Caroline_Oliveira_Projeto_Módulo_02.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Caroline_Oliveira_Projeto_Módulo_02.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "57le5wJLm5w-"
      ],
      "toc_visible": true,
      "mount_file_id": "1-DDIHeclaA3pdP4aPEnKtHxXVulzXlTJ",
      "authorship_tag": "ABX9TyPe8LAXrFynRkrJcXmwQ2uo",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/CarolineOlive/Projetos-Bootcamp/blob/master/Caroline_Oliveira_Projeto_M%C3%B3dulo_02.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5srbGm_WjUJI"
      },
      "source": [
        "# Projeto Módulo 2 - Cobertura Vacinal \n",
        "Dados fonte: TABNET - DATASUS \n",
        "\n",
        "**Bootcamp Data Science 2021 - Alura**\n",
        "\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Autora: Caroline Silva de Oliveira\n",
        "\n",
        "E-mail: karolsilvaoliveira@yahoo.com.br\n",
        "\n",
        "LinkedIn:  www.linkedin.com/in/caroline-oliveira-quim\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P6SRlGl9EWGW"
      },
      "source": [
        "![Design sem nome 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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0chjTuUNH6Ln"
      },
      "source": [
        "## Contextualiazação\n",
        "O termo **cobertura vacinal** refere-se ao percentual da população que está vacinada. Quanto mais pessoas receberem determinada vacina, maior será a cobertura vacinal. \n",
        "\n",
        "O Brasil é um país que tem um Programa Nacional de Imunizações (PNI) reconhecido internacionalmente. No entanto, vive um contexto de queda no percentual de cobertura vacinal ao longo dos anos, ou seja, aumenta a parcela da população sem vacinação adequada [1]. A meta de cobertura vacinal determinada pela OMS é de 95% e é preocupante e tem chamado a atenção das autorizadades de saúde [2]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7EyyAiERNJDt"
      },
      "source": [
        "## Sobre os dados utilizados\n",
        "\n",
        "**Coberturas vacinais por Imuno e Ano - 2000-2019**\n",
        "\n",
        "Imuno: BCG, Hepatite B, Poliomielite, Febre Amarela, Hepatite A, Tríplice Viral D1\n",
        "* Fonte: TABNET-DATASUS - Ministério da Saúde\n",
        "* Disponível em: <http://tabnet.datasus.gov.br/cgi/dhdat.exe?bd_pni/cpnibr.def> Acesso em: 09/02/2021\n",
        "\n",
        "**Coberturas vacinais por Unidade da Federação e Ano - 2014-2019**\n",
        "\n",
        "Imuno: Hepatite A\n",
        "* Fonte: TABNET-DATASUS - Ministério da Saúde\n",
        "* Disponível em: <http://tabnet.datasus.gov.br/cgi/dhdat.exe?bd_pni/cpnibr.def> Acesso em: 09/02/2021\n",
        "\n",
        "**Número de casos por Unidade da Federação e Ano**\n",
        "\n",
        "Imuno: Hepatite A\n",
        "\n",
        "* Fonte: Indicadores e Dados Básicos das Hepatites nos Municípios Brasileiros\n",
        "* Disponível em: <http://indicadoreshepatites.aids.gov.br/> Acesso em: 10/02/2021\n",
        "\n",
        "A base de dados do governo dispõe de informações sobre o número de casos de hepatite A e a taxa de incidência num período de 1999 a 2019. Os dados são disponibilizados separadamente por UF, sendo assim, foi necessário fazer uma compilação dos dados em um único banco de dados."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vMkedl-6g_bP"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "#importanto bibliotecas\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.ticker as ticker\n",
        "import numpy as np\n",
        "import seaborn as sns"
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B2bQ1A_2VRl9"
      },
      "source": [
        "##**Coberturas Vacinais - Imunos**\n",
        "\n",
        "**Imuno:** BCG, Hepatite B, Poliomielite, Febre Amarela, Hepatite A, Tríplice Viral D1\n",
        "\n",
        "**Período:** 2000-2019\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "v6X1zBrsjcVy",
        "outputId": "712adb59-151e-4f47-ab33-f4b29fc6dc2c"
      },
      "source": [
        "# Importando o banco de dados de cobertura vacinal por ano segundo Imunos selecionados\n",
        "dados_vacina_imuno = pd.read_csv('/content/drive/MyDrive/Bootcamp Data Science/Módulo 2/Projeto 2/A130647189_28_143_208_CV_IMUNOS_BR.csv', encoding=\"ISO-8859-1\", na_values='-',\n",
        "                    skiprows = 4, skipfooter=20, sep=\";\", thousands=\".\", decimal=\",\", engine='python')\n",
        "dados_vacina_imuno.head()"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Imuno</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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>072 BCG</td>\n",
              "      <td>111.74</td>\n",
              "      <td>112.60</td>\n",
              "      <td>110.28</td>\n",
              "      <td>108.47</td>\n",
              "      <td>113.36</td>\n",
              "      <td>114.48</td>\n",
              "      <td>113.06</td>\n",
              "      <td>111.08</td>\n",
              "      <td>108.91</td>\n",
              "      <td>108.71</td>\n",
              "      <td>106.71</td>\n",
              "      <td>107.94</td>\n",
              "      <td>105.69</td>\n",
              "      <td>107.42</td>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "      <td>104.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>073 Hepatite B</td>\n",
              "      <td>91.08</td>\n",
              "      <td>91.88</td>\n",
              "      <td>91.47</td>\n",
              "      <td>92.00</td>\n",
              "      <td>96.26</td>\n",
              "      <td>98.46</td>\n",
              "      <td>100.30</td>\n",
              "      <td>99.89</td>\n",
              "      <td>96.06</td>\n",
              "      <td>100.20</td>\n",
              "      <td>96.08</td>\n",
              "      <td>97.71</td>\n",
              "      <td>96.67</td>\n",
              "      <td>100.56</td>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>94.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>074 Poliomielite</td>\n",
              "      <td>101.44</td>\n",
              "      <td>102.83</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.48</td>\n",
              "      <td>104.30</td>\n",
              "      <td>105.12</td>\n",
              "      <td>105.25</td>\n",
              "      <td>105.43</td>\n",
              "      <td>100.18</td>\n",
              "      <td>103.66</td>\n",
              "      <td>99.35</td>\n",
              "      <td>101.33</td>\n",
              "      <td>96.55</td>\n",
              "      <td>100.71</td>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>96.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>006 Febre Amarela</td>\n",
              "      <td>37.14</td>\n",
              "      <td>40.24</td>\n",
              "      <td>38.70</td>\n",
              "      <td>34.68</td>\n",
              "      <td>38.29</td>\n",
              "      <td>42.95</td>\n",
              "      <td>46.17</td>\n",
              "      <td>49.23</td>\n",
              "      <td>47.09</td>\n",
              "      <td>49.69</td>\n",
              "      <td>49.25</td>\n",
              "      <td>48.95</td>\n",
              "      <td>49.31</td>\n",
              "      <td>51.50</td>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>45.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>096 Hepatite A</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>63.73</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Imuno   2000   2001   2002  ...  2017  2018  2019  Total\n",
              "0            072 BCG 111.74 112.60 110.28  ... 97.12 97.72 52.95 104.96\n",
              "1     073 Hepatite B  91.08  91.88  91.47  ... 86.29 92.91 55.93  94.10\n",
              "2   074 Poliomielite 101.44 102.83 100.01  ... 84.27 88.17 51.54  96.61\n",
              "3  006 Febre Amarela  37.14  40.24  38.70  ... 46.46 58.40 39.91  45.06\n",
              "4     096 Hepatite A    nan    nan    nan  ... 83.05 82.16 52.09  63.73\n",
              "\n",
              "[5 rows x 22 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "pPGwDoUvksS0",
        "outputId": "5c5bf916-2bf1-43c3-ac5d-83746eea1f7c"
      },
      "source": [
        "dados_vacina_imuno.tail()"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Imuno</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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>073 Hepatite B</td>\n",
              "      <td>91.08</td>\n",
              "      <td>91.88</td>\n",
              "      <td>91.47</td>\n",
              "      <td>92.00</td>\n",
              "      <td>96.26</td>\n",
              "      <td>98.46</td>\n",
              "      <td>100.30</td>\n",
              "      <td>99.89</td>\n",
              "      <td>96.06</td>\n",
              "      <td>100.20</td>\n",
              "      <td>96.08</td>\n",
              "      <td>97.71</td>\n",
              "      <td>96.67</td>\n",
              "      <td>100.56</td>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>94.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>074 Poliomielite</td>\n",
              "      <td>101.44</td>\n",
              "      <td>102.83</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.48</td>\n",
              "      <td>104.30</td>\n",
              "      <td>105.12</td>\n",
              "      <td>105.25</td>\n",
              "      <td>105.43</td>\n",
              "      <td>100.18</td>\n",
              "      <td>103.66</td>\n",
              "      <td>99.35</td>\n",
              "      <td>101.33</td>\n",
              "      <td>96.55</td>\n",
              "      <td>100.71</td>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>96.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>006 Febre Amarela</td>\n",
              "      <td>37.14</td>\n",
              "      <td>40.24</td>\n",
              "      <td>38.70</td>\n",
              "      <td>34.68</td>\n",
              "      <td>38.29</td>\n",
              "      <td>42.95</td>\n",
              "      <td>46.17</td>\n",
              "      <td>49.23</td>\n",
              "      <td>47.09</td>\n",
              "      <td>49.69</td>\n",
              "      <td>49.25</td>\n",
              "      <td>48.95</td>\n",
              "      <td>49.31</td>\n",
              "      <td>51.50</td>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>45.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>096 Hepatite A</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>63.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>021 Tríplice Viral  D1</td>\n",
              "      <td>77.50</td>\n",
              "      <td>88.43</td>\n",
              "      <td>96.92</td>\n",
              "      <td>112.95</td>\n",
              "      <td>110.93</td>\n",
              "      <td>106.55</td>\n",
              "      <td>105.35</td>\n",
              "      <td>106.80</td>\n",
              "      <td>99.81</td>\n",
              "      <td>103.74</td>\n",
              "      <td>99.93</td>\n",
              "      <td>102.39</td>\n",
              "      <td>99.50</td>\n",
              "      <td>107.46</td>\n",
              "      <td>112.80</td>\n",
              "      <td>96.07</td>\n",
              "      <td>95.41</td>\n",
              "      <td>90.85</td>\n",
              "      <td>91.89</td>\n",
              "      <td>57.19</td>\n",
              "      <td>97.99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    Imuno   2000   2001   2002  ...  2017  2018  2019  Total\n",
              "1          073 Hepatite B  91.08  91.88  91.47  ... 86.29 92.91 55.93  94.10\n",
              "2        074 Poliomielite 101.44 102.83 100.01  ... 84.27 88.17 51.54  96.61\n",
              "3       006 Febre Amarela  37.14  40.24  38.70  ... 46.46 58.40 39.91  45.06\n",
              "4          096 Hepatite A    nan    nan    nan  ... 83.05 82.16 52.09  63.73\n",
              "5  021 Tríplice Viral  D1  77.50  88.43  96.92  ... 90.85 91.89 57.19  97.99\n",
              "\n",
              "[5 rows x 22 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "aBzmkBmFkW4A",
        "outputId": "ee92edd8-8fee-47e2-af9b-a7f8583c28c9"
      },
      "source": [
        "#Transformando a coluna 'Imuno' em indice\n",
        "dados_vacina_imuno = dados_vacina_imuno.set_index(\"Imuno\")\n",
        "dados_vacina_imuno.head()"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        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>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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Imuno</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>072 BCG</th>\n",
              "      <td>111.74</td>\n",
              "      <td>112.60</td>\n",
              "      <td>110.28</td>\n",
              "      <td>108.47</td>\n",
              "      <td>113.36</td>\n",
              "      <td>114.48</td>\n",
              "      <td>113.06</td>\n",
              "      <td>111.08</td>\n",
              "      <td>108.91</td>\n",
              "      <td>108.71</td>\n",
              "      <td>106.71</td>\n",
              "      <td>107.94</td>\n",
              "      <td>105.69</td>\n",
              "      <td>107.42</td>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "      <td>104.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>073 Hepatite B</th>\n",
              "      <td>91.08</td>\n",
              "      <td>91.88</td>\n",
              "      <td>91.47</td>\n",
              "      <td>92.00</td>\n",
              "      <td>96.26</td>\n",
              "      <td>98.46</td>\n",
              "      <td>100.30</td>\n",
              "      <td>99.89</td>\n",
              "      <td>96.06</td>\n",
              "      <td>100.20</td>\n",
              "      <td>96.08</td>\n",
              "      <td>97.71</td>\n",
              "      <td>96.67</td>\n",
              "      <td>100.56</td>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>94.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>074 Poliomielite</th>\n",
              "      <td>101.44</td>\n",
              "      <td>102.83</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.48</td>\n",
              "      <td>104.30</td>\n",
              "      <td>105.12</td>\n",
              "      <td>105.25</td>\n",
              "      <td>105.43</td>\n",
              "      <td>100.18</td>\n",
              "      <td>103.66</td>\n",
              "      <td>99.35</td>\n",
              "      <td>101.33</td>\n",
              "      <td>96.55</td>\n",
              "      <td>100.71</td>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>96.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>006 Febre Amarela</th>\n",
              "      <td>37.14</td>\n",
              "      <td>40.24</td>\n",
              "      <td>38.70</td>\n",
              "      <td>34.68</td>\n",
              "      <td>38.29</td>\n",
              "      <td>42.95</td>\n",
              "      <td>46.17</td>\n",
              "      <td>49.23</td>\n",
              "      <td>47.09</td>\n",
              "      <td>49.69</td>\n",
              "      <td>49.25</td>\n",
              "      <td>48.95</td>\n",
              "      <td>49.31</td>\n",
              "      <td>51.50</td>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>45.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>096 Hepatite A</th>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>63.73</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    2000   2001   2002   2003  ...  2017  2018  2019  Total\n",
              "Imuno                                          ...                         \n",
              "072 BCG           111.74 112.60 110.28 108.47  ... 97.12 97.72 52.95 104.96\n",
              "073 Hepatite B     91.08  91.88  91.47  92.00  ... 86.29 92.91 55.93  94.10\n",
              "074 Poliomielite  101.44 102.83 100.01 100.48  ... 84.27 88.17 51.54  96.61\n",
              "006 Febre Amarela  37.14  40.24  38.70  34.68  ... 46.46 58.40 39.91  45.06\n",
              "096 Hepatite A       nan    nan    nan    nan  ... 83.05 82.16 52.09  63.73\n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XEDKv9ausQZJ"
      },
      "source": [
        "A fim de garantir a correta comparação entre os imunos, optei por selecionar os dados de 2014 a 2019, anos que comtemplam dados de todos os imunos selecionados."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "S48zTZOnYqlu",
        "outputId": "5eb3230f-cae2-4b03-de67-68de7728c710"
      },
      "source": [
        "#Selecionando apenas os dados de 2014 a 2019\n",
        "dados_vacina_imuno_selc = dados_vacina_imuno[[\"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\"]]\n",
        "dados_vacina_imuno_selc.head()"
      ],
      "execution_count": 61,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Imuno</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>072 BCG</th>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>073 Hepatite B</th>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>074 Poliomielite</th>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>006 Febre Amarela</th>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>096 Hepatite A</th>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    2014   2015   2016  2017  2018  2019\n",
              "Imuno                                                   \n",
              "072 BCG           107.28 105.08  95.55 97.12 97.72 52.95\n",
              "073 Hepatite B     96.42  97.74 105.19 86.29 92.91 55.93\n",
              "074 Poliomielite   96.76  98.29  84.43 84.27 88.17 51.54\n",
              "006 Febre Amarela  46.86  46.31  44.59 46.46 58.40 39.91\n",
              "096 Hepatite A     60.13  97.07  71.58 83.05 82.16 52.09"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i_EyPydVjKMr"
      },
      "source": [
        "#alterar a forma de mostrar os dados (2 casa após a vírgula)\n",
        "pd.options.display.float_format = \"{:.2f}\".format"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x2kqepzLsv8K"
      },
      "source": [
        "### Cobertura Vacinal total"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "TvBpuc0Xg-xD",
        "outputId": "5977c057-c8c8-45b7-ced6-22d34a155db9"
      },
      "source": [
        "#Criando uma nova coluna 'Total'\n",
        "dados_vacina_imuno_selc[\"Total\"] = dados_vacina_imuno_selc[[\"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\"]].mean(1)\n",
        "dados_vacina_imuno_selc.head()"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Imuno</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>072 BCG</th>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "      <td>92.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>073 Hepatite B</th>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>89.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>074 Poliomielite</th>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>83.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>006 Febre Amarela</th>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>47.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>096 Hepatite A</th>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>74.35</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    2014   2015   2016  2017  2018  2019  Total\n",
              "Imuno                                                          \n",
              "072 BCG           107.28 105.08  95.55 97.12 97.72 52.95  92.62\n",
              "073 Hepatite B     96.42  97.74 105.19 86.29 92.91 55.93  89.08\n",
              "074 Poliomielite   96.76  98.29  84.43 84.27 88.17 51.54  83.91\n",
              "006 Febre Amarela  46.86  46.31  44.59 46.46 58.40 39.91  47.09\n",
              "096 Hepatite A     60.13  97.07  71.58 83.05 82.16 52.09  74.35"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 413
        },
        "id": "-mjresjMNk5-",
        "outputId": "34f2c236-f8ee-437d-f052-bcd1d496f851"
      },
      "source": [
        "#ordenando os dados pelo total\n",
        "dados_vacina_imuno_selc = dados_vacina_imuno_selc.sort_values('Total', ascending = True)\n",
        "\n",
        "#criando a vizualização dos dados totais de cobertura vacinal dos imunos selecionados\n",
        "plt.figure(figsize=(8,6))\n",
        "ax = plt.barh(dados_vacina_imuno_selc.index, dados_vacina_imuno_selc[\"Total\"], height = 0.5, color = \"darkred\")\n",
        "\n",
        "plt.title(\"Dados de Cobertura Vacinal Total por Imuno\", fontsize = 16, fontweight = \"bold\") #título\n",
        "plt.xlabel(\"Cobertura Vacinal %\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Imuno\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.grid(True, color='maroon', alpha=0.5, linestyle='dashed', linewidth=0.5)\n",
        "\n",
        "plt.xlim(0,dados_vacina_imuno_selc[\"Total\"].max()*1.12) #aumentando o limite do eixo x para caber o valor de cada barra sem sobrepor o eixo\n",
        "\n",
        "#rotina para adicionar o número em frente cada barra\n",
        "for index, value in enumerate(dados_vacina_imuno_selc[\"Total\"].round(2)):\n",
        "  plt.text(value, index, str(value), color='black', fontweight=\"bold\", fontsize=12, verticalalignment='center')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XPN9R0zwVZtO"
      },
      "source": [
        "#### Observações:\n",
        "O gráfico mostra que de forma geral, todos os imunos apresentam cobertura vacinal abaixo de 95%, taxa recomendada pelo OMS. Hepatite A e Febre amarela são os imunos com menor taxa de cobertura vacinal, acendendo um alerta sobre possíveis problemas que vão desde a falta de acesso a vacina à falta de disponibilidade da mesma."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VzckRkhiowFg"
      },
      "source": [
        "####Manipulação dos dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "vhfbe6suLsBe",
        "outputId": "bf5b4917-700a-492a-a1e7-be025b8362f8"
      },
      "source": [
        "#removendo os números contidos antes dos nomes dos imunos no indice\n",
        "dados_vacina_imuno_selc.index = dados_vacina_imuno_selc.index.str[3:]\n",
        "dados_vacina_imuno_selc"
      ],
      "execution_count": 65,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Imuno</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>Febre Amarela</th>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>47.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hepatite A</th>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>74.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Poliomielite</th>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>83.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hepatite B</th>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>89.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tríplice Viral  D1</th>\n",
              "      <td>112.80</td>\n",
              "      <td>96.07</td>\n",
              "      <td>95.41</td>\n",
              "      <td>90.85</td>\n",
              "      <td>91.89</td>\n",
              "      <td>57.19</td>\n",
              "      <td>90.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BCG</th>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "      <td>92.62</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014   2015   2016  2017  2018  2019  Total\n",
              "Imuno                                                            \n",
              " Febre Amarela       46.86  46.31  44.59 46.46 58.40 39.91  47.09\n",
              " Hepatite A          60.13  97.07  71.58 83.05 82.16 52.09  74.35\n",
              " Poliomielite        96.76  98.29  84.43 84.27 88.17 51.54  83.91\n",
              " Hepatite B          96.42  97.74 105.19 86.29 92.91 55.93  89.08\n",
              " Tríplice Viral  D1 112.80  96.07  95.41 90.85 91.89 57.19  90.70\n",
              " BCG                107.28 105.08  95.55 97.12 97.72 52.95  92.62"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "IwpqbN9zMQhL",
        "outputId": "a53b67a1-070d-462d-9425-4eeb48a6b021"
      },
      "source": [
        "# verificando o indice usando a função .index pegando o primeiro valor do indice\n",
        "dados_vacina_imuno_selc.index[0]  "
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "' Febre Amarela'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        },
        "id": "QYeShMaFNN1L",
        "outputId": "143bc87b-bca7-4792-c182-b6957fe25f9d"
      },
      "source": [
        "#removendo o espaço que há antes do nome\n",
        "dados_vacina_imuno_selc.index = dados_vacina_imuno_selc.index.str.strip()\n",
        "dados_vacina_imuno_selc"
      ],
      "execution_count": 67,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Imuno</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>Febre Amarela</th>\n",
              "      <td>46.86</td>\n",
              "      <td>46.31</td>\n",
              "      <td>44.59</td>\n",
              "      <td>46.46</td>\n",
              "      <td>58.40</td>\n",
              "      <td>39.91</td>\n",
              "      <td>47.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hepatite A</th>\n",
              "      <td>60.13</td>\n",
              "      <td>97.07</td>\n",
              "      <td>71.58</td>\n",
              "      <td>83.05</td>\n",
              "      <td>82.16</td>\n",
              "      <td>52.09</td>\n",
              "      <td>74.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Poliomielite</th>\n",
              "      <td>96.76</td>\n",
              "      <td>98.29</td>\n",
              "      <td>84.43</td>\n",
              "      <td>84.27</td>\n",
              "      <td>88.17</td>\n",
              "      <td>51.54</td>\n",
              "      <td>83.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hepatite B</th>\n",
              "      <td>96.42</td>\n",
              "      <td>97.74</td>\n",
              "      <td>105.19</td>\n",
              "      <td>86.29</td>\n",
              "      <td>92.91</td>\n",
              "      <td>55.93</td>\n",
              "      <td>89.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tríplice Viral  D1</th>\n",
              "      <td>112.80</td>\n",
              "      <td>96.07</td>\n",
              "      <td>95.41</td>\n",
              "      <td>90.85</td>\n",
              "      <td>91.89</td>\n",
              "      <td>57.19</td>\n",
              "      <td>90.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BCG</th>\n",
              "      <td>107.28</td>\n",
              "      <td>105.08</td>\n",
              "      <td>95.55</td>\n",
              "      <td>97.12</td>\n",
              "      <td>97.72</td>\n",
              "      <td>52.95</td>\n",
              "      <td>92.62</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     2014   2015   2016  2017  2018  2019  Total\n",
              "Imuno                                                           \n",
              "Febre Amarela       46.86  46.31  44.59 46.46 58.40 39.91  47.09\n",
              "Hepatite A          60.13  97.07  71.58 83.05 82.16 52.09  74.35\n",
              "Poliomielite        96.76  98.29  84.43 84.27 88.17 51.54  83.91\n",
              "Hepatite B          96.42  97.74 105.19 86.29 92.91 55.93  89.08\n",
              "Tríplice Viral  D1 112.80  96.07  95.41 90.85 91.89 57.19  90.70\n",
              "BCG                107.28 105.08  95.55 97.12 97.72 52.95  92.62"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yZ5glGVEYcza"
      },
      "source": [
        "### Cobeturas Vacinais por Ano"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 413
        },
        "id": "YzDW9yYPmZei",
        "outputId": "40b87bb5-35d5-4696-fc55-afe23a0ccbce"
      },
      "source": [
        "ax = dados_vacina_imuno_selc[[\"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\"]].T.plot(figsize=(10,6), colormap = 'viridis', )\n",
        "\n",
        "plt.title(\"Cobertura vacinal por Ano segundo Imuno\", fontsize = 16) #Título figura\n",
        "plt.xlabel(\"Ano\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Cobertura Vacinal %\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.ylim(0,120)\n",
        "\n",
        "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
        "plt.axhline(95, linestyle=\"--\", color='red')\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "57le5wJLm5w-"
      },
      "source": [
        "#### Observações\n",
        "Observa-se que os imunos BCG, TRIPLICE VIRAL, HEPATITE B e POLIOMELITE apresentam perfis de cobertura vacinal (CV) acima de 95%, como recomendado pela OMS, até 2015. \n",
        "Após esse período, observa-se uma queda na CV da maioria dos imunos, mantendo apenas BCG dentro da faixa.\n",
        " \n",
        "* Febre amarela aprensenta a menor combertura vacinal (CV) dentre os imunos selecionados, apresentando um pequeno aumento com o passar dos anos, no entanto sem atingir valores muito maiores que o inicial.\n",
        "* Hepatite A, teve sua campanha de  imunização inciada em 2014, o que justifica o grande aumento da CV em 2015. No entanto, a taxa caiu consideravelmente nos anos seguintes, mantendo valores bem abaixo da meta.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MfwyI4PhSj98"
      },
      "source": [
        "##Imuno: Hepatite A\n",
        "\n",
        "A vacinação contra hepatite A iniciou-se em 2014, como uma das ações do Ministério da Saúde contra Hepatites Virais. Neste ano, a cobertura vacinal foi de 60,13 [3].\n",
        "\n",
        "\n",
        "A hepatite A pode ser transmitida por contato direto entre as pessoas, pela água ou por alimentos contaminados, por mãos mal lavadas ou sujas de fezes e por objetos que contenham a presença do vírus [1].\n",
        "\n",
        "O crescente aumento do número de casos tem sido amplamente discutido e preocupado os orgãos de saúde [4, 5].\n",
        "\n",
        "Por ser uma vacina relativamente nova e haver uma discussão a respeito do aumento do número de casos, escolhi explorar um pouco mais os dados desse imuno.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YbkzNDC-WycH"
      },
      "source": [
        "###Cobertura Vacinal"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "VOMPwuXmTOWd",
        "outputId": "8df0266c-9cd4-4fe5-e9f0-c6afb9f9d394"
      },
      "source": [
        "# Importando o banco de dados de cobertura vacinal por ano segundo Unidade da Federação - imuno Hepatite A\n",
        "dados_vacina_hep_A = pd.read_csv('/content/drive/MyDrive/Bootcamp Data Science/Módulo 2/Projeto 2/A160201189_28_143_208_HEPA_CV_UF.csv', encoding=\"ISO-8859-1\", na_values='-',\n",
        "                    skiprows = 4, skipfooter=20, sep=\";\", thousands=\".\", decimal=\",\", engine='python')\n",
        "dados_vacina_hep_A.head()"
      ],
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "        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>Unidade da Federação</th>\n",
              "      <th>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>11 Rondônia</td>\n",
              "      <td>67.33</td>\n",
              "      <td>116.26</td>\n",
              "      <td>84.04</td>\n",
              "      <td>87.45</td>\n",
              "      <td>82.45</td>\n",
              "      <td>52.60</td>\n",
              "      <td>81.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>12 Acre</td>\n",
              "      <td>11.52</td>\n",
              "      <td>73.22</td>\n",
              "      <td>60.42</td>\n",
              "      <td>69.47</td>\n",
              "      <td>76.11</td>\n",
              "      <td>48.41</td>\n",
              "      <td>56.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>13 Amazonas</td>\n",
              "      <td>44.12</td>\n",
              "      <td>97.74</td>\n",
              "      <td>68.07</td>\n",
              "      <td>79.94</td>\n",
              "      <td>78.19</td>\n",
              "      <td>56.47</td>\n",
              "      <td>70.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>14 Roraima</td>\n",
              "      <td>52.93</td>\n",
              "      <td>98.21</td>\n",
              "      <td>72.93</td>\n",
              "      <td>90.29</td>\n",
              "      <td>90.46</td>\n",
              "      <td>52.67</td>\n",
              "      <td>76.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>15 Pará</td>\n",
              "      <td>24.11</td>\n",
              "      <td>73.83</td>\n",
              "      <td>55.85</td>\n",
              "      <td>67.50</td>\n",
              "      <td>66.50</td>\n",
              "      <td>41.59</td>\n",
              "      <td>54.99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Unidade da Federação  2014   2015  2016  2017  2018  2019  Total\n",
              "0          11 Rondônia 67.33 116.26 84.04 87.45 82.45 52.60  81.68\n",
              "1              12 Acre 11.52  73.22 60.42 69.47 76.11 48.41  56.49\n",
              "2          13 Amazonas 44.12  97.74 68.07 79.94 78.19 56.47  70.85\n",
              "3           14 Roraima 52.93  98.21 72.93 90.29 90.46 52.67  76.10\n",
              "4              15 Pará 24.11  73.83 55.85 67.50 66.50 41.59  54.99"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "FwKaZBkJHpXi",
        "outputId": "9df34031-df16-407c-c75c-d87fdca641ce"
      },
      "source": [
        "#Transformando a coluna 'Unidade da Federação' em indice\n",
        "dados_vacina_hep_A = dados_vacina_hep_A.set_index(\"Unidade da Federação\")\n",
        "dados_vacina_hep_A.head()"
      ],
      "execution_count": 70,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>11 Rondônia</th>\n",
              "      <td>67.33</td>\n",
              "      <td>116.26</td>\n",
              "      <td>84.04</td>\n",
              "      <td>87.45</td>\n",
              "      <td>82.45</td>\n",
              "      <td>52.60</td>\n",
              "      <td>81.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Acre</th>\n",
              "      <td>11.52</td>\n",
              "      <td>73.22</td>\n",
              "      <td>60.42</td>\n",
              "      <td>69.47</td>\n",
              "      <td>76.11</td>\n",
              "      <td>48.41</td>\n",
              "      <td>56.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13 Amazonas</th>\n",
              "      <td>44.12</td>\n",
              "      <td>97.74</td>\n",
              "      <td>68.07</td>\n",
              "      <td>79.94</td>\n",
              "      <td>78.19</td>\n",
              "      <td>56.47</td>\n",
              "      <td>70.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14 Roraima</th>\n",
              "      <td>52.93</td>\n",
              "      <td>98.21</td>\n",
              "      <td>72.93</td>\n",
              "      <td>90.29</td>\n",
              "      <td>90.46</td>\n",
              "      <td>52.67</td>\n",
              "      <td>76.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15 Pará</th>\n",
              "      <td>24.11</td>\n",
              "      <td>73.83</td>\n",
              "      <td>55.85</td>\n",
              "      <td>67.50</td>\n",
              "      <td>66.50</td>\n",
              "      <td>41.59</td>\n",
              "      <td>54.99</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014   2015  2016  2017  2018  2019  Total\n",
              "Unidade da Federação                                            \n",
              "11 Rondônia          67.33 116.26 84.04 87.45 82.45 52.60  81.68\n",
              "12 Acre              11.52  73.22 60.42 69.47 76.11 48.41  56.49\n",
              "13 Amazonas          44.12  97.74 68.07 79.94 78.19 56.47  70.85\n",
              "14 Roraima           52.93  98.21 72.93 90.29 90.46 52.67  76.10\n",
              "15 Pará              24.11  73.83 55.85 67.50 66.50 41.59  54.99"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Xm-7agn2vHvZ",
        "outputId": "cae748fe-7988-4d1c-9505-76d74e8aafb2"
      },
      "source": [
        "# Criando uma nova coluna para associar uma região a cada estado.\n",
        "# A partir do indice, foi selecionado apenas o primeiro número para usar como referência para as regiões\n",
        "dados_vacina_hep_A[\"Região\"] = dados_vacina_hep_A.index.str[0]\n",
        "\n",
        "# criando um dicionário que associa a chave 'index'(estados) às correspondentes regiões. \n",
        "regiao_estado = {1:\"Norte\", 2:\"Nordeste\", 3:\"Sudeste\", 4:\"Sul\", 5:\"Centro-Oeste\"}\n",
        "\n",
        "# criando uma função que associa o estado (key) à região (value) e cria a nova coluna.\n",
        "dados_vacina_hep_A[\"Região\"] = dados_vacina_hep_A[\"Região\"].map(lambda x: regiao_estado[int(x)])\n",
        "\n",
        "dados_vacina_hep_A[\"Região\"]"
      ],
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unidade da Federação\n",
              "11 Rondônia                      Norte\n",
              "12 Acre                          Norte\n",
              "13 Amazonas                      Norte\n",
              "14 Roraima                       Norte\n",
              "15 Pará                          Norte\n",
              "16 Amapá                         Norte\n",
              "17 Tocantins                     Norte\n",
              "21 Maranhão                   Nordeste\n",
              "22 Piauí                      Nordeste\n",
              "23 Ceará                      Nordeste\n",
              "24 Rio Grande do Norte        Nordeste\n",
              "25 Paraíba                    Nordeste\n",
              "26 Pernambuco                 Nordeste\n",
              "27 Alagoas                    Nordeste\n",
              "28 Sergipe                    Nordeste\n",
              "29 Bahia                      Nordeste\n",
              "31 Minas Gerais                Sudeste\n",
              "32 Espírito Santo              Sudeste\n",
              "33 Rio de Janeiro              Sudeste\n",
              "35 São Paulo                   Sudeste\n",
              "41 Paraná                          Sul\n",
              "42 Santa Catarina                  Sul\n",
              "43 Rio Grande do Sul               Sul\n",
              "50 Mato Grosso do Sul     Centro-Oeste\n",
              "51 Mato Grosso            Centro-Oeste\n",
              "52 Goiás                  Centro-Oeste\n",
              "53 Distrito Federal       Centro-Oeste\n",
              "Name: Região, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "qNYkY6BfvrMW",
        "outputId": "62e85e08-bdb9-4d2a-e464-023185fcf4a2"
      },
      "source": [
        "dados_vacina_hep_A.head()"
      ],
      "execution_count": 72,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "      <th>Região</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>11 Rondônia</th>\n",
              "      <td>67.33</td>\n",
              "      <td>116.26</td>\n",
              "      <td>84.04</td>\n",
              "      <td>87.45</td>\n",
              "      <td>82.45</td>\n",
              "      <td>52.60</td>\n",
              "      <td>81.68</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Acre</th>\n",
              "      <td>11.52</td>\n",
              "      <td>73.22</td>\n",
              "      <td>60.42</td>\n",
              "      <td>69.47</td>\n",
              "      <td>76.11</td>\n",
              "      <td>48.41</td>\n",
              "      <td>56.49</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13 Amazonas</th>\n",
              "      <td>44.12</td>\n",
              "      <td>97.74</td>\n",
              "      <td>68.07</td>\n",
              "      <td>79.94</td>\n",
              "      <td>78.19</td>\n",
              "      <td>56.47</td>\n",
              "      <td>70.85</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14 Roraima</th>\n",
              "      <td>52.93</td>\n",
              "      <td>98.21</td>\n",
              "      <td>72.93</td>\n",
              "      <td>90.29</td>\n",
              "      <td>90.46</td>\n",
              "      <td>52.67</td>\n",
              "      <td>76.10</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15 Pará</th>\n",
              "      <td>24.11</td>\n",
              "      <td>73.83</td>\n",
              "      <td>55.85</td>\n",
              "      <td>67.50</td>\n",
              "      <td>66.50</td>\n",
              "      <td>41.59</td>\n",
              "      <td>54.99</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014   2015  2016  2017  2018  2019  Total Região\n",
              "Unidade da Federação                                                   \n",
              "11 Rondônia          67.33 116.26 84.04 87.45 82.45 52.60  81.68  Norte\n",
              "12 Acre              11.52  73.22 60.42 69.47 76.11 48.41  56.49  Norte\n",
              "13 Amazonas          44.12  97.74 68.07 79.94 78.19 56.47  70.85  Norte\n",
              "14 Roraima           52.93  98.21 72.93 90.29 90.46 52.67  76.10  Norte\n",
              "15 Pará              24.11  73.83 55.85 67.50 66.50 41.59  54.99  Norte"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "naRjweSyHEfa"
      },
      "source": [
        "#removendo os numeros contidos antes dos nomes dos imunos no indice\n",
        "dados_vacina_hep_A.index = dados_vacina_hep_A.index.str[3:]"
      ],
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_iDMUjIaH5Xy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "a91e2ccc-7470-4ef0-9cb3-6132eda28ff9"
      },
      "source": [
        "#removendo o espaço que há antes do nome\n",
        "dados_vacina_hep_A.index = dados_vacina_hep_A.index.str.strip()\n",
        "dados_vacina_hep_A.head()"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "      <th>Região</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Rondônia</th>\n",
              "      <td>67.33</td>\n",
              "      <td>116.26</td>\n",
              "      <td>84.04</td>\n",
              "      <td>87.45</td>\n",
              "      <td>82.45</td>\n",
              "      <td>52.60</td>\n",
              "      <td>81.68</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Acre</th>\n",
              "      <td>11.52</td>\n",
              "      <td>73.22</td>\n",
              "      <td>60.42</td>\n",
              "      <td>69.47</td>\n",
              "      <td>76.11</td>\n",
              "      <td>48.41</td>\n",
              "      <td>56.49</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>44.12</td>\n",
              "      <td>97.74</td>\n",
              "      <td>68.07</td>\n",
              "      <td>79.94</td>\n",
              "      <td>78.19</td>\n",
              "      <td>56.47</td>\n",
              "      <td>70.85</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Roraima</th>\n",
              "      <td>52.93</td>\n",
              "      <td>98.21</td>\n",
              "      <td>72.93</td>\n",
              "      <td>90.29</td>\n",
              "      <td>90.46</td>\n",
              "      <td>52.67</td>\n",
              "      <td>76.10</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pará</th>\n",
              "      <td>24.11</td>\n",
              "      <td>73.83</td>\n",
              "      <td>55.85</td>\n",
              "      <td>67.50</td>\n",
              "      <td>66.50</td>\n",
              "      <td>41.59</td>\n",
              "      <td>54.99</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014   2015  2016  2017  2018  2019  Total Região\n",
              "Unidade da Federação                                                   \n",
              "Rondônia             67.33 116.26 84.04 87.45 82.45 52.60  81.68  Norte\n",
              "Acre                 11.52  73.22 60.42 69.47 76.11 48.41  56.49  Norte\n",
              "Amazonas             44.12  97.74 68.07 79.94 78.19 56.47  70.85  Norte\n",
              "Roraima              52.93  98.21 72.93 90.29 90.46 52.67  76.10  Norte\n",
              "Pará                 24.11  73.83 55.85 67.50 66.50 41.59  54.99  Norte"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5SRf4H0NNJme",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 648
        },
        "outputId": "96dd875b-2935-44e7-e46e-e9afccc4a301"
      },
      "source": [
        "#ordenando os dados pelo total\n",
        "dados_vacina_hep_A = dados_vacina_hep_A.sort_values('Total', ascending = True)\n",
        "\n",
        "#criando a vizualização dos dados totais de cobertura vacinal de hepatite A\n",
        "plt.figure(figsize=(8,10))\n",
        "ax = plt.barh(dados_vacina_hep_A.index, dados_vacina_hep_A[\"Total\"], height = 0.5, color = \"maroon\")\n",
        "\n",
        "plt.title(\"Dados de Cobertura Vacinal de Hepaptite A \\n por Unidade da Federação\", fontsize = 16, fontweight = \"bold\") #título\n",
        "plt.xlabel(\"Cobertura Vacinal %\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Unidade da Federação\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.grid(True, color='brown', alpha=0.5, linestyle='dashed', linewidth=0.5)\n",
        "\n",
        "plt.xlim(0,dados_vacina_hep_A[\"Total\"].max()*1.12) #aumentando o limite do eixo x para caber o valor de cada barra sem sobrepor o eixo\n",
        "\n",
        "#rotina para adicionar o número em frente cada barra\n",
        "for index, value in enumerate(dados_vacina_hep_A[\"Total\"].round(2)):\n",
        "  plt.text(value, index, str(value), color='black', fontweight=\"bold\", fontsize=12, verticalalignment='center')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I_n94xS8w2iM"
      },
      "source": [
        "O gráfico mostra que todos as unidades federativas apresentam coberturas vacinais abaixo de 90%, como estados como Acre e Pará, apresentando taxas pouco maiores que 50%. \n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PLiv7tuWunVY"
      },
      "source": [
        "#construindo um novo Dataframe sem a coluna \"Total\"\n",
        "dados_vacina_hep_A_uso = dados_vacina_hep_A.drop(\"Total\", axis=1) "
      ],
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6NX-dDeD8kPj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "outputId": "0cbeafc5-7ee9-47ad-96ff-2489a49ea5bd"
      },
      "source": [
        "#visualizando os dados de cobertura vacinal segundo UF no período de 2014 a 2019\n",
        "ax = dados_vacina_hep_A_uso[[\"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\"]].T.plot(figsize=(10,6), colormap = 'copper')\n",
        "\n",
        "plt.title(\"Dados de Cobertura Vacinal por Ano \\n segundo Unidade da Federação\", fontsize = 16) #Título figura\n",
        "plt.xlabel(\"Ano\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Cobertura Vacinal %\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.ylim(0,120) #definindo limites do eixo y\n",
        "plt.axhline(95, linestyle=\"--\", color='red') #construindo linha indicativa de taxa de 75%\n",
        "\n",
        "\n",
        "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5)) #posicionando a legenda\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jNvXSgpCCVEL"
      },
      "source": [
        "Apesar das diferenças nas coberturas vacinais, o gráfico mostra que todas as UF's apresentaram o mesmo perfil no decorrer dos anos, mantendo as taxas de cobertura vacinal abaixo do recomendado desde 2016. Essa semelhança nos perfis levanta da hipótese de que os fatores que influenciaram no aumento ou redução da cobertura vacinal foi comum para todas as Unidades Federativas."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dEnrPn1iy6kN"
      },
      "source": [
        "#### Cobertura Vacinal por Região"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6AzoqaoBNc02",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "80d4bc88-5767-4311-ab47-db8648eae5ac"
      },
      "source": [
        "dados_vacina_hep_A.head()"
      ],
      "execution_count": 78,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Total</th>\n",
              "      <th>Região</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Pará</th>\n",
              "      <td>24.11</td>\n",
              "      <td>73.83</td>\n",
              "      <td>55.85</td>\n",
              "      <td>67.50</td>\n",
              "      <td>66.50</td>\n",
              "      <td>41.59</td>\n",
              "      <td>54.99</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Acre</th>\n",
              "      <td>11.52</td>\n",
              "      <td>73.22</td>\n",
              "      <td>60.42</td>\n",
              "      <td>69.47</td>\n",
              "      <td>76.11</td>\n",
              "      <td>48.41</td>\n",
              "      <td>56.49</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maranhão</th>\n",
              "      <td>43.49</td>\n",
              "      <td>91.82</td>\n",
              "      <td>56.54</td>\n",
              "      <td>72.03</td>\n",
              "      <td>69.80</td>\n",
              "      <td>46.01</td>\n",
              "      <td>63.25</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rio Grande do Norte</th>\n",
              "      <td>41.17</td>\n",
              "      <td>87.97</td>\n",
              "      <td>63.17</td>\n",
              "      <td>66.93</td>\n",
              "      <td>76.86</td>\n",
              "      <td>44.84</td>\n",
              "      <td>63.45</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>38.02</td>\n",
              "      <td>88.47</td>\n",
              "      <td>87.09</td>\n",
              "      <td>69.18</td>\n",
              "      <td>68.17</td>\n",
              "      <td>47.09</td>\n",
              "      <td>66.77</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  2016  2017  2018  2019  Total    Região\n",
              "Unidade da Federação                                                     \n",
              "Pará                 24.11 73.83 55.85 67.50 66.50 41.59  54.99     Norte\n",
              "Acre                 11.52 73.22 60.42 69.47 76.11 48.41  56.49     Norte\n",
              "Maranhão             43.49 91.82 56.54 72.03 69.80 46.01  63.25  Nordeste\n",
              "Rio Grande do Norte  41.17 87.97 63.17 66.93 76.86 44.84  63.45  Nordeste\n",
              "Amapá                38.02 88.47 87.09 69.18 68.17 47.09  66.77     Norte"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8BVDF8glwBwX"
      },
      "source": [
        "# calculando o valor médio da cobertura vacinal por região\n",
        "norte = dados_vacina_hep_A.query(\"Região == 'Norte'\")[\"Total\"].mean()\n",
        "sul = dados_vacina_hep_A.query(\"Região == 'Sul'\")[\"Total\"].mean()\n",
        "sudeste = dados_vacina_hep_A.query(\"Região == 'Sudeste'\")[\"Total\"].mean()\n",
        "centro_oeste = dados_vacina_hep_A.query(\"Região == 'Centro-Oeste'\")[\"Total\"].mean()\n",
        "nordeste = dados_vacina_hep_A.query(\"Região == 'Nordeste'\")[\"Total\"].mean()"
      ],
      "execution_count": 79,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_HjJPitjwOxP"
      },
      "source": [
        "# criando um dicionário para associar região e cobertura vacinal\n",
        "dados_cv_hep_A_regiao = {'Região': [\"Norte\", \"Sul\", \"Sudeste\", \"Centro-Oeste\", \"Nordeste\"], 'Cobertura Vacinal': [norte, sul, sudeste, centro_oeste, nordeste]}"
      ],
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yZUO4p_UwvnX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "f5d1fe26-62e8-4723-e4d6-8c2500795b5d"
      },
      "source": [
        "# Criando um novo DataFrame com a região e a cobertura vacinal\n",
        "dados_cv_por_regiao = pd.DataFrame(data=dados_cv_hep_A_regiao)\n",
        "dados_cv_por_regiao = dados_cv_por_regiao.sort_values('Cobertura Vacinal', ascending = False)\n",
        "dados_cv_por_regiao"
      ],
      "execution_count": 81,
      "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>Região</th>\n",
              "      <th>Cobertura Vacinal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>79.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>79.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>77.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>71.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>68.89</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Cobertura Vacinal\n",
              "3  Centro-Oeste              79.76\n",
              "1           Sul              79.54\n",
              "2       Sudeste              77.37\n",
              "4      Nordeste              71.32\n",
              "0         Norte              68.89"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_G98T1yNy33Y",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "outputId": "e62565ca-ef8c-4c6d-ba3d-af7c22b326eb"
      },
      "source": [
        "#criando a vizualização dos dados totais de cobertura vacinal de hepatite A por Região\n",
        "\n",
        "plt.figure(figsize=(10, 7))\n",
        "ax = plt.bar(dados_cv_por_regiao[\"Região\"], dados_cv_por_regiao[\"Cobertura Vacinal\"], color = \"firebrick\")\n",
        "\n",
        "plt.title(\"Cobertura Vacinal de Hepatite A por Região brasileira\", fontsize = 16, fontweight = \"bold\") #título\n",
        "#plt.xlabel(\"Região\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Cobertura Vacinal %\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.axhline(80, linestyle=\"--\", color='red') #construindo linha indicativa de taxa de 95%\n",
        "plt.ylim(0, 100)\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "30OKK2eqhwKB"
      },
      "source": [
        "#### Observações:\n",
        "O gráfico mostra que em termos gerais Centro-oeste e Sul são as região com maior cobetura vacinal e, ainda assim, com taxa de pouco abaixo de 80%. A região Norte é a que apresenta menor taxa."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qa_SHdMLKE2e"
      },
      "source": [
        "### Número de casos de hepatite A"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xK1SavLw6cZ0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "85ff51d0-8185-4d42-c838-0731d4848ee1"
      },
      "source": [
        "#Importando o banco de dados de número de casos de hepatite A  por ano segundo unidade da Federação\n",
        "dados_casos_hep_A = pd.read_excel('/content/drive/MyDrive/Bootcamp Data Science/Módulo 2/Projeto 2/dados_compilados_casos_hepatite_a.xlsx')\n",
        "dados_casos_hep_A.head()"
      ],
      "execution_count": 83,
      "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>Unidade da Federação</th>\n",
              "      <th>Total</th>\n",
              "      <th>1999-2006</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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Acre</td>\n",
              "      <td>4583</td>\n",
              "      <td>2306</td>\n",
              "      <td>224</td>\n",
              "      <td>111</td>\n",
              "      <td>74</td>\n",
              "      <td>108</td>\n",
              "      <td>402</td>\n",
              "      <td>641</td>\n",
              "      <td>304</td>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alagoas</td>\n",
              "      <td>4024</td>\n",
              "      <td>1855</td>\n",
              "      <td>233</td>\n",
              "      <td>390</td>\n",
              "      <td>292</td>\n",
              "      <td>230</td>\n",
              "      <td>337</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Amapá</td>\n",
              "      <td>4264</td>\n",
              "      <td>2210</td>\n",
              "      <td>121</td>\n",
              "      <td>171</td>\n",
              "      <td>168</td>\n",
              "      <td>252</td>\n",
              "      <td>340</td>\n",
              "      <td>224</td>\n",
              "      <td>91</td>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Amazonas</td>\n",
              "      <td>14245</td>\n",
              "      <td>7751</td>\n",
              "      <td>519</td>\n",
              "      <td>780</td>\n",
              "      <td>956</td>\n",
              "      <td>708</td>\n",
              "      <td>795</td>\n",
              "      <td>521</td>\n",
              "      <td>660</td>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Bahia</td>\n",
              "      <td>9263</td>\n",
              "      <td>5022</td>\n",
              "      <td>764</td>\n",
              "      <td>593</td>\n",
              "      <td>848</td>\n",
              "      <td>411</td>\n",
              "      <td>316</td>\n",
              "      <td>191</td>\n",
              "      <td>345</td>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Unidade da Federação  Total  1999-2006  2007  ...  2016  2017  2018  2019\n",
              "0                 Acre   4583       2306   224  ...    62    39    14    12\n",
              "1              Alagoas   4024       1855   233  ...    45    25     8     6\n",
              "2                Amapá   4264       2210   121  ...    44    37    17     3\n",
              "3             Amazonas  14245       7751   519  ...    69    56    59    29\n",
              "4                Bahia   9263       5022   764  ...    60    55    40    14\n",
              "\n",
              "[5 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iTPqnTN_Iij-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "266ee8a6-e4a5-4e9c-9f9f-be652c7f767b"
      },
      "source": [
        "#Transformando a coluna 'Unidade da Federação' em indice\n",
        "dados_casos_hep_A = dados_casos_hep_A.set_index(\"Unidade da Federação\")\n",
        "dados_casos_hep_A.head()"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "\n",
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              "    }\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>Total</th>\n",
              "      <th>1999-2006</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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>4583</td>\n",
              "      <td>2306</td>\n",
              "      <td>224</td>\n",
              "      <td>111</td>\n",
              "      <td>74</td>\n",
              "      <td>108</td>\n",
              "      <td>402</td>\n",
              "      <td>641</td>\n",
              "      <td>304</td>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>4024</td>\n",
              "      <td>1855</td>\n",
              "      <td>233</td>\n",
              "      <td>390</td>\n",
              "      <td>292</td>\n",
              "      <td>230</td>\n",
              "      <td>337</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>4264</td>\n",
              "      <td>2210</td>\n",
              "      <td>121</td>\n",
              "      <td>171</td>\n",
              "      <td>168</td>\n",
              "      <td>252</td>\n",
              "      <td>340</td>\n",
              "      <td>224</td>\n",
              "      <td>91</td>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>14245</td>\n",
              "      <td>7751</td>\n",
              "      <td>519</td>\n",
              "      <td>780</td>\n",
              "      <td>956</td>\n",
              "      <td>708</td>\n",
              "      <td>795</td>\n",
              "      <td>521</td>\n",
              "      <td>660</td>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>9263</td>\n",
              "      <td>5022</td>\n",
              "      <td>764</td>\n",
              "      <td>593</td>\n",
              "      <td>848</td>\n",
              "      <td>411</td>\n",
              "      <td>316</td>\n",
              "      <td>191</td>\n",
              "      <td>345</td>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Total  1999-2006  2007  2008  ...  2016  2017  2018  2019\n",
              "Unidade da Federação                                ...                        \n",
              "Acre                   4583       2306   224   111  ...    62    39    14    12\n",
              "Alagoas                4024       1855   233   390  ...    45    25     8     6\n",
              "Amapá                  4264       2210   121   171  ...    44    37    17     3\n",
              "Amazonas              14245       7751   519   780  ...    69    56    59    29\n",
              "Bahia                  9263       5022   764   593  ...    60    55    40    14\n",
              "\n",
              "[5 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CcWxlu_N0vvL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "3fb59d2c-e260-4c1c-a927-f7bed440f7b3"
      },
      "source": [
        "#criando novo dataset sem as colunas 'Total' e '1999-2006'\n",
        "dados_casos_hep_A_uso = dados_casos_hep_A.drop(\"Total\", axis=1)\n",
        "dados_casos_hep_A_uso = dados_casos_hep_A_uso.drop(\"1999-2006\", axis=1)\n",
        "dados_casos_hep_A_uso.head()"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>224</td>\n",
              "      <td>111</td>\n",
              "      <td>74</td>\n",
              "      <td>108</td>\n",
              "      <td>402</td>\n",
              "      <td>641</td>\n",
              "      <td>304</td>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>233</td>\n",
              "      <td>390</td>\n",
              "      <td>292</td>\n",
              "      <td>230</td>\n",
              "      <td>337</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>121</td>\n",
              "      <td>171</td>\n",
              "      <td>168</td>\n",
              "      <td>252</td>\n",
              "      <td>340</td>\n",
              "      <td>224</td>\n",
              "      <td>91</td>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>519</td>\n",
              "      <td>780</td>\n",
              "      <td>956</td>\n",
              "      <td>708</td>\n",
              "      <td>795</td>\n",
              "      <td>521</td>\n",
              "      <td>660</td>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>764</td>\n",
              "      <td>593</td>\n",
              "      <td>848</td>\n",
              "      <td>411</td>\n",
              "      <td>316</td>\n",
              "      <td>191</td>\n",
              "      <td>345</td>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2007  2008  2009  2010  ...  2016  2017  2018  2019\n",
              "Unidade da Federação                          ...                        \n",
              "Acre                   224   111    74   108  ...    62    39    14    12\n",
              "Alagoas                233   390   292   230  ...    45    25     8     6\n",
              "Amapá                  121   171   168   252  ...    44    37    17     3\n",
              "Amazonas               519   780   956   708  ...    69    56    59    29\n",
              "Bahia                  764   593   848   411  ...    60    55    40    14\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6dz9nLvyS7v5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "b04376e2-059d-4a83-dd56-adceb0fc4900"
      },
      "source": [
        "#Ordenando os dados pela em ordem alfabetica pela unidade da federação\n",
        "dados_casos_hep_A_uso = dados_casos_hep_A_uso.sort_values('Unidade da Federação', ascending = True)\n",
        "dados_casos_hep_A_uso.head()"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>224</td>\n",
              "      <td>111</td>\n",
              "      <td>74</td>\n",
              "      <td>108</td>\n",
              "      <td>402</td>\n",
              "      <td>641</td>\n",
              "      <td>304</td>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>233</td>\n",
              "      <td>390</td>\n",
              "      <td>292</td>\n",
              "      <td>230</td>\n",
              "      <td>337</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>121</td>\n",
              "      <td>171</td>\n",
              "      <td>168</td>\n",
              "      <td>252</td>\n",
              "      <td>340</td>\n",
              "      <td>224</td>\n",
              "      <td>91</td>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>519</td>\n",
              "      <td>780</td>\n",
              "      <td>956</td>\n",
              "      <td>708</td>\n",
              "      <td>795</td>\n",
              "      <td>521</td>\n",
              "      <td>660</td>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>764</td>\n",
              "      <td>593</td>\n",
              "      <td>848</td>\n",
              "      <td>411</td>\n",
              "      <td>316</td>\n",
              "      <td>191</td>\n",
              "      <td>345</td>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2007  2008  2009  2010  ...  2016  2017  2018  2019\n",
              "Unidade da Federação                          ...                        \n",
              "Acre                   224   111    74   108  ...    62    39    14    12\n",
              "Alagoas                233   390   292   230  ...    45    25     8     6\n",
              "Amapá                  121   171   168   252  ...    44    37    17     3\n",
              "Amazonas               519   780   956   708  ...    69    56    59    29\n",
              "Bahia                  764   593   848   411  ...    60    55    40    14\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VZ8EwTeqTRAy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "b5a8769c-676b-407a-e4e5-2c536b3c455a"
      },
      "source": [
        "#criando nova coluna com a Região a que cada estado pertence\n",
        "dados_casos_hep_A_uso['Região'] = dados_vacina_hep_A[\"Região\"]\n",
        "dados_casos_hep_A_uso.head()"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></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",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>224</td>\n",
              "      <td>111</td>\n",
              "      <td>74</td>\n",
              "      <td>108</td>\n",
              "      <td>402</td>\n",
              "      <td>641</td>\n",
              "      <td>304</td>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>233</td>\n",
              "      <td>390</td>\n",
              "      <td>292</td>\n",
              "      <td>230</td>\n",
              "      <td>337</td>\n",
              "      <td>148</td>\n",
              "      <td>203</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>121</td>\n",
              "      <td>171</td>\n",
              "      <td>168</td>\n",
              "      <td>252</td>\n",
              "      <td>340</td>\n",
              "      <td>224</td>\n",
              "      <td>91</td>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>519</td>\n",
              "      <td>780</td>\n",
              "      <td>956</td>\n",
              "      <td>708</td>\n",
              "      <td>795</td>\n",
              "      <td>521</td>\n",
              "      <td>660</td>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>764</td>\n",
              "      <td>593</td>\n",
              "      <td>848</td>\n",
              "      <td>411</td>\n",
              "      <td>316</td>\n",
              "      <td>191</td>\n",
              "      <td>345</td>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2007  2008  2009  2010  ...  2017  2018  2019    Região\n",
              "Unidade da Federação                          ...                            \n",
              "Acre                   224   111    74   108  ...    39    14    12     Norte\n",
              "Alagoas                233   390   292   230  ...    25     8     6  Nordeste\n",
              "Amapá                  121   171   168   252  ...    37    17     3     Norte\n",
              "Amazonas               519   780   956   708  ...    56    59    29     Norte\n",
              "Bahia                  764   593   848   411  ...    55    40    14  Nordeste\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BJzsijQ8UQ2-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "43a92637-ad3b-4db9-a5f5-2fd175482040"
      },
      "source": [
        "#selecionando apenas os dados de 2014 a 2019\n",
        "dados_casos_hep_A_uso_selc = dados_casos_hep_A_uso[[2014, 2015, 2016, 2017, 2018, 2019, \"Região\"]]\n",
        "dados_casos_hep_A_uso_selc.head()"
      ],
      "execution_count": 88,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "      <td>Nordeste</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  2016  2017  2018  2019    Região\n",
              "Unidade da Federação                                              \n",
              "Acre                   190    96    62    39    14    12     Norte\n",
              "Alagoas                143   109    45    25     8     6  Nordeste\n",
              "Amapá                  376   210    44    37    17     3     Norte\n",
              "Amazonas               940   402    69    56    59    29     Norte\n",
              "Bahia                  476   128    60    55    40    14  Nordeste"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j9trxZM0VBwO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "outputId": "d70c6933-4bda-48c5-a730-dd575d1d3c8d"
      },
      "source": [
        "#criando uma nova coluna Total\n",
        "dados_casos_hep_A_uso_selc[\"Total\"] = dados_casos_hep_A_uso_selc[[2014, 2015, 2016, 2017, 2018, 2019]].sum(1)\n",
        "dados_casos_hep_A_uso_selc.head()"
      ],
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "      <th>Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>Norte</td>\n",
              "      <td>413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>336</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>Norte</td>\n",
              "      <td>687</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "      <td>1555</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>773</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  2016  2017  2018  2019    Região  Total\n",
              "Unidade da Federação                                                     \n",
              "Acre                   190    96    62    39    14    12     Norte    413\n",
              "Alagoas                143   109    45    25     8     6  Nordeste    336\n",
              "Amapá                  376   210    44    37    17     3     Norte    687\n",
              "Amazonas               940   402    69    56    59    29     Norte   1555\n",
              "Bahia                  476   128    60    55    40    14  Nordeste    773"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FPbRbdQTaIXm"
      },
      "source": [
        "#### Proporção por cem mil habitantes"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_D0cidTldp0j",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fdc69b26-14ca-4bae-8ba1-36e5a57da90e"
      },
      "source": [
        "dados_casos_hep_A_uso_selc.index"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Acre', 'Alagoas', 'Amapá', 'Amazonas', 'Bahia', 'Ceará',\n",
              "       'Distrito Federal', 'Espírito Santo', 'Goiás', 'Maranhão',\n",
              "       'Mato Grosso', 'Mato Grosso do Sul', 'Minas Gerais', 'Paraná',\n",
              "       'Paraíba', 'Pará', 'Pernambuco', 'Piauí', 'Rio Grande do Norte',\n",
              "       'Rio Grande do Sul', 'Rio de Janeiro', 'Rondônia', 'Roraima',\n",
              "       'Santa Catarina', 'Sergipe', 'São Paulo', 'Tocantins'],\n",
              "      dtype='object', name='Unidade da Federação')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e79Gk7Wnr-nA"
      },
      "source": [
        "# criando uma lista com a população de cada UF\n",
        "UF_habitantes = [4064052, 2318822, 3534165, 3055149, 3281480, 2809394, 7113540, 9187103, 1796460, 631181, 3351543, 7252502, 4039277, 11516840, 894470, 7114598, 11422973, 3526220, 1590248, 9616621, 861773, 21292666, 14930634, 8690745, 17366189, 4207714, 46289333]"
      ],
      "execution_count": 91,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "36_Sjeo8uvj1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "outputId": "04c600f5-3845-4525-a306-06760212ea77"
      },
      "source": [
        "# criando uma nova coluna com o número de habitantes de cada UF\n",
        "dados_casos_hep_A_uso_selc['Habitantes'] = UF_habitantes\n",
        "dados_casos_hep_A_uso_selc.head()"
      ],
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "      <th>Total</th>\n",
              "      <th>Habitantes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>Norte</td>\n",
              "      <td>413</td>\n",
              "      <td>4064052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>336</td>\n",
              "      <td>2318822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>Norte</td>\n",
              "      <td>687</td>\n",
              "      <td>3534165</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "      <td>1555</td>\n",
              "      <td>3055149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>773</td>\n",
              "      <td>3281480</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  2016  2017  ...  2019    Região Total  Habitantes\n",
              "Unidade da Federação                          ...                                  \n",
              "Acre                   190    96    62    39  ...    12     Norte   413     4064052\n",
              "Alagoas                143   109    45    25  ...     6  Nordeste   336     2318822\n",
              "Amapá                  376   210    44    37  ...     3     Norte   687     3534165\n",
              "Amazonas               940   402    69    56  ...    29     Norte  1555     3055149\n",
              "Bahia                  476   128    60    55  ...    14  Nordeste   773     3281480\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_ILQMR53wP32"
      },
      "source": [
        "#transformando os números de caso de hepatite A em nº de casos por milhão de habitantes.\n",
        "casos_por_milhao = (dados_casos_hep_A_uso_selc[\"Total\"] * 100000) / dados_casos_hep_A_uso_selc[\"Habitantes\"]"
      ],
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rt9VRnlKwb2M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "outputId": "60173e3b-5aa4-49b1-a8d6-c175e974a000"
      },
      "source": [
        "#criando uma nova coluna com o n° de casos por milhão\n",
        "dados_casos_hep_A_uso_selc[\"Casos por cem mil habitantes\"] = casos_por_milhao\n",
        "dados_casos_hep_A_uso_selc.head()"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "      <th>Total</th>\n",
              "      <th>Habitantes</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Acre</th>\n",
              "      <td>190</td>\n",
              "      <td>96</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>14</td>\n",
              "      <td>12</td>\n",
              "      <td>Norte</td>\n",
              "      <td>413</td>\n",
              "      <td>4064052</td>\n",
              "      <td>10.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alagoas</th>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>336</td>\n",
              "      <td>2318822</td>\n",
              "      <td>14.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amapá</th>\n",
              "      <td>376</td>\n",
              "      <td>210</td>\n",
              "      <td>44</td>\n",
              "      <td>37</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>Norte</td>\n",
              "      <td>687</td>\n",
              "      <td>3534165</td>\n",
              "      <td>19.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "      <td>1555</td>\n",
              "      <td>3055149</td>\n",
              "      <td>50.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahia</th>\n",
              "      <td>476</td>\n",
              "      <td>128</td>\n",
              "      <td>60</td>\n",
              "      <td>55</td>\n",
              "      <td>40</td>\n",
              "      <td>14</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>773</td>\n",
              "      <td>3281480</td>\n",
              "      <td>23.56</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  ...  Habitantes  Casos por cem mil habitantes\n",
              "Unidade da Federação              ...                                          \n",
              "Acre                   190    96  ...     4064052                         10.16\n",
              "Alagoas                143   109  ...     2318822                         14.49\n",
              "Amapá                  376   210  ...     3534165                         19.44\n",
              "Amazonas               940   402  ...     3055149                         50.90\n",
              "Bahia                  476   128  ...     3281480                         23.56\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ef95quiHzITQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 726
        },
        "outputId": "30cd34fd-b2c3-47dd-affa-4bc8b71d4ac4"
      },
      "source": [
        "#ordenando os dados pelo total\n",
        "dados_casos_hep_A_uso_selc = dados_casos_hep_A_uso_selc.sort_values('Casos por cem mil habitantes', ascending = True)\n",
        "\n",
        "#CriANdo a figura\n",
        "plt.figure(figsize=(14,10))\n",
        "plt.suptitle(\"Número de casos de Hepatite A por Unidade da Federação - 2014 a 2019\", fontsize = 16, fontweight = \"bold\")\n",
        "\n",
        "#Gráfico 1 - número total de casos\n",
        "#criando a vizualização dos dados de número de casos total\n",
        "ax = plt.subplot(1,2,1)\n",
        "plt.barh(dados_casos_hep_A_uso_selc.index, dados_casos_hep_A_uso_selc[\"Total\"], height = 0.5, color = \"brown\")\n",
        "\n",
        "plt.title(\"Número Total de Casos\", fontsize = 15, fontweight = \"bold\") #título\n",
        "plt.xlabel(\"Casos\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Unidade da Federação\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.grid(True, color='brown', alpha=0.5, linestyle='dashed', linewidth=0.5)\n",
        "\n",
        "plt.xlim(0,dados_casos_hep_A_uso_selc[\"Total\"].max()*1.12) #aumentando o limite do eixo x para caber o valor de cada barra sem sobrepor o eixo\n",
        "\n",
        "#rotina para adicionar o número em frente cada barra\n",
        "for index, value in enumerate(dados_casos_hep_A_uso_selc[\"Total\"].round(2)):\n",
        "  plt.text(value, index, str(value), color='black', fontweight=\"bold\", fontsize=12, verticalalignment='center')\n",
        "\n",
        "\n",
        "#ordenando os dados pelo total\n",
        "dados_casos_hep_A_uso_selc = dados_casos_hep_A_uso_selc.sort_values('Casos por cem mil habitantes', ascending = True)\n",
        "\n",
        "#Gráfico 2 - número de casos proporcional ao número de habitantes\n",
        "#criando a vizualização dos dados de número de casos por cem mil habitantes\n",
        "ax = plt.subplot(1,2,2)\n",
        "plt.barh(dados_casos_hep_A_uso_selc.index, dados_casos_hep_A_uso_selc[\"Casos por cem mil habitantes\"], height = 0.5, color = \"brown\")\n",
        "\n",
        "plt.title(\"Número de casos \\n por cem mil habitantes\", fontsize = 15, fontweight = \"bold\") #título\n",
        "plt.xlabel(\"Casos por cem mil habitantes\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Unidade da Federação\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.grid(True, color='brown', alpha=0.5, linestyle='dashed', linewidth=0.5)\n",
        "\n",
        "plt.xlim(0,dados_casos_hep_A_uso_selc[\"Casos por cem mil habitantes\"].max()*1.2) #aumentando o limite do eixo x para caber o valor de cada barra sem sobrepor o eixo\n",
        "\n",
        "#rotina para adicionar o número em frente cada barra\n",
        "for index, value in enumerate(dados_casos_hep_A_uso_selc[\"Casos por cem mil habitantes\"].round(2)):\n",
        "  plt.text(value, index, str(value), color='black', fontweight=\"bold\", fontsize=12, verticalalignment='center')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.subplots_adjust(top=0.90)\n",
        "plt.show()"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lOMxff4LMqI4/sulq6/nyosH5ABDuO0cCo/AvG1bjRyLeGgWbmeNQwyhbrJFuNBdG4N+UHk7uIU2ro/34gXNAAXGvK9AtJq5k+uZ4+BJ+uHk2uR6ek7g6hgVoErbJk1428TdF+2b55VrttKHaE+JKuLZvTsdDe48D2oa4N2noOuemOef2wQ/D/Sp+6PBc/LlOhmTHujfmTRievkV2GOfcVfgH2j2DlnuD1/H44Zj5yJmfYZh/rkZAkmZ1YmNWXrZwztU6xL6BNDTdOO86kLFpmXNuNT5vkrrjOqBTiO9hclNoA7PQYza3fELNBvhX8A9zk/G9xwlHKuv7xXWwTZ79pLzkLJ/UfR3na1DnYla0v3OW3y55wsWsjfYLPW+L8SNVALYOjauE7PsN1LzufwC0D+fsrRxh8927csUb590v8pSLuhql9Unv62QaL/fgRzkJv4p3sYltOyCPbcliWw3NszvyxNvCObfJiuHhpWRMffKjkDpiMH5KDfhVwPvj7ztfzxE2372/JZk6bh1+5EZRkfQd/FSbtsDH+Hnok7OCTSKz6vsXo2Pb4of4gz9v0+uZfDK9akvglZBO/PKkS/j/ffJTlHIsvzDjODLD/a9wzp2f4wXj69H+F6P9nfOEKRjn3DLn3EXOuT7OuXbOucH4+1NC2X7NxzByYY10o1ngnHsbeCT8zdWzF/dWfVV+dehe+DmIjcHj0f6dkraX1FpSX0mnSXqJzDzzuhgb7f9GfsXuXaipfSz5+RD/ZhlgD0mnS+ok6Yf4ee/F1v4ymYb2UPkVv3sE3cdJSuaXxy86qoDWkn5JjoaupJ/Kr/jeDv/W/4HIpuShLM6DCyXtGhrovyHTSz82xPdFSVfg5+HNxJed56Lj44ZTNq+S6bE8StJhkrbAz3/MtQp0kp8VwB2S+oX83E7Sd6nZe1tMGpru2ZL2kdQZPxc6sSnJn/i8LQfWSToa/63cXCRlobsK/wRO/KJmt2iOMmxm+Qzn6msFaGhD/VYDHhE09MG/NEx4NvzG5fNqSb3kV52+PHKv7TouhNfxQ20Bvij/VYNDJF2IH+6e8MRmprOR0IBL1uXoDlwS7i8n4b9RnE1cfpbiF/r+NrBHjrAvRPtXSNpS0h5k5vnHPB3F/WP5Vd47SNpC0kGSbqPmitO5qE96sR0rgFWSvoKfE15s4jL/e0m7SWoTytDxkh4ns25HbMPPw9zcL+AX1cvmP2QaMWdIOlX+qxsVkr4s6QYKn8tdn/x4LNq/OpTRDvJfNUiuhzi+1fh7zTZs+n1tqHnuT5d0QLjOLyfz0n6cc25VjmMBcM4Nz/GSYny+8ACSfgbcgX/mmIRvoH+cI+7FZEb7fUHSD8IL9yvJNJDHJA1a+ZX8u4eGbzwCpiJyLxabXY7l14P4N/778BuA7zvnRuYJnkwpAl8++0vaFT9iItGQrC+SfAUm22YlbuFFcuJ4sqS9QvntIek8/OfbwK8Z8iiGkSZKPd7eNtvqu5F/DuUuZM1rzjruhcivGl85VUduI6Ow4yP3/sGtf+Q2Po+eIcGtA/6Bubb5UUm8Q3JpiOKva3X32wrIs+E5jluP71nI1lOw9lrSK2R19//L4TefaIXpKL7natHyzyhcoau7H1BLuPXAnvUog8m2gqg8RWF74RfLy5ufBZy/0dn5F/n1j21sSLpZ5SPXXPaNq7uHvMteP2A9NVeSHxLFfUuO+EbnSHd4dMyJuc5fMconftGyJNwDOfzjebov1+O85Mq3YqzuPrqe98dTc5yfeLstK/zIPOctdo/PTeIW3wMPIffc8vnZcZNZiTr72pmVff7Iv9p6HG983/5ZHeVik/trVl4UnB6+B3RljrAf5sq3POkNyZWfOcK1wDfUa7Mtyd98q7vHNoyO4j4lz7nLFXZ84p5DY8H5QQGru+OHXU+tI75YW5Ov7l7H+cgum9viR3/lCjcV6Jznnp43jwrQVciXSopRjkfWRy8114/J3r5Xyz22rjzOt0r9AqJ1QGyzLS2b9aQbzQbn3Lv4ij8fp+HfpFbhe0LHULN3qZhaVuB7Nn6B77Fcga8IP8H32p5Fpie4rrg+w7+hvgk/nG4NvlfhVeAs51xtQ9mSOEbjFw5Kjp+MX/X0ncbQ7px7BD/X/G8hbDLUcAKZOYjX4SvrOSH+Cfihctmr34I/V0/g51Wuwr8AmIYfknd6lO73gG/jh/4tD+E+wS82t3fIS4LbrcG+xfiH1MX44XpHOj9nvTauwD8Uzsb38ryGb9zNzw7onJuHP3/X4xcBS3qFPgTuo8jfvS5CuiPwowKSeX2vAIeE6wvnv1d7WhTnVPxQ23zfsR2JLweb5E0t/AO/ivNMMsNEE7s2t3zGQ93/ksP/eTLzWPeTn7NZCMfj83UJPp8fws9NXRF0VwfdV+IbUavxZfm/+F7Or7uGrcxcA+fcffjr6F/4PF+H77F+Gd8jfG7+oxuc5vP4KSvv4u8v0/CLeW0yMsA5dy9+FNB0vP1v4OeS5uqB/BzfkH0uhP0cf83nXKXdOXc9fkTHk/jRGOvwC4n+B1+ux+Q6riHpOeem4YcKTwphp+MXwrwvO+zmEsrFsfiFUl/Dl6/V+BFiTwX3t0LYlfhFuB7Gv1yrwn/h4pw8cd+Pf/H2D/wLinX4cvMG/h792wI1FpwfzjmHv2ecQ+ZLCOCv9/tDmHUhvifxa4cswM83vjBP+tfg82gc/hpch78/34V/6Vrb+iiNjnNuBn5h29H4MrkWb+8o/BSGXPVeU+hqsnIcpXkZvp5+A3/vXo7/6sjXnHN/2oyon8TfT5fg83cGvp7f3TmXa70fwyhrku9qGoZhGP+jSBpO5lN13w4vdYw6kDQav3AT+E/FVZZOjWGkE/mF6T4CTnHOTSi1HsMwjHLAetINwzAMwzCMJiesy9AaP/rlhFoDG4Zh/A9hjXTDMAzDMAyjFDyIH8reAz/k3jAMw8CGuxuGYRiGYRiGYRhG2WA96YZhGIZhGIZhGIZRJlgj3TAMwzAMwzAMwzDKBGukG4ZhGIZhGIZhGEaZYI10wzAMwzAMwzAMwygTrJFuGIZhGIZhGM0USQdL2iDpX5JalVqPYRh1Y410wzAMwzAMwyhDJI2W5MI2KctvZOR3QJ7jOwOjgVeBYc65dY2vurRIGhLly/BS6zGMhmCNdMMwDMMwDMMof3aXdFQ9j7kFWAYc45xb0QiaDMNoBKyRbhiGYRiGYRjp4NL6BHbOne6c29k5t6ixBDUUSe1KrcEwyhVrpBuGYRiGYRhG+bMeOEDSgfkC5BvqHQ+bj9zi4fIHSxonaYWkSZK+LGlLSQ9KWi7pI0mn50jvVEmvhDArJU2UNCwrTDxkf+8QfjXw/eC/paTfS6qUtEbSfEkPSdqlrgyR1FLSteGYpZLGAJ3zhG0r6XJJ70laJalK0lhJe9WVTjh+z6BrXtA5W9LfIv+zJP1b0mfBf6mklyWdmBXPXpIeD+FWh98XJJ2dFe5rkiaEeFZJmizpJ5JaRmF6SvqzpBkhzEJJb0q6sRCbjPLFFo8wDMMwDMMwjPLn78DJwGXAi40Qd7ewvzvwGDAd+HJwGwiMkfSmc24qgKQrgV9mxfMl4G+S+jnnfpMjnWeArsmfMGf+P8AOUZjuwDeAIyUd6Jx7sxbdI4BLov9nAIdlBwoL5j0JDI2c2wJHAYdIOsQ593K+RCR9FRgLtI6c+wDD8OeEkG68NkBrYD9gP0lHO+eekFQBPA1sGYXrFbZq4I6Q3rnAH7Nk7ALcgM/j5EXIGOCILJu6ATsCP8xnj1H+WE+6YRiGYRiGYZQ/vwVWA4dL2rPIcb+ObzjeEP73BHrjG+dJT7CAEwAkbYd/WQDwB3zDsCtwf3C7UtLGxnjEVGBACP8PfEMyaaBfh+8FPwHYAHTA25wTSV3INERnAoOAbYDPcwQ/hUwD/UygPbAd8B6+YZs3ncCt+Eb3BvwIgC7AtsAvojC3A7sFv9bATsCs4Pf98LsTmQb6N4A2QF/gWOBfwa5O+LwAmBPi7AWMC24nSRoS9pOXAjcGm3oAB4b/RoqxRrphGIZhGIZhlD+fAXeH/ctqC9gAbgjz1sdFbqOdcx8TGo+BfuH3q0Ay7Pp8YBGwGN8YBt9g3DdHOj90zk13zi12zs0CDg/uq4ARzrmlzrlHyIwUOEBS+zyaBwMdw/4dzrn3Q5w35Qh7ZLQ/BliJHykwKLjtI6lDrkQk7QB8Ifx9xDn3J+fcEufcTOfc1VHQz4CRwIfBnvfJ5FfyImIOftoC+Hz7IX7kwsvOuT8F9/2ATmH/z865d5xznwNXRmklowVmhN+j8OsVHAzMcc5lj3AwUoY10g3DMAzDMAwjHVwPrAOOx/fKFkrLOvyTxt6qyG0mgHNuTeTWNvz2KCDNbjncJmf97x5+5zvnVkfus8NvyzzxAGwd7c+J9j/NEbYuvSIahl/LsR/kPNgP238af156sml+twNwzn0GXAgswTeorwMeBz6TNCKE7R4dNyvanx3tJ5q+h3/ZsCNwOfAA8HGY8x4PzTdShjXSDcMwDMMwDCMFOOemA3/DP8OfmCNI3NCNV0/vX0fUub6fXts31RdE+8c55xRvQAvn3L3ZBznnVmU5JfH0kNQ2cu8bftfje+hzMTfa7xPt965F7wagWx69c3IcBzA/2t8xT5h9I83XAhUh3k3m0zvn/ohvZO8DnIafK98KGCGpLzXztm+e/QUhrpedcwPwIwJOAH4f/I8GTsqj1UgB1kg3DMMwDMMwjPRwDeDI3Tse97YeJs/BwP5F1vAsvsELcJWkwZLaSOov6fzgXwjPhN92+EbqFpKOxc+rBj8MPN/33d8Blof9syXtJKkfcHGOsE+F3xbAbZL6hNXeB0u6mlrmcDvnPgSmhb/HSzon6OwrKZl20CY6pBpwkk4DaqwdIKmXpGuD+yf4efkvJd74XvRXIrvOkbSrpB7UnP/+TIjvakmHA0vxPfIPR2EKGe1glCnWSDcMwzAMwzCMlBBWV380j98sYGL4ezy+8fY8NYexF0PDJ2QWN9sFeBvfiz8duAW/4Fwh3EimAXwpfhj4P/FtlJXAT2rRUEWmcb0NfhG4mdTsVU+4j8w895PwLzNWBd2X4Rd7q43zgLVB1+1B5ywgmZP+HzI9/r8CVgB3sunQ+/b41ehfxfeGr4rimAVMdc4txecF+N7zd/CL4R0a3B5yzr0Q9k/Dv4CYA6wBJgT3tdRcX8BIGdZINwzDMAzDMIx08eta/E7BN8yr8Q3BHwIPFluAc+4y4Fv4BupyfKN6GnAPvlFbSBxVwFfwK8TPxA+xXwg8AuzrnHu9jiiuwM/TXxg03I+fp52dzlr8InUj8I351fiG9mT8QnO/q0Pns/gh7Q/jh7+vxTeMHwz+C/ErtL+Fb3hPCf+nZUW1EBgFTMI36pN47gMOTeb/O+duwb9k+XewazV+ZfxLyCzOB3AzvmE+L8Q1H3/uj3bOvVObTUZ5I+dcqTUYhmEYhmEYhmEYhoH1pBuGYRiGYRiGYRhG2WCNdMMwDMMwDMMwDMMoE6yRbhiGYRiGYRiGYRhlgjXSDcMwDMMwDMMwDKNMsEa6YTQzJB0saYOkf0lqVWo9hmEYhmEYhmEUjjXSDaOMkDRakgvbpCy/kZHfAXmO7wyMxn9/c5hzbl3jq24aJFVG9te2DSkwvotDng4vgqbxDTw+0Ty6oRryxNtD0q8lvSNpuaSlkt6VdIOkbYuZlmEYhmE0JZKGRPXn8ODWP3IbWcfx40O4yiLpqU/aw3M9r4TnkZGSjiuGpjo0dInSG1LnAUZJsF42wyhfdpd0lHPuiXoccwuwDDjGObeikXQ1Fy4GtsV/X3R0aaUUD0l7AWOBXlleO4dtDv6bsIZhGIZhlAcjwu8Y4J+NnFaXKD2A8Y2cntEArCfdMMqbS+sT2Dl3unNuZ+fcosYS1FAktduc451z/Z1zcs4JGBp5jUncwzZ+s4SmGEmdgMfINNB/A/QF2gG7ATcDa0ujzjAMwygmktqXWkMpcM6Nj+r80aXWUx+cc6PtecUoBGukG0b5sh44QNKB+QLkGvIV3DcOm4/c4uHyB0saJ2mFpEmSvixpS0kPhuHRH0k6PUd6p0p6JYRZKWmipGFZYeIh+3uH8MAqA4YAACAASURBVKuB7wf/LSX9PgwVXyNpvqSHJO1ShDxD0jaS7pY0J8T/adC0bfDvH/IlGfZ9UPYwNUmXSHotaFsrabGkZyUNzZNsIbq+JWlayLfxkgbVErbOfM7D2UDvsP+Ac+6nzrk5zrnVzrl3nHMXAreFNHaU9LCk6SGd1UHf9ZIqIi0Vkn4r6eOgpUrSZEl3xA+IdeV7FO48Sf+VH4JfHeJ9UNLO9clPwzCMciSrrj1Q0mPhXjc3+Ckr/NckTQj3xFXh/voTSS3zxHmIpGckrQCuqUPLiaG+WRLu3x9IuiTybyHpB+E5YEWoC8ZLOjQrno3DwyUdLmlqCP+4pJ6Sdg91VnWoO/cqIJ82ThcL9WNSF/011DuHyE/ZWibpeUkDomNzPvs0BPnnn/8EeyZLOizyaxXqsSnhOWBtOI/3Sdouf5S6VNLsKI+2iTxrDHdPbImOPzPbtlAH/1fSwqBhvqRHJe2elfDGKXShrv0k5OnG/AtxTo8OG6Gs4feS2kq6XNJ7oUxWSRqbfV4lHSrphaBntXz9/5SaYMj+/wTOOdtss61MNvywaxe2+8PvU8FvZOR3QHAbErkNzxVP5BYfvzDad8A8/Dz22G0D8MXo+Cuz/OPtJ3lsWBTtXwx0Bj7IE0c1sFeB+RTbPTpy3zbYkiv+ecG/fy12jAzxZOdFsq0BdovSqwzu4+vQe0jIzziuuXlsKCif86TzdBR23zrCHlFLOg9E4W6tJVz3QvM9hBtWS1wnlvr6s80222zb3I2ade2CHPe6y6Kw5xZ4H47jjOvVm2rRMSJPvOOjMH/JE2YDcFIUbnxwXw6sygr7Ug47ZwKt68inpP5clKN+fCpHOq9Gxw6J3IcHt/6R28g60o7tqc5KZzmwZQjXrpbzUwm0y5H23BxhpwItQ9jhkfuQLFuyt8S2z/L4VwFbR3bF7tlhX82RfvY2BD8Velwe/1XA/iGebYGVecLdUurrsDls1pNuGOXLb4HVwOGS9ixy3K8DWwI3hP898T2wA4ETg5uAEwDCG+PLgvsfgG5AV/yLBIArJXXNkc5UYEAI/w/gh8AOwe86fKP9BHwF3QFv8+ZwRbAF4Ach/h+E/z2BK5xzlc4PmZ8R3Ce4zNCzkcHtV8AgYAugDbA3sAJoDXyngbqEHx1xDD7vnskOtBn5nLBNtP9+HZreBw4HtsLbuCXw5+D3TUlbhv1kkcK/Ax2Dnn3wLxNWR/bVmu9ZcX0CbI0/54OAC8mcD8MwjObCu/h77GDg0+D2M0md5KcnXRfc5uCnJPXCN5AATlLuRb3mhfg6AaNyJSqpP/DLKPxX8ffvwcDfQpj/ByQj5v4vxLc1vgEr4EZJ2e2EiqC5C75xDrA/MBFfhyTrnfQDvpxLWw66At8FugMfB7fDgb8Gv4eD25cl9S0wzkKpwM8B74av9xO3I8P+WuBkfIO0XfA7O/htCxyVI85O+Cl53YB7g9sg4NRcAlwYuh85xVP4Rge3C/DPZxVAe3z+gK9rT8kRbWfgzKDh2eD2ZUl9Q5zxKIArXM3h96eQmVJ4ZkhvO+A9oC2Z57S98XkC8KXgt22wMykbxmZgjXTDKF8+A+4O+5fVFrAB3OD8vPVxkdto59zHwL8it37h96tAMvTufPyb78VkKof2wL450vmhc266c26xc24WmYplFTDCObfUOfcI8GJwP0CbN8cuiX+6c+6WEP8t+DfeAIflPmwTqoDf44eErQLewDcoIfOSoSDCkMV9wt8JzrmxzrkqfM9INg3N5wRXD2lz8W/NJ+AXG1wInJPIBrYP+0njeX/gF/iXDNXOuRHOuWXBr9B8T+LqA1wOnIF/2LvVOfd6PbQbhmGkgV855+Y55yYDdwa3zvhFPPfDN+gA/uz8lKTP8S9AE3LVWZc75yY755Y75z7Jk+5hZOqSq5xzzznnqsNxtwX3I6PwV+PrgaReAP/ifseseNcA1zrnlgAvR+6/Cc8UT0Zu/SiMWc65O5xzC/F1bcI1oa58ugFxFso64BLn3GIyL8M3puOcW4+v+x/CjxaoBu6IwuV6HngkNLwX4+u5hP03Q+dq4C78i54V1MyTXBomOuf+EjQ8ErkXkn9xuRiD7y2fjn/RALCPpA7UfLF+Gf6ZZSfgcefc3wpIx6gDW93dMMqb6/FvbY/HVyaF0rIO/+TmuipymwngnFujzJS5tuG3RwFpdsvhNjnrf/fwO985tzpynx1+W4Z45hSQXi6S+Gdnuc/GD0er047QA/EkmYenbOq7AF53fA881LTr0xxhG5rPCTPJVKQ7Aq/VEvYGMr3duUjs/Am+h35X4OeJp6TXgcPCQ1Sh+f5H4EB8Q//cKNynko51zr2BYRhG82FWtB/f//tQsy6Jw8X30Vx1Qna9mov4uA8KCJOP7PpmvnNuZdjf5PkB34hPaEthzIz2ixVnocyLXjbHabcFkPQNfOM4H7meB2o75/VG0pfxownytdlyafgo2t/Erjqoq1wI6Oqce0PS1cCP8M+oxwf/lZIudM7dkTcGoyCsJ90wyhjn3HT80LQWZIahx8QN3fhG3b+OqHM1+Gt7CbAg2j/O1VxNXUAL59y92Qc551ZlOSXx9JAUVxbJELb1+J7jhpLEnz0krk+WP+TvdT6cTAP9fPycM+F7mhuqKVlRPa6ke+cJm1BwPkfEb9cvyhVAmcWIvhl+3wW2CfFv0mh3zr3vnBsMfAH4Gn7o+nr88Lbzs3TXmu/OuRXOua/jh8Afih/mPhefF7UugGQYhpFC4ntifP+fQ837fd88+3GYhOx6NRfzo/3s3vBcce+ep755OeuYfM8J9elEKOhY59zmxNmQtHM9EyTPXavww/db4V9Y10Zt57whHEemgf41/PS0fJ0ICXXZVduou6RcbAC65SkXcwCcc7/Av6TfHz/X/VX8iL9RkqwjeDOxRrphlD/X4G+ouXrH4zfuh8lzMJs3rCoXz+Jv2ABXSRosqY38Sunnk5nzVBfJPOx2+BVFt5B0LL53FeBlt3nfd0/i3y6sbNpJ0nlk5l/F88CTlwHbSOocubeJ9pcDrST9DD/frt6E4XJJj/ZBko6S1IXcw903N5/vINNDf4qkayX1DnEMlnQzYZV9MnauBaol7Uim0b0RST+TlIzkeAZ4kMxDYvLGvaB8l19p+Hv4eYb/AR4gU4YL6dUxDMNIE7+Q1EvSrmTWM1kCTAFewdcxAOdI2lVSD/y0ooRN1i4pkGfwL1MB/k/+iy4dJH1RUlIHPBWFv0nSwFBX7Cjp58B9DUy7OZHUkw4/HSBf3R1zgvyq/l2oOXUh+4VHNskzycCsaX/xM8ky/PPTr+uIqy7izpCdJLWO/iflogVwm6Q+YbX3waHn/EaAUF5/iR9uPwU/JWBSOLY9db9IMOrAGumGUeY456YCj+bxm4VfsAX8UKOlwPMU9qa9Pho+IbPAzS7A2/he/OnALfgFTQrhRmBa2L8U/7DyT/y9aCV+aPXmMILMW+A/4PPjD+H/guCfkMyB3g6oCp8fORT/cJP0fI/BP0Rdgp+n3lBGknnRMhZfQR6dHWhz8zkM2zsW+Dw4XYJ/e786xHUBmaH3Y8PvHvhRAu9HfjFH4YfazQjxTMEvXgOZnvtC830X/CfgPsTPq5uH75GHmg+MhmEYzYFB+PVl3iEzeup659wy59xSfD0Ivvf1Hfy9O/n82UPOuRcakqhzrpLMQmhb4Z8LqvH375NDmAlk5mEPwQ+RXo2vC67BLyL3v05ST7bHL4S7ANg9f3DAN6Qn4Ov504Lbe9T90iN5JtkfWBGeSQZGGsAv6reU3AvWFUwoex+Gv8OANSG9VkFnsk7QSfgX6avwzxCX4V9UgO+4uBLfMK/CPysl09heC/Phjc3AGumGkQ5qe2t6CpkKeAF+BfUHiy3AOXcZ8C18D+hyfKN6GnAPcF6BcVQBX8E34Gbie2cX4hc22XdzFw8LDyZfwn9W5rMQ/2f4VWK/FPwTRgCPkdX4ds59gK+03sdXTBPxQ+CXbIau5/GLpE3HPwS9hP8sW66wm5XPYV73rsC1+AeyFSGeKfhVWZNFZC7CV8ZV+HJzPbmHnI/Gv7j4FD83cBG+B+hk59yTIc1KCsv35/Blc3qkayp+cZ2498gwDKM58A38i+gV+Ab4lUT32bDA5vHAv/H3w9X4e+Il5F61u2Ccc1fgpzW9iG84rsY3xOMXot/CTzuahK/vluPrvtvxK77/r3M3/iX7p/hnrIep+7wkefcpPk+fAI4Io+pq40J8I3xZ7OicG4dv/FbinwfGkVmsdXM4E/9iYGXs6JxbG+IfgX+5sBr//DMZv3r/70LQaXhbpwT/1UHj7fgh+sZmIufqsxiwYRiGYRiGYRi5kDSSzOih7bJeDhuGYRSE9aQbhmEYhmEYhmEYRplgjXTDMAzDMAzDMAzDKBNsuLthGIZhGIZhGIZhlAnWk24YhmEYhmEYhmEYZYI10g3DMAzDMAzDMAyjTGhVagHG/w7du3d3/fv3L7WM4uAcSKVWURzMlvLEbClPSmzLm2++ucA516NkAoz/SVJTf6fhXpMGjZAOnaaxeKRBZxo0Ql6d9a2/rZFuNBn9tt6aN954o9QyisLS6dPZYrvtSi2jKJgt5YnZUp6U2hZJM0qWuPE/S1rq71Jfn4WQBo2QDp2msXikQWcaNEJ+nfWtv224u9FkbFi3rtQSisbK+fNLLaFomC3lidlSnjQnWwyjUNJSf6fh+kyDRkiHTtNYPNKgMw0aoXg6rZFuNBmt2rUrtYSi0XWnnUotoWiYLeWJ2VKeNCdbDKNQ0lJ/p+H6TINGSIdO01g80qAzDRqheDqtkW40GetXry61hKJR9dFHpZZQNMyW8sRsKU+aky2GUShpqb/TcH2mQSOkQ6dpLB5p0JkGjVA8ndZIN4wGoBbN59IxW8oTs6U8aU62GEZzIw3XZxo0Qjp0msbikQadadAIxdOZDmuNZkHLtm1LLaFodErDKrcFYraUJ2ZLedKcbDGMQklL/Z2G6zMNGiEdOk1j8UiDzjRohOLptEa60WSsW7Wq1BKKxpKUDLkpBLOlPDFbypPmZIthFEpa6u80XJ9p0Ajp0Gkai0cadKZBIxRPpzXSjSajZevWpZZQNDr06lVqCUXDbClPzJbypDnZYhiFkpb6Ow3XZxo0Qjp0msbikQadadAIxdNpjXSjyXDOlVpC0diwdm2pJRQNs6U8MVvKk+Zki2EUSlrq7zRcn2nQCOnQaRqLRxp0pkEjFE+nNdKNJiMt31kthFWLFpVaQtEwW8oTs6U8aU62GEahpKX+TsP1mQaNkA6dprF4pEFnGjRC8XRaI91oMlq1b19qCUWj2847l1pC0TBbyhOzpTxpTrYYRqGkpf5Ow/WZBo2QDp2msXikQWcaNELxdFoj3Wgy1q1cWWoJRWPRlCmlllA0zJbyxGwpT5qTLYZRKGmpv9NwfaZBI6RDp2ksHmnQmQaNUDyd1kg3moy0fN+wEFq2a1dqCUXDbClPzJbypDnZYhiFkpb6Ow3XZxo0Qjp0msbikQadadAIxdOZjruu0SxokZLVYQuhonfvUksoGmZLeWK2lCfNyRbDKJS01N9puD7ToBHSodM0Fo806EyDRiieTmukG03G+tWrSy2haCz95JNSSygaZkt5YraUJ83JFsMolLTU32m4PtOgEdKh0zQWjzToTINGKJ5Oa6QbTUbLNm1KLaFoVPTpU2oJRcNsKU/MlvKkOdliGIWSlvo7DddnGjRCOnSaxuKRBp1p0AjF02mNdKPJcOvXl1pC0VhXXV1qCUXDbClPzJbypDnZYhiFkpb6Ow3XZxo0Qjp0msbikQadadAIxdNpjXSjydiQkkq+EFZXVZVaQtEwW8oTs6U8aU62GEahpKX+TsP1mQaNkA6dprF4pEFnGjRC8XRaI91oMtLyndVCSMu3GgvBbClPzJbypDnZYhiFkpb6Ow3XZxo0Qjp0msbikQadadAI9p10I4Wk5TurhZCWbzUWgtlSnpgt5UlzssUwCiUt9Xcars80aIR06DSNxSMNOtOgEew76UYKSct3VguhVYcOpZZQNMyW8sRsKU+aky2GUShpqb/TcH2mQSOkQ6dpLB5p0JkGjVA8nem46xrNgrR8Z7UQ2vfsWWoJRcNsKU/MlvKkOdliGIWSlvo7DddnGjRCOnSaxuKRBp1p0AjF02mNdKPJSMt3VgthWWVlqSUUDbOlPDFbypPmZIthFEpa6u80XJ9p0Ajp0Gkai0cadKZBIxRPpzXSjSYjLd9ZLYSO/fqVWkLRMFvKE7OlPGlOthhGoaSl/k7D9ZkGjZAOnaaxeKRBZxo0QvF0WiPdaDLS8p3VQliTks9AFILZUp6YLeVJc7LFMAolLfV3Gq7PNGiEdOg0jcUjDTrToBGKp9Ma6UaTkZbvrBbCmmXLSi2haJgt5YnZUp40J1sMo1DSUn+n4fpMg0ZIh07TWDzSoDMNGqF4OuWcK0pEzR1JtwFznHO/KkJclcDZzrnnNltYIyBpG2Aq0Nk5V7SaeUD79u6qAQOKFZ1hcGr4zMVNN93EXXfdxZQpU9iwYQMjRoxg5MiRNcIuXLiQXXfdlblz59K5c2eqojedK1eu5PLLL+eBBx7gs88+o3v37px11llcddVVAJx55pk899xzLFiwgE6dOrH33ntzzTXXsMceezSabWurq2ldUdFo8TclZkvxkPSmc27vkglIIVZ/bz5WfxuG0dicOmVKrc9za6ur+XTBAi655BKeffZZqqur6devH9deey3f+MY3ABg7dixXXnklU6ZMoaKigmHDhnH99dfTrl27nGmOHDmSK664Iqff9OnTAdhuu+1y+ud61kx05npOqG/93arQgM2dUPH2AtYDy4GngAucc8sBnHPfL506j6T+wHSgtXNuXWOl45ybCXRsrPgNo9i8+eabdOvWjd69ejF77tycYb73ve8xf/78Tdydc5xwwgk89dRTDBgwgDPPPJMlS5Ywbdq0jWFmzJjBQQcdROfOnRk3bhxPP/007733HjNmzGg0mxZNmUKvffZptPibErPFaEys/s5g9bdhGGkmeZ7r16/fJs9YH738MoeddRZz5szhK1/5CoMHD2bGjBkbG9OvvPIKxx57LK1ateLkk0/mvffe4+abb2bt2rXceuutOdPbd999ueiiizb+f//993n66afZYost6NGjB6tXr67h75zjD3/4A+vXr2fgwIE54yzWc4I10mvyNefcc5K2Ap4GLgX+r8SaygpJwo/A2FBqLYaR8Ne//hWAow85JGcjfcyYMTzyyCP88pe/3OSN6bhx43jqqafYaaedmDRpUs63rePHj9+4/9Zbb7HXXnsxe/Zs1q5dS+tG+jRRm06dGiXeUmC2GE2A1d91YPW3YRjlTvI8d9xxx23SSL/rkUeYM2cOZ555JqNHj97k2Icffpj169dz+umnc/fdd1NVVUXXrl258847GTFiBFtttdUmxxxxxBEcccQRG/8nPfLf+c53qKiooKKigptuummj/7/+9S9GjRrFVlttxUknnZTThmI9J9ic9Bw45z7DV/K7J26SRku6Kvp/jqRpkhZJekxS73zxSTpd0gxJCyX9X5ZfC0k/l/Rx8H9QUrdCdEo6WtIkSUslzZI0MvLrL8lJOlPSTEkL4rRrSzc6tlX4P17S1ZJeBlYAAyTtJ+l1SUvC736FaDaMxiTXt3xnzJjBhRdeyI9//GOGDBmyif/zzz8PQMeOHdltt93o2LEjQ4YM4e23364R7pZbbuG8887jlFNOAeDHP/5xozXQAdp06dJocTc1ZovRVFj9bfW3YRjNk5defx2ATz/9lK222oott9ySb33rWyxYsABgYyfLBx98wNKlS3k9hF+7di1Tp06tM/7KykoeffRRWrZsyYUXXpgzTNJgP++882iT56sXxXpOsEZ6DiT1BY4EpuXxPxi4BjgJ2BqYAfwtT9gvArcCpwO9gS2BvlGQHwDHAQcF/8XAHwqUWg2cAXQBjgbOlXRcVpgDgB2BQ4DLJQ1qYLqnA98FOgHLgLHAqGDP74CxkrYsULdhNArrVq6s8X/Dhg2cccYZbLfddhvnl2eT3NzfeOMNBg0axD777MOECRM4+uijqa6u3hjuoYce4tZbb+XDDz+kb9++7L///o1nCLB81qxGjb8pMVuMpsLq75xY/W0YRuqZ//nnAPz73//mqKOOokePHtx7772cffbZAJxzzjl0796dV155hc6dO3PYYYdtPPazzz6rM/6bb76Z9evXc+yxx9K/f/9N/CdPnsy4ceNo164d3/9+/llUxXpOsOHuNfmnJIefzzUOGJEn3GnAXc65twAkXQosltTfOVeZFfZE4HHn3Ish7C+BCyL/7+Pnzs0O/iOBmZJOr2vemnNufPT3HUn34yvtf0buVzjnVgJvS3ob2A14r7Z08yQ32jk3JYQ9DPjIOffX4He/pAuBrwGj44MkfRf/cED3Rux1NP43mTdxIm06daJNly4snzULtfK3tOVz5rC2upq3n3uOF198kV0GDeLogw9m6erVAFQvX87RRx7JdRddxBbhmB22246/3X03i6dNY8ehQ5kzZw7P3nMPB4eb/APXX0/7/v155K9/5ayf/YwTTzyRVx56iB13350Na9eyatEiuu28M4umTKFlu3ZU9O7N0k8+oaJPH9ZVV7O6qmqjf6sOHWjfsyfLKivp2K8fa6qqWLNs2Ub/Np060bJDB+ZNnEin/v1Z+fnnrFuxYqN/2y5daFVRQfWcOWwxYADVn37K+lWrNvq369aNFq1bs2LePDpvvz3LKitxGzbQZfvtWfz++7Tv0QOAlfPn03Wnnaj66CPUogWd+vdnyUcf0aFXr6LatKqqisXvvbfxPKXZplVVVaytrt54npraJiMvVn9b/W0YRoqZN3Hixrpu9ZIlgH+eWzZjBhvWrqVrGEZ+8tFHc/3FF/PeKadw4GGH8eSTT7Jg6lTaLl/O5Dff5K6bb2bBkiXss99+XPrLX1I5ezbtVq5k3sSJNZ6z4vp7fmUld9x+OwBnHHYYVR9+uEn9fc0vfgHA8V/9Km2WLGHZihU56+9VVVUsDfPkN6f+tkZ6TY4Lc9oOAu4DugO5PnbXG3gr+eOcWy5pIdAHqMwRdlYUtjqETdgWeERSPEdsPX4RnDm1iZX0ZeBaYBegDdAW+HtWsPjV0QoyC8rUlm4u4tdCvfG9DzEz8PbXwDl3O3A7+NVh89liGA0hXpijYuutIXytomOfPrSuqKD7brsB8O577/FudNy69et54qmn+MOtt/KlJUvg1ltp1b497bp2pccee6CWLQHY5ktfovVWW9GmTRu2CKt7nnzBBVx45ZUsXbqUZVtsQadttwWgcw5N7bt3r1Vzh549M9qz/Be+++7G/SRc9vEd+/TZJJ3YP9HWrmvXnP6JTT332mujW7vIv1g2dezdm66DBtVwT6tNG9avp3VFxaZlr4ltMjbB6m+rvw3DSDFJvddzr71o29nX1h379NlYR+66yy68OXUqHXr1ovvgwbQLw9nbtWvHluEZY/369Vx2ww0AvPDCC1TOnk1FRQVfPekkOnXqxNy5c1myxRZ069aNrj17bqy/H3vgAZYuX85ee+3Fsd/73kZNSf293DkeefZZAC69+mo6h0XjctXfHXv33lhvb079bY30HDjnJkgaDfwGP6Qsm0/xlSQAkirww8ZyVcpzgUFR2A4hbMIs4Czn3MsNkHofcAtwpHNulaSb8A8mhZA3XflVaLOJK+ga9ge2wa+oaxhNzh133MFLL73EO2HO0T//+U8qKys57rjjiD8zOX78eIYOHVrjE2x9+/blC1/4AlOnTuW4445j2bJlLF26lN13353Bgwfz0ksvceqpp3LggQfStWtX/v3vf7N06VJ69OjBnnvu2Wg2rVuxotHibmrMFqOpsPpb/XOEt/rbMIxUkDzPvfWWf5caP8+d881vcs/DD3PXXXexcuVKXnnlFQDOOOMMJLF8+XJ22mknDj74YNatW8cjjzwC+M+sdQq98Jdeeiljxozhoosu2ji/3DnHqFGjALj44otz6rrttttYtWoVhxxyCLvuumutNhTrOcHmpOfnJuCrknbL4Xc/8G1Ju0tqC/waeC3HUDmAh4BjJB0gqQ1wJTXz/TbgaknbAkjqIenYAjV2AhaFCn4f4NQCj9vcdJ8AdpB0qqRWkoYBXwQer0f6hlE0XnrpJcaMGcOcefMAePvttxkzZgz//e9/6zy2VatWPPXUUxx55JE8++yzTJ48mZNPPpnHH3+cVq1a0bt3b3bYYQeeffZZ7rzzThYvXsw3v/lNxo0bR+fOneuMv6F023nnRou7qTFbjCbG6u/8WP1tGEbZkjzPzQrzuuPnuS8deSSPP/44gwYN4r777mPlypVceuml3BB6zlu3bs2AAQN47LHH+Mc//sHAgQO54447+MlPflJrmmPHjmXatGlsvfXWDBs2bBP/+BNu+RrxMcV6TrCe9Dw45+ZL+gtwOfCNLL/nwty0fwBdgf8AJ+eJZ4qk8/FvzSvwi7TMjoL8HhDwjPwKs58DDwCP1iYv/J4H/FbSLcAE4EH8IjSF0JB0E5sWSjomxHErfoGeY5xzCwpM2zCKyujRoxk9ejTzJk6s9duUQ4YMqdGznjBw4ECeeOKJnMfssMMONT7B1lQ0p+9xmy1GU2L1dy2JW/1tGEYZkzzP5WLexIkcfvjhHH744Tn927Zty4svvljv+I855picz4YJrVu35tNPP6013phiPSeoNlFGeSFpMPCicy6V3wDaY5dd3KR33607YAqo+vBDuuywQ6llFAWzpTwxW8qTUtsi6U3n3N4lE2A0CKu/m4ZSX5+FkAaNkA6dprF4pEFnGjRCfp31rb9tuHtKkNQC/8mYN0qtpaEki3E1B1pVVJRaQtEwW8oTs6U8aU62GE2D1d9NRxquzzRohHToSMa37wAAIABJREFUNI3FIw0606ARiqfTGunpYSZwBPDDUgtpKOvXrCm1hKJRPafWhXtThdlSnpgt5UlzssVoMqz+biLScH2mQSOkQ6dpLB5p0JkGjVA8nTYnPSU45/qWWsPm0rJt21JLKBpbDBhQaglFw2wpT8yW8qQ52WI0DVZ/Nx1puD7ToBHSodM0Fo806EyDRiieTutJN5qMDWvXllpC0aiuxwIS5Y7ZUp6YLeVJc7LFMAolLfV3Gq7PNGiEdOg0jcUjDTrToBGKp9Ma6UaT4TZsKLWEorF+1apSSygaZkt5YraUJ83JFsMolLTU32m4PtOgEdKh0zQWjzToTINGKJ5Oa6QbTUar9u1LLaFoNKdvJZst5YnZUp40J1sMo1DSUn+n4fpMg0ZIh07TWDzSoDMNGqF4Oq2RbjQZ61auLLWEorFoypRSSygaZkt5YraUJ83JFsMolLTU32m4PtOgEdKh0zQWjzToTINGKJ5Oa6QbTUaLVs1nncJ23bqVWkLRMFvKE7OlPGlOthhGoaSl/k7D9ZkGjZAOnaaxeKRBZxo0QvF0WiPdaDIklVpC0WjRunWpJRQNs6U8MVvKk+Zki2EUSlrq7zRcn2nQCOnQaRqLRxp0pkEjFE9nOl6NGs2Cqo8+4r6UzCepjVOnTGHFvHl02nZb7r//fk499VQALrroIm666SYWLVrEj370I5555hkWLlxIr169OP7447n++utpGz5j88c//pFbbrmFyspK2rdvz9577811113H7rvv3uT2JLY0B8yW8sRsMYx001zqb6NhnDplCuPHj2fo0KE5/e+++25GjhzJjBkzNvE76KCDGD9+fM7jHnzwQUaOHMnMmTNxztG/f3/OP/98zjvvPADefPNNRowYwX//+18WLFhAr169GDZsGL/61a9o27ZtKu7HadAI6dCZBo1QPJ3WSP8fRZIDtnfOTcvjfzlwNnA0MMo5l/vO/D9K5+23Z/bs2Zx33nm0atWKdevWbfT70Y9+xJgxY+jbty/Dhw/n73//O6NGjaJLly5cccUVjB8/nvPPP58WLVpwyimn8OGHH/LMM8/w/vvv56zgmsKW5oLZUp6YLYZRPKz+NkpB3759ueiiizb+X758OXfeeScAAwcO5KyzzmLRokUb/R9++GFmzZrFwIED88Y5Y8YMtt12Ww466CBmzZrF2LFjOf/88xk0aBBDhw5l8uTJvPjiiwwdOpROnTrx4IMPcsMNN7B+/Xp++9vfpuJ+nAaNkA6dadAIxdNpjfQmQFIl0Bvo7ZxbELlPAnYHtnPOVZZGXV4GAwcDtwH/LrGWsmPp9Omc+dOf0rt3b3bddVceeOCBjX4ff/wxAJdccgkXXHABnTp14re//S2VlZU1/PfYYw/uuece3n33XXbddVfmzJnD2rVrad3Ew3mWVVbSrmvXJk2zsTBbyhOzxUgrVn8bhmfgwIHcdNNNG//ffPPNAOy5554ccMABHHDAARv95s+fz5/+9CcALrzwwrxx/vSnP+WnP/3pxv+DBw9m8uTJTJ8+naFDh3LAAQcwa9YsOnfuvFHDFVdcwbPPPguk436cBo2QDp1p0AjF02mN9KZjOnAKcDOApF2BDg2JSFIr59y6ukM2HOfciWH30MZMJ63cds89vPTSS7z22ms1Ki3ww95fe+01rrvuOiZPnszf//53ttxySy644AIAjj32WK677jomTZrE6aefzgcffIAkLr300iZvoEN6vn9bCGZLeWK2GCnH6m/DiHDOMWrUKAAuvvjiTfxvu+02Vq1axcEHH8zgwYNrjWvixInce++9fPzxx0yePJlBgwZx7LHHAmzSC79mzRrA9+pDOu7HadAI6dCZBo1QPJ22cFzT8VfgjOj/mcBfkj+SjpY0SdJSSbMkjYz8+ktykr4jaSYwLrj/XdJnkpZIelHSztExoyX9QdJYScskvSbpC1maDpX0kaSqEFbh2C9IGidpoaQFku6V1CWKe5Ck8eG4KZK+XsyMKnfeffddfv3HP3LllVfmnEO+zz77sN9++zF79mxuv/12Fi9ezNChQxkwYAAA3bp147TTTkMS99xzD6+//joDBgzIO9ersemSkuFDhWC2lCdmi5FyrP42jIjHH3+cadOmsfXWWzNs2LAafmvWrOHWW28Fcjfgs5k6dSqjRo1i7NixtGjRgiOOOIJOnTptEu7ll1/mxhtvpF27dlx11VVAOu7HadAI6dCZBo1QPJ3WSG86XgW2CBVkS+Bk4J7Ivxr/ENAFP4/sXEnHZcVxEDAIODz8fxLYHugJvAXcmxX+ZOAKoCswDbg6y/8Y4Ev4oXEnRfEKuAY/xG8Q0A8YCSCpNfAv4JmQ7g+AeyXtWFg2pJ9//OMfrFmzhgkTJnDMMcfw/PPPA/DYY49x6aWX8s1vfpMJEyZwzTXXsGLFCs477zweeughzj33XAD+9Kc/MXLkSPbcc08WLlzISy+9xMcff8zXvvY1FixYUFvSjcLi999v8jQbC7OlPDFbjJRj9bdhRCQjCM8991zatGlTw++BBx5g7ty5DBw4kGOOOabOuIYPH8769ev56KOP2H333bnxxhu54YYbaoR54oknOOyww5DEo48+yp577gmk436cBo2QDp1p0AjF02nD3ZuW5G38BOA9YE7i4ZwbH4V7R9L9+Er9n5H7SOdcdXTMXcl+eHO/WFJn59yS4PyIc25i8L8X+F2Wnmudc1VAlaQX8PPrngqL0SQL0syX9DtgRPi/L9AxHLsBGCfpcfxQwJHZBkv6LvBdgO4p+XRCXaxbvRrnHE8++WQN9+nTpzPhmWeY8sEHAOzcty/rPv+c7cP3Et+dNInP33yTdyZNAmBgv360WrKEfs7RunVrVqxYwX+ffpoDjjqKJR99RIdevdiwdi2rFi2i2847s2jKFFq2a0dF794s/eQTKvr0YV11Naurqjb6t+rQgfY9e7KsspKO/fqxpqqKNcuWbfRv06kTbbp0YfmsWXTq35+Vn39O9dy5rK2uZtGUKbTt0oVWFRVUz5nDFgMGUP3pp6xftWrj8e26daNF69asmDePzttvz7LKStyGDXTZfnsWv/8+7Xv0AOD/s3fmcVXV+f9/vkF2EMQttwRC01xza6Yxl7K0GUvKr5mYSGralGnq2DqW9mtyappS2ya3oFymrDTLFjNzSlsYl0xwX0ACRBFQVhH5/P641zuogFc9cu/n+nk+Hj7k3s85n/N8wT3nfT9nLTlyhHpt2pC/Zw/i5UVIREStZBIvL44mJ1NeXOxo1zUTQHZSkuPvpHOmoqws8nbsOOezp2OmyutLVevT5c5kcBmmfhuuWLKTkhzb0C1JSaxduxZ/Pz+G3HQTJTk5Z2xDX37hBQDuj4khNyXljG1o8ubNnCwqonO/fhTt3csJLy/qN2tGYXo6TSMiaB8VxebNm9m5fTvZSUn4hYWx7IsveGjKFOrWrcui2bPpFBbm2AaXl5RQkJbm8rpQ0/esE/n5ZCcluX2tEy8vspOSnP7u6Ir6Xbn+Xo7vw1ZlKsrK4viBA+dkulBEKWXF+muoAfuNZ8YAe4DvgB+BVcBS4CQQCTQG/g60B3wBP2CZUmqEiERguybOVyl10t6nN7Y960OAhkAFEApEK6X2iUgC8JtS6q/26fsAi5RSze2vz7g7bOXpRaQxMBu4CQjBdsZFnlKqhYgMBf6ilOpeKd/fgfpKqQdq+j1EBQSo5+2nfOtMbEoKxw8coG5kJGDbC5yYmOh4BFv//v1ZvXo1UVFR9OvXjxUrVnD48GEefPBB3nrrLcdj23x8fBg2bBj79u1jw4YN1K9fn4MHDxIYeFGXOl40lbPojsninpgs1iEim5RS3VwmcIVh6rcNT6nfhosjNiXF8fPo0aNZuHAho0ePZv78+WdM9/3339OrVy/CwsJIT08nODj4jHb7VRls2bKFzp0707p1ayIjI4mKiiIjI4NVq1ZRUVHB4sWLiY2NZfXq1QwYMAClFAMGDODaa/930sesWbNcvj12Bh0cQQ9PHRyhes8Lrd/mdPdaRCmVhq1Y/xH4+KzmJcBKoIVSKhTbXVnl7C4q/RwLDMJ2Y5hQIML+/tnzXAwv2JfVQSlVF7ivUr+ZQAsRqfzZuZpKRxWuBEqOHKm2LSEhgREjRlBSUkJCQgJ+fn6MHz/ecfrWsGHDeOWVV4iOjmbZsmXs2LGDfv368cUXX9T6AB1qzqIbJot7YrIYdMfUb4MBcnJyWLJkCVD19eazZ88GbAP5swfoVdGvXz927drFwoULWb9+Pd26dSMhIYHY2FgAMjMzOX0w8csvv2T27NmOf6DH9lgHR9DDUwdHsM7TnO5e+4wG6imlikSk8u8/BMhVSpWKSA9sRXx1Df2EACeAo9juMvuChY4hwDHgmIg0A6ZWavsZKAYeE5F/An8A7sB2bdwVQ702bRw/JyQkkJCQ4HjdpEkT3n333Srm+h+TJk1i0qRJl0vvgqicRXdMFvfEZDF4CKZ+G65oGjRoQElJSbXtH374YY3zn3327ptvvlnj9PHx8cTHx1fbrsP2WAdH0MNTB0ewztMcSa9llFL7lFIbq2h6CHhORAqAZ4APztPVu0Aatj3g27Hd2MYqZgBdsBX6VVQ6aqCUKsNW1G8HcoA3gTillB53c7AIT7o21GRxT0wW98STshguDFO/DQb3QoftsQ6OoIenDo5gnac5kl4LKKUiqnm/nP+dhpYKVLkLUimVylmnwSmlCrGdLleZdyu1x581/TqgeaXXZ/cXX+nnFKDrWX3/86z23lW51kTdyMgzrmvSGfHynP1bJot7YrK4J56UxXB+TP22oUv9PrJlCw2vv97VGjWigyPo4anD9lgHR9DDUwdHsM5Tj7QGj8Dbz8/VCpYREhHhagXLMFncE5PFPfGkLAaDs+hSv3VYP3VwBD08jaN16OCpgyNY52kG6YZao7y01NUKlnFMk1NunMFkcU9MFvfEk7IYDM6iS/3WYf3UwRH08DSO1qGDpw6OYJ2nGaQbag1vD3rOamDjxq5WsAyTxT0xWdwTT8piMDiLLvVbh/VTB0fQw9M4WocOnjo4gnWeZpBuqDXOvqunzlScPOlqBcswWdwTk8U98aQsBoOz6FK/dVg/dXAEPTyNo3Xo4KmDI1jnaQbphlqjorzc1QqWUZqb62oFyzBZ3BOTxT3xpCwGg7PoUr91WD91cAQ9PI2jdejgqYMjWOdpBumGWqNOQICrFSwjvF07VytYhsninpgs7oknZTEYnEWX+q3D+qmDI+jhaRytQwdPHRzBOk8zSDfUGuUlJa5WsIxcDR5F4ywmi3tisrgnnpTFYHAWXeq3DuunDo6gh6dxtA4dPHVwBOs8zSDdUGvo8nxDZ/D293e1gmWYLO6JyeKeeFIWg8FZdKnfOqyfOjiCHp7G0Tp08NTBEazz1GOra/AIvDS5O6wzBDVt6moFyzBZ3BOTxT3xpCwGg7PoUr91WD91cAQ9PI2jdejgqYMjWOdZx5JeDJYgIs8AY4A/AXOUUn1drHQGIqKAVkqpvRczf/6uXSzR5HoSg8FgiE1JYcyYMWzYsIH09HT8/PzofO21zJ47l/bt2wNQWlrKc889x9KlS8nKyiI6OpoZM2YwePBgRz8ick7fDz/8MK+//joAv/zyC48//jgbN26kpKSEiIgIxo8fz0MPPVQ7QQ2XjKnfBt2ITUlh3bp19O1b9Ud11rRpTHzuOZYtW8b06dPZu3cvTZo04aGHHuKxxx6rtt8PPviA6dOnc/DgQZRSRERE8PDDD1+W7dnx/fsJaNDA8n6tRAdH0MNTB0ewztMcSa9FRKSniPwgIsdEJFdENohI90qTdARuBl4Fvr+E5awTkVIRKRSRHBH5WESaXKq/wWAwXGksWLCAsLAwhg0bRt26dVn7448MGDCA0tJSACZPnszMmTPx8fEhLi6OrKwshgwZwo8//nhGP82aNWPixImOf5W/GMfExLB69WquueYaBg8ezM6dO3n44Yf59ttvazWroXpM/TZ4Is2bNz9juzR69GhHW9vrr+fHH39k6NChHDx4kHvvvZfy8nIef/xx3n777Wr7TEtLo2XLlowYMYK+ffuyffv2y7Y9C2rWzPI+rUYHR9DDUwdHsM7THEmvJUSkLvAZ8GfgA8AXuAk4cXoapdT/2X/sZ8Eixyul5otIOPAhti8O91rQr8FgMFwxbNy4ka5duwKQmppKZGQkGRkZbN++nS5durBs2TIA5s2bR+/evbnuuuuYNGkSL7zwAp9++qmjn+joaGbNmnVO/ydPniQ9PR2AhQsX0r59e3bs2MGmTZtITU29/AEN58XUb4OncvZ26bXXXgOgS5cu9GjXjvjHHkMpxfTp05kyZQrffPMN/fr1Y+bMmYwbN67KPqdOncrUqVMdrzt27Mi2bds4cOBAtUftL5byoiJL+7sc6OAIenjq4AjWeZoj6bVHawCl1FKl1CmlVIlSarVS6lcAEblGRNaKyFH73vPFIhJ2emYRaWvfw54vIikicqczC1VK5QIfAe3t/SwTkUP2owHfiYjj/DV7/2MqvY4XkfVV9SsioSLyrogcEZE0EfmriJjPk8Fg8ChOD9ABysrKAPD29qZJE9vBTX/7DWI2b95MSUkJW7duBXD8f5qff/6ZwMBAmjRpwogRI8jKygLAx8eHiRMnAjBq1ChGjBjB5s2b6dSpE3fdddflDWdwFlO/DR6PUoo5c+YA8Oijj3IiP58tW7YA0K1btzP+T0tLIz8/v9q+kpKSmDhxIgMHDmTbtm20bduWQYMGWe58ogYHd0EHR9DDUwdHsM7TbJRrj93AKRFJFJHbRaTeWe0CzASaAm2BFsB0ABHxAT4FVgONgEeAxSJy7fkWKiINgMHAFvtbXwCt7P1sBhZfZJ7XgFAgCugNxAH3X2RfBoPB4NYUFhZy//22TdzkyZMdg/SnnnrK8V5gYCAJCQkAHDp0yDFvkyZNiImJYfjw4QAsWrTojGvWY2JiiIiI4L///S+LFi2iTp06xMTEEBISUhvRDOfH1G+Dx/PZZ585rjsfOnQo4e3akZ2dDUBwcDAAQUFBjukrb+POZvv27cyZM4dVq1bh5eXFgAEDLsv2TIfnZuvgCHp46uAI1nma091rCaXUcRHpCTwOzAOuEpHPgQeUUtn2m7mcvqHLERF5BXjW/vp3QDDwd6VUBbBWRD4DhmH/IlAFc0TkZaAIWAdMtnssPD2BiEwH8kQkVCl1zNksIuKN7dS7zkqpAqBARP4JjAAWnDXtWGAsQANN7g5rMBgMAEeTkwlo1IgDW7YQ9/jjbN66lSG9e/P8M8+QnZSEb0gIcTExRPj789OuXZQVFtIoLIzJf/sb9cPCyN+9mzpBQWxevpzQa66hKDOT+Ntuo+c99/Djjz+y64cf8AsMZED//pSUlrJywQKujYxk+F/+wowZMwjx8uKBESMoOXKEem3akL9nj6t/JVckpn6b+u2JHNmyBVVRQVirVuTt3MnLM2cCMOKOO6C0lH0rV9KwXj1+O3SIg//9L60bNCD36FHH/F4ZGeSUlRHUtCnH9+8nqFkzyouKOJGfz/AhQ+jfpg2/5eYy9sknefXVVwnx9eXRkSMpKyggvF07clNS8A0JwTcsjML0dEIiIig5fJjy4mJHu19YGHWCgijKyKBuVBRFmZmcKi11tBdmZNCoSxeKs7MJbdWKgtTUMzIFNGwIcMY2VLy8CImI4NiePQQ2bkzFyZOU5uY6+vT2968y0+n2OoGBBDRqREFqKsEtWlCWn19jpoxvv6VuZKTTmfzDw/Hy8an1TEUZGfjVq+dUpgv9O1mVKeuHH7hm8ODL8neyMtP+FStoetNN52S6UEQpdUkrueHiEJE2wCJgj1JqmIg0BmZju84tBNtZDnlKqRYiMhT4i1Kqe6X5/w7UV0o9UEXf64BFSqn5Z73vDfwNGAI0BCqw7U2PVkrtO3s+EYkHxiiletpfK2x78QuAQ0CwUqrI3jYAeE0p1aq6zFEBAer5qKgL+0UZDAaDi4hNSSEtLY3bbruN3bt38+STTzIlNpb69ju7g+0UeF9fX8fr+Ph4EhMTiYuLIzExkczMTMLCwggMDARg165dtGnTBrAdiUpPT6d79+74+PhQUFCAn58fI0eO5N1332X8+PGOa0RPIyKblFLdaiG+oRpM/TZ4ArEpKY6ft23bRseOHfH39+fgwYM0bNiQo8nJjHr6aVauXMlLL73E1KlT+frrr7ntttu4+uqrSUtLA2Dnzp0AREZG4ufnR0FBwRlHzceNG8fcuXMd20QrOZqcfMb22B3RwRH08NTBEar3vND6bY6kuwil1E4RSQBO33njBUABHZRSuSISA7xub8sEWoiIl31PPMDV2E7BuxBigUHYbmyTiq3A52E7VQ9se+0DK01/VTX95AAngZbA9ko+GRfoYzAYDG7NjTfeSGZmJldffTXFxcU8M2cOPoGBxMbG0qNHD+bNm8fixYvp0KEDycnJ/PDDD4SGhjJt2jQAVq9ezZQpU7j55psJCwvjs88+A+CWW26hcePGBAcHEx4eTm5uLrfccgvXXHMNS5cuBaBnz54uy22oHlO/DZ7G6ZvHDR8+nIb2o5oBjRrx2GOP8emnnzJjxgySk5NZs2YNAE888YRj3rZt2wKwZcsWOnfuTNeuXYmMjCQqKoqMjAxWrVoFQP/+/S33DmjUyPI+rUYHR9DDUwdHsM7TXJNeS4hIGxGZIiLN7a9bYDvd7Sf7JCFAIXBMRJoBUyvN/jNQDDwmIj4i0ge4A/j3BWqEYLsb7VFsxfyFs9p/Ae4WkUARiQZGUwVKqVPY7nD7NxEJEZGW2E7HW3SBPgaDweDWZGZmAnDw4EFmz57Nm/PmMXv2bLZvt41voqOjyc3NJTExkW3btjFw4EA2bNhAdHQ0YLvRUq9evdiwYQPvvvsufn5+PPLII3zwwQeA7RrPzz//nH79+rFjxw6WLVvmuOPy0KFDXRPacAamfhs8mZycHJYsWQLYbhh3moLUVP7whz+wdOlSrr76apYuXYq3tzczZ87kwQcfrLa/fv36sWvXLhYuXMj69evp1q0bCQkJxMbGWu5eoMETMHRwBD08dXAE6zzNkfTaowC4AZhsv+trPrZHupwu5jOAd4Fj2K5tew+YBKCUKhORO4A3gSex7fGOU0rtvECHd4H+9vlzgWnYHilzmleB7kA28Cu2m9JU9ziZR7DdfGY/UIrtOr2F1UxrMBgMWnL2JWFFWVkENfnfY6v79+/vON2zKtq3b8/y5ctrXMYNN9zA119/fWmihsuJqd8Gj6VBgwaUlJSc835wixYADB06tMYdhmdvI998801rBWvgtKM7o4Mj6OGpgyNY52muSTfUGte3b6+2JCe7WsMS8nbsoJ79FC/dMVncE5PFPXF1FnNNusEV6FK/Xb1+OoMOjqCHp3G0Dh08dXCE6j0vtH6b090NtUbFqVOuVrCMsoICVytYhsninpgs7oknZTEYnEWX+q3D+qmDI+jhaRytQwdPHRzBOk8zSDfUGnUCAlytYBm6PKvRGUwW98RkcU88KYvB4Cy61G8d1k8dHEEPT+NoHTp46uAI1nmaQbqh1iiv4ponXcmt9OgS3TFZ3BOTxT3xpCwGg7PoUr91WD91cAQ9PI2jdejgqYMjWOdpBumGWsPL29vVCpbhW+kZoLpjsrgnJot74klZDAZn0aV+67B+6uAIengaR+vQwVMHR7DO0wzSDbWGaFLkncE3LMzVCpZhsrgnJot74klZDAZn0aV+67B+6uAIengaR+vQwVMHR7DO0wzSDbXGqbIyVytYRmF6uqsVLMNkcU9MFvfEk7IYDM6iS/3WYf3UwRH08DSO1qGDpw6OYJ2nGaQbag1vPz9XK1hGSESEqxUsw2RxT0wW98STshgMzqJL/dZh/dTBEfTwNI7WoYOnDo5gnacZpBtqjYqTJ12tYBklhw+7WsEyTBb3xGRxTzwpi8HgLLrUbx3WTx0cQQ9P42gdOnjq4AjWeZpBuqHWUBUVrlawjPLiYlcrWIbJ4p6YLO6JJ2UxGJxFl/qtw/qpgyPo4WkcrUMHTx0cwTpPM0g31Bq6PGfVGXR5VqMzXClZZs2aRceOHfH29kZEmD59uqMtISEBETnn38aNGwFITU2tsv3ll1929BEREXFO+8CBAy9LFt0wWQwGvdGlfuuwfp7t2KdPn3NqR/v27R3tb7zxBtdccw1+fn5ce+21JCYm1th/Xl4eDz30EC1atMDf358ePXrwn//855I93RHjaB06eOrgCNZ51rGkF4PBCfJ27GCJJiuYwbOITUlh06ZNhIeH06JFC9LS0qqc7tZbb+W6665zvG7cuPEZ7W3btuW2225zvO7atesZ7SEhIYwaNcrxut0lfN5zU1Jo3KPHRc/vTpgsBoPemPptPbFnPUt54sSJjp+bNGkCwL///W/Gjx9Pw4YNGTZsGCtXriQ+Pp6rrrqK/v37V9nv8OHD+eKLL7j++uu57bbbWLp0Kf3792fXrl20bNnSaT8dtnXG0Tp08NTBEazzNIP0WkBE1gGdgKuUUidcrGMwXJG89957AMTExFQ7SI+NjSU+Pr7aPnr06MGsWbOqbQ8PD6+x/ULw0+RRI85gshh0xdRvQ21RVe34+9//DsBbb73F4MGDWbBgAWPGjGHmzJlVDtILCgr48ssvAVi+fDktW7YkJCSE2bNn8/LLL/Paa6857aPDts44WocOnjo4gnWe5nT3y4yIRAA3AQq406UyBoOhRiZOnEhAQABt2rRh9uzZ57R/+OGH+Pv7c/XVV/PII49w/PjxM9ozMjIICQmhYcOGDBo0iN27d1+0S52goIue190wWQw6Yuq3oTapV68eYWFh3HLLLfz3v/+lvLyc5ORkALp163bG/7/88kuVffj6+uJtf6b9pk2bKCwsJMV+xH7r1q0X5KPDts44WocOnjoLV02qAAAgAElEQVQ4gnWeZpB++YkDfgISgJGn3xSRBBF5U0S+EJFCEdkgIleJyCwRyRORnSJyfaXpnxCRfSJSICLbReSuSm1b7X2c/qdEpI+97U4RSRGRfBFZJyJtK82XKiJ/EZFfReSYiLwvIv72tnoi8pmIHLH7fCYizSvNGy8i++0+B0Rk+GX8HRoMlxUvLy+6d+/OPffcw+23387evXt59NFHmTt3rmOaqKgo7rrrLoYNG8bx48d5/fXXefDBBx3t9evXZ9CgQcTGxhIaGsrKlSu5/fbbKS0tvSinooyMS87lLpgsBk0x9dtw2QkJCWHgwIEMHTqUli1bsnbtWvr3709OTg6nTp0CIDg4GIAg+5f/Y8eOVVlb/Pz8mDx5MgCDBw8mJCSENWvWAHDo0KEL8tJhW2ccrUMHTx0cwTpPc7r75ScOeAX4GfhJRBorpbLtbfcA/YEU4HPgR+BZYAowwz5fX/u0+7Dt0T8EDAEWiUi0UipLKdXp9MJEZCwwGdgsIq2BpUAMsA6YBHwqItcppcoqOQwASoENQDzwL2w7cN6xt3sDC4HXgRgRCQLmAN2VUrtEpAkQbslvy2BwASNGjCAuLs7x+sknn+Tvf/87H330EWPHjqVly5bs27fP0X7vvfcyYMAAVqxYQUVFBV5eXmzcuBERASA/P5+mTZuyf/9+tmzZwu9///sLdqobFXXpwdwEk8WgKaZ+Gy47K1eudNSOsrIyWrduTVpaGl9//TXe3t6cOnWKwsJC6tevT2FhIQChoaH4+/tX2d+LL77Irbfeyvr16wmw3/DviSeeoGHDhhfkpcO2zjhahw6eOjiCdZ5mkH4ZEZGeQEvgA6VUjojsA2KBV+2TLFdKbbJPuxx4SCn1rv31+8D4030ppZZV6vp9EXkS6AF8ctbyngd6KqWOi8hEYJVS6mt7+8vAROBGbEUfYI5SKtPe/inQ2b68o8BHlfr+G/BtJYcKoL2IHFRKZQFZ1fwOxgJjARr4+Jz3d2YwXA4KMzIoysigblQUZfZT1E+VlZGdlIR/eDgHMjJoEhBAaKtWFKSmUmQ/4nCyoIDjBw5wMCODMC8vGrVvT/6ePeTv3QuAAAVpaeTm5FB27BhRv/89uSkpFJaVOZZdmpND/u7dnMjPJ7xdO3JTUqgTGEhAo0YUpKYS3KIFZfn5lBUUONp9Q0IoOnQIn6AgQiIiKDl8mPLiYke7X1gYdYKCHJmKMjM5VVrqaPcPD8fLx4fi7GxHJlVRQVirVuTt3EmA/ctayZEj1GvThvw9exAvL0IiIji2Zw+BjRtTcfIkpbm5jj69/f0JatqU4/v3E9SsGeVFRU5nSl+zhoadOuEbFkZherrWmY5s3UrkHXc4/k61nclQO5j6ber35SZ/927yDh3Cq2lT/HNzqRMYiHdYGKfs9aPsyBGujYxk+969rF6yhP+LiWG9/ah4h+uu42hyMiXHj5Pn78+xvXu5rmNHfENCyEtN5Q+dO9O5USPKioq478knAejZpQsFaWlOb29+W7uWsFatLltdsGIbWpKTQ/127VxeF2rKlLVhA8HNmrl9rSvJycEnMPCy/J2sypS9caOj/rr6s1dTpvQ1a7jqhhvOyXShiFLqEjYxhpoQkXlAU6XUn+yvnwHuVkp1FpEE4Del1F/tbWOA+5RSfeyvo4GdSqk69tdx2PawR9i7DwbGKaUW2NtbYNvbP1op9YX9vbeAQqXU1EpOPwGvKaUWi0gqMEYptcbeNh2IVkrdJyKB2L6MDADq2WcPAeoopU6JSH/gL0B3bHvwpyildtb0+4gKCFDPa7IXzOBZxKakMH/+fNavX8/atWtJT0+nU6dOdO7cmZiYGGbNmkVubi7du3cnLy+PlStXcurUKd577z3uu+8+pk+fzvz58+nVqxd+fn4sX76cY8eOMXr0aObPn8+6desYOHAgt9xyC1dddRXffPMN+/bt47rrrmPLli34+vpesHN2UpIWdzF1BpPFOkRkk1Kqm8sErhBM/T4TU7+tJzYlhdTUVK699lpuvvlmWrZsyY8//sivv/5K48aNSU5OZvXq1QwfPpyGDRvyxz/+kU8++YT8/Hw+//xzbr/9dlJTU4mMjARsj14LCwvj8ccfZ9OmTURFRZGUlMTWrVtp0aIFv/zyC+Hhzp804eptnTMYR+vQwVMHR6je80Lrt7km/TIhIgHYTjXrLSKHROQQttPVOolIp5rnPqevlsA8bHvm6yulwoBkbAfyTi9rBTDrdIG3k4ntSMDpfgRoAThzscQU4FrgBqVUXaDX6W4AlFJfKaVuBZoAO+1+BoPbsn79ehITE0lPTwdsN9FJTEzkl19+4b777sPf35+PPvqIr7/+mo4dO5KQkMB9990HwM0330z79u1Zs2YNS5cupWHDhvz1r3913Ck3OjqaQYMGsWXLFhITEyktLWXEiBF8+eWXFzVAB32eB+oMJotBJ0z9NtQW9evXJy4ujt27d5OYmEh2djYxMTF88803NGjQgNjYWGbPnk1wcDBLliyhYcOGLFiwgNtvv73aPq+77jr27dvnqHfDhg1jw4YNFzRABz22dcbROnTw1MERzHPSdSAGOAV0AMoqvf8BtuvcLoQgbHeXPQIgIvcD7Su1L8S21/6ls+b7AHhCRG4BvsN2qtwJ4AcnlhkClAD5IhKO7Vo77MtvDPwOWGOfphDb6XMGg9uSkJBAQkJCte1jxoyptq1Xr1706tWr2vbmzZuzePHiS9E7B12eB+oMJotBM0z9NtQKISEhzJtX8z6SCRMmMGHChCrbIiIiOPuM2JEjRzJy5Mgqp78QdNjWGUfr0MFTB0ewztMcSb98jATeUUodVEodOv0P281bhnMBO0iUUtuBf2K7MU02ti8OGypNci9w11l3iL1JKbULuA94DcgB7gDuqHTTmZqYBQTY5/sJ+LJSmxe2U/cygVygN/BnZ/MYDIbz43+BRz3cGZPFoBmmfhuueHTY1hlH69DBUwdHsM7TXJNuqDW6dOyoNv/6q6s1LKEgLY2Qli3PP6EGmCzuicninrg6i7km3eAKdKnfrl4/nUEHR9DD0zhahw6eOjhC9Z7mmnSD23Lq5ElXK1hGcXb2+SfSBJPFPTFZ3BNPymIwOIsu9VuH9VMHR9DD0zhahw6eOjiCdZ5mkG6oNepU80xPHQlt1crVCpZhsrgnJot74klZDAZn0aV+67B+6uAIengaR+vQwVMHR7DO0wzSDbXGqRMnXK1gGQWpqa5WsAyTxT0xWdwTT8piMDiLLvVbh/VTB0fQw9M4WocOnjo4gnWeZpBuMFwEqsJzboZrsrgnJot74klZDAZPQ4f1UwdH0MPTOFqHDp46OIJ1nmaQbqg1vP38XK1gGWGanHLjDCaLe2KyuCeelMVgcBZd6rcO66cOjqCHp3G0Dh08dXAE6zzNIN1Qa5SXlrpawTLydu50tYJlmCzuicninnhSFoPBWXSp3zqsnzo4gh6extE6dPDUwRGs8zSDdEOt4VXH6UfLuj0BDRu6WsEyTBb3xGRxTzwpi8HgLLrUbx3WTx0cQQ9P42gdOnjq4AjWeZpBusFgMBgMBoPBYDAYDG6CGaQbao2K8nJXK1hGyZEjrlawDJPFPTFZ3BNPymIwOIsu9VuH9VMHR9DD0zhahw6eOjiCdZ6ilLKkI4PeiEgX4N/ADcAWYIxSao2Vy4gKCFDPR0VZ2aWlxKakADBy5EjWrFlDTk4OISEhdOvWjZkzZ3L99deTm5vL5MmTWf3VVxzNzaVx48bcddddvPTSS/jZb6yTmJjIP//5T/bu3Uv9+vUZM2YM06ZNw8vLPfeJlR0/jm/duq7WsASTxT0xWaxDRDYppbq5TMDgdpj67XpOf384zdKlS4mNjQVg4sSJzJo1izlz5jBnzhwyMjLw8fGhdevWPPbYY9xzzz3n7X/9+vX07t2biooKBg0axIoVKwAoLS3lueeeY+nSpWRlZREdHc2MGTMYPHjwJWdy9bbOGYyjdejgqYMjVO95ofXbPUcNBgcikioiJSJSKCLZIpIgIsEWL8MPeBu4VymVZ2XfOpKWlkbv3r0ZNWoU9evX56uvviImJgaAyZMnk5iYiChFfHw8hYWFzJkzhxdeeAGADz74gPj4eA4ePMjw4cOpW7cu06dP5x//+IcrI9VI/p49rlawDJPFPTFZDFcipn5fmfz222889NBD1DnrOv4DBw7Qvn177h04kOuvv55NmzYxbNgw9u7dW2N/BQUFxMXFVbmjf/LkycycORMfHx/i4uLIyspiyJAh/Pjjj5ecQ4dtnXG0Dh08dXAE6zzNIF0P7lBKBQNdgG7AX52dUWyc7+98LfCsUmrzJTh6DOvWrWPJkiW89dZbLF26FLAV3ZMnT7Jv3z4AHhk5krfffptRo0YBkJqaCsCyZcsAmDRpEvPmzWPx4sUAvPjii5S76emC4qZH+C8Gk8U9MVkMVzCmfl9BKKUYOXIkTZs2Pedo9quvvsqKFSt46amnWLduHaGhoVRUVHDw4MEa+5wwYQLFxcWMHTv2nLbT3znmzZvH3LlzmTZtGkopx4GDS0GHbZ1xtA4dPHVwBOs89UhrAEAplQF8AXQQkc9E5IiI5Nl/bn56OhFZJyJ/E5ENQDEQJSL3i8gOESkQkf0iMq5S1+HA3LMW111Ettv7f0dE/O1916tp2Z7C66+/zkMPPcSwYcMAmDJlCj4+PkycOBEfHx9eX7SIcePGsXDhQurXr8/48eMB8Pf3ByA5OZni4mI2btwIQF5e3nkLsasIiYhwtYJlmCzuicliuNIx9fvKYNasWaxfv57Fixc7vg9U5ssvv+SZt96iT58+HDt2jJ49e9KzZ89q+1u+fDkJCQksWLCAhlXcMfr0MjZv3kxJSQlbt24FcPx/KeiwrTOO1qGDpw6OYJ2nGaRrhIi0AP4I7AfeAVoCVwMlwOtnTT4CGAuEAGnAYWAgUBe4H3jVfh1bdQwH+gPXAK35395/LyeWrT0ffvghb731Frt376Z58+b84Q9/AKBHjx7ceOONZGRmMnfuXPLy8ujbty9R9mv1Jk2aREBAAB9++CFBQUE88MADjj4PHTrkkizn45gmpw85g8ninpgshisdU789n+TkZJ588kmee+45OnfuXOU0P/30E/+aN4/vvvsOf39//vjHP+Lj41PltIcOHWLs2LE8+OCD/OlPf6pymqeeegqwnfYeGBhIQkKCY95LRYdtnXG0Dh08dXAE6zz1ePClYYWIlAPHgFXAY0qpktONIvI34Nuz5klQSlW+k8mqSj//R0RWAzcB1Z0i97pSKr1S/68Bf1VKHQU+Os+yqdQ+FtuXDRpUU4jchbwdOygrKCC8XTvef+klKnx9+W7LFmLHjOH//u//+O+qVYyaPJktKSlMjYtj0pQpPPvKK8xLTKSirIy3/9//o1l5OclbtvDeW29RWFbG72+4gfvGjaPkxAm8jxzh8KZNhLVqRd7OnY7nKJYcOUK9Nm3I37MH8fIiJCKCY3v2ENi4MRUnT1Kam0t4u3bkpqTg7e9PUNOmHN+/n6BmzSgvKuJEfr6jvU5gIAGNGlGQmkpwixaU5ec7MuWmpOAbEoJvWBiF6emERERQcvgwxdnZnCwqIjclBb+wMOoEBVGUkUHdqCiKMjM5VVrqmN8/PBwvHx+Ks7MJbdWKgtRUVEWF22TyqlOHo8nJlBcXO9p1zSReXmQnJTn+TjpnKs7OJm/HjnM+ezpmqry+VLU+Xe5MBu0w9fsK4PCmTbw7bx5lZWWs/uQTvl29muTt2wFY+cknVOTl8cyUKTw+fjzDO3fmaFAQQ+Ljeeqpp2jauDED2rc/Z3vzcUICOTk57Ny+nVt79uTAb78B8MP33zMyNpZXnnqKu7t2pdO6daxcuhRvPz+atmjB+KlTaVC/Pjm//npJ25uSI0c4smVLrX8nuZBt6KkTJyhIS3N5XagpU9mxY2QnJbl9rfOqU4fspKTL8neyKlPl+uvqz15NmYqzszl+4MA5mS4Uc3d3N0dEUjnrTq0iEgi8CgwA6tnfDgHqKKVOicg6YLFSal6leW4HnsW2V90LCAReVEpNE5E+wCKlVPNKy3xYKbXK/rodsFEpFXC+ZdeUxd3vDhubkkJJSQm+vr54e3sDcOLECRo1asTx48dZu3Ytd9xxB0VFRax87z3uuO8+3nnnHUaNGkX79u3Ztm0b5eXleHt7IyIAjvaWLVty4MABx/vuxLG9ewmNjna1hiWYLO6JyWId5u7u+mDq95VDbEoK06dPZ8aMGVW29+7dm08//ZSQkBDHNqR///6sXr2aZ555hhkzZlBcXMzBgwfx9vamVatWJCQkcP/991fZX8uWLUlNTaWsrAxfX1/H+/Hx8SQmJhIXF0diYuIlZXL1ts4ZjKN16OCpgyNU72nu7n5lMAXbzWJuUErVBXrZ3688AnTsfbHf/fUj4GWgsVIqDPj8rOnPpkWln68GMi9g2dry888/06JFC+69917+/Oc/07VrV44fP07Dhg3p0qWL47T3R554gnHjxvHEE08AOK4p27lzJ61bt2b06NHcfffdjBkzBhHhpZdecssBOkBpbq6rFSzDZHFPTBaDwYGp3x7K9OnTUUo5/o0cORKwPYJt3bp1NGnShDvvvJMJjz9Ov379WL16NV5eXtx6660AJCUl0bZtW7p37w7YBtyV+3v22WcBGDRokONmtfPmzePGG29k3Lhx/OEPfyAxMZHQ0FCmTZt2yXl02NYZR+vQwVMHR7DO0wzS9SQE27Vk+SISjm0Pe034An7AEaDcvlf+tvPM87CINLf3/zTw/kUuWyuaNm1K69at+frrr1mwYAF5eXkMGTKEtWvXEhoaSkJCAiNGjKDs1CkSEhLw8/Nj/Pjxjkes1atXj3r16vH+++/z+eef061bN1asWOHUc1BdRXi7dq5WsAyTxT0xWQwGB6Z+X6H069ePTZs28e/PPmPr1q307t2bTz75pMYbx52P6OhocnNzSUxMZNu2bQwcOJANGzYQbcHRRh22dcbROnTw1MERrPM0p7u7OdWcLtcUWILtcS6ZwD+BfwE+Sqly++lyi5RS8yvN8zDwDLZi/yngA+xVSv21mtPl3sZ285qmwCfAn5VSxedbdk1Z3P10udiUlPNPZCc7KYnGPXpcRpvaw2RxT0wW98TVWczp7vpg6veVgyd+f9DB0zhahw6eOjhC9Z4XWr/NjePcHKVURBXvZQJ9znr77UrtZ7ehlHoDeKOaZawDmld6fXqZMy902TVRNyrqggqZO+NdxaNVdMVkcU9MFvfEk7IYLi+mftc+Ob/+SoOOHV2tUSO6bEN08DSO1qGDpw6OYJ2nOd3dUGt4edDdYYOaNnW1gmWYLO6JyeKeeFIWg8FZdKnfOqyfOjiCHp7G0Tp08NTBEazzNIN0Q61x6sQJVytYxvH9+12tYBkmi3tisrgnnpTFYHAWXeq3DuunDo6gh6dxtA4dPHVwBOs8zSDdUGt4V3pMiO4ENWvmagXLMFncE5PFPfGkLAaDs+hSv3VYP3VwBD08jaN16OCpgyNY52kG6YZaQ52q8TGsWlFeVORqBcswWdwTk8U98aQsBoOz6FK/dVg/dXAEPTyNo3Xo4KmDI1jnaQbphlqjQpMi7wwn8vNdrWAZJot7YrK4J56UxWBwFl3qtw7rpw6OoIencbQOHTx1cATrPM0g3VBr1AkIcLWCZejyrEZnMFncE5PFPfGkLAaDs+hSv3VYP3VwBD08jaN16OCpgyNY52kG6YZao7ykxNUKlpGrwaNonMVkcU9MFvfEk7IYDM6iS/3WYf3UwRH08DSO1qGDpw6OYJ2nGaQbag3x8pyPW53AQFcrWIbJ4p6YLO6JJ2UxGJxFl/qtw/qpgyPo4WkcrUMHTx0cwTpPPba6Bo9Al+esOkNAo0auVrAMk8U9MVncE0/KYjA4iy71W4f1UwdH0MPTOFqHDp46OIJ1nmaQbqg1dHnOqjMUpKbW+jLXrVuHiFT5LyEhgYiIiCrb+vTpA0BOTg69evWifv36+Pr60qxZM+Lj4zm4dWutZ7lcuOLvcrkwWdwTT8piMDiLu9fvMWPG0LZtWxpGRFC/fn3++Mc/kpyc7Gj/4IMPuO666wgODiYoKIh27drx5ptv1tjn9OnTq6ypOTk5jmmOHj3K2LFjueqqq/Dz86Nly5a88cYbNfaryzZEB0/jaB06eOrgCNZ51rGkF4PWiEgEcADwUUqVV9H+FBCllBpzKcspSE1liSY3fXA3YlNSaN68ORMnTnS8V1hYyIIFCwCIjo5m1KhR5ObmOto//vhj0tPTiY6OBqC4uJjCwkLuvPNOvLy8WL58OYmJiZwsLmbxrbfWbqDLRHCLFq5WsAyTxT3xpCwG/TH121YfFyxYwO9+9zt+16UL6374gS+++IJff/2VvXv34u/vT1paGi1btqR3796kp6ezatUqHn74Ydq2bUvfvn1r7H/w4ME0b97c8TrAfhO9EydOcMstt7B161Y6dOjAoEGDyM7OZu/evTX2p8s2RAdP42gdOnjq4AjWeZpBugchIqlAY+AUcBL4AXhQKZV+Kf0qpV64dDvDpRIdHc2sWbMcr1977TUAunTpQs+ePenZs6ej7ciRI7z99tsATJgwAYCrr76azZs3O6Zp164dU6ZM4cD+/bWhXyuU5ecT1KSJqzUswWRxTzwpi8F9MPX70ti4cSNdu3Ylb8cOjgUEEBkZSUZGBtu3b6dLly5MnTqVqVOnOqbv2LEj27Zt48CBA+cdpI8fP95xRlplFi1axNatW+nbty9r1qzBy8nr9nXZhujgaRytQwdPHRzBOk9zurvncYdSKhhoAmQDr7nYx3AZUEoxZ84cAB599NFz2v/1r39RWlrKzTffTMeOHc9oe/TRRxk1ahTPP/88/v7+PHDPPbXiXBuUFRS4WsEyTBb3xJOyGNwOU78vkq5duwK29bOsrAwAb29vmlT6opyUlMTEiRMZOHAg27Zto23btgwaNOi8fcfExBAYGEinTp1YsmSJ4/1vvvkGgPLyciIjIwkNDeWOO+4g9TynuuqyDdHB0zhahw6eOjiCdZ5mkO6hKKVKgQ+B6wBE5E8iskVEjotIuohMr2K24SJyUERyROTp02+KyHQRWVTp9TIROSQix0TkOxFxz3PgPJjPPvuMvXv30qRJE4YOHXpGW1lZGW+99RZQ9QB+9uzZvPPOO+Tl5dGpUye63HxzrTjXBro8Q9MZTBb3xJOyGNwTU78vHt+WLbn//vsBmDx58hmD9O3btzNnzhxWrVqFl5cXAwYMICQkpNq+6tSpQ69evRg6dCg33XQTv/76K8OHD+err74CcFybvmHDBnr27Enr1q357LPPuOuuu2p01GUbooOncbQOHTx1cATznHTDeRCRQGAo8JP9rSIgDggD/gT8WURizpqtJ3AtcAvwjIi0rab7L4BWQCNgM7DYWnvD+Th92vuf//xnfH19z2h7//33ycrKIjo6moEDB54zr1KK/Px8nn76aX7++efzfqHQCV2eoekMJot74klZDO6Jqd8Xx5EjR+jbty8//PADDzzwAC+++OIZ7fHx8Zw6dYo9e/bQuXNnXn31Vf7xj39U29/TTz/Nf/7zH95++22++uor7r33XsB2vxeAhg0bAjBgwAAWL17M559/DsAvv/zCwYMHq+1Xl22IDp7G0Tp08NTBEazzNNekex4rRKQcCAKOAP0BlFLrKk3zq4gsBXoDKyq9P0MpVQJsFZGtQCdgx9kLUEotPP2zfY9+noiEKqWOnT2tiIwFxgI00OQRLu7IyaIiclNS8Pb350B+PmvXrsXfz49ht95KdlIS4e3akZuSQp3AQF795z8BeDA+nvydOykrKCC8XTsOJiURftVV+IaFUZqezi2//z1/Aw5mZlKcn0/B7t34hYVRJyiIoowM6kZFUZSZyanSUkf//uHhePn4UJydTWirVhSkpqIqKghr1Yq8nTsJsH9pKTlyhHpt2pC/Zw/i5UVIRATH9uwhsHFjKk6epDQ319Gnt78/QU2bcnz/foKaNaO8qIgT+flnZApo1IiC1FSCW7SgLD/fkSk3JQXfkBB8w8IoTE+n4uRJjiYnU15c7GjXNdOpEyfITkoiJCKCksOHtc5UkJZ2xt9J50wFaWlVfvZqK5PBozH1+yIoyspiX0oKd48ezb6DB5kwciTTJ02i+NAhx7p5+MABAkQIb9eOkNxcOrRqxebNm9n6ww+U5OSQn5bGvn37CI2OpkFZGYENGnAgI4MmAQGOdbPUfmPW0pwcjh84QGv7zeQqyss5vGkTR4/971eo8vI4VlZW5famIC3tkmtdbWxvCtPT8fLxqbX6fTGZTti3ya6uCzVmys4+43uau9a6ipMnyU5KcovPXnWZKtdfV3/2aspUkJZmSf0WpdRFbhYN7ob9xjNjlFJrRMQbGATMx3bKXEvg70B7wBfwA5YppUZUdXdYEVkHLFJKzbcX8mil1H32fv8GDAEaAhVAqL19X01+UQEB6vmoKEszXynEVtorN3r0aBYuXMjo0aOZP3/+GdN9//339OrVi7CwMNLT0wkODna0TZ8+nY8++oiuXbvi7e3NZ599xuHDh7m5Vy+++c9/ai3L5aQoK0uLm4o4g8ninrg6i4hsUkp1c5mA4bJg6vfFE5uSQrNmzcjMzKRFs2bc/X//97+22Fh69OhB69atiYyMJCoqioyMDFatWkVFRQWLFy8mNjaW1NRUIiMjAcjLyyMsLIzIyEiuuuoqOnTowMGDB/nqq6/w8vJi7dq19O7dm7y8PKKiojh+/Dj33nsvu3fvZuPGjQwcOJBPP/20Wl9Xb0OcRQdP42gdOnjq4AjVe15o/Tanu3soSqlTSqmPsd0ptiewBFgJtFBKhQL/AuQiuo7F9uWhH7biHmF//2L6MlwgOTk5jhvXVHe9OdgG8pUH6ACdO/1pKQcAACAASURBVHfGx8eHjz/+mCVLlhAcHMzEiRN5c9q0yy9eSxSmX9KNkN0Kk8U98aQsBvfE1O8LJzMzE4D0jAxmz57t+Ld9+3YA+vXrx65du1i4cCHr16+nW7duJCQkEBsbW22fDzzwAMXFxSxdupSffvqJG2+8kZUrV9K7d28A6tWrx+rVq7nxxhv5+OOPyczMZNy4cbz33ns1uuqyDdHB0zhahw6eOjiCdZ7mdHcPRUQEuBOoh+2UtxAgVylVKiI9sBXr1RfRdQhwAjgKBAJXxONd3IUGDRpQUlJSbfuHH35YbVtMTAwxMWdfxgjFhw9b4uYOhEREuFrBMkwW98STshjcE1O/L5zTZ4UWHz5MYKNG57S/+eabNc4fERHB2WeWPvXUUzz11FM1zte9e3e+//77C3LVZRuig6dxtA4dPHVwBOs8zZF0z+NTESkEjmM7rW2kUioFeAh4TkQKgGeADy6y/3eBNCAD2M7/bmxj0JQSDxqkmyzuicliMDiFqd+XiA7rpw6OoIencbQOHTx1cATrPM2RdA9CKRVRQ9uH2B7pUlVbKmed7qaU6lPp5+mVfi7EdrpcZd51xi8kIuKMa6t1JjspicY9erhawxLKi4tdrWAZJot7YrIYDDVj6rc16LB+6uAIengaR+vQwVMHR7DO0xxJN9QadQICXK1gGbo8q9EZTBb3xGRxTzwpi8HgLLrUbx3WTx0cQQ9P42gdOnjq4AjmOekGDSmv4Vpq3dDlWY3OYLK4JyaLe+JJWQwGZ9GlfuuwfurgCHp4Gkfr0MFTB0ewztMM0g21hpe3t6sVLMMvLMzVCpZhsrgnJot74klZDAZn0aV+67B+6uAIengaR+vQwVMHR7DO0wzSDbWGaFLknaFOUJCrFSzDZHFPTBb3xJOyGAzOokv91mH91MER9PA0jtahg6cOjmCdpxmkG2qNU2VlrlawjKKMDFcrWIbJ4p6YLO6JJ2UxGJxFl/qtw/qpgyPo4WkcrUMHTx0cwTpPM0g31Brefn6uVrCMulFRrlawDJPFPTFZ3BNPymIwOIsu9VuH9VMHR9DD0zhahw6eOjiCdZ5mkG6oNSpOnnS1gmUUZWa6WsEyTBb3xGRxTzwpi8HgLLrUbx3WTx0cQQ9P42gdOnjq4AjWeZpBuqHWUBUVrlawjFOlpa5WsAyTxT0xWdwTT8piMDiLLvVbh/VTB0fQw9M4WocOnjo4gnWeZpBuqDV0ec6qM+jyrEZnMFncE5PFPfGkLAaDs+hSv3VYP3VwBD08jaN16OCpgyNY51nHkl4MBifI27GDJZqsYLVJbKXnKS5fvpwXXniB5ORkfH196dChA59++imBgYE89thjLF++nOzsbOrXr89tt93GK6+8Qnh4ONOnT2fGjBlV9n/gwAEiIiKqXX5uSgqNe/SwOpZLMFncE5PFYNAbd6jfsSkpzJo1i4ULF5KSkkJFRQXPPvss06dPB6C0tJTHH36Ylf/5D1lZWURHRzNjxgwGDx583r6PHj1Khw4dyMrKIjQ0lPz8/DPalVLcfvvtfPXVVwBs2bKFzp07X1QOXbYhOngaR+vQwVMHR7DO0xxJN1w0IuIjIr+IyJ9c7eIJLF26lLvvvptt27YxaNAghgwZwvHjxykuLmbmzJnMmTOHwsJCRo4cibe3N4mJiUyaNAmA3/3ud0ycONHxr3///gDUrVuXhg0b1rhc//Dwy56ttjBZ3BOTxWBwL3St35s2bSI8PJwWLVqc0zZ58mTmJCbi4+NDXFwcWVlZDBkyhB9//PG8/Y4bN44jR45U2/7GG2/wzTffXJL7aXTZhujgaRytQwdPHRzBOk8zSNcQEVknInki4urbrT4JfKaUWuViD+1RSvH4448D8OWXX/Lvf/+b+fPn8+uvv9KsWTP27dsHwKhRo5g7d65j2tTUVAAGDBjArFmzHP+C7M9oHD16tOPn6vDy8blMqWofk8U9MVkMBhumfl8a7733HuvWravyKPayZcsAmDdvHnPnzmXatGkopXjhhRdq7DMxMZHly5fz9NNPV9m+c+dOHnvsMaZNm3bpAdBnG6KDp3G0Dh08dXAE6zzNIF0zRCQCuAlQwJ0u9PAG8oFnXOXgSezZs4f09HQCAgJ46aWXCA4OJjo6mjfeeAOABx98kJCQEBYuXMi4ceN48cUXCQwMZOrUqef0lZqayieffIK3tzcTJkw477KLs7Mtz+MqTBb3xGQxGEz9vtz4+/sDsHnzZkpKSti6dSuA4/+qSEtLY8KECUyZMoU+ffqc037y5Enuu+8+OnXqVO0g/kLRZRuig6dxtA4dPHVwBOs8zSBdP+KAn4AEYOTpN0UkQUTeFJEvRKRQRDaIyFUiMsu+136niFxfafonRGSfiBSIyHYRuatSW7x9/tdF5Jh93lsqtd8PJAN/A/aKyLhayO3R5OTkAFBSUsL+/fu55557yMjIYPz48axYsYLrrruO2267jby8PObOnctvv/3GDTfcQPv27c/p67XXXuPUqVMMGjSoxmvRTxPaqpXVcVyGyeKemCwGA2Dq92XlqaeeAmynvQcGBpKQkADAoUOHqpy+oqKCuLg4IiMjef7556ucZsaMGezatYtFixbh7e1tiacu2xAdPI2jdejgqYMjWOdpbhynH3HAK8DPwE8i0lgpdXqXzT1AfyAF+Bz4EXgWmALMsM/X1z7tPmx79A8BQ4BFIhKtlMqyt98AfAg0AO4GPhaRSKVULpADDAT2A72AL0Tkv0qpzWfLishYYCxAA01OU6ltspOSCK1059z5b7xBq5AQvMvLmf/ee7y/YAGL33uPjz7+mPuHDuXlf/yDV158kb+98QaD77yTz+fPJ7xdO3JTUigFFsyfD8C4ESPI27GDsoICR7tvSAi+YWEUpqcTEhFByeHD5GzdSlRMDLkpKfiFhVEnKIiijAzqRkVRlJnJqdJSx/z+4eF4+fhQnJ1NaKtWFKSmoioqCGvVirydOwmwX/9ecuQI9dq0IX/PHsTLi5CICI7t2UNg48ZUnDxJaW6uo09vf3+Cmjbl+P79BDVrRnlRESfy8x3tdQIDCWjUiILUVIJbtKAsP7/aTGWFhQQ2akR5cbGjXddMhRkZ+Nat6/g76Zwp7fPPadSlyzmfPR0zHd682bG+VLU+Xe5MBq0x9fsSyE5Kcqw7ZcePA1CYkUFRVhZl+fnc3bUrLefN47uNG/Hy9aV5y5Y8/Je/0KB+fY4mJ5+zbmbm5fHdd9/RoV07BvbrR25eHgBFhYUM6NuXN19+mXcXLqRuSAh/jo9HVXJ5eOxYHp8wgRtat77g7c3Br76iWZ8+l1TramN7c/DLL6nXpk2t1e+LyVR8+DANOnRweV2oKVPm998T0qKF29e64sOH8Q0OdovPXnWZDv38s6P+uvqzV1OmtM8/p8mNN56T6UIRpdT5pzK4BSLSE/gWaKKUyhGRncDbSqlXRSQBOKmUesA+7SPAQ0qptvbXHYDvlVJh1fT9C/CsUuoTEYkHXgCaKfsHRESSgNeUUu9VMe8K4Ful1Oya/KMCAtTzUVEXld2TiU1JoaysjIYNG3L8+HGSkpLo3r07Dz/8MG+++SaPPPIIa9euJSUlhYULF3L//ffz7bffcvPNNxMcHExBQYGjr9dee40JEybQtWtXNm7c6NTyD2/aRKOuXS9XvFrFZHFPTBbrEJFNSqluLhMwXBSmfl86lZ+EEhMTwyeffHLG3d3LysrI37bNsX7Gx8eTmJhIXFwciYmJgO36coDIyEiysrKIjIysdnkHDhygT58+pKWlVdn+zjvvEB8ff8E5XL0NcRYdPI2jdejgqYMjVO95ofXbHEnXi5HAaqVUjv31Evt7r9pfV74IoqSK18GnX4hIHDAZiLC/FYxtr/tpMtSZe3DSgKb2eW8BpgFRQIV9vm0XG8oAvr6+PProozz33HPExcXx+9//nqVLl+Lt7c3w4cM5ceIEKSkpPPHEE/z000+sWbMGgJ49ezr6UEoxZ84cAB599FGnlx2myelDzmCyuCcmi8Fg6rcVzJ8/n/Xr17N5s+3A/4oVK0hNTSUmJoaMjAwWvfsuHTt3Jjk5mR9++IHQ0NAzbvjWtm1b4H+PUKv8a1q3bh19+/Y94xFsp2/OehoROWP+i0GXbYgOnsbROnTw1MERrPM016RrgogEYDsdrreIHBKRQ8Ak/j97Zx5XZZX/8feXTVZF3DI3dNDRtLKynCYnlymrySZabNFJ0WaytN3JlqnRynJqrNwayzGDtPrZ5l5Nm1Q6Fg3upKUpiKioAQoIAnJ+fzyXGyjgVY7c5+B5v1685N5ne3/knud7n+0cOFdEzj3BdXUA/g3cDTTznJ3fCEil2dpIRTVyaA/sEpEQYBHwAtBBKRULfH7UspaT4IknnuCRRx4hLy+P+fPn06NHDxYvXkzv3r2ZPHkyY8aMITQ0lMTERIqKihg2bJj3mTuAZcuWsXXrVlq3bs3NN9/s83ZzPVcWGgI2izuxWSynM7Z+62PFihUkJSWRmZkJOJ3CJSUlsXbtWuLi4tifnU1SUhIbNmxg0KBBrFy5kri4OD9bV8WUfYgJntZRHyZ4muAI+jztlXRziAeOAGcDJZXefwfnObcTIQKnd9l94O1I5ugeyFoC94rIvzzb7obznFwjIAwo9Cx7FXA5Bp2JdytBQUFMmjSJSZMmHTMtKiqKGTNmMGPGjBqXHzRoEOokHl8JO8446iZhs7gTm8VymmPrtyYSExOrnJw+mtTly2lcyy3stdXIfv36HbeG6nhE1JR9iAme1lEfJnia4Aj6PO1BujkMB15XSu2o/KaIzACmAZ/5uiKl1Pci8gJOxzTlwBvAyqNm+xbojNPJTDZwo1LqZ8827wXexin4S4DFvmy3SVwcQzYY812gVg5u317rFwGLxWKxWDzY+m2xWCyWE8IepBuCUurKGt5/B+ds/NHvzwZmV3q9lUp/b6XU34DaBv1USqm7cW6pO3rCy8DLPst7KC8rO9FFXEvRvn0N5iDdZnEnNos7aUhZLPWDrd/1hwnt0wRHMMPTOurDBE8THEGfp30m3VJvBIWG+ltBG027dvW3gjZsFndis7iThpTFYvEVU+q3Ce3TBEcww9M66sMETxMcQZ+nPUi31BtHDh/2t4I2GtJ4xTaLO7FZ3ElDymKx+Iop9duE9mmCI5jhaR31YYKnCY6gz9MepFuOQSmVqJTqc/w5T18koOE0HZvFndgs7qQhZbE0PE73+m1C+zTBEczwtI76MMHTBEfQ52lGWkuDILBRI38raCMqNtbfCtqwWdyJzeJOGlIWi8VXTKnfJrRPExzBDE/rqA8TPE1wBH2e9iDdUm+UFRf7W0EbBwy55cYXbBZ3YrO4k4aUxWLxFVPqtwnt0wRHMMPTOurDBE8THEGfpz1It9QbgcHB/lbQRnirVv5W0IbN4k5sFnfSkLJYLL5iSv02oX2a4AhmeFpHfZjgaYIj6PO0B+mWekMp5W8FbZSXlvpbQRs2izuxWdxJQ8pisfiKKfXbhPZpgiOY4Wkd9WGCpwmOoM/THqRb6g1Txln1heKcHH8raMNmcSc2iztpSFksFl8xpX6b0D5NcAQzPK2jPkzwNMER9Hnag3RLvREUFuZvBW3EdO/ubwVt2CzuxGZxJw0pi8XiK6bUbxPapwmOYIanddSHCZ4mOII+zyAtaznNEZFXgCyl1NP+djmViMhHwP8ppZJOZvncTZt4y5AG5jaGpKWRnJxM//79q53++uuvM2HCBDIyMo6Z1rdvX5KTk9m/fz/XX389aWlp5Ofn06JFCy6//HIeGTqUrpdffqoj1As5aWm0uugif2towWZxJw0pi8XB1vDj4+/6PSQtjSlTpjBnzhzS0tIoLy9n/PjxTJgwAYDi4mKeeuop5iUmsjcnh7i4OJ588kluuOGGGte5bt06HnzwQVJSUigoKKBDhw6kp6dXO++oUaOYNWsWAAsWLCA+Pv6ks5iyDzHB0zrqwwRPExxBn6c9SK8FEUkHzgTOVErtr/T+GqAn0FEpla6UutNPfrcADwA9gEJgO5AEzFSn4AEypdRVutdp8Z22bdty3333eV8XFBTw2muvARAXF8fIkSPJqXSLzQcffEBmZiZxcXEAHDp0iIKCAv74xz8SEBDAggULSEpKoignh/kN5CA9MDTU3wrasFncSUPK0tCxNbwqptfw1NRUYmJiaNeu3TEnpB988EFmzpxJp/btGTZsGO+//z6DBw9m5cqVXHzxxdWub8eOHezZs4fzzjuPr7/+usbtLl26lFmzZhEUFESZhtv+TdmHmOBpHfVhgqcJjqDP0x6kH5/twK3AdAARORsI96uR4zEWGAeMAf4DFOB86fgr8Bpw+ATXF6SUMuOhs9OUuLg4pkyZ4n09ffp0AM4//3z69OlDnz59vNP27dvHq6++CsC9994LQPv27Vm9erV3nu7duzN27Fiy9u2rD/16IeLMM/2toA2bxZ00pCynCbaGNxDmzp0LQHx8/DEH6e+++y4AM6dNY+C113LWWWfxwAMP8Oyzz7JkyZJq13fNNddwzTXXsHDhwhoP0vft28ftt9/OiBEj+OKLL6q9W+1EMWUfYoKnddSHCZ4mOII+T/tM+vGZCwyr9Ho48EblGUQkUUQmen7vJyI7RWSsiOwVkd0iMqLSvFeLyBoROSgimSIyodK0UBGZJyI/i0ieiHwnIsf04y8iTYCngNFKqfeUUvnKYY1SaqhS6rBnvkYiMllEdohItoi8IiJhR3k+LCJ7gNdFpKmILBWRfSKS6/m9baXtJovInz2/x4nIlyJyQET2i8j8Ov9PW3xGKcW0adMAuP/++4+Z/sorr1BcXMyAAQM455xzqky7//77GTlyJBMnTiQ0NJTbr7uuXpzrg4PbtvlbQRs2iztpSFlOE2wN/2W7DbaGh3quXH2TnExRURHr1q0D8P57svzlL38hMjKSqVOn1tmxAlP2ISZ4Wkd9mOBpgiPo87QH6cfnG6CxiHQTkUDgFmDecZY5A2gCtAFuB14WkaaeaYU4XxiigauBu0Sk4uGm4Z7l2gHNgDuBomrWfzHQCFh0HI9/AF1wzs7HeXz+fpRnDNABuAPn8/C653V7z7Zn1LDup4FPgKZAWzxXKSz1w9KlS9m6dSutW7fm5ptvrjKtpKSEmTNnAtUfwE+dOpXXX3+d3Nxczj33XM6+8MJ6ca4PItq08beCNmwWd9KQspwm2BpePQ2qhj/22GMAjJ8yhfDwcBITEwHYs2fPSa9z9uzZLF26lLlz5xIVFaVDEzBnH2KCp3XUhwmeJjiCPk97u7tvVJyJ/xLYBGQdZ/5S4CnPrWcfikgB8GvgG6VUcqX51ovI20BfYKFnuWZAnFJqPZBaw/qbA/sr39omIv8FzsIp/FcAX+MU7XOUUjmeeZ4F3gIe9SxWDoyvOGuPU9Dfr7TOZ4DltWTsgPOs305gRXUzicgdHg+aBwfXsCrL8SgtLCQnLY3A0FAizjyT5596CoARgweTu3YtMd27k5OWRlB4OAu+/JLdu3fzq44dueRXvyI7JcU7PSQqioJdu9i1aROzlyzh+SlTuHHIELZs3UpOWhqNoqMJioigMCuLxp06UbhrF0eKi73Lh8bEEBAczKHsbJp07kx+ejqqvJzozp3J3byZsBYtACjat4+mXbuSt2ULEhBAVGwsB7ZsIbxVK8pLSynOyfGusyLTwW3biGjThrLCQg7n5VXJFNayJfnp6US2a0dJXh4l+flVMoVER1OQmYkqL+dwbi5lhw55p5uaqTg3l8KsLKJiYynau9foTNnffktpt27ev5PJmXI2baLRFVcc89mrr0yWk8LW8Ooz1lrD3VS/83780ds2D+fmAk5dzE5JIbJdO27p14/YOXP4KjWV8tJS2rRrx31PPEGz6GgO7d1ba9s8fPAgAEdKSry1NjQmhjdee43GERFMfPJJyg4dYq/ngH/CY4/xc3o6g6+99qT2N9nffgu9e9ep1tXH/mbvd99RtHdvvdXvk8lUkp+PKivze12oLdP+desozMpyfa0rLSigMCvLFZ+9mjLtX7/eW3/9/dmrLVP2t99Sft55x2Q6UeQU9E3SYPB0OvNnYAvwFbAKWAa8jVPgOiql0kUkEdiplHpcRPoB85RSbY9ej1LqMxHpjXN2vAcQglOQ31VK3SYiwcBjwM04Z+nnAX9TSpUe5XUVsAQIPfoZNBHZCfwJ+B7IBg5UngwEKqUiPZ5vKqXaVFo2HHgJuBLn7DpAFBCklDoiIsmebLNF5AycM/FXA7nAC0qpObX9f3YKC1MTO3WqbRZLDQxJS/P+vmHDBs455xxCQ0PZsWMHLTw7twp69epFamoq06dP5+677/a+n5+fX+VqwKpVq/jtb39LYGAgRUVFBDeAkyjZKSlG9PzpCzaLO/F3FhFJVUr18puAQdgaDmiq4f6u35VrYHx8PIsWLarSu3tJSQkhISHe9pmQkEBSUhLDhg0jKcnpzH7z5s0AdOzYkUaNGnnXt3DhQq677rpjenfv168fX375ZbU+lbd9ovh7H+IrJnhaR32Y4GmCI9TseaL1215J9wGlVIaIbAf+gHPrW114C+f2s6uUUsUiMgXnrDqeQv4k8KSIxAIfAj/gdCJTmVU4ncpcS6Wz5kexH+esenelVE1XDY4+QzMW52pBb6XUHhHpCazB+WJQdUGl9gB/ARCRPsBnIvKVUmprDduyaKKi87ihQ4cec4D+9ddfk5qaSnR0NAkJCVWmvfDCC7z//vtccMEFBAYGsnTpUgD69+3bIA7QwZwxNH3BZnEnDSnL6YKt4Q2jhs+ePZsVK1Z4O0BduHAh6enpxMfHk5WVxZtvvkn3rl35/oEH+O9//0uTJk144oknvMt369YNgDVr1tCzZ082b97MP/7xD3bs2AHA/v37SUhIoHnz5kyePJnk5OQq24+NjSUjI6POQ7CZsg8xwdM66sMETxMcQZ+nfSbdd24HBiilCuu4niggx1PcLwKGVEwQkf4icrbnubmDOGf6y49egVIqD+eLwL9E5EYRiRKRAE9BjvDMUw78G3hJRFp61t9GRK44jlsRkCciMcD4mmYUkcGVOqTJxfmycIyrRS/79+/nrbfeAmp+3hzg9ttvJzIyssq0nj17EhwczAcffMBbb71FZGQk9913HzMeffSY9ZhKTqWrLaZjs7iThpTlNMPW8EqYWMNXrFhBUlISmZmZgNMpXFJSEmvXriUuLo6cnBzmvvkmGzZsYNCgQaxcudI7BGl17Nmzh6SkJJYvd54IKCwsJCkpiffee++U5jBlH2KCp3XUhwmeJjiCPk97Jd1HlFI/aVrVaOAFEZmB83zcOzi3xYHTCcwrOJ24FADzcZ6lq87neRHJwhnC5Q2czmy2AQ8D//XM9jBOJzPfiEhznOfwZuIM91IdU3CuEuwHdgEvADWdLr4QmOLppTYbuE8pZUa3iwbTvHlzioqq64fIobYvF/Hx8dWe/f9540Ytbm4gKNzvIytpw2ZxJw0py+mEreHHYFwNT0xM9HYIVx2bN2/m540badajR7XTj368s1+/fse8VxuVb4WvC6bsQ0zwtI76MMHTBEfQ52mfSbfUG+f37KlWr13rbw0tHNq7l/CWLf2toQWbxZ3YLO7E31nsM+kWf2BK/fZ3+/QFExzBDE/rqA8TPE1whJo9T7R+29vdLfXGkcOHjz+TIeRrOqPuBmwWd2KzuJOGlMVi8RVT6rcJ7dMERzDD0zrqwwRPExxBn6c9SLfUG4EhIf5W0EZku3b+VtCGzeJObBZ30pCyWCy+Ykr9NqF9muAIZnhaR32Y4GmCI+jztAfplnpDHTnibwVtlOTl+VtBGzaLO7FZ3ElDymKx+Iop9duE9mmCI5jhaR31YYKnCY6gz9MepFvqjXJDirwvlOTn+1tBGzaLO7FZ3ElDymKx+Iop9duE9mmCI5jhaR31YYKnCY6gz9MepFvqjaCwMH8raMOUsRp9wWZxJzaLO2lIWSwWXzGlfpvQPk1wBDM8raM+TPA0wRHsOOkWAymrZegw0zBlrEZfsFncic3iThpSFovFV0yp3ya0TxMcwQxP66gPEzxNcAR9nvYg3VJvBAQG+ltBGyFRUf5W0IbN4k5sFnfSkLJYLL5iSv02oX2a4AhmeFpHfZjgaYIj6PO0B+mWekMMKfK+EBId7W8Fbdgs7sRmcScNKYvF4ium1G8T2qcJjmCGp3XUhwmeJjiCPk97kG6pN46UlPhbQRsFmZn+VtCGzeJObBZ30pCyWCy+Ykr9NqF9muAIZnhaR32Y4GmCI+jzDNKyFovFB/LT03nLkE4fLPXPkLQ0pkyZwpw5c0hLS6O8vJzx48czYcIEAN555x0mTJjAjh07UEoRGxvLmDFjGD16NACbNm1i2J13smXbNoqKijjjjDOIj4/nueeeIzQ0tMq2Jk2axGOPPQbASy+9xP3331+vWX0hKjbW3wrasFksFrPxZ/0e4nm+s7b6cPjwYcaNG8cH77/P3n37aNasGQMHDuTFF18kJiam2vXGxsaSkZFxzPt9+/YlOTkZABE5ZvqYMWOYMWPGSecxZR9igqd11IcJniY4gj5Pe5BuOWlEJBj4DvibUmqZv30s5pOamkpMTAzt2rU75stTRkYGHTp0oG/fvmRmZrJs2TLGjBlDt27d6N+/Pz///DMBSjF48GCKi4t5//33mTZtGtHR0Tz55JPe9axZs4bx48cTFBREWVlZfUf0maK9ewlv2dLfGlqwWSwWd2Fi/a6tPkyaNMnZ3zduzPDhw/noo49ISkpCKUVSUlK16xs5ciQ5OTne1x988AGZmZnExcVVma9NmzbceOON3te/+93v6pTDlH2ICZ7WUR8meJrgCPo87UH6aYSIpAOtgCNAIfARcLdSquAkV/kosNSUAm9xP3PnzgUgPj7+mC9hDz30EA899JD39TnnnMOGBLGYagAAIABJREFUDRvYvn07/fv3p0+fPix+9VVaXXQRAE2bNmX69Ols377du0xxcTFDhw7l0ksvpbS0lK+++qoeUp0cZYcO+VtBGzaLxVI3bP2uvT789NNPANwyaBAzZ81ixowZ3HPPPaSnp9e4vr///e/e3/ft28err74KwL333ltlvri4OKZMmaIjAmDOPsQET+uoDxM8TXAEfZ72mfTTj2uUUpHA+UAv4HFfFxSHAM/vgUAe8Pfal7JY9JGSksJ9993HoEGD2LBhA926dePaa6/9ZYbWrbn//vu57bbbmD17NtHR0dx1113eyQ8//DB79uwhMTGx2tsY3YQp44H6gs1isWjB1u8auPPOO4mKimL+Rx8xatQonnvuOcLDw6uc2K2NV155heLiYgYMGMA555xTZdq3335LeHg4rVu35rbbbmP37t11cjVlH2KCp3XUhwmeJjiCHSfdUkeUUlk4Z+LPFpGlIrJPRHI9v7etmE9EkkXkGRFZCRwCOonICGAj8AywVURG+SWE5bTj+++/Z9q0aSxbtoyAgACuvPJKoioNdbEjNZWpU6cyb948ioqK+M1vfkP79u0B+PTTT5k+fTozZ86kbdu2NW3CNZgyHqgv2CwWiz5s/T6Ws846i4EDB5Kbm8usWbPYuXMnvXv3pkePHsddtqSkhJkzZwIc0z9J69atiY+PZ+jQoQDMmzePG264oU6upuxDTPC0jvowwdMER9DnaW93P00RkXbAH4AvgGTgJiAQmAPMAOIrzX4bcBXwAyBAN2AQsA24FPhIRL5TSq2uZjt3AHcANA8OPkVpLA2B7JQUItq0oaywkMO5uQAUZGXx88aNhLVsSX56OoOvuIJrNm5ky+bNjJ44kZdeeonwI0d49JFHKMjMpN0ZZ7B/wwb2ZGXxzzffJGnuXP50000seecdXps6lUaNGvHayy8ze/p0NmzaBMCrL79McU4OIwYNoknnzuSnp6PKy4nu3JnczZsJa9ECgKJ9+2jatSt5W7YgAQFExcZyYMsWwlu1ory0lOKcHGK6dycnLY3A0FAizjyTg9u2/ZIpL887PSg83Jspsl07SvLyKMnP904PiYqivKyM7JQUomJjKdq7l7JDh7zTG0VHExQRQWFWFo07daJw1y6OFBd7p4fGxBAQHMyh7GxXZCrYuZOQqChCoqMpyMw0OlPBzp1V/k71ncliOd3qd0FWVpW2WVEfSgsLyU5JIbJdO0aOHMnCjz9mxE038fcxY0hctIgnX3yR666+mpXLl9faNpf+73/s3r2bjm3bckX//mSnpHjb5uoFC4ju0oX89HRGXHkll9x4I6tWreLHb7/ljJYtT2p/U7Bz50nXhfrc3xTu2sW+NWtOea2rS6aS/HzyMzL8XhdqzbR/P9kpKa6vdaq83Nue/P3ZqylT5frr789ebZkKdu7UUr9FKVXnHajFDDzPtDUHyoADwDJgrFKqqNI8PYHlSqmmntfJwFdKqRpvixORhZ5lpta2/U5hYWpip051jWFpoFT04AvOM4eLFi2q0ntvfn5+lavmo0aNYtasWQwbNoykpCTy8/ORgweJbNMGgLfffpshQ4bQvn17MjIySEhIqLEDoeHDh5OYmHjKsp0MBVlZ3iymY7PoQ0RSlVK9/CZg8Qunc/2uXBug+vrQo0cP0tLS+NcLL3DXgw+yfPlyBgwYQGRkJPn5+QBs3rwZgI4dO9KoUSPv+nr16kVqairTp0/n7rvv9r6/a9cuoqOjCQ8PB+CHH36ga9euAOzZs4dWrVqdVB5/70N8xQRP66gPEzxNcISaPU+0ftsr6acf8UqpzypeiEi4iLwKXAk09bwdJSKBSqkjntdVBvwTkd8DTwCdgHKcLw4bTrm5pcEze/ZsVqxYwerVzkWdhQsXkp6eTnx8POPGjaNjx4506tSJrKwsli1z+ju64oorAKezn3Xffcf5v/kNhw8fZvHixVWmJyYmVjkQ79evH19++aVrh2ArNKQY+YLNYrFo4bSu37XVh0suuYS0tDT+PnEia3/4gc8+c/6b+vTp412+W7dugDPCR8+ePQH4+uuvSU1NJTo6moSEhCrb++STTxg7diwDBgwgOjqapUuXAvD73//+pA/QwZx9iAme1lEfJnia4Aj6PO1BumUs8Gugt1Jqj+dM/Bqc2+Iq8N5uISIhwCLgVpyeYZWILDpqfovlpFixYkWVq93r1q1j3bp1xMbGctlll/Hhhx+SnJxMREQEvXr1YvTo0QwZMgSAiy++mG9XreLtt99GRGjXrh333Xcff/vb3/wVp040bkB3ndgsFssp4bSq37XVh8mTJxMcHMziRYtITEykWbNmDBs2jOeff77WdU6d6txAcPvttxMZGVllWq9evbj00ktZuXIlP//8M61bt+aee+7xXr0/WUzZh5jgaR31YYKnCY6gz9MepFuigCIgT0RigPHHmb8REIYzBAwichVwOYacibe4m6Ovdp8Id9xxB9f/5jc0P6pn3ppITk4+qe3UF4W7dhHWvLm/NbRgs1gsp4TTqn4frz7MmDGDCXfcUWMNqO7xzvfee6/G9fXo0YMFCxacsOfxMGUfYoKnddSHCZ4mOII+T9u7u2UKTtHeD3wDfFzbzEqpfOBe4G0gFxgCLD7FjhaLTxwpLva3gjZsFnfSkLJYjMfW76MwoX2a4AhmeFpHfZjgaYIj6PO0HcdZ6o0Lzj9fpa4+pgNZIyktLCQ4IsLfGlqwWdyJzeJO/J3Fdhxn8Qem1G9/t09fMMERzPC0jvowwdMER6jZ80Trt72Sbqk3yoqKjj+TIZgyVqMv2CzuxGZxJw0pi8XiK6bUbxPapwmOYIanddSHCZ4mOII+T3uQbqk3AoIaThcIoTEx/lbQhs3iTmwWd9KQslgsvmJK/TahfZrgCGZ4Wkd9mOBpgiPo87QH6ZZ6Q8SIDmR9IiA42N8K2rBZ3InN4k4aUhaLxVdMqd8mtE8THMEMT+uoDxM8TXAEfZ72IN1SbxwpLfW3gjYOZWf7W0EbNos7sVncSUPKYrH4iin124T2aYIjmOFpHfVhgqcJjqDP0x6kW+qNoNBQfytoo0nnzv5W0IbN4k5sFnfSkLJYLL5iSv02oX2a4AhmeFpHfZjgaYIj6PO0B+mWeuPI4cP+VtBGfnq6vxW0YbO4E5vFnTSkLBaLr5hSv01onyY4ghme1lEfJnia4Aj6PO1BusVyEqjycn8raMNmcSc2iztpSFksloaGCe3TBEcww9M66sMETxMcQZ+nPUi31BuBjRr5W0Eb0YbccuMLNos7sVncSUPKYrH4iin124T2aYIjmOFpHfVhgqcJjqDP0x6kW+qNsuJifytoI3fzZn8raMNmcSc2iztpSFksFl8xpX6b0D5NcAQzPK2jPkzwNMER9Hme0MCXIhINnOt5uU4plafFwnJakJ+ezlvdu/tbwy8MSUsDYMGCBTz77LNs3LiRkJAQzj77bJYsWcKOHTt48MEHSUlJoaCggA4dOpBewzMto0aNYtasWd71xcfH18ktrEWLOi3vJmwWd2Kz+B9bvy11wZ/1e0haGlOmTGHOnDmkpaVRXl7O+PHjmTBhAgCHDx9m3LhxLFiwgOzsbJo1a8bAgQN58cUXialhvOJ33nmHCRMmsGPHDpRSxMbGMmbMGEaPHg1Aamoq48ePZ+3atezfv59WrVpx88038/TTT9OojncVmLIPMcHTOurDBE8THEGfp89X0kXkGWAP8IXnZ4+ITNRiYQAiki4iJSLS/Kj314iIEpFYH9YR65n3hE6OHLWOKBF50eNTKCI7ROQ9Eel9suu01A9vv/02119/PRs2bODaa69l8ODBHDx4kEOHDrFjxw727NnDeeedV+s6li5dyqxZswgKOumPkMViOc043es32BpuOqmpqcTExNCuXbtjpk2aNIlp06ZRUFDArddfT2BgIElJSTzwwAM1ri8jI4MOHTpw22230b9/f77//nvGjBnD8uXLAdiwYQNfffUVF1xwATfeeCO7d+/mn//8J4899tgpy2ixWCyV8ekgXUTuBB4FQgDx/IQAj4rIHadOz3VsB26teCEiZwPh9bVxEWmE8wXrbGAQ0BjoBvwfcFUNy9ijOReglOLhhx8G4OOPP+b//u//mD17NuvXr6dNmzZcc801pKWl8eCDD9a4jn379nH77bczYsQI2rRpo82taN8+bevyNzaLO7FZ/Iet31WwNdxQ5s6dS3JyMj179jxm2k8//QTAyJEjee6BB7y1tqa70QAeeughPvroI2bOnMnSpUs5++yzAdi+fTsAffr0ITMzk0WLFjFv3jzvwfmnn35a5yym7ENM8LSO+jDB0wRH0Ofp65X0OwGFU0iu9fzMxyn2d2kxMYO5wLBKr4cDb1SeQUSu9pyZPygimSIyodLkrzz/5olIgYhcLCIBIvK4iGSIyF4ReUNEmtSw/duAtkC8UmqjUuqIUqpQKfWeUsq7Hc+Z/jEisgXY4nnvLyKyVURyRGSxiJzpeV9E5CXPtg+KyAYR6eGZ9gcR+V5E8kUkS0T+Wmkb1a7PUj1btmwhMzOTsLAwnn/+eSIjI4mLi+Pll1/2eR1/+ctfiIyMZOrUqVrdmnbtqnV9/sRmcSc2i1+x9fsXbA3/ZRsNpobfeeedREVFMWfOHP42cybPPfcc4eHhPPTQQ7Uul5KSwn333cegQYPYsGED3bp149prrwUgLi6OJk1++TOWlJQA0LZt2zr7mrIPMcHTOurDBE8THEGfp68H6b8G0pVSQ5RSSzw/twLpnmmnC98AjUWkm4gEArcA846apxDnS0A0cDVwl4hUPDR8qeffaKVUpFJqFZDg+ekPdAIigRk1bP8y4D9KqUIfXOOB3sBZIjIAmATcBLQGMnC+sAEM9Hh1AZp45vnZM+01YJRSKgrogXMFgOOsz1IN+/fvB6CoqIht27Zx0003kZWVxd13383ChQuPu/zs2bNZunQpc+fOJSoqSqtb3pYtWtfnT2wWd2Kz+BVbv3/B1nAaXg0/66yzGDhwILm5ubyWmMjOnTvp3bs3PXr0qHW577//nmnTprFs2TICAgK48sorq62vK1eu5KWXXiI0NJSJE+v+lIgp+xATPK2jPkzwNMER9Hn6ehtVGRAuIsFKqVIAEQkBwoAjWkzMoeJM/JfAJiCr8kSlVHKll+tF5G2gL1DTkdhQ4EWl1DYAEXkU2CgiI5RSZUfN2xz4X8ULEekJJOOcbNmtlKr8hWuSUirHM99QYI5SanWlbeR6nsErBaKArkCKUmpTpXWU4nxBWKeUygVyKzlXuz6lVHplYc/tlHcANA8OruG/oOHTOCTE+/ucmTP5VUQEgaWlzJ43j/mvvcYfBgwgb8sWDmzbBsCRkhLyMzIoLy2lOCeHeW+8QeOICCY88giBoaHs3bMHgKeeeILdGzbw5wcfJCctjaDwcMJatiQ/PZ3Idu0oycujJD+fmO7dyUlLIyQqipDoaAoyM4mKjaVo715yN2+madeu5KSl0Sg6mqCICAqzsmjcqROFu3ZxpLjYu3xoTAwBwcEcys6mSefO5Keno8rLie7cmdzNm72dZRTt20fTrl3J27IFCQggKjaWA1u2EN6qlTdTxToDQ0OJOPNMDm7bRkSbNpQVFnI4L887/UQylRQU8PPGjZQdOuSdbmqmw7m5ZKekeP9OJmfK3byZ4PDwYz57Jmaq3F6qa0+nOtNJYOt3VWwN97GGu6V+F2Rledtm+RHnI3to714O7d1Lfno6oydO5IMlS0i44QaeGDOGOe+/zzMvv8yN113HsldfrbFt3nj55VyxahU/BwQwNCGBl156ieioKEZdfbW3bS7+4APuePxxBEicPJkecXFkp6TUaX+Tu3kz4WecUadaVy/7mx9/rNf6fTKZDu3dS35Ght/rQm2ZDqano44ccX2tO3zgANkpKe747NWQqXL99fdn73iZQj2dVtalfotS6vgziXwFXIJTXBZ43r4O6AWsVEpdWtOyDQURSQf+jHPr2VfAKmAZ8DZOIeyolEoXp/OXf+CctQ4BGgHvKqVu8xTU7UBwRfEWkU3AX5VSyzyvQ4EioK1SqsqXBxGZDxQrpYYf9f5lwGylVKzntQK6KKUqbpP7CFiqlHq50jJ7gBuUUitF5F6c2/46AB94fA6KyIXA4zhn6dcDjyilVh1vfTX9H3YKC1MTO3U6zv90w+TGNWto0aIFBw8eJCUlhQsvvJAxY8bwr3/9i3vuuYdp06YBsHDhQq677rpjenfv168fX375ZbXrrtzL7clQnJtLaNOmJ728m7BZ3InNog8RSVVK9TqB+U/7+g22hlPHGu7P+l0xOgpAfHw8ixYtqlL3evToQVpaGnPmzOHW+HhWrV3LgAEDiIyMJD8/H4DNniGROnbsSKNGjcjPz69y1bxi1JRhw4aRlJQEOM/Bjxw5ksaNG7N06VIuvvhiLXn8vQ/xFRM8raM+TPA0wRFq9jzR+u3r7e6TcZ5f6wU84/m50DPteV831hBQSmXgFOk/4BTDo3kLWAy0U0o1AV7B+b8D57nAo9mFU1graI9z5SO7mnk/BwaKSIQvqjVtw7N8MzxXEJRS05RSFwBn4dwy95Dn/e+UUtcCLXGuIrzjy/osxxISEsL9998PwLBhwxg5ciRz5swhMDCQoUOHsnnzZhISErwH6/v37ychIYG//tV5hDA5ORmllPenQwfnv3/BggV1OkAHOGDI7UO+YLO4E5vFr9j6XQlbw4+/Pjcye/ZsEhISWL16NeCc0E5ISGDhwoVccsklADzyyCPcMXIkf/7znwGn87cKunXrRrdu3di0ybnR4IILLuCKK67grrvu4o9//COzZ88G4IorrgDgk08+Yfjw4ZSVlXHRRRcxf/587r//fm8drwum7ENM8LSO+jDB0wRH0Ofp00G6Umoxzu1hmfzSO+wOYJhSaqkWE7O4HRhQw3NlUUCOUqpYRC4ChlSatg8ox3lurYK3gQdEpKOIRALPAvOruU0OnA5udgMLRKSHiAR6ztof76zM28AIEekpTu+yzwLfeq4aXCgivUUkGOdZvGKgXERCRGSoiDTx3CJ50ONe6/qO43Fa88QTT/DII4+Ql5fH/Pnz6dGjB4sXL6Z3797s2bOHpKQk7/AvhYWFJCUl8d57751yr/BWrU75NuoLm8Wd2Cz+w9bvarE13LAavmLFCpKSksjMzARg3bp1JCUlsXbtWiZPnsyYMWMIDQ1l/ocfUlRUxLBhw0hMTKxxfZdddhk//PADc+bMYcWKFfTq1YvExESGDHH+3Lt27aLiTtOPP/6YqVOnen/qiin7EBM8raM+TPA0wRH0efo8tIdSah4wT0RaeF6b0Q/+KUAp9VMtk0cDL4jIDJxn3t7B6YAGpdQhccarXekpqFcCc4AzcW6/CwX+A9xTw3aLRaQ/8CTObXrNgf04tzHeVIvvZyLyBPA+0BT4L06HOeAMAfMSzpeOYs/2/+mZdhsww9PBzg84z7Edb32WGggKCmLSpElMmjTpmGn9+vXzfiHwhdqGljlRyktLta3L39gs7sRm8S+2flfF1nDzanhiYmKtB90zZsxgxowZHNi6lSZxccdMP7q+/utf/6p1ewkJCSQkJJyM6nExZR9igqd11IcJniY4gj5Pn55J987sdDbTAgis/L5SaocWG0uD5txu3dS6TZuOP6MBZKek0Oqii/ytoQWbxZ3YLO7E31lO9Jm2SsvZ+m05aUyp3/5un75ggiOY4Wkd9WGCpwmOULPnidZvn66ki0gUMBtnSJCjl1G+rsdyehMUFuZvBW3EdO/ubwVt2CzuxGZxJ6ZlsfXbogNT6rcJ7dMERzDD0zrqwwRPExxBn2eNz6SLyA8i8qDn5URgMBDML8+0Vf6xWI5LWVGRvxW0kVOpt1nTsVncic3iTkzIYuu3RTem1G8T2qcJjmCGp3XUhwmeJjiCPs/aOo4bCjzh+f1anDPuz3he/4TT42kOcLcWE0uDRwJ8HUzA/QSGhvpbQRs2izuxWdyJIVls/bZoxZT6bUL7NMERzPC0jvowwdMER9DnWdte91bgRc/vrYFtSqmKor9fKTUaOACcr8XE0uAJCA72t4I2Is48098K2rBZ3InN4k4MyWLrt0UrptRvE9qnCY5ghqd11IcJniY4gj7P2g7SRwLfen4/DOR7fi8G2np6Nm2EcxudxXJcjhw+7G8FbRzcts3fCtqwWdyJzeJODMli67dFK6bUbxPapwmOYIanddSHCZ4mOII+z9oO0u8DHvP8vgdo4/n9J5zhRvZ5/jVjz23xO4EhIf5W0EZEmzbHn8kQbBZ3YrO4E0Oy2Ppt0Yop9duE9mmCI5jhaR31YYKnCY6gz7PGg3Sl1BtKqX6el98C4SJyDpCI09lMY8+0N7SYWBo86sgRfytoo6yw0N8K2rBZ3InN4k5MyGLrt0U3ptRvE9qnCY5ghqd11IcJniY4gj5Pn4ZeUUrdVunlehHZDfwGWA+8psXE0uApN6TI+8LhvDx/K2jDZnEnNos7MS2Lrd8WHZhSv01onyY4ghme1lEfJnia4Aj6PEUppWVFFsvxuOD881Xq6tX+1tBCaWEhwRER/tbQgs3iTmwWd+LvLCKSqpTq5TcBy2mJKfXb3+3TF0xwBDM8raM+TPA0wRFq9jzR+u3TlXQReQUYCFyvlFrree9c4APgP56eYi2WWsndtIm3unf3twZDPOMXDh8+nM8++4z9+/cTFRVFr169mDRpEueddx7Tpk1j2rRpZGVlERwcTJcuXRg3bhw33XQT4IyBGPSrX/Hoo4+yePFicnNzOeOMMxg3bhxjxozxZ7wTJictjVYXXeRvDS3YLO7EZvEftn5bdHCq63dFXZ4yZQpz5swhLS2N8vJyxo8fz4QJE6rM+/PPP3P22Weze/dumjRpQl6lq1Y1tc+tW7fSs2dPCgsLOffcc1m7di0ASilefPFFZs2aRUZGBm3btmXs2LHcddddpyyrKfsQEzytoz5M8DTBEfR5+jrw5TVAUEWBB1BKrcM5yP+jiAwUkSki8vs6G1lqRUQSRWSivz0aAhkZGfTt25eRI0fSrFkz/vOf/xAfHw/A9u3b6dGjByNGjOC8884jNTWVW2+9la1btwJwJCiI3//+9/z73/+mZcuWJCQkcN5553mnm0RQeLi/FbRhs7gTm8Wv2PrtImwNr53U1FRiYmJo165djfOMGjWKffv2VTutuvZZVlbGn/70Jw5X00P9P//5T/7617+Sn5/P8OHDKS0tZfTo0cyfP//kQxwHU/YhJnhaR32Y4GmCI+jz9OlKOtAcqO7oowDoCowFdgNzcXqMtWhARJKBc4EzlFK2F17NJCcne39fvXo1F1xwATt37qS0tJSXXnrJO00pRdOmTTlw4AA7duwgLi6ORV9+ybp16+jfvz+fffYZAQG+nu9yH2EtW/pbQRs2izuxWfyKrd9+wtbwE2fu3LkAxMfHk5GRccz0pKQkFixYwBNPPMGTTz55zPTq2uczzzzD+vXrGTt2LM8991yVae+++y4AkyZNYvjw4SxcuJDrrruOiRMncvPNN+uI5JOjGzHB0zrqwwRPExxBn6evRxY/A11E5JKKN0Tkt8Cvgb1KqSuAMUBTLVYWRCQW+B2ggD/6VaYBM2PGDEaPHs2tt94KwNixYwkODgbg448/5p577qFfv34cOHCAPn360KdPHwA+/fhjwDlD37FjR5o0acI111xDenq6X3LUhXwDnWvCZnEnNotfsfXbD9garp+MjAzuvfdexo4dS79+/aqd5+j2+d133zFx4kQmT55M165dj5k/NDQUgLVr11JcXMxqz3P333//PaWlpVr9a3J0KyZ4Wkd9mOBpgiPo8/T1IP0LIBD4QkQ+F5HPgeU4Q7l85pknCnhYi5UFYBjwDc6QOcOrm0FEmorIUhHZJyK5nt/bVpreUUS+EpF8EflMRF4WkXmVpv9RRNJEJE9EkkWkW6Vpj4jIT55lvxeR6ypNixORL0XkgIjsF5FTd1/YKea9995j5syZ/Pjjj7Rt25ZLLvF+j+Wbb75hxowZfPXVV4SGhvKHP/zBewB/oLgYgJUrV9KnTx+6dOnC0qVLue6666rdjpuJrOW2QtOwWdyJzeJXbP32D7aGa6S8vJxhw4bRsWNHJk6s+WmByu3z0KFD/OlPf+Lyyy9n9Ojqu154+OGHCQwMZMqUKYSFhfH00097t1fTLfV1xZR9iAme1lEfJnia4Aj6PH09SB8PHACCgX6en2AgzzMNpdQepdQ0LVYWcAr8m56fK0SkVTXzBACvAx2A9kARMKPS9LeAFKAZMAHwDsUjIl2At4H7gRbAh8ASEQnxzPITzlWAJsCTwDwRae2Z9jTwCc6Vl7bA9LpF9R/JyckUFRWxcOFCdu3axY033ui9xW7ChAmUlpaybt06WrZsyWOPPcZbb70FQExUFABXXnklb775Jh9++CHgnI3fsWOHf8KcJCWGDGnhCzaLO7FZ/Iqt3/7B1nCNZGZm8tVXX6GU4vrrr+fRRx8FoLCwkEGDBrF3716gavv87rvv+PHHH8nNzWXQoEFMmTIFcPqcGTRoEACDBg1iw4YNTJo0ib///e8sWLAAgMDAQGJiYk5JFlP2ISZ4Wkd9mOBpgiPo8/R1nPSfRKQX8Degoru6b4FnlVLbtJhYvIhIH5yi/Y5Sar+I/AQMAV6qPJ9S6mfg/UrLPYNzhQQRaQ9cCPxeKVUCrBCRxZUWvxlYppT61DP/ZOA+4LdAslLq3UrzzheRR3H+9ouAUo/fmUqpncCKWrLcAdwB0NxzFdrflBYWkpWaSniTJkS2bk1+ejq/O/dcIsLDyS8o4Me0NMq2bSPmjDMIiY6mVXExnTt1YseOHaxevpyb4uNp7xlaoay4mOyUFA43buxdfyMRslNSCI2JISA4mEPZ2TTp3Jn89HRUeTnRnTuTu3kzYS1aAFDAEeyKAAAgAElEQVS0bx9Nu3Ylb8sWJCCAqNhYDmzZQnirVpSXllKck0NM9+7kpKURGBpKxJlncnDbNiLatKGssJDDeXne6UHh4YS1bEl+ejqR7dpRkpdHSX6+d3pIVBQh0dEUZGYSFRtL0d697Fu9msj27clJS6NRdDRBEREUZmXRuFMnCnft4khxsXd5t2c6nJtL+ZEjlB065J1uaqaD6emU5Od7/04mZ8r+7juAYz57JmbK/u47b3uprj2d6kwniq3f9U9DqeH1Wb8PbN1apW2WHDwIQEFWFgVZWRz46ScA1q9fz/r1673LlZWVsWzZMnavX09JeDg/bd1K4IYNdOvenUP79wPOXXGVOXjwIMuWLaMgK4u8jAxiu3Thz3/4A0eKi5nuOUjvff75lGZnc+AU7G+yv/uO4MaNtdTvU7m/yU5Npay4uN6/k5xIpoKsLILCw/1eF2rLtH/9+irT3VrrCrOyKMnPd8Vnr6ZMleuvvz97tWXK/u47Aj2P0tSlfttx0l2IiPwbp3he7Xn9d5zhc3qKSCKwUyn1uIiE4xT9K/nlecIonJMvFwKLlVItK613EtBOKfUnEZkJFCilHqo0/RtgulLqTREZBjwIxHomRwKjlFKvicgZOGfirwZygReUUnOOl6tTWJia2KnTSf6v6GNIWhrJyckMGTKESy+9lKZNm/L111+TlpZGixYt2LJlC23atGHAgAG0adOGLVu28PnnnxMQEMCXX35Jnz592LtzJ78++2wOHjzILbfcwo8//sj//vc/Bg0axJIlS/wd8YQwZdxJX7BZ3InNog87Trr7aYg1/FTX74oh2GbPns2KFSv44osvyMzM5Nxzz6Vnz57Ex8d7R18B5y64/v37VxmCLT09nY4dOwKQm5tLdHR0lW0kJiYyYsSIKkOwLV26lMcff5wLL7yQHTt28MknnxAcHMzy5curPP6mE3/vQ3zFBE/rqA8TPE1wBH3jpPvcJbWIhIhIfxEZKiLDKv/4ug7L8RGRMOAmoK+I7BGRPcADwLnijG1bmbE4nf/0Vko1Bi6tWA1Ob70xni8BFVR+SGIXzpn0iu2KZ3qWiHQA/g3cDTRTSkUDGz3rrbg18i9KqTOBUcC/RCROQ/x648wzz6RLly58+umnvPbaa+Tm5jJ48GC++OILmjRpwmWXXUZqaipz5sxh3bp19O3bl0WLFnk7jlO7dvHJJ5/w29/+lg8++IBdu3YxatQob8+0JpHj+XLUELBZ3InN4l9s/a4/bA2vGytWrCApKYnMzEwA1q1bR1JSkvegWjdt2rShvLycN998kxUrVtCvX79TeoAO5uxDTPC0jvowwdMER9Dn6dPt7iLSGaeDmbbVTFbAG1psLADxwBHgbKCk0vvv4DzjVpkonGfY8kQkBs/zhQBKqQwR+R8wQUQeBy7AGS93SaX1PSLO2Lhf4dwmdxj4LxCH83fdByAiI4AeFesWkcHAKs9tcrmeecvrnLwe6dKlS5Uh2I5m4cKFtS4fEhXFhd268fXXX2s2q39CPM/XNwRsFndis/gPW7/rHVvD60BiYiKJiYnHna9fv34cfSdobGwsOd9/T9Nu3apdJiEhgYSEhCrvnXfeeVVun68PTNmHmOBpHfVhgqcJjqDP09cr6f/AOUMrNfxY9DEceF0ptcNztnuPUmoPTmcyQ6l6YmUKEAbsx+lF9uOj1jUUuBhnCJ6JwHycIo5S6gfgTzgdxuzHKf7XKKVKlFLfAy8Aq4BsnC8bKyut90LgWxEpABYD951uzzaGHHUbncnYLO7EZnEnBmax9bt+sTXcj5jQPk1wBDM8raM+TPA0wRH0efp0JR2nh9Ay4CrgU2AN8DxOcbhFi4kFAKXUlTW8/w7OmfPK7+3C6am3Mq9Wml7RuysAnmFWNleavgBYUMP2/obT0VB108YB42qJUS1RsbHe585MpyAzk4jWrY8/owHYLO7EZnEnBmax9bseaag13JT6bUL7NMERzPC0jvowwdMER9Dn6euV9Ghgk1Lqc5zbokqVUvOBPcBjdbawnBJE5EIR+ZWIBIjIlcC1QO33cZ9CAhs18temtRMVG+tvBW3YLO7EZnEnBmax9dtQ3FTDTanfJrRPExzBDE/rqA8TPE1wBH2evh6k51eatwDoKiK9ccb1vFiLieVUcAaQjPM3mwbcpZRa4y+Z8tJSf21aO0WeMVkbAjaLO7FZ3ImBWWz9NhfX1HBT6rcJ7dMERzDD0zrqwwRPExxBn6evt7vvAH4lIoHABpzC/l/PtO1aTCzaUUot4ZdOZvyOKndFvzRaKDt0yN8K2rBZ3InN4k4MzGLrt6G4qYabUr9NaJ8mOIIZntZRHyZ4muAI+jx9vZL+JvAl0AV4BijF6XCmHJigxcTS4AkKC/O3gjZiunf3t4I2bBZ3YrO4EwOz2PptqTOm1G8T2qcJjmCGp3XUhwmeJjiCPk+fDtKVUpOVUtcopTYppT4CugE3Aj2UUvO0mFgaPGVFRf5W0IYpYzX6gs3iTmwWd2JaFlu/LTowpX6b0D5NcAQzPK2jPkzwNMER6nGcdBEJxulgJgfoohy2Y2+Ts5wgAYGB/lbQRiNDhoHwBZvFndgs7sSkLLZ+W3RhSv02oX2a4AhmeFpHfZjgaYIj6PM87pV0pVQpzricxUoppWWrltMSMaTI+0JQRIS/FbRhs7gTm8WdmJTF1m+LLkyp3ya0TxMcwQxP66gPEzxNcAR9nr4+kz4F+LWIXK5lq5bTkiMlJf5W0EZhVpa/FbRhs7gTm8WdGJjF1m9LnTGlfpvQPk1wBDM8raM+TPA0wRH0efrau/tVOJ3MfCwiPwDZOOOtAiil1O+12FgaNKaMs+oLjTt18reCNmwWd2KzuBMDs9j6bakzptRvE9qnCY5ghqd11IcJniY4gj5PXw/S++IUdQG6en4qXttb6BoIIjIUGK6UGnjU+52A5UAfpVTmya4/74cfeEtjz4xD0tKYMmUKc+bMIS0tjfLycsaPH8+ECRMAKC4u5qmnnuLtt99m9+7dxMXF8eSTT3LDDTd41yEix6x3zJgxzJgxo9ZtF+7aRVjz5tqy+BObxZ3YLO7EwCy2fp8GmFK/h3g6VKqtdgO8++67TJgwga1bt9K6dWtGjx7NuHHjalzv4cOHGTduHO+/8w77cnJo1qwZAwcO5MUXXyQmJgY4+XqvG1P2ISZ4Wkd9mOBpgiPo8/T1IP0rbDE3BhG5BXgA6AEU4nQSlATMrO25RKXUmzjD9RzNK8AddSnwp4rU1FRiYmJo164dGRkZVaY9+OCDzJw5k86dOzNs2DDef/99Bg8ezMqVK7n44ou987Vp04Ybb7zR+/p3v/vdcbd7pLhYXwg/Y7O4E5vFnRiYxdZvgzhd6ndttXvVqlXcfPPNREREcMstt/D555/z8MMP06RJE0aNGlXt+iZNmsS0adOIbtyY4cOH89FHH5GUlIRSiqSkJO98J1PvdWPKPsQET+uoDxM8TXAEfZ4+HaQrpfpp2ZrllCMiY4FxwBjgP0AB0BP4K/AaTidCJ7K+dsAcpdR/NKtqYe7cuQDEx8cfU+jfffddAP7973/Tt29fzjrrLB544AGeffZZlixZ4p0vLi6OKVOmnNB2TRmr0RdsFndis7gT07LY+m0Op1P9rq12P/fccyilmDBhAmPHjuXzzz/nsssuY9KkSTUepP/0008AjEhI4MWpU5kxYwb33HMP6enpVeY7mXqvG1P2ISZ4Wkd9mOBpgiPU8zjpFYjIxSLygIiMEJHGItJeRMx4UOk0QESaAE8Bo5VS7yml8j1D7qxRSg1VSh0WkSYi8oaI7BORDBF5XEQCPMsniMiKSuubCvwXmCUiqSLyu0rTLhKR/4nIQRHJFpEX6zvv8QgNDQVg9erVFBUVsW7dOgDvvxV8++23hIeH07p1a2677TZ279593HWbMlajL9gs7sRmcSemZrH1293Y+v0La9asAaBXr15V/s3IyCAvL6/aZe68806ioqJ4PTGRUaNG8dxzzxEeHs5DDz1UZb6Tqfe6MWUfYoKnddSHCZ4mOII+T58O0kUkREQWASuAycBfgMtxbsO6T4uJRQcXA42ARbXMMx1oAnTCeVZxGDCihnlTcc7ixwBvA++KSKhn2lRgqlKqMfAr4J0622vmscceA5zb3sPDw0lMTARgz5493nlat25NfHw8Q4cOBWDevHlVnlmviVDPM24NAZvFndgs7sS0LLZ+G4Ot3x6ys7MBiIyMBCCi0nBGlet3Zc466ywGDhxI3sGDzJo1i507d9K7d2969Ojhnedk671uTNmHmOBpHfVhgqcJjqDP09dn0p8ErjnqvWVACXA18LwWG0tdaQ7sV0qVVbwhIv8FzsIp/lcCtwA9lVL5QL6IvADchnMrXRWUUm9UejlZRB4Hfg2sA0qBOBFprpTaD3xTnZCI3AHcAdA8OLjuCSuxb80aomJjObBlC2WHDgFQkJVFaWEhOWlpDL7kErr/5z98+MEHBEdF0TI6mnsff5wWzZuTnZJCUHg4W9asoSAjg8h27fjLddfR++qrWbVqFes//JB2HTsSEh1NQWYmUbGxFO3dS9mhQ8R0707Opk2o8nKCIiIozMqicadOFO7axZHiYmd6WhqhMTEEBAdzKDubJp07k5+ejiovJ7pzZ3I3byasRQsAivbto2nXruRt2YIEBHgzhbdqRXlpKcU5Od51BoaGEnHmmRzcto2INm0oKyzkcF6ed3pQeDhhLVuSn55OZLt2lOTlUZKf750eEhV1TKaD27cT3ro1OWlpNIqONjpTQFAQP2/c+MvfyeBMpYWFZKekHPvZMzHTpk2Ul5bW3J4MypS3dau3vVTXnk51ppPA1m8zOC3qd8nBg1Xa5uHcXACKc3LITkkhpnt3mjdtStaePfy8cyfZR45Q6jlYB2gWFeWt35Xb5siRI1n48cfcfuutPH7nnSQuWsSTL77IdVdfzcrlyynau5fVCxbQrEcPctLSuOOGG7joqqtYtWoV2zZupHF5eb3tb3I2bSIwLExL/T6V+5vcH36gJD+/3r+TnEimI4cPu6Iu1Jbp4PbtVdbv1lpXXlJCdkqKKz57NWXK2bTJW3/9/dmrLVPOpk1IYOAxmU4UqaUfkl9mEkkHWgG/xzkb/41S6rci8iMQpZRqfcJbtmhHRK4ClgChlQu9Z9pOYCzwf0CkUqrQ8/6VwHSlVGcRSQD+rJTq45l2N3A7zpeHI0Bb4Aql1Oci0hnn1ryKKzJPKqWW1ubXKSxMTdQ4fEJFL7HgPNe2aNGiKj3ElpSUEBIS4p0nISGBpKQkhg0bRlJSErt27SI6Oprw8HAAfvjhB7p27Qo4Z+tbtWpV47azU1JoddFF2rL4E5vFndgs7sTfWUQkVSnV6wTmT8fWb9dzutTvynUbqq/d1157LYsXL+b555/noYce4tNPP2XgwIG0b9/e+/z65s2bAejYsSONGjWiR48epKWl8dLjj3P/00+zfPlyBgwYQGRkJPn5+XWq97rx9z7EV0zwtI76MMHTBEeo2fNE67evV9JbA98rpf571BAWRUAHXzdmOeWswulY5lrg/Wqm78c5g94B+N7zXnsg6+gZReQS4AmcYVu2eN7Lwxm2B897t3qeh7seeE9EmlV8eagvZs+ezYoVK1i9ejUACxcuJD09nfj4eLKysnjzzTc5++yz2fj/7J15fFTV+YefN3tIAmFXEIgIVgwCKoJVKiha1EKhtRWLW8RdaEEtinULv1pR6wKudUOiCMUVF8SioFbUGgFBCCIgJIQgCRgiIQsJ5P39cSfjELJMkpvMPeE8n898yMw9c+7zHebMO/fOveeuXcvnn39OmzZtuPPOOwFYvHgxN998M2eddRaJiYm8+67zHWX48OF1Fuw2vXs3bbBmxGbxJjaLNzEwi63fZnBY1e/aavctt9zCO++8w7Rp01i7di0ffvghAFOnTvU/v0+fPoBz/vqAAQM4/fTTycjIYPrTT/NtXp7/OUOGDAEaV+/dxpTPEBM8raN7mOBpgiO45xnsxHE7gWNExP9J5rv25nFArismlkajqgU4hzY+KSJ/EJEEEQkTkQFAHM7e9FeAf/iW9QBuAuZU010iUAEU+c5pvAtIqFwoIpeISEdVrQAqZ3KpaLp01bNs2TLS0tLIznauLrN69WrS0tJYtWoVvXr1Ij8/n7S0NNasWcPIkSP57LPP6NWrF+BMRnPGGWfw2Wef8eKLLxIdHc2f//xnXnml7tPzCqvMGGsyNos3sVm8iYFZbP02gMOtftdWu08//XTmzZtH9+7dmTdvHuHh4UyfPp3rrruuxv4efPBBJkyYQFR4OLNnz6akpITLLrvMPxdNY+q925jyGWKCp3V0DxM8TXAE9zyD/SX9fWA8sBbneqvJwErf8xe5YmJxBVV9QERycC7j8iLOdVY3A7fizPS6Gmfymc1AKfAsMKuart7H+b9d7+vjESDwOqvnAg+LSCsgC7hIVUuaIlNtzJ4921+Eq6PykLjq6Nu3L2+++WaD1qsVzb4/osmwWbyJzeJNDMxi67chHE71u67aPXbsWMaOHVvj8qqnaiYkJPD4449z1xVX0Onkkw9p35h67zamfIaY4Gkd3cMETxMcwT3PYM9J7wx8iXNoVSBbgVNVtfrpNi2WAE4+8URd4bu0iumU7dlDVOvWodZwBZvFm9gs3iTUWRpwTrqt35ZGY0r9DvX4DAYTHMEMT+voHiZ4muAINXvWt34Hdbi7quYCJwGpwHu+2zTgZFvgLcGyv7Q01AqusbuWX+hNw2bxJjaLNzEti63fFjcwpX6bMD5NcAQzPK2je5jgaYIjuOcZ7OHuqGo+zmygFkuDCIsI+u3meSovF9ESsFm8ic3iTUzMYuu3pbGYUr9NGJ8mOIIZntbRPUzwNMER3POs8VPXN9FIUKiqLf4Wi8VisXgAW78tFovFYjGb2naNpuJMMhMMtshb6qRi//66GxlCyc6dtD766FBruILN4k1sFm9iSJZUbP22uIgp9duE8WmCI5jhaR3dwwRPExzBPc+6jl+SOpZD8F8ELIc5ETExoVZwjbbHHRdqBdewWbyJzeJNDMpi67fFNUyp3yaMTxMcwQxP6+geJnia4AjuedY4cZyqhlXegCHAHuBqoLXvdhVQDJzjiomlxXNg375QK7hGwcaNoVZwDZvFm9gs3sSELLZ+W9zGlPptwvg0wRHM8LSO7mGCpwmO4J5nULO7A48D21T1eVXd67vNAjKBh10xsVgMQsKCHTrex2bxJjaLNzEwi63flsMGE8anCY5ghqd1dA8TPE1wBPc8g52usw9QISL9VPUbABHpBxxN8Bv6lsOc8OjoUCu4RkJSUqgVXMNm8SY2izcxMIut35ZGY0r9NmF8muAIZnhaR/cwwdMER3DPM9gC/R0QA6wUkW9F5Ftghe8xMy5aZwk5plxnNRh+MuSQm2CwWbyJzeJNDMxi67el0ZhSv00YnyY4ghme1tE9TPA0wRHc8wx2I/3PQJGv/S98t3Ccc9r+4oqJpcUTHhkZaoUGMW/ePEQEEWHy5MkAfLlxI0OGDCE2NhYRYdiwYQc959tvv2Xw4MEkJiYSHR1Njx49mDRpEqUe/KLTqnPnUCu4hs3iTWyWkGLrt6XRuFm/Z8yYQb9+/QgPD0dESE1NPWj5q6++SnJyMtHR0SQlJfHAAw/U2t/q1asZPnw4CQkJHDF4MEnV/Ip14MABpk+fTq9evYiKiqJjx46MHz/etUz1wZTPEBM8raN7mOBpgiO45xnU4e6q+qmI9AImAH19D68FnlTVXFdMLC2ego0bmZucHGqNOhmXkeH/e9u2bdxwww1ERESwP+ASNBs3baK4uJi+ffuyfPnyQ/r48ccfiYiI4I9//COlpaW8/vrrPProoyQmJjJt2rRmyREsFeXloVZwDZvFm9gsocPWb4sbuFG/K2vrihUraNeuHd26dSMrK+ugNl988QVjx44lLi6Oiy66iCVLlnDrrbfSpk0brr322mr73bp1Kzt27ODEE0/k008/rbbNhAkTePrppzniiCO45JJLKCsrY/PmzY3K01BM+QwxwdM6uocJniY4gnuewZ6TjqrmAXe7slZLSBGRj4H+wBGqasaUrSFAVbn88svp0qULJ5xwAvPnz/cvu+S887j57ruZMWNGtRvpQ4YM4bPPPvPfb9u2LY899hhbtmxpFvf6UJqfT5tQS7iEzeJNbJbQYut3y6El1O+XXnoJgDFjxhyykX7//fejqqSmpnLzzTezZMkSzj77bKZPn17jRvqoUaMYNWoUCxYsqHYjfePGjTzzzDN06NCBb775ho4dO7ofqh6Y8hligqd1dA8TPE1wBPc8g540RkQGi8h/ROQnEVkmImeLyCwROc0FD0szISJJwK9wro/72wY8P+gdO6YzY8YMli1bxssvv0xMlWvEtgviF4X8/HwmT57MpZdeynPPPUdiYiLXX399U+k2mGCymILN4k1sltBi63fL4HCo319//TUAAwcOPOjfrKwsCgoKGtTnRx99hKrSoUMHfv3rXxMXF8fAgQP5+OOPXXGuL6Z8hpjgaR3dwwRPExzBPc+gNtJ9hfwT4Gwgwfe8bCAFuNIVE0tzcRnwP2A2cHnlgyLSTUTeEJGdIvKjiDzuezxFRD4TkUdE5EcgVUSiReRBEdkqIrki8i8RiQ1JmiZi7dq13Hbbbfzf//0fAwYMOGR5fsAh8TWxZ88eZs6cyZw5cygpKeHUU0+le/fuTaHbKILJYgo2izexWUKHrd8tihZfv3NznTMw4uPjAYiLi/Mv27FjR4P63LVrFwDr16+nbdu2nHPOOaxYsYJRo0axbdu2RhrXH1M+Q0zwtI7uYYKnCY7gnmewv6T/HYgCPqh8QFW/A3YCp7tiYmkuLgNe9t1GiEhnEQkH3gWygCSgK/DvgOcMBjYDnYF/APcBxwIDgF6+9nc1k3+z8Prrr1NWVsYnn3zCyJEjWbJkCQBvv/02t912G+FVflmvjqSkJFSVvLw8rrjiCt5//31SUlKa2Lz+BJPFFGwWb2KzhBRbv1sOLb5+d/ZNuLR3796D/gU44ogjGtRn5eHtrVu3ZvHixSxYsIDjjz+evXv3snTp0kYa1x9TPkNM8LSO7mGCpwmO4J5nsIc+DQa2AucBBwIezwF6u2JiaXJEZAjQA3hFVXeJyPfAOJw9812AKapaOTvasoCnblfVx3x9HACuAfqpar7vsXuBucBt1azzGl97Ohgyu3t5URGF27ahqixatOigZVu2bOHzZcu4/qyzKNiwgX0//QQ4k0Ts+uYbDpSW0i45ma3p6XTo1o2wyEgqcnMZetppvPDCC6xfu5ayPXvYvX49sb4vDiU7d9L2uOMo2LgRCQsjISmJnzZupFXnzlSUl1Oan0+75GTyMzIIj4khrksX9mzeTFzXruwvKmJfQYF/eUSrVsR26kRhZibx3bpRVlBAWWGhf3lUQgJRiYnszc4mISmJkrw8inNzKS8qIj8jg+jERCLi4ijKyaF1z54Ubd/uz5SfkUFMu3aERUZSnJtLm969KczMRCsqSOzd2xOZIlu35se1a9lfXOxfbmomiYggNz3d//9kcqbi3Fx2f/vtIe89EzMFjpfqxlNTZ2oAtn63AFpC/c5NTz9obB7wTa60r6CAnzZtojQ/n34nnMDWrVv56K23GJSczOJ58wA4qksX9m3YQHlyMl8uXEhETAy/OPFEyn74wT82K8fHgbKygz5vjj3qKAD0wAHKi4r48bvvqCgrA2D/Dz9QsmtXs37eFOfmsjcnx5X63ZSfNyU7d7Lz66+b/TtJfTIRFkZhVlbI60Jtmcr27CE3Pd3ztS4sKorc9HRPvPdqyhRYf0P93qstU3FuLnt8c1A1pn6LqtbdSGQvzgf9sSJSAfxPVU8Tke1Agqom1HvNlmZHRJ4Fuqjqb3z37wJ+D9wL3KKqA6t5Tgpwtaqe7rvfCcgFfgpsBoSranxt6+8ZG6v39OzpRpQmJXB290pSUlJIS0tj0qRJzJgxg7efeYY3Pv+cdevW8dVXX9G5c2fOPfdcjjvuOKZOncoVV1zBunXrOOGEE9i3bx9vv/02e/bs4eqrr+aZZ54JQaqayU1Pp/OgQaHWcAWbxZvYLO4hIiuq+6yupb2t3y2AllC/K2vrc889x7Jly1i6dCnZ2dn079+fAQMGMGbMGDp27MivfvUrWrVqxQUXXMCHH37I9u3befLJJ/1zuogI4Jy/PmDAANavX899993nbNx/9BFxcXH84Q9/oEOHDjz44IMADB06lP/+97+cddZZJCQk8NZbb9G1a1cyMjJo06Z5p6IK9WdIsJjgaR3dwwRPExyhZs/61u9gf0lfC5wiIvf47rcRkceAI4Avgl2ZJXT4zjm7EAgXkcoTu6KBRJyi3V1EIgL2xAcSuCdnF1ACJKtqTlM6e5ntRUWkpaX57+fm5pKWlsbQoUOZOnUqv/zlL0lPT/dfY71bt25MmjSJ22+/PYTW1RPXtWuoFVzDZvEmNktIsfXbcFpa/V62bNlB9XP16tWsXr2apKQkUlNTmTdvHtOmTWPevHkcccQRTJ8+neuuu67G/nbs2HFQf0W++tyjRw//Rvorr7zCpEmTWLRoEeHh4Zx//vk89NBDzb6BDuZ8hpjgaR3dwwRPExzBPc9gf0m/COdwqOoaX6yq/67mcYuHEJE/AU/gnIdWFrDoFWAFcBbOOYt34xwSebKqfubbE3+Vqg4J6GsmcCQwUVXzRKQr0FdV/1Obg8m/pFelYMMGEo89thlsmh6bxZvYLN4k1Fka8Eu6rd+G01LqdzC1tbGEenwGgwmOYIandXQPEzxNcISaPetbv4OaOM5XxKcAxTiHRgnO3tiptsAbw+XAC6q6VVV3VN6Ax4E/AaNwJpHZCmwDxtbS163AJuB/IrIH+BD4RZPae4x9DbwUjBexWbyJzdvNEFwAACAASURBVOJNTMti63eLwNbvIDFhfJrgCGZ4Wkf3MMHTBEdwzzOoX9L9jZ1Driov/pahqiWuWFgOC04+6SRdsXJlqDVcobyoiMiAS8OYjM3iTWwWbxLqLPXdEx/wPFu/LQ3GlPod6vEZDCY4ghme1tE9TPA0wRFq9nT1l3QRmSUigSfRngPEqOpyW+At9WV/Sct5y5hyrcZgsFm8ic3iTUzJYuu3xU1Mqd8mjE8THMEMT+voHiZ4muAIzXed9BTgNwH3FwD3u7Jmy2GHhAV1doURRLRqFWoF17BZvInN4k0MypKCrd8WlzClfpswPk1wBDM8raN7mOBpgiO459mQT11xZc2Ww44wQ66THgyxnTqFWsE1bBZvYrN4E8Oz2PptaRCm1G8TxqcJjmCGp3V0DxM8TXAE9zzN2DVqaREc2Lcv1AquUZiZGWoF17BZvInN4k1aUhaLJVhMqd8mjE8THMEMT+voHiZ4muAI7nkGc530aBHpxs8b9JX3/XvkVXWrKzaWFk14VFSoFVwjvlu3UCu4hs3iTWwWb2JYFlu/La5gSv02YXya4AhmeFpH9zDB0wRHcM8zmF/SBwCZwGac66xW3t/iu212xcTS4tEDB0Kt4BplhlwGIhhsFm9is3gTw7LY+m1xBVPqtwnj0wRHMMPTOrqHCZ4mOIJ7nsH8km7PYbO4QoUhRT4YygoLQ63gGjaLN7FZvIlhWWz9triCKfXbhPFpgiOY4Wkd3cMETxMcwT3PujbSp7myFosFiIiNDbWCa7RLTq67kSHYLN7EZvEmBmWx9dviGqbUbxPGpwmOYIandXQPEzxNcAT3PGvdSFdVW+QtrmHKdVaDIT8jg86DBoVawxVsFm9is3gTU7LY+m1xE1Pqtwnj0wRHMMPTOrqHCZ4mOIJ7nsEc7m6x1IiIvAe8o6pP1dW2MDOTuU24F2xcRgZXXXUVn332GdnZ2URHRzN48GAeeOAB+vbtC8Arr7xCamoqW7duRVVJSkpiwoQJ3HDDDQCUlJQwbtw4/ve//7Fjxw4AtmzZQlJS0kHrikpIaLIczY3N4k1sFm/SkrJYDm+ao36Py8gAYNWqVdx6660sX76ckpISkpKSmDhxor/2VqWuWj537lyeeuop1q9fT1FRET179uTGG2/k96edVm/H5saUzxATPK2je5jgaYIjuOdpL8HWghCRcSKyXET2isgPIrJIRIY04fouA/KDKfDNxfPPP09iYiJ/+tOfaN26NYsWLeLcc8+ltLQUgKysLHr06MGll17KmWeeybp165gwYQIfffQRAGVlZaxYsYJTTjml1vVEJSY2eZbmwmbxJjaLN2lJWSzeoaXX7zFjxrB48WKOOeYYLrjgAtavX39Q7a1KXbV88eLFZGZmMmLECIYMGUKGbyf9h+npzRGnUZjyGWKCp3V0DxM8TXAE9zztRnoLQURuAmYA9wKdge7Ak8Bol9cTHnA3HrjWzf4by/Lly/niiy949tln/cU/JyeHdevWATBlyhQWLVrEU089xbvvvssJJ5wAOL+WA7Rp04atW7fy4osv1rqevdnZTZiiebFZvInN4k1aUhaLN2jp9bu8vJxs37iZNWsWL730EieddBIAmTVcT7iuWj558mQyMzOZM2cOixcvZujQoQD85733mjhN4zHlM8QET+voHiZ4muAI7nnajfQWgIi0Af4PmKCqb6hqkaqWq+o7qjpFRMJEZKqIfC8iP4rIKyLSLuD5r4rIDhH5SUT+KyLJActmi8hTIvKeiBQBZ4rIb0Tka+A+YL2IpDZ35po4+eST/X+XlZUBEB4ezpFHHul/PD09nUmTJjFy5EjWrFlDnz59GD26ft+FEqoc/m4yNos3sVm8SUvKYgk9h0P9joyMZNKkSQCMHz+eSy+9lJUrV9K/f39+97vfVfucumr5gAEDCA8PP6RN0i9+0SQZ3MSUzxATPK2je5jgaYIjuOdpN9JbBr8EYoA3a1j+Z2AMMBToAuwGnghYvgjoDXQCVgIvV3n+OOAfQAKwDCgBLgMSgd8AN4jIGDeCuMXevXu54oorALjpppsO2khft24djz76KAsXLiQsLIxzzz2XhHqeP1KSl+eqbyixWbyJzeJNWlIWiyc4LOr3mDFjSEpK4quvvmLOnDlEREQwZsyYOmtvbbW8kocffpgvvviCXr16ccn55zeJv5uY8hligqd1dA8TPE1wBPc86zVxnIgcjVMkAg+ZQlX/64qNpaG0B3ap6v4all8HTFTVbQC+PedbReRSVd2vqrMqG/qW7RaRNqr6k+/ht1T1M9/fpcDSgL6/EZG5OF8gFlRdsYhcA1wD0CEysqH5guKnTZsozc/nQKdOnH/++az+9luuuPRSbrrgAvbm5LC/qIh9BQVc/Mc/MuK449iWn881t93GI488QkJUFJMvv5yywkLaJSeTt2KFv9+dq1bRqVUrSvLy2F9cTLvkZHauXEl4VBQRcXEU5eTQumdPirZv50BpKe2Sk8nPyCCmXTvCIiMpzs2lTe/eFGZmohUVJPbuze7164nt2BGAkp07aXvccRRs3IiEhZGQlMRPGzfSqnNnKsrLKc3P9/cZHhNDXJcu7Nm8mbiuXf2ZKpdHtGpFbKdOFGZmEt+tG2UFBf5M+RkZRCUkEJWYyN7sbBKSkijJy2PnypW0Pvpo8jMyiE5MNDrTvt27Afz/TyZn2pudzf7iYv//k8mZdq5cSVh4+CHvPRMzBY6X6sZTU2dqKLZ+e5YWXb9z09MpiYjgvHPPpbikhKXvv0/XqCgu+vOfmTZtGjHFxUyYMKHasVkcFcVvf/97Vn/7LZdfeCE3XXAB5UVFB43Nu26/nYeee46kbt3490MPEblvH7np6SEZm8F+3uxcuZLotm1dqd9NmWnnqlVUlJc3+3eS+mTam5NDVEJCyOtCbZnyMzI8896rLVNRTg77i4s98d6rKVNg/Q31e6+2TDtXriQyLu6QTPVFVLXuRiJH4HyAVzeblqqqnSU+hIjIucC7QEx1hV5EioH9QEXAwzHAMcAOnL3sfwQ6+tq0AXqp6vciMhvIUdXbA/o7yfecPoD42r+jqpfW5tkzNlbv6dmzoTHrZFxGBllZWfz6179mw4YN3Hbbbdx7770HtSksLDxoz/21117LM888w2WXXUZaWpr/8YKCAtq2bQtUP7t7eVGRfwCajs3iTWwWbxLqLCKyQlUH1qO9rd8epqXX73EZGSxfvpxTTjmFyMhICgsLiY6O5vLLL+fFF19k4sSJ3HPPPfzwww/ExMT4a21dtbyiooKJEyfy1FNPceKJJ/Lee+9xxBFHhHx8BoMJjmCGp3V0DxM8TXCEmj3rW7+DPdz9PmAQzgd6dTdLaPkC2IdzSFx1ZAPnqWpiwC1GVXNwDoUbDZyNU6yTfM8J/H+tuidnPs6Xil6q2gNIwyPvg9NOO40NGzbQvXt3iouLmTx5MpMnTybdN+PrySefzIgRI7j++uv57W9/y3PPPQfAiBEj/H2kpKQcdFmYv/71r6SkpLBr1y7/Y/m+y8q0BGwWb2KzeBMDs9j67W1afP3u06cP7dq1o7y8nOHDh3P55Zczb948AIYMGcKbb75Jnz59GDPm55egrlp+55138tRTTxEWFsaJJ57Ifffdx+TJk/lnampTRnEFUz5DTPC0ju5hgqcJjuCeZ7B70M/B2UN7LfAssA54CZiCcyiWJYSo6k8ichfwhIjsBxYD5TiF+0zgX8A/RORyVc0SkY7Aaar6Fs55avuAH4FWOLPL1kUiUKKq+0VkEPAn3zpDzvbt2wHYunUrM2fO9D8+YMAABg0axNlnn817773Hxx9/TFxcHAMHDuSGG25g3Lhx/raBv6gDvP766wCkpqbSoUMHAKINuQxEMNgs3sRm8SYGZrH128McDvU7Li6O9957jzvuuIOVK1eycuVKevXqxbXXXsvYsWOZPXv2Ic+pq5bn5OQAzi/qs2b5j/jn9EGD+FtThnEBUz5DTPC0ju5hgqcJjuCeZ7Ab6R2B71T1eRF5FtirqveLyOXARcBrrthYGoyqPiQiO4A7cCaOKQRW4BzW9j+cPeWLRaQLkIezN/0t4EVgBJAD5AN3AtfXsbrrgYdEZCbwCfAKTuEPOXWdvvHkk082ug+ACAMOtwkWm8Wb2CzexMAstn57nMOhfg8ePJgPPvig2mUpKSmkpKQc9FhddXj27NnVbtzv9W28exlTPkNM8LSO7mGCpwmO4J5nsBvpRTjnRFX+3VNEOuMU/xE1PsvSrKjqyxw6s2slD/tuVZ+zl0OvxfpiwPKUap7zGg34YpeQlMQ4Qw5VqYuinBziu3YNtYYr2CzexGbxJgZmsfXbAGz9dgcTxqcJjmCGp3V0DxM8TXAE9zyDPSc9B+jm+3sDzmyk24F2QEGjLSyHBeHR0aFWcI3WTTgBXnNjs3gTm8WbGJjF1m9LozGlfpswPk1wBDM8raN7mOBpgiO45xnsRvoiIEdE+gIzfI9VTjozs8ZnWSwBVJSXh1rBNYp858u1BGwWb2KzeBMDs9j6bWk0ptRvE8anCY5ghqd1dA8TPE1wBPc8gzrcXVWn4EwyA7BWRLbgzBb7jap+6IqJpcWjFRV1NzKEA6WloVZwDZvFm9gs3sS0LLZ+W9zAlPptwvg0wRHM8LSO7mGCpwmO4J5nUNdJt1jc4OSTTtIVK1eGWsMVTLlWYzDYLN7EZvEmoc5S3+usWixuYEr9DvX4DAYTHMEMT+voHiZ4muAIzXCddBFZGuRtSQMzWA4z9peUhFrBNUy5VmMw2CzexGbxJiZksfXb4jam1G8TxqcJjmCGp3V0DxM8TXCE5rlO+jBAcc5bw/d3VaSGxy2WQwiLCPZiAt4npl27UCu4hs3iTWwWb2JIlmHY+m1xEVPqtwnj0wRHMMPTOrqHCZ4mOIJ7nrV96v6Xgwv4QCAa+MZ3vx/OZV3+54qJpcUjInU3MoSwyMhQK7iGzeJNbBZvYkgWW78trmJK/TZhfJrgCGZ4Wkf3MMHTBEdwz7PGw91VdZiqnqmqZwJzfQ+foKoDfcfTnwBUAG+5YmJp8RwwZHbYYCjOzQ21gmvYLN7EZvEmJmSx9dviNqbUbxPGpwmOYIandXQPEzxNcAT3PIO9BNvtQJaqflf5gO/vTOAmV0wsLZ6ImJhQK7hGm969Q63gGjaLN7FZvImBWWz9tjQaU+q3CePTBEcww9M6uocJniY4gnuewW6kdwKOE5GJItLZd5sI9AE6umJiafEc2LevQc+bMWMG/fr1Izw8HBEhNTXVv2zu3Ln86le/omPHjrRq1Yq+ffvy/PPP+5fv2rWLM844g/bt2xMVFUXXrl1JSUkhPz+/UVkKMzMb9XwvYbN4E5vFmxiYxdZvS6NpaP3++OOPEZFqb7Nnz25Q+1deeYXjjz+e+Ph44uLiSE5O5sknnwTMGJ8mOIIZntbRPUzwNMER3PMMdiaQj4DzgJm+W9VljUZE/gXkqOrf3eivuRGRVKCXql7iQl+zgW2qekdj+/ISe7ZsYW5ycr2eMy4jgxUrVtCuXTu6detGVlbWQcsXL15MZmYmI0aMIC8vjw8++ICrrrqKTp06MWrUKIqLi9m7dy+//e1vCQsL48033yQtLQ1VJS0trcFZTLlmbDDYLN7EZvEmBmax9bsObP2um4bW76OOOopJkyb5H9u7d69/R3qvXr0OeU4w7bOysujRowdDhw4lOzubhQsXMmHCBPr06UNy69b1ztbcmPIZYoKndXQPEzxNcAT3PIPdSL8GeAM4pcrjy33L6kREMoHOwAFgL/A+MFFV9wKo6nVBulTXdxQwFbgYOAoowJkg5xFVXdzQfk1DRJKALcAiVT0/4PE5wCZVTW1gvwr0VtVNLmjWm5deegmAMWPGHLKRPnnyZJ5//nnCw8MBGDZsGJ988gkffPABo0aNonv37qwMuLZrcnIyN998M1u2bGmUU6Ihh9wEg83iTWwWb2JgFlu/DaCl1u9evXoxY8YM//3HHnsMgJNOOokhQ4Y0qP2UKVOYMmWKv02/fv1Ys2YNW7Zs4fQ//KFJcriJKZ8hJnhaR/cwwdMER3DPM6jD3VU1R1UHA2cBk3y34ao6SFVz6rG+UaoaDwwATgRuq69wDbwGjAYuA9oCR+P8YvCb6hqLiBnXEmk4g0XktMZ2YsLrNGDAAP8GOkBZWRng7I0PZPLkyYwfP5577rmHmJgYbrzxxkatd/f69Y16vpewWbyJzeJNTMti67dxtNj6rao8+uijgFOTG9M+PT2dSZMmMXLkSNasWUOfPn0YPXq0EePTBEcww9M6uocJniY4gnuewZ6TDoCqfqyqj/luDT5MTlV3AP/BKfaAc4iYiNwTcP9qEdkkIvki8raIdKmuLxE5GzgHGK2qX6pqme/2vqpOCmiXKSK3isg3QJGIRIjIVBH5XkQKRWSdiPwuoH2KiCwTkQdFZLeIbBGR8wKWHy0in/ie+wHQoYrXqSLyuYgUiMhqERlW0+shIieKyEpfX/OBmCrLg3otAngA+Ect66uxPxFREZkgIhuBjSLyX9+i1SKyV0TG+tqNFJFVvnyfi0i/OpyanIcffpgvvviCXr16cd11B/+wM3PmTF544QV2795N//79+cUvftGodcV2bDmnctos3sRm8SamZrH129bvUNfvd999l02bNnHkkUcyduzYRrVft24djz76KAsXLiQsLIxzzz2XhIQEI8anCY5ghqd1dA8TPE1wBPc867WR7hYichTOOXLVHn4lImcB04ELgSOBLODfNXR3NvClqm4LYtV/wtk7n6iq+4HvgV8BbYBpwBwROTKg/WDgO5wC/gDwvIj/YqFzgRW+ZX8HLg/w7wosBO4B2gF/BV4XkUP+18Q51G8B8JKv7avABQ18LSp5EjjW9wWo6vqC6W+ML/vxqnqG77H+qhqvqvNF5ERgFnAt0B54GnhbRKLr8GoyUlNTufnmm+nZsydLliyhdZXz0lSVgoICbr/9dr788ktGjx4dIlOLxWIxF1u/D8pq63c9qDyM/frrrycqKqpR7VNSUjhw4AAbN25kwIABPPLII/zzn/90X9pisVhCRHMfDrVAnPOj4oGlwN01tLsYmKWqKwFE5DZgt4gkqWpmlbYdgB2Vd0SkHbAZECBaVQP3aj+qqtmVd1T11YBl833rGcTP147NUtVnff2m4RTPzr7CfApwtqruA/4rIu8E9HUJ8J6qvue7/4GILAfOB6rOVnYqEAnMUFUFXhORwMvi1Oe1qKQEZ0/8PcCHVZYF0990Va1t+vNrgKdV9Uvf/TQR+ZsvyyeBDUXkGl97OkRG1tJl9ZTt2cPu9euJ7diR/cXFgDPLbN6KFUhYGHHdu3PDtdeS9vrr9Dv+eOY8+CBHtm9Pbno64TExVLRujeblEde1K1pUxC+PPhqALVu2sOPrr2ndtSuFmZnEd+tGWUEBZYWFtEtOJj8jg6iEBKISE9mbnU1CUhIleXnsLy6mXXIy2z/9lIryciLi4ijKyaF1z54Ubd/OgdJS//Nj2rUjLDKS4txc2vTuTWFmJlpRQWLv3v5MACU7d9L2uOMo2LgRCQsjISmJnzZupFXnzlSUl1Oan+/vMzwmhrguXdizeTNxXbuyv6iIfQUF/uURrVoR26lTvTLtXLmS2E6dyM/IIDox0ehM+3bvpryoyP//ZHKmPZmZlOzcech7z8RM2z/9lAOlpTWOJ5My5X71lX+81PYZ0VSZQoit37Z+14vA+p2xfj1Lly4lJiaGC375S3Z+/TUJSUlkf/01e1SJDA+nc6tW/rHxXXa20z46mktGj6Zgwwb/2Nyank5ix47EdupEQn4+/Y8/npUrV7L6888pHDKEkp07QzI2g/282f7pp4RFRblSv5sy0/bPPmNfQUGzfyepT6a9OTlIWFjI60JtmXLT0ynZudMT773aMhXl5FCyc6cn3ns1Zfrh88/99TfU773aMm3/9FP/52Bj6rc4daXpEWfimatU9UMRGYqzJ3to5WQmEjAjqogsAt5V1ScCnr8DuEBVP6vS7/3Aqao6tMrjvYCNqioB679aVT8IaHMZznVik3wPxQPXqurzIpLi8x0S0F6B3jhfLN5R1Y4By6YD3VT1EhF5EhgPlAYoRQJ/V9X7qnheBNysqqcEPDYP+L4Br0USzsQzkThHSXwH/AUYi2/imbr682U8VlU3Biw/aOIZEXkPGAaUBaw+CrhSVedRAz1jY/Wenj1rWlwt4zIyeO6551i2bBlLly4lOzub/v37M2DAAMaMGcNXX33FvffeS1hYGCkpKSQkJADO5DMTJ04kNTWV119/nZNPPpnw8HDeffdd8vLyOOecc1i8uOFzEpXt2UOUAbPIBoPN4k1sFm8S6iwiskJVBzbzOjOx9dvW7wbU70quvPJKZs2axZVXXslzzz3nf3z27NlcccUV9O/fn1WrVtXZHuDYY4/l6KOPpmfPnuTk5LBw4UIqKip4+eWX+cPIkZ7/rAn1Z0iwmOBpHd3DBE8THKFmz/rW75Ac7q6qnwCzgQdraLId6FF5R0TicA7Lqm6SmyXAKb5D8OpcdUCfPYBngYlAe1VNBNbi7MGvix+Atj6vSroH/J0NvKSqiQG3uKoFPqCvrgGH4VXtqz6vhR9VLcM5BPDvVTIF019de26ygX9UydeqtgLfGJYtW0ZaWhrZ2c6PKKtXryYtLY1Vq1aRk+NoV1RUMGvWLGbOnMnMmTN57bXXAGdiucjISN544w3mzp1LfHw8kyZNYv78+Y1yCvEvWq5is3gTm8WbtKQsDcHW70P6svW7Dnbt2sXcuXOB4CaMq6v92WefzXfffcesWbNYtmwZAwcOZPbs2YwbN86I8WmCI5jhaR3dwwRPExzBPc96baSLSFcR+Z2InOvCumcA54hI/2qWzQOuEJEBvvOk7sU5by2zakN1LtHyEc6heINFJEpEInEO3aqNOJxithNARK4A+gYjrqpZOJevmeZb3xBgVECTOcAoERkhIuEiEiMiw2r4IvIFsB/4i4hEisjvcQ7ZqyTo16IaXsKZxCbw/6sh/eUCgbvQnwWu873eIiJxIvIbEUkIwqnezJ49G1U95Jaamlrjso8//hhwLtu2cuVK9uzZQ0lJCd9//z0zZsygbdu2jXKSsJDs32oSbBZvYrN4E1Oz2PrtX6et381YvwE6dOhASUkJqkrfvgf/N6WkpKCqB/2KXlt7gCeffJLMzEz27dtHfn4+X375JZdf7kwrYML4NMERzPC0ju5hgqcJjuCeZ1C9+D7IZwKZOJdLuUtELhORAyIysSErVtWdwIvAXdUs+xC4E3gdZ0/1McBFtXT3O+BdnOJagHPI2MXAiFrWvw54CKfI5gInAJ/V1L4axuFMzpKPc27eiwF9Z+NcUuZvOF8isoEpVPN6+/aY/x5I8fU1FueatpXL6/taBPZ9AOf1bdfI/lJxzlsrEJELVXU5cDXwOLAbZwKhlGCcWgoJSUmhVnANm8Wb2CzexLQstn5Xi63fLbR+mzA+TXAEMzyto3uY4GmCI7jnGdQ56SLyV5zZUSv5H04B/RH4SFVrLKYWSyX9+/TR1d9+G2oNV8hNT6fzoEF1NzQAm8Wb2CzeJNRZ6ntOm63fFjcwpX6HenwGgwmOYIandXQPEzxNcISaPZvqnPRrgAM4s54CoKqFwDbg+GBXZjm8CW/A7LBepVXnzqFWcA2bxZvYLN7EwCy2flsajSn124TxaYIjmOFpHd3DBE8THME9z2A30nsAa1V1bpXHfwLMuLK8JeQ015UEmoOK8vJQK7iGzeJNbBZvYmAWW78tjcaU+m3C+DTBEczwtI7uYYKnCY7gnmewG+kFQPfA2VBFpD1wLM45TRZLnVTs3x9qBdcoza/tMrRmYbN4E5vFmxiYxdZvS6MxpX6bMD5NcAQzPK2je5jgaYIjuOcZ7Eb6R0AizoyoAL18f8cAS10xsbR4ImJjQ63gGu2Sk0Ot4Bo2izexWbyJgVls/bY0GlPqtwnj0wRHMMPTOrqHCZ4mOIJ7nsFupN8J7AF+gXPZk/Y4h9D9hDNzqMVSJ/tLSkKt4Br5GRmhVnANm8Wb2CzexMAstn5bGo0p9duE8WmCI5jhaR3dwwRPExzBPc+gNtJVdSMwEJgNfOu7pQGDfcssljox5fqGwRAeExNqBdewWbyJzeJNTMti67fFDUyp3yaMTxMcwQxP6+geJnia4AjueUYE21BVvwfGu7JWy2FJmCGzwwZDXJcuoVZwDZvFm9gs3sTELLZ+WxqLKfXbhPFpgiOY4Wkd3cMETxMcwT3PGjfSReSyYDtR1RddsbG0aA7s2xdqBdfYs3kzsR06hFrDFWwWb2KzeBMTstj6bXEbU+q3CePTBEcww9M6uocJniY4gnuetf2SPhvn/LW6UMAWeUudhEdFhVrBNeK6dg21gmvYLN7EZvEmhmSZja3fFhcxpX6bMD5NcAQzPK2je5jgaYIjuOdZ1+Hu4spaLBagYMMG5hoyM6MbjPNNHDFs2DA++eSTg5YlJyezdu1a8vPzuemmm1i8eDE//vgjnTt35ne/+x0PPPAA0dHR/vaqynnnncd//vMfAL7++msGDBjgiuf+oiJX+vECNos3sVlCgq3fFtcItn6PC5gw6c033+Tee+9l7dq1REVFccIJJ/DOO+/Qtm3bQ55XWlrKlClTmD9/PoWFhZx00kk8/PDDDB48GICkpCSysrIOed7QoUP5+OOP/fdNGJ8mOIIZntbRPUzwNMER3POsbSP96IC/jwdeAWYA832PXQj8FfiTKyaNQET+BeSo6t9D7dIQRCQV6KWql7jQ12xgm6re0di+6rleBXqr6qbmXK9JTJo0yf/3kUceCcBNN91EWloaRx11FCkpKbz66qs8+uijJCYmMm3aNH/7J554giVLljSJ176CgibpNxTYLN7EZml2bP1uJmz9rp558+Yxbtw4FarsnAAAIABJREFUoqOjGTNmDPHx8aSnp1NcXFztRvrkyZN5+umn6du3L8OHD2f+/Pmcc845bN68mQ4dOjB+/HjyA649/MYbb5CdnU2vXr0O6seE8WmCI5jhaR3dwwRPExzBPc8aN9JV1b/LUkReBLJV9c6AJmtF5A/ALcBbrtjUgIhkAp2BA8Be4H1goqru9ble14i+o4CpwMXAUUAB8A3wiKoubpy5WYjIlcAUoCtQDKwAxqpqYUjFWggzZsw45LHvv/8egFtvvZWJEyeSkJDAQw89RGZmpr/N+vXrueWWW7jzzju5++67Xfcy5bqTwWCzeBObpXmx9dvWb0JYv1WVW2+9FYD333+fYcOG1do+Ly+PWbNmERYWxpIlS+jUqRMRERHMmTOHxx9/nNTUVO666y5/+507d/L0008D8Je//OWgvkwYnyY4ghme1tE9TPA0wRGa/zrpg4AuInJk5QMicgROMTjJFZO6GaWq8cAA4ETgNpf6fQ0YDVwGtMX5BWIm8JvqGotI0DPim4SIDAXuBf6kqglAH37+1cXiAm3btiUxMZHhw4fz1VdfAc6v65GRkdx///1ce+21zJo1i/bt2zNx4kQAysvLueSSS+jfvz+33357k3iZct3JYLBZvInNElJs/fZh63fzsHHjRrKzs4mNjeWBBx4gPj6eXr168cQTT1TbPiMjg/Lycrp3706nTp0AGDhwIACrVq06pP2//vUvSktLOeuss+jXr99By0wYnyY4ghme1tE9TPA0wRGa+TrpwFYgAVgvIotEZBHwHRDvW9ZsqOoO4D84xR5wDhETkXsC7l8tIptEJF9E3haRaufCF5GzgXOA0ar6paqW+W7vq+qkgHaZInKriHwDFIlIhIhMFZHvRaRQRNaJyO8C2qeIyDIReVBEdovIFhE5L2D50SLyie+5HwAdqnidKiKfi0iBiKwWkWE1vR4icqKIrPT1NR+IqbI8qNcCOAX4QlW/9r3O+aqaVrkXXkQ+FpGrqmasycvyMwkJCYwcOZKxY8fSo0cPli5dyogRI9ixYweDBg3itNNOY9u2bTzzzDPs3r2bM888k549ewIwbdo0vvvuO+bMmUN4eHiT+EW0atUk/YYCm8Wb2CwhxdZvW7+btX7v2rULgJKSEjZv3syFF15ITk4OEydOZMGCBYe0z83NBSA+Pt7/WFxcHAA7duw4qG1ZWRlPPfUU4BwiXxUTxqcJjmCGp3V0DxM8TXAE9zyD3as8FeectgTg177HBKjAvT3iQSEiRwHnAUtrWH4WMB3HMwN4EPg3cEY1zc8GvlTVbUGs+k84e+d3qep+Efke+BWwA/gjMEdEeqnqD772g4E0nAJ+DfC8iHRVVQXmAl/4HAcDC/EdcigiXX33L8U5LHA48LqIHKeqO6tkjQIW4Jxr+DjOLwrzgPsb8Fp8CfxdRKYBi4Hlqtroa66IyDW+/HQw5DqrbvHTpk2ERUby7B13kHjssRRmZrIvJYUhY8eStXUr782fz5MvvMCK1au55+67ueScc5g2cyYvvPoq+3bv5uXnn+eltDQSYmP5y8SJlBX+fNTi9Vdcwe1TpzLkxBPZV1BAu+Rk8jMyiGjVithOnSjMzCS+WzfKCgooKyz0L49KSCAqMZG92dkkJCVRkpfH3u3baX300eRnZBCdmEhEXBxFOTm07tmTou3bOVBa6n9+TLt2hEVGUpybS5vevSnMzEQrKkjs3Zvd69cT27EjACU7d9L2uOMo2LgRCQsjISmJnzZupFXnzlSUl1Oan+/vMzwmhrguXdizeTNxXbuyv6iowZki4uP5ce1a9hcX+5ebmkmB3PR0//+TyZn2bt9OWHj4Ie89EzMFjpfqxlNTZ2oAtn7b+t0gGlK/S3fvJnznz1FnTJ3KaUOHEl5eznNz5rDg9dc5rVu3g8ZmgjoXIvjpxx8pLyoiPyODHRs2ANA2Opq9OTn+sfneN9/www8/cHT37pw1aBC56ekHfd7EdOpEbnp6SMZmsJ83e7dvJ7pt20bVuubIVLRjBxXl5c1WvxuSSYHCrKyQ14XaMpXu3k1ueron3nu1ZSIs7JDxFKr3Xk2ZAutvqN97tWXau307kb4djY2p36IazFVaQET64kw0c4LvobXAQ6r6Tb3XWk/EOaetA87lYuJxCvwFqlrgWz4b32QrIvI88KOq3uJbFg/sxpkUJbNKv88B8ap6ke9+O2AzzheYaFWNCVj//6nqrFocVwF3q+pbIpIC3KGqvXzLWgFFwJFAlG8dbVS1yLd8LlChqpeIyK1AX1W9NKDv/wBzVTWtyjrPwCnalV8eEJHPgaX1fS18y88DbsD58hIBPANMUdUDIvIxMEdVn/O1TQGuUtUhvvt1TjzTMzZW7/H9Qnw4MC4jg+LiYgoKCujSxfkBpKysjGOPPZasrCz+/e9/c+WVV1JUVMTSpUs588wzeeGFFxg/fjx9+/ZlzZo1Nc5oC/DCCy+QkpLSaM/c9HQ6DxrU6H68gM3iTWwW9xCRFao6sJ7PsfXb1u9mqd/jMjIoKyujY8eO7Nmzh/T0dE455RQmTJjAk08+yZ///Gf+/ve/88MPPxATE0NSUhK5ubl069aNAwcOsH37djp37szFF1/M3Llzueuuuw6aRHXgwIGsWLGCxx57zH9aWCChHp/BYIIjmOFpHd3DBE8THKFmz/rW72APd0dV16pqiqqe7Ltd3hwFPoAxvnOthgHHUeUQswC6AP6tGt/kND/inH9XlR9xCm9l23xVTQROBqKrtM0OvCMil4nIKt8hbQVA3ypO/mO0VLXY92e8z293ZYH3EbgV1gP4Y2W/vr6HBHpWyZpTWeCr6as+rwWqukhVRwHtcPbqpwBXVdfWEhx5eXkcffTRnHfeeVx33XWccsopZGVl0blzZ4YPH87pp58OwFVXXcW1117L1KlTARgyZAgAmZmZqKr/VsnXX3/tygY6QHy3bq704wVsFm9is4QWW79t/W5OoqKi/IeiX3bZZYwfP55Zs2YRHh7OxRdfzJtvvkmfPn0YM2YMAJ07dyYlJYWKigqGDx/ORRddxLx584iPjz9oQ/zTTz9lxYoVJCYm1lj/TBifJjiCGZ7W0T1M8DTBEdzzDHojXUSiRORMEbnYV+D8N1dMgkRVPwFm4xz6VR3bcQolACISB7QHcqppuwQ4xXcIXp2rDuizB/AsMBFo7/tisJbgrkv7A9DW51VJ94C/s4GXVDUx4BanqvfV0FdXEQlcb2Bf9Xkt/KhqhaouwfnFo6/v4SIg8CSLI2rrw+LQvn17LrvsMjZs2EBaWhq5ubmMGTOGJUuW0KFDB2bPns2ll15KSUkJs2fPJjo6mokTJ/LPf/6z2RzLDLmkRTDYLN7EZgkttn7b+k0z1+8777yTqVOnUlBQwPz58+nbty9vv/22/7rnVZk5cyY33HADubm5LFiwgFNPPZXFixfT0XcYbGUbgCuvvPKg89cDMWF8muAIZnhaR/cwwdMER3DPM6hz0kWkN/AhziVOqqLAi67YBM8MIFNE+qvq6irL5gHzfIegfYsz4+mX1R0epqqLReQjYIGITAC+xslzah3rj/O12wkgIlfwczGsFVXNEpHlwDQR+RvOzLujgLd9TeYAX4nICJzXPNLns6mac+++APYDfxGRJ339DAI+qu9rISKjgVicSX0KcCaiGQpUzsyyCvi97xDDLsCVQG4wmQ9nEhISePbZZ2tcfuSRR/Lii8EPn2BPT6kPgee6m47N4k1sltBh6/ch2PrdDPU7IiKC6dOnM3369EOWpaSkHPJLeGxsLE888USNM8ADvPbaa3Wu14TxaYIjmOFpHd3DBE8THME9z2AnjrsP8MwxBqq6U5xrv94FXFBl2YcicifwOs4lWT4HLqqlu98Bf8Mprl2BfGANMKKW9a8TkYdwimwFzpecz+oRYRzOpDT5vj5eBBJ9fWf7Cu4DOEX6AJAOXF+NR5mI/B7nV4F7gPeANwKW1+e12A38BWcCm2icvfz/VNWXfcsfwSn8uTjXoX0ZZ+KeoGnbpw/jVq6sz1M8S3lRkX9SCNMx5bqTwWCzeBObJaTY+n3wOmz9bsH124TxaYIjmOFpHd3DBE8THME9z6AmjhORPJwidB7wAc4e6weAx4CLVLXamVotlkD69+mjq7/9NtQarmDK5BXBYLN4E5vFm4Q6S30nnrH12+IGptTvUI/PYDDBEczwtI7uYYKnCY7Q/BPHJQLf+s5zUqBcVefjTK7yt2BXZjm8CWui63yHgqiEhFAruIbN4k1sFm9iYBZbvy2NxpT6bcL4NMERzPC0ju5hgqcJjuCeZ7CHuxfy8wb9XuA4ERmMM8nJMa6YWFo8YkiRD4aoxMRQK7iGzeJNbBZvYmAWW78tjcaU+m3C+DTBEczwtI7uYYKnCY7gnmewv6RvBXqISDjO+V4JOOdHJeCc+2Sx1MmBsrJQK7jG3uzsuhsZgs3iTWwWb2JgFlu/LY3GlPptwvg0wRHM8LSO7mGCpwmO4J5nsBvpLwOfAMcC/wDKcS5XUgGkumJiafGER1e9dK25JCQlhVrBNWwWb2KzeBMDs9j6bWk0ptRvE8anCY5ghqd1dA8TPE1wBPc8g9pIV9UHVXWUqn6rqouAPsAfgL6qOscVE0uLp6K8PNQKrlGSlxdqBdewWbyJzeJNTMti67fFDUyp3yaMTxMcwQxP6+geJnia4AjueQZ7TvpBqOoWYIsrBpbDBq2oCLWCa+wvLg61gmvYLN7EZvEmpmex9dvSEEyp3yaMTxMcwQxP6+geJnia4Ajueda4kS4im4PsQ1XVTj5jqZOI2NhQK7iGKddqDAabxZvYLN7EhCy2flvcxpT6bcL4NMERzPC0ju5hgqcJjuCeZ22HuyfVcesR8LfFUif7S0pCreAa+RkZoVZwDZvFm9gs3sSQLEl13Gz9ttQLU+q3CePTBEcww9M6uocJniY4gnuetR3unhbwtwAXAPuAj32PDQNaAa+4YmJp8ZhyndVgiDbkMhDBYLN4E5vFmxiSxdZvi6uYUr9NGJ8mOIIZntbRPUzwNMER3POscSNdVa+o/FtE7sCZEbaPqu70PdYR2ADkuGJicR0RScI59zBSVfeH1gZ++v575hpyqEpTMS5g79qbb77Jvffey9q1a4mKiuKEE07gnXfe4YMPPiA1NZWtW7eiqiQlJTFhwgRuuOEG/3PT0tJ46KGH2LRpE+3bt+eqq67izjvvJCws2As2/ExEXJwr2byAzeJNbJbmxdZv8zG1flfWuGHDhvHJJ58ctCw5OZm1a9dW+7ykpCSysrIOeuw3v/kN7777LgDbtm3jlltuYenSpezZs4dTTz2VGTNm0K9fv4OeY8L4NMERzPC0ju5hgqcJjuCeZ7ATx00A8ioLPICq7hSRXOAq4HZXbDyOiGQCnYEDQBGwCJioqntD6WUxj3nz5jFu3Diio6MZM2YM8fHxpKenU1xcTFZWFj169GDo0KFkZ2ezcOFCJkyYQJ8+fTjzzDN55ZVXSElJoU2bNlx88cV8/vnnpKamEhMTw6233lpvl6KcHOK7dm2ClM2PzeJNbJaQYus3tn6HikmTJvn/PvLII2ttm5CQwPjx4/33k307BQ4cOMD555/PmjVrOOOMM+jevTvz5s3j7LPP5vvvvychIcH/HBPGpwmOYIandXQPEzxNcAT3PIPdSI8HOonIg8Crvsf+iHPd1aJGW5jFKFX9UES6Av8B7gCmBvNEERFAVNWMaVItTYKq+jem33//fYYNG3bQ8ilTpjBlyhT//X79+rFmzRq2bNnCmWeeyauvOkPwxhtv5O6772bVqlWceOKJ3H///dx8881ERNTvog2te/ZsXCAPYbN4E5slpNj6/TO2fjczM2bMCLptu3btqm2/fv161qxZQ1RUFB9++CGRkZEUFhby1ltv8cwzz3DzzTf725owPk1wBDM8raN7mOBpgiO45xnssbHv4JzXdiPwue92o2/Z266YGIaq5uDsie8rIqeKyOciUiAiq0VkWGU7EflYRP4hIp8BxUBPEVERuU5ENvqe84TvCwAicoyILBWRH0Vkl4i8LCKJAf1lisgUEflGRIpE5HkR6Swii0SkUEQ+FJG2VXTHi8h2EflBRP4a0NdsEbkn4P4wEdkWcL+biLwhIjt9Po/7Hg8TkTtEJEtE8kTkRRFp4+4r3HLZuHEj2dnZxMbG8sADDxAfH0+vXr144okn/G3S09OZNGkSI0eOZM2aNfTp04fRo0cDEBMTA8DatWspLi5m+fLlAOzevZutW7fW26do+3YXUnkDm8Wb2CwhxdbvKtj63Xz1u23btiQmJjJ8+HC++uqrWtvm5OSQkJBAx44dGT16NBs2bAB+rnnl5eWsWrWK/Px8Nm3aBMDq1asP6sOE8WmCI5jhaR3dwwRPExzBPc9gN9KvA17DKfSBt9eB610xMQwR6QacD/wALATuAdoBfwVe953zV8mlwDVAAlB50tVI4BSgH3AhMKKya2A60AXoA3QDUqus/gLgHJxfQkbhfNn4G9AR5//0L1Xanwn0Bn4N3CoiZweRLxx41+ebBHQF/u1bnOK7nQn0xPml5vG6+rQ47Nq1C4CSkhI2b97MhRdeSE5ODhMnTmTBggUArFu3jkcffZSFCxcSFhbGueee6z+k78YbbyQ2NpbXXnuNuLg4rr76an/fO3bsqLfPgdJSF1J5A5vFm9gsIcXW7yrY+t309TshIYGRI0cyduxYevTowdKlSxkxYkSNNap9+/aMHj2acePG0aZNG95++23OO+88SktLOeaYYxg7diyqyqBBg2jfvj0ZvnPfq/Znwvg0wRHM8LSO7mGCpwmO4J5nUMfFquoe4EIRORro63s4Q1WDvRZrS2KBiOwHfsIp7rnAe6r6nm/5ByKyHOcLQOUMu7NV1T9jmG+n+32qWgAUiMhHwADgfVXdBGzyNd0pIg8Dd1dxeExVc319fYpzvuHXvvtvAsOrtJ+mqkXAGhF5AfgT8GEdOQfhfNGYEjBpzTLfvxcDD1f+/4vIbcBaEbmi6gQ3InINzhccOkRG1rHKlk/eihW0Cbje7FP33cfxXboQFR7O0889xysvvMC5Q4dy3vHHU7B5M5s3byZlwgQeeeQRoktKuPn66+nTvTvL5s/nP8uX82NeHicfdxxX3nYbJSUlROzeTXFeHoWZmcR360ZZQQFlhYW0S04mPyODqIQEohIT2ZudTUJSEiV5eewvLaW8qIj8jAyiExOJiIujKCeH1j17UrR9+/+zd+bhUVRp376fLJCtIYRNwxYQEAiICIo7KC6g+MIMIgICQVkUUBhxZlxGDY4O6qsjIjPOiGAiCjgfCqKoqCzuGgWElwAChgQImASyb2Q73x/d6QmQpUOKdJ3m3NfVF91Vp07dv9Cnn67qWigvLnYvHxQRgV9gIIVpaTTv1o285GRURQXh3bqRtWcPwa2d322LMjJo0aMH2fv2IX5+OKKiyNm3j5C2bakoLaU4M9Pdp39QEKGRkeQmJRHarh1lBQWcyM52zw8ICSG4TRuPMgW3acPxnTspKyx0z9c1U1CrVqQlJPz3/0njTGXFxWTt3n36e0/DTFXHS7Xj6Sxnqi+mfp+Eqd9nuX4XZ2WRl5zM608+SYvu3cnaswf/P/yB/kOGcDA1lc8++oib+/Y9bWxuWLmSE1lZRERHc+D777l4+HCSkpLY8PbbDBo6lFfnzWNo//7sPXaM4JISjmZm8uqbb+Lw86Pg6FH3540jKoq0hASvjE1PP2/KiovJT01tUK1rjEzlJSVkbNvWaPX7TDIFBAeTl5Li9bpQWyZESEtIsMV7r65MaQkJtnjv1ZSpav319nuvtkxlxcXkHjhwWqb6Ikqpei90riLOC89MUUp9XmXaP4G7gaq7TQKBvyqlnhWRzcDbSqnFVZZRQDdXQUdE4oDDSqm/iEhb4GXgGpx77v2ALKVUh+ocROQtYL9SKtb1egpwp1LqBvnv1WHDXEUeEZkJDFdKDau6Xte8wcBbSqn2InIH8Cel1IBq/g67gYeUUutcr4OAIqC96zDCaukSHKye1uR8krPFuMRESkpKaN26Nbm5uSQkJHDppZcyc+ZM/vnPf3L//ffzzDPPnHQhnOnTp/Paa68xceJE4uPjKSsrw9/fv/LLIm+88QZ33303nTp14sCBA+7pnpKWkEDbyy6zNKe3MFnsicliHSKypbrPZUPtmPrt9j+r9XtcYiKFhYVkZ2cTGRkJQElJCd27dyclJYWVK1cyZMgQjh07hsPhoF27dhw/fhw/Pz9atHAe6V+5bFFREd9//z0DBw6kpKSEJk2aAM6j0C655BL27NnD0qVLmTzZfTMDr49PT9DBEfTwNI7WoYOnDo5Qs2d963eNv6SLSBKwVSl1u+t5TSil1AWertAHOQQsU0pNraVNffaE/M3Vvo9SKlNERtLwQ9E6AHtczzsClSdLFOC8V24l51V5fgjoKCIB1dz+5QjQqcrrjkAZzl8lDHXQpEkT5syZw1NPPcXEiRO54oorWLFiBf7+/owfP57+/fvTuXNnunTpQmpqKuvWrQPg5pudR1Tu2bOH3/3ud1x77bVkZWXx/vvvIyI8//zz9d5ABwiKiLA0nzcxWeyJydK4mPrtMaZ+n4X6nZ6ezoUXXsj1119Pp06d+O6770hJSaFt27YMGTKERYsWMW/ePEaMGMGaNWv4v//7P4YPH86QIUM477zz2LBhA0VFRfTq1Yt+/foBMHnyZHJycoiMjGTTpk3s37+ffv36MX78+JPWrcP41MER9PA0jtahg6cOjmCdZ23npEfhPFyq8nltj3OZt4DbRORmEfEXkSDXBVzan2F/DiAfyBHnFWj/WEd7T3hcREJEJBqYDLzjmv4zcIuIRIjIecCcKssk4Dxf71kRCXXluso1bwXwBxHpLCJhOL+YvGOHe7nqwuOPP87DDz9MdnY277zzDr1792bt2rUMHDiQG264gV9++YWlS5fy9ddfM2DAAOLi4hg3bhzgvBBPixYteOedd/joo48YMGAAa9as4Y477jgjFz8fOg3BZLEnJkujE4Wp355g6vdZqN8tW7Zk4sSJ7N27l/j4eNLS0hg5ciQbNmygVatWp7Xv2rUrI0aMYNu2bcTHx1NcXMyECRP45JNP3L+e9+nTh23bthEXF0deXh7Tp09nw4YN7vmV6DA+dXAEPTyNo3Xo4KmDI1jnWds56W8C+6o8N8fFV4NS6pCIjACex1n8ynEWyDO9IM88nH/vHJznti3jv1fiPVO+cPXlB7yglPrUNX0ZcAOQ7Hq8AcwFUEqVi8htwELgIM7//+XAN8BSnF8AvwSCcN7K5v4GOp5TBAQEMH/+fObPn3/avH/+85+1LtuuXTsSEhIscylMS8PRqVPdDTXAZLEnJkujY+q3B5j6fXbqt8PhYPHixTXOj42NJTY21v26ffv2vP3227X2+fDDD/Pww3XfLU+H8amDI+jhaRytQwdPHRzBOk9zTrqh0ejfr5/asm2btzUsoTgri6AWp94pR09MFntistgTb2cx56QbvIEu9dvb49MTdHAEPTyNo3Xo4KmDI9TsWd/67ekt2Co7byrOe292rPqoTx+Gc5fyEye8rWAZecnJ3lawDJPFnpgs9kTXLKZ+GxqCLvVbh/GpgyPo4WkcrUMHTx0cwTpPj27BJiLdgSXAldXMVp72YzD4CqqiwtsKlmGy2BOTxZ7olsXUb8O5hA7jUwdH0MPTOFqHDp46OIJ1np4W58XAVXW2Mhhqwb9pU28rWEZ4t27eVrAMk8WemCz2RMMspn4bGowu9VuH8amDI+jhaRytQwdPHRzBOk9PD3fvD1QALwFTcV5htPJxtyUmBp+nrLi47kaakLVnT92NNMFksScmiz3RMIup34YGo0v91mF86uAIengaR+vQwVMHR7DO09Nf0g8D5UqpuZas1XBO4hfgO0dVBrdu7W0FyzBZ7InJYk80zGLqt6HB6FK/dRifOjiCHp7G0Tp08NTBEazz9PSX9L8AF4jILZas1WAwGAwGQ2Ng6rfBYDAYDJrh6Ub6/wICfCAimSKSVOXx61n0M/gQFWVl3lawjKKMDG8rWIbJYk9MFnuiYRZTvw0NRpf6rcP41MER9PA0jtahg6cOjmCdp6fHL1W9I3u461GJudG6wSMCgoK8rWAZLXr08LaCZZgs9sRksScaZjH129BgdKnfOoxPHRxBD0/jaB06eOrgCNZ5evpL+ptAfA2PNy0xMfg8utxn1ROy9+3ztoJlmCz2xGSxJxpmMfXb0GB0qd86jE8dHEEPT+NoHTp46uAI1nl69Eu6UirGkrUZzmlyDxxgeXR0g/sZl5jIggULWLp0KYmJiVRUVPDkk08SGxsLQFRUFCkpKactN2jQIDZv3gzA5MmT2bRpk7vdpk2bGDx4sMcO4ufp/i37Y7LYE5PFnuiWxdRvgxXUVb/HJSae9HrFihWMGzcOgNmzZ7NgwYJql9u4cSNPPPEEO3fupKysjO7du/PII48wevRoAGJjY5k3b95py2VkZNCqVavTpuswPnVwBD08jaN16OCpgyNY56nH5ToNZwURyQcuUkolWdDXA8B1wO+VUmf9EMotW7YQERFBhw4dTtsgv/vuu8nMzHS/fu+99zh06BBdu3Z1T/vuu+/o06cPR48epaSkpN7rd0RFnbG73TBZ7InJYk98KYtBX+xcvw8fPsyMGTMICAigrJZz2QsKCrjtttsoLCzk+uuvp3nz5qxevZo777yTSy65hAsuuMDddtSoUbRv3979Ojg4uNo+dRifOjiCHp7G0Tp08NTBEazzrHVTX0TKa3jkiMiXIjLUEgvDWUVEkkWkSETyRSRNROJEJEwpFWZRge+G8367MY2xgQ6wbNkyNm/ezMUXX3zavCeeeIIFCxawYMECHnvsMTJcF3B44IEH3G327NnDBx98UGOhr4scTQ6Y9fjdAAAgAElEQVS58QSTxZ6YLPZElyymfvsGutVvpRSTJk0iMjKSUaNG1dr2t99+o7CwEID333+f9957j5YtW1JRUcHBgwdPajtr1ix3XV+wYAGhoaHV9qnD+NTBEfTwNI7WoYOnDo5gnWddv8dLDQ8HcDXwoYjcYImJ4Wxzm1IqDLgEGIDztjxW0RMYp5TKsbBPS/jXv/5FcXEx119/PRdddJFl/Ya0bWtZX97GZLEnJos90SiLqd++gzb1e8GCBXz99de8/fbbBNVxsbkLLriA3/3udwCMGDGC3//+9xw/fpwhQ4ZwzTXXnNR25MiRhISE0LdvX5YvX15jnzqMTx0cQQ9P42gdOnjq4AjWedZ1uHt8DdNb4jw0KhT4M/C5JTaGs45SKlVEPgZ6i4gCuiml9ovIrcDTwAVADrBEKRULICKDgbeUUu5jzUQkGZiilPoc5xeHO4C7GjNLXZSUlPDqq68CMGfOHEv7rigttbQ/b2Ky2BOTxZ5olMXUbx/D7vV7586dPPLIIzz11FPVHuVWHRMmTODLL79k48aNAISFhfH73/+egADn19OAgACuvfZaevToQXJyMp9++injx4+nZcuW3Hzzzaf1p8P41MER9PA0jtahg6cOjmCdZ60b6UqpyTXNE5H+wI9Af0tMDI2CiHQAbgHeA26tMqsAmAgkAr2Bz0TkZ6XUmgaubxowDaBVYGBDunJTkptL9r59iJ8f5a6BcCI7m5z9+ynOzCQiOprMxETe/ewzjh49Suf27Rncrx/Ze/dyIjvbPT8gJARcR/cVHT9O1u7dlOTluec3cThoEh5O/qFDOKKiKEpPp6ywkIjoaI5++y2qooKA0FAKUlNp1qULBUeOUF5c7F4+KCICv8BACtPSaN6tG3nJyaiKCsK7dSNrzx6CW7d2rjsjgxY9ergzOaKiyNm3j5C2bakoLT0pk39QEKGRkeQmJRHarh1lBQWnZQpu04a85GTCOnSgJDu7zkwZW7cScv75ZCYm0jQ8XOtMJ7KyKCsudv8/6ZwpNzmZ4szM0957OmY6+u23VJSW1jiedMqU9uOP7vFS22fE2crkKaZ++x52rt95KSnEL1xISUkJn33wAZ9/+CF7DhwAYM177+F34gR/njz5pLF5qKiIUaNGERoSQsInn9C0vJzb7r2XmTNn0kIpRo4Zw5Qbb2TO5MnusflAs2b8Z9Uqlr/+Otf063fa501ZURHFmZleGZueft4c/fZb/IODLanfZzPT0e+/pyQvr9G/k9QnU35qqi3qQm2Z0rdsOal/u9a6gtRUijMzbfHeqynT0W+/dddfb7/3ast09NtvEX//0zLV+zP4TE9BEhF/oAQoV0o1OaNODI2Ca695K6AM5172dcBcoBDXnvhqllkAKKXUH+raEy8isUBXpVSte+K7BAerp7t0aXCeqleRHTlyJO+///5JV3evZMCAAWzZsoVXXnmFWbNmVdtXeHg4OTk59b66e2lBAYE1nBOnGyaLPTFZ7Im3s4jIFqXUgAb2Yeq3JuhSv8clJtZ4JXZw3l1l1apVHDt2DIfDQbt27Vi1ahWjR4+mU6dOJCcnu9t9+eWXvPDCC8ydO5f9+/efdNHXsWPHsnLlSu699173kXJV8fb49AQdHEEPT+NoHTp46uAINXvWt3435Brxk3Ce33asAX0YGo+RSqlwpVQnpdQMpVRR1ZkiMlBENolIhojkAPfi/GJgS15//XViYmLYunUrAGvWrCEmJoY1a5w/HHz11Vds2bKF8PBwYmJiTlv+oYceIiYmxn3RmmeffZaYmBj27Nnj0fozT7ndjM6YLPbEZLEnPpLF1G+90KJ+x8bGopRyPyZNmgQ4b8G2efNmFi1aRM+ePZk5cybg3JHetGlTUlJSGDZsGGPGjOHLL79ERLjqqqsAuPHGG7niiiuYNm0aQ4cOZeXKlfj5+XHnnXdW66DD+NTBEfTwNI7WoYOnDo5gnWeth7uLSE1XDo3AefEZBWy2xMTgbZYDi4BhSqli1574yiJfAIRUNnT9CtO68RX/y9dff018/H9Pudy+fTvbt28nKiqKkSNH8vLLLwNwzz33EBYWdtryq1atOunWbevXrwcgJiaGHj161Ll+/zouiKMTJos9MVnsiS5ZTP0+p9CqflcSFRXFmjVr+Otf/8p3331HeXk5/fr146GHHuLyyy8HYOrUqbzzzjusWLECf39/rrzySh599FEGDRpUbZ86jE8dHEEPT+NoHTp46uAI1nnWdeG4qDrmZwJPWmJi8DYOINNV4C8DxgGfuubtBYJcF6f5FHgUaOodTSdxcXHExcXVOH/VqlW1Ll95aN2ZEhoZ2aDl7YTJYk9MFnuiUZaoOuab+u072LJ+n1qnY2NjTzstbejQoQwdWvPdAB999FEeffRRj9epw/jUwRH08DSO1qGDpw6OYJ1nXYe7fwl8ccpjM85zop4B+iql9LhpnaEuZgBPiUge8ATwn8oZrluzzABeB1Jx7pk/7A1Ju5Cb1ODb09oGk8WemCz2RKMspn6fO5j67UKH8amDI+jhaRytQwdPHRzBOs8zvnCcwVBfLunbV23dvt3bGpaQn5pKWLt23tawBJPFnpgs9sTbWay4cJzBUF90qd/eHp+eoIMj6OFpHK1DB08dHKFmz8a8cJzBUC9Uebm3FSyjrKDA2wqWYbLYE5PFnvhSFoPBU3Sp3zqMTx0cQQ9P42gdOnjq4AjWeZqNdEOjUaFJkfeEE9nZ3lawDJPFnpgs9sSXshgMnqJL/dZhfOrgCHp4Gkfr0MFTB0ewztNspBsajYDgYG8rWEZEdLS3FSzDZLEnJos98aUsBoOn6FK/dRifOjiCHp7G0Tp08NTBEazzNBvphkajrKio7kaaoMu9Gj3BZLEnJos98aUsBoOn6FK/dRifOjiCHp7G0Tp08NTBEazzNBvphkZD/Hzn7RYQElJ3I00wWeyJyWJPfCmLweAputRvHcanDo6gh6dxtA4dPHVwBOs89fjUNfgEfoGB3lawjOA2bbytYBkmiz0xWeyJL2UxGDxFl/qtw/jUwRH08DSO1qGDpw6OYJ2n2Ug3NBrlJ054W8Ey8pKTva1gGSaLPTFZ7IkvZTEYPEWX+q3D+NTBEfTwNI7WoYOnDo5gnafZSDc0Gv5NmnhbwTLCOnTwtoJlmCz2xGSxJ76UxWDwFF3qtw7jUwdH0MPTOFqHDp46OIJ1nmYj3dBo6HKfVU8o0eQ2EJ5gstgTk8We+FIWg8FTdKnfOoxPHRxBD0/jaB06eOrgCNZ5BljSi8EnEJF84CKlVNLZ6D/n119ZbpPbJ4xzXXlx0qRJfP755xw7dgyHw8GAAQOYP38+/fr1c7fdv38/F198MQUFBfTt25eff/6Zkrw8vvjiC2bPnk1SUhKlpaW0b9+eu+66iyeeeAIR8Va0elOSl+dtBcswWeyJyWIwnF28Wb/rU0+r8t133/Hoo4+ydetW/P39GT58OAsWLCAiIgKA2NhY5s2bd9pyGRkZtGrVqto+dRifOjiCHp7G0Tp08NTBEazzPKc20kXkauB5IBooB3YDc5RSPzaw38HAW0qp9g3oownwKDAeiAQygI3AU0qp5LO9fgClVFhDlteRlJQUBg0aRPPmzdm4cSPr169n9+7dpKSkAFBWVsZdd93FiVPOx4uIjubI2rVEREQwcOBAsrKyeO+994iNjaVjx45MnjzZG3HOCF3uO+kJJos9MVkMDcXU79qxQ/2uq55WJSkpiZtuuomCggLGjBnDsWPHWLZsGRkZGXz88ccntR01ahTt2//3zxNcyz3bdRifOjiCHp7G0Tp08NTBEazzPGc20kWkGfAhcB/wH6AJcA1gl6uhrALaA+OAbUAocBcwBFhyNlcsIgFKqbKzuQ67snnzZvfzrVu30r9/fw4fPkxpaSmBgYE888wz7Nixg7lz5/Lcc8+522YmJjJ27FjGjh3rnvY///M/fPDBBxw4cKAxIzSYzMRE2l52mbc1LMFksScmi6EhmPpdM3aq33XV06p8/PHH5OfnM3jwYFasWEFFRQWtWrXik08+YcuWLfTv39/ddtasWQwePNgjBx3Gpw6OoIencbQOHTx1cATrPM+lc9K7AyilViilypVSRUqpT5VSOwBE5AIR2Sgix0XkmIi8LSLhlQuLSLKIPCQiO0QkR0TeEZEgEQkFPgYiRSTf9YgUkctE5DsRyRaRoyKyyLW3/TRE5AbgRmCEUupHpVSZUipHKfUPpdQSV5vJIrJbRPJEJElEprumn9H6RUSJyEwR2QfsqzKtq+t5nIj8Q0TWudb5g4hcUGX5l0XkkIjkisgWEbnGwv+rRmXRokXMmDHDvcE9d+5cAgMD+fHHH3n66ad54YUX6NGjx0nLNHE4AOeh8HPmzGH06NF89NFHtGvXjokTJzZ6hoZQmcUXMFnsicliaCCmfmtSv2uqp6cSFBQEOH99T09PZ9euXRQUFACwffv2k9qOHDmSkJAQ+vbty/Lly2tdvw7jUwdH0MPTOFqHDp46OIJ1nufSRvpeoFxE4kVkmIi0OGW+APNxHqrWE+gAxJ7S5g5gKNAZuAiIUUoVAMOAI0qpMNfjCM7D8f4AtAKuwLlHfUYNbjcACUqpQ7X4pwPDgWbAZOAlEbmkgesfCQwEetWwzjuBeUALYD/wTJV5PwIXAxHAcuD/iUhQLf62ZdWqVbz66qvs3buX9u3bc9VVV1FYWMhdd93FjTfeyIwZp/+3NQl3fv87fPgwL7/8MqtWraK8vJzrrruO1q1bN3aEBlGZxRcwWeyJyWJoIKZ+a1K/q6un1TF69Gi6devGgQMHaNu2LX369KGkpASA3377DYCAgACuvfZaxowZwzXXXMOOHTsYP34869evr3H9OoxPHRxBD0/jaB06eOrgCNZ5njOHuyulcsV5TtufgcXAeSLyETBVKZWmlNqPs5ABZIjI34EnT+lmoauAIiIf4CxyNa1vS5WXySLyb2AQsKCa5i2Bo3X4r6vy8gsR+RTn4X5bG7D++UqpzFpWu1oplQAgIm8Df6/S/1tV2r0oIn8BLgRO2gUuItOAaQCtqtmb7i3SEhIICAkhuE0b3nn+eQJat+aTdeuYOHs2t99+O/955RX27t1LuMPBjVdfTZrrSo1J+/dz67BhvDh2LOddfjkDunXj6PffkxcczH0zZ/LWW2/RJCCAv913H0EREfgFBlKYlkbzbt3IS05GVVQQ3q0bWXv2EOzamC/KyKBFjx5k79uH+PnhiIoiZ98+Qtq2paK0lOLMTCKio8lMTMQ/KIjQyEhyk5IIbdeOsoICTmRnu+dXZspLTiasQwdKsrMpyctzz2/icNAkPJz8Q4dwREVRlJ5OxtatXDBqFJmJiTQNDycgNJSC1FSadelCwZEjlBcXu5e3e6YTWVkUHz9OWWGhe76umXKTk0/6f9I506HPPqPtpZee9t7TMVPajz+6x0t14+lsZzoXMfXb3vU7Z/9+9/v4k9WryfjlFzZ+8w13/+lP3D5qFNs2b6Zju3anjc3vN23ijX/8g6M5OXTr3Jk3V6zg261baZqfz7EdO3hw+nSm3nSTe2xOnjWLNZ99xtv/+hcD2rWr9vOmrKiI/EOHvDI2Pf28OfTZZ7QfMsSS+n02Mx3asIGW0dGN/p2kPpnyU1Npc8klXq8LtWU68uWXNOvc2RbvvdoyFaSmkn/okC3eezVlOvrtt+766+33Xm2ZDn32GZHXXHNapvoiSql6L+QLiEgP4C1gn1JqrIi0BV7GWTgdOI8yyFJKdXC1TwamKKU+d72OBboqpe6Sai78IiLdcRbFAUAIzh0iW5RSpx1WJiLPAlcopQbV4jsM55eO7i63EOA5pdTjZ7J+EVFAd6XUvirLKKCbUmq/iMQBh5VSf3HNO2kdIvIQcA/OXy4Uzl8IblRKbagpQ5fgYPV0ly41zW5UxiUmUlRURJMmTfD39wfgxIkTtGnThtzcXDZu3Mj1119f4/IFaWmUBwfjqHJIy/z583n00Ue59tpr+eKLL856BqsoTE8npE0bb2tYgsliT0wW6xCRLUqpAV4TsAGmfturfntST/v06eO+6nu7du0AKCkpoYnr/ut79uyhb9++lJaWsm/fPi644AL2799P165d3esZO3YsK1eu5N577+XVV1+t1sXb49MTdHAEPTyNo3Xo4KmDI9TsWd/6fS4d7n4SSqk9QBzQ2zXpbziLVR+lVDOcF33x9D5a1e3peBXYg7NoNsN55dea+vscuExEqr26q4g0Bd4FXgDaKqXCgY+q9Hem6z+jPTSu89f+hPPwwRYun5xq+rc1P/zwAx06dODOO+/kvvvuo3///uTm5tK6dWsuueQSlFLuxxtvvAFA3759UUpRlJ7OyJEjGTRoENOnT+eOO+5w3yrm5ptv9maselOUnu5tBcswWeyJyWKwElO/a1yuTs5W/a6rni5atIiePXsyc+ZM9zJ9+vRh3LhxxMTEcMUVV1BSUsKMGTO44ALn6fM33ngjV1xxBdOmTWPo0KGsXLkSPz8/7rzzzho9dBifOjiCHp7G0Tp08NTBEazzPGc20kWkh4jMrSykItIBGAt872riAPKBHBFpB/yxHt2nAS1FpHmVaQ4gF8h37fW/r6aFXXv3PwNWi0h/EQkQEYeI3Csid+O8km1TnLd1KXPtlb/JqvWfAQ6gzOUTICJP4NwTrxWRkZF0796dzz77jCVLlpCVlcXo0aPZuHEjzZs3r3XZssJCBg0axJEjR3jzzTdZv349F154IS+++CKPPPJIIyWwhrLCQm8rWIbJYk9MFkNDMPXb/vX7TOpp7969Wb9+PcuXL6dVq1Y899xzLFy40D1/6tSpFBYWsmLFCr7//nuuvPJK1q5dy6BBNR60oMX41MER9PA0jtahg6cOjmCd5zlzuLurcL8EXAWEA9k4b+nyR9f5btHAmzjPy9oPLAP+UOXwsGRqOFzO9XopMALwx3khl67Aazhvy7IN2ARcr5S6uga/JsBjOO+zej5wDGfhf0opdVBEZgJP4Cz2HwCBwP4qh7PVa/1VD42r4uDR4XIi4o/zvMDbgQLX33VG1b9PddjtcPeGUFpQQGBoqEU23sVksScmiz3xdpZz8XB3U7/tXb8bWk+txNvj0xN0cAQ9PI2jdejgqYMj1OxZ3/p9zmykG7xP35491fbdu72tYQlpCQla3KvRE0wWe2Ky2BNvZzkXN9IN3keX+u3t8ekJOjiCHp7G0Tp08NTBEWr2NOekG2yLn+uCMr5AU01uA+EJJos9MVnsiS9lMRg8RZf6rcP41MER9PA0jtahg6cOjmCdp9lINzQaokmR94QADQ638RSTxZ6YLPbEl7IYDJ6iS/3WYXzq4Ah6eBpH69DBUwdHsM7TbKQbGo3ykhJvK1hGQWqqtxUsw2SxJyaLPfGlLAaDp+hSv3UYnzo4gh6extE6dPDUwRGs8zQb6YZGw79pU28rWEYzm1wAzwpMFntistgTX8piMHiKLvVbh/GpgyPo4WkcrUMHTx0cwTpPs5FuaDQqSku9rWAZBUeOeFvBMkwWe2Ky2BNfymIweIou9VuH8amDI+jhaRytQwdPHRzBOk+zkW5oNFRFhbcVLKO8uNjbCpZhstgTk8We+FIWg8FTdKnfOoxPHRxBD0/jaB06eOrgCNZ5mo10Q6MREBzsbQXLiIiO9raCZZgs9sRksSe+lMVg8BRd6rcO41MHR9DD0zhahw6eOjiCdZ5mI93QaJQVFXlbwTIyExO9rWAZJos9MVnsiS9lMRg8RZf6rcP41MER9PA0jtahg6cOjmCdp9lINzQafgEB3lawjKCICG8rWIbJYk9MFnviS1kMBk/RpX7rMD51cAQ9PI2jdejgqYMjWOepx6euwSfI2b+f5TY/VGXcKXu/VqxYwbhx4wCYPXs2CxYsAOD1FSv4Z1wchw8fJioqikcffZRJkyYBsHv3bmJiYvjll18oKirivPPOY+TIkTz33HMEBQU1biAP8AsM9LaCZZgs9sRkMRj0pqb6XVkzJ02axOeff86xY8dwOBwMGDCA+fPn069fv2r7i4qKIiUl5aRpt956Kx9++GGDPHUYnzo4gh6extE6dPDUwRGs8zS/pBsahIh8JCL3edvjbHD48GFmzJhBwCm/IKxcuZKHnniCvLw8xo4dS0ZGBjExMaxfvx6A48ePExAQwOjRo7njjjvIyMhg4cKFzJ8/3xsx6qQwLc3bCpZhstgTk8VgsB9W1u+UlBQGDRrE3XffTcuWLVm/fj0jR46sdRmHw8Hs2bPdjxEjRjTYQ4fxqYMj6OFpHK1DB08dHME6T/NLumaISDLQFigHCoCPgVlKqXwvuEwEMpVSrzb2us82SikmTZpEZGQkffr04Z133nHPe/bZZwF49dVXGTVqFEuWLGHKlCnMnz+fm2++mauvvppvvvnG3b5Fixa88sorHDhwoNFzeELzbt28rWAZJos9MVkMBt+u35s3b3Y/37p1K/379+fw4cOUlpYSWMOvShEREe6j06xCh/GpgyPo4WkcrUMHTx0cwTpP80u6ntymlAoDLgEGAH/xdEFxYtX/exgw3aK+bMWCBQv4+uuvefvtt086RL2srIydO3cCMGDAgJP+/fnnn93tMjMzmTNnDhMmTOD1118nPDyc++6z5wEHecnJ3lawDJPFnpgsBoMbn63fixYtYsaMGYwdOxaAuXPn1riBDpCamorD4aB169aMGDGCvXv3NthBh/GpgyPo4WkcrUMHTx0cwTpPs5GuMUqpVJx74vuIyIcikiEiWa7n7SvbichmEXlGRL4BCoEuIjJZRHaLSJ6IJInI9CrtB4vIYRGZKyLpInJURCZXmX+riGwDngX2iEhso4VuBHbu3MkjjzzCU089xcUXX3zSvGPHjlFeXg5AWFgYAKGhoQDk5ORQ7Lo3Ym5uLi+//DJvvfUWRUVFXH755XTs2LERU3iOLve/9QSTxZ6YLAbDyfhi/V61ahWvvvoqe/fupX379lx11VU1tm3ZsiUjRoxg3LhxNG/enLVr1zJs2DB3DT1TdBifOjiCHp7G0Tp08NTBEazzNBvpGiMiHYBbgCTgDaAT0BEoAhad0nwCMA1wAClAOjAcaAZMBl4SkUuqtD8PaA60A+4B/iEiLVzzioCJQDhwKzBDRGo/+Uwj3n33XUpKSvjiiy8YPnw4GzZsAGDt2rW8/PLL+Pv7A5Cfn3/Sv82bN3f/6h4VFYVSivT0dCZPnswnn3xCTExM44fxgHBNDh/yBJPFnpgsBsPJ+GL93rx5M0VFRaxZs4YjR45w++23n3ZxuEp++uknVq1axb///W9++ukngoODSUpKYtu2bQ1y0GF86uAIengaR+vQwVMHR7DO05yTridrRKQMyAHWAX9SSrlvYioizwCbTlkmTilV9dLl66o8/0JEPgWuAba6ppUCTymlyoCPRCQfuBD4Xim1scqyO0RkOTAIWHOqqIhMw/nlglYaXJUxLSGBshMnUErx8ccfnzTvwIEDfPHpp/Tq2ZP/27mTTWvWcPvtt7PhP/8BoFfXrqQlJBDYsSOlBw8SFBFBUGAgl3XuzBvAnp07Sd+yhfBu3cjas4fg1q0BKMrIoEWPHmTv24f4+eGIiiJn3z5C2ralorSU4sxMIqKjyUxMxD8oiNDISHKTkght146yggJOZGe75weEhBDcpg15ycmEdehASXY2JXl57vlNHA6ahIeTf+gQjqgoitLTydi6lQtGjSIzMZGm4eEEhIZSkJpKsy5dKDhyhPLiYvfyQRER+AUGUpiWRvNu3chLTkZVVNgm04msLGcfhYXu+bpmyk1OJqhlS/f/k86Zktasoe2ll5723tMxU9qPP7rHS3Xj6WxnMmiPT9XvtIQEVEgIQSEhnDh2jObdutH/vPMIDQ4mr6CAn9ato2LgQI5nZRFQXEyva68l6ccf8Q8IoMNFF5Gzbx8lQUGgFAAVJ06QlpBwxp83ZUVFBAQHe2Vsevp5k/LRR7QfMsSS+n02MyWtXUvL6OhG/05Sn0z5qam0ueQSr9eF2jKlbtpEs86dbfHeqy1TQWoqTVu0sMV7r6ZMR7/91l1/vf3eqy1T0po1RF5zzWmZ6oso1wejQQ9cF56ZopT6vMq0EOAlYChQubfcAQQopcpFZDPwtlJqcZVlhgFPAt1xHlERAjynlHpcRAYDbymlqh5y516va4/9M0BPQHDusf9AKTWhNvcuwcHq6S5dGpD+7HPqLdgAYmJiiI+Pd9+Cbfny5YwfP57WrVtzyy238P7775Odnc1HH33EsGHDmDx5Mrt27aJPnz6cOHGCtWvXkpuby9SpU3nttde8kKp2cg8coFnnzt7WsASTxZ6YLNYhIluUUgO8JmA4Y3yxfo9LTGTz5s2MGzeOa6+9lhYtWvDVV1+RmJhI69at2bdvHy+99BLz5s1jxIgRrFmzhs2bNzN8+HCGDBnCeeedx4YNG/j111/p1asX27Zto0mTJvX5s56Et8enJ+jgCHp4Gkfr0MFTB0eo2bO+9dsc7u4bzMW5l3ygUqoZcK1rulRp494bIyJNgXeBF4C2Sqlw4KNT2tfGO8CHQFelVCcgvh7Las+4ceN47oknCAsLY/ny5bRu3ZolS5YwbNgwAK644gry8/NZsWIFq1evJjIykscff5xXXnnFy+YGg8FgsBna1+/IyEi6d+/OZ599xpIlS8jKymL06NFs3LiR5s2bn9a+a9eujBgxgm3bthEfH09xcTETJkzgk08+adAGusFgMPgS5nB338CB8zyzbBGJwLmHvTaaAE2BDKDMtVf+JmCnh+sLB4qUUmUichkwFvj0jMw1IC4ujri4uJOmTbr1Vv40b1617adNm8a0adMawcwaijIytNgz6Qkmiz0xWQyGGtG+fnfv3v2kW7CdSmxsLLGxse7X7du35+23327IKmtEh/GpgyPo4WkcrUMHTx0cwYUsse0AACAASURBVDpP80u6b7AACAaOAd8Dn9TWWCmVBzwA/AfIAsYBa+uxvvuAJ0UkD3jC1c85RYsePbytYBkmiz0xWeyJL2Ux2AJTvy1Eh/GpgyPo4WkcrUMHTx0cwTpPc066odG4uFcv9fOuXd7WsIT0LVto07+/tzUswWSxJyaLPfF2FnNOusEb6FK/vT0+PUEHR9DD0zhahw6eOjhCzZ7mnHSDoREQP98ZOiaLPTFZ7IkvZTEYfA0dxqcOjqCHp3G0Dh08dXAE6zz1SGvwCfybNvW2gmU4oqK8rWAZJos9MVnsiS9lMRg8RZf6rcP41MER9PA0jtahg6cOjmCdp9lINzQaZcXF3lawjBwful+xyWJPTBZ74ktZDAZP0aV+6zA+dXAEPTyNo3Xo4KmDI1jnaTbSDY2Gf2CgtxUsI6RtW28rWIbJYk9MFnviS1kMBk/RpX7rMD51cAQ9PI2jdejgqYMjWOdpNtINjYYvXaSworTU2wqWYbLYE5PFnvhSFoPBU3Sp3zqMTx0cQQ9P42gdOnjq4AjWeZqNdEOjUVFW5m0FyyjOzPS2gmWYLPbEZLEnvpTFYPAUXeq3DuNTB0fQw9M4WocOnjo4gnWeZiPd0GgEBAd7W8EyIqKjva1gGSaLPTFZ7IkvZTEYPEWX+q3D+NTBEfTwNI7WoYOnDo5gnafZSDc0GmVFRd5WsIzMxERvK1iGyWJPTBZ74ktZDAZP0aV+6zA+dXAEPTyNo3Xo4KmDI1jnaTbSDY2GLvc39AT/oCBvK1iGyWJPTBZ74ktZDAZP0aV+6zA+dXAEPTyNo3Xo4KmDI1jnGWBJLwbbICLJwBSl1OeNuM7BwFtKqfa1tctNSmK5RYeAjHPtpVqwYAFLly4lMTGRiooKnnzySWJjYwE4ceIEf/rTn1i9ejVpaWm0bNmSm266ib///e9EREQQGxvLvHnzqu3/wIEDRNVyn8PQyEhLctgBk8WemCz2xJeyGOyFbvV7XGIiU6ZM4ZtvvuHQoUM0bdqUgQMH8vzzz9O7d+8a+xo8eDBffPHFSdOio6PZuXMnAJmZmTz44IN8+umnHD9+nLZt2/K73/2O559/nqZ13K9dh/GpgyPo4WkcrUMHTx0cwTpPW+waFZFkESkRkVanTN8mIkpEojzoI8rV9ox3PIiIQ0T+7vIpEJGDIrJKRAaeaZ+6ICJNRORFETksIvmuv8ECb3vVxZYtW4iIiKBDhw6nzZs/fz4LFy4kPz+fSZMm4e/vT3x8PH/4wx8AuPzyy5k9e7b7cfPNNwPQrFkzWrduXet6c5OSrA/jJUwWe2Ky2BNfymIFpn57H2/W7yVLlhAeHs7YsWNp1qwZH3/8MUOHDqXYg/uqV62/EyZMcE9/8MEHiY+Px9/fn5iYGPLz81m4cCF/+9vf6uxTh/GpgyPo4WkcrUMHTx0cwTpPO/2SfgAYC7wCICJ9gJDGWrmINAU2AtnAcGA3EAQMcz1+qGaZAKWUHpc8rZtHgAHAZcBRoBNwrVeNPGDZsmUAjBw5kpSUlJPm/frrrwDcfffdvPDCCyxatIj777+f5ORkAIYOHcrQoUPd7UeNGgXAPffcQ2hoaK3rDW3XzqoIXsdksScmiz3xpSwWYuq3d/Fa/f7pp5/o378/AMnJyXTu3JnU1FR27drFJZdcUuuyCxZUvx+hsnb/+c9/ZtasWTgcDl588UV37a4NHcanDo6gh6dxtA4dPHVwBOs8bfFLuotlwMQqrycBb1ZtICK3uvbO54rIIRGJrTL7S9e/2a49yVeIiJ+I/EVEUkQkXUTeFJHmNax/AtAeGKmU2qmUKldKFSilViml3Otx7e2fKSL7gH2uaVNFZL+IZIrIWhGJdE0XEXnJte5cEfk/EentmneLiOwSkTwRSRWRh6qso9r+qkNEJrjyHReRx06Z11REFojIEddjgevLTHVcCqxWSh1RTpKVUm9W6UuJSNcqr+NE5OmavOzAvffei8PhYOnSpUyfPp3nnnuOkJAQ/vjHP57WNjk5mffffx9/f38eeOCBOvsuKyg4G8pewWSxJyaLPfGlLBZi6vd/13FO1e/KDXSAkpISAPz9/Tn//PPrXLZFixaEh4czZMgQfvzxR/f02bNnExgYyHPPPcf06dNZunQpLVu2ZNasWXX2qcP41MER9PA0jtahg6cOjmCdp5020r8HmolITxHxB+4E3jqlTQHOLwLhwK3AfSIy0jWvcq9xuFIqTCn1HRDjelwHdAHCgEU1rP8GYL1SypO/7EhgINBLRK4H5gN3AOcDKcBKV7ubXF7dgeauNsdd85YA05VSDqA3zl8BqKO/kxCRXsCrOL+gRAItcX5RqeQx4HLgYqAvzr3sf6kh0/fAgyIyQ0T6iIh48HewNb169eKmm24iKyuL1157jcOHDzNw4MBqz5V75ZVXKC8vZ8SIEbWei17Jiezss2DsHUwWe2Ky2BNfymIhpn5zbtfv/Px8Jk+eDDgPV69tI93hcDB8+HDGjBlDp06d2LhxIzfffDO//fYbAJdddhlXXnklhw8f5rXXXiMrK4vrrruOLl261Omhw/jUwRH08DSO1qGDpw6OYJ2nnQ53h//ujf8C5+FqqVVnKqU2V3m5Q0RWAIOANTX0Nx74u1IqCUBEHgF2isjkag5zawX8VPlCRC4GNuPckXFUKXVhlbbzlVKZrnbjgaVKqa1V1pElzvPwSgEH0ANIUErtrtJHKc4vCduVUllAVhXnavtTSiWf4nw78KFS6ktX28eBqruaxwP3K6XSXfPnAf8GHq/mbzXf5TAeeAk4LiKPKKXiq2nrMSIyDZgG0CowsCFdnUT6li2Inx+OqChy9u2jrLAQgPzUVEoLCshMTGT644/z/qefEjNqFM8/+yz/+Ne/mPfii4y+/XY+/Oc/CQgJIbhNG37btYslr78OwMSbbnIv38ThoEl4OPmHDuGIiqIoPZ2ywkIioqMpKy4me+9eAkJDKUhNpVmXLhQcOUJ5cTER0dFkJiYSFBGBX2AghWlpNO/WjbzkZFRFBeHdupG1Zw/BrvPeizIyaNGjB9n79p2UKaRtWypKSynOzHT36R8URGhkJLlJSYS2a0dZQQEnsrPd8ysz5SUnE9ahAyXZ2ZTk5bnnV5upuNiduWl4uNaZgtu04fjOne7/J50zBbVqRVpCwmnvPR0zlRUXk7V7d43jSadMVcdLbZ8RZyuTjTH1+xyr35XjIF8pRk+bxrYdO7h74kQeuvNO0rdsqfF9/PqTT+Ln748jKoqMXbu4eswYDqamsmbxYu558EFG3nIL2xITeeovf2HCjTfyt6VLWRwfz4msLN59//1aP28cUVGkJSR4ZWx6+nlTVlxMfmqqNfX7LGYqLykhY9u2xv9OUo9MAcHB5KWkeL0u1JYJEdISEmzx3qsrU1pCgi3eezVlqlp/vf3eqy1TWXExuQcOnJap3iilvP4AknHuCe/Ef/c8T8C5E0EBUa52A4FNQAaQAxQDy1zzolxtA6r0uxu4tcrrIFebdtU4vAPEVzP9BiC5ymsFdKvy+mNg5inL/AZc5Xr+ALAFOAa8BjRzTb8UeB9nYf0CuMKT/k6Z/i/gf0+ZdhS4wfW8CIiuMq8HUOLB/0cwMBMoB3pWyd21Sps44GnX88HA4br67RwUpN7u1cuSx6mMGDFCAerJJ590T4uOjlaAWrp0qVJKqY0bNypAhYWFnbTswoULFaD69+9/Wr818dsPP3jc1u6YLPbEZLEn3s4C/KRsULcrH6Z+n7v1WymlkpOTVffu3RWgHnnkkdPer9nZ2Wr37t3qwIEDSimlCgoKVGpqqnv+iRMnVKdOnRSgVq5cqZRSKjQ0VAFq48aNSimlli5dqgDVu3fv0/o/FW+PT0/QwVEpPTyNo3Xo4KmDo1I1e9a3ftvpcHeUUik4L0BzC/BeNU2WA2uBDkqp5jiLXOVhXaqa9kdwfnGopCNQBqRV03YDcJOI1H7FsNPXddI6XMu3xPUrglJqoVKqP9AL52Fzf3RN/1EpNQJog/OXhP940t8pHAU6VGkb4mpbrRvO/EfqDKdUkVLqHzi/gPRyTS7k5AsBnVdXP43B66+/TkxMDFu3bgVgzZo1xMTEsGbNGq666ioAHn74YaZPn86UKVMAuPrqq93LK6VYuHAhAHPmzPF4vQEhjXZNpLOOyWJPTBZ74ktZrMTU77r7OwWfqN9XXnkle/fupWPHjhQWFjJnzhzmzJlDQkICAKtXr6Znz56MHOk8syE9PZ3OnTszbNgw7r33Xi699FJSUlJo27YtQ4YMAXDX7ilTpjB9+nQefvhh4OTaXRM6jE8dHEEPT+NoHTp46uAI1nnaaiPdxT3A9ar6c8scQKZSqlhELgPGVZmXAVTgPHetkhXAH0Sks4iEAX8D3lHVX9H1TZxFc7WI9BYRfxEJwnnF1NpYAUwWkYtdF3X5G/CDUipZRC4VkYEiEojzfLxioEKct0sZLyLNlVKlQK7Lvdb+qln3KmC4iFwtIk2Apzj5/3QF8BcRaS3O2+M8wennCQIgInNEZLCIBItIgIhMwvn33uZq8jMwzvV3GYrzMEWv8/XXXxMfH8+hQ4cA2L59O/Hx8fz888+88MILzJw5k6CgIOLi4igqKmLixInExcW5l1+3bh379+/n/PPPZ8yYMR6vN7hNG6ujeA2TxZ6YLPbEl7KcBUz9Psfq95Ejzv0GBw8e5OWXX3Y/du3aVW37li1bMnHiRPbu3Ut8fDxpaWmMHDmSDRs20KqV8y5+cXFxTJgwgaKiIuLi4mjatCmzZs3if//3f+v00WF86uAIengaR+vQwVMHR7DO027npKOU+rWW2TOAF0VkEc5DzP6D8yI0KKUKReQZ4BtXUR0KLMV5QZYvcR4qtx64v4b1FovIdcA8YB3Oc9yO4TzP7Y5afD93nUv2LtAC+BbnRXMAmuE8P6wLzgK/HqisMhOARa6L7PyC81yyuvo7dd2JIjIT5y8UocDfgcNVmjztctjhev3/XNOqoxB4EeiK85eGvcAo5TofEJgNxOM8jG4NNZ9H2KjExcWdtNF9KosWLWLRopquNQTDhw+vPPyvXuQlJxOiyYdFXZgs9sRksSe+lMVqTP0+9+p3XfUzJiaGmJgY92uHw8HixYtrXeb888/nzTffrLVNTegwPnVwBD08jaN16OCpgyNY5ylnsoFiMJwJl/Ttq7Zu3+5tDUsoOHqUUA9uMaMDJos9MVnsibeziMgWpVRdvxAbDJaiS/329vj0BB0cQQ9P42gdOnjq4Ag1e9a3ftvxcHeDj6LKy72tYBklmtwGwhNMFntistgTX8piMHiKLvVbh/GpgyPo4WkcrUMHTx0cwTpPs5FuaDQqNCnynlCSl+dtBcswWeyJyWJPfCmLweAputRvHcanDo6gh6dxtA4dPHVwBOs8zUa6odEICA72toJlRERHe1vBMkwWe2Ky2BNfymIweIou9VuH8amDI+jhaRytQwdPHRzBOk+zkW5oNMqKirytYBmZiYneVrAMk8WemCz2xJeyGAyeokv91mF86uAIengaR+vQwVMHR7DO02ykGxoNP39/bytYRhOHw9sKlmGy2BOTxZ74UhaDwVN0qd86jE8dHEEPT+NoHTp46uAI1nmajXRDoyGaFHlPaBIe7m0FyzBZ7InJYk98KYvB4Cm61G8dxqcOjqCHp3G0Dh08dXAE6zzNRrqh0SgvKfG2gmXkHzrkbQXLMFnsicliT3wpi8HgKbrUbx3Gpw6OoIencbQOHTx1cATrPM1GuqHR8G/a1NsKluGIivK2gmWYLPbEZLEnvpTFYPAUXeq3DuNTB0fQw9M4WocOnjo4gnWeZiPd0GhUlJZ6W8EyitLTva1gGSaLPTFZ7IkvZTEYPEWX+q3D+NTBEfTwNI7WoYOnDo5gnafZSDc0GqqiokHLL1iwgIsuugh/f39EhNjY2NPaHD9+nMjISESE8CrnhOzevZuBAwcSHh5O06ZN6dSpE7Nnz6a4uPiMXMoKC880hu0wWeyJyWJPfCmLweAp1dXvKVOm0LNnT8LCwmjZsiW33HILO3furLWf4uJi7r//ftq0aUNwcDBXXXUVP/zwg3v+9u3bGTJkCA6HAxEhqp6/SOkwPnVwBD08jaN16OCpgyNY5xlgSS8+gIj8C0hVSv3Vgr46AruA5kqp8gbLWYCIRAEHgEClVNlZ6D8ZmKKU+rymNnnJySw/w3sHjktMZMuWLURERNChQwdSUlKqbTd9+nQyMjJOm378+HECAgIYPXo0xcXFvPvuuyxcuJDw8HDmzZtXbx9d7tXoCSaLPTFZ7IkvZfEVTP1ucP/J1LN+j0tMZMmSJVx++eVcffXVfP7553z88cfs2LGD/fv3ExQUVG0/c+bM4d///je9e/dmyJAhvPPOO9x4440kJSXRqlUrDh48yG+//Ua/fv346quv6p1Fh/GpgyPo4WkcrUMHTx0cwdwnvV6ISLKIFIlInohki8i3InKviLjzK6Xu9aTAu/q6obY2SqmDSqmwygIvIptFZIoF/vlVHpFn2p+uLFu2jM2bN3PxxRdXOz8+Pp7Vq1fz2GOPnTbv6quv5ptvvmHx4sUsW7aMKVOc/x0HDhw4Ixdd7tXoCSaLPTFZ7IkvZdEBU7/ty08//cR3333H4sWL2bRpEwCpqans2rWr2vbp6eksXboUPz8/NmzYwIoVKxg/fjx5eXksWrQIgNtuu43ExEQefPDBM3LSYXzq4Ah6eBpH69DBUwdHMPdJPxNuU0o5gE7As8CfgSVWr0REztbRCbe5vjhUPo6cpfWcxlnMZBkpKSk88MADzJ07l8GDB1fbJjMzkzlz5jBhwgRef/11wsPDue+++85ofU01uQ2EJ5gs9sRksSe+lEUjTP0+Q85m/e7fv7/7eYnr6u/+/v6cf/751bZPTEyktLSUjh070qZNGwAGDBgAwM8//2yJkw7jUwdH0MPTOFqHDp46OIJ1nufSRjoASqkcpdRaYAwwSUR6A4hInIg87XreSkQ+dO21zxSRr0TET0SWAR2BD1x7w/8kIlEiokTkHhE5CGysMi1ARJ4BrgEWuZZZ5FrHlSLyo4jkuP69sr5ZRKS5iCwRkaMikioiT4uIv2uev4i8ICLHRCQJuLUey8aIyDci8pKIHAdiReQCEdkoIsddfb4tIrYYLRUVFUycOJHOnTvz9NNP19guNzeXl19+mbfeeouioiIuv/xyOnbseEbrDAgNPVNd22Gy2BOTxZ74UhbdMPXbo2UbvX7n5+czefJkAB588MEaN9LT0tIACAsLc08LdY2n3377zRIXHcanDo6gh6dxtA4dPHVwBOs8z7mN9EqUUgnAYZwF+FTmuua1BtoCjzoXUROAg/x3r/jzVZYZBPQEbj5lPY8BXwGzXMvMEpEIYB2wEGgJ/B1YJyIt6xkjDigDugL9gJuAysPypgLDXdMHALfXY1mAgUCSK/8zgADzgUhXzg5AbD19zwqHDh3iyy+/RCnF73//ex555BEACgoKGD58OOmuqyxGRUWhlCI9PZ3JkyfzySefEBMTc0brLEhNtUrf65gs9sRksSe+lEVXTP22T/3OyMjguuuu49tvv2Xq1Kk899xzNbZt27Yt4Nyor6Ty+XnnnWeFjhbjUwdH0MPTOFqHDp46OIJ1nrY/jPkscwSIqGZ6KXA+0EkptR9nka6LWKVUAYCI1NX2VmCfUmqZ6/UKEXkAuA1n8a2ONSJSecGYzcB04BYgXClVBBSIyEvANODfwB3AAqXUIZfTfGCw63nbOpYFOKKUesX1vAzY73oAZIjI34En6woqItNc/dIqMLCu5jWS6zp3vCgjg4oy55+h4OhRirOySN+2DYAdO3awY8cO9zJlZWWsW7eOlG+/pbxnT4JFOJGdTUR0NJd17swbwC979pCWkEBYhw6UZGdTkpdHRHQ0mYmJNHE4aBIeTv6hQziioihKT6essJCI6GhO5OSQvXcvAaGhFKSm0qxLFwqOHKG8uNi9fFBEBH6BgRSmpdG8WzfykpNRFRWEd+tG1p49BLdu7c7UokcPsvftQ/z8cERFkbNvHyFt21JRWkpxZqa7T/+gIEIjI8lNSiK0XTvKCgrcmTITEwkICSG4TRvykpM9znQiJ4fSggIyExNpGh6udabAZs04vnOn+/9J50wBYWGkJSSc9t7TMdOJnByydu+ucTzplKnqeKntM+JsZTK4MfXbi/U7LSGBPIeDoUOH8uvBg8ydMYM/TprEiexs9/tY2rThl+++o/n559OpfXtaFxcTGBjIwYMHSfz8cy7o35+vPvkEgAs7dCAtIcE9NnKTkwEoLykhPzXV48+b4PPOIy0hwStj09PPmxM5OfXK5Ml3krORqSQvj4xt2xr9O0l9MuHnR15KitfrQm2ZyktKTnpv27XWBTZrdkbfhxszU9X66+33Xm2ZTuTknLTdcsb1Wynl8w8gGbihmumHgPtcz+OAp13PHcCLOPdEJwEP19QXEAUonFddPXVagOv1ZpxXTq2c/2fg/53ishJ4zFN/4DKgAsiu8sgFEl3z9wC3Vml/YaWTB8vGAN+csr62LsdUV9t84FBdf+Oqj85BQertXr3O6KGUUosXL1aTJk1SHTp0UIDq27evmjRpklq9erWqyqZNmxSgmjdv7p4WExOjLrvsMnXPPfeou+66SzVr1kwBaurUqepMyNi+/YyWsyMmiz0xWeyJt7MAPykb1NXGepj6bc/6rZRSkZGRClAdO3ZUs2fPdj9++OEHpZRSb7zxhrtWVzJ16lQFqOjoaDVmzBglIiosLEylp6crpZTavXu3mjRpkrruuusUoEJDQ9WkSZPU3LlzlSd4e3x6gg6OSunhaRytQwdPHRyVqtmzvvX7/7N37uFRVecefr+EkDskXAsIRAoWJSoqigpWlCPaUy9pbbXiLShHLcVqtQr2VKWt9ULRAmJtFVNSL9RbQaw3VKSnKBoFQR1AgpgYEhISkkDuCWSdP2ZIAyQwgZWZvYbvfZ55mJm199rvL8zKlzX7dsTuSReRU4EBwIp924wxVfgPmbs9cM7bMhH52BjzLv5C2Rbtvd9WWxH+C+C0ZhDwZjDuAQqABqCXafuWLFvxH9LWuv9g14X9ne8PvHe8MaZcRDKAeR3wPWxWrFhBdnZ2y+u1a9eydu1a0tLSyMjIOOC6Z5xxBjk5OSxcuBARYeDAgdxyyy1tXgk+GHYf4v3VvYhm8SaaxZtEUhZX0frtjfpdVOS//t0333zDnDlzWt4fOXIkp512WpvrzJkzh5iYGF544QU2bdrE6aefzsMPP0zvwJ604uLivep8TU0N2dnZDB48mFmzZh3UyYXx6YIjuOGpjvZwwdMFR7DnecSdky4i3UTkQvzfKj9jjPm8jWUuFJGh4j/ubQewG/831wAlwJAObnbfdV4HjhGRiYGL01wOHAf8M9gOjTFbgaXAw4FMUYGLw5wdWOQF4OcicpSIpALTO7BuWyTj//Z9h4gMAO4I1tUWCxYsaPObphkzZuy13Lhx4zDGUFlZ2fLeDTfcgM/no6amhurqatavX89vf/tbYmNjD8nFlXs1BoNm8SaaxZtEUhbX0Prtrfrd3t6fPdd6yczMxBiz15Xb4+PjeeyxxygtLaW+vp4PPviAM844o6V9T/3e95EXOPz9YLgwPl1wBDc81dEeLni64Ah6n/RD4VURqcL/LfT/4r/Yy6R2lh0GvIO/qK0E/mSMeS/Q9gDw68CVY38Z5LbnAD8SkQoRmWuM2Y7/ojC3A9uBO4ELjTFlHcx0DdAVWAdUAC/hPxcP4EngLWAtsBr4RwfWbYvfACfj/6PntTb6O6Jw5V6NwaBZvIlm8SaRlMUhtH4Hv25bHDH124Xx6YIjuOGpjvZwwdMFR7DnKf5D5BWl8znp+OPNp5/vt+PDSXZs2kT3oUPDrWEFzeJNNIs3CXcWEVlljBkVNgHliMSV+h3u8RkMLjiCG57qaA8XPF1whPY9O1q/j6Q96UqYCeKquc4QdRhXqvcamsWbaBZvEklZFCVYXKnfLoxPFxzBDU91tIcLni44gj1PnaQrIWN3U1O4FaxRW1ISbgVraBZvolm8SSRlUZRgcaV+uzA+XXAENzzV0R4ueLrgCPY8dZKuhIwucXHhVrBG92HDwq1gDc3iTTSLN4mkLIoSLK7UbxfGpwuO4IanOtrDBU8XHMGep07SlZCxu6Eh3ArWqArySrMuoFm8iWbxJpGURVGCxZX67cL4dMER3PBUR3u44OmCI9jz1Em6ohwCprn54As5gmbxJprFm0RSFkWJNFwYny44ghue6mgPFzxdcAR7njpJV0JG9CHek9yLpDhyyE0waBZvolm8SSRlUZRgcaV+uzA+XXAENzzV0R4ueLrgCPY8dZKuhIxd9fXhVrBGxYYN4VawhmbxJprFm0RSFkUJFlfqtwvj0wVHcMNTHe3hgqcLjmDPUyfpSsiI6tIl3ArWiO/dO9wK1tAs3kSzeJNIyqIoweJK/XZhfLrgCG54qqM9XPB0wRHseeokXVEURVEURVEURVE8ghtfjSpWEZErgWuNMRNCud0dmzbx3IgRodwkE30+Jk+ezPvvv09BQQGxsbGMHj2amTNnkp6eDkBDQwN33nknixYtoqSkhJ49ezJhwgQeeeQRevToAYCI7Nf3z372M+bNmxfSPJ1BXWkp3Y4+OtwaVtAs3kSzKIodvFK/J/p8zJ49m6ysLHw+H83Nzdx7773MmDGj3T7WrVvHtGnTWLlyJQ0NDYwfP545c+YwePBgANauXcttt91GTk4O1dXVDB48mLwOXiXZhfHpgiO44amO9nDB0wVHsOepk3QPISJ5QF9gN1ANvAlMNcZU29yOMeZZ4FmbfXqZp556itNPP52xY8fyzjvv8MYbb/DZZ5+xadMm4uLieOCBB5g7dy6pqalce+21vPHGG2RnZ2OMITs7u6WfAQMG4Hzr3AAAIABJREFU8KMf/QiA3Y2NjDvnnHBFskrq8OHhVrCGZvEmmkWJdI7E+r1q1Sp69OjBwIEDyc/PP+CylZWVnHfeeRQVFXHhhRfStWtX/vGPf7Bp0yY+++wzoqKi+OabbyguLuakk07i3//+9yE5uTA+XXAENzzV0R4ueLrgCPY89XB373GRMSYJGAmcBNzVkZVFRL942YdPPvmElStX8uSTT/Lee+8BUFhYyLp16wD46quvALjuuut44oknmDZtGsB+3+APHTqU2bNnM3v2bO6+/nouvfTS0IXoRCpzc8OtYA3N4k00i3KEcETV76effprly5czcuTIgy77/vvvU1RURFpaGq+++iovv/wyJ554Ij6fj0WLFgFw0UUX4fP5uO222w7ZyYXx6YIjuOGpjvZwwdMFR7DnqZN0j2KMKQbewl/sEZGLRcQnIpUislxEjt2zrIjkicg0EfkMqBGRLiIyXUS+EpEqEVknIj9otXymiKxo9dqIyBQRyQ0s/zsR+baIfCAiO0XkBRHpGlg2VUT+KSKlIlIReH5UyH4wh8App5zS8ryxsRGA6Oho+vXrB8BNN91EcnIyWVlZ3HjjjTz00EMkJCRwxx137NXPRx99REJCAv369eNn99zD1q1bQxeiE5GoyPk1oFm8iWZRjiS0fu9PXFwcANu3b2fz5s1s2bKFoqIiwH+Yuy1cGJ8uOIIbnupoDxc8XXAEe55upD0CCRTO7wGbROQYYCFwK9AbeB14dU/hDXAF8H0gxRizC/gKOAvoDvwGeEZE+h1gk+cDpwCnA3cCTwBXAQOB9ED/4P/M/BUYDAwC6gAnTsyurq5m0qRJANx2220tk/TjjjuOCRMmUFFRwRNPPMGWLVsYPXp0yznrAP369SMjI4Mrr7wSgJdefz1i9qQnp6WFW8EamsWbaBblSELr9/6cffbZjBkzhqqqKr797W8zcOBASktLASguLra2HRfGpwuO4IanOtrDBU8XHMGep1OHVh0hLBYRAyQBy4B7gZuB14wxbwOIyCzgFuBMYHlgvbnGmII9nRhjXmzV5/MichdwGvBKO9udaYzZCfhE5AtgqTFmc2B7b+A/dC/bGLMdeHnPSiLye+C99sKIyA3ADQC9YmKC+gHYpK6sjJ2bN1MbF8elV17Jp198wfWZmdx26aVs/+IL4vv0IfPKK1nyzjtcf8UV/Pqmm3juX//if++5h0svvpj/e+stqgsKyP30U+pLS9lVW8stU6Zw/Mkns3LlSjatXk3yrl10GzKEmqIidtfX02PECMp9PuJ69CAqJobakhK6DxtGVV4eprmZlGHDqNiwoeUWDXWlpaQOH05lbi4SFUVyWho7cnNJ6NuX5qYm6svLW/qMjosjsX9/dm7eTOKAAeyqqaGhsrKlvUtCAvF9+lCVl0fSwIE0VlbSWFXV0t41OZmuKSlUFxSQnJZG3bZtlK5ezbcvvZRyn4/YlBS6JCZSU1joZKaGigp/H7W1Le2uZtqZl0dcz54t/08uZ8p79VX6nnrqfp89FzOVfPxxy3hpazx1dibF0xwx9bskJ6flc9xUUwNAdWEh9RUV7X6O/z5zJu+uW8enH3zAUf368cnGjTz/0kt079qVHZs2tYzNPZ9z09xMSU5Oh37f7Kqro0t8fFjGZrC/b/Jff52jxo+3Ur87M1Pea6/Rc8SIkP9N0pFM1YWF9Dn55LDXhQNlKnzvPbodfbQnPnsHylRTWEhsaqonPnvtZdr6wQct9Tfcn70DZcp79VX6n3XWfpk6ihhjOryS0jkELjwz2RjzjoicDTwHnA3cDlQbY+5oteyHwKPGmGcD6/3Pnj8CAu3XALcBaYG3koAbjTFPiUhmYDtjA8saYJgxZlPg9QpgvjFmQeD1fcC3jDGTRSQB+CNwAZAa6DsZ6GKM2X2gfEPi4819Q4Yc0s/mUJno85Gfn8+ECRPYuHEjd911F/fff/9ey6Snp+Pz+cjKymLSpEm89957nHvuuSQlJVFVVUVRUREpKSkkJCQA8OWXXzI8cFGI4uJi+vbtG9JMtqnKzyc5cHVd19Es3kSz2ENEVhljRoVNQGmTI61+T/T5Wp5nZGTwyiuv7HV19x07drB161bi4uJIC+xVamxspGtX/wEEpaWlHHfccZSVlbFs2TLOaXUh1sWLF/ODH/zgkK7uHu7xGQwuOIIbnupoDxc8XXCE9j07Wr91T7pHMcb8S0QWALOAVcDxe9rEfz+wgUBh61VatQ8GngTGAyuNMbtFZA2w/33EOs7twHeA0caYYhEZCXxqqe9O4cwzz6SoqIhBgwZRW1vLrbfeCsDEiRM57bTTGDNmDD6fj+nTp/Phhx/yzjvvADB27FgAli5dyu233865555LSkoK//znPwEYP3688xN0gOampnArWEOzeBPNohxJHCn1e/78+axYsYLVq1cD/sl1Xl4eGRkZVFZWMmnSJE488UTWrFkDwIQJE+jZsycpKSm88cYblJWV8f3vf79lgr5hwwYefPBBvvnmGwDKysrIzMykV69ezJo1KygnF8anC47ghqc62sMFTxccwZ6nTtK9zWwgD/8hc9NFZDzwf/gPlWsAPmhnvUT8Rb8UQEQm4T8vzQbJ+M9jqxSRHgE3T7Pn4jTffPMNc+bMaXl/5MiRnHbaacyaNYuYmBheffVVFixYQM+ePbnmmmuYOXMmAKNGjeK73/0u77//Ptu3b6dfv35cf9llzHz88bDksU19eTndwy1hCc3iTTSLcgQS8fV7xYoVe92mdO3ataxdu5a0tLSWveetOeGEE3j++ecpLy+nX79+TJs2ba/7qhcXF+/VX01NDdnZ2QwePDjoSboL49MFR3DDUx3t4YKnC45gz1Mn6R7GGFMqIn8D7sF/EZhHgQHAGvy3emlsZ711IvIwsBJoBv4GvG9Jazb+w/jKgCLgYSDDUt+dwsFO6UhOTmbevHnMm9f29XPS09NbbhGzh6aaGmISE605hpMeI0aEW8EamsWbaBblSONIqN8LFixgwYIF7bZnZmbu9Xru3LnMnTu33eXHjRt30Hp9MFwYny44ghue6mgPFzxdcAR7nnpOuhIyTjz2WLN2/fpwa1ihJCeHvqedFm4NK2gWb6JZvEm4s+g56Uo4cKV+h3t8BoMLjuCGpzrawwVPFxyhfc+O1m+9BZsSMly5v2EwRAfu+RoJaBZvolm8SSRlUZRgcaV+uzA+XXAENzzV0R4ueLrgCPY83fitq0QEUWG4BVtnkdi/f7gVrKFZvIlm8SaRlEVRgsWV+u3C+HTBEdzwVEd7uODpgiPY89RJuhIydjc0hFvBGjs3bw63gjU0izfRLN4kkrIoSrC4Ur9dGJ8uOIIbnupoDxc8XXAEe546SVdCRnTg/qiRQOKAAeFWsIZm8SaaxZtEUhZFCRZX6rcL49MFR3DDUx3t4YKnC45gz1Mn6UrIMLt3h1vBGrtqasKtYA3N4k00izeJpCyKEiyu1G8XxqcLjuCGpzrawwVPFxzBnqdO0pWQ0exIkQ+GhsrKcCtYQ7N4E83iTSIpi6IEiyv124Xx6YIjuOGpjvZwwdMFR7DnqZN0JWR0iY8Pt4I1XLlXYzBoFm+iWbxJJGVRlGBxpX67MD5dcAQ3PNXRHi54uuAI9jx1kq6EjF11deFWsEa5zxduBWtoFm+iWbxJJGVRlGBxpX67MD5dcAQ3PNXRHi54uuAI9jx1kq6EDFfusxoMXRISwq1gDc3iTTSLN4mkLIoSLK7UbxfGpwuO4IanOtrDBU8XHMGepxu/dZWIwJX7rAZDfJ8+h7zuokWLOPXUU4mPj6d79+6MHTuWiooKnnvuOc466yx69+5NQkIC6enpPPXUU3utO2nSJNLS0hARRITly5cfZpLDy+I1NIs30SyK4jb71u/Zs2dzwgknEB0djYgwY8aMA65/7bXXMmDAAGJjY+nVqxcXXHABn3766X7Lbdq0iaSkJESEkSNHdtjThfHpgiO44amO9nDB0wVHsOfZxUovSsQgIj7gZ8aY5bb7rvzyS55z5HwS20wMHPqycOFCJk6cSGxsLBkZGSQlJZGTk0NtbS1Lly4lLy+P888/n23btvH2228zefJk+vTpw0UXXQTAypUrOf7449m6dSuNjY1W3Kry8khw5BffwdAs3kSzKErnE6r6PdHnY9WqVfTo0YOBAweSn59/0PXz8/M5++yz6d69O8uWLeOtt95i/fr1e627a9currrqKhoO457sLoxPFxzBDU91tIcLni44gj1PnaSHGBGpbvUyAWgA9lw29UZjzLMhdFkAbDHG/HrPe8aYI3MWHQKMMUybNg2AN998k3Hjxu3Vfuutt/LUU08RHR0NwLhx4/jXv/7F22+/3TJJ37BhAwApKSnWJulJAwda6ccLaBZvolmUSEDr9394+umnAcjIyAhqkt76qK/Vq1dzyimnsGXLFpqamogJ7KX//e9/z2effcbtt9/OQw89dEheLoxPFxzBDU91tIcLni44gj1PPdw9xBhjkvY8gG+Ai1q9F7ICr4Se3NxcCgoKiI+PZ+bMmSQlJTF06FAee+wxAEaOHNkyQQdaJuFHHXVUp3o1OnJLi2DQLN5EsyiRgNbvw2PevHlMmTKFK664AoDbb7+9ZYL+8ccfc9999zFr1iyGDx9+yNtwYXy64AhueKqjPVzwdMER7HnqJN0jiEisiMwWkaLAY7aIxLZqv0RE1ojIThH5SkQuCLw/SUTWi0iViGwWkRtbrTNORLaIyO0isk1EtorIpEDbDcCVwJ0iUi0irwbezxOR/wo8nyEiL4jI3wL9+0RkVKv+p4lIYaDtSxEZH5qflpuUlZUBUFdXx+bNm7nssssoLCxk6tSpLF68eK9lH3nkEVauXMnQoUO56aabOtWrsaqqU/sPJZrFm2gWJZLR+h0cL730Eo8//jgbN27kqKOOYsyYMQDU1tZy1VVXcd555zFlypTD2oYL49MFR3DDUx3t4YKnC45gz1Mn6d7hf4HTgZHAicBpwK8BROQ04G/AHUAK8F0gL7DeNuBCoBswCfijiJzcqt9vAd2BAcD1wGMikmqMeQJ4FpgZ2AtwUTteFwN/D2x3CTAv4PQdYCpwqjEmGTi/lZPSBr179255/vTTT5OVlcV1110HwJIlS1raZsyYwe23386QIUN499136datW6d6uXLfyWDQLN5EsygRjtbvIFi+fDl1dXUsXryYoqIifvSjH5Gfn8/HH3/Mxo0bqaio4MILL2T27NkAfP3111x44YUd2oYL49MFR3DDUx3t4YKnC45gz1PPSfcOVwI3G2O2AYjIb4C/AHfjL85Zxpi3A8sW7lnJGPNaqz7+JSJLgbOA1YH3moDfGmN2Aa8Hzqn7DvBhkF4rjDGvB5yeBm4NvL8biAWOE5FSY0xeWysHvvG/AaBXBF3dvaPUV1SQUFFBcmIiVTU1bPf52NmrF407dwIQ37UrxR9/zF1/+AMLXnyR47/zHf7x9NN0b2ykJCeHHiNGUO7zER0XR2L//pjd/tMgqwsK9mrvkpBAfJ8+VOXlkTRwII2VlTRWVbW0d01OpmtKCtUFBSSnpVG3bRulq1fz7UsvpdznIzYlhS6JidQUFtJtyBBqiorYXV/fsn5cjx5ExcRQW1JC92HDqMrLwzQ3kzJsGBUbNhAf+CKirrSU1OHDqczNRaKiSE5LY0duLgl9+9Lc1ER9efl+mXZu3kzigAHsqqmhobLykDI1VFT4+6itbWl3NdPOvDzievZs+X9yOdNXL79M31NP3e+z52Kmko8/bhkvbY2nzs6keJIjqn6XffZZy+e4oaICgIbKSkpycug+bBiFn39OcWkpvY85hu51dZCcTNeYGBrLy0kdPpyT+/QhMSGBqupqPnntNeJ79ADgww/3jrVz505ee+01qgsLg/59s6uuji7x8WEZm8H+vsl//XWOGj/+sGpdKDJtXrKEniNGhKx+H0qm6sJC+px8ctjrwoEyFb73Ht2OPtoTn70DZaopLCQ2NdUTn732Mm394IOW+hvuz96BMm1evJj+Z521X6aOIsaYDq+k2EFE8oDJxph3RKQOGGWM8QXahgOfGWO6isjrwOvGmHlt9PE94F7gGPxHRiQADxlj7haRccAzxpijWi3fepsL2OfCM/u0zwCGGmOuCrSlAV8DMcaYXSIyEZgCjADeAm4zxhS1l3dIfLy5b8iQjv+gIoA9V3e/9957+e1vf8vw4cM544wzWLhwIU1NTbz//vssWbKE+++/n6ioKDIzM0lOTgZg6NChTJ06FYBf/vKXlJWV8dxzz9HU1MT555/Pt771LaZPn37I5/FVrF9P6rHH2gkaZjSLN9Es9hCRVcaYUQdfUulMjuT6PdHnY/78+axYsYJly5ZRUFDAiSeeyMiRI8nIyKCyspJJkyZx4oknsmbNGpYvX87EiRP57ne/S2pqKv/+97/x+Xz07t2b3Nxcunfvvte2FixYsNf6HSHc4zMYXHAENzzV0R4ueLrgCO17drR+6+Hu3qEIGNzq9aDAewAFwLf3XSFwztvLwCygrzEmBXgdkCC3eVjf0BhjnjPGjMXvbYBDuxzrEcTdd9/N9OnTqays5Pnnnyc9PZ0lS5YwevRoCgv9O1iam5vJyspizpw5zJkzh5deeqll/Zdeeons7GyampoAeOutt8jOzqa4uPiQnbqmpBxeKA+hWbyJZlEinCOufq9YsYLs7GwKCgoAWLt2LdnZ2W1Oqvv3788xxxzD22+/zVNPPUVFRQU//vGPWbZs2X4T9MPFhfHpgiO44amO9nDB0wVHsOepk3TvsBD4tYj0FpFewD3AM4G2p4BJIjJeRKJEZEDgm/qu+A9ZKwV2Bb6Vn9CBbZYAh7RrW0S+IyLnBv7QqAfqgOZD6etIokuXLjzwwANs3bqVmpoaPv74Y/77v/8b8O89MMbs92h965q8vLw2l9n3dm4doTrwR1YkoFm8iWZRIpwjrn63V69mzJhBZmYmxpiWCfsxxxzD8uXL2b59O42NjRQWFvLCCy+Qnp7eZt/7rt8RXBifLjiCG57qaA8XPF1wBHueOkn3DvcBnwCfAZ/jPyftPgBjTA6Bi8oAO4B/AYONMVXAz4EXgApgIv6LwwTLU/jPSasUkcUHXXpvYoEHgTKgGOgD3NXBPhQPkJyWFm4Fa2gWb6JZlAhH67dHcGF8uuAIbniqoz1c8HTBEex56jnpSsgYOWKEWRM4N9t1tn/xBT3b2QvgGprFm2gWbxLuLHpOuhIOXKnf4R6fweCCI7jhqY72cMHTBUdo31PPSVc8i2mOnKPhd9XWhlvBGprFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyGjS3x8uBWs4cq9GoNBs3gTzeJNIimLogSLK/XbhfHpgiO44amO9nDB0wVHsOepk3QlZOyqqwu3gjXKHTjsL1g0izfRLN4kkrIoSrC4Ur9dGJ8uOIIbnupoDxc8XXAEe546SVdCRlR0dLgVrBHryG0ggkGzeBPN4k0iKYuiBIsr9duF8emCI7jhqY72cMHTBUew56mTdCVkiCNFPhi6JCaGW8EamsWbaBZvEklZFCVYXKnfLoxPFxzBDU91tIcLni44gj1PnaQrIWN3Y2O4FaxRU1gYbgVraBZvolm8SSRlUZRgcaV+uzA+XXAENzzV0R4ueLrgCPY8dZKuhIzo2NhwK1ij25Ah4VawhmbxJprFm0RSFkUJFlfqtwvj0wVHcMNTHe3hgqcLjmDPUyfpSshobmoKt4I1aoqKwq1gDc3iTTSLN4mkLIoSLK7UbxfGpwuO4IanOtrDBU8XHMGep07SlZDhyn1Wg2F3fX24FayhWbyJZvEmkZRFUYLFlfrtwvh0wRHc8FRHe7jg6YIj2PMUY4yVjhTlYAyJjzf3hfBQlYk+H5MnT+b999+noKCA2NhYRo8ezcyZM0lPTwcgLS2N/Pz8/dY9++yzWb58OWVlZfzwhz/E5/NRVVVF7969Oe+883jod7+j78CBIcvSmTTV1BDjyMU4DoZm8SaaxR4issoYMypsAsoRSev6PdHnY/bs2WRlZeHz+Whububee+9lxowZ7a5/sFrc0NDAnXfeyaJFiygpKaFnz55MmDCBRx55hB49egTtGe7xGQwuOIIbnupoDxc8XXCE9j07Wr91T3oEIyJGRIa2ep0kIh+LyPMd7OcNEbnWvmHn89RTT5GSksIVV1xBt27deOONN7jggguoD3zLdd1113HLLbe0PAYGJt5Dh/p/bLW1tVRXV3PxxRdz9dVXU1dXR3Z2NjffdFPYMtnGlftOBoNm8SaaRVE6jpdr+KpVq+jRo0dLzTwYB6vFDzzwAHPnzqW6upprr72W6OhosrOz+cUvftEhLxfGpwuO4IanOtrDBU8XHMGeZxcrvSgdQkTygL7AbqAaeBOYaoyp7uRN/xG4EzhNRCYbY+YHs5Ix5nudq9V5fPLJJ5xyyikA5OXlcfTRR1NYWMi6des4+eSTueeee1qWLS0t5S9/+QsAP//5zwEYNGgQq1evbllmxIgR3H777WzZti2EKTqXuA7spfA6msWbaBYlktAaDk8//TQAGRkZbR6Nti8Hq8VfffUV4P/ifNasWcybN4+bb76ZvLy8Dnm5MD5dcAQ3PNXRHi54uuAI9jx1kh4+LjLGvCMi3wLeAu4C/rczN2iM+Z/A0/c6czteYs8fBQCNgVvIREdH069fv/2W/fOf/0x9fT3nnnsuJ5xwwl5tt956Kzt37mTx4sXExcUxdfLkzhUPIVExMeFWsIZm8SaaRYlAtIZ3gIPV4ptuuolXXnmFrKwsqqqqeP3110lISOCOO+7o0HZcGJ8uOIIbnupoDxc8XXAEe556uHuYMcYU4y/wIwFE5GIR8YlIpYgsF5Fj9ywrInki8ksR+UxEdojI8yIS16r9DhHZKiJFInJd6+2ISHcR+ZuIlIpIvoj8WkSiAm2ZIrJCRGaJSIWIfC0i32u17nIRmRx4/m0RWSYi20WkTESeFZGUzv0pHT7V1dVMmjQJgNtuu22/SXpjYyOPP/444J+Q78ucOXP461//SkVFBSeeeCJHde/e+dIhorakJNwK1tAs3kSzKJGK1vCO0V4tPu6445gwYQIVFRU88cQTbNmyhdGjR7ecsx4sLoxPFxzBDU91tIcLni44gj1P3ZMeZkTkKOB7wDIROQZYCGQAy4FfAK+KyHHGmMbAKpcBFwD1wPtAJvBnEbkA+CUwHvgaeHKfTT0KdAeGAD2BpcBW4KlA+2ggG+gF3AA8JSIDzP5XFhTgAeD/gG7Ay8AMYP+ZrT/fDYH+6BXib8DKPvuMxP792bxqFddMm8bqtWu56pJLuO+eeyjJyaFLQgLxffpQlZfHqx99xNatWzn6qKM4/5xzKMnJoWtyMl1TUqguKKCmpISSr75i7pNPMvuvf+XaX/6ST08+mS6JidQUFtJtyBBqiorYXV9PjxEjKPf5iOvRg6iYGGpLSug+bBhVeXmY5mZShg2jYsMG4nv3BqCutJTU4cOpzM1FoqJITktjR24uCX370tzURH15eUuf0XFxJPbvz87Nm0kcMIBdNTU0VFa2tLfOlDRwII2VlTRWVbW0t86UnJZG3bZtNFZV0VRTQ7nPR2xKitOZuqamsv2LL9hVW9vS7mqmmG7dKMnJafl/cjlTY1UVFevX7/fZczXTnvHS1njq7EyKt4jkGt5e/S777LOWz3FDRQUADZWVlOTkHPBzXLBxI9fedRerPv2Uq3/wA34zfTolOTkk9O3L9VOmsOj117npf/6HaVddRdY//sHv5szhB9//Pv9eujTosZkwYMB+9dtrv28aq6qoLiy0Ur87M1NTbS2ln34a8r9JOpJJunShKj/fE3WhvUzNu3dTkpPjic/egTJ1TU2lJCfHE5+99jK1rr/h/uwdKFNjVRU7v/56v0wdRa/uHgYC57P1AgyQBCwDLgVuBo43xlwWWC4KKACuNMYsD6z3a2PMM4H2mUA3Y8xNIpIFbDPGTA+0HQN8CQzDX/DrgJHGmHWB9huBK4wx40QkM9Dv0EBbAlAD9DPGFIvIcuCZts5/E5EM4F5jzEkHyx2Oq7vn5+czYcIENm7cyF133cX999/f5rKjRo1i1apVPProo0ydOrXl/aqqKpKTk1ter1y5kjPPPJPo6Gjq6uqIceTQmwNR+umn9D7poP99TqBZvIlmsYde3T38HIk1fN+ru+8hIyODV155Za+ru+/YsYOtW7cSFxdHWloawEFrcXp6Oj6fj6ysLCZNmsR7773HueeeS1JSElVVVQdS24twj89gcMER3PBUR3u44OmCI7Tv2dH6rXvSw0dG4Hy2s4Hn8Bf8/kDLFViMMc0iUgAMaLVecavntYF1CPy7qlVb6yu59AJi9nkvv71+jTG1IgL+Pz72QkT6AnOAs4Bk/KdMVBwoaDg588wzKSoqYtCgQdTW1rYcyj5x4kROO+00AP7973+zatUqUlJSyMzM3Gv9hx9+mJdffplTTjmF6Oho/vnPfwIwdtSoiJiggzv3vw0GzeJNNIsSgRzRNXz+/PmsWLGi5cKqixcvJi8vj4yMDCorK5k0aRInnngia9asAQ5ei8eMGYPP52P69Ol8+OGHvPPOOwCMHTu2Q14ujE8XHMENT3W0hwueLjiCPU+dpIcZY8y/RGQBMAt/gT5+T5v4q+xAoDCIrrYGlt3DoFbPy4AmYDCwrlV7MP3uy/349x4cb4wpD3wLP+8Q+gkJRUVFAHzzzTfMmTOn5f2RI0e2TNL3vH/99deTlLT33zQjR45kyZIl/OMf/6CpqYn+/ftzxRVXcFcHbwvjZVKGDQu3gjU0izfRLEqkcqTW8BUrVpCdnd3yeu3ataxdu5a0tLSWveetOVgtnjVrFjExMbz66qssWLCAnj17cs011zBz5swOebkwPl1wBDc81dEeLni64AilS2CXAAAgAElEQVT2PPXCcd5gNnAesAT4voiMF5EY4HagAfggiD5eADJF5LjAoW737mkwxuwOtP9eRJJFZDBwG/DMIbgm47/lzA4RGQB07NKrIcYY0+aj9R7zl156CWMMs2bN2m/9jIwMVq9ezc6dO6mrq+Orr75i9uzZ4MjFK4KhYsOGcCtYQ7N4E82iRDhHXA1fsGBBm7V1xowZZGZmYoxp2YseyHDAWpycnMy8efPIz8+noaGBoqIisrOz6du3b4e8XBifLjiCG57qaA8XPF1wBHueuifdAxhjSkXkb8A9wFX4LxAzAFiD/zYvjQdaP9DHGyIyG/+5cc3Ar4ErWy1yc6DfzfgvWPMkkHUIur8B/gbsADYBT+O/OM5B6T50KBM///wQNuk99lzkIhLQLN5Es3iTSMqi2OFIqOGu1G8XxqcLjuCGpzrawwVPFxzBnqdO0sOAMSatjfd+2urlomDWM8bM2Of1g8CDrd7KatVWgf+Ph7b6XQAs2Oc9afV8XKvnPuAU9ubhtvpVFEVRlEhDa7iiKIrS2ejh7krIaN61K9wK1qgrLQ23gjU0izfRLN4kkrIoSrC4Ur9dGJ8uOIIbnupoDxc8XXAEe546SVdCRpe4uHArWCN1+PBwK1hDs3gTzeJNIimLogSLK/XbhfHpgiO44amO9nDB0wVHsOepk3QlZOxuaAi3gjUqc3PDrWANzeJNNIs3iaQsihIsrtRvF8anC47ghqc62sMFTxccwZ6nTtIV5RCQqMgZOprFm2gWbxJJWRQl0nBhfLrgCG54qqM9XPB0wRHsebqRVokIomNjw61gjeQ27gPrKprFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyFjV319uBWsscORQ26CQbN4E83iTSIpi6IEiyv124Xx6YIjuOGpjvZwwdMFR7DnqZN0JWREx8SEW8EaCX37hlvBGprFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyHDGBNuBWs0NzWFW8EamsWbaBZvEklZFCVYXKnfLoxPFxzBDU91tIcLni44gj1PnaQrIcOV+6wGQ315ebgVrKFZvIlm8SaRlEVRgsWV+u3C+HTBEdzwVEd7uODpgiPY89RJeiciIheLyEci0rWd9moRGRJqr3BRlZfHcyNG7PfYw7hx4xCRvR7p6ekAlJeXk5mZSf/+/YmNjWXQoEHccsstNITptjA9Wnm7jmbxJprFm0RSFuXAaA3/D1V5eS3P6+vrufnmm+nTpw/x8fGMGTOGjz766IDrL1q0iFNPPZX4+Hi6d+/O2LFjqaioAOCFF17guOOOIykpicTEREaMGMGf/vSnQ/J0YXy64AhueKqjPVzwdMER7HnqJB0QkTwRqQsU3D2PeYfZZ0/gfuDHxpjGtpYxxiQZYzYHll8gIvcdxvZGiMhSESkXkUoRWSUi/32o/bXqN01EjIh0Ody+guWWW25peVx99dUA3HbbbWRnZxMdHU1mZibV1dXMnTuX+++/P1Rae1Hu84Vlu52BZvEmmsWbRFKWSEFr+AH7tV7Db731VubNm0ffvn3JyMhg5cqVnHfeeZSVlbW5/MKFC/nhD3/I559/ziWXXMKPf/xjdu7cSW1tLQD5+fkMHjyYq6++mnPOOYd169bxs5/9jPfee6/Dbi6MTxccwQ1PdbSHC54uOII9z5BNvBzgImPMOxb7GwHcYIz5Zt8GEelijLF97NirwOPAhYHXpwJieRshYfbs2fu999VXXwEwbdo0pk6dSnJyMg8//DB5rb7dDyXRcXFh2W5noFm8iWbxJpGUJcLQGh4Ctm3bRlZWFlFRUbz77rv06dOHLl268MwzzzBv3jxmzJix1/LGGKZNmwbAm2++ybhx4/br84477uCOO+5oeX3CCSfw+eef8/XXX3POOed0yM+F8emCI7jhqY72cMHTBUew56l70g+CiAwVkX+JyA4RKROR51u1GRH5uYhsDrT9QUT2/EyHADP3WfZnIpIL5LZ6b6iI3ABcCdwZ2APwaqD9WBFZHvhW3SciF7fj2As4GnjSGNMYeLxvjFkRaE8VkX+KSKmIVASeH9Vq/eUi8jsReV9EqgLf5vcKNP9f4N/KgNsZIhIlIr8WkXwR2SYifxOR7hZ+3ACkpqaSkpLC+PHj+fjjjwH/3vWYmBgeeughbrzxRrKysujZsydTp061tdkOkdi/f1i22xloFm+iWbxJJGU5EtAabreG+3w+mpqaGDRoEH369AFg1KhRAKxZs2a/5XNzcykoKCA+Pp6ZM2eSlJTE0KFDeeyxx/ZaLicnh1tuuYULL7yQzz//nGOPPZZLLrkkGKW9cGF8uuAIbniqoz1c8HTBEex56iT94PwOWAqkAkcBj+7T/gNgFHAycAlw3QH6ygBGA8e1ftMY8wTwLDAzcPjcRSISg/+b9aVAH+Bm4FkR+U4b/W4HNgHPiEiGiOx77f8o4K/AYGAQUAfseyjgRGBSYFtdgV8G3v9u4N+UgNtKIDPwOAf/HzJJbfTXYZKTk7nwwgu5/PLLGTx4MMuWLeP888+nuLiY0047jTPPPJMtW7bwxBNPUFFRwTnnnMOQIeE5HXDn5s1h2W5noFm8iWbxJpGU5QhBa7gfKzW8pKQEgKSkpJb3EhMTASguLt5v+T2HwNfV1bF582Yuu+wyCgsLmTp1KosXL25Zbt26dcydO5fXXnuNqKgoLrjgApKTk4NR2gsXxqcLjuCGpzrawwVPFxzBnqce7v4fFotI68PX7jDGPAk04S+M/Y0xW4AV+6z3kDGmHCgXkdnAFcD8drbxQGDZYDgdf+F80BjTDCwTkX8G+p/RekFjjBGRc4DpwMPA0SKyArjeGJNrjNkOvLxneRH5PbDvyV5/NcZsDLS/ALT5jX+AK4FHWp2LdxfwhYhM2vcQwMAehhsAerVzn9WSnBzievTg2UcfpW7bNroPG8b23FzOyMigYOtWFj/5JPNffplVa9fyv1OmcMc99/CLm2/mry++SHNTE3/61a9I6NuX5qYm6svL6TFiBOU+H9FxcST278/OzZtJHDCAXTU1NFRWtrR3SUggvk8fqvLySBo4kMbKShqrqlrauyYn0zUlheqCApLT0qjbto1dtbX0GDGCurIyKjdupEtiIjWFhXQbMoSaoiJ219e3rB/XowdRMTHUlpTQfdgwqvLyMM3NpAwbRsWGDcT37g1AXWkpqcOHU5mbi0RFkZyWxo7c3JBlqisro6mmhnKfj9iUFKczRcfFsf2LL1r+n1zOFBUTQ0lOzn6fPRcz1ZWVUbF+fbvjyaVMrcfLgX5HdFYmpV20hluu4fvW75KcHFICh3Hu2L69ZRyUfv01AKmxsdRXVOz1OZaiopaNzp4+nXN/+EOoruavL77Iohdf5Iz+/Uno25cfjB3L+StXUpmQwE8uu4w//vGPdIuL46cZGR36fRObmkpJTk5Yxmawv2/qysqoLiy0+jdJZ2SqLy+n9NNPQ/43SUcyNe/aRVV+ftjrwoEyNdXUUJKT44nP3oEyRcfFUZKT44nPXnuZWtffcH/2DpSprqyMnYHfi4dVv40xR/wDyAP+q522bwFPAkWAD7iuVZsBRrR6/X1gfeB5JrBin2WH7dO3AYYGni8A7mvVdjnw8T7LP4j/cLiD5RkIvAGsDLxOAP4C5AM7Aw8DRAfalwOTW63f4g6kBZbt0qp9PfD9Vq/jAssMOJDX0XFx5tnjjtvvYYwxNTU1prCw0OyhoaHBDB482ADm73//u0lMTDSAWbZsmTHGmKysLAOY9PR0Ew4qvvwyLNvtDDSLN9Es3iTcWYBPjAfqppceWsM7v4YfHRdnjDGmuLjYxMTEmKioKFNcXGyMMWbixIkGMPfcc4+prKw069evN19//bUxxl/Lu3XrZgCTk5NjjDFmypQpBjA333yzMcaYnTt3mtbccMMNBjDXXHON6SjhHp/B4IKjMW54qqM9XPB0wdGY9j07Wr/1cPeDYIwpNsb8jzGmP3Aj8CcRGdpqkYGtng/C/4dAu911oK0IGNjq/Lg9/RcG4VwAPAakB966HfgOMNoY043/HP4WzEVp2nIuwr9norXXLqAkiP7aZNu2bRx99NF873vf46abbuLUU08lPz+fvn37Mn78eMaMGQPA5MmTufHGG5k+fToAY8eOPdRNHhYNlZVh2W5noFm8iWbxJpGU5UhAa7jdGt63b18yMzNpbm5m/Pjx/OQnP2HhwoUkJSUxdepUFi1axLHHHktGRgYAXbt25dZbbwXgmmuu4brrriMrK4vo6GiuvPJKAE455RTOP/98fvrTn3LxxRczf77/QIbzzz8/iHh748L4dMER3PBUR3u44OmCI9jz1En6QRCRH7e6QEsF/oLX3GqROwIXdRkI3AI8v28fQVKC/9ywPXwE1OK/EE2MiIwDLgL+3oZjqoj8JnABm6jABWOuAz4MLJKM/xy2ShHpAdzbAa9S/Hlbuy0EfiEiR4tIEv7b1DxvDuNqtz179uSaa65h48aNZGdnU1JSQkZGBu+++y69evViwYIFXH311dTV1bFgwQJiY2OZOnUqf/jDHw51k4eFK/dqDAbN4k00izeJpCxHAlrD7dfwOXPmMGXKFEpKSli8eDGnn346S5cupXfgkNV9ufvuu5k+fTqVlZU8//zzpKens2TJEkaPHg3Af/3Xf/Hll1+SlZXFihUrGDVqFAsWLGDixIkdiOnHhfHpgiO44amO9nDB0wVHsOjZkd3ukfrAf6hcHVDd6rEo0DYT/zff1cBX+G/J0vpQt58Dm/Ff+OVh/nP4WSb7Hyo3dJ/ttj5UbhiwBqgEFgfeGwH8C9gBrAN+0I5/IpAdyFENFOMvwgMC7f3xHw5XDWzEvzeh5fA3DnCoXOD1b/EX+kr859lFAfcABYH3nwFSD/ZzPtDh7q5R/NFH4VawhmbxJprFm4Q7C3q4u9bwMNTwPYe7e51wj89gcMHRGDc81dEeLni64GhM+54drd/iX0c5FERkzzlqm8Lt4gIjR4wwa3y+cGtYYfsXX9AzPf3gCzqAZvEmmsWbhDuLiKwyxowKm0AEoTU8eFyp3+Een8HggiO44amO9nDB0wVHaN+zo/VbD3dXQkZUO1d3d5H4wP1hIwHN4k00izeJpCyKEiyu1G8XxqcLjuCGpzrawwVPFxzBnqdO0pWQsbuhIdwK1qjKywu3gjU0izfRLN4kkrIoSrC4Ur9dGJ8uOIIbnupoDxc8XXAEe556n/TDwBgTzJVVlQDRXbuGW8EaSQMHHnwhR9As3kSzeJNIynKkozU8eFyp3y6MTxccwQ1PdbSHC54uOII9T92TroQMs3t3uBWs0ejIbSCCQbN4E83iTSIpi6IEiyv124Xx6YIjuOGpjvZwwdMFR7DnqZN0JWQ0O1Lkg6GxqircCtbQLN5Es3iTSMqiKMHiSv12YXy64AhueKqjPVzwdMER7HnqJF0JGV3i48OtYA1X7tUYDJrFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyFjV11duBWsUe7ArWiCRbN4E83iTSIpi6IEiyv124Xx6YIjuOGpjvZwwdMFR7DnqZN0JWRERUeHW8EaXZOTw61gDc3iTTSLN4mkLIoSLK7UbxfGpwuO4IanOtrDBU8XHMGep07SlZAhjhT5YOiakhJuBWtoFm+iWbxJJGVRlGBxpX67MD5dcAQ3PNXRHi54uuAI9jx1kq6EjMqNG3luxIigHgCzZ8/mhBNOIDo6GhFhxowZe/X34osvMmLECGJjY0lLS2PmzJktbTNmzEBE2nzkWbh/YXVBwWH34RU0izfRLN4kkrIoSrBUbtzY8ry+vp6bb76ZPn36EB8fz5gxY/joo48OuP6iRYs49dRTiY+Pp3v37owdO5aKigoAnnvuOc466yx69+5NQkIC6enpPPXUU4fk6cL4dMER3PBUR3u44OmCI9jz1PukKwCIyJ+BQmPM78LtsodVq1bRo0cPBg4cSH5+/l5tK1eu5PLLLycxMZGf/OQnvPvuu0ybNo3u3btz4403cvrpp3PLLbe0LL9hwwbeeustunXrRu/evQ/bLTkt7bD78AqaxZtoFm8SSVmUyCGUNfzWW2/lL3/5C+np6YwfP57nn3+e8847j82bN9OrV6/9ll+4cCETJ04kNjaWjIwMkpKSyMnJoba2ltTUVJYuXUpeXh7nn38+27Zt4+2332by5Mn06dOHiy66qENuLoxPFxzBDU91tIcLni44gj1P3ZPucURkrIh8ICI7RKRcRN4XkVNtb8cYc5OXJugATz/9NMuXL2fkyJH7tT300EMYY5gxYwbZ2dlkZ2cD8MADDwBwwQUXMHv27JZHYmIiANdff33L88Ohbtu2w+7DK2gWb6JZvEkkZVE6n0ir4du2bSMrK4uoqCjeffddFi5cyJVXXklVVRXz5s1ry4tp06YB8Oabb/L3v/+d+fPn89lnnzFgwADAP+nPy8vjmWeeYenSpZx99tkAvP322x32c2F8uuAIbniqoz1c8HTBEex56iTdw4hIN+CfwKNAD2AA8BugoYP9RNwRE59++ikAo0aN2uvf/Px8Kisr91o2Ly+PV155hejoaH7+859b2f6u2lor/XgBzeJNNIs3iaQsSucSiTXc5/PR1NTEoEGD6NOnD/Cf+rtmzZr9ls/NzaWgoID4+HhmzpxJUlISQ4cO5bHHHmtZZuTIkUS3Oue9sbERgKOOOqrDfi6MTxccwQ1PdbSHC54uOII9T52ke5tjAIwxC40xu40xdcaYpcaYzwBE5DoRWS8iFSLylogM3rOiiBgR+ZmI5AK5gffuFJGtIlIkIpMDywwNtC0QkfsCz8eJyBYR+ZWIlIlInohc2arvWBGZJSLfiEiJiPxZREJ6E9WSkhIAkpKSAPbaO15cXLzXso8++ii7d+/mkksuIc3SISiu3KsxGDSLN9Es3iSSsiidTsTV8H1rL/yn/u5bewHKysoAqKurY/PmzVx22WUUFhYydepUFi9evN/yjzzyCCtXrmTo0KHcdNNNwSjthQvj0wVHcMNTHe3hgqcLjmDP0zPfziptshHYLSLZwN+BD40xFQAicgnwK+Ai/AV8OrAQOLPV+hnAaKBORC4AbgPGA18DTxxk298CeuH/5v904HUR+cQY8yXwIPBtYCTQBDwH3APctW8nInIDcANAr5iYoIOXfvopprmZlGHDaAhcXKahooKSnBxShw+nd2oqW4qLKd+6lZKcHBrj4lrW7ZmcTElODtFxcZhu3Zj/hD/q9ZdeSklODj1GjKDc56NLQgLxffpQlZdH0sCBNFZW0lhV1dLeNTmZrikpVBcUkJyWRt22beyqraXHiBF89fLLfOv00+mSmEhNYSHdhgyhpqiI3fX1LevH9ehBVEwMtSUldB82jKq8vJZMFRs2EB84N76utJTU4cOpzM1FoqJITktjR24uCX370tzURH15eUuf0XFxJPbvz87Nm0kcMIBdNTU0VFYeVqbS1av59qWXUu7zEZuS4nSmhooKfx+B/yeXM+3MyyOuZ8/9PnsuZvrq5Zfpe+qp7Y4nlzKVfPxxy3g50O+IzsqkOIXTNXzf+l2Sk0NKoNbu2L6dppoayn0+Sr/+GoDU2FjqKyr2+hxLUVFLf7OnT+fcH/4Qqqv564svsujFFzmjf/+Wsfm7hx7i4fnzGTxgAC/Om0dMYyMlOTkd+n2zq66OLvHxYRmbwf6+yX/9dY4aP95K/e7MTJuXLKHniBEh/5ukI5mqCwvpc/LJYa8LB8pU+N57dDv6aE989g6UqaawkNjUVE989trLtPWDD1rqb7g/ewfKtHnxYvqfddZ+mTqMMUYfHn4AxwILgC3ALmAJ0Bd4A7i+1XJRQC0wOPDaAOe2as8CHmj1emhgmaGB1wuA+wLPxwW2ldhq+ReAuwEBaoBvt2o7A/j6YFmOjoszzx53XFCP1lxyySUGMPfee2/LexdffLEBzMyZM40xxixdutQAZtCgQXutO3fuXAOYU045xdik4ssvrfYXTjSLN9Es3iTcWYBPjAdqkz6OrBp+dFycMcaY4uJiExMTY6KiokxxcbExxpiJEycawNxzzz2msrLSrF+/3nz99dfGGGMaGhpMt27dDGBycnKMMcZMmTLFAObmm282xhize/du89Of/tQA5qSTTjJbt241h0q4x2cwuOBojBue6mgPFzxdcDSmfc+O1m893N3jGGPWG2MyjTFHAelAf2A2MBiYIyKVIlIJlOMvvgNard76HgD993l9sPsDVBhjalq9zg/00RtIAFa12vabgfetMn/+fDIzM1m9ejUAixcvJjMzk8WLF3PnnXciIvzmN7/h2muvJTMzE4Dp06e3rG+MYe7cuYD/wjQ26WLh4nNeQbN4E83iTSIpi9L5RFoN79u3L5mZmTQ3NzN+/Hh+8pOfsHDhQpKSkpg6dSqLFi3i2GOPJSMjA4CuXbu21N9rrrmG6667jqysLKKjo7nySv8R+HfffTePP/44UVFRnHTSSTz44IPceuutbV6I7mC4MD5dcAQ3PNXRHi54uuAI9jx1ku4QxpgN+L8tT8dfoG80xqS0esQbYz5ovUqr51uB1ldhGXiQzaWKSOtP2SCgCCgD6oARrbbb3RiT1GYvh8GKFSvIzs6mIHC/wbVr15Kdnc2aNWsYM2YMCxcuZNCgQSxcuJDo6GgeeOCBvc5he+2119i0aRP9+vXj8ssvt+pWU1hotb9wolm8iWbxJpGURQktkVLD58yZw5QpUygpKWHx4sWcfvrpLF26tN3bm959991Mnz6dyspKnn/+edLT01myZAmjR48GoDAwppqbm8nKymLOnDnMmTOHl156KVilFlwYny44ghue6mgPFzxdcAR7nuLf+654EREZDnwfeN4Ys0VEBuI/r20d8DrwO+ByY4xPRLoDE4wxLwbWNcAwY8ymwOvv4T9c7lz836g/DlyzZxkRWQBsMcb8WkTGAe/g/7b/V/jPiXsTOMUYs0FE5gD9gKnGmG0iMgBIN8a8daA8Q+LjzX1DhgSVfaLPF9wPKUzUlZUR38b9YF1Es3gTzeJNwp1FRFYZY0aFTUAJmkiq4UPi483mujqrP5/OINzjMxhccAQ3PNXRHi54uuAI7Xt2tH7rnnRvU4W/uH4kIjXAh8AXwO3GmEXAQ8DfRWRn4P3vtdeRMeYNYC7wHrAp0Be0fyuYYqAC/zfvzwI3BfYCAEzb00dg2+8A3znUkC5S0+piOK6jWbyJZvEmkZRF6XS0hocYF8anC47ghqc62sMFTxccwZ6nXt3dwxhjCoHLDtD+NPB0O23SxnsPAA8AiMixQDP+Q+gwxmS2sfzvgd+38X49/m/nfxVEjBaS09I8v4c8WHbX14dbwRqaxZtoFm8SSVmUziWSaniypduXdjYujE8XHMENT3W0hwueLjiCPU/dk34EISI/CNwfNRX/N/ivGmN2hWr7XeJDeiv1TsWVezUGg2bxJprFm0RSFsUtwlnDXanfLoxPFxzBDU91tIcLni44gj1PnaQfWdwIbAO+AnYDPw3lxnc5cD5bsJRHyBEBoFm8imbxJpGURXGOsNVwV+q3C+PTBUdww1Md7eGCpwuOYM9TD3c/gjDGXBDkcsvZ+yqyVojqEjkft7gePcKtYA3N4k00izeJpCyKW4SzhrtSv10Yny44ghue6mgPFzxdcAR7nronXQkZIvudYucsUTEx4VawhmbxJprFm0RSFkUJFlfqtwvj0wVHcMNTHe3hgqcLjmDPUyfpSsjY3dQUbgVr1JaUhFvBGprFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyGjS1xcuBWs0X3YsHArWEOzeBPN4k0iKYuiBIsr9duF8emCI7jhqY72cMHTBUew56mTdCVk7G5o73au7lGVlxduBWtoFm+iWbxJJGVRlGBxpX67MD5dcAQ3PNXRHi54uuAI9jx1kq4oh4Bpbg63gjU0izfRLN4kkrIoSqThwvh0wRHc8FRHe7jg6YIj2PPUSboSMqJjY8OtYI0URw65CQbN4k00izeJpCyKEiyu1G8XxqcLjuCGpzrawwVPFxzBnqdO0pWQsau+PtwK1qjYsCHcCtbQLN5Es3iTSMqiKMHiSv12YXy64AhueKqjPVzwdMER7HnqJF0JGa7cZzUY4nv3DreCNTSLN9Es3iSSsihKsLhSv10Yny44ghue6mgPFzxdcAR7njpJVxRFURRFURRFURSPoJN0JWQ079oVbgVr1JWWhlvBGprFm2gWbxJJWRQlWFyp3y6MTxccwQ1PdbSHC54uOII9T52kKyHDlfusBkPq8OHhVrCGZvEmmsWbRFIWRQkWV+q3C+PTBUdww1Md7eGCpwuOYM9TJ+lKyHDlPqvBUJmbG24Fa2gWb6JZvEkkZVGUYHGlfrswPl1wBDc81dEeLni64Aj2PHWSriiHgERFztDRLN5Es3iTSMqiKJGGC+PTBUdww1Md7eGCpwuOYM/TjbRKRODKfVaDITktLdwK1tAs3kSzeJNIyqIoweJK/XZhfLrgCG54qqM9XPB0wRHseeokXQkZrtxnNRh2OHLITTBoFm+iWf6/vXuPtqMs7zj+/YUAUYhKJCIRTEQIhAgooFJFwBte6qXiDQGFuqBdUm0Vq3ZZL+lS493q0uW1apAIaG3xsoouqyWI0FAwChJMAoSASgAhkHtCEp7+8b7bDJtz9tnnZM6eeZPfZ61ZZ+93bs8zM3veefe8e0477Uy5mPWrlPq7hM9nCTFCGXE6xvqUEGcJMUJ9cbqRbgOz2+67Nx1CbR65335Nh1Ab59JOzqWddqZczPpVSv1dwuezhBihjDgdY31KiLOEGKG+ON1It4GJiKZDqM2DW7Y0HUJtnEs7OZd22plyMetXKfV3CZ/PEmKEMuJ0jPUpIc4SYj4bsAUAABKPSURBVIT64nQj3QamlP+z2o9Nq1Y1HUJtnEs7OZd22plyMetXKfV3CZ/PEmKEMuJ0jPUpIc4SYoT64nQj3QZm4iMe0XQItZkye3bTIdTGubSTc2mnnSkXs36VUn+X8PksIUYoI07HWJ8S4iwhRqgvTjfSbWC2btzYdAi1WbV4cdMh1Ma5tJNzaaedKRezfpVSf5fw+SwhRigjTsdYnxLiLCFGqC9ON9JtYEr5/4b92G3SpKZDqI1zaSfn0k47Uy5m/Sql/i7h81lCjFBGnI6xPiXEWUKMUF+cZZx1bacwoZCnw/Zjr2nTmg6hNs6lnZxLO+1MuZj1q5T6u4TPZwkxQhlxOsb6lBBnCTFCfXG6kW4Ds23z5qZDqM2a5cubDqE2zqWdnEs77Uy5mPWrlPq7hM9nCTFCGXE6xvqUEGcJMUJ9caqUf6th5ZO0FljadBw12Re4p+kgauJc2sm5tFPTuUyPiKkNrt92QQXV301/PvtRQoxQRpyOsT4lxFlCjDB8nKOqvyfWF4/ZiJZGxLFNB1EHSdc6l/ZxLu3kXMyKV0T9XcLns4QYoYw4HWN9SoizhBihvjjd3d3MzMzMzMysJdxINzMzMzMzM2sJN9JtkL7adAA1ci7t5FzaybmYla2U476EOEuIEcqI0zHWp4Q4S4gRaorTD44zMzMzMzMzawnfSTczMzMzMzNrCTfSzczMzMzMzFrCjXQbd5KmSLpE0npJt0k6remYepG0QNImSevysLQy7rScw3pJ35c0pTKu0TwlvVXStZI2S5rXNe75kpZI2iDpMknTK+P2lPQNSWsk3SnpvH7nHXQukmZIisq+WSfp/S3PZU9JX8/HxFpJv5H0kn5ials+vXIpdN/Ml7Qyx7RM0tn9xNPGXMzGQ9P12jAxjfk81ECsY7qeGGB867qGbZI+n8c1ti2HuwbI48Z8bh5EjJKOk/TfklZJ+pOkf5e0f2X8HElburbrQQ3EuUN19oBiPL0rvg055mPy+IFty17nnTy+/uMyIjx4GNcBuAj4DrA3cDywGpjddFw94l0AnD1E+WxgLXBCzuVC4OK25AmcAvwV8CVgXqV83xzLa4FJwCeBhZXxHwWuAPYBZgF3Ai/uZ94GcpkBBDBxmPnamMtewJwc+wTgZfk4mlHavhkhlxL3zWxgz/z6sBzTMaXtFw8exmughfX3jpyHGoh1AWO4nmgo1r2BdcAJ+X1j25JxuJ4ZYIwvyfE9Cngk8A3gJ5Xxc4D5LdiWY66zBxXjENOdBdzC9meqDWxbjnDeGZfjciAHiIddd8gH9QPAzErZBcDHmo6tR8zDVapzgQsr75+cc5vcpjyBD3ediP8GuKprn2wEDsvv7wBOroz/EPliYaR5G8hlpEqltbl0xXk98OqS980QuRS9b4BDgZXA63aG/eLBw44ObarX+oi1r/NQA3EtYJTXEw3GeiawnO0NoMa35RDXAGM+Nw8qxiHGHw2srbyfwwAb6T225Zjr7Aa35WXAB5velpX17/C1XK/B3d1tvM0EtkbEskrZdaRvkdvso5LukXSlpJNy2WxS7ABExC3kCxjanWd33OtJ30TOlrQPsH91PA+Ne9h5xznmkdwm6Q+SvilpX4BScpG0H+l4WdwrphLy6cqlo6h9I+mLkjYAS0iN9Et7xdPmXMxq1uZ67c/6PQ81aLTXE005E/hW5FZERZu25Y6cm5tyAg89NgFenrvDL5b0liaCqhhLnT1wufv4CcC3ukY1si1rvJYblhvpNt72BtZ0la0m3X1uq/cABwFPIP2vwx9JejIpl9Vd03ZyaXOeI8VN1/hq3L3mbcI9wNOB6aRuyZOBb+dxrc9F0u6keM+PiCUjxNTqfIbIpch9ExHn5vU8B/hPYPMI8bQ2F7OatbleA0Z9HmrCWK4nBi43gE4Ezq8Ut21bwo6dmwdO0pHAB4B3VYq/S+ryPBU4B/iApDc0EN6O1NlNeBNwRUTcWilrZFvWfC03LDfSbbytI/0up+pRpN9xtFJEXB0RayNic0ScD1wJvJTeubQ5z5Hipmt8Ne5W5RUR6yLi2ojYGhF3AW8FTpY0mZbnImkCqavoA6S4R4qptfkMlUvJ+yYitkXEL4EDgLeMEE+rczGrUauP5TGchwZujNcTTXgj8MtqA6ht2zLbkXPzQEk6GPgx8A8RcUWnPCJujIg7cr1zFfA54DWDjm8H6+wmvImHfonUyLYch2u5YbmRbuNtGTBR0iGVsqN4eNefNgtApJiP6hTmJ0juScqxzXl2x70X6fdviyPiPlIX36Mq01fjHnbecY65X51ueRPanIskAV8H9gNeHRFbRoqprfn0yKVbEfumy8TKeovaL2bjoLX12ljOQwMJbGT9XE804WENoCG0YVvuyLl5YHLPhJ8BH4qIC0aYvHNMNG00dfZASXo2MA343giTjuu2HKdrueE19WN7D7vOAFxMekLsXsCzacHTYXvE+hjgRaSnM04ETgfWk353MpvU9e85OZf5PPTp7o3mmeOdRHqK5AWVHKbmWF6dyz7OQ586+THgctJTJw/LJ5POk6p7zttALs8kPeBrAvBY0lOHL2tzLnndXwYWAnt3lZe4b4bLpah9AzwOOJXUFW23/LlfD7yixP3iwcN4DLS0/h7reWjAMY75emLAcT4rxzW5q7yxbck4XM8MMMYnkH6P/I/DzPfKHJ+AZwB/BM5sYFuOuc4eVIyV8V8lPS+h6W1Z+7Vcz/WNVyIePHQGYArw/VwJ3A6c1nRMPWKdClxD6oZyf/4wvrAy/rScw3rgB8CUtuRJespldA1z8rgXkB6MtZH0tNkZlfn2JP2LkDXAXcB5Xcsddt5B5wK8Abg1b+OVpAeIPL7luUzP8W8idXvqDKeXtm965VLaviF91i8nfc7XAL8Fzuknnrbl4sHDeA20sP7ekfPQgOMc8/XEgOP8CnDBEOWNbUvG6XpmEDECH8yvq8fmusp8FwH35vIlwN83sS1H2r9t2JZ53KT8+Xn+EPMNbFv2Ou+M13HZ+TcLZmZmZmZmZtawtvxGx8zMzMzMzGyX50a6mZmZmZmZWUu4kW5mZmZmZmbWEm6km5mZmZmZmbWEG+lmZmZmZmZmLeFGupmZmZmZmVlLuJFuZmZmZma7PEkLJIWkBZWyyMOcHvOdVZluRg1xrMjLmlfHdFYeN9LNrFiS9pT0Dkn/K2m1pI2SbpL0dUmzmo7PzMzay3WIDeFG4Or8twS/JsV7S6dgUA33ob7QsPpMbDoAM7OxkLQP8HPgabloHXATcCDwZuC3wO+aic7MzNrMdcjoSNojIh5oOo7xFhHnNh3DaETEq5qOwcaH76SbWam+wPaLq08BUyLiyIjYB/gL4DpJx0j6uaSVkjZLWi/pGklnVBck6QxJiyStydMsk3SxpEdXpnmFpCskrZO0SdJ1kt4iSaNZjpmZtcKIdQhACfVI9Y6mpLdJuj33CrhU0gFd0/61pF/l8eslLZT02sr4GZVu2++W9H1JG4BP9Fj/wZLm5230gKQ7JH2lMn6ypM9IujWPXynpy5IeU5lmXl7nirwNVkhaK+mLkiZJmitpVV72B4aLJS/rpEoOb5Z0Wc73akmzJL1Q0g15+ZdKevxQ27LXOkYwS9L/5HUukfSyyvKnS/qxpN/n8RtzLG+vHgcPTUfvl3Rn3l8Xdh1Tf75r3tl3wPQ8+szOdsjT9nssd7bdxyV9QdK9ku6W9DlJEzvTACfmWU5UV1d/STPzcXt33uc3SXqXpAmV9bxY0pWS7svb4VZJl0h60g5s+51HRHjw4MFDUQPwaGALEMBvAA0z3WuAbcAKYBGwKs8TwF/maY4EHsxlNwPXA6vz+wPyNGdU5rsLuLXy/qP9LseDBw8ePDQ/9FuH5GlbX48AC/I0m4ANpK7aneVcXZnufZV13g7cUXn/t3maGZWyzXn9vwU+Ncy6Dwbuy9NvI/U++AOwIo/fA/hVZXnXkXotRC7fPU83rzLNupx/J47FOY7bK2Uv7LE9TqpMtwlYmpcbpG7h63OcnW307SG25YJKWWdZc3qs86zKdBuAZflvAGtIXwIBHJvLfk86nu6qzPd3leWtyGXrgPtzDp3pvjvEdPOA/YGFlVz/lN8v7PdY7sr3AeDevD87ZefkaRbmvDr5LczD/l3HxH15n2/L7z+f59+3EuftpM/hvfn98U2fI9ow+E66mZVoJtt/rnNF5DP+EK4EpkXEjIg4GphGqvgBTs1/DwFE6uY4MyKOBPYBjiNVYAAfyX+vJX1DfRBwcS57p6QpfS7HzMya128dAmXVI7sBR0fE4cB5uewZkp4raS/gvbnsh6TG+HTgilz2oepdzmw5MD0ijgDeM8w63ws8BtgKPDciZkXEAcApefypwNF5/NERcRQwm9RoOxp4Xdfy9gBeRNpHv89lhwBHAYeTGt0Az++xHaouiIhDgU/m9wcBcyNiFvDtUS6rX1+KiJlsPz4mA8/Ir28GnhQRB+bjaX/gF3ncqTzcZtKxcCjwuVz2GkkHdU8YESsj4jhgZS76r4g4LpdBf8dy1R9I2+tg0hc6kLdVXuaiXLaos56IWMn2Y2IZ8MS8z9+Upz1X0oGkY28PYC1wWEQ8NSIeS9rPS4eIZZfjRrqZlajaJazXxdWDwKdz97itwEZSZQOpcoJUad1HughYJeka4Gukb703SHoc8MQ87SURsSlf0F2Uy3YnVSo9l7MDuZqZWb36rUOgrHrk+ohYkl9/p1L+FFLD+BGdcRHxYERsAb6Xy6ayvZt0x/kRcT9ARGwbZp3PzH9/GRGdxiYRsahr/ETghtxNegXpCwVIX0BU3RcRV0bEg6Q7rAA3RMSKiFgH3J3L9hsmnm4/yn9XDFG2fJTL6tcF+W/14XOddWwB3i3pNklbSF9WnJDHTePhFkREJ+fOPhVpf45WP8dy1Q8jYnVEbCL1/Kjm0Utnn88E1uR9Pj+XTSB9YbGYtP0nA3dL+rWk+aQvYu4ZZV47JT84zsxKtJT0rfxE4HhJGuZOyHzgBaSLsBtJ3cYOJ1UKuwFExJ2SZgNvBI4BjiA9NOjNkk4hXTSNaKTlRMQlY03WzMxq1W8dArt2PXJXjcvawvY7r73WsabyeusQZZ39NNTvt4fSmXfrEGUjfUEzVvcPsc5OvJ8Fzs6vbyL1kHgyqfv3boyvEY/lLvdXXndy6Xe7Q+q+fvMQ5RsjYpOkY0jH+jNzHKcBp5N6F/zrKNazU/KddDMrTkSsBr6b3z4NmNt5mAmApBMkPY/t39B/LSKeAryUVClRmXYaMDUiPhERr8/dBDt3Ip6Xv8HufJv/qvwAGwFvyGVbSA+p67mcunI3M7MdM4o6BMqqR46UdGh+/dpK+Q2kO5cb8/vXS5ogaXfS75Qh/X75tq7l9dOIvTr/PV7SszuFkp6aX16T/04E3l7pfn088C9sv8O6q+gcTz/NXeJPAv7YY/oTJU3Nr6v7dHGPeTq9LvYaZt3DHsujNNx6Ovt8PfDyyj4/mfRTgEslPQqYBXwhIs7I3e9/mufzNRNupJtZud5G+v+gAP9E6hp4vaR7gctJD+C5Po8/W9Ji0gNjJnUt53DSxdHdkn4jaTlwWB7Xmf+f899jSV3mlrP991ufjohVfS7HzMzaoZ86BMqqRzYDi3Kcn81l10bEZRGxHpiby16RY1gBPCeXvT93MR+tuaQ7rhOBX0i6UdLtQOeu/0Xkh/MBV0laLOl3pAfBXUr6bfyupLMfT5a0lPS7+wN7TD8JuClP+45c9r2IWN5jns4XO6coPcn/m13r7nUsj0ZnPcfmz85P8vu5pP37ROC2fCzfSrqzPi9P8zjgKuDePO8S0rMIqnHu0txIN7Mi5QuaZwHvBP4vF88kdWM7n/SN7FnAZaQHzTwSeDsPP/kvBy4kXWQcQqo4biRdtP1bXtd84JWkLouTSV2xrgfOZfuDeEZcjpmZtUOfdQiUVY9cS2rI7U16MvdP2P4ANyLiw6Tu84tIv0Hfh3Qn/PUR8ZWHLa0PEXEz8PQc959y3BPJ2y8iNpPuFn+G9KXAIXndi4EPk+7y70rOA35AuoM9mfRAux/1mP4/gE+T/iPBBtLv0s8ZYR3vIz1p/QHSw/mOyOVnMfKxPBqfAn5GyuUI0hdQRMQyUhf2i0kPhjuc9JC4BXmdkBrs3yQ95G4G6XkItwAfJ/Ww2OWp9wMtzczMzMysrZT+p/eJwOURcVKz0ZhZHXwn3czMzMzMzKwl3Eg3MzMzMzMzawl3dzczMzMzMzNrCd9JNzMzMzMzM2sJN9LNzMzMzMzMWsKNdDMzMzMzM7OWcCPdzMzMzMzMrCXcSDczMzMzMzNrCTfSzczMzMzMzFri/wHW1LnifbnOggAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1008x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gVnD7m61qh-3"
      },
      "source": [
        "#### Observações\n",
        "\n",
        "O segundo gráfico apresenta os dados de número de casos proporcionais ao número de habitantes. Essa relação de proporcionalidade nos permite visualizar de forma mais precisa as UF's que apresentam maior número de casos, destacando então Rio de Janeiro, Maranhão e São Paulo.\n",
        "\n",
        "Esses dados serão importantes para avaliarmos a incidência de casos em cada região."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6Q4Cum53YAoA"
      },
      "source": [
        "#### Número de casos por região"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rRlI1ppyX_Pe"
      },
      "source": [
        "# calculando número de casos total por região - 2014 a 2019\n",
        "norte1 = dados_casos_hep_A_uso_selc.query(\"Região == 'Norte'\")[\"Casos por cem mil habitantes\"].sum()\n",
        "sul1 = dados_casos_hep_A_uso_selc.query(\"Região == 'Sul'\")[\"Casos por cem mil habitantes\"].sum()\n",
        "sudeste1 = dados_casos_hep_A_uso_selc.query(\"Região == 'Sudeste'\")[\"Casos por cem mil habitantes\"].sum()\n",
        "centro_oeste1 = dados_casos_hep_A_uso_selc.query(\"Região == 'Centro-Oeste'\")[\"Casos por cem mil habitantes\"].sum()\n",
        "nordeste1 = dados_casos_hep_A_uso_selc.query(\"Região == 'Nordeste'\")[\"Casos por cem mil habitantes\"].sum()"
      ],
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uheoS2ruYYms"
      },
      "source": [
        "# criando um dicionário para associar região e cobertura vacinal\n",
        "dados_casos_hep_A_regiao = {'Região': [\"Norte\", \"Sul\", \"Sudeste\", \"Centro-Oeste\", \"Nordeste\"], 'Casos por cem mil habitantes': [norte1, sul1, sudeste1, centro_oeste1, nordeste1]}"
      ],
      "execution_count": 97,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cbY9sPGEbcj2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "outputId": "577a4eb6-61fe-44c0-c5d1-41890302e00c"
      },
      "source": [
        "#ordenando os dados pelo 'casos por milhão de habitantes'\n",
        "dados_casos_hep_A_uso_selc = dados_casos_hep_A_uso_selc.sort_values('Casos por cem mil habitantes', ascending = False)\n",
        "dados_casos_hep_A_uso_selc.head()"
      ],
      "execution_count": 98,
      "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>2014</th>\n",
              "      <th>2015</th>\n",
              "      <th>2016</th>\n",
              "      <th>2017</th>\n",
              "      <th>2018</th>\n",
              "      <th>2019</th>\n",
              "      <th>Região</th>\n",
              "      <th>Total</th>\n",
              "      <th>Habitantes</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unidade da Federação</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>Rio de Janeiro</th>\n",
              "      <td>438</td>\n",
              "      <td>193</td>\n",
              "      <td>41</td>\n",
              "      <td>183</td>\n",
              "      <td>509</td>\n",
              "      <td>99</td>\n",
              "      <td>Sudeste</td>\n",
              "      <td>1463</td>\n",
              "      <td>861773</td>\n",
              "      <td>169.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maranhão</th>\n",
              "      <td>248</td>\n",
              "      <td>128</td>\n",
              "      <td>43</td>\n",
              "      <td>24</td>\n",
              "      <td>23</td>\n",
              "      <td>22</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>488</td>\n",
              "      <td>631181</td>\n",
              "      <td>77.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>São Paulo</th>\n",
              "      <td>327</td>\n",
              "      <td>241</td>\n",
              "      <td>155</td>\n",
              "      <td>1121</td>\n",
              "      <td>823</td>\n",
              "      <td>291</td>\n",
              "      <td>Sudeste</td>\n",
              "      <td>2958</td>\n",
              "      <td>4207714</td>\n",
              "      <td>70.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Amazonas</th>\n",
              "      <td>940</td>\n",
              "      <td>402</td>\n",
              "      <td>69</td>\n",
              "      <td>56</td>\n",
              "      <td>59</td>\n",
              "      <td>29</td>\n",
              "      <td>Norte</td>\n",
              "      <td>1555</td>\n",
              "      <td>3055149</td>\n",
              "      <td>50.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Paraíba</th>\n",
              "      <td>295</td>\n",
              "      <td>61</td>\n",
              "      <td>4</td>\n",
              "      <td>18</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>Nordeste</td>\n",
              "      <td>389</td>\n",
              "      <td>894470</td>\n",
              "      <td>43.49</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                      2014  2015  ...  Habitantes  Casos por cem mil habitantes\n",
              "Unidade da Federação              ...                                          \n",
              "Rio de Janeiro         438   193  ...      861773                        169.77\n",
              "Maranhão               248   128  ...      631181                         77.32\n",
              "São Paulo              327   241  ...     4207714                         70.30\n",
              "Amazonas               940   402  ...     3055149                         50.90\n",
              "Paraíba                295    61  ...      894470                         43.49\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VCZhhypFYb6v",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "5205384a-f294-44d0-87ec-cb8ed0dc3fa3"
      },
      "source": [
        "# Criando um novo DataFrame com a região e a cobertura vacinal\n",
        "dados_casos_por_regiao = pd.DataFrame(data=dados_casos_hep_A_regiao)\n",
        "dados_casos_por_regiao = dados_casos_por_regiao.sort_values('Casos por cem mil habitantes', ascending = False)\n",
        "dados_casos_por_regiao"
      ],
      "execution_count": 99,
      "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>Região</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>259.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>185.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>103.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>33.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>13.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Casos por cem mil habitantes\n",
              "2       Sudeste                        259.83\n",
              "4      Nordeste                        185.87\n",
              "0         Norte                        103.78\n",
              "3  Centro-Oeste                         33.76\n",
              "1           Sul                         13.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xOlEAPL7ZFv1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "outputId": "f220f479-d323-41ee-a0c3-b785de739419"
      },
      "source": [
        "#criando a vizualização do número de casos de hepatite A por Região no período de 2014 a 2019\n",
        "\n",
        "plt.figure(figsize=(10, 7))\n",
        "ax = plt.bar(dados_casos_por_regiao[\"Região\"], dados_casos_por_regiao[\"Casos por cem mil habitantes\"], color = \"indianred\")\n",
        "\n",
        "plt.title(\"Número de casos de Hepatite A por cem mil habitantes \\n 2014 a 2019\", fontsize = 16, fontweight = \"bold\") #título\n",
        "#plt.xlabel(\"Região\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Casos\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HEkpaMhxayIR"
      },
      "source": [
        "#### Observações:\n",
        "O gráfico mostra que o Centro-oeste e Sul são as regiões com menor número de casos total. Esse dado parece coerente quando comparado com os dados de cobertura vacinal em que as mesmas regiões apresentam maior cobertura.\n",
        "\n",
        "O Sudeste se destaca como a região com maior número de casos. Sendo assim, é interessante avaliarmos a progressão do número de casos no decorrer dos anos. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nu88VzAasYwO"
      },
      "source": [
        "##### Região Sudeste"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SHlT7gc_sYcR"
      },
      "source": [
        "#selecionando apenas os dados da região sudeste\n",
        "dados_sudeste = dados_casos_hep_A_uso_selc.query(\"Região == 'Sudeste'\")"
      ],
      "execution_count": 101,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Obe0d5kkoXP-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "outputId": "0b2ca1c3-4f12-46f7-afa6-a22e2dac8de4"
      },
      "source": [
        "#gerando a visualização dos dados de número de casos de hepatite A da região Sudeste\n",
        "ax = dados_sudeste[[2014, 2015, 2016, 2017, 2018, 2019]].T.plot(figsize=(10,6), colormap = 'viridis')\n",
        "\n",
        "plt.title(\"Número de casos por Ano\", fontsize = 16) #Título figura\n",
        "plt.xlabel(\"Ano\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Casos\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LIKQxHS323Vs"
      },
      "source": [
        "##### Observações\n",
        "\n",
        "Quando observamos apenas os dados dos estados da região Sudeste, observamos que houve um aumento considerável no número de casos de hepatite A nos estados de São Paulo e Rio de Janeiro em 2017 e 2018, motivo pelo qual a região se destaca no número de casos no Brasil[6].\n",
        "\n",
        "A Secretaria Municipal de Saúde de São Paulo atribuiu o aumento dos casos ao sexo oral-anal sem proteção — embora a hepatite A não seja considerada uma infecção sexualmente transmissível, o contato com a região perianal ou com material que contenha resíduos de fezes pode gerar contaminação[6, 7]. \n",
        "\n",
        "No Rio de Janeiro, gestores da saúde, indicaram como causa mais provável a presença do vírus na água, principalmente pela ocorrência em uma região pobre com deficiência no saneamento básico. O laboratório da FioCruz analisou a água em 10 pontos na região do Vidigal e identificou presença do vírus em três locais, levantando o alerta para a população manter cuidados preventivos[7]."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Mnj1zQxS0oAQ"
      },
      "source": [
        "##### Região Nordeste"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YXgKSh5Zu3si"
      },
      "source": [
        "#selecionando apenas os dados da região nordeste\n",
        "dados_nordeste = dados_casos_hep_A_uso_selc.query(\"Região == 'Nordeste'\")"
      ],
      "execution_count": 103,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eVgFMREAvJik",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "outputId": "1fc95489-5c7d-4b42-ac79-9c1785329f7e"
      },
      "source": [
        "#gerando a visualização dos dados de número de casos de hepatite A da região Nordeste\n",
        "ax = dados_nordeste[[2014, 2015, 2016, 2017, 2018, 2019]].T.plot(figsize=(10,6), colormap = 'viridis', )\n",
        "\n",
        "plt.title(\"Número de casos por Ano\", fontsize = 16) #Título figura\n",
        "plt.xlabel(\"Ano\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Casos\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MApBUXry04Cr"
      },
      "source": [
        "##### Observações:\n",
        "O Nordeste é a segunda região em maior número de casos e a segunda com menor taxa de cobertura vacinal."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9I9wNVYERTkV"
      },
      "source": [
        "### Nº de Casos x Cobertura vacinal"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nb13fdaitsjg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "75931551-8010-410c-b9c4-31f03a62970d"
      },
      "source": [
        "#ordenando os dados de cobertura vacinal pela 'Região'\n",
        "dados_cv_por_regiao = dados_cv_por_regiao.sort_values('Região', ascending = True)\n",
        "dados_cv_por_regiao"
      ],
      "execution_count": 105,
      "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>Região</th>\n",
              "      <th>Cobertura Vacinal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>79.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>71.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>68.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>77.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>79.54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Cobertura Vacinal\n",
              "3  Centro-Oeste              79.76\n",
              "4      Nordeste              71.32\n",
              "0         Norte              68.89\n",
              "2       Sudeste              77.37\n",
              "1           Sul              79.54"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gBmja2QStz-x",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "26fbf66b-f1da-46b1-9dfe-cc0180276d35"
      },
      "source": [
        "#ordenando os dados de nº de casos pela 'Região'\n",
        "dados_casos_por_regiao = dados_casos_por_regiao.sort_values('Região', ascending = True)\n",
        "dados_casos_por_regiao"
      ],
      "execution_count": 106,
      "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>Região</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>33.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>185.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>103.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>259.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>13.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Casos por cem mil habitantes\n",
              "3  Centro-Oeste                         33.76\n",
              "4      Nordeste                        185.87\n",
              "0         Norte                        103.78\n",
              "2       Sudeste                        259.83\n",
              "1           Sul                         13.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Q3OHjv-us3w",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "52ce1a94-0e43-4907-c9f3-e99c050fb2d0"
      },
      "source": [
        "#criando novo dataset com o nº de casos e a cobertura vacinal por região\n",
        "dados_cv_casos = dados_cv_por_regiao\n",
        "dados_cv_casos"
      ],
      "execution_count": 107,
      "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>Região</th>\n",
              "      <th>Cobertura Vacinal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>79.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>71.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>68.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>77.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>79.54</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Cobertura Vacinal\n",
              "3  Centro-Oeste              79.76\n",
              "4      Nordeste              71.32\n",
              "0         Norte              68.89\n",
              "2       Sudeste              77.37\n",
              "1           Sul              79.54"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mlo_W-7HwWTZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "bbb48afe-a492-43f3-8a43-08888ae07c52"
      },
      "source": [
        "#criando a coluna de 'Casos por cel mil habitantes'\n",
        "dados_cv_casos['Casos por cem mil habitantes'] = dados_casos_por_regiao[\"Casos por cem mil habitantes\"]\n",
        "dados_cv_casos"
      ],
      "execution_count": 108,
      "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>Região</th>\n",
              "      <th>Cobertura Vacinal</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>79.76</td>\n",
              "      <td>33.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>71.32</td>\n",
              "      <td>185.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>68.89</td>\n",
              "      <td>103.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>77.37</td>\n",
              "      <td>259.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>79.54</td>\n",
              "      <td>13.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Cobertura Vacinal  Casos por cem mil habitantes\n",
              "3  Centro-Oeste              79.76                         33.76\n",
              "4      Nordeste              71.32                        185.87\n",
              "0         Norte              68.89                        103.78\n",
              "2       Sudeste              77.37                        259.83\n",
              "1           Sul              79.54                         13.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ODaUMaH_wpYS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "83b626bb-8fed-4e4f-d070-75a8d1eb6cf1"
      },
      "source": [
        "#ordenando os dados pelos valores de nº de casos\n",
        "dados_cv_casos.sort_values('Casos por cem mil habitantes', ascending = False)"
      ],
      "execution_count": 109,
      "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>Região</th>\n",
              "      <th>Cobertura Vacinal</th>\n",
              "      <th>Casos por cem mil habitantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sudeste</td>\n",
              "      <td>77.37</td>\n",
              "      <td>259.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Nordeste</td>\n",
              "      <td>71.32</td>\n",
              "      <td>185.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Norte</td>\n",
              "      <td>68.89</td>\n",
              "      <td>103.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Centro-Oeste</td>\n",
              "      <td>79.76</td>\n",
              "      <td>33.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Sul</td>\n",
              "      <td>79.54</td>\n",
              "      <td>13.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Região  Cobertura Vacinal  Casos por cem mil habitantes\n",
              "2       Sudeste              77.37                        259.83\n",
              "4      Nordeste              71.32                        185.87\n",
              "0         Norte              68.89                        103.78\n",
              "3  Centro-Oeste              79.76                         33.76\n",
              "1           Sul              79.54                         13.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 109
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KWYR_xAtw99e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "outputId": "2beeaeee-e41f-459f-a369-2b22c6c65aa3"
      },
      "source": [
        "#vizualizando os dados de cobertura vacinal versus número de casos\n",
        "plt.figure(figsize=(8,8))\n",
        "sns.scatterplot(data=dados_cv_casos, x=\"Cobertura Vacinal\", y=\"Casos por cem mil habitantes\", \n",
        "                hue = \"Região\", size=\"Cobertura Vacinal\", sizes=(50, 150), palette=\"rocket\")\n",
        "\n",
        "plt.title(\"Cobertura Vacinal versus Número de Casos\", fontsize = 16) #Título figura\n",
        "plt.xlabel(\"Cobertura Vacinal\",fontsize = 14, fontweight = \"bold\") #título eixo x\n",
        "plt.ylabel(\"Casos por cem mil habitantes\",fontsize = 14, fontweight = \"bold\") #título eixo y\n",
        "\n",
        "plt.tick_params(axis=\"x\", labelsize=12) #modifica o tamanho do tick em x\n",
        "plt.tick_params(axis=\"y\", labelsize=12) #modifica o tamanho do tick em y\n",
        "\n",
        "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
        "\n",
        "plt.xlim(0,85)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wiw8Ikef0BMr"
      },
      "source": [
        "### Observações e Conclusões\n",
        "\n",
        "O grafico mostra que apesar de haver uma certa relação entre cobertura vacinal e número de casos, ela não segue uma proporcionalidade. Como visto anteriormente, a região sudeste apesar de alta taxa de cobertura vacinal apresentou altos números de casos devido a problemas de saúde sexual e saneamento.\n",
        "\n",
        "Nas regiões Centro-oeste e Sul, a cobertura vacinal, apesar de abaixo do recomendado, tem se mostrado eficiente no controle da doença. Sendo assim, o número de casos nessas regiões é baixo.\n",
        "\n",
        "Na região Nordeste, o número de casos é alto, apesar de ter uma taxa de cobertura vacinal semelhante a da região centro-oeste. Esse dado indica que existem fatores que colaboram para o aumento do número de casos e um destes pode ser a distribuição desigual de imunos pelo país [7\n",
        "].\n",
        "\n",
        "Em todos os casos, as baixas taxas de cobertura vacinal estão associadas a diversos fatores como a falsa sensação de segurança contra doenças que diminuíram sua incidência, a distribuição desigual de imunos pelo país e as falhas de comunicação dos órgãos de saúde com a população. A crise do Sistema Único de Saúde (SUS) também tem sido apontado como um dos fatores."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yx0dHpk5_aDd"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8QHQnUwh_cVz"
      },
      "source": [
        "## Referências\n",
        "\n",
        "[1] Revista Radis aborda queda da cobertura vacinal no Brasil. Disponível em: <https://portal.fiocruz.br/noticia/revista-radis-aborda-queda-da-cobertura-vacinal-no-brasil> Acesso em: 13/01/2021\n",
        "\n",
        "[2]Em queda há 5 anos, coberturas vacinais preocupam Ministério da Saúde. Disponível em: <https://agenciabrasil.ebc.com.br/saude/noticia/2020-10/em-queda-ha-5-anos-coberturas-vacinais-preocupam-ministerio-da-saude#:~:text=Para%20ambas%2C%20a%20meta%20%C3%A9,%2C%20a%2068%2C46%25> Acesso em: 13/02/2021.\n",
        "\n",
        "[3] SUS passa a oferecer vacina contra hepatite A para crianças. Disponível em: <http://www.blog.saude.gov.br/index.php/570-destaques/34211-sus-passa-a-oferecer-vacina-contra-hepatite-a-para-criancas> Acesso em:10/02/2021\n",
        "\n",
        "[4] Capital tem aumento de 960% de casos de Hepatite A. Disponível em: <https://g1.globo.com/sp/sao-paulo/noticia/capital-tem-aumento-de-960-de-casos-de-hepatite-a.ghtml> Acesso em: 19/02/2021\n",
        "\n",
        "[5] Casos de hepatite A crescem 73% no Brasil puxados por alta em SP. Disponível em: <https://g1.globo.com/bemestar/noticia/casos-de-hepatite-a-crescem-73-no-brasil-puxados-por-alta-em-sp.ghtml> Acesso em: 19/02/2021\n",
        "\n",
        "[6] Novos surtos em São Paulo e no Rio revertem uma década de queda nos casos de hepatite A. Disponível em: <https://www.bbc.com/portuguese/geral-42629636#:~:text=Em%202017%2C%20somente%20a%20cidade,anterior%2C%20houve%20apenas%20dez%20registros> Acesso em: 19/02/2021.\n",
        "\n",
        "[7] Hepatite A: Crescem os riscos de contaminação. Disponível em: <https://radis.ensp.fiocruz.br/index.php/home/noticias/hepatite-a-crescem-os-riscos-de-contaminacao> Acesso em: 19/02/2021\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    }
  ]
}