Build_Week_1_Vis_2_CM.ipynb

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    "colab": {
      "name": "Build_Week_1_Vis_2_CM.ipynb",
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      "authorship_tag": "ABX9TyNUaXrWHjsFE/G8T1w7OOLJ",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/KristineYW/Unit-1-Build/blob/master/Build_Week_1_Vis_2_CM.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "96EDbWHG46gq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Import libraries\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import math"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cnev_PxrACRl",
        "colab_type": "code",
        "outputId": "ee252f39-9ddc-4b59-c821-5e2c37076e5a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "ch_mort = pd.read_csv('https://raw.githubusercontent.com/KristineYW/Unit-1-Build/master/NCHS_-_Childhood_Mortality_Rates.csv')\n",
        "\n",
        "ch_mort.head()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1900</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1,983.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1901</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1,695.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1902</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1,655.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1903</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1,542.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1904</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1,591.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Year  Age Group Death Rate\n",
              "0  1900  1-4 Years    1,983.8\n",
              "1  1901  1-4 Years    1,695.0\n",
              "2  1902  1-4 Years    1,655.7\n",
              "3  1903  1-4 Years    1,542.1\n",
              "4  1904  1-4 Years    1,591.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
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        "colab": {
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        }
      },
      "source": [
        "ch_mort['Death Rate'] = ch_mort['Death Rate'].str.replace(',','').astype(float)\n",
        "\n",
        "ch_mort.head()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1900</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1983.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1901</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1695.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1902</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1655.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1903</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1542.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1904</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>1591.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Year  Age Group  Death Rate\n",
              "0  1900  1-4 Years      1983.8\n",
              "1  1901  1-4 Years      1695.0\n",
              "2  1902  1-4 Years      1655.7\n",
              "3  1903  1-4 Years      1542.1\n",
              "4  1904  1-4 Years      1591.5"
            ]
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          "execution_count": 27
        }
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        }
      },
      "source": [
        "ch_mort_p = ch_mort.pivot(index='Age Group',columns='Year',values='Death Rate')\n",
        "\n",
        "ch_mort_p.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Year</th>\n",
              "      <th>1900</th>\n",
              "      <th>1901</th>\n",
              "      <th>1902</th>\n",
              "      <th>1903</th>\n",
              "      <th>1904</th>\n",
              "      <th>1905</th>\n",
              "      <th>1906</th>\n",
              "      <th>1907</th>\n",
              "      <th>1908</th>\n",
              "      <th>1909</th>\n",
              "      <th>1910</th>\n",
              "      <th>1911</th>\n",
              "      <th>1912</th>\n",
              "      <th>1913</th>\n",
              "      <th>1914</th>\n",
              "      <th>1915</th>\n",
              "      <th>1916</th>\n",
              "      <th>1917</th>\n",
              "      <th>1918</th>\n",
              "      <th>1919</th>\n",
              "      <th>1920</th>\n",
              "      <th>1921</th>\n",
              "      <th>1922</th>\n",
              "      <th>1923</th>\n",
              "      <th>1924</th>\n",
              "      <th>1925</th>\n",
              "      <th>1926</th>\n",
              "      <th>1927</th>\n",
              "      <th>1928</th>\n",
              "      <th>1929</th>\n",
              "      <th>1930</th>\n",
              "      <th>1931</th>\n",
              "      <th>1932</th>\n",
              "      <th>1933</th>\n",
              "      <th>1934</th>\n",
              "      <th>1935</th>\n",
              "      <th>1936</th>\n",
              "      <th>1937</th>\n",
              "      <th>1938</th>\n",
              "      <th>1939</th>\n",
              "      <th>...</th>\n",
              "      <th>1978</th>\n",
              "      <th>1979</th>\n",
              "      <th>1980</th>\n",
              "      <th>1981</th>\n",
              "      <th>1982</th>\n",
              "      <th>1983</th>\n",
              "      <th>1984</th>\n",
              "      <th>1985</th>\n",
              "      <th>1986</th>\n",
              "      <th>1987</th>\n",
              "      <th>1988</th>\n",
              "      <th>1989</th>\n",
              "      <th>1990</th>\n",
              "      <th>1991</th>\n",
              "      <th>1992</th>\n",
              "      <th>1993</th>\n",
              "      <th>1994</th>\n",
              "      <th>1995</th>\n",
              "      <th>1996</th>\n",
              "      <th>1997</th>\n",
              "      <th>1998</th>\n",
              "      <th>1999</th>\n",
              "      <th>2000</th>\n",
              "      <th>2001</th>\n",
              "      <th>2002</th>\n",
              "      <th>2003</th>\n",
              "      <th>2004</th>\n",
              "      <th>2005</th>\n",
              "      <th>2006</th>\n",
              "      <th>2007</th>\n",
              "      <th>2008</th>\n",
              "      <th>2009</th>\n",
              "      <th>2010</th>\n",
              "      <th>2011</th>\n",
              "      <th>2012</th>\n",
              "      <th>2013</th>\n",
              "      <th>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Age Group</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1-4 Years</th>\n",
              "      <td>1983.8</td>\n",
              "      <td>1695.0</td>\n",
              "      <td>1655.7</td>\n",
              "      <td>1542.1</td>\n",
              "      <td>1591.5</td>\n",
              "      <td>1498.9</td>\n",
              "      <td>1580.0</td>\n",
              "      <td>1468.3</td>\n",
              "      <td>1396.8</td>\n",
              "      <td>1348.9</td>\n",
              "      <td>1397.3</td>\n",
              "      <td>1176.0</td>\n",
              "      <td>1094.1</td>\n",
              "      <td>1193.4</td>\n",
              "      <td>1024.2</td>\n",
              "      <td>924.2</td>\n",
              "      <td>1111.5</td>\n",
              "      <td>1066.0</td>\n",
              "      <td>1573.5</td>\n",
              "      <td>928.0</td>\n",
              "      <td>987.2</td>\n",
              "      <td>801.2</td>\n",
              "      <td>742.0</td>\n",
              "      <td>806.7</td>\n",
              "      <td>683.2</td>\n",
              "      <td>641.0</td>\n",
              "      <td>723.4</td>\n",
              "      <td>591.0</td>\n",
              "      <td>647.5</td>\n",
              "      <td>625.5</td>\n",
              "      <td>563.6</td>\n",
              "      <td>526.6</td>\n",
              "      <td>461.9</td>\n",
              "      <td>472.6</td>\n",
              "      <td>507.7</td>\n",
              "      <td>440.9</td>\n",
              "      <td>439.8</td>\n",
              "      <td>418.7</td>\n",
              "      <td>383.8</td>\n",
              "      <td>318.3</td>\n",
              "      <td>...</td>\n",
              "      <td>67.9</td>\n",
              "      <td>64.2</td>\n",
              "      <td>63.9</td>\n",
              "      <td>60.6</td>\n",
              "      <td>58.2</td>\n",
              "      <td>56.1</td>\n",
              "      <td>52.2</td>\n",
              "      <td>51.8</td>\n",
              "      <td>52.4</td>\n",
              "      <td>52.1</td>\n",
              "      <td>51.5</td>\n",
              "      <td>49.8</td>\n",
              "      <td>46.8</td>\n",
              "      <td>47.4</td>\n",
              "      <td>43.5</td>\n",
              "      <td>44.6</td>\n",
              "      <td>42.7</td>\n",
              "      <td>40.4</td>\n",
              "      <td>38.0</td>\n",
              "      <td>35.5</td>\n",
              "      <td>34.1</td>\n",
              "      <td>34.2</td>\n",
              "      <td>32.4</td>\n",
              "      <td>33.4</td>\n",
              "      <td>31.4</td>\n",
              "      <td>31.8</td>\n",
              "      <td>30.3</td>\n",
              "      <td>29.9</td>\n",
              "      <td>29.1</td>\n",
              "      <td>29.4</td>\n",
              "      <td>29.3</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.5</td>\n",
              "      <td>26.3</td>\n",
              "      <td>26.3</td>\n",
              "      <td>25.5</td>\n",
              "      <td>24.0</td>\n",
              "      <td>24.9</td>\n",
              "      <td>25.3</td>\n",
              "      <td>24.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10-14 Years</th>\n",
              "      <td>298.3</td>\n",
              "      <td>273.6</td>\n",
              "      <td>252.5</td>\n",
              "      <td>268.2</td>\n",
              "      <td>305.2</td>\n",
              "      <td>279.8</td>\n",
              "      <td>272.2</td>\n",
              "      <td>265.8</td>\n",
              "      <td>247.9</td>\n",
              "      <td>230.5</td>\n",
              "      <td>235.9</td>\n",
              "      <td>222.2</td>\n",
              "      <td>202.2</td>\n",
              "      <td>214.8</td>\n",
              "      <td>207.2</td>\n",
              "      <td>196.7</td>\n",
              "      <td>205.1</td>\n",
              "      <td>218.9</td>\n",
              "      <td>375.1</td>\n",
              "      <td>236.4</td>\n",
              "      <td>229.9</td>\n",
              "      <td>209.9</td>\n",
              "      <td>186.6</td>\n",
              "      <td>188.2</td>\n",
              "      <td>179.8</td>\n",
              "      <td>181.0</td>\n",
              "      <td>171.4</td>\n",
              "      <td>167.5</td>\n",
              "      <td>173.8</td>\n",
              "      <td>165.0</td>\n",
              "      <td>152.8</td>\n",
              "      <td>150.3</td>\n",
              "      <td>142.2</td>\n",
              "      <td>138.0</td>\n",
              "      <td>141.5</td>\n",
              "      <td>143.4</td>\n",
              "      <td>141.0</td>\n",
              "      <td>128.3</td>\n",
              "      <td>113.8</td>\n",
              "      <td>106.5</td>\n",
              "      <td>...</td>\n",
              "      <td>33.7</td>\n",
              "      <td>31.8</td>\n",
              "      <td>30.8</td>\n",
              "      <td>29.5</td>\n",
              "      <td>28.2</td>\n",
              "      <td>27.3</td>\n",
              "      <td>28.3</td>\n",
              "      <td>28.0</td>\n",
              "      <td>28.6</td>\n",
              "      <td>27.1</td>\n",
              "      <td>27.7</td>\n",
              "      <td>27.4</td>\n",
              "      <td>26.0</td>\n",
              "      <td>25.6</td>\n",
              "      <td>24.4</td>\n",
              "      <td>25.3</td>\n",
              "      <td>24.8</td>\n",
              "      <td>25.1</td>\n",
              "      <td>23.4</td>\n",
              "      <td>22.5</td>\n",
              "      <td>21.5</td>\n",
              "      <td>20.4</td>\n",
              "      <td>20.3</td>\n",
              "      <td>19.1</td>\n",
              "      <td>19.4</td>\n",
              "      <td>18.9</td>\n",
              "      <td>18.4</td>\n",
              "      <td>17.7</td>\n",
              "      <td>16.2</td>\n",
              "      <td>16.5</td>\n",
              "      <td>15.2</td>\n",
              "      <td>15.1</td>\n",
              "      <td>14.3</td>\n",
              "      <td>14.2</td>\n",
              "      <td>13.9</td>\n",
              "      <td>14.1</td>\n",
              "      <td>14.0</td>\n",
              "      <td>14.6</td>\n",
              "      <td>14.6</td>\n",
              "      <td>15.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15-19 Years</th>\n",
              "      <td>484.8</td>\n",
              "      <td>454.4</td>\n",
              "      <td>421.5</td>\n",
              "      <td>434.1</td>\n",
              "      <td>471.4</td>\n",
              "      <td>439.3</td>\n",
              "      <td>445.2</td>\n",
              "      <td>437.7</td>\n",
              "      <td>397.7</td>\n",
              "      <td>363.6</td>\n",
              "      <td>371.9</td>\n",
              "      <td>366.0</td>\n",
              "      <td>347.2</td>\n",
              "      <td>360.3</td>\n",
              "      <td>340.5</td>\n",
              "      <td>330.9</td>\n",
              "      <td>355.8</td>\n",
              "      <td>380.3</td>\n",
              "      <td>777.4</td>\n",
              "      <td>438.5</td>\n",
              "      <td>402.9</td>\n",
              "      <td>326.5</td>\n",
              "      <td>319.6</td>\n",
              "      <td>325.8</td>\n",
              "      <td>313.5</td>\n",
              "      <td>314.0</td>\n",
              "      <td>307.5</td>\n",
              "      <td>289.5</td>\n",
              "      <td>307.8</td>\n",
              "      <td>298.0</td>\n",
              "      <td>277.8</td>\n",
              "      <td>263.5</td>\n",
              "      <td>237.5</td>\n",
              "      <td>223.4</td>\n",
              "      <td>224.0</td>\n",
              "      <td>222.3</td>\n",
              "      <td>230.4</td>\n",
              "      <td>219.0</td>\n",
              "      <td>192.3</td>\n",
              "      <td>179.8</td>\n",
              "      <td>...</td>\n",
              "      <td>98.9</td>\n",
              "      <td>98.8</td>\n",
              "      <td>97.9</td>\n",
              "      <td>90.0</td>\n",
              "      <td>85.4</td>\n",
              "      <td>81.1</td>\n",
              "      <td>80.4</td>\n",
              "      <td>80.5</td>\n",
              "      <td>86.2</td>\n",
              "      <td>83.5</td>\n",
              "      <td>86.7</td>\n",
              "      <td>85.9</td>\n",
              "      <td>87.9</td>\n",
              "      <td>88.7</td>\n",
              "      <td>83.6</td>\n",
              "      <td>85.8</td>\n",
              "      <td>85.5</td>\n",
              "      <td>82.1</td>\n",
              "      <td>77.5</td>\n",
              "      <td>73.6</td>\n",
              "      <td>69.5</td>\n",
              "      <td>68.6</td>\n",
              "      <td>67.1</td>\n",
              "      <td>66.3</td>\n",
              "      <td>67.0</td>\n",
              "      <td>65.4</td>\n",
              "      <td>64.9</td>\n",
              "      <td>63.8</td>\n",
              "      <td>63.0</td>\n",
              "      <td>60.3</td>\n",
              "      <td>55.9</td>\n",
              "      <td>51.9</td>\n",
              "      <td>49.4</td>\n",
              "      <td>48.9</td>\n",
              "      <td>47.2</td>\n",
              "      <td>44.8</td>\n",
              "      <td>45.5</td>\n",
              "      <td>48.3</td>\n",
              "      <td>51.2</td>\n",
              "      <td>51.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5-9 Years</th>\n",
              "      <td>466.1</td>\n",
              "      <td>427.6</td>\n",
              "      <td>403.3</td>\n",
              "      <td>414.7</td>\n",
              "      <td>425.0</td>\n",
              "      <td>396.3</td>\n",
              "      <td>377.4</td>\n",
              "      <td>365.6</td>\n",
              "      <td>354.2</td>\n",
              "      <td>330.2</td>\n",
              "      <td>348.4</td>\n",
              "      <td>310.0</td>\n",
              "      <td>287.5</td>\n",
              "      <td>317.7</td>\n",
              "      <td>291.6</td>\n",
              "      <td>260.6</td>\n",
              "      <td>282.4</td>\n",
              "      <td>290.7</td>\n",
              "      <td>447.9</td>\n",
              "      <td>300.0</td>\n",
              "      <td>295.2</td>\n",
              "      <td>281.4</td>\n",
              "      <td>239.6</td>\n",
              "      <td>240.0</td>\n",
              "      <td>221.7</td>\n",
              "      <td>211.5</td>\n",
              "      <td>213.8</td>\n",
              "      <td>208.3</td>\n",
              "      <td>213.1</td>\n",
              "      <td>208.0</td>\n",
              "      <td>189.8</td>\n",
              "      <td>182.0</td>\n",
              "      <td>165.9</td>\n",
              "      <td>161.3</td>\n",
              "      <td>165.1</td>\n",
              "      <td>162.4</td>\n",
              "      <td>154.6</td>\n",
              "      <td>142.9</td>\n",
              "      <td>128.8</td>\n",
              "      <td>112.6</td>\n",
              "      <td>...</td>\n",
              "      <td>32.7</td>\n",
              "      <td>31.1</td>\n",
              "      <td>30.4</td>\n",
              "      <td>29.1</td>\n",
              "      <td>28.3</td>\n",
              "      <td>26.5</td>\n",
              "      <td>25.3</td>\n",
              "      <td>25.0</td>\n",
              "      <td>23.9</td>\n",
              "      <td>24.7</td>\n",
              "      <td>24.5</td>\n",
              "      <td>24.1</td>\n",
              "      <td>22.2</td>\n",
              "      <td>21.5</td>\n",
              "      <td>20.3</td>\n",
              "      <td>21.0</td>\n",
              "      <td>19.7</td>\n",
              "      <td>19.4</td>\n",
              "      <td>19.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>17.2</td>\n",
              "      <td>16.9</td>\n",
              "      <td>15.8</td>\n",
              "      <td>15.3</td>\n",
              "      <td>15.2</td>\n",
              "      <td>14.8</td>\n",
              "      <td>14.8</td>\n",
              "      <td>14.6</td>\n",
              "      <td>14.0</td>\n",
              "      <td>13.8</td>\n",
              "      <td>12.6</td>\n",
              "      <td>12.5</td>\n",
              "      <td>11.5</td>\n",
              "      <td>12.1</td>\n",
              "      <td>11.4</td>\n",
              "      <td>11.8</td>\n",
              "      <td>11.5</td>\n",
              "      <td>11.7</td>\n",
              "      <td>12.2</td>\n",
              "      <td>11.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4 rows × 118 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "Year           1900    1901    1902    1903  ...  2014  2015  2016  2017\n",
              "Age Group                                    ...                        \n",
              "1-4 Years    1983.8  1695.0  1655.7  1542.1  ...  24.0  24.9  25.3  24.3\n",
              "10-14 Years   298.3   273.6   252.5   268.2  ...  14.0  14.6  14.6  15.5\n",
              "15-19 Years   484.8   454.4   421.5   434.1  ...  45.5  48.3  51.2  51.5\n",
              "5-9 Years     466.1   427.6   403.3   414.7  ...  11.5  11.7  12.2  11.6\n",
              "\n",
              "[4 rows x 118 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I8ecm42UJGu9",
        "colab_type": "code",
        "outputId": "d042b9d8-7e49-410b-ac6e-3fa6e88db6cf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 649
        }
      },
      "source": [
        "fig, ax = plt.subplots(figsize=(18, 10))\n",
        "\n",
        "ax.set_title(\"Child Mortality Rates\", color='black', weight='bold', fontsize=24, x=.475, y=1.05)\n",
        "\n",
        "#ax.set_yticklabels([0,200,400,2000], color='#000000', fontsize=15)\n",
        "ax.set_xticklabels([1880,1900,1920,1940,1960,1980,2000,2020], color='#000000', fontsize=15)\n",
        "\n",
        "\n",
        "fig.set_facecolor('#FFFFFF')\n",
        "ax.set_facecolor('#FFFFFF')\n",
        "\n",
        "ax.spines['right'].set_visible(False)\n",
        "ax.spines['top'].set_visible(False)\n",
        "\n",
        "ax.plot(ch_mort['Year'],ch_mort['Death Rate'], color='green',linewidth=3);"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A33zII08E16Q",
        "colab_type": "code",
        "outputId": "a6f4cd19-6560-4ddf-d8ec-d79e4762fd52",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "# Pull out each age group into separate dataframes\n",
        "\n",
        "first = ch_mort.loc[ch_mort['Age Group'] == '1-4 Years']\n",
        "\n",
        "first.tail()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2013</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>25.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>2014</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>2015</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2016</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>25.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>2017</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Age Group  Death Rate\n",
              "113  2013  1-4 Years        25.5\n",
              "114  2014  1-4 Years        24.0\n",
              "115  2015  1-4 Years        24.9\n",
              "116  2016  1-4 Years        25.3\n",
              "117  2017  1-4 Years        24.3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LKdooHtLFPIF",
        "colab_type": "code",
        "outputId": "406c6d0f-4dd6-4b7f-e604-9048311bf79a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "second = ch_mort.loc[ch_mort['Age Group'] == '5-9 Years']\n",
        "\n",
        "second.head()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>1900</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>466.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>1901</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>427.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>1902</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>403.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>1903</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>414.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>122</th>\n",
              "      <td>1904</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>425.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Age Group  Death Rate\n",
              "118  1900  5-9 Years       466.1\n",
              "119  1901  5-9 Years       427.6\n",
              "120  1902  5-9 Years       403.3\n",
              "121  1903  5-9 Years       414.7\n",
              "122  1904  5-9 Years       425.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QEpQD2iDFT6e",
        "colab_type": "code",
        "outputId": "f258ce8f-c02c-462d-bb45-59dcb1510fc2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "third = ch_mort.loc[ch_mort['Age Group'] == '10-14 Years']\n",
        "\n",
        "third.head()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>1900</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>298.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>1901</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>273.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>238</th>\n",
              "      <td>1902</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>252.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>1903</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>268.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>1904</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>305.2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year    Age Group  Death Rate\n",
              "236  1900  10-14 Years       298.3\n",
              "237  1901  10-14 Years       273.6\n",
              "238  1902  10-14 Years       252.5\n",
              "239  1903  10-14 Years       268.2\n",
              "240  1904  10-14 Years       305.2"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KvKGja5iFcqo",
        "colab_type": "code",
        "outputId": "d5a70293-0133-4d87-e39d-dfc53fe31756",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "fourth = ch_mort.loc[ch_mort['Age Group'] == '15-19 Years']\n",
        "\n",
        "\n",
        "fourth.head()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>354</th>\n",
              "      <td>1900</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>484.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>355</th>\n",
              "      <td>1901</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>454.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>356</th>\n",
              "      <td>1902</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>421.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>357</th>\n",
              "      <td>1903</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>434.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>358</th>\n",
              "      <td>1904</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>471.4</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year    Age Group  Death Rate\n",
              "354  1900  15-19 Years       484.8\n",
              "355  1901  15-19 Years       454.4\n",
              "356  1902  15-19 Years       421.5\n",
              "357  1903  15-19 Years       434.1\n",
              "358  1904  15-19 Years       471.4"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p_ceiD1FFmzd",
        "colab_type": "code",
        "outputId": "20b62196-4aa7-41d5-8915-237f2141dc43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 802
        }
      },
      "source": [
        "fig, ax = plt.subplots(figsize=(18, 10))\n",
        "\n",
        "ax.set_title(\"Child Mortality Rates\", color='black', weight='bold', fontsize=35, x=.475, y=1.15)\n",
        "fig.text(x=.25,y=.95,s=\"Number of child deaths per 100,000 by age group\", fontsize=25)\n",
        "fig.text(x=.28,y=.69,s=\"*WWI\", fontsize=15)\n",
        "\n",
        "ax.set_yticklabels([0,0,250,500,750,1000,1250,1500,1750,2000], color='#000000', fontsize=15)\n",
        "ax.set_xticklabels([1880,1900,1920,1940,1960,1980,2000,2020], color='#000000', fontsize=15)\n",
        "\n",
        "\n",
        "fig.set_facecolor('#FFFFFF')\n",
        "ax.set_facecolor('#FFFFFF')\n",
        "\n",
        "ax.set_xlabel('Year',fontsize=25,labelpad=30)\n",
        "ax.set_ylabel('Deaths per 100,000',fontsize=25,labelpad=20)\n",
        "\n",
        "ax.spines['right'].set_visible(False)\n",
        "ax.spines['top'].set_visible(False)\n",
        "\n",
        "l1 = ax.plot(first['Year'],first['Death Rate'], color='#0e1f4c',linewidth=4);\n",
        "l2 = ax.plot(second['Year'],second['Death Rate'], color='#17396c',linewidth=4);\n",
        "l3 = ax.plot(third['Year'],third['Death Rate'], color='#245b96',linewidth=4);\n",
        "l4 = ax.plot(fourth['Year'],fourth['Death Rate'], color='#6597b0',linewidth=4);\n",
        "\n",
        "ax.legend((l1,l2,l3,l4),labels=('1-4 Years','5-9 Years','10-14 Years','15-19 Years'), \n",
        "          fontsize=22,bbox_to_anchor=(0.9,0.9),shadow=True,facecolor='#f1f1f1',borderpad=1)\n",
        "\n",
        "ax.plot(first['Year'],first['Death Rate'], color='#0e1f4c',linewidth=3);\n",
        "ax.plot(second['Year'],second['Death Rate'], color='#17396c',linewidth=3);\n",
        "ax.plot(third['Year'],third['Death Rate'], color='#245b96',linewidth=3);\n",
        "ax.plot(fourth['Year'],fourth['Death Rate'], color='#6597b0',linewidth=3);\n",
        "\n",
        "plt.plot();"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:26: UserWarning: You have mixed positional and keyword arguments, some input may be discarded.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1296x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BCmxrZ3xqGQb",
        "colab_type": "code",
        "outputId": "65f95d95-9b5c-4737-b304-4f000d34f167",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        }
      },
      "source": [
        "first_1 = first.loc[first['Year'] >= 1990]\n",
        "\n",
        "first_1.head(54)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>90</th>\n",
              "      <td>1990</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>46.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>91</th>\n",
              "      <td>1991</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>47.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>1992</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>43.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>93</th>\n",
              "      <td>1993</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>44.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>1994</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>42.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>1995</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>40.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>1996</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>38.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>1997</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>35.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>1998</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>34.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>1999</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>34.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>100</th>\n",
              "      <td>2000</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>32.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>2001</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>33.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>2002</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>31.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>2003</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>31.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>2004</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>30.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>2005</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>29.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>2006</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>29.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107</th>\n",
              "      <td>2007</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>29.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>108</th>\n",
              "      <td>2008</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>29.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>2009</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>27.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>110</th>\n",
              "      <td>2010</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>26.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>111</th>\n",
              "      <td>2011</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>26.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>112</th>\n",
              "      <td>2012</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>26.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>113</th>\n",
              "      <td>2013</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>25.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>2014</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>115</th>\n",
              "      <td>2015</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>2016</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>25.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>2017</td>\n",
              "      <td>1-4 Years</td>\n",
              "      <td>24.3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Age Group  Death Rate\n",
              "90   1990  1-4 Years        46.8\n",
              "91   1991  1-4 Years        47.4\n",
              "92   1992  1-4 Years        43.5\n",
              "93   1993  1-4 Years        44.6\n",
              "94   1994  1-4 Years        42.7\n",
              "95   1995  1-4 Years        40.4\n",
              "96   1996  1-4 Years        38.0\n",
              "97   1997  1-4 Years        35.5\n",
              "98   1998  1-4 Years        34.1\n",
              "99   1999  1-4 Years        34.2\n",
              "100  2000  1-4 Years        32.4\n",
              "101  2001  1-4 Years        33.4\n",
              "102  2002  1-4 Years        31.4\n",
              "103  2003  1-4 Years        31.8\n",
              "104  2004  1-4 Years        30.3\n",
              "105  2005  1-4 Years        29.9\n",
              "106  2006  1-4 Years        29.1\n",
              "107  2007  1-4 Years        29.4\n",
              "108  2008  1-4 Years        29.3\n",
              "109  2009  1-4 Years        27.4\n",
              "110  2010  1-4 Years        26.5\n",
              "111  2011  1-4 Years        26.3\n",
              "112  2012  1-4 Years        26.3\n",
              "113  2013  1-4 Years        25.5\n",
              "114  2014  1-4 Years        24.0\n",
              "115  2015  1-4 Years        24.9\n",
              "116  2016  1-4 Years        25.3\n",
              "117  2017  1-4 Years        24.3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CHOS4r_glXUU",
        "colab_type": "code",
        "outputId": "1417b53a-d8ff-462a-8bd0-5af9b53d098d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        }
      },
      "source": [
        "second_1 = second.loc[second['Year'] >= 1990]\n",
        "\n",
        "second_1.head(54)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Year</th>\n",
              "      <th>Age Group</th>\n",
              "      <th>Death Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>208</th>\n",
              "      <td>1990</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>22.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>1991</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>21.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>1992</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>20.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>1993</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>1994</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>19.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>1995</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>19.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>1996</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>19.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>215</th>\n",
              "      <td>1997</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>216</th>\n",
              "      <td>1998</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>17.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>217</th>\n",
              "      <td>1999</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>16.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>218</th>\n",
              "      <td>2000</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>15.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>2001</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>15.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>220</th>\n",
              "      <td>2002</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>15.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>2003</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>14.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222</th>\n",
              "      <td>2004</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>14.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>2005</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>14.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>2006</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>2007</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>13.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>226</th>\n",
              "      <td>2008</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>12.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227</th>\n",
              "      <td>2009</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>12.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>228</th>\n",
              "      <td>2010</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>229</th>\n",
              "      <td>2011</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>12.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>230</th>\n",
              "      <td>2012</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>231</th>\n",
              "      <td>2013</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>2014</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>233</th>\n",
              "      <td>2015</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>234</th>\n",
              "      <td>2016</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>12.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>2017</td>\n",
              "      <td>5-9 Years</td>\n",
              "      <td>11.6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year  Age Group  Death Rate\n",
              "208  1990  5-9 Years        22.2\n",
              "209  1991  5-9 Years        21.5\n",
              "210  1992  5-9 Years        20.3\n",
              "211  1993  5-9 Years        21.0\n",
              "212  1994  5-9 Years        19.7\n",
              "213  1995  5-9 Years        19.4\n",
              "214  1996  5-9 Years        19.0\n",
              "215  1997  5-9 Years        18.0\n",
              "216  1998  5-9 Years        17.2\n",
              "217  1999  5-9 Years        16.9\n",
              "218  2000  5-9 Years        15.8\n",
              "219  2001  5-9 Years        15.3\n",
              "220  2002  5-9 Years        15.2\n",
              "221  2003  5-9 Years        14.8\n",
              "222  2004  5-9 Years        14.8\n",
              "223  2005  5-9 Years        14.6\n",
              "224  2006  5-9 Years        14.0\n",
              "225  2007  5-9 Years        13.8\n",
              "226  2008  5-9 Years        12.6\n",
              "227  2009  5-9 Years        12.5\n",
              "228  2010  5-9 Years        11.5\n",
              "229  2011  5-9 Years        12.1\n",
              "230  2012  5-9 Years        11.4\n",
              "231  2013  5-9 Years        11.8\n",
              "232  2014  5-9 Years        11.5\n",
              "233  2015  5-9 Years        11.7\n",
              "234  2016  5-9 Years        12.2\n",
              "235  2017  5-9 Years        11.6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JdN2lfbAlynS",
        "colab_type": "code",
        "outputId": "9d967ebf-41b6-42b0-f01f-6e4c3518068d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        }
      },
      "source": [
        "third_1 = third.loc[third['Year'] >= 1990]\n",
        "\n",
        "third_1.head(54)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>326</th>\n",
              "      <td>1990</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>26.0</td>\n",
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              "    <tr>\n",
              "      <th>327</th>\n",
              "      <td>1991</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>25.6</td>\n",
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              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>1992</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>24.4</td>\n",
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              "    <tr>\n",
              "      <th>329</th>\n",
              "      <td>1993</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>25.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>1994</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>24.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>331</th>\n",
              "      <td>1995</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>25.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>332</th>\n",
              "      <td>1996</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>23.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>333</th>\n",
              "      <td>1997</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>22.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>1998</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>21.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>1999</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>20.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>336</th>\n",
              "      <td>2000</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>20.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>337</th>\n",
              "      <td>2001</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>19.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>338</th>\n",
              "      <td>2002</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>19.4</td>\n",
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              "    <tr>\n",
              "      <th>339</th>\n",
              "      <td>2003</td>\n",
              "      <td>10-14 Years</td>\n",
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              "    <tr>\n",
              "      <th>340</th>\n",
              "      <td>2004</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>18.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>341</th>\n",
              "      <td>2005</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>17.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>342</th>\n",
              "      <td>2006</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>16.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>343</th>\n",
              "      <td>2007</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>16.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>344</th>\n",
              "      <td>2008</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>15.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>345</th>\n",
              "      <td>2009</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>15.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>346</th>\n",
              "      <td>2010</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>347</th>\n",
              "      <td>2011</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>348</th>\n",
              "      <td>2012</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>13.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>349</th>\n",
              "      <td>2013</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>350</th>\n",
              "      <td>2014</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>351</th>\n",
              "      <td>2015</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>352</th>\n",
              "      <td>2016</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>14.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>353</th>\n",
              "      <td>2017</td>\n",
              "      <td>10-14 Years</td>\n",
              "      <td>15.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year    Age Group  Death Rate\n",
              "326  1990  10-14 Years        26.0\n",
              "327  1991  10-14 Years        25.6\n",
              "328  1992  10-14 Years        24.4\n",
              "329  1993  10-14 Years        25.3\n",
              "330  1994  10-14 Years        24.8\n",
              "331  1995  10-14 Years        25.1\n",
              "332  1996  10-14 Years        23.4\n",
              "333  1997  10-14 Years        22.5\n",
              "334  1998  10-14 Years        21.5\n",
              "335  1999  10-14 Years        20.4\n",
              "336  2000  10-14 Years        20.3\n",
              "337  2001  10-14 Years        19.1\n",
              "338  2002  10-14 Years        19.4\n",
              "339  2003  10-14 Years        18.9\n",
              "340  2004  10-14 Years        18.4\n",
              "341  2005  10-14 Years        17.7\n",
              "342  2006  10-14 Years        16.2\n",
              "343  2007  10-14 Years        16.5\n",
              "344  2008  10-14 Years        15.2\n",
              "345  2009  10-14 Years        15.1\n",
              "346  2010  10-14 Years        14.3\n",
              "347  2011  10-14 Years        14.2\n",
              "348  2012  10-14 Years        13.9\n",
              "349  2013  10-14 Years        14.1\n",
              "350  2014  10-14 Years        14.0\n",
              "351  2015  10-14 Years        14.6\n",
              "352  2016  10-14 Years        14.6\n",
              "353  2017  10-14 Years        15.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ODsymsmwl2aE",
        "colab_type": "code",
        "outputId": "7b036ff0-132d-4c2d-906f-8bc154e3e820",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 917
        }
      },
      "source": [
        "fourth_1 = fourth.loc[fourth['Year'] >= 1990]\n",
        "\n",
        "fourth_1.head(54)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>444</th>\n",
              "      <td>1990</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>87.9</td>\n",
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              "    <tr>\n",
              "      <th>445</th>\n",
              "      <td>1991</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>88.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>446</th>\n",
              "      <td>1992</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>83.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>447</th>\n",
              "      <td>1993</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>85.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>448</th>\n",
              "      <td>1994</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>85.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>449</th>\n",
              "      <td>1995</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>82.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>450</th>\n",
              "      <td>1996</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>77.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>451</th>\n",
              "      <td>1997</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>73.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>452</th>\n",
              "      <td>1998</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>69.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>453</th>\n",
              "      <td>1999</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>68.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>454</th>\n",
              "      <td>2000</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>67.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>455</th>\n",
              "      <td>2001</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>66.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>456</th>\n",
              "      <td>2002</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>67.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>2003</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>65.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>458</th>\n",
              "      <td>2004</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>64.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>459</th>\n",
              "      <td>2005</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>63.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>460</th>\n",
              "      <td>2006</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>63.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>461</th>\n",
              "      <td>2007</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>60.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>462</th>\n",
              "      <td>2008</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>55.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>463</th>\n",
              "      <td>2009</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>51.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>464</th>\n",
              "      <td>2010</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>49.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>465</th>\n",
              "      <td>2011</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>48.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>466</th>\n",
              "      <td>2012</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>47.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>467</th>\n",
              "      <td>2013</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>44.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>468</th>\n",
              "      <td>2014</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>45.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>469</th>\n",
              "      <td>2015</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>48.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>470</th>\n",
              "      <td>2016</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>51.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>471</th>\n",
              "      <td>2017</td>\n",
              "      <td>15-19 Years</td>\n",
              "      <td>51.5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Year    Age Group  Death Rate\n",
              "444  1990  15-19 Years        87.9\n",
              "445  1991  15-19 Years        88.7\n",
              "446  1992  15-19 Years        83.6\n",
              "447  1993  15-19 Years        85.8\n",
              "448  1994  15-19 Years        85.5\n",
              "449  1995  15-19 Years        82.1\n",
              "450  1996  15-19 Years        77.5\n",
              "451  1997  15-19 Years        73.6\n",
              "452  1998  15-19 Years        69.5\n",
              "453  1999  15-19 Years        68.6\n",
              "454  2000  15-19 Years        67.1\n",
              "455  2001  15-19 Years        66.3\n",
              "456  2002  15-19 Years        67.0\n",
              "457  2003  15-19 Years        65.4\n",
              "458  2004  15-19 Years        64.9\n",
              "459  2005  15-19 Years        63.8\n",
              "460  2006  15-19 Years        63.0\n",
              "461  2007  15-19 Years        60.3\n",
              "462  2008  15-19 Years        55.9\n",
              "463  2009  15-19 Years        51.9\n",
              "464  2010  15-19 Years        49.4\n",
              "465  2011  15-19 Years        48.9\n",
              "466  2012  15-19 Years        47.2\n",
              "467  2013  15-19 Years        44.8\n",
              "468  2014  15-19 Years        45.5\n",
              "469  2015  15-19 Years        48.3\n",
              "470  2016  15-19 Years        51.2\n",
              "471  2017  15-19 Years        51.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lUATk2ITl9Hl",
        "colab_type": "code",
        "outputId": "62e6f80c-c282-44a5-8303-2b544458f002",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 802
        }
      },
      "source": [
        "fig, ax = plt.subplots(figsize=(18, 10))\n",
        "\n",
        "ax.set_title(\"Child Mortality Rates\", color='black', weight='bold', fontsize=35, x=.475, y=1.15)\n",
        "fig.text(x=.25,y=.95,s=\"Number of child deaths per 100,000 by age group\", fontsize=25)\n",
        "\n",
        "ax.set_yticklabels([0,10,20,30,40,50,60,70,80,90], color='#000000', fontsize=15)\n",
        "ax.set_xticklabels([0,1990,1995,2000,2005,2010,2015], color='#000000', fontsize=15)\n",
        "\n",
        "\n",
        "fig.set_facecolor('#FFFFFF')\n",
        "ax.set_facecolor('#FFFFFF')\n",
        "\n",
        "ax.set_xlabel('Year',fontsize=25,labelpad=30)\n",
        "ax.set_ylabel('Deaths per 100,000',fontsize=25,labelpad=20)\n",
        "\n",
        "ax.spines['right'].set_visible(False)\n",
        "ax.spines['top'].set_visible(False)\n",
        "\n",
        "l1 = ax.plot(first_1['Year'],first_1['Death Rate'], color='#0e1f4c',linewidth=4);\n",
        "l2 = ax.plot(second_1['Year'],second_1['Death Rate'], color='#17396c',linewidth=4);\n",
        "l3 = ax.plot(third_1['Year'],third_1['Death Rate'], color='#245b96',linewidth=4);\n",
        "l4 = ax.plot(fourth_1['Year'],fourth_1['Death Rate'], color='#6597b0',linewidth=4);\n",
        "\n",
        "ax.legend((l1,l2,l3,l4),labels=('1-4 Years','5-9 Years','10-14 Years','15-19 Years'), \n",
        "          fontsize=22,bbox_to_anchor=(.95,1),shadow=True,facecolor='#f1f1f1',borderpad=1)\n",
        "\n",
        "ax.plot(first_1['Year'],first_1['Death Rate'], color='#0e1f4c',linewidth=4);\n",
        "ax.plot(second_1['Year'],second_1['Death Rate'], color='#17396c',linewidth=4);\n",
        "ax.plot(third_1['Year'],third_1['Death Rate'], color='#245b96',linewidth=4);\n",
        "ax.plot(fourth_1['Year'],fourth_1['Death Rate'], color='#6597b0',linewidth=4);\n",
        "\n",
        "plt.plot();"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:25: UserWarning: You have mixed positional and keyword arguments, some input may be discarded.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MHTsWa9asMZimdnNWkqc/AGiOAGJtbY2WLVtqtmvZsiWsra1VR9f4+++/TW7bgv73v/+ZF2gZSUhIQEREhOZTQebQShjdK1599VXV0ZCWLFmCuXPnAshPjBVOsgH5TwXZ29uXe4xFuXPnDj777DOEhISgd+/eZrX58ccf8dprryEhIaHEyy2Pfa82yg4A3L59u0TbuvAIVl27doWTk5NRPyA//fQTfvrpJwD5yZaGDRuicePGeOSRR9CpUyc0adKk2MsmIrrf8AkQIqIK4OPjo1mm9ph4eQgICNAss7OzU52u9ih2edMaXtXb21szTiD/6YuqoF27dmjatKnJOg888ACeeuqpEs1f69dfb29vkzdfDg4Omq9bFecX5Yp8+iM+Ph5t2rQpVfIDQIlG6ahKevToobrdV61apaxbVRv9Rc3ly5fRr18/zVe4Clq8eDEGDRpUquQHUD77vqyfwCj8iqSXlxemT59uss3t27cRExODVatW4dVXX0XTpk3RuHFjfPXVV5Vy3SYiulcwAUJEVAG8vLw0kyCHDh2qkBgcHR01y6ysqs7HgdYNS+G+NQozlRypaEU93fHCCy+UON7MzEzV6ebMT6uO1jzVaD0tVB7Cw8Nx5cqVClteVaXT6VRfX0tKSsKGDRsAwKgfCQB46KGHzH6yp7SmT58OEUFmZiZiY2PxxhtvwNra2qheXl4eRo0ahdOnT2vOKz4+Hq+99lqVvZEvzvliDrWk78SJE/HZZ58V63yLjY1FWFhYlUp6ERFVNVXnGy8RkQXT6XTo0qWLatnVq1c1hym9H3l4eKhOv337tsl2RZVXpGeeeUbzxsXa2lqzPw5zaD3FoTYErLl1itMRb0Uly+Lj4/HLL7+olrVu3RqbN2/G5cuXkZOTAxGBiGD37t0VEltleP7551WPqSVLluCPP/7AuXPnjMoq40bY3t4ewcHB+Pjjj1WHmQXyX4cZN26c5jy+/vpr1SSDTqfDuHHjcOzYMdy8eVPZ7yJSocP8lnXH1WqvpQH5idTLly9j5cqVeOaZZ9CgQQPVpFJhK1euxNatW8s0RiIiS8E+QIiIKkjPnj01H1P/6KOP8Pjjj1dwRFWT1qsst2/fRmJioma5Vt8hlcHZ2RkjRozAggULjMr69Olj1sgWWvz8/FSnp6am4vLly/D391ctv3TpEtLS0oo1z8q0d+9e1ekBAQH49ddfVUebMTXa0r3OxcUFoaGhmDdvnsH03377De+//75RfTs7OzzzzDMVFZ6qkSNHIjIyEjt27DAq27ZtG/bt24d27doZlWnt+/Hjx2POnDmqZRW572vUqKE6vWbNmiXu20eLs7Mzhg8friR47t69i/j4eJw9exZHjhzBqlWrcPbsWaN23333XYX310NEdC9gAoSIqIIMHToUb731luoj/Vu3bsWyZcs0RzlRk5mZiYsXL6JBgwZlGWala9GihWbZ1q1bERoaqllWlbz00ktYuHCh0WP8pb1BatOmDXQ6nerrAZs3b9YcCUarHw2dToe2bduWKiYtWn2SpKenF9k2MTFRdfqjjz6qOdTutm3bzA+ugpRmGxT28ssvY8GCBUbDFm/ZssWobp8+fUz2PVRRZsyYoZoAAYD33ntP9SkfrX3fsWNH1empqanYv39/seIqzX5p27at6jl48+ZNjB07Fq6ursWKpTjs7OwQHByM4OBgPPHEExg7dixq1KhhNHKWVmfJRET3O74CQ0RUQRwcHPDmm29qlo8ZMwZffPFFkfMREWzevBlNmjTBzz//XJYhVgmBgYGao9XMmjVL9SmGkydPaj5dU1kaNmxoNOxlUFCQ5qtQ5qpWrZpmkmjmzJmqowqlpKRg1qxZqm1atmxpcpSi0nBzc1OdfuPGDdVfrQvSetT/1KlTRgkAANizZ49ZnWtWNK1tUJK+f+rWrWv2CCpVpR+IFi1aaA7/unPnTvzxxx9G07X2vdboKxMmTCj2K3ClOTa9vb1VR51KT0/H66+/bnbfJfv378eIESOMhuo9e/Ysli5dalYyxtnZWXV7lSTBRkR0P2AChIioAo0ZMwbdu3dXLcvNzcXYsWPRqlUrrFixAhcuXEB2djby8vJw48YN7N27FzNmzEBwcDD69u2rOuSlpdB6Eubff/9Ft27dcPDgQeTm5uLOnTtYv349evTogezs7AqOsmi//PKLQT8FcXFx0Ol0pZ7vG2+8oTr9woUL6NixI3bv3o3s7GxkZ2fjt99+Q6dOnXDhwgXVNhMnTix1PFrq1q2reTPbpUsXvP7665g5cyZmzZqFWbNmYe3atQZt1cTGxmLEiBE4e/ascm7Mnz8fvXr1Qk5OTrmsR2k0bNhQdfrevXvRvXt3TJ8+XVn/WbNmITY21uT8Xn311SKX6efnh549e5Yo3vIwefJkzbIZM2YYTdPa9zNmzMCKFSuQkpICEcGJEycwePBgLFmypNgxlebYBLTXaenSpejcuTM2btyIa9euAchPWt++fRsnTpzA6tWrMWbMGAQEBKBdu3ZYuXKl0bXr+vXrGDVqFHx9fdG/f398/vnn2LdvH65du6bUTUtLw759+9CvXz/V4cqryqhYRERVDV+BISKqQNbW1li7di1at26teaNz6NAhg1+HraysVH/xtmTh4eFYuHCh6qPwv//+O9q0aXNfbhe9J598Eh07dkR0dLRR2V9//YUuXbooiRZTv0Z36tQJAwcOLK8w4ejoiEcffRQHDx40KktISMDcuXMNpvXo0QODBw8GAHTu3BmOjo6qN3fffPMNvvnmG6NjoCoeE6b69tm5cyd27txpMK127dpo1KiRZpvOnTsjJCQEJ0+e1KwzfPhwszrLrChdunRBixYtEBMTY1S2ZcsWHD9+3GDo6CeeeEL1la2MjAyEhoYiNDS01Pu+NMcmAPTr1w89evRQfb0nOjpaOTf1nQaX5LhMT0/Hpk2bsGnTJoPpNjY2RSb7SvukGRGRpeITIEREFczd3R179uxBjx49zKpf1W7oKoKHhwcWL15s8mmJwttF68kaS6TT6bBu3TrUq1dPs47+qRMt9erVw7p168rkiRRTXn755RK18/DwUB36taCCx4BOp8OECRNKtKzyFBQUhG7dupXpPF955RWT5VXl9ZeCJk2apDpdRIyeAnn++ecRGBhocn4F932DBg0wYMCAYsdU0mNTLzIyEiEhISbr5OXllfk1vKjkh4+Pj2ZfQERE9zsmQIiIKoGPjw+2bt2Kjz76qMT9L1hZWaFatWplHFnV0a9fPyxatMisG/QBAwbg888/r4Coqg4fHx8cOnTI7ERaQd27d8ehQ4fKre+PgoYNG1bijl/ff/99s37J1ul0+PTTT9GrV68SLae8LV++HMHBwWU2v2effVZzKNY2bdogKCiozJZVVgYOHKj5OtCGDRsQFxen/NvBwQE//PCD5lDSBfn7++Pnn3+Gi4tLsWMqzbEJ5CezDxw4gKeffrrE8/D399fs1LckfHx88NNPP+GBBx4os3kSEVkSJkCIiCqJlZUVJk6ciISEBMybNw9t2rSBra1tke2aNm2KqVOn4uzZs5U+zGV5Gz16NPbs2YOHHnpItbxatWpYsGABNmzYABub+++tTm9vb2zbtg2bN29Gx44dTb72YGVlhfbt22PTpk3Yvn17hSQ/9D777DNERUVh+PDhCAoKgqurq1mJLTs7O2zbtg1TpkzRvEls2rQpfv755zIffrQsBQQE4MiRI/j888/RvXt3+Pn5aY5CYg5HR0eMGDFCtawqPv0B5B9/Wn3X5OXl4cMPPzSY1rx5cxw+fFizA1U7OzsMHToUhw8fLtVIWCU9NvVcXV3x3XffYe/evRg4cCAcHR2LbFOvXj2MHj0aO3bswIULF4ySFSEhIVi+fDmGDh2KgIAAs+KoUaMGJkyYgNjYWLRu3drs+ImI7jc6MberaiIiKncZGRk4fPgwrly5gqSkJKSkpMDBwQEeHh6oV68eQkJCLPqpD1P++usvxMTE4Nq1a/D09ESDBg3QoUOH+zLxoSU1NRUHDhzAxYsXkZSUBADw8vJCzZo10aZNG7N+Ua+qbt++jejoaJw5cwbZ2dmoUaMGmjZtqpkcs3T9+vXDTz/9ZDDNyckJiYmJ5ToMa2U4c+YM9u3bh8TERDg5OaFmzZro0KFDhSbxzJWdnY2jR4/in3/+QXJyMtLS0uDk5AQPDw/UrVsXjRs3LvbTGdevX0dsbCwSEhJw48YNpKenw9raGi4uLqhRowYaN26M4ODgcn+djYjIEjABQkRERHQP2bt3Lzp27GjUt0RoaCiWL19eSVERERFVfUyAEBEREVVhixYtwq1bt5CRkYHTp09j06ZNyMzMNKp39OhRNGvWrBIiJCIiujcwAUJERERUhdWuXRsJCQkm6wwcOBAbNmyooIiIiIjuTewElYiIiOge5u3tjYULF1Z2GERERFUeEyBERERE96gHHngA27Ztg7+/f2WHQkREVOWx63wiIiKie4irqysaNmyI3r17IyIiokqOhkJERFQVsQ8QIiIiIiIiIrJ4fAWGiIiIiIiIiCweEyBEREREREREZPGYACEiIiIiIiIii8cECBERERERERFZPCZAiIiIiIiIiMjiMQFCRERERERERBaPCRAiIiIiIiIisnhMgBARERERERGRxWMChIiIiIiIiIgsHhMgRERERERERGTxmAAhontGx44dodPp8M4771R2KJUqIyMDb7/9Nho1agRHR0fodDrodDr8+eef5bbM6OhoZTll3b48510Wvv76a+h0OtSuXbtc5l+eynvbEN2L7uVzmoiISocJEKJ73DvvvKPc4Dg5OeHKlSuadc+fP6/UjY6OrrggqUwNGTIEM2bMQFxcHHQ6HXx9feHr6wtbW9vKDo0q0DvvvIN33nkH58+fr+xQ7ks5OTnYtWsXZs+ejaFDh6Jhw4awsrKCTqfDiBEjzJ5Pamoq3nnnHTRp0gQuLi5wd3dHy5Yt8cknn+Du3btFtr969Spef/11BAUFwdHREV5eXmjfvj2WLVsGESnFGuY7e/YsRo8ejTp16sDBwQHVqlVDjx49sGHDBrPaHz16FM8++yxq1qwJe3t7+Pn5YcCAAdi9e7dZ7aOiojBgwAD4+fnB3t4eNWvWxLPPPoujR4+WZrWIiOg+ZVPZARBR2blz5w7effddfPnll5UdCpWTuLg4bNmyBQAQGRmJwYMHV3JE5nFyckJQUFBlh2FR3n33XQD5T0bxl+yKd+nSJXTt2rVU80hISEDHjh2VJJaTkxOysrIQExODmJgYrF69Grt27YKnp6dq+yNHjqBHjx5ISkoCALi4uCA1NRX79u3Dvn37sH79evz000+ws7MrUXxbt27FU089hYyMDACAm5sbkpOT8csvv+CXX37ByJEjsXz5cs0njJYtW4bw8HDk5OQAANzd3XH16lVs3LgRGzduxPTp000+0ffOO+8ox7lOp4ObmxsuX76M1atXIzIyEosWLcILL7xQonUjIqL7E58AIbIwX331FU6fPl3ZYVA5OXHiBADA29v7nkl+AMCjjz6KuLg4xMXFVXYoRGXG1dUV7dq1w6uvvoqVK1fi4YcfNrttTk4O+vTpg/Pnz8PPzw87d+5Eeno6MjIysGbNGri6uuLYsWN49tlnVdvfunULvXv3RlJSEoKDg3H48GGkpqYiPT0dn332GWxtbbFjxw6MGzeuROt27tw5DB48GBkZGWjbti3++ecf3Lp1C7du3cK0adMAACtWrMDs2bNV2x88eBBjxoxBTk4O+vfvj4sXLyIlJQXXr1/H6NGjAeQn8dauXavafu3atUryY/To0bh+/TpSUlJw8eJF9O/fHzk5ORgzZgwOHjxYovUjIqL7ExMgRBYiICAATZs2RU5ODt58883KDofKif6XWBcXl0qOhOj+VqtWLdy6dQt79+7F/PnzMXz4cLi7u5vdfuXKlUpCc8OGDcrTJFZWVhgyZIjyJN/WrVuxa9cuo/Zz5sxBYmIiHB0dsXXrVrRo0QIAYGdnh7FjxyrJgyVLlpQoKT5t2jSkp6ejevXq2LJlCxo2bAgg/9rz7rvvYtSoUQCADz74ADdv3jRqP3HiROTm5qJJkyZYu3YtatasCSA/ebt48VmX7JEAACAASURBVGL06NEDADBp0iTk5uYatM3NzcXEiRMBAD179sTixYvh7e0NAKhZsyYiIyMREhJiUI+IiMgcTIAQWQgrKyvMnDkTQP6X6T/++KNY7Qv2D2KqT4HatWtDp9Ph66+/Ntk+ISEBL774ImrVqgUHBwfUq1cPU6dORXp6utLm5MmTePbZZxEQEAAHBwc0aNAAM2bMQHZ2dpHx3r17F7NmzULTpk3h7OwMT09PdOvWDdu2bSuy7cmTJzFq1Cg0aNAATk5OcHFxQdOmTfHWW2/hxo0bqm30fa107NgRQP427t69Ox544AFYWVkVu2PWzMxMzJ8/H23atIGnpyccHBwQGBiI4cOHq3Zmql++vm+BhIQEZXsXt88BvUOHDmHkyJGoX78+nJyc4ObmhsaNGyM0NBQ7duww2fbMmTMIDQ1FQECA8l7+iy++iMuXL6vWL21nnHFxcXjmmWdQvXp1ODg4oG7duoiIiMDVq1dLNL/Cfv/9d/Tv3x8+Pj5wdHREUFAQ3nrrLaSlpZnV/vr165g6dSqaNWsGd3d3JcawsDD8/fffJpc7adIktG/fHoGBgXBwcICHhwdatWqFjz76SHX5I0aMMNiOnTp1MjgWTL0OU9z9BuRv+1GjRqFhw4ZwcnKCg4MDAgIC0KpVK7z55pvFfqqn8LEQExODJ598En5+fnBwcED9+vXxxhtvICUlxeR87t69iy+++AKdOnWCj48P7OzsUL16dfTr18/kdaBgP0jXrl3D+PHjlXUrzvGp7++jpFauXAkgf/+1bt3aqHzo0KGoU6cOAGDVqlVG5fppBesVFBERARcXF+Tm5mL16tXFii09PV3p4yM8PBweHh5GdaZMmQIAuH37NjZu3GhQFh8fj3379gEAJkyYoNo/kb79+fPnsWfPHoOy3377DQkJCQb1CrKzs8OECRMAAPv27cO5c+eKtX6F7dy5E7169UK1atXg6OiIBx98EDNmzEBmZqZR3VatWkGn0+Gll14yOc9du3ZBp9PBysoK8fHxZsdy8+ZNLF++HIMHD0aTJk3g5eWlfD4MGzYMv//+e5Hz2LNnD/r06aN6PTOnA9iSXs/MkZCQgLCwMKVPmJo1a2LkyJE4c+aMye8hheOOiopC//794efnB2tra6PPwLNnzyI8PBwNGjSAo6Mj3Nzc0Lx5c7z33nu4ffu2amzmbJvixFic44qIKpAQ0T1t+vTpAkACAwNFRKRDhw4CQDp16mRU99y5cwJAAEhUVJRm2blz5zSXFxgYKABkxYoVmu03bNggHh4eAkDc3NzE2tpaKWvfvr3cvXtXtmzZIk5OTgJA3N3dRafTKXWGDBmiumz9uk2ZMkXat28vAMTGxkZZlv5v+vTpmvF/9NFHYmVlpdR1cnISOzs75d9+fn5y9OhRze3coUMHGT9+vAAQnU4nnp6eYm1tbXKZhV26dElCQkKUZdra2oq7u7vybysrK1m4cKFBm9mzZ4uvr6+4ubkpdXx9fZW/V155xezl5+TkyCuvvGKwzZydncXT01PZD+7u7gZtoqKilLq7d+8WFxcXASCurq5iY2OjlNWoUUMuXbpktMyC7YtTJiKybds2sbe3V+q4uLiIg4ODsr+++uork+2Lsnz5coNjwt3dXTkmgoODZe7cuQbnWGE7d+40OAZtbW3F2dlZ+bednZ2sXLlStW3BfeDk5CSenp4G0xo3bixXr141aPPKK6+Ir6+vUsfT09PgWGjRooXqti3Jfvvll18Mtr2trW2xzjc1BWPauHGjsq3d3NwMzsXAwEDNa9H58+flwQcfVOrqdDqDcwiAjBkzxuQ2X7p0qbIdHRwcxNXVtcTHkJ7+GvX888+brJeenq4ccx9//LFmvfDwcAEg1atXN5geFxenrMfatWs12/fq1UsASKtWrYq1Htu3b1fm/8cff2jWa9SokQCQoUOHGkxfvHix0r7w8auXk5OjbPPJkycblE2ePFk5TnNyclTbX716VVnG4sWLi7V+K1asUI6xzz//XLnueXh4GJwXzZo1k+TkZNW2bm5ukp6errmMIUOGCADp1q1bsWLTf9YAEGtra/H09DQ4B3U6nSxYsECz/cKFCw0+Twtezxo1aiTz5s0rt+tZUQ4cOKDscwDi6OioXJPc3Nxk7dq1mt9DCu6z+fPnG3xW2draGpxzkZGRBtvM1dXV4N8BAQFy6tQpo/gKLkOLqe9KpTmuiKjiMAFCdI8rnAA5ePCg8iG7bds2g7oVlQDx8PCQLl26yN9//y0iIhkZGbJw4UIlETJ16lRxd3eXIUOGyPnz50VEJDU1Vd566y1lHjt37jRatv7mwt3dXezt7WXx4sVy584dERG5cOGCPPnkk0r7TZs2GbVftmyZcgP9wQcfyH///Sci+V/EY2JipHPnzgJAatasKampqarbWf9lbdKkSXLt2jUREcnMzFTWoyg5OTny2GOPKevx7bffSlZWloiInD17Vnr37q18yd26datRe3O+oBVl4sSJynYKDQ2Vf/75RylLSUmRjRs3GiWhCt60enp6St++fSU2NlZERLKysiQyMlL5Yvvcc88ZLbOkCZCLFy8qSZ+mTZvKoUOHREQkNzdXtm3bJjVr1jT4sl5cR44cUb6YduzYUVmnu3fvyvfffy8eHh7K/NW2+fHjx8XR0VEAyIsvviinTp1SbtgSEhLkpZdeEiA/UXf48GGj9n369JHIyEjlWBTJP19++OEHCQoKEgAyYMAA1di1zuWCSrvf6tWrJwCke/fucuLECWX6nTt35OTJk/Luu+8aXQuKUjAmd3d36dixo3Izkp2dLZGRkUoiqGXLlkY3wGlpaRIcHKzss+joaMnMzBSR/ON37ty5ynk6f/58ze3m4uIiQUFBsmvXLsnNzRURMTgXSsLcBEhMTIwSh9p5rvf5558r9ZKSkpTp69evV6ar3cjpvfHGG8rNZXHMmTNHmX9GRoZmvaeeekoASJMmTQymv/zyywJAHnjgAZPLadmypQCQPn36GEzXXwcfffRRk+2rVasmACQiIqKINTKkv446OTmJra2tPPXUU3LhwgURyT//Fi1apNwwFz7/MjIylOPzq6++Up3/9evXlaTD+vXrixXbl19+KdOnT5eYmBjlsyEvL0/i4+Pl1VdfFZ1OJ9bW1qqJ+v379yuJtW7duinHc3Z2tqxbt068vLyU2MvjembKzZs3xc/PTwBI3bp1Zffu3ZKXlyciIn/88Yc89NBDBglgreSCg4ODWFtby4gRI5R9lpOTI2fOnBGR/Gu6ra2tAJC2bdvK8ePHRST/M+Onn35SYqhXr57R53xZJUBKclwRUcVhAoToHlc4ASIiMmDAAAEgDz/8sPIFQ6TiEiAPPvigckNS0HPPPafU6datm0FsevonO8LCwozK9DcXAGT58uVG5bm5ufL4448rMRR0+/Zt5UZ2+/btquuWnZ0tjzzyiACQefPmGZQV/FVu/Pjxqu3NsWbNGmU+O3bsUI1BnyAJCQkxKi9tAuSff/5RviBPnDjR7HYFb1o7deqk3DAWtHDhQgHyf9XLzs7WbG9q3oXpfwH39vZW/SX5xIkTypfdkiRA9L+QN2zYUPVGr+Av4WrbXJ80mzJliuYy9E/b9OvXr1ixXbp0Sezt7UWn00lCQoJReXETIMXdbwV/Yb9y5UqxYjelYExa233nzp1KncJPOLz33nsC5D+NdffuXdVl/PDDDwJAfHx8jI5F/Xzd3Nzk4sWLZbZeIuYnQH766Scljr/++kuz3saNG5V6BRNQ+n0GQG7duqXZfv78+Uq9wjd7puifcvP09DRZb9y4ccr5WdDAgQMFyP+l25T+/fsLAHnkkUcMpjdv3tysm8SHH35YAMigQYNM1itMfx3VH0dq54U+YQ4YPwWjX2+tJ2v0CSRfX1/NY7Skxo4dq/kZ2aVLFwHynxxT+wzevXt3pV3P3n//fSWB8e+//xqVX79+XXx8fIpMLgCQgQMHai6nZ8+eAkDq16+v+oTO0aNHlaT37NmzVZdR2gRISY8rIqoY7AOEyAJ9+OGHsLa2xp9//onvv/++wpf/2muvwd7e3mi6vtM7AJg8ebLq+/P6OsePH9ecf0BAAEaOHGk03crKClOnTgUA/P3330oHg0B+nx0pKSlo1qyZQRwF2djY4OmnnwYAzT4wrKysMGnSJM3YihIZGQkAaN26Nbp3764aw/Tp0wHk91VScB3KwsqVK5GXlwdvb2+lk8TievPNN2FlZfzx0a9fPwD5wzH/+++/pYoTAERE2V5jxozBAw88YFQnJCQETz75ZInmn5KSouznN954A46OjkZ1evToodo/A5D/Lvju3bthY2Oj9EegZvjw4QCAX3/91aizR1P8/f3x0EMPQURw4MABs9tpKe5+c3V1Ver/999/pV6+Gq3t3rVrV7Rp0wYAsGbNGoOy5cuXAwDGjx+v2rcEAPTv3x9ubm64ceMGjhw5olrnueeeUzrmrGipqanK/zs5OWnWK1hWsE1p25sbn6l5FywvPO/Kbl8cU6dOVT0vRo4cqRwfhY/BMWPGAMjvw0ftGr1s2TIAQGhoqOYxWlJPPPEEACh9rOglJydj9+7dAPLPK7XP4E6dOqF9+/aq8y3v69m6desAAEOGDEH9+vWNyn18fBAeHm7WvNT6hQGMr+lqx0+zZs0wcOBAACjX70clOa6IqGIwAUJkgYKDg5UEwdtvv21Wp6Jl6dFHH1Wd7uvrq/x/y5YtTdZRG1VAr2PHjpqdD7Zv3x42NjYA8jtX1Nu/fz8AIDY2FtWrV9f8e++99wBA6YCvsPr166veiJtLH5N+xAc1nTp1grW1tdE6lAX9jXS3bt3g4OBQonk89thjqtNr1Kih/H9ycnKJ5l3QuXPnlPl07txZs56pMlOOHj2KvLy8Es9ff0zl5eWhcePGmsdUz549AeR3LJmUlGQwj7y8PHz33Xfo27cvatWqBUdHR4MOTfWdGV+6dKlE61hQcfebo6MjunTpAiB/JI5p06bh0KFDuHv3bqlj0TNnuxc8By5fvqycm2FhYZrb3M/PT+lAVutcbtu2bVmtBt2jbGxsNBMCVlZWSqfXha/DQUFB6NSpEwBg6dKlBmV79+5FXFwcdDodXnzxxRLFFR8fjwkTJuCRRx6Bh4cHrK2tlWvC//73PwDG14Rjx45BRAAAHTp00Jy3fp0KK4vrmZa7d+8qnaeWJLaCHB0d0bx5c9Wyo0ePKtvA1Gdst27dAOT/0FIe349KelwRUcWwqewAiKh8vPPOO1i9ejXi4+OxePFiREREVNiyXV1dVafrExPm1DH1pcTf31+zzMHBAd7e3rh69SquXbumTL9y5QqA/NFXzOmBXT/cbGGlSX4AUGIqah18fHyM1qEsJCYmAgACAwNLPA9z9m9ZfKksuO6mtldJf8Uv7fz1x1ReXp7Zo9EUPK4yMjLQu3dvREVFKdPs7Ozg5eWl/GqcnJyM7Oxsg9GTSqok+23ZsmXo27cv/vrrL7z//vt4//33YWdnh5YtW6Jfv34ICwuDl5dXiWMytd31ZWrnMQDNEZsKK69zuTQK7gut+AqXFWxTuL2bm1ux2psbn6nYCpYXnndltzeXj4+P6pMSemrHoN6YMWMQFRWFb7/9Fh9//LGSUF6yZAmA/JtstdF5ivLjjz/i6aefRlZWljLNzc0NDg4O0Ol0uHv3Lm7evGl0Tbh+/bry/wWTmlrrVFhpr2emJCcnK0+LlCS2gry9vVWfrACKf03PyclBcnKywY8zZaE0xxURlT8+AUJkofz9/ZWkx4wZM8weztNS6b98DRkyBJLf/5HJP62hgPVPZtyrSjNsJxnSH1O+vr5mHVMiYjC84gcffICoqCg4Ojpi3rx5SEhIQGZmJpKSkpCYmIjExETlqQ39r5oVrVatWjh69Ci2b9+OV155BY888gjy8vKwf/9+TJw4EfXr11ceu68IBR+5j42NNWubaw0RXZnncsGbQFNDEBcsK9imuO3d3Nzg4uJS7Phu3ryJO3fuFDn/wje1+n+biq0821eEAQMGwNfXFzdv3sTatWsB5G+v9evXAwBGjRpV7HkmJSVhxIgRyMrKQufOnREdHY2MjAzcunULV69eRWJiovIqiSkluc6X9npmrtJ+Bt3rn8FEVPmYACGyYJMnT4anpyeuXbuGTz75xGTdgr8Cm3pC4tatW2UWX0mZ+lKclZWlPJZb8Bfe6tWrA9B+HL6i6GMy9UqD/ia4YP2yUlW2gzkKrru5N4kVOX/9trxx40aJntDQv/89bdo0jBs3DrVq1TK6OdA/sVOZrKys0KNHDyxYsAAxMTFITk7G6tWrUatWLdy8eRPDhg0r8Wsx5mx3tfMYuDeOYS2NGjVSfsU+efKkZj19WfXq1Q2etAkJCTGqY6p948aNixVfcef/4IMPqra/du2awZMJBeXm5iIuLs5k+9jYWM1+JgrOu3B7c924ccPksat2DOrZ2toiLCwMwP9/Debbb79FZmYmqlevjr59+xY7nq1bt+L27dvw9PTE5s2b0aFDB6M+crSuCdWqVVP+v+CTUoWV1/XMFC8vLyVxUZLYzFVwP5n6jNWX2djYGJxX+u9Bpf0OVJrjiojKHxMgRBbM09MTkydPBgB88sknml9E9XX1Ll68qFrn9OnTSElJKdsgS+C3337T/EV87969yMnJAQC0aNFCma5/3//IkSPl1qGjOfQx7dq1S7NOdHS0sg5afaWUlL5jyZ07d5r1KlBlqlOnjvLltOBrIoWV9AmE5s2bKzehJZm//pjKzc3Ftm3bir18/XnWrFkz1fLz58/jzJkzmu31yZKKfjrE1dUVw4YNUzojvXr1aok76zW13fVlBc/j2rVrK4+Pb968uUTLrAqcnJyU42f79u2qdURE6dCxcIfJDRs2RK1atUy2T09Px969e1XbF6Vdu3bKjbfW/BMSEhAbG6s6f30fC6ba79+/X+m8VKt9amqqZgfABedb3PXTy8nJUbZRYSKC3377DYDhMVjQqFGjYGVlhX379iE2NlZJhIwcObJEnZ/qrwlBQUGaHcD++uuvqtObNWumXBOio6M1l6FVVtrrmSl2dnZKkqoksZmr4DXd1Gesfhs+9NBDBvtJ/z3o2rVrBq8gFXTo0KEi4yjtcUVE5YsJECILFxERgZo1ayI1NRXvv/++Zj1nZ2fUq1cPQP6IKWo++OCDcomxuC5cuICVK1caTc/Ly8OHH34IIP8XzyZNmihlTz31FDw8PJCdnY3x48ebvGnMy8srt0TP0KFDAQAHDx7EL7/8YlSek5OjdMQaEhJi8EtsWRgxYgSsra2RlJSkjDZTVel0OgwePBgAsHjxYtU+H06dOqU8cl5cHh4eyo3TnDlzVBNCv/76q+YNWIMGDZTO7N56660ifxks3DGsu7s7AOCvv/5Sra9PXmrR9/tQXsdqUU91FPxlWuud/KJobfeoqCilU8YhQ4YYlOk7lly+fDmOHTtmcv5l0RlveXn++ecB5K+r2k3VunXrEB8fD+D/j7yhp9PplGlr1qxRfWXv888/R1paGqytrfHMM88UKzZnZ2cMGjQIALBo0SLVY/ujjz4CkJ8Q69+/v0FZ3bp10a5dOwD5yXe1PoFmzZoFIL8/oscff9ygrEOHDko/Rfp6BWVnZytPNbZr165EfW3offDBB0pnyAWtXLlSSUgUPgb1AgMD0atXLwD5fYKcOHGiVJ2f6q8Jp0+fVj0v/vzzT3z33Xeqbb28vJSOWT/55BPV83fPnj2aN+alvZ4VRT9aV2RkJM6ePWtUnpSUhMWLFxdrnoV5eHgoo7zNnj1btY+Sv/76S/mOox/1Te+hhx4CkJ+k+PHHH43a3rlzB/PmzTMrltIcV0RUzsp6XF0iqljTp08vctz6guPO6/+ioqKM6k2dOlUAiK2trXz++eeSkZEhIiIXLlyQsLAwsbe3FycnJwEgK1asMGh77tw5Zd7nzp1TjSMqKkqpo2XFihWa69OhQwcBIO7u7uLg4CBLliyRO3fuKDEOHjxYmf8PP/xg1P7rr79Wynv16iW///675ObmiohIbm6unDp1SubMmSPBwcHyzTffGLTVb+cOHTpoxm6OnJwceeyxx5T1WL16tdy9e1dEROLj46Vv375KjFu3bi3W9jHX5MmTlWWEhYXJ6dOnlbJbt27JmjVrpH///gZtzNl3IqJ5fJlqb6osISFBXF1dBYA8/PDDcvjwYRERycvLkx07dkitWrXEw8PDrNjUHD58WKytrQWAdO7cWeLi4kREJDs7WyIjI8XT01OZv9o2P3HihLi4uAgACQ4Olo0bNyrHpIjIpUuXZNWqVdK5c2d54YUXDNo+++yzAkBcXV1lw4YNkp2dLSL5x8HTTz8tOp1OPD09BYBMnz7daNlt27YVADJo0CBJT09XXb/S7LeoqChp0qSJzJ07V06dOqWcK3l5ebJ//35p0qSJAJCaNWtKTk6OyflrxeTu7m603detWydeXl4CQJo3b65sF73U1FRl2e7u7vLpp5/KjRs3lPKbN2/K1q1b5bnnnpPGjRubta4llZKSItevX1f+2rRpIwBk6NChBtNTUlKM2mZnZyvr4e/vL7/++quI5F+L1q5dK25ubsq1SmvZ1atXFwDSuHFjiYmJERGRrKws+eKLL8TOzk4ASHh4uGp7/bVEa1vEx8eLs7OzAJD27dsr14m0tDR59913RafTCQD56KOPVOe/f/9+5dwaOHCgXLp0SUREkpKSJDw8XFl2ZGSkavvIyEilTnh4uCQlJYlI/jk1cOBAASDW1tZy4MAB1fam6NfdyclJbG1tZciQIXLx4kUREblz5458+eWX4uDgIACkX79+Jue1efNmg8/W7t27FzsevdOnT4uVlZXRNsvKypLIyEipVq2aeHt7a57Te/fuVfZLjx49lH2WnZ0tGzZsEB8fH+WaUtbXs6IkJyeLr6+vAJD69etLdHS05OXliUj+dbhZs2ZKbGrfI8z97Dty5IjY2toKAGnXrp0cP35cRPLPq59//llq1KghAKRevXqSmppq1L5du3YCQPz8/GTnzp3KtS0mJkbatGmjXJtMxVgWxxURlR8mQIjuceYkQHJyciQ4OLjIBEhqaqo0btxYqWNlZaXc/Nna2sr3338vgYGBlZ4AmTJlivIlxdbW1uBLEwCZOnWq5vwXLVqk3BgAEHt7e/H29la+MOn/vv32W4N2ZZUAEcn/Evnggw8qy7KzszO4ibeyspIFCxaoti2LBEhOTo6MHTvWYH1dXFzE09NT+fLs7u5u0KayEiAiIlu2bBF7e3uljqurqzg6OipfUr/66qsSJ0BERL788ktlvfXrrl9ecHCwzJ071+Q237dvn3Ijqr8p8/b2VmLU/xW+YTh//rxyQwBAbGxsxN3dXfn3hx9+qBzzagmQb775Rqlra2sr/v7+EhgYKG3btjV72+ppJUAKxm9rayve3t5iY2OjTHNzc5M9e/aYva0Lz3fjxo3KuVdwuwOQWrVqSXx8vOo8Ll++LK1atVLq6nQ68fDwUJIG+r/69eubta4lpd8/Rf1pXTfOnTsntWvXVuo5OTkpN0gApFmzZpKcnKy5/JiYGIMbYldXV4NrWffu3SUzM1O1bVEJEBGRn3/+WUl66/eRPqkBQEaOHKncxKpZunSpwfHi4eFhcK6pHdcF6a+7BfdxwfNl6dKlJttrKXgd/eyzz5SYPD09DbbfQw89ZJBcU5Obm6t8LgKQ9evXlygmvUmTJhkcO+7u7kpMderUkdWrV5s8p+fNm2fQ3sPDQzmvQkJClPKgoCDV9iW9nplj7969SoJFf7zr/+3h4SHr1q1Tyv777z+DtsX57FuzZo3B57ybm5vBeRUQECCnTp1SbXvs2DGD64iDg4OSCPT19ZWff/5ZKTOVpCntcUVE5YcJEKJ7nDkJEBGRH374weDLi9YX3uTkZBk/frzUqVNH7OzspFq1ajJo0CDl18WqkACZPn26ZGVlyYcffighISHi5OQk7u7u0qVLF/n5559Nbgd9rBMmTJCHHnpI3NzcxNraWjw9PaVFixYSEREhO3fuVH7t1ivLBIhI/q9Bc+fOlVatWom7u7vY2dlJQECAPPfcc3Ls2DHNdmWRANHbt2+fPPPMM1KrVi2xt7cXDw8PefDBByUsLEz5NVqvMhMgIiJ///23DB06VB544AGxt7eX2rVry8svvyyJiYlmx2bKgQMHpE+fPuLl5SUODg7SsGFDmTJlity+fdusbX779m2ZM2eOPP744+Lt7S3W1tbi4uIijRo1kmeffVZWr14taWlpRu0uXrwoYWFhUqNGDbGxsRFfX1/p3bu37NixQ0TEZAJEJD8J0q5dO3F3d1d+OS4YZ2n2W1pamqxdu1bCw8PlkUceET8/P7G1tRUXFxd5+OGHZeLEiXL58mWT81VTOKbDhw/LoEGDxNfXV+zs7KROnTry+uuvm7zxF8lP5H3//ffSt29fqVGjhtjZ2YmDg4PUrl1b+vTpI/Pnz5crV66Yta4lVdoEiEj+sTNt2jQJCQkRZ2dncXV1lUceeUTmzJkjWVlZRcaQmJgor732mjRo0EAcHBzEw8ND2rVrJ0uXLjW6jhU0Y8YMAfKTn9euXdOsd+bMGXnxxReldu3aYm9vLz4+PtKtWzezb/SPHDkiw4YNE39/f7GzsxNfX1/p37+/7Nq1y6z2u3btkv79+yvHh7+/vwwbNkz5TCqJwuf0L7/8Ij179hRvb2+xt7eX4OBgee+995SnIIvy2muvCQCpXr268kRfaaxatUoeffRRcXR0FCcnJ2nUqJG8+eabkpKSYtY5HR0dLf/73//E09NTHBwcJCgoSKZOnSppaWlKQvexxx7TbF/S65k54uPjZeTIkco5W7NmTQkNDZX4+Hg5evSosm4FnzwRKf5n37///iujR4+WevXqib29vXLdevfdd+XWrVsm28bGb3h4MAAAIABJREFUxiqfN3Z2dhIYGChjx46V//77z+R3nbI+roiofOhEKmlsPSIiIrrvREdHK30V8CtI5enatSt27dqFqVOnmuwfiorWpEkTnDx5ElOmTFH6oaqqnnnmGXz33XcIDQ1VOjKuKpYuXYpRo0ahbt26qv2EVHVff/01Ro4cicDAQNV+eYioamAnqERERET3kaysLBw4cABeXl6YMGFCZYdzT4uOjsbJkydhZWWFUaNGVXY4Jp0+fRo//PADAKBnz56VHI2hzMxMzJ8/H0DVi42ILAsTIERERET3kd9//x137tzBxIkTlZFHqPiuXr2KcePGAcgf5aR27dqVGxCAadOm4bPPPsOFCxeUUUjS09MRGRmJTp06ITMzE8HBwUYj91SENWvWYOrUqTh58qQySk1OTg727NmDzp0749SpU3BwcMCrr75a4bER0f3DprIDICIiIqKK06FDB75+VApDhw7F/v37kZiYiJycHLi6uqoO11sZjh8/jk2bNiEiIgK2trZwdXVFSkqKkgzx9/fHunXrYGtrW+GxJSYm4oMPPsAHH3wAnU4HT09PpKWlKckQOzs7rFixAg0bNqzw2Ijo/sEECBERERGRmRITE3Hp0iW4u7ujZcuW+Oijj1CnTp3KDgsA8Nprr6FGjRo4cOAA/vvvPyQnJ8PV1RUNGzZE79698fLLL8PLy6tSYuvduzeuX7+O6OhoJCQk4MaNG7C1tUXdunXRqVMnjBs3jskPIip37ASViIiIiIiIiCwe+wAhIiIiIiIiIovHBAgRERERERERWTwmQIiIiIiIiIjI4jEBQkREREREREQWjwkQIiIiIiIiIrJ4TIAQERERERERkcVjAoSIiIiIiIiILB4TIERERERERERk8ZgAISIiIiIiIiKLxwQIEREREREREVk8JkCIiIiIiIiIyOIxAUJEREREREREFo8JECIiIiIiIiKyeEyAEBEREREREZHFYwKEiIiIiIiIiCweEyBEREREREREZPGYACEiIiIiIiIii8cECBERERERERFZPCZAiIiIiIiIiMjiMQFCRERERERERBaPCRAiIiIiIiIisnhMgBARERERERGRxWMChIiIiIiIiIgsHhMgRERERERERGTxmAAhIiIiIiIiIovHBAgRERERERERWTwmQIiIiIiIiIjI4jEBQkREREREREQWjwkQIiIiIiIiIrJ4TIAQERERERERkcVjAoSIiIiIiIiILB4TIERERERERERk8ZgAISIiIiIiIiKLxwQIEREREREREVk8JkCIiIiIiIiIyOIxAUJEREREREREFo8JECIiIiIiIiKyeEyAEBEREREREZHFYwKEiIiIiIiIiCweEyBEREREREREZPGYACEiIiIiIiIii8cECBERERERERFZPCZAiIiIiIiIiMjiMQFCRERERERERBaPCZAS6NmzZ2WHQERERERERETFwARICdy4caOyQyAiIiIiIiKiYmAChIiIiIiIiIgsHhMgRERERERERGTxmAAhIiIiIiIiIovHBAgRERERERERWTwmQIiIiIiIiIjI4jEBQkREREREREQWjwkQIiIiIiIiIrJ4TIAQERERERERkcVjAoSIiIiIiIiILJ5NZQdQHjZu3Ihp06bhn3/+QY0aNRAREYHx48cb1BERzJw5E4sWLcKNGzfQsmVLLFy4EA8//HAlRU1EREREdG/Jzs7G1atXkZycjOzs7MoOh4gAWFtbw8XFBd7e3vDw8IBOp6vskKoMi0uA7N+/HwMHDkRoaCjmzJmDQ4cOYdKkSbCyssK4ceOUerNmzcL777+P2bNnIzg4GHPnzkXXrl1x8uRJVK9evRLXgIiIiIio6svLy8OZM2dgY2MDPz8/2NnZ8UaLqJKJCHJzc5Geno5Lly4hLS0NNWvW5Ln5f3QiIpUdRFnq0aMHMjIysHfvXmXa66+/jhUrViAxMRF2dnbIzMyEr68vXn/9dUybNg0AkJ6ejtq1a2P06NGYMWOGyWW0aNECMTEx5boeRERERERVWWJiIlJSUuDn58ebK6IqKDc3F+fPn4eXlxcCAwMrO5wqweL6APnzzz/RrVs3g2ndu3fHzZs3cfDgQQDAgQMHcPv2bQwePFip4+zsjD59+mDbtm0VGi8RERER0b3o1q1bcHNzY/KDqIqytraGj48Pzp49i+Tk5MoOp0qwuARIZmYm7OzsDKbp/x0bGwsAiIuLg7W1NRo0aGBQr1GjRoiLi6uYQImIiIiI7mEZGRlwdHSs7DCIyARnZ2e4urrixIkTlR1KlWBxCZD69evj8OHDBtP++OMPAFCyXjdv3oSLiwusra0N6nl6eiIjIwN3796tmGCJiIiIiO5ReXl5sLKyuNsJIotibW0NKysr/tD/fyzuijVmzBhs3LgRS5cuxc2bN7Fjxw7MnTsXAEp1gV6yZAlatGiBFi1a4Pr162UVLhERERHRPYuvvxBVbfpzNC0tDRbW/WeJWFwCJDQ0FOHh4QgPD4eXlxcGDhyIt99+GwCU0V08PT2RlpaG3Nxcg7Y3b96Ek5OT0Ss0ADBq1CjExMQgJiYG1apVK/8VISIiIiIiIioDTH7ks7gEiLW1NT777DNcv34dx48fx9WrV9GqVSsAUP4bHByM3NxcnDlzxqBtXFwcgoODKzxmIiIiIiIiIipfFpcA0fP09ESTJk3g4uKCL774Am3atFGSG23atIGb2/9j777jaz77P46/cnISGeIIIcQeEbFH1IpRo3argxYtrc7gpkaNRlGhVrnbUtGWuu+qUapFjZgxoiSkJWZqpVGrBElIZJ38/vCTu6cnNAiH5P18PDzK9bmu6/s551GRfM41CrFs2bKs/klJSfz000906NDBVimLiIiIiIiIyANitHUCuW337t2EhYVRp04dEhISWLx4MevXrycsLCyrj5OTEyNHjiQoKAh3d3eqVq3KjBkzMJvN/Otf/7Jh9iIiIiIiIiLyIOS5AoiDgwPfffcd48aNw2Aw0KxZM3bu3EnNmjUt+o0cORKz2cykSZOIi4vDz8+PjRs34unpaaPM84eEpBu4ODli1InhIiIiIiIi8hDluQJI/fr1ra7BzY6dnR2BgYEEBgY+hKzyl6TUVH47E8eJC5c5HRfPxfjrJCSnkJJ289BZOzt4vlF1nqpd2caZioiIiIiISH6R5wog8nCYzWZ+vxjPsfNx/P7nVc5fTeTK9RskpaRh/ocThjMz4ftdh7iRmsbTDXwfUsYiIiIiIiKSn6kAInd09XoyR89c4uSFK5y5nEBcYhKJySmkZZjve+7Vkb+Rmp7BC41r5EKmIiIiIiIiIrenAoiQmp7OifOXOXYujtOX4vkz4TpXr6dwIy2NB31d9Ib9J0hNN9OzWa0H+yARERERERHJ11QAySfMZjMX4q9z9MxFYv68yrmriVxOTOZ6SioZ5tyvctjZ2eHsaKSwixOehQtSxsNElZJF2XYohj0nzlj03XroFCnp6bz2ZL1cz0NEREREREQEVADJ8349dZavN/9CSnrGA5nf0WiPm3MBPAq5ULpIISp6uuPj5UEhF6ds+1fx8sDRaM/O6FiL9l3Rp0lLz+Cttg0eSJ4iIiIiIiKSv6kAkscVLFDgvosf9gY7XAo4UKSgMyULu1G2WGF8SnlQyt0Nwz1cZ9vnybo4OtgTevCURfveE2dJS99N/w6N7itfERERERERkb9TASSPq1DCPUf97IACjkZMzk4UM7lQxsOEd4kieJf0oIBD7v9v0sO/Fo5Ge9bvO27Rvv/3C8z4aSdDujTN9WeKiIiIiIhI/qUCSB5nNBgw2htI//9bWxzsDRR0cqSImwte7m5ULO6OT6lieBRyeei5Pd+oOo5Ge37aG23RfvTMJab8uJ33nvG/pxUmIiIiIiIiIn+nAkg+8HqrehR2daJccXeMj1hBoYtfVQo4GPl+1yGL9hMXrvDRD9t5/7nmKoKIiIiIiIjIfdNPlvlA/UqlqFSi6CNX/LjlqdqV6eFf06o99lI845dtJd1stkFWIiIiIiIikpc8mj8RS77zZI2K9GlRx6r97JVExi7ZTHq6iiAiIiIikrcdO3aM4OBg3nzzTfz8/ChcuDAmk4kVK1bk+rM+/PBDTCYTJpOJzz77LMfjunXrhslkon///nfsFxYWRuHChSlVqhQxMTH3ma1I7lABRB4ZTX3L8Wab+lbtFxOSGL1kEylp6TbISkRERETk4Zg3bx4jR45k6dKlHDt2jMzMzAfynMjISD799FPs7Ozueuxnn31G4cKF+fbbb9mwYUO2fa5fv07//v3JzMwkKCiI8uXL32fGIrlDBRB5pDSoXJp+7Z7g71+KL19LZvTiTSSlptokLxERERGRB83X15eBAwcyf/58fv31V/z9/XP9GSkpKQQEBFC8eHE6dep01+NLlizJtGnTABg4cCBXr1616jNu3DhiYmJo1aoVffv2ve+cRXKLCiDyyKlToSSDOjW2qkjHJ6UwetFmkm6oCCIiIiIieU+fPn0ICgriueeeo2LFig/kGRMnTiQ6Opp///vfFCpU6J7m6N69O126dOHcuXOMGDHCIhYWFsZXX32FyWRi1qxZuZGySK5RAUQeSdXKFGdYl6YY/lYEuXYjlfcXbyIh6YaNMhMREREReTzt3buXWbNm0a1bNzp06HBfc33yySd4eHiwZMkS1q5dC1hufZk8eTKlSpWyePZrr72Gr68vHh4eVKxYkZdeeoldu3bdNtfRo0fTokULKleujIeHBz4+Przyyivs2bMn2zGTJk3CZDIxadIkYmNj6devH76+vhQpUoSRI0dm9fv+++/p3Lkz5cqVo2jRolSoUIHGjRszdOhQTp48eV/vizzadA2uPLK8vYoyomszpq7cQYb5f/sfk1LSGL14Mx+++CTuBV1smKGIiIiI5JYytXrZOoX7cjpqoa1TuKMbN27wzjvv4O7uzpQpU+57Pg8PD2bMmEHv3r159913adSoER999BExMTF06NCBnj17ZvWdOXMmH3zwAQC1a9emQYMGnD17lvXr17N+/Xr+/e9/8+qrr1rMP378eMLCwvD19aV+/fo4Ojpy/PhxVq1axZo1a5g3bx7PPvtstrmdOHGCZs2a4eTkRMOGDcnIyMBkMgE3iySTJ0/GwcGBhg0bUqJECeLj44mNjWXu3Lk0btz4ga2+EdtTAUQeaRU83Rn9fAsm/rCd9Iz/3QRzIy2dD5ZsYWz3JylWyNWGGYqIiIiIPPqCgoI4duwYX3/9NUWLFs2VOZ955hm6devGsmXL6NatG5GRkRQpUsTiVpmNGzcyevRoSpYsybfffoufn19WbPfu3XTr1o1hw4bh7+9P5cqVs2IDBw5k7ty5FC9e3OKZ69at45VXXmHw4MG0a9cOFxfrD0SXLVtGr169+OSTT3B0dMxqT0lJ4dNPP6VgwYJs27bN4nlws3Bib29/3++LPLq0BUYeeaWKmvjghZY42Fv+75qansG477Zw7kqijTK7dylp6Xy/6yBTftzOx6vCmB0SzvzQX1i26yDrfvmNnUd+J+r388RejCch6QZms64BFhEREZF7Ex4ezuzZs+ncuTPPP/98rs49depUSpQowd69e8nMzOTjjz+2KFpMmjQJuLkK5K/FD4BGjRrx3nvvkZaWxvz58y1ibdq0sSp+AHTo0IGuXbty5coVduzYkW1ORYoUYcqUKRbFD4DExESSk5OpUKGCVfEDoFKlSrqxJo/TChB5LJR0d+PDF1vz4bItpKRlZLWnZZgJWraVkc82p2wxkw0zzJmYP6+wbNchjp+P415uNTPY2WFvsMPe3oCDwYCj0R5HByNODvY4OTrg4uiASwEHCjo74uZUgELOjphcnSjk7ESRgs4UcNBfeREREZH8JDk5mYCAANzc3Jg+fXquz1+kSBGGDh3Ke++9R506dSwKLHFxcURGRlKoUCFatWqV7fimTZsCEBERYRWLi4sjJCSEw4cPEx8fT0bGzZ8Djhw5AsDx48dp166d1biWLVvi5uZm1e7h4UHZsmU5cOAAgYGB9OnThypVqtz9i5bHln4akseGRyEXgl5qzdjvtpCcmp7Vnm42M+nHbbz3TDMqerrbMMPsmc1mNh04yaaoE1y9fn+Ht5ozMzFnZJKWYeZeZ7IDDAY77A0GjPYGHOwNuDkVoG3tSjT2KXtf+YmIiIjcq0f9DI1HVWBgIJcvX7ZoK1KkCBMnTgRunqVx4sQJPv/8c0qUKPFAcnB1vbklvWDBghbtMTExACQkJFCkSJE7znHp0iWLP3/99dcEBgaSlJR02zGJidmvBC9Tpsxtx3zxxRf07t2bWbNmMWvWLDw8PGjQoAGtW7eme/fuWWeFSN6kAog8Vgq7OjOhRxvGLNnM9ZS0rPYMcyZTV+xgSJcmVPHysGGG/3PlWhLf/XyQqJjzpJvvYbnHA5LJzfcrw5xBavrNKnp8UgrzQ39l4/4TDOrcGJOLk22TFBEREZEcWbVqFbGxsRZtZcuWzSqArF69GoPBwOLFi1m8eLFFv99++w2AefPmsX79eipUqJCrV9fe2sZtMpno1KnTHfv+tUASGRnJkCFDMBqNBAUF0aFDB7y8vHBxccHOzo4PP/yQGTNmkHmbJdXOzs63fU6TJk2IiooiJCSEsLAwIiIiCAkJYd26dUyaNIkff/yR2rVr38OrlceBCiDy2HFzLsDEHm344LvNJCanZrWbMzOZ/tNOBnZoTPWy1vsFH5bIk2dZtedojs4mKVG4IAWdHLmRmk5Kejqp6RmkZZhJzzCTYTZjNmfyMEsnf1xOYMSCDXT286FzfZ+H+GQRERERuRcHDhz4xz5ms5mwsLDbxmNiYoiJiSE+Pj43U8u6BtdoNBIcHJzjcatWrSIzM5O3336bgQMHWsXv96paFxcXnnvuOZ577jkAzp8/z6hRo/jhhx8YNmwYGzduvK/55dGlAog8llycHJnYoy1jvttssa0kMxM+W7uLd9o1oG4Fr4eWz43UdFZEHOHn32K58ZftOdkxGgzULl+C7k2q5/ga3xup6Vy5nszV6zdITL5BQlIqiSkpXEtOJSkljaTUNG6kpnEjLYPUtP8vpJjNZGSYyTBnYr6LA0fMmZms2nOUnUdjGdixESXdrfdPioiIiMjj4U4FkoCAABYtWkRQUFC2hYb75eXlRfXq1Tl06BA7duygWbNmORp35coVAEqXLm0Vu3TpEqGhobmaZ4kSJfjggw/44YcfOHjwYK7OLY8WFUDkseXkaGRCj9aM/S6UuMT/7Q3MBILX7+GN1vV4wvv2+/9yw6kLV1i2+yAnzl3+x5Ua7q5OtK1VmVY1K2Aw3N0FTE6ORko6ut1XMcJsNnPtRipXr6dwNSmZxKQUEpJTuJhwnZ+jT1sVSeISkxj73RZaVq/AS01r3HXOIiIiIiKBgYH07NmTt956i1mzZtG6dWuLeEZGBmFhYbi4uNCgQQOArINJFy9ezCuvvJJ1tkhiYiL9+/e/55UqsbGxhIaG8uyzz1KoUCGLWEhICHDn80Pk8acCiDzWHI1Ggv7/dpgL8dctYnM3/0Jqegb+vuVz9Zlms5mNUSfYFHWC+KSUO/a1swPvkkXp1rg65YrZ9oBWg8FAIRcnCrk4URbLw52ebViNz9bu5veLV63GbT10ir0nztCv3RNULpk7d8aLiIiIiLV9+/YxdOjQrD9HR0cDNw8ynTlzZlb75s2bH3pu96pTp05MnDiRMWPG8Nxzz1G5cmW8vb1xdXXlwoULREVFER8fz4wZM7IKIL169SI4OJj9+/dTu3ZtGjVqBMDOnTtxdHTk5Zdf5ttvv73rXK5evcrAgQMZNmwYNWvWpFy5cpjNZqKjozly5AgODg6MHz8+V1+/PFpUAJHHntFoYOyLrZjw/VbOXrY8d+ObbftJyzDzZI2K9/2cSwlJLNt1kKjfz5PxD4eaujg60LRqWZ5uUPWxuHrWzbkAgc+3YFd0LN9uv/me/dW1G6lMXRlGvQoleaO1H0ajVoOIiIiI5LbExET27t1r1X7ixAkbZJN7BgwYQIsWLfjiiy8ICwsjNDQUo9GIp6cnTZs2pX379nTp0iWrv7u7O1u3bmXChAmEhoayYcMGihUrRpcuXQgMDGT+/Pn3lEeFChWYNGkSYWFhHDlyhKNHj2IwGChZsiSvvvoqAQEBVK1aNbdetjyC7DJvd3Su3Jafn1+2X5jEtsxmM5N+3JHtKobnGvrSvu693fG95/gZftp7lPNXr/1jX68ibnRt4EudCiXv6VmPgpS0dILXR3D4j4vZxgs42PN6q/qP9WsUERGR+xcZGYm3t7et0xCRf3Ds2DFCQ0MZOnQodnZ2tk7Hph79j6ZFcshgMDDq2WZM/+lnjp2Ls4j9EH6E1PQMnm7gm6O5klJTWRF+lN2/neZG2j8campvoG6FknRrXJ3Crre/cutxUcDByLudm3Aw9jxfbYok+W+HuqakZTB7fQTeJYvSv8MTuDg62ihTERERERGRnFMBRPIUg8HAe8/488nqn61WMKyO/I3U9AxeaFzjtuNPnI/j+12HOHnhyj8falrQmfZ1KtOiWvk8eUBojbIlmP5qB/6z5Vcijv9hFT92Lo5h/1nPS/41aV6t/MNPUERERERE5C6oACJ50rudmzA7JJx9Mect2jfsP0FqupmezWpltaWbzWzcd5zNB06SkPzPh5pW8fKge5MalClqumPfvMBoMPBGm/q0qVWRWevCrd6fdLOZb7fvZ+vBUwzq3BiTi5ONMhUREREREbkzFUAkz+rXviFzN0VarV7YeugUKenpdK7vw7KfD3Ig9sI/H2pawAH//z/U1NGY//7alC/uztRXnuL73YfYHHXSanXMH5cTGLFgA53qV6GLnw6OEhERERGRR0/++0lO8pU32tTH0Wgg7GisRfuu6NPsij79j+NLFy1E1yd8qVWuxINK8bFhMBjo3qQmLatX4LO1u/nzb9cOmzMz+WlvND9Hn2Zgx0aUdHezUaYiIiIiIiLWVACRPK93y7o4Go1sOXgyR/0d7A3Uq+jFC42ra0tHNoqbCjKhRxvW7zvGj+FHMP/tIqm4xCTGfreFFtXK08O/Zp48H0VERERERB4/KoBIvvCSf00cjfaE7Dt22z5FCzrTro43zauV0w/tOdCujjdNfMry2drd2V49vO1wDJEnz9Kv3RNULlnUBhmKiIiIiIj8jwogkm8816gajg72rNpzNKvNzs6OqqU86N64OqXywaGmuc3NuQCBz7dgV3Qs327fT1qG2SJ+7UYqU1eGUa9CSd5o7YfRqMKSiIiIiIjYhgogkq90ru9DVS8PNuw/TpmiJtrVrZwvDzXNbY19ylKvohfB6yOsrh8G+OXUOQb/dy2vt6pPnQolbZChiIiIiIjkd/rJT/KdyiWLakvGA1DAwci7nZtwKPZPvty0h+TUdIt4SloGs9dH4F2yKP07PIGLo6ONMhURERERkfxI69FFJFdVL1uc6a924InKpbONHzsXx7D/rGf74ZiHm5iIiIiIiORrKoCISK4zGgy80aY+7z/XnELOBazi6WYz327fz/iloVy9nmyDDEVEREREJL9RAUREHpjyxd2Z+spTtK1VCbts4n9cTmDktxv5ae/RbKIiIiIiIiK5RwUQEXmgDAYD3ZrUIKhHa4qbXK3i5sxMftobzaiFGzl3JdEGGYqIiIiISH6gAoiIPBTFTQWZ0KMNzzeqhsHOej1IXGISY7/bwo8Rh22QnYiIiIjtBQQEYDKZbvvLz8/vnueOjo4mICCAatWq4eHhQeXKlenVqxfh4eE5niMtLQ1/f39MJhNTpky5Y98lS5ZgMpnw9fXl6tWr95y3SG7SLTAi8lC1q+NNE5+yfLZ2N79ftP7HcN0vxzh3OZF+7RvaIDsRERER22vUqBEVK1a0avf09Lyn+UJCQnj11VdJTk7G29ubDh06EBsby+rVq1m7di2ffvopvXv3/sd5HBwcmDNnDk8++STTpk2jY8eO1KxZ06rf+fPnGTFiBAAzZ86kcOHC95S3SG5TAUREHjo35wIEPt+C3b+dZsG2faRlmC3i+2LOM35ZKO8/2wKjUQvVREREJH/p3bs3vXr1ypW5/vzzT9544w2Sk5MZP348gwYNyoqtXbuWV155hcGDB9OwYUN8fHz+cb4aNWowfPhwJkyYQEBAAKGhoTg4OFj0GTRoEFevXqVPnz60adMmV16HSG7QTxYiYjONqpRhxqsdqFa6mFXsj7gERi7cQGJyig0yExEREckbFixYQGJiIk2bNrUofgB07NiR1157jfT0dKZPn57jOYcMGUL9+vU5cOAAU6dOtYgtXryYkJAQypYty8SJE3PlNYjkFhVARMSmCjgYebdzE7o+4WsVS0hOYdTCjZyJi7dBZiIiIiKPv19++QWAli1bZhtv1aoVcHM1SHp6eo7mtLe3Jzg4GCcnJ2bMmMG+ffsAOHfuHCNGjMDOzo7PP/8cNze3rDGbNm3ipZdeonLlynh4eFClShX69u3LoUOHsn1GaGgoQ4cOpWnTppQvX55ixYpRo0YN3nnnHaKjo7Mdc+sMlYULF3Lw4EF69+6Nt7c37u7uzJ49G4CMjAzmzZtH27ZtKVOmTNZ5KM2aNSMwMJBLly7l6D2Qx5O2wIjII6FjvSoUK+TK3M17ycz8X3tqegZB32+jX/snqFWuhO0SFBERkQeqSvtAW6dwX34Lyb3VDjt27ODQoUNcu3aN4sWL06hRI1q1aoXBcPefX1+/fh2AIkWKZBsvWrQoAImJiRw/fpyqVavmaF4fHx9Gjx7N6NGjCQgIYNu2bbz77rvEx8fz9ttv07x586y+I0aMYM6cORiNRurVq4eXlxcnT55k+fLlrFmzhgULFvDUU09ZzD948GDOnj1L1apVadq0KQCHDx9m8eLFrFy5kh9++IHGjRtnm9vu3bsZPHgwJUuWxN/fn2s2+FpAAAAgAElEQVTXruHs7AzAgAEDWLRoEc7OzjRq1IiiRYsSFxfHqVOnmDVrFl27dsXDwyNH74E8flQAEZFHRoPKpfBwc+HjVWEW54KYMzOZtS6c7k1q0KZWJRtmKCIiIvLgLV682KqtatWqfP3111SvXv2u5ipW7OZW45iYmGzjp06dyvr977//nuMCCED//v1Zs2YNu3btolOnTkRERFCpUiXGjRuX1WfevHnMmTMHX19fvvnmG6pUqZIVW716NX369OGNN95g//79uLu7Z8UmTJiAv7+/xQGqmZmZzJ8/n8GDBzNo0CDCw8Oxy+Z2wW+++YZhw4YRGBhoUTSKjY1l0aJFlC5dmtDQUIoXL24xLioqipIlS+b49cvjR1tgROSRUsHTnQk9WuNawMEqtvTngyzaEWWDrEREREQevJo1azJ16lQiIiI4e/Ys0dHRLF26lJo1a3L06FGeeeYZzp49e1dz3lqJsXTp0qzVIH/19ddfZ/0+MTHxruY2GAzMnj0bV1dXIiIiMBgMBAcH4+LiAtzcbnLrjJD//Oc/FsUPgM6dO/Paa68RHx/P0qVLrWJ/vz3Gzs6Ovn370rBhQ6Kjozl69Gi2eVWpUoX333/fasXMxYsXAahdu7ZV8QOgVq1aWQUjyZtUABGRR457QRcmv/wUnqaCVrGth04x46edmM3mbEaKiIiIPL769evH22+/jY+PD66urpQoUYJ27dqxZcsWGjRowMWLF5kxY8ZdzdmtWzcqVarEhQsX6Nq1K3v27OHatWscOXKEPn36EB4ejtF4c2NAdqsp/knFihV57bXXgJtFi4YNG2bFoqKiOH/+PL6+vrddWXJre0tERIRV7MyZM3z99deMGjWK/v37ExAQQEBAABcuXADg+PHj2c7ZsWNH7O3trdqrVKmCm5sb69ev5+OPPyY2NvbuXqw89rQFRkQeSQUcjHz44pN8unY3R/64aBE7euYSY7/bwugXWlLAQV/GRERE8oLcPEMjr3F0dGTIkCH06NGDDRs2WMQCAgKs+nt7ezNkyBAAnJycWLZsGT179iQiIsLiWlqj0cjEiROZMWMGcXFxFltQ7kbBggUt/nvLrW03R44cwWQy3XGOvx8++tFHHzF9+vQ7Hsx6uxUrZcqUybbdzc2NWbNmMWDAAIKCgggKCsLLy4sGDRrQrl07nn/+eZycnO6Ypzze8uRPDkuWLGHq1Kn89ttvmEwmWrduzeTJk/Hy8srqk5mZyaRJkwgODubSpUs0aNCAzz77jDp16tgwcxH5K4PBwODOTVi0I4qth05ZxC7EX2fktxsY060l7gVdbJShiIiIyMNxa/vIuXPnLNoXLVpk1dff3z+rAAJQqVIldu7cybp16wgPDychIYEyZcrwzDPPUKZMGcaMGQNw1+eL/JOMjAwAvLy8bnsLzS3e3t5Zv1+5ciVTpkzBzc2NiRMn0rx5c0qUKJF1kOnrr7/O999/T+ZfT87/i1v9stO1a1datmzJ2rVr2blzJ+Hh4axcuZKVK1cyefJk1q1bR+nSpe/ylcrjIs8VQFatWkWPHj3o378/06ZN49y5c4wePZpOnToRGRmZtQ9s8uTJBAUFMW3aNKpWrcqMGTNo06YNBw8epEQJ3TQh8ijp2awWxU2uLP35oEX79ZQ0Ri/ezLCn/angeW+fWIiIiIg8Di5fvgyAq6urRXt8fHyOxhuNRrp06UKXLl0s2rdu3UpGRgbVqlXD09Mzd5L9f7cKCZ6engQHB+d43IoVKwAYM2YMffr0sYqfPHnyvvIqXLgwPXv2pGfPnlnzDRw4kB07djB27FjmzZt3X/PLoyvPnQGyaNEi6tWrx6xZs2jdujUvv/wyn332Gfv27cu6L/rGjRtMnjyZUaNGMWDAANq0acOyZcuws7Nj1qxZNn4FIpKdNrUqMaBDQwx/25ualmFm8ort7Dn+h40yExEREXnwfvzxRwDq1auXq/POnDkTgLfeeitX5wWoX78+RYoUISoqihMnTuR43JUrVwAoVaqUVSw6OpqoqNw9FL9ixYoMGzYMgIMHD/5Db3mc5bkCSFpamtX+slunB99aIvXzzz+TkJBA9+7ds/q4urrSpUsX1q1b9/CSFZG7UqtcCT54oQWORstDrTIz4atNkaz95TcbZSYiIiJyf6KioggJCcnaNnJLeno6M2fOZM6cOcDNg1Lv1r59+0hNTbVoS0pKYtiwYWzatIlGjRplu9Lifjk4ODB8+HAyMjLo1asXkZGRVn1SU1NZu3Ytv/32v+/jbm33+e9//2uR98WLF3nnnXfueC7Inezfv5/ly5eTnJxsFQsJCQFuf36I5A15bgtM37596dq1K9988w1du3bl/PnzjB49mlatWlGtWjUAjh49ir29vcU+MwBfX1++++47W6QtIjlUqqiJSb3a8uHSUBKSUyxiKyKOcP5KIn1b17dRdiIiIiL3JjY2ll69euHu7k7t2rUpVqwYly9f5vDhw5w7dw6DwcD48eMtDjHNqcDAQA4cOECtWrXw9PQkISGB8PBw4uPj8fPzY/HixVZXxuaWgIAATp8+zeeff06rVq2oUaMG5cuXx9HRkXPnzhEVFcX169dZvnx5VuEjICCAJUuWsH79eurWrUv9+vW5ceMGO3fupFSpUnTu3JnVq1ffdS6nT5+mb9++uLi4ULt2bUqVKkVqaipRUVHExMTg5ubG+++/n9tvgTxC8twKkE6dOvGf//yHt956C5PJhI+PDxkZGSxfvjyrz5UrVyhYsKDV1Uju7u4kJSVZVUdF5NHi5lyAyb2eonTRQlax3cf+YPKP20nXNbkiIiLyGKlRowYBAQF4e3sTHR3NqlWr2LlzJ87Ozrz88sts2bKFQYMG3dPcL774InXq1OHYsWOsXLmSPXv2ULNmTT777DM2bNhAkSJFcvnVWProo49Yu3Ytzz//PFevXmXDhg1s3ryZuLg42rVrx9y5c2ncuHFW/woVKrB9+3aef/55MjMzCQkJITo6mldffZWNGzdSqJD194A50aBBA8aOHUuTJk04c+YMa9asYdu2bbi4uDBgwAB+/vnnXN9iJI8Wu8zbHZ37mAoNDeXpp5+mX79+dOjQgQsXLjBu3DhKlCjBpk2bsLe3Z+LEiUybNo2rV69ajJ07dy5vvvkmKSkpODo6WsS+/PJLvvzyS+Dm0qvff//9ob0mEbm94JBwfo05b9VepKAzY7q3xOVvf5dFREQkd0RGRlqtqBaRR8+xY8cIDQ1l6NCh2P3tPL38Js+tABk6dChPP/00U6ZMoWXLlrz44ousWLGCrVu3snLlSuDmSo9r165Z7a+7cuUKLi4uVsUPuHko0N69e9m7dy/FihV7KK9FRP5ZQPuGtK9j/c3X5WvJjPx2I3/GX7NBViIiIiIi8qjJcwWQo0ePUqdOHYs2Hx8fnJ2ds04erlq1KhkZGRw/ftxqbNWqVR9ariKSO55rVI3eLWrz93r2jdR0xn63heizF22Sl4iIiIiIPDryXAGkXLly/PLLLxZtR44cITk5mfLlywPQpEkTChUqxLJly7L6JCUl8dNPP9GhQ4eHma6I5BJ/3/IMeboJ9gbLMkiGOZMZq34m7EiMbRITEREREZFHQp67Beadd95h8ODBeHl5ZZ0BMn78eMqXL0/Hjh0BcHJyYuTIkQQFBeHu7k7VqlWZMWMGZrOZf/3rXzZ+BSJyr3y8ivHhi62YuHwbyan/ux4tE/hm234uxF/n+UbVbZegiIiIiIjYTJ4rgAwcOBBHR0eCg4OZM2cOhQsXxt/fn0mTJuHq6prVb+TIkZjNZiZNmkRcXBx+fn5s3LgRT09PG2YvIveruKkgk15uy/ilW7l8zfKO9/X7jnPh6jX6tW9oo+xERERERMRW8twtMA+Dn58fe/futXUaInIH6WYz01eGceLCFatY6aKFeP/ZFhiNeW4XoIiIyEOjW2BEHg+6BeZ/9N2/iORJRoOBEc82p5F3aavYH3EJjFy4gcTkFBtkJiIiIiIitqACiIjkaX1b16frE75W7QnJKYxauJEzcfE2yEpERERERB42FUBEJM/rWK8Kb7bx4+8r/lLTMwj6fhtRv5+3TWIiIiIiIvLQqAAiIvlCg8qlGNm1OQ72ll/2zJmZzFoXzqaoEzbKTEREREREHgYVQEQk36jg6c6EHq1xLeBgFVv680EW7YiyQVYiIiIiIvIwqAAiIvmKe0EXJr/8FJ4mV6vY1kOnmPHTTsxmsw0yExERERGRB0kFEBHJdwo4GPnwxVb4li5mFTt65hJjv9tCSlq6DTITEREREZEHRQUQEcmXDAYDgzs3oWX1ClaxC/HXee+b9Rw/F2eDzERERERE5EFQAURE8rWezWrRvUkNq/YbaelMXRnG8t2HbJCViIiI5EfHjh0jODiYN998Ez8/PwoXLozJZGLFihU5Gr9s2TLat29PmTJl8PLyokWLFnz11Vf3vL33jz/+YO7cufTv358mTZpQpEgRTCYTn3322V3PNX/+fEwmEyaTiWHDhuV43NChQzGZTDz99NNkZmbett/x48cpUaIERYoUYc+ePXedn+QPRlsnICJia21qVaK4yZXZIRGY//YP6/p9xzkQe4HhT/vj4uRoowxFREQkP5g3bx7BwcH3NHbo0KHMnTsXJycnWrRogYODA9u2bWPYsGFs3bqVBQsWYDDc3effq1atYtSoUfeUz1/FxsbywQcfYGdnd8ciRnbGjx/Ppk2b2LZtG3PnzuXNN9+06mM2m+nXrx/JyckMHjyYBg0a3HfOkjdpBYiICFCrXAnGdn+SgtkUOc5eTuS9Bes5FPunDTITERGR/MLX15eBAwcyf/58fv31V/z9/XM0buXKlcydOxdPT09+/vlnli5dysKFC/nll1/w8fFh9erVfPHFF3edT7ly5QgICOCLL74gIiKCl1566a7nyMzMZMCAAZjNZnr06HHX411dXQkODsZgMDB27FhiYmKs+nz++eeEh4dTrVo13n///bt+huQfKoCIiPy/ku5uTO3djlrlPK1iaRlmPl27iwXb9tkgMxEREckP+vTpQ1BQEM899xwVK1bM8bgZM2YA8OGHH1KpUqWs9uLFi2fF/v3vf9/1VphOnToxefJkXnrpJXx8fO56BQncXNWybds2xo4dS9myZe96PECTJk3o168f169fp3///harSI4dO8aECRNwcHBgzpw5ODpqxa7cngogIiJ/YTQYGNChEX1a1MFgZ2cV33HkdwIXbSQ+6YYNshMRERGxdObMGfbt24ejoyNdu3a1ivv7++Pl5cWFCxce+tkYMTExjB07lsaNG/PWW2/d11wffPABVapUISwsLGs1y62tLzdu3GDYsGHUrl07q390dDT9+/enZs2aFC9enLJly/L000+zdu3abOc/evQoEydOpG3btvj4+ODh4UHFihV54YUX2LRpU7ZjFi5ciMlkIiAggMuXLzN8+HBq1qyJh4cHPXv2zOq3efNmunXrRqVKlShatCjlypXDz8+P/v37s2+fPlx7mHQGiIhINpr6lqNq6WJMXbGDK9ctix0XE5IY+e0G+raqT4PKpWyUoYiISN5Sv99CW6dwXyJn97LJc6OiogCoWrUqzs7O2fapV68eZ8+eJSoqioYNGz6UvG5tfUlPT2fWrFnYZfPB0t1wcnJizpw5tG3blg8//JC2bduyZs0aIiIiqF27tsXBqt9//z0BAQGkpqbi6+tLu3btiIuLY9euXWzbto3hw4cTGBhoMf+sWbNYsGABPj4+1KhRAzc3N2JiYti4cSMbN25k4sSJDBgwINvc4uLiaNmyJQkJCTRp0oS6detSpEgR4GaRpF+/fhgMBvz8/ChTpgzXr1/nzJkzLFy4kEqVKlGnTp37em8k51QAERG5jaJuLkzq1Zb5ob8SfuwPi1iGOZOvNu3l11NneaN1/XtaEioiIiJyv37//XeAO24vKV26NEC252c8KF9++SU7duxg3LhxVK5cOVfmrF+/Pu+++y7Tp0+nT58+HDt2jAIFCvDFF19gNN780fbgwYMEBATg6OjIokWLaNu2bdb4I0eO8MILLzB16lSaNWtG8+bNs2IvvfQS7733HuXKlbN45t69e3n22WcZN24czz77LKVKWX/4tX79elq1asU333yDm5ubRWzKlCkAhISEWBWfzpw5Q2Ji4v29KXJX9B27iMgdGAwGXm9dn7efaoDRYP3Jxd4TZxnx7UYuJly3QXYiIiKS3127dg0AFxeX2/ZxdXW16PugnTx5knHjxlG3bl0GDhyYq3OPHDmS6tWrc+DAAW7cuMGoUaPw9fXNin/88cekpqZmrRL5K19fXyZOnAjcLND8lb+/v1XxA8DPz48333yTtLS0226fcXBw4JNPPrEqfgBcvHgRk8mU7cqbUqVKUbVq1X9+0ZJrtAJERCQH6lf0wvvlp5i2MowL8ZbFjvikG3yweDM9m9WiebXytklQRERE5BFwa+tLWloas2bNwt7ePlfnd3R0ZMyYMbz44osUK1bMosBiNpvZvHkzdnZ22Z6HAmTdrJPdeSiJiYmsX7+eAwcOcOXKFdLS0gA4ceIEAMePH892ztq1a2dbPIGbq1Z27NjB22+/Tb9+/ahVq9Z9bweSe6cCiIhIDhVycSKoRxsW74gi9NApi5g5M5Nvt+/nl1NnGdChEUZtiREREbkrtjpD43FXsGBBAJKSkm7b5/r16xZ94ebNMceOHbPqGxwcfF/5zJkzh507dzJixAhq1KhxX3Pdzq0VLc7OzhYFlsuXL5OQkABgcRtOdi5dumTx5zVr1tC/f3+uXLly2zG3265SpkyZ246ZPn063bt3Z8mSJSxZsgSTyUS9evVo2bIlPXr0wNPT+vZBeXBUABERuUs9mtWiToUSfB4SQWp6hkXs8OmLvPffEIY93ZRSRU02ylBERETyi1tnf8TGxt62zx9/3DzL7K+rFDZv3kxYWJhV3/stgKxevRqA0NBQdu7caRG7lePq1as5cuQIrq6uLF269L6e91cZGTe/L7O3t+fFF1/M8bgzZ87w+uuvk5yczJAhQ3jhhRcoW7Ysrq6uGAwG5s+fz7vvvmtx/e5f3e7wWQAfHx/27t3L5s2b2b59O7t372bHjh2EhoYyZcoUFixYQJs2be7uhco9UwFEROQe+JYuztTeTzF95U5OxyVYxK6npDF+2Vaea1SNdnW8bZShiIiI5Ae1atUCbl7jmpycnO0P47/++qtFX7i54uFBioiIuG3s3LlznDt3DpMpdz8sKlq0KM7OziQnJzNt2jSLFS93EhISQnJyMk8//TRjx461ip88efK+8nJwcKB9+/a0b98egCtXrjBlyhSCg4MZMGAAR48eva/5Jee0RltE5B65ODryQbcn6VivilUsE1i++zBTVuwgNT394ScnIiIi+ULp0qWpXbs2qamprFixwioeFhbGmTNn8PT05Iknnnjg+axZs4b4+Phsf40cORKAN998k/j4+DuuWrkXRqORli1bArBy5cocj7u17eXWbTl/lZKSwqpVq3Ilv1vc3d0JCgrCYDBw7tw5q+048uCoACIicp+6PuHLqGeb4+RovajuxPnLDPvvek6cj7NBZiIiIpIfDBkyBICxY8dmHdgJN28gGTp0KACDBw/GkA/OKBs+fDgODg6MHDmS77//3mrbSmZmJpGRkWzevDmrrUqVmx9mrVq1ij///DOrPTU1lffee++erw9OSkpi1qxZ2RY41q9fj9lsplChQrm+EkZuT1tgRERyQQVPdz7u3Y5P1uzi+LnLFrEbaelMWRFGh7rePNuwmo0yFBERkUfdvn37sgoWANHR0QCMHz+emTNnZrX/9Yd3gK5du/L6668zb948mjRpQsuWLTEajWzfvp2EhAQ6d+7MW2+9ddf5nD9/nl69/nc47alTNw+B//LLLy1WWCxcuJASJUrc9fwPQr169ZgzZw4DBgzg9ddf58MPP8THxwd3d3cuXbrEgQMHuHjxIu+++y6tW7cGoGPHjtSqVYuoqCjq1auHv78/BQoUIDw8nISEBN555x3mzJlz17mkpqYSGBjImDFjqFatGpUqVcJgMHDq1Cl+/fVX7OzsGDduHA4ODrn9NshtqAAiIpJLHI1Ghj/TjA37j7N81yH+fkzWul+PceD3Cwzr2hQXR0eb5CgiIiKPrsTERPbu3WvV/tdVHbczY8YMGjduzFdffcXOnTvJyMjA29ubV155hddff/2eVn+kpKRkm8/p06c5ffq0Rb9HyQsvvEC9evX44osvLA5jLV68ODVr1qRdu3Y888wzWf2NRiNr165l2rRprFmzhi1btlC4cGH8/f0ZNWrUHc8zuZOCBQsyY8YMwsLCOHDgAFu2bCEtLY2SJUvSrVs33nnnHfz8/HLlNUvO2GXe7ihbuS0/P79svxCIiNxy5nIC01ft5NqNVKuYg72B/u0bUq1McRtkJiIikjsiIyPx9tZh3yKPumPHjhEaGsrQoUOxs7OzdTo2lfc3gYmI2ECpIoWY2rsdNcpaFznSMsx8smYX327fZ4PMRERERETyJxVAREQeEKPBwMCOjendojaGbKrt2w//TuCijSQk3bBBdiIiIiIi+YsKICIiD5i/b3km9GhDYVcnq9jFhCRGfLuByBNnbJCZiIiIiEj+oQKIiMhD4FHIhcm92tKgcimrWIY5ky827uWrTXsxm802yE5EREREJO9TAURE5CExGAy82caPt9v6YW+w3hKz5/gZRi7cyKWEJBtkJyIiIiKSt6kAIiLykNWvVIopLz9F8UKuVrGr128wevEmwo7EPPzERERERETyMBVARERsoJCLExN6tqFFtfJWMXNmJt9s289na3aRri0xIiIiIiK5QgUQEREb6tW8Nu92aoyDvfWX44On/2TEgg3aEiMiIiIikgtUABERsbFqZYozrU87ShctZBVLTE5h9OJN7Dn+hw0yExERERHJO1QAERF5BLg4OjKm25N0qOdtFTNnZvLVpkj+G/qrDTITEREREckbVAAREXmEPPtENYY/44+j0d4qtjM6ljFLNpN0I9UGmYmIiIiIPN5UABERecRULlmUqb2foqS7m1Xs/NVrDP92A8fOxtkgMxERERGRx5cKICIijyAXR0c+fLEVzXzLWsVS0zOYtiqM1ZHRNshMREREROTxpAKIiMgj7JUWdXm7rR/2Bjur2Ko9R/l4VZiuyhURERERyQEVQEREHnH1K5Ui6KU2FHIuYBX77Wwcw79Zz4Wr12yQmYiIiOSmY8eOERwczJtvvomfnx+FCxfGZDKxYsWKO44LCAjAZDLd9pefn9895bNv3z4++eQT+vTpQ82aNbPm++WXX/5xbHR0NAEBAVSrVg0PDw8qV65Mr169CA8Pz/Hz09LS8Pf3x2QyMWXKlDv2XbJkCSaTCV9fX65evZrjZ0j+YrR1AiIi8s88Crkw+ZWn+HxdOIdO/2kRu3YjlbHfbaFPyzo09rHeMiMiIiKPh3nz5hEcHHzP4xs1akTFihWt2j09Pe9pvqlTp7JmzZq7HhcSEsKrr75KcnIy3t7edOjQgdjYWFavXs3atWv59NNP6d279z/O4+DgwJw5c3jyySeZNm0aHTt2pGbNmlb9zp8/z4gRIwCYOXMmhQsXvuucJX9QAURE5DFhNBgY1KkxG/YfZ/muQ2T+JWbOzGR+6K8c/uMirz1ZF4NBC/xEREQeN76+vgwcOJC6detSp04d/vWvfxEWFpbj8b1796ZXr165lk+DBg2oVq0aderUoW7durRv357Y2Ng7jvnzzz954403SE5OZvz48QwaNCgrtnbtWl555RUGDx5Mw4YN8fHx+cccatSowfDhw5kwYQIBAQGEhobi4OBg0WfQoEFcvXqVPn360KZNm3t7sZIvqAAiIvKYeap2ZaqULMr0n3aSkpZhEQs/9gcnL1xm5LPNcctmy4yIiIg8uvr06WPrFCwMHjz4rscsWLCAxMREmjZtalH8AOjYsSOvvfYaX331FdOnT+fLL7/M0ZxDhgxh3bp1REZGMnXqVAIDA7NiixcvJiQkhLJlyzJx4sS7zlfyF31EKCLyGCpf3J1pr7SnTNFCVrGLCUmM/HYDR/64aIPMREREJD+7dT5Iy5Yts423atUKuLkaJD09PUdz2tvbExwcjJOTEzNmzGDfvn0AnDt3jhEjRmBnZ8fnn3+Om5tb1phNmzbx0ksvUblyZTw8PKhSpQp9+/bl0KFD2T4jNDSUoUOH0rRpU8qXL0+xYsWoUaMG77zzDtHR2d+8d+vslYULF3Lw4EF69+6Nt7c37u7uzJ49G4CMjAzmzZtH27ZtKVOmTNZ5KM2aNSMwMJBLly7l6D2Q3KEVICIijyknRyMfdHuSxWFRhB48ZRFLyzDz79U/07FeFbo+4WujDEVERHJu2KJQW6dwXz7u+aStU2DHjh0cOnSIa9euUbx4cRo1akSrVq0e6tbY69evA1CkSJFs40WLFgUgMTGR48ePU7Vq1RzN6+Pjw+jRoxk9ejQBAQFs27aNd999l/j4eN5++22aN2+e1XfEiBHMmTMHo9FIvXr18PLy4uTJkyxfvpw1a9awYMECnnrqKYv5Bw8ezNmzZ6latSpNmzYF4PDhwyxevJiVK1fyww8/0Lhx42xz2717N4MHD6ZkyZL4+/tz7do1nJ2dARgwYACLFi3C2dmZRo0aUbRoUeLi4jh16hSzZs2ia9eueHh45Og9kPunAoiIyGOuh38tfEsV44uNe8gwZ1rE1v7yG9FnLjK0iz9Goxb9iYiI5GWLFy+2aqtatSpff/011atXfyg5FCtWDICYmJhs46dO/e9Dm99//z3HBRCA/v37s2bNGnbt2kWnTp2IiIigUqVKjBs3LqvPvHnzmDNnDr6+vnzzzTdUqVIlK7Z69Wr69OnDG2+8wf79+3F3d8+KTZgwAX9/f4sDVDMzM5k/fz6DBw9m0Dixil0AACAASURBVKBBhIeHY2dnZ5XXN998w7BhwwgMDLQoNsXGxrJo0SJKly5NaGgoxYsXtxgXFRVFyZIlc/z65f7pu2ERkTygToWSTOrVFndXJ6vYiQtXGLYghDOXE2yQmYiIiDxoNWvWZOrUqURERHD27Fmio6NZunQpNWvW5OjRozzzzDOcPXv2oeRyayXG0qVLs1aD/NXXX3+d9fvExMS7mttgMDB79mxcXV2JiIjAYDAQHByMi4sLcHO7ydSpUwH4z3/+Y1H8AOjcuTOvvfYa8fHxLF261Cr299tj7Ozs6Nu3Lw0bNiQ6OpqjR49mm1eVKlV4//33rVbaXLx4czty7dq1rYofALVq1coqGMnDoQKIiEgeUdjVmUm92lKnfAmrWFJKGuOXhbLjSMzDT0xEREQeqH79+vH222/j4+ODq6srJUqUoF27dmzZsoUGDRpw8eJFZsyY8VBy6datG5UqVeLChQt07dqVPXv2cO3aNY4cOUKfPn0IDw/HaLy5ESG71RT/pGLFirz22mvAzaJFw4YNs2JRUVGcP38eX1/f264subW9JSIiwip25swZvv76a0aNGkX//v0JCAggICCACxcuAHD8+PFs5+zYsSP29vZW7VWqVMHNzY3169fz8ccf/+MNOvLgaQuMiEgeYjAY6Ne+IaEHT7Jk5wEy/7IjJjMTFmzbz6HTf/JWGz9dlSsiIo+UR+EMjbzG0dGRIUOG0KNHDzZs2GARCwgIsOrv7e3NkCFD7uuZTk5OLFu2jJ49exIREWFxLa3RaGTixInMmDGDuLg4iy0od6NgwYIW/73l1rabI0eOYDKZ7jjH3w8f/eijj5g+ffodD2a93YqVMmXKZNvu5ubGrFmzGDBgAEFBQQQFBeHl5UWDBg1o164dzz//PE5O1qt35cFRAUREJA96skZFKpcsyscrw0hOtfyH/JeT5whctIlRzzWnkIv+0RUREcnLbm0DOXfunEX7okWLrPr6+/vfdwEEoFKlSuzcuZN169YRHh5OQkICZcqU4ZlnnqFMmTKMGTMGINfPJcnIyADAy8vrtrfQ3OLt7Z31+5UrVzJlyhTc3NyYOHEizZs3p0SJElkHmb7++ut8//33ZGZmZjvXrX7Z6dq1Ky1btmTt2rXs3LmT8PBwVq5cycqVK5k8eTLr1q2jdOnSd/lK5V6pACIikkeVKWpiWu92fLxyJzEXr1rE4q4lM/LbjfRr34AaZa23zIiIiEjecPnyZQBcXV0t2uPj4x/oc41GI126dKFLly4W7Vu3biUjI4Nq1arh6emZq8+8VUjw9PQkODg4x+NWrFgBwJgxY+jTp49V/OTJk/eVV+HChenZsyc9e/bMmm/gwIHs2LGDsWPHMm/evPuaX3IuT65/btmyJXZ2dtn+2rVrF3DzRN+PPvqIMmXK4OzsTPPmzbPukxYRySscjUbef74FT9WuZBVLN5v5bG04y3YdtEFmIiIi8jD8+OOPANSrV8/Gmdw0c+ZMAN56661cn7t+/foUKVKEqKgoTpw4keNxV65cAaBUqVJWsejoaKKionItR7h5jsmwYcMAOHhQ34c9THmyADJ79mx27dpl8att27Z4eHjQoEEDACZPnkxQUBAjRozgp59+omDBgrRp04bz58/bOHsRkdz3QuMaDOrYGKO99Zf9jftPMHH5VlLvsOdVREREHk1RUVGEhIRkbf+4JT09nZkzZzJnzhzg5kGpD8u+fftITU21aEtKSmLYsGFs2rSJRo0aZbvS4n45ODgwfPhwMjIy6NWrF5GRkVZ9UlNTWbt2Lb/99ltW261tQv/9738t8r548SLvvPPOHc8FuZP9+/ezfPlykpOTrWIhISHA7c8PkQcjT26BqVatmsWfU1NT2bt3Ly+++CJGo5EbN24wefJkRo0axYABAwBo3Lgx5cuXZ9asWUyYMMEWaYuIPFDVyxZncq+2TPpxB3GJSRax3y/G89436xnaxZ+yxe58aJiIiIg8GPv27WPo0KFZf46OjgZg/PjxWSsnADZv3pz1+9jYWHr16oW7uzu1a9emWLFiXL58mcOHD3Pu3DkMBgPjx4+3OIw0p9avX591rSyQ9WFx//79s66eLVGiBAsXLrQYFxgYyIEDB6hVqxaenp4kJCQQHh5OfHw8fn5+LF68+IEdxh4QEMDp06f5/PPPadWqFTVq1KB8+fI4Ojpy7tw5oqKiuH79OsuXL88qfAQEBLBkyRLWr19P3bp1qV+/Pjdu3GDnzp2UKlWKzp07s3r16rvO5fTp0/Tt2xcXFxdq165NqVKlSE1NJSoqipiYGNzc3Hj//fdz+y2QO8iTBZC/CwkJ4cqVK/To0QOAn3/+mYSEBLp3757Vx9XVlS5durBu3ToVQEQkzyrk4sTEHq2ZuzmSvSfOWsSSU9OZuHwrL/nX5MkaFW2UoYiISP6VmJjI3r17rdrvtJ2jRo0aBAQEEBkZSXR0NLt27cLOzg4vLy9efvll3njjDerWrXtP+Vy6dCnbfA4fPpz1+7Jly1rFX3zxRezt7YmOjmb37t0ULFiQmjVr0r17d15++eVsr4zNTR999BGdOnVi3rx5hIeHs2HDBpydnfH09KRdu3Z07NiRxo0bZ/WvUKEC27dvZ/z48ezevZuQkBBKlizJq6++yvDhwxk5cuQ95dGgQQPGjh3Lzp07+e2339i3bx+Ojo6UKlWKAQMG8Pbbb2f7/smDY5d5u6Ns85CePXuyY8cOYmNjsbOzY/bs2QwcOJCUlBSLv3zTpk1j3LhxXL9+/Y7z+fn5ZfuFQETkcbLjSAzfbt9Pdv8K1C7nSUC7J3RVroiI3FZkZKTFTRoi8mg6duwYoaGhDB06FDs7u/9j777Do6zT/fG/n2mZTGYmmfRGGglJIPQAKr0KAse1YgPWhm7xHF13Xfe4liO74n7x6P487nHFsoqrIip6BJHeBAWlhgCBhIQkpJfJ9P7M7w/WKCYZUmcmyft1XV7rzuczz9yjXHHmnc9z34EuJ6AG/Cdbq9WKzz//HLfeemvrv2y9Xg+1Wt0medTpdLBarW3uVwOANWvWID8/H/n5+WhoaPBL7UREfWlqbhqeuXUWwkLkbdZOlNfh8fe2o8XS9p5VIiIiIqL+aMAHIBs3boTFYmm9/aW7VqxYgcOHD+Pw4cOIiYnppeqIiAIrQafB6qXzMTQ+ss1ai8WOP7y3HTsKzsNotQegOiIiIiKi3jPge4CsW7cOmZmZyM/Pb31Mp9PBbDbD4/FcdgpEr9dDpVJBoVAEolQiooCQyST4/c+m4v++O4Mvjpy7bM0jerH+60Ks/7oQEkFAmFKOaG0YhkRpkZ0YjRHJsVAp+TOTiIiIiILfgA5ADAYDvvzySzz22GOXPZ6TkwOPx4OSkhJkZ2e3Pl5UVIScnBx/l0lEFBSun5CLnKRovPzFQbg8Ypt10euFyeaEyeZEWZ0e+06XAwCkEgFqpQIx4WFIjY5AdmI0cpNjECIf0P+JISIiIqJ+ZkB/Ov3000/hcDja3P5yzTXXQKvV4qOPPsIf//hHAJd6hWzcuBErVqwIRKlEREEhOzEGf1l6LZ7fsA/1Rt8Nob/nEb0wWB0wWB0oqWnGzpOlAACZRAKNKgSx4WFIi4lATmIMshOjIZMN+LsviYiIiCgIDegAZN26dRg9ejRyc3Mve1ypVOLxxx/HypUrodPpkJOTgxdffBGiKOKhhx4KULVERMFBrVTgT3fMwaeHTuPrsxUw253wiF0fGOYWRejNNujNNpytasTW4yUAALlUAq1KifgINdJiIzA8KRbp8TrIOHGGiIiIiPpQpwMQg8GAzz77DNu2bcOpU6dQXV0Nk8kEANBoNEhMTMSIESMwb948/OxnP0N4eHifFd0ZjY2N2LlzJ1auXNnu+uOPPw5RFLFq1So0NTUhPz8f27dvR1xcnJ8rJSIKTjdMGo4bJg0HAJjtTpyurMO5miZUNhrQaLTC4nBB7MYkdZdHRJPJiiaTFacq61v7jihkUkSolEjQqZEeF4nhyTFIiQ7nKF4iIiIi6hWC13vlT68vvPAC/vznP8NoNAIAOnrK92NmNRoNnnzySTz66KO9WGrwyM/Px+HDhwNdBhFRwBmsdhSW1+FcbROqmoxoMllhdbrQjVykQ0q5DDq1EjmJMZg1MgNxEereuzgREXXbkSNHkJWVFegyiOgKiouLsXv3bjz66KOt39kHqyueALnvvvvwj3/8ozX0yM3NRV5eHpKSkqBSqQBc6p9RVVWFwsJCnDlzBkajEY899hiKiorw+uuv9+07ICKigAlXKTE5NxWTc1Mve7zBaMGpinqU1DajqtkIvdkGm9OF7uQidpcbNXozavRm7D5VhhC5FKkxEbg6awgmZQ1hTxEiIiIi6hSfAciGDRvw1ltvAQBWrFiBP/zhD0hNTfX1FFRUVOD555/Ha6+9hrfeegsLFy7Ez372s96rmIiIgl6MNgwz8tIxIy/9ssermo04VVmP0rpm1OhN0JvtsLvcXbq2w+XBueomnKtuwjt7jyNKHYoRKbGYmZeBpEhtb74NIiIiIhpAfAYga9asgSAIeOqpp/D000936oIpKSn43//9X8THx+OZZ57Ba6+9xgCEiIgAAEmR2jYhhSiKqGwy4FRlA8rqmlHTYkaLxQ6n29OpazaZbdh3uhz7TpdDIZMiJTock7KGYHJ2Ck+HEBEREVErnz1AYmNjodfrYTAYWm936Syr1Yrw8HBERkairq6ux4UGE/YAISLqe25RRFmtHqer6nG6sh4Xm4xwecQuXUMXpsTw5FjMGpWBIVGBbc5NRDTQsAcIUf/AHiA/8HkCxGQyQa1Wdzn8AACVSgW1Wt06KYaIiKgrZBIJshKjkJUYhesnXBpnfqFej92nynDmYgNaLPYrXkNvsePA2QocOFsBuVSCIdHhmJCZhCk5qQiRD+hJ8ERERET0Ez4//SUkJKC8vBznz5/H0KFDu3ThkpISGAwGpKenX3kzERFRJ6TF6nB3rA4A4HS7caCoAt+WVKGioeWKp0NcHhGldXqU1unx4YFChKuUyE2OwcwR6UiP0/mjfCIiIiIKIJ8ByNy5c/H666/jnnvuwcaNG6HVdq65nMlkwr333gtBEDB37txeKZSIiOjHFDIZZuZlYGZeBgCgssmAPYWlOFXZgGaz7YrPN1jtOHiuEgfPVUImlSA5Uov8zCRMy02DUsHTIUREREQDjc8eIKWlpRg1ahRsNhvi4+Pxy1/+EvPnz0deXh5CQkIu2+twOFBYWIgtW7bg1VdfRU1NDVQqFQoKCgbcKRD2ACEiCm5ut4hviitw8NxFlDe0dLqh6ve0oSHITorGzBHpyEyI6qMqiYj6N/YAIeof2APkBz4DEADYvHkzlixZAovFctk/LJ1O19obxGq1Qq/Xt655vV6EhYVh/fr1WLBgQR+VHjgMQIiI+pcavQm7C8twsqIOzSYrfP6H7yekEgFJkVqMz0jE9OFpUCkVfVYnEVF/wgCEqH9gAPKDK57xve6663Dy5Ek8+eST2LBhA2y2S8eKm5ub0dzc3GZ/aGgobrrpJjz77LNIS0vr9YKJiIi6KkGnwR1TRwG4NF3mu+KL+PpcJcrrW2B3uX0+1yN6UdFoQEWjAZ9+ewYyqQRhIQpEaUKRqNMgLVaHnKRoxIar/fFWAkoURdQZLCitbUZNiwkxWjWuzk6GQsZbhoiIiCj4XfEEyI9ZrVbs378fhYWFqK6ubp3wotFokJiYiLy8PEyZMqVbU2P6E54AISIaOOoNZuwuLENBeS0ajV07HfJTSrkM2tAQxISHYUhUODITIpGZEAmVov+cGrE6nSitbcaFBgOqm41oMFrQYrHD6nB12Gg2SqPCmLR4zBk1FFGagf0ZgIh+wBMgRP0DT4D8oEsBCF3CAISIaGASRRFHSqtxoKgCZfV62Jy+T4d0lkQQoAqRI1IdirgINVJjIpCdGIUhUeGQSCS98hqdJYoiqvQmlNXpUdloQK3BjGaTFWa7E3aXGz39VBAWIkd2YjRmjxyKrET2TyEayBiAEPUPDEB+wDOrRERE/yKRSDAhMxkTMpMBAE0mK3YXluLEhTrUG83dDgdErxdmuxNmuxMVjQZ8V1LVuiaXSqAJDUG0VoUknRbpcTrkJscgXKXs9vsw2Rw4X9uM8sYWVDeb0Gi0oMXqgM3hglv0PS64pywOF46W1eBoWQ1kUglSo8NxTU4Krs5OgczPYQ8R9T2v1zvov1ARBTOv1wueefhBtwMQq9V62S0wA/22FyIiGnyiNCrcfHUebr46DwBQ12LG2epGlNXpUd1iQrPJBovd2aNQweUR0Wy2odlsw7nqJuw+VQYAEAQgVC5HeJgSca231EQhKz4KkAAXGw0oq790iqPOYEGz+VItDpe7R7fxdIZMKkGITAqLw+Vzn9sj4nydHufr9Pjn3hOICQ/D+IxEzB6ZAW0PAh4iCg4ymQxutxtyuTzQpRBRB5xOJ4PKH+l0AFJSUoL33nsP27Ztw+nTp2E0Gi9b12q1GD58OObNm4c777wTmZmZvV4sERFRIMVFqBEXoca04WmXPe52izhf34TimmZUNrSgzmBBi9UOm9PV7VMjXi9gdbpgdbpQozfh+IXanr+BThIEAUq5FBplCCI1oYgLV2NIdDiGxumQoNO03rbjdLtxoKgCX5+txMUmAzxix2/WC6DeYMGXx4rx5bFiqJUKDE+OxZxRGUiL1fnpnRFRbwoPD4fRaERUFG93IwpGXq8XTU1NaG5uhlwuZwiCTvQAcbvdePjhh7FmzRp4PJ4rHp8RBAFSqRQPPPAAXnzxxQGZCLMHCBERdZbRakdRVQNK61pQ1WxEo9ECk90Jp9sT0LrkUglUIXJEhCkRow1DYqQW6TE6pMdHdLtp66mKeuw+VYrimqYu9U9RyKRIi43AtNxU5A9N8ntfFCLqHrvdjlOnTiEyMhJarRYymYxfsIgCzOv1QhRF2Gw26PV6GI1GFBQUIDY2FjfccEOgywu4KwYgCxYswLZt2+D1eqFWqzF16lTk5eUhKSmp9bYXq9WKqqoqFBYW4quvvoLZbIYgCLj22muxefNmv7wRf2IAQkREPSWKIi42mXCuuhHljS2o0ZugN9tgdbp8nqToLIkgQKmQQaMMQZQmFPERGqREh2NofCRitKo+DxnqWszYXlCCk+V10FvsnX6eIAAJERqMH5qI2XkZUCn7zwQdosGoqqoKBQUFiI6OZnhJFCS8Xi+cTidaWlrQ2NiI2tpa3HjjjbxLA1cIQN58803cf//9kMvl+K//+i889NBDCAsL83lBq9WKV155BU899RRcLhfeeOMN3H333b1eeCAxACEior5kd7pxrqYR5+uaUdloQIPBAoPV0aa/h0ImRdi/TnHEhquRFKlBepwOaTE6hMiDp8+53enGnlOl+LakCtXNJohduC8oXBWCEUNiMXd0JpIitX1YJRF11+nTp7FlyxZ4vV6EhIQwCCEKAqIotvb/uPrqq3H11VfzhBauEIBMmzYNBw4cwCuvvIJf/OIXXbrwq6++il/96leYOnUq9u7d2+NCgwkDECIiCpQmkxVeLxCt7Z/Nx0VRxInyWuw5dQGldc1wuDp/K1CIXIqh8ZGYMTwdo1Lj+CWLKIgYjUaUlZWhpqYGLpfvBslE1PdkMhmio6ORkZGByMhIhh//4jMAiYqKgtlshsVigUzWtd8kuVwuqNVqqNVqNDU19bjQYMIAhIiIqHdUNRmwreA8TlXUw2hzdPp5EkFAUqQGE7OSMT4jCZFqJQMRIiIi8slnAKJSqSCXy2EwGLp18fDwcLjdblgslm4XGIwYgBAREfU+s92JXSfP40hpNWpbzF2eoCMRBMhlEijlMqhCFNCGhiAiTIlITShiNWGI16mREKnpdpNXIiIi6t98HutISUlBcXExjh07hrFjx3bpwkePHoXJZMKwYcN6VCARERENDmqlAv82IRf/NiEXoiji25IqfHWmHBfq9XB5xCs+X/R64XB54HB5YLA6UKM3dbhXJpFAIZciVC5DmFKBcJUSOrUS0RoV4iLUiI/QICY8DDKeKiEiIhowfAYgCxcuxEsvvYSlS5di8+bNSElJ6dRFKyoqsGzZMgiCgEWLFvVKoURERDR4SCQSXDVsCK4aNgQAUFqnx86C8zhT1QCz3dnj67tFEW6HCKvDhSazDUD7p10FAZBLpQiRS6FSKKAJVVw6VaIORYxWjXhdGBJ1WmhCQ3pcExEREfUtn7fA1NfXY/jw4dDr9QgNDcXtt9+O+fPn+xyDu2XLFqxbtw4WiwXR0dE4deoUYmJi/PaG/IG3wBAREQWOwWrHjoLzOFZag0aTtUtTZfqSUi5DbHgYhsZHYkxaArITo9iXhIiIKIj4DEAA4MiRI1i0aBHq6uo63TnW6/UiPj4emzZtwrhx43ql0GDCAISIiCh4iKIIg9WO6mYzag0mNBqtaDbb0GK1w2xzwOZ0w+Fyw+0R4e+oJCxEjgSdBlmJURifnoSUmHA/V0BERETfu2IAAlwaa7V69Wq8++67qKio8Lk3JSUFy5Ytw29/+1totdpeKzSYMAAhIiLqn9xuETUGE2r1JtQZLGgyWqG32mC0OmCxO2F3ueF0e+AR+yYqEQRAGxqCpEgtcpKikT80ud+ONCYiIupvOhWA/Ni5c+dQWFiI6upqmEyXmotpNBokJiYiLy9vUDQ9ZQBCREQ08BmtdtS0mFCrt6DBaG49VWKyOmF1OuFweeDyeLo8reanpBIBEWGhSInSYviQOIwfmgi1kpNqiIiIeluXAxBiAEJEREQ/cIsiLtTpcaysBsW1TahvscDqdPXomnKpBFEaFdJiIjAyNQ6jUuMRIvfZu56IiIiugAFINzAAISIiIl/coojTlfU4caEGpXUtaDRa4HB7enRNpVyGGK0KGXH/arKaHM0xvURERF3QrQCkpaWl3VtgIiIier3AYMQAhIiIiLrK7nTj+IUanKyoQ3lDC5rNNrg9Yo+uGRYiR1yEGlkJURiXnojUmHBOniEiIupApwOQ3bt3Y+3atdi2bRtqa2vb3RMfH4958+Zh2bJlmDlzZq8WGkwYgBAREVFvMFjtOFpajdOV9ahoMsJgsfdorK8AIFQhR3iYErHaMKREhyMzIQpZ8VGQyRiMEBHR4HbFAMRgMOCuu+7C5s2bAVwacevzgv8alXvdddfhn//8J8LDB964NwYgRERE1FfqWsw4UlqNM1UNqG42wWxz9Mr4XplEQJhSgUh1KOJ1GqTH6JCdFI0EnaYXrk5ERBT8fAYgLpcLV111FY4fPw6v14v09HTMnz8feXl5SEpKgkp1aWyb1WpFVVUVCgsLsXXrVpSWlkIQBIwbNw7ffPMNZLKB1bSLAQgRERH5iyiKKG8w4EhpFYprm1HXYobV0bMmqz8VIpdCGxqCGG0YkqO0GBofieyEaKg4jYaIiAYQn8nE//zP/+DYsWPQarX4+9//jttuu61TF12/fj1WrFiBo0eP4pVXXsHDDz/cK8USERERDTYSiQTpcTqkx+laH3OLIoou1uP4hVqU1unRYLTA4ep+k1WHy4MGlxUNRitOX2wATpy/9NqCAFWIHBFhSsRHqJEaE4FhCdHsNUJERP2SzxMgEydOxJEjR7Bu3TrccsstXbrwRx99hCVLliA/Px/ffvttjwsNJjwBQkRERMHG4XLjbHUjztc2o7LRgAajBQarAw6Xu1duofkpuVQCdWgIojUqJOo0yIjTIScpGjq1qg9ejYiIqOd8BiARERFwOp2wWq1dvrDX60VYWBgUCgVaWlp6VGSwYQBCRERE/UmD0YKzVQ0oq9ejutmEJrMNZruzx1No2iMACFMqMDU3FddPyOFJESIiCho+AxCN5lJTrO/H3XaVWq2GRCKB0WjsXnVBigEIERERDQRuUURZrR7FtU2oaGhBrcEMg8UOm9Pdo2k031PIpLh2TCYWjhvGIISIiALOZw+Q9PR0nDp1Crt37+7yWNtdu3bBarVi5MiRPSqQiIiIiPqGTCJBVmIUshKj2qyZbA4UVTWirL4ZF5uMaDBaYbI54HR3vteI0+3BxsNnse1ECRaOG4Z5ozMZhBARUcD4DEBuvPFGFBYWYunSpdiwYQMmTpzYqYt+9913WL58OQRBwI033tgrhRIRERGR/2hCQzAhMwkTMpMue1wURdToTSiqbkR5gwE1ehOazTZYHU54xPZPjThcHmw4dAZfHivG4vwczBk11B9vgYiI6DI+b4Exm80YOXIkysvLIQgCZs6ciQULFvgcg7tlyxbs3r0boigiPT0dBQUFCAsL89sb8gfeAkNERETUlsPlxtHSamw4dAYGq73DfaoQOW6cNBzThqf5rzgiIhr0fAYgAFBeXo7FixejsLAQgiBc8YLfX27kyJH4/PPPkZqa2juVBhEGIERERES+fVtciQ+/LoTJ5uxwj1qpwM1XjcA1OSl+rIyIiAarKwYgAODxePD2229j7dq1OHDgAESx/Y7hEokEkydPxvLly7F8+XJIpdJeLzgYMAAhIiIi6pwDZ8rxyaHTMNs7DkK0oSFYMjkPEzKT/VgZERENNp0KQH7MZrPhzJkzqK6ubp0Oo9FokJiYiNzcXISGhvZJocGEAQgRERFR1+wpLMNn352B1eHqcE9EmBJ3TBmFMekJfqyMiIgGiy4HIMQAhIiIiKi7dpw4j88PF8Hucne4J1IdirumjUJeSrwfKyMiooGOAUg3MAAhIiIi6j5RFLH1eAk2Hz0Hh4+xujFaFe6aNga5yTF+rI6IiAYqBiDdwACEiIiIqOdEUcSmI2ex9XgJXJ72e8wBQFx4GJbPGIvMhCg/VkdERANNnwUgzz77LADgqquuwrx58/riJQKGAQgRERFR7xFFEZ99W4SdJ8/7DEISdBr8fMZYpMfp/FgdERENFH0WgEgkktaxuVOnTsVzzz2Ha665pi9eJlZpdQAAIABJREFUyu8YgBARERH1PrcoYsPBU9hTWAa32PFH1OQoLX4+YxxSYsL9WB0REfV3fRqAXPZCgoAFCxZg06ZNffFyfsUAhIiIiKjvuN0iPvz6JPYXlcPjIwhJjQnHPbPGI0Gn8WN1RETUX/VZAFJeXg4AqKqqwu7du7Fz504cPHgQVqu1L17OrxiAEBEREfU9p9uND746iW/OVUL08ZE1I06Hu2eOQ1yE2o/VERFRf+PXJqhOpxMKhcJfL9dnGIAQERER+Y/D5cZ7+07gUEkVfH10zUqIwt0zxyFaq/JjdURE1F9Irryl9/gr/HC73Xj++eeRlZWFkJAQJCcn45FHHrlsj9frxXPPPYchQ4YgNDQU06ZNw/Hjx/1SHxERERF1Xohchntmj8dLd89H/tBE/KvNXBvFNU34z/e348WNB9Bisfm3SCIiCnqyQBfQF37+859j165dePrpp5GTk4PKykqcPn36sj3PP/88Vq5cidWrVyMnJwcvvvgi5syZg8LCQsTHxweociIiIiLqiEqhwIq5E2C2O7F2zzGcuFCL9s6DFFU14rF3tyFvSCxWzJ0ApWJAfuQlIqIu6vItMA6HA2fOnEF1dTVMJhMAQKPRIDExEbm5uQgJCemTQjtry5YtWLx4MU6cOIHhw4e3u8dutyMuLg6PPvoonnrqKQCAxWJBWloaHnjgAfzpT3/y+Rq8BYaIiIgo8IxWO97ecwyFFfUd7lHKZfj9DVORFKn1Y2VERBSMOhWAeL1evP3221i7di32798PUWx/PrtEIsGUKVOwfPlyLF++vHUMrj/deuutMBgM2Lp1a4d7du3ahdmzZ+PMmTPIyclpffyee+7BiRMncOTIEZ+vwQCEiIiIKHi0WGx4a9dRFFU1trsuEQTcP2c8xg9N8nNlREQUTK7YA6SyshJjx47Ffffdh71798Lj8cDr9bb7l8fjwd69e3Hvvfdi3LhxuHjxoj/ew2UOHTqEYcOG4de//jW0Wi1UKhVuvPFGVFdXt+4pKiqCVCpFVlbWZc/Nzc1FUVGRv0smIiIioh6ICAvFbxZPxqo75yIrIarNuuj14rXth/Hpt6fbeTYREQ0WPm+INJvNmDZtWutI2xkzZmDBggXIy8tDUlISVKpLHbatViuqqqpQWFiILVu2YPfu3Thx4gSmT5+OEydOQK3230iy2tpavP322xg9ejTWrVsHk8mExx57DDfccAMOHjwIQRCg1+uhVqshlUove65Op4PVam13Ws2aNWuwZs0aAEBDQ4Pf3g8RERERdU6URoXfXT8FNXoT/vLZV7A6XJetf3m0GBUNBjy0YBIkEr/OAiAioiDg8xaYZ555Bs8++ywSExPx8ccf46qrrurURQ8dOoSbbroJNTU1ePrpp1v7bPiDQqGAQqFAeXk5oqIu/QZg3759mD59Onbs2IHZs2fjz3/+M1avXo2WlpbLnvvGG2/g/vvvh8Ph8DmxhrfAEBEREQU3h8uNVRv2oVpvarMWo1XhiRunQ6X0z4RCIiIKDj6j7w0bNkAQBLzzzjudDj8AYNKkSXjnnXfg9XrxySef9LjIrtDpdBg5cmRr+AEAU6ZMgUKhaJ0Eo9PpYDab4fF4LnuuXq+HSqXy27heIiIiIuobIXIZnlkyC/lDE9usNRit+P1721DVZAhAZUREFCg+A5CysjKoVCrMnj27yxeePXs2VCoVysrKul1cd+Tm5qK9Qy1er7f1qGNOTg48Hg9KSkou21NUVHRZU1QiIiIi6t9WzJ2AGyfltnnc4fJg5cd78V1JVQCqIiKiQPAZgEil0janJDrL6/VCFEW/31+5aNEinDx5Eo2NP3QB37dvH1wuF0aPHg0AuOaaa6DVavHRRx+17rFardi4cSMWLFjg13qJiIiIqG/NHzsM/3Hd1ZBKLp9QKHq9eH3HYWw4yOaoRESDgc90YtiwYXA4HN26jeWTTz6B3W7HsGHDul1cd6xYsQJRUVFYvHgxNm7ciPfffx9Lly7FnDlzMGXKFACAUqnE448/jueeew5/+9vfsHPnTtxyyy0QRREPPfSQX+slIiIior43IiUWz942G2Eh8jZrW44X46+bvoYoigGojIiI/MVnAHLbbbfB6/Xivvvuu+y0xJV8/PHHuP/++yEIAm6//fYeF9kVWq0Wu3btgk6nw2233YZf/epXmD17NtavX3/ZvscffxxPPPEEVq1ahUWLFsFoNGL79u2Ii4vza71ERERE5B8x2jD8Zek8JEVq26ydvtiAJz7YCavdGYDKiIjIH3xOgXG5XJg0aRKOHz8OQRCQkZGB+fPn+xyDu3XrVpw/fx5erxfjxo3DwYMHIZP5nLbb73AKDBEREVH/9vqOw+32/wiRS/HYz6ZiSFR4AKoiIqK+5DMAAYCWlhbccccd2LJly6UnCIKv7a0NSBcsWID33nsPERERvVRq8GAAQkRERNT/bTtRgo+/OdXmcUEQcO+ssZiYNSQAVRERUV+5YofSiIgIbN68GTt27MDSpUsRFxcHr9fb7l9xcXFYunQpduzYgS+++GJAhh9ERERENDDMG52JRxa1bY7q9Xrxxs6j+PibwgBVRkREfeGKJ0Da09zcjOrqaphMJgCARqNBYmIiIiMje73AYMQTIEREREQDR6PRiuc27IW5nf4fOUnReHjh1X6fbEhERL2vWwHIYMcAhIiIiGhgcbrdeP7Tr3CxydhmLVIdij/ePANqpSIAlRERUW9hlE1EREREg55CJsNTt8zEpKzkNmvNZhse/+c2VDQYAlAZERH1li6fACkuLsapU6favQVmxIgRyMrK6pNCgwlPgBARERENXDtOnMf6dvp/CAJw98xxuGoYm6MSEfVHnZpPazabsXr1arz77rsoLy/3uTc1NRXLli3Db3/7W6jV6l4pkoiIiIjIX+aMHoqkKC3+Z/M3cIs//K7Q6wXe2nUUlY0G3HJNXgArJCKi7rjiCZBjx45h0aJFqK2tRWcPiwiCgISEBGzatAljxozplUKDCU+AEBEREQ18TSYr/vxJ+81RsxOj8cgiNkclIupPfAYg9fX1GDFiBJqamhAaGoolS5ZgwYIFyMvLQ1JSElQqFQDAarWiqqoKhYWF2LJlC9atWwebzYaYmBgUFhYiJibGb2/IHxiAEBEREQ0ObreI5z/bh4rGtv0/dOpQPMnmqERE/YbPAOTRRx/FSy+9hNzcXGzatAnp6emduuiFCxewcOFCFBUV4Te/+Q1Wr17dawUHAwYgRERERIPLP3YdxTfnKts8rpBJ8bvrJyM1RheAqoiIqCt8ntnbtGkTBEHAu+++2+nwAwDS0tKwdu1aeL1ebNy4scdFEhEREREF0t2zxmHJ5LZ9P5xuD57bsA/fnK0IQFVERNQVPk+AqFQqyOVyGAzdG/kVHh4Ot9sNi8XS7QKDEU+AEBEREQ1OZ6sb8P9tOgi3KLZZmz0yA0smjwxAVURE1Bk+T4CEhobCbrfD7XZ3+cIulwt2ux1KpbLbxRERERERBZPsxBj8+Y7Z7fb92HmyFKv/b3+74QgREQWezwBkxIgRcLvdeOONN7p84TfffBMulwt5eRwRRkREREQDh06twv+761qkxoS3WSuuacIT722HyeYIQGVEROSLzwBk+fLl8Hq9ePjhh7F69WrYbLYrXtBut+OFF17Aww8/DEEQsHz58l4rloiIiIgoGMhkEjxx0wxckz2kzZreYscf3tuOC/X6AFRGREQd8dkDBADmz5+Pbdu2QRAEqNVqTJs2zecY3K+++gomkwlerxfz58/H5s2b/fJG/Ik9QIiIiIjoe7sLS/HB/pNtHhcEYPn0sbgmJyUAVRER0U9dMQBxOp14+OGH8frrr8Pj8UAQBJ8X9Hq9kEqlWLFiBV566SUoFANvLjoDECIiIiL6seLqJrz0xddwe9r2/5iZl47bp4wKQFVERPRjVwxAvldcXIx//vOf2L59O06dOgWTyXTZukajwYgRIzB37lzceeedGDZsWJ8UHAwYgBARERHRT7VYbFj58d52+3+kRIfjd9dPQYhcFoDKiIgI6EIA8lNms7k1BNFoNFCr1b1aWDBjAEJERERE7XG7Rfy/z7/ChfqWNmshcikeWTQZGXG6AFRGRETdDkAGMwYgREREROTL2j3HsL+oot21xeOzsXhCjp8rIiIin1NgiIiIiIio65bNGItl00e32z9v45GzWPXpPjjd7gBURkQ0eDEAISIiIiLqA1Ny0/DsklnQKNsOBSir0+N3a7eivIGjcomI/KXPApCmpiZIJBLIZGz0RERERESDU1yEGn9Zdi3yhsS2WbM53Xjuk33YcuxcACojIhp8+vwECFuMEBEREdFgJpNI8O8Lr8btU0bip3fEeAFsOHQGq/9vP9zutiN0iYio9/AWGCIiIiIiP5iZl4GnbpmJsBB5m7Ximib89t0tqGoyBKAyIqLBgQEIEREREZGfJEVqsXrpfGQnRbdZszpcePajPdhRcD4AlRERDXw+x+BmZGR0+8KiKKKiogKCIMDj8XT7OsGIY3CJiIiIqKe2nSjBJ9+cQnsfxnOTY/DQdVdBJuHvK4mIeovPAEQikUAQhB718WAAQkRERETUvooGA/574wHYnK42a2qlAr+7fgoSdJoAVEZENPD4DECUSiVcLhfuuuuuLp8GsVqtWL16NQMQIiIiIiIfnG43/rrpG5TUNrdZEwTg9smjMCMvPQCVERENLD4DkPHjx+P48eN45ZVX8Itf/KJLF25qakJMTAwDECIiIiKiTth05Cw+/66o3bWRKXH41fyJkPCWGCKibvP5E3T8+PHwer04evSov+ohIiIiIhqUFo3Pxh9umAalXNZm7WRFHR57dxsajJYAVEZENDD4DEDGjRsHAAxAiIiIiIj8ID1Oh9XLrkVabESbNaPNgSc/2IkDZ8oDUBkRUf/XNl7+kUmTJiElJQUWiwVerxeCIHT6wiqVCk8//XSPCyQiIiIiGkxC5DL8543T8dm3Z7D56LnL1kSvF+/sPY6Cijo8MDeft8QQEXWBzx4g1D72ACEiIiIifyipacJfv/gGTnfbnnoRYUr8/mdTEaVRBaAyIqL+h5ExEREREVGQykyIwgvL5mNIlLbNWovFjife34FviysDUBkRUf/DAISIiIiIKIgpFTI8ectMzB09tM2a6PXijZ1H8fqOwxBFMQDVERH1HwxAiIiIiIj6gVuuzsMji66BXNr2I/x3JVX4z/d3oMViC0BlRET9AwMQIiIiIqJ+Ijc5BquXXotEnabNWrPZhj+8tx1HSqsDUBkRUfBjAEJERERE1I+olAo8s2QWZo5Ib7PmEb14bdt3eHv30QBURkQU3BiAEBERERH1Q7dPHYV/v24SZO3cEvP12Uo88f52mGyOAFRGRBScGIAQEREREfVTeSnx+Mtd8xAbHtZmrcFoxe/f3YaC8toAVEZEFHwYgBARERER9WOa0BD86fY5mJKT0mbNLYp45ctDeG/fiQBURkQUXBiAEBERERENAMtmjMUvrp0AqURos7b39AU88f52FFc3BaAyIqLgIHi9Xm9nN+/btw8AMGrUKERERPRZUcEuPz8fhw8fDnQZRERERERtGKx2PP/pV2gyWdtdj9KosOSaPIxJT/BzZUREgdWlAEQikUAqlaK+vh46na4v6wpqDECIiIiIKJiJooi3dx/DweKLHe7Rhobg+ok5mJqb5r/CiChoOVxutFjsMFgv/WW0OWCyOWFzunD7lFGBLq9XdCkA0el0kEqlaGxs7Muagh4DECIiIiLqD74ruYi3dh2FR+z4I3+oQo5rx2Ri/phMSCS8Q56ov3GLIsw2B/TmH4ILs90Jk80Bi8MFq8MJm9MNu9MFh8sDh9sDt8cDl0eERxQhil5cKRT43/sWQybr/z8fZF3ZnJmZiYKCAjgcDoSEhPRVTURERERE1AsmZCZjVGo8PjxwEt+cq2w3CLE5Xfjs2zPYfPQcpg9Pww0Thw+ILzpE/VVBeS1OXKiB2e6CzemCzemGw+WGw+2By+2B2yPCLYrwiF504TxDjxhsdkRpVH55rb7UpQDktttuw5EjR7B+/XosXbq0r2oiIiIiIqJeEiKXYdmMsbhj2mj837dnsLuwDE63p80+p9uD7QXnsauwFBOzknH75FFQKrr0dYGIeuBURT3e3nMMBqs90KW00WKxDYgApEu3wLjdbkyfPh2FhYX44IMPcN111/VlbUGLt8AQERERUX8liiK2nSjBluMlsDpcHe4TBGB0ajzumjYaWpXSjxUSDS5VzUa8vv0wqvWmQJcCAJAIAiQSATKJBDKpBAqZFL+4dgJSY/p/H9AuBSDPPvssbDYb/va3v8FisWDEiBGYPHkyYmNjIZVKO3zeU0891SvFBgsGIEREREQ0EBw4U47PvjsDg9Xhc192YjSWTh+N2HC1nyojGviMVjve2HkERVW902NTEC6FF1KJBHKpBHKZFAqpFCFyKZQKOVQKGUJDFFAr5VArQ6AJVSBcpYQ2NAQ6dSg0SsWA7wPU5SkwgiBcdp+RILSdM/5THk/bI3b9GQMQIiIiIhpIjpfV4KNvCtFgbH907vdSY8Jx17TRA+I3wUSB4naLeHffcRwsrkRH38blUglitGFQKmRQKmQIUyigCpFDHaqAWqmANlSJcFUIIsKUiAhTQiHj7Wqd0aUAZMaMGZ0KPH5q9+7dXX5OT7z99tu4++672zz+6quv4sEHHwQAeL1erFq1Cq+++ioaGxsxYcIEvPzyyxgzZswVr88AhIiIiIgGopKaJrz/VQEuNht97ouPUOP2KSORmxzrp8qI+j9RFLHpyFlsOVYCtyi2u0ciCJgxIh03XzMCsgF+GiMQuhQT7dmzp4/K6Bu7du1CaGho6//PyMho/fvnn38eK1euxOrVq5GTk4MXX3wRc+bMQWFhIeLj4wNRLhERERFRQGUmROGpW2eiqtmIf+47gfO1ze3uq20x46VN30CnDsXNVw3HhMxkP1dK1L98c7YCHx4ohNXZcd+dMWnx+PmssVApFH6sbHDp0gmQ/uL7EyAmkwlqddv7FO12O+Li4vDoo4+29iexWCxIS0vDAw88gD/96U8+r88TIEREREQ0GOjNVqzdewKnK+vh60uDWqnA4vxszMzL8LGLaPA5V92It3YdRbPZ1uGetNgIrJgzAdHa/j9lJdgNyhuFvv76axiNRtx6662tj4WFhWHx4sX48ssvrxiAEBERERENBjq1Cv+x8GpY7U6891UBjpRWQ2zn96dmuxMf7D+JTw+dwZxRGVg0PnvAN1Mk8qXeYMaa7YdR0WjocE+MVoV7Zo3D0PgoP1Y2uHU7ACkoKMDWrVtRXl4Om82GN998s3XN5XKhoaEBgiAgISGhVwrtjqFDh6KpqQlDhw7Fb37zGzzwwAMAgKKiIkilUmRlZV22Pzc3Fx9++GEgSiUiIiIiCloqpQL3z83HcrcbH319CgfOVsDtadvDwO5yY9ORc9h6vARTclNx01XD2ZyRBhWr3Yk3dx3FyYq6DveEhchx+5SRmJg1xI+VEdCNAMRgMOCee+7BZ599BuBSM1FBENoEIKNHj4Zer8eJEycwYsSI3qu4ExISErBy5UpMnDgRHo8H69atw4MPPgir1YpHHnkEer0earW6zehenU4Hq9UKp9MJxU/uu1qzZg3WrFkDAGhoaPDbeyEiIiIiChYKmQx3ThuNJVNG4osjZ7GzoBR2l7vNPpdHxO7CMuw9dQH5Q5Nwx5SRUCnZ14AGLrcoYt3+Auw/U9HuKSng0mSXheOzcd24YX6ujr7XpR4gLpcL06dPx6FDh6BSqTBz5kzs2LEDDoejzajbxx57DC+88AKefvppPP30071eeFctWbIEO3bsQENDA1atWoXVq1ejpaXlsj1vvPEG7r//fjgcjjYByI+xBwgRERER0aWpFrtPleGLI+dgtjs73CcIwIghsVg2fQwiwkI73EfUH209XozPvyuCq51TUcClP/+Ts1Nwx5TRkMl4a1ggdekEyJtvvomDBw9i6NCh2Lt3LxITE5GQkID6+vo2e2+66Sa88MIL2LdvX68V2xM333wz1q9fjwsXLkCn08FsNsPj8Vx2CkSv10OlUvkMP4iIiIiI6BKJRILZI4di9sihOHiuEp8eOg29xd5mn9cLFFbU47F3tyFUIUeoQga1UgFtaAh0aiWiNGGICw9DYqQWMeFhHP9J/cKR0mq8t++Ez/Bv+JAY3Dc7H2qegAoKXQpAPvjgAwiCgJdeegmJiYk+944dOxYSiQRFRUU9KrC3CILQ+r85OTnweDwoKSlBdnZ2656ioiLk5OQEqkQiIiIion7rqmFDcNWwIThVUY91BwpQZ7C0u8/mdMHmdPmciiEIgEwiQYhchrAQOdShIQhXhSBKrUK0VoX4CDWSIrXQqpR99XaIOlRWp8ebO4+g3tj+n3EAGBKlxX1z8pGg0/ixMrqSLgUgJ0+ehCAImDdv3hX3KhQKhIeHo6mpqdvF9aaPP/4Y0dHRSE1NRUJCArRaLT766CP88Y9/BABYrVZs3LgRK1asCHClRERERET914iUWKxMmYOyOj3e++qEzykYHfF6L/URcXmcMNudHYYpACCVCJBLpVAqZAgLUUCrCkFEmBLRahViwsOQoFMjQadhM1bqsSaTFW/sOIzzdfoO9+jClPj5zHHITY7xY2XUWV36KWC1WqHRaDp9i4jL5YIsAD9obrrpJkycOBGjRo2Cx+PBhx9+iA8//BAvv/wyJBIJlEolHn/8caxcuRI6nQ45OTl48cUXIYoiHnroIb/XS0REREQ00KTH6fDHm2egrsWMd/cdx7nqvvnFqEf0wiO6YXe50WKxo6q5/X0CAJlUAoVMCk1oCEalxuHaMVnQhIb0SV00cNidbry9+yiOltV0uEepkOHWq0dgSm6a/wqjLutSOhEdHY2amhqYzWao1Wqfe8vKymA2m5GZmdmjArsjOzsbb731FiorK+H1ejF8+HCsXbsWS5cubd3z+OOPQxRFrFq1Ck1NTcjPz8f27dsRFxfn93qJiIiIiAaquAg1fvtvU2B3unGqsg51BguaTBY0m+0wWu2wOFywOd1wut3wiJ2ez9BlXnx/qkSExeFCbYsZ206cR7hKiTFp8Zg/NgtRGlWfvT71P6Io4pODp7GrsLTDP5tSiYB5YzJxfX4OJOxdE/S6NAXmpptuwmeffYb3338fS5YsAYDWJqg/nQLzm9/8Bn/9619x9913XzYidyDgFBgiIiIior5htjtR02xCrcGEBoMVTWYrWix2mGwOWB0u2F1uuD1ih6NGe0KtVCAvJQ4Lxmaxd8Mgt7uwFBsOnYbD5Wl3XQAwITMZy2aM5u1V/UiXApAvvvgCixcvRmZmJvbs2XPZFJgfByCvvfYafvnLXwIAvv76a0yaNKn3Kw8gBiBERERERIEliiIaTVZUN5tQb7Sg0WhFs9kKg9UBs90Ju9MFh9sDdwejSa8kVCFHblI0rh2ThfQ4XS9XT8GqsKIW7+w5DoPV0eGeYYlRuH9OPsLZhLff6VJUtXDhQtx000345JNPkJ+fjzvuuAM226XuzWvWrEF5eTk2bdqEwsJCeL1e3H///QMu/CAiIiIiosCTSCSIDVcjNtz3rfnApR4ONXoTaltMqG0xo7CiDhebTfD1u2Cb04WjZTU4WlYDhUyKYQlRmDt6KHKTY3vzbVCQqGgw4M1dR1CjN3W4J0Gnxr2z8pESE+7Hyqg3dekECADY7Xbcf//9eO+991pHy/7Y95e755578Pe//z0gTVD7Gk+AEBERERH1b6Io4lDxRew5fQEVDS2d7j8ik0qQHqvDrJEZGJsWz74P/VyD0YI3dh5BmY/JLtrQECybMQajUuP9WBn1hS4HIN/bv38/3njjDXz99deorq6Gx+NBfHw8Jk+ejBUrVmDatGm9XWvQYABCRERERDRwiKKIgvI67DxZitK6Zrg6eduMVCJgSHQ4puWm4qrsFMgYhvQbJpsDb+46gtOVDR3uUcikuGFSLmaPHOrHyqgvdTsAGcwYgBARERERDVxnLjZgR8F5nKtp7LAJ5k8JApCk0+Ka7BRMG5HKxphByuFyY+2e4zhcWoWOvglLBAEz89Jxy9UjeMJngGEA0g0MQIiIiIiIBocL9XpsPV6CM1UNsDpcnX5eXLgaE7OSMHtUBlQKRR9WSJ3hFkWsP1CIfacvdDhBSAAwfmgilk0fC6WCAdZA1OMApLy8HPX19QCA2NhYpKam9kphwYwBSPeZzVaoVEomqURERETU79ToTdhyvBiF5XUw2Z2dfl6URoXxGQmYNzoTWk4O8StRFLHpyFlsPV7i89am4ckxuGfWOP77GeC6FYBUV1dj1apV+PDDD9HU1HTZWmRkJG677Tb8/ve/R3Jycq8VGkwYgLTPaLLi2MliFJ65gOLzlbhQWYea2iY0NRthMlvhcLrg9QJSqQS/+/Wt+MMjdwa6ZCIiIiKibtGbrdhyrATHLtSgxWLv9PPCVSEYk5aAa8dkIVqr6sMKaXdhKT49dAZ2l7vDPemxEbh39vhOTROi/q/LAci2bduwZMkSGI3GDsdGCYIAjUaDdevWYf78+b1SaDAZjAGI3e7EyTNlOHm6FGeLK1FWUYOqmiY0NhlgNFlgtzs7PErWkTF5Q/HFuuegVvMHPxERERH1X2a7E9uOl+Dw+So0mqydfp5aqcDMEelYOH4YT0j3ou9KqvDB/gKYfZzSSdBpcM+ssUiN0fmxMgq0LgUgZ8+exdixY2G32xEZGYkHH3wQs2bNQlJSEgCgqqoKu3fvxmuvvYbGxkYolUocO3YM2dnZffYGAmGgBSButxtF5ypx4vR5FBVXovRCDS5WN6ChsQUGowU2mwMesXOdsLtKFRqCdW8+ienXjO6T6xMRERER+ZPd6cauwlIcPFeJuhYzOvNlSyaRYGJWEm6dnMd+IT3GuInkAAAgAElEQVRw5mID1u45hiazrcM9kepQLJ8xBrnJsX6sjIJFlwKQu+66C++//z5GjRqF7du3IyYmpt19jY2NmDNnDk6ePIk77rgD7777bq8VHAz6UwAiiiIuVNbh+MnzOHPuAs6XVaPiYj3qGvRoMZhhtTrg9nSus3VfevDni/GXZ1YEugwiIiIiol7jdov4qugC9p8pR1Wz6YonpgUAuckxuHPaaMRow/xT5ABQ0WDAW7uOoFpv6nCPWqnA7VNGYkLmwGzTQJ3TpQAkISEB9fX1OHToEPLz833u/e677zBp0iTExcWhpqamx4UGk/4UgHy2eT+W//Ivfns9iURAqDIE4dowxERFICkxGhmpCcjJGoKRIzLw3dGz+P1/rYGnnQZEWUOTseWj5xEdGe63eomIiIiI/EEURRwqvoi9py+gvKEFHtH317DkKC1umzwSwxKj/VRh/9NgtOCNnUdQVqfvcI9SLsMNk3IxMy/Dj5VRsOpSABIaGgqFQgGDwdCp/VqtFi6XCzZbx0eQ+qP+FICUltdg7PTeOVkhCAKUIXJoNWGIjgpHYnwU0lPiMSxzCEYOT8eo4RlQdaJrcml5DRbc8jhq65vbrIUo5PjHK49h4byreqVmIiIiIqJgI4oiDp67iM8PF6HZx+0aAKALU+JnE3NxdXaKn6oLfiabA2/uOoLTlQ0d7pFLJbh2TCYWjc9mfxVq1aUAJCMjA/X19TCbzZ3ar1arERsbi9LS0m4XGIz6UwAiiiJ0Gdd3am9IiByaMBWiIrVIiI9E2pB4ZGUkY0RuGsaOzEREL3ZGFkUR9zy0Gp9+sb/d9SU3zMTf//th/rAiIiIiogGtuLoJ6w4UoLLJ6HNfqEKGWSMzsHB8NmSD9DOy3enG2r3HcOR8dYe9VSSCgGnD03Dr5LxB+8+JOtalAOTXv/41Xn31VWzfvh2zZs3yuXfnzp2YO3cufv3rX+Pll1/ucaHBpD8FIAAQn3sz3G4P1GFKREZoEBcbiZTkWGRmJGNETirGjsxEQlxUQGr75PN9eODRl+BqZzRVcmI0tn2yGkkJPPZHRERERANbg9GC978qwOmL9fD1DU0qETAhMxm3XZMHlXJwNEx1iyLWHyjEvtMXOuyjIgAYPzQRy6aPhVIh82+B1G90KQCpq6vDmDFjoFQqsXXrVgwbNqzdfcXFxbj22mvhcDhw7NgxxMYOrA67/S0ACXZ19XrMu/l3uFBR12ZNJpPilb/8O26/yXfgRkREREQ0EFidTnx04BQOFV+E28ckRgFAdlI07pw6GnERvXdSO5iIoohNR85i6/ESuNrpIfi94UNicM/McdB24nZ8Gty6FIDs27cPpaWleOSRR2C323HLLbe0Owb3o48+glKpxEsvvYT09PR2rzVt2rTeeQcBwACkb/zHH17B2x9sbXfturmT8N5r/8lbYoiIiIhoUBBFEZuPFWNHwXlYHS6fe5MitbhtSh6yE9uf0tkf7S4sxaeHzsDezknx76XH6XDf7PGcmEOd1qUARCKRQBCEnr+oIMDt7vgPcrBjANJ3tu85jLseWAW7w9lmLSY6HF9++DyyhnJ0FRERERENHt8WV+LTb4vQZLL63BcRpsS/5WdjSm6afwrrA9+VVOGD/QUw29t+H/hegk6De2aNRWqMzo+V0UDQ5QCkt4g+jnMFOwYgfavFYMaCWx/H6bPlbdYkEglWPXkfHrx7cQAqIyIiIiIKnPO1Tfhg/0lUNPqeyqmUyzAzLx2LJ+T0m0agZy7W4509x31OxYlSh2LZjDHITR5YLRbIf7oUgNAlDED848lV/8DLr21od23q1SOx4Z1noFAMjsZPRERERETfazRa8f7+EzhVeeWGqflDk7Bk8kiog6BhqtPtRnm9AWUNelQ1GVFvMENvscNsd8Lp9nT4PI1SgdumjMKEzCQ/VksDEQOQbmAA4j9ff3sKN//8GVis9jZr4dowfP7+nzAmLzMAlRERERERBZbd6cZH3xTi4LlKn01CBQDDEqNxx9RRSNBp+rSmBqMF52ubUdloQI3ehCazFUarAzanu8MJLh1RymW4YVIuZuZl9FG1NNgwAOkGBiD+ZbXasfiOJ3D4+Lk2a4Ig4A8P347f/8ftAaiMiIiIiCjwRFHE1uMl2HaiBJYrNExN1Glw6zV5GD6ke7eROFxulNbpcaFej6pmE+qNZrRY7LDYnT5DmK6QSyW4dkwmFo3P5hAE6lUMQLqBAUhg/Pff1mPlC/9Ee39kx4zMxBcf/BlqtSoAlRERERERBYfvSqrw6aHTaLxCw9RwVQgW5+dg2vC0yx4XRRF1BgtKa5tR0WRAbYsZzSYrTDYn7K6un+LoCqlEwNTcNNw6Oa/f9C6h/oUBSDcwAAmcwtNlWHj7f6LFYG6zplIpsf6tpzD1qpEBqIyIiIiIKHiU1enxwf4CXGho8blPKZchNjwMBqsdVoer105xdEQAoJBJEaZUQKcORWx4GIZEhiMtNgIZcTqe+KA+xQCkGxiABJbT6cSt967E7q+Ot7v+y3uvx6on7/NzVV3XYjCjtq4JmRlJkMlkgS6HiIiIiAYgvdmK978qQEFFfbsnqfuCVCIgVCFHuEqJaI0KiZEapMREIDM+8v9n776jo67y/48/pyWTSZv0Dgk1dBCQIkUBFRDrrthWWHRFsa4/6+qqa1lZl5XddXXtLvbeVmyACEjvvbeQRnqfzExmJr8/UL6yQkjCpPJ6nJOTMHM/9/MO5zAkr7n3fQm3WZulBpHjUQDSCApAWoeX3/iS+x59Ce9xUuruXVL45qO/EGkPa4HKfsnpdPPNwtV8+90a1m3aQ0ZWHs4fzzY3Go3079OZO268jEsmjmjhSkVERESkPXLVePh45XaW7cw45VUeBgMEms2E/LiKI94eTHJUOGmxESRHh2v7irRaCkAaQQFI67E/I5fxv76PvIKSXzwXGGBhzr/vY+K4Ic1ak8/nY/HyzXw1byWr1u1kf0YOFXWcZ/5zgQEWRg7rw/2/v5rBA7o3caUiIiIicrrx+XzM37yPbzfupfLHN+SOx2wyYguwEG4LJCYsmITIUDpG2+kcH0loUGAzViziPwpAGkEBSOvi8/n47S1P8fnXy4/7/DWXj+XZp25vsv2EG7fu5fOvlrF89TZ2782ipKyizvPY6ys8LJgLzh3C/b+/mo4pcac+oYiIiIjIz6zbn8OyHRnU+HzEh4eQEh1O57gIEiJC1YtD2iUFII2gAKR1+uCz75lx9z/xeLy/eK5DcizffPgUSQnRp3SPg5mH+eSLH1iyYjPbd2VQUFiGz9e0jaIAEuOjuPKyc7jr5st10o2IiIiIiEgjKABpBAUgrVduXhHn/epeDmXl/+I5s9nEc7Pu4MpLz6nXXIXFZfz36+UsWLyeLdv3k3u4iJrjhCv1ZTAYiI4MI71bB0YO7cMlF4wg0h7KX595j0/mLqWwuKwecxzpbzJ96iSmXT1eybyIiIiIiEg9+TUA2bJlCwsWLMBoNHL++eeTnp7ur6lbFQUgrZvP5+O2+/7FWx8uOO7zk84fxpvP339MeOBwOPl6wWq+WbiG9Zv3kJVdgNN14j2R9REeFkyXtCSGn9mTi8YPZ9CA7nUGFjt3Z/Dk399h/uL1OBzOk85vNpkYfEZ3/t+MX3PemMGnVKuIiIiIiEh716AAZOHChTzxxBMMHTqUJ5988pjnZs+ezb333nv0aCWj0cjs2bO57bbb/FtxK6AApG345rvVTLn5L7hcNb94LjbazqTzh7Jmw24OZORSWVW/JqUnEmyzktohnjPP6M7EcUMYM2rAKR1t+93i9fztuQ9YvX7ncbf0/C9bUCBjRp3Bg3deTc/01EbfV0REREREpL1qUAAyY8YMXnrpJZ5//nmmT59+9PHdu3fTq1cvvF4vgYGBmEwmHA4HRqORNWvWMGDAgCYpvqUoAGk7ikvLmTD5D+zcfchvcwYGWkhOjGFAny6cP2YQE8cNabK+HD6fjzfem8cLc75g557Mep3dHhkRxiUTh3P/HVcTFxvRJHWJiIiIiIi0NQ0KQPr168fWrVs5ePAgKSkpRx+/9957+dvf/sbo0aOZO3cuAQEBXHPNNXz00Udcf/31vPzyy01SfEtRANL2PPjEqzz7ymcNvs5sNhEfG0mfnmmMGTmASy8YQUy0vQkqPLnKSgf/fOkT3vnoO7JyCut1TYfkWKZMPpfbpl+G1RrQxBWKiIiIiIi0Xg0KQBISEigqKsLlcmEwGI4+3rdvX7Zt28aCBQs455wjDSb37dtH165d6dq1K7t27fJ/5S1IAUjbtHTVFiZPe4yqE/TXMBoNREeG06N7R0YO68tlF5xF57SkZq6yfrJzC5n593f44tsVlJZVnnS8wWCgd480brn+Yq649Gw1TxURERERkdNOgwKQwMBAQkNDKSz8v3efKyoqsNvtBAcHU1paeswvVjabDYPBQFVVlX+rbmEKQNouh8PJ5OsfY/X6nQRZA+nWOZlhg3tx8cThDOjTpU0GAxs272XmP95m8bLN9WrcarGYGX5mL+69/QpGDOnTDBWKiIiIiIi0vAYFIOHh4TgcDtxu99EVIN9++y0TJkxg7NixzJ8//5jxUVFROJ1OBSAizeS/Xy/nny9+zIbNe/H6fCcdHxoSxPljBvPAnVe32tUuIiIiIiIi/tCgt7u7dOmCz+dj8eLFRx/75JNPMBgMjBgx4pixbrebsrIy4uLi/FOpiJzURROG891nT5O/+2OefOh3dElLrHN8RWU1H/13CWeccxO9hl/Hm+/Pa6ZKRUREREREmleDApALLriA2tparr/+et5//33+8Y9/MGfOHAAuu+yyY8Zu2LABn89Hhw4d/FasiNSP2WzmlusvZt33L5Kx6V1u/d0lJz0RJiungFvv+xeJPS/nnodfwHGCXikiIiIiIiJtUYO2wJSWltKvXz8yMzOPboGpra3liiuu4N133z1m7AMPPMBTTz3FH/7wB5544gn/Vt3CtAVG2qr9Gbk8OfttvvluNRWV1XWONRqNjD6rL7P+dCNdOyc3U4UiIiIiIiJNo0EBCEB2djaPPPIIK1aswG63M2nSJO655x7MZvPRMW63mw4dOpCfn8/8+fMZO3as3wtvSQpApD1YumoLs/71PstWbaOmxlPn2C5piTxy71QumjC8maoTERERERHxrwYHIKIARNoXj8fD31/4hOdf+5yi4vI6x9rDQ7j+NxO5/44rCAgIaKYKRURERERETp0CkEZQACLt1fxFa3noyf+wY/ehOseZzSbGjz2Tv/5pOkkJ0c1UnYiIiIiISOMpAGkEBSDS3mVk5nHvn15k/qJ1eL11H6fbu0caTzx4HeeM6N9M1YmIiIiIiDRcowOQFStWsHnzZoqLi6mpqalz7MMPP9yo4lorBSByunA63fz5728z551vKK9w1Dk2NtrOrTdcym03XILR2KADpkRERERERJpcgwOQBQsWMH36dDIyMup9jdfrbXBhrZkCEDkdffj5Yv48+y0OZByuc1xggIVLJ41g5sO/I9Ie1kzViYiIiIiI1K1BAcjq1asZNWoUbrcbgLS0NBITE485AeZ4vv/++1OrspVRACKns+07D3Lvoy+xbOVWfHW8fBgMBgYP6M5fHrmBgf26NWOFIiIiIiIiv9SgAOTCCy/kyy+/JD09nQ8++IDevXs3ZW2tlgIQESivcPDwzNd475PvqXa66xybnBjDvbddwdSrzm+m6kRERERERI7VoAAkOjqakpISVq9ezcCBA5uyrlZNAYjI//H5fLz61tfM/veH5BwuqnNssM3KNb8ey6P3/xabzdpMFYqIiIiIiDQwALHZbJhMJioqKpqyplZPAYjI8a1cu50/PP4K6zftqXOc0Whg1PC+/O3Rm+jaObmZqhMRERERkdNZg45q6NixIz5f3Udiisjpa+ignnz/+Wz2rn2TX180igDL8fsD+Xy1LFq6iUFjZzDwnBv579fLm7lSERERERE53TQoAPnVr36F0+lkyZIlTVWP32VnZxMSEoLBYKCysvLo47W1tTz55JOkpKQQFBTEqFGj2LhxYwtWKtJ+xETbefWZe8jd8SF/vPtaoiJPfBrM3gM5XDtjJh36Xsljs9482mRZRERERETEnxq0BaayspIBAwZgtVpZtGgRUVFRTVmbX1x99dUsXLiQvLw8KioqCAkJAWDmzJk89thjzJo1i/T0dGbPns3q1avZunUr8fHxdc6pLTAiDTdv4Roe/sscduw+VOc4i9nExRPPYtZjN+oYXRERERER8ZsTBiAnWuWRk5PDLbfcgsViYfr06QwZMoTQ0NA6bzJq1KhTr7QRlixZwiWXXMIDDzzAPffcczQAcTqdxMXFcdddd/Hwww8DUFVVRWpqKjfeeCNPPPFEnfMqABFpvIzMPO7904vMX7QOr/fEW+oMBgNnDenN7Cdm0L1LSjNWKCIiIiIi7dEJAxCj0YjBYDj1GxgMeDyeU56nobxeL2eccQbTpk3Dbrczbdq0owHIwoULGTt2LDt27CA9Pf3oNddddx2bNm1i3bp1dc6tAETk1Dmdbv7897eZ8843lFc46hyb3jWFvzx8A+eMHNBM1YmIiIiISHtTZw+Q2traU/5oqaapL7zwAi6Xi1tuueUXz+3cuROTyUTXrl2PebxHjx7s3LmzuUoUOa1ZrQE8/odpZG55n1f+eTepHeJOOHbnnkwuufZhup85ldfe/roZqxQRERERkfbihAGIz+fz20dzKyoq4qGHHmL27NlYLJZfPF9SUkJISAgmk+mYxyMiInA4HMdtwvjSSy8xaNAgBg0aREFBQZPVLnI6uvzi0Wxa8goLP3+agf26nXDc4fxi7nzw3yT1msxDM/+jhqkiIiIiIlJvDToFpq148MEHGTp0KBMnTvTbnNOnT2ft2rWsXbuWmJgYv80rIv9nYL9uLPz8abav+A8Txp2JyXT8l6jKqmqeefETEnpO5re3PkVhcVkzVyoiIiIiIm1NgwKQQ4cOkZ2dXe/xOTk5HDpU94kP/rZt2zZee+01Hn74YUpLSyktLcXhONJfoKysjOrqaiIiIqisrMTr9R5zbUlJCTabjYCAgGatWUSOlZQQzXuvPETWlve54dqJWK3H/zfp8Xj5dO5Sugy8lvGT72Pn7oxmrlRERERERNqKBgUgqampnHnmmfUef9ZZZ9GpU6cGF3Uq9uzZQ01NDcOGDSMiIoKIiIijfUCSk5O57bbbSE9Px+v1snfv3mOu3blz5zFNUUWkZdlsVv72+Axyt3/I4w9OIyri+Mfi1tbWsmL1doacdyuDx85g/iI1KRYRERERkWM1eAvMCQ6N8dv4UzVixAi+//77Yz7uu+8+AL766ivuuecehg8fTlhYGB9++OHR6xwOB1988QUTJkxo1npF5OSMRiO333AZ+ze8zVsvPkCnjgknHLt7Xxa//u2jdB10LS+9PrfFGjGLiIiIiEjrcsJjcI/HaDQSHx9PTk5OvcYnJCRQXFyMy+VqdIH+MGfOnGOOwQWYOXMmjz/+OLNmzSI9PZ3Zs2ezatUqtm3bRlzciU+jAB2DK9IabNy6l7sfeoE1G3bVOS7YZmXa1eN55N5rtb1NREREROQ01mRNUHNycigoKCAqKqqpbnFK7r//fh588EFmzpzJpEmTKC8vZ/78+ScNP0SkdejfuwsLPv0bO1fNYdL5w07YMLXK4eTZVz4joedkpt78FwoKS5u5UhERERERaQ3qXAGyZMkSFi1adPTPf/rTnwgJCeHuu+8+4YS1tbWUlpby1VdfsXfvXi666CI+/fRTvxbd0rQCRKT1cTrdPDTzP7z5/jyqnSc+HtdggKGDejL78Rn0TE9tvgJFRERERKRF1RmAPProozz66KMYDAbgSLjx09cnU1tbi9VqZdGiRQ1qnNoWKAARab18Ph/P/+cL/v7vDykoqvt43C6dkvjzg9cxfmz7eo0SEREREZFfqjMAef3115kzZ87RPy9evJiAgACGDRt2wgmNRiNhYWH07t2bqVOn0qVLF78W3BooABFpG75asIo//vk19h2ou29RTHQ4d918OTf+9kKMxibbGSgiIiIiIi2oSZugtlcKQETals3b93P3Q8+zev1O6nrFswUFMvWq8/nTvVOxWtUwVURERESkPWlQAPL6668TFBTE5MmTm7KmVk8BiEjblJdfwj2PvMDceSvxek98PK7JZOSi8cOZ/ecZRNrDmrFCERERERFpKg0KQOQIBSAibZvT6ebRWW8w551vcFSf+Jhug8HAOSP688xfbiMlKaYZKxQREREREX9TANIICkBE2gefz8dLr3/J0899QP5JjscdPKA7z8y8VSfHiIiIiIi0UY0KQFwuFx9//DFLly4lKyuLqqoqTjSNwWDgu+++O+VCWxMFICLtz7yFa3jgz6+xZ19WneN6dOvA7CduZviZvZqpMhERERER8YcGByDLly/niiuuICcn55hjcX+a5ufH5P70vNfr9WPJLU8BiEj7tXn7fu74w7Os37SnznEdU+KY+dDvuOC8oc1UmYiIiIiInIoGBSCZmZn07duXsrIy+vbty/jx4/nrX/9KSEgIv//97zl8+DALFy5k//79REdHc9NNN2EymXjkkUea8ntodgpARNq/g5mHuf3+Z1myfPMJV7gBxEbb+eNdv2HqVec3Y3UiIiIiItJQDQpA7rzzTv75z38yYcIE5s6di8FgOO7RuM8//zy33347EydO5PPPP2+SwluSAhCR00dBYSn/74//5sv5q+o8OSY8LJg7bryMO2f8GqPR2IwVioiIiIhIfTTop/R58+ZhMBh49NFHj9nq8r9mzJjBo48+yty5c3n55ZdPuUgRkZYSE23nzRce4NCmd7l28rkEWMzHHVdWXsVjs94ksddkHnziVdxudzNXKiIiIiIidWnQCpDQ0FCcTicul+voO5xGo5HIyEgKCwuPGVtWVkZUVBRDhgxh2bJl/q26hWkFiMjpy+Px8OisN3nljS/rPELXYjEz+ZLR/PWR6YSE2JqxQhEREREROZ4GBSAhISHYbDby8/OPPhYaGorL5cLlcv1iVUhUVBQARUVFfiq3dVAAIiI+n49nXvqUvz//EaVllSccZzIaGT/uTP755C3ERNubsUIREREREfm5Bm2BSUpKoqKi4pjHkpOT8Xq97Nix45jHHQ4HpaWlOByOU69SRKSVMRqN/P6mX5Gx6V2e++sdxMVGHHec1+fjy3kr6Tp4CpOueoD9GbnNXKmIiIiIiEADA5BOnTrhdrvZt2/f0ceGDBkCwAsvvHDM2NmzZ1NbW0tqauqpVyki0or9ZvI4dq9+g3df+SOpHeKPO6a2tpYfVmxhwOjpjL7wTjZu3dvMVYqIiIiInN4aFICcffbZ1NbWMn/+/KOP/e53v6O2tpbnnnuOiRMn8uCDDzJp0iQeeeQRDAYDV111ld+LFhFpjSaOG8KmJS/z7UdP0Ss99YTjNm7Zy+hJdzJo7Ay+X7qx+QoUERERETmNNagHyMGDB5k2bRoDBgxg9uzZRx+/7777mDVr1pEJDQZ+mnLUqFHMmzePgIAAP5fdstQDRETqY+fuDG7/w7OsWrezznHJidE8dv80fnXRqGaqTERERETk9NOgAKQuCxYs4L333iMzM5Pw8HDGjx/PlClTMJuPf2RkW6YAREQaIju3kNvv/xcLl2zAV8dLblRkGPffcRXTp05qxupERERERE4PfgtATicKQESkMYpLy7n7oRf4/KvleLzeE44LDQnilusv5r47rjp65LiIiIiIiJwaBSCNoABERE6F0+nmgSde5a0P5uNy15xwnNlsolvnZM4fM4hpV0+gY0pcM1YpIiIiItK+NDoA8fl8rFu3joyMDBwOB1OmTPF3ba2WAhAR8QePx8Nf/vEez//nv1RWVZ90fLDNSu8eqVw0/iymXHkeYaG2ZqhSRERERKR9aFQA8q9//YsnnniCwsLCo495f7acu6SkhJEjR+LxeFi8eDFxce3rXUsFICLiTz6fjxfnfMFf//UBxSXl9b4u0h7KwP7dmHzJaC6bNLJd9lwSEREREfGXBgcgt9xyCy+88AK1tbWEhYVRWVlJbW3tMQEIwJQpU3j77bf55z//ya233urXoluaAhARaSoffPY9jzz1Ojm5RQ26zmAwkBAfyVln9ubaK85l5NA+6h8iIiIiIvIzDQpAvvnmGyZOnEhoaChvvPEGF198MQkJCeTn5/8iAPlp7EUXXcRnn33m98JbkgIQEWlq2bmFzHn3G75esIbdezPr7BVyPCaTkbSOCYwbdQbX/WYC3bukNFGlIiIiIiJtQ4MCkEsuuYQvvviC2bNnc8cddwCcMAApKysjIiKCtLQ09u3b59+qW5gCEBFpbpu372fOO9/y/Q8byMjMw+vzNeh6a2AA6d06MHHcmVx3zQRiou1NVKmIiIiISOvUoADkp7CjtLSU0NDQYx773wAEwG63U1NTQ1VVlf8qbgUUgIhIS/L5fHz/w0be/HA+K1Zv53B+cYPnCAu10b9PFy69YARXXnoONpu1CSoVEREREWk9GhSABAYGEhwcTHHx//2wXVcAEhkZSXV1NdXVJz/doC1RACIirYnb7ebD/y7ho8+XsH7zHkrLKhs8R2y0naGDenDVr8cyfsxg9Q8RERERkXanQQFITEwMJSUlVFdXY7FYgBMHIMXFxcTExJCYmEhmZqZ/q25hCkBEpDUrLi3njffm88U3y9m2K4PqaleDrjcaDaQkxTJ6eD+unTyOlORYqp1unNUuql1uqp0uXM4anC43Tqcbd40Hl8uN01WDy12D2+XG5fbgqqmhpsaD2+3B7a7BXePBXVNDTY2XmpoaPB4vNR4vNR4PnpojX3s8XjxeL16vD+/PvrZYTAwd1JP77riKTh0TmuhvTkRERETaswYFIGPGjGHx4sUsXryYESNGACcOQNAKOtcAACAASURBVJ577jluu+02Lr74Yj799FP/Vt3CFICISFuyPyOX1976ivmL1rH3QA4ezy9X7LUlUZFhXHDuUO69/UpSkmJauhwRERERaSMaFID8+9//5tZbb2XMmDHMmzcPo9F43ABk06ZNnH322ZSXl/Puu+8yefLkJim+pSgAEZG2bOXa7bzx/jyWLN9MVk4hDTwNvVWJjbZz8YTh3HPblcTFRrR0OSIiIiLSijUoAKmpqWHAgAHs2LGDs88+mzvvvJPrrruOoqIidu7cycGDB/niiy949dVXqa6uZtiwYSxduhSDwdCU30OzUwAiIu2Fx+Nh7ryVvP/pIlav20lhcVlLl9RoifFRXDZpJHfe/GuiI8NbuhwRERERaWUaFIAAZGRkMH78eHbt2nXCYKO2tpY+ffrw7bffEh8f75dCWxMFICLSXlVWOnj3k+/59MulbN62j4rK/2tibTAYMBh++mzAaDBgMB75bDQaMRqPfDYZjZhMxiNfm376MGE2GTGbTT9+bcJsNmGxmDCbzUc+m0xYLGYCLOYjnwN++trC9l0ZrF63A3eNp17fR0pSDJdfPJo7Z1xOWKitqf66RERERKQNaXAAAuBwOHj66ad57bXXyMjIOOa5pKQkbrjhBu666y6Cg4P9VmhrogBERKT5+Xw+5n67kude/Yy1G3fXu5dJaod4rrpsDLf+7mJCQtpmGOLz+Vi5dgfzvl/Dhi17CQuxceO0CxkxpE9LlyYiIiLSZjQqAPm5nJwccnJy8Hq9xMfH07FjR3/V1mopABERaVk+n48PPl/Mi3O+YNPWfXi9vpNeYzBA59RErrl8HDdfdzFWa0AzVNpwDoeTeYvW8v0PG1m/eQ8ZmXmUlVcdd2x4WDCXXjCCP971G2Ki7c1cqYiIiEjbcsoByOlIAYiISOvh8/l48/35vPLWV2zdcQCf7+T/rRkMBrp3TeG3V57H9b+ZQEBAy4Qh2bmFfDV/FUtXbmHLjgPk5BZS7XQ3aq4uaYncfP3FTLt6PEaj0c+VioiIiLR9CkAaQQGIiEjr5PF4eO3tb/jPO9+wY/ehep1wYzQa6Nk9let/M4EpV5yL2Wz2e10+n4/N2/fzzYI1rFy3nV17MskvLG2SI4ktZhMjhvXhobuvZWC/bn6fX0RERKStalAAUlpaymeffcbixYvZt28fxcXFAERFRdG5c2fOPvtsLrnkEsLCwpqs4NZAAYiISOvndLp58fW5vPnBfPbuz6I+/9uZTEb69OzE9KkXcNVlYxq1ksLtdrNo6SbmL17Puo27OZCRS0lZpV+OGw4LtZGYEE1mVj5VDudJx0dGhDH54tH84c6rsYeHnPL9RURERNqyegcgTz31FH/5y18oLy8/+thPl/78NJjw8HAeeOAB7r77bj+X2nooABERaVscDifPvfIZ73y8kP0ZufW6xmw2MaBPF2ZMu4hLJ404bhhSWFzGNwvWsHj5JjZv20dmdkG9gomTMRqNREWE0jktkcEDunPuOYM468xex6xO+WrBKmb96302btlbr20/6d06cPv0Sxsd7IiIiIi0dfUKQK699lreeeedo4GHyWSiU6dOREZGAlBcXMz+/fvxeo8s5TUYDEyZMoX//Oc/TVh6y1EAIiLSdpVXOHjmxU94/7PvOZSVX69rLBYzgwd0Z/TwfqzfvJsduw9xOL8Yt7t+x/LWJcBiJi42gvSuHRh+Zi8mjjuT9G71byjudLr5+/Mf8vp788jNKz7p+MAAC+eM7M8j90yhZ3rqKVQuIiIi0racNAB58cUXmTFjBgADBgzggQceYPz48b844raqqoqvv/6amTNnsmHDBgwGAy+++CK/+93vmq76FqIARESkfSguLWf2cx/y8dwfyMktavL7BdusJCfG0LdXJ0YP78uEc4cQHRnut/n37MvisVlvMG/ROpz1aKYaG23nql+N5d7bJrfZI4JFRERE6qvOAKSmpobExESKi4u58sormTNnDhaLpc4Ja2pqmDp1Ku+99x4xMTFkZ2c3SUO5lqQARESk/cnLL+Fvz33A518vIy+/5JTmMhgM2MNDSOsYz6B+3Rg7+gzGjOzfrKfNfDJ3KbP//SFbdxw4af8Rg8FAn55p3Dnjci6bNKKZKhQRERFpXnUGIB9//DGXX345nTp1YuvWrVit1npN6nQ66dWrFwcPHuSjjz7i0ksv9VvBrYECEBGR9i07t5BZ/3qPud+upKCorM6xZrOJmKhwunVJYdigHowfO4R+vTu1mj4blZUOnvrX+7z38ULyC0tPOt5qDeD8cwbxyL1T6JyW1AwVioiIiDSPOgOQW2+9leeff56nn36a3//+9w2aePbs2dx9993cfPPNPPvss6dcaGuiAERE5PSxPyOXWc+8x4LF63FUu4iLsdO7RxojhvZhwrghpCTFtHSJ9bZ1+wEe+9sbfL90Y736lyTGRzHlinO5c8blWK3Nt3qlLpWVDvYfOszBjMNk5hRQUlLBkEHpjB11RqsJnURERKR1qjMAOeuss1i5ciWbN2+mV69eDZp427Zt9OnTh2HDhrFs2bJTLrQ1UQAiIiJtmc/n491PFvLMS5+yc/ehk443Gg0M6NOV+++4kvPGDPZbHYXFZew/kENGVj6Z2fnk5hVTUFhKQVEZpWUVlFc4qKysptrlxu2uwev1nXAuk8lI105JXHDeMG6cOom42Ai/1SkiIiLtQ50BSEpKCrm5udTU1Bxz1G191NbWYrFYSEhIIDMz85QLbU0UgIiISHtRWlbJn2e/zUf/XUJxSflJxwfbrEw8dwiP3Dv16OoXn89Hdm4RBzMPk3Eoj+zcAg7nF5NXUEpxSTklZZWUV1ThcLhwOt24azz4fCcOM/zBHh7CkIHpXHvFeVxw7hCtDhEREZG6A5Dw8HCMRiMlJY1rBhcZGYnX66WsrO79022NAhAREWmP1m3azeN/e5MfVmzB4/GedHxAgBlPjRffSZqstjST0UhaagITzx3CTb+9kKSE6JYuSURERFpAnQGIyWQiLi6OnJycRk2ekJBAQUEBHs/J9xm3JQpARESkPfP5fLz61te88J//svdA434GaEoGgwGL2URgoAWDwUB5haNB14eF2hg8oDvX/Hocl04aodUhIiIip4k6AxCj0Uh8fPwpBSD5+fl4vSd/F6ktUQAiIiKni4LCUp54+i0+/XIpZeVVfp/faDRgsZixBgYQbLMSGmLDHh5MVGQ4sdF24mMjSE6MITkplrSO8SQnRGM2m4+Zo7C4jFff/Ir/frOcnXsy67V65ef3T+sQz3ljBnPTtAtJTYn397coIiIirYQCkEZQACIiIqejpau28OTsd1i5dvtxG5KaTEYCLGas1kCCbVbCw4Kxh4cQHRlGXEwE8XGRJCXGkJoSR1qHBGKiw5tk9cX3Szcy551vWLZq60mPMf5fIcFBDOzfjasuG8PlF4/6RdgiIiIibddJA5CGNj/9udraWgwGgwIQERGRdsTj8bBg8XqcLjcdk+NJ6xiPPTykpcs6rtKySl596ys+/2o5O3Zn4K6p/7Zcg8FAx5RYzh09kBt/eyFdOyc3YaUiIiLS1E4agJzyDRSAiIiISCuxfPU2Xn3rK35YsYW8goY1ebfZrAzo04WrLjuHKy49m4CAgCaqUkRERJpCnQHIo48+6pebPPLII36Zpz4++ugjZs+eza5du6iqqqJjx45ce+213HvvvUd/UKmtrWXmzJk8//zzFBYWMnjwYJ555hn69+9fr3soABEREWn7KisdvPbuN3w6dynbdhzE5a6p97UGg4HkxGjGjT6D6VMm0TM9tekKFREREb+oMwBpi1588UUyMzMZOHAgdrud1atX86c//Ynrr7+eZ599FoCZM2fy2GOPMWvWLNLT05k9ezarV69m69atxMefvPmZAhAREZH2Z82GXbzy5pcsWraJw3nFDbo2yBpAREQoYSE2IuyhREaEERsdTkJcFEkJMXTsEEdqSjxJCVE6dUZERKSFtLsA5HgefPBBnnvuOUpKSnC5XMTFxXHXXXfx8MMPA1BVVUVqaio33ngjTzzxxEnnUwAiIiLSvjkcTt54fz4ff7GEzdv343S6/Ta30WDAbDFhDQzAFmQlJCQIe1gwUZFhxETZiYuNJDkxmpSkGFJT4umYEqvtNiIiIn5wWrQ2j4qKwu0+8oPL8uXLKS8vZ/LkyUefDw4O5sILL+Trr7+uVwAiIiIi7ZvNZuWmaRdy07QLAdi8fT8vzZnLwh82kJ1beEpz+2prcbs9uN0eyisckH/yawwGMJtMBAYGEBQUQGiwjbCwYCLtocRE24mLjSAxLpK0jgkMP7M3YaG2U6pRRESkPWq3AYjX68XlcrF+/XqeeeYZZsyYgcFgYOfOnZhMJrp27XrM+B49evD++++3ULUiIiLSmvXt2Yln/3o7AE6nm3c+/o4PPlvEpq37cFS7mvz+tbVQ4/FS46mmsqqagsK6j/c1m02EhwaTmBBNt85J9OvdhRFDezOgTxdtwRERkdNWuw1AgoODcbmO/EAyZcoUZs2aBUBJSQkhISGYTKZjxkdEROBwOHC73cddZvrSSy/x0ksvAVBQUNDE1YuIiEhrZbUGcN01E7jumgkA7NydwVcLVpN7uIi8ghIKi8spLaukrLyKKocTp9OFu8aD1+trtho9Hi9FJeUUlZSzZft+Pv7ih2Pqj44Mo0NyHL26d2Rg/+6cPaIfCXFRzVafiIhIS2i3Acjy5ctxOBysXr2axx57jFtvvZV///vfjZ5v+vTpTJ8+HTjSA0REREQEIL1bR9K7dazX2NKySg5kHCYj6zCHsvPJPVxMfkEJBUVllJRWUF5RRUVlNdVON253DR6P1+/1Op1usnIKycopZPnqbbz85lcAGI0GQoKDiI+NpHNaIv16dWLooJ4MG9wLq1U9SEREpO1rtwHIGWecAcCIESOIjo5m6tSp3HXXXURERFBZWYnX6z1mFUhJSQk2m01NxkRERKTJ2MNDGNC3CwP6dqn3NQ6Hk0NZeew/dJis7AKycgrJKyimsKiMopJyysuPhCaOahfVTlejV5r4fLWUVzgor3Cwe18WXy9YffS5AIsZe3gIyUkxpHdJ4Yx+3Rg5tDfduqQ0yZYat9tNXkEZuYcLySssJb+ghMKiMgqLyykpraCsvIryiioqq6qprHJS7XThdLpx13io+XG1zf/2+TcYDBgMP30+8mE0GDAYDRiNRowGA0ajAZPJiNFoxGQ0YjL99GHC/NNn888+fvyzxWLG8uPnAIv56GMBFgvWQAsjh/Vl0vlDtf1IRKSFnRanwGzdupU+ffowf/58jEYjY8eOZefOnXTv3v3omOuvv56NGzeybt26k86nU2BERESktSosLmPJ8i2s2bCTbTsPcvDQYQqKynA4nE1yv2CblZjocFI7xNM7PY3BZ3QntUM8BYWl5OWXUlhcRmFRKSWllZSUVR5Z5VLhoNLhxFHtxOmsweVyU+Px4PH48Pmab6tQcwoMsDBiaG/uv+MqzhzYo6XLERE5LZ0WAciLL77ITTfdxN69e0lKSiIuLo577rmHP/7xjwA4HA5SU1OZPn26jsEVERGRdsnn87Fz9yGWrNjChi172LU3k+ycQkrKKqmp8bR0eaeVsFAbE88dwgN3XkPHlLiWLkdE5LTR7rbAjB8/nnHjxtGrVy9MJhPLli3j6aef5oorrqBz584A3H///Tz++ONERESQnp7O7Nmz8fl83HbbbS1cvYiIiEjTMBqN9ExPpWd66i+eczicrFiznRVrtrNlx372HcwlL7+YyqpqfL52/15ZsyuvcPDeJ9/z3iffkxAXyZWXncP/u3myji8WEWli7W4FyEMPPcSnn37KwYMHMZvNdOrUiWnTpnHTTTdhsVgAqK2t5cknn+T555+nqKiIQYMG8cwzzzBgwIB63UMrQEREROR0kZldwJIVm1i3cQ/bdx/kUGY+RcXlOF3uJr+30WjEbDZiMZsJDAzAarVgC7ISYrMSGmojLDSYiPAQIuwhREfZiY4MJy7WTkJsFHGxEQQGBlBd7cLpcuN0uY/2Cql2unG53LjdHpwuFy5XDU5XDS5XDS73kQa07hoPbrfnZ1/XHO0xUuPx/vjZQ02NF4/nyGNejw+P14vH48Xj9eL1eikrd1BSWnHS79VggG6dU7hhygVMu/p8zOZ29z6liEiLa3cBSHNQACIiIiKnO4/Hw4Yt+1i2aisbt+5lz75scg4XUV5ehdfnw2QyHm0KarUGEGQNJCTYSmiIjdAQG/bwEOzhIURHhhEdFU5sTARx0XYS4qOJiwlvV43pd+7OYOY/3mX+onVU1aMXi8lkZPCA7tw549eMH3tmM1QoInJ6UADSCApARERERKQxvv9hA7Oe/YBV63bU65jjoKBAzhnRnz/ceTV9e3ZqhgpFRNovBSCNoABERERERE6Fz+fjzffn88KcL9ix+9Avju09nkh7KBdPHM4ffn8NcbERzVCliEj7ogCkERSAiIiIiIi/OBxO/v7CR7zz0Xdk5RTW65oOybH85vJx3HHjr7Ba2892IRGRpqQApBEUgIiIiIhIU8jOLWTm39/hi29XUFpWedLxBoOBXump3Hz9RVx12RiMRmMzVCki0jYpAGkEBSAiIiIi0tQ2bN7LzH+8zeLlm3E6T37qjsViZtjgntx7+5WMHNqnGSoUEWlbFIA0ggIQEREREWlOX3y7gn++8DHrN+/B6/WddHxIcBDnjxnEg//vGjqnJTVDhSIirZ8CkEZQACIiIiIiLcHj8fDyG1/yyltfs3d/dr2uiY2286uLRnHTtAtJTYlv4gpFRFovBSCNoABERERERFpaaVklf3v2fT74fDF5+SX1usZoNGAPCyElKZbePVMZNqgn484eSEJcVBNXKyLS8hSANIICEBERERFpTfZn5PLk7Lf55rvVVFRWN/h6k8lIpD2Ujilx9OmZxllD+jB29AAi7WFNUK2ISMtQANIICkBEREREpLVaumoLs/71PstWbaOmxnNKc1nMJqIiw0nrGE+/Xp0ZMawP55zVj5AQm5+qFRFpPgpAGkEBiIiIiIi0dj6fjw8+X8xzr3zGrj2ZuNw1fps7IMBMTJSdTqkJDOjblbOH92PksN4EBAT47R4iIv6mAKQRFICIiIiISFvjcDhZtHwTS5ZvZuPWvRzIOExRcfkprxL5Oas1gNhoO107JXFG326cPbIfQwf2wGw2++0eIiKNpQCkERSAiIiIiEh7UVpWyXeL17Ns9TY2b9tHRmYexSUVeLxev93DFhRIQlwknVITsYeHEGyzEhIcRGiIjZDgIMLDbISHhRAaaiPCHkJEeCgR9lBCgq0YjUa/1SEipzcFII2gAERERERE2ru8/BIWLFnH8lXb2LrzIIey8ikrq8Tr8zV7LQaDAaPRgMloxGQ2YTYZsZjNWALMBFjMBAZYsFoDCAwIICgoENuPH8HBVoJtPwUtVsLDggkLDcYWFIjBaGj27+N/xcVE0K9XJ62QEWkmCkAaQQGIiIiIiJyuMjLz+G7Jelas2c72XQfJyimkrLwK/VrReNbAAKIiw+iQEkvPbqkM7N+Vs8/qT1JCdEuXJtKuKABphLYWgPz13RUEBZqJjwwhKTqUjnFhJESFaDmhiIiIiPjNrr2ZLFi8njXrd7JjdwY5h4uoqHSg3zYaz2g0EBIcRFxsJJ1TE+jbqxNDB/Zk2OCe2GzWli5PpM1RANIIbS0A6fqb54/7uMEAZpORQIuJoAAzIUEBhAYHYg+xEh0eRKzdRkJkCInRoSTHhNEhLpQALc8TERERkXry+Xxs3r6fhUs2sGbDLjKzC3C63LjdNbjcNdS4PdR4PHg8XrxeH16fD5/Ph8+nX1FOxmIxExEeQlJiNN27pDCwXzdGDOlNercOeqNT5AQUgDRCWwpAnG4Pfa572W/zGQCTyUiA2YQ10Eyw1UKYLRB7SCCRoVZiI4KJiwgmMTqElJgwOsSHE2LVcWgiIiIi0nAOh5OSskpKSiooraikrKyK0vJKKiqqqaiooryqmqoqJ5VV1VQ5nFRXO3E4XVRXu3G53LhcR4IWd00NNTVePJ4jH74W6GNyPG4/nsDzczabldjocDqmxNMrPZUhA9MZNbwvkfawJrmfSFuhAKQR2lIAsieriIn3f9DSZWAyGrCYj6w0ibYHMbh7IhcM7cKg7vFKqEVERETktOTz+di5+xBLV21l3abd7NqbSXZOISVllX49nvgnJpORsNBgEuOj6Nopib69OnHWkN4M6t9NjVjltKAApBHaUgCyO7OIG/72FQ6XB6fbQ43Hi7cVLSk0GiDabqNXagxjB3Rk4tCuhNq0YkRERERETm8Oh5NV63awfM02Nm/bz76DueTlF1NZVe33LUIGAyQlxDBu9BncOHUSPdNT/Tq/SGuhAKQR2lIAciIVDjeH8svIKignu6CSwyWVFJY6KKpwUlbhpLzaTVW1G6fbg9vjw+NtvmWCwVYLnRLsDO2ZxCUjutEtJarZ7t2UPB4fa/fksnxLFlsO5HMgt4zyKhdBgWbCgwOJDA8izh5MUnQoqfHhdEqMoEtyhLYQiYiIiMgxMrMLWLpyC2s27GL77oNkZuVTWFyO0+n2y/xB1gD69e7Mry8azbWTz8Wqn0f9wufzUVRczr6DORzKyiMrp5Dcw0XkF5ZSWFxOSWkF5RVVVFU58dXWkpQQTb9enThnZH/Gjx1CWKitpb+FNk8BSCO0hwCkMZxuD1kFFRzKKyOnqJK8kkrySxwUlldTWumkvMpFVbWbarcHV40Xj9fnl67fZpOBhMgQ+nWJ47xBnRg7sGOrbsbq8/nYvL+ApVsOsWlfAftzSigodVDtbtwyRgNgMRuxBlgItQUQEWolOtxGQmQwybFhdEqw0zkxgo5xYa16O5HT7SGvpIq84irySx0UlTsoLq+mtNJFaaWTCoebUFsAV5zTk+G9k1u6XBEREZE2x+PxsGnbfpau3MqGLXvYuz+HnNwjxxR7vN5Gz5uYEMU5I/ozfeok+vfu4seK2y6fz0dmdgEHMw+TmVVAVk4Bh/OLyC8so6i4jNKySsorHVRVOXG53LhrPKe8cicw0EJCXBQ9u3dkxNA+XHDeEFJT4v30HZ0eFIA0wukagDSGx+Mjt7iSzPxysgsrOHi4jLW7ctiTXUKFo/EJtT04kG4pkYzo24GLh3clMTrUj1XXj8/nY3dWCT9sPsSGvXnsyy4hr6SKKmdNs9fyE6PRQKDZhM1qObKqJOzIaT6J0aF0iA0jLdFOt6RIIsOC6j2nx+OjqMLB4eIqCsscFJY6KK5wHgkvqlyUVbmorHZT6XDjcHmodtfgcntxe7x4PD92c2/gq0ygxUT/LnFMOa8P4wamtupgR0RERKQtKC2rZNmqraxct4Ot2w9w8NBh8gtLqayqbtA81kALvXuk8euLRjH1yvPbzXG8P/VjWbluB1k5hRzOL6KgsIziknJKyyqpqKqmutqF0+mmxuOltfwabTIZiY4Kp2unZIYM7MH4MYMYNKC7fn4+AQUgjaAAxD8czhrmrz3A/HUH2LI/n7ySqkb3JwmwmEiJCWNQ93gmDunC0J6Jfv1HfyC3lCWbD7F+92H2ZBdzuKiKymo3bfkfj8VkxBpgJiTIQlCgBaf7SJ8YV42Xmh+Di9bQL8ZsMtIrNZorx/TkspF6MRcRERHxJ6fTzTsff8cHny9i05Z9OKpdDbo+PjaSUcP7Mn3qJAYP6N5EVfrX/oxcFixax8q129mx+xBZOQVUVFa3mlDjVBkMEB4WQmpKHGf068qYUWdw7uiB2sqEApBGUQDSdDbty+PLFXtZuT2bg3llVLsauW3EANFhQfRIjeGc/h2ZNKwL9pCTp9O5RZUs2ZTBml2H2Z1ZRE5RJRUOV4NXMJywLiAkKID4qGC6JkWS3iGK4vJqcooqKfhxZUWFw0WVs4Yaj9dv920vjEYD3ZIj+dWodK4e17NVb4USERERaYt27s7gxdfnsmDxejKzCxoUCgQGWOjRvSOXTRrJtKvHt3jPity8IuYtXMvKtdvZuvMgmdkFlJVX+r2JbEMZjQYsFjPWwACCbVZCQ2xE2EOIjAgjNtpOQlwUTpeL1et3sXd/NoXFZXj90JPRFhRIYkI0fXqmMWpYXy44dyhxsRF++I7aDgUgjaAApPkUl1fzxYo9LN54iB0ZhRSVVzd61YUt0ExavJ0zeyZy/uBOHMorZ+2uHHZkFJFdWEFplcuvL4bBVguxEcF0SYpgQJc4RvbtQLfkiAatYHB7PBzMLWNvdgkHDpeSVVBB3o9bUUqrXFQ6jjSqrWnGJrWnymQ0YDIasZiNBFpMWAPMWAPN2AItHMoro7yeW6MMBkiLt3PRWV2ZOr6vmsWKiIiI+Jnb7eaDz5bw3qcLWb9pD1UOZ4Ouj422M3JYH677zQRGDOnTRFVCcWk5CxatY9mqbWzZfoCMzDxKyir8EhqcjMlkxGIxE2QNJNhmJTwsGHt4CNGRYcTFRBAfF0lSYgypKXGkdUggJjq8USua92fk8tW8VSxdtYUduzPIzSvG5Tr1rfcWi5nYaDvpXVMYNqgnE8YNoXfPtFOet7VSANIICkBajs/nY9nWLL5atY/1uw+TVVCO29Oyv/xbA8zE2m10SoygX+cYRvTpQN9OMc2+VaO4vJq92SXsyynhUH45OYUV5JceaTRaVuXC4azB5fE2OuQxGsBkNGI2GwkwmwgMMBEUYMEWaCbEFkBIUADhwYHYf+w9EhlqJdpuIzrcRnxkMFGhNszmk/+d7M0u4eW5G1i0MYPiivr/J5scE8qEMzvzuwv6N6jHiYiIiIjUz74D2bwwZy7zvl9LRmZeg1aHWCxmenTrwEUTzuKGaydiDw9p8P0rKx0s/GEjP6zcwuZt+zhw6DBFxeV4PI1v8Pq/rNYjqzJCgoMIDwsmwh5KTFQ4sTERJMRH0iEplo7J3imunAAAIABJREFU8aR1jG/U9+BPpWWVfLNwDd//sIHN2/aTmZ1PRWXDerocj9FoICI8lM5piQzs343zzxnEyGF9MLeD1dcKQBpBAUjrkplfzufLdrF0SxZ7skoodzRs32J9BVpMRIfbSI0Pp2+nWIb1SmJw98R6/VLfmng8PjILytmTVczBvDKy8sspd7gID7ZiDzkSXkSF2Yi124ix24iLCMZmtbRIrTmFFbw0dwML1h0kr6Sq3tfFRtg4d2Aa0ycNaJEGuSIiIiLtncfj4ZO5P/D2R9+xbuPuBv/iHRUZxoghvZl2zQTOGdH/mOecTjc/rNzM4mWb2Lh1H/sO5lBYVIa7kacqHk9ggIWYaDud0xI5o28XRg/vx1lDehEQ0LZXFXs8Hn5YsYV5i9axdsMu9h3MoaS04pRXut9x46947A+/9U+RLUgBSCMoAGndnG4P89fuZ/66g2zel8/h4soGNfO0mI1EhgaRGh9Oz9RohvdKZmjPJKwBbT/xbMuKy6t55cuNfL16H1kFFfW+LjLUyqh+HbjxwjPoknR67XEUERERaS4ZmXm89Ppcvv5uNQcychv0C7fZbKJLWiKOahf5BaU4XY0/LfJ/WSxmoiLD6NQxgf59ujByWB/OHt6v3ZxeU19btx/g64VrWLF6K7v2ZpJXUEpNTf0Dpa8/+AvDz+zVhBU2DwUgjaAApO3ZdrCAL5bvYeX2HA7kluBweTCbDESEWEmJDaNnagxnpicyok8Koba2nfqeDiqdbt78dgufLdvNgdxS6vsqFmoLYHivZG6Y1J9+neOatkgRERGR05TP5+O/3yznzffns2bDLsrK67+St7HMJhOREaGkdoinT89OjBjahzEj+7f4NpXWLC+/hK8XrGLR8k1s3XGQ7JyCE54CVLL/83ZxGqMCkEZQACLSerg9Ht79bjsfL97Jrqzier/bYAs0Myg9kesn9GN47+QmrlJERETk9JWdW8jLb8zly3mr2Hcw55Sak5qMRuzhIaQkx9KnRxrDzuzJuFEDT7vTTJqK0+nmuyXrWbB4Hes37+XgocNYAwPYtfr1li7NLxSANIICEJHWyefz8dnS3by7cDtbDxTgqed/roEWE/27xHHteb05d2Bau0i3RURERFojn8/HNwvX8Pq737Jq3Q5KSiuPO85oMBAWFkxyYgy90lMZOqgHY0edQccUreKVxlMA0ggKQERaP5/Px4J1B3lj/hY27snDVVO/7uBmk5GuSRH0SI1mULcERvVLIS5CSydFREREmkJefgmvvPUlK9fuICoijCED0xk3eiBdO2uFrvifApBGUAAi0vas2JbFq19tYs3OXBwNPDPdZDQQHmIlJSaUHh2jODM9kZF9O2APOb2aZ4mIiIiItGUKQBpBAYhI27Zlfz4vzd3A8q1ZlDsa32XcbDISGXqkkW6vtBiGpCcyvE8yIVY10hURERERaW0UgDSCAhCR9mN/bgkvfrGBRRsPUVzesPPrTyTAbCQqLIiO8XZ6p8UwvFcSQ3omEmDWUcoiIiIiIi1FAUgjKAARaZ9yCit4Y94WNu3L51B+GSXlTmpOoUv5/wq0mIgOt9EpwU7fzrEM75XMGV3jMZvVdFVEREREpKkpAGkEBSAip4/yKidLNmexekc2Ow4VkZlfTmmlE289j9utj6BAM7H2YDol2hnQJY7hvZPpkxaj02hERERERPxIAUgjKAARkYJSB4s3ZbB212F2Hioip7CCsioXPj++pIYEBZAUE0qv1GhG9E7m7P6phNrUX0REREREpDEUgDRCWwtA1m7ZT1pKLFF2HeUp0tSyC8pZvOkQ63YfZldWMbmFFVRUu/HXK22gxURcRDDdUiIZ0iOJcwemkhQT5p/JRURERETaMQUgjdDWApAOo3+Pu8aLwWDAZg0g0h5MYmwEnVJi6NUlmYG9O9KnWzJmNWgUaTJ7s0v4YfMh1u85zN7sEg4XV1JZ3bDjeE/EZDQQFRZEWqKdgV3jOWdAKn07aQuNiIiIiMjPKQBphLYUgHg8HpJH3VmvsRazidBgK7FRYaQkRNItLYF+3VMY1CeNxNiIJq5U5PTj8/nYcaiIpZsz2bg3j705JeSXVOFweU55bgMQFhxISmwYfTvFMrJvCiP6pGANUNApIiIiIqcnBSCN0JYCkM07Mznvur+e8jwGAwQFBhARFkxCbDhpKbH07JzIgF4d6d+9A1ar+hKI+IvH42P9nsMs3nSIDXsPcyC3lOIKJz4/NF4NCjSTEBlCj45RDOuZxNiBaUSH2/xQtYiIiIhI66YApBHaUgDy1aJN3PDQa3j9eJTn8ZhNRkKDrURHhJKcEMn/Z+/Oo+Oq7/vhv2e7s++jXbL2xbYs23gBbIwJuwmJE0jIA6VZaAukp2nOE3qe5Jy2KQlpkobTNLR9cvpAmzRpE+DnkBBMDCbsm8E2xpZtWbZk7euMZt/u3Llz5/ljJMWODdjj0TZ6v06GkUZX936v/J0b3be+38+3ua4cHS3V2LSmAbVVnjk9NtFy0T8ewsuHBvBu9xh6RgLwBhOQ5Mwl71enUcPjMKGp0olNbRW47rI6tNS4C9BiIiIiIqLFgwFIHpZSADJDFCW8f2IQ73cNoqt3DP0jPoz7QghGEhBThSvQ+EGMeh0cNhPKSxxY1ViJT163Hts2trJGAdElCsVEvPL+IN46NoKuQR/GpmKIi5deW0StUsFh0aO2zI7LWspx8+ZG1hUhIiIioiWNAUgelmIA8lFGJwM40NmPzpPDODUwgeFxP3yBKKJxEekC/IX5fFQqwOO0or2lGtdvWY3bbtwIp808J8ciWk4kWca7XWN49cgQOk97MTgZRigmXnLQqVIBLqsRTdVOXLmqCrdc3oT6CkdhGk1ERERENMcYgOShGAOQDyNJMjpPDuH9E4M43jOG/mEvxrwhBMJxJEQJhexCJoOAhhWl2HJZMz5z4yZ0tNUUbN9Ey133kB8vvteH905N4PRoEL5wEvIlTo/TqFUodZrRtsKNre3VuOXyJpQ4WFOEiIiIiBYfBiB5WG4ByEfx+iM4cLQPR04M4dTgJIbG/PD6w4jEkpDSlzZ6RKNWo6LUjnUra7Hj6g58fPvaoii4OuEL4cDRfkxMhbBtYxvaGioWukm0TE0GY3jpvQG8c2IM3UN+jPtjEKVLW4VG0KpR4baivd6D7WtrccOmeliK4H1LREREREsbA5A8MAC5cLIso6t3HO8d78fxnlGc6p/AqcEJhCKJvPdptxjRWl+Bqze34vabN6G+qqSALS4MSZJx+MQQDnUNoOv0GAaGfRjzBREIx5EU0+eMmhF0GtRVl2DbhhbceeuVaG+pXqCWEwEJMY03jw7jjaNDONLrxZA3csl1RYx6LWpKbVjXWIprL6vD9o5aaLWsJ0JERERE84cBSB4YgFw6SZLx/Bud2PPaERw6PogxbzDvofiCToOaCjc2rWnAJ69dj2sub5uXQo3D437s7+zDsVMjubopEwH4/FFEEyLkS6ybotNqsKLSja2XteBzH78cG1bXFabRRHkSJRkvHxrAK4cH0dnnxagvitQljvCymgTUlTuwsaUcN21uwPqmMhZZJSIiIqI5wwAkDwxA5kZX7yieeuEg3jx4Er2DXsSTqbz2o1IBbocV7c1VuG7LKtx24ya4HZaL3k9ClHC4axCHugZwoncM/aM+jPvCCEXiEMU05vONo9GoUVPuwhXrmnDHjs24Yl0jbxRpwYViIvbuP43XO4dxfGAK3mAc6UuoKaJSAU6LAU1VTlyxqgo7Lm9CU5WzgC0mIiIiouWs6AKQXbt24X/+53/w3nvvIRwOo7W1FX/zN3+DO++886ztHnvsMfzgBz/A8PAwVq9ejR/84Ae47rrrLugYDEDmRyiawDMvHcILbx7D0VPD8PqjeRdcNRoENFSX4Mr1Tbj9po1Yv6oOiqJgYHRqdhRH7+AkhicCmApGEUukkLnE4pAfRavVQKtWQ5QufmqBWq1CVZkTl3c04vabNmH7Zi4pTIvDqC+CPe+exr7jozg57MdUJAlFyf//ZjRqFTx2E5qqnLAYBWg1Kui0Ggha9fSzBlqNGoJOA70u97mgm35oc6/pBQ30Oi0MggY6rQZGQQu9kPvcKGhh0GuhVav5HiIiIiIqckUXgFx55ZWor6/Hpz71KXg8HuzZswf//M//jH/913/FV77yFQDA448/jrvvvhsPPvggrrrqKvz0pz/Frl27cODAAbS3t3/kMRiALAxFUfDO4dN4+sVDePdILwZH/XmFB0AuQLiUm7ILoVKpYNTr4LSbUVnqQH1NKVY1VuKyVXXoaK2eLeY65g3i8WffwUv7juNk30ReI1/UKhXKS+zYuKYen75hI266qp03c7RodA/58dy7vXj3xBj6xkK5JXkXulEfQaUCVNMfqJB7j6lUKgg6NVaU2nH5qkrs3NqC1XWLrwYREREREZ1f0QUgU1NT8Hg8Z7121113Yd++fejv7wcAtLa2YuvWrfjJT34CIHdjvXbtWqxduxb/+7//+5HHYACyeIx5g3hq70G88k4XTpweRzASn9fj67Qa2CxGlLisWFHpRmtdOTraVmDTmnqUlzjy2qcvEMETv3sXv3/zGE70jSEaFy96HyoVUOa2Y8PqOuy8/jLcsr0DWq02r/YQFZqiKNh/chy/P9iP905OYHAyjFhSWuhm5UWjVqHMaUZHYylu2FCPGzc1wCDwvUZERES0GBVdAHI+Dz/8MP7u7/4OqVQKfX19aGxsxHPPPYebb755dptvf/vbeOSRR+D3+z9yfwxAFi9JkvH7t4/hd68exnvHBzA6GbqkgqRqlQomowCX3YLKMgcaa0qxqrkKG9vrsbqpcl5ChWAkjv+zZz/2vtGJ4z2jCMeSF70PFQCPy4r1q2px68fW45MfW1cUywlT8ZBkGa++P4SX3h9A52kvRnzRS16Od6HYTAKaql24qr0an9zagtoy+0I3iYiIiIiwTAKQ2267DT09PTh69Cj27NmDj3/84+jv70ddXd3sNrt27cIdd9wBr9eLkpIPH9LMAGRp6e4bx6/3HsDrB0+id3ASscTZU0wEnRZ2qxFlbhtqKz1oaajAurYabFzTkFfx1LkWiSXx1N4DeO61Thw9NYxgnksKux0WdLTV4NZr1uLTN26CiYEILTKRuIi9B/rxeucQhicjSCsKMpksMoqCTEZBRslOPxQoShaKkkUmm3tWsllks1koWSA7/XE2i9wDuY/ni06rRrXHistaKrBjcwO2ddRwihoRERHRAij6AOSll17CDTfcgJ/85Cf44he/iF/84he4++67EQwG4XD8YYrCiy++iBtuuAEnT55ES0vLOft59NFH8eijjwIAfD4fBgcH5+0cqLAisST2HzmNyjIn2hoqlvyNSEKU8JsXDuDZV4+gs3sY/lAsr/2oVCpoNWpotbmCkXq9Fka9ALNRD4vZAKvZAIfVBIfNBLfDArfTghKXDaVuGypK7Ch1WTnNhpYsSZaRkhSIkjz9SEOUMpDkDFJSBqIkI5XO4GifF/u6RtE/HkJczK8GkQqAy2bEylo3tq+txSe3NMNlMxb2hIiIiIjoHEUdgAwMDODyyy/Hli1b8Jvf/AYA8g5AzsQRILSYiaKEZ145jN0vH8LhE0PwBaLzeny1WgWtJrfahl7QwqDXwWTUw2wUYDUbYTMbYLeZ4LSZ4XFa4HJYUOa2o8xjQ2WZEw6raV7bS5SvSFzE7945jZffH0TXgA++cCLvkSVGQYvacjs2r6zEJ65sxrqmssI2tsAURUEoloLFpIPA4JOIiIiWiKINQAKBALZu3Qqr1YpXX30VJlPupmpmCszAwABqa2tnt+cUGCpWsixjz2ud+O2Lh/De8QFM+sPzOvw/Hxq1GjqdBga9DmajPjf6xGaC22FFqcuK8hI7qsqcqK5woaG6FB6nZcmP5KGlb6a46559vTh4chxD3ghS6fxqEKnVKpQ5TFjTUIrrN9Tjpk0NMBl0BWlnTJTgDcYxGYhjKpzAVDiJYFREMJZEOC4hEk8hlpQQF9NIpmQkJRlSWkZaViBnctONzryEqFW5gtAmgw42kx4uqwElDhMq3RZUl9rQWOlEc7UTJXYT36dERES0oIoyAEkkErj++usxOTmJffv2obS0dPZrM0VQn3/+edx0002zrz/00EP40Y9+xCKoVPRkWcbv3+7Cb35/EAeP9mPCF4ZSBJcBtVo1PepEB5NBgM1igN1qgtNuRqnLhjKPDVVlLlRXuFBb4UZVmYNTdmjOjftjeOatU3jj6DBODgcQil38qk4zrEYBTVVObGmvxspaNwIREf5IAsFYCqGoiEhCQjSRQkxMIymmkZRkpKan8cgZBRlFWfDwU6NWwSBoYTEKsFv0cNuMKHOaUeWxorbMjqYqJxornQULe4iIiIjOVHQBiCzL2LlzJ/bv34+3334bzc3N52zT2tqKbdu24T//8z8B5P5qt27dOnR0dHAZXFp2FEXBVDCGCV8YE/4wpgJR+AIRBMNxBCIJhKMJRKJJxBIi4skUkqIEMZVGKi0jnc7MFqBcimbqnhj0OhgNAiwmPexWE6rLXdh6WTNu2b4WpW7bQjeTiogky3jl/UHs3d+Hw6e9GPfHIGeUhW7WoqNSATqNBka9FjaTAIfViFK7CeVuM2pKbKivcKC52oUqD0d/ERER0YUrugDk3nvvxWOPPYZHHnkEmzdvPutr69evh16vx+OPP467774b3/rWt7B161b87Gc/w5NPPokDBw6gvb39I4/BAIToXKIoYdIfweRUBJP+MKaCUUwFowiG4whGEgjHkojGkoglUognUxBTaYipNNJpGWk5syj+On0+Oq0GHpcVrXXl2NTRgB1Xd2BVU9VCN4uKyKlhP377Vg/2dY2ibyyYd3HV5UqjVkHQaWA26GA3G+C2GVDqNKPSbcWKMhuaqpxornLCZjYsdFOJiIhogRVdAFJXV/eBK7ScufTtY489hn/6p3/C8PAwVq9ejYcffhjXXXfdBR2DAQjR3FAUBeO+EAZH/Rgcm8KYN4QJXxi+YBTBUAzBaALRuIjEdICSljMLMvpEpVLBaTOhvroE61fV4rorV2PbxmZOqaGCiCYk7Hm3F68cGsSxAR98oTgK3c1VmClYrIZOq4Gg08AoaGHUa2E26GAxCrCZ9bCbBTgtRjitBrhtRpQ4TChxmFHmNMNqEhBNSOgdDeD0WBBDkxGMTkUxGYrDH04iHE8hnsyNFsssklFiOq0aBkELq1GA02KA22FChcuMqhIbGirsaKx0oa7MDq2Wo0qIiIiKUdEFIPOBAQjR4qEoCvyhGAZHpzA8HsDIZBATvhC8gSj8wShC0SQisQTiCQmiJEGScqNN5oLZqEdNhQvtzdW4enMbbryqnava0CVTFAWHeibw7L5eHDg5juHJCGRFgU6TCy4MQi68MBkEWIw6WE258MJpMeRu8u1GeOwmlDpMKHWa4bIa5n3aiKIomAjEcWokgP7xEIZ9EYz7Y/CFEghERUQTEpKpNCQ5syhGgqlVKgg6NUx6HexmPZw2I0odJlS4LVhRakdjZW4KjsfO9zcREdFSwgAkDwxAiJa+SCyJgZEpDE/4MTIRxLg3CG8gAq8/iv4RH7z+CNJyfit4nEnQaVHusaO1oRxb1jfj5u0dqK/68JWmiJYzUZLRNxZE72gQg5NhjExFcyvWRJIIRUXERQmilFk0tVO0GjUMggYWo4AShxm1ZTa01LixtqEUHU2lsBiEhW4iERERTWMAkgcGIETLgy8QwQtvHsUbB0/heM8oRieDSIjSJe9Xo1bB5bCgcUUpNrXX47qtq7F5TQOLORJdJF8ogZ6RAPrGQxjyhjHuj8EbSiAYyU3BSaTSkNLKgq50pVGrYDLo4LYZUemxoqHCgVW1HqxvLkdDhZ3veyIionnEACQPDECIli9RlPDagW68/M4JHO4ewuDoFMLRREGG7dssRqyodGNd2wps39yGj12xEhYTCzcSXSpZVtA/EUTvaAgDk2GM+iIYD8QxFUogFBMRTUoQJRlpef5HlQg6DewmAaUOM2rKbGipdmFNQykuay5j4VYiIqICYwCSBwYgRHQmRVFwpHsIL7x5DAeO9qN3cBK+YBSZAgzR12o1sFuMqCx1oLmuDB2tK7BlfTPaW6r4l2OiORCKidOFXUPThV0j8IYS8EeSiMRTiItppNLzU4BZrVLBZNDCaTWi0m1BfYUdK1d4sK6pDG0r3LwGEBERXSQGIHlgAEJEF2J43I/n3+jEvkO96Do9hglfGKJUuCVOjQYd3A4LVlS4sbKxEpetrsO2ja0oddsKdgwiOj9FUTDsi6J3NICB8TD6J0IYmAhjzB9DMJpEQpTnfOqNoFXDYtKjxGFCTYkVzVUurG0qxfaOWq5kQ0REdB4MQPLAAISI8hWJJfHyvi68ur8bR08OY2jcj2hcLOgx1GoVrGYDyjx2NNSUYk1LNS7vaMDmjkYIApfqJZovoZiIQ6cmcLTfh97RAIYnI/CG4ggnJEjpSy+y/EFUKqC6xIZr1q3An96wBvUVjjk7FhER0VLCACQPDECIqJBkWcb+zn78/q1jOHR8AKeHvQiE43MyxF7QaeG0m1BV5kRLXQUuW12LLeub0VRbVvBjEdEHUxQFp8eCONQzie4hP/rGQxibisIfSSIhppEp4PvfpNdhTUMJPnVVCz65tRmClkEoEREtTwxA8sAAhIjmgy8QwVvv9eDgsX6cOD2GoTE/pkIxJAuwEs0fU6kAk0GPEpcVdVUerGqqwqaOBly5vgkOq6ngxyOiDxcTJRzumcTRfh9ODfsxOBmBNxhHOC5ClPIfPaJSAZVuK67uqMGf3tiO5mp3AVtNRES0uDEAyQMDECJaSIqioKt3DPsO9+Bw1xB6Bicx5g0iHE0iLc/NsHqNWgWNRgNBp4Fe0MEg6GAyCjCZ9LCZDLBZjHDYTHDYzfA4LHA7rShzW1HqtqOi1AGb2cCCjUQFMlN/5HDPJI4P+NA7FsToVBT+cG7534thFLRYVefBzq0t+PS2Vhg4TY6IiIoYA5A8MAAhosUqlhDxzvu9OHCsH8dOjWBgdApefwSxRAoLfblXqQCNWg2tVgNBp4Ve0MJoEGAyCLCaDbCYDXBYTXBYTXA5zHA5LCh12VDitmJFhRuVpc4FbT/RUpAQ0/g/r57As/t60D3kR+oiao2oAJS7zNi6pgZ/ekM7VtWVzF1DiYiIFgADkDwwACGipWhwdApvHerBoeMDONU/geEJPwLhOFKSvNBNuyAatRqlbitWNVXh6k1t2HndepSXsLgj0Yc5PuDD/7xwDG8dG8ZEIH5R36vXabCy1oNbr2zCZ7evhMmgm6NWEhERzQ8GIHlgAEJExUSWZRw6PoR9h3vQeXIEfcNeTPhCiMREZBRloZv3oQSdBhWlDnS0rsC1V6zEx69ZB5vFuNDNIlqUREnGr1/vxm/f7kHXwBTEiww/S50mbFldjbtvaMfaRhZOJiKipYcBSB4YgBDRciGKEsb9YUxOheGdisAXjGIqGEMoHEcwEkc4lkQ0lkQskUIiKSGZkpCS0pDSGchyBhlFwXz/v4zRoENNhRuXrarDjVvbcf2W1Vz+l+g8Tg378fMXjuKNzmGM+2O4mLeqoNWgtcaFj1/RhM9dtwoWgzBn7TwfRVHgj4jwhuKYDMThjyQxFUkiGE0iHEshEk8hmpTgshlx86YG3LixAVot6xARES13DEDywACEiOjCKYqCSFzEuDeECV84F6IEIvCH4wiEYohEk7kgJSEinkghOR2kSGkZUjqDTCZzyUuCWs0GNNSUYNOaBtyyfS2uWNfIoqxEZ5BkGb99swdPv3kSR/t9SKYubnSIx27EFauq8CfXr8bG1soP3TYmSpjwx+ELxeELJeCPJBGIJhGKiQjFUogmJESTEuLJNJKpNERJhiRnIMkKMhklr+uBCoDbbsTahjLsuLwRO65o4HLARETLEAOQPDAAISKaX6FoAs+9dgQv7evC0VPDGPeGIF1Eccc/plIBTpsZzXXl2LK+CZ+4dj1WNVUVsMVES1vfeBA/33sUrx8ZwshU9KJGcum0apQ6zJDkDFKSDElWIGeUBRkR9mFcVgPaG0px86YGfPyKJtY4ISJaBhiA5IEBCBHRwhvzBvHMS+/j9YMncaJ3FF5/9JJqlqjVKpS6bFjZWIFtG1ux8/rLUFXmKmCLiZYmWVawe18PfvPmSXSe9iIuphe6SXPCYTFgVZ0HN2yox86tLbCa5ndaDxERzT0GIHlgAEJEtDh1941j98uH8PahXpwamEAgHL+k5X91Wg0qShxY01KNay5fiVuvXQenzVzAFhMtPcPeCH6+txMvHx7EiDeCS5yhdklmltfWadTQaTUwCBoYBC1MBh0MghYj3gimIsm89m0zCVhZ68F1l9Xh9qtbYTMbCtx6IiKabwxA8sAAhIhoaVAUBQePDuDZ1w5j/5HT6Bv2IRLL72ZohkoF6LRamAwCrBYDXHYzSt02VJY6UVvpRn1NKVrry1FX5WGdESp6iqJgz7t9+PXr3TjcO4loUrqg71MhN+pKOx1cCDoNjIIWRr0WZoMOFqMAm1kPu1mA02KE02qAx25EidOMUocJpU7zBRdelWQZLxwYwJ53e3GkdxK+UOKiCr7OsBgFtNa4cO1ldbhtWys8dlMeeyEiooXEACQPDECIiJYuSZLxyrtdeOHNY3jv+ACGxvxIiBd203axNGoV9IIOZpMedqsJHqcF5R47qspdqKv0oKm2FG2NlRxVQkVjbCqKJ17uwmQoDrtZD7fVCJfNiBKHaTa4cFkNCxoOyrKCl98fwLPv9OJwzwQmgvG8apOYDTo0VTlxzboVuP3qlahwWwrfWCKiBTTuj+H1I4MIREV8eeeGhW5OQTAAyQMDECKi4hJLiNjzWide3nccR7qHMTYZRCp9catgXCqdVgOjQQf3czCXAAAgAElEQVSryQinw4wSlxWVJQ7UVLjRUFOClvoKNK0ogZYrVxAVlKIoeKNzGM+83YP3Tk1g3B+Dksevx0ZBi8YqJ67uqMEd16xEVYltDlpLRFR4U+EE3ugcxv7uMZwc8mNkKopwPAVleo6jRq1C98/vX+BWFgYDkDwwACEiKn5efwTPvPQ+XjtwAl09Y5j0hyFn8i+yWigz0wZUKhXUahXUKvX0swpqtRoajQoade41jUYNjUYNrUbzh2e1ClqtBjqNBlptbvqBdvoxMxVBp9NC0Gqh06oh6LS5h6CFXtBNf66BXtDB47JiRYUbdZVuGC5wOgLRYqcoCt49MYan3zqFA93jGJuK5rX0rl6nQUOFA1etqcHKWjf0M+8dXa5OiV6ngUGvhWH6dYNeC5Og5dQ5Ipoz0YSENzqHsL97DF0DUxj2RRCMihd0jdv3/36hKKb+MQDJAwMQIqLlSRQl9A550TMwgb4RH4bHA5jwheANRBGMxBGLixBTaaTl/JfoXcq0M7Uc9AIsZj1sZiOcNjM8LgtKXTZUlDpRXe5ETbkbddUe2CzGhW4y0QV579Q4nn7zJN7tGsOwLzpvYahq+j8qqKBSIRd8zj6rzghCVdCocx9r1DMfq3Mfa9TQqlXQaTWodFuwqs6Dja0V2NBaDoEjyoiKUkJMY1/XCN7tGsOxAR+GJiMIRJJIX8K16wf3XYtPb2stYCsXBgOQPDAAISKij+ILRHCybxy9Q14Mjk5hZDKISV8Y/nAM4WgC8WQKKUmeHV66XGnUagiCBgZBgMWkh9VihMNqhNtpRanLiopSB6pKnaipcKG+phRuB+ss0MI72ufFr984iX3HRzHkDSMtL/zosHzotGo4LAZUui1orHJibUMprlhdhYYK50I3jYgugCTLONg9gbeOjeDYgA8D4yFMhZOQCviHGJ1WDbfNiK/fuQW3XtlUsP0uFAYgeWAAQkREhSLLMvpGfOgZmETfsA9DY36MeYPw+iMIRuKIxkQkUxLS6UxeK1cUI7VaBUGrhV6vhcmoh3YxTBlQAYIuN03IoNfCIOhgNAgwGfUwGQVYjHpYzAZYTAZYzQbYLUZYzQY4bCY4bGbYrUY4bSbWeFmiTg378avXuvHW8REMTIQhpZf2KDAVAKNeB4/diBVlNrTWuHFZczmuWFXJ5YCJFoCiKHi/dxJvHh1BZ58X/WNB+MIJiFLhrjVajRpOqwE1pTasrvPg8pWV2LK6BlZTcU1xZQCSBwYgRES0EELRBE71TcAfjiGVSkOU0pDSMiQpAymdRkqSIaXl2ee0nMk9pzOQZBlyOgNJzkCWM5AzCtKzH2cgywrkTAYZJQtZziCjKMhklOnnLBRFgaJkkZl+VrIK0rICeZlO95lLKgAq9R9quWjPqNei02lztSSE6ZBFr4NBr4PRqIfZIMBuNaKhpgyrmyuxprUGFhNvVhdC/3gIv3qtG28eHcbgZK5+UDabhZIFstksssg9I/e/JUWjVsFm0qPMZUZDhQOr60uwua0S7XUl0GoXQRhJlIfJYAzH+n04NRzAmD+a18pQheYPJ3F6LIjJYByJVOEKs2vUKtjNelSX2rCq1o1NrZW4ak0NXLblMS2VAUgeGIAQERH9gShKGJrwY2DUj9GJAMa9IUz4I5gKRhEIxRCJJRFLpJCYnvYzczNIc0+tUsGg18FmMcLjtKCi1IG6qhK01JWjvaUKq5uqIQgcdbJYKIoCUcpAlOTcIy1DTMmQZAViWkYqJSOVziCVzj2nZQWp6WBTSsuQ0gokOYN0RpkOPnNBZzqjIJaUMOKLwhdKIC5Kc3KDp9dp4LIaUFViQ0u1C2sbS3Hl6mouEUwLKhQTcazfh5NDfvSNBzHsi2IyGEcoKiKWTBd0ushiolapYDMJqPJY0brCjY2tFbh6bQ3KnMv7/cgAJA8MQIiIiC6NLMsYnQxhcNyP4bEpjHlDmJyKwBuIIBiOIxRJIBoXkRAlpFJppDOZZV8vZa5o1CoYDQLsFhM8biuqS51oqClBa0MF2ltq0FJXxpVJitCoL4J9XaM4cnoSPSNBjE5FEYyKSM3B9B21CjAbBJQ4TKgqscIo5FaZ0mk10GrUELQaCNOfz6yUo9Woc6vj6DS56WU6DfSCBoJWA71OC72ggVHQQi9oYRByrxkELQStmv11GUmIaZwYmsKJQT9OjwUx5I1gIhBDIJJELCkhlc4sitEcc0mlAixGARVuC1qqXbisuRxXr12B2jL7QjdtUWIAkgcGIERERPNPURR4/REMjE1hZDyAkYkgvP5wXkuUFr5tWSRFCYlkCglRQjKVhpiSIKb+MDVJSuemHKXlzB+mFym50TCL/bcxrUYNk1EPh82EMrcN1eUuNNSUoK2hEh2tNaipcPGms0jIsoKj/V7sP5FbPaJ/IozJQBzRRGpRvNculgq5G0SoVFABZ62eI2g1s0GK0aCDxaCDxSjAbtbDbtHDZTXAZTXCYzehxGFCmdOMUod5yU/1ESUZ4biIcCyFSCKFcDwFFVS5wGk2TNLAIOhgEHLBkl5Qz/uqQbKs4OSIH10DU+gZDWB4MoJxfwxTkSSiiRREKQNlsV88C8xs0KHMZUZTpXM66KhBc7V7oZu1pDAAyQMDECIiIio0WZYRjokIRxMIRhIIRxKIxJKIxJOIxJKIJ1KIxsXcdCIxhURSQlKUkExJSKVkiFIa8UQKkVgSYio97zcGOq0GFpMeTrsZLrsZJoMeBoMOZqMeZqMeJpMeVpMeVrMRtukisHabCQ6LKVcE1m6GxaRnkLKIhWIi3j0xivdOTeDkcADD3gj84URB6xMsFWqVClpNrkbPzOgUo14Hk14Hi0kHq1GA3WyAw6KHy2aEy2pAyXSQUu6ywGE5u68rSm6aUjguIRQTEY6nEE1IiCRSiCUkxMQ04kkJcVFCIiUjKcpISLmAVZQyEGfrPU1Pe5IVyNM1nHJBKwp+TVCdtURzbnnmmaWa1Wcs0Tzz8fmWZ1ar1bmfo1oNqFSz555Mpec9cNOoVTDpdbCaBGjUqnk99vlotRrUlduxvqkMW9qrsaa+hNfHAmAAkgcGIERERLTYxRIijp4cxvGeMfQMTmBobArjvjD8oRiicREpKb1oR56ozrhp0mrU0Go10Go00Ommp0gIOgg6ba4ArF4Hg0GAySDAbMoVg7WYDLBajGipK8N1V67i6jpzTFEU9I2H8U7XKI72edEzGsSEP4pQPLVklwieD6rp/yzW92ExUatVMApa2EwC3HYTKtwW1JbZ0VzlRHt9CRoqnEt+ZA9dGAYgeWAAQkRERMXAH4qhs3sYJ06PomdwEsPjAUxMhREIxRBLpCCli+Mv+y67GaubqnDtlatw+02bUOq2LXSTlg1RknHo1AQOnBzHiYEpTATjuZWnpleXkpXs9JSw3OeZbG5KmaIoULLZ6VWnsrMjGLIzK+lkgSyW5ko6VFgqFWDQaWE1CXDZjCh3WbCizIamSidW1nrQtsINA4s90zQGIHlgAEJERETLxZg3iCPdw+g+PYbewUmMTAQw6Y8gGIkjkZSQXoIrKBj0OtRVeXDluibsvOEybF7TwKHlRUKWFYhybvWclCQjKeVWzRGlXB2emVV0ogkJgaiIQCSJUCyFcFxENCkhlkjn6vhMTy2R0hmkM5nccuBFdtukmpmqospN91Cml2jGbMC08FQABJ0GFqMAl9WAMpcZNSU2NFQ60VbrxuraElhNwkI3k5YQBiB5YABCRERElKMoCvqGfTh6chjd/ePoG/YhFI4jeUYR2JlCsLnaBDJkWZktBDvzF/6FpFarUOqyoaOtBjdd1Y5PXHsZbBbjgraJFidJluELJuANJeANxeEPJ+GPJBGIirkaPgkJsaSEeDJXq0NMpWeXKpbPqMfxYXLTvwC1Sg2NJjcNTKeZXiVHq4ZOp4FhulCpXtDCJOhg0GtgNuhgNggwGXI1SCwmAVajAJtZD7tZD5tZD6dFD4tRuOjAT1EUSLICKS3PhkO5gElGSsqdXyqd+ziVzi3LLKYzkGVl+mvTYZKcq1MiZ86uV5KeHgXksRvRUO5A6wo32utL4LGbLuFfi+hcDEDywACEiIiIqPBEUUJoughsKBJHJJZEOCYiEk0ilhARTYiITS+PnJguBptMpZFMpZGaWXFHkiHJudAlEkvm3RaLSY+m2jJs29CC22/ejLaGigKeKS130YSEiUAU2Sxgt+hhNxs4TYNoHjAAyQMDECIiIqLFT5ZlvPxuN5595TAOdPZhZCKQ95QdrVaDqjIHNqyuw8evWYcbtrRD4A0rEdGSwgAkDwxAiIiIiJam3sFJPPXCQbxxoBunBiYQiYl578tpM2NlYwU+dsUq3H7TRlSWOgvYUiIiKjQGIHlgAEJERERUHBKihGdfOYy9r3fi8IkhjE+FoCj5/XqsF7SorfLg8o5G7LxuPbZc1sziqkREiwgDkDwwACEiIiIqXu8dH8BvXjiIfe/3om/Eh6Qo5bUflUqFUpcVbqcVWo0aGo0aOo0GWm2uoKVWq4FOp4VOq4FOq4ZOp4Wg1ULQaSDotBCE3Nf0gg6CTgu9kHsYBN30axoY9LrphwCDXgejIfexXtDCZLj4YpdERMWMAUgeGIAQERERLR++QARPv/geXnq7C8d6RuEPRT9yJY/FyGjQobLUiVVNVdi2sQU3b+tAqdu20M0iIpo3DEDywACEiIiIaPlSFAWvvtuNZ15+HweO9mF43A8pnV9x1YWm02pQ4rKipa4cl69txE3b1mBVU9VCN4toWVMUBYqiQKtloeVCYwCSBwYgRERERHSm/lEfnnr+AF7ffxIn+8cRvoQleBeaSqWC02ZCfXUJLltdh2uvWIVtG5uX9M2YLMvo7pvA0VPDONU/gZSURltjJTa216OtoYJThWhexBIiTvZPoGdgAv0jPoyMBzAxFcZUMIpQNIFYPAVRSiOTUQAAarUKBkEHm8UIj8uKylIH6qpL0FpXhvaWGqxsqORqVBeJAUgeGIAQERER0YcRRQm/e+0IXt3fjXhchCRnIMsZyBkF6dmPM5BlJfecUZDJKMgoZz5np/8SnEVm+lnJZpGdec7+4Tn3G312TqfmWEx6VJe70N5cjas3t+HGq9rhsJrm7oAXSFEU9A37cPTkMLr7x9E37MPoZAA+f+6mMiFKszeUH0TQaWG3GlHqsqG20o3Whgp0tK3A5o4GuB2WeToTWooURcHA6BRO9k+gf9iLgVE/xrxB+AIRBMJxRGMiEqKEtCzPyftTo1bDaNDBbjWhxGVFVZkLjTUlaG2owJrWajStKGPAdwYGIHlgAEJEREREi52iKBAlGUlRwrg3hBffPo53O0/jVN8EvIEI0vKlT9vR67Qo89jR2lCOLeubcfP2DtRXlRSg9X8wOhnAkRPDONE3hr4hL0YmApj0RxCMxJFISgU5jw+jVqlgMgpw2S2oLHOgvroEq5uqsaG9FmtaqpfMyBhJkjEyGcDgqB/DE36Me0MY94XhD0Wh02hgs5rgspvhcpjhcVpR6rKhvMSOilIH7BbjsruJDkbi6D49ht5BLwbGpjA87sfkVAT+UAzhaALxRG60Rr6rRs0nrVYDs0GAw25CmcuO6gonGmpKsbKxEh2tNagqcy6bf18GIHlgAEJERERES53XH8HeN47irUOncKxnFGOTQSTyXPHmTBq1Gi6HGY0rSrGpvR7XbV2NzWsaznuD5Q/FcOTEELpOj6J30IvhcT8mpsIIhuOIJVKQ0vIlt2eu6bQa2CxGlLisWFHpRnNdOda21mBzRwPKSxxzcsyEKGFwdAoDo1MYnQhifCqEyekwIxCOIxxNIp5MIZGUIKVlyJnMJY8+UKkAtVo9vWrRH1YgMhv1MBv1sFkMsFqMcNrMcNnNcDus8DgtKPPYUF7qQIXbDoNBKMwPALlpTeGYiGA4jlAkjkhMRDiaQDiWRCwhIhoXEYuLiCel6Z9FCmIqjWRKgpiSkZLSkCQZUlqGlJ4ekTU9KmuuQ7XFSNBpYDYa4HKYUea2oabSjaYVZVjZUIG1K1egxFUcBZMZgOSBAQgRERERFSNRlPDK/m68+u4JHD4xiMFRP8KxREGG7s+EBJFYEtG4iJSUntfVdFQABEELq9kAjUaNcDQJMZWe22OqAKNegNNuRmWpA/U1pVjVWIl1q1ZgXesKGAwCQtEE+oe9GB4PYHQyiDFvCL5ABP5gDMHpG/tYQoSYSk+HGR8+nWexU6tUuSWhtRoI08s6Gw0CTAYBciaD1BmhRFqWIctnTAtTlDOmfC1NKpUKep0WJqMAm8UIt8OCMrcNlWVO1Fa50bSiHK0N5bCYDDh2agTHe0fQM+DF0NgUxn0h+ENxxOIiUun5ff88/P/8X/jTT22dvwPOEQYgeWAAQkRERETLhaIoeP/EEF586xj2d/ahd2gSU8HYR9bVmG/5/AVbURQMjvtxoLMfR08Oo3dwAsMTQUwFoogmxEV3jrR4zYyKsZoNcNrMKHFZUV7iQE2FC401pWipL0dDdUlBR8H4AhEcPTkyLyOonv3//m9sXNNQsP0tFAYgeWAAQkRERETL3fC4H8+/0Ym3DvWi+/QYxn0hpKS5mbKyUDUMRFHC+ycG8X7XILp6x9A/4sO4L4RgJAExJS3JkQhajRqCTguDXgeLyQCr2YCMoiAhSkiK0uwIDFnOTI+4WOgWLxy1WgW9kJvmY7ca4XFYUOqxo7rMifqaEjStKENzXdminh5SqBo6Ay//c0HDm4XCACQPDECIiIiIiM4ViSXx0tvH8eqBbhw9OYLhcT+icfFDv+d8q1g0VHvQ2lCB9pYatNQt3lUshsf9OHi0H50nh9EzOInhcT98gSiicXHO60ioVIBWo4EwPZ1i5iZ9pv5GWYkdFR4HqsqdqKvyoLbKA1OeN7ChaAITvjAmp0LwBaLwBaIIhGIIhOMIRZOIRBOIJkTEE7m6I6KURkpKIz1dWyMzh4VCVarctBKNWp17aNTQatXQabUQdLmfj17QTtcsEWDU62AyCDAZ9TAZ9bCY9LCaDbCY9bCajbBbTWiuLUNdlXvJFLi9FBeyihIAjL7xyAK3tDAYgOSBAQgRERER0YWRZRnvHD6NF98+jpHJICrLnGitK0N7Sw1WNlRCEIrzJlOSZHSeHMJ7xwfRdXoU/UO50SOBcBwJUcKZt2EqlQo6rQZ6IRdmWM1G2C1GOO3TUyk8udVYasrdqK1yo7rMteR+brIsYyoYw7gvBK8/Aq8/Cn8oBn8ohlA0gUgsCUGnhXk6lDBPBxM2ixFWkwF2qwl2m2n252K3GJZFQLEYKIqyaEPIi8UAJA8MQIiIiIiI6FL4AhFIaRkVJY6iubkkWuwYmREREREREc2zxVw3gqhYFWXU2Nvbi/vuuw8dHR3QaDS45pprztkmm83iu9/9LmpqamA0GnH11Vfj8OHD899YIiIiIiIiIppzRRmAHD9+HHv27EFraytaWlrOu833v/99PPTQQ/j617+O3bt3w2Kx4Prrr8fExMQ8t5aIiIiIiIiI5lpR1gA5s0jLZz7zGUxNTeHVV1+d/booiigrK8MDDzyAb37zmwCAeDyOuro63HffffjOd77zoftnDRAiIiIiIiKipaUoR4B8VBGht99+G5FIBHfcccfsa2azGZ/4xCfw3HPPzXXziIiIiIiIiGieFWUA8lG6u7uh0WjQ3Nx81usrV65Ed3f3ArWKiIiIiIiIiObKsgxAgsEgLBYLNBrNWa87nU4kEglIknTO9zz66KPYuHEjNm7cCJ/PN19NJSIiIiIiIqICWJYBSD7uvfdeHDx4EAcPHkRJSclCN4eIiIiIiIiILsKyDECcTidisRgymcxZrweDQZhMJgiCsEAtIyIiIiIiIqK5sCwDkLa2NmQyGfT29p71end3N9ra2haoVUREREREREQ0V5ZlALJlyxbYbDbs2rVr9rVEIoHdu3djx44dC9gyIiIiIiIiIpoL2oVuwFxIJBLYs2cPAGB0dBSRSAS/+tWvAAC33HILTCYTvvGNb+Chhx6C0+lEW1sbfvjDH0JRFHzlK19ZyKYTERERERER0RwoygDE6/Xis5/97FmvzXze39+Puro6fOMb34CiKPje974Hv9+PjRs34ve//z3KysoWoslERERERERENIdU2Ww2u9CNWGo2btyIgwcPLnQziIiIiIiIiOgCLcsaIERERERERES0vDAAISIiIiIiIqKixwCEiIiIiIiIiIoeAxAiIiIiIiIiKnoMQIiIiIiIiIio6DEAISIiIiIiIqKixwCEiIiIiIiIiIoeAxAiIiIiIiIiKnqqbDabXehGLDUejwd1dXUL3YyL5vP5UFJSstDNIPpA7KO02LGP0mLHPkqLHfsoLXbso8XB4/Hg+eefP+d1BiDLyMaNG3Hw4MGFbgbRB2IfpcWOfZQWO/ZRWuzYR2mxYx8tbpwCQ0RERERERERFjwEIERERERERERU9zYMPPvjgQjeC5s+GDRsWuglEH4p9lBY79lFa7NhHabFjH6XFjn20eLEGCBEREREREREVPU6BISIiIiIiIqKixwBkiejt7cV9992Hjo4OaDQaXHPNNedsEwqFcM8998DlcsFisWDHjh3o7e09Z7unn34aHR0d0Ov1qK+vxw9/+MNztslms/jud7+LmpoaGI1GXH311Th8+PBcnBoVifnuo3V1dVCpVGc9ysvL5+LUqAjs2rULn/zkJ1FVVQWLxYINGzbg8ccfP2e7xx57DM3NzTAYDNiwYQNeeumlc7YZHR3Fpz/9aVitVng8HvzVX/0VEolEXvsimjHfffSaa6455xqqUqkgiuKcnSMtbYXqoz6fD3/913+NzZs3QxAE1NXVfeAxeR2lizHffZTX0aWJAcgScfz4cezZswetra1oaWk57zaf+9znsHfvXjzyyCP45S9/Cb/fj+uuuw6RSGR2m7feegu33XYbNm/ejN27d+Oee+7B17/+dfzoRz86a1/f//738dBDD+HrX/86du/eDYvFguuvvx4TExNzep60dM13HwWAu+66C/v27Zt97NmzZ87Oj5a2H/7wh7BYLPiXf/kXPPPMM/jYxz6Gu+66C//2b/82u83jjz+O+++/H5///Ofx3HPPYfXq1bj11ltx7Nix2W3S6TRuuukmDA4O4oknnsAjjzyCXbt24d577z3reBeyL6IzzXcfBYCPfexjZ11D9+3bB71ePy/nS0tPofro6OgonnzySZSXl2PdunUfeDxeR+lizXcfBXgdXZKytCRkMpnZj2+//fbs9u3bz/r622+/nQWQffHFF2dfm5iYyBqNxuzDDz88+9qNN96Yveqqq8763q997WtZp9OZTaVS2Ww2m00mk1mbzZb91re+NbtNLBbLejye7N/+7d8W8rSoiMxnH81ms9na2trsAw88UOCzoGLl8/nOee3OO+/M1tXVzX7e0tKS/dKXvjT7eSaTyba3t2f/5E/+ZPa1X/7yl1m1Wp3t6+ubfe3JJ5/MqlSq7KlTpy5qX0Rnmu8+un379uztt99e6NOgIlaoPnrm7wsPPPBAtra29rzH43WULtZ891FeR5cmjgBZItTqD/+nOnz4MHQ63VnTDsrKyrB27Vr87ne/O2u7G2644azvvfHGGxEMBrFv3z4AwNtvv41IJII77rhjdhuz2YxPfOITeO655wpwNlSM5rOPEl0sj8dzzmvr16/H2NgYAKCvrw+nTp0667qnVqvx2c9+9qzr3nPPPYdNmzahvr5+9rVPfepTEAQBzz///EXti+hM89lHifJRqD76Ub8vXMy+iM40n32Uli7+6xYJURSh0Wig0WjOel0QBJw4ceKs7QRBOGcbALPbdXd3Q6PRoLm5+aztVq5cie7u7rloPi0DheyjM/7rv/4LgiDAbrfjM5/5DAYHB+eo9VSM9u3bNztda+ba1tbWdtY2K1euRCAQgM/nm93uj7cRBAGNjY2z+7jQfRF9lLnqozNeeOEFmEwmmEwm3HTTTejs7JyrU6EilU8fvRC8jlKhzFUfncHr6NLDAKRINDU1QRRFHD16dPa1ZDKJY8eOIRAInLXdgQMHzvre/fv3A8DsdsFgEBaL5ZwbVafTiUQiAUmS5uo0qIgVso8CwM6dO/HjH/8YL730Eh5++GHs27cP27ZtQzgcnuMzoWLw0ksv4emnn8YDDzwAIHfdAwCHw3HWdk6n86yvB4PBc7aZ2e7MbS5kX0QfZi77KABs374djzzyCPbu3YtHH30UQ0ND2LZtGwYGBubidKgI5dtHLwSvo1QIc9lHAV5HlyoGIEXipptuQn19Pe677z6cPHkS4+PjuP/++xEOh88axnX//ffj6aefxmOPPYZgMIi9e/fOrrDB4V40lwrdRx955BHceeed2LZtG+69917s3bsXY2Nj+OlPfzrv50ZLy8DAAO666y7s3LkTX/ziFxe6OUTnmI8++q1vfQtf+tKXsG3bNtx999145ZVXoFKpzltwmuiP8TpKix2vo/RBeMdbJARBwBNPPIHJyUm0tbWhsrISfX19+PznP3/W0qD33HMPvvzlL+PLX/4yXC4XbrvtNvz93/89AMxu53Q6EYvFkMlkzjpGMBiEyWQ6Z3oC0YUoZB89n/b2drS2tuLQoUNzfi60dAUCAezYsQO1tbX4xS9+Mfv6zF9//ngE0cxfg2a+7nQ6zzvKKBgMnrXNheyL6Hzmo4+eT3l5ObZu3cprKH2kS+2jF4LXUboU89FHz4fX0aWBAUgR2bx5M3p7e9Hd3Y3e3l688cYb8Hq9uOKKK2a30Wg0+Pd//3f4fD50dnZicnJy9uszz21tbchkMujt7T1r/+ebV0x0MQrVRz/IzPrrROeTSCRw6623QpIkPPvsszCZTLNfm7m2/XGNhO7ubrhcLpSUlMxu98fbSJKEvr6+2X1c6L6I/th89dEPwmsofZRC9NELweso5Wu++ugH4XV08UttGf4AAAsJSURBVGMAUmRUKhVaW1vR2NiInp4evPjii/izP/uzc7ZzOp1Ys2YNLBYLfvzjH2PLli2zF4UtW7bAZrNh165ds9snEgns3r0bO3bsmLdzoeJUiD56PseOHUN3dzc2bNgwl82nJUqWZXz2s59FT08Pnn/+eZSWlp719YaGBrS0tJx13VMUBbt27Trrurdjxw4cOHDgrIK7zzzzDFKpFG6++eaL2hfRmeazj57PxMQE3nzzTV5D6QMVqo9eCF5HKR/z2UfPh9fRpUHz4IMPPrjQjaCPlkgk8Nvf/hZdXV3Yu3cvgsEgysrK0NXVhbq6Ouh0Ojz00EPwer3wer3YvXs3vvCFL+C2226bLfwDAO+88w6eeOIJJBIJHD58GN/85jexe/du/PrXv0ZZWRkAQKvVAgD+8R//EQ6HA9FoFF/72tcwMjKCn/3sZ7BYLAvyM6DFbT776O9+9zv8wz/8A1KpFPx+P55//nnce++9cLvd+I//+A/o9fqF+jHQInX//ffjySefxPe+9z24XC6MjIzMPkpKSqDVauHxePDNb34TGo0GmUwG3/72t/H666/j5z//+ewvUW1tbXjqqafw1FNPoaamBgcPHsRXv/pV7Ny5E3/xF38xe7wL2RfRmeazj3Z2duKee+5BOp1GMBjE66+/jj//8z9HIpHAf//3f8Nuty/kj4IWqUL1UQD41a9+ha6uLrz88svo7+9HfX09urq6UFJSArPZDIDXUbp489lHeR1dwrK0JPT392cBnPfR39+fzWaz2a9+9avZysrKrCAI2cbGxuz3v//9bDqdPms/Bw8ezG7cuDFrNpuzVqs1e8stt2Q7OzvPOZ6iKNnvfOc72aqqqqzBYMheddVV2UOHDs3HqdISNZ999MiRI9lrr7026/F4slqtNltWVpb9whe+kB0dHZ2v06Ulpra29iP7ZzabzT766KPZxsbGrCAI2fXr12dffPHFc/Y1PDyc3blzZ9ZsNmddLlf2L//yL7PxePyc7S5kX0Qz5rOPjoyMZHfs2JEtLy/P6nS6rMvlyt52223ZEydOzMep0hJVyD76Qft55ZVXztqO11G6GPPZR3kdXbpU2Ww2W/hYhYiIiIiIiIho8WANECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiIiIqegxAiIiIiIiIiKjoMQAhIiIiIiIioqLHAISIiIiIiIiIih4DECIiIiIiov+/vbsJier74zj+uWYJk+kEKhomUrSQyBCGEtpYJi4cKoMppIXpwoqKpAeiol0RBGFFQc8uR9LIQrGwxRCkBA1RGENRlDg5Fknz0Kg4NvNfRPP/iWn5y58Pl/cLhLmec+49Z1by8XvOBWB6BCAAAAAAAMD0CEAAAAAAAIDpEYAAAAAAAADTIwABAAAAAACmRwACAABmpVgsppKSEhmGoWXLlunbt2+/HbNt2zYZhqHMzEx9+fJlGmYJAADmCgIQAAAwKxmGoVu3bik1NVXv37/XoUOHJuzvdDrV2NgoSbpx44bS0tKmY5oAAGCOIAABAACz1tKlS3Xx4kVJ0rVr19TW1vbLfj6fT/v27ZMkVVdXy263T9scAQDA3GDEYrHYTE8CAABgIlu3btXdu3e1ZMkSdXV1afHixaPa7Xa7WltblZubq5cvX2rRokUzNFMAADBbUQECAABmvatXryo9PV29vb3au3fvqLabN2+qtbVVhmGovr4+Hn50dXWppqZGK1askMViUXJysvLz83XixIlxzweJRCK6f/++ampqZLPZlJWVpQULFigjI0OlpaVyOp0a739HLpdLhmHIMAxJ0vPnz7Vjxw5lZ2dr/vz5KioqmrovBAAATBoVIAAAYE5obm5WeXm5JOn27dtyOBzq7u5Wfn6+gsGgamtrVVdXJ0k6e/asjh07pmg0KkmyWCwaGRnR8PCwJCkrK0utra0qKCgY9QyXy6X169fHr1NSUhSLxRQKheK/czgcamhoUEJCwrhjm5qaVFFRoUgkopSUFA0PD2vt2rVyuVxT+6UAAIA/RgUIAACYE7Zs2aLKykpJ0p49e+Tz+VRdXa1gMKi8vDydOXNG0o+KkKNHj8pisej06dPy+XwKh8MaGBjQs2fPtGHDBvl8Pm3atGnMm2UsFot27dql9vZ2BQIBBQIBBYNB9ff368KFC0pJSVFjY6MuXbo04Vx37typkpISeTweBQIBDQ4O6vr16//NFwMAAP4IFSAAAGDOCAQCWrVqlXp6epSdnS2v16vExER1dnbKZrMpFAopJydHfr9fDx48UGlp6Zh7jIyMqLCwUG63W3V1daqtrf3j5zc1NcnhcGj58uV6+/btqLZ/VoCsWbNGHR0dmjdv3t8tGAAATBkqQAAAwJyRmpqq+vp6GYYhr9crSTp+/LhsNpsk6c6dO/L7/SooKPhl+CFJiYmJqqiokCQ9fPhwUs8vKyuTJL179059fX3j9jty5AjhBwAAs0ziTE8AAABgMoqLi7V582Y1NzcrPT1dJ0+ejLc9efJEkuTxeJSZmTnuPQYHByVJ3d3dY9pCoZCuXLmilpYWeTwe+f1+RSKRMf28Xu+4z1i3bt2k1gQAAP57BCAAAGDOSU1NlfTjzI7ExP//OdPb2ytJGhoa0tDQ0G/vMzAwMOr6zZs3Ki4ujleX/HyG1WqNH3r66dMnSVI4HB73vhkZGX+4EgAAMF3YAgMAAEzj+/fvkqTt27crFov99ufDhw+jxldVVcnr9So3N1eNjY3q7+9XOBzW58+f1dfXp48fP8b7TnSMGttfAACYfagAAQAApvFzS8qvtrb8Tk9Pjzo6OiRJTqdThYWFY/pMdO4HAACY3agAAQAApvHz7A232y2fzzepsT09PfHPBQUFv+zz6NGjfz85AAAwowhAAACAaTgcDlmtVkUiER08eHDCbSrRaFR+vz9+/fNcEUl68eLFmP6hUEinTp2a2gkDAIBpQwACAABMw2q16vz585KkhoYGlZWV6enTp4pGo5J+hB4ej0fnzp3TypUr1dLSEh+bl5ennJwcSVJ1dbXcbne8rbOzU0VFRfr69es0rgYAAEwlzgABAACmUllZqcHBQR04cEBtbW1qa2tTUlKSkpOTFQwGR73S1jCM+OeEhARdvnxZ5eXlevXqlWw2mywWi6Qfb4tZuHCh7t27p40bN077mgAAwN+jAgQAAJjO7t279fr1ax0+fFirV69WUlKS/H6/kpOTZbPZtH//frW3t6uiomLUOLvdrsePH6usrExWq1UjIyNKS0tTVVWV3G63iouLZ2hFAADgbxmxiTbHAgAAAAAAmAAVIAAAAAAAwPQIQAAAAAAAgOkRgAAAAAAAANMjAAEAAAAAAKZHAAIAAAAAAEyPAAQAAAAAAJgeAQgAAAAAADA9AhAAAAAAAGB6BCAAAAAAAMD0CEAAAAAAAIDpEYAAAAAAAADT+x+r9kuvqZ06YAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1296x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}