Desafios_Aula_03.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Desafios-Aula-03.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyPpQqU1BZeS/OIkT7pQtl6l"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jIR6W_jtG9vi"
      },
      "source": [
        "# ***3ª Imersão Dados Alura***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qlhcUxSFHA-x"
      },
      "source": [
        "Este projeto utiliza o notebook do Google Colab para realizar as análises e resultados dos desafios referente a primeira aula da imersão. #imersaodados #alura"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nL7b0m3OHDtQ"
      },
      "source": [
        "**Aula 03 - Correlações, Casualidade e Relações entre genes**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0n-rovKQHQvR"
      },
      "source": [
        "**Importando os dados do GitHub**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 427
        },
        "id": "JsDpyxTFG4LH",
        "outputId": "10fc21a6-f477-445e-c83d-bdea073419c7"
      },
      "source": [
        "import pandas as pd\n",
        "url_dados = 'https://github.com/alura-cursos/imersaodados3/blob/main/dados/dados_experimentos.zip?raw=true'\n",
        "dados = pd.read_csv(url_dados, compression = 'zip')\n",
        "dados"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
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              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
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              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
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              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
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              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>id_fffb1ceed</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>df1d0a5a1</td>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.0636</td>\n",
              "      <td>-0.1112</td>\n",
              "      <td>-0.5080</td>\n",
              "      <td>-0.4713</td>\n",
              "      <td>0.7201</td>\n",
              "      <td>0.5773</td>\n",
              "      <td>0.3055</td>\n",
              "      <td>-0.4726</td>\n",
              "      <td>0.1269</td>\n",
              "      <td>0.2531</td>\n",
              "      <td>0.1730</td>\n",
              "      <td>-0.4532</td>\n",
              "      <td>-1.0790</td>\n",
              "      <td>0.2474</td>\n",
              "      <td>-0.4550</td>\n",
              "      <td>0.3588</td>\n",
              "      <td>0.1600</td>\n",
              "      <td>-0.7362</td>\n",
              "      <td>-0.1103</td>\n",
              "      <td>0.8550</td>\n",
              "      <td>-0.4139</td>\n",
              "      <td>0.5541</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.5573</td>\n",
              "      <td>-0.4397</td>\n",
              "      <td>-0.9260</td>\n",
              "      <td>-0.2424</td>\n",
              "      <td>-0.6686</td>\n",
              "      <td>0.2326</td>\n",
              "      <td>0.6456</td>\n",
              "      <td>0.0136</td>\n",
              "      <td>-0.5141</td>\n",
              "      <td>-0.6320</td>\n",
              "      <td>0.7166</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0807</td>\n",
              "      <td>0.4024</td>\n",
              "      <td>-0.0895</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9641</td>\n",
              "      <td>-0.1846</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>0.3154</td>\n",
              "      <td>-0.2071</td>\n",
              "      <td>-0.6158</td>\n",
              "      <td>-0.2977</td>\n",
              "      <td>0.0992</td>\n",
              "      <td>0.6838</td>\n",
              "      <td>0.5259</td>\n",
              "      <td>0.7882</td>\n",
              "      <td>0.3119</td>\n",
              "      <td>-0.7697</td>\n",
              "      <td>0.2203</td>\n",
              "      <td>-1.0710</td>\n",
              "      <td>0.5979</td>\n",
              "      <td>0.0848</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.6293</td>\n",
              "      <td>1.1660</td>\n",
              "      <td>0.3329</td>\n",
              "      <td>0.2754</td>\n",
              "      <td>0.4108</td>\n",
              "      <td>-0.1252</td>\n",
              "      <td>-0.2340</td>\n",
              "      <td>0.2267</td>\n",
              "      <td>0.1969</td>\n",
              "      <td>0.0262</td>\n",
              "      <td>-0.8121</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.5372</td>\n",
              "      <td>-0.3246</td>\n",
              "      <td>0.0631</td>\n",
              "      <td>0.9171</td>\n",
              "      <td>0.5258</td>\n",
              "      <td>0.4680</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>id_fffb70c0c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>ecf3b6b74</td>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.3478</td>\n",
              "      <td>-0.3743</td>\n",
              "      <td>0.9905</td>\n",
              "      <td>-0.7178</td>\n",
              "      <td>0.6621</td>\n",
              "      <td>-0.2252</td>\n",
              "      <td>-0.5565</td>\n",
              "      <td>0.5112</td>\n",
              "      <td>0.6727</td>\n",
              "      <td>-0.1851</td>\n",
              "      <td>2.8650</td>\n",
              "      <td>-0.2140</td>\n",
              "      <td>-0.6153</td>\n",
              "      <td>0.8362</td>\n",
              "      <td>0.5584</td>\n",
              "      <td>-0.2589</td>\n",
              "      <td>0.1292</td>\n",
              "      <td>0.0148</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>-0.2182</td>\n",
              "      <td>-0.9235</td>\n",
              "      <td>0.0749</td>\n",
              "      <td>-1.5910</td>\n",
              "      <td>-0.8359</td>\n",
              "      <td>-0.9217</td>\n",
              "      <td>0.3013</td>\n",
              "      <td>0.1716</td>\n",
              "      <td>0.0880</td>\n",
              "      <td>0.1842</td>\n",
              "      <td>0.1835</td>\n",
              "      <td>0.5436</td>\n",
              "      <td>-0.0533</td>\n",
              "      <td>-0.0491</td>\n",
              "      <td>0.9543</td>\n",
              "      <td>...</td>\n",
              "      <td>0.1410</td>\n",
              "      <td>1.2640</td>\n",
              "      <td>-0.8663</td>\n",
              "      <td>0.8129</td>\n",
              "      <td>-0.1514</td>\n",
              "      <td>-0.4652</td>\n",
              "      <td>-0.7390</td>\n",
              "      <td>-1.3270</td>\n",
              "      <td>0.9925</td>\n",
              "      <td>1.0570</td>\n",
              "      <td>-0.3355</td>\n",
              "      <td>-0.2555</td>\n",
              "      <td>0.8219</td>\n",
              "      <td>0.6995</td>\n",
              "      <td>-0.2942</td>\n",
              "      <td>0.2408</td>\n",
              "      <td>-0.7781</td>\n",
              "      <td>-0.0929</td>\n",
              "      <td>-0.0329</td>\n",
              "      <td>0.0781</td>\n",
              "      <td>-1.4440</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>0.3188</td>\n",
              "      <td>-1.1080</td>\n",
              "      <td>0.4895</td>\n",
              "      <td>-0.2144</td>\n",
              "      <td>1.0960</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.4444</td>\n",
              "      <td>-1.1130</td>\n",
              "      <td>0.4286</td>\n",
              "      <td>0.4426</td>\n",
              "      <td>0.0423</td>\n",
              "      <td>-0.3195</td>\n",
              "      <td>-0.8086</td>\n",
              "      <td>-0.9798</td>\n",
              "      <td>-0.2084</td>\n",
              "      <td>-0.1224</td>\n",
              "      <td>-0.2715</td>\n",
              "      <td>0.3689</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>id_fffc1c3f4</td>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>cacb2b860</td>\n",
              "      <td>0.3942</td>\n",
              "      <td>0.3756</td>\n",
              "      <td>0.3109</td>\n",
              "      <td>-0.7389</td>\n",
              "      <td>0.5505</td>\n",
              "      <td>-0.0159</td>\n",
              "      <td>-0.2541</td>\n",
              "      <td>0.1745</td>\n",
              "      <td>-0.0340</td>\n",
              "      <td>0.4865</td>\n",
              "      <td>-0.1854</td>\n",
              "      <td>0.0716</td>\n",
              "      <td>0.1729</td>\n",
              "      <td>-0.0434</td>\n",
              "      <td>0.1542</td>\n",
              "      <td>-0.2192</td>\n",
              "      <td>-0.0302</td>\n",
              "      <td>-0.4218</td>\n",
              "      <td>0.4057</td>\n",
              "      <td>-0.5372</td>\n",
              "      <td>0.1521</td>\n",
              "      <td>-0.2651</td>\n",
              "      <td>0.2310</td>\n",
              "      <td>-0.8101</td>\n",
              "      <td>0.4943</td>\n",
              "      <td>0.6905</td>\n",
              "      <td>-0.3720</td>\n",
              "      <td>-1.4110</td>\n",
              "      <td>0.4516</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.1949</td>\n",
              "      <td>-1.3280</td>\n",
              "      <td>-0.4276</td>\n",
              "      <td>-0.0040</td>\n",
              "      <td>-0.3086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.6845</td>\n",
              "      <td>0.7127</td>\n",
              "      <td>0.7294</td>\n",
              "      <td>0.4718</td>\n",
              "      <td>-0.2020</td>\n",
              "      <td>0.2783</td>\n",
              "      <td>0.4934</td>\n",
              "      <td>0.4144</td>\n",
              "      <td>0.5449</td>\n",
              "      <td>1.4690</td>\n",
              "      <td>-0.6142</td>\n",
              "      <td>0.6068</td>\n",
              "      <td>0.3434</td>\n",
              "      <td>0.9880</td>\n",
              "      <td>-0.0468</td>\n",
              "      <td>-0.1882</td>\n",
              "      <td>-0.0087</td>\n",
              "      <td>-0.0356</td>\n",
              "      <td>0.5718</td>\n",
              "      <td>0.4971</td>\n",
              "      <td>0.1057</td>\n",
              "      <td>0.2111</td>\n",
              "      <td>0.6992</td>\n",
              "      <td>0.0708</td>\n",
              "      <td>0.6169</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.5994</td>\n",
              "      <td>0.2689</td>\n",
              "      <td>0.0305</td>\n",
              "      <td>1.2320</td>\n",
              "      <td>0.5409</td>\n",
              "      <td>0.3755</td>\n",
              "      <td>0.7343</td>\n",
              "      <td>0.2807</td>\n",
              "      <td>0.4116</td>\n",
              "      <td>0.6422</td>\n",
              "      <td>0.2256</td>\n",
              "      <td>0.7592</td>\n",
              "      <td>0.6656</td>\n",
              "      <td>0.3808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>id_fffcb9e7c</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>8b87a7a83</td>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.4392</td>\n",
              "      <td>0.2044</td>\n",
              "      <td>0.8531</td>\n",
              "      <td>-0.0343</td>\n",
              "      <td>0.0323</td>\n",
              "      <td>0.0463</td>\n",
              "      <td>0.4299</td>\n",
              "      <td>-0.7985</td>\n",
              "      <td>0.5742</td>\n",
              "      <td>0.1421</td>\n",
              "      <td>2.2700</td>\n",
              "      <td>0.2046</td>\n",
              "      <td>0.5363</td>\n",
              "      <td>-1.7330</td>\n",
              "      <td>0.1450</td>\n",
              "      <td>0.6097</td>\n",
              "      <td>0.2024</td>\n",
              "      <td>0.9865</td>\n",
              "      <td>-0.7805</td>\n",
              "      <td>0.9608</td>\n",
              "      <td>0.3440</td>\n",
              "      <td>2.7650</td>\n",
              "      <td>0.4925</td>\n",
              "      <td>0.6698</td>\n",
              "      <td>0.2374</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.8771</td>\n",
              "      <td>-2.6560</td>\n",
              "      <td>-0.2000</td>\n",
              "      <td>-0.2043</td>\n",
              "      <td>0.6797</td>\n",
              "      <td>-0.0248</td>\n",
              "      <td>-0.0927</td>\n",
              "      <td>...</td>\n",
              "      <td>0.3360</td>\n",
              "      <td>-0.6136</td>\n",
              "      <td>0.5011</td>\n",
              "      <td>0.9261</td>\n",
              "      <td>0.4419</td>\n",
              "      <td>0.0295</td>\n",
              "      <td>0.4220</td>\n",
              "      <td>0.4677</td>\n",
              "      <td>-0.1184</td>\n",
              "      <td>0.4524</td>\n",
              "      <td>0.4135</td>\n",
              "      <td>0.1356</td>\n",
              "      <td>-0.5801</td>\n",
              "      <td>0.0411</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>1.0340</td>\n",
              "      <td>-0.0270</td>\n",
              "      <td>-0.4194</td>\n",
              "      <td>0.7403</td>\n",
              "      <td>-0.6793</td>\n",
              "      <td>-0.1423</td>\n",
              "      <td>0.7307</td>\n",
              "      <td>0.7946</td>\n",
              "      <td>-0.0650</td>\n",
              "      <td>0.9038</td>\n",
              "      <td>0.2324</td>\n",
              "      <td>0.9676</td>\n",
              "      <td>1.0940</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.5187</td>\n",
              "      <td>-0.1105</td>\n",
              "      <td>0.4258</td>\n",
              "      <td>-0.2012</td>\n",
              "      <td>0.1506</td>\n",
              "      <td>1.5230</td>\n",
              "      <td>0.7101</td>\n",
              "      <td>0.1732</td>\n",
              "      <td>0.7015</td>\n",
              "      <td>-0.6290</td>\n",
              "      <td>0.0740</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>id_ffffdd77b</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>972f41291</td>\n",
              "      <td>-0.8598</td>\n",
              "      <td>1.0240</td>\n",
              "      <td>-0.1361</td>\n",
              "      <td>0.7952</td>\n",
              "      <td>-0.3611</td>\n",
              "      <td>-3.6750</td>\n",
              "      <td>-1.2420</td>\n",
              "      <td>0.9146</td>\n",
              "      <td>3.0790</td>\n",
              "      <td>1.2460</td>\n",
              "      <td>1.9460</td>\n",
              "      <td>1.4370</td>\n",
              "      <td>2.9780</td>\n",
              "      <td>2.2370</td>\n",
              "      <td>-0.6818</td>\n",
              "      <td>0.6870</td>\n",
              "      <td>-1.1060</td>\n",
              "      <td>0.0182</td>\n",
              "      <td>-0.9247</td>\n",
              "      <td>-0.0738</td>\n",
              "      <td>-0.1919</td>\n",
              "      <td>-0.7722</td>\n",
              "      <td>-1.4050</td>\n",
              "      <td>-1.0050</td>\n",
              "      <td>-1.1170</td>\n",
              "      <td>-0.5293</td>\n",
              "      <td>-1.1720</td>\n",
              "      <td>-0.2885</td>\n",
              "      <td>0.1599</td>\n",
              "      <td>-0.4250</td>\n",
              "      <td>0.3591</td>\n",
              "      <td>-0.1420</td>\n",
              "      <td>-0.9530</td>\n",
              "      <td>-0.2005</td>\n",
              "      <td>-1.8340</td>\n",
              "      <td>...</td>\n",
              "      <td>-6.9170</td>\n",
              "      <td>-1.8640</td>\n",
              "      <td>-2.5090</td>\n",
              "      <td>-4.7130</td>\n",
              "      <td>-1.7250</td>\n",
              "      <td>-3.8650</td>\n",
              "      <td>-3.0800</td>\n",
              "      <td>-4.1530</td>\n",
              "      <td>-1.2030</td>\n",
              "      <td>-1.1690</td>\n",
              "      <td>-4.1460</td>\n",
              "      <td>-1.2670</td>\n",
              "      <td>-1.1300</td>\n",
              "      <td>-2.4390</td>\n",
              "      <td>0.1591</td>\n",
              "      <td>-2.2490</td>\n",
              "      <td>-2.5860</td>\n",
              "      <td>-1.9520</td>\n",
              "      <td>-2.1810</td>\n",
              "      <td>-4.6690</td>\n",
              "      <td>-3.9450</td>\n",
              "      <td>-2.9560</td>\n",
              "      <td>-2.7930</td>\n",
              "      <td>-2.1560</td>\n",
              "      <td>-2.4100</td>\n",
              "      <td>-1.8190</td>\n",
              "      <td>-3.3480</td>\n",
              "      <td>-0.1414</td>\n",
              "      <td>-2.6430</td>\n",
              "      <td>-2.5810</td>\n",
              "      <td>-3.3890</td>\n",
              "      <td>-1.7450</td>\n",
              "      <td>-6.6300</td>\n",
              "      <td>-4.0950</td>\n",
              "      <td>-7.3860</td>\n",
              "      <td>-1.4160</td>\n",
              "      <td>-3.5770</td>\n",
              "      <td>-0.4775</td>\n",
              "      <td>-2.1500</td>\n",
              "      <td>-4.2520</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                 id    tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0      id_000644bb2     com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1      id_000779bfc     com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2      id_000a6266a     com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3      id_0015fd391     com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4      id_001626bd3     com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "...             ...           ...    ...  ...  ...     ...     ...     ...     ...\n",
              "23809  id_fffb1ceed     com_droga     24   D2  ...  0.0631  0.9171  0.5258  0.4680\n",
              "23810  id_fffb70c0c     com_droga     24   D2  ... -0.2084 -0.1224 -0.2715  0.3689\n",
              "23811  id_fffc1c3f4  com_controle     48   D2  ...  0.2256  0.7592  0.6656  0.3808\n",
              "23812  id_fffcb9e7c     com_droga     24   D1  ...  0.1732  0.7015 -0.6290  0.0740\n",
              "23813  id_ffffdd77b     com_droga     72   D1  ... -3.5770 -0.4775 -2.1500 -4.2520\n",
              "\n",
              "[23814 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 247
        },
        "id": "x_a1ZPsPHW3E",
        "outputId": "7d446ee2-e760-437f-bf45-39e80cbd8b61"
      },
      "source": [
        "#Esta função é utilizada para ler apenas as 5 primeiras linhas da nossa tabela\n",
        "dados.head()"
      ],
      "execution_count": 111,
      "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>id</th>\n",
              "      <th>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>droga</th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>...</th>\n",
              "      <th>c-60</th>\n",
              "      <th>c-61</th>\n",
              "      <th>c-62</th>\n",
              "      <th>c-63</th>\n",
              "      <th>c-64</th>\n",
              "      <th>c-65</th>\n",
              "      <th>c-66</th>\n",
              "      <th>c-67</th>\n",
              "      <th>c-68</th>\n",
              "      <th>c-69</th>\n",
              "      <th>c-70</th>\n",
              "      <th>c-71</th>\n",
              "      <th>c-72</th>\n",
              "      <th>c-73</th>\n",
              "      <th>c-74</th>\n",
              "      <th>c-75</th>\n",
              "      <th>c-76</th>\n",
              "      <th>c-77</th>\n",
              "      <th>c-78</th>\n",
              "      <th>c-79</th>\n",
              "      <th>c-80</th>\n",
              "      <th>c-81</th>\n",
              "      <th>c-82</th>\n",
              "      <th>c-83</th>\n",
              "      <th>c-84</th>\n",
              "      <th>c-85</th>\n",
              "      <th>c-86</th>\n",
              "      <th>c-87</th>\n",
              "      <th>c-88</th>\n",
              "      <th>c-89</th>\n",
              "      <th>c-90</th>\n",
              "      <th>c-91</th>\n",
              "      <th>c-92</th>\n",
              "      <th>c-93</th>\n",
              "      <th>c-94</th>\n",
              "      <th>c-95</th>\n",
              "      <th>c-96</th>\n",
              "      <th>c-97</th>\n",
              "      <th>c-98</th>\n",
              "      <th>c-99</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>id_000644bb2</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>b68db1d53</td>\n",
              "      <td>1.0620</td>\n",
              "      <td>0.5577</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-0.6208</td>\n",
              "      <td>-0.1944</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>-1.0220</td>\n",
              "      <td>-0.0326</td>\n",
              "      <td>0.5548</td>\n",
              "      <td>-0.0921</td>\n",
              "      <td>1.1830</td>\n",
              "      <td>0.1530</td>\n",
              "      <td>0.5574</td>\n",
              "      <td>-0.4015</td>\n",
              "      <td>0.1789</td>\n",
              "      <td>-0.6528</td>\n",
              "      <td>-0.7969</td>\n",
              "      <td>0.6342</td>\n",
              "      <td>0.1778</td>\n",
              "      <td>-0.3694</td>\n",
              "      <td>-0.5688</td>\n",
              "      <td>-1.1360</td>\n",
              "      <td>-1.1880</td>\n",
              "      <td>0.6940</td>\n",
              "      <td>0.4393</td>\n",
              "      <td>0.2664</td>\n",
              "      <td>0.1907</td>\n",
              "      <td>0.1628</td>\n",
              "      <td>-0.2853</td>\n",
              "      <td>0.5819</td>\n",
              "      <td>0.2934</td>\n",
              "      <td>-0.5584</td>\n",
              "      <td>-0.0916</td>\n",
              "      <td>-0.3010</td>\n",
              "      <td>-0.1537</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4805</td>\n",
              "      <td>0.4965</td>\n",
              "      <td>0.3680</td>\n",
              "      <td>0.8427</td>\n",
              "      <td>0.1042</td>\n",
              "      <td>0.1403</td>\n",
              "      <td>0.1758</td>\n",
              "      <td>1.2570</td>\n",
              "      <td>-0.5979</td>\n",
              "      <td>1.2250</td>\n",
              "      <td>-0.0553</td>\n",
              "      <td>0.7351</td>\n",
              "      <td>0.5810</td>\n",
              "      <td>0.9590</td>\n",
              "      <td>0.2427</td>\n",
              "      <td>0.0495</td>\n",
              "      <td>0.4141</td>\n",
              "      <td>0.8432</td>\n",
              "      <td>0.6162</td>\n",
              "      <td>-0.7318</td>\n",
              "      <td>1.2120</td>\n",
              "      <td>0.6362</td>\n",
              "      <td>-0.4427</td>\n",
              "      <td>0.1288</td>\n",
              "      <td>1.4840</td>\n",
              "      <td>0.1799</td>\n",
              "      <td>0.5367</td>\n",
              "      <td>-0.1111</td>\n",
              "      <td>-1.0120</td>\n",
              "      <td>0.6685</td>\n",
              "      <td>0.2862</td>\n",
              "      <td>0.2584</td>\n",
              "      <td>0.8076</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.1912</td>\n",
              "      <td>0.6584</td>\n",
              "      <td>-0.3981</td>\n",
              "      <td>0.2139</td>\n",
              "      <td>0.3801</td>\n",
              "      <td>0.4176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>id_000779bfc</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>df89a8e5a</td>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.4087</td>\n",
              "      <td>0.2991</td>\n",
              "      <td>0.0604</td>\n",
              "      <td>1.0190</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.2341</td>\n",
              "      <td>0.3372</td>\n",
              "      <td>-0.4047</td>\n",
              "      <td>0.8507</td>\n",
              "      <td>-1.1520</td>\n",
              "      <td>-0.4201</td>\n",
              "      <td>-0.0958</td>\n",
              "      <td>0.4590</td>\n",
              "      <td>0.0803</td>\n",
              "      <td>0.2250</td>\n",
              "      <td>0.5293</td>\n",
              "      <td>0.2839</td>\n",
              "      <td>-0.3494</td>\n",
              "      <td>0.2883</td>\n",
              "      <td>0.9449</td>\n",
              "      <td>-0.1646</td>\n",
              "      <td>-0.2657</td>\n",
              "      <td>-0.3372</td>\n",
              "      <td>0.3135</td>\n",
              "      <td>-0.4316</td>\n",
              "      <td>0.4773</td>\n",
              "      <td>0.2075</td>\n",
              "      <td>-0.4216</td>\n",
              "      <td>-0.1161</td>\n",
              "      <td>-0.0499</td>\n",
              "      <td>-0.2627</td>\n",
              "      <td>0.9959</td>\n",
              "      <td>-0.2483</td>\n",
              "      <td>0.2655</td>\n",
              "      <td>...</td>\n",
              "      <td>0.4083</td>\n",
              "      <td>0.0319</td>\n",
              "      <td>0.3905</td>\n",
              "      <td>0.7099</td>\n",
              "      <td>0.2912</td>\n",
              "      <td>0.4151</td>\n",
              "      <td>-0.2840</td>\n",
              "      <td>-0.3104</td>\n",
              "      <td>-0.6373</td>\n",
              "      <td>0.2887</td>\n",
              "      <td>-0.0765</td>\n",
              "      <td>0.2539</td>\n",
              "      <td>0.4443</td>\n",
              "      <td>0.5932</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.7639</td>\n",
              "      <td>0.5499</td>\n",
              "      <td>-0.3322</td>\n",
              "      <td>-0.0977</td>\n",
              "      <td>0.4329</td>\n",
              "      <td>-0.2782</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.5934</td>\n",
              "      <td>0.3402</td>\n",
              "      <td>0.1499</td>\n",
              "      <td>0.4420</td>\n",
              "      <td>0.9366</td>\n",
              "      <td>0.8193</td>\n",
              "      <td>-0.4236</td>\n",
              "      <td>0.3192</td>\n",
              "      <td>-0.4265</td>\n",
              "      <td>0.7543</td>\n",
              "      <td>0.4708</td>\n",
              "      <td>0.0230</td>\n",
              "      <td>0.2957</td>\n",
              "      <td>0.4899</td>\n",
              "      <td>0.1522</td>\n",
              "      <td>0.1241</td>\n",
              "      <td>0.6077</td>\n",
              "      <td>0.7371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>id_000a6266a</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>18bb41b2c</td>\n",
              "      <td>0.6280</td>\n",
              "      <td>0.5817</td>\n",
              "      <td>1.5540</td>\n",
              "      <td>-0.0764</td>\n",
              "      <td>-0.0323</td>\n",
              "      <td>1.2390</td>\n",
              "      <td>0.1715</td>\n",
              "      <td>0.2155</td>\n",
              "      <td>0.0065</td>\n",
              "      <td>1.2300</td>\n",
              "      <td>-0.4797</td>\n",
              "      <td>-0.5631</td>\n",
              "      <td>-0.0366</td>\n",
              "      <td>-1.8300</td>\n",
              "      <td>0.6057</td>\n",
              "      <td>-0.3278</td>\n",
              "      <td>0.6042</td>\n",
              "      <td>-0.3075</td>\n",
              "      <td>-0.1147</td>\n",
              "      <td>-0.0570</td>\n",
              "      <td>-0.0799</td>\n",
              "      <td>-0.8181</td>\n",
              "      <td>-1.5320</td>\n",
              "      <td>0.2307</td>\n",
              "      <td>0.4901</td>\n",
              "      <td>0.4780</td>\n",
              "      <td>-1.3970</td>\n",
              "      <td>4.6240</td>\n",
              "      <td>-0.0437</td>\n",
              "      <td>1.2870</td>\n",
              "      <td>-1.8530</td>\n",
              "      <td>0.6069</td>\n",
              "      <td>0.4290</td>\n",
              "      <td>0.1783</td>\n",
              "      <td>0.0018</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.5477</td>\n",
              "      <td>-0.7576</td>\n",
              "      <td>-0.0444</td>\n",
              "      <td>0.1894</td>\n",
              "      <td>-0.0014</td>\n",
              "      <td>-2.3640</td>\n",
              "      <td>-0.4682</td>\n",
              "      <td>0.1210</td>\n",
              "      <td>-0.5177</td>\n",
              "      <td>-0.0604</td>\n",
              "      <td>0.1682</td>\n",
              "      <td>-0.4436</td>\n",
              "      <td>0.4963</td>\n",
              "      <td>0.1363</td>\n",
              "      <td>0.3335</td>\n",
              "      <td>0.9760</td>\n",
              "      <td>-0.0427</td>\n",
              "      <td>-0.1235</td>\n",
              "      <td>0.0959</td>\n",
              "      <td>0.0690</td>\n",
              "      <td>-0.9416</td>\n",
              "      <td>-0.7548</td>\n",
              "      <td>-0.1109</td>\n",
              "      <td>-0.6272</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>0.1172</td>\n",
              "      <td>0.1093</td>\n",
              "      <td>-0.3113</td>\n",
              "      <td>0.3019</td>\n",
              "      <td>-0.0873</td>\n",
              "      <td>-0.7250</td>\n",
              "      <td>-0.6297</td>\n",
              "      <td>0.6103</td>\n",
              "      <td>0.0223</td>\n",
              "      <td>-1.3240</td>\n",
              "      <td>-0.3174</td>\n",
              "      <td>-0.6417</td>\n",
              "      <td>-0.2187</td>\n",
              "      <td>-1.4080</td>\n",
              "      <td>0.6931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>id_0015fd391</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>8c7f86626</td>\n",
              "      <td>-0.5138</td>\n",
              "      <td>-0.2491</td>\n",
              "      <td>-0.2656</td>\n",
              "      <td>0.5288</td>\n",
              "      <td>4.0620</td>\n",
              "      <td>-0.8095</td>\n",
              "      <td>-1.9590</td>\n",
              "      <td>0.1792</td>\n",
              "      <td>-0.1321</td>\n",
              "      <td>-1.0600</td>\n",
              "      <td>-0.8269</td>\n",
              "      <td>-0.3584</td>\n",
              "      <td>-0.8511</td>\n",
              "      <td>-0.5844</td>\n",
              "      <td>-2.5690</td>\n",
              "      <td>0.8183</td>\n",
              "      <td>-0.0532</td>\n",
              "      <td>-0.8554</td>\n",
              "      <td>0.1160</td>\n",
              "      <td>-2.3520</td>\n",
              "      <td>2.1200</td>\n",
              "      <td>-1.1580</td>\n",
              "      <td>-0.7191</td>\n",
              "      <td>-0.8004</td>\n",
              "      <td>-1.4670</td>\n",
              "      <td>-0.0107</td>\n",
              "      <td>-0.8995</td>\n",
              "      <td>0.2406</td>\n",
              "      <td>-0.2479</td>\n",
              "      <td>-1.0890</td>\n",
              "      <td>-0.7575</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>-2.7370</td>\n",
              "      <td>0.8745</td>\n",
              "      <td>0.5787</td>\n",
              "      <td>...</td>\n",
              "      <td>-2.1220</td>\n",
              "      <td>-0.3752</td>\n",
              "      <td>-2.3820</td>\n",
              "      <td>-3.7350</td>\n",
              "      <td>-2.9740</td>\n",
              "      <td>-1.4930</td>\n",
              "      <td>-1.6600</td>\n",
              "      <td>-3.1660</td>\n",
              "      <td>0.2816</td>\n",
              "      <td>-0.2990</td>\n",
              "      <td>-1.1870</td>\n",
              "      <td>-0.5044</td>\n",
              "      <td>-1.7750</td>\n",
              "      <td>-1.6120</td>\n",
              "      <td>-0.9215</td>\n",
              "      <td>-1.0810</td>\n",
              "      <td>-3.0520</td>\n",
              "      <td>-3.4470</td>\n",
              "      <td>-2.7740</td>\n",
              "      <td>-1.8460</td>\n",
              "      <td>-0.5568</td>\n",
              "      <td>-3.3960</td>\n",
              "      <td>-2.9510</td>\n",
              "      <td>-1.1550</td>\n",
              "      <td>-3.2620</td>\n",
              "      <td>-1.5390</td>\n",
              "      <td>-2.4600</td>\n",
              "      <td>-0.9417</td>\n",
              "      <td>-1.5550</td>\n",
              "      <td>0.2431</td>\n",
              "      <td>-2.0990</td>\n",
              "      <td>-0.6441</td>\n",
              "      <td>-5.6300</td>\n",
              "      <td>-1.3780</td>\n",
              "      <td>-0.8632</td>\n",
              "      <td>-1.2880</td>\n",
              "      <td>-1.6210</td>\n",
              "      <td>-0.8784</td>\n",
              "      <td>-0.3876</td>\n",
              "      <td>-0.8154</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>id_001626bd3</td>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>7cbed3131</td>\n",
              "      <td>-0.3254</td>\n",
              "      <td>-0.4009</td>\n",
              "      <td>0.9700</td>\n",
              "      <td>0.6919</td>\n",
              "      <td>1.4180</td>\n",
              "      <td>-0.8244</td>\n",
              "      <td>-0.2800</td>\n",
              "      <td>-0.1498</td>\n",
              "      <td>-0.8789</td>\n",
              "      <td>0.8630</td>\n",
              "      <td>-0.2219</td>\n",
              "      <td>-0.5121</td>\n",
              "      <td>-0.9577</td>\n",
              "      <td>1.1750</td>\n",
              "      <td>0.2042</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1244</td>\n",
              "      <td>-1.7090</td>\n",
              "      <td>-0.3543</td>\n",
              "      <td>-0.5160</td>\n",
              "      <td>-0.3330</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>0.7649</td>\n",
              "      <td>0.2057</td>\n",
              "      <td>1.3720</td>\n",
              "      <td>0.6835</td>\n",
              "      <td>0.8056</td>\n",
              "      <td>-0.3754</td>\n",
              "      <td>-1.2090</td>\n",
              "      <td>0.2965</td>\n",
              "      <td>-0.0712</td>\n",
              "      <td>0.6389</td>\n",
              "      <td>0.6674</td>\n",
              "      <td>-0.0783</td>\n",
              "      <td>1.1740</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.2274</td>\n",
              "      <td>0.3215</td>\n",
              "      <td>0.1535</td>\n",
              "      <td>-0.4640</td>\n",
              "      <td>-0.5943</td>\n",
              "      <td>0.3973</td>\n",
              "      <td>0.1500</td>\n",
              "      <td>0.5178</td>\n",
              "      <td>0.5159</td>\n",
              "      <td>0.6091</td>\n",
              "      <td>0.1813</td>\n",
              "      <td>-0.4249</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.6529</td>\n",
              "      <td>0.5648</td>\n",
              "      <td>0.4817</td>\n",
              "      <td>0.0587</td>\n",
              "      <td>0.5303</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>-0.3966</td>\n",
              "      <td>-1.4950</td>\n",
              "      <td>-0.9625</td>\n",
              "      <td>-0.0541</td>\n",
              "      <td>0.6273</td>\n",
              "      <td>0.4563</td>\n",
              "      <td>0.0698</td>\n",
              "      <td>0.8134</td>\n",
              "      <td>0.1924</td>\n",
              "      <td>0.6054</td>\n",
              "      <td>-0.1824</td>\n",
              "      <td>0.0042</td>\n",
              "      <td>0.0048</td>\n",
              "      <td>0.6670</td>\n",
              "      <td>1.0690</td>\n",
              "      <td>0.5523</td>\n",
              "      <td>-0.3031</td>\n",
              "      <td>0.1094</td>\n",
              "      <td>0.2885</td>\n",
              "      <td>-0.3786</td>\n",
              "      <td>0.7125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 877 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id tratamento  tempo dose  ...    c-96    c-97    c-98    c-99\n",
              "0  id_000644bb2  com_droga     24   D1  ... -0.3981  0.2139  0.3801  0.4176\n",
              "1  id_000779bfc  com_droga     72   D1  ...  0.1522  0.1241  0.6077  0.7371\n",
              "2  id_000a6266a  com_droga     48   D1  ... -0.6417 -0.2187 -1.4080  0.6931\n",
              "3  id_0015fd391  com_droga     48   D1  ... -1.6210 -0.8784 -0.3876 -0.8154\n",
              "4  id_001626bd3  com_droga     72   D2  ...  0.1094  0.2885 -0.3786  0.7125\n",
              "\n",
              "[5 rows x 877 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138
        },
        "id": "P8cpxtYgHaa8",
        "outputId": "c0b23f36-a6ac-48a4-e083-d990dd41c11c"
      },
      "source": [
        "#Essa função permite criarmos uma tabela cruzada de dados\n",
        "pd.crosstab(dados['dose'], dados['tempo'])"
      ],
      "execution_count": 112,
      "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>tempo</th>\n",
              "      <th>24</th>\n",
              "      <th>48</th>\n",
              "      <th>72</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>D1</th>\n",
              "      <td>3886</td>\n",
              "      <td>4354</td>\n",
              "      <td>3907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>3886</td>\n",
              "      <td>3896</td>\n",
              "      <td>3885</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tempo    24    48    72\n",
              "dose                   \n",
              "D1     3886  4354  3907\n",
              "D2     3886  3896  3885"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "el5uxUt-KN1d",
        "outputId": "9611e4a6-8ba7-414c-c421-1b9b7b874232"
      },
      "source": [
        "#A função normalize coloca as informações em % (proporção)\n",
        "#O True faz a % do total\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize = True)"
      ],
      "execution_count": 113,
      "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",
              "    .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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012640</td>\n",
              "      <td>0.150542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.014403</td>\n",
              "      <td>0.168430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012892</td>\n",
              "      <td>0.151172</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150374</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.012808</td>\n",
              "      <td>0.150332</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.012640   0.150542\n",
              "     48         0.014403   0.168430\n",
              "     72         0.012892   0.151172\n",
              "D2   24         0.012808   0.150374\n",
              "     48         0.012808   0.150794\n",
              "     72         0.012808   0.150332"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "vRS4lGE8XUM-",
        "outputId": "ef6b0753-6d70-4ddf-faf0-12f1dea34630"
      },
      "source": [
        "#A função normalize coloca as informações em % (proporção) \n",
        "#O index faz a % da soma das linhas\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], normalize = 'index')"
      ],
      "execution_count": 114,
      "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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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.077458</td>\n",
              "      <td>0.922542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078778</td>\n",
              "      <td>0.921222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078577</td>\n",
              "      <td>0.921423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.078487</td>\n",
              "      <td>0.921513</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.078285</td>\n",
              "      <td>0.921715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.078507</td>\n",
              "      <td>0.921493</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.077458   0.922542\n",
              "     48         0.078778   0.921222\n",
              "     72         0.078577   0.921423\n",
              "D2   24         0.078487   0.921513\n",
              "     48         0.078285   0.921715\n",
              "     72         0.078507   0.921493"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "SPi71AcsY-Gm",
        "outputId": "fa879874-79e6-457c-f583-1ad50d6f3d61"
      },
      "source": [
        "#Utilizamos a função values para adicionar uma nova variável (nesse caso, a coluna)\n",
        "#Utilizamos a função aggfunc para trazer a média\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values = dados['g-0'], aggfunc = 'mean')"
      ],
      "execution_count": 115,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>-0.251760</td>\n",
              "      <td>0.367996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>-0.122773</td>\n",
              "      <td>0.412469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>-0.295271</td>\n",
              "      <td>0.286250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.010754</td>\n",
              "      <td>0.115253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.013174</td>\n",
              "      <td>0.214480</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.070250</td>\n",
              "      <td>0.253439</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24        -0.251760   0.367996\n",
              "     48        -0.122773   0.412469\n",
              "     72        -0.295271   0.286250\n",
              "D2   24         0.010754   0.115253\n",
              "     48         0.013174   0.214480\n",
              "     72         0.070250   0.253439"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "_4Wu5iQmkqaU",
        "outputId": "f47e45bc-f17a-4cb0-8906-42e13d7ec01f"
      },
      "source": [
        "#Selecionando colunas de uma tabela\n",
        "dados[['g-0','g-3']]"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>g-0</th>\n",
              "      <th>g-3</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.0620</td>\n",
              "      <td>-0.6208</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.0743</td>\n",
              "      <td>0.0604</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.6280</td>\n",
              "      <td>-0.0764</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.5138</td>\n",
              "      <td>0.5288</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.3254</td>\n",
              "      <td>0.6919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>0.1394</td>\n",
              "      <td>-0.5080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>-1.3260</td>\n",
              "      <td>0.9905</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>0.3942</td>\n",
              "      <td>-0.7389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>0.6660</td>\n",
              "      <td>0.2044</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>-0.8598</td>\n",
              "      <td>0.7952</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          g-0     g-3\n",
              "0      1.0620 -0.6208\n",
              "1      0.0743  0.0604\n",
              "2      0.6280 -0.0764\n",
              "3     -0.5138  0.5288\n",
              "4     -0.3254  0.6919\n",
              "...       ...     ...\n",
              "23809  0.1394 -0.5080\n",
              "23810 -1.3260  0.9905\n",
              "23811  0.3942 -0.7389\n",
              "23812  0.6660  0.2044\n",
              "23813 -0.8598  0.7952\n",
              "\n",
              "[23814 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "yfU5927vlA3A",
        "outputId": "35610a70-a916-402a-9191-b63f4cda0024"
      },
      "source": [
        "#Importando seaborn\n",
        "import seaborn as sns\n",
        "#Essa função serve para salvar as configurações de padrão de imagem do seaborn\n",
        "sns.set()\n",
        "#O scatterplot nos permite plotar um gráfico de dispersão\n",
        "sns.scatterplot(x = 'g-0', y = 'g-3', data = dados) "
      ],
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe9ee566390>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        },
        "id": "o7e1fKYXlN7S",
        "outputId": "1203038f-c931-49f0-b6fa-a61c4ad63f84"
      },
      "source": [
        "#Gráfico de dispersão \n",
        "sns.scatterplot(x = 'g-0', y = 'g-8', data = dados)"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe9eea5dc90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 118
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5UeAU0i+SzKVQY6TTS4vNw3Od1OWQAwg5Eq1axeN3/0AyVVPf7GDJ7ALqWpygUAgpHbNRzYxxWaAApULB4BQjNocHp7uDeJNOVKsJXWfBzHwarS6S4nU0t7no8AX4WzeG21e7TzCpKF0U/dx5XSFJ8Toara6uGoVBfVoHcsoUWNj7pdNy+0+aaoClaGX0XwwIdpnD4aC9PehhA4EAH3/8MQUFBRHHzZo1ixUrVgBQWVnJ7t27mTJlSp/aejEgmvTLjHFZkcylzkX0sec3s+twM8+9/S1mo5pBFiOl03JZMDNfpKDs9fq4d94oEZtuYUk+67ZW0Wh1cLzBxpETbbi8Pn50bSFzJg+hbONhVq6rYNXnh2hocZKcqGfluoP8+e2dlH1xWKTSrFWrIABJ8TqunjwEp9snOJjwe7l+Wp7gYEKvv/zB3qBD6zxPolkr3NuvX97CU29so6bRQXVjl/zP6Zha4e9v2FbNwpL8AcUklCHjdBgQkUxTUxM//elP8fl8+P1+cnNz+dWvfgVAaWkpL774Iqmpqdx555387Gc/o6SkBKVSyeOPP47J1PNc9kWJaKmdsNe9Pv8p6cXhO2/RIqsAs1HN1ZOH8OyKyCio3e7F54dWm1ukBP3x5qOoVUoMOo2ofvPIzeN45cO9ogX8uZXfMnd6nmR/TahWs3rzUWaMywq+Pi1X8l7cHp/k6xq1kkUlwxmaHovD46Ou2U7ptFy+OVDPpKJ0fvvaVlHEEmdUSzaChpha4UyuRqtLSOvlZcaREqfr90xCAXLzpowoGBBOJjMzk/fff1/yvbKyMuFng8HAs88+21dmXXg4xZCwcEmYR28ZF5Ve3J251J0OO3NCdkSEsKK8grnT80hN1PO393bh9fm5evIQUaoqvAM+9Lnq+jZJR6DTKllwRb5oUc9OM/P43T+go8NHamIhPn+A0mm56DRKybRbSqJe8h6HpMXy0gd70KizKf+oiinFGSiVsKhkOO+sr4iIWH5772TmTI5sBE2M1QKRTK5Gq4uyjYd55uHpwTrMQFio5eZNGafAgEiXyegbREvtNLV5RK/XNztY1C2ts7S0kAkFKRELS3iTYlDKxSDpGFIS9FhtbmqbHKId/W1zCvjl0ok43V5Kp+UKaS+ANItRsgEyMyVWSKGVfXGYOZOH4HR7abQ6qahu5ZkVO/l/y3ZQ9sVhdJoYfnTtJRFpt8oTbdw2p0B0j/fcUMRLH+xhSnEG5VuqKJmYzaadx/D74WCNlRuvyGdYZpzovhzuDslGUJszmE6L1mybljRwervk5k0Zp8KAiGRk9A2iNeE1tblEr6/+8ig3TM8TUlpKhYJ4o5YEY2RqJ7xPo9HqwuHySkYIdU0OId3m9vpotLrYsL2aOZOH8PhLWyR7YRqsjohemjuvK+Slst0Ri/p//+hS9h5pZtXnh0Tvvb56Hw/dNJZXPhRHSW98sp+FJfldzLeMeFxeX5D5pkDkaLpfv6W9QujVcbg6ojDGHBg0KmL1asn+GhFVuJ+nouTmTRmnguxkZAiI1oRnidVFpHQ+3HSEh28ae3p5/G5NimaDhkUl+aL0UchxAILTMBvV/OiakVTXt4kYYuH1lYwUMy+V7aF0aq7Qje90ewUKdAhur49Wmwd/ICDd+e+Trr+kJ5lwuLycbHHy11W7mDE+S4g4lEpE6s6hz7z8wV7BvgcWFJMYK/1MtRpV1yJ8KibXAEhFyc2bMk4FOV12sSNsaJhSqZBM3VhiNRGvL5lVgMWsOTNtrbC59u12D6s7U2ELZubzwMJiyrdU0Wh1CWmyxVcNZ/GVI3hmxTcsL68QMcTcXh+Zg0w8sLCYGJWCKydmd6XGNh4mIzVWMoVmidORkWzk0VvGc9ucAoHVlmYxCE60+2cqa9tYtnY/GrWSdruXDduqWVSSz6ZvjpGTHhd1SufQwbE8dd9kCrLisJg13HNDUbfU4kg+2nT4jBbhgZCKGoj6ejL6DnIkczFDYpf8yOKxkdIo/jOQTJFK6Ugg3qyl3e4VelaS4nWiwni73UtqojGiyB8ewdTU2Vi5voJhmXHcdnUBj906njabB502hsYWO/fOG8Vf3+3qe7nvxlE0tTqJiVHy4cZDTChMY9M3x7j2h7kkmjX8eeXOiLTb0tJCVqyrENWHUEBGiok7rxtJIBBgeFaC5A7eoIvB6w8Eoys/jM5L5Jd3TqS+2YFWo+KjTYe55oe5wiJ8qlRYtFRUY7u7/zDPBqC+noy+g+xkLmJI7ZKfXraDp+6bTFao8BxaKHqQ0rEkRtLHu2tptdu9aDXBAWKWWD11zQ6OnWyXXFiVSoTU2rDMOK6cmMNvXumiDIfoyWqVksduHY/D5cWgU/P393cLcjBLS0eyYWuQFbZszX7mTs+jtskhUgQYPSyZytpW1CoxS23TN8dQKhQU5Vp4/OUtZA0yced1hbz8wV6RDc+u3Em73cs9NxQxOjcRfJCWoMOoDabI7r6+SHAwUVNhnYiWijpU04rb7et52qw36jwRk07l5k0ZkVD9+te//vX5NqI/wen00F3NzWjU4nCcWur9fOH72FZvdbF+W43oNZ8/wA+K0ogznCKV05liq7e6UKiUuL0+nuzsDwFIiNWSFG/A6e7A3eFHoVSgiVEKi5I/EOCKS7PISDGROziej786yr/31HHouJXLRqfTZvdysMaKL0zeR6tWceOMfFaUH8AfCLBk1iU8/07X3BefP8D+yhZmTxrClr11/HtPHTMnZPG717dhtXmEY3YdbOSWqy+h1e5h16FGLhlqYe+RJhyuDvYebWLPkSaS4/UYtGpG5lpYtuYAuw41cqjGytLrR5KfGY/V5ibVYmRfZTN7jzYxe9IQrr4sh/RkE2u2VNJodeHzB9hZ0cClI9NoanOjUCqJNaiJM2iEtFKb0yt6bj5/gO37TzK1eDBOt4/jjXYMejUFOYkcPdHK1ZOHUJRnYfbkIazfWsXaLdVMLR4ckeo7LTo3BU++tpX122r4bPsxhgyOJyVB1+Ucuv2NtequzLrRqMXh9EScIzcjgeQw9t/5QH/+X4X+bV9PbVMoFBhOsV7IkcxFjB4VbKWiloXFwjlCnfQruvWFZCSbUMco2V9txR8IoNeqyEmLxeX28WBuMSgUHDneSkaKiTSLkYwUE8dOdmmiLSrJp67Jxo+uLcTT4cfh8kZtlgxFHzan9DFujw8CXb094dCqVWSmmlEAz6zoivLMRjUNzU7+vKJrVEEoqlq5voIHFhSzvPxAxLVqG+3UNjpQKqEgJ5HMZIMwhTNaKux4k4NnV2wWrvPzW8ez6MrhPP+OWPqmpf1ojxhcUhHsc29/yy9un0BmkgE4Pdmgz8eCyxiwkJ3MRYyeyMBLLS419TbBWYU66btTiBeW5GM2aAQKccj5bN59gslF6SzvZJT5/QER8+zO6wqxO72s7lQEmDs9j+3761gyu4BFJfn4AwjMs1Cz5O/f3N7ZNDpe0okmxet5e30F9904ClUYbVqrVvGfi8eAQoHb4xOx2maMy4rod1lRXiFosKUnG1lUMjyoUkDQpna7F0ucnr+9t1s4//3zR5No0mAyaKI6+Zp6m8i5Odw+wcGEX3vu9LweMbiiObd9lc3EdabxTudAZNqyjDOF7GQuZvSgYCu1uKzbWiUU21FIM67ijFpefD+yf+WBhcWCxEzpuNyIhTxECQ4NI8tMNZKSMITfvtpVi1lYkk/5lirmTs/jpQ/2CJ9f9flB7iodyd/DpGjunltEo9XBtLGZGLVqXv6wiwKdYNIEI4kGh9D/c8P0PN77/FDU+0pNNPL0Az+kus4W4UCTE/S8tWafyGGcaLDj9frZc7SFEVnxEU7+3nmjePPTfUBXVBhN2SAz1XT6ArtE7SWac/P7EYa3nc6ByLRlGWcK2clc7DhLtV2pxaXd7iXVYuCJeybh9vgo+yJy8dFrVZILlytcIyzKQh4qvKdZDJj0Gp5dsVXkiFaUV/DQTWOobbKLemQO1rQClfz3jy6l3REcL+Dz+Vi+9gBX/iAHl6eD2iYHG7ZXM2NcFpmDzBystkY4izmTh+D2+iUX1WMnbSTF6yJ2/svLK/j/loyjodXFgivy0euC0zW7kwQmFKbwxN2TaGpzYYnVodOphEFu4fpqUtcebDGc1sFIpb2MuhiWlo4U6cCFHPXkkamgUJzWgfTaJFAZFzxkJyPjrBCrj+GRxWM5fKJN2O3HGdW88sEeJhels3ZLFYuvGs6yNQdEi6lOGxMldRXsVQk5B6ljCAQdzLzLh7GvslnSETndPsnPV9fZ8Hb4eWb5N4I9P55bxJffHicvM5E0i4FZk3JYtuYAI7ITJCVgfn77BLxeX8R9hUYC5GfFUzotF+hK3bm9Pnz+gEDPLp2ay/K1kefOSY/ld69vEy3Ujywey9PLdghON6TOHF7nOpMFPVrdJJRyfOimsVTWtuL3Q/mWKpbMKhBYb6d1IDJtWcYZQnYyMs4ang6/aLe/+KrhQl3F7fXx4b+OsGDmMBLMOpIT9MTEKHnlgz0svmo4n35VKYhK5qTHsXzNfuZfkU+7w8O/vj0eoQawtHQkNqeHe24YxW9f28qiK/Mlax/1zQ6M+pgISvF9N47i7XUHulQBgHfWV3BXaRGVda3cf+Mo9hxpoXRaLp4onf92p5equnY2bKsWaM6ZqWbe/+IQk4vSeeof20SOJ6QonWjW8odlO4RoTOrcB6paJGsfzzw8naZWJ2VfHBb16iiVMG54Chaz5rQLerS6iT8Q4GBNKy99sFsQBb1/fjHpYeyyguw4UYRlidUIhAUB8swZGWcA2cnIOCtI7Y6XrTkgYpg1WoPjiwH++45LcXt8jBsxiN2HGiRZUm+vr2Da2ExmTxqC29MhOCidRsUrH+2l0erip/OLMRvVKBWKiHSWVqPivc8PcfNVBaz999GgLR4fSfF61KoAEwrTRFHAwpJ8qurbKN9STbxJJ5zvrtKRkpGUtd2FUqEQFJIXleTz6kd7mTkhW5IMMHd6HunJRpweryDzn5Nmljx3ZqqZBTPzRRGQ1e5hTEYCLpeHBxYWC5NHyzYe5ifzR0sv+N2hAKNeLUmOCDHqQoPctGoVkwtTRfTlfVWtvPnpPqYUZ1BZ2xbBjDst+rnemoy+g+xkZJwVou2OXR6fdNPgsVaWlx9Aq5aW6w918vsDAV5YtVvo6r9tTgEmg1qoT7TaXcyckC2kq0KfX15ewZLZI5g5IRt1jIIrLs0Wzaq5f/5oyrdURVzzgYXFTCnO4IVVXWSEVV8c4pbZI3jjk/1dqbXrR6JSgsfr57Y5BQzLTKDR6uQnNxZjd0k/i+R4PW+t2c+Sqwu49oe5LFuzH7NRHRGlhZxVu90bEQF9tbtWeFYhBejkBD3HT9o4fLyd3HRz9EU7yuTSUEpME6MUMeq6p8LaHF7e/HRfhPjnT+aPpjA7/vRfkgGgtyaj7yA3Y3bDxdSM2RMoVEo+234solEyNyOOotwk9le24PMHhEV0zZZKHK4OfP4AGSkmvj3YKDqfzx+gKM9CIAC7DjVyxYRMxhekMMhixOHyMXtyDja7m6+/q2fyqHS+3HUi4vPTijN445N95KTF8sbH+4WF3+cPsGP/Se6ZN5r9Vc04XB3C60PT49BolOQOjqcw10LhUAtHT7RS3+zgnhtGkZZkZHhWIp9+VUlmaixf7jpBZoqZ59/ZxZe7TvDV7lrGFaRSVduGzdmlI6ZVq7hsdDpxZh1uT5Bk4Pb6cLg6ON5gY85lQ7lu6lCyBpn5avcJJhcNZkROIn4/FA61cPm4TMwGNb955WvRfeysaMASpycQCODp8BEfq0WjkpYelGry3F/Zwn/dcSnxRg1en59ZP8hm2ph05kzKISNJTCCot7ow6DS8+9mhiGc5tXgwiXF6HE5P1GbNUzWZnnXj6FmiP/+vQv+2T27GlNEvIMUquvO6QuwuL0qFgifumYTd6SUmRsWflu8QqMcAGrVSMtrJSYvjpQ92B9NHg0zU1Nl4MoyifPfcIq794VDsbuloqa7ZgdvrI96kk4wsHE4vV08eIowI0KpVqJQKjDq1UIwP3UcgEBBqLCEsW3OABxeO4ZkVQfJAUryOGeOyqG20c/+Nxfzz0+8oyktBqYQh6XG8sx3Sy7oAACAASURBVKGC6job99wwSnSeRquL5eUHWFSSjyVOx+KrRnCgqgV/AL7YUcPCK4dTkBMcEBd+nVAtSatRsnxtMB3X3O7BlBwTmb5SwPEmh+RzONniFEV5DywoJj0xkqEWb9ZGFf+02j34/YFTRioDtodGTvGdEwwYJ9PS0sKjjz5KdXU1Go2G7OxsHn/8cRITE0XH/exnP2Pz5s0kJCQAMGvWLO69997zYfKFiTBW0fEmBzX1QbHKdrs3qFdm0mAxamhzdaBWKbll9gjiTTqM+hhijWruun4kf3+/izq7tHQk676uZOaEbFITDXi8flEKy+318cKq3fzyzom8s2GfxOeDQpYAep1K0glpNSrKt1RxxzWF1NS3MywzARTw+zBn4vYGe3Ieu3U8ZqMat1W8yBv1MZiNasyouykaHObeeaNotbmwu3y89tFeSiZm09J+NCiIKWGPOkaJzeHlpbIugsLCknxWrD3A4MVjqam3kWYxSM6qMRvV+AMBWtrcGLUxWMwa0cLo8wdEzbHh1w1v8gwnGXRf+GP1MRTkJEalMdc22k/ZrDkge2jkFN85w4BxMgqFgqVLlzJx4kQAnnrqKZ5++ml++9vfRhz74x//mCVLlvS1iRcPQqyizDgGWwyMyI4PUliNatrsXmxOL3q9moUlw0VqyCFxyhDTS6tW4vf7mTxqsOBY/vPmsZK74JZ2F5OK0kmI1QnD0ggEpWNCdZvQxM7udY82m5uSieJazd1ziwRnEn6diuoWZk7IZt3WKkl5HCCi2P/Xd3cJtaRQ7WPGuCzWba2KcIqLrxpOepKRp/8pXZtqbnOzbmsVS68riqhfvfzBXuZOzwNAr42hzeEJRidhC+PS0kK276+LoDzfPbeIZWv3RzxXyegiAJnJBn4yfzTPvf2taNGNNaipszpPGakMxB4aWSbn3GHAOJn4+HjBwQAUFxfz1ltvnUeLZAjOxqCmzeFlX3UrjVYnSqUCu7MjYgplaMDYyvUVQpQQb1JxssVJ1iATY/JTie0UkOy+CzYbNPzz0/3cdX1RF315ezXQNehs9ZdHmddtYqdWo8Lh7mDluoMR0dHc6XkivbFQ13vWICM/umakkB4LfWZ5eQUPhrHoQginKIecBYpgk2q8UdvJEGtHHaNEHaPk8PFWyXMolWDQxdBu90ZVoh6UaMDt7aC+2cbw7ER+/8b2bs846IjCxxMoFQpiw0gU4fcbNbrwQ2F2vGQfTGKs/tSRygDsoRmwKb4BgAE5tMzv9/PWW28xY8YMyfdfffVVrr32Wu677z4OHz7cx9ZdJAgNO2u0U9Po4Kk3t/O/b27H6fbx5if7o06hVCq75FLKNh7mz2/v5IsdNVw5MUf4fVFJvlAgDjVPfr69mpKJ2Tz1j23BAWWdg8xyBpnJSjXz8OKx/OjaQgDyMuJIswRHFbz3+SG8HX5JW9KTjaLrLCzJZ9POY8SbdVGlXJQqZUTxOtQwGn6PSoWChSX5QABru4v0ZBNpSSY2fXOMrFSzcI6keB0LrshnUUk+I4cmodcGo50OX0DyOpZ4HZ9vryEzNRaXu0Oo3Sy4Ip8FM/MpnZZLZqpJmNlT9sVhNGolK9YH9ePC7/e0g8XChs2FD6ZLSzKefkhZlM/2V4RSfOHo9ym+AQJFINCdS9X/8T//8z/U19fz3HPPoVSK/WR9fT3JyckolUref/99nnnmGdatW4dKdW5ZLQMVfn+A2kY7zW1OEmP1pCUZxfPlJdDR4Wf34Ua+O9qEPxCcs1IyMZuPNx9lzmVDcLp85KSbeWb5zojdbrDLvE0U5Sy4Ip+yjYeF35PidcyckE1Omhm9NoYPNx1m6OAEyjYexmxUd9VJdDHEmbSilNzCknwUClj77+DMGL1OxdD0OH4bxnYK2XLHtZeQHG/gYE0Lfj9s2nmMGy4fht/vo6nNQ9kXhyM+8/PbJtDS7hKJXoboxyFSwaO3jKeuyUaMSolWEyOZMpxQmEb5lqqIustd148kNSE4VwcUIumXxVcNB8ASp2NIWhwxMUp+/fevIs6xtHQkHR0+4kxaAkB9s52PN1eiVil5ZMl43N4OEs1n9rc+7fem3XnW5+r+nUtNNFDf7Dir72Bvw+8PRNDGH7ppLJOK0vrclgsNA87JPPXUUxw4cIC//e1vaDSn32VMnDiR9957j8GDB5/R+ZuabPj94keSnGymoaG9R/aea3wv23pS7FTA3iqrKFcfqkNcN2UoKQkGDh6zotWoUKuUop6TRSX5ZA8y4/UF+L+vbxVOuWBmPis7i/fheHDhGP72XnCBXlSSz7qt1aI6yaKS4SJnBUFHsGDmMBQKBeVbqpg1KYdPv6qMWIhD9ZWv99ZSOi0Pb4efWKOGuiY7ibE6Xnh/t2RNJjQU7fZrCvEHgtFGaChamsXA0tIi3N4OEsw6nO6OCKaaVq2idGou31TUs2RWAfsqmyOaJedOzyMpXodCAXqNmur6NtQxSvTaGF5fHRTcTLMYuOeGUaBAEAsNv0Z4T1LI9oxk06n7a84QvfmdS7MYWDAzX+S0v0/B/fva1ubwntMU34W4liiVCiyWyAGFIQyYmgzAH/7wB/bs2cOLL74Y1cHU19eTmpoKwKZNm1AqlcLvMsToSbGzzeEVHEzoMyvKKwR9spDMvlat4rY5Bdx69QiS4g0YdDHEGdSYdDHUdS6moXPoNNLUZre3g4duGkt9s42ctDhSEgycbHEKBftoKbl4sw6Xu4MHF43hVy/+G7fXx1e7TwhaXeoYJTqNCk+Hjx8UpfPHt74RFrzb5gTn1dxVWkT5lkpKp+aSlmSkvtnB6s5oBeAPy3Zw25wChmbEccvsAvyBAE63j9+/0SUxc/cN0uQCvU7FpKJ0IbrqHg3FqBS8u+Egt8y+BKe7A38ADNoYWu1eSqflotMo0Wli+O1rWymdliv5DCprW0V/o+XlFTx1/+S+pehKUIK7f+emFGcIDiZk63kruMsyOecEA8bJHDx4kBdeeIGcnBwWLVoEQEZGBn/5y18oLS3lxRdfJDU1lccee4ympiYUCgUmk4m//vWvxMQMmNvsU4QXO8Ppuna3L+ouLlqBNDXRIBry5fb6eH31Pkqn5hJn8hFvNmDszHmrY5QsLS3kpbK9mI1q4k3aCFXgH88dSUayicraNvRatWhBvm9eEVqtWtS5HoJWraK+ycGmnce45epLhPfG5KeK2FpJ8Tp+uqBYiAKS4nWUTMwW7f7vun4k67+uIic9L2IgmdmoRqeJ4Vcv/FsyqnJ7fbzwnjS5ICXBIDDdQseGCANlGw9TONRCYqxOIB6kWQzMvyKfb785xjVTcgXJnKLcROGc3Z+Bv1v/jNvr43ijI6JP5pxRdKMpQOtjxN+fKJpucsH9wsGAWX2HDRvGgQMHJN8rKysTfn7ttdf6yKKBj1Cx02wU936UfXE46gIUrQdCoVBELfQfO2nn2Ek7uemxeDr8PLtyJ2ajmrnT8xg5NJGDNVbWbqkSBCBz0uJoaXPyyxf/zdLSkbz3WRczzGxU09zmZnn5bkmplsVXDWf3oQbmTs+juq69y9awxSzkUJtbXcJgsvBha6H3G61ObrumEJ8/wB3XFJAUb6C20Y6nw49RFyPq54kWVaUmGkQSLvfcMIrGKBRgrUbJwpJ8fAE/b6/vYqnlDDLzxY4aZkwQ07B/PLeIQMDPPTeMor7ZIUwR/cn80SxbI6Yra9Uq6psdIsd2LiOGaFHyE3dPihK1DqCeGhlnBVlWphsuJlkZrVpJbkYCSfEG3tnQtZCfSgYk9Jnt+08K8jF3XleIzeFh75HmCLmZ2ZOG8M5nFeSkx2G1eXh99Xe4vUGZlT1HmhhfkMrLH+zFavOw92gTe440sfW7ei6fkMUXO46x62AjV07MYe/RJgCuuWyoIHcSLtUyY3wmJROziDNpKcpLpuyLQ+w50sRNVw5nWGYCKQkGhg6Ow+3t4NofDsXt9dPuCKoUFOcno9epyM9K4MpLsygcauGfn+7n24ONbNp5gsHJZtQxSl5ctYdvKho4VGNl8qh0GqwOZk7IpjDXQk6amW37Tkbc/9DBseRlJFCYa2FEdiIqBWSnxbG/spmrJw8RJG2aW51c9YNg3ahoaBJJCQbe/ewQuw41sm3fSW69+hL+HJam9PkDfFvRwJTRGfzhrR0crLFy53UjWXhFHgmxWganmPnmQINI4kenUVFV1yaS1ykenoJarRLJwvTGd67e6mL9thrRaz5/gGlj0ikeliJ8f5pbndw25xJ2VnTZ+sCC4qDUTQ/Qn/9XoX/bJ8vKyPj+kMiRF2TFodVIDxSL1qgX3gOhUCj423u78Pr8QgostNO+87pC3v0sqAZAAPxE7vadbml5fU9nRNFodREiECbF60hNNIiOD0m1LJiZLxLYvP/GUTjcHeg0wfSMy+MlJUHP0tKRfHekOULJOS8jjide3Sp8PnwHvmzNfuZOzxOnwlbt5tFbxgs1mDSLIWIKZ4goEKrjhEgJHm8HN1w+TJQeXFo6koA/wO3XFKLTxlC+pUo0nuBYg3TfjNPTIfz813d38X/uvBS7swNNjIqf3Toen99PTb1NGF8d6lMK2XPkeBt/fOubrsiV4Heksc2NXhuD2aDGpFWddUotWsRr0qlJTzSIe2iM6gHVUyPj7CA7mYsFp2CSJcXpzi5lEV4gVcBjS8ZhtXswGzUsLMknwayjvtnByvUVqFVKHrt1PG6PD6NezaawAWUAbQ635LVPNNiZMS6Lso2HyUmLE2RWGqxOyeNDI4NTLQYWXZlPS7uHZWvEzLbPdxzlpitHCOm1UFrM7fXhDwRTcdFqBP5u4a3b6+NgTdcsmNomB+9+dpD/vHks/gBoYoKeUd0pYikwvFJN6HVq/vdNcTf/S2V7+OWdEzla1cKwzHhJSZk0iwGvzy/UzkJNliGYjWpqGx0i5xUahRC6Tshhh85pdwXJBG9+uo+f3zqempN20Xekp6y0WEOMoBgQSsemJxmxu4O9RrGGsAK7Xy64X8iQncyFim5Ri1JBdCaZQX12MiAKsLk6aHN24HJ3kBSnIyvZiM3VgQJYue4AV182hLtKR9Jm94qGet09t4i311cIlN+s1FjunTcqotfl481HmTkhi4Ul+bz7WQW3zbmE11d/x5UTsyMGk91zQxFqlZJHbxlPa7sLt8fPqs8jp1A+sLAYa7tbcDDdKcqh5kkpJxaawRL+WmaqWYi2ALw+Pxq1iv2dtORN3xxj0ZXDMeqCc3Dqmm202tw4XR2i84ec3ckWB/4AdPgCgl0h+1/+YC//50cTOFjTKqpBLZk9QrBh5oRswcGE3/fc6XmCwx43PIUh6XEEAvD66r3UNjmEe7e5OiTHSD+8eCwn29y43B3Em7RY/KfxAp3zaJat2c+iknzMRo1IWqc36dQy+j9kJ3MhQiJque/GUSwqycfpCS4gob6MUErsjGVAFHD4RDvHGmyixe6BBcUkxmrwBwLcOCOfVIseh6tDtOiZjWpOtji5/dpCdGoVCgX89d1d/HhukUiPLDRXZVReEq9+tBcINl7OnZ7Hyx/sJWuQiQcXjiFAgDijln9++h37qqwCI8ykly7Cuzw+Wm1B+nR4oT/0/oryCm69ekSE7tcts0dgNqhFBfyFJfm8+ck+Qd0ZYM7kIfzfbrTk5WsPMG1spjBT5+e3TWB/VYtwLilnd++8UZL2O9y+CN20Nz/ZL6T4uqcSQ8f4AwGUSvjJ/NG4PR3EmTQCtTv83h9ZMk46JefuECZ8hnpw8gdHdxDhRX+n28fycmnHlxyvE6djZRXkCxKyk7kAIcXsef6dXcydnsfKdRWiBspwvakzSVm0ObwcPtEWQdd989N93HTVCFauO4jZqGbO5CG4vT5hIZ09KYfEWD31zQ7+/v5u2u1eFpXkc/20XE6ctAWlT7pFFQdrWrh8XCZaTQx7j7aw6vNDmI1qJhWlC/TeUD/O+EsGdRbzPYyIoiCs06h4Z0s1S2aPwO70Si6oCbF6vthezUM3jcXl7sDu8mDSq1ne2QuUmmgAhYLmViden18YgKZAEaF1FqIlx6gUwmvNbS7Wba0SHJmUs6trklZvdro7JG3OTjNzz9yRJMVLpz2VCgVFeRYO1VipOWkjPzOOBTOH4fYGec6hDYdRr5b8fF2TmJX2x7d2iFlp3ZyDLezZatTKqI5PVPOTVZAvWMhO5gLEqWa7h35eUV7BL26fcNZFVqvNI0nXnVKcwV862U+l43JZXl7B7dcU8PPbJuD2+jjRYOefa/aJpkCGdrQ5aWZeX/0dpVNz0euCfSSNVic5abH4AwF+9/o2oemwdFyuaFE2G9W4PT5BAFOrVnH7nAIWXzVcmKIZog5/tq2a66YMRalUkpxuiLKg2pk+PpM4kxqn20uCWccbn+zD6/OjVCqEXqAQXfrDfx2hqq4dZZRajlKJKK1mtblot3v5ePNRFswcRkpCZPSxbmtVBIliUUk+yfHSwpQKAiTE6Wm1ubnnhiJR9/yiknwGJRmorm1j2ZoDmI1q9JohoucV2nC4PR0RUdyd1xUKRIHw+6ptcYJCQawhhn1VYudw//zR3HFNAf4ApCeZojq+8JqfrIJ84UJ2MhcgojF7wp2J2+sj0JmeOttzKxWKiPOLhlwpIGuQCXWMSpRmCTmX0O6/qq6drEEmYpQKlsweQaPVhV4bw5ufBGfL76tsZnhWAkW5iWQPMndGEkbRdWeMy4pIIb22eh+LSvKFvpvMVDONVgeTRw1mkMXA/7y0hUUl+ZJjAXQaFXWNDv70lnh0sVat5B9hUzfdXh/L1hxgYUk+LrcPTRTVguHZCby4ajezJ+Xg9vgJBOCxW8fz9roD6LUxqFSRn2u3e0mzGPnPm8dSXdeOx+tn9eajKJVEOIF7541CoVQIabo0i4GHbhqLx9tBUkLQKXk6/ML9hDYAEamym8ehADGrLQBOd4ekevPR42386a1vhJ6c8PP95e1vO5+9gtc+2hth89LSkREp2T5TQZZTcn0O2clcgJCa5xGi04bQ04a3WH0MuemxEQv0kPQ40WI5d9owyfTRQzeNobbRjruzNvTGx/u45eoCWm0enG6fpM7YvfNG8WZnNHFXaZF4UZZoskQBqRYDr3y4l0ari0Ul+ahjlJxscXbRtTsX0QcWFuPy+LC2u1i9+Sh3XFPIaxLd+I/dMl5yERxkMfLKh3uYM3mIpNMKBGDKmAwGJ5sE+RqtWsUDC4tptLp44+PvIhbhRSX5/GnFN7TbvSwtHYnN6UGtUpIUb6DN7uYXt0+guc2FRq3CpIvht6936aPVNjn441s7mDs9j3izlkGxOo6EDSuLxp7z+f00Nrq4cmK26B6kosLQZsHt9fFcp0MJj3ZCz9cfCFDb5BCNHSAAKQk6MpOMosW9TwadySm58wLZyVyIkJjn0WB1CTtSgT3WOWTsrHZ1AchNN5MYF+xZCQA19Tbe2VAhLJbfHKgne5BZcjGrrG1Dq1axbO1+IXXW0ubiHx/vp3RaLlOKMyJqFKGhYICwM966t5ZrpuTiDwR49JbxbNhaxSVDkyLqOuVbqhienUCHL8ArH+xhypgM0iwGjDq1iKG2sCQftUqJxys9FsDl7ZBcBFVKBY1WF06Pjw3bqkWL6erNR5n1gxzKvjjM0tKRgo6Z2+ujpt4m1LVCi7BSCVmpsbzy0R6BsfZS2R7mTs9j/hX5fLO/jvxsi0hiJ9rwtWBKM1hzCaeoR9OJ02tjeH3TEWZemsWPry9Cr1NhbXczNCOONpuHBxeOweP1caLRLmisha7VTQg9eD6NSlA7aLS6RL05k0dOjvie9cWgszNKycmRTq9DdjLnCuf7y9qtkB9rUEc0wHXPpYt2daeyPwDtdg+vfLSXm0pGCNpcLe1uFpXkE2fSBmXuJRYzvz84WTK0+w1FN6Hjos2WDzUl1jY5+O5IIzMn5ogkVsIbI0OfWVFewf938ziOHG/F2+FnaWkRrTYXS68bye/f3I7ZqKZ0XNApeLzB9/0Bv/SO2qyTjFRiVEqGZcaRMyiWmROyIhSV05KC6b2XyvYE2X1un5BODDmH8EV4wcx8YQEP3Yc/EOCFVbv5rzsu5clXvxbd49vrK/jRNSOprGsDgtdutweVDJLjtMG/fecC/uan+9BpYiLu48fXj8Tj7YiIIBeW5NPQ4sQSrydGocDT4eevnarY4c8mJ60ritWqg7pzfj+88cm+iCgtquPog0Fnp03JyZHOOYHsZM4FevplPZeOqZvTabOfYldnUJ/W/sQ4HXMmDxE1RzZaXZ2U1d0U5Sby47lFvLiqqwi9tHQka7dUipyG2+tDr41Bq1axYVs1S7unw+iqJ+m0Qcd1+fisCIHJ8MbIENxeHzaXV1TkvueGIhpbnRF6baG03OBUI48uGcfBY1bRrByny0NqkiFi6uZLZbu578bR7D3SNVvn6slDhFkxCuC2OQWkJZnwen0cb7ALGmNSigBS/TihRtPummchUc9wpl2orpQUr8fnh4oTbVjidBQMiePBRWPYWdGAVqMS2GVKhQKb00tygkGS0v1fd0zgxEk7bQ43I3IShJ4ms1HNzAnZpCYaaLQGx16nJ5sw6mOwO7soz+FR2rjhKVjMmujf6XOsgny6lJxMPjg3kLXLuqE3tMvanF6eDBuSdSotMAGdjunJ17ayflsNn20/Rm5GAsnxOslj25xe6q0uAgFQ9WC+aTRtqR8UpaFQKCLsP3qileL8FBpbXShUSpRKBUdr29FplFw9OYeD1S3YnF6K8ix8e7CRH47O4NOvjnLlxBxBt2vNvyuZWJjOoWNWRmQnsvdoE1q1iunjMkhPMlJ5oo3BySamjhlM9qBY6prt+HwB7p5bxCdfHWXkUAuXj8/C5/ezaecJke2XDA1SdLtrh2Wmmvn2YINwHzsrGrhmylBMek2EXltVbRtpFhP/XLOfrNRYlEq4cmI2W/acIC8zkZY2J8kJBnTqGJLidHzyVSVVdTZSEw0sL6/gUI2V66bmUr6liiWzC3j/80NMGTMYtydIId/07QkO1liD4p31bezY38Ccy4ay50jwOTy4qJjkOD3pyUYu6dQzu25qLmu/rsLnCzBjXAbpyWYuGRrUOxuRnSAaK+3zB9hf2cLcy/NQqRTsrGigud3Nmq+OYjJoefrNHXx7sJH9lS2MzE1i7ZYqvv6unvysBFRKJV/uEj9Tnz9AamKwtrW/soVBiUY2bKtmzmVDGD8ilTc/3c+Xu06w90gzI3Mt5GfGoVYp2XOkiW8PNgLgcHUImnSXjUoj7hQaV72BU/2vdtfdC5EkXB4fCqUSq90T9X+it+yWtctk9Ap6wpQ5411UL4X0p9rVdbc/tGP+7xe+6qoF3FDEFztqhI7xO68rxOn2kpeRwKrPD4MimNrqTn9VKmFRST6bd59gUclw0pONtNu9bN59Qmi2DI86LHE63lqznx9dW0i708sf39pB6bTcCNs3fXOM+24czfPvdA1TW1payIp1kfRba7uLrEFmUboMQK9R8d5nByPSRvfdOIpvK+oZf0kaDS1O9DoVH248zKSidGwOryCrH9r9l07Npaa+nZKJ2dicHcI9dT9m5foKMlNNPLiwmJQEHXaXj0PHuyKo+Vfk4/J4UauUPLComLpmh0hz7Z4bpJs265sdPP9Ol4JC+ACz7jaUbTwsRGXR0puhz4TSnHZnh0AECH9vzLCkTop7P1VWDkvJ2VxeWto9ovrWL26f0D/tHuDowR5YxunQk3nhoYW9+7x2m0tMH43mjNocXqnTRkUoTx+yMzxf3t1+qYbBF97bzZTiDOH3lz/Yi93p47m3d3L//NHotSrJZ5CTFscluYnMnjSEL3bUcKzehtPdwdxpwyIW47+9t5vvjrawr8pKdX07L3T2f2zYVh0xr37e5cOIN6l59JZxLCrJ56HFY0mM00vSb2NUKhpaHMyZPISyjYdZua6Csi8OYzKouTLMwYTsWL72AEMGJ/DEK1/z7MqdPLN8JzMmZLN1by23zSlkw/Zq4fyhQnhOWhzlW6qwO6SbPlGEelwUpFoMnGh08v/+uYPl5UFbSiZm8/b6CtrsHcybMQy3u0OYMho6R32zQ/IZ1zaKmyfDB5h1t/Ou60eSnWYizWLg3nmjRM90YUl+xL2h4JQzYOLNWjZ9cyzi7/OT+aNFOmsCOqPy6gY7No9P+LnN1SE4/15FZ0rOpFNHDN/723u7+Mn80ZL/EzJ6DjmS6S10q6c8sngsT4f1iIgKnhK1l3izVhCBDN9FZ6aYSE80CFFKY5tb8h+8sc19dnnjUxRauzN9ohXjUztH54YK3SiC+l1mvRoCAclZLy99sJufLiimfEslt80ppLK2lbpmB9pTdIYHf+5ifTVaXUKuP3OQCaVCwftfHKK6zsbPb59AglmLWa/m0DErj94yjpfK9ggR1703juL11XuZeWmWKNUULM7v5cGFxRF2TCnOELTVuo7dw0M3jaG+2S7QpiEYgYTm4Vw7ZSitdpfk7lipUHD33CL8AR/eDn+E5lgo0vAHAvz9/T3cc0OR8H6Iqh2jUkTc391zi1i2VjxLJlpkEUyTKfhw02F2H27m/huLeGjxWI6fbKcgJ5E/r9wJwIIr8gVBTq1aidPjizhfiLFntbm554ZRLF+7X6jFFOQkkpkc/A63OcO+92GNnCGViO5SReeq6C6VbahtcpBg1siK0L0M2cn0BqKksJ5+4Ie02r2CiOSpji3IjuOeG0YJ4TsEF5vn3v5WlDILFcm7Lxg6bQ/+lN0LrXQtApmpJp66bzJ1LU78fmnRyPomB2UbDwtUYbNBzU/nFxMA/vJOsDgcovQqFQr8/gDtdi8uVweXj88SUjjBXfToqItx+O/hjqZs4+GIHo3jJ9vRaWJ4/OUtIsKBw+UhPcmMXqtkypgM4k26KBHGaRpNw47t8AUYkh7Lk6+KKcVb9hxn8+56HrppDOu+rooQ9LzzoaksDAAAIABJREFUukLsTi9vr6/gruuLsDul5WJCjaSl03JJSQjSgaUIC/fcUITH6yMj1Yzd4eWu0iKaW5202IL59d0HT3L33CJhyFqIIPD8u9/Sbvdy53WFVNa185d3gpM89VoVNfXt3HJ1AfVNjsihcAdPiiaZpnVuNsLTqT+ZP5oEswaTTi0s1N2/97+4fYLwu1ST6LMrd/J/7pyISRfT6+zMU40ikBWhexcDpvB/9OhR7rnnHl566SU++ugjJkyYQHx8vOgYn8/Hb37zG5544gneeOMN9Ho9hYWFZ3WdnhT+pQr9R0+0kpkay9Nvbuez7ceEQr5eG8MTr0qTAlwe32kLjwqlAkucjv2VLaKBVEMGmQV5+R6hG/Fgw7ZjXDLEQkaKib+88y3XTc0VXXNhST5rv66i3eFlf2ULjywZj1al4KUP9pI7OJ4vd50Qir57jwQLvwU5iRQPSybVYuSZ5TuF9OCsSTmsKD8QcY275xaREKdl+76TnGi0ceOMfPYdbRbd99qvq4QhXFq1imunDBWaHkPPb9fBRhZdmU+Hz8++yhYCgD/gF64VglatYtakbIZlJrDrYKNwneum5rJlT13EsZNGplFd386OAyeFa+2saGDu5cPYuPM4GSkmhudY2LC1iqljMinKs3DdlFysNjd2VwfZabHYXV6aW90clCAtXDcll9c+2suWvXXsO9rEktkFDLKYIggLOysauPIH2fz21a18vuMYW7+rZ8Ilg/jXt8c5VGPl1jmXoFYpmT4+g+K8ZDJTzazZUkmj1RV8PocauX5aLjsONHDJUAvvrD9ITnocDpeXFd2IBfuONnPL1Zew+ssjzBifxfXTcrl8bAa/f3O76Lgd+09y5aXZJJiC39umdg/7q1sYnp1IfbOddoeXQRaDQBAozLWw61BjxHc/KV7Pc29/G/zf0cVQ1+JEoVISbcjamRavpYbvfZ9haWcKufDfj/GrX/2KxYsXU1paSllZGb/85S/5xz/+ITrmww8/pLq6mrVr12K1Wrn++uuZNGkSGRkZ59Q2qdB7SnFGRM43tDOLls+OJlBo1HVFGiatioxkk4hKm5FswqT7fju9UxEPlswq4M1P91E6NZdBFgN1TQ6+2n1ClCY6fKwFTYyKWZNyMOiko63Rw5KxOTzYXV11ivB6T/emRG9HB6s3HWHBzGFkpphRKBDmtRi0Kuwur6jB9N55o2jvVgNJig9SrWvq7fztva5i+G1zClh81YiImTN1jXZSEvU8uGgMRl0Mx06288mXRyTp2Ku+OMjkUelCOgmCfSquznSS3w8vdg5SW7m+QhCwXF5eIVCALXF6bA43t8weIdRcQkX9d9YfEGbv1DY5eHfDQe64tlD6+9PuFjV7/r1sD4/cPJaakzZ+9/q2MLsLWbe1KqIXJzFWT5rFgF6jonRqLqmJBuJMGslGz6q6dqrrbFw/1cTQNBNHam2SNtWctGF3arGHjRAIbVA+3nw0Io0Xjboe+i7OnZ4nqFl/71RaH/TlyAhiQDiZpqYmvvvuO1599VUArrnmGn7zm9/Q3NxMYmKicNzHH3/M/PnzUSqVJCYmMnPmTD799FOWLl16Tu2TCr2jpVhcHunO8XijhhPNDsk6htvbAXSpJeemm0lN1NPm7MDr9ZFg1n7vezgVI64gK04YTGbUqXl7fYXkUC2nO8g6euTmsZKNix0dPp7+5w4eXFTc9QzCisjhTYlLZo3g7fUHg05HoaDN4WH911VcMyUXt8eHQRvD9u/qeOimsRw72U6HL0CMCuLMGhaVDMcfCKDTKNFpYmizewUHE7qv1zv1zR67dTxHjrfi8frZvPsEk4vSeWHVHtGCWFnXzriCDh5cOAanpwOdRsX7XxzC5vBi0mtYvlY8KyXOoBFJr4QcUEhnTSrldf+No4I6aB4fSoUCvVbFviqr6O9R2+RAHaXJ9WSLUxg70Gh14fb6UKmUESSGl8r2Cot1qLaj1ShJjNVyzw1FnGxxCdL8ofvp3suTPcjM3Ol5ZKYY2VfVSs1JW1Sb4kxaak7aKJ0WVGzYsK1aqDdt+uaYMNhsw7bqiO9M6BmGbA8XeO2V/pVz3JdzTnC+m7x7gNM6Gb/fz7Jlyzh48CBTp07liiuu4H//93/ZuHEjI0aM4Oc//7looT8XqK2tJTU1FZUqyPpQqVSkpKRQW1srunZtbS3p6enC72lpadTV1Z1T20BaEqO7lhcE//GSzFpJ+QylUsEzy3dG1DEATLrIf6TuEwy/787ulI1q3SZh/nhukbA7hi522X90du6HdMkeuXksKpWSVpublnYXng4/i0ryabd7hFHFoet0v+7QwXE8uLAYfyBAnEnLsk/3MWNCtqjL/8dziyj74iBFeSls2F7NvOl5uL3+iNHKMSqFpAN1e33sr2zp6ra/Il9SPLJ0ai4fbDwSQbF+ePFYoekwdPzy8goeu3W8sNiHduOA4FC7K0m7vT7+8s4uUX1pUclwyefS4fNHdNGHFuPw8cpadfTRAIOTjZIkk4duGht16FkoglhYks+rHwU14fIy4oSivZRNX+0+gSVOK/p7hGxVKmHJrAIKsoPRRGObm+MNNhbMHEa8WUdDi1MkXyN6joS1BBjUokX3tAPVBjIGqCLBaZ3Mk08+yddff82UKVP405/+xLp162htbeXBBx/k/fff5ze/+Q1//OMf+8LWPoHFYpJ8PTnZfOrPJZrIzYinttHGgWqrSMsr/J94SEYCQzISyM2Ip7ndSaJZT1qSkb1HGoMLn9UnKmQ/est4hmQkoFR2FcCPn7RJpraeeXg6g1Ok7Q/B7w9Q22inuc0ZTJEkGVEqFVj8AVE/Rbi94df2+wMcPSmdHgkEgiwjp8fH2s6O9+79JjqNivRkE8+/ExRW1GtVEYXx8KL0wpJ8OnwBrpmSG9Hl/+Kq3fzi9gl4vD6K88fh7fBFECeWl1fw4MJiyQV7WGYCL5Xt7rqJKNTcQRYDi68aQavNzeKrhhNn1JKcqKe5zRU1dRVyMPffOIrGVhdLZo1g2P/P3psHRlWebePXmX3PZCbbZA9JhoSQEBLCWjBgAiJKCEgCFAsqKFoLH337tm+1fa1fbfv1bd/609alLlVckEVAFBBIENxQRGU3ZIMskH2ZzL5kzvz+OHNOzplzBoICgs39F0zO8pztuZ/7vq/7upL1MBlVYc/DhuxWH+UDBpbNycKFLjv2HD6P9csK4HD6oJCL0dXv5BxDLhVjddlY9FuFkW1KmQR3zx3DIzANB3WO1itRUWJGSpyWEZGjo8WyW9LxwZct2HP4PMOsTQvPzSpMZuQK6GNtDjqtojGxyEjUQyQiEG0EnA3deO+Tc5hVmAyrwwODTs5JhQoRvJqiNKi7aOW9s1NyTZx39kazy80l4ey7fPfXemyXsss6mX379mHnzp0wGo1YsWIFiouL8fnnnyMiIgITJ07EnDlzrvqgQs1kMqGzsxN+vx9isRh+vx9dXV0wmUy87dra2pCXlweAH9kMx3p77SBDVkPR0Vp0d9suu6+MoOYJNpcXHZXkZUQhPlKB3l47s22cTgEggN5eO1RhUGPxBiWzD20dPQ7ByaCj1w4ZcYklzWVWQuYELS9HzTl3cH+xRDhlo1VJsWJeDtUwOYNarbMbHtt7nNCppWi8YIHPT3X5uTzUMSpKMhFnVKO1085Jz9C6N+EmdI93EAMOH/765teM5kzoNp39Tp7Dv788Fy6PF4tmZTLSwEISBnTah17J3zc/B7sPn0NhVizGpBmFoz+tHP/1kwno7HNiwOHl0dw73T4GKUbXtWh4MG02hw8Oly+oIKlEt8UFg1aGdz85BwCw2j08gs+qI83ISonE2Hsm4mKXDTGRSl4t6YGFudh2sA65mTG8exUO6tzZR6EI1y8twG2TU5EUq8Wru85gU9WQdPOew+fR1e+EWiFBlF6JpaVZ0KikgjWdpFgNIlWSoXeLAKQSEX48JxtWhweDfkp87tF7JgIgoVMKE7y6XF5ek+mTb32NuMgblwZmuHOJkH3r7/4aj00kIsIuzoFhOBmv1wudTgcAiIiIgEgkgkpFITDUajX8fv+ldr8qZjQakZ2djV27dqGsrAy7du1CdnY2L0132223YevWrZg9ezYsFguqq6vx5ptvXvPxsY2ddqJrDHKpGFNzYi8Z0l4JC+23pUW/LKvAZXLU9P5LZpsF0yNiMYGL3TZmRR2OHyzNpEUgkMar2Xh9JOOgaaMdCQ3hDb1mtVKG/904tCIX2sbjJVF9tBnlxRlIiFFDKhGjs9eBgFKCAbsXaxbmwRihQIAkEb1gLF54h1+ToMfy8rtUTYMkA2i8aBGk6W9utyI+WoNUk44XWb208zR+c+9EPLw4Dz0Wd0j9LQtRegUTwe0/0ow7p4+Cxe4GGQjgYo8TMwuTYLF5BVkE1i8twIvvUE2yOz9qxLrK8Xj7QB2HGXprdR3TRBt6rz4+doEXPdHOa3XZWGzYfYbpx6EdS4/Fjc1B1VCVXAqn28dJaS6bk4X3PmnkpL0itXJYXYNUPQFDCx+6V4buXzIZVXigPA8WhxfRkUr88cGp6La4YNQpYNTJ0NIpPOleVoPmJqxrANdJDuEa2GUhzEePHsWRI0cgk8nwwgsvgCAI2O12jB49Gq+//jocDgcWLlx4zQc6btw4/O1vf8PLL7+M2tpa/OEPf0BkZCRWr16NtLQ0xMbGwmw249ixY/jjH/+IrVu3Ys2aNZg6deoVnee7cpeFhUZGq2B1UnxjYqkYbq8fnRb3EBwzAETrFZiRn4DJuSbcOS2Vsw8btvlt4ZeX4isbDjdTr82DSJ0SRp0S3kE/xo4yYnSKAVkpBhyr7URqfAQiNHIc/aYTWakGpCfoeXDbY7XdmDYugdPcSHNu3T4tFTGRKoabqzPIXTZ5rAlbq2uxaJaZAy1eVTYWbo+f4dzq7HOgvDiDA4NeNmc0xCICSbE6EASBwUES/9h6Ap29DowdFYXX9tTg05NtOHyyHfExGhz6uhVzJqeguCARsyel4M19ZzlILD8ZQOmkZPgGSUSo5Rj0k7htciqS47QYnWKAIUIOt9cPrUoKq8OLw6faefc71qBCTKSacWb07zXn+7B+aQEKs2KgVkhgMqohl4rhcPupHl6CQIxBCWOEAh8eu8g7blq8DuMyo3HkdBvummWGTCrG3s+bGRj5mfO9DL/cgS9bePdq/ox0fHriIlbeMRaZSXrMn5EOh9OLiWNN2Fw1hHSjn9fcKWk4c74XfjKARTMzgpIPfMjzL35ciCm5JmQm6VE0Jg4dvQ40d9ggk0lAEGDg/3dMG4VtB6n6DQ1tf377KYbLLzpSic3Vddj7WTOyU43QaWQwRigwJviuON0UqObOaalUDUfIroQj8BrYd4EwX2vY9fcGYX7sscfw+OOP489//jNWrFiB+++/H6tXr8aTTz6JxMRE/P3vf7/iQX0bS09Px9atW3m/v/jii8y/xWIxHn/88esynrAmBI1k0epfrrOZXWC/FBU/fQ6nzw+VVDws+OV3WgkRQL/Di50fNXJW7TS1/CMri/DHV48iOU6D++bnYMehBlSUjBZcaYayCQNU1NPd7+IV7eUyMS5221HTbMEgGWBExqIiFNi0/yzunDHEY0YzAZQXZyA1XodzFwbw3ifnOE6iosQMgIKY082J9LjoIv/np9ux4JYMuLyDKClK4UB+5VJKeyW01qSUi+H1kbA7B5m/hSvekyTQeNEieG/6rR78fetxVJSYoVZI4PZygQzL5mTBnKwXPG6cUY033q9BeXEG9h1pwpRck+B2afERjAR0eXEGEmPUMOgUqG/tR25GDF569xRTU1pbmQ+3x884GPZY6RqSyaiCx0uhv0L54D74sgVnzvdh54eNWDYnC2oFhcyjI6K1bIYFVq1KiMqI5k774KsWXOi2cxg16IhrxbycS34LNzXT8k0Ku76sk0lISMALL7zA+e3AgQOwWCyIjIy8ZgO7qe0StPrhOptDX/LhprbSkw1UHnUYL9p3EYayOn34x5YTvI/+kXuKEKGUwuKgIND1rQPot9Vh7pRUGHTCTk2IjLGkKIVH3bKpqg6/XlnEbF/fOoC/vPEVAGpiKy/OwHsfNXK6z20OH6IjlVDKRIxDZJ87FOnFNo/PD51aitkhWjV0yszm8GHNwjy88h43VfXs2yfxu9WTMeDwoKnNxtQhqo82h4XlzpqQLHhvBhweAFTq6sFFeQybAH2ujfvO4j+XF/LSdPfNz2FQXy+/ewZlM9JBgKAaVo80Y3p+IkQiIC0+Al6fDxUlmTDqlOjoc+LV3d+gpIiCV7PVRQGgx+KEw82nkaHvJd3t33jRCrVCwltALSk1c8ZeXpyB6fmJ2HKA2qa1kwt/Zv59CXCEkOT25qo6PPHAFJhTDJxaT2ha7LrJPF8ruwlh19+qT2b37t244447rvZYfrDGebEvQS7IfsmvycfwHVZC4TjTfD4SOqMUA04fJ6J4/f2zyE7R46G78jiMwJWlZrzzYQNvkow1qDjHpyc7u9MHBAJYOS8br+6uYbafPSkFVV80Y7w5FgQCeGzVZHT1OxGplaOtx45zFz1YPjcLb7x/lucsaBMEWkRr8OI73AhnU1UdhZxqt8HqcAuu6k/Ud2NTVR2vXrH78Hk8ck8RGlot8HhJ5vePj13gOEe6KK9TSnHPHdnISIzEgEP4HRgkA/jsVBun1uJw+zhqlSAAl9ePY7WdPOj1A+W5UMjEHAEyuUyMn9yejUitAp19TkbzZlXZWMgkfl6thqaNKcqOwW/++Rm0ainWlOfhL6zOf61aCo+PRKxByXDckYEAD0VHU96we2XCPR+a+0/ovjjcviFUWRiQS0K0+qasa9zM9q2czH//93+POJkrsNA01XBe8mtW5KNXQsH+gpYux7CKn5fiTLM6qWbH0Ilo5oRkHK/txG/vm4TTjT0gSTCTrN1JpdjOnO8DAkC/bUj8LEqv4AEGls0ZTSlLev1QyMSIi1KhpcOO+tYBCrq6rIATCQHUKvs3905Ed78LKqUUHs8QQ8DHxy5gzcI8DgtAZamZKZyHatY3d9iw5UAdKkrMYVNg9LZsKn+bw4ea8/2IiVRi64E6Jg1VOikF+480oaIkEwadEp19TmzcR0lSry4bC4fTCxERbqINoHRiCtWIq1Og2+JEtF6FKL0CPRY3TEYVJX/t9aP8lkweVPmfO07hV3dPYH6L0isgIghs3F/Li7he2nk6+O8GlBdnID5ajR6LC2IxAZ1azqD+tJBymBxCn6HJqMKq+bnw+AYRFaFEcowGXRYnqo60wOb0Mk21APDYqkkgSRJJMRqGNYO9SCgpSrnstxEuE/CXh6fhF8sK0NhmZRgz0uN1N0Xa6Wa1b+VkAqGV8RG7pLHTVEKdzUIpq2uqef4tmrq0KqlgF79OKUGf1YP2Xif8JIn1SwvQ1D4AkgR2HGrA7EkpUMgIxEWp8RwroqkoMUNEADs/bGQcCx3dhObjtWopXB6qX8PldWLP4fO480dp+PmyAgz6SWhVMnT1OxjVRvoc5cUZuNBlg1gkwpMbv0ZynAbrlxaADJBo6bDD6fJyogHaAQpp1tP3JZxz2sOKkOhIgv03m8OHR++ZiLqWfpiiqNpJe68T482xHDYCAHiRYXjmM0AsKTWjvcfB1Cdee/8sKkvNeP39Gtw+NQ1Hz7RzpKmXlJoFV/2ewaEU2KzCZJ4+DNtRGoPkrjSMu2xGOl7fU4O7546BSATcc8cYxBrUcLp9WFI6GtVHmznPkNYjYvezUDWUFtw1KxN7P29CS4edUet0uilC2XijihN1i0QE0uJ10KpkMEWpOBFyKCV/uEyA1emFd5Bb51pbkT/sT+c7GQFc7LKjo2d4C7sfin0rJzNhwoSrPY4ftoWkqQxaOSXwdKmU1TUs8n2b4uelONPo/gqnexCv7vqa83FvqqpDAGZEaKT4+bKCIN2LGFuqarFoZiYzifZY3Kg60oz1Swvg8oRfEdOoMqVMjPNtVmhVEryy6wxKilIwLsOAdZXj4Q+QaO2wY0swcojSK1BRkon0BD3+tOEolsw2Qy4VweYaFKzbhGrWryobi83V1AS7aGYm9n8+xLE2Js2I57ad4IAL5FKKeqVsRjqna713wAWRCMGmzixc7HaEZSO42G2HUi4BAfAkn7cHJ0g6bUQ7hM1VdXhs9WScrO9mmiTD9b4oZGI8uHAsOvrciNYrBVOVsQYVlpSOhkYpw7ypadiwpwZatRRj0gxIjNWgpdOGr852YGpuPMeBLCk1w08GmGMKFfHpMb/wzmmUzUhHfesAjDolk8JjL3yYd5KgmC7+tOFLaNVSitomVoMEo4r3bYTLBMilEjy95egVvftXxW7Sbv2rYcN2Mk899RTz77FjxzL/l8lkiIuLw/Tp0xEVFXX1R/hDMQFa/csW765Rke9b1XuCnGnRekVY/ZnWLpvgcd1eP/bsP884i6m5sZgzJQ0vv3cGd04fhfLiDEjEBBJjtJBKCGhVKs4qm8+/dZpRdbxvPsWyvamqFlplDpQKKbr6XRzn0WNxY0t1PX6+jKK92f3peSwszoBIRAj2hWw7yO0t0agkWFpK9bA8v/0k2nudDK8YDUBgH+PBRXlMpEKbXEqJie38qBFLSs3YfugbSMUi/HRxPpaUmkEGKCQWQIEg4oxqSMQiRGhlIP0UUzJJBrD9UAOProbtcE6yakMr5mUjEAjwIq/75uegpcOGpFgtntt+mqM0KuTU756bhcQYDUM2+qcNRxmCz6Wzs/Dn17gUQ5uq6vDbeycNq4jPjvo6+pyXnPzZiyOPxc9EVn9+aCrv2wiXCWCn9Ib97l8Fu6lRbd/Rhu1kmpqaUFVVhby8PJhMJrS3t+PkyZOYNWsWDh48iMcffxxPP/00ZsyYcS3He2PaTdbc9a3rPeGcXjDqiolUYschYUQXW2gsN92AM+f7MX18YpAwlBIs85Mk+vs8iI5UMQzJl5ugaCTVzo8aYdSrMGB3IzNJj9ULxuLFd04zk2F8tBoapQwmowrtvU5sP9RAoagQwCMri1DfakF8lAavv/8N2nudqG8dYMZPp40qSsy8on97rxMuD1Vf6hlwQymTgAz4cduUVCYFxU6b0ZPwklIzAgB+z9K9WTEvG77BAIcZes3CXCTEqBGlVzLMBKEpOvoes2tDWrUUHm/wXLPNnNoPXStaVZYDrVqKY7WdDAhByKm//v5Z/HpFEe780Si4PH4smW2GWiHFy++eweJbM8MsLAYZB06PUei9kEspzaAHF+Xhjb01vOOwJ/8rWhyFyQRYXeEJaq+l3fSotu9gw3YyJEniySefRGlpKfNbdXU1du3ahS1btmDHjh343//9338/J3MThsHfut5zKWcaAIw6GdYszMXz27niWDSiq8fixsfHLyDOqOKRJlYfbcGsCckQEcC2Qw1YWJyB8uIMJMdpwqOMMCTuVVlqZhQv//Xel3j0niL8dtVEtHc7GP4suZTi9Np2sB7tvUNRxd+3HofN4cPDd+Xh9mlpHEQavT2AsLQzKXERkEpEcLt9sNjcUMol2PtZE0cagZ028/j8iDGoeFxsVoePuS/0b89vP8Xch8pSM0gygMQYLTbsPsNENJWlZhw9084UzytKzFDKhiQFYiKpPhYaNUaP46WdlIMGgO0H61FRkglTlEZwMvQO+qHTyLFxH0XkuWk/5YgSY4Sfz6A/gC0H6piUViiSju5reeiuPKTFaQGCEJTKZiZ/AlArpZyoj77+sA5CYFGkU0kY5uerXuu8hN2s3fpXw4btZD755BP87W9/4/w2c+ZM/PKXvwQAzJ8/H7///e+v7uhuArspw2DWKs/u9kEulcDh9g1RfQh9bMNwplaHD1uq6xiiRK2KQrGxOadobrPQ/Dw9GWmUUuw41MhEGp19TsEJir2KT4rVMj0itExzj8UN76Afr7z3DedcL+48jXWV49HUYYVCJkZ6YgTunktBd6ViQCQmsH7peFzoskMkIhChkeGWgiSQgQCUcjHuF6Cd+cfblJNaUmrG+581AaDqECIRYIxQcJo+6TG7PX7eZE4GAoITPBkI4KlNx/HL5YX4nze+QnKcBmsWUto5WrUUvRYXZk9O5dRF7pufg+Q4DabkxnN6ftjwajoiBCjZbIIg0NJhE5wMpRIxnt/2NbRqKVJMlFpnpFYGjVIimHL0kyQitXKQZACtnTZkJOrxyMoiDJIklDIpfIODKFheyJEkD7vwAf/dox3rktlZsDi8AEEwNDVhLdjgvHGfgDQ0eeldv6tdUyDPDW7DdjLJycl46623sHz5cua3TZs2ITk5GQDQ398PpVJ59Ud4g9tNGwYHAJ1Kios9TqYQeqkobDjO1GL3MsSXIgKwOX346NgFrK3MR0evAwnR2iFuM5Z5fH7EGVR4ZdcZLJ6VycgA0LxvK+Zl4zf3TsS5iwNIjtPihR2nOKt42sGwUzBd/S5e7w19LhBAQrQa7T1OPL3lOAMOKClKQbReic5+O7NS/sWPCyjCVAJwuAbxyYmLKJuRjlEJOjS12zhknmxafFqW+o29NYIs0wMOPkNyuEiJFu46327FklIz1Eopw4kml4o57Nn0Nb787hmsqxzPgy+zUWN0qooMBFBSlMIQmgrxsYmJAMdpadVSVJaMxu//dZQpwscaVOizulAVZOAunZjCY5Een2mERilBr5VAR78LPjIAo1YGkOEXPiICvHev6kgzls7J4tyHtRX58AUItHcLo7fY7zANUadrOtf8Ww0u7J76eTE6eu03Tbf+1bBhO5knnngCP/vZz/Diiy8iNjYWnZ2dEIvFDK3M+fPnsW7dums20BvVbuYw+EqisOE4U0MEVRgOXTnv+rgRsyenYsPuM1izME/wfkVoZXj4Lko/Zmt1LUNnEqVXYM+n5yAWEVAppGjrtmN6fiJkUpFg2qjqSDOzWg/XT9HeY4fHR2JLNTXRCBXvzSGIAAAgAElEQVS76WMZdAr8ncV0AAAtHXbcvyBXkMwzOU6L5bdlwesjGeiyw0V12EfplTDoFPB4BuH2+XkRWoRayouU6GuRS8UwRalBAHj9/RrOMwtH0R8uMqIL7Q/dlYcItQwdfQ5olHKmoE7XzkAAqXFaWOwePLf9FEceoKwwnRm7FlKQZACdfQ4kx+lw5/RR8Hj9PBLPjfvOwpw8CY1tVk5Kdc3CXIxLNwCk8MLnwUV5PDbn6fmJeEZAefZS6pnf+4IwACTEaIYYk/8NHAxwBU4mJycH+/btw4kTJ9DV1YXo6Gjk5+dDKqUeTlFREYqKiq7ZQG9Uu5nD4Cv56IbjTEk/GZbuw6iTIS2uEHbPIFaV5XDqJEtKzXjmbUo/Zm3lOEwOSfGsWZiHLdW1mD05BbGRKry2h6qZ0FBbkQjIy4hGbUsfpucnMukgIU2WB8pzUXWkCbmZMZdEsNGsxq/sOsOTaV5VNpaRUuallcQibD1Qz6vp+Pwk7vxROqe3Y8W8bFSWmhETSUkdIxDAa+/XUJQvEUqmlkOn4l7ZdYZhaGbXeMLBlCVi4cgoNQiv3rS/FrMnpcCgk2PA7mG2ZbOHr63MZxBtHKcVBF6Ea5wNpwxrdw2is8/FUcp8fvspPH7/ZMTo5IILn+e2nWScB22hx6ffBVr75oMvW3gLppt5QXgz22VZmDkbi8WIj49HZmYmEhISGKXKH5J9GxZmHntylOq6OZjvwupKiEU4+NUF+Fn6OXKpMIvtcBhgw7E8T8szIUIpg1xKac4ABIwRSswsTEJynA77jjShx+JGpE6OAnMsegdcGJ1iQGefAzanD8frujF7UioG/QG89/E5zJ+RjrNN/bA5fWi4YMG0vHi09zqwaX8dTjb0wOkepM7tD+DWCUmYMCYW6QkRuLUoGZv21+Ke+WOhVUqRkx6Fk/U9yEo14GRDj8C445FqioDX50d2mgFZqRTj9L7PmxAfpUZhdixONgyxQleWmrHv8ybcNiUVsyelYEqeCRqlFOOzYjA118Q4GPr4pxt7seCWdAz6B/H2gXrkpEchPVGPpBgtfH4SERo5xmVEISFGy9wjNgNyZ78Dd0wbBblMhDunj0Jdcz/sLh8zlg+OtvCYq5eUmrHlQB2O1nTC7vLhbFM/EmN1IADkpBs5rMyVpWYOS8GcScn49GQ7/GQAOaOMaGi1YO6UNIY5mb6umvN9WFCcgU9PtPHeren5CXhp52mcbOhBQ6sF5cUZaOm0ItUUgX67F2QgIPgOzZ2aiq9qht698lsy8Nkpaiy0o9t2sAGHT7WjodWCu2ZloqnDirzMaIZh/FqzGA/Hvsv3eq3te2NhHrFh2E1IWgdcYRQ2jObQYa0USSDeqES/TY2L3XaGp4qeKOh0TGiRWiQCqo+24Papaag60swUblNNEdh2sA79No+gxs0/3znFrPhpCLLN4WXqCmUz0pFq0gqOmyAISMQESDLA0ThZvSAXvQNubD9Yz4wjMykSm6rOwu70QauS8VKGgTCpK6fbh0NfXcCsohQ8v/0kSiel4KlNQ/veNz+Hgwij91MrxbwIYs3CPFgdbjhcfqYusv9IE8qLM5ASp4VcJsazIY2jHh/FpEAQwIDDg4qSTAQC4KUiH1yUh36bi+Gio5krPD4+gMHj88Nic/PYCh5clIet1bVDPUgAqo40U2lNmRhPbz6OJx6YIvgsEqJUeGRlEWqa+kCSwOaqswySUSgS3bivFpWlZu67d5OyGN/sNuJk/p3tSj+6yzjTcE5LJCLQwi7GkkBOij4IZW68ZMqK7oHJTIrEjkONTK0lxaRFc7uNoaUHqAlrbWU+PF4/uoIa8QBQcasZIhGQHKuFyaiCSEQw9YctB+o4lDbslNiG3WegUUlx1ywz1i8dD41SCpvLi7oWCwM1ZheQf3vfJDjcPpy/aGVqCPR1CElAm4wqKOUSzCpKQVuPHbMnpfDSjbRI2qaqWk56MCMxEv/Yyk0rPb/9JB5ZWYRzbQNYPjcb7T0OjB8di+qjzVg5bwzqWmyCMOFuy5DyJ63c6fZ4UTIxGR4fCblUBLmUQEevG/tZDj49QQfPICnoFC50OVB9tJlxKCKCgE4tQ1GOibcQSIhS4+2D9UGHNSj8DhEERwAOACx2KhXbMyCsmhofreG/zzfpgvBmthEn8+9uV/OjC4FGK+VU9/3h050Mqy+7GCuXiJjid7imS5EIWF02FgN2N9ZW5qO10waSDODAF82YNDaeA4+uKBmNQCAAm9MLpZyqj5ROSuFMaqsXjIWVVX8AwKK0GY9BMgARCLz+/jfw+UlMyY3H3zZyKVPCUcGcbuwRZGL2+PgS0CajCotmZnLQUasXjBWUK441qGAyqjjXsuNQI682Q0VGg0AAPKmC3gGqRiWEHGMrf7608zTKizMAAO9/RqXolpSORnOHQ9Cx/uT2LB6AYc3CXEbsjU00+p/LCwUXEv/x4wLUtw7AZFRBLpUgQg088cAUONw+ZuHT0sVXwWzvdcLh9kGnlgk6Oo3yW0QpV9pYfZM1Yn8fNuJkRuzqGgsa/ft/HeWsWPccPs8pxvZZPdh/pIkhrRSaKJJitXjj/RrcPTcbTR02BhEGAAMOL9ZWUuSGeq0cbo8PvsEAXtn1DaL0CtxzRw6v4fHFd07jsdWTeFQrpZNSsGH3N1gxbwwcrkH4/KTg/pvCRCVyaXgmZrlUDJfbj4+PX8Cj91Cs0Eq5hAcvfvGd07wCt1wqRr/NjQcXjcMfXvlCMNJjT/piMcGLhjZV1aGiJJPDugACyEkz4O9bj/PSZ2QggI37qLTWx8cvICs1Er0WN8OHxnZqSrkUVUeaGDE5hUwMu9MrGDGJRcLOuaXDhuwUPeZMScNv/vkZJ4JJjlYDAer5mowqSjo6mGr7+NgF6NUyiKUiBvbOBlxEqK8QMXaljdU3YSP292E3hZN5/PHH8dlnn0Emk0GlUuHRRx9Fbm4ub7vt27fjj3/8IxISEgAAiYmJeOaZZ673cP/tTQghxJ4QafSaXitHS4cdL717CvOmpgk2XdI9MGKxiFc7qW8dwNObj2P90gK0tFuh08gZSYIeixvNHcI9OVa7F16fj8MYTdcwei1Uf828qWlo7RTePzQqYTtR9nZsJuaqI824bUoqGi9aKLhvPymoIhlrGOJto9FwNqcXdS39YSM9AEwfiijMRO4bpDwgGzmWM8og6AwQoGhpctMNiDOq8KdXuYuFz061Ybw5FiIRkBSrwayiFE7ktHxuFtZW5vOiKaWcL1ZHLyTSTDr8D0uLxuPjwul1agkqZ4/mMHmvWZgLnVoKq8OHbcH6GM03t+1gPX61vBCQDh+cdKWN1eG2/+19k6BRSEaimqDdFE5mxowZeOSRRyCVSnHw4EGsX78e1dXVgttOnToVTz/99HUe4YixLRw0mp506WIsu4az+/B5LCrOwPplBWhqG+Boz8ilYgzY3IiPVuPBu/I4E80D5bkgQMLt9ePVYDGfhkgDwtDe3gEXTFEaRjsGBNV3UXWkGasX5MI3SEGx2cSR7P09XhLVR5tRXpyBhGg1pFIxNgSdIXu7tHgdHllZBLd3ENPzE/HeJ+cAAGsrxuN824CgimRslBK/uXcS6lr64PGSqDrShLJbMgEEBMeSHKvDzxbno9viQqRWBgTA0O2zJaNDmaXvm5+Dtm47U5ynOd5iDSo4XF4sKs7AmfP9PJobGtr95FtU93+qKYJZGNDbvBGUH1hSakasQQVCRMCgk8NidWPlvGwMOHwMq3SkVo62bnt4AIHDC51KitYuJ/Pc6b89v/0UVU+0e9He6+Sk5gCgx+a5osK+3eXjgBLoqC1cH0249/xkQw92ftg4EtUE7aZwMjNnzmT+nZ+fj46ODpAkCVGo8MeI3RAWDmUmIgguei0AJMWosa5yPEQi4Mm3jkGrluLOH43ikEuuWZQHqZiAXCZBerwc6yrHo6XTiqRYLXosLvgGxYg1qHH/glwoFWKQQV0bEQFeWmzZnNHw+khsra7lsScvKTXj2W0nUFKUDI/Pjw++bOFFLMvmjAZJBrC0NAvdFhfe/bgRMwuTcNuUNE4vzf0LxuK13d/gtimpSE+I4LBCt3ZYER+lwV/f5K7cNwXrEy7PIDIS9WhqH0BuRgxeevcUAPD6iypLzfjXrtOYNSEZW6rrgnWpTADAj+dko9/mwtEzHSi7JRMdvXasWzIeUjGB+tYBONw+ho16xbxsKGQShv6GvhdymUhwEqWbP8sK08M3gpIBiEQEnmJFM8vmZEEhE3F46+5fMBbReiVauuyC74xeLUOvzYuapr6wTijc+9bQOgCPxz+8iZ4A+u1e5jmxI9BwfTTh5QREl42C/p3spnAybHvzzTdRXFwc1sF88cUXKCsrg0ajwerVq1FcXHx9BzhigiizBxflYZRJC42Cm0Los3rQ2e+AXqOgVrMWP9775BzKZqRDJhUhzaTDS++eRnuvk0mRWOyeYJ3BjBi9AoRIxIE+P7goD70Ddjjcfpyq72KIIwf9AZBBnZOaZgu6B9wom5GOWIMK3RYXUwBPitUyRIy0zDGVGhriSKsoMXPqQ3dMS+PovkglBBbfmgmCINB4cYAD57W5BuHutApOmucuDnDAAx98NVQDsbt8zDlokTWbw8chCzXolBynen95LjbsPsPcvwcX5eFUQxdyM2LQY3Fj+6EG3HvHWDy1+RgnfefxkUhP0F2y9gQifCOoKUrNq2dt3HcW5cUZnN9eeIfikvv42AWeQ3948Th0W9xobBsIex69Wib4vrHF4piJ/hJFeqvTx5Bm0mPbXFWHR1YW8dGRwX1EBARF5djP84anl7oOdkM4mfLycrS1tQn+7fDhw0zT5+7du/Hee+/hzTffFNy2uLgYt99+OxQKBb755husXr0ar732GtLT04c9FqNRI/h7dLR22Me43nYjjs1o0CA9UY8+mwsGrRKmKPWQ/jrLvAECTo8fLZ1DxIx03WBJ6Whenv757aewrnI86GZRU7QG//elI5xtntt2koE+0+zMtKTyklIzUuMjmLoNTeG/pbqO6dUJ7XGhqGpG4433a3gpMY/Pj/HmWDy7jU+C+bvVk/G7Fz9nCuZLSs2ICdZcxGG68UlyqHvd6/Pj3jty8K+gY9v/eTMv+golC+0M0WR5YccpphZG35tfryxCZ68DUXoFpGIRQFA1GCFxuBXzsrFhdw3z20N3jcOm/WeZMZ+q7+LV0u4vz4XFKgwrJkM6nT0+P9p67CidlMLpfxqTZkScUYWf/fUQym5JF3RCP6vIR1piJEQiAkaDBoYIBY7VdXNUTgHAQ5IYJAhc7LajtrkfZIACDayYl4MpuSaIRAQ6GroFx+v2+nH4dCezeMhM0mNCdiyzz24WkAIBYPfh85g1IZl5HnFGDaKjuXPKjfi90nYtxnZDOJkdO3Zcdpuqqio8+eSTePXVV8OKoxkMBubfY8aMQUFBAU6ePHlFTqa3104RIrIsOlqL7m7bsI9xPe1GHltCjDbI0xRAb69dcBuZCCAICMJrE2OEaed9fkpWeP+RZkrLPkz9hw04oOtBOaOisHHvN5xz0cSU4Xp1Hr13Iqx2N5bOHo22HifDyEwXt0Ph11F6BeZOScWAw4N1S/Ihk4hwql6BAIagxdkpekEZ589OtYXlUZs9KQVVX1COJjFGDaVcipd2DpGF3jc/h1eXoO8F+/8Wqwdurx9rFuZCRIhgsXmYaIZ97S/tPI3/s3Q81i0ZD4kI6Ox34VR9J1OA/+DLFqyaT0VK7In27QN1uPv2MWFTpmyTS8Xw+kh88FULpe9DADmjjEgwUCk0Om0Z2oRLsyez3yulTMzIedNmMqpgGfCgpd3OA5Vs2H0GcZEK6JRSqIKAkdDxBgLgpPeWlJoRHSGHRi6BSi6BzeHj3HMaOEEjzWSiAOf7vJG/1287NpGICLs4B24QJ3M5O3jwIP70pz/hlVdeQWJiYtjtOjs7ERsbCwC4ePEijh8/jgcffPB6DXPEvo0FqInA5vDhs1NtDBRWKZMgxiDMD9ZjcUFEEFg+NxsGnfA2oXozAIFVZTkgQGLJ7Cy4vYP43erJGLB7IBYRuH/BWHRbXIIOa8Duwca9tbhtSipnwnlwUR6WzRmN6EglM4YovYJXU1pSasYd09PxBovYsqbZAou9Fo+sLILDPYhIrRxPbz6G6fmJYXnU2nvsKMyKRapJh20H6zA1L55DFtrZ5wiLFmP/v6PPifQEHfqtXmbipbv3Q6/9fJsVOz9sxLI5WTBGyKBIjcLm/bXMZB9AQLDoLhMTjHAcfR/uuWMMB2HG7tNho96KsmIADNU8aOg13YiaHKuD10uN1epipb9UEg4jNZVezUNNkzCAoWxGOpPOEkq5PXRXHjbs5pJ8bqqqQ2ZyJDRyieA+Dy8eh0itDFPHxo6wCQTtirjLvi9bunQpAODQoUPYtGkTNm3ahNtuuw1KpRKPPvooAGDUqFF44YUX8MQTT2Dz5s3YvXs3HnrooSsWUfs23GXfp/0QxiaXipCdakSERo6X3z2Dw6fa8WVNJwrMMZiQHcvhmlqzMBfvfXwOn5xsx1c1XZg+zoTsUUYcr+vmcG7t/6IZTjelgjh/+igYI5SwObxo7rTjmbdP4Og3nRiXGQ2RiMD/bvwada39mDctjeHDGhqbGLMnpaAwKxbPbuNyjx2r7caoBD22H2pAeXEGwyn29gf1nO3ONvUjPlqD5FgdzpzvZY5td/kwcUwsLHYP3vuoEWW3ZMDh9uFEPZ9HbWqeCX1WN6QSEcRiAhEaBQxaBVyeQez/ohlf13ZhZkEistMMHD61VWVjse/zJg6n2b4jTZicY+LAb8cEuchCrz0rhTpezfk+lE5MwVObjsFi9+LM+V6cPteLpBgt6gX2izWqYYxQ4Ef58cg3xyAjSY9BP4mdH53D+qUFKC5IwJ3TUiERi3Do64ucZ/fm3rOIj9YiMUaFtHg9vj7bxfDUjcuMxpYDFEfdmFFR+LquG10WNzbuo/aZkmtCUVY0JueaUDY9DT5/gKLJiaWcMMNrRwaQm2FERkIEk3oN5SAkCOC9T5r4zyLXhEiNTHCfpGg1tAopc8xv+018H3atuMuIQCB0Sv33tpF02dWzKxmb1eXDr549zItI/vLwNJBkYIj2JtgXwabB6Rxwoc9KfRwKmQQv7TzFFLrvm5+Dqi+a0dJhR2WpGQSoonZ8tBq9Ay7EGZTo6ndj475aJMdpcNuUNLzAQlk9UJ4LjVKCc21WhmeNtii9AvfekYOmDhsUMhEIEIjQyPH0luO866soMUNEgHMMuZTSgqGpcX7x4wLo1DL84ZWjvPuwfmkB2nrsTL/Nxn21HNhxv80FsUiEvZ81DTUsBoBTDV24Y3o6eixOpJoiUN9qwaA/gNR4Lf7fhi851yKUpqNrG1F6BR5aNA5nm/sBUPBeAJg3NQ0RGjkHmcYuulMREolYgwqxBiriszm90GvkjMhYr82Lr2q7QJJggA5yqRiPrCzC89tPYnp+Io+nToj5ee9nTXhs1RQqRSvQKMm+Hvr4SaFktixwgFolxW+e/4z3LP7806nQKb5dMf+H8r2y7QeRLhuxH76F6znos3mQHKUeQuiQQRoclRRWpw8tXQ6oVVKG8HJhcQbDDoAAsCXIIgwAyXFaDNg8PGVLhUwclDjWQq0QY13leLi8g1DIxNCqJPjDK1/yemai9JR2zlMhDYcGXXj4dqppCK1FT4y0g5FLKb6vpFhCsNGzvZdyMGsW5uGPrx4VLNT/dPE4/GTeGPx/b3FJRnd93Ihbi1IYChuTUYXRybmccdLUOo/eMxF9A2509Dk5Dmbe1DT8+bUvOWOXSkTYsLuGES1LitVALCJwocuOWROScay2E2qlFJuquDDx3UEH9ItlBYjWK9BrdVOSykEHQwMfegfcmD4+kSO1/JPbs5AYo0XvgBvrluRjx6EG1LcOYOO+WlSUZKLP5kKcTnHJhuCdHzXi4cXj+IqYIY7JZFTxmASWlJp5daURaplL24iTGbEbwq5I60NgMlizMBdbquvg8fqhVkp5BWC5VAyvl2QcDDCUY//1yiL02/rQ1m3H3s+bOJP3usp8pvi8bM5optZSUsQns9xUVYfHVk/ibMd2PtsO1gUVJJVQyqXY+WE9U2dIjY/Atg/qAMThw69bOYV0OnpZMS8HfVZ30OGJeLWbZ7aewO8fmILy4gxIxARMUWoEAgGU3ZLJUc6cnp+IF945xXNmFSWjsfuTRsz70Sj4SZKp7whd68Z9tQwc2WPxo/poM6+59Jd3T8D/vP4l7x6trcxHZ58DPQMu/JXFC0cDH2YWJsHq8KGjzwkRQWDp7NGw2DwIBID4KA2e336SiVQfKM/FzEIfth9qRKRWAYNWCYCKfIUWLanxOioSUUp5ksuhjqm914ltB+sZOXEaPWaKUiPOoGIisRFqmUvbiJMZsRvChIqov1hWAAC8HgWhyWD/501YOicLz2w9Aa1ayutfWDEvG4QIHLEsmrzS7vIhQi1FZIQCNoePw+8VE6li8utSiYjpU4mJVIYBCXjxzbkerF9aAD9JQimXoKPXgT6rB/WtA6hvHcDainxUf9GE2ZNTOQqR9CQbClN+aFEufIMBXkFb6Px2lxexBiVzXJNRhWVzsjg9MMkxGkzPTwRJBrCuMh+d/U643H5EaGSYlp+IP7xCRUrL5oxGcpwODpfvsnDkWYXJPEdU3ypMhdPcYcPODxuxpNTMYauuOtKMBxeNQ++AG1aHDx982QKpWIRFMzMZqYXQtNc/d5xCeXEG5k1NQ4yBgsr39tlBhJGybumwId6gFHQAQtF0e68TzSzOPLlUjHMXrXjyrWNYW5GPhCjVFVHR/DvaiJMZsRvDQmQHDFo5WrscTJ2GvUKkJwM6rQICSInTMvBgj8WP3YfPo7w4A9F6JawOD3yDJC+NRNcNLnRSdbhdn57Hw3fl4WIQpqxWSBAA8PDicRCLRXh9zzdo73UCoGosQpNYc7sNk3PjsWH3Gfj8JEqKUpAQrQZJehClp5xYV78Lc6ekMT1A7L6Y8uJMGPVyPLZqEjr7XDBEyHGh08aogQJB/rQ+ZxjILQGpBFhXOR5+koRUKoZGLmaiDK1aisqS0bzO9o+PX0BRdgyTEtNCCj8ZwP/bcDQsvQ4nbSTAoh2ugRKBoaiG7uGJ0itQOimFIQGlxxUIBJh0FX3tbB482tltqqrDE2umQCQiYHX68Pz2kzxVVPqZZ6XoBR3ApZgq6H/Tx6CdyX8uLxR0pCNNmEM24mRG7MYxluyA1RWerJBm5GVT3989N4vzsfdY3NhUVUt17pPg0LrQE1VlqRnxURpc6LJhVLIe5y72o8/mxY5DDdCqpZg3NQ2/f/mI4Ar6gy9bwk5iNocPFSVUtz+3OJ2FxBgNzrcNwOenCDK1EK6tOJxevLq7BslxGsyfns6byKqPNjOiXezzv32gFrdOTMGL7ww51P9aMYGJMsoK03lcY5ur6vDrFUWwuYZW8uyeoXD0OjKJiJmURQKRw8fHLoS9R/S56R6ecD1K9y/IFZzE6f3YTsvhotJ7NJeZw81nSJCKRVDIJWizuOH2DCIqQsFEyOH0kJJi1Eg1aXHuopUnraAM018zIuk8ZCNOZsRuSAsHBLA4vEiOVjMFcHobk1Et+LGPTjGgtlmY9ypKr+SkoB66Kw97g6vUssJ0XvqHvYLusbjh8vg4+Xr2BKTXKPDCO6c4+9O0KrRAGEVdExCsrfz2vkn4z+UFIAiKayz02mwOH7RKKad2Q/eSvBhSd6ptZqWtwuj2WJ1eyKQslmTWdmyJgDijCh29Tuz9rAmLb83E71ZPhsXugUomRlRIX0xpsHmU3o8WkmMTd9JRgkgkPC6lQpi5mW54pJ0We2KnI5Ldn57nOHCTUYWls0ej5nwfJ5XKrqHwRPyCaEaJWMRjrJBLxdBeibrsv6mNOJkR+34tDDLnkkCAAHhyxuHo9zt67UiOE+bgaut2cCbjZ98+ifVLC9D97qlLiqjR+yfH6lDbYhEEGSjkYsH96ToGnS4KV1s53dgDuVQMY4QcX53tEFTuJMQiToQGCE/WdNpKq5YiNU5YajpSK8ezb59gIg/6d7aj2flRIx5ZWYRAAFh5Rw4sNjd+9+LnTNT3xZl2rK3Mh9fnR5RehY17v0F96wBaOuz4+dLxiItScUTmVi8YCyCAR++ZCLVSyqikssfV3e/iNXX+dPE4KKQUIpCOHJmJHdyIZE8wbRprUEEpF6Op3cZrzOTUUNgifgRQ08wt6rPRcWsr8qFRSK6dpPMPBLU24mRG7PuzS4g+hUtd0CvLQX+AQ2nv8vjx8bELPFTW9PxEfPBlK1+9cVEe3txbwxmOx0cxDM8qHOKeCp30aPLM0SmR0KqlSIhW8UAG95fnosfiCrsCZ58vHOSZJKmemvLiDBRmxXHACCKCgNc3iK5eB0/6gOZlC01bPbQoF31WD15/v0bQYYlFVJG76otmrF9agM4+Oy/VtXrBWA6yiy7czypMxv6gHg+b923NwlxMzvVgTKoRRq0MPTY3Hr1nInVvZGJ89HUrJowx4a9vfCUI1rhvfg4cLh/2fd6E8uIMZCRGIEonZ5xJjF6BrBQ9f2JnRSQ9Ng8aWgfw5r4ahlMsbA0lCIu32L0wRCjg8fp5KdtNVXWUXoxczDnnVZd0Dn4bb+ytYfqEaCqdUFTcjW4jTmbEvjcLJ/r0xANT4HD5kBCtxl8enoYuixsKuQQRGimzsqQbEdmU9hUlZkG01pTceGwPilqJRIA5ORJiEQQpWEiSigaqj7YITnpd/U6QJKCQS/Dos58hOU6DilvN+NVPJsDt9UOjlOCtfWexcGYmb5JmSx3T5/P6/GEF0OjIx2RUMxxZNLLM7fHh1d01WDLbzEnZbfugjnfeO6ePgkohY0g8aYdFM0u/8X4NFt9qhsmoQn3rAF569xRmFSbDGPxxv6QAACAASURBVKHEusrxaOuxI9Wkw8tBNmz6WdGFe1qPJzTt9/x2ipxzwOmFUSdDR58bzwSZjun7uf0ghRpjgzWS4zTQquVo7bDC5fWjMCsOaSYtRsVpGIkI4DITe2Con8rj8TPPWqh2REfI9IKHjsw8PmGNm8FBP3R6xbdyJiQZ4FLhhIlOrE4f3thbw5MPf3jxOOSk6G+qiOamoJW5njZCK3P1jDc2gurs77S4QYhFsDi8OPBlK2cfPxmAMUKBf7x9Ege/uoD0RD3eeL8G7358DhFqBTbs/oZpRHz7g3p8erINZ5v6sWiWGaNT9bi1IBGFY+JQlB0Lh9uHhGgNtlTXc6hQPj/dgR+Ni0duRhSO1XLpaA5+1Yrbp6YhK9UAt9eP7DQDxqQZsCDYmxKlV4Ek/dAoZThW14ULXQ58fLwNHx67iE9PtiE5ToviwmTIJGK8tucbzJ6Uipx0I8ZlRkEpl+CLM50sypccKOUSvP1BPVYvyEVyrBajkw3Y/0Uz03w4Js0IERHALQWJGBUfgdKJKVApxGjvdeFitw1JsTrYHD6882EjTjb0oM/qQSBAYuUdOYiPUiM/MxqBAIGufidDV+N0DzL3IjFGiyNnOnC8rhtrFo7D0W86GQqXWwuT4Pb58e5HjchKNaDqixbesxo/OhqJMRoo5RIcPtXO+3tBVjQcLh9kUgkaL1gwOsVAcaw5fTjZ0IPZk1IZqh2nexCnz/ViTKoB3f0uvLm3FicbelDfakHRmDgKDt7vAiEWQS4VlvoQeueUcgkm58YjSi+HVilFikmHs039zHNYW5EPvUaGJ4JMC3dMG4VtBxswOsUgSLVz57RUyGVizrscbjwcI4ATDb34/Stf4MCXrcH3OxLRegVv006LGyqFDNsODqX2/GQAX5/twoz8BAZWfzXtWtHKjEQyI3Z9TCA19sjKorCpIoC7Gt5yoA5ksA5TVpjOWzW/tPM0Hls1Cf1WD+cc4WoeZ5v70dDaj18uL0T9BQsjwVxZOhoOpxsXu5xM/eSDL1uw41AjKkqofo1VZWPx5t4azJuaxkQmdFNlrEENnVICjUKC5bdlc8ayYl42ls/NgkYpQ2efE5ur6yAVi1BRYsYb79cwdDHsyEchE0OjlOLgly3IGRXF0c1hNy+yFS5zRkXhpZ2U6mesQYWnNh8PC0NmE4kSBKgo0u1jIOR7Pj3HkEwK7Z8Yo8WTb30d9vhZqQacuziA/xsGpScSgQNFFxEEUhMiePINT285jmVzRsPhGmRSRwadHL0Wd/iIQOCd+8WyAhSOjkZmciSFLgum31q6hupzdD2OjaqjI+ekWA1AEGhss3EaSYfTgGl1+jhNsbx6EMv0WnlYMMTNBo8ecTIjdl1MKDX2/PaTeHjxOEYsKhTiSm/HpqqXS8Vhi/IO9yDvHOH6SUgSaOqwoaPPAXNyJCw2D0omJmPfZ+cxe/IQ27LJqMKq+bm40GVDWnwEtGopXtp5Gr/4cQEaL1qx/LZsKOQSbNg1JAxGTzjZyRF44oEpDC/X9kMNmFWYjDfeP8sZj9XhxS0FSSADAaxfWgCXhyKzlEpE+Oc7p2Bz+PDb+yYxcGr62mi02/ZDDbjzR6Pw3/dNAhkI4Il/Ub0mtFZO6IQpdK/lUjFi9RTtvVEjg9U1lK6paepD9VH+/g+yWIrDHd/tGeRcL3vcOz9qRHaaAXKpmJOWNEYomCZN2rRqKZRyCccJryobi83VtbA5fFQaKVV/2Xfurxu/xp8fmop4dvQgADSRS4fYn5eUmqFRSTmqpMvmZGFJqRmuIBv0G3tr8KvlhZec/C+FmGT2Cxb77S4fslIMw4dH38AggREnM2LXxcJ1U0dqZQwyR62Q4m9vfc0TBqM/Flr4y+MjBT8+tULK6+ivPtqMBxfl4bltJzmT477DFLyVbnKkJ8UJY+KYug7dIMiGOdPRg83p49D+syfs1i475DIxoiIUcATZj+lJVGh1+t4n51BZMpqnd8KG+3axxMho8/goiG9JUQpiIlUY9JNouGDhbceeMOlazNj0KDyz9TiTlnt48Tjo1ENUKxa7l6mzlN2SzjAhVJRkwqBTorPPiX6rm6nRsI+fHKeBSiFFZ58DLveg4LjjjCr8rCIfcqkY+48086JSGupNW0lRCl5+9wyHuaB3wI15U9OwYU8N/rH1BB5ZWQRj5BBR47Am9aCxgSb0e7apqi7ICkFi004u5f/GfWexrnI8/rXrNGwOHypLzXD5BpnzCk30l6VOCom8slP0PGCHIDz6EgCaG8HRjDiZEbsuFu4D0yikHMhoaIqJ5iQDqEJ9mkkHiVQEYwRX737Nwlz8fcsxJppgN0aOMmm5EFONFHq1HH/acJQzcYQ2/4VrEPz5sgKcb7NyHNrmqjrBBswlpWacOddD6eR4/IiKVMBkVDGTM31ddqcXFSWZSIjRoqnNyusnkcv4/SImowoGnQLPsiah9csKONuFTpg7P2rEynnZUEhFWDFvDMhAAJ29TmzcdxbLb8umJiYAWrUMqSYtym5Jh0ImGlLI9JKM0Foo60GPxY2Pj1/A3XPH4GxzP0QEAY1SyrteuVSMrn4X0y8U6lA9Pj8SYob6nuRSMWINKkFS0Pvm5yBKr0CPxY2apj7EGtSQEZd+5wQjgSAi7S8PT4PVNQi/38+kDgf9AUFn1dJpRcWtZlR90YyqI82I0ivxzNYvwk70OiVf7+bhxeNgd/kAgoCIACfyojWH6HGEg0eHA9DcKNQ2I05mxK6LhYUkh4Gespvh0uIKmf8DwK+ePUytaIPIptQ4HV5//xsO8mlzEP6bFKOBRiFh0EYAAD91snCRATMxhUnL+Qb9glGMUAPm/iOUkiUb2vtAeS62HqjjOERauOueO8ZALhVx+klWlY3Fro8befWBVJMWTe02Dv/Xhl1nOOgym8OHGIMSlaVmkGQAqXE62N0+PBqksKfP7/OTeHrLcfzl4Wno7HOhLeh4htJDo7Gk1IwIjZzjwNgpMpNRhUUzMzl1oyWlZvz0rnH4/b++4PxG17LY6TNa+EwuFUMmEeM3906kIkqdHDbnIEqKUnhO/+V3zzCpN5IEw8I87HcuJM3U3e/i1VoSooUbfUkSePndM1i/tAAXu20Mco4eG2+iDwBTck2Ii6Teb4IgOJDwBxfl8dKENHNBcpSaOUaoXUnEJmjBe9DR0A1VUIztakZAI05mxK6PCTkQoaa1QAg0leQ2x7X1u3kpsYoSM2elDFAfWUZixBDsFeBphQhNHN39Lobenf4tdJsLXdwmTtqhxUQqhvp0guObnp/ITPj09v/ccQprK/PR3uNAYowWG3afYdJW8UZqMqHpUEQEAZEImJwbj72fNQnWB9iRAD0p0WmxwtExMOpkSIrW4EKPA95BkkkdssdPT/JW1yAa26y8hsWN+2qxbM5oROmVQaYC6vr2HD6PdZXj0dJpRXaqgcPC4PFRMOdH75mIx1ZToAwA6Oxz8J4Vu8n1p3fl4WK3HW4vRVcTiNfBFKMKK8ctEoGRqJ41IQnMA79EBz/bqfxr1xmmFyUtPgLJcRrUtw4wjuIvD0/jOSs2zLypfQAxkaphTfQiEcH8n62f5PH58dy2k7w0YdjIi2VXFLGF2nVItY04mRG7fhbqQK7kJb6ECFW43oconZzjYELlAUJrNUzz3xGq+c+crEfCXePw7NtDwAS62Mw2j8+PpFgNOvtdHOLJFfOyoZRLBScft8cP7yCJth4bZk9KoejjI5VMo2FSnA4Xum1oaB3AW/up880qTGbQYuGchFwqhsvtx86PGrG2Ih9GLcWQ4PNTaTGPT7j3AwR1z9yeQZCBAKf2AQDHajsRoZHzCCyrjjQDRAAJ0Rr0DrgFj221e+Dx+Tk6PqECYsmxOlSUmJGZGIG2Hicv5djW64BYJPyc6V6f5bdlUyzMvfahAbD6ZezuQZw818955svmZOHO6aOoVCDrPei30fUYStMoFMTBHjtJAsYIYRnwcBO9EMkrAKQncDWHhkNRIyLA6+laVTYWYsnlYdXXI9U2DHD392v/9V//hRkzZqCsrAxlZWV47rnnwm77zDPPoKSkBCUlJXjmmWeu4yhH7FpbOBGqkqIUpMfrsDZYRAbA/TjD7N/e68SA3YPy4gz8rCKfmaQ37KlBfesANlXVQkQAoxK0WFc5Hv+ncjweWVkEg04u2MQplYg4nGFatRQe7xC6LXT7bosLW6rrsLmqHgAQb1QxtCYIAAkxGoyK1SApRgObw8fUO0AQl3QS983PgVopxhMPTGHqKzUtA+gZcGNTVR1DMRM6HhFBYG1FPqIiFFArJJg3NQ07P2rEluo67PywEbMnpWJzVS3v/t89dwx0ahk27jsLtZIvOyyXihGhlfN0fDZX1WFWYTKTirPY3dj5YSO8gySTpqO33VRVh4RoDbQqihWA/ZwfrhgHQ4QC980fi4RotfDLQwCNbTZc6HbyoriN+87C6vBxfnv53TMc1geaysiolSEhWoOdHzUyDua++Tk41dCFSI2M9w7+dPE46DTCEzVN8np7yH12e/34y8PT8LtVk/Dnh6YOK6Los3pw+FQb1i8twJJSM4U4PFiPxotWDjJTyC6VartadlNEMvfffz+WL19+yW2OHj2KvXv3YteuXQCAxYsXY+LEiSgqKroeQxyxa2zhPgYmJQZcMhUntL/DPYgt1RTMN5QDjJ5cWtrtDJT3ue0nBelPVi8YC98gydmf1lfRqqUCDMZZeO+TRgBBZ+Qj0WVxg2QxAgPg0qNY3eizetDSYRNcMafEaTnknb9bNYkDRV46h2KpFoIaP7AwF5mJEVDLqAlyVHwEnghGLPR9fmnnaU7dhP49gACe2XoC7b1OvLjzFE+wbVXZ2LARTmo8Neb3PjkHqViEJx6Ygj6bR7gO5ifx7LZTnFqciCAQqZXjdy98zpxv/dICmBO0nGdvdw/iQrc9bBRHhnRfe3x+yKQifiQRAHLS9PjVTyagrqUfJAnsONSAihIzNEoJslMjOH97a99ZVJSYMS7dwKOC0SklPJJXj8+Pf2w9gT8/NPWSNZhQ02vlKMyK4/TgAMBz205eNiL5Tqm2YdpN4WSGY3v27MGCBQugUFBFvwULFmDPnj0jTuYHYuE+BnZKjI5cLHYvQBCcCVtofzrNJjTxrq3Ih0hE4Oktx1E2Y6j5M1SrprPPiQi1DI0XrdzjB0EDHoufwzuWGqeFxU7VJqL0Ch5aismHh5hcJsHL737NcVo0ACDWoEJnn4ORL5ZLxTBo5bC6fOjod2H53Gy0dtphMqowPT8RBAGsrcxHR68DmcmROH/RAo/XD7+fhMXmhT8gDIoQheQ95FKKWJMNY/7kxEU8srII/TYPtEopXnr3NKaPTxR8dgqZhEnx0ak9KUs+gL1tgAww95Pt6JbAzJmkn3zra+7ESgB2N+VcksOQg4bKKculYqQnUkgzGjRCm9Xuw4vvUI2uIIDp4xOxpboOaXGF8PkDjB4P/Xw7+1xoVNoQrVcySpoABEle6Wu40mZLnVKCpFjhetXljjUscMR3tJvCybzyyivYvHkzkpKS8B//8R9IT0/nbdPe3o6JEycy/zeZTDh69Oj1HOaIXUO77MdwmQKm0P66oPrjxn21DFtvUqwGCUYVtws8BGXG1qrZcqAOd8/NQvXRZo6jYteJeixuZjKlkVBlM9KhlIvh8ZEcIAOdD48G95rKbknnOK0lpWaolVKeVkvVkWbce0cOWrsczLUuKTXjq7OdWDgzk9OL80B5Ltq77fjkRBtDyKlVS7G6LFdwMs5OHWoOpO+vRjkEoIjSKzAlNx7Pbz+J5XOzUX/BgunjE3GstpPnxNcszINETODXK6gUpMPlg9U1CKmMwJqFeQxMmo6GOvvDN9WyjTOxCtThQolSl8/N4pCU0vfxhR2n8KvlhbyJ1u7y8fjEKkvNsLt9sLsGOQ5GaAFhNAz18eg1VymKCAAJUcIIuMseixUtO31+qKTiqy5T8L07mfLycrS1tQn+7fDhw1i/fj2io6MhEonwzjvvYNWqVaiuroZYfPW5ewDAaNQI/h4drb0m57sa9u8yNqNBg/REPfpsLhi0lNQurfFxscvOTCZ0MbW1y4a4KDUyEvUQiQhm/5ZOKxpaB7D9UAMAMFHGuMwoiisseEyPf6h+IfQBj0kzYkmpmSGwZEcsSrmYByxgI5LkMhHUSik2VZ0ZmgCDzAKuQRIkGYCXJDh1JLbTcnn8gno3f3xoGpRyCdY/+SHzNzIAFGbF8cTKaOniRTPNTKqlrDAdr+46w3MKP6vIR15GNJ5cfws6ex1QyCUw6BSIiVQxvR+zCpNRJcDGTDewsvVotlTXUnozR5oxe1IKdh8+j+gIBUonpWLrgToGHZeZFIkBuxv7P2/mjemni8fhrX1nOe+IXCpGnFGD6GgN550AqDrc9oP1/z973x1eRZm2f5/eT07OSTvpISEkQEggIE0smABKCUVICNgWRFBW1/25q+vq6q5t3W+/dfWzt8UVBVEpCipFQFlAll4DCYGEhPRycnqf3x9zZjJzZk4ICCbuzn1dXFdCpjzvOzPv8z7tfvBgaQHqmm1Ijdfj/Y0nMP36DE5fnjaLG05fAJmpRgSDBBrbHOiwuiCXS3lrp56/fzxUSjn9jPhqrF5ZcwSZyQYkxZHfhClIcOpmHp4/AhnJ0ZzeNZf8Nn7ktWIv626Xhz5XMuvWrevx7/Hx8fTPM2fOxAsvvICmpiYkJSWxjjObzSxl1djYCLPZfNnytLeTrXiZiI3VobXVdtnX+inw3yabXIRQHQTByiJqanPQCoa5g1y3s5pl0chFQJxBhf/9qNt/TVkZ44bEd19TBNQ323DvzKH4fHsVZ4FbPjcfxig5hmXFwun24YG5+Xjt06P0tRbNGILNe8/TC1p4RtKgNCNNEzMwJQpzbs5GTWMXggTwyurDuGvqEGiV7KJKlqUUgdeq0+pGa4C0jqgU7+0HLmDB5NyI8Yiaxi46myzeSBZOMhUmCMCglaHT4sD5i1xrUaOU0u5DPjZmJo0MM65DFbBSbM4DU6JQfdGKCcOTAZBM2Ot2VuP391yHhbfmos3iwryigfD5gyTtfZyaU7z78PwRkIsJtLba6HeCicZ2J+qabUiJ0yE5Vo1flRZAJpXgD6G4DgWFTAK1TILWNhvLGgrvwEqN0ebwIDVOQ3crjVRj1WFzQS7qXl+yk3ScWCIrO+4y8GOvdaXfq1gsirg5B/qBkrkUmpubaUWza9cuiMViluKhMGXKFDz77LNYsGABAGD9+vV48sknf1JZBfQdqJhLpB0k00+vV0nxSPkIVDdY6VqUzEQ9y01gdfrw/saTeGBuPm4ckULHMRrbHPAHCMSbVGi3eFBR04EgARyvasHjd4+C0+1HbZMNDrcPFbUW+INnaQUycWQqdh2ux6TRaaiq66SVYvF1XOqaDzadxCMLClFWPIgOTO893kD3VYnSyHmbfJ2t7+KtpLfY3bzWGAhAoZBg6rgMcrEPEV1SLj7quHFD4yOmuz5UOhzb9tdi4sjUiMqPqmWhqHcoazPeqEFp8UCoFFIOVc9dU3MRCBKwOb2gwibmGA2SYzRkrCTATIzwQKmQItagAvUQI8XxCgfFkandAOpaHFj5zTHemBzVX4Y9Zn5KI4NGDgSB/Ewjnr1vLFxePzbwHGfUdcsH4Mel9Yfjal7rKqLfK5lHH30U7e3tEIlE0Gq1eOONNyCVkmL//ve/x8SJE3HLLbdg9OjRmDRpEqZOnQqAtHqYMRoB/9mgYi51LbZeBUC9/iBrQXtwXgHrHMr3fqK6Hau3ViIcKfFalkuofPIgvLn2GB5dWAizUQWHh3SBjc1LZCmQpbOH4as95zB8UDytFMOLNakdfl2LnSVjWXE2kmO1dDZdeIwpUiX9hu+rkRyjjVhQyLT8IiVBcJiKGXN7odmK28ZlYO/xBsyZmM27COcPjMUrnxxGm8XNG6/47cJC/GXlQfo8nUYGn59gsQ6UFWejy+ZBcijzyuryoc3qgUwqxsVWO7781zm6Y2VPje+o2iGry0f3jyEIAktm5kGllCA+Wo1oDbnhCM9K7Gl+QAAIAiatHBDJOfdePjcf8UY1OjvZxaj/6RARRHj3lP9uCO6yq4efXDYR0G7z4om39nIWOaYlY3X5WNXWfMe028nrlNyYydtemarMpnbkZPzAAJVCCqfbD7VSCn8giOf+sZ9zbskNmdh+8AJuG5cBry/Aq8R+u7CQVXTJJyPNYODwQiqV4O+r2eSiAKmITFFKsqNiaGGtb3WgvsWBbftrYXP48Mt5+fjrR4foc6gxpSfqEB+thkQMWGwkS8LfPj7E4SFjusIOVzZj0uh0dhfS2XnY8kMNbh6ZyqKBYY6NSgun7p1m1tFKPHzeh2WZOC0dyoqzoZBLsHbnWdgcvu55YsxReGr7hVYHXv38KKZfP4CVdn3/7cOQlx5Nzpfbj0df282Sw2xS49fzR0TmE6OYlN0+iERinK7tgMcbxK4j9bhr6hBOinV/wX+tu0yAgF4jVDDH3EGaTWosnT2MLC4LpTX3huvJ4fZF3NkvmzMMK7+pwMicWNw6NgNV9RYo5CTdDHPnvXxuPu99ICIz1PYeb8DCKbn8Kbvgdzs1dbpY6dl6lQx6jQyNHW7eItGmdifeWnecXnT1ShkGpxkQH61GulkHk17JSRumiDQfWTACJ851sMZEEZaGE5FS47I7fTDHqPHkotFwe/2I0shpxXTdUDNm3ZSFeKOKlaABEZCaoENumgGjhphp5me+8ccaVOiye1HXYmdxtlGtqicWpmLNt5Xdz7IHF5JBp8Bt4zJoBUPd4/XPjuHZpWPhcPpg0CnwyILhqL5oo12rKfEamPRy0mIJu2YkZorDlc2YUJCMmsYumPQK2pr6b4CgZAT8Z4GRkml3+9Bp89IFb5RrIxLhIVVbQnGbUezBTIr81Hg9ovVyxEYpMT4/mXbxlBUPwrqd7FjQxVZHxLqMGIMS40Lpvnx9WFoipOyeu2jFS6sOs+ppTtZY8PHm05zrLJoxBGu+reS6C0MuHZNOTu64nV7evj51LXbelsrP3DcWh3joVYYPikVKnBbPvPdvlkL2Bcg84027z2P2TVlQK8m5DU8FXjZnGItVgG/8rRZ+9mYqiYFiPmCl7kbotaJXSZEYo+FVZnXNZGaa2aTGnIkDWW7L8sk5sMf6oVVwl0++uNXWEEkq5RYNT0b5T4fQfjkMQvvlq4erKltY6+aI7W4ZC4pKIcPb64+TxZkg29cePN2CyaNTkZtuwsHTLXQL3kfKR6DT5sVzK/bj2wN1+P7wRdw5dTAuNFnR0unC2XoL8gfGYs23lRg/LBGDM2JYFdaDB5hw7GwbS5SmDgfuvG0wjlW10fcpn5wDiRi4Pj8J731xEha7Fxdb7bh1bAbyskyYNDoNn35biao6C2bdlMVqE1xanI0t/66FzenDwVAbXo8viOc/OMB7HYvdg73Hm6CQhVoGh9Kxqbk812THqZpOfP1DDYxRKkwek4Zxw8zIMOvx1Z7zSInXc8YUCBK4qTAZCqkE//yqAjanj1beRq0cz3/QXYwYCBKobbRiSUkeRg9NQG6aCcYoBdbtqEJpcQ4rpToQJHD4TCvdjrm5w4HbJw5ExfkOevxlxdnYvK8GTrcfgSCB0zWduHVsBk6eb4fZpMaNw5OhlEsweUwa4gxKVv3Ucyv24+jZVshlUngDBBRyKXyBIAIEgT3HGjktlicMT8Luow0cSycQJFBxvgNj8hKhU3KVTLPFzWkpftu4DKzawr4G/fz8wctr4XwtEHofLrbaEQQuWw6h/bKAnz96yxTbA4kms1cJRXj48q9vQlO7ndVCgLkDfWvtcTxUOhw1TVa6fsLm8IEAYHNyXW7hO2+bwweDVo6SGzIxIEmPhGgVWi1u/PXjQyx3EDOT645bcxiEiQTKJw9CgkmDhlY7ggSBiSNJTq3tBy7Q/FJ81ykrzkYwGMbjxlO0ajapOUWapcXZEcekkJGV+rlpSlazOY/XjzZrNyVMjEGJW8emI8agQoAgsPLrCtrFVj55EJra7RGz0KixfPmvcygtzka8UQ2VQorXPz/Kijl5fGRrhjtvy0W8UQ2IgC6HBy2dLni9AcQbVbC6/HRw/7ZxGdi6rxYTCpJR12zDwBQDFHIxhyaorDgbcqkEMQZlxFRkt8fP+6ryMktEyLi72O5kJY88Uj4CsQblT9vdMsTrFp5pmZl49eJGgpIR0O/RW6bYSCSa4b1KWK4UAoBIBIudnzOLAEEH/qkF6H8/Osipimc2B2Mu1vWtdmz4vro7JqKW4cX7x8HhCfAmFGQkRtHUJFQMJClOjYZWO9Zsq2LJYdQpIqbUDkozQiYBxg2N56RmM+doQkEyp0iTmrNIY/rrygNkg7O0KFxsc+KFkPVSVjwICpmEt7kYU9l/vPkMHiot4JV7YEo0/f8yiRiJMVrUt9iQGKuBTMLeYZtNakTrlazOkaXF2fjuUB0UsjQ0tDvgCHXmLCnMpAtFmXItLhkKc4ya1VpBIZfg3Q3HWSSZ4XLGRCl431W+jLZBqdG816hr7la0Oo0M9a12Ti+ba+1So3jdwrMY440qXnfglUBwl4VBcJddPfxo2UJmfFOnC/EmDZo7HHC6yR1kIEhgTJ4ZUQwznc9VEQgSyMsy4cS5dvrDTY5Vo+JCF/747g/49kAddhysxw3Dk7D3ONdtUnxdKqaOS8PIwQlIiddBBCAlXg+AwKjBCTgacoUFAgRG5sYhOy0aOelG5KQZseNgHZLj9CgalQKJWARCJIJCLobHF4TXF8CwgbE4xHDZLZ+bjw82nWK5945UtuKG/CS8sqa7IRblKrq+IAkenx+JsVqWW23RjCEwRclhNqhJFxnD1RgggEOVLfQ8DsnkuvkCQYL8/6o2FObGYeLIFCTHaTEo1Ygt/65FS6cLnVYXslKNsDq9w8g+9AAAIABJREFUmDQ6FYPSDCAIAqNy45EUq8Nn26s48lKurUCQQHaqAYMHmDjuwH+faMB9s4dh+KBY5KYb8eqnR3G4shUHKlpo96U91NL6V2Uj8NKqw5z7TBqdjs93nMXNI1PQZffibJ0FOelGpCXo8fmOs6zjj1W1Ic2sR2KsBkq5FHanD1/tPY+WThdGDo6DQibB9QVJOHymleW2k4rFMOr5FU2sQYkbCpIwJs+MKWPSsPKbCkwak84a6/23D8P6787Sz2Ha+AEc2SiXGu3mvAZos3vpzqrMOYzkDuSD4C4T8PPEJVxfHIsEPRff5aRF0+mmVgfX4nlz7TG6ap95v9c/P4pHFxZCGfJTM3f1S2YNxdP3jkGX3QOjXol2qwsrVnX3JVk2ZxhiDEqapdhsUmNeUTbeXHucdlX97q5RAAgYNHLYXT7e5mvtVn4W4yOVrTDqldh/spFVnb9u51mSdyvCPFL1NMz2zuFzRrE6r915FkWjUllp1gNTojBxVBqefucHxlzk4ciZFgweEIO0BF3ErDrq+vFGLfz+AP6waDSd4rv3eAPG5iXij+/u46Q5U+7L/7dgBGxOH8wmNewuX8T7eHwBeH0BqOSk0u2wegARPyGl2xugWRkoi5fZ2rqsOJu2dEAAm0Ju04gMx4yMtgutDlTUWtDa5WYzKOjk7GzACG65yyXL7BUYcUupVMzpxtmTO/BKICgZAf0SPbm+qIZc4fUJPRXfMdNN+VKYG9ud0CilvBxWVNwhPNPq7XUn8PyycQgECDz51l7kZRrx+3uuQ5vFBaVcApvTS2daAaRrilIw1D1f+GA/Hr97FDmWCM3XTHr+hljM9r/Mgk/m3PDNI5Xuu3rrGew6XI/7ZufhrZBclIuOGUNhurAAYOaNWawaFnIujuMPi0dj5VenUDYph1dehHrZ3DtzKN794jjd1XTNNnJhn3dLd3ZcpEXX4fKjy+6BXCqOmL1H3UerkuPNtWR7gOnXD0BqfGQW5uwUAz799gzm3ZINsRgYOsCE10LN6lzeAC0jE71RANTGh8ugMI71rkZqvHc1KfcB9HrTERPBSrsSCEpGQL9EpFqWAUl6cgcZoXVzb1o8R7J49Bp5xL4yFgdbHqrGo63LjboWO1ITtLhuiJnVOXLRjCGsXWIUoxcK0N0++my9BVFqMl7DqyT13OpxZn1KfYuNlVzAHHNPfXieXjyabknMmjOtDEb9MJIyJwh89u0ZFnuxx8vfl+X42TbcPDIVrZ1OTixn2RySdXle0UDYnF7WLl4hkyA1QYuctGggxEitlPNT/puiFEiIUeHpt/fx9uqhmKjvv30Y1u7obs/wj42nkJtmwP23D6PdQ9QCa4pSIhj0Y9KYDBb7M5MGh2qTQD27XYfre50mHYk9XM94V406BVLitNeUch+49KbjWtxXqPgPg1Dxf/XwY2Tjq7RWyCRXpS2s3ePHwTOtnIyiwkGxLIp8ZvDV7glgz/EmBAkCKgW5+2VWiTOtCaa8TGaABZNzaEuGuSAuvDUXGqWUbFQVWqw4tOshNgOq/S+zdwxl3fHNzZXMIx8jAlXUWlHTgdx0I6vZFnVNSo6nFo+BVilBMEjA4vBCIZfC7vSivsVOtxOguNJ0GhnKJw1CMAi8w8hwu2tqLnz+IGuOyyfnICslCnanD9UXu7D9wAUAZIM4tUqCrORoVNd3wuEKYNeRehSPTmNlFgLAPdNyEW/Uwun2QSGXoKXDiT3HG1hM1OFjisRiQDcju1T2I4N1IMGkhVxM8C/gPbATXC1caHXg6ff2cf7/iXuug1olvSKq/0tV/AuB/zAIgf+rhx8jm0ImRmZyNKuW5cF5BUiOUf9ouZo6Xfhoy2ncOjYDQzJNyEkjA9p5WTHIStTRQdvp49Pp+1U32PDBplM4drYNuekmfPotO7CdHKfF0SpuAP228RlIidfiphHJWLXlDCuof7qmE0tn56O104H0kCuHHLsEaYkGWKxuNHd211CoFRJ4/QSrPqW0OBs7Dtbh3pI83rm5knnkS6Cwu3xIM+sgFYux+YcazC0ahKOVrbw1PBMKEhGrV5IsCG1O/OXDg6hvtWFcXiJuLEzG0MwYpJl1GD8sEUa9EhmJUfhbWAD/RHU78rJiUHRdGtLNegzNNEEhl+CVT45g56F6nK2z4I5bc5GeqIc/QEAiFuP1z47hwOkWnDzfDrvLx0o2iDEoMWNCJqJ1SkilIvzz6wps+3cdLrbaMX9SDtweP5LjdZzkkrwsExKMWk6dy5HKVjoob3X58BxD6fIF7RUyCaLUciTE6eCM1NpYRBJwun0BSCRiWOweMlnkKtbPiCRi7DhYz0lwKbk+AzkZMQh4Lz8WIwT+Bfw80UvX15XAoFPA5vCxOizS/m8eGhKKSJFaRII8HQ2DBH8A/UKTDau3Vkas2bnYakNWsoE9NhGw93gjJ86SmxrFmhONUgaPz48RAwsjzw0B5KZF4dn7xqLd6oZJr4RJL+e0Aw6fn/CxmE1qxEdrIJOKkJM+BG2dDjy1eDSOnW3jVP4bNHLa8rrYakdp8UAo5VL8z0cHWZbjqCFxiLOT/WX43G86tbw7dnNLNtZsq2C5eZg8aJEofMRi0rVJWU7M++8JJRqE975hjqVwUFzExAsqJtMbmqJLIkKiy9Z9tWS6OF8qcwQXXU+I5L4Ti0U4frYVaoX0qtfn9FGJqQABvUBowU+N0dA8VFcD1IfG3GXSfmgKobTfC60OVpEhhfC00l2H63H/7cNY1ywrzsa2/bUAuhMXqNoL6pgBSQbIpSJYXX7a3291+liuG4+PrAuyOn2sOTFp5UiMVrOIPy+0OmB1d18LIqCitgtPvLUXf/7nATzx1l5UX7TB7vGjweLGuWY7+3ie+TGb1JhblI2XPzmM51bsx9Pv/IC2Lg/W7qiCUa/Ehu+r6UV52Zxh0GtkqLhA3nP11kp8srUKMqkYZZOyEWNQ0nEAh4uk3jEZlJz5VMgkUCtldOwmUkEjlSBAJQGEXyMlXodfzi3gNHhbvbUSs24cyNv7ZmJhKhQysimax+uHKUoJs0nNuTYVk6GUcqS/9waREl0mFCR3P3smQkrp0df34On39uHR13aj4kIX6znygrF5e3rxaLx4/zholFLsOdGMI1Vt+OFkM6obbJe+zmVAsGQE/Pch9KExK/7DLQnmrpIqMqQWAL4ixUmj07DxX+foFs5RWgWHFZnaWQOgF+Rv9pzDvlMt7PiPy8ebIBBxZ8yzC6aqx9usHhaZpE4jQ1uXC/Wtdpb8rBhCmBWpUcpYzNbMYPGabytRWpyNBJMGYhEQHaXkTRF/d8NJzLopC7eNy6CD6Q2tDqzbeRYHT2txb8lQVkymrDgbn++oDBFqqqFSSCKmWscYlNi2vxaLZgzhtKP+x8aTuGvq4AgKij+l2RyjxqN3jsQ764/TGXbhxKDL5+bD7vKRZKXqS7QG53le4RZIJGuIUqLhz763Bcq8YFjrdo8f5xut17QYU1AyAv47wPNhJ8Vpu7sUMhaD8A942/5allKxOXxIjtXSzbLO1nfRKaBVdV1QyCR49r6xvKzIBdmxSDfrYdAp8MHGk6iotQDoXiT+Z/l4dNq9dJYb021i0MhpAk+meyRcXr7q8UUzhsDh9iE+Wh0imeRv7Aag+/rq7loPvgUwNUGH6ddnQKWQ4eXVh7sX2NIC3uODBEGnoYvFIjqTq6quC0ANHiodjiARRFy0GkqZGImxWhAE8MGmk/AFgrzsAyu/rqDpYlweP35/z3WwOb2oa7bTNEAxUSr+1GUxfwabOUaDpxidMj0+khj0j0vGwO3xQyQiZacUzoPzCpCb1jvXbjBI8CYJRCJtpdKxw62iq+KiA2B1+XmtvIGp0YKSESCg14jAz2Qy8mfEhH/AbRY3Nu05jycXjYbfH2AtIha7F6u3nmGd7/EF4PH5eXe3cXoF4nQKukgv/Dyry0+zIVP/98nWSjx+9yia90ynkaFoVBpS4rVIitFwihInFqZyFg4qfvHyJ0c4qdXUMeFcWg/MzUdslAIatQwKGUkXQ/GqiUUiGLRkDOvlTw6z7lXXbI+4YFLWXEq8lvX3qrou/GXlAfxmYSFiQjT48dEqvPjhAVbq8MPzR5BtqhlxoE+2VuLRO0dCLhPjy++rUTQqDWMGxyEnzUA+K70My+YMwxufs9OTP99eyVFcy0MuMr4FvKHVAZlUjI83n6aLZsMtCKqb5oUWB2+cpKndgboWO0pCqdrbD1ygNxd8aepb99Vi2ZxhEEvEdP0WEDkN/3Lratwe/rEKxZgCBFwGIvEzpbY7wLfnoz7g8EVVr5JCq1CSB13iY9cqZUg0qiPubiOdF+mj9weCtIKheMGYyuauqbnYtDuUVBChkJH6//e+OEmnVjPvzeTS8vgCeO3To3h4/ghs+K4CD5bmo6XDxVqQU+K00KqlnHsdPN2EZbcPwxufHaNlTIrVoMvugdmkRm66EWIxf/FhnEHVvUCrpVg4JZe18C6dPYzT5M3jC+DcxS58+m0VFpcMxdqdVbhvZh6dEl5xrgufbD1Dt2tIN0fh8x2VqKrrQqfNg4dKC+D1BWGKUiIpVoWmTg+vbFR2G5MLj7q/xeGFXi27ZCrz6ZoO1ntIJRp02Dx0gkaHzYMorRx2pw83jkjBym8qWB0/L1V/czmxy5go/kJfoRhTgIDLQCSXQE66EfE8H5NeJcUj5SM4cYuUOC07y0cE+AJBLJ09DM0dTrrTZFlxNsRiUY8NsyItEpE+eoWcXMxLCjNpBRNOQrm4ZChMUUrIpWJs+I7fkqDGn2BU0/dRyEgurQ+/rmDNg8cXQE1jF/Ky4tDc4eIEyV9ZcwTP3jeWJS/VJ+eTLWdQVpwNrVqGdzd0x0mWzMrD6i2n0drl5lgR983Kw99WHeJ1Q7VZPdCoZRCL+LP4vL5gKPZzAg+WFtBuI6YrkVlxX3JDJqrqukimbJ0SWqUEWpUUFTVdWPlNBafIs6w4Gy0dZBZcgkmNGIOSVSFv0MgvGSexOn0snjDKSp11UxYMGjkqarmV+Nv219L3YcVcrlL25dVSVj2h3yuZu+++G52dnQCAQCCAqqoqbNiwATk5Oazj9u3bhyVLliA9PR0AIJfL8emnn/7U4groh+jZJcCzYyNIkkMqpkEdz/rIeYLti2YMgcPlw6Y955GRqO/Zpx1pkQB4e8MHAqEEBLmYpWzYwfUTmHVTFqI0MpRPHsQqZGRWrytkEiTFafDEL66D0+2HUU9aVTKJGPNuyWZVtQdDxYZuRpU/s6Ol1x/EI+Uj6LkqGpVGKw6XJ8BR7m+vO05bApv2nMesm7IQa1BBqZDQVDZ8801ZCXwKgBobJVeQIKBRks8onKmBujbV3Gz53HwkGBRkbIuRsBDeqM5id2PtzrNQyCRo6XRh6rgMmsOMWpQvtPDHri6V6pwSr4VYLOKtxKfmihobb2dUnk1Mr8F4DzkFwFcJ/V7JrFixgv5527Zt+Pvf/85RMBQyMzOxdu3an0gyAT8XRLIO4k2aiOdEWhDabB7a7x6+KFBxD5vD1zvfeIRFgpn5Fh5kXlwylEynjeASCxIEVmyqQFlxNr1IDs4w4Y1QLxZqp2qxeliJAb+7cySLvJOyOvz+AIJBAlE6Je1CZFpQG76rxvJ5+Xh+2Ti0WlyQiEXdcvXgtmMqBJVSgoZWBy85KLVA291+1LXYMWF4MkQiYF7RQPj8QQzOMOHDr08BAMeye3BeAaL1CpQVDyLJLUHGQGwOH9ITdHh4/gia+DT8mTO5xh6cV4C1O8/C5vDR3UZjo5T4f+WFsNg8dN8ZpguUGp9YDKgUUkACaFQy3vcwyaRGB0+aPHOuZt+UBavDh3MNVtQ02q56zxcAdNuLq41+r2SY+OyzzzBnzpy+FkPAzwx8LoHlc/Nhc3rglUp4i88ixUzO1nXB4wlAo+LGIqig9iXdDZcqoiOApDgt3G4vp5HauxtO4LG7RuJMraXH4LrL2+0eWjglBzeOSEFWchRi9AqIxSL85tXdrOuevmDB0cpmPLJgBCRiMVxePyw2D6QSEWQyCT786hRKi7Ph9QXphZxaSC+22CERi/H+lydQNCqNJRev608m5iiE395RyLtAa5QyQALUtzm659kbhF4jw9d7zyLBpMGsmwaisY3bKnrlNxWc1sllxdkw6hVo7nBy2JQjPXNTlBLTr89AvFGLz3dUIlqn4LBQL52dh/wsIx6cV4CV31Sw+tas21mN+2blYd+JBo4VRr8rEQgyxSIRpo7LgMcb4I4jSgmb40c2OOttQ8AfgZ8Nd1lrayuKioqwY8cOGI1Gzt/37duHZcuWIS0tDVKpFOXl5Zg1a1YfSCqgPyIYJNDY5kC71YVAgMCqzRXIy4qjd/p5mTGQSsWs48Or7im3jM3hw/P3j8fjr3M5wZ6/fzyykg1kTCaCHOHXfXj+CIzNMwMAGtsc6LC6YNSr0OVw49FXd3Ou8dyycYiJUqGipoOTMUXJR7lZFDKSPy3drMfYPDNd2f34G3tYbq/sFAP8gQAa25wcYstPtp5BY7sTMQYl5hfn4P8+PYIYg5I3JuT1+hETrcaKjWTacXil/ZJZebA7vayWxgBZ8FlWnI12qwfROiUrxvXkoutQdcHCqdgXi0WIN2rwwaaTWDAlF3/96CBrnubdks1LeDqvaCC+3ltDj314diwGZ5gQDBLYeaieRZK5uGQotu+vxcRRadiyrwZVdV34zcJCFgt1+LM/U9uBJxl1RdTff3vHSNQ0dsGgVUKllMAco8WAxCiIxSL6vfhg00lMKEim38sEkxpNHU489/6/Odd7qLQAf1l5kPUORXrvIuFiix1/fHcvh/zzqcVjkRQXmY/sctDnlsysWbPQ0NDA+7c9e/ZAIiEradevX48JEybwKhgAGDJkCL777jvodDrU1dXhnnvuQXx8PMaNG3dZ8ggEmVcP/U02uQjQyCV4ceVBTofE5XPzMSTNwNq9ZSfp8OQikjqFSf0PAC63lzdgGq2Wor3dHlEGq4tbzf/SqkNINI3nkHMun5ePe6YNhiPEpUW5euQSMRpb7UiJ12LR9MFQKmVoaHXQCoaibifTkIchPV4HrVKK9g47Sb7p9uOeaYMBgEPyGR5DeePzY7TCarO40dxJuu0mFqbyxoRKbsjEP78+hPtvHwa9Ro6AP4iH549AfYsNXl8Q2/bVYPbNAznFpr5AEP4AwYm17D3eAK8vyJu4QRVMThqdBrFIRLacJrqLVyOxBChlEo7L78F5BUiJ02DNtjOsdg9rd1TR3UMfKi1ATZMNBA+tkMcXQGunE9EqKTp4aGh0GhmsDg+ru+myOcMQpZTQmWcJRiUW3pqLumY7tu2vxbqd1XikfAQCEe4XIAjMK8rG9gMX8NKqQ0iIvnzy2LZOJ+dbKC3ORpvF0V1DdglciiCzz5XMunXrenXc2rVr8dvf/jbi37Xa7kGmpKSgqKgIhw4dumwlI+A/Gxa7FxMKkjkL5KufHuVWSxOAVinlbZN8qRTliPePEIimetGzZFpzlKyq31ZJ797jjCo6A8tsUmPBlBy0d7mREq9F+aQc6DVytHY6MXFkKsQiEZJitXQCQjiLAeV+oe5X09jFko2ydBJCzda2H7hAsx14fPx0/1Qc5vXPjuEPi0ejor4r5PaSwhyjQGq8Fk6Pn1VsumjGEIjFwNvruW2gHywtgDXCnHl8AWjVMmhUMrpWh1lfkptu5HVBpSTo6ZYM1LVeWXMETy0ezdrRU0zX1JhqmmzY8F01Hrg9H2aTmhVDUsjIvj8AYOKJARaNSmP1EqIUONW2IlKDvuoGKxQR2h7UNZGtvaljr6TBmUIu5aXWefa+sZd1nZ7ws+AuO3ToEGw2G2644YaIx7S0tIDy/FksFuzevTtigoCA/xCIIvB19QCDThFxh2vhYcftkefsCrjVNEoZfS0KCpkELjd/l0cqYE3t3ps7XPTiNml0Glo7Xfh48xn8z8qDeGvdcdQ12+AONdlavfUMbXlRgfOSGzNx5205SI7VcO5HkXwCoN1hG76vxitrjmDDd9WYd0s2pl+fgZR4HfIHxvKOg5kmffxsG1Z+czrEXUZmj11otnPSeN/74iRiDGre8bu9ASjlEt57iSDCnJuzaSoZ6pxPtlbi1/NHICVWjeVz81nPrnzyIFTVdfLeq9PmwYbvq7FmWyU2fFeN28ZlkEkWBDve9dpnR7F0NpunbunsPJiiyGQPk06OpbPzWH+PN/KPr83qQUOnm5e3jEqM2LT7PMonD2Jdr7Q4G9sPXqCPLRqVdkUNzhwR3juH2xfhjMtHn1syvcHatWsxc+ZM2nVG4eWXX0ZcXBzmz5+PLVu2YNWqVZBKpQgEApg5cyaKior6SGIB1xxXGLDUq6QRd7i8H+lVZoP2eP28KbhUVT1fIJ8+N7ToUogzqjkdKleHdv/U+WqlFBAB5xptrMAxlaVGKawYgxJKOek2JMkmxbysAfOKBuJsfRdSE7T4dfkIrNh4ks58o9xbVHfJdLOerid5J+RKi5Rx1tHl5h2/Si5Fc4eDd84a2+3weEk+tpJCtvvN4fbBpJNDIhHRrZPFIhFkUjEkEQpBw4tRP9laiYfnj8AHm06yUsA9vgBsTh+eWToWLR1OiEQibNxVDblUgty0KFgdPphjNKyWzZ02F38iSX0XL6s3ZRWKRSLYHD58+a9zKLkhE/EmNZrbnRw275R4LfQaWY/s2nwwaK8Oc0BP+FkomWeffZb3/x966CH654ULF2LhwoU/lUgC+hhXTBBIgN7hUvQtlyxAu9x6hB6yx7RqObbuq2X5/bfuq0V+VgwnxkPFVihQ2UYU3B5+l5Xb031+VCjdmkoQoI55d8MJutEas4kYde+ls4fxUs8Y9SpOYFyjlEIsFmPDd1UYm5fIW8NCuZ2ocYQvap02NxaXDGEVbi4uGQK1UoLkOB0d72HO2dLZw2B1erFsdj7e3dBNZllWnA2lQgqry4eXV3MD9L9ZUMgpBF1cMgSfbOMyCQAEbhyRwlrUFTIJ6lvsqG+xQy4Td7fptlegfHIOXv30KGdOzSY1lswcSrsEFTIJ7rg1Bz5/EHoNmWbNLLyknnVmop5+L9Z8W4my4kG8yQzNHU56Q8QsFr5UKwChGFOAgAj4UQSBQWBImiEyC/OPwSUsLL2KS5VSWpyNv350EL+YNoS2mOKMGlxsttEkm1RygkTSvQu3OvnpTzRqGWbdlIXkWC20SmnEIkGqbXOaWcexiN5ce4yXeqa5w8lRVo/eORKvf34U90wbwrkORYi54ftqgCDjHOFsyYtmDIHL40NirBalxdlwe8me935/EK9+dhSzb8rCpNFpYUphKKt+iG1pBNFh9UCjlPIqSrcvgE2hYktKadldPl5C04utdpiiFKznQN1r4shUenxrviVp+amNi8dC3oNKFlDJJfAHgrR1o5ST7b5fC2sFTaVVL5szDAPMZMIGABbrQVKcBq+uOcpR5Mx07F5b+kIxpgAB/PjRBIGhWhQ+FuYfg0taWKGP+tn7xtKtlKmd8F8/PoQX7x+H1BgNYmN1UEpAKx2qKNMXWqhS4rVIidMgxqBiLTjL5+YjSiNF4aBYONw+WF1+GCMUo3p9wdDuOJtXCcWHUc9QhYjhx3XaPLA5fKhtsvFeRywGySm2owptFjd2HLiAR+8cifMNXUiK1eGDTSdZlPo6tQzNHU64vQFMHJkKpVyKtTvP4uH5w1HTaEVKvI7DDvDJVnIcBMChg9kUZoVIpWJO0zqziWvdUov31PEZLNcXtaBTMZoojQzzbslGgkmN0uKBEEEEV8it2dThwIbvqlFyQybL/TjvlmxawVBjWL21Ek/84jrolNLuhT6UeXaxzUm/V2aTGo/dNRK1TVbEGtRoCSV6bD9wgZdOh0rgqGuxIS5aBVOIgJRGyFLPTDWS2aBXuahFUDICfpb4Kcz8K0GvLCwCcLh8vESP4cdRPzOLMldvPQOFTIIX7x+HIakGVrxIIhWj+qKVVT/z4LwCmvqFIqyMN6rRaXPBbFIjJ40/RtVhdaHkhkykJuigVkoRDBK8u32LzU0XavJdJzfdiK92n8Pd04bA6yMbjK3achqzbhzISed+c+1xzLopCwqZmN7V/7p8BGyhavc12yoxryiblx0gUoyKssgUMpIfze/3o3xyDj7efJqhUAYhPVGHF+8fh6ZOFxrbHAgSBCaOTAVBENBrZPhgUwVHAZlNaqhVMvzz69MsxUalm989NRfL5+XjYoud/V5EiE0FAkF2Ekmowyhz49LY7sSfPzhAuzuZ9zXqFKz3MLyead3Oaq5FE3KrNV2jzpiCkhHw88RVDsgDuKJ2tuHorYUViemZWiSYuJTiYnJ71bXYOanJlCX19JIxqGuycVxVX+85h6Wz81iUMkwXDLVIm01q3DcrD2+tO846f+u/a2F3+vCL6UN4XWE1jV2YPDYDcqkIf2PwwdU0WXnHFSQIOoGhttGGz7ZX4u6puYjSKlFWnI2s5CjceVsunQRBLeiRYlSxBhXmFWVDLBLB5w8g3qSFWinH/1swAiqFFOcudtFMx8vn5iNaL4dWLce7jCZq5ZNz8OidI2F3+Vg1Sb+9YySq6iws6n4m59iKTRX4n+XjkRCtxrqd3FhKj+9JyOVV18JvITJTzimFOnxgDOv94qtnuhQH39Wu+BeUjICfL64GQSCFq/Sx9dbCuiTTMwO9UVyUe6TkxkzOgqTTyGB1++F0+eBwk8WalDtn3c6zmFCQjDXbKvHs0rFo6XSxGn5R7qYYgxITCpJhc3rx5C9Go/piJxwukupk0ug0KOQSvLX+OACy58vFVhvHFbZsDjeZIFJGnccXQG2TjSaH9PqDePmTw9BpZFDIMjguMaNeAaWCP0NPqSCD6LHRSvj9QVTWstkDyicPAtBdL/VgaQGtYKj//3jzafz+nlH4evc55GXFYeLIVKjkEnRY3bw0Va7sAAAgAElEQVTU/VSSg8cXQIfNg9RYDeu92HW4HotLhrIUWfh7wnymfOMKhmWSsTce5HsYSUHxudWov/W6w2YvISgZAQJwBdlqkawentbFHq8fVpefbRldguk5lnGr3iguprXDtJDkMjFS4nV447OjrOwravdfWpwNkYh0wbR3uZESp0WSSY10sw4EgPe+OAGASz65aMYQBAlgwvBkbNlXi+kTBtB8Y2oluaiHu8Le+JydTMDXxppapJnp2xMLU2lmgpLCTN7qf5Iq5jQvRf8/Np6k3W7nG6wcS+/jzWcwr2ggPN4gSzkw4fGRRKHTrs9kFbSu3sAtIJ11UxbNGkJvBkLvxfP3j8f+U00IBoEt+2poEtPCQXGcWAn1TA+faeYopKWz87DlhxqWjKyNR+h+cdEqXguKOu5qddjsCYKSESAAvfzYQorF7vKh0+7lpEDTVg8B6NUyXGxz4oUPDtDHPFI+ArEGJa2YwjtaMu/JQi9cg5S1s/3ABdw1NRceb4B38W6zuFnuHKqqXiGT4NxFK15adRgPzitAqlmLhlYnzYMW7nKhGKc3fF+N8smDoNfKWTGLxSX83TdTE3Q0/cuuw/VkG+sHxqHV4obPT6ChzR5qxKbByq9PAwA0KgmdCZZu1vFe1+MLos3ixleh9gEp8VrUNdtZQf/zDV0IEvwKhJmaXVY8KKLlmBqroZ+DP8Bf35JgVGPl5gruZoAg66SYsbiqui7EGJQYmhnD6aZJPdPh2fFYu6OKlQ23Zlslls4ehudX7I9sMRNkYSgfOSxVU3O1Omz2BEHJCBCAXnxsDHcatbj2ZPWEW0Y6jQz1rXYWvf7yufz0JJGKQntyDTKtHZfHT3NkUfIxU209vgBrx+7zB/Fw+Qh8vr2SHsuz943Fio0nQwF9bqxDp5EhzaxDyY2ZcHkCaLe4Wfd7dwN/980LTTas3lpJjz8ziaSrv9jq5FhqD8zNR3W9BXqNAh9v7o4D8WWMiUUixBiUKBqVhgSTGlEaOVrkYjrrqs3iRpAg4158z5mZmr1tfy1vW2a7y0f2clGTz8Hq9vNeKylOg+W35/NuBox6FeucGIMSU8dl4Jn39nE2LEyXV2O7k5PZRxBE5I0Hw9JONWvx+N2jUFHTgWAQ+HjzaSycksu6x7VMoJE8/fTTT1+dS/1nwOXyIpyXWqNRwOnkUo70BwiyXTmY8ilkYmQmR+Pg6RYEggT9sSXHqAGQ9DXPhXaNQzJNJGkmA4EggTF5ZkSpSQXRbHHj2wN19N+njR+Az3d0u2kCQQKHTrdg6ex87D/VTN+zrDgbSbEaROtVlz13sQYlbihIglgsxneHL3LkG5Jpwslz7VDIJMhJM+LkefLnpFgtVmw8hfmTBmFCfiIykvTQa2RQKeTQaWTITonG7qMNCIRcQNTC+N4XJ3HsbBuq6iy4bkgCzjd2wRki8wwECUwek4ZDjPksn5yDb344D6fbT49/bF4i/IEgPbfUuQdPt2B4dhzUShkr1TcQJHC6phNTxw/AidBY7pqai8zkKKSb9fh48xnsPtaA3ccaMWSACTsO1GHK2HRcbLWjvtmGG0YkIcOsx+maTlquZXOGYf33Z2nZnW4/LrbasXT2MGQmRWHa9QPwwaZT+OJf57HjYD0yk6MRa1BGfGdSYzWIUstJl18Y4mK0SIvXISlOh8EDTLi5MAXrdp6Fxe5ljX1EbgIIAMmxahh0Snx/+CI9/+T7KsH08enQq2Tce4U2RM+t2I9vD9QhSqPEO+tP4GhVG06eb4fd5cPB0y24oSAJCpkEKoUUY/ISMSE/EdPHp5Pv/GUoGJFIBLU6suUjWDICBACXdEmFu9Mu5WLgWEYRUlapgkjKDUJ11cy4wjGQGUP8u3WKg4vJ0ky50Tw+Mn2YstKWzh6G42dbMGqIGa9+eoTVaZPZ/ZIaB+U+Y7Y4lkklePTOkbDYPFCrZHh3w3Ha+qDOq6zrREq8jpWdBZBxGLfXD6VCwusei4vuzhgDgNomG1aG0oipYyjrjYqTpMRpkZMShfhoNTKSomCxeaAMFUkWjUpjVdzbHD7UNpIM4i/+80BEq/VKMhy9/iBvsgCTJubY2TZs+I5kYY43qrBszjBOWnqke4Vb0ZFoaywOLy62ObHymwq6vUBuupF0pQkpzAIEXAP04JJiKo3tBy5Ebj4VOifcDRHJTeMPECw3yBX7wxnuEZ1GznH3LLt9GFRyCZ5aPBoXW+1YMDkHjW1cDiy5TBxSOMfw+N2j8PyK/dBpZJBJxZh1UxakEhESY7W8i5ZY3D2G0uJsvPsFmW1WWpSNmgYrp8bGbFJDo5LjuX90xxXumpoLnz/IakHA5x5rYriPqPoXPpko5R4XrUJKnAYIADKxCLWNVqgUUtbCzay4Z1b19xiru8wMx8Y2ByfBhOnKpMYDgu1i1WlkdKwpyaTuUZnxxRf53j2NUoa31h3vVduLHwNByQgQ0AswlUabxY2t+2rx+N2jQBAE/w42zDIy6hRIidNyfN9yaTeNO0tZXQ5EQHWDDdUNVgQJAulmHfYcb6AtpLSE7gr5eUXZ2PBdNR4qLeDlwDLHkC2pPb4A2rvcdEYXFdQHgDtvy+FdtFLj9fhV6XC0W1208jKb1EiJ1yHWoAp19OyEQi4BQQBmkwa1TTbaUvH4ArA6fJzsr/CCSiaFDHVMnEHJ22aZst6a2p0w6hXQKqU412iDyxNgNU6j7vPEL67DyXMdHK6yXgXGe1Fn1WF19UpB7z3egHumDUFdsw0lN2Zi+4EL2La/lu48CpEoYh1XuBXNl8X34LwCeLz+3re9+BEQlIwAAb3BpTK8ekGsyXs+8KMLSu1uP+pb7Zz2vNTun4qhrN5aSS84rRYnL7NxSyeZhKCQSeie9OGuvq/21PCe+/7GE3TxZrROgcUz8hAIBtFl98Jic+P9L0/RxJGRSDQjuXbSzDr8ZmEhRBDhw69PsdxuZpMaHXYvZ/wKuQRf7jqHRTOGYMeBCxg3NJ4mC+WrJ/L4Aqi80Am5TExbXXz1LMvn5nOfU2/qrERk/xY+pTUsKxax0Wq0drqw93gDxuYl0uwFVC2PTCrGB5sqaNaGlHgtkmI0HGUTbkXbHD4yiy/sPbO6/D22vRCUjAABPzV+bPFnhPN/bEGp3e3nrR2hdv82hw8KOdl22OMjK/jItsWnOMzGEwqS6UWtzeIM8Zqx6WKYltzJ8x2crqGDMwyIM6o4lCdU7U64rEx3USS3YjBIYOXXFXhgbj7KJg2ie9KQLrYhnJqc1Vsr8evyEZhQkIx1O89iwa05gJjMYiu5MRPKCI3APN4gth+8gJIbMsnWx+1Oup6FmqfocO4v9KLOKqSEVn5TwVHQy+fmw+f3w+rwQK+RoTAngWNdfLz5DGbdlAWdRsapWeIosx42RGzKostse3GFEJSMAAE/Z4iATpuHdzeamRyFpxePhkYpo7tpAmR22PTrB6C0eBArJrF0dh5kEjEeLh+BDzaexIThydh+4AKmjsvg0MUUj07DuYYu3q6hcpkUb609wFn0e+onAxF5bnKcBgtvzaGD+EwLq7HdiWfe+zeeXzaORVhZH6GqvfpiF80Y0Nrhwv99cpShmHJZyQzhFtWab0mONMqlWFXXRY9v3NB4zjOwewKs5IW2UEo3X2X9VyEGaLEYyMuMwaufHqELZcsn50RscBYkiF7RxDBddqmxmm6izXAQgFGv4FhqZcXZEIt70QGwlxCUjAAB/QmhRaKxqhVyqRgerx9atTyi/93q9KGu2c67G43VK+iF5xfThqC6wQqpRISUeB1WbDwJXyCIh0qH40KzFcEg8NHm03QcZeGtuRCFGmZ98FUFYgxKemFMidfhHxtPQiYR44G5+Xgt1D+FcuF0RWiX3FM/mcEZRqQl6GB1ePDV7vO8FhZ1nVaLi1V/M68oO2I2HQBe6+mDTRW4e2ouHiodDgIEdGo5Vm2uYLnhIlK/aGSwOroX8tZOF6v+icn7xldZTykxCkw26Y83n8ZT947hHY9YJEIQ/O7ENhtpBVXUXgY1kgjocvjQZffgodICNHc64XIH6AxHqm33j4WgZAQI6C/g8etT/eqp4rnwxcJi92Lb/lqOC2bZnGGsuEGktNn3N57gNCwrK85Gl92DL3edo6/bZnFjw/fVKCvOxvrvztIKJSVOi/9ZPh7nGm20VRSpYl4sEvEWOpZPHoTzDV1YvaWS1x3EDPQrZBJE9yKwzWr4xmM96TQyKORSvPzJYfqcxSVDYbF7aati4ZRcpCZo8eSi0XB7/IjRK3gXcsoVSCUvMFOmqWcQqdiXj38sGAjwFkjKpWJUN1h5r3O2rgsyibj31EgR3rXtBy+wlOPVgIggwksPf3ps2LAB7777Lqqrq/H444+zOly6XC787ne/w8mTJyGRSPDoo4/i5ptv5r3OmjVr8M4774AgCNxwww144oknIKbSNnqJ9nY7zTtEITZWR/ZZ6IcQZLtyXJZ8V4GhmQUx0G71ot3qhilKCZNejvYuL9ljhuh2uShkErp25cX7x5EB2xC1jUIuRZfDi7P1XTh4ugnDs+MBEaBRSpGdGg2Hy4eYKCUCBIHHQ60CqN4iGpUE2alGWB1eqJVSKOQStHe5EaWVAyIRjlW2IkgAh880Y3h2PM2vpVRIcK7BitVbztC1FcMGxqDqggWOUDHj4TPNuD4/mUWlv2zOMBj1cni8QSjlZHbUuYtdyEiMwitrDiM2SonyyTmwOX2QiEXQaxWw2Dww6BXo7HKCgBhtFheykg0giCCsTh8uNNnptsrJcWpIJWTNS7ReCbvDg7+tIhfQu6bmYvWWStbCXFY8iJXFBpCL9dP3jkEgEIBEIoHD5YNGJYPd5UWURgEgiCAhwlNv/8A6j7L8GtscSIzRoNPqRnpSFDzeANRKKfRaKax2P+xOL9RKOaxOD0QQQaUQY9XmM6iotSDGoMStY9MRrVMiLlqFKJ0cAX8QrV0eyGVi6DRy+H1B2N0+2BxeVkyKUsJFo1I57SMA4OnFo5Eao2G9wxqVDE+8tZcz/qfuHQMREUS8QdXr91ssFsFk0kb8e7+wZHJzc/HSSy/h7bff5vztvffeg1arxdatW1FTU4MFCxZgy5Yt0Gg0rOPq6urw6quvYv369TAYDLj33nvxxRdfYObMmT/VMAT8p+Jq06GLgaPVHSxq/ftm5eHTbys5nR6ptsWUf58qnguvbaB27jKJGHNuHoin3/mh+9qz86DTyKADaSVs3VeLKWPTWccwa0TKirOxbf8FVr1Im8WNlHgdUmI1WL3lDOv+63ZWs0g3yycPgilKjt8sKITd5UNTh5Om0i+fnIMv/1UNm8OH+2blQa2SYtnsPLi9QZyt78KWfbUoHp2Gv63qtjCWzMrDtn3VqKi10PEUhVzCsszunTkUn28/Q8/fkplD8ds7RpKdT3VKjqUTKe5ReaETaqUMa3dUceZ46ew8ON1svrkYgxLFo9NYmWClxdl4dc0RFI9Ow5madowemohPv63kXK98cg5uHZcB4DzG5CVyaoNio1X46JvT0KplmDImnW7dbDap8fD8EfD4/GizuBiZeT2kW4e9w5Ea1R2rakVctBrxJhXgv4J3m/9173tkZ2cjKyuL1+r4+uuvUVpaCgBIT0/H0KFD8f3333OO27x5M4qKimA0GiEWizF37lx89dVX11x2Af/5iJQ5ZHX6LnEmP9qtXlrBUNd7a91xVtzhk62VmFiYyqrU1yhleGXNEd7ahtVbK/FQ6XDccetgvBPGDPzW2uMoGpVGB40nFCTz1ohMLEzl/MyUo67ZDquLv7aCec7Hm89ALJLg7MUuvLH2GFZvPUMHwj/efJo+7q11x+F0+SGVkNdeHZIt/NpvrzuOaRMy6d+tDh/eXsce4zvrT7Dm7+31J1BVZ4FBp8QrnxzBpj3n8WBpAcqKs1FyQyY6bS5ybhlQyCRIN+vx7oYTvHK8ufY4kuN0rPP4AvGfMMZx2/gB9LPlZoydRkObE2WTcnifR32LAxMKkjHzxixawQBkDOelVYfQ2OaExxuk40i7Dtdj0YwhtHzMuisuCwB4xx8MAm+tO47mDs9lvtWR0S8smZ7Q0NCApKQk+nez2YympibOcY2NjUhMTKR/T0xMRGNj42XfL5LZFxuru+xr/VQQZLty9Ea+prOtvLs+py+AzFTjZd+zqqmhx8A49btYDDom8/D8Ed1B3wgZWi6PP2IjsHijGs0djh7PZ9HcM36m5Phqz3kMSjVErK1gnuPy+iPWvDCP63KQixl9bATZqAZlrGMvMX9BgqAbmXksAfxj40k63qPTyHjbDNiopIUIcnRaPaz4V09z4fEFYHX2fL0gQdBFr3x/gwgRm7EFCYJVxFk8Og1b/11LJ00Mz47F4AwTxGIR5x3mY61gUgx12twYmhmDq4GfRMnMmjULDQ0NvH/bs2cPJBIukVxfQYjJXD30Z9mA3sunVvAX0KllkisanzFCEJjpelPIJCjIjoXfH8CIgYV08Rxzlxp+frRWEbHOpMPqQmq8rsfzqfuH/0xlk9kcPkRr5RicYbrk+Sq5NKIszONkEglUoaZiPcmmlHevEZe6LvW7WCSCSimhj2W2AshI0qOpzUHXDlGsCHfcltujHDKZGFv3dS/k1JzyyaKQSaDXyHu8nlgkgilKGTmbLEiwxhD+99R4HX45rwCtnd1us6q6LjLVekg82tvtALjvMFXr9PS9Y3C0qhXBYHetE5lcoez1u32pmMxP4i5bt24d9u3bx/vvUgomMTERFy92M8o2NjYiISGBc5zZbGYpsoaGBpjN5qs3CAH/taAqqPncEFcCk06OpbPzWNe7b1Yedh2pp39/eP4IxOkVSIxWMziySDl2Ha5HaXE2Rx6TXo7MRD1Z7c74270zh2Lbvy/g/Y0nUVacjV2H61E+eRDrmLJQZhHfz5SCocaclxmD5XPzI56/ZNZQuL0+RIWsBeZx5ZNz6OPunTkUUglgc3qQFKOmZQsf25JZedi4q5r+Xa+RoXxyTo/zVz55EKI0Mnz5fTUWlwylj7U5fIgxKKFRiKFRyrBmWxXWbKvEyq8rcPst2fTxfHIsnU3KUTw6DRu+r8aabZX48OsK1vUpi2DXEfL8r/51jpSN53rlk3MQpZFh5TcVnPGUFWcjOU6DXUfqsW7nWSyZOZTz98xEPWQSET77tpLFUsD3fvK9wwun5CLepEBctBobvq+mFcx9s/IQb+S2Ab9S9IvsMgqPPfYYhg4dysou+7//+z80Nzfj2WefRU1NDcrLy7FlyxZotWzNWVdXhwULFrAC/9OmTcOsWbMuSwbBkrl66M+yAVeYXfYj6F9YYGaX6ZUwRclhtXdfPyM5mt6F8slhd/ugkEnhcPvY8ohIBgCry0+m3UYpIJGI0eXwwe3xIy5aCY8vCKvDC51aji6HF0q5BAq5BJ1WD6J1ChAgyMU4irSMOmwe1j1iY3VobbPR86FRyRAkyHPUShmCRAAqhQweXwAEAQSDBFweP7RqGaQSMZnFplFAp5ZCo5DA7vLD5SeP9XpJN5BCJoXF7oFBqwBBBCEWi+Fwkdd3e/1QyMmdfKfNgyiNAnqtFH5vEA5vAHKJGB6fHyqlDF5fEF6/H3IpeT3mfR2eAGxOP7oc7PsQRBCAGA63DxqlDHaXD1EaOSAKQkSQ16bmXqOUwR8MQCQSo8vuhV4jh8fnh0wqgccbgEohRZSOyi4js9Ucbh/UCim0StKR1GHzwKhTIEgQaOvyQKmQQq+SQquWor3LizarG7HRKgQCBMlorZQiSiOj61h6fB968w5LgeYODzptbkTrlKSCuYyg/6UsmX6hZDZu3Ii//OUvsFqtkMlkUKlUeP/995GVlQWn04nHHnsMFRUVEIvF+M1vfoOioiIAwMsvv4y4uDjMnz8fALB69Wq8++67AIDx48fjD3/4w2W74gQlc/XQn2UD+rd8gmxXhv4sG9C/5btS2X4WSqY/QVAyVw/9WTagf8snyHZl6M+yAf1bvmulZPpFCrMAAQIECPjPhKBkBAgQIEDANYOgZAQIECBAwDVDvy/G/KkRieL6alJfX20Isl05+rN8gmxXhv4sG9C/5bsS2S51jhD4FyBAgAAB1wyCu0yAAAECBFwzCEpGgAABAgRcMwhKRoAAAQIEXDMISkaAAAECBFwzCEpGgAABAgRcMwhKRoAAAQIEXDMISkaAAAECBFwzCEpGgAABAgRcMwhKRoAAAQIEXDMISuYy8OGHH2LKlCmYPn06SkpK+locDvbt24fc3FysXLmyr0Vh4Y9//COmTJmCGTNmoKysDMePH+9Tec6fP4/S0lJMnjwZpaWlqKmp6VN5KHR2duLee+/F5MmTMX36dCxfvhwdHR19LRYHr776KgYNGoTKysq+FoUFj8eDp556CpMmTcL06dPx5JNP9rVINHbs2IGZM2eipKQEM2bMwJYtW/pMlhdffBETJ07kPMNr9l0QAnqFzZs3E+Xl5YTNZiMIgiBaW1v7WCI2bDYbcfvttxNLliwhPvzww74Wh4Xt27cTXq+X/vmWW27pU3nuuOMOYv369QRBEMT69euJO+64o0/lodDZ2Un88MMP9O9//vOfid/97nd9KBEXJ06cIBYtWkTcfPPNxJkzZ/paHBaeeeYZ4rnnniOCwSBBEP3nGw0Gg8TIkSPp+aqoqCAKCgqIQCDQJ/Ls37+faGho4DzDa/VdCJZML/H+++9j+fLldNvnmJiYPpaIjT//+c9YtGgRoqOj+1oUDm6++WbIZGS/8YKCAjQ1NSEYDPaJLO3t7Th16hSmTZsGAJg2bRpOnTrVLywGg8GA0aNH078XFBSgoaGhDyViw+v14k9/+hOefvrpvhaFA4fDgfXr1+Ohhx6CSEQSNvanb1QsFsNmIxuC2Ww2xMXFQSzum+V35MiRMJvNrP+7lt+FwMLcS1RXV+Po0aN4+eWX4fV6UVZWhnnz5vW1WACA7777DjabDVOmTMHOnTv7Wpwe8dFHH+Gmm27qsw+ssbER8fHxdFtuiUSCuLg4NDY2wmg09olMfAgGg1i1ahUmTpzY16LQePnllzFjxgwkJyf3tSgc1NXVwWAw4NVXX8W+ffug0Wjw0EMPYeTIkX0tGkQiEf7+97/j/vvvh1qthsPhwNtvv93XYrFwLb8LQcmEMGvWrIi7xj179iAQCKCxsREff/wxOjs7MX/+fGRkZGDUqFF9Kts333yD//3f/8U//vGPay5HJFxq7qgXd9OmTfjyyy/x0Ucf/ZTi/SzxzDPPQK1WY+HChX0tCgDg8OHDOHHiBB555JG+FoUXgUAAdXV1GDx4MB599FEcPXoUS5cuxdatW2nvQ1/B7/fjrbfewuuvv47CwkIcPHgQv/rVr7Bp0yZoNJo+le2ngKBkQli3bl2Pf09MTMS0adMgFothMpkwbtw4HDt27CdRMj3JduDAAbS2tmLu3LkAyODxjh07YLFYsHz58msu26Xko7B161a89NJLWLFiRZ+6McxmM5qbmxEIBCCRSBAIBNDS0sJxH/QlXnzxRdTW1uLNN9/sM4svHPv370d1dTVuueUWAEBTUxMWLVqEF154Addff30fS0c+V6lUSrt78vPzER0djfPnzyMvL69PZauoqEBLSwsKCwsBAIWFhVCpVKiursawYcP6VDYK1/K76B9v8M8A06ZNw65duwAATqcTBw8eRE5OTh9LRfpX9+7di+3bt2P79u2YPHkyfvnLX/5kCqY32LFjB1544QW89957fe5qMZlMyM3NxcaNGwEAGzduRG5ubr9xlf3tb3/DiRMn8Nprr0Eul/e1ODSWLFmCf/3rX/R7lpCQgPfee69fKBgAMBqNGD16NHbv3g2AzJRqb29HWlpaH0sGJCQkoKmpCefOnQNAut7b29uRmprax5J141p+F0LTsl7C7XbjySefxKlTpwAAJSUlWLJkSR9LxcVjjz2GoUOH9hs3CwCMGTMGMpmM9cKuWLGiz5IUqqur8dhjj8FqtUKv1+PFF1/EgAED+kQWJqqqqjBt2jSkp6dDqVQCAJKTk/Haa6/1sWRcTJw4EW+++Says7P7WhQadXV1ePzxx2GxWCCVSvGrX/0KN954Y1+LBQD44osv8M4779BJCQ8++CCKior6RJZnn30WW7ZsQVtbG6Kjo2EwGLBp06Zr9l0ISkaAAAECBFwzCO4yAQIECBBwzSAoGQECBAgQcM0gKBkBAgQIEHDNICgZAQIECBBwzSAoGQECBAgQcM0gKBkBAgQIEHDNICgZAQJ+hrBYLHjggQdQUFCAm2++GV9++WVfiyRAAC8EWhkBAn6G+NOf/gSZTIbdu3ejoqIC9913H3JycjBw4MC+Fk2AABaEYkwBAvoJTv7/9u7ex5QwCgP4w3STSDRMQ5Ao6Gh0U1IREZGoVDoKIhr8FVMr9RLa0SqmE9mEROKjETQKRiKD7SSye+/eezfD3Ozzq88kT3fynndy3rc3NJtNLJdLyLIMu90On8+HarX6UKfrOmKxGPr9PgKBAACgXq9DkiTLLrCkn4vjMiILOJ/PKJfLyGQy0DQNyWQSqqp+WrtYLCAIwr3BAEAoFMJsNntWXKI/xnEZkQWMRiMYhoFCoQCbzYZEIvHL7cG6rn9YX+9wOHA8Hp8Rleiv8CRDZAHb7RaSJN0XKAK4r1kvFouIRqOIRqPo9XoQRRGHw+Hh+8Ph8CPeJqH/D08yRBbgcrmw2Wxwu93ujWa9XsPr9aLdbj/U6rqOy+WCxWIBv98PAJhMJggGg8+OTfQlnmSILCASiUAQBHQ6HRiGAVVVMR6PP60VRRHxeByKotzfNhoMBkin009OTfQ1/l1GZBHj8RitVgur1QqyLON6vSIcDqNUKn2o3e/3aDQaGA6HcDqdqNVqSKVSL0hN9HtsMkQWlcvlkM/nkc1mXx2F6J9xXEZkEZqmYbfbwTAMdLtdTKdTyLL86lhE3yzv95kAAABLSURBVMKLfyKLmM/nqFQqOJ1O8Hg8UBQFbrf71bGIvoXjMiIiMg3HZUREZBo2GSIiMg2bDBERmYZNhoiITMMmQ0REpmGTISIi07wDw5cZWrhIRcgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "eSkTwE2Fnvuh",
        "outputId": "ab03bbe3-dbe4-4806-c838-a1378639d471"
      },
      "source": [
        "#A função lmplot inclui uma linha de tendência no gráfico\n",
        "sns.lmplot(data = dados, x = 'g-0', y = 'g-8')"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fe9ee518b50>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "WMN84ZmLn_cU",
        "outputId": "5ed9f965-2921-4faa-c67e-11f8e4b954d1"
      },
      "source": [
        "#A função line_kws nos permite a trocar a cor da linha de tendência para facilitar a visualização\n",
        "sns.lmplot(data = dados, x = 'g-0', y = 'g-8', line_kws= {'color' : 'red'})"
      ],
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fe9ee9cae90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "id": "9YcOfhAepWmw",
        "outputId": "05e69b9a-ed86-4a77-a878-001530ede2ff"
      },
      "source": [
        "#A função col (coluna) permite analisarmos melhor um parâmetro específico, assim podemos comparar os g em relação com o tratamento\n",
        "sns.lmplot(data = dados, x = 'g-0', y = 'g-8', line_kws= {'color' : 'red'}, col = 'tratamento')"
      ],
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fe9ee8f6cd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 121
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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t2sVnzJjBJ06cyF944QVzsFzswGO/389vvfVWPm7cOD5z5ky+efPmuEFr//znP/n8+fP5xIkT+dKlSznnnK9evZqff/75fNKkSfyxxx7jS5Ys4W+++Sbn3BiouGjRInP9R48e5WPHjo1r1/Tp083BfeFwmD/55JN89uzZfPz48Xzu3LlmpYi2FSU4jx98mahthw8f5kuWLOETJkxoV5kkXU6cOMGXLl3KJ02axCdNmsQffvhhzrkxQO/ZZ5/lF154IS8vL+d33nmnOagy0b6fPn06//jjj82/77zzTr5mzZpOt79+/Xp+ySWX8HHjxvHLLruMf/HFF5zzjt9720Gdbfft+vXr+dSpU/nEiRPjqn/ECofD/OGHHzarfzz88MM8HA4nXF9tbS3/2c9+xqdMmcLLysr4NddcEzdolqQf45ySFQkhfaeiogJ5eXkYOXIk9uzZg2XLluGNN97A2Wef3d9NI4QQQrqNcqoJIUnzGq+44oou54B3xu12Y/ny5WhubsbQoUPx4IMPUkBNCCEk41FPNSGEEEJIjL7saCCDBwXVhBBCCCGE9BBV/yCEEEIIIaSHKKe6jYYGP3S97zvv8/OdaGrquAh8f6L29cxAbx8w8NtI7euZ4uLEk4j0BJ0vE6P29cxAbx8w8NtI7euZ7p4vqad6gJAksb+b0CFqX88M9PYBA7+N1D4SNdD3NbWvZwZ6+4CB30ZqX/+goJoQQgghhJAeoqCaEEIIIYSQHqKgmhBCCCGEkB6ioJoQQgghhJAeoqCaEEIIIYSQHqKgmhBCCCGEkB6ioJoQQgghhJAeoqCaEEIIIYSQHqIZFcmgVVHpxo79VXB7wijKtWNu+SiUjinq72YRQgghZBCioJoMShWVbry26zBEUYDTLqE5EMFruw4DAAXWhBBCCEk7Sv8gg9KO/VUQRQE2iwjGGGwWEaIoYMf+qv5uGiGEEEIGIQqqyaDk9oRhleK/3lZJgNsT7qcWEUIIIWQwo6CaDEpFuXZEVD3usYiqoyjX3k8tIoQQQshgRkE1GZTmlo+CpumQFQ2cc8iKBk3TMbd8VH83jRBCCCGDEA1UJINSdDAiVf8ghBBCSF+goJoMWqVjiiiIJoQQQkifoKCakA5QrWtCCCGEpIKCakKSoFrXhBBCCEkVDVQkJAmqdU0IIYSQVFFQTUgSVOuaEEIIIamioJqQJKjWNSGEEEJSRUE1IUlQrWtCCCGEpIoGKhKSBNW6JoQQQkiqKKgmpAOnUq3rT7+qwxs7D9EFBCGEENINFFQTQlBR6cbru48ADFQ+kBBCCOkGyqkmhGDH/ipIEqPygYQQQkg3UU81IQNUX87m6PaEkZtlhapx8zEqH0gIIYSkjoJq0qmKSjd2b6hAzUl/rwd3NC24oa9ncyzKtcMfViAKrTevqHwgIYQQkrqMCKqPHz+OZcuWmX/7fD74/X789a9/jVvu2Wefxfr16zFkyBAAwIQJE/DAAw/0aVsHm2hwZ7OKvR7c0bTgrWJncwQAm0WE3PJ4b+yLueWj8PruI1CZBqskIKLqVD6QEEII6YKMCKpHjhyJd955x/z70UcfhaZpCZe96qqrcM899/RV0zJOV3uCo8Gd3SpBUfVeDe76OpAcyNyeMJz2+MOzN9MxSscUITfXSdU/CCGEkG7KiKA6ViQSwdatW/Hiiy/2d1MyTnd6gvsyuOvrQHIgK8q1ozkQMS8wgN5Pxyg7qwSji5y9tn5CCCFkMMu4oPq9995DSUkJvve97yV8ftu2bdizZw+Ki4uxfPlyjB8/vkvrLyzMSkczu6W4OLtX1797QwVsVhF2q/GxWy0iwhEVuz+rxpzJ30r4mmHFWWjyhgAAFsnItw1HVAwrzkp7e6PbsscEkl3ZVm/vv57qSvuuu+RMPL+pAprecndA0QBuPN6b73Mw7cP+MNDbl26D+XzZU9S+nhno7QMGfhupfX0v44LqjRs3YsGCBQmfW7RoEW699VZYLBbs3bsXP/nJT7B9+3bk5+envP6GBj90nXe+YJoVF2fj5Elfr26j5qQfTruRxhElMIaak/6k254zfrjZmy0wZubazhk/PO3tjW5L1XhcXm8q2+qL/dcTXW3f6CInFs35TrtUndFFzl57n4NtH/a1TGhfug3m82VPUPt6ZqC3Dxj4baT29Ux3z5cZFVTX1dXhk08+wapVqxI+X1xcbP576tSpGDZsGL7++mtMmjSpr5o4oHUnpSCaFrL7s+per/5B04LHO5VmcySEEEIyXUYF1Zs3b8aMGTOS9jzX1dWhpKQEAPDVV1/hxIkT+Na3Eqc1nIrmlo/Ca7sOQwa6VOGhdEwR5kz+Vp9cVVIgSQghhJBMlHFB9S9+8Yu4x3784x/j9ttvx7nnnovVq1fjiy++gCAIsFgsWLVqVVzv9amOeoIJIYQQQnpHRgXVf/rTn9o99tvf/tb89+OPP96XzclI1BOcOpqIhhBCCCGpyqigmpCotgHvdZecmdZycDQRDSGEEEK6Quh8EUIGlmjA2xyImAHv85sqUFHpTts2YieiYYzBZhEhigJ27K9K2zYIIYQQMnhQUE0yTqKAV5JYWgNetycMqxR/eJyqE9EQQgghpHMUVJOMkyjgtVnEtAa8Rbl2RGLqeQO9P6MhIYQQQjIX5VSTTlVUurF7Q0Wv16lOVaJ627KioSjXnrbBhd0tP0gIIYSQUxP1VJMORfOXm7yhuAF76cxf7qq55aOgaTpkRQPnHLKiQVU5zhyV1y7XurttLR1ThCUXj0Wey4pgWEWey4olF4+lQYqEEEIISYh6qkmHovnLdqsxvbnNIkJueby/AsxE9bavu+RMvLHzkJlrDaDHbU2l/CCV3SOEEEIIQEE16YTbE4bTHv81GQgD9toGvMXF2Vjz1v/0aVup7B4hhBBCoij9g3Qokwbs9XVbqeweIYQQQqKop3qQSveAvXBEhcDYgB6w19eDCwdqLz4hhBBC+h4F1YNQOtMSosvv/qx6wFT/SCZRrnVvtjVRFZKB2otPCCGEkN5FQfUgFJuWAKRnwN6cyd/CyZO+NLc0/VIZXJguVHaPEEIIIVEUVA9CmZqWkGmVNPq6Z5wQQgghAxcF1YNQV9IS+jKQ7Whb3U1Zia6z0R9BQZYVZ47Kw6Gq5j4LcvuyZ5wQQgghAxdV/xiEopOjeAMR1DYEcLzeh4bmMM4clRe3XDSQTcdkKZ3pbFvdqaQRu85sh4S6phC27DuK2sbggJmohhBCCCGnBgqqB6HSMUWYes5Q+EMKFI1DEkW4HBL2HqyNCzD7siRcsm1teP8IVq0/gMPHmtHklREMK+ZrOktZabvOkKyCgSEU0ajEHSGEEEL6FKV/DFKHqppRmGuPSwHx+GWs2/IlnHYJRbl2nHAHkJ9ti3tdb+VeJ8rzVlUN9V4ZQzhgkQSomo5GnwwAcNotnVbScHvCYAyo88lQNQ5N0yEIgBpTqzoTcskJIYQQkvkoqB6k2gaxwbACX0gBOEdRnpFzHZY1eIUIcrNaA+t0l4SL5jx7/DK8gQhys6xw2i0AAG9AgdTS05ybZUOjNwzOjcdFUei0kobdKqKmIQDGBIgCoGmApgMWifXa++muT7+qwxs7D9GARkIIIWSQoqB6kGo7WNEbVAAOWKTW9IsspwX+kAK7TeqVknCxgw/zso2gudErg3MOSRKhajoKWwJeh01CQY4dHr8MRdWQ57ImDTyjgXq1OwCdA6Kgg3MBgmAE1bqug3M+YErcVVS68fruIwADTWdOCOmxTKuURMipgoLqPtLXJ8G2NZQVVQcDR47Lai6T7bRA03Tkuay90q64etktec/NPhkev4IxIxyQBAZV5+byDpsEQWDIc1mxYvGEhOuMDdQZMwYFaDoAGIG6U2IIyzqCYXXA/Njs2F8FSWIQBWMIQ0/rhhNCTl3pnNyLEJJeFFT3gf44CbatoWy3iLBZRThsrR95RNUxvMiVNIDtSKKLhNjtFeXaUe0OIK9NzjZjgKLpqKrzQ1FVqBoAZgT+TrsFksg67FmOBuqapoNzQOcAAyAIwNACJ2RFw4ii5EF5f3B7wsjNskLVWi8gKNebENId6Z7cixCSPhRU94H+OgnG1lCOBvayovU41SPRRcJL2w8BnMPpsJiPhSIaxKCCHJcVIVlFozcMTePgAIKy2rpCbgT4ekjBZZM7Tvk4fKwZAgN0GAE6OMABKCqHxy/DIglpTV9Jx92Folw7/GHF7KkGBk6uNyEks2Tq5F6EnAooqO4DA+Ek2N3Z/9pOrjK3fJR5kaDrHPVNIaiaDk3jEEWG/BwjULRZRLjsEvxBBTarCI9fhq4bAXVbAgMsFhH52TYcqmrG/ARtiAbxFkmErGgAAFFgYGhdZ0hWceO8c+LeU3cD43TeXZhbPgqv7z4ClfX8goYQcmrryuRehJC+RUF1HxgoJ8Guzv4XG1hmO1oDSzmiwWYV0eSTATAIjEEFh6pxhGTVTDHJcVmh6Rx5LitqG4JJt8O5UQYv2YVGbE9/jsuCk81GUK3p8SG6rOg4WuM13+OWPf/Atr9UQec6JFGApvOUA+N03l0oHVOE3FxnWqt/0EAlQk5NbcfL0EU6IQMHBdV9IFNPgokmbJEBqJqKsD8CI6COf427OQQOI1COOl7vgyiwdkFwFAcgSQK8gQgiio4Va/fFBYqxPf1OuwWiICdd17aPq3D6sBzz3zrnEAUBmg74ghFkO60pBcbpvrtQdlYJRhc5u/XatnrSi07BOCGZrf14GQGSRcSrOw+jKLeq3TGd6JifU5zdX80nZFCjoLoPdDf1or8lCyxFkSEc0SEIDLwlp5kxmAMH2/KHtU63JTLAG4wg12VrFyjG9vQHwwp0njigFpjRex2dQVHTOUTW+pzOGYJhBW4PS/j6WAPl7kIi3e1Fp6oBhAwO0buOnR3TyZ7PzXWm7SKfENKKpinvI6VjirBi8QSsWjoFKxZPyIggpijXjkjM7ISAEViOKHJheKETAmNGneiW8nadEZhRqSMWA2C3CgAYcl02c1Bjk09Gg9eYAfLMUXnQNB2yosEbUCAk2ZggMFhEozfZ7QnDIgpxOdwCA1QttcB4bvkoc5ucc8iKNmDuLrg9YVil+EM3lV70vpyWnhDS+zo7ppM9v+mDI/3cckIGp4zpqZ49ezasVitsNqNE21133YXp06fHLRMKhfAf//Ef+OKLLyCKIu655x7MmjWrP5o7KMSmrUgiaxdYRntANE0385w7wjlQnO+ANxCBomqwWSTcPP9s44Jj7T447RKCYQWNPhkMRu+1rKjYe7AWU88ZikNVzahvDEIQmNkzHkvnHFk20QyaVU2HL6RD5xwMRi+6wFKrDpKuuwuJBnr29IKqu73oA2HALCEkfTo7ppM9X9+YfIwLIaT7MiaoBoBnnnkGY8eOTfr8iy++iKysLOzatQtHjx7FkiVLsHPnTrhcrj5s5eARG1g2+SPITxAU7thfhcoTHmMiFhadiCUxI9eaIy/bBk3TseTisea67BYBtQ1BRFTdrDsNJkAQGDz+CLb9pQpjRuRgeJELNY1BJCojwoC4knqv7TqMbIcFIVmDohnrzXFZkuYeJnr/PR1MmGigZ3Td3dXdHP2BnNJCCOm6zo7pZM8PKaDUD0J6Q0YF1Z354x//iF/96lcAgNNPPx3nnHMOPvzwQ8ybN6+fW5a5ooFlcXE2Tp70JXxuxdp9ADia/BEIjCfMq4462RyGzSJgXkxAW1HphjekQtONiJwjGpwbedvRZI/axiC8gUjS9QuMxQXqQGtPM9d1NAcUNPkjsIgCgmEFazYfhMMqYniRq1dy3JMN9OxpffLu9qJn6oBZQkhinR3TyZ6/euZ3+rXdhAxWGRVU33XXXeCcY+LEibjjjjuQk5MT93x1dTVGjBhh/j1s2DDU1tZ2aRuFhVlpaWt3FA/wEdnJ2jesOAtN3hCGSCKa/TLCEa1dagYAiCIzk/g//rIe5505FGVnlWD3hgrkuCxwOSyoawiaAxEZM2pRGyMhOfwhJWFALQiARRQxdnQ+5kz+FgDg06/qsPuzajT6I2AC0OCJmAMqI4rW+m+VwR9W8PruI8jNdaLsrJIe76eoRn8E2Q4JrCUH3CIJkESGJn+kx5/1nOJs87125ahiC5oAACAASURBVDW5uU5s+uAI6huDGFLgxNUzvxP3njP1OzhQDPT2pRudL5Pri/Z1dkyncswPVAP98wUGfhupfX0vY4Lq1157DcOGDUMkEsGjjz6KlStX4oknnkj7dhoa/NA76mrtJYl6gvtaR+XWOmrfnPHD8dK2rxCOaNB0DotoVAiJKDoADl1v6X3WODQAQsvc4m/sPITRRU7UnPTDaZcgSgxFeXY0esPg3KjewbkxuYuAlukTE+A6IOsamjwh7P74n9j/RS0+/rLeCJzbvCo22OfcyLsWBQEq08z2pEtBltW89WqRBCiqMfAxP8vab5/16CInfrawNO6xaFsGwnewI9S+numNH7BT+XzZkb5sX0fHdLLn2y4z0Az0zxcY+G2k9vVMd8+XGRNUDxs2DABgtVqxePFiLF26tN0yw4cPx4kTJ1BQUAAAqKmpQXl5eZ+2M9NEA+lqdwChiAaXXUKOy9pp/m9sAG63CFC16A+rEcpaJBGFOXYEwmrLJDGtAa7OAVXVzME0Rbl21DWFEJJVqJoOxox5EhmMlI7cLCsavXJc9RBRZOY2OQCLxKDqHM9v+QIhuXXQZGc/99EJa+xWMeUBe6nWeu5soCchhBBCBo+MCKqDwSA0TUN2djY459i+fTvOOuusdsvNnTsXb7zxBs4991wcPXoUf//73/Hkk0/2Q4szQ+xAOlnRoOscvpACiyTAabckzP+tqHRjw/tHUN0QhCQKyM2yor45DE3XUZjrMGdTlBUN4Bz+oGK+NhrgCgxo9kdglUSsWLvPyHf2R8wFohOPn3laLqobgvD4I9B0o5cbMErnxfZBSyJDttOKZp+RehKVvG87XqM3jGynFSX5jk4D5lRqPbe94ABj8IfUhAM9CSGEEDI4ZERQ3dDQgOXLl0PTNOi6jjFjxuCBBx4AAFx55ZVYt24dSkpK8KMf/Qj33nsvLr74YgiCgJUrVyIrq/9y/ga66EA6XeeIKLoZgDb7I3DaLe3KrUUDSo8/AkEwalQ3+WQY2RwM3kDEDKqtkoBgWIXdJgIRQImp6mGkXXBwriEoqwnbJjDg6xNeWC1GFna0hJ7AgCy7FBc86zpHk1dut45Ub0pzDviDCmacN6zTgLmziVfaBt0RVYemavjJwnE02QIhhBAyiGVEUH3aaafh7bffTvjcO++8Y/7b6XTimWee6atmZTy3JwzGYKZnRCmqjpCsQhBYXLm1aECp6dxIxWBGcBxNqdQiGqpP+pGfY4cgMNitIoJhFbquw9IyWQnn3JxiPNFU45LIzMldIqqOcESDKBiVM6LrC8kaSgocqG4IgIFB5zzlADoRSRRgtQg4VNUcFzBrmg6PP4I1m/6OMSNyMbd8VKd1YZMF3Zs+OJIwr5EQQgghg0NGBNWke5KlMkQf9/gjUDWjbF1sjjIANPtk5LakK0RFA0pJMiZ80XW9XTUOReM42RSCwyZBEhmsFgGyyloGM3HkuGztgvhYmsYhSMwMuKMDC+WIhnBEgyQyOG0SshwW5Dit8IUU8A5qY3emOM8OURQgMaDyhNcs6xd9X2JLuZJor7XdYpSlSlYXliZbIIQQQk5NFFQPUslyf4/WeLH3YC1EUUBulgVujwxN5xAFI4DU9JZcZI52NZ+jEwnkOC1o9MnQ2wSzZg5zy3TgOVl2s/KFN6gY1S9aep4T9VKj5fVtp0aPDfZVjSMU0XDCHYDNIkBgDFoK/dSjSrIQklU0+yNQYtbf6A0b7yPBDI2AsT8skmD2OIMxeHzhuMGQDMDks4bE7aPBMtlCqoMyCSGEkFOd0PkiJBMlmnhEFAXs/OS4+bjLYYUkGqkWmg5IkojiPDtKCp0YMyKnXfA0t3wUNE2HKArIz7KaoSyDkbZhkQQILcFpRNVR1xCExy/DabdgaIETI4tdkERmbrO7LCKDP6jA7ZHjAuSOeANGnnh+tq1loCPM981h5Gp3xioJaPCE4gJqwHj9n/5ahYpKt7mPZEUD59ys+JGJky1EL8yaA5G4C7OKSnd/N40QQggZcCioboO17X7NUG5PGFYp/uO1SgLCETXu8fxsG0SRQRSAknyHkTOdpOxb6ZgiLLl4LPJcVgAMtpZBhMYMiByqFp8OwmEMeqyq86HaHUBVnR/eoAJZ6dk+lmMGVXZGbEltCYRVyIoGj19O2CXd4fTqLctHVB2y0vraaA0SAAgrujlYMbqPgmEVeS4rllw8NiMmW2gr2YXZjv1V/d00QgghZMCh9I82XHf/FKGbboF6xlktlZIzU7I0BLtVissJdtotUFQdEUVHMKx2eos/OjV5RaUbL237CopqBNKcJ6+2wTlS7lHuDGOJBzgmWk5gDIwZFw5yRIMksO4F9DE9ztEhkW2/GZzDHKwY3UeZrrNBmYQQQghpRUF1G7YP3oP1D68hvPgGhO9cAW3osIS5tgNd7MQjVskYXKdpOi45fyT2HqyNe9wiCbhx3pldCgR37K+C02GBzSq2y1OW2gx6TKdUPwvGjHSUHJcVgsCQ4xIhK5pZmq9L2wRDnssYtLluy5cIyqo5W2Pr9hBXKaUjmZKnnOzCLNX3SQghhJxKKP2jDb2wECwSgeN3LyJ3Wjmcq1dBCPj7u1ldliwNYf60byd8vKtBXTS9xGm3YHiRC6OHZqOlEp5ZEi9V6b4fIDBAEhiG5DsgCAyaZpQI9PgjXQ6oJZEhP9uGFYsnoHRMES45f6T5Pjlae+ftFiGlmRIzKU85WX44zQhJCCGEtEc91W34Xvg9LM+tgePV30HwNMP5y0dge/UVBO/+OeRrrgMXB+YuS9b7mShYTkd6QttezFDMJC5tq3d0hAGQJAGq2nGeNIuZHrGzuFhvGShZ4w6gpMCJyWcNxZa9R8Fa0kG6ElhnO61xPbPzp30bAPDH/VWQFWNCm4JsK26Ym1pPf2eTxwwksRPeDPRedUIIIaS/DcwIsR9po0dB+8V9kK+9Do41z8D2zmaIx44h+/alsL+4DsH7H4QyfVaPJhtJt1Smzk632PQSTdPR6A1DYAxWC0NY0VMOXB02EVlOK042hTpcjvPUpx0HjB7mwjwHZEXDp4fqIYkCdM4hsvjUFKskQNWNEiCJUrWbfTKafDJue+pDXHL+SMyf9m3zv0Q6S+3ItDzlwZIfTgghhPQ2Sv9og3NAc7iglY5HcPUz8LyxGZGp0wEAls8/Q+6CK5G95BpYDn2JLmY59Jp0VmmoqHRj1foDWLF2H1atP5A0LSE2vaTZJ0MUBBTk2DCkwIVRJdnIy7JCFFiH+4gBkBUNgZCSUg5IVy5kYvdDXVMYOS6L+Xox5ls/JM+Ogmw7GDNmVhSF9k2xiAyyomHLvqPYsucfSbeZSmpHUa49ric/JKuobQjC4490uL8JIYQQMrBRT3USHIDmyoZ+4Uz4x0+A5d0dcDz1JKT/PQTbrj/B+v5uyIuvR3DFL6AN6d9yaenq/eyox3tOcXa75aO9mCvW7oPTLoHFRNA5Lis0nSPXacGJhmDCnmtJMqY8D7ZMia6laXCjILSWwTPKB3JIkgiXTTJmYORGOklBlhUrb5qMFWv3oSDHDl9Qgaox2KxCSx4xzOnVRWaU3dv5yfGkvdQdpXbMmfwtAIl7+AGG/Gxrj+8wpGsAZKYMpCSEpAcd84SkBwXVneCMQcvJhX7VQigz5sD25h9g/80zEOvqYP+v38G6eSPCS5cjuOx2cEf/zJrX3SoNbU+k/pDSLij0yCrWvn0QazYfBDhQkm9H2ZlDcKiq2Xwd5xy1DUHonEMSWytujChyYcXiCbj/hY9R3xxGRDVykAUBYEyAKDA4rCK8QSVtATUACEwwJ5iJqDpKCpzwBiIIhFWIAmsJ8DmCEQ33v7gfHr8Mxhhys6xw2i0AgG9qfQnWbFwArFi7r0upHdXuAH6+di9qTvpRlGvH1HOG4lBVMypPeCAKQtx2u5tfHb0gUjWOYFhBky+MyhNeXHbBKPMiIJUfzv5IJSKE9B865glJH0r/SBEXRGiFRQj/eCm8f3ofwWW3Q3e5IPh8cK56DPlTJsLxh9+D9UP9ve5UaUiUqlDtDkCLmQUlGFbgDUaMyVY4BwdHdUMQb+85iqo6H3xBBYePNaPBKyOi6lA1jnBEQ31TCHUNQZxwB7D0yQ9w3B00S+4ZE8UY05iHIxq8QSWt+8KYYl1HttNi7oeFM8cgx2WkowBG73OWw4KIoqO+KYS8bBs0XUejV0YgFDFL78XOsqhzbk7h7gsqOHzcgzWbD8alg7RN7UDLsqGIhiZvyNzPew/WYm75KNhtRu9+o1dGbWMQwbDS7fzqHfuroGocvmAEmg6IgpFDvu1jY6bHVKuO0IQvhJxa6JgnJH0oqO4iXZKgDh+J0M/vh3fHboSvuQ5cFCGeOIGsf1+GvDnTYPvze32ab52sfF5HvQyJTqSSKMDjj5jLeIMK9JZAUhQECIyZg/mCsgZN1xMO7gOM4NkXM3tib19qxJa501smYmnyhuENyPj1WxU4fjIARdXhsksoKXAirOhgzAiWnXYLCnMdEAUGj19BnsuKyWcNAVommuGcm4MbjYsCHSIDdJ1j21+qzMA00cWNP6jAZZdgt0pxP1gb3j+CsKxB1XQIrCUVxCfDG4h0qw602xNGMKwAYObFgNDS/h37q1L+4Uw2E+dAHUhJCOkZOuYJSR9K/+gm3WKFfsbZ0FY/C/mGG+F4chWsf34f0sG/I+eaqxCZczECDzwM9cyz+6Q9Xa3SkChVIcdlQaNXhqxosEqC2bssigNkRGYC0Yog0RsEggAwMOict5s9kQPwBBT4QkbwydCaM+2wSbBbRQTDKlYsnoCKSje+PuFFgycMreX1AgBBZGYdbgYORdOxZtNBjBmRg7nlo7Dk4rFxKRaBkIIcl9VsQzCswBtQICsaRJG11LpmZgAcCKvdqgNdlGtHky8MUWj9ceQALGLrj2Mqefc04QshmaWn+dAdHfOUa01I11BPdQ/pNjuUC6bC//s/wPvy76GefQ4AwLp7F/JmTUP2HcshnKzv51a2lyhVQZJEDC90mj3edovYElAnDqp7a9bEzggMZipH2xboutGD3FEWTnQZXefQdI4TJ/2oawzCF1TMH5LXdh2GJAk4rSQLQwudsIgCdLTuCT2m91rRdPyj2ouXtn0FAFixeAJWLZ2CFYsnYESRy9zPwbCCRp8MNZpi09LGaI+5JBo55t350TpzVB503fgxjKg6NN2o++2wiSjKtSf8vBMFyzThCyGZIx2TSSU75s8clZcxE1URMlBQUJ0GnAOa3YnIZfPh/e8d8P9yFbRhw8E0FfZXX0HBpHFwPfFLsFDHtZj7UrIT6cJZ38GKxRNw/SVjUZBtha5zqJoORTPSPfqbwIDbF5Yiz2VJukyqoT6HEVwzAIqqwxOQceaovISpEllOCxgzLiQUTW93QaFzo5d5w/tH4h6P7udwRIU3oAAtlUcsktCSt80gCgwjirOQn2PH8CJXp+1uW/Zwy55/YO/BWjhsrT1Nmg7YLSIskjHTY6rBcndSiQgh/SMd+dDJjvlDVc2Ua01IF1H6RxpxMGhZOQj/8BZErrwa9nVrYX9xXctgxl/C9l8vI3TPLxBefAM469/rmdIxRTha48XOT44jHFGNwXt2Ca/uPAy75Qi8IRVOu4TCHBua/REziBQFI20gFOmfAJtz4NdvVaQtRzs6m6MgMDNHGuDIy7YBMbdDs50WBMMtOeJtNi4IRkqIDo6axhBWrT8Qd7t0ycVjsfuzalSfDMAiCcjNsoFzjkafbKSQqHrKPcKJRupv+0sVXA4JxfnOlsGlChTVmICnbUCcyq1cmvCFkMyQrnKqiY75V3cezqiJqggZCKinuhdwxqAVDUHwP+6DZ/cehBdfDy5JEGtrkfWz5cibORXWD3b3axsrKt3Ye7AWOVlWFObaoWo6mgMKAI765jACoQh0ncPlsGJEcRZGDnHBIgoYUZyFIQUuSCJLZb6WtONI76DH3Jbyf4qqQ9ONVA5V5zjZHEa1O9Ay+M9IlRAFAVkOKa4qCNBaEzuaTtL2dikAPLZ0Ksaelof8HDscNglOuwUF2TYIzAjIU+0RTtQzpXMdIdnI/HbaLRha4MTIYhecdilufaVjiuJSUyhwJiSzpZrWNdDWTchgRUF1L+JMgHr6txB48hl4tr+LyJyLAQDSV18g99rvI/faq2A59GW/tC02OPMFFTBmpCP4Qio0nQNg8AZaK4EYg1i4eZJ12qQBNVV7d9U3hcwBmVHRmFlRjYocHr8MTdPBuY6QrEIQhLgLCt4yxbnOjenRk90ubZuCIYpGjeplV5+bcpCbaKS+JApQtM5//FKdLZMQkhl6cwwEja8gpOso/aMP6KIEfdwE+H7/Oiwf7IbjV4/CUvE5rB+8B8usqZCv+z/Ak/8PEDvPp02X2NuGEbWlDjUHVE2DRRJaysgZgVpIVuHxR6BzoMETNqbtVvs/v7q3cMBMB9E0Dm9Awfypo/HH/VUwdkn79y4wI1c6L8sa93js7dJo0Lzhg0rUuAMAGEryu9brk2ikvtNugT+kmFVbIqre7scvXRM8UDUAQvpX22MwOplUuo/J6DroeCckdRRU9yFdskC+aC6U6TNhe+t1OFb/P4jHj8G+/lXgnc1w3boMwdvv6JOZGaPBma5zcJ2bvc4MMCeAkUTBqFgRM5W2pgPNPjlZQZB2oiXvMgnnrSkdgDEI8e09R5Muzxjw7eE5ONkUhDegoMkXgSQJyHFaIIqC2WNcUenGhg8qUe0OtMw8aYHKkXJwW1Hphj+koL4xaL5ekkRIIsNlk0d1+MMavTOhaTrqfDJUVYcoMGx4/0jKP5I08xoh/SvRMbj3YG2vDSam8RWEdA2lf/QD3WZH+IYb0fzBPgRX/Bx6bh4QCMD55CoUnH8eHK++Amha5yvqgeitvWafHDdRDWMAa3lgSL4DzT4ZoiBgSL4DLocVOS4rmMDapSC0JYkMgsBQnO9ol4M82IwodGJu+SgoOswKKZpmzNAYDCmYWz4Kn35Vh9d2HUZNYxA6N+4OuD3G86mMqDenIdc5CluC9EavDIkZgxHnT/t2h/nSbk8Yqqqh0WeksggtZfyqG4Ipp4HQzGuE9K9T8RiktDWSSSio7iecA3pOLoJ33wvPh38BbrkF3GqFUF+HrDuWI3/WFNjef7fXth8to8S5EURbJMEYfMgYJFGAy2HByh+VIzfLhqGFTrgcrSXsLKIAVTNmJ0zEZhHMcnUNnpAZpA9WYUXHjv1VRrWUXIc5oYwoMOS4rCgdU4RNHxyBqhnpJEBrR783qKCuIYjKE54Ofyxif0yddguGFbkwpMAJMIYd+6s6/cEpyrXDG1DAYJTxMz4T47OO/iB/+lVdhz9eNPMaIf1rsB2DnQXM6ajDTUhfoqC6n3EOqMNGAGvXwvPunyHPvQwAIB36CjnXXY3cBVdA+uJgr2y7dEwRxozIQXG+A8OLXC1VPrKQn2PDiJZ6yYlGgDtsIgQmINtlhTOmNjIAWCVm5GJzwG4VoOloGfg4eLk9YXxT60UgFMHJ5hDCEQ2azmGzCghHNFRUunHoaCOafLL5mtg9wgGoOsdL275K+mNR7Q6gyRs2J6oJySo0TUe1O5DSD87c8lFQNd2cFMf4SDhys6xwe8KoqHTj+U0VHa4rk6sBUG8XGQwy+RhsK5WA+VTsmSeZjYLqgYIxKGd+D75XXoNn01YoE8oAANaP/oy8OdOQvfxWiHU1ad9sZyO8YycviT6v6xw5LgtONoUQkjWIAkNhthUji13Q9JZKGDpHuINa1uIgywkJRXT4gqoZtHIO+IIqwrKC13Yd7jQFhgEJJ48BjB+fUESDqnEIjEHVOBq9YTT6ZEgp/uCUjinC8CIXRIGZszcW5NjNnO8d+6sgSckrlwCZWw2AervIYJHuY7A/LzZTCZgHW888GfxooOIAw5mAyLQZULfthHXzRjgffxTiN0dhf2M9bFs2I3TLMgRuvwPIykrL9job4R39/+7PqnG02oOIoiGiGjm5nBtVMgAOHQzeoAKtZYbCzvqmB3vvdZQ/rCHLZYPTboGsyEmXYy3VQ+qawnGj++1WEfVNIaiq3rJPjcBa58Y+zM9NXm2krYUzx5iDnNpWCXl152HkZlnjZopsu65MrQYQ++MNGOUh5ZbHB3rbCYnVk2Mw9rwyrDgLY4ZmYe/BWnPQY21jEGs2H4QkAIwZ6YDDi1y9doynMnFNompHmdozT04NGRNUNzU1YcWKFaiqqoLVasXo0aOxcuVKFBQUxC137733Yt++fcjPzwcAzJ07F0uXLu2PJveILkoIL7wOkcvmw/7i83A8+xSEpiY4n34C9tdeQXDFzxFa8q+A1POPMNkI79iTsMtpAWPMCKSZUW6OAzA6EQSEZBWKagyuPDXC5VadXURomg5fUOlwHTo3bhvpXDcDX8aAmoYANN0o2QduTD+ugRtBOABJik+/6egHp6Mf5KLcKvjDCkRB6HBdmVgNIF2zzhGSiopKN3ZvqEDNSX+vXHimcgy2Lbt35qi8uAC6yRvClko3BIGZnSPRtD0FgChwyApHXVOoSxV+ulJyM5WAeW75KLy26zBkIGm5UEIGkowJqhljuOmmm1BeXg4AePzxx/HEE0/gsccea7fszTffjOuvv76vm9grdIcDwdt+CnnxDXA8+Tjs//UyhJMnkXX3z2BftxaBBx9F5KJLgDQOBqyodGPD+0dQ3WCUbsvNsqLWHTBycsEgCczsaVY1DsY41N4tVjKgtQ2oWZvHPf5Ipx8P5wAYh0USzF7VOp8MxgQAOmI79hkzLmw44wiGVQCp/+Ak+0GeWz4Kr+8+ApUlr3Wdqai3i/SVaKqRzSr2W9nJRGX3tn1chSyHBU67cQxoqnFO0TUOi8jaTYBlpIkxhGQVedk2865OR0FzV0tuphIwZ+rdMXLqypigOi8vzwyoAWDcuHH4wx/+0I8t6ltaQSH8j65C+KZb4Hz0IVi3vgPp68PIXXINlKnT4X/4l1DPKe3xdrbs+Qe2fVxlnmQjqo6TzUaPnpEXzKFzBtaS/gG0/p8YYneH0yYiHDHyzjvq0WYMcDmsAOdmDqGq6RAYgygAsRMmcg5AAHIcVmTZJWQ5rT3+wSkdU4TcXCfe2Hlo0P14UW8X6SvRVCO7VYKi6h2mGvXGREoVlW6s2/IlZEWFRRJhtxrnH0U1yqdaJAEOm4Rmf2sqmlEJKP7MpLQMatY0QFU1nHAHcP+L++Nq7LcNmmPTrIJhBd6gAkXVsW7Ll7h5/tnt3luqAXMm3h0jpy7GeeaFRLqu44c//CFmz56NH/zgB3HP3Xvvvfjkk0/gdDpx2mmn4c4778SYMWP6qaW9aM8e4N57gb17jb8ZA5YsAX75S2DkyG6t8tOv6vDY7/4KnbeWfmtLYEb9aZ3r0AfvpIppIwpAlsNi/rAlSyUvzrfjJwvGYdMHR9DkDcFulXDiZKD1lqymmxcyAgNKCpxw2iX4Qype+MXFffumMtCnX9Vh0wdHUN8YxJACJ66e+R2UnVXS380ig8yPHt2FbIcUV0aUc97uOP30qzo8v6nCHBwsKxpUleOWq0uTfi+j3+G6xiBKEnyHo+s82RwyLsQ5oGkcotiSrseNu2jR2WKjV/mSJMRVBmpLMKpvwiKK0HQdDAwcHMV5DogiQ36OA48tnWq+92BYxcnmEBgYGOPQdKA4z9HheyNksMjIoPqhhx5CXV0d/vM//xOCED8yuK6uDsXFxRAEAW+//TZ+/etf491334UoiknWFq+hwW+ccPpYcXE2Tp70dek1jOuwbd8KxyMPQao0qkZwmw2hW5Yh+O93gGfndLqO2N6SYFhFSFZhaenNS7hNAEV5dnj8kbhlGAAmoMNAu22Pq73lxyTjvoBdEP0Ry3ZaYLdJxgQsXtkMriUByHbZIIkMSy4eC8CYYVFRdQTCqnnHQADABCORuiA7OvBRQ57LihWLJ6Slrd35DnYk3T1x6W5fumVC+9Itk86XfWHV+gNoDkSQ5bCYx26i4zS6XGxKUkfHczS1ou15oTDbihvmnonSMUXmOhs84bh0jo7ukLnsEjSdI6LqCT9HsSXVTxKNiwSh5WJB040OAoExCIxh2dXnYMf+KjQHImgyJ5gyBlRLIkNetq1L56qB+vnGGuhtpPb1THfPlxlXUu/xxx/HN998g6effrpdQA0AJSUl5uNXXXUVgsEgamtr+7qZfYIzAeHLrkTzh/vxj7seQCArD0yW4XxmNXInngvHS+sAJfkAuS17/oE1mw/i8HEPfEEFIVk1aiZrSQJqBnNgy7eH52BksQtWSYAkCsbkMQk+j1iCIJil9CSRwWbNuK9fl3EYVTqsFhF5LitkRQdgpM/YrSJcDguCsooGr4x1W74EAEw9ZygCIRW6rkMSGUSRgTOYlVUavTJq3AFztsaBIrY81/0vfIyXth+iMnbklJKoBGmiVKOulorbsd9IyfMGI3EBc4MvYta3d3vC0DQjtSlW0pQzAIqqY0i+A0PyHchxWSGw6JgN41xvkQTzDpkkCkYeNjd6n6PdcYwZHQFnjsqDpulQVB0MrbXwc1xWGhhMThkZFdWsXr0aBw8exJo1a2C1WhMuU1dXZ/77o48+giAIKCkZ3LecPq/y4LHcKXjkF69izyWLEbHYYGluQta9d6Fg+iTYdmxrl/hcUenGtr9UQdc5RGb0PESXSNbx5LCK+O7IXHMq7IUzx7TcNtQRUfWkvdtRXOdmUK1qHJ6AMqh7qWM1eMI4c1Qe7FYRYIAkMEQUDZ6AAlXVIDIgJKtYs/kgtu77BowBhbkOY0Ke4izkZdkgCqylpyjm12yAaFsLur45jEAoAl3nNGkDOWVEZ6rNz3EgGFaR57JiycVj292h6eokLm5PGCFZM+8EtmRkAADCEQ079lehKNe4g2h0XnTcTkEwziIRVUeNOwBV1ZHjkCAKAiyigKI8B04bkoWSrqAXRQAAIABJREFUAicsomDODgvEzwrLGJCXbYMoCjhU1YwlF4+F3SLG1cJ32CQaGExOGRkzUPHrr7/G888/j9NPPx2LFi0CAIwcORJr1qzBlVdeiXXr1qGkpAT33HMPGhoawBhDVlYW1q5dCykNZecGsh37q8AEBp/owFuX3IS9F16Nf3nneZR++i7Ef1Qi5wf/B0r5BfCvfAzq+Inma3SumyXUUskCCsoazhyVZ/5dOqYI+VlWNPgiKbVT1TlY5mUbpQXnHFv2fgPGOMABHa0XL9EyeYAxaU60skqjN2z+KAXDxgXIsJaZLgHjdvGGDyoHxMj4trWgjffA4A1E4LAZxx/1VpFTQemYIsyZ/K0Ob23HDp7VNB0efwSqpkNRNNz/wscIK3qbkpd2NCaZkVXVdLg9YVx/yVg8s6HCvJvYkWhwbrMIcNotaPSFkeO0IjfLgiZfBA2ekDk5lN0mAZxDEBjys23mwHVJZMhvOT9xzuH2hFE6pgg3zz87rh5+pkwSRUg6ZEy0+d3vfhf/+7//m/C5d955x/z37373uz5q0cARW4dX0zmOWfPx8nX/gdHTF2L5X1+DZc+HsOz/C/L/ZRbk7y+E/xcPwO0JQxIFswZyqpOx7D1Yi9OH5ZiBm8NugRiIgDEhadpIrFM0pjZvhZq/hkn3Azd7gGKDUlXTYWkzLkDTdNQ3hjGkZdBiX5TvSpYn3bYWtCQJ0DQ97jtBvVWEGKLH54YPKlHfaJyLsxwWNPtlNIMhP9sadzzPLR+Fr4//PeG6dA7YLQJKxxTBaRPhD6de31TngD+kgIEhFNEwtMAJxhg8/giafTLGjMjFotnfwdEaL3Z+chzhiAqBMVgkBsYYGr1G28WWQH7F2n2wW0Xomo5mXwQAR0mBE4tmt++tJ2Qwyqj0D5JYoluJQVlFzagz0Lzpv+F97U2oY88AANg2b0DBlDL8aM9/oRgyjBJ5qQe7jd4w1m35Elv2/AOr1h9AtTsAQRDATplEjt6l6UYPUHT2REXVICsaBCbAYYsPqj3+SMrTlKdDR9N9t/0O5jgt5kRBmTSlOSF9pXRMEcB5S+cGhz+kGBU6GOALqbBZRLMk3as7D3d8N5ExbNnzDwTk1ANqQWBmDrSmc8gRDR6/DKfdgqGFTuRm2cyBhXsP1iIny4qRQ7JgtQiQFR3hiAZN4whHNATCKgTBaPuJkwE0+CJGpRBmdAykS39Oq05IKiioHgSig2NkRUMgFEGNO4D6xiD8IQUVlW7IF89F84cfw//kr6EPKQGLyJi2az2eePZHuO6rP8HGWwcz5jgtZt5zIppuBOxb9h1FXVMIFkmArnNQdb30UTRuBqMCY8hzWXHZBaNgabmVGg1SVU1HjssS99reTLGITfFoG8THfgc55xBFAS67hCH5HeeWEnKqqqh0o7ohCJ1zRDs3dG6MN1EUDcGwAl9Igayo5vOJGDOvBvH2nqMpd46IIosZTNiq2R9BVa0Px+r8aPLJWLX+ADZ8UGke9+GIBjnSGrhHX85gtLvZJ8eNzdE5RyCsYsP7R1LeL8l0dFFPyECRMekfJDnzVuL7R1DvlSGJAgpz7VB1HpcOELrh3xBecC2c//k0HL95Fq6gF4v++ze46OO38c68H+O9UefD6bCYs/R1iBsD63KzbGj0hk/ZtI7eoqo6mABcdsFozJ/2bQDA6cNysOGDStS4AwAYJFGA2qaeeG+mWHQ03XeiiRwWzf4OBdGEJLFjf5XZS902c07niJt0q9mfvLeXc0Dr4gk42TwEQGugrOkcXx/3QNM5ivPsgEWENxCJuycZrQwSrRoVO4iRw7hTpYOjrqnnF/ptx210NLEOIf2FgupBIjqj1RCO+NqniD/pcKcLgRW/QOjGH8P1y5Wwvf4aitzV+NHvH8I1pRPw+zk/wk5hBCTByO5Nlmtt9KjocNgk2CwiAqkE4iRlHICFGSPqT2/JYz7hDiAsa8hyWpHttMAXVOAJGIOXclxW+IIK/EEFgZCCVesPpH3QYmfTfdPMZ4Skzu0JIzfL+v/ZO/M4uaoy73/PXWrtPZ10NsISlrAFDMgWyCQEYlgkiDhgXGAYmRlHcX2HcXlHcdQZdcZXRwdRVEA2F2KUJRpCApE1YQs0AUJICzTZOum1uta7nfePW7e6qruq1+o19/v5dNJddeveU1XnnvOc5zzP76G1c2CDs/fieazwxv/WrjTzQnqfMMN8W95xZEHKiCdO5Ia0jLz9/S3qfXwmCr5RPYUYyqDjzJhB9w/+l9Q/fYro179K4NGNVDW+yKcaX2TpomXcs+xaWmpmcqAj1ee1nhdCUxW64hnfoB4lDNth57ud7GjuLHi8oztDxrCYXhsBIGPYdHZnSBk20bBGVbQwyQkGLgU8GPxy3z6TkdEoB14O6qtDtHSkBsxGGYfaOn2QEt7ZP8TiZKInQbuhLjrQ4QNSbFHfnTTJGDY33vL0hPpufQ5d1Jtuuumm8W7ERCKVMsYllCEaDZJMjiyhY9ubB0lkLLQ8kVLDcqirDLL45FlFX+PUTydz5VVYZ56Ntv0VlIMHmLHvbf7m2YcIxrvYMf1oDD1Y9LUSSA0hMcZn6JTqiqbtZpe62rFu2XLDtEkZdq7apSIEu3Z3sm1XK4blIKVkf1uSZ17dz/M7WphWHaKhLpI750B9sKEuQipt8trbHbR2pUmk3YJBz+84yHOv7+9zvnJTjntkNJkM7Ss3E3289OJwDcshFFBJZCxe3tVKQ2141Pvqllf28qv1O7j/ybfY9uZBKiN6wTXbulK83NQ2am0Ya3pL+clsNcVISOcjFx5LS0ey388jn2Lfb2VE5+VdrTjSrfTo7dRFQhoVEX3Mvtv+2jiR8Ns3MoY7XvpGdS8m+iTRH70HHc+TeMWSo0oOMo1Nrfxq/Q7Wvit5/tz3c9iZJ1OzcztarItj9rzBRds3gKazc/pROEqh+oSqiAnhRTlUMS2HUFCjrjLIntYEibSVTW50E4QylkM8ZVERCeA4ko7uDDJbzTGZsdm5u7NgAhqoDzY2tbJui1uYxjDtXCylEJJ4yuLVt9qZXR8dtQltMgzCE7195Waij5e/Wr8Dw3JyybVeVcDdB+IlHQ3l4PXmTm576NWixrxnXG59raVPLPVkplg/mDUtwkcuPJa398W455E3aYulsGyHeMpky2stbHr+XRqb2voY2MW+34a6CA21YXYfiNOVMEhnbCIhjeqK4Jh+t/21cSLht29kDHe89MM/JjhD2boslizW3/GeF0dVFSIhjYNxk++oJ3HNbzaR/O5/c/6mXxNNJ7jmsdu4eNs67jz3o2w+5txcsNx4xfn5uDiSXPjFrQ+8BtL1FoEbomM7EseRBDSFfW1JbFuSH/V4sDPND+9rRFcFDXUR/n7VyRxeX9og9hKFYkmzYDHlLuJ6Krv5268+E4VyxuEOZSxeu3lX0aS6NY/tIpaySGcsd7dpqiMlb++Lcf9Tb+fkAg3TIWM6KAIyJrR0pLh57XZCQZU59VFWnjmP5dMrS37e3md+4y1P+zHWPhMO36iewPQ2eosNPr0H9aEki5XKpn5oWwus+Bibz7iES9bfzuJn/8T0zha++ND3WTX7QX5x3jW8OufEcr9dnyEiBAQ1hbs37HR1oLNGtFvL0P1HyW6Tmv2UkLcdyb62BD/67TauWXlcyf7jGShW9lye8KKUPUZ8sQltosa0+kx9BkquHSy9x+JShZa8vr5zdxe6qlAV1YmEdJJpk87uzKFhSOexuzXJ3qd6pP4KwkNww9i6k+5uh2E6uc/1QCzDI1vf6ffzLtd36+NTTnyd6glMvtGbNmy6kwaOlAWDz0g0Olu70gS0wi4Q0BT2tCaIp0x2dCt8/9xP8MXrf8JLC84G4Oi9O/nOb7/Kvz30HWZ37BnR+/MZGaGAiiUhEtJ6Mu17HVNTESCeNPu8Nh83hEMhmbZyhWOKFVnwCrxo2T4j6cnyl7jhQL0nNF9b1mc86a2fPtwiRP1ptHvk9/WA5laYbe/O0BFL0xZLH3IGtUepEEFXntt1ASjCVZPyPtf7H//rgJ93ub5bH59y4hvVE5h8o9etStV38BlJ9bxilRhj2Vg1y5FURnQcR9IUbeDfLv5Xbvr4d3l79jEAnLFzCz/51Wf45OZfUJXsGnYbfIbHtKogQV2lozvDnoOJglAcr8y5IgThgEooqKJrpW91t/Kh269au9IlDeEF82qwbYdwQM0Z8d7rHUcSCqh9JrTBGCM+PqPFwvn1fOTCY6mJBkZUhKiUAyJ/Zya/r9dWhdx7REJ3ysSZQrHT5cLdTXPnNAm5xXpAU0hlrAE/73J9tz4+5cQP/5jA5G9vWbar5uDIwsFnJPFjxSTSEmmLiohOUFfp7M5kC4y4M8IL9cex7ervccFbz7D6sV8xrbOFi198iKWvPsrvz/wgfzzl0pJKIT7lQVHgMx9cyC/XvU4yY7nyhr0yhDwHUFgXtHSk3Mpm/WSUCtETf90VN7j1gdcI6AqRkFut0Xt83TPNNNSFcWynaFLS+Yvm9JnQfG1Zn/GmHPrpgwk1yO/r0ZCGXRWiK54hYx6aHuqBCAZUpJSuQ0C41XzBlckDePdA3D1QQiCgEg6ozOyVBO1r4/tMNHyjegKTb/Sqiugz+Iw0fixXiTGvSp8jJZrqJSK6hnw+DoINR57D5sPP4IOv/pnLn/gtkXScjz1+Fxe9tJ67Fq/msQV/gxT+JshoIB33e7NtmUtMtHsFfQjheoFShoOqMLDCQLYimyKgukJ3dbAtga4pCCEKKmZajiSWsqitDObk/AAyps2O5k4u63XqsYx79GO3fUaLwWi09+7r4aCGogg6Ymkypu+q7o3tSHTVdRRFQxrhoEYsYdCVyBDUFVKZnnHNMGxMy2bpqbPHscU+PgPjS+r1YiJJROVLCKUyFrYjqQjrVIT1QcnlDYaWjiTb3mwlGgkQ0ATJjEUibZFMWwgh3MS3Ip+HLRS2NxzHxlNWEFEcjti7i4p0nLN3beXMt59nT/VsDlQ3DLtdPsURwKpzj2TDc82Ylg2Iol5o7xGvjHAxvO1VT092Rm2EcFAnlbFxHIlpSwzTxslm7WuaQk1FkM64geM4VER6jGpVEXQlDC5872EF1xiOzGMp+pNgGi894sG2byJwKErqlYvecm51lUGuWHJUwaItv6/rmkLKcGN8dVW4cb9j1trJwYzaMA21EVZfcAz725MFMnm2U7gDpwg3d2TXnhibX9ozoM71SPBkZgfS054M97vfvuHjS+pNUfK3t0bDE+fFAdq2Q0fcyFVL7E8tIp/OQAU3n3MtD5x8EX/31N2897UnOGp/E/+x5t94fv57+eW5H2f3tMMGPpHPoPAk82bXR2npSJHKWFj91N/Jj+XsqYQpEAh++n+WAj3SVKYtaWlPYliOu5gybdfrLQQSd4ckmTazSUHusVXRAOGgVtL7PFSZx+FSSsnGl/jzKRcDhRrk9/WOuEFtRYAF82pY94yfP1CMjliaA+1JgNyY4I1Fe1uTqIpARSClxJaQylhIBPU1oZLqKyNlsCovPj6l8I3qSUSpQX0kxrYXB9jSnUGAa2A7Do5TuppfMd6tbODfV36Rk067jL/ffBtHv/s6pzc9x3v++gKPLFzBPWddTWe0Zghn9CnGrGmux8Tbjq6pDLK/LTmo1+YUqqVbsMXDK5fsxTJqisCSnjSfQBGC6grXK93encmdyLQc2rpSVEWDaKoomXU/FnGPg4nd9sNDfEYbr69Pn17Jpi1vcdufdmDZju+lLoIXErOjuZM3d3fx/nMOz4XQ6JqCaTm5JEZP5FoRrq61ZTmoimDNY7vKeg/7i3OfkeIHvk5yRipZ5imAWJaT0x0WQiEYUBH9vrI426cfw+ev/A++/4Evc6BuFqp0WPnyem69/ZNctfV3BM3MMM7qAxAOqly5dD7Qk/muDeNLsh2JI8lJ5a08cx7xpIlEIpA4UiIUQXU0wKy6MNUVAVRVobM7ky0g4yZMKopAIsgY9rhn3RdTssn3nvvSfj5jyfOvt3Dz2u3EEoZvUA8C25E8+PQ7OYWhSEhDSgc7q7svpVsl1pES23ZyVWP3tiXLeg8PRuXFx6c//JjqXuTHCA42tqocDDe+aKAyvAO9h8qIzrOvtWSLh2RVIgTUVgZJZizAHVTsodQjF4K3a+fyp5PfR6qqjmP27SSaSbDw3Ve44LVH6Q5W8E794X4y4xCYVhXk/EVz2PJaS+671FTB9rc6MPMyEfNt7P7s7WlVQQxb8vKuVhbOn8Yrf20D3MnNjZ0OUBHWSRk2H11xLDvebqczkfVkqwIhFEBSVxVE1xQ+uuK48r/pXvR3jwwUuz0W5aqnaoxgfxwqMdVDobGplVvv304ibY13UyYVXj+6YslRtMYyJFMmiifDqShIKRHC3TlzQ9IEqiJoi6XLdg9ve/MgiYyFpvbMTYblUFcZ7HONidwHwW/fSPFjqsvMcGOrxnqLub9t71Lv4e19MXY0d9LalSYUUDGzK/+soARImYupFqK0eP9AWKrO2pMvYsOx57H6xT+w8tkHqIu387kNP+bybQ/yyyXX8tLhp47sAzhEMG3Jw8+9i21LbMehozvNG+929onRkb1+11U3HtrzMHt0dBsoisBxHG5e+wq6pqJpAomCZTnEslUYZ9ZFWDi/nvVbmwloaRwpc4owjhR0xQ2Oml01yu9+YAaK3fal/SYOwhNGzzIeRvlwGcz4vmZzE53d/o7ccGjtSrNwfj3LzzqSgwe7c5/3ntYEVsZVKFKyiiEgCQc1mvZ0ceMtT5dlvh2MyouPT3/4RnUJhhNbNVRDPH+AnjW9guXvmT3kAaE/ybJi76ErY7HumWam1YSIhDT2tyWxHUk0pJPMWFi2q/aRTJvMqY+SSFvEU/1X5BuIeLCCW8/+GPeftJK/e+YeFm/fzBEH3+abv7+JF49cxG3nfpx3ph8xomtMZYQgV8rX+7s/Q0TJLoS8SocgUFXXC+2VFAeJabnPOkgCOsSTForIyjdaDrE8CavWrjRVUZ2OuFvV0zOJLFtOmAmnWFLv3Rt2Ul8dIhRQc55qD7+k8dgjpER99x2QDlLRQFEQqgKqCoqCVNRsbJFwHxPC3dFSFBAK0rWq3HN5VUTHyCgfzPje2NTKntaEH/IxTJJpi8amVpZPryz4vGsrg9mkbInlSAKaQiig0Z00UJXyJRWOVWK1z9TFN6pLMBzP1lAM8d4DdEcsNawBob+V9d0bdvZ5D6mMjSN7jAvHrRVLLGmiqSLn2TQth9OPm86j2/bilKkcWEvldL6z4nMc955L+cTjd7Dgne0seutFTn37JTadeD53n7Oa9oq6slxrSiF7eaAHmLEd6cZfRwIqHXEDTRVUVwRp7XT7rqIU7j5I3MnM+13iSoKFg1pOe9pbvNVVBoklzVyi0Mxp4Qk34RQzfpIpM2eF+R6o8UHEuwls3ICyfx9S00DXkboOegAZCLh/5/+v6RDUQQ9CMABCyWqwC4hFUbpSroGtqQg3yD/PKFdAVbKlRZU8w1wgVRWEUhAfNRjDfDDj+5rHdk0qz/tEI5mxuHntdg7EMrz4ekvB511bGaQ9lkFVBDNqw9kEbTeJ2qvWWo6kQr+gjM9I8I3qEgynaMVQDPE1m5voynr9NFWhtiqUK988lBu6v5V1fXVzwXtIZSwypqu/5smhaapC2nAf87b1Pd3iHc2dVIU1Eqnyxj29Mf1o/uWKb3LOOy/wd3+5g5ltu7lw+0bOe+MJ/nDa5aw9/XLSgXBZrzmZGWiO1lRREN6hCPjHy05k4fz6gt0QN9xDIoSC7LVQylcGqasKEQ5qSClzfddbvKmqQkNtOGeUXrns6LK+13JQzPgB0ARURAK+B2qciHznW0RuvWXYr5eaBoGAa4gHg1RreqFhHgy4/+taEUO952/3HAEIBpDBEDIYRASDyGAQQmGcYBCCQQiFkN5PIEh1y25qo2EMGcDUQ5hCI6grBTt5bbGMez+W0Pc/lFEECMUdq/rDtB1+veENgrrCjNqe/J9ISEdKSVfcJJm2kBJqKwO5yq/gh3T5jD++UV2C4cRW5RviybSZi0sN6SqNTa0FW4R7WxMIIXKVEg92pKitDAxrQCi1ss5/D7bt0B5zz60q7rZ9eyxNRVjPGdVALlatuiLIntYE6Yw9cEW+4SAETx9xOlsPO5WLX9/Eh5+6l8pEFx/e8lsueuVh7j77wzxy0gU4ijrwuQ5xpCw0qDVV4e4NOwkFmkBK0qaTC4FIpC23kJBdWCDGPY/rvIsljD7a00PdFs035kO66yFMG/a45hkk0xb/vnrRqF3Xp3/MZcuxHtuE0tEBhoEwDfd/ux+h9TyEZYFl5RzMYz0y/N8ij9mKiq3paN8JQSDATw2JqenYqo6pBbBVDUPTMVUdS3X/NzWdjBrA8p5TdAxVx1Q1TEUno2juc4qWfdz70bLn0bJ/B/J+13LnnqgJ4I4cvMEhJWQMh1jCoLqiJ2FM01Tmzwlz4+pFfO/eF+lMFDp8/JAun/HGN6p78bP7t/Pm7i7qq0MsPmlmLqGvtzFQLGHFM2K7MhbdKRMkCCTBgFoQ2rF+a3NWfcA1azwtznInfeUbQk17ulAVhWjIrTYHEseRdMV7BiXLdgjoKlXRIIlU1htQttYUx1Y1HjzpfWw85jyu2nY/73/uj9QkOvn0xlu4bNtD3H7eNTx/5Gk9lt8hQkVIJWW4qxlH9u/1yl/0ONL9HpNpg9Yu9wlNEVi2k1V2EYQCKrbTk4zq5Y15UnmmZbtqML0WkYPVSV8wr4antu9HVV2FkH3tKVylkNEr2pDPWJZG9xk8xvIVmOdfiPrOW8h8Q9q2wTQRpgmmgTCMnr8N728DYZhguY9VBhTiHd1Zw9xEZB93X5NBmFbhufLP6Z3LyGT/NnvOM0RDX3VsVMMGw3VYTITgNUtRsbLGt6EFMFUta9BrBca94R3jGeqKjqHpRY/ta9Dn/Wh5Rn2v13jn8pwjXvXX/OE892v2QZH3fNqwidpOzrGFlFx0ljsmXXTWPH6z6U1sx0FX3ecFPc8Ph6FOM/nHv/pWO5te2E1bLM20qhDLT5vLiUf27RH+DsbURkjpf8X5fOnmJ+hOGDnPdDH93fyYzXwv9kcuPBaAW/64nYzp6j5rmptkoSiCmmiAG1cv4sZbngZkroKhd1/ajuQzVy4cFWPDq1QlhCCZNumMGzmjKhJUSGZ6DLBg1qOpCFeL2Bpgu66cTOtu5dqtv2HJK5tQsl3z5XkLuW3Jtfx1xlFj1o7xRlcVgrogkbFHPAgL3Iz5yrCOKiCWtHCkU2CMa9nnE2kLKSXz51QPyqNc7F5o63J3QKqiAfa3J7FtBxBoqqAqGqCzO4OUMH9O1ZC81tOnV3LwYPeAx/V3f46mh3yw7Rsvpk+vLPs529riOUNpMAgp+xrVw6CuroL29viIzlEUbzB2HDCtPsb22++20fj6PlKxFNVBwcLDKlEsk51NB+lqj6NYBqpjo9kmumOh2Xk/jpn93UZzLDTbLHhedSx0231cLXaMM7LPbDyxhYKV9eBbmpY1+nUszTXUbVXLLQQsTcfWdBxNx9F19EiYpKOghUPMnlVDXX2lG8oTCNASt9l5IEW3DcFImGOPnsHs2bU9oT+6e5wbFqT3hA/pupsImyVnBnl9WZb4P4+6uijtbXFAsmt3Fw8/24yiCnTVLVxjOw4rz5jHMXN6HGWypha7unY0PuI+TIbxaKK3bzj4nupeBDS1IOlhzWO7+nik+0tYWXnmPMxsEpequNI/7bE0tZXBXGhHsaQvTRU01JYn6auYFz3fexcJ6cSSJqoiUBSBYUlUxY0DtByJlU1acyQ4Y2hQA7RV1vP9Cz7NH065mOufvJOT3nqJU5ob+cHdX2TzCUu5a/FqWiunj2mbxhpNFZi2g1mmOdStjJhNUnUk02pCBHWVVMaiPZZGStxdjIiOpilDMj6L3Qu2I0mmTaqiAaxsVTQhXG+xdz1g1LzWfgb/BKeyCoEscPPJ/KzB3u5CUeS5uiiovWoGFIi0D3C+3kaSd0yv13lHeaWxDjsTDst72RvvdvLg02+jNii0daVxvGIl2QblC1k6soQbdJDeUSEdFMtCs0zXaM/+7xnhActAd7KPWxYB28ga5CYB20S33L/17Gt1O/88FpploFkmqmVmr2GgWVnD3vKu03uhMDgtblU6qGYGylz868jsz3CQitIr5l7PGd9pVDoNSUYqiGCQ6roKKqqjBTH8VEUJ20AgQKqpg9MdAXogu0jQSQuV3W8EOX7xfKTmGvT2e06DMTKqfcaHSeOpfuutt/jSl75EZ2cnNTU1fPe73+WII44oOMa2bb71rW/xxBNPIITgH/7hH/jQhz40pOt87WdP52KPEymD9liGGXWRAo9X2rCprQwi8icFKUmmLeqrQ/x1b6yXnq+7vX7U7CpuXL2oqCcNCVcvP3rEE38pL93ik2bmtuQDmsLugwkErpj+WHqih4SUnNb8Ep94/A7mHnwHAEML8MdF72fNez9IKjg6hXjGG01VsLJuZE0d+fcjhLsDYUtQBcyqj+b6bipj0RXPYFoOJ86vH7Sso7dw2/luJ7qmUhXVcwlD+9uSWLbN3BmVBZ5qx3FQFDckRFUVZtZFiCUMMoZNJKQNaPxOBs/GRG9fuRmqp7pcTJTP2ovrDeoq+9uTZLL5KcKTppyoY2sR3MWvyP6QLbJCtuCKu2upIFEATUgUJKqUBB3XgA/YBkHbQDNMNDODZhqopuH+bhlopvujZg131e4x4FXbyhrsJoGs1161LMLCIShthGUSxqY2pBBVenYRzFQaM5lGmO7OgC5tFHNkErCjiYxEaNv2GrJ29AOFJso9UorJ0L7hMGk81V//+tdZvXo1q1at4v777+drX/sad955Z8ExDz74IM3NzWzYsIHOzk4uv/xyzj77bObOnTusa8YSJloRj7RtWyXBv7wZAAAgAElEQVQ1b/e0JnCyHl+QWVUnUaDnW8yTdtWKBRxeP3IjsZQXfUdzJx+58Ni85DEVRYF4agJX/RKCFw5/D9s+spAVrz/KR5+6l+p4B3/77O953/aN3HvWVTx88gpsddJ040Hi+bk8RZaRTcyebrWqiJxyh+epjiUMLNshFNC4YunRuT5YLE46VzBIV4ilLCIhDV1zFwDt2WIXkZBOOKiSSEkypk1lWKOj28BVw3bfmwSqInr2+hkkgvqasYm39vEpJ/lJsUFNyRnVUjKpDGrIRj7IHj/74FGBsPsjQIRAhEXOSFcUtwqikmegq8icYa4JgS4kQU1QEVKJxzNoAnRFkkqbCMumMqSiCnBMi/e9dw7HzKlh57sd/OmZdxCKQBMCw7KxLJtLzz6cBbMre2LmvfCdXGy94cbcG5nCmHvLRBgmz2xrxkpnCErbNfxtG2EahHE4YXY0F5sfwMFMJMEwOXigC6y8UB3LRLEtdMciIG33/IDTMAsZ9HM7pjKTwhppa2vjtdde4/bbbwfg0ksv5Zvf/Cbt7e3U1fWs+P70pz/xoQ99CEVRqKur44ILLmD9+vV84hOfGPS1DMtGSolhOVi2w7ReyU0BTclKmDl9lEEWzKuhaU/MTfjK7jDaDmgqzJ4WKTAUeid9lWvV1p+sX+/iGDev3T7i640FjqKy/sQL2XzMuVz54v1c/twfqE528clHb80lM26df8aUSWb0No8kYJdBI9x1eks0VXCwM0XGdFBVV15PcV1RBHSFn61t5OrlrkRevs5zS0eKHc2daKpASnIJtqGASnVFMBfSEUuYqKqCrilccva8nBE+qy5M2nRjrS1boquuNyyWMACBrill1Zn18RkrvLA623ZIZKzcAvZQRkp3DMumQQ94vJINlbzkrMPY0dxJV0CjMqLz9sEEthNA0UBHYWZtBNN2WLdf44ZzjmDDCzG662diGBbYDkFNENYVnu8QLDhttpsAKx1wHKTjuHH8toNwLK90cDYKKFdKGCRsTG0jHNQKphMp3V29G1e/J/dYXV0F3dm4/rebO3jwqbfd8U9VMG3XJnj/4iNYMK82u8qyoGEmRKbmDquPy6Qwqvft20dDQwNqNrFAVVVmzJjBvn37Cozqffv2MXv27Nzfs2bNYv/+/UO6VlVYp6UtSSigomsK7bE03Uk3PtSTGZtdH83FVveOta6I6HQnDYRQ3NLfjhtiUUrP1/MItscN6ioCI479HKzywcL59agqZYvbHQvSgTB3n3U1fzppBR/f+huWNW5kTsde/u8D/8n2uSdy25JreXPmMePdzBFjOxDQ3Fj3cskZCtx+4HmMPK1YRRXUVLhar7bjsH5rM0DBbkc86XpZPIPYa9OBjhTBgEo0pJE2bEzLpiba04cvy17bC0mqrgjQnTJxJLR1pdywKEVQFfF1Zj0GUwbbZ+LgKT61x9I4zkj3lA49FAGHzaggY9q5RXgkpOWM2JzzHHdsCAc1mg/EkULh9T3dJDNWLtlfIpE4ROLw4eqaPtcq8Lk4EqSDsJ2c4S2y/89acDjxZIaAwNXzdxwMw2KW7sZgC+n0SCVlw9kWHF6HEIInXt6Xy6E675RZrkHtXVzXp4zjx6c0k8KoHku+ct1ZPP96Cz9b20hFRKcrbmDarpetpjKIripctWIBpx/fwPKzClMk7t20i7qqIKGgRme3G6eqZ8up9j4W4PnXW/jNpl1omqAyrBFPm/xm0y6qqyOcfnzDsNp/1YoF/GxtI7bjbvFnTFeQ+KoVC/rECLmLlNEQoR5d2ivq+OHyf2btKZdw/VN3cmrTC5y0+1X+373/wl8WnMediz/KgerhfX4TBcOSjDzww8VNmHXPpKmKm0xlu8mxXrVFAE0KOuIGEqgMa7m46/xt7N4ZGI4tSdgW1RUBZk+v5D8+ubjP9TetaSSY9WqHgxqd8QyG6SAE1FQECnRo04bFrOkVvNOaZO3mXbS0J2moi3DF0qOZPr1yVOKCy8lI2pc/HlRXBMoyHow206ZVjNu1J0JfWD69kgOxDPc+/EbJY8p1H09FhADDtImGNDriBrOmV7D3YDf725J9PP4d3RkcKZmdHQe851WlR5fbchwcObK+sXiZyq1/aCSgu3O3Ydk4Clxy2UnUHTfDPci2wXGoO8w1unEczj7B4ez3ydxz7la1nXse24aKCqgbu347Ee6R/pjo7RsOAxrVjuNw77338uabb7JkyRKWL1/Of/3Xf/H444+zYMECvvzlLxd4i0eDWbNm0dLSgm3bqKqKbdscOHCAWbNm9Tlu7969LFy4EOjruR4MbW1xfrthBwioCAdQhMgVcUmlLT522QkcXh8pGqpRVxHIeYln1LoVATOm670rdrx3HVVRsoVgFCxh89sNO4YdX314fYSrlx/dx9vVu82NTa2k0hM3oWMwNNcfzr+t+jfe0/wyn3jiV8xr+St/s+MJznnzGR489VJ+d+aVJELjN+mPlKFMxP1N3LaTbxS7MZMS11ljmE5OWjGeMkilXY9zZ8w17CIhvaBIjN3LqhbCnS9iCZOPrZhdtJ/vOxgnEtIwLVcHfUZtBCklHd0ZFCGIp8yCMKr5Myv4yZqXUFWFkK5wsCPJT9a8xD9feWpZ8g5Gi5GGcOWPB5YtyzIe9G5fuZksiYqjuQPw4ustBDQlVzirdyy1b1CXRgjBgc4UlWGdmXURKgIKbV19FUK8cMr8cUYVgJTYjuwJu5ESVTCi+/Dw+ghXnd93Dp1bFy44b/E+KCgwq5TsD1kntQNyjJLzJkMi4ERv33AY0Kj+9re/zbPPPst5553HD3/4QzZu3EhXVxef/exn+eMf/8g3v/lNfvCDHwzr4oNl2rRpHH/88Tz00EOsWrWKhx56iOOPP76PMb9y5Uruu+8+VqxYQWdnJxs3buSee+4Z8vXy45IjIT1XHjWZtvodiIdahXEoZc2HQqkiHR7edvxUGey3zTuFGz78X5y/43E+/vTd1MbauOKFP3Lhq5v49Vl/y59PWYml6gOfaJIigMqITjwbWuGhZsuSe5J6HhLQNQXHcRBCsL8tmc0lgGhIo6bSjZNuj2WQsmfCKqZC5kg3VjuoqyX7XEhX2HMwngsb0TWFaEhjTj9hVMWSbddu3sXnr1xYpk9t4jFa48GhTr4iUiSklT0htrUrTXVFgLZYZlwWGJMZRbhSrom0xYJ5Nax7prloXLqUoGuF48zs+igtHSlSGQvLdtBUhXAwSEPWoTUSBppDh8Pk0FnzGSkDGtUPP/ww999/P9OmTeOaa65h6dKlbNmyherqas444wze9773jUU7uemmm/jSl77ET37yE6qqqvjud78LwPXXX89nPvMZTj75ZFatWsXLL7/MihUrAPjUpz7FYYcd1t9pizLcimxD1ccdr8pvntFSzKpWVYFjy6zBNKrNKCuOorLxhGU8ccw5XPHSg1yx9fdUprv5h82/5P0vreOOcz/O08ecPSVj2tzwPoGuq1n5Ojdkw+79BQq32qKTrfTpepklUrohQooCadOVt5tWHaazO0N7LOOGgRSZEabXhAkHtdxuTG8am1pZs7mJ3a3JgsdNy6ErYbD01NlFJ6+7N+wsalweaC88z1TDrwQ5OvRXV6AchpP3vXmLWJ/BofRalO9o7sSRrnFs2k5uyBG441ttVahgnPGcWDWVwUE5sXx8xoIBjWrDMKiqcisCVVdXoygKkWz2ajQaxR5hZazBMn/+fO67774+j//85z/P/a6qKt/4xjdGfK2hepzzGcoKN/86miqKloYeDTyPWCCgYpp2LhlEAJVhnYqwzu6DiVFtw2iR0YP8+r1X8ucTLuBjz/6W5S8/zKzO/Xz5oe+xY/Zx/GLJ3/HG7AXj3cyyk8rYVEV1V9quiAHseau9OT+gq1i2jRAwrTpMeyydKwAUS5rMrIsQCqjsa00SDWvEkga9hUgcxyFj2iTTFppwq3Z6C0lwFUS64kbR9koJ6555h+ffOAhSkjadooWKPAzLYUZd/yEQkz3JbyTjjk9pRnsHwPvenEEo9QjcnRrDmny5LGVHiKx3WaOhNkxrVxpNVbKKWUouLE3i7rr1vhf8Ik8+ExH1pptuuqm/A5577jm2bt1KIBDg1ltvRQhBPB7nuOOO46677iKRSHDFFVeMUXNHn1TKYEZthIbaMLsPxOnKVj68YolbIvtX63dw/5Nvse3Ng1RGdBoGMdGXek1DXc91YkmT2ooAVyw5atQHhW1vHiSRsQhoCmnTzor8uwNcJKRx1gkN7GjuHNU2jDbpQIhnjzydJ49dzMxEG7Pb91Df3caK7RuZ19ZM04yjiIemTpKEBKIhnUzGIn++FsJdsAkhspUTBfXVIWqrQsQSJiCwbAclW/1T4MZgV0UDGJZDKm3mwjY0VSnYwUhlbIK6m/ho2u4W7sGuNM+/cZCd73aiaQqJtFlyx0MCiZRJPGURDqoYtuTlXa0sOqaed1q6c9rannH58YtPoCZSPIzH2+I3LIdQQCWRsXh5VysNteEB79FyEY0GSSaLLyIGQ/54kD/ulGs8iEaDAx80RFIpY1y2tYfyWXvjnab2JLQZlkNdZZDFJ8/q55WDw/veXt7VhjkIuZ4+O0iHIIJsQSpHkjYtFp80k2TGrf9gmHZOz9r7qGbVhbl6+TF97oWGugiLT57Fhe89jMUnzxqzex1Gfr+PNn77RsZwx8sBKyru2bOHb3zjG+zZs4drrrmG0047jeuvv559+/Yxd+5cfvzjH7NgwdTx/JVKvClVqbC/ks5Dec1YBu0/8ORfefDpdwoGdyFgTn2UK5fOZ/3W5klvVPdm4e5X+MQTv+LIfbsAsBSNh95zMb8940PEw1PHuO6NqvRkxxuWq/jhVTPsqXYIdVWhXAy1pirUVgWxbVdBZm9bElW4RnCxghYBza3W6ElbOdI1HKbXhOhOmmQMO+cpzyU94va53hUWu7LKIF4lSVUVudjr5WcdWfIeya9s5+GFpdy4elGZPs3+maqJN/0x2ETFcu8iDOWzHs7YPRwam1r52QOvkspMIp3SMSQSVAG3SqPlSCzLQdMUwgGVmXWRnMffsiWpjIVp2SjC1by/7NyjcueZKDtSk+F+99s3fEYtUXHOnDnceuutBY9t2rSJzs5OamsPnRr2w4nLG+1YvuHQ2NTKo9v25iTWPEIBlSuXzmfh/Hru3rBzXNo2mjTOPZnPXv09lu58imuevJNpXQe5/IUHuODVTfzujA/x4KmXYGlTL5nRdkAI16T1MuhN02Z/exIja+yqqsgWcgkQixsEdIWaaIAF82p4fscBHEf2K7xoWG4yo5r1BKpZffbWzjRCETlDOr/HCcWNbffaZFkOybRJd8oEKamvqSgIfxjofvGT/CYuo50oOBBjFSawcH49/3jZidz18Bu0xfoqWPTGW2ROZck9L9xlRk2If//EWdx4y9NEQj1yneAqEnnFycD9njriBrVF6jaMd1/y8RmIYelUr1u3jksvvbTcbZnQDGfSnogT/fqtzaQzFqriFqcBN1nEtmWu8EcyPYFLl48AKRQeO+48npx/Jh9o/BNXPvM7KtIJrnv8Di59+c/csfijPHHcuVMumdH1LvckJgLYXsiH41YR6+zOcPjsaj62wk0ezJ+8QgGFtNH/tnb+Gs3bAZG4Bja9kl5VVTCtKpQtkZ7Vz9YUYkkTJOia2m+FxWKeKj/Jb+IyEZwLo6HmUOo6//XP9UyfXskn//ORPkm6+ajZ3ZipjFcVNpayaGxqHfA+9b6nUl7MidCXfHz6Qxn4kL587WtfK3c7Jjz11aE+ySUDTdrDec1o09qVxnacnEENPXG0e1oT3PPITgL6sLrFpMHUAvxu0eV84rqf8ufT34+tqMzoauHGP32f//ebGzlh96vj3cRRQclbLDiORNcUqisCqIros2WdP3lJBOoAXcIzDWxH9gorcuO5A5rC3PoIn/vQQuoqgyiKoDKiI6Wb5V8Z1rKJSW48t0fvRahn7HcmjAJP1YJ5Ndi2mzgppRyzpF+fgWntShPQCjvQeDsXxoIrlx3d7/rcsmXOkzu1lvGFBHXXq7x+azMrz5w3ovu0HH2psamV7937Ijfe8jTfu/dFGptah/R+fHz6Y1jW0wBh2FOS4QwGIx1ARoP66hCqohR4Dnuyq93Y1uqK4JQe5D1i4Sp+suTv+dS1P+a5BecAcMy+N/nu777KVx/4DrM79oxzC8uLRKIoroEscRd4XXED03JwpKQjluKeR3bS2NSam7ySaTcmur/8KyHchZlpOwUGtSeZVVcVZOa0CGnTYeH8ej5y4bHURANICbOmRZlVFwYEIV2lKupWXfTovQjNN/Y9b7aqKuxo7sydN5m2qIkGyh4z6zM8JqJzYSxYOL+es46f0e8xqjr1R9pkxsGy7FyIR3/3qWfw/v23Hylq8I60L5ValPuGtU+5GFD9oxgvvPACl1122Sg0Z/wplc0+nMz8obxmrDJhKyM6r7zVjmFaufcpJUSCGooiiIZ1V+ElZR4yYvXdoUr+csxith9xCkd07Kauu4257bu5qPFhalMxdjYcTUaf/AaAlD0/3t8ebrlgSTxl8PKuNiojOt1Jk66EMWDAp64JaiqCBd5uRZBTWzBtSUBXc2oL+Rn7yxbNZdmiuVz43sOYOyPKq2+191H9uGLJUTTURYhGg/x6wxuEAmpBTKaqCLoSBh9dcRyVEZ29rQlau9LsbU0MSqGnXEzVbPb+GIz6R2VE5+VdrSW/1+EwGT7rZNLgtONmIJA0t8SxHAdFCDSV7Gfh7h551U2nMqmMTV1lgGWL5pZU7MhX8KkIa3SnzD4KPr37Uixh0JUwSGcsGpvaBrzff7V+B4bl5Bblmuo6mHYfiA9ZCWay9MGJymRo33AYdEz1//zP/+R+P+mkk3J/BwIBZs6cyXnnnUd9/dT2Cg0nLm+0Y/mGmgm9cH491128gDWbm2hpTwKCmXUhrlzmlmXtTBjYtuu5nOLjfB9emXU8n/vb77D0rS1cs/kO6jtbuGTbOpa99hhr3vtB7n/PpRh6+Q2TiYDjuIVhFCFImzaxhEEiG1uvKPTrqTYtSXt3pqC/OJKcRJ85CL1lrx+nDRvbttBUweys6kd+f+4vJtNPYpqYHOp6wpede1SBegXA136xhQOdaWxHomkKQsicLvNURALt3QaNTa2DSuwvlVOR35f2tCZIZ2wqIjqVEX1Q9/tEzHPymVoM2lP929/+lvvuuw/LsnAchx07dvDnP/+ZyspKtmzZwg9+8ANOOOEEDj/88FFu8ugyGXRXPYarzdtQF2HZorm8f/GRvH/xETnvgecF8Ap2eNrGhxRC8HbtYaw7eSVGRRVH73uTaCbBKc2NLN/xF2LhSt6pP3zCJjNOrwkNO9FUVxWsbCWzjOn08Wznoyo9aiKlUBU3/ENXFaqiAV7c2VpU373QQ6WjaQqKIvrs6kSjQVRkSa/n+q3NZfNCDZXGplZ+8eBr/OEvTYPWsB9rxlOnutx6wpPBy9Vf+6ZVh9i5u5OKSIDqaMANDzSmthSfENAWS5e8F+9/8q3cLpRXndLbhbrwvT2Vkb2+9EpTG4oqiIb0Qd/v5dQsn+x9cLyZDO0bDoOOqXYchx/84Afce++9fP/73+fee+/lhz/8IYqi8Lvf/Y6vf/3rfP/73x9WI3yGR6n4Uk/FY6h48W5SSqR0E9kOVSxN575T3s8/XHcLfzrzcixVoz52kC/8+X/4n3v/hYXNjePdxKJ0dA8s5VWKjGmTFQMZEEfKPhUWeyOEIBoOENRVLEeWjGEcSj/uLyZzvBLivEVBRyzlx2n6DIre/bgirKOpA79usqKpAttx+r0XhxovPZz7fSLmOflMLQZtNT355JOcf/75BY8tW7aMxx9/HIDLLruMd999t7yt8+mX0TAiFs6vZ/6caqbXRmioixzShjVALFTJLYuv5dPX3cyzJ54HwJEtTXx7zde46f5vc1jbxOrzYyXRJYsY371991JKqsIakbDer8E81H68cH49N65exPc+eQ43rl6U82aPV0KctygIBbSyLG59Dg3y+3FFWEcIJVv9dLxbVj68iq4gUBWl33txqAbvcO73gRIlfXxGyqAtpnnz5vHrX/+64LHf/OY3zJvndviOjg7C4XB5WzcO/Oz+7ZPGwzRaRkT+4FZTERj4BYcAeyob+Ob7vsiXP/7f7DrseABOa3qO/73zs9zw6E+pSXSMcwsnDgKorQwyf041adMZ0GAuVz8eLy/UoSoZ51M+XKlTma00OrGt6v5ap6mCqohbREtVesI4LNvBtB3iSaPk/Jpv8MZTAxu8w73fSy3KfXzKwaATFb/1rW9xww038POf/5yGhgZaWlpQVZUf//jHALz11lt89rOfHbWGjhWxlDlpkpu8sq4ZKCi/O9CgMlBy48L59by9L8aG53aTMqZmIZjhsr3+aD5/5X+w9J3n+Njm25nRvo8VL61nyaub+cOZV/D791w2JZRChoJXEc7zXEdCGpoqWHnmvFzya6liD41NrcRTJgfak2iqQlVUR9PUYRnD45UQ5yVPBvzCMz790N+4W1/tFkOyHWfAsCoPRQxfNaSn8NcwXqsKKkIaiZSJtxbWNYWaigCRkE7GtF2teSnZ157Cka6xXVMRwJL0O78OVPyl97Fw6CbA+kxMhByC6LRpmrz88sscOHCA6dOnc+qpp6LrU6u089d+9jT72hLURAPcuHrRmF13MINIMYaq/pGvkJBviPfWCvWO6YhlsslrrpTDYAf8QwHdMVn1+kY++Pi9VKTc766jchp3n7OajccvxVGmcJBkHvXVIQzTxrIlqiqYk6fa0V9/A3LP2barmW3ZDrOnRbhy2dF9+nF/98hQ74Ny4r3HYEBFEaLoPTURmD69suznbGuL56p0jiXDHS/Hit7tG2jcbWxq5bZ1r7tVRfNQFJBOTzlz9zHhqjNljdXhhnyJARKNi9HbeNYUQca0S76v7937Yp9Fdca0B5xfJ/r3CxO/jX77RsZwx8shlSnXdZ3TTz99WBeaTEymrVtvZe8ZFXdv2El9dXNJo2IwZV7zj3Fl1siO7hLnkBPaK42p6Kw58SI2HLuE1S/8gRVb76e2u40bHv4xq7Y9yC+XXMuL804d72aOKpoqMEyb6y45vqTnCYp7k75374s9fVFXcxN1RSQwJGN0vKX0vGts2raXfQfjvsfMpw8DjbsL59dz3SXH86M1jTnvsWfAxhImlm0zd0bPJB9LGHR2Z5BS5naKhkxW8lIMwuOtKBDSNaoqAgQ0JRdqcfX5x+beX7EFrS9h53OoMSSj+lBhsm3dDsWoGMwgl3+MprleRFWALSEYULEs13M91QsWDJaYHuWnZ32UBxdexLVP3cVZr2xm3oG3+caam3j5qEX84tyP83b9EePdzD4MezLuRSJtseaxXUDxybWUVnt/fbGY53l5Cc/BYBaKo83C+fUsP+vICe158Rk/BjPuLpxfz7GH1fTx7JqWQyLlxgx73mBNFdRVBuhMGCXv4cF4oiMhzVX96cfbrQj4zAcXAqWN51L3WX+68j4+UxHfqO6FYU0+iZ2hGBWDGeTqq0Psb0+SMmzMrMya7UgCmkI4oBKzbCIhjXjKj7fOZ09kGt++8HOcePrlXPfoLzj2ne2c8tcX+Z+3XuIvC5dzx5kfpr2ibrybCfRUPOydIDjQa/IXUpoqUITAwY2dvG3d627xFkcSSxjctu71Ph7sfGM5mbawbIfqih49UMNyCOlKwSKxpSPFzWu3c/ufdzCrLtLHC+x7w3wmOoM1LovlyeiawiVnz2NHc2fOoF0wr4ZHt+3ttyiTFy7Sn9GdMW0qwjrxlFk0jCQSVJnXUDmg8VyK4eb9+PhMVoZVpnwq8+z2fVx01uFjvnU7EiH0fNF8j2Ki+TC4ksFtXSka/9qGdNxjwPV4BDTB3OkVLD5pJoblkEgZYybhNpk4GK7hkROWseewY5m/v4nKZIwjW/7KxY3rCWOzc8Z8LHV8cxFUVWCNYKvBy+wHcosury8owp3IDcvh3ZZuli2aC/QtVmQ7kljSLYMe1NVcX9RUBbLSdGnDpiue6SlCI0SfAkflLOgwEqZqMYP+mEzFssaS3u0bbKn2hroIDbVhdh+I05UwqKsMcsWSo1hy6pyC4jn3P/kWtpQkM1bB5y+Ee35NUbjhgyfTGc/QEc8Ut6wFKELBkZK66hChgIqZtdIDmkplRCcU1EZUTr7U+xlofp3o3y9M/Db67RsZo16m/FDhH1edNC6JNyNhKFtsg8mY3tHcSXU0SCrjehIDuko0rDO9OpRLLrkse+zXfrmVPQcTfqR1LySCv8w9jaeveQ+rdmzkis33UJns4sqnfsOFL63n1+d9hD8vOH/ckhmHsxiS9HirbUdm9XR7gkiEwPVcS4ntuIlUe1qTudLEvXdUqqKuXGPGsEmmrVxfvHvDzpznuSOWxrYlEnAMdxfJ04D2+qzvDfOZ6AxFqaJUuBT07PTsfLcTXVNylU0V4S1wJfU1YWqiPXkJO9c0uovoXve8m3vulke3bYePrug/Pnok793PL/A5VPCN6inAUI2KgQa51q40lRE9Z/SAu9VfbDv9yqXz+dGaxkOvnPkgMVFYs2AFG45ZwkdeWMsFW/5IdaKTf1p/M+9/4UHuWHINW+YtGvey54OV58o/xp2kJZGgRjJj5f7OR9IjoVUsTKMyoqMqgu998pzcY/XVrgyfbTuYeYaABNq7M9RWBPrEooIvreUzsSk17g5WuSY/d0bX1AJVJnCNZFURBWP/wvn1zJ4W4UBnGnepn805B5BunkxI1wqUavz7xsdn+PhG9RSg3EZFMc93xrRLer5nT4uwuzU5vMYfIsTUELecsZoHTrmYa566izNfepQ5B5v56u+/yetHLOQXS65lZ/1RY94u1RV1GVHSadqwShrluqbkPMuldlRCAZXv3ftiQbzoU9v30xUv3KlRCZYAACAASURBVBoUAFISS5gcNbuq4DnfG+YzGRlKknn+Tk9VVKe9O4NAIJAoQmA5DjNqI1y5dH7Ba69cdjT3PLIT03LoTpk51Y+qigCaKiac9KOPz2TGN6qnCOU0Kop5vpGU9Hxfuexobv7DdswhJL0dquwJ1vCfy2/gxPeu4tqNv+C4txo5/u1Gvv/2F3jy5GXcfvZHOFBR/glOVQAhkI4bSuHtLDhy6Fq1venPIK/JSnC1dqX56Ipj+/SrZNoCKbEcmTMqntq+n8UnzeTBp9/pcz7bAUf6oR0+U4OhJJnn7/REQm5ORixhYlo2R8+u6jecxLuW3ZrAtiUBXaWhNuzv6DC+Gvc+Uw/fqPbpQzHP91UrFnB4ffFklYXz67nkrHn88cm3x7CVkxcpYXvlPP71in/nvH0vs/qRXzDr4Luc+8pjnPH6U/z5jFXcu+gDJAPDSw7KRwEcXGNU1wQo2ZjorCXd26AeicyeqtBHjcDTnq6vDhXtV5oAK5uoCD1GxY7mTvd300YIcjHa4Brk/qTnMxUYinJN752eSEhHVZVBFSrr7XSZ6IU3xorx1rj3mXr4RrVPUYoNwpu2vFVyRX/ErCrCAYWU4XurB4stYfPMU9hyzY+49I1HufzRu6hOdLLq6fs4/6UN3Hfuh3ng+Auw1aHfpp5GrQNuVr9l4zgSiUT28xWNxGntZNVibKcncdErEpEf45nfr2685emSRoWqCqQhCwx1RVBQDtzHZzIzlCRzPyG3/EwEjXufqYVvVPv0i7c1tr89RSJtEg1pVEUDfVb067c2U10ZosJ2iCVNLMvJGVc+/ZN2BGuOWc7GY5dw9fNrueCp31OZ7OK6DT/lkhce5FdL/44n5p1WMplRUQRaVqbLQ1V6sv3Thu2qBCgCx5HoupJLKuxP53aoSFyPcn58dU000O92an9GRTxpEE+aOe+5wF0oVEeGJ0c41G1ef1vYZ7QZiqHsJ+SWH1/j3qfc+Ea1T0nyt8bShoXjSLpTJrqmuNv69KzovcFJZMtNAzS3dPuqIEOgU+r87PSrWHfKRXzsiTs586VNNLTt4cbff4vLDz+R2/7mOl6tn9/ndY4jMXt90L0XNLYjXalI4ap2aL0ktspVXdGjtjKYi9lc89gubl67HZA01BUmUq08cx63rXud9q40tiNRFUEooHL1+UezZnMTigJCKDnta8dxhqWUMtRtXn9b2GcsGKqh7CfklpexqvjoL9APHXyj2qck+Vtjlu0aPI6UxJImkZBesKL3BifHkXR0Z9xS5gOcX1dFgWSaj+uJfVer4jvLb+DEMy7nYxt/yfFN2zj2nVf5zp1fZOtJS7h98cfYE53e53X9/Q35Mlqyj9Fdzm/Bi4E+2JHkh/c1AtlESQT72hLc9qcdXHfxgp5JJWckZ/3R2b/Thk1dVYjupIllO+iaSkVFgLRhD7lNQ93mLXZ8zLC59YHXiIQ0f2L0KRu+oTx+jEVIjb9AP7RQBj5k/PnGN77BypUrueyyy7j66qt55ZVXih63du1aTj/9dFatWsWqVav41Kc+NcYtnVq0dqUJaG4X0TWFrKMTKxtmkL+iX3nmPJJpi4OdKcwBDGohXH3iS84+PFeVz6cQx5G8Ep3LVz/4DX7wsW+yZ8bhAJy5/XH+9xef5J+fuZNqMzHOrSyOltXp605ZuVLJdtbBLIRCOmOxfmszAGs2N5HOWDhSomsqNZVBIiEtJ8GnqgoNdRHmTK9gzvQoqqoMy4uU35c9+tvmbe1KY9sOLe1J9hyMs7c1QWc8Q9q0CybGxqbWIbfFx8dnYrBwfj0fufBYaqIBkmmLmmig7BKD+Qt0ka0U68mM+kw9JoWnesmSJXzlK19B13Uee+wxPv/5z7Nx48aix55zzjn86Ec/GuMWTk3yt8ZqKoMc7EjiSNdoKpaAVhXW6O6n7Kgn61YZ1plZF2FHcyeVEZ1Y0sDx8xuLYloOj04/mS1/9yMu3fEo7990JzXxDi56Zi1LXtrAH877MH848X0Ywr2Vq6M6XQlzXNtsO64n3OglsWg7El0V2I5Da1eaxqZW9rYmEELkYsDbY2lqK4NFJfjShjUsL1JjUyvJtEV7dwZdU6iK6ERCer/bvKGAyr62RDb0ROQWipoqchOjn9Dk4zP5Ge2dAj9u+9BiUniqly1bhq67cbqnnnoq+/fvd2MrfUaVlWfOw7YdMqZNJKhSGQmgCEFAV4qu6NOm028cgSOhMqyjaworz5xHa1eaRNryDepBkDQlv5u/jM/98895aNlq0nqIaCrORzf8nJ/e8WkueGcLmpDUVIbQ1cF7/8u9T6BkY7YTaavPc16RGVVRCAVUbn3gtVzJc0e6CY4g6IobOQk+z4vU2Z2ho9sgbdis39o8aA+xt/UaDKgIJJbl0N6doSue6d9Al7nUSKSUuW4t8+Jq/InRx8dnIOqrQ30cDKMRt+0zMZgUnup87rnnHpYuXYqiFF8PPPvss6xatYqKigquv/56li5dOrYNnELkJ9F0xA0aasNcs/K4kqv6kK6UtKk95QbDdHAcyfqtzUgp/YIxQ6TN0vj5aVex/j0Xc/Vf7uLsFx9hesd+Pvv773D5YQt48IpP01ZxBGaqr1FbjPzvq3fy4nBQFIHTzzmkdNA0jVjCIG3aOaUQN2ZfIoTbhvwdECBnGCtCDCkm0dt6jYRUdE0hljAwLRvDdLj2ogUlX582HWorA3SnLCzLcRMlexXK8SdGHx+fgfClEA8thJTjr8/wgQ98gL179xZ97umnn0ZV3WShdevW8aMf/Yh77rmH+vq+k2F7ezuRSIRQKMRrr73G9ddfz5133sn8+X0VE3zKzw3//RjN+2NFK+xVRHQyhk1DXThX1GNfWxLbT1QcNrqmcFJiN3/78C85adcLucdfOnExty+5hr+GZwzqPNGwTjSk0dqZGlG5cujRxy7FEbOqkEhs26GtK41luZ5gW0qQENAVZtZH+d//c37uNV+55Sk6YilCgR4fQNqwqK0K8x+fXAzA86+3sHbzLlrakzTURbhi6dGcfnwDf//tR6gMa4g8xRApJfGUxT9dsbDoa4pdM5G2ONCeRFMFc2dUkDFtLEvyj1cszL3Gx8dn8lFq7BiNaxxoTzJjlK7hMzGYEEb1YHjkkUf47ne/yx133MHcuXMH9ZobbriB888/nw984AODvk5bW9yVHhtjJnqFq8G078ZbnkYIaIulC0I6hHDjsCvCOlXRQO7x3Qe6AeHrWY+QcFDjnL2NXP/UnUR37QDAUlQef+/F3HXW1bSq0YLj83Wkvb9rKwK0x41RkUAUwt2pUBXBz/5lWa7gSyrjxjkL3OcdKamrCvUJK/KOD+hqbmdDSkkybfHRFcdy1/odtHW7sfy6phANaeiawkcuPJb1W5v7SGZlTBtNEa633LALpPyuu+R4Fs6vL8jYzy+pXhXWSJtOUfWPyXAPlxt/vCyO376RMVbtK3af27YzqGRF/zMcGZOhfcNhUoR/PPbYY/znf/4nt99+e78GdUtLCw0N7upvz549vPTSS3zyk58cq2Ye8niJjYfNqCSZNoklTUzLIaSraKqgslfRDk1VMG3J9JoQsaRJZhhSaT6QylhsmnYCL63+b1a89igXPfwrarvbOH/rg5z90iYeWnIVaxdeSly6hmVvG8iR5IzSkaKpwi0CY7sx0prqqsZI6dBQ55Zd9/pJJKRjmDbdSRNHgiIEi0+a2Wcy844P9NKSDekKt617nViyJzHTtBxiSYOqSID1W5tLbr2ahkMibSGEt8hw48DXPLarIHEpX1v26vOP9pMSfXymEH5FRZ9yMymM6i9/+cvous5nPvOZ3GN33HEHtbW1fPWrX+X8889n+fLl3HPPPWzatCkXLvKFL3yBE044YbyafciRb8BIKZGuNUVdVRBwDaF8j2EkpBNPma5sWm2Y3QfiQw4/EGTjeKXrbZRSZo248r2vkVDuoir90Ra3+O0Rf8Ojnz6XVVvXsvzJ3xPJJPnQI7ez/NmHuG/5NTx81LmYA4SxqwqD/gwDmmDmtCixhEEibREOqFRFA7TF0ti2xHYcNzExFODKpW4YltdPYoZNPGVm1T/cJNantu8HYEdzZ86YXTCvhqe27ydtWChC5AxjTVdzmtX5SteOA6mMTWtXumRxjZvXbs8a1CL3egdJS0dP4qGvH+zjM7XxlTl8ys2kMKq3bNlS8rlvf/vbud+/8IUv8IUvfGEsmuRTBM8AWfPYLg7EMmiqwrTqEJYjSabMXFEPz2OoqYJLzpqXM6BmT4vQ0pEaUkEYt9i29H5x/5sgBrWSjWuQY5iL6TiSlozC7af/LY+dtpIPPHo357y4gbqug/zj2v/moll/4O4V/8Cz0xeUDLsZTOnyoO5W1YwnTTq6M8ypjxaEQ3gVxPa2JrBsN27a02X1jrn1gdeQiAKZu1jCYN2WZqZVh3J60E9t38/ik2bStD/OvoPxnGF894aduffgaXV4ixjT7kkiLG4cyx6BD+8RCUJMkM7j4+Mz6oxVRUWfQ4dJYVT7TB4Wzq9n/dZmZkgKBioATUBFJNCnVOtlecd87RdbONCZ7iNB1B+Ok5Vyc9yQg7H0DpfC8/bWVQRpi2XG/Pqm5fAmFfx4xad59OzLufzhX3LKm88xb18TX/nVv9J43Bncff51vBGZOeTdAVVxZfCqogGCAZWaaIAbVy8qOCZftSOSjVfsrdoRCWnU14QKkgiTaTdkyKvKqWkK4YDKjuZO/uuzf1MQg1df3UwsYQASu5eao6qIfrPrG+oi7GlN4FgyZ5AjYNa0aMnX+Pj4TC18ZQ6fcuMb1T5lp9SWWjJt8e+9jK/epE2HmZ7H2vz/7L17lGVlfef9efbl3OucqurqOzRIE2gUGhGwQVCBhk4jkZsYGDFqiNExhsn4OmOccZJxzZqZvMOsTN4YGSbGEBORaOwg9gBpkJvSDTRgo0UDTUMBFn3vup7rvj/vH8/eu845dU5d+kar+7OWQve57bPPoer7/Pb3+X59wlCIWYmE4fGy5zHaqGmaOoYm8N6mA2vYHs+llrDjt/8za3YPct2/fJOT9r/O6lee4c92PseT567jOxd/nD16Yc4TfjXJluwbq9OTNdg9UuO2u7dNWyx18ytueHyITVuHmazalGsOpUKKXEb57Z3QmxL5633Hx3X9aVP1waERqg0X1w/UhJmp74muqSsgM1k3zjt9IbtHalP506jnOO/0hV0fk5CQ8KtFN3tYYvtKOFQSUZ1wxDmcS2rRY4s5k9Gyf9xYOeZLdNijEw0O1f2haRyxYpxqw+OxgXfx/O//JZe99BhXPfxtBsoHef9zmzh/8HF+dPFH+adzr2XC12d/MpQAdRyfkVD87hurU8ynWqbRnRZXvh9wYMxiUX+O3p40Y2WLsbKNlBLD0FsWUJFQDiQ47tQm1sGhEe58YAeWPZXFLVFXK5YN5LnhkpUdfylGlpSRSYt66P/2JdMm4ld3eUzyCzch4VePZO9EwpEkEdUJR5z5XlJrFi4ZU020cxkDDQ5ZkLZbQI6mJSQuBulwW+QPb46x07W5xQgGgTp/6nmCQ1pgCKAnZ1JpuASBZKzu88NTL+GpVe/nyqfv4fIt/0zervPhR7/Nxc8+wMa1n+CBVZdSd2Y+8+2HMlF1kFI1Oka75wdKGfaPN2jYHp4fIJg6H+MVm2LOZEEpy0TFZqxst+RQt9NcSrPh8SFqDQchNMymdJGlC/L8l99b0/HxzdFZuYzBeMUCIejvScdTcillywal9sfMp3QmISEhIeHXj0RUJxxx5nNJrV24OF4AUmJogiD0ZRfzqjimOTptvhiGNqf2xvYM57kQSDDDNsJuDw2aLArzyeUu5lM4ro9Tn/vywjQ0gkDG6RYpU+f0gTyrVvTGm0LHLY/71/4OT773Sq780be56Pkf0VcZ5ZP3/gVrF/2A76/7NFtOOHteMYeTNZe67ZNJaYxOWJiGoG77agNh23l1HJ8R16cna8aJLY7X+loyfJzWlNIBqNKgACBACLVIAcH+sXrXY2u3opiGHsbvueQyJg3bY6JiIyXcdvc21q9ZkcRtJSQkJCTMi0RUJxwV5npJrZNwAUBKMikDy1Vi2vdVWggIfD9An6VSu/2WuRZUzFdQF7IGdcvHn4P3OxKJ7R7gbmhC2R5uueoMvrZhcE7HlknpcR50c0HKpq3DPLptt6oD1wWu5+P5ATv9PMPrP89PLryaDz/4d5zz6jOccOBNvnDXf2L9ynP4xys+zfbiiXOuk3e9ANcLws2MWrxIaZ+yy/D/mhdKnT5PKdXjlw4o69Dg0Ei8KBHh7ariHEDrelztVpRiPsXoZAPXC6hbLmNlCxD09UxZWGzHp7cn3fI8SdxWQkJCQkI3ElGdcEzo5k2NxE5UFuN5yibgS0lvIY3tenhegB9I1cqng9CYU71589T5aBWHVhse2ZSGPYvo1DRBxtTwpdqEN9fNl9WGy4bHXlMJGXN4D44XKH9zzkTXNTIpne/8aCcN26Pa8Frue3DCit/DTzPLGLrpTznnrUE+/OCdrNz7GmcMPc9XX/9Dtp69lu9e+kmGjeKMC5nW96vhBxJD1/D84PA2kAo4b5WqXN+0dTgU7K2LEj+YEt6daPf5Z9MGxXwa2/GZqNjomtayYdIGPN+blq2exG0lJCQkJHSj+2gnIeEIEVk8VIvelDd1cGiEgVKGcs1hrGLj+0EcjSelEsKapsVTZgnkw2njfBJB9NBKcrRoOMGsWdQZU6fh+DjzbI0MJOwaqc/ZMhIEEtvxGZ20VDa4lHi+pNYmqDs9bqzm8cSiM/l/P/2/+NZ1/w8HSovQpOTCnz3MbV//NJ/dejeLDQ9NEzM+l66p55uroFZXIFoio2ME0FtIs2N4AlAT576edFx93vy4Gy49tetrrF+zAt8PsF0fKaWqKtcFn7n6nZQKaZYsyMWCGtREWtfFtMckcVsJCQkJCd1IRHXCUafZ4iGEIG3q6LoW10jXLA/CmmrJlMCarDpIqTzCkY6rWapVT9dERxHWTHT7fDzMh8pMryAEOK4353jAI0EgIWXqWG5Ape7M+XX9IGB/LeDhM9fyZ3/0f/jBZZ+gms6Tdm3W/+R7/Pntn+amHQ+ytKijN30AqpJcFbmAwDA0ivnUnDZXxlcT2v5eE5BO6fTkzNhyMVDKYBg6A6UMqZSuBH7ou960dZjBoZGOr7F65QA3X3EavfkUdcujN5/i5itOY/XKAQZKmWm56I4XsHwg3/UxCQkJCQkJ7ST2j4SjzkxVsKtXDpBN6WoKGE43hZjaVBiJaRGakCP7gWmotsbxit3V73vcpPFJ8GY5mDm6O2Z+DvVSpAw1IR6dtNDmmDQS4QeQTWn87ofOAODefJHt77+Kix/4By7e9iCl2gT/6r7/zdpn7+OBq36fh5aeQ9XyEOEH5YUpJRlNkEnpUx7yLu9P08Kq+baNjJpQlpliPtViuYiSZXRdtTCOlS2EUF7o4f0V/nLDIADZlMG680/g6otPiZ+zm89/prSaJG4rISEhIWGuJKI64agzW271soF8y+11y439vioZQjXmRaJR10Tske7rSXNwotFVkArmnvxxtGL35vKchyqoNU202GNAbRaM/n22aX5Ec0JHwwm4/Z4XKOZTCCHYa2V540N/wNMXfpjffPBbvOeVp1m0f5hP3fknXPeeNTz7iX/Lt8ZKVOouKUNH19TnO1FRMXnplI6Ukomq03rsAnqyJpYT4Ho+JyzM07BcxqsOhq48zpomWiwXzckyQ7snYy+07fjU7Slrje36bHzyTYAWYd1MS5RjSodwY2eSR52QkJCQcCgkojrhiDBTScZsudXtt+u6hqYpO0iUHBFNLkGJRylhsmrTV8zQk0uFddXTkYTCe7wxo7i99uKT2T9W56mXDhyxc3Is6JRqEv2NJua+SIjOaYTnS0bLNkKoyfXBistEZhlvfew/cfbul7jiX+7klLd2UNq2lbXbPkb/uy/hB+s+xav6ArxAxhGDui4o15yO03IhBLYb0FdMt1SdN3+XevOpaQI3mh5/6Y4nyWUMhBCxPaR54eUH8NCzuzqK6k5Rjr4f8PF1x87ekRTLJCQkJPxqkYjqhMNmtpKM2XKrO91+wRmL2LJ9H7qucXC8jhACCfSHEWflmovr+fTmU1xwxiLu3fxm1+PTNEFPzpw15/rFX0x0/PtsWsdx/TAb+eghRDgtPkKvoxYnAuEHauIfPm/zFLur6A5vlBLqtnqg6wW8NRkwtuidvPkHf86Fr2zhqsf/Ef3NN3jPzx7jzO2b+cmaD7Px/Tey28/i+j4nLipQtzqfdz+Q4E3f/DdXy0XzFZBoQRDFFoJaVFiON61cCCHYP9ZACOjtScc+/2OZQR39N+N6AQ3bZ6xiM7RnO1ddsKLrZD0hISEh4fgmEdUJh81cSjI6CaVI7OwZqcVTzeUD+Vhwn7y0yKatw4xONBBCUCqkAJVt7PoBmZTBqhW9bNm+r+uxCcDQBA27Nf0iKhURQm2CfOjZXXh+gKFPbYoMpEQTggU9afaPNwhQAdPtVg2BEu5CKCE7n8KUZqQEQ9cIjpCq9ryAgd4MYxUbEKRMQV8xw+ikRSFrUm243f3oHd4jKNFq2z6vuhqVVZdx8X/8DI997j9zxZZ7KFoVLt9yD+/d9jAPfvBGHj7/KkxDU3GA4RZULYzDi9A17ZA3/zVf4Wj2bOvhBxiEm1yjBR9I9o41ABn6vAVjZYv+YoZs2jimGdSbtg7jegGVhquiIoW66nD/U8OcvLSYTKwTEhISfglJRHXCYdNtI+KekRq33b0tnj43N/plTI1yw0PXBDXLJQhzh195a4KhPeV4Yrd65UDLVK/ScFHaVpJO6dz/1DCmITpuhBPAglIG2/VZ0JvF83xGJm1gqoUPJKVCmtFJK2zn01oe7wcSyw1YubzERM1homKr5kQZxOJQCHU/XRP0ZA18P5hznnM77SJXxQHKQ/JcK0uHpCdrUrM80qYeT/a3bN+HN4/Re/N02/Mlnu9zcNLi3hcn+MlFH+W5cy7nkse+y6U/e4hio8xHN/0N7996H1s+8lmqJ5zPSNXDD+S0aX8mfeg/gpqvcExULCxHRTJGn5tEUsiY8YJvvGKHU2wNKYPw35U9JZs2jkgG9VwtHSOTFo2wbTJqi9SFSl9JGhsT3m4Sa1JCwqGRiOqEw6bTRsRK3aXh+HE29f7xBjt3TVDMpSjmU+wbreMHAZqmtUTNSTl9Yhf9MP/GxpdASkxDp5hPkU0bTFRtXLuzf7gnnyJjanhh3Xna1JmsqemsEr2qynt0UrXpgarLjibVkTc3+qWihL2vRJAQCCHDybJEF7C0P4vlBizpy7JrpHtl9nzwAzkvb3RENDmfrLqsXF7s+EvxhzNYZroh2/507+Y3kRLKRomDV32OZ957JZc/ejdrXnmKJeN7+cg3v8rqE1axcf3v8fySM6g0vDjlo7eQIpM2DklEtv/S/9fXnMmbe8s89OwuLMcjE6Z/bH5hHylDLZQ8LxTdAoLwvQgkrhe0ZFAfqqB47uX9M9qgmhkoqSsIzbGEQXilImlsTHg7mc3Ol5CQ0J1EVCccEu0+1bql7BXRRsRq3SWfNWKh3bA9BIKG41MqRDFvAs8LYm9B6yYzNbGDKa+16/n0FzMtJR2RyjMNHc/3mzY2Cm750Cr+9v6XcdwAx/U7mogjQZ9JadiuD0GA3/TUugarVvS2CHvL9TENjb4ek1zGZLJq47gBlhvEIuzbD77CaNk+pHOrCTVhHy/beKEC1QSIMOljtqm1EEq0ZVI6dcuLNwBGbNz8Ohu3/OKwkk40AbYXxMfiegH7qwHV/pPZf9OX2fL6IFc9chdn7NnBb+zawRe/+e95btWF3Pebt/BqYSmWF1AqpKlbLkO7J/nSHU/OWcB2+6V/8xWn8fUvfKDlvjuGJ+IFn2Fo+GHkX8pU+deTVQcvkJSrDoYu2PD4EOWaQy5rzltQ3PP4a7PaoCLWr1nB0J7t8YIsCHvbc5lU0tiY8LYyFztfQkJCZxJRnTBvOiUnICWGJuJIslrDpZhPxY/xorbE0N4QCRxg2iazaGK3Z6TW8jrlmhPnEmcj20AolAMp0TUN6as4OYlkw+NDVJo3J86gIh3Xp7eQplKziRwYhi7oyaXYsn1fPDVfd/4J3P/UMJ7nU66pCLaG41HKp+OJ/O33bEfXp2cvN6O3eYvbyYW2hd7wHDZfCfjFvkrXx2kaLAg9wrbrTxNoGze/zsYn3zzshslAqh8eke3GCNM+6g2PvYbGxEnn8NYt7+Rdg5u56onvsnx8D+fteIqzX32WLeeuZ9Pam6mSZ6ysprKVustYxebVXS/QmzcRmtZVZM/nl36z77onazBecYCAnlwmrnFHGOQyylOtrqAoa5EIr27MVVDsH6urjZBNdPNpr145wFUXrOD+p4bxA+Xlz2VSGLpIGhsT3lZm6hVISEiYmURUJ8ybTqIGoJA1+S+/twaA2+7e1iIEDV1lRRvhpXhV3GGj6QK/yX+shZvachmVPZxrep1SIcVY2Q7zj3UcL8DQNFKmmo43t+LpAnaP1Ob8ngIJdcvDC9QvkFIhFU/EbdePp+Zbtu8jnzVo2D6uH+B4HvmMQTGfomF7qr1QgiZVo2C55kwTsJomKGQNJmvd00ia7Qh3PbSz5Zdc88Bd14in8+q8pmJB3alS+6FndyFQ1pUjUTYTHUvkIRdCfU6jkxYNw2Di7MvY+a4LOPep+7hy6w/pbUxyyTP3cd7g4zxy8Ud4+IJrOCjVZy1QnuvRioOhwXjFYmh3masubE3EmM8v/fZkmaX9WRACy1HJMYYm8AIZf8cCqSxB5bobf/5zFRSL+3McHK93zWNv5+qLT4k34ybe1YTjhdl6BRISErqTiOqEeTMXUdOePa02gtlkwyIQXdfIZwxSps7opDW1EU5ATy6lNgg6Hva4ryqvc8pqQr+21wAAIABJREFUIaVksurGE/ELzljEo9t2T8trnkPXyzSijXuBlGFihpoYR+8tWkzkMialgnrMWweq8eZClZUt0ITE8wNKhRx1y8P1lfiPot78QLYI6nZXipQwOtFgcX+ON/eWqVse4xUr9pIbusD1I1vI1CbN3rzJwr7cjALNcrw4HWO2vZSztTz6wZQHPcq5lsBFZy7h/qd+ge9LypZPmQwTH/htXjjnUt73xD1c8bOHKFhVrnn477nw2U38y9qb2XrWJRywNPxAmW+ixY0fSO5/Wvnr1y7sAeb/S3+miL4o6zrC0DUc18fzfXYdqGIYGtmUTiFjtGy67XRur7/kVP73hp91zWOHzhvA2u05nUg2jiUcK2brFUhISOiO/tWvfvWrb/dBHE80Gs5hT/AOhXw+Tb3eucDkeKD5+J5/9SA128PQpy51O15Af0+ai85aCqip3eK+LLsOVJmsOSzqzXLRmUuwHJ/JmkN/T5rzVy3irYNVtaEwpeH5Ej+Q5DMmvh/EE1gpJQ3Hx9AFhqGzbEGOr97yXi46aymnr+jjye37sBx/XnXcndA1EUavCQTg+mqT4OikheV4jFccUoYg1STmGpaH5wcU82kmqzZamKdtGBqFrPLsSglCU4Izaoec/tpT4rqvJ82CUoZqw2Pw9VEMXeCHGzgbtksmTKowdIGU6rhNXVAspBmZtLDdgKrlcmC8QU/OZHF/Ln6dh559S8UXahpz2f4oRPfblCu+9Vk0Aa/tnkTTlB1ECOUDrzoBlUwP+991Lif+7m/TG1hoO1+hYFV598tPcfrO57AWLaW+cBmOjEptVKShL2G8YrPugpOp1x16ciY/f22EIHzv0S/96z9wSst7nQvN3+WG7VGz3KlUF9T3r2H7KvFFQCalU7M9fv7aCIv7si2v9xsn9VNI6/F3vr8nzfUfOCUWv5FtyvGCGZ+nnUN9XDv5fHpe52YuJD8vO/PLfHztP7vbv8dv9/EdLxzvx5gc3+FxqD8vk0l1wryZ6ySj04Tw6qZ/v+3ubbGNJG3q5LMpbNenXHUohskQynMrEEgmqw6lQmra61iOzwmL8uw+WMN2/EPegCeEIJfWqVkeUoLr+oyVVU5EfzHDZNVhvOLguAG2F+B5QVzWsjfM2gaJpkFfTlkHdE2ga4IFYdpDc4a1EsWqlMUPCHOuRexFjzZ3+lKV3pTrKrkkCFQDZHs8Yc1SohAEeLBvrN6yyW5waARNyDDaLrRrNL1/XZ++EdLQpqbizfQWOltbAgkykPTmUjiu3bLQsR2PUd1k8vR3Uv+Lv+LVtdch/udtnPnWdk7d+yr/9h++wk9PPZ9/+c1PMtR/MpO2j5RgtiVizFYm1I1O097ou1x2fMo1u2XBE0gwNRC6wPODOXm4m7/z0evd9dBOBkoZqnXnkDaAJRvHEo41cy1gSkhIaCUR1Qnz5lBFTTvdbCSW4zFgZBBC0F/MUK45uJ7agNipKGSglKFqqY2RB5zGIb0nXVMCt2p5FDKhZ9qTGLqgt0dt/BNCcHC8QbnuYoRZaCoPWeULRxsTZSjMbNcPN8IJdF2wuC/L7oNVEIJ82qBmewgh0DQ1vZaqW4aG7ZFNGy2bO3OZKftL3fK4+uJTuBol3L6x8SVs14sLTaJs64bjx5F1AHfe/zINJ2ixdUiiEhyBoWlIoW6Iznc3i0il4caTYl0TuP5UEoiUKG85U8U4hqGRNjQsx+cvvz/Ib5xQ4sNrLmL0z/+aH9/1z3x48z+xYmwX5772LKtff54nVl/Gw2tvZm9hgEBo06wds/3SbxfQUUlQp8SQm684jW9sfCmsp2kPOxfIQOLL1ssLs/msOyWUHBir019Mt9hW5uLXPtyNY9G5GKs6/O1XrpjTYxISEhIS5k8iqhMOicOdZAwOjVC3PMYqNmaTZ1pd4lb2hrSpk00b8ca73nyq42uuX7OC7z7yGpomZkzc6IZA2Q2ih9Usj1zGxPMd/CBgvGIzXrGRbde5zdDzGwQSw9BY0p+jbrlMVlVJzMrlJW667FQAHnl+D3sPVkmbBilTo1RIk7Zcxiut01HPl4xMNBjozU7b3Amt3uHBoRHuvP9l6s1tkeFGO4ES481+cMvxEQLMsOBG2WvCEhspCQJ1u6YJNF1ZSnpyKUYmrdbpdWg7CV+QQIppFoBow6lExQPK0KeuLBWSsarDnQ+9yu+sO519a6/ijnedx5lPP8SHnrmXvtoEl/3sIda8tJmfvP96nlt7Ax+88PQ5f57NghYkr+8ps2N4AkMX9PWkp6V6fOlj7yGXMchnDUYmrBZbixvabDTRmuox28atTtNlQ9co11zy2alUnLlsABsoZdg/3qBhe3HrZzZtsLgvO69z0ZNNftwnJCQkHE2Sn7IJx5zoF306pWO7Hp4XMFaxcb0A09BYd/4JbNm+b14bvi47/0R+sm1Xi6BW02SBlAFLF+SxHB+QVBrqNf1gajapNU1vPV9i2V7YlKim0NBaMBNVW+8+WG2JCsxlTLJpY1o+9NoL3sHBg5X4vduuH26Im74CCCQcGG/EE+VMOEVvPw8bHnuNmuVNm696vgz951os2kYmrbhIJqK5FTKeskvQgJ6syZL+HOvXrOCv/vkFfKnOlR4K6sjWoazPrVPcdh92uaam1jLc2ChRHmlDE/yfH76IrgvQS7D+Rg584ArOeGgDH3zuX8g7da585C4u2f4onvZFOP33QiNQZ6N39J0Y2j2JECL2H0f39vzOG1BBCdfX95TRNBFffZj6PCS5jInt+nPeuNVpuhyloszneUDlpO/cNYFALRpdL8DxbD549tIZHwet4l7MZJBPSEhISDhsElGdcMyZStHQMQ0ttHf4OG7Ap65cxeqVAzNGjXW6tP7AljdUEoWmZFcQKBFlGoK+ngyW48epEUv61aRw31g99ji3T7cdL5gm3aL7aIK42jpKi5DQkhaxpMsGsug9bHh8aMZIPYCUoaNr6lgmKjbLBvLxeRgcGmH3SL2rf1wC2ZQei7ZNW4cZr1h4vpofN1tATENTiSxCiXdNCExDY9WKXjZtHVZTZ11Nn/1AIpvEecerAmFuuKap13A9P66hB7Up0/N87FCLr1hcYGSiwYsHXH6RKbHvQ7cQ/PaNXPbEP5P+4T1k9++BL38RvncXqT/6d3iXrSXI5pBySkjvHqlh2T7plBZ6wGX8GZqGFkcICqbi8pqnxOvXrOBrGwbRNNGSIW5oSoDf8qFV87I7Rd813w8o1108L0DX1KS8N5+al21qx7BqIm04Pl545SKb0tkxPNGyR6ETncR9QkJCQsLRIflpm3DMaf5FH9k7Iq9wJDBmspd0urQ+XlYWBTMslTENMeX5DUtU1q9ZwZ33v8zYpBV7hmei2+2BVJsj65byVltO5B1WE+uy53PJu5d1fd7VKweUWA0bEruxZIES5pH1JZp8R4uKmY7f1EU8aV69coA395Z55a2Jljr4iL4etcu5UndxXC+OxYs8yKWCyXjFwQtafdPd5p4S0HWNvpyppqpuQCO0qCgrhfJgg3qOPfEmT1S1fT7HA1aaFy74BLne9/Cbm7/PaTu3wfPPU/zUzTiXrqXxxS/xUv/JfOfhN5isOnFGudsIph1LEC4UAqmEtddWSx59JssW5DgwYeFLSKeUJSn67jQvhoZ2T3L7PdtZ3JfhhktP7WpJuvP+l9WVhDhKMcD15bz3H4xMWhTzKUzDiwV6Q84th71T/GBCQkJCwtFBm/0uby9f/vKX+cAHPsA111zDNddcwx133NH1vrfffjuXX345l19+ObfffvsxPMqE+TBQyrQUtcD8ygVGJi1STT7jhu1hu6r8JfADAilViQcS12srQRGqAv1wU8BEGLXnegH5jEE6pSNRor6UT7NjeGLW92Dq3f/zM5veX/umtGhRoWudZW3UBNks3nYMT9BbSKupLVOC2NBFvLBZvjDPwr4cK5eX2DE8ES9c8tkU+YwRC2pBqxWmE5EgNQ2Nz1z9TnpyJurtqldu3ijZXP7j+ZK65bJrtM7zE4KRd69hwyf/hG/e+GXqp52hzsdjj1C89iq0f3MrK0bfYlFea/k+tOP7Mi6l0TUl6nvzqWmbXm+49FQyKR1dE3hewGTVod5wWb9mhfKvP7CDvaO10MIi2TvW4M77X2ZwaGTaa65eOUAxn4o/I9PQWFDKkstMbRydKwMltVl3rGLjR5tX/QDL9ju+djPr16zA99Uion1PQEJCQkLCkeWXYlL9mc98ho9//OMz3ufZZ59l06ZN3HfffQB89KMf5b3vfS/nn3/+sTjEhHlwuOUCzdO3hu3FVdeA8ttKiQi9sRnTiMXTbXdvI5dRmx6FH8R2hvnmWwuglE9Rt5SYB0EmpUSd5wdUajblmsOX7ngyvsQfFZc0v4e61d3+0VvovplNCWy1cOhEX08aXddaItdGJi16cmZLdXzdcls8vpbjdW1xtMMNe5FAne2MjU5aLBvIc9Nl6twvG8iz62BVtVY2PbjdDy5Q1hoRth6OWpJ0rg97zWV86/wL+ET9RbL/++vo+/ay5rmHOGvwCR497yo2X3wtBwslxhoy3Mwn4ul39PyVuoMmtGkNjS3EvuNwu2L4501bh0OfvTZlfUFiOX7XaDvL8VmyINfiZZZSzrvuef2aFdz+g+0Q2psCCUJICjlz1li95qSe8erxmwmbkJCQ8KvAL4WongsPPPAA1157LZmMEh/XXnstDzzwQCKqj0PmGsnXrUWuWZRPVm21uS4ev6rCEQEsKKZbppGR7cTzglgY6aH4ni/VhhtPW13Px3b9MJou8uMq8RlFt5VKOU4ayMXvq9pwqdt+1+cfLduUay7ZtPKdR9PSTVuHmazaeEHHADj1PsMEi/2jdf5m43bGqw7jFZvRSQuhCVKGqlDXdY1lA3kKWVNVeC8ssPacZaxeOcBAabjFNuA05X/PZeC5qD9HIWvG5z7ebCcEpjbVxihpbW7UQzFsaITpHcr+YkmNCa0H5+OfxFm7jszdd8HffIOc0+C3ntzABYOP8sCFH2Hw/HUczGSpOepqhC7A9dRrmbpONq2zZfs+Tl5anPZ9U/5xEJqAQCDCNJnoO+gHQViao6wcQQAekqHdZQaHRjounI5E3fPqlQNkU7qyrAQSQ9co5tNkUvqcBHpkpVrYdnwJCQkJCUeWXwpR/Xd/93d873vf48QTT+SLX/wiK1eunHafvXv38t73vjf+89KlS3n22WeP5WEmzIO55Ay3b0ZsLjIBJXYOjNUxDZ3+YhqvaVOYlNMzrSORo2kirBZXwrR5qjkXotoUISSmocXJH2EJIKBEfqXusrg/hw3c8/hrfOGG1S3vqzn+zzQ0cmmdquURBBJTF3i+T60huepCNcGPHtfbk+bghNV1Wiyb/vnUSwdabwskjuszOtkgn01xy4dWxedo4cIeDh6sAK1XEzxvfoU62ZQ2zbLyxM/3EISLDR+1mNGY2jwoURsY4z9LZSGJcLyAUl8Ov1BErMzz4vW/y8bGyVzy9EYuefnHDFTH+MSP/oY3n3+Q+95/E8Pvfh+1VI79Exa9PamWCb3tdp4u7x6pUQ/TQjQBvh9QaQT4IzWWD+Tjspvm1BRQi4L2hVP7OTzcuudlA/lpAt12/XkL9ISEhISEo8fbLqqvu+469uzZ0/G2J598ki984QssXLgQTdO49957+fSnP83DDz+Mrh+djTcLFhSOyvPOheN9knQsj++RDYOkUzqZlPqKpkwdy/F45Pk9rL3gHaxd2MPaC97Bf7xjC+PlRny/UiGN5Xj0FbOsveAdLc9547pVfO17z4eCWhF5evNZk1xGZ6Li4PkqqSEIp6mdJsLRfRb2Ztg/Vp82vY02MzquTz5jcGCszsKFPS3vazKl43nqBQxdi33mmZTyNwNYjsfQvipD+6ot52OyppodD4VoQ2dfMT3tHEWf8dqFPZRKOe55/DVefL27b7d5yhzRcAL2jNTQNcGXv/E0UgaMVlqtB34gyaU1bFeydCCH56k8cNeXLOrPYjs+6ZSOoQts1wcJ119yanx8X/vhS1hnvIsHFy1l81mX8ltP38O5v/gZJ48M84c/uI2XBs/hZ9d/mhf7T0b25LCcKR+9oQvGq86073O0wImm0QBeEBDIqe9OueaEi4PovoIFvVl0TS2c/vvnLopvaz6HB8bqLOrPcf0lp3LeGYu7ns9u3LhuFX99zyB+oPLbo3Ny47pVb+vPjeTnZXeS4zs8jvfjg+P/GJPjO/a87aL6Bz/4wYy3L1489Qvo2muv5c/+7M/Yt28fy5cvb7nf0qVLW8T53r17Wbp09hzXdkZHqzMmMhwtmqeExyPH+vj2HqySyxhMVu14+mzoGpNVp+U41p6zLJ5ga0LE08C15yxruV9knRgPc4qbkUDGEPyPz74vvu93frSTyaoS2N2+DlLO7sfeO1pHCBXL9sjTb8Tvy/UCCllTFaJIwtQNFQfYE6ZmRO9p78EqQPw4UJ7ugxPz8+ZCWIWuCRb356jV3Tg7O2rc62+qgY9sDzJQU2Qhpk/0da3zlN/zVSlO4PuMTk4/56DE9/IFOQoZZT95x9JiS2Rgu/XnvDMWx5/pW/sqyvPdN4CXL/C9E0/hJ68Nct1TGzh5/+u8c+h5zvhf/4afvftSfnzpjdRPPJlxUuGmVp++Qmra91kPR+RRnre68iDRBZw0kOOT609nw+ND7DqoUjdMQ6OvJ00qjCQ8MFaf9pwnDeT4wg2rW/7uUP47Omkgx01rT512Tk4ayM35+Y7GL7Dk52VnkuM7PI7344Pj/xiT4zs8DvXn5dsuqmdj//79sbB+4okn0DStRWhHrF+/nv/6X/8rN998MwD33nsvf/Inf3JMjzXhyDFQyrBvrE6l4caX4z0/IAgkg0MjLdF7MNVY2Mmf3dqwN0UU7xZISbnutQi5jKl8x2NllTQSNS4KAfmMQdXyQMJY2Zq1wVFKyKR0vvOjnWRMLW6LzGWUvWGy6oTJITrplGqRjGj24DZf/s9lTDTNnregkXJqKj5Qykxr3JuoOdz5wA6QklzWJJcxGJlUPnFDn26Vmck2o2mCyZrb3aYiVWZ0IZfi4+tarTqz2YOa/cpOOotxYoHK0gX88LzzuIXXyd3xV+i7d3POTx9m1eBmHjlnPS9ccQPWgsUcDES8cGj+zD1fhvXwsqm5MB03F0bHdNvd2zp6pRd1ySY/Uhxui2lCQkJCwtHluBfVf/zHf8zo6ChCCAqFAnfccQeGoQ77K1/5Cpdddhlr165lzZo1rFu3jquuugpQU+1mj3XCLxfzSTxYvXIgbizsRBRB5/utdgnfl2iGaggMZMDtP9iOH0hMXcMLNwhefdHJ7BieYOdbE5iGRialY7kBMhTZMuhsgWgnZWg0bC8sugnCzWYmhqFTKqh4NyBuW4w8uHXLwxBKfDYcZSUp5lM4XkAhowRgS035HFApHlOlMFF0Xt32majYcZ15OqUjTHUeXC/A95WHXA83Gs5WCe/7EjmLG7u3J93RLw/TN6reuG5V7Flu9yuPVx3GAo1PXXEubu/5/PQ3zuHA1+/ksmfuI2fX+K1n7uV92x/niUt/m2Wfv4VTTuxh8I3RFt++8uQ7lPJpenJmVw90N6/09ZecOq/PISEhISHhV4vjXlR/61vf6nrbf/tv/63lz7feeiu33nrrUT6ihGPBfBMPnnt5P997aEfHNJEogq49UkwSpVCEG+YCdanfD9QGtZ6syY7hCb70sfdw293bWibnuibC5j61oa5meaGI7MyB8UZYQgILShkmqw5jZZtlC3Lc1LahMp6Wp3SQEk8q8anXXap1Fz+QLB/Ic9NlSsTd9dDOGVMgmkW/EBAEU5s4o+g8FU04ZdOQkrjSuzes1w4kcQJGPqtaBmd67bnM0If3VzF0QSFrxvnNm7YOs2ek1rKImKg5/PU9g9y09tSWiW27HeL0UwbwgUcmMsj1N7Hz3Eu5cPO9nP/8w/TXJ7jm/m/g7fwx9T/6Ai+4J7K4kKYhdTw/oFRQJTi246NromsqTbfXbranJCQkJCT8+nHci+qEX1/mmngwODTCdx95DQQdk0IGShle31MOxTAtyQ1BINE0gR8Wxvjh5FkT0LD9WDB2mpxHsXmVugtCdBWRzZYJM7R95DImtutTyKW62h5uu3sbXiDjPO6G7RHIAN/XWsTebZ8bYOPm13no2V1YjkcmZbDu/BN4dNvutkVJikxKb2mujGwUKht6qhQmSigs112W9OfiZsRcxohFJKhM6cPF8yWTNQfL8fjOj3bi+ZJKXdlGJqoOQSDpK2bwg6DlKsVMdoid+xr0FXvJn5Bl49rfYdPKi7n62Xs59/XnMF59heIf/mvWnXQWm9d/nLHTz6KczVGxA4ph/vhtn3vfjMecWDESEhISEtpJRHXCcctcI8k2bR3GMESc2pA2dezw76Nc669tGFT51aI1y0PTBClD0HBkS5ybL8EPfKhLPvs/HwNUE6MS1EqkSqkyriWQ0gWBULaKyHsdCXCt6TWbo93aY+faiXK1pwpu1HNZrj/NLnH1xadMKzTZMTzRcVGSMTVuu3tbPA2vN1xcT01nA6nq1pG0VHqbhsanrpyK34u82F5oA5Fy+mQ6so3MBSnBcWUoqJ2oegWJEvbplE4xn5pzcUrkyR+qO+TSJRad9i6+s2g5j775Ep999V8o7tjOql+8wGnf+DJPnX4RD190PdkVp1BL51jUO3NMXYv3PryaYLlBS853QkJCQsKvH8d9TXnCry+rVw5w8xWn0RtODztVS4MSn83CEVoFa9Toh1BT0SibWtdEPHWOymDahaHtBnEttbI/SPqLGRb359DCBykhrkKqNU2QNjUW9+dY2JdVOdZNxuNyzaEReqC7FYEMDo1w293bGK/YvLW/yoHxRljlLeMq9KgxcSbaK6rLNYcDY3V2j9bV5F6gjk2oBYkfqMKVBcUMA73ZGSu9m6vSgzZBrYWT/nlvokSGLZNiWmtjue7OK5d5/ZoVVOouQQDVhsebDY3R3oXsO/u9fP26P6byZ/+TysJlaFJy0Y7NfPnv/wMX//CbFIZf58ITMoguJvloMTERTvb3jtbYO9YAJOPlBt/50c5Zq8MTEhISEn41SSbVCcc1zZfZownhXQ/tbPG7DpQyVC23JV+4XbDecMlKbr9nO2hK8EmAMMmjXHNm9P9KpgSilDBatlg+kCcIVDPj1EZK9dy2GzA6YVHImfTkTMbKVvyarhcwOtmgmE8rW4agpc4ciC0QUeJIdAyeL9E06MuZs065o3MHsOHxIXYfrMXxf7qmNhiOV2z6ixlyGYNizlQWFTF1VSDaQBlF3EXT7YFSht0jNTIpfdrmT2javDiX6sU2bDeIbSjRo0V43jxPTrtK0a11s33hJaWkbPnUtDTldJa/9PJUPvKnnPvzR7ly2wP02FV+a9t9vH/HEzz5i4+inXgrLBwgyBfCiiBF88bO/RUbITSCIGC0bKNrDpoQbHjstWRanZCQkPBrSCKqE34pmKlhcf2aFXz3kdfwhN9iE1m1ordFCOo6aFJTcWmGRjFnkk0b1BoefhB0FdbtE1ffl0xUbNKmQcrUKBXS1C2XsYqqTE+bGtm0QbXhEgQSXdNYUMrEjY+uF1C3XNKmjidbfeBpU0fXNSp1G13XWtr7VLSgiP3Yc53a2q6ydoCatKt4PGWwKNccFvVlqVsen//ouztu9ux07i3bp265aJqGaGsYbCZyvsxJXod3iqwkzcI6Y+p89vrVLY2Fs7VuakIgdEL7DQRSYrsB+9yAnhP7cBYbbL3wwzxz2gVc8fwmLnvxUUr1Sa68/5t4Lz9G4998AfeSy6C/nyCbQ8opSw6oiEcpZbyIiOIZ94zWW2IfExISEhJ+PUhEdcJxS/MUsm55pEwtznZu9k1/6WPvoVTKtQjCVSt62bJ9X4vg8n3IZ3VKhSlhZrs+i/sy7Bqpz/m4UobGsoH8lOfb9SnXXAin1aVCmmzaIJM2GJ2wWLIgR8rUcb2AXMZESsnekRq5rBnbVqL3s3+sztKBPI6nBFvzsFfTVPyf7frTvOXRudozUlNTbhmgCS0W1FHucpR04sdV6EE81T/vjMUtojWieTobHWvK1KhZAdBZTceCeK6COqS3kIpzuxHQm08RBJJiPsUd9wzG5TSrVw60RCXur9h4nmq5/PaDr7Cwdxg/bEMUbcF+AnDcgLeqAblsH4tPKvBI/8fY8q4PctUzP2TN0DMYrw/R82//EPe9a6jf+gXE2e8m6Otn2UCOAxPKbmToGrbjq+cUqhwHqaxFnWrQ3y6ay33+9itXvN2Hk5CQkPArSyKqE4453S7Zt9+neQo5XrGwPYFpTAnrZgtEuyC87e5t04RgIWdSbbhk0kbLRPumK07jr/75hVnbESNKBbVhrjla7cBYHdPQYkEdHV8gJftG6wRSoutqOq5KaAQpo3VLg/qzUMkXUdkMTaJUgIbyODefs3jToC+pWcpHLAFNBHFKSSCJa9CBWFjrmui4+bOZ5uksQN1y55SN3anefTZKhTQpU2dssoEXhMkqqAXFgjCp5M4HdlDMGuwZVQuh5o9NSslo2Q6972lGJu1pxyCBiYoFQlBteNQ1jUW9i+gt9PC9/kVs2X8Ft77xIOZPn8N8ZivFT/wrnA99mPq//jzX/sYC/nnQpuyr5ksrFNV6uIEVJKVCmpFJa07f86PN4NAId97/Mpbjh8eXkJCQkHC0SER1wjFltkv2Ee3TUdNQk95y3Y1FdbeNfjBdCAL05Ex8P6A3TJHIpHQMoXHXQztVIcocRLWmCXRdozdM8ZipZS8ShH4QIMJkkLGyTT5jsLgvEzcrRjhewOK+DPvHrThbutlXrCH4/PVnThNm0bmq1JXHFxHEE2IBXa0ZgZT05dOkDXUOHnl+T5xe0SwIK3WH8aodx+x5gZzVLn2o8q1he2pCj0DXIQizvyeqDpNVB8PQ8Lzkv5esAAAgAElEQVQAy/bQ9enpItFHOFF1KObMrq9TqbuYpo7r+iAlI1WXWjrD0pNWYK5cSuXfXY+5+Qmyt38N443XSd+/kdTDD3Lmv/o4XH49T48KfiFMqimDhuMpv7uAYl4tmgxNtHzP943Vuf0H28mm9Pgqx7EQ2Bsee42a5YV+fzH7AxISEhISDpkk/SPhmNIsloUQsYe4PcliZNJqmeSqKDqJG9oimi0Qg0Mj/Mc7tvClO57ktru3MTg0wkAp0zKZBSValw3k+dLH3sPH152G7fqxpzmbNuKNhs3k0jqGLjB0Tf2zy2S3PWnDdn2qdZeenMmCUhbTUOJZ1wTFfIobLj2VesNl70iNXQeq7B2pUW+43HDpqWTSOqahowniTXspUyeT1jsKsehceX4Qx9uB+qeudxZSugb9PWmVABKegyi9YuPm11sSLhxXtSn6vsT1ZxfUh8PoZIPxih3bVJpfKtroGf1ztgMph4uaTgQSsik9zjbXNUHdcnnjoE3p1BWwbDnu5esof/sfqf3xVwj6+hG2TfZbf8u5t/4Ot+zezEffITg977GwxyRtamgaVOoOdcuD8MpElDFeCf31tuvHC8ljkRISLdC0OE4yISEhIeFokUyqE44pnSbInZIsolKSaJKbTRsU82lsx6duedPSMtIpvWXyfdGZS3j0+T2MTVpxC2AmbcQthO2T8KhNLyo4yaR0yjWHXFZNtyerDp4vWbIgyw2XnjotkWRk0iJjaiBEfHy1hksxn0IIJaSjBUHdCq0TQpXOqM2D6n9v7i2zvEvpTW9TxnW73zzyTHu+jKfcSkO1mjDSKT3eoLl3pM6C3kz8Or6n3ue9m9+MNxiKJmE/z4S8+SNAIgh8GS4GBF23j4r5T8Pb7SiOG6ALqDXUJNc0dLJpncd/toflCwucvXI5WrWC/dEbsa/4TbJ3/T2Zf7wLbXyM/G3/nZULvsVp778Bc9X5VHM9HAxMqpZPMWtghd8jUOJeoK5y+GGZT3OO+tElXAQlejohISHhqJOI6oRjQiQCJ6s25ZpDqZCa0cbRqfjF0AWfvPqdLUIk8k5nUgZuaKewgedeOdg0yYxCqKckVVxdHm5wMwyNnqyBoRtxm16zcD1lWbElDeO2u7exe6SGZftxdJ7jBfiez8fXndbVEhK9101bh9E1EWZmq7YVz5fcu/lNFvSkcMMhe6fSm3YLjR9IJms22ZSB6/mxclT52YESqBL6i+n4nNuuD8j4asBExWKyNjXZbZ52w9QE39RFHO93xJFwwqI8uw/Wwuef+TXai3zm8PQxmoBiIcV4WaLJINxgmiKbNrBdPxa8fqGIyOXReopYf/CHWNfdQO4bd5B64P8yMLqH37n3a7yx4gwevuQmlpz+Tpy+IrtsjYW5FOPhZ+956gpCIKPPevbinyPF4v4ce0drBFKgi8RTnZCQkHA0SewfCUed5sKM3p40fqC8xbWG0zHJAuZX/NJpw9/+sTq5rMnSgTwnLCqwdCBPLmvGNpOMqTFecfBDy4TvB4xXHDKmFovmux7aSbXukEnpjExabNo63GKNcNyAQKqK7b2jdUYmGkxWHTY8PgR0toRE71VNmFXRSSSoIyoNZR8wNNHxvbdbaIr5FKV8Gikhn1FT6ExKLTTyGZOl/TnyGSOM6FMlMKMTFoGEfaP1cKHT3SoBU5NvdZRHaewpVDmOnIO/RErm3NbY9hJqMSPU5tXIMhPFC8J0wSs1Hb+vn+CEFbByJbU//Srlv7+bN95xJgDvGH6Z3/+H/8wVd/8F5osvcJosc/15i0gZKn1Fpa4AyLhRc6b9AEeSGy5ZST6bQhNHaSGUkJCQkBCTTKoTjjotVotQCE5UbCarLiuXZ7tu2upU4tFOZBNJtU2Du6VrxGIpnnJqsV0CAhqOH0+BQcZtef1F9Tr3Pz1MIWuSy+gtOcVBoGwXAZI9I7WWnOJNW4cZrzr0NcXBDZSGGa9Y6JqG2yR21MZCSS5rUsia/JffWzPtPXfbhKlrIp6ytzM4NNJSAqNryktct3wmqs6M55jwTPVk1f0hiP3ncYZ2Ux71oaR+RC9SszxKhTRBELRMziOi4pr5+LqNMO87SkXxA0n01TAMLV5YeeGb6SZ4A8NELl6CaDTw0xn2/Y+/5LHv/F8+tGUDS0Z2cdaLT7JqxzPs/62PkD/vD/jUWQV+PNzg5UAyXrYp5EwyKb3rQvJI0Z46ctk5y9gxPMH4HD7nhISEhIRDJxHVCUeddhGoJqk6dcvjSx97z2E9d2QTGa/YVOtOOHnUKOaMjukakViyHJ/+YoZK3cXzA5VsoWmMlm1ShkapkGKi6sSthqOTFgtKGfxAVWkX8yk0TeB6U+ou2ljXnFMc/W/hwh4OHqy0HPfQ7jJ+W5KGEErozWQPaPebt7+3bjSXwAgBddtXjZIzbOiLSJsaadOglEuBEOwfqyOEQISWAk2IcJFx6MkfAIZGHFWnNbxpxTtBkyskssbMJuK9DvEngVTRgMWcyVhFRfAZuphV8EoJMpNFLFvO6cUieirFP7zzHE555jHWb72XQnWCE374PYIfP8g7b/kMKz/yEURxGS9XBPdt28fe0fpRjdfrlK6zZfs+br7iNNZe8I4j/noJCQkJCVMkojrhqHOoInAurF45wJt7yzzw9DBeIDF1tdnMDcBtKLHYyZccHdPi/lzchhjtxAukZGTSahG7gYSxio3GlEjraj+QzOqXXb1ygKsuXMH9Tw/HUX6aAKEJiqE/u9v56eQ3n23yGV0tCKSMhXUgJXbkQ3f9GY/3yjUruPriU+I/Dw6NcOcDO6g1nHBaLUNLhRZXjethw+BcNziWCikcV5XRlGuq8hsh23Ko1T8jj/LUVYa5k88YWI7HZNVhyYIc6YZLw/FxPEm56rDu/BNaBG+3vGm/UOSUC8/i1DNORFy3moL5R9Rv/z9kv/MPaBMT5P/XbWS+/13qf3Arqy5dyxmXLSPo7SMwukf9HS6dinqiTZGJqE5ISEg4uiSe6oSjzkze4iPBjuEJFvVnOXFRgSULcpQKaXIZg2I+1dWTvWpFL6OTFm8dqCoBHdo3zLCApX30GSVgIEATGiMTja7HE8CcFgxXX3wKn7/uTE5YmEcTyqbQV0jFLYHdzs9c/ebNRN7zKX9vmDntBWTT+owuaSHUOZ6GVBXsgihpBBb2Zrn24pM5/cReshljXjFulbqL7frUGy6u56smxC6COZBqUdDt2dujESN0TU2jC1nVbDlesXE9SW8hzYmLChQLKbZs3xfH3TXvB2hOl4lul0Kb8lsvWoT1+59l4vv3Yl1zPVLT0N8apuc//Ht6PnsL2pOb0XYNo4+Novmzl+ccCt32GByLTZEJCQkJv+4kk+qEo06zt/hotMuNTFqUCqmWjVgpQ6NueR09yYNDI2zZvo9C1qRuudiusngUs6Zq8ytb0+wEelgRLqXk6otOYuOWX3Q9Hl0Tc14wRPaQ5mloe2PiTI+bK9FkvphPMVa2CKSIj9U0NDIpFcfndtnMtmek1vLnDY+9huX4amof+i9MQwMpufriUzh5aIRvbHwJP5Bz9lj7QRilJ1QqSvOxaJpQvnVA05SXu73GvZlOf6+JqPkQGrbPyuUlgJarKO1xdzNNfpvPf2CYsLAf6RuQzlD/D1/B/u2byN7+l6Se3IL5859R+vSnsC9fR+Nzf4hccRKi1EtQKiHFkZttHM2rQgkJCQkJM5OI6oRjwnxF4HwYKGWoWi66NiVOZhISkVDKZXSK+RT7xuqqpc/xKRXS9BczHJxoICOhiBJwCDB1jc0v7IunpJ003VUXTBfEz728n+89tKPromK+52e+FdiRZUTXNfp60tNytzdtHebgpMVoh4mmoDU5YnBohD2jdbUxs+kEOF7ArpE6Gze/zpbt+7BCS8l83BlBIJssJa1/D1NlNqYhkFJ2TbRo/tvocwqksu5omsDzJevXrOCuh3bOmJs+11z1+DhDv7VWreAbJtU//xrGs8+Q+6v/D+PVV0g//BD6o4/yxLsu4ZHzf4uFK5dzwcWrWLlqBfIIlLMcijUoISEhIeHIoH/1q1/96tt9EMcTjYZzVBvjupHPp6nXj9/d+cfz8fXkTAaHxsJUCxELies/cAqL+3PT7v/DzW+QSemxNUET0HB8giCgJ5cikMoXlU4ZlAopegspQGA5HoWsSSFnqui38LHNHoS0qfHFm85peb3BoRH+/oGXsVyfTEqnZnv8/LURFvdlOx7fbESWBMcL5vx8i/tzLO7LsutAlbrlsXxhnovOWkK57vL0S/sJpIwXEu1IIJPWWT6Q5+837eDBZ4ZD+0Xn43t9T5l8NsztPoQYt+gYdG36xFnTVE52X08a15NzqpZXzyWaNpJqLOnPctPlp/H8qwep2V6cHw1qcdDfk+ais5bOenszU/+NCGQqDcUiQmjIhQP8/N0f5KmyyfIDb5Kz67zjwOusefEnjNddfjxmsCgDC/pykFLftUOl+XOerDn096R5z28M8PRL+/neI69yzQdWHvJzdyL5edmZ5PgOj+P9+OD4P8bk+A6PfD59SI9LJtUJv/SsXjlAqZSbcRLc3kDoB1OZwbmMiesFOG5A3fLIhK2Dk3WXctXB0NVks5hLxc2LcTqIVIUogQSJ5MoOE8FNW4cxDBFP0ufaqNdtGt3NkrDhsddmnF43T8PbUyIcL+gojqKovFLOjO8fzKCidE2JzvGyjTPL5seZEALl1w7TRaKUFF3XKOZMchmT0bI95+cLAompC3ypPrsbLlXNmrNNdg9n8hv5rbWeHn66ZTdj53yQrSe+mw8MPsK6nz9I3qlz9Zbvc/H2x3li142s/OPfRctmoa+PIJfn56/N72pERPvnfOf9L2M5/oyfW0JCQkLC4ZOI6oRfCc47YzEnDXSe0rYLSM8PmKwpQRY1IZqGxqeuXAXQYpOIRBSOH4twULXmqkjFxQ8kmZTB2Sv72TE8weY7nmwRQSOTFoYuOFi1WtobZ9o81ika7c77X6aYT7FnpIZp6BTzZtyQWGs4VOoeulbH0DX8QPKdH+0E6CjEOgnzlKHjB0GcNR1Vk2ua8jlH99c0Db9L8kkQ/rWqTVe13M0bI5cP5GjYHqOVmScUMrRqRB7oUj5FzfLo60nHpSp66LOeiWaLTiAlGdPg1GVFvrHxJSzHiz+38arTUbweif0AgWHyYiPNCScsRw90Hj33Qzx1+vu4ctsDXLzjCfonD3LNvV/He+3H1G/9At7Z7+aNMZdHX5qgERgtGySbj2kubHjsNWqWF+aKJ13lCQkJCUeTRFQn/MrTLiCjabPtKGHWLJSi2vP2KbDne9Nyr7MZk6UL8nzpY+/pKIIjEZQxNfaONaYKU8L2xqX92Tkfs+8H1CwPy/ExDQ3PD1QMYEilrtIkdE3DD6BSd+jJpbpOwzt5hfuKaQ6M1SnmU1TrLm4oWPtKacphG+ZsSNS0WrUvilhYa5rg89edyeqVA3zpjidjg8NMkjiQEPgqlaVcc1jQm4lbJgdKGS44YxEbn3wzFvLdjgeUN75USHHqsiJbdxxAIOIkkK07DnD1+06OIwOjRs1mET2fPPVOVxh6cia/qDh4hQX09RSRE2m+f9GN/OSsS/nIT3/IO4eex9j+AsXP3oJz6Vq2nX4lqdIiTl7QSzXXw6SrU224s17daGf/uBUL6vkksSQkJCQkzJ9EVCf8UtIuXG5ct6rrpLqTgCyGcXTtDYTdNqbpulCxgHS2AcyUEhHnzSFa2hsRoqvFo/04ynU33Bgo6e/JMDJpEfiSgxNW/PSR7VdlOAvqlsuekWCaQFSNjtNTIgxdsGwgD2GVeVSCo+sakzUHva5Kb2SYdd3JzyyA/mIGIVTtdzSxTpt6LAYHShnKNSeu7m4vwGlHE8pDnTZ1bMfn4+ta4wM3bnlzxixsIWBRX5YbLlnJNza+FAtqlaGtXnvjll9w8tIiQNfF0VzEbLfF1UVnLmHL9n34Et6sS0o9CxnosXB6c3x7yee5ua/Mqn/6W4yXXyT12CN8+seP89y7L+MnF15Npq+PQm8vk4Uc+ypzt7wownOb6OmEhISEo04iqhN+6egkXP76nkFuWntqR+Ezn5ixgVKG/eMNGrYXCkKNbNpg+UCe9WtWdLUBzJYSsbAvy0TFjp+zJ6eEZXMl+ut7ynxtwyDLBvJkTK1lMu6FdgvTmB6/FgnSZmGqCfUeA0mcsbx/vMHt92wnk9Yp5Uzqlhc+t0+55uIFkmUL1MJkUX+u5XzlMwbVsHnR92Vruka4UBAiWoCoxUU2rc6H7fr0Nlln1q9ZERfHEArcKMVD08S0qDw/gNGyTW9ekk4b8bR2cGiEHcMTqp3TVv7t9kSWtKnxuWvPjD8ny/HiBUHzoiCQyi6Tbjp+9fi5+d8jui2udgxPcPMVp7Fp6zC+H1B3Jbu1NAt68/S6VR4kR/lP/4LVO58le8fX0fftZc22H3H2i5vZvObDbD33ctKZHGcuG0AEPlLTZz6QkMX9OfaO1gikQBeJpzohISHhaJKI6oRfOjY89hqTVUdVSxtq41o6pXcVPvPZbLZqRS87d00gEGhCtSY6ns0Hz146Y+zdbMK9arktyRy26+P5Hrmw6GW86oQlKoID4w0yaSNWySlDC4VgQDGfitsGNV1t3BOA4/othShRnXc+YxAEkr2j9akGSFuSz5ogJa7rM16xMXSNRX1ZvEByYKxOfzHd8l6K+RS241FtuNNaDCNBvaCYptZwOTjeiAWrrgvyGZObLjs1vv/qlQPc8qFVbHh8iP1jddQEXx23EcapeIFs8UtLCeNVh54gwPOCloVVszjWNGWBCaSa3PfkUi2fWSal2hQ7TbY9XzJRsVjadsUjWhzNFmP43Mv7GdpdJpBT38tcxowf32mjqCU0aqUFaHg8+so44l0XcPp3L6X8zW+x+J++TdZucPlP/olzf/YID154PStWfxR91zCyt5+gp2fWjOsbLlnJnQ/swLK9rvGDCQkJCQlHhkRUJ/xSEWUka5qI/cljFZuFpUzXjX+RkNnw2GvsHakDsmv03I7hCYq5FA3HjzcVZlM6O/7/9t49Sq6yTPu+nmcf6thVfW4SkhAMhoAQwkHhE6OcAnEJAUb4QIgz+qI4o7wj846Dx1k6yDjCWs4gAirO67CWwcPIBxjMGAMIKomGQ9QQSQg0hA7pdPpYXefap+f749l7966uQ5+Srkq8f2upSWdX7btq795e+973c119KayrU9dUwv3HT70Gi9ll/6YoDLrKcShTkqEmjMEWDkxLwHJMaIqMLB9zH/k7DjA0VvA7sZwDbVENjDGMjBfAIAWl6S7w01QZ7DKaLpZZ25m2gG07iEY0pLOG35XWVA7Tkp30dM5ELDLRXU7nDDckp/aoxmi6VCFWbVvAtGzsO5iuEKTBYJ6Nz76Ojdv2yflrhjJBHZy/zhYsHN8Zn4hddwQMc2Ko2nGkmOZMLnQMPo3Y2TuMSEhBvlQ9zTBfNAGIitl5w3IQ1njdsZCdvcP48VOv+W4pdmDmXVE4OpPhCgcaXeOIhuVC2RFwKPEO/H4IOPnEOBKf+gReuuAysO8+gDNffBJt6RFc/8vvwerbivwtt8I662zwVApob4MTT9ScTfduYDZv78NYtnntqwiCII4FSFQTRxWbt/f5UdtedLjjxk2f6M7E1qJkOehoDfvCdvKs7M7e4bJOY3sihGhYxllPFfM8lUtENcu/zdv7kMoZsCxH3iA4jh96orqicDRjoGhYcBvP5QjZ2Y6EVCRiIZQMG9GwWvb+r/enARn47Y9GMMgZ7Z62CIqGhU61fAwmGdcxMl5EyZQ3AemcgXTeqDu37HlAB5ELFjkM08am3/WhozVcc07ZWyS45fm3UDTKRW9wJFgI+KEtjMG/4QhuazsOAAbOuH9T43WGNa322ETJdBDSOPIFOeYSvAFSNaXuWIhnm9jaEsJougiAgUFgPGsgGdexYklrmSgfyxRRsuRNj+fgYtkCLw1bcBYvAU+l8PaVCsQ9X0N2/98h+u1vQX/6Kai7X0biUzfDWP0+5D/5v+GceCJ4alyK62gM1YLbvQ55V1dL7QNIEARBzJmmF9Uf+chHMDY2BgCwbRuvvvoqfvazn2HFihVl223fvh0333wzli5dCgDQdR0//elP57tc4gjjRZKPZUpwhOxWCyG7r/W8g6eKm/ZEV71O41TUGw+pZfn30BN7JxbNeYLa9b12BKp2VSdmmBnGsyVwLl023vfORdjTl8LweBGbt/dhxZJW7OlLVThtMCZntGV4jFrRmVUUjoWdMcQjGobHizBMB8lYCOPZyk50PRwBaBwwbADcqfvdb97e50ehxyIacgVLLoh0PcKDtQNy3ObVA+NwJs13A3IGW1NZWbJl8PhzVju4JhJS4Qh5U+O5jEw3eTEZ16FwjvaEnJc3LWlP6M1SB88/TVVgWg7SeRPRsIZ80cR41oAQAnf+6I94/3lLcMaSxeBjY3BOYMh+7S6oO/+EyLfuhrZrJ/Tf/hratmdRuvJqFG76BIRRghKJQLS1wYlEGxLIQhAE8ZdO04vqBx980P/zk08+ibvvvrtCUHssW7YMjzzyyDxVRjQCb3bZEy6el/HCrnjdhWTBhYSFkuWKHhsjqYIv6hSF1+w0Hs6Y5+AYQFhX0BJRMZadSGicavZVCLmdqnCYllwEuGJJK7buGigbT/jVjgN1BKTAyHgRKgdGUkXEoxpCGsdoWi6mXOguzPQs8KJhFeM5ozLicIo6vX0HEwmB8jnlh57YC8sWyBVNAAywpCgumZUx5LGwioee2IuTFiZqpjUyyKh4r/sNTFpIOnkoPEAyHkLJtBGP6rg9YKPXmeyrOzPfmQwjWzShcLmwNRJS/QWaK5d1VojyREzHyHgBpuUgVzAwljEACLQn5Pm9YcteiDXLsXJZN3hLC/jYKKwzViHzwPehPf0Uovd/C8qBtxB+5GGENv8ChQ9/BMXrPwQUClBiMTitbXBCsjbvfBvNGvi/X1xT83gRBEEQc6P+Kpcm4+GHH8YHP/jBRpdBNJC15y6BbTvgnKG7LYLO1giScR1/84FT676uMxmGYTkolCyMpouwbAHmevc+9MRe9A/noKtSELUnwlAVz4VC4MY1y6fl/DAdPBHpOXJYjgBXONadvxQhjU/ZCfa6zpqmoC0RwvLFrbjthrOwpy/ld0IZkxZ2RcMGc7vYCmf+ax0hNWU8oqGrLYpYRMV4roTBsQJsIT2lD47k8K3/7yX80/1bMZ41MDCSh8Ll+8wE273p8UYcPDxB6i06HcuU3E69O8DAGOKRCRHKGdCeCKEjGYGicLy4d7jmPjWVY+uuAezsndjGO/7AxMLP4HfKGRDWpWDOFQy80pfCx+78FW75j99g47Ov++ddybQxli6i71AGAyN5vHEwje9t3IVs3kD/cB4Hh3PIF02UTLtspj64fwD+yE5YUzCeNaFwho5kBNGwhpA7arJ5e588XuEI7AULgZ4eQNdhXnQJxn/0MHK3/iOcRBIsn0P0u/ched0HoW96HCKdBus/AHV4EHtfP4Sf/Oo1pHIGWiJN30MhCII4qjlqRPXQ0BB+97vf4corr6y5zb59+3D11Vfj2muvxaOPPjqP1RHzxcplnbhxzXK0uj7TKmcIqRzffmQn7vrhjjIhFcQTRalMyW1SyrEBz4fZsoUveiIhFT3tUXS1RbHs+ORhE9RA+RiCJ34VhWNPXwpdyfCUotXT3BFdKRNtw+NF6JPs9mxHwLbd/ziVNniaysEYQzIegsq5tLPzXuPI14+kS4iEFNiOgGU7cFyP6ukiu+8C2byJ4VQBAyN57B/MYmS8iLa4jgMjef97l/PQslNfMmyYlgx+WdITx+KeFrQnZOfVsmwYlgOlxtXLcuQThoef6fV/tvbcJcgXLRwczknB6y6IVDmTi145QyKmYyxdRCZvuSE2Mhxm47Z92HcwjRvXLIdp2kjnTRmZzqU7zO9eHsRopoTuVlmffALAym7GgqJcCIGSaUNVGG5edyrCIcVdbFrEwGge+aIJ23bQe2Act317G+764Q78qXcEdqwFzuIlQEcnWDiM0nU3YPynj6Fww4chNA3K4CHEv/plJD6yHur230OMj+O5X76IpWoRPQm94mkBQRAEcXhpeOvi6quvRn9/f9V/27ZtGxRFdo8ee+wxrF69Gu3t7VW3fcc73oFf//rXaGlpwf79+/HRj34UPT09ePe73111+1p0dMRn9gEOI82+kKhZ6ru4qwUXn3ciXth9CN99ZCdM20auYGEkVcDr/btwzcVvx4cuXVHxmmQyiq89+JwvKFvjIcQiciFioWTJWWpHzv6WTBsQwHWXrpjyc7+w+xAeeeY1HBrNo6c9ir+64CScc0pPxXZdXS0YzcqOYTDdTlWYP/7R1RrG4FhBLsRE9cTBaEjB4uMSZftZ0BXHWLqAcGA8Qbht72rvwRhDxg1zAeRiz1pjJ+m8CV3lYI6AYAyawmEbNlRFJjtWQ1WkNZ6AgKJwqCpDNm+BM0DXFMQiGrbvGao7TWJY0nvaiycH5HHL5E3ZXeYc3BW2QYQQMCyBt4ZyePIPB/ChS1cgOZyHm7Yuv3sh49MFpHBvjYfREtUwlCr4++GMgQOwHAdPvHgAP77jDHzv57uhKAycMVi249dfMGws7NIRj+ooGhbaEhFcfN6Jfk3e+ffgpj+jf0jOjh/fFccfe0eQzZsTx8h2pIuKI6BrMnwnWzTx46deQzIZlce7OwmUeoDRUSDbAnz5S8D/+hvg7ruBn/8c6quvIPH3fwe8973gSy6BWHQC2ooFsPa22l/2LKHrZW2ovrnR7PUBzV8j1Tf/NFxUT7ej/Mgjj+C2226r+e/x+MTFffHixbjkkkuwY8eOGYvqkZFsmZ3XfNHV1YKhocy873e6NGN9P9myB0XDQqZggru+0rYj8NMnX0V3IlTRYT6hM4plCxNls19LiNoAACAASURBVLGmJbuHC9qjVcNdTuiM1v3cQb/ksMYxNJbH/Q//0e9SBudZdYUhlS5iOCWgBXyMS6aNtrgUt6mcgY5kGKOZEkSNpMFL37nYnxf2arv4zIV46Im9yOZNFEo2TNtBnfRuOI60uvMEKWe1JLy7vZCCOuoG4Xjf4f7BbFlYi+L6RJuWtAzkkHHwJWmoIbvRtoOxdHHqRY8CiIZVpLMGNJUjFlaRK1owLQeJmIZc0UJ5SqX7ssCfvXNh8/Y+hEMqdE2RM/Nu4A5nDOGQiojG3YWCrmsJpDgH5OO8QtHE0FAGhaL06TYn3YAIITvU+ZIFy3JwaKSAp37/Rtk5OD6eR75goiMpHWhSmSKeOZgu8+sIzoknYjosW0DhHBaz8ZMte8oXu6px8IgKPjoCEW8HvvgvUK7+fxH91t3Q/rgD+M1v8L/Zb/HcKe/B42ddDmNBdSvBuUDXy+pQfXOj2esDmr9Gqm9uzFbwN1xUT4cdO3Ygk8ngve99b81tBgcH0dXVBcYYUqkUtm7dik9/+tPzWCUx3wyPF1Eo2W7XkklB5FrTzSYIpp57Ry02b++DZQtk8qWyBEZvHtYT3JwBB0dy0npOSPeN0UwJ+aIFw3SQK5hIxnSMZ0swTBs1GsAAgF9s7/NFdXDRoxACmbz0WtYUjlIdseMIQNgCbw1moHAZw446mosz5o+TBBf96aocnWEQMG3pYGK7NiZCOG43GL5e95xapoOAHAWxHAfprIFCycKC9ihULsNhQrqKMX+cpxLpouL43080rGJwrABgwjXGcgSKJQuFooVlxyeQzhkV8euOkKExgPzfWj7XMkRHSmTGUOFj/cDGl1E0bf+GqmDY/udUFVYR1z6aLiGdN5GIaoiE1Kq2jk4oDLFgIXguC4yMwD71Hcjc/wC03/4a0fvugdL3Js57+bdYtfc5fPn/fH9a3ztBEAQxO44KUf3II4/gqquu8kdBPL75zW+iu7sbH/rQh7Blyxb86Ec/gqqqsG0bV111FS655JIGVUzMB51uR1cJtPocIZ0mpgqCqZeMNxP6h3PIFU0wxt2RAIF0rgTbdsrmpwfHCmCMy+RAxvx53XzJQjKmIxHTkXG7zLXwesklN+xkclz7wIgMtulIRhAJqdh/KDNlN9gLS9EUDkNxajpqeLHe+ZIlReU4kIxJx5CSMTG+IMpeM91vsRLPtcSyHegqRyKuA65HNQDfMcRxHD92PIg3fqIqTLqsaBwD7vw2Y4BwzxnhAN43nsoZUBUOw7LKahAQuPSdiwAAl75zER57dl+dymU6ZGtLCJyzspurkmlBYcy3a3TsCe9wmZDJysZwguFGLZaD42oEFgkw2LEWsGgMfHwcLDUG870XYPzd5+OFr96Pd//mEcSLWTiCVX09QRAEcXg4KkT1HXfcUfXnwU70+vXrsX79+vkqiWgC1p67BL39u+A4AhzCFZAC0bBe11d6Nh3pWkgBJDufgCuEhBTXwY6u6Qa8CCFHLxZ2xjAwkoNpCyTjcl64EOiA1nF988cFgqI9XzT9BX/DqQI6WyNIxHSk6qToKQorW6yZLZrgHL5fdpDJohUAxnNm3e9mLgRnyh0hP5PCOR5+ptdPYnxg48sQkAEqcU2mQAp4Xtby1dGwjrCuIJ03Ax10wLt3kMdNdoiHUwVwJlMsLVugaFgI6youfeci/8nAuve8DT97dl/NQRnLdqC5C0Y920DvOGmqAst2EyNF+dC8Fy8fFNQiMNKUK1pT2joKxmG3toHHpQWfyGbwq5Pfix0nn4fzn/8FFnRGZnwcCIIgiOlzVIhq4i+D4CjDdDrIK5d14gPnLcGm38kRDFVhiIZ1qAo7rL7S9fDGJjxRJACAyZ97ntrBCHAAUF3RZdkOtMDTl+Civ2qC2vtRe0KK8APDORimA9OyyzrSjgBG00W0J8KykxyI8fZq9MYUbFtgKFX0Z8y9iHbTtKcd9DL5BoBBLvQzrDm0quGNjQgIwdzxEwf9wznf4aVk2jKm3LDh2I4bQW5L0Ww7AAOyeROcydnssK5gLFMqW9jImOyoczYx4pItmFh3/lI/SGdPXwpLe4f9c/H4rhgOjuQAVHbIAXnTNJqWHuSOA+xNp6C5do3ZgglHTNgbMg5EdRWWLWC6xz8R1RAOqb4Pu6pIl5jp3gg6qgqnqxs8kcDCxW9iZDCFp1d/EI1bUkgQBPGXAYlqoimYPMpQLcq6Guve8zYsXZDAU3/ox8Gh7JzHOWbK8Z0xDIzmUTBsWJYDVeWI6AqOcxc+evPbybiOobE8AIaWiAwG4YwjEpoQ1dJNQw4jVFs2yFwv5Q9fdjJ29g6jWLJlEmM1AS6AVKYkw2WiclbbtIVchMc5bNspe51pSU9rxxFoawlBVzn2H8rWWbo4gaZwmAEnDAH4AnE2hFy/6JIhBXLwZoMx4Ae/fAWmaxM4sT8B27ER0jgM0wHj0qUkEpJCuiMZRjQsZ5MLJQvj2RJKpvwOvCAdR0y858+27vPHcrxzcd/BNPb0pWQITg1BDcC368sWLLTGddiOAst2kC2YiEc0FA25QDTidsE98d6ZDCNbMOW8uHuT44UUKZxjZ0DYTwcnFMYZ7zsDT/9mN5RMehZHgiAIgpgJJKqJpmCqGPF6rFzWiYvPO/GIrSSu10H3hHM4pMK2HYxnDaRzBuLu2IcXUT2WNbCgIwYIgaLpoDWm47xTurF11wBKpu0HzxQDi9eCMAacvLjV3/ddP9yBeFRDJi/HO4IiXFM5HNdXGkyFqsqkyOFUEZYDcOFUCHFHAIqQ9nWWLfzRkOlgOaLiJmAuMdklo/ZcuRDASLrkj9sEcQRgmA5aW0K+VSAg48bHs4YfQBMJqTLanTP0D+fAueyCB+8DhAAyBROayhENaxgvWdj0uz50tIbR1hKCwhlSWcMf6eFcZnB6fuByKEgmNGqqKd1chBzxaUuEYduO7xCzLvAZvJvLtGEjnSvJd2EMusYrbjKn82Tn1BM7YDkr8Owf30KuUJjBUSAIgiBmColqoikoi5F28WZSG8lUHXRPxDz8TC8GR4tQFY72RAiWkIvTblyzHLfdcFZV+6CdvcN4Yc8gDo0VAQj0tEehcIaxrFzEBshRkXhEQ09bBLcFYrOHx4toiWrQVI6hVKFMxLa5i+TSWZna6DgCY5mSKx6rd7YB2WFlTHaGC8b0O83VLNU8h75qu+IcUBjzXUDqzY9XvC8m5qxrbdASLU9vTMQ0jKZL/s1LJm8inTMg3C6/U8uNRAik8yaiYQ2Fkg1HOP5NXzIeQr7oLmjkcoY++CGEkFZ8A6N5WJbjutMImJa8oar1NMX7WXBePGi96N1kzuTJjneeHouesARBEM0EiWqiKQjOH3t4UdaNZDod9JXLOrF5ex+626Nl9dfrtAdF0YLOKAzXL/s9px+HrbsGoCi8wvIviPd9ATLMRAQE3ch4AbGInC3XVe7byMlAPVHflUNMxJjPFlWRYyQi8HdvAZ4M3dHBGHPr8hZ3Tu+9p9qMoTzUBgBUVcHCjijiUd11a7Hk4lbOAgtcK7EdQJiya27aDrRJiYSeWE9GQjKp0/255xriQKY/cvf4CAALO6JlN0cek7vOisKwqDVWFhIUvMmcy5MdgiAI4shAubVEU1AtxrmamJxvqsV/V+ugT3c7j3px5cEY9taYjvNPOw6bt/f5kdU7e4fLYtcZ4Ed2yz9zJCIqFnbGYFgOLNvxxyUYY2BVRic8OK8fAjMdLNtLK5SC2nMiSUQ1dLg3SalMyd9+LtZ7kwnrHOO5kt+J9s6jay48CbfdcBYWdsagcAZF4VA4g+p6iHswhrK/SwtD2992YDSPtwazsgNtCyzsiKKnLQLOme+XrmuKvxDUcdwER6/HXuXL926wUjnD7zoXS7aMdQ/sL50z/JvM4PmWL5oYGM1jaKyA3gNpfyEnQRAEMb+QqCaagpXLOivEpDdz2kg6k+EKF4tqHfTpbudRT4SvXNaJ2244C+svXY5s3sDGrfvwen8ajKHsMf+Na5b7Fn3egjtdV5CIaSiaji+8PVcLx+2WskkiMkg1z+fZwjlDPKIhlSkhVzBQMqWryIh7o9ESVaFUG46eJQpn6GqLIhHVUTLsqufR8HgRtuOUCedgDQpn7n/k34UA0u7sdK5owTBscCbDe9J5A+es6MZtN5yFtpYQ3nZ8Aou74+hpj/rJjIB0hlEVhvZE2J+Z9/BCYUbTRaQyJRQNGyFNQUjnyJfk4tfg/lYsaQUwcb7li3Je23bvTLzQGRLWBEEQ8w+NfxBNw+H0jz5c1EtgnM12HlONu3jdy/GsAc4ZHCET+9oTYSgKl53rG85CT1sYB0cLYEz2Qi3LxvC4FH6bt/fh/NOOwwuvDKF/OAeFc9+z2UMIzxNZ/nm2NniMTQhyb3SEAcgWTEgfbzlDnc7J0QzPmzusmxhOFefYG5fYjsCbAxn/RqE9EUI2b2DDlr0I672AEBjPlmAHUh+9783rUCsKd11cFIQYYFoCibiOsXTRH+uwHQFdUxAJqdjTl8I6yOOZLZpQuFTSqirfJ6Rz9LihLSXTRmtgLMU7xkXThuIGB3lWiJ6vuaZy3/s6uD/vfBvPGq49X2XozOQFjaNZA//3i2sOwzdNEARBVINENXHMMlPf62pMN4HRX7D49Gs4OCyTDXtqJOABU4twbzzEs2djDHAEQzpnoLstMjFW4q0IBIcIzEsrCkcqZ2DrrgHcuGa5rO2ZXhwYzlXU4gnqWniWc/UEt/d6hXM4jlyYZ9vCj2h3hCsQLRuFko2ka5psmPZhEdTVajkwnANnDLGwirFMEQCDrrKymHThjqloKkNEVxGNaP7xGBzLgzOGobGCO4MNqO7oiOxGC/84rD13CX781GvImYYM4jEdCAARRc5TV7vJmgiF4e4ThYljLIW0UnYOBffnnW/3PfIShBByQWMshEhILdsuOLvfEqHLPUEQxJGErrLEMclsfa+rMZMOesly0NEa9oWZt8+LJzkvTCXWPTcU1RVcDFLcWrbjL2r82J1Py2Q+AHJZnIRBjoQEF6/ddsNZ2Ly9D5rCq9rHBV8bFLktURWxiI58wZyyiy1FtHTfyBYs11ZuYr46EdWQzk2EnOSLZs1UxulMdjPA99auhkxOFMgUvA6ytDNU+MQcNwPAFYaetiiuuWCZfzzCGpffi9vBtuGFxAgIIV8cfLKwclknBtMl/PSpV/1OtsJlpHwqU8LCzljFzZh3jBNRTcaWuwFCsktd7mE+eX/ePpcdn6z7xGPy7D5BEARx5CBRTRyTzNQd4XB0tevt8+LzTqzYvp5Y98ZDPMFlBcJaDo3m63aWg3PTwcWScp5YgDMGpkxEYk9+bZBM3kK+aPsL7+ohIO38FEUK0pJpw7RFmS2cZcvEwpJpIx0Q1KoyMTrijZKoCq+YQa74nFNWBT9h0f9sTH4vjhA4visOIQTyRavseNz1wx3QUkUZl84AVZlYgBlSedWFtC/1jqAjGS53gHFHPqo5fnjHOBrWUDJsZAqmO47DcM6KTrzWn/ZtAGc7dlTNqpIgCII4MtDVljgmmYnv9XS72pOF94olrWVpeAeGc2hrCU1rn1PhiSVF4YiGFGTy0hM5aE9XDyGk+DYtGyFNxc7eYXQmw0jnDNiOA2dGo9MChjX1PjVXTLfGdFx/0UkA4H8G3RWiqsLwgfOWYE9fCoOjed8xgzMGy71TEEKOmyRiOopG/cCS6fZeg9XLLrUU+0D1BaXD40Uk4zrGMiU4bkw6Z1JU6xqv6jV9aDSPsDZ9Bxh/LrpkIVeywBkDmEAipuO1/jTOP+24svOr3thRrRvCarP7BEEQxJGBRDVxTDId32tPJPcekM4arS0h395ucld7svAeGM1j71spJGMhtEQ13wZtxJHdYMt2oCpycVlPW2TG9QfF0khKOoW0tsiZ2TcHaidHeiLTdgRgOWVpfOefdhzeHEjDsKZfh1zExwExtQo3bQdhXSkTdfsOprHl+bdQNCyE3VjupQsS2NOXAiDFru2IihEOw3KQzhkI60rNbjVzF/LZdbrZkwkuNmyPajWtG73zpz0R9mecVYWjuy2C2286t+p797RHMTSWLzvn0jkDhungtm9vqxC8waAXCAFNVZCI6YiEZIz9nr5U1Q73ZLwOu3c+b9iyF53JPqw9d0lZJ3s6TxsIgiCI2UOimjgmmeqxeFAkO+5qNc95IRJSKzqMk0c7CoYNBoZCyUIipvs2aNmCBYUzcCZnYw2rhPedsWBWn8ETS7d9exuiYXVaM7HBGWN1Uhrfnr4UOpIRHBzJTdsbWqYXirrjJkEOjub9Lj8AbN01gERcR6cqLeB+9Yd+YMcB1w+7fD9lfxeiqpgOpi8ySCGbL5oYSRcruu9Be0DmLra0A8k2qUwJyXgIYY2XCdGVyzrLnhR0t0X88+eaC5bV/Ox/dcFJuP/hP/rnXDpnIJ03kIyFaj4BWbmsE9Gwis7WcM2gl2pUe2rihQYF93XjmuW4cc1ybN7eh7GsUfP9CIIgiLlDopo4JpnqsXhQJHuLAQHpvBAJqRVd7cnjJL5/cECdmpYjxZvq2bJxRHTF78rOlpk8wmcBeRrs/gZF2vFdcQyOFerOKweptRCwGrYtYNkCm7f3AUDFjPmoWwPjzE00rDHb7f7I6yxP/jkw8fNoWJM3MKYDVWEoGDZiYRWJmI6BkTxsx0FHUj4tGE0Xwdx57UhIwWimWPa0YbLoncmc/Tmn9PgCdni8CMN0kIyF/HTHWnP9M00TrTautOn3fYhHNETDlfP8t91wFsWUEwRBzAMkqoljlnoLAYMi2VsMyCBgus4ak0cCJgsfTzh7c7mAFNi6quC4GjZos8XrmqYNG/lidbcMj2AH2rQcDKWKAIpgDIiFFDiCYXi8WDdVsR4KlwmB9ea6xzIlZPPy5qR10oy5aTtlwlhVWFn3eaYcGMygJRaCpnJ85P0rsHJZJzY++zq2PP8W3hrMQlU4QpoKzhnG0kXf0SMR05DOmxVPG4Kidza+6UExvjedgu3I4JdoWAMgF0z2HhgvGweZqcd5tQWxtiOQL5bHs3s3UuRTTRAEMT9QoiLxF0kwATEa1tDeEnIXo7GqaY6TY9QjugIB4fsCl0x7WjZos2Hlsk6cf9pxyBZM302jHtVmZ4UAskUbhmn5f58pCpc+1Hwaitx2BNJ5E32Hsth/KINUpohUplixX8uuP1oyVZPccmTAzPmnHefPFXsjJ4u642hPhqEqDCpnMC05F93eEpJOJFWeNsx2YalHMHLcC24ZzZSQL5oolCzZKWesYhxkJmmi1dI4NYWXfQ5AnnthXcH3N+3G6/1pjI7XX/RJEARBzA3qVBN/kUzuDioKRzJeW8xMHgc4rj2KC1YtLHNnOO+UbmzdNTClDdp0Cc7N5osW4hHN70TuH8zWHMuoFjPu+T5bjhTHgdHiim1qwZgUco4bwe1tX20+25k0plHLj3o6BH2lg2iKTJrsSIb9pMGHn34N41kDpuUAblqiqnAkogLLF7dO+bRhrjdBwS5yMh7CqNsdT+dMWK4/uBAOBscKSMR0mJaDBza+LOeqk2Gsv7S2mPaoNi4SCSnIFUTFuWcaDnJFy02MpIWKBEEQRxIS1cRfJLOZma02DrBu0jZLFyTm7HcNSEH9/U27UTRs2I6A7QgUSpYfV60EFiROFp3VOr+TLeW8eG6BCc/mrtYIDo7ka9YkhANbyG61oiqIhTWMpos1Ra/HVOMdXh0MgFLFMrCa/R9zo9VVlZeNOfS79Qv3v6Tod9A/kse6Fe5ND+QYhmHa0sPasHFgKIuWqA5VYTVvgqbjZR4cK4qEVLQnwhjPlmBYcl+eyLdsgeFUwRf+na1hDIzmcd+juxDRlaphMR7VxkU0leMD/8+SCgu++x7Z5QtqCn8hCII4spCoJv5imc3M7Hy958NPvxboMMpEPwFgLF1EpCteplI5YxCuh/J0CYpcb2xAzl9P4O1b4Rym7SCkqYiGVYQ1jnTBgqpyxCMaMoX6XWhtUsR5sCPOGHDy4lZkCyYGxwpwhEBYVxDWFeSLFgzL8QV38ON58eKJqOZ3lzdv74OqcNmlDuAJ/l9s74OuKTBMw48Rn/gOBNI5A1e8+4Sa4UDT8TKf3EWOhOQ8dzpruAE+QvqEe08KhOy4F0qW/B7d0Jx6CaD1bggn3+QBwp8jJwiCII4sJKoJogk5NFYse2TvJfqZtoAQQkZauzZxjiOgaQpMt/OqqpXCsh6O8MQzYLmGIN78tPfvusqhKgxhjePAcB4CQK5gVh01mczkbSaL42zBxDknd2HrrgFYtlxwl8kb4IyjMxn2u/Sm5ZTZ+9m2XAQa1hVcf9FJ2LBlL5JxveLmwKNkOkjEdJQMG6LKZ+QM/hjJZKZK6NzZO4ynHt6JA8M5FEs24lENLa7gt20HirtYcSRdquja20JgLFPyg3BMy8FYpuSPhty87tSqwno6N2897VEcHMnBEQwKm+VqUIIgCGJa0EJFgmhKyhfwyUWUsuGYL1oIaSqSMR0LO2NY1B3Hce1RqAqHpnIofOZtSUfIMQtXY/rdXcedo9BUjmzRxMHRgi+KpyOop7Od5Qhs3TWAkxYm/MWYqqIgFlExmi5CVRh62qM4cWECyYC7BSBFeaFk4/ubdmMsU6q7yJAByORN6UuO8pEVzuSYSK3XV1scGBw7eeiJvRhLF9DWEkIsoiJbMJHKlPxFh8d3xqCqClSl8pLLXTcVBvhx9LbtQGFAybTw0BN7sbN3uO53WItrLliGkKa6i2xnFKNJEARBzBAS1QTRhCTjIdiOgGE5MG0HtiM708d3xXDX370bN687FZob/e25j4R1BeGQCtOa2n9aVZgv8DwJrqoMHYkwElHX/s1xoHCgJaqjZDjuXC5mbcfHJ72WMyCkKwhpChSF40+9o+hIhrG4O47jOqJIxkNQFY7xQGhJOlc9wCSdl13zerPbnMNPRpyM486K11qkGHSL8QiOnSgKR1iXAT3JeAgdybC/qHTDlr3IFkzk3c6+5n733PXq9mr2RkIU7o70gEFT5Xfj+X7PBlVh0NwnDQRBEMSRg8Y/CKLJ2Nk7DMO0/eATIeSIQDSk+ol+k+dqwxpHIqZjPGdACAbGhL9Qrxq2LaAoMubbcQRUleP4rjhMy4GiyCTGeFT3Z3Yt20G+aLljIvV9qiejKTLZkE0Ke3EEYJo2Do3m0RLVUDQsdKpS1BZKFtI56eIhIMV0eyJUd2681kJHb1EmY1JYyhGQwqS0SIFwWK+5SLGel/SGLXvLgoHk9+tgcLSI7vYoomEZJgTGoCkMli0XFiZi0sM7lSkBmJiN54z5TwgSsVCZzd90FksG2by9D9GIhrZEeEorRoIgCGJukKgmiHnghd2H8JMte6YlhjwhFNIVpPMmLMuBwhnaW/Sy13hztcFFdG0tISicIZ03EA2ryBYsf3tNAUy3iS0AxMIqOOcYz5Wk77bb8bZtB9dPsha864c78Hp/Go6Qos+b8a4HdzuujgB0TUFLVAauWPZEJ11AhtSMpovQXLHqOAKj6SIABkVhEEIgWzArOsWTEZD7k59zojbVvQkQwkFLNAzOGVpiOjQOpPMWGBPoaY/5Nyx3/XBHWfy356gR1hVACOSLVtkx7Ez2IZUzoAcs7sazhhs8MzGDDQCJiIqSe+PiiXPPyhEAHtj4MkqmdHkJ6yrSOQMj4zZCmoqNz75eNYrcOxcms7N3GL0H5DFTVenPTRAEQRw5SFQTxBFkZ+8wHn6mF/0jeaicIRGrHocdxLNlY5riJ/EJV8xNfu/N2/vQe2DcHTvQwVx/ZAAwTAeaIq3UwrqCXMmCqsguNZicL17YGcP7zliAF/YMou9QFhACPYFESG8f/cM5WI4ju99M1LXQ8+CQ+xIAIgpDJKTCsgVKgXh0rwvPGRAPy9nf8awh7eeYfG17IgxF4cjkTcTCKnKTvocgwcRGb9jBEQKcM7TGdQgBtMZ0XH/RSRXf/WSHj0NjBex9K4VEVEcipvvd6cle0l4Xu2hY4Iwhk5c3AAzAodE8EjEdkZAKXeXIFy2sv3R5zW7zzetOxUNP7HXdSEryUzAGXeN1o8hrfRbm2qbYtoOhFIW/EARBHElIVBPEEcITNuNZwx3lEBjLGmhvCflzstVEdbVwj8mhJEEB6Ai5yG3UHSOIhmVIjBRwp/o1SJHJoChSqHLOEI9oWLogga27BtDTHgFnDIbl4KEn9mLfwbTfGW11a05lSlNa9zH3vxxIMahw6byRypT87jZ3faY972bOAMY5blyzHPc9sku+D2NgrjOGwmVdi7vjEKKAfKn63HhwploAaI3rSMZDKJk2WmM6brvhrJp1T3b4KJQsGWNu2EjGWU0R6/35qT/0483+cRQMuyzOfTRdRCysolCS8++bt/fVfFLh/eyBjS+7M9VyFCcall3+WlHktT5La0vI7/qzutE+BEEQxFxpiiG7n/3sZ7jiiitw6qmnYsOGDWX/VigUcOutt2LNmjVYu3Ytnn766Zrv89///d9Ys2YNLrnkEtx+++1wqqVGEMQ84QkbRwgoXEagM8hFdZPnZO/64Q7c9u1tuOuHO7BiSWtZJLo3khGc9w0KQE1VIEWTfG9gQoSvXNaJG9cshxDSik9VGNoTYb9zOjxerFho5y0c3PL8W/4+GJOzyJrKp1yoKAAkY7q/4LCrLSoX7kU13+qvLNGRSScOr95lxyeQiOmyZjDfHQOQs9VdbVF0t0UQ1hUoXArLkMbBXV9tD4Uz5IoWDo3mcWg0j1f6Urj1nt/irh/uqOqmMdnhw7LdGHNr6hjzlcs68bW/Ox+JqCY9tYUcj3EcB7YtMJ4zYTsOWltC/pOKWo4eK5d1IhpWsagrhuPao/7TilpR5NUWV3qfxQugURU2Ix9zgiAIYuYwIeqtl58f9u7dC845HnjgAaxcuRLr16/3/+3ee+/FwMAA7rjjDuzbARQhZAAAETBJREFUtw833ngjtmzZglgsVvYe+/fvx4033ojHHnsMra2t+PjHP44rrrgCV1111YxqGRmpHf98JOnqasHQUGbe9ztdjrX6Zrrgayo2Pvs6tjz/FoqGhbCu4oxl7XjhlWF3IZxsx6qcux7TQFdbBK0x3R8dMC0HhZIN05bz0+cs78RY1vBneQtFE+m8BUAgGQ9hZLxYNRRlMt5iRw9v0R4gPa672yIoGjaiYRW6pmA8W0I6b/ppg0EUzqZto9cSlWMah/O+dvJnqUbMXRQ4E59uxgCVA7bD3Jlx+fPpfNSQxhDSVP9mpl69nvuGqsgFk6blwLJF1e9U5UA8qkPXFKRzhj9rDkhhn4zrUBQO23Zwozv/PjnWPqQrSMR0HBrJo+gO0z/+jSun/b1MB7peVofqmxvNXh/Q/DVSfXOjq6tlVq9rik718uXLcdJJJ4HzynJ+8Ytf4LrrrgMALF26FKeddhp+85vfVGz3y1/+Epdccgna29vBOce1116L//mf/znitRNHH97oRCpnlC34mq0X8MZnX8fGbftQMm0onKFoWPjdy4NyBhlStDmO7HzK0BHmd543b++DaTnIFGQnU2GA4wi88Mow1p67BOsvXY50zkAqZ0JACrBhV1AD9QU1UCkMhXA9qYVcIJjOGQhrcsFcrmBiNFPyQ2QmM11BDQCZ/OEV1MD0RG6uaM1IUAPyOzFt+P7V3vczHUqmqCqovfcJ4nXbTctBtmChZDo1v1PLAVJZA0NjBRimXSZcHSEwMl6EylmZoA6e07omF6C+NZT1BTVBEARxZGkKUV2P/v5+HH/88f7fFyxYgIGBgYrtDh48iIULF/p/X7hwIQ4ePDgvNRJHF8HRieC4w2y9gLc8/xYYGBQuFwUGZZL0dZaBLAJSMHe3hn0xNDxeRKFku3PF8vUKZ3CEg83b+7B5ex+Khu2nKx7OnqCqckQjGsCkyB9NF8EwfUFJzBzbEb54nxZut5tB+lfLLjdHd3sU8YhWZq0YPKeT8RASUV0uSiUIgiDmhXlZqHj11Vejv7+/6r9t27YNiqJU/bdG0NERb9i+Z/u4Yb44VuobzRpoicj5YQ9VYRjLGrP6jEXThuouTAMmZoWFALraokhlSjBMG6rC8YWPvAvnnNLjv3ZBVxxjr4/4ghyQnUhNVTCWNXwvZU9wH65hLV2Vs94x13bvk9eswtcefO6wvf/RzlRjNbNlpt+vl47pHX9AwLLlcQuer9XO6Y5kGKls9bCcwwVdL2tD9c2NZq8PaP4aqb75Z15E9aOPPjrr1y5cuBAHDhxAe3s7ANmRPvfccyu2W7BgQZlw7+/vx4IFC2a8P5oRrM6xVF97XK9w1yiZNtri+qw+Y1hT3NEPed4wJsUTZ1K8drdFYDsO4mENJ3RGy/Zx8ZkLsWffKGxHQOETseCRkIa2uHR5SKWLUlgH3huT/jwTmOtEoigcuaKFtriOEzqjWLG0HUNjeQyO5v/iu9UCs/9+gyiKXEDquGmP0kt7+k8DOGNg7rgQh3ydqjD/uHnnUq1z+khD18vqUH1zo9nrA5q/RqpvbhzVM9X1WLt2LX7yk58AAPbt24eXXnoJq1evrtjusssuw5NPPonR0VE4joOf/vSneP/73z/f5RJHAWvPXTKlu8ZMuPSdi/x5Z+Ha2wFAJKT6729Zour7r1zWiQ+ctwScsbJYcFVhWHvuEqw9dwnCuuLOQk+8N4CyP88Erwsb0ZWyz/1XF5wE23Yq0gFn8/6Hm2hIKXP2OJKwSf87F1oiGlrjOhhj4Bzoag0jGQ9NK+pdVznCuiKDeQD3/HIQCakV52utc3pRZ7T2DgiCIIjDivKVr3zlK40u4uc//zk+9rGP4c9//jOef/55bNiwAatXr0Z7eztOP/10bNq0Cf/+7/+OTZs24Utf+hJWrFgBAPjmN7+JN954A6effjqSySQikQg+//nP4wc/+AFOO+003HzzzVUXP9ajUDAa8gg8Fgshnz+yj2rnwrFUX097FD1tEbw1mMV4TvpG/9V73zZr94+Tl7QBQuDNgSxMy0FYV3HOyZ3STcN9/7+5/B04eVGy5utPOC6OsUwJtiPQ3Rrx6+lpj2JhZwz7D2WQK8ro8vZEGBGdw7RkdzsWkTZu1Ra9eX7QgHSUCOsKVEVBSFOwsCNW9rnffkI74iEFg2MF5IsmrMD7MQAdiRCEEFWTFD1XEYUzLOyI4qKzjsdQqoBCDT9p7z2D9VVD4UBHIgxNVdDVFoXCZahNtd9RzhjOO7Ub11ywDLveGClLYNQUYPniVnQmQhhx/byDtWsKENZVqAqgqQo0lUFVFIRDCloiWs19hjSGWFhDyZzYl6owrDt/KdaeuwQDo3nkS/IpSEtUh2XL4/ue049DtmAiV7Sqvm9HIoSPXX4qzlzehYHRPIqGDe6G+CzoiFacr7XO6esvWY5X3hzFcFp+5hsuW1Hn2545dL2sDtU3N5q9PqD5a6T65kYsNrsE2qaw1Gsm6HFmdai+udHs9QHNXyPVNzeOxPwiXS+rQ/XNjWavD2j+Gqm+uXHMjn8QBEEQBEEQRLNDopogCIIgCIIg5giJaoIgCIIgCIKYIySqCYIgCIIgCGKOkKgmCIIgCIIgiDlCopogCIIgCIIg5giJaoIgCIIgCIKYI/MSU340wecrtq3J9j0dqL650ez1Ac1fI9XXXND1sjZU39xo9vqA5q+R6pt/KPyFIAiCIAiCIOYIjX8QBEEQBEEQxBwhUU0QBEEQBEEQc4RENUEQBEEQBEHMERLVBEEQBEEQBDFHSFQTBEEQBEEQxBwhUU0QBEEQBEEQc4RENUEQBEEQBEHMERLVBEEQBEEQBDFHSFQTBEEQBEEQxBwhUd2EbN++Haeccgo2bNjQ6FLK+Jd/+ResXbsW69atw/XXX4+XXnqp0SXhjTfewHXXXYfLLrsM1113Hfbt29foksoYGxvDxz/+cVx22WW44oorcMstt2B0dLTRZVXl3nvvxcknn4y9e/c2upQySqUSvvzlL+PSSy/FFVdcgX/+539udEllPP3007jqqqtw5ZVXYt26ddiyZUujS8Kdd96Jiy66qOJ4Nvvvy2yg6+X0afbjT9fLuUPXy5lx2K+VgmgqMpmMuOaaa8TNN98sfvCDHzS6nDJ+9atfCcMw/D9ffPHFDa5IiA9/+MPiscceE0II8dhjj4kPf/jDDa6onLGxMfH73//e//vXv/518fnPf76BFVVn165d4qabbhIXXniheOWVVxpdThlf/epXxb/+678Kx3GEEEIMDQ01uKIJHMcR55xzjv+d7d69W6xatUrYtt3Qup5//nnR399fcTyb/fdlptD1cmY0+/Gn6+XcoevlzDjc10rqVDcZX//613HTTTehra2t0aVUcOGFF0LTNADAqlWrMDAwAMdxGlbPyMgIXn75ZVx++eUAgMsvvxwvv/xyU3U2Wltbce655/p/X7VqFfr7+xtYUSWGYeD222/HV77ylUaXUkEul8Njjz2GT3/602CMAQA6OzsbXFU5nHNkMhkAQCaTQXd3Nzhv7KX1nHPOwYIFC8p+djT8vswUul5On6Ph+NP1cm7Q9XLmHO5rpXpEqiRmxa9//WtkMhmsXbsWzzzzTKPLqctDDz2ECy64oKG/DAcPHkRPTw8URQEAKIqC7u5uHDx4EO3t7Q2rqxaO4+BHP/oRLrrookaXUsY3v/lNrFu3DosWLWp0KRXs378fra2tuPfee7F9+3bEYjF8+tOfxjnnnNPo0gAAjDHcfffd+OQnP4loNIpcLocHHnig0WVV5Wj7fZkKul7OjKPt+NP1cubQ9fLwMJffFRLV88jVV19d86578+bN+MY3voH/+q//mueqJqhX37Zt2/wTbNOmTXj88cfx0EMPzWd5Rz1f/epXEY1GsX79+kaX4vOHP/wBu3btwmc+85lGl1IV27axf/9+nHrqqfjsZz+LP/3pT/jbv/1bPPHEE4jH440uD5Zl4bvf/S7uv/9+nH322XjxxRdx6623YtOmTYjFYo0u76iGrpd/2dD1cubQ9bLxkKieRx599NGa//bCCy9gaGgI1157LQC5YOPpp59GKpXCLbfc0vD6PJ544gn8x3/8Bx588MGGP1ZasGABDh06BNu2oSgKbNvG4OBgxaOcZuDOO+/Em2++ie985zsNHw0I8vzzz6O3txcXX3wxAGBgYAA33XQT/u3f/g3vec97GlydPMaqqvqP4c444wy0tbXhjTfewOmnn97g6oDdu3djcHAQZ599NgDg7LPPRiQSQW9vL1auXNng6so5mn5fALpeHm6OpuNP18vZQdfLw8OcfleOyOQ3MWc++9nPNuXCmwsvvFDs27ev0aX4rF+/vmwxwfr16xtcUSXf+MY3xPr160U+n290KVPSjAtvPvrRj4rf/va3QgghXn/9dfGud71LjI+PN7gqyeDgoDjzzDNFb2+vEEKI1157Tbzzne8UY2NjDa5MMvl4Hg2/L7OBrpfT42g4/nS9nBt0vZwdh+tayYQQ4sjrfmKmfO5zn8Npp53WVI++zjvvPGiaVjZT9OCDDzZ0kVBvby8+97nPIZ1OI5FI4M4778Tb3va2htUzmVdffRWXX345li5dinA4DABYtGgR7rvvvgZXVp2LLroI3/nOd7B8+fJGl+Kzf/9+fOELX0AqlYKqqrj11lvxvve9r9Fl+WzcuBHf+973/IVBf//3f49LLrmkoTXdcccd2LJlC4aHh9HW1obW1lZs2rSp6X9fZgtdL6dHsx9/ul7OHbpezozDfa0kUU0QBEEQBEEQc6R5hpUIgiAIgiAI4iiFRDVBEARBEARBzBES1QRBEARBEAQxR0hUEwRBEARBEMQcIVFNEARBEARBEHOERDVBEARBEARBzBES1QTRBKRSKXzqU5/CqlWrcOGFF+Lxxx9vdEkEQRBNCV0viWaFYsoJogm4/fbboWkatm7dit27d+MTn/gEVqxYgbe//e2NLo0gCKKpoOsl0axQ+AtBHCH+/Oc/44tf/CLefPNNrF69GpxznHDCCfiHf/iHsu3y+Tze9a534fHHH8eJJ54IAPinf/on9PT04DOf+UwjSicIgphX6HpJHAvQ+AdBHAEMw8Att9yCq6++Gs899xwuv/xyPPnkk1W33bdvHxRF8f8PAgBWrFiB1157bb7KJQiCaBh0vSSOFWj8gyCOAH/6059gWRb++q//GowxXHrppTj99NOrbpvP5xGPx8t+1tLSglwuNx+lEgRBNBS6XhLHCtSpJogjwODgIHp6esAY83+2YMECAMDHPvYxnHnmmTjzzDOxceNGRKNRZLPZstdns1nEYrF5rZkgCKIR0PWSOFagTjVBHAG6urpw6NAhCCH8/6M4ePAgFi9ejP/8z/8s2zafz8O2bezbtw9Lly4FAOzZswcnnXTSfJdNEAQx79D1kjhWoE41QRwBVq1aBUVRsGHDBliWhSeffBIvvfRS1W2j0SjWrFmDe+65B/l8Hi+++CKeeuopXHnllfNcNUEQxPxD10viWIHcPwjiCPHSSy/hS1/6Evr6+rB69Wo4joNTTjkFn/rUpyq2TaVS+MIXvoBt27ahtbUV//iP/4grrriiAVUTBEHMP3S9JI4FSFQTxDxx7bXX4vrrr8cHP/jBRpdCEATR1ND1kjgaofEPgjhCPPfccxgaGoJlWXj00UfxyiuvYPXq1Y0uiyAIoumg6yVxLEALFQniCPHGG2/g1ltvRaFQwKJFi3DPPfegu7u70WURBEE0HXS9JI4FaPyDIAiCIAiCIOYIjX8QBEEQBEEQxBwhUU0QBEEQBEEQc4RENUEQBEEQBEHMERLVBEEQBEEQBDFHSFQTBEEQBEEQxBwhUU0QBEEQBEEQc+T/B0+Op1K2WLo5AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "QMbPO518rD0Y",
        "outputId": "61f46e87-031d-4aeb-b0ae-0cf207d747d9"
      },
      "source": [
        "#A função row (linha) permite analisarmos melhor um parâmetro específico, assim podemos comparar os g em relação com o tratamento e tempo\n",
        "sns.lmplot(data = dados, x = 'g-0', y = 'g-8', line_kws= {'color' : 'red'}, col = 'tratamento', row = 'tempo')"
      ],
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7fea1729f510>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 122
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x1080 with 6 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "thitcTG-sD_0",
        "outputId": "d45bb2b7-8b5a-45ff-e38e-1295cc59e6b7"
      },
      "source": [
        "#A função .corr() calcula a correlação dos valores\n",
        "dados.loc[:, 'g-0' : 'g-771'].corr()"
      ],
      "execution_count": 123,
      "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>g-0</th>\n",
              "      <th>g-1</th>\n",
              "      <th>g-2</th>\n",
              "      <th>g-3</th>\n",
              "      <th>g-4</th>\n",
              "      <th>g-5</th>\n",
              "      <th>g-6</th>\n",
              "      <th>g-7</th>\n",
              "      <th>g-8</th>\n",
              "      <th>g-9</th>\n",
              "      <th>g-10</th>\n",
              "      <th>g-11</th>\n",
              "      <th>g-12</th>\n",
              "      <th>g-13</th>\n",
              "      <th>g-14</th>\n",
              "      <th>g-15</th>\n",
              "      <th>g-16</th>\n",
              "      <th>g-17</th>\n",
              "      <th>g-18</th>\n",
              "      <th>g-19</th>\n",
              "      <th>g-20</th>\n",
              "      <th>g-21</th>\n",
              "      <th>g-22</th>\n",
              "      <th>g-23</th>\n",
              "      <th>g-24</th>\n",
              "      <th>g-25</th>\n",
              "      <th>g-26</th>\n",
              "      <th>g-27</th>\n",
              "      <th>g-28</th>\n",
              "      <th>g-29</th>\n",
              "      <th>g-30</th>\n",
              "      <th>g-31</th>\n",
              "      <th>g-32</th>\n",
              "      <th>g-33</th>\n",
              "      <th>g-34</th>\n",
              "      <th>g-35</th>\n",
              "      <th>g-36</th>\n",
              "      <th>g-37</th>\n",
              "      <th>g-38</th>\n",
              "      <th>g-39</th>\n",
              "      <th>...</th>\n",
              "      <th>g-732</th>\n",
              "      <th>g-733</th>\n",
              "      <th>g-734</th>\n",
              "      <th>g-735</th>\n",
              "      <th>g-736</th>\n",
              "      <th>g-737</th>\n",
              "      <th>g-738</th>\n",
              "      <th>g-739</th>\n",
              "      <th>g-740</th>\n",
              "      <th>g-741</th>\n",
              "      <th>g-742</th>\n",
              "      <th>g-743</th>\n",
              "      <th>g-744</th>\n",
              "      <th>g-745</th>\n",
              "      <th>g-746</th>\n",
              "      <th>g-747</th>\n",
              "      <th>g-748</th>\n",
              "      <th>g-749</th>\n",
              "      <th>g-750</th>\n",
              "      <th>g-751</th>\n",
              "      <th>g-752</th>\n",
              "      <th>g-753</th>\n",
              "      <th>g-754</th>\n",
              "      <th>g-755</th>\n",
              "      <th>g-756</th>\n",
              "      <th>g-757</th>\n",
              "      <th>g-758</th>\n",
              "      <th>g-759</th>\n",
              "      <th>g-760</th>\n",
              "      <th>g-761</th>\n",
              "      <th>g-762</th>\n",
              "      <th>g-763</th>\n",
              "      <th>g-764</th>\n",
              "      <th>g-765</th>\n",
              "      <th>g-766</th>\n",
              "      <th>g-767</th>\n",
              "      <th>g-768</th>\n",
              "      <th>g-769</th>\n",
              "      <th>g-770</th>\n",
              "      <th>g-771</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>g-0</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.086032</td>\n",
              "      <td>0.176188</td>\n",
              "      <td>0.011266</td>\n",
              "      <td>0.403153</td>\n",
              "      <td>-0.165478</td>\n",
              "      <td>0.238348</td>\n",
              "      <td>-0.374451</td>\n",
              "      <td>-0.604212</td>\n",
              "      <td>-0.428779</td>\n",
              "      <td>-0.547606</td>\n",
              "      <td>0.219762</td>\n",
              "      <td>-0.199453</td>\n",
              "      <td>0.472223</td>\n",
              "      <td>-0.346179</td>\n",
              "      <td>-0.201323</td>\n",
              "      <td>-0.513026</td>\n",
              "      <td>-0.433536</td>\n",
              "      <td>-0.002073</td>\n",
              "      <td>-0.074622</td>\n",
              "      <td>-0.468599</td>\n",
              "      <td>0.052445</td>\n",
              "      <td>0.022269</td>\n",
              "      <td>-0.076298</td>\n",
              "      <td>-0.337522</td>\n",
              "      <td>-0.235191</td>\n",
              "      <td>-0.422814</td>\n",
              "      <td>0.148432</td>\n",
              "      <td>-0.471092</td>\n",
              "      <td>-0.296871</td>\n",
              "      <td>-0.528327</td>\n",
              "      <td>0.558136</td>\n",
              "      <td>-0.133229</td>\n",
              "      <td>-0.155987</td>\n",
              "      <td>-0.120247</td>\n",
              "      <td>0.327593</td>\n",
              "      <td>-0.147800</td>\n",
              "      <td>-0.591868</td>\n",
              "      <td>0.602623</td>\n",
              "      <td>0.450769</td>\n",
              "      <td>...</td>\n",
              "      <td>0.365095</td>\n",
              "      <td>-0.528006</td>\n",
              "      <td>0.295970</td>\n",
              "      <td>0.067108</td>\n",
              "      <td>-0.250243</td>\n",
              "      <td>-0.110665</td>\n",
              "      <td>-0.214344</td>\n",
              "      <td>-0.280492</td>\n",
              "      <td>-0.036098</td>\n",
              "      <td>-0.128288</td>\n",
              "      <td>-0.498922</td>\n",
              "      <td>-0.469595</td>\n",
              "      <td>0.673664</td>\n",
              "      <td>0.538050</td>\n",
              "      <td>0.297528</td>\n",
              "      <td>0.066530</td>\n",
              "      <td>0.240252</td>\n",
              "      <td>-0.170949</td>\n",
              "      <td>0.485924</td>\n",
              "      <td>-0.093815</td>\n",
              "      <td>0.397476</td>\n",
              "      <td>0.017923</td>\n",
              "      <td>0.321260</td>\n",
              "      <td>-0.131709</td>\n",
              "      <td>-0.133430</td>\n",
              "      <td>0.178220</td>\n",
              "      <td>0.201902</td>\n",
              "      <td>-0.205648</td>\n",
              "      <td>-0.676835</td>\n",
              "      <td>-0.433554</td>\n",
              "      <td>0.005085</td>\n",
              "      <td>-0.239410</td>\n",
              "      <td>0.548401</td>\n",
              "      <td>0.425222</td>\n",
              "      <td>-0.308095</td>\n",
              "      <td>-0.052622</td>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.514201</td>\n",
              "      <td>0.405908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-1</th>\n",
              "      <td>0.086032</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>-0.151590</td>\n",
              "      <td>-0.122541</td>\n",
              "      <td>0.144537</td>\n",
              "      <td>-0.009973</td>\n",
              "      <td>-0.047558</td>\n",
              "      <td>-0.009051</td>\n",
              "      <td>0.161274</td>\n",
              "      <td>0.037178</td>\n",
              "      <td>-0.009256</td>\n",
              "      <td>0.002632</td>\n",
              "      <td>-0.070193</td>\n",
              "      <td>-0.063414</td>\n",
              "      <td>-0.000944</td>\n",
              "      <td>-0.023748</td>\n",
              "      <td>-0.034714</td>\n",
              "      <td>-0.131031</td>\n",
              "      <td>0.196596</td>\n",
              "      <td>-0.061441</td>\n",
              "      <td>0.090620</td>\n",
              "      <td>-0.004299</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.019435</td>\n",
              "      <td>0.015661</td>\n",
              "      <td>-0.098907</td>\n",
              "      <td>-0.091071</td>\n",
              "      <td>-0.053331</td>\n",
              "      <td>-0.049514</td>\n",
              "      <td>0.187382</td>\n",
              "      <td>-0.091232</td>\n",
              "      <td>0.045417</td>\n",
              "      <td>0.044373</td>\n",
              "      <td>-0.077671</td>\n",
              "      <td>-0.005265</td>\n",
              "      <td>-0.042213</td>\n",
              "      <td>0.050546</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.015556</td>\n",
              "      <td>-0.017184</td>\n",
              "      <td>0.043104</td>\n",
              "      <td>-0.189662</td>\n",
              "      <td>-0.050194</td>\n",
              "      <td>-0.007878</td>\n",
              "      <td>-0.083539</td>\n",
              "      <td>-0.042175</td>\n",
              "      <td>0.014307</td>\n",
              "      <td>-0.134166</td>\n",
              "      <td>-0.026985</td>\n",
              "      <td>0.088382</td>\n",
              "      <td>-0.077453</td>\n",
              "      <td>0.015545</td>\n",
              "      <td>-0.027527</td>\n",
              "      <td>-0.071078</td>\n",
              "      <td>-0.095445</td>\n",
              "      <td>0.049612</td>\n",
              "      <td>-0.040518</td>\n",
              "      <td>-0.074277</td>\n",
              "      <td>-0.022356</td>\n",
              "      <td>0.125763</td>\n",
              "      <td>-0.082779</td>\n",
              "      <td>0.020292</td>\n",
              "      <td>-0.023171</td>\n",
              "      <td>-0.207192</td>\n",
              "      <td>-0.066570</td>\n",
              "      <td>-0.057007</td>\n",
              "      <td>0.002062</td>\n",
              "      <td>0.029795</td>\n",
              "      <td>-0.205998</td>\n",
              "      <td>0.060051</td>\n",
              "      <td>0.115071</td>\n",
              "      <td>0.160140</td>\n",
              "      <td>0.015098</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.032233</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-2</th>\n",
              "      <td>0.176188</td>\n",
              "      <td>-0.054518</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>0.018516</td>\n",
              "      <td>0.015190</td>\n",
              "      <td>-0.144205</td>\n",
              "      <td>-0.128029</td>\n",
              "      <td>-0.081332</td>\n",
              "      <td>-0.105050</td>\n",
              "      <td>0.011198</td>\n",
              "      <td>-0.063501</td>\n",
              "      <td>0.082011</td>\n",
              "      <td>-0.082204</td>\n",
              "      <td>-0.059607</td>\n",
              "      <td>-0.137811</td>\n",
              "      <td>-0.085491</td>\n",
              "      <td>0.053335</td>\n",
              "      <td>0.028813</td>\n",
              "      <td>-0.061160</td>\n",
              "      <td>-0.129131</td>\n",
              "      <td>-0.007426</td>\n",
              "      <td>-0.034230</td>\n",
              "      <td>-0.128312</td>\n",
              "      <td>-0.067363</td>\n",
              "      <td>-0.126554</td>\n",
              "      <td>0.036984</td>\n",
              "      <td>-0.129481</td>\n",
              "      <td>-0.017941</td>\n",
              "      <td>-0.152288</td>\n",
              "      <td>0.172191</td>\n",
              "      <td>-0.100086</td>\n",
              "      <td>-0.033010</td>\n",
              "      <td>-0.015481</td>\n",
              "      <td>0.001098</td>\n",
              "      <td>-0.020374</td>\n",
              "      <td>-0.157977</td>\n",
              "      <td>0.169464</td>\n",
              "      <td>0.144449</td>\n",
              "      <td>...</td>\n",
              "      <td>0.089525</td>\n",
              "      <td>-0.140916</td>\n",
              "      <td>0.008587</td>\n",
              "      <td>0.042106</td>\n",
              "      <td>-0.018846</td>\n",
              "      <td>-0.008093</td>\n",
              "      <td>-0.074404</td>\n",
              "      <td>-0.080120</td>\n",
              "      <td>-0.020085</td>\n",
              "      <td>-0.028099</td>\n",
              "      <td>-0.098775</td>\n",
              "      <td>-0.113000</td>\n",
              "      <td>0.175916</td>\n",
              "      <td>0.119166</td>\n",
              "      <td>0.071051</td>\n",
              "      <td>0.025358</td>\n",
              "      <td>0.078971</td>\n",
              "      <td>-0.086326</td>\n",
              "      <td>0.149456</td>\n",
              "      <td>0.033432</td>\n",
              "      <td>0.124239</td>\n",
              "      <td>-0.006327</td>\n",
              "      <td>0.120148</td>\n",
              "      <td>-0.041162</td>\n",
              "      <td>-0.030040</td>\n",
              "      <td>0.048549</td>\n",
              "      <td>0.096369</td>\n",
              "      <td>0.000494</td>\n",
              "      <td>-0.172627</td>\n",
              "      <td>-0.130200</td>\n",
              "      <td>0.090115</td>\n",
              "      <td>-0.055655</td>\n",
              "      <td>0.138085</td>\n",
              "      <td>0.061574</td>\n",
              "      <td>-0.093631</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>0.103985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-3</th>\n",
              "      <td>0.011266</td>\n",
              "      <td>-0.027855</td>\n",
              "      <td>0.042633</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>0.042231</td>\n",
              "      <td>-0.043177</td>\n",
              "      <td>-0.175692</td>\n",
              "      <td>-0.086167</td>\n",
              "      <td>-0.014052</td>\n",
              "      <td>-0.074101</td>\n",
              "      <td>0.181024</td>\n",
              "      <td>0.030539</td>\n",
              "      <td>0.192727</td>\n",
              "      <td>0.128792</td>\n",
              "      <td>-0.045688</td>\n",
              "      <td>0.033974</td>\n",
              "      <td>-0.070920</td>\n",
              "      <td>0.237669</td>\n",
              "      <td>0.112392</td>\n",
              "      <td>0.027867</td>\n",
              "      <td>-0.167263</td>\n",
              "      <td>0.197013</td>\n",
              "      <td>-0.049480</td>\n",
              "      <td>-0.113336</td>\n",
              "      <td>0.175615</td>\n",
              "      <td>0.111355</td>\n",
              "      <td>0.007168</td>\n",
              "      <td>-0.022381</td>\n",
              "      <td>-0.128269</td>\n",
              "      <td>-0.042827</td>\n",
              "      <td>0.098416</td>\n",
              "      <td>-0.091962</td>\n",
              "      <td>-0.083806</td>\n",
              "      <td>0.184985</td>\n",
              "      <td>-0.070933</td>\n",
              "      <td>-0.317859</td>\n",
              "      <td>-0.228039</td>\n",
              "      <td>0.084346</td>\n",
              "      <td>0.054827</td>\n",
              "      <td>...</td>\n",
              "      <td>0.039519</td>\n",
              "      <td>0.000851</td>\n",
              "      <td>0.011655</td>\n",
              "      <td>-0.116724</td>\n",
              "      <td>0.304819</td>\n",
              "      <td>-0.087159</td>\n",
              "      <td>-0.134135</td>\n",
              "      <td>-0.031211</td>\n",
              "      <td>0.174116</td>\n",
              "      <td>0.060289</td>\n",
              "      <td>-0.119276</td>\n",
              "      <td>-0.140391</td>\n",
              "      <td>0.110547</td>\n",
              "      <td>0.145925</td>\n",
              "      <td>0.155011</td>\n",
              "      <td>0.049182</td>\n",
              "      <td>-0.007754</td>\n",
              "      <td>-0.128488</td>\n",
              "      <td>0.078139</td>\n",
              "      <td>0.012422</td>\n",
              "      <td>0.040728</td>\n",
              "      <td>0.164467</td>\n",
              "      <td>0.171886</td>\n",
              "      <td>-0.069777</td>\n",
              "      <td>0.066560</td>\n",
              "      <td>0.102111</td>\n",
              "      <td>-0.036922</td>\n",
              "      <td>0.111994</td>\n",
              "      <td>-0.133740</td>\n",
              "      <td>-0.226928</td>\n",
              "      <td>0.075982</td>\n",
              "      <td>0.178422</td>\n",
              "      <td>0.016467</td>\n",
              "      <td>-0.089317</td>\n",
              "      <td>-0.166426</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>0.058219</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-4</th>\n",
              "      <td>0.403153</td>\n",
              "      <td>0.193647</td>\n",
              "      <td>0.013968</td>\n",
              "      <td>-0.033039</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.057449</td>\n",
              "      <td>0.206405</td>\n",
              "      <td>-0.032748</td>\n",
              "      <td>-0.474828</td>\n",
              "      <td>-0.274167</td>\n",
              "      <td>-0.458021</td>\n",
              "      <td>0.116467</td>\n",
              "      <td>-0.207078</td>\n",
              "      <td>0.210440</td>\n",
              "      <td>-0.307280</td>\n",
              "      <td>0.019531</td>\n",
              "      <td>-0.275700</td>\n",
              "      <td>-0.422889</td>\n",
              "      <td>-0.012207</td>\n",
              "      <td>-0.088152</td>\n",
              "      <td>-0.311798</td>\n",
              "      <td>0.286106</td>\n",
              "      <td>-0.055368</td>\n",
              "      <td>-0.113396</td>\n",
              "      <td>-0.120743</td>\n",
              "      <td>-0.233682</td>\n",
              "      <td>-0.340708</td>\n",
              "      <td>0.070292</td>\n",
              "      <td>-0.360274</td>\n",
              "      <td>-0.225461</td>\n",
              "      <td>-0.402256</td>\n",
              "      <td>0.324362</td>\n",
              "      <td>0.091731</td>\n",
              "      <td>-0.052787</td>\n",
              "      <td>-0.073490</td>\n",
              "      <td>0.195062</td>\n",
              "      <td>-0.124394</td>\n",
              "      <td>-0.277002</td>\n",
              "      <td>0.285256</td>\n",
              "      <td>0.300517</td>\n",
              "      <td>...</td>\n",
              "      <td>0.215930</td>\n",
              "      <td>-0.292602</td>\n",
              "      <td>-0.008241</td>\n",
              "      <td>-0.005070</td>\n",
              "      <td>-0.284391</td>\n",
              "      <td>-0.116918</td>\n",
              "      <td>-0.252399</td>\n",
              "      <td>-0.250280</td>\n",
              "      <td>0.000141</td>\n",
              "      <td>-0.172896</td>\n",
              "      <td>-0.324769</td>\n",
              "      <td>-0.291644</td>\n",
              "      <td>0.302912</td>\n",
              "      <td>0.222951</td>\n",
              "      <td>0.144028</td>\n",
              "      <td>-0.020950</td>\n",
              "      <td>0.129354</td>\n",
              "      <td>-0.141319</td>\n",
              "      <td>0.215713</td>\n",
              "      <td>-0.060261</td>\n",
              "      <td>0.240649</td>\n",
              "      <td>-0.250950</td>\n",
              "      <td>0.144547</td>\n",
              "      <td>-0.045769</td>\n",
              "      <td>-0.083932</td>\n",
              "      <td>-0.100498</td>\n",
              "      <td>0.118725</td>\n",
              "      <td>-0.257704</td>\n",
              "      <td>-0.386764</td>\n",
              "      <td>-0.172222</td>\n",
              "      <td>-0.023752</td>\n",
              "      <td>-0.164868</td>\n",
              "      <td>0.404440</td>\n",
              "      <td>0.317500</td>\n",
              "      <td>-0.225094</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.250713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-767</th>\n",
              "      <td>-0.052622</td>\n",
              "      <td>-0.003378</td>\n",
              "      <td>-0.053149</td>\n",
              "      <td>-0.179370</td>\n",
              "      <td>0.124425</td>\n",
              "      <td>-0.081016</td>\n",
              "      <td>-0.000886</td>\n",
              "      <td>0.137336</td>\n",
              "      <td>-0.101191</td>\n",
              "      <td>-0.013157</td>\n",
              "      <td>-0.016431</td>\n",
              "      <td>-0.009570</td>\n",
              "      <td>-0.102954</td>\n",
              "      <td>-0.066698</td>\n",
              "      <td>-0.093822</td>\n",
              "      <td>0.244340</td>\n",
              "      <td>-0.069415</td>\n",
              "      <td>-0.094064</td>\n",
              "      <td>-0.127133</td>\n",
              "      <td>-0.080124</td>\n",
              "      <td>0.043800</td>\n",
              "      <td>0.077647</td>\n",
              "      <td>-0.163991</td>\n",
              "      <td>-0.007126</td>\n",
              "      <td>-0.059084</td>\n",
              "      <td>-0.105259</td>\n",
              "      <td>-0.023880</td>\n",
              "      <td>0.128335</td>\n",
              "      <td>-0.119971</td>\n",
              "      <td>-0.107446</td>\n",
              "      <td>-0.035556</td>\n",
              "      <td>0.094170</td>\n",
              "      <td>0.158429</td>\n",
              "      <td>0.108885</td>\n",
              "      <td>-0.077054</td>\n",
              "      <td>-0.067268</td>\n",
              "      <td>0.334189</td>\n",
              "      <td>0.217292</td>\n",
              "      <td>0.049036</td>\n",
              "      <td>-0.031135</td>\n",
              "      <td>...</td>\n",
              "      <td>0.052898</td>\n",
              "      <td>0.121333</td>\n",
              "      <td>-0.038647</td>\n",
              "      <td>0.140140</td>\n",
              "      <td>-0.246716</td>\n",
              "      <td>0.000084</td>\n",
              "      <td>-0.021733</td>\n",
              "      <td>-0.003739</td>\n",
              "      <td>-0.010499</td>\n",
              "      <td>-0.045364</td>\n",
              "      <td>0.103892</td>\n",
              "      <td>0.056790</td>\n",
              "      <td>-0.046818</td>\n",
              "      <td>-0.082454</td>\n",
              "      <td>-0.050249</td>\n",
              "      <td>0.043764</td>\n",
              "      <td>0.028057</td>\n",
              "      <td>0.107099</td>\n",
              "      <td>0.006368</td>\n",
              "      <td>0.071568</td>\n",
              "      <td>-0.041222</td>\n",
              "      <td>-0.271532</td>\n",
              "      <td>-0.134224</td>\n",
              "      <td>0.100008</td>\n",
              "      <td>0.023745</td>\n",
              "      <td>-0.179493</td>\n",
              "      <td>0.113520</td>\n",
              "      <td>-0.331936</td>\n",
              "      <td>-0.050898</td>\n",
              "      <td>0.190015</td>\n",
              "      <td>-0.010391</td>\n",
              "      <td>-0.180252</td>\n",
              "      <td>0.003976</td>\n",
              "      <td>-0.027425</td>\n",
              "      <td>0.153722</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.001136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-768</th>\n",
              "      <td>0.300241</td>\n",
              "      <td>-0.030756</td>\n",
              "      <td>0.115415</td>\n",
              "      <td>0.028452</td>\n",
              "      <td>0.115579</td>\n",
              "      <td>-0.139000</td>\n",
              "      <td>-0.005791</td>\n",
              "      <td>-0.419437</td>\n",
              "      <td>-0.209968</td>\n",
              "      <td>-0.291836</td>\n",
              "      <td>-0.279889</td>\n",
              "      <td>0.208202</td>\n",
              "      <td>-0.166361</td>\n",
              "      <td>0.243048</td>\n",
              "      <td>-0.241234</td>\n",
              "      <td>-0.042026</td>\n",
              "      <td>-0.363465</td>\n",
              "      <td>-0.247474</td>\n",
              "      <td>0.078093</td>\n",
              "      <td>-0.055035</td>\n",
              "      <td>-0.155576</td>\n",
              "      <td>-0.164930</td>\n",
              "      <td>-0.086306</td>\n",
              "      <td>-0.125517</td>\n",
              "      <td>-0.286908</td>\n",
              "      <td>-0.139057</td>\n",
              "      <td>-0.341518</td>\n",
              "      <td>0.102919</td>\n",
              "      <td>-0.257007</td>\n",
              "      <td>-0.141094</td>\n",
              "      <td>-0.372977</td>\n",
              "      <td>0.369303</td>\n",
              "      <td>-0.365516</td>\n",
              "      <td>0.058365</td>\n",
              "      <td>-0.062415</td>\n",
              "      <td>0.076001</td>\n",
              "      <td>-0.208400</td>\n",
              "      <td>-0.450344</td>\n",
              "      <td>0.463732</td>\n",
              "      <td>0.451185</td>\n",
              "      <td>...</td>\n",
              "      <td>0.234354</td>\n",
              "      <td>-0.463277</td>\n",
              "      <td>0.073003</td>\n",
              "      <td>0.006763</td>\n",
              "      <td>-0.143979</td>\n",
              "      <td>-0.034694</td>\n",
              "      <td>-0.171279</td>\n",
              "      <td>-0.200669</td>\n",
              "      <td>-0.031907</td>\n",
              "      <td>-0.057287</td>\n",
              "      <td>-0.288026</td>\n",
              "      <td>-0.177108</td>\n",
              "      <td>0.459642</td>\n",
              "      <td>0.291729</td>\n",
              "      <td>0.202785</td>\n",
              "      <td>-0.028499</td>\n",
              "      <td>0.130907</td>\n",
              "      <td>-0.233472</td>\n",
              "      <td>0.455238</td>\n",
              "      <td>0.141002</td>\n",
              "      <td>0.222363</td>\n",
              "      <td>0.074620</td>\n",
              "      <td>0.087545</td>\n",
              "      <td>-0.203831</td>\n",
              "      <td>-0.095647</td>\n",
              "      <td>0.048008</td>\n",
              "      <td>0.253031</td>\n",
              "      <td>0.087674</td>\n",
              "      <td>-0.403336</td>\n",
              "      <td>-0.394520</td>\n",
              "      <td>0.077292</td>\n",
              "      <td>0.000048</td>\n",
              "      <td>0.403211</td>\n",
              "      <td>0.241509</td>\n",
              "      <td>-0.250512</td>\n",
              "      <td>-0.048393</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.351651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-769</th>\n",
              "      <td>-0.127375</td>\n",
              "      <td>-0.006866</td>\n",
              "      <td>0.014489</td>\n",
              "      <td>-0.206077</td>\n",
              "      <td>-0.172727</td>\n",
              "      <td>-0.068537</td>\n",
              "      <td>-0.278587</td>\n",
              "      <td>-0.082554</td>\n",
              "      <td>0.268571</td>\n",
              "      <td>0.037013</td>\n",
              "      <td>0.184833</td>\n",
              "      <td>0.029409</td>\n",
              "      <td>0.052328</td>\n",
              "      <td>-0.137248</td>\n",
              "      <td>-0.016769</td>\n",
              "      <td>0.006056</td>\n",
              "      <td>-0.010654</td>\n",
              "      <td>0.164345</td>\n",
              "      <td>-0.161975</td>\n",
              "      <td>-0.096549</td>\n",
              "      <td>0.043702</td>\n",
              "      <td>-0.160018</td>\n",
              "      <td>-0.104794</td>\n",
              "      <td>0.011050</td>\n",
              "      <td>-0.057823</td>\n",
              "      <td>-0.046833</td>\n",
              "      <td>0.015717</td>\n",
              "      <td>0.061872</td>\n",
              "      <td>0.107534</td>\n",
              "      <td>-0.032060</td>\n",
              "      <td>0.086102</td>\n",
              "      <td>-0.108052</td>\n",
              "      <td>-0.154845</td>\n",
              "      <td>0.120802</td>\n",
              "      <td>0.040181</td>\n",
              "      <td>-0.082272</td>\n",
              "      <td>0.087573</td>\n",
              "      <td>0.078753</td>\n",
              "      <td>-0.032600</td>\n",
              "      <td>-0.061331</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.049599</td>\n",
              "      <td>0.017176</td>\n",
              "      <td>-0.005283</td>\n",
              "      <td>0.017348</td>\n",
              "      <td>-0.014663</td>\n",
              "      <td>0.101831</td>\n",
              "      <td>0.063218</td>\n",
              "      <td>0.151088</td>\n",
              "      <td>-0.116813</td>\n",
              "      <td>0.060308</td>\n",
              "      <td>0.087342</td>\n",
              "      <td>0.214832</td>\n",
              "      <td>-0.118092</td>\n",
              "      <td>-0.038540</td>\n",
              "      <td>-0.095170</td>\n",
              "      <td>-0.031114</td>\n",
              "      <td>-0.064939</td>\n",
              "      <td>0.044082</td>\n",
              "      <td>0.009613</td>\n",
              "      <td>0.146667</td>\n",
              "      <td>-0.059447</td>\n",
              "      <td>0.087822</td>\n",
              "      <td>-0.160610</td>\n",
              "      <td>0.041946</td>\n",
              "      <td>-0.001705</td>\n",
              "      <td>-0.116414</td>\n",
              "      <td>-0.033614</td>\n",
              "      <td>-0.029173</td>\n",
              "      <td>0.106610</td>\n",
              "      <td>-0.002356</td>\n",
              "      <td>0.020662</td>\n",
              "      <td>0.071082</td>\n",
              "      <td>0.013235</td>\n",
              "      <td>0.021152</td>\n",
              "      <td>0.151940</td>\n",
              "      <td>0.065450</td>\n",
              "      <td>0.079364</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>-0.083713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-770</th>\n",
              "      <td>-0.514201</td>\n",
              "      <td>-0.095108</td>\n",
              "      <td>-0.078661</td>\n",
              "      <td>-0.002142</td>\n",
              "      <td>-0.363673</td>\n",
              "      <td>0.144631</td>\n",
              "      <td>-0.143428</td>\n",
              "      <td>0.402451</td>\n",
              "      <td>0.441011</td>\n",
              "      <td>0.415967</td>\n",
              "      <td>0.550963</td>\n",
              "      <td>-0.238657</td>\n",
              "      <td>0.230249</td>\n",
              "      <td>-0.406279</td>\n",
              "      <td>0.386103</td>\n",
              "      <td>0.102904</td>\n",
              "      <td>0.406267</td>\n",
              "      <td>0.312653</td>\n",
              "      <td>-0.034036</td>\n",
              "      <td>0.091171</td>\n",
              "      <td>0.263679</td>\n",
              "      <td>-0.092925</td>\n",
              "      <td>0.008841</td>\n",
              "      <td>0.085105</td>\n",
              "      <td>0.370410</td>\n",
              "      <td>0.246689</td>\n",
              "      <td>0.550753</td>\n",
              "      <td>-0.190110</td>\n",
              "      <td>0.393393</td>\n",
              "      <td>0.295798</td>\n",
              "      <td>0.596868</td>\n",
              "      <td>-0.526634</td>\n",
              "      <td>0.231931</td>\n",
              "      <td>-0.039510</td>\n",
              "      <td>0.260259</td>\n",
              "      <td>-0.366389</td>\n",
              "      <td>0.228281</td>\n",
              "      <td>0.571426</td>\n",
              "      <td>-0.592994</td>\n",
              "      <td>-0.429418</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.370370</td>\n",
              "      <td>0.514880</td>\n",
              "      <td>-0.155936</td>\n",
              "      <td>-0.010076</td>\n",
              "      <td>0.375338</td>\n",
              "      <td>0.014833</td>\n",
              "      <td>0.343938</td>\n",
              "      <td>0.369822</td>\n",
              "      <td>0.077286</td>\n",
              "      <td>0.246165</td>\n",
              "      <td>0.439648</td>\n",
              "      <td>0.367189</td>\n",
              "      <td>-0.618890</td>\n",
              "      <td>-0.378256</td>\n",
              "      <td>-0.264342</td>\n",
              "      <td>0.081357</td>\n",
              "      <td>-0.240273</td>\n",
              "      <td>0.285457</td>\n",
              "      <td>-0.468321</td>\n",
              "      <td>0.077384</td>\n",
              "      <td>-0.270256</td>\n",
              "      <td>-0.015109</td>\n",
              "      <td>-0.077811</td>\n",
              "      <td>0.206666</td>\n",
              "      <td>0.238529</td>\n",
              "      <td>-0.184568</td>\n",
              "      <td>-0.126731</td>\n",
              "      <td>0.034281</td>\n",
              "      <td>0.601289</td>\n",
              "      <td>0.488580</td>\n",
              "      <td>0.014331</td>\n",
              "      <td>-0.010849</td>\n",
              "      <td>-0.498222</td>\n",
              "      <td>-0.489116</td>\n",
              "      <td>0.284882</td>\n",
              "      <td>0.008603</td>\n",
              "      <td>-0.382607</td>\n",
              "      <td>0.135853</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.425063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>g-771</th>\n",
              "      <td>0.405908</td>\n",
              "      <td>-0.032233</td>\n",
              "      <td>0.103985</td>\n",
              "      <td>0.058219</td>\n",
              "      <td>0.250713</td>\n",
              "      <td>-0.093237</td>\n",
              "      <td>0.075019</td>\n",
              "      <td>-0.441309</td>\n",
              "      <td>-0.450561</td>\n",
              "      <td>-0.295420</td>\n",
              "      <td>-0.432786</td>\n",
              "      <td>0.144358</td>\n",
              "      <td>-0.229938</td>\n",
              "      <td>0.404019</td>\n",
              "      <td>-0.298917</td>\n",
              "      <td>0.004588</td>\n",
              "      <td>-0.385330</td>\n",
              "      <td>-0.372534</td>\n",
              "      <td>0.073349</td>\n",
              "      <td>-0.110113</td>\n",
              "      <td>-0.288734</td>\n",
              "      <td>-0.127502</td>\n",
              "      <td>0.003787</td>\n",
              "      <td>-0.162129</td>\n",
              "      <td>-0.302231</td>\n",
              "      <td>-0.223294</td>\n",
              "      <td>-0.362299</td>\n",
              "      <td>0.158596</td>\n",
              "      <td>-0.392234</td>\n",
              "      <td>-0.138101</td>\n",
              "      <td>-0.419937</td>\n",
              "      <td>0.447443</td>\n",
              "      <td>-0.303933</td>\n",
              "      <td>0.048098</td>\n",
              "      <td>-0.040134</td>\n",
              "      <td>0.175169</td>\n",
              "      <td>-0.187705</td>\n",
              "      <td>-0.481214</td>\n",
              "      <td>0.540181</td>\n",
              "      <td>0.453666</td>\n",
              "      <td>...</td>\n",
              "      <td>0.269242</td>\n",
              "      <td>-0.542694</td>\n",
              "      <td>0.130851</td>\n",
              "      <td>0.026660</td>\n",
              "      <td>-0.232375</td>\n",
              "      <td>-0.079203</td>\n",
              "      <td>-0.154633</td>\n",
              "      <td>-0.212674</td>\n",
              "      <td>-0.012768</td>\n",
              "      <td>-0.035397</td>\n",
              "      <td>-0.358442</td>\n",
              "      <td>-0.379846</td>\n",
              "      <td>0.561525</td>\n",
              "      <td>0.327231</td>\n",
              "      <td>0.283659</td>\n",
              "      <td>0.083172</td>\n",
              "      <td>0.193545</td>\n",
              "      <td>-0.195285</td>\n",
              "      <td>0.459616</td>\n",
              "      <td>0.099866</td>\n",
              "      <td>0.318208</td>\n",
              "      <td>-0.046797</td>\n",
              "      <td>0.190287</td>\n",
              "      <td>-0.175624</td>\n",
              "      <td>-0.081839</td>\n",
              "      <td>0.175881</td>\n",
              "      <td>0.237110</td>\n",
              "      <td>-0.035015</td>\n",
              "      <td>-0.551324</td>\n",
              "      <td>-0.341807</td>\n",
              "      <td>0.076596</td>\n",
              "      <td>-0.085319</td>\n",
              "      <td>0.426342</td>\n",
              "      <td>0.337007</td>\n",
              "      <td>-0.249602</td>\n",
              "      <td>-0.001136</td>\n",
              "      <td>0.351651</td>\n",
              "      <td>-0.083713</td>\n",
              "      <td>-0.425063</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>772 rows × 772 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            g-0       g-1       g-2  ...     g-769     g-770     g-771\n",
              "g-0    1.000000  0.086032  0.176188  ... -0.127375 -0.514201  0.405908\n",
              "g-1    0.086032  1.000000 -0.054518  ... -0.006866 -0.095108 -0.032233\n",
              "g-2    0.176188 -0.054518  1.000000  ...  0.014489 -0.078661  0.103985\n",
              "g-3    0.011266 -0.027855  0.042633  ... -0.206077 -0.002142  0.058219\n",
              "g-4    0.403153  0.193647  0.013968  ... -0.172727 -0.363673  0.250713\n",
              "...         ...       ...       ...  ...       ...       ...       ...\n",
              "g-767 -0.052622 -0.003378 -0.053149  ...  0.065450  0.008603 -0.001136\n",
              "g-768  0.300241 -0.030756  0.115415  ...  0.079364 -0.382607  0.351651\n",
              "g-769 -0.127375 -0.006866  0.014489  ...  1.000000  0.135853 -0.083713\n",
              "g-770 -0.514201 -0.095108 -0.078661  ...  0.135853  1.000000 -0.425063\n",
              "g-771  0.405908 -0.032233  0.103985  ... -0.083713 -0.425063  1.000000\n",
              "\n",
              "[772 rows x 772 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "id": "eOAV73O73Cx-",
        "outputId": "2a6fdd5a-1c24-41b2-d1f4-1546ac7c7e40"
      },
      "source": [
        "#Importando o numpy\n",
        "import numpy as np\n",
        "#Importando o matplotlib\n",
        "import matplotlib.pyplot as plt\n",
        "#Copiamos o código do site https://seaborn.pydata.org/examples/many_pairwise_correlations.html para elaborarmos um mapa de calor\n",
        "#Compute the correlation matrix (Calcule a matriz de correlação)\n",
        "corr = dados.loc[:, 'g-0' : 'g-50'].corr()\n",
        "#Generate a mask for the upper triangle (Gere uma máscara para o triângulo superior)\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "#Set up the matplotlib figure (Configure a figura matplotlib)\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "#Generate a custom diverging colormap (Gerar um mapa de cores divergentes personalizado)\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "#Draw the heatmap with the mask and correct aspect ratio (Desenhe o mapa de calor com a máscara e a proporção correta)\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0, square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe9ee5598d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 124
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "id": "KvD-Pf3v3Y6m",
        "outputId": "35542aed-25c6-4dd8-ee57-3b845f13d97a"
      },
      "source": [
        "#Compute the correlation matrix (Calcule a matriz de correlação)\n",
        "corr = dados.loc[:, 'g-0' : 'g-50'].corr()\n",
        "#Generate a mask for the upper triangle (Gere uma máscara para o triângulo superior)\n",
        "mask = np.triu(np.ones_like(corr, dtype=bool))\n",
        "#Set up the matplotlib figure (Configure a figura matplotlib)\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "#Generate a custom diverging colormap (Gerar um mapa de cores divergentes personalizado)\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "#Draw the heatmap with the mask and correct aspect ratio (Desenhe o mapa de calor com a máscara e a proporção correta)\n",
        "#Retiramos o parâmetro vmax=.3 para ele não definir o 0.3 como valor máximo\n",
        "sns.heatmap(corr, mask=mask, cmap=cmap, center=0, square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fea17322bd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 125
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PItXtOT67MRS"
      },
      "source": [
        "#Calculando a matriz de correlação dos tipos celulares\n",
        "corr_celular = dados.loc[:, 'c-0' : 'c-50'].corr() "
      ],
      "execution_count": 126,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 572
        },
        "id": "S6IpLajQ7Sy4",
        "outputId": "04316aa0-f944-4194-9abf-9a61b542f985"
      },
      "source": [
        "#Generate a mask for the upper triangle (Gere uma máscara para o triângulo superior)\n",
        "mask = np.triu(np.ones_like(corr_celular, dtype=bool))\n",
        "#Set up the matplotlib figure (Configure a figura matplotlib)\n",
        "f, ax = plt.subplots(figsize=(11, 9))\n",
        "#Generate a custom diverging colormap (Gerar um mapa de cores divergentes personalizado)\n",
        "cmap = sns.diverging_palette(230, 20, as_cmap=True)\n",
        "#Draw the heatmap with the mask and correct aspect ratio (Desenhe o mapa de calor com a máscara e a proporção correta)\n",
        "#Tirando o parâmetro vmax=.3 ele retira o 0.3 como valor máximo\n",
        "sns.heatmap(corr_celular, mask=mask, cmap=cmap, center=0, square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": 127,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fea17266750>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 127
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-sStRsCGYxPo"
      },
      "source": [
        "## **Desafios**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p49atRS8Yyl2"
      },
      "source": [
        "***Desafio 01: Criar tabelas de frequência com o pandas.groupby().***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        },
        "id": "pvX2lNKN8CPs",
        "outputId": "27a5dd89-c68b-4f8b-eac6-de4e69bf8bee"
      },
      "source": [
        "#A função groupby permite agruparmos informações\n",
        "#Aqui utilizamos as informações de tratamento, dose e tempo\n",
        "dados.groupby(['tratamento', 'dose'] )['tempo'].value_counts().unstack()"
      ],
      "execution_count": 128,
      "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>tempo</th>\n",
              "      <th>24</th>\n",
              "      <th>48</th>\n",
              "      <th>72</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tratamento</th>\n",
              "      <th>dose</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">com_controle</th>\n",
              "      <th>D1</th>\n",
              "      <td>301</td>\n",
              "      <td>343</td>\n",
              "      <td>307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>305</td>\n",
              "      <td>305</td>\n",
              "      <td>305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">com_droga</th>\n",
              "      <th>D1</th>\n",
              "      <td>3585</td>\n",
              "      <td>4011</td>\n",
              "      <td>3600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>3581</td>\n",
              "      <td>3591</td>\n",
              "      <td>3580</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tempo                24    48    72\n",
              "tratamento   dose                  \n",
              "com_controle D1     301   343   307\n",
              "             D2     305   305   305\n",
              "com_droga    D1    3585  4011  3600\n",
              "             D2    3581  3591  3580"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 128
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_9jfGoRcY4Bp"
      },
      "source": [
        "***Desafio 02: Normalizar o crosstab pela coluna.***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        },
        "id": "9EeLdORHY8jw",
        "outputId": "b60afd24-f723-4a79-eeb5-caaf36abd10f"
      },
      "source": [
        "#Para normalizar o crosstab por coluna utilizaremos a função normalize declarando o que queremos, columns nesse caso\n",
        "pd.crosstab([dados[\"tratamento\"], dados[\"dose\"]], dados[\"tempo\"], normalize = \"columns\")"
      ],
      "execution_count": 129,
      "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>tempo</th>\n",
              "      <th>24</th>\n",
              "      <th>48</th>\n",
              "      <th>72</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tratamento</th>\n",
              "      <th>dose</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">com_controle</th>\n",
              "      <th>D1</th>\n",
              "      <td>0.038729</td>\n",
              "      <td>0.041576</td>\n",
              "      <td>0.039399</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>0.039243</td>\n",
              "      <td>0.036970</td>\n",
              "      <td>0.039143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">com_droga</th>\n",
              "      <th>D1</th>\n",
              "      <td>0.461271</td>\n",
              "      <td>0.486182</td>\n",
              "      <td>0.462012</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D2</th>\n",
              "      <td>0.460757</td>\n",
              "      <td>0.435273</td>\n",
              "      <td>0.459446</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tempo                    24        48        72\n",
              "tratamento   dose                              \n",
              "com_controle D1    0.038729  0.041576  0.039399\n",
              "             D2    0.039243  0.036970  0.039143\n",
              "com_droga    D1    0.461271  0.486182  0.462012\n",
              "             D2    0.460757  0.435273  0.459446"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 129
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7U4jOmiTaQPN"
      },
      "source": [
        "***Desafio 03: Explorar outros agregadores.***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MkRgs1jIy1UH"
      },
      "source": [
        "Algumas opções de agregadores:\n",
        "\n",
        "*   **count():** Contagem do total de valores;\n",
        "*   **mean():** Média dos alores;\n",
        "*   **min()**: Valor mínimo;\n",
        "*   **max():** Valor máximo;\n",
        "*   **value_counts():** Contagem por frequência;\n",
        "*   **std():** Desvio padrão."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "id": "wNsg4eYoaP3J",
        "outputId": "27d6b0c3-f6b5-4e78-94b4-7552d53fd538"
      },
      "source": [
        "#Iremos utilizar o agregador std (desvio padrão)\n",
        "pd.crosstab([dados['dose'], dados['tempo']], dados['tratamento'], values=dados['g-0'], aggfunc='std')"
      ],
      "execution_count": 130,
      "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>tratamento</th>\n",
              "      <th>com_controle</th>\n",
              "      <th>com_droga</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dose</th>\n",
              "      <th>tempo</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D1</th>\n",
              "      <th>24</th>\n",
              "      <td>0.751395</td>\n",
              "      <td>1.461954</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.853396</td>\n",
              "      <td>1.693903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.769294</td>\n",
              "      <td>1.458600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">D2</th>\n",
              "      <th>24</th>\n",
              "      <td>0.836626</td>\n",
              "      <td>1.044999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>0.836845</td>\n",
              "      <td>1.315476</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>0.878041</td>\n",
              "      <td>1.451532</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "tratamento  com_controle  com_droga\n",
              "dose tempo                         \n",
              "D1   24         0.751395   1.461954\n",
              "     48         0.853396   1.693903\n",
              "     72         0.769294   1.458600\n",
              "D2   24         0.836626   1.044999\n",
              "     48         0.836845   1.315476\n",
              "     72         0.878041   1.451532"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 130
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CZlH8xW3aUnw"
      },
      "source": [
        "***Desafio 04: Explorar o melt.***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZjVhb__maPgn"
      },
      "source": [
        "Melt é utilizado para transfromar ou remodelar um dataframe. É um comando dentro da biblioteca do pandas, portanto o utilizaremos da seguinte maneira: pd.melt().\n",
        "\n",
        "Dois parâmentros são muito importantes no melt, sedo elas: id_vars e value_vars. \n",
        "\n",
        "*   id_vars: refere-se a coluna que você não quer alterar, as demais colunas passam a serem linhas;\n",
        "*   value_vars: se não o informarmos todas as colunas vão ser consideradas em nossa análise.\n",
        "\n",
        "Também é possível filtrar o df, basta utilizar: df_dados[df_dados['variable']=='nome que deseja filtrar'].\n",
        "\n",
        "Além de podermos renomear as colunas 'variables' e 'values', utilizamos: var_name = '' , value_name = ''\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.melt.html"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "-XNE6IzFdCmK",
        "outputId": "5da9de01-aa25-4c09-fc6a-ccecf0aa8230"
      },
      "source": [
        "pd.melt(dados, id_vars = ['tratamento', 'tempo', 'dose'], value_vars = ['g-5'])"
      ],
      "execution_count": 131,
      "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>tratamento</th>\n",
              "      <th>tempo</th>\n",
              "      <th>dose</th>\n",
              "      <th>variable</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-1.0120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>0.5207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>1.2390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>48</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-0.8095</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D2</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-0.8244</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23809</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>g-5</td>\n",
              "      <td>0.7201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23810</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D2</td>\n",
              "      <td>g-5</td>\n",
              "      <td>0.6621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23811</th>\n",
              "      <td>com_controle</td>\n",
              "      <td>48</td>\n",
              "      <td>D2</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-0.0159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23812</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>24</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-0.0343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23813</th>\n",
              "      <td>com_droga</td>\n",
              "      <td>72</td>\n",
              "      <td>D1</td>\n",
              "      <td>g-5</td>\n",
              "      <td>-3.6750</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>23814 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         tratamento  tempo dose variable   value\n",
              "0         com_droga     24   D1      g-5 -1.0120\n",
              "1         com_droga     72   D1      g-5  0.5207\n",
              "2         com_droga     48   D1      g-5  1.2390\n",
              "3         com_droga     48   D1      g-5 -0.8095\n",
              "4         com_droga     72   D2      g-5 -0.8244\n",
              "...             ...    ...  ...      ...     ...\n",
              "23809     com_droga     24   D2      g-5  0.7201\n",
              "23810     com_droga     24   D2      g-5  0.6621\n",
              "23811  com_controle     48   D2      g-5 -0.0159\n",
              "23812     com_droga     24   D1      g-5 -0.0343\n",
              "23813     com_droga     72   D1      g-5 -3.6750\n",
              "\n",
              "[23814 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nnHAHD_eAxj4"
      },
      "source": [
        "***Desafio 05: Calcular e analisar a correlação entre G e C e refletir sobre os efeitos biológicos.***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QWDP6pO6CdaL"
      },
      "source": [
        "#Utilizamos o loc para selecionar as colunas que iremos calcular a correlação de genes\n",
        "g = dados.loc[:,'g-0':'g-771']"
      ],
      "execution_count": 132,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cLWKeHvfG5Su"
      },
      "source": [
        "#Utilizamos o loc para selecionar as colunas que iremos calcular a correlação de celulas\n",
        "c = dados.loc[:,'c-0':'c-99']"
      ],
      "execution_count": 133,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OVivgbwbLKgn"
      },
      "source": [
        "#Utilizaremos a função .concat para montarmos uma tabela só com G e C\n",
        "g_c = pd.concat([g, c], axis=1, join = 'inner')"
      ],
      "execution_count": 134,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kzxdpo0hLewC"
      },
      "source": [
        "#Aqui nos iremos fazer a correlação do G e C\n",
        "corr = g_c.corr()\n",
        "#Utilizaremos a função .loc para limitar os dados até 15\n",
        "corr_g_c = corr.loc[:'g-15', 'c-0':'c-15']"
      ],
      "execution_count": 135,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 615
        },
        "id": "29yQ-OwvL3iV",
        "outputId": "d9303835-cd3d-49cd-dcb7-86f196f91b3d"
      },
      "source": [
        "#Gerando mascara para o trinangulo\n",
        "mask = np.triu(np.ones_like(corr_g_c, dtype=bool))\n",
        "#Definindo tamanho da figura\n",
        "f, ax = plt.subplots(figsize=(15, 10))\n",
        "#Definindo cores do mapa de calor\n",
        "cmap = sns.color_palette('viridis', as_cmap=True)\n",
        "sns.heatmap(corr_g_c, mask=mask, cmap=cmap, center=0, square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
        "#Adicionando título no gráfico\n",
        "plt.title('Correlação entre G-0 | G-15 x C-0 | C-15', {'fontsize': 20})\n",
        "#Plotando\n",
        "plt.show()"
      ],
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x720 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zol6Vw0fQkK4"
      },
      "source": [
        "Quanto maior a relação entre os genes e as células maior a viabilidade, mais amarelo os quadrados ficam, quanto menor a relação, mais roxo ficam.\n",
        "\n",
        "Vale ressaltar que os valores positivos estão diretamente correlacionados, ou seja, possuem maior viabilidade, já os valores negativos indicam o contrario. \n",
        "\n",
        "Uma das hipóteses para termos correlações negativas são os genes ligados a morte celular.\n",
        "\n",
        "Podemos concluir que os genes importantes para manter a viabilidade da célula apresentam correlação positiva.\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Lvt45FJA3O8"
      },
      "source": [
        "***Desafio 06: Estudar o código que plota a matriz de correlação (heatmap).***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HRHSlqQSW0Cz"
      },
      "source": [
        "Importação da bibliotecas que irão ser utilizadas no código:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HV7ZT2qHWw0X"
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 137,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RzK4pXt-XNab"
      },
      "source": [
        "Após importar as bibliotecas notamos que o código começa criando a mask, que é responsável por criar a figura em forma de triangulo:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zdDr4JMfXrxS"
      },
      "source": [
        "mask = np.triu(np.ones_like(corr_g_c, dtype=bool))"
      ],
      "execution_count": 138,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cXqk2vtoXy3K"
      },
      "source": [
        "No próximo passo é definir o tamanho da nossa figura (gráfico):"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NwJ4jwhTX1_P"
      },
      "source": [
        "f, ax = plt.subplots(figsize=(15, 10))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EESxM2NbX1fa"
      },
      "source": [
        "Nessa parte do código nós iremos definir o mapa de cores do nosso gráfico:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Ab2FWMsYHHD"
      },
      "source": [
        "cmap = sns.color_palette('viridis', as_cmap=True)"
      ],
      "execution_count": 140,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ATXdL9hcZZ3-"
      },
      "source": [
        "Agora o código tem a função de desenhar nosso mapa de calor com todas as customizações, entre elas a mascara, qual irá ser a base de dados que irá ser utilizada para a realização do mapa, o centro do mapa, as linhas, a largura dos quadrados e a formatação das barras informativas ao lado direito do mapa:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GqRO-UjuYJ1b"
      },
      "source": [
        "sns.heatmap(corr_g_c, mask=mask, cmap=cmap, center=0, square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7oKh7de_ZbAE"
      },
      "source": [
        "Adicionando um título para nosso gráfico:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Qb5G-7pYRHD"
      },
      "source": [
        "plt.title('Correlação entre G-0 | G-15 x C-0 | C-15', {'fontsize': 20})"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H_bnZE3LZfbq"
      },
      "source": [
        "Plotando o gráfico:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LmM_ttaxYZxr"
      },
      "source": [
        "plt.show()"
      ],
      "execution_count": 143,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sT6zF3FMA84H"
      },
      "source": [
        "***Desafio 07: Resumo do que você aprendeu com os dados.***"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HKZXbNExAv-q"
      },
      "source": [
        "*   Algumas variáveis genéticas tem efeitos sobre os tipos celulares e outras não, como mostrado no heatmap obtido no desafio 5;\n",
        "*   As correlações negativas podem estar ligadas ao fato dos genes ligados a morte celular;\n",
        "*   As correlações positivas indicam maior viabilidade entre a correlação dos genes com as células."
      ]
    }
  ]
}