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   "source": [
    "# General temporal aggregation methods"
   ]
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   "source": [
    "# If first time running, uncomment the line below to install any additional dependencies\n",
    "# !bash requirements-for-notebooks.sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from earthkit.transforms import aggregate as ek_aggregate\n",
    "from earthkit import data as ek_data\n",
    "\n",
    "from earthkit.data.testing import earthkit_remote_test_data_file\n",
    "ek_data.settings.set(\"cache-policy\", \"user\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load some test data\n",
    "\n",
    "All `earthkit-transforms` methods can be called with `earthkit-data` objects (Readers and Wrappers) or with the \n",
    "pre-loaded `xarray`.\n",
    "\n",
    "In this example we will use hourly ERA5 2m temperature data on a 0.5x0.5 spatial grid for the year 2015 as\n",
    "our physical data.\n",
    "\n",
    "First we download (if not already cached) lazily load the ERA5 data (please see tutorials in `earthkit-data` for more details in cache management).\n",
    "\n",
    "We inspect the data using the describe method and see we have some 2m air temperature data. For a more detailed representation of the data you can use the to_xarray method."
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    "# Get some demonstration ERA5 data, this could be any url or path to an ERA5 grib or netCDF file.\n",
    "remote_era5_file = earthkit_remote_test_data_file(\"test-data\", \"era5_temperature_europe_2015.grib\")\n",
    "era5_data = ek_data.from_source(\"url\", remote_era5_file)\n",
    "era5_data.describe()\n",
    "# era5_data.to_xarray()"
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    "## Reduce the ERA5 data over the time dimension\n",
    "\n",
    "The default reduction method is `mean`, other methods can be applied using the `how` kwarg.\n",
    "\n",
    "Note that we do not need to worry about the data format of the input array, earthkit will convert it to the required xarray format internally.\n",
    "\n",
    "The returned object is an xarray dataset, however this may change in future version of the package.\n",
    "\n",
    "### The mean over the time dimension"
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       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1...</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-ed853cdf-c126-4bdd-a49c-d4422bafa28a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ed853cdf-c126-4bdd-a49c-d4422bafa28a' 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'>number</span>: 1</li><li><span class='xr-has-index'>step</span>: 1</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-489ceb4d-3e44-46da-a921-26e3feb75ee7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-489ceb4d-3e44-46da-a921-26e3feb75ee7' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-b4624cff-ae56-4217-90d9-87ef04d527e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4624cff-ae56-4217-90d9-87ef04d527e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6d8c4d2-a826-4782-9e6c-1f4ce5b20263' class='xr-var-data-in' type='checkbox'><label for='data-e6d8c4d2-a826-4782-9e6c-1f4ce5b20263' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-5c1ffb40-d3f2-4abe-8291-28fc403fe85d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c1ffb40-d3f2-4abe-8291-28fc403fe85d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6ce6b42-221c-41ee-816a-ad25da7de052' class='xr-var-data-in' type='checkbox'><label for='data-c6ce6b42-221c-41ee-816a-ad25da7de052' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([0], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-485b1d69-c806-41b9-8313-d63a2121a35e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-485b1d69-c806-41b9-8313-d63a2121a35e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25f80942-c43c-46c9-b76a-b99b4a0539b2' class='xr-var-data-in' type='checkbox'><label for='data-25f80942-c43c-46c9-b76a-b99b4a0539b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.75 79.5 ... 30.5 30.25 30.0</div><input id='attrs-baaa00f8-fdad-454e-9527-3370546b59df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baaa00f8-fdad-454e-9527-3370546b59df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67c25146-5063-4d43-9ecc-d8d92abede01' class='xr-var-data-in' type='checkbox'><label for='data-67c25146-5063-4d43-9ecc-d8d92abede01' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([80.  , 79.75, 79.5 , ..., 30.5 , 30.25, 30.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.0 -9.75 -9.5 ... 59.75 60.0</div><input id='attrs-8d069cc9-efac-437d-80c0-49feaf7e0679' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d069cc9-efac-437d-80c0-49feaf7e0679' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0771b6fe-abaa-4138-8e9d-b6f90435b82e' class='xr-var-data-in' type='checkbox'><label for='data-0771b6fe-abaa-4138-8e9d-b6f90435b82e' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-10.  ,  -9.75,  -9.5 , ...,  59.5 ,  59.75,  60.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8f9798ff-4582-41cc-95e2-7cb8d68bb821' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f9798ff-4582-41cc-95e2-7cb8d68bb821' class='xr-section-summary' >Data variables: <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>t2m</span></div><div class='xr-var-dims'>(number, step, surface, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>262.5 262.6 262.6 ... 297.4 294.4</div><input id='attrs-4783737e-820f-4cab-9478-93bf52d98d65' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4783737e-820f-4cab-9478-93bf52d98d65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5410f929-9953-4a57-ad16-41bcfd3504cd' class='xr-var-data-in' type='checkbox'><label for='data-5410f929-9953-4a57-ad16-41bcfd3504cd' title='Show/Hide data 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([[[[[262.5087 , 262.5504 , 262.59155, ..., 266.0045 , 266.01108,\n",
       "           266.0531 ],\n",
       "          [262.7588 , 262.7883 , 262.81763, ..., 266.2775 , 266.235  ,\n",
       "           266.19247],\n",
       "          [262.9496 , 262.97974, 263.01157, ..., 266.43918, 266.42944,\n",
       "           266.4202 ],\n",
       "          ...,\n",
       "          [291.8643 , 292.8288 , 293.9913 , ..., 298.31854, 296.62   ,\n",
       "           294.54953],\n",
       "          [291.51022, 291.65958, 292.73248, ..., 298.49518, 296.56384,\n",
       "           294.04434],\n",
       "          [291.65176, 292.43878, 292.6089 , ..., 299.27054, 297.38718,\n",
       "           294.43887]]]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d3980536-817d-45c1-acb8-e4efaa31f0f4' class='xr-section-summary-in' type='checkbox'  ><label for='section-d3980536-817d-45c1-acb8-e4efaa31f0f4' class='xr-section-summary' >Indexes: <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-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-891c2ae4-c2f8-4001-9c05-73dbed2e57a6' class='xr-index-data-in' type='checkbox'/><label for='index-891c2ae4-c2f8-4001-9c05-73dbed2e57a6' 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], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-223717f1-a585-4a01-a8fd-d30bd61daaa9' class='xr-index-data-in' type='checkbox'/><label for='index-223717f1-a585-4a01-a8fd-d30bd61daaa9' 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(TimedeltaIndex([&#x27;0 days&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2ae88feb-58a1-4b2a-97af-320fcdcbc59b' class='xr-index-data-in' type='checkbox'/><label for='index-2ae88feb-58a1-4b2a-97af-320fcdcbc59b' 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], dtype=&#x27;float64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dde9d532-9d3a-4d39-9325-833a8a047f1a' class='xr-index-data-in' type='checkbox'/><label for='index-dde9d532-9d3a-4d39-9325-833a8a047f1a' 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([ 80.0, 79.75,  79.5, 79.25,  79.0, 78.75,  78.5, 78.25,  78.0, 77.75,\n",
       "       ...\n",
       "       32.25,  32.0, 31.75,  31.5, 31.25,  31.0, 30.75,  30.5, 30.25,  30.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=201))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4fcc504e-c900-40fb-a255-1b873699b1a9' class='xr-index-data-in' type='checkbox'/><label for='index-4fcc504e-c900-40fb-a255-1b873699b1a9' 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([-10.0, -9.75,  -9.5, -9.25,  -9.0, -8.75,  -8.5, -8.25,  -8.0, -7.75,\n",
       "       ...\n",
       "       57.75,  58.0, 58.25,  58.5, 58.75,  59.0, 59.25,  59.5, 59.75,  60.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=281))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c83ea22e-ea2b-4c03-ad0f-250329e739ca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c83ea22e-ea2b-4c03-ad0f-250329e739ca' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.14.0/ecCodes-2.36.0 with {&quot;source&quot;: &quot;N/A&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 230kB\n",
       "Dimensions:    (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number     (number) int64 8B 0\n",
       "  * step       (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface    (surface) float64 8B 0.0\n",
       "  * latitude   (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude  (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m        (number, step, surface, latitude, longitude) float32 226kB 262...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era5_t_mean = ek_aggregate.temporal.reduce(era5_data)  # how=\"mean\"\n",
    "era5_t_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14ff47450>"
      ]
     },
     "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": [
    "# A simple matplotlib plot to view the data:\n",
    "era5_t_mean.t2m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The median over the time dimension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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: 230kB\n",
       "Dimensions:    (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number     (number) int64 8B 0\n",
       "  * step       (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface    (surface) float64 8B 0.0\n",
       "  * latitude   (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude  (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m        (number, step, surface, latitude, longitude) float32 226kB 262...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1...</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-493d73d0-93ae-4cd0-8bef-83cbd8db1f97' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-493d73d0-93ae-4cd0-8bef-83cbd8db1f97' 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'>number</span>: 1</li><li><span class='xr-has-index'>step</span>: 1</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6b64fdf8-2c99-4c01-85f9-99470349a965' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6b64fdf8-2c99-4c01-85f9-99470349a965' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-29dec25f-ba26-494a-94c6-350833d01fef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29dec25f-ba26-494a-94c6-350833d01fef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d93192ec-5efc-4624-ba95-73cded2f2788' class='xr-var-data-in' type='checkbox'><label for='data-d93192ec-5efc-4624-ba95-73cded2f2788' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-cc461b98-6aeb-446d-a292-5a37337fbd01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc461b98-6aeb-446d-a292-5a37337fbd01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0e944b9-5e90-44ff-b0b1-028c74c8f3f4' class='xr-var-data-in' type='checkbox'><label for='data-d0e944b9-5e90-44ff-b0b1-028c74c8f3f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([0], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-635a089b-ec14-4ef7-9897-6ba505260f7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-635a089b-ec14-4ef7-9897-6ba505260f7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-935668c1-cc62-491f-8bbb-1318d5c01539' class='xr-var-data-in' type='checkbox'><label for='data-935668c1-cc62-491f-8bbb-1318d5c01539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.75 79.5 ... 30.5 30.25 30.0</div><input id='attrs-6dd0067a-c4d9-4b94-a241-152dbe19b292' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dd0067a-c4d9-4b94-a241-152dbe19b292' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-119c248f-2249-4869-86fe-59ba20ce686d' class='xr-var-data-in' type='checkbox'><label for='data-119c248f-2249-4869-86fe-59ba20ce686d' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([80.  , 79.75, 79.5 , ..., 30.5 , 30.25, 30.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.0 -9.75 -9.5 ... 59.75 60.0</div><input id='attrs-6bd02ef4-884d-4620-a2c6-b17f8ac02de3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bd02ef4-884d-4620-a2c6-b17f8ac02de3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8be63545-99bf-47cf-9aab-5545168b180c' class='xr-var-data-in' type='checkbox'><label for='data-8be63545-99bf-47cf-9aab-5545168b180c' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-10.  ,  -9.75,  -9.5 , ...,  59.5 ,  59.75,  60.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95f1bba1-435a-461d-952e-0d42bf52433b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95f1bba1-435a-461d-952e-0d42bf52433b' class='xr-section-summary' >Data variables: <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>t2m</span></div><div class='xr-var-dims'>(number, step, surface, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>262.2 262.2 262.3 ... 298.2 294.9</div><input id='attrs-07b589dd-b3b4-4a58-a119-ccb82b972406' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07b589dd-b3b4-4a58-a119-ccb82b972406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d71b3e25-2561-4d7e-9694-e544b7f3a79b' class='xr-var-data-in' type='checkbox'><label for='data-d71b3e25-2561-4d7e-9694-e544b7f3a79b' title='Show/Hide data 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([[[[[262.1565 , 262.2146 , 262.30563, ..., 269.32007, 269.3398 ,\n",
       "           269.36227],\n",
       "          [262.38242, 262.391  , 262.43542, ..., 269.49   , 269.46655,\n",
       "           269.39862],\n",
       "          [262.6541 , 262.65015, 262.7306 , ..., 269.56372, 269.5463 ,\n",
       "           269.49408],\n",
       "          ...,\n",
       "          [292.11346, 292.8698 , 293.5777 , ..., 299.16003, 297.2898 ,\n",
       "           295.15112],\n",
       "          [291.87836, 291.8169 , 292.52698, ..., 299.2842 , 297.276  ,\n",
       "           294.4057 ],\n",
       "          [292.06885, 292.6853 , 292.60828, ..., 300.00146, 298.1529 ,\n",
       "           294.94257]]]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a268516-829a-44c9-8e5e-74b454db9e42' class='xr-section-summary-in' type='checkbox'  ><label for='section-6a268516-829a-44c9-8e5e-74b454db9e42' class='xr-section-summary' >Indexes: <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-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-391ebf24-a321-42ad-a861-dd08d2c0fc55' class='xr-index-data-in' type='checkbox'/><label for='index-391ebf24-a321-42ad-a861-dd08d2c0fc55' 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], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aa33be63-4428-45aa-b000-2e041bceecfb' class='xr-index-data-in' type='checkbox'/><label for='index-aa33be63-4428-45aa-b000-2e041bceecfb' 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(TimedeltaIndex([&#x27;0 days&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0249844f-d691-4fe6-96b4-266e1757f4ec' class='xr-index-data-in' type='checkbox'/><label for='index-0249844f-d691-4fe6-96b4-266e1757f4ec' 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], dtype=&#x27;float64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8c1b5939-f103-4575-ac92-a3e65f44517f' class='xr-index-data-in' type='checkbox'/><label for='index-8c1b5939-f103-4575-ac92-a3e65f44517f' 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([ 80.0, 79.75,  79.5, 79.25,  79.0, 78.75,  78.5, 78.25,  78.0, 77.75,\n",
       "       ...\n",
       "       32.25,  32.0, 31.75,  31.5, 31.25,  31.0, 30.75,  30.5, 30.25,  30.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=201))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9298dcf7-eebd-4a09-90fd-8b9143b790bb' class='xr-index-data-in' type='checkbox'/><label for='index-9298dcf7-eebd-4a09-90fd-8b9143b790bb' 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([-10.0, -9.75,  -9.5, -9.25,  -9.0, -8.75,  -8.5, -8.25,  -8.0, -7.75,\n",
       "       ...\n",
       "       57.75,  58.0, 58.25,  58.5, 58.75,  59.0, 59.25,  59.5, 59.75,  60.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=281))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6d15ffc-3e6c-431f-b0a8-7c4754ca7e9a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f6d15ffc-3e6c-431f-b0a8-7c4754ca7e9a' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.14.0/ecCodes-2.36.0 with {&quot;source&quot;: &quot;N/A&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 230kB\n",
       "Dimensions:    (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number     (number) int64 8B 0\n",
       "  * step       (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface    (surface) float64 8B 0.0\n",
       "  * latitude   (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude  (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m        (number, step, surface, latitude, longitude) float32 226kB 262...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era5_t_median = ek_aggregate.temporal.reduce(era5_data, how=\"median\")\n",
    "era5_t_median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x1533b1e10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0009jjz32kPnnzp3bVH1A8f610UYbYYMNNsC1116LadOmZfIDjT3LHqsZVrbRTiOwGYuZjE6POuoo3qdPH/7jH/+Y33fffXzmzJl8s802sxoA6zIPO+ww3r9//4wOO++8M990003ld2EIN3r0aP7lL3+Z/+53v+M33XQT33DDDfmAAQP4P//5T5n3/vvv5+3t7XzixIn85ptv5gsWLOB33nknnzlzJv+f//mfzPX87W9/a7SpmsINN9zAAfBjjjmGz58/n1911VX8E5/4BN99991zy7oMgJctW8Zvu+02ftttt/FTTjmFA+AzZszgt912mzUeBgwGwAD4zjvv7NTj8ssv51/72tf4nDlz+P3338//8Ic/8P/5n//hAPg999wj840ZM4Z/+tOf5vfccw//29/+JvV+7rnn+ODBg/nnPvc5Pnv2bD5//nw+d+5cftFFF/FddtlFli9z/3sC5557LmeM8e9+97v8gQce4D/84Q95e3s7P/roo3PLPvPMM7xv3758k0024bfeeiufO3cu32OPPfjo0aOVe/ree+/xwYMH889+9rP8jjvu4L/97W/5QQcdxMeNG2c1MhdGv4wx/tJLLylpv/3tb/lee+3Fr7zySj5v3jx+77338m9961scAL/qqqucOi9evJiPHDmSb7755vzOO+/kf/jDH/hOO+3EBwwYwF944QUlb5l+rRvlril1tfLZ2W233fjgwYP51Vdfze+9917+7W9/29gHbO9Szs3v3zL96+677+bVapVvueWW/LrrruPz58/n1113HT/44INlnqLPMufme/HFL36Rh2GonDv77LN5GIb8gQcecLalR/djjR/MLFmyhB911FF8+PDhvH///nzfffflr7/+ercNZm644QZ+4okn8qFDh/L29nb+hS98gT/22GOZ8n//+9/5AQccwIcNG8ar1SofMWIE/+IXv8ivuOKKzPWsrMEM57HXxBZbbMHb2tr4iBEj+Iknnsg//PDD3HKuwYzLc2fMmDFGefpg5sMPP+QA+EEHHeTU45FHHuFf+cpX+JgxY3h7eztfe+21+c4778znzp2r5Lvvvvv4+PHjeXt7OwfADzvsMEXfyZMn809+8pO8Wq3yoUOH8h122IGfe+65Mk/Z+98TuPTSS/lGG23E29ra+HrrrcfPOuss3tnZWajsX/7yF/7//t//4+3t7XzEiBH8tNNO41dddVXmnj788MN8++235/369eNDhw7lRx11FH/iiSesg5mOjg7e3t7O99xzz0zaP/7xD/71r3+db7DBBrxv37580KBB/HOf+xyfM2dOIZ3/+c9/8kmTJvGBAwfyfv368V133ZU//vjjxrxF+7XtR391rqvVz87ChQv5//zP//AhQ4bwQYMG8W984xvSM62ZwQzn5frXI488wvfaay8+aNAg3t7ezjfYYAN+8sknK3mKPMucm+/FzjvvzPX5v9A7z8PQo/uxWg5mPFZ9iMHMP//5z4wLehnUajXe1dWVGcz8/ve/54wx/vTTT7dC3abRUxGgV3fMnTuXA+C///3vV7YqvRar2rPj4dEKrNE2Mx4rHxtuuCGA2ONAGD+Xwdprr61EdRaYP38+DjrooExgOI9VE88//zzeeOMNnHLKKdhyyy2VUAcePQv/7HisifCDGY9uwb777qsYtDa6C+4DDzwgQ7YPGzZMnv/hD3/YlH4ePYspU6bgL3/5C7baaitcd911q02cojUR/tnxWBPBOM+Jje7h4eHh4eHhsQpjtY4A7OHh4eHh4eGxUgcztVoN3/ve9zB27FgZAOqcc85BFEUyD+ccM2bMwKhRo9C3b19MmDABzz333ErU2sPDw8PDw2NVwkodzFxwwQW44oor8NOf/hQvvPACLrzwQvzwhz9Uwk1feOGFuOiii/DTn/4Uf/vb3zBixAjsvvvuzl10PTw8PDw8PHoPVqrNzD777IPhw4fjmmuukee++tWvol+/frjhhhvAOceoUaMwdepUfPvb3wYQh80ePnw4LrjgAhx77LG5dURRhH//+98YMGCANzr08PDw8HCCc44PP/wQo0aNQhB033x/xYoV6OzsbFpOW1ubdYPN3oSV6s2044474oorrsBLL72EjTbaCH//+9/x0EMP4ZJLLgEAvPbaa1i0aBEmTpwoy7S3t2PnnXfGww8/bBzMdHR0KPuEvP3228peJR4eHh4eHnl48803nZtXNoMVK1Zg7Ji1sGhxvWlZI0aMwGuvvdbrBzQrdTDz7W9/G0uWLMHGG2+MMAxRr9dx3nnnyU3RxMZ2+i6ww4cPxxtvvGGUOWvWLJx99tmZ8zviS6gg2YSRpaNtFjjYGmYflSvlBOOjyyJMEAuC+Dsd6bOsDMaCWI5I08vQtDBQdQxY+p2xOB0AZwwIhY4BeMikrjxg4EI+i8vxJC9n6TVxxoAg+Z/k5SJNlE104Ix818CZdt30PJXjAgeY4BM5J5/JeXEq0OWn12aSwSIAkSokk0/kNZGaUfYUq0dgiUxW5/Fn+T2SZVgUAVEEVk/k1uppZXGO9BpIPxD3i9Zv0k3cQyNIPxP9g4v+Q/tcks6ZVhZpfzAigLFtpAgbQayf5tzYf2IhdvndAV6E6dXb29EGjcLadkC2/ZS0pA9yZO+nkEk/5+rhrkeRb8qmvz5z5LEoew4c2X5Q4D5xcp9qtQ785W8/xIABA3LLNYrOzk4sWlzHa4+PwcABjbM/Sz+MMHbrN9DZ2ekHMyuz8l/+8pe48cYbcfPNN2PTTTfFU089halTp2LUqFE47LDDZD59eYhzbl0ymj59OqZNmya/L126FKNHj0aFtaPC4sGMOhApOLCh+W35GEsHLUD840D1DFg8WEk+Gwcs9Jz4H4o0w0AnTMvFP0LiByhIBzCMpS/ekCk/Tlx8R/JjFJC66WcWl5UvCjJgYURfLrI4mlJ/adHrFWks4vJlFQ8g0hcvGMiAAkBdpMVl6MudR2TwRQZSdDDDIp7KSwYbcvBRi+IBBwBWB1CLUvnaS5q2ufKZVdJBYSVuZ0bqkwMbMZARcutcrUsYxifXyOl9Em0VJOWpbqJcEAAIlL6gDFJEHwzjAS6vJH2pkg5sJMg9TAe/9pvu/MEFCv/I63IKDSiKohtWFIrql9s+RdDCgVKz+tDrbkqWqWhJedZBUV65HjBLGDggaGow45FipQ5mTjvtNHznO9/BQQcdBCDexv6NN97ArFmzcNhhh2HEiBEAYoZm5MiRstzixYszbI1Ae3u7cddUDw8PDw+PVQl1Hom5WMPlPWKs1MHMxx9/nDGwCsNQumaPHTsWI0aMwLx58zB+/HgAMT23YMECXHDBBaXqYmEIxkL1nIWhMYLkZaEqR2FiyHcWhmk5xgBajunMjJaPyiRpypIRI0tEQZyXztbp8hFXWBqkM+0AiBR56bVSBoVTlkakMfq5/Cwmw9AQxiVmmpJ8nIOJzFHMZgRd6bJNUBOMRcKqCKamHoHVtIddMjNkyYXOIkV+hRFJ0qJIZWbqRHYUxaycWJqpBODiflfD9J5FDCwgy18hA6+I9g8V/WOGJUniXGGgOGVfiBpc5CXLBAo7QO6jyh6lfZCHDFElkO3DGWHkRD300aEvY57OxLnSX3L6B300HDNv3oK1pJayOQK6SNslWKpWdGqUSQiy7U7vhcJY5rBoRdpZl2nNV/SemX6XDUUzS8kuFkhfQrPoq8jsQUeRCBxRozc8Ke8RY6UOZvbdd1+cd955WG+99bDpppviySefxEUXXYTJkycDiGm+qVOnYubMmRg3bhzGjRuHmTNnol+/fjj44INL1cXCIB3MmJaJXA+3budiWD6Kk5IfM9MykxiUyAGMOkhR7WBSuxUqg4tlAWWJSLN3ET9ASl2qXQUPUpsH1X4mu3ZObVlMdhKAOrBxgQdQ17kN6fIzaF5GfpvjJUaRN+iCHIgGXVE8oBHLQl11OThhXfVkYEIGCsTWiS6xSLsiQC7pqIrSwQb5XK/HBwDWSQa9IVmyqYbxIKdK7psYUIDHA02aJpagiApG2wJq42BBdvBIlhhDXaijnF63zJj8Mzxfhe0h0E2DjRJwXW9hFJRhvK8sm1YEpnYrNaAsmS83r8Hcy5gmEBrO5cnVkyJtgGXo88Zy9D4UMTfwWOWwUgczl112Gc4880xMmTIFixcvxqhRo3Dsscfi+9//vsxz+umnY/ny5ZgyZQref/99bLfddrj33nu71TjLw8PDw8OjuxEhasrUqbnSaxbW+L2Zli5dikGDBuGLfQ9EJbDb0rAM2+JgX1zGuxmWJSCf1TTFgJPIUAx5KfsSxIyEnDkETJFBlwM4I/kYsktHpnzJeaOnimlJKAFlVFzLETKL0ajPcM4AFokj9WhIl5U4ghpH0Bk/4EFnHayLsDT1urJUI6ZjirG09PYinj3UQ6gWxXKA2EC3K94EE7U6YFu/DsNUXrUCVENiXBuo95cyaAnbFldOmkr3YtLvWSugLHu4b464ny7DbgXNvHJsTECezBawPbY2btTAtCkUacMS99BYxlZvq+9pQTjbWXeYKqqP4ZGtdy3Hg38+B0uWLMHAgQML61cG4nfpzX98smlvptEbv92tuq4u8GbUHh4eHh4eHqs1VuoyU08iNgDW3J8ztjDEkEx3wdaZGIuBLoTdjPhOXaep8S411q2kNho8kZd+V+0aqCGu0ViXMC4Kq+JiTHTXd02WrEs/R9b2TfYYNnCiozFeDKDMtHQ7Gxr/BlpgiQgAZ6lLsWBmgloIVqtLFoeDrPdT9/RKkNFL0aMdik0OEoaFddUBwdIASr+I7yk5T+VGSA1tAygzX8ZjO5r0MpPz4HZbBaPdhJalwKRV7x9uG5d8eaoCJex6WiCzZaBVOGyYnOXV7loMprYve72tap8S/a6wyIIkimxnjXVhhja1GR1nGBvxXNLnULcf60Z4A+DWodcMZjw8PDw8PFYlROCo+8FMS9B7BjNhCATJ5er2LxQ2WxhbFF4qI3HNVTxjmDo7l+66oca40GirxC4mIoHqePJZj2YLWJgZ/Zr0vCS/TNPsX1xyjPIc50x1prMtps5ACVPDQ8g0I0sjZASq8HrAwJJZVsQBFoXqGjnx/FLa1OW+yROvKQCsLUxtcoQtjZBP7z1xA5fMG3ELz9TtsJOhuku3WzCZlYOrMjU5cZ6CMN2nUgKKy28pAqZGcda/twKUHdTr8rDDcB8KMVua67TLu08tp9ZHGRtFBvGkkoE2PVYr9J7BjIeHh4eHxyoEv8zUOvSewUxiE8Ns8V2CQGVfaLwYUxlbjBKW/Q4IW4w0QBqne9+EenwYs6eK4p2EEuwLKSPTDTYweTKNcm0okE9nD+KAb+kJGTpFiaOSlCX55Kc6i4POJYJZlGYUrIqUT7YwkOnyS8rO0O0R4q0GoM72xD0JGXgQKsyMYoejbxkh20BlafS9pihsHhrK1gZ6s5iYgrIsRQ+zDS3xzNLtHlpsB6HYieXJbmXVZWxuaF6j3U1LNLLLN6HAfShk0wW4+7FIKhoHhyDqwf5e5xz1JjzBmim7pqH3DGY8PDw8PDxWIURobkstH2UmRa8ZzLBqFSysqp5IlGGpaE1B7WJMWwoQ75TMlgKaZxIARBVm91JiIBsU2j2RXB5Drl2ny8aBKc3IGGSW9n7Rr5HMKmPGJmkPytbQE1IOYXQCKLY2jAMirBILUhsdybgActNJGbuGbDoJzsFqPN7WwAayBQDdfTxlaVj2/pJ8rA6yfQKpW99AUw8lLzeaTOSIXRkUFgiKrUfLY9OUxcquvwnY2q7b27SMfIfdVFMqdDPLU7gNKYPSAEGhMsEE9fKyPFY+es1gxsPDw8PDY1VCvUlvpmbKrmnoPYOZSgUIK6otDABrhF7CzOibOyp7J2k2MlxjX+jmfcqeSIltjEgDOa/HhdG9l5zMhoOFoSjCyJRhY4rJL5Ff/67FoJFL4qQgD1T7mvgztZ8h+YltCgsZiSjM4si+oSgXszHiMxABNUOsSZ2donYylZSFo95pAJIozkRGwNLYMkjLgfNYN8QMTcwQGYx+IgbGeNo/qd0EYYiMaHJ2vVKZHp1N7OlItSt5P6luhe4R1MSlGmNStQIWmXnRxo269KjNDJrcNbt1uqzu6D2DmWoIhNXsVgTa4IWHhjTDeXUwow5Y9AEMQJYaTAMYw7JS0S0FuP67anp/OwclJZaUmhmMFNXHUt60/CS/p7/9yed0SUr+4Is0sUKkuIKnBrSMcQRgQE0sLVED4CgeFFledmIpMf4cKDtjQ+kHsP7Q8hBgdJsLKRzSfZRFDAgdbzGba7Y2UG7qR6U7At+1EjnB3RrZgmCVuK4eQkt3kVaWR/WKiskuvC2KXs7EXNC5rCE58071WC3QewYzHh4eHh4eqxC8AXDr0HsGM2EIVELQLQZ0Q15p3AvE57WAdwAkE6MsJZEgZ4rhp2HrAbqkQJePlPPazN9m3Ju3pFSWkTGWKb1U5ajTpVPRyZ+JsdGWoNTPTH5kHOBB6nItDf3oyg9j4IyE1kruKYA4IGIIZaaZBvaL73sk7n1I3PA1lk1ZRjQEAxMMDFfKMs3oWW0IZxAxk6G4A86NI1N1Mmglc9Hdmze6A63lFM67zjLu002ikTYvtZ1FA/chI7/M8rVSTldK+5rDsJjq1mFkbnoQERjqTXSWaHW2om8xPKHm4eHh4eHRC3D55Zdjiy22wMCBAzFw4EBsv/32+OMf/yjTOeeYMWMGRo0ahb59+2LChAl47rnnFBkdHR044YQTsM4666B///7Yb7/98NZbb/X0pWTQe5iZahW8rZK1hdGYGMXNWrIqWSaGsid6gDsluB11gyVpmYBxhKVR0l1sjCHdigJr00VmTK4w+blySkwiSs04SV7d3VK0FxNGw8IgmANM2qBAzvpYBLB6ek9VA2AhVA3EJ+oR7Iys17LRp60NXcaR6m4PWbsP2/yyEVuDUttTlNgqw12p/atT3+4w6M3RO7f9AhRjtxpFkzYsMZvpvgh5jTnsiFW+IqygYnmgciwsTWlGj7al2B6kB8mOiDe300bZsuuuuy7OP/98bLjhhgCA6667Dl/+8pfx5JNPYtNNN8WFF16Iiy66CHPmzMFGG22Ec889F7vvvjtefPFFDBgwAAAwdepU/Pa3v8Wtt96KtddeG6eccgr22WcfPP744wjD0FV9t8IzMx4eHh4eHisB9WSZqZmjDPbdd1986UtfwkYbbYSNNtoI5513HtZaay08+uij4JzjkksuwRlnnIH9998fm222Ga677jp8/PHHuPnmmwEAS5YswTXXXIMf//jH2G233TB+/HjceOONeOaZZ3Dfffd1RxMVRq9hZng1BK9UnLYw8bnU5kFhZuRmkshsTJhxrU2+qzYtOZ4kDruGIu7WjdjH5Ja1sQl5aVp6obpy6i8De+A9kodDeuWDqxvX0e+szuNAdgACElwPSFgb3VaF2EjpbJvIQxmYwhvmGVA4f1nX2rIsHu0LAQr0DXFTstPKzMyauuEbrR01Wi4nS25ekw560bIMZkH0qLcUucdGjx5bA/WwiYbdFgbGe5jXhlZ5q/m2AEuXLlW+t7e3o7293VmmXq/jtttuw7Jly7D99tvjtddew6JFizBx4kRFzs4774yHH34Yxx57LB5//HF0dXUpeUaNGoXNNtsMDz/8MPbYY4/WXlgJeGbGw8PDw8NjJaBVzMzo0aMxaNAgecyaNcta5zPPPIO11loL7e3t+Na3voU777wTm2yyCRYtWgQAGD58uJJ/+PDhMm3RokVoa2vD4MGDrXlWFnoPM9MWglfCOLAd9T7S48WISSPZEM0Y7E6zhUk/a0wNSFpST+acljeux3ARTdgy5OYvKr8kI1OmvsxmiWVBGRlNfrwZI62MZKOEC0++C2YmYPIpiTiDuhEkmd1GlntmAEfKMkShjXEwFGoUltgqDdslWey2coM7ZurLKpDZnUKxfyrA5LQAeZP0QverxaBtXrR+HhTLm/EIBKx9pluhNbzbVqq8eOsWKFpdPXnNEWfxe6WJ8gDw5ptvYuDAgfK8i5X59Kc/jaeeegoffPABbr/9dhx22GFYsGCBTGe6HRznmXM6iuTpbnhmxsPDw8PDYyWgVcyM8E4Sh2sw09bWhg033BDbbLMNZs2ahc9+9rO49NJLMWLECADIMCyLFy+WbM2IESPQ2dmJ999/35pnZaHXMDNRJUTQFma9TGi0XsbSGZAe+0XzWJIwMDEmFkY5L8uadc3zWCrLxrjLWIuU80qwMTZl2JcWDOx1zyF53hWXRZmVce07VDsZenGm2Zwp4Khij5N4TLjsoFrBDLjsCUztU5YJLMAwtsKzSZurZ9mlAjKKwhz6PnuSeiu1CmVsPXgJhxElr8tOyNKnmorH44CNJbHbtBSUZyxrqUN/fsXmsl2rt/1MWXDO0dHRgbFjx2LEiBGYN28exo8fDwDo7OzEggULcMEFFwAAtt56a1SrVcybNw8HHHAAAGDhwoV49tlnceGFF660awB60WCGVwNE1UAZmCiDFyRLSGQHY335SH4GzC/tBgcvcd2FL6W022fZ4HbuwYhbhrl9tIy2QVyR62kRk6lQ64y2Kcv8mCq7VVuWQXjyRx24UBmyROYlmhosc5kFMLygiRu4CyxC+b7W4JJoM33FrJw7r27I3YgMWGS4llv0Mpm+alubahH13rRxMOeZNnEOkJoZqJgGRt2wjGOaJLjaW0xMpHF/jYMlA5igFqWfV3S2RsECqCNAvYkFkrIbfH/3u9/FXnvthdGjR+PDDz/ErbfeigceeAB33303GGOYOnUqZs6ciXHjxmHcuHGYOXMm+vXrh4MPPhgAMGjQIBx55JE45ZRTsPbaa2PIkCE49dRTsfnmm2O33XZr+DpagV4zmPHw8PDw8FiVwJu0meEly77zzjv45je/iYULF2LQoEHYYostcPfdd2P33XcHAJx++ulYvnw5pkyZgvfffx/bbbcd7r33XhljBgAuvvhiVCoVHHDAAVi+fDl23XVXzJkzZ6XGmAEAxvlq7pOWg6VLl2LQoEH4wk5nIWzva9xiQHymDAxgnlmWChVfop85Z9tFmYwmtyjIy1dmdq6wMWWYmKJt1kpbMwObIqtxpqkUTnZJKlvOmgdoGeXuhPOean3Z1Ocd54wyTXWX1L8RQ9AybVeYKViV3pQNtqUsXmJZprQMwXxE2XPGckX6veu5pNkY4pAJSd2MhFMIuyIEHXUEK2I+I+joAmpxRtZVA2rx+VrHR7jv31diyZIlilFtKyF+l/70zHroP6BxZmbZhxF23fxf3arr6gLPzHh4eHh4eKwENBL4Ti/vEaPXDGbqbQFYNQk3b7CFSb9D/a6jCbsYG8qyMs2vn5vlFqozZ2ZO3d6tMorUmXONLQ0wRmxm9GBcNtsaAIpRMUvCjFG1qEg1Pn/6nSt1a33LMu1u9NKdtjB6v3d8V8oVVKgIUwdobJepLiDblsjO1JUslra3yneVbQStkGETTV22DdflYjDSL1qi1g+tMnTzbMszlAvDlgJW3cRpem08ZWICDoQr6giXC/alJtmXoKML6OwCVnTEmbu6wOtxPh5xWTevLS+hfHOo8wD1MgaTmfItVGY1h3fN9vDw8PDw8Fit0WuYGV5l4BWmsDGFmBiBgsHucvUoMnzsbuawqI2DnubMp868S9vDNMrEtKitXDNVmxs39YyQXlAiA3Ee4VRPsZZvqC4zA2bMaL9QzOsrm0n091zbp6Lsm7XuAvpZYJSt3w/DdF33RGKONJ1hc+pTLJtbXiNsbYvKFGKd8p49azmVUdG36JCbvFLvOq7qZAxbQOUYbINY8pyFK+KHKeyIEK6oSRnBihpYR1f8vaML6OxM5dfraT0rOtLnKwyBMFaYVfoAH5nbotWIwBA1wSlEq5Qh18pFrxnMeHh4eHh4rErwNjOtQ68ZzPCAISKB7zLpBnsCo5wG+06pZdEcmxZrnBnOc/XPZWXKMCRyBu+whyghvyWB/VqATLPS2aFmX6MzNTJz6kQR24Ho9gQGLykOk6dHgxdoYVecbKSNfSk542859Bm/wgiY8nG7flz5p8jNJMDR9Sx2N0UYn8Jt1+o2LmgrlGUIVRmFrtVmN2M6Tx4im0zFQ4kDiDiCJLhd0FkHS5iZYNmK2CupK2FmurrAOxJmpl6P34+JCzHr0w4EyYu5UgEqiWsxqwHvOa7NY5VErxnMeHh4eHh4rEpo3gDYLzMJ9JrBTK5HRsOCs3JNEBsRitlFbv8tuJ7dKEpfu4FhMc3ejSHzXe3einvS4jay2s8krIzO1ADp+r58tyizfZZ+FywNz8rQi9mQN/s3sjHK9yxDWcrTrNl8LjiuzRyh15zR6smTsYfKbkCapjkYHAvz0PA7pWC5MvKdDIsiNFtHK7dryGx4aWNtEl1MdTNyPuiIEHTWEXYkHkvLu8CWrYgTP14O1GrgXTVSOL5w1r+fysBUKpKZiTcijn8OI9ZzEYBjm5nGH5xmyq5p6DWDmUIv7kZCj5csUngQ3tCPulqo0QGLrVwpQ+ECSxlGmT1kLFkYmrGifRuE+Lyiiu2FrQ8waP5M+2Qzmt2XtXxF2r/MkmJPIW8Jw6WTtvxqHKTkLVmxtH3120EHscxwr5R6XGi23bU+6HJfVooVbVPXUpJrIKLVq7Sdvut3uhoLpj1k1CCeRfG3cHlq5BusqCPorIEtTwYdnZ2xyzUQ/6+EYH37ZBVrqwLVKnh7/LPH+7TJ+88rAXg1VrLWg2RH1OR2Bt4AOIV3zfbw8PDw8PBYrdF7mBk0PtNsZoba0HJoUQZEKZPDyriYqWaXGPJYmQbrbohZKrjsV0iOSR9taUmZrcMwe0ey9MSpEDOMS3SmfGCtYVW6gXnR3W4LG5k65BRhIWR6UfmO4iIYIgNX7ifNZ1zyojJa0bZFn8sSy0dWcZYlNKsbNbTlKJ0ZNLhqK/UZN6OM1/UEG8MigCU0CatzBF1J8LvOxPU6CXiHegREicBQ+IMnlVdCoFqNxfdtQ9SnDVHfhJkJWcrMBSlLF9V6bo7vbWZah141mPHw8PDw8FhVECHwcWZahF4zmGmY0TCWcdTTU0wMUIqNKZKnUJq0R2Dm2aFuD+KQkaubCUXsCUrOivMC/BWZtZrcrenaP83msqVxMUsrxYZFoIG6C9tY5b2Ptf5UyP3ZIiMTKI7eG739qeE2taUxMHSKjFUFBeyL5Fe9v1vaR7cVshpIu6A8J1yWYxFUF+yuCGGH2IqgDtYlmJg6EPH4EEjYF4RB7Hot3o3VCqJ+bQCAqE8VUVtgZGPK2JJ5rJroNYMZDw8PDw+PVQl1zlBvYgTcTNk1Db1vMNNiJgbIYWNawhLkC3GxHnmMTS6TkpzX2RilTkbOOWxmjPpY9Go0T6uDktlm+YA607exLk42xqOUrQug2iUZxZnYLY1NM4byF+VIXjU5/Ua3VLDZz5j0Kmy30t2wtA+g28KoeTIeUgYRkmnhWgKIrQwndjEJwxJ0cgQ1jiDZGJLVIgQrEvfrzhpYZ+JuXavHByeGN8JWploFr1aAaux+HbVVwNuSz9UAUSVws9GWc92FepPeTHX/YpHw3kweHh4eHh4eqzV6DzPDGJQNJjPp9qK5we6KzvALMwb2jEW9gQqxLbY0ahdD8iksi4N9adiDqVXt2CjjkiPPJDajS8EZemmsyROwHJuTQvFRDDIytk4kr9FLx2CzZBTB42dDifdThjEsGBemKExeRmXyu3QxtqGLEbPVGZH/ip0MR9ghmJkIQVddei2xrtROhnXWYjYGQGbz1T7tMRsDgLdVwNtD8ISpiapp/BjBLOe/P3qOmol4gKgJb6bIezNJ9J7BjIeHh4eHxyoEv8zUOvSqwUwhbx9Lv+Jhvty8NfE4kztDozY8WVbFnN9kW2PbVNDExJjLZ+sqG3W2VWwL0CCJQWedNnuLMnIazVM0SquevKq+04roZWFY5CndTsMVJIbIsMZI0WxcFBbCZEOTfNYj2/IyndKgqymSc2kUeefoRfKYK1V8mkVT17lBJwdYPU2TWxHUOFidy/gxQZ0jENsSdEaxbYxgY7rqgNiWoKNTtYtpr0gjCd5WAW+Lf8rq7SF4NTC+03hQ7N3L685sHqsoes1ghgfIGqI2YLjrdDfNeViKyilct3OJSM1nXDIy1Vt0kFJ0GSnH2M5YRkPpV34zLLHpWmzydMUKLjlxVx7zuDIXyhKG9mPdU8gdZFCUGbQVWEbJWw6xGv7aDF9NenEtX9FBqfV5zrnDZQeC4lSRQZJtqa1I3SzNYt7/ioOGKmAcacC7OsCokW9XlKZ11cFqJABePYoPQFlKQiUAb6sgkka+AaL2+HM8AWvRe7gHEKE5jyRT7MHeil4zmPHw8PDw8FiV0HzQPO/DI9BrBjM8KG+8W2zJx56pkaWTptyo9aUj1/JSDgNjlunQzaWnjmZZmEYnMgXKlZokuWa2BetzLbFY26LArNlltFwaBVmeUm7HZZbaCrA7VoNeLW+GfTEsOWUMgg16ZFS06NzUzD+vf5nAzYxPhq1xLe256qI2zxr7It2tM/JSg19EPA6MV+cZGdKwVzhqtIWA2BSyGiJqT7YlqDBE1RC8kuQLmHnpzKT+SmZidDS/nYEfzAj4lvDw8PDw8PBYrdFrmBkAxZgQY7liw/kyLt8tZWBIHlMgu1x5JXVwytDRDAvToFxjXUXzl525UWPTJm1Vcqs2MQ6ufAXUKXS5pYx3LKdzZDiNUYva1xgMf01ZM0atmv2M0yCYCsxxKbfqWRQF5DsZL6V8mlDW8Nhq+MvpZ67k0zeSVIynOeRWBKwWgUURycfAgsSVOmTgYWIL0xYiqqbu1lGFGdu19DtlJRvOR2CImuBPmym7pqF3DWY8PDw8PDxWEfhlptah9wxm8tawm7F9MdRjLdsEW2IM+qTZSOS6SbvqMqQXYmC6i30pIj+vfAMTl2budzPzJFdY/FZ4z1i3WjDV56jKiQZnvk7PmkauO8+uyGRD47KfofKLMGR63rz8FC75Ds8uY7uZ7rke8I/IyXO/ttnJZHTkSLcpqMcHALA6R9AVyTQA4AkTgwBgiBBVQnleBrwLWGojEzIgtDRmVLDDeaxx6D2DGQ8PDw8Pj1UIzQfN88yMQK8ZzHDBaDQatK7ArKpoQDn3eWbPW8AOxqRDJq+eXsZWRuQxn86iCZbDqE+DdZT2Yig7s3bYa+RWVSQmiauMo5xSuAQz0DLGpiirQk+72IYi8gWL5Yoz45KXY6tSqg1ymM2GveAoTLY+uizFC4lnzjULhbGpx8HwhMeSiC0Tf+axfY0wk2Fpg/NKAI5A8VJCErsrqgQxIwOAV5j9faa9302BTHP7QNRzdigRZ4iaiTOzqrlnrUT4YZ2Hh4eHh4fHao1ew8zkbjQp85lPF9oKwcXMSObEwbzQ85RpKcv06PqVsTmhMvXMTdq3FEGzXkct9yppUh8jHHYPRcUXnVQbbW3Ksh2t9o4yZS7oBeWcVdvYKhNDYynmtE1qlH2zVpZj2lPkJufYuKhpBXuNzaYor1hiFxPUY+aFxpYRtjU8YEA1QCQSOQejDcp5Gkk9YJKNydgKCj1NukPVP8M80+wr3ZupuWUmHzQvRe8ZzHh4eHh4eKxCaH7XbD+YEehVgxnTKF1Jo8jLV4CZMUbhtbE3ZdgX14zEpE+BvEBBJqbgrLShpdxWyS553T2KPK8kkUc/pc+Qc9gDUznjnkJlmI4CKHJ5RphslERSYRrKIoNlzyl2OZbzmWi3DfZP530rei8KwNVOGVamKMVmYJJoEku+cXD5axKxOKP0YAqY9F5iEeIowOKXh9jPMM7VzYa032nZjyMeezMRWzDr3ls5KGWf5bFKo9cMZqzbGeiwDB7shrX6m8uSV5yny0e2Ogv+GBcdgAGOd1eJZZluCzxnQDOG2I3U36wdXdM/uKY8GrijrDUEPwzXxrX/hiqdBsAFdc/8/pdpI4cRrrWti7ZpwWU+6yAnry49a9EfTNMSiV5G7wNae5vExWlMSzOvHZqWlXQ96FKd/ByxeEADgFfivPVkiYhFaUbdnTuoI93aIFmektsiRGQQxkm+COARadeQZQY+jQxSVoYtbR0M9SZemM2UXdPQawYzHh4eHh4eqxL8MlPr0HtaghF2hpFDR+JiyEmeuByTRxSmBw8AHiZHhXxOjqiSHOJc4D6g6aeka9+V62BS9ezBsnmLHFw7RDvmHjnQ5ZqOXNkF6y9SVytmZEXrcbajswJyIJ5t0oOmKekRwOrxEdSAoAsIO5KjKzlX0/J1AWGnelQ64iNcEX8PuixHJ8Bq8RHUNb2LXi+9rjIo2pYF73fe/bM9h5nqTPfJdWjlCsPx/Or6ccbSI2CFypm+y4O8I6HJlO/G5F3IQ/IuraQHT96nwlkjfuexLPvNEW9WKY4aB+tKjlpifCwOU/vl9JGeZGjqSNmZxo5ymDVrFrbddlsMGDAAw4YNw6RJk/Diiy8qed555x0cfvjhGDVqFPr164c999wTL7/8spJnwoQJYIwpx0EHHdRcYzSJ3jOY8fDw8PDw6MVYsGABjjvuODz66KOYN28earUaJk6ciGXLlgEAOOeYNGkSXn31Vdx111148sknMWbMGOy2224yj8DRRx+NhQsXyuPKK69cGZck0WuWmeQMCkDkGsKRmUv6OT2vnNPKZPI68lnzmPJqaMj+xZLHWXeOwWl3Gvnm5evWuhtFQeNaqw2Irp+t/TWbFzELBWJmBSz9Dn12T75zBgQG+xn5rBAWiNbJkplxLMMUGp9JnXUmQ8inz6OLKe8Wo8wmZer3L2Ofobedpd6WX1t3G7CynC6pvTdEP6B2MgwxUyPzAAiSghEDUKHGwkx17yaVNdJ2mecuk8GW0H3o6WWmu+++W/k+e/ZsDBs2DI8//jh22mknvPzyy3j00Ufx7LPPYtNNNwUA/PznP8ewYcNwyy234KijjpJl+/XrhxEjRjSse6vhmRkPDw8PD4+VALHRZDMHACxdulQ5Ojo6CtW/ZMkSAMCQIUMAQJbr06ePzBOGIdra2vDQQw8pZW+66Sass8462HTTTXHqqafiww8/bLo9msFKHcysv/76mXU3xhiOO+44ADHlNWPGDIwaNQp9+/bFhAkT8NxzzzVUl3UdWNjChPEhbWGI3Qty7FzEERlsYkAPss7usg/hzLKcbskPhoytjVKXbnfjqFtnj2zlMoxTiw5Xfda6i+qho1E9bdDT8vKbYLCdEOcVm5YOoLIiPqQNTGIHQ79XVnCE5Ai6ELu/JmwO7QfU44/ViD1NndRNwtQDAOOpjYK0yeni8dHJUV0eH5XlHJUV8SH160ztb3LtHPLaymJ3IvN1MxT7lpz6GrIHyrs+iy2VZO0yNldcORRZpusx1GFVlbBx8n1GbA6p7R8YEFXjo97GEFUZomqQHAz1tuRoD+QRtQeotzN5RG0MvJocFVU+rVfAar+ktcHqhNGjR2PQoEHymDVrVm4ZzjmmTZuGHXfcEZttthkAYOONN8aYMWMwffp0vP/+++js7MT555+PRYsWYeHChbLsIYccgltuuQUPPPAAzjzzTNx+++3Yf//9u+36imClLjP97W9/Q72emjA9++yz2H333fG1r30NAHDhhRfioosuwpw5c7DRRhvh3HPPxe67744XX3wRAwYMWFlqe3h4eHh4NA0OhqiJdS3hcv/mm29i4MCB8nx7e3tu2eOPPx5PP/20wrhUq1XcfvvtOPLIIzFkyBCEYYjddtsNe+21l1L26KOPlp8322wzjBs3Dttssw2eeOIJbLXVVg1fTzNYqYOZoUOHKt/PP/98bLDBBth5553BOccll1yCM844Q474rrvuOgwfPhw333wzjj322HKVkVmydUsBnZVghs8FylG4YsE0ZPuSJ7+kPBpXIleWLb3Es1jK1qVo3p7mF6lerlkc9UyJ1PN01mud5RKWgiXMjJDF6tDsYlIhPGBpTA5tRs0jnrIvdEJO+gG1wYnlqZ+Fl4lEwFMZpJxyzaB6cICzdD8/lqZl7LX0tinaJ3TjjoKzbdPGhK68pZDoYYwfQ1HmmlvFItC+WtTOx1J3/maeDHJ7A3JtDJAen+KM/tykddAXKWUKtbpoGST1in5Y52o/z7sv3QC6VNRoeQAYOHCgMpjJwwknnIC5c+fiwQcfxLrrrqukbb311njqqaewZMkSdHZ2YujQodhuu+2wzTbbWOVttdVWqFarePnll1faYGaVsZnp7OzEjTfeiMmTJ4Mxhtdeew2LFi3CxIkTZZ729nbsvPPOePjhh61yOjo6MuuHHh4eHh4evR2ccxx//PG44447cP/992Ps2LHWvIMGDcLQoUPx8ssv47HHHsOXv/xla97nnnsOXV1dGDlyZHeoXQirjDfTb37zG3zwwQc4/PDDAQCLFi0CAAwfPlzJN3z4cLzxxhtWObNmzcLZZ5+dOS/jFeisigBZ31XOiXxMK+NiamBOAyyTmZwySvkSeZ3lTGlNsjx59ZSVVTpfIzqUgDVmhawYCgsiQe1AeBL1lLAqSnnAyNqwxM4FiG1S9DRxzfFEjVtnl4zHNiqAysaI2B1CHoviWXIskyEK1WtkrtmwuOwKsmyo0JF4M7GI5AuIjQeQvfcam5RhckwoYMNi+p7xUkL2fB6UNgaszGzuVhVFrrMgaFRdY/0uNsYqUzthkw0oTEq3w8DK2Wyb5PNU7zn9Is4QNfHCKlv2uOOOw80334y77roLAwYMkL+zgwYNQt++fQEAt912G4YOHYr11lsPzzzzDE466SRMmjRJEguvvPIKbrrpJnzpS1/COuusg+effx6nnHIKxo8fj89//vMNX0uzWGUGM9dccw322msvjBo1SjnPtIBJnPPMOYrp06dj2rRp8vvSpUsxevRo+2DFsmSk58stR9OovrqCrheVSZ6tjIaGl4iayGutsyfr6kEYaWhtKUVZ+om0cyBpYsmo7vgh4LHBrZAR1OLTQY3H5ekPrNgXJ2Txb4VhUCWWgeSghQ4wGFIjSQbwIN29mLpR0+UuRVfZAOqylJ4mddL0Z5kPqV6KbH1Zt4HfHduPc2bgYdMjtwJa0LF8QX5obQOnMnANKOL0dBBTbvCRU0+ZfNpAxjSIsi8tmeWU0pcxRGHS/wOWPr/E9bsHh1qoN7lrdtmyl19+OQBgwoQJyvnZs2dLImHhwoWYNm0a3nnnHYwcORKHHnoozjzzTJm3ra0Nf/rTn3DppZfio48+wujRo7H33nvjrLPOQhiGWFlYJQYzb7zxBu677z7ccccd8pzwX1+0aJFCXS1evDjD1lC0t7cXMn7y8PDw8PDoTeAFWLETTzwRJ554ojV99OjRWLBgQSvVaglWicGMCNyz9957y3Njx47FiBEjMG/ePIwfPx5AbFezYMECXHDBBaXr4KZZnYWV0dNzg+YZ5AE5rEyDbEzhGaKLNeGO9FbWlZdWpo6ScpuC43lXAshBY18o40LkKMsmSN2d489cob3pxntxPrr0Q2aPIly8+C7XmTg4ndkS9kWuVBA3Vbq8oxjdcuZsY+vSpM5iSoYo26gKw0OXURhZlqITz2R5Sq5A5RqaZvU1lbGltdoQ1BgskVx3YYPgwstD3JhmWmahcuh9MbaXuCdl2svGpBieJWOaQbaZ+THVYVaMM6T9KyDGxj3IAvf0MtOajJU+mImiCLNnz8Zhhx2GSiVVhzGGqVOnYubMmRg3bhzGjRuHmTNnol+/fjj44INXosYeHh4eHh7NI0KAqIllpmbKrmlY6YOZ++67D//6178wefLkTNrpp5+O5cuXY8qUKXj//fex3Xbb4d577208xkyOrYv1e846vpJmqtP1PU9eA/YzuflsbdAimTpawvBYZFJX2sIu5siZRdrSE1YmE0wM6SxP6hCZL4fpM0dGWRog6OIIaoKZSV1HFXuuhJWJwsSmJSRpDAobo6hvY1PEtdjgejaIvMyGgDCzA0xvR023mLDI3kwuguoV6Se258igO+03umt2Q8HtXGrl2HcYzzXDGBXMK/tgnYPVbJnivkbvs/OZM7FxJlbIFrbAIiuPWcotp6STj+IagiIdrDWoc4Z6E+xKM2XXNKz0wczEiROt63iMMcyYMQMzZszoWaU8PDw8PDw8Vhus9MFMjyGZ2RZmY0QZ+h/u2a0ckhWxp3GwMUXSnecNaDa4XtE8znpaaadD8wtmQK+nEU8XYfsiGJEAxEU58SjSgtcBkF4+ug0NAMVjiUVc+07KJEG8RBvUq0yZ+UrvooSJSfuiqQNxqZfUA1A9jRgzeh7R7Q1EQRloT/fQYtl2N9nHmO6FrY8zTuxi6pw8h4kdDw3MZ2F+ss81I5/V+jK2cZY2sdqnOPpsrtdQUTsZGxR53Jpm1IWcN3paaXLENiNKFQ0QA7onXkY/F6NjQUMB7yx5e5Ls8DYzrUPvGcx4eHh4eHisQuBN7prNmyi7pqH3DGYMMzIn+1GQSXHayDRg/5KbxzIQ7wnPo0L1NDhRaInckkyVsvaelBWB3iTjUgMCsgGtwnRoodAZiO1BVxojJt6wMWFKBHtjswHQ2EEa68X63uLcyhronlSsnl4rD9MLZzDYktSFDkSGidmQdZmm29p/vR6YbW1kcaWduPrAafZLuu2LqobZdoJnGKiUraLxdXR7O+Wa8hiQQrYd2VNFtg6I89kZmSIyOEMaFDFkYBVLXqNdjCpH1qn3b52lpMxhERiuycrGuGLZUFkM+e3usdqg9wxmPDw8PDw8ViHUwVBvwhe8mbJrGnrNYMYV3VfJU1Qe/dICxqWQ11KZ9eoSdjbdsgVBI/IbeS4ts6uMPMfsmXFIOwxW11gQ4ikkvZkIY6HbkKTeSjxrX4K0nOKl49KbltEYG4XBoddCmBqdzaHbFMQZhMJ651LLyCZghqyuvmZiBrTnkIFn2BlbjJQ4LT3vnEUb7r/uScUAaQMVvyO4sjWEKQoyZXLodciqDMxQGVD7qvi/Xf8M20zvt27XY2GSaLmMvZElP9Uz1SvVV2cE9XxOxojoSe1o9DJMz2+RJ8sl7clDls1H+mrP2sw0Z/diIkN7K3rNYMYK8oI1GQ5mwMoNZFq9tNTQFgJlfnxyYKN2Wz5gadUASxtkSGj0uHLbyYCFGgMjgmqwy9N9jsIOgNW53HIg7OQIO3kqg/xAcQZElbjGqEqMcDOjBPvSiAJ9UMNIJ6WDAsaUgUwjg2GT0aoyZtCeH8VgXuvH6Y8MEGhvZdP1xm7BdBCk/R6RH/zC/dGwfCFuQxx8MB310OUnToynmbZUlYFtEKG1pXObBVJG2Zmcp4MeMJZdNjPV7ZgAGAP7ic+RVh+Rmx1w2X9lc5e+DHIyAxnbWNehf7rUZaiUTA78MtPqCT+Y8fDw8PDwWAmImjQAbqbsmobeM5gpyjrYmBOdmcxjcFBidkhRhpVplI1pgb4NB/PLKdMMxWucUZH7xvTZKa3XphdJCGpA2JWyMSyKg9wBwuCXfufx7tZAlguumC9SukQT/lwuJ2i6WGeP+tKHTjuRNJ39cLFtNmYrE2TOUp4aWbvusZj9qyfJZ8IsBTWYZ/ZQ2ZKMsbcmO7MMKORHhmuAYO24cj0pa8PSXcFRoD8T5kS/LyIoYrwMqlIRAd0KQp7nYGCp6zpz6GHp4+J+MnKtylIPYSazbuYGFiUPBpbI6qLtWO7KMFCm5950L3owQJ4JERiiJuxemim7pqH3DGY8PDw8PDxWIfgIwK1DrxvMFGYU9PX+ImVsdVjKNBxgroD80gbHRep1oYFyha+/4Ewvb807w05x9SsA6bpMDSJFePeYeQGCzuQ72W4gqCe2BESm4u4qGJaAIQpjWxlZsSOgW6QEuaMXY7E90NvUwEZJGxSapM9uXcwVrcfA7ihMDXVfp0amJAAbA1JbHgZAZ0R0KHYcqk2QksXUJsl9V+TrTL24VxozpWyMyblan2jTgMe2PZSpsb1HHMj7jVINfbX+I5Uu0Y7E9oVp7asYXOuu/konYqk6ebszS8MkrtoDOexkjHVq50wBEWV28hwaVfK2Mqs1et1gxsPDw8PDY1WAt5lpHXrVYKYZRs46aHfZtGjpTh0sNi1NeTqVkVMEBcv0iGeTYxZltOFw3ZtIOxcRmwSueiyFHRxhwszE9gPJLLKmsQSAMlOVm0Im2yOks3WmMCIKYeSYZTNynS4PFKvbqwZOKy7ILGbkO1gZIGU2XEyFHhxQmWlTLxeZP21XKsPGLDGNdeJMSyPpuseMKzhb6knFwDm11+FkOwzmfv4NjJCsXLP5oSwk3W6jyLPHNIZF6ce0LqqbqD5Q76u9PpaVQ+pPv7B8FkeDiQF0vesUQlNnZFcyGxOhye0MvM2MhB/WeXh4eHh4eKzW6DXMTJ43j5wBMu07tAmGYVZZ1P6kEDtimW3b6s7IdqXZ6szTySarQRktQZE6XN45NF5MlNrFSAYkKRt0QsaOYbXEZoZ4LKUyeDrjhdp/1BglLGZpivSf1GFGMWNRYonIc6q9iAw6V3DmqTMWut2Mjf3RGR1r/A+9vsiWoF4fD5i2pUGqV0TeXhlbCWpTpNsXQXtebPYWOutE1aQNkmFsyPWRa2ERV+KZ6GVS4ep3HtgZBBp3x2mbo7N1REcWpfGR5FYb1P5FyBf3JCRyCrCmyr3W2TvyXVw2S4RyzaiNtkFkm4YbtsZQPdK49RYb83czeJPeTLxHXrarB3rNYMbDw8PDw2NVgt81u3XoPYOZZIbhZEdc/aKRfASF402Y8hZcG7amFWGECBr2slpVQJgCo/0BkG74mHwWdjBBpxbDg3ixhF1cTWPpdJGHDBFLbTgUNiZk0rNJsZfRkImFousvZ+AsO1vPMA9MKWOuLy1EGZYMS5MpaGYr5SzbZntDaSaX7EBjmpI2ZRFHFLBcOYxzVcdAM8twXStlRJhaxJlGy9P7pjyTOr1lrteUJmPOsHgDU+lZRRgLVjewS7puMLM8kunTPYqQbtGZ2QrD9HxpOgFaGcpaIcvEKKSU1l6KbVMjSK7Jeu88Vmv0msEMt7xgJIpQtRa5ugxjmiWPfq7IQMYmt8wAZpVZLuoOWKhv6lYddsUGvUBs1Cto9qAGsDpXtxiw7DnDGdJ9XlgyUKG7XBN6ni6b0IFORl/iGhtvfZD8iHGuDlAcA4q8JaK8BJ78cS5V2QYU2vKOqc+KdnL1Qbq3FL0XdBCaaUchn4s2MwgWbZt8MBr2GvQQ9VEZJrmAYWlGvxf0HWMa+Cm/6LpCsQzbRuOMLIcZjXlpmvzCwAOufDdB2T3dKEfLz8x5dCPirHKONCJXaTubUa9hB+0yE8vuhvdmah16zWDGw8PDw8NjVYJfZmodetdgxkXBIjtiT+lOTYaet8gsuChL46izUL1lmZ+i+hiwKjxHTspZMXKEOqtXZtIMUZjM1JMdrZVgeLohqFwySpeP0uURopdpthjx2KhVGAprbsgsSIvxkNAvkcZkUPaF3t8SFLxVXvJdGBdmN/kzV8KZNknW+mpqqJpcC1nasOmm7wKtu24btylwMZhczM6Z/J4yGTxzzzIsQCJf3wpCYZ7oDtuMZVkaB+ui1EWXheRnU2NpYoqwMbQ4I0s9AbcbHOf1LY1lsm2OypDeQxbRYnofz6lQ9n/tAaDPnmWpSuhnCm/A66vAi82jNHrXYMbDw8PDw2MVgd+bqXXoNYMZfUaXgZgxpRO2YvYqja6/FrWTyUFRpqUUY1S2rkafp0YN+agIOuPTZ6gJGwOkrAzddE6wKqxC7Cyi2GbGFBiMIbH3SOxkIhq2ntjLyEszrOkzzmP7F6T1SflJH5V6KTNyetGOtX9tVuxyN87YO5hYjkQGbTcO1V26MPNHq+MA14MVWvJZZVNGxHZdIs1wTZl6aQQ9UcQonyOyGq0k2QP1uyrU/DljR2JiY0z5WoC0jycMDVHOuVGjQ5YCsn2BS5bKPLvb2CpAs5mxbZJq+z2IQvP57oBfZmodes1gxsPDw8PDY1WCH8y0DoUGM1tttVUpoYwxzJ07F5/85CcbUqpbkGMvI/IYyYJG7VDKlCvAzuR6Wrnk5ellQGFvrEbRClmWWReQzGBpm3HIrQsyG+olDI5we824YCMO1CU2SZQytWtQ2ozahEjGTytAZEhWxmAvwg02OEZvkQSR5d4pGwXqzADVSWcyNJUls1SCXqPeWJm+b7JN0WCbYcuvcgsBdz5YWC0u6rDY4aRsFzPXA6huyLo8TabN20h4rumMDNXFYCLkhnbNNpd0ycIpQRhdN0WzV9HPmVShbUnZkSiHPS8KJUgfaSzB0thYdo/VGoUGM0899RROOeUUrLXWWrl5Oec4//zz0dHR0bRyHh4eHh4eayo8M9M6FF5mOu200zBs2LBCeX/84x83rFB3QXocFJ1IarNuGyvSSCyZTDkHK1M6MF4eY5TT90vZ76yM56jA/dPDpwMx8xJ0QQnbLtkXPT+zrJsnkzzaF2j8GCWmiD7z1eQrs0Ntxky9gbjJ44clOhs8oqR8i50DZwCENxa1v3AwCBSMayyRbqOQKZA9Ja/Z1n9yaAd73JzkX8Kg2TZEdL3/XUHnlMt06KCwXxoydl0Wjx0lrhBUBoza8pg8royeSNq7z8rSGBkcZiyXrcOcaNpY0hhUMDDIEDGeStjX8RBpW+jeUuCgWzUo7Gyy2abCynYz/GCmdSg0mHnttdcwdOjQwkKff/55jBo1qmGlPDw8PDw8PDyKotBgZsyYMaWEjh49uiFluhVFbGb0/AlMszUns2I5X4j1KMCEWOtukEUpzMYUbD99xmOz7XB5Ilmhs2s5bBvdsiCox5F/xXcxExPeQUKec+YeQPVaIvYzutePomNkOC/0I/eVRZC2NpQBycRACtJJbMazydEmjNgNKddKQv47Y4yQGa/UUc9jrNjyGVo/MFVtYUX1slKG0Q4lX5ZNnlE5jc2Q/Sy5Z6YoyBm2jKf2NzaGRuSntlYKS0PudaYaXaSuP5Gh9Nscu6Ui7z7FLkaTybRCtjanrJDTbsdYLpFNog3HjBZpxyj1Wgy7OFhX/IV19hw1Ez+OjbMrJQirNR4NeTN98MEH+Otf/4rFixcjilQ/wUMPPbQlirUacpmJmV92Io8CFzVdcCDSknJFKHLTQMdVZ049hfRywGgcmaOHK9S4dbCjv5QB40tbLjvYdgrW9SQvQ3pe7IuUKqbmiwxp4ACzBYgz/nob0mkoee2HOfee0/5DdNEHUhLaMknGaJJDMW7ODOAsyxzK8pxlIOvqN5kBiSZfya8t87kGy4WZenqdth99fZnPJQfqIMa5d5NhACTLM5mk3iu4r9u1t1c6GMsKSI137Q3nGkhllvu1fuPajiAPmWCVpC/TbUIAIOxMBzBhZ4SgIx7EhB+vKFVnM/DLTK1D6cHMb3/7WxxyyCFYtmwZBgwYAEYfLMZW2cGMh4eHh4eHx5qJ0oOZU045BZMnT8bMmTPRr1+/7tCpW8BJgDPbrKlRF+tWyCht6Fs2n4aiS1WFaXdrRVo+xxJR4UkGQ8qwmO6lSKvFRr8AYtdrjnQrAp5urieXdxD/V9TiUI18Qyjut5Q1sOnPQ3WCmcsSGFghBa520pkBIk9mMSyFSVYrqVdhS8hsV8z8lVUJmz6W2bm+1MNt/UNWYMinydTTXUatioqG9qHXWrj/a8sa9Brd95vJfIpOej10KYmrjI7VsJd+5w49CvZNnRmjLIi+tJy5DhdrZ6vfFPBOl2tIE20EQFlmQhTvei8NfTsjhCtiNoZ1RQi64s+8s2avoMXwzEzrUHow8/bbb+PEE09crQYyHh4eHh4eqxr8YKZ1KB2iaI899sBjjz3WHbp0K3glOUL7gcByMMMh5DL1ABz5tXOZcrCkOeQ489Hrd9Vn+gzLDNFRhxEuGabvDl1M7RQnxgd1v5ZHYvgr7UOSI6oA9XYWH20MURWIqkC9LU6j/SKqMESVlJWhujAx401scpT6yHmqt9haw3iEsVu42CpB1mViLFzt5rpPou8EpO8zqW5cJ61b6286ZL/SrkW/Vlk9aTPdJTzTHroM/bpoecuz6epbwpbKdCj6iGCG4l5Y9Jd5yPvDqn+R59hy7+PNOplap+H6rcjrh1KXVEi2z3N5SGN6QDnHIq60caadSrxPMu8AIYqrhyJfyRifYDVOjig+ogg8ZOAhQ71/e74yqylmzZqFbbfdFgMGDMCwYcMwadIkvPjii0qed955B4cffjhGjRqFfv36Yc8998TLL7+s5Ono6MAJJ5yAddZZB/3798d+++2Ht956qycvJYNCzMzcuXPl57333hunnXYann/+eWy++eaoVqtK3v3226+1Gnp4eHh4eKyB6GlmZsGCBTjuuOOw7bbbolar4YwzzsDEiRPx/PPPo3///uCcY9KkSahWq7jrrrswcOBAXHTRRdhtt91kHgCYOnUqfvvb3+LWW2/F2muvjVNOOQX77LMPHn/8cYRhD25uRcA4zzcXD4JiBA5jDPV6D0YcKoClS5di0KBB2PDbM1Fp65Ndn9WvvpzxvIqcmRBgZ0XKeBUVtY0plM81k7PMwl0QdgZlglylws110vNiw0hj3cnGkqyW5lWC5HWpZa3eHGQGqATCM+SlLriK23OgMnWp3U16znSdnJYjjAZnjmBehnZz2pcYvUYc6Vz9XNTGIi9fER1dba+c1u6TNXCdxnQU1ctpP5PXP2zfbW1newYMMpwu3YBiC5ZrwwTtPut1Rdz67OW+h3SGx3GNRm8mU0A+cu1F+mH8PuAIu+IT4Yo6wuV1KSuqxg9bF+/Enx88G0uWLMHAgQMdghuH+F36/F3Ho9IEE1Rb1oG/fPmnDev67rvvYtiwYViwYAF22mknvPTSS/j0pz+NZ599FptuuikAoF6vY9iwYbjgggtw1FFHYcmSJRg6dChuuOEGHHjggQCAf//73xg9ejT+8Ic/YI899mj4eppBoVFKFEWFjlVtIOPh4eHh4bGqIgJr+gDiwRE9im4ntGTJEgDAkCFDAECW69Onj8wThiHa2trw0EMPAQAef/xxdHV1YeLEiTLPqFGjsNlmm+Hhhx9uvlEaRGmbmeuvv97YUJ2dnbj++utbolS3gCFjIxPR72IWXNRmxrXma0kz2R9Y18kt+crYxjhlamvjxvww1G1pW92mQi/HLWlOEJsTVksOwr6wGhB0kqMLcsNIQJ2tiY0lpU1EXTuonQTtK8SuRNjLGNsx2SRS2GZFpE+ZGC/j9RvaX16n5mChtGugfdZscBTdbRCMhYU1MMoLs/ZF9FlSPmv2GOL+KHYOprawnWeqPhlmiupagbSJiiqExTG1nePZEvZQGXss0n/0fpbRmantY3zfGK4184zJz8x90L5paSt6H/R3gfI5iG1KXDY2pkOxr5E3CGpfs7JUDHT7AZVtJmkBUw/Le42HDPWqOALU20PU20NEbSF4NQCvBoiqeS+mVQ+jR4/GoEGD5DFr1qzcMpxzTJs2DTvuuCM222wzAMDGG2+MMWPGYPr06Xj//ffR2dmJ888/H4sWLcLChQsBAIsWLUJbWxsGDx6syBs+fDgWLVrU+osriNKDmSOOOEKO5ig+/PBDHHHEES1RysPDw8PDY02HsJlp5gCAN998E0uWLJHH9OnTc+s+/vjj8fTTT+OWW26R56rVKm6//Xa89NJLGDJkCPr164cHHngAe+21V64tDOdciTvX0yjtmm1T+K233sKgQYNaolR3QJl1JVA29RNxCUzrtiSdls2t0zIjp9+V/7aylv7RsJ1NI/kcepSB1Z7GZi8jqpbr9sh4Rsjou6G2mWQt3b5A2svonidQ+0WGTdHvGdnEjs4oWfLdZgdCzyv1MaKSxm4xDuN0I8+2KROfxtKnjbYSVGdit2LtPjZWhdQr6lK2jNBkyBgmtDxy+qMOza6EEz0YvZ+h1uZa3zKxBMq7g8FqQyPvnUk9vR25dq8NOhlB2k/0u1gGz5Zj2TI8TBmkjGiHDZFUq8APlmRjoLUT52Bgyr1xgtrF2HohY5l7IfOa2kQgZOCVhNnhMesEALzecz/InDPwkka8enkAGDhwYCmbmRNOOAFz587Fgw8+iHXXXVdJ23rrrfHUU09hyZIl6OzsxNChQ7Hddtthm222AQCMGDECnZ2deP/99xV2ZvHixdhhhx0avpZmUXgwM378eDDGwBjDrrvuikolLVqv1/Haa69hzz337BYlPTw8PDw8PJoD5xwnnHAC7rzzTjzwwAMYO3asNa8gJ15++WU89thj+MEPfgAgHuxUq1XMmzcPBxxwAABg4cKFePbZZ3HhhRd2/0VYUHgwM2nSJADAU089hT322ANrrbWWTGtra8P666+Pr371qy1XsKVwsRD6rBVklmLyeinAzGTqoDrkzT5dbE2B/IU9L0x5G5koFGyPPBmyzcnMkUZU5QwAtf8IID2Igq7EdqaWfpcz/sS+w7i/DyNsBl3nN4EBEZ19E0ZB8fSgTBNT753CPtC6NQ8eJZ/GXGVYOdI+Rg8aqhcsaUqCWkZRjTAHzr6j2cPIj0nMH/p8ZZ5Fwlg4+70BQRLtWWZnMWsHQNmPSsrU74WBvcu0Pyz5kOhraXOdoXK+W4qyv4x84ZAxX4zemiIbvU4XQ6PfawebR1kmncEp1M8SXRS2SsjQvLas/U70OZ62gbCjY1oEYNS53F+KM4AntjL1qLT1RcPoadfs4447DjfffDPuuusuDBgwQNq4DBo0CH379gUA3HbbbRg6dCjWW289PPPMMzjppJMwadIkafA7aNAgHHnkkTjllFOw9tprY8iQITj11FOx+eabY7fddmv4WppF4cHMWWedhXq9jjFjxmCPPfbAyJEju1OvloMajzmpca1M9qTyL98l0DXIKNAP85alygxamimTC8fAUMmm/5iKAYD2YlVocPLDJI0KkxNBF8DEUlJdc79m2WuNyKDFuMwE7TeGfBEvaUUkvRd0CYpAX8ZSytEfa9c7VP/h066NcfW/EdyenlkCoTrSa9TvX7YKBDJ8vJYmltyTZQ4pShtAKMu/jsESq5vbTl6LZUCnL7HkDcgAZAL/KdnrhroMfUukKbfRMJixDUIyulnS5QaQli0P5Clyf3U9lL6VKaiVN8ktes069AGjPO9SSCuvXYvybPDUvZxXmHItUbLMVO9BA+BWLTMVxeWXXw4AmDBhgnJ+9uzZOPzwwwHELMu0adPwzjvvYOTIkTj00ENx5plnKvkvvvhiVCoVHHDAAVi+fDl23XVXzJkzZ6XFmAFK2syEYYhvfetbeOGFF7pLHw8PDw8PD49uQIGwcjjxxBNx4oknOvP06dMHl112GS677LJWqdY0ShsAb7755nj11Veda22rJPSZeB4cMyPnrK4B5C4zuZYXysp11ePMZ+GU5fdixTLsAFfPB53msmJWzIDYXTlJo+7YIkiedM92zbgRLzsBiN2paR66zKEZhGZm3fqlGILiSVqf1lHknhqYvWyFWRnOmT0t7mINbdDYTV6wLlrWtGTDyJeiz5SNUREbe9oMzZ3LcFRPUoeyeSSQYZOU4g5mSWHALPXK9rDon5FrZdvSTCznJllWzFxquqEvrZHztiVFkZdWVCSoYZ4zhsJAMQZOCtCglNIAuOeIGfAml5maYXXWNJReHDzvvPNw6qmn4ne/+x0WLlyYCdbj4eHh4eHhkQ9h3tPwsbIvYBVCaWZGeCztt99+iou2cNleZaMAa7PhQvkpirIxeb2rwJq3Is7BLhQelOfW2eAjUcQ2hqs2LMp3mr8GhB3xIfMKEZTZYFCCyCkGfnUgqKdr4tSFOxKbKUo3bibLBTwOqCYuyUqI5DElenZ9C4NEf92mgKYBhA3g6mdFjzwmjLIgtGgB+5BMWd0OgRE5XL3XQGpsC7J8robgz+pAmYzC3ZG2q1Ymw04VuW4DlGsjM3yuuzZb2jtjcKznIWyMYvSst5eJkTHVbamLMya3PqCfdX2KuNrbbIcUffU+Y4HRnsZ2b7Tnwmn/RdtLtHHA4mUWomfK2niGY3VH6cHM/Pnzu0MPDw8PDw+PXoUIDNb4OQXLe8QoPZjZeeedu0OP7gedTTZWvMUZVRR1jy5sM9Mo22JDicYT4dzjciQhStxmhSt1EqpffA47gXCFEEKqpJ4kPGFlDJcng4aJmRdlgFjMxkg5+saEglAU4d7ljJZkc7EqGmS4euSU0Zk2C/PGmZnRMlee891UhBlUtPQ1WwA8K5sFS7/VZ/LidBk7HCJTt8WQ1RD7FhNhYLs1+uw/w9LYWC0DG2mSmbGlEnkE2yXK6XZbJrbHdSGybksGU6OYWKeCrDKHdk8VBiTLmmXCJVgYPJ29szKYDKlHV8TBK2laxJgkYahXW+xOz431did62ptpTUbpwQwAfPDBB7jmmmvwwgsvgDGGTTbZBJMnT16lIwB7eHh4eHisSog4A+vBODNrMkoPZh577DHsscce6Nu3Lz73uc+Bc46LLroI5513Hu69915stdVW3aFn8yhqM2OaFZjW+JvtQ2VsL4qwMYbpRBEdC89CTPHbDXYTYtO9VInY4wjIBrULu1JmJuzi0uYFiGdWwvaCxvjgAVPDtiuMQUIvJMpEJC0KmbLJnuL9ozE4yv3V7rXSXPS80JGl323MBoXrHukeSq44Sc6gZDk2CLr8IjDFIckEi6NVkJk6Z4iDIrJsOcZVtsKpl61NAaAiJ9oKkyc2k6XMoWmGL+Rn7DmEvjYmVX9/6PYupKxuL6LY5GjfjXYeyD5rihxdRWIzYwPt92k5Lc0CZYsRrR314InMlE/XxVGXHhtKrzdlDlnaEZCwpZQCUm6wHxiszig9mDn55JOx33774eqrr5ZbGtRqNRx11FGYOnUqHnzwwZYr6eHh4eHhsaZB30y8kfIeMRpiZuhABgAqlQpOP/10uRHVqggaAZjCyUxEaR6uzZKUmUULBvSFZ580RkLRek1r4kRGQ+wMsQugM1/hQaSwMcIupjP+HnbypJzqeSTkxipzyGXvChCJDeFCnrAgLFGJeifE4cnFzJMr3jQcrJZG+WRkM0keAvp2BqZZH4AMyUE9lngl/e4M9W6b1Wt5aZpiMyP6IJ39U6Xo/TbZZVjYGStyjEys4vTnhuYjE2aXCoVjzhi+y2c0zGaU90MrrDNDCvtWRBHBqhAbr4xnH20TEudElyPrpZ815odrLFNsr+bWlJl+ATN9MD1hJf00zyB7hSoZovTPnHJOFGEoOS/8fpPvgx5kaLzNTOtQejAzcOBA/Otf/8LGG2+snH/zzTcxYMCAlinWcogfKMuPDM2GJBsTLxrDw2B7SVvzFYVj8GKUV2ZAI4WU1ImKEYOPuvYSFW7OSdA66TpdT92twxXJ3ijJUhKLIANVRWQgINLEkhPj8TIUAERRvFwUhelylB7KXrlm8YLiTP2FI3npYIbr5fT2pXS5NiDSl51M5UoNfvUlj0BN4lE2W6asKdFWv2upygW9TclAyuo+q7tV8/Sjrov+O6jcA5pJDFBMu19rgzsl6B+ynwG43bst1yUGq7pBqlImZzlI5HG5HivvHyqfpwP9zECKLrcU3R7AopuQIYLxmZYYKRRX6bz3TwODGJmk9zm6o7Y2sMksL3us1igdNO/AAw/EkUceiV/+8pd488038dZbb+HWW2/FUUcdha9//evdoaOHh4eHh8caB8HMNHN4xCjNzPzoRz8CYwyHHnooarV4+l2tVvG///u/OP/881uuYMvhmGkD6oxHTib0GZpJDi1bpn5jHstSUplZNoVJdzojpZM0x2wQSDcRZPWUjQk7obhYs3p8DgCCrpiNEWlBF11aShuWBwxRFai3JUwN+ay4egtdxOSTuEDL2bg+E07yZZY6BEXeRZiZUGVc4gykLp2FIMsEGRdjw+y81LuHwzjdyGxWaTICpepb7rUiQ6/XUj4XljbIKyLrSu6horOJiRH5aR4H86GzftRFX1+mUfLZ9NdYGto/rUuMWtnM0rfoj3pAPlfV2rOQYaNIm4gfPt21O8NOm9bslHQbLWXLn5WVaROiS25/s9RjyqMYl4MBnKeMb5QyNTxgkonvSZbGezO1DqUHM21tbbj00ksxa9YsvPLKK+CcY8MNN0S/fv26Qz8PDw8PDw8PDycaijMDAP369cPmm2/eSl26F8y2CO0Y2ZJZhHN5u8jsLU83m7xGbWRy6xSVqafzBvoyncx0o0q8JQAA8HrC3hCGS7hY19tYbADcldYtDYXrsbGBmOHSGWcUMjBZQXxervkTZsbqHouUmTGyUKbZrKiOunMLdsfE1DDN5qIkO2EFZRnI9WVm4SIbz85unR4POXYbgFl/Y1BE3R6IG77Tsoa6BESfcW0KqWyRIP+Q+8Kz+US6qW6RL/c1YbJ5IfcmzxjW+LkZ6P3d1PdY2u6KQTQpn3tOyswqngmXUJDNM9mQKYy4CxZWUen/yrPNM3px2mdKG100D+/N1DqUHswsW7YM559/Pv70pz9h8eLFiCL1zfTqq6+2TDkPDw8PD481FZws/zVa3iNG6cHMUUcdhQULFuCb3/wmRo4cqWw2uVqi4DTK2WdcTWCRX9wV21VxQbhmSqYZp6Oc4nosZu4kQBlqcR4RsK5eZcqMOagx8OVx5rCTyXy8DkRVhnpbqov0ymBAJD4H0FgbSJYoImHL4xMGdoZ8Nt0DLuogNhWKW7VeQJ9pm2QWsQMoAJs7seKdk9wzRWdyz6yzVgpx3ynTpTN5TPuv6SjFaN+V63DZhVg8TWxqUdUkA8dIvrpMytjC0K0y9LY1K6dXqN4bhawyyOLEzspmB5crw8QwAgojpegKGJ/dXBRg7ox5mTmbsX0tfYrDbG+Tp5eNzdNt75RIE4z0g6LbhnisUig9mPnjH/+I3//+9/j85z/fHfp4eHh4eHj0Cvg4M61D6cHM4MGDMWTIkO7QpVtRJGheZrajLNDDnFEXYqjXimZtbcrAxcC46rXMyHmQznZpnBkZf4bMvkUaZ7GXU0VsJom0faI2hnpb7NEEQIkTQoPRRRVtRqvfV6bNviyeKoonEmVitFl9Rgay9QkZtA79vjf0zrEwatKGy8VsGGamdBYqxVMGx8KqKDNdTQY957S/omwRy2bPNA+pT9crogyDZRatX4+0E6lDYdtMdVOmpsizmHn8yX0zeY8pMWIMEP1P3jdXfQYWx+QhReVlL0DNn2cjqJQrwvA42KI8j6SCZIwKve/LbRzcr3HlWe4hlCHJbOU9YpS+bT/4wQ/w/e9/Hx9//HF36OPh4eHh4dEr4OPMtA6lmZkf//jHeOWVVzB8+HCsv/76qFarSvoTTzzRMuV6Ara+oMzO9ZF+GTuYRpiZjOAGyrhQdEZlUiVIp3pyDb6GdOuHOhDUySw8imPLAPH5sIPL71EbQ1SNM0pWxjA7isKYnRHnqZ0MoM10KQMTQcaOYBEy3kZKbBkqg8yeGUcmHL6yhYHGUBibtZl7Ziqr2xhoNjJWPTR5mZg5BJFuh6PXLcS5+qYtr+h/Nv01Wbr9jKKXZdsAcKj7BnL1ozH2SYhMzB5XjB76ejCyMzpstiKW/NZYLPpJx300yhNt77CdKmLXpOZn2fgzObY+cQU5dRj6SCaLgxnL1E+f2YBQNYxJGz1vVLt6ovRgZtKkSd2gRg9AWzooXTYBp28wQ7qrbEMo+QIsjZwfoEw+8eIPuNyKgFcAnoxpozqUl4nY1gCADFYmXhpRmC4rieUhxViVGuGKZSbTQEbbS0eG+Q/SF5PRlVn5NTJ8BlSjYW15wBSIr8g9sRkE5xkK60amsip9WYPb1bAanVIkMgr1dbF1gMinbVNQ2ICT6G91x+ZQlwSh5eHqZ6P7uKFufSBL92QzumFr5Uy/nYWMmw3LOybofbehx96kj7WTkI90UJkjg2vrh8xUqaE9jf3MUE0Ro+fMs6H1I1a3P3srxQDYrzO1DKUHM2eddVahfLfccgv2228/9O/f35nv7bffxre//W388Y9/xPLly7HRRhvhmmuuwdZbbw0A4Jzj7LPPxlVXXYX3338f2223HX72s59h0003Lau6h4eHh4fHqoNml4r8MpNEw0Hz8nDsscdiu+22w6c+9Slrnvfffx+f//znscsuu+CPf/wjhg0bhldeeQWf+MQnZJ4LL7wQF110EebMmYONNtoI5557LnbffXe8+OKL5Ta2bIaZsckrgTJ9rqFgUWVhk+GSrekVVcg0S6P4hZFv2MlRSTaaZHUOVodcMmI8ZW6iCk+o6uR7CMna8DB1uxZuyClVnM6o5EzZskFopl0NIeh1ZkMxHNeWoPLug2tWq/QHslRSeKLFNBnaDJTT82XZIhszohQgH3WXX0O30Ld6UESRJS3orAWtJ4wPfclI5FcMtYkBuXGpiJHvot9E8c7uOhMk6pbQmR3tHOOakbKeueQSjrFTFCnrWG7JLVekbsvyFrOVQ8zKMs4li6MsTeUtkRVYjpLNS8Um/UJurUI33BRLSyH8uGA1R7cNZniBhccLLrgAo0ePxuzZs+W59ddfX5FxySWX4IwzzsD+++8PALjuuuswfPhw3HzzzTj22GNbrreHh4eHh0dPwEcAbh1WQgDnFHPnzsU222yDr33taxg2bBjGjx+Pq6++Wqa/9tprWLRoESZOnCjPtbe3Y+edd8bDDz9slNnR0YGlS5cqh4CYZa+Mowwybq/60YNQrkHTge4QQW0Zwk6gspyjspyj+jFHuCJCuCKKbWIqWpsI+4bEfTuqxEe9Haj3SY+oLTmqcVqUHPW2tAxP7GnEDF45Kmm+qJIaFfOKmo+yL1a32gL3IWMYTOuA1pa6bUbOYQz4R3QS6/9lQrRnDHn1+oK03kxfoIyVdl2yjwimhFv042l+HpD7VI3vcb2NsDLEJkYeHEob6KxBRm8DeJD0u/a0/4l+J/oWTHZSupyCz6jyjqBbZRh0FO1IN+J0uloXYWVK2mu4rosZdOKMSQZG/8w4T1kZbjkylUDt46b3rOvdqwV45QEDD8lB+nhPwXsztQ4rdTDz6quv4vLLL8e4ceNwzz334Fvf+hZOPPFEXH/99QCARYsWAQCGDx+ulBs+fLhM0zFr1iwMGjRIHqNHj+7ei/Dw8PDw8PBYqei2ZaYiiKII22yzDWbOnAkAGD9+PJ577jlcfvnlOPTQQ2U+fcsEzrl1G4Xp06dj2rRp8vvSpUsxevTo2CbAVKC7B7YN0oCmAbfJ7qLRMPkND+jpjJecE7cjqgD1KhC0i1kYECTu13ImLmZXQereTWfj4rtJX8lwEJdr6rqrNIdrqE7sShilenXbDqbqUrjddHZNT6PMVIP3wuZtlAmqpsvP6TMZ+xadtdFFCKYu0hNI3Q6bE4C0MWVQiuoq8ul5DfdfPDM6I2TU2VSPPAHF66mhfmHQTdalMy8G+x9r3TRvI+8H7f5nXPRt1+Cwk1GYx6J6tWoJRb5vkvtO3dBWNhqh7vXyHgBWMjMzcuRIbLLJJsq5z3zmM/jXv/4FABgxYgQAZFiYxYsXZ9gagfb2dgwcOFA5PDw8PDw8VjUIm5lmDo8Y3cbMjBkzJhNQT8fnP/95vPjii8q5l156CWPGjAEAjB07FiNGjMC8efMwfvx4AEBnZycWLFiACy64oJxCjrVya36KRjtNyVmMC6ZBuMtjxlWuEShMkDJ75ogq8RdWj20NRFIlYmBRXEiwMvWEtYmq6mxPBsQDssNsOnMnzEyG5TDNoMlnU3txuiGlNivler/JYSzyIOSZgsMZ75PpnIHNUWwVqG4m2wrDNVjjwVjK6N5fSjkh0xKvw2XHk0krYvshdCJlXEWUOmztq5/S+w25B5k+QmQo7cPUcno9+gagGds5kea4uIY3NNXLKbYv5s+Z+oo8AxyxrUxZZjLDNmpB+hzXTYmYmCUS7yMmbdiUe+jJjtUSpQczb775JhhjWHfddQEAf/3rX3HzzTdjk002wTHHHCPzPfvss7myTj75ZOywww6YOXMmDjjgAPz1r3/FVVddhauuugpAvLw0depUzJw5E+PGjcO4ceMwc+ZM9OvXDwcffHBZ1T08PDw8PFYdNLoUSMt7AGhgMHPwwQfjmGOOwTe/+U0sWrQIu+++OzbddFPceOONWLRoEb7//e8XlrXtttvizjvvxPTp03HOOedg7NixuOSSS3DIIYfIPKeffjqWL1+OKVOmyKB59957b7kYMzoaGXm3iqkxlHOuueszO4esphkYfeaow6ZnSGbqwkOIyiSIQibZlyhM04XNjNy2gLIvUG1peMiVcqwefwnExpc2BoswMzQWC40UbGxrOgNHQVYlz+bE0sZF7mEmi3ZfMrNlx6zbZHNijImjXbNLf0bvTR7LoJ9z6ah91210FAJEZxDs4rP5LPeuYdZDZyFyGFTT/c3IK2pzUtD2KJPPxQjSNqe2R1ScjQ1M+lmGSSR5rDFolHthviDJHpveAQGSKONpQysMr8zXc9SM3zW7dSg9mHn22Wfxuc99DgDwq1/9Cpttthn+8pe/4N5778W3vvWtUoMZANhnn32wzz77WNMZY5gxYwZmzJhRVlVNEFpLHxZ9SdiKF3256J9teVoxQs+jfF2/CORXi9WBgCwxiP2XRPA7dWBCPldiF1yRl1fU5alEfLzkpAw+knycKS9KxXBXe+lyXYa+NOIYqCjLFK6Xvym/CUX7JRkYWOl9/UdFX+qhPyQF+4yyPxUN9Q/DIIVb2idv6cpRt1JWW/6whaZXT2jVu+6VtmwWJkEd9f257AIceUzLGA79jYNmgwhT9Xom4wDJtNRjesaLDNSZ1tcsbSSWmGQxTT4njh1cd/JQBuw5S0y0oVh6oXQ5iW6torhk9zTb4dmVlqC0AXBXVxfa29sBAPfddx/2228/AMDGG2+MhQsXtlY7Dw8PDw8PD48clGZmNt10U1xxxRXYe++9MW/ePPzgBz8AAPz73//G2muv3XIFW47i28AWlEfLIHeUrbAGDc5Wc/Wg+uTlzzPgc81WTGlJG4ilJN4PMiAeD5NkupQklpyqyRYGgpmpcHWGH2gKyLrTaZ5sU+qqrbAznITNtzS0zsI4ZqVGw0/LrLUUjLQHlPZWWAkHo+Z039d11ZeQLEtuLCJ59CUPW/vxgo+eXqfWt3SmhrroW6Hr6GoP0g6627/4HFVgv6eajEx9DbCpJibOWlTvMrQrcUs2BwtpyxdnVj9nGCWpg3ZCY9essPSluP8RA2DTspvoy1SOybic9Hm6/NRT8MtMrUNpZuaCCy7AlVdeiQkTJuDrX/86PvvZzwKIo/mK5ScPDw8PDw+PHPAWHCUwa9YsbLvtthgwYACGDRuGSZMmZTyKP/roIxx//PFYd9110bdvX3zmM5/B5ZdfruSZMGECGGPKcdBBB5W9+paiNDMzYcIEvPfee1i6dCkGDx4szx9zzDHo169fS5VrKZzxvy35KRTLUaZOebhWzLZu7rLbKTJDKbu2WmTQXnRm5JiV0YCEURWo9UsZFxalzIwwwKXMTESYGYWNYZBsjDOIGUs3rUPCvHB1cT39GKX3KmOLYWMlDDAas5r6VrOTJn2HRGqX5GAXMsQAmdFm7BUMujptcpJ7aJwG6f2ekbqhtZumZIZZIXYNij2ThfWgG1AabYIs95VO6pUNOkV2A0vD6sgYqCu3KjB3ByMMejntgDTyQDf81u9daVLIxUzq7asX1SsrwoYpdTFrm7rq5YyByY6Q3BdxrwCyhUhWvikQ4JpMdixYsADHHXcctt12W9RqNZxxxhmYOHEinn/+efTv3x9A7GU8f/583HjjjVh//fVx7733YsqUKRg1ahS+/OUvS1lHH300zjnnHPm9b9++PX49FA3FmeGc4/HHH8crr7yCgw8+GAMGDEBbW9uqPZjx8PDw8PBYpeCa4RYtXxx333238n327NkYNmwYHn/8cey0004AgEceeQSHHXYYJkyYACAmKq688ko89thjymCmX79+MrDtqoDSy0xvvPEGNt98c3z5y1/Gcccdh3fffRcAcOGFF+LUU09tuYLdCRFJ2joStyVmpgxIZyI8ncWxOkNQiw8WsdiFOAKgrcVnGBD9cKU1etigz8RsVCaVFSQ2L1WAVznqfTi6BiA+1kqPWj+g3lffzC/Oz6s8nkGFHAg5eMid90ZJI3pwweiII2LyYFHsvh3U49m1sjme5TppHhpmPrV94smB7MHKH/b7wpVMxhD2GiPC6T1iyGxyWXgGqhFEPNT0dbGRtJylfagMaV/F0jLWDR4FS6P1A+mZ4nqGTCJ48pneY9JWUZiGE9A3hlT0pfqb9OCkYltbkfYyPb+mTURFW3KWlaG3u01eXp9QnhUDeW0qzxkr/C7SyUgqU2/PeDsU8TywhNlhyvVEodYWoblN4ueabH7ZU2jRMpO+uXJHR0eh6pcsWQIAGDJkiDy34447Yu7cuXj77bfBOcf8+fPx0ksvYY899lDK3nTTTVhnnXWw6aab4tRTT8WHH37YWBu0CKUHMyeddBK22WYbvP/++wqt9JWvfAV/+tOfWqqch4eHh4eHhxujR49WNlieNWtWbhnOOaZNm4Ydd9wRm222mTz/k5/8BJtssgnWXXddtLW1Yc8998TPf/5z7LjjjjLPIYccgltuuQUPPPAAzjzzTNx+++3Yf//9u+XaiqL0MtNDDz2Ev/zlL2hra1POjxkzBm+//XbLFGs1ONyzDqfXB5CdMsjIXVwVzIGgK1tRbCvC5UyExk4pt1Ndi1CUnVHOO/QU11WJ83Axw6EsBlPzKp8Zb6gJOAOYtK1hsThhoxMR2xKhhxYnRcoQX0xeZoTxYAAiw1YK0k7CZKTADDJN8uFoXk6VZuZ6LPJsXdemh3GDQpEWaN2/rrIRmXIu2xrxlbIMVTVdsWNhUO5PXncx2jYRuUIX6RRDmRMk9zmEGZyI1FkWpubTyynMkKF9MnGSuHbPXLYptkbR7EOU7mRSUbRJwiTruhkLUTUIwyFYk0LgajdPZaTfTaykaieU2tAom9AyVawup7COrYSN+S5THnFkfroPoQif4sLxxx+Pp59+Gg899JBy/ic/+QkeffRRzJ07F2PGjMGDDz6IKVOmYOTIkdhtt90AxPYyApttthnGjRuHbbbZBk888QS22mqrJi6ocZQezERRhHq9njn/1ltvNReV18PDw8PDozchd325QHmg9KbKJ5xwAubOnYsHH3xQbk0EAMuXL8d3v/td3Hnnndh7770BAFtssQWeeuop/OhHP5KDGR1bbbUVqtUqXn755ZU2mCm9zLT77rvjkksukd8ZY/joo49w1lln4Utf+lIrdetxZGwXxMI5Z4rthaR5xCHsYOpA2MkQdAFBV7r+DyC2AanEzAVlaGTF8nMJhXWDDttB8zYD3XXClUfYrIQ8vWZqDyMOYXPSikkREwyNOpMTSdRORi8mj7p2RI6mY9y47p+B8MKxzcIcMmgX1GF9D2osQRHbI92+wsRkCGaL9uuoqpXTDxfodTvsKZT25477ocvW69Fm97KPJLo67ZcMuslbqj2+1lttYKQyNjcsZoScUaNtbSVYGotdhf5KUO67fs2krF5OZrH2WZ7asOSxHa5kjaFzXZuiEwOp3yCWXHdvA+ccxx9/PO644w7cf//9GDt2rJLe1dWFrq4uBIHaOGEYIorswZyee+45dHV1YeTIkd2idxGUZmYuvvhi7LLLLthkk02wYsUKHHzwwXj55Zexzjrr4JZbbukOHVcKlN9twg3zIP4BE/sBsTokDRvUWPrDBfWBYRxALRXMopSrVyhU+YJL08qMQSSVqlDP+lvBcqFl4CrnULiR6qhLNW0bo/yAvB85cdsWP1oyzSJGXzKgOheZREkOG9mXMSwvUMf9Ve6ntIQkL3e9XlGO9jsii4kfvBwo7sXaMkPmR88qBOp9M6XrSPRT3KvF0mBkv27XoI5peih7RoHUJdqm7I8c0y6FW9L0e6Trykk2x1wh028LDgjK5DFtBWJ0GdfbDoAMjWB67ciBFc/kAaAOfrTnTR3Qas+2IoM8hkGqmOs9yjjAoiSfKwBji8E5acMGy5fBcccdh5tvvhl33XUXBgwYgEWLFgEABg0ahL59+2LgwIHYeeedcdppp6Fv374YM2YMFixYgOuvvx4XXXQRAOCVV17BTTfdhC996UtYZ5118Pzzz+OUU07B+PHj8fnPf77xi2kSpQczo0aNwlNPPYVbbrkFTzzxBKIowpFHHolDDjlkpfuZe3h4eHh4rDawsbVlypeACH4n3K4FZs+ejcMPPxwAcOutt2L69Ok45JBD8N///hdjxozBeeedh29961sAgLa2NvzpT3/CpZdeio8++gijR4/G3nvvjbPOOgthaDMy6340FGemb9++mDx5MiZPntxqfVZdMDFqV6dGvMLBOtWZSIaNAcBqTJkh0t1beZCG8Qd4nCVIp5VGtkXkdiwf5FxK9kseDdQAG9Mo8aOwMUBmhm+SyziAgMzYuGDVyGyR5OUG+XJGZ6GndaNf5/URlsZKaRuaLY+Joy7iJjnOoG2avsZZqM5O6IwU/W5gG0wGnBmjWNOSRvJZCVAXqWmKsba2hJLpG+SxVFTRmZM83fQyQjZT85jAiR6ynIutcuggv9LH1MAkZvRM8rneI5kyBh25nqalwybfyKSZlXYZbSsq5V03Be0HFlYrMrn+9wRaZDNTOHsBKmfEiBGYPXu2NX306NFYsGBBqXp7Ag2tGt5www3YcccdMWrUKLzxxhsA4uWnu+66q6XKeXh4eHh4eHjkofRg5vLLL8e0adOw11574f3335eeTYMHD1YMg9ckqEaSPHVBpXYMQGoASWZtQS0+wk4g6Iz/h53p+aAGGfJfCfufGMZa9WhiQG8tV4QScBkZG/QsCpa4UUtx+iGFu9momD2JhSiGjdpBDV4VI1BLUDHFcFQaMLsuSFfOcC2mfLC0HWdZJsImWyPb9ABrxjYBMvqZDIMzDJPtPmUuypGHXGugGWArxtP03pn0t8iE4RqUwH2u6yN1WqHrobMLpnSHvDwCVNgt6UbuRiNuS9+3yXVCa3dnQD96ztb24gjTQ39/6vWnrCh575K8jBM2L+dZU95TK4OVgfuVWsa/w6OBwcxll12Gq6++GmeccQYqlXSVaptttsEzzzzTUuU8PDw8PDzWWJgmbmUPDwAN2My89tprGD9+fOZ8e3s7li1b1hKlugW20XejnYHOiMSmipzHW7LT9X6o+Tj9LIKNBUDUHqdwBrnBYnfCNjvTzWZc3tiFmRcTSyGSIrKgLdgHrYziQcO07wbItApZWE+MKkw2IqrnGjI2J4oNRuLNJnWmn3UUaZ+it5rOwgwMjCLPcc8UvThhIrjhmqn+BfVUPIdMMkX9TMsXGT5Dy6fBal9hYkisCmvymf1Wyq5pa/eydTtATRsYZVPynkHyPWLkK5VX5IeQMJFpZcgwO0rTOXRzNYd+DcpXg47iHWV8B0jmUrxPU/fw2AMq1VPpm7T+nt7SwKMlKM3MjB07Fk899VTm/B//+EdssskmrdDJw8PDw8NjzYfJdqDs4QGgAWbmtNNOw3HHHYcVK1aAc46//vWvuOWWWzBr1iz84he/6A4duxcO1sBahEMd1icjf7lhGZntSvZFbHCWsDhRhcuhZGxrQ5iZlQRumo0Z0p3IyZPxRhHtSLceEGlUbPI9njSl4cpzdQpFwXhKJmdppKzOHlCCSLkmYodj09MIV/4c5sG5Jm6arbvag6lNnmGkbGUbZeQaBLVboV5KUpe8+g22EZkstFvYxFCGSOsjNq+YUnZiXOuDtueO1M+Y+3ZzetKSUeShTJ+N+ZG6mSrT6nJ6XZpsrSyyqC7WLkmZQ1p33c6sxNudcCPDRu91T8aZaXqpyJNIEqUHM0cccQRqtRpOP/10fPzxxzj44IPxyU9+EpdeeikOOuig7tDRw8PDw8PDYw0B5xy//vWvMX/+fCxevDgTXfiOO+4oLbPUYKZWq+Gmm27Cvvvui6OPPhrvvfceoijCsGHDSlfc07AxcoWjadpmZiQeSjz74IiSigKodgJx+P40L6/QqYEm2zUbagVaOaKns76S+soZVYB0g0jAPv0sMjO31MOILOn1pFWleGHoujBtRqgXLgITE+OYFReWSb9yIsrQVkocJNF3dZF6+zeim8X+RK8wUxepT2fBnDN1mxo2+wq9bgMDxfR7T+Vx7bsi2CBDq4f2JZNtijPirl1trUOr+ii6ke957QBkGT2F0dSiazvtpWzPcNLGkhmh/Y7qpG0Gy2g6A/SYUiorpbG6nGRZGSxHL2VmTjrpJFx11VXYZZddMHz4cLAWbPJZajBTqVTwv//7v3jhhRcAAOuss07TCnh4eHh4ePRK9NLBzI033og77rijpfs5ll5m2m677fDkk09izJgxLVOix6C763DzRmQ0e/ol+a/PTgJ1sZgHTMaH4REpF0HGWxDypCcPRUCnCipMszyXt5ETpusWMyabHJpWwC7BqBRpc9O12NbnpfwAmfg7NjCOmDlLPsc2TSajAHJf8kziHaxKxivD1Y4meYa2l22lMQF5DJXs4pqORVmWTL8qaE8DWl9BULuVPNsNU9TmTL20nZD9nFXAcp4yS5RF0cpxQ52Kx0/RtqRVu65TE5HpTpY+WfQRtfURl00MrUDYDjq7maPfUOZQ1qnbsRRlC1m2DaTdXMSVe5rpgx7dhkGDBuFTn/pUS2WWHsxMmTIFp5xyCt566y1svfXW6N+/v5K+xRZbtEy5lsLkj5fja6w8vDqlSg1XI/IG40iXjzgVEj+QTGxvEKlvOFl1mLzZiUGwHvDMhrLGh9mT6n+jvLw6yoyolMERh27dmHGJ1s8BSn7FzVvk0V6wGfdmLZ9yL/TLcVmL6uDIf/mLukkZ9y8OS9XQZ3T6IFBfEtHrKgGnIbI+6ASUH3RGEzKCHZUaBnxSHr1WxzJK4Vmrq10sgxIAmY1L5X+9XlOf1qshWzjoZTIqFrwXRZdDdRf3vEfYOOCkzxp9npD7mrXraWMtkufY7TCQvC/AsrfXUm6lDGKa9UhaTUdeM2bMwNlnn41rr722ZXs6lh7MHHjggQCAE088UZ5jjIFzDsaYjAjs4eHh4eHhYUezUXxX1wjAX/va13DLLbdg2LBhWH/99VGtVpX0J554orTMhoLmrbFwWgrG/+Qs1bBEZFz+EIRQBLA6Q1BTz8flmJzlMZ64/yZ6sDDla6nRqhUZK0X9OtIZSykUfWpcYum0HeqsiQNgAU/1oixFzA0nH8l2EiYdNVol0wRKkD4iX2OjzMyVYQ1Bpll0MmR3shwuGcLNnCydGWU46lYT7Xrp5QovZ9KJpj5zty0LmZL0skmmDEukdCBNZ1dAQEtdhcMP5C1zmPRyXb/ujq5dD13a0m0lFXJKZ6hIYmaFlWU/ymUqA5EtMxiYPp3dyTAeOttraDupv4HZiyrIbD5qdGsv8HqUWVnKqnvX7J7F4Ycfjscffxzf+MY3Vo4BMIDV01bGw8PDw8PDY5XA73//e9xzzz3YcccdWyaz9GBm7ty5xvOMMfTp0wcbbrghxo4d27RiLYe2jiuh2UQoboGGfEZ3SZsdB2dy80hWZwCPZxipTrZpOCEBOJlS5a3ta8yHcwpdlp/Ur62gnUFmdq7IUJkUzmJ2RofOCrgItDhDtpxonyLGww1Rt6ZZbwGmJjc0gIE1YEEc/I9b8tmYBjHjV4ysLTo627godJaGzqQd9g4KTOwRlWmSY9A7w7hpbI9RfRdjo+thIBRlPaZnALDeM1M5q90HM9xPvd9rdZnS9GZk5ItkkxG/v3L7BTdcj4EFtebNE88AHqYMCgey9kYm5tx0Dzn5LO5h6bj4HmUxevRoDBw4sKUySw9mJk2aJG1kKKjdzI477ojf/OY3GDx4cMsU9fDw8PDwWJNQxHIgr/zqiB//+Mc4/fTTccUVV2D99ddviczSY9B58+Zh2223xbx587BkyRIsWbIE8+bNw+c+9zn87ne/w4MPPoj//Oc/OPXUU1uiYE+BRTErI2b+rM7Ug0M5bKBB13jAwSsArwBRG0fUzhH1ieKjnSNqQ3xU49kAT6LsZVy2hUyxyaHpgOV8qw4hP0iOvLy67iY99XxJ++mH3r5qG6dHFKrfab08T09DHW72p8AbqGCdpms2enyQa+GB1iEDLvuH0gZaPeoJVb5eP73MTN/n5CgCUrf00Cvaf2zXUKS8lk/Wa0nX8+r9rcivh73fQGk3pU1N7xZbfSYWh2np+uGSp90LhvS6oxCotcdHvd1x31xtwBGHpkg8tuiRua4I9n4l6kreQTxMj6iSHrZfNcaBoM7BkiPs5AjqQFBPdeYMiCoFbrJHU/jGN76B+fPnY4MNNsCAAQMwZMgQ5WgEpZkZEblvhx12kOd23XVX9OnTB8cccwyee+45XHLJJZg8eXJDCnl4eHh4ePQK9FLX7EsuuaTlMksPZl555RXjWtfAgQPx6quvAgDGjRuH9957r3ntWgkxqrfNJDliRsRmyS6srfNsLqgHDU8D6IFxlXHh6XdhnS8/A3HAPaG3mGlETJ26mWYgeTPlRvu+aDt5bQVl5dgCFIrFIsqR/C7PItvzbfWEMelpkZW1bbAYatB+pLMJmo0FTddnq6atBwopSeIbuey9rPczz2amaD8qYMuj58+zI7LdwrL6ZM65mCubLYr4rNmtuPq1LT5KxjuHZ7Ox5I+xK+jvN/KdB/Z6Y1uy+GNQQ2znF6blZDbHM58J6gjIZ8DUd8WGu877l/eOoX2XFmPp65rVuWpGSN61QT1tc14BeMhk+R5DGXbTVn41xGGHHdZymaWXmbbeemucdtppePfdd+W5d999F6effjq23XZbAMDLL7+Mddddt3Vaenh4eHh4eHhYUHowc8011+C1117Duuuuiw033BDjxo3Duuuui9dffx2/+MUvAAAfffQRzjzzzJYr2xSKjoDpOrDBPiTDCoq19QDgoW7TQmwZknQbqxjb7LCEIUq/K3Y8SawamTdZh7aySY3AZYdgm5kWlWdM4ymb5ZJJ7Ari7+aG1L2Vito6lbGJUIRLI5N4Rstq8RGQgyWzXVZH2q9oHxPi6lDvqewL6fUrthWkbpkWwejJQSGL6U+/zcbC1O+LoCgro/U1oZs8HPWbbIOM12K5LqetScFrc53XbUeMrJOp3xXVw9VvdUbCUk6PMM5DTabQw9R3HXUr9kDUVkY8K6b+ztX6qP1W0TaI35U8OdLnMOwUnzmCGk/sYxIPLWJ/06PeTHqfa+RYzfDzn/8cu+22Gw444ADcf//9Stp7773X8DYHpZeZPv3pT+OFF17APffcg5deegmcc2y88cbYfffdEQRxL5g0aVJDynQ7xA+AATG1q/Ga0vrRIZKRfNpurkpZOsCR5RIZQUqLBgxATefV06eUcfJOjljmx7vQj3FenmbDSlp9XaFSx0pzxwHzyFeLbPU2ZY1amTPMuVWvMhCVRnRwJQYdTH6X4lky0BXnaX3EENJkEGl1446YUrdziYSozSxpxiVYy2CkMIhM40CE/PhkylnuiW3lQfnB48j2Mypbr8sGW3uIMrYwDmj+EQK3PCYijSRmqrJMHGztzTj5AQ9gD64nZBjkcKg6Wd+DYnAjzpP964QLuNAlAsBsA1XL9WSuLYoHL7RcvRoX5CEQhennTIiNHkBRXwJX+dUJP/nJTzB9+nQcccQRWLJkCb70pS/hrLPOwvTp0wEA9Xodb7zxRkOySw9mAIAxhj333BMTJkxAe3t7S6L3eXh4eHh4eKy5uPLKK3H11Vfj4IMPBhDv9Thp0iQsX74c55xzTlOySxNqURThBz/4AT75yU9irbXWktsbnHnmmbjmmmuaUqa7IZZthDse/ZxmSvlRl7uspLeTJSSIzSep+7S+ER1ddqpwcHpU4yOqCqqTJ+63+mcodLyVMlcu3JBHX38xrcXkyS2LXMqfLMPl1Wmir7UlGWWJjif33zQTcjA5slwUu+ijzhQ3U+VzkXUYDoVaV5aQMnnTJUUWMftSj6F/0jQn00HLBuTIuRSbO3lmWajAoSwpmZaWXPlJHiW/xYXY+Ey7DlNbmr5r9UrZ2nKAy/BZ/+xcRSByM6qaliJ0d2hdDyqPPDfG54E+Q7RthQjhOu04pDyyDMTqpH6b27bpeeGQy1asDgRdPJXBAB6w5IiZGBnKocLk0lLL33VFYbpXZY/VCK+99priCb399tvj/vvvx1VXXSXZmUZRejBz7rnnYs6cObjwwgvR1tYmz2+++ebSZsbDw8PDw8MjB71sMLPOOuvgzTffVM5tuummuP/++zF79mycdtppDcsuPZi5/vrrcdVVV+GQQw5BGIby/BZbbIF//OMfDSvSE5DmDCz72cXCKGCI7R/oIdiWJD0TyCyTrh0BJPvCw5ipUdgXoX+osjkKC0T0yx4O9sVaJnvdhWewFPpDZ2JFDA9kmUBlmcuLDIEHRUbxUU/X9JDNRAyt5YyVMioWRXioHvp1mG5DnpGtUibg6kw36WOFjBctbarUb2n/DJuRE0CxkedLr9fKopD8vGidededowtgYBlc/bOBfqwXU5V1yyj0LIqv4ro1NoQySkbGh5RX6iUMTUSD2lXiwKBRNf5sZeE0Vit2eCCHxgjJx62usjs62ynlhywJsMdSVsYUcDPnPrUSLoK86LE6Yccdd8Ttt9+eOb/JJpvgT3/6E+6+++6GZZcezLz99tvYcMMNM+ejKEJXV1fDinh4eHh4eHisufjOd76Dz372s/jXv/6V2RJp0003xfz58xuOQVPaAHjTTTfFn//858zu2bfddhvGjx/fkBI9An2d15DumtU4Z5Kuc+KzaQRNh9VBnJFzIKry2D5DLxexmAkyKoj8gH42fakY63VyJdEegMugN2VlrJ5OXP1Ps0o3nJy6XdDr5YSdYTybLJKYUiTj8JYRzwznHOq4PDFyN8WkTBMnHwzXSutVnoNss6fPgsZGyDIZPVLZShbXM2VQM6OHpqNRf03tTP2GehWZ5HPGBTjnnUB1kura6hR1URZIn1lrnznLJsngdFqbG2XYoLebNqVlHFmPJprXoJciVuhmYmODpMlpQD2RP4RybcLmBTCwQIR5CYSbNwAWcfWaIqRTdpYwMMmCQqS7YfcgIyORR8cWKb8aYYsttsAWW2yBMAyxcOFCDBs2TEkfMWIErrvuOlx77bWlZZcezJx11ln45je/ibfffhtRFOGOO+7Aiy++iOuvvx6/+93vSivg4eHh4eHRK2FZZi9VfjWE2JRax0cffYQ+ffo0JLP0YGbffffFL3/5S8ycOROMMXz/+9/HVltthd/+9rfYfffdG1KiR5B4DIHaOnCmzPKKDHKlHQXZnEwwIs6ZZrJhpYDwTkoz0gJ5i+sNpom69TxFFl7zGkewHHkPpxKcQpsK22aZGtsQ2z6k02maLV7nNyhgmvIz+31TyhGGSJmx0ltlYDOM16J/NjA/mVmo/llvY322H2hCqAxLkmSddHkmGRYI3SlLZWUqLPfaxFjp7KaRCdEZMTrDN7KiaV5bl2wkeJokESnbExC9KBsWaQRRQM7rnpBEvqI/3aZAb1cLA2O1D0r+c47Um4iwR9RrzFSH8hxClaHowVLGk4dQg35a2CqNoFPzcYCRB1MJAig8lZLzUYUhqsbfo0qDLK9Hw5g2bRoAgDGGM888E/369ZNp9Xod//d//4ctt9yyIdkNxZnZY489sMceezRUoYeHh4eHhwd6XdC8J598EkDMzDzzzDOKR3RbWxs++9nP4tRTT21IdkODmdURwquEBUhZhBrNoE1k9JkhJRDIho/KTF3rWYrHTMTAaox4DDBp/yK3QhBVi5g1iR4yzTmj0i+AXEpRJsZUXp9uJcIy9gVURmYaZYFDZ6siGTaHtBuYWndRhshVq8Ji5OjrNJ7Q6JD09ioMgs1WgYrPazLKXMVsFWHNHDKbXX43laeMkYSp7+jsC01S6AuzfIXQ1NgaxyNqLGdlxmxwMD8ZeTSN9gNG1EhsR6w2fhr7pcg3XZ+WliHFtO0MwAhLRPuk6Z6Z7jnX2CXKdok/OqOZfGZ19dpMj6m0jyEMmojkK9hZmZenHn5R4s2ktJ12OeqHHoDOsjZSfjXC/PnzAQBHHHEELr30UuOm1Y2i0GBm8ODBhaP8/ve//21KoW4H3RmbxSH0AZUaNoI8cDzkqXGmcL01lKdLSawaIUKAQGxVYN2dO9HL9JTpL3Pyo5UxwqQPifJydgyMENO/xrr1lyQxzgODanysvJnN9WQrhnn5IQPT201NU1/u6RcnpWxZ9lBOmbaroLItAyRlWUx+zPLzNtdhXT9jMzl+8N2W70lxfWnKJh/qZRYdAOkTBZdBPQ2Y5hoT6upllqYs98o5EDfkzWTL0UkfoGYSjb+g2UEJnUcYDWANsE3IjAbu9PnVBZjkB1paZuCg1W0YNIjBozLI1QdLPM2rz6Uy9Wi68Sh5LQpDYMay12kZrAqdop7cm6mXYvbs2S2XWWgwc8kll8jP//nPf3Duuedijz32wPbbbw8AeOSRR3DPPfeseptLenh4eHh4rKrglsFZifIeMQoNZqjf91e/+lWcc845OP744+W5E088ET/96U9x33334eSTT269li0CixAb7hpm68bZGmU7KKMRkuBklJHQZj9MnwEoyypkesJ5uvTFuD2cvGM26TLqYxwpk+TSUTuXYWhc1LcNDgrcyDTZytrKOGa6+nQ9NgxlMp+2cpZbtSuhzDslJq4M96MgM+LUS2cHTaycVQZXsqnGuKkgrt8DXQdFgbRMpu8Y2CQ9j4nwshkAK0UdrExGP312ntO3rdcvlSJtaErTg9OZRJDzETPcOstzxYl8IHY/zpRh6v3IsDRl2VRABpSkMIkxLrmJjIkbtdSLXhe0fLoM4eqdyOPiJcaQccWWhtCirE3ZnoD+/mqkvAeABoLm3XPPPdhzzz0z5/fYYw/cd999LVHKw8PDw8PDo7WYNWsWtt12WwwYMADDhg3DpEmT8OKLLyp5PvroIxx//PFYd9110bdvX3zmM5/B5ZdfruTp6OjACSecgHXWWQf9+/fHfvvth7feeqsnLyWD0oOZtddeG3feeWfm/G9+8xusvfbaLVGqO8BqAVCLpyTKpoQinU7rGNRQ9BUOVOODV8lWAgnbwZh6CHAer+HyCLEBcJRMiWwL8YKV0bdBYLAcXBEnRAh7GU6rSw7GABZweSiFNNP6zDWZgrEZZ+hZWbRt5cG1g2zAiDo5IkNeW92mGazOTiRHuoFndkGeG24VPacfxvvjgFGO6X4YkEtL27YYCBxp5FDC9MvvWnsVvV6SZm0zks/UlsbtA/LaWL9emmRh8gobQOffIqN85Zx23a5rFrqpfQXpVgDG+4V0O4FkSwF5hFA2gqR66O2vyLHUl7lH+ivO9NnQL/S2yr2GAv2OhzEjE1EZtm0oCj67LYXtvVbmKIEFCxbguOOOw6OPPop58+ahVqth4sSJWLZsmcxz8skn4+6778aNN96IF154ASeffDJOOOEE3HXXXTLP1KlTceedd+LWW2/FQw89hI8++gj77LMP6vW6qdoeQWlvprPPPhtHHnkkHnjgAWkz8+ijj+Luu+/2G016eHh4eHgURE+7Zut7H82ePRvDhg3D448/jp122glAbAN72GGHYcKECQCAY445BldeeSUee+wxfPnLX8aSJUtwzTXX4IYbbsBuu+0GALjxxhsxevRo3HfffSstbEvpwczhhx+Oz3zmM/jJT36CO+64A5xzbLLJJvjLX/6C7bbbrjt0bA0iKEHrBOQMQt+0MeBKmlyCNfUebRGfJUJ4nWUDR0nbG1oGKUcm9DB1UkN4e1tnpu7dLNAyumYe1EiBBokzbtxo+Szk6ApmIqIxNT9P82QCmdHw52TBX8wUZaKuk8vWQDlPM6qF9EBlaiLJo03tmSGfs1pnBqbUZfUoEmk2XfWZJ70VLl20W2UMTJhRxlxerxqwX49Rmq1LsUxyVgbPtl+enpl6maOpDDpIkbSvaFXl6qTfJ5ZN45rQvE0wbZEEqBzdk4p6SVKbH2dYAfJYZhg5+mNOmCd5bch+FvWKYIQ6w069Dun7QW4i6WJzAMfNXXWxdOlS5Xt7ezva29tzyy1ZsgQAMGTIEHluxx13xNy5czF58mSMGjUKDzzwAF566SVceumlAIDHH38cXV1dmDhxoiwzatQobLbZZnj44YdXn8EMAGy33Xa46aabWq2Lh4eHh4eHR0mMHj1a+X7WWWdhxowZzjKcc0ybNg077rgjNttsM3n+Jz/5CY4++misu+66qFQqCIIAv/jFL7DjjjsCABYtWoS2tjYMHjxYkTd8+HAsWrSoNRfUAAoNZpYuXVoquM2HH36IAQMGNKxUt0DYv9BpRsDT+ARhPEVgZJYvc+atoerTGsGI0ABNYnv7JM4MIywLr/A0gJ5phkY9qVzr/Rr7IskffesEG8SMz05SFLIryDADJpZGfJceXbFwZoi/o1Cxku1KygWI7ZkAcDAt3g3U2VbRtXAbS2G6LkW+xuiAsEym9gCyDWqbnlMhDNltFYpAs2XQ9aKB0jIyLf2Ama7FFW9H1G1i+oDMPTJJ0pmOXBmUQRCeRJai+YmkDts9pTqQLm4kL0X3dzFj9Nbz9D7pVYkvlInIVmguaHtEJZsh8pPtYDJsmqPrcprPkcaCbB6aVyirMEHkXtQDKPaQmY0kKZOrsULW2F/dCdOzVrY8gDfffFP5jS7Cyhx//PF4+umn8dBDDynnf/KTn+DRRx/F3LlzMWbMGDz44IOYMmUKRo4cKZeVjKpY9lvqKRQOmmfa4dKGT37yk3jqqafwqU99qinlPDw8PDw81lS0ymZm4MCBpQiHE044AXPnzsWDDz6IddddV55fvnw5vvvd7+LOO+/E3nvvDSDe6fqpp57Cj370I+y2224YMWIEOjs78f777yvszOLFi7HDDjs0fjFNotBghnOOX/ziF1hrrbUKCe3q6mpKqW5BlYO3RxlmRrGF0QeVjQwy6QwlIEwPOBAy8KTFuc4Q6VMXk42BPhukzIamP2NIWQoGOKdlmu7caB/DzdMqqjOMX9OaIs3YgCO1Y+LmKozQ1tIlm8MMbWQqo8PEnNg8znIYC1MMI9PMy/gCKxgHJv6s6ajPkp1y0iIGRy4lTwYuFXVmyqWHRgvZyEiXrY2LGLFVJTdmLMKq0M8RireJJZ9sD8u1UcZA6i3y0UfNwl6JLsHJtSrvBN1+z8Fs2byReAAlTg5lUq0bc9pYTmisWeBmHBWGiKaRDTtFnBrlWjPPtqWOlUcq9Bg45zjhhBNw55134oEHHsDYsWOV9K6uLnR1dSEI1JsZhiGiKG7UrbfeGtVqFfPmzcMBBxwAAFi4cCGeffZZXHjhhT1zIQYUGsyst956uPrqqwsLHTFiBKrVasNKdQtCDlbl6tNiokaNHbrk0Nn4ImDJU5YOPiQjx3g6gDBUlQ00ZfgF4kz5deIc0hA5dvnW36SGNyoHuG4k7VhGKTLyYByAkJkYYac/8gyM7o/FoBpCmxBo7yI9aKHydkTB+wtp4KyPz+i2DZy2p0mebWBgACf33rhUkyeosB+xqWwDZbTrpPdQzccLqUaXRbODC5b94TeoohTT73XBGS8dHMjBNKlAyqBbWeiDiRDaCYOy4qt+rVbF1KbVmsfc78QPNTMUAunTpvpEH3e1mf5scMcAhurVYFpmuVNXnOoTEp1oG+iDfMsAstBAvrvQzDJTSRx33HG4+eabcdddd2HAgAHSxmXQoEHo27cvBg4ciJ133hmnnXYa+vbtizFjxmDBggW4/vrrcdFFF8m8Rx55JE455RSsvfbaGDJkCE499VRsvvnmzmWo7kahwczrr7/ezWp4eHh4eHj0MugDtkbKl4AIfifcrgVmz56Nww8/HABw6623Yvr06TjkkEPw3//+F2PGjMF5552Hb33rWzL/xRdfjEqlggMOOADLly/Hrrvuijlz5iAM9ZF9z6HX7Jote41uoMRoekEUHbmT5QpeZzErIViKgKsBq4hLsmLM66hLDdDHs2nGLQyY+gCR6R8v+2ARGsNG2sRGfdqUTrAgdVIfS2a4RZkIki9r6GhYRxE66hS+LlvrJiYdxUw8rtd8n5yutjYIdo3qQsKyS8hrgvof5jpzDSoL6ab+T2f5GhNjmT0bzxvIyKzxu0EWPWUgy0x5bO6/Vhd3krcIrO7kpufCJtPSVrluzxpDQQPtmRgHSV4aGBymrcTntatJDyGHpumfnW7otF+UKUtkcPJZZ2fo+0Jpux5kSFYW9N8JE0aMGJG7EWSfPn1w2WWX4bLLLmuVak2jFw1mPDw8PDw8Vh20ygDYozcNZuSIX58qFSxbJBvjsWGvkBkxaYPC6kwNPEdtBkKuzq6pMa9JZ6OKOVOLpG4e6Xpw9fqoGN2Y1To7JNfM47okG0MD9gWIXeClUFUPK/nCWbqRHEdseyMYLxqSPTTJSE4kLt1K4ERhX0Rny8n1i3xBLWFnkMxaA6DeltRd5dKgOwqhbHFBDanpLTS+fHQjbpNxA2WiWMyIKBk0xkRthDRPq19+RlbGpUOih8tIlmWm0okIE2tjsnVI5NPZOdfLUf2LtonBDsOUhxKCha2USV6dNTLpSI3LrYaxFoNaabdjYro0ltPYnyxMICfnMkyVEvQS5nbRGSPA2OZKuAtNhmRSLW2t2PBT5o1b7ll3w/VeLVreA0ADezN5eHh4eHh4eKxKWKmDmRkzZoAxphwjRoyQ6ZxzzJgxA6NGjULfvn0xYcIEPPfccw3VZdyGAEgZG9dREJKVEYvy5OABwCtcHqhGYMmBkAOVKD7C5Hsyy2dBpOhCN4nMbhhZ/FokvSl1hnGULwNQCUZHHHV6AKyLgXUxBB0BwhUMwYogPjoYWGcQH10qm0I3L+SCtRHXydM6WZ3oQWarnMUMStAVH6wz+dyZHB0MwfIAwfJYp3B5eq28whG1IT7aOaK25Kgm//tEiPpEqPXlqPVLjr5AVCVtF5Hr7mJgNZZulAmoTA1SvZULqDOl7eM1/aRNyGanPEg3zJN2H2LjR30zUuUGan1UYyWo/UghuJ4Jys7p/cnAqkhWjR66PqRfm3QVMiJ9Q0FygGXrUA5dB1s+V5toZYztqsnhpA0yG2lCk2HTgdTNAyCqOGQS3WjbKe0pdGLZz5nroNdJz+n1azpmbNxEWb3/0A1mTW1gSNPvv1IsyZ+++9RzKwOMN394xGhoMPPnP/8Z3/jGN7D99tvj7bffBgDccMMNmUiCRbDpppti4cKF8njmmWdk2oUXXoiLLroIP/3pT/G3v/0NI0aMwO67744PP/ywEbU9PDw8PDxWHfAWHB4AGrCZuf322/HNb34ThxxyCJ588kl0dHQAiLcwmDlzJv7whz+UU6BSUdgYAc45LrnkEpxxxhnYf//9AQDXXXcdhg8fjptvvhnHHntsWdWN7Ax3TEutbI6tvJ494GChHiM7XaRlJm8jw3pyET30PJnrYiIfwMmidryGLBJ5yiyBMDJAyjZQOxrFjiUpU1NnC5wxaQMRB9mi9BDJF/DYE4MuXEuPLo1SUq4TqU1LHQDdgZ4zRUcu7FqQMkOiKhr3BQyprQHxNGScxwxRwjCFHUSvCOAVhkhsrRDG7I+8bqoWuQ5mmG4bN87ksG8BkFxDKtyRh8POxHAtrzit6W/LR+vIlU9PG7qEWgV5TjhTYwsZhFCbCGu9dEZvs5Ug5YyPIGFQDKfTNKF+jgxqB0Pj2sTPjb1OakOibD9A6lTuoejfIs00pWXaf5BmMtx/ruWlLCq1WWK0fh2UMUmux9jXmNYmmqxMf6Wg90OvPmmHqCe9i5sdkPjBjERpZubcc8/FFVdcgauvvloJjLfDDjvgiSeeKK3Ayy+/jFGjRmHs2LE46KCD8OqrrwIAXnvtNSxatEjZmbO9vR0777wzHn744dL1eHh4eHh4eKyZKM3MvPjii9hpp50y5wcOHIgPPviglKztttsO119/PTbaaCO88847OPfcc7HDDjvgueeek5EJhw8frpQZPnw43njjDavMjo4OyRYB2tbohlljEdYjD0KGHiHWuEUCt0wLqI5550yzShjYGBJVWN+iwD47VyP0ylmMvhWBOIeUGQEAXsnO0nT3DMqIKDPAIKUNOPkcT9nSj+psWqOyIo0ZIjE3wNLYPnFkX6KX1IM5mQu5/o94BqeHAwoS1iZiPPdWp/oTHXXQyMR0hq9Nv0WbyjRbOHedKaBsAM2jq0j7nMl2QSngSDPIN6aT+622CzczJtSFRpNvfMJpHn3jRn17DF1IziuDE0ahcBwbnb3QdFS2OtDvJ8mTsYEhEW4zj5PlPtji00gWRr4TzHrI7zS/YIFEsmVD2UysK9v7kEN9lvX2pqxQgVe8M1ZSN8K7ZrcOpQczI0eOxD//+U+sv/76yvmHHnqo9MaSe+21l/y8+eabY/vtt8cGG2yA6667Dv/v//0/AMjswpm3M+esWbNw9tln2ystODCw0s+mwRAjn3PATBS5Aa7lL9PDJvOL/xEZwESGoHY2PZQfBS63QeDJjwij2y6IwUmo/bCafgxlxeRzgHTZhyF2h6aDJ6krkWXTOdFDuY0RT+UkAxklUKH80SKu5Pr4U3M7V4yQqzzj+ipp/QCxQbC4TpqHBuIjF8VEOTKwUgYb2g9ruoTA1B3SoeXV+2zeACZvQK3/oMKS5spnK25bWhBfNZmc3hu6nKlcM8vKlEsZ2eeAB1mldXEZ92PLgE5fDnKGOJD1Gyo1DRb0/IkixmUmOjHRVTC836w/7nReofdrfRJhen8iO7CiVevtY3x36AOAogNN27sf6bMHwLzs1l0o0B9yy3sAaGCZ6dhjj8VJJ52E//u//wNjDP/+979x00034dRTT8WUKVOaUqZ///7YfPPN8fLLL0s7GsHQCCxevDjD1lBMnz4dS5Yskcebb77ZlE4eHh4eHh4eqzZKMzOnn346lixZgl122QUrVqzATjvthPb2dpx66qk4/vjjm1Kmo6MDL7zwAr7whS9g7NixGDFiBObNm4fx48cDADo7O7FgwQJccMEFVhnt7e1ob2/PnGeMp8tBJotD/bPpu+2coa78TOSzzppQY0Y6owq4Itu0rMTJLtRGiJmtHqiNpEvWhjMwMfVNZlqcLF/IoHAaj0uXiPQZrA0mtsA489Vne3rbUYNdgBgUI7OLsAK6DCcYGPJd6EBn/ZzWJxgmUYYE52M1Io8nrubCaFkjwqJKqqMazI8r+WjjBJE2q2SQwfxUpbT6jA3hvl+CGbE9QmrmgnL18/qMX1uSMLEGSjA0cY2yrxg289QYE1UdQyfUXew1hRQShfZ5jeFViCULiyX6mIkhoAa9Uoy+2apJSfKcO1lfjfVTkpjG6mgMWCYAnaUaDqT3WO+bGstCbqHV4BcBCMuq5aHPEJEl5SvL0JqMnoBnZlqGhiIAn3feeTjjjDPw/PPPI4oibLLJJlhrrbVKyzn11FOx7777Yr311sPixYtx7rnnYunSpTjssMPAGMPUqVMxc+ZMjBs3DuPGjcPMmTPRr18/HHzwwY2o7eHh4eHhscrA28y0Dg1vZ9CvXz9ss802TVX+1ltv4etf/zree+89DB06FP/v//0/PProoxgzZgyAmAVavnw5pkyZgvfffx/bbbcd7r33XgwYMKCpepsx+jXNaijj45RdZGbKNf3I7IzXGbhrZdBgpBvLz9qx2Op2lqPXF6XTMmU2JWY4XGMqxBdtxqa7RAtXZU6m2soWBDZd6XnBktDeXWcIarTCdEYbu2xrck0zUz3oF2kffRYdgKfsjMakJEXj/xEQkO0SWB3qRpZJsahC2pvFZVgtlZXaWTAgAKIkjVd5yh4JxkDO0LPXmCqotYWN8NNYGqcxMM3jsMnIQDc0NTwCChOTsIjKDFwR4X5GKfNQyIqbE+aHM1UXjWmQuuoitXbU7WAUEbp7emaj1fS8aTsDyVSZXgoGWx9FNLk2hQ2zsTQiWbuHpjZQ2g2aPKRtEtSy18X0/mlibskzByFP5KMu7T3JzHi0DIUGMyLOSxHccccdhfPeeuutznTGGGbMmIEZM2YUlunh4eHh4bFawC8ztQyFBjODBg2SnznnuPPOOzFo0CDJzDz++OP44IMPSg16ehyGtdPCoLMFB/OSSWukPsP6PfVK4pR9YVDiyfEIltkWV+TanMF4UkemLPks3M+ZvijOtPxyZkSNTFT7Ax5wMLFmLVyqRd6AKQHwmL45pgnaddKmkPteJoxFPNuPM0RtkMHuEAr2w0BFiC0YKuQaaXORIIOcIb02BiCKy7A6oLh/s2w3Mc3Q5TYYIj2A9OoLO7XrYtIJDVGNIUrCQUVVtX2guL9rthfQmplOpV3si81LjnqFuZ5Fw4ya62+pIiwjiMqRmqa4/+Y9o4L10GTo9aaMgGBpSP8xsQQQzICFznC57AfpfTR6DpI0nf0R1xKnac9lIiDrDabDfW08yJan7KByPtP5s6+LzHnN401hiMi5THVc7QtyKw3x2cKydif8MlPrUGgwM3v2bPn529/+Ng444ABcccUVCMO4h9brdUyZMgUDBw7sHi09PDw8PDw8PCwobTNz7bXX4qGHHpIDGQAIwxDTpk3DDjvsgB/+8IctVbBVsLERcgKeZz/QCtDZC2epN1DAnfFnlBgyEVPWfMkyuDvWhT4TLTAjNMmSdhtgYJFhemtihmjMmApRlAFYEU+DgiTGjJwVBVzayrCIkc0bVdGuYFeUaaiHsbyoPWFIOlkqvw4EkjXSZmkMKVsTIN4M07LdgN7JVC8TQZUksqUXFFAXG+JFoo60bi6ZInVNv97OEQimpsLk1gqsFrM0oo8EXUDUmVTdxlBv5+BthOFRmDdyzeKa5LU5GEmHrQTN5JxFWo00dDnaOaX9DedhmGnrz4qLaTLoTAPRmfSl7co0XU2B85yVGfK5PG8y3kAmojbQ0nTjFIcmlD3lQUpJMaj9xtTmJn0zsjU5jJTTY0Qp+ekrLLLYvyTPnnydUls59Cwjk1YK520vVN4DQANxZmq1Gl544YXM+RdeeAFRZAjr6OHh4eHh4ZEFb8HhAaABZuaII47A5MmT8c9//lNG6X300Udx/vnn44gjjmi5gq2EI3CwM80EG5PDmJom4r7wehDbvNDZroC26WEmg76mTSKU6jM/s7I5i+A0FL5eH62I2lcwrrIN2vWkGaFsUsnC1O4GHIQdiT00hGcP6kzZjoGyIe7ZLTmtRBHm4CFPJ4gBUmaJ2CExjjhyr7TdSWK/JDIQcns7MwDV+GJpfKDYqyn5UmHgYcpSKB4V4tooQ2LajDRhbCQxVmXg1aQdOxmCLoYw2dEj7AAqyWfeGW+3UOsb543aVPsfleVKt34we8ilaYI5NIWoV/IVmJXL+ujM2mhEoemlM5t6IBydIaH12pgYTWTm+kxMUA5TYmWPdHI0ghoziTYBfV+QtKyRjFlfzoGAbJIatan90cZaZZnf9IKcHm2kbt3GhpEfZNH3le0kDHULezR5KtJuob5RpKgr6QfSBouyPeQaisTFahU0Uqmh8h4xSg9mfvSjH2HEiBG4+OKLsXDhQgDxFgenn346TjnllJYr6OHh4eHh4eHhQunBTBAEOP3003H66afLTRxXC8PfZs3GBcQs1GUbYEjjnCcsRXY6xiOuyqWshy47SKeZQqRMpqIts0gpXzuv65S9AKbMMmM7FsKcKHnTc3J/oqQuRd8uYrdSg7rnFl13J14fOsmkx6YAoNjdZPSSeQjzoLlDZDbVpLNKGuNDU4Rxbk4jNj+cp58z8vUophVuYOySr7SpQo66YGYqDFGdIUq+RxWGyoqkTD22oUnII9TrDPW2REYVxMsM6pQxbzGak3LKrN7NCNJ9vpSNMvWgJbKAes7kNaPk5Zb+madiTtXSZs3CsmQ+i7LUu03Pq3b9LLtpki2SCbOX0dnSBlEflXLhJJ+4BakMrR5Jl8BIUWcYXuNNIoyOztLQeghbQpkxRWJITlDd9IyCiTExMLS/9yTdQdq34fIeAJoImgesJoOYBHQ7AxOcIb4VQY6Xs/6y5ekGhmE1QsQYEIg3GowvgliQ9ll5GaY/vEwvo4xR9F8/849i9sF10PX6y1FkDbkhXyI+Sn/85bst2Vk66Axk4De9KvpyyVDqeT+S4uVLBo7iRUg3njTWK5KEcTYxJmRRslO2KFflygaVymCPDBpps0nXUPqip27PDOmgIiTy9UGbHoSvkixvIQC6Ul3qDHIj0LATCJdDLkHF2yrEaTVwIMnH27g2mFHbKkP50x8SJXQAN/4wif6hGEgr/SrnDa3/8FvzkX6TCTmQCsiMFUw/prSs6wdTL8eQHQwq/ZzomAz8Y8NUtV9kJieWa1HU0CYu+lKScawh+p+YaDGuTFoyy3KmwZUclFveOYByj6VeYmmW9Celr1H3bnUslh1oGdSTg22D/sryrnfNXi1RejAzduxY567Vr776alMKeXh4eHh4eHiUQenBzNSpU5XvXV1dePLJJ3H33XfjtNNOa5VePQ7BqhRy1XbKycqM5XEEVQaxlkCD3/GIqcyQhWqVcM4cksy2zed0cMtnqTdJ4+myUCZAXUhnwamOEeeqESs17EXMbsjPDOrSj/hYZ+nXZFsCEdROaW992wN9qYee4iwNNEevV9DQgskhsz4eMqAPRyT6SpAGxmehwfVYYRvUz7K9dB6fcbBQ7YvxFyj3h/M0nZEgagg4UEG64WgIaeQb1RlYNWWpgk6qKkM9WXqQbFTF0CECnmEpUtaJZQLx0XLWwHscKRslmsMULkBno7g6i3YtFynsnhKA0VCGMC/OWTolzWxshb5Bpa2LcpYyD3rgOvoO0NgWIyzPu4PYyzKV9Pmjzzm9d5S942m/goEBybhKm947+lI8h/E5NN0ymwGzsoyV/DG6ba8saCxTQ+U9ADQwmDnppJOM53/2s5/hsccea1ohDw8PDw+PXgM/IGkJmrKZodhrr70wffp0JVrwqgTGUMr92s6wuIXY7HJieSQtTGVFUTpd4NRQVCui160H2ottRBzr1EpmyyyZZiFMhzT4JTPJNJgc2ZaAAxyESSHB73RDRcUtGVDXyCOWBieLGCofxRmDrjgoXOounRZnZPuD9OKUKtPvtXQLAFaDdNfkQfxZbAEADhngLl2XJ/QdnT0DqZ2ONg1W6g9Stkq5h6a+Y5sFK+3GMvdQMhEhEAl9RdAw2a5pG4SdIFRPvMWDvN4A4JXUaEMPP5DaV8RlmUjUGRZ6/TZ2RF4j7fgiTevv+jVTkRHL9C0jaPMLRooGZytglGAj5KSMAmUZDK7wSsQ4i4CCdSle2452cyLD5qifM97wJlbLwNBk3LoF8xlBMrDQjX8zxubGjwpjZHS9LnGvPFZttGww8+tf/xpDhgxplTgPDw8PD481Gt4AuHUoPZgZP368YgDMOceiRYvw7rvv4uc//3lLlWspcryZsvltp5uXIZMTfcIg3UySBwCPgnTaydPZPqMulEkarSOzJYKNccksfJOP2mya1Yj3Fc2eBKET9SqeQxxAp9imAEnQOEhbEE77D9E5/DhIXbWJPUTYAVQ/TD53JkyKYEvo7C/RXzpRaDYxUZUyPyn7EkRAZJm91ftA2vXwSjJ7pjZAIn/CWin2GIrNRvIhYbHSWTLLvpFM981E2sjrTKfFsV0AV+0VEtuXeoUjqjNUxAaVKzSWpispkKTXhc4hjQ+f2MwQhk43aVHtU4jClOHUbYwo46e7zJjsLHLANdsdhZXQPHR0LxbZrzUPqKydiaayJk/qQfXX24uq4SLpcliXIqC2Ilb7IgNTK93mpSdgkqDcW/Wz+lyaOi+RRRuElOUcYPX0WTOZUYly8mvy/CueWrT9C7RVJuhed8LbzLQMpQczX/7yl5XBTBAEGDp0KCZMmICNN964pcp5eHh4eHh4eOSh9GBmxowZ3aBGD6LZddEmytuYIRqPhgHgLEKUTIs5qTP1gGIyTc5JSujFyMydi7gnQggDZJx8xtQZGyNsTMg1u6LkQ0cA1sUQdGZn1hzxrEumRZAxUIIaUF2aehhR24WgA6guS0TVgbCLy3wR6cH1aqy/sJ0JO9X2jirxZotx3lSvrv7EBqcS1y1saKJ2jkh4XCWbZJo8rgAkIdYpHUOmh+Kj6z6JmWMRWw8ArCtRpA4EIkZJTM2kxauqXQ8PIAPlsRpDWEvTZCyeevyZEfstsfWD3FxQ0l/p9hIyppDOTMgvpD04M8+ewclJqEyB3na6rZCjrRQPFp0G0ZCaqmjsDjnPKVPAtC02dKpE0Z9s50FlGuxYbHoojE7R5163N6L0DNeiUtn6n+5lRW3jCMPAQ6QbqgqBDm8pm45SFqB4KrK6dt1cvzZyaTqTDWT7EU2zpXcT/DJT61A6PFAYhli8eHHm/H/+8x9lJ20PDw8PDw8PB3gLDg8ADTAz3BKApaOjA21tbU0r1G3QZ7x6cg8PcZUlZqbF7ggAlrg18bppvMnlP07WninjkqlElLRFQgXSGY6wo2AAF7HvRTVipq3PuDsSG5nlsUGItGmp8DTi74oAQS221QCAykepN01Qh2oLQ0KUh50py8KieB1dlKtXGToHxvJrfWO7jzCJn1Lvk15cVI0ZiagtlS8YlqgCyb7wMGF2TB4tCTPFHPYAjI7ni3YpYyhWB5gqPOgKEC4nM/eQI2pPrieC9MaKbUWAqD3+Wq8zyWJR2xYWxayNZGaIp41GEsRslOiOGisj0oHE/oHGkiFuLFyPQWO8XsNp3eMpMwvn5HN6PjYZIzN9Lbqu6u1iYAsqXGWMsjlsCeq9M3ih0WpV5ooruumegbnQ21AzWNKZJepIRdVVP2h9IRUXf1faVdxrqNGxKcsk+oEhcjMPefpZeyVmTM4CALJf8zQmFfR7Sz5SbykfAXi1ROHBzE9+8hMAAGMMv/jFL7DWWmvJtHq9jgcffHCVt5nJG7D0ILsY15eJ7kTOC3qVLjnpVLEebM8in3NG3Ky1F6hOKdOXLeNgwkU5SgZC4keNhrhfHsoBC4vipZk0KBxQXRIXqn4EVJYB1Y/jtLAjHaRE1XifoHqikFjqAOI8nAwuGGNYMTjOt2IIsHxUnLHyYYDqsvQBj0Lyw92W6CV+IEggPuGOLa+nov+4iyWc7I+13SqRZCGnjctMiuUnVDrcRPlHDDwiVHqQrtMEXQDrYOgS5ULEFs6JqowsFdaBdKuDFSzdsZzHciK5gzlkAD25PEF+TOXgjkMJBimvQb9csVIVZgNIZn6YGNKBsz5goV9Jv6VxCAEoe2MZDVxD830DZ2ndZH+wzMDLpLRp+wFxm2R7GXaAR9w3TXbhoipOdcl7admWjOj3jIx0KSxjlOwIOJhZXTPVzRDvci2eqTay/1iIdIlbFBP3hoSd0J+hzDswfRxiiEE0MmOldEAdpveCR5b+4LFKo/Bg5uKLLwYQMzNXXHGFsqTU1taG9ddfH1dccUXrNfTw8PDw8FgT0exSkR93SRQezLz22msAgF122QV33HEHBg8e3G1KdQcoC9IsA9OqJSlFJ8KiAGTyRjYb5BFTAuzFU+H0o45IulUzOaMSBr9KiHIxyZOzYDFFQTpz4fGMUQbKoxQ5CVBW78PBIqDyUVx3ZRlDuDxOCxPXXx7Embv6ASuGxJ87BwL1vqkhblCDdK0OVzBi1AtUlgMdn4i/19aCnNkFtVjnep84ras/UO8nmJ8IIMawrCNQdvSmTJKyXKLt2E2bXLYZoLIHSWbj5oC5yyiU/THMOJHcC7F1AABeBep9k+usxPdJLDOhGklWJXbhTsXykIOL3bU5h6RzXN074GoIAG13Z6azSRYwwvkzhrRfiTYTfTyzLUfaPrYtR3hiyJ5uvYF0qS0RYb1I5eaSL2S5zsTkML2ctmwjZbtYK3F/RVuIbDrbRWXq4RhssLF8Uq8CDCNLGNm8ZVETU0KN5sP0HcBDnknLLhdC3fxSvzQO47YHJlUyqhK3c8rU9hh6eDAza9Ys3HHHHfjHP/6Bvn37YocddsAFF1yAT3/60zKPbe/FCy+8UG5ZNGHCBCxYsEBJP/DAA3HrrbeWU6iFKH3b5s+fv9oNZDw8PDw8PHo7FixYgOOOOw6PPvoo5s2bh1qthokTJ2LZsmUyz8KFC5Xj2muvBWMMX/3qVxVZRx99tJLvyiuv7OnLUVCImZk2bRp+8IMfoH///pg2bZoz70UXXdQSxVoN24SxWZaldSyN+CTWhVMGRCFA6CSNMcU1m7IlnPqORilLkNmMMUrdMnmFq23UGSgB4pSQ6OIkkATQS04FQLAsQLgiTmv/ILaNAYCwg6O6LM1b68OwbN04X8c6daBvPQ0QWGNgiVFx+HGQGvzWgK4BMesCAPX+kVx/7xrI0bUWEPVPaJy2CEFb/DlgQKVal8xXrTNEtCzp/nTzy5DH10Nmi8ImJNN/TPee2EMw01RBt9nQZ+pKunkaz8J45i9ZjACoV+LrZBFkkEJRTN57IL6JJJigmJnW+6RBBFk9dp+XhtthkLqnVyNnKHn1WlOGgtHZv2S+iCGF6GaizQysFqcPgihJWBJO2o1FTGFQrEHilHOZDp4m0e0chNEzkZFxtybkaTaqIE0jlTDtv8gWEEZRf36Vchotkcmn6aGUJ21VT9tBtzGxulXT0xkr8TRRNgFhQjPvmEivELA8CplzMuAe1ZEE4gSQMpAM8v0ZkQ1vWfq73u3oaQPgu+++W/k+e/ZsDBs2DI8//jh22mknAMCIESOUPHfddRd22WUXfOpTn1LO9+vXL5N3ZaLQYObJJ59EV1e8RvDEE09YaSgPDw8PDw+PgujhZSYdS5YsAQDrVkTvvPMOfv/73+O6667LpN1000248cYbMXz4cOy1114466yzMGDAgOYUagKFBjPz58+Xnx944IHu0qXb0QyL4irbyrFdVhZXEukmf3T9mvN4lmHeoBIKS4O6FuxKIAIQsnT9ucaklw8LeXZjSCGkorYND1J7l6ALCLrSWVnnWgz19oSNGQJ0DE2Yk0GdCMIo3soBMZsQ9Y0/d/ULVPsHjtj+BVA2w4y9rziqfbvS9kkQMI4wjBAkOtcqdXQkn+vLK5IFklsDiJljBcSjhcwm9cYTtkzUy8SUD8jYmSguojSgIWeEodPKBZBB81hnoE6EIyDoSGajdSa3MxCeJGGHsFcgLunEg4vVmdVdmSU2M4qLv7rrpfk6tSmoujUHsTHhiaKi/bkqQjmp2XkoagRQNyfM2KdoTAr9QJ8dYW+kuZ0rTBOghKygz5uSL8O8IdM1lHOUqaGMhl5etl3Oi0jfakN0iygNYCiDQhIWR9nM1cFwmVzJ9bT0ekifJO8sRitxXI+SlGM3JLdREVuOBES+sFGspYxx1LIdC3sOS5cuVb63t7ejvb3dWYZzjmnTpmHHHXfEZpttZsxz3XXXYcCAAdh///2V84cccgjGjh2LESNG4Nlnn8X06dPx97//HfPmzWvuQppAaZuZyZMn48MPP8ycX7ZsGSZPntwSpTw8PDw8PNZ0MM6bPgBg9OjRGDRokDxmzZqVW/fxxx+Pp59+Grfccos1z7XXXotDDjkEffr0Uc4fffTR2G233bDZZpvhoIMOwq9//Wvcd999eOKJJ5prkCZQegx63XXX4fzzz8/QScuXL8f111+Pa6+9tmXKtRI2ZqURtsbGxATNLH5aEJGpXMA4oiAdgUb/v70vj7ekqO/9VlUv55y7zQYzA4wIyo4gSzQsEYwCEeLDmGfUmAjRp0FZRDQSYxIwKiCJRGISFEIQEwyaJ0R9RgSjDEEkQcSIguCCQMwMA8PM3Ln3nnO6u6reH7X36XPnzsJst76fz8A9p7urq6qXU/Wt7+/7EyScxZCQjZDe5Cec+TodBS1c1kMiCIQMEwAaRkRSpaWAp9MIzmPKKAiSaWLTDyRdz0uDAFN7ExQL9Dr14gJUaxEIASiVMGYnwey/Xau/N7vlnLrZFRNIUycIYVRCmG1E/W2ud5pw8Ew1QlTUzVo9RgNQM/Mg2qu+di9rf8taR+u+qt9nhpUg1DEUlpXxmTd7gN8HBLJ00Vhsmg6YfiUzugyhPHwApYvx/XtUxJjHLhgWrjJpHNRnkQuQxBPe1O4zU2Fpotrq10q3jfjMlnR6hUDrBY96VAd6f6PZv8VsC/72NEuChJFPwxJIGq2HqTOTTpNTv+4Erp4SMMqzgQgr4h1c96cR/slRe5YbGBhzrM+QNnkf1Y+xZXrf+yRNPWKsZqjn6ksGq9tQpiHX/FMHxwDOZ8Yr3z5znv7Ojyq0Ohgv8sjUOWCFhr2Gibu3VTluX1oSm9TSJlzdHpitvnM9HsCTTz6J8fFx+/WmWJnzzz8fX/rSl3DXXXdhn332adzn3//93/HII4/gc5/73CarcfTRRyNNU/z4xz/G0UcfPff6b0PMeTAzOTkJKSWklNi4cWMwUuOc41//9V+x5557PieVjIiIiIiIiGjG+Ph4MJgZBiklzj//fNx666248847sd9++w3d9/rrr8cxxxyDI488cpPl/vCHP0RZlli+fPlm1XtbYs6DmQULFoAQAkIIDjzwwIHthBB88IMf3KaV25YgZPNZGDMpnM3BdUvZGL8uvjbC/86UL+Bm7mpSSwbKcFE03lTJ0wJI4k9xADcdAoiZiRAV9eO77VqWoFTRIUaj4rMUhBOwjWo6xboE2XoXweQzA909gN5yDjqh8g0wKm0bKJNBXyoXZDnQTkIcywIAacrtNkrkQD8y73NC3bTeT+6ZdUpUmnkQGQO6LGAsBrx8bJHePkZTEcwYB+sPcx8GXzmGop6Swh5LAKl9gyQnIAUBNdFehduftxSjwg3bI5QTMqBnpERCeG7NFl70j2wBIhNOl0QdQ0H0NQvi3oL+kEGdfWbG/a3bY3fzZ/+ole1tk/pg0rBNHxvUx49I81gtMFljH7zTCe8ZZ76wxD9R7TuPpSHCXk39Xy+JozmlsdqvR535HwMWZAun7vX70f8eaNaa1N2L/WbX9g+0ePX96rqw+p/mDwbbH1ZyZiMLRXP5RAZpEILyfK0Swu8gVJ8bVtqPdpPcux71lC/PIbZ3NNO5556Lz372s/jiF7+IsbExrF69GgAwMTGBdrtt95ucnMQ///M/42Mf+9hAGT/96U9x00034fTTT8eSJUvw0EMP4T3veQ+OOuoonHDCCVvemK3EnAcz3/zmNyGlxK/+6q/iC1/4QqB+zrIM++67L/baa6/npJLPFeYq3N3UAGZTA5NNlz+4v/+dP04hQfmuYpQKFcbtrYlY1jqggNWyiQm7lVQq0S+gliAq4gzG6lRuKkGsmFQChdqR9KkVnCbTKsM166v9BFMpBwCgv0iCjJZ2EMESMZArSujPvErsk0qpBNXW91S/yFjDi5jowcxcBqGESDBr80+Qj6rlqYpTFHkKvl4lcSIFdYZutTUO4gslKRlK+TfdE4FJor8UM9u9Y/YrKWhJQfU1rNoSMtP9nUrITECMeJy/qP0g5N45/NNZ0bMbSNp6GXOxev0k3DUUUGNlb9nPluH3lW2Oq1coavfqFfyIIcjxBLhzy9ItFSrRs3CnY/51a+hffxDhC4cFwgGLf4C/niG9/aj0BjR6o78GwoldYhkIefYFxf5yT60P6gLaYTrZYBmovmw129JMPfR+GLxBXLC8OHCPNAx8vRQYbt1cD5IDga53Lv+8/kBNwvbpAILYcuLZAqiPwaTFYK5GhNsC9b7fkuM3A9dccw0A4OSTTw6+v+GGG3D22WfbzzfffDOklHjjG984UEaWZfi3f/s3XH311ZiamsKKFStwxhln4JJLLtmhyabnPJg56aSTACgn4BUrVoDS7WmTGBERERERsXthezMzwxJF1/H2t78db3/72xu3rVixYsD9d2fAZguA9913XwDAzMwMnnjiCRRFEWw/4ogjtk3NngNsTgi1z74ISWZlY7bm+81D2ICB5YtQJerudEls27mQIInHMgTe3YrNMctORLrNvCWBnFsTOlEwQM9qSOXs83lFUPUdZUukl6k6AQiTSuirq2iYGAqgkgRcsz2yom5JK5WgejmJJQKESHCzRJRwJ/Kt9UkTo+ZvT727P2Oq/FLPLLq52iilY0CEpOElYNKeRKVAcP2sZoBuRii9abAECdgFUp+BW0Zt2JRblWNSGMhM2uzmKnQaIS1l2IvaLRiGMtfeqj5bUWMefUif79d/GkaGMBnMygeeAY+d8lkaiGaGS21220RFnSFa0TC5Mst8Ddm8g918lkxKSOu8BsjK1cv2F5G1sHOESyn1JQ7zuSEtQVN0OqDvJ3+512/TLGyMzw4Gy0B+OZb9atimmc+6Brix0gHzg0EmybIwPis02AdoMgKsl9+0zZxutnQP0qsQQRB2rrLD603SLTttKsI9YufEZg9mnn76afze7/0evvrVrzZu55w3fh8RERERERHhYTsvM+3O2OzBzIUXXoh169bh3nvvxctf/nLceuuteOqpp/DhD3+4USy0s2BTrMxsQt4mYenczjn8mLmyRFK6cqyImfizDr9Qw86oD6JhHVkZ0xEg0WJSI3QwqBy7IBgg2prB6VTIOqWd5JSCQBLNojBnONVfJMFzapM95uuUjgYAeJug6CUQRsNAvD5KRTgl8tMxdClET9WRJ0q/YRmilILp8iQVEJJZLYyvn2E01LtQSMvG+MgYB2cU2ZhSMBcsg+hqbVAZzgBJQV1Ya10TQgHkQzJNMgnJ3Uc7cayt1QcGel4yT0CJec1MkmQivNd8HQJcveauEZMDbEMAb8asQuhdW2giQn3NLEyZX6DdSxKXLmCgXg31MKaRiTsXSYVi8AzBIlx966H9AeNiRLz6vpCCKC0U4EwRdR2l95wEWilBVOiwnzDTMAg60acfgd3YG4aVaSrfHOexIANJY32dyZD+l/5/vXswKGegYjUzxZpuZZBarFM0UCxN3bzPMiUkDBOvHToowK/Vxd/WoCsEVaxoaO7nVdUySQ3lP0fY3stMuzM2ezDzjW98A1/84hfxS7/0S6CUYt9998Upp5yC8fFxXH755TjjjDOei3pGRERERERERDRiswcz09PT1k9m0aJFePrpp3HggQfiRS960Q51/9sUKJE2pLeJhTH26k1siooSIna/pmPd34PnNRBzXIwN6kfC44bqKMwsw8w6iLRhyX6Uk5RUlWEjNryyqdI5GDtvmQuQEbWonLYq5Gnl6pIDRWnYHeZmNYmE4ADXYcO85TQzpALYusRZ6LcEyKgS6GRZhXZeWrakVyXoF6oiRZGAd9XfpMdASqJCqAHwRIDm2miPSbDEGeclTASMDK1N6WwACgnN9UbyAu1M1aubVei2lHtc1UshCwpS6Huh8iJT1MGuX5lUGhv/+hgkXiJLT88ha7oVQkPTNqPfoIVOUWCs9pmoaXCCZrpZtinKu5dnu6+D5Il11skry2diTOh2Uz0Cbcow1I+t7+vVg+UcUngRU5YtEmGi1eD42v/h+idgWqCZMu8NaSOndGJSEypPCnf/k4qAco/B86tgCMkmBoAqQ0x7jJfstElqZNmFevfMJRJHa+j8PettD+kLc5zWnBgGi9conbouxt53Hqs4EBbvrpM0z8Kw22M2JsvcxwNVCftDpt75BQl1SeY53J5KibjMtM2w2YTaQQcdhEceeQQA8OIXvxif+tSn8Itf/AKf/OQnd6hhTkRERERExK4Gs9S0Jf8iHLZIM7Nq1SoAwCWXXILTTjsNN910E7Isw6c//eltXb9tjmHamKbZojV0m2W2U19brn+25mWzTEYHzOK8+tTZHEKkG4HWl55RG6h70xS7xE4ECAGEVyFjqEcIhWBwyfVyjkRrUxLGQYi0xnNSApVmRASFi0hgAoITlOOqjKoN64Fi1uZFS5WRjJYYG+sCAEayAinltv2tpESVq5ZWnKE7om7Vbj9DMZ3axhGvr2RBIQqGkqp901ZlWZos5aCUW3+aOkNXvy/M51ZaWk1OP+UoS4aqm7oyjAFdBcXYGIkF4JgTX0PBCVDCagNkIu2UQvr2+TBKEt3ffsQGQaCpqPvA+MlIpRfJZmAn33J2VtG36w/YnAHNg6uXr1OaLbKv/rwNjZjaxBvbRE75x0hBw+fQP1UDYzLY7sHzUypdSgfdH1wzk1ykYNPONJJ1nWlk1YFNEyEpwqSNQKCtofp+kYxAZDLw/bFaEq2RGYiAa2prPbqxpmFxEWQyuIb+PiF9E6Y6kQQqxQlqOh6pPa5MJJgkbj8Jde+atjF3/w+wFH71h7bRfDbvTVMOsU2zza6Z+Smtn6yVAwjZpHWL2Nmx2YOZN73pTfbvo446Cj//+c/xox/9CM973vOwZMmSbVq5iIiIiIiI3RZSDlFbb8bxEQC2YDBTR6fT2WGJpTYHw9xVZ/PQEHoRe5iOpmkbpTLQacyqD5gFjJiIHBLOOiUJ2RpZ+zOYcbrZuk2BAAlCBYzNr+TES/AmFRujPUuSrEKWqClVmvCBvspyxXqUNJytizYHN07BVCLpaN1NViFhAonWxXSyEjlT2/o8QSmYY8O8c2VJZY9hVKLHOLi+NlIScK1d4P0E4CoJIwCUnNhkkrxVATlgvdMBmybCj1Yb1FVRe0za4uixFD3d1BKAMP4mBQXref1PAWpmptwxMzLRM0Iz0xZu1oqKqFm48YzxrP0JdTN1menIL+OW3EtA9DGUCc2mDagHHGxb3VdSKkbD/O07+wb3X90nhPj3mf7KZw2aGJJalerROJvS8rh9ia2zrffQnWfZFlQm3NExpd4mAqRJhSRRdSwowDNDPWRgfYJso/qYbYRN2MkzgOcI0oWkU65+IlPlVR3l12QYTAGAWHZHasKC2OMCx9oBNmOQeRho67D97TbvXP77hXpRaH60XS36CgKD0XuGxKGwmZ+tfs8UOts1I7W/fcZN0bWDRRj2yD/WsKLEu77b0QE4RjNtO8xpMHPRRRfNucCrrrpqiyuzvdE00OiXqkuqIrEvR2PUZo5RL1y1LRA8Qr38EmMa1jCA8l/Szbb7BIwK+0PLBVWZoQH7/2BQgfAF4A8qghxO9lzqB8DsR5hUYdEAWCqQt0pbf0qF+xsypOMT7pZ3AAjufghpWyAZU8dlaYWWXuqhRA30/PqbdjIqlEjbUOBEgnpvHbNfnujBj75OZcXsMqBMOCQlNj0DCCBKNWgrhBr05HoA1spKUM+K3R88+YPRhHFkemAmJAGjEq1UiYP7rQSFrkfRT1DNuMeJFC6rNRVuOUFC/+3R4NZSXeolBvPiT9x1E8xLJZELnZ/JOBpSwCx5pCIQshMWCnKl9O/75jehFCRc1jKdFBzjPrvBizZErP/Q1EGAwPA/MNbT95C5pt6zZj67fd0vwcByWt3cz/+DNCwt6foHH4csmfmTBADodPp2SbQLgj5LQPQAm/XgMsjP6IGM6y4kXV2WkOC5HhyNEhQLgEKPNimUjyAAEFqrOHUdJJkMBcDmh912gD94qa29DZtzNQ1G/a9sqg+vT/U9IL1bJRB0B2s/0mmNPTNNu6+Bl+F6k0tPs/3CE6/Y2sDGnpbNcnzETos5DWYeeOCBORVGNsdiNyIiIiIiYj5Ds6BbdXwEgDkOZr75zW8+1/XYLqgLDytOBwS2lQ4HNuI+ABClZ2Pv2eyrQqU15wKRkBV1s3AKEE0/01TAF1JSL0SRJSKcdUhn86+YFMOwhDNVKbxZrQRoIoOEfWTIrFVKXR+oZQmqZyJ5WoFSYcOjTYbqJkipWBcAYEygrBQDQolEmnBbRsIcg8OoCJZwhLdkRom0S2t1ECKRU83IIAEjYnCGDiDJOITwTP+E6ztRMlQ9apclKHEMS/1cA2JgfXFSxpGzyi5xjbd6mC5yAMBMmqKfJ5ah4iUF75nHi7l8lH2X7RpQaSKM4SABVLJPs+wHOAYnFe4WMYZwZibLiU30KTiFLCmEn94gdUwh0LxESpgzv5Pa+K1x+cHOos39I93fDckom8LAbTmmyAFGpPnvoAIDqJcvg5m9Cz3G0Jn7Jo0xHeEXnEtItQwLAHSii2nZxoxO9En6FMmUut7ZOrX8ZG7zdKNE0jNshLQsTb4e6E1TsK4qo7eEgGg7A94SwZoIKakzT9SZz232Z+qxHolnSulnAx/SDy79Bty+9hC/I8wxXgESwXtRSth73Bxg+oB4hoaSqPvcpt8Q0jJcA2yfv7QkB7fPmu6h1ox6/bfnnJx4rO2WHh+hsNWamYiIiIiIiIgtQGRmthnmzWDGrX9LK+wVHuvBOQUkgahIcAyghJGyMAZZyhTLzn4knDCTan2ELkMSQGgBqkhkkHCt8jQQ3E/EpoWdA0ZeBn3qzLe4Cw0GAJlIa0jn2+v7a8CEAiTlwdq6mVUapoJ52wYEzlYv4J2XCrS0lkXpSkS4/5AZb0KcNqjOytRFz6aMnFWQkqAUjj0yWiI1IXR6Eeq6SoETq2uZAUBGtOYhG2RofPh9QIkE1awTJRJZYgz6OPpJAq7Vnb0isUJhDoDolAhIAFq4GRWtiGNEGvUmHiPizYwl9wz7vEYSTrS+wEuWqFlGUWcliKdToAg6y9deET98ForNM7NuxewNnx42aU0Ac02HHjZ7eTUWU30P+8FquWTtfEPqFX6/iXM3oC48Hls4g0rfk1XFQPZQO8wsydHbkCDboN85GUE6rf5OZyRo6ViL9rMC1GjkOAHvqP2qtr6PTLuFu9QiA0Qq7TuBejmARS5Rjeow9kwo7Q1z7N1c2ipBNGtjv3DXkCJMU1C/f4KCCKQN44ajUcz9b40iiWMf69XxnwfSsN3uN8uvfZ3RmcsxETst5s1gJiIiIiIiYmdCjGbadpg3g5lwTVRrLJgAh4kUAgR3TI1S4+sZHieNecsAAJ4RltQW5EPX57k3G5Ww4YrEn52gFsHhsTZSh/hSPdNmMwTUpLDnYeVE4n2srSHzduISSI5707ch/QQ0a2fsd7WorVBPEJrTJR6NQIgE041LqMBMmVkNTcWpTSngpyEQkiClHKO5ciWrEoZepW7jXj8NNDOUSjA9y+MA0KM2XLoCUOba6KzVD+ouau21BoYNfdFOSluvhAhU+mbImDPo6yUCJVE5HQSlqJhLdse61IZmsz5BNSKtySAygcC/y9yPFUAK6lg5SQITPsKJSooJqGuv72mq9QnGFFF6GitwBDNkQuBmxd71NSkWjD6GMrHZBIvE7PqUuvxi1h2aTi5rm2TIntSZlGFpF4aVb6IUQx2aZhg1K5l6lgYGacpRjCboLdIRcOtTpBvU/ZJu9Jg2rkz3WF/Vo7VOAutVGTwnynzPXCruMTMM4C0SMBbmcStHidoBgMiVzkaO6roTEUYS1ZkOeysZVtZ1cBAZx9yffmg/GWAcnfme5MQxN8Qc6L0L/Xepd3zwXUNdLYRjdwY0h7J27RtD1Z9jRJ+ZbYbtmB80IiIiIiIiImLbY94wMybRJIjn2UC4N7Bl4QhfEmfRrycMajdlFCVNskSjhYEb5ZvygzVk1LQNEtbuWzK42U+iZrpUW6fTRDhmoKKQqbCRTiJJ3GSiVOZrhnmgJZy2xlPMEwGwHkGpdUM8Zyh10kaREaQkTM44DHWmJvTPcRFBFNKZ02lPEhvR5e0nJMH6mTbK0oY9WGajnRY2jUIlKEAkmG6cz/RQItFnie0f7hmqESogKbNaJ1JS9KYVWzLJhNULGZNAP8rK1l+q9BRGM+P3g2lLbjaksHqaIk/wrN6vyhmkJPb6VutyJJO6zRXAOwLI9LVvVRCFb26oyzYeMD6LaJqaSMBLgCmptGkVDBtntFok0Aw4jxKahNx3wNDpWbbTTjVoK4ZFMJnyauXOlkokYGkkGSizkRGsHStrTIMvRarXt37SQPNTq6Ova7P3C5r7xCDLXIoNMtFDV9+D/ekUxItyo32CROtpWmuBRGX9QDIjlU7GRMB5/itESEhGUGp9jUgBrg37WM/tJwsCnhGYQCGMeT5aRhczR3oiZGmCDc1JL730DUBNj+XroaAZHcM4+hocOnidhtogcQS6G0K8c/uMkX9TbMe1m7jMtO0wbwYzEREREREROxX8ifKWHh8BYB4NZpr0H9yb4VEqa0SKs+gnFXUaBOiBvfF2YNJGBegzNdtiS7XWbaOgKmKjnoK194QCuQDRs3OWOE0Cp9L6mACAzHgwG5UAShPZU1A7O4eEZZlspJWX6M0wMbThyZht9lzfZxhoba29af8+T9DrpeAzaipJUo6io6afI5m0M9+6BodRgXaqdD+thGCGZuhrz5uiTFyS0JZyARaVLr8gkNpnfiOnKMaUbma83UPCHDtlNDqmDwhprsvA/yGxuDVj69nS2pqePr9Jz7CGjaGfKT6nKijQqWCmi6KXqOg16FmkjVSTkAkJI7XMtkRqV2HT+QSio6OvMg6aisBd14fvduu7CJu2A8q7h3rRKX4S1sHyZr8vhkU6De5nmhIyhr5HVD2FCBcuDQhBLarNfGkP2HS9ySx1HHQpJkP3FYIgz5wjdmuhui+mWrnzuCoYqoKCt3RE1CgBLQzjqhJZWkKEwzJ2Sc9o6tRG1gc0MaOYmI6uQwqQDiBTzWBmbMD1tpnxamzSwDHKPbrWfivyAYIUDE16O9s44thlglDT4tOK/qmodMwlEL6bCQnPjVoZTfqciF0G82YwA7iXdN0oD9A6LE7d0hLgWXX78Y9QQjc92AATTsAma8+wZ10O1Gl9T5hZuoePVARCApwye1CmX35pWgFpSIszu8QlwQW1SyxV5fIccU4HMh3b55aGP0j1dAP1vpvL4MZPS2CO9bf5/d/SuZlKztBqlZjuq3an7cqGaydUoOBu+QkIf8jsAIIKtFDaH7Y84XbAKoRa2uEt/ebvOwEteSZFXw8anp1gWDA+g8zrj1ILJ7mgyhSQcrvNH9gkVKhlMNNOfS+1WIXFbTWwKTjDTJXaJbDF49N4Vvd/fyoDZhLQnh7ACNhQezEiwFrapDAREJyi0umYiXACYDNwZT2zzARAZxEXPQaeCnB975JU2OUulniDAUECIbVv3Cg5gaDSZlMnhNj7h1EJLsicBykG/v03mBvLQUhVL5uXS9fTnMcfUFAm7JJhWTGXloNIVJwOXaraHDSlWeDaoNIXI/r3asKEbVuvSNDvqTuNFxRSLykSbe9ATbonppcfoVemF3iTIngTE6LGDNl6dfbWWqD9jNqWP81RddT3xQhRy9C2AQyVWWLMOYI0CIAV/s51QqMMGL2cchLBQKQuCA7eKcEykJhluctbO6T+QIqqwYzXJ35m9WCZUsIJ7HeQe31cZtp2mFeDmYiIiIiIiJ0GMZppm2HeDGYoNFtAJMy8ScDNPglRMwFROQbAMC4s49b8ztq8+9RoMDucRTznLU+BSpvgkVfUFSehlqRM4kCZ2FlTllXI0yos0lvW8M3uhCSWzShKhqoKmQ17PJU2fNRfXqlDyLnNuIelPxi23YQyp4xjJC/AR/WsMncJLytBg2OaWBmDnFWWOeGCos914tC0QlUxSG22J5m0Ga8pvESN3QSTtI12Sy1d5Ull75GCM9U/+qnx+8qkZki8JTuzQFhpRsfs12IVBHP3TEuHoPeRBRm2CQeI2a+kEEzP3KlElpf2HuS9xIlHuaIFhAnvlsSap5GSgMwwiFQLvlsCvGNTdgfpCPK8gh/CaowmOaeQ0kt6SqXNeqxmwJsfIDlgzFjbbgzo+t1UCaJLr6211CKmAJlI9HOT7byy9aXMJE91S22mbYNpFeqfh7fBJWfV19kToZv7JGECFaeYmlHLisXaNtJ16lrkXnZtyRQ5YWwXfBalagHVqISwzLDX7lSCZBxyT9XuyakM0+vUzdr5BUO+XrM0kwKsVCJgAKjaLmmppIBMPCNEj6Uh9ZQRw2DYl4bVHJP0tonVIpoytodJJyI2mdyDczSxxEQCXsJNYyVg619nDj1W3WIOARAROx/mzWAmIiIiIiJiZ0JcZtp2mJeDGcdmhKZWhEpYHzLuZgWESTAt2JQ6eaHPxrjke/rOsuGH8FgaaVkXtY9LWQAvBNHVUf/fE7AJQVBWDFTPHFigdZGBhgOSOJt/6XQNWVopBoaY5IMuhNgke2yafdUZkGFWaXWxb9Ox/mefZRnLe3ZbllSB7mY2xicw5fP6IKECqRdGnTCBbqqmv1xQK6auCuaF4RNUBUOPpPa4lmbDWkmFhHHL/PjnNloPXzPjszH+/n4de0icBopKyETClO5b1cO7z6RQ19Ya13VK8MywC2oWW1WeENzE4IpQawHmZs+SOy0ZoQKEOOaJEAmh/QYYU9YAfui6qX/F2dDrNMxUsQ4pCSpOHSvHKQotjBUFAwpqLQ0giQ07B5VONwSAJE5YWvWZfTaFIANO+JS6Z8GHEHURtNvGqLTHSen0IaXua8Og+szexm6OokjAu6o9yQaGdFKX14dl5ESqrjvTXo6kcqHYIlOMGka0fip1SVeFPre5r7PxPkqtbdo4kqJcrQrJNhAk00DS08dt1IEHALhJg2Ikex4LLQWZnZ3xWG5Fxujj4PqR1Gm3mtYJBDAPgBTU63MnDPaT6OoTBMEFfkg4rb1X5bD70BMe02Q7MjN1xmlLjo8AME8HMxERERERETsakZnZdpg3gxkCN/OidpFWIvFmChWnwai+MZS4NrOQXhigFCRYKyZUWpZGCqKmPWZWqWeIgFqjtoyNmYF76n9uZlyCoNR6BgBgtELmJT0U0kV6cEmQ6dnhSO4ilKjW9Rh2wY8u8tMT1FGPAGvywzKYKyvT9L0JszYMhjl3nd2YLb2Cb6Qn9EVf0OqiVyVoa3M8LqjVYpSCoW/CYgWF4ASVNu/rec3uZCWkJOiWKgKFURFENg1rm/CEAIH5H9TsMNfMWK9doRAU6Llt1jSMSjvThQSKmTQwVhwZUdN4E61Rao1UmSY2qsrCXGYCG5UkpY4E8fuTunvGJG1MqIDwptd+YlETXeffT4YBLAWzs+xWWqFXJsHM2DEbTOm99PWQnFjjQFCpUjxoHRGdYUDhi950Yalw2jQgjKypFINh+i5NXdoJIUnAvtQ1M4YtMs+Y6ePEY08NI2OO7ZUpuj3F8pWTOdg0cx5xHOAt/bfHwhGhtlHNzFDhjDhpCdAehaAmwo4g7ei0H0yAMhdFR4hE1lbbSLtEj7ZVF7QT5M8CTGupWmthE172FjMUi5wfI824YzeoY2cGUNPBEHfLWy2M2ygH+tYe47FCUri2SAHP1FEE0WvCZ8qpSrXRlPzUMHIumsmxTEJ413vHBDZFbCXmzWAmIiIiIiJip4KQnmX8Fh4fAWAeDWZ8i/0mvQfnSkMhff8GvZ+vOTGqeuvbUlPYB9vg/W1YGTO5ToWnuAeCRXz/DyltnUSpmKPCq37dOMzMGkeyopE1qLMws2lR6mxIwM7UPm+KcZnLuTb2WzYCK6EuxQAjwkUJNdS7bvYXnMf7s5OUEKjs+Qw7UgqGLlWz516Zoo/E+k9UfYauvoZFmSBNuNPkMG5n5SkVSBhHzly02TCvFMDdg+20tH/3yhQlSyAt8+GxfIJY9k5pIojVH+R5hZFcTbO7ZaIYEhMFlZcewxj6CPkz6cC/RSotmWFcuHC+LIQ4rQgAsLrOxGM3uCQ2GstnPLgkNrLH9KvRd/GSQhTM3vOkouEzJmsMgHTf+/5nUhDAME1+kJUERNeZxImMomRak8PV88k0W0U9TZGfVJELirKXKF8qXYlEs6VlopmlKe1UVFAk67VWpSJIp4FiXFclcc+2n5YAAGQK8LauPnfbWB+QlICWJgUJQ9nVVEaLgyQCiY7iyhIesMt0D3XdZrI2qlGGZEonWu0B6ZQqIt0IiJQ5WVIiIOAiwUAaeZlAW2M9qcz7c2Bfx6o0JX60DAnlkNJF8PkJZNV9qN8FbFCHFbwf/ChP4eov4Fgm6pGS23V4EDUz2wwx0WRERERERETELo15xcyYGYM/aud+AjMiVZI9Dbte60V6SMO8+Cp7e4COKDD7UmmT+kkJgElQPetLMm5nGtybfUrjMWPWgwsXiQFJILlLWcArikKv/RMqkTCO8bZaaM9YhVbiWAiDJg3LgGamYVsT5hphNPTckCi0u+6GXhsFd9oVQqRlaRa2ZywzY47b3DpYV1npthlbfkokWO4ixCgV6GoPYCkIyp6qUwmgYAJZy0V/mQiagjOUglp2Y4ChMbNKMxOEYwnNMULq+0o09DnxZvEEoAlHq63YmPF2z56v1CwKIU4TxTwNkYl6M+fzZ7T+Pc6otMlIARf1Z5gXX2diYKNqPN8Wq93RWhhVBwEhKIq+ZkRKCql1YaQiIH0aarJ8FtSbfomWgGiIPCGJjmgxEV3CRdbUxV6ypOAmeqagIBVBmRrRBrFuzJK4YwlX6QVsahAqIVKdMJKqdBLZpDqOFQDTSSIpB4oxuOgggkCeZv4WifsHaA2NYWZmlCRIJJql6wNSMzO8RSGZRNnSOqVWgvaofh+kLqpqbOEMijGmHKehtILlRs2AmDQr9t1HbWJVQqAEPA3vhLoDMyAdqUXgaVqE9vTSfQlvG3GsDuC8eppAvGiyJv+fpkSoSoOm9DGAupVsUwKGffvRHb48ckuPj1CYN4OZiIiIiIiInQrRAXibYacZzFx++eX4oz/6I7zrXe/Cxz/+cQCAlBIf/OAHce2112LdunV46Utfir/5m7/BYYcdtkXnoERCoNnngjGBJOF2qMvL0DFXehNAQqXnTElsThWbPNIUn7sbjbUq0ESg3TLRNCTQIRgIQcAlILUXBSlJkEQQgHMH5gRCf5d1CozkBUYyNRNrecxAffg+q8akBl9nNMwfZtgxQ7d7rITRrVSCgnPHbKgy+NBj/UinAQ8cL19SvU5NWhtKnZ4qY120ksRqYSan2m76xlUOJFMCY8JGItUh0JwDrH4tumWKqb6aIfd6aZhoz2c9aOifQahrC6POuXkkK9ArU/uO85kYs69lSPxZsCSW9BAI/VV8docQAjbEe8WgsNs8fxEibXsqzsBLBmGesb6XFLUa7LN6EkRp2NM2t9FYqk/0PVFR67miNsAyOkRHRDkvKAKpLyEp1fNLNWNEC9gcV4GLrQBI5V0m6rG7Njmt+qzce9XfPFMeMrR0ZZr9JHPRTCKBzsdkmCAv2JETiMRpXETinINVuQRSC0BExtAdVW0pFhYYHe3aeuapRDLhvHz4iH6nFAyyZIBXR9s2y764d5+/zYfxO1L7IWDU/PvY94ipvw8Zk7Zv/fvMlau2pUk1cKyvwwlQq7OTKHr39GyhmhE7LXaKwcx9992Ha6+9FkcccUTw/ZVXXomrrroKn/70p3HggQfiwx/+ME455RQ88sgjGBsb26xzBOZm+jspiRVfDiR5FbDLEIYatWUxJyFWaQN0GYKCtKTN1JqNlO5HMlV28eY8lKqXui4lyEwrmIQw5+ZuSUtKKPtt4zROpRUrjo30sGRk2v1ADxHI1n/860tJ9c92CWogtTAaUT9/0w+6Pb9XJCMCFaH2ZSS8JIKAC7euJyKsL5MNS1I4G4QkyDwjvCzjNs1CN02VqR4AKWkg8E4pt9mwTYh800Cq8ZwmMzbcoJYlQiVPTPWbv+8tZxLYJUpC1RLoTFeHiDOBtK22meWmohp8tBk1ZoleaLX5Y5b6EiLBdX+YQQ3zBNnWnI6zYJBelAmYfhaEl9KBG5GwuU6JhHWM66jBojApCySs0FlK/TzoNCA05XYAQ4hblhCVMkGU9jmBe4aMyNks2ZXUnppWRFkm6FuBcGIHCn4XsQIAc5+l90NtBj1Ed79M4HWyOtZ2NYW9FCKBe6aI2scM2viYsD+wfIyClAQ8Vwe2n3Ih1iJVxxmzPckICj1g7GcJunoprNMq9FKhdw11SHmVUVScoeob1zzAt4nwB8OzGegRIr12D2YRl7XlfUC/z2qJbs3kpn4WQqSdcBDistD7aUQGyiASgACz91P4nnPv5u24zCS3cpkpjrssdrgAeGpqCm9605tw3XXXYeHChfZ7KSU+/vGP4wMf+ABe+9rX4vDDD8eNN96ImZkZfPazn92BNY6IiIiIiNgGkNvgXwSAnYCZOffcc3HGGWfgla98JT784Q/b7x977DGsXr0ap556qv0uz3OcdNJJuOeee/D7v//7jeX1+330+337eXJS+YX7AmAfVnypxZtmxpBk3M4q23lp9zczf58aLfWshmoGZ7blGJ/hMbOJUrIgLT2hElSHV8rUCe4IABAJppMDttqFFfwubM8gIWEI9lxEuH4d62Z09TL8tiRENC7jzHa+JhbIiJRLwcAlRV93Na8YCjMblbSRidlcDGOd/PQCZr8Rbd6XjAlMZqqOG6dbqApmDfXMsYDuDxDLIAm4RJ/1fkyoCzXvJKVlO6aSHBvQRmlC8QW8VARe/XRCR2lDxhnKXJ1L9Wdly/SXegz8bTac2WMsUz075qWiJfqFM7ijVCVqNILgjHFw3c5+xdDtZyj1EqkU1DEn/mxXC0CZZlgEldbEjjEBSiVK3ceSk8DewFvtUWkdtICcMmeUxk1osLFZEIDUDx7RPwBEMz9EAFR7HajwaC/Rp7eUJBJApo41JDRkZOwx5nG1xm9um4HUb12RwgnSKVzKAqbPa9otCIhOLEnyErKiqLRpXjXNwHRagmRGt02frxzx6seJXTrnKbXvNl0jy0pYtqMVPreqjppB8WjsJmbGfmcDF7x66KUdkrh70K9LPfFnpu8z5iXBDZei1fPkL6X6z7mUblm0ErQ2ffeY8qZ674a4/PLLccstt+BHP/oR2u02jj/+eHz0ox/FQQcdZPchQzKqXnnllfiDP/gDAOp39r3vfS/+6Z/+Cd1uF694xSvwt3/7t9hnn322SzuasEOZmZtvvhnf/e53cfnllw9sW716NQBg6dKlwfdLly6125pw+eWXY2Jiwv5bsWLFtq10RERERETENgCRcqv/bQ5WrlyJc889F/feey/uuOMOVFWFU089FdPT03afVatWBf/+/u//HoQQ/OZv/qbd58ILL8Stt96Km2++GXfffTempqbw67/+6+B8UOe4vbDDmJknn3wS73rXu3D77bej1WoN3a8+SpRSDh05AsD73/9+XHTRRfbz5ORkMKDxhYjc02WYWQCxLIsTTlLUww69+sDNMFU5zqq+rFgQ+l1PTucfY9MNUIBQrlIcNIASiTxT9MVoXqBjGATNyszFDI8SaetYCBYkRxSSDBjUzVaOf9xcj2nU5BCJPKlQpV6iRj1DYrWprR+mXT/nMDFwE6Mz23Gjul87SWlTIABAN3EiijytrNamzu5AOhF2JWmg+QFCbdGS1oz9uxQMU1aD5RmUEbgEgq0KqU4YCqjZtLmfumUKRoVlvPw+MGkhAhbKiqB5oDXgnsZFSvecCMEghNM2cUFt+HW/n6g6Wu2HtMZyoufmTSQR6p8JjWcu7LwSyoqAmZk7JeClF2LNpE2+6qcOUXXT2qNUgHNimQ61r/6jUJoTw9pIKiFyn0GQdhupnFhX0jqDA1DTxd7fIgHg3BkgiTfRlwAqN4MkHFafA+JynRKdZNKIj+VGBqHDxUUqUU1wkDF1wm6Hg65T92S+jiDdCMe2eboe2qPgqXrdzwDI8jJIV+FDaVAG3z8+Iw3o+6LhcTepL8w9Wd/FsHuAOo//vulVCbp9I2pxrGLGuE2Ia8r22RjLsmqGlASWAeE7wP/9d5pJYmsqG9r+nEEg0FRt0fGbgdtuuy34fMMNN2DPPffE/fffj5e97GUAgGXLlgX7fPGLX8TLX/5y7L///gCADRs24Prrr8c//MM/4JWvfCUA4B//8R+xYsUKfP3rX8dpp522hY3ZOuywwcz999+PNWvW4JhjjrHfcc5x11134a//+q/xyCOPAFAMzfLly+0+a9asGWBrfOR5jjzPn7uKR0REREREbANsCbtSPx5wcgqDuf4ObtiwAQCwaNGixu1PPfUUvvKVr+DGG2+0391///0oyzKQgOy11144/PDDcc8998y/wcwrXvEKPPjgg8F3v/d7v4eDDz4YF198Mfbff38sW7YMd9xxB4466igAQFEUWLlyJT760Y9u1bnNiL7gzIUBGotsL2zYJr/zFsdNigCb5AzE2rILQQN9hJDErv+q7QDVoYaJ1gYAalbsG475ESG+st4o/TuamRnPe+joaJom1mGYpoVCBuyG1XnMkV2pl9mkz2nS2tSjjVQkmNOVSEls25CV9jqZSCG/vM2NWBpW92GovOtm2JfFnWmsxQimeyoq5H/WLMAGbUo20elij/Z0o54nI3yAMbMsiFeN0bRAP3fW/jOS2L+lgJ26EyIx2irsTLVbpig0OyIYQY4KgobX1G/3sEgzM5vlkoJRgU6m2Kk8qdDX0VHG/M4PffVDZQlxeghIAl7ofqTSakCkINrQTjMsiQwillQoj/osRGjsR5gATU0Ui7RslT0PNHuTCMCETAsC6O20R0Eqp3eRiad3ka6PzTautSoik8omAQDrUuRrPWaGqLBrdW4Es2XW99gXDZtlIVNMC6AYHVMP1idgXXecyJyBntHEUBsxWZm8pOiTFJJodgaAyAGutS8iD8Nm/MhKn5Frei4SFr7zbP9IGTAg7nvDBLr9LEtT+7//LGdJpf4xl/zUaGbqVgGUhFFPJq0GJapOfpoNGy1YY09ljaW04d10xy2VbCnqcopLLrkEl1566azHSClx0UUX4cQTT8Thhx/euM+NN96IsbExvPa1r7XfrV69GlmWBQE7wKYlIM81dthgZmxsbKADR0ZGsHjxYvv9hRdeiMsuuwwHHHAADjjgAFx22WXodDr47d/+7R1R5YiIiIiIiG2HrY1I0sc++eSTGB8ft1/PhZU577zz8P3vfx9333330H3+/u//Hm9605tmlYLYqmxCAvJcY4dHM82G973vfeh2u3jnO99pTfNuv/32zfaYAdyMw0+ax4gES8JReLCe6o3azWyBURGM6DPGkdY0HGZbJSgqapL3hVEl9TVpMzuiVCjdjHdPGC0AFzRIGknhmCSQZg8Z+3ctBYBvGGc9T7aQ8ZgtAmqgHjV9TZ11STwfEz9SaFh5m1O32Y6rs1hJw3r8gqyHqSLHZKUebDGVYkbrPtpZOdC2YdFkFM3bWqzCSFqAjqhtacIxk6r+6XdTqyvpd1MQItHKBqM+UsqD+yzztDADepkh1416TBIAlJwF7EjFqX1OyopZvyQpiI4+cpoHe3syGUSJOHYG4NLpzgiVYMwlYaXSpYyAVDobn600zwnxk0L659QfjWeLyIVNfglAG+Dpa2YYG7NZwKYzAJe2jGqMA5JZZkZSV74k2jvEaIBGnG4FBKE5XipthJTS0zh9jkitXRVIBSTa745zApFTiNwkl6zQ0uxgj0j0kxTUsFU5IHRqAzpeBGlRiiJRaVRMH+rrneclEhYmIx2mQwuSQsK9O03UqIki8rU16gcvPI7X3m++NsZELnHOvPLV+8F4KtWNK/37vH6PNzExAIK0IpJtR2ZmGzkAj4+PB4OZTeH888/Hl770Jdx1111DI5D+/d//HY888gg+97nPBd8vW7YMRVFg3bp1ATuzZs0aHH/88VvQiG2DHe4z4+POO++07r+AEv9eeumlWLVqFXq9HlauXDmUDouIiIiIiIgYDiklzjvvPNxyyy34xje+gf3222/ovtdffz2OOeYYHHnkkcH3xxxzDNI0xR133GG/W7VqFX7wgx/s0MHMTs3MPBeYLVX8sGgXRgRSj5nxE/SRBm8W474aulQOH32rmS6xf6volHC7KkMzKXrfHneXz7AcA069ABLqZtoFDy+5z9LUnTMHMAcGsWkWV9do0BpzYLb5LI3vmdNU7pZgmD/NMBbFHGOjgQjBeN7DdFsJJLoE6Hg+P7PVc/boMscCLcpnsJ60ASiWZTxXJiLPph1MTWlGqM/QI5nVY7Xy0pstK1bJaH6ER/HNVod6hJiPlDlHZEIkGKH2vu5Tab2BCJHgFbU6FsXUGBoCjqIwM3ajAZIqhQcA0ESAg4L5whOPaUlSHqQSIdrml0iXrNWeW3iUiO0EqSKTjM9M5ZgZIgAk0rr+SuaYE5FKQLssg0pUo1V4PsNyFBTgBJQbJtg7N1HRU35aBOszU5IgAqq/SNpIKlq5ZJVJF5CMomSKmSnSBIn2pBoZ76GbCHThLTGM6OeropDW1Vda3xq1kdhrITlB3i7RaSm9VP19IhAyLgF8Njk4TNo0D03vX+MuzcXgu8NpbGB1W5RKsFo5hp1JiAjekU3wmUr/XJUWblFWNR73XICEUqYtOn5zcO655+Kzn/0svvjFL2JsbMxqXCYmJtBut+1+k5OT+Od//md87GMfGyhjYmICb33rW/Ge97wHixcvxqJFi/De974XL3rRi2x0047AvBrMUBLmqfHFa2r5yVvugcuFEwjH/AzHACAJqiDMOvxhNJl8uKRBiHFAa0r3d1Wp0FdjSkapMygD1A+c2Xdjv4W+fogXt2ZmXSaqjLnYJkK2ZzPKaxooNaEuKBy2FOaX3WJVYwhzvR5bk7Jgc5aZAoNATzDerxL74kxH3WBjNsE10LDM590L9f4YTdQPyQxSFERdt/F2zw5quzwH7yboW3M9EixFjuW9xrQKGeMD19YXJps6VjIkbCmRLis3YXrg7DKHm0FoKajKwKzFyFxQazDI+4n9hZNCCYVtTZj7gVdplMNUFsZQz2Rb9g0mDYLyoH80zRecqEEGAAi9BGRSGJThj54kCH+UJ1Q7WatCps0Tq4rpEHSvL80Ai0pVf1Mud9m17TlMril/ySOR9mPVEZCJgJzRmaynqF2aIlylLzCCZymcGZ4UROW7MuZ2goBscK94puvEO8KmhAAAdJkVHwueAu3S9nGScHvfASafl/7gt7820wnzdxG7BmDCtm0ARe259Cd9aSDYZfY96E/8AKBftZBzdW06aYFOUg4dnNfvf3/Qb5/zXXCZaa645pprAAAnn3xy8P0NN9yAs88+236++eabIaXEG9/4xsZy/vIv/xJJkuC3fuu3rGnepz/9aTDGGvffHphXg5mIiIiIiIj5CjnHwc/b3/52vP3tbx+6vdVq4ROf+AQ+8YlPbKuqbTXmzWDGiGVpLezOzEJN0knmmZk1LQ1xHTrtw5+VBDMXDybjrF268sS7nNCAfpVwM+qRtLJskhHWEW82zTwmoy6UtW0Uw0fLs4l1mz4Pw1wYnAHhKwkTNNI5PGhbk8pgoJ7DxNJDRIMzVYpeldpw8rFW34bGG5M63wxv+LkGWRn/GHM/+ctuFaVYNKqWstYRoCgSu5zDvDD/SlD0eWLLTb37vUkgXjfxA9TSXyVpkKG8p18VpVB2Br1KpzqokkAMD0/YzrxlA8mJy5INuKSpUOHWLhEkUcyCt2xmRb6GcTB1phJmIlhVsGkUrAOdVdB6M39jkumvYhkSZUQoIa91tZOgWoCdZVWw5CEq4oz4ABcunnElgNaMveDEZrlHSVWYuKmPFwYe5GmAYo8Ma8QKwF5GogXHNgmua1s5kwIzzJn+eUlqaUnC7OM9ZgXHtE8DATPn1LIUKeMD6QO4JwC27ZehsWgQSEGAVHc4r7F+fooZE9xg3mm+EWXOKpQitHEw28qSYe1GlbthA2thtFVgj86UrbMxr2xaRvffP6Y8vg2WtOcK0pDuYnOPj1CYN4OZiIiIiIiInQrbeZlpd8a8GcyYRJNAbZbu3Qv1tdvUSyvf52ZmSgOrd99ozzAvZgbAagnQ/Fkyl9TOBPplgplKiUp5xUCZANXrwwnj9rhEz1zMTCOjwzUQdWyuId6myqtjcxgcu69/CBlkM5pYGMtezKE9AwI/r88TIhrX1StBIUDQ1UkWfQ3Uxn4L/YrZ2dxY1rdpD2arTxMrM/w60UBjZJifhArMGDYkK5SmRN8j7TxMuaBYRgUT7mrK8PsuoSIQf/tMDIRjLRMqkAhVRs4qdD12yk/Z4YfOmr4z5xapsMyDKJgSnBrpiyChfoQ7moIwgSQL2VQrryG1NCOmjB5TmphE14tKl5zSECPmFmQS1YjurVGujutpuoequgJAnzjBMk1V6LhhZggVSLSuJ004KBUh02pm/EKHROsyZUYBo4upqDPh66l0C6lOl0MLNwMXqQ7vTgw75ZrPcg4uFRsEAKRPLUsjiGNzaJ+CFi5dQjnqws5BgaKbour09ceQTVXXsyEItv6oep+Z96ATqYIbguvmvUuZ91wmVARscyXd+9iwpIC6B80putM5iiJBv3LsaVs/QwuyHiiRKDym2pZPPJZ+e2pmIrYZ5s1gJiIiIiIiYqeCN7De4uMjAMyjwcyw8Nsw4eOgfkFt8MO0JeDNaBMvNX2iLbbNvgkVlkUpBENChB3996oEvVKFUPbKFGWhLoWoCARnKPV6f1ElyHNVRospq++MukgSA1XX4bZBWxraPFtyxi3BUAM9KEbLZ822JMzZ314JGkTm9KrErrsDzpDLBxcU/YqhX6hZ31i7Z2eRKVNpJ/YcUevxraRColmzwtOpNLe1WScT7N8QIu/3h2EHp/sZetOZ1WlQKm2EVc6qgA00bB6g7s/Cy74opGNH/FB4k2zUaJgK7tgoU56Z7fazBD3NYhWcKTbS9L+nBZMJtxb8hSAIBCfSRRdB6yGI1pmIhMAQFlk7TN0hPYZUCI9llQAEAZ0ZvL4iF5CJdzoKSGMsRwVEyVzoN3PMjyiZZUtZImw4NKBSoTj7BAlGpb0v6s8oz0u7b69I0Sc6jLqkYF3NmHU1G+PrZAyLo5It5AAAWoNJREFUxQDB4KKDBCxzpRJ0chsJVpIMZNrTKRn2pVKh6UGaBdNVHJCFYzArSW06A8PybUq3Ntvz2ZT+wNyvqWaasxoTbcvV9+NMlaIUzD6/I3mBKamY7apkqPoJTA7oqak2mNY9bRjpYnHHZYfOKLfWBRROc7hdNTPbKDdTxDwazEREREREROxUiJqZbYZ5M5jxmZlh+gZfX+AzLH4UFNOsjNHTZJ4OJtEW/P7MxRjb9aokiITxWYGKUztrJRSgTFm6N7YDEoXOOtdki28YAOHpQ5raWvdtadonLLdJC+LONfw4sYntXrk1Dc1cMMy3pglcUswUegbnGRWWlVvVl0KzFfqLLOFYkCvHsk5SohAMHe0D49fdGBPOJdpqIKooiCSqYLIKqv1cwkjLSEhlCMe1CVqZOI1GnlRIiLBMiu8f02tgj5rqVO9Pf4ZMiUQLlf28IOuh0Nb6G/ot9HkSJBE08BlQyqQySLPeTfBIRcVLGcM7kkrrM2PrVas3oKKNuGF+aApZUpB1qh8lA8So7o/REpQJVH1nbEm1liTJOEoC+5mlHHmqfWaYsBFr5t1gknv2K9fmfpmAkNImOlQJa9XfxmvKRtAkFKVmVUTGIHVoFuHKzM8QbILCvqlJpfUznneNiWRr5SX6RYKiq9ie5NkEiWZ7RAJIqyECyjHXizKVgH6NEU6Ailp2x4+eNBFErEFrZrYbNJmJAorZpkQG7z+zn2KdeZDGxGcpzbu05Az9MgHzfMAWjqhndCMT6PYyVFqXJHoMvFTP/JqNGdaNdDA2oryhxvMeRrTmrZOUW806R+xYzJvBTERERERExE4FiXB0viXHRwCYR4MZw8zUZ/LE+5tLAq6ZkwxAWvMQAfTaqjdTbbEyYB58n5CCMxsVM11k6JVpkFTNahm8xG7m+5FczRgmWl2ruzEzFhd1wgdm0X5d5sq0zKZNaXKSdds2ndorrE89Iecge+RHG83JU8b3uiCDzr0JHLNB075jKTyWzI90yxOOVlraCLIFeQ8tpu4DCuV826Rt8aMiBvtg8xyLjSZKgNhyF+Rdq//ptxJwTsErV/+Bdtfcpk3/ZIQ3XtOmqDh333HLQPZ4ip5IbGRVr0qde7V2AC5KxyxJL9JJaMt/UVEQJkFMpFPJrOeKTRNifVSch465RolJQkmcVqUoElRTOgKtpCASqBbp+o+UWDyuPHrG8x4yxrGu21F9WXmRLUygzFhwL4xkKqon8PwRFKVgyBLXvz57ASDQZvkrARzM6nAYExgdVSxBL+Po60zHItGMijnOu6dIpXxnhI5E4gWDbFX2PJQ6Jot3BGRqtEcSUqdjIExCEmn7mBIJoZkqOaMiwXp91ZedrLSJHxPWrAMy39GGew5Q6WBY7bnwmWfzXmuxKoiwA7xnwXuPTBcZNky3bV9T5s4mhGLCDLtG2hUE1Reqz1D2GZ7VfkR8EbEM+ygp7HPO6faLZoqamW2HeTWY8f8PhD8yKeNBvo+UcTuI6STl0PxFlWBW7AcAlXQvemNgBqiXG2PCpkivKmZfGNR7sVMmkSQcY9omv5OU9kelPhgwbXB/Nw8ugn28dA1NGCZinW0gQokM+0CEIlMnyA3N++rHDat/Jb2BX70PvOoaAbEf2uyfy6ew22lprcxLzgJDrrDOFBUxqSDEgNFcvW8b+3WWMdlsKSLq28yAIk8rpCm3qQKqIsE0U1T6Hp0ptFhlr5ff58OWkZq2q9B1Fwprymux0vYDAHTLzC2dcmUoWZgfRk4CUzfhDRzSlsv/U1YM3WlVf1EwoM9AtGGczAlKPSASNbNKKQi4/mFK1idoTetnqyPBF1XYZ5+1AIAl7Wnbd+o+cMtk63ttW3/ACXgBIEuqZlM1oZaLzBLUaNYP0nAUgtl7i+tQf/M3IdIOlM2yCqACBDaMKqe9tWMj6E9loRzC3NIFBeu6PFRkYwIx4sLyE8YxMqIGYDNU2v6RlQvTRiLBcm4HFJxTUB1kIIiEFATFjJ6EZZlbyqsZQ/rLTdwT2wfPINQAz+zbtNTvv3M6rMBYqt59DBJTXN0Xz/ZHsGZ6FACwfrID3md20ObfF6KikBW1YfSQbmAsUwHCCaRegtrw7Chm9JLcs6NdK+wfI+sRseth3gxmIiIiIiIidipIbKUAeJvVZJfHvBnMEAwKyoxgFxic8VPiEugFSQIb7p4ed6GpG8scU3012mdEWPtuRX+SkNq3wsMK7VzNrsZbPUxkPYymanYlJG1kZDYHdQrYlDsMdhkCrr6VTiXsltdcWLKQ1DIAhpXyw9P9ZQ1/1lZJCpNBzyR9M7O7StDg2pj+qCfMzFjl2IfapWnOIO5miCZLbicprbiw4Ay9KkVpZutJaduZeGLcJsyWxmFLUGcRTd3Hsj5SyrGWKgt3LqhlCQQICsHQYsZ4jNtrXSFMkjpMsOwzMe787n5psdL2+dKRjbaeBWeYLjM8y9QSzvR0yyZE9DMzk1SxGivG1+s6CqwfUxnB106PYHq6BfmU+kwnGXhHMxsESFsVuF6u4tMpmA49pgVBfw/9vE4U2GeP9Th4wRoAihV1YmaOlAi7/FtwZpcrTNZ505djWR8LMiUsLYRL26AE1pX3bDh21iw7z0VUX3nPTSIEaNvtO+1lQgdCQ8JeL0W1UTEWySRD2dVmikwgSytQE+qccmvQR6YpWN8wRATIK8fMVMwuAQKaydCn7heJXRonJENRJG4ZLqsw0VH9M5IWIPqZMf1plnAqES7Dm7428J+PSlKs7SsGZqrMMK3Fu09PjaLX1caifYZspLBCXkZcQAbR4uL104rlKvqpW37Umdttr3YZSm1a+MyGHOtG1PO0ZwfbDzGaaZth06KHiIiIiIiIiIidGPOGmTFrs8EsmQwKYX09xGxl+eyFmXlsLHNM9lrgWpQ4PtLzRItiQHxshJMmnBYARtNi+Mx/lhDkJqbFryPqIuWGmaMx9fOZFGP9XXCGgrvbZTTrN6YeMKG5Zo3cD0Wtp1/o8cSb3VJwz8q/nZZWT5DVBHk+01TwxNPd0IG+GdAAedqnLHHl2mR0XpttnRH2+1zFvHMRMA/TcNWREGEFii1WQqSOuQJg0yqYe1NY/cLsQuomIXj9WUkaBJELMyWoFSA28aCQFBnjWNhSs/X/TiawfkpNc8v1udXBIJVopaVl2xZmM1icKzOzBXkPazsd/IIsAABU0ylIV8/4+wwidaLZGSZQ5VpszAkW7KE0D8vHJnHw+FOO9SBh/fsisffnmBb4Auo5FJK4dCHM3a8JEU4AC4k2K0NzQ6+vKsHs/ZkSEQpjJUVp2UgKGAKQcnQ1w7son0GPp/a94t+TlaB4ho1gUpsKymkGTKltPWTg7fA9YHUlmQCZ1vqiDQwVzdAf0bokQQD9zpICAHEJLJXOT5VVlkwls+xrIToFptqKQVu4cBp7aM1JJWjwjskYDzRF9XfMjGZfelWCbj9Fb0brp0qmkpACSNsuCKMz0cV4u4+2d8+b69TnCUCF1WO18xJTiWLKy34CWTDVRmgGirl2mlf+ZLeN7Qbd31t1fASAeTSYiYiIiIiI2JkQo5m2HebNYKaumjffDeyDwZlqfcZcZyT8zwv0rBQAJvJeEE7tMwr1kOXwXGjcNnju4WxMNYSJMbM8/3xmm68tANTaN7dRGQSlYHaJtlclQV+ZaCBjZ280J1x6CQxZmHiz4iwIaW0lZbDdb4sJwaVEAhIQMtTOmL7a1MqpS/RY/971R8bCUPym/eaCzTXh2tT+WRD5JbCsvVH97WmbCpE06r8AF301Wyi++r8YTDA4hLE04eqqTgQ5rSxjMdNx4e+ThUsTMD7exfMn1ll2J6euv5/XeRadpMAebcXU/HjtEkxPq9k/n0zBC4ZCx0QvGp8JEgou76j+2G/kGQBApWmPlAhwb/o7U+VYoKMFK88iwbBapv/8+8CPgGqzQrVTP2OlF21X13TlrALV0+dSMpQ11iz3UpN0TGiwJOjyNCjfGGWunhkDIY6pKBZQN7PnFGU3tZGRLONOR9bi4B193oIABYXQZoeECctQEAKgoJC6HX2WulBvzZRIre0hFQX7H8V6bHgqx7MLx9V52xVAJFot1Z5l45MDei3zvnh2qoNCp3KpegkAAvT0M9zmNm0EJRKJZltGWwXaaWHZSJ+hrARFUWWWDZaSYI8JxRhNdlvo9lJUWmMECWtWmrWchqic2hqqZDMRNTPbDFEzExEREREREbFLY14yM00zUzPjbNzWwOA06RDG0n4QIQWEUVK09nfdbG8Y5qa9UOU1JSn0yxAgLlIHivUw7Eu3TCGEMwAjJPRwIETaSIWu9sgB1OwnTcwMioDDRTRwHcUFAAWXSJiz3lcsiNbFJFWQxK5bprYenaQMIpt8his09qNBvzZFgQ1lJTxvms1hY+p6iOcKs7KKErWEkSHTN1s54TaxyX2aYJJBpDpyyrAge7am0NXRbRPtHnLNdOzZVjNlw0SUgnplCOzdWm/LrgTF1KjSUKxujyNNONqpOm5Ra8Z6QS3OprEgnbHHCVCr9UkJh9DztvVlWyVPNOxLUgXtVaaYOnWJx9QqA0NTnkBKBbiZFXu3mdB9bxiXnDgPGMvW6G2MSLRpof/2PFsk1cyPeWadX9VMliGhApOpZqtGujZyR3CCqpdYo0JRuZQdEARCJ9SUOYBMuMSZqQCvdDtLphJs2jJctFeaK38j047pqRy8pd4lrTUUcoO61iJPIQnQy9V+P13cRmvMaZMYE5Zp7U9nXoJQAtaq0JpQfTbW6ltvm26ROrNBqnR4RnM1kXZRaaZ2QTaD9UXH1nGqzOzfKeWYyTJMJqrv+t3URnFxTtHSEaVJ7hi55xyRmdlmmDeDmYiIiIiIiJ0KcTCzzTCvBjPDIlsat83i7VKfgc8WMWNdMSHRFG1jjpjruf3z+1EmFBLFLP4WflSSr43xk2tSIrU1uzqGUQGmq2YSxHW1VX09qZyfFsLXKBDinjcpCcrK6WR8DU1CRGCNzwXBSKZmrZWkGE+UxkFFRAmrTQiZKBH8v6kffDRFrDUl7wy2z3JthnmzbA/2xo+mqd9jzg/IMVhN9Z0LI2Ncjoc5SSeUg+rzLEi7WLCwG2zzweXgteOSAIRaFuSAsafxtPYdWdbZiDYrPRZVoK3ZHZ994ZKAEel0PkRCeNU0UXsAAEnRYeo+y1kVRD5RIsEa7pGEclAIq7syUVAAkIOCQnjsi+vjFBwt6jE1kHY7JQLpQNSVYz9LnYSSQ+lpjF7E93CZ6mVK52aSLBbMsjTq9aPbwiQIE1YLQ6i02hHJCZBQyzYRJpDqdAl5WmEkL2xUl5AEpda09EhHaXEAsB4BEUC60XzO0B/T742WAFLhkowy93drrI89JzZicUsxbInHMD5DO55XkMCCrIcRnfB1NCmCeyklAk/1xmwdTR+ljCOTFRbopJQbiES/p/qYlxSFdtRubaWvV8SOwbwZzDSFXA+KR2c/Fmim7a1pmGCgUjYa8W1OWO8wozxjxtXUFjNwaqrrZJGjp+l+Lih6lQtNTakbULTTEpxR+7LKWeWlUlDlbiyU4G8myewLREoSLjulaqACqEGQGRBVnNqBktlmBkXTRQYuqTXo8k21WqzCWKIoZfNjbX6oSsGsuHA2bMq4bnMGs3NF8zLX4IBncwbOzecJlz3De4DCXwdR9+vsuWea+soINlPKh6ZtGDyX+zFiRNr7xQ9dbqqzKssMlgSW5pPu+yHXWoCiFJ5IHG6wRL3wcVNvI0ymREIwY4bHB8TCw9oi9KDF1NUNRNQyjB2k1PqJkbB/7PIa4bZPGNTApuUtUZVS5xNKKdajYwXBUyJHxxvYEAIUetBS9RlkT2cHlwASXRcqQaiE1P0liQu/JkxCSgmYnFqC2GUgIQlK4SZMi0ennSVDp2sz0hdFgrKXAFPq3LSgoKVbMpOCgIzqfGeJy0s31laGoUbonlAX0r1Mi7vVdRJYlE3bPp/iue2PPk8wVeVY21OWAN0yDQIQpvtZkLHbiNIlJ9aUrxIZthtiaPY2w7wZzEREREREROxMiKHZ2w7zajDTJPKd65LEQFk2FJNiSps+GdbEMjNMBBR/U5boej2aZurWjl4fbzJBz/AsKM9PmOeH6/rLN4BiYHxRnGFmhCQoSZiY0Oy3IOuizUrs3VH7Tlc51hdKeDhVunpMTecoS4ZEU9hZWrklKJ1oz7IxVXguxoRldPK0skLPTlJ4/UMCtmIk6WO6yu222eAzGHNl5Xywzbg/fPBZ6rWpczeF8tfR1G6TYmOmStGr1GM+mhagRFra3b9XjSEfACuCduW6+9Ys4fj1LqXHiNTqaZZ3Kq8ts9kN2O+GMDBcEi/8WdSuo2NO/P/7ZdVFzvUszYATNHMQy9JwyZDCMVp9kVg2IKOVFTOPsl7Asqj2NS8j15ewGFzdUsJry06KfUlJZc8PKJZLaOO/lHGUnFkTuvW0DXNVJaeannHZx81nKeFYGh0AYDW5JUW/1KZzGUeRJ+i03flG9bmXd1xaCyEJZqoUT8+o5cGN3RyVyfAugSyrsPeCDaq/9D0JqHvVN9TLaGWXl3Na2f7osAIdWqAn3c/Xs7o/zDVZmKulpHZS2oCHjUWOXpGi6uu61G4xsyRXdFNE7HqYV4OZiIiIiIiInQZRALzNMG8GMz4rMxc2pj5bE7WFTd+G3+gJemUKLonVp2SsQicp9d9h0jWf9RhN+nZGYdAocIVEIZidkdQNv3pV4hJbSoLKGNcJEgg2CSFgiUtMKMy5PJM8AJgqcnSpm6UUSRLM4BflSqjnh04XJUNvJkPBXYJNsy5t6mmYmaqiYIljsVIibahtOymtXgeADb2sX5dKhOzOpjCMkdlS1mUu8PUim4stFQyb+6xXJZjst/Tf6QA71dL3JzJnylcJZRzYpC8z/WSuB+BfEwEQxzgM08XUjSapJ9Zt6icTltwXSRgiDSDVQtvSexYMe+TDfDbpBZwmRwbCZHMOU45/f5nQciOAdmkciNXPGEYlYGa8/qibZTb9nWn2xRcLG9aGaTbKsBQjSR/PFiO2HgIEM5VOD1Am4KV5jwjQVJ/D9LGpv2e/kOYVKJUQUtWBV9QKis1z28l0Uty8ZxNxLsxmMMpc+DUAdHVIfd97t5m/20Z07Rkmmm3muzYrMZHM6Pa7NqdEsTSprmMrqzCRaFFv2kZfJCi9+9Ncw41VjsmRlk0q2+eJfd/1qwTTPd1vM9vRNE9Iy5Bt8fERAOphNBERERERERERuxjmDzND5CZZmVmTS3qmakKGjEnu2blXnKFbKjZjstvyDOgkGHVRDnla2SR3ddMuIZkLpfbCqCuhDO7MuetMCgAX2ixJYFwnvP0YE0hNeGXtWC4onBcYAdUMy7Oyg15aYDRV9RpN+nY9e3lrA/btqHMta2/E6u6YXacWIJgumqMDKk6tRialKpFfqmfJnaQ50WQ9JLiU1B7Da3qa2bApVqYeKdb0fVN96gzebOcwmIumZnMYmoQIjKfq2nSSAot0io1MW/DPaObQNy0EYL+vR7Bt0irAtNlEMxHTLhboQswksq518eHSJqhzri87WKuZh/X9FoQk2GtERTdNpF27HyWDbIyfRsBqfkACdsq/XpVk2FC07cy9EMzq0JRJmwkF7mNBOmMZhA4rgnDxoD2QYMS/fxHqcLxtjnmo62UQ7DNGu8gydW7DXACK2agEw2TRGjiOUAmqGVJeEUhOrEaEMAnKvHcQFci1oZ5IKURLR3sxjtG8wLIRFVm0tDVp3wFCEsvMGLbMsCV+v7gIJFXHUjD7/KaEI6el3adF3N89GepYGBH2XdpBgTGmzrUk2Yj/LhZZZoZB2PJ7IkXVZpjRerINZdtqy6bKDLk201szxbDdEJeZthnmzWAmIiIiIiJi58JWDmY2YTkxnzAvBzN1JmTYNh9+4kZlDOZmYGYmO5oWKtGZZlUm+y07s6s4RVkxcGpmOSLQDZiIk55exzUzxm6RemWoRI/GE8Kvqx8lZD6bmRijEsxatIvArM7X1pQ1ZgZwWp+MVRhNCyzOVQLARem0nYl1WN/OwJ+Xr0U5nlhdT1+kdhY2VWVY2x+1DMD6ftsm82slFTLKA48eo89psyLQW/hmZkKEM7a6LsH/3sfgLH4OrNwctg3bdxhjU6/LMJZmWLua6iMksTqQBDyMVIKLXKpq5Q1LveGjXr8mxmmYp1IY4TM84aV/7Hjas303qr2GjN6CQboZuKdLaopisuZ6Unm7BM+enp0XIkGvSmy/CEmshqvFKmuuZxJNGmaGSwrotpUiAahzPlJeMoYhCl+3DO4+ZhjsbxO55G+joGCgVk8zRntgOk3BBt7BM+Woff9QKsESl3AxTVV5hDBwGjK1ldbWVCUD5xSMevomE+UjEqwt0kBvtHBUMUMTmgk08KMyVRSn7lNI5LTEkmSj7h93LVLCwUGD9voMi+sXDkaE1QcyImwUHYfSGjH9fs5pac89I5U3lrlui9IZdJlhIx0TTBYQ/GzgajxHiMzMNkPUzERERERERETs0pg3zAytJeAD5s7KNPlgmFks9ezVAQRJ7Ja1N2KyVKzEul4bM2VmE6eNpIWNBgKASaG8HPo8Qb90UUllxawrLtcRG3YwTl2dDRPjf/YjRPw6KvbF6WlMNJYQBHniogvytEJbR7ssaU1jLOljUaaYmRYt7Zo107MtABihavZsZlQ9kWJCr2eXKcOCtIvJSvXJorwVMBYJEXZWCYSeIGYGmzNlHW8iH3xrfccSNLMKc2FjNsf5d3N0LMM0OHXMFvk0F/3MoJNuk8eKdnymfIDNaEJTfWbbf3MTVQ4cDz/aSGBRqu45c0/ZmTwVNRv7UGdi9vcjZtaXbaztj2C9jvAKfKFI+P8scQ60naRwySNppXQ4WoeWEJdCIte6JBDjL0Xtc5KSKtRqbYZ9q2kbg7RlAwCHwB6a5UgJx7pqxDK5UgJp6jlp6yik0kv0CABZylEkJvIxdBGnxOlpzHvIHDtTpVhbKj3TZNXGXq113nHNCV/N96mfisVGygmVagXOndm4IPuu00ynfrAOzA3pYAxfW4oEM9rR9+liNDj3COvbMjNa2fdxe3Q7JpoUElu1VBSjmSzmzWAG8ASNs+RkGnqsJ/A0tDSgXnyZ97LMqBOxUkhL6acsQwulFQsvymdsyGCPJ1YwW1ThJVF5j9zSVPCiocLSwXZg4YVBG/Gx5DQI2faXqlLKLZXOqMBo1rd0KyUSHZ3/ZEk2jTYrNvkCLiUL+rdFSzu24CAYYz2MMUVJ84zaF02XpyglQ+qFcfrl1PMLuWWnwYHCrD+0Q14cs5kWDi1riLnhJo/bxFJUU/2b8hi5H4vZBhaDQufg/GbJcrYX6iyRqrMdx4LnbMt9163BozatE57bWV0wbOD/wDEITFbK4PGxjYuwZuMYZrR1fZpyjHfU/dhKS6TeUicVEi1t3GgmQwDQ5epYc0/m1C1dmAGUHXjV+qB+f/kDMJcCQQ3STI4g5qVHYFDLK26ABPt8dWgfbeqWZKW3RORnq6dUIoGwwQLdfhosUZcVRVHo51AStNpFUIZ5d2woWljf3wuAWoaeGlP9ctjo/0BIir6xU/DqC8KRksq+R1ROLbds5S8z9UVql8N9wS+FQEoqcC0Knha5fS+UMglE15QIdPWAa33RwWSRW1nAgrzrJqXe9e3oTObbBVKof1tzfASAuMwUERERERERsYtj3jAzW8LK+ALJyjOWKzhzx1Kg4mE6A5ed2GVsXd9tg0sKkaltM1Vm0yBMF7nNRp0xDkI8k6zECd24ULOipqWkenuEdKGXfpoDlcWaWOHtSFbYtAEtVqGTFIEQ1IgtBwzQPBMrcz4AKJAMLMv5wkc/9JJBYExv20hbKCWzM9q+SAIWxs28VLivsY8vCbdLTkLSYNmpXt/ZMCyTdFAGkQNtC7dvXcLI2VBna7gkjeerz/w3ZQbYFFI8YL8/Rxp8tpDrcL/ZmLPhCShN/9f3aSrfZ9/7MrUpFyZ7LUxtbFlmn1MZZJ6uP0NWuCppeJ8RYRkRxQSEbTIC1KCmUiXY5MbQjSBIJuk/T1ktPLtJAGu3UScwHmM9LMgV0zRd5NgoHCNb6pQCjLnkjgAgOIUwJpdcJ5Y00facoEdSexylKu0IoNIZTPV1ckbetozWKCuwOJuyy9d9mSLX7Swlg6DULksH7xB90g1cJYmkRNhAixTclpGZJTxvLr5RtHQ7KXoitexvX6RB8AAXFM+WqvweTzCu7TEMA636ejua5kUB8DbDvBnMRERERERE7FSImplthnk1mGlKNGkwwKr4iRp5amdv9ZDSySIPDOK6RRowA2bG9uykWrft5arLR9LCJoQzrIwPP/yaSLNu3LyP3wajrQjM7wQFNToAIjHSKtAxBmBeoreWFjM3ifPqn1mNFTDsixJvUmsM5s/yOYgKp7UNcOGnE8kMSsnQ16HWDBn6ek289A3/tP28maVRyjzrcmPXPptAdvPXmJvYgc0vYzjzYffZFHvUcF817TVrPQZE7837b04/1e+RYVqZTRnlbcm5mtg7QDM8WlvT5wnW9lXSw5kiQ9YurUZkotPFSKaehYk8DC82TIM7Ty2JJgxbSEFNmhIqlK7O3Mc18Wv9yvvhxYZxqjMP5hlR7VKiWFOu0s+oPlnEplCkDHu1FgEAnu21LSsrJPH0JxL9itnP7VaBbi9zZxDKSM/UQVQ6CSUnIExaVidj3Gr0pBR44tmFAIANvTb2HtuAw8f/R/Wjl6CzFAygzjQPQKCfUUyKCywwz0pGXaqEQjLAY3HHaNeW8VQ5gSmeB/eCYdU7ibLOMNdtfa9t2aMpltnUM6TcfXUol19+OW655Rb86Ec/QrvdxvHHH4+PfvSjOOigg4L9Hn74YVx88cVYuXIlhBA47LDD8PnPfx7Pe97zAAAnn3wyVq5cGRzz+te/HjfffPN2a0sdUTMTERERERGxI2CWmbbm32Zg5cqVOPfcc3HvvffijjvuQFVVOPXUUzE9PW33+elPf4oTTzwRBx98MO68807813/9F/7kT/4ErVboLP22t70Nq1atsv8+9alPbZMu2VLMG2aGDGFl/BG8Sh1AB7YVnIWmeRBW79Its4A5mOll6Hsp5JNcm1ZxlV5ApIPr80YnA6h16PrM3x7RQAj4M1PuJYxjVNhZOEm4TV+QsQrjWd9FbEAO9Ilhd9KG2TlrUP8bxkXVhwZJ3sx2AxXt5Fgbs3Zu+r0MEhgK+5cNxSYSbcIta2OSEJptoqYlGZbYb0vhM3P1ZIlN+/r18uuxJRqaTSU/BbZN+LkfEr85YLOwPk1lBXqvIYxSnQkdeDaGaMYAdx+XkmK9Z/FPicQCbfa2Z2cqSGgKuCglX38lQOxqgLqeOnWDagmo/lGx//f6IvXCtAVcShUhKUodhqx0MP4xrk4M7lk2rE1oGKf2axGBvdN1OGREMSJdkeJhvlT1AWc2Msu0wby3WkllI5sqTiFFmArFlC9BQKRERTWb0ctseDpjApWOgHqmN4p+xWwk54r2OrRYGDZv+mBdNWL7Z5T1MMp6jhGXadgPntVEX6aW/cpZiWXpBrvfJG/b6DXAvX8yyrEg7wb6SZOEdYNoWYPQtNyOc3yJrdTMbN7ut912W/D5hhtuwJ577on7778fL3vZywAAH/jAB3D66afjyiuvtPvtv//+A2V1Oh0sW7Zs8+v8HCEyMxEREREREbswJicng3/9fn/TBwHYsEENAhctUkuTQgh85StfwYEHHojTTjsNe+65J1760pfiX/7lXwaOvemmm7BkyRIcdthheO9734uNGzdus/ZsCeYNMwM0szJ+0sZKsMC0LThOumMKyezMqG5OV/RT8J7qVpJIiESvB7cqjLb7WNJxdJ5JYcAFdevZTQZlXuoBKUnAwJhEjZRIMOq8ZRIirAGenyYgo3xgxuxriSgRlpHJaeV5aVTBDDGMtJADGhmfjbHf1f4viECvciyWALHbbL/DnwkDfUGVSZ+eTeessonjlKGY67eqwYCvCZujg5mNCZht38FtW+JrM5xV3NpoqU21xWddfCauuaxtp5MZptnaXJjjEsaRZALjuUvE6Uey+c+HkDSY+daTivrwIxgFoaCeTsTc0ykNGaCAQQRxrCQBUji2ikJaRoZCBFb+gMfWgCADx97pOlXmqDOae3x6oesDIiBSYtnmINoRKikl56o9sqAgBbUbJZUoC+2lwxIwwzwDmBhXbJdJIPvT9UsAAOuLNsZT9eM6kXYxnvawZzppz2kYlpRwMCqcz4tw1417jG9KOCCdTm9G5LYPFiVTGGddzBDFnPdFYn/kWCIxxTPLxPVYYt+X3V6Oaf1epeV2FNVuo2imFStWBF9fcskluPTSSzdxqMRFF12EE088EYcffjgAYM2aNZiamsIVV1yBD3/4w/joRz+K2267Da997WvxzW9+EyeddBIA4E1vehP2228/LFu2DD/4wQ/w/ve/H//1X/+FO+64Y8vbspWYV4OZiIiIiIiInQZCYFOi/U0fDzz55JMYHx+3X+d5vslDzzvvPHz/+9/H3Xff7RWnyjvzzDPx7ne/GwDw4he/GPfccw8++clP2sHM2972NnvM4YcfjgMOOADHHnssvvvd7+Loo4/e8vZsBebNYCZwidWzqCrQxyiVuz/zswkea2yBSoJY2bJ6WrfxzPQIpARoptde24qNAYDxvIeJvGfLXzMzil6hZiSJt55ccRpYdxMCoBZVYWaIKRWOoUgq5Uasy0qIsKxKnY0BQj1MXWNiPieU21lSSrmOdDLJ75ojWAQGWRleYw3qkVC2HpA2YR/gZreCuMSJJadB9EhKBRYmM7odimExepoZNKeicO0ern1p0rvMhb3gTcKm2rF1/cxc9y20bqgULEgmyYhEEnj+hDqhLdUNzca+DMNcWJm5leOuw1zLCa6Zp7Pq8swyAxhzzzCg/J7McQuyLkYSR893eYqUOta1zvSx4DpR7/+1KCji7VOLaPKZB99/CRi06Qe0E673HPowSUaXMbV0MNbqYqnWkjzaXo4newttfwAuzUOXOwdg8+55dkZ5sZQzKUz4Ie1S0ArQpt3gIxxCRz2xvERHR4W1kxKVoOhqXeFTU2P4BZ8AAHSyEivG1iMfVYXuna8LdHItWtokmimprOfMjGxhRqd8yWmJjFT2WTPfA8CydAP2zZ/Ben1c30tEW0qG1f0JTOkUM4G/EHWsbl5Li/GcYhsxM+Pj48FgZlM4//zz8aUvfQl33XUX9tlnH/v9kiVLkCQJDj300GD/Qw45JBj01HH00UcjTVP8+Mc/joOZiIiIiIiIiOcOUkqcf/75uPXWW3HnnXdiv/32C7ZnWYZf+qVfwiOPPBJ8/+ijj2LfffcdWu4Pf/hDlGWJ5cuXPyf1ngvm3WCmkjSYwZnZlv+92WZ8B4yWBFAsR04r51ZZtLGxVDODsmKgTEAHKKCVlVa3IkCwttdBZXIwcYbxtlq3z1ll124Ni9G4Lq/PaSID2kmJUe0X02Jl4Nzrz8hz6hLcmaSNQyN+aIVUM0E5Ke3szcyW/Aim+kzSlgHnnAov6mk2XUddL6P2N7NFd22YnbEb/Y1EX6eVy1GCg1qtQYeVNqKliaExZVR+BJXN6TJ3bYyPTbEZHHNnGgqR2GitHk8xVamZronAMF5BC7IeFudTAAY1OJvS5GwJezJb1NKsxw0516Zcf7cEFMLeu2nKsbylGIqn+mOYqXLMaK3Wun4bvTK158pZhba+19Vz4xgiv/7c83Ty68lBVJQQNW0WLucWtFtwwz3is5UcFClcRJMftaZ8ZbhzCK+VxQkB1ydfQLpYTBVruXeyDk+31cz958USlJJZ1rVFSmyc0AlxqxGsKcbwCN0TAFCUCXpU3XeySoGCwli+iNxFOglB0dd+We2kxHjWt07EPZ5g2rqdZ5iqMpuTrUVKLGCqjkY7Y5gaCuHyuHEa5L3ynZN95/BpkavkpGwKptMNwzWtGRzjBt3jidXsdanjwVLseszMXHHuuefis5/9LL74xS9ibGwMq1evBgBMTEyg3VYRYH/wB3+A17/+9XjZy16Gl7/85bjtttvw5S9/GXfeeScAFbp900034fTTT8eSJUvw0EMP4T3veQ+OOuoonHDCCVvelq3EvBrMVJKiEi7MOiECoYiSWKHseNp1L0PvB9kMgIwl9uOTC7F2vTLk4n2mHm79VExVFIVJU5BWSBNuBykL2zP2YR+oB4h92VaCBmHUSGGXkjpJgbYOf0y88E8DqutPSZh6IKXOoKtJVOrazYNBjD8IYmi2rqcQgH7hqs/hwEYd6178PFjqc32QUg6hX1D1rM2pt4TGiLRtqYeE+8ZpKeHKSl2X1eWZfakBsP2YEg5KpF2iqGNzhLA+hi0/1SEksYOrdUXHisQLwSwtzqhASrlNCGrao9pR1AYDYcqJ2QYHcxH1zkVoPOwc9QzdTeHYs9dPBIkIubcMwyBstmVAL6Ho4rsis/cxoN4DRugfZLwXFN0giaxLKSDgsklXggXX038/NPWhKSPV5Zl9U8KR6QFLkNVeEnDilmc5qFeGQIvUhcTSnjvVR6j/ujqOkQIjZC0AYBGdsiHh7pw6E3aW4+lszC7d/qy9BD9Zp4S8z5AxCJ6D9lW5pPIGc1TYYASVBoLY+3M87WNUpwuoWhQtVtp+/u9iERYlU7Ydz5RjeLoYs/U/qLNat80lmkwJxwjtoyfDwQ8APFuNoCdTjFH1bh1jPWQwqU8YclraZ3007WNjoQY4raxy5ZfuXnnOsZ0dgK+55hoAyvTOxw033ICzzz4bAPAbv/Eb+OQnP4nLL78cF1xwAQ466CB84QtfwIknnghAsTf/9m//hquvvhpTU1NYsWIFzjjjDFxyySVgbDCAZnthXg1mIiIiIiIi5ivkHJmct7zlLXjLW97SuG3FihUD7r87A+bNYKaUDEyoRG8tPWOoamHYCRXBUo1dyiDSJocreIJ1RQdPbFgAAHjm2THIDW42JzOJdFwnL2sX6GQ6iWOilpzM0tVo0nesijfDrgRD6S15Cepm0+NpDynlloUxS0YGA8kgbeoBGcyC05rAzZ8N+2Z7Ka2CfRU702Ck5wseQVToKMxyGQCPNeIeU8MgIUydJQ3Etj5jw4i0bNFswv+mWX2pwy37QjExhvXo88Tur8LO/Rk6a5xh19mVzRHIDtu3XmYlmV1aClg5IpFlzswt84zeMloFAlRKuOsvIDAcHFav2ZijUNS75ZEXczHJazzO23fY3z7MPTvF1ax7Y9nCgnQm2Mc+h2mBEbNcl3cxlvRsXw6I5E0oM8jAkllqmVuhBcaDy5Vmu6lfFhjCee0iUjNN5hnyQrH1ZWrNIlKlxoAzCHoAepqNGaehB0kBhp6+RxawLsZoF3skyjNk73wdFmaq776f7oVV6QTEarUcIQkAneqg308xqc/LaMjadpLSvuMScPQ89mtdMYJleglwWb5Bh6i75V+zHAUAM9yL0HFfg0EE76kWLe0y04jX1hZV6VrKTEsLBMOMXrothUvvIKvtl85ASgEpt/x8W3Ps7oZ5M5iJiIiIiIjYqSDl1iWLjFmzLebNYEZICimpbrAbzVrrcs88DtBshp4tdXlqw2LXdEfx3+sWoDup7dG7DFSbSolcIJvoY/G4MsbbozNlZ4CZFhO2WWHP1/H0LmZmUUqGSjLL2hQisfUaT7UYrqY9MOCeSJF6mhZ/Bjtb6HFKuV3XV9t8NqfSTJDTK1gRYk28qM5v2BhfC0S1sV2zYZwSOg6a5uUoAZrqY4RiEYxwGyHCsHBiWQmVLNTppVrMhYAmXui6EnuHs17bhq00ptsUhCRBeolO4vQvVCfYBJqFtMxqO4i9VwHFvJjPzhxxUC/VxBxtqZlfE+p1Fp5Qe65lzBVCKhGsYV59zZhhrFw49gzGNVHQZqUKr/fEvP419+8t/11Rv3/8Z4gFejvFbPqMjH3W4EK964wTIyJ4xgowpHqfVvDsDTKHpU1N4u5r89tZ6GethcpaTWQQGGElxjSjQSEAlSMXXZ6iXyZ4WpuCQqo0LQAgSoppnTKi4hTtvMTC9ozt6wV5V/WVru8zPVVoyRme7SumZ3o0R0I4xhP1nuuLxAticDqWp/rjmOK5FTDvmU1a0e4CNoMx1sUYcUlDDcPVIQVamoUDgKmkhdFUh35XLpkwZcNZr4idF/NmMBMREREREbFTQW6lADgyMxbzZjAjJAEDdBSDmrFllGNEq+wpwgiWUjA8XagopUIwrJlWf2/Y2EY5mQPaTItwAj6mZzXjBZYv2oA92oqZWdqatDNBo1sx5xCS2nX1MdYbCKcdZSaSZzDahxOjOQkZkYS47yiRLikk5GCkzxBTMj+BZOqFgBpWxpQ5TK9gZp1ujd8PhXf6GNUnHND1YjrKo/SugQtJpUhMhAZVrIztRxCUNTMzM5vz1+YBFcViZoYmxF61xbEhdT0RAAjd332+bZgZv45q9uzK9cPoc7r5YdUqksSxEj5zZQzRXESSsBqMpnZvCzSxSMMi6YLjGiKW5gqVRNGZCgoQG+KbkjF1D+hi/cg4E8lmWL9SUsd0epoZqqP6/CiiQJ8WaIPc36Z8lxIkTKLonrUaMzOLvoiDeNoYCQqA6WvKJZCb5xyehoZoblqa51wGvVwCWEDUe1GwjdaUbp/WeqweGcf0hNKZCEEhtCat7CeW8O5PZ6hKBq6flyWjU1b71UkKZJRbJqjPE6ydcSzNitH1th5tVmJGR+n5fVJKip9s3APjmWZwZIrn50/b7S1SYoQ6Bsb1owSTAmNMsUQTSReLUsceGQaT88FjnzMI4RmFbgGiZsYiJpqMiIiIiIiI2KUxf5gZEOTawMqkH1AzOGeaV/DE+rus77cx1ddK94phZqPWyHACknE7o2WdCp2OWl9eMjqFZZ2N2DNXkQDjSS/waSlFYmfAfZkGMzHjiwCo2ahvEGVm0tZMqoFaTEk5YLRnLM/7IrWMSt2YLvUiqRQTI60hla+R8VmeOcGyMLBeLxQ8sHcHAJ87oSBgmvEqJQucMKyuh3Aw5tIGVDpCzfxdyWSQCdJtyWqJM00ESkL5UEM3X9thGBVz7i3xnPH1E6pdNGCFUiqQNBj9zTkhJQl9NxRT430ONEXM3kuCkKAevicP4LQmm2UgOCR6Ka1F+vjsoPm7ziQOQxMLwohiQI2XyXjSQ0drQHJWBSyL3x+KzZSAeSZq3e30dULfn9J+72vVfM1MSivrC2P0MpbdHMLGzMrESBr4zPgRSz4rAwAZ8VJhSBlsU70rG4+Dt+8C2sdeyToAwNpsFOPpUrTzUu9GrFGeEASVYVUrCi4IprWehhAZMsyswpKWijZKqADXWpV13TbypMKe+lWbEoEZHbbUkYX3DhCYKl04k9KaqT4bYz2k4PbapNofS/0tQaXEOFXMzD7Zs/ZZHk+6NnKqL7ajz0xcZtpmmDeDmYiIiIiIiJ0JUgjIrVhmiqHZDvNuMFNJapmZqTLDU0K79wqKilNMazamO50j0b4evKJIW8YavcJ4u29nCa20tMkeF+VdLMmmsThVmpkx1rMqfAYBzqhNfLaBt+3srUMLq8xnRFhbbyCcZVtWhAzOcpXNeeiLwezMSwYzUHMes415bIGvBfD386MugOYkeAF8119/8kC8BJI1lgY6ER+gGBsza0oBlQhOnRgcEh3dLZxWVj9TEDngFlxPslh3+jWwx5HBdpm2plSgdHKLoOy65qTulDsXViWlQuuomC3T9fMs2pnA54cGzJ2QxH6u+yoJuKSlQjJ7nQr9Wgii5vQpctrsPmv2q/d/03424scrq+53E3iKzAL/+TDXYIZn6IsEozpycHE67WzxawkjS8Gsds069Op7TVDi2NBaJF8bZRAR6GvL/LapMl1KkIC18TUzs1zfQiYe6yTRk2G0Wl5jy5juQ/8OZAQo9W4tQux3qj0SqbkPAIBIW0aHSiyGYjIOyFbj550leGLjAgBAt0ytZkZw6p5zKiErAkFU301NtWwiSwqJpD1jr8Ee+RQ6Wrf4i6kJTBW5dQ6mRNrEnz2RWhZ5JOljSWsGz/Q6dj+jb3w6G8OKdK314UmJRGp9dwgoOPYwqQ4AsEz1+8akhWcrVca6ZG5u3dsEkZnZZphXgxn1g+JMySZ7LXT7auAgJYEUBKUOO5QFhUzVA7Fk4RSWjqilo05SIqOVDfH1f7T2zDdiWb7BZqrNSUhXljKxb5gJuBd3i5T2xaZobiWGAzTlP9CG5rbVf0CbjNAYEYNLTV4o9kDeHTsgEgPH+D9c/uCGesJSSDN08epgyvIGNqoMtaij/pag9gXrwuRTWqEvUpQ6Vf2MzNxAgg4uzQj9ojfLiZaqZsJLARH2Uz1rdTCg9ELZfQhJkVA+a5buJvhLHokWXPsDTz8b9mw/eMMybXNQ424PRuVA6Ho1JGWE8IwbKwB9/aqoGNNWAubHmwfLRqVIbW4v6hm/NcEOtv2lAKj7dkLb6aeEO0G3TIIs7MpgzSwTe6JwXW8r7KUVnq2UyHR92dZ1Cy0KDEx2eNVfzUaTxvixaSDFJQ3MJlvEzwLN0SKll/pAYFhqh3q/mXuCg4BKatMRTAPgcD/c/vPLvGUmBgIu/fZ47ZbevlLCn2FwCSzSg7sem8aLOk9i1cQEAGCybOHxDQsBAFXFIEpdZyoBQuwAWJQUMzNqcEqImlgtbWvbBVZhTIdiL+0wTJWZm2xWubWy6IosGHQuzGaCSam5jj8iy7GAzSDVE9EXpDPIvQkKIxJ9qd61Je3aa20M9QCAM8+RL2KXwbwazEREREREROw0EBLYGo+lyMxYzJvBjDEj6yQFeqlqdko5RFuN6DOmlh2emVYzuA3TbbRbalYwlvdsKGFCOdqstDOGnFaYSBQNuzCZxhjtIvOYDjOrLEwIMsyyTYWOZ6xVWuq4siJCQM2srVU9QiFoXYBqzmkQLLEEaQ+82b4Xiq1mjW6/FimDpauM8DC5nzEX8wR49Rmlf7wACdmF+nNIqA01ZMSxNNCCVK8xdnaee8tMTEoVdupnM64ZxTUhrbULCNkjuwSiE+j5/crtMg1B6YVu+8kHAVi2YpABIQN1880Om5b86m3zt3FJIYiXwFO6pbW+SED98xMglWbpxH1fCQbhieN9lIKhBEPfMGUiTMKq+srdC6a9XDrxu0C4vFjP4g6P9ehLapdd+yJBX6ZBJnSbcsQrcLrKQYnAglQ9lx1a4L+LRQBUuL4AQeYtcVnxMShKwYJEq01LQgBsuLI63heZDiaTrLObgYllU3oQba5nrqGfHiSFWnos9KX3hedMczQuNDtkaUaoEeI7xlN9dt9REt6fysxPfbeIlnhBtgavXPQQAOCpcgJCvhAA8JNiCUrzcyIIIIi9OwkFuDYW3Vi10StSdAt1TZeMZFjWngSgjCwTym2KgWd7bdt3leza68mlCrs3hqSFYNigDftM4sixBYrtWZbMoEPMEpf6/xJmro0LuoAACm2H8TTZjj+L0j0vW358BBBDsyMiIiIiIiJ2ccwbZiahHBkVGGWFDZ0eZX07A5yuckxWLbs/IW7GRomzkm/r2cMo0+HY6ZTVyJSSQYCiZ8y1akrzMJlcmBzNQM1maaNZ2OAM3jE/db2Mv3+TnsZnd3zNQ2CMV6ujn8LAfB44p9YBMLj0DAZKZ+OzGiEYRCDATT21kDlvKRMISKtDgIAdkhsBqmFmSsms0DCt9V0pqD2ugi+yDtvMfP0PWMCkhOLiUEtTSmpngjmtrH6qVHxLwNAY5oTVZu6+fkO1b/D6N8ITUgOO7erQIrhm9VQTgQZKEie69mC0Gz7jVQ/XLsXgPUmJsOWllAe6Elq7zwRE0MdcZ06cERlmPCPEuuGjudaFYBhJnOFjX6R4qj9my8tohRYbDL8tBQWlzFrjq3ppE0ifkYRATkuk0rCnYVi+Sf2h/g4FwACG6mT88s2xqj9m12EV5v6VqjaG8mTEiYGDGbz+ytyfIUtmtDmmDGIZnhYhWMa6YNkq/bnEL0YXqDoIhmdbSpA73c8wM9l29cg9UTWnkIJgY1e9a/tVgl6lfoaeN7oeGa0wJRW7MtXPsVYz5Z2sxPJRxeDs016PDiuxQb+TW6xyzzxnWDUzjsc7SwAAB2RPYam+dCUEOiRFavqLAqXs6/YSPM3H1XnnKD7fFpBCQm7FMtNcs2DPB+xQZuaaa67BEUccgfHxcYyPj+O4447DV7/6VbtdSolLL70Ue+21F9rtNk4++WT88Ic/3IE1joiIiIiI2EaQYuv/RQDYwczMPvvsgyuuuAIvfKFad73xxhtx5pln4oEHHsBhhx2GK6+8EldddRU+/elP48ADD8SHP/xhnHLKKXjkkUcwNja2WeeqhFLKV8IlcezyFBt0dMOa7ih6VWqjiCiRNlHaviPPYlmuZgUu1FqNiCfYjD1Hi5TgoAPr62p/te5t1v8Hon88+AxICeaFRYeRNb5xVz05ZJ2JYd52X6OQEm5TENQN8ShEEJ7rszLFLKZmgS6GDIZzm5lmnWngkgZJ+JpYCSqlYrz0odxLl6C0GD6zw60Jn69tAUwSO1VI4hkHglCUEsHM2rww6okw66izMzYaSDBn/kULAM500Z/xm+vun3uuyR5tm/Ux5vpTSAhPB0EbZuimrqU3Y60EswkXU+JSP+S0Qof1HWvg6Vt6Ig1SgjSxPe5vCm61DA6lZCparSFSSGjWzURgJYQHjIjQfTWW9HU9la7t2WoEM5WabReCYUHWDwwT6yZ+TVBRVS4UG9IxmL7xowm/NqAQVkOX1fQ3dZYz1NI4y4Qg2aWk9lk2CJ5Lz+RRSGkZlowQ+7eQus+9619K875R2GBC8Ykz0GMg6BCCPXSYOyVPg4+pui3LN2B1X0U5/Xd3IX6aLsZMV6cioBJjbRMaT0GItKHa/TLBU5PuXb7XyKRNqEvHJdbq8OtukWJdr63rT9BilU5No1KTtHLVp5NljukywwOTKwAA++VrsAf7HwDABEkhIJATdcVaEOjoZ3+9l7l6ijuGPmLXwQ5lZl796lfj9NNPx4EHHogDDzwQH/nIRzA6Oop7770XUkp8/OMfxwc+8AG89rWvxeGHH44bb7wRMzMz+OxnP7sjqx0REREREbHVkEJu9b8IhZ1GM8M5xz//8z9jenoaxx13HB577DGsXr0ap556qt0nz3OcdNJJuOeee/D7v//7jeX0+330+337eXJSMSomkgmAtTlf3R3DjLbFZlRgSXvaJkQbT7tYqrU1z8vXYkxbYLdoGbAeyp8gNC0zs9GU8IB94NLpNEoZdr1va55Jjp5UdWTSmeiZ6B4WRCY5JiaYxdd0H2a2qKKEaiZbvtme15Ymi/9NJf5jRAazTMVIMVc2QTDT9EFr/RVAH5ORaiACyDIZ4OC+Pw2hdr2far+YYckZwzY6xitgSsAhKLWaELU9ZH6aUEpqmaSSsDBNREPEUlPKiKZr7vu0hO1xrIefDgMY1C35yTzteaWO2tP3zCjrW71HTku0SOnYGKS2v1PCURKXBoHWNFCGmeuJFKBOU+YzGTMiC5KNdljfGkr2RIopnjem8+BwjI2Br4fzUxGkRFimyfcGYtrwzvRDwHyiCp6hAkmQ6sNoolq0tCysgR/B6H+mkJat8XU3A+kyglQHUuvSTJnuXEanZn7fBAio9XvyGTnlJSO87wxrs16o6zfpRWst1okZOQgyCGtCN04K7K1THXAvsmya5xhvjdhEk4RIjGTqGlZe+g4A6GQFZgqdNkYwTBYtjKbq/T2e9uy+M2lqI5XW9jqY6ufWB2gkK6xx6UyZYaqfYb1mce7KDrZ17KQFcmT2PUpBMaYjlzq0xAKmzE6tHm97QApsXTRTXGYy2OGDmQcffBDHHXccer0eRkdHceutt+LQQw/FPffcAwBYunRpsP/SpUvx+OOPDy3v8ssvxwc/+MGB78vpAgX1liMAVN0+Km2LKalAWRWQ+gEpkgL9Ui9HlRUS/fIThAcvAUF5bTAjZxnMSCsOLms/oP5gRkiJPsyPkUTPuGyCopRyboMZDxQC1RYMZupDDvWSNmGszaDevgalvxQAirpp37C6+PCN0nqCoK/7r8cpKrMMJIkOZXf95YfxVnVBtq4XaRgY2YGcF64uJEFfOoGrbAzRbm6XEflRVgaDGf+cpv0mqNUPm/d/puc0mLH3T4OZovdZGsGnpHapoa8bIfQ9k7AS0Pe/pBUkqVDqZ6AviVuiEBJ9QVAXFtfBCQehJaTJW0Yre3/2eInS60TKKhB97l5ZoihKVMINTEy/chAUwvvRpxX6mQ7dLUqUlc4CLQkKVoBQk4XdDWYEFQApIfX5OK3spKAiVfAMFRLBYEYQ937wnxPA7SfMgMobzJRzGMz4A2U1mHFLUIl37TM9MM6Ce0v9PwmWbD1hsIap75S+ftNeX+Y6lNkMZhJiwqUJprmqf7eq0Ct0f3cLVNN98Bl11xIiUWmhbX0wIyQB1+/gqixQVgXKVGetJhylzu9UVQKVl8yaFwD0u7oqCzA9mKlKCV5ImJXVYqrEtHH5TQWEJzbvS4G+vnenuMRMpb+fNrmnnnvWo0K5VQbAFbbjwGsnB5E7WA5dFAWeeOIJrF+/Hl/4whfwd3/3d1i5ciXWr1+PE044Af/zP/+D5cuX2/3f9ra34cknn8Rtt93WWF6dmfnFL36BQw899DlvR0RERETE7oMnn3wS++yzz3NSdq/Xw3777YfVq1dvdVnLli3DY489hlZrfmt9djgzk2WZFQAfe+yxuO+++3D11Vfj4osvBgCsXr06GMysWbNmgK3xkec58txRpKOjo3jooYdw6KGH4sknn8T4+Phz1JIdh8nJSaxYsWK3bR+w+7dxd28fsPu3cXdvH7D7t9G076GHHsJee+31nJ2n1WrhscceQ1EUm955E8iybN4PZICdYDBTh5QS/X4f++23H5YtW4Y77rgDRx11FADF4qxcuRIf/ehH51wepRR77703ANgQ8N0Vu3v7gN2/jbt7+4Ddv427e/uA3b+Ne++9Nyh9buNjWq1WHIRsQ+zQwcwf/dEf4VWvehVWrFiBjRs34uabb8add96J2267DYQQXHjhhbjssstwwAEH4IADDsBll12GTqeD3/7t396R1Y6IiIiIiIjYibBDBzNPPfUUfvd3fxerVq3CxMQEjjjiCNx222045ZRTAADve9/70O128c53vhPr1q3DS1/6Utx+++2b7TETERERERERsftihw5mrr/++lm3E0Jw6aWX4tJLL92q8+R5jksuuSTQ0uxO2N3bB+z+bdzd2wfs/m3c3dsH7P5t3N3btztjh0czRURERERERERsDWLW7IiIiIiIiIhdGnEwExEREREREbFLIw5mIiIiIiIiInZpxMFMRERERERExC6N3X4w85GPfATHH388Op0OFixY0LjPE088gVe/+tUYGRnBkiVLcMEFF2wTZ8bthb/927/Ffvvth1arhWOOOQb//u//vqOrtMW466678OpXvxp77bUXCCH4l3/5l2C7lBKXXnop9tprL7TbbZx88sn44Q9/uGMqu5m4/PLL8Uu/9EsYGxvDnnvuide85jV45JFHgn125fYBwDXXXIMjjjjCmqodd9xx+OpXv2q37+rtq+Pyyy+3nlgGu3obL730UhBCgn/Lli2z23f19gEqzc3v/M7vYPHixeh0Onjxi1+M+++/327fHdo437DbD2aKosDrXvc6vOMd72jczjnHGWecgenpadx99924+eab8YUvfAHvec97tnNNtwyf+9zncOGFF+IDH/gAHnjgAfzKr/wKXvWqV+GJJ57Y0VXbIkxPT+PII4/EX//1Xzduv/LKK3HVVVfhr//6r3Hfffdh2bJlOOWUU7Bx48btXNPNx8qVK3Huuefi3nvvxR133IGqqnDqqadienra7rMrtw8A9tlnH1xxxRX4zne+g+985zv41V/9VZx55pn2h2BXb5+P++67D9deey2OOOKI4PvdoY2HHXYYVq1aZf89+OCDdtuu3r5169bhhBNOQJqm+OpXv4qHHnoIH/vYx4LJ7q7exnkJOU9www03yImJiYHv//Vf/1VSSuUvfvEL+90//dM/yTzP5YYNG7ZjDbcML3nJS+Q555wTfHfwwQfLP/zDP9xBNdp2ACBvvfVW+1kIIZctWyavuOIK+12v15MTExPyk5/85A6o4dZhzZo1EoBcuXKllHL3a5/BwoUL5d/93d/tVu3buHGjPOCAA+Qdd9whTzrpJPmud71LSrl7XMNLLrlEHnnkkY3bdof2XXzxxfLEE08cun13aON8xG7PzGwK3/72t3H44YcHScVOO+009Pv9gHbcGVEUBe6//36ceuqpwfennnoq7rnnnh1Uq+cOjz32GFavXh20N89znHTSSbtkezds2AAAWLRoEYDdr32cc9x8882Ynp7Gcccdt1u179xzz8UZZ5yBV77ylcH3u0sbf/zjH2OvvfbCfvvthze84Q342c9+BmD3aN+XvvQlHHvssXjd616HPffcE0cddRSuu+46u313aON8xLwfzKxevXogC/fChQuRZdk2Sc/+XOKZZ54B53yg/kuXLt3p674lMG3aHdorpcRFF12EE088EYcffjiA3ad9Dz74IEZHR5HnOc455xzceuutOPTQQ3eb9t1888347ne/i8svv3xg2+7Qxpe+9KX4zGc+g6997Wu47rrrsHr1ahx//PFYu3btbtG+n/3sZ7jmmmtwwAEH4Gtf+xrOOeccXHDBBfjMZz4DYPe4hvMRO13W7Lng0ksvxQc/+MFZ97nvvvtw7LHHzqk8QsjAd1LKxu93RtTruSvVfUuwO7T3vPPOw/e//33cfffdA9t29fYddNBB+N73vof169fjC1/4As466yysXLnSbt+V2/fkk0/iXe96F26//fZZMx7vym181ateZf9+0YtehOOOOw4veMELcOONN+KXf/mXAeza7RNC4Nhjj8Vll10GADjqqKPwwx/+ENdccw3e/OY32/125TbOR+ySzMx5552Hhx9+eNZ/Zra7KSxbtmxgtL1u3TqUZTkwMt/ZsGTJEjDGBuq/Zs2anb7uWwITUbGrt/f888/Hl770JXzzm9/EPvvsY7/fXdqXZRle+MIX4thjj8Xll1+OI488EldfffVu0b77778fa9aswTHHHIMkSZAkCVauXIm/+qu/QpIkth27chvrGBkZwYte9CL8+Mc/3i2u4fLly3HooYcG3x1yyCE2aGJ3aON8xC45mFmyZAkOPvjgWf/NNmvycdxxx+EHP/gBVq1aZb+7/fbbkec5jjnmmOeqCdsEWZbhmGOOwR133BF8f8cdd+D444/fQbV67rDffvth2bJlQXuLosDKlSt3ifZKKXHeeefhlltuwTe+8Q3st99+wfZdvX3DIKVEv9/fLdr3ile8Ag8++CC+973v2X/HHnss3vSmN+F73/se9t9//12+jXX0+308/PDDWL58+W5xDU844YQBS4RHH30U++67L4Dd9znc7bGDhMfbDY8//rh84IEH5Ac/+EE5OjoqH3jgAfnAAw/IjRs3SimlrKpKHn744fIVr3iF/O53vyu//vWvy3322Ueed955O7jmc8PNN98s0zSV119/vXzooYfkhRdeKEdGRuTPf/7zHV21LcLGjRvtNQIgr7rqKvnAAw/Ixx9/XEop5RVXXCEnJibkLbfcIh988EH5xje+US5fvlxOTk7u4JpvGu94xzvkxMSEvPPOO+WqVavsv5mZGbvPrtw+KaV8//vfL++66y752GOPye9///vyj/7ojySlVN5+++1Syl2/fU3wo5mk3PXb+J73vEfeeeed8mc/+5m899575a//+q/LsbEx+07Z1dv3n//5nzJJEvmRj3xE/vjHP5Y33XST7HQ68h//8R/tPrt6G+cjdvvBzFlnnSUBDPz75je/afd5/PHH5RlnnCHb7bZctGiRPO+882Sv19txld5M/M3f/I3cd999ZZZl8uijj7ahvrsivvnNbzZer7POOktKqcImL7nkErls2TKZ57l82cteJh988MEdW+k5oqldAOQNN9xg99mV2yellG95y1vsvbjHHnvIV7ziFXYgI+Wu374m1Aczu3obX//618vly5fLNE3lXnvtJV/72tfKH/7wh3b7rt4+KaX88pe/LA8//HCZ57k8+OCD5bXXXhts3x3aON9ApJRyu9NBERERERERERHbCLukZiYiIiIiIiIiwiAOZiIiIiIiIiJ2acTBTERERERERMQujTiYiYiIiIiIiNilEQczEREREREREbs04mAmIiIiIiIiYpdGHMxERERERERE7NKIg5mIXQInn3wyLrzwwt3qvGeffTZe85rXbFUZz3/+80EIASEE69evH7rfpz/9aSxYsGCrzhUxHGeffba9Dv/yL/+yo6sTETHvEAczERGz4JZbbsGHPvQh+/n5z38+Pv7xj++4CjXgz/7sz7Bq1SpMTEzs6Krs9rjzzjsbB45XX311kN8tIiJi+yLZ0RWIiNiZsWjRoh1dhU1ibGzMZvrd0SjLEmma7uhqbHdMTEzEwWRExA5EZGYidkmsW7cOb37zm7Fw4UJ0Oh286lWvwo9//GO73SyrfO1rX8MhhxyC0dFR/Nqv/Vowe66qChdccAEWLFiAxYsX4+KLL8ZZZ50VLP34y0wnn3wyHn/8cbz73e+2SwoAcOmll+LFL35xUL+Pf/zjeP7zn28/c85x0UUX2XO9733vQz2TiJQSV155Jfbff3+0220ceeSR+L//9/9uUf98+tOfxvOe9zx0Oh38xm/8BtauXTuwz5e//GUcc8wxaLVa2H///fHBD34QVVXZ7T/60Y9w4oknotVq4dBDD8XXv/71YBnl5z//OQgh+PznP4+TTz4ZrVYL//iP/wgAuOGGG3DIIYeg1Wrh4IMPxt/+7d8G5/7FL36B17/+9Vi4cCEWL16MM888Ez//+c/t9jvvvBMveclLMDIyggULFuCEE07A448/Pqe2b6pdV111FV70ohdhZGQEK1aswDvf+U5MTU3Z7Y8//jhe/epXY+HChRgZGcFhhx2Gf/3Xf8XPf/5zvPzlLwcALFy4EIQQnH322XOqU0RExHOLOJiJ2CVx9tln4zvf+Q6+9KUv4dvf/jaklDj99NNRlqXdZ2ZmBn/xF3+Bf/iHf8Bdd92FJ554Au9973vt9o9+9KO46aabcMMNN+Bb3/oWJicnZ9U73HLLLdhnn33sss7mLCt87GMfw9///d/j+uuvx913341nn30Wt956a7DPH//xH+OGG27ANddcgx/+8Id497vfjd/5nd/BypUr594xAP7jP/4Db3nLW/DOd74T3/ve9/Dyl78cH/7wh4N9vva1r+F3fud3cMEFF+Chhx7Cpz71KXz605/GRz7yEQCAEAKvec1r0Ol08B//8R+49tpr8YEPfKDxfBdffDEuuOACPPzwwzjttNNw3XXX4QMf+AA+8pGP4OG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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A simple matplotlib plot to view the data:\n",
    "era5_t_median.t2m.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calling the temporal reduce method with an arbitary function\n",
    "\n",
    "The `temporal.reduce` method can take any method which is accepted by the xarray reduce method, typically this means it must take `axis` as an argument. See the [xarray.Dataset.reduce](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.reduce.html) documentation for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "  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 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\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: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: 230kB\n",
       "Dimensions:       (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number        (number) int64 8B 0\n",
       "  * step          (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface       (surface) float64 8B 0.0\n",
       "  * latitude      (latitude) float64 2kB 80.0 79.75 79.5 ... 30.5 30.25 30.0\n",
       "  * longitude     (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m_made_big  (number, step, surface, latitude, longitude) float32 226kB ...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:56 GRIB to CDM+CF via cfgrib-0.9.1...</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-3439cb0b-9400-4b3e-aac5-649eb432f4ce' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3439cb0b-9400-4b3e-aac5-649eb432f4ce' 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'>number</span>: 1</li><li><span class='xr-has-index'>step</span>: 1</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0b760e2c-b148-4645-ab8e-946166a5f34d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b760e2c-b148-4645-ab8e-946166a5f34d' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-17156d1e-d0ba-4252-876c-a5c75cbb5a32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17156d1e-d0ba-4252-876c-a5c75cbb5a32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58a272ac-8fd7-4e2a-b976-7244b7286e93' class='xr-var-data-in' type='checkbox'><label for='data-58a272ac-8fd7-4e2a-b976-7244b7286e93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-b93dfe26-6c5f-4d93-9ce7-412083931a83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b93dfe26-6c5f-4d93-9ce7-412083931a83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9fd51a3-5c11-496e-a10d-1b5ff192a28d' class='xr-var-data-in' type='checkbox'><label for='data-c9fd51a3-5c11-496e-a10d-1b5ff192a28d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([0], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-333e5d5a-63dd-471c-88f4-7476a963e7f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-333e5d5a-63dd-471c-88f4-7476a963e7f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f493bf65-f3da-45e9-838b-9cfea19f086d' class='xr-var-data-in' type='checkbox'><label for='data-f493bf65-f3da-45e9-838b-9cfea19f086d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.75 79.5 ... 30.5 30.25 30.0</div><input id='attrs-582ade2c-59ea-460e-a4f1-ff3f0940e454' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-582ade2c-59ea-460e-a4f1-ff3f0940e454' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e291e52-4bf0-41bf-9466-55cff8cded43' class='xr-var-data-in' type='checkbox'><label for='data-5e291e52-4bf0-41bf-9466-55cff8cded43' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([80.  , 79.75, 79.5 , ..., 30.5 , 30.25, 30.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.0 -9.75 -9.5 ... 59.75 60.0</div><input id='attrs-c78ffcd5-94f7-457a-af74-a7a3d7b80484' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c78ffcd5-94f7-457a-af74-a7a3d7b80484' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea52b9cc-b02a-49e3-a335-c08d9c690c27' class='xr-var-data-in' type='checkbox'><label for='data-ea52b9cc-b02a-49e3-a335-c08d9c690c27' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-10.  ,  -9.75,  -9.5 , ...,  59.5 ,  59.75,  60.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f7b23fdd-5f4f-47c9-88e2-ddf5e11ec38f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f7b23fdd-5f4f-47c9-88e2-ddf5e11ec38f' class='xr-section-summary' >Data variables: <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>t2m_made_big</span></div><div class='xr-var-dims'>(number, step, surface, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.244e+03 2.249e+03 ... 2.904e+03</div><input id='attrs-ab6b30bd-f58f-42a5-85e7-e7c012c4e5cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab6b30bd-f58f-42a5-85e7-e7c012c4e5cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-381e9b87-3aa0-43b7-ada8-4c8471786bed' class='xr-var-data-in' type='checkbox'><label for='data-381e9b87-3aa0-43b7-ada8-4c8471786bed' title='Show/Hide data 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([[[[[2243.777 , 2249.4653, 2255.5884, ..., 2222.437 , 2228.294 ,\n",
       "           2223.9346],\n",
       "          [2218.9473, 2225.5703, 2232.6553, ..., 2214.3787, 2221.7725,\n",
       "           2229.3064],\n",
       "          [2205.3516, 2212.682 , 2218.015 , ..., 2225.8914, 2227.5881,\n",
       "           2229.4446],\n",
       "          ...,\n",
       "          [ 730.9425, 1217.7166, 1868.3383, ..., 3101.2358, 2996.876 ,\n",
       "           2928.0737],\n",
       "          [ 669.073 ,  835.9615, 1553.5703, ..., 3062.2107, 2995.8184,\n",
       "           2917.736 ],\n",
       "          [ 665.2961, 1042.8284, 1557.7971, ..., 3099.5571, 3001.3623,\n",
       "           2904.0195]]]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a3d42c32-b220-4f38-b8bd-3664cce8cef1' class='xr-section-summary-in' type='checkbox'  ><label for='section-a3d42c32-b220-4f38-b8bd-3664cce8cef1' class='xr-section-summary' >Indexes: <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-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-af44b4d9-3cb9-4611-a3bd-542d13fc7a07' class='xr-index-data-in' type='checkbox'/><label for='index-af44b4d9-3cb9-4611-a3bd-542d13fc7a07' 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], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a96c25f-b54c-4de9-acbb-053f5013e1bc' class='xr-index-data-in' type='checkbox'/><label for='index-3a96c25f-b54c-4de9-acbb-053f5013e1bc' 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(TimedeltaIndex([&#x27;0 days&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-34fa6e5e-ae09-40a0-bd57-bdccc91dc067' class='xr-index-data-in' type='checkbox'/><label for='index-34fa6e5e-ae09-40a0-bd57-bdccc91dc067' 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], dtype=&#x27;float64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a9a6f21d-fe64-416b-9b89-ee4d67299ba1' class='xr-index-data-in' type='checkbox'/><label for='index-a9a6f21d-fe64-416b-9b89-ee4d67299ba1' 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([ 80.0, 79.75,  79.5, 79.25,  79.0, 78.75,  78.5, 78.25,  78.0, 77.75,\n",
       "       ...\n",
       "       32.25,  32.0, 31.75,  31.5, 31.25,  31.0, 30.75,  30.5, 30.25,  30.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=201))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-85853c87-d209-442d-ab4a-01330f169725' class='xr-index-data-in' type='checkbox'/><label for='index-85853c87-d209-442d-ab4a-01330f169725' 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([-10.0, -9.75,  -9.5, -9.25,  -9.0, -8.75,  -8.5, -8.25,  -8.0, -7.75,\n",
       "       ...\n",
       "       57.75,  58.0, 58.25,  58.5, 58.75,  59.0, 59.25,  59.5, 59.75,  60.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=281))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-38cc491d-ba8d-48fe-a6a9-4e97f59c0782' class='xr-section-summary-in' type='checkbox'  checked><label for='section-38cc491d-ba8d-48fe-a6a9-4e97f59c0782' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2024-07-29T08:56 GRIB to CDM+CF via cfgrib-0.9.14.0/ecCodes-2.36.0 with {&quot;source&quot;: &quot;N/A&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 230kB\n",
       "Dimensions:       (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number        (number) int64 8B 0\n",
       "  * step          (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface       (surface) float64 8B 0.0\n",
       "  * latitude      (latitude) float64 2kB 80.0 79.75 79.5 ... 30.5 30.25 30.0\n",
       "  * longitude     (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m_made_big  (number, step, surface, latitude, longitude) float32 226kB ...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:56 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "def my_method(array, axis=None, **kwargs):\n",
    "    return np.mean(array, axis=axis, **kwargs) * np.std(array, axis=axis, **kwargs)\n",
    "\n",
    "era5_t_my_method = ek_aggregate.temporal.reduce(era5_data, how=my_method, how_label=\"random\")\n",
    "era5_t_my_method\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x15625c210>"
      ]
     },
     "execution_count": 16,
     "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": [
    "# A simple matplotlib plot to view the data:\n",
    "era5_t_my_method.t2m_random.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate a rolling mean with a 50 timestep window\n",
    "\n",
    "There is no temporal specific method for a rolling reduction. The general rolling_reduce method can do this calculation by specifying the dimension over which you would like to reduce."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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",
       "  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: 330MB\n",
       "Dimensions:     (number: 1, time: 1460, step: 1, surface: 1, latitude: 201,\n",
       "                 longitude: 281)\n",
       "Coordinates:\n",
       "  * number      (number) int64 8B 0\n",
       "  * time        (time) datetime64[ns] 12kB 2015-01-01 ... 2015-12-31T18:00:00\n",
       "  * step        (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface     (surface) float64 8B 0.0\n",
       "  * latitude    (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude   (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "    valid_time  (time, step) datetime64[ns] 12kB dask.array&lt;chunksize=(1460, 1), meta=np.ndarray&gt;\n",
       "Data variables:\n",
       "    t2m         (number, time, step, surface, latitude, longitude) float32 330MB dask.array&lt;chunksize=(1, 1459, 1, 1, 201, 281), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1...</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-87bf7c54-18d6-461b-bfce-91df4e8547a2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-87bf7c54-18d6-461b-bfce-91df4e8547a2' 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'>number</span>: 1</li><li><span class='xr-has-index'>time</span>: 1460</li><li><span class='xr-has-index'>step</span>: 1</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8bd76250-4d00-44bc-88a4-60605130b66f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8bd76250-4d00-44bc-88a4-60605130b66f' 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'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-be383248-98de-419d-9b1c-2586dfa96889' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be383248-98de-419d-9b1c-2586dfa96889' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1d8334b-bf0d-4ba8-b9d7-5b5e018a0518' class='xr-var-data-in' type='checkbox'><label for='data-f1d8334b-bf0d-4ba8-b9d7-5b5e018a0518' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><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'>2015-01-01 ... 2015-12-31T18:00:00</div><input id='attrs-301658d0-eccf-4c33-a09f-af0e732b6fe1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-301658d0-eccf-4c33-a09f-af0e732b6fe1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59c7c788-4e79-4d52-b2f6-e5bf41794286' class='xr-var-data-in' type='checkbox'><label for='data-59c7c788-4e79-4d52-b2f6-e5bf41794286' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2015-01-01T00:00:00.000000000&#x27;, &#x27;2015-01-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-01-01T12:00:00.000000000&#x27;, ..., &#x27;2015-12-31T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-12-31T12:00:00.000000000&#x27;, &#x27;2015-12-31T18:00:00.000000000&#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'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-e7f1540d-fba5-48a5-88ad-c32d31cae09e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7f1540d-fba5-48a5-88ad-c32d31cae09e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2838587c-4584-4219-a042-f8ab4941f8b5' class='xr-var-data-in' type='checkbox'><label for='data-2838587c-4584-4219-a042-f8ab4941f8b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([0], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-2b86139d-55cf-41d9-9f13-9959aa0b20f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b86139d-55cf-41d9-9f13-9959aa0b20f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9b7c8de-a790-450e-b52f-bfc099161a3c' class='xr-var-data-in' type='checkbox'><label for='data-a9b7c8de-a790-450e-b52f-bfc099161a3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.75 79.5 ... 30.5 30.25 30.0</div><input id='attrs-0a0bba10-09ed-4576-9c10-a81120f9d8f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a0bba10-09ed-4576-9c10-a81120f9d8f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf82f54f-6391-4a3f-a669-3f0aeb745536' class='xr-var-data-in' type='checkbox'><label for='data-bf82f54f-6391-4a3f-a669-3f0aeb745536' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([80.  , 79.75, 79.5 , ..., 30.5 , 30.25, 30.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.0 -9.75 -9.5 ... 59.75 60.0</div><input id='attrs-8bcd99ac-381d-49ea-8545-cecb34e8b400' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bcd99ac-381d-49ea-8545-cecb34e8b400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-909531c9-04c9-4601-b6a1-40a1bfc45020' class='xr-var-data-in' type='checkbox'><label for='data-909531c9-04c9-4601-b6a1-40a1bfc45020' title='Show/Hide data repr'><svg class='icon xr-icon-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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-10.  ,  -9.75,  -9.5 , ...,  59.5 ,  59.75,  60.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>(time, step)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1460, 1), meta=np.ndarray&gt;</div><input id='attrs-05da9674-ea41-401a-9582-7e1022371a88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05da9674-ea41-401a-9582-7e1022371a88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b81e25cf-8425-428c-a233-dc5ee4fd187b' class='xr-var-data-in' type='checkbox'><label for='data-b81e25cf-8425-428c-a233-dc5ee4fd187b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 11.41 kiB </td>\n",
       "                        <td> 11.41 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1460, 1) </td>\n",
       "                        <td> (1460, 1) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-1fee03ee-1874-448b-91ec-29a6c7041fad' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1fee03ee-1874-448b-91ec-29a6c7041fad' class='xr-section-summary' >Data variables: <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>t2m</span></div><div class='xr-var-dims'>(number, time, step, surface, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1459, 1, 1, 201, 281), meta=np.ndarray&gt;</div><input id='attrs-44585180-0d5d-4bf8-8481-e7c58f750fe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44585180-0d5d-4bf8-8481-e7c58f750fe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c5c6eb9-a558-409e-b61c-8a07928c810b' class='xr-var-data-in' type='checkbox'><label for='data-9c5c6eb9-a558-409e-b61c-8a07928c810b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_dataType :</span></dt><dd>an</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>56481</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>281</dd><dt><span>GRIB_Ny :</span></dt><dd>201</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>80.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>30.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-10.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>60.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 314.57 MiB </td>\n",
       "                        <td> 314.35 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1, 1460, 1, 1, 201, 281) </td>\n",
       "                        <td> (1, 1459, 1, 1, 201, 281) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2 chunks in 29 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-3780aa10-8b00-4495-a5df-f5a871d0f2ea' class='xr-section-summary-in' type='checkbox'  ><label for='section-3780aa10-8b00-4495-a5df-f5a871d0f2ea' class='xr-section-summary' >Indexes: <span>(6)</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>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4a84e969-8c9d-4d2d-8240-1152da6b8b5f' class='xr-index-data-in' type='checkbox'/><label for='index-4a84e969-8c9d-4d2d-8240-1152da6b8b5f' 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], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><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-e33cc840-6536-41ae-93e1-d74bd982f134' class='xr-index-data-in' type='checkbox'/><label for='index-e33cc840-6536-41ae-93e1-d74bd982f134' 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;2015-01-01 00:00:00&#x27;, &#x27;2015-01-01 06:00:00&#x27;,\n",
       "               &#x27;2015-01-01 12:00:00&#x27;, &#x27;2015-01-01 18:00:00&#x27;,\n",
       "               &#x27;2015-01-02 00:00:00&#x27;, &#x27;2015-01-02 06:00:00&#x27;,\n",
       "               &#x27;2015-01-02 12:00:00&#x27;, &#x27;2015-01-02 18:00:00&#x27;,\n",
       "               &#x27;2015-01-03 00:00:00&#x27;, &#x27;2015-01-03 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-12-29 12:00:00&#x27;, &#x27;2015-12-29 18:00:00&#x27;,\n",
       "               &#x27;2015-12-30 00:00:00&#x27;, &#x27;2015-12-30 06:00:00&#x27;,\n",
       "               &#x27;2015-12-30 12:00:00&#x27;, &#x27;2015-12-30 18:00:00&#x27;,\n",
       "               &#x27;2015-12-31 00:00:00&#x27;, &#x27;2015-12-31 06:00:00&#x27;,\n",
       "               &#x27;2015-12-31 12:00:00&#x27;, &#x27;2015-12-31 18:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1460, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-66d58167-de66-4cd5-a3bb-f169fc023f73' class='xr-index-data-in' type='checkbox'/><label for='index-66d58167-de66-4cd5-a3bb-f169fc023f73' 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(TimedeltaIndex([&#x27;0 days&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d58a7fb7-0e3e-42f4-9238-df2be8f8aefe' class='xr-index-data-in' type='checkbox'/><label for='index-d58a7fb7-0e3e-42f4-9238-df2be8f8aefe' 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], dtype=&#x27;float64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14f44121-449b-40d2-b955-862a38580afd' class='xr-index-data-in' type='checkbox'/><label for='index-14f44121-449b-40d2-b955-862a38580afd' 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([ 80.0, 79.75,  79.5, 79.25,  79.0, 78.75,  78.5, 78.25,  78.0, 77.75,\n",
       "       ...\n",
       "       32.25,  32.0, 31.75,  31.5, 31.25,  31.0, 30.75,  30.5, 30.25,  30.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=201))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77439029-8dc1-4851-b9fe-86befe9c5247' class='xr-index-data-in' type='checkbox'/><label for='index-77439029-8dc1-4851-b9fe-86befe9c5247' 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([-10.0, -9.75,  -9.5, -9.25,  -9.0, -8.75,  -8.5, -8.25,  -8.0, -7.75,\n",
       "       ...\n",
       "       57.75,  58.0, 58.25,  58.5, 58.75,  59.0, 59.25,  59.5, 59.75,  60.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=281))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4a2a9e22-dce6-4127-a8f3-3686854c4647' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4a2a9e22-dce6-4127-a8f3-3686854c4647' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.14.0/ecCodes-2.36.0 with {&quot;source&quot;: &quot;N/A&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 330MB\n",
       "Dimensions:     (number: 1, time: 1460, step: 1, surface: 1, latitude: 201,\n",
       "                 longitude: 281)\n",
       "Coordinates:\n",
       "  * number      (number) int64 8B 0\n",
       "  * time        (time) datetime64[ns] 12kB 2015-01-01 ... 2015-12-31T18:00:00\n",
       "  * step        (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface     (surface) float64 8B 0.0\n",
       "  * latitude    (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude   (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "    valid_time  (time, step) datetime64[ns] 12kB dask.array<chunksize=(1460, 1), meta=np.ndarray>\n",
       "Data variables:\n",
       "    t2m         (number, time, step, surface, latitude, longitude) float32 330MB dask.array<chunksize=(1, 1459, 1, 1, 201, 281), meta=np.ndarray>\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-07-29T08:52 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era5_rolling = ek_aggregate.rolling_reduce(\n",
    "    era5_data, time=50, center=True,\n",
    ")\n",
    "era5_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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