918e+02,\n",
-       "        -1.9715718e+02, -1.9714487e+02, -1.9715251e+02, -1.9714418e+02,\n",
-       "        -1.9714218e+02, -1.9706715e+02, -1.9705818e+02, -1.9705084e+02,\n",
-       "        -1.9708583e+02, -1.9708820e+02, -1.9714618e+02, -1.9709253e+02,\n",
-       "        -1.9707854e+02, -1.9714384e+02, -1.9717952e+02, -1.9718620e+02,\n",
-       "        -1.9718388e+02, -1.9716652e+02, -1.9712685e+02, -1.9720485e+02,\n",
-       "        -1.9718315e+02, -1.9713019e+02, -1.9714951e+02, -1.9724086e+02,\n",
-       "        -1.9716119e+02, -1.9719583e+02, -1.9724786e+02, -1.9716052e+02,\n",
-       "        -1.9725883e+02, -1.9720285e+02, -1.9717485e+02, -1.9725154e+02,\n",
-       "        -1.9714687e+02, -1.9711821e+02, -1.9714719e+02, -1.9711786e+02,\n",
-       "        -1.9714052e+02, -1.9714351e+02, -1.9715118e+02, -1.9712117e+02,\n",
-       "        -1.9710718e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
-       "        -1.9706255e+02, -1.9714519e+02, -1.9712418e+02, -1.9705786e+02,\n",
-       "        -1.9708685e+02, -1.9711749e+02, -1.9707716e+02, -1.9707919e+02,\n",
-       "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-46b1204c-9611-4b1c-ac05-95b954782894' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46b1204c-9611-4b1c-ac05-95b954782894' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c86a487e-4d9c-46fd-ad8a-56fc4ee29a89' class='xr-var-data-in' type='checkbox'><label for='data-c86a487e-4d9c-46fd-ad8a-56fc4ee29a89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
-       "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
-       "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
-       "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569212 , -1.2552022 ,\n",
-       "        -1.2558354 , -1.2547812 , -1.2564313 , -1.2570257 , -1.2564919 ,\n",
-       "        -1.2552761 , -1.2551885 , -1.254373  , -1.2521615 , -1.253256  ,\n",
-       "        -1.2520183 , -1.2556639 , -1.2544196 , -1.2537049 , -1.2514051 ,\n",
-       "        -1.251719  , -1.2501887 , -1.2550075 , -1.2560523 , -1.2542702 ,\n",
-       "        -1.2513357 , -1.2537422 , -1.25587   , -1.2554086 , -1.2568508 ,\n",
-       "        -1.2513126 , -1.251984  , -1.2514541 , -1.2487588 , -1.249171  ,\n",
-       "        -1.2487395 , -1.2432916 , -1.2308283 , -1.2085198 , -1.1925628 ,\n",
-       "        -1.1850357 , -1.175814  , -1.1718632 , -1.1669031 , -1.1620393 ,\n",
-       "        -1.1585126 , -1.1573663 , -1.1550487 , -1.1537894 , -1.1520277 ,\n",
-       "        -1.1507337 , -1.1474868 , -1.1443372 , -1.1442864 , -1.1430473 ,\n",
-       "        -1.1418384 , -1.141045  , -1.1385593 , -1.1344901 , -1.134764  ,\n",
-       "        -1.1317551 , -1.1333026 , -1.1325271 , -1.1293766 , -1.1324316 ,\n",
-       "        -1.1310244 , -1.1295373 , -1.1287975 , -1.1317044 , -1.1290994 ,\n",
-       "        -1.1286312 , -1.1276112 , -1.1271322 , -1.128308  , -1.1257491 ,\n",
-       "        -1.1227695 , -1.1230273 , -1.119395  , -1.1190095 , -1.1182653 ,\n",
-       "        -1.1186818 , -1.1167871 , -1.1160123 , -1.1153725 , -1.1143075 ,\n",
-       "...\n",
-       "         9.716884  ,  9.718464  ,  9.717347  ,  9.717715  ,  9.714792  ,\n",
-       "         9.714857  ,  9.712732  ,  9.712222  ,  9.713994  ,  9.715383  ,\n",
-       "         9.71674   ,  9.716182  ,  9.717108  ,  9.716772  ,  9.715446  ,\n",
-       "         9.714425  ,  9.7126045 ,  9.713626  ,  9.7121105 ,  9.711023  ,\n",
-       "         9.711408  ,  9.709459  ,  9.712988  ,  9.7141695 ,  9.710418  ,\n",
-       "         9.713371  ,  9.713164  ,  9.711615  ,  9.713355  ,  9.714377  ,\n",
-       "         9.714473  ,  9.719391  ,  9.71805   ,  9.71583   ,  9.716421  ,\n",
-       "         9.71658   ,  9.71583   ,  9.71334   ,  9.7177305 ,  9.716677  ,\n",
-       "         9.71476   ,  9.716166  ,  9.713404  ,  9.715751  ,  9.715623  ,\n",
-       "         9.712237  ,  9.714856  ,  9.7166605 ,  9.713179  ,  9.7175865 ,\n",
-       "         9.710929  ,  9.71484   ,  9.715895  ,  9.712062  ,  9.71591   ,\n",
-       "         9.714346  ,  9.716932  ,  9.718177  ,  9.718816  ,  9.713802  ,\n",
-       "         9.717826  ,  9.715128  ,  9.711727  ,  9.713515  ,  9.718353  ,\n",
-       "         9.716836  ,  9.716278  ,  9.717762  ,  9.718656  ,  9.714761  ,\n",
-       "         9.713004  ,  9.710816  ,  9.71409   ,  9.716276  ,  9.713579  ,\n",
-       "         9.716166  ,  9.718401  ,  9.716804  ,  9.718209  ,  9.71428   ,\n",
-       "         9.714553  ,  9.715957  ,  9.7148075 ,  9.717874  ,  9.716309  ,\n",
-       "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
-       "         9.715256  ,  9.714936  ,  9.7148075 ,  9.711726  ,  9.711886  ,\n",
-       "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-66d06c2c-bd2e-4996-b5b5-ba589e57b5fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66d06c2c-bd2e-4996-b5b5-ba589e57b5fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5ddc8ed-095e-4d98-b4e4-696af069547d' class='xr-var-data-in' type='checkbox'><label for='data-c5ddc8ed-095e-4d98-b4e4-696af069547d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-15c9c44d-d3c5-4a48-8ce4-6d873cffbb20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15c9c44d-d3c5-4a48-8ce4-6d873cffbb20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3efbacfb-7d62-4858-b87c-821787f8223e' class='xr-var-data-in' type='checkbox'><label for='data-3efbacfb-7d62-4858-b87c-821787f8223e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355693e+09, 1.05355686e+09, 1.05355693e+09,\n",
-       "       1.05355699e+09, 1.05355686e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355693e+09,\n",
-       "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
-       "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355693e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "...\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-297b8fbf-740d-4abd-9031-0598d65507a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-297b8fbf-740d-4abd-9031-0598d65507a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a67f119-6cdb-46e7-a66e-d907e680773a' class='xr-var-data-in' type='checkbox'><label for='data-2a67f119-6cdb-46e7-a66e-d907e680773a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
-       "        -0.02035667, -0.01573333],\n",
-       "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
-       "        -0.00658667, -0.00238   ],\n",
-       "       [ 0.02739334,  0.01897667,  0.01496333, ...,  0.00196667,\n",
-       "        -0.00096667,  0.00083946],\n",
-       "       ...,\n",
-       "       [        nan,         nan,         nan, ...,         nan,\n",
-       "                nan,         nan],\n",
-       "       [        nan,         nan,         nan, ...,         nan,\n",
-       "                nan,         nan],\n",
-       "       [        nan,         nan,         nan, ...,         nan,\n",
-       "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-538241e5-a10c-4c59-8268-c21f482db45c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538241e5-a10c-4c59-8268-c21f482db45c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5027d2b2-8a7b-431b-9ba2-4cefabf900e8' class='xr-var-data-in' type='checkbox'><label for='data-5027d2b2-8a7b-431b-9ba2-4cefabf900e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
-       "        81.745   ],\n",
-       "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
-       "        78.045   ],\n",
-       "       [73.58833 , 74.355   , 75.083336, ..., 75.265   , 75.098335,\n",
-       "        74.92976 ],\n",
-       "       ...,\n",
-       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "              nan],\n",
-       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "              nan],\n",
-       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-a65f35cd-777d-4e00-b3a4-2b3b223bfae8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a65f35cd-777d-4e00-b3a4-2b3b223bfae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f69b5dac-a215-4e37-a4cc-a214d0c865c6' class='xr-var-data-in' type='checkbox'><label for='data-f69b5dac-a215-4e37-a4cc-a214d0c865c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
-       "        92.61667 ],\n",
-       "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
-       "        96.57667 ],\n",
-       "       [97.19    , 97.32333 , 97.136665, ..., 96.08667 , 97.16    ,\n",
-       "        96.96667 ],\n",
-       "       ...,\n",
-       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "         0.      ],\n",
-       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "         0.      ],\n",
-       "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-4bec0e51-ca20-4b23-9298-9aa49c02fed7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bec0e51-ca20-4b23-9298-9aa49c02fed7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd70347f-70ee-4b01-9d6c-7d045c455cb2' class='xr-var-data-in' type='checkbox'><label for='data-cd70347f-70ee-4b01-9d6c-7d045c455cb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
-       "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
-       "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
-       "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
-       "        [-1.26286745e-01, -1.26509830e-01, -1.26157105e-01, ...,\n",
-       "         -1.09885700e-01, -1.09676003e-01, -1.09719723e-01]],\n",
-       "\n",
-       "       [[ 9.76216435e-01,  9.76112664e-01,  9.76405323e-01, ...,\n",
-       "          9.76383269e-01,  9.76462007e-01,  9.76460576e-01],\n",
-       "        [-2.14884892e-01, -2.15368673e-01, -2.14055121e-01, ...,\n",
-       "         -2.14541376e-01, -2.14190111e-01, -2.14200497e-01],\n",
-       "        [-2.69518793e-02, -2.67608669e-02, -2.67287735e-02, ...,\n",
-       "         -2.34543420e-02, -2.33496260e-02, -2.33698264e-02]],\n",
-       "\n",
-       "       [[-1.05265796e-03, -1.35056104e-03, -1.13043608e-03, ...,\n",
-       "         -8.24717747e-04, -8.40478169e-04, -8.31306970e-04],\n",
-       "        [-1.29126370e-01, -1.29302278e-01, -1.28952518e-01, ...,\n",
-       "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
-       "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
-       "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
-       "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-bc7b5757-d49e-4310-8739-c8fe662b1c7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc7b5757-d49e-4310-8739-c8fe662b1c7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fa91cc2-2039-4555-a442-bb831c9e93b0' class='xr-var-data-in' type='checkbox'><label for='data-7fa91cc2-2039-4555-a442-bb831c9e93b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
-       "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
-       "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
-       "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
-       "         0.00056599,  0.00061758,  0.00068752,  0.00066373,  0.00073918,\n",
-       "         0.00085721,  0.00084523,  0.0009018 ,  0.00089635,  0.00084324,\n",
-       "         0.00086276,  0.00089614,  0.00096862,  0.00108153,  0.00095481,\n",
-       "         0.00098828,  0.00098117,  0.00097845,  0.00099421,  0.00095727,\n",
-       "         0.00108126,  0.00108415,  0.00096381,  0.00100037,  0.00098756,\n",
-       "         0.00103554,  0.00096841,  0.00107755,  0.00104051,  0.0009601 ,\n",
-       "         0.00106976,  0.0010707 ,  0.00102194,  0.0009954 ,  0.00100513,\n",
-       "         0.0010245 ,  0.00102471,  0.00096594,  0.0010335 ,  0.00105437,\n",
-       "         0.00105971,  0.00095506,  0.00102042,  0.00097918,  0.00088768,\n",
-       "         0.0009018 ,  0.00096684,  0.00101125,  0.00096008,  0.0008592 ,\n",
-       "         0.00082965,  0.00095935,  0.00094485,  0.00081024,  0.00092011,\n",
-       "         0.00098175,  0.00094213,  0.00095046,  0.00099598,  0.00104662,\n",
-       "         0.00101681,  0.0010222 ,  0.00099111,  0.001044  ,  0.00103549,\n",
-       "         0.00097536,  0.00099907,  0.00097684,  0.00104176,  0.00094763,\n",
-       "         0.0009761 ,  0.00097227,  0.00089143,  0.00096118,  0.00097306,\n",
-       "         0.00096506,  0.00094653,  0.00092565,  0.00091383,  0.0009503 ,\n",
-       "...\n",
-       "        -0.00262043, -0.00258136, -0.00261717, -0.00257811, -0.00261066,\n",
-       "        -0.00255532, -0.00266274, -0.00254881, -0.00255858, -0.00259764,\n",
-       "        -0.00258462, -0.00252602, -0.00258787, -0.00256183, -0.00260415,\n",
-       "        -0.00251626, -0.00250975, -0.00243488, -0.00254881, -0.00264321,\n",
-       "        -0.00260089, -0.00263996, -0.0026367 , -0.00271157, -0.00256183,\n",
-       "        -0.00271808, -0.00277993, -0.00284178, -0.00276365, -0.00277016,\n",
-       "        -0.00279946, -0.00295896, -0.00294594, -0.00302732, -0.00302407,\n",
-       "        -0.00301756, -0.00298501, -0.00291339, -0.00296548, -0.00294269,\n",
-       "        -0.00311196, -0.00294594, -0.0030143 , -0.00297198, -0.00296873,\n",
-       "        -0.002985  , -0.0030729 , -0.0030143 , -0.00306638, -0.00288084,\n",
-       "        -0.00289386, -0.00281899, -0.00278644, -0.0028255 , -0.00276365,\n",
-       "        -0.00277993, -0.002666  , -0.00267576, -0.002666  , -0.00268227,\n",
-       "        -0.00268878, -0.00263019, -0.00254881, -0.00262368, -0.00263019,\n",
-       "        -0.00260415, -0.00257811, -0.0026074 , -0.00249673, -0.00254881,\n",
-       "        -0.00258787, -0.00263019, -0.00255532, -0.00269204, -0.00258136,\n",
-       "        -0.00259113, -0.00272133, -0.00258462, -0.00263019, -0.00261066,\n",
-       "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
-       "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
-       "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
-       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-249663e1-6f7d-4320-b41d-dd342f1539e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-249663e1-6f7d-4320-b41d-dd342f1539e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62887a06-1b0e-4cba-a74c-c54451e0a3d8' class='xr-var-data-in' type='checkbox'><label for='data-62887a06-1b0e-4cba-a74c-c54451e0a3d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
-       "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
-       "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
-       "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
-       "         0.6253524 ,  0.6254653 ,  0.62515104,  0.62495625,  0.62512195,\n",
-       "         0.6251015 ,  0.624793  ,  0.6250713 ,  0.6249948 ,  0.62489176,\n",
-       "         0.6248301 ,  0.62451917,  0.6248372 ,  0.62479085,  0.62502736,\n",
-       "         0.6249378 ,  0.62497205,  0.62445515,  0.62417245,  0.6244453 ,\n",
-       "         0.6248608 ,  0.62453014,  0.62416404,  0.6242139 ,  0.62425303,\n",
-       "         0.62470126,  0.6248098 ,  0.62460905,  0.62480783,  0.6246901 ,\n",
-       "         0.6245936 ,  0.6248162 ,  0.624754  ,  0.62437105,  0.62430066,\n",
-       "         0.6244233 ,  0.6243633 ,  0.62407166,  0.6241861 ,  0.6241456 ,\n",
-       "         0.6239719 ,  0.62391376,  0.62415487,  0.6238682 ,  0.6239241 ,\n",
-       "         0.62390107,  0.6236789 ,  0.6237806 ,  0.6236614 ,  0.62358916,\n",
-       "         0.6236376 ,  0.62371755,  0.6237382 ,  0.6238726 ,  0.6240171 ,\n",
-       "         0.6239264 ,  0.623931  ,  0.6237308 ,  0.62395936,  0.6234018 ,\n",
-       "         0.6237265 ,  0.6237913 ,  0.6235492 ,  0.62318647,  0.62349266,\n",
-       "         0.62327045,  0.6232548 ,  0.6233126 ,  0.6232084 ,  0.6232786 ,\n",
-       "         0.62339824,  0.62359285,  0.6235284 ,  0.6235471 ,  0.6234016 ,\n",
-       "         0.6233313 ,  0.6232729 ,  0.6232614 ,  0.62335205,  0.6232998 ,\n",
-       "...\n",
-       "         0.7798304 ,  0.77984285,  0.7798039 ,  0.7798881 ,  0.77983624,\n",
-       "         0.779747  ,  0.7796003 ,  0.7796562 ,  0.77964693,  0.77976   ,\n",
-       "         0.77982175,  0.77987325,  0.7798803 ,  0.77981853,  0.7798599 ,\n",
-       "         0.77976817,  0.7797355 ,  0.7797223 ,  0.77958274,  0.7794968 ,\n",
-       "         0.77951866,  0.7793451 ,  0.77977306,  0.7798404 ,  0.7796792 ,\n",
-       "         0.77951556,  0.7797541 ,  0.7796244 ,  0.77954704,  0.779882  ,\n",
-       "         0.7796897 ,  0.78009367,  0.77984214,  0.77977324,  0.77981466,\n",
-       "         0.77967215,  0.77980614,  0.7795769 ,  0.77972573,  0.77955645,\n",
-       "         0.7796588 ,  0.77955323,  0.7795721 ,  0.7795167 ,  0.7794243 ,\n",
-       "         0.77918714,  0.77930677,  0.7793621 ,  0.77909505,  0.7792217 ,\n",
-       "         0.7788761 ,  0.7790808 ,  0.7791028 ,  0.7788446 ,  0.7789332 ,\n",
-       "         0.7788981 ,  0.7789904 ,  0.779241  ,  0.7791693 ,  0.77889454,\n",
-       "         0.7789502 ,  0.77890694,  0.7785553 ,  0.77865255,  0.7788394 ,\n",
-       "         0.7787025 ,  0.7788493 ,  0.77891165,  0.7789452 ,  0.77867603,\n",
-       "         0.7785905 ,  0.7783878 ,  0.77855736,  0.778772  ,  0.7786441 ,\n",
-       "         0.77870494,  0.77878624,  0.77881914,  0.77884936,  0.77857053,\n",
-       "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
-       "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
-       "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
-       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-a7e823ec-24f5-4377-8a95-1a95da2b173e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7e823ec-24f5-4377-8a95-1a95da2b173e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92536e33-550f-4745-bbf1-ee46c2c42b1b' class='xr-var-data-in' type='checkbox'><label for='data-92536e33-550f-4745-bbf1-ee46c2c42b1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-611825d7-5271-4d27-a72d-ff4b5e390601' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-611825d7-5271-4d27-a72d-ff4b5e390601' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b3bd447-85f3-4be3-84d1-3031537131a9' class='xr-var-data-in' type='checkbox'><label for='data-6b3bd447-85f3-4be3-84d1-3031537131a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4448bbd9-b593-40b2-b58c-072b98492615' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4448bbd9-b593-40b2-b58c-072b98492615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673aba38-c31c-4c3c-9918-8990d37228a2' class='xr-var-data-in' type='checkbox'><label for='data-673aba38-c31c-4c3c-9918-8990d37228a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ff482eee-9029-43c4-93f5-66e8228b90cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff482eee-9029-43c4-93f5-66e8228b90cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31618f71-8540-44d9-85ff-e6866de2fed7' class='xr-var-data-in' type='checkbox'><label for='data-31618f71-8540-44d9-85ff-e6866de2fed7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-b3c849c7-37f8-4509-bd76-c64ecac873aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3c849c7-37f8-4509-bd76-c64ecac873aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3a64d6c-df81-491b-a306-b02af38afc75' class='xr-var-data-in' type='checkbox'><label for='data-d3a64d6c-df81-491b-a306-b02af38afc75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
-       "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
-       "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
-       "       0.12      , 0.12333333, 0.12      , 0.11      , 0.11      ,\n",
-       "       0.11666667, 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11333334,\n",
-       "       0.12      , 0.11666667, 0.11666667, 0.11666667, 0.11333334,\n",
-       "       0.12      , 0.11666667, 0.11      , 0.12333333, 0.13333334,\n",
-       "       0.13333334, 0.13      , 0.13333334, 0.12666667, 0.13333334,\n",
-       "       0.13      , 0.13      , 0.15333334, 0.13333334, 0.15333334,\n",
-       "       0.14333333, 0.13666667, 0.11666667, 0.13666667, 0.13333334,\n",
-       "       0.13666667, 0.14666666, 0.14      , 0.15666667, 0.13333334,\n",
-       "       0.13333334, 0.15      , 0.15      , 0.12666667, 0.13666667,\n",
-       "       0.15      , 0.13      , 0.13666667, 0.13      , 0.13666667,\n",
-       "       0.13666667, 0.14333333, 0.13666667, 0.12666667, 0.13666667,\n",
-       "       0.12333333, 0.12333333, 0.13333334, 0.12      , 0.11666667,\n",
-       "       0.11      , 0.11      , 0.11666667, 0.12333333, 0.11      ,\n",
-       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
-       "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
-       "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
-       "       0.11      , 0.20333333, 0.22666667, 0.22      , 0.22      ,\n",
-       "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
-       "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
-       "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
-       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-b8a3d627-053f-4298-ac79-4a0c3c3d1f55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8a3d627-053f-4298-ac79-4a0c3c3d1f55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25036bcc-c32c-45ef-8197-8c0061ffc31e' class='xr-var-data-in' type='checkbox'><label for='data-25036bcc-c32c-45ef-8197-8c0061ffc31e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
-       "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
-       "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
-       "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
-       "       3.3772287, 3.3739138, 3.3298807, 3.368963 , 3.357279 , 3.3420138,\n",
-       "       3.3332636, 3.2887158, 3.3332634, 3.3267972, 3.3609293, 3.34788  ,\n",
-       "       3.3524635, 3.2797818, 3.2383478, 3.2774158, 3.3357968, 3.2894654,\n",
-       "       3.237099 , 3.2444148, 3.250231 , 3.3133483, 3.3285973, 3.3003979,\n",
-       "       3.3281136, 3.3106983, 3.2960656, 3.3239977, 3.3058155, 3.231132 ,\n",
-       "       3.2188826, 3.2362165, 3.2269833, 3.1857452, 3.2025456, 3.1971133,\n",
-       "       3.1716278, 3.1624265, 3.196963 , 3.1550453, 3.162944 , 3.158162 ,\n",
-       "       3.1250577, 3.1385927, 3.1210082, 3.1101758, 3.116926 , 3.1283762,\n",
-       "       3.1307604, 3.149876 , 3.1709106, 3.1579425, 3.157861 , 3.1293783,\n",
-       "       3.1623626, 3.0823452, 3.1290247, 3.1371257, 3.103561 , 3.0512455,\n",
-       "       3.0958426, 3.0634787, 3.061212 , 3.0691292, 3.0543785, 3.0647104,\n",
-       "       3.0809944, 3.1082118, 3.099077 , 3.1025605, 3.0808105, 3.070144 ,\n",
-       "       3.061945 , 3.0596778, 3.0728438, 3.0654464, 3.082978 , 3.0888774,\n",
-       "       3.090909 , 3.1166098, 3.1326916, 3.1294093, 3.1606429, 3.0821111,\n",
-       "       3.0704782, 3.099461 , 3.1288106, 3.0858114, 3.1094916, 3.1244771,\n",
-       "       3.0631604, 3.098195 , 3.0228472, 3.0709112, 3.0849445, 3.0772102,\n",
-       "       3.10411  , 3.0789108, 3.122175 , 3.0939767, 3.126108 , 3.1068432,\n",
-       "       3.1269426, 3.124676 , 3.133493 , 3.1521947, 3.1957629, 3.174427 ,\n",
-       "       3.1647441, 3.2137322, 3.1900635, 3.2544334, 3.2174487, 3.2122307,\n",
-       "       3.2605999, 3.244882 , 3.2509172, 3.234432 , 3.1874464, 3.200428 ,\n",
-       "       3.251467 , 3.2418153, 3.24985  , 3.3141315, 3.2959988, 3.2620163,\n",
-       "       3.2882996, 3.2601004, 3.2490656, 3.242116 , 3.2917488, 3.306215 ,\n",
-       "       3.3455298, 3.3139143, 3.274265 , 3.2986312, 3.2870982, 3.271833 ,\n",
-       "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
-       "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
-       "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
-       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-f62001ed-6467-4693-967f-e4902c176c26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f62001ed-6467-4693-967f-e4902c176c26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5929ec33-17f1-4434-97f7-63721111aae1' class='xr-var-data-in' type='checkbox'><label for='data-5929ec33-17f1-4434-97f7-63721111aae1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
-       "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
-       "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
-       "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
-       "       -0.04223333, -0.0388    , -0.05338333, -0.0568    , -0.0611    ,\n",
-       "       -0.0627    , -0.07021666, -0.05368333, -0.0487    , -0.0493    ,\n",
-       "       -0.05311666, -0.06443334, -0.04586667, -0.04441666, -0.04498333,\n",
-       "       -0.03575   , -0.03521667, -0.07056666, -0.07609999, -0.0662    ,\n",
-       "       -0.04191666, -0.06681666, -0.06818333, -0.07636666, -0.07111666,\n",
-       "       -0.05511666, -0.0493    , -0.05571667, -0.04891667, -0.04571667,\n",
-       "       -0.04198333, -0.00336667,  0.08048334,  0.25323334,  0.22161667,\n",
-       "        0.19196668,  0.15959999,  0.11676668,  0.09488333,  0.07456666,\n",
-       "        0.05981667,  0.06043334,  0.06175001,  0.05643333,  0.04858334,\n",
-       "        0.06248334,  0.06495   ,  0.07498333,  0.06741667,  0.07038333,\n",
-       "        0.06546666,  0.06541666,  0.06608333,  0.07325   ,  0.0566    ,\n",
-       "        0.054     ,  0.061     ,  0.0511    ,  0.05655   ,  0.02896667,\n",
-       "        0.02978333,  0.04755   ,  0.01526667,  0.00998333,  0.0108    ,\n",
-       "        0.00458333,  0.00831667,  0.00378333, -0.00401667, -0.00796667,\n",
-       "        0.00555   ,  0.01133333,  0.00541667, -0.0047    , -0.0019    ,\n",
-       "       -0.00158333, -0.01193333, -0.00146667, -0.00791667, -0.00841667,\n",
-       "       -0.00898333, -0.00903333, -0.002     ,  0.00205   ,  0.00393333,\n",
-       "       -0.00233333,  0.01098333, -0.01495   , -0.01253333,  0.0059    ,\n",
-       "        0.01675   , -0.0048    ,  0.00353333,  0.00155   , -0.01018333,\n",
-       "        0.00053333, -0.0111    , -0.01913333, -0.02155   , -0.02396666,\n",
-       "       -0.01793333, -0.02523333, -0.0194    , -0.02291666, -0.02203333,\n",
-       "       -0.0282    , -0.02571667, -0.03851666, -0.0208    , -0.03573333,\n",
-       "       -0.02388333, -0.03908334, -0.04381667, -0.031     , -0.04036666,\n",
-       "       -0.02826666, -0.04583333, -0.0394    , -0.03658333, -0.04336667,\n",
-       "       -0.04073333, -0.05656667, -0.0553    , -0.05688334, -0.04293333,\n",
-       "       -0.05556666, -0.05011667, -0.02433333, -0.03963333, -0.04716667,\n",
-       "       -0.05826667, -0.05943333, -0.06553333, -0.04911667, -0.04304999,\n",
-       "       -0.023     , -0.03935   , -0.03393333, -0.04798333, -0.05141667,\n",
-       "       -0.04823333, -0.05695   , -0.05431667, -0.07600001, -0.0419    ,\n",
-       "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
-       "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
-       "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
-       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-0629cd39-673d-4d21-998a-2ab00fc8783c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0629cd39-673d-4d21-998a-2ab00fc8783c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94dd308d-41fb-47db-887f-d873e67e2fa4' class='xr-var-data-in' type='checkbox'><label for='data-94dd308d-41fb-47db-887f-d873e67e2fa4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
-       "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
-       "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
-       "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
-       "       -7.3838835, -7.3748665, -7.3916   , -7.391783 , -7.3853164,\n",
-       "       -7.377949 , -7.3945003, -7.3738666, -7.373867 , -7.369084 ,\n",
-       "       -7.372767 , -7.3854327, -7.3678336, -7.3722672, -7.3625836,\n",
-       "       -7.3666334, -7.360083 , -7.3809   , -7.3875995, -7.3742666,\n",
-       "       -7.3516665, -7.369966 , -7.387017 , -7.386867 , -7.379284 ,\n",
-       "       -7.361167 , -7.3493667, -7.3615665, -7.344417 , -7.350366 ,\n",
-       "       -7.3399496, -7.300467 , -7.236433 , -7.0768504, -6.997516 ,\n",
-       "       -6.949867 , -6.899017 , -6.8814178, -6.8526497, -6.8263836,\n",
-       "       -6.813383 , -6.8076496, -6.78375  , -6.781251 , -6.7671165,\n",
-       "       -6.7577667, -6.7516494, -6.728033 , -6.72715  , -6.716767 ,\n",
-       "       -6.708234 , -6.69495  , -6.6866503, -6.6791   , -6.6603007,\n",
-       "       -6.659384 , -6.6542172, -6.659967 , -6.6461835, -6.667401 ,\n",
-       "       -6.6473837, -6.6366506, -6.6365337, -6.649917 , -6.6360173,\n",
-       "       -6.638784 , -6.6400666, -6.62885  , -6.628683 , -6.617567 ,\n",
-       "       -6.6096334, -6.59625  , -6.589217 , -6.5807333, -6.5850334,\n",
-       "       -6.5764165, -6.5684667, -6.5721836, -6.55585  , -6.5561   ,\n",
-       "       -6.5420327, -6.5459166, -6.5430665, -6.5388503, -6.5341506,\n",
-       "       -6.5321503, -6.52225  , -6.539833 , -6.5372   , -6.528584 ,\n",
-       "       -6.5262337, -6.5375338, -6.5275497, -6.51875  , -6.5324664,\n",
-       "       -6.525267 , -6.548233 , -6.5326   , -6.5178337, -6.5193667,\n",
-       "       -6.505567 , -6.5125165, -6.4989333, -6.508083 , -6.49675  ,\n",
-       "       -6.50315  , -6.4925   , -6.485383 , -6.492067 , -6.4811997,\n",
-       "       -6.4708   , -6.4739504, -6.472566 , -6.4622664, -6.4698668,\n",
-       "       -6.4504333, -6.4621997, -6.4667   , -6.45215  , -6.4554167,\n",
-       "       -6.454716 , -6.461316 , -6.4738665, -6.473217 , -6.458534 ,\n",
-       "       -6.46535  , -6.4565167, -6.4414663, -6.4526324, -6.4590497,\n",
-       "       -6.4487834, -6.4628167, -6.46505  , -6.4660163, -6.4543834,\n",
-       "       -6.4556837, -6.4339333, -6.443283 , -6.4565334, -6.4484835,\n",
-       "       -6.4508667, -6.4604836, -6.4581666, -6.4554834, -6.4470496,\n",
-       "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
-       "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
-       "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
-       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-f29e11ee-40ef-48ea-8152-093e958ca80e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f29e11ee-40ef-48ea-8152-093e958ca80e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43a2aeb-935a-406f-843a-629a2e3b816f' class='xr-var-data-in' type='checkbox'><label for='data-a43a2aeb-935a-406f-843a-629a2e3b816f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
-       "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
-       "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
-       "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
-       "       1023.23627, 1023.24646, 1023.2652 , 1023.2814 , 1023.2947 ,\n",
-       "       1023.3131 , 1023.32043, 1023.33435, 1023.3452 , 1023.3554 ,\n",
-       "       1023.3606 , 1023.366  , 1023.37103, 1023.37616, 1023.38043,\n",
-       "       1023.38403, 1023.3869 , 1023.3915 , 1023.38855, 1023.3802 ,\n",
-       "       1023.3759 , 1023.3691 , 1023.3694 , 1023.3698 , 1023.3653 ,\n",
-       "       1023.3579 , 1023.3548 , 1023.35455, 1023.3548 , 1023.35455,\n",
-       "       1023.3522 , 1023.3529 , 1023.3504 , 1023.3525 , 1023.3523 ,\n",
-       "       1023.3569 , 1023.35583, 1023.35565, 1023.35364, 1023.35455,\n",
-       "       1023.35675, 1023.3567 , 1023.35565, 1023.35364, 1023.35144,\n",
-       "       1023.3499 , 1023.3452 , 1023.347  , 1023.3427 , 1023.3374 ,\n",
-       "       1023.3326 , 1023.32874, 1023.3249 , 1023.3244 , 1023.3244 ,\n",
-       "       1023.3202 , 1023.3271 , 1023.32477, 1023.3281 , 1023.3215 ,\n",
-       "       1023.3281 , 1023.3284 , 1023.3283 , 1023.3299 , 1023.33887,\n",
-       "       1023.3277 , 1023.3379 , 1023.343  , 1023.33966, 1023.35315,\n",
-       "       1023.35333, 1023.34064, 1023.33875, 1023.33   , 1023.3218 ,\n",
-       "       1023.32404, 1023.32294, 1023.30853, 1023.3122 , 1023.3125 ,\n",
-       "       1023.3147 , 1023.3218 , 1023.32446, 1023.3674 , 1023.42395,\n",
-       "       1023.4842 , 1023.5248 , 1023.5321 , 1023.545  , 1023.555  ,\n",
-       "       1023.5453 , 1023.53784, 1023.5425 , 1023.5531 , 1023.56085,\n",
-       "       1023.5671 , 1023.5697 , 1023.5727 , 1023.5777 , 1023.5851 ,\n",
-       "       1023.598  , 1023.61127, 1023.61774, 1023.6253 , 1023.63873,\n",
-       "       1023.6415 , 1023.64105, 1023.6321 , 1023.6085 , 1023.58875,\n",
-       "       1023.55664, 1023.53424, 1023.4919 , 1023.4661 , 1023.4329 ,\n",
-       "       1023.4105 , 1023.3956 , 1023.38354, 1023.3727 , 1023.36206,\n",
-       "       1023.3528 , 1023.34467, 1023.34357, 1023.345  , 1023.34937,\n",
-       "       1023.34894, 1023.3448 , 1023.3418 , 1023.3417 , 1023.3436 ,\n",
-       "       1023.3458 , 1023.3482 , 1023.3505 , 1023.34937, 1023.348  ,\n",
-       "       1023.34607, 1023.3471 , 1023.3476 , 1023.3501 , 1023.3529 ,\n",
-       "       1023.35187, 1023.34894, 1023.3476 , 1023.3455 , 1023.3432 ,\n",
-       "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
-       "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
-       "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
-       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-a229de0a-42e4-4718-8da1-7173c1238db9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a229de0a-42e4-4718-8da1-7173c1238db9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27910dde-2db5-4d77-818f-4dad1e0be671' class='xr-var-data-in' type='checkbox'><label for='data-27910dde-2db5-4d77-818f-4dad1e0be671' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
-       "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
-       "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
-       "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
-       "        9.90408  ,  9.8704815,  9.843054 ,  9.8099   ,  9.782674 ,\n",
-       "        9.751141 ,  9.722181 ,  9.688391 ,  9.658139 ,  9.624396 ,\n",
-       "        9.591585 ,  9.559362 ,  9.5206785,  9.487036 ,  9.4516325,\n",
-       "        9.418625 ,  9.378983 ,  9.347703 ,  9.310125 ,  9.274782 ,\n",
-       "        9.240932 ,  9.203833 ,  9.168937 ,  9.127398 ,  9.091378 ,\n",
-       "        9.048801 ,  9.012082 ,  8.96804  ,  8.932783 ,  8.890241 ,\n",
-       "        8.854867 ,  8.815892 ,  8.781367 ,  8.746559 ,  8.714514 ,\n",
-       "        8.678216 ,  8.641088 ,  8.608247 ,  8.566862 ,  8.532115 ,\n",
-       "        8.495453 ,  8.461118 ,  8.42251  ,  8.39378  ,  8.36608  ,\n",
-       "        8.334696 ,  8.308269 ,  8.283072 ,  8.254289 ,  8.228873 ,\n",
-       "        8.203963 ,  8.179552 ,  8.162701 ,  8.144332 ,  8.124536 ,\n",
-       "        8.104092 ,  8.085614 ,  8.068075 ,  8.053603 ,  8.043172 ,\n",
-       "        8.025586 ,  8.014922 ,  8.00194  ,  7.9942083,  7.985075 ,\n",
-       "        7.9840665,  7.978806 ,  7.97339  ,  7.9731627,  7.971814 ,\n",
-       "        7.972329 ,  7.9674144,  7.9723177,  7.9744887,  7.9855638,\n",
-       "        7.991272 ,  7.9956956,  8.006041 ,  8.023605 ,  8.038973 ,\n",
-       "        8.049008 ,  8.066569 ,  8.078107 ,  8.090951 ,  8.110414 ,\n",
-       "        8.1288595,  8.1531725,  8.172004 ,  8.192166 ,  8.219532 ,\n",
-       "        8.241356 ,  8.265544 ,  8.288776 ,  8.314842 ,  8.338862 ,\n",
-       "        8.363347 ,  8.388729 ,  8.418659 ,  8.4457035,  8.479128 ,\n",
-       "        8.511397 ,  8.542225 ,  8.57435  ,  8.609074 ,  8.643846 ,\n",
-       "        8.674181 ,  8.707741 ,  8.740917 ,  8.776131 ,  8.809834 ,\n",
-       "        8.847663 ,  8.883326 ,  8.921983 ,  8.956591 ,  8.994466 ,\n",
-       "        9.032357 ,  9.072943 ,  9.107945 ,  9.147928 ,  9.18505  ,\n",
-       "        9.218539 ,  9.25671  ,  9.293107 ,  9.324933 ,  9.361722 ,\n",
-       "        9.397845 ,  9.436231 ,  9.464766 ,  9.502145 ,  9.534171 ,\n",
-       "        9.566268 ,  9.601108 ,  9.627889 ,  9.660232 ,  9.6932535,\n",
-       "        9.72142  ,  9.752015 ,  9.780852 ,  9.808266 ,  9.838272 ,\n",
-       "        9.864178 ,  9.885547 ,  9.914127 ,  9.934637 ,  9.957427 ,\n",
-       "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
-       "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
-       "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
-       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-7cc0e12c-ac1d-465f-b919-ff4396f1f4fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cc0e12c-ac1d-465f-b919-ff4396f1f4fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c229b4ba-1f27-4846-9eb7-379c42e5b345' class='xr-var-data-in' type='checkbox'><label for='data-c229b4ba-1f27-4846-9eb7-379c42e5b345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
-       "        0.04634431],\n",
-       "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
-       "        0.03873245],\n",
-       "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
-       "        0.04237254],\n",
-       "       ...,\n",
-       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-       "               nan],\n",
-       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-       "               nan],\n",
-       "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-       "               nan]], shape=(28, 183), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3ce677c8-4493-441f-8813-1154a1999004' class='xr-section-summary-in' type='checkbox'  ><label for='section-3ce677c8-4493-441f-8813-1154a1999004' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 2.3: Apply an Acoustic Signal Correlation Filter\n",
+        "\n",
+        "After removing data from bins at or above the water surface, we typically apply a filter based on acoustic signal correlation to the ADCP data. This helps to eliminate erroneous velocity data points, which can be caused by factors such as bubbles, kelp, fish, etc., moving through one or multiple beams.\n",
+        "\n",
+        "You can quickly inspect the data to determine an appropriate correlation value by using the built-in plotting feature of xarray. In the following example, we use xarray's slicing capabilities to display data from beam 1 within a range of 0 to 10 m from the ADCP.\n",
+        "\n",
+        "It's important to note that not all ADCPs provide acoustic signal correlation data, which serves as a quantitative measure of signal quality. Older ADCPs may not offer this feature, in which case you can skip this step when using such instruments."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1200x800 with 8 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
       ],
-      "text/plain": [
-       "<xarray.Dataset> Size: 379kB\n",
-       "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-       "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
-       "Coordinates:\n",
-       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
-       "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
-       "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
-       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
-       "  * beam            (beam) int32 16B 1 2 3 4\n",
-       "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
-       "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
-       "  * q               (q) <U1 16B 'w' 'x' 'y' 'z'\n",
-       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
-       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
-       "Data variables: (12/38)\n",
-       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
-       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
-       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
-       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
-       "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
-       "    ...              ...\n",
-       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
-       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
-       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
-       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
-       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
-       "Attributes: (12/41)\n",
-       "    fs:                        1\n",
-       "    n_bin:                     300\n",
-       "    n_fft:                     300\n",
-       "    description:               Binned averages calculated from ensembles of s...\n",
-       "    filehead_config:           {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"...\n",
-       "    inst_model:                Signature1000\n",
-       "    ...                        ...\n",
-       "    has_imu:                   1\n",
-       "    beam_angle:                25\n",
-       "    range_offset:              0.6\n",
-       "    declination:               15.8\n",
-       "    declination_in_orientmat:  1\n",
-       "    principal_heading:         11.1898"
+      "source": [
+        "%matplotlib inline\n",
+        "fig, axes = plt.subplots(2, 2, figsize=(12, 8), sharex=True, sharey=True)\n",
+        "\n",
+        "for i, ax in enumerate(axes.ravel()):\n",
+        "    ds[\"corr\"].isel(beam=i).sel(range=slice(0, 10)).plot(ax=ax)\n",
+        "    ax.set_title(f\"Beam {int(ds['beam'].isel(beam=i).values)}\")"
       ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ds_avg"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 800x1200 with 4 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "It's beneficial to also review data from the other beams. A significant portion of this data is of high quality. To avoid discarding valuable data with lower correlations, which could be due to natural variations, we can use the `correlation_filter`. This function assigns a value of NaN (not a number) to velocity values corresponding to correlations below 50%.\n",
+        "\n",
+        "However, it's important to note that the correlation threshold is dependent on the specifics of the deployment environment and the instrument used. It's not unusual to set a threshold as low as 30%, or even to forgo the use of this function entirely."
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "vel = ds_avg[\"vel\"]\n",
-    "\n",
-    "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
-    "labels = vel.coords[vel_dim].values\n",
-    "\n",
-    "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 3 * len(labels)), sharex=True)\n",
-    "\n",
-    "if len(labels) == 1:\n",
-    "    axes = [axes]\n",
-    "\n",
-    "for ax_i, label in zip(axes, labels):\n",
-    "    values = vel.sel({vel_dim: label}).values.ravel()\n",
-    "    values = values[np.isfinite(values)]\n",
-    "\n",
-    "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
-    "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
-    "    ax_i.set_ylabel(\"Count\")\n",
-    "\n",
-    "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1500x400 with 6 Axes>"
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "ds = api.clean.correlation_filter(ds, thresh=50)"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
-    "\n",
-    "for i, ax in enumerate(axes):\n",
-    "    ds_avg[\"vel\"][i].plot(ax=ax)\n",
-    "    ax.set_title(ds_avg[\"vel\"].coords[\"dir\"].values[i])\n",
-    "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
-    "\n",
-    "plt.tight_layout()"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 4. Calculate Speed and Direction\n",
-    "\n",
-    "Two additional variables that might be of interest, which are not automatically provided, are the magnitude of the horizontal velocity (referred to as `U_mag` or speed) and its direction (`U_dir`). These can be accessed via \"shortcut\" functions through the keyword `velds`, as demonstrated in the subsequent code block.\n",
-    "\n",
-    "For a comprehensive list of these \"shortcut\" functions, you can refer to the [DOLfYN documentation](https://dolfyn.readthedocs.io/en/latest/apidoc/dolfyn.shortcuts.html)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "ds_avg[\"U_mag\"] = ds_avg.velds.U_mag\n",
-    "ds_avg[\"U_dir\"] = ds_avg.velds.U_dir"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Plotting"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Plotting can be accomplished through the user's preferred package. Matplotlib is shown here for simplicity, and flow speed and direction are plotted below with a blue line delineating the water surface level."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x249c4fdac30>"
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1500x400 with 6 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+        "\n",
+        "for i, ax in enumerate(axes):\n",
+        "    ds[\"vel\"][i].plot(ax=ax, vmin=-1.5, vmax=1.5, cmap=\"RdBu_r\")\n",
+        "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+        "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+        "\n",
+        "plt.tight_layout()"
       ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x600 with 2 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 2.4 Rotate Data Coordinate System\n",
+        "\n",
+        "After cleaning the data, the next step is to rotate the velocity data into accurate East, North, Up (ENU) coordinates.\n",
+        "\n",
+        "ADCPs utilize an internal compass or magnetometer to determine magnetic ENU directions. You can use the set_declination function to adjust the velocity data according to the magnetic declination specific to your geographical coordinates. This declination can be looked up online for specific coordinates.\n",
+        "\n",
+        "Instruments save vector data in the coordinate system defined in the deployment configuration file. To make this data meaningful, it must be transformed through various coordinate systems (\"beam\"<->\"inst\"<->\"earth\"<->\"principal\"). This transformation is accomplished using the `rotate2` function. If the \"earth\" (ENU) coordinate system is specified, DOLfYN will automatically rotate the dataset through the required coordinate systems to reach the \"earth\" coordinates. Setting `inplace` to true will modify the input dataset directly, meaning it will not create a new dataset.\n",
+        "\n",
+        "In this case, since the ADCP data is already in the \"earth\" coordinate system, the `rotate2` function will return the input dataset without modifications. The `set_declination` function will work no matter the coordinate system."
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "%matplotlib inline\n",
-    "from matplotlib import pyplot as plt\n",
-    "import matplotlib.dates as dt\n",
-    "\n",
-    "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
-    "# Plot flow speed\n",
-    "t = dolfyn.time.dt642date(ds_avg[\"time\"])\n",
-    "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_mag\"], cmap=\"Blues\", shading=\"nearest\")\n",
-    "# Plot the water surface\n",
-    "ax.plot(t, ds_avg[\"depth\"])\n",
-    "\n",
-    "# Set up time on x-axis\n",
-    "ax.set_xlabel(\"Time\")\n",
-    "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
-    "ax.lines[-1].set_label(\"Water surface\")\n",
-    "ax.legend(loc=\"upper right\")\n",
-    "ax.set_ylabel(\"Altitude [m]\")\n",
-    "ax.set_ylim([0, 12])\n",
-    "plt.colorbar(label=\"Speed [m/s]\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
+    },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x600 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Data is already in the earth coordinate system\n"
+          ]
+        }
+      ],
+      "source": [
+        "dolfyn.set_declination(ds, 15.8, inplace=True)  # 15.8 deg East\n",
+        "dolfyn.rotate2(ds, \"earth\", inplace=True)"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ax = plt.figure(figsize=(10, 6)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
-    "# Plot flow direction\n",
-    "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_dir\"], cmap=\"twilight\", shading=\"nearest\")\n",
-    "# Plot the water surface\n",
-    "ax.plot(t, ds_avg[\"depth\"])\n",
-    "\n",
-    "# set up time on x-axis\n",
-    "ax.set_xlabel(\"Time\")\n",
-    "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
-    "\n",
-    "ax.set_ylabel(\"Altitude [m]\")\n",
-    "ax.set_ylim([0, 12])\n",
-    "plt.colorbar(label=\"Horizontal Vel Dir [deg CW from true N]\");"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Saving and Loading DOLfYN datasets\n",
-    "Datasets can be saved and reloaded using the `save` and `load` functions. Xarray is saved natively in netCDF format, hence the \".nc\" extension.\n",
-    "\n",
-    "Note: DOLfYN datasets cannot be saved using xarray's native `ds.to_netcdf`; however, DOLfYN datasets can be opened using `xarray.open_dataset`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Uncomment these lines to save and load to your current working directory\n",
-    "# dolfyn.save(ds, 'your_data.nc')\n",
-    "# ds_saved = dolfyn.load('your_data.nc')"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 7. Turbulence Statistics\n",
-    "\n",
-    "The next section of this jupyter notebook will run through the turbulence analysis of the data presented here. There was no intention of measuring turbulence in the deployment that collected this data, so results depicted here are not the highest quality. The quality of turbulence measurements from an ADCP depend heavily on the quality of the deployment setup and data collection, particularly instrument frequency, samping frequency and depth bin size.\n",
-    "\n",
-    "Read more on proper ADCP setup for turbulence measurements in: Thomson, Jim, et al. \"Measurements of turbulence at two tidal energy sites in Puget Sound, WA.\" IEEE Journal of Oceanic Engineering 37.3 (2012): 363-374.\n",
-    "\n",
-    "Most functions related to turbulence statistics in MHKiT-DOLfYN have the papers they originate from referenced in their docstrings.\n",
-    "\n",
-    "### 7.1 Turbulence Intensity\n",
-    "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this can be simply calculated as `<raw dataset>.velds.I`, but be aware that this will be a conservative estimate. Another function, `turbulence_intensity`, is capable of subtracting instrument noise from this parameter and is discussed below. The noise-subtracted TI is more accurate and typically 1-2% lower than the non-noise-subtracted estimation.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x249daa0dd30>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "To rotate into the principal frame of reference (streamwise, cross-stream, vertical), if desired, we must first calculate the depth-averaged principal flow heading and add it to the dataset attributes. Then the dataset can be rotated using the same `rotate2` function. We use `inplace=False` because we do not want to alter the input dataset here."
       ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "ds.attrs[\"principal_heading\"] = dolfyn.calc_principal_heading(ds[\"vel\"].mean(\"range\"))\n",
+        "ds = dolfyn.rotate2(ds, \"principal\", inplace=False)"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Turbulence Intensity\n",
-    "ds_avg[\"TI\"] = ds_avg.velds.I\n",
-    "ds_avg[\"TI\"].plot(cmap=\"Reds\", ylim=(0, 11))"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.2 Power Spectral Densities (Auto-Spectra)\n",
-    "\n",
-    "Other turbulence parameters include the TKE power- and cross-spectral densities (i.e the power spectra), turbulent kinetic energy (TKE, i.e. the variances of velocity vector components), Reynolds stress vector (i.e. the co-variances of velocity vector components), TKE dissipation rate, and TKE production rate. These quantities are primarily used to inform and verify hydrodynamic and coastal models, which take some or all of these quantities as input.\n",
-    "\n",
-    "The TKE production rate is the rate at which kinetic energy (KE) transitions from a useful state (able to do \"work\" in the physics sense) to turbulent; TKE is the actual amount of turbulent KE in the water; and TKE dissipation rate is the rate at which turbulent KE is lost to non-motion forms of energy (heat, sound, etc) due to viscosity. The power spectra are used to depict and quantify this energy in the frequency domain, and creating them are the first step in turbulence analysis.\n",
-    "\n",
-    "We'll start by looking at the power spectra, specifically the auto-spectra from the vertical beam (\"auto\" meaning the variance of a single vector direction, e.g. $\\overline{u'^2}$, vs \"cross\", meaning the covariance of two directions, e.g. $\\overline{u'w'}$). This can be done using the `power_spectral_density` function from the `ADPBinner` we created (\"avg_tool\"). We'll create spectra at the middle water column, at a depth of 5 m, and use a number of FFT's equal to 1/3 the bin size."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "rng = 5  # m\n",
-    "vel_up = ds[\"vel_b5\"].sel(range_b5=rng, method=\"nearest\")  # vertical velocity\n",
-    "U = ds_avg[\"U_mag\"].sel(\n",
-    "    range=5, method=\"nearest\"\n",
-    ")  # flow speed, for plotting in the next block\n",
-    "\n",
-    "ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n",
-    "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 2\n",
-    ")"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the auto-spectra, we're primarly looking for three components: the energy-producing region, the isotropic turbulence region (so-called \"red noise\"), and the instrument noise floor (termed \"white noise\"). \n",
-    "\n",
-    "The block below organizes and plots the power spectra by the corresponding ensemble speed, averaging them by 0.1 m/s velocity bins. Note that if an ensemble is missing data that wasn't filled in, a power spectrum will not be calculated for that ensemble timestamp."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "[Text(0.5, 0, 'Frequency [Hz]'),\n",
-       " Text(0, 0.5, 'PSD [m2 s-2 Hz-1]'),\n",
-       " (0.01, 1),\n",
-       " (0.0005, 0.1)]"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Updated velocity histograms and contour plots for rotated velocity. "
       ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 600x500 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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9+/fjs88+q3Aa07x586Q1GnPnzoW9vT22bt2KuLg4LF26FAqFAgAwffp0fP311xg+fDhmz56NXr16obCwEEePHkVQUBAGDBhg8P5eXl4AgC+++AI2NjawsLCAu7u79I2+iYkJpkyZglmzZsHa2lpv7UJd6N27N4KCguDt7Q07OztcvnwZmzdvho+Pj5SwdevWDQCwZMkSBAQEwMTEBN7e3hgyZAj8/f0xa9Ys5Obmol+/fjh//jzmzZuH7t27IzQ0FADQtWtXjBkzBitWrICJiQkGDhyIixcvYsWKFVAoFGjRomrffwUFBSE2NhadO3eGt7c3kpOTsWzZsjo5l2P+/PmYP38+Dh48WOk6i7lz5+LOnTsYNGgQ2rRpA41Gg48//lhnncNTTz0FS0tLbN26FV26dEHLli3h6upaaZI7evRobN26FUOHDsW0adPQq1cvmJmZ4c6dOzh8+DCGDx+OkSNHom/fvrCzs8Nbb72FefPmwczMDFu3bsW5c+dqvU+Ah8lkWVkZDh48qLMd7eDBgzFv3jzIZDIMHDiw0ntUpc+mT5+OnTt34oUXXsA777wDb29vPHjwALdu3UJCQgKioqLQu3fvOnmPRPQYDbx4nIioVn388ccCgPD09DRYn5mZKSIjI4W7u7swMzMT9vb2okePHuL9998X+fn5Uhwe2SFJCCEuXLgggoODhUKhEObm5uKZZ54xuJtPdna2mDZtmmjbtq0wMzMTTk5OIjAwUFy5cqXS+69evVq4u7sLExMTgzsF3bx5UwAQb731VpX7IywsTFhbW+uVz5s3T283p0fbNHv2bNGzZ09hZ2cn5HK56NChg3jnnXfE3bt3pRitVismTJggHB0dhUwmEwCknaoKCwvFrFmzRLt27YSZmZlwcXER//rXv0R2drbOc4uKisSMGTOEk5OTsLCwEH369BFJSUlCoVDo7OhUvivUo7sBCfGwzyMiIoSTk5OwsrISzz//vPjll1+Er6+v8PX1leLKd4X69ttvda6v6N7l/ZSZmalXZmgHr7/bt2+fCAgIEK1btxbm5ubCyclJDB06VPzyyy86cdu3bxedO3cWZmZmOn8GFf3ZCfFwx6bly5eLZ555RlhYWIiWLVuKzp07i0mTJolr165JccePHxc+Pj7CyspKODo6igkTJojTp0/rfb4qepavr6/o2rWrXnm7du1EYGCgTtmDBw+EUqkUAMRff/0llf/v//6vACD+8Y9/6N3n0V2hqtpn+fn54oMPPhAeHh7C3NxcKBQK0a1bN/HOO+8ItVptsM+IqO7JhOCGz0RETcGaNWsQGRmJlJQUacH5k+r48ePo168ftm7dipCQkIZuDhERVQETCyKiRu7MmTO4ceMGJk2ahH79+mH37t0N3aRalZiYiKSkJPTo0QOWlpY4d+4cFi9eDIVCgfPnzz/2AEAiImocmFgQETVy7du3h1qtRv/+/bF582aoVKqGblKtOnnyJKKionDp0iXk5eVBqVTC398fixYtMri1LBERNU5MLIiIiIiIyGjcbpaIiIiIiIzGxIKIiIiIiIzGcyzq2YMHD5CamgobG5t6PdyKiIiIiKi6hBDIy8uDq6vrY88WYmJRz1JTU+Hm5tbQzSAiIiIiqrLbt28/9tBRJhb1zMbGBsDDPxxbW9sGbg0RERERUcVyc3Ph5uYm/Q5bGSYW9ax8+pOtrS0TCyIiIiJqEqoyhZ+Lt4mIiIiIyGhMLIiIiIiIyGhMLIiIiIiIyGhcY0FERERUi9RqNTQaTZXjW7VqBZVKVXcNIqonTCyIiIiIaolarUbgsJHIzS+o8jW2La0Rt2cXkwtq8phYEBEREdUSjUaD3PwCdB4yFrZKl8fG595Nw5XEr6DRaJhYUJPHxIKIiIioltkqXWDn0q6hm0FUr7h4m4iIiIiIjMbEgoiIiIiIjMapUEREREQVqO4OT9evX0dZWVndNYioEWvUicWnn36KTz/9FDdv3gQAdO3aFXPnzkVAQAAAQAiBmJgYfPHFF8jOzkbv3r2xbt06dO3aVbqHVqvFzJkzsX37dhQWFmLQoEH45JNP0KZNGykmOzsbkZGR2LNnDwBg2LBhWLNmDVq1aiXF3Lp1C1OmTMGhQ4dgaWmJkJAQLF++HObm5nXfEURERFTvarLDU7G2CFn3NCgtLa3DlhE1To06sWjTpg0WL16Mp59+GgCwadMmDB8+HGfOnEHXrl2xdOlSrFy5ErGxsejUqRM++ugjDBkyBFevXoWNjQ0AYPr06di7dy927NgBBwcHREVFISgoCMnJyTAxMQEAhISE4M6dO4iPjwcAvPnmmwgNDcXevXsBAGVlZQgMDISjoyOOHTuGrKwshIWFQQiBNWvWNEDPEBERUV2r7g5PAJD6+zlk7t3AUQtqlhp1YhEcHKzzesGCBfj0009x4sQJeHp6YvXq1Xj//ffx8ssvA3iYeDg7O2Pbtm2YNGkScnJysH79emzevBmDBw8GAGzZsgVubm44cOAA/P39cfnyZcTHx+PEiRPo3bs3AODLL7+Ej48Prl69Cg8PDyQkJODSpUu4ffs2XF1dAQArVqxAeHg4FixYAFtb2wrfg1arhVarlV7n5ubWah8REVHjxsPSmr7q7PCUk5lax60harwadWLxd2VlZfj2229RUFAAHx8f3LhxA2q1Gn5+flKMXC6Hr68vjh8/jkmTJiE5ORklJSU6Ma6urvDy8sLx48fh7++PpKQkKBQKKakAgD59+kChUOD48ePw8PBAUlISvLy8pKQCAPz9/aHVapGcnIwBAwZU2O5FixYhJiamlnuDiIiaAh6WRlVRWlqC69evV+saJqDUGDX6xOLChQvw8fFBUVERWrZsiV27dsHT0xPHjx8HADg7O+vEOzs7488//wTw8B90c3Nz2NnZ6cWo1WopxsnJSe+5Tk5OOjGPPsfOzg7m5uZSTEXmzJmDGTNmSK9zc3Ph5uZWlbdORERNHA9Lo8cpzNMgXa3G5GlRMDMzq/J1TECpMWr0iYWHhwfOnj0LjUaDnTt3IiwsDEePHpXqZTKZTrwQQq/sUY/GGIqvSYwhcrkccrm80hgiInqy8bA0qkhx0X2ghQk8BodC6Vq1zwgTUGqsGn1iYW5uLi3e7tmzJ06dOoWPP/4Ys2bNAvBwNMHF5b/fAmVkZEijCyqVCsXFxcjOztYZtcjIyEDfvn2lmPT0dL3nZmZm6tzn5MmTOvXZ2dkoKSnRG8kgIiIiqi4bBxWTT2rymtwBeUIIaLVauLu7Q6VSITExUaorLi7G0aNHpaShR48eMDMz04lJS0tDSkqKFOPj44OcnBz8+uuvUszJkyeRk5OjE5OSkoK0tDQpJiEhAXK5HD169KjT90tERERE1BQ06hGL9957DwEBAXBzc0NeXh527NiBI0eOID4+HjKZDNOnT8fChQvRsWNHdOzYEQsXLoSVlRVCQkIAAAqFAhEREYiKioKDgwPs7e0xc+ZMdOvWTdolqkuXLnjppZcwceJEfP755wAebjcbFBQEDw8PAICfnx88PT0RGhqKZcuW4d69e5g5cyYmTpxY6Y5QRERERETNRaNOLNLT0xEaGoq0tDQoFAp4e3sjPj4eQ4YMAQC8++67KCwsxOTJk6UD8hISEqQzLABg1apVMDU1xahRo6QD8mJjY6UzLABg69atiIyMlHaPGjZsGNauXSvVm5iYIC4uDpMnT0a/fv10DsgjIiIiIqJGnlisX7++0nqZTIbo6GhER0dXGGNhYYE1a9ZUepCdvb09tmzZUumz2rZti3379lUaQ0RERI1bdc4VuX79Og+6I6qGRp1YEBEREdWW6p4rUqwtQtY9DUpLS+u4ZURPBiYWRERE1CxU91yR1N/PIXPvBo5aEFUREwsiIiJqVqp6rkhOZmo9tIboydHktpslIiIiIqLGh4kFEREREREZjVOhiJqQ6uxmUq64uBjm5uZVjm/VqhVUKlU1W0ZERETNHRMLoiaiuruZAEBpaQnuZmTA0Vmlc3ZLZWxbWiNuzy4mF0RERFQtTCyImojq7mYCPNzRJH3vBnQc+E8oXR+/UDH3bhquJH4FjUbDxIKIiIiqhYkFURNT1d1MgP/uaGLjoKryNUREREQ1wcSCiHSUlpbg+vXr1bqG6zKIqCFUd90ZT9ImqltMLIhIUpinQbpajcnTomBmZlbl67gug4jqW03WnfEkbaK6xcSCiCTFRfeBFibwGBxapTUZANdlEFHDqOm6M56kTVR3mFgQkR6uySCipqIm686IqG4wsSBqQNWZH8y5wU+G6s4J5/qV5ofrnIioqWJiQdRAqjs/mHODm76azAnn+pXmheuciKgpY2JB1ECqOz+Yc4Obvur+mXP9SvPDdU5E1JQxsSBqYFWdH8y5wU+O6swJp+aJ65yIqCliYkFERqvunHDOByciMg7/3aXGiIkFERmlJnPCOR+ciKjm+O8uNVZMLIjIKNWdE8754ERExuG/u9RYMbEgolrBOeFERPWL/+5SY8PEgoioEeOZBkRE1FQwsSAiaqR4pgERETUlTCyIiBopnmlAzU11Tqa/fv06z/UhamSYWBARNXKcR03NQXVPpi/WFiHrngalpaV13DIiqiomFkRERFVUnW/UAX6rXh3VPZk+9fdzyNy7gf1L1IgwsSCqJfyFg+jJVt1v1AF+q14TVT2ZPicztR5aQ0TVwcSCqBbwFw6iJ191v1EH+K06ETUvTCyIagF/4agebqFKTVlVv1EH+K06ETUvTCyIahF/4Xi8J2kLVU5/IyIi+i8mFkRUr56ULVQ5/Y2IiEhXnSUWHTp0wKlTp+Dg4KBTrtFo8I9//KNK0yAWLVqE77//HleuXIGlpSX69u2LJUuWwMPDQ4oRQiAmJgZffPEFsrOz0bt3b6xbtw5du3aVYrRaLWbOnInt27ejsLAQgwYNwieffII2bdpIMdnZ2YiMjMSePXsAAMOGDcOaNWvQqlUrKebWrVuYMmUKDh06BEtLS4SEhGD58uUwNzevaTcRNVtNfQtVTn8jIiLSVWeJxc2bNw3+n6dWq8Vff/1VpXscPXoUU6ZMwXPPPYfS0lK8//778PPzw6VLl2BtbQ0AWLp0KVauXInY2Fh06tQJH330EYYMGYKrV6/CxsYGADB9+nTs3bsXO3bsgIODA6KiohAUFITk5GSYmJgAAEJCQnDnzh3Ex8cDAN58802EhoZi7969AICysjIEBgbC0dERx44dQ1ZWFsLCwiCEwJo1a4zuL2p8eFATVQWnvxERET1U64lF+Tf+APDTTz9BoVBIr8vKynDw4EG0b9++Svcq/yW/3MaNG+Hk5ITk5GS88MILEEJg9erVeP/99/Hyyy8DADZt2gRnZ2ds27YNkyZNQk5ODtavX4/Nmzdj8ODBAIAtW7bAzc0NBw4cgL+/Py5fvoz4+HicOHECvXv3BgB8+eWX8PHxwdWrV+Hh4YGEhARcunQJt2/fhqurKwBgxYoVCA8Px4IFC2Bra1vjPqPGhwc1EREREVVPrScWI0aMAADIZDKEhYXp1JmZmaF9+/ZYsWJFje6dk5MDALC3twcA3LhxA2q1Gn5+flKMXC6Hr68vjh8/jkmTJiE5ORklJSU6Ma6urvDy8sLx48fh7++PpKQkKBQKKakAgD59+kChUOD48ePw8PBAUlISvLy8pKQCAPz9/aHVapGcnIwBAwYYbLNWq4VWq5Ve5+bm1ui9U/3iQU1ERERE1VPricWDBw8AAO7u7jh16hSUSmWt3FcIgRkzZuD555+Hl5cXgIffKgOAs7OzTqyzszP+/PNPKcbc3Bx2dnZ6MeXXq9VqODk56T3TyclJJ+bR59jZ2cHc3FyKMWTRokWIiYmpzlulRoQHNRERERFVTYu6uvGNGzdqLakAgLfffhvnz5/H9u3b9epkMpnOayGEXtmjHo0xFF+TmEfNmTMHOTk50s/t27crbRcRERERUVNUp9vNHjx4EAcPHkRGRoY0klFuw4YNVb7P1KlTsWfPHvz88886OzmVbzupVqvh4vLf6SoZGRnS6IJKpUJxcTGys7N1Ri0yMjLQt29fKSY9PV3vuZmZmTr3OXnypE59dnY2SkpK9EYy/k4ul0Mul1f5vVLd4HkDRERERHWrzhKLmJgYzJ8/Hz179oSLi8tjRxAMEUJg6tSp2LVrF44cOQJ3d3edend3d6hUKiQmJqJ79+4AgOLiYhw9ehRLliwBAPTo0QNmZmZITEzEqFGjAABpaWlISUnB0qVLAQA+Pj7IycnBr7/+il69egEATp48iZycHCn58PHxwYIFC5CWliYlMQkJCZDL5ejRo0cNeojqC88bICIiIqp7dZZYfPbZZ4iNjUVoaGiN7zFlyhRs27YNP/zwA2xsbKS1DAqFApaWlpDJZJg+fToWLlyIjh07omPHjli4cCGsrKwQEhIixUZERCAqKgoODg6wt7fHzJkz0a1bN2mXqC5duuCll17CxIkT8fnnnwN4uN1sUFCQdGaGn58fPD09ERoaimXLluHevXuYOXMmJk6cyB2hGjmeN0BERERU9+ossSguLpa+7a+pTz/9FADw4osv6pRv3LgR4eHhAIB3330XhYWFmDx5snRAXkJCgnSGBQCsWrUKpqamGDVqlHRAXmxsrHSGBQBs3boVkZGR0u5Rw4YNw9q1a6V6ExMTxMXFYfLkyejXr5/OAXnUNPC8ASIiIqK6U2eJxYQJE7Bt2zZ8+OGHNb6HEOKxMTKZDNHR0YiOjq4wxsLCAmvWrKn0IDt7e3ts2bKl0me1bdsW+/bte2ybiIiIiIiamzpLLIqKivDFF1/gwIED8Pb2hpmZmU79ypUr6+rRRERERERUz+ossTh//jyeffZZAEBKSopOXU0WchNR81ZaWoLr169XOb5Vq1bSznFERERU9+ossTh8+HBd3ZqImpnCPA3S1WpMnhalN/pZEduW1ojbs6tayUV1tiXmlsREleM230TNT52eY0FEVBuKi+4DLUzgMTgUStfHL8DPvZuGK4lfQaPRVDmxqO62xNySmKhi3OabqHmqs8RiwIABlU55OnToUF09moieUDYOqirv7FVd1d2WmFsSE1WM23w3PtWdTgpwSilVX50lFuXrK8qVlJTg7NmzSElJQVhYWF09lojIKFXdlphbEhM9Hrf5bhxqMp0UqNmUUmre6iyxWLVqlcHy6Oho5Ofn19VjiYiIiOhvqjudFKjZlFKiel9j8cYbb6BXr148WI6IiIioHtXldFIiAGhR3w9MSkqChYVFfT+WiIiIiIjqUJ2NWLz88ss6r4UQSEtLw2+//WbUadxERFVR3YWK3OqSiIjIOHWWWCgUCp3XLVq0gIeHB+bPnw8/P7+6eiwRUY0WKnKrSyIiIuPUWWKxcePGuro1EVGlarJQkVtdUlPGk+mJqDGo88XbycnJuHz5MmQyGTw9PdG9e/e6fiQREYDqLVTkVpfUVNXXyfRERI9TZ4lFRkYGRo8ejSNHjqBVq1YQQiAnJwcDBgzAjh074OjoWFePJiIiajbq42R6IqKqqLPEYurUqcjNzcXFixfRpUsXAMClS5cQFhaGyMhIbN++va4eTURE1OxwK1Eiamh1lljEx8fjwIEDUlIBAJ6enli3bh0XbxMRERERPWHq7ByLBw8eGJzraWZmhgcPHtTVY4mIiIiIqAHUWWIxcOBATJs2Damp/10Q+ddff+Gdd97BoEGD6uqxRERERETUAOossVi7di3y8vLQvn17PPXUU3j66afh7u6OvLw8rFmzpq4eS0REREREDaDO1li4ubnh9OnTSExMxJUrVyCEgKenJwYPHlxXj6RmRK1WQ6PRVCmWJyoTERmP/+4S0ePUemJx6NAhvP322zhx4gRsbW0xZMgQDBkyBACQk5ODrl274rPPPkP//v1r+9HUTKjVagQOG4nc/IIqxfNEZSIi4/DfXSKqilpPLFavXo2JEyfC1tZWr06hUGDSpElYuXIlEwuqMY1Gg9z8AnQeMha2SpfHxvNEZSIi4/DfXSKqilpPLM6dO4clS5ZUWO/n54fly5fX9mOpGbJVulRpz3aeqExEVDv47y4RVabWF2+np6cb3Ga2nKmpKTIzM2v7sURERERE1IBqfcSidevWuHDhAp5++mmD9efPn4eLy+OHUYmIiKhulJaW4Pr161WO52JsIqqKWk8shg4dirlz5yIgIAAWFhY6dYWFhZg3bx6CgoJq+7FERERUBYV5GqSr1Zg8LarSGQZ/x8XYRFQVtZ5YfPDBB/j+++/RqVMnvP322/Dw8IBMJsPly5exbt06lJWV4f3336/txxIREVEVFBfdB1qYwGNwKJSuj18vAXAxNhFVTa0nFs7Ozjh+/Dj+9a9/Yc6cORBCAABkMhn8/f3xySefwNnZubYfS0RERNVg46Cq0kJsgIuxiahq6uSAvHbt2mH//v3Izs7GH3/8ASEEOnbsCDs7u7p4HBERERERNbA6O3kbAOzs7PDcc8/V5SOIiIiIiKgRqPXtZomIiIiIqPlhYkFEREREREZr9InFzz//jODgYLi6ukImk2H37t069UIIREdHw9XVFZaWlnjxxRdx8eJFnRitVoupU6dCqVTC2toaw4YNw507d3RisrOzERoaCoVCAYVCgdDQUGg0Gp2YW7duITg4GNbW1lAqlYiMjERxcXFdvG0iIiIioial0ScWBQUFeOaZZ7B27VqD9UuXLsXKlSuxdu1anDp1CiqVCkOGDEFeXp4UM336dOzatQs7duzAsWPHkJ+fj6CgIJ1t80JCQnD27FnEx8cjPj4eZ8+eRWhoqFRfVlaGwMBAFBQU4NixY9ixYwd27tyJqKiounvzRERERERNRJ0u3q4NAQEBCAgIMFgnhMDq1avx/vvv4+WXXwYAbNq0Cc7Ozti2bRsmTZqEnJwcrF+/Hps3b8bgwYMBAFu2bIGbmxsOHDgAf39/XL58GfHx8Thx4gR69+4NAPjyyy/h4+ODq1evwsPDAwkJCbh06RJu374NV1dXAMCKFSsQHh6OBQsWwNbW1mAbtVottFqt9Do3N7fW+oaIiIyjVqv1RqcrwtOnqbmp7gntrVq1gkqlqsMWUWPX6BOLyty4cQNqtRp+fn5SmVwuh6+vL44fP45JkyYhOTkZJSUlOjGurq7w8vLC8ePH4e/vj6SkJCgUCimpAIA+ffpAoVDg+PHj8PDwQFJSEry8vKSkAgD8/f2h1WqRnJyMAQMGGGzjokWLEBMTUwfvnoiIjKFWqxE4bCRy8wuqFM/Tp6k5qckJ7bYtrRG3ZxeTi2asSScWarUaAPQO3HN2dsaff/4pxZibm+udoeHs7Cxdr1ar4eTkpHd/JycnnZhHn2NnZwdzc3MpxpA5c+ZgxowZ0uvc3Fy4ublV9S0SEVEd0Wg0yM0vQOchY2GrdHlsPE+fpuakuie0595Nw5XEr6DRaJhYNGNNOrEoJ5PJdF4LIfTKHvVojKH4msQ8Si6XQy6XV9oWIiJqOLZKlyqdQM3Tp6k5qs4J7USNfvF2Zcoz4kdHDDIyMqTRBZVKheLiYmRnZ1cak56ernf/zMxMnZhHn5OdnY2SkhK9kQwiIiIiouamSScW7u7uUKlUSExMlMqKi4tx9OhR9O3bFwDQo0cPmJmZ6cSkpaUhJSVFivHx8UFOTg5+/fVXKebkyZPIycnRiUlJSUFaWpoUk5CQALlcjh49etTp+yQiIiIiauwa/VSo/Px8/PHHH9LrGzdu4OzZs7C3t0fbtm0xffp0LFy4EB07dkTHjh2xcOFCWFlZISQkBACgUCgQERGBqKgoODg4wN7eHjNnzkS3bt2kXaK6dOmCl156CRMnTsTnn38OAHjzzTcRFBQEDw8PAICfnx88PT0RGhqKZcuW4d69e5g5cyYmTpxY4Y5QRERERETNRaNPLH777TedHZfKF0KHhYUhNjYW7777LgoLCzF58mRkZ2ejd+/eSEhIgI2NjXTNqlWrYGpqilGjRqGwsBCDBg1CbGwsTExMpJitW7ciMjJS2j1q2LBhOmdnmJiYIC4uDpMnT0a/fv1gaWmJkJAQLF++vK67gIioWrhFJBERNYRGn1i8+OKLEEJUWC+TyRAdHY3o6OgKYywsLLBmzRqsWbOmwhh7e3ts2bKl0ra0bdsW+/bte2ybiYgaCreIJCKihtLoEwsiIqo6bhFJREQNhYkFEdETiFtEEhFRfWvSu0IREREREVHjwMSCiIiIiIiMxsSCiIiIiIiMxsSCiIiIiIiMxsXb1ODUajU0Gk2V469fv46ysrK6axARERERVRsTC2pQarUagcNGIje/oMrXFGuLkHVPg9LS0jpsGRERERFVBxMLalAajQa5+QXoPGQsbJUuVbom9fdzyNy7gaMWRERERI0IEwtqFGyVLlXecz8nM7WOW0NERERE1cXF20REREREZDQmFkREREREZDROhSIiIiIio5WWluD69evVuqZVq1ZQqVR11CKqb0wsiIiIiMgohXkapKvVmDwtCmZmZlW+zralNeL27GJy8YRgYkFERERERikuug+0MIHH4FAoXau2GUvu3TRcSfwKGo2GicUTgokFEREREdUKGwdVlXd5pCcPF28TEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRmFgQEREREZHRuCsUERE9EdRqNTQaTZXjr1+/jrKysrprEBFRM8PEgoiomXsSTstVq9UIHDYSufkFVb6mWFuErHsalJaW1mHLiIiaDyYWRETNWGM+Lbc6IxDXr19Hdk4uur40DrZKlypdk/r7OWTu3cBRCyKiWsLEgoioGWusp+VWdwSifPThuVaOVT6cKycz1ZgmEhHRI5hYEBFRozstV6PRIDe/AJ2HjK3SCARHH4iapupOxWxs0zBJFxMLIiKqtur+MlBcXAxzc/Mqx5cvrLZVulQp4eHoA1HTU5OpmPUxDZNqjokF1brqzovmN4xETUt1fxkoLS3B3YwMODqrYGJiUqVncGE10ZOvulMx62MaJhmHiQXVqprOi+YvD0RNR3V/GUj9/RzS925Ax4H/rPI6Dk5tImo+GttUTKo5JhZUqzgvmqj5qOovA+XTlKrzywOnNhERNT1MLKhOcF40ERERUfPCxIKIiIiImoQn4UDPJxkTixr45JNPsGzZMqSlpaFr165YvXo1+vfv39DNIiIiInpiNeYDPekhJhbV9PXXX2P69On45JNP0K9fP3z++ecICAjApUuX0LZt24ZuXq2rzg5PAHd5IiIiorpR0wM9U35cj9OnT6NDhw5VuoYjHDXHxKKaVq5ciYiICEyYMAEAsHr1avz000/49NNPsWjRIr14rVYLrVYrvc7JyQEA5Obm1k+DH5GVlYWsrKwqxd69exf/b/Z7uF+ofXzw/6+4uAj3snOQcfsaSoruPzY+J/0OhHiA7LSbaCGqlpBU9xo+g8/gM/gMPoPP4DOenGeUFhdV6XcMAMjPzoQ6LQ1vTZ0OM9OqjXJYys2xfOkiKJXKKsUDgEwmgxCizuIBwMHBAQ4ODtW6pjaU/85alfbKRHXfVTNWXFwMKysrfPvttxg5cqRUPm3aNJw9exZHjx7VuyY6OhoxMTH12UwiIiIiolp1+/ZttGnTptIYjlhUw927d1FWVgZnZ2edcmdnZ6jVaoPXzJkzBzNmzJBeP3jwAPfu3YODgwNkMlmdtrc25ebmws3NDbdv34atrW1DN+eJxX6ue+zj+sF+rnvs4/rBfq577OO6Z0wfCyGQl5cHV1fXx8YysaiBRxMCIUSFSYJcLodcLtcpa9WqVV01rc7Z2tryL309YD/XPfZx/WA/1z32cf1gP9c99nHdq2kfKxSKKsW1qPadmzGlUgkTExO90YmMjAy9UQwiIiIiouaEiUU1mJubo0ePHkhMTNQpT0xMRN++fRuoVUREREREDY9ToappxowZCA0NRc+ePeHj44MvvvgCt27dwltvvdXQTatTcrkc8+bN05vWRbWL/Vz32Mf1g/1c99jH9YP9XPfYx3WvvvqYu0LVwCeffIKlS5ciLS0NXl5eWLVqFV544YWGbhYRERERUYNhYkFEREREREbjGgsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiIiIiIjIaEwsiajZGjhwJS0tLaDSaCmP++c9/wszMDOnp6VW+r0wmQ3R0tPENrOL9L126hOjoaNy8ebNWnxMeHo6WLVvWqE1VsX///jrtJ6pcamoqoqOjcfbs2YZuChE9oZhYEFGzERERgaKiImzbts1gfU5ODnbt2oWgoCA4OzvXc+sqlpSUhAkTJkivL126hJiYmFpPLIxpU1Xs378fMTExddQiepzU1FTExMQwsSCiOsPEgoiajYCAALi6umLDhg0G67dv347CwkJERETUc8sq16dPH7Rp06ahm6GjMbbpcQoLCyGEaOhmNBn3799v6CYQURPDxIKImg0TExOEhYUhOTkZFy5c0KvfuHEjXFxcEBAQAABQq9WYNGkS2rRpA3Nzc7i7uyMmJgalpaWPfVZKSgqGDx8OOzs7WFhY4Nlnn8WmTZv04jQaDaKiotChQwfI5XI4OTlh6NChuHLlihTz92lHsbGxeO211wAAAwYMgEwmg0wmQ2xsLP7973/D1NQUt2/f1nvO+PHj4eDggKKiose2/Y8//sDQoUPRsmVLuLm5ISoqClqtVifm0alQ9+/fx8yZM+Hu7g4LCwvY29ujZ8+e2L59O4CH06zWrVsnXVv+Uz7qUlRUhDlz5sDd3R3m5uZo3bo1pkyZojdtTavVIioqCiqVClZWVnjhhReQnJyM9u3bIzw8XIqLjY2FTCZDQkICxo8fD0dHR1hZWUGr1eKPP/7AuHHj0LFjR1hZWaF169YIDg7W+0wcOXIEMpkM27Ztw6xZs+Di4oKWLVsiODgY6enpyMvLw5tvvgmlUgmlUolx48YhPz//sf1ryI4dOyCTybB27Vqd8nnz5sHExASJiYmPvce3336L3r17Q6FQwMrKCh06dMD48eOl9/Lcc88BAMaNGyf1f/mfYfk0uAsXLsDPzw82NjYYNGgQAKC4uBgfffQROnfuDLlcDkdHR4wbNw6ZmZk6z//666/h5+cHFxcXWFpaokuXLpg9ezYKCgp04sqfdeXKFfj7+8Pa2houLi5YvHgxAODEiRN4/vnnYW1tjU6dOhn8e0NEjZQgImpGrl27JmQymZg+fbpO+cWLFwUAMXv2bCGEEGlpacLNzU20a9dOfP755+LAgQPi3//+t5DL5SI8PFznWgBi3rx50usrV64IGxsb8dRTT4mvvvpKxMXFiTFjxggAYsmSJVJcbm6u6Nq1q7C2thbz588XP/30k9i5c6eYNm2aOHTokMH7Z2RkiIULFwoAYt26dSIpKUkkJSWJjIwMkZ6eLuRyuXj//fd12peVlSUsLS3F//t//6/SvgkLCxPm5uaiS5cuYvny5eLAgQNi7ty5QiaTiZiYmErf86RJk4SVlZVYuXKlOHz4sNi3b59YvHixWLNmjRBCiD/++EO8+uqrAoDU5qSkJFFUVCQePHgg/P39hampqfjwww9FQkKCWL58ubC2thbdu3cXRUVF0nPGjBkjWrRoIWbPni0SEhLE6tWrhZubm1AoFCIsLEyK27hxowAgWrduLd58803x448/iu+++06UlpaKo0ePiqioKPHdd9+Jo0ePil27dokRI0YIS0tLceXKFekehw8fFgBEu3btRHh4uIiPjxefffaZaNmypRgwYIAYMmSImDlzpkhISBBLliwRJiYmYurUqTr9NG/ePAFAHD58uNK+F0KIt956S5ibm4tTp04JIYQ4ePCgaNGihfjggw8ee+3x48eFTCYTo0ePFvv37xeHDh0SGzduFKGhoUIIIXJycqQ++eCDD6T+v337tvRnb2ZmJtq3by8WLVokDh48KH766SdRVlYmXnrpJWFtbS1iYmJEYmKi+J//+R/RunVr4enpKe7fvy+14d///rdYtWqViIuLE0eOHBGfffaZcHd3FwMGDNBp698/Zx9//LFITEwU48aNEwDEnDlzRKdOncT69evFTz/9JIKCggQA8dtvvz22D4io4TGxIKJmx9fXVyiVSlFcXCyVRUVFCQDi999/F0I8/EW5ZcuW4s8//9S5dvny5QKAuHjxolT26C/Zo0ePFnK5XNy6dUvn2oCAAGFlZSU0Go0QQoj58+cLACIxMbHS9j56/2+//bbCX1bDwsKEk5OT0Gq1UtmSJUtEixYtxI0bNyp9TlhYmAAgvvnmG53yoUOHCg8Pj0rb5OXlJUaMGFHp/adMmSIMfZ8VHx8vAIilS5fqlH/99dcCgPjiiy+EEP9N/mbNmqUTt337dgHAYGIxduzYStskhBClpaWiuLhYdOzYUbzzzjtSeXliERwcrBM/ffp0AUBERkbqlI8YMULY29vrlMXExAgTExNx5MiRx7ajqKhIdO/eXbi7u4tLly4JZ2dn4evrK0pLSx97bfnnsvyzZcipU6cEALFx40a9uvI/+w0bNuiUl/ftzp07Dd7rk08+MfisBw8eiJKSEnH06FEBQJw7d07vWX+/Z0lJiXB0dBQAxOnTp6XyrKwsYWJiImbMmFHp+yeixoFToYio2YmIiMDdu3exZ88eAEBpaSm2bNmC/v37o2PHjgCAffv2YcCAAXB1dUVpaan0Uz5N6ujRoxXe/9ChQxg0aBDc3Nx0ysPDw3H//n0kJSUBAH788Ud06tQJgwcPrrX3Nm3aNGRkZODbb78FADx48ACffvopAgMD0b59+8deL5PJEBwcrFPm7e2NP//8s9LrevXqhR9//BGzZ8/GkSNHUFhYWOU2Hzp0CAB0pjIBwGuvvQZra2scPHgQwH/7fNSoUTpxr776KkxNTQ3e+5VXXtErKy0txcKFC+Hp6Qlzc3OYmprC3Nwc165dw+XLl/Xig4KCdF536dIFABAYGKhXfu/ePZ3pUHPnzkVpaSl8fX0Ntu/v5HI5vvnmG2RlZeEf//gHhBDYvn07TExMpJiysjKdz+ODBw8AQJrmNGrUKHzzzTf466+/Hvs8Qx7tr3379qFVq1YIDg7Wee6zzz4LlUqFI0eOSLHXr19HSEgIVCoVTExMYGZmJr3vR/tVJpNh6NCh0mtTU1M8/fTTcHFxQffu3aVye3t7ODk5PfbzR0SNAxMLImp2Xn31VSgUCmzcuBHAw92K0tPTdRZtp6enY+/evTAzM9P56dq1KwDg7t27Fd4/KysLLi4ueuWurq5SPQBkZmbW+gLo7t27o3///tJ6hn379uHmzZt4++23q3S9lZUVLCwsdMrkcvlj12b85z//waxZs7B7924MGDAA9vb2GDFiBK5du/bYZ2ZlZcHU1BSOjo465TKZDCqVSuqv8v99dMcuU1NTODg4GLy3oT+HGTNm4MMPP8SIESOwd+9enDx5EqdOncIzzzxjMCGyt7fXeW1ubl5peVXWsVTk6aefRv/+/VFUVIR//vOfeu0fNGiQzuexfA3FCy+8gN27d6O0tBRjx45FmzZt4OXlJa1xqQorKyvY2trqlKWnp0Oj0cDc3Fzv74JarZb+HuTn56N///44efIkPvroIxw5cgSnTp3C999/DwB6/Wroc2Zubq7Xp+XlxvQpEdUfw1/xEBE9wSwtLTFmzBh8+eWXSEtLw4YNG2BjYyMtigYApVIJb29vLFiwwOA9ypMEQxwcHJCWlqZXnpqaKt0bABwdHXHnzh1j3opBkZGReO2113D69GmsXbsWnTp1wpAhQ2r9OX9nbW2NmJgYxMTEID09XRq9CA4O1lmIboiDgwNKS0uRmZmpk1wIIaBWq6Vv48uTh/T0dLRu3VqKKy0tlZKOR8lkMr2yLVu2YOzYsVi4cKFO+d27d9GqVasqvd+68j//8z+Ii4tDr169sHbtWrz++uvo3bu3VP/5558jLy9Pel3+WQKA4cOHY/jw4dBqtThx4gQWLVqEkJAQtG/fHj4+Po99tqG+UiqVcHBwQHx8vMFrbGxsADwcdUpNTcWRI0d0RmcqOzOGiJ48HLEgomYpIiICZWVlWLZsGfbv34/Ro0fDyspKqg8KCkJKSgqeeuop9OzZU++nssRi0KBB0i9af/fVV1/BysoKffr0AfBw+9vff/9dmgpUVXK5HID+t8DlRo4cibZt2yIqKgoHDhzA5MmTDf7SWFecnZ0RHh6OMWPG4OrVq9K2pRW1u3z3oS1btuiU79y5EwUFBVL9Cy+8AODh7kN/991331Vpp65yMplMaku5uLi4Gk8fqi0XLlxAZGQkxo4di19++QXe3t54/fXXkZ2dLcV4eHjofA4NTW+Ty+Xw9fXFkiVLAABnzpyRyoGKPzeGBAUFISsrC2VlZQb/Hnh4eAD4b1LyaL9+/vnnVe8AImryOGJBRM1Sz5494e3tjdWrV0MIoXd2xfz585GYmIi+ffsiMjISHh4eKCoqws2bN7F//3589tlnFU5jmjdvnrRGY+7cubC3t8fWrVsRFxeHpUuXQqFQAACmT5+Or7/+GsOHD8fs2bPRq1cvFBYW4ujRowgKCsKAAQMM3t/LywsA8MUXX8DGxgYWFhZwd3eXvtE3MTHBlClTMGvWLFhbW+utXagLvXv3RlBQELy9vWFnZ4fLly9j8+bN8PHxkRK2bt26AQCWLFmCgIAAmJiYwNvbG0OGDIG/vz9mzZqF3Nxc9OvXD+fPn8e8efPQvXt3hIaGAgC6du2KMWPGYMWKFTAxMcHAgQNx8eJFrFixAgqFAi1aVO27sqCgIMTGxqJz587w9vZGcnIyli1bVifncsyfPx/z58/HwYMHK11nUVBQgFGjRsHd3R2ffPIJzM3N8c033+Af//gHxo0bh927d1f6nLlz5+LOnTsYNGgQ2rRpA41Gg48//lhnncNTTz0FS0tLbN26FV26dEHLli3h6upaaZI8evRobN26FUOHDsW0adPQq1cvmJmZ4c6dOzh8+DCGDx+OkSNHom/fvrCzs8Nbb72FefPmwczMDFu3bsW5c+dq1G9E1EQ18OJxIqIG8/HHHwsAwtPT02B9ZmamiIyMFO7u7sLMzEzY29uLHj16iPfff1/k5+dLcXhkhyQhhLhw4YIIDg4WCoVCmJubi2eeecbgbjzZ2dli2rRpom3btsLMzEw4OTmJwMBAnW1PDd1/9erVwt3dXZiYmBjc6efmzZsCgHjrrbeq3B9hYWHC2tpar7x8y9S/e7RNs2fPFj179hR2dnZCLpeLDh06iHfeeUfcvXtXitFqtWLChAnC0dFRyGQyAUDaqaqwsFDMmjVLtGvXTpiZmQkXFxfxr3/9S2RnZ+s8t6ioSMyYMUM4OTkJCwsL0adPH5GUlCQUCoXOjk7lu0KVb936d9nZ2SIiIkI4OTkJKysr8fzzz4tffvlF+Pr6Cl9fXymufFeob7/9Vuf6iu5d3k+ZmZl6ZY/bbvaNN94QVlZWOruNCfHfHcBWrVpV6fX79u0TAQEBonXr1sLc3Fw4OTmJoUOHil9++UUnbvv27aJz587CzMxM58+woj97IR7u2LR8+XLxzDPPCAsLC9GyZUvRuXNnMWnSJHHt2jUp7vjx48LHx0dYWVkJR0dHMWHCBHH69Gm9z2dFz/L19RVdu3bVK2/Xrp0IDAys9P0TUeMgE4LHkBIRPWnWrFmDyMhIpKSkSAvOn1THjx9Hv379sHXrVoSEhDR0c4iImi0mFkRET5AzZ87gxo0bmDRpEvr16/fYKTRNTWJiIpKSktCjRw9YWlri3LlzWLx4MRQKBc6fP6+30xAREdUfJhZERE+Q9u3bQ61Wo3///ti8eTNUKlVDN6lWnTx5ElFRUbh06RLy8vKgVCrh7++PRYsWGdxaloiI6g8TCyIiIiIiMhq3myUiIiIiIqMxsSAiIiIiIqPxHIt69uDBA6SmpsLGxqZeD6wiIiIiIqouIQTy8vLg6ur62POCmFjUs9TUVLi5uTV0M4iIiIiIquz27duPPUiUiUU9s7GxAfDwD8fW1raBW0NEREREVLHc3Fy4ublJv8NWholFPSuf/mRra8vEgoiIiIiahKpM4efibSIiIiIiMhoTCyIiIiIiMhoTCyIiIiIiMhrXWBARUYNTq9XQaDQV1rdq1Qoqlar+GkRERNXGxIKIiBqUWq1G4LCRyM0vqDDGtqU14vbsYnJBRNSIMbEgIqIGpdFokJtfgM5DxsJW6aJXn3s3DSk/rsfp06fRoUMHg/fgiAYRUcNjYkFERI2CrdIFdi7t9MoL8zRIV6sxeVoUzMzMDF/LEQ0iogbHxIKIiBq14qL7QAsTeAwOhdJVP/HIvZuGK4lfQaPRMLEgImpATCyIiKhJsHFQGRzRICKixoHbzRIRERERkdEaNLH4+eefERwcDFdXV8hkMuzevVunXgiB6OhouLq6wtLSEi+++CIuXryoE6PVajF16lQolUpYW1tj2LBhuHPnjk5MdnY2QkNDoVAooFAoEBoaqret4a1btxAcHAxra2solUpERkaiuLhYJ+bChQvw9fWFpaUlWrdujfnz50MIUWv9QURERETUVDVoYlFQUIBnnnkGa9euNVi/dOlSrFy5EmvXrsWpU6egUqkwZMgQ5OXlSTHTp0/Hrl27sGPHDhw7dgz5+fkICgpCWVmZFBMSEoKzZ88iPj4e8fHxOHv2LEJDQ6X6srIyBAYGoqCgAMeOHcOOHTuwc+dOREVFSTG5ubkYMmQIXF1dcerUKaxZswbLly/HypUr66BniIiIiIialgZdYxEQEICAgACDdUIIrF69Gu+//z5efvllAMCmTZvg7OyMbdu2YdKkScjJycH69euxefNmDB48GACwZcsWuLm54cCBA/D398fly5cRHx+PEydOoHfv3gCAL7/8Ej4+Prh69So8PDyQkJCAS5cu4fbt23B1dQUArFixAuHh4ViwYAFsbW2xdetWFBUVITY2FnK5HF5eXvj999+xcuVKzJgxAzKZzOD70Gq10Gq10uvc3Nxa6z8iIiIiosai0a6xuHHjBtRqNfz8/KQyuVwOX19fHD9+HACQnJyMkpISnRhXV1d4eXlJMUlJSVAoFFJSAQB9+vSBQqHQifHy8pKSCgDw9/eHVqtFcnKyFOPr6wu5XK4Tk5qaips3b1b4PhYtWiRNwVIoFHBzczOiV4iIiIiIGqdGm1io1WoAgLOzs065s7OzVKdWq2Fubg47O7tKY5ycnPTu7+TkpBPz6HPs7Oxgbm5eaUz56/IYQ+bMmYOcnBzp5/bt25W/cSIiIiKiJqjRbzf76BQjIUSF044qijEUXxsx5Qu3K2uPXC7XGeUgIiIiInoSNdoRi/JDjh4dDcjIyJBGClQqFYqLi5GdnV1pTHp6ut79MzMzdWIefU52djZKSkoqjcnIyACgP6pCRERERNTcNNrEwt3dHSqVComJiVJZcXExjh49ir59+wIAevToATMzM52YtLQ0pKSkSDE+Pj7IycnBr7/+KsWcPHkSOTk5OjEpKSlIS0uTYhISEiCXy9GjRw8p5ueff9bZgjYhIQGurq5o37597XcAEREREVET0qCJRX5+Ps6ePYuzZ88CeLhg++zZs7h16xZkMhmmT5+OhQsXYteuXUhJSUF4eDisrKwQEhICAFAoFIiIiEBUVBQOHjyIM2fO4I033kC3bt2kXaK6dOmCl156CRMnTsSJEydw4sQJTJw4EUFBQfDw8AAA+Pn5wdPTE6GhoThz5gwOHjyImTNnYuLEibC1tQXwcMtauVyO8PBwpKSkYNeuXVi4cGGlO0IRERERETUXDbrG4rfffsOAAQOk1zNmzAAAhIWFITY2Fu+++y4KCwsxefJkZGdno3fv3khISICNjY10zapVq2BqaopRo0ahsLAQgwYNQmxsLExMTKSYrVu3IjIyUto9atiwYTpnZ5iYmCAuLg6TJ09Gv379YGlpiZCQECxfvlyKUSgUSExMxJQpU9CzZ0/Y2dlhxowZUpuJiIiIiJozmeDR0fUqNzcXCoUCOTk50mgIEVFzduXKFQS/PAq9xsyCnUs7vfqb55Nw6KslGPr2Uqjad9Krz077E79uX4K933+Dzp0710eTiYiajer87tpo11gQEREREVHTwcSCiIiIiIiMxsSCiIiIiIiMxsSCiIiIiIiMxsSCiIiIiIiM1qDbzRIRUfOgVquh0WgM1l2/fh1lZWX12yAiIqp1TCyIiKhOqdVqBA4bidz8AoP1xdoiZN3ToLS0tMbPKC0twfXr1yusb9WqFVQqVY3vT0REj8fEgoiI6pRGo0FufgE6DxkLW6WLXn3q7+eQuXdDjUctCvM0SFerMXlaFMzMzAzG2La0RtyeXUwuiIjqEBMLIiKqF7ZKF4MH4OVkphp13+Ki+0ALE3gMDoXSVf/+uXfTcCXxK2g0GiYWRER1iIkFERE9EWwcVAYTFyIiqh/cFYqIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzGxIKIiIiIiIzW6BOL9u3bQyaT6f1MmTIFABAeHq5X16dPH517aLVaTJ06FUqlEtbW1hg2bBju3LmjE5OdnY3Q0FAoFAooFAqEhoZCo9HoxNy6dQvBwcGwtraGUqlEZGQkiouL6/T9ExERERE1BY0+sTh16hTS0tKkn8TERADAa6+9JsW89NJLOjH79+/Xucf06dOxa9cu7NixA8eOHUN+fj6CgoJQVlYmxYSEhODs2bOIj49HfHw8zp49i9DQUKm+rKwMgYGBKCgowLFjx7Bjxw7s3LkTUVFRddwDRERERESNn2lDN+BxHB0ddV4vXrwYTz31FHx9faUyuVwOlUpl8PqcnBysX78emzdvxuDBgwEAW7ZsgZubGw4cOAB/f39cvnwZ8fHxOHHiBHr37g0A+PLLL+Hj44OrV6/Cw8MDCQkJuHTpEm7fvg1XV1cAwIoVKxAeHo4FCxbA1tbW4PO1Wi20Wq30Ojc3t+adQURERETUSDX6EYu/Ky4uxpYtWzB+/HjIZDKp/MiRI3ByckKnTp0wceJEZGRkSHXJyckoKSmBn5+fVObq6govLy8cP34cAJCUlASFQiElFQDQp08fKBQKnRgvLy8pqQAAf39/aLVaJCcnV9jmRYsWSdOrFAoF3NzcjO8IIiIiIqJGpkklFrt374ZGo0F4eLhUFhAQgK1bt+LQoUNYsWIFTp06hYEDB0qjBGq1Gubm5rCzs9O5l7OzM9RqtRTj5OSk9zwnJyedGGdnZ516Ozs7mJubSzGGzJkzBzk5OdLP7du3a/TeiYiIiIgas0Y/Ferv1q9fj4CAAJ1Rg9dff136by8vL/Ts2RPt2rVDXFwcXn755QrvJYTQGfX4+38bE/MouVwOuVxe8ZsiIiIiInoCNJkRiz///BMHDhzAhAkTKo1zcXFBu3btcO3aNQCASqVCcXExsrOzdeIyMjKkEQiVSoX09HS9e2VmZurEPDoykZ2djZKSEr2RDCIiIiKi5qbJJBYbN26Ek5MTAgMDK43LysrC7du34eLiAgDo0aMHzMzMpN2kACAtLQ0pKSno27cvAMDHxwc5OTn49ddfpZiTJ08iJydHJyYlJQVpaWlSTEJCAuRyOXr06FFr75OIiIiIqClqEonFgwcPsHHjRoSFhcHU9L+zt/Lz8zFz5kwkJSXh5s2bOHLkCIKDg6FUKjFy5EgAgEKhQEREBKKionDw4EGcOXMGb7zxBrp16ybtEtWlSxe89NJLmDhxIk6cOIETJ05g4sSJCAoKgoeHBwDAz88Pnp6eCA0NxZkzZ3Dw4EHMnDkTEydOrHBHKCIiIiKi5qJGiUWHDh2QlZWlV67RaNChQwejG/WoAwcO4NatWxg/frxOuYmJCS5cuIDhw4ejU6dOCAsLQ6dOnZCUlAQbGxspbtWqVRgxYgRGjRqFfv36wcrKCnv37oWJiYkUs3XrVnTr1g1+fn7w8/ODt7c3Nm/erPOsuLg4WFhYoF+/fhg1ahRGjBiB5cuX1/r7JSIiIiJqamq0ePvmzZs6h8uV02q1+Ouvv4xu1KP8/PwghNArt7S0xE8//fTY6y0sLLBmzRqsWbOmwhh7e3ts2bKl0vu0bdsW+/bte3yDiYiIiIiamWolFnv27JH++6effoJCoZBel5WV4eDBg2jfvn2tNY6IiIiIiJqGaiUWI0aMAPBw29WwsDCdOjMzM7Rv3x4rVqyotcYREREREVHTUK3E4sGDBwAAd3d3nDp1Ckqlsk4aRURERERETUuN1ljcuHGjtttBRERUZ0pLS3D9+vUK61u1agWVSlWPLSIievLU+OTtgwcP4uDBg8jIyJBGMspt2LDB6IYRERHVhsI8DdLVakyeFgUzMzODMbYtrRG3ZxeTCyIiI9QosYiJicH8+fPRs2dPuLi4QCaT1Xa7iIioCVGr1dBoNAbrrl+/bnAnwfpSXHQfaGECj8GhULq206vPvZuGK4lfQaPRMLEgIjJCjRKLzz77DLGxsQgNDa3t9hARUROjVqsROGwkcvMLDNYXa4uQdU+D0tLSem6ZLhsHFexc9BMLIiKqHTVKLIqLi9G3b9/abgsRETVBGo0GufkF6DxkLGyVLnr1qb+fQ+beDQ06akFERHWvRidvT5gwAdu2bavtthARURNmq3SBnUs7vR9rO8eGbhoREdWDGo1YFBUV4YsvvsCBAwfg7e2ttxhu5cqVtdI4IiIiIiJqGmqUWJw/fx7PPvssACAlJUWnjgu5iYiIiIianxolFocPH67tdhARERERURNWozUWREREREREf1ejEYsBAwZUOuXp0KFDNW4QERERERE1PTVKLMrXV5QrKSnB2bNnkZKSgrCwsNpoFxERERERNSE1SixWrVplsDw6Ohr5+flGNYiIiIiIiJqeWl1j8cYbb2DDhg21eUsiIiIiImoCajWxSEpKgoWFRW3ekoiIiIiImoAaTYV6+eWXdV4LIZCWlobffvsNH374Ya00jIiIiIiImo4aJRYKhULndYsWLeDh4YH58+fDz8+vVhpGRERERERNR42mQm3cuFHnZ/369Vi8eHGtJxXR0dGQyWQ6PyqVSqoXQiA6Ohqurq6wtLTEiy++iIsXL+rcQ6vVYurUqVAqlbC2tsawYcNw584dnZjs7GyEhoZCoVBAoVAgNDQUGo1GJ+bWrVsIDg6GtbU1lEolIiMjUVxcXKvvl4iIiIioqTJqjUVycjK2bNmCrVu34syZM7XVJh1du3ZFWlqa9HPhwgWpbunSpVi5ciXWrl2LU6dOQaVSYciQIcjLy5Nipk+fjl27dmHHjh04duwY8vPzERQUhLKyMikmJCQEZ8+eRXx8POLj43H27FmEhoZK9WVlZQgMDERBQQGOHTuGHTt2YOfOnYiKiqqT90xERERE1NTUaCpURkYGRo8ejSNHjqBVq1YQQiAnJwcDBgzAjh074OjoWHsNNDXVGaUoJ4TA6tWr8f7770trPjZt2gRnZ2ds27YNkyZNQk5ODtavX4/Nmzdj8ODBAIAtW7bAzc0NBw4cgL+/Py5fvoz4+HicOHECvXv3BgB8+eWX8PHxwdWrV+Hh4YGEhARcunQJt2/fhqurKwBgxYoVCA8Px4IFC2Bra1tr75eIiIiIqCmq0YjF1KlTkZubi4sXL+LevXvIzs5GSkoKcnNzERkZWasNvHbtGlxdXeHu7o7Ro0fj+vXrAIAbN25ArVbrTL+Sy+Xw9fXF8ePHATwcUSkpKdGJcXV1hZeXlxSTlJQEhUIhJRUA0KdPHygUCp0YLy8vKakAAH9/f2i1WiQnJ1fafq1Wi9zcXJ0fIiIiIqInTY0Si/j4eHz66afo0qWLVObp6Yl169bhxx9/rLXG9e7dG1999RV++uknfPnll1Cr1ejbty+ysrKgVqsBAM7OzjrXODs7S3VqtRrm5uaws7OrNMbJyUnv2U5OTjoxjz7Hzs4O5ubmUkxFFi1aJK3dUCgUcHNzq0YPEBERERE1DTVKLB48eAAzMzO9cjMzMzx48MDoRpULCAjAK6+8gm7dumHw4MGIi4sD8HDKUzmZTKZzjRBCr+xRj8YYiq9JjCFz5sxBTk6O9HP79u1K44mIiIiImqIaJRYDBw7EtGnTkJqaKpX99ddfeOeddzBo0KBaa9yjrK2t0a1bN1y7dk1ad/HoiEFGRoY0uqBSqVBcXIzs7OxKY9LT0/WelZmZqRPz6HOys7NRUlKiN5LxKLlcDltbW50fIiIiIqInTY0Si7Vr1yIvLw/t27fHU089haeffhru7u7Iy8vDmjVraruNEq1Wi8uXL8PFxQXu7u5QqVRITEyU6ouLi3H06FH07dsXANCjRw+YmZnpxKSlpSElJUWK8fHxQU5ODn799Vcp5uTJk8jJydGJSUlJQVpamhSTkJAAuVyOHj161Nn7JSIiIiJqKmq0K5SbmxtOnz6NxMREXLlyBUIIeHp6Sjsv1ZaZM2ciODgYbdu2RUZGBj766CPk5uYiLCwMMpkM06dPx8KFC9GxY0d07NgRCxcuhJWVFUJCQgA8PMgvIiICUVFRcHBwgL29PWbOnClNrQKALl264KWXXsLEiRPx+eefAwDefPNNBAUFwcPDAwDg5+cHT09PhIaGYtmyZbh37x5mzpyJiRMncgSCiOgJUFpaIm0OYkirVq0M7lBIRET/Va3E4tChQ3j77bdx4sQJ2NraYsiQIRgyZAgAICcnB127dsVnn32G/v3710rj7ty5gzFjxuDu3btwdHREnz59cOLECbRr1w4A8O6776KwsBCTJ09GdnY2evfujYSEBNjY2Ej3WLVqFUxNTTFq1CgUFhZi0KBBiI2NhYmJiRSzdetWREZGSrtHDRs2DGvXrpXqTUxMEBcXh8mTJ6Nfv36wtLRESEgIli9fXivvk4iIGk5hngbpajUmT4syuH4QAGxbWiNuzy4mF0RElahWYrF69eoKv6VXKBSYNGkSVq5cWWuJxY4dOyqtl8lkiI6ORnR0dIUxFhYWWLNmTaVTtOzt7bFly5ZKn9W2bVvs27ev0hgiImp6iovuAy1M4DE4FErXdnr1uXfTcCXxK2g0GiYWRESVqFZice7cOSxZsqTCej8/P36LT0T0BFKr1dBoNAbrrl+/jrKysvptUB2wcVDBzkU/sSAioqqpVmKRnp5e4TAx8PCU7MzMTKMbRUREjYdarUbgsJHIzS8wWF+sLULWPQ1KS0vruWVERNSYVCuxaN26NS5cuICnn37aYP358+fh4uJSKw0jIqLGQaPRIDe/AJ2HjIWtUv/f+NTfzyFz74YnYtSCiIhqrlqJxdChQzF37lwEBATAwsJCp66wsBDz5s1DUFBQrTaQiIgaB1uli8GpQjmZqQaiiYioualWYvHBBx/g+++/R6dOnfD222/Dw8MDMpkMly9fxrp161BWVob333+/rtpKRERERESNVLUSC2dnZxw/fhz/+te/MGfOHAghADzcncnf3x+ffPLJY0+iJiIiIiKiJ0+1D8hr164d9u/fj+zsbPzxxx8QQqBjx46ws7Ori/YREREREVETUKOTtwHAzs4Ozz33XG22hYiIiIiImqgWDd0AIiIiIiJq+phYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0ZhYEBERERGR0UwbugFERNTw1Go1NBqNwbrr16+jrKysfhvUyJSWluD69esV1rdq1QoqlaoeW0RE1PgwsSAiaubUajUCh41Ebn6BwfpibRGy7mlQWlpazy1rHArzNEhXqzF5WhTMzMwMxti2tEbcnl1MLoioWWNiQUTUzGk0GuTmF6DzkLGwVbro1af+fg6Zezc021GL4qL7QAsTeAwOhdK1nV597t00XEn8ChqNhokFETVrjXqNxaJFi/Dcc8/BxsYGTk5OGDFiBK5evaoTEx4eDplMpvPTp08fnRitVoupU6dCqVTC2toaw4YNw507d3RisrOzERoaCoVCAYVCgdDQUL1pAbdu3UJwcDCsra2hVCoRGRmJ4uLiOnnvRET1zVbpAjuXdno/1naODd20RsHGQWWwfwwlY0REzVGjTiyOHj2KKVOm4MSJE0hMTERpaSn8/PxQUKA7XP/SSy8hLS1N+tm/f79O/fTp07Fr1y7s2LEDx44dQ35+PoKCgnS+fQsJCcHZs2cRHx+P+Ph4nD17FqGhoVJ9WVkZAgMDUVBQgGPHjmHHjh3YuXMnoqKi6rYTiIiIiIiagEY9FSo+Pl7n9caNG+Hk5ITk5GS88MILUrlcLq9w+DknJwfr16/H5s2bMXjwYADAli1b4ObmhgMHDsDf3x+XL19GfHw8Tpw4gd69ewMAvvzyS/j4+ODq1avw8PBAQkICLl26hNu3b8PV1RUAsGLFCoSHh2PBggWwtbWtiy4gIiIiImoSGvWIxaNycnIAAPb29jrlR44cgZOTEzp16oSJEyciIyNDqktOTkZJSQn8/PykMldXV3h5eeH48eMAgKSkJCgUCimpAIA+ffpAoVDoxHh5eUlJBQD4+/tDq9UiOTm5wjZrtVrk5ubq/BARERERPWmaTGIhhMCMGTPw/PPPw8vLSyoPCAjA1q1bcejQIaxYsQKnTp3CwIEDodVqATzc7cTc3Bx2dnY693N2doZarZZinJyc9J7p5OSkE+Ps7KxTb2dnB3NzcynGkEWLFknrNhQKBdzc3GrWAUREREREjVijngr1d2+//TbOnz+PY8eO6ZS//vrr0n97eXmhZ8+eaNeuHeLi4vDyyy9XeD8hBGQymfT67/9tTMyj5syZgxkzZkivc3NzmVwQERER0ROnSYxYTJ06FXv27MHhw4fRpk2bSmNdXFzQrl07XLt2DQCgUqlQXFyM7OxsnbiMjAxpBEKlUiE9PV3vXpmZmToxj45MZGdno6SkRG8k4+/kcjlsbW11foiIiIiInjSNOrEQQuDtt9/G999/j0OHDsHd3f2x12RlZeH27dtwcXm4/V+PHj1gZmaGxMREKSYtLQ0pKSno27cvAMDHxwc5OTn49ddfpZiTJ08iJydHJyYlJQVpaWlSTEJCAuRyOXr06FEr75eIiIiIqKlq1FOhpkyZgm3btuGHH36AjY2NNGKgUChgaWmJ/Px8REdH45VXXoGLiwtu3ryJ9957D0qlEiNHjpRiIyIiEBUVBQcHB9jb22PmzJno1q2btEtUly5d8NJLL2HixIn4/PPPAQBvvvkmgoKC4OHhAQDw8/ODp6cnQkNDsWzZMty7dw8zZ87ExIkTOQpBRERERM1eox6x+PTTT5GTk4MXX3wRLi4u0s/XX38NADAxMcGFCxcwfPhwdOrUCWFhYejUqROSkpJgY2Mj3WfVqlUYMWIERo0ahX79+sHKygp79+6FiYmJFLN161Z069YNfn5+8PPzg7e3NzZv3izVm5iYIC4uDhYWFujXrx9GjRqFESNGYPny5fXXIUREREREjVSjHrEQQlRab2lpiZ9++umx97GwsMCaNWuwZs2aCmPs7e2xZcuWSu/Ttm1b7Nu377HPIyJqbNRqNTQajcG669ev6xwYSkREVBONOrEgIiLjqdVqBA4bidz8AoP1xdoiZN3ToLS0tJ5bRkRETxImFkRETziNRoPc/AJ0HjIWtkoXvfrU388hc+8GjloYobS0BNevX6+wvlWrVlCpVPXYIiKi+sfEgoiombBVusDOpZ1eeU5magO05slRmKdBulqNydOiYGZmZjDGtqU14vbsYnJBRE80JhZERERGKC66D7QwgcfgUChd9RO33LtpuJL4FTQaDRMLInqiMbEgIiKqBTYOKoMjQkREzUWj3m6WiIiIiIiaBiYWRERERERkNCYWRERERERkNCYWRERERERkNC7eJiJ6AvBkbSIiamhMLIiImjierE1ERI0BEwsioiaOJ2sTEVFjwMSCiOgJwZO1G6/S0hJcv369wvpWrVrx8DwiavKYWBAREdWhwjwN0tVqTJ4WBTMzM4Mxti2tEbdnF5MLImrSmFgQERHVoeKi+0ALE3gMDoXSVX9EKfduGq4kfgWNRsPEgoiaNCYWRERNAHd9avpsHFQGp6oRET0pmFgQETVy3PWJiIiaAiYWRESNHHd9IiKipoCJBRFRE8Fdn55c3DWKiJ4ETCyIiBoBrqFovrhrFBE9KZhYEBE1MK6haN64axQRPSmYWNTAJ598gmXLliEtLQ1du3bF6tWr0b9//4ZuFhE1UVxDQUDlu0ZxqhQRNQVMLKrp66+/xvTp0/HJJ5+gX79++PzzzxEQEIBLly6hbdu2Dd08ImqkqjLViWsoyBBOlSKipoKJRTWtXLkSERERmDBhAgBg9erV+Omnn/Dpp59i0aJFDdw6Iqqpyn7xB4Di4mKYm5vXqD4zMxNvT3sH94uKDV/LqU5UiapMlUr5cT1Onz6NDh06GL7HYz6/HPEgotrAxKIaiouLkZycjNmzZ+uU+/n54fjx4wav0Wq10Gq10uucnBwAQG5ubt01lBqlrKwsZGVlVVgvk8kghGB9A9TfvXsX/2/2e7hfqDVYX1pagqy7d6F0dIKJiUm164uLi3AvOwfeg19DSztHvfp7t/8PGUk/4u6d/4Mo1U8+ctLvQIgHyE67iRZCfzoU65tHfWlxEUqK7uvV52dnQp2WhremToeZqf6IxuM+nwBgKTfH8qWLoFQqDdY/7u9XVWJYb1y9g4MDHBwcKqwnqivlv7M+7t8AAJCJqkQRACA1NRWtW7fG//7v/6Jv375S+cKFC7Fp0yZcvXpV75ro6GjExMTUZzOJiIiIiGrV7du30aZNm0pjOGJRAzKZTOe1EEKvrNycOXMwY8YM6fWDBw9w7949ODg4VHhNY5Sbmws3Nzfcvn0btra2Dd2cJxb7ue6xj+sH+7nusY/rB/u57rGP654xfSyEQF5eHlxdXR8by8SiGpRKJUxMTKBWq3XKMzIy4OzsbPAauVwOuVyuU9aqVau6amKds7W15V/6esB+rnvs4/rBfq577OP6wX6ue+zjulfTPlYoFFWKa1HtOzdj5ubm6NGjBxITE3XKExMTdaZGERERERE1NxyxqKYZM2YgNDQUPXv2hI+PD7744gvcunULb731VkM3jYiIiIiowTCxqKbXX38dWVlZmD9/PtLS0uDl5YX9+/ejXTvDhxo9KeRyOebNm6c3rYtqF/u57rGP6wf7ue6xj+sH+7nusY/rXn31MXeFIiIiIiIio3GNBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRFRFYwcORKWlpbQaDQVxvzzn/+EmZkZ0tPTq3xfmUyG6Oho4xtYxftfunQJ0dHRuHnzZq0+Jzw8HC1btqxRm6pi//79ddpPVHULFy7E7t27DdZ98MEHCAoKQuvWrSGTyRAeHl6vbSOihsXEgoioCiIiIlBUVIRt27YZrM/JycGuXbsQFBQEZ2fnem5dxZKSkjBhwgTp9aVLlxATE1PriYUxbaqK/fv3IyYmpo5aRNVRWWKxatUqZGVlYdiwYTA3N6/fhhFRgzNt6AYQETUFAQEBcHV1xYYNGzB58mS9+u3bt6OwsBAREREN0LqK9enTp6GboKcxtulxCgsLYWFhAZlM1tBNaTCFhYWwtLSsNCYvLw8tWjz8znLz5s310SwiakQ4YkFEVAUmJiYICwtDcnIyLly4oFe/ceNGuLi4ICAgAACgVqsxadIktGnTBubm5nB3d0dMTAxKS0sf+6yUlBQMHz4cdnZ2sLCwwLPPPotNmzbpxWk0GkRFRaFDhw6Qy+VwcnLC0KFDceXKFSnm79OOYmNj8dprrwEABgwYAJlMBplMhtjYWPz73/+Gqakpbt++rfec8ePHw8HBAUVFRY9t+x9//IGhQ4eiZcuWcHNzQ1RUFLRarU7Mo1Oh7t+/j5kzZ8Ld3R0WFhawt7dHz549sX37dgAPp1mtW7dOurb8p3zUpaioCHPmzIG7uzvMzc3RunVrTJkyRW/amlarRVRUFFQqFaysrPDCCy8gOTkZ7du315myExsbC5lMhoSEBIwfPx6Ojo6wsrKCVqvFH3/8gXHjxqFjx46wsrJC69atERwcrPeZOHLkCGQyGbZt24ZZs2bBxcUFLVu2RHBwMNLT05GXl4c333wTSqUSSqUS48aNQ35+/mP715Du3bujf//+euVlZWVo3bo1Xn75ZamsuLgYH330ETp37gy5XA5HR0eMGzcOmZmZOte2b98eQUFB+P7779G9e3dYWFggJiYGMpkMBQUF2LRpk/Tn8OKLL0rXlScVRNQ8ccSCiKiKxo8fj8WLF2PDhg1YtWqVVH7p0iX8+uuvmD17NkxMTKBWq9GrVy+0aNECc+fOxVNPPYWkpCR89NFHuHnzJjZu3FjhM65evYq+ffvCyckJ//nPf+Dg4IAtW7YgPDwc6enpePfddwE8/Gb4+eefx82bNzFr1iz07t0b+fn5+Pnnn5GWlobOnTvr3TswMBALFy7Ee++9h3Xr1uEf//gHAOCpp56CEAILFizA559/jo8++ki65t69e9ixYwfefvttWFhYVNo/JSUlGDZsGCIiIhAVFYWff/4Z//73v6FQKDB37twKr5sxYwY2b96Mjz76CN27d0dBQQFSUlKQlZUFAPjwww9RUFCA7777DklJSdJ1Li4uEEJgxIgROHjwIObMmYP+/fvj/PnzmDdvHpKSkpCUlAS5XA4AGDduHL7++mu8++67GDhwIC5duoSRI0ciNzfXYLvGjx+PwMBAbN68GQUFBTAzM0NqaiocHBywePFiODo64t69e9i0aRN69+6NM2fOwMPDQ+ce7733HgYMGIDY2FjcvHkTM2fOxJgxY2BqaopnnnkG27dvx5kzZ/Dee+/BxsYG//nPf6Rro6OjERMTg8OHD+v88v6ocePGYdq0abh27Ro6duwolSckJCA1NRXjxo0DADx48ADDhw/HL7/8gnfffRd9+/bFn3/+iXnz5uHFF1/Eb7/9pjMicfr0aVy+fBkffPAB3N3dYW1tjREjRmDgwIEYMGAAPvzwQwCAra1thW0jomZGEBFRlfn6+gqlUimKi4ulsqioKAFA/P7770IIISZNmiRatmwp/vzzT51rly9fLgCIixcvSmUAxLx586TXo0ePFnK5XNy6dUvn2oCAAGFlZSU0Go0QQoj58+cLACIxMbHS9j56/2+//VYAEIcPH9aLDQsLE05OTkKr1UplS5YsES1atBA3btyo9DlhYWECgPjmm290yocOHSo8PDwqbZOXl5cYMWJEpfefMmWKMPR/WfHx8QKAWLp0qU75119/LQCIL774QgghxMWLFwUAMWvWLJ247du3CwAiLCxMKtu4caMAIMaOHVtpm4QQorS0VBQXF4uOHTuKd955Ryo/fPiwACCCg4N14qdPny4AiMjISJ3yESNGCHt7e52ymJgYYWJiIo4cOVJpG+7evSvMzc3Fe++9p1M+atQo4ezsLEpKSnTe686dO3XiTp06JQCITz75RCpr166dMDExEVevXtV7nrW1tU5/VaSqcUT05OCYJRFRNURERODu3bvYs2cPAKC0tBRbtmxB//79pW+L9+3bhwEDBsDV1RWlpaXST/k0qaNHj1Z4/0OHDmHQoEFwc3PTKQ8PD8f9+/elb+x//PFHdOrUCYMHD6619zZt2jRkZGTg22+/BfDwG+5PP/0UgYGBaN++/WOvl8lkCA4O1inz9vbGn3/+Wel1vXr1wo8//ojZs2fjyJEjKCwsrHKbDx06BAB6uw+99tprsLa2xsGDBwH8t89HjRqlE/fqq6/C1NTw4P0rr7yiV1ZaWoqFCxfC09MT5ubmMDU1hbm5Oa5du4bLly/rxQcFBem87tKlC4CHo0ePlt+7d09nOtTcuXNRWloKX19fg+0r5+DggODgYGzatAkPHjwAAGRnZ+OHH37A2LFjpfe3b98+tGrVCsHBwTqfy2effRYqlQpHjhzRua+3tzc6depU6bOJiP6OiQURUTW8+uqrUCgU0nSm/fv3Iz09XWfRdnp6Ovbu3QszMzOdn65duwIA7t69W+H9s7Ky4OLiolfu6uoq1QNAZmYm2rRpU2vvC/jvXP3y9Qz79u3DzZs38fbbb1fpeisrK73pUnK5/LFrM/7zn/9g1qxZ2L17NwYMGAB7e3uMGDEC165de+wzs7KyYGpqCkdHR51ymUwGlUol9Vf5/z66Y5epqSkcHBwM3tvQn8OMGTPw4YcfYsSIEdi7dy9OnjyJU6dO4ZlnnjGYENnb2+u8Lt8pqaLyqqxjMWT8+PH466+/kJiYCODhZgJarVYn4UpPT4dGo4G5ubneZ1OtVut9Lg29fyKiynCNBRFRNVhaWmLMmDH48ssvkZaWhg0bNsDGxkZaFA0ASqUS3t7eWLBggcF7lCcJhjg4OCAtLU2vPDU1Vbo3ADg6OuLOnTvGvBWDIiMj8dprr+H06dNYu3YtOnXqhCFDhtT6c/7O2toaMTExiImJQXp6ujR6ERwcrLMQ3RAHBweUlpYiMzNTJ7kQQkCtVuO5556T4oCHv1y3bt1aiistLZWSjkcZ2gFqy5YtGDt2LBYuXKhTfvfuXbRq1apK77cu+Pv7w9XVFRs3boS/vz82btyI3r17w9PTU4pRKpVwcHBAfHy8wXvY2NjovG7OO2ARUc1wxIKIqJoiIiJQVlaGZcuWYf/+/Rg9ejSsrKyk+qCgIKSkpOCpp55Cz5499X4qSywGDRqEQ4cOSYlEua+++gpWVlbSVq0BAQH4/fffpalAVVW+kLmi6UYjR45E27ZtERUVhQMHDmDy5Mn1+gums7MzwsPDMWbMGFy9ehX379+vtN2DBg0C8PAX/r/buXMnCgoKpPoXXngBAPD111/rxH333XdV2qmrnEwmk9pSLi4uDn/99VeV71EXTExMEBoait27d+OXX37Bb7/9hvHjx+vEBAUFISsrC2VlZQY/l48uPK+IXC6v1nQ1Imo+OGJBRFRNPXv2hLe3N1avXg0hhN7ZFfPnz0diYiL69u2LyMhIeHh4oKioCDdv3sT+/fvx2WefVTiNad68edIajblz58Le3h5bt25FXFwcli5dCoVCAQCYPn06vv76awwfPhyzZ89Gr169UFhYiKNHjyIoKAgDBgwweH8vLy8AwBdffAEbGxtYWFjA3d1d+kbfxMQEU6ZMwaxZs2BtbV0vJyf37t0bQUFB8Pb2hp2dHS5fvozNmzfDx8dHSti6desGAFiyZAkCAgJgYmICb29vDBkyBP7+/pg1axZyc3PRr18/aVeo7t27IzQ0FADQtWtXjBkzBitWrICJiQkGDhyIixcvYsWKFVAoFFXeJjUoKAixsbHo3LkzvL29kZycjGXLltX6tDTg4edo/vz5OHjw4GPXWQAPp0MtWbIEISEhsLS0xOuvv65TP3r0aGzduhVDhw7FtGnT0KtXL5iZmeHOnTs4fPgwhg8fjpEjRz72Od26dcORI0ewd+9euLi4wMbGRkpKjh49Km1dW1ZWhj///BPfffcdAMDX11dvyhoRPWEaevU4EVFT9PHHHwsAwtPT02B9ZmamiIyMFO7u7sLMzEzY29uLHj16iPfff1/k5+dLcXhkhyQhhLhw4YIIDg4WCoVCmJubi2eeeUZs3LhR7xnZ2dli2rRpom3btsLMzEw4OTmJwMBAceXKlUrvv3r1auHu7i5MTEwEAL1737x5UwAQb731VpX7IywsTFhbW+uVz5s3T283p0fbNHv2bNGzZ09hZ2cn5HK56NChg3jnnXfE3bt3pRitVismTJggHB0dhUwmEwCknaoKCwvFrFmzRLt27YSZmZlwcXER//rXv0R2drbOc4uKisSMGTOEk5OTsLCwEH369BFJSUlCoVDo7OhUvivUqVOn9N5Pdna2iIiIEE5OTsLKyko8//zz4pdffhG+vr7C19dXiivfFerbb7/Vub6ie5f3U2Zmpl6ZoR28KtK3b18BQPzzn/80WF9SUiKWL18unnnmGWFhYSFatmwpOnfuLCZNmiSuXbsmxbVr104EBgYavMfZs2dFv379hJWVlQCg8759fX0FAIM/1XkfRNQ0yYQQol4zGSIiatTWrFmDyMhIpKSkSAvOn1THjx9Hv379sHXrVoSEhDR0c4iImjQmFkREBAA4c+YMbty4gUmTJqFfv37YvXt3QzepViUmJiIpKQk9evSApaUlzp07h8WLF0OhUOD8+fOPPQCQiIgqx8SCiIgAAO3bt4darUb//v2xefNmqFSqhm5SrTp58iSioqJw6dIl5OXlQalUwt/fH4sWLeLWqkREtYCJBRERERERGY3bzRIRERERkdGYWBARERERkdF4jkU9e/DgAVJTU2FjY8NTTYmIiIioURNCIC8vD66uro8984eJRT1LTU2Fm5tbQzeDiIiIiKjKbt++/djDQJlY1DMbGxsAD/9wbG1tG7g1REREREQVy83NhZubm/Q7bGWYWNSz8ulPtra2TCyIiIiIqEmoyhR+Lt4mIiIiIiKjMbEgIiIiIiKjMbEgIiIiIiKjcY0FERHVOrVaDY1GI71u1aoVVCpVwzWIiIjqHBMLIiKqFeXJRGZmJt6e9g7uFxVLdbYtrRG3ZxeTCyKiJxgTCyIiMpparUbgsJHIzS9AsbYIWfc06P/PGbB3dkPu3TRcSfwKGo2GiQUR0ROMayyIiMhoGo0GufkF6DxkLDr0HYEH4gGsWznBzqUdbJUuDd08IiKqBxyxICKiWmOrdIEQoqGbQUREDYAjFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDQmFkREREREZDTThm4AERE9+UpLS3D9+nUAQKtWraBSqRq4RUREVNuYWBARUZ0qzNMgXa3G5GlRMDMzg21La8Tt2cXkgojoCcOpUEREVKeKi+4DLUzgMTgUnYeMRW5+ATQaTUM3i4iIahlHLIiIqF7YOKggl8sbuhlERFRHOGJBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGY2JBRERERERGa9DE4ueff0ZwcDBcXV0hk8mwe/dunXohBKKjo+Hq6gpLS0u8+OKLuHjxok6MVqvF1KlToVQqYW1tjWHDhuHOnTs6MdnZ2QgNDYVCoYBCoUBoaKjeVoe3bt1CcHAwrK2toVQqERkZieLiYp2YCxcuwNfXF5aWlmjdujXmz58PIUSt9QcRERERUVPVoIlFQUEBnnnmGaxdu9Zg/dKlS7Fy5UqsXbsWp06dgkqlwpAhQ5CXlyfFTJ8+Hbt27cKOHTtw7Ngx5OfnIygoCGVlZVJMSEgIzp49i/j4eMTHx+Ps2bMIDQ2V6svKyhAYGIiCggIcO3YMO3bswM6dOxEVFSXF5ObmYsiQIXB1dcWpU6ewZs0aLF++HCtXrqyDniEiIiIialoa9ByLgIAABAQEGKwTQmD16tV4//338fLLLwMANm3aBGdnZ2zbtg2TJk1CTk4O1q9fj82bN2Pw4MEAgC1btsDNzQ0HDhyAv78/Ll++jPj4eJw4cQK9e/cGAHz55Zfw8fHB1atX4eHhgYSEBFy6dAm3b9+Gq6srAGDFihUIDw/HggULYGtri61bt6KoqAixsbGQy+Xw8vLC77//jpUrV2LGjBmQyWQG34dWq4VWq5Ve5+bm1lr/ERERERE1Fo12jcWNGzegVqvh5+cnlcnlcvj6+uL48eMAgOTkZJSUlOjEuLq6wsvLS4pJSkqCQqGQkgoA6NOnDxQKhU6Ml5eXlFQAgL+/P7RaLZKTk6UYX19fncOd/P39kZqaips3b1b4PhYtWiRNwVIoFHBzczOiV4iIiIiIGqdGm1io1WoAgLOzs065s7OzVKdWq2Fubg47O7tKY5ycnPTu7+TkpBPz6HPs7Oxgbm5eaUz56/IYQ+bMmYOcnBzp5/bt25W/cSIiIiKiJqhBp0JVxaNTjIQQFU47qijGUHxtxJQv3K6sPXK5XGeUg4iIiIjoSdRoRyxUKhUA/dGAjIwMaaRApVKhuLgY2dnZlcakp6fr3T8zM1Mn5tHnZGdno6SkpNKYjIwMAPqjKkREREREzU2jTSzc3d2hUqmQmJgolRUXF+Po0aPo27cvAKBHjx4wMzPTiUlLS0NKSooU4+Pjg5ycHPz6669SzMmTJ5GTk6MTk5KSgrS0NCkmISEBcrkcPXr0kGJ+/vlnnS1oExIS4Orqivbt29d+BxARERERNSENmljk5+fj7NmzOHv2LICHC7bPnj2LW7duQSaTYfr06Vi4cCF27dqFlJQUhIeHw8rKCiEhIQAAhUKBiIgIREVF4eDBgzhz5gzeeOMNdOvWTdolqkuXLnjppZcwceJEnDhxAidOnMDEiRMRFBQEDw8PAICfnx88PT0RGhqKM2fO4ODBg5g5cyYmTpwIW1tbAA+3rJXL5QgPD0dKSgp27dqFhQsXVrojFBERERFRc9Ggayx+++03DBgwQHo9Y8YMAEBYWBhiY2Px7rvvorCwEJMnT0Z2djZ69+6NhIQE2NjYSNesWrUKpqamGDVqFAoLCzFo0CDExsbCxMREitm6dSsiIyOl3aOGDRumc3aGiYkJ4uLiMHnyZPTr1w+WlpYICQnB8uXLpRiFQoHExERMmTIFPXv2hJ2dHWbMmCG1mYiIiIioOWvQxOLFF1+s9ORqmUyG6OhoREdHVxhjYWGBNWvWYM2aNRXG2NvbY8uWLZW2pW3btti3b1+lMd26dcPPP/9caQwRERERUXPUaNdYEBERERFR08HEgoiIiIiIjMbEgoiIiIiIjFajxKJDhw7IysrSK9doNOjQoYPRjSIiIiIioqalRou3b968ibKyMr1yrVaLv/76y+hGERFR46dWq6HRaAAA169fN/j/C0RE1HxUK7HYs2eP9N8//fQTFAqF9LqsrAwHDx7kYXFERM2AWq1G4LCRyM0vAAAUa4uQdU+D0tLSBm4ZERE1lGolFiNGjADwcBvYsLAwnTozMzO0b98eK1asqLXGERFR46TRaJCbX4DOQ8bCVumC1N/PIXPvBo5aEBE1Y9VKLB48eAAAcHd3x6lTp6BUKuukUURE1DTYKl1g59IOOZmpDd0UIiJqYDVaY3Hjxo3abgcRERERETVhNT55++DBgzh48CAyMjKkkYxyGzZsMLphRERERETUdNQosYiJicH8+fPRs2dPuLi4QCaT1Xa7iIiIiIioCalRYvHZZ58hNjYWoaGhtd0eIiIiIiJqgmp0QF5xcTH69u1b220hIiIiIqImqkaJxYQJE7Bt27babgsRERERETVRNZoKVVRUhC+++AIHDhyAt7c3zMzMdOpXrlxZK40jIiIiIqKmoUaJxfnz5/Hss88CAFJSUnTquJCbiIiIiKj5qVFicfjw4dpuBxERERERNWE1WmNBRERERET0dzUasRgwYEClU54OHTpU4wYREREREVHTU6PEonx9RbmSkhKcPXsWKSkpCAsLq412ERERERFRE1KjxGLVqlUGy6Ojo5Gfn29Ug4iIiIiIqOmp1TUWb7zxBjZs2FCbtyQioidMaWkJrl+/jitXruDKlStQq9UN3SQiIqoFNRqxqEhSUhIsLCxq85ZERPQEKczTIF2txuRpUdIZSLYtrRG3ZxdUKlUDt46IiIxRo8Ti5Zdf1nkthEBaWhp+++03fPjhh7XSMCIievIUF90HWpjAY3AolK7tkHs3DVcSv4JGo2FiQUTUxNUosVAoFDqvW7RoAQ8PD8yfPx9+fn610jAiInpy2TioYOfSrqGbQUREtahGicXGjRtrux1ERERERNSEGbXGIjk5GZcvX4ZMJoOnpye6d+9eW+0iIiIiIqImpEaJRUZGBkaPHo0jR46gVatWEEIgJycHAwYMwI4dO+Do6Fjb7SQiIiIiokasRtvNTp06Fbm5ubh48SLu3buH7OxspKSkIDc3F5GRkbXdRiIiIiIiauRqNGIRHx+PAwcOoEuXLlKZp6cn1q1bx8XbRERERETNUI1GLB48eCDtP/53ZmZmePDggdGNIiIiIiKipqVGicXAgQMxbdo0pKamSmV//fUX3nnnHQwaNKjWGkdERERERE1DjRKLtWvXIi8vD+3bt8dTTz2Fp59+Gu7u7sjLy8OaNWtqu41ERERERNTI1WiNhZubG06fPo3ExERcuXIFQgh4enpi8ODBtd0+IiIiIiJqAqo1YnHo0CF4enoiNzcXADBkyBBMnToVkZGReO6559C1a1f88ssvddJQIiIiIiJqvKqVWKxevRoTJ06Era2tXp1CocCkSZOwcuXKWmscERERERE1DdVKLM6dO4eXXnqpwno/Pz8kJycb3SgiIiIiImpaqpVYpKenG9xmtpypqSkyMzONbhQRERERETUt1UosWrdujQsXLlRYf/78ebi4uBjdKCIiIiIialqqlVgMHToUc+fORVFRkV5dYWEh5s2bh6CgoFprXHR0NGQymc6PSqWS6oUQiI6OhqurKywtLfHiiy/i4sWLOvfQarWYOnUqlEolrK2tMWzYMNy5c0cnJjs7G6GhoVAoFFAoFAgNDYVGo9GJuXXrFoKDg2FtbQ2lUonIyEgUFxfX2nslIiIiImrKqpVYfPDBB/9fe3ceV1W1/w38c2Q4DMKR+YApoNcwcwxTwZwHIsGpm6VeBEWzTJHEx6lboje1nJ80K7sJ5oS/Ms0pgpz9iUokKYJmFwdMDshwmAQOw3r+8GFfjwwCBzign/frdV7XvfZ37/09y52XL2uvtZGVlYXnn38eq1evxo8//oiDBw/i008/hZubG7KysvDBBx80aIIvvvgiUlNTpc+jIyarV6/G+vXrsXnzZsTGxkKpVGLEiBHIy8uTYoKDg7F//35ERETg7NmzyM/Ph4+PD8rKyqSYSZMmIT4+HpGRkYiMjER8fDz8/Pyk/WVlZRg1ahQKCgpw9uxZREREYN++fQgJCWnQ70pE1NypVCpcu3YNycnJWv+OEhER1ek9Fg4ODjh37hzeffddLF68GEIIAIBMJoOXlxe2bNkCBweHhk3Q0FBrlKKCEAIbN27EBx98gPHjxwMAtm/fDgcHB+zevRszZ85ETk4OvvnmG+zYsUN6x8bOnTvRrl07/PLLL/Dy8kJSUhIiIyNx/vx59O3bFwDw9ddfw8PDA9evX4ebmxuioqKQmJiIlJQUODk5AQDWrVuHgIAArFixospVsioUFxejuLhY2q5YqpeIqKVRqVQYNXoccvMLoCkuQmaWGqWlpfpOi4iImok6v3nb2dkZR48eRUZGBi5cuIDz588jIyMDR48ehYuLS4MneOPGDTg5OcHV1RVvvfUWkpOTAQA3b96ESqXCyJEjpVi5XI5Bgwbh3LlzAIC4uDiUlJRoxTg5OaFr165STExMDBQKhVRUAEC/fv2gUCi0Yrp27SoVFQDg5eWF4uLiJ66CtWrVKukRK4VCgXbt2unYI0RE+qFWq5GbX4DOI6agg+dYlItyjloQEZGkzoVFBSsrK7z88svo06cPrKysGjInSd++ffHtt9/i559/xtdffw2VSgVPT09kZmZCpVIBQKUREgcHB2mfSqWCsbFxpfwej7G3t690bXt7e62Yx69jZWUFY2NjKaY6ixcvRk5OjvRJSUmpQw8QETU/lraOMLey03caRETUzNTpUaim5u3tLf25W7du8PDwQMeOHbF9+3b069cPwMPHsB4lhKjU9rjHY6qKr09MVeRyOeRyeY0xREREREQtXb1HLPTB3Nwc3bp1w40bN6R5F4+PGKSnp0ujC0qlEhqNBtnZ2TXGpKWlVbrW/fv3tWIev052djZKSkoafE4JEREREVFL1KIKi+LiYiQlJcHR0RGurq5QKpWIjo6W9ms0Gpw6dQqenp4AAHd3dxgZGWnFpKamIiEhQYrx8PBATk4OLl68KMVcuHABOTk5WjEJCQlITU2VYqKioiCXy+Hu7t6o35mI6GlXWlqC5ORkXLt27YmPlxIRUfPVrB+Fmj9/Pnx9fdG+fXukp6fj448/Rm5uLvz9/SGTyRAcHIyVK1eiU6dO6NSpE1auXAkzMzNMmjQJAKBQKBAYGIiQkBDY2NjA2toa8+fPR7du3aRVol544QW8+uqrmDFjBr766isAwNtvvw0fHx+4ubkBAEaOHIkuXbrAz88Pa9asQVZWFubPn48ZM2bUuCIUERHVrDBPjTSVCrPmhsDIyAiWrc1x5OD+KlcDJCKi5q1ZFxZ3797FxIkTkZGRATs7O/Tr1w/nz5+Hs7MzAGDBggUoLCzErFmzkJ2djb59+yIqKgoWFhbSOTZs2ABDQ0NMmDABhYWFGDZsGMLDw2FgYCDF7Nq1C0FBQdLqUaNHj8bmzZul/QYGBjhy5AhmzZqF/v37w9TUFJMmTcLatWubqCeIiJ5OmqIHQCsDuA33g7GxMa5Ffwu1Ws3CgoioBWrWhUVERESN+2UyGUJDQxEaGlptjImJCTZt2oRNmzZVG2NtbY2dO3fWeK327dvj8OHDNcYQEVH9WNgoudAFEVEL16LmWBARERERUfPEwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHTGwoKIiIiIiHRmqO8EiIiIKpSWliA5OVnabtOmDZRKpR4zIiKi2mJhQURE1VKpVFCr1QCA5ORklJWVNdq1CvPUSFOpMGtuCIyMjAAAlq3NceTgfhYXREQtAAsLIiKqkkqlwqjR45CbXwAA0BQXITNLjdLS0ka5nqboAdDKAG7D/WDr5IzcjFRci/4WarWahQURUQvAwoKIiKqkVquRm1+AziOmwNLWEff++B33D21r1FELALCwUcLK0blRr0FERA2Pk7eJiKhGlraOsHJ0hrmVnb5TISKiZoyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6Yxv3iYiomartLQEycnJAIA2bdpAqVTqOSMiIqoOCwsiImqWCvPUSFOpMGtuCIyMjGDZ2hxHDu5ncUFE1EyxsCAiIi0qlQpqtRrJyckoKyvTWx6aogdAKwO4DfeDsbExrkV/C7VazcKCiKiZYmFBREQSlUqFUaPHITe/AJriImRmqVFaWqrXnCxslJDL5XrNgYiInoyTt4mISKJWq5GbX4DOI6agg+dYlItyvY5aEBFRy8ERCyIiqsTS1hFCCH2nQURELQgLCyIiahEeXSEK4CpRRETNDQsLIqJnXMVkbQB6n7BdncdXiALAVaKIiJoZFhZERM+wRydrA2g2E7Yf9+gKUbZOzsjNSOUqUUREzQwLCyKiZ9ijk7UtbR1x74/fcf/QtmY5agE8XCHKytFZ32kQEVEVWFgQEREsbR1h5eiMnPv39J1KrfGt3EREzQsLCyKiZ1BzeQleffGt3EREzQ8Li3rYsmUL1qxZg9TUVLz44ovYuHEjBgwYoO+0iIiq9egE7fv372P23PfxoEjTbOdUPMnjb+VO+Okb/Pbbb+jQoQMAjmAQEekDC4s62rt3L4KDg7Flyxb0798fX331Fby9vZGYmIj27dvrOz0iIklFMfFoIQH8d4L2gMnzUJST1aznVDyJhY0S5ZrCSitGmcqN8PlnG2FnZ8cig4ioibCwqKP169cjMDAQ06dPBwBs3LgRP//8M7744gusWrWqUnxxcTGKi4ul7ZycHABAbm5u0yRMRA0uMzMTmZmZAACZTKb1IrlHt/W5LyMjA/9n0RI8KCyGRlOErOwcdB/+Blpb2SEr5T9Ij/kJmsIHKNUUQ4hyZKfeQitRhpy0u9K2Jj+n5eyTyeDQbRAsbeyRk3YXV078gMkBgTAyNIKp3BhrV6+Cra1ts/o70sc+Gxsb2NjYgIiotip+Zq3NS1Nlgq9WrTWNRgMzMzN89913GDdunNQ+d+5cxMfH49SpU5WOCQ0NxbJly5oyTSIiIiKiBpWSkoLnnnuuxhiOWNRBRkYGysrK4ODgoNXu4OAAlUpV5TGLFy/GvHnzpO3y8nJkZWXBxsYGMpmsUfNtSLm5uWjXrh1SUlJgaWmp73SeWuznxsc+bhrs58bHPm4a7OfGxz5ufLr0sRACeXl5cHJyemIsC4t6eLwgEEJUWyTI5XLI5XKttjZt2jRWao3O0tKS/9E3AfZz42MfNw32c+NjHzcN9nPjYx83vvr2sUKhqFVcqzqf+Rlma2sLAwODSqMT6enplUYxiIiIiIieJSws6sDY2Bju7u6Ijo7Wao+Ojoanp6eesiIiIiIi0j8+ClVH8+bNg5+fH3r37g0PDw9s3boVd+7cwTvvvKPv1BqVXC7H0qVLKz3WRQ2L/dz42MdNg/3c+NjHTYP93PjYx42vqfqYq0LVw5YtW7B69Wqkpqaia9eu2LBhAwYOHKjvtIiIiIiI9IaFBRERERER6YxzLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIamHcuHEwNTWFWq2uNmby5MkwMjJCWlparc8rk8kQGhqqe4K1PH9iYiJCQ0Nx69atBr1OQEAAWrduXa+cauPo0aON2k9UeytXrsSBAwcqtcfFxeG9995Dt27dYGFhAQcHBwwfPhzHjx9v+iSJSC9YWBAR1UJgYCCKioqwe/fuKvfn5ORg//798PHxgYODQxNnV72YmBhMnz5d2k5MTMSyZcsavLDQJafaOHr0KJYtW9ZIGVFdVFdY7NmzBxcvXsS0adPw448/4t///jfkcjmGDRuGb7/9tukTJaImZ6jvBIiIWgJvb284OTlh27ZtmDVrVqX9e/bsQWFhIQIDA/WQXfX69eun7xQqaY45PUlhYSFMTEwgk8n0nYreFBYWwtTUtNr9CxYswNq1a7XaXnvtNbz00ktYvnw5pkyZ0tgpEpGeccSCiKgWDAwM4O/vj7i4OFy5cqXS/rCwMDg6OsLb2xsAoFKpMHPmTDz33HMwNjaGq6srli1bhtLS0ideKyEhAWPGjIGVlRVMTEzQs2dPbN++vVKcWq1GSEgIOnToALlcDnt7e7z22mu4du2aFPPoY0fh4eF44403AABDhgyBTCaDTCZDeHg4/vWvf8HQ0BApKSmVrjNt2jTY2NigqKjoibn/+eefeO2119C6dWu0a9cOISEhKC4u1op5/FGoBw8eYP78+XB1dYWJiQmsra3Ru3dv7NmzB8DDx6w+//xz6diKT8WoS1FRERYvXgxXV1cYGxujbdu2eO+99yo9tlZcXIyQkBAolUqYmZlh4MCBiIuLg4uLCwICAqS48PBwyGQyREVFYdq0abCzs4OZmRmKi4vx559/YurUqejUqRPMzMzQtm1b+Pr6VronTp48CZlMht27d2PhwoVwdHRE69at4evri7S0NOTl5eHtt9+Gra0tbG1tMXXqVOTn5z+xf6vSq1cvDBgwoFJ7WVkZ2rZti/Hjx0ttGo0GH3/8MTp37gy5XA47OztMnToV9+/f1zrWxcUFPj4++OGHH9CrVy+YmJhg2bJlkMlkKCgowPbt26W/h8GDBwMA7O3tK+VgYGAAd3f3Ku8rInr6cMSCiKiWpk2bhk8++QTbtm3Dhg0bpPbExERcvHgRixYtgoGBAVQqFfr06YNWrVrho48+QseOHRETE4OPP/4Yt27dQlhYWLXXuH79Ojw9PWFvb4/PPvsMNjY22LlzJwICApCWloYFCxYAAPLy8vDKK6/g1q1bWLhwIfr27Yv8/HycPn0aqamp6Ny5c6Vzjxo1CitXrsSSJUvw+eef46WXXgIAdOzYEUIIrFixAl999RU+/vhj6ZisrCxERERg9uzZMDExqbF/SkpKMHr0aAQGBiIkJASnT5/Gv/71LygUCnz00UfVHjdv3jzs2LEDH3/8MXr16oWCggIkJCQgMzMTAPDhhx+ioKAA33//PWJiYqTjHB0dIYTA2LFjcezYMSxevBgDBgzA5cuXsXTpUsTExCAmJgZyuRwAMHXqVOzduxcLFizA0KFDkZiYiHHjxiE3N7fKvKZNm4ZRo0Zhx44dKCgogJGREe7duwcbGxt88sknsLOzQ1ZWFrZv346+ffvi0qVLcHNz0zrHkiVLMGTIEISHh+PWrVuYP38+Jk6cCENDQ/To0QN79uzBpUuXsGTJElhYWOCzzz6Tjg0NDcWyZctw4sQJ6Yf3qkydOhVz587FjRs30KlTJ6k9KioK9+7dw9SpUwEA5eXlGDNmDM6cOYMFCxbA09MTt2/fxtKlSzF48GD8+uuvWiMSv/32G5KSkvDPf/4Trq6uMDc3x9ixYzF06FAMGTIEH374IQDA0tKy2txKS0tx5swZvPjii9XGENFTRBARUa0NGjRI2NraCo1GI7WFhIQIAOKPP/4QQggxc+ZM0bp1a3H79m2tY9euXSsAiKtXr0ptAMTSpUul7bfeekvI5XJx584drWO9vb2FmZmZUKvVQgghli9fLgCI6OjoGvN9/PzfffedACBOnDhRKdbf31/Y29uL4uJiqe3TTz8VrVq1Ejdv3qzxOv7+/gKA+J//+R+t9tdee024ubnVmFPXrl3F2LFjazz/e++9J6r6v6zIyEgBQKxevVqrfe/evQKA2Lp1qxBCiKtXrwoAYuHChVpxe/bsEQCEv7+/1BYWFiYAiClTptSYkxBClJaWCo1GIzp16iTef/99qf3EiRMCgPD19dWKDw4OFgBEUFCQVvvYsWOFtbW1VtuyZcuEgYGBOHnyZI05ZGRkCGNjY7FkyRKt9gkTJggHBwdRUlKi9V337dunFRcbGysAiC1btkhtzs7OwsDAQFy/fr3S9czNzbX6qyYffPCBACAOHDhQq3giatn4KBQRUR0EBgYiIyMDBw8eBPDwN7I7d+7EgAEDpN8WHz58GEOGDIGTkxNKS0ulT8VjUqdOnar2/MePH8ewYcPQrl07rfaAgAA8ePBA+o39Tz/9hOeffx7Dhw9vsO82d+5cpKen47vvvgPw8DfcX3zxBUaNGgUXF5cnHi+TyeDr66vV1r17d9y+fbvG4/r06YOffvoJixYtwsmTJ1FYWFjrnCtWHHr0USYAeOONN2Bubo5jx44B+G+fT5gwQSvu73//OwwNqx68f/311yu1lZaWYuXKlejSpQuMjY1haGgIY2Nj3LhxA0lJSZXifXx8tLZfeOEFAA9Hjx5vz8rK0noc6qOPPkJpaSkGDRpUZX4VbGxs4Ovri+3bt6O8vBwAkJ2djR9//BFTpkyRvt/hw4fRpk0b+Pr6at2XPXv2hFKpxMmTJ7XO2717dzz//PM1Xrsm//73v7FixQqEhIRgzJgx9T4PEbUcLCyIiOrg73//OxQKhfQ409GjR5GWlqY1aTstLQ2HDh2CkZGR1qficZCMjIxqz5+ZmQlHR8dK7U5OTtJ+ALh//z6ee+65BvtewH+f1a+Yz3D48GHcunULs2fPrtXxZmZmlR6XksvlT5yb8dlnn2HhwoU4cOAAhgwZAmtra4wdOxY3btx44jUzMzNhaGgIOzs7rXaZTAalUin1V8X/Pr5il6GhIWxsbKo8d1V/D/PmzcOHH36IsWPH4tChQ7hw4QJiY2PRo0ePKgsia2trrW1jY+Ma22szj6Uq06ZNw19//YXo6GgADxcTKC4u1iq40tLSoFarYWxsXOneVKlUle7Lqr5/bYWFhWHmzJl4++23sWbNmnqfh4haFs6xICKqA1NTU0ycOBFff/01UlNTsW3bNlhYWEiTogHA1tYW3bt3x4oVK6o8R0WRUBUbGxukpqZWar937550bgCws7PD3bt3dfkqVQoKCsIbb7yB3377DZs3b8bzzz+PESNGNPh1HmVubo5ly5Zh2bJlSEtLk0YvfH19tSaiV8XGxgalpaW4f/++VnEhhIBKpcLLL78sxQEPf7hu27atFFdaWioVHY+ragWonTt3YsqUKVi5cqVWe0ZGBtq0aVOr79sYvLy84OTkhLCwMHh5eSEsLAx9+/ZFly5dpBhbW1vY2NggMjKyynNYWFhobdd3BaywsDBMnz4d/v7++PLLL5/plbSInjUcsSAiqqPAwECUlZVhzZo1OHr0KN566y2YmZlJ+318fJCQkICOHTuid+/elT41FRbDhg3D8ePHpUKiwrfffgszMzNpqVZvb2/88ccfdX75WMVE5uoeNxo3bhzat2+PkJAQ/PLLL5g1a1aT/mDo4OCAgIAATJw4EdevX8eDBw9qzHvYsGEAHv7A/6h9+/ahoKBA2j9w4EAAwN69e7Xivv/++1qt1FVBJpNJuVQ4cuQI/vrrr1qfozEYGBjAz88PBw4cwJkzZ/Drr79i2rRpWjE+Pj7IzMxEWVlZlffl4xPPqyOXy6u9f8LDwzF9+nT84x//wL///W8WFUTPGI5YEBHVUe/evdG9e3ds3LgRQohK765Yvnw5oqOj4enpiaCgILi5uaGoqAi3bt3C0aNH8eWXX1b7GNPSpUulORofffQRrK2tsWvXLhw5cgSrV6+GQqEAAAQHB2Pv3r0YM2YMFi1ahD59+qCwsBCnTp2Cj48PhgwZUuX5u3btCgDYunUrLCwsYGJiAldXV+k3+gYGBnjvvfewcOFCmJubV5q70Bj69u0LHx8fdO/eHVZWVkhKSsKOHTvg4eEhFWzdunUDAHz66afw9vaGgYEBunfvjhEjRsDLywsLFy5Ebm4u+vfvL60K1atXL/j5+QEAXnzxRUycOBHr1q2DgYEBhg4diqtXr2LdunVQKBRo1ap2v2fz8fFBeHg4OnfujO7duyMuLg5r1qxp8MfSgIf30fLly3Hs2LEnzrMAHj4O9emnn2LSpEkwNTXFm2++qbX/rbfewq5du/Daa69h7ty56NOnD4yMjHD37l2cOHECY8aMwbhx4554nW7duuHkyZM4dOgQHB0dYWFhATc3N3z33XcIDAxEz549MXPmTFy8eFHruF69elUqyojoKaPv2eNERC3R//2//1cAEF26dKly//3790VQUJBwdXUVRkZGwtraWri7u4sPPvhA5OfnS3F4bIUkIYS4cuWK8PX1FQqFQhgbG4sePXqIsLCwStfIzs4Wc+fOFe3btxdGRkbC3t5ejBo1Sly7dq3G82/cuFG4uroKAwMDAaDSuW/duiUAiHfeeafW/eHv7y/Mzc0rtS9durTSak6P57Ro0SLRu3dvYWVlJeRyuejQoYN4//33RUZGhhRTXFwspk+fLuzs7IRMJhMApJWqCgsLxcKFC4Wzs7MwMjISjo6O4t133xXZ2dla1y0qKhLz5s0T9vb2wsTERPTr10/ExMQIhUKhtaJTxapQsbGxlb5Pdna2CAwMFPb29sLMzEy88sor4syZM2LQoEFi0KBBUlzFqlDfffed1vHVnbuin+7fv1+praoVvKrj6ekpAIjJkydXub+kpESsXbtW9OjRQ5iYmIjWrVuLzp07i5kzZ4obN25Icc7OzmLUqFFVniM+Pl70799fmJmZCQDS965YGay6z5NWFiOilk8mhBBNWcgQEVHztmnTJgQFBSEhIeGpf//AuXPn0L9/f+zatQuTJk3SdzpERC0aCwsiIgIAXLp0CTdv3sTMmTPRv39/HDhwQN8pNajo6GjExMTA3d0dpqam+P333/HJJ59AoVDg8uXLT3wBIBER1YyFBRERAQBcXFygUqkwYMAA7NixA0qlUt8pNagLFy4gJCQEiYmJyMvLg62tLby8vLBq1SqdllYlIqKHWFgQEREREZHOuNwsERERERHpTK+FxenTp+Hr6wsnJyfIZLJKz/MGBARAJpNpfSrWcK9QXFyMOXPmwNbWFubm5hg9enSll0ZlZ2fDz88PCoUCCoUCfn5+UKvVWjF37tyBr68vzM3NYWtri6CgIGg0Gq2YK1euYNCgQTA1NUXbtm2xfPlycMCHiIiIiEjP77EoKChAjx49MHXqVLz++utVxrz66qsICwuTto2NjbX2BwcH49ChQ4iIiICNjQ1CQkLg4+ODuLg4GBgYAAAmTZqEu3fvSm8bffvtt+Hn54dDhw4BAMrKyjBq1CjY2dnh7NmzyMzMhL+/P4QQ2LRpEwAgNzcXI0aMwJAhQxAbG4s//vgDAQEBMDc3R0hISK2/c3l5Oe7duwcLCwu+OIiIiIiImjUhBPLy8uDk5PTkd/7oaZnbSgCI/fv3a7X5+/uLMWPGVHuMWq0WRkZGIiIiQmr766+/RKtWrURkZKQQQojExEQBQJw/f16KiYmJEQCktd6PHj0qWrVqJf766y8pZs+ePUIul4ucnBwhhBBbtmwRCoVCFBUVSTGrVq0STk5Oory8vNbfMyUlpcZ1vvnhhx9++OGHH3744ae5fVJSUp74c26zf/P2yZMnYW9vjzZt2mDQoEFYsWIF7O3tAQBxcXEoKSnByJEjpXgnJyd07doV586dg5eXF2JiYqBQKNC3b18ppl+/flAoFDh37hzc3NwQExODrl27wsnJSYrx8vJCcXEx4uLiMGTIEMTExGDQoEFabw318vLC4sWLcevWLbi6ulaZf3FxMYqLi6Vt8f8fnUpJSYGlpWXDdBIRERERUSPIzc1Fu3btYGFh8cTYZl1YeHt744033oCzszNu3ryJDz/8EEOHDkVcXBzkcjlUKhWMjY1hZWWldZyDgwNUKhUAQKVSSYXIo+zt7bViHBwctPZbWVnB2NhYK8bFxaXSdSr2VVdYrFq1CsuWLavUbmlpycKCiIiIiFqE2jzC36wLizfffFP6c9euXdG7d284OzvjyJEjGD9+fLXHCSG0vnxVHdEQMRWjDzV19OLFizFv3jxpu6LqIyIiIiJ6mrSo5WYdHR3h7OyMGzduAACUSiU0Gg2ys7O14tLT06XRBKVSibS0tErnun//vlZMxchEhezsbJSUlNQYk56eDgCVRjseJZfLpdEJjlIQERER0dOqRRUWmZmZSElJkd6Q6u7uDiMjI0RHR0sxqampSEhIgKenJwDAw8MDOTk5uHjxohRz4cIF5OTkaMUkJCQgNTVViomKioJcLoe7u7sUc/r0aa0laKOiouDk5FTpESkiIiIiomeNXt+8nZ+fjz///BMA0KtXL6xfvx5DhgyBtbU1rK2tERoaitdffx2Ojo64desWlixZgjt37iApKUmaQPLuu+/i8OHDCA8Ph7W1NebPn4/MzEyt5Wa9vb1x7949fPXVVwAeLjfr7Oystdxsz5494eDggDVr1iArKwsBAQEYO3astNxsTk4O3NzcMHToUCxZsgQ3btxAQEAAPvroozotN5ubmwuFQoGcnByOXhDRU0WlUmm9I6hNmzZQKpX6S4iIiHRWp59da71OaiM4ceJElctZ+fv7iwcPHoiRI0cKOzs7YWRkJNq3by/8/f3FnTt3tM5RWFgoZs+eLaytrYWpqanw8fGpFJOZmSkmT54sLCwshIWFhZg8ebLIzs7Wirl9+7YYNWqUMDU1FdbW1mL27NlaS8sKIcTly5fFgAEDhFwuF0qlUoSGhtZpqVkhhMjJyREApGVsiYieBqmpqeKll/uJv73QTfq89HI/kZqaqu/UiIhIB3X52VWvIxbPIo5YENHT6Nq1a/AdPwGdR0yBpa0jcjNSkfDTN/h84zp06NABAEcwiIhaorr87NqsV4UiIqKWxdLWEVaOzijMUyNNpcKsuSEwMjJ6uK+1OY4c3M/igojoKcXCgoiIGpym6AHQygBuw/1g6+SM3IxUXIv+Fmq1moUFEdFTioUFERE1GgsbJawcnfWdBhERNYEWtdwsERERERE1TywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZywsiIiIiIhIZ4b6ToCIiFomlUoFtVoNAEhOTkZZWZl+EyIiIr1iYUFERHWmUqkwavQ45OYXAAA0xUXIzFKjtLRUz5kREZG+sLAgIqI6U6vVyM0vQOcRU2Bp64h7f/yO+4e2cdSCiOgZxjkWRERUb5a2jrBydIa5lZ2+UyEiIj1jYUFERERERDpjYUFERERERDpjYUFERERERDrTa2Fx+vRp+Pr6wsnJCTKZDAcOHNDaL4RAaGgonJycYGpqisGDB+Pq1ataMcXFxZgzZw5sbW1hbm6O0aNH4+7du1ox2dnZ8PPzg0KhgEKhgJ+fn7REYoU7d+7A19cX5ubmsLW1RVBQEDQajVbMlStXMGjQIJiamqJt27ZYvnw5hBAN1h9ERERERC2VXguLgoIC9OjRA5s3b65y/+rVq7F+/Xps3rwZsbGxUCqVGDFiBPLy8qSY4OBg7N+/HxERETh79izy8/Ph4+OjtTLJpEmTEB8fj8jISERGRiI+Ph5+fn7S/rKyMowaNQoFBQU4e/YsIiIisG/fPoSEhEgxubm5GDFiBJycnBAbG4tNmzZh7dq1WL9+fSP0DBERERFRy6LX5Wa9vb3h7e1d5T4hBDZu3IgPPvgA48ePBwBs374dDg4O2L17N2bOnImcnBx888032LFjB4YPHw4A2LlzJ9q1a4dffvkFXl5eSEpKQmRkJM6fP4++ffsCAL7++mt4eHjg+vXrcHNzQ1RUFBITE5GSkgInJycAwLp16xAQEIAVK1bA0tISu3btQlFREcLDwyGXy9G1a1f88ccfWL9+PebNmweZTNYEPUZERERE1Dw12zkWN2/ehEqlwsiRI6U2uVyOQYMG4dy5cwCAuLg4lJSUaMU4OTmha9euUkxMTAwUCoVUVABAv379oFAotGK6du0qFRUA4OXlheLiYsTFxUkxgwYNglwu14q5d+8ebt26Ve33KC4uRm5urtaHiIiIiOhp02wLC5VKBQBwcHDQandwcJD2qVQqGBsbw8rKqsYYe3v7Sue3t7fXinn8OlZWVjA2Nq4xpmK7IqYqq1atkuZ2KBQKtGvXruYvTkRERETUAjXbwqLC448YCSGe+NjR4zFVxTdETMXE7ZryWbx4MXJycqRPSkpKjbkTEREREbVEzbawUCqVACqPBqSnp0sjBUqlEhqNBtnZ2TXGpKWlVTr//fv3tWIev052djZKSkpqjElPTwdQeVTlUXK5HJaWllofIqJnUWlpCZKTk3Ht2rUaR3qJiKhlaraFhaurK5RKJaKjo6U2jUaDU6dOwdPTEwDg7u4OIyMjrZjU1FQkJCRIMR4eHsjJycHFixelmAsXLiAnJ0crJiEhAampqVJMVFQU5HI53N3dpZjTp09rLUEbFRUFJycnuLi4NHwHEBE9RQrz1EhTqTBrbgh8x0/AqNHjWFwQET1l9FpY5OfnIz4+HvHx8QAeTtiOj4/HnTt3IJPJEBwcjJUrV2L//v1ISEhAQEAAzMzMMGnSJACAQqFAYGAgQkJCcOzYMVy6dAn/+Mc/0K1bN2mVqBdeeAGvvvoqZsyYgfPnz+P8+fOYMWMGfHx84ObmBgAYOXIkunTpAj8/P1y6dAnHjh3D/PnzMWPGDGmEYdKkSZDL5QgICEBCQgL279+PlStXckUoIqJa0BQ9AFoZwG24HzqPmILc/IJK7xMiIqKWrV7LzXbo0AGxsbGwsbHRaler1XjppZeQnJxcq/P8+uuvGDJkiLQ9b948AIC/vz/Cw8OxYMECFBYWYtasWcjOzkbfvn0RFRUFCwsL6ZgNGzbA0NAQEyZMQGFhIYYNG4bw8HAYGBhIMbt27UJQUJC0etTo0aO13p1hYGCAI0eOYNasWejfvz9MTU0xadIkrF27VopRKBSIjo7Ge++9h969e8PKygrz5s2TciYioiezsFFqra5HRERPj3oVFrdu3dJ6AV2F4uJi/PXXX7U+z+DBg2t8c7VMJkNoaChCQ0OrjTExMcGmTZuwadOmamOsra2xc+fOGnNp3749Dh8+XGNMt27dcPr06RpjiIiIiIieRXUqLA4ePCj9+eeff4ZCoZC2y8rKcOzYMc43ICIiIiJ6BtWpsBg7diyAhyMJ/v7+WvuMjIzg4uKCdevWNVhyRERERETUMtSpsCgvLwfwcMWm2NhY2NraNkpSRERERETUstRrjsXNmzcbOg8iIiIiImrB6lVYAMCxY8dw7NgxpKenSyMZFbZt26ZzYkRERERE1HLUq7BYtmwZli9fjt69e8PR0ZHvcSAiIiIiesbVq7D48ssvER4eDj8/v4bOh4iIiIiIWqB6vXlbo9HA09OzoXMhIiIiIqIWql6FxfTp07F79+6GzoWIiIiIiFqoej0KVVRUhK1bt+KXX35B9+7dYWRkpLV//fr1DZIcERERERG1DPUqLC5fvoyePXsCABISErT2cSI3EREREdGzp16FxYkTJxo6DyIiIiIiasHqNceCiIiIiIjoUfUasRgyZEiNjzwdP3683gkREREREVHLU6/ComJ+RYWSkhLEx8cjISEB/v7+DZEXERERERG1IPUqLDZs2FBle2hoKPLz83VKiIiIiIiIWp4GnWPxj3/8A9u2bWvIUxIRERERUQvQoIVFTEwMTExMGvKURERERETUAtTrUajx48drbQshkJqail9//RUffvhhgyRGREREREQtR70KC4VCobXdqlUruLm5Yfny5Rg5cmSDJEZERERERC1HvQqLsLCwhs6DiIiIiIhasHoVFhXi4uKQlJQEmUyGLl26oFevXg2VFxERERERtSD1KizS09Px1ltv4eTJk2jTpg2EEMjJycGQIUMQEREBOzu7hs6TiIiIiIiasXqtCjVnzhzk5ubi6tWryMrKQnZ2NhISEpCbm4ugoKCGzpGIiIiIiJq5eo1YREZG4pdffsELL7wgtXXp0gWff/45J28TERERET2D6jViUV5eDiMjo0rtRkZGKC8v1zkpIiIiIiJqWepVWAwdOhRz587FvXv3pLa//voL77//PoYNG9ZgyRERERERUctQr8Ji8+bNyMvLg4uLCzp27Ii//e1vcHV1RV5eHjZt2tTQORIRERERUTNXrzkW7dq1w2+//Ybo6Ghcu3YNQgh06dIFw4cPb+j8iIiIiIioBajTiMXx48fRpUsX5ObmAgBGjBiBOXPmICgoCC+//DJefPFFnDlzplESJSIi/VOpVLh27RqSk5NRVlam73SIiKgZqdOIxcaNGzFjxgxYWlpW2qdQKDBz5kysX78eAwYMaLAEiYioeVCpVBg1ehxy8wugKS5CZpYapaWl+k6LiIiaiTqNWPz+++949dVXq90/cuRIxMXF6ZwUERE1P2q1Grn5Beg8Ygo6eI5FuSjnqAUREUnqNGKRlpZW5TKz0skMDXH//n2dkyIioubL0tYRQgidzlFaWoLk5GRpu02bNlAqlbqmRkREelSnwqJt27a4cuUK/va3v1W5//Lly3B0dGyQxIiI6OlUmKdGmkqFWXNDpF9WWbY2x5GD+1lcEBG1YHV6FOq1117DRx99hKKiokr7CgsLsXTpUvj4+DRYckRE9PTRFD0AWhnAbbgf+kxciM4jpiA3vwBqtVrfqRERkQ7qNGLxz3/+Ez/88AOef/55zJ49G25ubpDJZEhKSsLnn3+OsrIyfPDBB42VKxERPUUsbJSwcnTWdxpERNRA6lRYODg44Ny5c3j33XexePFi6RlbmUwGLy8vbNmyBQ4ODo2SKBERERERNV91fvO2s7Mzjh49ioyMDFy4cAHnz59HRkYGjh49ChcXlwZNLjQ0FDKZTOvz6PO3QgiEhobCyckJpqamGDx4MK5evap1juLiYsyZMwe2trYwNzfH6NGjcffuXa2Y7Oxs+Pn5QaFQQKFQwM/Pr9KQ/J07d+Dr6wtzc3PY2toiKCgIGo2mQb8vEREREVFLVefCooKVlRVefvll9OnTB1ZWVg2Zk5YXX3wRqamp0ufKlSvSvtWrV2P9+vXYvHkzYmNjoVQqMWLECOTl5UkxwcHB2L9/PyIiInD27Fnk5+fDx8dHa4nESZMmIT4+HpGRkYiMjER8fDz8/Pyk/WVlZRg1ahQKCgpw9uxZREREYN++fQgJCWm0701ERERE1JLU6VEofTA0NKxylRAhBDZu3IgPPvgA48ePBwBs374dDg4O2L17N2bOnImcnBx888032LFjB4YPHw4A2LlzJ9q1a4dffvkFXl5eSEpKQmRkJM6fP4++ffsCAL7++mt4eHjg+vXrcHNzQ1RUFBITE5GSkgInJycAwLp16xAQEIAVK1ZU+cLACsXFxSguLpa2K95aTkRERET0NKn3iEVTuXHjBpycnODq6oq33npLWvf85s2bUKlUGDlypBQrl8sxaNAgnDt3DgAQFxeHkpISrRgnJyd07dpViomJiYFCoZCKCgDo168fFAqFVkzXrl2logIAvLy8UFxc/MQXAq5atUp6xEqhUKBdu3Y69ggRERERUfPTrAuLvn374ttvv8XPP/+Mr7/+GiqVCp6ensjMzIRKpQKASpPFHRwcpH0qlQrGxsaVHtV6PMbe3r7Ste3t7bViHr+OlZUVjI2NpZjqLF68GDk5OdInJSWlDj1ARERERNQyNOtHoby9vaU/d+vWDR4eHujYsSO2b9+Ofv36AXi4ItWjhBCV2h73eExV8fWJqYpcLodcLq8xhoiIiIiopWvWIxaPMzc3R7du3XDjxg1p3sXjIwbp6enS6IJSqYRGo0F2dnaNMWlpaZWudf/+fa2Yx6+TnZ2NkpISLq9LRERERIQWVlgUFxcjKSkJjo6OcHV1hVKpRHR0tLRfo9Hg1KlT8PT0BAC4u7vDyMhIKyY1NRUJCQlSjIeHB3JycnDx4kUp5sKFC8jJydGKSUhIQGpqqhQTFRUFuVwOd3f3Rv3OREREREQtQbN+FGr+/Pnw9fVF+/btkZ6ejo8//hi5ubnw9/eHTCZDcHAwVq5ciU6dOqFTp05YuXIlzMzMMGnSJACAQqFAYGAgQkJCYGNjA2tra8yfPx/dunWTVol64YUX8Oqrr2LGjBn46quvAABvv/02fHx84ObmBgAYOXIkunTpAj8/P6xZswZZWVmYP38+ZsyYUeOKUEREREREz4pmXVjcvXsXEydOREZGBuzs7NCvXz+cP38ezs7OAIAFCxagsLAQs2bNQnZ2Nvr27YuoqChYWFhI59iwYQMMDQ0xYcIEFBYWYtiwYQgPD4eBgYEUs2vXLgQFBUmrR40ePRqbN2+W9hsYGODIkSOYNWsW+vfvD1NTU0yaNAlr165top4gIiIiImremnVhERERUeN+mUyG0NBQhIaGVhtjYmKCTZs2YdOmTdXGWFtbY+fOnTVeq3379jh8+HCNMUREREREz6oWNceCiIiIiIiaJxYWRERERESkMxYWRERERESkMxYWRERERESkMxYWRERERESkMxYWRERERESks2a93CwRET0bSktLkJycLG23adMGSqVSjxkREVFdsbAgIiK9KsxTI02lwqy5ITAyMgIAWLY2x5GD+1lcEBG1ICwsiIhIrzRFD4BWBnAb7gdbJ2fkZqTiWvS3UKvVLCyIiFoQFhZERFQtlUoFtVoNAEhOTkZZWVmjXcvCRgkrR+dGOz8RETUuFhZERFQllUqFUaPHITe/AACgKS5CZpYapaWles6MiIiaIxYWRERUJbVajdz8AnQeMQWWto6498fvuH9oW6OOWhARUcvF5WaJiKhGlraOsHJ0hrmVnb5TISKiZoyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YyFBRERERER6YwvyCMiomantLQEycnJ0nabNm2gVCr1mBERET0JCwsiImpWCvPUSFOpMGtuCIyMjAAAlq3NceTgfhYXRETNGAsLIiJqVjRFD4BWBnAb7gdbJ2fkZqTiWvS3UKvVLCyIiJoxFhZERNQsWdgoYeXorO80iIiollhYEBGRRKVSQa1WAwCSk5NRVlam34SIiKjFYGFBREQAHhYVo0aPQ25+AQBAU1yEzCw1SktL9ZwZERG1BCwsiIgIAKBWq5GbX4DOI6bA0tYR9/74HfcPbeOoBRER1QrfY0FERFosbR1h5egMcys7fadCREQtCAsLIiIiIiLSGR+FIiKiZu/RF+bxZXlERM0TCwsiImrWHn9hHl+WR0TUPLGwICJ6xlUsMdtcl5d99IV5xsbGfFkeEVEzxcKCiOgZ9ugSs819eVkLGyXkcrm+0yAiompw8jYR0TPs0SVmO3iORbkob5ajFkRE1PxxxIKIiGBp6wghhL7TqJVHJ3IDnMxNRNRcsLAgInrGVMypANBs51VU5/GJ3AA4mZuIqJlgYVEPW7ZswZo1a5CamooXX3wRGzduxIABA/SdFhHREz06pwJAs59X8bhHJ3LbOjkjNyMVCT99g99++w0dOnQAwBEMIiJ9YWFRR3v37kVwcDC2bNmC/v3746uvvoK3tzcSExPRvn17fadHRFTJ4yMU2Tm5ePHVqbC0dcS9P37H/UPbWtSoBfBwIreVo3OVIximciN8/tlG2NnZscggImpCLCzqaP369QgMDMT06dMBABs3bsTPP/+ML774AqtWrdJzdkRE2oXE/fv3MXvu+3hQpAHw3xGKl9vYwcrRGTn37+kxU909PoKRfvs6/vd/NsFv2tswMjLSKjIAQKPRwNjYWDqehQcRUcNhYVEHGo0GcXFxWLRokVb7yJEjce7cuSqPKS4uRnFxsbSdk5MDAMjNzW28RImoyWRmZiIzM1PalslkWpOgH92uaZ8usY9uZ2Rk4P8sWoIHhQ//3dFoipCVnYPuw99Aays7ZKX8B+kxPyHj7n8gSjXISbsLIcqRnXoLmvwc6c+tRJnWvse36xLbFMeWaopQUvQARXk5EDIZHLoNgijV4MqJHzA5IBBGhkYoLS1BZkYGbO3sYWBgAAAwlRtj7epVsLW1bbC/g6b6u27KY21sbGBjYwMievZU/MxamwU+ZKKlLAPSDNy7dw9t27bF//7v/8LT01NqX7lyJbZv347r169XOiY0NBTLli1ryjSJiIiIiBpUSkoKnnvuuRpjOGJRDzKZTGtbCFGprcLixYsxb948abu8vBxZWVmwsbGp9pjmKDc3F+3atUNKSgosLS31nc5Ti/3c+NjHTYP93PjYx02D/dz42MeNT5c+FkIgLy8PTk5OT4xlYVEHtra2MDAwgEql0mpPT0+Hg4NDlcfI5fJKb4pt06ZNY6XY6CwtLfkffRNgPzc+9nHTYD83PvZx02A/Nz72ceOrbx8rFIpaxfHN23VgbGwMd3d3REdHa7VHR0drPRpFRERERPSs4YhFHc2bNw9+fn7o3bs3PDw8sHXrVty5cwfvvPOOvlMjIiIiItIbFhZ19OabbyIzMxPLly9HamoqunbtiqNHj8LZ2VnfqTUquVyOpUuXVnqsixoW+7nxsY+bBvu58bGPmwb7ufGxjxtfU/UxV4UiIiIiIiKdcY4FERERERHpjIUFERERERHpjIUFERERERHpjIUFERERERHpjIUFVWvFihXw9PSEmZlZrV/qFxAQAJlMpvXp169f4ybawtWnn4UQCA0NhZOTE0xNTTF48GBcvXq1cRNtwbKzs+Hn5weFQgGFQgE/Pz+o1eoaj+G9/GRbtmyBq6srTExM4O7ujjNnztQYf+rUKbi7u8PExAQdOnTAl19+2USZtlx16eOTJ09WumdlMhmuXbvWhBm3LKdPn4avry+cnJwgk8lw4MCBJx7D+7ju6trPvJfrZtWqVXj55ZdhYWEBe3t7jB07FtevX3/icY1xL7OwoGppNBq88cYbePfdd+t03KuvvorU1FTpc/To0UbK8OlQn35evXo11q9fj82bNyM2NhZKpRIjRoxAXl5eI2back2aNAnx8fGIjIxEZGQk4uPj4efn98TjeC9Xb+/evQgODsYHH3yAS5cuYcCAAfD29sadO3eqjL958yZee+01DBgwAJcuXcKSJUsQFBSEffv2NXHmLUdd+7jC9evXte7bTp06NVHGLU9BQQF69OiBzZs31yqe93H91LWfK/Berp1Tp07hvffew/nz5xEdHY3S0lKMHDkSBQUF1R7TaPeyIHqCsLAwoVAoahXr7+8vxowZ06j5PK1q28/l5eVCqVSKTz75RGorKioSCoVCfPnll42YYcuUmJgoAIjz589LbTExMQKAuHbtWrXH8V6uWZ8+fcQ777yj1da5c2exaNGiKuMXLFggOnfurNU2c+ZM0a9fv0bLsaWrax+fOHFCABDZ2dlNkN3TB4DYv39/jTG8j3VXm37mvayb9PR0AUCcOnWq2pjGupc5YkEN7uTJk7C3t8fzzz+PGTNmID09Xd8pPVVu3rwJlUqFkSNHSm1yuRyDBg3CuXPn9JhZ8xQTEwOFQoG+fftKbf369YNCoXhif/FerppGo0FcXJzWPQgAI0eOrLZPY2JiKsV7eXnh119/RUlJSaPl2lLVp48r9OrVC46Ojhg2bBhOnDjRmGk+c3gfNy3ey/WTk5MDALC2tq42prHuZRYW1KC8vb2xa9cuHD9+HOvWrUNsbCyGDh2K4uJifaf21FCpVAAABwcHrXYHBwdpH/2XSqWCvb19pXZ7e/sa+4v3cvUyMjJQVlZWp3tQpVJVGV9aWoqMjIxGy7Wlqk8fOzo6YuvWrdi3bx9++OEHuLm5YdiwYTh9+nRTpPxM4H3cNHgv158QAvPmzcMrr7yCrl27VhvXWPeyYb2PpBYpNDQUy5YtqzEmNjYWvXv3rtf533zzTenPXbt2Re/eveHs7IwjR45g/Pjx9TpnS9TY/QwAMplMa1sIUantaVbbPgYq9xXw5P7ivfxkdb0Hq4qvqp3+qy597ObmBjc3N2nbw8MDKSkpWLt2LQYOHNioeT5LeB83Pt7L9Td79mxcvnwZZ8+efWJsY9zLLCyeMbNnz8Zbb71VY4yLi0uDXc/R0RHOzs64ceNGg52zJWjMflYqlQAe/rbB0dFRak9PT6/024enWW37+PLly0hLS6u07/79+3Xqr2f1Xq6Kra0tDAwMKv3mvKZ7UKlUVhlvaGgIGxubRsu1papPH1elX79+2LlzZ0On98zifaw/vJefbM6cOTh48CBOnz6N5557rsbYxrqXWVg8Y2xtbWFra9tk18vMzERKSorWD8DPgsbsZ1dXVyiVSkRHR6NXr14AHj6PferUKXz66aeNcs3mqLZ97OHhgZycHFy8eBF9+vQBAFy4cAE5OTnw9PSs9fWe1Xu5KsbGxnB3d0d0dDTGjRsntUdHR2PMmDFVHuPh4YFDhw5ptUVFRaF3794wMjJq1Hxbovr0cVUuXbrEe7YB8T7WH97L1RNCYM6cOdi/fz9OnjwJV1fXJx7TaPeyTlO/6al2+/ZtcenSJbFs2TLRunVrcenSJXHp0iWRl5cnxbi5uYkffvhBCCFEXl6eCAkJEefOnRM3b94UJ06cEB4eHqJt27YiNzdXX1+j2atrPwshxCeffCIUCoX44YcfxJUrV8TEiROFo6Mj+7kar776qujevbuIiYkRMTExolu3bsLHx0crhvdy3URERAgjIyPxzTffiMTERBEcHCzMzc3FrVu3hBBCLFq0SPj5+UnxycnJwszMTLz//vsiMTFRfPPNN8LIyEh8//33+voKzV5d+3jDhg1i//794o8//hAJCQli0aJFAoDYt2+fvr5Cs5eXlyf9mwtArF+/Xly6dEncvn1bCMH7uKHUtZ95L9fNu+++KxQKhTh58qRITU2VPg8ePJBimupeZmFB1fL39xcAKn1OnDghxQAQYWFhQgghHjx4IEaOHCns7OyEkZGRaN++vfD39xd37tzRzxdoIeraz0I8XHJ26dKlQqlUCrlcLgYOHCiuXLnS9Mm3EJmZmWLy5MnCwsJCWFhYiMmTJ1daxpD3ct19/vnnwtnZWRgbG4uXXnpJa2lDf39/MWjQIK34kydPil69egljY2Ph4uIivvjiiybOuOWpSx9/+umnomPHjsLExERYWVmJV155RRw5ckQPWbccFcuaPv7x9/cXQvA+bih17Wfey3VTVd8+/nNDU93Lsv+fEBERERERUb1xuVkiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiIiIiItIZCwsiImpwLi4u2LhxY7M936PnlclkkMlkUKvVDX7+mlRct02bNk16XSKixsLCgoiIJL6+vhg+fHiV+2JiYiCTyfDbb781cVZAbGws3n77bWlbJpPhwIEDDXLu5cuXIzU1FQqFokHON3jwYHz55ZdPjEtNTW2UYomISF9YWBARkSQwMBDHjx/H7du3K+3btm0bevbsiZdeeqnJ87Kzs4OZmVmjnNvCwgJKpRIymUznc2VlZeHcuXPw9fV9YqxSqWywYoaIqDlgYUFERBIfHx/Y29sjPDxcq/3BgwfYu3cvAgMDAQDnzp3DwIEDYWpqinbt2iEoKAgFBQXVnvfOnTsYM2YMWrduDUtLS0yYMAFpaWlaMQcPHkTv3r1hYmICW1tbjB8/Xtr36KNQLi4uAIBx48ZBJpPBxcUFt27dQqtWrfDrr79qnXPTpk1wdnaGEKLWfRAeHo42bdrg8OHDcHNzg5mZGf7+97+joKAA27dvh4uLC6ysrDBnzhyUlZVpHXvkyBH06NEDbdu2RXZ2NiZPngw7OzuYmpqiU6dOCAsLq3UeREQtDQsLIiKSGBoaYsqUKQgPD9f6Yfy7776DRqPB5MmTceXKFXh5eWH8+PG4fPky9u7di7Nnz2L27NlVnlMIgbFjxyIrKwunTp1CdHQ0/vOf/+DNN9+UYo4cOYLx48dj1KhRuHTpEo4dO4bevXtXeb7Y2FgAQFhYGFJTUxEbGwsXFxcMHz680g/uYWFhCAgIqPNoxIMHD/DZZ58hIiICkZGROHnyJMaPH4+jR4/i6NGj2LFjB7Zu3Yrvv/9e67iDBw9izJgxAIAPP/wQiYmJ+Omnn5CUlIQvvvgCtra2dcqDiKhFEURERI9ISkoSAMTx48eltoEDB4qJEycKIYTw8/MTb7/9ttYxZ86cEa1atRKFhYVCCCGcnZ3Fhg0bhBBCREVFCQMDA3Hnzh0p/urVqwKAuHjxohBCCA8PDzF58uRqc3r0fEIIAUDs379fK2bv3r3CyspKFBUVCSGEiI+PFzKZTNy8ebPW5xVCiLCwMAFA/Pnnn1LbzJkzhZmZmcjLy5PavLy8xMyZM6XtoqIiYWFhIS5fviyEEMLX11dMnTq12mtXXEuhUNQYQ0TUUnDEgoiItHTu3Bmenp7Ytm0bAOA///kPzpw5g2nTpgEA4uLiEB4ejtatW0sfLy8vlJeX4+bNm5XOl5SUhHbt2qFdu3ZSW5cuXdCmTRskJSUBAOLj4zFs2DCd8h47diwMDQ2xf/9+AA/nhAwZMkR6dKouzMzM0LFjR2nbwcEBLi4uaN26tVZbenq6tH38+HHY2NigW7duAIB3330XERER6NmzJxYsWIBz587V85sREbUMLCyIiKiSwMBA7Nu3D7m5uQgLC4Ozs7P0g395eTlmzpyJ+Ph46fP777/jxo0bWj+MVxBCVPko0qPtpqamOudsbGwMPz8/hIWFQaPRYPfu3VIxVFdGRkZa2zKZrMq28vJyafvRx6AAwNvbG7dv30ZwcDDu3buHYcOGYf78+fXKh4ioJWBhQURElUyYMAEGBgbYvXs3tm/fjqlTp0pFwEsvvYSrV6/ib3/7W6WPsbFxpXN16dIFd+7cQUpKitSWmJiInJwcvPDCCwCA7t2749ixY7XOz8jIqNLEaQCYPn06fvnlF2zZsgUlJSVaE8AbkxAChw4dwujRo7Xa7ezsEBAQgJ07d2Ljxo3YunVrk+RDRKQPLCyIiKiS1q1b480338SSJUtw7949BAQESPsWLlyImJgYvPfee4iPj8eNGzdw8OBBzJkzp8pzDR8+HN27d8fkyZPx22+/4eLFi5gyZQoGDRokTdBeunQp9uzZg6VLlyIpKQlXrlzB6tWrq83PxcUFx44dg0qlQnZ2ttT+wgsvoF+/fli4cCEmTpzYICMhtREXF4eCggIMHDhQavvoo4/w448/4s8//8TVq1dx+PBhqZAiInoasbAgIqIqBQYGIjs7G8OHD0f79u2l9u7du+PUqVO4ceMGBgwYgF69euHDDz+Eo6NjleepeJmdlZUVBg4ciOHDh6NDhw7Yu3evFDN48GB89913OHjwIHr27ImhQ4fiwoUL1ea2bt06REdHo127dujVq1elvDUaTb0fg6qPH3/8EaNGjYKhoaHUZmxsjMWLF6N79+4YOHAgDAwMEBER0WQ5ERE1NZkQdVjcm4iIqJlbsWIFIiIicOXKlSfGuri4IDg4GMHBwTpds3v37vjnP/+JCRMm1Om48PBwBAcHQ61W63R9IqLmgCMWRET0VMjPz0dsbCw2bdqEoKCgWh+3cOFCtG7dGjk5OfW6rkajweuvvw5vb+86Hde6dWu888479bomEVFzxBELIiJ6KgQEBGDPnj0YO3Ysdu/eDQMDgycec/v2bZSUlAAAOnTogFatmu73bX/++ScAwMDAAK6urk12XSKixsLCgoiIiIiIdMZHoYiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGcsLIiIiIiISGf/D1NfWjyMTJeeAAAAAElFTkSuQmCC",
+            "text/plain": [
+              "<Figure size 800x800 with 4 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "vel = ds[\"vel\"]\n",
+        "\n",
+        "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+        "labels = vel.coords[vel_dim].values\n",
+        "\n",
+        "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 2 * len(labels)), sharex=True)\n",
+        "\n",
+        "if len(labels) == 1:\n",
+        "    axes = [axes]\n",
+        "\n",
+        "for ax_i, label in zip(axes, labels):\n",
+        "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+        "    values = values[np.isfinite(values)]\n",
+        "\n",
+        "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+        "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+        "    ax_i.set_ylabel(\"Count\")\n",
+        "\n",
+        "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+        "plt.tight_layout()"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import matplotlib as mpl\n",
-    "\n",
-    "plt.rcParams.update({\"font.size\": 18, \"font.family\": \"Times New Roman\"})\n",
-    "\n",
-    "\n",
-    "def plot_spectra_by_color(auto_spectra, U_mag, ax, fig, cbar_max=4.0):\n",
-    "    U = U_mag.values\n",
-    "    U_max = U_mag.max().values\n",
-    "\n",
-    "    # Average spectra into 0.1 m/s velocity bins\n",
-    "    speed_bins = np.arange(0.5, U_max, 0.1)\n",
-    "    time = [t for t in auto_spectra.dims if \"time\" in t][0]\n",
-    "    S_group = auto_spectra.assign_coords({time: U}).rename({time: \"speed\"})\n",
-    "    group = S_group.groupby_bins(\"speed\", speed_bins)\n",
-    "    count = group.count().values\n",
-    "    S = group.mean()\n",
-    "\n",
-    "    # define the colormap\n",
-    "    cmap = plt.cm.turbo\n",
-    "    # define the bins and normalize\n",
-    "    bounds = np.arange(0.5, cbar_max, 0.1)\n",
-    "    norm = mpl.colors.BoundaryNorm(bounds, cmap.N)\n",
-    "    colors = cmap(norm(speed_bins))\n",
-    "\n",
-    "    # plot\n",
-    "    for i in range(len(speed_bins) - 1):\n",
-    "        ax.loglog(auto_spectra[\"freq\"], S[i], c=colors[i])\n",
-    "    ax.grid()\n",
-    "\n",
-    "    # create a second axes for the colorbar\n",
-    "    cax = fig.add_axes([0.8, 0.07, 0.03, 0.88])\n",
-    "    # cax, _ = mpl.colorbar.make_axes(fig.gca())\n",
-    "    sm = mpl.colorbar.ColorbarBase(\n",
-    "        cax,\n",
-    "        cmap=cmap,\n",
-    "        norm=norm,\n",
-    "        spacing=\"proportional\",\n",
-    "        ticks=bounds,\n",
-    "        boundaries=bounds,\n",
-    "        format=\"%1.1f\",\n",
-    "        label=\"Velocity [m/s]\",\n",
-    "    )\n",
-    "\n",
-    "    # Add -5/3 slope line\n",
-    "    m = -5 / 3\n",
-    "    x = np.logspace(-1, 0.5)\n",
-    "    y = 10 ** (-3) * x**m\n",
-    "    ax.loglog(x, y, \"--\", c=\"black\", label=\"$f^{-5/3}$\")\n",
-    "    ax.legend()\n",
-    "\n",
-    "    return ax, sm\n",
-    "\n",
-    "\n",
-    "# Set up figure\n",
-    "fig, ax = plt.subplots(1, 1, figsize=(6, 5))\n",
-    "fig.subplots_adjust(left=0.2, right=0.75, top=0.95, bottom=0.1)\n",
-    "\n",
-    "# Plot spectra by color\n",
-    "plot_spectra_by_color(ds_avg[\"auto_spectra_5m\"], U, ax, fig, cbar_max=2.0)\n",
-    "# Set axes\n",
-    "ax.set(\n",
-    "    xlabel=\"Frequency [Hz]\",\n",
-    "    ylabel=\"PSD [m2 s-2 Hz-1]\",\n",
-    "    xlim=(0.01, 1),\n",
-    "    ylim=(0.0005, 0.1),\n",
-    ")"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.3 Instrument Noise\n",
-    "\n",
-    "The next thing we want to do is calculate the instrument's Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
-    "\n",
-    "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>Statistic</th>\n",
-       "      <th>Value</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>mean</td>\n",
-       "      <td>0.024059</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>std</td>\n",
-       "      <td>0.007032</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>min</td>\n",
-       "      <td>0.013010</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>max</td>\n",
-       "      <td>0.046780</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1500x400 with 6 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
       ],
-      "text/plain": [
-       "  Statistic     Value\n",
-       "0      mean  0.024059\n",
-       "1       std  0.007032\n",
-       "2       min  0.013010\n",
-       "3       max  0.046780"
+      "source": [
+        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+        "\n",
+        "for i, ax in enumerate(axes):\n",
+        "    ds[\"vel\"][i].plot(ax=ax, vmin=-1.5, vmax=1.5, cmap=\"RdBu_r\")\n",
+        "    ax.set_title(ds[\"vel\"].coords[\"dir\"].values[i])\n",
+        "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+        "\n",
+        "plt.tight_layout()"
       ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ds_avg[\"noise_5m\"] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra_5m\"], pct_fN=0.9)\n",
-    "\n",
-    "noise_stats = pd.DataFrame({\n",
-    "    \"Statistic\": [\"mean\", \"std\", \"min\", \"max\"],\n",
-    "    \"Value\": [\n",
-    "        float(ds_avg[\"noise_5m\"].mean().values),\n",
-    "        float(ds_avg[\"noise_5m\"].std().values),\n",
-    "        float(ds_avg[\"noise_5m\"].min().values),\n",
-    "        float(ds_avg[\"noise_5m\"].max().values),\n",
-    "    ]\n",
-    "})\n",
-    "\n",
-    "noise_stats\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.4 TKE Dissipation Rate\n",
-    "\n",
-    "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, the frequency range of the isotropic cascade, and the instrument's noise."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Frequency range of isotropic turubulence cascade in same units as PSD frequency vector\n",
-    "f_rng = [0.1, 0.5]\n",
-    "# Dissipation rate\n",
-    "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
-    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
-    ")\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We have just found the spectra and dissipation rate from a single depth bin at an altitude of 5 m from the seafloor, but typically we want the spectra and dissipation rates from the entire measurement profile. If we want to look at the spectra and dissipation rates from all depth bins, we can set up a \"for\" loop on the range coordinate and merge them together:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import xarray as xr\n",
-    "\n",
-    "spec = [None] * len(ds.range)\n",
-    "e = [None] * len(ds.range)\n",
-    "n = [None] * len(ds.range)\n",
-    "\n",
-    "for r in range(len(ds[\"range\"])):\n",
-    "    # Calc spectra from each depth bin using the 5th beam\n",
-    "    spec[r] = avg_tool.power_spectral_density(\n",
-    "        ds[\"vel_b5\"].isel(range_b5=r), freq_units=\"Hz\"\n",
-    "    )\n",
-    "    \n",
-    "    # Calculate doppler noise from spectra from each depth bin\n",
-    "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
-    "    \n",
-    "    # Calc dissipation rate from each spectra\n",
-    "    e[r] = avg_tool.dissipation_rate_LT83(\n",
-    "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
-    "    )\n",
-    "\n",
-    "ds_avg[\"auto_spectra\"] = xr.concat(spec, dim=\"range\")\n",
-    "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
-    "ds_avg[\"dissipation_rate\"] = xr.concat(e, dim=\"range\")\n",
-    "\n",
-    "del spec, n, e  # save memory"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now that we have a profile timeseries of dissipation rate, we need apply some quality control (QC). Since we can't look at each individual spectrum to ensure we can see the isotropic turbulence cascade, we want to QC the output from `dissipation_rate_LT83` to make sure what was calculated actually falls on a f^(-5/3) slope. We can do this using the function `check_turbulence_cascade_slope`, which uses linear regression on the log-transformed LT83 equation (ref. to Lumley and Terray, 1983, see docstring) to calculate the spectral slope for the given frequency range. \n",
-    "\n",
-    "In our case, we're calculating the slope of each spectrum between 0.2 and 0.5 Hz. We'll use a cutoff of 20% for the error, but this can be lowered if there still appear to be erroneous estimations from visual inspection of the spectra."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Quality control dissipation rate estimation\n",
-    "slope = avg_tool.check_turbulence_cascade_slope(\n",
-    "    ds_avg[\"auto_spectra\"], freq_range=f_rng\n",
-    ")\n",
-    "\n",
-    "# Check that percent difference from -5/3 is not greater than 20%\n",
-    "mask = abs((slope[0].values - (-5 / 3)) / (-5 / 3)) <= 0.20\n",
-    "\n",
-    "# Keep good data\n",
-    "ds_avg[\"dissipation_rate\"] = ds_avg[\"dissipation_rate\"].where(mask)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "If we plot the dissipation rate below in a colormap, we can see that the profile map has a lot of missing data. One of the reasons is that the 1 Hz sampling rate doesn't provide enough information needed to make dissipation rate estimations, and the other part is that turbulence measurements push the boundaries of what ADCPs are capable of.\n",
-    "\n",
-    "Also, 1x10^-4 to 3x10^-4 $m^2/s^3$ is reasonable for a dissipation rate estimate for the 1 - 1.5 m/s current speeds measured here. They can be a magnitude greater for faster flow speeds, typically increase closer to the seafloor, and depend heavily on bathymetry and regional hydrodynamics."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x249c4a40f50>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 3. Average the Data\n",
+        "\n",
+        "As this deployment was configured in \"burst mode\", a standard step in the analysis process is to average the velocity data into time bins. \n",
+        "\n",
+        "However, if the instrument was set up in an \"averaging mode\" (where a specific profile and/or average interval was set, for instance, averaging 5 minutes of data every 30 minutes), this step would have been performed within the ADCP during deployment and can thus be skipped.\n",
+        "\n",
+        "To average the data into time bins (also known as ensembles), you should first initialize the binning tool `ADPBinner`. The parameter \"n_bin\" represents the number of data points in each ensemble. In this case, we're dealing with 300 seconds' worth of data. The \"fs\" parameter stands for the sampling frequency, which for this deployment is 1 Hz. Once the binning tool is initialized, you can use the `bin_average` function to average the data into ensembles."
       ]
-     },
-     "execution_count": 35,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "scrolled": true
+      },
+      "outputs": [],
+      "source": [
+        "window = 300 # seconds\n",
+        "avg_tool = api.ADPBinner(n_bin=ds.fs * window, fs=ds.fs)\n",
+        "ds_avg = avg_tool.bin_average(ds)"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ds_avg[\"dissipation_rate\"].plot(cmap=\"turbo\", ylim=(0, 11))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.5 Noise-Corrected Turbulence Intensity\n",
-    "\n",
-    "Now that we've calculated the noise floor for each ping, we can recalculate TI and include subtracting instrument noise using the `turbulence_intensity` function. If we subtract this from the non-noise corrected function, we can see there's a large difference\n",
-    "at slower slow speeds, but the average difference is about 0.008 (0.8%). Notice this will also remove measurements where noise is \n",
-    "high."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'TI Difference')"
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Dateframe, velocity histogram, and contour plot for 5 minute averaged velocity. "
       ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+              "<defs>\n",
+              "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+              "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+              "</symbol>\n",
+              "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+              "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+              "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+              "</symbol>\n",
+              "</defs>\n",
+              "</svg>\n",
+              "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+              "\n",
+              ":root {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, white)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              "html[theme=\"dark\"],\n",
+              "html[data-theme=\"dark\"],\n",
+              "body[data-theme=\"dark\"],\n",
+              "body.vscode-dark {\n",
+              "  --xr-font-color0: var(\n",
+              "    --jp-content-font-color0,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+              "  );\n",
+              "  --xr-font-color2: var(\n",
+              "    --jp-content-font-color2,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+              "  );\n",
+              "  --xr-font-color3: var(\n",
+              "    --jp-content-font-color3,\n",
+              "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+              "  );\n",
+              "  --xr-border-color: var(\n",
+              "    --jp-border-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+              "  );\n",
+              "  --xr-disabled-color: var(\n",
+              "    --jp-layout-color3,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+              "  );\n",
+              "  --xr-background-color: var(\n",
+              "    --jp-layout-color0,\n",
+              "    var(--pst-color-on-background, #111111)\n",
+              "  );\n",
+              "  --xr-background-color-row-even: var(\n",
+              "    --jp-layout-color1,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+              "  );\n",
+              "  --xr-background-color-row-odd: var(\n",
+              "    --jp-layout-color2,\n",
+              "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+              "  );\n",
+              "}\n",
+              "\n",
+              ".xr-wrap {\n",
+              "  display: block !important;\n",
+              "  min-width: 300px;\n",
+              "  max-width: 700px;\n",
+              "  line-height: 1.6;\n",
+              "}\n",
+              "\n",
+              ".xr-text-repr-fallback {\n",
+              "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-header {\n",
+              "  padding-top: 6px;\n",
+              "  padding-bottom: 6px;\n",
+              "  margin-bottom: 4px;\n",
+              "  border-bottom: solid 1px var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-header > div,\n",
+              ".xr-header > ul {\n",
+              "  display: inline;\n",
+              "  margin-top: 0;\n",
+              "  margin-bottom: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-obj-type,\n",
+              ".xr-obj-name,\n",
+              ".xr-group-name {\n",
+              "  margin-left: 2px;\n",
+              "  margin-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name::before {\n",
+              "  content: \"📁\";\n",
+              "  padding-right: 0.3em;\n",
+              "}\n",
+              "\n",
+              ".xr-group-name,\n",
+              ".xr-obj-type {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-sections {\n",
+              "  padding-left: 0 !important;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+              "  margin-block-start: 0;\n",
+              "  margin-block-end: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input {\n",
+              "  display: inline-block;\n",
+              "  opacity: 0;\n",
+              "  height: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input + label {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "  border: 2px solid transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label {\n",
+              "  cursor: pointer;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:focus + label {\n",
+              "  border: 2px solid var(--xr-font-color0) !important;\n",
+              "}\n",
+              "\n",
+              ".xr-section-item input:enabled + label:hover {\n",
+              "  color: var(--xr-font-color0);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary {\n",
+              "  grid-column: 1;\n",
+              "  color: var(--xr-font-color2);\n",
+              "  font-weight: 500;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary > span {\n",
+              "  display: inline-block;\n",
+              "  padding-left: 0.5em;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label {\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in + label:before {\n",
+              "  display: inline-block;\n",
+              "  content: \"►\";\n",
+              "  font-size: 11px;\n",
+              "  width: 15px;\n",
+              "  text-align: center;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:disabled + label:before {\n",
+              "  color: var(--xr-disabled-color);\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label:before {\n",
+              "  content: \"▼\";\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked + label > span {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary,\n",
+              ".xr-section-inline-details {\n",
+              "  padding-top: 4px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-inline-details {\n",
+              "  grid-column: 2 / -1;\n",
+              "}\n",
+              "\n",
+              ".xr-section-details {\n",
+              "  display: none;\n",
+              "  grid-column: 1 / -1;\n",
+              "  margin-top: 4px;\n",
+              "  margin-bottom: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box {\n",
+              "  display: inline-grid;\n",
+              "  grid-template-columns: 0px 20px auto;\n",
+              "  width: 100%;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-vline {\n",
+              "  grid-column-start: 1;\n",
+              "  border-right: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "  width: 0px;\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-hline {\n",
+              "  grid-column-start: 2;\n",
+              "  grid-row-start: 1;\n",
+              "  height: 1em;\n",
+              "  width: 20px;\n",
+              "  border-bottom: 0.2em solid;\n",
+              "  border-color: var(--xr-border-color);\n",
+              "}\n",
+              "\n",
+              ".xr-group-box-contents {\n",
+              "  grid-column-start: 3;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap {\n",
+              "  grid-column: 1 / -1;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 20px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-array-wrap > label {\n",
+              "  grid-column: 1;\n",
+              "  vertical-align: top;\n",
+              "}\n",
+              "\n",
+              ".xr-preview {\n",
+              "  color: var(--xr-font-color3);\n",
+              "}\n",
+              "\n",
+              ".xr-array-preview,\n",
+              ".xr-array-data {\n",
+              "  padding: 0 5px !important;\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-array-data,\n",
+              ".xr-array-in:checked ~ .xr-array-preview {\n",
+              "  display: none;\n",
+              "}\n",
+              "\n",
+              ".xr-array-in:checked ~ .xr-array-data,\n",
+              ".xr-array-preview {\n",
+              "  display: inline-block;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list {\n",
+              "  display: inline-block !important;\n",
+              "  list-style: none;\n",
+              "  padding: 0 !important;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li {\n",
+              "  display: inline-block;\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:before {\n",
+              "  content: \"(\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list:after {\n",
+              "  content: \")\";\n",
+              "}\n",
+              "\n",
+              ".xr-dim-list li:not(:last-child):after {\n",
+              "  content: \",\";\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-has-index {\n",
+              "  font-weight: bold;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list,\n",
+              ".xr-var-item {\n",
+              "  display: contents;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > div,\n",
+              ".xr-var-item label,\n",
+              ".xr-var-item > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-even);\n",
+              "  border-color: var(--xr-background-color-row-odd);\n",
+              "  margin-bottom: 0;\n",
+              "  padding-top: 2px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-item > .xr-var-name:hover span {\n",
+              "  padding-right: 5px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-list > li:nth-child(odd) > div,\n",
+              ".xr-var-list > li:nth-child(odd) > label,\n",
+              ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+              "  background-color: var(--xr-background-color-row-odd);\n",
+              "  border-color: var(--xr-background-color-row-even);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name {\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dims {\n",
+              "  grid-column: 2;\n",
+              "}\n",
+              "\n",
+              ".xr-var-dtype {\n",
+              "  grid-column: 3;\n",
+              "  text-align: right;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-preview {\n",
+              "  grid-column: 4;\n",
+              "}\n",
+              "\n",
+              ".xr-index-preview {\n",
+              "  grid-column: 2 / 5;\n",
+              "  color: var(--xr-font-color2);\n",
+              "}\n",
+              "\n",
+              ".xr-var-name,\n",
+              ".xr-var-dims,\n",
+              ".xr-var-dtype,\n",
+              ".xr-preview,\n",
+              ".xr-attrs dt {\n",
+              "  white-space: nowrap;\n",
+              "  overflow: hidden;\n",
+              "  text-overflow: ellipsis;\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name:hover,\n",
+              ".xr-var-dims:hover,\n",
+              ".xr-var-dtype:hover,\n",
+              ".xr-attrs dt:hover {\n",
+              "  overflow: visible;\n",
+              "  width: auto;\n",
+              "  z-index: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  display: none;\n",
+              "  border-top: 2px dotted var(--xr-background-color);\n",
+              "  padding-bottom: 20px !important;\n",
+              "  padding-top: 10px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in + label,\n",
+              ".xr-var-data-in + label,\n",
+              ".xr-index-data-in + label {\n",
+              "  padding: 0 1px;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+              ".xr-var-data-in:checked ~ .xr-var-data,\n",
+              ".xr-index-data-in:checked ~ .xr-index-data {\n",
+              "  display: block;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > table {\n",
+              "  float: right;\n",
+              "}\n",
+              "\n",
+              ".xr-var-data > pre,\n",
+              ".xr-index-data > pre,\n",
+              ".xr-var-data > table > tbody > tr {\n",
+              "  background-color: transparent !important;\n",
+              "}\n",
+              "\n",
+              ".xr-var-name span,\n",
+              ".xr-var-data,\n",
+              ".xr-index-name div,\n",
+              ".xr-index-data,\n",
+              ".xr-attrs {\n",
+              "  padding-left: 25px !important;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs,\n",
+              ".xr-var-attrs,\n",
+              ".xr-var-data,\n",
+              ".xr-index-data {\n",
+              "  grid-column: 1 / -1;\n",
+              "}\n",
+              "\n",
+              "dl.xr-attrs {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  display: grid;\n",
+              "  grid-template-columns: 125px auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt,\n",
+              ".xr-attrs dd {\n",
+              "  padding: 0;\n",
+              "  margin: 0;\n",
+              "  float: left;\n",
+              "  padding-right: 10px;\n",
+              "  width: auto;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt {\n",
+              "  font-weight: normal;\n",
+              "  grid-column: 1;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dt:hover span {\n",
+              "  display: inline-block;\n",
+              "  background: var(--xr-background-color);\n",
+              "  padding-right: 10px;\n",
+              "}\n",
+              "\n",
+              ".xr-attrs dd {\n",
+              "  grid-column: 2;\n",
+              "  white-space: pre-wrap;\n",
+              "  word-break: break-all;\n",
+              "}\n",
+              "\n",
+              ".xr-icon-database,\n",
+              ".xr-icon-file-text2,\n",
+              ".xr-no-icon {\n",
+              "  display: inline-block;\n",
+              "  vertical-align: middle;\n",
+              "  width: 1em;\n",
+              "  height: 1.5em !important;\n",
+              "  stroke-width: 0;\n",
+              "  stroke: currentColor;\n",
+              "  fill: currentColor;\n",
+              "}\n",
+              "\n",
+              ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+              ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+              ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+              "  color: var(--xr-font-color0);\n",
+              "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+              "  stroke-width: 0.8px;\n",
+              "}\n",
+              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
+              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
+              "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
+              "Coordinates:\n",
+              "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+              "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
+              "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
+              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+              "  * beam            (beam) int32 16B 1 2 3 4\n",
+              "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+              "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+              "  * q               (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+              "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+              "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+              "Data variables: (12/38)\n",
+              "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+              "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+              "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+              "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+              "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
+              "    ...              ...\n",
+              "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+              "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+              "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+              "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+              "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+              "Attributes: (12/41)\n",
+              "    fs:                        1\n",
+              "    n_bin:                     300\n",
+              "    n_fft:                     300\n",
+              "    description:               Binned averages calculated from ensembles of s...\n",
+              "    filehead_config:           {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;...\n",
+              "    inst_model:                Signature1000\n",
+              "    ...                        ...\n",
+              "    has_imu:                   1\n",
+              "    beam_angle:                25\n",
+              "    range_offset:              0.6\n",
+              "    declination:               15.8\n",
+              "    declination_in_orientmat:  1\n",
+              "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1811e13e-f880-4011-b109-b340e090ae0a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1811e13e-f880-4011-b109-b340e090ae0a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-dc51f27a-6892-46c8-9f35-4aca9d0bb526' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dc51f27a-6892-46c8-9f35-4aca9d0bb526' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-3969c29d-3f99-4470-9c2b-282fc5be82c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3969c29d-3f99-4470-9c2b-282fc5be82c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757c60e7-45bc-469c-b109-075c6d118451' class='xr-var-data-in' type='checkbox'><label for='data-757c60e7-45bc-469c-b109-075c6d118451' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
+              "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
+              "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
+              "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
+              "       &#x27;2020-08-15T01:02:30.001023769&#x27;, &#x27;2020-08-15T01:07:30.001024723&#x27;,\n",
+              "       &#x27;2020-08-15T01:12:30.001034259&#x27;, &#x27;2020-08-15T01:17:30.001035451&#x27;,\n",
+              "       &#x27;2020-08-15T01:22:30.001024961&#x27;, &#x27;2020-08-15T01:27:30.001025438&#x27;,\n",
+              "       &#x27;2020-08-15T01:32:30.001025676&#x27;, &#x27;2020-08-15T01:37:30.001031875&#x27;,\n",
+              "       &#x27;2020-08-15T01:42:30.001029014&#x27;, &#x27;2020-08-15T01:47:30.001030683&#x27;,\n",
+              "       &#x27;2020-08-15T01:52:30.001033067&#x27;, &#x27;2020-08-15T01:57:30.001029014&#x27;,\n",
+              "       &#x27;2020-08-15T02:02:30.001028299&#x27;, &#x27;2020-08-15T02:07:30.001020908&#x27;,\n",
+              "       &#x27;2020-08-15T02:12:30.001016378&#x27;, &#x27;2020-08-15T02:17:30.001012802&#x27;,\n",
+              "       &#x27;2020-08-15T02:22:30.001014709&#x27;, &#x27;2020-08-15T02:27:30.001018524&#x27;,\n",
+              "       &#x27;2020-08-15T02:32:30.001022577&#x27;, &#x27;2020-08-15T02:37:30.001020193&#x27;,\n",
+              "       &#x27;2020-08-15T02:42:30.001002311&#x27;, &#x27;2020-08-15T02:47:30.001003503&#x27;,\n",
+              "       &#x27;2020-08-15T02:52:30.001002550&#x27;, &#x27;2020-08-15T02:57:30.001000165&#x27;,\n",
+              "       &#x27;2020-08-15T03:02:30.001000642&#x27;, &#x27;2020-08-15T03:07:30.001000404&#x27;,\n",
+              "       &#x27;2020-08-15T03:12:30.000999450&#x27;, &#x27;2020-08-15T03:17:30.001003026&#x27;,\n",
+              "       &#x27;2020-08-15T03:22:30.001004695&#x27;, &#x27;2020-08-15T03:27:30.001004219&#x27;,\n",
+              "       &#x27;2020-08-15T03:32:30.001001834&#x27;, &#x27;2020-08-15T03:37:30.001005887&#x27;,\n",
+              "       &#x27;2020-08-15T03:42:30.001003742&#x27;, &#x27;2020-08-15T03:47:30.001000642&#x27;,\n",
+              "       &#x27;2020-08-15T03:52:30.001000404&#x27;, &#x27;2020-08-15T03:57:30.001001834&#x27;,\n",
+              "       &#x27;2020-08-15T04:02:30.001001834&#x27;, &#x27;2020-08-15T04:07:30.001001358&#x27;,\n",
+              "       &#x27;2020-08-15T04:12:30.001004695&#x27;, &#x27;2020-08-15T04:17:30.001001358&#x27;,\n",
+              "       &#x27;2020-08-15T04:22:30.001009464&#x27;, &#x27;2020-08-15T04:27:30.001006603&#x27;,\n",
+              "       &#x27;2020-08-15T04:32:30.001002550&#x27;, &#x27;2020-08-15T04:37:30.001004695&#x27;,\n",
+              "       &#x27;2020-08-15T04:42:30.001004934&#x27;, &#x27;2020-08-15T04:47:30.001004934&#x27;,\n",
+              "       &#x27;2020-08-15T04:52:30.001004457&#x27;, &#x27;2020-08-15T04:57:30.001002788&#x27;,\n",
+              "       &#x27;2020-08-15T05:02:30.001008749&#x27;, &#x27;2020-08-15T05:07:30.001017570&#x27;,\n",
+              "       &#x27;2020-08-15T05:12:30.001015186&#x27;, &#x27;2020-08-15T05:17:30.001005887&#x27;,\n",
+              "       &#x27;2020-08-15T05:22:30.001001358&#x27;, &#x27;2020-08-15T05:27:30.001011610&#x27;,\n",
+              "       &#x27;2020-08-15T05:32:30.001020431&#x27;, &#x27;2020-08-15T05:37:30.001011848&#x27;,\n",
+              "       &#x27;2020-08-15T05:42:30.001020908&#x27;, &#x27;2020-08-15T05:47:30.001013517&#x27;,\n",
+              "       &#x27;2020-08-15T05:52:30.001021146&#x27;, &#x27;2020-08-15T05:57:30.001010656&#x27;,\n",
+              "       &#x27;2020-08-15T06:02:30.001004219&#x27;, &#x27;2020-08-15T06:07:30.001012563&#x27;,\n",
+              "       &#x27;2020-08-15T06:12:30.001021862&#x27;, &#x27;2020-08-15T06:17:30.001018524&#x27;,\n",
+              "       &#x27;2020-08-15T06:22:30.001016139&#x27;, &#x27;2020-08-15T06:27:30.001016616&#x27;,\n",
+              "       &#x27;2020-08-15T06:32:30.001012325&#x27;, &#x27;2020-08-15T06:37:30.001016378&#x27;,\n",
+              "       &#x27;2020-08-15T06:42:30.001021862&#x27;, &#x27;2020-08-15T06:47:30.001023769&#x27;,\n",
+              "       &#x27;2020-08-15T06:52:30.001024007&#x27;, &#x27;2020-08-15T06:57:30.001014709&#x27;,\n",
+              "       &#x27;2020-08-15T07:02:30.001006126&#x27;, &#x27;2020-08-15T07:07:30.001019477&#x27;,\n",
+              "       &#x27;2020-08-15T07:12:30.001013994&#x27;, &#x27;2020-08-15T07:17:30.001016855&#x27;,\n",
+              "       &#x27;2020-08-15T07:22:30.001019239&#x27;, &#x27;2020-08-15T07:27:30.001024961&#x27;,\n",
+              "       &#x27;2020-08-15T07:32:30.001011610&#x27;, &#x27;2020-08-15T07:37:30.001024484&#x27;,\n",
+              "       &#x27;2020-08-15T07:42:30.001018524&#x27;, &#x27;2020-08-15T07:47:30.001029968&#x27;,\n",
+              "       &#x27;2020-08-15T07:52:30.001009464&#x27;, &#x27;2020-08-15T07:57:30.001014232&#x27;,\n",
+              "       &#x27;2020-08-15T08:02:30.001011610&#x27;, &#x27;2020-08-15T08:07:30.001028299&#x27;,\n",
+              "       &#x27;2020-08-15T08:12:30.001027107&#x27;, &#x27;2020-08-15T08:17:30.001024723&#x27;,\n",
+              "       &#x27;2020-08-15T08:22:30.001022577&#x27;, &#x27;2020-08-15T08:27:30.001018047&#x27;,\n",
+              "       &#x27;2020-08-15T08:32:30.001019477&#x27;, &#x27;2020-08-15T08:37:30.001017808&#x27;,\n",
+              "       &#x27;2020-08-15T08:42:30.001018762&#x27;, &#x27;2020-08-15T08:47:30.001015186&#x27;,\n",
+              "       &#x27;2020-08-15T08:52:30.001020431&#x27;, &#x27;2020-08-15T08:57:30.001026630&#x27;,\n",
+              "       &#x27;2020-08-15T09:02:30.001021146&#x27;, &#x27;2020-08-15T09:07:30.001016378&#x27;,\n",
+              "       &#x27;2020-08-15T09:12:30.001025676&#x27;, &#x27;2020-08-15T09:17:30.001024246&#x27;,\n",
+              "       &#x27;2020-08-15T09:22:30.001026630&#x27;, &#x27;2020-08-15T09:27:30.001017570&#x27;,\n",
+              "       &#x27;2020-08-15T09:32:30.001015901&#x27;, &#x27;2020-08-15T09:37:30.001016139&#x27;,\n",
+              "       &#x27;2020-08-15T09:42:30.001018762&#x27;, &#x27;2020-08-15T09:47:30.001014709&#x27;,\n",
+              "       &#x27;2020-08-15T09:52:30.001016378&#x27;, &#x27;2020-08-15T09:57:30.001024961&#x27;,\n",
+              "       &#x27;2020-08-15T10:02:30.001021146&#x27;, &#x27;2020-08-15T10:07:30.001022100&#x27;,\n",
+              "       &#x27;2020-08-15T10:12:30.001017808&#x27;, &#x27;2020-08-15T10:17:30.001013994&#x27;,\n",
+              "       &#x27;2020-08-15T10:22:30.001018762&#x27;, &#x27;2020-08-15T10:27:30.001021385&#x27;,\n",
+              "       &#x27;2020-08-15T10:32:30.001016855&#x27;, &#x27;2020-08-15T10:37:30.001021385&#x27;,\n",
+              "       &#x27;2020-08-15T10:42:30.001015186&#x27;, &#x27;2020-08-15T10:47:30.001020193&#x27;,\n",
+              "       &#x27;2020-08-15T10:52:30.001021623&#x27;, &#x27;2020-08-15T10:57:30.001021862&#x27;,\n",
+              "       &#x27;2020-08-15T11:02:30.001018047&#x27;, &#x27;2020-08-15T11:07:30.001021146&#x27;,\n",
+              "       &#x27;2020-08-15T11:12:30.001011848&#x27;, &#x27;2020-08-15T11:17:30.001015901&#x27;,\n",
+              "       &#x27;2020-08-15T11:22:30.001014232&#x27;, &#x27;2020-08-15T11:27:30.001015663&#x27;,\n",
+              "       &#x27;2020-08-15T11:32:30.001012325&#x27;, &#x27;2020-08-15T11:37:30.001004457&#x27;,\n",
+              "       &#x27;2020-08-15T11:42:30.001018524&#x27;, &#x27;2020-08-15T11:47:30.001023292&#x27;,\n",
+              "       &#x27;2020-08-15T11:52:30.001009464&#x27;, &#x27;2020-08-15T11:57:30.001002311&#x27;,\n",
+              "       &#x27;2020-08-15T12:02:30.001004695&#x27;, &#x27;2020-08-15T12:07:30.001007556&#x27;,\n",
+              "       &#x27;2020-08-15T12:12:30.001012086&#x27;, &#x27;2020-08-15T12:17:30.001007080&#x27;,\n",
+              "       &#x27;2020-08-15T12:22:30.001011371&#x27;, &#x27;2020-08-15T12:27:30.001014471&#x27;,\n",
+              "       &#x27;2020-08-15T12:32:30.001016378&#x27;, &#x27;2020-08-15T12:37:30.001012563&#x27;,\n",
+              "       &#x27;2020-08-15T12:42:30.001015901&#x27;, &#x27;2020-08-15T12:47:30.001010417&#x27;,\n",
+              "       &#x27;2020-08-15T12:52:30.001009464&#x27;, &#x27;2020-08-15T12:57:30.001010894&#x27;,\n",
+              "       &#x27;2020-08-15T13:02:30.001016855&#x27;, &#x27;2020-08-15T13:07:30.001020908&#x27;,\n",
+              "       &#x27;2020-08-15T13:12:30.001018762&#x27;, &#x27;2020-08-15T13:17:30.001018762&#x27;,\n",
+              "       &#x27;2020-08-15T13:22:30.001018047&#x27;, &#x27;2020-08-15T13:27:30.001013517&#x27;,\n",
+              "       &#x27;2020-08-15T13:32:30.001015424&#x27;, &#x27;2020-08-15T13:37:30.001009225&#x27;,\n",
+              "       &#x27;2020-08-15T13:42:30.001011133&#x27;, &#x27;2020-08-15T13:47:30.001008749&#x27;,\n",
+              "       &#x27;2020-08-15T13:52:30.001019477&#x27;, &#x27;2020-08-15T13:57:30.001022338&#x27;,\n",
+              "       &#x27;2020-08-15T14:02:30.001019716&#x27;, &#x27;2020-08-15T14:07:30.001026868&#x27;,\n",
+              "       &#x27;2020-08-15T14:12:30.001021623&#x27;, &#x27;2020-08-15T14:17:30.001034021&#x27;,\n",
+              "       &#x27;2020-08-15T14:22:30.001024961&#x27;, &#x27;2020-08-15T14:27:30.001032352&#x27;,\n",
+              "       &#x27;2020-08-15T14:32:30.001023292&#x27;, &#x27;2020-08-15T14:37:30.001024484&#x27;,\n",
+              "       &#x27;2020-08-15T14:42:30.001044034&#x27;, &#x27;2020-08-15T14:47:30.001032352&#x27;,\n",
+              "       &#x27;2020-08-15T14:52:30.001019239&#x27;, &#x27;2020-08-15T14:57:30.001032829&#x27;,\n",
+              "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
+              "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
+              "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
+              "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-d2b52450-e391-4d06-90f0-0cb100d2f2f2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d2b52450-e391-4d06-90f0-0cb100d2f2f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32c14244-7cdf-4e3e-90df-be017aa63f72' class='xr-var-data-in' type='checkbox'><label for='data-32c14244-7cdf-4e3e-90df-be017aa63f72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-7d3f1d76-3df8-454f-86e3-064b400d7ae5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d3f1d76-3df8-454f-86e3-064b400d7ae5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b0419ba-1197-4d3b-9d05-4fa146751fd4' class='xr-var-data-in' type='checkbox'><label for='data-9b0419ba-1197-4d3b-9d05-4fa146751fd4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-9175ac6e-8477-4ec6-88c6-762c6864e8f0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9175ac6e-8477-4ec6-88c6-762c6864e8f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-889ace0f-984b-4d07-a712-d467bec0921d' class='xr-var-data-in' type='checkbox'><label for='data-889ace0f-984b-4d07-a712-d467bec0921d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-8600c4a1-8c7a-4709-9154-cd20b7782c4f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8600c4a1-8c7a-4709-9154-cd20b7782c4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56b50da3-96cd-408f-a003-37f36a45e561' class='xr-var-data-in' type='checkbox'><label for='data-56b50da3-96cd-408f-a003-37f36a45e561' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-06294a44-81e7-4d5d-b666-6f287898e8c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06294a44-81e7-4d5d-b666-6f287898e8c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f07b72c-afd6-4db8-965b-827699946c3f' class='xr-var-data-in' type='checkbox'><label for='data-8f07b72c-afd6-4db8-965b-827699946c3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-e6d831ce-bf06-4075-9e3f-685100f7941b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6d831ce-bf06-4075-9e3f-685100f7941b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cf4aa13-7750-4c5c-af88-d64dd89c423f' class='xr-var-data-in' type='checkbox'><label for='data-5cf4aa13-7750-4c5c-af88-d64dd89c423f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-57294f19-d384-4b0c-b7ec-2df7da1fc422' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57294f19-d384-4b0c-b7ec-2df7da1fc422' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff1bb7f-9c0f-408d-b60f-4df13caebe38' class='xr-var-data-in' type='checkbox'><label for='data-8ff1bb7f-9c0f-408d-b60f-4df13caebe38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-12dc82a3-3656-44d2-9aa8-be453b1554e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12dc82a3-3656-44d2-9aa8-be453b1554e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10ace266-3709-4d44-bb57-be6e9383e03b' class='xr-var-data-in' type='checkbox'><label for='data-10ace266-3709-4d44-bb57-be6e9383e03b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
+              "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
+              "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
+              "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T01:02:29.938493013&#x27;, &#x27;2020-08-15T01:07:29.938492536&#x27;,\n",
+              "       &#x27;2020-08-15T01:12:29.938490867&#x27;, &#x27;2020-08-15T01:17:29.938497781&#x27;,\n",
+              "       &#x27;2020-08-15T01:22:29.938496112&#x27;, &#x27;2020-08-15T01:27:29.938498497&#x27;,\n",
+              "       &#x27;2020-08-15T01:32:29.938496589&#x27;, &#x27;2020-08-15T01:37:29.938497781&#x27;,\n",
+              "       &#x27;2020-08-15T01:42:29.938495635&#x27;, &#x27;2020-08-15T01:47:29.938497066&#x27;,\n",
+              "       &#x27;2020-08-15T01:52:29.938498735&#x27;, &#x27;2020-08-15T01:57:29.938496112&#x27;,\n",
+              "       &#x27;2020-08-15T02:02:29.938496589&#x27;, &#x27;2020-08-15T02:07:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T02:12:29.938497304&#x27;, &#x27;2020-08-15T02:17:29.938496828&#x27;,\n",
+              "       &#x27;2020-08-15T02:22:29.938496112&#x27;, &#x27;2020-08-15T02:27:29.938496828&#x27;,\n",
+              "       &#x27;2020-08-15T02:32:29.938496112&#x27;, &#x27;2020-08-15T02:37:29.938497304&#x27;,\n",
+              "       &#x27;2020-08-15T02:42:29.938495159&#x27;, &#x27;2020-08-15T02:47:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T02:52:29.938490867&#x27;, &#x27;2020-08-15T02:57:29.938492059&#x27;,\n",
+              "       &#x27;2020-08-15T03:02:29.938489675&#x27;, &#x27;2020-08-15T03:07:29.938488245&#x27;,\n",
+              "       &#x27;2020-08-15T03:12:29.938485622&#x27;, &#x27;2020-08-15T03:17:29.938485622&#x27;,\n",
+              "       &#x27;2020-08-15T03:22:29.938488245&#x27;, &#x27;2020-08-15T03:27:29.938485145&#x27;,\n",
+              "       &#x27;2020-08-15T03:32:29.938486099&#x27;, &#x27;2020-08-15T03:37:29.938482046&#x27;,\n",
+              "       &#x27;2020-08-15T03:42:29.938489437&#x27;, &#x27;2020-08-15T03:47:29.938489437&#x27;,\n",
+              "       &#x27;2020-08-15T03:52:29.938485860&#x27;, &#x27;2020-08-15T03:57:29.938491582&#x27;,\n",
+              "       &#x27;2020-08-15T04:02:29.938488006&#x27;, &#x27;2020-08-15T04:07:29.938491106&#x27;,\n",
+              "       &#x27;2020-08-15T04:12:29.938492059&#x27;, &#x27;2020-08-15T04:17:29.938487052&#x27;,\n",
+              "       &#x27;2020-08-15T04:22:29.938489675&#x27;, &#x27;2020-08-15T04:27:29.938491582&#x27;,\n",
+              "       &#x27;2020-08-15T04:32:29.938491106&#x27;, &#x27;2020-08-15T04:37:29.938493251&#x27;,\n",
+              "       &#x27;2020-08-15T04:42:29.938489675&#x27;, &#x27;2020-08-15T04:47:29.938492059&#x27;,\n",
+              "       &#x27;2020-08-15T04:52:29.938491582&#x27;, &#x27;2020-08-15T04:57:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T05:02:29.938491106&#x27;, &#x27;2020-08-15T05:07:29.938499212&#x27;,\n",
+              "       &#x27;2020-08-15T05:12:29.938491821&#x27;, &#x27;2020-08-15T05:17:29.938493490&#x27;,\n",
+              "       &#x27;2020-08-15T05:22:29.938495397&#x27;, &#x27;2020-08-15T05:27:29.938490390&#x27;,\n",
+              "       &#x27;2020-08-15T05:32:29.938493967&#x27;, &#x27;2020-08-15T05:37:29.938493728&#x27;,\n",
+              "       &#x27;2020-08-15T05:42:29.938491582&#x27;, &#x27;2020-08-15T05:47:29.938493013&#x27;,\n",
+              "       &#x27;2020-08-15T05:52:29.938495159&#x27;, &#x27;2020-08-15T05:57:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T06:02:29.938493013&#x27;, &#x27;2020-08-15T06:07:29.938496589&#x27;,\n",
+              "       &#x27;2020-08-15T06:12:29.938494920&#x27;, &#x27;2020-08-15T06:17:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T06:22:29.938493728&#x27;, &#x27;2020-08-15T06:27:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T06:32:29.938492536&#x27;, &#x27;2020-08-15T06:37:29.938495159&#x27;,\n",
+              "       &#x27;2020-08-15T06:42:29.938496112&#x27;, &#x27;2020-08-15T06:47:29.938497304&#x27;,\n",
+              "       &#x27;2020-08-15T06:52:29.938496112&#x27;, &#x27;2020-08-15T06:57:29.938493728&#x27;,\n",
+              "       &#x27;2020-08-15T07:02:29.938497304&#x27;, &#x27;2020-08-15T07:07:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T07:12:29.938492059&#x27;, &#x27;2020-08-15T07:17:29.938493490&#x27;,\n",
+              "       &#x27;2020-08-15T07:22:29.938493967&#x27;, &#x27;2020-08-15T07:27:29.938497304&#x27;,\n",
+              "       &#x27;2020-08-15T07:32:29.938494443&#x27;, &#x27;2020-08-15T07:37:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T07:42:29.938495635&#x27;, &#x27;2020-08-15T07:47:29.938493967&#x27;,\n",
+              "       &#x27;2020-08-15T07:52:29.938492298&#x27;, &#x27;2020-08-15T07:57:29.938489675&#x27;,\n",
+              "       &#x27;2020-08-15T08:02:29.938493013&#x27;, &#x27;2020-08-15T08:07:29.938493728&#x27;,\n",
+              "       &#x27;2020-08-15T08:12:29.938497066&#x27;, &#x27;2020-08-15T08:17:29.938497781&#x27;,\n",
+              "       &#x27;2020-08-15T08:22:29.938495159&#x27;, &#x27;2020-08-15T08:27:29.938492774&#x27;,\n",
+              "       &#x27;2020-08-15T08:32:29.938495397&#x27;, &#x27;2020-08-15T08:37:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T08:42:29.938494920&#x27;, &#x27;2020-08-15T08:47:29.938494682&#x27;,\n",
+              "       &#x27;2020-08-15T08:52:29.938494443&#x27;, &#x27;2020-08-15T08:57:29.938491821&#x27;,\n",
+              "       &#x27;2020-08-15T09:02:29.938497066&#x27;, &#x27;2020-08-15T09:07:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T09:12:29.938495397&#x27;, &#x27;2020-08-15T09:17:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T09:22:29.938498020&#x27;, &#x27;2020-08-15T09:27:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T09:32:29.938495159&#x27;, &#x27;2020-08-15T09:37:29.938498735&#x27;,\n",
+              "       &#x27;2020-08-15T09:42:29.938493728&#x27;, &#x27;2020-08-15T09:47:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T09:52:29.938500642&#x27;, &#x27;2020-08-15T09:57:29.938496589&#x27;,\n",
+              "       &#x27;2020-08-15T10:02:29.938497781&#x27;, &#x27;2020-08-15T10:07:29.938500881&#x27;,\n",
+              "       &#x27;2020-08-15T10:12:29.938504457&#x27;, &#x27;2020-08-15T10:17:29.938501358&#x27;,\n",
+              "       &#x27;2020-08-15T10:22:29.938507556&#x27;, &#x27;2020-08-15T10:27:29.938496112&#x27;,\n",
+              "       &#x27;2020-08-15T10:32:29.938495635&#x27;, &#x27;2020-08-15T10:37:29.938500165&#x27;,\n",
+              "       &#x27;2020-08-15T10:42:29.938496112&#x27;, &#x27;2020-08-15T10:47:29.938493251&#x27;,\n",
+              "       &#x27;2020-08-15T10:52:29.938493728&#x27;, &#x27;2020-08-15T10:57:29.938492536&#x27;,\n",
+              "       &#x27;2020-08-15T11:02:29.938492774&#x27;, &#x27;2020-08-15T11:07:29.938492774&#x27;,\n",
+              "       &#x27;2020-08-15T11:12:29.938493967&#x27;, &#x27;2020-08-15T11:17:29.938494443&#x27;,\n",
+              "       &#x27;2020-08-15T11:22:29.938496589&#x27;, &#x27;2020-08-15T11:27:29.938496112&#x27;,\n",
+              "       &#x27;2020-08-15T11:32:29.938495397&#x27;, &#x27;2020-08-15T11:37:29.938493967&#x27;,\n",
+              "       &#x27;2020-08-15T11:42:29.938493013&#x27;, &#x27;2020-08-15T11:47:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T11:52:29.938493967&#x27;, &#x27;2020-08-15T11:57:29.938498735&#x27;,\n",
+              "       &#x27;2020-08-15T12:02:29.938496589&#x27;, &#x27;2020-08-15T12:07:29.938498020&#x27;,\n",
+              "       &#x27;2020-08-15T12:12:29.938494443&#x27;, &#x27;2020-08-15T12:17:29.938495159&#x27;,\n",
+              "       &#x27;2020-08-15T12:22:29.938495635&#x27;, &#x27;2020-08-15T12:27:29.938497066&#x27;,\n",
+              "       &#x27;2020-08-15T12:32:29.938493967&#x27;, &#x27;2020-08-15T12:37:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T12:42:29.938496112&#x27;, &#x27;2020-08-15T12:47:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T12:52:29.938494443&#x27;, &#x27;2020-08-15T12:57:29.938496589&#x27;,\n",
+              "       &#x27;2020-08-15T13:02:29.938494205&#x27;, &#x27;2020-08-15T13:07:29.938494205&#x27;,\n",
+              "       &#x27;2020-08-15T13:12:29.938492536&#x27;, &#x27;2020-08-15T13:17:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T13:22:29.938493251&#x27;, &#x27;2020-08-15T13:27:29.938495397&#x27;,\n",
+              "       &#x27;2020-08-15T13:32:29.938494920&#x27;, &#x27;2020-08-15T13:37:29.938497066&#x27;,\n",
+              "       &#x27;2020-08-15T13:42:29.938497304&#x27;, &#x27;2020-08-15T13:47:29.938494920&#x27;,\n",
+              "       &#x27;2020-08-15T13:52:29.938493490&#x27;, &#x27;2020-08-15T13:57:29.938492774&#x27;,\n",
+              "       &#x27;2020-08-15T14:02:29.938496112&#x27;, &#x27;2020-08-15T14:07:29.938489675&#x27;,\n",
+              "       &#x27;2020-08-15T14:12:29.938489913&#x27;, &#x27;2020-08-15T14:17:29.938494443&#x27;,\n",
+              "       &#x27;2020-08-15T14:22:29.938495397&#x27;, &#x27;2020-08-15T14:27:29.938492774&#x27;,\n",
+              "       &#x27;2020-08-15T14:32:29.938491582&#x27;, &#x27;2020-08-15T14:37:29.938493251&#x27;,\n",
+              "       &#x27;2020-08-15T14:42:29.938492536&#x27;, &#x27;2020-08-15T14:47:29.938492774&#x27;,\n",
+              "       &#x27;2020-08-15T14:52:29.938491106&#x27;, &#x27;2020-08-15T14:57:29.938495635&#x27;,\n",
+              "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
+              "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
+              "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
+              "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-124e68c7-9e14-433a-970b-214ec1c81d73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-124e68c7-9e14-433a-970b-214ec1c81d73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a801f5e0-b92a-4246-8fb7-ff85a6c7216f' class='xr-var-data-in' type='checkbox'><label for='data-a801f5e0-b92a-4246-8fb7-ff85a6c7216f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5355f84-2e22-4402-9544-d18d997db428' class='xr-section-summary-in' type='checkbox'  ><label for='section-a5355f84-2e22-4402-9544-d18d997db428' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-7b15658c-9552-4593-a483-d27435d85551' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b15658c-9552-4593-a483-d27435d85551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8386bd7-0425-4809-ac90-d409300f755c' class='xr-var-data-in' type='checkbox'><label for='data-e8386bd7-0425-4809-ac90-d409300f755c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
+              "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
+              "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
+              "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
+              "       1500.6763, 1500.2716, 1500.1096, 1499.8009, 1499.5637, 1499.3373,\n",
+              "       1499.2163, 1499.0955, 1498.9806, 1498.8579, 1498.7637, 1498.6821,\n",
+              "       1498.6133, 1498.5066, 1498.5637, 1498.7421, 1498.8367, 1498.984 ,\n",
+              "       1498.9717, 1498.9644, 1499.0553, 1499.21  , 1499.2789, 1499.2766,\n",
+              "       1499.265 , 1499.2623, 1499.3181, 1499.2903, 1499.3444, 1499.2922,\n",
+              "       1499.2983, 1499.195 , 1499.2087, 1499.212 , 1499.2494, 1499.2227,\n",
+              "       1499.1742, 1499.1772, 1499.1937, 1499.2306, 1499.2719, 1499.3043,\n",
+              "       1499.4073, 1499.3677, 1499.4554, 1499.5647, 1499.6683, 1499.7489,\n",
+              "       1499.8341, 1499.8446, 1499.8396, 1499.9257, 1499.781 , 1499.8274,\n",
+              "       1499.7506, 1499.8904, 1499.7473, 1499.7411, 1499.7415, 1499.7079,\n",
+              "       1499.508 , 1499.7562, 1499.5327, 1499.4186, 1499.4877, 1499.1946,\n",
+              "       1499.1821, 1499.466 , 1499.5144, 1499.7024, 1499.8877, 1499.8373,\n",
+              "       1499.8597, 1500.1703, 1500.0886, 1500.082 , 1500.0476, 1499.9003,\n",
+              "       1499.8434, 1498.8927, 1497.6433, 1496.299 , 1495.386 , 1495.2273,\n",
+              "       1494.9376, 1494.7117, 1494.9341, 1495.1063, 1495.0103, 1494.7747,\n",
+              "       1494.5977, 1494.4548, 1494.4042, 1494.3356, 1494.229 , 1494.0669,\n",
+              "       1493.7662, 1493.4755, 1493.3303, 1493.1544, 1492.8477, 1492.7877,\n",
+              "       1492.8064, 1493.0189, 1493.5558, 1494.0146, 1494.7506, 1495.2681,\n",
+              "       1496.2244, 1496.8036, 1497.5472, 1498.0507, 1498.3839, 1498.663 ,\n",
+              "       1498.8971, 1499.136 , 1499.3384, 1499.535 , 1499.5739, 1499.5245,\n",
+              "       1499.4437, 1499.4467, 1499.5509, 1499.6014, 1499.5997, 1499.5935,\n",
+              "       1499.525 , 1499.4967, 1499.4364, 1499.4977, 1499.503 , 1499.5526,\n",
+              "       1499.5083, 1499.5023, 1499.474 , 1499.4028, 1499.436 , 1499.4973,\n",
+              "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
+              "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
+              "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
+              "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-83dd93a3-3695-4ab1-b721-54f82362d41b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83dd93a3-3695-4ab1-b721-54f82362d41b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ce0ce88-1900-4949-bb45-ce3df3c7c592' class='xr-var-data-in' type='checkbox'><label for='data-9ce0ce88-1900-4949-bb45-ce3df3c7c592' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
+              "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
+              "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
+              "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
+              "       14.572268 , 14.502767 , 14.376032 , 14.268402 , 14.178566 ,\n",
+              "       14.055    , 14.005532 , 13.911533 , 13.838566 , 13.7688675,\n",
+              "       13.7339325, 13.696598 , 13.661633 , 13.626367 , 13.597433 ,\n",
+              "       13.572568 , 13.552067 , 13.520534 , 13.538133 , 13.592899 ,\n",
+              "       13.620734 , 13.665668 , 13.661699 , 13.658334 , 13.686766 ,\n",
+              "       13.7354   , 13.754033 , 13.754901 , 13.7525   , 13.751934 ,\n",
+              "       13.767399 , 13.760633 , 13.776802 , 13.761433 , 13.7625   ,\n",
+              "       13.731066 , 13.7371   , 13.737367 , 13.748701 , 13.741634 ,\n",
+              "       13.726335 , 13.726666 , 13.7323   , 13.743701 , 13.756766 ,\n",
+              "       13.766968 , 13.797334 , 13.7852   , 13.812601 , 13.847366 ,\n",
+              "       13.878734 , 13.903067 , 13.928333 , 13.931099 , 13.930567 ,\n",
+              "       13.957533 , 13.912533 , 13.9264   , 13.9032   , 13.947433 ,\n",
+              "       13.902601 , 13.900833 , 13.900665 , 13.890833 , 13.830032 ,\n",
+              "       13.9046335, 13.8364   , 13.801933 , 13.8241   , 13.735    ,\n",
+              "       13.732666 , 13.818233 , 13.8298   , 13.888301 , 13.944167 ,\n",
+              "       13.928867 , 13.9361   , 14.0331   , 14.008999 , 14.006901 ,\n",
+              "       13.992832 , 13.946533 , 13.9282   , 13.643267 , 13.266466 ,\n",
+              "       12.865967 , 12.595367 , 12.5469   , 12.462267 , 12.3959   ,\n",
+              "       12.461133 , 12.512366 , 12.482166 , 12.411167 , 12.3605995,\n",
+              "       12.3201   , 12.303568 , 12.284267 , 12.252732 , 12.203699 ,\n",
+              "       12.118533 , 12.031001 , 11.988433 , 11.939434 , 11.8505   ,\n",
+              "       11.8341   , 11.837234 , 11.8984995, 12.0561   , 12.189    ,\n",
+              "       12.403767 , 12.5546   , 12.837867 , 13.010934 , 13.233933 ,\n",
+              "       13.384068 , 13.485199 , 13.565999 , 13.639567 , 13.711732 ,\n",
+              "       13.774034 , 13.829665 , 13.838365 , 13.829668 , 13.8013   ,\n",
+              "       13.805167 , 13.833833 , 13.855499 , 13.857698 , 13.844232 ,\n",
+              "       13.831333 , 13.816167 , 13.802168 , 13.811266 , 13.820599 ,\n",
+              "       13.834399 , 13.828466 , 13.826566 , 13.810034 , 13.792601 ,\n",
+              "       13.800402 , 13.820232 , 13.830032 , 13.8446665, 13.8607   ,\n",
+              "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
+              "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
+              "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
+              "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-8d769817-807e-4573-83b5-e886781433ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d769817-807e-4573-83b5-e886781433ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00c9861b-b802-4d19-b78e-2dfec17e0afd' class='xr-var-data-in' type='checkbox'><label for='data-00c9861b-b802-4d19-b78e-2dfec17e0afd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
+              "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
+              "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
+              "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
+              "       9.218047 , 9.186557 , 9.157551 , 9.123754 , 9.09348  , 9.059697 ,\n",
+              "       9.026804 , 8.994499 , 8.95571  , 8.92198  , 8.886473 , 8.853367 ,\n",
+              "       8.813594 , 8.782229 , 8.74448  , 8.708926 , 8.674907 , 8.637604 ,\n",
+              "       8.602573 , 8.560874 , 8.524677 , 8.48187  , 8.4449835, 8.400766 ,\n",
+              "       8.365373 , 8.322662 , 8.28713  , 8.248011 , 8.21333  , 8.178404 ,\n",
+              "       8.14623  , 8.109827 , 8.072543 , 8.039574 , 7.9980125, 7.963136 ,\n",
+              "       7.926347 , 7.8918767, 7.8531103, 7.824253 , 7.7964296, 7.7649107,\n",
+              "       7.7383432, 7.7130632, 7.6841335, 7.65858  , 7.633538 , 7.609003 ,\n",
+              "       7.592057 , 7.573613 , 7.5537395, 7.533187 , 7.5146875, 7.497063 ,\n",
+              "       7.48256  , 7.472039 , 7.454433 , 7.4437304, 7.4306965, 7.422947 ,\n",
+              "       7.4138427, 7.4127507, 7.407543 , 7.4021435, 7.40189  , 7.4006333,\n",
+              "       7.401152 , 7.3961263, 7.4010367, 7.4031525, 7.414211 , 7.4199567,\n",
+              "       7.4243903, 7.4346695, 7.4523306, 7.4677606, 7.47785  , 7.4955306,\n",
+              "       7.507134 , 7.52034  , 7.540297 , 7.5592594, 7.583973 , 7.6029363,\n",
+              "       7.623276 , 7.6508303, 7.67267  , 7.6968994, 7.7202635, 7.7465167,\n",
+              "       7.7706933, 7.795326 , 7.820833 , 7.8509097, 7.8781033, 7.9117236,\n",
+              "       7.9442267, 7.9752865, 8.007596 , 8.042522 , 8.077546 , 8.108029 ,\n",
+              "       8.1417265, 8.17497  , 8.210143 , 8.243827 , 8.281553 , 8.317181 ,\n",
+              "       8.35565  , 8.390187 , 8.42794  , 8.465797 , 8.50642  , 8.54146  ,\n",
+              "       8.581511 , 8.618688 , 8.65223  , 8.69048  , 8.72701  , 8.758973 ,\n",
+              "       8.795943 , 8.832204 , 8.870703 , 8.8993225, 8.936847 , 8.969017 ,\n",
+              "       9.001257 , 9.036253 , 9.063161 , 9.095617 , 9.1287565, 9.157017 ,\n",
+              "       9.187741 , 9.216694 , 9.244237 , 9.274386 , 9.300383 , 9.32181  ,\n",
+              "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
+              "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
+              "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
+              "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-9cbe0b2b-fbe0-4105-948a-facb1c05e1fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cbe0b2b-fbe0-4105-948a-facb1c05e1fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b06d265e-c58a-4826-9bcd-ddb013e5e034' class='xr-var-data-in' type='checkbox'><label for='data-b06d265e-c58a-4826-9bcd-ddb013e5e034' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
+              "         3.60746217e+00,  3.56795740e+00,  3.58543777e+00,\n",
+              "         3.56357908e+00,  3.57667398e+00,  3.60632110e+00,\n",
+              "         3.56949067e+00,  3.57479167e+00,  3.59876704e+00,\n",
+              "         3.60281253e+00,  3.59981132e+00,  3.59064198e+00,\n",
+              "         3.59985065e+00,  3.58579111e+00,  3.57373047e+00,\n",
+              "         3.56544852e+00,  3.58114982e+00,  3.58714032e+00,\n",
+              "         3.55944085e+00,  3.58880138e+00,  3.53171992e+00,\n",
+              "         3.53358531e+00,  3.49057865e+00,  3.49481201e+00,\n",
+              "         3.49612260e+00,  3.45677161e+00,  3.42318940e+00,\n",
+              "         3.46062589e+00,  3.41326380e+00,  3.41770315e+00,\n",
+              "         3.41921234e+00,  3.43796873e+00,  3.42292237e+00,\n",
+              "         3.41392589e+00,  3.38415337e+00,  3.38218069e+00,\n",
+              "         3.43648434e+00,  3.38592434e+00,  3.34218621e+00,\n",
+              "         3.38532996e+00,  3.37350154e+00,  3.37754154e+00,\n",
+              "         3.35902476e+00,  3.34339881e+00,  3.35676146e+00,\n",
+              "         3.35692763e+00,  3.32560086e+00,  3.27195191e+00,\n",
+              "         3.19083190e+00,  2.95882225e+00,  2.40057945e+00,\n",
+              "         2.16090226e+00,  1.92318320e+00,  1.78795314e+00,\n",
+              "         1.62216699e+00,  1.56376326e+00,  1.46418226e+00,\n",
+              "...\n",
+              "        -1.96982498e+02, -1.97061203e+02, -1.96969849e+02,\n",
+              "        -1.97076538e+02, -1.97007187e+02, -1.97028168e+02,\n",
+              "        -1.97006195e+02, -1.97027512e+02, -1.97029175e+02,\n",
+              "        -1.96980515e+02, -1.97019150e+02, -1.96939850e+02,\n",
+              "        -1.96979843e+02, -1.97032181e+02, -1.97038193e+02,\n",
+              "        -1.96942871e+02, -1.96959534e+02, -1.96986191e+02,\n",
+              "        -1.97056839e+02, -1.97049850e+02, -1.97026855e+02,\n",
+              "        -1.97041199e+02, -1.97016525e+02, -1.97084503e+02,\n",
+              "        -1.97077499e+02, -1.97032166e+02, -1.97061508e+02,\n",
+              "        -1.97079834e+02, -1.97101852e+02, -1.97092865e+02,\n",
+              "        -1.97062164e+02, -1.97118851e+02, -1.97044510e+02,\n",
+              "        -1.97032166e+02, -1.97112183e+02, -1.96995499e+02,\n",
+              "        -1.97103195e+02, -1.97131195e+02, -1.97147202e+02,\n",
+              "        -1.97079849e+02, -1.97053513e+02, -1.97125504e+02,\n",
+              "        -1.97132843e+02, -1.97114838e+02, -1.97074829e+02,\n",
+              "        -1.97085831e+02, -1.97115845e+02, -1.97091156e+02,\n",
+              "        -1.97044174e+02, -1.97063873e+02, -1.97090515e+02,\n",
+              "        -1.97129501e+02, -1.97007523e+02, -1.97017838e+02,\n",
+              "        -1.97019165e+02, -1.97129166e+02, -1.97051849e+02,\n",
+              "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-547dee17-0806-4d1d-9e36-3a49d9cff3b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-547dee17-0806-4d1d-9e36-3a49d9cff3b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50f085bb-e921-446a-aa0e-c6381d93d031' class='xr-var-data-in' type='checkbox'><label for='data-50f085bb-e921-446a-aa0e-c6381d93d031' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
+              "        -1.2613868 , -1.2610568 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
+              "        -1.2618904 , -1.258823  , -1.2596216 , -1.258702  , -1.2583325 ,\n",
+              "        -1.2578007 , -1.2583394 , -1.2576339 , -1.2579147 , -1.2534361 ,\n",
+              "        -1.2568558 , -1.2559422 , -1.2557042 , -1.2571892 , -1.2556211 ,\n",
+              "        -1.2540294 , -1.2548382 , -1.2532483 , -1.2525105 , -1.2511989 ,\n",
+              "        -1.2522614 , -1.2561746 , -1.2530836 , -1.2531874 , -1.2519903 ,\n",
+              "        -1.2518218 , -1.2511966 , -1.2544034 , -1.2561861 , -1.2536184 ,\n",
+              "        -1.2504781 , -1.2535783 , -1.2560768 , -1.2559297 , -1.257113  ,\n",
+              "        -1.2519604 , -1.2501055 , -1.2515699 , -1.2483989 , -1.2508361 ,\n",
+              "        -1.2479837 , -1.2430646 , -1.2314413 , -1.2083213 , -1.1935245 ,\n",
+              "        -1.1852744 , -1.1747023 , -1.1735051 , -1.1686733 , -1.1616861 ,\n",
+              "        -1.1579937 , -1.1570411 , -1.1541711 , -1.1540251 , -1.1536013 ,\n",
+              "        -1.1516274 , -1.147889  , -1.1449583 , -1.1449729 , -1.14322   ,\n",
+              "        -1.1418625 , -1.1392603 , -1.1384715 , -1.136121  , -1.1344364 ,\n",
+              "        -1.132704  , -1.1329331 , -1.1329101 , -1.130972  , -1.1331373 ,\n",
+              "        -1.1304799 , -1.1283726 , -1.1294136 , -1.132449  , -1.1283008 ,\n",
+              "        -1.1297874 , -1.1291262 , -1.1277461 , -1.1284393 , -1.1265595 ,\n",
+              "        -1.1229205 , -1.1222471 , -1.1207403 , -1.1196108 , -1.1196036 ,\n",
+              "        -1.1186633 , -1.1185873 , -1.1168755 , -1.1150851 , -1.1146263 ,\n",
+              "...\n",
+              "         9.716357  ,  9.717475  ,  9.7163725 ,  9.718897  ,  9.715463  ,\n",
+              "         9.711327  ,  9.713148  ,  9.713642  ,  9.712924  ,  9.715384  ,\n",
+              "         9.715974  ,  9.716772  ,  9.718337  ,  9.714473  ,  9.717203  ,\n",
+              "         9.714393  ,  9.71425   ,  9.713914  ,  9.711695  ,  9.708918  ,\n",
+              "         9.711455  ,  9.70863   ,  9.711487  ,  9.71433   ,  9.710337  ,\n",
+              "         9.711295  ,  9.7138815 ,  9.70997   ,  9.713227  ,  9.717092  ,\n",
+              "         9.713419  ,  9.719773  ,  9.71832   ,  9.716453  ,  9.717108  ,\n",
+              "         9.715989  ,  9.7141695 ,  9.711615  ,  9.71741   ,  9.715814  ,\n",
+              "         9.71428   ,  9.717347  ,  9.712972  ,  9.7162285 ,  9.713419  ,\n",
+              "         9.712238  ,  9.714361  ,  9.716245  ,  9.713563  ,  9.718161  ,\n",
+              "         9.713195  ,  9.715207  ,  9.71591   ,  9.713914  ,  9.7165    ,\n",
+              "         9.7136755 ,  9.717347  ,  9.719837  ,  9.718688  ,  9.713898  ,\n",
+              "         9.717618  ,  9.715941  ,  9.710864  ,  9.71433   ,  9.717777  ,\n",
+              "         9.716262  ,  9.716644  ,  9.719199  ,  9.718911  ,  9.715112  ,\n",
+              "         9.714042  ,  9.710752  ,  9.714153  ,  9.716006  ,  9.715191  ,\n",
+              "         9.716421  ,  9.718177  ,  9.717875  ,  9.718033  ,  9.713227  ,\n",
+              "         9.714537  ,  9.714841  ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
+              "         9.715717  ,  9.711741  ,  9.710465  ,  9.712621  ,  9.71337   ,\n",
+              "         9.715622  ,  9.715989  ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
+              "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-da988fe4-acd9-4495-9d8a-59b66fb7154e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da988fe4-acd9-4495-9d8a-59b66fb7154e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-847ccef9-14f0-4904-97f0-2043874dbdcc' class='xr-var-data-in' type='checkbox'><label for='data-847ccef9-14f0-4904-97f0-2043874dbdcc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
+              "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
+              "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
+              "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
+              "       16.466002, 16.476501, 16.464167, 16.464666, 16.462667, 16.460833,\n",
+              "       16.462164, 16.460167, 16.459501, 16.459002, 16.454332, 16.449501,\n",
+              "       16.444332, 16.4325  , 16.422   , 16.412834, 16.400167, 16.397667,\n",
+              "       16.385334, 16.382334, 16.380499, 16.383333, 16.381332, 16.379833,\n",
+              "       16.382   , 16.379168, 16.380499, 16.378834, 16.374832, 16.384499,\n",
+              "       16.374166, 16.373333, 16.377167, 16.376   , 16.38    , 16.370333,\n",
+              "       16.376501, 16.382   , 16.3775  , 16.3815  , 16.378   , 16.3785  ,\n",
+              "       16.378   , 16.383667, 16.374668, 16.3845  , 16.353   , 16.372334,\n",
+              "       16.377668, 16.378168, 16.372334, 16.372665, 16.363167, 16.367167,\n",
+              "       16.372833, 16.363333, 16.355165, 16.367002, 16.368334, 16.372665,\n",
+              "       16.360834, 16.367834, 16.367   , 16.360834, 16.358   , 16.342833,\n",
+              "       16.341167, 16.328001, 16.317   , 16.305332, 16.295   , 16.2915  ,\n",
+              "       16.279333, 16.281166, 16.280834, 16.276167, 16.279333, 16.279333,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275333, 16.279001, 16.279001, 16.275333, 16.279001, 16.279001,\n",
+              "       16.275   , 16.278334, 16.276834, 16.271   , 16.2725  , 16.27    ,\n",
+              "       16.265165, 16.268333, 16.268   , 16.264   , 16.268   , 16.268   ,\n",
+              "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.268   ,\n",
+              "       16.264   , 16.268   , 16.268   , 16.264   , 16.268   , 16.263334,\n",
+              "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
+              "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
+              "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
+              "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-b683fade-bd5e-41c8-9f67-ecacb1a5b478' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b683fade-bd5e-41c8-9f67-ecacb1a5b478' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d711a60-0cf6-4d1e-b1e8-667195558c35' class='xr-var-data-in' type='checkbox'><label for='data-2d711a60-0cf6-4d1e-b1e8-667195558c35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
+              "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
+              "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
+              "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
+              "       20.25    , 20.25    , 20.163334, 20.      , 20.      , 20.      ,\n",
+              "       19.766666, 19.75    , 19.75    , 19.726667, 19.553333, 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.606667, 19.746666, 19.75    , 19.75    , 19.75    ,\n",
+              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+              "       19.556667, 19.5     , 19.5     , 19.5     , 19.626667, 19.75    ,\n",
+              "       19.75    , 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+              "       19.75    , 19.75    , 19.75    , 19.54    , 19.413334, 19.233334,\n",
+              "       19.      , 18.91    , 18.75    , 18.746666, 18.5     , 18.5     ,\n",
+              "       18.5     , 18.5     , 18.366667, 18.25    , 18.25    , 18.25    ,\n",
+              "       18.25    , 18.2     , 18.      , 18.      , 18.      , 18.      ,\n",
+              "       17.873333, 17.75    , 17.75    , 17.75    , 17.863333, 18.      ,\n",
+              "       18.      , 18.17    , 18.25    , 18.44    , 18.513334, 18.75    ,\n",
+              "       18.783333, 19.      , 19.      , 19.196667, 19.25    , 19.25    ,\n",
+              "       19.25    , 19.433332, 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
+              "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
+              "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
+              "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-508d37e9-1081-44d6-a86c-6b5aeced1a6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-508d37e9-1081-44d6-a86c-6b5aeced1a6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bce5dde-d8b5-40cf-bb61-c5a30e0daa0c' class='xr-var-data-in' type='checkbox'><label for='data-2bce5dde-d8b5-40cf-bb61-c5a30e0daa0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-bf922854-672f-49b1-8ee9-f232d24c35a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf922854-672f-49b1-8ee9-f232d24c35a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f495638f-30d9-4cff-b90e-59496e0ae46a' class='xr-var-data-in' type='checkbox'><label for='data-f495638f-30d9-4cff-b90e-59496e0ae46a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "...\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355693e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-ebf56e38-28ef-4e12-b40e-0e4ea0be98d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebf56e38-28ef-4e12-b40e-0e4ea0be98d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e989d3d2-f2a9-4473-b931-b9b1ad317246' class='xr-var-data-in' type='checkbox'><label for='data-e989d3d2-f2a9-4473-b931-b9b1ad317246' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
+              "         -0.18383324, -0.17606331],\n",
+              "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
+              "         -0.19696543, -0.20011853],\n",
+              "        [ 0.26504937,  0.28428233,  0.31169885, ..., -0.2103943 ,\n",
+              "         -0.21627884, -0.21236075],\n",
+              "        ...,\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan]],\n",
+              "\n",
+              "       [[ 0.02619691,  0.04430203,  0.04002393, ...,  0.05932099,\n",
+              "          0.06400961,  0.07232199],\n",
+              "        [ 0.06181316,  0.07802678,  0.06236525, ...,  0.0768801 ,\n",
+              "          0.08184617,  0.0892335 ],\n",
+              "        [ 0.08793733,  0.10133781,  0.08016948, ...,  0.08136398,\n",
+              "          0.08639657,  0.10118616],\n",
+              "...\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan]],\n",
+              "\n",
+              "       [[-0.00417333, -0.01056667, -0.01045333, ..., -0.02584564,\n",
+              "         -0.02752333, -0.02575667],\n",
+              "        [ 0.01358667,  0.00760333,  0.00634667, ..., -0.01625333,\n",
+              "         -0.01776333, -0.01595   ],\n",
+              "        [ 0.01556187,  0.00811371,  0.00740333, ..., -0.00842   ,\n",
+              "         -0.01147667, -0.01189667],\n",
+              "        ...,\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan],\n",
+              "        [        nan,         nan,         nan, ...,         nan,\n",
+              "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-eb58591d-0974-4d2a-b938-7792383cfa02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb58591d-0974-4d2a-b938-7792383cfa02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc8f996a-8297-4f04-b2bd-bc0c732d7f59' class='xr-var-data-in' type='checkbox'><label for='data-bc8f996a-8297-4f04-b2bd-bc0c732d7f59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
+              "         81.68667 ],\n",
+              "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
+              "         77.528336],\n",
+              "        [72.81167 , 73.391304, 74.26833 , ..., 74.525   , 74.39667 ,\n",
+              "         74.253334],\n",
+              "        ...,\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan]],\n",
+              "\n",
+              "       [[80.706665, 80.93833 , 81.255   , ..., 82.19833 , 82.225   ,\n",
+              "         82.17    ],\n",
+              "        [76.80666 , 76.996666, 77.44833 , ..., 78.38333 , 78.41167 ,\n",
+              "         78.06    ],\n",
+              "        [74.31834 , 74.64667 , 75.903336, ..., 75.16333 , 75.26833 ,\n",
+              "         74.875   ],\n",
+              "...\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan]],\n",
+              "\n",
+              "       [[80.185   , 80.55    , 80.885   , ..., 81.888336, 81.945   ,\n",
+              "         81.85833 ],\n",
+              "        [75.78    , 76.291664, 76.76833 , ..., 77.97667 , 78.03833 ,\n",
+              "         77.87666 ],\n",
+              "        [72.67725 , 73.55666 , 74.44334 , ..., 74.75833 , 74.665   ,\n",
+              "         74.47    ],\n",
+              "        ...,\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan],\n",
+              "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-9b7da4e9-e561-43fe-b0e4-4cf59df5d9c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b7da4e9-e561-43fe-b0e4-4cf59df5d9c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f3a6394-ea11-484f-b854-9429527a22d8' class='xr-var-data-in' type='checkbox'><label for='data-8f3a6394-ea11-484f-b854-9429527a22d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
+              "         92.06333 ],\n",
+              "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
+              "         96.03333 ],\n",
+              "        [97.166664, 96.246666, 95.94    , ..., 96.45333 , 97.206665,\n",
+              "         97.263336],\n",
+              "        ...,\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ]],\n",
+              "\n",
+              "       [[93.333336, 93.61    , 93.31333 , ..., 91.6     , 91.49    ,\n",
+              "         91.14667 ],\n",
+              "        [96.57    , 96.39    , 96.12666 , ..., 96.27    , 96.56333 ,\n",
+              "         96.44334 ],\n",
+              "        [97.37666 , 97.09333 , 96.87666 , ..., 96.17333 , 97.30334 ,\n",
+              "         97.32667 ],\n",
+              "...\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ]],\n",
+              "\n",
+              "       [[92.78333 , 93.223335, 92.63    , ..., 92.22    , 92.34    ,\n",
+              "         92.61    ],\n",
+              "        [96.75    , 96.34333 , 96.34    , ..., 96.53    , 96.69    ,\n",
+              "         96.27333 ],\n",
+              "        [96.346664, 97.05    , 97.24    , ..., 96.66333 , 96.89333 ,\n",
+              "         97.41    ],\n",
+              "        ...,\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ],\n",
+              "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-4e7b833e-436d-41e2-a85b-1b23566968fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e7b833e-436d-41e2-a85b-1b23566968fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1659316e-b84b-415d-9c8a-d7ae49cd3a37' class='xr-var-data-in' type='checkbox'><label for='data-1659316e-b84b-415d-9c8a-d7ae49cd3a37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
+              "          5.81927113e-02,  5.85613623e-02,  5.85512854e-02],\n",
+              "        [ 9.98300374e-01,  9.98323679e-01,  9.98248577e-01, ...,\n",
+              "          9.98254061e-01,  9.98234987e-01,  9.98234689e-01],\n",
+              "        [-1.05408905e-03, -1.34927384e-03, -1.13080605e-03, ...,\n",
+              "         -8.26976204e-04, -8.38353124e-04, -8.28948745e-04]],\n",
+              "\n",
+              "       [[-9.89950538e-01, -9.89953220e-01, -9.89922285e-01, ...,\n",
+              "         -9.91938353e-01, -9.91944909e-01, -9.91939366e-01],\n",
+              "        [ 5.68153895e-02,  5.63202463e-02,  5.76671995e-02, ...,\n",
+              "          5.77317439e-02,  5.80984168e-02,  5.80891557e-02],\n",
+              "        [-1.29125342e-01, -1.29299909e-01, -1.28952131e-01, ...,\n",
+              "         -1.12354711e-01, -1.12130061e-01, -1.12175331e-01]],\n",
+              "\n",
+              "       [[-1.28852651e-01, -1.29014045e-01, -1.28667876e-01, ...,\n",
+              "         -1.12116747e-01, -1.11889169e-01, -1.11934915e-01],\n",
+              "        [ 8.45469162e-03,  8.69723968e-03,  8.63243733e-03, ...,\n",
+              "          7.35414820e-03,  7.39390310e-03,  7.38611678e-03],\n",
+              "        [ 9.91627276e-01,  9.91604209e-01,  9.91649806e-01, ...,\n",
+              "          9.93667483e-01,  9.93692815e-01,  9.93687749e-01]]],\n",
+              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-d2b61070-dec7-49c0-86b1-b2659f42f5ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2b61070-dec7-49c0-86b1-b2659f42f5ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5106cc26-0e44-48d6-95d4-09032b3ba348' class='xr-var-data-in' type='checkbox'><label for='data-5106cc26-0e44-48d6-95d4-09032b3ba348' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
+              "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
+              "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
+              "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
+              "         0.00054653,  0.00055442,  0.00072552,  0.00056834,  0.00065792,\n",
+              "         0.00086152,  0.00080709,  0.00096736,  0.00085591,  0.00094166,\n",
+              "         0.00090368,  0.00095632,  0.00094047,  0.00091472,  0.00092718,\n",
+              "         0.00097144,  0.00090388,  0.00098592,  0.00099217,  0.00104627,\n",
+              "         0.00101094,  0.00108953,  0.00094413,  0.0010326 ,  0.00105636,\n",
+              "         0.00098609,  0.00101084,  0.00101927,  0.00101796,  0.00096841,\n",
+              "         0.00102785,  0.00113951,  0.00098156,  0.00111134,  0.00100472,\n",
+              "         0.00104199,  0.00104198,  0.00100612,  0.00103637,  0.00099132,\n",
+              "         0.00102272,  0.00102712,  0.00100425,  0.0010416 ,  0.00097589,\n",
+              "         0.00090605,  0.00108258,  0.00090169,  0.00096689,  0.00081777,\n",
+              "         0.0009423 ,  0.00087804,  0.00102183,  0.00083111,  0.0009242 ,\n",
+              "         0.00094747,  0.00110261,  0.00097415,  0.00097692,  0.00113317,\n",
+              "         0.00105406,  0.00104935,  0.00102722,  0.00093711,  0.00103575,\n",
+              "         0.00095867,  0.0009583 ,  0.00104538,  0.00100466,  0.00095809,\n",
+              "         0.00101549,  0.00097118,  0.00090704,  0.00094464,  0.00096578,\n",
+              "         0.00105039,  0.00093799,  0.00100518,  0.00088882,  0.00095506,\n",
+              "...\n",
+              "        -0.00263344, -0.00258787, -0.00256183, -0.00256183, -0.00250324,\n",
+              "        -0.00268227, -0.00268227, -0.00259113, -0.00262693, -0.00257485,\n",
+              "        -0.00259113, -0.00252602, -0.00267576, -0.00253904, -0.00256509,\n",
+              "        -0.00242511, -0.00249998, -0.00250975, -0.00252277, -0.00261066,\n",
+              "        -0.00257485, -0.00265298, -0.00264647, -0.00261391, -0.00260089,\n",
+              "        -0.00270181, -0.0027604 , -0.00278318, -0.00288084, -0.00274412,\n",
+              "        -0.00280272, -0.00289386, -0.0030729 , -0.0029492 , -0.0029199 ,\n",
+              "        -0.00302407, -0.00299803, -0.00296222, -0.00288084, -0.00299477,\n",
+              "        -0.00304034, -0.00298175, -0.00296222, -0.00296873, -0.00305337,\n",
+              "        -0.00302081, -0.00299803, -0.00304034, -0.0030729 , -0.0029199 ,\n",
+              "        -0.00295571, -0.00287433, -0.00287433, -0.0028548 , -0.00275714,\n",
+              "        -0.00271157, -0.0027018 , -0.00278644, -0.0026074 , -0.00264972,\n",
+              "        -0.00273761, -0.00259764, -0.00258787, -0.00256834, -0.00263344,\n",
+              "        -0.00255207, -0.00265623, -0.00261391, -0.00255207, -0.00249673,\n",
+              "        -0.00258787, -0.00256183, -0.00253579, -0.00264321, -0.00268553,\n",
+              "        -0.00255858, -0.00264321, -0.00262693, -0.0025423 , -0.00256834,\n",
+              "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
+              "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
+              "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
+              "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-4efa1abc-ed50-4212-8bd9-2b5b594aa043' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4efa1abc-ed50-4212-8bd9-2b5b594aa043' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfc40073-a2d0-4354-a110-c18404a46756' class='xr-var-data-in' type='checkbox'><label for='data-cfc40073-a2d0-4354-a110-c18404a46756' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
+              "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
+              "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
+              "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
+              "         0.6253574 ,  0.6254711 ,  0.6251542 ,  0.6249595 ,  0.62512624,\n",
+              "         0.62510735,  0.62479544,  0.6250753 ,  0.624999  ,  0.6248949 ,\n",
+              "         0.6248343 ,  0.6245227 ,  0.6248399 ,  0.624795  ,  0.6250311 ,\n",
+              "         0.62494355,  0.6249766 ,  0.6244582 ,  0.62417775,  0.6244494 ,\n",
+              "         0.6248647 ,  0.6245337 ,  0.62416995,  0.6242157 ,  0.62425923,\n",
+              "         0.6247039 ,  0.6248129 ,  0.6246122 ,  0.6248121 ,  0.6246928 ,\n",
+              "         0.6245991 ,  0.6248212 ,  0.6247573 ,  0.6243741 ,  0.6243043 ,\n",
+              "         0.6244282 ,  0.6243682 ,  0.6240724 ,  0.62418926,  0.6241515 ,\n",
+              "         0.6239765 ,  0.62391806,  0.62415963,  0.62387216,  0.6239287 ,\n",
+              "         0.62390673,  0.6236841 ,  0.62378633,  0.6236643 ,  0.6235926 ,\n",
+              "         0.62364197,  0.6237233 ,  0.62374234,  0.62387735,  0.62402254,\n",
+              "         0.62393117,  0.62393445,  0.62373453,  0.62396324,  0.62340415,\n",
+              "         0.62373024,  0.62379295,  0.62355286,  0.6231889 ,  0.62350035,\n",
+              "         0.6232749 ,  0.6232579 ,  0.6233172 ,  0.6232117 ,  0.62328154,\n",
+              "         0.6234021 ,  0.62359464,  0.6235321 ,  0.62355274,  0.62340564,\n",
+              "         0.6233349 ,  0.6232732 ,  0.62326413,  0.62335676,  0.6233057 ,\n",
+              "...\n",
+              "         0.77982664,  0.7798403 ,  0.77980125,  0.7798833 ,  0.7798343 ,\n",
+              "         0.77974474,  0.7795985 ,  0.77965385,  0.77964175,  0.7797572 ,\n",
+              "         0.7798193 ,  0.77987343,  0.77987754,  0.7798154 ,  0.7798561 ,\n",
+              "         0.77976704,  0.77973217,  0.77971977,  0.77958   ,  0.7794924 ,\n",
+              "         0.77951276,  0.77934176,  0.77977145,  0.77983665,  0.7796758 ,\n",
+              "         0.77951133,  0.77975136,  0.7796223 ,  0.7795445 ,  0.7798783 ,\n",
+              "         0.7796854 ,  0.78009176,  0.77983886,  0.77976817,  0.7798124 ,\n",
+              "         0.77966744,  0.77980477,  0.77957195,  0.7797228 ,  0.7795519 ,\n",
+              "         0.77965647,  0.7795511 ,  0.7795689 ,  0.77951413,  0.77942085,\n",
+              "         0.7791843 ,  0.7793043 ,  0.7793574 ,  0.7790914 ,  0.77922   ,\n",
+              "         0.7788722 ,  0.77907705,  0.7790985 ,  0.778842  ,  0.7789314 ,\n",
+              "         0.77889466,  0.7789852 ,  0.7792381 ,  0.77916646,  0.7788889 ,\n",
+              "         0.77894676,  0.7789039 ,  0.7785506 ,  0.7786492 ,  0.7788344 ,\n",
+              "         0.7786969 ,  0.77884805,  0.7789083 ,  0.77894056,  0.7786727 ,\n",
+              "         0.77858806,  0.7783844 ,  0.7785528 ,  0.7787677 ,  0.77864134,\n",
+              "         0.77870125,  0.7787834 ,  0.7788154 ,  0.7788442 ,  0.7785659 ,\n",
+              "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
+              "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
+              "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
+              "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-989abd66-5dfb-416f-b419-451fb8212e79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-989abd66-5dfb-416f-b419-451fb8212e79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37c06dec-017f-49cb-ab56-a02e63104a9a' class='xr-var-data-in' type='checkbox'><label for='data-37c06dec-017f-49cb-ab56-a02e63104a9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
+              "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
+              "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
+              "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
+              "       13.       , 12.941335 , 12.800002 , 12.631333 , 12.598    ,\n",
+              "       12.411335 , 12.400001 , 12.230666 , 12.199998 , 12.119332 ,\n",
+              "       12.       , 12.       , 12.       , 11.957999 , 11.800002 ,\n",
+              "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.800002 ,\n",
+              "       11.800002 , 11.800002 , 11.800002 , 11.800002 , 11.834001 ,\n",
+              "       11.999333 , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.104667 , 12.193999 , 12.199998 , 12.199998 ,\n",
+              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.086667 ,\n",
+              "       12.113999 , 12.192665 , 12.032667 , 12.078666 , 12.03     ,\n",
+              "       12.       , 12.111999 , 12.199998 , 12.199998 , 12.199998 ,\n",
+              "       12.202665 , 12.219333 , 12.274    , 12.367333 , 12.203999 ,\n",
+              "       12.217332 , 12.199998 , 12.199998 , 12.119332 , 11.845334 ,\n",
+              "       11.496667 , 11.219998 , 11.       , 10.952001 , 10.800002 ,\n",
+              "       10.800002 , 10.800002 , 10.800002 , 10.751334 , 10.599999 ,\n",
+              "       10.599999 , 10.599999 , 10.599999 , 10.5546665, 10.400001 ,\n",
+              "       10.400001 , 10.334666 , 10.2      , 10.2      , 10.191999 ,\n",
+              "       10.029333 , 10.       , 10.009334 , 10.198667 , 10.243333 ,\n",
+              "       10.415334 , 10.599999 , 10.772668 , 11.       , 11.186666 ,\n",
+              "       11.398002 , 11.528    , 11.599999 , 11.746667 , 11.800002 ,\n",
+              "       11.876667 , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       , 12.000667 , 12.006    ,\n",
+              "       12.       , 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.001333 , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.024667 , 12.173999 , 12.199998 ,\n",
+              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+              "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
+              "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
+              "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-a030aa68-c7eb-4884-9c2f-64538120fa21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a030aa68-c7eb-4884-9c2f-64538120fa21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e6ccde-3a11-4023-bb55-dbdab5cccd39' class='xr-var-data-in' type='checkbox'><label for='data-65e6ccde-3a11-4023-bb55-dbdab5cccd39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
+              "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
+              "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
+              "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
+              "       244.98334, 244.94   , 244.86333, 244.82666, 244.79333, 244.84666,\n",
+              "       244.76666, 244.73334, 244.82666, 244.75   , 244.86333, 244.83   ,\n",
+              "       244.84334, 244.91333, 244.96666, 245.08   , 245.25333, 245.30667,\n",
+              "       245.4    , 245.51   , 245.61333, 245.61   , 245.65666, 245.76666,\n",
+              "       245.73   , 245.79666, 245.83333, 245.85333, 245.81   , 245.85667,\n",
+              "       245.90334, 245.89333, 245.90666, 245.90334, 245.89333, 245.90666,\n",
+              "       245.93   , 245.91333, 245.91667, 245.92334, 245.92334, 245.92   ,\n",
+              "       245.96   , 245.95   , 245.94333, 245.96   , 245.94667, 245.97   ,\n",
+              "       245.95   , 245.93666, 245.93   , 245.95667, 245.94   , 245.95667,\n",
+              "       245.95   , 245.95334, 245.96666, 245.98   , 245.96666, 245.97   ,\n",
+              "       245.97   , 245.98   , 245.97333, 245.97   , 245.98666, 245.97667,\n",
+              "       245.97667, 245.98334, 245.97667, 245.99333, 245.97667, 245.98334,\n",
+              "       245.99667, 245.99667, 245.99   , 245.97333, 245.98334, 245.98666,\n",
+              "       245.97   , 245.99667, 245.98666, 245.98   , 245.85667, 245.44667,\n",
+              "       244.92334, 244.41667, 244.16333, 244.00667, 244.06   , 244.07333,\n",
+              "       243.87334, 243.77333, 243.75   , 243.69   , 243.76334, 243.79666,\n",
+              "       243.55   , 243.5    , 243.37666, 243.20334, 242.92334, 242.87666,\n",
+              "       242.83   , 242.83333, 243.07666, 243.41   , 243.88333, 244.20334,\n",
+              "       244.40334, 244.45334, 244.48666, 244.41   , 244.38   , 244.43333,\n",
+              "       244.6    , 244.72333, 244.90666, 244.9    , 244.97667, 245.03667,\n",
+              "       245.22667, 245.36   , 245.4    , 245.42   , 245.48334, 245.62666,\n",
+              "       245.67   , 245.71333, 245.75667, 245.77   , 245.84   , 245.87   ,\n",
+              "       245.87666, 245.89   , 245.87666, 245.94333, 245.93   , 245.91333,\n",
+              "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
+              "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
+              "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
+              "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-fdd68d68-b2aa-4ae0-8275-40b3640d73ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdd68d68-b2aa-4ae0-8275-40b3640d73ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1d170b5-2947-40bf-a00f-0fcd44c3d88e' class='xr-var-data-in' type='checkbox'><label for='data-e1d170b5-2947-40bf-a00f-0fcd44c3d88e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
+              "         3.6116719e+00,  3.5757926e+00,  3.5947008e+00,  3.6243417e+00,\n",
+              "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830538e+00,\n",
+              "         3.6165168e+00,  3.5789921e+00,  3.5747981e+00,  3.5690453e+00,\n",
+              "         3.5796013e+00,  3.6261466e+00,  3.6063533e+00,  3.6014795e+00,\n",
+              "         3.6353865e+00,  3.6033041e+00,  3.6023455e+00,  3.5552027e+00,\n",
+              "         3.5689840e+00,  3.5028169e+00,  3.5047083e+00,  3.5002160e+00,\n",
+              "         3.4591196e+00,  3.4518204e+00,  3.4781299e+00,  3.4272485e+00,\n",
+              "         3.4080899e+00,  3.4372404e+00,  3.4341383e+00,  3.3986638e+00,\n",
+              "         3.4168522e+00,  3.4093900e+00,  3.3794670e+00,  3.3934760e+00,\n",
+              "         3.4050257e+00,  3.4207287e+00,  3.3710022e+00,  3.3771679e+00,\n",
+              "         3.3508575e+00,  3.3733418e+00,  3.3524203e+00,  3.3316767e+00,\n",
+              "         3.3258898e+00,  3.3680136e+00,  3.2842207e+00,  3.1945534e+00,\n",
+              "         3.0031645e+00,  2.4369471e+00,  2.1365104e+00,  1.9519800e+00,\n",
+              "         1.7708881e+00,  1.6470156e+00,  1.5729071e+00,  1.4625059e+00,\n",
+              "         1.3881445e+00,  1.3379683e+00,  1.3052688e+00,  1.2468668e+00,\n",
+              "         1.2023062e+00,  1.1269653e+00,  1.1022494e+00,  1.0541168e+00,\n",
+              "         1.0267943e+00,  9.7805512e-01,  9.2956728e-01,  9.2703992e-01,\n",
+              "         9.1599506e-01,  8.9450091e-01,  8.5012424e-01,  8.2220656e-01,\n",
+              "         7.9883534e-01,  7.8205061e-01,  7.3997599e-01,  7.3860037e-01,\n",
+              "...\n",
+              "        -1.9736919e+02, -1.9725951e+02, -1.9730052e+02, -1.9728384e+02,\n",
+              "        -1.9724889e+02, -1.9722919e+02, -1.9715518e+02, -1.9727151e+02,\n",
+              "        -1.9724452e+02, -1.9721884e+02, -1.9717354e+02, -1.9723384e+02,\n",
+              "        -1.9719716e+02, -1.9714218e+02, -1.9723254e+02, -1.9710817e+02,\n",
+              "        -1.9708250e+02, -1.9709784e+02, -1.9708986e+02, -1.9712950e+02,\n",
+              "        -1.9721385e+02, -1.9720052e+02, -1.9717422e+02, -1.9710918e+02,\n",
+              "        -1.9715718e+02, -1.9714487e+02, -1.9715251e+02, -1.9714418e+02,\n",
+              "        -1.9714218e+02, -1.9706715e+02, -1.9705818e+02, -1.9705084e+02,\n",
+              "        -1.9708583e+02, -1.9708820e+02, -1.9714618e+02, -1.9709253e+02,\n",
+              "        -1.9707854e+02, -1.9714384e+02, -1.9717952e+02, -1.9718620e+02,\n",
+              "        -1.9718388e+02, -1.9716652e+02, -1.9712685e+02, -1.9720485e+02,\n",
+              "        -1.9718315e+02, -1.9713019e+02, -1.9714951e+02, -1.9724086e+02,\n",
+              "        -1.9716119e+02, -1.9719583e+02, -1.9724786e+02, -1.9716052e+02,\n",
+              "        -1.9725883e+02, -1.9720285e+02, -1.9717485e+02, -1.9725154e+02,\n",
+              "        -1.9714687e+02, -1.9711821e+02, -1.9714719e+02, -1.9711786e+02,\n",
+              "        -1.9714052e+02, -1.9714351e+02, -1.9715118e+02, -1.9712117e+02,\n",
+              "        -1.9710718e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
+              "        -1.9706255e+02, -1.9714519e+02, -1.9712418e+02, -1.9705786e+02,\n",
+              "        -1.9708685e+02, -1.9711749e+02, -1.9707716e+02, -1.9707919e+02,\n",
+              "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-0fbc2e0a-e093-4d4b-9035-fff95de3ba46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fbc2e0a-e093-4d4b-9035-fff95de3ba46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-150192e3-30a3-4605-b576-2e4966a1f9e0' class='xr-var-data-in' type='checkbox'><label for='data-150192e3-30a3-4605-b576-2e4966a1f9e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
+              "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
+              "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
+              "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569212 , -1.2552022 ,\n",
+              "        -1.2558354 , -1.2547812 , -1.2564313 , -1.2570257 , -1.2564919 ,\n",
+              "        -1.2552761 , -1.2551885 , -1.254373  , -1.2521615 , -1.253256  ,\n",
+              "        -1.2520183 , -1.2556639 , -1.2544196 , -1.2537049 , -1.2514051 ,\n",
+              "        -1.251719  , -1.2501887 , -1.2550075 , -1.2560523 , -1.2542702 ,\n",
+              "        -1.2513357 , -1.2537422 , -1.25587   , -1.2554086 , -1.2568508 ,\n",
+              "        -1.2513126 , -1.251984  , -1.2514541 , -1.2487588 , -1.249171  ,\n",
+              "        -1.2487395 , -1.2432916 , -1.2308283 , -1.2085198 , -1.1925628 ,\n",
+              "        -1.1850357 , -1.175814  , -1.1718632 , -1.1669031 , -1.1620393 ,\n",
+              "        -1.1585126 , -1.1573663 , -1.1550487 , -1.1537894 , -1.1520277 ,\n",
+              "        -1.1507337 , -1.1474868 , -1.1443372 , -1.1442864 , -1.1430473 ,\n",
+              "        -1.1418384 , -1.141045  , -1.1385593 , -1.1344901 , -1.134764  ,\n",
+              "        -1.1317551 , -1.1333026 , -1.1325271 , -1.1293766 , -1.1324316 ,\n",
+              "        -1.1310244 , -1.1295373 , -1.1287975 , -1.1317044 , -1.1290994 ,\n",
+              "        -1.1286312 , -1.1276112 , -1.1271322 , -1.128308  , -1.1257491 ,\n",
+              "        -1.1227695 , -1.1230273 , -1.119395  , -1.1190095 , -1.1182653 ,\n",
+              "        -1.1186818 , -1.1167871 , -1.1160123 , -1.1153725 , -1.1143075 ,\n",
+              "...\n",
+              "         9.716884  ,  9.718464  ,  9.717347  ,  9.717715  ,  9.714792  ,\n",
+              "         9.714857  ,  9.712732  ,  9.712222  ,  9.713994  ,  9.715383  ,\n",
+              "         9.71674   ,  9.716182  ,  9.717108  ,  9.716772  ,  9.715446  ,\n",
+              "         9.714425  ,  9.7126045 ,  9.713626  ,  9.7121105 ,  9.711023  ,\n",
+              "         9.711408  ,  9.709459  ,  9.712988  ,  9.7141695 ,  9.710418  ,\n",
+              "         9.713371  ,  9.713164  ,  9.711615  ,  9.713355  ,  9.714377  ,\n",
+              "         9.714473  ,  9.719391  ,  9.71805   ,  9.71583   ,  9.716421  ,\n",
+              "         9.71658   ,  9.71583   ,  9.71334   ,  9.7177305 ,  9.716677  ,\n",
+              "         9.71476   ,  9.716166  ,  9.713404  ,  9.715751  ,  9.715623  ,\n",
+              "         9.712237  ,  9.714856  ,  9.7166605 ,  9.713179  ,  9.7175865 ,\n",
+              "         9.710929  ,  9.71484   ,  9.715895  ,  9.712062  ,  9.71591   ,\n",
+              "         9.714346  ,  9.716932  ,  9.718177  ,  9.718816  ,  9.713802  ,\n",
+              "         9.717826  ,  9.715128  ,  9.711727  ,  9.713515  ,  9.718353  ,\n",
+              "         9.716836  ,  9.716278  ,  9.717762  ,  9.718656  ,  9.714761  ,\n",
+              "         9.713004  ,  9.710816  ,  9.71409   ,  9.716276  ,  9.713579  ,\n",
+              "         9.716166  ,  9.718401  ,  9.716804  ,  9.718209  ,  9.71428   ,\n",
+              "         9.714553  ,  9.715957  ,  9.7148075 ,  9.717874  ,  9.716309  ,\n",
+              "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
+              "         9.715256  ,  9.714936  ,  9.7148075 ,  9.711726  ,  9.711886  ,\n",
+              "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3a80e8d0-e1cb-4b9d-8fbb-a98553a57307' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a80e8d0-e1cb-4b9d-8fbb-a98553a57307' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21bbc13f-6bcc-444c-a75d-b078e8077e08' class='xr-var-data-in' type='checkbox'><label for='data-21bbc13f-6bcc-444c-a75d-b078e8077e08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-4e2a127a-722e-4e3d-b832-2e441c6c1281' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e2a127a-722e-4e3d-b832-2e441c6c1281' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf24eb9b-eb79-448d-9766-627b781801a5' class='xr-var-data-in' type='checkbox'><label for='data-cf24eb9b-eb79-448d-9766-627b781801a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355693e+09, 1.05355686e+09, 1.05355693e+09,\n",
+              "       1.05355699e+09, 1.05355686e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355693e+09,\n",
+              "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
+              "       1.05355693e+09, 1.05355693e+09, 1.05355693e+09, 1.05355693e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355693e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355693e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "...\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-ded02086-1aa9-47f4-9ad4-9340683e0a78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ded02086-1aa9-47f4-9ad4-9340683e0a78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd3a7ae-5412-4b81-b197-f498d81280bd' class='xr-var-data-in' type='checkbox'><label for='data-fdd3a7ae-5412-4b81-b197-f498d81280bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
+              "        -0.02035667, -0.01573333],\n",
+              "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
+              "        -0.00658667, -0.00238   ],\n",
+              "       [ 0.02739334,  0.01897667,  0.01496333, ...,  0.00196667,\n",
+              "        -0.00096667,  0.00083946],\n",
+              "       ...,\n",
+              "       [        nan,         nan,         nan, ...,         nan,\n",
+              "                nan,         nan],\n",
+              "       [        nan,         nan,         nan, ...,         nan,\n",
+              "                nan,         nan],\n",
+              "       [        nan,         nan,         nan, ...,         nan,\n",
+              "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-49a172f6-4972-4afb-836c-d50c632be796' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49a172f6-4972-4afb-836c-d50c632be796' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-275d7786-316d-4218-a75a-faa242769033' class='xr-var-data-in' type='checkbox'><label for='data-275d7786-316d-4218-a75a-faa242769033' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
+              "        81.745   ],\n",
+              "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
+              "        78.045   ],\n",
+              "       [73.58833 , 74.355   , 75.083336, ..., 75.265   , 75.098335,\n",
+              "        74.92976 ],\n",
+              "       ...,\n",
+              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "              nan],\n",
+              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "              nan],\n",
+              "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+              "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-b0580eef-8bc8-4736-bff0-9168e45752bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0580eef-8bc8-4736-bff0-9168e45752bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34c2e6b9-d367-4a90-b096-9c9f3372fedf' class='xr-var-data-in' type='checkbox'><label for='data-34c2e6b9-d367-4a90-b096-9c9f3372fedf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
+              "        92.61667 ],\n",
+              "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
+              "        96.57667 ],\n",
+              "       [97.19    , 97.32333 , 97.136665, ..., 96.08667 , 97.16    ,\n",
+              "        96.96667 ],\n",
+              "       ...,\n",
+              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "         0.      ],\n",
+              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "         0.      ],\n",
+              "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
+              "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-184218df-2500-4c7a-a730-b3c40ed75966' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-184218df-2500-4c7a-a730-b3c40ed75966' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b57434c7-640a-4e6f-b13c-98477a03e826' class='xr-var-data-in' type='checkbox'><label for='data-b57434c7-640a-4e6f-b13c-98477a03e826' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
+              "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
+              "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
+              "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
+              "        [-1.26286745e-01, -1.26509830e-01, -1.26157105e-01, ...,\n",
+              "         -1.09885700e-01, -1.09676003e-01, -1.09719723e-01]],\n",
+              "\n",
+              "       [[ 9.76216435e-01,  9.76112664e-01,  9.76405323e-01, ...,\n",
+              "          9.76383269e-01,  9.76462007e-01,  9.76460576e-01],\n",
+              "        [-2.14884892e-01, -2.15368673e-01, -2.14055121e-01, ...,\n",
+              "         -2.14541376e-01, -2.14190111e-01, -2.14200497e-01],\n",
+              "        [-2.69518793e-02, -2.67608669e-02, -2.67287735e-02, ...,\n",
+              "         -2.34543420e-02, -2.33496260e-02, -2.33698264e-02]],\n",
+              "\n",
+              "       [[-1.05265796e-03, -1.35056104e-03, -1.13043608e-03, ...,\n",
+              "         -8.24717747e-04, -8.40478169e-04, -8.31306970e-04],\n",
+              "        [-1.29126370e-01, -1.29302278e-01, -1.28952518e-01, ...,\n",
+              "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
+              "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
+              "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
+              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-08484c2e-58ca-4393-ae9d-41e927dc4c3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08484c2e-58ca-4393-ae9d-41e927dc4c3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b1bdb9c-e0c1-444f-b7e9-04332e08b3cf' class='xr-var-data-in' type='checkbox'><label for='data-5b1bdb9c-e0c1-444f-b7e9-04332e08b3cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
+              "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
+              "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
+              "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
+              "         0.00056599,  0.00061758,  0.00068752,  0.00066373,  0.00073918,\n",
+              "         0.00085721,  0.00084523,  0.0009018 ,  0.00089635,  0.00084324,\n",
+              "         0.00086276,  0.00089614,  0.00096862,  0.00108153,  0.00095481,\n",
+              "         0.00098828,  0.00098117,  0.00097845,  0.00099421,  0.00095727,\n",
+              "         0.00108126,  0.00108415,  0.00096381,  0.00100037,  0.00098756,\n",
+              "         0.00103554,  0.00096841,  0.00107755,  0.00104051,  0.0009601 ,\n",
+              "         0.00106976,  0.0010707 ,  0.00102194,  0.0009954 ,  0.00100513,\n",
+              "         0.0010245 ,  0.00102471,  0.00096594,  0.0010335 ,  0.00105437,\n",
+              "         0.00105971,  0.00095506,  0.00102042,  0.00097918,  0.00088768,\n",
+              "         0.0009018 ,  0.00096684,  0.00101125,  0.00096008,  0.0008592 ,\n",
+              "         0.00082965,  0.00095935,  0.00094485,  0.00081024,  0.00092011,\n",
+              "         0.00098175,  0.00094213,  0.00095046,  0.00099598,  0.00104662,\n",
+              "         0.00101681,  0.0010222 ,  0.00099111,  0.001044  ,  0.00103549,\n",
+              "         0.00097536,  0.00099907,  0.00097684,  0.00104176,  0.00094763,\n",
+              "         0.0009761 ,  0.00097227,  0.00089143,  0.00096118,  0.00097306,\n",
+              "         0.00096506,  0.00094653,  0.00092565,  0.00091383,  0.0009503 ,\n",
+              "...\n",
+              "        -0.00262043, -0.00258136, -0.00261717, -0.00257811, -0.00261066,\n",
+              "        -0.00255532, -0.00266274, -0.00254881, -0.00255858, -0.00259764,\n",
+              "        -0.00258462, -0.00252602, -0.00258787, -0.00256183, -0.00260415,\n",
+              "        -0.00251626, -0.00250975, -0.00243488, -0.00254881, -0.00264321,\n",
+              "        -0.00260089, -0.00263996, -0.0026367 , -0.00271157, -0.00256183,\n",
+              "        -0.00271808, -0.00277993, -0.00284178, -0.00276365, -0.00277016,\n",
+              "        -0.00279946, -0.00295896, -0.00294594, -0.00302732, -0.00302407,\n",
+              "        -0.00301756, -0.00298501, -0.00291339, -0.00296548, -0.00294269,\n",
+              "        -0.00311196, -0.00294594, -0.0030143 , -0.00297198, -0.00296873,\n",
+              "        -0.002985  , -0.0030729 , -0.0030143 , -0.00306638, -0.00288084,\n",
+              "        -0.00289386, -0.00281899, -0.00278644, -0.0028255 , -0.00276365,\n",
+              "        -0.00277993, -0.002666  , -0.00267576, -0.002666  , -0.00268227,\n",
+              "        -0.00268878, -0.00263019, -0.00254881, -0.00262368, -0.00263019,\n",
+              "        -0.00260415, -0.00257811, -0.0026074 , -0.00249673, -0.00254881,\n",
+              "        -0.00258787, -0.00263019, -0.00255532, -0.00269204, -0.00258136,\n",
+              "        -0.00259113, -0.00272133, -0.00258462, -0.00263019, -0.00261066,\n",
+              "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
+              "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
+              "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
+              "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-783a8e7c-a6f7-4666-95ec-2657d964c021' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-783a8e7c-a6f7-4666-95ec-2657d964c021' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-544db24d-04b2-4a17-b5c6-53148ebfc79f' class='xr-var-data-in' type='checkbox'><label for='data-544db24d-04b2-4a17-b5c6-53148ebfc79f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
+              "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
+              "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
+              "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
+              "         0.6253524 ,  0.6254653 ,  0.62515104,  0.62495625,  0.62512195,\n",
+              "         0.6251015 ,  0.624793  ,  0.6250713 ,  0.6249948 ,  0.62489176,\n",
+              "         0.6248301 ,  0.62451917,  0.6248372 ,  0.62479085,  0.62502736,\n",
+              "         0.6249378 ,  0.62497205,  0.62445515,  0.62417245,  0.6244453 ,\n",
+              "         0.6248608 ,  0.62453014,  0.62416404,  0.6242139 ,  0.62425303,\n",
+              "         0.62470126,  0.6248098 ,  0.62460905,  0.62480783,  0.6246901 ,\n",
+              "         0.6245936 ,  0.6248162 ,  0.624754  ,  0.62437105,  0.62430066,\n",
+              "         0.6244233 ,  0.6243633 ,  0.62407166,  0.6241861 ,  0.6241456 ,\n",
+              "         0.6239719 ,  0.62391376,  0.62415487,  0.6238682 ,  0.6239241 ,\n",
+              "         0.62390107,  0.6236789 ,  0.6237806 ,  0.6236614 ,  0.62358916,\n",
+              "         0.6236376 ,  0.62371755,  0.6237382 ,  0.6238726 ,  0.6240171 ,\n",
+              "         0.6239264 ,  0.623931  ,  0.6237308 ,  0.62395936,  0.6234018 ,\n",
+              "         0.6237265 ,  0.6237913 ,  0.6235492 ,  0.62318647,  0.62349266,\n",
+              "         0.62327045,  0.6232548 ,  0.6233126 ,  0.6232084 ,  0.6232786 ,\n",
+              "         0.62339824,  0.62359285,  0.6235284 ,  0.6235471 ,  0.6234016 ,\n",
+              "         0.6233313 ,  0.6232729 ,  0.6232614 ,  0.62335205,  0.6232998 ,\n",
+              "...\n",
+              "         0.7798304 ,  0.77984285,  0.7798039 ,  0.7798881 ,  0.77983624,\n",
+              "         0.779747  ,  0.7796003 ,  0.7796562 ,  0.77964693,  0.77976   ,\n",
+              "         0.77982175,  0.77987325,  0.7798803 ,  0.77981853,  0.7798599 ,\n",
+              "         0.77976817,  0.7797355 ,  0.7797223 ,  0.77958274,  0.7794968 ,\n",
+              "         0.77951866,  0.7793451 ,  0.77977306,  0.7798404 ,  0.7796792 ,\n",
+              "         0.77951556,  0.7797541 ,  0.7796244 ,  0.77954704,  0.779882  ,\n",
+              "         0.7796897 ,  0.78009367,  0.77984214,  0.77977324,  0.77981466,\n",
+              "         0.77967215,  0.77980614,  0.7795769 ,  0.77972573,  0.77955645,\n",
+              "         0.7796588 ,  0.77955323,  0.7795721 ,  0.7795167 ,  0.7794243 ,\n",
+              "         0.77918714,  0.77930677,  0.7793621 ,  0.77909505,  0.7792217 ,\n",
+              "         0.7788761 ,  0.7790808 ,  0.7791028 ,  0.7788446 ,  0.7789332 ,\n",
+              "         0.7788981 ,  0.7789904 ,  0.779241  ,  0.7791693 ,  0.77889454,\n",
+              "         0.7789502 ,  0.77890694,  0.7785553 ,  0.77865255,  0.7788394 ,\n",
+              "         0.7787025 ,  0.7788493 ,  0.77891165,  0.7789452 ,  0.77867603,\n",
+              "         0.7785905 ,  0.7783878 ,  0.77855736,  0.778772  ,  0.7786441 ,\n",
+              "         0.77870494,  0.77878624,  0.77881914,  0.77884936,  0.77857053,\n",
+              "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
+              "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
+              "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
+              "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-5d44956c-ab08-4505-8349-958abb22d285' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d44956c-ab08-4505-8349-958abb22d285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af079542-e422-4727-a9aa-ee35e55d167b' class='xr-var-data-in' type='checkbox'><label for='data-af079542-e422-4727-a9aa-ee35e55d167b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-0e61f0b6-7c4c-40e0-96e7-bb1e2a4cebbe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0e61f0b6-7c4c-40e0-96e7-bb1e2a4cebbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c7662af-9d5a-40a9-8d38-b6a8fb5de2a7' class='xr-var-data-in' type='checkbox'><label for='data-8c7662af-9d5a-40a9-8d38-b6a8fb5de2a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-06ac4f63-6a95-4bb6-a462-653a100a377e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06ac4f63-6a95-4bb6-a462-653a100a377e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06baa9a2-45ff-48b3-a9ee-74d355a0a411' class='xr-var-data-in' type='checkbox'><label for='data-06baa9a2-45ff-48b3-a9ee-74d355a0a411' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-c0805455-2ff4-4e88-89b0-7c7091550ab0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0805455-2ff4-4e88-89b0-7c7091550ab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c831574-6334-440f-9598-3ba702c50951' class='xr-var-data-in' type='checkbox'><label for='data-5c831574-6334-440f-9598-3ba702c50951' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-27e99ded-1aab-4d10-95c2-cc8021014e94' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27e99ded-1aab-4d10-95c2-cc8021014e94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69ec1af4-09a2-4e22-ba4e-a2bd2ebf7406' class='xr-var-data-in' type='checkbox'><label for='data-69ec1af4-09a2-4e22-ba4e-a2bd2ebf7406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
+              "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
+              "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
+              "       0.12      , 0.12333333, 0.12      , 0.11      , 0.11      ,\n",
+              "       0.11666667, 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11333334,\n",
+              "       0.12      , 0.11666667, 0.11666667, 0.11666667, 0.11333334,\n",
+              "       0.12      , 0.11666667, 0.11      , 0.12333333, 0.13333334,\n",
+              "       0.13333334, 0.13      , 0.13333334, 0.12666667, 0.13333334,\n",
+              "       0.13      , 0.13      , 0.15333334, 0.13333334, 0.15333334,\n",
+              "       0.14333333, 0.13666667, 0.11666667, 0.13666667, 0.13333334,\n",
+              "       0.13666667, 0.14666666, 0.14      , 0.15666667, 0.13333334,\n",
+              "       0.13333334, 0.15      , 0.15      , 0.12666667, 0.13666667,\n",
+              "       0.15      , 0.13      , 0.13666667, 0.13      , 0.13666667,\n",
+              "       0.13666667, 0.14333333, 0.13666667, 0.12666667, 0.13666667,\n",
+              "       0.12333333, 0.12333333, 0.13333334, 0.12      , 0.11666667,\n",
+              "       0.11      , 0.11      , 0.11666667, 0.12333333, 0.11      ,\n",
+              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.11      , 0.11333334, 0.11      , 0.11      ,\n",
+              "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11      ,\n",
+              "       0.11      , 0.11333334, 0.11      , 0.11      , 0.11333334,\n",
+              "       0.11      , 0.20333333, 0.22666667, 0.22      , 0.22      ,\n",
+              "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
+              "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
+              "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
+              "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-7f13db59-d349-450f-8878-6f0209dfe965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f13db59-d349-450f-8878-6f0209dfe965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f78f2c5-6cad-4576-9ed9-4afdfc8f8653' class='xr-var-data-in' type='checkbox'><label for='data-3f78f2c5-6cad-4576-9ed9-4afdfc8f8653' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
+              "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
+              "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
+              "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
+              "       3.3772287, 3.3739138, 3.3298807, 3.368963 , 3.357279 , 3.3420138,\n",
+              "       3.3332636, 3.2887158, 3.3332634, 3.3267972, 3.3609293, 3.34788  ,\n",
+              "       3.3524635, 3.2797818, 3.2383478, 3.2774158, 3.3357968, 3.2894654,\n",
+              "       3.237099 , 3.2444148, 3.250231 , 3.3133483, 3.3285973, 3.3003979,\n",
+              "       3.3281136, 3.3106983, 3.2960656, 3.3239977, 3.3058155, 3.231132 ,\n",
+              "       3.2188826, 3.2362165, 3.2269833, 3.1857452, 3.2025456, 3.1971133,\n",
+              "       3.1716278, 3.1624265, 3.196963 , 3.1550453, 3.162944 , 3.158162 ,\n",
+              "       3.1250577, 3.1385927, 3.1210082, 3.1101758, 3.116926 , 3.1283762,\n",
+              "       3.1307604, 3.149876 , 3.1709106, 3.1579425, 3.157861 , 3.1293783,\n",
+              "       3.1623626, 3.0823452, 3.1290247, 3.1371257, 3.103561 , 3.0512455,\n",
+              "       3.0958426, 3.0634787, 3.061212 , 3.0691292, 3.0543785, 3.0647104,\n",
+              "       3.0809944, 3.1082118, 3.099077 , 3.1025605, 3.0808105, 3.070144 ,\n",
+              "       3.061945 , 3.0596778, 3.0728438, 3.0654464, 3.082978 , 3.0888774,\n",
+              "       3.090909 , 3.1166098, 3.1326916, 3.1294093, 3.1606429, 3.0821111,\n",
+              "       3.0704782, 3.099461 , 3.1288106, 3.0858114, 3.1094916, 3.1244771,\n",
+              "       3.0631604, 3.098195 , 3.0228472, 3.0709112, 3.0849445, 3.0772102,\n",
+              "       3.10411  , 3.0789108, 3.122175 , 3.0939767, 3.126108 , 3.1068432,\n",
+              "       3.1269426, 3.124676 , 3.133493 , 3.1521947, 3.1957629, 3.174427 ,\n",
+              "       3.1647441, 3.2137322, 3.1900635, 3.2544334, 3.2174487, 3.2122307,\n",
+              "       3.2605999, 3.244882 , 3.2509172, 3.234432 , 3.1874464, 3.200428 ,\n",
+              "       3.251467 , 3.2418153, 3.24985  , 3.3141315, 3.2959988, 3.2620163,\n",
+              "       3.2882996, 3.2601004, 3.2490656, 3.242116 , 3.2917488, 3.306215 ,\n",
+              "       3.3455298, 3.3139143, 3.274265 , 3.2986312, 3.2870982, 3.271833 ,\n",
+              "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
+              "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
+              "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
+              "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-08bf9483-f94a-47e8-a9f7-3ebd5cd4d73c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08bf9483-f94a-47e8-a9f7-3ebd5cd4d73c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc6b05ac-bc98-4aca-b40b-b17091d5b850' class='xr-var-data-in' type='checkbox'><label for='data-bc6b05ac-bc98-4aca-b40b-b17091d5b850' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
+              "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
+              "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
+              "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
+              "       -0.04223333, -0.0388    , -0.05338333, -0.0568    , -0.0611    ,\n",
+              "       -0.0627    , -0.07021666, -0.05368333, -0.0487    , -0.0493    ,\n",
+              "       -0.05311666, -0.06443334, -0.04586667, -0.04441666, -0.04498333,\n",
+              "       -0.03575   , -0.03521667, -0.07056666, -0.07609999, -0.0662    ,\n",
+              "       -0.04191666, -0.06681666, -0.06818333, -0.07636666, -0.07111666,\n",
+              "       -0.05511666, -0.0493    , -0.05571667, -0.04891667, -0.04571667,\n",
+              "       -0.04198333, -0.00336667,  0.08048334,  0.25323334,  0.22161667,\n",
+              "        0.19196668,  0.15959999,  0.11676668,  0.09488333,  0.07456666,\n",
+              "        0.05981667,  0.06043334,  0.06175001,  0.05643333,  0.04858334,\n",
+              "        0.06248334,  0.06495   ,  0.07498333,  0.06741667,  0.07038333,\n",
+              "        0.06546666,  0.06541666,  0.06608333,  0.07325   ,  0.0566    ,\n",
+              "        0.054     ,  0.061     ,  0.0511    ,  0.05655   ,  0.02896667,\n",
+              "        0.02978333,  0.04755   ,  0.01526667,  0.00998333,  0.0108    ,\n",
+              "        0.00458333,  0.00831667,  0.00378333, -0.00401667, -0.00796667,\n",
+              "        0.00555   ,  0.01133333,  0.00541667, -0.0047    , -0.0019    ,\n",
+              "       -0.00158333, -0.01193333, -0.00146667, -0.00791667, -0.00841667,\n",
+              "       -0.00898333, -0.00903333, -0.002     ,  0.00205   ,  0.00393333,\n",
+              "       -0.00233333,  0.01098333, -0.01495   , -0.01253333,  0.0059    ,\n",
+              "        0.01675   , -0.0048    ,  0.00353333,  0.00155   , -0.01018333,\n",
+              "        0.00053333, -0.0111    , -0.01913333, -0.02155   , -0.02396666,\n",
+              "       -0.01793333, -0.02523333, -0.0194    , -0.02291666, -0.02203333,\n",
+              "       -0.0282    , -0.02571667, -0.03851666, -0.0208    , -0.03573333,\n",
+              "       -0.02388333, -0.03908334, -0.04381667, -0.031     , -0.04036666,\n",
+              "       -0.02826666, -0.04583333, -0.0394    , -0.03658333, -0.04336667,\n",
+              "       -0.04073333, -0.05656667, -0.0553    , -0.05688334, -0.04293333,\n",
+              "       -0.05556666, -0.05011667, -0.02433333, -0.03963333, -0.04716667,\n",
+              "       -0.05826667, -0.05943333, -0.06553333, -0.04911667, -0.04304999,\n",
+              "       -0.023     , -0.03935   , -0.03393333, -0.04798333, -0.05141667,\n",
+              "       -0.04823333, -0.05695   , -0.05431667, -0.07600001, -0.0419    ,\n",
+              "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
+              "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
+              "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
+              "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-2d6f4d64-3246-4832-b1fc-083c048d424f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d6f4d64-3246-4832-b1fc-083c048d424f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33ad160c-075a-434a-9ede-419f3fb177f2' class='xr-var-data-in' type='checkbox'><label for='data-33ad160c-075a-434a-9ede-419f3fb177f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
+              "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
+              "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
+              "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
+              "       -7.3838835, -7.3748665, -7.3916   , -7.391783 , -7.3853164,\n",
+              "       -7.377949 , -7.3945003, -7.3738666, -7.373867 , -7.369084 ,\n",
+              "       -7.372767 , -7.3854327, -7.3678336, -7.3722672, -7.3625836,\n",
+              "       -7.3666334, -7.360083 , -7.3809   , -7.3875995, -7.3742666,\n",
+              "       -7.3516665, -7.369966 , -7.387017 , -7.386867 , -7.379284 ,\n",
+              "       -7.361167 , -7.3493667, -7.3615665, -7.344417 , -7.350366 ,\n",
+              "       -7.3399496, -7.300467 , -7.236433 , -7.0768504, -6.997516 ,\n",
+              "       -6.949867 , -6.899017 , -6.8814178, -6.8526497, -6.8263836,\n",
+              "       -6.813383 , -6.8076496, -6.78375  , -6.781251 , -6.7671165,\n",
+              "       -6.7577667, -6.7516494, -6.728033 , -6.72715  , -6.716767 ,\n",
+              "       -6.708234 , -6.69495  , -6.6866503, -6.6791   , -6.6603007,\n",
+              "       -6.659384 , -6.6542172, -6.659967 , -6.6461835, -6.667401 ,\n",
+              "       -6.6473837, -6.6366506, -6.6365337, -6.649917 , -6.6360173,\n",
+              "       -6.638784 , -6.6400666, -6.62885  , -6.628683 , -6.617567 ,\n",
+              "       -6.6096334, -6.59625  , -6.589217 , -6.5807333, -6.5850334,\n",
+              "       -6.5764165, -6.5684667, -6.5721836, -6.55585  , -6.5561   ,\n",
+              "       -6.5420327, -6.5459166, -6.5430665, -6.5388503, -6.5341506,\n",
+              "       -6.5321503, -6.52225  , -6.539833 , -6.5372   , -6.528584 ,\n",
+              "       -6.5262337, -6.5375338, -6.5275497, -6.51875  , -6.5324664,\n",
+              "       -6.525267 , -6.548233 , -6.5326   , -6.5178337, -6.5193667,\n",
+              "       -6.505567 , -6.5125165, -6.4989333, -6.508083 , -6.49675  ,\n",
+              "       -6.50315  , -6.4925   , -6.485383 , -6.492067 , -6.4811997,\n",
+              "       -6.4708   , -6.4739504, -6.472566 , -6.4622664, -6.4698668,\n",
+              "       -6.4504333, -6.4621997, -6.4667   , -6.45215  , -6.4554167,\n",
+              "       -6.454716 , -6.461316 , -6.4738665, -6.473217 , -6.458534 ,\n",
+              "       -6.46535  , -6.4565167, -6.4414663, -6.4526324, -6.4590497,\n",
+              "       -6.4487834, -6.4628167, -6.46505  , -6.4660163, -6.4543834,\n",
+              "       -6.4556837, -6.4339333, -6.443283 , -6.4565334, -6.4484835,\n",
+              "       -6.4508667, -6.4604836, -6.4581666, -6.4554834, -6.4470496,\n",
+              "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
+              "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
+              "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
+              "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-35b2ed85-ed6d-4fe3-b607-ccf38d8398a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35b2ed85-ed6d-4fe3-b607-ccf38d8398a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06996559-8ed5-44f7-b751-bd2d98806fca' class='xr-var-data-in' type='checkbox'><label for='data-06996559-8ed5-44f7-b751-bd2d98806fca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
+              "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
+              "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
+              "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
+              "       1023.23627, 1023.24646, 1023.2652 , 1023.2814 , 1023.2947 ,\n",
+              "       1023.3131 , 1023.32043, 1023.33435, 1023.3452 , 1023.3554 ,\n",
+              "       1023.3606 , 1023.366  , 1023.37103, 1023.37616, 1023.38043,\n",
+              "       1023.38403, 1023.3869 , 1023.3915 , 1023.38855, 1023.3802 ,\n",
+              "       1023.3759 , 1023.3691 , 1023.3694 , 1023.3698 , 1023.3653 ,\n",
+              "       1023.3579 , 1023.3548 , 1023.35455, 1023.3548 , 1023.35455,\n",
+              "       1023.3522 , 1023.3529 , 1023.3504 , 1023.3525 , 1023.3523 ,\n",
+              "       1023.3569 , 1023.35583, 1023.35565, 1023.35364, 1023.35455,\n",
+              "       1023.35675, 1023.3567 , 1023.35565, 1023.35364, 1023.35144,\n",
+              "       1023.3499 , 1023.3452 , 1023.347  , 1023.3427 , 1023.3374 ,\n",
+              "       1023.3326 , 1023.32874, 1023.3249 , 1023.3244 , 1023.3244 ,\n",
+              "       1023.3202 , 1023.3271 , 1023.32477, 1023.3281 , 1023.3215 ,\n",
+              "       1023.3281 , 1023.3284 , 1023.3283 , 1023.3299 , 1023.33887,\n",
+              "       1023.3277 , 1023.3379 , 1023.343  , 1023.33966, 1023.35315,\n",
+              "       1023.35333, 1023.34064, 1023.33875, 1023.33   , 1023.3218 ,\n",
+              "       1023.32404, 1023.32294, 1023.30853, 1023.3122 , 1023.3125 ,\n",
+              "       1023.3147 , 1023.3218 , 1023.32446, 1023.3674 , 1023.42395,\n",
+              "       1023.4842 , 1023.5248 , 1023.5321 , 1023.545  , 1023.555  ,\n",
+              "       1023.5453 , 1023.53784, 1023.5425 , 1023.5531 , 1023.56085,\n",
+              "       1023.5671 , 1023.5697 , 1023.5727 , 1023.5777 , 1023.5851 ,\n",
+              "       1023.598  , 1023.61127, 1023.61774, 1023.6253 , 1023.63873,\n",
+              "       1023.6415 , 1023.64105, 1023.6321 , 1023.6085 , 1023.58875,\n",
+              "       1023.55664, 1023.53424, 1023.4919 , 1023.4661 , 1023.4329 ,\n",
+              "       1023.4105 , 1023.3956 , 1023.38354, 1023.3727 , 1023.36206,\n",
+              "       1023.3528 , 1023.34467, 1023.34357, 1023.345  , 1023.34937,\n",
+              "       1023.34894, 1023.3448 , 1023.3418 , 1023.3417 , 1023.3436 ,\n",
+              "       1023.3458 , 1023.3482 , 1023.3505 , 1023.34937, 1023.348  ,\n",
+              "       1023.34607, 1023.3471 , 1023.3476 , 1023.3501 , 1023.3529 ,\n",
+              "       1023.35187, 1023.34894, 1023.3476 , 1023.3455 , 1023.3432 ,\n",
+              "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
+              "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
+              "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
+              "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-1e73a2bb-1751-48d6-b785-a83f6bc250d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e73a2bb-1751-48d6-b785-a83f6bc250d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8977d6d-2db2-41d9-81e9-240c8bb2fd19' class='xr-var-data-in' type='checkbox'><label for='data-e8977d6d-2db2-41d9-81e9-240c8bb2fd19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
+              "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
+              "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
+              "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
+              "        9.90408  ,  9.8704815,  9.843054 ,  9.8099   ,  9.782674 ,\n",
+              "        9.751141 ,  9.722181 ,  9.688391 ,  9.658139 ,  9.624396 ,\n",
+              "        9.591585 ,  9.559362 ,  9.5206785,  9.487036 ,  9.4516325,\n",
+              "        9.418625 ,  9.378983 ,  9.347703 ,  9.310125 ,  9.274782 ,\n",
+              "        9.240932 ,  9.203833 ,  9.168937 ,  9.127398 ,  9.091378 ,\n",
+              "        9.048801 ,  9.012082 ,  8.96804  ,  8.932783 ,  8.890241 ,\n",
+              "        8.854867 ,  8.815892 ,  8.781367 ,  8.746559 ,  8.714514 ,\n",
+              "        8.678216 ,  8.641088 ,  8.608247 ,  8.566862 ,  8.532115 ,\n",
+              "        8.495453 ,  8.461118 ,  8.42251  ,  8.39378  ,  8.36608  ,\n",
+              "        8.334696 ,  8.308269 ,  8.283072 ,  8.254289 ,  8.228873 ,\n",
+              "        8.203963 ,  8.179552 ,  8.162701 ,  8.144332 ,  8.124536 ,\n",
+              "        8.104092 ,  8.085614 ,  8.068075 ,  8.053603 ,  8.043172 ,\n",
+              "        8.025586 ,  8.014922 ,  8.00194  ,  7.9942083,  7.985075 ,\n",
+              "        7.9840665,  7.978806 ,  7.97339  ,  7.9731627,  7.971814 ,\n",
+              "        7.972329 ,  7.9674144,  7.9723177,  7.9744887,  7.9855638,\n",
+              "        7.991272 ,  7.9956956,  8.006041 ,  8.023605 ,  8.038973 ,\n",
+              "        8.049008 ,  8.066569 ,  8.078107 ,  8.090951 ,  8.110414 ,\n",
+              "        8.1288595,  8.1531725,  8.172004 ,  8.192166 ,  8.219532 ,\n",
+              "        8.241356 ,  8.265544 ,  8.288776 ,  8.314842 ,  8.338862 ,\n",
+              "        8.363347 ,  8.388729 ,  8.418659 ,  8.4457035,  8.479128 ,\n",
+              "        8.511397 ,  8.542225 ,  8.57435  ,  8.609074 ,  8.643846 ,\n",
+              "        8.674181 ,  8.707741 ,  8.740917 ,  8.776131 ,  8.809834 ,\n",
+              "        8.847663 ,  8.883326 ,  8.921983 ,  8.956591 ,  8.994466 ,\n",
+              "        9.032357 ,  9.072943 ,  9.107945 ,  9.147928 ,  9.18505  ,\n",
+              "        9.218539 ,  9.25671  ,  9.293107 ,  9.324933 ,  9.361722 ,\n",
+              "        9.397845 ,  9.436231 ,  9.464766 ,  9.502145 ,  9.534171 ,\n",
+              "        9.566268 ,  9.601108 ,  9.627889 ,  9.660232 ,  9.6932535,\n",
+              "        9.72142  ,  9.752015 ,  9.780852 ,  9.808266 ,  9.838272 ,\n",
+              "        9.864178 ,  9.885547 ,  9.914127 ,  9.934637 ,  9.957427 ,\n",
+              "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
+              "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
+              "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
+              "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-400cff7d-055a-406c-82dd-65f3899bfa15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-400cff7d-055a-406c-82dd-65f3899bfa15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d307196c-3293-4485-b360-dd1af5b8f79e' class='xr-var-data-in' type='checkbox'><label for='data-d307196c-3293-4485-b360-dd1af5b8f79e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
+              "        0.04634431],\n",
+              "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
+              "        0.03873245],\n",
+              "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
+              "        0.04237254],\n",
+              "       ...,\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan],\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan],\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan]], shape=(28, 183), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7981bfe4-6c23-4de2-90a7-27bebe03c277' class='xr-section-summary-in' type='checkbox'  ><label for='section-7981bfe4-6c23-4de2-90a7-27bebe03c277' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
+            ],
+            "text/plain": [
+              "<xarray.Dataset> Size: 379kB\n",
+              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
+              "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
+              "Coordinates:\n",
+              "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+              "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
+              "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
+              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+              "  * beam            (beam) int32 16B 1 2 3 4\n",
+              "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
+              "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
+              "  * q               (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+              "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+              "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
+              "Data variables: (12/38)\n",
+              "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+              "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+              "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+              "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+              "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
+              "    ...              ...\n",
+              "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+              "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+              "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+              "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+              "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+              "Attributes: (12/41)\n",
+              "    fs:                        1\n",
+              "    n_bin:                     300\n",
+              "    n_fft:                     300\n",
+              "    description:               Binned averages calculated from ensembles of s...\n",
+              "    filehead_config:           {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"...\n",
+              "    inst_model:                Signature1000\n",
+              "    ...                        ...\n",
+              "    has_imu:                   1\n",
+              "    beam_angle:                25\n",
+              "    range_offset:              0.6\n",
+              "    declination:               15.8\n",
+              "    declination_in_orientmat:  1\n",
+              "    principal_heading:         11.1898"
+            ]
+          },
+          "execution_count": 19,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "ds_avg"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
-    "\n",
-    "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
-    "plt.title(\"TI Difference\")"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.6 Reynolds Stress Components\n",
-    "\n",
-    "The next parameters we'll find here are the Reynolds normal and shear stresses (-$\\overline{u_iu_j}$). Since we're using the vertical beam on the ADCP, we can directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
-    "\n",
-    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the normal and shear stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. \n",
-    "\n",
-    "Both of these functions will give comparable results, but `stress_tensor_5beam` takes into account instrument tilt, and `stress_tensor_4beam` does not. Both will throw a tilt warning if tilt is greater than 5 degrees.\n",
-    "\n",
-    "#### Quick 5-beam ADCP lesson before we dive in:\n",
-    "\n",
-    "There are a couple caveats to calculating Reynolds stress tensor components:\n",
-    "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unknowns, 5 knowns)\n",
-    "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
-    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly (\"coupled ADCPs\")\n",
-    "  4. Measurements close to the seafloor can be suspect due to increased vertical flow. ADCPs operate under the \"assumption of homogeneity\", which means that they can only accurate measure consistent horizontal currents with relatively little vertical motion.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "As an example, we'll calculate the Reynolds stresses from the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs: the raw dataset in \"beam\" coordinates, the instrument Doppler noise, the ADCP's orientation and its beam angle. It outputs both the normal stress (\"tke_vec\") and the shear stress (\"stress_vec\") vector. Note, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
-   "outputs": [
+    },
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\dolfyn\\adp\\turbulence.py:407: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
-   "source": [
-    "dolfyn.rotate2(ds, \"beam\", inplace=True)\n",
-    "ds_avg[\"tke_vec\"], ds_avg[\"stress_vec\"] = avg_tool.stress_tensor_5beam(\n",
-    "    ds, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "There is one other important thing to note on Reynolds stress measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the stress transported by larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue, though on its own it may not be particularly useful."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.7 TKE Production\n",
-    "\n",
-    "Though it can't be found from this deployment, we'll go over how to estimate the TKE shear production rate. Note that we're assuming here that the buoyancy production is negligible and we're in a well-mixed tidal channel. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
-    "\n",
-    "It is possible to estimate production rates from either an ADV or an ADCP aligned with the flow direction (so \"X\" would align with the principal flow direction). The following estimation for shear production rates takes into account both along- and cross-stream shear:\n",
-    "\n",
-    "$P = -\\overline{u'w'}\\frac{du}{dz} - \\overline{v'w'}\\frac{dv}{dz}$\n",
-    "\n",
-    "Note that the signs can get tricky but are important here. We found the Reynolds shear stresses -$\\overline{u'w'}$ and -$\\overline{v'w'}$ above using the Reynolds stress equations. If ADV data is available, those estimations are preferred because the ADV's point measurement does not have the assumptions that ADCP measurements have.\n",
-    "\n",
-    "The velocity shear components can be found from the aptly named functions `dudz` and `dvdz` in ADPBinner. These functions, which are useful alone in their own right, approximate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"approximate\" is also used here for velocity shear.\n",
-    "\n",
-    "The velocity shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation. If using ADV data, take the mean again of the \"range\" dimension."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
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",
+            "text/plain": [
+              "<Figure size 800x800 with 4 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "vel = ds_avg[\"vel\"]\n",
+        "\n",
+        "vel_dim = [d for d in vel.dims if d in (\"dir\", \"earth\", \"inst\", \"beam\")][0]\n",
+        "labels = vel.coords[vel_dim].values\n",
+        "\n",
+        "fig, axes = plt.subplots(len(labels), 1, figsize=(8, 2 * len(labels)), sharex=True)\n",
+        "\n",
+        "if len(labels) == 1:\n",
+        "    axes = [axes]\n",
+        "\n",
+        "for ax_i, label in zip(axes, labels):\n",
+        "    values = vel.sel({vel_dim: label}).values.ravel()\n",
+        "    values = values[np.isfinite(values)]\n",
+        "\n",
+        "    ax_i.hist(values, bins=50, color=\"steelblue\", edgecolor=\"black\", alpha=0.8)\n",
+        "    ax_i.set_title(f\"Velocity histogram: {label}\")\n",
+        "    ax_i.set_ylabel(\"Count\")\n",
+        "\n",
+        "axes[-1].set_xlabel(\"Velocity [m/s]\")\n",
+        "plt.tight_layout()"
+      ]
+    },
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Vertical shear gradients\n",
-    "upwp_ = ds_avg[\"stress_vec\"][1]\n",
-    "vpwp_ = ds_avg[\"stress_vec\"][2]\n",
-    "\n",
-    "# Find shear velocity and and ensemble-average it\n",
-    "ds.velds.rotate2(\"principal\", inplace=True)\n",
-    "dudz_raw = avg_tool.dudz(ds[\"vel\"], orientation=\"up\")\n",
-    "dudz = avg_tool.mean(dudz_raw.values)\n",
-    "\n",
-    "dvdz_raw = avg_tool.dvdz(ds[\"vel\"], orientation=\"up\")\n",
-    "dvdz = avg_tool.mean(dvdz_raw.values)\n",
-    "\n",
-    "# Calculate Production\n",
-    "P = -upwp_ * dudz - vpwp_ * dvdz\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 7.8 TKE Balance \n",
-    "We can plot the production rates and the ratio of production rates to dissipation rates to get an understanding of the TKE balance.We always expect production to be greater than 0, though negative values can give us an indication of uncertainty. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates are possibly high because our stress components aren't aligned with the flow (1.3x10^-3 $m^2/s^3$ is quite large), but if this weren't the case, we would conclude that TKE is produced (kinetic energy is lost to turbulence) but not dissipated (turbulent energy is lost to entropy) here."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 1500x400 with 6 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "fig, axes = plt.subplots(1, 3, figsize=(15, 4))\n",
+        "\n",
+        "for i, ax in enumerate(axes):\n",
+        "    ds_avg[\"vel\"][i].plot(ax=ax, vmin=-1.5, vmax=1.5, cmap=\"RdBu_r\")\n",
+        "    ax.set_title(ds_avg[\"vel\"].coords[\"dir\"].values[i])\n",
+        "    ax.tick_params(axis=\"x\", labelrotation=45)\n",
+        "\n",
+        "plt.tight_layout()"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 4. Calculate Speed and Direction\n",
+        "\n",
+        "Two additional variables that might be of interest, which are not automatically provided, are the magnitude of the horizontal velocity (referred to as `U_mag` or speed) and its direction (`U_dir`). These can be accessed via \"shortcut\" functions through the keyword `velds`, as demonstrated in the subsequent code block.\n",
+        "\n",
+        "For a comprehensive list of these \"shortcut\" functions, you can refer to the [DOLfYN documentation](https://dolfyn.readthedocs.io/en/latest/apidoc/dolfyn.shortcuts.html)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "scrolled": true
+      },
+      "outputs": [],
+      "source": [
+        "ds_avg[\"U_mag\"] = ds_avg.velds.U_mag\n",
+        "ds_avg[\"U_dir\"] = ds_avg.velds.U_dir"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Plotting"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Plotting can be accomplished through the user's preferred package. Matplotlib is shown here for simplicity, and flow speed and direction are plotted below with a blue line delineating the water surface level."
+      ]
+    },
     {
-     "data": {
-      "text/plain": [
-       "Text(0.5, 1.0, 'TKE Balance')"
+      "cell_type": "code",
+      "execution_count": 23,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<matplotlib.colorbar.Colorbar at 0x26b1487b9d0>"
+            ]
+          },
+          "execution_count": 23,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 800x500 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "%matplotlib inline\n",
+        "from matplotlib import pyplot as plt\n",
+        "import matplotlib.dates as dt\n",
+        "\n",
+        "ax = plt.figure(figsize=(8, 5)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
+        "# Plot flow speed\n",
+        "t = dolfyn.time.dt642date(ds_avg[\"time\"])\n",
+        "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_mag\"], cmap=\"Blues\", shading=\"nearest\")\n",
+        "# Plot the water surface\n",
+        "ax.plot(t, ds_avg[\"depth\"], color=\"black\", label=\"Depth\")\n",
+        "\n",
+        "# Set up time on x-axis\n",
+        "ax.set_xlabel(\"Time\")\n",
+        "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
+        "\n",
+        "ax.set_ylabel(\"Altitude [m]\")\n",
+        "ax.set_ylim([0, 12])\n",
+        "plt.colorbar(label=\"Speed [m/s]\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "scrolled": false
+      },
+      "outputs": [
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 800x500 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "ax = plt.figure(figsize=(8, 5)).add_axes([0.14, 0.14, 0.8, 0.74])\n",
+        "# Plot flow direction\n",
+        "plt.pcolormesh(t, ds_avg[\"range\"], ds_avg[\"U_dir\"], cmap=\"twilight\", shading=\"nearest\")\n",
+        "# Plot the water surface\n",
+        "ax.plot(t, ds_avg[\"depth\"], color=\"black\", label=\"Depth\")\n",
+        "\n",
+        "# set up time on x-axis\n",
+        "ax.set_xlabel(\"Time\")\n",
+        "ax.xaxis.set_major_formatter(dt.DateFormatter(\"%H:%M\"))\n",
+        "\n",
+        "ax.set_ylabel(\"Altitude [m]\")\n",
+        "ax.set_ylim([0, 12])\n",
+        "plt.colorbar(label=\"Horizontal Vel Dir [deg CW from true N]\");"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Saving and Loading DOLfYN datasets\n",
+        "Datasets can be saved and reloaded using the `save` and `load` functions. Xarray is saved natively in netCDF format, hence the \".nc\" extension.\n",
+        "\n",
+        "Note: DOLfYN datasets cannot be saved using xarray's native `ds.to_netcdf`; however, DOLfYN datasets can be opened using `xarray.open_dataset`."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Uncomment these lines to save and load to your current working directory\n",
+        "# dolfyn.save(ds, 'your_data.nc')\n",
+        "# ds_saved = dolfyn.load('your_data.nc')"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 7. Turbulence Statistics\n",
+        "\n",
+        "The next section of this jupyter notebook will run through the turbulence analysis of the data presented here. There was no intention of measuring turbulence in the deployment that collected this data, so results depicted here are not the highest quality. The quality of turbulence measurements from an ADCP depend heavily on the quality of the deployment setup and data collection, particularly instrument frequency, samping frequency and depth bin size.\n",
+        "\n",
+        "Read more on proper ADCP setup for turbulence measurements in: Thomson, Jim, et al. \"Measurements of turbulence at two tidal energy sites in Puget Sound, WA.\" IEEE Journal of Oceanic Engineering 37.3 (2012): 363-374.\n",
+        "\n",
+        "Most functions related to turbulence statistics in MHKiT-DOLfYN have the papers they originate from referenced in their docstrings.\n",
+        "\n",
+        "### 7.1 Turbulence Intensity\n",
+        "For most users, turbulence intensity (TI), the ratio of the ensemble standard deviation to ensemble flow speed given as a percent, is all most will need. In MHKiT, this can be simply calculated as `<raw dataset>.velds.I`, but be aware that this will be a conservative estimate. Another function, `turbulence_intensity`, is capable of subtracting instrument noise from this parameter and is discussed below. The noise-subtracted TI is more accurate and typically 1-2% lower than the non-noise-subtracted estimation.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.QuadMesh at 0x26b14973fd0>"
+            ]
+          },
+          "execution_count": 26,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "# Turbulence Intensity\n",
+        "ds_avg[\"TI\"] = ds_avg.velds.I\n",
+        "ds_avg[\"TI\"].plot(cmap=\"Reds\", ylim=(0, 11))"
       ]
-     },
-     "execution_count": 39,
-     "metadata": {},
-     "output_type": "execute_result"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.2 Power Spectral Densities (Auto-Spectra)\n",
+        "\n",
+        "Other turbulence parameters include the TKE power- and cross-spectral densities (i.e the power spectra), turbulent kinetic energy (TKE, i.e. the variances of velocity vector components), Reynolds stress vector (i.e. the co-variances of velocity vector components), TKE dissipation rate, and TKE production rate. These quantities are primarily used to inform and verify hydrodynamic and coastal models, which take some or all of these quantities as input.\n",
+        "\n",
+        "The TKE production rate is the rate at which kinetic energy (KE) transitions from a useful state (able to do \"work\" in the physics sense) to turbulent; TKE is the actual amount of turbulent KE in the water; and TKE dissipation rate is the rate at which turbulent KE is lost to non-motion forms of energy (heat, sound, etc) due to viscosity. The power spectra are used to depict and quantify this energy in the frequency domain, and creating them are the first step in turbulence analysis.\n",
+        "\n",
+        "We'll start by looking at the power spectra, specifically the auto-spectra from the vertical beam (\"auto\" meaning the variance of a single vector direction, e.g. $\\overline{u'^2}$, vs \"cross\", meaning the covariance of two directions, e.g. $\\overline{u'w'}$). This can be done using the `power_spectral_density` function from the `ADPBinner` we created (\"avg_tool\"). We'll create spectra at the middle water column, at a depth of 5 m, and an FFT length equal to 1/2 the bin size with 50% overlap between FFT segments"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\991425260.py:12: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n"
+          ]
+        }
+      ],
+      "source": [
+        "rng = 5  # m\n",
+        "vel_up = ds[\"vel_b5\"].sel(range_b5=rng, method=\"nearest\")  # vertical velocity\n",
+        "U = ds_avg[\"U_mag\"].sel(\n",
+        "    range=5, method=\"nearest\"\n",
+        ")  # flow speed, for plotting in the next block\n",
+        "\n",
+        "# fill NaN values with mean to not affect statistics\n",
+        "vel_up = dolfyn.adv.clean.fill_nan_ensemble_mean(\n",
+        "    vel_up, vel_up.isnull(), int(ds.fs), window=window\n",
+        ")\n",
+        "\n",
+        "ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n",
+        "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 2, pct_overlap=0.5\n",
+        ")"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "In the auto-spectra, we're primarly looking for three components: the energy-producing region, the isotropic turbulence region (so-called \"red noise\"), and the instrument noise floor (termed \"white noise\"). \n",
+        "\n",
+        "The block below organizes and plots the power spectra by the corresponding ensemble speed, averaging them by 0.1 m/s velocity bins. Note that if an ensemble is missing data that wasn't filled in, a power spectrum will not be calculated for that ensemble timestamp."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[Text(0.5, 0, 'Frequency [Hz]'),\n",
+              " Text(0, 0.5, 'PSD [m2 s-2 Hz-1]'),\n",
+              " (0.01, 1),\n",
+              " (0.0005, 0.1)]"
+            ]
+          },
+          "execution_count": 28,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 600x500 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import matplotlib as mpl\n",
+        "\n",
+        "plt.rcParams.update({\"font.size\": 18, \"font.family\": \"Times New Roman\"})\n",
+        "\n",
+        "\n",
+        "def plot_spectra_by_color(auto_spectra, U_mag, ax, fig, cbar_max=4.0):\n",
+        "    U = U_mag.interp(time=auto_spectra[\"time_psd\"]).values\n",
+        "    U_max = U_mag.max().values\n",
+        "\n",
+        "    # Average spectra into 0.1 m/s velocity bins\n",
+        "    speed_bins = np.arange(0.5, U_max, 0.1)\n",
+        "    S_group = auto_spectra.assign_coords({\"time_psd\": U}).rename({\"time_psd\": \"speed\"})\n",
+        "    group = S_group.groupby_bins(\"speed\", speed_bins)\n",
+        "    count = group.count().values\n",
+        "    S = group.mean()\n",
+        "\n",
+        "    # define the colormap\n",
+        "    cmap = plt.cm.turbo\n",
+        "    # define the bins and normalize\n",
+        "    bounds = np.arange(0.5, cbar_max, 0.1)\n",
+        "    norm = mpl.colors.BoundaryNorm(bounds, cmap.N)\n",
+        "    colors = cmap(norm(speed_bins))\n",
+        "\n",
+        "    # plot\n",
+        "    for i in range(len(speed_bins) - 1):\n",
+        "        ax.loglog(auto_spectra[\"freq\"], S[i], c=colors[i])\n",
+        "    ax.grid()\n",
+        "\n",
+        "    # create a second axes for the colorbar\n",
+        "    cax = fig.add_axes([0.8, 0.07, 0.03, 0.88])\n",
+        "    # cax, _ = mpl.colorbar.make_axes(fig.gca())\n",
+        "    sm = mpl.colorbar.ColorbarBase(\n",
+        "        cax,\n",
+        "        cmap=cmap,\n",
+        "        norm=norm,\n",
+        "        spacing=\"proportional\",\n",
+        "        ticks=bounds,\n",
+        "        boundaries=bounds,\n",
+        "        format=\"%1.1f\",\n",
+        "        label=\"Velocity [m/s]\",\n",
+        "    )\n",
+        "\n",
+        "    # Add -5/3 slope line\n",
+        "    m = -5 / 3\n",
+        "    x = np.logspace(-1, 0.5)\n",
+        "    y = 10 ** (-3) * x**m\n",
+        "    ax.loglog(x, y, \"--\", c=\"black\", label=\"$f^{-5/3}$\")\n",
+        "    ax.legend()\n",
+        "\n",
+        "    return ax, sm\n",
+        "\n",
+        "\n",
+        "# Set up figure\n",
+        "fig, ax = plt.subplots(1, 1, figsize=(6, 5))\n",
+        "fig.subplots_adjust(left=0.2, right=0.75, top=0.95, bottom=0.1)\n",
+        "\n",
+        "# Plot spectra by color\n",
+        "plot_spectra_by_color(ds_avg[\"auto_spectra_5m\"], U, ax, fig, cbar_max=2.0)\n",
+        "# Set axes\n",
+        "ax.set(\n",
+        "    xlabel=\"Frequency [Hz]\",\n",
+        "    ylabel=\"PSD [m2 s-2 Hz-1]\",\n",
+        "    xlim=(0.01, 1),\n",
+        "    ylim=(0.0005, 0.1),\n",
+        ")"
       ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "In the figure above, we can see the energy-producing turbulent structures below a frequency of 0.2 Hz (one tick to the right of \"10^-1\"). The isotropic turbulence cascade, seen by the dashed f^(-5/3) slope (from Kolmogorov's theory of turbulence) begins at around 0.2 Hz and continues until we reach the Nyquist frequency at 0.5 Hz (1/2 the instrument's sampling frequency, 1 Hz). The instrument's noise floor can't be seen here, but will show up as the flattened part of the spectra at the highest frequencies. For this instrument (Nortek Signature1000), the noise floor typically varies around 10^-3, depending on flow speed and range distance."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.3 Instrument Noise\n",
+        "\n",
+        "The next thing we want to do is calculate the instrument's Doppler noise floor from the spectrum we calculated above. (We are making the assumption that the noise floor of the vertical beam is the same as the noise floor of the other 4 beams). This gives us a timeseries of the noise floor, which varies by instrument and with flow speed, at that depth bin.\n",
+        "\n",
+        "We can do this using the `doppler_noise_level` function. The two inputs for this function are the power spectra and \"pct_fN\", the percent of the Nyquist frequency that the noise floor exists. Because in this particularly dataset we can't see the noise floor, we'll just use 90% or pct_fN=0.9 as an example. If the noise floor began at 0.4 Hz and ran til our maximum frequency of 0.5 Hz, we'd use pct_fN = 0.4 Hz / 0.5 Hz = 0.8."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Statistic</th>\n",
+              "      <th>Value</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>mean</td>\n",
+              "      <td>0.026137</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>std</td>\n",
+              "      <td>0.010011</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>min</td>\n",
+              "      <td>0.010585</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>max</td>\n",
+              "      <td>0.055315</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "  Statistic     Value\n",
+              "0      mean  0.026137\n",
+              "1       std  0.010011\n",
+              "2       min  0.010585\n",
+              "3       max  0.055315"
+            ]
+          },
+          "execution_count": 29,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "ds_avg[\"noise_5m\"] = avg_tool.doppler_noise_level(ds_avg[\"auto_spectra_5m\"], pct_fN=0.9)\n",
+        "\n",
+        "noise_stats = pd.DataFrame({\n",
+        "    \"Statistic\": [\"mean\", \"std\", \"min\", \"max\"],\n",
+        "    \"Value\": [\n",
+        "        float(ds_avg[\"noise_5m\"].mean().values),\n",
+        "        float(ds_avg[\"noise_5m\"].std().values),\n",
+        "        float(ds_avg[\"noise_5m\"].min().values),\n",
+        "        float(ds_avg[\"noise_5m\"].max().values),\n",
+        "    ]\n",
+        "})\n",
+        "\n",
+        "noise_stats"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.4 TKE Dissipation Rate\n",
+        "\n",
+        "Because we can see the isotropic turbulence cascade (0.2 - 0.5 Hz) at this depth bin (5 m altitude), we can calculate the TKE dissipation rate at this location from the spectra itself. This can be done using `dissipation_rate_LT83`, whose inputs are the power spectra, the ensemble speed, the frequency range of the isotropic cascade, and the instrument's noise."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Frequency range of isotropic turubulence cascade in same units as PSD frequency vector\n",
+        "f_rng = [0.1, 0.5]\n",
+        "# Dissipation rate\n",
+        "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
+        "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "We have just found the spectra and dissipation rate from a single depth bin at an altitude of 5 m from the seafloor, but typically we want the spectra and dissipation rates from the entire measurement profile. If we want to look at the spectra and dissipation rates from all depth bins, we can set up a \"for\" loop on the range coordinate and merge them together:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+            "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_4972\\3010848191.py:10: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=150 samples, pct_overlap=0.5).\n",
+            "  spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n"
+          ]
+        }
+      ],
+      "source": [
+        "import xarray as xr\n",
+        "\n",
+        "spec = [None] * len(ds.range)\n",
+        "e = [None] * len(ds.range)\n",
+        "n = [None] * len(ds.range)\n",
+        "\n",
+        "for r in range(len(ds[\"range\"])):\n",
+        "    # Calc spectra from each depth bin using the 5th beam\n",
+        "    vel_up = ds[\"vel_b5\"].isel(range_b5=r).fillna(vel_up.mean(\"time_b5\"))\n",
+        "    spec[r] = avg_tool.power_spectral_density(vel_up, freq_units=\"Hz\", pct_overlap=0.5)\n",
+        "    \n",
+        "    # Calculate doppler noise from spectra from each depth bin\n",
+        "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
+        "    \n",
+        "    # Calc dissipation rate from each spectra\n",
+        "    e[r] = avg_tool.dissipation_rate_LT83(\n",
+        "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
+        "    )\n",
+        "\n",
+        "ds_avg[\"auto_spectra\"] = xr.concat(spec, dim=\"range\")\n",
+        "ds_avg[\"noise\"] = xr.concat(n, dim=\"range\")\n",
+        "ds_avg[\"dissipation_rate\"] = xr.concat(e, dim=\"range\")\n",
+        "\n",
+        "del spec, n, e  # save memory"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Now that we have a profile timeseries of dissipation rate, we need apply some quality control (QC). Since we can't look at each individual spectrum to ensure we can see the isotropic turbulence cascade, we want to QC the output from `dissipation_rate_LT83` to make sure what was calculated actually falls on a f^(-5/3) slope. We can do this using the function `check_turbulence_cascade_slope`, which uses linear regression on the log-transformed LT83 equation (ref. to Lumley and Terray, 1983, see docstring) to calculate the spectral slope for the given frequency range. \n",
+        "\n",
+        "In our case, we're calculating the slope of each spectrum between 0.2 and 0.5 Hz. We'll use a cutoff of 20% for the error, but this can be lowered if there still appear to be erroneous estimations from visual inspection of the spectra."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 32,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Quality control dissipation rate estimation\n",
+        "slope = avg_tool.check_turbulence_cascade_slope(\n",
+        "    ds_avg[\"auto_spectra\"], freq_range=f_rng\n",
+        ")\n",
+        "\n",
+        "# Check that percent difference from -5/3 is not greater than 20%\n",
+        "mask = abs((slope[0].values - (-5 / 3)) / (-5 / 3)) <= 0.20\n",
+        "\n",
+        "# Keep good data\n",
+        "ds_avg[\"dissipation_rate\"] = ds_avg[\"dissipation_rate\"].where(mask)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "If we plot the dissipation rate below in a colormap, we can see that the profile map has a lot of missing data. One of the reasons is that the 1 Hz sampling rate doesn't provide enough information needed to make dissipation rate estimations, and the other part is that turbulence measurements push the boundaries of what ADCPs are capable of.\n",
+        "\n",
+        "Also, 1x10^-4 to 3x10^-4 $m^2/s^3$ is reasonable for a dissipation rate estimate for the 1 - 1.5 m/s current speeds measured here. They can be a magnitude greater for faster flow speeds, typically increase closer to the seafloor, and depend heavily on bathymetry and regional hydrodynamics."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 33,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.QuadMesh at 0x26b0ef15350>"
+            ]
+          },
+          "execution_count": 33,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "ds_avg[\"dissipation_rate\"].plot(cmap=\"turbo\", ylim=(0, 11))"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.5 Noise-Corrected Turbulence Intensity\n",
+        "\n",
+        "Now that we've calculated the noise floor for each ping, we can recalculate TI and include subtracting instrument noise using the `turbulence_intensity` function. If we subtract this from the non-noise corrected function, we can see there's a large difference\n",
+        "at slower slow speeds, but the average difference is about 0.008 (0.8%). Notice this will also remove measurements where noise is \n",
+        "high."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 34,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Text(0.5, 1.0, 'TI Difference')"
+            ]
+          },
+          "execution_count": 34,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
+        "\n",
+        "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
+        "plt.title(\"TI Difference\")"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.6 Reynolds Stress Components\n",
+        "\n",
+        "The next parameters we'll find here are the Reynolds normal and shear stresses (-$\\overline{u_iu_j}$). Since we're using the vertical beam on the ADCP, we can directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
+        "\n",
+        "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the normal and shear stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. \n",
+        "\n",
+        "Both of these functions will give comparable results, but `stress_tensor_5beam` takes into account instrument tilt, and `stress_tensor_4beam` does not. Both will throw a tilt warning if tilt is greater than 5 degrees.\n",
+        "\n",
+        "#### Quick 5-beam ADCP lesson before we dive in:\n",
+        "\n",
+        "There are a couple caveats to calculating Reynolds stress tensor components:\n",
+        "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unknowns, 5 knowns)\n",
+        "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
+        "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly (\"coupled ADCPs\")\n",
+        "  4. Measurements close to the seafloor can be suspect due to increased vertical flow. ADCPs operate under the \"assumption of homogeneity\", which means that they can only accurate measure consistent horizontal currents with relatively little vertical motion.\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "As an example, we'll calculate the Reynolds stresses from the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs: the raw dataset in \"beam\" coordinates, the instrument Doppler noise, the ADCP's orientation and its beam angle. It outputs both the normal stress (\"tke_vec\") and the shear stress (\"stress_vec\") vector. Note, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 35,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\adp\\turbulence.py:421: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+            "  warnings.warn(\n"
+          ]
+        }
+      ],
+      "source": [
+        "dolfyn.rotate2(ds, \"beam\", inplace=True)\n",
+        "ds_avg[\"tke_vec\"], ds_avg[\"stress_vec\"] = avg_tool.stress_tensor_5beam(\n",
+        "    ds, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "There is one other important thing to note on Reynolds stress measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the stress transported by larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue, though on its own it may not be particularly useful."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.7 TKE Production\n",
+        "\n",
+        "Though it can't be found from this deployment, we'll go over how to estimate the TKE shear production rate. Note that we're assuming here that the buoyancy production is negligible and we're in a well-mixed tidal channel. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
+        "\n",
+        "It is possible to estimate production rates from either an ADV or an ADCP aligned with the flow direction (so \"X\" would align with the principal flow direction). The following estimation for shear production rates takes into account both along- and cross-stream shear:\n",
+        "\n",
+        "$P = -\\overline{u'w'}\\frac{du}{dz} - \\overline{v'w'}\\frac{dv}{dz}$\n",
+        "\n",
+        "Note that the signs can get tricky but are important here. We found the Reynolds shear stresses -$\\overline{u'w'}$ and -$\\overline{v'w'}$ above using the Reynolds stress equations. If ADV data is available, those estimations are preferred because the ADV's point measurement does not have the assumptions that ADCP measurements have.\n",
+        "\n",
+        "The velocity shear components can be found from the aptly named functions `dudz` and `dvdz` in ADPBinner. These functions, which are useful alone in their own right, approximate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"approximate\" is also used here for velocity shear.\n",
+        "\n",
+        "The velocity shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation. If using ADV data, take the mean again of the \"range\" dimension."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 36,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\rotate\\api.py:71: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
+            "  warnings.warn(\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Vertical shear gradients\n",
+        "upwp_ = ds_avg[\"stress_vec\"][1]\n",
+        "vpwp_ = ds_avg[\"stress_vec\"][2]\n",
+        "\n",
+        "# Find shear velocity and and ensemble-average it\n",
+        "ds.velds.rotate2(\"principal\", inplace=True)\n",
+        "dudz_raw = avg_tool.dudz(ds[\"vel\"], orientation=\"up\")\n",
+        "dudz = avg_tool.mean(dudz_raw.values)\n",
+        "\n",
+        "dvdz_raw = avg_tool.dvdz(ds[\"vel\"], orientation=\"up\")\n",
+        "dvdz = avg_tool.mean(dvdz_raw.values)\n",
+        "\n",
+        "# Calculate Production\n",
+        "P = -upwp_ * dudz - vpwp_ * dvdz\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### 7.8 TKE Balance \n",
+        "We can plot the production rates and the ratio of production rates to dissipation rates to get an understanding of the TKE balance.We always expect production to be greater than 0, though negative values can give us an indication of uncertainty. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates are possibly high because our stress components aren't aligned with the flow (1.3x10^-3 $m^2/s^3$ is quite large), but if this weren't the case, we would conclude that TKE is produced (kinetic energy is lost to turbulence) but not dissipated (turbulent energy is lost to entropy) here."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 37,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Text(0.5, 1.0, 'TKE Balance')"
+            ]
+          },
+          "execution_count": 37,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "# Remove estimations below 0\n",
+        "P = P.where(P > 0)\n",
+        "# Plot production rate\n",
+        "P.plot(cmap=\"turbo\", ylim=(0, 11))\n",
+        "plt.title(\"TKE Production\")  # remove bogus title\n",
+        "\n",
+        "# Interp to same time coordinates\n",
+        "dissipation = ds_avg[\"dissipation_rate\"].interp(time_psd=P[\"time\"]).values\n",
+        "\n",
+        "# Plot difference between production and dissipation rate\n",
+        "plt.figure()\n",
+        "balance = P - dissipation\n",
+        "balance.plot(ylim=(0, 11))\n",
+        "plt.title(\"TKE Balance\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "work",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.10"
     }
-   ],
-   "source": [
-    "# Remove estimations below 0\n",
-    "P = P.where(P > 0)\n",
-    "# Plot production rate\n",
-    "P.plot(cmap=\"turbo\", ylim=(0, 11))\n",
-    "plt.title(\"TKE Production\")  # remove bogus title\n",
-    "\n",
-    "\n",
-    "# Plot difference between production and dissipation rate\n",
-    "plt.figure()\n",
-    "balance = P - ds_avg[\"dissipation_rate\"].values\n",
-    "balance.plot(ylim=(0, 11))\n",
-    "plt.title(\"TKE Balance\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Updated_MHKiT",
-   "language": "python",
-   "name": "python3"
   },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
+  "nbformat": 4,
+  "nbformat_minor": 4
 }
diff --git a/examples/adcp_waves_example.ipynb b/examples/adcp_waves_example.ipynb
index 8b8dda1b7..be3c17240 100644
--- a/examples/adcp_waves_example.ipynb
+++ b/examples/adcp_waves_example.ipynb
@@ -55,7 +55,8 @@
      "output_type": "stream",
      "text": [
       "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\io\\nortek2_lib.py:304: UserWarning: Dual Profile detected... Two datasets will be returned.\n",
-      "  warnings.warn(msg)\n"
+      "  warnings.warn(msg)\n",
+      "Dual Profile detected... Two datasets will be returned.\n"
      ]
     },
     {
@@ -106,39 +107,86 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        "html[theme=\"dark\"],\n",
        "html[data-theme=\"dark\"],\n",
        "body[data-theme=\"dark\"],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1f1f1f;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -161,11 +209,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -174,6 +229,8 @@
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
        "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -184,10 +241,12 @@
        "  display: inline-block;\n",
        "  opacity: 0;\n",
        "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -196,7 +255,7 @@
        "}\n",
        "\n",
        ".xr-section-item input:focus + label {\n",
-       "  border: 2px solid var(--xr-font-color0);\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label:hover {\n",
@@ -241,7 +300,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -251,6 +309,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -258,6 +317,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -328,7 +413,9 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -339,6 +426,7 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -388,8 +476,15 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -402,6 +497,12 @@
        "  float: right;\n",
        "}\n",
        "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -461,6 +562,14 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 11MB\n",
        "Dimensions:                 (time: 18073, time_altraw: 35, range: 13, beam: 4,\n",
        "                             dir: 4, dirIMU: 3, n_altraw: 2583, x1: 4, x2: 4,\n",
@@ -504,10 +613,10 @@
        "    fs:                    1\n",
        "    bandwidth:             &quot;BROAD&quot;\n",
        "    has_imu:               0\n",
-       "    beam_angle:            20</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-73387bb8-ff17-4a70-ae1e-d28a835b009f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-73387bb8-ff17-4a70-ae1e-d28a835b009f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 18073</li><li><span class='xr-has-index'>time_altraw</span>: 35</li><li><span class='xr-has-index'>range</span>: 13</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span>n_altraw</span>: 2583</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-27c70c72-cbfa-4901-8a76-d6732546a6f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-27c70c72-cbfa-4901-8a76-d6732546a6f3' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.334399938 .....</div><input id='attrs-350fc6a3-4a51-4516-852d-72c058e09c1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-350fc6a3-4a51-4516-852d-72c058e09c1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0454cb8e-de6e-4294-92e8-71f7c12e30bb' class='xr-var-data-in' type='checkbox'><label for='data-0454cb8e-de6e-4294-92e8-71f7c12e30bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.334399938&#x27;, &#x27;2024-10-22T19:29:37.334399938&#x27;,\n",
+       "    beam_angle:            20</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d999aca-1678-4838-a66b-eb7dc2983e73' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d999aca-1678-4838-a66b-eb7dc2983e73' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 18073</li><li><span class='xr-has-index'>time_altraw</span>: 35</li><li><span class='xr-has-index'>range</span>: 13</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span>n_altraw</span>: 2583</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c7caa3aa-86df-4606-aeaa-a0c72cf41d90' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c7caa3aa-86df-4606-aeaa-a0c72cf41d90' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.334399938 .....</div><input id='attrs-a0951f09-1486-4d1d-baad-53c7a01eb31c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0951f09-1486-4d1d-baad-53c7a01eb31c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f81df920-491e-447b-949f-dd117b36fd88' class='xr-var-data-in' type='checkbox'><label for='data-f81df920-491e-447b-949f-dd117b36fd88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.334399938&#x27;, &#x27;2024-10-22T19:29:37.334399938&#x27;,\n",
        "       &#x27;2024-10-22T19:29:38.334399938&#x27;, ..., &#x27;2024-10-23T04:10:38.334399938&#x27;,\n",
        "       &#x27;2024-10-23T04:10:39.334199905&#x27;, &#x27;2024-10-23T04:10:40.334399938&#x27;],\n",
-       "      shape=(18073,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.000999927 .....</div><input id='attrs-a83feb10-8d6d-4ad1-ac67-586f62800524' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a83feb10-8d6d-4ad1-ac67-586f62800524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dc11762-06c3-4059-8f71-42ce8da479da' class='xr-var-data-in' type='checkbox'><label for='data-5dc11762-06c3-4059-8f71-42ce8da479da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time altraw</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.000999927&#x27;, &#x27;2024-10-22T19:46:39.000999927&#x27;,\n",
+       "      shape=(18073,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.000999927 .....</div><input id='attrs-62e065c8-7144-459e-a541-387bcd6cc0d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62e065c8-7144-459e-a541-387bcd6cc0d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6737f532-67fb-445d-972f-4eb75b517b0f' class='xr-var-data-in' type='checkbox'><label for='data-6737f532-67fb-445d-972f-4eb75b517b0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time altraw</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.000999927&#x27;, &#x27;2024-10-22T19:46:39.000999927&#x27;,\n",
        "       &#x27;2024-10-22T19:59:36.000999927&#x27;, &#x27;2024-10-22T20:16:39.000999927&#x27;,\n",
        "       &#x27;2024-10-22T20:29:36.000999927&#x27;, &#x27;2024-10-22T20:46:39.000999927&#x27;,\n",
        "       &#x27;2024-10-22T20:59:36.000999927&#x27;, &#x27;2024-10-22T21:16:39.000999927&#x27;,\n",
@@ -524,26 +633,26 @@
        "       &#x27;2024-10-23T02:29:36.000999927&#x27;, &#x27;2024-10-23T02:46:39.000999927&#x27;,\n",
        "       &#x27;2024-10-23T02:59:36.000999927&#x27;, &#x27;2024-10-23T03:16:39.000999927&#x27;,\n",
        "       &#x27;2024-10-23T03:29:36.000999927&#x27;, &#x27;2024-10-23T03:46:39.000999927&#x27;,\n",
-       "       &#x27;2024-10-23T03:59:36.000999927&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.7 42.2 45.7 ... 73.7 77.2 80.7</div><input id='attrs-53fed162-6709-4959-a5d8-201416b8999f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53fed162-6709-4959-a5d8-201416b8999f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7330cf07-c451-4027-a6ed-e43f3d8e2f2d' class='xr-var-data-in' type='checkbox'><label for='data-7330cf07-c451-4027-a6ed-e43f3d8e2f2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([38.7, 42.2, 45.7, 49.2, 52.7, 56.2, 59.7, 63.2, 66.7, 70.2, 73.7, 77.2,\n",
-       "       80.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-ef7db9ae-55b6-4a12-9776-70aaae2e400c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef7db9ae-55b6-4a12-9776-70aaae2e400c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6232025-af30-4bb2-80a8-3a057008a4c2' class='xr-var-data-in' type='checkbox'><label for='data-a6232025-af30-4bb2-80a8-3a057008a4c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3a01b450-c477-4353-8e47-db9fe814c450' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a01b450-c477-4353-8e47-db9fe814c450' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fac65951-3380-4519-8ee1-506ead0d5c7e' class='xr-var-data-in' type='checkbox'><label for='data-fac65951-3380-4519-8ee1-506ead0d5c7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-21a9de9c-0c8a-4c32-8cc6-2093c588b3e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21a9de9c-0c8a-4c32-8cc6-2093c588b3e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7148f06d-250c-48ea-af49-bc641a440ab7' class='xr-var-data-in' type='checkbox'><label for='data-7148f06d-250c-48ea-af49-bc641a440ab7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-fe5abe59-7bfe-4c4c-a098-56b744a76e91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe5abe59-7bfe-4c4c-a098-56b744a76e91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dda39fb-7e49-4532-82d4-879deeb89bf6' class='xr-var-data-in' type='checkbox'><label for='data-9dda39fb-7e49-4532-82d4-879deeb89bf6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-d4fa9332-8b4c-4c7e-8b61-810c37b99b9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4fa9332-8b4c-4c7e-8b61-810c37b99b9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97718d04-c918-4c2c-aebe-1894d35366fc' class='xr-var-data-in' type='checkbox'><label for='data-97718d04-c918-4c2c-aebe-1894d35366fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-eafcd6d5-996d-4074-a5ed-f31aa2267539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eafcd6d5-996d-4074-a5ed-f31aa2267539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-966715da-7d57-49d8-9f64-d8a6c9c88221' class='xr-var-data-in' type='checkbox'><label for='data-966715da-7d57-49d8-9f64-d8a6c9c88221' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-4c1da1c1-472d-4c5d-a982-999437fd7b63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c1da1c1-472d-4c5d-a982-999437fd7b63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b541531-af2c-45cd-be99-47e20225ff94' class='xr-var-data-in' type='checkbox'><label for='data-4b541531-af2c-45cd-be99-47e20225ff94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-23a85adb-4f1f-4474-9918-711e537d8c41' class='xr-section-summary-in' type='checkbox'  ><label for='section-23a85adb-4f1f-4474-9918-711e537d8c41' class='xr-section-summary' >Data variables: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.503e+03 1.503e+03 ... 1.485e+03</div><input id='attrs-9a1b7651-c756-4536-ac7d-e6035a7d1292' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a1b7651-c756-4536-ac7d-e6035a7d1292' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a50ef2ee-0433-4e59-95bd-7532c123e2fc' class='xr-var-data-in' type='checkbox'><label for='data-a50ef2ee-0433-4e59-95bd-7532c123e2fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1503.2, 1503.2, 1503.2, ..., 1484.6, 1484.5, 1484.6],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.93 13.92 13.92 ... 8.23 8.23</div><input id='attrs-58234fe8-4d64-4dbd-99ff-08ceeb89ccc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58234fe8-4d64-4dbd-99ff-08ceeb89ccc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e458078-e7e7-4df7-9f70-c59564dbedf7' class='xr-var-data-in' type='checkbox'><label for='data-0e458078-e7e7-4df7-9f70-c59564dbedf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([13.93, 13.92, 13.92, ...,  8.23,  8.23,  8.23],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.768 0.765 0.762 ... 74.71 74.71</div><input id='attrs-c662c573-491e-44ce-aa86-4f9e6c511913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c662c573-491e-44ce-aa86-4f9e6c511913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-113b1785-2e28-41d7-b802-f20174c725bd' class='xr-var-data-in' type='checkbox'><label for='data-113b1785-2e28-41d7-b802-f20174c725bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.768,  0.765,  0.762, ..., 74.694, 74.706, 74.711],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>216.1 215.8 216.7 ... 212.7 212.9</div><input id='attrs-4d728563-cd12-4b75-92cf-2f5e003c40a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d728563-cd12-4b75-92cf-2f5e003c40a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78383fa9-b0e4-4d41-b9e0-24b5b44bfd30' class='xr-var-data-in' type='checkbox'><label for='data-78383fa9-b0e4-4d41-b9e0-24b5b44bfd30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([216.09, 215.8 , 216.7 , ..., 212.88, 212.72, 212.95],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.59 -28.03 -29.35 ... 2.21 2.22</div><input id='attrs-bf52dbc0-c274-4968-b0ad-1250476ba1f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf52dbc0-c274-4968-b0ad-1250476ba1f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a8dc43-d59c-4d39-b557-94b9859e0b82' class='xr-var-data-in' type='checkbox'><label for='data-84a8dc43-d59c-4d39-b557-94b9859e0b82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-27.59, -28.03, -29.35, ...,   2.19,   2.21,   2.22],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>73.04 71.68 67.74 ... -0.36 -0.4</div><input id='attrs-a2ba103c-550c-4c48-a191-ae4284dd20e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2ba103c-550c-4c48-a191-ae4284dd20e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8e8b50-6351-43ae-ad5f-68f98c39442b' class='xr-var-data-in' type='checkbox'><label for='data-0b8e8b50-6351-43ae-ad5f-68f98c39442b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([73.04, 71.68, 67.74, ..., -0.38, -0.36, -0.4 ],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.9 8.8 8.4 ... -60.9 -60.8 -60.9</div><input id='attrs-31c0002c-0d0b-489f-b6f1-974696770951' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31c0002c-0d0b-489f-b6f1-974696770951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee0b1dcf-c40e-46fd-a282-1362f210328b' class='xr-var-data-in' type='checkbox'><label for='data-ee0b1dcf-c40e-46fd-a282-1362f210328b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  5.9,   8.8,   8.4, ..., -21.7, -21.8, -21.7],\n",
+       "       &#x27;2024-10-23T03:59:36.000999927&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.7 42.2 45.7 ... 73.7 77.2 80.7</div><input id='attrs-b480889a-2752-4d80-a556-14d2d3fa49e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b480889a-2752-4d80-a556-14d2d3fa49e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8f43935-6b41-4b38-8d68-1a480818f72e' class='xr-var-data-in' type='checkbox'><label for='data-f8f43935-6b41-4b38-8d68-1a480818f72e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([38.7, 42.2, 45.7, 49.2, 52.7, 56.2, 59.7, 63.2, 66.7, 70.2, 73.7, 77.2,\n",
+       "       80.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-7a128d3d-f06e-4611-8b9d-eea8bd218e6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a128d3d-f06e-4611-8b9d-eea8bd218e6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb17efd8-df6d-42d7-9487-c4d7a003c709' class='xr-var-data-in' type='checkbox'><label for='data-bb17efd8-df6d-42d7-9487-c4d7a003c709' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-9d8e48d2-05e1-4aa8-b3d2-69da9063835c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d8e48d2-05e1-4aa8-b3d2-69da9063835c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31cb655a-ab4b-450d-be6b-54a17704ea5c' class='xr-var-data-in' type='checkbox'><label for='data-31cb655a-ab4b-450d-be6b-54a17704ea5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-e906626f-cef0-4bd6-a4fd-4c57ce51247c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e906626f-cef0-4bd6-a4fd-4c57ce51247c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a598964-fc16-44a5-bb04-641cf8c57cda' class='xr-var-data-in' type='checkbox'><label for='data-1a598964-fc16-44a5-bb04-641cf8c57cda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-9f561613-9800-4d14-907a-19e2ee16d103' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f561613-9800-4d14-907a-19e2ee16d103' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88ae1a6-4daa-4e41-b553-61ac143ffc68' class='xr-var-data-in' type='checkbox'><label for='data-f88ae1a6-4daa-4e41-b553-61ac143ffc68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-1b6bcf3d-bfce-4941-ad0d-8cd07a48962e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b6bcf3d-bfce-4941-ad0d-8cd07a48962e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54dbc7f9-5458-4da4-bba5-1f3c23680b94' class='xr-var-data-in' type='checkbox'><label for='data-54dbc7f9-5458-4da4-bba5-1f3c23680b94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-e32a7cd2-e4e7-4733-8a25-a915f4f25ed4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e32a7cd2-e4e7-4733-8a25-a915f4f25ed4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-848f9801-4af8-4273-b8d8-d6af17cf7125' class='xr-var-data-in' type='checkbox'><label for='data-848f9801-4af8-4273-b8d8-d6af17cf7125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-482c3815-d1d8-4a0c-9906-a4c105ae5108' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-482c3815-d1d8-4a0c-9906-a4c105ae5108' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92047868-1584-4ae7-ae74-ae8f784bf576' class='xr-var-data-in' type='checkbox'><label for='data-92047868-1584-4ae7-ae74-ae8f784bf576' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a573ed7c-ccb0-4f73-b9cf-d31743ebb182' class='xr-section-summary-in' type='checkbox'  ><label for='section-a573ed7c-ccb0-4f73-b9cf-d31743ebb182' class='xr-section-summary' >Data variables: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.503e+03 1.503e+03 ... 1.485e+03</div><input id='attrs-a54c0da6-de6a-4ecb-85dc-6b01a15ed416' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a54c0da6-de6a-4ecb-85dc-6b01a15ed416' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7749a1bb-8b02-45ff-b205-cd1128bb7752' class='xr-var-data-in' type='checkbox'><label for='data-7749a1bb-8b02-45ff-b205-cd1128bb7752' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1503.2, 1503.2, 1503.2, ..., 1484.6, 1484.5, 1484.6],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.93 13.92 13.92 ... 8.23 8.23</div><input id='attrs-025bbdc9-a713-4ee2-bd2a-2457abc667d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-025bbdc9-a713-4ee2-bd2a-2457abc667d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d199a491-6d9a-4cee-a1fb-306d816d9105' class='xr-var-data-in' type='checkbox'><label for='data-d199a491-6d9a-4cee-a1fb-306d816d9105' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([13.93, 13.92, 13.92, ...,  8.23,  8.23,  8.23],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.768 0.765 0.762 ... 74.71 74.71</div><input id='attrs-2f678b9a-815f-4b48-8c7d-fea6de6d3863' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f678b9a-815f-4b48-8c7d-fea6de6d3863' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7af5288-d2a7-431c-89b2-3ac45cfff57d' class='xr-var-data-in' type='checkbox'><label for='data-e7af5288-d2a7-431c-89b2-3ac45cfff57d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.768,  0.765,  0.762, ..., 74.694, 74.706, 74.711],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>216.1 215.8 216.7 ... 212.7 212.9</div><input id='attrs-99367d76-603e-4887-8f01-19db9dcee92e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99367d76-603e-4887-8f01-19db9dcee92e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-191b6e6b-d697-428b-9708-f408b829b1eb' class='xr-var-data-in' type='checkbox'><label for='data-191b6e6b-d697-428b-9708-f408b829b1eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([216.09, 215.8 , 216.7 , ..., 212.88, 212.72, 212.95],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.59 -28.03 -29.35 ... 2.21 2.22</div><input id='attrs-0ed157b7-9e3c-441c-bb17-0a45517876d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ed157b7-9e3c-441c-bb17-0a45517876d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1bf99de-922b-44f3-824d-87336cccd4a7' class='xr-var-data-in' type='checkbox'><label for='data-d1bf99de-922b-44f3-824d-87336cccd4a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-27.59, -28.03, -29.35, ...,   2.19,   2.21,   2.22],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>73.04 71.68 67.74 ... -0.36 -0.4</div><input id='attrs-70225c8c-c8bd-412a-bdd5-b6b0cca70cd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70225c8c-c8bd-412a-bdd5-b6b0cca70cd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbaea8c3-cda8-41d4-8543-4d6ac43e3ad6' class='xr-var-data-in' type='checkbox'><label for='data-dbaea8c3-cda8-41d4-8543-4d6ac43e3ad6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([73.04, 71.68, 67.74, ..., -0.38, -0.36, -0.4 ],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.9 8.8 8.4 ... -60.9 -60.8 -60.9</div><input id='attrs-9c02d73c-1ab9-4824-bb2c-00ed13e32809' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c02d73c-1ab9-4824-bb2c-00ed13e32809' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ab23978-23b5-4891-87d7-326a67f846ab' class='xr-var-data-in' type='checkbox'><label for='data-2ab23978-23b5-4891-87d7-326a67f846ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  5.9,   8.8,   8.4, ..., -21.7, -21.8, -21.7],\n",
        "       [-57.6, -56.9, -56.9, ..., -12.1, -12.1, -12.1],\n",
        "       [ -1.9,  -4.9,  -7.3, ..., -60.9, -60.8, -60.9]],\n",
-       "      shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.489 -4.6 -4.715 ... 9.773 9.777</div><input id='attrs-d26746c4-67d4-4f14-a377-4519ffd73bd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d26746c4-67d4-4f14-a377-4519ffd73bd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86efcf88-f7ff-4b64-9bea-6c588e5a2b79' class='xr-var-data-in' type='checkbox'><label for='data-86efcf88-f7ff-4b64-9bea-6c588e5a2b79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.4888654 , -4.6002336 , -4.714596  , ...,  0.37541932,\n",
+       "      shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.489 -4.6 -4.715 ... 9.773 9.777</div><input id='attrs-cf0d45e1-8fbc-4d91-9fb6-156ed9f78c79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf0d45e1-8fbc-4d91-9fb6-156ed9f78c79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99f66ea4-1ac5-4209-b1f4-4f665a3e368c' class='xr-var-data-in' type='checkbox'><label for='data-99f66ea4-1ac5-4209-b1f4-4f665a3e368c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.4888654 , -4.6002336 , -4.714596  , ...,  0.37541932,\n",
        "         0.37781432,  0.38020936],\n",
        "       [ 8.21312   ,  8.201145  ,  7.7568693 , ..., -0.06586304,\n",
        "        -0.06346802, -0.06825805],\n",
        "       [ 2.503993  ,  2.7147546 ,  3.1745985 , ...,  9.772877  ,\n",
-       "         9.772877  ,  9.777068  ]], shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>23.4 23.4 23.4 ... 18.5 18.5 18.5</div><input id='attrs-6e108b4b-c6ea-43e1-af15-516e824500b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e108b4b-c6ea-43e1-af15-516e824500b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-091ff0a7-b374-407b-9409-bf1eed6d19e7' class='xr-var-data-in' type='checkbox'><label for='data-091ff0a7-b374-407b-9409-bf1eed6d19e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([23.4, 23.4, 23.4, ..., 18.5, 18.5, 18.5],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>19.75 19.75 19.75 ... 9.75 9.75</div><input id='attrs-77f41760-8bbb-4917-939f-0a355b82901b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77f41760-8bbb-4917-939f-0a355b82901b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-214e9e4b-9e26-43ed-a3ac-63a70dd39317' class='xr-var-data-in' type='checkbox'><label for='data-214e9e4b-9e26-43ed-a3ac-63a70dd39317' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([19.75, 19.75, 19.75, ...,  9.75,  9.75,  9.75],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-f68cecff-ef50-4eba-92a0-9633402adf22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f68cecff-ef50-4eba-92a0-9633402adf22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-183c312e-2364-45a9-961e-547ec67eead6' class='xr-var-data-in' type='checkbox'><label for='data-183c312e-2364-45a9-961e-547ec67eead6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>675807234 675807234 ... 944504834</div><input id='attrs-1e4bf90a-0b05-4c18-b072-21533f2b3eca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e4bf90a-0b05-4c18-b072-21533f2b3eca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8f9e70a-eebd-474f-8535-a5cca8fb0662' class='xr-var-data-in' type='checkbox'><label for='data-b8f9e70a-eebd-474f-8535-a5cca8fb0662' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([675807234, 675807234, 675807234, ..., 944504834, 944504834,\n",
-       "       944504834], shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 24285 24287 24289 24291</div><input id='attrs-f2725916-7755-4c32-8d36-b22ba1239c2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2725916-7755-4c32-8d36-b22ba1239c2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26f9b5d1-c9e4-4896-b699-dfc29c58a7e4' class='xr-var-data-in' type='checkbox'><label for='data-26f9b5d1-c9e4-4896-b699-dfc29c58a7e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 24287, 24289, 24291],\n",
-       "      shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.231 -2.796 0.219 ... -0.264 0.694</div><input id='attrs-c423276c-a8fe-466b-a156-d7243e75df98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c423276c-a8fe-466b-a156-d7243e75df98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81675a96-bab9-4be0-8ca3-f4de51cab812' class='xr-var-data-in' type='checkbox'><label for='data-81675a96-bab9-4be0-8ca3-f4de51cab812' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[ 1.231e+00, -2.796e+00,  2.190e-01, ...,  1.280e-01,\n",
+       "         9.772877  ,  9.777068  ]], shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>23.4 23.4 23.4 ... 18.5 18.5 18.5</div><input id='attrs-06300640-9ae8-4611-a8f4-d8ae7c8d246d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06300640-9ae8-4611-a8f4-d8ae7c8d246d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-847024c3-c198-471c-b272-d7e703c855e5' class='xr-var-data-in' type='checkbox'><label for='data-847024c3-c198-471c-b272-d7e703c855e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([23.4, 23.4, 23.4, ..., 18.5, 18.5, 18.5],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>19.75 19.75 19.75 ... 9.75 9.75</div><input id='attrs-8f8395e7-da3e-471c-a49e-f77a80a2687b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f8395e7-da3e-471c-a49e-f77a80a2687b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3315053-15f2-41fc-8411-27ba60694b30' class='xr-var-data-in' type='checkbox'><label for='data-d3315053-15f2-41fc-8411-27ba60694b30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([19.75, 19.75, 19.75, ...,  9.75,  9.75,  9.75],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-be55a666-829b-4bae-b954-7668554cada0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be55a666-829b-4bae-b954-7668554cada0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7ca32ff-a69e-4c53-bfa4-e057464df7dd' class='xr-var-data-in' type='checkbox'><label for='data-a7ca32ff-a69e-4c53-bfa4-e057464df7dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>675807234 675807234 ... 944504834</div><input id='attrs-e67c54cc-26aa-4da6-a682-7f0fa6dcd01a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e67c54cc-26aa-4da6-a682-7f0fa6dcd01a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a09841e0-3bc1-44e5-8392-ee0107aece0c' class='xr-var-data-in' type='checkbox'><label for='data-a09841e0-3bc1-44e5-8392-ee0107aece0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([675807234, 675807234, 675807234, ..., 944504834, 944504834,\n",
+       "       944504834], shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 24285 24287 24289 24291</div><input id='attrs-4a5bdc63-be24-46b4-81a6-3a7f0f84b72f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a5bdc63-be24-46b4-81a6-3a7f0f84b72f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b4b1f06-ac65-400b-bf6f-ba2f22bf52a6' class='xr-var-data-in' type='checkbox'><label for='data-5b4b1f06-ac65-400b-bf6f-ba2f22bf52a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 24287, 24289, 24291],\n",
+       "      shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.231 -2.796 0.219 ... -0.264 0.694</div><input id='attrs-f87b142e-8c08-46fa-84fd-11eb44d61d45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f87b142e-8c08-46fa-84fd-11eb44d61d45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c7f9ab0-6a25-461b-9dad-14c7e1425bed' class='xr-var-data-in' type='checkbox'><label for='data-6c7f9ab0-6a25-461b-9dad-14c7e1425bed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[ 1.231e+00, -2.796e+00,  2.190e-01, ...,  1.280e-01,\n",
        "          6.200e-02,  6.400e-02],\n",
        "        [-4.220e+00, -1.316e+00,  1.423e+00, ...,  8.900e-02,\n",
        "          3.900e-02,  8.000e-03],\n",
@@ -583,7 +692,7 @@
        "        [-1.834e+00,  3.931e+00, -2.047e+00, ..., -2.470e-01,\n",
        "         -5.820e-01,  3.050e-01],\n",
        "        [-2.065e+00,  5.129e+00,  4.794e+00, ..., -6.620e-01,\n",
-       "         -2.640e-01,  6.940e-01]]], shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>38.5 39.5 36.5 ... 48.0 43.0 46.5</div><input id='attrs-cfd8139d-1961-4ebe-9c3d-92b0c5977e83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfd8139d-1961-4ebe-9c3d-92b0c5977e83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0991d93-62c5-4eb3-9569-402c2d9f4b8a' class='xr-var-data-in' type='checkbox'><label for='data-e0991d93-62c5-4eb3-9569-402c2d9f4b8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 38.5,  39.5,  36.5, ...,  45. ,  43. ,  42. ],\n",
+       "         -2.640e-01,  6.940e-01]]], shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>38.5 39.5 36.5 ... 48.0 43.0 46.5</div><input id='attrs-7914c53a-36d6-4692-bd9a-b287aab32c81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7914c53a-36d6-4692-bd9a-b287aab32c81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ff945e8-d2bb-4e29-b462-28236f17a268' class='xr-var-data-in' type='checkbox'><label for='data-5ff945e8-d2bb-4e29-b462-28236f17a268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 38.5,  39.5,  36.5, ...,  45. ,  43. ,  42. ],\n",
        "        [ 34.5,  38.5,  37. , ...,  42.5,  41. ,  42. ],\n",
        "        [ 38.5,  36. ,  38.5, ...,  42.5,  41. ,  42. ],\n",
        "        ...,\n",
@@ -614,7 +723,7 @@
        "        [ 29.5,  31.5,  33.5, ...,  91. ,  89.5,  96. ],\n",
        "        [ 28.5,  33.5,  33.5, ...,  81. ,  71.5,  80. ],\n",
        "        [ 30. ,  31. ,  34.5, ...,  48. ,  43. ,  46.5]]],\n",
-       "      shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>26 65 32 45 32 1 ... 91 87 86 84 88</div><input id='attrs-74f69510-5da1-4e88-a1e7-01735d537de8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74f69510-5da1-4e88-a1e7-01735d537de8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95bf7d72-9d9f-49f8-8428-74653b70379e' class='xr-var-data-in' type='checkbox'><label for='data-95bf7d72-9d9f-49f8-8428-74653b70379e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 26,  65,  32, ..., 100,  99,  95],\n",
+       "      shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>26 65 32 45 32 1 ... 91 87 86 84 88</div><input id='attrs-3cebf583-cc25-47c1-8c77-685315a2f4b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cebf583-cc25-47c1-8c77-685315a2f4b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30ad181a-5bbe-4ae8-9577-cd864ad2a5ae' class='xr-var-data-in' type='checkbox'><label for='data-30ad181a-5bbe-4ae8-9577-cd864ad2a5ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 26,  65,  32, ..., 100,  99,  95],\n",
        "        [ 21,  58,  34, ...,  98,  96,  98],\n",
        "        [ 20,  61,  50, ...,  98,  97,  97],\n",
        "        ...,\n",
@@ -645,47 +754,47 @@
        "        [ 27,  13,  64, ..., 100, 100, 100],\n",
        "        [  7,   5,  24, ...,  76,  50,  62],\n",
        "        [ 13,  20,  31, ...,  86,  84,  88]]],\n",
-       "      shape=(4, 13, 18073), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.76 0.766 ... 74.7 74.71</div><input id='attrs-a55ec02e-d476-4301-8a55-2fb4ecbbd7a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a55ec02e-d476-4301-8a55-2fb4ecbbd7a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd70aedd-1080-4963-a4bb-b91f7ada2d69' class='xr-var-data-in' type='checkbox'><label for='data-dd70aedd-1080-4963-a4bb-b91f7ada2d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure measured during AST ping</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.76 ,  0.766, ..., 74.672, 74.703, 74.707],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.22 ... 73.36 73.73</div><input id='attrs-7f3c0de6-4375-47e0-82c1-2632fb2f41f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f3c0de6-4375-47e0-82c1-2632fb2f41f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7539dee0-96d7-413e-afbd-5be9ae33d328' class='xr-var-data-in' type='checkbox'><label for='data-7539dee0-96d7-413e-afbd-5be9ae33d328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.222515, 42.222153, ..., 73.09078 , 73.35817 ,\n",
-       "       73.73138 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 168.8 150.8 171.1</div><input id='attrs-68f066e2-66c7-49db-8a10-c14a1aa7fab2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68f066e2-66c7-49db-8a10-c14a1aa7fab2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ace59c6d-9b22-4368-8846-07366617a7c0' class='xr-var-data-in' type='checkbox'><label for='data-ace59c6d-9b22-4368-8846-07366617a7c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , ..., 168.79, 150.79, 171.05],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 73.21 73.48 73.87</div><input id='attrs-b3e4dce1-876a-4e92-bf55-b6a63b1265a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3e4dce1-876a-4e92-bf55-b6a63b1265a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad0962f4-0c82-44da-aea9-22de34da1fc4' class='xr-var-data-in' type='checkbox'><label for='data-ad0962f4-0c82-44da-aea9-22de34da1fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ..., 73.210526, 73.476036,\n",
-       "       73.86819 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 58.44 58.52 61.61</div><input id='attrs-043e8363-cbf8-4e3a-bc47-c8d20be06070' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-043e8363-cbf8-4e3a-bc47-c8d20be06070' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-550717ee-26bb-4f02-917b-877dea03a7da' class='xr-var-data-in' type='checkbox'><label for='data-550717ee-26bb-4f02-917b-877dea03a7da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  , ..., 58.44, 58.52, 61.61],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3334 -0.3333 ... -0.3331 -0.3333</div><input id='attrs-8c7eb74e-d75b-4cd4-81e3-8c3923ca04e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c7eb74e-d75b-4cd4-81e3-8c3923ca04e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64927e71-1cd2-4937-ba97-52191fcf8ef6' class='xr-var-data-in' type='checkbox'><label for='data-64927e71-1cd2-4937-ba97-52191fcf8ef6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([-0.3334, -0.3333, -0.3332, ..., -0.3333, -0.3331, -0.3333],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.4 12.4 12.4 12.4 ... 7.0 7.0 7.0</div><input id='attrs-2a316ee4-6443-43f2-a28b-6112a316f9ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a316ee4-6443-43f2-a28b-6112a316f9ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd6922c9-c0b0-4331-a132-820cc43d410d' class='xr-var-data-in' type='checkbox'><label for='data-fd6922c9-c0b0-4331-a132-820cc43d410d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.4, 12.4, 12.4, ...,  7. ,  7. ,  7. ],\n",
-       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>170 169 169 169 ... 194 194 194 194</div><input id='attrs-cada8132-eada-463a-a522-f666fad7741d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cada8132-eada-463a-a522-f666fad7741d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35aa781a-198c-4874-8580-d41e70e08c32' class='xr-var-data-in' type='checkbox'><label for='data-35aa781a-198c-4874-8580-d41e70e08c32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([170, 169, 169, ..., 194, 194, 194], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.773 0.769 ... 74.83 74.74</div><input id='attrs-62243207-4af1-4be0-8280-6b5d74a4c0d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62243207-4af1-4be0-8280-6b5d74a4c0d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2265ce8a-96d0-4d62-ab9a-0d4b2c8f5c85' class='xr-var-data-in' type='checkbox'><label for='data-2265ce8a-96d0-4d62-ab9a-0d4b2c8f5c85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.773,  0.769, 25.605, 61.209,  0.777, 34.85 , 62.615,\n",
+       "      shape=(4, 13, 18073), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.76 0.766 ... 74.7 74.71</div><input id='attrs-14af6ea0-5df1-4a99-a429-a9d84c2851e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14af6ea0-5df1-4a99-a429-a9d84c2851e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3b44c25-93d1-4f9a-b524-11853f0f053f' class='xr-var-data-in' type='checkbox'><label for='data-b3b44c25-93d1-4f9a-b524-11853f0f053f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure measured during AST ping</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.76 ,  0.766, ..., 74.672, 74.703, 74.707],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.22 ... 73.36 73.73</div><input id='attrs-116ab0e0-f0df-4a83-8c01-04a7346bfbd2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-116ab0e0-f0df-4a83-8c01-04a7346bfbd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e98b614-b92c-4c5b-8ffb-de6e4a793845' class='xr-var-data-in' type='checkbox'><label for='data-3e98b614-b92c-4c5b-8ffb-de6e4a793845' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.222515, 42.222153, ..., 73.09078 , 73.35817 ,\n",
+       "       73.73138 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 168.8 150.8 171.1</div><input id='attrs-32540a4d-e75a-4c59-be6d-b7954b1adfc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32540a4d-e75a-4c59-be6d-b7954b1adfc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2655d95c-6e0e-409f-8a75-04a25453f425' class='xr-var-data-in' type='checkbox'><label for='data-2655d95c-6e0e-409f-8a75-04a25453f425' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , ..., 168.79, 150.79, 171.05],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 73.21 73.48 73.87</div><input id='attrs-5d315a11-4474-4eb0-9d53-569528f5ab74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d315a11-4474-4eb0-9d53-569528f5ab74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fd8a2b9-9289-4f72-b16a-e1ed15057cce' class='xr-var-data-in' type='checkbox'><label for='data-7fd8a2b9-9289-4f72-b16a-e1ed15057cce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ..., 73.210526, 73.476036,\n",
+       "       73.86819 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 58.44 58.52 61.61</div><input id='attrs-9c26543e-0b77-4d42-b7ee-3bd46d080300' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c26543e-0b77-4d42-b7ee-3bd46d080300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7420cdce-cf4e-4b41-8d7c-0830186c452f' class='xr-var-data-in' type='checkbox'><label for='data-7420cdce-cf4e-4b41-8d7c-0830186c452f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  , ..., 58.44, 58.52, 61.61],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3334 -0.3333 ... -0.3331 -0.3333</div><input id='attrs-9892fa89-2708-44a5-bf59-1e82bdf02307' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9892fa89-2708-44a5-bf59-1e82bdf02307' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-504f2a41-c288-42ec-83ed-3f8cf30bd9c2' class='xr-var-data-in' type='checkbox'><label for='data-504f2a41-c288-42ec-83ed-3f8cf30bd9c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([-0.3334, -0.3333, -0.3332, ..., -0.3333, -0.3331, -0.3333],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.4 12.4 12.4 12.4 ... 7.0 7.0 7.0</div><input id='attrs-166cc5c9-d569-49e2-bd68-3f82e9409ce5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-166cc5c9-d569-49e2-bd68-3f82e9409ce5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f75fb38-03f4-470d-8e83-22daa5ae9aa0' class='xr-var-data-in' type='checkbox'><label for='data-3f75fb38-03f4-470d-8e83-22daa5ae9aa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.4, 12.4, 12.4, ...,  7. ,  7. ,  7. ],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>170 169 169 169 ... 194 194 194 194</div><input id='attrs-8fcf50a9-75fa-45b5-bf06-1e7dbe791a1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fcf50a9-75fa-45b5-bf06-1e7dbe791a1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26150dc9-8646-4c53-ac67-cf6251cad50d' class='xr-var-data-in' type='checkbox'><label for='data-26150dc9-8646-4c53-ac67-cf6251cad50d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([170, 169, 169, ..., 194, 194, 194], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.773 0.769 ... 74.83 74.74</div><input id='attrs-c41fb70d-685f-43e9-a527-afd8d1df5883' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c41fb70d-685f-43e9-a527-afd8d1df5883' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-642821e5-6375-4dab-9952-f674145f73b8' class='xr-var-data-in' type='checkbox'><label for='data-642821e5-6375-4dab-9952-f674145f73b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.773,  0.769, 25.605, 61.209,  0.777, 34.85 , 62.615,\n",
        "       76.575, 76.654, 76.721, 76.75 , 76.721, 76.793, 76.756, 76.727,\n",
        "       76.724, 76.687, 76.631, 76.559, 76.467, 76.287, 76.343, 76.16 ,\n",
        "       76.039, 75.903, 75.822, 75.618, 75.482, 75.335, 75.275, 75.104,\n",
-       "       74.998, 74.829, 74.743], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.25 ... 72.77 73.4</div><input id='attrs-e65bc53b-7e50-44a5-8d43-ffc3c3af4eb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e65bc53b-7e50-44a5-8d43-ffc3c3af4eb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ab0f174-5fe2-420c-a30f-be54c4a854a7' class='xr-var-data-in' type='checkbox'><label for='data-8ab0f174-5fe2-420c-a30f-be54c4a854a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.22245 , 42.248127, 53.838898, 60.334473, 42.095585,\n",
+       "       74.998, 74.829, 74.743], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.25 ... 72.77 73.4</div><input id='attrs-7ac413f2-a4e0-4e7b-95f4-6ec807c44aae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ac413f2-a4e0-4e7b-95f4-6ec807c44aae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29a7e235-3421-4a2c-9efa-43ba426e632b' class='xr-var-data-in' type='checkbox'><label for='data-29a7e235-3421-4a2c-9efa-43ba426e632b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.22245 , 42.248127, 53.838898, 60.334473, 42.095585,\n",
        "       41.693676, 60.747128, 74.52789 , 75.47511 , 75.798546, 75.46673 ,\n",
        "       75.08749 , 75.53308 , 75.00033 , 75.2663  , 75.62667 , 75.66341 ,\n",
        "       75.13237 , 75.59258 , 75.48645 , 74.45196 , 75.09751 , 74.65656 ,\n",
        "       74.63918 , 74.48755 , 74.70199 , 74.48076 , 74.06819 , 73.60065 ,\n",
        "       73.40783 , 73.81639 , 74.335014, 72.76904 , 73.397766],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 67.05 206.4 146.7</div><input id='attrs-28dc13a1-c8d1-4d28-b48a-1e066bf78b1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28dc13a1-c8d1-4d28-b48a-1e066bf78b1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1f3939d-8e78-4087-9f40-cc8241ee0cce' class='xr-var-data-in' type='checkbox'><label for='data-b1f3939d-8e78-4087-9f40-cc8241ee0cce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , 108.67, 135.71,   0.  ,   0.  , 189.97,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 67.05 206.4 146.7</div><input id='attrs-1f7c9ad8-c93d-43fb-b66a-f511e6a53947' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f7c9ad8-c93d-43fb-b66a-f511e6a53947' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0e4cbb1-18fb-4331-86f9-d2d566e8f8c0' class='xr-var-data-in' type='checkbox'><label for='data-a0e4cbb1-18fb-4331-86f9-d2d566e8f8c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , 108.67, 135.71,   0.  ,   0.  , 189.97,\n",
        "       119.84, 127.84, 119.72, 184.63, 123.2 , 213.47, 154.79, 235.96,\n",
        "       135.53, 126.95, 159.85, 207.4 ,  66.16, 212.89, 127.26, 196.62,\n",
        "       125.15, 113.1 , 150.91, 219.6 , 130.77, 113.49, 104.92, 227.87,\n",
-       "        67.05, 206.42, 146.73], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 74.34 72.9 73.52</div><input id='attrs-8ab06b4f-d423-414d-a34c-54b3335244fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ab06b4f-d423-414d-a34c-54b3335244fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ac71329-61c4-40f5-89fe-c081b3e90a79' class='xr-var-data-in' type='checkbox'><label for='data-7ac71329-61c4-40f5-89fe-c081b3e90a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      ,  0.      , 60.475662,  0.      ,\n",
+       "        67.05, 206.42, 146.73], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 74.34 72.9 73.52</div><input id='attrs-c5ccd16d-7917-4045-bfe9-648599fb81b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5ccd16d-7917-4045-bfe9-648599fb81b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32f2261a-263e-4d8e-bf29-88b15bf65af1' class='xr-var-data-in' type='checkbox'><label for='data-32f2261a-263e-4d8e-bf29-88b15bf65af1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      ,  0.      , 60.475662,  0.      ,\n",
        "       41.92075 , 61.05163 , 74.65894 , 75.74271 , 76.07448 , 75.692055,\n",
        "       75.19689 , 75.82613 , 75.08403 , 75.32452 , 75.729965, 76.012314,\n",
        "       75.22676 , 75.71552 , 75.81318 , 74.594826, 75.21046 , 74.7399  ,\n",
        "       75.11347 , 74.77125 , 74.823235, 74.63242 , 74.20987 , 73.8131  ,\n",
        "       73.52494 , 73.96451 , 74.34137 , 72.897064, 73.523224],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 53.5 65.63 61.81</div><input id='attrs-e79fa286-bc6e-40ea-9cea-2846549b3dfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e79fa286-bc6e-40ea-9cea-2846549b3dfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b4c1612-fd31-4410-b834-323e531daf2b' class='xr-var-data-in' type='checkbox'><label for='data-4b4c1612-fd31-4410-b834-323e531daf2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  ,  0.  , 52.53,  0.  , 23.02, 68.83, 57.15,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 53.5 65.63 61.81</div><input id='attrs-320d9532-1283-41d4-bfbd-9aeea6e15b59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-320d9532-1283-41d4-bfbd-9aeea6e15b59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d080e1ce-3043-4496-9485-e8ad4c9daa71' class='xr-var-data-in' type='checkbox'><label for='data-d080e1ce-3043-4496-9485-e8ad4c9daa71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  ,  0.  , 52.53,  0.  , 23.02, 68.83, 57.15,\n",
        "       67.61, 54.94, 74.65, 53.76, 73.48, 61.66, 73.67, 56.12, 64.72,\n",
        "       65.88, 67.59, 49.72, 65.22, 54.34, 65.64, 50.62, 63.58, 60.39,\n",
        "       68.26, 58.79, 66.06, 56.41, 66.77, 53.5 , 65.63, 61.81],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4669a56d-c4b5-4b96-bec9-f3503c81a85f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4669a56d-c4b5-4b96-bec9-f3503c81a85f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-650076c8-e23e-4751-8cba-8cb4ab824210' class='xr-var-data-in' type='checkbox'><label for='data-650076c8-e23e-4751-8cba-8cb4ab824210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-1740b662-0412-42cd-8700-88ece894a085' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1740b662-0412-42cd-8700-88ece894a085' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af17424-9dda-4656-b924-0d4d6261e6cf' class='xr-var-data-in' type='checkbox'><label for='data-8af17424-9dda-4656-b924-0d4d6261e6cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>2583 2583 2583 ... 2583 2583 2583</div><input id='attrs-bd232f89-61fd-4b08-b886-884b1e9eddec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd232f89-61fd-4b08-b886-884b1e9eddec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d874b6e6-09ea-4331-b20d-b20a4b994fe7' class='xr-var-data-in' type='checkbox'><label for='data-d874b6e6-09ea-4331-b20d-b20a4b994fe7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Number of Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
+       "       0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>2583 2583 2583 ... 2583 2583 2583</div><input id='attrs-fabbe260-8d67-486a-8b9f-eedd4fea9dda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fabbe260-8d67-486a-8b9f-eedd4fea9dda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dae552dd-ccea-4235-be40-b9e56d3f179f' class='xr-var-data-in' type='checkbox'><label for='data-dae552dd-ccea-4235-be40-b9e56d3f179f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Number of Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
        "       2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
        "       2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
-       "       2583, 2583], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.024 0.024 0.024 ... 0.024 0.024</div><input id='attrs-72072e2c-baa1-4ae1-8d49-839c9f13580e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72072e2c-baa1-4ae1-8d49-839c9f13580e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef658323-3cc0-47ac-87cf-a987a54a5c69' class='xr-var-data-in' type='checkbox'><label for='data-ef658323-3cc0-47ac-87cf-a987a54a5c69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Distance between Samples</dd></dl></div><div class='xr-var-data'><pre>array([0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
+       "       2583, 2583], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.024 0.024 0.024 ... 0.024 0.024</div><input id='attrs-89d8af41-5816-4940-8ea4-2093ea4f5dc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89d8af41-5816-4940-8ea4-2093ea4f5dc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d54c38ff-e368-4c5b-9440-6aadf51f3fcc' class='xr-var-data-in' type='checkbox'><label for='data-d54c38ff-e368-4c5b-9440-6aadf51f3fcc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Distance between Samples</dd></dl></div><div class='xr-var-data'><pre>array([0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
        "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
        "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
        "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samp_altraw</span></div><div class='xr-var-dims'>(n_altraw, time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.98 9.539 14.62 ... 11.14 15.56</div><input id='attrs-111f42b3-668f-431d-bd58-507c396a476e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-111f42b3-668f-431d-bd58-507c396a476e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26b27615-b591-4d06-bbf0-84dc0d373766' class='xr-var-data-in' type='checkbox'><label for='data-26b27615-b591-4d06-bbf0-84dc0d373766' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([[1.39804688e+01, 9.53906250e+00, 1.46250000e+01, ...,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samp_altraw</span></div><div class='xr-var-dims'>(n_altraw, time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.98 9.539 14.62 ... 11.14 15.56</div><input id='attrs-82fe3d43-12c0-4daa-a6c3-e0e3ef07efbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82fe3d43-12c0-4daa-a6c3-e0e3ef07efbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34037a8b-b0c9-478d-a405-74e675d60a6b' class='xr-var-data-in' type='checkbox'><label for='data-34037a8b-b0c9-478d-a405-74e675d60a6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([[1.39804688e+01, 9.53906250e+00, 1.46250000e+01, ...,\n",
        "        1.00000000e+01, 1.39804688e+01, 2.00468750e+01],\n",
        "       [0.00000000e+00, 1.81328125e+01, 2.25078125e+01, ...,\n",
        "        1.71601562e+01, 1.78515625e+01, 1.39804688e+01],\n",
@@ -698,10 +807,10 @@
        "        1.81328125e+01, 1.61250000e+01, 1.39804688e+01],\n",
        "       [1.50546875e+01, 1.61250000e+01, 1.78515625e+01, ...,\n",
        "        6.99218750e+00, 1.11406250e+01, 1.55625000e+01]],\n",
-       "      shape=(2583, 35), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-a19a017f-4537-476c-81e2-5db05586ce87' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a19a017f-4537-476c-81e2-5db05586ce87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b179e896-c912-4d66-8427-42b203554fea' class='xr-var-data-in' type='checkbox'><label for='data-b179e896-c912-4d66-8427-42b203554fea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-28428c19-d5bd-4372-a913-28a77fa60127' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28428c19-d5bd-4372-a913-28a77fa60127' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-150a8de7-bd79-4c6a-9a3b-f781d4daa1c6' class='xr-var-data-in' type='checkbox'><label for='data-150a8de7-bd79-4c6a-9a3b-f781d4daa1c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-6d305b4d-d4c2-42d5-b8ac-663a59d6ef53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d305b4d-d4c2-42d5-b8ac-663a59d6ef53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-877d4613-bd9d-440b-af1b-1cb901921e6f' class='xr-var-data-in' type='checkbox'><label for='data-877d4613-bd9d-440b-af1b-1cb901921e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-3b765d2c-9f89-434c-be62-8478b3e5900f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b765d2c-9f89-434c-be62-8478b3e5900f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e90cd8f-c7af-472d-94af-e913f025c104' class='xr-var-data-in' type='checkbox'><label for='data-9e90cd8f-c7af-472d-94af-e913f025c104' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.462 0.0 -1.462 ... 0.0 0.532</div><input id='attrs-3f3f20fa-e5fc-4603-af02-b4c1b8c63b3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3f20fa-e5fc-4603-af02-b4c1b8c63b3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0e015c2-ad24-4295-bd56-b42e6d4dc508' class='xr-var-data-in' type='checkbox'><label for='data-f0e015c2-ad24-4295-bd56-b42e6d4dc508' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.4619,  0.    , -1.4619,  0.    ],\n",
+       "      shape=(2583, 35), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-3919dee3-d87a-4ca6-ac0f-a592bbda69e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3919dee3-d87a-4ca6-ac0f-a592bbda69e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d9afa24-678a-4668-9697-58c589aa8d0d' class='xr-var-data-in' type='checkbox'><label for='data-0d9afa24-678a-4668-9697-58c589aa8d0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-fff6c468-6e00-40b8-9f63-c08c9fe77e1c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fff6c468-6e00-40b8-9f63-c08c9fe77e1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-020021e3-caa6-4fdb-b5ff-05ba4ea9979b' class='xr-var-data-in' type='checkbox'><label for='data-020021e3-caa6-4fdb-b5ff-05ba4ea9979b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-885c6053-df60-4385-9cc3-d0b5be4210d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-885c6053-df60-4385-9cc3-d0b5be4210d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-815e0a47-8662-4be1-aef6-8539fe5f3a3f' class='xr-var-data-in' type='checkbox'><label for='data-815e0a47-8662-4be1-aef6-8539fe5f3a3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-518e25b3-fdc3-4b49-9bd1-332726999a40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-518e25b3-fdc3-4b49-9bd1-332726999a40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49af1221-8523-4727-bf8b-59aea1662fd0' class='xr-var-data-in' type='checkbox'><label for='data-49af1221-8523-4727-bf8b-59aea1662fd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.462 0.0 -1.462 ... 0.0 0.532</div><input id='attrs-b789b1f8-1586-4281-b942-0c78810b42f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b789b1f8-1586-4281-b942-0c78810b42f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7af9e871-451b-4ff4-b7d0-fd8898458136' class='xr-var-data-in' type='checkbox'><label for='data-7af9e871-451b-4ff4-b7d0-fd8898458136' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.4619,  0.    , -1.4619,  0.    ],\n",
        "       [ 0.    , -1.4619,  0.    ,  1.4619],\n",
        "       [ 0.532 ,  0.    ,  0.532 ,  0.    ],\n",
-       "       [ 0.    ,  0.532 ,  0.    ,  0.532 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.5221 -0.5163 ... 0.9992 0.9992</div><input id='attrs-2cf23729-32c9-485e-b9ec-d880bc87892e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cf23729-32c9-485e-b9ec-d880bc87892e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ef3281d-b14a-429d-83a8-6d4c91dce910' class='xr-var-data-in' type='checkbox'><label for='data-8ef3281d-b14a-429d-83a8-6d4c91dce910' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.52207047, -0.51634324, -0.5209149 , ..., -0.54248476,\n",
+       "       [ 0.    ,  0.532 ,  0.    ,  0.532 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.5221 -0.5163 ... 0.9992 0.9992</div><input id='attrs-0202ff75-5017-461a-b90a-9bb2aa81b995' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0202ff75-5017-461a-b90a-9bb2aa81b995' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a27930b6-a2d3-4657-a5d1-294b1f5b8883' class='xr-var-data-in' type='checkbox'><label for='data-a27930b6-a2d3-4657-a5d1-294b1f5b8883' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.52207047, -0.51634324, -0.5209149 , ..., -0.54248476,\n",
        "         -0.54013205, -0.5434986 ],\n",
        "        [-0.71620005, -0.71592724, -0.69886136, ..., -0.8391961 ,\n",
        "         -0.84069633, -0.83851576],\n",
@@ -720,65 +829,7 @@
        "        [ 0.45426297,  0.4355064 ,  0.4042198 , ...,  0.02849078,\n",
        "          0.02904635,  0.02870771],\n",
        "        [ 0.2585327 ,  0.27745417,  0.3301868 , ...,  0.9992476 ,\n",
-       "          0.99923646,  0.9992251 ]]], shape=(3, 3, 18073), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-650c496b-7f37-49e0-be28-fb2630ad357b' class='xr-section-summary-in' type='checkbox'  ><label for='section-650c496b-7f37-49e0-be28-fb2630ad357b' class='xr-section-summary' >Indexes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9e883d52-e0f6-48b3-8a5a-a9d0bd489dab' class='xr-index-data-in' type='checkbox'/><label for='index-9e883d52-e0f6-48b3-8a5a-a9d0bd489dab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-10-22 19:29:36.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:37.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:38.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:39.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:40.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:41.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:42.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:43.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:44.334399938&#x27;,\n",
-       "               &#x27;2024-10-22 19:29:45.334399938&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2024-10-23 04:10:31.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:32.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:33.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:34.334500074&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:35.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:36.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:37.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:38.334399938&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:39.334199905&#x27;,\n",
-       "               &#x27;2024-10-23 04:10:40.334399938&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=18073, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_altraw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-46d4f296-97f9-46b3-a2f5-06c419429b35' class='xr-index-data-in' type='checkbox'/><label for='index-46d4f296-97f9-46b3-a2f5-06c419429b35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-10-22 19:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 19:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 19:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 20:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 20:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 20:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 20:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 21:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 21:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 21:46:39.001100063&#x27;,\n",
-       "               &#x27;2024-10-22 21:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 22:16:39.001100063&#x27;,\n",
-       "               &#x27;2024-10-22 22:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 22:46:39.001100063&#x27;,\n",
-       "               &#x27;2024-10-22 22:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 23:16:39.001100063&#x27;,\n",
-       "               &#x27;2024-10-22 23:29:36.000900030&#x27;,\n",
-       "               &#x27;2024-10-22 23:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-22 23:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 00:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 00:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 00:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 00:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 01:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 01:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 01:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 01:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 02:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 02:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 02:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 02:59:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 03:16:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 03:29:36.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 03:46:39.000999927&#x27;,\n",
-       "               &#x27;2024-10-23 03:59:36.000999927&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_altraw&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e4fcb6f5-a6f6-407e-992e-d0c83ec17643' class='xr-index-data-in' type='checkbox'/><label for='index-e4fcb6f5-a6f6-407e-992e-d0c83ec17643' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([38.7, 42.2, 45.7, 49.2, 52.7, 56.2, 59.7, 63.2, 66.7, 70.2, 73.7, 77.2,\n",
-       "       80.7],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b0583c1e-7301-4de4-b940-5df1c71c574a' class='xr-index-data-in' type='checkbox'/><label for='index-b0583c1e-7301-4de4-b940-5df1c71c574a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-97d2bc5f-5040-4bef-accb-984b31cbe1da' class='xr-index-data-in' type='checkbox'/><label for='index-97d2bc5f-5040-4bef-accb-984b31cbe1da' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3d8b080c-dcd5-4909-88de-4e2aba2e6644' class='xr-index-data-in' type='checkbox'/><label for='index-3d8b080c-dcd5-4909-88de-4e2aba2e6644' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5fe2f197-9e3c-4a27-893b-d05d20fa45fb' class='xr-index-data-in' type='checkbox'/><label for='index-5fe2f197-9e3c-4a27-893b-d05d20fa45fb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-be361aad-4461-4a2a-acb5-e6fee66f1068' class='xr-index-data-in' type='checkbox'/><label for='index-be361aad-4461-4a2a-acb5-e6fee66f1068' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fec6f7f8-b5c7-474c-b73c-fdeb1cebf483' class='xr-index-data-in' type='checkbox'/><label for='index-fec6f7f8-b5c7-474c-b73c-fdeb1cebf483' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e5d69dd7-6678-4b81-be6e-ebbb72fb8b3c' class='xr-index-data-in' type='checkbox'/><label for='index-e5d69dd7-6678-4b81-be6e-ebbb72fb8b3c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-91509bc0-29a8-4fb5-8cb7-835ecfdb2ae4' class='xr-section-summary-in' type='checkbox'  ><label for='section-91509bc0-29a8-4fb5-8cb7-835ecfdb2ae4' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2024-10-22 19:29:32\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature250\\&quot;,SN=104922&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2215, &quot;FPGA&quot;: 186, &quot;DIGITAL&quot;: &quot;\\&quot;I-5\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-1\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;C-1(High-Power 4 Channel)\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;I-0\\&quot;&quot;, &quot;BOOT&quot;: 25, &quot;FWMINOR&quot;: 15}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=250,TTR=2.4444,TTRB5=2.0000,TTRB5AUX=0.0000,AUXRS=0&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 471.15, &quot;BURST&quot;: 384.15, &quot;AVG&quot;: 90.34, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 471.15}, &quot;MEM&quot;: {&quot;PLAN&quot;: 1.141, &quot;BURST&quot;: 0.649, &quot;AVG&quot;: 0.492, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1.141}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: 1.15, &quot;BURSTHORZ&quot;: 6.98, &quot;BEAM5&quot;: -9.99, &quot;AVGBEAM&quot;: 0.56, &quot;BURSTBEAM&quot;: 3.37}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 1, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 35.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1800, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S104922A004_PWS_SITE_02.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 250, &quot;NSTT&quot;: 0}, &quot;AVG&quot;: {&quot;NC&quot;: 39, &quot;CS&quot;: 2.0, &quot;BD&quot;: 0.5, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;AI&quot;: 120, &quot;VP&quot;: 0.0, &quot;VR&quot;: 5.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 120, &quot;NB&quot;: 4, &quot;CH&quot;: 0, &quot;MUX&quot;: 0, &quot;BW&quot;: &quot;\\&quot;BROAD\\&quot;&quot;, &quot;ALTI&quot;: 0, &quot;BT&quot;: 0, &quot;ICE&quot;: 0, &quot;ALTISTART&quot;: 0.5, &quot;ALTIEND&quot;: 150.0, &quot;RAWALTI&quot;: 1}, &quot;XFAVG&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;BURST&quot;: {&quot;NC&quot;: 13, &quot;NB&quot;: 4, &quot;CS&quot;: 3.5, &quot;BD&quot;: 35.2, &quot;CY&quot;: &quot;\\&quot;BEAM\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1024, &quot;VR&quot;: 5.0, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 1, &quot;CH&quot;: 0, &quot;ALTI&quot;: 1, &quot;VR5&quot;: 5.0, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 1, &quot;ALTISTART&quot;: 42.0, &quot;ALTIEND&quot;: 104.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;READALTIBURST&quot;: &quot;EN=1,START=42.00,END=104.00,SAMPSIZE=0.024,NB=1,NSAMP=2583,RAW=1&quot;, &quot;USER&quot;: {&quot;POFF&quot;: 9.5, &quot;DECL&quot;: 0.0, &quot;HX&quot;: 0, &quot;HY&quot;: 0, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;ON24H\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AUTOZUPDOWN\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 72, &quot;DY&quot;: 163, &quot;DZ&quot;: -42, &quot;M11&quot;: 32767, &quot;M12&quot;: 477, &quot;M13&quot;: -250, &quot;M21&quot;: -118, &quot;M22&quot;: 31551, &quot;M23&quot;: -399, &quot;M31&quot;: 838, &quot;M32&quot;: 376, &quot;M33&quot;: 32316}, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=61991026688,TC=62260248576,VS=62260248576,FF=4092,TF=4095&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=20.00,PHI=0.00,FREQ=250,BW=25,BRD=1,HWBEAM=1,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=20.00,PHI=-90.00,FREQ=250,BW=25,BRD=1,HWBEAM=2,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=20.00,PHI=180.00,FREQ=250,BW=25,BRD=1,HWBEAM=3,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=20.00,PHI=90.00,FREQ=250,BW=25,BRD=1,HWBEAM=4,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=500,BW=25,BRD=1,HWBEAM=5,ZNOM=100.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.95754e+01,P1=-6.89010e-02,P2=3.07926e-03,P3=8.38340e-05,P4=6.24624e-06,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.84575e+01,P1=-4.85768e-02,P2=3.40215e-03,P3=4.97871e-05,P4=5.28907e-06,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=2.03578e+01,P1=2.87348e-02,P2=1.24284e-03,P3=9.11659e-06,P4=9.46557e-06,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.98482e+01,P1=9.94687e-03,P2=3.95698e-03,P3=1.23846e-05,P4=5.44124e-06,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=5.14952e+00,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;639HSK16KKMKB\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;WULC7672JKMKB\\&quot;,DESC=\\&quot;Wave Mode\\&quot;,TYPE=6&quot;, &quot;KEY=\\&quot;8MTRYSYPJKMKB\\&quot;,DESC=\\&quot;64GB Recorder\\&quot;,TYPE=10&quot;], &quot;CALCOMPGET&quot;: &quot;DX=72,DY=163,DZ=-42,M11=32767,M12=477,M13=-250,M21=-118,M22=31551,M23=-399,M31=838,M32=376,M33=32316&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99836&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=-4.726771E-03,B1X=-2.648151E-04,B2X=-2.372674E-06,B3X=4.496909E-08,A1X=-1.020020E-04,A2X=1.769976E-06,A3X=-1.568007E-09&quot;, &quot;AY=1.000000E+00,B0Y=1.559532E-02,B1Y=-1.851641E-04,B2Y=-1.864571E-06,B3Y=-1.016134E-07,A1Y=-1.244390E-04,A2Y=2.423802E-06,A3Y=1.712951E-07&quot;, &quot;AZ=1.000000E+00,B0Z=-9.057428E-03,B1Z=1.972058E-04,B2Z=5.130616E-06,B3Z=-3.403830E-08,A1Z=1.938282E-04,A2Z=1.197075E-06,A3Z=-4.228993E-07&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5291115000e+02,RB0=3.7937528130e-01,RB1=-2.1489579690e-01,RB2=4.4181650000e-04,RB3=6.5130350000e-09,T0=-3.1473080000e+03,T1=2.4586100000e+00,T2=-6.5718281250e-04,T3=6.1275925000e-08,ID=\\&quot;P059353\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=1.4675400000e-01,A1=3.9377600000e-04,A2=-1.2027480470e-07,A3=1.1867438750e-11,B0=-6.2100006250e-01,B1=6.3748125000e-04,B2=-1.8018650000e-07,B3=1.6830001560e-11&quot;, &quot;C0=7.9542968750e-04,C1=-6.7488718750e-07,C2=1.9400940630e-10,C3=-1.8681940630e-14,D0=-3.0979950000e-06,D1=2.6566440630e-09,D2=-7.6620243750e-13,D3=7.3948556250e-17&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.98619,M12=0.01139,M13=0.01828,M21=-0.01080,M22=1.00513,M23=-0.00519,M31=-0.01061,M32=-0.00616,M33=0.96537&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.66,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature250</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: true, &quot;altraw&quot;: false, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>13</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>10.31</dd><dt><span>SerialNum :</span></dt><dd>104922</dd><dt><span>nominal_corr :</span></dt><dd>89</dd><dt><span>cell_size :</span></dt><dd>3.5</dd><dt><span>blank_dist :</span></dt><dd>35.2</dd><dt><span>power_level_dB :</span></dt><dd>-15.0</dd><dt><span>tilt_over_5deg :</span></dt><dd>0</dd><dt><span>tilt_over_10deg :</span></dt><dd>0</dd><dt><span>multibeam_alt :</span></dt><dd>0</dd><dt><span>n_beams_alt :</span></dt><dd>1</dd><dt><span>power_level_alt :</span></dt><dd>high</dd><dt><span>burst_config_alt :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: false, &quot;amp&quot;: false, &quot;corr&quot;: false, &quot;le&quot;: true, &quot;altraw&quot;: true, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_alt :</span></dt><dd>0</dd><dt><span>coord_sys_axes_alt :</span></dt><dd>beam</dd><dt><span>ambig_vel_alt :</span></dt><dd>0.0</dd><dt><span>SerialNum_alt :</span></dt><dd>104922</dd><dt><span>nominal_corr_alt :</span></dt><dd>0</dd><dt><span>cell_size_alt :</span></dt><dd>0.0</dd><dt><span>blank_dist_alt :</span></dt><dd>42.0</dd><dt><span>power_level_dB_alt :</span></dt><dd>-26.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>up</dd><dt><span>orient_status :</span></dt><dd>auto_UD</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;mag&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>beam</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>bandwidth :</span></dt><dd>&quot;BROAD&quot;</dd><dt><span>has_imu :</span></dt><dd>0</dd><dt><span>beam_angle :</span></dt><dd>20</dd></dl></div></li></ul></div></div>"
+       "          0.99923646,  0.9992251 ]]], shape=(3, 3, 18073), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1e88c7a9-62f2-483c-8b78-5aea96a214dd' class='xr-section-summary-in' type='checkbox'  ><label for='section-1e88c7a9-62f2-483c-8b78-5aea96a214dd' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2024-10-22 19:29:32\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature250\\&quot;,SN=104922&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2215, &quot;FPGA&quot;: 186, &quot;DIGITAL&quot;: &quot;\\&quot;I-5\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-1\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;C-1(High-Power 4 Channel)\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;I-0\\&quot;&quot;, &quot;BOOT&quot;: 25, &quot;FWMINOR&quot;: 15}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=250,TTR=2.4444,TTRB5=2.0000,TTRB5AUX=0.0000,AUXRS=0&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 471.15, &quot;BURST&quot;: 384.15, &quot;AVG&quot;: 90.34, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 471.15}, &quot;MEM&quot;: {&quot;PLAN&quot;: 1.141, &quot;BURST&quot;: 0.649, &quot;AVG&quot;: 0.492, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1.141}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: 1.15, &quot;BURSTHORZ&quot;: 6.98, &quot;BEAM5&quot;: -9.99, &quot;AVGBEAM&quot;: 0.56, &quot;BURSTBEAM&quot;: 3.37}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 1, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 35.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1800, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S104922A004_PWS_SITE_02.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 250, &quot;NSTT&quot;: 0}, &quot;AVG&quot;: {&quot;NC&quot;: 39, &quot;CS&quot;: 2.0, &quot;BD&quot;: 0.5, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;AI&quot;: 120, &quot;VP&quot;: 0.0, &quot;VR&quot;: 5.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 120, &quot;NB&quot;: 4, &quot;CH&quot;: 0, &quot;MUX&quot;: 0, &quot;BW&quot;: &quot;\\&quot;BROAD\\&quot;&quot;, &quot;ALTI&quot;: 0, &quot;BT&quot;: 0, &quot;ICE&quot;: 0, &quot;ALTISTART&quot;: 0.5, &quot;ALTIEND&quot;: 150.0, &quot;RAWALTI&quot;: 1}, &quot;XFAVG&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;BURST&quot;: {&quot;NC&quot;: 13, &quot;NB&quot;: 4, &quot;CS&quot;: 3.5, &quot;BD&quot;: 35.2, &quot;CY&quot;: &quot;\\&quot;BEAM\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1024, &quot;VR&quot;: 5.0, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 1, &quot;CH&quot;: 0, &quot;ALTI&quot;: 1, &quot;VR5&quot;: 5.0, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 1, &quot;ALTISTART&quot;: 42.0, &quot;ALTIEND&quot;: 104.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;READALTIBURST&quot;: &quot;EN=1,START=42.00,END=104.00,SAMPSIZE=0.024,NB=1,NSAMP=2583,RAW=1&quot;, &quot;USER&quot;: {&quot;POFF&quot;: 9.5, &quot;DECL&quot;: 0.0, &quot;HX&quot;: 0, &quot;HY&quot;: 0, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;ON24H\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AUTOZUPDOWN\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 72, &quot;DY&quot;: 163, &quot;DZ&quot;: -42, &quot;M11&quot;: 32767, &quot;M12&quot;: 477, &quot;M13&quot;: -250, &quot;M21&quot;: -118, &quot;M22&quot;: 31551, &quot;M23&quot;: -399, &quot;M31&quot;: 838, &quot;M32&quot;: 376, &quot;M33&quot;: 32316}, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=61991026688,TC=62260248576,VS=62260248576,FF=4092,TF=4095&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=20.00,PHI=0.00,FREQ=250,BW=25,BRD=1,HWBEAM=1,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=20.00,PHI=-90.00,FREQ=250,BW=25,BRD=1,HWBEAM=2,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=20.00,PHI=180.00,FREQ=250,BW=25,BRD=1,HWBEAM=3,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=20.00,PHI=90.00,FREQ=250,BW=25,BRD=1,HWBEAM=4,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=500,BW=25,BRD=1,HWBEAM=5,ZNOM=100.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.95754e+01,P1=-6.89010e-02,P2=3.07926e-03,P3=8.38340e-05,P4=6.24624e-06,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.84575e+01,P1=-4.85768e-02,P2=3.40215e-03,P3=4.97871e-05,P4=5.28907e-06,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=2.03578e+01,P1=2.87348e-02,P2=1.24284e-03,P3=9.11659e-06,P4=9.46557e-06,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.98482e+01,P1=9.94687e-03,P2=3.95698e-03,P3=1.23846e-05,P4=5.44124e-06,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=5.14952e+00,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;639HSK16KKMKB\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;WULC7672JKMKB\\&quot;,DESC=\\&quot;Wave Mode\\&quot;,TYPE=6&quot;, &quot;KEY=\\&quot;8MTRYSYPJKMKB\\&quot;,DESC=\\&quot;64GB Recorder\\&quot;,TYPE=10&quot;], &quot;CALCOMPGET&quot;: &quot;DX=72,DY=163,DZ=-42,M11=32767,M12=477,M13=-250,M21=-118,M22=31551,M23=-399,M31=838,M32=376,M33=32316&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99836&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=-4.726771E-03,B1X=-2.648151E-04,B2X=-2.372674E-06,B3X=4.496909E-08,A1X=-1.020020E-04,A2X=1.769976E-06,A3X=-1.568007E-09&quot;, &quot;AY=1.000000E+00,B0Y=1.559532E-02,B1Y=-1.851641E-04,B2Y=-1.864571E-06,B3Y=-1.016134E-07,A1Y=-1.244390E-04,A2Y=2.423802E-06,A3Y=1.712951E-07&quot;, &quot;AZ=1.000000E+00,B0Z=-9.057428E-03,B1Z=1.972058E-04,B2Z=5.130616E-06,B3Z=-3.403830E-08,A1Z=1.938282E-04,A2Z=1.197075E-06,A3Z=-4.228993E-07&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5291115000e+02,RB0=3.7937528130e-01,RB1=-2.1489579690e-01,RB2=4.4181650000e-04,RB3=6.5130350000e-09,T0=-3.1473080000e+03,T1=2.4586100000e+00,T2=-6.5718281250e-04,T3=6.1275925000e-08,ID=\\&quot;P059353\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=1.4675400000e-01,A1=3.9377600000e-04,A2=-1.2027480470e-07,A3=1.1867438750e-11,B0=-6.2100006250e-01,B1=6.3748125000e-04,B2=-1.8018650000e-07,B3=1.6830001560e-11&quot;, &quot;C0=7.9542968750e-04,C1=-6.7488718750e-07,C2=1.9400940630e-10,C3=-1.8681940630e-14,D0=-3.0979950000e-06,D1=2.6566440630e-09,D2=-7.6620243750e-13,D3=7.3948556250e-17&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.98619,M12=0.01139,M13=0.01828,M21=-0.01080,M22=1.00513,M23=-0.00519,M31=-0.01061,M32=-0.00616,M33=0.96537&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.66,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature250</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: true, &quot;altraw&quot;: false, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>13</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>10.31</dd><dt><span>SerialNum :</span></dt><dd>104922</dd><dt><span>nominal_corr :</span></dt><dd>89</dd><dt><span>cell_size :</span></dt><dd>3.5</dd><dt><span>blank_dist :</span></dt><dd>35.2</dd><dt><span>power_level_dB :</span></dt><dd>-15.0</dd><dt><span>tilt_over_5deg :</span></dt><dd>0</dd><dt><span>tilt_over_10deg :</span></dt><dd>0</dd><dt><span>multibeam_alt :</span></dt><dd>0</dd><dt><span>n_beams_alt :</span></dt><dd>1</dd><dt><span>power_level_alt :</span></dt><dd>high</dd><dt><span>burst_config_alt :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: false, &quot;amp&quot;: false, &quot;corr&quot;: false, &quot;le&quot;: true, &quot;altraw&quot;: true, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_alt :</span></dt><dd>0</dd><dt><span>coord_sys_axes_alt :</span></dt><dd>beam</dd><dt><span>ambig_vel_alt :</span></dt><dd>0.0</dd><dt><span>SerialNum_alt :</span></dt><dd>104922</dd><dt><span>nominal_corr_alt :</span></dt><dd>0</dd><dt><span>cell_size_alt :</span></dt><dd>0.0</dd><dt><span>blank_dist_alt :</span></dt><dd>42.0</dd><dt><span>power_level_dB_alt :</span></dt><dd>-26.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>up</dd><dt><span>orient_status :</span></dt><dd>auto_UD</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;mag&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>beam</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>bandwidth :</span></dt><dd>&quot;BROAD&quot;</dd><dt><span>has_imu :</span></dt><dd>0</dd><dt><span>beam_angle :</span></dt><dd>20</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 11MB\n",
@@ -857,7 +908,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x20f3d5e2f90>"
+       "<matplotlib.legend.Legend at 0x1d8048e60d0>"
       ]
      },
      "execution_count": 4,
@@ -1012,7 +1063,9 @@
     "\n",
     "We'll start wave processing by first spinning up DOLfYN's binning tools to compute wave height and period. A comprehensive overview of wave measurement and analysis can be found [here](https://essopenarchive.org/doi/full/10.22541/essoar.175130482.28547248).\n",
     "\n",
-    "Wave stats are typically computing windows of 30 minutes to an hour. Shorter windows can be used but they have lower statistical certainty. We'll use a bin size equal to 30 minutes of data, and an FFT length of half the bin size.\n",
+    "Wave stats are typically computing windows of 30 minutes to an hour. Shorter windows can be used but they have lower statistical certainty. \n",
+    "\n",
+    "In this case, the instrument was running on a duty cycle, with 600 samples measured at 1 Hz (10 minutes). Therefore, we'll use 600 datapoints in each binning window. Additionally, because we're on a duty cycle, we will create one PSD from each set of samples; so, to avoid jumping duty cycle bins, we'll set the FFT overlap to 0%. If we were sampling continuously, we'd use an FFT overlap of 50%.\n",
     "\n",
     "Now, we can calculate the energy spectrum for the surface using `power_spectral_density`."
    ]
@@ -1024,13 +1077,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "window = 20*60\n",
+    "n_duty_cycle = 600\n",
+    "pct_overlap = 0\n",
     "fft_tool = dolfyn.VelBinner(\n",
-    "        n_bin=window * ds_waves.fs, fs=ds_waves.fs, n_fft=ds_waves.fs * window // 2\n",
+    "        n_bin=n_duty_cycle, fs=ds_waves.fs, n_fft=n_duty_cycle\n",
     "    )\n",
     "\n",
-    "Szz_ast = fft_tool.power_spectral_density(ds_waves[\"ast_dist_alt\"], freq_units=\"Hz\")\n",
-    "Szz_le = fft_tool.power_spectral_density(ds_waves[\"le_dist_alt\"], freq_units=\"Hz\")"
+    "Szz_ast = fft_tool.power_spectral_density(ds_waves[\"ast_dist_alt\"], freq_units=\"Hz\", pct_overlap=pct_overlap)\n",
+    "Szz_le = fft_tool.power_spectral_density(ds_waves[\"le_dist_alt\"], freq_units=\"Hz\", pct_overlap=pct_overlap)"
    ]
   },
   {
@@ -1074,7 +1128,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x20f3fef6a90>"
+       "<matplotlib.legend.Legend at 0x1d804f6e0d0>"
       ]
      },
      "execution_count": 10,
@@ -1083,7 +1137,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1100x500 with 2 Axes>"
       ]
@@ -1094,11 +1148,11 @@
    ],
    "source": [
     "fig, ax = plt.subplots(1, 2, figsize=(11, 5))\n",
-    "ax[0].loglog(Szz_ast[\"freq\"], Szz_ast.mean(\"time\"), label=\"Altimeter AST\")\n",
-    "ax[0].loglog(Szz_le[\"freq\"], Szz_le.mean(\"time\"), label=\"Altimeter LE\")\n",
+    "ax[0].loglog(Szz_ast[\"freq\"], Szz_ast.median(\"time_psd\"), label=\"Altimeter AST\")\n",
+    "ax[0].loglog(Szz_le[\"freq\"], Szz_le.median(\"time_psd\"), label=\"Altimeter LE\")\n",
     "ax[0].set(xlabel=\"Frequency [Hz]\", ylabel=\"Energy Density [m$^2$/Hz]\", title =\"Full frequency range\", xlim=(5e-3, 0.5), ylim=(5e-3, 5))\n",
-    "ax[1].loglog(Szz_ast[\"freq\"].sel(freq=slc_freq), Szz_ast.sel(freq=slc_freq).mean(\"time\"), label=\"Altimeter AST\")\n",
-    "ax[1].loglog(Szz_le[\"freq\"].sel(freq=slc_freq), Szz_le.sel(freq=slc_freq).mean(\"time\"), label=\"Altimeter LE\")\n",
+    "ax[1].loglog(Szz_ast[\"freq\"].sel(freq=slc_freq), Szz_ast.sel(freq=slc_freq).median(\"time_psd\"), label=\"Altimeter AST\")\n",
+    "ax[1].loglog(Szz_le[\"freq\"].sel(freq=slc_freq), Szz_le.sel(freq=slc_freq).median(\"time_psd\"), label=\"Altimeter LE\")\n",
     "ax[1].set(xlabel=\"Frequency [Hz]\", title=\"Frequency limits of 1/22 to 1/3 Hz\", xlim=(5e-3, 0.5), ylim=(5e-3, 5))\n",
     "ax[1].legend()"
    ]
@@ -1156,23 +1210,15 @@
     "# Create averaged dataset\n",
     "ds_waves_avg = fft_tool.bin_average(ds_waves)\n",
     "# Convert wave parameters to xarray and add to averaged dataset\n",
-    "ds_waves_avg[\"wave_height_ast\"] = Hs_ast.to_xarray().astype(\"float32\")\n",
-    "ds_waves_avg[\"mean_period_ast\"] = Tm_ast.to_xarray().astype(\"float32\")\n",
-    "ds_waves_avg[\"peak_period_ast\"] = Tp_ast.to_xarray().astype(\"float32\")\n",
+    "ds_waves_avg[\"wave_height_ast\"] = Hs_ast.to_xarray()\n",
+    "ds_waves_avg[\"mean_period_ast\"] = Tm_ast.to_xarray()\n",
+    "ds_waves_avg[\"peak_period_ast\"] = Tp_ast.to_xarray()\n",
     "\n",
-    "ds_waves_avg[\"wave_height_le\"] = Hs_le.to_xarray().astype(\"float32\")\n",
-    "ds_waves_avg[\"mean_period_le\"] = Tm_le.to_xarray().astype(\"float32\")\n",
-    "ds_waves_avg[\"peak_period_le\"] = Tp_le.to_xarray().astype(\"float32\")\n"
+    "ds_waves_avg[\"wave_height_le\"] = Hs_le.to_xarray()\n",
+    "ds_waves_avg[\"mean_period_le\"] = Tm_le.to_xarray()\n",
+    "ds_waves_avg[\"peak_period_le\"] = Tp_le.to_xarray()\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "af09e51b",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
    "id": "f86c69d7",
@@ -1190,7 +1236,7 @@
     {
      "data": {
       "text/plain": [
-       "[Text(0, 0.5, 'Peak Period [s]'), Text(0.5, 0, 'Time')]"
+       "[(0.0, 15.0), Text(0, 0.5, 'Peak Period [s]'), Text(0.5, 0, 'Time')]"
       ]
      },
      "execution_count": 13,
@@ -1199,7 +1245,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x700 with 3 Axes>"
       ]
@@ -1211,48 +1257,48 @@
    "source": [
     "fig, ax = plt.subplots(3, 1, figsize=(10, 7), constrained_layout=True)\n",
     "ax[0].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"wave_height_ast\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter AST\",\n",
     ")\n",
     "ax[0].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"wave_height_le\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter LE\",\n",
     ")\n",
     "ax[0].legend()\n",
-    "ax[0].set(ylabel=\"Significant Wave Height [m]\")\n",
+    "ax[0].set(ylim=(0,5), ylabel=\"Significant Wave Height [m]\")\n",
     "\n",
     "ax[1].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"mean_period_ast\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter AST\",\n",
     ")\n",
     "ax[1].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"mean_period_le\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter LE\",\n",
     ")\n",
     "ax[1].legend()\n",
-    "ax[1].set(ylabel=\"Mean Period [s]\")\n",
+    "ax[1].set(ylim=(0, 15), ylabel=\"Mean Period [s]\")\n",
     "ax[2].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"peak_period_ast\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter AST\",\n",
     ")\n",
     "ax[2].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"peak_period_le\"],\n",
     "    \".-\",\n",
     "    label=\"Altimeter LE\",\n",
     ")\n",
     "ax[2].legend()\n",
-    "ax[2].set(ylabel=\"Peak Period [s]\", xlabel=\"Time\")\n"
+    "ax[2].set(ylim=(0, 15), ylabel=\"Peak Period [s]\", xlabel=\"Time\")\n"
    ]
   },
   {
@@ -1269,7 +1315,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 14,
    "id": "c477be85",
    "metadata": {},
    "outputs": [
@@ -1277,15 +1323,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Data is already in the earth coordinate system\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\adp\\clean.py:90: UserWarning: The 'range_offset' is either already known or can be calculated from 'bin1_dist_m': 0.5 m. If you would like to override this value with 0.5 m, ignore this warning. If you do not want to override this value, you do not need to use this function.\n",
-      "  warnings.warn(\n"
+      "Data is already in the beam coordinate system\n",
+      "Data is already in the beam coordinate system\n"
      ]
     }
    ],
@@ -1318,9 +1357,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_5016\\212097317.py:10: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
+      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_13508\\212097317.py:10: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
       "  fig.colorbar(h1, ax=ax[0], label=label, fraction=0.05, pad=0.02)\n",
-      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_5016\\212097317.py:21: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
+      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_13508\\212097317.py:21: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
       "  fig.colorbar(h2, ax=ax[1], label=label, fraction=0.05, pad=0.02)\n"
      ]
     },
@@ -1384,7 +1423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "317a1faa",
    "metadata": {},
    "outputs": [],
@@ -1393,7 +1432,7 @@
     "\n",
     "## \"SUV\" method - AST, u velocity, v velocity\n",
     "fft_tool = dolfyn.adv.api.ADVBinner(\n",
-    "    n_bin=window * ds_waves.fs, fs=ds_waves.fs, n_fft=ds_waves.fs * window // 2\n",
+    "    n_bin=n_duty_cycle * ds_waves.fs, fs=ds_waves.fs, n_fft=n_duty_cycle\n",
     ")\n",
     "# Create 2D tensor for spectral analysis\n",
     "disp = xr.DataArray(\n",
@@ -1406,15 +1445,20 @@
     "    ),\n",
     "    coords={\"dir\": [\"u\", \"v\", \"z\"], \"time\": ds_waves[\"time\"]},\n",
     ")\n",
+    "\n",
+    "# fill NaN values with mean to not affect statistics\n",
+    "disp = dolfyn.adv.clean.fill_nan_ensemble_mean(\n",
+    "    disp, disp.isnull(), int(ds_waves.fs), window=n_duty_cycle\n",
+    ")\n",
     "# Auto-spectra\n",
-    "psd = fft_tool.power_spectral_density(disp, freq_units=\"Hz\")\n",
+    "psd = fft_tool.power_spectral_density(disp, freq_units=\"Hz\", pct_overlap=pct_overlap)\n",
     "psd = psd.sel(freq=slc_freq)\n",
     "Sxx = psd.sel(S=\"Sxx\")\n",
     "Syy = psd.sel(S=\"Syy\")\n",
     "Szz = psd.sel(S=\"Szz\")\n",
     "\n",
     "# Cross-spectra\n",
-    "csd = fft_tool.cross_spectral_density(disp, freq_units=\"Hz\")\n",
+    "csd = fft_tool.cross_spectral_density(disp, freq_units=\"Hz\", pct_overlap=pct_overlap)\n",
     "csd = csd.sel(coh_freq=slc_freq)\n",
     "Cxz = csd.sel(C=\"Cxz\").real\n",
     "Cxy = csd.sel(C=\"Cxy\").real\n",
@@ -1449,7 +1493,7 @@
    "id": "7b9ee95d",
    "metadata": {},
    "source": [
-    "And plot. Some datapoints may be missing for velocity data that was quality controlled out, but we can see that the highest energy waves are coming from -80 degees (10 degrees north of due West), with a spread of approximately 20 degrees."
+    "And plot. Some datapoints may be missing for velocity data that was quality controlled out, but we can see that the highest energy waves are coming from -80 degees (10 degrees north of due West), with a spread of approximately 10-20 degrees."
    ]
   },
   {
@@ -1461,7 +1505,7 @@
     {
      "data": {
       "text/plain": [
-       "[Text(0, 0.5, 'Peak Wave Spread [deg]')]"
+       "[(0.0, 90.0), Text(0, 0.5, 'Peak Wave Spread [deg]')]"
       ]
      },
      "execution_count": 17,
@@ -1470,7 +1514,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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WrVqp58jLy9OgQYM0c+ZMNWvWrMx+CGfDBHgAAAAAgJKU+Trz06dPl7u7u6Kjo1W7du0i97300kvq1auXPvjgA73wwgulnsPT01M7d+60aaI8AAAAAABQMpu72f/yyy964YUXigV5SQoJCdHEiRP1888/X/Q8I0eO1OzZs+2rEgAAAAAAWNncMh8TE6OePXuWen/Pnj319NNPX/Q8ubm5+uyzz7R06VJ17txZ/v7+Re6/2Dr1AAAAAABUdTaH+dTUVFWvXr3U+6tXr67U1NSLnmfnzp3q2LGjpIILBIXR/R4AAAAAgIuzOcwbhiE3t9J75ZtMJpU2l9727dvVpk0bubm5XfY69QAAAAAAVHV2hflmzZqV2np+oUnxO3TooPj4eIWEhKhRo0basGGD3evTAwAAAACAAjaH+Tlz5lzyg1SvXl2xsbEKCQnRoUOHZLFYLvlcAAAAAABUdTaH+VGjRl3yg9x+++3q27ev6tSpI5PJpM6dO8vd3b3EfQ8ePHjJjwMAAAAAQFVgc5i/HLNmzdJtt92m/fv3a9y4cXrwwQcVEBBQEQ8NAAAAAIDLqZAwL0mDBw+WJG3atElPPPEEYR4AAAAAgEtU+vT05WTOnDkuEeQ/+ugjRUZGysfHR506ddLKlSsdXRIAAAAAoIqo8DDvChYtWqTx48frxRdf1JYtW3TllVfq2muvVVxcnKNLAwAAAABUASbjQmvKXUBubq5iY2PVuHFjeXhUWG/9SqFbt27q2LGjPv74Y+u2li1b6pZbbtGUKVMuenxqaqqCgoKUkpKiwMDA8iwVAAAAAOBEbM2LdrfMZ2ZmavTo0fLz81Pr1q2trdHjxo3T1KlTL71iJ5Gbm6tNmzZp0KBBRbYPGjRIq1evLvGYnJwcpaamFrkBAAAAAHCp7A7zEydO1LZt27RixQr5+PhYtw8cOFCLFi0q9bjMzMxLq7CSSUpKktlsVmhoaJHtoaGhSkhIKPGYKVOmKCgoyHqLiIioiFIBAAAAAC7K7jD/ww8/aMaMGerdu7dMJpN1e6tWrXTgwIFSj6tevbquvPJKvfLKK1q+fLlycnIureJKovDPLkmGYRTbds7EiROVkpJivR05cqQiSgQAAAAAuCi7w/zJkycVEhJSbHtGRkapYVaSZs+erebNm2v+/Pm66qqrFBwcrAEDBuiNN97QqlWrlJeXZ28pDlGrVi25u7sXa4VPTEws1lp/jre3twIDA4vcAAAAAAC4VHaH+S5duuiXX36xfn8uwH/66afq0aNHqceNGDFCn332mfbv36+4uDh98sknioyM1Jw5c9S3b18FBwfrmmuuuYQfoWJ5eXmpU6dOWrp0aZHtS5cuVc+ePR1UFQAAAACgKrF7GvopU6Zo8ODB2rVrl/Lz8zV9+nRFR0drzZo1ioqKsukc9erV08iRIzVy5Ejt27dPX3zxhT744AP98ccfdv8AjjBhwgSNGDFCnTt3Vo8ePTRr1izFxcVp7Nixji4NAAAAAFAF2B3me/bsqb///ltvv/22GjdurCVLlqhjx45as2aN2rZte9HjDx48qOXLl2vFihVasWKFUlJS1LNnTz333HPq27fvJf0QFW3IkCE6deqU/vWvfyk+Pl5t2rTRr7/+qgYNGji6NAAAAABAFXDJ68zba9SoUVq+fLnS0tLUq1cv9enTR3379lXnzp3l7u5eESVUGqwzDwAAAAAoia150e6W+f79++uee+7RHXfcoaCgIJuP+/LLL1W/fn298MILuuqqq9ShQ4cLTpgHAAAAAABKZvcEeG3bttVLL72ksLAw3X777frhhx+Um5t70eN27dql559/Xps2bdL111+vGjVq6MYbb9Tbb7+tjRs3ymKxXNIPAAAAAABAVXNJ3ewtFov++OMPzZ8/X4sXL5a7u7vuuOMODR8+3OZx77t27VJUVJSWL1+ulStXKisrS71799b//d//2f1DOBu62QMAAAAASmJrXrzsMfPZ2dn6+eefNWnSJO3YsUNms9nmYxMSErRixQotX75cCxcuVHp6ul3HOyvCPAAAAACgJOU2Zr6whIQELVy4UF999ZW2b9+uLl26XHD/xMREa3hfsWKFYmJi5OXlpa5du+rJJ59U//79L6ccAAAAAACqBLvDfGpqqr777jvNnz9fK1asUKNGjTRs2DAtXLhQTZo0KfW4Vq1aae/evfLw8FCXLl10++23q3///urVq5d8fHwu64cAAAAAAKAqsTvMh4aGKjg4WHfddZcmT5580db4c26++Wb1799fvXv3lp+fn92FAgAAAACAAnaPmV+yZIkGDhwoNze7J8JXamqqqlWrVuxYs9msjIyMKjN+nDHzAAAAAICS2JoX7U7kgwYNuqQgv3jxYnXu3FnZ2dnF7svJyVGXLl30888/231eAAAAAACqmkuaAO/bb7/VN998o7i4uGJrzG/evLnEYz766CM9++yzJXax9/Pz03PPPacZM2boxhtvvJSSAAAAAACoMuxuYv/ggw903333KSQkRFu2bFHXrl1Vs2ZNHTx4UNdee22px0VHR6tfv36l3t+nTx/t2LHD3nIAAAAAAKhy7A7zH330kWbNmqUZM2bIy8tLzz77rJYuXapx48YpJSWl1OPOnDmj/Pz8Uu/Py8vTmTNn7C0HAAAAAIAqx+4wHxcXp549e0qSfH19lZaWJkkaMWKEFixYUOpxDRs21MaNG0u9f+PGjWrQoIG95QAAAAAAUOXYHebDwsJ06tQpSVKDBg20du1aSVJsbKwuNDH+bbfdphdffFEnTpwodl9CQoJeeukl3X777faWAwAAAABAlWP3BHgDBgzQzz//rI4dO2r06NF68skn9e2332rjxo267bbbSj3u+eef148//qimTZvqnnvuUfPmzWUymbR79259/fXXioiI0PPPP39ZPwwAAAAAAFWB3evMWywWWSwWeXgUXAf45ptvtGrVKjVp0kRjx46Vl5dXqcempKRo4sSJWrRokXV8fHBwsIYMGaLJkyerevXql/6TOBHWmQcAAAAAlMTWvGhzmO/du7cGDBig/v37q0ePHvLx8bnk4gzDUFJSkgzDUO3atWUymS75XM6IMA8AAAAAKImtedHmMfPNmzfX/PnzddVVVyk4OFj9+vXTv/71L61atUp5eXl2FWcymVS7dm2FhIRUuSAPAAAAAMDlsrub/dGjR7Vs2TJFRUVpxYoVio2Nla+vr3r27KkBAwZo4sSJ5VWry6BlHgAAAABQkjLvZl+aI0eOaObMmfrwww+Vnp4us9l8OaerEgjzAAAAAICS2JoX7Z7NXpIOHDigFStWWG/Jycnq0aOH+vbte8kFAwAAAAAA29gc5ufMmaPly5drxYoVSklJUa9evdS3b189+uij6ty5s3V2ewAAAKCqiU/JUmxShiJr+atOkK+jywFQBdicwEePHq369evrxRdf1P333y9PT89LesAPPvigxO0mk0k+Pj5q0qSJ+vTpI3d390s6PwAAAFCRFm2I08Tvd8hiSG4macptbTWkS31HlwXAxdk8Zv7jjz9WVFSUoqKilJ2drd69e6tfv37q27evOnXqZPOs9JGRkTp58qQyMzMVHBwswzCUnJwsPz8/VatWTYmJiWrUqJGWL1+uiIiIy/rhKivGzAMAALiG+JQs9Zy6TIU/UbubTFr1fH9a6AFckjJfmu7hhx/WwoULFR8fr7///lvXXXed1q9frxtuuEHBwcG6/vrr9fbbb1/0PJMnT1aXLl20b98+nTp1SqdPn1ZMTIy6deum6dOnKy4uTmFhYXryySdtLQ0AAACocAdOpuuJBVt0ftOY2TAUezLDMUUBqDIuezb748eP66OPPrJ5NvvGjRvru+++U/v27Yts37Jli26//XYdPHhQq1ev1u233674+PjLKa3SomUeAADAeSWmZuv9P/dp0YYjMltK/ijdJKSaXriuhfo3D7G5BysASOU4m/2JEyeKzGQfExMjLy8vdevWTf3797/o8fHx8crPzy+2PT8/XwkJCZKk8PBwpaWl2VsaAAAAUG5Ss/M0M+qAZq+KVXaeRZI0sGWo2tYL1Ad/7JfZMGSS5OXhpv2J6bp/7kZ1aRisZ65poa6RNRxbPACXY3OYf/TRR7V8+XLt3btXHh4e6tKli+644w71799fPXv2lI+Pj03n6d+/v8aMGaPPPvtMHTp0kFTQKv/www9rwIABkqQdO3YoMjLyEn4cAAAAoGzl5Jv15ZrD+s/y/TqTmSdJ6tQgWM9f20JdGhaE9Ls6R+hQUqYa1vKTj4e7Pok6oLmrD2nDoTO6a+Ya9WteW89c01ytw4Mc+aMAcCE2d7Pv0aOH+vfvr/79+6tXr17y8/O7pAdMSEjQiBEj9Oeff1pnxM/Pz9dVV12lL7/8UqGhoVq+fLny8vI0aNCgS3qMyo5u9gAAAJWf2WLox63H9M6SGB1LzpJU0H3+2Wua6+pWoRftPp+Qkq0PlhXtjn/DFXX01KDmiqzlX+71A3BOtubFyx4zf6n27NmjmJgYGYahFi1aqHnz5o4owyEI8wAAAJWXYRhaEXNSb/1vj/YkFAz9DAv00ZNXN9XtHevJw93mOaQlSbFJGXpvaYx+2nZckuTuZtJdnetp3FVNmfHeCcSnZCk2KUORtfx5vlAhKn2Yz83NVWxsrBo3biwPD7uH7js1wjwAAEDltPVIsqb+b7fWHjwtSQrw8dAj/Zro3p4N5evlflnn3nU8VW8v2atlexIlFYytH9WjgR7u10Q1/L0uu3aUvUUb4jTx+x2yGJKbSZpyW1sN6VLf0WXBxVXaMJ+ZmanHH39c8+bNkyTFxMSoUaNGGjdunMLDw/X8889XZDkOQZgHAACoXA6cTNfbv+/V/3YWTMjs5eGme3s21CP9Gqu6X9kG7Q2HTuvfv+3V+kMFFwyqeXvowSsbafSVkarmXbUauSqrhJRs/bDlmKb+tqfYfU1CqqlOkI9q+nupVjVv1azmrZrVvFSrWqHv/b3k43l5F39QdVXaMP/EE0/o77//1vvvv6/Bgwdr+/btatSokX766Se9+uqr2rJlS0WW4xCEeQAAcCF066045y8zZzJJt3espyevbqa61cvvd3+uK/+/f9urXfGpkqQa/l56tH8TDe9WnyBYwSwWQ9uPpWjZ7hP6c0+ioo+nXvY5q3l7qFY1L2u4r1nNW7XPfX82+Neq5qWa/t4K8vWUm5vtSxjyHuHaHBLmDcO46EQgDRo00KJFi9S9e3cFBARo27ZtatSokfbv36+OHTsqNfXy/+NUdoR5AABQGrr1VozU7DzNijqo2atilZVnliQNbBmiZ65poeZhARVWh8Vi6Jcd8Xp3aYxikzIkSeFBPho/sJlu61jX7vH5sF1adp5W7UvSn3sStWJvopLSc633mUxS6zqBij6eqsJhyc0kvXNXexmGoVPpuUpKz1FSeq5OZeRYvz+Vnqtcs8WuWjzcTKpxNvAXBPzSW/2X70nUKz/u5D3ChZXbOvNTpkzRxIkTi203m8265557tGDBggsef/LkSYWEhBTbnpGRcdELAQAAVCa0jKAsZOeZte9EuvYkpGrz4TNasOGI9T6LIT3//Q41qu2vzg1q8FmpDOTkm/XV2jjNWLbPusxcx/rV9fy1LR2yFrybm0k3tgvX4DZh+nbTUU3/Y5+Op2Tr2e+265O/DujpQc11bZswnvsyEpuUoWV7ErVszwmtjz2tPPM/UT3A20N9mtXWgBYh6te8tmpW89aiDXF64fudMhuG3E0mTb6tjW7tUPeCj2EYhtJy8guF+4LAfy7on8oo+n1KVp7yLYYS03KUmJZj189jMaTnv9shT3c39WpSSyEB3rxWqhC7W+ZDQ0P1xhtv6KGHHrJuM5vNuvvuu7Vz507t3r37gsf37dtXd9xxhx5//HEFBARo+/btioyM1GOPPab9+/frt99+u7SfxInQMn9hfDgG4Ay+XntYL9MyAjtYLIbiTmdqT0Ka9iakae+JVO2JT9OhUxmy2PBpLCzQR90a1VC3yJrq1qiGGtXy50O7HUpaZq5xbX89O7iFBtmwzFxFyc4rWNP+oxX/rGnftm6Qnrmmua5sWqvS1OkscvMt2njo9NkAn6iDZ3s/nNOolr8GtAjRgJYh6tKwhjxL6AkRn5KlQ0mZaljLr1w+m+bmW3QmM1cn03J0KiNXp9JzirX6nwv+J9NylH+BN4zqfp5qERagFmGBBf/WCVSz0Gry82IuBmdSbt3sN23apIEDB2rmzJm66667lJeXpyFDhmjPnj1atmyZwsLCLnj86tWrNXjwYA0fPlxz587VmDFjFB0drTVr1igqKkqdOnWypxynRJgvHV0LAVRWZzJytenwGW2KO6M1B05p65HkYvvc17OhOjesoeZhAWpY06/Kd4+tyhdnT6XnaG9CmjW47zmRppiENGt37vMF+3mqRVig6gX76ttNR3X+hzMPNyn/vF67tQO81TWyhrpH1lC3RjXVpHY1u8bcVhUlLTMXGuitJwc20x2d7F9mrqKkZefp05Wxmr3yoDJyC1433RvV0LODW6hj/WAHV1e5JaXnaMXek1q+J1F/xZxUWk6+9T4PN5O6NaqhAS1CNaBFiCJr+TuwUvsdT85U77eWF7kAaJLUoKafjpzJkrmEoG8ySQ1q+KlFWKCahwWoZZ2CsF+/hh/vGZVUuY6ZX7FihW6++WZ98cUXmj17tg4cOKBly5YpNDTUpuN37Niht99+W5s2bZLFYlHHjh313HPPqW3btvaW4pQI8yWLT8lSr6nLirw5uZmkv58fUOU+BML1VeWQ4wwsFkMHk9K16fAZbTxUEOAPnsy4+IGFeHu4qWloNTUPLWgdaR4WoBZhAapdRbpAzl55UG/+uluGUfBB887O9TSgRaj8vNzl7+0uPy8P+Xt5yM/bXf5eHvLxdHPK30vhLvIFre0FAf5kKV1lbXldlNSt96Z2dbUl7ozWxp7WuoOntOVIsnLPS/c1/L3UpWGwteW+ZVhglf+gXtIycw/3a6z7ekZe9jJzFSUpPUcfLT+gr9Yeto7DHtgyVE9f00wtwvgcKRVcsNkVn6rlexL1555EbT2SrMIJp6a/l/q3CNFVLULUu2ktBfh4Oq7YMlDSe8SQLvWVnWfW/sT0sxcRU7UnIU2749OUlF7y+5Gvp7uahQWopfW9qOB9KZhlEh2u3CfA++mnn3T77berZcuWWrZsmWrVqnXJxVY1hPnisvPMeu677fpx6/Fi99UO8FKXhjXUpm6Q2p69lfUSMUBFWrg+Ti8spgdKZZKZm69tR1K0Oe6MNh46rc1xyUrJyiu2X+Oz45Yb1/bX1N/2FG0ZMUnXtw3TkdNZijmRfsEW2MIfmpqHBahZaID8nXg5qjMZudpxLKXgdjRFW48kKyE1265zmEySn6e7/Lw95O91Nux7u8vXq+j3fme/9/Vyl7+3R8HFgUIXBfy8ip7Dy+PSWl3Pv+BmsRg6ciZTu+MLdZFPSNOhpNK7yDeo6afmoQFnn+dAu3psXKxbb3aeWduOJGtd7Gmtjz2tTYfPFHvNBfp4qGvkP93yW9UJrLSt0GXl3PPmbjJp3ppD+nVH+S8zV1GOJWdp+h8x+nbTUVmMgv8zN7cL14Srm6t+TT9Hl1fhsnLN+nt/kpbtTdTyPYmKTyn6ntM6PFBXtQjRgJahuqJukMtd2LKn63/S2Z5Cu+NTrT2GYk6kKef87j5nhQZ6F/yNqhNg7bLfuHa1Yu+nNEyUnzIN87fddluJ29euXasmTZoUCfLff/99icXYqiqEW8J8UVExJ/XyDzsVdzrT5mMiaviqbd0gAj4qpZx8sxJSsnU8OVvHk7MKbilZOp6crcOnMnToVPHX+ti+jdStUU21rhOokEAfB1RdtcSnZBW0uB8+o81xZxR9PLVY10QfTze1q1ddnRoEq3PDYHWICC7SWlFay4hUMDb3yOlM7TnbMrL37O1CY6Pr1/CzttKeC/uVsat+cmbR4L7jWIqOnsmy6dhmodXkZjIpM9eszNx8ZeSYS73oUVY83U3yOxfyi10A8Dh7AaHoBYEdx1L0XaGu7vWCfXU6I1eZuRfuIl/4+avoCzS5+RbtOJaidbGntO7gaW08dNraNfucat4e6tQg2Dru/op6QSWOD3Y26Tn5SkzN1qINRzTrr4NFhihU1DJzFWl/YrreXbrXeqHCw82koV3r6/EBTVz+78fRM5lafnbs++oDp4qEUR9PN/VuUltXtQxR/+YhCgty7d/F5TJbDB06laE98QWt+LsT0rQnIVVHTpf8fu7hZlLj2tXOBvxAJaZma96aQ07XMOEsFyDKNMzfd999Nj/wnDlzim1zc7O965zZXL5/1CsDwnyBxLRsvfF/u/XztoLW+DpBPhrYMlTz18VZPxy/dENLNQsNsH5w3HksRYdLCELSPwG/bd3qZ4N+IAG/AjnLm2NJ7KndYjF0KiPXGtKPJWcpPqVwaM8utXutrWpV81br8EC1Dg9Uq/BAtQ4PUgPGtV2yPLNFe+LTtPFwQevl5sNndDyleKtxWKCPOjUMVqf6BeG9ZZ3AiwYdeydFOr9L9p6zt9K6QHp5uKlpSLVCIbGgNb+iZitOyczTzuMp2n604P13+7HkUj/oNazpp7b1qqtt3UCFB/lq3MItRS5cuJtMWvV8/2K/J4vFUFaeWRm5+crMKfg3K9esjFyzMnPyC/49F/xzi36fmZuvzEL7Fnxd8O/5XdDLwrnno3Cviso6dCLfbFH08VRruF9/6LTSsvOL7OPr6V4Q7s+OuW8XESRvj8rR9dxiMXQ6M1eJqTlKTCt4X01My9HJs7fEtGzr96VdZJGkL0d31ZVNa1dg5RVnx9EUTft9j1buS5JUEGbv7Rmph/s2VpCfc3cjP8dsMbQl7oz+3FPQ+n5uzoNz6lb3LQjvLULUo1FN+XhWjtevM0vPyT/79+ns36n4gq9Tz3v/KElYoI98PN3k7maSp3vBvx5uJnm4n9tmkrubmzzdTAX3uZvk4eZ2dp+z97mbihzn4XZ2n8LbC9939t/C5y84b9HjPN3c9MfuE/pw2T6nuADhkHXmSxMVFWX9+tChQ3r++ed17733qkePHpKkNWvWaN68eZoyZYpGjRpV3uU4XFUP8xaLoa/Xx2nab3uUlp0vN5N0X69IPXl1M1Xz9rjoh+NzHy5tDfhX1K1epAXfVf7AVSbOPHHh+bW/dmNr9WhcU8cLBfRjyVmKT87W8ZSCf21ZO9bH003h1X0VHuSr8Oo+1q+9Pd305KKtxSauubpVqA4mZejgyfQSW26reXuoZZ0AtapTEO5bhQeqWWjAJXchdmXJmbnaEpdcMN798GltO5JSrPXX3c2klnUC1LlBDXVsEKxODYId2mpn72Rp1f081Tw0QC3rFLQGNw8LUPPLbAlOycpT9Nn31e0XeW9tUNNPbeoG6Yqz76ut6wYpyLfoe+uFei5UhDyzpUgPgHPBv/D353oGZJy7EJCTr7jTmVoXe7rY+d6+s51uaR9e6XpK2MpsMbQ7PlXrY09rXewprY89bZ0p/RwvDzd1iKiubo1qqntkDXWoH1xsXPnlXrjNzjMXBPL0HCWm5uhkoaCeWCioJ6XnljiRV2l8PNyUXcIFnAUPdlePxjXtrtOZrDlwStN+36MtccmSCuYFGNu3se7r1bDSz2Be0uspJTNPUftOatnuE4qKOVnkdepmkjo1CLZOXtcstFqlu5DmigzDUHxKtrW32ap9SVp94JSjy7pspV1krgwqVZgv7KqrrtIDDzygoUOHFtk+f/58zZo1SytWrKjIchyiKof53fGpemHxDusfnCvqBWnyrW3Vpm7QZZ33/IC/42hKqd3269fwK9ZFn4B/aZIzc/Xz9uN6+YfoYvdV9/WUh7tJJpNJJhV0dTTJJDeTrH94TSbJzWQ6e1/B1zr7tcl0dl+dvb/wec4dd/YkboWOOf881vOXcK7cfLPWHCz+of1iTCYpNMBH4dV9VKe6r+pW91V40NnAfvYW7OdZ6geMC4WcrFyz9iSkKvp4wW3X8RTtSSh5XJunu0lNQgKsrfitw4PUsk6A00/sczGFP/yFBfooNilDG8+2uG86fEb7EtOLHRPo41EQ2usHq1PDYLWrV73Sj1E/N0Z7z9mWEVvGaEfU8C0ysVrLOgFqWNNfHu5uRX5v/t4e2nk2sO84lqodR5NLHP5x7pznLopeUS9IbcJtf88s7+WcykNJk7FW5g98l8piMbQvMd3acr8u9pSS0nOL7OPpblK7etWt3fIPJWXotZ+ji124NQxDqdn5OpmWXRDQzwb1xBKCeklzUVxITX8v1Q7wVkigj2pX81ZIoLdCArwLtgX4nP3XW6nZeVXieSuNYRj6Y3ei3v59r/aeKGi9rlXNW48PaKKhXetXygu/519MH9w6TElnVw0pfCEn0MdDfZsXTF7Xt1ltJmerBEqbtHrWyM6q7uupfIuhfLOhfIvl7L+GzJbC31sK7WPIbLEoz3x2H/PZ+wqfw2LIbDaUZ7Gc3af4ufPMBfflnT3f+fdl5ubrdEbx95/KesGvXMP8t99+q2+++UZxcXHKzS36xr958+YLHuvn56dt27apadOmRbbHxMSoffv2ysy0fdy0s6qKYT4zN1/T/9inz1bFymwxVM3bQ08PaqYRPRrKvZy6DhcJ+GfHdV5uwHfmruRlwWIxtP1YiqL2nlRUTMFssXY0nDgNX083Najpr/DqvqpzNqTXPRvS6wT5KCzI57LHmdoTcvLNFh1MylD08RRFH0vVrviCoF/ah+IGNf2s4b6gJd81xuFn55k15+9YTft9r3WWYj8v9xK72Daq5W9tce/cIFiNXWjJrpJmK96bkKbEUoZ3eHm4qaa/V7HJoUpSL9i3ILBX8flIHN2rwBEMw9CBkxlFwv2J1IsPGQoL8tGZjNxSJ9IqiZe7m2pbA3lBQK9dzadYUK9Zzcuu99qq+Lydz2wx9NO2Y3p3aYx1SEy9YF89ObCZbulQt9w+c9njdEauVu47qfELtxZbgvGcpiHVCtZ+bxGiTg2CnbZHjCtztv9vznahttzC/AcffKAXX3xRo0aN0qeffqr77rtPBw4c0IYNG/Too49q0qRJFzy+efPmuuGGG/TOO+8U2f7UU0/p//7v/7R37157ynFKVS3M/7n7hF75MVrHkgv+qFzXNkyv3NDaIROTJGfmauexVGv3fFsD/hX1ghRzIk1v/N8up+xKfjlOpuVo5b6Tioo5qZX7knQ6o+gFvMhafjqUlFnkD7KbSfri/m6qWc1LhiEZMgr+LfS1xTBk6Oy28762nN1PhqxfFxxbcJzObrNYdPY44+ybc9H9zn1tWL8+99gF285k5mrKr3uK1e4MyyEahqFjyVlnW+//acUvaSy49M84/FaFWvErwzj8fLNFpzNyC1rt0nOUdPbfk4XGxp77/vzxvud4upvUPqK6OjWooU4NgtWxfnXVrOZdwT+J453OyP1nebRCsxWXNp44LNBH7SOqq229f4I7LV7/cMZeBWXJMIyCIQcHT2tt7Cn9tfekks57/z9foI+HNYgXBPRzLen/tKCHBPgo0Nej3LpGV/Xn7ZzcfIsWbYjTB8v2W+dxaRZaTU8Naq5BrUIrpGv6ud5Fu44XXIQ+9++FLiyO6tFAo3s3qpKz8zsjZ/v/5kwXIMotzLdo0UKvvvqqhg4dqoCAAG3btk2NGjXSK6+8otOnT2vGjBkXPP7XX3/V7bffrsaNG6t79+6SCmbFP3DggL777jtdd9119pTjlKpKmE9IydZrP0Xrt+iC2VbrVvfVG7e01oAWoQ6urCh7An5hJpM0c0QndWlQw6U+AOebLdpyJFkr9iYqKuakdh4ruhpFgLeHejWppb7Na6tPs9qqW93Xqd4cz+fMtZfkdEbu2Q9MKdau+qWNw/f3clfLOv+E+9LG4dvbI8UwDKVm5etkenaRCavOD+lJ6Tk6lZEr+/4KFffl/V11ZTPXnODqclkshn7adlzjF20tdl9l7VqIyqm0brWf3NNJLesEqnaAN5OPVUKZufmau/qQPllxwDqBWfuI6nr2mubq2aTslpXOyS+Y3PNcYI8+nqLd8WlKzyn5Imy96j46mlw01FfmVlK4Dme5AFFuYd7Pz0+7d+9WgwYNFBISoqVLl6pdu3bat2+funfvrlOnLj4ZwtGjR/Xxxx9r9+7dMgxDrVq10tixYxUREWFPKU7L1cO82WLoizWH9M6SGKXn5MvdzaQHrozUE1c1rfQTsZxzfsBff+iUTqaV3iJR3c9TDWv6q1EtfzWs5a/Is7eGtfxVrZKPy5UK3tgKus6f1Kr9ScVaQNvUDVTfZrXVt1mIOtSvXmK3R2d5cyyJM9dui6xcs3YnFG3Bt3Uc/onUbM3666C1R8rTg5qrW6MaJbSc5/7Tsp6WY9MkgeeYTFJNf29rt9va1Qp9Xeh7i2Fo8Pt/OU0XucrC2boWovJytYufVUlKZp5m/nVAc/4+ZJ1Ys3eTWnrmmuZqF1HdrnMlZ+b+09J+NrzvT0xXfglXjb3c3dQ8rGDy1lZne4e1CCuY24XXE1C6cgvzjRo10rfffquOHTuqS5cueuCBBzRmzBgtWbJEd999t06ftn8yqarGlcP8zmMpemHxDm0/miJJ6lC/uibf2lYt6zj3z1nSh2FJql3NWydLWVLKuk+Ad0G4r+mvyNr+BaG/tr/q1/BzWCtGTr5ZGw+dUVTMSUXtPWmdLOecYD9PXdm0tvo2q60rm9VSSIDzj7dGUeePw48++4HM3smpLuRcl9uCm0+xkF6rWsHEVjX8vGweD8mHv0vD7w1lxdUvfrq6xLRszVi2XwvWxynPXPChZnDrMD19TTP5e3sU6YVlGIaOnsmyBvfo46naHZ9qHTZ5viBfz4LhXIWCe+Pa1S447wGvJ6Bk5RbmH3jgAUVEROjVV1/VJ598ogkTJqhXr17auHGjbrvtNs2ePbvYMdu3b1ebNm3k5mbbh7Xo6Gg1b95cHh6Vv0XzUrhimE/Pydc7S/Zq3upDshgFy6I8f20LDe1S3+FjcstKaR+GM3PzdSgpU4dOZSg26Z/boaQMnbrA+EKTSQoP8i3Sit/o7Nf1gn3LfLKXuFOZioop6Dq/+sCpIuNo3UxSu4jq6tcsRH2b11bbukGVYpIcVKzC4/Cjj6dq1b6T2nx25YnCalXzUkQNv1Jb0AuCevl1ueXD36Xh9wbgnCOnM/Xe0hgt3npMhlGw+su5QGCS1LCWv5LSS5+rJKKGb0ForxNkDe7hQT4sEweUkXIL8xaLRRaLxRq0v/nmG61atUpNmjTR2LFj5eVVfOywu7u7EhISVLu2bWMaAwMDtXXrVjVq1Mie0pyGK4V5wzD0e/QJvfZTtBJSC8Y+3dQuXC/d0NIlW3Pt/TCckpWnQ0nnhfxTGYo9maG0UsaRSZKHm0kRNfwKQv7ZFv1zLft1An1KvEBy/rjmrFyz1h48VdD6HnNSsUkZRfavHeB9tut8bfVuUsulxv2jbJTcPVta5QQTBAIALm5vQpre/GWXVu5LKvF+T3eTmoYEFAT2sy3uLesEKsjXtZdABRytUq0z7+bmpoceekh+frbNTPnRRx9p165dZRrmJ02apF9++UVbt26Vl5eXkpOTi+0TFxenRx99VMuWLZOvr6+GDRumt99+u8gFih07duixxx7T+vXrVaNGDY0ZM0Yvv/yyXVciXSXMH0vO0qs/7tQfuxMlFcz+/uYtbdSHiaguyjAMncrILdaSfy7sZ+eVPt7Y28NNDWv6q2EtP0XWqqbIWn6KTcqwjms2SWoSUk2HT2cqt9CYaA83kzo1CFa/5gXrtLasE8AVdFwU3bMBwLWtPpCkYZ+uK7Z96m1tdVvHepVyjXrA1dmaFy+pH/vKlSs1c+ZMHThwQN9++63q1q2rL7/8UpGRkerdu3ex/fv06WPXknM9evSQr2/Ztvrk5ubqzjvvVI8ePUocCmA2m3X99derdu3aWrVqlU6dOqVRo0bJMAx9+OGHkgp+qVdffbX69++vDRs2KCYmRvfee6/8/f311FNPlWm9lVm+2aI5fx/Se3/EKDPXLE93k8b0aazHBjRhJlsbmUwm1apW0BW5S8MaRe6zWAwlpGbrUFKGDhYK+bGnMhR3KlM5+RbtPZF2dpz7iWLnNiTtS0yXVLCCQN/mBa3vPRvXVIAPV9JhnyFd6qtPs9p0zwYAFxVZy19uJhWbJLNv89oEeaCSszvMf/fddxoxYoSGDx+uLVu2KCenYPKvtLQ0TZ48Wb/++muxY1asWHHZhV6u119/XZI0d+7cEu9fsmSJdu3apSNHjig8PFyS9M477+jee+/VpEmTFBgYqK+//lrZ2dmaO3euvL291aZNG8XExOjdd9/VhAkTqkQr55a4M3ph8U7tji9YrqxrwxqadGsbNQ0NcHBlrsPNzaTw6r4Kr+5bbNmYfLNFx5KzioT8LXFntOO85eMk6e072+n2jnWrxOsS5atOkC8hHgBcVJ0gX025rW2xXli87wOVn91h/s0339Qnn3yikSNHauHChdbtPXv21L/+9a8yLa4irVmzRm3atLEGeUm65pprlJOTo02bNql///5as2aN+vbtK29v7yL7TJw4UYcOHVJkZGSJ587JybFe9JAKWvidTWp2nv792159te6wDKNgKbYXrm2pOzrVc5kJ7pyBh7ubGtT0V4Oa/lLzgm2lLTvVq0lNgjwAALgoemEBzsnuvjN79+5Vnz59im0PDAwscRy6s0hISFBoaGiRbcHBwfLy8lJCQkKp+5z7/tw+JZkyZYqCgoKst4iIiDKuvuzFp2Rp9YEkHU/O1M/bjuuqd6L05dqCIH9bx7r6c0Jf3dUlgiBfCZy7ou5+NrhzRR0AANirTpCvejSuyecHwInY3TJfp04d7d+/Xw0bNiyyfdWqVRU++/xrr71m7T5fmg0bNqhz5842na+kVkzDMIpsP3+fc/MHXqgFdOLEiZowYYL1+9TU1Eod6BdtiNPE73cUW1O9US1/vXlLm2Jdv+F4XFEHAAAAqha7w/yYMWP0xBNP6PPPP5fJZNLx48e1Zs0aPf3003rllVfKo8ZSPfbYY7r77rsvuM/5Fx1KExYWpnXris7keebMGeXl5Vlb38PCwoq1wCcmFszkfn6LfWHe3t5FuuZXZvEpWSUG+dG9G+qZa1owwV0lxrhmAAAAoOqwO8w/++yzSklJUf/+/ZWdna0+ffrI29tbTz/9tB577LHyqLFUtWrVUq1aZdNK3KNHD02aNEnx8fGqU6eOpIJJ8by9vdWpUyfrPi+88IJyc3Oty9UtWbJE4eHhNl80qOxikzKKBXlJGtgyjCAPAAAAAJXEJa03MWnSJCUlJWn9+vVau3atTp48qTfeeKOsaytTcXFx2rp1q+Li4mQ2m7V161Zt3bpV6ekFS3gNGjRIrVq10ogRI7Rlyxb9+eefevrpp/Xggw9a1/YbNmyYvL29de+992rnzp1avHixJk+e7FIz2Z9bnqQwd5NJDWv5OaYgAAAAAEAxNof5zMxMPfroo6pbt65CQkL0wAMPqGHDhuratauqVatWnjWWiVdeeUUdOnTQq6++qvT0dHXo0EEdOnTQxo0bJUnu7u765Zdf5OPjo169eumuu+7SLbfcorffftt6jqCgIC1dulRHjx5V586d9cgjj2jChAlFxsM7OyZTAwAAAIDKz2Scm8HtIp555hl99NFHGj58uHx8fLRgwQL169dP//3vf8u7RpeTmpqqoKAgpaSkWFv9K5v4lCwmUwMAAACACmZrXrR5zPz333+v2bNnWyecu+eee9SrVy+ZzWa5uzOW2tUwmRoAAAAAVF42d7M/cuSIrrzySuv3Xbt2lYeHh44fP14uhQEAAAAAgJLZHObNZrN1BvdzPDw8lJ+fX+ZFAQAAAACA0tnczd4wDN17771F1kvPzs7W2LFj5e/vb932/fffl22FAAAAAACgCJvD/KhRo4ptu+eee8q0GAAAAAAAcHE2h/k5c+aUZx0AAAAAAMBGNo+ZBwAAAAAAlQNhHgAAAAAAJ0OYBwAAAADAyRDmAQAAAABwMoR5AAAAAACcDGEeAAAAAAAnQ5gHAAAAAMDJEOYBAAAAAHAyhHkAAAAAAJwMYR4AAAAAACdDmAcAAAAAwMkQ5gEAAAAAcDKEeQAAAAAAnAxhHgAAAAAAJ0OYBwAAAADAyRDmAQAAAABwMoR5AAAAAACcDGEeAAAAAAAnQ5gHAAAAAMDJEOYBAAAAAHAyhHkAAAAAAJwMYR4AAAAAACdDmAcAAAAAwMkQ5gEAAAAAcDKEeQAAAAAAnAxhHgAAAAAAJ0OYBwAAAADAyRDmAQAAAABwMoR5AAAAAACcDGEeAAAAAAAnQ5gHAAAAAMDJEOYBAAAAAHAyhHkAAAAAAJwMYR4AAAAAACfj4egCqiLDMCRJqampDq4EAAAAAFCZnMuJ53JjaQjzDpCWliZJioiIcHAlAAAAAIDKKC0tTUFBQaXebzIuFvdR5iwWi44fP66AgACZTCZHl1NlpKamKiIiQkeOHFFgYKCjy4ED8Bqo2nj+qzae/6qN5x+8Bqo2Z3v+DcNQWlqawsPD5eZW+sh4WuYdwM3NTfXq1XN0GVVWYGCgU/wnRvnhNVC18fxXbTz/VRvPP3gNVG3O9PxfqEX+HCbAAwAAAADAyRDmAQAAAABwMoR5VBne3t569dVX5e3t7ehS4CC8Bqo2nv+qjee/auP5B6+Bqs1Vn38mwAMAAAAAwMnQMg8AAAAAgJMhzAMAAAAA4GQI8wAAAAAAOBnCPAAAAAAAToYwDwAAAACAkyHMwyH++usv3XjjjQoPD5fJZNIPP/xQbB/DMPTaa68pPDxcvr6+6tevn6Kjoy943kOHDmn06NGKjIyUr6+vGjdurFdffVW5ubnWfbZt26ahQ4cqIiJCvr6+atmypaZPn37B854+fVqPP/64mjdvLj8/P9WvX1/jxo1TSkqKXY+NAq74/EvSTTfdpPr168vHx0d16tTRiBEjdPz4cdt/MVWII18Dp06d0uDBgxUeHi5vb29FREToscceU2pq6gXPnZOTo8cff1y1atWSv7+/brrpJh09erTIPmfOnNGIESMUFBSkoKAgjRgxQsnJyTb/XqoKV33+J02apJ49e8rPz0/Vq1e3+fdR1bji889nANu54vMv8RnAHq76Gii8b/v27WUymbR169aL/j4uB2EeDpGRkaF27dppxowZpe4zbdo0vfvuu5oxY4Y2bNigsLAwXX311UpLSyv1mD179shisWjmzJmKjo7We++9p08++UQvvPCCdZ9Nmzapdu3a+uqrrxQdHa0XX3xREydOvGAtx48f1/Hjx/X2229rx44dmjt3rn777TeNHj3arsdGAVd8/iWpf//++uabb7R371599913OnDggO644w47fjNVhyNfA25ubrr55pv1008/KSYmRnPnztUff/yhsWPHXrDm8ePHa/HixVq4cKFWrVql9PR03XDDDTKbzdZ9hg0bpq1bt+q3337Tb7/9pq1bt2rEiBF2/GaqBld9/nNzc3XnnXfq4YcftuO3UfW44vPPZwDbueLzL/EZwB6u+ho459lnn1V4eLgNv4kyYAAOJslYvHhxkW0Wi8UICwszpk6dat2WnZ1tBAUFGZ988old5582bZoRGRl5wX0eeeQRo3///nad95tvvjG8vLyMvLy8y3rsqs6Vn/8ff/zRMJlMRm5url3nrmoqw2tg+vTpRr169Uq9Pzk52fD09DQWLlxo3Xbs2DHDzc3N+O233wzDMIxdu3YZkoy1a9da91mzZo0hydizZ49dNVclrvL8FzZnzhwjKCjIrjqrKld8/u157KrOlZ9/PgPYxtVeA7/++qvRokULIzo62pBkbNmyxa567UXLPCql2NhYJSQkaNCgQdZt3t7e6tu3r1avXm3XuVJSUlSjRo3L3qekYwIDA+Xh4VGm54VrPP+nT5/W119/rZ49e8rT09Ouc6NiXwPHjx/X999/r759+5a6z6ZNm5SXl1eknvDwcLVp08Zaz5o1axQUFKRu3bpZ9+nevbuCgoLsrrmqc8bnH2XHVZ5/PgNcGld4/vkMcHmc9TVw4sQJPfjgg/ryyy/l5+dnV52XijCPSikhIUGSFBoaWmR7aGio9T5bHDhwQB9++OEFu86sWbNG33zzjcaMGWPzeU+dOqU33njjgsfY8tgomTM//88995z8/f1Vs2ZNxcXF6ccff7T5vPhHRbwGhg4dKj8/P9WtW1eBgYH67LPPLliPl5eXgoODS60nISFBISEhxY4NCQmxq2Y45/OPsuMKzz+fAS6dMz//fAYoG874GjAMQ/fee6/Gjh2rzp0721zj5SLMo1IzmUxFvjcMw7pt7NixqlatmvV2vuPHj2vw4MG688479cADD5R4/ujoaN1888165ZVXdPXVV9tUU2pqqq6//nq1atVKr776aon72PLYuDhnfP6feeYZbdmyRUuWLJG7u7tGjhwpwzBsOjeKK8/XwHvvvafNmzfrhx9+0IEDBzRhwgS76ytcT0n1lrQPbOdszz/KlrM+/3wGKBvO+PzzGaBsOdNr4MMPP1RqaqomTpxo93kuS7l24gdsoBLGyhw4cMCQZGzevLnI9ptuuskYOXKkYRiGceLECWPfvn3WW2HHjh0zmjVrZowYMcIwm80lPm50dLQREhJivPDCCzbXmpqaavTo0cO46qqrjKysrBL3seWx8Q9Xe/4LO3LkiCHJWL16tc2PURU56jVQ2MqVKw1JxvHjx0u8/88//zQkGadPny6y/YorrjBeeeUVwzAMY/bs2SWOkw4KCjI+//zzi9ZQVbnK818YY+Zt52rPP58B7ONqz39hfAawjau8Bm6++WbDzc3NcHd3t94kGe7u7taaywMt86iUIiMjFRYWpqVLl1q35ebmKioqSj179pRU0HW1SZMm1ts5x44dU79+/dSxY0fNmTNHbm7FX+bR0dHq37+/Ro0apUmTJtlUU2pqqgYNGiQvLy/99NNP8vHxKbaPLY+Ni3PW5/98xtmr8Tk5OTY9Bv5R3q+B813suerUqZM8PT2L1BMfH6+dO3da6+nRo4dSUlK0fv166z7r1q1TSkqKdR/Yxhmff5QdZ33++QxQNpz1+bf3vCidM74GPvjgA23btk1bt27V1q1b9euvv0qSFi1aZPNnzUtSbpcJgAtIS0sztmzZYmzZssWQZLz77rvGli1bjMOHD1v3mTp1qhEUFGR8//33xo4dO4yhQ4caderUMVJTU0s977Fjx4wmTZoYAwYMMI4ePWrEx8dbb+fs3LnTqF27tjF8+PAi9ycmJpZ63tTUVKNbt25G27Ztjf379xc5Lj8/3+bHRgFXfP7XrVtnfPjhh8aWLVuMQ4cOGcuWLTN69+5tNG7c2MjOzi6D35prceRr4JdffjE+//xzY8eOHUZsbKzxyy+/GK1btzZ69ep1wZrHjh1r1KtXz/jjjz+MzZs3GwMGDDDatWtnfQ0YhmEMHjzYuOKKK4w1a9YYa9asMdq2bWvccMMNl/Gbck2u+vwfPnzY2LJli/H6668b1apVs/6MaWlpl/Hbcj2u+PzzGcB2rvj88xnAPq74GjhfbGxshcxmT5iHQyxfvtyQVOw2atQo6z4Wi8V49dVXjbCwMMPb29vo06ePsWPHjgued86cOSWet/B1q1dffbXE+xs0aGB3vZKM2NhYmx8bBVzx+d++fbvRv39/o0aNGoa3t7fRsGFDY+zYscbRo0cv51flshz5Gli2bJnRo0cPIygoyPDx8TGaNm1qPPfcc8aZM2cueO6srCzjscceM2rUqGH4+voaN9xwgxEXF1dkn1OnThnDhw83AgICjICAAGP48OEXPW9V5KrP/6hRo0p87OXLl9v7K3Jprvj88xnAdq74/PMZwD6u+Bo4X0WFeZNhMCsDAAAAAADOhME8AAAAAAA4GcI8AAAAAABOhjAPAAAAAICTIcwDAAAAAOBkCPMAAAAAADgZwjwAAAAAAE6GMA8AAAAAgJMhzAMAAAAA4GQ8HF1AVWSxWHT8+HEFBATIZDI5uhwAAAAAQCVhGIbS0tIUHh4uN7fS298J8w5w/PhxRUREOLoMAAAAAEAldeTIEdWrV6/U+wnzDhAQECCp4MkJDAx0cDUAAAAAgMoiNTVVERER1txYGsK8A5zrWh8YGEiYBwAAAAAUc7Eh2UyABwAAAACAkyHMAwAAAADgZAjzAAAAAAA4GcI8AAAAAABOhjAPAAAAAICTIcwDAAAAAOBkCPMAAAAAADgZwjwAAAAAAE6GMA8AAAAAgJMhzAMAAAAA4GQI8wAAAAAAOBnCPAAAAAAAToYwDwAAAACAkyHMAwAAAADgZAjzAAAAAAA4GcI8AAAAAABOhjAPAAAAAICTIcwDAAAAAOBkCPOF5Ofn66WXXlJkZKR8fX3VqFEj/etf/5LFYrHuYxiGXnvtNYWHh8vX11f9+vVTdHS0A6sGAAAAAFQ1hPlC3nrrLX3yySeaMWOGdu/erWnTpunf//63PvzwQ+s+06ZN07vvvqsZM2Zow4YNCgsL09VXX620tDQHVg4AAAAAqEoI84WsWbNGN998s66//no1bNhQd9xxhwYNGqSNGzdKKmiVf//99/Xiiy/qtttuU5s2bTRv3jxlZmZq/vz5Dq4eAAAAAFBVEOYL6d27t/7880/FxMRIkrZt26ZVq1bpuuuukyTFxsYqISFBgwYNsh7j7e2tvn37avXq1aWeNycnR6mpqUVuAAAAAABcKg9HF1CZPPfcc0pJSVGLFi3k7u4us9msSZMmaejQoZKkhIQESVJoaGiR40JDQ3X48OFSzztlyhS9/vrr5Vc4AAAAAKBKcdow37FjR7v2N5lM+umnn1S3bt1S91m0aJG++uorzZ8/X61bt9bWrVs1fvx4hYeHa9SoUUXOVZhhGMW2FTZx4kRNmDDB+n1qaqoiIiLsqh8AAAAAgHOcNsxv3bpVTz31lKpVq3bRfQ3D0NSpU5WTk3PB/Z555hk9//zzuvvuuyVJbdu21eHDhzVlyhSNGjVKYWFhkgpa6OvUqWM9LjExsVhrfWHe3t7y9va25ccCAAAAAOCinDbMSwXhOyQkxKZ933nnnYvuk5mZKTe3otMIuLu7W5emi4yMVFhYmJYuXaoOHTpIknJzcxUVFaW33nrLzuoBAAAAALg0ThvmY2NjVbt2bZv337Vrl8LDwy+4z4033qhJkyapfv36at26tbZs2aJ3331X999/v6SC7vXjx4/X5MmT1bRpUzVt2lSTJ0+Wn5+fhg0bdlk/DwAAAAAAtjIZhmE4uojKIi0tTS+//LIWL16sxMREhYeHa+jQoXrllVfk5eUlqaDL/uuvv66ZM2fqzJkz6tatm/7zn/+oTZs2Nj9OamqqgoKClJKSosDAwPL6cQAAAAAATsbWvOgSYX779u0lbjeZTPLx8VH9+vUr1Zh1wjwAAAAAoCS25kWn7WZfWPv27S84m7ynp6eGDBmimTNnysfHpwIrAwAAAACg7LldfJfKb/HixWratKlmzZqlrVu3asuWLZo1a5aaN2+u+fPna/bs2Vq2bJleeuklR5cKAAAAAMBlc4mW+UmTJmn69Om65pprrNuuuOIK1atXTy+//LLWr18vf39/PfXUU3r77bcdWCkAAAAAAJfPJVrmd+zYoQYNGhTb3qBBA+3YsUNSQVf8+Pj4ii4NAAAAAIAy5xJhvkWLFpo6dapyc3Ot2/Ly8jR16lS1aNFCknTs2DGFhoY6qkQAAAAAAMqMS3Sz/89//qObbrpJ9erV0xVXXCGTyaTt27fLbDbr//7v/yRJBw8e1COPPOLgSgEAAAAAuHwusTSdJKWnp+urr75STEyMDMNQixYtNGzYMAUEBDi6tGJYmg4AAAAAUJIqtTSdJFWrVk1jx451dBkAAAAAAJQ7lxgzL0lffvmlevfurfDwcB0+fFiS9N577+nHH390cGUAAAAAAJQtlwjzH3/8sSZMmKBrr71WZ86ckdlsliQFBwfr/fffd2xxAAAAAACUMZcI8x9++KE+/fRTvfjii/Lw+GfkQOfOna1L0wEAAAAA4CpcIszHxsaqQ4cOxbZ7e3srIyPDARUBAAAAAFB+XCLMR0ZGauvWrcW2/+9//1OrVq0qviAAAAAAAMqRS8xm/8wzz+jRRx9Vdna2DMPQ+vXrtWDBAk2ZMkWfffaZo8sDAAAAAKBMuUSYv++++5Sfn69nn31WmZmZGjZsmOrWravp06fr7rvvdnR5AAAAAACUKZNhGIajiyhLSUlJslgsCgkJcXQppUpNTVVQUJBSUlIUGBjo6HIAAAAAAJWErXnRJVrmC6tVq5ajSwAAAAAAoFw5bZjv0KGDTCaTTftu3ry5nKsBAAAAAKDiOG2Yv+WWW6xfZ2dn66OPPlKrVq3Uo0cPSdLatWsVHR2tRx55xEEVAgAAAABQPpw2zL/66qvWrx944AGNGzdOb7zxRrF9jhw5UtGlAQAAAABQrlxiArygoCBt3LhRTZs2LbJ937596ty5s1JSUhxUWcmYAA8AAAAAUBJb86JbBdZUbnx9fbVq1api21etWiUfHx8HVAQAAAAAQPlx2m72hY0fP14PP/ywNm3apO7du0sqGDP/+eef65VXXnFwdQAAAAAAlC2XCPPPP/+8GjVqpOnTp2v+/PmSpJYtW2ru3Lm66667HFwdAAAAAABlyyXGzDsbxswDAAAAAEpSpcbMAwAAAABQlThtmK9Ro4aSkpJs3r9+/fo6fPhwOVYEAAAAAEDFcNox88nJyfrf//6noKAgm/Y/deqUzGZzOVcFAAAAAED5c9owL0mjRo1ydAkAAAAAAFQ4pw3zFovF0SUAAAAAAOAQTjtmHgAAAACAqoowDwAAAACAkyHMAwAAAADgZAjzAAAAAAA4GcI8AAAAAABOxmlns09NTbV538DAwHKsBAAAAACAiuW0Yb569eoymUw27Ws2m8u5GgAAAAAAKo7TdrNfvny5li1bpmXLlunzzz9XSEiInn32WS1evFiLFy/Ws88+q9DQUH3++ed2nffYsWO65557VLNmTfn5+al9+/batGmT9X7DMPTaa68pPDxcvr6+6tevn6Kjo8v6xwMAAAAAoFQmwzAMRxdxua666io98MADGjp0aJHt8+fP16xZs7RixQqbznPmzBl16NBB/fv318MPP6yQkBAdOHBADRs2VOPGjSVJb731liZNmqS5c+eqWbNmevPNN/XXX39p7969CggIsOlxUlNTFRQUpJSUFIYAAAAAAACsbM2LLhHm/fz8tG3bNjVt2rTI9piYGLVv316ZmZk2nef555/X33//rZUrV5Z4v2EYCg8P1/jx4/Xcc89JknJychQaGqq33npLY8aMselxCPMAAAAAgJLYmhedtpt9YREREfrkk0+KbZ85c6YiIiJsPs9PP/2kzp07684771RISIg6dOigTz/91Hp/bGysEhISNGjQIOs2b29v9e3bV6tXry71vDk5OUpNTS1yAwAAAADgUjntBHiFvffee7r99tv1+++/q3v37pKktWvX6sCBA/ruu+9sPs/Bgwf18ccfa8KECXrhhRe0fv16jRs3Tt7e3ho5cqQSEhIkSaGhoUWOCw0N1eHDh0s975QpU/T6669fwk8GAAAAAEBxLtEyf91112nfvn266aabdPr0aZ06dUo333yzYmJidN1119l8HovFoo4dO2ry5Mnq0KGDxowZowcffFAff/xxkf3On0XfMIwLzqw/ceJEpaSkWG9Hjhyx7wcEAAAAAKAQl2iZl6R69epp8uTJl3WOOnXqqFWrVkW2tWzZ0tq6HxYWJklKSEhQnTp1rPskJiYWa60vzNvbW97e3pdVGwAAAAAA57hMmJekzMxMxcXFKTc3t8j2K664wqbje/Xqpb179xbZFhMTowYNGkiSIiMjFRYWpqVLl6pDhw6SpNzcXEVFRemtt94qg58AAAAAAICLc4kwf/LkSd1333363//+V+L9ZrPZpvM8+eST6tmzpyZPnqy77rpL69ev16xZszRr1ixJBd3rx48fr8mTJ6tp06Zq2rSpJk+eLD8/Pw0bNqzMfh4AAAAAAC7EJcbMjx8/XmfOnNHatWvl6+ur3377TfPmzVPTpk31008/2XyeLl26aPHixVqwYIHatGmjN954Q++//76GDx9u3efZZ5/V+PHj9cgjj6hz5846duyYlixZYvMa8wAAAAAAXC6XWGe+Tp06+vHHH9W1a1cFBgZq48aNatasmX766SdNmzZNq1atcnSJRbDOPAAAAACgJFVqnfmMjAyFhIRIkmrUqKGTJ09Kktq2bavNmzc7sjQAAAAAAMqcS4T55s2bWyeua9++vWbOnKljx47pk08+KTLrPAAAAAAArsAlJsAbP3684uPjJUmvvvqqrrnmGn399dfy8vLS3LlzHVscAAAAAABlzCXGzJ8vMzNTe/bsUf369VWrVi1Hl1MMY+YBAAAAACWpUmPmz8nNzdXevXvl5eWljh07VsogDwAAAADA5XKJMJ+ZmanRo0fLz89PrVu3VlxcnCRp3Lhxmjp1qoOrAwAAAACgbLlEmJ84caK2bdumFStWyMfHx7p94MCBWrRokQMrAwAAAACg7LnEBHg//PCDFi1apO7du8tkMlm3t2rVSgcOHHBgZQAAAAAAlD2XaJk/efKkdZ35wjIyMoqEewAAAAAAXIFLhPkuXbrol19+sX5/LsB/+umn6tGjh6PKAgAAAACgXLhEN/spU6Zo8ODB2rVrl/Lz8zV9+nRFR0drzZo1ioqKcnR5AAAAAACUKZdome/Zs6dWr16tzMxMNW7cWEuWLFFoaKjWrFmjTp06Obo8AAAAAADKlNO3zOfl5emhhx7Syy+/rHnz5jm6HAAAAAAAyp3Tt8x7enpq8eLFji4DAAAAAIAK4/RhXpJuvfVW/fDDD44uAwAAAACACuH03ewlqUmTJnrjjTe0evVqderUSf7+/kXuHzdunIMqAwAAAACg7JkMwzAcXcTlioyMLPU+k8mkgwcPVmA1F5eamqqgoCClpKQoMDDQ0eUAAAAAACoJW/OiS7TMx8bGOroEAAAAAAAqjEuMmS/MMAy5QGcDAAAAAABK5TJhfvbs2WrTpo18fHzk4+OjNm3a6LPPPnN0WQAAAAAAlDmX6Gb/8ssv67333tPjjz+uHj16SJLWrFmjJ598UocOHdKbb77p4AoBAAAAACg7LjEBXq1atfThhx9q6NChRbYvWLBAjz/+uJKSkhxUWcmYAA8AAAAAUBJb86JLdLM3m83q3Llzse2dOnVSfn6+AyoCAAAAAKD8uESYv+eee/Txxx8X2z5r1iwNHz7cARUBAAAAAFB+XGLMvFQwAd6SJUvUvXt3SdLatWt15MgRjRw5UhMmTLDu9+677zqqRAAAAAAAyoRLhPmdO3eqY8eOkqQDBw5IkmrXrq3atWtr586d1v1MJpND6gMAAAAAoCy5RJhfvny5o0sAAAAAAKDCuMSY+fMdPnxYu3btksVicXQpAAAAAACUOacO8/PmzdP7779fZNtDDz2kRo0aqW3btmrTpo2OHDnimOIAAAAAACgnTh3mP/nkEwUFBVm//+233zRnzhx98cUX2rBhg6pXr67XX3/dgRUCAAAAAFD2nHrMfExMTJH15X/88UfddNNN1uXoJk+erPvuu89R5QEAAAAAUC6cumU+KytLgYGB1u9Xr16tPn36WL9v1KiREhISHFEaAAAAAADlxqnDfIMGDbRp0yZJUlJSkqKjo9W7d2/r/QkJCUW64QMAAAAA4Aqcupv9yJEj9eijjyo6OlrLli1TixYt1KlTJ+v9q1evVps2bRxYIQAAAAAAZc+pw/xzzz2nzMxMff/99woLC9N///vfIvf//fffGjp0qIOqAwAAAACgfJgMwzAcXURVk5qaqqCgIKWkpBQZ8w8AAAAAqNpszYtOPWYeAAAAAICqiDAPAAAAAICTIcxfwJQpU2QymTR+/HjrNsMw9Nprryk8PFy+vr7q16+foqOjHVckAAAAAKDKIcyXYsOGDZo1a5auuOKKItunTZumd999VzNmzNCGDRsUFhamq6++WmlpaQ6qFAAAAABQ1bhUmM/NzdXevXuVn59/WedJT0/X8OHD9emnnyo4ONi63TAMvf/++3rxxRd12223qU2bNpo3b54yMzM1f/78Us+Xk5Oj1NTUIjcAAAAAAC6VS4T5zMxMjR49Wn5+fmrdurXi4uIkSePGjdPUqVPtPt+jjz6q66+/XgMHDiyyPTY2VgkJCRo0aJB1m7e3t/r27avVq1eXer4pU6YoKCjIeouIiLC7JgAAAAAAznGJMD9x4kRt27ZNK1askI+Pj3X7wIEDtWjRIrvOtXDhQm3evFlTpkwpdl9CQoIkKTQ0tMj20NBQ632l1ZeSkmK9HTlyxK6aAAAAAAAozMPRBZSFH374QYsWLVL37t1lMpms21u1aqUDBw7YfJ4jR47oiSee0JIlS4pcFDhf4ceQCrrfn7+tMG9vb3l7e9tcBwAAAAAAF+ISLfMnT55USEhIse0ZGRkXDNnn27RpkxITE9WpUyd5eHjIw8NDUVFR+uCDD+Th4WFtkT+/FT4xMbFYaz0AAAAAAOXFJcJ8ly5d9Msvv1i/PxfgP/30U/Xo0cPm81x11VXasWOHtm7dar117txZw4cP19atW9WoUSOFhYVp6dKl1mNyc3MVFRWlnj17lt0PBAAAAADABbhEN/spU6Zo8ODB2rVrl/Lz8zV9+nRFR0drzZo1ioqKsvk8AQEBatOmTZFt/v7+qlmzpnX7+PHjNXnyZDVt2lRNmzbV5MmT5efnp2HDhpXpzwQAAAAAQGlcomW+Z8+e+vvvv5WZmanGjRtryZIlCg0N1Zo1a9SpU6cyfaxnn31W48eP1yOPPKLOnTvr2LFjWrJkiQICAsr0cQAAAAAAKI3JMAzD0UVUNampqQoKClJKSooCAwMdXQ4AAAAAoJKwNS+6RMt8//79NXv2bKWkpDi6FAAAAAAAyp1LhPm2bdvqpZdeUlhYmG6//Xb98MMPys3NdXRZAAAAAACUC5cI8x988IGOHTumH3/8UQEBARo1apTCwsL00EMP2TUBHgAAAAAAzsAlx8xnZ2fr559/1qRJk7Rjxw6ZzWZHl1QEY+YBAAAAACWxNS+6xNJ0hSUkJGjhwoX66quvtH37dnXp0sXRJQEAAAAAUKZcopt9amqq5syZo6uvvloRERH6+OOPdeONNyomJkbr1q1zdHkAAAAAAJQpl2iZDw0NVXBwsO666y5NnjyZ1ngAAAAAgEtziTD/448/auDAgXJzc4mOBgAAAAAAXJBLhPlBgwY5ugQAAAAAACqMS4R5Sfr222/1zTffKC4urtga85s3b3ZQVQAAAAAAlD2X6Jf+wQcf6L777lNISIi2bNmirl27qmbNmjp48KCuvfZaR5cHAAAAAECZcokw/9FHH2nWrFmaMWOGvLy89Oyzz2rp0qUaN26cUlJSHF0eAAAAAABlyiXCfFxcnHr27ClJ8vX1VVpamiRpxIgRWrBggSNLAwAAAACgzLlEmA8LC9OpU6ckSQ0aNNDatWslSbGxsTIMw5GlAQAAAABQ5lwizA8YMEA///yzJGn06NF68skndfXVV2vIkCG69dZbHVwdAAAAAABly2S4QNO1xWKRxWKRh0fB5PzffPONVq1apSZNmmjs2LHy8vJycIVFpaamKigoSCkpKQoMDHR0OQAAAACASsLWvOjUYb53794aMGCA+vfvrx49esjHx8fRJdmEMA8AAAAAKImtedGpu9k3b95c8+fP11VXXaXg4GD169dP//rXv7Rq1Srl5eU5ujygQsWnZGn1gSTFp2Q5uhQAAAAA5cypW+bPOXr0qJYtW6aoqCitWLFCsbGx8vX1Vc+ePTVgwABNnDjR0SUWQcs8ytqiDXGa+P0OWQzJzSRNua2thnSp7+iyAAAAANipSnSzL82RI0c0c+ZMffjhh0pPT5fZbHZ0SUUQ5lGW4lOy1GvqMlkK/U92N5m06vn+qhPk67jCAAAAANjN1rzoUYE1lasDBw5oxYoV1ltycrJ69Oihvn37Oro0oFxtOnymSJCXJLNh6FBSJmEeAAAAcFFOHebnzJmj5cuXa8WKFUpJSVGvXr3Ut29fPfroo+rcubN1dnvAVR08ma43/293iff5e7tXcDUA4DriU7IUm5ShyFr+XBgFAFRKTt3N3s3NTfXr19fEiRN1//33y9PT09El2YRu9igLO4+laNTn63UqI1e1qnnpdEZukRb6RrX9tfDB7goJdI5VHgCgsvh67WG99MNOGWIeEgBAxasSY+Y//vhjRUVFKSoqStnZ2erdu7f69eunvn37qlOnTjKZTI4usUSEeVyuNQdO6cEvNio9J19t6gZq7n1dlWe26FBSprw8TBq3YKuOJWepcW1/LXyoh2oHeDu6ZACo9CwWQ1+uPaRXf9pVZDvzkAAAKlKVCPOF7dq1yzqb/blw36tXL/Xv319PP/20o8srgjCPy7EkOkGPLdii3HyLukXW0GejOivAp2ivlLhTmRoya43iU7LVNKSaFjzUXbWqEegBoCSGYWhFzElN+22vdsenlrjPgge7q0fjmhVcGQCgKqpyYb6w48eP66OPPmI2e7icbzcd1XPfbZfZYmhgy1DNGNZBPp4lj40/lJShu2etVUJqtpqHBmj+g91Uk0APAEVsjjujt/63R+tiT0uS/L3clZlrVuEPR24m6e/nB9AyDwCoEFVqNvsTJ04Umck+JiZGXl5e6tatm/r37+/o8oAy8dnKg3rzl4LJ7m7vWE9v3d5WHu5upe7fsJa/FjzUXUNmrtHeE2ka/tk6zX+wu2r4e1VUyQBQae1PTNO03/Zqya4TkiQvDzeN6tFAj/RroiW7EvTC9ztlPtve0TwsgCAPAKh0nLpl/tFHH9Xy5cu1d+9eeXh4qEuXLurfv7/69++vnj17ysenck78Rcs87GEYht5eslf/WX5AkjS6d6RevK6l3NxsmxPiwMl03T1rrU6m5ahVnUDNf7CbqvsR6OG8mGUcl+N4cpbeWxqj7zYflcUoaHW/o1M9jR/YTOHV/3k9xadkac2BU3r6v9tkMaRvxvRQ18gaDqwcAFBVVIlu9j169LCG9169esnPz8/RJdmEMA9bmS2GXv5xp+avi5MkPXNNcz3Sr7HdkzvuT0zT3bPWKSk9R63DAzX/ge4K8nOO1R+Awhasj9MLi3fIMJhlHPY5k5Grj1bs17w1h5Wbb5EkXdM6VM9c01xNQgJKPe7FxTv09bo4dahfXd8/3LPSTq4LAHAdVSLMOyvCPGyRm2/Rk99s1S/b42UySW/e0kbDuzW45PPtO5Gmu2et1amMXLWtG6SvHuimIF8CPZzH4VMZ6vvvFUW2Mcs4LiYzN1+fr4rVzKiDSsvJlyR1i6yh565toY71gy96fGJatvpOW6GsPLM+uaejBrepU94lAwCqOFvzYukDbgE4TEZOvkbP26BftsfL092kGUM7XlaQl6SmoQHWMfM7jqVo5Ox1Ss3OK6OKgfKVk2/W+IVbi203G4YOJWVWfEGo9PLMFn255pD6TFuht5fEKC0nXy3rBGrufV208KHuNgV5SQoJ8NGDV0ZKkqb9tld5Zkt5lg0AgM0I80Alk5yZq3tmr9PKfUny9XTX7FFddP0VZdMS1DwsQF8/0E3Bfp7adjRFoz5frzQCPSq57Dyzxny5SVuOJBe7z90kNazlHEOsUDEsFkM/bTuuge9G6eUfo5WUnqP6Nfw0/e72+uXx3urXPMTurvIP9W2smv5eOpiUoW82HimnygEAsA9hHqhEElKyddfMNdoSl6wgX099/WA39WlWu0wfo2WdQH31QDdV9/PUlrhk3Ttng9LPdj0FKpvsPLMe+nKTVuw9KR9PNz14ZaQKz/14S4e6dLGHpILJQqNiTurGGas0bsEWHT6VqVrVvPSvm1vrjwl9dXP7ujZPHHq+at4eGndVU0nS+3/sU2Yu75kAAMdz+TDPlABwFrFJGbr949WKOZGu0EBv/XdsD5u7gdqrdXiQvhrdTYE+Htp0+Izum7NeGQR6VDLZeWY9+MVG/RVzUr6e7ppzb1e9eH0r/f38AN3TvWDSu2V7EpWcmevgSuFoW+LOaNin6zTq8/WKPp6qat4eeurqZop6pr9G9mgoL4/L/7gztGt9Najpp5NpOfpsZWwZVA0AwOVxiTA/ZcqUErebzWYNGzasgqsB7LfzWIru/GS1jiVnqWFNP307tqeahZY+u3JZaFM3SF8/0F0BPh7acOiM7pu7gdYmVBpZuWY9MG+jVu5Lkp+Xu+be10U9GteUJNUJ8tWrN7ZWs9BqOpOZp3//vtfB1cJR9iema+yXm3TrR6u15uApebm76YHekfrr2f56/Kqm8vf2KLPH8vJw09ODmkuSZkYd0Kn0nDI7NwAAl8Ilwvz777+vWbNmFdlmNpt19913a+vWrY4pCrDRuoOnNHTWWiWl56pVnUD9d2xPRdSomDHAbesVtNAHeHtofexpjZ67UVm55gp57KouPiVLqw8kKT4ly9GlVDpZuWaNnrdBq/afC/Jd1a1RzSL7eLq76V83t5EkzV8fpx1HUxxRKhwkPiVLz3+3XYPei9Jv0QnWteKXP9NPL93QSjX8vcrlca9vW0dt6wYpI9esD5ftL5fHgPPifR1ARXOJpek2bdqkgQMHaubMmbrrrruUl5enIUOGaM+ePVq2bJnCwsIcXWIRLE2Hc/7YdUKPzt+snHyLujasoc/u7axAn4pfLm5L3BmNmL1e6Tn56tWkpmaP6iIfT/cKr6OqWLQhThO/3yELa6UXk5mbr/vnbtDag6fl7+Wuefd3VeeGNUrd/4mFW/Tj1uNqF1Fdix/uecljouEckjNz9fGKA5q7+pByzq4Vf3WrgrXiy7s30zmr9ydp2Gfr5Olu0h8T+qpBTf8KeVxUXhaLoX8v2aNPVhyUId7XAVy+KrU0XadOnbR48WI9+OCD+vHHH3X77bdr7969Wr58uV1BfsqUKerSpYsCAgIUEhKiW265RXv3Fu2+aRiGXnvtNYWHh8vX11f9+vVTdHR0Wf9IqAK+33xUY77apJx8i65qEaIvRnd1SJCXpA71gzXv/i7y93LX3/tP6cEvNio7jxb68hCfkmUN8pJkMaQXvt9BS44KlmS8d05BkK/m7aEvRl84yEvSC9e1VDVvD207ksws4y4sK9es/yzfryunLdfMvw5aL4B+93APfTqyc4UFeUnq2aSW+jarrTyzobeXxFTY46Jyyc4za9meE5r4/XZ1evMPfXw2yEvn3td38r4OoNy5RJiXpH79+unLL7/UHXfcoUOHDikqKkqhoaF2nSMqKkqPPvqo1q5dq6VLlyo/P1+DBg1SRkaGdZ9p06bp3Xff1YwZM7RhwwaFhYXp6quvVlpaWln/SHBhn6+K1YRvtslsMXRbh7r6ZEQnh7eEd2pQQ3Pv7yo/L3et3Jekh77cRKAvB3viU61B/hyzIf29/5RjCqokMnLydd+cDVofe1oBZ4N8pwYXDvKSFBroo/EDC2YZf+u3PUyG52LyzBZ9tfaw+v57uf79+16lZeerRViA5tzbRYvGdLfpNVIenhvcQiaT9PO249p+NNkhNaDipWTmafGWo3rk603q+MZS3T93oxasP6IzJbzvmA1Dh5IyHVAlgKrEabvZ33bbbSVuX7t2rZo0aaJatWpZt33//feX9BgnT55USEiIoqKi1KdPHxmGofDwcI0fP17PPfecJCknJ0ehoaF66623NGbMGJvOSzf7qsswDL23NEYfnB1reX+vSL10fctK1TV43cFTunfOBmXlmdW/eW19MqKTvD3ocl8WzBZD985Zr5X7kord5+lm0sP9m+iRfo0dfmGnoqXn5Ovez9dr4+EzCvDx0Jeju6l9RHWbj88zW3TDB6u090Sahnerr0m3ti2/YlEhLBZDv+6M1ztLYhSbVHBBPaKGr566urluahdeKd4zJyzaqu+3HFPPxjX19QPd7F67Hs7heHKWlu46oSW7ErTu4GnlF7oaGxboo6tbhapzw2A9uWhrsQu1w7vV1xs3t6kUr1e4nviULMUmZSiylj9LtLogW/Ni2U3zWsGCgoJK3H7NNdeU2WOkpBRMqFSjRsGV/9jYWCUkJGjQoEHWfby9vdW3b1+tXr261DCfk5OjnJx/Zr1NTU0tsxrhPCwWQ6/+FK0v1x6WJD11dTM9NqBJpfsA2K1RTX1+bxfdN3e9lu89qUe+2qyP7ulIoC8Dk37ZrZX7kuTuZpJhGNYx801DqmnviXR98Oc+/bztuN68pY16Nal18RO6gLTsPN07Z4M2nQ3yX43upnZ2BHnp3GR4rTVk1lrNXx+nIV0idEU9+86BymPlvpOa9tte7ThW8De4pr+XHh/QRMO6NSiTJebKypNXN9P/bY/X6gOn9Ne+JPVtVtvRJaEMGIahvSfStCS6IMDvPFb0M1vz0ABd3SpUg1qHqm3dIOvf8Ow8s174fqfMhiGTJEPS1+vilJyVp3fubFflLtKifC3aEKfnv98hg7l3qjynbZkvb4Zh6Oabb9aZM2e0cuVKSdLq1avVq1cvHTt2TOHh4dZ9H3roIR0+fFi///57ied67bXX9PrrrxfbTst81ZGbb9FT/92mn7cdl8kk/evmNhrRvYGjy7qgv/cn6f65G5STb9HAlqH6aHjHSvVB2tnM/TtWr/28S5I0Y1gHdWoQrENJmWpYy09hgT76384EvfZTtBLTCi783dqhrl68vqVqVfN2ZNnlKjU7T6M+X68tcckK9PHQVw90u6wQPn7hFv3AZHhOa/vRZL312x7rkJNq3h568MpGGn1lpKqV4RJzZenN/9ulz1bFqmWdQP3yeG9ec07KbDG08dBpLdl1Qkt3nVDc6X+6x5tMUucGwRrUKkxXtwpVw1qlT3gYn5JlfV9fe/CUnv12u/LMhro0DNasEZ0VXE6rLKBqOXomU1e+tVyFA5ybSfr7+QG00LsQW1vmCfOlePTRR/XLL79o1apVqlevnqR/wvzx48dVp04d674PPvigjhw5ot9++63Ec5XUMh8REUGYryIyc/M19qvN+ivmpDzcTHp3SHvd1C784gdWAiv3ndToeRuVm2/RNa1DNWNYR3m6E+jttXTXCY35cqMsRsFY24f7NS5xv9TsPL3z+159sfawDEMK8vXUxGtb6K7OES4XElKz8zRy9nptPZKsIF9Pff1AN7WpW3KPK1slpmZrwDtRSs/J19Tb2ururrRSOIODJ9P19pK9+nVHgiTJy91N93RvoEf7N1bNSn4x60xGrvr8e7nSsvP13pB2urVDPUeXBBtl5Zq1ct9JLdl1Qsv2JOp0xj/j3r093HRl01oa1CpMA1qGXPJF1dUHkjTmy01Ky85Xo1r+mnNfF1Y/wGXJyMnXiNnrtDkuudh9H9/TUde2qVP8IDilKhfmv/32W33zzTeKi4tTbm7RiUg2b95s17kef/xx/fDDD/rrr78UGRlp3X7w4EE1btxYmzdvVocOHazbb775ZlWvXl3z5s2z6fyMma86kjNzdf/cDdoclyxfT3d9fE9H9Wse4uiy7BIVc1IPflEQ6K9tE6YPhnYg0Nthx9EU3TVzjbLyzBraNUKTb2170aEVW48k64Xvd2hXfEH3zi4NgzXp1rYVOmN3eUrJytPI2eu07WiKqvt56qvRlx/kz/ls5UG9+ctuBft5avnT/VTdj5awyiohJVvT/9ynbzYekdliyGSSbutQT+MHNlVEDT9Hl2ezj1bs17Tf9qpudV/9+VRfulNXYqczcvXn7oLW97/2nVR2nsV6X3U/Tw1oEaJBrcLUp1kt+XmVTW+QmBNpum/OBh1LzlJNfy99NqqzOtQPLpNzo2o5lpyl0XM3aE9CyZNuB/t56sOhHdW7adUYpufqqtTSdB988IHuu+8+hYSEaMuWLeratatq1qypgwcP6tprr7X5PIZh6LHHHtP333+vZcuWFQnykhQZGamwsDAtXbrUui03N1dRUVHq2bNnmf08cA0nUrM1ZOZabbZ2Ie7qdEFekvo2q62ZIzrJy91N/9uZoPELtyrfbLn4gdDRM5m6f17BZIJ9mtXWv25uY9McCe0jquunx3rppetbys/LXRsOndF101fq37/vcfoVBlIy8zTibJAP9vPU/Ae6l1mQl6RRPRuqeWiAzmTm6d+/7734AahwKZl5mvq/Per77+VasD5OZouhgS1D9NsTffTOXe2cKshLBROZhgX66Fhylr46OycKHCc+JUurDyRZl4U7cjpTs1fFasjMNer85lI98+12Ldl1Qtl5FtWt7qv7ejXUgge7a+OLA/XuXe01uE1YmQV5SWoWGqDFj/RU6/BAncrI1dBP1+r36IQyOz+qhi1xZ3TzjL+1JyFNtap565F+jeV+9vOEm0kKDfTWmcw8jfh8nd7+fS+f06oQl2iZb9GihV599VUNHTpUAQEB2rZtmxo1aqRXXnlFp0+f1owZM2w6zyOPPKL58+frxx9/VPPmza3bg4KC5OtbMAblrbfe0pQpUzRnzhw1bdpUkydP1ooVK7R3714FBNjWakbLvOs7lJShEZ+v05HTWQoJ8NYXo7uqRZhzP9d/7j6hsV9tUp7Z0I3twvXeXe3kQQt9qVKz83THx6sVcyJdLcIC9N+xPRTg42n3eY4lZ+m1n6K1dNcJSVL9Gn5645Y2TjnZVnJmru6ZvU47j6Wqhr+Xvn6gm1rWKfv/F+sOntKQWWtlMkk/PtqLyfAcqPBsy8F+Xpq7+pA+Wr5fqdn5kgp6nTw3uIU6N3TMEnNlZdGGOD333Q5V9/NU1DP9FeRr//91XL4F6+P04uIdshiSSQUBJyE1p8g+reoEalDrUA1qFaaWdQIqbBLajJx8PTZ/s5bvPSmTSXrlhla6r1fkxQ9ElffTtuN6+r/blJtvUYuwAM2+t4vqVvctMkdDsJ+XXv95lxasj5NU8N46/e4OCq/OGHpnVaW62fv5+Wn37t1q0KCBQkJCtHTpUrVr10779u1T9+7ddeqUbes3l/aGPmfOHN17772SClrvX3/9dc2cOVNnzpxRt27d9J///Edt2rSxuV7CvGvbdTxVIz9fr6T0HDWo6acv7++m+jWdq6WpNEt3ndAjXxcE+pvbh+vdu9rL3cXGcpeF3HyL7pu7Xn/vP6XQQG8tfqTXZf9B/T26YIK8+JRsSdKN7cL18g0tFRLgUxYll7szGbka/tk67YpPVU1/L81/sLuah5XfsIEnF23V4i3H1K5ekBY/0svl5hxwBos2xGni9/8EqwAfD2uIbx4aoGcHN9eAFiGVbkWPS5Fvtuja6Su1LzFdj/RrrGcHt3B0SU7LMAyl5+QrOTNPKVl5Ss3KU3JWwdfnbsmZBdtTsvKUnJWrlKw8ncnIVXpO8Z5LbiapW2RNDWodqoEtQx3a8yPfbNErP0Vr/rqCwDW6d6RevK5yLU+LysMwDL3/xz5N/3OfJGlgyxC9f3eHC04I+vO245r4/Q6l5+Srup+n3rmzna5qGVpRJaMMVakw36hRI3377bfq2LGjunTpogceeEBjxozRkiVLdPfdd+v06dOOLrEIwrzr2nDotO6fu0Fp2flqWSdQ8+7v4jRhy1a/Ryfo0a83K99i6LYOdfXvO9sR6AsxDEPPfrtd/910VH5e7vpmTI8y60aenpOv95bGaM7fsbIYBeHoucEtNKxr/Ur9YfD02SC/Oz5VtaoVBPnyHv9feDK8Kbe11VAmw6tQ8SlZ6jV1WbF1t8MCffTs4Oa6uX1dl3vf+GPXCT3wxUb5eLppxdP9FRbkWu/959iytrVhGMrKM1uDtzWIZ54XyguH9MyCUJ6anS/z+S+cy/DpyE66ulVYmZ3vchmGoU+iDuqt3/ZIkga3DtP7d7evsnMtsFZ6ybLzzHrm2+36edtxSdJDfRrpucEtbHrfPJSUoccXbLEu7/lA70g9O7gFKxI5mSoV5h944AFFRETo1Vdf1SeffKIJEyaoV69e2rhxo2677TbNnj3b0SUWQZh3Tcv3JOrhrzcpO8+iLg2D9dmoLi7b1fJ/O+L12IItMlsM3dGpnqbdfkWlDpMVacayfXp7SYzcTNLsUV3Uv0XZz5Ow81iKXli8Q9uPFvyh7lC/uibf2rZcuqxfrlPpORr+2TrrOL8FD3ZT0wqayG/2qli98X+7FOznqWVP9WNZqAr0+apY/ev/dhXb/sX9XdSnmfPNHWILwzB018w12nDojIZ0jtBbd1zh6JLK3Pm9LXo0rqnQQB8lnw3ihW955sv7eOnl4abqvp4KOnur7uepwMLf+3oqyO/c917Kzbdo+Gdri1xAcjeZtOr5/pUyJP649Zie+e925Zot6lC/uj4b2bnSr95Q1gq/nlgr/R+Jadl66ItN2nokWR5uJk26tY3dv5ecfLOm/m+P5vx9SJLUrl6QPhza0WV6ilYFVSrMWywWWSwWeXgUdDv55ptvtGrVKjVp0kRjx46Vl1fl+gBHmHc9P2w5pqf/u035FkMDWoToP8M6ytfLta+y/7I9XuMWFgT6IZ0jNO6qJjp8OrNKX13/cesxPbFwqyTpjVvaaET3BuX2WGaLoS/XHNLbS2KUnpMvdzeTHugdqScGNi3TyZsuR1J6joZ/uk57T6SpdoC3FjzYXU1CqlXY4+ebLbrhw1Xak5CmYd3qa/KtbSvssauqmBNpeut/e/TnnsRi91XmYFVWNh0+o9s/Xi03k/T7+D4VduGqIsSnZKnn1GWy51Ojh5up5BB+7ubn9c/XZwP7ua8vpaV60YY4vfD9TpkNQ+4mkybfZn8IqkjrDp7SQ19uUkpWnhrU9NPc+7oq8gLr2LuSknrvmCQte6qfImtXjd9BSXYdT9UD8zboeEq2qvt56uPhndSjcc1LPt+S6AQ98+12pWTlKcDbQ2/dcYWua8vydc6gSoV5Z0OYdy3zVh/Sqz9FS5JuaR+uf9/Zrsos3fbztuN6YuGWIn+Mq+rV9XUHT2nE7PXKNVv04JWRevH6VhXyuAkp2Xr952j9b2fB7Mh1q/vqjVtaa0ALx46RO5mWo+GfrVXMiXSFBHhrwUPd1bh2xQX5c5gMr2LEp2Tp3SUx+m7zUVkMyd3NpC4Ng7U+9nTB904QrMrKmC836vfoExrYMlSfjers6HLKzNtL9mrGsv3Ftg/vFqF29YKLBvazodzPy73C50QoPCmYM1w42p+YrnvnrNfRM1kK9vPUZ6M6q1MD554Q0ha/bD+uR+dvKbY92M9TL17fSrd1qFvlevwt3XVCTyzcosxcsxrV8tfse7uUycWdY8lZenz+Zuva9Pd0r6+Xrm9VZYd2OIsqF+ZXrlypmTNn6sCBA/r2229Vt25dffnll4qMjFTv3r0dXV4RhHnXcP7EJPf2bKhXbmhV5f74zFsdq1d/Ktqd1t0krXp+gFN8kCoLB06m67aPVislK0/XtgnTf4Z1rPDXwZ+7T+iVH6N1LLlgOabr2obp1RtbKzSw4sftJqZla9in67Q/MV2hgQUt8o0cEOTPYTK88pOSlaePVxzQnL9jlZNfsBTSdW3D9PSg5mpUu5rTBauycOBkuga995fMFkP/HdtDXZx8pn7DMPTRigMlLvVYFXpbVISTaTkaPW+Dth9NkZeHm94f0t6lW08T07J1x0erFXcmq9R9WtUJ1IvXt1SvJq6/ZrphGPp05UFN+d8eGYbUq0lNfTSsk4L8ym6oZp7ZoneXxujjFQckSS3CAvSf4R0dcpEdtqlS68x/9913uuaaa+Tr66stW7YoJ6dgGZK0tDRNnjzZwdXBFVkshl77Kdoa5J8c2Eyv3lj1grykEruRmg3p078OKiMn3wEVVaxT6Tm6b84GpWTlqX1Edb03pL1DXgdXtQzV0gl9NKZPI7m7mfTrjgRd9U6U5v4dW6aTSV1MYmq2hs5aq/2J6QoL9NHCh3o4NMhL0sTrWijA20PbjqZo0cYjDq3FVWTnmfXpXwfVZ9pyfRJ1QDn5FnWNrKHFj/TUR8M7WZ/zOkG+6tG4ZpUKe41rV9OQLhGSpCm/7pYzt5nkmS16/rsd1iB/ZZNaOvf2dq63RVV6bstL7QBvLXyouwa2DFFuvkWPzt+sz1YedOrXTmmS0nM07NN1ijuTpeq+nkVeT2/e0kbPX9tCAT4e2hWfquGfrdN9c9Yr5kSaY4suR7n5Fj333XZN/rUgyA/vVl9z7+tapkFekjzd3fTc4Baad39X1fT30p6ENN344Sp9v/lomT4OKp5LtMx36NBBTz75pEaOHFlknfmtW7dq8ODBSkhIcHSJRdAy77ziU7K0PzFdX6w+rKW7C9b9fv2m1hrVs6FjC3Og0matlgpmW7+zU4RG9mighi44DjA7z6yhn67VlrhkRdTw1eJHeqlWJZjAaNfxVL2weIe2HkmWJF1RL0iTb21bZrPql+bE2SB/MClD4UE+WvBQdzWoWTme93OT4VX389RyJsO7ZGaLoR+2HNO7S2OsvUCahVbTc4NbuMwyc2UhMTVbff+9Qll5Zn1yTycNblN5ZlO3VWp2nh79erNW7kuSm0l67abWGtmjYZXsbVFRzBZDr/8crS/WHJYkjerRQK/c2NplVn44nZGrYZ+u1Z6ENNUJ8tGih3rI08NU7PV0OiNXH/y5T1+tPax8iyE3kzSkS4SeHNhMIQ7obVZezmTkauxXm7Qu9rTcTNLLN7TSvT0blvv76InUbI1fuFVrDhYs3X1Hp3r6182tK818OyhQpbrZ+/n5adeuXWrYsGGRMH/w4EG1atVK2dnZji6xCMK8cyo866pUMDb8vSHtdXP7uo4trBIoPOmQm0m6vm0d7TiWokOnMiVJJpPUr1ltjezZUH2b1naJHgwWi6HHFmzWrzsSFOTrqe8e7lmhk7tdjMViaP76OL312x6lZefLzSTd2zNSEwY1u+AatZcqISVbQz9dq9ikDNWt7qsFD3avVLPmMhne5TEMQ1ExJzX1f3u0J6GglaxOkI+evLqZbu9Yz2XCRll6Z8lefbhsvxrV9teS8X3k4URzqRxLztL9czZo74k0+Xm568OhHViruoIYhqHPVsZq0q+7JUkDW4bqg6HtnT5oJWfmatin67QrPlUhAd5aNKbHRceDxyZlaNpve6xzwvh5uWtMn8Z6sE+k0/8+9iema/S8DTp8KlPVvD304bAO6t+84lb6MFsMzVi2X9P/jJHFkBrX9td/hndUizBySWVRpcJ848aNNXPmTA0cOLBImP/iiy80depU7dpVfHkcRyLMV375ZotikzK0Kz5Vu+JTtTUuWetiTxfZx80k/V2FxoVfzPmtNRaLob/2ndS81Ye0fO9J636Rtfw1onsD3dG5ngJ9nHfpvim/7tbMvw7K092kL0d3U/dGlz7bbHlKTMvWG/+327pWbZ0gH712U2td07rsWgrjU7I0dNZaHTqVqbrVfbXwoe6KqFF5gvw562NP666Za2QyST880kvtIqo7uiSnsP1osqb8usfaihPg46FH+zfRvT0bMoHSBaRl56nvv1fodEauJt/aVsO6OcfkfzuOpuj+eRt0Mi1HIQHe+vzeLuXeqwfF/bI9Xk9+s1W5+Ra1qxekz0Z1Ue0Ax/f8uhQpWXm657N12nEsRbWqeWvRGPsmRN146LTe/GW3tbdZSIC3nhrUTHd0inDKC4mr9iXp4a83KS07X/WCfTV7VBc1D3PMyhdrDpzSEwu3KDEtR94ebnrtpta6u0sEvawqgSoV5qdNm6Z58+bp888/19VXX61ff/1Vhw8f1pNPPqlXXnlFjz32mKNLLIIwX7mkZedpT0Kadh1P1e6z4X1vQpp1MqcLWfBg98taMqSqOJSUoS/X/n979x0V1bX9Afw7M8DQR+lFmlgABQs20KjYE40mPo0ag+VZE02e0RjbezHNYNRfjCVGTRSNMaJJbIm9V1SkKIIoIL1K78ww9/z+GJyAIA4ITNuftVgLL3fuPc65DHffc87eSTh0NwXFFbJ19IZ6AozvaY/pPs5qV77p11tJ+O/RBwCAjZO64e0e7ZTcope78vgp/ns0Eil5sqnRwz2s8cXYLrBr82oPo9ILyjHlp1tIyi1Du7ayEXlVDOSfWXwwAofD0+BVnQxPHW8EW0tiTinWn32EE/czAAB6Aj6m+zphgV8HtDGkZQqKCLyRgC/+ioaViRCXlw5W+dHE89FZ+PBAOMolUrjZmGD3jN6v/BlBmu5uYh7m/HIX+WUSOJgZIHBGH5WaAaaIogoJ/Hfdwb2UApgb6SFobr8m/c1njOFEZAa+PR0j/zvmZmOCFW+4Y1Any+ZudovZdysJnx+PgpRj6OXUFtv9vZW+PC+3pBKLD93DlceygZcxXrYIGO8JEzUecNEEWhXMA8CqVauwceNG+ZR6oVCITz75BF999ZWSW1YXBfPKwRhDWkF5ddBejOiMQjzMKEZyXlm9+xvqCeBuawp3WxPYtzHEujMxterrUhbfxiutrMKR8DTsvZmI2OwS+fb+Hcwx3ccZQ92tVT64uvQoG7P2hIBjwOLhnfDR0I7KbpLCysVSbLkYi51Xn6CKYzDUE2Dx8E6Y4evcpCnAaQWyEfnkvDI4mMkC+XZtVTeQB2QzFYZuuILiyiq1Gi1tTTklldhyIRb7byejimPg8YC3e9hj8fBOKt+/qqaySoph311BSl45PhnRCQuHqO7nxd6bifjiryhwDBjYyRI/vNuDbuZVwJOnJZgRGILkvDKIDHSx098bfVV0JtjzSiqrMG3XbYQlF6CNoS4OzOkHd9tXu++trJJiX3AStlyMQ2G5BADwWkcLrHjdHR52qntPXSXl8PWJh9hzMxEAML6HPQL+5QmhjmrMbuI4WUb99WceoYpjcDI3xNYpPeHZjmblKIvWBfMAUFZWhujoaHAcBw8PDxgbq+bTSwrmW15llRSxWSWIzqgeba8edS+qqD+7uq1IHx62pnC3NYWHnSk8bE3haGZYa213zXXh2lQzuSUwxhAcn4u9wYk4F50lz0Ng38YA/j5OmNTLQSUTlEWlF+Kd7cEoFUsxwbsd1k/wUsupaI+zirHycCTuJuUDkJUAChjv2ahp56n5ZZjy0y2k5JXD0cwQQXP7qc0I3u7rCfiSkuHVUVpZhZ+vJWDn1XiUiqUAgEGdLLFslJtK3ySrumMRafhPUASMhTq4snQwzFUgSWZNUo5hzYmH2H0jAQAwpY8DvhzXFbpqtMZf0+WWVGL2L3cRnlwAPQEfG97phrHd7JTdrAaViaswY3cI7iTmwVRfB7/N6desyzUKysTYejEOe4MTIZHKHjpO6NkOS0Z0ho1ItZLkFVVI8OFv4fKR76UjO+ODwa4qef8QmpSPjw6EI62gHLoCHla+4d4qSflIXVoRzJeVlWHp0qU4evQoJBIJhg0bhs2bN8PCQrVrUlIw37xySyrxMKNYPkX+YUYR4rJLUFVPenVdAQ8drEzgbmsCD1tTeQCv6M08ZfFtfqn5Zfj1VjKCQpJRUCZ7yi7U4WNcdztM93VGFzvVeCqcUViOt364gayiSvi6mmPPzD7Q01Hfm12OYzh0NwUBp2JQWC4BjwdM6+eEJSM7vzSXQUpeGSbvvIW0gnI4mcsCeXX6faiZDG9KH0cEjNfuZHgSKYegkBRsOh+LnBJZaVevdiIsH+UGXy2o8dzSOI5h7A/X8SCtCDP7O2P1m12U3SS5MnEVFgVF4Gy0rDrLslFumD+oPd24q6AKiRT/CQrHmSjV76tysRQz99zBrSd5MNHXwf7ZfeHVrk2LnCs5twzrzsTg7+rlQPq6fMx9rT3mDnJtkWSvjZWSV4Z/7wlBbHYJ9HX52PhOd7zuaavsZjWosEyCpX/ck38uDPewxvoJXrS8qpVpRTC/dOlSbNu2DVOnToW+vj4OHDiAwYMH4/fff1d20xpEwXzDMgrLkZBTChcLo1oBgpRjSMwtrTXSHp1RhKyiynqP08ZQF+42spF29+rAvYOVsVoHYJqsQiLF8Xvp2HszEVHpRfLtvZ3bYrqvM0Z2sVHaSFFxhQQTtwcjJrMYHa2M8cf7vhAZaMb005ySSqw58RBHwtMAyBILfT62C17valPvTWJyrmxEPq2gHC4WRjgwp5/KjYIogpLhyWbInH6QifVnHuFJTikAwNHMEEtHdsZoT1uNqDqhKq7H5uC9XbehK+DhwuLBKlHpIbu4ArP33sX91ELo6fDxfxO74U0VH+3Vds/Poni3ryO+HNtFpSolVEikmL33Lq7H5cBYqIN9s/qgh2PbFj9vWHI+vjnxUD7jzMJYiI+Hd8SkXg5Ke39CEvMwb18o8krFsDYV4udpvdVm2jpjDHtvJuKbkzEQSznYifSx5d0e8HYyU3bTtIZWBPOurq5Ys2YNJk+eDAC4c+cO+vfvj4qKCggEqrEGpT4UzL9YzfJvPB4wrpsdDIU6iE6XJaUrl0jrfZ2zuaEsaK8RvNuK9FXyiTVpGGMMoUn52BuchFORGfIZFtamQkzt64QpfRxbNaNvlZTDrL13ceXxU1gYC3HkA1+VTvDWVDficvDfow+QUB3U+XW2xJfjutb6vybllmLKzltIL6xAewsjHJjbD9ZqXPNX25Lh1XxQmpxbhoBTMfLs0OZGevhoaEdM6eNIDzxbiP+u27gWm4Nx3e2waXIPpbYlNqsYMwJDkFZQjraGuvhpWi/0cqabdHWx+3oCvjoRDcZkn9Vb3+0JIxUYha6QSDFvXyiuPH4KQz0Bfvl3n1a9rhhjOBOVibWnYuSlcTtYGWPlG27w62zVqveEh8NSsfzPSIilHLram+Lnab3V8sH3g7RCLPwtDIm5ZRDwefhkRGfMG9ieHva2Aq0I5vX09JCQkAB7+3/qfBsYGODx48dwcHBQYssaRsF8/dLyyzDg20to6ILU1+Wjs41p9RR5E3jYmaKzjalKTKUizS+rqAL7byfjt9vJ8um/egI+RnvZYpqPU4s/7WeMYeWRBzhwJxn6unwcnOuj0SO4FRIptl2Ox/bL8RBLOejr8rFoWCe84WmD0MR8BJyKQXZxJdpbGiFoTj9YqXEgD2hXMryaD0prMtAVYM5rLpgzsD0lO2thD9IKMWbLdQDA3x8OUFq5t5txOZj3q6wslouFEQJn9IbzS+p9E9Vz+kEm/hMUjsoqWbC4e3pvpX4mi6s4zP81FBdjsmGgK8Cemb2VlqhPXMXht9tJ2HQhFvnVy/d82ptj1Wj3Fv+94ziGDWcfYdvleADAqC42+G5SN5WvZNGQ4goJVh55IC9xO7CTJb57p5vSs/BrOq0I5gUCATIzM2Fp+U9JChMTE9y/fx8uLi5KbFnDKJivKyQxD0v/uIfEnLqZ5cd2s8NwD2u425rCxcJI40fPSF3iKg6nHmRgz81EhCcXyLd3ayfCdF9njPaybZGMsNuvxGPtqRjweMCO97wxohlrs6uyuOwSrDoSidsJeXV+ZmUixN8fDYCViXoH8s88Kx2mycnwMgrL0X/txTqB/Nvd7bBitLvG9KU6WBQUjqMR6RjQwQK/zu7b6uf/IzQVy/+8jyqOobdzW+z076WR17y2CEvOx+y9d5FXKoZ9GwMEzuyNTkoo9SqRcliwPwxno7Mg1OEjcEZvlci3UVguwY+X47H7RgLE1eWGx/ewx5KRnWHfAglby8RVWHzwHk5HZQIAFvi5Ysnwzhoxis0Yw8GQFHz+VxQqJBwsTYTYNLk7XCyM6l0aq8petJxX1WhFMM/n8/H6669DKPznydBff/2FIUOGwMjon6fMhw8fVkbzXoiC+X+kFZRj7akY+dO+51H5N/K8+6kF2HMzEX/fy4BYKvvjbG6khyl9HDG1n2OzXSt/30/Hwt/CAQCfjfHAvweo7gPClsAYw67rCfj6xMNa2/k84MbyIRrzO6npyfCKKiT435EHOFbPZ+yBOf3g46oeJa40RUpeGYb+3xWIpRz2zeqD1zq2Tn1sxhg2nnuMzRfjAMgekq+b4AV9XdVdkkgUk5RbihmBIUjIKYWJvg52+HvD17X1AukqKYePgsJxMjITejp87Jreq9Wua0Wl5pdhw5lHOBoh+xzU0+Fj1gAXvD/Y9aUJXxWVWViB2b+E4EFaEfQEfKz9lyfG92zXLMdWJY8yi7HwtzB5eWEeAAbZvUHAeE+Vr/JUc5aaqrdZK4L5mTNnKrRfYGBgC7ekcSiYl2U63X4lHjuuxqNCwoHHAyb3doSrpRECTsZQ+TfyUrkllQgKScGvt5KQUVgBABDweRjVxQbTfJzQx8WsyevjQpPyMOWn2xBXcZjh64zPx6pO9unWdDM+B+/+dLvOdk0LAmsmwzvyQX9014ClFOIqDvtvJ2FzjWmmNdGDUuX58q9o7L6RgC52pvhr4YAWH7WrrJJi+Z+R8iSXC/06YPHwThoxWkhk8krFmPvLXdxNyoeugId1E7zwdo+WDySlHMPHByNw/F469AR87JjmDb/OVi1+3qa6n1qANSceymedmRnpYdEwWa6QV0mwG5laiNm/hCCrqBJmRnrY4e+N3hqcg6JMXIVP/7iHv+9n1trOA/B2D3vo6wnAGIOUY5BysoeJ0up/Mya7bqSMyffhGMDJv2fgOEDKnn0v25fjntun+ji19mGosX/d4z47V02q/LdQK4J5daXNwTxjDH/dz8Dakw+RXh2A9XExw+o3PeQlyKj8G2mMKimHc9FZ2HMzsda0cHdbU0z3ccK47vYw0FN89CkxpxRvb7uB/DIJhrlbY4e/t9Yu7ahverYq/+F7FYsPReBwmPonw2OM4e/7GVh/5hGS82TLltpbGmGAqwX2306ClIEelCpZXqkYg9ZdQnFlFTZN7o5x3e1f/qImKigTY+6+UNxJyIMOn4dv3vbEO71VN6cQaboKiRRLDt3DiUhZibYlwzth4ZAOLZb0TcoxLP39Hg6Hp0FXwMOPU70xzMO6Rc7VnBhjuPAwG9+ceognT2UJX9tbGGH5624Y7mHd6PfrVGQGPj4UgQoJh45Wxtg9o7dGJsl93ose9qsjVR2goGBehWlrMB+ZWogv/oqSlw2xb2OAVaPdX1gCi5DGephRhF+CE3EkPA0VEtkUfJGBLib1doB/P6eX/oHNLxVj/I83kZBTCk97EQ7O66fWSWuaw8GQZKw8/EDjZ8s8La7EkA2X1ToZ3q0nuQg4+RD3UgsBAJYmQnw8rBPe6dUOOgI+PShVIT9cisP6M4/Qrq0BLiwZ1CI5P5JySzFzTwiePC2FiVAHP77njQEdlb+OmbQcjmNYezoGO68+AQBM6uWAr9/u2uxlXTmOYdmf9/F7aCoEfB5+eLcnRnVVr5wyEimHoJAUfH/uMXJLxQCAPs5mWDnaXaHZWYwx/HApDhvOPgYADOpkiS3v9mi2afuqrr6H/TwAM3ydITLUhYDHA5/PA5/Hg4AP8HnPvueBzwP4fJ5sn+r96t1H/j2vxv7Vr322nYca38u2C/gAjyfbX8DngVe9T05xJcb9cENtBigomFdh2hbMZxdXYMOZR/g9NBWMybInfzDYFXMGtqf1eqRFFJSJ8fvdVPxyKxEpeeUAZKUOh7pZY4avM/p3MK/zAKlCIoX/rtsIScyHfRsDHFngS4nBqmlLEFgzGd7FJYNhpiaJwR5nFePbUzG4EJMNADDSE2DuQFfMfs1FJcpVkbrKxVIM3nAJWUWV+N8YD8xq5pwcoUn5mPOLLDGanUgfgTP7oLNN6ydGI8qxLzgRq49HgWPAax0tsG1qz2arVsFxDKuOyqq8CPg8bJ7cA6O9bJvl2MpQXCHBjitP8NO1J6isTpI3tpsdlo7s/MIBgOeXrszwdcZ/R7srrZ69sqjjw351ajMF8ypMW4L5yiop9txIxJaLcSiprAIAvNXdDsted9PogICoDinHcCkmG3uDE3EtNke+3dXSCNN9nTG+ZzsYC3WQll+GT/64j+D4XJgIdfDnB75KyQhMlKt2MjwHBIz3UnaTGpRZWIGN5x7j99AUcEw28vBuH0d8NLQjLE2oZJCqC7qTjOWHI9HWUBdXPvVrthG9k5EZ+PhghMqULCPKcT46Cx8eCEe5RAo3GxPsmdnnleucM8bw2bEo7LuVBD4P2DipZZeJtKaMwnJsOPMYh8NlA096Aj5m9HfGgsEdIDL853czp6QS8/aFIjQpHwI+D1+M7YL3+jkpseXKpY4P+9WlzRTMqzBND+afrUf6+kQ0EnNlaza7tRPhsze7wNupZeuCE/Iicdkl2BeciD9CU1EqlgIAjIU68GonQnB8Lp59EM55zQWrRnsor6FEqUIS8zBxu2onw3s2kvTz9Sfy5SSjuthg6ajOcLU0VnLriKKqpBxGfn8V8U9LscDPFUtHur3S8Rhj2Hn1CQJOxQAAhrlbYdPkHjQ7Q4vdTy3Av/eEIKdEDFuRPnbP6A1326bddzLG8OXf0Qi8kQgeD/i/id00Mlt7VHohvjn5EDficgEAbQx18dGQjhjmboXgJ3nYeP4xMgsrYKKvgx+n0tIV0nIomFdhmhzMx2YV48u/o+WjoJYmQiwb5YbxPewpcy5RCcUVEhwOS8Pe4ER58puaVHn9FGkdqpoMT1zF4cCdZGy6EIu86jWe3k5tsfINN3g7aW7mZE12NioTc/eFQl+XjytL/WDdxBH0KimH1cejsP92MgDZtN//jfFQmWuXKE9KXhlmBN5B/NNSGAt18ON7PRtdOo4xhoBT/6zFX/cvL41OpMgYw+XHTxFw8iEeZ5XU+bmZkR4OzfNBByt6eEpaDgXzKkwTg/mCMjG+Px+LfbeSIOUY9AR8zHrNBQv8OsCYRgWICuI4hp3XnmBt9ShWTaqa2ZS0jprJ8Na83RVT+yp3CiVjDCcjM7H+TIx8tlN7CyMse90NI5qQfZmoDsYYJmwPRmhSfpOXdpRUVmHhb2G4/OgpeDzgf6M98O9mXoNP1FudqgbjPfFOL8WCccYY1p95hG2X4wFAbROENkWVlMOuawkIOF37PoHPA24sH0IP/UmLUjRe1K5MDaTZVUk57AtOxOANl7HnZiKkHMPILtY4t3gglo1yo0CeqCw+n4dx3e3w/MCVgMeDs4Xml5UhL2ZpIsSSEZ0AAOtOP5KPgivDnYQ8vL3tJhb8FobE3DJYGOvh67e64szHAzGyC1UCUXc8Hg8r35BNrz8YkoK47OJGvT6jsBwTtwfj8qOn0NflY8d73hTIkzraGOph36w+GNvNDlUcw6d/3Md35x5DkfG8jedj5YH8l+O6aE0gDwA6Aj48HUR1tnMMSMwpU0KLCKmLgnnSZDficjB683X871gUCsok6Gxtgv2z+2KHfy84mRspu3mEvJStyAAB4z0hqA6InmU2paft5L1+TnCzMUFhuQTrz9SdvdHS4rKLMXvvXbyzIxgRKQUw1BPgP0M74vJSP7zXz6nZS00R5fF2MsMID2twTPbwSFFR6YV464cbeJhRBAtjIQ7O9cGILupVHoy0HqGOAN9P6o4PBrsCADZfiMWS3+9BXJ3BvT5bLsRi84VYAMBnYzwwzce5NZqqUlwsjOihP1FpNM1eCdR9mn1SbinWnHiIs9FZAGTJQZYM74QpfRy1riwH0QzqktmUtK6ayfAOv++LHo4tn8Azu6gCG8/H4mBIsjxD/aTeDlg0tCNlJNdgcdnFGLHxKjgG/DHfB72cG86BcOlRNhbuD0OpWIqOVsbYPaP3C8toEfK8324n43/HHkDKMfi6mmO7v3edago/Xo7Ht9XTy1e+4Ya5A12V0VSVoE7lzIjmoDXzKkxdg/mSyipsvRiH3dcTIJZyEPB58O/nhEXDOqKNoXrUYyaEkMZYcuge/gxLhae9CEcXtFwyvJLKKuy8+gQ/XX2Ccoms2sIID2t8OsqNkixpiRWH7+PAnRT0cmqL3+f7vHAJxa+3krD6eJQ8EPvxPW+IDJqnrB3RHpceZWPB/jCUiaXoZG2MwJl9YN9G9jD752tP8PWJhwCApSM7Y4FfB2U2VSXQQ3/S2iiYV2HqFsxzHMOfYalYd+YRnhZXAgBe62iBz8Z4oCPV4iaEaLCnxZUY8n+XUVzRMsnwJFIOQdUZ6nNKZGvzezi2wco33NH7JaOzRLNkFVVg0PpLqJBw2OnvXWfKPMcxfHs6BjuqM4pP8G6Hb972hJ4OzYgjTfMgrRAz94TgaXElrEyEWDfBCxdjsvFLcBIAYNGwjlg0rJOSW0mIdqJgXoWpQzCfUViOhJxSlFRUYeulONxPLQQAOJsb4r+jPTDU3YoSLxFCtMKeGwn4/K9oiAx0cemTwTAzevWZSIwxnInKxLenHyEhR1Yi0dncEMtGuWFUV0psp63Wn4nBD5fi4WpphDOLBsqXrlVIpFh8KAInIzMBAEuGd8LCIR3oOiGvLDW/DDMDQxCbXbsE25DOVtg1oxddY4QoCQXzKkzVg/mDIclYcTgSXI0rw1iog4+GdsB0X2cIdQTKaxwhhLSyKimHN7fKEo1N7u2Atf9qfPmwmu4m5uGbkw8RllwAADA30sN/hnXElD6OlNhOyxVVSDBo3SXkl0mwdrwnJvdxRG5JJWb/chfhyQXQE/CxboIX3uphr+ymEg3yOEuWs6EmAQ+4TuXXCFEaReNFqhtGaskoLMfyw5Go+YiHByBobj90ta9bnoMQQjSdjoCPr8Z1wYTtwTh4NwWTejs0KRleXHYJ1p2OkScPNdAVYM5rLpgzsD1M9GnNMwFM9XWxcEhHfPV3NDacfQSOMWy9FIf0ggqIDHSxw98b/dqbK7uZRMPklFTW2SatLr9GwTwhqo2GAEgtCTmleH6uBgNQXFGllPYQQogq6OVshn/1bAfGgM+OyZKPKSq7uAKrjkRi5PdXcTY6C3weMKWPAy4vHYzFIzpTIE9qea+fI9oa6iKnRIyVRx4gvaACZkZ6OPyBLwXypEVQ+TVC1BcF86QW+kAnhJD6LX/dDSb6OohMK8SBO8kv3b+0sgrfn3+MwesvY//tZEg5hmHuVjizaCACxnvBmkrNkXrklYpRUCapta2gTAxDPVriRlqGrcgAAeM9IaheH/+s/BqNyhOi+miaPanl2Qf68/U06QOdEKLtLE2E+GREZ6w+HoX1Zx7hDU/bepPhSaQcDoak4PvzsfLpq90c2mDl627oSyOr5CUSckrx/LwPjqY8kxY2qbcjBnaypPJrhKgZCuZJHfSBTggh9Zva1xFBISl4mFGEdadjaiXDY4zhbHQWvj0dgydPZRnqncwN8elIN7zhSRnqiWKezZCruZKDZsiR1mArMqB7PkLUDE2zb6Jt27bBxcUF+vr68Pb2xrVr15TdpGZlKzKAj6s5fagTQkgNz5LhAUBQSArORmfiZnwOzkZlYuL2YMzbF4onT0thZqSHz9/0wLmPB2G0ly0F8kRhNOWZEEKIoqg0XRMcPHgQ/v7+2LZtG/r3748dO3bg559/RnR0NBwdHV/6elUvTUcIIaRhn/x+D3+EptbZrq/Lx+wB7TFvEGWoJ68mo7CcZsgRQoiWojrzLahv377o2bMnfvzxR/k2d3d3vPXWWwgICHjp6ymYJ4QQ9RaVXojRm6/X2sYDcGxBf3g5tFFKmwghhBCiGajOfAsRi8UIDQ3F8uXLa20fMWIEbt68We9rKisrUVn5Tw3PwsJCALJOIoQQon7Ss/PAVZbV2Z6dW4AiEa1gI4QQQkjTPYsTXzbuTsF8I+Xk5EAqlcLa2rrWdmtra2RmZtb7moCAAHzxxRd1tjs4OLRIGwkhhCjH8O+V3QJCCCGEaIri4mKIRKIX/pyC+SZ6PpkRY+yFCY5WrFiBxYsXy//NcRzy8vJgbm5OSZFaUVFRERwcHJCSkkLLG7QUXQPajfpfu1H/azfqf0LXgHZTt/5njKG4uBh2dnYN7kfBfCNZWFhAIBDUGYXPzs6uM1r/jFAohFAorLWtTZs2LdVE8hKmpqZq8UtMWg5dA9qN+l+7Uf9rN+p/QteAdlOn/m9oRP4ZWtjXSHp6evD29sa5c+dqbT937hx8fX2V1CpCCCGEEEIIIdqERuabYPHixfD390evXr3g4+ODnTt3Ijk5GfPnz1d20wghhBBCCCGEaAEK5ptg0qRJyM3NxZdffomMjAx07doVJ0+ehJOTk7KbRhogFAqxevXqOkseiPaga0C7Uf9rN+p/7Ub9T+ga0G6a2v9UZ54QQgghhBBCCFEztGaeEEIIIYQQQghRMxTME0IIIYQQQgghaoaCeUIIIYQQQgghRM1QME8IIYQQQgghhKgZCuYJIYQQQgghhBA1Q8E8UYqrV6/izTffhJ2dHXg8Ho4ePVpnH8YYPv/8c9jZ2cHAwACDBw9GVFRUg8dNTEzErFmz4OLiAgMDA7i6umL16tUQi8Xyfe7du4cpU6bAwcEBBgYGcHd3x6ZNmxo8bl5eHj788EN07twZhoaGcHR0xEcffYTCwsJGnZvIaGL/A8DYsWPh6OgIfX192Nrawt/fH+np6Yq/MVpEmddAbm4uRo0aBTs7OwiFQjg4OGDhwoUoKipq8NiVlZX48MMPYWFhASMjI4wdOxapqam19snPz4e/vz9EIhFEIhH8/f1RUFCg8PuiLTS1/9esWQNfX18YGhqiTZs2Cr8f2kYT+5/uARSnif0P0D1AY2jqNVBz3+7du4PH4yEiIuKl78eroGCeKEVpaSm6deuGrVu3vnCfdevW4bvvvsPWrVsREhICGxsbDB8+HMXFxS98TUxMDDiOw44dOxAVFYWNGzdi+/btWLlypXyf0NBQWFpa4tdff0VUVBRWrVqFFStWNNiW9PR0pKenY8OGDYiMjMSePXtw+vRpzJo1q1HnJjKa2P8A4Ofnh0OHDuHRo0f4888/ER8fjwkTJjTindEeyrwG+Hw+xo0bh+PHj+Px48fYs2cPzp8/j/nz5zfY5kWLFuHIkSMICgrC9evXUVJSgjFjxkAqlcr3effddxEREYHTp0/j9OnTiIiIgL+/fyPeGe2gqf0vFosxceJEvP/++414N7SPJvY/3QMoThP7H6B7gMbQ1GvgmU8//RR2dnYKvBPNgBGiZADYkSNHam3jOI7Z2NiwtWvXyrdVVFQwkUjEtm/f3qjjr1u3jrm4uDS4zwcffMD8/PwaddxDhw4xPT09JpFIXunc2k6T+//YsWOMx+MxsVjcqGNrG1W4BjZt2sTatWv3wp8XFBQwXV1dFhQUJN+WlpbG+Hw+O336NGOMsejoaAaA3bp1S75PcHAwA8BiYmIa1WZtoin9X1NgYCATiUSNaqe20sT+b8y5tZ0m9z/dAyhG066BkydPMjc3NxYVFcUAsPDw8Ea1t7FoZJ6opISEBGRmZmLEiBHybUKhEIMGDcLNmzcbdazCwkKYmZm98j71vcbU1BQ6OjrNelyiGf2fl5eH/fv3w9fXF7q6uo06NmndayA9PR2HDx/GoEGDXrhPaGgoJBJJrfbY2dmha9eu8vYEBwdDJBKhb9++8n369esHkUjU6DZrO3Xsf9J8NKX/6R6gaTSh/+ke4NWo6zWQlZWFOXPmYN++fTA0NGxUO5uKgnmikjIzMwEA1tbWtbZbW1vLf6aI+Ph4bNmypcGpM8HBwTh06BDmzZun8HFzc3Px1VdfNfgaRc5N6qfO/b9s2TIYGRnB3NwcycnJOHbsmMLHJf9ojWtgypQpMDQ0hL29PUxNTfHzzz832B49PT20bdv2he3JzMyElZVVnddaWVk1qs1EPfufNB9N6H+6B2g6de5/ugdoHup4DTDGMGPGDMyfPx+9evVSuI2vioJ5otJ4PF6tfzPG5Nvmz58PY2Nj+dfz0tPTMWrUKEycOBGzZ8+u9/hRUVEYN24cPvvsMwwfPlyhNhUVFWH06NHw8PDA6tWr691HkXOTl1PH/l+6dCnCw8Nx9uxZCAQCTJs2DYwxhY5N6mrJa2Djxo0ICwvD0aNHER8fj8WLFze6fTXbU19769uHKE7d+p80L3Xtf7oHaB7q2P90D9C81Oka2LJlC4qKirBixYpGH+eVtOgkfkIUgHrWysTHxzMALCwsrNb2sWPHsmnTpjHGGMvKymKxsbHyr5rS0tJYp06dmL+/P5NKpfWeNyoqillZWbGVK1cq3NaioiLm4+PDhg4dysrLy+vdR5Fzk39oWv/XlJKSwgCwmzdvKnwObaSsa6Cma9euMQAsPT293p9fuHCBAWB5eXm1tnt5ebHPPvuMMcbYrl276l0nLRKJ2O7du1/aBm2lKf1fE62ZV5ym9T/dAzSOpvV/TXQPoBhNuQbGjRvH+Hw+EwgE8i8ATCAQyNvcEmhknqgkFxcX2NjY4Ny5c/JtYrEYV65cga+vLwDZ1NUOHTrIv55JS0vD4MGD0bNnTwQGBoLPr3uZR0VFwc/PD9OnT8eaNWsUalNRURFGjBgBPT09HD9+HPr6+nX2UeTc5OXUtf+fx6qfxldWVip0DvKPlr4GnveyvvL29oaurm6t9mRkZODBgwfy9vj4+KCwsBB37tyR73P79m0UFhbK9yGKUcf+J81HXfuf7gGah7r2f2OPS15MHa+BzZs34969e4iIiEBERAROnjwJADh48KDC95pN0mKPCQhpQHFxMQsPD2fh4eEMAPvuu+9YeHg4S0pKku+zdu1aJhKJ2OHDh1lkZCSbMmUKs7W1ZUVFRS88blpaGuvQoQMbMmQIS01NZRkZGfKvZx48eMAsLS3Z1KlTa/08Ozv7hcctKipiffv2ZZ6eniwuLq7W66qqqhQ+N5HRxP6/ffs227JlCwsPD2eJiYns4sWLbMCAAczV1ZVVVFQ0w7umWZR5DZw4cYLt3r2bRUZGsoSEBHbixAnWpUsX1r9//wbbPH/+fNauXTt2/vx5FhYWxoYMGcK6desmvwYYY2zUqFHMy8uLBQcHs+DgYObp6cnGjBnzCu+UZtLU/k9KSmLh4eHsiy++YMbGxvL/Y3Fx8Su8W5pHE/uf7gEUp4n9T/cAjaOJ18DzEhISWiWbPQXzRCkuXbrEANT5mj59unwfjuPY6tWrmY2NDRMKhWzgwIEsMjKyweMGBgbWe9yaz61Wr15d78+dnJwa3V4ALCEhQeFzExlN7P/79+8zPz8/ZmZmxoRCIXN2dmbz589nqampr/JWaSxlXgMXL15kPj4+TCQSMX19fdaxY0e2bNkylp+f3+Cxy8vL2cKFC5mZmRkzMDBgY8aMYcnJybX2yc3NZVOnTmUmJibMxMSETZ069aXH1Uaa2v/Tp0+v99yXLl1q7Fuk0TSx/+keQHGa2P90D9A4mngNPK+1gnkeY5SVgRBCCCGEEEIIUSe0mIcQQgghhBBCCFEzFMwTQgghhBBCCCFqhoJ5QgghhBBCCCFEzVAwTwghhBBCCCGEqBkK5gkhhBBCCCGEEDVDwTwhhBBCCCGEEKJmKJgnhBBCCCGEEELUDAXzhBBCCCGEEEKImqFgnhBCCCGEEEIIUTMUzBNCCCGEEEIIIWqGgnlCCCGEEEIIIUTN/D8g4RKDq2nlMgAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 1000x500 with 2 Axes>"
       ]
@@ -1482,18 +1526,18 @@
    "source": [
     "fig, ax = plt.subplots(2, 1, figsize=(10, 5), constrained_layout=True)\n",
     "ax[0].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"peak_wave_direction\"],\n",
     "    \".-\",\n",
     ")\n",
-    "ax[0].set(ylabel=\"Peak Wave Direction\\n[deg CW from N]\")\n",
+    "ax[0].set(ylim=(-180, 180), ylabel=\"Peak Wave Direction\\n[deg CW from N]\")\n",
     "\n",
     "ax[1].plot(\n",
-    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"time_psd\"],\n",
     "    ds_waves_avg[\"peak_wave_spread\"],\n",
     "    \".-\",\n",
     ")\n",
-    "ax[1].set(ylabel=\"Peak Wave Spread [deg]\")"
+    "ax[1].set(ylim=(0, 90), ylabel=\"Peak Wave Spread [deg]\")"
    ]
   },
   {
diff --git a/examples/adv_example.ipynb b/examples/adv_example.ipynb
index b497a8635..d0eb0d83c 100644
--- a/examples/adv_example.ipynb
+++ b/examples/adv_example.ipynb
@@ -108,9 +108,7 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
        "  --xr-font-color0: var(\n",
@@ -189,6 +187,7 @@
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -211,11 +210,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -224,6 +230,8 @@
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
        "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -234,6 +242,7 @@
        "  display: inline-block;\n",
        "  opacity: 0;\n",
        "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
@@ -292,7 +301,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -302,6 +310,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -309,6 +318,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -547,7 +582,7 @@
        "  * x2                   (x2) int32 12B 1 2 3\n",
        "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
        "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "Data variables: (12/17)\n",
+       "Data variables: (12/16)\n",
        "    beam2inst_orientmat  (x1, x2) float64 72B 2.575 -1.305 ... 0.3582 0.3455\n",
        "    batt                 (time) float32 864kB 13.4 13.4 13.4 ... nan nan nan\n",
        "    c_sound              (time) float32 864kB 1.477e+03 1.477e+03 ... nan nan\n",
@@ -555,12 +590,12 @@
        "    pitch                (time) float32 864kB 0.0 0.0 0.0 0.0 ... nan nan nan\n",
        "    roll                 (time) float32 864kB 0.0 0.0 0.0 0.0 ... nan nan nan\n",
        "    ...                   ...\n",
+       "    vel                  (dir, time) float32 3MB -0.034 -0.043 ... 0.075 0.082\n",
        "    amp                  (beam, time) uint8 648kB 84 93 104 103 ... 106 106 95\n",
        "    corr                 (beam, time) uint8 648kB 94 98 98 97 99 ... 95 97 97 92\n",
        "    accel                (dir, time) float32 3MB 9.53 9.536 ... -1.229 -1.219\n",
        "    angrt                (dir, time) float32 3MB 0.000111 ... -0.0005012\n",
        "    orientmat            (earth, inst, time) float32 8MB 0.1533 ... -0.1279\n",
-       "    pressure             (time) float32 864kB 8.865 8.869 8.86 ... 7.073 7.073\n",
        "Attributes: (12/42)\n",
        "    inst_make:                   Nortek\n",
        "    inst_model:                  Vector\n",
@@ -574,36 +609,37 @@
        "    duty_cycle_description:      300.0 second bursts collected at 32.0 Hz, wi...\n",
        "    fs:                          32.0\n",
        "    coord_sys:                   inst\n",
-       "    has_imu:                     1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9186d64b-b865-42cc-a908-89f87d0ed3ef' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9186d64b-b865-42cc-a908-89f87d0ed3ef' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 216039</li><li><span class='xr-has-index'>beam</span>: 3</li><li><span class='xr-has-index'>dir</span>: 3</li><li><span class='xr-has-index'>x1</span>: 3</li><li><span class='xr-has-index'>x2</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-49402275-9697-459b-9c64-9097a1e809b9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-49402275-9697-459b-9c64-9097a1e809b9' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-02-25T10:00:03.587208032 .....</div><input id='attrs-eff3ac2f-0af3-46e6-9a1b-00994e1407c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eff3ac2f-0af3-46e6-9a1b-00994e1407c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b5504c7-f21e-44cf-9ac4-59343399fd1c' class='xr-var-data-in' type='checkbox'><label for='data-1b5504c7-f21e-44cf-9ac4-59343399fd1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2025-02-25T10:00:03.587208032&#x27;, &#x27;2025-02-25T10:00:03.618207931&#x27;,\n",
+       "    has_imu:                     1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4b5393f3-a94e-412a-8a12-4f798c82ca2c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4b5393f3-a94e-412a-8a12-4f798c82ca2c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 216039</li><li><span class='xr-has-index'>beam</span>: 3</li><li><span class='xr-has-index'>dir</span>: 3</li><li><span class='xr-has-index'>x1</span>: 3</li><li><span class='xr-has-index'>x2</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d5e0bb5b-f6c5-4b9a-8244-2b608a165836' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5e0bb5b-f6c5-4b9a-8244-2b608a165836' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2025-02-25T10:00:03.587208032 .....</div><input id='attrs-fafc6aea-9f63-4b5e-b199-68793d0107a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fafc6aea-9f63-4b5e-b199-68793d0107a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbd96772-4886-4e7d-b4b8-2b95b773aece' class='xr-var-data-in' type='checkbox'><label for='data-cbd96772-4886-4e7d-b4b8-2b95b773aece' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2025-02-25T10:00:03.587208032&#x27;, &#x27;2025-02-25T10:00:03.618207931&#x27;,\n",
        "       &#x27;2025-02-25T10:00:03.649207830&#x27;, ..., &#x27;2025-02-25T17:22:33.502970933&#x27;,\n",
        "       &#x27;2025-02-25T17:22:33.533971071&#x27;, &#x27;2025-02-25T17:22:33.564970970&#x27;],\n",
-       "      shape=(216039,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-d3769759-8b33-4440-b664-424be3f6a136' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3769759-8b33-4440-b664-424be3f6a136' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aad9ef2-f664-46a9-9b09-9cfbe244cf29' class='xr-var-data-in' type='checkbox'><label for='data-3aad9ef2-f664-46a9-9b09-9cfbe244cf29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-c20bd223-457c-4725-a7e2-7907937bf51e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c20bd223-457c-4725-a7e2-7907937bf51e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18a77b6f-a9fa-464c-a931-a3d42d9c4096' class='xr-var-data-in' type='checkbox'><label for='data-18a77b6f-a9fa-464c-a931-a3d42d9c4096' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>inst</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-9531ef32-2f78-4994-a414-b5145b8b8a70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9531ef32-2f78-4994-a414-b5145b8b8a70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-962d69db-4cd8-4348-b7ab-828e64130f02' class='xr-var-data-in' type='checkbox'><label for='data-962d69db-4cd8-4348-b7ab-828e64130f02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-462cc399-321e-41a0-bcd1-3e434618547a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-462cc399-321e-41a0-bcd1-3e434618547a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50dbbc40-296a-45b6-9f34-9aa5280be69a' class='xr-var-data-in' type='checkbox'><label for='data-50dbbc40-296a-45b6-9f34-9aa5280be69a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-3ba1208a-637f-4084-ab52-a62e69715ec4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ba1208a-637f-4084-ab52-a62e69715ec4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0f634a5-5d0e-4a42-af6d-c0c6b18721e9' class='xr-var-data-in' type='checkbox'><label for='data-c0f634a5-5d0e-4a42-af6d-c0c6b18721e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-accda159-01c2-47bc-9b9a-961b6bd24148' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-accda159-01c2-47bc-9b9a-961b6bd24148' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8fd4399-07bf-41a2-a616-3ba9294c8d46' class='xr-var-data-in' type='checkbox'><label for='data-b8fd4399-07bf-41a2-a616-3ba9294c8d46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dff74e9-7f8c-4938-b311-3d75825c109e' class='xr-section-summary-in' type='checkbox'  ><label for='section-8dff74e9-7f8c-4938-b311-3d75825c109e' class='xr-section-summary' >Data variables: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.575 -1.305 ... 0.3582 0.3455</div><input id='attrs-703132a7-060e-40d7-80ea-9c1c194b616e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-703132a7-060e-40d7-80ea-9c1c194b616e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c98e53b5-781b-4e70-a978-374e6337b474' class='xr-var-data-in' type='checkbox'><label for='data-c98e53b5-781b-4e70-a978-374e6337b474' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 2.57543945, -1.3046875 , -1.25878906],\n",
+       "      shape=(216039,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-42bbc816-d6b1-4ff2-92df-bbc3708eeec5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42bbc816-d6b1-4ff2-92df-bbc3708eeec5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13a313ef-1bc9-4a34-8888-1d36c7e771fa' class='xr-var-data-in' type='checkbox'><label for='data-13a313ef-1bc9-4a34-8888-1d36c7e771fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-ef3f4aab-ea83-47aa-9eb1-79e202bb39e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef3f4aab-ea83-47aa-9eb1-79e202bb39e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-397ee9bf-470f-4bbc-ae63-fd8284588539' class='xr-var-data-in' type='checkbox'><label for='data-397ee9bf-470f-4bbc-ae63-fd8284588539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>inst</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-d6cea542-05df-4dfb-8a49-0e0d9eae235c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6cea542-05df-4dfb-8a49-0e0d9eae235c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bec94053-73b9-411d-b2f0-8f1c41e7542f' class='xr-var-data-in' type='checkbox'><label for='data-bec94053-73b9-411d-b2f0-8f1c41e7542f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-c274cc6a-c86a-4256-a8bd-2ecabf4ba00a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c274cc6a-c86a-4256-a8bd-2ecabf4ba00a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cd0c068-6bfb-4c9d-b445-b17e36c68510' class='xr-var-data-in' type='checkbox'><label for='data-6cd0c068-6bfb-4c9d-b445-b17e36c68510' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-08ca5061-7e38-4fcc-9c14-c0d43d8c13a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08ca5061-7e38-4fcc-9c14-c0d43d8c13a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30db0d58-ca31-4193-911d-56059a69116d' class='xr-var-data-in' type='checkbox'><label for='data-30db0d58-ca31-4193-911d-56059a69116d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-e1b67d8c-07f9-441b-8cee-3b283d46eac5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1b67d8c-07f9-441b-8cee-3b283d46eac5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6304748-8efa-4d2f-987a-21f5432bbb06' class='xr-var-data-in' type='checkbox'><label for='data-a6304748-8efa-4d2f-987a-21f5432bbb06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1df3977-bef9-465d-a677-605b43314827' class='xr-section-summary-in' type='checkbox'  ><label for='section-f1df3977-bef9-465d-a677-605b43314827' class='xr-section-summary' >Data variables: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.575 -1.305 ... 0.3582 0.3455</div><input id='attrs-ff3a7ca4-5f29-41ec-82ef-e14c1e7c75a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff3a7ca4-5f29-41ec-82ef-e14c1e7c75a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03789d13-c7fd-4a78-9e68-d7f54489768a' class='xr-var-data-in' type='checkbox'><label for='data-03789d13-c7fd-4a78-9e68-d7f54489768a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 2.57543945, -1.3046875 , -1.25878906],\n",
        "       [-0.02807617,  2.33764648, -2.31494141],\n",
-       "       [ 0.32958984,  0.3581543 ,  0.34545898]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.4 13.4 13.4 13.4 ... nan nan nan</div><input id='attrs-9fbc3a68-a119-428a-b5e0-4884f07aed8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fbc3a68-a119-428a-b5e0-4884f07aed8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91211106-919d-4fb9-8526-aa0c9624b0c2' class='xr-var-data-in' type='checkbox'><label for='data-91211106-919d-4fb9-8526-aa0c9624b0c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd></dl></div><div class='xr-var-data'><pre>array([13.400001, 13.400001, 13.400001, ...,       nan,       nan,\n",
-       "             nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.477e+03 1.477e+03 ... nan nan</div><input id='attrs-08f5c789-30e6-4957-a092-0111aab90a02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08f5c789-30e6-4957-a092-0111aab90a02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e40162e-fc57-4ab4-ba56-4741fe6b2a87' class='xr-var-data-in' type='checkbox'><label for='data-2e40162e-fc57-4ab4-ba56-4741fe6b2a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1476.8, 1476.8, 1476.8, ...,    nan,    nan,    nan],\n",
-       "      shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-696a27c2-0b75-4e07-aad9-d514c4d988df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-696a27c2-0b75-4e07-aad9-d514c4d988df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f507ce9f-f2a9-4bf8-9e7d-a8f7f0e0d8ae' class='xr-var-data-in' type='checkbox'><label for='data-f507ce9f-f2a9-4bf8-9e7d-a8f7f0e0d8ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-6d793d89-3908-4e9c-93fb-b463fc26b963' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d793d89-3908-4e9c-93fb-b463fc26b963' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1e564d3-b960-4bb9-ab01-df67b4f075fe' class='xr-var-data-in' type='checkbox'><label for='data-e1e564d3-b960-4bb9-ab01-df67b4f075fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-2714a71d-7966-4693-bc13-3e7177d1606f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2714a71d-7966-4693-bc13-3e7177d1606f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f29a596-9898-4616-a54f-d16f41ffd7c4' class='xr-var-data-in' type='checkbox'><label for='data-7f29a596-9898-4616-a54f-d16f41ffd7c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>7.51 7.51 7.51 7.51 ... nan nan nan</div><input id='attrs-7f1c6a3b-3cbf-4764-9478-b56c84c25ca6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f1c6a3b-3cbf-4764-9478-b56c84c25ca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f96a993e-4d5f-4406-b138-052df6351aa9' class='xr-var-data-in' type='checkbox'><label for='data-f96a993e-4d5f-4406-b138-052df6351aa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([7.5099998, 7.5099998, 7.5099998, ...,       nan,       nan,\n",
-       "             nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-51161105-e083-4022-b1b1-b28cc6a38d38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51161105-e083-4022-b1b1-b28cc6a38d38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbfc8b23-634a-4037-8159-796637a6920c' class='xr-var-data-in' type='checkbox'><label for='data-bbfc8b23-634a-4037-8159-796637a6920c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(216039,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>112 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0</div><input id='attrs-e3db266f-7865-4291-9bb5-7ffa423e1d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3db266f-7865-4291-9bb5-7ffa423e1d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-262740b5-afdc-49da-baa8-481ebd33832d' class='xr-var-data-in' type='checkbox'><label for='data-262740b5-afdc-49da-baa8-481ebd33832d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([112,   0,   0, ...,   0,   0,   0], shape=(216039,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientation_down</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-db0c387e-c000-407c-969b-4f529c88dbd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db0c387e-c000-407c-969b-4f529c88dbd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a813a6fa-6ab8-4084-8054-d73a7c7201c0' class='xr-var-data-in' type='checkbox'><label for='data-a813a6fa-6ab8-4084-8054-d73a7c7201c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation of ADV Communication Cable</dd></dl></div><div class='xr-var-data'><pre>array([False, False, False, ..., False, False, False], shape=(216039,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.034 -0.043 ... 0.075 0.082</div><input id='attrs-94a03591-2a9b-4716-8679-a01998138cc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94a03591-2a9b-4716-8679-a01998138cc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d33f4988-79d8-4631-a2c4-e058057fb41b' class='xr-var-data-in' type='checkbox'><label for='data-d33f4988-79d8-4631-a2c4-e058057fb41b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-3.4000002e-02, -4.3000001e-02, -3.3000000e-02, ...,\n",
+       "       [ 0.32958984,  0.3581543 ,  0.34545898]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.4 13.4 13.4 13.4 ... nan nan nan</div><input id='attrs-3422a17d-c9fa-413d-a842-fa96d223ceec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3422a17d-c9fa-413d-a842-fa96d223ceec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11e10126-4f62-49b6-8558-68d42fd87006' class='xr-var-data-in' type='checkbox'><label for='data-11e10126-4f62-49b6-8558-68d42fd87006' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd></dl></div><div class='xr-var-data'><pre>array([13.400001, 13.400001, 13.400001, ...,       nan,       nan,\n",
+       "             nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.477e+03 1.477e+03 ... nan nan</div><input id='attrs-a715a354-0c41-4d70-bcb9-3be45bbaee23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a715a354-0c41-4d70-bcb9-3be45bbaee23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e318cd15-6711-45e6-9c0d-d16399cf2b99' class='xr-var-data-in' type='checkbox'><label for='data-e318cd15-6711-45e6-9c0d-d16399cf2b99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1476.8, 1476.8, 1476.8, ...,    nan,    nan,    nan],\n",
+       "      shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-5cb2af55-0336-4ce4-b321-4ffe3adc3dc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5cb2af55-0336-4ce4-b321-4ffe3adc3dc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49b17d4f-4788-427a-8dc9-eec7c06077c7' class='xr-var-data-in' type='checkbox'><label for='data-49b17d4f-4788-427a-8dc9-eec7c06077c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-731580d7-9b16-4e2c-98a8-8ce4f0418fc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-731580d7-9b16-4e2c-98a8-8ce4f0418fc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07b0462f-aa79-4bac-a253-29b37adf6101' class='xr-var-data-in' type='checkbox'><label for='data-07b0462f-aa79-4bac-a253-29b37adf6101' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... nan nan nan nan</div><input id='attrs-0f730a7c-8052-44f2-a98e-7fa7642686d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f730a7c-8052-44f2-a98e-7fa7642686d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad86bcd8-1377-4650-97d5-0482c314bd70' class='xr-var-data-in' type='checkbox'><label for='data-ad86bcd8-1377-4650-97d5-0482c314bd70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0., ..., nan, nan, nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>7.51 7.51 7.51 7.51 ... nan nan nan</div><input id='attrs-9dc4ffa4-6441-48fa-8663-52d09f4d29b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dc4ffa4-6441-48fa-8663-52d09f4d29b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28d33a53-0954-4b5e-b686-f84609fd0781' class='xr-var-data-in' type='checkbox'><label for='data-28d33a53-0954-4b5e-b686-f84609fd0781' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([7.5099998, 7.5099998, 7.5099998, ...,       nan,       nan,\n",
+       "             nan], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-d8a3dc5d-af89-4381-9df8-90812359b847' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8a3dc5d-af89-4381-9df8-90812359b847' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b3c9caa-0d17-4fc3-998d-74e3cdba33be' class='xr-var-data-in' type='checkbox'><label for='data-9b3c9caa-0d17-4fc3-998d-74e3cdba33be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(216039,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>112 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0</div><input id='attrs-acbff165-98a3-4e60-9963-514b570bb3d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acbff165-98a3-4e60-9963-514b570bb3d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca495460-2ee3-45aa-93c3-c74f787e8155' class='xr-var-data-in' type='checkbox'><label for='data-ca495460-2ee3-45aa-93c3-c74f787e8155' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([112,   0,   0, ...,   0,   0,   0], shape=(216039,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.865 8.869 8.86 ... 7.073 7.073</div><input id='attrs-e5fa83a0-27d7-433c-be58-2b88c9db2e24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5fa83a0-27d7-433c-be58-2b88c9db2e24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e699d3b-3e2b-476f-b15c-2f209a7bca5c' class='xr-var-data-in' type='checkbox'><label for='data-8e699d3b-3e2b-476f-b15c-2f209a7bca5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([8.865001 , 8.869    , 8.860001 , ..., 7.0680003, 7.0730004,\n",
+       "       7.0730004], shape=(216039,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.034 -0.043 ... 0.075 0.082</div><input id='attrs-33cb36eb-732e-45d4-98e2-dec6bed64e8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33cb36eb-732e-45d4-98e2-dec6bed64e8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c71ac85-17e6-420e-ba99-0d4eac55f3cb' class='xr-var-data-in' type='checkbox'><label for='data-1c71ac85-17e6-420e-ba99-0d4eac55f3cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-3.4000002e-02, -4.3000001e-02, -3.3000000e-02, ...,\n",
        "         1.1380000e+00,  1.0910001e+00,  1.0620000e+00],\n",
        "       [ 2.0000001e-03,  0.0000000e+00,  0.0000000e+00, ...,\n",
        "         2.5100002e-01,  1.9200000e-01,  1.5800001e-01],\n",
        "       [-1.0000000e-03, -6.0000001e-03, -7.0000002e-03, ...,\n",
        "         8.4000006e-02,  7.5000003e-02,  8.2000002e-02]],\n",
-       "      shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>84 93 104 103 ... 106 106 106 95</div><input id='attrs-32e26ac8-431b-4585-95a0-032f9bbbc32d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32e26ac8-431b-4585-95a0-032f9bbbc32d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0363d896-6753-43b4-ad17-793eae97a1ad' class='xr-var-data-in' type='checkbox'><label for='data-0363d896-6753-43b4-ad17-793eae97a1ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 84,  93, 104, ..., 110,  99, 102],\n",
+       "      shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>84 93 104 103 ... 106 106 106 95</div><input id='attrs-a487cc2a-c549-4089-872b-83c855bd2365' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a487cc2a-c549-4089-872b-83c855bd2365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b90a150f-ee9e-4a6d-bb81-5c0ac43a4ed3' class='xr-var-data-in' type='checkbox'><label for='data-b90a150f-ee9e-4a6d-bb81-5c0ac43a4ed3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 84,  93, 104, ..., 110,  99, 102],\n",
        "       [ 89,  93,  93, ..., 101,  98,  92],\n",
        "       [ 96, 101,  99, ..., 106, 106,  95]],\n",
-       "      shape=(3, 216039), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>94 98 98 97 99 ... 95 95 97 97 92</div><input id='attrs-f4c10bea-8188-4239-9107-6ae1e469d080' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4c10bea-8188-4239-9107-6ae1e469d080' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81c68f19-1008-4f72-83d1-feeb6f7b0714' class='xr-var-data-in' type='checkbox'><label for='data-81c68f19-1008-4f72-83d1-feeb6f7b0714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd></dl></div><div class='xr-var-data'><pre>array([[94, 98, 98, ..., 94, 98, 97],\n",
+       "      shape=(3, 216039), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>94 98 98 97 99 ... 95 95 97 97 92</div><input id='attrs-c05dcb9e-2d04-47e0-805c-625d30499b19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c05dcb9e-2d04-47e0-805c-625d30499b19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5199e7fa-ed11-4726-b520-7708827366f0' class='xr-var-data-in' type='checkbox'><label for='data-5199e7fa-ed11-4726-b520-7708827366f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd></dl></div><div class='xr-var-data'><pre>array([[94, 98, 98, ..., 94, 98, 97],\n",
        "       [99, 99, 99, ..., 98, 93, 96],\n",
-       "       [98, 99, 99, ..., 97, 97, 92]], shape=(3, 216039), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.53 9.536 9.526 ... -1.229 -1.219</div><input id='attrs-8313f6d6-55fe-49c2-84ca-3da6a337db35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8313f6d6-55fe-49c2-84ca-3da6a337db35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75f65cb0-8618-419f-8738-e63a7604c3e9' class='xr-var-data-in' type='checkbox'><label for='data-75f65cb0-8618-419f-8738-e63a7604c3e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[ 9.530013  ,  9.536455  ,  9.525976  , ...,  9.601015  ,\n",
+       "       [98, 99, 99, ..., 97, 97, 92]], shape=(3, 216039), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.53 9.536 9.526 ... -1.229 -1.219</div><input id='attrs-b554f8ba-bce7-41a5-9aab-8eea7591e81e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b554f8ba-bce7-41a5-9aab-8eea7591e81e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-960b2368-5142-48dd-9fc0-176bb1782ffc' class='xr-var-data-in' type='checkbox'><label for='data-960b2368-5142-48dd-9fc0-176bb1782ffc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[ 9.530013  ,  9.536455  ,  9.525976  , ...,  9.601015  ,\n",
        "         9.597994  ,  9.593181  ],\n",
        "       [ 1.0119547 ,  1.0139961 ,  1.0076023 , ...,  0.996303  ,\n",
        "         0.9979168 ,  0.99355274],\n",
        "       [-1.1934966 , -1.1835487 , -1.1902841 , ..., -1.2235923 ,\n",
-       "        -1.2292643 , -1.2193956 ]], shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000111 0.0004271 ... -0.0005012</div><input id='attrs-eff92a37-a78c-4330-86d8-1c72202f9aa1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eff92a37-a78c-4330-86d8-1c72202f9aa1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10fcd485-cfac-40d7-ad84-95d75ab86cdf' class='xr-var-data-in' type='checkbox'><label for='data-10fcd485-cfac-40d7-ad84-95d75ab86cdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00011099,  0.00042707, -0.00056194, ..., -0.00380341,\n",
+       "        -1.2292643 , -1.2193956 ]], shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000111 0.0004271 ... -0.0005012</div><input id='attrs-d66abc60-d067-4f0c-9252-ca01559da6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d66abc60-d067-4f0c-9252-ca01559da6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36c6fc98-c701-4e77-ad11-319d49830af8' class='xr-var-data-in' type='checkbox'><label for='data-36c6fc98-c701-4e77-ad11-319d49830af8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00011099,  0.00042707, -0.00056194, ..., -0.00380341,\n",
        "        -0.00334683, -0.00371215],\n",
        "       [-0.00019397, -0.00023042, -0.00117751, ..., -0.00171529,\n",
        "        -0.00122215, -0.00037502],\n",
        "       [-0.00022086, -0.00021133,  0.0006542 , ..., -0.00037107,\n",
-       "        -0.00060423, -0.00050117]], shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1533 0.1533 ... -0.128 -0.1279</div><input id='attrs-81336e5e-38b8-4c77-b35f-05167ea062ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81336e5e-38b8-4c77-b35f-05167ea062ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-968c5f71-43ce-4b01-9678-a579235367ee' class='xr-var-data-in' type='checkbox'><label for='data-968c5f71-43ce-4b01-9678-a579235367ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.15330946,  0.15328561,  0.1532521 , ...,  0.16398108,\n",
+       "        -0.00060423, -0.00050117]], shape=(3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1533 0.1533 ... -0.128 -0.1279</div><input id='attrs-4bc9910f-5bfa-4f2b-9a72-c2c9db2ee017' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bc9910f-5bfa-4f2b-9a72-c2c9db2ee017' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1782b33-5850-42de-9113-885b1f1c8618' class='xr-var-data-in' type='checkbox'><label for='data-f1782b33-5850-42de-9113-885b1f1c8618' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.15330946,  0.15328561,  0.1532521 , ...,  0.16398108,\n",
        "          0.164008  ,  0.16400433],\n",
        "        [-0.06399706, -0.06394877, -0.06394862, ..., -0.0096143 ,\n",
        "         -0.00960174, -0.00956409],\n",
@@ -622,29 +658,7 @@
        "        [-0.88791287, -0.8878246 , -0.88774526, ..., -0.6709966 ,\n",
        "         -0.6710047 , -0.67098564],\n",
        "        [-0.12639016, -0.12635832, -0.12636189, ..., -0.12795062,\n",
-       "         -0.12796111, -0.1279361 ]]], shape=(3, 3, 216039), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.865 8.869 8.86 ... 7.073 7.073</div><input id='attrs-0ed78f99-057c-4dc3-9d4c-526b9acce917' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ed78f99-057c-4dc3-9d4c-526b9acce917' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb3f29c5-3399-43e9-bb40-4b10c57fee12' class='xr-var-data-in' type='checkbox'><label for='data-eb3f29c5-3399-43e9-bb40-4b10c57fee12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([8.865, 8.869, 8.86 , ..., 7.068, 7.073, 7.073],\n",
-       "      shape=(216039,), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1c5324d0-dedb-4b2d-8a50-30fa86a36c6a' class='xr-section-summary-in' type='checkbox'  ><label for='section-1c5324d0-dedb-4b2d-8a50-30fa86a36c6a' class='xr-section-summary' >Indexes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b4658096-4005-4418-9701-61d9d31fd850' class='xr-index-data-in' type='checkbox'/><label for='index-b4658096-4005-4418-9701-61d9d31fd850' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2025-02-25 10:00:03.587208032&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.618207931&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.649207830&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.680207967&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.711207866&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.742207765&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.773207664&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.804207563&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.835207462&#x27;,\n",
-       "               &#x27;2025-02-25 10:00:03.866207599&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2025-02-25 17:22:33.285971164&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.316971302&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.347971200&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.378971099&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.409970998&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.440971136&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.471971035&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.502970933&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.533971071&#x27;,\n",
-       "               &#x27;2025-02-25 17:22:33.564970970&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=216039, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-efd01a09-807d-4e7d-bbe0-727eef21bdc6' class='xr-index-data-in' type='checkbox'/><label for='index-efd01a09-807d-4e7d-bbe0-727eef21bdc6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-51013bab-9732-4ef4-a4be-0535f1430381' class='xr-index-data-in' type='checkbox'/><label for='index-51013bab-9732-4ef4-a4be-0535f1430381' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e769141e-b98e-44fd-8b97-9174a4b58f02' class='xr-index-data-in' type='checkbox'/><label for='index-e769141e-b98e-44fd-8b97-9174a4b58f02' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b1f2b53a-f25b-4fb5-9424-fbc0addb8094' class='xr-index-data-in' type='checkbox'/><label for='index-b1f2b53a-f25b-4fb5-9424-fbc0addb8094' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-ddb448d1-2a7c-4fe0-8f27-a1c3a494b559' class='xr-index-data-in' type='checkbox'/><label for='index-ddb448d1-2a7c-4fe0-8f27-a1c3a494b559' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f1d010a6-4a8f-48f2-a0ac-8922cc64b60f' class='xr-index-data-in' type='checkbox'/><label for='index-f1d010a6-4a8f-48f2-a0ac-8922cc64b60f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44785129-9e06-4e10-8633-4f6a2e5448af' class='xr-section-summary-in' type='checkbox'  ><label for='section-44785129-9e06-4e10-8633-4f6a2e5448af' class='xr-section-summary' >Attributes: <span>(42)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_model :</span></dt><dd>Vector</dd><dt><span>inst_type :</span></dt><dd>ADV</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;angrt&#x27;]</dd><dt><span>n_beams :</span></dt><dd>3</dd><dt><span>profile_mode :</span></dt><dd>continuous</dd><dt><span>burst_mode :</span></dt><dd>True</dd><dt><span>power_level :</span></dt><dd>1</dd><dt><span>sync_out_pos :</span></dt><dd>end</dd><dt><span>sample_on_sync :</span></dt><dd>False</dd><dt><span>start_on_sync :</span></dt><dd>False</dd><dt><span>compass_update_rate :</span></dt><dd>1</dd><dt><span>n_bins :</span></dt><dd>1</dd><dt><span>deployment_name :</span></dt><dd>VIV</dd><dt><span>wrap_mode :</span></dt><dd>False</dd><dt><span>analog_in :</span></dt><dd>0</dd><dt><span>software_version :</span></dt><dd>2.00.02</dd><dt><span>salinity :</span></dt><dd>32.0</dd><dt><span>comments :</span></dt><dd>VIV deployment Feb2025 Time in PST </dd><dt><span>user_specified_sound_speed :</span></dt><dd>False</dd><dt><span>analog_output :</span></dt><dd>False</dd><dt><span>output_format :</span></dt><dd>Vector</dd><dt><span>serial_output :</span></dt><dd>False</dd><dt><span>power_output_analog :</span></dt><dd>False</dd><dt><span>n_pings_per_burst :</span></dt><dd>1</dd><dt><span>pressure_sensor :</span></dt><dd>yes</dd><dt><span>compass :</span></dt><dd>no</dd><dt><span>tilt_sensor :</span></dt><dd>no</dd><dt><span>carrier_freq_kHz :</span></dt><dd>6000</dd><dt><span>serial_number :</span></dt><dd>VEC14837</dd><dt><span>ProLogFWver :</span></dt><dd>4.13</dd><dt><span>PIC_version :</span></dt><dd>0</dd><dt><span>hardware_rev :</span></dt><dd>4</dd><dt><span>recorder_size_bytes :</span></dt><dd>3037724672</dd><dt><span>vel_range :</span></dt><dd>normal</dd><dt><span>firmware_version :</span></dt><dd>3.43</dd><dt><span>duty_cycle_n_burst :</span></dt><dd>9600</dd><dt><span>duty_cycle_interval :</span></dt><dd>1200</dd><dt><span>duty_cycle_description :</span></dt><dd>300.0 second bursts collected at 32.0 Hz, with bursts taken every 20.0 minutes</dd><dt><span>fs :</span></dt><dd>32.0</dd><dt><span>coord_sys :</span></dt><dd>inst</dd><dt><span>has_imu :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
+       "         -0.12796111, -0.1279361 ]]], shape=(3, 3, 216039), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f093a3f-f223-40c2-98e4-9acedd891c79' class='xr-section-summary-in' type='checkbox'  ><label for='section-5f093a3f-f223-40c2-98e4-9acedd891c79' class='xr-section-summary' >Attributes: <span>(42)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_model :</span></dt><dd>Vector</dd><dt><span>inst_type :</span></dt><dd>ADV</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;angrt&#x27;]</dd><dt><span>n_beams :</span></dt><dd>3</dd><dt><span>profile_mode :</span></dt><dd>continuous</dd><dt><span>burst_mode :</span></dt><dd>burst</dd><dt><span>power_level :</span></dt><dd>1</dd><dt><span>sync_out_pos :</span></dt><dd>end</dd><dt><span>sample_on_sync :</span></dt><dd>False</dd><dt><span>start_on_sync :</span></dt><dd>False</dd><dt><span>compass_update_rate :</span></dt><dd>1</dd><dt><span>n_bins :</span></dt><dd>1</dd><dt><span>deployment_name :</span></dt><dd>VIV</dd><dt><span>wrap_mode :</span></dt><dd>False</dd><dt><span>analog_in :</span></dt><dd>0</dd><dt><span>software_version :</span></dt><dd>2.00.02</dd><dt><span>salinity :</span></dt><dd>32.0</dd><dt><span>comments :</span></dt><dd>VIV deployment Feb2025 Time in PST </dd><dt><span>user_specified_sound_speed :</span></dt><dd>False</dd><dt><span>analog_output :</span></dt><dd>False</dd><dt><span>serial_output :</span></dt><dd>False</dd><dt><span>power_output_analog :</span></dt><dd>False</dd><dt><span>n_burst :</span></dt><dd>9600</dd><dt><span>pressure_sensor :</span></dt><dd>yes</dd><dt><span>compass :</span></dt><dd>no</dd><dt><span>tilt_sensor :</span></dt><dd>no</dd><dt><span>orientation_down :</span></dt><dd>0</dd><dt><span>carrier_freq_kHz :</span></dt><dd>6000</dd><dt><span>serial_number :</span></dt><dd>VEC14837</dd><dt><span>ProLogFWver :</span></dt><dd>4.13</dd><dt><span>PIC_version :</span></dt><dd>0</dd><dt><span>hardware_rev :</span></dt><dd>4</dd><dt><span>recorder_size_bytes :</span></dt><dd>3037724672</dd><dt><span>vel_range :</span></dt><dd>normal</dd><dt><span>firmware_version :</span></dt><dd>3.43</dd><dt><span>duty_cycle_n_burst :</span></dt><dd>9600</dd><dt><span>duty_cycle_interval :</span></dt><dd>1200</dd><dt><span>duty_cycle_description :</span></dt><dd>300.0 second bursts collected at 32.0 Hz, with bursts taken every 20.0 minutes</dd><dt><span>fs :</span></dt><dd>32.0</dd><dt><span>coord_sys :</span></dt><dd>inst</dd><dt><span>has_imu :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 25MB\n",
@@ -658,7 +672,7 @@
        "  * x2                   (x2) int32 12B 1 2 3\n",
        "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
        "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
-       "Data variables: (12/17)\n",
+       "Data variables: (12/16)\n",
        "    beam2inst_orientmat  (x1, x2) float64 72B 2.575 -1.305 ... 0.3582 0.3455\n",
        "    batt                 (time) float32 864kB 13.4 13.4 13.4 ... nan nan nan\n",
        "    c_sound              (time) float32 864kB 1.477e+03 1.477e+03 ... nan nan\n",
@@ -666,12 +680,12 @@
        "    pitch                (time) float32 864kB 0.0 0.0 0.0 0.0 ... nan nan nan\n",
        "    roll                 (time) float32 864kB 0.0 0.0 0.0 0.0 ... nan nan nan\n",
        "    ...                   ...\n",
+       "    vel                  (dir, time) float32 3MB -0.034 -0.043 ... 0.075 0.082\n",
        "    amp                  (beam, time) uint8 648kB 84 93 104 103 ... 106 106 95\n",
        "    corr                 (beam, time) uint8 648kB 94 98 98 97 99 ... 95 97 97 92\n",
        "    accel                (dir, time) float32 3MB 9.53 9.536 ... -1.229 -1.219\n",
        "    angrt                (dir, time) float32 3MB 0.000111 ... -0.0005012\n",
        "    orientmat            (earth, inst, time) float32 8MB 0.1533 ... -0.1279\n",
-       "    pressure             (time) float32 864kB 8.865 8.869 8.86 ... 7.073 7.073\n",
        "Attributes: (12/42)\n",
        "    inst_make:                   Nortek\n",
        "    inst_model:                  Vector\n",
@@ -903,7 +917,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -993,13 +1007,22 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_28328\\1876082538.py:5: UserWarning: The PSD time coordinate differs from other VelBinner outputs when pct_overlap > 0. Timestamps represent the center of each overlapping sliding window (step=9600 samples, pct_overlap=0.5).\n",
+      "  ds_binned[\"auto_spectra\"] = binner.power_spectral_density(ds[\"vel\"], freq_units=\"Hz\", pct_overlap=0.5)\n"
+     ]
+    }
+   ],
    "source": [
     "# Calculate the variance of each variable in the dataset and add to the averaged dataset\n",
     "ds_binned = binner.bin_variance(ds, out_ds=ds_binned)\n",
     "\n",
     "# Calculate the power spectral density\n",
-    "ds_binned[\"auto_spectra\"] = binner.power_spectral_density(ds[\"vel\"], freq_units=\"Hz\")\n",
+    "ds_binned[\"auto_spectra\"] = binner.power_spectral_density(ds[\"vel\"], freq_units=\"Hz\", pct_overlap=0.5)\n",
     "\n",
     "# Calculate the cross power spectral densities\n",
     "ds_binned[\"cross_spectra\"] = binner.cross_spectral_density(\n",
@@ -1070,7 +1093,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1b22a9eec90>"
+       "<matplotlib.legend.Legend at 0x23d8ba015d0>"
       ]
      },
      "execution_count": 13,
@@ -1079,7 +1102,7 @@
     },
     {
      "data": {
-      "image/png": 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z6NGjpX1JDMMwTgcLf6bEUwB/+ukndO3aFUlJSRgwYIDo5MUwDMOUHCz8nZh9l+7gveUnsOtCXJ5pNEUJBfstWbIEdevWFXW4aQBAAwGGYRimZGDh74Rcu5uCCX8cwsM/78W8PVfw+C/7MHTGbmw8FVtigwDqAkj1t0NCQnD48GHhDmAYxnm5ffs2xo8fj8qVK4saIeHh4aIs+K5du0r70hwSDvhzIlIysvDj1ov4efslpGflQK0COtYKwd5Ld3Dk2n08Ne8/1A33wYSuNdGvUQVoaIdipHr16vj3339FwSTqA8AwjPNCDXkoDZi69tGzITY2Fps2bRId/5iih4W/E0Da/PIjMfh8zRncTEgT69pWD8R7AxqgfoQvbiem49edUZi/5zLO3EzEC38exjcbzmF85xoY0qwiXLXFZyBq27atKACkVrMRimGclfv372PHjh2iLn/nzp3FuipVqqB169Zinkr6jhkzxuJ9U6ZMwfvvvy9iicyh93PVP9uw8Hdwjl67jw9WnMShq/fFcqUAD7zbvx56Nwg3/GBCfNzwZt+6QtjP3X0Zc3ZHISouGa8vOYbpG8/h2c418HCrSLi7aIrlGpWCf8WKFdBoNJwCyDBFNPBPzUotlXN7aD2sCmVbLX1pWrZsmVAIzDvyUWZQnz59DMs0SBg5cqSoGULcuHHDpPMf7UtlxRnbsPB3UG4lpOGLtWex5FC0WPZ01Qhz/rgO1WwKcT9PF7zUoxbGdayGBfuuYNaOKMTEp2HKvyfx3eYLeKpjNTzRtgq83Yrnz2bjxo0YPHgwPD09sXPnTjRt2rRYzsMwzgIJ/jYL2pTKufc9tg+eLp527UuNeki7f/rppzFz5kw0b95cWACoJHjjxo3h4eEhJoLahZOr8NNPP0XPnj3FOooPkAc75D6gniuUVcTYhm2tDkZaZjZmbL2ArlO3GgT/g80rYsurXYTwt0d7J+H+TKca2PF6V3w0uAEq+nsgLilduA0e+Hwzpm04h3vJGUV+7fRj79atmxi5UxdAygRgGMY5IKFNab8UB0SaO2n3NAigQYFMfHy8yA6i58Nrr71mcYy3334be/bswfLlyw2DBcY6Kl1J5niVQYYOHSr+yLp3747Fixfn671yVz/6g/T19UVpQl/jupOx+HT1aVy9myLWNY30x5SB9dGsckChjp2ZnSNiBmhQcel2ssGSQFYAsgaE+rijKH1/ZMo7deqU0Py3b98OHx8f0+vJzBTNgsg14OLiUmTnZuyHv4Oyef/T0tIQFRUl2t+6u7uXG7O/LZ566ils2LBBtAanFuok9KltL7UJp8+n5Pfffxf70/OcXAfFSU5Ojnj+03O/NOKVzL/ngsglpzf7v/TSSxg7dqyIMC2vnLmZgA9XnMLui1JUbJivG97oUxdDmlaEuggi9l00agxrUQlDm1XE2hM38f2WCzh9I0FkDVCMwCOtIkXMgKdr4f+c/P39RQpgmzZtcOTIEWH2o1G8tf7dDMPkDglfe03vZZH69euLOADilVdewfHjx0V5cHOBR9o+CX4y9Re34HcUnP6J2qVLFzFSLI/cTc4QJvg/9l1Bjg4iKv+ZjtUxvksNeBWDX55S//o3roB+jcKx5ewtfL/5gggkpFoBWTk6fDq0UZGch2r+U+AfuQFIu3n55Zfx3XffFVqLYBimbELpfMOHDxeKGPn4ydpHQv7LL78UcUBz5swRzcCWLl0qngPUIIygIEEqEEYWXFIUqC6AvI0Ch6mOCFMOff5k8h04cCAiIiLEFy6PAJX88MMPQljQSJC0xf3798PRITP8nF1R6PLVFszfKwn+vg3DsWlSZ7zau06xCH4l9F10qxuGJePb48fHm4t1f+2/KqwBRQWl+JAZjyDTpZN7pxjGoSEhTs/vadOmoVOnTmjYsCEmT54sAgC///57YeYns/+gQYNQoUIFwzR16lScOXNG1AQg661yW6tWrUr7Y5VpyrTmT4FfTZo0EaPBBx980GqHuEmTJonoUPrDmT59uhj5nT17FqGhoWIf8htnZWVZvHf9+vViUJEf0tPTxaT0rcj+N5pKgh3n4/DJmrO4qPe91w3zxrv966JNtUDDtZQkPeoGo2+DMKw5GYsP/j2BeWNaFpmGTj/0vXv3olmzZuKHT5PyM5b0Z2WM8HdQNu8/LdNAmXzSNJUXKG7hk08+EZM1Zs+eLSZbyM8Gc4rrHuj0yoh8r0saOiedm75vsnAosfc3WW4C/kigkMlnyJAhhnUk8Gl0RyND+YZERkbihRdewJtvvmn3scnsT8fIK+CPikl88MEHFusXLFgg0tOKk1upwLIrapy8JxlrvLQ6DKicg7ahOlGprzS5kwZ8ekSDLJ0KY2tno0lQ8fxJ0SCOSoDSqJ5hGEsoNobS3ug5SD00GMckIyMD165dEy4Oc+U2JSUFjz32mOMG/NGHP3jwIN566y3DOoq67NGjhwj+KA7oXGRpUGr+9CPr1atXsUX7J6Zl4oetlzDv+FVkZuugVaswsm1lTOxSHb4eZSfKOs73AmZsu4T1t70x6ZH2cCvigkD0h0w+PcoCoMHa6dOnRY4vR5qXDqRdUBQ2fwdl6/5TFDgJBTKjmwfFMUWHTqdDYmKiiE0ojVgk+p4plZFcJNai/e2h3Ar/uLg4YeoJCwszWU/L5AOyFxosUE95cjFUqlQJixYtslkZiqpOmVeeIujHV9QPwOwcHRYfvIav1p1FXJKUU9+1Tgje6V8fNUO9UdaY0K0Wlhy+juh7qZi3PxrPd6lZpMen+0t+ParkNXjogxjw3Lvoqdaw4ClliuNvnyn4/adnIgkjUoS4ZHbxkaM39cv3uqShc9K5rf3+7P09llvhX5RV5fILBRnSZMvPVFj2R90VJXlPxkgjuOohXpjcvz661pXiGMoiFGRI6YWT/j4qsgCGNa+EUN+i0zwob1VOATxz6iQuT5sK3yr1MHlQkyI7B8MwjLNQboeGwcHBItCBtEEltCyXeiwuqLQkmZ+pIU1Rcv1+KiYuOIQRP+0Rgt/HXSvq8K99qVOZFvwyVFegSaQ/UjKy8eW6s0V+fGr1uXjpMqi0bkiLOoipH7yNC7cSi/w8DMMwjk65Ff4UzNKiRQvR8lFpiqHl8tjQ4adtF9Ft6lasPHYD5EJ6rE1lbH21C57qWL1Yu+oVJVRQiCoKEosPRuNYtNRMqCjJCKiG4IGvksENCYdW45EXJnMaIMMwTD4p01KFijdQlTeaCCpnSPNXr14VyxR8N2vWLJHfSQFg48ePF757a60fywPpWTkiZW/lCx1EwZwgb8v4grJO88oBohIg8cGKU0UumLeeuQXP2u1Qu5/0HR9a/gsW7TpVpOdgGIZxdMq0z58qPHXt2tWwLEfajxo1SjR7oDaPlPr13nvviZQHyulfu3atRRBgUVMcPv/RD1RF9RBv9KgXWu4r2ZHvn8oAH7xyD/8ejcHgptJgoLDQQGLL2dti/omHBmGbvxtOudXH/3bGYmDruvBwLZ6WwwzDMI6GuqyX3pWruyknZZeniRMniqYPVHxn3759IiCsuCkOn7+bVoOe9cPKveAnwv3cRYlhgjoBpmYUzSDpUlyyaFrkolGhjj/wz8/foFrt+iJWgpoOsfmfYRjGAYQ/U355plN10Qr4Rnwaftp+sUiOueXMLfHaqmoA3DQQmv7kAfXEuum/r0D7jp3tznFlGIZxZlj4M8WCu4sGb/WrK+ZnbruImPuFbyu6VW/y71Lb2Kyjd4NwPFDNHzf/nYq9u3aI5iBccpZhGCZ3WPgXAPL3U6tJbhyRO/0bVUDrqoFIy8wR5v/CkJyehX1RUsvizrWCDevJTfLhg00Q/tDbULm4iZ4NVN6ZXQAM4/hQUzfqAkjxXsr4MOLRRx8VcWMtW7YU26lZEAWIMxIs/MtQnr+jQYL5vYH1ReoiBf4dvHK3wMfadSFOlDeuHOiJasGmfRRqhHhjwrBeCB74Op1U9PT++uuvi+ATMAxT1tm9e7fIAtuyZYtJ2vfFixdFUzDqDkvbKSbs008/Fe2DGRb+TDHTsKIfRrSINKT+5VD/4QIgR/lTiWNrQZEvdKuJ6i06I6DbU2L5tddew5IlSwp17QzDlBxkrXvmmWcQGBgofuNyindBoL4vzZs3F4Xg5KZrFBRemPbgXbp0wcsvvwxHgYU/U+y82rsOvN20OBYdjyWHovP9fvqxbj0rBft1sVHpkMoLv9m3LnxaDEJ4O6nz4xNPPFGoBwjDMCUHpWlTJtfKlStFDw8y0+cFDRI6d+4sXLB//PGHYT25/6jhGnH//n3RGp56t5BSQNVhmTKe519WKe7a/o5GiI8bJnarKfz+VPa3b6MKYjBgL2djE0XWgLuLGu2qB5FRz+p+nWtLVgHXDmPQxz8Dvj7eqFOnThF+EoZhigsy01O77vbt2xvWka/evGWtLNwjIiKwc+dOVKxYUQwWqElbo0aNRAwAVXqlNHDC399fNG+j0u8PPvgghg0bVuy1YMoDrPkXAPb5558xD1RFlSBP3E5Mx4wtF/L13i1nJJN/+xrBIovAFgFergj2doNKrcH7//sFf/75p2h7yTBM2Wb06NEiUJeqt9IAngL5CLLcnThxwmIiwU+Q4Cdo0NCvXz8cOnRItNolnz81A1NCAp8sADt27LB5HYsXLxYDCHpuBAUFiQEFVY21BrkRXnrpJYSGhoq2uh06dLCQCeQqoEEITXQ9ZHWYPNlYkpyu87PPPkO1atXEOen66BpKAhb+TIlARYze6Sfl5P+yIwpX7lj/QVlji97kT/7+vKgdJrU7vhqfZWi1ST+wX3/9lVMAGaeFBJitiXrD27tvaqppyq6t/fLL//73P3z44YfCNE9avD2KFZ2HBL1cCn7z5s1o0KCBeJUj/0nbl/eJj48XwX+2rIE3btwQGQJjx44V5eK3bt0qLAW2YgSmTJmCf/75R5SXp0FHzZo10bt3b9y9axrYTNu1Wi32798vPuc333yDX375RWwjwT9v3jzMnDkTJ0+exCuvvCLcldu2bUNxw2Z/psSgCoYdagZj54U4TFhwCIuebZ9nSd741ExRJpjoUifvzoa1Qr2x++IdXLiVZFhHQUQk/Pfs2SNSfRyhiiLD5Advb2lQbA3SmKldtgxpsikpKVb3Jf86CUUZ0tDj4uIs9stvUB1pxT4+PiJAz96urCTYhw4dKubJBfv0008L3//zzz+PkSNHivVU/ZV+/3KgH1kXSLO3JfzJxUACv0qVKmKdrX1p4DF79mwx9e3bV6yjZ8uGDRvEs4ZiC2QiIyMxbdo08dyhgcfx48fF8pNPPimyD6itvNyMrnr16sKVQRlLdK+LExb+TIlBf/yfPdgIg77fiRPXE/DmP8cw/eGmuQrjnefjkJ2jQ81Qb0QGmqb4WaNWmI94PRdrbPU7ZMgQzJkzR/woa9WqhTfeeKOIPhHDMKUFCUry5ZtDGvZ3330n5lu3bm130G+TJk3QvXt3IfBJg6eAQYoPCAgIsBqfQJbEBx54wLDOxcVFnI+sBkratm1r8owjQU+pyBcuXBCDrJ49e5rsn5GRIVIUixsW/kyJQgJ8xuMt8MSv+7D8SAzqV/DFs52lPgCFNfnLmj9xXqH5DxgwQJjbaNT/5ptviocGVQJkGGeBzOK2IG1bya1b0m/OGrIrTeby5csoa1Bhn4Kg0WiE5k51AyigkAYQ77zzjqgPQD754vpOyOoixy7IuLkVf0dX9vkXAK7wVzja1QjClIH1xfzna88Y0vjMoZoAcknfrnaY/Inaes0/+l6qqAooQwE3FJxDkEmQXAAM4yx4eXnZnChYzd59zQNobe1XXlGpVEKb/+CDD3D48GG4urpi6dKlFvvVqFFDbNu1a5dhHVkCKFaBZIMSGjwo2bt3r7BA0n4k5CnIkeIFlBO5CoobFv4FgKP9C8/ItlXwSKtIkGvwhT8P49JtS83kZEwC4pLS4eWqQcuqgXYdV4r4dxXzF82OSaa2gQMHiijdwYMH49KlS0X0aRiGKe/s01cAJMsBCWQK5qOW8fXqSYHKSmiAQ4GB5EKk+gQkDyjmgMz448aNM9mXjkXt6M+ePSsykMiiQIoIxTi8+uqrIsiPggLJlUCBg7SdlosbNvszpTbC/mBwA+GbP3T1Pp6e9x+WTXgAPu4uFib/DrWC4aq1f5xK8QFxSXdxPjYJjSv5m5j1FixYgE6dOonIWgq8IRcAwzCMr6+vyAaYPn266A5KQX+kMMgBfdai/SmKnyyJlFFAPQTWrVtnESNAgX2UJUHxAPQMIsFPQYjERx99hJCQEBH1T8oI1SSgyoRvv/12sX9eFv5Mqab/zXyiBQZ9vwsXbyfj5b+OYNaTLaFWq8z8/faZ/JWm/72X7uLcLWPQnzLqmSqI0Q+N8nIZhikbUOnc0iyfW69ePaHF20KZ5UCQu4RiieTgQltQICANKH788UerShANBmSXZEnCZn+mVAn1dcdPI1sIzX7TmVv4ZsM5sf5ucgaOXLtvd4qftaC/C7HWg5yoQIhS8N+7d4+7ADIM41Sw8GdKnSaR/vj8QSmf9vstF7Dq2A1sP3dbxAPUq+CLcD/TgCS70/2saP7mkOmfUnzI7MYwDOMssNm/AHBt/6LnweaVcPpGAmbtiMKri46ibgWffKX4WdP8KeI/JSMLnq62/8wp6v/atWsipYf8/4888kghPgXDMIxtV0FZgjX/AsDR/sXDG33qomOtYKRmZuPwVcnk39VGF7/cCPJ2Q5CXq7AcXLxlvdTorgtxeHvpcYwcPU5E4sr1xSnHl8jMzsHMbRdNKgUyDMM4Ciz8mTKDVqPG9482Fw2ACF93LZpFGqP18wNF/BPnbZj+3//3JBbsu4plR67jyy+/FKl/cgogpdxQASLqQkhWCIZhGEeDhT9TpvDzdMEvT7ZE3XAfPNelhhgQFAS52M85K0F/sQlphgqAJ67Hi/Qb6gXeokULUae8f//+OHDmqthOQYcx902bmTAMw5R3WPgzZQ4K2Fv7cic836VmIY6hj/i3ovnvvmhsRELCXy7asWLFClFZi4pxLPrxc8M+60/eLPB1MAzDlEVY+DMOSa1QH4sa/zI7z98xzJ++mSj8+3JPcKqzTZ3CvDqONuyzloU/wzAOBgt/xiGRNf+rd1OQmmHMyqB8fqXmn5GVYxLURx29ZsxZgESdG+RGXPuj7uJOUnqxXWt6VjZmbL2AszetxycsP3Id63gAwuQDrlvh2OiK4Ptl4c84JBTtH+DpIkX8K2r8R8Ul40Z8Glw1ajSp5Gdi+pc5fTNBvNYI9oLnuXVIOLEFG0/HFtu1rjsZiy/XnsVna0xbgRLxqZl4ZeER0f+ABgkMk1c1OYJqzDOOS4r++5W/74LAef7OnOcffRA4tQxoNwHwCYcjQWUzKXaAtHaK+G9YURL0uy5KJv/mVfzRIMIPR6PjRQMhZYNfWQN3vX4Qp5d+B2i0+K1hLTzc6tliudbLcVI64s34NItt95IzkKOTLBS3EtJFS2SGsQUFr1J9eLktr6enp0kveaZoyMnJQUZGBtLS0izaHBe3xk+Cn75f+p7N2zHnBxb+Bczzp4maP/j5SUKlXJGdCWyfCmz/CtBlA3cvAY/8AUeDiv0I4a+I+N91XjL5d6gZjEoBnlY1/zM3JM2/b/+ByDm3A+tWLce6/72Ow493RLOGpu06iwI5myAuKcNiW0JapmH+ZkIaC38mT8LDpYG8PABgikcIp6amihbHpTG4IsEvf88FhYW/sxF3AfjnaSDmkHHdmZXA7bNASB04Eubpftk5Ouy5JGn+7WsGizoCxKkbCWKbRt9Q6Ixe868f4YexC/9AhXotkXjtDAb0H4Bjhw4gKCioSK/zul74301OR06OztDYiEhIzTLMk7uCYfKChBEFr4aGhooe80zRk5mZKToAUofQwpjeCwKdrzAaf6GE/7///pvv9/Ts2VOMkphSgpzf/80G1r8LZKYA7n5A/2+AE/8AZ1cBO6cDQy27TpVnDA1+9Ol+p2IShA/dx02LxhX9xEPSw0WDlIxsRMUloWaoj0kAYN0KvvDy8sBLn/+Mz8YPQ8zVKJEJsGHDBri5uRW58Cfz/v3UTAR6uVrX/OO53gBjPyQgikJIMJbQfc3KyhKd/Upa+BcVBRL+Q4YMydf+9JA9f/48904vLRJjgX9fAM6vk5ardQKG/Aj4VQICqkrC//jfQNe3Af9IOApyg58rd1OQlpmNnRckk3+b6oGG4kH1I3xx8Mo9nLieIIT/pbgkZOXo4OOuRYS+odCITo3x67ApiP3jNezYsQPjxo3D/Pnzi8TcR+ZDZRGhuKR0U+GfahT+rPkzDFNUFDhS4ebNmyLowZ6Jgk6YUuLMKuDHdpLg17gBvT8FRi6XBD9RqSVQtSOQkwXszr0vdXkj2NsV/oqIfznF74GawYZ9Gkb4mvj9z9yQrARUYVAW7g0r+qJarboIHvI2tC4uaN26dZH5+ah1cVqmVGdAFv5KyFIhYy0gkGEYpsSE/6hRo/Jlwn/iiSfg6ys9ZJkSIj0RWD4R+OsxIOUOENYQeGarFNlvHp3aUWpsg0PzgGRjDnx5hwR0bX2xn5PXE3Dg8l1L4a/PAjgRE2+S5lc33NfkOM90qg6Pqk0R9tQsVHzgwSK7xpj7pgL9jlnQn3nAH8MwTKkJ/zlz5sDHR3qo2sOPP/6I4GDjA5cpZq7uA2Z2AA7PJ9EFPPAS8PRmIMxGpHr1rkCFpkBWKrDXsfz+NfXFfhb+d01o2CE+boZYAKXwp8EBBdvJaX51wk3/vp9sVwVPdagGrW8wXl9yDJvPxOL+/fs4ePBgkfj7ZcyLCSkD/vKr+VP8gly9kGEYRgkX+XEkKIVv00fAnD7AvcuAXyQweiXQ80NAm0uAGpmwZe1//ywgTdJ+HYHaekFPfn3igRpBJiZ76v7nqlUjMT0L1+6lGMz+9SqYCn96z9v96uHBZhVFZsAzMzegReu2IpCVegEUmfBPtq3530pMR5adwpz2G/T9TvSatl0MAhiGYYpU+Hfr1g0ffPCBxfp79+6JbUwJcfsc8EsPYMdUQJcDNH4EGL8LqNrBvvfXHQgE1QLS44GDc+BoQX8ylOKnxEWjRj29lr/jfJzBtC6nCSqhFLwvhjVG1zohyNB44k6GRvydUxdA6gZYEORgP3k8Yp7rrwz4o0GHtVoA1jh87b5IWaSKhudirZcNZhjGeSm08N+6dSu+//57kQGQnCxVKiOo+tG2bdsKe3gmLyiajbT1nzoBN44A7v7A8LnAgz9J6Xz2QnEAHV6W5vf8AGQ6hn9ZaeI39/ebm/4XH4wWr5UCPODjbj19hwYL0x5uCi9PT/gMfBsVKlXGxYsXxd8/VfvKL9fvScK/Roi3dbN/mtHsT9ywM91v61ljgRdbPQMYhnFeisTsv3HjRhH937ZtW1y+fLkoDsnYQ8IN4PeHgNWvSv76Gt2A5/cADYYW7HiNRgC+FYGkWODoAjgC5OP385AEebVgL1T097Ap/I9cu28R7GcNf09XPNSiIjRe/mj//FeiyuOuXbswduzYfDfciNEL88b6PgMWZn+95i9bBnLz+yemZeKo/jNsPXvbsP60vmIhwzBMkQp/qiZFWj51RGvVqpWwBjgyVNe/fv364rOWGqeWSyl8FzcBWneg75fA40sA34iCH1PrCrR/QZrf9T8g21TrLLc1/vXaf/sa1ivzNYwwtZCY+/utMfaBauL1v3gvfPfr79Bqtfjzzz8xZcqUApn9m1Tyt6H5S8K/ir6sb265/k/8uh+Df9iFP/dfFf0KZOSKhQzDMEUm/OXgKap4tmDBArz00kvo06cPZsyYAUeF6vqfOnUKBw4cKPmTUzDe0vHA308CqfeA8MbAM9uANs9apvAVhOZPAh6BUsAgNf1xAAY3qyi0/4dbWS9gVDvcG1pFSV3zSH9rVA/xRve6oWL+nKYqfvrpJzE/d+5cxMeb9gqwBRUekn34jWTN38Lnn2USgxCbkCaCBLtO3Yq5u6JM9pW1/rf+OW6y/ow+fZFhGEam0NLC3Mz57rvv4o8//sDXX39d2EMz5lzZDcx8QDLJq8hHPwl4ahMQWrfozuHqBbQdL83vnCbFFJRzRratgqNTeqGxXrs2x02rMQnwy8vsLzOuQzVDrMCDjzwhUlr37dtnd7MnWev3ctWgRrBknaCsAxoUEBmxZ/Fozkp0UR9GwyBpcEIBifsu3RGBfCuO3cj1+B1rBQt3AQ0wbieaWhQYhnFuCi38o6KiLHL4H3roIezduxezZ88u7OEZIisD2Pg+MKcfcP8q4F8ZGL0a6DFFMtUXNa2fBly9gdgTwPn1cAYa6f3+blo1qgbZV5GyXY0gUQkwNTMbf+6/hueee064wGTyaqoiF/iJ8PeAr4cWLhqVoeofDbrUC5/Aey7zMdf1K4w5+SRUyEFSWhaS0yVrgPxqCxrQVNa7Cy7dNnY2ZBiGKbDwp3a2NAUEBCApKcmwLE+VK1cWTVCYQnLrNPBLN0kLhw5o+gTw3C6gSrviO6dHANByjDS/4xs4A1TCl6gV5m2o+2+Py0vW/snPrrSCkfWrSZMmuH3bGHhnS/Ov4C+1BQ3ycjOa/i/vgPbuOaTqpMGdT0o0fJEiLAM0EUl5CH8S/HKfAGWZYIZhGHVh+gmT4Lc1yduZApKTI1Xb+6kzcPO45IcfMR8Y8gPgXgKlkttOADSuwLW9krvBwRnSrCIGNYnA//XMX1vj/o0riM6AV++m4Gi05OunlD8K/Dt9+jQGDx5sMwUwLlkyxYd4S0I/yNvVuJ46MAJYkt0RiZC09yBVgonmn5fwjwz0gK8+ZdE8ZZBhGOemQF39iC1bthjmSePp168ffvnlF1SsWLGors15SYgBlj0PXNLf45o9gcHfAz7hJXcNvhWApo8BB+dK2n+V9nBkKK//20eb5ft9nq5a9KgfhhVHY8TUNNJftPlctWoV2rVrhz179mD06NEiGFZtFpB5T5/WF+glCegg/SAgKe46cHqFmP8juwe6uJ6GT04KgpCA2HQS/lJMAA0E6Ldnq8kQaf6++jRH1vwZhikS4d+5c2eL/saU589tewvJiX+Ala8AafcBrQfQ6yOg1VPGRO+ShHoCULOfCxuAG8eACo3hNFBWxYbJQOp9yQJCsRVUA4GCLF2kVr8yZDEgwb/yWAze6VdPVAKsU6cO/vnnH/Tq1QsLFy5EjRo18Mknn5i8726yJJAD9eb+YL2JPuTiP6LL4t3ApjgdUwVJGn8gJ0Zo/hfTswwaP7UeTs/KgbuLRj8IMI3PrBTgCV93rUWlQIZhGK7tX1ZIiwf+eQZYPEYS/BHNgOd2SMF3pSH4icDqxoJBIubAiaA0R7J60Ovxv4HDvwPbvpDqK5jRqXYwfNy1iE1IN3QOJLp06SKsYcSnn35qEQB7V2/2N2r+kvAPviOlkF4K6yNeU1wCpfWqeKHt0yQjDwQysnNMBD8VN6JBgVzgSNkjQCb6XgpG/roP28/ZjktgGMYxYeFfVlj6HHBsoZTC1+l1YNwGILhWaV8V0OEV6ZWE4J2LcBrizkuv1ToDvT4BqjwgLd86aTVVsE8DySWz4liMybYRjz6OB4Y/K+afffZZHD161LDtbookkAM89UJfmP11qJAoneOKZ0Pxmu4qxc6Q2Z+E/N0UYy0A2f9PFgAlcpS/bPZXdgeUmbjgsOhn8OTs/fm6NQzDlH+KVPjb8j0ydtD9PSCkHjB2HdDtHUBjvbZ8iRPeCKjVS2oWRFX/nIW7l6TXugOA9hONFhBqoGSFgU2kyoqrj9806bw3e1cUrlUbgIBGXfH666+LKpjmPn9Z468f4YuqqpvwykmATuOGKE1VsT7DXapMSGZ/udCPTKLeCiDXBrAQ/u6Wmj8VCXpwxi5DOWOGYZyPAvv8KY1PKewpopnynL28vEz2I78nYweh9YDxu4umSl9RQ35uyvc/+ifQ5S0pGNBZhD+5Pojg2tJrnPX2vVQ6mNLqKEd/18U76Fw7BHFJ6Zix5aL4nfj0fQXvf9jfJOhP5PMrNP8ONYPR1z8aSAViverivl7Bz/GQ6miEahKBLNP6/gbNP9M44BjarKIhBZHqB5gH/H26+jQOXWXBzzDOTKFS/aiSmTw98cQTiIiIMFlnb6UzRk9ZFPwE1RSo3A7IzgD2fA+nSLO8qy+dGygJUYToUwCp7HGWZbU8qg3Qr5Fk+v901WlcvJ2EaRvOGXzyKpXaULo3NTUV70yejIQkqQumnItPg4SHQm+K+c1JkYhLlPbXeYVIl6BOtDDxy8dPz5I0f39PF9F1UG5WZND8FcJfthbISO4GhmGciQJr/pUqVRI5zC1btizaK2LKJqT9LxgO/DcH6Ph/gKcUhOaQJN6QuiSqtYB/FWmddxjg5gekx0uxD2H1rTb7WXXsBs7GJuLVb39Hd90euGEIcjRuyMzWCUtAuJ87RowYgZUrV8KzzgMIG/qmQUAT1TNOi9ddadWx6UysmFd7hxgC/syRhX+aXvOnCoVK5IA/pcDP0A8UZEJ9WPgzjLNRYFXz+vXrIrefBgHjx4/H2rVrkZFh2pSEcSBq9QTCGgGZycD+WXAKkz+VUdbox8fk4grJ3fRPzX7WvtwJD9QIxKeq7zFRuwwfVvwPNUOlvgEk/InXXnsNWhcXpJzdhZRdv4vUQEFmKtRUUpnaC+fUEAMGwiNAsigE6Cwb9Jhr/hThr8QY8GfU/K/eSTHZJ4ssHbmQk6PDpIVH8P1mfRAkwzDOK/wpbenmzZuijamPj4/o5kc1/qmu/7x583D3rjHlqaxy7do1kY5F7XkbN26MRYsWlfYllV1I+HV4WZrfNxPIkEzWZZ7Em9JgZd07UhfEfPn7a5iuD66Ta9AfEebrjvn93FFPfU0sD/Y5hWC5cp/e7N+pUye89ZkUPBm7YyFmzdIPpqiWQk4W4BWKeZMewht96uLFbjXRop6U9eGrS4AGplq7nPZnS/OX8/ypJHC2qAuQjRuKgEFrmQLm7I26g38OX8fU9bY/N8Mw5YtCOZkpeKljx4748ssvcfbsWdHRrE2bNqK9Kfn/6SE3depUYSUoi1AP9unTp4v2vOvXr8fLL7+M5ORyItRKg/pDgIBqQOpd4OBvKLNQ86M9PwC/9ga+rgusflWKVdjymX3vv3vRNNhPJg/NX0Z97C/DvHv0HoTr+wTd0Wv+RMseg+H3wGNinixnGzZsAE7/K22MbI0aoT4Y36UGJvWqA603RftL1oEAmDboSc5D86fKhTKJaZm4djdV1AOgToJfD29iESxojfv6lESGYRyHIo0wq1evnkhn2rVrl9CqR40ahR07dgjrQFmEOrA1bdpUzIeHhwvLRXmwWJQaZAKnqn8ECVPqNliWoGC82X2A6Y2AdW9LfQmoGVKo3j9P1QqT7+Q/0j8fmr+4J8f+luapZkNWKprqTpuY/cWlJmfA74FHUeuBvsjOzsawYQ/hxKqfpI0tRpseU60BPOV0P1O/v9zkx5bm76pVi94Dcq7/1bvS4LZykBcaV/IzGTjYQrndvIU3wzDlk2ILLw8JCcG4ceOwfPlyvPrqqwU6xvbt2zFw4EBhRaBI6GXLllns88MPP6Bq1aqinjpZHfbvL1jBkoMHD4qHcGRkZIHe7zRQvX/vcCDhulSUqKwQcwT4pSdwdY+kJVNRnj5fAK+clFIowxtLQXwHpIp7uXJHL/yDaljX/O+cB3JsCMzz6yTLCN2jRsPFqoap/5mY/eU0P/qbfmL8K+jY4QG4IAsJyalSZceaPSyPq4/4l3P9zc3+tjR/QlnljzR/onKghyhOJL03d81faRmQ4xAYhnEy4U9pStbM+CdPWlY+Kyxkgqe2qCTgrUE10ydNmiQ6qB06dEjs27t3b9y6dcuwD2n2DRs2tJhiYoyV2Ejbf/LJJ/Hzzz8X+WdwOLRuQLsJ0vyu6baFYElyYRMwtz+QfAsIawi8fAwYsxpo+xzgV0mKV5AtFvt/AjJMA95MIM3WluZPkf8aNyArTXItWOOI3srVeIRUHIkyJeP3WWj+JPxbq07jvfPDsLTjOewd44H2kVqg8xvWyzl7Sbn+wTAV/skZ5pq/pfBX5vrLAYI0IHBzUdsn/BXbqcIgwzBOluq3ePFi4Rcn83hOTo4IVCJtmxg5cqQQwEVJ3759xWSLb775Bk8//TTGjJF6z8+cOVN0U6NgxDfffFOsO3LkSK7nSE9Px5AhQ8T+7du3z3NfmmQSEqQHcWZmppichiZPQLvja6juXEDWiWXQ1RtUoqeX7zW9qo7/Dc3KF6HKyUJO1Y7Ifug3qeWx+fdRuz+0fpWhir+K7IPzkdNyrPWDJ9yAS1YqdCoNsrwqWBxHG1QDqlunkHXzFHQ+lUzfmxwH7fl1wjuf2XCE0Na1UME/4RxCcA+3E30M134nKQ1dNFKp3yDXdAS5ArqwRsiq1h2Xzp4V1ixlQSCNZ5AYqZub/SmKn46ZnCZZFVw1xvsj4+Mm/czvJqUhSb+fm0YFNVVtBEQgYGpauqhVYI2UdOPxUtLS4abWmXwHTMnD9790ySzD99/ea8qX8P/444+FeTwsLEy8kk//7bffxmOPPVbivkBKK6RreOuttwzr6GHZo0cP0UbVHuiaqd1qt27dxOAlLz777DN88MEHFuspWNDTUx/V5STU9e+MOjeXI2nNh9h2SVPyzYd0Olye/yLq35AyNKID2uKQ3xjoNu+0+ZZqPp3ROH4+0rZMxcbYUMknb0ZQ4hl0IDnuEoRN6zZYbG+Z4Q1qWn1m57+4eN60WE7luK1olpOF+x5Vse0AWQ8uobNHFfinXkYn9XFsuOOP1atXi33PX1XjIZWUEXA+tB+S3cJwy7cRdn3yCb766ithwaK/TZlGt5NR3YrZP/pmnDjmset0/zWIi72B1atNLXNpifQ51di5/xBiU2k/Na5fu4Ktm6IMj4AVq9fCzdJoIDh6TXo/sXb9RvhJyQsCEajIlBp8/0uXDWXw/qek5GLZLKjwpxEFCX6iRYsWwidPZX4vXLhQ4nX94+LihI9evh4ZWj5z5oxdx6DARHIdUJqfHE8wf/58k/rrSmigQW4GpeZPMQLUttXX1xdORUob6L7fIARb/3qe0FXvWmKnzkxPw825o1E9bqNYzm47EWHd3kNfK8LchIzO0H2/Cl6pt9C/ejZ09QZY7KI6fAe4AHhWaiTqWJij3n4c2LEf9UM0qGO2Xb12G3AN8GkyAP26S9vUHoeB3dPQSXMMy7I7o0+fXiKvf8al3aibLrkOqvV5HrrItmhAqX9pfwnXGv090kD2mWeekY6z4xRwewOCIWn+FK2fnJENF09v9Ov3AC5uvghcvYjqVSujXz/TAkTb00/g5L0YVKpeBxpK87sRjQZ1amJglxp4bb/08OrSvYehzLA5R9acBaKviPmOnbuiUoCHeBbQg69nz55wcTHtQ7H57G2cjEnA2PZV4KW3OjBFS273n3Hu+5+gt0jnRb5+maGhoTh27JgQlkRgYKC4AWQBoPXljQ4dOgj3hb24ubmJyRz68svaH0Cx4xcONB8F7PsR2j3fAnUk/3axkxwHzT/PoHrcJuiggqrPZ9C0HQ8bSqspLv5A62eAbZ9Du+c7oNFDlhaLeEnIqYNrQG3tOw2rJ22/c95yuz4FUBPeEBp5W+2eQvh3VR+BW2YqkrOkFr6ZyfdRUSVlHmgrNKI/IjFPFqgrV65g8uTJonZGzZo1hRVAPm879SmRwRDm545Lt5ORnJ4t/vYy9YY3T1fLv8UQHw/xei81G3qXPzzdXOHu5goXjUoE8eVAg7O3UrDq+A1M7FrTRGjTIEMmR6U2Ob61v/2PVp1B9L1UnIxJxK+jW+X5tTAFxymfPWUIlzJ4/+29nnwJf9KKKTdeiaurq0jlmzhxIkoSijvQaDSIjZVKoMrQMqXtFScUgEgTWR6cGup2R9Hzl3dIkfZuPoCrJ+DqDbjQq5c0L9Z5AS607CWVBq7UKv+dC6N2AEuegjrpJrJVLtAN+RHaJlJEvd20flrqTnjjiHTd1TrZl+Nvnu5Hgp5cXfLggeZvnTI2aZKp3FYcy/fuJQzXbENcUi8EeLogLO2i+PVl+VSE1sPf5BTvvPOOsKb99ttvGD58uLBQNarTE9laT1TJuoUmqovw9GkjhL+xvK/0tygH8Zlcsr7I0J3kdGTl6KsG6vejAMHM7CyRLTDgu52G6P73BhqtB/I5iEw7Av5I8BM7L8TluS/DMKVDvoQ/lfI1h0yU5Dt/4AGp3zlpLUuXLhVV88gcXlzQoINcD5s2bRIBewRp8bRc3AORCRMmiInMK07dvIgi6Zs9DhycC0TnM8XSpwLQ/ElpouPkBmUUbPsC2Pal0Hp1wbWxLXgUOlLRofxCUfPNngAOzJIGARbCX27oY5bmJxNUU4oVSIsHkm4BPnq3E81Tih+F+8lNgOQcfcqOWPV/GKdZjej4t0V9/xo6yeSvouwEM8iFRpkn9FvaunUr+vfvLwpoeVTpCf+LyzFIswcn/DpLp03PEr8/OSLf3Uq0v9wymBoLyXUA5JRAWqYkBGVE/+FrppUQTfsC2G8p48wAhim7FNohR819HnzwQdHO9/79+yL6n8wO5JOnaHyqXlZQkpKShAYkExUVJaL3yd1QuXJl4X8nlwM1F2rdurWo1kfpgXL0P1MC9P0SaPCgJAyp5C/V/s+wMmWmABlJ0jyl0lHzHBLo278CavcBKPq+RnfLzoYJMcCSp4Er+kC+Zk8gq8cnSNy4reDXTML4v1+BCxuBm8eB8EZ5p/nJuLhLKX/3oiTtXxb+stZP73ORzOwGmjyGhNUfoLL6NmIvrMa9oIdRTyUJf004efqtD26pHXa7du1E9UyqovnW40OBi8sxRLMTLeK+wRVVMxzS1RZpfrlp/kFeboZUQ3kg4EFpAYqiQMpcfor+tyX87dH8ZbgeEMM4sPCn9L5p06YZUgEp4O7w4cNYsmQJ3nvvvUIJ///++w9duxoDyeRgOxL4c+fOxcMPP4zbt2+L81CfAcrppwZD5kGARQ2b/c3y/qtLWqjdUBW8MyukDoFkej+7WpqokU6LMUCzkQB1sju3Hlj2HJByR3IfDJgONB5umcaXX6hNL1kNTv4D7JwGDJtt7ANAgxSVRroWW5BmT8L/9lmj5eDWaUuTv4yrJ3YGDEG/u/NQ9cyvuNZgCOroa/8jzLrwJwICAkQkP/2tff7556II0H2dF4JUiQi6vRxTXI5jcMbHSEzPNAhvd7MKfyaaf3IGPA1CX2OoAGhexS/LrJAPlQWWyasmADUBUkJWiZIOBmYYpgQq/FFaATX2kVPeyApAKXdt27YVZsvCQE136OFhPpHglyETP52H8u/l3gLFDZn8qR/AgQMHiv1cDonWFWj4EDB6JTDhANBmPODuJxXO2fQB8E09YE5/qYUwCX6qzvfsdknwFxUd9VkbJ5dKLXpNuvlFStdoi2C5xr+izK/B32/Z6pc4ETEC6ToXhCScgOb8GtRR5S38ierVq+Prr78W1jRvby+8nDkBC7O6iG0NVJfhAcrdl3z2tir8BXu7GQoLpeiD94yav2WVP2WXP/q9KWv726rwt+7kTXy36byFqT+vwQLDMOVU+FM0MqUlUS3/devWGfz8VGXP6dLfmPxDJXP7fg5MOgMMngFUbAHkZBrN/K2fBZ7aaFlqt7CQqb9Wb4AK3ZDv355gPxlZYF+l3gHIW/PXt+Wdmy39NurveRU+qlRkwkWKIbATDXRYtn4vnt8fgVSPcGhVOWiiviT8/oYKf1bM/nIKH5nzY/Ud/WQLgbHKn0LzV2jv52KThMXAxOeffAfqHV/BPcPYB+PZ+Qfx9YZzWHnshk2XAcMwDiT8yeROtfupIhlp3eSjlK0AzZo1K4prZJwBygig4MGnNwPPbAPavwg89jfQ70vJtVAcyNr/kQVSbIGtVr7m1OwpuQZuHgPiLpCtG7h9JlfNP9jHDV9njcBl11pwyZaKcNxyq5KvjAdyq8UfXIm7G3/G0htSRktz1TmhmRs0fysBf2Tal1v73tNr8eY+/9QM6z7/vYeP4GHNFrhCX9GMNPsFI6DZ/gWCz8wxxBrI7L6ojPDXwW39a8Cmj+z+jAzDlBPhP2zYMFy9elX458nfLtO9e3dDLICjQT5YymZo1YpzmIuFiKZAr4+A2r2L9zyUhkcNgMjSsPt7o/k/L83fKwiooY9FobiB+GtSMKOaNHnrA4cgL1dkwAWfe72GdLUUEHjH236tn6AYlwqt+gprxTM/78PRm9loqT6HeykZuWr+StO/jDHaX3qlY1jz+Q85MBJfuMzCeI3UbjgrPQW4LjUqqpd1BvP3mfY4uHDL2HK4tioavsd/A3ZMLRs9IBiGKbzwJ42fyusSlFdPWr6yFjlF39etWxeOCPv8HQhZ+z84R8r9J+xxMVDMAnHiH6PJn2IBbGjypPkT/yUG4tXsibiYUwEasnTkAwqcWzjvV9Rt3g7JqenovyAF4UlncC8pLVfNXxn0JyO3+ZU1f2oxbM1P75cjpf111Uj3ptO2hw3bjuTUwI14Y68L4lxsovEzK/sQUJaHGFgYMxMYhimHwj86Olo03aHcf4roX7Nmjai3zzDlCkovrNBEivKXO/XlpfkTdfsDGlfg9mngxJJc/f1EiF7zpra+K9Kb4Snfmaj/wMB8X27HuhWwZ9Nq1KtXF9cTdXjirzikRR/PU/OX0/1k5P3k17sKzZ9a/5qjonoFFAuZeN6wLg5+IgaABLqMfB1EIBIthH/v6dvRcMo6JCsKBynfzzBMGRf+1DmP0uuouh9F+8vd/h566CHMmzdPtMllmDIPpaF1/D/FslrK488Lyk4g3z9xfFGewt9c8360dWSBU+D8/f2xatVqBHlpcfhmDn798j2k6lv7WrT03TMDmD8UFTyybGj+erO/WVCfuXau0UgxAzkU66DHFVkiut9WRH+YSvEMoMEVgIu3k0VA4bFoySrw5dozaPLBely8bXQXMAxTxn3+ZObv2LGjKEBChUjkVLuffvoJERER6NSpE6ZOnYrr1027jJV32OfvYNQdCATVkub98kjzU9LwQf2MLtdgP8LTVWvIsad6+g81z6OqYR5Uq1YNMyb2RLCnCv1aVkGG3k/vbq75r3sLuLgZ3ROkxlUyygp/hDKiX24VnKPQyDVaLTTIhlpnHBS4IAuZWTk2q/5VUAp/iolQIHcBnbH1ougd8Pka+5pxMQxTRgL+lNSrVw+vv/66qEVOqX9UjGfHjh3COuBIsM/fwaBYlc6vS/MVm9v/PqpMqFVU88tF81cG3fVuEI4gswC8glC/RXtEveSNvjV0xgp/Ss1fUWKvUrqxUqZWrYKLRm3q81eY/WWhnJBw3/gejRZu+oh/pfDPTfMPUfj8delJJlkEV+6m4K/ff0ZL1RmLQkIMwxQ/xdZvMyQkBOPGjRMTw5R5Go+QqvrJBXzswc0bqNNHKhREjYzycBc0ruSHmPupGPNA1cJfL5ngg+vA21WF8PQrQgBnxcdi/65tiBzYV9ohxah5+2UYG2ApCwG56efvJZsK37m7L2NglWy00C+7qrLgBtMBgptKqixoS/P3g+TnJzLTk0wsCTOWbsQOt9fwiBtQNW0B1wNgmLKu+VMjH2tm/JMnTxbVNTFM6UCpf9RxMD80fkR6peJE5n0JzPhqWBNsebULWlTJ5zls4BIuWRoq5sQg5+5V3Jj3fxj16HBRXluQdNOwr2/iOWG2txD+es2fqv+Zc+Om8XfunpMMdyuaPwUHZtgoc+2rMgr/rNQkk+JBlAZoRGfSOdAeyG3w5/6rOBmjyChgGKZ4hD8VGalVq5boMta4cWPh45ehPuQM43SQ5v/4EmDIj3nuSoV1IgM9i+zU3qHVkKRzF0K4hj/gGlJVNLYaMGCAyMYRvQr0aLJSDQJXGRdgKPKjdxsMaFwBHULTUUN1HXfjFNaC7GS4qUwHCBTwF5+aaRLhr8QXUpCfQfgrNP9AlTETQIMcpOrLDotrycgWgYBHrhndDuasPxWLt/45jv7f7sSMrRfQ/9sd4loYhikG4f/xxx+L3H7qrDdnzhxh0l+wYIFJAA/DOB21ekj9AEqYAG83XNBFiPk62puIGPaOCESNiYkRA4DE2Msm+9dXXTGJ9LfWC8DbTYvfE8Zgk9trUCt6F7hnJ1rV/KlioK3Wvb4qo/DPTk8y6QugTAPUIlvEIcj8tP2iiDkY8sMum59dWUzoy7VncTImAfP3mH5ehmGKSPhnZmYaOua1aNEC27dvF5H9H374oVN17uJof6Ys4OWqwSVIWQO1VNGoExmGVatWid/o0aNH8cirX5uY2oPUiRYC38vNNOzHU7GtSoJUyY9wzU6BB9KtCv/7ZsGCMr4Kn39OOpn9jYOEAJWp8NdojM+PS7eToUVWnp/dFB24XADDFJPwDw0NxbFjxwzLgYGB2LBhA06fPm2y3tHhaH+mLEAD7utaKciwlvo66ob7iB4b//77Lzw8PLB672m8tCbNYJULc02z0Pzl9EMZX1ej+d0/02j2V0FnWrFPHwRInL6hKOajh4ID3VVGS0FOerJJ2WClS4CEv5Kq2Vdx3O0pvKJdBCTGArO6A4fmm+zjqRi0+CIJu9xeRNeor3K5WwzDFFj4z58/XwwAlLi6uopUvm3btuXnUAzDFAG3PaTMgVqq66gd7mMorf3HH3+I+kX7rmcjRS111wzVplpUASQzvxJfrVEQB6sSTLaF6/P2s3Uqg8+fOHXDdD9z4U7kZKRKTYGsCHwXZJtkDAy89SM8VBl4SbsUWDVJ6iXw70QM/mEXDl+Vyg0r3QSPaTajouoOGl9faMcdYxgm36l+VMrXGmlpaaLf+MqVK5GjMO0RgwYN4jvNMMXEPa8aIOt6dVUMYkONNQeGDh2KpROaoYfPBXhVrAdE70eQJtWK5m/6CPB3MZrbQ2AacPeRy1zxmghP+CPZ0OnvdExCrpH+RE52lkmev6vCKkAm/jSF8HfVGd0LuusHIYv5o9fu47FZ+3D6uRBERm2nIY+wSTiPw5FhylCeP3Xyo0j/O3fuWDVLZttIA2KYgrIyaiVmJMxAtbvV0DisMZyZNM8IpOpchaZc34M0cykAkBhcMwe4pwJC6gjhr06XhLmH4ldvrvn7aI3CX6uy7kRP1HnCX5UsfP7EpThTQS/OYRYfQM8BZcCfsmCQVpUt6gXIyIMKQpV4w+Q4IithVjdQtE0X9WvYmtNMuCQYhinhCn8vvPACRowYgRs3bgitXzmx4GeKGvJfzzo+CzdzbuLd3e8iPdtUyDgbd1OzDRH/IalRxg3k50+SfPa64Nr4cFs6Bk/djXoJezH1fF9g53SxzcvNzOevzTtqjjR/Qhb+1iBTvpKc7ExDwN/H2l/RV3PAZF/qSng7UfouXXT2NQiro4oW1gmTHgIMw5SM8I+NjcWkSZMMWQDOAEf7lx4X7l/AtaRrYj4qIQozjsyAM3MrMQ3ndZI7TnX7rHFDfLTUTEelQYp3NSw6lYlbiZk4ueRbpKalAxunAAkxFtH+Ppq8c+UTIbkXXFXZUMH6YMF8YKDLzhKaP+3/hHaTyTby/5NHoNUnG7Hov2tQ59g3oKP3HXB/HqO0G6zvQO2Wj3IcAMMUi/AfNmwYtm7dCmeCo/1Lj41XN4pXP5WfeJ17ci6O3z4OZ+W13nVxPkcfi0PCP/kOsO4d4LA+Oj6iKbzCqmHVY54I99Hg2q0EjFiUIqUA7vnBQvh72SH8E3SeNjV8GW8XU1N8Tk62KPJj3h/AfKAwefkJaLLt0/xfc/nb9sasDGDxGGDpM9I9YRimaH3+33//PYYPHy4a+DRq1EgE/il58cUXC3sKhjGw6YqkNXZ3747UsFSsubwGk3dNxsKBC+GmKXyznPLGoCYRaJvRG1j1F3D7NLDzG2DP98YdqnYAPPxR2U+NFY96odPcZKy7mI0XVqdhRo0TJnn9hJfa0pSfo9JCrTOuz4KyrW8mMmD6mye8tToojQI6YfbXWcQCyBX+ZCgYUWOn5m+T9ZOB0yuMy+nxgFdQ4Y7JMA5GoYU/pfmtX78e7u7uwgKgLPZD8yz8maLiWsI1nL13FhqVBnVd6qJHix7Yf3M/LsZfxMyjM/FS85fgjIRWbyLNxJ0HPM2EXNWOgLu/mG1ZAVjwVAM8OOMYZh7MRK0VxzBplEqkzcnFgChw0Jx09xB4pBoD7yL9XAB9gT1bfn8v0vzTTTV/SvV7RrvKYl/lMSj7QJtpn+Zvk93fmi6bZSAxDFMEZv933nkHH3zwAeLj43H58mVERUUZpkuXLhXNVTIMaf1XJa2/RWgLeKo94e/mj8ntJot1s0/Mxom4E3BKqJug2gXISgPumZW4jWwDuHoBammcP6RKIqb2kiwkr/5zWRToytHp0EB1Gd+4zIBHvOVvNsPddEDRMMQFOv3xyOxPfnyqMKj0/3ubBQ6Sz9897iTGaxUauZWcf+p/oNIVcaBwDncMZJgiF/4ZGRl4+OGHoc6joxnDFJW/v1tkN8O67pW7o2+1vsjR5Qjzf4ad/mKHQqMFAvRtgpXCv+4AwN2XTHAG7R8pd/BKW1e82NoVvw7yQL06tUWw3e+un+JBzU6oN71vcfgsjxDTFZmpgN7Fss3tFUS5P4ENbq9jnGaNYRdPjanP/25iKrat/svq5VOqn+F9rhoTF0ORwMKfYSwotMQeNWoUFi7kiFqmeLmdchtHbx8V810qdTHZ9lbrtxDoHigyAcj875QE1TBdnngQGDHPuOzhb+KO+19fd4xp6gKkShXzAlTGRjnmZHuZZfJQFoHGxcJN0EptzDbwVFQKJO4lpVoU/rEWNOiptT/VzyrWGozlcLc/hilynz/l8n/55ZdYt26daPNrHvD3zTffFPYUDIPNVzeL18YhjRHqaVpiOsA9AJPbTsYrW18R5n+yBjQIbgCnIlAh/MkFEFgNUCuC+WTNX4Y0d6qRkHQL2SnxGLsuFdN6u8PP3bJeXo6XmebvGSjeZ45c/lecTp1jEdTnY1byV0bZxGdkimLAUhB0lv79b9aeQJ8+NVA/QipzrGT3hTh8tf4sPhnSyOp2hnFUCq35Hz9+HM2aNRNm/xMnTuDw4cOGiVr/MkxRmvx7VO5hdXuPKj3Qp2ofZOuy8eWBL+HUmr9fRVPBb6b5C8GvdxPokmJxe+knmHMkE8MXpZhU4ZNRu3kbFyq2BAb+D9C4GlZtzG4mXiNVxgGBm8KUL06JbJMWv7Z8/v0TFha5if/AhRsYMkPfHpgsHRc2UdUhsfjYL/tw+Op9jPuN03YZ56LQmv+WLVvgbFCRH5q4gmHJEJ8ejwM3pYczafW2mNB0AtZeXisC/7JysqDVB6U5nfD3r2y5Xan5U0aAdygQdxaq5DhEdh+JmAVvYcOlbExYnYafBribZO2oXYw9A/DURimGQG/2J6jIUA8cRqAqSWj3VAGQCgDZq/nbqhVgDgUU6vLSV6iwjxnUgMjQOOjXXkDcOaDvV0CbZwz73El2wlgRxqnhKL0CwEV+Spat17YKjb52QG1U9rUi2PTQNg+tBzJyMnAtUaoC6JRmfz8r98gn3DhPOe+yKT/5FqpX8MNfD3mIBjmzDmVi6m5TQZhdvSsQUA2o3VcS/ITWWFMhTueHezrJOlBBJRXUkYV/hk6yQNRXX7FoCay0CgA6vKrNXeuXBgl51PFfNt5ilbJXgBD8xIkluR+HYRycAgn/Y8eOWXTvy42TJ08iK4sjbpniMfnLqFVq1PCThOD5e+fhVPhWBLTutjV/ivyXcfGUNH8i+TbCVfcwsI4LpveRBPrrG9Ox+JSi8Y5XAPDCQeDRPw3r/nVV45XQYKSqVEiFG1LhaiJoZeGfpl8foopHI7VZGqJ8OapstFOfwkTt8lw/IrkHlAWBrGM5OPjcZRZCcS/X/RQdgjFl9xSMWDECmdkcKMg4LgUS/uTjt9bFzxbt2rXD1atXC3IqxslJyUzBnpg9Yr5bZWOKny1qBtQUr+fvO5nwp1Rb0s4J/0jL7ZXbGuev7TNq/km3MaK29Bh4sY0bXmgtCeuRS1OxL1oasLu6U50AjVHrB/CuaxI2enniL19vVAoNhKeb9D5ZOJOpnUjXC/+8hHoQEuzYL8um8M/NHhCkSsR+9wlmbzA9jrIx8D/n/8Hpu6ex7+Y+sZyTo8OdJOduIMU4HtqCdlabPHkyPD2NNb7zqgXAMAVh5/WdonNfpE+kMPvnRS1/6vEOXLh3AU4H+bAP/wHUtGIhIcHddgKw9weg27tSxD6Rehd9KlcE9Er5tN5uiLqfg7NxOQjylAYFbu62f+f31Wq80rMRsMEdyAAqquJwVFdTaPNEms6VJGuewp9a/uSFK7LxpnauxfrdHu54KyQIH9y+iy6pqbYPoA/ys5YSKI9r6NlmuC59zMj7K05i3p4rWPB0G7SvEZzndTKMwwr/Tp064exZRQcxOzR/Dw9F0BBTJoiKjxLBcaRRe7l4oayb/JVBaLaoFVDLOTV/ouVYabJFr4+BegOAiObAyaXSuqw0aBJjpPmwhtDEnsCfD3kgPUtnEP4uLpL2fjn+Mir6VIQLpRLqUcluBL2gnOH6LSZkGKP9ZbO/kvcyR+FDl98Myw81CcV9TSCQR3+m3poDeExrGWD8bLjkwnghPATHo3KxMOprGkiYCX/9a6aiJoDcK4IEP/HRytNY81LH3C+SYRxZ+DtbFz9HIjY5VkTEr45ajVN3Tol19QLr4ccePyLIo2w1P6Fqfdujt4v57lVsR/lbE/5XE64iLSsN7rIfnJFcA1XaS/Mu+vuSmQYk3jCWAo49AW9XlZhk9u7bh4SQBLy661X0rtobUztPNT0uZQOojKmFr2kXwj94ABADqOg8ZsH8y7IfwKLszvhQOxfDtdvRtIIHrukDBnOjusrYX6BAKDR/MuWrzYMOz61DakgdwzpXRTojkZTOMQCM48DR/k6SKrfk3BKMWzcOPRf3xNT/pgrBTw1ySOMn/+botaMRk6TXAMsIe2/sRXJmMkI9QtEouJFd7wlyD0KAWwB00ImGP4wNtHpLXFYqkBBjGReg59dDGejYsSMmPD9BmMTXXV5n+QAh4a+oK+ClSjNo/hQPYA7FAaTCHen6boCq7HRoNGZ1CawQorqf63YXMtm7Sa2e86oBkJRm6oocqVoLLBiBC9/3Mayj30dexQMZprzCwt9BSc1KFRr+i5tfRJe/u+D9Pe+LDngkFJuHNse7bd7F5hGb8Vf/v1DBqwIuJ1zGk2uexKX7l8pcI5+ulbuKSH57INeAHPRX3v3+R24dwYwjM4on6lzW/LPSgYTr0ny45QAr3FslhP7FDRcRtyrOwi8uHcvTRPP3RBo0+oC/6y5afBQUgGta43ZZ6BtaAWelw1Wx3RYhsJ4qKONDGUi5uYaOGVMJVWZm/z4qqQhQBIyFiqhfhBIW/owj4URVUBwf8lfuu7EPqy+tFoIzJctYVIWC5fpV6yea4ER4RxjWU038eX3n4dkNz+JS/CWMWjtKuAAaBjdEaZKdk40tV7cYqvflBwr6o6JAhUn3o/Pvitkl7gPdo9Lgs/2fCQtNsEcwRtQZke/3f7z3YzEI/PiBjy3jJWR3SMpdIC3emC6oJ1PlKmrs96/tgm+//QoTJ05E7OJYuIa6IvUxY1CdSmdN809Htl7LfktzB6d9fbDf3R0rrstme5XJIEAS/nkP7kJVRp89nXaFtxfqpxs1eHfqUJRbY6dNHxivmy4h9iS2uL6CaVnDjcdV3CaLQQ7DOBCs+Zdz6AFFGuInez9Bj0U9MH7jeKy4tEII/oreFfF0o6fxz6B/sGTQEoxrNM5E8MuEe4Vjbp+5aBjUEPfT7wv3AA0iSpNDtw7hXvo9+Ln5oUVYi3y9tyiC/nZc34EJmybgwz0fojSgwcfF+5LbYk2UsVteflIkF55diH8v/ouYZCvuHFn4J92UXl29pQ6Ao1eLbICjft1Milo1HCoNBqN/jsa/m/81M/tTwJ+p5i535juNNPF62dW054eJ5p+du/Dfl1PXwuy/ydMD74QEYWilCoZ1JLd11NbYDtSk1S99DtXUsfjW9XtDwJ9S3Ftq/jwYYBwH1vzLaXlf0mopaI8Ew/Wk6yaaPAVlkZbfJKSJXRHycnOcX3r/gpe2vCQEPw0ivur0ld2BdsVl8qcOfsrocnuo6V94sz9ZQYj9N/YLQawxr5VfzNxIviFSHImDsQdFoGaYeXe9XEjMSDTMJ2VY6dinLNlL+OoHhVUfEFPWiWdNNtd5sg6uXL6CxMOJeO6x5xD2ZpiwAhiOZeYfV+k1cBeokGkjCz9dJ32v9zMSEZsWC2OonSlxOqnhjq/KaHE45masMChDZ1FZaexjDWH2J5eHnoa4aCn88ywoxDDllyIT/lTulgr5mOf0Dxo0CI4GaUI0JSQkwM8vlwCjIoaEPAl7EvpKk7an1lOYxkngt6nQpsA17Sn4b0b3GXhj+xsixW7Stkl4v937GFprKEoS0rA2XtlYIJO/UvjfSr0lgh3JepBfbqVIvt/EzETRKrhOoC3RVDzIgw+C4jQo0O7JBk/a/f6kTKPAv5tm7LZnQFGe10T466k9bArOzzyA2zWGgvID7mbcReRzkbj06SXEX4mH2x43hA4ORYZKHzxo/jcXHy1efFQuuKtv0UtDZeUQQTb7d03Yi6yEPVjuokX1TMtKoPd0PhbrsqyMaZUm+7wQQl7Rn8BkvQ1Nn/V+xpEotPC/dOkShg4dKrr7kZYp/2BkjZOb3xQOenCvv7xeCPzDtw4b1pM23LFiR/Sr3g+dK3UuspQ2Sm/6qvNX+GjvR6LS2Xu73xMCdHTD0SgpyG0RmxIr6vS3i2iX7/d7u3ojwitCmLtpkNQyvGWBhb/sgihp4U81GOTvmWI5KHgzP8JfqfnfSzMtbXvu3jm8uHECxnt7YXBSsrTSW1H7nyxIoREIfO8QaunN3/R3qHZTo8rLVVD9anVcbSzl02eIJj9aYfY/5uaKf3y88cLd+wiKOSS2e9CgQG8FoIJAQYqy4LLwz9KL1QPu7qiuGLTI3FdZttrNslIUKF/CmZ5TeQSRcsAf48gU2uf/0ksvoVq1arh165ao+Ed1/Ldv346WLVtyPYACQultKy6uEKb3bn93wyf7PhGCn0qQtglvgw/af4AtI7bgf93+J0z8RZ3LTpYD0vjHNBgjlr8++DWmH5xeIj7P+afm452d74j5h2o9ZCi0kl8K6/enwYfM4VjjoKukhf+QmkPE93487jjiUqVoe3tIyEiwqfm/ueNNXE+5iXdDFHUdyN9v61jpCaKxEuES4ILK/SobBvdpKhfp70KlxuMR4Vji443/BRo7CCYoiuYkU50BBYaAPz22FPd78LVP89dPcWbnMZxPBRxycxMWiGt3k5Fs7SCKq7AQ/qz7Mw5EoTX/PXv2YPPmzQgODoZarRZThw4d8Nlnn+HFF1/E4cMl/+Asj1A6F5WyJQ2futilZRsDlxoENRAm/T7V+iDUU9+QpZihh/uklpOEyXz6oen49cSviM+IFymCxeH/pgctDTDmnJwjlh+t+yhebflqgY9Hpv9t0dsK7PdXav4Hbx0UAs7e+ImiNPu3DGspBP+Zu2dEBgNla9hCeY1Kzd9c+MsDCxMo4M8GFASqhOIPiOzUbMz/QwdtwqcYT+0E9LLxiov0WCEDfqLOKPyTlN1zRMc/08ePefqdTLyVAkDZVr4Levd7wYFY5uON72/eQnh2tij9+0R8ohhmvBYSjC1ennj+3n10uwucu52KZmaHUV7Bgct30NLUIMIwDkOhhT+Z9X18JJ8cDQBiYmJQp04dVKlSJV8lgJ2dd3a9YxLVXcW3CvpX6y8e9lX9qpbadVGGAA0AyA2w+NxioQV+1vEzi+pnhR34kHth5aWVYvml5i9hXMNxhRK2hdH8aSASlxJnMhAgFwJlT5QUsoCu5lcNrcNbC+FPdRqsCf+snCxRo4GsJD/3/BkuGheTID9z4U/7m6Nz8bSqedO+yoEocTNZyhBIPJqI6H3ReHffu/j7uapAW0lI+2VLGnOimQYua/5ta2lx6P5KeMIPOcYxignZOhU0Io8QSFJZ9haw1SOUBD8xM8APJ/RBgWodMCohUQh+4ndfH4y/L8UkWNwHxfx3R6ahY7Waxm2s+DMORKHN/g0bNsTRo0fFfJs2bfDll19i165d+PDDD1G9evWiuEanoHvl7gjxCMGT9Z/EXwP+woohKzC+6fhSFfwyw2oPE5H/5A5Yf2U9Jm6aKFLJisrFMXHzRCH4qaLaRw98hKcaPVVoLVsW/qT559ddQcIyS5clCgvVD6ov1h2KlXzYxQFdH2n1FFshn5+0bTL30/dPwl/OPLAVCErWgf9i/8OfZ/40BCpa8/mbm7KJrR4eaHnlDxFbomT39d1ou6Ct4ZjmwYT+bf3RfFhzMX/8lytIPi/FD7jr73e6j2l2gjwYUIf9DrfgrTgSsVOKGdDzYXAQ3gmWairkKB5NaXDHZa0W7wcFiriCX/x8cUNrqbfcUqzTKr7yc2ZphvY0ESI0Htfx9CZjnAXLfsaRKLTwf/fddw0PVxL4UVFRohzo6tWr8e233xbFNTqN8N8wbANea/WaMPOXpInZHnpV7YUfuv8ggvD23NiDp9c/bRBWBYV82GPXjcXumN3iuN91+074uIuCar7VoFVphRBU+u/tQd6fSgW3CmtlCPorLqimAN0HqtVAyFUWqSYD3ZfmYc3FQORq4lWD1q3kdsptw/zMozOFsFf6/KlegjV3hgcVxdE3xMnQZYs+9kqm7Jki0g0p8NMWLca2QFjrMOiydLj6v6tIj01Hkl7IZwZUMdk3WW/2P37niHiNzriDdLO/83/1mnuOQkBnqzR4PTQYS3y9RVwBxRQc8Mg9zkVbQDXd/F1Jmcb7yJo/40gUSvhnZmYKTZ+0f6JmzZo4c+YM4uLiRABgt255919nJEirLulc8vzSPqI9fun1i3ADHIs7JvoByP7f/HIt4ZowVVMFO6rF/2uvX9GxUtF1TCPTt2w1oej2/HArWRKQFF/RLKxZsQf9UZEmgnosEFEJRpM/4ePqg/qBkgWCLATmKAMBabBD7gFbPn9lCmGaiiajkDVPifTSmnZ69Hax9L1HJUUhaFwQPKt5IDspG1emXcGtVElKZtbuZbJvkpXoenPhT1zXagzCf5uHOy5UWI/TbvlzM2kVYpzOmm1nSmDu6YJm0v/+NeDQfJN6AQzjFMLfxcUFx44ds1gfGBhY5jRXpmhoHNIYc3vPFc12KP+dygFTB738cPLOSTyx5glcS7wm/OhUXrhRiH2NewpU7Od+/oL+ZO1YCP9QSfhTk6D7abk3likoZ++dNZjvqaCQ0t8v06pCK0PBH3Nupxo1f4IsMraEv/K70qlU2KnQoM3LGAd7BltUgjSH3BOUAtji5ZoI91cj42YGdsy7C3R5G1l1BpjsKywCvT/NU/j3iayI2YHSQGNieCiSPK3753NDafanMzwWYXRB5KbA26PcG9xIM9oB/04EdnyT7+tjmHIf8PfEE0/g119/xeeff140V8SUeahxzrx+8/DM+meEKfrx1Y8bBC0N+uifmKdX8d+4TNtJ06Xyw3UD64o+AlS7vjggvz/lx+e3xr9s9ifhTwKRhDAJ5CO3j6BLZJciv07ZMkH5/DTwuJIg9Y+v6muM96jiU8WqoLe2jkz+yoA/GghQUCVZQyjGQskcP1+bgYHk9lAS5hkmSg4rU97kYEA/fzf8MtIHDy1OQ8XhkUCXN5B556TJ+5OaPw60mwCcm5mr8Cdm+vtgwj3T+gT5QWn2T1GpcMpKRUDi3eBAEYj4za04xKvVGFzJsvy1TP+sjTj7+Ud4IukFzHq2J5rKA6yLm4CubxX4WhmmXAr/rKwszJ49Gxs3bkSLFi3g5WVqKvzmGx4VOyKksf/W9zdRi4Ai0SnYLD9QJcLpXaaLgjzFBTX4IawJ/23XtmHN5TWY3HayqGxoTfMnYUdQF0QS/hT0V9TCn7R0pR8/OinaqvD3dZOENGVbmKPMTBD7ZCSYaP6y358GMxk5phU4j7m72RT+5oGSni6ewjVgnvpHuKnUaBWiRs1PaiJbLb3XvBthgpWmO7aEf2FRhvhlmp1D/lR0dcv1MQbRWi1We1tmFSj5ADMp+hDjsRhDfvDEZdlocv2QvmgQWzsZJxL+J06cQPPmUsTvuXOmvlU2/Ts2pLHP7zsfe2/sNaaD6aRiKLLgEPOKZdl33KFiB6GJFidya1/yc1PKmlz2mHzkb+x4Q2jBFND3UO2HbJr9CQq4W3J+SbEE/ZkPTGiQEZ0YbUj3lPF11Qt/RSCfueZf2aeysMSQ4DffjwQ7fR5r7YFbpKbhoIe76ABIWRwk5AnzFD93jbsYKFkX/hp45uRApVYhBzpxz6cvnY74Y/Hway3FEsRaKTOcbqMgT2FRav62hH+OYjXFBGTbyAJQiyr/xuscptku2hYbD5gNHP0LaPpokV0/w5R54b9li9R2lXFOqLpgcZjCi8o6QdHyJNTI113dX0o9/e7wdwbzt7U6AObCX/b7U6xCWlZakVZUNA9GpIEUVdOj61YWdMpN+MsBf/T5SPiTdcBC89en+5FrwZzm6ek44eWL9JwMYSEwCH+zDnn0uc2tJIZtKg1cFO6A3t/1xqWPLglJq/XTwquOF26kWbos0twt6/YXBbc0xuBZZTqhEqWwp0A/W218fnP5HCMz3zYs+6pS8IjWrHrp4fks/JlyRaGH3dTMx1YeNW1jmNKC0uPkWARZyFN2wdLzSw37WHMJmJv9K3lXEgGOZD2gBjv2QoKWBh7kf7f1G5GFvxxJvzdmr0HrV1rOcjP7y5p/Db8aRp+/Phdf/gzyYMCa8K+YmWUI9rubatTO5a6CMlREyFrEv9im0pgE2blXcodPEx+RAnjt26tIv5mOmNTbFvchw614hD9ZMmQyzWR/qlqNCWEhhtRDWLEEKOmoOZH3Cct4pg7DFLnwp7r+t29bjujv3LkjtpVl7t+/L3oQNG3aVKQrzpo1q7QviSliDJX+7p0XgueL/V8IN0SdgDom62XI7C0XyJE1bxLCPav2FPOTd03GrGOz8iwc9OORH9Fifgu0/qM12v3ZDi9uftHqfvLgQ05zlM+tNPkTfq6S6Zx89kqNPCM7w1BvQbZskCVAFtxyVULZYkD7mxORlYVADym4T1kTgQYuSsgaIVsFrGn+JP40cmMvtQqVnq4Ej+oeyEqWUgAT7ida1IZIdbVuSShKMq2Y87d7emC7h0eezYJkLrk9bnOb+MRR2wt3kQxT3oS/rZrnSUlJcHcv2oYzRQ2VJaYmREeOHMG+ffvw6aefikEL4zjIQX+U7kdaO/ntyXc9tfNUkX1AZu47aXcstGhqk6wMRvy/lv+HR+o8IgYO3x7+Fq9tf81mlUMSvtQLQRkVvzV6qyGQT1ltT7ZIdKtsWhPDXPiTuZ0qIJqb/mWTP3X/IwuFnDJI0OejQkHK91jV/LOyDRr9K1tfEdYRa5o/mf1ta/6SB9FFMSgSXQBfqgKvUC9kxGbg6rdXEZdkGpyYojDPFxe2zP5kATBvCmQLtb7UsLXqiF0qV8RuK886ejbeiDcdQOXJzmnAf1J/C4Ypkz7/SZMmiVcS/JMnTxYd/ZT1/kmYkkZdltFoNIbrTk9PFz/Wkuhcx5QcctAfCTRZqI1tNFYUAKrsW1kIZNK+5XRDc3+/DAnXd9q+g9qBtfHp3k/FQIL88O+1e8/inL+f+l0IzsbBjTGr1yxM2joJu2J2iaZN45uMN+xHgX2kXZM5/YGIB0yOoYz0l39nVOyHgu3I9C9fn3y9VBpaLtIja+w0YJDXye4Ca5p/eFaWYZBAHL19VJQ1Nvf503Uqff5aaJGlr7Lvpg+mdNGJgHjjPn5a9P24L5a+vBQp51Lw/DPPQzfIqDCk5hIUfHnkImDn/6GwWG3eZ9YfgKwD2QWIT6bqiMSzFUJxPCMZUFgyPl19GrN2SDUbfh/XBh1q6VNaU+5KmQEeAaYHu3cZ2Pi+NN9S6qjJMGVO86dufTSRsDx+/LhhmSaq8tekSRPMnTu3UBdHWvnAgQMREREhHhbLli2z2OeHH35A1apVhZWBegvs32+9/nlupn+61kqVKuG1114TzYkYx9P8byTfEBMVqhndYLTJNqXfX5njb43htYfjq85fifnNVzdbDBZJw/7r7F9innoUkJm8X/V+YpkaNyn3pxRJooZ/DSHYlUV2zDV/ZdAfdVc01/ypII+8XYYsF+aBgtY0f6qd93g9o1lbNs2bR/uT2V8p/Bu6SJU9CXdZ87eiP4dWD0WT/2sC8gvsvbJXxAHIpOgFbuM0yyp5A4tA8JuXClbydZBR+JLgL/Swf+vnUspfqhRcKQt+4olf90kzmWnAl9WAL6oCOcq6g6SBGGszKGsJs0LClCnNX47yHzNmjKjhL3f2K0qSk5OFYB47diwefPBBi+0LFy4UFoiZM2cKwT99+nT07t1bdBMMDZUe3mR9oFoE5qxfv14MKvz9/UVjotjYWHGOYcOGISzMtCEJU34J8ggSQlXOYf+/Fv8nhJhsFdh4daNJxL8tzV9Jp0qdhBZM7gJKaSPhLbPwzEKRSUCBhp0jO4t13SK7if0pjY+q+VFxI4LOrcwmiPSJNFxnbsJfGfQnuylI85eDAmXoM1gIfyupfkSdwDoY23AsZp+YjR+P/ig+Q17R/v5qf5OAP3Ozvwz1WIhoFoH7b90XMQAUD2Ai/HVA4/R03NFocF3fDrgkzP7mkf+29jrp6ooGGZYWEwtunQJWvwYcmAU8scT6PvrS0QK6v8qYB2X5Y2rAdHIZNmx9Hx8H+WJq1+loFS5VeWSYoqDQv7RatWph0aJFQkArocI/FAj4xhtvFPjYffv2FZMtqIDQ008/LQYgBA0CVq1aJc795ptvinXkz7cHEvg00NixY4cYAFiDXAM0ySQk6B+omZliYkoG+V7be88pCp6EatOQpuhWsZvhfdV9pAC583fPG9bdTJQK7gS7B9s8PokJOta+m/uwO3o3KntVNpjb552aJ+ZH1xuN7Kxs0D83lRs6RHTApmubsOLCCtRoVkNE45PlgOhbua84V4RXhDC5+7v5w1PtaXF+2d9+L/WeYdu9FEnL9HXxhTpHLQYZhmA/r4rw0kjCJT4tXrxH3ta3al9R5Gh4gj4LIDMTPlofQyzC3JOWVjsXuMBdbfRtB6iNmrOr3ohoTfhTrALdM8+aRtegKAIUl4nkMGl/zxydyXvpPZTyWBTYM6Agzd+WGfSwu5sQ/tRx8JyrKxbE3DQpIiSTk5MNNQl+4veH0Fj1EY7ppIFhBOKQefcakJNleO8/5//FzlsH8FG7j6QW2dnZhm2ZGelwWTwWk6pVBjISRDGtPQ/vKfBvgClaMsvw/bf3mgot/H/++WcsWLDAYn2DBg3wyCOPFEr450ZGRgYOHjyIt94yltVUq9Xo0aMH9uwx/khyg7R98vmT1SI+Pl64GcaPN/pkzfnss8/wwQcfWLUiKGMemJJhw4YNdu1XJ7MO4rRx6JTWCWvWrDGsv50tac3n7p7DylUrRWrgsWSpV8XtqNtYHbPa5jF90ySNeuWxlfC9KM0fSD8gfPIkFLNPZWP1aeP7QzMkS8LyM8tRM6YmDmccFoI4RB2CqL1RuKy6jLRUSdP2zfIVXTGtWcKIfUf2QXNG0rSPpx4Xr7eib2H1ndVwyXFBOiQBn3YjDeduS6mE125fE8e8mSQNbnxv+eLf2CxU0Q8eaNuVdNOARHOOHz6O+Jx4q8I/+d59g8/fnFs3biEx21h3ICczBzFzYpB4NBHnX3cFqgCeuhyTZjxFJfjthQoBqW1Y11X665I7DlJHwVOurmiXahrMlxp9HMrchX/dJqNq2gJREGi3+4vAt8B9j8qQ7SVT/pP6HLjedkU7t3bwTruO7vpta9esxkDl9WVnWv2bsPc3wBQPG8rg/U9JSSkZ4X/z5k1UqFDBYn1ISAhu3LiB4oI6B1JgobmJnpYp5sAerly5gmeeecYQ6PfCCy+gUSPbDWZooCEHOsqaf2RkJHr16gVfX1OTK1O8I1v60fXs2VM0l8qLfuiHSTB+bzLUROfHv38U6XONOzUWFfIWrlsI3AG6tOyC7pHyo9iSSnGVsGH9BkSrotGnbx8xcPhn4z9AKvBk4ycxsL7y0Q10z+6OFf+sQHxmPG5XvY0rN66IfR9p9Aj6N+gv9gmJDcHWTVvRu15v9GssxQkoObL/CI5fOI6KNSsath/afwi4ADSq3Qj9GvXDryt/RVKC5Dvu2ryr0P5/3/g71B5q9OvXD3+v/xuIA1q1aIXIKhWgXj0JObV6i23u19yxbIdlXI0MpcVSTMS/B/61EP4VgoKB69Y1/7AKYbh79y4gu7R1EK1/s5OzseyHC6jwblW95o9SI1sh5K2h1KX+8fbCOm8v/M8gxiW8MkwzGYhnNCuwMaeFYdk/1bL2ScUa0vepo4Ga1NgRfXr3Ao4a96GYJ/qOKGuFsjnah7XP12+AKd1nUEkiW6SLXfiT8Nu1a5dFTj+tI596WaZ169Z2uwUINzc3MZlDX35Z+wNwBgp738mMTf56aqV7OfEyagTWwG19FboIn4hcj90krInwf5Mv/VLiJQS4B4g0QjJvD6g5wOK9tDym4RhRXfC7o9+JdbTvoFqDDPu2r9Qeux7dJcz71tJn/T0kYZOclWx4T2q2pH36uvuKdcq2vNX8qxlcBVQ/gLZn6aT4Fw9XD2hbjQUiW0IdUhdqrQsCPU27+pmTo8oR1jUZb7Ux7U+ujqfU3mUydZkmaY9qVykF8OJHFxF/Kw2Z316FZqyv1YFDSZFNmr+NbZ8HBYpJ5lo+4hLedvkTb+PPPLOO6Lu5lJAByREFuGhNUyBzcnLEPiNWjxDL83vPl/bjZ0+p4lIG77+911PoPH/yub/88suYM2eO0KRpIp/7K6+8IrYVFxSVTz8aMt0roeXwcMvWo0UJZRjUr18frVpxAI7DFAG6f174uuUmObkF/BHUJ6BFmKTR7b+5X6TxEbTOWutb4pnGz+C1lq8ZlltXaG2xL0X92+qJYa3Er1ymWBbyytLDFEBIx5Mr/JF1S071o9RFkW5WoQmglQa0FGtgjhwcKQdPKq/NRWV8yGToxb+1Kyf3Bt1bJVpfLaq8UgVqTzVSLqRgxsJ70GbbKrBbUpq/fSgrGeYHsh7M9fXBWVfrD+ccnaLuwLp3TLaZn9LQppoGTMlcm4TJP4XW/Ck9jgrjPP/888IPT1DaHfn6lf74osbV1VV0Edy0aROGDBliGB3T8sSJE1GcTJgwQUxkXvHzM2paTPlDme5HQYGkGZMJ3542w63DW2N79HYh/GOTpUGonNZniycbPIkK3hUw98Rck5x/e7Am/OXWvXIUvrKmP2U5yOl65EOnNspUopgQAWZmKK0GMhRASAWRKFOBghzpflEwYJuwNsJ9IJOhF+7W0uooa4Ba45jjHuGOyhMr4/LXl7HtaDqarrwLPCxVJCxpsoqhCdlsPx/c0Grx9p174q58E+iP3/UtlI9HGc3/uuTbFgJeddC+Qj+alS8Ax/6Ssgtq9ijiT8A4MoUW/qQJfPHFF6LQz+nTp+Hh4SEyAKyZx/MLVQm8cEE/wqUKmlFRwkwfGBiIypUrC//7qFGjhC+STPiU6kdBUXL0P8PkR/OXc/ypj73cATAv4U/sjtlt6BrYq0qvPN/Xs0pPMeUXa/X9zTV/Zcc9+m1SNUPS8im///FVj+NywmWj5m9+fLM6AbIlgVIbaRLncfXGqqGrRPqsMgDNQ29EtBamR9YGc81fxru+NyqOrojrv17HsfX3UKNrMNxCC//syC+WycC2uWlmkrfFtEApJmJIYhL8c3IMgt+CFElzd4u/ZFhFAwF7hiNqEvzE9qks/Jl8UWRJtd7e3kVuBv/vv//QtWtXw7IcbEcCnwoIPfzwwyKd8L333hOBh5TTv3bt2mLP0yezP00UcMg4hvCnrn/XEq/ZZfJX5saTwJQ1cWpTbE17Lirk+v4mmr++gY+XPl9caaaXBwB0jVST4GL8RcN6a5q/tW6FNHgwR2n6n9x6MjZf34xHMv1sNsdJz5GqZ9oioGMABkTfR0xdX0SVguAnVnh7YauXfRk7t7TWH5unXF1QPyPTahnhs66m99uksmFONrJzdAjc/ZFY/DgoALs83LH4upSZwTDFQZE006bc+CeeeALt27fH9etSXfH58+dj586dhTpuly5dDJH4yklZOZBM/BRnQPn3VFKYiv0UN2TyP3XqFA4cOFDs52KKF1Ecx9VXmMX33diXL+FP7gFZ+yf6V5Oi9osLg+afi8//w/YfigJB07tOzzVtzprmb4282hcPrTkUM3vMhKfeUmKtOU56VnqeqXvjuniiam3TgUtJYq/gz40fAixjJmz1DZiu2Feny8az8w8i5r7kolno64NoFxes8rbd9Eh1eQf8UqKsVgRkmBIR/kuWLBFV9cjcf+jQIUMRHMqbp0Y5DFOWIS1W1v53X9+dL+FPyFXXqBGQXNGvuDCv8EcDYYPmr/f5NwpphJVDV6J7ZWOaotIVIOOqttT8CWpdrIQ+V36wpvlTICEFH+aGVqczmCHTYtIQ9WUUshLyY4wvfahT4A0bjYp0ZvdlgZ+iImr0f6h7biZyzB7H13NxL6hPLEKXs1MMy/dS7KhAyDBFKfw//vhjUVmP2uEqUwweeOABMRhgmPIS9BeTHCNewzztdxv1rdYXzUObY2KziRYm9+IS/nJbX3qVA/hsddsjrAleF411zX/JoCUm1oz8ujGoTK7Mw3UeFqWLP+rwET7v+HmeEfTUDpgGNNdnXUfyqWRc+d8V5GSUXgZAQXg7RGqNrCRPnTzpFl51WYQIlWmdgNn+ynuvE64BW1y9a6OwC5VzNu8hwDBFIfypjn6nTlIwkBKKgqemOY4Ip/o5FrLmL5MfzZ/y+3/r+xtG1h+J4sa8ra8c6U9QAyFb/K/r/ywGNLbM/v7u/mge1ty4bCX9zyp6s7OyM967bd/FvL7zUN2vOir5VMJ33aT6Btag+gAavSWm0jOVoPHSIPViKqJnRUOXi9Ara/zn4Y4l3l4mAv+tkCB8qQ/+yw1PfWVG66jQ8QupHLR1rNyj7CxgeiPgw0Dg71FA7Mk8r4FxHgot/CmnXhmRL0P+/urV5ZIVjgX7/B2Lwgj/kkRu6yub/mV/Pw0KKP4gt883qcUkuzR/QmnByL/mX7D4AVnzJ9wquCFyYiRUGhUSDiQg9h/TWh5lnfdDgkwSGylAkIL+8kKryt3KERNv2mgpT+5FAYn6KqunlgG/9s7f+xmHpkiK/Lz00ksi2I4eTjExMfjjjz/w6quv5lonn2HKCtSBT0l+zP4ljVwUaOmFpRb+/twwtwzY8vkXWvjnki9vLXNAxry6n3c9b0SMlSqExq2Mw91tUrfD8kKp2SpycoDlE4ADv1huU9SAYJhCp/pR9zwqrtO9e3fRUIBcAJTjT8KfauUzTFmHtOkKXhVwI/lGmdb8iYlNJ2Li5omieyAV4MnL3y9jHo+QW7S/UkjnV/jnFFTzFwWATQcOAQ8EIONWBm4vv42YeTHwCPeAR53SywgoLuFfpAOFc2uAw79L08SDRXlkxsEotOZP2v4777wjGnecOHECe/fuFbn3H30k5awyTHky/ZOQtEeTLi0oo4AC6YhZx2fZLfyVUfsUN6BR244k93DxsKgtkDd6nz8KpvnbKpkbOiQUfm39RDtgr8iy+73Yk/VgC7uK+VhNGDTSRHcWWP8ukGbsuoh4yyZCDFOkef5yud169eqJIDgq+OPIcMCf45r+yeRvq7Z+WWFwjcEmy7kF+1nbJ68cf+VAwe6APz1Vc+klnrvPX2eRDkfQd1FxXEVUfbUqTPrllnGslTm2RaId8QBkF6moyiP2Yfd3pvn+84fafQ2M81Ekwv/XX39Fw4YNRU1/mmj+l1+s+JwcBA74czwaBDUQr5V9K6OsY566l1+zf27BfoU1+39xO06ULv6z/5/58/nnoteqXdRikksEx++PR0562U4BvG+HQFfm/C/yyX1ko1OpkFzdWNyMYUpd+FNpXQr4GzhwIBYtWiQmmqeufrSNYcoDVBTn/Xbv483Wb6KsQwJZjvq3O+DPzOyfG4UJ+IvMysY3Xb5Bw+CG+df8rawf3WC0yXLjw41xbca1Mp8C2Kty/hoUfRhsWR/AnGxX09TptV6emO/rY1pt9fytfJ2XcV4KLfx//PFHUeDns88+w6BBg8RE8z///DNmzJhRNFfJMMUM+cAfqv1QnpXoygJkCldeJzXbyQulHz87j6Ivyg58dgv/Ns9J3uumj9vcRQ5QtB3wZ8r8vvPxfy3/z2Tdcw89B5VWhYT/EhC7uHylABYlmSoVXgsNxpdBAbjkYozb/veoVKiqIFDdiA1XNiA1K7WIrpJxaOGfmZkpuuqZQ+12qfMXwzBFT2WfyvnS/JWpfdS2ODeUQX65mepNCKgCvBsLDLE94FfGUlT1rYpnGz9rEvCnM/sccmyC0mrRsWNHVBwradVxq+Nwd2v5SgHMjd/MtPjc+C7A+B0lKFwMX7n8nL+0wBNLgLtSj4D/2/Z/mLR1Ej7Z+4n9x2CcV/iPHDlSaP/mkOb/+OO2tYDyDAf8MaWNieZvh89fKXipvW9uVPWrKlwg33f7Pn/Bj1r7O/JRvwFlxgHN6aqbVgqV2yoHugearPdv74/QoVI6JqUABlzJu3peeWBqUABy/2aM3Ff0ENDkw/txI16h1Z9YDCweC3zb1NCamlh+cbn9B2Scu6UvBfytX78ebdu2FctU8Ofq1at48sknDW14iW+++QaOEvBHU0JCgihjzDClKfzzm5oo9wPIDXKBFCck/LUqs8ePwjWhFP6vtnoVL295GZ0rGRsnhQwKQUZsBu7vvo+jXx9F6OuhcK9kp5WiDFOQKAYpDdA+Lt5KRgU//X2+XLiuq4yTC3/K7W/eXKoFfvGi1C88ODhYTLRNpqynTzGMI2v+ZRHzWgPU1Mea2Z+CMalTYZB7kMnzJGJMBCKzInF8/3F4n/fOVfhTgGRiOahwZy3d0V7zLfn+3wwJxnP349EtJdVQGaDI8rkZh6LQwn/Lli1FcyUMw9iNMiXRLR/m9rKEueZvHvIna/5EFd8qFu+n9L/3fnoP7tHueOvOW7meq2lIU+y4vgNlnT/y4fc3hwT/aTdXvBQWguNRV/FiaDCiXF2wNPqGSKUkau59C6jyP8CV4ijKbrYEU/wUeFC4Z88erFy50mTdvHnzUK1aNYSGhuKZZ55BenpuXaoYhikoIR4hhvmUTBvtXMsgfav2Fa/1AuuZav5VOlho/krhbwu/AD8MGDDAsJydlm1IAawTUAcVvStictvJNosVNQyyTEksTabZ0f3PFsrAP2KrlyeuuLjgkLtxcBh+8W9g1/8KdY2Mkwv/Dz/8ECdPGltEHj9+HOPGjUOPHj1Evf8VK1aIlD+GYYoeMnv3qtJLCLWOFTuivPBeu/dELYXvu39vqvk/udxC88+rEiGhVjzCMu9mIuqTKNz8+yZ2PboLiwYuwtqH1mJEnRGY2GwigrSW7pFRDUehvKPLw/dvsfbQPODKbumVcVoKLPyPHDkimvnI/PXXX2jTpo3I+acgv2+//RZ///03HBGO9mfKAlM7T8Xm4Zvh756/ErylCdUkeLze46J5Uv/q/UU5ZVGuWKMtkOYvV9GloMeUCylIu5aGO2vv4I9f/zCJM4rwjsCWpm+iRkaG6fvzYfkOL8Opy3fUalxzcbGv1HBiDDBHssAwzkuBhf+9e/cQFmZsfbpt2zb07Wv8gyLBeO3aNTgiXN6XKQuQcMurVG9ZHwisH7YeH3f4OE+fvxJKQZRR6QXblhFbULNzTYQ+KKUATpw4EWvWrDF5n6piMwtBaL2uoHU+uX0HZZHtnh7oUqWS7R3sCCK8nXLb+oYNU6QeAdlld+DDlLDwJ8EfFSUVh8jIyMChQ4cMqX5EYmIiXGyMRBmGYQi1yvgICvYItsvsH+IZYvF+Kkkc5BGEkIEh8H/AX7QZHzFiBI4dO2Z8o39l6AJMezeYWxtyo6zmK/0QkLvlx54uCN0WdTNdcVEfyL1rOnBxszQxDkWBhX+/fv2Eb3/Hjh1466234OnpKapvydCPrkaNGkV1nQzDODgvNnvRpGeBrR4EyvWy5i8PBOQUwC5duiApKQn9+/dHTIyx5G22mTVBWcrYUVF+wmR7U67nDzE7iL3lhxiHF/4fffQRtFotOnfuLPz8NFFbX5nZs2ejV69eRXWdDMMUknfbvCten2/yPMoiFLswrcu0PGuDmAh/xT5yAKFaq8Y///yDOnXqIDo6Gs8+aywjLHcGLAhlVfO3xi9+vhbrtnu4o23VSExTlAZmnJcC5/lTEZ/t27cjPj4e3t7e0CjKTRLU3Y/WMwxTNni47sPoVrmbhXm9LKEs5GNvcSBr6wMCArB69Woh+JXlx82Ff77M/uUoLf5/gUZXgBznMCFcioeY7e+HV+7FG7YrGwPlZ+hDZaL3xOxB09Cm8HW1HGwwDl7kx1Z528BA03rcDMOUPkp/eVmkZkBNTGk3RWQD2EKp+StjBpTzRPXq1bFhwwaTddm6bJMqifkJ+CtPmn9+uKEtmBiYdWwWfjz6o6jZ8PdAx8zscmS48iPDMGWKYbWHoVMl0yY/tjR8pc/foleAGYsXL0b0+mjD8p/9/7Rb8++Q4rhtbtd5Gbsm5ocVF1eI19N3TxfxFTHlprEPwzBMSWEr4C+3ugB79+7F8OHDhfpexacKfJr4wM/NL5+afzmy+5v1C4jWWneVEEt97HDPWom/4H4t5RvW/AsAF/lhmNLDVsCfp4ttDZYKkFEFUpLf1368htQrkibv4+JjYnF4KMsYtKykPIu5Zd5e6BtZMV/voaz+rBUvG1dYsZAoB15M+YOFfwHgIj8MU3qYmP2Vwl9rW/jTfhT459fQDzlpObgy/QquX7+OLpFdTPYb5oDCf3MBzPrNqlVGqzsbccrVdq0W1vzLNyz8GYYpt5q/MnqfSvzmBhUdq/1ibbhFuCHrXpZoCJRq5stvmKPGK3fvWX2/rlwPAfJPlkqFL+VGQ389ChycC1zZY7ACsOZfvmHhzzBMuRX+yoC9vIQ/4enriSqvVIHGVyP6kzzyyCOGLoCCrHQEZ1uvBVA+Pf7WSbJTaz/o4Y7elSJwi1K5V7wEzOmDnP2zkD6tGXRpxnRBpvzBwp9hmHKFMqVPqfk3C22W53u/7fataDs+7bdpcHd3R926dQ3bhCabnW5TyFPgnKMQ5eKCeLMWwLaIcdFipr8xj1+95jW4xV+COumWcafZfYBU6xYTpmzC0f4Mw5QrlFH9SuHfsVJHfNnpS9T0r2nzvY1DGos2v8SAUwPEQGDdb+uMO2RlWBX+KgfT/EdXCEOGWoXl0cbSx7lh0RnQPA7i6h5g5zSg54dFd5FMscKaP8MwDqH5E32r9UWtgFp2HYcEv+E4mTmIPh0NZKU5lJC3BQl+YpmdVVitpTleMg8G3PczMK0RcIvz/ssDLPwZhim/AX9F0JgnOyUbl6dextwJc3HoWorVfVT5KAPsiBxyd8dtTR7iIisViL8KLLPRO4LcAmfXANncJKgswMKfYZhyhTLFLD+1+W2hdlVDpVUhMy0TAxbrEJdo3RvqiOLf3sJFpOV3q1xJzEe5aJGRy7667EzkKIMoZX4bCPz5CLD9q4JeLlOEsPBnGKbcUpgufTIk+CtPqIyQaiG4cesOPlmoRnaqsQeATG5isk9SMsojR9zd8rX/Ng93DKoUgVERYTb3OX8rCUNn7JIWsrOAeUOA9ZOBm8f1B/kCB/btKNR1M4WHhT/DMOWWojD7ExpPDR6b+hjCwsJw5ewVUQVQl63LNeAvM7GeeO1SoT1GJiSivJrz88NEfWfAE262Bw21dVFodGMxUjJTsOXAt0iP2gLs/tZkn1ZrBiD6nnUXC1MysPBnGKbckpNTNMKfCKgQgH///Reu7q5IOpaEG3/cMLgVrurC8E7mGJP9s+JbYPGApfimx/fQNXiwyK7DEfjYZQ4mbZyAF8/OwRdyoSAzbsSnlfh1MUZY+BcAru3PMGUDZYveoqB169Z4ceqLQtW/v/c+Mu9KwWlndJG4jAoW+1fzqw4XtQt0bccX6XU4Artu/Sdel9hoHFR920tAyt0SvipGhoV/AeDa/gxTNshPVz57adOzDSJGR6D6u9XhGiTV+s9JjbR6di5vL3E2lx4Atr6hoKh/gU1cF6C0YOHPMIxTB/xZG1AEdg6Ee4Q7lg1ehgcCxiL9dnurYoxlv8SwihVwwtV6UyRdbiOkxBvFd1FMrrDwZxim3EIV+4qKALcAi/TBGv414H4hBDdmv4ys+/dsph0WhwWivPFoxfD8v0lRsIkpWfjOMwxT7tgyYgsWD1yM6n7VC32srzp/hZ5VemJco3FiuXfV3nDXuKNTpU4ioHDpT18g88413PzjF6spgHm1E3Y26A5t93C3zy3Awr/U4DvPMEy5I9gjGHUC6xTJsfpU7YNvunxj6Aro5+aH3Y/uxvfdvodarcbTH/4AjVcAMmJv4NoPxhRAXY6bwexP15Jxp1ORXE95528fb0zQpwTKvBkSZH3nMysxd+cl3EpIA26fBY4vhq4wGRxJtw0th5ncYeHPMAxjhovGxWDSDwyLQMiwKVC5uCDpRBJi5scg/W5rZCfXMgn4S7/VD87OSVdXbPSytIJcsBEPQLRZPxjvzPwL+KE1sGQcJn38ORb9dw2IPQns+p9otmQXRxYAU2sCGyYX5iM4DSz8GYZh8sAtvCZChz0uIvzubb2HuBW0VmVSavjr4U1M3vNW41lIv93TZF1OzBA4Mo9UDMeZXCL/icNurtjs6WFYrqe+ilkpLxmWq2acw2uLjwE/tgc2vAd8UQX4XxNA2ULYGmvekF53fwckxtrcLTM7B/P3XsHF20lwZlj4MwzD5IJsRfaq3xDhj0hBbfe2zEHqlaMm+z3UQqp9L9O8Qn1kxHU3WZcc3xaOToLG2HhJSYpKhSNurngyIhwvhYXgmtb6fhZkpgD3LgPbp+a+n9Lc/3VtIMF6u+K5uy5j8rIT6P71NmD1a8Dq1+GMsPBnGIaxCx2CegUhsFsgvBp0gXvF+rnuXTfcFx8OblBiV1fWeTY8FCMjjBkBsVqtzWZDVVQ3LTfkWdDJzNd/dY/Vvf67IhUW8kcisP9nYP9PTllsiIU/wzCMXVBRHxUqPFEBQf0nQaXN3bxNPNmuaolcWXlsImQrLO9F7TJsc5uUu2afkQwsHY+Y/cvw2Ky92HvpDpCRhxk/7rxkQdCjVfaFyCnaSpHlARb+DMMwuVDRX/JP56RW1q9xNfj6s7Oz8dVXXyE+Pr4Ur7B8ku+Y/HNrjfM7pwNHFyBi9SjsvngHj/y8N/f3psUD37cUsQM6fbthXeGuptzDwp9hGCYXBjaJwPNdamD2yK7Y9vA2JJ0zRpNPnDgRr7/+OoYPH47MzEw8WvdRsX5MA9MmQEwRkHAd+P0h4M5Fm/582++13F/n5PUZWfgzDMPkgkatwut96qJr3VAEugcCOmPa2tNPPw1PT09s2LABzz//PF5v+ToWDVyEl1u8XKrXXB6Qde1orQb/eHtBaqGUBxc2At81BxJjivhidAV+a3aODq8tOoo1a5abuBXKOiz8KQo1JQVVqlTBq6++WtqXwjBMOaJ58+b466+/hBvgl19+wTdff4O6gXWhzqVyXdvUVMO8RxG2JC5vyJ+8b2RFTAkJwu9+Pva/OeawyaJa6b/Xc/jqfSw7fN3mIXS5LOWHjadjcejQPvTd96SUklhOYOEP4JNPPkHbto6fgsMwTNEzcOBATJ8+Xcy/8cYbWLx4ca77z7x5GxuvXse/0THYdNW2cHJ0zM3uB9zd8/FmU2H/q8tXFrv8ujMKLy88grvJGVbFfKAqMfdT6HR4c8kxfLfpfK77JaZloYHKhsYvpyimWvaFKG2cXvifP38eZ86cQd++fUv7UhiGKae8+OKLeOGFF8T8yJEjsW/fPpv7UnZ7WHY2qmVmwceZS9EWxuVOAXwKumpMay4oSU7PAo78YVi+d+W4eJ3u8kOupzhxPQF/HbiGrzecK/h1/twV2PwRsKLsuYHKtPDfvn27GFVHREQIs9qyZcss9vnhhx9QtWpVuLu7o02bNti/f3++zkGm/s8++6wIr5phGGdk2rRpGDBggJi/edNKnjpjAg17lJX+Ckod1dW8d6Kqf3oW57wiXhupFdp6ZiqNCkzekpppO/1PdWIxBh9+EqqLm3Ifw6Tq6wdc3mm6Pj5asgiUYn2BMi38k5OT0aRJEyHgrbFw4UJMmjQJU6ZMwaFDh8S+vXv3xq1bxjKQTZs2RcOGDS2mmJgYLF++HLVr1xYTwzCMPUzqaf15odFo8Oeff2Lnzp0YPHhwnsfZX/kp6Xh3y55JuKSEP1X6k0lXlEpOUqlwy0alQHPWub1Z+Iv5sT3wv8bA9UNAZhoOXb2HET/tseoKuHY3Bdrlz4ll7V8PF8yMMbuvsAjs+GoYqr65Kk/XQnFgvcRSGYFM8bmZ47/55hsRbTtmjJRWM3PmTKxatQqzZ8/Gm29KfxBHjhyx+f69e/eKYJ1FixYhKSlJpOr4+vrivffes7p/enq6mGQSEhLEK72PJqZkkO813/PSw5m/g2pBRm3V/PO7ubmhcePGhvWkZOiydFBpLYVDhL8noq8EY0x8HL4JDICzYR6it1/RBrhd1UjxuuVKNIILGBT5uGYTQlX3ETbf+vPcooQwMaureHkxnWI4jJ0J5e9zxtZLmLbpAi4rwhNyzAoEHblyB7XDvOGiUUMuA6VTqZCl+FtxiZesFa1yjolXci0816loCkLZ+5ss08I/NzIyMnDw4EG89dZbhnXUfrNHjx7Ys8d6WUdzyNwvm/znzp2LEydO2BT88v4ffPCBxfr169eLdB+mZKH0KqZ0ccbv4MgdEuSSVrp69Wqb+128eBEff/wx0AiIGCO5LpUk3orGocqvoFfcbHpkF/t1l0dOubmiXWoa4jQaVMjOxmWtFj45OQiyY0DQTnNKTLBqWNHl+t4nNRvwadbjhmX5e562x1JkHj161ORoQ37ci6ZBORhTOwey/edecgZ+WbAGVXx0OBSnwhf69cq/iNz+lvKbvebQwj8uLk5U1woLCzNZT8sUwFcc0ECD3AxKzT8yMhK9evUSFgOmZKCRLQmdnj17wsUl7xKrTNHjzN+B+mQs5pyTAsz69bPdxnfNmjWi8l/O9hy4hroiZEAIqgZ5AsnS9tq1a6Fmx2ep6j2woDmcjWsueYufC64umOXvJ0oDf3o7Dm+HBIv1x6Ps8PPnwmV3o2C3xhjNWoPwr4A76Nt7GFQ5mXh3z3rUNYsxCKlcA/cvmcaaHbmjxkWPWoblLJ0KM05rMKhxBfx76Qa+sJLYkNvfUn6QLdIOK/yLmtGjR+e5D5n0aDKHHn7O9gAsC/B9L32c8Tsg375Mbp990KBB+O677zBhwgTELo4VA4DjP3QF3tcfR62BxsnunZLPgwLz3GeNlxfOuElFlWTBXxK4qLJF458H1Cfxg+u32PHJT3jA5SyOu1taaPruHI7zeNBi/bebL2KSmZBff9p2q+Gi+h3Ze5wyHfCXG8HBweJHGBtrejNpOTzc2DmqOKAAxPr166NVq1bFeh6GYco3VPWPOgES0T9H2+2SdFZuajTYoMgAKM1EyCPuzwrBT3TUnIA6x7prprb6ukXNguqqGLgqXDny50jLNHVXuKkyrRYoKgnKrfB3dXVFixYtsGnTJsO6nJwcsdyuXbtiPTeN5E+dOoUDBw4U63kYhin/hD8SDp9mPiLwj6wBl+7l/bBv7FPFMN8/Se8ncAJ6Vq6ISYoMgPLCIM1uw3xP9X/Y7PYq/nT92K4+AiM0W1EalGnhTxH4FK0vR+xHRUWJ+atXJZ8L+d9nzZqF3377DadPn8b48eNFeqAc/c8wDFPaeEKHyOci4V7FXcQqvbkxTdpgFgCo5NEKnUruAssw5aUEUm/Nf4b5UZp14rWF2pi+p4YOgUiAyoqWX0slVXlMomJEJUiZ9vn/999/6NpVSr0g5GC7UaNGiej8hx9+GLdv3xYR+lRUg3L6165daxEEWBxmf5oo4JBhGCY35ty4hc+CAjDttU74+3AkpoX8ned7NCpjXEGj9HSs8vaCM3JO7+8vT3TQnLRYRymHh9yl2gA7sxtYfd8PWy7gjT51UVKUaeHfpUsXUVQhN6ilJk0lCZn9aaKoSj8/vxI9N8Mw5YsGGRn4/UYsUK81ev3yC/D+Irvetzw6Bkfd3NAtJdWu4DimfA4OVHr7Rmy83iJUQpRpsz/DMExZo8Dl+F2M2jspNV8s2CqaillFpUL1zCwMTUo2CAfGMWmuPo9xmtVITi1Z4V+mNX+GYZhyz4BpwH+zgR76HD8A265k483f1lAyG6pVq2bxFrXaaPZXsex3aJqqL4rpo/P0RZdcd1nW/AsAp/oxjPNSNTif1TxbjgWe2wn4VjCs6lJVi/8bIQX1UYBy8jnTiP6uocZni843wuKQLnEjEZmZif+745x9AZSpgdQHwBHopTlYoudj4V8AONWPYZyXBhF++P6xZlj6fPtCHeeLZ/thyJAholT51W+vIj3W2DfENbItULsP4F8ZGLXK4r3atOZYce0mamc4b1ngWI1GpAa2r1IJjkAbdfFUprUFC3+GYZh8MqBxBJpVLlwzHo1Gjd9//x0tW7ZEdlI2rnxzBVlJ+nQvtRp4bCHw8nHovKwH+x3V1YAzc0SfCUBNc5j8w8KfYRimlPDy8sKKFSvgEuSCjNgMXP3uKnTZeTv5Sdw9n/GSSWeYMUkZqOSEXRaZgsHCn2EYpjTQC24qR17llSrQeGng38YfKo2pJms13VkF3IRUNlhm4rClqK4ytqF1dG5rtRZugIEVK2Cer0+pXVN5goV/AeCAP4ZhipIebXqg9pe1EdjN0sSvyyXVT7lFHVIb/nU6wln4IsjU7fJdgB8uu7rgK7P1jHVY+BcADvhjGKYo+aH7D2hZraVh+c6dO1i3TioTy9hHJvv+8wULf4ZhmFLBKKzUKjW8XbzFfFZ8lmhORk2AduzYYVXzl9+p3KLKpXkMw5jDwp9hGKYMUMNfit7X+GjQuHFjkQJIqYDnzxsbxOSGyok136mB/rhoZx97RoIr/DEMw5QBxjcZjxxdDnpV7YXaj9RGdHQ09u3bh8cffBwuL7tA6235uH4+40UAfxk0f2fR/s+bCfrf/HxL7VrKK6z5FwAO+GMYptCYaeqeLp54rdVraBLSBB4eHli+fDmqVq2Kixcuwut3L4ysPVLxVum9yfCwWOcMPFjJWC2RKRgs/AsAB/wxDFPcUGvyVatWic6hB/cexOrPV1tJ+zNddqYBAFM4WPgzDMOUUcjCuHjxYmi1Wpw5fAbZCdmmO7Cst0oiD4LyhIU/wzBMGaZHjx5YsmQJpi6eCq2f5Pf/dEgD8fpgU1Pzt7P4/PNin4c7ngkPwSZPD5MmQCu8PME1ECVY+DMMw5QK9gtqSvvrXr+7mHfTuKFpuBu+bpOFPg3D8nXGnAzrfQIcjS+DArDHwwMvh4UY1g2qVAFvhwZzcKAeFv4MwzDlgAreFbBh2AaMSx2HunXr4mZMdL6PEeTlBmfgHjVGMiNVv263h3spXFHZg4U/wzBMOSHYLRjz58zHrVu38NFHH+H+nfv5CvgL9/GHs5HOnhCrsPAvAJzqxzBMaUCBf5QCWK1aNcTGxuK9Z95DTkaO3e//vOPnuW5/OCERjkCaQvOfEOY8zY7yAwv/AsCpfgzDlBYhISFYtmyZaAd86tApXP/lOnQ5UspfBa/c89+r+FbJdbt7zV5wxOC/7QpTPxsCJFj4MwzDlAbuBQ88q1evHt58801otBrE74/HrX9uifWjG4zGQ7UeKvBxdcG14IhMCGft3xwW/gzDMCVJ/6+BugOAZsaKfQWhUaNG+H7G92L+9srb2LZtG9y17ni//ft4pvEzBTqmM6YKXtVqMTk4EJdcnKvavXN9WoZhmNKm1VPSVASMGz0O169eh4uLCzp16mRY/0KzF9A6vDWeWm96Ho1ag4drD0fCoblY4+0FZ+SWRmOy/Ex4KK67aLHd0wPbrl6Hs8DCn2EYphxDUf/54d22k4F1X1sV/mQ5cHQuu5o2BSLBT9w1GxQ4Omz2ZxiGcRCSk5NFQDJlApjzZus3pRlKBxy9yur76wTWgTOQwuV/WfgzDMM4CmPHjsWMGTMwePBgpKWmGdb/2f9PPF7vceOOVTs4tc9/tp1V/szbKDkSLPwLAOf5MwxTFvnwww8REBCAffv24cOXPjSkADYMbmjX+51F+N/VqGHWIsmCmf6+6Fy5IqK1jukOYOFfADjPn2GYskidOnWwdOlSEQC4eeVmxC6xNP/nhs6hdV0ji3x90LRa5VzN/z8E+OOeRoP/BThmVUQW/gzDMA5E586d8euvv4r5uFVxuLvtrl3vG1pzaK7b26WmwtEYW8F58/9Z+DMMwzgYI0eOxLhJ48R8zLwYbNy40WKff4f8i087fGpYdlG75Gr299C7EByJk255Nzpa66ApkSz8GYZhHJBx/zcOfu38oPHSwMfHx2J7Nb9qGFhjoN3Hc45oAOeB8/wZhmEcEOrwV3FsRWQlZKFNmzaF9/lXaAIknC+6C2RKFdb8GYZhHBAfFx+oXdRwDXI1rDt+/DhSUlIKdDyVyjnEhQ7AZ4EBcHSc49tkGIZxMuoH1cfYhmMxmSr6AVi5ciXatm0r4gFycqy3ATb3+f894G84G6u9PLHAz9JN4miw8GcYhnFQs/8rLV7BiDojxLKfnx+ysrLwzz//iI6A9lAvqB6ciSgXLb4P8IMzwMKfYRjGCejYsSNmz54t5r/66iv89NNP+Xq/MxQAGlQpAtEuprX/iZsOWPefhT/DMIyT8Pjjj+ODDz4wFCtbt26diZsgVzTG2AFno29kBBwNFv4MwzBOxOTJk4XfPzs7G8OHD8enNT/FO23ewZCaQ3J/o7fzFsTJUqmQrgLWennivtoxxKZjfIoShmv7MwxTnmMBZs2aJSoBJiYmYsVvK/BI3UegUZuatn/u+bN4rehdUbz2qtYbzsyDFSvgtdBgdKxSCWkO0BWQhX8B4Nr+DMOUZ9zc3ETgHzUCoi6A1mgX0U68Lh64WHQF7B7ZHc7MVUUswHNhISjvsPBnGIZxQgIDA4ULQKuVar3pdDpU861msZ+3q7fdXQGdhYMe7ijvcIU/hmEYJyczMxPjx4+Hr68v5rw+B0EeQU7b8c9eVnh54oHUNATaqJlQ1mHhzzAM4+Rs27bN0AmwZs2aeP755y320aiMMQE9q/TEhisb4My8HRosXo9HXUV5hM3+DMMwTk6PHj3w8ccfi/kXXngBa9assdiHAgJXP7gay4csh5eLY3a6cyZY+DMMwzB4++23MXr0aFH6d8SIETh69KjFPpE+kajuV71Urq+sk6ZSIQPlBxb+DMMwjEgBpKp/Xbt2RVJSEgYMGICYmBinrfZnLxQJQUK/VdVIdK5SqdxERrDwZxiGYQSurq5YsmQJ6tati+joaAwdOtRmEyBG4qC7G6JdpPC5JLUaBb5bne3rt1BUcMAfwzAMYyAgIACrVq1Cr169RB0AtYNUtCsurmq1CMzONiy/FRKEexo1amVk4qibG+bciIVdhZE9/FGS8LfKMAzDmFC9enWcPn0avXtbr+rXr3o/8VrFt4rJ+nqBztUFkJgSEoQ9irz/Nd5e2Ovhgfl+vjjm7obNXp6wi8CSjaVg4c8wDMNY4KKoaHf+/Hn8/vvvhuW2Fdpi+eDlWDRwkWHd8NrD8VPPn9Aq3PnKnn8eFGhzm9EmkAe1eqEkYbM/wzAMY5Nr166hbdu2uH//vnAJ9O/fX6yv7m+qqQ6qMQgB7gEYWnMoDtzk0uf5poT7BbDmzzAMw9ikUqVKePDBB0Xg38MPP4wjR46U9iWVK1LVtoX6a5nPoLRg4c8wDMPkmgJIzX+oEFBycrLQ/CkTwBZuGrcSvb6yzgfBQbipMe2YKHM5JxylhdML/6pVq6Jx48Zo2rSpyG9lGIZhLP3/ixYtEq3MKfd/4MCBoh2wNbpV7oaOFTuiTYU2JX6dZZXVrR9FWcPphT+xe/duYcrasmVLaV8KwzBMmcTf31+kAIaGhorn5SOPPIKsrCyL/bRqLWb0mIFfev2C3/r8VirXWuao2AKpKhWeDg/BfF8fseq9zFGlekks/BmGYRi7LaUrVqyAu7s77t27JyoBylir9988rHkJX2HZZG/MXizx8RYpgF8GBWBndgPMy+6NFI9b+CLQHyklHOxX5oX/9u3bhXkpIiJC+J2WLVtmsc8PP/wg/iDpj7FNmzbYv39/vs5Bx+3cuTNatWqFP/74owivnmEYxvFo3bo1Nm/eLCayBrzT5h083ehp1AqoVdqXVmbZc2OPqAQoc9RTsphcrbIav/v5YkaAX4lfU5lO9aPgkiZNmmDs2LEi2tSchQsXYtKkSZg5c6YQ/NOnTxdFKc6ePStMUwT58q2ZptavXy8GFTt37kTFihVx48YNEdDSqFEjEQNgjfT0dDHJxMfHi9e7d++KfthMyUD3OiUlBXfu3DHJRWZKDv4OnPv+165dWzyfaeoZ0hPXr18X12KN7FS7M90dmnVqN0B/L34ISIIWfxvuzS73EIyxcf/yixyLodPl0WVAV06gS126dKnJutatW+smTJhgWM7OztZFREToPvvsswKd49VXX9XNmTPH5vYpU6aI6+CJJ5544oknlOHp2rVrucq7Mq3550ZGRgYOHjyIt956y7COalCT9r5nzx67jkGjVspd9fHxEb4rMmNRK0tb0LnI0iBD7yWtPygoSLgPihtyTRw4cKBEj2HP/nntY2t7ftYr1yUkJCAyMlIUH/H19UVJUVbvf1775XebPetK4zvg+1+699/WtTnDM6hVObr/pCuT9k+W7dwot8I/Li4O2dnZCAsLM1lPy2fOnLHrGLGxsaJrFUHHevrpp8XNtYWbm5uYlJDPq6TQaDSF/kPL7zHs2T+vfWxtz896a+touSR/eGX1/ue1X3632buupL8Dvv+le/9zuw5HfwZpytn99/PLO4ag3Ar/ompecfToUZQXJkyYUOLHsGf/vPaxtT0/64viszvq/c9rv/xu4/uf//2d4f478zNoggPdfxmV3p9e5iGz+tKlSzFkyBCD2d/T0xOLFy82rCNGjRolalAvX768FK+WKU7I5EYjWwq4LMlRN2OEv4PShe9/6ZLgAPe/TKf65YarqytatGiBTZs2mfjgabldu3alem1M8UKulylTpli4YJiSg7+D0oXvf+ni5gD3v0xr/hSEd+HCBTHfrFkzfPPNN6IEb2BgICpXrixS/UjT/+mnn0TuKaX6/f3338Lnbx4LwDAMwzBMORD+W7dutVpvnwT+3Llzxfz333+Pr776Cjdv3hQ5/d9++63I+WcYhmEYphwKf4ZhGIZhip5y6/NnGIZhGKZgsPBnGIZhGCeDhT/DMAzDOBks/BmHhspvdunSBfXr1xcNmxYtWlTal+R0UBXNgIAADBs2rLQvxSlYuXIl6tSpg1q1auGXX34p7ctxOoaWk793DvhjHBrq1khlnCkThDJCqDbEuXPn4OVl2XucKb6sHao1/ttvv4miXEzxQR1MaaC7ZcsWUYSG/t53794t+o8wJcPWcvL3zpo/49BUqFBBCH4iPDwcwcHBohkTU3KQ5YWaZzHFz/79+9GgQQPRptzb2xt9+/YV7cuZkqNLOfl7Z+HPlCrbt2/HwIEDRQcqKuG8bNkyi31++OEHVK1aFe7u7qKGAz3gCgJ1gaQGTtSNiyn5+88U//cRExMjBL8MzV+/fr3Err+8s92Jfg8s/JlShdoqN2nSRPygrEFVHKmNMpXSPHTokNi3d+/euHXrlmEf0uwbNmxoMdGDUIa0/SeffBI///xziXyu8kJJ3X+m5L4PpuAkO9P9J58/w5QF6M9x6dKlJutat26tmzBhgmE5OztbFxERofvss8/sPm5aWpquY8eOunnz5hXp9ToaxXX/iS1btugeeuihIrtWZ6Ag38euXbt0Q4YMMWx/6aWXdH/88UcJXrXjgEL8HsrD3ztr/kyZhTo3kqm+R48ehnVqtVos79mzx65j0G949OjR6NatG0aOHFmMV+t4FMX9Z0r2+6AeJydOnBCmfuqNsmbNGqGZMoUnw8F+Dyz8mTJLXFyc8NGbN2miZYrct4ddu3YJUx357sg8TdPx48eL6Yodi6K4/wQ9HIcPH47Vq1ejUqVK5fJBWV6+D61Wi6+//lr0RKG/9f/7v//jSP8S/j30KCd/79rSvgCGKU46dOggWj0zpcfGjRtL+xKcikGDBomJKR02lpO/d9b8mTILpeVpNBqRp6+Eliltjyle+P6XLfj7KF2CHez+s/Bnyiyurq6iSMmmTZsM60iLp+V27dqV6rU5A3z/yxb8fZQurg52/9nsz5QqFJR04cIFw3JUVBSOHDmCwMBAVK5cWaTVjBo1Ci1bthTBTNOnTxfpOGPGjCnV63YU+P6XLfj7KF2SnOn+l3a6AePcUEoM/RmaT6NGjTLs89133+kqV66sc3V1Fak2e/fuLdVrdiT4/pct+PsoXbY40f3n2v4MwzAM42Swz59hGIZhnAwW/gzDMAzjZLDwZxiGYRgng4U/wzAMwzgZLPwZhmEYxslg4c8wDMMwTgYLf4ZhGIZxMlj4MwzDMIyTwcKfYRiGYZwMFv4MwzgNo0ePhkqlEtOyZcuK9Nhbt241HHvIkCFFemyGKWpY+DOMgwgz5aRsTsKY0qdPH9y4cQN9+/Y1rLM1GKD7a68gb9++vTjuiBEjivR6GaY44K5+DOMAwmzOnDkm60JCQiz2y8jIEG1JnR03N7di6b9O95aO6+HhgfT09CI/PsMUJaz5M4yDCDPlpNFo0KVLF0ycOBEvv/wygoOD0bt3b7H/iRMnhNbr7e2NsLAwjBw5EnFxcYbjUYvSJ598UmyvUKECvv76a3EsOk5umrK/vz/mzp1rWL527ZrQgmk9tUQdPHgwLl++bKFVT506VZwnKCgIEyZMQGZmpmEfEqJvvPEGIiMjxeesWbMmfv31V+pGKubpvUqo/WpxWT7o2q1ZWejeMEx5g4U/wzgwv/32m9BId+3ahZkzZ+L+/fvo1q0bmjVrhv/++w9r165FbGysian6tddew7Zt27B8+XKsX79e+LIPHTqUr/OSAKfBho+PD3bs2CHOT4MJslKQBUJmy5YtuHjxonila6XBg3IAQYOQP//8E99++y1Onz6Nn376SRyHhO7YsWMtLB603KlTJzEwKGpoAEJmfXk6fPiwGLDQ+Rim3FHaPYUZhik41Gdco9HovLy8DNOwYcPEts6dO+uaNWtmsv9HH32k69Wrl8m6a9euiZ7lZ8+e1SUmJoo+5X///bdh+507d3QeHh66l156ybCO9l+6dKnJcfz8/HRz5swR8/Pnz9fVqVNHl5OTY9ienp4ujrNu3TrDtVepUkWXlZVl2Gf48OG6hx9+WMzT9dB5NmzYYPWzX79+XXz2ffv2ieWMjAxdcHCwbu7cubner8GDB1usp/O4u7ub3EeatFqt1f1TU1N1bdq00Q0YMECXnZ1t1zkYpizBPn+GKed07doVP/74o2HZy8vLMN+iRQuTfY8ePSq0bNKezSENPDU1VWjmbdq0Mawnk32dOnXydU10HjK9k+avJC0tTZxHpkGDBsJFIUPm/+PHjxtM+LStc+fOVs8RERGB/v37Y/bs2WjdujVWrFgh3ATDhw9HQZg2bRp69Ohhso5cDtnZ2Rb7ktUhMTERGzZsgFrNBlSm/MHCn2HKOSTsbZm5lQMBIikpCQMHDsQXX3xhsS8JXnt95WR2lxRmI0pfPZ2HBh5//PGHxXuVwYguLi4Wx83JyRHzFDiXF0899ZSIWSDBTSb/hx9+GJ6enigIFCthfh9p8EKuEiUff/wx1q1bh/3791sMbhimvMDCn2GciObNm2PJkiWoWrUqtFrLn3+NGjWEQN63bx8qV64s1t27dw/nzp0z0cBJgJPfW+b8+fNISUkxOc/ChQsRGhoKX1/fAl1ro0aNxECA4g/MNXKZfv36iQEOWT4ofmH79u0oTujeffjhh1izZo24VwxTXmF7FcM4ERRNf/fuXTz66KM4cOCAMMGTFjtmzBhh3iZ3wLhx40TQ3+bNm0VmAEXlm5u2KWjw+++/F0FvFDj43HPPmWjxjz/+uMgwoAh/CviLiooSgYMvvvgioqOj7bpWGqCMGjVKmNgps0A+xt9//23Yh9wCdH1vvfUWatWqhXbt2qG4oHtBAYjkCiB3xc2bN8VE95Nhyhss/BnGiSA/OUXek6Dv1auX0K4phY/S8WQB/9VXX6Fjx47CPUAad4cOHSxiByj9j6Lfab/HHnsMr776qom5neZJCyfrwYMPPoh69eqJQQX5/PNjCSCNftiwYXj++edRt25dPP300yIVUQkdl+IUaABTnNAgh6wbZPYnF4k80edjmPKGiqL+SvsiGIYp21Aue9OmTTF9+nSUNciy0L17d1FXgOoW5AZZCciHX9SlfUv6HAxTWFjzZximXEKR/eRCeP/990WEf16CX2blypXCvUGvRT0IoeNaC3JkmLIGB/wxDFMuoeI/ZPIni8S8efP+v307NgEYhoEo6qE0nibQ1MGuXaRIEbj3KjeuPxzo1Z+ZWd193nuy/1JVnfPE7XZKCX9i9geAMGZ/AAgj/gAQRvwBIIz4A0AY8QeAMOIPAGHEHwDCiD8ArCwPWqfBgdEXlJ8AAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 500x400 with 1 Axes>"
       ]
@@ -1093,7 +1116,7 @@
     "for spec in ds_binned[\"S\"]:\n",
     "    ax.loglog(\n",
     "        ds_binned[\"freq\"],\n",
-    "        ds_binned[\"auto_spectra\"].sel(S=spec).mean(dim=\"time\"),\n",
+    "        ds_binned[\"auto_spectra\"].sel(S=spec).mean(dim=\"time_psd\"),\n",
     "        label=spec.values,\n",
     "    )\n",
     "ax.plot(\n",
@@ -1111,7 +1134,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x400 with 1 Axes>"
       ]
@@ -1139,7 +1162,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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q1aVy5coJik8AAFJPl/HpaO/bb79t1vPDpsP+M2bMMPswa3nGr776Sp599lkz9N+sWTOzxv+RRx4xewD4M12lsHHjRsmePbu5UtULAF2tkC9fPqubBgAB4+bNm9KlSxdZtWqVSerT3fpg44Q/HebXNf5vvvmmHDp0yBRy0KS/qVOnSpEiRaRx48bmKvD3338Xf6R7FWjgd1216t7SegAAUkc7gU8//bSp7Jo5c2az+suV+A0bZ/vHV7FiRRk6dKgZDdClfz169JBvv/1WPv30U7deT3vl4eHh5kJCk0f0lyox3QtaVxpojWi98Ni6dWuah/41UVGnL3SuKn/+/G61FQCcRjtL06dPl7lz55rO1GeffWaW98H/ZfTmjk26zEMPd+lQvAbmiIgIMxyf2Pz5800m6ZQpU0zgf/fdd6VFixZmFCI0NNQ8R+fzdUgqMV16ohcVuvxk9+7dZi2qvoeuXtAqhQCA2xszZoxZv69mzZplpnxh0+CvG/mcO3fObMwQ3/79++Xee+/1ZNtMQqEeKRk3bpz07t1bevbsac71ImDZsmUmH+Gll14y9+3atStV76UBXy80dKRCLwCSo1MDerhcvHjR/Hvjxg1zAPAd12eOz551NMdr/Pjx8s9//lM6derEz8LH0vP/nabgr7X7NbFPh8Z1nkez47XHrbp162bq/PuKrizQpYbDhg1LkIOgQ06bN29O1Wtob1/n/DXx78KFC2aaQVcu3O4qd+TIkUnuX7duXVzuAADf0iQzWEenXnU5n2sEAL6j5fV9Evz/9a9/mYCrvWT9V+f0X375ZencubPPE+XOnj0rMTExSYbo9fynn35K1Wvo3gOaqOJK9Bs4cKBUqVIlxefrhYZOM8Tv+RcvXlyaNGnCCgHAgl6PBn7tfWbKlMnq5jjGggULTI6UJvXxM7DWn3/+6Zvgrz9oV7CtVauW6Snrus7Dhw+bhLxAo4WIUjstoHRDiuQ2pdBfen7xAWvw+fOdpUuXmk6fZvVrcrWW7lX8DKyRnv/zNGX7axKdbs/oouv49arv4MGDCe73BZ160OxSHbqPT8+14iAAwHN0elPzoTSBWpOjdXUXAleagv+cOXPisuhd9ApQl/Jt2LBBfEnfV0cf1qxZE3ef5iHoOWtMAcBztIZLmzZtTMKzZvTPnDkzQTl3BJ40DfvrPE9yoqOjzfCDDglpAI5Pf2HcdfnyZTOl4HLkyBEzTK8jDiVKlDDz7zoEpSV6dQhfl/rp8kBX9r83E1z00JwDALCzvXv3mlVX+vdYN2ybN2+eZMzotVXi8JF0/wRXrFhhMv2TSzzQPID0BMjt27ebZDoXV7KdBnxdU6pLS86cOWM2GTp16pRZ06/t8fY6/f79+5tDE/5CQkK8+l4AYBVNim7evLn89ddfUq9ePVNoTQuqIfClO/hrhrxu4qAB2NNB98EHH7zjKoIBAwaYAwDgWfo3XYP+b7/9ZpbysUOffaQ7+GuCnfbIqYoHAPaivXxd2qd1UPLkyWN1c+BB6c7Y0OzP9evXe6Y1AABL6X4nWrXPNeqq8/vUMbGfdPf833vvPXn00UdNWVwtkJN43eGgQYPS+xYAAB/QhGndjl03Z9Mt2nXHVthTuoO/LvPTTXJ0eEhHAOIX+9Hbdgz+ZPsDsBtdxqfr9zXwayKzVm6FfaU7+L/yyium3r1upOOUdZ9k+wOwEy3c06VLF9OR031KNLlPV0/BvoI8scGOLrlzSuAHADvR2iy6O+oXX3xhiqctXrxYGjRoYHWz4GXpjti65n7+/PmeaQ0AwKeef/55UzdFy6Xr33LdGRX2l+5hf5331qSQlStXStWqVZMk/I0bNy69bwEA8BLdll17/NOnT5d27dpZ3RwESvDX0o81atQwt/ft25fgsUDc6Q8AnOTxxx+X+++/32xPDufI6ImdnpyGbH8AgUyH9xs2bChFixY158kF/phbsbL1yDmJuhQtobmySt3SeSU4iA6dXbA7gxvI9gcQqHRjHl3GV7JkSdm6dasUKFAgyXNW7DspI786ICcvRMfdVzgkq4wIryQtKxf2cYvhNwl/e/bsSbJ73+3s37/fLCUBAFhn2bJlZiM2rd7XsmVLyZ8/f7KBv9/cnQkCvzp1Idrcr4/DocFf5/iT28UvJfXr15fjx4+781YAAA/QImxajl07Ytrz16nLxHlZOtSvPf7ktlNz3aeP6/PgwGF/vWp89dVXTTGI1NYCAABYQ4f3w8PDJTo6Wtq0aWOW9iVXm0Xn+BP3+OPTkK+P6/Pq3029f8cF/8aNG8uhQ4fS1PPPli2bO28FAEgHnXZt1aqVXL58WZo0aWKS/RIvyXbR5L7USO3zYLPgzy5+ABAYcufOLYUKFZJ77rnHVO/TfVhSoln9qZHa58F/ke0PADamy/k2bNhghvlz5cp12+fqcj7N6tfkvuRm9TVDoFDIf5f9IbBRkN8NmihTqVIlqVOnjtVNAYAkzpw5Y3r5LprVnzfvnQO2ruPX5Xwq8Yp+17k+znr/wEfwd4Ou8T9w4IBs27bN6qYAQAIXLlyQFi1aSPv27WX27Nlp/npdxz+5a03Tw49Pz/V+1vnbA8P+AGATV69elUceeUR+/PFHU7xH6/a7QwN8s0qFqPBnYwR/ALCBa9euSYcOHeS7774zlUe/+eYbKV++vNuvp4Ge5Xz25ZFh/2+//Va6du1qlvT9/vvv5r45c+aYX0IAgHdp4Z4uXbqY3VW1/sry5culevXqVjcLdg7+X3zxhZlf0nX8OtSkV5+ueafXX3/dE20EAKRAS6337t3b/C3WrXkXLVokDRo0sLpZsHvw/9e//iVTpkyRadOmJSgcoVtE7ty5M70vDwC4DS3Rq/P7wcHBZtOeZs2aWd0kOCH4a6U/rfiXmM45nT9/Pr0vDwC4Q/AfO3asGXnVDH/AJ8FfK0cdPnw4yf0631+mTJn0vjwAIBk6vK+1+l0XAFWqVLG6SXBS8Ne5pmeeeUa2bNlifgH/+OMP+fjjj2XIkCHSr18/sSOK/ACwkk6zai//4YcfZuM0WLPU76WXXjIJJ02bNjVrTHUKIEuWLCb4Dxw4UOxa5EePixcvmukNAPAV3ZinT58+5natWrVS3KQH8Grwj4yMlGHDhskLL7xghv915yjtFefIkUOOHz8uJUqUSO9bAABEZNmyZWZZtW6rrhcAOtevI66Az4N/6dKl5eTJkxIaGmqCvsuff/5pHouJiUnvWwCA4+nmPB07djRr+jt37mymHwn8sGzOX69Ak6MjALfbOhIAkDrbt2+X8PBwk+Cn/86aNcss7QN83vMfPHiw+VevPF977TVTVcpFe/uaAEiFKQBIP+3ta7Bv0qSJfPbZZ8zzw7rgr2tKXT3/vXv3mspSLnq7WrVqJukPAJA+9erVk++//16KFy/OiCqsDf7r1q0z//bs2VP+85//yF133eWZFgEA5HjkCVm367DkLn7Pf3fVq1CRXfXgPwl/M2fO9ExLAADGvI37JKLjwxJ94awUfGykZClaUQqHZJUR4ZXMdruA32zpe+DAAbO0L3HBiTZt2njqLQDA9r7YfEh6PNZOrp85LsG58ktwzrzm/lMXoqXf3J0yuWtNLgBgffD/7bffTKUpnffX5D9X9r9rCQpL/QAgdS5dviI9n+go10//KkHZQ6Rgp9GSMaSgeUz/supf1ZFfHZBmlQoxBQBrl/ppaV9dzx8VFWUy/vfv3y8bN26U2rVry/r168WOKO8LwNN01LT5w23l0rF9kiFzdin42CjJlK94gufoBcDJC9Gy9cg5y9oJe0h38N+8ebOMGjVK8ufPL0FBQeZo2LChjBkzRgYNGiR2pKV9dZpj27ZtVjcFgE2W8nXp0kV+2LhGMmTMIqGPjpDMBe9O8flRl/67oQ9gWfDXYf1cuXKZ23oBoBv7qJIlS5rtfgEAt3fjxg2zV0jGTJmkQPuXJWuxe2/7fM3+Byyd869cubLs3r3bDP3fd9998uabb5p1/h988AFb+gJAKmTLlk2WLFkiW7Zukxe/u2aS+5Krnaqz/IVCskrd0v9NAgQs6/kPHz7c7OqndPj/yJEj0qhRI1m+fLlZ/w8ASJ7mRbmSpHU31MaNGprlfCpxOp/rXB8n2Q+WB/8WLVpIhw4dzO2yZcvKTz/9JGfPnjUJgA0aNEh3AwHAjsaPH2/K9Wqp9Ph7pOgyPl3Opz38+PScZX7wu3X+8el2vvqLrVMAp06d8sZbAEDAmjFjRtz+KPny5UuyO58GeF3Op1n9mtxnKvyVzkuPH9YH/2vXrsk///lPWbVqlZnjHzp0qLRr1878UutUgG5C8dxzz3mupQBgAwsWLJDevXub27r/ySuvvJLs8zTQ1787n49bB6dwO/jrTn5Tp06VsLAw2bRpkzz66KOmzv8PP/wg48aNM+dsOQkA/+frr782S/o0T0ovAHR0NHGvH/Dr4K9Xr7Nnzzble/ft2ydVq1Y1a1U1859fZgBISIufaX6ULuvr1KmTTJ48mb+VCLyEvxMnTkitWrXilvtppqoO8/PLDADJl0LX6dKHH35Y5syZw8goArPnr8V9dK4/7oUyZpScOXN6ql0AYCtPPvmkFCtWTO6//37JlCmT1c2Bw7kd/HVpiv4ya49fRUdHS9++fU2mf3xffvll+lsJAAHo6NGjZs+T0NBQc645UkBAB/8ePXokOO/atasn2gMAtqClzps2bWp6+atXrza9fiDgg//MmTPFqXRXPz3YrhhAcrTQWbNmzcw8/9133838PuxX4c+J2NUPQEp0g56WLVuavxFFixY1vf7ChanKB/9C8AcAD7l69aqEh4fLjh07zC6nGvhLlSpldbOAJAj+AOAB169fl44dO5r1/HfddZesXLlSKlSoYHWzgGQR/AHAQ/P8P//8s9med9myZVKzZk2rmwT4dmMfAHCaIkWKyLfffiuHDh2Shg0bWt0c4Lbo+QNAOuqdaHlzF03se/DBBy1tE+Cznv+aNWvMERUVZTasiE93+QMAOxo9erSMGjVKZs2aRa0TOCv4jxw50vzy165d21z1UtsfgBP85z//kREjRpjb586ds7o5gG+D/5QpU8xVb7du3dL7UgAQEHRE89lnnzW3tfMzaNAgq5sE+HbOX5e3NGjQIL0vAwABQbcz7927t7k9ePBgGT58uNVNAnwf/Hv16iWffPJJel8GAPzeihUrpEuXLia3Sf/2vf3220x1wpnD/rqb3wcffGAqWVWtWjXJVpXjxo1L71sAgF/Qwj03btyQTp06mSlPAj8cG/z37Nkj1atXN7fjL3lRfDAA2Il2ZqpVqyadO3dmsx44O/ivW7fOMy0BAD907NgxU8BHRzW1Q/Pkk09a3STAP9b5nz9/Xj788EM5ePCgOb/33nslIiJCQkJCPPHyAGCJI0eOmGp9Wqr3s88+M6V7ATtId8Lf9u3bzX7V48ePN2td9dChMb1v586dnmklAPjYH3/8IWFhYebf3377Tf7++2+rmwT4T8//ueeekzZt2si0adMkY8b/vtzNmzdNJqyug9UdrgAgkPz555/SvHlzE/TLlCkjq1atkrx581rdLMB/gr/2/OMHfvOiGTPK0KFDTdU/AAgkFy9elJYtW8r+/fvNXL+uZNJ/ATtJ97C/7lt9/PjxJPdHRkZKrly50vvyAOAzOrQfHh5uOjX58uUzPf7SpUtb3SzA/4K/rnd96qmnZP78+Sbg6zFv3jwz7P/EE0+IHU2aNEkqVaokderUsbopADzowIEDsmPHDtOp0TX9+jkH7Cjdw/6uClfdu3c3c/1Kl8T069dP3njjDbGj/v37m0OHB1nRANhHrVq1zA6lWrZcb6uYW7Gy9cg5iboULaG5skrd0nklOIgaJnB48M+cObPZ3WrMmDHy66+/mvs00z979uyeaB8AeFVsbKzJ6C9atKg5v+++++IeW7HvpIz86oCcvBAdd1/hkKwyIryStKxc2JL2An4x7O+iwb5KlSrmIPADCJTA/8ILL5iqfTrcH58G/n5zdyYI/OrUhWhzvz4OOKrnrztZjR49WnLkyGFu3w61/QH4q3/961/yzjvvxJUnjz/Urz3+2GS+Ru/TQX99vFmlQkwBwDnB/8cffzSbW7hup4Ta/gD8lU5Xvvbaa+b2u+++Kz169Ih7TOf4E/f4E18A6OP6vPp35/NJewHLg3/8ev4fffSRFCtWTIKCgpIMp2nmPwD4m5kzZ5oiZGrkyJHyzDPPJHhck/tSI7XPA2w3569rYM+ePZvkfi3zy/pYAP7m888/N0uRlU5bvvrqq0meo1n9qZHa5wG2C/7aw0/O5cuXJWtWPhgA/If+vZoyZYrcunXL1CdxLVVOTJfzaVZ/ShOXer8+rs8DHLXUz5Xopx8cnTeLn+EfExMjW7ZskerVq3umlQDgAfr3asmSJfLee+/J888/n2Jekibx6XI+zerXZ8Tv4ri+Qh8n2Q+OC/6uRD+9kt67d69Z7++it3XpzJAhQzzTSgBIh6ioKAkNDTW3taOie4/cia7jn9y1ZpJ1/oVY5w8nB39X0l/Pnj1N1qyWwwQAf3Pw4EFp3LixqTqqyX1pWYWkAV6X81HhD3YT5ImsWQI/AH909OhRadasmUlKXr58uURHpz07XwO9LudrW72o+ZfADztId3nf+Bti6O5+WhM7vjZt2njqLQAg1U6ePClhYWHy+++/mw16VqxYIdmyZbO6WYA9gv9vv/0m7du3N/P+Opzmyv53Da1p8h8A+NKff/5pevy634guOdatefPnz291swD7DPtrcQz9cGlCjSbS7N+/XzZu3Ci1a9eW9evXe6aVAJBKly5dklatWpm/RUWKFJHVq1ebfwF4sOe/efNmWbt2rbmq1ip/ejRs2NDs8jdo0KDblv8FAE9buXKlbNu2TfLly2d6/GXKlLG6SYD9ev46rJ8rVy5zWy8AdGtMVbJkSTl06FD6WwgAadCxY0eZNWuWmePXuX4AXuj5V65cWXbv3m2G/nUf7DfffNOs8//ggw+44gbgE9oJuXLlill5pHlH3bt3Z2MxwJs9/+HDh5tSmWrUqFFy5MgRadSokVlWM2HChPS+PADclgZ7XcOva/lPnz5t7iPwA17u+bdo0SLudtmyZeWnn34ym/rkyZOHDyAArwf+YcOGybRp00y+0datWyU8PNzqZgHOWeevXMv88uZlswsA3rdgwQL55JNPzG2daiTwAz4a9lcffvihmfvXXfz00NvTp0/3xEsDQLImTZoUF/jHjRtndukD4KOev+7opx+8gQMHSv369eOW/z333HOm4p/mAQCAJ2k2v/6NceUduW4DSJ0Msa6xejcVKFDAJPY98cQTCe7/9NNPzQWB1tS2q4sXL0pISIj5HnVNMQDv+/vvv6VixYpy7NgxM8z/+eefJ9hVFL5z48YNk9zdunVryZQpk9XNcWQly/z588uFCxfSvMdORk/88LWaX2K1atWSmzdvpvflASABrc+/YcMGmTp1qtStW5fEYsCKOf9u3brJ5MmTk9yvyTddunRJ78sDgKHr+F20iFhat+cF4OFsf034++abb6RevXrmfMuWLWa+XwttDB48OO55mhsAAGmlZcJbtmwpU6ZMMRuJAbA4+O/bt09q1qxpbusOWkrnIPTQx1y4QgfgDq0dovVEzpw5IxMnTpR27drx9wSwOvivW7dOAt3Vq1dNAtGjjz4qb7/9ttXNAfA/R48elbCwMBP4NY9o0aJFBH7AX9b5B7p///vfcVMWAPzDyZMnTeD//fffzcW5btST1oxmAB7s+es8/ujRoyVHjhwJ5vST4+/z/L/88osZVtQlQ/GnKQBYR0uEN2/e3Ewl6qZhujWvTiUCsLDnr8k3usTPdTulY9euXelq3MaNG01QLlKkiBnq0yG/5Kp8lSpVylQW1F0FtbZ3WgwZMkTGjBmTrnYC8Kz333/fXIwXLlxYVq9eLUWLFrW6SYCtZEzvPL835/x1aU+1atUkIiJCOnTokOTx+fPnm5EHzQDWwP/uu++axKBDhw5JaGioeU716tWTrTegqxO2bdsm5cqVM8emTZvu2J5r166ZI36RH6UXQq6LIQDp98ILL5jCJbpcuHjx4sl+vlz38dmzDj8Da6Xn/z3dFf602pa+RPbs2c25Vt1auHChVKpUyQzbeYr2/PV1NdPXRQN+nTp15L333jPnurWw/qHQyoIvvfTSHV9TdwObO3euBAcHy+XLl81/5PPPP29KFifnn//8p1lbnJjWF3d9/wDcoxfp+jnXzyOA1CWrd+7c2a0Kf+kO/hrgtVfet29fOX/+vJQvX96U2tSStzrfr/tseyP4X79+3QRcLe0Z/4KgR48eph2LFy9Oc61wHWa8XbZ/cj1/vdjQxCTK+wLui4mJkSeffNJcwM+cOTNV5Xr1Yl1zAZo1a0ZpWYvwM7C+vK9OjVlS3nfnzp0yfvx4c1sDcaFChcx8/xdffGF60J4K/onpxYX+wShYsGCC+/VcE/i8IUuWLOZITH/p+cUH3KP9jwEDBphpvIwZM5qpvLSsvuHzZz1+BtZIz/95Rk8MO+TKlStuHl1HAYKCgsyHV6cAAoX2OgD4PvC/+OKLphy4ju7pNBzLboEAWOdftmxZk4UfGRkpK1eujJvnj4qK8uqaXF32o3ODp0+fTnC/nuvoAwD/pytt3nrrLXNbLwA6depkdZMAR0h38NehfV0up8vtNAGvfv36caMANWrUEG/ROUGt+LVmzZq4+3S+UM9dbfAWXV6oCY2abAjAPZqo+8orr5jb77zzjvTq1cvqJgGOke5h/44dO0rDhg1N0psuy3Np2rRpujfg0Az8w4cPx50fOXLE1A7ImzevlChRwswNaoKfbimsW3vqUj9dHtizZ0/xpv79+5tDE/5CQkK8+l6AHf3xxx8ydOjQuA7EnYqFAfCz4K9L/XR43zXU7lrqp+U4NSCnx/bt26VJkyZx564/EBrwNTtfhwi15rf+8Th16pRZ068lQBMnAQLwL1q4a/ny5WaEUJfQAgiw4N+2bdsES/106F8zED2x1O/BBx80CUG3o1nCegAIjLX8mtHv+nzrkRoxt2Jl65FzEnUpWkJzZZW6pfN6uaWAvQV5Yqlfo0aN4pb6aa9be/+zZ8+WCRMmeKKNAGzg+++/NyOC+/fvT9PXrdh3UhqOXStPTPtBnpm3y/yr5yv3J0z2BeDD4G+XpX4AvEdzdR5++GGTw6O7aKYl8Pebu1NOXohOcP+pC9EycN5u2f0n2/sCjlrqZyWy/YHU07029O+CViHT5ODp06eneqh/5FcHJLmJP9d9Xx4NMs8D4JClflbSTP8DBw6YjYEApExH/8LCwkxibs2aNWXp0qWp3gdD5/gT9/jj05B//noG2X7sLw+2GHAGv17qByBw6QocDfwnTpyQChUqmJU4aVkaq8l9qXve/+23AcBHwV/pMr/EVfXSu8wPQGDTsr06x6+jgqtXr5YCBQqk6es1qz91z0u63wYALwR/XW8/evRoyZEjxx2Lc+hyPwDOM3HiRImOjjYJfkWLFk3z1+tyvsIhWU1yX3Kz+prqF5I5VmqXzOOR9gJO4lbw1137dCtH1+2U6EYdAJxDS2zrah+lCb+6U5+7goMyyIjwSibbX/+SxL8AcP1l6VDqlnkeAB8E/3Xr1iV7G4BzaYfg0UcflQYNGsSV7k2vlpULy+SuNU3Wf/zkv0IhWeWVVuUl5tgOj7wP4DQZ03uVr2V2v/zySzl69Kjp6ZcuXdokAXbr1s22PX9d6qdHTEyM1U0B/IL+LdA9NRYvXmyW/OpFgP4t8NQFQLNKhZJU+LsVc1OWU0oE8G3w17K7bdq0MfW5Ncu/SpUq5r6DBw/Kk08+aS4IdP2/HbGxD/B/9HOvn4ePP/7YlO7VSp+eCvwuOrRf/+58Ce67xbU34Pvgrz3+jRs3mi1042++o9auXSvt2rUzJX67d+/ufusA+L1hw4bJlClTzEjf3LlzTSU/ADYt8vPpp5/Kyy+/nCTwq4ceekheeukl0xMAYF9jxoyRsWPHmttTp041O20CsHHw37Nnj7Rs2TLFx1u1aiW7d+929+UB+LkdO3aYDoB6++23pXfv3lY3CYC3h/3PnTtndvBLiT7211+U3QTsqlatWmbnTt2++/nnn7e6OQB8Efw10921L3dygoODzd7dAOyX4OdayTNw4ECrmwPA19n+mtWfJUvypTWvXbNvvW2W+sGpVq1aZSr2LVy4UPLkobIe4Ljg36NHjzs+x66Z/iz1gxNt3rzZrOK5evWqvPHGG3GJfgAcFPxnzpzp2ZYA8FuavNu6dWsT+Js3by6jRo2yukkArMj2B+AMP//8swn458+fl/vvv98U8Eppug+Ag7b0BeCfYm7FJimLm5aNcI4fPy5hYWESFRUlNWrUkGXLlpndPAEENoI/YFMr9p1MsiGObpGrO+VpvfzUJPV27dpVIiMjpUKFCqZmPzkugD0w7A/YNPDrVrjxA786dSHa3K+P34ku55s+fbo0btzYZPkXKFDAiy0G4EsEf8CGQ/3a449N5jHXffq4Pu9OypUrJ+vXr5dixYp5vJ0ArEPwB2xG5/gT9/jj05Cvj+vzEouOjpa2bduaIX4Xu27NDTgZwd8NWuCnUqVKUqdOHaubAiShyX3uPO/GjRvy+OOPy5IlS6RLly5y6dIlL7UQgNUI/m7QAj8HDhyQbdu2Wd0UIAnN6k/r827duiURERGyePFis4zv888/l1y5cnmxlQCsRPAHbEaX82lWf0qD9Xq/Pq7Pc2X1DxgwQObOnWv269DA/+CDD/q0zQB8i+AP2Iyu49flfCrxBYDrXB93rffXbXknT55s5vZnz54tjzzyiI9bDMDXCP6ADek6/slda0qhkIRTAHqu97vW+Wu1Pq3Tr6ZMmSJPPPGEJe0F4FsU+QFsSgN8s0qFblvhr02bNmYDrsqVK8vTTz9taXsB+A7BH7AxDfT1786X4uM6xz9r1iyW8wEOw7A/4DCa0d+nTx+JiYkx5wR+wHno+QMOsmbNGnnsscfk+vXrZqOevn37Wt0kABag5w84xObNm031Pg38HTp0kF69elndJAAWIfgDDrB7925p3bq1XLlyRZo3by6ffPKJme8H4EwEfzdQ3heB5JdffjEB//z583L//feb5X1axQ+AcxH83UB5XwQKHeLXHn9UVJRUr15dli5dKjly5LC6WQAsRvAHbCxz5szyn//8xyT36U59uXPntrpJAPwAwR+wOe35b9++XUJDQ61uCgA/QfAHbOby5ctma97Dhw/H3RcUxEcdwP8h3RewkejoaGnXrp1Zz793717Zs2ePBAcHW90sAH6G7gBgEzdv3jQb82jg16S+GTNmEPgBJIvgD9jArVu3JCIiQhYtWmSW8X311Vdy3333Wd0sAH6K4A8EuNjYWBk0aJDMmTPHFO5ZsGCBNGnSxOpmAfBjBH8gwE2cONEUntINembPni3h4eFWNwmAnyP4AwGuS5cuptrk5MmTzZw/ANwJ2f5AgMuXL598//33kilTJqubAiBA0PMHApBuzKM9fRcCP4C0oOcPBJglS5ZI9+7dJSYmRsqWLSvNmjWzukkAAgw9fyCA6Br+xx57zAR+vQBo2rSp1U0CEIAI/m5gS19Y4YcffpC2bdvKtWvXpH379vLhhx9StheAW/jL4Qa29IWvaZneVq1ayZUrV8ww/6effmrW9AOAOwj+gJ87e/asNG/eXM6fPy/169eXhQsXmip+AOAugj/g5/Lnzy/PPPOMVK9eXZYvX27q9gNAehD8gQAwbNgw2bx5s+TOndvqpgCwAYI/4Id0iF9zSy5duhR3X9asWS1tEwD7IGMI8DOa1Pfwww/Lpk2b5MSJE7J48WKrmwTAZuj5A37EtYxPA78O8Y8ePdrqJgGwIXr+sK2YW7Gy9cg5iboULaG5skrd0nklOCiD+KubN2+ajXlWrVplkvq+/vprqVq1qtXNAmBDBH/Y0op9J2XkVwfk5IXouPsKh2SVEeGVpGXlwuJvbt26JU899VTcMj4t4VuvXj2rmwXAphj2hy0Df7+5OxMEfnXqQrS5Xx/3N6+88orMnj1bgoODZf78+fLQQw9Z3SQANkbwh+2G+rXHH5vMY6779HF9nj/R4f7ChQvLRx99ZEr4AoA3MewPW9E5/sQ9/vg05Ovj+rz6d+cTf6Fz+z///LPkzJnT6qYAcAB6/rAVTe7z5PO8acaMGfLtt9/GnRP4AfgKPX/Yimb1e/J53qIb8/Tq1csU7vnxxx+lfPnylrYHgLPQ84et6HI+zepPaUGf3q+P6/OssnTpUunevbvExsZKRESElCtXzrK2AHAmgj9sRdfx63I+lfgCwHWuj1u13n/dunXSsWNHs6a/W7duMmHCBMmQwX9rDwCwJ4K/TWk2++Zf/5TFu343//pbdrs36Tr+yV1rSqGQhEP7eq73W7XOf8uWLdKmTRtTxa9du3Zmzj8oiI8gAN9jzt+GAq3AjTfo99msUiG/qfD3yy+/SKtWreTy5csSFhYm8+bNk4wZ+fgBsAZ/fWxa4CZxP99V4MbKnq+vaaD3l+V8JUqUMIV7/vjjj7gqfgBgFYK/GyZNmmSOmJgYCaQCN9rn1ce1R+zPNe7tSIO99vavXr3Kkj4AlmPC0Q26z/qBAwdk27ZtEqgFbuB9UVFRMmbMGFO3X+kw/1133WV1swCAnr+dBFKBG7s7f/68tGjRQnbt2iUXLlyQN954w+omAUAcev42EigFbuzuypUr8vDDD5vAHxoaatbyA4A/IfjbsMDN7Vhd4MbudBlf+/btZdOmTZI7d25ZtWoVRXwA+B2Cv41oEl+barfP5NfHSfbzDi3co7vzacDPkSOHLF++3GzYAwD+huBvI5rtv2T37feq18edVPDHl/r06WOW8WXOnFkWLVok9evXt7pJAJAsgr+N3CnbX5Ht7z1axCdbtmzy2WefmUI+AOCvyPa3EbL9raU1+xs1aiQFCxa0uikAcFv0/G2EbH/f+/DDDyUyMjLunMAPIBAQ/G0kELaztZMPPvhAevXqJQ0bNpS//vrL6uYAQKoR/G3E37eztZNPP/1U+vbta2537txZ8uTJY3WTACDVCP4246/b2drJ0qVLpXv37hIbGyv/7//9P3n99detbhIApAkJfzbkb9vZ2sn69evl0UcfNWv6u3btKhMnTpQMGfh/BRBYCP425U/b2drFjh07JDw8XKKjo6Vt27YyY8YMCQpi8AxA4CH4A6lUtGhRKVWqlMno1+15M2XKZHWTAMAtBH8glQoVKiQbNmwwFfyyZmW5JIDAxZglcBsnTpyQBQsWxJ3nzZtXcubMaWmbACC9CP5ACs6cOSPNmjWTxx57TObMmWN1cwDAYwj+QDIuXLggLVq0kJ9++kmKFy8uDzzwgNVNAgCPIfgDiVy9elUeeeQR+fHHHyU0NFRWr14tJUqUsLpZAOAxBH8gnmvXrkmHDh3ku+++k9y5c8s333wj5cqVs7pZAOBRBH/gf2JiYqRLly6ycuVKyZ49uyxfvlyqVatmdbMAwOMI/sD/aMGee+65xyzlW7x4sdSvX9/qJgGAVxD8gf/RMr1jxoyRffv2SVhYmNXNAQCvIfjD8T7++GP5+++/48619w8Adkbwh6O98847ZoOe1q1by40bN6xuDgD4BMEfjjVt2jQZMmSIua3FfKjVD8ApHF/bXzdqueuuu0yyV548eWTdunVWNwk+oBvz9OnTx9weOnSoDBs2zOomAYDPOD74q02bNlGv3UGWLVsm3bp1k9jYWOnbt6+88cYbJtkPAJyCYX84yvr166Vjx45y8+ZN6dy5s0yaNInAD8Bx/Dr4b9y4UcLDw6VIkSLmD/SiRYuSPEf/eOvQvW6xet9998nWrVvT9B76ulq3vU6dOibrG/amxXuyZcsmbdq0kVmzZpnpHgBwGr8e9r9y5YqpsBYREWFKriY2f/58GTx4sEyZMsUE/nfffddsxnLo0CFTk11Vr17d9PIS07KtelGhZVyLFi0qJ0+eNGu7q1SpIlWrVvXJ9wffq1u3rvzwww+mVj8JfgCcyq+Df6tWrcyRknHjxknv3r2lZ8+e5lwvAnQ+d8aMGfLSSy+Z+3bt2nXb99DArwoXLmyWe+3cuTPF4K913/WIv/ObOnfunBvfHXzlyJEj5melF4IqX7585sJSDwQuXZqpmzD9+eefXMhZhJ+BtVyxR/OXbBX8b+f69euyY8eOBFnaOoSrvffNmzen6jX0j/+tW7ckV65ccvnyZVm7dq3Zuz0lWv1t5MiRSe5n4xcAgFX04iskJMQZwf/s2bNmI5aCBQsmuF/PdQ/21Dh9+rS0b9/e3NbX0lEEnftPiV5o6DSDy/nz56VkyZJy/PjxNP/Hw3P0Z7Zt2zaxK3///qxq38WLF6V48eISGRlplusG2vfoyddM72u5+/W+/BkgKR3R1CnMvHnzSloFbPD3hDJlysju3btT/fwsWbKYIzEN/PziWyc4ONjW///+/v1Z3T59b2+/vze+R0++ZnpfK71f74ufAVLmTuJywKY658+f3/zCau89Pj0vVKiQZe2C7/Xv31/szN+/P39vn79+j558zfS+lhN+hkgoQ6w7mQIW0CV5CxculHbt2sXdpxn+mr09ceJEc67z9zoEMmDAgLiEP2/SIS/t9evQC1e9gG/x+bMeP4PA/f/362F/TcI7fPhwgqxtzd7X+Q0N8jr/3qNHD6ldu7a5CNClfprE58r+9zadAhgxYkSyUwEAvIvPn/X4GQTu/79f9/y1GluTJk2S3K8BXwu0qPfee0/eeustOXXqlFnKNWHCBDMiAAAAAjD4AwAAzwvYhD8AAOAegj8AAA5D8AcAwGEI/neQll0D9+/fL//4xz/M83Vpoq4+AOCbz58mAevnLv6hXwdrdlyF92ipea3KqKXpdRM7XQKvG9qlBcH/Nly7BupSCt3wR3cY1F0Do6Kikn2+bnChVQPfeOMNCg0BPv78KV3rrDt0uo5jx475tM1O4dpxVS/O4HsbNmwwhZl0h9JVq1aZDZaaN2+ets3KNNsfyatbt25s//79485jYmJiixQpEjtmzJg7fm3JkiVjx48f7+UWAvaV1s/fzJkzY0NCQnzYQigNIwsXLrS6GY4WFRVlfg4bNmxI9dfQ87/DroG6S6C7uwYC8O3nTwuD6WZbutlM27ZtzVQcYHcX/re9fFo2+CH4u7FroBYUAuBfn7/y5cvLjBkzZPHixTJ37lxT7rtBgwZy4sQJH7Ua8D39PX/22Wfl/vvvl8qVK9ujvC8ApFb9+vXN4aKBv2LFijJ16lQZPXq0pW0DvEXn/vft2yffffddmr6O4J8Cdg0EAvvzlylTJqlRo0aC/UEAOxkwYIAsXbrUrL4oVqxYmr6WYf8UZM6cWWrVqiVr1qxJMLyi5/F7FwD88/On0wZ79+6VwoULe7GlgO9pnqUGft3pdu3atVK6dOk0vwY9/9u4066B3bt3l6JFi5o1l64kpQMHDsTd/v33380uhDlz5pSyZcta+r0Adv/8jRo1SurVq2c+a+fPnzcbfulSv169eln8ndjPnXZchfeH+j/55BOT36Jr/V15MLq9b7Zs2VL3Il5df2ADEydOjC1RokRs5syZzdKjH374Ie6xBx54ILZHjx5x50eOHDHLLRIf+jwA3v38Pfvss3HPLViwYGzr1q1jd+7caVHL7W3dunXJ/q2L//OA9yT3f6+HLndNLXb1AwDAYZjzBwDAYQj+AAA4DMEfAACHIfgDAOAwBH8AAByG4A8AgMMQ/AEAcBiCPwAADkPwB2CUKlXKlND119eL/7oZMmQwh5bx9SXX++bOndun7wt4GsEfCHDh4eHSsmXLZB/79ttvTbDas2ePz9u1bds2efrpp+POtR2LFi3yyGtrHf+TJ0+aWuae0KRJE5k+ffodn6fv6Y0LGsDXCP5AgHvqqadk1apVcuLEiSSPzZw502yMU7VqVZ+3q0CBApI9e3avvLZuZqJb++oFRXqdO3dOvv/+e3MRdSf6np664ACsRPAHAtwjjzxiAu2sWbOS7Ly2YMECc3GgvvvuO2nUqJHZ9at48eIyaNAgs0teSo4fPy5t27Y1u1Ledddd8thjj8np06cTPOerr76SOnXqSNasWSV//vzSvn37ZIf99bbSxzVg6/nRo0clKChItm/fnuA19WtKlixptvBNLf3edShe9zYvX768uejo2LGjXL16VT766CPzfnny5DHfs271G9+yZcukZs2aUrBgQfnrr7+kS5cu5v9T/5/uuececwEF2A3BHwhwGTNmNNvbagCMv0+XBn4NdE888YT8+uuvZmrgH//4h5kCmD9/vrkY0D3Bk6OBVwO/9oo3bNhgRhZ+++036dSpU4KgqcG8devW8uOPP8qaNWvM1rspTQEoDaQ6dK7nGpDDwsKSBFc9f/LJJ82FQVpooJ8wYYLMmzdPVqxYIevXrzftW758uTnmzJkjU6dOlc8//zzB1y1ZssR8r+rVV18123J//fXXcvDgQZk8ebK5qAFsx4u7DgLwkYMHD5otPXWrVZdGjRrFdu3a1dx+6qmnYp9++ukEX/Ptt9/GBgUFxf7999/mvGTJkrHjx483t7/55pvY4ODg2OPHj8c9f//+/eY9tm7das7r168f26VLlxTbFP/1lH7twoULEzxn/vz5sXny5ImNjo425zt27IjNkCGD2R47ta+rdCtTff3Dhw/H3denT5/Y7Nmzx166dCnuvhYtWpj7XfR9c+bMGbtv3z5zHh4eHtuzZ88U39v1XiEhIbd9DuDv6PkDNlChQgVp0KCBzJgxw5wfPnzYJPu5hvx3795tRgZ0CN91tGjRwvTwjxw5kuT1tNerUwN6uFSqVMkMretjateuXdK0adN0tbtdu3YSHBwsCxcuNOfaRk2+c00TpIUO9d99991x5zqMr6+j32v8+6KiouLO165dK6GhoXLvvfea8379+pmRg+rVq8vQoUNl06ZN6fr+AH9F8AdsQgP9F198IZcuXTJD5xoIH3jggbj5/z59+piA7Tr0guCXX35JEDDTQufE0ytz5sxmykLbe/36dfnkk08kIiLCrdfKlClTgnPNLUjuvvi5BDrk36ZNm7jzVq1aybFjx+S5556TP/74w1zcDBkyxK32AP6M4A/YhCbk6Ty5BtDZs2ebIOrKhteENp3LLlu2bJJDA3BiFStWlMjISHO46NfrunodAVC6gkDn+VNLA3HiZDvVq1cvWb16tbz//vty8+ZN6dChg/iCzkRowqJrvt9Fk/169Oghc+fONcmHH3zwgU/aA/gSwR+wCR3e1oS8YcOGmaQ6TZpzefHFF80Qtib4aa9fe/yLFy9OMeFPE/GqVKliMt937twpW7duNT10HUnQpYNqxIgR8umnn5p/dSpg7969Mnbs2BTbp0PwerFw6tQpk1Uf/0KjXr16po2anOiJEYXU2LFjh0kSbNiwYdx9r732mvl/0WmT/fv3m9UD2j7Abgj+gM2G/jWw6nx+kSJF4u7XXrpm7f/8889muV+NGjVMoIv/nPh0xECDoC6Pa9y4sbkYKFOmjFkl4PLggw+aFQU6dK5z5A899JC5SEjJO++8Y1YNaB6Bvn/iduuwv7tD/u7Q709XKuhqCRcdBdGLJ/3/0u9b8xE0BwCwmwya9Wd1IwA42+jRo82FRGoqEeoIwrPPPmuO9NAAP3z4cDNdkhaalKjv7evSwoAn0fMHYBlNRNy3b5+89957MnDgwFR/nU4R6DTHhQsX3HpfHWXQmgea4JcW+p59+/Z16z0Bf0LPH4BlNC9B8wZ0yZ8mKuow+51oNv6NGzfMbZ2KSGsxoPTQXACl7SxdurTP3hfwNII/AAAOw7A/AAAOQ/AHAMBhCP4AADgMwR8AAIch+AMA4DAEfwAAHIbgDwCAwxD8AQAQZ/n/yMw6ZpJJk6QAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 500x400 with 1 Axes>"
       ]
@@ -1157,6 +1180,9 @@
     "y_labels = [r\"10$^{-5}$\", r\"10$^{-4}$\", r\"10$^{-3}$\", r\"10$^{-2}$\"]\n",
     "U = np.arange(0, 2, 0.1)\n",
     "\n",
+    "# Set U_mag and dissipation rate to the same time coordinates for plotting\n",
+    "dissipation = ds_binned[\"dissipation_rate\"].interp(time_psd=ds_binned[\"time\"])\n",
+    "\n",
     "fig, ax = plt.subplots(\n",
     "    figsize=(5, 4),\n",
     "    subplot_kw={\"xscale\": \"log\", \"yscale\": \"log\"},\n",
@@ -1164,7 +1190,7 @@
     ")\n",
     "ax.scatter(\n",
     "    abs(ds_binned[\"U_mag\"]),\n",
-    "    ds_binned[\"dissipation_rate\"][0]\n",
+    "    dissipation[0]\n",
     ")\n",
     "ax.plot(U, U**3 * 10 ** (-3), \"--\", color=\"black\", label=\"U$^3$ slope\")\n",
     "\n",
@@ -1191,7 +1217,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1b2336a9af0>"
+       "<matplotlib.legend.Legend at 0x23d902bf010>"
       ]
      },
      "execution_count": 16,
@@ -1200,7 +1226,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x300 with 1 Axes>"
       ]
@@ -1238,7 +1264,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1b234258c20>"
+       "<matplotlib.legend.Legend at 0x23d90392b50>"
       ]
      },
      "execution_count": 17,
@@ -1247,7 +1273,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 700x300 with 1 Axes>"
       ]
@@ -1303,7 +1329,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -1317,7 +1343,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.11"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/data/dolfyn/test_data/BenchFile01_avg.nc b/examples/data/dolfyn/test_data/BenchFile01_avg.nc
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diff --git a/examples/data/dolfyn/test_data/BenchFile01_func.nc b/examples/data/dolfyn/test_data/BenchFile01_func.nc
index 4581f14642e6021c6e7ffd3432c5c6474817e24b..a2cb12acd9e89f2dfe149d844316c752744c65b7 100644
GIT binary patch
delta 2070
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diff --git a/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc b/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc
index 18b65d846fff175e746c25537cda0e49b0579aa4..b7a157d3e3242bdd3cd2d1df74658d7095a26169 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data01_bin.nc b/examples/data/dolfyn/test_data/vector_data01_bin.nc
index bfb6875ccad59e959da42a789778a2d5b0660679..13d2baa86006bf41b2d606e4113722ddde9c8833 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data01_func.nc b/examples/data/dolfyn/test_data/vector_data01_func.nc
index 466b11c6c20275b5a2bfe59eac8d3f8a2bc66a74..5e79a8b881c0f9a477cab0a8fda701bc870c6978 100644
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diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index 5bfe1ae9c..8eb9276ab 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -201,21 +201,13 @@ def sound_pressure_spectral_density(
     fs: Union[int, float],
     bin_length: Union[int, float] = 1,
     fft_length: Optional[Union[int, float]] = None,
-    rms: bool = True,
+    pct_overlap: float = 0.5,
 ) -> xr.DataArray:
     """
     Calculates the sound pressure spectral density (SPSD) from audio
     samples split into FFTs with a specified bin length in seconds,
-    using Hanning windowing with 50% overlap.
-
-    By default (`rms=True`), this function returns the mean-squared SPSD,
-    which found by scaling the total spectral power (frequency domain) with
-    the time-domain averaged mean-squared power, in accordance with
-    Parseval's theorem.
-
-    Setting `rms=False` disables this scaling and returns the
-    power spectral density of the sound pressure signal.
-    Both forms have units of [Pa^2/Hz] or [V^2/Hz].
+    using Hanning windowing with 50% overlap. Uses Welch's method to
+    average overlapping FFT windows within each bin.
 
     Parameters
     ----------
@@ -227,14 +219,13 @@ def sound_pressure_spectral_density(
         Length of time in seconds to create FFTs. Default: 1.
     fft_length: int or float, optional
         Length of FFT to use. If None, uses bin_length * fs. Default: None.
-    rms: bool
-        If True, calculates the mean-squared SPSD. Set to False to
-        calculate standard SPSD. Default: True.
+    pct_overlap: float
+        Percentage of overlap between FFT segments. Default: 0.5 (50%).
 
     Returns
     -------
-    spsd: xarray.DataArray (time, freq)
-        Spectral density [Pa^2/Hz] indexed by time and frequency
+    spsd: xarray.DataArray (time_psd, freq)
+        Spectral density [Pa^2/Hz] or [V^2/Hz] indexed by time and frequency
     """
 
     # Type checks
@@ -256,36 +247,21 @@ def sound_pressure_spectral_density(
         nfft = nbin
 
     # Use dolfyn PSD functionality
-    binner = VelBinner(n_bin=nbin, fs=fs, n_fft=nfft)
-    # Always 50% overlap if numbers reshape perfectly
-    # Mean square sound pressure
-    psd = binner.power_spectral_density(pressure, freq_units="Hz")
-    if rms:
-        # Scale PSD by mean square of original signal
-        samples = (
-            binner.reshape(pressure.values) - binner.mean(pressure.values)[:, None]
-        )
-        # mean squared pressure ("power") in time domain
-        t_power = np.sum(samples**2, axis=1) / nbin
-        # pressure ("power") in frequency domain
-        f_power = psd.sum("freq") * (fs / nbin)
-        # Adjust the amplitude of the PSD to return the mean-squared PSD
-        # based on Parseval's theorem: total energy computed in the time
-        # domain must equal the total energy computed in the frequency domain
-        psd = psd * t_power[:, None] / f_power
-        long_name = "Mean Square Sound Pressure Spectral Density"
-    else:
-        long_name = "Sound Pressure Spectral Density"
+    binner = VelBinner(fs=fs, n_bin=nbin, n_fft=nfft)
+    # Sound pressure spectral densities with 50% overlap between FFT windows
+    psd = binner.power_spectral_density(
+        pressure, freq_units="Hz", window="hann", pct_overlap=pct_overlap
+    )
 
     out = xr.DataArray(
         psd,
-        coords={"time": psd["time"], "freq": psd["freq"]},
+        coords={"time_psd": psd["time_psd"], "freq": psd["freq"]},
         attrs={
             "units": pressure.units + "^2/Hz",
-            "long_name": long_name,
+            "long_name": "Mean Square Sound Pressure Spectral Density",
             "fs": fs,
             "bin_length": bin_length,
-            "overlap": "50%",
+            "overlap": f"{pct_overlap*100}%",
             "n_fft": nfft,
         },
     )
@@ -304,7 +280,7 @@ def apply_calibration(
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density in V^2/Hz.
     sensitivity_curve: xarray.DataArray (freq)
         Calibrated sensitivity curve in units of dB rel 1 V^2/uPa^2.
@@ -737,10 +713,11 @@ def _convert_to_band_spectral_density(
         partial_pts=partial_pts,
         weights=weights,
     )
+    time_dim = spsd.dims[0]
     out = xr.DataArray(
         band_spsd,
-        coords={"time": spsd["time"], "freq": bands[:, 1]},
-        dims=["time", "freq"],
+        coords={time_dim: spsd[time_dim], "freq": bands[:, 1]},
+        dims=[time_dim, "freq"],
         attrs=spsd.attrs,
     )
 
diff --git a/mhkit/acoustics/sel.py b/mhkit/acoustics/sel.py
index 9083dc163..fd262c935 100644
--- a/mhkit/acoustics/sel.py
+++ b/mhkit/acoustics/sel.py
@@ -91,7 +91,7 @@ def sound_exposure_level(
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Sound pressure spectral density in [Pa^2/Hz] with a bin length
         equal to the time over which sound exposure should be computed.
     group: str
@@ -136,9 +136,10 @@ def sound_exposure_level(
     # Sound exposure level (L_{E,p}) = (L_{p,rms} + 10log10(t))
     sel = 10 * np.log10(exposure / reference) + 10 * np.log10(spsd.attrs["bin_length"])
 
+    time_dim = spsd.dims[0]
     out = xr.DataArray(
         sel.astype(np.float32),
-        coords={"time": spsd["time"]},
+        coords={time_dim: spsd[time_dim]},
         attrs={
             "units": "dB re 1 uPa^2 s",
             "long_name": long_name,
diff --git a/mhkit/acoustics/spl.py b/mhkit/acoustics/spl.py
index c553d8dbf..23a8b48c9 100644
--- a/mhkit/acoustics/spl.py
+++ b/mhkit/acoustics/spl.py
@@ -54,7 +54,7 @@ def _argument_check(spsd, fmin, fmax):
     _check_numeric(fmax, "fmax")
 
     # Ensure 'freq' and 'time' dimensions are present
-    if ("freq" not in spsd.dims) or ("time" not in spsd.dims):
+    if ("freq" not in spsd.dims) or ("time" not in spsd.dims[0]):
         raise ValueError("'spsd' must have 'time' and 'freq' as dimensions.")
 
     # Check that 'fs' (sampling frequency) is available in attributes
@@ -89,7 +89,7 @@ def sound_pressure_level(
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density in [Pa^2/Hz]
     fmin: int
         Lower frequency band limit (lower limit of the hydrophone). Default: 10 Hz
@@ -116,9 +116,10 @@ def sound_pressure_level(
     # Mean square sound pressure level
     mspl = 10 * np.log10(pressure_squared / reference)
 
+    time_dim = spsd.dims[0]
     out = xr.DataArray(
         mspl.astype(np.float32),
-        coords={"time": spsd["time"]},
+        coords={time_dim: spsd[time_dim]},
         attrs={
             "units": "dB re 1 uPa",
             "long_name": "Sound Pressure Level",
@@ -138,7 +139,7 @@ def _band_sound_pressure_level(spsd: xr.DataArray, octave: int, base: int):
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density in [Pa^2/Hz]
     octave: int
         Octave subdivision (1 = full octave, 3 = third-octave, etc.)
@@ -191,13 +192,14 @@ def _band_sound_pressure_level(spsd: xr.DataArray, octave: int, base: int):
             )
 
     # Mean square sound pressure level in dB rel 1 uPa
+    time_dim = spsd.dims[0]
     out_spl = xr.DataArray(
         10 * np.log10(out_sp / reference),
         coords={
-            "time": spsd["time"],
+            time_dim: spsd[time_dim],
             "freq_bins": bands[:, 1],
         },
-        dims=["time", "freq_bins"],
+        dims=[time_dim, "freq_bins"],
     )
     return out_spl
 
@@ -211,7 +213,7 @@ def third_octave_sound_pressure_level(
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral in [Pa^2/Hz].
     fmin: int
         Lower frequency band limit (lower limit of the hydrophone).
@@ -253,7 +255,7 @@ def decidecade_sound_pressure_level(
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density in [Pa^2/Hz].
     fmin: int
         Lower frequency band limit (lower limit of the hydrophone).
diff --git a/mhkit/acoustics/spsdl.py b/mhkit/acoustics/spsdl.py
index 70b41f024..a67333d72 100644
--- a/mhkit/acoustics/spsdl.py
+++ b/mhkit/acoustics/spsdl.py
@@ -29,7 +29,7 @@ def sound_pressure_spectral_density_level(spsd: xr.DataArray) -> xr.DataArray:
 
     Parameters
     ----------
-    spsd: xarray.DataArray (time, freq)
+    spsd: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density in Pa^2/Hz
 
     Returns
@@ -47,7 +47,7 @@ def sound_pressure_spectral_density_level(spsd: xr.DataArray) -> xr.DataArray:
 
     spsdl = xr.DataArray(
         lpf.astype(np.float32),
-        coords={"time": spsd["time"], "freq": spsd["freq"]},
+        coords=spsd.coords,
         attrs={
             "units": "dB re 1 uPa^2/Hz",
             "long_name": "Sound Pressure Spectral Density Level",
@@ -260,7 +260,7 @@ def band_aggregate(
         raise ValueError("'fmax' must be greater than 'fmin'.")
 
     # Value checks
-    if ("freq" not in spsdl.dims) or ("time" not in spsdl.dims):
+    if ("freq" not in spsdl.dims) or ("time" not in spsdl.dims[0]):
         raise ValueError("'spsdl' must have 'time' and 'freq' as dimensions.")
 
     # Validate method and get method_name and method_arg
@@ -307,7 +307,7 @@ def time_aggregate(
 
     Parameters
     ----------
-    spsdl: xarray.DataArray (time, freq)
+    spsdl: xarray.DataArray (time_psd, freq)
         Mean square sound pressure spectral density level in dB rel 1 uPa^2/Hz
     window: int
         Time in seconds to subdivide spectral density level into. Default: 60 s.
@@ -322,19 +322,6 @@ def time_aggregate(
         Time-averaged sound pressure spectral density level [dB re 1 uPa^2/Hz]
         indexed by time and frequency
     """
-    warnings.warn(
-        "The 'time_aggregate' function is deprecated and will be removed in a future release. "
-        "Please use one of the following alternatives instead to convert the SPSD to the "
-        "appropriate time-aggregated form before calculating the SPSDL using "
-        "'sound_pressure_spectral_density_level':\n"
-        "- For time-averaged SPSDLs, use the 'mhkit.acoustics.time_average' function.\n"
-        "- For time-summed SPSDLs, use the 'mhkit.acoustics.time_summation' function.\n"
-        "If you are using this function for a different purpose, please reach out to the MHKiT "
-        "developers to discuss how we can support your use case with a more specific function.",
-        DeprecationWarning,
-        stacklevel=2,
-    )
-
     # Type checks
     if not isinstance(spsdl, xr.DataArray):
         raise TypeError("'spsdl' must be an xarray.DataArray.")
@@ -342,7 +329,7 @@ def time_aggregate(
         raise TypeError("'window' must be an integer.")
     if not isinstance(method, (str, dict)):
         raise TypeError("'method' must be a string or dictionary.")
-    if "time" not in spsdl.dims:
+    if "time" not in spsdl.dims[0]:
         raise ValueError("'spsdl' must have 'time' dimension.")
 
     # Value checks
@@ -350,15 +337,16 @@ def time_aggregate(
         raise ValueError("'window' must be a positive integer.")
 
     # Ensure 'time' coordinate is of datetime64 dtype
-    if not np.issubdtype(spsdl["time"].dtype, np.datetime64):
-        raise TypeError("'spsdl['time']' must be of dtype 'datetime64'.")
+    time_dim = spsdl.dims[0]
+    if not np.issubdtype(spsdl[time_dim].dtype, np.datetime64):
+        raise TypeError("spsdl 'time' must be of dtype 'datetime64'.")
 
     # Validate method and get method_name and method_arg
     method_name, method_arg = _validate_method(method)
 
     window = np.timedelta64(window, "s")
     time_bins_lower = np.arange(
-        spsdl["time"][0].values, spsdl["time"][-1].values, window
+        spsdl[time_dim][0].values, spsdl[time_dim][-1].values, window
     )
     time_bins_upper = time_bins_lower + window
     time_bins = np.append(time_bins_lower, time_bins_upper[-1])
@@ -367,7 +355,7 @@ def time_aggregate(
     )
 
     # Use xarray binning methods
-    spsdl_group = spsdl.groupby_bins("time", time_bins, labels=center_time)
+    spsdl_group = spsdl.groupby_bins(time_dim, time_bins, labels=center_time)
 
     # Handle method being a string or a dict
     if isinstance(method, str):
@@ -388,20 +376,24 @@ def time_aggregate(
     if method == "quantile":
         out = out.drop_vars("quantile")
 
+    if "time_psd_bins" in out.dims:  # if this dim has not already been changed
+        out = out.rename({"time_psd_bins": "time_bins"})
     return out
 
 
 def time_average(spsdl, window):
     """
-    Reorganizes spectral density level frequency tensor into time windows and takes the
-    spectral average of all of the inputs along the time dimension. This is effectively
-    time-averaging the original SPSDs.
-    Note: 'window' must be larger than the original 'bin_length' of the SPSD
+    Reorganizes spectral density level frequency tensor into time windows and computes
+    the energy-averaged SPSDL for each window. Values are converted from dB to linear
+    power, averaged across the window, then converted back to dB. This is equivalent
+    to Welch's method: it produces the same result as recomputing the SPSD from the
+    original time series using 'bin_length=window'.
+    Note: 'window' must be larger than the original 'bin_length' of the SPSD.
 
     Parameters
     ----------
     spsdl: xarray.DataArray
-        Sound pressure spectral density level with dimensions (time, freq)
+        Sound pressure spectral density level with dimensions (time_psd, freq)
     window: int
         Time in seconds to group spectral density level into.
 
@@ -413,12 +405,14 @@ def time_average(spsdl, window):
     """
 
     def spectral_average(x):
+        # time dimension name
+        time_dim = x.dims[0]
         # Convert value in decibels to absolute magnitude, still relevant to original units
         magnitude = 10 ** (x / 10)
         # Sum energy in each time bin
-        summed_magnitude = magnitude.sum("time")
+        summed_magnitude = magnitude.sum(time_dim)
         # Take average
-        average_magnitude = summed_magnitude / magnitude["time"].size
+        average_magnitude = summed_magnitude / magnitude[time_dim].size
         # Convert back to decibels
         result = 10 * np.log10(average_magnitude)
 
@@ -429,16 +423,19 @@ def spectral_average(x):
 
 def time_summation(spsdl, window):
     """
-    Reorganizes spectral density level frequency tensor into time windows and takes the
-    spectral sum of each window. This is the equivalent of recalculating the SPSD using
-    `mhkit.acoustics.sound_presssure_spectral_density` with 'bin_length=window' instead
-    of the original 'bin_length'.
-    Note: 'window' must be larger than the original 'bin_length' of the SPSD
+    Reorganizes spectral density level frequency tensor into time windows and computes
+    the spectral sum for each window. Values are converted from dB to linear power,
+    summed across the window, then converted back to dB. This represents the total
+    accumulated spectral energy within each window and is proportional to N times the
+    window-averaged SPSDL (where N is the number of input bins per window). It is NOT
+    equivalent to recomputing the SPSD with a longer 'bin_length'; use 'time_average'
+    for that purpose.
+    Note: 'window' must be larger than the original 'bin_length' of the SPSD.
 
     Parameters
     ----------
     spsdl: xarray.DataArray
-        Sound pressure spectral density level with dimensions (time, freq)
+        Sound pressure spectral density level with dimensions (time_psd, freq)
     window: int
         Time in seconds to group spectral density level into.
 
@@ -450,10 +447,12 @@ def time_summation(spsdl, window):
     """
 
     def spectral_sum(x):
+        # time dimension name
+        time_dim = x.dims[0]
         # Convert value in decibels to absolute magnitude, still relevant to original units
         magnitude = 10 ** (x / 10)
         # Sum energy in each time bin
-        summed_magnitude = magnitude.sum("time")
+        summed_magnitude = magnitude.sum(time_dim)
         # Convert back to decibels
         result = 10 * np.log10(summed_magnitude)
 
diff --git a/mhkit/dolfyn/adp/clean.py b/mhkit/dolfyn/adp/clean.py
index 6011c7946..99f577140 100644
--- a/mhkit/dolfyn/adp/clean.py
+++ b/mhkit/dolfyn/adp/clean.py
@@ -5,7 +5,7 @@
 import numpy as np
 import xarray as xr
 from scipy.signal import medfilt
-from ..tools.misc import medfiltnan
+from ..tools import medfiltnan
 from ..rotate.api import rotate2
 from ..rotate.base import quaternion2orient
 
diff --git a/mhkit/dolfyn/adp/turbulence.py b/mhkit/dolfyn/adp/turbulence.py
index 2707edae5..66849dd6d 100644
--- a/mhkit/dolfyn/adp/turbulence.py
+++ b/mhkit/dolfyn/adp/turbulence.py
@@ -370,10 +370,10 @@ def doppler_noise_level(self, psd, pct_fN=0.8):
         N2 = psd.sel(freq=f_range) * psd.freq.sel(freq=f_range)
         noise_level = np.sqrt(N2.mean(dim="freq"))
 
-        time_coord = psd.dims[0]  # no reason this shouldn't be time or time_b5
+        time_dim = psd.dims[-2]
         return xr.DataArray(
-            noise_level.values.astype("float32"),
-            coords={time_coord: psd.coords[time_coord]},
+            noise_level.values,
+            coords={time_dim: psd[time_dim]},
             attrs={
                 "units": "m s-1",
                 "long_name": "Doppler Noise Level",
@@ -568,9 +568,9 @@ def _beam_variance(self, ds, time, noise, beam_order, n_beams):
             bp2_[i] = np.nanvar(self.reshape(beam_vel[beam]), axis=-1)
 
         # Remove doppler_noise
-        if type(noise) == type(ds["vel"]):
-            noise = noise.values
-        bp2_ -= noise**2
+        if type(noise) is type(ds["vel"]):
+            noise = self._interp_noise(noise, self.mean(ds["time"].values))
+        bp2_ -= noise[..., :] ** 2
 
         return bp2_
 
@@ -623,7 +623,7 @@ def reynolds_stress_4beam(self, ds, noise=None, orientation=None, beam_angle=Non
         vpwp_ = (bp2_[2] - bp2_[3]) / denm
 
         return xr.DataArray(
-            np.stack([upwp_ * np.nan, upwp_, vpwp_]).astype("float32"),
+            np.stack([upwp_ * np.nan, upwp_, vpwp_]),
             coords={
                 "tau": ["upvp_", "upwp_", "vpwp_"],
                 "range": ds["range"],
@@ -739,7 +739,7 @@ def stress_tensor_5beam(
         ) / denm
 
         tke_vec = xr.DataArray(
-            np.stack([upup_, vpvp_, wpwp_]).astype("float32"),
+            np.stack([upup_, vpvp_, wpwp_]),
             coords={
                 "tke": ["upup_", "vpvp_", "wpwp_"],
                 "range": ds["range"],
@@ -759,9 +759,7 @@ def stress_tensor_5beam(
             # Guerra Thomson calculate u'v' bar from from the covariance of u' and v'
             ds.velds.rotate2("inst")
             vel = self.detrend(ds.vel.values)
-            upvp_ = np.nanmean(vel[0] * vel[1], axis=-1, dtype=np.float64).astype(
-                np.float32
-            )
+            upvp_ = np.nanmean(vel[0] * vel[1], axis=-1)
 
             upwp_ = (
                 sin(th) ** 5 * cos(th) * (bp2_[1] - bp2_[0])
@@ -778,7 +776,7 @@ def stress_tensor_5beam(
             ) / denm
 
             stress_vec = xr.DataArray(
-                np.stack([upvp_, upwp_, vpwp_]).astype("float32"),
+                np.stack([upvp_, upwp_, vpwp_]),
                 coords={
                     "tau": ["upvp_", "upwp_", "vpwp_"],
                     "range": ds["range"],
@@ -938,6 +936,14 @@ def dissipation_rate_LT83(
         idx = np.where((freq_range[0] < freq) & (freq < freq_range[1]))
         idx = idx[0]
 
+        # Interpolate U_mag to the same time dimension as PSD
+        umag_time_dim = U_mag.dims[-1]
+        # If overlap is not 0%
+        if psd["time_psd"].size != U_mag[umag_time_dim].size:
+            U_mag = U_mag.interp({umag_time_dim: psd["time_psd"].values}).values
+        else:
+            U_mag = U_mag.values
+
         # Set the correct magnitude whether the frequency is in Hz or rad/s
         if freq.units == "Hz":
             U = U_mag / (2 * np.pi)
@@ -947,12 +953,10 @@ def dissipation_rate_LT83(
         # Use the transverse value derived from the Kolmogorov constant
         a = k_constant
         # Calculate dissipation
-        out = (psd[:, idx] * freq[idx] ** (5 / 3) / a).mean(axis=-1) ** (
-            3 / 2
-        ) / U.values
+        out = (psd[:, idx] * freq[idx] ** (5 / 3) / a).mean(axis=-1) ** (3 / 2) / U
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             attrs={
                 "units": "m2 s-3",
                 "long_name": "TKE Dissipation Rate",
@@ -1037,8 +1041,8 @@ def dissipation_rate_SF(self, vel_raw, r_range=[1, 5]):
         # bm shape is [range, ensemble time, 'data within ensemble']
         bm = self.demean(vel_raw.values)  # take out the ensemble mean
 
-        e = np.empty(bm.shape[:2], dtype="float32") * np.nan
-        n = np.empty(bm.shape[:2], dtype="float32") * np.nan
+        e = np.empty(bm.shape[:2]) * np.nan
+        n = np.empty(bm.shape[:2]) * np.nan
 
         bin_size = round(np.diff(rng)[0], 3)
         R = int(r_range[0] / bin_size)
@@ -1076,7 +1080,7 @@ def dissipation_rate_SF(self, vel_raw, r_range=[1, 5]):
         noise = np.sqrt(n / 2)
 
         epsilon = xr.DataArray(
-            epsilon.astype("float32"),
+            epsilon,
             coords={vel_raw.dims[0]: rng, vel_raw.dims[1]: time},
             dims=vel_raw.dims,
             attrs={
@@ -1089,7 +1093,7 @@ def dissipation_rate_SF(self, vel_raw, r_range=[1, 5]):
         )
 
         noise = xr.DataArray(
-            noise.astype("float32"),
+            noise,
             coords={vel_raw.dims[0]: rng, vel_raw.dims[1]: time},
             attrs={
                 "units": "m s-1",
@@ -1098,7 +1102,7 @@ def dissipation_rate_SF(self, vel_raw, r_range=[1, 5]):
         )
 
         SF = xr.DataArray(
-            D.astype("float32"),
+            D,
             coords={vel_raw.dims[0]: rng, "range_SF": r, vel_raw.dims[1]: time},
             attrs={
                 "units": "m2 s-2",
diff --git a/mhkit/dolfyn/adv/api.py b/mhkit/dolfyn/adv/api.py
index 7d4c13757..880fd45e6 100644
--- a/mhkit/dolfyn/adv/api.py
+++ b/mhkit/dolfyn/adv/api.py
@@ -3,4 +3,4 @@
 from . import clean
 from .motion import correct_motion
 from ..velocity import VelBinner
-from .turbulence import turbulence_statistics, ADVBinner
+from .turbulence import ADVBinner
diff --git a/mhkit/dolfyn/adv/clean.py b/mhkit/dolfyn/adv/clean.py
index 09b5010b4..87698df8e 100644
--- a/mhkit/dolfyn/adv/clean.py
+++ b/mhkit/dolfyn/adv/clean.py
@@ -3,7 +3,7 @@
 import warnings
 import numpy as np
 from ..velocity import VelBinner
-from ..tools.misc import group, slice1d_along_axis
+from ..tools import group, slice1d_along_axis
 
 sin = np.sin
 cos = np.cos
diff --git a/mhkit/dolfyn/adv/turbulence.py b/mhkit/dolfyn/adv/turbulence.py
index 8c73c39bc..14ad69815 100644
--- a/mhkit/dolfyn/adv/turbulence.py
+++ b/mhkit/dolfyn/adv/turbulence.py
@@ -1,54 +1,44 @@
 import numpy as np
 from ..velocity import VelBinner
 import warnings
-from ..tools.misc import slice1d_along_axis, _nans_like
+from ..tools import slice1d_along_axis, _nans_like
 from scipy.special import cbrt
 import xarray as xr
 
 
 class ADVBinner(VelBinner):
-    """
-    A class that builds upon `VelBinner` for calculating turbulence
-    statistics and velocity spectra from ADV data.
-
-    Parameters
-    ----------
-    n_bin : int
-      The length of each bin, in number of points, for this averaging
-      operator.
-    fs : int
-      Instrument sampling frequency in Hz
-    n_fft : int
-      The length of the FFT for computing spectra (must be <= `n_bin`).
-      Optional, default `n_fft` = `n_bin`
-    n_fft_coh : int
-      Number of data points to use for coherence and cross-spectra FFT's.
-      Optional, default `n_fft_coh` = `n_fft`
-    noise : float or array-like
-      Instrument noise level in same units as velocity. Typically found from
-      :func:`doppler_noise_level <mhkit.dolfyn.adv.turbulence.ADVBinner.doppler_noise_level>`.
-      Default: None.
-    """
-
-    def __call__(self, ds, freq_units="rad/s", window="hann"):
-        out = type(ds)()
-        out = self.bin_average(ds, out)
-
-        out["tke_vec"] = self.turbulent_kinetic_energy(ds["vel"])
-        out["stress_vec"] = self.reynolds_stress(ds["vel"])
-
-        out["psd"] = self.power_spectral_density(
-            ds["vel"], window=window, freq_units=freq_units
-        )
-        for key in list(ds.attrs.keys()):
-            if "config" in key:
-                ds.attrs.pop(key)
-        out.attrs = ds.attrs
-        out.attrs["n_bin"] = self.n_bin
-        out.attrs["n_fft"] = self.n_fft
-        out.attrs["n_fft_coh"] = self.n_fft_coh
+    def __init__(
+        self,
+        n_bin,
+        fs,
+        n_fft=None,
+        n_fft_coh=None,
+        noise=None,
+    ):
+        """
+        A class that builds upon `VelBinner` for calculating turbulence
+        statistics and velocity spectra from ADV data.
+
+        Parameters
+        ----------
+        n_bin : int
+          The length of each bin, in number of points, for this averaging
+          operator.
+        fs : int
+          Instrument sampling frequency in Hz
+        n_fft : int
+          The length of the FFT for computing spectra (must be <= `n_bin`).
+          Default = `n_fft` = `n_bin`
+        n_fft_coh : int
+          Number of data points to use for coherence and cross-spectra FFT's.
+          Default = `n_fft_coh` = `n_fft`
+        noise : float or array-like
+          Instrument noise level in same units as velocity. Typically found from
+          :func:`doppler_noise_level <mhkit.dolfyn.adv.turbulence.ADVBinner.doppler_noise_level>`.
+          Default = None
+        """
 
-        return out
+        VelBinner.__init__(self, n_bin, fs, n_fft, n_fft_coh, noise)
 
     def reynolds_stress(self, veldat, detrend=True):
         """
@@ -77,7 +67,7 @@ def reynolds_stress(self, veldat, detrend=True):
         time = self.mean(veldat["time"].values)
         vel = veldat.values
 
-        out = np.empty(self._outshape(vel[:3].shape)[:-1], dtype=np.float32)
+        out = np.empty(self._outshape(vel[:3].shape)[:-1])
 
         if detrend:
             vel = self.detrend(vel)
@@ -85,12 +75,10 @@ def reynolds_stress(self, veldat, detrend=True):
             vel = self.demean(vel)
 
         for idx, p in enumerate(self._cross_pairs):
-            out[idx] = np.nanmean(vel[p[0]] * vel[p[1]], -1, dtype=np.float64).astype(
-                np.float32
-            )
+            out[idx] = np.nanmean(vel[p[0]] * vel[p[1]], -1)
 
         da = xr.DataArray(
-            out.astype("float32"),
+            out,
             dims=veldat.dims,
             attrs={"units": "m2 s-2", "long_name": "Specific Reynolds Stress Vector"},
         )
@@ -107,6 +95,7 @@ def cross_spectral_density(
         window="hann",
         n_bin=None,
         n_fft_coh=None,
+        pct_overlap=0,
     ):
         """
         Calculate the cross-spectral density of velocity components.
@@ -120,13 +109,20 @@ def cross_spectral_density(
           (`f` or :math:`\\omega`)
         fs : float (optional)
           The sample rate. Default = `self.fs`
-        window : string or array
-          Specify the window function.
-         Options: 1, None, 'hann', 'hamm'
+        window: str
+          Type of window to apply to each FFT segment.
+          Example options: 'boxcar', 'hann', 'hamming', 'blackman', 'bartlett'.
+          See `scipy.signal.window` for more options.
+          Default: 'hann'.
         n_bin : int (optional)
           The bin-size. Default = `self.n_bin`
         n_fft_coh : int (optional)
           The fft size. Default = `self.n_fft_coh`
+        pct_overlap : float (optional)
+          Fractional overlap between consecutive sliding windows, in [0, 1).
+          Controls both the bin-to-bin advance and the within-bin FFT overlap
+          passed to scipy.signal.welch. Industry standard is 50%.
+          Default = 0 (0% overlap).
 
         Returns
         -------
@@ -139,10 +135,18 @@ def cross_spectral_density(
             raise TypeError("`veldat` must be an instance of `xarray.DataArray`.")
         if ("rad" not in freq_units) and ("Hz" not in freq_units):
             raise ValueError("`freq_units` should be one of 'Hz' or 'rad/s'")
+        if (pct_overlap < 0) or (pct_overlap > 1):
+            raise ValueError(
+                f"pct_overlap must be between 0 and 1, received {pct_overlap}."
+            )
 
         fs_in = self._parse_fs(fs)
+        n_bin = self._parse_nbin(n_bin)
         n_fft = self._parse_nfft_coh(n_fft_coh)
-        time = self.mean(veldat["time"].values)
+        step = int((1 - pct_overlap) * n_bin)
+
+        # Get time coord before changing veldat from xarray to numpy array
+        time_coord = self.mean(veldat["time"].values, step=step, n_bin=n_bin)
         veldat = veldat.values
         if len(np.shape(veldat)) != 2:
             raise Exception(
@@ -151,7 +155,7 @@ def cross_spectral_density(
             )
 
         out = np.empty(
-            self._outshape_fft(veldat[:3].shape, n_fft=n_fft, n_bin=n_bin),
+            self._outshape_fft(veldat[:3].shape, n_fft=n_fft, n_bin=n_bin, step=step),
             dtype="complex",
         )
 
@@ -164,31 +168,32 @@ def cross_spectral_density(
             fs = fs_in
             freq_units = "Hz"
             units = "m2 s-2 Hz-1"
-        coh_freq = xr.DataArray(
-            self._fft_freq(fs=fs_in, units=freq_units, n_fft=n_fft, coh=True),
-            dims=["coh_freq"],
-            name="coh_freq",
-            attrs={
-                "units": freq_units,
-                "long_name": "FFT Frequency Vector",
-                "coverage_content_type": "coordinate",
-            },
-        ).astype("float32")
 
         for ip, ipair in enumerate(self._cross_pairs):
-            out[ip] = self._csd_base(
+            f, out[ip] = self._csd_base(
                 veldat[ipair[0]],
                 veldat[ipair[1]],
                 fs=fs,
                 window=window,
                 n_bin=n_bin,
                 n_fft=n_fft,
+                pct_overlap=pct_overlap,
             )
+        coh_freq = xr.DataArray(
+            f,
+            dims=["coh_freq"],
+            name="coh_freq",
+            attrs={
+                "units": freq_units,
+                "long_name": "FFT Frequency Vector",
+                "coverage_content_type": "coordinate",
+            },
+        )
 
         csd = xr.DataArray(
             out.astype("complex64"),
-            coords={"C": self.C, "time": time, "coh_freq": coh_freq},
-            dims=["C", "time", "coh_freq"],
+            coords={"C": self.C, "time_psd": time_coord, "coh_freq": coh_freq},
+            dims=["C", "time_psd", "coh_freq"],
             attrs={
                 "units": units,
                 "n_fft_coh": n_fft,
@@ -262,9 +267,10 @@ def doppler_noise_level(self, psd, pct_fN=0.8):
         N2 = psd.sel(freq=f_range) * psd.freq.sel(freq=f_range)
         noise_level = np.sqrt(N2.mean(dim="freq"))
 
+        time_dim = psd.dims[-2]
         return xr.DataArray(
-            noise_level.values.astype("float32"),
-            coords={"S": psd["S"], "time": psd["time"]},
+            noise_level.values,
+            coords={"S": psd["S"], time_dim: psd[time_dim]},
             attrs={
                 "units": "m/s",
                 "long_name": "Doppler Noise Level",
@@ -404,8 +410,6 @@ def dissipation_rate_LT83(
             raise TypeError("`psd` must be an instance of `xarray.DataArray`.")
         if len(U_mag.shape) != 1:
             raise Exception("U_mag should be 1-dimensional (time).")
-        if len(psd["time"]) != len(U_mag["time"]):
-            raise Exception("`U_mag` should be from ensembled-averaged dataset.")
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
         # if the spectra are 1D, then the first dimension should be time (any length)
@@ -419,7 +423,7 @@ def dissipation_rate_LT83(
         else:
             noise = np.array([0, 0, 0])[:, None, None]
 
-        # Noise subtraction from binner.TimeBinner.calc_psd_base
+        # Noise subtraction
         psd = psd.copy()
         if noise is not None:
             psd -= noise**2 / (self.fs / 2)
@@ -429,6 +433,15 @@ def dissipation_rate_LT83(
         idx = np.where((freq_range[0] < freq) & (freq < freq_range[1]))
         idx = idx[0]
 
+        # Interpolate U_mag to the same time dimension as PSD
+        umag_time_dim = U_mag.dims[-1]
+        psd_time_dim = psd.dims[-2]
+        # If overlap is not 0%
+        if psd[psd_time_dim].size != U_mag[umag_time_dim].size:
+            U_mag = U_mag.interp({umag_time_dim: psd[psd_time_dim].values}).values
+        else:
+            U_mag = U_mag.values
+
         # Set the correct magnitude whether the frequency is in Hz or rad/s
         if freq.units == "Hz":
             U = U_mag / (2 * np.pi)
@@ -448,7 +461,7 @@ def dissipation_rate_LT83(
         ) ** (3 / 2) / U
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             attrs={
                 "units": "m2 s-3",
                 "long_name": "TKE Dissipation Rate",
@@ -505,13 +518,13 @@ def dissipation_rate_SF(self, vel_raw, U_mag, fs=None, freq_range=[2.0, 4.0]):
             lag = U_mag.values[slc[:-1]] / fs * np.arange(up.shape[0])
             DAA = _nans_like(lag)
             for L in range(int(fs / freq_range[1]), int(fs / freq_range[0])):
-                DAA[L] = np.nanmean((up[L:] - up[:-L]) ** 2, dtype=np.float64)
+                DAA[L] = np.nanmean((up[L:] - up[:-L]) ** 2)
             cv2 = DAA / (lag ** (2 / 3))
             cv2m = np.median(cv2[np.logical_not(np.isnan(cv2))])
             out[slc[:-1]] = (cv2m / 2.1) ** (3 / 2)
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             coords=U_mag.coords,
             dims=U_mag.dims,
             attrs={
@@ -597,9 +610,14 @@ def dissipation_rate_TE01(self, dat_raw, dat_avg, freq_range=[6.28, 12.57]):
             raise TypeError("`dat_avg` must be an instance of `xarray.Dataset`.")
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
-
+        if "tke_vec" not in dat_avg:
+            raise Exception(
+                "The bin-averaged dataset must have the `tke_vec` variable "
+                "(i.e., calculated from `ADVBinner.calc_turbulence` or "
+                "`VelBinner.bin_average`)."
+            )
         # Assign local names
-        U_mag = dat_avg.velds.U_mag.values
+        U_mag = dat_avg.velds.U_mag
         I_tke = dat_avg.velds.I_tke.values
         theta = np.angle(dat_avg.velds.U.values) - self._up_angle(
             dat_raw.velds.U.values
@@ -610,9 +628,18 @@ def dissipation_rate_TE01(self, dat_raw, dat_avg, freq_range=[6.28, 12.57]):
         alpha = 1.5
         intgrl = self._integral_TE01(I_tke, theta)
 
+        # Interpolate PSD to the same time dimension as dat_avg
+        umag_time_dim = U_mag.dims[-1]
+        psd_time_dim = dat_avg["psd"].dims[-2]
+        # If overlap is not 0%
+        if dat_avg[psd_time_dim].size != U_mag[umag_time_dim].size:
+            psd = dat_avg["psd"].interp({psd_time_dim: dat_avg[umag_time_dim]}).values
+        else:
+            psd = dat_avg["psd"].values
+
         # Index data to be used
         inds = (freq_range[0] < freq) & (freq < freq_range[1])
-        psd = dat_avg["psd"][..., inds].values
+        psd = psd[..., inds]
         freq = freq[inds].reshape([1] * (dat_avg["psd"].ndim - 2) + [sum(inds)])
 
         # Estimate values
@@ -620,18 +647,18 @@ def dissipation_rate_TE01(self, dat_raw, dat_avg, freq_range=[6.28, 12.57]):
         out = (
             np.nanmean((psd[0] + psd[1]) * freq ** (5 / 3), -1)
             / (21 / 55 * alpha * intgrl)
-        ) ** (3 / 2) / U_mag
+        ) ** (3 / 2) / U_mag.values
 
         # Add w component
         out += (
             np.nanmean(psd[2] * freq ** (5 / 3), -1) / (12 / 55 * alpha * intgrl)
-        ) ** (3 / 2) / U_mag
+        ) ** (3 / 2) / U_mag.values
 
         # Average the two estimates
         out *= 0.5
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             coords={"time": dat_avg["time"]},
             dims="time",
             attrs={
@@ -695,7 +722,7 @@ def integral_length_scales(self, a_cov, U_mag, fs=None):
         L_int = U_mag.values * T_int
 
         return xr.DataArray(
-            L_int.astype("float32"),
+            L_int,
             coords={"dir": a_cov["dir"], "time": a_cov["time"]},
             attrs={
                 "units": "m",
@@ -703,55 +730,3 @@ def integral_length_scales(self, a_cov, U_mag, fs=None):
                 "standard_name": "turbulent_mixing_length_of_sea_water",
             },
         )
-
-
-def turbulence_statistics(
-    ds_raw, n_bin, fs, n_fft=None, freq_units="rad/s", window="hann"
-):
-    """
-    Functional version of `ADVBinner` that computes a suite of turbulence
-    statistics for the input dataset, and returns a `binned` data object.
-
-    Parameters
-    ----------
-    ds_raw : xarray.Dataset
-      The raw adv datset to bin, average, and compute turbulence statistics
-      from.
-    freq_units : string
-      Frequency units of the returned spectra in either Hz or rad/s
-      (`f` or :math:`\\omega`). Default = 'rad/s'
-    window : string or array
-      The window to use for calculating spectra.
-
-    Returns
-    -------
-    ds : xarray.Dataset
-      Returns an 'binned' (i.e. 'averaged') data object. All
-      fields (variables) of the input data object are averaged in `n_bin`
-      chunks. This object also computes the following items over
-      those chunks:
-
-      - tke_vec : The energy in each component, each components is
-        alternatively accessible as:
-        :attr:`upup_ <dolfyn.velocity.Velocity.upup_>`,
-        :attr:`vpvp_ <dolfyn.velocity.Velocity.vpvp_>`,
-        :attr:`wpwp_ <dolfyn.velocity.Velocity.wpwp_>`)
-
-      - stress_vec : The Reynolds stresses, each component is
-        alternatively accessible as:
-        :attr:`upwp_ <dolfyn.data.velocity.Velocity.upwp_>`,
-        :attr:`vpwp_ <dolfyn.data.velocity.Velocity.vpwp_>`,
-        :attr:`upvp_ <dolfyn.data.velocity.Velocity.upvp_>`)
-
-      - U_std : The standard deviation of the horizontal
-        velocity `U_mag`.
-
-      - psd : DataArray containing the spectra of the velocity
-        in radial frequency units. The data-array contains:
-        - vel : the velocity spectra array (m^2/s/rad))
-        - omega : the radial frequncy (rad/s)
-    """
-
-    calculator = ADVBinner(n_bin, fs, n_fft=n_fft)
-
-    return calculator(ds_raw, freq_units=freq_units, window=window)
diff --git a/mhkit/dolfyn/binned.py b/mhkit/dolfyn/binned.py
index 2cc9e3f23..b4802e4f7 100644
--- a/mhkit/dolfyn/binned.py
+++ b/mhkit/dolfyn/binned.py
@@ -1,7 +1,7 @@
 import numpy as np
 import warnings
-from .tools.fft import fft_frequency, psd_1D, cpsd_1D, cpsd_quasisync_1D
-from .tools.misc import slice1d_along_axis, detrend_array
+from scipy import signal
+from .tools import slice1d_along_axis, detrend_array
 from .time import epoch2dt64, dt642epoch
 
 warnings.simplefilter("ignore", RuntimeWarning)
@@ -55,13 +55,16 @@ def _outshape(self, inshape, n_pad=0, n_bin=None):
         n_bin = int(self._parse_nbin(n_bin))
         return list(inshape[:-1]) + [int(inshape[-1] // n_bin), int(n_bin + n_pad)]
 
-    def _outshape_fft(self, inshape, n_fft=None, n_bin=None):
+    def _outshape_fft(self, inshape, n_fft=None, n_bin=None, step=None):
         """
         Returns `outshape` (the fft 'reshape'd shape) for an `inshape` array.
         """
         n_fft = self._parse_nfft(n_fft)
         n_bin = self._parse_nbin(n_bin)
-        return list(inshape[:-1]) + [int(inshape[-1] // n_bin), int(n_fft // 2)]
+        if step is None:
+            step = n_bin
+        n_slices = (inshape[-1] - n_bin) // step + 1
+        return list(inshape[:-1]) + [int(n_slices), int(n_fft // 2)]
 
     def _parse_fs(self, fs=None):
         if fs is None:
@@ -173,88 +176,49 @@ def _new_coords(self, array):
 
         return dims_list, coords_dict
 
-    def reshape(self, arr, n_pad=0, n_bin=None):
+    def reshape(self, arr, step=None, n_bin=None):
         """
-        Reshape the array `arr` to shape (...,n,n_bin+n_pad).
+        Reshape the array `arr` into sliding windows of shape (..., n_slices, n_bin).
 
         Parameters
         ----------
         arr : numpy.ndarray
-        n_pad : int
-          Is used to add `n_pad`/2 points from the end of the previous
-          ensemble to the top of the current, and `n_pad`/2 points
-          from the top of the next ensemble to the bottom of the
-          current.  Zeros are padded in the upper-left and lower-right
-          corners of the matrix (beginning/end of timeseries).  In
-          this case, the array shape will be (...,`n`,`n_pad`+`n_bin`)
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
-          Override this binner's n_bin. Default is `self.n_bin`
+          Window (bin) size. Default is `self.n_bin`
 
         Returns
         -------
         out : numpy.ndarray
-
-        Notes
-        -----
-        `n_bin` can be non-integer, in which case the output array
-        size will be `n_pad`+`n_bin`, and the decimal will
-        cause skipping of some data points in `arr`.  In particular,
-        every mod(`n_bin`,1) bins will have a skipped point. For
-        example:
-        - for n_bin=2048.2 every 1/5 bins will have a skipped point.
-        - for n_bin=4096.9 every 9/10 bins will have a skipped point.
+          Shape (..., n_slices, n_bin) where
+          n_slices = (N - n_bin) // step + 1
         """
 
-        n_bin = self._parse_nbin(n_bin)
+        n_bin = int(self._parse_nbin(n_bin))
         if arr.shape[-1] < n_bin:
             raise Exception("n_bin is larger than length of input array")
-        npd0 = int(n_pad // 2)
-        npd1 = int((n_pad + 1) // 2)
-        shp = self._outshape(arr.shape, n_pad=0, n_bin=n_bin)
-        out = np.zeros(
-            self._outshape(arr.shape, n_pad=n_pad, n_bin=n_bin), dtype=arr.dtype
-        )
-        if np.mod(n_bin, 1) == 0:
-            # n_bin needs to be int
-            n_bin = int(n_bin)
-            # If n_bin is an integer, we can do this simply.
-            out[..., npd0 : n_bin + npd0] = (arr[..., : (shp[-2] * shp[-1])]).reshape(
-                shp, order="C"
-            )
-        else:
-            inds = (np.arange(np.prod(shp[-2:])) * n_bin // int(n_bin)).astype(int)
-            # If there are too many indices, drop one bin
-            if inds[-1] >= arr.shape[-1]:
-                inds = inds[: -int(n_bin)]
-                shp[-2] -= 1
-                out = out[..., 1:, :]
-            n_bin = int(n_bin)
-            out[..., npd0 : n_bin + npd0] = (arr[..., inds]).reshape(shp, order="C")
-            n_bin = int(n_bin)
-        if n_pad != 0:
-            out[..., 1:, :npd0] = out[..., :-1, n_bin : n_bin + npd0]
-            out[..., :-1, -npd1:] = out[..., 1:, npd0 : npd0 + npd1]
-
+        if step is None:
+            step = n_bin
+        step = int(step)
+        sliding_window = np.lib.stride_tricks.sliding_window_view(arr, n_bin, axis=-1)
+        out = sliding_window[..., ::step, :].copy()
         return out
 
-    def detrend(self, arr, axis=-1, n_pad=0, n_bin=None):
+    def detrend(self, arr, axis=-1, step=None, n_bin=None):
         """
-        Reshape the array `arr` to shape (...,n,n_bin+n_pad)
-        and remove the best-fit trend line from each bin.
+        Reshape the array `arr` into sliding windows and remove the
+        best-fit trend line from each window.
 
         Parameters
         ----------
         arr : numpy.ndarray
         axis : int
-          Axis along which to take mean. Default = -1
-        n_pad : int
-          Is used to add `n_pad`/2 points from the end of the previous
-          ensemble to the top of the current, and `n_pad`/2 points
-          from the top of the next ensemble to the bottom of the
-          current.  Zeros are padded in the upper-left and lower-right
-          corners of the matrix (beginning/end of timeseries).  In
-          this case, the array shape will be (...,`n`,`n_pad`+`n_bin`).
-          Default = 0
+          Axis along which to detrend. Default = -1
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
           Override this binner's n_bin. Default is `self.n_bin`
 
@@ -263,26 +227,21 @@ def detrend(self, arr, axis=-1, n_pad=0, n_bin=None):
         out : numpy.ndarray
         """
 
-        return detrend_array(self.reshape(arr, n_pad=n_pad, n_bin=n_bin), axis=axis)
+        return detrend_array(self.reshape(arr, step=step, n_bin=n_bin), axis=axis)
 
-    def demean(self, arr, axis=-1, n_pad=0, n_bin=None):
+    def demean(self, arr, axis=-1, step=None, n_bin=None):
         """
-        Reshape the array `arr` to shape (...,n,n_bin+n_pad)
-        and remove the mean from each bin.
+        Reshape the array `arr` into sliding windows and remove the
+        mean from each window.
 
         Parameters
         ----------
         arr : numpy.ndarray
         axis : int
           Axis along which to take mean. Default = -1
-        n_pad : int
-          Is used to add `n_pad`/2 points from the end of the previous
-          ensemble to the top of the current, and `n_pad`/2 points
-          from the top of the next ensemble to the bottom of the
-          current.  Zeros are padded in the upper-left and lower-right
-          corners of the matrix (beginning/end of timeseries).  In
-          this case, the array shape will be (...,`n`,`n_pad`+`n_bin`).
-          Default = 0
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
           Override this binner's n_bin. Default is `self.n_bin`
 
@@ -291,10 +250,10 @@ def demean(self, arr, axis=-1, n_pad=0, n_bin=None):
         out : numpy.ndarray
         """
 
-        dt = self.reshape(arr, n_pad=n_pad, n_bin=n_bin)
+        dt = self.reshape(arr, step=step, n_bin=n_bin)
         return dt - np.nanmean(dt, axis)[..., None]
 
-    def mean(self, arr, axis=-1, n_bin=None):
+    def mean(self, arr, axis=-1, step=None, n_bin=None):
         """
         Reshape the array `arr` to shape (...,n,n_bin+n_pad)
         and take the mean of each bin along the specified `axis`.
@@ -304,6 +263,9 @@ def mean(self, arr, axis=-1, n_bin=None):
         arr : numpy.ndarray
         axis : int
           Axis along which to take mean. Default = -1
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
           Override this binner's n_bin. Default is `self.n_bin`
 
@@ -313,15 +275,17 @@ def mean(self, arr, axis=-1, n_bin=None):
         """
 
         if np.issubdtype(arr.dtype, np.datetime64):
-            return epoch2dt64(self.mean(dt642epoch(arr), axis=axis, n_bin=n_bin))
+            return epoch2dt64(
+                self.mean(dt642epoch(arr), axis=axis, step=step, n_bin=n_bin)
+            )
         if axis != -1:
             arr = np.swapaxes(arr, axis, -1)
         n_bin = self._parse_nbin(n_bin)
-        tmp = self.reshape(arr, n_bin=n_bin)
+        tmp = self.reshape(arr, step=step, n_bin=n_bin)
 
         return np.nanmean(tmp, -1)
 
-    def variance(self, arr, axis=-1, n_bin=None):
+    def variance(self, arr, axis=-1, step=None, n_bin=None):
         """
         Reshape the array `arr` to shape (...,n,n_bin+n_pad)
         and take the variance of each bin along the specified `axis`.
@@ -331,6 +295,9 @@ def variance(self, arr, axis=-1, n_bin=None):
         arr : numpy.ndarray
         axis : int
           Axis along which to take variance. Default = -1
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
           Override this binner's n_bin. Default is `self.n_bin`
 
@@ -339,9 +306,9 @@ def variance(self, arr, axis=-1, n_bin=None):
         out : numpy.ndarray
         """
 
-        return np.nanvar(self.reshape(arr, n_bin=n_bin), axis=axis, dtype=np.float32)
+        return np.nanvar(self.reshape(arr, step=step, n_bin=n_bin), axis=axis)
 
-    def standard_deviation(self, arr, axis=-1, n_bin=None):
+    def standard_deviation(self, arr, axis=-1, step=None, n_bin=None):
         """
         Reshape the array `arr` to shape (...,n,n_bin+n_pad)
         and take the standard deviation of each bin along the
@@ -352,6 +319,9 @@ def standard_deviation(self, arr, axis=-1, n_bin=None):
         arr : numpy.ndarray
         axis : int
           Axis along which to take std dev. Default = -1
+        step : int
+          Number of samples to advance between consecutive windows.
+          Default: n_bin (non-overlapping windows).
         n_bin : int
           Override this binner's n_bin. Default is `self.n_bin`
 
@@ -360,7 +330,7 @@ def standard_deviation(self, arr, axis=-1, n_bin=None):
         out : numpy.ndarray
         """
 
-        return np.nanstd(self.reshape(arr, n_bin=n_bin), axis=axis, dtype=np.float32)
+        return np.nanstd(self.reshape(arr, step=step, n_bin=n_bin), axis=axis)
 
     def _psd_base(
         self,
@@ -370,10 +340,10 @@ def _psd_base(
         noise=0,
         n_bin=None,
         n_fft=None,
-        step=None,
+        pct_overlap=0.5,
     ):
         """
-        Calculate power spectral density of `dat`
+        Calculate the power spectral density of `dat`
 
         Parameters
         ----------
@@ -381,8 +351,11 @@ def _psd_base(
           The raw dataArray of which to calculate the psd.
         fs : float (optional)
           The sample rate (Hz).
-        window : str
-          String indicating the window function to use. Default is 'hanning'
+        window : {None, 1, 'hann', numpy.ndarray}
+          The window to use (default: 'hann'). Valid entries are:
+            - None,1               : uses a 'boxcar' or ones window.
+            - 'hann'               : hanning window.
+            - a length(nfft) array : use this as the window directly.
         noise  : float
           The white-noise level of the measurement (in the same units
           as `dat`).
@@ -392,10 +365,8 @@ def _psd_base(
         n_fft : int
           n_fft of veldat2, number of elements per bin if 'None' is taken
           from VelBinner
-        step : int (optional)
-          Controls amount of overlap in fft. Default: the step size is
-          chosen to maximize data use, minimize nens, and have a
-          minimum of 50% overlap.
+        pct_overlap : float
+          The percent overlap between FFT windows (default: 0.5)
 
         Returns
         -------
@@ -408,42 +379,71 @@ def _psd_base(
         """
 
         fs = self._parse_fs(fs)
+        # n_bin determines the number of time bins in the output
         n_bin = self._parse_nbin(n_bin)
+        # n_fft determines the length and resolution of the frequency vector
         n_fft = self._parse_nfft(n_fft)
-        out = np.empty(self._outshape_fft(dat.shape, n_fft=n_fft, n_bin=n_bin))
-        # The data is detrended in psd, so we don't need to do it here.
-        dat = self.reshape(dat)
-
-        for slc in slice1d_along_axis(dat.shape, -1):
-            out[slc] = psd_1D(dat[slc], n_fft, fs, window=window, step=step)
+        # step is the advance between consecutive bin slices.
+        # For pct_overlap fraction of overlap: step = n_bin * (1 - pct_overlap).
+        step = int((1 - pct_overlap) * n_bin)
+        out = np.empty(
+            self._outshape_fft(dat.shape, n_fft=n_fft, n_bin=n_bin, step=step)
+        )
+        n_samples = out.shape[-2]
+        for i in range(n_samples):
+            sample_slice = slice(i * step, i * step + int(n_bin))
+            freq, psd = signal.welch(
+                dat[sample_slice],
+                fs=fs,
+                window=window,
+                nperseg=n_fft,
+                noverlap=int(pct_overlap * n_fft),
+                detrend="linear",
+                return_onesided=True,
+                scaling="density",
+            )
+            # Drop DC bin (index 0): always ~0 after linear detrending, excluded by convention
+            out[i, :] = psd[1:]
         if np.any(noise):
             out -= noise**2 / (fs / 2)
             # Make sure all values of the PSD are >0 (but still small):
             out[out < 0] = np.min(np.abs(out)) / 100
-        return out
+        return freq[1:], out
 
-    def _csd_base(self, dat1, dat2, fs=None, window="hann", n_fft=None, n_bin=None):
+    def _csd_base(
+        self,
+        dat1,
+        dat2,
+        fs=None,
+        window="hann",
+        n_fft=None,
+        n_bin=None,
+        pct_overlap=0.5,
+    ):
         """
-        Calculate the cross power spectral density of `dat`.
+        Compute the cross power spectral density (CPSD) of the signals dat1 and dat2.
 
         Parameters
         ----------
         dat1 : numpy.ndarray
-          The first (shorter, if applicable) raw dataArray of which to
-          calculate the cpsd.
+          The first raw dataArray of which to calculate the cpsd.
         dat2 : numpy.ndarray
-          The second (the shorter, if applicable) raw dataArray of which to
-          calculate the cpsd.
+          The second raw dataArray of which to calculate the cpsd.
         fs : float (optional)
           The sample rate (Hz).
-        window : str
-          String indicating the window function to use. Default is 'hanning'
+        window : {None, 1, 'hann', numpy.ndarray}
+          The window to use (default: 'hann'). Valid entries are:
+            - None,1               : uses a 'boxcar' or ones window.
+            - 'hann'               : hanning window.
+            - a length(nfft) array : use this as the window directly.
         n_fft : int
-          n_fft of veldat2, number of elements per bin if 'None' is taken
-          from VelBinner
+          Number of elements in the FFT. If 'None', is taken
+          from VelBinner (uses n_fft_coh).
         n_bin : int
-          n_bin of veldat2, number of elements per bin if 'None' is taken
-          from VelBinner
+          Number of elements per bin. If 'None', is taken
+          from VelBinner.
+        pct_overlap : float
+          The percent overlap between sliding windows (default: 0.5).
 
         Returns
         -------
@@ -452,70 +452,53 @@ def _csd_base(self, dat1, dat2, fs=None, window="hann", n_fft=None, n_bin=None):
 
         Notes
         -----
-        PSD's are calculated based on sample rate units
+        PSDs are calculated based on sample rate units.
+        This removes a linear trend from the signals.
+        The two signals must be the same length and both be real.
 
-        The two velocity inputs do not have to be perfectly synchronized, but
-        they should have the same start and end timestamps
-        """
+        This performs:
 
-        fs = self._parse_fs(fs)
-        if n_fft is None:
-            n_fft = self.n_fft_coh
-        # want each slice to carry the same timespan
-        n_bin2 = self._parse_nbin(n_bin)  # bins for shorter array
-        n_bin1 = int(dat1.shape[-1] / (dat2.shape[-1] / n_bin2))
+        .. math::
 
-        oshp = self._outshape_fft(dat1.shape, n_fft=n_fft, n_bin=n_bin1)
-        oshp[-2] = np.min([oshp[-2], int(dat2.shape[-1] // n_bin2)])
+            fft(a)*conj(fft(b))
 
-        # The data is detrended in psd, so we don't need to do it here:
-        dat1 = self.reshape(dat1)
-        dat2 = self.reshape(dat2)
-        out = np.empty(oshp, dtype="c{}".format(dat1.dtype.itemsize * 2))
-        if dat1.shape == dat2.shape:
-            cross = cpsd_1D
-        else:
-            cross = cpsd_quasisync_1D
-        for slc in slice1d_along_axis(out.shape, -1):
-            out[slc] = cross(dat1[slc], dat2[slc], n_fft, fs, window=window)
-        return out
+        This implementation is consistent with the numpy.correlate
+        definition of correlation.  (The conjugate of D.B. Chelton's
+        definition of correlation.)
 
-    def _fft_freq(self, fs=None, units="Hz", n_fft=None, coh=False):
+        The units of the spectra is the product of the units of `a` and
+        `b`, divided by the units of fs.
         """
-        Wrapper to calculate the ordinary or radial frequency vector
-
-        Parameters
-        ----------
-        fs : float (optional)
-          The sample rate (Hz).
-        units : string
-          Frequency units in either Hz or rad/s (f or omega)
-        coh : bool
-          Calculate the frequency vector for coherence/cross-spectra
-          (default: False) i.e. use self.n_fft_coh instead of
-          self.n_fft.
-        n_fft : int
-          n_fft of veldat2, number of elements per bin if 'None' is taken
-          from VelBinner
-
-        Returns
-        -------
-        out: numpy.ndarray
-          Spectrum frequency array in units of 'Hz' or 'rad/s'
-        """
-
-        if n_fft is None:
-            n_fft = self.n_fft
-            if coh:
-                n_fft = self.n_fft_coh
 
         fs = self._parse_fs(fs)
+        n_fft = self._parse_nfft_coh(n_fft)
+        n_bin = self._parse_nbin(n_bin)
 
-        if ("Hz" not in units) and ("rad" not in units):
-            raise Exception("Valid fft frequency vector units are Hz \
-                            or rad/s")
+        if dat1.shape != dat2.shape:
+            raise ValueError(
+                "Cross-spectral density requires equal-length input arrays. "
+                "Quasi-synchronized (different sample rate) inputs are not supported."
+            )
+        if np.iscomplexobj(dat1) or np.iscomplexobj(dat2):
+            raise ValueError("Velocity cannot be complex")
 
-        if "rad" in units:
-            return fft_frequency(n_fft, 2 * np.pi * fs)
-        else:
-            return fft_frequency(n_fft, fs)
+        step = int((1 - pct_overlap) * n_bin)
+        oshp = self._outshape_fft(dat1.shape, n_fft=n_fft, n_bin=n_bin, step=step)
+        out = np.empty(oshp, dtype="c{}".format(dat1.dtype.itemsize * 2))
+        n_samples = oshp[-2]
+        for i in range(n_samples):
+            sample_slice = slice(i * step, i * step + int(n_bin))
+            freq, cpsd = signal.csd(
+                dat1[sample_slice],
+                dat2[sample_slice],
+                fs=fs,
+                window=window,
+                nperseg=n_fft,
+                noverlap=int(pct_overlap * n_fft),
+                detrend="linear",
+                return_onesided=True,
+                scaling="density",
+            )
+            # Drop DC bin (index 0): always ~0 after linear detrending, excluded by convention
+            out[i, :] = cpsd[1:]
+        return freq[1:], out
diff --git a/mhkit/dolfyn/io/nortek.py b/mhkit/dolfyn/io/nortek.py
index 76d619143..c33cbb180 100644
--- a/mhkit/dolfyn/io/nortek.py
+++ b/mhkit/dolfyn/io/nortek.py
@@ -8,7 +8,7 @@
 from . import base
 from . import nortek_defs as defs
 from . import nortek_lib as lib
-from ..tools import misc as tbx
+from .. import tools as tbx
 from ..rotate.vector import _calc_omat
 from ..rotate.base import _set_coords
 from ..rotate import api as rot
diff --git a/mhkit/dolfyn/time.py b/mhkit/dolfyn/time.py
index bceb699b5..4ad5c31bd 100644
--- a/mhkit/dolfyn/time.py
+++ b/mhkit/dolfyn/time.py
@@ -1,6 +1,6 @@
 from datetime import datetime, timedelta, timezone
 import numpy as np
-from .tools.misc import fillgaps
+from .tools import fillgaps
 
 
 def _fullyear(year):
diff --git a/mhkit/dolfyn/tools/misc.py b/mhkit/dolfyn/tools.py
similarity index 98%
rename from mhkit/dolfyn/tools/misc.py
rename to mhkit/dolfyn/tools.py
index 6bcfbc5f7..24a84b625 100644
--- a/mhkit/dolfyn/tools/misc.py
+++ b/mhkit/dolfyn/tools.py
@@ -205,7 +205,7 @@ def fillgaps(a, maxgap=np.inf, dim=0, extrapFlg=False):
 
     See Also
     --------
-    mhkit.dolfyn.tools.misc._interpgaps : Linearly interpolates in time.
+    mhkit.dolfyn.tools._interpgaps : Linearly interpolates in time.
 
     Notes
     -----
@@ -278,7 +278,7 @@ def interpgaps(a, t, maxgap=np.inf, dim=0, extrapFlg=False):
 
     See Also
     --------
-    mhkit.dolfyn.tools.misc.fillgaps : Linearly interpolates in array-index space.
+    mhkit.dolfyn.tools.fillgaps : Linearly interpolates in array-index space.
     """
 
     # If this is a multi-dimensional array, operate along dim dim.
diff --git a/mhkit/dolfyn/tools/__init__.py b/mhkit/dolfyn/tools/__init__.py
deleted file mode 100644
index af4fca326..000000000
--- a/mhkit/dolfyn/tools/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-from mhkit.dolfyn.tools import misc
-from mhkit.dolfyn.tools import fft
diff --git a/mhkit/dolfyn/tools/fft.py b/mhkit/dolfyn/tools/fft.py
deleted file mode 100644
index 2bd5b6511..000000000
--- a/mhkit/dolfyn/tools/fft.py
+++ /dev/null
@@ -1,316 +0,0 @@
-import numpy as np
-from .misc import detrend_array
-
-fft = np.fft.fft
-
-
-def fft_frequency(nfft, fs, full=False):
-    """
-    Compute the frequency vector for a given `nfft` and `fs`.
-
-    Parameters
-    ----------
-    fs : float
-      The sampling frequency (e.g. samples/sec)
-    nfft : int
-      The number of samples in a window.
-    full : bool
-      Whether to return half frequencies (positive), or the full frequencies.
-      Default = False
-
-    Returns
-    -------
-    freq : numpy.ndarray
-      The frequency vector, in same units as 'fs'
-    """
-
-    fs = np.float64(fs)
-    f = np.fft.fftfreq(int(nfft), 1 / fs)
-    if full:
-        return f
-    else:
-        return np.abs(f[1 : int(nfft / 2.0 + 1)])
-
-
-def _getwindow(window, nfft):
-    if window is None:
-        window = np.ones(nfft)
-    elif isinstance(window, (int, float)) and window == 1:
-        window = np.ones(nfft)
-    elif isinstance(window, str):
-        if "hann" in window:
-            window = np.hanning(nfft)
-        elif "hamm" in window:
-            window = np.hamming(nfft)
-        else:
-            raise ValueError("Unsupported window type: {}".format(window))
-    elif isinstance(window, np.ndarray):
-        if len(window) != nfft:
-            raise ValueError("Custom window length must be equal to nfft")
-    else:
-        raise ValueError("Invalid window parameter")
-
-    return window
-
-
-def _stepsize(l, nfft, nens=None, step=None):
-    """
-    Calculates the fft-step size for a length *l* array.
-
-    If nens is None, the step size is chosen to maximize data use,
-    minimize nens and have a minimum of 50% overlap.
-
-    If nens is specified, the step-size is computed directly.
-
-    Parameters
-    ----------
-    l       : The length of the array.
-    nfft    : The number of points in the fft.
-    nens : The number of nens to perform (default compute this).
-
-    Returns
-    -------
-    step    : The step size.
-    nens    : The number of ensemble ffts to average together.
-    nfft    : The number of points in the fft (set to l if nfft>l).
-    """
-
-    if l < nfft:
-        nfft = l
-    if nens is None and step is None:
-        if l == nfft:
-            return 0, 1, int(nfft)
-        nens = int(2.0 * l / nfft)
-        return int((l - nfft) / (nens - 1)), nens, int(nfft)
-    elif nens is None:
-        return int(step), int((l - nfft) / step + 1), int(nfft)
-    else:
-        if nens == 1:
-            return 0, 1, int(nfft)
-        return int((l - nfft) / (nens - 1)), int(nens), int(nfft)
-
-
-def cpsd_quasisync_1D(a, b, nfft, fs, window="hann"):
-    """
-    Compute the cross power spectral density (CPSD) of the signals `a` and `b`.
-
-    Parameters
-    ----------
-    a : numpy.ndarray
-      The first signal.
-    b : numpy.ndarray
-      The second signal.
-    nfft : int
-      The number of points in the fft.
-    fs : float
-      The sample rate (e.g. sample/second).
-    window : {None, 1, 'hann', numpy.ndarray}
-      The window to use (default: 'hann'). Valid entries are:
-      - None,1               : uses a 'boxcar' or ones window.
-      - 'hann'               : hanning window.
-      - a length(nfft) array : use this as the window directly.
-
-    Returns
-    -------
-    cpsd : numpy.ndarray
-      The cross-spectral density of `a` and `b`.
-
-    See Also
-    ---------
-    :func:`psd`,
-    :func:`coherence_1D`,
-    :func:`cpsd_1D`,
-    numpy.fft
-
-    Notes
-    -----
-    `a` and `b` do not need to be 'tightly' synchronized, and can even
-    be different lengths, but the first- and last-index of both series
-    should be synchronized (to whatever degree you want unbiased
-    phases).
-
-    This performs:
-
-    .. math::
-
-        fft(a)*conj(fft(b))
-
-    Note that this is consistent with :func:`numpy.correlate`.
-
-    It detrends the data and uses a minimum of 50% overlap for the
-    shorter of `a` and `b`. For the longer, the overlap depends on the
-    difference in size.  1-(l_short/l_long) data will be underutilized
-    (where l_short and l_long are the length of the shorter and longer
-    series, respectively).
-
-    The units of the spectra is the product of the units of `a` and
-    `b`, divided by the units of fs.
-    """
-
-    if np.iscomplexobj(a) or np.iscomplexobj(b):
-        raise Exception("Velocity cannot be complex")
-    l = [len(a), len(b)]
-    if l[0] == l[1]:
-        return cpsd_1D(a, b, nfft, fs, window=window)
-    elif l[0] > l[1]:
-        a, b = b, a
-        l = l[::-1]
-    step = [0, 0]
-    step[0], nens, nfft = _stepsize(l[0], nfft)
-    step[1], nens, nfft = _stepsize(l[1], nfft, nens=nens)
-    fs = np.float64(fs)
-    window = _getwindow(window, nfft)
-    fft_inds = slice(1, int(nfft / 2.0 + 1))
-    wght = 2.0 / (window**2).sum()
-    pwr = fft(detrend_array(a[0:nfft]) * window)[fft_inds] * np.conj(
-        fft(detrend_array(b[0:nfft]) * window)[fft_inds]
-    )
-    if nens - 1:
-        for i1, i2 in zip(
-            range(step[0], l[0] - nfft + 1, step[0]),
-            range(step[1], l[1] - nfft + 1, step[1]),
-        ):
-            pwr += fft(detrend_array(a[i1 : (i1 + nfft)]) * window)[fft_inds] * np.conj(
-                fft(detrend_array(b[i2 : (i2 + nfft)]) * window)[fft_inds]
-            )
-    pwr *= wght / nens / fs
-    return pwr
-
-
-def cpsd_1D(a, b, nfft, fs, window="hann", step=None):
-    """
-    Compute the cross power spectral density (CPSD) of the signals `a` and `b`.
-
-    Parameters
-    ----------
-    a : numpy.ndarray
-      The first signal.
-    b : numpy.ndarray
-      The second signal.
-    nfft : int
-      The number of points in the fft.
-    fs : float
-      The sample rate (e.g. sample/second).
-    window : {None, 1, 'hann', numpy.ndarray}
-      The window to use (default: 'hann'). Valid entries are:
-      - None,1               : uses a 'boxcar' or ones window.
-      - 'hann'               : hanning window.
-      - a length(nfft) array : use this as the window directly.
-    step : int
-      Use this to specify the overlap.  For example:
-      - step : nfft/2 specifies a 50% overlap.
-      - step : nfft specifies no overlap.
-      - step=2*nfft means that half the data will be skipped.
-      By default, `step` is calculated to maximize data use, have
-      at least 50% overlap and minimize the number of ensembles.
-
-    Returns
-    -------
-    cpsd : numpy.ndarray
-      The cross-spectral density of `a` and `b`.
-
-    See also
-    --------
-    :func:`psd`
-    :func:`coherence_1D`
-    `numpy.fft`
-
-    Notes
-    -----
-    cpsd removes a linear trend from the signals.
-
-    The two signals should be the same length, and should both be real.
-
-    This performs:
-
-    .. math::
-
-        fft(a)*conj(fft(b))
-
-    This implementation is consistent with the numpy.correlate
-    definition of correlation.  (The conjugate of D.B. Chelton's
-    definition of correlation.)
-
-    The units of the spectra is the product of the units of `a` and
-    `b`, divided by the units of fs.
-    """
-
-    if np.iscomplexobj(a) or np.iscomplexobj(b):
-        raise Exception("Velocity cannot be complex")
-    auto_psd = False
-    if a is b:
-        auto_psd = True
-    l = len(a)
-    step, nens, nfft = _stepsize(l, nfft, step=step)
-    fs = np.float64(fs)
-    window = _getwindow(window, nfft)
-    fft_inds = slice(1, int(nfft / 2.0 + 1))
-    wght = 2.0 / (window**2).sum()
-    # Take FFT of first segment
-    s1 = fft(detrend_array(a[0:nfft]) * window)[fft_inds]
-    if auto_psd:
-        pwr = np.abs(s1) ** 2
-    else:
-        pwr = s1 * np.conj(fft(detrend_array(b[0:nfft]) * window)[fft_inds])
-    # take FFT of remaining segments
-    if nens - 1:
-        for i in range(step, l - nfft + 1, step):
-            s1 = fft(detrend_array(a[i : (i + nfft)]) * window)[fft_inds]
-            if auto_psd:
-                pwr += np.abs(s1) ** 2
-            else:
-                pwr += s1 * np.conj(
-                    fft(detrend_array(b[i : (i + nfft)]) * window)[fft_inds]
-                )
-    pwr *= wght / nens / fs
-    return pwr
-
-
-def psd_1D(a, nfft, fs, window="hann", step=None):
-    """
-    Compute the power spectral density (PSD).
-
-    This function computes the one-dimensional `n`-point PSD.
-
-    The units of the spectra is the product of the units of `a` and
-    `b`, divided by the units of fs.
-
-    Parameters
-    ----------
-    a : numpy.ndarray
-      The first signal, as a 1D vector
-    nfft : int
-      The number of points in the fft.
-    fs : float
-      The sample rate (e.g. sample/second).
-    window : {None, 1, 'hann', numpy.ndarray}
-      The window to use (default: 'hann'). Valid entries are:
-      - None,1               : uses a 'boxcar' or ones window.
-      - 'hann'               : hanning window.
-      - a length(nfft) array : use this as the window directly.
-    step : int
-      Use this to specify the overlap.  For example:
-      - step : nfft/2 specifies a 50% overlap.
-      - step : nfft specifies no overlap.
-      - step=2*nfft means that half the data will be skipped.
-      By default, `step` is calculated to maximize data use, have
-      at least 50% overlap and minimize the number of ensembles.
-
-    Returns
-    -------
-    cpsd : numpy.ndarray
-      The cross-spectral density of `a` and `b`.
-
-    Notes
-    -----
-    Credit: This function's line of code was copied from JN's fast_psd.m
-    routine.
-
-    See Also
-    --------
-    :func:`cpsd_1D`
-    :func:`coherence_1D`
-    `numpy.fft`
-    """
-
-    return np.abs(cpsd_1D(a, a, nfft, fs, window=window, step=step))
diff --git a/mhkit/dolfyn/velocity.py b/mhkit/dolfyn/velocity.py
index 9b8dd557b..6646b542f 100644
--- a/mhkit/dolfyn/velocity.py
+++ b/mhkit/dolfyn/velocity.py
@@ -1,10 +1,11 @@
+import warnings
 import numpy as np
 import xarray as xr
 from .binned import TimeBinner
 from .time import dt642epoch, dt642date
 from .rotate.api import rotate2, set_declination, set_inst2head_rotmat
 from .io.api import save
-from .tools.misc import slice1d_along_axis, convert_degrees
+from .tools import slice1d_along_axis, convert_degrees
 
 
 @xr.register_dataset_accessor("velds")  # 'vel dataset'
@@ -779,7 +780,16 @@ def autocovariance(self, veldat, n_bin=None):
             self._outshape(indat.shape, n_bin=n_bin)[:-1] + [int(n_bin // 4)],
             dtype=indat.dtype,
         )
-        dt1 = self.reshape(indat, n_pad=n_bin / 2 - 2)
+        # Need to pad velocity timeseries with zeros to incoporate the full range of
+        # the auto-covariance.
+        n_pad = int(n_bin / 2 - 2)
+        npd0 = n_pad // 2
+        npd1 = (n_pad + 1) // 2
+        # Pad with zeros at boundaries to replicate the original n_pad behavior
+        indat_padded = np.pad(
+            indat, pad_width=[(0, 0)] * (indat.ndim - 1) + [(npd0, npd1)]
+        )
+        dt1 = self.reshape(indat_padded, step=int(n_bin), n_bin=int(n_bin + n_pad))
         # Here we de-mean only on the 'valid' range:
         dt1 = dt1 - dt1[..., :, int(n_bin // 4) : int(-n_bin // 4)].mean(-1)[..., None]
         dt2 = self.demean(indat)
@@ -811,6 +821,13 @@ def autocovariance(self, veldat, n_bin=None):
 
         return da
 
+    def _interp_noise(self, noise, time):
+        """Return noise as a numpy array, interpolating to binned `time` if needed."""
+        noise_time_dim = noise.dims[-1]
+        if time.size != noise[noise_time_dim].size:
+            return noise.interp({noise_time_dim: time}).values
+        return noise.values
+
     def turbulence_intensity(self, U_mag, noise=0, thresh=0, detrend=False):
         """
         Calculate noise-corrected turbulence intensity (TI).
@@ -838,7 +855,7 @@ def turbulence_intensity(self, U_mag, noise=0, thresh=0, detrend=False):
         if "xarray" in type(U_mag).__module__:
             U = U_mag.values
         if "xarray" in type(noise).__module__:
-            noise = noise.values
+            noise = self._interp_noise(noise, self.mean(U_mag["time"].values))
 
         if detrend:
             up = self.detrend(U)
@@ -903,7 +920,7 @@ def turbulent_kinetic_energy(self, veldat, noise=None, detrend=True):
         if "xarray" in type(veldat).__module__:
             vel = veldat.values
         if "xarray" in type(noise).__module__:
-            noise = noise.values
+            noise = self._interp_noise(noise, self.mean(veldat[veldat.dims[-1]].values))
 
         if len(np.shape(vel)) > 2:
             raise ValueError(
@@ -948,7 +965,7 @@ def turbulent_kinetic_energy(self, veldat, noise=None, detrend=True):
                     coords[nm] = veldat[nm].values
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             dims=dims,
             coords=coords,
             attrs={
@@ -967,7 +984,7 @@ def power_spectral_density(
         noise=0,
         n_bin=None,
         n_fft=None,
-        step=None,
+        pct_overlap=0,
     ):
         """
         Calculate the power spectral density of velocity.
@@ -980,9 +997,11 @@ def power_spectral_density(
           Frequency units of the returned spectra in either Hz or rad/s
         fs : float (optional)
           The sample rate. Default is `binner.fs`
-        window : string or array
-          Specify the window function.
-          Options = 1, None, 'hann', 'hamm'. Default = 'hann'
+        window: str
+          Type of window to apply to each FFT segment.
+          Example options: 'boxcar', 'hann', 'hamming', 'blackman', 'bartlett'.
+          See `scipy.signal.window` for more options.
+          Default: 'hann'.
         noise : numeric or array
           Instrument noise level in same units as velocity.
           Default = 0 (ADCP) or [0, 0, 0] (ADV)
@@ -990,10 +1009,11 @@ def power_spectral_density(
           The bin-size. Default = `self.n_bin`
         n_fft : int (optional)
           The fft size. Default = `self.n_fft`
-        step : int (optional)
-          Controls amount of overlap in fft. Default: the step size is
-          chosen to maximize data use, minimize nens, and have a
-          minimum of 50% overlap.
+        pct_overlap : float (optional)
+          Fractional overlap between consecutive sliding windows, in [0, 1).
+          Controls both the bin-to-bin advance and the within-bin FFT overlap
+          passed to scipy.signal.welch. Industry standard is 50%.
+          Default = 0 (0% overlap).
 
         Returns
         -------
@@ -1007,8 +1027,14 @@ def power_spectral_density(
             vel = veldat.values
         if ("rad" not in freq_units) and ("Hz" not in freq_units):
             raise ValueError("`freq_units` should be one of 'Hz' or 'rad/s'")
+        if (pct_overlap < 0) or (pct_overlap > 1):
+            raise ValueError(
+                f"pct_overlap must be between 0 and 1, received {pct_overlap}."
+            )
+        n_bin = self._parse_nbin(n_bin)
+        step = int((1 - pct_overlap) * n_bin)
 
-        # Create frequency vector, also checks whether using f or omega
+        # Set units correctly
         if "rad" in freq_units:
             fs = 2 * np.pi * fs_in
             freq_units = "rad s-1"
@@ -1017,18 +1043,8 @@ def power_spectral_density(
             fs = fs_in
             freq_units = "Hz"
             units = "m2 s-2 Hz-1"
-        freq = xr.DataArray(
-            self._fft_freq(fs=fs_in, units=freq_units, n_fft=n_fft),
-            dims=["freq"],
-            name="freq",
-            attrs={
-                "units": freq_units,
-                "long_name": "FFT Frequency Vector",
-                "coverage_content_type": "coordinate",
-            },
-        ).astype("float32")
 
-        # Spectra, if input is full velocity or a single array
+        # Spectra, if velocity is a 2D array (dir, time)
         if len(vel.shape) >= 2:
             if vel.shape[0] != 3:
                 raise ValueError(
@@ -1041,48 +1057,64 @@ def power_spectral_density(
             else:
                 # Reset default to list of 3 zeros
                 noise = np.array([0, 0, 0])
+            # Set up input velocity array, coordinates, and dimensions
+            vel_in = vel[:3]
+            coords = {"S": self.S}
+            dims = ["S"]
 
-            out = np.empty(
-                self._outshape_fft(vel[:3].shape, n_fft=n_fft, n_bin=n_bin),
-                dtype=np.float32,
-            )
-            for idx in range(3):
-                out[idx] = self._psd_base(
-                    vel[idx],
-                    fs=fs,
-                    noise=noise[idx],
-                    window=window,
-                    n_bin=n_bin,
-                    n_fft=n_fft,
-                    step=step,
-                )
-            coords = {
-                "S": self.S,
-                "time": self.mean(veldat["time"].values),
-                "freq": freq,
-            }
-            dims = ["S", "time", "freq"]
+        # Spectra, if velocity is a single array
         else:
             if np.array(noise).any() and np.size(noise) > 1:
                 raise ValueError("Noise is expected to be a scalar")
+            # Add dummy axis
+            vel_in = vel[np.newaxis]
+            noise = np.atleast_1d(noise)
+            coords = {}
+            dims = []
 
-            out = self._psd_base(
-                vel,
+        # Do power spectral density calculation for each velocity component
+        out = np.empty(
+            self._outshape_fft(vel_in.shape, n_fft=n_fft, n_bin=n_bin, step=step)
+        )
+        for idx in range(vel_in.shape[0]):
+            f, out[idx] = self._psd_base(
+                vel_in[idx],
                 fs=fs,
-                noise=noise,
+                noise=noise[idx],
                 window=window,
                 n_bin=n_bin,
                 n_fft=n_fft,
-                step=step,
+                pct_overlap=pct_overlap,
             )
-            coords = {
-                veldat.dims[-1]: self.mean(veldat[veldat.dims[-1]].values),
+        # If not 3D (ADV) data, remove the new axis
+        if "S" not in dims:
+            out = out[0]
+
+        # Create frequency vector, also checks whether using f or omega
+        freq = xr.DataArray(
+            f,
+            dims=["freq"],
+            name="freq",
+            attrs={
+                "units": freq_units,
+                "long_name": "FFT Frequency Vector",
+                "coverage_content_type": "coordinate",
+            },
+        )
+
+        # Update coordinates and dimensions
+        time = veldat[veldat.dims[-1]].values
+        time_coord = self.mean(time, step=step, n_bin=n_bin)
+        coords.update(
+            {
+                "time_psd": time_coord,
                 "freq": freq,
             }
-            dims = [veldat.dims[-1], "freq"]
+        )
+        dims += ["time_psd", "freq"]
 
         return xr.DataArray(
-            out.astype("float32"),
+            out,
             coords=coords,
             dims=dims,
             attrs={
diff --git a/mhkit/tests/acoustics/test_analysis.py b/mhkit/tests/acoustics/test_analysis.py
index 2e78e6adb..a5c8d872a 100644
--- a/mhkit/tests/acoustics/test_analysis.py
+++ b/mhkit/tests/acoustics/test_analysis.py
@@ -19,7 +19,9 @@ class TestAnalysis(unittest.TestCase):
     def setUpClass(self):
         file_name = join(datadir, "6247.230204150508.wav")
         P = acoustics.io.read_soundtrap(file_name, sensitivity=-177)
-        self.spsd = acoustics.sound_pressure_spectral_density(P, P.fs, bin_length=1)
+        self.spsd = acoustics.sound_pressure_spectral_density(
+            P, P.fs, bin_length=1, pct_overlap=0.5
+        )
 
     @classmethod
     def tearDownClass(self):
@@ -89,18 +91,15 @@ def test_sound_pressure_spectral_density(self):
         # Assert that output is an xarray DataArray with expected dimensions
         self.assertIsInstance(spsd, xr.DataArray)
         self.assertIn("freq", spsd.dims)
-        self.assertIn("time", spsd.dims)
+        self.assertIn("time_psd", spsd.dims)
         self.assertEqual(spsd.attrs["units"], "Pa^2/Hz")
         self.assertEqual(spsd.attrs["bin_length"], bin_length)
         self.assertEqual(spsd.attrs["n_fft"], bin_length * fs)
 
-        # Calculate expected number of segments
-        overlap = 0.0
-        step = int(win_samples * (1 - overlap))
+        # Calculate expected number of segments using the default pct_overlap=0.5
+        default_pct_overlap = 0.5
+        step = int(win_samples * (1 - default_pct_overlap))
         expected_segments = (len(pressure) - win_samples) // step + 1
-
-        # Calculate expected number of segments without overlap
-        expected_segments = len(pressure) // win_samples
         self.assertEqual(spsd.shape[0], expected_segments)
 
     def test_apply_calibration(self):
@@ -151,27 +150,27 @@ def test_spsdl(self):
 
         cc = np.array(
             [
-                "2023-02-04T15:05:08.499983310",
-                "2023-02-04T15:05:09.499959707",
+                "2023-02-04T15:05:08.499983072",
+                "2023-02-04T15:05:08.999971389",
+                "2023-02-04T15:05:09.499959945",
+                "2023-02-04T15:05:09.999948263",
                 "2023-02-04T15:05:10.499936580",
-                "2023-02-04T15:05:11.499913454",
-                "2023-02-04T15:05:12.499890089",
             ],
             dtype="datetime64[ns]",
         )
         cd_spsdl = np.array(
             [
-                [61.72558153, 60.45878138, 61.02543806, 62.10487326, 53.69452342],
-                [64.73788935, 63.7154788, 56.60306848, 55.59145693, 65.14298631],
-                [54.88840931, 64.81213715, 68.5464288, 66.96210531, 57.26933701],
-                [47.83166387, 46.34269439, 55.26689475, 59.97537222, 62.87564412],
-                [51.84125861, 58.33037915, 56.42519674, 55.83574275, 55.48694318],
+                [61.988365, 60.721523, 61.288155, 62.367813, 53.957424],
+                [62.66007, 62.149723, 63.124702, 53.72768, 59.11971],
+                [64.50701, 63.48456, 56.372044, 55.36059, 64.91209],
+                [58.399498, 55.154545, 60.971836, 63.37324, 61.89729],
+                [54.477947, 64.40175, 68.13605, 66.5518, 56.858593],
             ]
         )
 
         np.testing.assert_allclose(td_spsdl.head().values, cd_spsdl, atol=1e-6)
         np.testing.assert_allclose(
-            td_spsdl["time"].head().astype("int64"), cc.astype("int64"), atol=1
+            td_spsdl["time_psd"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
     def test_averaging_deprecated(self):
@@ -193,39 +192,39 @@ def test_averaging_deprecated(self):
 
         cc = np.array(
             [
-                "2023-02-04T15:05:23.499983310",
-                "2023-02-04T15:05:53.499983310",
-                "2023-02-04T15:06:23.499983310",
-                "2023-02-04T15:06:53.499983310",
-                "2023-02-04T15:07:23.499983310",
+                "2023-02-04T15:05:23.499983072",
+                "2023-02-04T15:05:53.499983072",
+                "2023-02-04T15:06:23.499983072",
+                "2023-02-04T15:06:53.499983072",
+                "2023-02-04T15:07:23.499983072",
             ],
             dtype="datetime64[ns]",
         )
         cd_spsdl_50 = np.array(
             [
-                [63.45507, 64.753525, 65.04905, 67.15576, 73.47938],
-                [62.77437, 64.58199, 65.18464, 66.37395, 72.30796],
-                [64.76277, 64.950264, 65.80557, 67.88482, 73.24013],
-                [63.654488, 62.31394, 65.598816, 67.370674, 71.52472],
-                [62.45623, 62.461388, 62.111694, 66.06419, 72.324936],
+                [62.650208, 64.61388, 64.1676, 66.67151, 72.549095],
+                [62.699905, 64.61284, 65.24815, 66.801186, 72.43181],
+                [64.310326, 64.8985, 65.44002, 67.19502, 72.76947],
+                [63.27369, 62.90754, 65.678055, 67.20142, 72.70676],
+                [62.58354, 63.303997, 62.390503, 65.700806, 72.212715],
             ]
         )
         cd_spsdl_25 = np.array(
             [
-                [59.33189297, 62.89503765, 61.60455799, 64.80938911, 70.59576607],
-                [60.37440872, 60.69928551, 61.9694643, 64.91986465, 70.00148964],
-                [61.1297617, 63.02504444, 64.41207123, 66.37802315, 71.38513947],
-                [59.52737236, 59.45869541, 62.48176765, 66.0959053, 70.06054497],
-                [58.55439758, 59.88098335, 59.66310596, 63.86431885, 70.20335197],
+                [58.7102747, 62.32302952, 61.36541462, 63.74158669, 70.69015503],
+                [58.94279099, 61.4001379, 61.44286156, 64.70808029, 70.42274666],
+                [59.65940571, 62.35227299, 63.31204796, 64.50473785, 71.06458282],
+                [60.09864521, 59.31335735, 62.70079613, 65.46805, 70.75235939],
+                [59.34419155, 59.50090408, 59.94284725, 63.75802994, 70.25077629],
             ]
         )
         cd_spsdl_75 = np.array(
             [
-                [66.33672714, 67.13593102, 67.34234238, 68.7525959, 75.30982399],
-                [64.58539009, 66.84792709, 67.11526108, 69.7322197, 74.50746346],
-                [66.56425095, 67.85562325, 69.30602646, 69.83069992, 74.79984283],
-                [67.34252357, 65.65701294, 67.48604202, 70.948246, 73.59340286],
-                [66.26214409, 65.43437958, 64.36196518, 67.67719078, 74.33639717],
+                [65.79078293, 67.23075867, 67.50594711, 68.57876396, 74.55014038],
+                [65.39378929, 67.34802818, 67.36330605, 69.40702248, 74.43621254],
+                [66.60365868, 67.17274666, 68.90455437, 68.7287178, 74.3719368],
+                [66.52753067, 66.5525074, 67.94759941, 70.20380783, 74.38684845],
+                [65.72010803, 66.15189743, 65.57708931, 67.85847664, 74.39115524],
             ]
         )
 
@@ -254,58 +253,58 @@ def test_averaging(self):
 
         cd_spsdl_dd = np.array(
             [
-                [65.93822, 62.86854, 60.797012, 62.410725, 60.77913],
-                [68.95052, 65.88085, 63.982758, 65.66743, 61.178196],
-                [59.101044, 56.03137, 63.76194, 66.764084, 67.23888],
-                [52.0443, 48.974625, 46.74791, 48.29464, 53.098785],
-                [56.053894, 52.98422, 57.43947, 60.282322, 57.38807],
+                [66.201004, 63.131325, 61.059765, 62.673466, 61.041855],
+                [66.8727, 63.80303, 62.277332, 64.10167, 62.71208],
+                [68.71965, 65.64997, 63.751846, 65.4365, 60.947254],
+                [62.612133, 59.542458, 56.17782, 57.10649, 59.21533],
+                [58.690582, 55.620907, 63.351555, 66.3537, 66.82849],
             ]
         )
         cd_spsdl_md_head = np.array(
             [
-                [61.725582, 60.458782, 61.02544, 62.104874, 53.694523],
-                [64.73789, 63.71548, 56.60307, 55.591457, 65.14299],
-                [54.88841, 64.81213, 68.54643, 66.962105, 57.269337],
-                [47.831665, 46.342693, 55.266895, 59.975372, 62.875645],
-                [51.84126, 58.33038, 56.425198, 55.835743, 55.486942],
+                [61.988365, 60.721523, 61.288155, 62.367813, 53.957424],
+                [62.66007, 62.149723, 63.124702, 53.72768, 59.11971],
+                [64.50701, 63.48456, 56.372044, 55.36059, 64.91209],
+                [58.399498, 55.154545, 60.971836, 63.37324, 61.89729],
+                [54.477947, 64.40175, 68.13605, 66.5518, 56.858593],
             ]
         )
         cd_spsdl_md_tail = np.array(
             [
-                [33.43558, 44.184784, 33.868732, 34.39551, 34.410404],
-                [33.27611, 45.362965, 33.23099, 34.436787, 36.571167],
-                [33.29176, 45.027763, 34.02678, 35.329945, 36.35523],
-                [33.95818, 44.993164, 34.119263, 34.288776, 35.93025],
-                [34.140266, 45.39091, 33.197502, 34.189434, 35.96681],
+                [33.159134, 44.89513, 33.894135, 35.1973, 36.2197],
+                [34.903515, 45.169323, 34.188465, 34.95029, 34.81385],
+                [34.266838, 45.30183, 34.427937, 34.59744, 36.227085],
+                [33.16512, 45.08286, 35.00004, 33.66843, 35.56141],
+                [34.143913, 45.394566, 33.20116, 34.19309, 35.91248],
             ]
         )
 
         cc = np.array(
             [
-                "2023-02-04T15:05:23.49998",
-                "2023-02-04T15:05:53.49998",
-                "2023-02-04T15:06:23.49998",
-                "2023-02-04T15:06:53.49998",
-                "2023-02-04T15:07:23.49998",
+                "2023-02-04T15:05:23.499983072",
+                "2023-02-04T15:05:53.499983072",
+                "2023-02-04T15:06:23.499983072",
+                "2023-02-04T15:06:53.499983072",
+                "2023-02-04T15:07:23.499983072",
             ],
             dtype="datetime64[ns]",
         )
         cd_spsdl_avg = np.array(
             [
-                [62.4551, 59.374382, 58.97122, 61.07321, 59.783104],
-                [61.14534, 58.064617, 57.62369, 59.71631, 59.29018],
-                [62.43891, 59.358192, 59.07586, 61.207146, 60.29722],
-                [61.163094, 58.08237, 59.036198, 61.416603, 60.38328],
-                [62.242744, 59.162025, 57.95079, 59.82794, 58.536304],
+                [62.115547, 59.03482, 58.580532, 60.669807, 59.47111],
+                [61.637085, 58.556362, 57.79539, 59.804375, 58.961555],
+                [62.613922, 59.5332, 59.79988, 62.052376, 61.0739],
+                [61.275757, 58.195038, 58.81557, 61.13693, 59.859146],
+                [61.34059, 58.25987, 57.532692, 59.550877, 58.448174],
             ]
         )
         cd_spsdl_sum = np.array(
             [
-                [77.22632, 74.14559, 73.74243, 75.84442, 74.55432],
-                [75.91655, 72.83583, 72.394905, 74.487526, 74.06139],
-                [77.21013, 74.1294, 73.84707, 75.97836, 75.06843],
-                [75.9343, 72.853584, 73.80741, 76.18781, 75.154495],
-                [77.01396, 73.93324, 72.72201, 74.59916, 73.30752],
+                [79.89706, 76.81634, 76.362045, 78.451324, 77.252625],
+                [79.418594, 76.337875, 75.576904, 77.58589, 76.74307],
+                [80.39543, 77.31471, 77.58139, 79.83389, 78.85541],
+                [79.057274, 75.976555, 76.59708, 78.91844, 77.640656],
+                [79.1221, 76.04138, 75.3142, 77.33239, 76.22969],
             ]
         )
 
diff --git a/mhkit/tests/acoustics/test_io.py b/mhkit/tests/acoustics/test_io.py
index 90ca1201d..62061c0c7 100644
--- a/mhkit/tests/acoustics/test_io.py
+++ b/mhkit/tests/acoustics/test_io.py
@@ -200,11 +200,11 @@ def test_calibration(self):
         # Check time coordinate
         cc = np.array(
             [
-                "2023-02-04T15:05:08.499983310",
-                "2023-02-04T15:05:09.499959707",
+                "2023-02-04T15:05:08.499983072",
+                "2023-02-04T15:05:08.999971389",
+                "2023-02-04T15:05:09.499959945",
+                "2023-02-04T15:05:09.999948263",
                 "2023-02-04T15:05:10.499936580",
-                "2023-02-04T15:05:11.499913454",
-                "2023-02-04T15:05:12.499890089",
             ],
             dtype="datetime64[ns]",
         )
@@ -212,46 +212,46 @@ def test_calibration(self):
         cd_spsd = np.array(
             [
                 [
-                    6.63068204e-02,
-                    3.81400273e-03,
-                    9.28277032e-04,
-                    3.86833846e-04,
-                    2.31924928e-05,
+                    7.04428102e-02,
+                    4.05186564e-03,
+                    9.86163910e-04,
+                    4.10977795e-04,
+                    2.46398082e-05,
                 ],
                 [
-                    1.32674948e-01,
-                    8.07329208e-03,
-                    3.35305424e-04,
-                    8.63341841e-05,
-                    3.23737989e-04,
+                    8.22255815e-02,
+                    5.62956783e-03,
+                    1.50523430e-03,
+                    5.62088860e-05,
+                    8.08846064e-05,
                 ],
                 [
-                    1.37353862e-02,
-                    1.03924150e-02,
-                    5.24537532e-03,
-                    1.18371618e-03,
-                    5.28236923e-05,
+                    1.25805956e-01,
+                    7.65523631e-03,
+                    3.17934716e-04,
+                    8.18645956e-05,
+                    3.06975506e-04,
                 ],
                 [
-                    2.70499444e-03,
-                    1.47833274e-04,
-                    2.46503548e-04,
-                    2.36905027e-04,
-                    1.92069973e-04,
+                    3.08283050e-02,
+                    1.12449483e-03,
+                    9.16890290e-04,
+                    5.18037680e-04,
+                    1.53328923e-04,
                 ],
                 [
-                    6.80966653e-03,
-                    2.33636493e-03,
-                    3.21849897e-04,
-                    9.13295549e-05,
-                    3.50420384e-05,
+                    1.24966808e-02,
+                    9.45535593e-03,
+                    4.77241430e-03,
+                    1.07700449e-03,
+                    4.80567438e-05,
                 ],
             ]
         )
 
         np.testing.assert_allclose(td_spsd.head().values, cd_spsd, atol=1e-6)
         np.testing.assert_allclose(
-            td_spsd["time"].head().astype("int64"), cc.astype("int64"), atol=1
+            td_spsd["time_psd"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
     def test_wispr(self):
diff --git a/mhkit/tests/acoustics/test_metrics.py b/mhkit/tests/acoustics/test_metrics.py
index 5c679acc5..9a59d8494 100644
--- a/mhkit/tests/acoustics/test_metrics.py
+++ b/mhkit/tests/acoustics/test_metrics.py
@@ -21,7 +21,7 @@ def setUpClass(self):
         P = acoustics.io.read_soundtrap(file_name, sensitivity=-177)
         self.spsd = acoustics.sound_pressure_spectral_density(P, P.fs, bin_length=1)
         self.spsd_60s = acoustics.sound_pressure_spectral_density(
-            P, P.fs, bin_length=60, rms=True
+            P, P.fs, bin_length=60
         )
 
     @classmethod
@@ -51,19 +51,19 @@ def test_spl(self):
             ],
             dtype="datetime64[ns]",
         )
-        cd_spl_head = np.array([98.12284, 98.639824, 97.62718, 97.85709, 96.98539])
-        cd_spl_tail = np.array([98.420975, 98.10879, 97.430115, 97.99395, 97.95798])
+        cd_spl_head = np.array([98.38563, 98.20744, 98.40893, 98.760826, 97.21689])
+        cd_spl_tail = np.array([97.29747, 97.51031, 98.302605, 98.08264, 97.961624])
 
         cd_spl10_freq_head = np.array(
             [10.0, 12.589254, 15.848932, 19.952623, 25.118864]
         )
         cd_spl10_head = np.array(
             [
-                [63.707756, 73.40367, 71.83326, 74.295204, 82.49378],
-                [61.048367, 68.54169, 63.2604, 71.18353, 82.87061],
-                [67.130325, 69.02487, 69.4047, 74.431915, 83.363075],
-                [66.81117, 68.42907, 65.77348, 71.172745, 75.995766],
-                [66.638435, 73.6602, 65.55014, 72.049995, 79.03914],
+                [63.97053, 73.666466, 72.09614, 74.55805, 82.75655],
+                [62.93203, 66.638306, 70.98349, 77.45272, 81.752464],
+                [60.817398, 68.31071, 63.029625, 70.95255, 82.63971],
+                [62.09812, 64.15272, 69.552284, 68.90529, 80.36065],
+                [66.71991, 68.61455, 68.994385, 74.02169, 82.95276],
             ]
         )
         cd_spl10_freq_tail = np.array(
@@ -71,21 +71,21 @@ def test_spl(self):
         )
         cd_spl10_tail = np.array(
             [
-                [82.50739, 80.50211, 80.871185, 83.187004, 82.15865],
-                [83.363846, 81.93087, 81.5197, 83.476814, 82.54627],
-                [83.13403, 81.25866, 81.41169, 83.52817, 82.50404],
-                [83.35105, 81.70449, 81.42432, 83.45459, 82.16487],
-                [83.0968, 80.904686, 81.39755, 83.36778, 82.327],
+                [83.001396, 81.12602, 81.27904, 83.39552, 82.37139],
+                [83.49641, 81.45716, 81.33536, 83.458916, 82.2894],
+                [83.659706, 82.013145, 81.73298, 83.76325, 82.473526],
+                [83.58633, 82.00813, 81.56679, 83.64441, 82.30002],
+                [83.10043, 80.908325, 81.40121, 83.37144, 82.33061],
             ]
         )
         cd_spl3_freq_head = np.array([10.079368, 12.699208, 16.0, 20.158737, 25.398417])
         cd_spl3_head = np.array(
             [
-                [63.88229, 73.85718, 71.21643, 75.30319, 82.05813],
-                [61.557175, 68.491905, 63.157738, 73.00873, 83.248314],
-                [67.5524, 68.75996, 69.92572, 74.80283, 84.11074],
-                [67.03263, 68.281166, 66.243065, 72.29833, 77.29135],
-                [67.13636, 73.57136, 65.761345, 73.54653, 79.427895],
+                [64.145065, 74.11997, 71.47932, 75.56602, 82.32091],
+                [63.103104, 66.557434, 71.07715, 77.72599, 81.811295],
+                [61.326202, 68.260925, 62.92696, 72.777756, 83.01741],
+                [62.4825, 63.912766, 69.58983, 69.38629, 80.71226],
+                [67.14199, 68.34964, 69.5154, 74.39259, 83.70042],
             ]
         )
         cd_spl3_freq_tail = np.array(
@@ -93,11 +93,11 @@ def test_spl(self):
         )
         cd_spl3_tail = np.array(
             [
-                [82.13845, 80.43939, 81.25442, 83.51936, 80.834045],
-                [83.07329, 81.89704, 81.748245, 83.87166, 81.16063],
-                [82.843, 81.24031, 81.632744, 83.92745, 81.09888],
-                [83.10067, 81.60538, 81.68111, 83.73491, 80.842834],
-                [82.74249, 80.793686, 81.695526, 83.699776, 81.01264],
+                [82.71037, 81.107666, 81.50009, 83.79481, 80.966225],
+                [83.16837, 81.403625, 81.59755, 83.72969, 80.989555],
+                [83.40933, 81.91403, 81.98976, 84.04357, 81.151474],
+                [83.374664, 81.88523, 81.79578, 83.965515, 80.91496],
+                [82.746124, 80.797325, 81.69917, 83.70343, 81.01623],
             ]
         )
 
@@ -108,7 +108,7 @@ def test_spl(self):
             td_spl.tail().values, cd_spl_tail, atol=1e-6, rtol=1e-6
         )
         np.testing.assert_allclose(
-            td_spl["time"].head().astype("int64"), cc.astype("int64"), atol=1
+            td_spl["time_psd"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
         np.testing.assert_allclose(
@@ -195,29 +195,29 @@ def test_sel(self):
 
         cc = np.array(
             [
-                "2023-02-04T15:05:37.999295949",
-                "2023-02-04T15:06:37.997894048",
-                "2023-02-04T15:07:37.996495485",
-                "2023-02-04T15:08:37.995094776",
-                "2023-02-04T15:09:37.993695497",
+                "2023-02-04T15:05:37.999294757",
+                "2023-02-04T15:06:07.998594760",
+                "2023-02-04T15:06:37.997895240",
+                "2023-02-04T15:07:07.997195243",
+                "2023-02-04T15:07:37.996495246",
             ],
             dtype="datetime64[ns]",
         )
-        cd_sel = np.array([116.18274, 121.698654, 143.28117, 147.37479, 127.01828])
-        cd_sel_lf = np.array([112.363075, 120.177086, 142.74931, 146.57983, 125.83696])
-        cd_sel_hf = np.array([112.22166, 118.88085, 139.94121, 144.33324, 124.328995])
-        cd_sel_vhf = np.array([110.23136, 114.00643, 133.20006, 139.13504, 118.88397])
-        cd_sel_pw = np.array([112.22191, 119.87286, 141.67467, 145.6534, 125.419975])
-        cd_sel_ow = np.array([110.945404, 118.06397, 139.08435, 143.51094, 123.68077])
-
-        np.testing.assert_allclose(td_sel.values, cd_sel, atol=1e-5)
-        np.testing.assert_allclose(td_sel_lf.values, cd_sel_lf, atol=1e-5)
-        np.testing.assert_allclose(td_sel_hf.values, cd_sel_hf, atol=1e-5)
-        np.testing.assert_allclose(td_sel_vhf.values, cd_sel_vhf, atol=1e-5)
-        np.testing.assert_allclose(td_sel_pw.values, cd_sel_pw, atol=1e-5)
-        np.testing.assert_allclose(td_sel_ow.values, cd_sel_ow, atol=1e-5)
+        cd_sel = np.array([116.081825, 117.38323, 120.408775, 127.583755, 143.19513])
+        cd_sel_lf = np.array([112.261665, 114.67835, 118.88702, 126.86423, 142.66327])
+        cd_sel_hf = np.array([112.121216, 114.001945, 117.59107, 124.69318, 139.85515])
+        cd_sel_vhf = np.array([110.1319, 110.81934, 112.71749, 118.208664, 133.114])
+        cd_sel_pw = np.array([112.120964, 114.46142, 118.58291, 126.152115, 141.58862])
+        cd_sel_ow = np.array([110.844246, 113.00219, 116.77398, 123.92641, 138.99828])
+
+        np.testing.assert_allclose(td_sel.head().values, cd_sel, atol=1e-5)
+        np.testing.assert_allclose(td_sel_lf.head().values, cd_sel_lf, atol=1e-5)
+        np.testing.assert_allclose(td_sel_hf.head().values, cd_sel_hf, atol=1e-5)
+        np.testing.assert_allclose(td_sel_vhf.head().values, cd_sel_vhf, atol=1e-5)
+        np.testing.assert_allclose(td_sel_pw.head().values, cd_sel_pw, atol=1e-5)
+        np.testing.assert_allclose(td_sel_ow.head().values, cd_sel_ow, atol=1e-5)
         np.testing.assert_allclose(
-            td_sel["time"].astype("int64"), cc.astype("int64"), atol=1
+            td_sel["time_psd"].head().astype("int64"), cc.astype("int64"), atol=1
         )
 
     def test_spl_vs_sel(self):
diff --git a/mhkit/tests/dolfyn/base.py b/mhkit/tests/dolfyn/base.py
index d03fbe8bf..eb6d6b281 100644
--- a/mhkit/tests/dolfyn/base.py
+++ b/mhkit/tests/dolfyn/base.py
@@ -23,7 +23,7 @@ def assert_allclose(dat0, dat1, *args, **kwargs):
     # For problematic time check
     names = []
     for v in dat0.variables:
-        if np.issubdtype(dat0[v].dtype, np.datetime64):
+        if v in dat1.variables and np.issubdtype(dat0[v].dtype, np.datetime64):
             dat0[v] = time.dt642epoch(dat0[v])
             dat1[v] = time.dt642epoch(dat1[v])
             names.append(v)
diff --git a/mhkit/tests/dolfyn/test_analysis.py b/mhkit/tests/dolfyn/test_analysis.py
index 62fabdaf0..0eda42533 100644
--- a/mhkit/tests/dolfyn/test_analysis.py
+++ b/mhkit/tests/dolfyn/test_analysis.py
@@ -65,11 +65,16 @@ def test_calc_func(self):
         test_ds["tke_vec_demean"] = c.turbulent_kinetic_energy(
             self.adv1.vel, detrend=False
         )
-        test_ds["psd"] = c.power_spectral_density(self.adv1.vel, freq_units="Hz")
+        test_ds["psd"] = c.power_spectral_density(
+            self.adv1.vel, freq_units="Hz", pct_overlap=0
+        )
 
         # Test ADCP single vector spectra, cross-spectra to test radians code
         test_ds_adp["psd_b5"] = c2.power_spectral_density(
-            self.adp.vel_b5.isel(range_b5=5), freq_units="rad", window="hamm"
+            self.adp.vel_b5.isel(range_b5=5),
+            freq_units="rad",
+            window="hamming",
+            pct_overlap=0,
         )
         test_ds_adp["tke_b5"] = c2.turbulent_kinetic_energy(self.adp.vel_b5)
 
@@ -81,25 +86,20 @@ def test_calc_func(self):
         assert_allclose(test_ds, load("vector_data01_func.nc"), atol=1e-6)
         assert_allclose(test_ds_adp, load("BenchFile01_func.nc"), atol=1e-6)
 
-    def test_fft_freq(self):
-        f = self.adv_tool._fft_freq(units="Hz")
-        omega = self.adv_tool._fft_freq(units="rad/s")
-
-        np.testing.assert_equal(f, np.arange(1, 17, 1, dtype="float"))
-        np.testing.assert_equal(omega, np.arange(1, 17, 1, dtype="float") * (2 * np.pi))
-
     def test_adv_turbulence(self):
         dat = tv.dat.copy(deep=True)
         bnr = avm.ADVBinner(n_bin=20.0, fs=dat.fs)
-        tdat = bnr(dat)
-        acov = bnr.autocovariance(dat["vel"])
-
-        assert_identical(tdat, avm.turbulence_statistics(dat, n_bin=20.0, fs=dat.fs))
+        tdat = bnr.bin_average(dat)
+        tdat["psd"] = bnr.power_spectral_density(
+            dat["vel"],
+            freq_units="rad",
+            window="hann",
+        )
 
         tdat["stress_detrend"] = bnr.reynolds_stress(dat["vel"])
         tdat["stress_demean"] = bnr.reynolds_stress(dat["vel"], detrend=False)
         tdat["csd"] = bnr.cross_spectral_density(
-            dat["vel"], freq_units="rad", window="hamm", n_fft_coh=10
+            dat["vel"], freq_units="rad", window="hann", n_fft_coh=10
         )
         tdat["LT83"] = bnr.dissipation_rate_LT83(tdat["psd"], tdat.velds.U_mag)
         tdat["noise"] = bnr.doppler_noise_level(tdat["psd"], pct_fN=0.8)
@@ -107,13 +107,16 @@ def test_adv_turbulence(self):
             tdat["psd"], tdat.velds.U_mag, noise=tdat["noise"]
         )
         tdat["SF"] = bnr.dissipation_rate_SF(dat["vel"][0], tdat.velds.U_mag)
+        tdat["stress_vec"] = bnr.reynolds_stress(dat["vel"])
+        tdat["tke_vec"] = bnr.turbulent_kinetic_energy(dat["vel"], noise=tdat["noise"])
         tdat["TE01"] = bnr.dissipation_rate_TE01(dat, tdat)
+        acov = bnr.autocovariance(dat["vel"])
         tdat["L"] = bnr.integral_length_scales(acov, tdat.velds.U_mag)
         slope_check = bnr.check_turbulence_cascade_slope(
-            tdat["psd"][-1].mean("time"), freq_range=[10, 100]
+            tdat["psd"][-1].mean("time_psd"), freq_range=[10, 100]
         )
         tdat["psd_noise"] = bnr.power_spectral_density(
-            dat["vel"], freq_units="rad", noise=[0.06, 0.04, 0.01]
+            dat["vel"], freq_units="rad", noise=[0.06, 0.04, 0.01], pct_overlap=0
         )
 
         if make_data:
@@ -143,12 +146,14 @@ def test_adcp_turbulence(self):
         dat.velds.rotate2("beam")
 
         tdat["psd"] = bnr.power_spectral_density(
-            dat["vel_b5"].isel(range_b5=len(dat["range_b5"]) // 2), freq_units="Hz"
+            dat["vel_b5"].isel(range_b5=len(dat["range_b5"]) // 2),
+            freq_units="Hz",
+            pct_overlap=0,
         )
         tdat["noise"] = bnr.doppler_noise_level(tdat["psd"], pct_fN=0.8)
         tdat["stress_vec4"] = bnr.reynolds_stress_4beam(
             dat, noise=tdat["noise"], orientation="up", beam_angle=25
-        )
+        )  # upvp is always nan here
         tdat["tke_vec5"], tdat["stress_vec5"] = bnr.stress_tensor_5beam(
             dat, noise=tdat["noise"], orientation="up", beam_angle=25, tke_only=False
         )
@@ -179,14 +184,16 @@ def test_adcp_turbulence(self):
         ) = bnr.dissipation_rate_SF(dat["vel"].isel(dir=2), r_range=[1, 5])
 
         slope_check = bnr.check_turbulence_cascade_slope(
-            tdat["psd"].mean("time_b5"), freq_range=[0.4, 4]
+            tdat["psd"].mean("time_psd"), freq_range=[0.4, 4]
         )
         # Check noise subtraction in psd function
-        tdat["psd_noise"] = bnr.power_spectral_density(
+        psd_noise = bnr.power_spectral_density(
             dat["vel_b5"].isel(range_b5=len(dat["range_b5"]) // 2),
             freq_units="Hz",
-            noise=0.01,
+            noise=0.0001,
+            pct_overlap=0.5,
         )
+        tdat["psd_noise"] = psd_noise.rename({"time_psd": "time_psd_50pct"})
         tdat["friction_vel"] = bnr.friction_velocity(
             tdat, upwp_=tdat["stress_vec5"].sel(tau="upwp_"), z_inds=slice(1, 5), H=50
         )
diff --git a/mhkit/tests/dolfyn/test_shortcuts.py b/mhkit/tests/dolfyn/test_shortcuts.py
index 948736603..2b7b37868 100644
--- a/mhkit/tests/dolfyn/test_shortcuts.py
+++ b/mhkit/tests/dolfyn/test_shortcuts.py
@@ -15,7 +15,10 @@ class analysis_testcase(unittest.TestCase):
     def setUpClass(self):
         dat = tv.dat.copy(deep=True)
         self.dat = rotate2(dat, "earth", inplace=False)
-        self.tdat = avm.turbulence_statistics(self.dat, n_bin=20.0, fs=self.dat.fs)
+        bnr = avm.ADVBinner(n_bin=20.0, fs=dat.fs)
+        self.tdat = bnr.bin_average(self.dat)
+        self.tdat["tke_vec"] = bnr.turbulent_kinetic_energy(self.dat["vel"])
+        self.tdat["stress_vec"] = bnr.reynolds_stress(self.dat["vel"])
 
         short = xr.Dataset()
         short["u"] = self.tdat.velds.u
diff --git a/mhkit/tests/dolfyn/test_tools.py b/mhkit/tests/dolfyn/test_tools.py
index 6abfe5e3d..44ebf9a06 100644
--- a/mhkit/tests/dolfyn/test_tools.py
+++ b/mhkit/tests/dolfyn/test_tools.py
@@ -15,12 +15,12 @@ def tearDownClass(self):
         pass
 
     def test_detrend_array(self):
-        d = tools.misc.detrend_array(self.array)
+        d = tools.detrend_array(self.array)
         assert_allclose(d, np.zeros(10), atol=1e-10)
 
     def test_group(self):
         array = np.concatenate((self.array, self.array))
-        d = tools.misc.group(array)
+        d = tools.group(array)
 
         out = np.array([slice(1, 20, None)], dtype=object)
         assert_equal(d, out)
@@ -35,7 +35,7 @@ def test_slice(self):
         )
         out = np.zeros((3, 3, 3))
         slices = list()
-        for slc in tools.misc.slice1d_along_axis((3, 3, 3), axis=-1):
+        for slc in tools.slice1d_along_axis((3, 3, 3), axis=-1):
             slices.append(slc)
             out[slc] = tensor[slc]
 
@@ -56,8 +56,8 @@ def test_slice(self):
 
     def test_fillgaps(self):
         arr = np.concatenate((self.array, self.nan, self.array))
-        d1 = tools.misc.fillgaps(arr.copy())
-        d2 = tools.misc.fillgaps(arr.copy(), maxgap=1)
+        d1 = tools.fillgaps(arr.copy())
+        d2 = tools.fillgaps(arr.copy(), maxgap=1)
 
         out1 = np.array(
             [
@@ -121,8 +121,8 @@ def test_interpgaps(self):
         arr = np.concatenate((self.array, self.nan, self.array, self.nan))
 
         t = np.arange(0, arr.shape[0], 0.1)
-        d1 = tools.misc.interpgaps(arr.copy(), t, extrapFlg=True)
-        d2 = tools.misc.interpgaps(arr.copy(), t, maxgap=1)
+        d1 = tools.interpgaps(arr.copy(), t, extrapFlg=True)
+        d2 = tools.interpgaps(arr.copy(), t, maxgap=1)
 
         out1 = np.array(
             [
@@ -192,7 +192,7 @@ def test_medfiltnan(self):
         arr = np.concatenate((self.array, self.nan, self.array))
         a = np.concatenate((arr[None, :], arr[None, :]), axis=0)
 
-        d = tools.misc.medfiltnan(a, [1, 5], thresh=3)
+        d = tools.medfiltnan(a, [1, 5], thresh=3)
 
         out = np.array(
             [
@@ -252,80 +252,12 @@ def test_medfiltnan(self):
         assert_allclose(d, out, atol=1e-10)
 
     def test_deg_conv(self):
-        d = tools.misc.convert_degrees(self.array)
+        d = tools.convert_degrees(self.array)
 
         out = np.array([90.0, 89.0, 88.0, 87.0, 86.0, 85.0, 84.0, 83.0, 82.0, 81.0])
 
         assert_allclose(d, out, atol=1e-10)
 
-    def test_fft_frequency(self):
-        fs = 1000  # Sampling frequency
-        nfft = 512  # Number of samples in a window
-
-        # Test for full frequency range
-        freq_full = tools.fft.fft_frequency(nfft, fs, full=True)
-        assert_equal(len(freq_full), nfft)
-
-        # Check symmetry of positive and negative frequencies, ignoring the zero frequency
-        positive_freqs = freq_full[1 : int(nfft / 2)]
-        negative_freqs = freq_full[int(nfft / 2) + 1 :]
-        assert_allclose(positive_freqs, -negative_freqs[::-1])
-
-    def test_stepsize(self):
-        # Case 1: l < nfft
-        step, nens, nfft = tools.fft._stepsize(100, 200)
-        assert_equal((step, nens, nfft), (0, 1, 100))
-
-        # Case 2: l == nfft
-        step, nens, nfft = tools.fft._stepsize(200, 200)
-        assert_equal((step, nens, nfft), (0, 1, 200))
-
-        # Case 3: l > nfft, no nens
-        step, nens, nfft = tools.fft._stepsize(300, 100)
-        expected_nens = int(2.0 * 300 / 100)
-        expected_step = int((300 - 100) / (expected_nens - 1))
-        assert_equal((step, nens, nfft), (expected_step, expected_nens, 100))
-
-        # Case 4: l > nfft, with nens
-        step, nens, nfft = tools.fft._stepsize(300, 100, nens=5)
-        expected_step = int((300 - 100) / (5 - 1))
-        assert_equal((step, nens, nfft), (expected_step, 5, 100))
-
-        # Case 5: l > nfft, with step
-        step, nens, nfft = tools.fft._stepsize(300, 100, step=50)
-        expected_nens = int((300 - 100) / 50 + 1)
-        assert_equal((step, nens, nfft), (50, expected_nens, 100))
-
-        # Case 6: nens is 1
-        step, nens, nfft = tools.fft._stepsize(300, 100, nens=1)
-        assert_equal((step, nens, nfft), (0, 1, 100))
-
-    def test_cpsd_quasisync_1D(self):
-        fs = 1000  # Sample rate
-        nfft = 512  # Number of points in the fft
-
-        # Test with signals of same length
-        a = np.random.normal(0, 1, 1000)
-        b = np.random.normal(0, 1, 1000)
-        cpsd = tools.fft.cpsd_quasisync_1D(a, b, nfft, fs)
-        self.assertEqual(cpsd.shape, (nfft // 2,))
-
-        # Test with signals of different lengths
-        a = np.random.normal(0, 1, 1500)
-        b = np.random.normal(0, 1, 1000)
-        cpsd = tools.fft.cpsd_quasisync_1D(a, b, nfft, fs)
-        self.assertEqual(cpsd.shape, (nfft // 2,))
-
-        # Test with different window types
-        for window in [None, 1, "hann"]:
-            cpsd = tools.fft.cpsd_quasisync_1D(a, b, nfft, fs, window=window)
-            self.assertEqual(cpsd.shape, (nfft // 2,))
-
-        # Test with a custom window
-        custom_window = np.hamming(nfft)
-        cpsd = tools.fft.cpsd_quasisync_1D(a, b, nfft, fs, window=custom_window)
-        self.assertEqual(cpsd.shape, (nfft // 2,))
-
 
 if __name__ == "__main__":
     unittest.main()

From 80671f0e0be44b71d243b317f79d73f13758c7a4 Mon Sep 17 00:00:00 2001
From: Andrew Simms <andrew.simms@nlr.gov>
Date: Wed, 8 Jul 2026 15:19:51 -0600
Subject: [PATCH 9/9] Release: Prepare MHKiT-Python v1.1.0 (#449)

# MHKiT-Python v1.1.0

## Additions

* Acoustics: Add millicdecade and WISPR instrument support
  * Added millidecade spectral conversion
  * Added a WISPR hydrophone reader
  * Added a voltage-based `export_audio` resampling option
  * Refactored band-averaging to avoid losing information at frequency-band boundaries
  * #447
  * Author: @jmcvey3
  * Reviewer: @simmsa
* DOLfYN: Add [Nortek Aquadopp](https://www.nortekgroup.com/oceanography/aquadopp-series) ADCP support
  * Added DOLfYN support for reading Aquadopp instruments
  * Cleaned Nortek parsing code
  * Simplified handling of the non-cabled ADV orientation flag
  * #434
  * Author: @jmcvey3
  * Reviewer: @akeeste
* Examples: Add ADCP waves example: `example/adcp_waves_example.ipynb`
  * Added an example notebook showing how to ingest and analyze wave measurements from a dual-profile Nortek Signature 250 deployment at PacWave.
  * #430
  * Author: @jmcvey3
  * Reviewer: @akeeste

## Improvements

### Acoustics

- Improved flexibility and robustness of the Acoustics module
  - Added a configurable FFT length for sound pressure PSDs
  - Renamed bin/windowing attributes for clarity
  - Fixed an incorrectly signed gain correction
  - #433
  - Author: @jmcvey3
  - Reviewer: @akeeste

### DOLfYN

- Refactored PSD calculations to use `scipy.signal.welch`
  - Replaced DOLfYN's custom Welch-like PSD implementation (built each segment from bin slices, could not overlap FFT segments) with `scipy.signal.welch`
  - Removed the bin-based segment structure and added a `step` argument to control overlap
  - Dropped float32 casts in some functions in favor of float64
  - Removed `fft.py` and renamed `tools/misc.py` to `tools.py`
  - Breaking Changes:
    - NaNs are no longer tolerated in PSD calculations
    - DOLfYN defaults to 0% overlap to preserve existing array shapes
    - Acoustics defaults to 50% overlap
    - PSD output time dimension renamed to `time_psd`
  - #452
  - Author: @jmcvey3
  - Reviewer: @akeeste, @simmsa
- Improved handling of "averaged" profiles
  - Fixed handling of Nortek Signature dual-profile ADCP data by defaulting to "_avg" velocity variables when untagged ones are absent.
  - #430
  - Author: @jmcvey3
  - Reviewer: @akeeste
- Critical PSD bugfix
  - Fixed a bug where individual FFTs received a 50% overlap twice, which corrupted the first and last spectrum of a timeseries.
  - #430
  - Author: @jmcvey3
  - Reviewer: @akeeste

### Examples

- Added histograms to ADCP example
  - #448
  - Author: @browniea
  - Reviewer: @akeeste


### River/IO

- Fixed Qhull interpolation and D3D coordinate-system errors
  - #448
  - Author: @browniea
  - Reviewer: @akeeste
  - Fixes: #442, #444
- Delft3D module updates
  - Added new Delft3D coordinate names
  - Added a new grid-convergence-index calculation function
  - Added support for xarray/netCDF4 input in the D3D module
  - #428
  - Author: @browniea
  - Reviewer: @akeeste

### Wave

- NDBC Directional Wave Units
  - Fixed NDBC directional wave spectrum output to return degrees instead of radians
  - Updated polar plots so 0 deg is at the top and increases clockwise
  - #437
  - Author: @jmcvey3
  - Reviewer: @akeeste
  - Fixes: #427

### Wave/Hindcast

- Added a `hindcast_guard` exception-handling decorator (`hindcast_exceptions.py`) that surfaces a clear error on HSDS request failures, distinguishing the known NLR HSDS outage (#450) from other failures
  - #449
  - Author: @simmsa
  - Reviewer: @akeeste

## Maintenance

- Added Python 3.13 support
  - #445
  - Author: @simmsa
  - Reviewer: @akeeste
  - Fixes: #441
- Added [pandas 3](https://pandas.pydata.org/community/blog/pandas-3.0.html) Support
  - Updated the pandas dependency to allow pandas 3.x
  - Added a compatibility shim for NDBC missing-value handling related to pandas 3 object to String dtype api changes
  - Fixed a deprecated period alias in tests
  - #443
  - Author: @simmsa
  - Reviewer: @akeeste
  - Fixes: #440
- Updated GitHub Actions CI, expanded installation/developer documentation, refreshed dev environment, and trimmed dependencies
  - Refactored optional dependencies
  - Standardized conda/conda-forge environment builds
  - Scoped black linting to changed files
  - #436
  - Author: @simmsa
  - Reviewer: @akeeste
- Update `rex` dependency to target pypi package to [`NLR-rex[hsds]>=0.5.0`](https://pypi.org/project/NLR-rex/)
  - #449
  - Author: @simmsa
  - Reviewer: @akeeste
---
 .github/actions/upload-coverage/action.yml    | 32 +++++++
 .github/workflows/main.yml                    | 64 +++++++++----
 .hscfg                                        |  2 +-
 environment-dev.yml                           |  7 +-
 examples/WPTO_hindcast_example.ipynb          |  4 +-
 examples/metocean_example.ipynb               |  8 +-
 mhkit/__init__.py                             |  2 +-
 mhkit/tests/tidal/test_io.py                  | 16 +++-
 mhkit/tests/wave/io/hindcast/test_hindcast.py |  7 +-
 .../wave/io/hindcast/test_wind_toolkit.py     |  9 +-
 mhkit/wave/io/hindcast/hindcast.py            |  4 +
 mhkit/wave/io/hindcast/hindcast_exceptions.py | 92 +++++++++++++++++++
 mhkit/wave/io/hindcast/wind_toolkit.py        | 10 +-
 pyproject.toml                                |  2 +-
 14 files changed, 226 insertions(+), 33 deletions(-)
 create mode 100644 .github/actions/upload-coverage/action.yml
 create mode 100644 mhkit/wave/io/hindcast/hindcast_exceptions.py

diff --git a/.github/actions/upload-coverage/action.yml b/.github/actions/upload-coverage/action.yml
new file mode 100644
index 000000000..b7083d0b9
--- /dev/null
+++ b/.github/actions/upload-coverage/action.yml
@@ -0,0 +1,32 @@
+name: Upload coverage to Coveralls
+description: Install the macOS reporter if needed and upload lcov coverage to Coveralls.
+
+inputs:
+  github-token:
+    description: Token used to authenticate with Coveralls.
+    required: true
+  flag-name:
+    description: Unique flag identifying this coverage job.
+    required: true
+  fail-on-error:
+    description: Whether an upload failure should fail the job.
+    required: false
+    default: "true"
+
+runs:
+  using: composite
+  steps:
+    # Fix for coveralls on homebrew 6+: https://github.com/coverallsapp/github-action/pull/265
+    - name: Install coveralls reporter (macOS)
+      if: runner.os == 'macOS'
+      shell: bash
+      run: brew install coverallsapp/coveralls/coveralls --quiet
+
+    - name: Upload coverage data to coveralls.io
+      uses: coverallsapp/github-action@v2
+      with:
+        github-token: ${{ inputs.github-token }}
+        flag-name: ${{ inputs.flag-name }}
+        parallel: true
+        path-to-lcov: ./coverage.lcov
+        fail-on-error: ${{ inputs.fail-on-error }}
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 7ca82b44d..20896457f 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -22,6 +22,7 @@ env:
   CONDA_ENVIRONMENT_NAME: mhkit-dev-env
   # Coveralls: Set to false to ignore upload failures during outages.
   #   Check status: https://status.coveralls.io/
+  # Note this only affects the code coverage percentage badge in the README, nothing else
   COVERALLS_FAIL_ON_ERROR: true
 
 jobs:
@@ -39,10 +40,35 @@ jobs:
           if [[ "${{ github.event_name }}" == "pull_request" && "${{ github.base_ref }}" == "develop" ]]; then
             echo "matrix_os=[ \"ubuntu-latest\"]" >> $GITHUB_OUTPUT
           else
-            echo "matrix_os=[\"windows-latest\", \"ubuntu-latest\", \"macos-latest\"]" >> $GITHUB_OUTPUT
+            echo "matrix_os=[\"windows-latest\", \"ubuntu-latest\", \"macos-26\"]" >> $GITHUB_OUTPUT
           fi
 
 
+  # `coveralls-gate` controls whether code coverage data is uploaded to coveralls.
+  # The README code coverage badge is main-only. Because this is a simple metric we don't need to
+  # calculate this for every code push, just the ones that can change the badge coverage percentage
+  #
+  # Specific code changes that are relevant to the coverage badge are:
+  #     * a PR targeting main
+  #     * a push to main
+  # Coveralls badge:
+  #   <img src="https://github.com/MHKiT-Software/MHKiT-Python/actions/workflows/main.yml/badge.svg">
+  coveralls-gate:
+    runs-on: ubuntu-latest
+    outputs:
+      should-upload: ${{ steps.gate.outputs.should-upload }}
+    steps:
+      - id: gate
+        run: |
+          should_upload=false
+          if [[ "${{ github.event_name }}" == "pull_request" && "${{ github.base_ref }}" == "main" ]]; then
+            should_upload=true
+          fi
+          if [[ "${{ github.event_name }}" == "push" && "${{ github.ref }}" == "refs/heads/main" ]]; then
+            should_upload=true
+          fi
+          echo "should-upload=$should_upload" >> "$GITHUB_OUTPUT"
+
   # This job decides if the hindcast test suite should run.
   check-changes:
     runs-on: ubuntu-latest
@@ -64,11 +90,15 @@ jobs:
 
       - id: hindcast-logic
         run: |
-          if [[ "${{ github.event.pull_request.base.ref }}" == "main" || "${{ steps.changes.outputs.wave_io_hindcast }}" == "true" ]]; then
-            echo "should-run-hindcast=true" >> "$GITHUB_OUTPUT"
-          else
-            echo "should-run-hindcast=false" >> "$GITHUB_OUTPUT"
-          fi
+          # TODO(restore-hindcast): NLR HSDS endpoint is down for v1.1, so hindcast
+          # jobs are disabled. Restore the logic below when the service is back online.
+          # See https://github.com/MHKiT-Software/MHKiT-Python/issues/450
+          echo "should-run-hindcast=false" >> "$GITHUB_OUTPUT"
+          # if [[ "${{ github.event.pull_request.base.ref }}" == "main" || "${{ steps.changes.outputs.wave_io_hindcast }}" == "true" ]]; then
+          #   echo "should-run-hindcast=true" >> "$GITHUB_OUTPUT"
+          # else
+          #   echo "should-run-hindcast=false" >> "$GITHUB_OUTPUT"
+          # fi
 
   prepare-nonhindcast-cache:
     runs-on: ubuntu-latest
@@ -201,7 +231,7 @@ jobs:
 
   conda-forge-build:
     name: conda-forge-${{ matrix.os }}/${{ matrix.python-version }}
-    needs: [set-os, prepare-nonhindcast-cache]
+    needs: [set-os, prepare-nonhindcast-cache, coveralls-gate]
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
@@ -249,17 +279,16 @@ jobs:
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@v2
+        if: needs.coveralls-gate.outputs.should-upload == 'true'
+        uses: ./.github/actions/upload-coverage
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: conda-forge-${{ runner.os }}-py${{ matrix.python-version }}
-          parallel: true
-          path-to-lcov: ./coverage.lcov
           fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   pip-build:
     name: pip-${{ matrix.os }}/${{ matrix.python-version }}
-    needs: [set-os, prepare-nonhindcast-cache]
+    needs: [set-os, prepare-nonhindcast-cache, coveralls-gate]
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
@@ -310,12 +339,11 @@ jobs:
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@v2
+        if: needs.coveralls-gate.outputs.should-upload == 'true'
+        uses: ./.github/actions/upload-coverage
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: pip-${{ runner.os }}-py${{ matrix.python-version }}
-          parallel: true
-          path-to-lcov: ./coverage.lcov
           fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   hindcast-calls:
@@ -326,6 +354,7 @@ jobs:
         prepare-wave-hindcast-cache,
         prepare-wind-hindcast-cache,
         set-os,
+        coveralls-gate,
       ]
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
 
@@ -388,12 +417,11 @@ jobs:
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@v2
+        if: needs.coveralls-gate.outputs.should-upload == 'true'
+        uses: ./.github/actions/upload-coverage
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: hindcast-${{ runner.os }}-py${{ matrix.python-version }}
-          parallel: true
-          path-to-lcov: ./coverage.lcov
           fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   test-wheel-packaging:
@@ -636,9 +664,11 @@ jobs:
         conda-forge-build,
         pip-build,
         hindcast-calls,
+        coveralls-gate,
       ]
     if: |
       always() &&
+      needs.coveralls-gate.outputs.should-upload == 'true' &&
       (
         (
           needs.conda-forge-build.result == 'success' &&
diff --git a/.hscfg b/.hscfg
index f9aa99caa..c280dc421 100644
--- a/.hscfg
+++ b/.hscfg
@@ -1,4 +1,4 @@
-hs_endpoint = https://developer.nrel.gov/api/hsds
+hs_endpoint = https://developer.nlr.gov/api/hsds
 hs_username =
 hs_password =
 hs_api_key = jODGciIBnejrYd9GXxgXjbbAjMDLBMWQer05P98N 
diff --git a/environment-dev.yml b/environment-dev.yml
index e624a7286..455c8eaeb 100644
--- a/environment-dev.yml
+++ b/environment-dev.yml
@@ -26,5 +26,10 @@ dependencies:
   - notebook
   - matplotlib>=3.9.1
   - fatpack
-  - nrel-rex
   - cartopy
+  # rex is installed from PyPI (NLR-rex), not conda-forge. The conda-forge
+  # `nrel-rex` is frozen at 0.2.84, which predates the s3:// fsspec support
+  # needed to read the wave hindcast .h5 files directly from S3. The [hsds] extra
+  # pulls the HSDS client dependencies the hindcast reads use.
+  - pip:
+      - NLR-rex[hsds]>=0.5.0
diff --git a/examples/WPTO_hindcast_example.ipynb b/examples/WPTO_hindcast_example.ipynb
index 1f251b7a9..3a6fe3faf 100644
--- a/examples/WPTO_hindcast_example.ipynb
+++ b/examples/WPTO_hindcast_example.ipynb
@@ -51,7 +51,7 @@
         "\n",
         "### Setting up Access to WPTO Hindcast Data\n",
         "To access the WPTO hindcast data, you will need to configure h5pyd for data access on HSDS. \n",
-        "        To get your own API key, visit https://developer.nrel.gov/signup/. \n",
+        "        To get your own API key, visit https://developer.nlr.gov/signup/. \n",
         "\n",
         "To configure h5phd type:\n",
         "\n",
@@ -59,7 +59,7 @@
         "        \n",
         "and enter at the prompt:\n",
         "\n",
-        "    hs_endpoint = https://developer.nrel.gov/api/hsds\n",
+        "    hs_endpoint = https://developer.nlr.gov/api/hsds\n",
         "    hs_username = None\n",
         "    hs_password = None\n",
         "    hs_api_key = {your key}\n",
diff --git a/examples/metocean_example.ipynb b/examples/metocean_example.ipynb
index 4f4540ab8..06098aeb2 100644
--- a/examples/metocean_example.ipynb
+++ b/examples/metocean_example.ipynb
@@ -567,7 +567,7 @@
       "source": [
         "## 2. Request Surface Wind Data from WIND Toolkit\n",
         "\n",
-        "MHKiT can be used to request historical data from [WIND Toolkit](https://www.nrel.gov/grid/wind-toolkit.html). The WIND Toolkit is a high-spatial-resolution dataset of meteorological parameters covering several offshore regions including California, Hawaii, the Northwest Pacific, and the Mid-Atlantic. The offshore datasets span 2000-2019 (or to 2020 for the Mid-Atlantic region). \n",
+        "MHKiT can be used to request historical data from [WIND Toolkit](https://www.nlr.gov/grid/wind-toolkit). The WIND Toolkit is a high-spatial-resolution dataset of meteorological parameters covering several offshore regions including California, Hawaii, the Northwest Pacific, and the Mid-Atlantic. The offshore datasets span 2000-2019 (or to 2020 for the Mid-Atlantic region). \n",
         "\n",
         "\n",
         "### Included Variables: \n",
@@ -588,7 +588,7 @@
         "\n",
         "### Setting up Access to WIND Toolkit\n",
         "To access the WIND Toolkit, you will need to configure h5pyd for data access on HSDS. \n",
-        "To get your own API key, visit https://developer.nrel.gov/signup/. \n",
+        "To get your own API key, visit https://developer.nlr.gov/signup/. \n",
         "If you have already accessed WPTO Hindcast data, you may skip this step.\n",
         "\n",
         "To configure h5pyd type:\n",
@@ -597,7 +597,7 @@
         "        \n",
         "and enter at the prompt:\n",
         "\n",
-        "    hs_endpoint = https://developer.nrel.gov/api/hsds\n",
+        "    hs_endpoint = https://developer.nlr.gov/api/hsds\n",
         "    hs_username = None\n",
         "    hs_password = None\n",
         "    hs_api_key = {your key}\n",
@@ -615,7 +615,7 @@
         "* location\n",
         "* year\n",
         "\n",
-        "A full list of available historical parameters can be found [here](https://github.com/NREL/hsds-examples/blob/master/datasets/WINDToolkit.md#model).  Here we are interested in historical surface wind data (`'windspeed_10m'`, `'winddirection_10m'`) and a vertical temperature profile. For demonstration purposes, not all temperature elevations will be used. Additionally, we will use the latitude and longitude of NDBC buoy `'46022'` to later compare to the NDBC dataset. The buoy location can be found [here](https://www.ndbc.noaa.gov/data/stations/station_table.txt). The `elevation_to_string` can be used to easily combine an array of elevations with a parameter name to create the correctly formatted parameter string. This is demonstrated for the array of temperature parameters."
+        "A full list of available historical parameters can be found [here](https://github.com/NatLabRockies/hsds-examples/blob/master/datasets/WINDToolkit.md#model).  Here we are interested in historical surface wind data (`'windspeed_10m'`, `'winddirection_10m'`) and a vertical temperature profile. For demonstration purposes, not all temperature elevations will be used. Additionally, we will use the latitude and longitude of NDBC buoy `'46022'` to later compare to the NDBC dataset. The buoy location can be found [here](https://www.ndbc.noaa.gov/data/stations/station_table.txt). The `elevation_to_string` can be used to easily combine an array of elevations with a parameter name to create the correctly formatted parameter string. This is demonstrated for the array of temperature parameters."
       ]
     },
     {
diff --git a/mhkit/__init__.py b/mhkit/__init__.py
index 6f9eefeec..0d248d505 100644
--- a/mhkit/__init__.py
+++ b/mhkit/__init__.py
@@ -11,7 +11,7 @@
 
 configure_warnings()
 
-__version__ = "v1.0.1"
+__version__ = "v1.1.0"
 
 __copyright__ = """
 Copyright 2019, Alliance for Energy Innovation, LLC under the terms of 
diff --git a/mhkit/tests/tidal/test_io.py b/mhkit/tests/tidal/test_io.py
index be34cd444..a97c78c37 100644
--- a/mhkit/tests/tidal/test_io.py
+++ b/mhkit/tests/tidal/test_io.py
@@ -21,7 +21,6 @@
 import numpy as np
 import mhkit.tidal as tidal
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -68,6 +67,11 @@ def test_load_noaa_data_xarray(self):
         self.assertEqual(len(data["index"]), 18890)
         self.assertEqual(data.attrs["id"], "s08010")
 
+    # TODO(noaa_api_failures): NOAA Tides and Currents API intermittently
+    # returns 504 Gateway Timeout, causing this test to fail in CI. Re-enable
+    # once the upstream API is reliable. See
+    # https://github.com/MHKiT-Software/MHKiT-Python/issues/451
+    # @unittest.skip("NOAA API intermittently unavailable; see issue #451")
     def test_request_noaa_data_basic(self):
         """
         Test the request_noaa_data function with basic input parameters
@@ -89,6 +93,11 @@ def test_request_noaa_data_basic(self):
         self.assertEqual(data.shape, (183, 3))
         self.assertEqual(metadata["id"], "s08010")
 
+    # TODO(noaa_api_failures): NOAA Tides and Currents API intermittently
+    # returns 504 Gateway Timeout, causing this test to fail in CI. Re-enable
+    # once the upstream API is reliable. See
+    # https://github.com/MHKiT-Software/MHKiT-Python/issues/451
+    # @unittest.skip("NOAA API intermittently unavailable; see issue #451")
     def test_request_noaa_data_basic_xarray(self):
         """
         Test the request_noaa_data function with basic input parameters
@@ -116,6 +125,11 @@ def test_request_noaa_data_basic_xarray(self):
         self.assertEqual(len(data["index"]), 183)
         self.assertEqual(data.attrs["id"], "s08010")
 
+    # TODO(noaa_api_failures): NOAA Tides and Currents API intermittently
+    # returns 504 Gateway Timeout, causing this test to fail in CI. Re-enable
+    # once the upstream API is reliable. See
+    # https://github.com/MHKiT-Software/MHKiT-Python/issues/451
+    # @unittest.skip("NOAA API intermittently unavailable; see issue #451")
     def test_request_noaa_data_write_json(self):
         """
         Test the request_noaa_data function with the write_json parameter
diff --git a/mhkit/tests/wave/io/hindcast/test_hindcast.py b/mhkit/tests/wave/io/hindcast/test_hindcast.py
index 456ea05b7..44cbc1aed 100644
--- a/mhkit/tests/wave/io/hindcast/test_hindcast.py
+++ b/mhkit/tests/wave/io/hindcast/test_hindcast.py
@@ -26,7 +26,6 @@
 import unittest
 from os.path import abspath, dirname, join, normpath
 from pandas.testing import assert_frame_equal
-import xarray.testing as xrt
 import pandas as pd
 import mhkit.wave as wave
 import xarray as xr
@@ -37,6 +36,12 @@
 )
 
 
+# TODO(restore-hindcast): 6/30/2026, NLR HSDS endpoint is non functional
+# https://github.com/MHKiT-Software/MHKiT-Python/issues/450
+@unittest.skip(
+    "TODO(restore-hindcast): NLR HSDS endpoint unavailable. See "
+    "https://github.com/MHKiT-Software/MHKiT-Python/issues/450"
+)
 class TestWPTOhindcast(unittest.TestCase):
     """
     A test call designed to check the WPTO hindcast retrival
diff --git a/mhkit/tests/wave/io/hindcast/test_wind_toolkit.py b/mhkit/tests/wave/io/hindcast/test_wind_toolkit.py
index 0113a0cab..ad9dd7141 100644
--- a/mhkit/tests/wave/io/hindcast/test_wind_toolkit.py
+++ b/mhkit/tests/wave/io/hindcast/test_wind_toolkit.py
@@ -1,4 +1,4 @@
-from os.path import abspath, dirname, join, isfile, normpath, relpath
+from os.path import abspath, dirname, join, normpath
 from pandas.testing import assert_frame_equal
 import matplotlib.pylab as plt
 import mhkit.wave.io.hindcast.wind_toolkit as wtk
@@ -6,7 +6,6 @@
 import unittest
 import pytest
 
-
 testdir = dirname(abspath(__file__))
 datadir = normpath(
     join(
@@ -24,6 +23,12 @@
 )
 
 
+# TODO(restore-hindcast): 6/30/2026, NLR HSDS endpoint is non functional
+# https://github.com/MHKiT-Software/MHKiT-Python/issues/450
+@unittest.skip(
+    "TODO(restore-hindcast): NLR HSDS endpoint unavailable. See "
+    "https://github.com/MHKiT-Software/MHKiT-Python/issues/450"
+)
 class TestWINDToolkit(unittest.TestCase):
     @classmethod
     def setUpClass(self):
diff --git a/mhkit/wave/io/hindcast/hindcast.py b/mhkit/wave/io/hindcast/hindcast.py
index 83119a782..5be667683 100644
--- a/mhkit/wave/io/hindcast/hindcast.py
+++ b/mhkit/wave/io/hindcast/hindcast.py
@@ -20,6 +20,8 @@
 from mhkit.utils.cache import handle_caching
 from mhkit.utils.type_handling import convert_to_dataset
 
+from mhkit.wave.io.hindcast.hindcast_exceptions import hindcast_guard
+
 
 def region_selection(lat_lon: Union[List[float], Tuple[float, float]]) -> str:
     """
@@ -74,6 +76,7 @@ def region_search(
 # pylint: disable=too-many-locals
 # pylint: disable=too-many-branches
 # pylint: disable=too-many-statements
+@hindcast_guard
 def request_wpto_point_data(
     data_type: str,
     parameter: Union[str, List[str]],
@@ -283,6 +286,7 @@ def request_wpto_point_data(
 
 # pylint: disable=too-many-branches
 # pylint: disable=too-many-statements
+@hindcast_guard
 def request_wpto_directional_spectrum(
     lat_lon: Union[Tuple[float, float], List[Tuple[float, float]]],
     year: str,
diff --git a/mhkit/wave/io/hindcast/hindcast_exceptions.py b/mhkit/wave/io/hindcast/hindcast_exceptions.py
new file mode 100644
index 000000000..d54dbdcf1
--- /dev/null
+++ b/mhkit/wave/io/hindcast/hindcast_exceptions.py
@@ -0,0 +1,92 @@
+"""
+Exceptions for the hindcast API and a decorator that turns low-level request
+failures into clear, actionable errors.
+
+A 502 or 503 response means the NLR HSDS service is down, which is tracked in
+the MHKiT issue below. Any other failure asks the user to open a new issue and
+paste the stack trace. To handle a new failure mode, add an exception class and
+a branch to :func:`hindcast_guard`.
+"""
+
+import functools
+import traceback
+from typing import Callable
+
+# Existing MHKiT issue tracking the known NLR HSDS service outage.
+HINDCAST_UNAVALIABLE_ISSUE_URL = (
+    "https://github.com/MHKiT-Software/MHKiT-Python/issues/450"
+)
+# Where to open a new MHKiT issue for any other hindcast request failure.
+NEW_ISSUE_URL = "https://github.com/MHKiT-Software/MHKiT-Python/issues/new"
+# HTTP status codes that mean the HSDS service is down (tracked in #450).
+_SERVICE_DOWN_CODES = ("502", "503")
+
+
+class HindcastApiError(RuntimeError):
+    """Base class for hindcast API errors, also raised for unexpected failures."""
+
+
+class HindcastApiUnavailableError(HindcastApiError):
+    """Raised when the hindcast API is down (HSDS 502 or 503)."""
+
+
+def _is_service_down(err: Exception) -> bool:
+    """Return True when the error looks like an HSDS 502 or 503 response."""
+    text = str(err)
+    return any(code in text for code in _SERVICE_DOWN_CODES)
+
+
+def _unavailable_message(trace: str) -> str:
+    return (
+        "Could not retrieve the hindcast data. The NLR HSDS endpoint "
+        "(developer.nlr.gov) returned a 502 or 503 error and is likely down.\n\n"
+        "This is a known outage tracked here:\n"
+        f"  {HINDCAST_UNAVALIABLE_ISSUE_URL}\n\n"
+        f"Stack trace:\n{trace}"
+    )
+
+
+def _unexpected_message(trace: str) -> str:
+    return (
+        "An unexpected error occurred while retrieving the hindcast data.\n\n"
+        "Please open an issue and paste the stack trace below:\n"
+        f"  {NEW_ISSUE_URL}\n\n"
+        f"Stack trace:\n{trace}"
+    )
+
+
+def hindcast_guard(func: Callable) -> Callable:
+    """
+    Convert a failed hindcast API request into a clear HindcastApiError.
+
+    The wrapped function runs normally, so cached results and a recovered
+    service still work. Input validation errors (TypeError, ValueError) and
+    existing HindcastApiError subclasses pass through unchanged. An HSDS 502
+    or 503 raises HindcastApiUnavailableError pointing to the tracking issue.
+    Any other failure raises HindcastApiError asking the user to open an
+    issue. Both include the stack trace for the user to copy into the issue.
+
+    Parameters
+    ----------
+    func : callable
+        Hindcast data-request function to wrap.
+
+    Returns
+    -------
+    callable
+        The wrapped function.
+    """
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        try:
+            return func(*args, **kwargs)
+        except (TypeError, ValueError, HindcastApiError):
+            raise
+        except Exception as err:
+            trace = traceback.format_exc()
+            if _is_service_down(err):
+                raise HindcastApiUnavailableError(_unavailable_message(trace)) from err
+            raise HindcastApiError(_unexpected_message(trace)) from err
+
+    return wrapper
diff --git a/mhkit/wave/io/hindcast/wind_toolkit.py b/mhkit/wave/io/hindcast/wind_toolkit.py
index a22cbe7ba..cfc55b8a1 100644
--- a/mhkit/wave/io/hindcast/wind_toolkit.py
+++ b/mhkit/wave/io/hindcast/wind_toolkit.py
@@ -30,6 +30,8 @@
 from mhkit.utils.cache import handle_caching
 from mhkit.utils.type_handling import convert_to_dataset
 
+from mhkit.wave.io.hindcast.hindcast_exceptions import hindcast_guard
+
 
 def region_selection(lat_lon: Tuple[float, float], preferred_region: str = "") -> str:
     """
@@ -108,6 +110,7 @@ def region_search(x: str) -> bool:
     return region[0]
 
 
+@hindcast_guard
 def get_region_data(region: str) -> Tuple[np.ndarray, np.ndarray]:
     """
     Retrieves the latitude and longitude data points for the specified region
@@ -210,7 +213,7 @@ def plot_region(
     supported_regions = ["Offshore_CA", "Hawaii", "Mid_Atlantic", "NW_Pacific"]
     if region not in supported_regions:
         raise ValueError(
-            f'{region} not in list of supported regions: {", ".join(supported_regions)}'
+            f"{region} not in list of supported regions: {', '.join(supported_regions)}"
         )
 
     lats, lons = get_region_data(region)
@@ -278,6 +281,7 @@ def elevation_to_string(
 # pylint: disable=too-many-statements
 # pylint: disable=too-many-positional-arguments
 # pylint: disable=duplicate-code
+@hindcast_guard
 def request_wtk_point_data(
     time_interval: str,
     parameter: Union[str, List[str]],
@@ -369,7 +373,6 @@ def request_wtk_point_data(
     meta: DataFrame
         Location metadata for the requested data location
     """
-
     if not isinstance(parameter, (str, list)):
         raise TypeError("parameter must be of type string or list")
     if not isinstance(lat_lon, (list, tuple)):
@@ -427,6 +430,9 @@ def request_wtk_point_data(
         else:
             raise TypeError("Coordinates must be within the same region!")
 
+    # NOTE: NREL to NLR name changes
+    #   * developer.nlr.gov must be configured via ~/.hscfg
+    #   * As of June 2026 the HSDS data domain is still "/nrel/...".
     if time_interval == "1-hour":
         wind_path = f"/nrel/wtk/{region.lower()}/{region}_*.h5"
     elif time_interval == "5-minute":
diff --git a/pyproject.toml b/pyproject.toml
index c9805d480..02386a2b8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -47,7 +47,7 @@ wave = [
     "scikit-learn>=1.5.1",
     "statsmodels>=0.14.2",
     "pytz",
-    "NREL-rex>=0.2.63",
+    "NLR-rex[hsds]>=0.5.0",
     "beautifulsoup4",
     "bottleneck",
     "lxml",