My_wee_deseasoned_graph.ipynb

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    "import numpy as np\n",
    "from datetime import datetime\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "from eofs.standard import Eof\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose"
   ]
  },
  {
   "cell_type": "code",
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    "# Load in the datasets \n",
    "sst = xr.open_dataset('sst_monthly.nc')['sst']\n",
    "msl = xr.open_dataset('msl_monthly.nc')['msl']\n",
    "u10 = xr.open_dataset('u10_monthly.nc')['u10']\n",
    "v10 = xr.open_dataset('v10_monthly.nc')['v10']"
   ]
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   "id": "f89d71b0-2ade-43d5-88ac-955a90c20361",
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    "# slice data for the specified region, 30S–30N, 100E–70W\n",
    "region = dict(latitude=slice(30, -30), longitude=slice(100, 290)) # 70W == 360-70=290 degrees\n",
    "\n",
    "# reduce datasets to information for the specified region only\n",
    "# xr.sel selects the coordinates defined in region from dataset xr\n",
    "sst_red = sst.sel(**region)\n",
    "msl_red = msl.sel(**region)\n",
    "u10_red = u10.sel(**region)\n",
    "v10_red = v10.sel(**region) "
   ]
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   "execution_count": 23,
   "id": "a186dbf9-7007-4277-a9a6-bf967b9df9b0",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 459, latitude: 81, longitude: 253)&gt; Size: 75MB\n",
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       "        ...,\n",
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       "          0.93639074,         nan],\n",
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       "                 nan,         nan],\n",
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       "\n",
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       "        [        nan,         nan,         nan, ..., -0.34362836,\n",
       "         -0.41585519, -0.52269296],\n",
       "...\n",
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       "                 nan,         nan],\n",
       "        [-0.50973312, -0.47211722, -0.27902949, ...,  0.5814206 ,\n",
       "                 nan,         nan]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,  0.26841198,\n",
       "          0.52394117,  0.6138279 ],\n",
       "        [        nan,         nan,         nan, ...,  0.16117355,\n",
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       "        [        nan,         nan,         nan, ...,  0.18185382,\n",
       "          0.2128434 , -0.12106123],\n",
       "        ...,\n",
       "        [-0.43590364, -0.51392465, -0.41072365, ...,  1.07061214,\n",
       "         -0.18502828,         nan],\n",
       "        [-0.33649351, -0.37070379, -0.28759747, ...,  0.11522083,\n",
       "                 nan,         nan],\n",
       "        [-0.25465082, -0.15174261, -0.15786039, ..., -0.13039971,\n",
       "                 nan,         nan]]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 1kB 100.5 101.2 102.0 ... 288.0 288.8 289.5\n",
       "  * latitude   (latitude) float32 324B 30.0 29.25 28.5 ... -28.5 -29.25 -30.0\n",
       "  * time       (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01\n",
       "    month      (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 ... 6 7 8 9 10 11 12 1 2 3</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 459</li><li><span class='xr-has-index'>latitude</span>: 81</li><li><span class='xr-has-index'>longitude</span>: 253</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-70764482-73ef-4e49-ae40-6cd09e0db09f' class='xr-array-in' type='checkbox' checked><label for='section-70764482-73ef-4e49-ae40-6cd09e0db09f' 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>nan nan nan nan nan nan nan ... 1.254 1.149 0.8047 -0.1304 nan nan</span></div><div class='xr-array-data'><pre>array([[[        nan,         nan,         nan, ...,  0.43397739,\n",
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       "          0.05573809, -0.00775125],\n",
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       "                 nan,         nan],\n",
       "        [ 0.15537938,  0.21718903,  0.26642408, ...,  0.8896367 ,\n",
       "                 nan,         nan]],\n",
       "\n",
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       "        [        nan,         nan,         nan, ..., -0.34362836,\n",
       "         -0.41585519, -0.52269296],\n",
       "...\n",
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       "          0.08786802,         nan],\n",
       "        [-0.69345155, -0.52454216, -0.38728498, ...,  0.54884379,\n",
       "                 nan,         nan],\n",
       "        [-0.50973312, -0.47211722, -0.27902949, ...,  0.5814206 ,\n",
       "                 nan,         nan]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,  0.26841198,\n",
       "          0.52394117,  0.6138279 ],\n",
       "        [        nan,         nan,         nan, ...,  0.16117355,\n",
       "          0.29564151,  0.28092493],\n",
       "        [        nan,         nan,         nan, ...,  0.18185382,\n",
       "          0.2128434 , -0.12106123],\n",
       "        ...,\n",
       "        [-0.43590364, -0.51392465, -0.41072365, ...,  1.07061214,\n",
       "         -0.18502828,         nan],\n",
       "        [-0.33649351, -0.37070379, -0.28759747, ...,  0.11522083,\n",
       "                 nan,         nan],\n",
       "        [-0.25465082, -0.15174261, -0.15786039, ..., -0.13039971,\n",
       "                 nan,         nan]]])</pre></div></div></li><li class='xr-section-item'><input id='section-13eef294-ff84-4a03-97a2-d48cb5db4c80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13eef294-ff84-4a03-97a2-d48cb5db4c80' class='xr-section-summary' >Coordinates: <span>(4)</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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>100.5 101.2 102.0 ... 288.8 289.5</div><input id='attrs-3005c6dd-315b-4941-848b-7b25c406d851' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3005c6dd-315b-4941-848b-7b25c406d851' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb24d781-8644-4232-9993-00687d6d40e1' class='xr-var-data-in' type='checkbox'><label for='data-fb24d781-8644-4232-9993-00687d6d40e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([100.5 , 101.25, 102.  , ..., 288.  , 288.75, 289.5 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>30.0 29.25 28.5 ... -29.25 -30.0</div><input id='attrs-ffefe79a-1bda-4ae8-b711-9b55e142efa1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffefe79a-1bda-4ae8-b711-9b55e142efa1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4804e94d-e305-479e-bf44-9de06979dbae' class='xr-var-data-in' type='checkbox'><label for='data-4804e94d-e305-479e-bf44-9de06979dbae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 30.  ,  29.25,  28.5 ,  27.75,  27.  ,  26.25,  25.5 ,  24.75,  24.  ,\n",
       "        23.25,  22.5 ,  21.75,  21.  ,  20.25,  19.5 ,  18.75,  18.  ,  17.25,\n",
       "        16.5 ,  15.75,  15.  ,  14.25,  13.5 ,  12.75,  12.  ,  11.25,  10.5 ,\n",
       "         9.75,   9.  ,   8.25,   7.5 ,   6.75,   6.  ,   5.25,   4.5 ,   3.75,\n",
       "         3.  ,   2.25,   1.5 ,   0.75,   0.  ,  -0.75,  -1.5 ,  -2.25,  -3.  ,\n",
       "        -3.75,  -4.5 ,  -5.25,  -6.  ,  -6.75,  -7.5 ,  -8.25,  -9.  ,  -9.75,\n",
       "       -10.5 , -11.25, -12.  , -12.75, -13.5 , -14.25, -15.  , -15.75, -16.5 ,\n",
       "       -17.25, -18.  , -18.75, -19.5 , -20.25, -21.  , -21.75, -22.5 , -23.25,\n",
       "       -24.  , -24.75, -25.5 , -26.25, -27.  , -27.75, -28.5 , -29.25, -30.  ],\n",
       "      dtype=float32)</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'>1979-01-01 ... 2017-03-01</div><input id='attrs-fb0044e9-4fea-42eb-a636-3f991c8d5a5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb0044e9-4fea-42eb-a636-3f991c8d5a5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2dbcb945-9ff4-47cc-8db2-1a5f1fb54c29' class='xr-var-data-in' type='checkbox'><label for='data-2dbcb945-9ff4-47cc-8db2-1a5f1fb54c29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-03-01T00:00:00.000000000&#x27;, ..., &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-02-01T00:00:00.000000000&#x27;, &#x27;2017-03-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 9 10 11 12 1 2 3</div><input id='attrs-642ee3b3-1fb1-4286-a16c-0401a554101c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-642ee3b3-1fb1-4286-a16c-0401a554101c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5556f10b-2a67-4939-ba7f-926ebcad934d' class='xr-var-data-in' type='checkbox'><label for='data-5556f10b-2a67-4939-ba7f-926ebcad934d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, ..., 1, 2, 3], dtype=int64)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3c572f27-646f-454c-9889-d43f762d5447' class='xr-section-summary-in' type='checkbox'  ><label for='section-3c572f27-646f-454c-9889-d43f762d5447' class='xr-section-summary' >Indexes: <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-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c3a869ea-641a-489b-9a36-5df93bb2cf0e' class='xr-index-data-in' type='checkbox'/><label for='index-c3a869ea-641a-489b-9a36-5df93bb2cf0e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 100.5, 101.25,  102.0, 102.75,  103.5, 104.25,  105.0, 105.75,  106.5,\n",
       "       107.25,\n",
       "       ...\n",
       "       282.75,  283.5, 284.25,  285.0, 285.75,  286.5, 287.25,  288.0, 288.75,\n",
       "        289.5],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;longitude&#x27;, length=253))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0d9d9497-953d-4b87-aa16-65c40573b7e6' class='xr-index-data-in' type='checkbox'/><label for='index-0d9d9497-953d-4b87-aa16-65c40573b7e6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  30.0,  29.25,   28.5,  27.75,   27.0,  26.25,   25.5,  24.75,   24.0,\n",
       "        23.25,   22.5,  21.75,   21.0,  20.25,   19.5,  18.75,   18.0,  17.25,\n",
       "         16.5,  15.75,   15.0,  14.25,   13.5,  12.75,   12.0,  11.25,   10.5,\n",
       "         9.75,    9.0,   8.25,    7.5,   6.75,    6.0,   5.25,    4.5,   3.75,\n",
       "          3.0,   2.25,    1.5,   0.75,    0.0,  -0.75,   -1.5,  -2.25,   -3.0,\n",
       "        -3.75,   -4.5,  -5.25,   -6.0,  -6.75,   -7.5,  -8.25,   -9.0,  -9.75,\n",
       "        -10.5, -11.25,  -12.0, -12.75,  -13.5, -14.25,  -15.0, -15.75,  -16.5,\n",
       "       -17.25,  -18.0, -18.75,  -19.5, -20.25,  -21.0, -21.75,  -22.5, -23.25,\n",
       "        -24.0, -24.75,  -25.5, -26.25,  -27.0, -27.75,  -28.5, -29.25,  -30.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;latitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-54281909-d212-4340-a210-0d1d5f4188bf' class='xr-index-data-in' type='checkbox'/><label for='index-54281909-d212-4340-a210-0d1d5f4188bf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1979-01-01&#x27;, &#x27;1979-02-01&#x27;, &#x27;1979-03-01&#x27;, &#x27;1979-04-01&#x27;,\n",
       "               &#x27;1979-05-01&#x27;, &#x27;1979-06-01&#x27;, &#x27;1979-07-01&#x27;, &#x27;1979-08-01&#x27;,\n",
       "               &#x27;1979-09-01&#x27;, &#x27;1979-10-01&#x27;,\n",
       "               ...\n",
       "               &#x27;2016-06-01&#x27;, &#x27;2016-07-01&#x27;, &#x27;2016-08-01&#x27;, &#x27;2016-09-01&#x27;,\n",
       "               &#x27;2016-10-01&#x27;, &#x27;2016-11-01&#x27;, &#x27;2016-12-01&#x27;, &#x27;2017-01-01&#x27;,\n",
       "               &#x27;2017-02-01&#x27;, &#x27;2017-03-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=459, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cf9b9993-55b7-4bcf-aea6-1fcbff24c15b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cf9b9993-55b7-4bcf-aea6-1fcbff24c15b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 459, latitude: 81, longitude: 253)> Size: 75MB\n",
       "array([[[        nan,         nan,         nan, ...,  0.43397739,\n",
       "          0.38122884,  0.33992995],\n",
       "        [        nan,         nan,         nan, ...,  0.26258699,\n",
       "          0.22002447,  0.17687638],\n",
       "        [        nan,         nan,         nan, ...,  0.08151908,\n",
       "          0.05573809, -0.00775125],\n",
       "        ...,\n",
       "        [-0.12161599, -0.0219593 ,  0.05764894, ...,  0.80554414,\n",
       "          0.93639074,         nan],\n",
       "        [ 0.04371827,  0.12986036,  0.20738824, ...,  0.84220461,\n",
       "                 nan,         nan],\n",
       "        [ 0.15537938,  0.21718903,  0.26642408, ...,  0.8896367 ,\n",
       "                 nan,         nan]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ..., -0.04673863,\n",
       "         -0.0803171 , -0.17052744],\n",
       "        [        nan,         nan,         nan, ..., -0.18829521,\n",
       "         -0.23608173, -0.33342691],\n",
       "        [        nan,         nan,         nan, ..., -0.34362836,\n",
       "         -0.41585519, -0.52269296],\n",
       "...\n",
       "        [-0.57906286, -0.48410623, -0.39133782, ...,  1.28630639,\n",
       "          0.08786802,         nan],\n",
       "        [-0.69345155, -0.52454216, -0.38728498, ...,  0.54884379,\n",
       "                 nan,         nan],\n",
       "        [-0.50973312, -0.47211722, -0.27902949, ...,  0.5814206 ,\n",
       "                 nan,         nan]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,  0.26841198,\n",
       "          0.52394117,  0.6138279 ],\n",
       "        [        nan,         nan,         nan, ...,  0.16117355,\n",
       "          0.29564151,  0.28092493],\n",
       "        [        nan,         nan,         nan, ...,  0.18185382,\n",
       "          0.2128434 , -0.12106123],\n",
       "        ...,\n",
       "        [-0.43590364, -0.51392465, -0.41072365, ...,  1.07061214,\n",
       "         -0.18502828,         nan],\n",
       "        [-0.33649351, -0.37070379, -0.28759747, ...,  0.11522083,\n",
       "                 nan,         nan],\n",
       "        [-0.25465082, -0.15174261, -0.15786039, ..., -0.13039971,\n",
       "                 nan,         nan]]])\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 1kB 100.5 101.2 102.0 ... 288.0 288.8 289.5\n",
       "  * latitude   (latitude) float32 324B 30.0 29.25 28.5 ... -28.5 -29.25 -30.0\n",
       "  * time       (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01\n",
       "    month      (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 ... 6 7 8 9 10 11 12 1 2 3"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Step 1: Compute the monthly climatology\n",
    "climatology = sst_red.groupby(\"time.month\").mean(\"time\")\n",
    "\n",
    "# Step 2: Subtract climatology to deseasonalize\n",
    "deseasoned_sst = sst_red.groupby(\"time.month\") - climatology\n",
    "deseasoned_sst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "5e5f73f4-337e-4dc7-8d1c-ea2c06b313ec",
   "metadata": {},
   "outputs": [
    {
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       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 459)&gt; Size: 4kB\n",
       "array([298.87672864, 298.93464549, 299.16859527, 299.41593237,\n",
       "       299.46615979, 299.38221436, 299.14570536, 299.06614898,\n",
       "       299.20484512, 299.23368887, 299.19259479, 299.09607941,\n",
       "       299.11707752, 299.13107444, 299.43790727, 299.52610433,\n",
       "       299.63600696, 299.49330168, 299.25146335, 299.05604679,\n",
       "       299.11045544, 299.09997593, 299.09351161, 298.95364757,\n",
       "       298.79826865, 298.89042545, 299.19367774, 299.41909664,\n",
       "       299.56626739, 299.46310525, 299.23205313, 299.00895684,\n",
       "       299.1656836 , 299.15729741, 299.13607778, 299.05533229,\n",
       "       299.12376477, 299.11812328, 299.31680196, 299.4588436 ,\n",
       "       299.55713298, 299.45832133, 299.19292259, 299.0936184 ,\n",
       "       299.14479279, 299.31651071, 299.32657233, 299.34598549,\n",
       "       299.29903542, 299.35642233, 299.46872425, 299.61094674,\n",
       "       299.63944528, 299.67537473, 299.32881712, 299.1672512 ,\n",
       "       299.22292923, 299.28812345, 299.16427755, 299.05798588,\n",
       "       299.05577474, 299.19945328, 299.33884007, 299.50223819,\n",
       "       299.50293653, 299.29108654, 299.18158247, 299.00735245,\n",
       "       299.17019469, 299.03083376, 299.02344854, 298.76112574,\n",
       "       298.76158386, 299.00313139, 299.16406126, 299.24329381,\n",
       "       299.31929193, 299.22331595, 299.05807871, 298.87333639,\n",
       "...\n",
       "       299.11072482, 299.09366999, 298.95325978, 298.81693279,\n",
       "       298.75316833, 298.95617211, 299.20251043, 299.40065183,\n",
       "       299.51007332, 299.42591253, 299.14761595, 299.00058545,\n",
       "       298.95501105, 298.99711915, 299.03123383, 298.9633209 ,\n",
       "       298.99594087, 299.19156247, 299.42059429, 299.63013634,\n",
       "       299.71249248, 299.53580565, 299.31147158, 299.13805928,\n",
       "       299.1958022 , 299.29690307, 299.33553986, 299.28726483,\n",
       "       299.11272856, 299.28690407, 299.46489554, 299.69048858,\n",
       "       299.69027593, 299.57079113, 299.40416004, 299.29523271,\n",
       "       299.32570286, 299.28218297, 299.2707952 , 299.21511634,\n",
       "       299.12980462, 299.18580054, 299.4307919 , 299.64351277,\n",
       "       299.82648398, 299.76455289, 299.57012491, 299.46226615,\n",
       "       299.49244204, 299.49164578, 299.48452889, 299.34618468,\n",
       "       299.21593726, 299.33974661, 299.57352715, 299.89809563,\n",
       "       299.95792642, 299.93785462, 299.7566361 , 299.68982446,\n",
       "       299.77517594, 299.74957946, 299.85866852, 299.73564332,\n",
       "       299.74180728, 299.74996493, 299.96825078, 300.07699379,\n",
       "       300.12524033, 300.08810208, 299.89120405, 299.66516101,\n",
       "       299.62156921, 299.66141756, 299.59445418, 299.48855944,\n",
       "       299.46844747, 299.57615925, 299.82228475])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 459</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-036cd448-63d8-4541-bf64-4494ffece4b6' class='xr-array-in' type='checkbox' checked><label for='section-036cd448-63d8-4541-bf64-4494ffece4b6' 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>298.9 298.9 299.2 299.4 299.5 299.4 ... 299.6 299.5 299.5 299.6 299.8</span></div><div class='xr-array-data'><pre>array([298.87672864, 298.93464549, 299.16859527, 299.41593237,\n",
       "       299.46615979, 299.38221436, 299.14570536, 299.06614898,\n",
       "       299.20484512, 299.23368887, 299.19259479, 299.09607941,\n",
       "       299.11707752, 299.13107444, 299.43790727, 299.52610433,\n",
       "       299.63600696, 299.49330168, 299.25146335, 299.05604679,\n",
       "       299.11045544, 299.09997593, 299.09351161, 298.95364757,\n",
       "       298.79826865, 298.89042545, 299.19367774, 299.41909664,\n",
       "       299.56626739, 299.46310525, 299.23205313, 299.00895684,\n",
       "       299.1656836 , 299.15729741, 299.13607778, 299.05533229,\n",
       "       299.12376477, 299.11812328, 299.31680196, 299.4588436 ,\n",
       "       299.55713298, 299.45832133, 299.19292259, 299.0936184 ,\n",
       "       299.14479279, 299.31651071, 299.32657233, 299.34598549,\n",
       "       299.29903542, 299.35642233, 299.46872425, 299.61094674,\n",
       "       299.63944528, 299.67537473, 299.32881712, 299.1672512 ,\n",
       "       299.22292923, 299.28812345, 299.16427755, 299.05798588,\n",
       "       299.05577474, 299.19945328, 299.33884007, 299.50223819,\n",
       "       299.50293653, 299.29108654, 299.18158247, 299.00735245,\n",
       "       299.17019469, 299.03083376, 299.02344854, 298.76112574,\n",
       "       298.76158386, 299.00313139, 299.16406126, 299.24329381,\n",
       "       299.31929193, 299.22331595, 299.05807871, 298.87333639,\n",
       "...\n",
       "       299.11072482, 299.09366999, 298.95325978, 298.81693279,\n",
       "       298.75316833, 298.95617211, 299.20251043, 299.40065183,\n",
       "       299.51007332, 299.42591253, 299.14761595, 299.00058545,\n",
       "       298.95501105, 298.99711915, 299.03123383, 298.9633209 ,\n",
       "       298.99594087, 299.19156247, 299.42059429, 299.63013634,\n",
       "       299.71249248, 299.53580565, 299.31147158, 299.13805928,\n",
       "       299.1958022 , 299.29690307, 299.33553986, 299.28726483,\n",
       "       299.11272856, 299.28690407, 299.46489554, 299.69048858,\n",
       "       299.69027593, 299.57079113, 299.40416004, 299.29523271,\n",
       "       299.32570286, 299.28218297, 299.2707952 , 299.21511634,\n",
       "       299.12980462, 299.18580054, 299.4307919 , 299.64351277,\n",
       "       299.82648398, 299.76455289, 299.57012491, 299.46226615,\n",
       "       299.49244204, 299.49164578, 299.48452889, 299.34618468,\n",
       "       299.21593726, 299.33974661, 299.57352715, 299.89809563,\n",
       "       299.95792642, 299.93785462, 299.7566361 , 299.68982446,\n",
       "       299.77517594, 299.74957946, 299.85866852, 299.73564332,\n",
       "       299.74180728, 299.74996493, 299.96825078, 300.07699379,\n",
       "       300.12524033, 300.08810208, 299.89120405, 299.66516101,\n",
       "       299.62156921, 299.66141756, 299.59445418, 299.48855944,\n",
       "       299.46844747, 299.57615925, 299.82228475])</pre></div></div></li><li class='xr-section-item'><input id='section-bf763123-46eb-4f8a-9a8c-60930200be1b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bf763123-46eb-4f8a-9a8c-60930200be1b' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>1979-01-01 ... 2017-03-01</div><input id='attrs-62da4050-f373-4b46-b90f-ab854fc141a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62da4050-f373-4b46-b90f-ab854fc141a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee3871f2-80d4-4672-8c71-f6c0a0a43d62' class='xr-var-data-in' type='checkbox'><label for='data-ee3871f2-80d4-4672-8c71-f6c0a0a43d62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-03-01T00:00:00.000000000&#x27;, ..., &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-02-01T00:00:00.000000000&#x27;, &#x27;2017-03-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1ea5dda-a413-41ef-b645-ffcce053fc64' class='xr-section-summary-in' type='checkbox'  ><label for='section-e1ea5dda-a413-41ef-b645-ffcce053fc64' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4362533d-654c-4d57-92ac-80751579f807' class='xr-index-data-in' type='checkbox'/><label for='index-4362533d-654c-4d57-92ac-80751579f807' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1979-01-01&#x27;, &#x27;1979-02-01&#x27;, &#x27;1979-03-01&#x27;, &#x27;1979-04-01&#x27;,\n",
       "               &#x27;1979-05-01&#x27;, &#x27;1979-06-01&#x27;, &#x27;1979-07-01&#x27;, &#x27;1979-08-01&#x27;,\n",
       "               &#x27;1979-09-01&#x27;, &#x27;1979-10-01&#x27;,\n",
       "               ...\n",
       "               &#x27;2016-06-01&#x27;, &#x27;2016-07-01&#x27;, &#x27;2016-08-01&#x27;, &#x27;2016-09-01&#x27;,\n",
       "               &#x27;2016-10-01&#x27;, &#x27;2016-11-01&#x27;, &#x27;2016-12-01&#x27;, &#x27;2017-01-01&#x27;,\n",
       "               &#x27;2017-02-01&#x27;, &#x27;2017-03-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=459, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fb0193d2-3938-484b-9b55-7b3a62fe3ddb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fb0193d2-3938-484b-9b55-7b3a62fe3ddb' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 459)> Size: 4kB\n",
       "array([298.87672864, 298.93464549, 299.16859527, 299.41593237,\n",
       "       299.46615979, 299.38221436, 299.14570536, 299.06614898,\n",
       "       299.20484512, 299.23368887, 299.19259479, 299.09607941,\n",
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       "       299.31929193, 299.22331595, 299.05807871, 298.87333639,\n",
       "...\n",
       "       299.11072482, 299.09366999, 298.95325978, 298.81693279,\n",
       "       298.75316833, 298.95617211, 299.20251043, 299.40065183,\n",
       "       299.51007332, 299.42591253, 299.14761595, 299.00058545,\n",
       "       298.95501105, 298.99711915, 299.03123383, 298.9633209 ,\n",
       "       298.99594087, 299.19156247, 299.42059429, 299.63013634,\n",
       "       299.71249248, 299.53580565, 299.31147158, 299.13805928,\n",
       "       299.1958022 , 299.29690307, 299.33553986, 299.28726483,\n",
       "       299.11272856, 299.28690407, 299.46489554, 299.69048858,\n",
       "       299.69027593, 299.57079113, 299.40416004, 299.29523271,\n",
       "       299.32570286, 299.28218297, 299.2707952 , 299.21511634,\n",
       "       299.12980462, 299.18580054, 299.4307919 , 299.64351277,\n",
       "       299.82648398, 299.76455289, 299.57012491, 299.46226615,\n",
       "       299.49244204, 299.49164578, 299.48452889, 299.34618468,\n",
       "       299.21593726, 299.33974661, 299.57352715, 299.89809563,\n",
       "       299.95792642, 299.93785462, 299.7566361 , 299.68982446,\n",
       "       299.77517594, 299.74957946, 299.85866852, 299.73564332,\n",
       "       299.74180728, 299.74996493, 299.96825078, 300.07699379,\n",
       "       300.12524033, 300.08810208, 299.89120405, 299.66516101,\n",
       "       299.62156921, 299.66141756, 299.59445418, 299.48855944,\n",
       "       299.46844747, 299.57615925, 299.82228475])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mean temperatures for all lon & lat\n",
    "sst_mean0 = sst_red.mean(dim='latitude', skipna=True)\n",
    "sst_mean = sst_mean0.mean(dim='longitude', skipna=True)\n",
    "sst_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "bceb963e-0ed7-47e6-8966-b30ccda2399c",
   "metadata": {},
   "outputs": [
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       "       -2.94272193e-01, -2.83273952e-01, -2.32138186e-01, -1.92644478e-01,\n",
       "       -1.10225932e-01, -1.49060595e-02,  5.65360129e-03,  4.36358633e-02,\n",
       "        7.14913587e-02, -1.01062733e-02, -3.49954663e-02, -7.48333243e-02,\n",
       "       -5.34810433e-02,  1.65099656e-02,  7.21678407e-02,  1.31299451e-01,\n",
       "        6.56176596e-03,  8.04355427e-02,  4.99548451e-02,  1.03988098e-01,\n",
       "        4.92748122e-02,  2.48792066e-02,  5.76929923e-02,  8.23401108e-02,\n",
       "        7.64196156e-02,  1.78986971e-03,  7.42318447e-03,  5.91509596e-02,\n",
       "        2.36378196e-02, -2.06679825e-02,  1.58512052e-02,  5.70122956e-02,\n",
       "        1.85482865e-01,  2.18640966e-01,  2.23657865e-01,  2.49373547e-01,\n",
       "        2.43158799e-01,  2.11252681e-01,  2.21156874e-01,  1.90219302e-01,\n",
       "        1.09770465e-01,  1.33278086e-01,  1.58586461e-01,  3.11595155e-01,\n",
       "        3.16925300e-01,  3.91942705e-01,  4.10169055e-01,  4.76931854e-01,\n",
       "        5.25892692e-01,  4.69186356e-01,  5.95296507e-01,  5.79677939e-01,\n",
       "        6.35640482e-01,  5.43496408e-01,  5.53310091e-01,  4.90493315e-01,\n",
       "        4.84239216e-01,  5.42190161e-01,  5.44737006e-01,  4.52268411e-01,\n",
       "        3.72285967e-01,  3.81024454e-01,  3.31082164e-01,  3.32594060e-01,\n",
       "        3.62280675e-01,  3.69690723e-01,  4.07344057e-01])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01\n",
       "    month    (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 6 7 8 9 10 11 12 1 2 3</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 459</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f9f36b39-0896-415a-947d-2516390d5c66' class='xr-array-in' type='checkbox' checked><label for='section-f9f36b39-0896-415a-947d-2516390d5c66' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-0.2294 -0.2718 -0.2463 -0.1706 ... 0.3326 0.3623 0.3697 0.4073</span></div><div class='xr-array-data'><pre>array([-2.29438156e-01, -2.71823041e-01, -2.46345425e-01, -1.70568104e-01,\n",
       "       -1.74841322e-01, -1.63697562e-01, -2.00761686e-01, -1.46743628e-01,\n",
       "       -4.44381227e-02, -4.67042314e-02, -7.07772228e-02, -5.98859685e-02,\n",
       "        1.09107251e-02, -7.53940841e-02,  2.29665766e-02, -6.03961453e-02,\n",
       "       -4.99415636e-03, -5.26102436e-02, -9.50036967e-02, -1.56845813e-01,\n",
       "       -1.38827806e-01, -1.80417173e-01, -1.69860402e-01, -2.02317809e-01,\n",
       "       -3.07898147e-01, -3.16043078e-01, -2.21262948e-01, -1.67403836e-01,\n",
       "       -7.47337268e-02, -8.28066719e-02, -1.14413920e-01, -2.03935763e-01,\n",
       "       -8.35996452e-02, -1.23095696e-01, -1.27294240e-01, -1.00633084e-01,\n",
       "        1.75979684e-02, -8.83452470e-02, -9.81387253e-02, -1.27656878e-01,\n",
       "       -8.38681320e-02, -8.75905939e-02, -1.53544462e-01, -1.19274201e-01,\n",
       "       -1.04490452e-01,  3.61176021e-02,  6.32003108e-02,  1.90020116e-01,\n",
       "        1.92868620e-01,  1.49953799e-01,  5.37835642e-02,  2.44462597e-02,\n",
       "       -1.55584000e-03,  1.29462808e-01, -1.76499314e-02, -4.56414007e-02,\n",
       "       -2.63540112e-02,  7.73034745e-03, -9.90944708e-02, -9.79794933e-02,\n",
       "       -5.03920580e-02, -7.01525049e-03, -7.61006249e-02, -8.42622896e-02,\n",
       "       -1.38064592e-01, -2.54825383e-01, -1.64884582e-01, -2.05540157e-01,\n",
       "       -7.90885593e-02, -2.49559347e-01, -2.39923479e-01, -3.94839641e-01,\n",
       "       -3.44582933e-01, -2.03337139e-01, -2.50879428e-01, -3.43206671e-01,\n",
       "       -3.21709183e-01, -3.22595965e-01, -2.88388334e-01, -3.39556215e-01,\n",
       "...\n",
       "       -1.38558424e-01, -1.86723118e-01, -3.10112232e-01, -3.39032588e-01,\n",
       "       -3.52998469e-01, -2.50296420e-01, -2.12430259e-01, -1.85848649e-01,\n",
       "       -1.30927794e-01, -1.19999393e-01, -1.98851096e-01, -2.12307153e-01,\n",
       "       -2.94272193e-01, -2.83273952e-01, -2.32138186e-01, -1.92644478e-01,\n",
       "       -1.10225932e-01, -1.49060595e-02,  5.65360129e-03,  4.36358633e-02,\n",
       "        7.14913587e-02, -1.01062733e-02, -3.49954663e-02, -7.48333243e-02,\n",
       "       -5.34810433e-02,  1.65099656e-02,  7.21678407e-02,  1.31299451e-01,\n",
       "        6.56176596e-03,  8.04355427e-02,  4.99548451e-02,  1.03988098e-01,\n",
       "        4.92748122e-02,  2.48792066e-02,  5.76929923e-02,  8.23401108e-02,\n",
       "        7.64196156e-02,  1.78986971e-03,  7.42318447e-03,  5.91509596e-02,\n",
       "        2.36378196e-02, -2.06679825e-02,  1.58512052e-02,  5.70122956e-02,\n",
       "        1.85482865e-01,  2.18640966e-01,  2.23657865e-01,  2.49373547e-01,\n",
       "        2.43158799e-01,  2.11252681e-01,  2.21156874e-01,  1.90219302e-01,\n",
       "        1.09770465e-01,  1.33278086e-01,  1.58586461e-01,  3.11595155e-01,\n",
       "        3.16925300e-01,  3.91942705e-01,  4.10169055e-01,  4.76931854e-01,\n",
       "        5.25892692e-01,  4.69186356e-01,  5.95296507e-01,  5.79677939e-01,\n",
       "        6.35640482e-01,  5.43496408e-01,  5.53310091e-01,  4.90493315e-01,\n",
       "        4.84239216e-01,  5.42190161e-01,  5.44737006e-01,  4.52268411e-01,\n",
       "        3.72285967e-01,  3.81024454e-01,  3.31082164e-01,  3.32594060e-01,\n",
       "        3.62280675e-01,  3.69690723e-01,  4.07344057e-01])</pre></div></div></li><li class='xr-section-item'><input id='section-2252e6bc-b8c4-46bc-bcd2-5927ceb3c8ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2252e6bc-b8c4-46bc-bcd2-5927ceb3c8ec' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>1979-01-01 ... 2017-03-01</div><input id='attrs-36a0fa12-19d9-4623-b0ff-84dc7b9587dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36a0fa12-19d9-4623-b0ff-84dc7b9587dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea004f13-9590-480b-ab71-47d7efc285e1' class='xr-var-data-in' type='checkbox'><label for='data-ea004f13-9590-480b-ab71-47d7efc285e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1979-01-01T00:00:00.000000000&#x27;, &#x27;1979-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1979-03-01T00:00:00.000000000&#x27;, ..., &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-02-01T00:00:00.000000000&#x27;, &#x27;2017-03-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 9 10 11 12 1 2 3</div><input id='attrs-056cb8bb-9821-4861-b543-0aabb0726939' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-056cb8bb-9821-4861-b543-0aabb0726939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ec29290-2215-4d40-8606-ed4071335578' class='xr-var-data-in' type='checkbox'><label for='data-1ec29290-2215-4d40-8606-ed4071335578' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, ..., 1, 2, 3], dtype=int64)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6976446d-8e4f-4e2d-8ff6-424c75c5f2fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-6976446d-8e4f-4e2d-8ff6-424c75c5f2fc' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9c5bdfb3-01f4-4f8a-8bec-aaf50d62e865' class='xr-index-data-in' type='checkbox'/><label for='index-9c5bdfb3-01f4-4f8a-8bec-aaf50d62e865' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1979-01-01&#x27;, &#x27;1979-02-01&#x27;, &#x27;1979-03-01&#x27;, &#x27;1979-04-01&#x27;,\n",
       "               &#x27;1979-05-01&#x27;, &#x27;1979-06-01&#x27;, &#x27;1979-07-01&#x27;, &#x27;1979-08-01&#x27;,\n",
       "               &#x27;1979-09-01&#x27;, &#x27;1979-10-01&#x27;,\n",
       "               ...\n",
       "               &#x27;2016-06-01&#x27;, &#x27;2016-07-01&#x27;, &#x27;2016-08-01&#x27;, &#x27;2016-09-01&#x27;,\n",
       "               &#x27;2016-10-01&#x27;, &#x27;2016-11-01&#x27;, &#x27;2016-12-01&#x27;, &#x27;2017-01-01&#x27;,\n",
       "               &#x27;2017-02-01&#x27;, &#x27;2017-03-01&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=459, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d400c4d-6cf8-4f8e-9e8d-85981e8c046f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7d400c4d-6cf8-4f8e-9e8d-85981e8c046f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 459)> Size: 4kB\n",
       "array([-2.29438156e-01, -2.71823041e-01, -2.46345425e-01, -1.70568104e-01,\n",
       "       -1.74841322e-01, -1.63697562e-01, -2.00761686e-01, -1.46743628e-01,\n",
       "       -4.44381227e-02, -4.67042314e-02, -7.07772228e-02, -5.98859685e-02,\n",
       "        1.09107251e-02, -7.53940841e-02,  2.29665766e-02, -6.03961453e-02,\n",
       "       -4.99415636e-03, -5.26102436e-02, -9.50036967e-02, -1.56845813e-01,\n",
       "       -1.38827806e-01, -1.80417173e-01, -1.69860402e-01, -2.02317809e-01,\n",
       "       -3.07898147e-01, -3.16043078e-01, -2.21262948e-01, -1.67403836e-01,\n",
       "       -7.47337268e-02, -8.28066719e-02, -1.14413920e-01, -2.03935763e-01,\n",
       "       -8.35996452e-02, -1.23095696e-01, -1.27294240e-01, -1.00633084e-01,\n",
       "        1.75979684e-02, -8.83452470e-02, -9.81387253e-02, -1.27656878e-01,\n",
       "       -8.38681320e-02, -8.75905939e-02, -1.53544462e-01, -1.19274201e-01,\n",
       "       -1.04490452e-01,  3.61176021e-02,  6.32003108e-02,  1.90020116e-01,\n",
       "        1.92868620e-01,  1.49953799e-01,  5.37835642e-02,  2.44462597e-02,\n",
       "       -1.55584000e-03,  1.29462808e-01, -1.76499314e-02, -4.56414007e-02,\n",
       "       -2.63540112e-02,  7.73034745e-03, -9.90944708e-02, -9.79794933e-02,\n",
       "       -5.03920580e-02, -7.01525049e-03, -7.61006249e-02, -8.42622896e-02,\n",
       "       -1.38064592e-01, -2.54825383e-01, -1.64884582e-01, -2.05540157e-01,\n",
       "       -7.90885593e-02, -2.49559347e-01, -2.39923479e-01, -3.94839641e-01,\n",
       "       -3.44582933e-01, -2.03337139e-01, -2.50879428e-01, -3.43206671e-01,\n",
       "       -3.21709183e-01, -3.22595965e-01, -2.88388334e-01, -3.39556215e-01,\n",
       "...\n",
       "       -1.38558424e-01, -1.86723118e-01, -3.10112232e-01, -3.39032588e-01,\n",
       "       -3.52998469e-01, -2.50296420e-01, -2.12430259e-01, -1.85848649e-01,\n",
       "       -1.30927794e-01, -1.19999393e-01, -1.98851096e-01, -2.12307153e-01,\n",
       "       -2.94272193e-01, -2.83273952e-01, -2.32138186e-01, -1.92644478e-01,\n",
       "       -1.10225932e-01, -1.49060595e-02,  5.65360129e-03,  4.36358633e-02,\n",
       "        7.14913587e-02, -1.01062733e-02, -3.49954663e-02, -7.48333243e-02,\n",
       "       -5.34810433e-02,  1.65099656e-02,  7.21678407e-02,  1.31299451e-01,\n",
       "        6.56176596e-03,  8.04355427e-02,  4.99548451e-02,  1.03988098e-01,\n",
       "        4.92748122e-02,  2.48792066e-02,  5.76929923e-02,  8.23401108e-02,\n",
       "        7.64196156e-02,  1.78986971e-03,  7.42318447e-03,  5.91509596e-02,\n",
       "        2.36378196e-02, -2.06679825e-02,  1.58512052e-02,  5.70122956e-02,\n",
       "        1.85482865e-01,  2.18640966e-01,  2.23657865e-01,  2.49373547e-01,\n",
       "        2.43158799e-01,  2.11252681e-01,  2.21156874e-01,  1.90219302e-01,\n",
       "        1.09770465e-01,  1.33278086e-01,  1.58586461e-01,  3.11595155e-01,\n",
       "        3.16925300e-01,  3.91942705e-01,  4.10169055e-01,  4.76931854e-01,\n",
       "        5.25892692e-01,  4.69186356e-01,  5.95296507e-01,  5.79677939e-01,\n",
       "        6.35640482e-01,  5.43496408e-01,  5.53310091e-01,  4.90493315e-01,\n",
       "        4.84239216e-01,  5.42190161e-01,  5.44737006e-01,  4.52268411e-01,\n",
       "        3.72285967e-01,  3.81024454e-01,  3.31082164e-01,  3.32594060e-01,\n",
       "        3.62280675e-01,  3.69690723e-01,  4.07344057e-01])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 4kB 1979-01-01 1979-02-01 ... 2017-03-01\n",
       "    month    (time) int64 4kB 1 2 3 4 5 6 7 8 9 10 11 ... 6 7 8 9 10 11 12 1 2 3"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Mean deseasoned temperatures for all lon & lat\n",
    "des_sst_mean0 = deseasoned_sst.mean(dim='latitude', skipna=True)\n",
    "des_sst_mean = des_sst_mean0.mean(dim='longitude', skipna=True)\n",
    "des_sst_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "765f388d-afbe-473d-a9ee-7cc93ae21ba7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot seasonal\n",
    "plt.figure(figsize = (12,3.5))\n",
    "plt.plot(sst_red.time,sst_mean)\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "eb78c8cc-4f91-40ce-b1e3-f2d7399e6137",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Ai0Gyo9vIjk4QBFGxvNw3i1MTDhi0qohrRLZpNqc3puy5k5N4+vgEgmU0RjNnRbjP58P+/fuxffv2iNu3b9+OnTt3xn3cz372M5w+fRpf/OIXU/o+Xq8XNpst4g9BEARBEAsRRRGnJh0AgI0dVn57WAknOzpBEESl8vNdfQCAaze2o6ZKl7Pv08iU8BTs6JN2LybsXggCsKbVnLNjyjc5K8KnpqYQDAbR3NwccXtzczPGxsZiPqa3txef/exn8cgjj0Cj0aT0fe677z5YrVb+p7Ozc9HHThAEQRDliMcfgi8QAiDNgGWEe8L9ZaU0EARBEKkxYfPgidekGu2mbV05/V58TFkKdvSjo5LA2tNgQpUutfqwFMh5MJsgCBH/F0VxwW0AEAwGceONN+Kee+7BypUrU37+u+66C/Pz8/zP4ODgoo+ZIAiCIMqRebnnW60SUK0PL2ZYOvofD41gzX88gV+/TNdSgiCISuI3+4cQCInY0lWLde3W5A9YBM2yEj6ZghLOpnmsbcvtMeWbnG0nNDQ0QK1WL1C9JyYmFqjjAGC327Fv3z4cPHgQH/vYxwAAoVAIoihCo9Hg73//O6666qoFj9Pr9dDr9bn5IQiCIAiijJhz+wAAVqM2YkPcLCvhUw5pQfTiqSlcv5WcZQRBEJXC0RFJcb56XUvOv1cT7wlPQQmXj+ucVktOjynf5EwJ1+l02Lx5M3bs2BFx+44dO3DRRRctuL/FYsHhw4dx6NAh/ue2227DqlWrcOjQIVxwwQW5OlSCIAiCqAjmXZISXiP3gDOWNZgASAo5AMy6fPk9MIIgCKKgjNmkgjhX88GVsBFlE3Yv9p6dwYu9U3Hvy4rwtW3lVYTn1Fh/xx134KabbsKWLVuwbds2/OhHP8LAwABuu+02AJKVfHh4GD//+c+hUqmwbt26iMc3NTXBYDAsuJ0gCIIgiPSZk+3olqgifNuyevz1E5fg7JQTH/vlQcw4qQgnCIKoJMbmpSK82WLI+fdiI8pcviBu+NEuaFQC9nzu9RFZJQDg9AZwdtoJADiHivDUueGGGzA9PY17770Xo6OjWLduHR5//HF0dUnN/qOjo0lnhhMEQRAEkR1YT3hNVWQRLggC1rZZEQhKoWyzVIQTBEFUDKGQyK3hLdbcF+FVOg3Meg3s3gBEEfAHRfSO23HB0sixaMfHbBBFqYe8obq82o9zHsx2++23o6+vD16vF/v378dll13Gv/bQQw/h2WefjfvYu+++G4cOHcr1IRIEQRBERcDs6NYoJZzBVIgZsqMTBEFUDDMuH/xBEYIQtornmtaayGKfjc9UcqB/DkD5hbIBOVbCCYIgCIIoHrgSHqcIr5WLcI8/BLcvCKNOnbdjIwiCIAoDs6LXm/TQqnOu0QIAPvemNdh5ehp2jx+P7h3E6QlnxNefPDKG/37yBADg/J66vBxTPsnPq0wQBEEQRMFRpqPHwqRTQycvwEgNJwiCqAzGbcyKnj/L9xWrmvC5N63Bho4aAJFK+P7+Gdz+yAH4giFcvbYFH7i4O2/HlS+oCCcIgiCICmHeHQAAWKt0Mb8uCAJqTVKBTn3hBEEQlQFLRm/JQyhbNMubqgEApyfCRfjvDgwjGBLx+jVN+O6N50KvKT9XFhXhBEEQBFEhzLkSK+EAUCsX6JSQThAEURmM5zEZPZpljVIRPjznhssnbRS/dEoaWXbD1iXQ5Mken2/K86ciCIIgCGIBtiQ94UA4nI1mhRMEQVQGhVTC60w6ft05M+nE4IwLfdMuqFUCLlxafr3gDApmIwiCIIgKgc0Jt1YlUMJNpIQTBEFUEmM2LwCgOQ/jyWKxrNGEGacPpycd8PiDAIBNnTUwG+Jfq0odUsIJgiAIokJIlo4OAHWyHZ16wgmCICoDZkcvhBIOhPvCT0048OKpaQDAxcsbCnIs+YKUcIIgCIKoAEIhkRfhCXvCaVY4QRBERTE67wYAtBRMCZeK8N5xB17umwEAXEJFOEEQBEEQpY7dG4AoSv+2JFTCpa+RHZ0gCKL8cfuCsHmkQLRCBLMBwDJZCf/HiQn4AiGYdGqcu6SmIMeSL8iOThAEQRAVwLxLUsENWhUM2vjjXqgnnCAIonJgoWxGrRoWQ2H02TUtFqgEwBcIAQCuWd8KbZmmojNICScIgiCICiDcDx57RjiDp6M7/Tk/JoIgCKKwjLF+cKsBgiAU5BharAY89IHzMTbvwdp2C9a0WApyHPmEinCCIAiCqADm3MlnhAOKOeHUE04QBFH2jNvYjHB9QY/jspWNBf3++aa8dX6CIAiCIACElfBE48kApRLug8iayAmCIIiyY2zeg0f29AMoXDJ6pUJKOEEQBEFUAHOu5MnoQFgJD4RE2L0BWMp4TitBEESlMuP04U3ffgEzTh8MWhVuvKCr0IdUUVARThAEQRBlzM5TU/jRC2fQUC1ZDRPNCAcAo04No1YNtz+IWacPFoMWDzx7CtV6DW7e1p2HIyYIgiByzZ4z05hx+tBqNeAXt17Ax4QR+YGKcIIgCIIoY+5/qhd75bmrQHIlHJAs6cNzbsw4fVCrBHztiRNQCcANWzuh18RPVicIgiBKA7tXGku2usVMBXgBoJ5wgiAIgihT7B4/DgzMRtxWk6QnHAj3hU/avTg+agcAhETp/wRBEETp45SLcJOeNNlCQEU4QRAEQZQpu05PIxCKDFdLRQlf0SSpIkdHbTgxbue3T1ARThBlxb6+Gdzx2CEMzrgKfShEnmFFeDUV4QWBinCCIAiCKDNOTTjgDQTxQu8UAODNG1r5QqvWlHhOOACs77ACAA4PzePEmKIIt1ERThDlxA+fP4PfHRzGRx7eD48/WOjDIfKIwyv9vkkJLwz0qhMEQRBEGXFgYBbvfGAnNnbWYMYpFc1v39SOaze24S+vjuKq1U1Jn2NDRw0A4NXhedRVhYv2SUe4CJ9yePHznX24fmsnOmqrsvtDEASRF1iLydFRG+758xHc984NBT4iIl+QHb2w0KtOEARBEGUE6+F+ZXAOAKBRCdi2rB7Veg22r21J6TnOabVArRIwafdiSlF4T9o8/N8/ffEsvv/sadg8Adz9trXZ+wEIgsgbM04f//ejewdx/ZZOnLuktoBHROQLh1yEm6kILwhkRycIgiCIMmLW5Yv4/3ldtWn3/Bl1aqxsNgMAREVLubInfH+/FPimVMcJgigtpuXP79IGEwDgtRFbIQ+HyCMOUsILChXhBEEQBFFGzMlF+JK6KmjVAq7f0pnR82xoty64jRXhgWAIh4fmAQDzLn+GR0oQRCFx+4Jw+qS+4K3ddQCA/ilnIQ+JyCNhOzqNnSwEVIQTBEEQRBkxKxfFN2ztxNF7r8a7Nndk9DwbOsNFeJNZDwCYsEt29N4JB9xyiNOc27fwwQRBFD3TcmaETq3CunYLAKBvmorwSoHS0QsLFeEEQRQtQ7MuDM+5C30YBFFSMCW8tkoHrTrzy/yG9hr+70tWNAAIhzgdkvvNpe9HSjhBlCKsH7y+Wodu2Y5+lpTwisFOdvSCQkU4QRBFiccfxFu+8yLe8u0X4A+GCn04BFEyMCW8tir5PPBErGoxQycX8ZfKRfiUw4dgSOShbwDZ0QmiVJl2KIrweqkIH5xxIxgSEz2MKBNICS8sVIQTBFGUnJl0Ys7lx6zLj3k3LfIJIlVYMFtNVfJ54InQaVT45BtW4M3rW3H12lYIAhAMiZhx+iKUcLs3QBtlBFGCsMkHdSY92mqM0KlV8AVDGCEHWkXglOeEUxFeGOhVJwiiKDk16eD/tnsCaKjWF/BoCKJ0YPbwWtPilHAAuP2K5fzf9SYdphw+9E07cXLcHnE/m9uPevqMEkRJwezoDSYd1CoBnXVGnJ50om/aic66qgIfHZEqjgwU7VBIhNNHdvRCQko4QRBFyemJcBFuIyWcIFIiFBIjesKzSaPZAAB4+tgEQiLQZjXAbJAWb3P0GSWIkmNa0RMOAD1yX3jftKtgx0SkhzcQxBu++Rwuuu9p/OP4eMqPc/mDfPwkKeGFgYpwgiAKzl9eHcFlX3sGrw7N8duilXCCIJJj9wTA2jlrFtkTHg1LSP/DwWEA0vxx9j0onI0gSg9mR2cuFtYX3kfhbCXDztPTGJ33wOYJ4IMP7cODL55N6XGsH1ytEmDQUjlYCOhVJwii4Pzh4AgGZlx4+tgEvy1CCffQAp8gUoH1g1fp1NBrsjv7tVEuwsds0piyq9e1oMYoKWjzNKaMIEoOFsxWZ5I+xywhnYrw0mHHUUn9brFITqWvPnEc3kAw6eOYhd2kU0MQhNwdIBEXKsIJgig4bAzZhDz+KBgScUaxCLBTEU4QKTGbIys6EFbCAUCvUeHKVU2khBNECcN7wmU7OlfCaVZ4SRAKiXj6mFSE33fdetSbdPAGQjg8NJ/0sZSMXnioCCcIouAMzUr9ZxOywjY064IvEE5btrnJjk4QqcCK4Wxb0YHIIvzKVU0w6TWwGqkIJ4hSZZrZ0U2yHb1BCmOjMWWlweHheYzbvKjWa3DRsnps7a4DAOztm0n6WIeHQtkKDRXhBEEUFJvHz3u+mRJ+WtEPDpASThCpklMlXLY7AsA161sAhIt9CmYjiNJCFEVMRQWztVmN0GloTFmpwKzol69shF6jxvk9chF+NoUi3EtFeKGhIpwgiIIyPBu+0E/YJSX81ERkEW6jYDaCSInZHCrhzXIRrtOo8Lo1zdL3YT3hLuoJJ4hSwukLcscZU8JVKgGdtUYAwMBMOCFdFEW8NjwPjz95rzGRHw4MzOI3+wcBAK8/pwkAeBG+v28WTm8A/7d/iLsdomHjydiECyL/UBFOEERBGVIU4ZN2L4IhEacnpH60Kp0ULEXBbASRGrkaTwYA53bW4P3buvCla9fxPkJSwgmiNGHFWZVODaMuHOK4RJ4PrizCnz42gbd850X851+O5vcgiZg89vIArvv+TozbvGivMfJN0TWtFlTrNbB7A3j3D3bhzt+8gq8+cTzmczi80oaKSUdFeKHIeRH+wAMPoKenBwaDAZs3b8YLL7wQ976/+93v8IY3vAGNjY2wWCzYtm0bnnzyyVwfIkEQBWBf3wxmnT4Mz4Yv9CERmHZ6+XiyjR01AKgnnCBSJWxHz74SrlIJuOfadbh+aye/jXrCCaI0mXJEWtEZsYrwl+Ue41cUY0SJwvGD585AFIG3bmzDXz9xCSwG6TysVgnY3FULADg6agMAvNg7BVFc2N9PPeGFJ6dF+GOPPYZPfvKT+PznP4+DBw/i0ksvxTXXXIOBgYGY93/++efxhje8AY8//jj279+PK6+8Em9961tx8ODBXB4mQRB5Zu/ZGbzrB7vw6f97lSejMyZsXm5HP3dJDQDqCSeIVAnb0bOvhMeCfR9SwgmitIgOZWN01rFwtnARfmLcDgAYmHaBKCwTdg/OTjkhCMCX3r5uwbmeWdIBQBCAkXkPBmcW9veH09GzO8qSSJ2cFuHf/OY3ccstt+DWW2/FmjVrcP/996OzsxPf//73Y97//vvvx7/9279h69atWLFiBb7yla9gxYoV+POf/5zLwyQIIs8cHpbGZ7x4ahJnpyIv6q8Nz2Pe7YdKADZ11gCgnnCCSBVuRzdlXwmPBbOjU094afNC7yRe7J0q9GEQeYSNJ6s3xVbClUX4yTGpCLd5AvwcQxSGfX2zAIBVzWbuRFLyto1tWFJXhY9ftRznLZFU8d1npxfcj4LZCk/OinCfz4f9+/dj+/btEbdv374dO3fuTOk5QqEQ7HY76urqkt+ZIIiSgaWuevwhvHhqEgCgUQkAgBdOSQvB7gYTGuSRSKSEE0RqzDrzrIQbqSe8kLh9wZhW03Sf49b/3YebH9xDSmcU33m6Fzf+eDfcvvILJJuWi/C6qCK8M8qObvf4MTLv4V/vp/dIQWHJ50rFW0lnXRWe/7cr8f+2r8IF8n32nFmYls6VcApmKxg5K8KnpqYQDAbR3NwccXtzczPGxsZSeo5vfOMbcDqduP766+Pex+v1wmazRfwhCKK4USaie/xSOuvaNgsA4CW5CF/dYuZ9TjZa4BNESuQymC0WVqaEu/0I0VzhvPLEa2NY8x9P4Jd7Y7f4pcqUwwtvIISQCDy8uy87B1cGhEIifvj8Gew8Pc17ossJpoTXVccuwmddftg8fpwcj5xWouwVJ/IPey+ymeCJuHBpPQBg95mFSjhLR68mJbxg5DyYTRCEiP+Lorjgtlg8+uijuPvuu/HYY4+hqakp7v3uu+8+WK1W/qezszPufYnK4eyUE9/ccRJ3PHYI8xQYVHSMzC/sTzpXtk2xgKeVzWZY5B1ahzdAC3yCSAHWE56LYLZYMDukKAJ2ahvJK6xgZhuXmTKrsBc/9vIgXD76PQLS5A5m2e2bdhb4aLLPbJwNu2q9hlvUB2dcOCn3gzOoCC8cdo8fx+TAtXhKuJLNXbVQqwQMz7kxNBv5e2Pna0pHLxw5K8IbGhqgVqsXqN4TExML1PFoHnvsMdxyyy349a9/jde//vUJ73vXXXdhfn6e/xkcHFz0sROlzR8ODuPKrz+Lbz/di98dHMZj+xanEhDZR6mEA4BZr8HypuqI21Y1m2GRF/ghMbxrSxBEbDz+INzyHN982dH1GjUfJTjnpl7RfDHn8mG3bDEdVViFM2FWsVFt8wTwh4Mji3q+coGlSwPSxn65wTa8a2L0FYfD2dw4IfeDs5ax/jLckCgV9vfPIiRKffvNFkPS+5v0GmzosAII29gZTuoJLzg5K8J1Oh02b96MHTt2RNy+Y8cOXHTRRXEf9+ijj+Kf//mf8ctf/hJvfvObk34fvV4Pi8US8YeobPbIJxqdRnp7Hx2hFoViwuMP8l40dlFvrzWiyRyZ0LqyxQy9RgWtWroPqWwEkRi2qFarBO4iyQc1NKYs7zx9bAJB2R00vtgi3Bm5efLInv5FPV+5cHwsvHboK8MinCnhsTbslOFsvRNSEX7BUkl5JSW8cLBQtlSs6IxzWqW6qC+ql98pzwk3U094wcipHf2OO+7AT37yEzz44IM4duwYPvWpT2FgYAC33XYbAEnFvvnmm/n9H330Udx88834xje+gQsvvBBjY2MYGxvD/Px8Lg+TKDNYiBcLpDg2ak90dyLPsJFkJp2aJ3d21BrRpNjV1WlU6KqrgiAI4b5wCmcjiITwRbVRm1LbV7aw0piyvPPkkbDLcMLuXVS7DnvfrG+XFLNyVH0z4ViZK+HzCVpXOuuMAKSC+8SY1BP++jWSi5XC+wpHv7wBsqbVnPJjmszS2mrSHrlZR+nohSenRfgNN9yA+++/H/feey82bdqE559/Ho8//ji6uroAAKOjoxEzw3/4wx8iEAjgox/9KFpbW/mff/3Xf83lYRJlBhtnxYrw05MOeAPll2xaqrBk9LYaIy5Z0QAAWNViRrMlrIQvb6yGRi2dntguLSnhBJGYsLKVn35wRlgJJzv6YggEQ/j1vkF8/NGDCS2/Ll8Az52cDD8uJGLK6c34+zIlvKu+Sn7+IALBUMbPVy4cHwtv4A/OuuEvs9eE94Sb4ivh+/tnMSXPE3/daqkIH7V5aE1VIJjIZInRQhCPJnltNWGLPEc4aE54wcn59sftt9+O22+/PebXHnrooYj/P/vss7k+HKICYCeplc1m1FRpMefyo3fcgXXyLj9RWFg/eHutER+5fCm66qtw1eomGLRqCIIU8LSqJbzLyy42lJBOEImZ48pWfvrBGTWKhHQiM06M2fEvv9iPM7LiuqzRhE++fmXM+77cNwtvIISOWiN8gRAm7F6MzXu44pUurCecFV6AtOkZqzirFBzeAB/FpVEJCIREDM260dNgKvCRZYdQSOSf11ibdqwnnPXFr24xo7POiCqdGi5fEEOzbixrrF7wOCK3MDEinXYj1uo3YQ8X4aIoUk94EZDzdHSCyDesWLMYtVjTIvXCKANWiMKiVML1GjWu3dQOs0ELrVqFOrl4WNkcLsJJCSeI1EjU45lLWLE2Zc9cja1k5l1+fOjn+3gBDiQ+37Ee8BVN1Wi1SoX32CL6wtn7pqFaD5Mcslfp7T8n5H7wZoueh4aWU1+4zeMH62CoMS48X3TXhzcbVjRV439u2ARBEPhGDVnSCwMTmcyG1JVwFuA2bgufI7yBEALyG4CK8MJBRThRdrDFi9mgwRo5kOIYFeFFw5BchLfXGBd8rUO+wLOZ4QCoJ5wgUmQuz+PJGK3yIm/MtriAsEokFBJxx68PYWDGhY5aIz54cQ+AcHJxLJj1vM6kj7nAThdWhNeZdHxxb3NX9qYny5JZ02rhBWk59YUz90O1XsNDbJW01Rhx5/aV+PQbV+HPH7+Er6VYEU4J6YWBfS4taRThTAmfcnh5mKPy/EIjygoHvfJE2cGKNYtBy8MrqAgvHkYSFOFffvs67OubwSXLG/ht7GJDSjhBJIb19ubbRtwiq7GLHZVView8PY2nj09Ap1HhB+/bzMcIOX3xe25nHNLvub5aB5Pcz7mYDZBZZ9iWbDFqMGYLK26VyjFuww5vCJfTrPBU8iM+dtWKBbex3IDBqDGjRH4IK+Gpl2/11XqoBGnU67TTiyazgfeDV+nUUKvyF+JJREJFOFFW+IMhePxSeIpUhDMl3A5RFPOaGEzEhqWjt9cuLMLXtVsX9O6ziw31hBNEYpi6le9gtlar9FlejCW6UjkwII0cumZdC9a1W/lIzURK+IwzrFwzZWsxGyA8oKtKR84jGTaGa3lTNYIhaU1RTkr4XIYhjo0KVZXIL8GQyDfn0inC1SoB9dV6TNq9mLBJRTg7X8SaEU/kD7KjE2WFUi2tNmiworkaGpWAebefVJoiIBgS+UK9LYYSHgsezEZKOEEkZE5RTOWTFqu0MC9HO7rHH8Rdv3sVTx8bz8nzvzokjWDd0FEDAKiSle3EdnRZCTfpeE949uzobNOzss+3k3K+QaNZz+3oZaWEOzMLcawzSZ/1GSdNQsg3DsUaKJ2ecCBsSWfv6xd6pekKW3tSnzdOZB8qwomygqml1XoN1CoBeo0aSxulC+jJcZoXXmgm7V74gyLUKgHNZn3yB0ChhFe4MkMQyQgrmvlVN1pkJdzuCXCbY7nw7IkJPLp3EP/6q0MR6t/RERu+9VQvPP7FjWo6PDwHANjQITmAWEiS05dICZeOo75ahxbL4oLZ3L4gd49JdnRSwoGw0ttYreeJ6MOzbvgC5TGmLNMQx3q51YWK8PzDPpN6jSpmH38iWBHONuvYiMPLVzZm8QiJdKEinCgrlKFsDGafmqUZtgVndF6yojeb9XwOeDKoJzx/vNw3g2/uOEkzgkuUOW5Hz68SXq3XwCwXj+VmSWcOKoc3gG891ctvv+9vx/A/T53EX18dzfi5J2wejNu8UAnAOXLrFAtJcnmT94TXmfRo5kp4ZvZgdl3UqgVU6zUKO3rlnm8DwRCm5SKzwaxDo1lKjQ+JYZt6qZNpiGMdFeEFw5bBjHAGG184Yfdi0u7Fa8NS28ulK6gILyRUhBNlhTKUjcEWpMx+RRSOaQdb2KSmggPUE55P7vnzEXz76V48fXyi0IdCZMBsgezoABTFYHkV4cri9pd7B3B60gEg3B98YhEOq8PDkhV9WWM1V8BZ0Fo8R4EoirxArDeFlXCHN5BRmJpSERUEgc63AGZcPogioBKAepMegiCgi1nSy6QvPFMlnBXh004fRFHM+nER8YklMqVKs4XNCvfgeVkFX9du4SIVURioCCfKiljJkWynd46U8IKjDBRKFdb7VG4212JDFEWcnZQWmCwciigdQiER8+7CjCgDwHuTR+c9uOPXh3D1/c8v2qpdDEzYpU0FjUpAMCTiJy+cQSAY4gp57yKKcNYPvr4jHEbJlfA46ehOXxBe2RItpaNr+PUukw2QcG+w9J5hKlslO49Y32ydSceTo5klvVz6wherhPsCobjv0XJHFEV4A/n/2cNFePrn90Z5s27C5uVW9CtWNmXv4IiMoCKcKCv4DEWFXYepQiw5WMnQrAt3/+kIzbzME9MZFeHSAtNRwYvCfDDj9PHkVRrpV3rYPH7IQdl5t6MD4IrsiTEbfn9wGMfH7Ogdd+T9OLLNhKyEX7VaWrAeHbVjdN7DU8l7JzL/GZkSvkExEYIHs/kCMZVGZkU3aFWokgv2cF94+pb0aPdEJaejO7zSaz7FHFvVYZWwu0EazVUuCelz7sxcM1U6NfRyP3KlWtI/8NDLuPi//pH3MX7MnWLJQAlnPeEj825ehF9G/eAFh4pwoqywxVDCuR09hhL+q72DeGhnH36xuz8/B1jh8EChNIrwatmmSUp4blH2Oh4foxDDUoNtMpp06rRDe7IBU8IfPzwGVjvOlIH7iKnLFy6tBwCcnXRgUPFZGZ5zw5UgRC0eoijyIny9nIwOhM93ogi4YzgJpvk5NFwghue0pz+7OboIz6Ud3RsI4oMPvYy7/3Qk68+9WPb3z2LjPX/HN/5+MiIZndHTUA2gfIpw5Wz4dBAEgV+/pyuwCA8EQ3ihdwpTDl/e3wv2GO2WqcKK8NeGbZh3+9FQrcfmrtqsHh+RPlSEE2WFLUbPTNiOvnBRwRaJsVRyIvuElfDU+5CqDeEiPBSiHrRcoSzCB2Zced/lLwUePzyKe/98tCiD6zLt8cwWrCd8eC5cCM6WwSKdFeHn99RBEKRrzKGhOf51UQTOTKa/GGcBScpQNgAwatUQJAd0zI1HlqtRXx3+PTdbMu/H53Z0ubDKpR19z5kZ/OP4BB7a2cfno6fKiTE7rvz6s/i//UNZPy4A2N8/g2BIxAu9kxHJ6IweWQkvl57wxYwzZO+Vcvh8p4vSBZPvMX6L6Qlvks8RjDetb+GtFkThoCKcKCti7RTWJlDC2W5/opmsRPaYUQQKpQpThoDEY3uIxTEYlfpLI/0W8tUnjuPBl87ipdPThT6UBfBFtSn//eBAWAlXUuoTKTz+IN/Y7ayrQps8io0FGzFOZWBJZ5sVrVYjjDo1v10QhIQJ6bFyNZjKxWzU6RA91s6Sw5GQe8/O8H8/8MzptB774ItncXbKid/sG8z2YQEI94H3Tbv4v5UBomxW+Mi8pyyyDmZdmSnhQGQ4W6WhvE7mu2XD7s28CFduKAHAm9e3ZuWYiMVBRThRVsQKrqhJoISz+5PVOT9kEsym16igVUs7tvR7yh3Ro3eOjlIRHg1Tfl4dnCvsgcQgHLBVGCW8xWJccFupK2WsH9ygVcFi0PBwrv39korLlKTeifQ/KzMxFG1GlS5+Qno4GT28qGa2aVY8psNCO7rcE54DO/qes+HNq6eOjeNEim0v/mAITx4dA5C7YLQJ+bWbd/v5poqycKkz6Xjx0z9d2mPKPP4gb3XIxDkTnhWe2Vi8UmZwVlGE53mCAPt+mQSz6TQqvtHWZNZja3ddVo+NyAwqwomyggdXGJV29ARKuIeU8HzCrJR1MRae8RAEIdwXTuFsOYMV4W2yonmcwtkiCIVErkS8IqdaFxOFtqO3xFDCS70nfFxORm8yGyAIAi/C/UHJjrp5idRTeXTEho8+cgAff/RgymObEm1IsvNdrPRpnquhOIeyALFJRyZFeLQdPTftPx5/EK8MSp+bjXIa/A+fT00N331mmm+ij9u8ObleKzcwDsibLA3m8Gus/P2Xel84ey3VKiGjkC/WTlaJSrhys3o+z0U4E40y+Z0B4baVN61vhYqs6EUBFeFEWRFLCWdFuMsXXDBWgpTw/JKJHR0I94Xb6feUMwZnJHvs9rUtACicLRq7N8ADxw4PzxX0WGKR6cihbFFbpV0QCMfU+VKF9VizGbusCGNcKSemP3NiEn89PIo/vzIS0ROfiFiKNoMnpCfoCVcW70wJn8pECXdG29Glv0NiuP1n2uHFgy+ezSiAjnFgYBa+YAjNFj3+3/ZVAICDA3MpPfbxw2MR/8+FGj6heO3YdaaxOnJjiVnSS31MGd+wM2ohCOkXY3Vyy0upO10ygV0ngdh29MEZF772xHE+2jCbhIOHMzvHX7m6CWaDBjdesCSbh0UsAirCibLCxnvCwzuFZoMGbNMv2pIe7gkv/R6vYsftC1vg0rGjA4BZT7Nrc4kvEMKInKy8/ZxmAJISXglBeC5fICUbr9J6OG7zZhSClUsKrYQLgsD7ws9bUgOg9EcYMTs6CzXqaYwuwheO+BlI0ao87VioaDNYT3isDIxYYx4ztaOfGLPz7Aemkhm0aujU0tKQ9cN/95lTuPcvR/Gj58+k9fxK9pyR+sEv6Knn75Nk74+/HxnDgy+exZNHxuRjk44rF0p0rNdOqYQDQDebFV7iSnj4XJFZMceU8FL/fGdCpB194efzh8+fxgPPnsbDu7I/cSdW8HA6fObq1XjlP7ZjZbM5m4dFLAIqwomyIpYSrlIJcceUkRKeP9hoHZ1aFRG2lgrVNCs8pwzPuSGKUjLz1p466DUqOH1BnMyg17VU8AdDeOils7jov/6BS7/2j6QL+2jV49Uis6QXWgkHgGs3taO7vgrvPV9SWko9mI3Z0ZvNUtG4VKGEm/UarGo28w1fjbzT25diEZ7Ijm6Sz4+xlHD2uIbqhUW43RtIOTTM6Q3gXx7ZD28ghMtWNkYktDNLOgs6ZYU664XPBBbKdn5PHf+Z591++ONMGth1ehoffng/7v3LUcw4fait0uJq2aWT7SLY4w/GtBZHh1n1lMms8PC5IrMNu1jBbHMuH+YrYMpMMiW8d1zKE8hkYkIy7ItUwgGQDb3IoCKcKCtiKeFAeMdXaY/0B0NcmXV4Ayn38hGZoVx0pmuBM/NZ4eV/kS8ErM9tSV0VtGoVLlomzUR++thEIQ8rp3z97ydw95+PYs7lh8cfwrMnEv+s0arHq4oxVcVAdMBWIbjjDSvx7KevxBq5oCvVIvzJI2P4+pMnMDQrLbibZDt6e42Rh0R21FVBEATc984N+PhVy3HD1k4AQP9MaovvWIo2I1yEx5gTLivoyjGPZr0GerkVIFU1/L+fPIEzk060WAz4n+s3RizOw+Fs0nu+b0o6P7w6NJ/RddIfDOHgoFTAX7i0DjVVOj6GLVZgaiAYwj1/lmaJr2m1YGt3LT73pjVY3iTN6j6T5SJ4KkYvvVolLPgslYsdfUJ28cRyYaQCexy7pnv8QbzpWy/gLd99Ie6mSjng9gUj3iuxNm7YeyMX7xHeE27MTAknig8qwomyQRRFxUkqcqeQXUznFItCpbU5GBLhDZTvxaMYSLToTAbvCSclPCewIryzTlJ6Xi9b0p86Nl6wY8o1z52QxkytbJYW9vuSqHzRqkexhbMtZuRQtgnPEfaX5Obm3X86gu8+cwp/OzwKINwTrlGrsET+jHTWSmnwb97Qiv+3fRWWNUrvo1Tt6InyMUy62D3hoigqeskjQ8PSDWdjY9buftta1EcpvnxMmdsPXyCEUblVZd7tR/+0Cx/95QG8/Xsvpay6nxizw+MPwWLQYGlDNdQqATXyNTqWpfnRlwdxfMwOi0GDR269AL+57SK8e0snehqk1zjbSjTrB1fuDdebdAtUw45a6Xc/bvPyWdGlCHNrsE2FdGHrKfa7Ozlux8i8B4Mz7pK36idiaDbysx2dju70BjAut7D0T7uyfu6LNYKXKG2oCCfKBpcvyC+M0T0zzKI5q9h1t0ctqsmSnlsSjeRJBk9Hp99RThhUKOEA8Po1UhF+aHAuJwEzhSYUErlS8cGLewCEE5HjwRZcrPg5PDRXVAXmXBEo4Yw6+Rh8wRCcMRK+i5lQSORFGauzmB0dAC8E2YYVo1u2KmfDjl7Fe8IjXzspXFTaLI4+j6bTF+7xB/n7n/XvK2Gb2DaPH0OzLijrzV/uHcBfXx3FocE5HB5ObSPqkDzSb2NnDS9sw5bmyOMVRRHffroXgOSsUL4+PTnqyWav2cqmcK9sQ/XCwDyrYnM/ev1QSnDnU31VknvGhp0D7Z4AfIEQjikmaZRzoGf0GE/Wo82uA0r12+ENxEyP//uRMf55SAdfIASPX/rsZ9oTThQfVIQTZQNTSTUqAUatOuJrsXrCo+2l1G+cWzKZEc6gnvDcwtS7JXWSutdsMWBjhxWiCDxzvPws6WM2Dzz+EDQqAW/e0Aq1SsDovAcjCZKtmfVwa3cdtGoBsy4/tysXA8VgR2cYdWoeolVqCcrzbv8ClZMFswHAG9c2o1qvwZWrmiLus6ROKhAHpp1w+QL4/O8Pc7U5Fqz4jJWOXh0nHZ2dQw1aFS/UGekU4WennAiJkuLNHqfErHAe9UcVHj976Sz/d6oFFys6NnXW8NvqFG4JJR5/iP8M123uiPga2+iYdfkjXG2LhW26dNVXcddDrNdFp1HxtUW+x1NlE1YsZqqEW41aqOXNlFmXD8dGw+8Dlh9Qjgxyx5h0nbS5/XD7gnj9N5/Dxx89yNs2GNHz5A8PzePDD+/HOx54Cf+z42Rabgrlpk+6mTpE8UJFOFE2hEMrNAt6jpkSHmlHJyU8nyzGjm4mJTynxFJGmBq+42j5FeHMzrqkvgpmg5aHUiWypDPVo8GswwpZMTtaJLPU3b4gV0lqTcVhVayNE4ZZ7LCezyqdGo1mPepNOnTI1nMAePeWTrz6xe24ZEVDxOM664wQBEm9/sGzp/HIngH8xx9fi/k9XL4A/33VxXAGVeljp6OzY4tVuPMxZSnY0VmhtLLZHDOfw8J7wv3olz8rLHiOzUgHgJMpFuGvMCW8o4bfxq4DM1FKOCtu1SphQbFRpdOgRd4QOT3pzFoQGCv6G816dMmFaSwlHAir4aVahAdD4gLnU7qoVAJfU804fRHnwRNlrIQPypuua1ulOfc2jx/Hx2w4PenEn18ZwcGByOtHf1Rf+OOvSe0togh86+lefOXxYyl/byYyVenU0KipdCsX6DdJlA08lM24cBEaVsL9C+7PiJVES2SPGa78ZG5Hpznh2UcUYy/KXicX4S+emiy7UWWsCO+RF9ybu2oBJLakMzu6xaDF2japaD8yUhxFONtEsRg0i0rOzSbRfaOlwpTcNtNiNWDHpy7DU3dcDkOUsypWwrBeo0abVSrWf7l3EIBkTY9lnWazvnUaFe//VhIvHZ33kcco3FmSdypKOEtwXhFnVJHSjs6U8MtWLhzHlkrBZff4cWpS+n4bI5Rw6XijLbvKcNVYGwRMDf/nn+3Fuf/5d+zrm4n4+tERW8p9+YxJueWmyWzgCfgsjC+aUi/CR+fd8AdFaNUC2mqMyR8QB/b5nnb4IuzopaaEf+fpXnzk4X0pBcqx6yQ7/3v8oQiL+h8OjUTcX9maIooinnhNGrV35Srps/RMkjBQJTzvqEjO70R2oCKcKBsSzVCMFcxmi7I2k8qaW8J29NiLm0RUyxcesqNnnzmXn29usOAhAFjWJC1GPf5QyS4448GL8IbIIjzRCCblJt858iLsaJEU4Uxx6W7IzF6aC7jduMSUcGYTb6jWo6ZKx0PmUoFtYinV6Fip+8pQtliFJivMXVE94YncRA1p2NF75dGDK+S08WiY88juCfCC9spVjfy4XrdasuIfH7MlzUU4PDQPUZSS5ZUW7zoTm1gS+f5g5xprjM10INyTb/cEEBKB3Wem+dcGpl14+/dewnU/2AlvIPUsAqUS/s8Xd+PaTW24fktnzPtaq0q7CGcW6c66Km4pzwT2Hjw8PA+7JwD2VP0zLrhLJAfC7vHjW0/34skj4ylNu2AF9zltFh7ip9x0YJ/79e2SUq5UwnsnHDg75YROrcKn3rASADBhSy1EEQhff6gfvLygIpwoG5RKVTSxgtmiky2pCM8ti0pH10fOrSUW4guE8NdXR9N2dLCFRbNFH6H46TVqvhBOxeJaSjB1sjuqCD86aot7HmAZEpISLi2yjo4UR0I6W1h3ZdjjmQtqud24tD6zU3ZWhKd/nmIqrZJnY/SFJ8vHMMVpv2EKeqzHNaaRjs6U8JVpKOE9DdV495ZOtNcY8YW3nAO1SoDNE8CYLXFw40HWDx4VABdPCWcW83hF+Fs3tqKnwcTVyNOKecz/d2AIvqDUU/7sifj9+NGwnvAmsx6rWyz41nvO5Rt00ZS6Es7PFRla0RnMjbHjqKTurmw2o96kgyiGN3mKnV2npxGQXV7JCmJlmOfSxmq+UXVS/iwpYUq3UglnKvilKxqwVJ6k4PAGUl532qkIL0uoCCfKBtaX1GpdaLGKFcwWPe4q1kxWInskslImg114aKMkPo/tG8RHf3kAX/pr6n1mQOSM8GhYIZLq7OFSgSnhzHraVmNET4MJwZCIJ+XFUjRhJVyDNa1S8TIy7ymK4LFw0NLiFtbZhG98FsHrkw7hEWDpO3ZYOBsQDiHbdXp6wSivKT7rO04RLoeuuaKuSTMKlT6aVHvCvYFwMvqK5thKOBtzd3rCyc8PXfVVuPtta/HSZ69Cd4OJF6nJwtlYP/gmRT84EG5Lim5XYMVtrLYyALhoWQOeufMKfOJ1KwAApyakIigUEvG7A0P8fn88NJzwuJQolfBklH4RLv3uF7thd+HSegDAgYE5AJI6vKpFOi+WSl/4C71T/N/JNq8m7F54/CGoVQI6ao38/RnLfn+5XIQrlXBWhF+9rgXVeg0XFsYVm1gPvngWb/3OizGvt2GnJ9nRywkqwomygaU4sxOgEhZWNJegJ9zhLc2Laj6Yd/vxp1dG8MyJCQwnSJBOxEwCFScZfEQZ2dHjcmJM2oTacXQ8rR7u6BnhStKdPVwKBILhPj6lffud57YDAH6zfzDm45ROG7NBiy654C2GcLaiVMJLNphNOt54wVyJUG6CfOjSpWi1GuANhCIs00DiGeEAYJLT0Rco4QkU9Ca5gJywefG+n+zBjT/ejUCMPtczk+Fk9KY4RefFyxtQpVPjxLgdvoA0RaDVaoi4TyoFlyiKvEhT9oMDSqdEnJ7wOEU4g81lPz3pgCiK2Nc/i6FZN7RqySf81LGJBdf4vx0exZf+cjQilToUEnnRE68PXEnpF+HhTZXFcMPWzojAwnNaLdxZUSp94S/0ht0SyZRwtnHVUWuEVq3ijsvosWXNFj3WyEGfcy4/5l1+jNs8ODpqg0oIB56y95qyCH94dz8OD8/j8cOjC74/28yM5xAhShMqwomyYGjWhZPjDqhVAi5fsbAIb5LnvM66fNzuFq2EO0gJj8v/7DiJTzx6EB/42cu45Kv/wGspzodleANB3necSTAbH5lDSnhcRueki/mUw5tWYFiipNwGrq6VViGViKFZNwIhEQatiictA8A7N3dAEIDdZ2ZiBjvZohQ6lqheDH3hxaiEl2pPOE8gz8CxwzZB1CoBl6xowBXyhvBzUZb0ZPkYzI7u8sUOZovZEy5vGngDIbx4ago7T0/j1Rjn6WTJ6Oy5PnTpUv7/jlrjgkTm1c3Ji/DTk05MObzQaVTY0GGN+FoyJTxZsdFVXwWNSoDLF8SYzYPf7pdU8Ldvasfypmr4AiGuPjL+409H8JMXz0aMjptz+7klORX3Ay/Cs5TMnm8WO56Modeocef2Vfz/a1rDSngpzAofmHZF2MUn7InbKlgLE/uMW4zSZ5RFIrANrZ4GE6p04Q2u/hknXpbDA9e0WvjmE7v2sOLfr9gcPjCwMJuEvabL4+Q4EKUJFeFEWfCM3P+1eUktD05RUmfSYXlTNUQR2HVGsiCxRTUr8CgdPT7MVqUSpIvOi6emkjwiEuZAUAmZpXtWK+zoyYKAKpWR+fAiIp3U1UR2dNZnWk494cyK3l1viki5bq8x4uJl0tip3ypsrQxmB2SL8HBCemH7wr2BIJ9vvqSIivB4SmexM+3IvCd8TasZH75sKf7jLefAatTi3E4pa+CMom8ZUFje43yPKh2bEx7EM8cn8MPnTkMURd4THmsj06hTLxjp9VLvwvM0s2/Hs6IzPnTZUv59lsQo2FIpuPaclRwA53bWLEiYV27SKM/pqRbhWrWKv9+Pjdq4enjd5g5cu7ENAPDnV8Jp1ZN2L1e8lZvIrPiqM+mg0yRfEpeyEi6KYkR7wWJ528Y2qce5wYRNnTU8kOylU1MLUuuLjed7IzfGJpK0XLGCnW10Rr8/b7xgCQBga3cdgHDo56tD89jXNxvxNQBolotwpoQPzri4QyNWEc6uM+vaLQmPkygtqAgnygJmRb9i9UIVnHHJcmmBzfqAmBLOxspQER4fVoCsl/v60lXCWRFeU6WLOd4nGWa9dMETxYWJwYTE6Hy4TSBbRTgrRKbKqCc8Ohldybu3dAAA/vJq5KiZQDDErcEWeUOIJ6QX2I4+NOtGSJTnWmdgoc4VdcyOXmLBbOECOf3XUhAEfO5Na/D+i7oBAK010kJb+dkEktvRWTHtC4bwsV8ewH1/O45Xh+YVuRqxjy26pznWZimzI8cLHlMew2euWQ0AuGhZ/YKvM+vxGdkOHos9Z6RC7IKlCx/PinB/UIxwOKVahANhS/ov9wzC7g2g0azH+d11uFJOb1e6VJRjtJROoVF58zLVz04pF+GTDi9cviBUQuQkjExRqQT8/IPn4x93XgGTXoN17Va849x2hETgX391aEE7QDHxkvzZYKGcSe3oU5EOgmgx4bbLl+EvH78EH71yOYBwW+STR8awr38m4nsBYTs6CzbsU/SPD864I/rC3b4g3zxjoaBEeUBFOFHyePxB7DwtnVCvki++sbh0hVSEs4UJu0C0yL1uZHWOD1twXCwvxl4bnocoivjK48fwrad6kz6ejYarybCfyaBV8XEqFM62EJcvEJF3cGhwLiUF0h8MhVXUBD3h5aSEM/vs0saFRcjl8izk05NOrogCke85FoyzuiWczhws4Bx1ZdBSPHtxIWDhXjMlZkefXkRPeDRsDvPIXKTVNdmkiCpdWNF2ypuOZ6YcfHxavOKdFZJsw/nAwOyCzWXWHpCK9fr6LZ14+fOvx4cV1nT+vcxh+3usjVFRFLkSfmFP3YKvG7RqrvjPKNpdEk05iYYV4U8dGwcAXLWqCSqVwPMtpp0+/vMri/DXFO6VXtmez0YyJqOUR5Sx1qNWqzEl1T8Vos859167Fp11RgzPufHNv5/MyvfIBQflrII3r28FkDz3hNv45QkIysyCOpMOBq0a69qt3PFx9doWAFIwI9sM2tIdLsKbzZF29Gi3jFINPzZmQ0iUzknxchyI0oSKcKLkeWVwDh5/CC0WA1bFGbkCSLvxGpWA/mkXBmdcYSVcVitICY8PWxhdLC/u+qZd2Hl6Gj96/gz+56mTSUeHzTF1I0arQCoIgqAYU0a/p2jYIr9ar8HqFjNEMTJ0Jv7jJBVVr1HFTAZuLMOe8ENyWvPGqLRmQHJqrJRtui/3hRdBbDyZUavmi9dmiwEqAQiGRF4cFYK+qUibZLHArNazTt+CdPBixeMP8g2XTHrCo2EuK4c3EKEKTifpO9dpVNBF9WAfG7XD45eC1uIV7x+8pBtXrGrE19+9ER21RviDIvZG2YJZEc7CSpPRaNbHdC9V6dTQy5+FWBt+/dMujNu80KoFnLukdsHXlT+HcqOGfdZSU8IjC+fXrWnij2WPH5yVPh/KInxo1s17upmdflVzajbfUlbCh+XrRLsiUC3bmA1a3iv+SgqztwvBuM2DMZsHKiEs3Ew7vHE3U0VR5A6SWEp4s8Ww4DFLG6uxqtmMQEhESJRyFZSTe5j4w+zozKHFUBbhzLmxrt1SVButxOKhIpwoedjs7/ZaY8ITVLVeg3PlWaUv9E7xRVEr2dGTwhYcS+qq0C6rO9/4+wn+9bF5D05NOPCBn+3F/v6F/UxswZOpEg4oEtLp97QAZndttRp431kqCbVKK3qszw5PRy8TO7rDG8BJeYbtpqi0ZgZ7/V5WFC/K8WQMtUrgr08yK2MuCfd4Fk8yOiAFDzVU6xEIiXxMVbHDHB86tYrPAV4MRp2aOwKY4yQYEjEmW6BjjdNkVOkje6gPyotyg1bFFeRorl7Xioc+cD5arAauhkf3hbP2ADa2M1MEQeCKfPSsbyDcD76xowbGOMfLi3DFJl9adnRFSJVOo8IlstsNCDt7Bmek1/3YaOT5kPXYsvMk63FPRikX4ew9yK7huYKlpherg4qdj1Y0mdFZVwWVAIRERLiflEzYvXD7I238ymtBS5xU/avXtfB/b+mK3IhqZuno9sgi/MKl0vXnYP8cv+8Ruf2P5ZAQ5QMV4WWOLxDCztNTJaNEZAIryqJDaWJxyXLJbvriqUmuqLLRK6SwxsbjD8IbkBQYa5WWB4Ow0TOA1Ff3uwNDeObEJH6+q2/Bc7AFy2IWfnxWOP2eFsCS0VtrjDwQK5VFItvdjzWeDAino087vWURiHd4aB6iCLRZDWiKoV4AwPmydVYZLBTPIsv6+ibsHkw5vLjloZcjkpcXgyiKeOnUVNICthiT0QGpSLtAXlDuOVvcIU1/PzKGC77yFA/3qq/WZU1xYmo4+4xO2D0IhERoVEJMBY1h0kVez14dkhbi9SZ9Ssd2SVT7FYO1BtUusggHgLpqFr63sHhhv/MLY/SD88fHCO9LqwhvCBfhFy2rj7Dxd9ZJr/vAjAveQBCnJ6WeWjYq7ciIDcGQiN5x6fbVaRbhdk+goG0omTA8KxXhzP2XK1irw3SROqjYZ2ljpxVqlcAzFuKFs7F+8PbasI1f+f5sibOZds16RRHeHdmSwSb2jNukaysrwt95npRL8urwHPzyiEGuhFM/eNlBRXiZ84vd/bjxx3vw0xfPFvpQEhJrnmmqOGSViiVoJ+LSldLC5NkTk/wCypVwHxV3sWAqoCAA1TpNzAvB2LyH77L3RdmqAGDOvfgZl2E7eukpELlmRFbC26wGhVKT/P3MLJor47Rx1CvCk0pR+YmGWdE3yY6YWLDF0msjNu6OmY8aT8ZoUvT1/eHgMJ4+PoH7n8q8D/LAwCz+8y9H8f1nT+O9P96Nf/rJHrzvJ3sSnh+LcUY4g/UCM1W0WHl4dz/GbV585+lTALLTD85gBc+wfH5khVCL1cBzLmLBZoWzTWK2ERrPih6N0hHjDUib8L5AiPeY12bYGqSEFfKxii3Wc7u5O7YVHYhtRw9/1pJfz61VWv67el1UHkwnV8Jd6B13IBASYTVq8QbZsv7ayDz6pp3wBkIwatUxMzFifk/FOcBWYufEsBKe2w071mbh8gUXjNkrBphNfoPcksT6rOM5vmKNdVNuyLbE2Uxb1WzGhg4rdBoVLosancs2cH2BEEbmPTwg8PVrmmExaODxh3BizA5fIMRzTCiUrfygIrzMOTMl7fKmYk0tFP/+h8PY/KWneG9MujAlPBX74MaOGtSZdDxIRq0SeN+rk+aEx4T16FkMWqhUAtZ1LLwQjM57+Iiss1POBaopCw1bVBFOs8IX4A0E4QuEwkq41ZiWXZKl3Mcbe2LQqrkDoVithelwaFCy9MazogOSVbO9xohgSOSFBNuIin7/ssXbhN3LQ49eG7Zl5DzyBUK4/RcH8NMXz+KrTxzHbjlZ2u4N8AVaNKIo8uKuI4d9npnCUrH398/CF8h8ozWXBIIh3kJjz2I/OIOFs7GWkeEULcE1RukYbtrWFXF7qsfWZNajWq9BSAxv1DAVPNNRkdHEm/U94/RxZe/cBJ81lqDPHu8LhOCWPzupXituvbQH53fX4a3yWDLGEkURzjYb17SasVYeo3VkxMaLm5XN1SlP7dCqw+0ApbYxyd57uVbCq/UarhgXmxouimJYCZeL8EZz2NEUi76ofnAgckOWbZRFIwgCHv7gBXj6jssXjI/Ua9R8E2qvvElZW6VFnUnHJ28cH7Ojd8IOXzAEs0HD3R1E+ZDzIvyBBx5AT08PDAYDNm/ejBdeeCHh/Z977jls3rwZBoMBS5cuxQ9+8INcH2LZ8fcjY3hV3ulj/dLF3NP5Qu8U5t3+jPsG7WnY0dUqAVesDO9Img2a8AxqsjnHJFqZUCrh7KIwZnPzRabNE5nUDYSD2WoWob7wnvAy/T3tOTPNU/5TYc7lw4VfeRo3/XRPWAmvMaRchPuDIRyTF6FsvmssGnlfeHEtpjKBK+Gd8dU5ANgqq3cs1Cq8ERV5jmFF+LjNg0FZ4fQFQ2mP8AOAP70ygjGbB/UmHd5xbjtu3taFNnlxxwr8aOzeAC9uYwXrFZoVTdWoM+ng8Yf4NanYODJiW5DunUpyeKq0RtnRh+T3SbJwrDu2r8SHL1uKD17cE6Fap6qEC4LAJwCw5OVZxWZoJqMio6mTX6foIpxtdi1tNCVsQWJ2dlaoKcPrzCluEtx2+TL8+rZtC75Pp9y7Ozjr4v3ga1ot/Pp1etKBvbJlPtV+cEap9oXnqydcEAQ0JMgLKCT90y7Mu/3QaVT89843U+NkewzGGOOpdGo0xynCAcmtEa/di31fNsqvWx4byCZvHB+1RVjRKZSt/MhpEf7YY4/hk5/8JD7/+c/j4MGDuPTSS3HNNddgYGAg5v3Pnj2LN73pTbj00ktx8OBBfO5zn8MnPvEJ/Pa3v83lYZYVgzMufPjh/bjt4f0ApGRaoLiLcHYhiy7cUoUVZanY0QHwGaKApAZU68IzWZVqjSiK+OoTx2P2OFcSPJRKXhQ1mvXY0lWLJrMe77tAUmmG5zw8bAgAzk5HWtJ5MNsiinDeE17ESvjpSQd+/PyZtJVQjz+I9/9sLz7ws5fhTnEO+sGBOcy6/Nhzdob3X7bVKJTwJKOhescd8AWkHfZEVsxyGVM2Ou/GuM0LtUpIuOkAAJtlKy/bGAwHs0X3hMt2dLsXQ7PhQjlWOGEiQiERP3zuNADgQ5ctxf/csAn3XrsOK+Q2gcHZ2EU4O6+b9Ro+GqeYEAQBF/QUd1/43hjH1WDOphIeZUdnzoUkhdCFS+vxuTetgUGrxhKFAhdvPFkslsqLeuaIm81iPzgQVuWjCy3mIDkvTio6g7VznJWPj60FzAZNQqt+KrBz2sCMi48w29RZg0azHquapQkSD+/uBwCsakkv8KoUi3C7xw8bnwiTe0WV54kU2XWDWdHPabVwtZ63FcVZJ/MgRYWDIKInPEG2QyJYJsRL8uZ7j/x5XdMqnfePj9kplK3MyWkR/s1vfhO33HILbr31VqxZswb3338/Ojs78f3vfz/m/X/wgx9gyZIluP/++7FmzRrceuut+OAHP4ivf/3ruTzMsoJZwEbmPfAHQ2ElvMhOhIxQKNxrOpvhPNl0gtkA4LKVjfwCbzZoeO8dEJmQfmTEhu8/expf/uuxsgilyhRbjKCcRz98IZ779JVY0ypdGI4Mz8MfDL9G0X3hrCecWSwzoRTS0b/6t+P48uPH8OSRsbQeN2n3wuMPwRsIpbxhdmrCwf/NNo9arQa+0ZFsgchm5SbbYQ+PKSvOc0iqsIJ6VbM5blozY7k8f5glj8cNZouwo7v57ekW4c+cmEDvhANmvQY3XrCE386cJsrnVjIlv1cailAFZ7Bgrt1nirMvnG0OXLEq7JBqyKISHrajSwv54RSVcCVdik2y+jT61ZfK72OmhDM7+mI2Q5UwVX42ThF+boLsBQC4eLn03jg4OIcJmyfsusqCVb6txghBADz+EAZmXDAbNNh+jhSU9ek3SiO0WC5MqqFsjFIswtkYy5oqLUxZSP5PBk/OLzI7+gH53LxR0VbH+rPjXXtH+TSDcLFdY9RBrRKgEiKL83RgCens/M5cGlwJH1Mo4Uk2jonSJGdFuM/nw/79+7F9+/aI27dv346dO3fGfMyuXbsW3P+Nb3wj9u3bB78/9snO6/XCZrNF/KlkmCUYkE5+7KI75/LzcJZiwu4NgNW3s4tUws0pKuFWo5aPizAbNNCoVTBopY+CssBjcxq9ijCbSiRWAaJVq2DUqflFKVoJWVCEMxvkopTwcCptscIu1mzBk/i+bvzplREEQ2JEL9pUijOnlUU4Q9kTbvMEEm4eJesHZzTIatekvbAJ6YFgCKFFpBGzhc6K5uok9wS65P69oVkXgiGRK0jRYVFMCe8dt/NeVkA6d6TzWv3wuTMAgBsvXBLxOVNaamPBNlcbsxgklm2YGnp0pPiuzaGQyEfRffyq5bzdIJs94ewcOTrvRigkKnrCUw/H6lL0k6ZqRwfCytqZSaaES+fhbCnhdTEsx8GQyNs+zk3S9tFqNWJTZw1EEfj70fGYG76ZotOoeDI9ALzj3Ha++fa6NU18FBQQP5gyHomKcH8whA8+9DLe/+DeRZ2vsg2zorclGIuXTdhmUarXs3wQCIbw+GvSBvkliqC0pgQ94aGQyPOKlCMFjTo17nvHetz3zvUZbxopU9WvO6+Db8CubDZDEIAph48r96SElyc5K8KnpqYQDAbR3NwccXtzczPGxmKrRGNjYzHvHwgEMDUVu1fyvvvug9Vq5X86Ozuz8wOUKMoAn0m7N0JdnnL48NTRcXzxj68VTUiOMl10LkMlnPWEp7O7+4ZzpPcZsxHFUlmValb0Tj8gLTaG4iyOywlWgMRaGLXE6YU6Ox35uvARZWWejs56I1Ox4N39pyP4xKMH8Y/jExE78KkqB6fkhTVzbdZWaWHUqfnvKRgSE7oGwkV44h12Zkd/4sgYNt27Az96/nRKx5dNQiER7/rBLlz2389kPG6RWcpTeQ+2WAzQaVTwB0WMzLn5Aja6V5gt3lhPcb1JB51ahSmHj6voydjfP4u9fTPQqgV88OKeiK91Kiy1sWDvm2LsB2cwW/C005dyq0W+ODFux7zbjyqdGhs7anDbFcvQ02DiM7azQbPFAJUgTRiYcngzUsKV7SJp2dFZT/gU6wlnSniW7OiKYLZxmwef/NVB3P/USTi8AVTp1FiZwoYXm6X85JGxtMaTpYIyyOo9W8MOE0EQ8O9vPgcalYClDaa0Pz+JivBf7O7HP45P4LmTk3wGdDEQDmXLVxFefEr4ztPTmLR7UVulxeWKbKDGBHb0KacXgZAIlbDwPHv91k7coHhfpcs7z23H1Wtb8N0bz8U3rt/IW4qMOjUPgfMHRRi0Ku5qIcqLnAezRdscRVFMaH2Mdf9YtzPuuusuzM/P8z+Dg4OLPOLSZlShwA3OuuDxh4vtSbsXX/nbMfzvrv6szbJdLMqLWMZ2dE96dnQAeP9F3fjiW8/BHW9YFfFYZwwlHIjdr/61J47jkq8+g38cH8/ouEuFRCNjzAZtRCq9Ub6IKJXwQDDE1evFLP7qFYpsscKL8BTCaFhi8akJR8TFP5UCXhRFroS/93xpEcD6Rg1aNe91i2eXDARDODqams2NWZ3PTDox7/bjf3f2510RPzQ0h0ODcxiadfOk43SJN2YsFiqVgM7a8JzhE/J0iegAp+hRVksbTdxZkKolnfWCv+Pc9gVzo8MJz3Hs6PJ7pSGLym22sRg1/BwxPFdcm5Z7ZIv85q5aaNQq3H7Fcjxz5xVxZ8hnglat4j2nR0Zt3DERL1E5Fsrxc5ko4XMuP2acPn4dqzNl144+4/ThtweG8IdDI/jOP6Qxbxs7aqBRJ19iXr1WKsJ3nZ7GgHxOzFoRLjtJNnbW8MRpxrp2K5745KX45YcuTPt54xXhM04f/mfHyYj/FwthB0Zuk9EZDXxWePFcr/9wcBgA8JYNbfwaCUS2FUVf21g/eKNZD20K7+d06G4w4Qc3bcZbNrQt+JqyReKcVsuiMxKI4iRnRXhDQwPUavUC1XtiYmKB2s1oaWmJeX+NRoP6+vqYj9Hr9bBYLBF/KplRxZiv3vFIu+rYvJtf5E5OFMfIssgiPEM7ujc9OzogLYw+cHEPHxthilLCJ+yeiIVvrA2CF09J7gw27qJcSWYRVKrhW+RU6T7FmDKbwj4enS6dDswKNpbhKLtc4/YF+QI7lf5pVqiPzLkjlfAUFm5TDh/m3X4IAnDXm9bgs9esxj1vW8u/zn5X8cIOT0064PGHYNKp0ZNkvnRT1O7/8Jw7phU+FYZmXWklwDP+dniU/7s3w+8dr687Hqzw2Xt2BnMuP9QqAcubItUInUYVoUx21lbxTY1UjvPUhAM75NCoD1+2bMHXWREx5fDGVJFLQQkXBAEdbDNhNvZmQqFg53DWt54rWM/oy3L/eaNZn1aQntKOns4M8yqdhifsn51ycEdX9pRw6Vgc3gCODEdujl26MjU3QXeDCatbzAiERPz2wBCA1GaEp8K1m9rRWWfEndtXxvz68iZzXDdXIsLhl5Hn1289dTLiejfrLB7XFk9Gz9Mow3ihfYXC5QvgCTmr5e3ntkd8rdGshyBI2SrR6wtWhLfkycbPWK0IC6T54OVLzopwnU6HzZs3Y8eOHRG379ixAxdddFHMx2zbtm3B/f/+979jy5Yt0GqzszNa7ozOhRc50YX2ocF5BOQepegCvVDMZ8GO7uTBbJm/R6KL8AP9cxFfjy7C/cEQfw3H4szwLReSKYjKRcyFS+shCFKLAFMB2O+V9d9nSri30lOUQXnK90gyC14oJPLXZ3jOHTEaJZUC/rRsRe+oNaJar8Ftly+LmH3N+8JjKOE2jx93/uYVAMB5XbVJRxVdtKwBb1rfgv94yzncwveP4xNJjzEWH/vlQdz44z28ZzQVRFHE44fDm7OZbgDE6+uOB1OhWched31VzMJJWQB31FXxwiSV89mTR8YgisCVqxoXFPiAlKHANhdjtb6UQhEOhGeYD826MTbvwcO7+uDyFTbbwRcIYddpSQlXWlNzAbMAP31M+tykOyKqyazH6hYzOmqNC9wSyWA21tOTzqz3hFuMGmjk8wcLuPv6uzfiF7dcgA9fujTl53nbJkkJ7MuyEn7Jiga88G9X4dIV2f39MnfQ8bHIjYd/nJB+v3pZZZ3JcE2TC0bybkdngZ7F8Rq80DsFly+IJXVVOC8qMNCgVfPrZ/S1jRXlrVl0x6SC0nWVLLeFKF1yake/44478JOf/AQPPvggjh07hk996lMYGBjAbbfdBkCykt988838/rfddhv6+/txxx134NixY3jwwQfx05/+FHfeeWcuD7OsUPaE945HFuH7+sKjWHrLSAnnc8IXobIyNYup3wcHIq2k0YrimUknfEHJ6l+symy2YL208RZGSltld72JX6z65DFl2ZgRDoTHefgCoaKy+TGUxzSdJIxmzu3nybwjc+6I6QXKAn7e7ce3n+5Ff9TIN1aILo/TJ1YTxy4ZDIm45aGX8dqwDfUmHb741rWxHh6BUafGA/+0GR+8pAdXyeP9MinCPf4gDst96C+dSl0Nf23Yxq2UwMLzWqqk22/K1Mfj8iz11a2xF0JK63JnrRG1stU3FRWMvWcSBUMlCmdjC9x01NFCEC7CXfjak8fxhT8ewW8PDBf0mA4MzMLpC6LepMM5cX632eKNsuWatTWkq0YKgoA/f/wSPHXH5RE22lQIh7M5+cZQbZbS0QVBQK187WSbh+ctqcElKxrS2nC97rwOKPcCs1WE54rXr2mGTq3CK0PzfK0giiLG5c1UZiXOVFjIBSwsNG9FOE9HLw47OtuEWNduidneynKCdhyNbC8c5Up4fotwNqYMICW8nMlpEX7DDTfg/vvvx7333otNmzbh+eefx+OPP46uLmm28OjoaMTM8J6eHjz++ON49tlnsWnTJvznf/4nvv3tb+O6667L5WGWDXaPPyKI6WxUQrXSNn1qwlEUyZ3K4nbO5Utb4fQGgjxkLp2e8GiYHfG5k1Jxwfo52XNGK+HKHfCKUcLj2HiViaGtNQZ0y4s+5hRglr3FLqx0GhUvNkaL8DWPKMIdPngDQbznR7vw8UcPLvisKRcmw3PuiFRWZQH/m32D+OaOk/iu3GfJ4EV4DPUUiN+zeGhwFi/3zcKkU+Pnt5wf9/HxuHKVVITv65/lmzOpcmrCwTce0hnh9fhrkhWd2WrzZ0ePTK9eHadQVtr1O+uquNU3lYyLVPrUE40pKx0lnKXNu3FYvg71R12fsoUoiimdk1/olXJRLlnRkNQNsljesr41YiRSshnhsdCqVRnNgufhbJOOrAezAUCd4rl0alVEiFyqNFsM/NwCFH8R3mjW460bJfX+Zy/1AZDWMmwtwjbVimWzOBAM26zTdWFkCrtWzzh9RbHWZL+L6HBNxhvWSEX4zlPTEevosRjjyfJBZ20VNnRYsbK5Ou30fqJ0yHkw2+23346+vj54vV7s378fl112Gf/aQw89hGeffTbi/pdffjkOHDgAr9eLs2fPctWcSE50YaKc2wyAK7eANDtzqAj685RFgj8opj0KzOkN338xRTizI+7rm0X/tJOPhWC3RyvhRxXhUGWvhLuZjTe5Et5mNWK9vNj88uPHsL9/Niszwvnz14Qt6cWGsugKhETsPjOD3Wdm8OdXRvDrfZGBkUqLnt0TQN9UWOVUKuFsIy36s8rs6MmK8Dn3QgcHAJy7pDaj3fUl9VVY2mhCMCTihZPp9XYzRRmQVMhUF2bPyKr7bVdIPdNDs+6MrMxs0yCVYDYAWFIX2SsfVwlX2tFrjVxljNePryQVdZ4p4dEJ6aGQyDdsSkUJPzPp5Endozk6bz68ux8X3vf0gs9cNM/L79/LsmxVjoVKJeDf33IO/3+++nKBcG/pK0Nz/D1Zm6VgNiAyKK6nwZRxy9H1W8OTbVL9jBaSD1zcDQB4/PAoxuY9PAm9zqTjrq1YU1UKwfExO4IhESadOm/jDNn7IhAS096wzQWsNz1esOHypmp011fBFwxFBBezsb/5VsJVKgF/+tglePKTl6XtfiFKB/rNlhHxCpN4I01OZmjrzCbRSl26Fy2WjF6lUy8qPbK7wYTu+ioEQiLu+PUr8AdFbOqs4X1C0bayY6Ph127O5c94bFIpEC4UYm9ysIuTRiWg0azHR69cjq3dtbB7Arjpp3tweEjasFjMjHCGcuZusRGterAQJgC472/HI9Tv6L5v5c67skBnxXf0/NJkSrgljhLOWgSiVd50YEXLy4r2llRQpprPufw4M5Waoj0oF5+XLG/gKeCnJ9JXUdO1o3fUGqF0La5uSayEa1QCWq1G3m+bihKeylzkTp6QvnDsH9tozeZc61zAivBjozbuhhjP0UbaAdll8UqC3IFphxevjUiK/KUrsjeOLBFbu+tw/ZYOqFUCLujJbRCcknOX1ECnVmHc5uWFSLZ6wgGgTvHeW57CSLJ4XLW6iX++i3nuPWNduxXnd9chEBLxf/sHuWLabDFwi/5Mhi122eZ52fWxbVnuXR8MnUbFg1iLoS98Rj6GeOdKQRC4Jf0phSU9rITnN5hNeVxE+UJFeBnBQtk6onbZV0RdGJlSk6mtM5tEB0elO6bM7pUevxgVnMFUb2aVfd+FXbyPObpf/XjUmKRytaSHQiKfyx1PnVjZbIZaJfC/LQYt/veD52NjhxUuXxC/kRWpxcwIZ7AL4chc8b3e0UX4nrPT/N/zbj++qRhdk6hPbsbp5SoxC+NSjjDz+IN8w62nIT07OlPcWZ9oJjA3QrzxZ/GIDjFKxZJu9/i5O6bFauCbDizTom/KiS//9eiCAjUabyDIxzWmakc3aNVokRUtk04d18bJVK+2GiPUKoGfM+Zc/qTtNalsDCyJkyzOcgRqqrTQa9K3KecTZkdXkis3C3Mmjdvif8b2989CFIFVzeasjiNLxlev24DDd29fMOoulxi0amzsjHS9LDafQ4lyk39Fmu0tSrRqFb5343n41OtX5jytPluwou3EuIOHazZb9HwEXD6UcH8whB88dzrh1AnmWrosxcT6bMEcOsXQF85cQ4lG/L1OtqQ/3zsJURQhiiI/T+Xbjk5UBlSElyC+QAj7+mYWnNhG5JPFho7IC+6qqH6Sq1ZLJ5pMA46yyQIlPM2dYz4jfBGhbIzLV4VtiVajFm/Z0MoVg7mI5GsvJuxeCIJ0wQWK0x6dDRy+AJhrOF7x0lZjxF8/cQke+uBWfluVTsPthSw4LxsLP3YhHCsBJfyVQUlpu6CnDgAiEsFjjW1hhVhIlGzkoihyJdzuCfARVWyxp9eo4gYsxSvCmb29O8lYskSw90Gs5PV4iKLI3SNMeUylCB+XCyqzQYMqnQYrmqRz2clxB3rH7Xj3D3fhxy+cxf1P9SZ8HrtibFA65wpWAK9qMcdVkC5cWo+1bRbceIE0r52dM3zBEFxJ2mtSUcJZkFK0+2PKXhpWdED6+aJHSE7YPTnpFWXFd7R7RAlzga3Nc+qwIAio0mVn/FY6KJX3Kp06q5s2yqIm3YyJaC5YWo9/ff2KvKm1i4W5VAamnfxc1Ww28HNAPnrCv/VUL/7rb8fxr786BFEU4fAG8LOXzvIsFqc3gH39kmspH60XSoppTNl0kp5wANjUWQO1SsCUw4fReQ/mXH545T7/Jkvxn2eJ0oOK8BLk57v68K4f7MKWLz+FG364i4fzsMJkdYsFWnX4IrZCUYSrBODK1dKJuBiU8OgiId00UT4jPAtK+IVL66GT+9nevbkDBq06nHSs2BxgxURXXRWWykrkeJn2hbMiQadJHAq0usWCJnPkTrEyaAfITk84s76PFOGmR7SLg2UwXLRMKjqVPcKxxpC1Wg18o2La4cWUw8cXAEC4qGBKX4vVENeqxp5HWSiLosjt6N2LUMLjWd0TMenwYsbpg0oA3rNVKlb3pVCEj81LrxNTpJmr59kTE3jvj3fzc9+u01MJVWd2rGaDJq22FbZZsaolfrFWa9Lhr5+4FLddLvWsV+nU/DySzNmTihLOQtfmXH74FbkeTAkvBesusFAN9wfFrC3OJ+weePzBiFC2ROfkE3JoZPQGdblywdI6/u9sWtGBaCW8Ml5PBtukG5hx8fNys9XANybSdfaly76+GTzwrBTaOWn34viYHV9/8gTu+fNRfPcZaWNyz9lp+IMiOuuMi2pDygRW8BaDEs6D2RK07hi0au7meG14nosrDdW6oncbEaUJFeElCCsCRVGazckCaJS2GaU60mwx8EVee62Rj2MphoR0tghtyTDIxJGF8WSMKp0G7zm/E61WA95/UTcAxEw6ZrbaNa0WXhSWazhbun20StpqjFijCLPKRk84UwWL0f7PLvLRit/mrloAkQUx65HrViyKmiwGvqCdcvgWjKRilnSmiCaaF8yD2RSF/6TDC5cvCJWAjBKMo587nbCd4/I5q7vBhIuWSarcmUlnUqVIueEAhBf5x8fsmHL4cE6rtOE4Mu9B/3R8S3q6yeiM67d24vyeOrz3/M7kd5YRhEhLejz8wRC32if6fNUYtXzjQBnaVyrJ6IzoNikgO5uXEzYPLvmvZ3Dzg3th8wTglvM5Ju1e3n8ezUk5JHBlHm3hhWRzVy2f551NKzoA1MmFlloloLshv0VeoWGTC2Zdfp7T0WzRRyjh6U58SYV//8NhrPr3v+FdP9iFkAg+3u35k5N44rUxAGEnFgsgvHRFY977i1nBO1ngnvBAMMTPxYns6IDU6w9IRfiYrTChbETlQEV4CcLUYhYa9vhhaYQPm4PYVmOMKMLrTFq+UOuqM6Gr3gSdRgW3P1jwhHT2s7Ad2nTt6Mxmmo2ecAC499p12HXX67jNjF1M7Z4AArIKxecGt1h4IVSMRWE24MnoGW5yXLU6bH/LTk94+PUu9AZSNKygVPZFGrQqPu/T7g1wJZMpA+s7avh9m8x61LMeOqd3wWdz3Bap8LWkUIQr1WrWD95ea1xU2mrYjp56QjkLZVvTYkGtSYelshLPphDEI/pnXd1i5i6ff7pgCX592zacu0Ta5Nh1Zjr2kwCweRIn/Mdjc1ctfv2Rbdig+D2lQirhbMpNmeiNGyUqlaDYnAkrSkwJLwU7OhBZhLPNp2y08ZyacMAXDOHgwCy/BgJSW0csBc4XCPHpApWihFfpNHxqRbaVcJb0vqKpuuLUQrNBy4s6di5rNoeVcG8gxDeFsoUoivj1viHuktrYYcW/vm4lAOChnX184/LoqA2hkMh7xS9dnt9+cCB83lZ+LgvBjHweFoTk7//1chF+eHiej4VMdK0liMVARXgJwk4o7z2/E2qVgCMjNvRPO/mCpsVqiFBHaqp03LK4pL4KapXAC4VjUWFJ+SQUEnm/MLN9ZmpHr9bnZqSJ1ajlCcls3BOz8a9sro4oCssRpnZmOreV5Q8A2ZlN22wxQBAkq3cx9JkpmXFKr5VypmdPQ3XEz80KL6aEK2cHN5r1PB142uHjoWwM1gvOLdoJdudjF+GL7wcHAIuckp+OEn5kRDrPsIRxtoGYKMEaCH+u2M9aa9Lh0Q9diD997GJ8+R3rUa3XYJsc4rTz9DS+98wpvPdHu3mYICOshOenHzdeoKMS9rup1muSjnVi5/NJRUBf6SnhUuHdXmPkLVLZcBCx87I/KOLgwFzE12KFs/VNOxEIiTDrNRUVtsT6wpMpgemyscOKr123Ad+8flNWn7dUYBv2LPixxWqQWlI0rCUluwnpDm+AzyPf+dmr8PvbL8Y161sARG5qObwBvDo8j5Ny68X5PXULnyzHsLYndu0pFDOKqQDJ2pHW8SLcxl0F7HpFENmGivAShFm2lzZW8wXonb95BS5fEDq1Cm1WI1/MA9KJh9mmljdKxTebHXp8tHDhbHZPAMyp1dWQmRLOg9n0udmBZ2nfgLRBIIoiTsmhPiuaq7kSnquZt4WGFQqZzm3d1FmDZoseKiE7s3G1ahXfUCqmjQ9RFLnqqQwnWtZoglolcKWTvZ5cCW8PF+FNZn1ED120Es7s6Oko4TaPnzsGzk5nqQiXPw8uXzCiRzkekhojqdRbuqWF4MZUi3DWZ6n4Wbd010Uo08ze/sRro/jvJ09g15lpvHQqMil4MW0VmRAr0DGadI6Jqd2TEWPufPLXins8GePcJTUApOyNbAYsKt0Ge89GuiFi2d1PKKzolTT+56ZtXbhmXQvef1FXVp9XEARcv7UT57TlN+SuWIhu7Wmy6CEIAuqYGybLm8WsJcWkU6OtxgiVLKo0K4LD2Nv657v6AABLG03cZZVP2BQOlkVSKNh4slQ2oM5ptUAlSK4j5q56+7ntOT0+onKhIrwEUe7qsR3Ql/ukkKPbr1wGo07N1RFBkBZ5H79qBe66ZjVPrGYW2eixQfmELUKNWjUP9Uo3yCSbPeHxqFWoWsNzbjh9QWjVArrqTXwxmauZt4UmlfTmRKhVAn5xywX4xS0XxB3xlC6tPJyteBLSbe4A7z9VBiEukze9eI+22w+3L8h7gZUhik0KG+OU08eLcLaQmbAtDGaLB9s0EUWpEBdFMayELyKUDYi0TitTx+Mh9W97UaVT47yuGgCKInxoPmHPZCobDpuW1MCgVfGZ2YAUlKTElmTMXrbhgY7O+JuK6VjkeRFewkr4eUtq8eJnrsR/Xbde0caz+MAmZd/9nrORs+vHYySks2T0lYuYaV2KtNcY8f33bcbmrvwrouVMl6IIV6sEvpHK3DDZTkhno7aURbUgCLhkudT6pVEJuGadtC78yytSq+LWAv3O2bVmyuFLyzmVbZhrLpUi3KhTR2ykb1taH3PEIkFkAyrCSwx/MMQXb3UmHd64toWHcmzqrMHHrlwOILxos8qhPp11VfjI5ct47zQLzGL9zdnAnWQcTzRKJYjN1UwUZBSLXNvRAUU4m9PHreg9DSZo1SpeCE3YPbxnvJxgRdBi+k5XNJtxURb70dis8GJSwlmLSLVegzZFcby0UVqEsAXZvMvPF1E6jQoWo4YrKe21RoUd3cvt6OfJPc8TfArCQnU4GoNWDYNWOr3/00/2YMPdf+fqcM8iw5M0ahU/j6SSkP5C7yQASQFlPaNrWqXe7hnFZkMsou3osdBr1Nxqy37m6JC2cLZBforwWIGO0YTPf8k3EFmhHdETXmJFOCBZ0rVqVVgJty1+I03pNojuMY9lR+dKeIX0gxO5RamEN5n13O6cq4R05oCJTvnevlZq/bp8ZSN3SLIJHVu6a7N6DKlSrdfwtUMhLenTPD8jNdfQOoVD7brNHTk5JoIAqAgvOViRyhTuhmo9btjaiY5aI+6/YRPvLWQnvnghFKw3s2/aCZcv9YCleHzn6V5suOdJPLy7P+XHKIvwVBatscjmnPB41CqSjnu5FV16/RqqpYtuSEw9ZCgVC2+xMCwHqmRLxc4GrTXFp4Rzd4pJG6FQRCvh825/2EZs0kEQBHztXRtxz9vWYmOHlT92yuHDsFycMvWYzVUeT0EJV37PIyM22L0Bvnm3WDs6EO6tjp4VLooi7nv8GB588Sy/7YVels4b3ojRa9R8SsPBOJb0QDDEi85EGw4A8J/XrsO9167F5960BsBCJTz/dvRwC0s80rOjh1PzASAYEjHjLK0RZUpashhoGWvjlhX5EzHs6EwJr5RQNiK3dCqLcMV5qtaUm1nhzI4ePe/6jWtb8MtbL8DX370R57RZI762tbtw7ge26Xu2gEX4TBpKOBBuEzNq1dxVQBC5gIrwEoMt6qyKsTX3vXMDXvzMVRE2002dNTBq1Tg/zsm3vlqPRrMeohhWBhbDbnkW5Rf+8Bp+tXdgwddjWU6Vi9BwD2VmSng25oTHQ5l03CuHnLBgO7VK4Iu5jz16cEEgVDT//eRxbLzn7zg1Ubhe/HRghWA2+rmzBVtgj84VjxLO+v7qqnSoMWrRajWgtkrLbW1sRvqcy8d35VnBvbmrFu+/qBuCEE7BPjlmhzcQgkoANsr9z+M2L6adPgRCIgRBUl0SoSzu3raxDauazdjYWbOo8WQMS5wxZYMzbvzw+TP48uPH4PEH4fEHsbdPsghfuqIx4r7J+sInHV6ERECrFiJmEcdiSX0Vbt7WzdXNwbh29HwFs7FzRgI7ehpFeDiYTXrPzzh9CInSZmy2g7byQUsWAy1jvcYb5MDD6J5wty+Ifvm9USnjyYjcskQxZrJZcU7OXU94fFX3ouUNqDXpsKbVzPvCG836vM8HV8L7wqfij5DMNWE7emoblleva8HSBhM+dtVymHK4tiQIKsJLjBnFYj8RnXVVOPCFN+C/rlsf9z5MDc+GJV05v/au3x/mI4kAqdi+7L+fwb//4XDEY+bc0mMsRi1XjpTJnwCw9+wMXveNZ/H53x/GQIw5wHZvdkeUxUK5oD7Jk9HDC7hvXL8RNVVavDI4h9t+sT9hj+tLp6bh8gX5DM9iRHn8w3KhW1RKeDHa0RU77SqVgMc/cSl23HE5DFrJfs1mpM+5/fyzEmsRxX429r5usRj4aKd5t58rvPUmPbRJErVZcddZZ8TX3rUBT37qMvzxoxcnTeJOhXhjytgM82BIRN+0E3vPzsAXCKHNasCyxkgFPllCOnOWNJkNUCVJtGWwDYahWXdEe0imc8IzJdvBbI0Kh4T0t7yRY9Jl5feZb1gR7vQFk25cJmPevfA13qDYuFIyMOOCKIZdZASxWFosBp7roXQncSU8y3Z0VlBG29GVVOk0vPjd2l1b0ADC7iIIZ2PX52SbuYxWqxH/uPMKfFRu7ySIXFF6V+8Kh9m1a1MMmEh08mV20OOjiw9nYye5jlojRBF45sQE/9oRed7i/+0f4uFVQHgRWlOlhcWg5b3tyr7HX+0dwOlJJx7ZM4CrvvEs9kYF7zjkBVxegtmcPp6Mrgz1WdNqwS9uuQAalYCXTk1jJEFxyBQ5V5Znh2aLWacP2+77B+763avw+IP8d9FRhEp4UdnRoz6XtSZdxCJfaUefdCwM1mEsqa/Cvdeu5XbvnkYTrEYtH3fz2rC0edNiTV5AnLekFhqVgHvetpZvBmSLeEr4hCI4rHfcwdNlL1nRsOBcxNTKIyO2mBtX47z3PfViqcVigE6tQiAkRrSH2BaZ8p8utamMKHOlYUePGlHG/i7VQrJKp+Hv8cVupiVSwieigtnYpkiqi3GCSIZaJfDgLmXbTB1fN2Q3kGzKkdpn/wJ5JFm0Aynf9MjtT4W0o6eycUEQhYCK8BKDzSKO1+udDqvlhPRjixxTJooiL8LfvL4VALDnTLhYZsW2xx/CmUnHgtutRq08ZkM6nq89cZwvyplKb9ZrEAiJ2H0mcgSNIx9KuLxgOzZmi0hGV7Ku3cpVuP4EFxumHLqz0IefCw4OzmLM5sEfDo7wwKwqnTpvvbSp0Cqr8uM2Dx+/VWhmkzhUalgR7lIq4bEXUTdv68Zzn74SX3jLObjnbWshCAJXQl8ZmgMAtFiSb4p89prV2P/vb4iY1Z4tmK07OphNaf89NeHg88E3xpizuqTOBJUAuP3BiNRvRiop8NGoVAI65HGMSks664fP1/s4vWC21JXwebcfvkCoJEPZomG/11SzNOIR3cKkU6v4CM4phy8ig2OxIxcJIhas7UjZ6pPznvAkRfhnr16DH920GTds6czq908XpoQXtAiXNy5KsXWHKG+oCC8xuBJetfhFBJ8VPhZbiUoVmzuAgFwMXS2HWOzvn+V2UOVC/bWRecXjIhehX3nnOqhVAv5waAS/OzCMQDCEU3LR/gY5+XM0Sv1kwWzmPCjhTIVkyejRsL6rvhi2eQZTDp3e4lTCR2T7udsf5Cpme42xqObpNpmlueP+oIgp5+JHHMXj9KQDD+/uj3BvxIMVRXVxdtqVI8pYoZqogKo16XDLJT1YLm9MMTX41aHUlXBBELgNPtuE7eiRBZCymD414eAuGzaNQYlOo+L2++ggNSD2jPBU4JthyiKcF1/56e9j5wy7J4BAMIRQSMSnHjuEu353mJ9r0ykIrUYtNLJVaNrpTVkNK2bY7z76nJ4OoihydZvZb5utesmmL79eSmdVvgP6iMrgC28+B195x3q8cW04xCt36ejyZz9JQWmt0mL72paUW3lyBQsCnXf7s94fnyphO3rpni+J8oSK8BJjNs2Ux0SwRYvNE0hp1FA82Milar0GGzpqYDZo4PAGuMKutKy+NhzZKw6EF0Sbu+rwqdevAAB8c8dJ9E074QuEYNSqubVqWBHGFQyJfN5yLpVwduJmtdg5MQoKAFwdj9f75PEHeb+7u0jt6CNz4QXx08fGARRXKBsAaNUqXsDmsi/87j8dwRf+8Bp2HB1Let+xJPOs+Ygytx+D8uixzjRe1yaz9Lyn5EyCRHOz80EqdvSX+2YwYfdCEOInUbONq+iRYgAwIffzpvuzsrm9rLAXRTFc8OapJ1xZ5M25/Xi5bwa/PziMR/cOcGtkOrPLVSqBWykn7d6yUMJZi0uiEXXJcPqCfAOYWdBbLFKGAAsuVPaFUxFO5IIl9VW48YIlvG0IiAx0zSZha3VpfPaNOjVvITtbgL7wYEjEnPy5JyWcKDaoCC8xontPF4NBq+aLuMGZzBdCylAqtUrg4zD2nJWUVGWBf0RWwkVRxGFZWVb2G99yyVLo1CoMz7nx5BGpCFzZXM17rpRFovJ5c9kTvrW7Fu/Z2ok3r2/Fx69ajs9cszrm/cIpoLEvNMqCxektTju60hq683RYCS82mIo2ksOEdFbEHR1JnpmQrAhnhdacKzwXm72nUyE63TZddTjbhEeURb6PlXZ0VpB31VXFTZjlRXgMJXw8QyW8M6oId/vDhVq+ii+NWsVfozmXD395dZR/rV9eiKZbECpnhbNcgVIcT8Zgm3vDiyjC2aa0TqPC2jZpc5R9rpr4GLTw86eTSE8Qi4Ftmk07fFlrmwoEQ7yoL6X+ZqaGn53MfxE+6/JBlCdJZMNBShDZhIrwEiNZ72m6hNWIzMdHTEep8+fLqjULUYsowodtCIVEnJlyYnDGDZ1ahQuX1vOvG3VqbO6qBQD8784+AMCqFjPa5EJwdM7N7Zw/3yV9fWmjCXpNdoOnlGjUKvzXdRvwvX86D/9v+ypeAEaTSNUDIgsWt684lfBhxSYHU+2LTQkHFGPKchTOJorhedy9E44k91aEiMXpX2YjysbmPXzTqrMu9df1lkt7IsIA0+mTzgXWFJRwRiwrOoMVzNEjxZTPlWwUWzTMjs6mKbDPnVoloEqXu/NENGyjdMrhw99eCxfhbFRPukU4s55P2hV2dHPpLMSjYcXyYpRw9hrWVmlx/ZZO3H7FMp5ovFRO4z8xFjuHhCByCXPQBRRK7GKZdfkVBWXpfPZXyZN4mPCST1gPfY1RW5KTJIjyht6RJcaMK5wong065YXQ4CKK8OjxD6wIf7lvBqGQiHlF8Wn3BjA468Izxyf4faNVsktWNAAIL8JXtVh40eX0BWFzBzDl8OLHz58BANzxhpUZH3s26VGM4oi18x2hhBdpMFusoraYlfBc2dFtngA8fmkT4uR44uBChzfA2yKS2dHZ/WqqtDCnYY1uMhvwm49chCtXNaKj1shHMBUKbkePWlxOyBsXJkWxy7InYtFVJ31m+mPYFNkmSFMa6ehAeG4vU8LDVnRNXrMNWDjbn14Z4aPFAEn1D4ZE2NMMi2tQjCnjdvTqwm7GLAa2Aazc+EsXFspWY9ShpkqHf7t6NQ/JWtsm2dOVOSRUhBP5QqdRceU1OqU/FV4ZnFswvo+1/tVVSa7DUmFLtySs7OufSXLP7EOhbEQxQ0V4iZHNnnAgrMZlw47O7FHr263QqgXMuvwYtXkW9JsfGbHhuZOTAIArVi0cn3HJ8oaI/69uMcOgVfMif3jOje/+4xScviDWt1vxpnWtGR97NmmvMUKjEuANhDAe46KrLFhcRaiEh0JizKK2mMaTMdpq2JiyxRfhoijir6+ORqS3Tihs1X3TLvgCIXz45/twww93RcyfBsIbAWa9Jq7tOnrR35mGFZ0/R5UWP/vA+Xjh364seBHBequVn22PP8hTyC9QuFvWtMbuBwcUqnXU+cfjD/IitdGcWTDbvNuP4Tk3z2ioybNy1CifD3+5ZwAAeL9o/7QzYnGdrh1dUsJ9EbeVIh3M3TTvjkgwTwdmzY21Kb1OtqcfGaYinCgMLMsj1vSHROw+M41rv/cSPvu7wxG3h5PRS6ug3NIlCTNHR2x8ok2mHB6aj2h7SgZr3WlK8zpCEPmAivASI5054akQtgQuwo7uYBsD0oJQq1aFVRu7lxef7LZnjk/wEWZXrGpa8Hzr2q0Ri6SVcqgTs6T3Tzvxq5elhe2/Xb2q4OmfDI1axQvWWOM4WIECFGcRPuXwwh8UoRIi5+i216RfMOYaZscey4Id/dDgHD76ywO48zev8NvGFBf5YEjEU8fG8fej49hzdgZnon63vHc5gUW8SqeGVh1+n6ZjRY+mGJLqWcq48j3NgtT0GhXOW1LDb09kR2eq9ZTDG5GTwJ7LoA33VqdKlU7Dgxx/vqsPv9jdDwC4Msa5Jpd89MrlEa/DzRd2AZA2dVgxKL0vUrsMs/PnyJybb3w2lNhiXElDtR46jQohMXNHC7P5xirCz5GL8BFFCwiNKCPyCXPxTNjSK8L39Unro2OjkXkkrA2l1FK+W6wGdNQaERKBQwNzGT/P44dH8dbvvoiPPLw/5cew176UNyyJ8oWK8BLCHwxxdShbPeFhO/pilHB2YQgfE1swTjvDRfjrVkuL4N/sH4IvGEJnnRHLGk2IRq0ScPHyev6c7OTJLOk7jo7D4w+h3qRboJoXGjYTM1ZfeLEr4UxVbrEY+AJWqxbS7snNB9kMZmMFwMkxO88bGI9aND344ln+7+jf7ZjidYuHIAgRG0vphLIVI7FGlDHLZbPFwEerVes1CZ0UVqOWvy7Klhj2XE1mQ0abDh+6dCkA4Oc7+/FC7xRUAvCBi7vTfp7FcO6SWvzu9ovxzJ1X4E8fuxjXbe4AIG0iZqLIsoT5Z2UXkVollFRfaDQqlcBbXTLtC59zspGdC18Hs0HLW4RYIOgcKeFEHmHBiZOO9Irwk+NSjsHYvCdifGypKuEAsEXO+nm5LzNL+tCsC5/97asAkreIKQkr4cW3jiEIKsJLCKaCC0L2dvKZIjc068p4Vnh0MBsQvkhM2X18wfn+i7rxsSuXw6CV3nZvWNMSd4F9+UrJpr5eHjsDhJXwJ49II6PO66otClVQSXeCMWXKnnBXEfaEs+T51hojVy9brcaicRooYRsy4zZPSnO8E2GXFVi7NzyqL9rutq9/lv87eqZ1qvOslQv/dMaTFSNs/rg3EIJHHrfHNi6azHpcvLwemzpr8IGLu5N+RmMFGmYaysa4anUTljaa+CjA7ee08BC4fNPTYMKGjhr+c865/Pw9lE4xuG1ZPdprjDwwsd6kK8rPZjosNhiUF9VxMlJYYjobjUnp6EQ+acxQCWdFpkvOwGGwnvCGEpyKsEWemrNfcS1NFVEUccdjr3DnlcsXTNnWPpFhtghB5AMqwkuIWScLodFmLZSj1WqEIAAefyjt3VoGt6NXL1TCJx3ecIKtSYs737gKz3/6Stx/wyZ8+o2r4j7nuzZ34ktvX4e737qW38ZUExZuxXZWi4lueaEda0yZ8mJalEo4K8KtBqxrlzY/mLJfbDSZ9VAJUvLsdIbvW4ZDYalm2QixAsYYA9Ox7egt1sQXeWVPckeBCsJsUa3TgNXWzJ3D1WuLHmaDFn/46MX4f9vjf8YZ0WnmwOIXTiqVgFsvWcr//8FLejJ6nmxSpdPwTYWDsiUznbnlapWA67d08v+Xg71yseFsvD0rjiNAGc6mnBefrWBTgkgEU8LTCWYLBEM4oxjlNWoLfza4El6CIWMsnO3AwOyCXJVkDMy4sLdvBjq1imdrpNpnz8c5lsH5kig/qAgvIVhfW7b6wQEpLKhVVvD2nJnBDT/chT8eGs7ouGLZ0QdnXHxGL1twNlkMePu57TAmGBekVgl434VdEUVga02k0shO6sVEF58VHsOOrlTCi3BOOLN2t9cYcc26FnzxrefgP95yToGPKjYatYoHrSw2nE3Zi8ws0UzVVY7PY7CZ1gcHZjHt8KZkRweilfDSLsJVKgFmPesLZ+6BzAJwlkTN9QaUSnjmYTrvPK8dl65owHXndWBrkZwrmBr+632DABKH1sXi3Vs6wPZfy2FRuVg7+rwrvDEdi3XtkhJ+dMQGtz8IfzC/8+KJyobNqk8nmK1/xgWfokgdVbRcTXE7eul99lc2mWE2aODyBXFsNHU7OSDlaABAd0MV2mQX3ESK4WwTGV6XCCIfUBFeQsy5sjsjnMFUuXv+fBR7zs7gR/Lor1QQRZEX4XURRbj0b7ajq8nCjN42xagsnUbF1dpigtmkY7kKInrC/cGM7f+5go0na7UaoFWr8IGLe/i4n2KEbcqMLmLEEYAIWxubV83S7S9WZA6wi//AjAsv983gHQ/sxMd+eTAczJakCK+J6AkvbTs6EG6JYeqiUglPB25HVxTh41kI0zFo1Xj4lgvwjes3Fk3bSpfcrsLcA9dv7Ux09wW01Rh5q04pWlKjWWwwaDgdPbESfnbKiWG50M/GtYggUqFJMdEgVXqj+p1HFZvMzI5eij3hKpWATZ01AICjo+nNC2cjLLvqTbyYnkjxNWX3K4dNS6L8oCK8hJhJsuDIFKbKseTN3nFHyiNjHN4A37VVJnayBeKZKSlgxGrULnohrJxXvaHdCr2m+BZSNUbpdzPv9i8ospVJ0qIIPoe6WGB29LYinAsei44szLgHwj3hyudiu+ebltRwS/p7z18CABiacePpY9Kc+91np/lGU0uCdHQgXLQ2mfUwaIvvvZsu1qhZ4ZMZqtfLGqWNnoP9swsL+jJbOLF2FQDY0GHlRWI6fPqNq3F+dx3ek2YBX4y0L9KOnigdHZA2htnm2Z6zUiBUNq5FBJEKrPBLtWAEpPWXEuUEkPH50j4vsnP96cmF7XqJYM7C7vqqcJ99Cq+pNxDk15RSfc2I8oaK8BKCFUnNWQ6YiFblfFE9SYlgKrhRq46wl/NgNtk+lQ37X0O1HhrZi7m5SOyl0bCfMxgSee86wxY1L73YwtmYrbtUivAeuaCJNQ4uHaJ7wkMhMdznbTHglkt6cH5PHW7e1g2NSoAvGMKfXxkBIG2msCI+qRIuFwrloIIDioR0+fULOwLSOz+dt6QWq5rNsHsD+N+dfQAUBX2S17TUYEo4ANyQYRF9TpsFv75tGw86KmXYZ2F0LrOAxTnZjp4oJb5HnsDx6tAcALKiE/mDFX4ObyDl6/3JibBwAYSvy4FgiIeAtpfoNYQ5605NOJLcM5KBGaUSnnqfPbuO6NQq+twTRQkV4SUEKzZ6shyWpUwN1skza6PnU8aDJaNH26OirZLZSHNXqwR+8dnSVZwLUINWxV9D1j7AUPaEA8UVzuYNBPkFq2SKcHlxvdgiPLonfMblQyAkQhAkJeOO7avw649sg7VKGzdISq0SktqDWe/z6gRzs0uJWpP0mZ6RHTSZ9nGrVAI+etVyAMCDL52FwxtYdDp6scIWoUatGm/b2Fbgoyk8TWYDtGoBgZDI22FSJRQS+Tk2UdAa2/h4dUiywNKMcCJfVOs1MMqup1Qt6cyOfskKqRWKZY6M270IidIaraHE5oQzmBKebhHOesK76qv49WUyhcT5SYUVndwvRDFCRXgJcVa25GS7CGfzZ1ssBly3uR1AGkV4nLTO6IIkW7uQd791LT525XJcJc8cLzYEQeDjcuajlG9lOjpQXEX4+Lx0sdJrVKgtkeRgNg5usUW40o4+NOvmi556kx5adeQpcolCyVQOKGis1iedWPDWjW34yc1b8Jk3rl7U8RYLLRZZxZz3wOMPclUyE6fOm9e3YmmDCXMuP3724lnusCm3InxNqwVfevs6/OjmzTCnkYxerqhVAl+YHx1J7ZrDsHsDYOJ5outLl7z51RulMBJErhEEIS1LujIZ/fIVUvbDiLw5FR4haijZ0YRsE3Jw1sVHWyYjFBJ5aGe3QglPZZoPe80byuw6QpQPVIQXMbNOH97+vZfw6d+8AlEU+dirbBfh6zus+MH7NuMXt16A9e01AICjKRbhM3JQSF1UEV5bpYVy4zFb6sOVq5tw5xtXZW1EWy6wKgKrhmZd+NzvD+PUhIMr4cxS7ywiOzpTdttrjCWzY8w+B+M2b4SafXBgFqcmUk9fVdrRfYEQXhuWFLNYxWSXwjWy/ZwWnhDenKQfHAC0ahVef05z3JnGpUZbTTidni0Qq3TqjIoctUrAv1yxDADwoxekYEiNSkhoMy5V3ndhFy6VF9iE1BsPAIeH0wtrYsnoRq06YcYCU8KZ3Z2KcCKfpBPO1jctJaMbtWo+/WVs3gNRFMOZLdbScKrFoqFaB6tRC1FMffN8zOaBLxCCVi2g1WoIb2qkoYSX22YuUT5QEV5kTNq92N8/A1EU8dnfvYpDg3P4zf4h9E444PYHoVYJEfbxbHH1uhYsb6rmI3OOjdowNu/Bw7v74Q3E37Gc5snokSc5jVoVkeJuNWqyfszFCi/CXX78+uVB/HLPAL71dC98ASmIjfUOu4tICefJ6DWl04NbU6Xjmz99cnrqqQkH3vWDXbjpp3tTTp93RI2L29c/CyB2j3eXIljr4uX13DLYkuWchlKg1cr6ed18vF3bIjZx3rqxDWa9hieHN5n1Jav4EKmzvqMGQNgunirhGeGJi2rlZxagIpzIL+GiMXkPM9sAXtVi5m1hLl8QNk+Ab5SXSrtYLARBwDK5jSxVSzq7tnfUVkmjSS2p94RTMjpR7FARXmTc/sh+XPf9XXjdN5/Dk0fG+e0sCKqz1rjAIptNVrWYIQhSoNp139+JL/zhNTy6ZyDu/dl819YYSqCyT7ySFj41CiWcjVraeWoKgGRhZtYoZxHNCmdjUEptl707KpztN/sHEQyJGJ33LLD/x4MV4ayg33N2GkDsIly5AXZ+Tz3+6YIu6NSqom2PyCV8RJxCCV/MAtGgVeMtij7pxjILZSNis6E9rISnM7aRJaNbk7glqAgnCklTGnb0Q4NzAIBNnTUwaNV8g2l03s3Pse0ltFEei3TD2foV/eBAOHNk1uXnwkY8SAknih0qwouMk/J4CtYXZDZICvIfD0lFeHeWrejRVOk06JHte2znddeZ6bj3T2SRV/aFV9LCR2lHZ04B9rfZoEW1XrJOulPsicomE3ZPzPFzw7zfrLSK8J4G6YJ+dtKJQDCE3x8Y5l8bmkttdBkrwpkLZHDGHfF/JauapU2qJrMeK5qqccmKBpz40tW4YeuSRf0cpQjbsBmzefic58UuEN+1uYP/mxZOlcHqVjO0agEzTl9ao8rmUlTCq3SaiPdSJV2LiMLDJjykYkdnRfi5S2oAKNxG854It1Epw4rw05PpFeEsA6a2SgutWnJIJesLn5TVclLCiWKlcjzCJYDHH55p+N7zO2E2aFFbpcNXnzjOgymy3Q8eizWtFpxR9Ovs65uFKIoxbaZMgYy1OVBfqUW4vCicc/sx7Yy8SFiMGlTppI9droPZPP4gbv3ffRidd2N9uxXHRu04MW7HDVs68dV3bYi47yjvNyutXfaeBlkJn3bihd6pCLVhZM6TdA6zNxDku+nntFrw0ilpw+n927rwnhiFdXeDCT/7561oMofDcUqlhz7bNJqlkYGBkIiD8uJxsU6K85bUYGmDCWemnFSEVwh6jRqrWsx4bdiGw0Pz6KhNrd2KBQEmSkZndNVX8XNDJV2LiMLTWJ2aEu4LhHg44Ua5RaPVasDRURtG57LjNioG0k1I759m48mk84IgCGis1mNk3oMJmwftCV6PTCd2EES+yJkSPjs7i5tuuglWqxVWqxU33XQT5ubm4t7f7/fjM5/5DNavXw+TyYS2tjbcfPPNGBkZydUhFh1szq5Rq8ZX3rEen3vTGmzqrIm4Tz6K8KvXtUCrFvC5N62GTqPCtNMXM0TD7QtyG/PSmEp42CZoqaAk4Agl3BE5psxi0KJKnqeeazv6Qzv78OKpKZyedOIPh0ZwQh598tfDowvU8FLdZedK+JQT/7d/KOJrw7PJlXCnN7wRcvO2brzj3Hb86KbNuOfaddBpYp8er1jVhHPaymPM2GJQqwRu2T84MAdg8e8fQZAC2gQBuGR5w2IPkSgRWCDoq2mEs83y8WTJw/uU89lpRBmRTxrlHubxJD3hx8ds8AVDsBq1vOAMt/y4y6InHAgr4WemnDwsMRF9UXZ0INyqlMxdQHZ0otjJWRF+44034tChQ3jiiSfwxBNP4NChQ7jpppvi3t/lcuHAgQP4whe+gAMHDuB3v/sdTp48ibe97W25OsSig41GarEauLq2vsMakTKejyL8rRvbcPTeq/Hhy5Zhk7wj+3LfzIL7scCMmiotak0LF0JkR/djOsouJRXhkhKey2C2GacP3/vHKQDA7Vcswx1vWImvXbcBtVVaOLwBvDo0h98dGML7frIH0w4vH4PSVmL9Zt2yEn5k2Ia/vTYKALhwqTRDPhVrK0tGN2rV6Kyrwv/csAnb17bk6GjLD5YFwSz97bWLXyC+e0snTvznNbhmfeuin4soDTayhPQ0wtm4Ep7CtUU51aCSrkVE4elRjNIMxGgFY7wiu4k2dtbw9d+KJqkl6u9HxnlgZaldo6PpqK2CTq2CLxDigbDxcPkC3La+VN5wB1Lrsw+FxIg54QRRjOTEjn7s2DE88cQT2L17Ny644AIAwI9//GNs27YNJ06cwKpVqxY8xmq1YseOHRG3fec738H555+PgYEBLFlS/j2XY/JOqXLXrlqvwbLGam7d6a7PfREOgIe/be2pxd6+GbzcN7ug75Vb0eMcU4QSXkELH2aPnLB54IwqtCU7uqyE57AI//bTvbB7A1jbZsGd21dx6/RzJyfx18OjeOK1Mfxq7yDs3gAe2TPAL/CtJRfMJr33fPLi5n0XLsHShmrsPjPD1f1EsOKx2kCdOZnQVmME5DR5AAmtgekQz4VAlCfr5SL8lcE5TDu8Ea1M8Qj3hKeghCs2r6kIJ/LJkroqGLVquP1B9E27uBIczaFBaQNqU0e4heqadS24+89HuIuttiq8iV+qqFUCaqq0mLB7Mefyo6M2/n1f7J2CLxBCZ50xQglPpQifdfkQkJX2hhTOJwRRCHKy0tm1axesVisvwAHgwgsvhNVqxc6dO1N+nvn5eQiCgJqamhwcZfHB7EotUX25bI6qTqPKuxVpS7ekKu6LoYSzIjyWFR0gJZyF6ymxGLQwyUW4O0dzwkVRxO8PSgFln7l6dcSYp4tli++DL/XBLhegLHnfatTCpC+tC7xJr+HukH++qBv/ee06/hkZSkUJZ0V4if3cxYJypJ0gxE6UJ4hkrGo2Y0ldFezeAN7/s72wefxJHxNOR09TCU/h/gSRLVQqAStbJEX7xJg97v1eGZoDAGySQ9kAKdRt29J6/v9St6IzmChjcyf+nP/j+AQA4HWrmyOyVxr57PX4G+1MuGqzGmhTlyhacvLOHBsbQ1PTwpE9TU1NGBsbS+k5PB4PPvvZz+LGG2+ExRK//9Lr9cJms0X8KVXYOKuWqIUsG+HSVVcFdZ7n5m7uqoUgSH050XMZE4WyAVHBbBW08GFFOEtEb7EYeMq9xaiFUd7JjqeE2zx+/Pj5MzyIJV1mXX4e8Hd+T13E1y5eLl3Qlb1YvexiVaIX+B+8bzN+eNNmfPGt50AQBHTIluhYr9+pCTt+/PwZ3hPv8EqvExXhmaEMYmsy62mxQ2SERq3Czz6wFfUmHV4btuGzv3014utzLh+eOjoekWUxK9vRU1HCu+tNEARpRGSyNHWCyDarm1kRHnt9KooiX0+tbolc7167KTy2sVSv0dGwNVKizbZQSORFePQIUBbe+OKpKXjiTJl5TQ65W9ueOJyVIApJWiumu+++G4IgJPyzb98+ALETg+MlbEfj9/vxnve8B6FQCA888EDC+9533308/M1qtaKzszOdH6mo4Hb0qCL8LRvbcN6SGvzzxd15PyaLQcuV7pNjkWmWZxOMJwPCmwk6tQrVJW6hSgerMXJRWF+tw1o5yMti0MLERpTFKcJ/u38IX378GL71VG9G35/16rdaDTBo1RFfW1JXxYvUhmop3ZpRasnojFUtZrxxbQs/t7CFyqTdu+AC/V9/O44vP36Mh7gxGz4V4ZnRqnjPlMsCkSgMyxqr8aObNwMAnjo2EfHZ/fJfj+HWn+/DX18d5bfN82C25EW1tUqLr75zA+575/qSt/MSpccqWQk/FkcJd/qCfGM8elPp6rWt0Mntgdlq9yk0FlmUmE+ghL82Mo8JuxdVOjUuWBopJlyzrgXNFj0GZ9z48fNnYj7+iBzyuC7JhBSCKCRpFeEf+9jHcOzYsYR/1q1bh5aWFoyPjy94/OTkJJqbmxN+D7/fj+uvvx5nz57Fjh07EqrgAHDXXXdhfn6e/xkcHEznRyoqxlkwW1QR3lCtx+9uvxj/dEFXIQ6L28pZGi0j0YxwQLLVf+bq1fjS29dFWKLLnWjrfX21Hm/Z0AajVo2tPbUwallPeGw7OgsTYX1g6RI90kOJIAjYfo4UPHbb5Uv55gBQPkVUbZWWv8Ys7JDB3Ak7jkrnJ5aOTj3hmaF8z5TL+4coHOctqUVDtR6+QAivKkLadp6WRgcqZwuHlfDUlO3rt3YuyDUhiHywujWxHZ3ZsrVqAQZt5LLcWqXF69ZISvCyOP3kpQZXwt3xW/KePiap4JeuaIBeEykmmPQafO5NawAA33v2VEzX2xGmhNMkE6KISWvl2dDQgIaG5GNjtm3bhvn5eezduxfnn38+AGDPnj2Yn5/HRRddFPdxrADv7e3FM888g/r6+rj3Zej1euj15RG6MG5nPeHF9fOwndk5RRE+7/LzgiaeHR0A/uWKZbk9uCIkughvMOnwvgu78N7zl0CtEriaE29OOOtTPjPpSNk9oqRvShrpES8w79+uXoU3rW/B5q5aDM+58Yq82G0t8dRVhiAIaK814tSEA8Nz7oj3J3MfvHRqCm5fkOzoi0SphJeLSkMUDkEQcH5PLR4/PIaX+2Zwfk8dJmwePulgQm7ZCoZEbmWNdh4RRLHBLOYDMy44vIEF1xvmyLIYtDGv9195x3pcvrIR7zivPfcHmwcsKdjRn++dBCD1g8fibRvb8MjuAeztm8HDu/vxmatX86+5fUH0TkgbHuvIjk4UMTlp4FuzZg2uvvpqfOhDH8Lu3buxe/dufOhDH8Jb3vKWiGT01atX4/e//z0AIBAI4F3vehf27duHRx55BMFgEGNjYxgbG4PP54v3rcoGURR5T3iTubiKoVqTdMKccYZPmGdltbXJrKcCJgqdRsUT0AHJjg6A9/NXyXZ0VxwlnF2QbZ4AZpzpv/eZEh5vc8SgVWNLdx0EQcDmrnA0aTkVUUyVHZ6N3CFnGx/eQAgvnpriI8roPZwZdSYd9HIfeKm2MxDFxVY5DHTvWSkM9KA8ugkAzyWxuf0Q5ViLVOzoBFFI6kw6nuh9MobDjRWj5jiOrFqTDu85f8kCRbhUUY5xjUUgGMJRWcne0h07Pl0QBGxfKxXogzOuiK8dH7MhJEoTepotxSVqEYSSnKXoPPLII1i/fj22b9+O7du3Y8OGDXj44Ycj7nPixAnMz0sq3NDQEP70pz9haGgImzZtQmtrK/+TTqJ6qTLr8sMXkEJnii1huEZWwpV29GSFXqWjVMPrTJEXgSotK8JjK+GsCAeAM1MLE9aTcXaaKeEL7ejRKIvwUhtPlgi2oRA9K1z5mv/j+DhPiCc7emYIgsA3PMiOTmQDFia5v38WwZCIgwNz/GtsJBFLRq/Wa/g4TYIoZlYlSEi3y0V4pYxytRgSp6OfnXLCGwihSqdOOJaX5SdFjypjVvRz2qxpOwkJIp/kbOVZV1eHX/ziFwnvI4rhhObu7u6I/5c70w4v9vXPQqsWcNXqZt67Wm/SFV3CMOu5U9rRWd9ysW0YFAtWoxaj7HdaHWmXZGPAXN54dnSF42DSyZWhVAn3hCffIGm1GrG2zYKzU06sbC6PfjMAaJet9dFFuHIs3NPHJnDZykYApIQvhn+5fBmePDLGx98RxGJY3WKBWa+B3RvAsVEbDg6E59CzxfZsGqFsBFEMrG4x44XeKRwfXZiQznqj4ynh5YbFKP2cNk9sN+BR+TVa02pJmCfE3AVTC4pwFspG/eBEcVMZn/gi5IXeKXzysUPY0lWLq1Y3837wYixqa7kSHi4O2SKojhZBMVEq4Q1RRbhRl5odHQBOTzli3icecy4f5uTfU6xgtlj85rZtcPmC3PFQDrTXLrSji6IIl5y4rBKkBf3LfZLllYrwzLl+ayeu31q6UymI4kKtErC5uxbPnpjErtPTEQFt0w4vgiER8/I5jopwolRYIs+qZ1NwlDA7OlOIy51kdnSuZLcmLqJZER5PCad+cKLYKS7JtYI4R96hOzZqQygk8mT0YuxfiRXMNssXQeVTuGUTZRFeH2VHN8kjcpIFswGSEp4O/bIVvcmsT3kUT5VOwxPwywXmAjij2MTwBkK8j3RDRw2A8OtFRThBFA/M/fO9Z0/B7Q+iWq+BSgBColSIs03gVGaEE0QxwBxwzhgOOLbxXjFKeBI7+lFuJ09chDfKRbjDG+CiRjAkcsv/miRFPEEUGirCC8TSBhN0GhWcviAGZ118d7SlCMONWDCbUgmf44ugyti5TZfInvDYSnggJOL//foV3PPnIxFfdyiU8LNp9oSzGeGJ+qgqgeXyKJdxm5erDMpNj61RYS/UE04QxcO7NnegzWrgrp5NnTWorw6rXuz26EkUBFGssCJcucnOYMVopSjhlgRKuCiK3I6ebLxYtV7Dx5GyFsmROTe8gRB0ahV3HxBEsUJFeIHQqFVYLQd1HB2x8WT0YrSj82A2RVI3S+2uNZESEQulTTK6J1yZnP7bA0P42Ut9PJgFiLSj90+7EAylnpXAlN1UrejlisWgRYv8WTo1IanhbKdcp1FxJZxhJiWcIIqGZosBf7/jcnzo0h6YDRq887x2hfXUo9gEpusPURpUcyU8RhHORpRVyKaSNcGIsjGbBzNOH9QqASubzQmfRxAENFkiLemnJqXrfU+DiU+kIYhihYrwArJGnh15dNSGoVmpeCrGIpwtdOzeAPxBKcGdKRG0CIoNu8hU6dQLbOFatQq6qERfZlHzBoLwya+xSgB8wdCCMVuJ6Jui1HrGCjlo7tS4dFFmM8KrdOoFvWImKsIJoqio1mvw+Tefg1e/uB3vPK8jXITbvDwdnXrCiVLBlLAITzyirNxgmw0efwjeQKQ9n1nRlzWaYNAmH8nWWB0+LwDAGbmFb2kjrYGI4oeK8ALC+l0ODc5hX5+UALu+CIMkrEYt2JQHVnxTT15iWBEebUVnsF4mBrOoKa3oyxqlIvJMGuFszMZV6XZ0IGxJ752Q+sOYHb1Kq0ZXXVVEHzjZ0QmiOGEjhprM4XFEc5RJQpQY1XqpoIxlR2fut0qxo5v1Gr6mZMnwjONyP3eyUDZGWAmXWjpPy0o4Wz8RRDFDRXgBYUX4i6em4PYH0WjWJ+2BKQRqlcAvDnMuH0RR5P3hrF+ciITZ9OMFnn37vZvwrfdsQqucAcCs0uxiXK3X8IRvtsObjMND8zg+ZodOrcK2ZfWLOv5yYEWTZGXr5XZ0qQg36tRQqYSIizzZ0QmiuFEutvmIsgqx7xKlD1fCfcEF43hZT3ilKOEqlcA3waMt6ay3u7XGmNJzsc059rjT8vV+WRMJEUTxQ0V4AWE94ex8fNmKRr7rX2wwRXfW5YfLF4QvIFmmSQmPzWUrG/Hm9a34lyuWxfz65q46XLupfUFYC/u7Wq/hqerTil78RPxy7wAA4Op1LXEV+EqC2dF7mR3dL722rD1gbXu4CCclnCCKG6UdnQU60SYwUSqwa30wJMIrr58YfERZBW0qxRtTNsfH36a2hmmMGlN2Rm7JW9pASjhR/NDKs4CYDVosqavCwIzUD37ZyoYCH1F8WO/djNPHVQidWhURMkaEsRi0+N4/nZf0ftFjS7gSbtDw+eLTjuRKuMMbwJ8ODQMA3nv+koyOudxYLtvRhufccHoDEUo4AKxrk1o/VAJ4wipBEMVJI1O8FCPKrEbabCRKA5MiG8bhDUT0O1faiDKAWe/dC8aUzXCXZfpFuM3j54o49YQTpQAp4QWGWWIFAbh0RWOBjyY+ylnhcworerEq96WCSS4Iw3b0sC2NpaqnooT/6dAInL4gljaYcOHSuhwdbWlRa9LxdoDTk45wT7j8mm/slIrwOpOe3scEUeQwO/ronAczDtmOTsFsRImgVgl8szc6nK3SRpQByoT0yNeCTeFJdfwtc8hM2r08lK3JrIe5gl5LonSpnG23IuWcNgueODKGDR01RW0hZoudWZc/PJ6MrOiLJhU7+lQKSvies9MAgLef204FpYLlTSZMObzoHXdEpKNLXzPja9dtQGtN8U0kIAgiErbYHrNJAUz1Jh06ayt7FCNRWpj0Grj9wYhwNm8gyO3plWRHtxiltU+0HT3d8bfhnnBPuB+cQtmIEoGK8AJzw9ZOHBqcwwcv7in0oSREqYTzUBxSIRYNCydxyXZ0dnGOUMIdyZXw0TlpYdpDo8kiWNFkxu4zM+idcPCdd6M2fNq7fmtnoQ6NIIg0iJ4o8f6LuqHTkJmPKB2q9WpMOcLtZ0DYii59vXKW5FwJX2RPOHPITDt9OClPQqFQNqJUqJxPfJHSbDHgwX/eWujDSEotV8LDdvRiVu5LBabKsuKb94bptdxKPe1MroSPzEuzxFnaOiHBNiUGZpy8R5xyDAii9NBr1Kip0mLO5YdBq8JNF3YV+pAIIi1izQrnyeh6DdSqynGxMeu9Mh3d4w/CKTvWUnVa1lXpoFYJCIZE7D07A4BC2YjSgbaRiZRg81iVdnSa0bp4qqMuyspgNqUSHj3SBACOjMzD4Q0gFBIxLls0Ux3rUSmw13BOTvUHqAgniFKFWdKv39KZsl2VIIqF6PYzoDJD2YCw9V6phDOBR60SUn49VCqBh9i+MjgHAFjZbM7ikRJE7qAinEgJPqLM6eN2oVSDM4j4sHFZbPfX4ZUuQtV6DX/NAyERNndkeMlzJyfx5m+/iHv/fARTDi/8QREqAWg2x55LXqkwy9ucyw+XPzIdnSCI0uJ9F3Zhc1ctbr9ieaEPhSDSRrnpPuP04bmTkxU5ngxQ2tHDa5tZxdpSlYYrgPWFh0RgY4eVwmmJkqGytt6IjKlR2NFnWTo6KeGLxqSPTEtV7orrNWqYDRrYPQFMOb2wKjY9njk+AQB4uW8WI/OSCt5kNkCjpn01JcytMe/2LwhmIwiitLh5Wzdu3tZd6MMgiIxQKuFf+ONr+Ouro3jnee0AKlEJXxjMNpuhy5LlRRi1avzPDZtoHUSUDPROJVIiHMzmV+xWUhG+WKLt6I4oaxrvC48KZzswMAsAGJhxoX9aGstBKd8LqeFKuI+PgTPqKmuxQxAEQRSear7pHsRZeZzWjqPjACprPBmgHFEWLsJn0gxlY5zfUweVANzztrVYSsnoRAlBq1EiJXgR7laMKDNV1kUjF1SxIpzNCecjyqTXtt6kw9kpJ6YVY8rcviCOjtgAAMGQiD1yGEmblfrBo2EODqcvyG1vVVpSwgmCIIj8YtKFr/cscJW53yrNjs6D2ZRKOHNZprm2vO3yZXjv+Ut4YU8QpQIp4URKsGImGBIxMOMCQEp4NlDujAORwWxAOFhs2hlWwl8dmkMgFA5qe7F3CgAlo8fCbNCCjU0flRPkyY5OEARB5BtmR7d7AlzMYFSeHV1aU8ayo2cyeYcKcKIUoSKcSAmDVo1meR4jKxSpCF88fGec2dHlYDZ2Qa4zLbSjHxiYi3gOtilCyegLUasEvuM+KvfOUzAbQRAEkW9Y+9nYvBv+YOTEk8q1owcQlEUFmrxDVBpUhBMp81/XbYBWHU6spCJ88Zii7eh8TjjrCWdKeNiOzvrBo3eLSQmPDXNxeAMhAOFEeoIgCILIF+x63y9vnCupNCW8oVoPs0GDYEjEa8PzAMLp6On2hBNEqUJFOJEyV65qwndvPA8alYBGs77iLhq5gBfh3iBEUeTBbNyObgrPCn91aA5/PDSM/f1SEf72Te0Rz0VFeGxqomxqZEcnCIIg8g2bhjI0417wtUrrCVerBGxbWg8AePGU1FIX7gmnIpyoDKgIJ9LijWtb8OSnLsPv/uWitOY4ErHhI8p8AXj8Id7rbZatafVyOvqxMRve9YNd+NdfHcKM0wetWsC1m9oinquN7OgxsUbtqpMdnSAIgsg3zI7uC0quLJ1ilFal2dEB4JIVDQCAl1gR7gzPCSeISoCkTCJtltEIiKzBesJFEZi0S5ZzQQgneLNgtjPyOJOaKi3qqnR484ZWrGoxQxCkx2pUAh9nRkRCSjhBEARRaJjzjXF+Tx12nZlGMCRWpLPwomVSEb6vfxYef1AxeYeUcKIyqLxPPUEUEVU6NS+kWXp3tU7DXQbRhfUdb1iJm7d18/931BoxOONGs8UANTkTYlITtatepaXTHkEQBJFfqqOK8M46I1SqBuw6PYXlTZUnbixrNKHFYsCYzYN9fbOYo55wosIgOzpBFBBBELgaPi4r4cod8XrFjrBaJeDN61sjHr+0Qbpwt9VQP3g8opVwsqMTBEEQ+SZaCa8z6fCTm7dg112vq8h2MkEQcPFySQ1/+vg4nD5pVCsp4USlQEU4QRQYZo8el0doVSuK8JoqHZjAfdmKBt4jzmCtAa3WyruAp4qyJ1yjEqDT0GmPIAiCyC8sA4ZRb9JDp1FVdCvZJSukcLY/vzICgI0VJbcaURnQapQgCgyzqLE51krLmlol8Fnhbz+3fcFj37apDSuaqvH2c9sWfI2QUCrhpIITBEEQhSDajs4yXyqZq1Y3o6ZKiylHOJRNEKi1jqgMqAgniALDLGqnJx0AFvaBf/qNK3HjBUtw9bqWBY/d1FmDHXdcjqtWN+f+QEsUZU84hbIRBEEQhcCoVUMZ3VLJCjjDatTik69bwf9fS/3gRAVBRThBFBhWGL46NAcAWBYV0HLD1iX4yjvWQ6+hAjITIotwsrkRBEEQ+UeZAQOQEs74pwu7sLTRBICKcKKyoCKcIAoMs6jNuvwAaARctrEawxd1o5Y2MgiCIIjCoAxnq6MAMgCAVq3CvW9bB71GhQuX1Rf6cAgib5AsRBAFJjoxtRJHleQSsqMTBEEQxYAynI1GcYW5ZEUDXvnidhhoo5yoIEgJJ4gCE52YymxZRHawKoLZqvS070gQBEEUBuZ8q63SQqOmJbgSKsCJSoPOAARRYJQ9Yk1mPSwGbYJ7E+miVav4wqeKLvIEQRBEgWDOt+hxowRBVB5UhBNEgVHa0akfPDcwNZzs6ARBEESh4EU49YMTRMVDRThBFBilHZ36wXMD6wunOeEEQRBEoajmSjgV4QRR6VARThAFJlIJp37wXMCKcFLCCYIgiELBNt3rTWRHJ4hKJ2dF+OzsLG666SZYrVZYrVbcdNNNmJubS/nxH/nIRyAIAu6///5cHSJBFAXVyiKclPCcUCOPKTPSnHCCIAiiQGztroNGJeCCpXWFPhSCIApMzorwG2+8EYcOHcITTzyBJ554AocOHcJNN92U0mP/8Ic/YM+ePWhra8vV4RFE0VClo57wXLOqxQyAnAYEQRBE4bh2Uzteu+eNeMsGWt8S/7+9+4+Juv7jAP68QziUwUf5eTIUXTVtCjStAGfFty9d9A1JWb/M3aq1flhnP2zObGxYWwNbmTbbLFq1XBv0Q8itDYeDAOPApGNCP0iwH2YcmOJBUHfhvb5/ND7rAhXk8/nAwfOx3R987nUfPp8990TffLjP0Uyny2Whb7/9FpWVlWhsbER6ejoAoKSkBJmZmWhvb8eSJUsu+NpTp07B4XDg4MGDuP322/U4PKIpZfjP0+aEhWC+Ej7JRzM9PfGfK/G/lPlchBMR0aTiR3EREaDTItzpdEJRFHUBDgAZGRlQFAUNDQ0XXIT7/X7Y7XZs2bIFy5YtG9P38nq98Hq96td9fX0TO3gig11tjUJMRBhuWhIHk8k02YczLYWYTbzpHRERERFNCboswt1uN+Lj40dsj4+Ph9vtvuDrduzYgVmzZuHJJ58c8/cqKirCCy+8cFnHSTQVzIsIQ9Pz/8WsEN4nkYiIiIhouhvX//q3b98Ok8l00cfRo0cBYNQreiJywSt9zc3N2L17N957771xXQ3ctm0bPB6P+jh58uR4ToloSuACnIiIiIhoZhjXlXCHw4F77733ojOLFi3CsWPH0N3dPeK506dPIyEhYdTX1dfXo6enBwsXLlS3nT9/Hs8++yx27dqFH3/8cdTXWSwWWCz8qAciIiIiIiKa+sa1CI+NjUVsbOwl5zIzM+HxeHDkyBFcf/31AICmpiZ4PB6sWrVq1NfY7XZkZ2cHbLv11ltht9vx4IMPjucwiYiIiIiIiKYkXd4TfvXVVyMnJwcPP/ww3nzzTQDAI488gtzc3ICbsi1duhRFRUVYt24dYmJiEBMTE7Cf0NBQWK3Wi95NnYiIiIiIiChY6PZG1A8++AApKSmw2Wyw2WxITU3Fvn37Amba29vh8Xj0OgQiIiIiIiKiKcUkIjLZB6Glvr4+KIoCj8eDqKioyT4cIiIiIiIimubGsw7lLZmJiIiIiIiIDMJFOBEREREREZFBuAgnIiIiIiIiMogud0efTMNvce/r65vkIyEiIiIiIqKZYHj9OZZbrk27RXh/fz8AYMGCBZN8JERERERERDST9Pf3Q1GUi85Mu7uj+/1+/Prrr4iMjITJZJrsw5kUfX19WLBgAU6ePMk7xAcZZhecmFvwYnbBi9kFL2YXvJhdcGJuxhAR9Pf3IzExEWbzxd/1Pe2uhJvNZiQlJU32YUwJUVFRLFqQYnbBibkFL2YXvJhd8GJ2wYvZBSfmpr9LXQEfxhuzERERERERERmEi3AiIiIiIiIig3ARPg1ZLBYUFhbCYrFM9qHQODG74MTcghezC17MLngxu+DF7IITc5t6pt2N2YiIiIiIiIimKl4JJyIiIiIiIjIIF+FEREREREREBuEinIiIiIiIiMggXIQTERERERERGYSL8Cmqrq4Oa9asQWJiIkwmEyoqKgKe7+7uxgMPPIDExETMmTMHOTk5OH78eMCM2+2G3W6H1WpFREQEVqxYgY8//jhgpre3F3a7HYqiQFEU2O12nDt3Tuezm96Mym7RokUwmUwBj+eee07v05u2tMits7MT69atQ1xcHKKionD33Xeju7s7YIad055R2bFz2ioqKsJ1112HyMhIxMfHY+3atWhvbw+YERFs374diYmJmD17NrKysvD1118HzHi9XmzatAmxsbGIiIhAXl4efvnll4AZ9k5bRmbH3mlLq+zeeustZGVlISoqCiaTadQ+sXfaMjI79k5/XIRPUQMDA0hLS8OePXtGPCciWLt2LU6cOIFPP/0ULpcLycnJyM7OxsDAgDpnt9vR3t6OAwcOoLW1Ffn5+bjnnnvgcrnUmfvuuw8tLS2orKxEZWUlWlpaYLfbDTnH6cqo7ADgxRdfRFdXl/ooKCjQ/fymq4nmNjAwAJvNBpPJhOrqanzxxRfw+XxYs2YN/H6/ui92TntGZQewc1qqra3FE088gcbGRlRVVWFoaAg2my3gZ+HLL7+MnTt3Ys+ePfjyyy9htVpxyy23oL+/X515+umnUV5ejtLSUhw+fBi///47cnNzcf78eXWGvdOWkdkB7J2WtMpucHAQOTk5eP755y/4vdg7bRmZHcDe6U5oygMg5eXl6tft7e0CQNra2tRtQ0NDEh0dLSUlJeq2iIgIef/99wP2FR0dLW+//baIiHzzzTcCQBobG9XnnU6nAJDvvvtOp7OZWfTKTkQkOTlZXnvtNd2OfSa7nNwOHjwoZrNZPB6POnP27FkBIFVVVSLCzhlBr+xE2Dm99fT0CACpra0VERG/3y9Wq1WKi4vVmT///FMURZG9e/eKiMi5c+ckNDRUSktL1ZlTp06J2WyWyspKEWHvjKBXdiLsnd4uJ7t/qqmpEQDS29sbsJ29059e2Ymwd0bglfAg5PV6AQDh4eHqtpCQEISFheHw4cPqttWrV6OsrAxnz56F3+9HaWkpvF4vsrKyAABOpxOKoiA9PV19TUZGBhRFQUNDgzEnM8Nold2wHTt2ICYmBtdccw1eeukl+Hw+Q85jphlLbl6vFyaTCRaLRZ0JDw+H2WxWZ9g542mV3TB2Tj8ejwcAEB0dDQD44Ycf4Ha7YbPZ1BmLxYKbbrpJ7UtzczP++uuvgJnExEQsX75cnWHv9KdXdsPYO/1cTnZjwd7pT6/shrF3+uIiPAgtXboUycnJ2LZtG3p7e+Hz+VBcXAy3242uri51rqysDENDQ4iJiYHFYsGjjz6K8vJyXHHFFQD+ft9xfHz8iP3Hx8fD7XYbdj4ziVbZAcBTTz2F0tJS1NTUwOFwYNeuXXj88ccn47SmvbHklpGRgYiICGzduhWDg4MYGBjAli1b4Pf71Rl2znhaZQewc3oSEWzevBmrV6/G8uXLAUDtREJCQsBsQkKC+pzb7UZYWBjmzZt30Rn2Tj96Zgewd3q63OzGgr3Tl57ZAeydEWZN9gHQ+IWGhuKTTz7BQw89hOjoaISEhCA7Oxu33XZbwFxBQQF6e3tx6NAhxMbGoqKiAnfddRfq6+uRkpICADCZTCP2LyKjbqeJ0zK7Z555Rp1PTU3FvHnzcOedd6q/uSTtjCW3uLg4fPTRR9i4cSNef/11mM1mrF+/HitWrEBISIg6x84ZS8vs2Dn9OBwOHDt2bMRfHgAjOzOWvvx7hr3Tj97ZsXf60Tq7S+3jcvdDI+mdHXunPy7Cg9TKlSvR0tICj8cDn8+HuLg4pKen49prrwXw951+9+zZg7a2NixbtgwAkJaWhvr6erzxxhvYu3cvrFbriLv/AsDp06dH/BaNtKNFdqPJyMgAAHR0dPAHpA4ulRsA2Gw2dHZ24rfffsOsWbMwd+5cWK1WLF68GADYuUmiRXajYee0sWnTJhw4cAB1dXVISkpSt1utVgB/X92ZP3++ur2np0fti9Vqhc/nQ29vb8AV1Z6eHqxatUqdYe/0oXd2o2HvtDGR7MaCvdOP3tmNhr3THv8cPcgpioK4uDgcP34cR48exR133AHg7zsfAoDZHBhxSEiIerffzMxMeDweHDlyRH2+qakJHo/nov8AkjYmkt1ohu+c/s8fvKS9C+X2T7GxsZg7dy6qq6vR09ODvLw8AOzcZJtIdqNh5yZGROBwOLB//35UV1eP+IXH4sWLYbVaUVVVpW7z+Xyora1V+7Jy5UqEhoYGzHR1daGtrU2dYe+0Z1R2o2HvJkaL7MaCvdOeUdmNhr3TgdF3gqOx6e/vF5fLJS6XSwDIzp07xeVyyU8//SQiIh9++KHU1NRIZ2enVFRUSHJysuTn56uv9/l8cuWVV8oNN9wgTU1N0tHRIa+88oqYTCb57LPP1LmcnBxJTU0Vp9MpTqdTUlJSJDc31/DznU6MyK6hoUHd74kTJ6SsrEwSExMlLy9vUs55OphobiIi77zzjjidTuno6JB9+/ZJdHS0bN68OWCGndOeEdmxc9rbuHGjKIoin3/+uXR1damPwcFBdaa4uFgURZH9+/dLa2urrF+/XubPny99fX3qzGOPPSZJSUly6NAh+eqrr+Tmm2+WtLQ0GRoaUmfYO20ZlR17pz2tsuvq6hKXyyUlJSUCQOrq6sTlcsmZM2fUGfZOW0Zlx94Zg4vwKWr4YwP+/bj//vtFRGT37t2SlJQkoaGhsnDhQikoKBCv1xuwj++//17y8/MlPj5e5syZI6mpqSM+9urMmTOyYcMGiYyMlMjISNmwYcOoH1VAY2dEds3NzZKeni6Kokh4eLgsWbJECgsLZWBgwMhTnVa0yG3r1q2SkJAgoaGhctVVV8mrr74qfr8/YIad054R2bFz2hstMwDy7rvvqjN+v18KCwvFarWKxWKRG2+8UVpbWwP288cff4jD4ZDo6GiZPXu25Obmys8//xwww95py6js2DvtaZVdYWHhJffD3mnLqOzYO2OYRES0uaZORERERERERBfD94QTERERERERGYSLcCIiIiIiIiKDcBFOREREREREZBAuwomIiIiIiIgMwkU4ERERERERkUG4CCciIiIiIiIyCBfhRERERERERAbhIpyIiIiIiIjIIFyEExERERERERmEi3AiIiIiIiIig3ARTkRERERERGQQLsKJiIiIiIiIDPJ/ODTzYJH1iEoAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x350 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot deseasoned \n",
    "plt.figure(figsize = (12,3.5))\n",
    "plt.plot(des_sst_mean.time, des_sst_mean.values)\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c8029c5-7de1-4b13-9e51-f19aa9c23dee",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}