pr_tseries.ipynb

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   "source": [
    "# Daily time series\n",
    "\n",
    "Data access example to plot daily and monthly precipitation series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a4309a36-bb0a-459e-b4ca-c65a8167da43",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "from dask.diagnostics import ProgressBar\n",
    "ProgressBar().register()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cefd1fa6-4349-4bc4-8174-d1382506ff84",
   "metadata": {},
   "source": [
    "Open the virtual data set for daily (`day`) data interpolated to the regular lon-lat grid (CSAM-4i):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bd97646a-552f-41ce-9f98-5d4a364e2104",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (lon: 676, lat: 451, time: 1096, bnds: 2)\n",
       "Coordinates:\n",
       "  * lon        (lon) float64 -75.0 -74.96 -74.92 -74.88 ... -48.08 -48.04 -48.0\n",
       "  * lat        (lat) float64 -35.0 -34.96 -34.92 -34.88 ... -17.08 -17.04 -17.0\n",
       "  * time       (time) datetime64[ns] 2018-06-01T11:30:00 ... 2021-05-31T11:30:00\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;\n",
       "    hurs       (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    huss       (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    pr         (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    rsds       (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    sfcWind    (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    tas        (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    tasmax     (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    tasmin     (time, lat, lon) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "Attributes: (12/25)\n",
       "    Conventions:                    CF-1.8\n",
       "    history:                        Thu Jul 14 18:16:58 2022: cdo remap,desti...\n",
       "    institution:                    Instituto de Fisica de Cantabria, CSIC-Un...\n",
       "    creation_date:                  2022-07-13-T09:18:06Z\n",
       "    experiment:                     Evaluation run with ECMWF ERA5 reanalysis...\n",
       "    experiment_id:                  FPS-SESA\n",
       "    ...                             ...\n",
       "    comment:                        Simulation performed at CESGA (https://ww...\n",
       "    CDO:                            Climate Data Operators version 1.9.8 (htt...\n",
       "    CORDEX_domain:                  CSAM-4i\n",
       "    contact:                        meteo@unican.es\n",
       "    size:                           2147483647\n",
       "    size_human:                     6.0 GiB</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-ae4b6326-cfb5-43a5-a61a-594837a749e2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ae4b6326-cfb5-43a5-a61a-594837a749e2' 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'>lon</span>: 676</li><li><span class='xr-has-index'>lat</span>: 451</li><li><span class='xr-has-index'>time</span>: 1096</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d2fa6cfa-8e84-48c6-8f84-6f5afe4eac57' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2fa6cfa-8e84-48c6-8f84-6f5afe4eac57' class='xr-section-summary' >Coordinates: <span>(3)</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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-75.0 -74.96 ... -48.04 -48.0</div><input id='attrs-386d934e-fda5-4263-bb64-dcaeb51db49e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-386d934e-fda5-4263-bb64-dcaeb51db49e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afb4836e-6490-49f9-a298-e01a83b4ccf3' class='xr-var-data-in' type='checkbox'><label for='data-afb4836e-6490-49f9-a298-e01a83b4ccf3' title='Show/Hide data repr'><svg 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>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_ChunkSizes :</span></dt><dd>676</dd></dl></div><div class='xr-var-data'><pre>array([-75.  , -74.96, -74.92, ..., -48.08, -48.04, -48.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-35.0 -34.96 ... -17.04 -17.0</div><input id='attrs-798160a1-eb39-4eed-adab-45076dd7e855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-798160a1-eb39-4eed-adab-45076dd7e855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91f90958-0fc8-498c-85b7-c0f32e556287' class='xr-var-data-in' type='checkbox'><label for='data-91f90958-0fc8-498c-85b7-c0f32e556287' title='Show/Hide data repr'><svg 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>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_ChunkSizes :</span></dt><dd>451</dd></dl></div><div class='xr-var-data'><pre>array([-35.  , -34.96, -34.92, ..., -17.08, -17.04, -17.  ])</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'>2018-06-01T11:30:00 ... 2021-05-...</div><input id='attrs-2b6d84fe-3301-48e1-9c1c-c801c0e63ce2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b6d84fe-3301-48e1-9c1c-c801c0e63ce2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63b80757-3182-4db6-aaa3-1497fd3033da' class='xr-var-data-in' type='checkbox'><label for='data-63b80757-3182-4db6-aaa3-1497fd3033da' title='Show/Hide data repr'><svg 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><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>_ChunkSizes :</span></dt><dd>366</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-06-01T11:30:00.000000000&#x27;, &#x27;2018-06-02T11:30:00.000000000&#x27;,\n",
       "       &#x27;2018-06-03T11:30:00.000000000&#x27;, ..., &#x27;2021-05-29T11:30:00.000000000&#x27;,\n",
       "       &#x27;2021-05-30T11:30:00.000000000&#x27;, &#x27;2021-05-31T11:30:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2fd4eb2a-305e-4639-bda7-85f3388f8060' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2fd4eb2a-305e-4639-bda7-85f3388f8060' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 2), meta=np.ndarray&gt;</div><input id='attrs-62cc8c27-0532-45fa-b259-1b5d7181ea65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62cc8c27-0532-45fa-b259-1b5d7181ea65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64f156a5-e864-4d17-bbb7-d88935e6b73b' class='xr-var-data-in' type='checkbox'><label for='data-64f156a5-e864-4d17-bbb7-d88935e6b73b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_ChunkSizes :</span></dt><dd>[366   2]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 17.12 kiB </td>\n",
       "                        <td> 1.56 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
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       "                        <td> (100, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 12 Tasks </td>\n",
       "                        <td> 11 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> datetime64[ns] </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hurs</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-6668198a-7585-4b6e-a93a-0ac1458cc0c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6668198a-7585-4b6e-a93a-0ac1458cc0c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3938a002-ec99-43e6-99e5-de020a9edcfa' class='xr-var-data-in' type='checkbox'><label for='data-3938a002-ec99-43e6-99e5-de020a9edcfa' title='Show/Hide data repr'><svg 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>relative_humidity</dd><dt><span>long_name :</span></dt><dd>Near-Surface Relative Humidity</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>huss</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-b5ee5e04-7185-4fde-a2a1-3e9b48879526' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5ee5e04-7185-4fde-a2a1-3e9b48879526' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-874bfca0-cc39-40ad-8ebe-e1a9cb770856' class='xr-var-data-in' type='checkbox'><label for='data-874bfca0-cc39-40ad-8ebe-e1a9cb770856' title='Show/Hide data repr'><svg 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>specific_humidity</dd><dt><span>long_name :</span></dt><dd>Near-Surface Specific Humidity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table>\n",
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       "                        <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> 1.24 GiB </td>\n",
       "                        <td> 3.81 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (100, 100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 385 Chunks </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-5319c545-7215-4785-98b0-5d69355eca1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5319c545-7215-4785-98b0-5d69355eca1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1034f05-5e28-4325-a745-73efbafcc30e' class='xr-var-data-in' type='checkbox'><label for='data-a1034f05-5e28-4325-a745-73efbafcc30e' title='Show/Hide data repr'><svg 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitaion</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sfcWind</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-a554dcd8-b3e3-4ac8-90c5-35501e4afc01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a554dcd8-b3e3-4ac8-90c5-35501e4afc01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-497df8f3-62bf-40df-940e-65776a90d337' class='xr-var-data-in' type='checkbox'><label for='data-497df8f3-62bf-40df-940e-65776a90d337' title='Show/Hide data repr'><svg 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>eastward_wind</dd><dt><span>long_name :</span></dt><dd>Eastward Near-Surface Wind</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tasmax</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-2ddf4877-35e3-4ade-8bcc-c31f9d61b480' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ddf4877-35e3-4ade-8bcc-c31f9d61b480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-395b1346-0c01-427d-a8f4-9c1f6aa4eb41' class='xr-var-data-in' type='checkbox'><label for='data-395b1346-0c01-427d-a8f4-9c1f6aa4eb41' title='Show/Hide data repr'><svg 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>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: point</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div><div class='xr-var-data'><table>\n",
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       "Thu Jul 14 18:16:36 2022: cdo setgrid,source.grid -selname,hurs /gpfs/users/milovacj/workdir/SAM-SESA/output/post/CORDEX-FPS-SESA/output/CSAM-4/UCAN/ECMWF-ERA5/evaluation/r1i1p1f1/UCAN-WRF433/v1/day//hurs//hurs_CSAM-4_ECMWF-ERA5_evaluation_r1i1p1f1_UCAN-WRF433_v1_day_20200101-20210101.nc modelData_setgrid.nc</dd><dt><span>institution :</span></dt><dd>Instituto de Fisica de Cantabria, CSIC-Universidad de Cantabria, SPAIN</dd><dt><span>creation_date :</span></dt><dd>2022-07-13-T09:18:06Z</dd><dt><span>experiment :</span></dt><dd>Evaluation run with ECMWF ERA5 reanalysis forcing</dd><dt><span>experiment_id :</span></dt><dd>FPS-SESA</dd><dt><span>driving_experiment :</span></dt><dd>ECMWF ERA5, evaluation</dd><dt><span>driving_model_id :</span></dt><dd>ECMWF-ERA5</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1f1</dd><dt><span>driving_experiment_name :</span></dt><dd>evaluation</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>institute_id :</span></dt><dd>UCAN</dd><dt><span>model_id :</span></dt><dd>UCAN-WRF433</dd><dt><span>rcm_version_id :</span></dt><dd>v1</dd><dt><span>project_id :</span></dt><dd>CORDEX-FPS-SESA</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>references :</span></dt><dd>https://ifca.unican.es/en-us</dd><dt><span>tracking_id :</span></dt><dd>b43b874c-028c-11ed-8971-40f2e9035d1c</dd><dt><span>title :</span></dt><dd>WRF433 RCM model simulations forced with ERA5 reanalysis</dd><dt><span>comment :</span></dt><dd>Simulation performed at CESGA (https://www.cesga.es/), data postprocessed with WRF_CMORizer.f90 v0.41</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd><dt><span>CORDEX_domain :</span></dt><dd>CSAM-4i</dd><dt><span>contact :</span></dt><dd>meteo@unican.es</dd><dt><span>size :</span></dt><dd>2147483647</dd><dt><span>size_human :</span></dt><dd>6.0 GiB</dd></dl></div></li></ul></div></div>"
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       "    pr         (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    rsds       (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    sfcWind    (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    tas        (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    tasmax     (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    tasmin     (time, lat, lon) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "Attributes: (12/25)\n",
       "    Conventions:                    CF-1.8\n",
       "    history:                        Thu Jul 14 18:16:58 2022: cdo remap,desti...\n",
       "    institution:                    Instituto de Fisica de Cantabria, CSIC-Un...\n",
       "    creation_date:                  2022-07-13-T09:18:06Z\n",
       "    experiment:                     Evaluation run with ECMWF ERA5 reanalysis...\n",
       "    experiment_id:                  FPS-SESA\n",
       "    ...                             ...\n",
       "    comment:                        Simulation performed at CESGA (https://ww...\n",
       "    CDO:                            Climate Data Operators version 1.9.8 (htt...\n",
       "    CORDEX_domain:                  CSAM-4i\n",
       "    contact:                        meteo@unican.es\n",
       "    size:                           2147483647\n",
       "    size_human:                     6.0 GiB"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urlbase = 'https://data.meteo.unican.es/thredds/dodsC/CORDEX/fps/sesa'\n",
    "urls = {\n",
    "  'UCAN-WRF433' :\n",
    "     f'{urlbase}/output/CORDEX/output/CSAM-4i/UCAN/ECMWF-ERA5/evaluation/r1i1p1f1/UCAN-WRF433/v1/day/CORDEX_output_CSAM-4i_ECMWF-ERA5_evaluation_r1i1p1f1_UCAN-WRF433_v1_day',\n",
    "  'USP-RegCM471' :\n",
    "     f'{urlbase}/output/CORDEX/output/CSAM-4i/USP/ECMWF-ERA5/historical/r1i1p1f1/USP-RegCM471/v0/day/CORDEX_output_CSAM-4i_ECMWF-ERA5_historical_r1i1p1f1_USP-RegCM471_v0_day', \n",
    "  'ERA5' :\n",
    "     f'{urlbase}/reanalysis/ERA5-CSAM-4i_day',\n",
    "  'MSWX' :\n",
    "     f'{urlbase}/observations/CSAM-4i_GloH2O-MSWX_day'\n",
    "}\n",
    "ds = xr.open_dataset(urls['UCAN-WRF433'], chunks = dict(time = 100, lon = 100, lat = 100))\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52bba1be-5c16-443e-bb27-f3378bf84386",
   "metadata": {},
   "source": [
    "This loaded the full dataset (3 years and all variables) information into `ds`. Variables can be accessed as attributes of this object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a515c00c-a8c6-43ed-a4ae-12bcae25a15f",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (time: 1096, lat: 451, lon: 676)&gt;\n",
       "dask.array&lt;open_dataset-441c136e564bc7a192b319bde0bb8f9bpr, shape=(1096, 451, 676), dtype=float32, chunksize=(100, 100, 100), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -75.0 -74.96 -74.92 -74.88 ... -48.08 -48.04 -48.0\n",
       "  * lat      (lat) float64 -35.0 -34.96 -34.92 -34.88 ... -17.08 -17.04 -17.0\n",
       "  * time     (time) datetime64[ns] 2018-06-01T11:30:00 ... 2021-05-31T11:30:00\n",
       "Attributes:\n",
       "    standard_name:  precipitation_flux\n",
       "    long_name:      Precipitaion\n",
       "    units:          kg m-2 s-1\n",
       "    cell_methods:   time: mean\n",
       "    _ChunkSizes:    [ 7 50 50]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1096</li><li><span class='xr-has-index'>lat</span>: 451</li><li><span class='xr-has-index'>lon</span>: 676</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5a17b91e-8204-4acb-b83e-14d7297cb52f' class='xr-array-in' type='checkbox' checked><label for='section-5a17b91e-8204-4acb-b83e-14d7297cb52f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-9d79f112-0e08-4a91-8995-80866fcfbf46' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d79f112-0e08-4a91-8995-80866fcfbf46' class='xr-section-summary' >Coordinates: <span>(3)</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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-75.0 -74.96 ... -48.04 -48.0</div><input id='attrs-39da25f4-cba1-4a8f-ab11-80b7d993466d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39da25f4-cba1-4a8f-ab11-80b7d993466d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dee6657c-8ae2-4150-b26b-1c4c1cb4d079' class='xr-var-data-in' type='checkbox'><label for='data-dee6657c-8ae2-4150-b26b-1c4c1cb4d079' title='Show/Hide data repr'><svg 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>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_ChunkSizes :</span></dt><dd>676</dd></dl></div><div class='xr-var-data'><pre>array([-75.  , -74.96, -74.92, ..., -48.08, -48.04, -48.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-35.0 -34.96 ... -17.04 -17.0</div><input id='attrs-4a606469-044c-48f8-aacd-5b874ffece37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a606469-044c-48f8-aacd-5b874ffece37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0aa05e51-def4-4f55-abe4-25bad1691d56' class='xr-var-data-in' type='checkbox'><label for='data-0aa05e51-def4-4f55-abe4-25bad1691d56' title='Show/Hide data repr'><svg 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>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_ChunkSizes :</span></dt><dd>451</dd></dl></div><div class='xr-var-data'><pre>array([-35.  , -34.96, -34.92, ..., -17.08, -17.04, -17.  ])</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'>2018-06-01T11:30:00 ... 2021-05-...</div><input id='attrs-b531d568-8ad0-4426-bb73-5488b1d66f33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b531d568-8ad0-4426-bb73-5488b1d66f33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3631dd33-1e74-4c90-a24b-6ce213e09014' class='xr-var-data-in' type='checkbox'><label for='data-3631dd33-1e74-4c90-a24b-6ce213e09014' title='Show/Hide data repr'><svg 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><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>_ChunkSizes :</span></dt><dd>366</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2018-06-01T11:30:00.000000000&#x27;, &#x27;2018-06-02T11:30:00.000000000&#x27;,\n",
       "       &#x27;2018-06-03T11:30:00.000000000&#x27;, ..., &#x27;2021-05-29T11:30:00.000000000&#x27;,\n",
       "       &#x27;2021-05-30T11:30:00.000000000&#x27;, &#x27;2021-05-31T11:30:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3932251-58c4-4a57-9a13-cc8ee58f1ddc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3932251-58c4-4a57-9a13-cc8ee58f1ddc' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitaion</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 7 50 50]</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (time: 1096, lat: 451, lon: 676)>\n",
       "dask.array<open_dataset-441c136e564bc7a192b319bde0bb8f9bpr, shape=(1096, 451, 676), dtype=float32, chunksize=(100, 100, 100), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -75.0 -74.96 -74.92 -74.88 ... -48.08 -48.04 -48.0\n",
       "  * lat      (lat) float64 -35.0 -34.96 -34.92 -34.88 ... -17.08 -17.04 -17.0\n",
       "  * time     (time) datetime64[ns] 2018-06-01T11:30:00 ... 2021-05-31T11:30:00\n",
       "Attributes:\n",
       "    standard_name:  precipitation_flux\n",
       "    long_name:      Precipitaion\n",
       "    units:          kg m-2 s-1\n",
       "    cell_methods:   time: mean\n",
       "    _ChunkSizes:    [ 7 50 50]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.pr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e05d0be0-67d3-4762-818a-863272ac10ce",
   "metadata": {},
   "source": [
    "This is how the common spatial domain looks like (this operation takes some time since some data needs to be retrieved):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a62d235b-4498-48ae-a309-c9e496aca43e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed |  1min  9.0s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.feature_artist.FeatureArtist at 0x7f57883fb250>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfea\n",
    "from matplotlib import cm\n",
    "\n",
    "p = ds.pr.sel({'time': '2019-01-12'}).plot(\n",
    "    transform = ccrs.PlateCarree(),\n",
    "    #subplot_kws = dict(projection=ccrs.Orthographic(-60, -20)),\n",
    "    subplot_kws = dict(projection=ccrs.PlateCarree()),\n",
    "    cmap = cm.viridis_r\n",
    ")\n",
    "p.axes.add_feature(cfea.COASTLINE, linewidth=1)\n",
    "p.axes.add_feature(cfea.BORDERS, linewidth=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1452c079-764d-4f19-aaf9-53d25af7d5f3",
   "metadata": {},
   "source": [
    "## Extract a single time series"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0e4974b-0dcf-4d74-91e8-6cbf9310d2a3",
   "metadata": {},
   "source": [
    "Near Porto Alegre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "21024230-24c2-4699-b9ea-f46b0038b23c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 22.3s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f5741f73990>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "target_location = dict(lon=-51.22, lat=-30.04)\n",
    "tseries = ds.pr.sel(target_location, method = 'nearest') * 86400 # daily flux to mm/day\n",
    "tseries.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edb0ace7-7ce3-490b-98a1-3c27d75476a9",
   "metadata": {},
   "source": [
    "Average monthly rainfall in mm/day:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "85ee7cdb-9891-4457-b03c-1626270afc9d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 22.2s\n",
      "CPU times: user 1.45 s, sys: 359 ms, total: 1.81 s\n",
      "Wall time: 22.4 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f573c5e95d0>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "mtseries = tseries.resample(time = '1MS').mean(dim='time').compute()\n",
    "mtseries.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96c3edd7-2ad0-4bfa-97f6-76bcd6c4f236",
   "metadata": {},
   "source": [
    "## Load observations\n",
    "\n",
    "Load a virtual dataset prepared for the CORDEX FPS-SESA, interpolatd to the common CSAM-4i grid and aggregating times and variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b88c4820-a2fe-425b-bb2f-86dd652549ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "obs = xr.open_dataset(urls['MSWX'], chunks = dict(time = 100, lon = 100, lat = 100))\n",
    "obs_tseries = obs.pr.sel(target_location, method = 'nearest') * 86400 # flux to mm/day"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c222075-a4c0-4c3c-bebd-2b74376ef2a1",
   "metadata": {},
   "source": [
    "Load also ERA5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5709a0a3-2a1b-4c1c-aa4b-f04de2f9aaa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "era5 = xr.open_dataset(urls['ERA5'], chunks = dict(time = 100, longitude = 100, latitude = 100))\n",
    "era5_tseries = era5.pr.sel(target_location, method = 'nearest') * 86400 # flux to mm/day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ae4abbbf-c606-411a-bd0b-eefd1dfbb70f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[########################################] | 100% Completed | 29.9s\n",
      "[########################################] | 100% Completed |  3min 22.6s\n"
     ]
    }
   ],
   "source": [
    "obs_mtseries = obs_tseries.resample(time = '1MS').mean(dim='time').compute()\n",
    "era5_mtseries = era5_tseries.resample(time = '1MS').mean(dim='time').compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "70d21805-e311-4c65-8abf-92c5288c3090",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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leP62T6A28T8peuzB/H0fA6aKpbullA/n778E6JZSfjx/3ykhxL8CbwDuA94J/K6Usr9oLWeFEG9G/Z26UILsOWDGk2reJb0Dlf8aB6JCiE+jwsT/LKU8Aehw0YgQ4u+Bj+S/zwJuYLcQYkRKeWbW3+IckFIW53z+nRDiz1Dvwaqcz1pEZhXP9RXgK0KIC4G3oEQ8QAtKJBcTQl28lWPq8SGgRQghpJoF/Tngz6WUETE9VXRGhBCbgCuBl0gpk8DPhBDfKzrkTcAPpZQ/zH//IyHEfuAVQogH84+9TUqZAn4hhJgqQAE+KqWM5l/vnaiLxMP57z8BfFgIsVlK2VvT4g2GBmSmcPxb3vKWC+LxuC2Xy7F///7DAIlEQjz44INtn//85/s6Ojpyl112WfQ73/lO6xve8IbQddddF+3t7X2ura0t9/Wvf73trrvu2t7b2/tCvWszItTQ7KxHiT1Nb/42zdgUBzKG2kDnBSHEr1NwCH8upbxDSnmq6JDnhRAfBz7EHERo3q35JGpjrmUO8XpKBV3x76oblXP6VJFQEIC96LH7i47vK/P8xbdtBtYLIYJFt9lR7qi+/ztCiFzR/VlgDcot3gh8LR82/2/gT6WU6Qo/12bACZwrWrtNr0cIsRolhF6Mcv1swASAlPKEEOL9KGf0YiHEfcAHpJSDFV5rTgghPoi6cFiPcutbmRJeXoDX/DDK3QP4bynlu4rvl1IeF0IcBP4R+BUgkl9XMa1AmPJMPb4ViEgppRDilUBASvn1Ope/HpjQIjFPL+r9Aepv/7r862icwIP5x45LKWNF9/UVPbb4Ns1m4LNCiL8ruk2gBLgRoYZ5YzbHcin40pe+dOrqq6+O/+7v/u6Gt7/97Zvuv//+k9/+9rdbw+Gwfc+ePRcDxONxm9frzb3hDW8IdXZ2Wufv17/+9aEPfOADm86dO+dYt25dXZE+kxNqaHYGUZuIZlP+tpoRKh8yUuFf2RC4lPLLUsqW/L9KFdQStanVRT4s/q/AK6WUz9f48HOUbsCbir4eRYW8L5ZStuf/tUkpW4oe21N0/NSNHNTPpukDThc9V7uUMiClfEXR/XdMud8jpRyQUqallB+TUu5GhUHvRDl1lehDhe1XFT1Xq5RSh4T/v/zaLpVStqLcM+tvIKX8Sr5wbHP+uL8u8/PMmXz+5x+hXOUOKWU7yjXUa5n19YQQ98zwvryn3GOklJ8oel++q9wxKBNiW/7rg8AFQohA0f17qZz6cTB/f7ljbwP2CSGGhBBDwOtRaRB3z/az5jkHdAgh/EW3Fb9v+4D/mvI+8kspP5l/bKcQwld0fDXv23dOeT6vlPKRKtdrMDQ1brdbfvrTnx549tln/U8//bTna1/7WudnPvOZ3oGBgecHBgaeP3PmzPM///nPW8PhsO3s2bOOXE7p0AcffNCXy+VYs2ZN3almRoQamp2vAn8mhOgWQqxC5TPW1fJGSvmuoo176r9KuXHTEELckQ8XI4TYhUoNuLvofocQwoNyCe1CFeWUjUoIIW5FFSPdJaV8oo4f6xvAW4UQu/Mbsw5JI6XMocTtp/POIUKIDUKIlxU99m1CiIvyj/0/s7zWE8CkUEU/XiGEXQixRwhxZf7+zwN/pYs+8n+zV+W/vkUIcYlQhUWTqPB8xUp7KeU5VNHL3wkhWoUqetomhLgpf0gA5dYF8zmEH9KPFULsFELcKlQBWwIlxPVrDQNbhBAznhuFED/NpxPMRgCVijECOIQQ/4dSB3HW18u765Xel1W3jhKqsEz/nXejUi5+nH+NY8CzwEfy78fXAJeicmnL8SXgA/n3y3pUbul/5u/7c2AHKq/3MlQ+5r8CVRUF5kPg+4GPCSFcQogbUPmamv8GXimEeFn+PeYRqgixp+ixH80/9topjy3H51E50BeDVfD2umrWajA0AzonVP97z3veMy3NpqWlRb773e8e/sQnPrH2Zz/7WdvrXve6oL6vtbU1t2/fvsjXvva1tv/+7//u2LFjx8U7d+7c/f73v3/Tl770pVM2W/1S0oTjDc3OX6I29efy338zf9tSchvwn0KIFpTI+G/gE0X3/xlFYhDl0n0MtXFuAg4Bu6WUZ1Ebehsqn1Uf//NqxYeU8h4hxGdQVcC5/Gv/etEhf4QSl4/lRfwA8E/AffnHfg4V5swBf4EqBklWeK1sPkT6d6hCJjdwNP+aoNr1COD+vHA5j8qXvRtVQPZ5lPMayd8+28XEW1ApCodQYu8UBUfzYyihFELlhv4X8Pv5+9z5x12EEruPoHJJQb1/3gSMCSFOSylfVOG1N6KKX2bjPuAe4BgQBT5NaSi42tebD65HXQS0oETxNynkToPK3f1PVNrCWeC1+UIf7ejeU+SS/zOqoE0781/I30a+uMkK4wsh4kBU5x1Xya+hCs/GUQVKXwLa88/fl794+RvURWgWdQH07vxjfz3/c4zlb/86hRSTaUgpv5P/nXwtf4EUQrWc+mZ+/QeBT0gpvzz185lPx/lwLRepBsNik81my6YBPPHEE0eLv//Yxz42XO44gPvvv/+k/vrDH/5wubZtdSFUDrnBYGh28hvoUZS79yEp5dRK+Lk+/0XAC4BbrqDeikKIfwNeB5yXUm4XQvQA35RSXrvES1sWCFW89kZgWEq5bbbj63j+rwNHpJQfmfVgg2GeOXDgwJm9e/fWkse/bDlw4MCqvXv3bim+zYTjDYZlgpSyN59j2T5fAlQI8Zp8WLMD5TJ+byUJUAAp5W/l802357/vNwJ0/pBSvj2fWjAvAlQIcWU+NcOWz6d+FfC/8/HcBoNhfjEi1GAwzMQ7UaHbk6iw57tnPnx+maEg58WLuQ5DU7EW+CkqreNzwLullM8s6YoMK5lcLperuzB1uZD/HeSm3m5yQg0GQ0WklC9f4teft3ZahpWBlPJ7qBGlBkMj8MLIyMju7u7ukM1mW5H5j7lcToyMjLSh0rlKMCLUYDAYDAaDYQHIZDK/PTQ09IWhoaE9rNzocw54IZPJTBu00hSFSatWrZJbtmxZ6mUYDAaDwWAwzMpTTz01KqXsXup1NDpN4YRu2bKF/fv3z36gwWAwGAwGwxIjhDDTtqpgpVrDBoPBYDAYDIYlxIhQg8FgMBgMBsOis2AiVAjx70KI80KIF4pu6xRC/EgIcTz/f8dCvb7BYDAYDAaDoXFZSCf0P4Gp7V3+GPixlPJC1MziP17A1zcYDAaDwWAwNCgLJkKllD9Dzf0t5lWoecDk/3/1Qr2+wWAwGAwGg6FxWeyc0DVSynMA+f9XVzpQCPEOIcR+IcT+kZGRRVugwWAwGAwGg2HhadjCJCnlv0gp90kp93V3m1ZbBoPBYDAYDMuJxRahw0KIdQD5/88v8usbDAaDwWAwGBqAxRah3wV+I//1bwB3L/LrGwwGg8FgMBgagIVs0fRV4FFgpxCiXwjxW8AngduFEMeB2/PfGwwGg8FgMBhWGAs2tlNK+cYKd922UK9pMBgMBoPBYGgOGrYwyWAwGAwGg8GwfDEi1GAwNASJdJY3feFxDg6GlnopBoPBYFgEjAg1GAwNwVAowS9OjPLE6akzLgyGxuVAX5AfHRpe6mUYDE3JguWEGgwGQy0kMlkAQvH0Eq/EYKief/7ZSV4YmOT23WuWeikGQ9NhnFCDwdAQxFNGhBqaj3AiQyyVWeplGAxNiRGhBoOhIUikc4ARoYbmIpLMEMtfQBkMhtowItRgMDQEibTayCeNCDU0EZFEhng6i5RyqZdiMDQdRoQaDIaGQItQ44QamolIMoOUkMzklnopBkPTYUSowWBoCOJGhBqakEhC5YOakLzBUDtGhBoMhobA5IQamo1cThJJaRFqipMMhloxItRgMDQExgk1NBuxdBadCho3TqjBUDNGhBoMhoZA54Qm0jnra4OhkdGheChcRBkMhuoxItRgMDQExcLTVMgbmoFIsiBCTU6owVA7RoQaDIaGoFiEmpC8oRkoFqEmHG8w1I4RoQaDoSHQhUlgRKihOSgOxxsn1GCoHSNCDQZDQxA3TqihyYgkC+9TUx1vMNSOEaEGg6EhSKSzOGwCMCLU0ByEi5xQU0xnMNSOEaEGQ5MRiqX5xpN9S72MeSeRzrI64AaMCDU0B6YwyWCYG0aEGgxNxg+eP8cffvs5BoLxpV7KvJJI5+hu9QBGhBqag6gRoQbDnHAs9QIMBkNtTCaUQCveAJcD8XSWFredgNthRKihKQgnM7gdyssxfUINhtoxTqjB0GToitzlJkIT6Sweh51Wr9OIUENTEElkCHgc+Fx2U5hkMNSBcUINhiZD56Ett/BfPJ3F47LT5nWaZvWGpiCSzOB3O8hk5bL7PBoMi4ERoQZDkxFepk5oMp3D41Ai1DihhmYgksjQ4naQzJhRswZDPZhwvMHQZOjehMvNeUmks3hdNiNCDU1DOKlEqNdpX3afR4NhMTAi1GBoMnQ4PrrMctDi+ZzQNq+TYMyIUEPjo3NCvS4jQg2GejDheIOhydCFSbHk8tn0pJR5J9SOzSaME2poCqIp5YRmcpKxSGqpl2MwNB3GCTUYmozwMnRCU9kcOQkep3JCTY6doRmIJDK0mOp4g6FujBNqMDQZlhO6jMJ/iXQOUCLUle+7OBlP43Hal3JZBsOMqJxQJ/FUznoPGwyG6jFOqMHQZFg5ocuoOl67nh6nKkwCMzXJ0NgkM1lSmRwtbrtxQg2GOjEi1GBoIrK5Qj/C5eWE5kWow067EaGGJiCaz8lucZvCJIOhXowINRiaiOI80OXkhOqRh958s3owItTQ2Oi0mBaPE6/TTjKTI5uTS7wqg6G5MCLUYGgi9MYHy80J1TmhJhxvaA50WkyLWxUmgZkfbzDUihGhBkMTESlyP5dTdXw8pXNCjRNqaA70Z1HPjgdMXqjBUCNGhBoMTYQe2elz2ZdVn9BEpiBCW40INTQBenKZyglVjWYSKVMhbzDUghGhBkMTod2XNa2eZeWEJnVOqNOO3SYIuB1GhBoaGn1B6M+P7QSIpZfPZ9JgWAyMCDUYmgidE7o64F5WOaHxdMEJBWj1OgmZ0Z2GBqZ8OH75fCYNhsXAiFCDoYnQIcA1rZ5lVR2vC5O0o9TmdRon1NDQWNXx+RZNUMhtNhgM1WFEqMGQ569+cIhHTowu9TJmRIcA17S6SWZyZLLLIwetUJikTklGhBoanUgygxAqP9s4oQZDfRgRajCgmsB/4Renuffg0FIvZUZ0CLA74AYgtkxawhQXJoERoYbGJ5LM0OJ2IIQwLZoMhjoxItRgAMKJNFKW9uFsRCKJDH6XnYBHVZAvlwr5RN5BcjuME2poDiKJDAG3qorX1fHxZVQsaDAsBkaEGgxAMF8EM9noIjSZoaWoEGK5VMgnMjk8ThtCCADafEaEGhob/VmEQi6zCccbDLVhRKjBQKEnZTjR2MInnMzgdzvw552X5eKExlNZayMH5YQmMzlrprzB0GhE8p9FwOSEGgx1YkSowQAELRHa2M6iDgH63MvMCU1nrXxQwJqaNGncUEODEk6onFBQaSRCmOp4g6FWjAg1GIBgLAVAONnYokeHAC0ndLmI0ExumhMKZmqSoXGJJDME8uF4IQQ+p90UJhkMNWJEqMFAcTi+sUVdJO+++LUTuozC8W4jQg1NRDRZcEJBFSeZcLzBUBtGhBoMYE3nCScySCmXeDWVUW1hnPiWmROazGTxOgunIyNCDY2OuiB0Wt97XTZTHW8w1IgRoQYDhZzQbE42dEgtnEgTKArHLycntFxOaNCM7jQ0ILmcJJIqVMcD+JzGCTUYasWIUIOBUrHTqCF5KSXRVLZkTOBycUITmenV8WCcUENjEktnkRJa3IX3rNdlckINhloxItRgAELxlPV1o7ZpSqRzZHOSFo8Dl8OGy24jukycl6lOaKsRoYYGpjA3vhCO97nsxgk1GGrEiFCDgVKx06hOqK7c18UQPredWLIx11oriXQOd1FOqN0mCLgdRoQaGpKI/iwWh+NddtOiyWCoESNCDQZUOH5Vi5rH3qgiVLsvui2M3+VYNk5oIl0ajgflhpo+oYZGRJ8jAlOq40043mCoDSNCDQZUYdLGTi/QwCI0qUOAhSktyyYndEqzejDz4w2Niy4ILHZCvU7bsvk8GgyLhRGhhhWPlJJQLM3GDh/QuDmhhTw0HY53LIvqeClVR4KpTqgRoYZGJTIlNQbAZ/qEGgw1Y0SoYcUTT2dJZXP0dDS2ExrWTqgVjl8eTmg6K8lJ8DhLT0ftPiNCDY1JeMoFIeSr440INRhqwohQw4pHC50NHV6EaHwnNJCvyPW5locTmsion8GE4w3NwtTUGACf004mJ0lnc0u1LIOh6TAi1LDi0T1CO30uWlwOJhvUCY1MdULdy8MJTaSMCDU0F/qC0D/FCQVMSN5gqIElEaFCiN8XQhwUQrwghPiqEMKzFOswGKAgQtu8TgIeR8OG47UI1XPjfcukOj6RVs5Ruer4ZCZHwlQcLwu+e/S7HBk9stTLmBciyQxuhw2Xo7CFahFqQvIGQ/UsuggVQmwA3gfsk1LuAezAGxZ7HQaDRjeqb/M5CXicDRuODycyuBw23A612fldy6NPqG5rU84JBdOwfjlwauIUr/raq3jr/751qZcyL0SSGatVmsa3zKaYGQyLwVKF4x2AVwjhAHzA4BKtw2CwRE67z9XgTmi6NAfN7SCWzpLLySVc1dxJWCK09HRkROjyYTCsTvED4YElXsn8EElmSj6LAF6n+t6E4w2G6ll0ESqlHAD+FjgLnANCUsr7px4nhHiHEGK/EGL/yMjIYi/TsILQ4fh2r5MWj8MKezcakUTpxud32ZGyUNjTrGgntFyLJjAidDkQTARL/m92IolMSY9QKDihpmG9wVA9SxGO7wBeBWwF1gN+IcSbph4npfwXKeU+KeW+7u7uxV6mYQURjKdx2gU+l72hw/FT3Rdf/utmr5DXTqi7kgiNNebfw1A9oUQIgEgqQibXmBd5tRAu44T6TE6owVAzSxGOfwlwWko5IqVMA/8DXLcE6zAYAOWEtnmdCCEaOhwfnuK++JdJDlrCOKHLnlAyZH29HNzQqVEJMNXxBkM9LIUIPQtcI4TwCSEEcBtweAnWYTAAMBlPW4KnkUVoJJkpmVXtcy0XJ1RVx5uc0OVLsfBcFiK0bE6oDsc35vnDYGhEliIn9HHgW8DTwPP5NfzLYq/DYNAE4ynafS4AWj1OUtnGbAsUSU5xQt3LzAl1TW/RBEaELgd0OB6WkQidlhNqCpMMhlpxzH7I/COl/AjwkaV4bYNhKsFYmrWtqlWtbrsSTmSmtQxaaqJTc0K1E9rkm57VoslR+vu22wQBt8OI0GXAsgvHJzO05CeXaUyfUIOhdszEJMOKR+eEQrEIbTzhMy0nVDuhDVrNXy1Ws3rXdNHf5nMyaURo07OcwvHJTJZUJlexT6gRoQZD9RgRaljxhOJp2nx5EZp3NxotLzSVyZHM5EpyQv3LzAl1O6afjszozuXBcnJCdQ721JxQp92G0y6INWAqj8HQqBgRaljRpLM5IskM7V6VE1ocjm8konpufEk4fnnkhCbTWTxOG6pOsRQjQpcHyykntNzceI3HaTdOqMFQA0aEGlY0k9a0JB2O105oYwkf3UC/xVPIQ/Mvkz6h8XS2Yv6tEaHLg2LhORGfWLqFzAPhpHo/TnVCQV0YNvtFocGwmBgRaljRBPMCZ3pOaGNtJHo9xRuf22HDJprfCU2ks9OKkjRtXqf1NzI0L8spHK+d0Kk5oaCKBU11vMFQPUaEGlY0emSnlROqRWiDFftoJ7R44xNC4Hc5loETmitblATGCV0ulITjk8GlW8g8EE1NvyDUeJ32hmzvZjA0KkaEGlY0Vjg+74TqjaXxwvHlQ4A+d/OH/xLpbNmiJFC9QlOZxuzbaqiOdDZNNB21vm92J9SKSpR1Qu3GCTUYasCIUMOKJhhPAVjN6h12Gz6XvXHD8VM2Pr/L0fTV8Yl0dkYnFEzD+mZmMjlZ8n2zi1ArKlHOCTUi1GCoCSNCDSsaHY7XTijo0Z2NJXoqbXw+t30Z9AmdOScUjAhtZorzQWEZiNAZnFCvqY43GGrCiFDDikaL0NYSEepsOCe0UlsYn8th5ag1K4lZckLBiNBmRovOLm8X0PzV8ZFkBpsozIovxueyEzOz4w2GqjEi1LCiCcXTBDwO7LZCj0rlhDbWRhJJZhCi0BtU418G4b94vk9oOSwRGjMitFnRRUlb2rcAze+EhhMZ/G5H2b62XpfDOKEGQw0YEWpY0YTiaatHqEY5oY0lesIJNTd+6sbnczusRvbNSmKWPqFgnNBmRofjN7RuwC7sxDNxkpnkEq+qfiLJTNl8UFAXiUaEGgzVY0SoYUUTjKWsaUmaRnVCy218y8EJnUmE6gsEI0KbF+18trnb6PB2ANPzRJuJaDJTNh8UdDg+i5RykVdlMDQnRoQaVjTBeNpy2zStHgeTjSZCE+U3Pp9rOTihuYqFSXqClRGhzYsOx7d72mn3tAPNHZKPJDNle4SCGtspJSQzuUVelcHQnBgRaljRhGJpq1G9psXdmNXx5TY+v1s5oc3svMTTWbyu8qciu00Q8DiMCG1itOvZ5m5bFiI0nMiUjM8tRudsN3t0wmBYLIwINaxoQvF0SXsmUO5bMpMj1UBuRjhZfuPzuRxkcpJUtnHWWgvpbI5sTlZ0QsFMTWp2rHC8Z3mIUHVBWP79WhChzR2dMBgWCyNCDSsWKSXBsoVJynGMNFCYO5JIV8wJBYg16ejOeH4SUqUWTWBEaLNTLhzfzG2aIonK4XivS91uJnwZDNVhRKhhxRJJZsjm5LScUJ2H2Egh+WgyW3bj8+Vva9ZeoXqzdlcoTAIjQpudknC8ux1YDk5ohXC804TjDYZaMCLUsGIpTEuaXh0PNFSFfKRCRa4/77w066aXTKs0gnKNvzVGhDY3WnB+68vfYnRgtOS2ZiOXk0RTM1fHQ/N+Hg2Gxab8J8lgWAFoYTO1MEmL0MkGcUJzOVmxMMmXz01r1gp5HY6v1KwejAhtdrQT+o0vfYPV16yGS5pXhKr2S+XnxgN48iLU9Ao1GKrDOKGGFYsWNlMLk1qtcHxjCDsdag8sQydUh+ONE7p80TmhJCA+EQeaV4TONDcejBNqMNSKEaGGFYsVjvc1djheF0iVdUJdTe6EprQTWlmEtnqdpDI5U+zRpFiCMwmx8Zi6LRlcsvXMhUhSnTMqFSb5nPqisDk/jwbDYmNEqGHFEoynABq+MGkm98XvbnInNN8GayYRakZ3NjfWdKQEZKPqfdqs1fH6wrRydbx6H5sLJoOhOowINaxYCk7o9Gb10DhOaHgGJ1S3aGrW6viCEzpzTigYEdqMJDIJUtkUduyQARLq9qYNxydNON5gmE+MCDWsWCbjadwO2zQXzuWw4XbYGs4JLZcTqls0NWuf0GRm9nC8mR+/eGRzWd71/XfxXwf+a16eT4tNt3SrG5pdhM7ihHpMiyaDoSaMCDWsWIKx6Y3qNQGPs2Gc0EJO6PS16oKeZndCZytMAjVi1bCwPHXuKf75qX/mL372F/PyfLooyZHNizZVl9S8InSGqASoMbNuh83q+mAwGGbGiFDDiiUYT03LB9W0ehxWGHyp0e6Lv8yoQLtN4HXam9Z5SaRnd0L13yhonNAF59jYMQDG4mPz8nw6H9Seyv99m90JTVaOSmh8LrspTDIYqsSIUMOKJRhLT2tUrwl4HA3jhGoxHKgwpcXvtjdvdXyVzerBhOMXgxPjJwBVOJTNzf3CprgyHoAMOHCQzCZJZBJzfv7FpnBBOJMIdRBP5RZrSQZDU2NEqGHFEoqnpzWq16hwfGOInpmcUFCbXrM7oW5H5VOR7lZgROjCc3z8OAASOS9upQ7H5+IFUeYRHqA53dBIMoPHacNpr/x+9brsxNPNeVFoMCw2RoQaViyheHpao3pNIzmhkWQar9OOo8LG53M1rxOayGRxO2zYbIKhyBCv+tqr+Mnpn5QcY7cJAh4Hk0aELjjaCQUYj4/P+fl0OD4bKVwkuXIq+tCMbZrCFSaXFaPC8c15UWgwLDZmbKdhxTJzYZKjcZzQCnPjNX53EzuhqayVD/qDYz/gu0e/C8CtW28tOc5MTVocjo8dt74ei49xIRfO6fm0E5oKp6zbnBknOJvUCU3MLkI9TZyjbTAsNsYJNfDz3p+z7XPbeODUA0u9lEUjmckST2crFiY1UnV8OJGpOKsa8k5okxZCJNI5Kx9UO2/FQkhjROjCMx4fZyJRcCfHYnMvTtJCMzVZEKG2lK3kvmYiOssFIajPo5kdbzBUhxGhBr5+8OucmjjF945+b6mXsmhoQdPmq1yYFEtlyWSXvsBgVifU5WjaPqHxdNZqVK8F0InxE9OKYowIXXimiv/5DMdTXIPUxBXy1YbjTYsmg6E6jAg18Pz55wE4Fzm3xCtZPHTPyco5oer2SAPkWs4WAvS5m9kJLYTjdY5gOpemN9RbcpwRoQtPcT4ozE+bJkuEJgu35WLqwq4ZRaj6LJY/Z2i8TodxQg2GKjEidIUjpeT54ZUnQnXPyZlyQqExRndGZnFf/E1cHR8vFqFFoeCprpwRoQuProy3C/X3mM9wPAnwer0ApMPp0vuaiEgyM2OPUDB9Qg2GWjAidIUzGB60Nv9z4RUkQvNOaMWc0Lzom2yA4qTZwvG+Ju4TmkznpoXjodA0XWNE6MKjndBL11wKzFM4PlEIx19wwQVAIT+0+O/dLESSmYqt0jReUx1vMFSNEaErnBfOv2B9PRQZWsKVLC7BmNoIKzerz4fjG8QJnakwye9ykMzkGiJ/tVbi6axVmFTsjE0ToT4nqUzO6itqmH+0CL16w9XA/Ifjt23bBkB8Qs3ubEontKpwvJ1kJkc2JxdpVQZD82JE6ApH54MCRNNRwsnwEq5m8SgUJjV2OF5KqTa+WcYEAsSaUKCVywkFODY+3QkF07B+IdHh+Kt7lAidDye0OBy/fv163G631TO02URoMpMllc1VFY4HTHGSwVAFRoSucIpFKKycvNBQPI1NUNFhtERocmlFTzKTI5OTM7oveoRgM1bIJzIFJ3S2nFAopFEY5pfx+Djj8XH8Tj8Xd18MzJMTWhSO7+jooKOjo2mr46P5z1c11fGAKU4yGKrAiNAVji5K8jjUKL2VkhcajKVp9Tqx2UTZ+3U4fqmdUP361TihzVghH0/lcDvtSCktJ9QmbJwJniGZKZRUGyd0YdGh+O2d2+nydQFzL0ySUpaE4zs6Oujs7GxaEapTc2YToV6Xut+IUINhdowIXcFkchkOjRwCoMOuihFWSl5ocIaRndA44XjdImq2nFBoTic0mc8JjaQiZGUWn9PH1vatSCQnJ05axxkRurBoEXph14V0ejuBuYfjI6kIOZnDkXNADjo7O5vaCdVRkWqa1QPEzPx4g2FWjAhdwZwcP0kym2S1bwOR6GpgZYXjKzWqBzV6z2W3LXl1fDXui8/dxE5ovlm9DsV3eDrY0bUDKC1OMiJ0YdHpD9s7ttPmbsMu7IRTYVLZ1CyPrIx2QR0Z9d5t9nC8/izOdEEIWOklpkLeYJgdI0JXMDofdJ1/J3ap3I+VEo4PxVIzOqGg58cvcTi+CvfFckKbTISmsyrf1eu0W6H4Dq8RoUvBiYmCEyqEmBc3VOeD2tJqm5nqhE4kJpCyeSrIdVTCP2s4fvFyQnM5yU+Pnmd4MjH7wQZDA2JE6ApG54N2Ordhlx3AynFCg/F0xUb1mkYQodU4obpvYbTJwvG63ZLHabec0HZPuyVCi4uTdI6uEaELg+WEdm4HmBcRqp1OmVBC03JCs+DESSaXIZaOzWHVi4sWodWG4xdDhI7HUrz1P57knudXxnnbsPwwInQFo51QD1ssEbpickJj6YqN6jUBj5PwUofjk1WE45vUCU2kVV9Tj9NWcEI9HVzYeSFQ2qbJbhMEPA4mjQhdEKyc0Pzvfj6Kk3Q4Xo/ptEQo4JZuoLlC8tXkZ8PitkwbjajivVUB94K/lsGwEBgRuoLRIlRkNhXC8SvACc3lJJOJmQuTQAm/JXdCq3BfdDi+mZ1QLUYqhePBTE1aKCbiE4zFx/A7/axtWQsUnNC5tGnS4fhMRL2HrXA84MzmW241kwitolMFFFfHL/y5YySsRGh3ixGhhubEiNAVSjQV5eT4SRw2B7HomkI4fgXkhIYTGaRkxsIk0OH4pRU94SrC8ToHrfmc0Onh+A5PBxvbNuK2uxmKDDGZnLSONyJ0YShuz5TNZnn/+9/P5JD6vc9HOD4bzeJwOPD7/ZYItaenT8lqdCLJDDZRKDyqhG8RC5OME2podowIXaEcHj2MRLKzayfnJ7PYaAVpYyw+NqeK2GYgGNcjO2cPxy/12M5IMoPTLnA7Kn9UXQ4bLruNaJNV4+qJMiWFSZ4ObMLGhV0qLFycF2pE6MKgJyVt79zOAw88wGc/+1mee/w5YH7C8SSVCyqEsESoSKr+vM0kQsOJDC1uB0KU7y2sKVwULoIIDatz2SrjhBqaFCNCVyi6KGnXqouJprJs6mzBTjsAw5HhJVzZwqOn7syeE9oA4fgqNz6f204s2WxOqM4JLXJCvUqkWMVJ4wUR2u4zInQhKM4Hve+++wCIj6v57vNRHa+nJUHh/1xc/e2Lp2Q1OpFkZtZG9QBuhw0hFqcwaTSSxGW30TpLioDB0KgYEbpC0fmgm1p2AnD5xo4VUyEfzAuZ2arjWz0OIqkMudzStZGJJGeeG6/xuxxN54TqcLzXVdonFAoFMlPbNJmxnfNPsROqRWhyQoV555ITWjw3fqoIbcb58ZFEdZ9FIQQ+p31RZsePhJN0B9yzXqQaDI2KEaErFC1Cuz1qs79sY3vT9ApNZXJzytUMVSlCAx4nUkJkCXMtVQhw5nWCqshttpxQvUm7HaV9QoGyxUmtXieT8XRT9ZZsBrQT2pZt4/Dhw+rGfOekORUmTQnHDwTjuHwBANKT6jPYVCK0SicUVHHSYoTjRyJJVrXMnNtuMDQyRoSuUHQ4PuC4AIDLNrU3jRP69z86xqv/4eG6Hx+KqTyqNu/shUmwtKM7I8n0rC1hAHxuR9NWx3td9mlOaKWG9alszgrjG+YHnXd75ukzhRtVNH5u4fhkaTj+df/0CF95VonaeFC9QNOJUM/sF4SgLgoXozp+NJIy+aCGpsaI0BXISHSE4egwLa4WMqlVyGyGk0/+FGeuFWj8XqGHz01yciRad85V9Tmh6v6lrJCPJrNVhuObzwktqY6fwQnVzqeZmjT/6PZMPqePR3/0aOGOvAidS2FScTi+vaODwVCC3lAGt9tNLporPaYJiCQzVV0Qgiq2W6zq+G5TGW9oYowIXYG8cP4FAPas3sP5cIrk41/jV1/7K4iBQaDxw/GDeRelb6K+aSvBeBqfy45rhopzaBQntLoQoM/VjE5ovjDJYSuZmATQ7eumzd1GKBliNDYKGBE6F9LZXNnfmw7Fb+vYxo8f+DEAV1111fyE4xOFcLy3RV3gDkzE6ezsbMr58bpIsBq8roXPCc3mJGORpHFCDU2NEaErEJ0PesnqS+gbHmds//cBsE8ocdfI4XgpJQN5EXp2rD4RGorP3qgeikXo0omecJXFEH538zmhccsJLZ2YBKq4Q7dp0iH5RhOhY5EkDx49v9TLqIq//9Exbv3bnzI55b2sRWgXXYRCIS688EIlQuc5HK9zQQeD8ZL58U0lQqssEgQdjl9YEToRS5GTmJxQQ1NjROgKROeD7lm9h6d/fDeZeETdMaF2hkYWoaF42gpznR2v0wmNpWdtVA+N4oRWmRPaxNXxkhTpXBq33Y3X6bXun5oX2mgi9IuPnOE3//PJJR9oUA0PHjnPWDTFfz3aW3K7roxPDas86Ze97GV0d3dDGuzSTiKTqHu+e3E43ulTTmg4maG1rd0Soc3SoimXk0SSGfxVOqGqUHBhP4+mUb1hObAkIlQI0S6E+JYQ4ogQ4rAQ4tqlWMdKRTuhF3dfzMkHv2ndnh5WU1IaOSe0P+/WQv0iNBRPVemEqmMml0iEpvNFONWEAP2u5usTGk9ncTlshJJBoJAPqtnR2dgitHc8hpT1vw8Xi2AsxdHhMA6b4As/P0W06H2indBzL6gLT0uEAu6cEjf15IVmc1kiqQhIIAW4W6z7PP7WpnNCo6nq5sZrvC7HgofjdaN6M7LT0MwslRP6WeBeKeUuYC9weInWseLIyRwHRw4CMPDsEMmxflo71aYT7Ve5d0ORIXKyMSuQdT6o0y7om4sTWkM4fqmmJkWrmBuv8bkdxNLZJe1pWivJdK4kH1SH4jWWEzremCJUv//qfR8uFk+cHkdK+NDLdjIRS/PlxwtuqHZCTz91GqfTyc0332yJUEdKve/qCcnrcav2jF0JUbffus/ha2k6ERqp4bMIanTnQqfHjETUL9E4oYZmZtFFqBCiFbgR+DcAKWVKShlc7HWsVHqDvURSEda2rOVfP/dvAPzym95BIBAgHUsicn4yucycqmIXEp0Purenvf5wfDw9a49QUBWudptYsnBrNXPjNX6XHSkhkWmekHwinVXtmaZUxmumju7UznSjiFDtyvfWmZu8WDx2ahy3w8Zbr9/C9du7+JefnbZSIbQTyhi8+MUvpqWlxRKhWijWU5ykxaVIqSbqGYfPuk+4S0VoM/R9tS4IayhMWvBwvBnZaVgGLIUTegEwAvyHEOIZIcQXhBD+qQcJId4hhNgvhNg/MjKy+KtcpuhQ/FbfVn7x0IMIp4c3vvk32LhxIwD2jAqbzVdIPjnPomgwGMfjtHHZRiVCa93ApJSE4mnaqhChQoglHd0ZqWHj8+WPaaYK+Xg6Wzqyc4oTqqcmHR8/Tk7msNvU32OyAURoIp3lfFjl5DV6OP7x02Ncvqkdt8POe2+9kNFIkq8+cZZgIshobBRHzgFhFYoHLBGai6hoSD1OqC5Kkgn1+UzbfXicNlwOG1mnD3LglE5yMqfC9g2OdUFYpRPqddktob9QmJGdhuXAUohQB/Ai4J+klJcDUeCPpx4kpfwXKeU+KeU+68rcMGd0UVL4ZBiAlktuY8emtfT09AAgUsqxmI/ipOPDYfZ85D4ODU7O+bk0A8E469u9bO7ykczkLCFQLYl0jlQmR/ssjeo1SoQujeipJQTod9kBmqpCPpHO4i3TI1TT5mljjX8NiUyC/sl+QE25CuaHDSwl2pGHxhahoXiaQ+cmueaCLgCuuaCLq7Z08s8PneLQ+aPqoHxt0FQRmg6p9309URHdnikbVUIsYfPS5Xezvs1Dyq6Kz1w59RlshpC8/ixWmxPqc9pJZyXp7MKlNZmRnYblwFKI0H6gX0r5eP77b6FEqWER0E7okYeOABC44pdZ0+qxnFBbXDmE89Er9PmBEOms5IXB0JyfSzMQTLCh3cvGTiWWaxUAwbiellTd5JOA27l0TmgN4Xifqxmd0BzuGZxQKF8h3wjheB2KX9PqbmgRuv+Myge9emuXddt7b9vO0GSCLz+lTsGZ4Qxr167l0ksvBdSITSEEyWD98+MtYRkHr9dLOCPo8DtZ3+4lJjwAODLqPdsMFfL6s1htdbzXuihcuM+jGdlpWA4sugiVUg4BfUKInfmbbgMOLfY6VipahGYGM+y48iY61m0m4HFaTqgzrk6e8+GE6ly5/nncpAcm4mxo97JJi9Aa8/H0tKRqckKBJQ3Hh7X7UmWfUGhGJ3R6j9BiGlWE6mKk67etYmAiTmYBHa+58NipMVx2G5dvarduu2H7Ki7b2M73Dj6jbhiHl770pZajZrfb6erqmlOv0Klz48ejKTp8Lja0ewnnq+5tKbX9NIMTGq4xJ1RfFC5kr1AzstOwHFiq6vj3Al8WQjwHXAZ8YonWsaJIZpJqM5fACFx46+tZ26ZcCS1C7VGVwzUfOaFW9XBRW6W5kEhnGY0kWd/uZUOHFyFqd0K1gKmmRROoYpipDb4Xi4ITWrrW559/nj/8wz9kcrKQ5mA5oU3UKzQxJSdUT0sqxsoLzRcnNYoI7Z+I47QL9m3pJJOTnAsllnpJZXn89DiXbWrH47RbtwkheN9t2xlP5qvkx+HlL395yeO6u7vnNDXJmpaUnxs/EUvR6Xexvt1LWOaFU/600AwiVH8Wq7kgBPC61Na6kBeFZmSnYTmwJCJUSvlsPt/zUinlq6WUjR+PWQYcHTtKJpeBcbhk1yXYey5hbasSoVY4PqTC1fPihOYFYn+d4zWnojf6De1e3A4761o9NbfHsebGV+mEti5pYZJa69Sc0I9//ON86lOf4u6777Zus5zQJuoVmkhn8TiKwvHeGZzQ8WIndOl/xr6JGBvavWxZVV9ayGIQTqR5YSDENVs7p913y87VOF3D6ptxuP3220vu7+7untP8+OJG9R0dHUxoJ7TDq6rjgWwsW3psA6Or46sOxzvVcQsVjjcjOw3LBTMxaQXx3PBz6otheP/738/wZHKaE5odjQLzkxOqw/F94/PjhOoeoevbVWHDxk5fHU6oEtntVUxMgiUuTEpkEEIVORRz5IjK5x0eHrZu8zehExrPt2jSIqSacHyr18lkPL3kbX36J+Js7PQV0kIaUITuPzNBTsLVF3RNu08IQUr2AbC56yJWrVpVcn+xCJ1rOL69o4PJRMYKx9s8SoSmJ9XnqhlEaCSZweO04bRXt2X68jmhC1Uhb0Z2GpYLRoSuIO556h4AfFEfv/r6NzASSbKurdQJjQ8GARiYowiNpTKMROLYXf0MhWPz0qpJVyT3dCgRuqkOEWo5oVWG41s8DiLJzJKInnAyQ4vLgc1WqH7NZrMcP65C06Ojo9btvqasjs+Vzo0v44Ru69yGQHB64jTprBoykMpPklpK+sdj9HR4WdfmxWkXDdkr9LHTYzjtghdtmv57DSaCxGQY0iDbX0R2ypCD+QzH+wNtAHT6nSUiNDmZtNbS6ISTmWlpMTPhW+DCJDOy07BcMCJ0BfHjF34MwCuueAWRjI1sTrImH45vbW1VDevH1clteI45oWfHY0TsP+KU/V2EbfcwMA95oQMTcYTAWvPmLh/nw8makv9D8TQOm7BaGs1GwOMkJ5fGYYwkMtNC8X19fSST6m9ULEL9TdgnNJGauU8ogMfhYXP7ZrIyy+ng6YaYmhRLZRiLpujp8GG3CXo6fA05NenxU+Ps7Wm3KrWLsZrUj0NyzSXc80LpReecw/H5UawkwNOi5sZ3+F2sbfNgc7pxutzkoupCohlEaCSRqTofFBa+Ot6M7DQsF4wIXSGcOnWK4ZwK3/7eG3+PcyG1w2gnFPIh+QSQcxJNR+bURPrsWIyUTfUhTNnOlMx8r5fBYJzVATcuh3rb6jZNfTXknOppSdX21lvK0Z2RZGZaNe6xY8esr8fGCuLA7bBhE03mhGbyInQGJxQKxUnHxo41hAjV72XtyNeTFrLQRJMZnh8IcfUF0/NBAR49+igAjkkHF+29gv/3kxMlI1+nhuNrjQRYTmgSXL68CPW58DjtdAfcuIrmxzdFi6Zkxsq7rgarOj69MJ9HM7LTsFwwInSF8Hf/7++gHew5O9fuuJbhSXUS064iFBUnZdQAq7nkhZ4dj5EW6vFZMVGTUKzEQFC1Z9LU06YpVOXceI0eFbkUeaGR5HQn9OjRo9bXxU6oEAK/y9E0TmgmmyOdlapZ/QxOKJTmhTaGCFXvt54O9f7b3Omjdyy6ZOspx/7eCbI5WdIftJgHnn4AgK1tW3nf7bs4MhTmR4cLOcbd3d2QBUfWQVZmrVnw1WLlhCbA4VXh9458Hvb6di8OT3PNj48kpl8QzoTXuThOqClMMjQ7RoSuACYnJ/mPH/4HABd2XIjdZrcqzac5oYAtoW6bS4V871iMrE09PieC81KcNJiflqSppygkGE/VKELVxjPZaE6ot1SEAvjc9qZxQhMZFYq129IkMgmcNic+p6/ssY0mQvV7eWNnITd5MpEhFFv61lGax0+NYbcJrthcXtg/e/ZZAK7efjWvvHQ9m7t8/N+fHLccTz01yZ5WYqrW4qTi6njhCQDQ6VcitKfdC25/U4nQWnNCdTh+ofqEmpGdhuWCEaErgP/4j/8gHlAb59VbrgZgaDKBy26zNgYo6hWaUCfbufQKPTU6TkbkRZI9OOc2TbmcZDCYYENHQYR2+l34XfbaRGgsXXVlPGCd5JfECS2Th3bs2DG4GfhDOOcovUjwuxxNUx2vq4ZzQqV8dHg7EEIQCoWmhX7LidClHN3ZPxHD7bBZ+Xj1Tu9aSB4/Pc6lPW1lWwplMhkGEgMA/NK1v4TDbuN3bt7OCwOT/PToCFAQoSKu0lZqLU4qDsdLl4qs6AERGzq8ZBy+phKh0WRtOaG+BRahIxEzstOwPDAidJmTzWb53Oc+B6vV93tW7wFgKJRgTVvpSUyH4x0xddtcwvHHx09aX2fkxJw36NFoklQ2VxKOF0KwsbO2opBQPF11o3ooDsc3hhN69OhR2A4ImPRNks0WNjmf2940fUL15pyWYUCF4h999FE6Ozv5q7/6q5JjrYb148dp96oLiKV2Qns6vNZnZ3OXEqG9440Rko+lMjzXH6wYin/88cfJtqnf/4t3vxiA17xoAxvavXwu74ZqEZqNqONqLU4qDsenHT58LrvVMH99m6fpnNByn8WZcNptOO2C2AK1aBoJN+fIzm8c/Aa3fvFWRmOjsx9sWBEYEbrM+f73v8+pU6fwbFYh9ktWXwKoxu/rWr0lx1rh+LA6cdYbjs/mJH2Tpwrfk+Ts+NxOOrq6vliEQu1tmkKxdNWN6qEQjl8SEZooDQHG43F6+3qtCwrplQSDQet+n8tBtEnC8bplV1oqJ7Td087+/fvJ5XLce++9Jcdubt+M0+akf7Ifmy2JEDC5lDmhwZiVDwqN54Q+3RsknZUVi5L+997/BT84pIN1gXWAEk3vvnkbz5wN8vCJMatvaGZSvZ9qCccnM0kSmQTkgDSkHV4rHxRgQ4dPtWlqJhFaplPFbHid9gUMxzfnyM5/ePIfePDMg9x74t7ZDzasCIwIXeZ8+tOfBsC2Vv2pL1mjROjwZII1RfmgUHBCc+Nqd6hXhJ4LxUkyWHLbSHx4TvmKg0G1pvUVRGg11bvpbI5wMtMUhUm5nCSSKt34Tpw4AR2A3s/9U9o0uewLVggx38RTKic0lVMFLx3eDkZGVCj4+eefL/l7OmwOtnVuA+BU8CQBt2PJq+N1PiioeeKrWlw1FcgtJI+fVvmg+yrkg/7w0R8C0OPrwSYKW8Dr9vWwttXD5358HKfTSXt7OzKm/g61hOO1CyqSyilOCG9J2s/6dk+JCA0lQuTk0vZ9nYlkJksqm6vJCQWVF7pQOdqjTTot6dSEMid6g71LvBJDo2BE6DLmmWee4aGHHsK/zk9Mxuj0drKuZR1SqlnX66aIUO2EJodViHRwsj4RenasUBmvyYqJObVpGgiqDb44JxRUKDSZyTESTs76HJM1zo0HJeyEWHwnNJbOIiUEija+Y8eOwZqig3ylbZp8boc1XrDRSeSd0FSuEI4/f/48oArpzp49W3J8SV6ob+nmx4cTaYKxdIkTCo3VpunxU+PsWd9qXUAVMzo6yqHhQwBc0nNJyX1uh5133nQBT5wZ57FTY6UN62sIx+t8UBlXAjaCm47i3PP2vBMqwZVzIZE1V98vJro9W60i1OdyLMhFoR7Z2Wxz45OZJAOTKhf5TPDM0i7G0DAYEbpAfPnLX+ZVr3oVsdjSbUyf/exnAbj919Vc6EtWX4IQgolYmlQmZ82N17S2ttLS0kJmXBV99E2WupnVcnY8RiYvQltc+TnRYmJODb0HgwkCbgetUzZWHQrtreK5tXCppTBJCEGLe/FHd+qNzz9VhK4tOsjXzE6oWmcim3dCi0QowHPPPVdy/I7O0uKkpRKh+kJq4xQRWs/0roUgkc7ybF+w7KhOgAceeADyUfqLui+adv8br9pEwO3gewcG6x7dWZwP2traSiiRo7MoBabV68DrV71DHVn1/m7kkHwkWZ8I9TrtCzK2s1lHdvaGepGoC5MzoTNLuxhDw2BE6ALxt3/7t3z3u9/l5z//+ZK8figU4qtf/So2m41dN+4CCvmgQ/n2TGunOKFCCBWSz/eor3dqUu94jEy+PdO1PdcCkGVuTmj/RHyaCwq19QoN5oVLLTmhAK0e56I7oZGkWmtxOP7o0aPTnNDS0Z1N5ITmN+dYphCOn0mEXthVKE5aShGqL6R6pjrynT4Gg3FSmaUNKz99doJUNsfVW8vng953332WCN3euX3a/R6nnQ0dXs6Hk6VTk2oIx1uCMgkdHR1MxFIlF35CCFZ3K5GsW0A1hQitMSfUt0AXhc06slOH4sE4oYYCRoQuEGfOnAFgaGhu4y/r5fjx46RSKS655BIGMioEYlXGT6qdZaoIhXxIPgpIQTA5Ripbeyuc06NBMmIEm7BxTc81AAhHcI5OaHxaPiio8LwQ1RWF6D6OtYTjQRUnhRdZ3GnRO1s4vnR0p9r0lmLOfa3oPqGWCPUUckJB5YUWM7VN05I7oZ3Tw/E5qd6nS8njp8axCdi3ZboIlVKWiFAt7KfSHXAzokVoHfPji+fGd3R2Ek5kSnJCAdbmRWgzFCdFynwWq8G7UCK0SUd2FovQ3mBvQ+cBGxYPI0IXgGAwaFUtL5UI7e/vB1Sx0QvnXwAKRUlDIXUlPTUnVB+PBJFWgu989Py0Y2bj6OgpIMfmts1satsEgNsVntPUpKnTkjRuh511rZ6qBG4wrk7etRQmQV6ELnY4voz7cvjMYWgHly2/ofthZLQg3HwuB5mcJJVt/JN7Ir85R9JBYHYndLoIXRrHt28ihs9lp2OKm17P4ISF4PHTY+xe31r2Pf78889z7tw5bKvUab+cEwpTROgcw/EtrW0AJTmhABvXqhZQuvCpoUXoHJzQhaiOb9aRncUiNJ1Lz6kFoGH5YEToAtDbW6j8WyoR2tfXB8CGjRs4NKIKEQo9QuPYRPkraathfVLdV8+J4nTwBKA2ubUtKonR5gjVHY6PJDOE4umyTihUXxRiOaE15ISCqpBf9HD8lGKIsbExgq4gAHvX7sUlXGCHc2OFv48/3yA71gSjO3VhUiSlBEvAESAYDGKz2bDZbBw7doxEImEdv65lHX6nn7H4GA5HlMl4ekkc3/6J0h6hms1dqiF7NbnJC0UineXps5X7g953333ghpwvh9fhZX1gfdnjugNuRiJJ1aZJh+NrKEwqDsf7A+0AdE75zG1er/qMpSOZ0sc0IHPJCY0twOz4Zh3ZeTp4uuT73pCpkDcYEbognD5d+LAttRPq3eAlmU2yuW0zrW5VDHAulKA74MZhn/7nt0RoXJ1wa23TFIqlmUyr1y4WoRnqL0zSIc5yOaFQfVGIzgmtddSdckIXORw/ZeMrLkrau2YvbQ7lMJ0LFf4+vvyxzdArVDtEk8mguiGvN1evXs2OHTvIZrMcPnzYOl4IYYWPE/STyuZIpBff8e0bj00rSgJYHXDjctjmlHIyVw70BUllqssH3da5raQ9UzHdLW5SmRwt7Z31OaFF4Xi3X43snOocX7hR5ZWkJ5WgmohPVP38i024zup4r8thtSKbT5p1ZKd2Qre0bwFMXqhBMasIFULYhBC/uhiLWS7ofFBYeic006lOoDoUD2pk59TKeI3uFWqLKJep1tGdveNRqyipWIQmcuNqvnYduXwDWoS2l1/z5i4f58PJWUNfwViagMdRVnzPxJKE43UeWn6jKS5K2rt2L50epSaK0yX8LnVsM1TIawGpRWg2qtbc3d3NpZdeClQOyUcy6iJnsfNCpZQM5J3Qqdhsgk2dPnrHlm5q0uOnxxECriojQqPRqCqSzJuklULxgNX6x+lvVyJUKqcym6vufVUcjnf58iJ0Sjh+69pOhMNFLqbeB03hhNYVjp//C8JmHNkppbRE6K1bbgWMCDUoZt2NpZQ54HcXYS3LhkYQodoJDXnUhrCne09hTaFE2aIkKDihMqg2+FrD8WfHCz1Ct3duZ7Vfhd3C6TEk2bqcIj0taaZwPDDrfPpQPF1zPigUwvGLGf7VG5+/ghPa7Vc5deOJgkPlc6twfDNUyMfTWVx2GxMJ5YClw+r9tnr1ai65RF0wTStOyrdpmkipMJ7O8V0sQvE04WRmWlGSRjnyS1eY9PjpMXatbS2bbvLQQw+RSqXouUR9vvUo1HLoNB3haQWpKtgl0vpbzUZxON7uVSJ0amHShnZv00xNiiQy2IQKr9eCz2XP9/ud3/NGM47sHI+PM5mcJOAKcMX6KwAjQg2Kai2hHwkh/kAIsVEI0an/LejKmphGEKHaCR3Kqdef6oSuaysv6LQITY8qQddfY6/Q3rEYGaEes71zOy67iy5vFzmZJUe4rrzQwWAch02wOlBeOFdbFBKMpWivsT0TKDcyk5OLGv6NJDN4nDacedf28NHD1rjOS9dcytpWpUhD+ZxKaDYnNIvbWRChiQmlRlavXj2rEzoSPwMUcnwXC/3eLeeEgnof9lU5vWu+SWVyPNU7UTEUr0ehdl6o7q/GCc16lICsNSRf7IQKt8qVnfq5Wx1wl4pQnZbRgOi58bU6j16XHSkhOc9tu5pxZKd2QS/ouICt7VsBI0INimpF6G8C7wEeAvYX/TOUoViEBoNB4vHFdUdyuRwDA6ot06mI+vDrHqGRZIZwIsOaCuH4trY2WlpayE6oDb43OFDTa58eDZGxnUcguKDjAgArJK+mJtXhhAbjrG3zYLeV3wS0CO2dpVdoKJ6m3Vu7g7AUozvDU+bGv3DuBXDAeu962jxtrG9XRSVRomQyyvn0uZrHCU2ks7gdOWLpGHZhZ3JEtWoqdkIridDB/Ht6scPx+r07dVqSZlOnj0gyw3h0cR1agOf6gyTSOa6p0KT+xz/+MQCyQwnkGZ3QvAhNO5QIzUWUiKq2OKk4JzTnasHvsuN2lLqIDrsNj7+1OZzQZKbs9KnZ0M7pfF8UNuPITl2UdEHHBSYn1FBCtSJ0N/APwAHgWeD/Ahcv0JqaHi1C/X7lAgwPDy/q658/f550Ok3X2i5OBU/hsDnYuWonUGhUX649E6gCkJ6eHqth/WCN4fgjI6eALD2tPfSf6eeNb3wjAaE2M5drsq5w/GCF9kyaTr8Lv8s+uxMaT9fcqB4K/QEnF7E4SW186nVzuRxnEmcAuHz95QCsackniPpgYkK5iTp03yxOqMOpLs7aPe1Wj9DVq1ezefNmAoEAw8PDJW2bdGHS2fApJHLRRWjfePlpSZqlbNP0+GnlUpbLBx0fH+fQoUO43W6G0+pcNJMT2uZ14rQLgiloaWmpeX58cTg+6/BNywfVtLS2NYcITWRqLkqCwkVhfB6nJmVzkvFoqulGdhY7oZvbNwOqOt70CjVUK0K/CFwEfA4lQC/K32aYwsTEBKFQCL/fz0UXqbF4ix2S16H4rl1dSCS7Vu3CZVcbwfCkOutXckIhX5ykRnozHK1t7aeCJwG1yf3zP/8zX/va1wgNKmektSVaVzh+YGJmESqEYGM+FDoToVi65kb1UCgOWkwnNJosbHxnz54l06UE8BUbVD7VKt8qdWBRw3rdoqkpquPTWRx29ffq8BYa1Xd3d2Oz2crmhXZ6O+nydhFLR8kyviROaMDjqHghs6lr6UToY6fG2LkmMC33EuDRRx8F4PJrLud87Dweh4cNrRsqPpcQgu6W+nuFFofjkw5v2TUBtLe3W8/d0CI0mam5KAlUdTwwr8VJE7EU2ZxsupxQLUK3tm/F5/Sx2r+aVDZVc+GrYflRrQjdKaX8bSnlg/l/7wB2LuTCmhXtgm7ZsoV169YBiy9CrfZMW5Rw06F4UO2ZoLITCpQ4oROJkapz3FKZHMOxM4ASoQcPHlR35AWtx117w/pMNsfQZKJieybNbG2apJTKCa2zMAkKxUKLQbH7Ujwpae/avUB5EapbNDVFn9B0DmFXleTFc+NXr1aJrxWLk/Ih+Yx9gMnFdkIn4hVD8VBwSKsZITufpLP5fNALyueDPvLIIwDsvFadsrd1VG7PpNG9QkumJtURjk8ILx0V+vJ2dnZaTmhDt2hKZqwoQy34FiAcP9eRnc888wyRSGTe1lMtxU4omDZNhgLVitBnhBDX6G+EEFcDDy/MkpobLUK3bt3K2rUqF3KpnFDZrcSjblIPqlE9lB/Zqenp6YEMiLSTrExXHYbrnyitjNciNJ3PL3U4Q/SNx2sq3BgOJ8nJypXxGi1CKz13NJUlm5N1FyYBi9orNFzkvkytjAfo9qnq+GIRqnPQmsEJTaSzBRHqnS5CZytOcjiHlsQJrVSUBKoQZXXAvehO6PMDIWKpbMV80IcfVqfq1bvU77bSuM5iyk1NquY8IKUsCcdHcE/rEapZs6qrScLx6ZpHdkIhHD+vInQOIzu//vWv86IXvYg/+ZM/mbf1VMtUEbq5TYXkjQg1VCtCrwYeEUKcEUKcAR4FbhJCPC+EeG7mh64sip3QpRKh2gmNtajNsNgJHZpM0O5z4pmh3YjVKzSpHIxqQyZnx2Nk8iJ0g3cDZ8+eVes4r9aRExPE09maCjd0e6aZwvGgeoUmMzlGwsmy9wdj6jXrK0xa/HB8JFnY+J499iwEwI2brR2qstRyQv1qmhKA3SbUlJYmyQmVorITOpsIxXluUUWolJK+8XjFfFDN5i7fok9NevxU5XzQdDrNE088AYBjjXo/be+onA+qqXd0ZywdIyuzkAY7dsJZV8Wc0HVruiAFSAinwmRyjXPx9MILL/DQQw8BEE1m68oJ9eqc0Hn8PNY7sjObzfLRj34UoGQIxGKQyWU4GzqLQFj5oMYJNWiq/WS9fEFXsYwoFqFerxJOS+WEjthGIDulPVOocqN6jTU1KWoj26J6hRa7qZUo7hEqxwuOZGhAhecSObWJ9U3E6arySl5PS5rNCd1YVBSyuszPF8y386mrMMmqjl/kcHxe/D479Cx0wVb/ViuMqvuEFjuhAH63vUmq43NIpwoLlhOhe/ao99vBgwfJZrPY7WpD11XdGTG4qCJ0PJoins7O6ISCeh8+erL6EZfzwWOnxti+uqVsxfSzzz5LPB5nx44dnEuqz2ZVTmiLm/Fokq5Vqwrh+Cqc0OJ80Pb2diKp7LSRnZrN67pBgiPrJONIM5mcpNPbGJ3/Xv3qV9Pb28vp06fnkBO6cE5ordXx//M//8ORI0eAwkXrYtEX6iMrVbGqx6HOzUaEGjRVOaFSyt6Z/i30IpsJPbJzyZ1QH4SyIQKugBX6AN0jdGYRqp1QJlXlYrWjO0+PhskI9bOGz4St26PDyvGKpJVYqqVCvjAtqXTznxp2n60yWQuWenJCWxa5Ol5KSaQoD+1UVIWyLlt3mXVMh6cDgQAvnB8tVJD7XI6mcELj6Sw5oUSo3+4nFovhdrtpaWkBlIDZtGkTiUSCEydOWI/TTmhc9i+qCO3LO/KVGtVrNnX6GJpMkJjHiuiZyGRz7D8zXrE/qM4Hvf766zk+dhyYuTJe0x1wk5Pgb+uoyQktDsW3trUD06clabauV4nOImUvfewSE4lEOHnyJJlMhocffsTqE1orPme+MGke3wv1jOzM5XL85V/+ZeE5ii5aF4PioiSNEaEGjZkdP8+UK0w6d662Nkdzpa+vz5oRfWHXhSVNlmealqTRTmhmXIW2B6psWH/4/GkQGda1rOPE4YJw0EVO4wkllmqpkB8Ixun0uyxXAeDt33072//vdiKpQoL9hg4vQlTuFaoFSz05oXaboMW9eKM7k5kc6aykxe0gHo8z4VJFGzdsv6FoTXb8NtUCbGC80MvV52oWJzRLRqoLFUdWbairV68uea+W6xeqBVQkM8BELLFYyy3qETp7WoiUtb3H58LBwUmiVeSDXnfddZwYV5/JmXqEanQLIJce3Ul1hUnFRUmBvAitVB2/dnU+pSSfQdMoIvTkyZPW1w8/+hhQSMmphUI4fv4+j/WM7Pz+97/Pc889p1IrWHwndGo+KBgRaihgROg8IqVc8sIkq1F9u/q++OozmckyGkmxtnXmjbStrQ2/308upE6eZyaqa1ivN7mSyniAONiFnYnEBO0+aqqQL9ee6X+O/A+nJk7xwvkXrNvcDjvrWj0VXVYdjq8nJxT0/PjCZpLL5RZsMo6uwg94HGpDzBclvWj9i0qOa3e2AzA0WXh/+d3N44Sm8yLUllSnIR2K1+i80OIKeb/LT09rDzkyjMb7F2m1hR6hs4lQ7cjX0w+3Hh4/rQRFucp4KaUlQvdetZfh6PCs7Zk0WoTafG11h+O9La1A5Qu/jo4OAHL5PqSNUiFf7Lw//sTjAPVVxy9AOL7WkZ1SSv7iL/4CgD/90z/F5XIRj8cXdYBKORGqo3OmV6jBiNB5ZGJignA4TCAQIOFIcDCuhNjQ0NCijfIbHh4mk8ng36BcsmIRen5SWQ5r22bOJxJClPQKPVPF1CQpJf1hlYpQLEIvueQSkNBmbwNgVVuipg16MBhnfXvBuZ1MTlphwf7JUhGycYY2TXrOeD1OKGgRqoTs0NAQGzduxG6309rayvr169m5cydXXHEFN910E3feeSdveMMbePvb384HP/hBXnjhhVmevZRIXuy2uB28cPgF6AZkaW4vYOXPjcRGrNt8LntTVMcn0znSUjnZuhl6JRE6tThJO3ljyd5F+1z1T8Ro9zlnnZyzcZEb1j92apwLVvnLjrQ9e/Ysg4ODdHR0YOtSp/pq2jMBdLfkn8/TWnc43tOiPvOVnFBLhEZzpY9dYopF6HPPPoPM1heOX4iJSbWO7Lz//vvZv38/q1ev5u1vfztdXcoxX0w3tHhaksbv8tPt6za9Qg1VFyYZqqA4FP9b3/st7j1xL/5tfqInowSDQeuku5DoynjPOg9RolbYA1Q+KMDaCnPji+np6eHISZXIXs3UpJFIknhuAOzQ4+uhv78fj8fDddddx/PPP49f+hlnnPaWqFXxPhtSSgaCcV58Ybd1W2+wkII8VYRu6vTx0LERyhGKpXE5bDN2BZgJFY5X4u6//uu/GBxUKQrhcJhwODxjysVjjz1mOVLVoJ3QFreD7x97BOzQnm2nxdVSctxq/2oIwniiIA78Lod1sdGoZHOSVDaHzKqrnHRYiXsdLtTM1Cv0wTMPkpADxNNZfK6FP431TcxeGQ+qoMfrtM86QnY+yOYkT54e586968ver/NBr7vuOk4WDZGohlUBJRzTrhYVLs9BJBUhlU1Zgy/KURyOd3jVpLRKhUn6fCij6v3eiCI0EY+THu2lxXNtzc9jswncDpuVE/qGN7yBWCzG3XffXfMces1oJMmlG9qqOrbYBf3gBz+Iz+ejq6uLc+fOMTo6aqVdLTTlnFBQIfmR2AhngmdYHyj/HjYsf4wTOo8UFyU9NfgUAIFt6kS8WCF5XRlv61R/Wt3SB2Yf2VlMT0+P5YSOxGZf+9mxGGmbEmLuiLpS37Vrl3Wic6XURuTzhumfiJPLze5gheJpYqlsiRNanENUToSeDyfLtkQJ1jktSRPwOC0R+tWvfhWAb3zjGwSDQfr7+zl8+DBPPvkkDz74IN/73vf4yle+wuc//3mcTiePPfYY4+PVTZuBQhV+i8fBM+eeAeAC/wXTjlvXpnKOQ5mQdZvP3fhOqC7aSWTVvPhUSLnUU53QHTt24HK5OHXqFOFwodDNalhvG1i04qTZeoRqhBCzDk6YLw6fmySczHBNhSb19eaDgipwa3E7SNjzFz5V5oUWh+PtnnyRWQUR6vV6cbrckFDngkYToWvWqMKp5ODRuvqEgopMxFNZzp07x9e//nW+973v1e1C1jqy86c//SkPP/wwnZ2dvPvd7wZYEie0XGESmLxQg8KI0HlEO6Frtq6xQqSeNUpALZYI1U5oyqc29hInNDT7yE7Nxo0brYKiYKK8u1iM6hGq3MHkOeXE7d69m/Xr1RWuLabeag7nJKlsjvMV+nmW/CxleoTq0A6UEaH5sYn9ZXJOQ/F03aF4KITjjx49yjPPPENrayuvfOUraWtrY8OGDezatYt9+/Zx8803c+edd/LGN76Rd77znbz4xS8ml8vxwAMPVP1aVk6o28nJiHKw9KSkYta3q99tQiRIp5UY8zdBdbwWofGsEiyxvGs4VYQ6nU52794NUJLSoEVoepHaNEkpGZiIz1oZr9nUNfsI2fngsVP5fNCt5YuSSirjx6uvjNd0B9yE0jbVai7/48wWki8Ox+NpocXtwOWovM0E2tobrmG9FqFveMMbAEgOHqurRRMUulU8/vjj1m31VqfXOrJTV8S///3vJxBQZsiqVaoYbLFEaCgRYiw+hsfhYW3L2pL7jAg1gBGh84oWoZ6egsizd6jw76I6oQIiDqUgi0XouVACn8teVXuPnp4etTlkbSRzUaKp6IzHnx6NWO2ZRo+rk+zFF19sdQjIBJWwkragWmcVxUm6R2jxyM7ZnFAon48XjKfqLkoC5YRGkhnLBb3pDTcRl7OnFbz85arF7j333FP1a0WSSli1eByM2tXv8sYdN047bk1LfpanD8tp9TVBn1AdnoxllBMaHlEu51QRCuVD8gUROkAotvAidCScJJnJVeWEwuzTu+aLw+fCrG31lO12EQ6HOXDgAA6HgyuvvJJjY8eA6nqEarpb3IxGUjVNTSoOx0uXnw7/zBd+7e0dDSVC4/E4/f392G60cXz3cRCQOne0rpxQUBXy8XSGxx57zLptZGT2i/py1DKy85FHHuEnP/kJra2tvPe977VuX2wntDgfVAjBZz/7WTZt2kRfX58RoQbAiNB5RYvQbEfBicq2qK8Xq01TX18fBCBLljX+NficBfdmeFI1qq8mH8mamhRXJ9/ZeoUeOd+LFClW+1dz4qByEopFaGJU7TQpmS8qqkKEDpRpVF+3CI2l62pUr2n1OAjF00qEroEfrP8BV33hqlk3Ti1C77333qpFiS5MSoaDpLuUyLp5183Tjis3P97vcpDM5MhkG7fiNJHOIckSz0QQCCaGVFV0ORFarjhpa/tW7MJOVowwEglPe8x8o3uE1iJC4+ksI5GFzc09MxZly6ry7uwTTzxBLpfj8ssvJ+fI8eTAkwiENfa1GsrNj5/NCbXC8UlIO3wV80E1q7oKfUiDyWDVa1soTp06BQLkjZIfnvsh9k0O0mP95BL1Ods+l5pgNi8itIaRndoFfd/73kd7e7t1uxahi9Ur9PREaVHSF7/4Rfr6+vjJT35iRKgBMCJ0XtEiNOwubIwJtxJfixqOb1dfF7ugAOdC8Vl7hGp0LqeIKsF6bpbipKNFjbB1ZXyxCA2fU7+TQsP62V3EwWAct8NGV1F1bfEJayA8UNLeo9Pvwu8qXxQSiqfralSvCXgcRAaOc+zYMXxX+8iR48T4Cd7ynbfM2GJkz549bNiwgaGhIQ4cOFDVa4XzTubBk0+CH+wpuzXurpji0Z16U7HawixSs/R6SKSz5PK5Hu2edkZH1NqnFiZB+V6hTruTja1bQEh+fvrgtMfMN/qCqZrCJCikhZxd4OKkM6NRtq7yl72vOB/0x6d+TDqX5pqea+jylQ/dl6M74GZ06vz4WXJCrYuyBKTs3oqN6jWri+bHN0KLphMnTkAHSIe6YAxcvgqQHH7u6bqez+u0E4kn2b9/v3VbvQKwWid0//793HPPPfj9fn7v936v5L7FdkKtoqT2C8hkMhw6dAhQnRuMCDWAEaHzRnGP0KFsQXBOChVyXNRwfLv6urgoCWB4MlmzCM3lw+izOaFnQ+pks6llE4ODg3g8HrZu3Up3dzd2u53IkBIdI7FhVgfcVeXMDQRVj9Bi51afsJw2J5lchvPRwrQgIQQbO8vn44Xicy9Mih3+GQCOvcoddtldfO/Y9/jkLz5Z8XFCiBI3tBoiiQwOm+CR4z8HoDPTWda9Lje6U/czjCUbXISKggidOrKzmOJeocVO8u7unQB86clHOTQ4uaDrtXKTa3BCYWHbNE0m0oxFU2zuKi9Ci/NBf3j8hwDcsf2Oml6jO+BmMpGhs2tV9eH4osKkmPDQMYsT2tHRWOH4EydOQNHbUGxRF3X79z9Z1/N5XXZGzp4kGi2kM9XrhI7k8+hna9GkXdD3vOc9Vg4oqPZ2P7f/HNYsgQjtuIATJ06QTKqf4ezZs6ZXqAEwInTeGBsbIxKJ0NrayolQocVHLBcD9+KI0Gw2q1oH5TtBFVcjZnPSCsdXQ3t7O36/HxlSYubkWOXG4LFUhomUqspvSaqK2Isuugi73Y7NZlNN+/NFTkORITZ2+qqaKDMQTJRs/KFEiInEBF6Hl93dqmClXEh+6uafzGSJpbJzKkzyu2xED/8M1sKkfZLV/tV863XfAuDPfvJn3H/y/oqPveMOtflXmxeqZ1U/Pajcly3eLWWPKxeO105oI1fIx4uc0A5vYW58OSd07dq1rFq1yupCoNF5oXb3EO//+jMLOiazbzzGqhZX1a2gevLTuxZShPaOqufeUkaEZrNZHn30UQCuvfZa7jmh3nevuPAVNb2GDvv62zqqD8cnCuH4GN7mFKFFb8Nw6xgISgqLasHnsnP+ZGmf4Lk4obON7Hzuuee4++678Xg8fOADH7Bul1Lylu+8hbtDd8ONiyhCg/nK+I6tJXndZ8+eNb1CDYARofOGdkE3b99Mb7AXh81REIGtiyNCdaN6z1olNIvD8WORJJmcrKo9EygHr6enxxKPJ8cri9Cz4zEyNlUZL8eVW3XxxRdb969bt65EhPa0e6oqTBqYiLO+bXo+6Jb2LWxsUzmrlURosWtmzY2fZUOcid5DT5MNj+K/WlWZ/squX+GVO1/JR276CBLJr33710p6mBZz2223YbfbeeSRRwiFQmWPKSaSUM2xrcr4Cnl8xSJUuyt+VzM4oTlyQjlDAUeAdDpNIBBQVdhTEEKULU7SBTaXbo5xbDjC3953dMHW2z8RZ0OVoXgoTO9ayHD8mTH1+ysXjj906BCTk5Ns3ryZoCtI32Qfa/xruHzd5TW9hm4F5Al01BWOj9s8dM5SmNSQIrTICc3YErBaidB6Cs28Tgfj+ZSRK664ApiDE1rFyM6/+qu/AuAd73iHNbEP4FOPfIq7j96tvgksXk5osRM6VYSCqZA3GBE6b2gR2rWjC4lke+d2tnVuU3e2LY4I1U6Ro1sJkWInVDeqr6Y9k6a4TVNfqPL8+LNjMdJChesjveoB00RoCtzCTTwTp7tVci6UmLF4JpHOMhpJlq2M39K+hZ6AShco16YpmclZoSvAqqCeS07ow/epE7jtEuU0vu7i1wHwf276P9yx/Q7G4mO89puvJZGZPs+8vb2d6667jkwmw09+8pNZXyuSVCL0vFAO4Yt3vLjscX6nHwcOcMLw+DCgquOhCZzQfDjeg3o/lnNBNZWKkwDSYoQ3X7OZL/ziNI+cWJiNtW8ixsYqQ/GamaZ3zQdnRpUI3VSmbVRxPqgOxb98+8urmpRUjBahDl9bzdXxLulCONyz5oQ2pAjNvxW122670MP58+fp7S1/kTkTPped0FmVB3nnnXcCcwvHz9Se6ciRI3zzm9/E5XLxoQ99yLr9oTMP8Sc//pPCgf7FcUJzMmeds7e2lzqhfX19SCmNCDUYETpfTG3PtGvVLja1bgJAtAtGR0etXo4LhW5Unw0oF2xqeyaAdVVMS9IUN6yfqTCpdyxKJi9Czx1S/08ToUBAKBfR7wuTzUlrTeXQ95WrjN/SvoWe1goitEw+XjCu58bXJ0LT6TQP3vNdWA1hR5BVvlXcuFm1TLIJG//9K//NlvYt7B/cz/vueV/Z56ilVVMkmcHrTJMMJCEHL7v8ZWWPE0IQsKvf6UB+tKrlhDawCC0uTHLl1KZaLh9UU06EbmpTn62zobN8+BUXccEqPx/85oF5b9mUzUkGg3F6anBCATZ3LbAIHYuxrs2D1zV9AlhxPmi9oXgoiFC81Y3uzMkc4ZQ6YQQ87QghZq2O7+jogBSQg2g6Sjq7OMMHypFKpejt64V8gOGdV7wTANdO5TbXE5IXqSjJkbO43W5uv/12YC7h+JlHdn7iE59ASsnb3vY2K6f/XPgcr//W68nJHO940TvUgYskQgfDg6SyKdb41+B3+UtEaDQaZWJiwohQgxGh84UWobku5e5dtOoiK2TsW+dDSln3FXC19Pf3gw0SrgQCYW3UUGhUX21hElASjh+ND1c87tBwH1Ik6PR2cuyA6kdYLEJ1w3pPVr2226UKSWYKyVs9QsuI0K3tW2sSoVqY1JsT+sADDxCcGMe2rxWA1+x6DQ5bIS+r09vJ//zq/+BxePjXp/+Vf3v636Y9Ry2tmiLJDOHIs2ADe8jOms41FY/tcKkE4OGw+vv4tRPa0OH4ghNqT6n1ziRCy4Xji0Wox2nj06+/jJFwkj+/+4Wyz1Evw5MJ0lnJxs7anNCZpnfNB2fGomzuKi+MtRN6yZWX8Iuzv8Au7Nx+we01v0an34UQkHMHrJzQmZzQyeQkEglJCLS0A5WnJWmsUcYp9XlaSjf0zJkzyA4JDvX++qULfwmAzFr1w9cjQs+fUi7oZZdfbp0H59IntJIIPXnyJF/5ylew2+388R//MQDpbJrXf+v1DEeHuWXLLfy/V/w/7MIOHghFQgtuihSH4qPRKKdOncLpdLJzpyoqNBXyBjAidN7QIzsjHrW5XrTqImujdHWrE/FC9wrt6+uDVpBCsqF1A25H4YQ1NJnAaRcl7Y5mY+PGjZYTGkyer3jc4VElPLe0bmFoaAifz8eWLVus+7UTao8rwSEcSoT2z9CmaWCGaUkzOaEbyhSFFJzQ+nJCdYN6dqtcrNfufu20Yy5fdzmf/6XPA/A7P/wda2yr5rLLLmPNmjX09fVZbUoqEUlkGAurcZ2dqfIjGTU6L3Q0pguTmssJ1Q7bTCL04osvRgjBkSNHSKVUr8SAO0CHp4NEJsFIbIS9G9t5320X8t0Dg9z97MC8rbXf6hFamxOqpytVk/tcD5XaMw0NDXHq1ClaWloY8g2RyWW4buN1dHg7an4Np91Gh89F0tFSVU5ocaN6X0DNN++sJhwPkFSfraUUocWh+D2r97CjawdO2sk449BVnwg9d1xdOO278ior5WRkZKTm/NLZRnZ+8pOfJJvN8uY3v9k69374xx/m52d/zrqWdXz1rq/itDsLHTX81DRKuB6scZ0dWzl48CBSSnbt2sW2bSpNzYhQAxgROm9oJ/S8VGJt16pdBSeyXf230Hmh/f39VmX81B6hQ6EEqwMebLbZG9Vrenp6lAMiIZ4NVgyVnclXQHaiBNNFF12EzVZ4a2kRKsPqxJuU49jEzA3rB4JxhCh1bsuF4/sm+0oeV64oJBhTwqWeZvXxeJzvfOc70A25lhA+Rxu3bLml7LG/cdlv8K4r3kUym+Sub9xVsmHbbDZe9jIVVp+tVVM4mWEscQSALZ4tMx67ukWJt/Gk2lB0OL6xndCc5YRmo2qdM4lQn8/H9u3byWQyHDlyxLq92A0FeM/N27h8Uzt//r8vWE76XCn0CK3NCdWtk8r1rJ0rM7Vn0qH4q6++mvtO3gfU3pqpmO4WN3GbvyQcX0lAFTeqd/lV1GC2iUmWCG2AvNDioqSLu9WFj4896oZN8PTTT9fsHvYeUb2BL718H36/H4/HQyKRIBar7X0x08jOs2fP8sUvfhGbzcaf/InK/fzO4e/wt4/+LXZh5xuv+4Y1XW21P/8DLkJIvrhHqI5iXHLJJWzatMlatxGhBiNC5wGrR6gNzkbVhlgsQtNedeJaaBFa0iO0qCgJlAittjJe09PTAzkQcTsgS3pyarI5yfn4GQBcEXWCLA7FQ0GEpsaVGByJDrOuzWtNoinHYDDO6oC7ZO50sQjd0LoBUE7o1E1xalFIKJ5GCAjUMXrvBz/4AZFIhPUvUaG0XW234rRX3lg/8/LPcNWGq+gN9fLr//PrZHMFMVhtq6ZIIkNIKnF96ZpLZzx2Q4f6PYQzyrLWOYKN7ITG01mkTRXWpEL5KTAzFCbB7HmhAA67jc+8/jIyOckffPMAudzcx2bqoQrFucnVsJC9Qmdqz6RF6HXXXzenfFBNd8BNMOvAiRPSkMwmiaXL/0zFlfFOr2rVNluLps5OdeEqErL0OZaAYif04m51DnNl1P+BSwIkEomS999sSCk5dVBFNC6+bB9CCKtvZ60h+Zka1f/N3/wN6XSa17/+9ezYsYPjY8d5691vVffd/jfcsOkG61hLhPoWXoQWj+ysJEJNr1CDEaHzwOjoKLFYjMDGAKlsip7WHgLuABtbVU5ozBEDsUhOaLv6epoTOplgTY0iVI/uJO9gDoanV8ifC8VJSnV7akgJiqkiVOdCRYeV8BiKDNHT4Z2xYf1AMF6y8QcTQULJED6nj1W+VbS4Wmj3tJPKpqxQtGZqr1A9LakWF1ijQ/HyIvU7uMD/khmPdzvcfOt132KVbxX3nbyPjz30Meu+22+/HZvNxs9//nMikUjZx2eyOWLpDBGPcjZv2H5D2eM069vV7zZpT5JMJnE5bLjsNqILlIs4HyTSWci3aEoElQU2kxMK1YlQUA7k/7lzN4+cHOPfHz4957X2T8RYHXDjcU4vAJqJDp+TFrejqqEMtaLbM5Ub2anzQdfuXcu5yDnWB9bPeiEzE92B6fPjKxUnFYfjbd4AAbcDp33mLUY7oTKm3q9LLkK1E7r6YpKZLI6M6kec26gEUi0h+VOnThEOTWDztdO5Vn1Oi0PytaBHdk7NCT137hxf+MIXAPjTP/1TYukYr/3ma5lMTnLXRXfx+9f8fsnx3b5COH6h2zSVa880VYSaXqEGI0LnAR2KX3WRusq9aNVFAHidXlb5VpETOfAvrAjNZrMMDAyUdUKllJwLxVlXQ3smUK2FfD4fclKdgE9NTO8VenYsRsamcl3HT6jNaaoIXb16NUIIa3TnUFQ1rJ+tMKlSUZLukzdTcVJxUUgwVt+0pFAoxA9+8ANYBedy53Dgp9P5olkft7FtI1+762vYhI2/+Nlf8P1j3wfUyLyrrrqKVCrFT3/607KPjSazZMUoOVcGYnDtnmtnfK3iTUU7Gz63nViycZ3QRDqLzIfjI6Pq/9lE6GzFScW8/sqNvOSiNfzNfUc5OjS32fJ9EzErv7MWhBBs6vTROxad/eAa0e2ZNneWOqHxeJynnnoKIQRDAXWuuWP7HTP2lZyN7oCbkamjOysUJxWH43H5Z23PBODxePB4PBBbeif0+KnjkJ9qetGqi4gkMjjlFryOAFFnFFprE6F6Xrx7/U7iaXUO1SK0VgGondCpOaEPPvggyWSSl73sZezevZv3/OA9PDf8HBd2Xsi/v+rfp/3tlyQcP4MIBdMrdKVjROg8oIuSfJvUZrVr1S7rPisvdIF7hQ4PD5PNZnGuVmKreGTnZDxDIp2rqTIe8mMwi3qFHh+ZLkJ7x6JWj9Czz6iTylQR6nA4lMjI64GhyBAbO3wMTyZJZqY7drmcZDCYKC1KmigUJWm001yuVygU8vmC8XRdjer/93//l2QyyZZXqNdc534xsWR1G/ptF9zGJ279BAC/efdvMhJVzsdsrZrCyTTJnCr0YhguuOCCGV+neHSn3lT8LkeDO6E5snkRGhpSwmW+nFBQ79tP3nUJrR4Hv/e1Z8q+x6qlfyJOT435oNb6FqhXaKX2TE899RTpdJo9e/bwYP+DwNxC8aByQpOZHB1dqwoV8hWKk4qd0Jy7pSoRCqW9Qpdqfnwmk+F06DTY1YWu3+UnkswgsHNR55XqoM3wxBNPVP2cWrC61+8knszw2m+8lhcuVd0banVCK43sHB5WXTF27tzJF57+Al888EW8Di/f/tVv0+punfY8iyVCY+kYQ5EhnDYn9pidkZER2tra2LhxoxVhMyLUAEaEzgvaCZWr1NW8dkJh8USo7hFaLhx/blJZGLWKUCjtFVrOCT18fhApogRcAUbPjuL3+60r3WKmTk3SLW8GyuSFjkaTpLK5io3qrbVV2aYpFEvV1aheh+KzO5SI2dZyG5OJ6h3GD13/IW7deisjsRF+957fBUpFaLkCj0gyQyKlXIP2RDtO58zrrjS6s6FzQlNZslK9GSYGleiYTYRu3boVv9/P4OCgtXlWEqGgNuu/vutSjgyF+fsfHatrnZlsjnOhBBtrrIzXbO7y0TcRn5fc1GIqtWfSofh9N+zjkb5HcNgcvOSCmdNHZkM7b4H2zlnD8cU5oWm7l84qCwGLRejA5OJM8pnK2bNnyXapz/me1aoYKZz/rF+2WkUjbFttHDlyhGAwWNVzaifUtX4nh0YP8u3D32awZRD89eWElhvZqUVopjvDe+95LwCfv/PzXLLmkrLPs1gitNg0OHRQdQPZs2cPQgg2bNiAEILBwUHS6bQRoSscI0LnAS1CY14lei7qLhKhrQURupAtmvr6+sCuiqDswm4JNCj0CK21MAlKe4WWm5p08Lwal7jOpYqPdu/eXVIZr1m/fj3kI5PDkWHWt6u1lCtO0sK00shOa23VitB47eH48+fP88ADD2DvttOX6SPgCrCj7XrCieqrY23Cxhde+QX8Tj/fOPgNvnXoW+zbt4+uri5Onz7N8ePHpz0mksiQlicA2OzZPOtrWOH4YhHqdjR0dXw8nSaTfzOMn1OCpqura8bH2Gw29uxR4kCH9mYSoQC3XbSGN161iX/52SkeO1X7hnsulCCbk3U7oRs7faQyOYbDlYcy1EPvWPn2TLooyXuJl5zM8eJNLy7rhtWCFqHe4tGdVYTjE7bZ58ZrikXoufDizDSfSrmipEg+peWq9dcB4N6hfhdPPvnkrM+XSCR49tlnEULgXnshD/X9sHBnHfmYlUZ2nj9/Hjzwdb5OMpvknVe8k7fsfUvF51msnNBKRUkATqeT9evXI6VkYGDAiNAVjhGhecbGxsjl6qvO0yJ0BHV1uxROaHFR0sa2jSXN1LUIrWVkp6a4V+hQZLqIPjWhBFNLWlXDTg3Fa9atWwdZ8As/WZmlJS/Yy7VpGswXq5Q4oaEzQAURGi4VoZ1+F36X3RKhwXi65kb13/zmN8lms2x/5XYAXrnzlXT4/JY7Ui1bO7byqds/BcB7fvAexhPjvPSlLwXKt2oKJzOkXUrsX9Jd3s0oppwT6m9wJ3QyGQIkAVcAmZV0dnbO6vjC9JD8upZ12IWd4ehw2XGpAH/2SxexudPHB79xoOawvM5ZricnFIouhuaxTVM4kWY0Mr09k5TSEqFDLYV80LmiRaizpa2mcHzC5q0rHD8cWdjelZWYWpQEEM2L0H3r9+FxeIi3xMFXXV7oM888QzqdZseu3djcPh4dKPqst9TjhKbKtmcaGh6C18BYdowr1l3BZ17+mRmfZ7Gc0Er5oBrTpsmgMSIUeN3rXsfq1at55pln6nr8mTNnoAWi2SjtnvbCBx2sqUm2DhvRaLRiVfRcmak907lQAiFgdWBuTuhYfHqLpsHoGfVFfu+YUYQCvpzamLMEcdqF1QKnmIGg2u3Kjews/tkqOaFCCNWmaSxGLifrckJ1KD59oXI+X7f7dbS4HTU5oZp37ntnSVh+plZNo5FJcr5JyMLV266e9bk7vflm9j44P6L+Pj5XYzuh4bQSKwGHGjk6WyheM7U4yW6zV3wPaPxuBx971R4GgnG+f6C2SEShUX19TqgOmffOY17omQrtmY4fP87o6Cir16zmF8O/AOaeDwoqJxTA5m2bPRyfDKovEpCye2dtVK8pFqHjsaXJCZ3aIxQKTmiHz8e1PfkCwU3ViVAdir/q6qvJiBFOTRYK6mipwwkNl5+WdCJ3AnZCq7OVb/3qt/A4Zj7HL1aLJiNCDdViRCiqV10ul6tqrvdUrB6heUPqolUXlYRMtBPq6FLO5EK5ocVO6FQROjyZoMtf2nOzWopF6GSq9Oo9FEsTyajNP3pWhVdnE6HOlBKD52PDbGj3lq2QHwwmCLgdVh6nlLJsYdJMAkQXhYQTGaSE1hpE6NmzZ3n44Ydxr3FzKnkKv9PPy7a9jIDHSSKdI52tzTGfGpZPblNFBj/96U+Jx0tF+JGxgyCAUdiza8+sz+20O/HiBQED4/n58e7GdkKjeRHqE0qkVStCaylOKubGC1dx4eoW/v3h0zVNqukfj2ETsK6tPhG6vt2LTTCvbZoqtWfS+aAXv+RizkfPs6ltE7u7d8/59dq8Tpx2gfQEZg/HJwrheJsnUFc4fqmq44+ePAqdYMNmFZbqqEeLx8GNm29UB25WInS295EWqtddew0x22Old9blhJYXoSM59Tyv2PKKaW35ylE8MWkxROiWti0cPHgQwEqnAUyvUIOFEaHAK16hHIMf/vCHsxw5nfPnzxOPx/FtVptCcSgeCptkLqA+XAslQvv6+ipOSzpXR6N6TXE4PpYdKzn59o5HrfZMQ4fUz1VJhOpeoSKiBLoqTvJZblMx/ROlPUInEhOEU2FaXC0F549SETp1U9AidCI/LWm2GdbFfO1rXwNg12vUZnTnjjvxOr0E8kUBtYbkoTQs/+GHP8wl11xCIpHgZz/7Wclxx8bzs8+HYceOHVU9d6tD5f0NBlUY39fg1fFahLql2lRna1Sv0U7KCy+8YKXOVCNChRD85g1bOTg4yROnqw/39k/EWdvqqeviDdTYy/Xt3nmtkK/UnkmH4p0Xq4utubZm0thsglUtbtLO2efHl/QJ9bTQUUdhUiQ9Odcl18Xh84fBBj3+HrxOde7RTmjA7eTFm14MgH2bqvTWKViV0E7o9ddeQ9yuvtYFT7WK0EojO6WUhHPq5Lxl1ZaqnivgCuC2u8EFI8H6ZthXgxahzoiTeDxOT09PYToWmF6hBoslE6FCCLsQ4hkhxPeXag2a2267DafTyWOPPVZzmESfjPyb1aZQ3J4JYG3LWpw2Jxl3BhyL5IR2lDqhQ6FEXZXxkHdCM0ACJOmSUNzZ8RiZfHum0OkQgUCg0OB+CtoJTQfz06MiQ/R0+Ogvs0EPBuMVK+OLN9ZWdysBV4BYOjbNQdnU5SOZyXHivLJxawnH61B8/AIlkPWseC1CI3WIUCgNy2deqp5jqvt+bESlhLgmXNbvbDY63OrkrttA+V2N3Sc0nlFixZFRv89qndDOzk42bNhALBbj1Cm1yVUjQgFec/kGOnzOmhrY903E6KkzH1Szucs3r6M7z4zFWNs6vT2TdkIHvepCZD5C8ZrugJuE3T9rOH48pm5340HYHXXlhOr3xmKSzWY5m1Dvn0vXFRr7RxIZ7DaBx2njmp5rcNgcZLuz4J45JD80NERvby+BQIC1W9eSsD2PDTu/fflvqwNqDMdXGtk5OTlJ1qMuNjd1TO9IUg4hhBWSH0+N110HMRNSSqswafKsuqgoDsVDQYTqri4mJL9yWUon9PeAw0v4+hYtLS3cdNNNSCm5//77a3qsFqGiW4mj4sp4UKFYq1J9gYqTstksg4ODlUd2TiZYW0dREqgNwufzWSH500Vtmg4NDZITYTw2D0RUZXwl90ULqsSI2m301KSxaMoqANCoaUnlZ8ZPZbYK+ecG1KZWbWHSkSNHePbZZwlsCHAsdgyvw2sVeAQ86jkm68gLhdKw/GHbYdg9vTipN5iv/HZtqtrJ0iG20XihOj6Wzs57a6D5Ip5RG5NIqJ+vWhEK00Py1YpQj9POr129iR8dGq46PD6XHqGaTZ2+eQ/HTw3Fj4+Pc/jwYVztLg6GDuKyu7h1663z9prdLW4iwlcIx1coTNIXgj5XG0BdOaEpuTA58zMxMDBAtlOJub3r9lq3R5IZ/C47Qgj8Lj/71u9TqTIbZxah+r4rr7ySe0/eCyLHRv++wt7QAhMTE1XPoa80svP8+fOg6kFZ27K2queCQl6o9EpCofkX/eej54mlY3R6Ozl1SF0sVhKhpleoYUlEqBCiB/gl4AtL8frlqDckb7Vn8ufbM00Jx0OhOInWhWnTNDQ0RDabRXSpTb1YrMVTWULxdN1OqBCipFfo4eHCZn9wWPVf7BKqvU6lUDzA2rXqJBkeKp2aBEp0aiLJDKF4mg3thY22XFGSZjYR+nx/EKhehGoX9KK71N/xFRe+Ar9LudytcwjHa4rD8uJOwdG+o9awg5zMMZbpBWDPqtnzQTVrA+p3G0wFAeWESgmJOTRpX0gS+RBiLqZcmMUQoQBvvmYLNiH44iNnZj02lckxNJmgp84eoZpNnX7GoikrtDtXyrVnevTRRwHY8pItSCQ3br6RFlfLvLwe6PnxLmxJtV1UckInU+riwudUIrSmnNA0iJxAkmI0urhCtFxREqjPub7wBLhxU2leaCV0KP6aa67hf4/+LwBb/Texxr8GAHubcrGrzcmsNLJzeHi4LhG60HmhsxUlgRGhhgJL5YR+BvhDoGIsQAjxDiHEfiHE/lqTuOtBi9B7772XbLb6zfvMmTPghogtgtvuLuvWLXSbpr6+PnCqK1uX3cW6QCGMOzRZf49QTXFx0vHRPuv24+OqPZM7qk6OM4lQl8vFqlWrkJPKnVNTk5TLVOwUDeYFabETWq4oyVpbXoT2TfaV3L6hw4sQ8HzeCa2mMElKaYnQ2Ga1ptftfp11v96Q6qmQL0aH5aVPwisKbuiZ4BkytiREYO/2vbM8S4ENHRvUurJK3PncSiw3YoV8NidJ50VoJqyEWS0idGqFfC0idG2bh1dcso6vP9k3qygcDMaREus9Wi/z2aapUnsmnQ/q2KX+7q/YPn+heFAidDyWpsunLjbH4+PTcrDT2TSJbAJy4HG3A9Vf+OlcQVtKibNj54fnaeXVUdwj1MrbRLVoanEXWt29eLPKC2UTPP3006RSqbLPpwXqZVdexr0n1Gd7nfvFBaGYF47VhuQrjewsdkLXtKyp6rmgtE3TQvQKrUaEdnR04Pf7mZycJBQKGRG6gll0ESqEuBM4L6V8aqbjpJT/IqXcJ6XcV23hQr3cf/J+PnX0U2zasYmxsTH2799f9WNPnz5tVcbv6NqB3Wafdkxxw/qFEKHF+aCb2zZjE4U/67lQflpSneF4KC1OOj0xUHjdsBKHqSF1Mp5JhEK5qUlqgy4WodoV7ZmlR6imkhPqdthZ1+phNKLWVs3EpKeffprjx4/TtaWLg+GDeByekty6uRQmFaPD8m7hhj3wb4/+GwAHhg6oA4aqL0oCWN+uir7SzjTxeBx/Pl+wESvkk5ksufzIzmQov7nW8PmeyQmtpvL9N2/YSjiZ4Vv7+2Y8rtCeaa5OaOnghLlQqT3Tww8/DAL63Opnms98UFDiJyehq6MbkpCV2UJj+jzFjeqd3gABjwOnvbrtpbNTFRuKlIrkHB9ZXBF6+MRhqzJ+R1fhcxdJZmgpmlB0/cbrEQhEjyCZTZZ0adBks1lrtGdiXYJYOkabYyd22c0q3ypswkbWnQV79cVJlUZ2Dg0NFUSovwYR6lvYNk1ahG5s2ciJEyew2+3s2lVaKyGEMG2aDMDSOKHXA78shDgDfA24VQjx30uwDotP/uKT/Nsz/8aOO9UJqJaQfEl7pu7poXhYJCc0X3hYrigJ6hvZqSl2QgfCKp0glckxnlLu0/hJFZ6rVYR2+V14nfaSCnlrWlKZHqH6RPWnf/qn3HLLLSQSiRnbNGmR63PZcTumXxxMRbugF7/2YiSSl29/OQF3wLq/IELn5oSC+jt95NqPAPDU2qfon+jnwHBehA6rWdDVMnV+vM/VuE5oPJUll5+WFM23G6rFCd25cydOp5OTJ08SjUZpdbfS7mknnolXrNou5rKN7bxoUzv/8ciZGXNmC43q5+iEdmkRGp3T80D59kzpdFqJng3KCb+g44ISITUf6F6hgfYuq0J+akh+amV8tfmgUHBCiau/x+nx6f2IF5IDAwdAwFrXWtyOgtALT3FCO7wdXLrmUqRdwobyIfmDBw8SjUbZunUrPx36KQCbvDcRT2Wx2+wlLmS1IrTSyM6zI2fBAS7pslKGqmGhG9broiR3zE0ul2Pnzp243dPbSxkRaoAlEKFSyj+RUvZIKbcAbwB+IqV802Kvo5i7LroLgPAmZfdVK0KllPT29pb0CC3HQovQmXqE6nD8XEToxo0bLfE4HFXr75+IkUEJ0lhfjNbWVjZs2DDj86xbtw7iynEYj4+Tyqbo6SjtFToYjOOwCauxvpSyJCdUSsk//MM/8NOf/pT9+/fP2isUqquMz+VyVmum8Eb1PnjtRa8tOaZlnpxQzR+95I/wn/eDH978lTeXOKEXXnhh1c8zdXSn3924Tmgik7Oc0PB59XuuRYS6XC527dqFlNLqP1hLSB6UG9o7FuMnRyqLnf6JGHabmFMEAZQD3+Z1zpMTOr0907PPPks8HqfzauUmzldrpmJ0GNjf1lGxOKl4brx0t1SdDwoFEZqNqIumvuDizo8/HlTjc3d1lrp1kUS6xAkFrFZNlfJCraKkq6/ku8e+C8D2wC3E8i3TikPy1YbCK43s7B1V+eNt9raqnkdTnBO6kOH41LCKQk0NxWt0JxXTK3RlY/qEAq+56DUIBM+Gn8Xd6mb//v0q6XsWhoeHSSQSODcokTO1PZPGKkxqU4+Z77YYxdOSpoash0IJWj0Oyx2rh+LCpPG4+r2cHY+RzvcIZVy5oLNtfuvWrQMJftQmej56no2dvpKpSQPBOGvbPNhtIv9640RSEcvxGhoasio6jxw5UpUIrSYf9Omnn2ZgYIANOzbw7MSzuOwu7txxZ8kxbocdl8NGeJ6KTGzCxq8Hfh1S8NPRn/LD4+rixxtrp7W1+pnfU0d3Wk5oA/YKjacK4fjoaBS73V7SP7Aa5lKcBPDyi9eyvs0zY7umvnHVocFRZUh5JlTP2un9cGulXHsmnQ8qdqjPy3yH4qEgQt2B9ooN64vD8TmnryYn1OPx4PF4kHkndHBy8USolJKhnLqw3rdpX8l9kWSGlinnzalN66eii5LW7FvDaGyUbR3bWO/fQTw9XYRW74SWH9k5OKnacXW5u6p6Hs1CO6FahOoIWSURanqFGmCJRaiU8qdSyjtnP3JhWR9Yz/WbrieZTbLrlUpIlpvrPRVdGW9brX6N1Tih2Wx23j/4M43sHAol6p74oikOx4fTaoM4en6YnAjiwAHh2UPxUGhY706rTU23aZrqhBaH4nVoR/cIPXLkiHXfrCI0HwqtpkBCJ9Cvu3UdEslLt72UNs90h6HVU9/ozkq84WVvgHxXsFQuBRno9l1Q03NYIjS/qVhOaAP2Ck2ks+T0mykBq1atwmar7TQ0rTgpn3PdG+yt6vEOu423XLeFR06OcWSofHP0/okYPe1zywfVbOrycXZsfsLxZScl+WHMPYbH4eHmLTfP+XWmonMR7b62qsLxaYe/6qIkTen8+IWb5DOVc+fOkenIz4ifKkITmelOqC5O2gjHThxjYqJ0zKgWpqNd6jz56l2vxu9yWFEJS4TWEI6vNLJzOKoMgVqKkmBhRWgyk6R/sh+7sNP7vPo8ViNCwVTIr1SME5pHh17FxcpRqCYkf/r0abBDyp9CICrmYrW6W2lzt4ET8M1/SL6/v7/itKShyQRr5hCKh9JwfDynTq4Hzqn2TIF0AGR1IlT3CrXHlEhSFfI+wgnVlglUTmjPDPmghw8XWsseOXKEDk8HPqePcCrMZLJUUBTC8bO7MocOHQJgfK3aXKeG4jUBj5PJeQrHA1x//fX4j/jhVP6GEVjXs62m5yjOCR0dHcXfwE5ocWES8dpC8Zq5OqEAb7hyIx6njf/4xZmy9/dNxOecD6rZlJ8Mlp1j39besWhJUZKUUonQ7er7m7fcjM85P8K5GL/bofplelurCscnbR46awjHQ6kIHV3E+fEl7ZlWF85huZwkmsqW5ISCEpE7unaAC1iHVYQEEAqFOHToEE6Xk8dCyhF9za7X4HXZrXC8VUBUQzi+0sjO8ZQ6V21omzkNaioLKUJ7Q71IJBvbNnLwOZUuY0SoYSaMCM3zKxf9CgBHskfACffffz+ZzMxi48yZM9AJUki2dmy1xr2Vo9gNnc9eoZlMprRR/ZTCpHOhBOvmmNfW0dGBBw9kIEeMiXiYo2Mqj0pMKNFeiwjNTeZHmEaGrI2+bzxGJqt6M5YtSmrbAkwXoUKIWXuFVuPKHDp0CHxwhjM4bU5+eecvlz0u4HHUPTGpHC6Xi5fc9hK4GxwDDngcNmyuTYQGXAFs0gYuODd6Dl8DV8dHkxmrMInE3EWolLIgQierF6HtPhd3vaiH7zw7wFi+BY4mkc4yEk7OuTJes7nTRyYnrU4V9aDbM20p6hF69uxZBgcHce5W7+/5bs1UTHfATdZVeX58cTg+7fBVPS1JUyxCJ5Mh0tnFyQs8dPwQdIBN2riws5CHHc1/dgKe6WlMlfJCn3zySaSU7HzxTk4HT7Pav5preq7B67KTqDMcn6swshNgMqcuuqsd2amxcsj9MDI6v+0PdTu9jf6NDA0N0dLSwubNm8sea0SoAYwItdjYtpFreq4hkU2w7sZ1BINBK7+nEsWV8ZXyQYufH5j34qShoSFyrhx4wef0FU4wQDqbYzSSnLMTKoRgY0/BDX1hqJezIWXdRfuUoKhFhCbH1aavR3eCCn8OTSbIScqO7NTiujgcf/r06Rkr5Dv9Lno6vFzQPXvl6MGDB2EX5MjxkgteQoe3fJ5iYJ7D8QB33HEHhCDzrxl4FrZs217T44UQBGyqir9/vB9/A/cJnYiHQORw4YZcfSJ0/fr1dHR0MD4+zrlz5+pyQgHedv0WUpkcX3m89HGF9kzz54QCcxrfqR9b7IQ+8sgjYAO5TTmsd1x4xxxWOTPdATdJR0vF0Z2l1fGBmnJCoVSEZolYXT0WmidOKyeziy6c9sLFqu4jO9UJhaK80E2lIlR/3XKF6pv0yzt+GbvNjs9pJ52VpLO5mkVopZGdyWSSpEOdR2sVoV6nF5/dp9pETc6vCNX5oIGsOh/t2bOnYrpNT486bw8MDJDJZIwIXaEYEVqEDsEGrlYfoNlC8iXtmSrkg2qsXqGt8ytCpxYlFRcHnQ8nkXJujeo1xSH5I+f7GImrfJ/kuSTt7e1VzTnXx0SG1BPpcDyojX8wqDaemdozaSfU5/ORy+U4ceJERREqhOCBD9zEb98wc45lJBKht7fXSsXQs+LLEXA75606XvOyl72s5Ptt26uvjNe05afUDIWGcDts2ERjOqEj0cJ8cahPhAohStzQekXo9tUBbtrRzZce6yWVKThv/VZ7pvlxQi9a14oQ8FRv/WHm06PT2zM9/PDD0AMZR4YdXTvY3lnbxUstdAfcxGw+Kyd0qhNaHI63eVromENOaI6oNbRioXnh/AsAXBAoPUfoaMfUnFAoLU567PHHrP602rQY6lDn91fvejWAVUgWS2Vrro4fqWJk5/rA+lmfZyo6j3w0Nr9FYFqE2oJKWlQKxQO43W7Wrl1LNpvl3Llz1jm+N1RdbrdheWBEaBF37Vatms56VP+1qkRo3nicVYQuUJumGdsz6Ub18yBCiyvkn+4/RUKqysxqK+MBvF4v7e3thXB8dIg2n5OAx0HfeMzaeDZUKEyanJxkYGAAt9vNzTffDOSLkwKVi5M8Tjs228xrO3LkCHhBbpXYhZ1X7XxVxWOVEzq/4m7Lli2FZs7CxvZttRUmAXR6VIue89Hz+VnXjoZ0QrWD5swokVLvIAotQp9//nnWBdZhF3aGIkMkM8lZHlnKb96wlZFwkh88P2jdNt9OaIffxe51rTx8ov4Nv1x7pscffxzy1yt3bF84FxRUr9BJfJWd0KJwvM0bqKlFE0wRoSJSMsp3IenNX0xfuvbSktvDMzihm9s2s7F1I3hh3D7OqVOnkFKqv0cbnEmewe/0c9sFtwFY3SriZUTobAMWKo3srHduvEYXM02kJqoa8lAtp4L5CNmAer/OJELB9Ao1GBFawpb2Lexbv49ELoFrt4sDBw4wMDBQ9thcLlfaI7RCo3rNQonQmdszqQ15rr0OodQJPTB4hoytVIRWy9SG9QAbO3z0TcStjUeP7CzuEbqlfYsVit+xY4f1mrNVyFfDoUOHYCNgg+s3XW+NJyxHwOOc93A85EPygKN9Le0ttTtwujhpPKHEgc9tb0gndCLvmDnSyh2qxwmFwub23HPP4bA52NCqijNqfQ/ceOEqtq9u4d9/ccbajPsmYjjtgjWBuX9uNDdsX8XTZyfq/puUa8904sQJqyhpIVozFdMdcBMVXkuETnXQgvGg+iIJNndtLZpgqghdHCdUSsm4XX1ertt+Xcl9lhNaRoQKIQpV8vm80NOnTzMyMoJ/n7pIuOPCO/A41PunOEfbEowBNWhgcrJ8dwZNpZGdxXPja62OB1gbUOtIu9JEo3Pv3KDRTuj5o6oHby0i1OoVGjS9QlcSRoROQTeu775Zber33HNP2eOGhoZIppKWEzpbTuiCOqF6WlL71KIkdSKfj3B8sRN6fPwEWTGuimFC9YvQ4YhqMdLT4aV/IsZAME6n32U5B6OxUTX2zt1Gu6fdEqEXXXSR5RzOhwg9ePAg5LMJrlx/5YzHBjwOoqnsnCudp3LXXep9596wq+zGNxtrW9WmEkwHAZQT2oDV8cVhW6hfhOr3XL0N6zVCCN52/RaeHwhZ4fL+iTgb2r2zOui1cN32VaSzkifP1BeSn9qeaWJigmA2COtULrgVIl4gVrW4ETY7gXzax0ikNJdwNKJEqVv4EMI2p8IkYYstihM6OjpqtWe65oJrSu6zckLLhOMBbtxU2i9Uh+I9e9W59tU7X20d63EqERpPZ2lzt+Gyu1R1vXP2vFAtQqeN7BweIt9uuVDtXgMLUSEvpbRE6OmnVQSrWhHa19dn9QpNZpPW3mBY/hgROgUtQse6xsBeOSR/5swZaAWc6gPd6e2c8XkXqjCppEfolMr44ckEHqetqrnps1HcK3QypzZ+V9RVdXsmzfr166c7ofmG9QMTccsFhelFSTofdL5F6KFDhywRevnay2c8VlfLzmeFPKhWTZ/6yn10vuSdZStyZ6OnU/0OolK5Gj63vSH7hAYTSoTl8tNx6hWhu3fvBtR7IpvN1i1CAX7l8h7avE6reX3/eGze8kE1V27pwGW31R2Sn9qe6fTp05YLeuvWWy3XbaHQTly7R0UJJuKlYlp/77Ype66aKWXFFItQKaIMBBe+MOnAkQPQDiIr2N5Vmk87U2ESTGla/8TjKhTvhYnWCRw2R4kzrZ3QeCqLEKKm4qSRcPmRnaeHT4MNPDmPErU1shAidCIxwWRykhZnC7HRGOvWraOra+ZG+qZC3mBE6BQu7LqQvWv2kpAJuAAeeOABUqnUtONqKUoC2BDYgEBAAAaHB2c9vlqKc0KnhuPPhRKsbfXMyxi/4nB8SpwEIHNenahrdkKT4MRJNB0lkoqwscNLPJ3lhYFQST5opaKkXbt2WbPVjxw5woZAfaFYzaFDhyC/L7xo3YtmPLbVozbXyQUIyXdtuhCb21+XE7q+XRUnZJwZYrEYPpfDajPTSEymggCkJtVnql4R2t7ezoYNG0gkEpw5c8Yq/KtHhHpddt541SbufWGI/okY/RPxecsH1fhcDi7f1F6XCC3XnunUqVNWPuhCtmbSaBHa6l0FEibTk2RyhfeXdrjd9gCtHkfNk6aKRWhGRugfn78QcSV+fuTnALSl23DYSj9z+iIz4C4vpnet2kWXtwsC8MyZZ/jZz34GO1R3jZu33FzSXcNXVJgEtY3uHIkkWdXimj6yc6y+kZ2a4jZN8yVCtQu6yq42xtlcUDAi1GBEaFl0dXT7de2Ew2FVhTqFWtozATjtTlXFKCCUC5FIzM+V/tm+sxXD8UOhxLwUJUFpOB6h8nUy5zN0dnayZk31OUm6Qt6bVZt8cZumsWiq/LSkfI/Q4nB8V1cX3d3dRKNRkhNJXHYXE4kJoqnaNq9YLMapoVPQrsKalQYOaOZ7fnwxeuPz1yFCizcV1bC+0CC7kQjnC1ji+eKfeguToDQkPxcnFOAt125GCME//fQkY9HUvPUILeaG7as4ODjJeHT6Re1MFNozFdZ06tQpyBdF37L1lnlbYyW0CPUGCvPji93QyZTKbXTa22rOBwXo7OyEjHIlc6QZCE3Oa8FMOZ7pfwaADa7pzd61E6qnj01FCGG5oam1KZ599lnIbwOv2fWakmO9M4jQ2cPx5XuEDoRUrUKtIzs1xU7ofM2P1yLUm1DncCNCDdVgRGgZtAiNb4lXDMnXUhmvKc4LrWY2/WxkMhnOBc+BC9rcbdN6Ww5NJualKAnUJuHJTHmuGirjNVqEOpJKaKmG9YXNtZITmkqlOHHiBEIIduxQQlGH5I8ePVp3SP7IkSOWC7p3zV7stvKbjiZgidD5d0IjyQxuhw2Xo/aP5dSpST63g2gDhuMj+ZzV9GQat9tNIBCo+7nKitAaGtYXs77dyx171vK1J/uA+auML+a67eqq9dGTtTlPhfZMBSf02Klj0AY2bFzQUXs3hVrp8ish5Gxpn1YhL6UkmlFrdNhaa84HhbwTCthS6r0fTU8yEZv/z1gxx0Jq6tuuzukmQiSZweu0z+joFofkcfL/t3fe4XEV9/5+Z4u2aNV7syV3Wy6AC8am30DovSSkB34ESEhCertJbsolITchPcBNJQkQMBAChHCTAAZsU2yDK7YlW7KqZat3acv5/TF7Vqu+5eyurJ33eXhYbTlnZjy753O+FbFQ/g6ObXQRyI53+1t3pobnjp+qZWck8aCjPuc03hLqbZNiOxQRWlYmw9SUCE1elAidgCW5S6jMq2RIDEH5xCK0pqYm5Mx4HaOTk5qbm9EypLVgrCse4LtXr+BDG8Y/HwlCCEqzSiHYONEWniseRvrH61ZVvX+8zmQitLq6Gq/XS3l5OQ6HfI8RcaHhxIOCzI6HGFlChzwRxYNCUP9458y2hPa7/aV8/C07owkV0eNC9+3bx9xMmVkbqSUUZLkmPeHM6JhQgFWlGbhsFl4N0yU/UXmmd469AwLybfkRxQSGS4rFRJbTiim4dae/VuigZxAvXvCAZkkPu2UnjIjQ4DJNuvg2iqqWHu7bfJhfv3KE322poW5IWhNTTPN5YmcDT73dyLO7m3l+3zEOHuuZ1iMxSoTOA82isbZ4beC3SMehJyYNSw9SOO74yVp2tg3JtQ+3ZadOLGJC9W5JXbXyOx6KCM3Ly8Nms9HR0UFPT8+ICO2qNWRMiplPZFe8JOC6Zdexb/M+rKus7H9iP7W1tZSXlwder62tBb9mCdUSWpbuT04yqGD9qBqhY5KSAM5ZFLmrcyLKSsqo7qsOlAYJtzwTjFhC3R1uKJAiNNVmITs1hfYx7vjgxKQDW0Zc8TqjROj5UYjQEONBISgxKQZWxt4hT0TxoDBehDpdJTPSEtrv8ZekibBlZzCTueM1TYtI3J42J4tTyjJ5u74zJpZQi9nE+nk5bD0cpgidoDxTTZe84C/Iil2B+rHkpdnotaWNFKz3948Prnjgs6aSGYUI9fX5ZBtNcx9/39PM6rkTdy6LhC89sWdUw4ABpxS5L1bls7Vx17j3VxanT3m8VQWrSLWk0pfdB/6iGnqB+mAcY9roBkRo6tSW0Fi07NQJeE6MjAn11wg9cfAEJpNp1G/1ZAghmDNnDlVVVdTX11OeVw4oS2gyoSyhk6C75MUyAabRpZp8Ph+1x2shFVKtqePufCfDaEtofX19IB5Uj5uMJcHJScInwi7PBCMidOCENKeM1AqVF329ZWdwjdC5GXNHZcbrjBKhUxSsn4rg8kynFoViCY2hO37QE1E8KIwWocdPHCfVJi2hsY6rC5cB74gIjSYeFEYsoQcOHCDVkkqGLYN+d/+4Qurh8Ln/mMel8x3kTWB9MoKNC3I42tZPfXvoLTzHlmfyer20uKU7dnnxcsPHOBl5aTbc1vGtO4ML1Q9bHGSnhl+Nw263Y7fb0Qbkfl1ZZuWptxsN6yFf29rHjqMdfO7CRez+5oX89ZYFkK6BG7b+5//jpc+dy78+cw7Pf/psnv3kmfztExt58KPrpjym2WTmzDlnyj/89wITidDg7HgIqus5jTt+spadPp+PAZP8R5ifP3+6qU9I8O+FUf3jdXe8r83HwoULAx6r6VC1QpMbJUInoTKvksU5ixm2DMPc0S755uZmPBnyrnZJ7pKQrS4xEaGZ8vFEllCjCU5OEl0CfOGLUJfLhcvlwtMp108XoaXZTmwWEzn+eLLjfccZ8AyQZc8iw54xvQiN0B2/99BeyAGLsFCZN/1cRrLjjbcy9kRhCU0xp2DTbGCCpvYmnCkWPD6NYYMu4kYxqIvQgegtoRkZGZSWljI4OEhNTU3UyUkAf/jh1/nfj1/Ezp07oxrbZJzpjwsNxxo6tjxTQ0MDviz577okb/qkSKPIc9kYMKeOc8cH9433Wl0RxYTC6Az5lXOstPYO80qVMQLpybcaEQKuXV1Kut3K9sMyM97R66AiL53y3FQW5LtYXJhGZXEGK0szyQnhRuSc8nMCjxdmL5zQK2Y1m7CaBf3u8LLjJ2vZ2d7ejpYqxXppZmgGkLGkmFNwmV1gkq1+o8Xj83C086isANMVmiteJ1iEqlqhyYcSoZMghBjpIb4MXnjhhUBG+6ikpBDjQcF4ETpVy85YEFwr1NfqIzc3NyIhMVGt0Petm8NnLlgUEPRTlWfSmTt3LjabjcbGRnKsMku0oSd0ETowMEDNQA0IedNhs0x/0bFZ5AUlVtnxkcaEAvKiAjR2NJKquwBnWOvOYZ//LsYAdzwYmyEP8Oyzz+J2u/nVr34V9dgmYkG+i/w0G69Wh+YCnbQ8k78s8cKchbEY5oTkpdnoFSP943VLaLA73mx3RRQTCqNFaHGWRnZqCo/vmLhjXThomsaTbzWyYX4ORRnSOvfaEVlcPo/orPHBTQKuWnLVpAYJh9UcsISGmh0/WcvO4G5JkbTs1Mnx13w93nc84mPo1HfV49W8uHwu8EQuQkElJyUbSoROgV643rLCQv9Av6wFx+ikpCU5oVsigkVoc3Nz1OMb5Y6fIDHJaILd8XSEbwXVmah154YFuXzsnBHXUrAI9fl8o8oz6ZjN5kCmvKddisJwLKGHDh1CK5AWhdXFq0P6jBAiZq07o4kJBchKkZvhWPcxnP7jhFMr9B97j/Hcnuj35WRomoZb84tQAyyhYKwIbWpqCnwvH330UUPbGeoIIdi4IJet1a34Qui6NWl5Jl2EZsdXhHpS0kYsof6Y0FF94+2uiGJCYbQI7XV3ccWqYv65v4WuKLPkdxztoK69n2tOHbEa7jsuG25UuKK7eV9TvCbQKGAiV7yOM8USiAktSB1xxx8/MbkAnKxlZ3Df+EhaduroZd30JKdo0MvpWXrl744SoYpQUSJ0Ck4pPIV5WfPw2D0wZ8QlP6pQfRiW0GxHNjaTDezQ0BpZYfVg6hsm7xsfC0pLS2EfcBTYNRKTFy4TidCxBJKSMitoaGigv7+f/Px8WU8wCN0y2t0g3bzhiNBw40F10uyWmGXHT9YmMBRyHNKycaL/BKn+sjDhZMh/+5n9fH7TbroGYlMap8/dh4YX4TWB1xgRGpwhH60I3bFjR+BxT08PTz75ZNTjm4gN83No6xvmYEvPtO+dqDxTVU0VZIDQRFy+9zp5aTbMzoxx/eOD3fEmhyuiOqEwWoR2DnZy7WmlDHt9PLMnuuYeT7zViMNq5qLlI1bD2v5aAFYUhC6WJsJmsfGzi3/GlzZ+ifWl6yd9nyPFzIBbhlCkpqSSlpIGFujz9E1aM3qylp2NxxrBKf/99e98JBSlyx+/ruGuiI+ho8eDDh2TY1YiVBEqSoROgRCC65aOuORHidAwa4TqxytxyZIaTb3Rd0062noULJBlyyLNFnm9xVApKyuDY8DvgEZjLKEtfS0TBqAHW0IncsXr6M81VzdjMVlo7W9l0BNaI4Dg8kyhZMbrSBEam8Qk1yQdWkIh3yVFXcdgB05/ke1QM+Tr22W/7t4hD3967WjEY5gKvbi5aViOLdrEJDC2Vuj27duBkTJiv/vd76Ie30Rs9MeFhtI96Wjb+PJMexr2gIA8ax5Wc/QteUMlz2VHmK3YkVbZ4z3SihfsjjfZXRElJsFoEdox0MHyknQWFbh4fEfkN+yDbi/P7Gri3ZUFo5L+2szS+rdx4caIj61zy2m3cPe77sYkJr+cSnf8yHcxlLjQyVp2HmnxF4X3OaatazwVepe1QfPghF0Bw0EXof2N/TidTubNC712rRKhyY0SodMQyJKvFFRVV1FVVcXhusOQCWZhZkF2eCVSyrPKATjhPhFV5rLb7aZlWAZuz8uOfbFq8Best48UrI9KhHrB5rPh8XkmzGYOdEvKLJ/QFa8TKFh/4GCgfWdjd2hxZHve2QN5IBCsLFgZ8vhdNuMtoe19wwx7faQ7IreEFmfIi0qXpytsS6heQH1eXiq/21LLoNv4WNIOf994MSh/doy0hB44cCBwg3e0MzIRvX37diiGtZ9di81p44UXXuDoUeMFeXGmg3m5qSGJ0JrW8eWZqtqrAKjIiH0ceDC6W9hlla0iT/TKeMbR7vg0sgxwx3cOdSKE4NrTStlZ18mRE71Tf3gSXjxwnO5BD9ecNuKKb+tvw21zwzBsqNwQ0XHDxTmmbm9IInSSlp21rbVA5C07dYysFaqLUD1My2QKXVroBesbGhrw+XyqVmiSoUToNKwpXsOcjDloLg1KZamm6o5qEDDHNSdsS0RFtrxweJweuroid4M0NzcHXPHx6JgC/oL1pSM/5pGKUN3SZHPLi9pELvmJLKFTidBIMuTfbnwbzFDuKseV4pr2/ToyJtRYEfrkW1I4n78kcmFWki1FWJ/Wh8Pq7zwToiV06+FWcl02vnPlclp7h3h8Z/ThImPRLaHagLR8GyFC09PTKSsrY2hoCPxfp0jc8ZqmSRF6CTzV8xQrPijdiX/4wx+iHuNEbFyQy+s17dOWIKpt62NuzujC+U2D0ouytCB0L4wR6CLUaZUhMXp2fFuf/L8YNiGsdjIc0VtCdevqVaeWYBIj349weXxnI/lptoD1GeCN2jfkeFsFpSWRZZeHi2OMCA2lTNN0LTuzU7LHvRYORrbuDBah4bjiARwOB3l5edKw0tKiLKFJhhKh0zDWJf/MM8/Q7JbJC8sLw6/RZ1SGfHBmfDzjwvS71ry8vIjdqXqtUNEv7/DHilBN0zjaJS1Q04lQPTGpqqoqYAkNRYQODQ1R75EtGteWrQ1r/Ea74zVN4+E36jh1TiZLCqcukD0VJZly/j67D/whCaFYQjVNY9uRNtbPy+aM+TmsKs3ggZePBLoHGUVbv7R4e3ulMDbCHQ8jN0OtNa2YhInm3maGPENhHaOxsZHjnccD/dhPVEhh8Pvf/x6fz/gyVxsX5NA/7OXt+s4p33e0rY+KoHjQnp4e+mzSRX9K2SmGj2sqMh1WLCaBw1+Jotst47BPdMu1suIg05kyZavLqcjKGulLr4vQgnQ7Zy7M44mdjSElcgXT3jfMSwePc9WpJZhNI9bEVw7I8kwZQxlhWeyiwZkykh0PobXubJ2kZaf+exlpy04dIy2huucqEhEKqlZoMqNEaAgEl2r657/+iTdL/pgsLwhfhBrVNSk4Mz4e5Zl0dEtopFZQGBGh3i65jmNFaEtfC4OeQXIcOaTZ0gLu+IliQl0uF2VlZQwPD5OmybjYUETooUOH0ArlRW1taXgiNN1upcfAbkTbj3ZQfbyX966dE9VxggtQD/VIs2Ao2fE1rX20dA+xYX4uQghuO2c+R9v6eW6vsZnyJ/wilAGNtLS0kItZT0fAJb//wEhIRk94lrPt27dDKYFfxKMDR8ldl0tNTQ2vvPKKIeMM5ox5uQgxdVzoROWZampqApnxi3IWGT6uqTCZBLkuG1ZbNnhh0DfIkGcoYAm14Iw4KQkmtoQCXHtaCY2dA7xWE55QemZ3Ex6fxtWnjm5tubNB1oAtSYms5WUkOKxmBtyRuOPHi9D2Yfk9irRlp45RIrR7qJvW/lZMXhP0Ri9CVa3Q5EKJ0BA4vfR0eXHLQFpK9Mz4MJKSdIwq05RoS6gRInSwVV5xxorQYFd8e3s7x48fJzU1NXDusejiVPRIa0d9d/20Ywhu1xlKz/hg0uwWeoc8YVtmJuPhN+pw2SxctqooquMEi9D+Hun6DqVO6FZ/POgZ86WF68LKQublpnLf5sOGdlw64RcrDBhnBQVjyjRt375d9gAHMmwy1i77Iqn2fv/73xsz0CAynFZWlGRMKUInKs9UU1MD/oTocOPRjSAvzQb20f3jOwc6AbCQSpYz8kSp7OzsCUXohcsKcdksPLEzvBuLx3c2sqQwjaVFo70LhzoPAbA4a3HEYw0XR4pl0pjQiSyhU7Xs7PLKG8y5OXOjGpNeoilaEar3jMffETUSEar/tqvkpORDidAQMAlToGYoywhkxi/JDb9biVHu+Hh3S9L54Ac/yDXXXMNtt90W8TEyMjJwOBx4OkZ3TdLRf9TGZsZPVghaF6FDJ6QLNhRL6J59e0ZEaBjlmUCKUE0LrwbnZHT1u3l2dzNXnVqMMyXypCQIuqg4oadTXhFCGeO2I20UptsDYsdsEtx69jz2NnbzagjJM6HSqltCDSpUr2OYCPV/Nb/3ru9hNVmpNldDJjz22GP09kaWGDMVGxfk8lZd56RxuxOVZzpw+EBCyjPpBGqFBhWs7xzqBMAkIi/PBH5LqD+KomOgI3AD5Egxc+mKIp7b0xyotTkdh0/0sqtelnkaS7NH3vyfVhZ6RYxoke74ibPjJxKhk7XsBOgXcvHnF0TWslPHqJjQ4Had+fn5EX23VYZ88qJEaIhcuyxIhPotEZGI0ECf+XRoOhZ5mab6hnppmYVADE08WLx4MY8//jjLl0fes1oIMWWt0FDLM+nor3XWdQKhidA3Dr8BVsi15JLtCC/AP83futOI5KQn32pgyOPjveuic8VDkCU0FTra23BYzdPGhGqaxmuH2zhjfs4okX/1aSXkp9m4b/PhqMel0+63mBlVqF5Hd8cfPHiQ0jT5/QpHhGqaxva3/O54ZPjNDZU34NN8lFxVQl9fH5s2bTJsvDpnLsjF49N4o2biXvcTlWfaVbcLgBxTTlzLM+nkuWwMBbfu7G+j1y2/yIL0iAvVg1+EekF4BF7NS597pFnAtatL6Rv28o+9od24P7mzEZOAK08pHvX88b7jDJoHYRDWLgovDCcanClm+t3egLAOiNBJBOBkLTv7+vrwOuR3uiI3OuNDtiNbttl0wPG2yLsmRZOUpKNEaPKiRGiIbCzbKDtdZCFrc5oiq83psDpIN6WDGWpP1EY8nsMnDoMZclJycFiNia2LJ6GK0KnKM+kEaoUelBaOUETovnbZMWVFbvg/mnprzWhFqExIqmdlaQaVxdGVWwHItGciNAE2OHbiGKk287TZ8YdaemnrGw644nVsFjM3n1nBluo2djd0Rj02gHZ/drzRltC0tDTmzJnD0NAQDrf8LoQjQuvq6miztYFVhtjkOnP55OmfBKCjogOssXHJr56bRYrFNKm1eaLyTAdPHARkZY5EkJc2un98+0A7fR4pFr1aWvSWUEAMypuhYJf8mrlZlGU7QnLJ+3yyTefGBbnkp9tHvaZ3SuIELFwYv25TjhQzmgZDHploM50lNKSWnWmRt+wEMJvMpJnkNaypM3KDSLRJSaBEaDKjRGiImE1mrll6TeDvSKygOvl2eQGOpsd1fa+Me4ynFdRIphSh/vpwFZkVU2bG6+gi9MjuI5iEiZa+Foa9kxdfHh4ephkpWM+cf2bYYx+xhEaXIf9WfScHW3oMsYKCtDCnCmk1q2+r97cKnNoSuu2wFEBnzBvfeeWm0+eQZrcYZg3t9NcJNTomFEZc8p5WKbrD+W4Fu+LPmnMWAOtK1rGuZB39Wj/W06xs3rxZtss0ELvVzNryrEnjQo9OUJ6pvl9+7xfnxS+eMZi8NBs4RndNGtT8gZymzIhrhMKICPX1S6EWLEJNJsE1p5ay5XArTZ0DUx7nzdp2GjsHJnTFv9X4FgCiTUwaYx4LnFZ5I6F/H4Nd4cdbx1shQ2nZGU3feJ3MlEwAWnoiTwCqbq+WDzpjIEJVrdBZjxKhYRDIkgfWlK+J+Dh6hvyxgchiQt1uN+0+6cJblB/fDFmjKC4uDssdP5UILSoqIi0tjfbWdgqcsv5eU8/kd/ZVVVWBnvHr5qwLe+xGWUIffr2O1BQzl68qnv7NIZJmHrFsOFOmt4RuO9JGaZaDsmznuNfS7FY+sH4uz+09FohPjIauoM46RlpCYcQl31UnkzbCFqH+e7mz554deP7OdXcC4DpfXvVjUTN0w/xcDhzrCYiOYGrHlGfy+Xy0aTKB5NS54cUxG4Vs3ZkeiAk92nUUTWgwDGZbesTdkgDsdrtshjFBchLAtaeVomnT1wx9YmcjzhQzF1aO76v++pHXAcj15mKxRBeDHQ66NVvPkLearWTZs8A0UvQ/mMladh5tOgo2MPlMgQS6aMh1yBCeE/0Tl4kKhYNt0jpPa+QitKCgAKvVSmtrK/39/QERGkh6UsxalAgNg7Pnnh2Iu4skM15nfq4MKG/3ThwLNh1NTU1xL1RvNEVFRdAvEyzaBtoClkuf5guI0HxbPrW1tZjNZubPnzwIXwgRsIZmmaU1ZSqX/L59+wJJSeG069RJ87f/647CEto96Obp3U1ccUoJLptxF8Msm5x/S28LqbapLaE+n8ZrR9rZMH+8FVTnIxsrsJpNPPBy9FbAbn8Ci9ExoTBiCW0+IC3cdV11IWf2b98RZAmde1bg+euXXU9+aj4dtg6YK0Wo0TVDz/QXUdcrFOjo5Znm5oyI0GPHjuHLlOdfURxdz/NIyUuzYQqyhAbiAf0tO6OJCYXJyzQBzMlxsrY8iyd2Nkz6bzvo9vL3Pc1cvLxowkS/Pcf3AFCeWh7VOMPF4R9LcHJSkUtWw2h3t4/bV5O17DzcIr0STp9z0kTNcNCL5utln8Jl0DMoO5R5gc7Iq6aYTKaAZbq+vp7yzHLsFjtV7VVs2m98PLZi5qBEaBhYTBY+ffqnybJn8e4F7474OIsLpSut19yLxxO+NS24PFM8M+ONpKioCDSweeWd/vE+6ZI61nuMYe8wuc5cmmqb0DSNBQsWkJIy9cVNF6H2YRkDNpUI3frOVnCAU3MGLgThYERi0lNvNTLo9nGTQa54Hd2y0dbfJi2hU2QT72/upmvAPS4eNJi8NBvXrS7l8R0NHO8ejGps3cOd8kEMLKH6xa96bzXptnT63H2BNqFToWkar9e+DnYoSS0ZqV4B2Cw2Prb6YwA4z3Vy9OhRXnrpJUPHvbwkg3S7hS1Vo13yenmmitwRC/WRI0cCNUITUZ4JZGKSyWrD4pHfx6pW2UKUITA5osuOh6lFKEhr6OETfexqmLjb3L/eaaFnyMM1p42voalpGrV9tQCsKIiviB/rjgcoSpO/PZpTo719tAicrmVnuinyphbB6A0uerw9EX2+ur0aDQ06YEHFApzO8R6VUAl2yTutTr7/ru8D8NGnPsqhtkMRH1cxs1EiNEy+evZXaf9ie1QWSL1/PBn+GJ8wCS7PlIgyLUag1wq1DMg7fd0lH64rXkcXoVqXtJBMJULfqJNt+xY4F0RkTYjWHa9pGg+9UU9lcTorSqN3qQVTkCYtGx3DHaSmWKasE/raEX990Hm5k74H4Naz5uHx+fjtltqIx6VpGr1uv3CIgSU0uIe8Hu4Siku+pqaGnix5AT533rnjXr9tzW1YTBYGygcg3fgEJbNJcMb8HF6tbh1l3ZuwPFN1YsszwUiMol3IEIWxltBoYkJhtAjdUrdlXOerS1YWYbOYeHzHxN/vJ3Y2UphuZ/0EMc7Heo8xwAAMwKp5q6IaZ7g4U8aL0MkK1ncNuNle20FhxuikKoCGLjnvaFt26pRmybjZftGP1zt9TeGxHGz1u+LbInfF64yNC71z3Z3cUHkDPcM9XPvotfS7+6M6vmJmokRoAoi2a1JDQ0NCuiUZid4/XuuRF169M4YuQoOTkqYqz6Sjv2egRfoJpxKhVb3SerO6ZHUEI5cXFLNJcKxr6gSJydjd0MU7zd2GJSQFU5wl17Xb243TNrUldOvhNublpk54sQumPDeVi1cU8efXjkYcgjDgGcDjGwYP4DE+McnlcjF37lyGh4fJtUhRHYoInSweVKc4rZhrl14r4x7XwKZNm+ju7jZ07BsX5NLYOUBd+8hFdqLyTDtrZaefLLKwmOIXzxhMqs2Cw2rG7rfEtQ+N1H412aPLjge/CPWHJ9634z4W/mwh922/LyBG0+1WLqws5OndTQx5Roum1t4hNh86Ma5Np86+E4nJjIegmNBpCtYPe3zc9scdNHcN8Ll3j08+038n853G3MQFMuyd0NExvedgLIF40BiIUCEEv7781yzOWcze43u5/dnbDW2eoZgZKBGaAKItWF9bXwtpIBCUZcQvw9NIdEvocIeMBZ3IEhpKeSYdXYS218qL4mQi1O1205YiLYDnLz0/orELIbiospCH36jnwLHwBcnDb9ThsJrH1TA0grJsuR/66cc5RZ1Qj9fHGzXtrJ/CFR/M7efMp2fIw59fi6yiQ0dQeSaA3Nypra+RoFtDbUPSWheSCN0xPjN+LHqCknW9lQH3AI899pgBox1hoz8udEv1SFzoROWZ9rfsB6DYYfy+CYe8NBsp/tjrAENgdrjIcERXuzQrKwvehDty72B5/nLqu+u5/dnbWfizhdy//X6GvcNce1oJnf1uXjww2ov0t7eb8Pq0CV3xEFSe6TgsWBDfcIaxiUmALPkHARGqaRpfenw324608f1rV7Jh/vjvSNuQ3CPRtuzUibZ1pxFJSTpjRShAmi2NTTdswml18uCuB/n1zl9HdQ7FzEOJ0ARQ4CrApJkg1Z/tGCZVx6vABNmWbFLM0VkeEkV2djYpKSm426VlTRehE3VLCkWEzp8/H7PZzPFqeWGaTIRWV1cHMuPPKD8j4vF/68pK0h1W7vrLLoY9oSer9Ay6+duuJq5YVRyILTWS4gy/hdmuYfYOTJodv7epm94hz6jSTPdsuYdvbf7WhNaG5SUZnLUwl99uqWHQHb7bLhDfNyD/7a1W4+eux4X6OuS/Rygi9JW9r0AapFvSJy27tqFsA6cWnoo7xQ3L4Xe/+51xgwZpjU63jyrVNFF5pqM98rdiUXZiK2Lkpdkwm8aI0EHIysya0AIZDnqZpgXDC9h12y4eve5RKvMqqe+u57Znb2Phzxayv+txcl0mNu0YnSX/5FuNVBans6hg4vrNu47JQv+iVTB3bnxL2zmt0nI9lTv+x/+q4om3GvnMBYu4ZoLyUjDSsnNOjjFelKhFaJA7Xr8JjJSJRCjA8vzl3H/Z/QDc+dyd7GzeGdV5FDMLJUITgEmYSNekO+tQS/gB17q1sCzt5LSCgrQmFhYWjivTpNeFK0sv49AhuTahuONtNhvz5s0Df9jhZCJ0y64tkAYWjyWquN4cl43vXbOCd5q7+fG/Qv83/NuuJvqHvbxnXWz+7YL7x2sDPQx5fHi840XyVn99UD127njfcb74ry/yjZe+wU9f/+mEx77tnPmc6BkKu4c3MJIkFIOkJB1dhPY0yBjP6USoz+djV4cUJhtLN04aHyyECFhDTetNbNmyhaqqKqOGjRCCjQty2Xq4FZ9P3gCMLc8EcNwjb7BWlcU3nnEseS4bjBGhwm0mN8MV9bF1EdrR0YFJmLi+8np2376bv1z3F5blLaOuq46PP3cHh80387eqP9DcJf+tq1p62NPYFRBvmqbR3NPMlrot/HHXH/mvl/6Lf1T9A4BCU+G0iY5GM+KOn7h154tvV/OTf1dx3epS7jx/cittn5BhGgsKjLHk5qVG3j9e07SACDV1mKK2LusitL6+ftxr71/5fm5bfRtD3iGue/S6Ec+K4qRHidAEkWOVF/+a9vDroLUMybig+TnR9Q5ONKNqhfaNdsdbe60MDQ1RUlJCWlponamWLFkCvTJMobm3GY9vvBVw86HNABSJoqhLnLxrWQE3rinjvs2H2XE0tBInj7xRz5LCNE4py4zq3JMR3LrT0y8Vef8Elstth9tYVOAKJJpsqdsSeO1z//wcrzW8Nu4zG+bnsLI0gwdePozXF15sVuCiEYNC9Tq6CD1RJePrphOhhw8fZiBfxvVesOiCKd/7nuXvIceRg6/QB2XGJyhtXJBDR7+b/c3dE5ZnGhgYoN8uY0ZXz4ssltko8tJseMyZEBQebPbZyIoyHhRGi1AdkzBxQ+UN7Ll9T0CMdg43c8L6c1bct5Qfv/Zj7vr7d+mw3s9fjnycZb9YhvO/nRT/qJgzf3cmH/zrB/nm5m/S3N8MHlicGf9C/9MlJj23/RAbF+Tw31evmPR3ye12S2s8sKDIGBEaTf/4E/0n6BzqhEE5nmiFvV6iqa5u4vJq9150L6uLVlPTWcOH/vohfJqx5dIUiUGJ0ARRnCrdpo094VmVhoeH6TJJcbGsKDr3R6IZ2zXJp/lkzTmgt1G+EIorXmfJkiXghVRS8Wm+cUXwAXYdl5avpZmR13kN5muXLaU408FnHt01bWH4PQ1d7Gns4qbT5xhS428iApYNJ3j6Zbzq2Az5YY+P7bUdo1zxW+qlCC1ILcDj83DDYzfQ2j/6oiSE4LZz5lPb1s/z+8KLZY6HJVTfK/V7pSVlOhG6Y8eOQFJScH3QiXBYHdy6+lb5xzp48MEHI8omnoyNgXqhrROWZ6qtrQ2UZ4qmW5sR5KXZGLa4AgXrAcw+R9SZ8SBDNYBxJYtgRIzuvm03j1z7CC7TXNoGG7nr+bt4tu77dFue5p81z/FO6zsMegbJdeaytngtN1beyJfP/DI3OG6A+2FZefx/Nx0TlGgKFqEObx+/fN9qUiyTX5JbW1sD3ZKK042JC86wZcjQMBscaw3vOx1wxbfCsqXRr6nL5SIrK4uhoaEJW5naLXY23bCJLHsWTx96mh9s+UHU51QkHiVCE8TcTHn1062aodLc3BwozzQ/++S2hI4Voc09zbh9bvJT86k5KC3EYYtQIGVQXgzru8a7dY4OS5G7Yd6GaIYeIM1u5X+uX0Vdez93P/fOlO99+M067FYTV55iTFLBROQ4/MLSCUM9nQDjMuR3NXQy4PaOqg/6at2rAPzmit+wvnQ99d31vP+J94+zNry7spCK3FR+9dLhsDJVgy2hsRKheoa8u92NSZho6mmasn3rSztegmxIIYVTCk+Z9vi3r7kdszBDpSyV88ILLxg29oJ0OwvzXbxa3RYozxRsCd1ftV+WZ/KJwG9HoshLs2FyjhSsBxCagyxn9HG+E1lCx2I2mblx+Y3ce+6/yB3+AmsLLiXNcykfXf51nrjhCd7+2Nt0famLE58/wRv/7w0eue4R/vs//pu8ujw4Ef+kJJBtR+1W06h4aq8nFTQTOGBhlm/apK5jx44FRGggqSlKRrX6bR//ezkVwZnx4fxOT8VkcaE65Znl/PHqPwLwlRe+wku1LxlyXkXiUCI0QSzMlyVCOn2dYX1uNtQI1RkrQms6R5KS9Mz4UOJBdfT3ejvkD/3YuFCPx0N3qrQOXrzq4qjGHsz6eTnccmYFf3qtjs2HJm5/1zfk4am3Grl0RXHUGcRT4bA6sGpWMEO3v5zLWEvotsNtCAGnV0gR2u/uZ0fzDkzCxFlzz+LR6x4lx5HD84ef579f+e9RnzWbBLeePY89jV3juvxMRTwsoeB3yftk5ywNjcbuyT0NL9e+LD+TXhlSyaOyjDKuWnKV/NVcbXyC0sYFubxZ005Vi4xzLA8SodsPbwcg3ZeesPJMOnkuG+YxIlTzpUZdnglCE6E6V59aRoZ2Dp31H2eO6U5+ccXXuXrp1awqXEW6bXwx9+pq2eM8ESIUpDVUt4T2DXm45cEdmL0y1KhjYPp60TXNNWABs8dMakrqtO8PlQyLrFXc3N0c1ueCLaHxEqEAly66lK+c+RV8mo/3bHoPzT3hjVsxs1AiNEFUlsr4tX5reAV4Z0O3JJ2ioiJZ2sVnpne4l73H9wLhZ8brLF4sY736mqQlaawIfevAW5AJwiM4bW747Tqn4rMXLmZhvosvbNpFZ/9469vTu5roG/Zy0+mxTybTLRud/fLHeawldNvhNpYWpgdi+N5sfBOPz8PKgpWk29IpyyjjT9f8CYHgGy99gxdqRlv8rjmthLw0G78Lo3h9PCyhMBIX6vRIV/ZkLnmfz0e1W4qSCxZPHQ8ajJ6gxBp44qkn6OzsjHywY9i4IJcBt5e/vt00rjzTvmZZXqgoJfwOX0YTsIQG/XQJLS1mMaGTkeOyce7ifIa9Pi5ZUYjdap70vT09Pbz99tsAU7YAjiXOFNlG1+vT+OTDb7G/qZvSDOmSPx6CCK1qlslwTl/kXYkmIscmb0b1GqShkghLqM63zvsW51ecT0tfC+95/D0Txv8rTg6UCE0QeutOr8tLb29vyJ87UncE0sCkmShJi51bNx7oBeutw9Iy+Hrj6wDMzZgbkQjNyckhLy8PT7v8QRorQp976zkA0geNtybZrWbuvfEU2nqH+fpT+8a9/vCb9SwqcHHanKwJPm0sumWjs19aZfuDROig28uOuo4JXfFnlp0ZeO6iBRfxtbO/hk/z8d7H30tTT1PgNZvFzHmL89hZ1xGySz7YEhqrxCQYEaGiS8bcTiZCq6qqcBfJJI9Lll0S8vHPnns2K/JXgAuG5g/xl7/8JcoRj3D6vGxMAura+8eVZzrcKXuGz8uMvKKDUeSl2TA70kdZQk2mNLINiAkNR4QCvGetvKm7Yc3UN3ef+MQnaGlpYeXKlYGb1XjjSDEz4PbwX0/v498HjvNfV1SyOF+GVnS4p/8uGd2yU0ePI28bDC87PtgSGo7HaipCFaFmk5mHrnmIIlcRLx99ma/++6uGnF8RfxLr10li5mT667z5uyaF6iLa37QfsiDLlIXZNPmd/8mAXrBe9AmwE8jIzjHn0NnZSWZmJgUF4cU+LVmyhBOdUnw19IwWodtqtwFQnlIe5cgnZnlJBp/6j4X88J+HuGBZAZevkiJ7X1MXu+o7+cbly2KWkBRMtj2bo71H6RySiUV9Qe74nXUdDHt8bJg/Pilp45yN+Hw+TCZ5b/qNc77B1vqt/Lvm37xn03t44UMvBMT78pIMHt3eQHPXIMWZjmnHFFd3PNB/rB8yJhehm1/fDAVg8plYV7Iu5OPr5ZpufeZWOF1myX/sYx8zZOzpdiuryjJ5q65zXHmm5mFp1V5evNyQc0VDjisFkeJADJnQkDHDZnMmmQbHhGqaNu335V3LCtj25fMpyph8D/7xj3/kwQcfxOFw8Mgjj2A2J+Z305li5qWDJ+gf9nLr2fP4wBnlvHBc/ka4U9z09/eTmjq5m72hswHskGU19ka2MK0QjkOX3lY3BNxet2zZqkGJswSXK/ryXBC6CAVZb/vR6x/l3N+fyz1b7yEvNW/SEDXB6H00L2sepxadGvV4FdGjLKEJIt2WjtltBiscqD8Q8uf0Xs3FzsR2TTECXYR6OqWl7kCrXAfRKX8wlixZErZoW7JkCfibGI21hL7TKa2rqwpiV2fx9nPns6osk/98ai8t3bI90CNv1GOzmLj61PhYrnNTZaZ1t7+lYrAl9LXDbZgErK2QWchen5et9VsB+N4d32PlypUcPSqTt8wmM3++5s8UuYp4pe6VUdaG5SXS2rqnMbQLV7zc8brlvL1Gzn0yEfr3PX8HAaWmUhzW6UV0MO9b+T6y7FlQCq/VvcbBgwejG3QQG/1dcoKTkjRNo8ss13nt/LWGnStSbBYzWakppGgj1lqLJcuQmFC73Y7dbsftlqIsFKYSoFVVVdx+++0A/PSnPzXMbRwJekzoxcsL+dJF0nJY5PKHVwS17pyMlj5/y85UY78/pdmytmqPryfkzxzpOIJH80AXVC6qNGws4YhQgDPnnMn33/V9AD7/z89z/WPXT/jfdY9dN+q//935v4aNWREdyhKaQFI9qXRbu9nfuJ/LuCykzzT2yUSLkz0pCaRb1mw2y65JQWFafY0ypjOSC8aSJUtgk3w8VoQeQ5YgOXfxuRGNNxQsZhM/umEVl/70Fb74+G5++b7T+OtbjVyyoohMA9yVoVCYVggt0OPtxsloS+jWw22sKMkg3d+tad+JfXQNdVFoL2TXK7J81dlnn80LL7zA/PnzKXAV8Jfr/sJ5fziPe7bew8Y5G7li8RUsK0rHbBLsbezi3ZWF044p0DEpxpbQ1NRUysvLqW2vBaCue+KL2fbW7eCC9UXrwz6H0+rk5lNv5n+2/Q+cDps3bzbMxXv2ojx+/mI1C/NHLEsnTpzAlyktjkbHMkdKnsvGYc3FEL2ggcmaZUhMKEhraHNzMx0dHVNaBqdjaGiI97znPfT19XHjjTdy8803GzK+SFlRkoHFLLj3xlMw+TtLje0fX15ePunnWwelZ8Oo8kw65bnynAOmgZCszwCH2vwNOgxMSoLwRSjAZ874DCZhCnh0gtGYOMQhlGoYivigRGgCyTJl0U031cerQ/5Mm1fG7SwpTGytQCMwmUwUFhbS2Ds6g1kvNh6xCPXf0Df1NOH1eTGbzHQPdDPkGgIvXLr20qjHPhXz81x8+eKlfONv+7j1wR30DHl47zpj2uyFQmmWtGz0+XpxMmIJ7R/2sKuhk5vPHIkr1IvUZ/ZkcoxjpKSkUFdXx9lnn82///1vlixZwllzz+Lu/7ibL/zrC3zorx9i5607qciqYGG+K3xL6JAp4HKNFZWVldRurwUmtoR6vV6ardK9fdVpV0V0jjvW3sEPt/0QbbnGS2++xK233hrpcEexriKbTbedMSp2eH/VfkgHfDAnI377aCry0myYSQOOyeRCe7ohMaEwWoSWlk7cvjIUvvzlL7Nz504qKiq4//774xIKMxVfu2x8Lc2xrTunQm/ZOTfH2BJdJZnSQ6M5NXp6ekhPnz7mdFRS0pnGidCioiLMZjMtLS0MDg5it9un/YwQgrvOuIu7zrhr2ve63W5+8Ytf8IHLP2DEcBUGoNzxCSTfJi1CeoH26RgeHqbPKq2EK8tWxmxc8SS4TBPI+nfVB6QojyTYfcmSJeAB04AJj8/D8T6Zdfr828+DCaydVvKzY2eJ0/nA+rmctTCXV6tbmZ+Xytry2Cck6ZTlyiSNATGA1QR9/rIw22s7cHu10UlJ9TIp6fibcp3+9re/cfbZZ9PU1MQ555zDnj17APjchs9xxeIr6Bzs5PrHrmfIM0RlcQZ7G7tCSk5qH5Ducac1MxBzGisqKysD7VvrusZ3X3l739uy85EGlywPPSkpmIqsCtblrAMzvNL4SrRDHsWa8uyApQzg9SqZsOdyuxJenkknL82GQIZkMAhmh4t0g0qPhZucNBHPPvss9957LxaLhYcffpiMjAxDxmY0Yy2hU6G37Jyfb2x2f54z/NadsSjPBGA2mwM3Hg0NE7dejoYf//jH3HXXXVx55ZWGH1sRGUqEJpDSNPlla+prmuadkueffz5QnmleduKzZI1grAityKqIKDNeZ+7cudhsNnyd0n2pu+T/vf/fAOR5Y5eZHYzJJLjnupWUZTu449wFcbXCFKbJC5vm1LBpg/T7OzltPdyGxSRYM3dEEOuW0PZd7RQWFnLBBRfw3HPPccEFF3D8+HHOPfdcdu7ciRCC31/5e8ozy9nRvIO7nr+LFSXptPYO09I9NOV4hjxDDHoHwQtpqTlTvtcIKisrYRAsXgu9w70joQB+Nm3bBGbIGMwgwx65OLlo2UUANGgN9PSEHk8XLrvqZZhEviX2N0+hkueyoQ3lghdog8zMLMwmY/Z4tCK0qamJD3/4wwB897vf5fTTTzdkXLEgUHR+GhGqaRpDVvk9W1SyyNAxBGJMnaG37oxFeSadSFzyoXD06FG++c1vAvCZz3zG0GMrIkeJ0ARSkS3rfLZ5pr/77O/v55Of/CT49UNF5sldI1RnrAgtSS2hoaEBm81GRUX4czSbzSxatGhcctKOph0ALEoz9gd8KooyHLz8+fO4dnXkLsVICG7dmeLuC1hCtx1pY1VZJqk2aU2r76rnaNdRbJoNjsPVV1+NyWTC6XTyt7/9jcsuu4z29nbOP/98tm3bRpYji03XbyLFnMKvtv+KxuF/AtMnJwVnxqdn5cZm0kHoGfLmXpkFPdYl/+KRFwFYlhpdq8Ez5pwhHxT7W4DGiKo2WR+yPK08ZucIl7w0G8KUDz8D/gLZOdmGHTsaEer1enn/+99Pa2srF154IZ/73OcMG1csCNUd39nZCf7wWKPd8ZH0j3/nuDQUZHozDS+5FgsRqmkad955J/39/dxwww1cdNFFhh1bER1KhCYQvVZot+ie9r3f+c53qD1eC06wmW0UuIxp25ZoiouLR4lQl0cmZCxatCjiUioTZcgf6ZdVBdaVhV6OxwgSEYeW6/QLPSeYh3vpH/bQM+hmb2PXhKWZLM0W0OCaa64JvGa323n88ce59tpr6erq4sILL+Tll19mdfFqfnLRTwD472134TZVTy9CgzLjM+IgQvUwjuETsmnAWBF6YEBWYTh/wflRnWdN8Rr5oAi2vrY1qmNNReOAjJleWpC4zO6x5KXZMDnSoRMYhvxs48JNdBH6hz/8gd27d4f12bvvvpsXX3yR/Px8/vCHP8Q89CNa0m3pWLFCCjS1Tu4Raz7WHBChRmfHp6akYvbJSi2NrZN3GNPpHOyUSVLDUFlmXGa8TlmZDCcyUoQ+9dRTPP3006Snp3PvvfcadlxF9Mzsb+gsZ8WcFQAMpAxM+b79+/fzg3t/ADfKv88oOwOTmB3/dEVFRdA38rdeZDya4sdjReiwd5iOlA7Q4F0r3hXNcE8KAjFeTjAN99A35OXN2na8Po0z5gWJUL8rvu+dPrKzsznnnHNGHSclJYVHHnmEm266id7eXi666CL++c9/8rHVH+PDp3yYfnc/rfZv8frRqUuMBVtCM7Nj745PTU2loqICrVPGggaL0IGhAbrSpGi+aeNNUZ0nx5lDniUPrPDvPf+O6lhT0S5kPO3qitUxO0e45KX5W3cCFnsq2WnGdfG5+OKLSUlJ4aWXXmLVqlVcc801vPXWW9N+bsuWLQF36x//+EcKC6ev2pBohBCBup+NXZMLwKrGKjCBZdhCitn4KhtOf7mtutbphV8gHrQNli2NzpswEboltL4+vF72k9HT08Odd8pOZ9/97ncDTVIUM4PZoWROUlZWrAQf+Jw+Bt2DE75H0zRuv+N2PJd7YC6UpJXw4FUPxnmksaOoqAg8YPFIF/FAkxTk0cQZjRKhPQ3sbdmLZtKgHdauTHydxViTac9EaAIcoA120j/sYWt1GylmE6cFxYPqSUnUwRVXXIHVOj6xxGKx8OCDD3LzzTczMDDA5ZdfzrPPPsv9l93P+RXnM6y183Tjp+ganNwaGmwJzc6NvSUUxicn6Tz52pOQApYuC8vmRH8BXVsk99POYzujPtZEDA8PM5QqYwE3LN4Qk3NEQqB1J2Cyu8hONSYpCeCiiy7iyJEjfPKTn8Rut/Pkk09y2mmnccUVV7B9+/YJP9Pe3s5NN92E1+vlC1/4AhdeeKFh44k1eQ5506jXAZ2I6mMyWdPhDa+mbaikmWQP+4aO6ZOBYhkPCsa747/5zW/S0NDAmjVrAjVjFTMHJUITSKojFVOfCQTsqx/f6hHgwQcf5GXHy1AJaSlpPPe+5yjLiH3/8XihF6y3dlsRCDqqpGCJ5sdt6dKloyyh/9wrYxftnXYyMzOjGu/JgNlkxq7J0iZu9wn6hrxsO9LGaXMzA/21u4e62d2yG3xA02hX/Ljjmc088MAD3HHHHQwNDXHNNdfw9F+f5vEbHqfIuYABarni4Wtwe90Tfj7YEpqTG5/EsFEiNKhW6FNvPwVAqc+YON3zl0iXfqezk8bG6V2Z4XLgyAFZnskL83MT0/N8IvJcNqy5c0hNyyCleIlhNUJ1SkpK+MlPfsKRI0e46667cDgcPP3006xdu5ZLL72U119/PfBeTdO45ZZbqKurY926dXznO98xdCyxRk8k1OuATkTNiRrA+JadOlkp8ub0WM+xad8bq8x4HSNF6Ntvv81PfvITTCYT999/f8K6ZSkmR4nQBGMbsgGwu3Z87FN7ezsf//PHYT1YsPDUe55iRcGKeA8xpuiuEeezTl780IvU7ZE/PNG444MTk+q76nm1Wlr8Sk3xTRBKJC6TjK0d9rRyrHuQ/c3dnDFvxAr5WsNr+DQfNIHL5uKCCy6Y8ngmk4mf//znfPazn8XtdnPjjTfy9yf+zq8ufgyTlsnLdS9w2zO3TViuKWAJHYS8vPhkeE9mCX2z5U0A1uYbYxEPtPwsgTfffNOQYwaz9R0Za+occs6Y8kwAWc4UUpxpfOo3/yb7ss8ZViN0LEVFRfzoRz+ipqaGz3/+8zidTv7+97+zfv163v3ud7N161buu+8+nnzySdLT03n44YcntOjPZMoypVFBrwM6EQ2d0kKpi0WjybHLMJkTA1OXiYL4WkJDKf82GV6vl4997GN4vV7uvPNOTjttZjR6UIxGidAEk+aTbpADzePj6q7/1vX0bZQBkw9e8yDnVZwX17HFg/z8fIQQtB1uY23+WqqrqxFCRNWBJjU1ldIMf6257gZ2t0mBvzwn8X2340VGinSVDnraaO8bRtMYVR9UjwelDi699NKQi0L/4Ac/4Gtf+xper5cPfehDuFq7KRj+OlaTnd++/VvufvXucZ8LlEgagPz8BFhC/SLUp/moFzLO7PJVlxtyntOKTpOhDwXw6uuvGnLMYHYelW7+HBH7WNpwMJkEua4UajrdMq7RYEvoWAoKCrjnnnuora3lS1/6Ei6Xi//7v/9j48aNfOITnwDggQceYN68k690XVm2v66vaQC3e2JvwrFeaaHMd8TmJk5PdO0Ymr4iwf7j+wGw9dkCSURGkpGRQXp6Ov39/bS3t0d8nAceeIA33niD4uJivvWtbxk4QoWRKBGaYHIs8uJypO3IqOd/9uzPeCH9BQA+v+rzvHfFe+M+tnhgsVgCbRy3bt2Kx+OhvLwchyO62KdlC5bBALh9buq9UnictfCsqMd7sqBbNga9nQDYrSZOKcsMvB4cD3rttdeGfFwhBN/+9rf59Kc/jcfj4UPvv4n5tgrOzvk2AsFXX/gqD+95eNRngt3xsWzZGUygc5YmO2e5vW52N+/Gk+KBbrj0DGO6ZqWmpFLmKAMTvPTOS4YcM5iDJ6TVqcw580Jw8tJsHGqR9VGz4tSSNi8vj7vvvpva2lq+9rWvkZ6ejs/n4+abb+bGG2+MyxiMJtCG0zV5sfi2Qfl8cUZskmqKM+Vxuz1TV2rx+rwc7jgMwNK8pTGrPhCtS/7YsWN8+ctfBuCnP/1pSF2gFIkh7iJUCFEmhHhRCPGOEGKfEOJT8R7DTKLQIeOB6ntGMgF3NO7g09s+DWZY61nLPVfdk6DRxQc9LvSFF6ToNsLFE5ycpAkNumDd8viWZ0ok+S4p9gZ90hy4tjybFIv8uru9brbVbwMgpSWFiy++OOzj33PPPWzYsIHGxkbqHv8+Pe0r+eGFPwTgw099mFfrRqyCARE6AMWF8Skt5nQ6mTd3HvRIC2hTTxOPvf4YAK52F9nZxtW13DBXJgzt7diL1+s17LgAdb3yIrw4z5je9EaS57LR2ivLYBmZmBQKOTk5fPvb36a2tpa///3v3HfffXE9v5GEUiu0038zOSc7Nm1b5+TI4/YFlyqZgLquOoZ9w9ADyxfGzrMUrQj97Gc/S1dXF5dccsmU8e6KxJMIS6gH+KymaUuB9cDHhRDG13k4SdB7QbcMyMzIo51HOf835+Oz+nDWOHnhSy8kcnhxQY8L1UVoNPGgOsEiFIBmWLYsebZZUboU9kP+Iqzrg0oz7WrZxYBnANrgorMuwuVyhX18q9XKX/7yF3Jzc6nb8xoH//EH3ld5O59Y+wmGvcNc+ciVHGo7BEBrr//COmwmJyszuomFwViX/L+rZBmlxXZjBd05C2Rpq6GcIQ4ePGjosVt9cu1OmXOKocc1grw0W+BxvCyhY8nKyuLiiy/GYpk58bLhEkrrTl0czi+ITXJaeV45AIOWiau06ATiQWOUlKQTjQj95z//yUMPPYTD4eDnP/95Qmo1K0In7iJU07RmTdN2+h/3AO8AJfEex0xhYf5CADp8HbQPtHPBHy6gW+uGWvjTNX/ClRq+QDjZ0C2hevkVoy2hAK4eY61fM53SbBkTO2zqB0bHgwaslGG64sedo7SUhx56CCEEXVse5veP/Y0fX/RjLlt0Ge0D7Vz60KW09rdyvEf2pTdpLpwp8RMLwSL0aNdR9vbuBeCcinOm+FT4rC32JzmVMCpr2wj67FJ8bFgyc8oz6QSL0OwYx4TOZkIRoYGWncWx6fg2N1d2YfLZfQwMTF63Wr+xjFVSkk6kInRwcJA77rgDgK9//esRdd1TxJeExoQKIcqBU4Fxv9xCiFuFENuFENun6ql7srO0WH6Re829XPnIlVR1VsFxuKTnEq6+4uoEjy4+6CJUd2XGQoRWOJLrx2hOrvwRd1uG+NrFizmlNDPw2ovVsm2lqcHEZZddFtV5LrjgAr78tf8ENL712dtobmrm4Wsf5tTCU6lur+bKR64MJFWYRDp2a/x+ciorK2VHH+Dloy/TZ+6DAbh0rTHxoDorClZgxgy58Mqbrxh23IbjDWguDTxwSvkphh3XKHJdUoSaBKTbT66M9JnEdP3jBwYG8Dl9ACwsWhibMegd+FInj0uF2Jdn0olUhN59991UV1dTWVnJZz/72VgMTWEwCROhQggX8DjwaU3TxkVDa5r2gKZpazRNW2N0b9qZxMLShTAMXotXWqi6wL7Jzq9+9KtEDy1u6CJUxwh3fGFhIfbhkYzv1cUzp9tMPChI819UnHD18ixMJumS0jSNzTWbAVhfst4Q6/C3v/kNshatoa+rgxtuuAGbsPHMTc9Qll7G1vqt1PXJC4lZZGBPiV+dvmXLlgUsoY/tl/Gg1MGa1WsMPU+KOYVFadJC9cph40ToK/vksWz9Nizmmedu1i2hmc6UwP5ShI/D6sCm2cA8cceihuYGcAK+oJa8BhPcZW2q/vF6Zrypw8T8+bGrWxuJCD148CDf+973ALjvvvtOulJdyUpCRKgQwooUoH/WNO2JRIxhplBUVBS4UJqGTfBn+Pbnvx34EiYDwSI0Ly+PnJzoy9EIIZibJV1M9MHaxbO/U1Iwk11UjnQcocvXBX3wgYs/YMi5TCYT137m+6Rk5LFt2za++MUvUpxWzLM3PUtaSlrgfWZLNnZL/ERosDVcLxOV158Xk0zZs+efDcCRwSNTujPDYfsRGZ6SqWUacjyjyfNbQrOc6mIfLelmuSfr28e3qjzYIK2P1mErZlNsvj82iw2zxwxmONpydNL3vXP8HQAq0ipiKvL069+OHTu44IILuOuuu/jNb37D66+/Tk9Pz7j3a5rGHXfcwfDwMDfffDNnnnlmzMamMJZEZMcL4DfAO5qm/Sje559pZGdnI44IGATfn30sz1/Opz6VXAUDgnv5GuniOTX/VGgF3obly5OnRigEWUzGiNB/HfqXfFAPV111lWHnW7t0LtmXfwGLxcK9997LE088wYqCFWy6YRMmTDAAFlsOVnP8LGZOp5PStNENCk7NOTUm59pQLmM2fYW+kPqch8L+Y9LqVGKfmSHzuiVUxYNGT45N3ng39zSPe62quQqIXctOHbtXeo5qT9RO+HrfcB8tgy3ggZVzVsZ0LKWlpZx66qm43W7+9a9/8eMf/5hbbrmF9evXk56eTkVFBZdffjlf+cpXeOihh/jhD3/ICy+8QG5uLt///vdjOjaFsSTCx7MR+ACwRwjxtv+5r2ia9vcEjCXhmEwmincX0/h/jeCF+15NPjdCsCXUSBG6ctFKHvnKIwAseyh5MuMhSISmjo4ze/S1RwGoMFdQWFho2PmWl2RgK1nKxz7/DX5x93/ykY98hJUrV3Lhggt5b+97+fOf/oy9MjvumarLy5bTgL8fthveVfmumJxnbHLShg3RJxLVdNeAExZkL4j6WLEg2B2viI58Zz4HBg5wvP/4uNdqW2sBSBNp414zEpdw0UcfdW0Tu8ADSUntsGxpbH9PzWYz27dvp66ujj179rB3797Af++88w61tbXU1tbyzDPPjPrc//zP/xjiSVPEj7iLUE3TXgVUAFEQRUVFNDY28tGPfpSNGzcmejhxJ1gMGREPOvZYeXl55ObGJpZqppKakorZZ8Zr8dJ4YqSn+faW7WCHK065wtDzVRbLDk1L3nUj1x56m8cff5zrrruObdu2IY4JOAaOM2LTcnAqTllyCv8Y+gfYgHpY/+71MTnP4tzF2IWdwYxBNu/YzF3cFfUxW9yybNvKkthanSLFZbNgt5pi1rIzmShJL4E26HCP71hU3yFd9FnW2H5/MswZtNBCU3fThK+Pate5IXZJSTomk4ny8nLKy8u5/PKRDmdut5vq6upRwnTfvn2sW7eOD37wgzEfl8JYZl60exLymc98hieeeIJ77pndReknIyUlhZycHNra2gy1hG7YsIHMzMxRP2DJhBMnPfQEkh0a2hvotneDG+645g5Dz5XhsDI3x8nexm5++9vfsnv3bnbt2sWdd94ZsMQ60+NfImt55XLYCuQDdXDqqbFxx5uEieU5y9neup3X6l4z5Jg9Vhn7tn5RbIRztAghuPuaFSwuUN1oomVOzhyogW7f+I5FLb0t4JDW0liSZcsCDxzvHW+Nhfhlxk+H1Wpl6dKlLF26lOuvvz5h41AYg2rbOQN473vfy2OPPZbUboR169aRmprK6tXGZbEXFBTQ0tLCAw88YNgxTyb0ZIfGTmkJ/dUzsuKCq9vFonnG1xtcXpLB3qYu0tPT2bRpE3a7nd/85jds3iyz8VMz4y9Cly1bBs2ABuXu8ogK84fKuQvPBaDF0jJpvcdQ6ezvxOv0ggfWL52ZIhTg6lNLWVasRGi0zMuTPe/7Tf1omjbqtRODci/pDShihZ7M2DowcXb8gdYD8kEbLF488zp4KU5OlAhVzAj++te/UldXZ7jbPCUlBbM5fhnZM4nMlEyAQLH4p956CoDVebEpV7WiJIOGjgE6+oZZuXIlv/zlLwFZQBogPSv+N1lLlixB/EPAfXDWvLNieq7TS0+XD4rhjTfeiOpYWw9sBcDSYyHVmRrt0BQznNIsmUCnOTW6u0dbQ7s8snxKrFp26hRlSJHb6e6c8PXdTbsBKLAWkJqq9qTCGJQIVcwIUlJSkqqjUTzIcUjRd6L/BMPDwxzok5aMm868KSbnW1Ei40L3NsmL5kc+8hE+8pGPBF5Pz4y/CHU4HMwvmQ8tsGaNsfVBxzIqOemN6DonvVEtRWy6R1kZk4Gpuib1Ctl6d17+vJiOoSRTVmHo1XrHvaZpGke6jgBQWVAZ03EokgslQhWKWYpesL5jqIP/e+H/8BbIjlTXr49NHFWl3y27t3HEkvPzn/+ciy66iJLV/4HL5YzJeafjkksuwWaz8e53vzum55mTMUeGQDhh867NUR1rT+MeAAqtxlUwUMxcphKhQxZ/y86S2LTs1CnPLQegX/SPe62pp4lB3yD0w6qFq2I6DkVyoUSoQjFL0d1r3Z5ufv3sr8ECeVoeWY7YZNlmOlMoy3awt7Er8JzT6eS5555jxQe+gS2OheqD+eEPf0hLS0vM49iEEKwukqEOO47tGBfbFw7VHdUAVGQmV7vZZCXPmQcakAotJ1oCz3u9XrwOfzvj0tgmA80rkJbWYevwuNcCmfEJTkpSzD6UCFUoZillOWWAdK/9q0oWqT+34tyYnnNFSQZ7gkSozpDbiyOOLTuDsVgsZGRkxOVceuekvow+Dh8+HPFxmodk0fLKQuX6TAasZit2nx0EHGk5Eni+7lidLC/mgVxXbMvMzS+UbTh9dh8ej2fUa4HM+DYlQhXGokSoQjFLmZsr25a6LW76svsAuPyU2JarWl6SQV17P1397lHPD7i92C2z/+dmXck6+aBYFq2PlE5TJwBr5yVXu9lkxoWs3HC0daRt5oF6GcdtHbLGvNFDfpq/BJQTTrSODglQllBFrJj9VwWFIknJd/kvKqmANIpy1tzYZogv9xet39c02ho6mEBLaDwJJCcVw2tvRFYvtGeoB7fdLcszLZu55ZkUxqIXo2/sGmkuobfs1FtqxhKLyYJp0AQCDjePtuLvbpSZ8enu9KQuJagwHiVCFYpZSl6qrPtHEeCEXFsuczPmxvSceob8WJf8gNuL3Tr7RWheah4FtgJIgc37IktO2t0gL/iiU1BcVGzk8BQzmBy7FHfHeo8Fnqs5UQPEvmWnjs0jW7EePjZahB44IS2yi7JjmxylSD6UCFUoZimB/vFW+b/z5p8Xc5deVmoKJZmOUSJU0zQG3b6kcMcDrC+T1sv9XfsZHh6f5DEd2w5tAyB1KBWTKTnWTDGSId86OFIsPl4tO3WcmqxgERwSMOQZ4tjQMfDBKXNPics4FMmD+oVTKGYp2Y7RdVfPmhNbV7zOipKMURnyQx4fAPYkcMcDbCjfAIC3wMvu3bvD/vzbdW8DkGfOM3JYihlOaaYsWN/p6Qw8p1tF8xzx2Qsuk4xL1busAVS3V6OhQQcsX7o8LuNQJA9KhCoUsxSLyUKqaaSzycY5G+Ny3uUl6dS29dM9KJOTBt2yxIw9QSWa4k20yUmHWg8BMNcV29AJxcxCr9PZy0ixeL2FZnF6fMIyMq2ZABzrGQkJCCQlqcx4RQxQIlShmMWUZMkuKK4UFysLVsblnMv9caH7/EXrB93SEpoMiUkAq4tWIxBQCNve2Bb25xsGGgBYkr/E6KEpZjALChYAMGgeDDynW0XnZMW2ZadOrkOG8JzoG8mOV+WZFLFEiVCFYhajx4WuL12PxWSJyzkD7Tv9LvkB3RJqTY6fmzRbGuWucjDDK1WvhP35Nq0NgNXlqw0emWImM79A1un0OrwMDkohqltF9ULysabAJbustQ+1B57b1bQLAFuPjdLS0riMQ5E8JMdVQaFIUvKcMpbszLIz43bOHJeN4gx7IDlJd8c7kiA7XmdjuQx9qPPU0dnZGfLneoZ6GE4ZBg+sXaxqhCYTRWmywxkuaG2VbvhBqxSjC4sWxmUMxRnS7d/tHWm9u7dpLwBz0+bGPLFRkXwoEapQzGKuX3Y9i3IW8b6V74vreStLMtjbNNoSaksiEXp62enyQQm8+eabIX9OjwelHebPmx+DkSlmKlmOLPABDmhsacTn8+G1y+/OsjnL4jKGsmxZULgP2dxC0zRqemSZqBVFK+IyBkVyoUSoQjGLed/K93HwEwdZkL0gruddUZJBTWsfvUOepLSEBicnvfHGGyF/7s0jUrCm9KbgcrliMTTFDMUkTNjcsk5nVVMVDa0NYAGGID8rPy5jqMivAGDANABAa38r/Vo/DMFpC0+LyxgUyUV8gsQUCkVSsaIkA02DfY1dI9nxSSRCVxWswowZb56XLW9uCekz7QPtfO+17wGQ64ttn3DFzMTpczLEEEdOHCGvXobSWAbjd5meXySt754U2Ts+uF3nsnXxscYqkgtlCVUoFIazPKhzkp4dnyyJSQA2i42l2UtBwGt1r6Fp2pTvH3APcOXDV3K0/ygchzO0M+I0UsVMIt2UDkB9ez2HmmRohsPriNv55xXNAx9odo0hz5DKjFfEnOS5KigUiriRl2ajIN3GvqZuBoaTzx0PsLFCJid1ODqor6+f9H1en5drH7qWV+tfhW7gT/Duc94dp1EqZhLZNtlgoqm7idrWWgBcIn5hGXabHdEvk48OHzvMnuY9AJg6TMyfr2KUFcajRKhCoYgJK0oypCXUk3zueAiKCy2ZvGi9z+fjgnsv4Lna52AAnE84uf8H93PLLbfEcaSKmUK+Q8Z+Hu8/HveWnTrWYdnnt6qpirfq3wKgyFqExaKi9xTGo0SoQqGICctLMjh8opf2Xtk/PWlF6CTJSUePHmXxLYt5sfdF8MD62vUcfOUgt956qyqFk6QUpcsyTe3D7TT3NAPxa9mpY/PK5KijJ45S3V4NwNJ85YpXxAYlQhUKRUzQk5N21nUAyRUTCrA0dyl2kx2y4JWdI0XrfT4fv/jFL1h0wyKq51aDBp8s/SRbH96qioEnOXOyZWekLm9XoGVnoH5onEgVstVvTVsNx4Zl+841FWviOgZF8pBcVwWFQhE39OSk7Uc7MAlIMSfXz43ZZOaUglMAePv423g8Hg4dOsS5557LJ378CYYvkhbi75z5HX7ysZ8o66eCijxZIqnf1E+HR9686cI0XmSY5fd2V+sufMIHnbByaXxa/iqSj+S6KigUirhRkG4nL81Gz6AHu9WclCJrw9wNAAzlDPGpT32KVatW8crhVxA3CjDBFzd+ka++66sJHqViprCoeBEAQ9ahQMtOXZjGCz056p2+d+QTKjNeEUOUCFUoFDFD7yOfbJnxOmtL/K03S+CXv/wlg45B7Dfb0awaH1j5Ae7+j7sTO0DFjGJJyRIAfE4fgxbZslMXpvEi1ylr1B7zSVc8bbB48eK4jkGRPCgRqlAoYsbyYln3MNmSknSCk5OKFxZT9IUiBs2DXDj/Qn59xa+T0jqsmJys1CxwA1bwOmRViSVlS+I6hrExqNlaNg5H/GqVKpILJUIVCkXM0ONCky0pSacis4IcRw64IO3ONJqHmjmt6DQ2Xb+JFHNKooenmGEIIbAOWkee6IfCvMK4jqE0e3Ry3PwMVR9UETuS88qgUCjiwopSXYQmpyVUCMGaYplZfLD9IBWZFTx707Ok2dISPDLFTMXutQceWwYtmEzxvUzPzZk76u9TSk+J6/kVyYUSoQqFImYUptvJdaUkrQiFEZd8rjOX59//PIWu+Fq2FCcXqaQGHts99ineGRsqCoISodywdvHauI9BkTyoFggKhSJmCCG45rTSpCvPFMxta26jpbeF29fezsKchYkejmKGk2nJ5BgyKSieLTt15hTMAQ9SHbRB5SWVcR+DInlQIlShUMSUr1yS3OVditOKuf/y+xM9DMVJQq4tN/A4yxLflp0AeXl50AdkoMozKWJO8ponFAqFQqGYYQSHa+Q6cqd4Z2xwOp2Iflm1IXUglays+AthRfKgRKhCoVAoFDOEkoySwOPitOKEjCHFLSs3lKWWJeT8iuRBiVCFQqFQKGYIwdnpZVmJEYHFR4thF2zM2ZiQ8yuSByVCFQqFQqGYIcwvHKnLWZEf35adgfNqFfAkrFqyKiHnVyQPSoQqFAqFQjFDWFwy0iJzYVFiqils2LABq9XKeeedl5DzK5IHJUIVCoVCoZghlBSUwBGgERaXJaZn+7e+9S06OztZvnx5Qs6vSB5UiSaFQqFQKGYIqamp5D+fz8DAAIU/T0xjAyEETqczIedWJBdKhCoUCoVCMUMQQrD5pc0MDw+TkpKS6OEoFDFFiVCFQqFQKGYQS5YsSfQQFIq4oGJCFQqFQqFQKBRxR4lQhUKhUCgUCkXcUSJUoVAoFAqFQhF3lAhVKBQKhUKhUMQdJUIVCoVCoVAoFHFHiVCFQqFQKBQKRdxRIlShUCgUCoVCEXeUCFUoFAqFQqFQxB0lQhUKhUKhUCgUcUeJUIVCoVAoFApF3FEiVKFQKBQKhUIRd5QIVSgUCoVCoVDEHaFpWqLHMC1CiBPA0RifJhdojfE5ZjpqDdQaJPv8Qa0BqDUAtQbJPn+dSNdhrqZpeUYPZrZxUojQeCCE2K5p2ppEjyORqDVQa5Ds8we1BqDWANQaJPv8ddQ6xBbljlcoFAqFQqFQxB0lQhUKhUKhUCgUcUeJ0BEeSPQAZgBqDdQaJPv8Qa0BqDUAtQbJPn8dtQ4xRMWEKhQKhUKhUCjijrKEKhQKhUKhUCjijhKhCoVCoVAoFIq4o0SoQqFQKBQKhSLuJJUIFUKIRI8hkQghPiuEuND/OCnXIlnnraP2gCSZ5w5qH+gk89xB7QNI3nnPFJJChAohrhRC/AFYleixJAIhxIVCiOeBLwIfBNCSLCNN7QG1B0DtA7UPJGofqH2Q7HtgpmBJ9ABihRBCaJqmCSHOA74NuIEzhBBHNU3rSPDwYo7/7s4KfB04B7gbSAHWCiGsgGe2/+ioPaD2AKh9oPaBRO0DtQ+SfQ/MRGZliSZ9o/kflwNDwFLkHd/vNE3bnMDhxZwx81+radqb/sfnAL/VNG1+QgcYB9QeUHsA1D5Q+0Ci9oHaB8m+B2Yqs84dL4T4BPCEEOIuIUShpmm1mqY1a5r2AtACnCOEKEnwMGPGmPkXBf3YWP1fsiNCiIsTO8rYovaA2gOg9oHaBxK1D9Q+SPY9MJOZVSJUCHE18CHgp8BK4GtCiFOC3vJnYBFw+pjPzYrA5Anm/1UhhB7v4hFCZANHAW+Chhhz1B5QewDUPlD7QKL2gdoHyb4HZjqzSoQiN9GvNE17EfgmUAN8Un9R07TdwJvAciHE+UKIL/qfny0xCRPN/1Mg56hpWjvgAM4DEELMtn9/UHtA7QGJ2gdqH4DaB2ofqD0wo5kVGy7ojuUIcBOApmlHgWeBVCHEFUFvfxi4BfgLkDvm8yclYc7/T8A6IYRd0zRffEdqHGP/zZJtD0Q5/1mxB0DtA7UPJibZ9sFYknEfJPtvwcnKSSlChRAZQY9F0B3LJqBfCHGl/+9m4CVgmZC4gJ8Ae4CVmqZ9Hk6+O55I5+9/zgE8wsnvfhlV2SHZ9gARzt//3GzZAyCzfQMk4T6IaP7+52bTPkAIYdYfJ+E+iGj+/udmyz4YpWeScQ+cjJxUIlQIcboQ4ingf4UQHxVC2DRN04K+fB3Ak8DtfnHWBbgAu39DDQKf0jTtUk3TmhMzi8iJYv62oC/UU5qm/a+mae4ETCFqhBDrhRB/Bv5LCLFQn7sQQhdls30PRDr/WbMHAIQQZwghHgN+IIRYloT7INL5z8Z98C0ATdO8Qc/rAisZ9kEk8581+0AIsU4I8SfgbiHECuEPKUgWXXCyc9KIUCHESuAXyLuaTcD5wAIY9eVzAM8j73QeEEIUA6cia4GhaZpH07TjcR66IUQ5f49+nOAfqpMNIcRy4GfAM8Bx4FZGCi3rc5zNeyCa+c+KPQAghMgHfg78HWhDxrh9FJJmH0Qz/9m0Dz4E/AGZaHKD/zkLjLJizeZ9EM38T/p9IIQwCSG+AfwaeA7pHfo4/uLzyaALZgMnjQgFVgPVmqb9EfgnYAfq9Ds+IcS3kXc7BcBnkWUXHgI6ge8lYsAGk+zzB1gPHNA07WHgf4F+4H1CiHmQFGuQ7PPXWQUc0jTtd8APgSeAK4UQSwCEEN9hdq9Dss9fpxF5M34R8D8gBUWQVfibzO51SOr5++NXG4APa5r2Z+C7wFwgEJYw29dgVqBp2oz8D9nR4fSgv/ORxWW/i9x4rwG/BT6HFGQPAQvGHMOZ6Hmo+Ru6BquQsTwL/H9/A2kV/i8g1b8G82fLGiT7/IPmcBXwFeBS/995QJU+VyDbvxbfB5yzbR2Sff4TrMNl/r/NgNX/+FXg20HvzZ9t65Ds8x+zBvp3welfB5v/70eBy2fzGsy2/xI+gHEDgjTknX07UmRlBb22xP9D+0H/3+cgXVKnBb3HlOg5qPkbvgbZ/uddwD3Ay8BfkW7p9yCtAKagz5/Ua5Ds8w+aR55/ni8DtyFDEK7zv/Y94Mf6fIEzkdbh7NmyDsk+/2nW4Wr/ayn+/1cCXUDBBJ8/qdch2ec/3RoEvccKbAUWzcY1mK3/zUR3/DDwAvB+oAm4Xn9B07QDSCHW4H9qh/89ukvapJ3EJSb8JPv8YZI10DStV9O0LwCfQLZZuwyoBir1ec+SNUj2+evMB7Zomna2pmn3Id1pn/G/9jCwRAjxLv9825AutyGYNeuQ7PPXmWgd9AzmYSGEWdO0fcBj+F2sIqgD0CxYh2SfP0yxBkEsAVo0TTskhEgTQqyDQAWZ2bAGs5IZIUKFEB8UQpwjhMjUNG0IGWj8L+AQsEYIsSjo7f8HfMMfC/keYDnQCifvly3Z5w/TrsHq4DXQNG23pmlP+f88H3hNj409Wdcg2eev41+Hc4UQTuRN1oP+583AfmCf/617kGVlfiyEWAD8B/JmzAon7zok+/x1QliHPf6/BaABaJp2C/AhIUQHsEqcxIXXk33+ENYa6BUhcpClmD6MtIiu8AtQbdzBFTMGkah/H/+XpxAZs+EDDiPj2j6laVqr/z0Lke22hjRN+7b/OQfwADLewwx8UtO0/fGfQXQk+/wh7DUY1DTtO0GfXY1MyvACt2qadjjOw4+aZJ+/znTr4Lf0eIUQ7weu0DTthqDPfgHZcm8J8P80TXsn/jOIjmSfv06U6zAXuBcpRD6uadre+M8gOpJ9/hD1GtwNfBH4PTJUZXfcJ6AIn0TEAABm//8XAX/yP7Ygy888Pua9VwO/BBbiDyj2v7cwEWNX80/oGiwAHP7ncoBzEj0PNf+YrsMTY97zIHCD/3Fh0DFSEj0PNf+ErUOe//+ZwLpEz0PNPyFrUOD//0bgxkTPQ/0X3n+juq7EGr/Z/FuAWQjxdyAdf5cGTZaW+CTQJIQ4R9O0zf7nnxRCLEXWAXMJIc7T5N3+sXiO3QiSff4Q9Rr8A7kG52vS+rs5MbOInGSfv04k6wD0AjVCFue+RghxkaZpDZqmDSdiDtGQ7PPXMWgdLtE0rQ54IwFTiIpknz8YtgYXa5q2JRHjV0RH3GJGhBDnIOM6spDJFN9GFos9T/gDiDVN05Cb8ZtBn7se+CrwIrKl1knpbkr2+YOha3Cyhh8k9fx1IlkHfxzYR5ElqdKB8zRNaxh38JOAZJ+/joHrUBf3wRtAss8fDF2D+rgPXmEIcYsJFUKcBZRrstg6QohfIgOLB4A7NU1bLWQgdT7wU+CLmqbV+D+HpmmvxGWgMSLZ5w9qDZJ9/joRrMPnkW65O4EHNU3bmZiRG0Oyz18n2dch2ecPag0U8c2O3wE8Kkb6uW4B5mia9nukGf5OTWZ0lgJeTdNqQF54Z8nFN9nnD2oNkn3+OuGsg0/TtKOaph3WNO3Ts+Sik+zz10n2dUj2+YNag6QnbiJU07R+TdOGtJF+rhcAJ/yPPwIsFUI8g6x/N+s2V7LPH9QaJPv8dcJchx0QyJqdFST7/HWSfR2Sff6g1kBBfBOTIBDPoSELK//N/3QPshXXcqBG07TGeI8rXiT7/EGtQbLPXyecddDiFTcUR5J9/jrJvg7JPn9Qa5DMJKKYrQ9ZULkVWOm/y/lPpKn91SS4+Cb7/EGtQbLPXyfZ1yHZ56+T7OuQ7PMHtQZJS0KK1Qsh1iM7GmxFth/8TdwHkUCSff6g1iDZ56+T7OuQ7PPXSfZ1SPb5g1qDZCVRIrQU+ADwI022KEwqkn3+oNYg2eevk+zrkOzz10n2dUj2+YNag2QlYW07FQqFQqFQKBTJSyJiQhUKhUKhUCgUSY4SoQqFQqFQKBSKuKNEqEKhUCgUCoUi7igRqlAoFAqFQqGIO0qEKhQKhUKhUCjijhKhCoViViGEyBRC3OF/XCyE2JToMSkUCoViPKpEk0KhmFUIIcqBZzRNW57osSgUCoVicuLeO16hUChizPeA+UKIt4EqYKmmacuFEB8GrgLMyH7UPwRSkAWyh4BLNE1rF0LMB34B5AH9wP/TNO1AvCehUCgUsx3ljlcoFLONLwGHNU07Bfj8mNeWAzcB64DvAv2app0KbAM+6H/PA8CdmqatBj4H/DIeg1YoFIpkQ1lCFQpFMvGipmk9QI8Qogt42v/8HmClEMIFbAAeE0Lon7HFf5gKhUIx+1EiVKFQJBPBPal9QX/7kL+HJqDTb0VVKBQKRQxR7niFQjHb6AHSIvmgpmndQI0Q4noAIVll5OAUCoVCIVEiVKFQzCo0TWsDtggh9gI/iOAQ7wNuFkLsAvYBVxo5PoVCoVBIVIkmhUKhUCgUCkXcUZZQhUKhUCgUCkXcUSJUoVAoFAqFQhF3lAhVKBQKhUKhUMQdJUIVCoVCoVAoFHFHiVCFQqFQKBQKRdxRIlShUCgUCoVCEXeUCFUoFAqFQqFQxJ3/D6dumxYFbp2LAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "f = plt.figure(figsize=(10,6))\n",
    "ax = f.gca()\n",
    "mtseries.plot(ax = ax)\n",
    "obs_mtseries.plot(ax = ax, color = 'k', linewidth = 2)\n",
    "era5_mtseries.plot(ax = ax, color = 'g', linewidth = 2)\n",
    "l = f.legend(['WRF', 'MSWX', 'ERA5'])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "toc-showtags": false
 },
 "nbformat": 4,
 "nbformat_minor": 5
}