Mentor_Activity.ipynb

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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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        "<a href=\"https://colab.research.google.com/github/aparna8902/AI-Tasks/blob/master/Mentor_Activity.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
      "source": [
        "\n",
        "#**2. Random Forest**"
      ],
      "metadata": {
        "id": "78ioGvk7VAQ_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.ensemble import RandomForestClassifier"
      ],
      "metadata": {
        "id": "QXaQ0cXcVPNa"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset = pd.read_csv('/content/water_potability1.csv')"
      ],
      "metadata": {
        "id": "x0iR8kDFaR8y"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.shape"
      ],
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        },
        "id": "WdY7CC87ai3t",
        "outputId": "83c10cfa-ffee-4196-9c7e-6f34df29c0fd"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3276, 10)"
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          "metadata": {},
          "execution_count": 3
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      "source": [
        "dataset.head()"
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        "outputId": "10552f28-1416-4cd6-f36f-a35043f050b7"
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      "execution_count": 4,
      "outputs": [
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            "text/plain": [
              "         ph    Hardness       Solids  Chloramines     Sulfate  Conductivity  \\\n",
              "0       NaN  204.890456  20791.31898     7.300212  368.516441    564.308654   \n",
              "1  3.716080  129.422921  18630.05786     6.635246         NaN    592.885359   \n",
              "2  8.099124  224.236259  19909.54173     9.275884         NaN    418.606213   \n",
              "3  8.316766  214.373394  22018.41744     8.059332  356.886136    363.266516   \n",
              "4  9.092223  181.101509  17978.98634     6.546600  310.135738    398.410813   \n",
              "\n",
              "   Organic_carbon  Trihalomethanes  Turbidity  Potability  \n",
              "0       10.379783        86.990970   2.963135           0  \n",
              "1       15.180013        56.329076   4.500656           0  \n",
              "2       16.868637        66.420093   3.055934           0  \n",
              "3       18.436525       100.341674   4.628771           0  \n",
              "4       11.558279        31.997993   4.075075           0  "
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              "      <th>4</th>\n",
              "      <td>9.092223</td>\n",
              "      <td>181.101509</td>\n",
              "      <td>17978.98634</td>\n",
              "      <td>6.546600</td>\n",
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              "      <td>31.997993</td>\n",
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    {
      "cell_type": "code",
      "source": [
        "dataset.isnull().sum()"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "6htcXEWHa1ZO",
        "outputId": "89aa1fc0-7e32-4a22-df51-88a26864e749"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ph                 491\n",
              "Hardness             0\n",
              "Solids               0\n",
              "Chloramines          0\n",
              "Sulfate            781\n",
              "Conductivity         0\n",
              "Organic_carbon       0\n",
              "Trihalomethanes    162\n",
              "Turbidity            0\n",
              "Potability           0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Null values are substituted with their means\n",
        "mean1 = dataset['ph'].mean()\n",
        "dataset['ph'].fillna(value=mean1, inplace=True)\n",
        "mean2 = dataset['Sulfate'].mean()\n",
        "dataset['Sulfate'].fillna(value=mean2, inplace=True)\n",
        "mean3 = dataset['Trihalomethanes'].mean()\n",
        "dataset['Trihalomethanes'].fillna(value=mean3, inplace=True)"
      ],
      "metadata": {
        "id": "6F8KrTVnbPWj"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.isnull().sum()"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "ARkTlCSDcU0B",
        "outputId": "a23106a4-cb8f-419d-8c7b-20be4865fa54"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ph                 0\n",
              "Hardness           0\n",
              "Solids             0\n",
              "Chloramines        0\n",
              "Sulfate            0\n",
              "Conductivity       0\n",
              "Organic_carbon     0\n",
              "Trihalomethanes    0\n",
              "Turbidity          0\n",
              "Potability         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Data Visualization"
      ],
      "metadata": {
        "id": "aHCuiQomcliA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "ZezhrRsPcp79"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.describe()"
      ],
      "metadata": {
        "colab": {
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          "height": 300
        },
        "id": "qFUQAOgjc12I",
        "outputId": "a023428f-5649-4f41-cd82-449b65c604d0"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                ph     Hardness        Solids  Chloramines      Sulfate  \\\n",
              "count  3276.000000  3276.000000   3276.000000  3276.000000  3276.000000   \n",
              "mean      7.080795   196.369496  22014.092526     7.122277   333.775777   \n",
              "std       1.469956    32.879761   8768.570828     1.583085    36.142612   \n",
              "min       0.000000    47.432000    320.942611     0.352000   129.000000   \n",
              "25%       6.277673   176.850538  15666.690300     6.127421   317.094638   \n",
              "50%       7.080795   196.967627  20927.833605     7.130299   333.775777   \n",
              "75%       7.870050   216.667456  27332.762125     8.114887   350.385756   \n",
              "max      14.000000   323.124000  61227.196010    13.127000   481.030642   \n",
              "\n",
              "       Conductivity  Organic_carbon  Trihalomethanes    Turbidity   Potability  \n",
              "count   3276.000000     3276.000000      3276.000000  3276.000000  3276.000000  \n",
              "mean     426.205111       14.284970        66.396293     3.966786     0.390110  \n",
              "std       80.824064        3.308162        15.769881     0.780382     0.487849  \n",
              "min      181.483754        2.200000         0.738000     1.450000     0.000000  \n",
              "25%      365.734414       12.065801        56.647656     3.439711     0.000000  \n",
              "50%      421.884968       14.218338        66.396293     3.955028     0.000000  \n",
              "75%      481.792305       16.557652        76.666609     4.500320     1.000000  \n",
              "max      753.342620       28.300000       124.000000     6.739000     1.000000  "
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ph</th>\n",
              "      <th>Hardness</th>\n",
              "      <th>Solids</th>\n",
              "      <th>Chloramines</th>\n",
              "      <th>Sulfate</th>\n",
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              "      <th>count</th>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
              "      <td>3276.000000</td>\n",
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              "      <td>3276.000000</td>\n",
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              "      <th>mean</th>\n",
              "      <td>7.080795</td>\n",
              "      <td>196.369496</td>\n",
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              "      <td>7.122277</td>\n",
              "      <td>333.775777</td>\n",
              "      <td>426.205111</td>\n",
              "      <td>14.284970</td>\n",
              "      <td>66.396293</td>\n",
              "      <td>3.966786</td>\n",
              "      <td>0.390110</td>\n",
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              "      <th>std</th>\n",
              "      <td>1.469956</td>\n",
              "      <td>32.879761</td>\n",
              "      <td>8768.570828</td>\n",
              "      <td>1.583085</td>\n",
              "      <td>36.142612</td>\n",
              "      <td>80.824064</td>\n",
              "      <td>3.308162</td>\n",
              "      <td>15.769881</td>\n",
              "      <td>0.780382</td>\n",
              "      <td>0.487849</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>47.432000</td>\n",
              "      <td>320.942611</td>\n",
              "      <td>0.352000</td>\n",
              "      <td>129.000000</td>\n",
              "      <td>181.483754</td>\n",
              "      <td>2.200000</td>\n",
              "      <td>0.738000</td>\n",
              "      <td>1.450000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>6.277673</td>\n",
              "      <td>176.850538</td>\n",
              "      <td>15666.690300</td>\n",
              "      <td>6.127421</td>\n",
              "      <td>317.094638</td>\n",
              "      <td>365.734414</td>\n",
              "      <td>12.065801</td>\n",
              "      <td>56.647656</td>\n",
              "      <td>3.439711</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>7.080795</td>\n",
              "      <td>196.967627</td>\n",
              "      <td>20927.833605</td>\n",
              "      <td>7.130299</td>\n",
              "      <td>333.775777</td>\n",
              "      <td>421.884968</td>\n",
              "      <td>14.218338</td>\n",
              "      <td>66.396293</td>\n",
              "      <td>3.955028</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>7.870050</td>\n",
              "      <td>216.667456</td>\n",
              "      <td>27332.762125</td>\n",
              "      <td>8.114887</td>\n",
              "      <td>350.385756</td>\n",
              "      <td>481.792305</td>\n",
              "      <td>16.557652</td>\n",
              "      <td>76.666609</td>\n",
              "      <td>4.500320</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>14.000000</td>\n",
              "      <td>323.124000</td>\n",
              "      <td>61227.196010</td>\n",
              "      <td>13.127000</td>\n",
              "      <td>481.030642</td>\n",
              "      <td>753.342620</td>\n",
              "      <td>28.300000</td>\n",
              "      <td>124.000000</td>\n",
              "      <td>6.739000</td>\n",
              "      <td>1.000000</td>\n",
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              "  </tbody>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset['Potability'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bYNeAjHTkXXF",
        "outputId": "cd7a3dff-3a7e-4847-c6aa-c27e7de7b47f"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1998\n",
              "1    1278\n",
              "Name: Potability, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset.groupby('Potability').mean()"
      ],
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          "height": 143
        },
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      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  ph    Hardness        Solids  Chloramines     Sulfate  \\\n",
              "Potability                                                                \n",
              "0           7.084658  196.733292  21777.490788     7.092175  334.371700   \n",
              "1           7.074754  195.800744  22383.991018     7.169338  332.844122   \n",
              "\n",
              "            Conductivity  Organic_carbon  Trihalomethanes  Turbidity  \n",
              "Potability                                                            \n",
              "0             426.730454       14.364335        66.308522   3.965800  \n",
              "1             425.383800       14.160893        66.533513   3.968328  "
            ],
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              "      <th>ph</th>\n",
              "      <th>Hardness</th>\n",
              "      <th>Solids</th>\n",
              "      <th>Chloramines</th>\n",
              "      <th>Sulfate</th>\n",
              "      <th>Conductivity</th>\n",
              "      <th>Organic_carbon</th>\n",
              "      <th>Trihalomethanes</th>\n",
              "      <th>Turbidity</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Potability</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>7.084658</td>\n",
              "      <td>196.733292</td>\n",
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              "      <td>66.308522</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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    {
      "cell_type": "code",
      "source": [
        "correlation =  dataset.corr()"
      ],
      "metadata": {
        "id": "kYojFV50c7gx"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "sns.heatmap(correlation, cbar=True, square=True, fmt = '.2f', annot = True, annot_kws={'size':8}, cmap='Blues')"
      ],
      "metadata": {
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        "id": "zQcGtbzVqkOn",
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      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc4adbb98b0>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(dataset['Potability'], dataset['Solids']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "nMSt5DyVEmJ1",
        "outputId": "742036f6-7d83-4565-fc9f-494c1ebe1413"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.lmplot(y=\"Solids\", x=\"ph\",hue=\"Potability\", data=dataset);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "id": "eC9gK1jaCztN",
        "outputId": "f3bf076d-ac2c-40f2-d159-be8ae41f33c8"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 414.25x360 with 1 Axes>"
            ],
            "image/png": 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amCxg5kpHxZsf+wPtqRyupwibBo2JSKnG1qjXO8QvsP2Yy7j51eVHvN/ldXEO9eawjIGIThH4tPEAH+enJA7nSBPjHvM9fH3RN7h73QQq/s4m5opfRzOn0MJkgTLZ1f5MC6DNO9p5paMfUwRTBMdVHOjNsqQmOmqNre1P3MeiZ64j65p4VoyafCuNe77Eish6UvEzRrzf9eeu5Lm93bhKYYpvxfqM8QCftR7AQyhgEiXHR917OdmsYSLl48d6bjP6XHX9LU0F0D6TBcpkKuoejZa+G7bsImQYiAgivvlJKWjtztKeyo/oP9m8ox3n6VvIeia2GcP2FAczBgVlcanz4BHvd82qZj695nUYItiuhynwcfOneAguJgRbD+Hk1h+O+x7Gem4z/lzngl9HM+fQmskCZTIVdcsFEEA8bJEpOGObm8bB0JX5W1bW86tdXfx6dxeWgKsAA5RSOJ6fSLioOjKihrFhyy6+qdro97tGY4iglEeaMC1e26j3+9k/O4G3GdtLvVaSXgYXAws7qCcmOBjE1JAy7XDEcNuxnlsln+sRme1+Hc2cQwuTBcpkOghOpaT7aGacoSa33Z39/Hp3F02JMFHLoOB6gF+bouD6giRqGVTH/FyP4sQLviD59e4u9oaaaDF6sMUvhigiRFWONqNl9PvduYlTfnsTJMMQWox7sAMLDxVcgQAhXLJEBv/xjFISvrXbHPW56VbJmvmANnMtUCZTUXeyJd3HMuNs/a8fcUv+ev4zvY6v9n2Rk7O/wRBI5RwaExHAd4QbAoYBIVNoqY6Wjh8LmTQe3Ezy3vfxzYN/xX9aN/GM90YMzybkZUEpqiRPWBzuti4e/X6HhM264v+JDMR2KQSISGFwQ6pRwm3Hem6ztmWARjMBtDBZoEymg+BkS7qP6p/ZuYm/6rqNBtVNigR1XhfXyfd4m/ECBdejOhZiSU2MsGmQdxVVYYuGqjDVZSv5kzK/5m/Vd2lQXfRLkkVmD+83nuR+7220ebUkVIouo57nTvwSe+rP5lBvlo5UvqTRDPJNDCntbhkGtviiRIJ/jgiGmIOT/UYpCT/Wc5u1LQM0mgmgzVwLmIl2VJxsSfdRzTi/vAVlhsmqMIYIeaIIio/JI/zKPB2A6lgIyxSak9FST/YT0//Dpc6DNLuHqFJp0kTIGdUA2BIjBJylfs+H7Os449h61p+7kotXNVMbaEk1phALmcN9LkPCZj0jDJ5HGv/6LRwEQcwwRnldrlHCbcd6brO2ZYBGMwG0MNFMiMm09B3VP9Ozh5pkNf19OTyl/EgqibCMDpIRC6UUWdstrdTXrGrmtgNPsuiZjWRdk6xVTYvbSUzlcdwwOdNPLLQlygqzgzOW1Q/KBxnT2T0kbLbHi1FLjoxUUUcvHiAoOlQNi2Eg2e9d3xg13Has51bRVskzQLlPbG3sJdZbj1JXOKDrfi0gtJlLU3FGNePUriBp2iytiREyDVxPkTRtqF3BcY2JYSa4zTvaMbfe5uePhOI0JaN4ZhSFok71kHc8XKUIqRwHpGWYqai1O0MsZA4aG+TsHhI2u4dF3BX5IAetpXgICpMOo4leLzBpFZP9FnC4bblP7DxzOx/pvo3ejlZSJHXdrwWE1kw0FWdUM47hawJJA5IN8WBFb8KF13L3CYOTAouT1o/sg/QbSTzXo7U7Q4Iki8gRERuUwnJyREwP65yrh632xxXFVhY2+/WNW4P9P8zp+W1cmbkdWxmETRm5LtcCEB5DKdf2Lul9AEdC5InQkS6QbKwaXKJfM2/RmolmRlizqpm7153JU184j7vXnTkwyU9gRV+ctNrNRUTIY4jgKehTcXqkjpxEaTQzpEIN3Fn3mREbbk3U2V2+/7PhN3FLeB2dUs/iSG5BaR+jUa7ttXht5IlgiFBw/JBuXfdrYaA1E83RZ5wr+qIj/wF1CVdmbgeVI6csYhRwxeLr8b/luchqlFL0Zm2uHeEYE3V2r1nVzPv39fCdp18jXXDZGz6JJee8hzf92QmjXutcqXs2HZRre21GC3VeF1kVIWwFa1Vd92tBoIWJZhCTmQRnauIsTlrPRVbzb3yS9+V+TL0cZL9q5j/iH+C5yGpg7ByNiTi7N+9oZ++vH+ZO80EWR9s5KM38568vZvOyjxzxGDNV5Xi2UIywyxQcfhx9H1embyeCoqGqdnb2c9FUBFGDelzPf1avXq22bdt2tC9jVlI+CcZCZimKarT8k8l8Z7zc+vOdJY2gKmzy9lVNPLu3d9C5erM2gh8+PN3nB7j51tv4y67byCmLrAoRE5uoODyTeAcfbNw9YqfCS0t+loG1Wqbg0JyMzt1Kw2NQXFDs687w7lI018G50Zq5csjYu8wftGaiKTGZGlGVqit16893cssTr2IIWIavbTz84iHe+yeLONRXKJmorn/3G0vX8Up7ioLjDSrgOFWB8vbue8h5JjmJIAI5IsS9LBf13wOR44aVTuGE849KeZSjbVYbrO2dB1w1Y+fWzA60MNGUmMwkWKmJ8ztPvxYIEt/ubgg4nscvdnTw4t+/c8Tv3PDwS9TEjpCMOEkWqza6qRq0xKyWDCbeQIJiefLiCedPqu7ZWEykttl8N6tpZidamMxmjlCFtlJMZhIs/05f1uZwf5684xEPm2ze0T5sMhvvCjpdcLGGxBoa4o+PdKy+rE1VxKQm5tfsmqiGVDzWko6nuEIe4XWhTmJNx5EmRowCGRUp7RsRm7yy+OOhFGHLoCkRIRkZiFgq9yGUm94mWx5lLGFxVKoOazRD0KHBs5ViFdpU22BTSgWTvyZTI6r4nY5UjgO9WQquhwBVEXNYT46J9O2oCpt4Q9x5nvLHRzpWpuByOFUglbNL+4+kIY3US754rBVdz/B59zsk7MPsyYRJdx6gUVI00MPxsp83yF6Ol/14QB8JTMPve7K/N0s63V+KWCqve/aG1FZuyd/A4/IZ1mz96KR+fmP1nhkzEVOjmQG0MJmtjFKFtlJMpvhj8TuZgoun/La6S+tiNCaiw5pPTaQh18fPOQ5P+aYtT3nB1h8f6VgRywCBjlS+dIyhWtWtP9/J+h8+y693d9LVn2d3Zz83PPwSNz/2B0KmcKnzIDYWthFDRGjLGbgYVIl/zKKpyy8/7xBROQwgqnL0Z9KDIpbWrGrm7jUpvpH4IScls8SSDcMWBCMJtpEYS1joqsOa2YA2c81Wevb4Gkk5M5D8NZkaUWtWNVMdC3FMfRyRAe/C0NXxWP6VoSaw9/7JIn6xo6MUzfXxc47js0F+x9BjNSYivK7vV3yCRziuu9MP4TUvZu27P1I69r9s/iOeUn7ZFgWd/TYNCXitL8frmxO0pNtI4df2KibdVal+RGCXWoZSCgXEyVPAxDbqaPHaaDNb+Ia3lsObk7T+5IkB893WsgUBDPKtbPZOGd3PsXMT/PzL0PUqTzgee/NL+Y/4FSOGP0+3WU2jmQxamMxWRqlCOxtJhE1ePtRHMek5bBnUxUMc15go7TOaT2Ykv8D+niy3/sVpIwq3ocdaY2znE9Yd5LHo8apoMnv4SugOYsYpwPls/a8fcYdxF8ulg32qme/yHrZwKr0Zu3QdbUYLi90DJLw0FjauhAhhY2NyLAcIiUMBiw5VTbXYfLLm/wBwuD9HV85m2RDz3ePyGrFkA6mcQ0d/noLjETaFxbnXgh4uP2KxaqfNaOGB6CU8bZ7q+zmM7fDQpyDbBWJi4bHS280N/f/AnswxbAx/hF8ap5eEha46rJkNaDPXbOWsq/1kr0IGlJrVyV+bd7RzoCeL7RXbR0He8WhP5XnLyvrSfqP5ZCbak37osS7O3o8jFs11daxaXM2y5gZi0ZhvFgx6pjRJLz0qQaP0cL3xPd4qz5N3PVY2VmG7imflJOpVNxYFXCWYqoCBR1g5WDi4CCEclkkn/cRK99CVtqmLhwZd+1nec7iZHry232F0/xHLTuF4Cq+QYXfK4MOdtw7q4XJl5nbOVs+XyvKTT4GYgMLA88ve47HYO8Dn7I3ctvrwIGFxxHI1Gs0MoTWT2coJ5wNfD6K59s7a5K/NO9r57D3P05d3EXxBUjR0WYbwq11dfDZ4P9oK+rqHfndEE9iRIsDKj7WUdmI1jSSjZb/SRbNg0DPF9sIo1yOnIiDwMXmEp4zT+MIFqwBofOAlOqghqTKExcEhDKqAhctAaywAhafgDamtXCGPUGcd4LC3mAfyl/BcZLVfELKwkX4VJkKOEAVaVAcWtThiUlAmOWXhqAiW4fdwQeX4X9kf80rLW3wTp+eAYYLra07Fs8dMiNVW07L3TmB47TGN5mhRcWEiIiawDdivlForIscB9wANwLPAXymlCiISAX4AvAnoBD6olNodHOPvgI8BLvBZpdTjwfgFwC2ACXxHKXVzpe9nRpnlVWiLpql0wQGgGHxlGYJpCo7rDYsoOpJP5kgmsETEGmT+eu1wP+t/+CzJqMXrm5MlU0/7A4tI9BymIx33Q3Wj1oBZsKxnimEInqfIqBBL6eBdJ7UMXE+8m11ePX1eHYYIrlIc5+7GRXAwCeFgY9Gh6miSXr6R+CEYYXb11lDjdnJl5vZSmZe8MvFCDdh2mDrVQwSbKnJ83ruKLxvfpVtVIZ7yWxGLkFVhWlSbfz9bV0B/ByjP10pLCJjhsX1nMxxSrtHAzJi5rgb+UPb+a8C3lFLHA934QoJg2x2MfyvYDxF5I/AXwInABcC/iogZCKl/AS4E3ghcGuyrmSGKpqmoZSIysG53lUIpP+FwvBFFRbPVien/4abev2Nj1xX8U/o6Ti9sK5m/UjmHznQBTykyeYf2VI7P37+dv7l/Oz80LiJiuBhOhv09GdL9KbK5LDf3vZNn+6rpTfVRFTZLc3NcbNrNFp7d2zsQRVW7AsPJlgSJ7Xi4mLgYmHiEcImTZ7F0EidXcq43JaPkJEpembwv92Oa3UPkiNCUiGCHkrymFvMyx5AiztOcxj7VTExsDKHUw6XKsIk1rRxo0BVJgipGaAXGQ8OEqqbRfWcTDCkfb0SZRjMWFRUmIrIMeDfwneC94NdauD/Y5U7g4uD1RcF7gs/fHux/EXCPUiqvlHoNeBU4I/j3qlJql1KqgK/tXFTJ+9EMphiy2pSMYIqUNBNP4Te5ilrjjihas6qZ21Yf5nP2RmqcTrJmNauqMnwyczuv6/0VOw710dqdQXnKz+/wFPGwRX/eIZVzeKnqzfxb/JP0mg1Uq35+2xflyu5L2XhwJf+cfzeekyef6ccUqLFsqkyXR6r+fLBf5qyriZkuIS+L43p+NWIFEVyiFBAUggre58GzS851z1OkVZhG5xCdocUsTwjJqMWiSIHj5CBvYC9JMpzNc/y7t5aoOFSbNisb4qyqN1lWbVL3Z58HYLN3CjdHPssr3lJsDP+5mmGoXg5GaLDvbOcmuGMt/N/Xw83HwN1/4QsQzx4zpHwieT8azVhU2sz1beBvgWTwvgHoUUo5wft9wNLg9VKgFUAp5YhIb7D/UmBr2THLv9M6ZPzNI12EiKwD1gEcc8zsjIaaKaazhlPRNJWMhlhWB4d6c+QcDxF4fXOCL1ywakLHPmXvnVBbXYpgS+UccirHFTzMFjkVWyk8ANcjYvl5F66nKBYrfS6ymifVKezPZLHLMh7/2z0FT13OevNRlqsOuozFPBD1/RsxpQZ1WTx09k04T9/CMewhLnniFIZdZ/HITt9B9qulCL6GEfKyHJIWrDOvouq3N0G6g3imHUcUrhLSKsINxvf5VugTfNtYx5dqN0FucDHEgai2k3m6/l/I2i6n5bfxpdpNfuHEZMuA2aqohbg2ZLuDi3N8Y3Dffv99tOaIZrGKZs6PYGrb7J2yYMryL0QqJkxEZC3QrpR6VkTWVOo840EptRHYCH7V4EkfaI7boidVw2mUey7Pb0hELJbWxaZWsbdnDymSdBxOUwja74qEWUYHCr+ciq/1QFMywun5bXzJvJdl0k5nry8g7k+tGrFW65PeqTzpnQrAiqo41RHf2T8ouW/nJk7Zeyf50AGUlx3irxig5IZ3baKSw5YoNW43NaSoVmkObL0NzvoQbP0XQGGFoxRCDeQKYQw7w8eMRzn8vvupW/X5Ycf+2s920N6Xww0SQJuSEZ6PrItW7IEAACAASURBVOZT1jnc/akhFYeLia3pwyAGGIbvuFcuYEK6wxcmRzCLjZb3M6VFR1HIGeGSqS370Od41L6c9shqXT9snlJJzeRs4L0i8i4gClTjO8trRcQKtJNlQLCEYj+wHNgnIhZQg++IL44XKf/OkcannxH+QMorxc4FJrwSHeOepzu/oTu8hN6OVmyJ+qYs2yNGnkNmC5YSXE94qzzPleajrMocIK7SdBlJuhlwgO91P8LTnDbqefb3ZAGFZRoDyX1l9xpReVwBA2dADRmB11hGxqxhubOHKrL0SjW9UkNjYR88/U1wcv4kb2eJ08nKZDOEG/2OkiM8o8072tlxKAX4p3U8l9auDMvqYiOXRikmtjo531nvFgOzAc8FtwBtvwPDYtfiC/nSxq2DhMORgh6qwubUCkf+cniyZmdPlg/zIC+HfYGo64fNPyomTJRSfwf8HUCgmXxeKfVhEbkPeD++j+My4KHgKw8H738VfP6EUkqJyMPAXSLyTWAJ8Hrg1/gLxNcH0WH78Z30H6rU/Yz0BzLXeltPuMLvOO55Mhnz5avetaXeFwfoTZkkVRpDhLyKEJMCYRz+3V3LyqYEp+e38Yn+O8ljEVZZDDxajBQ1sSSHCnHydoYrQ/8/fwi/mUN9+SOe3zKEQ315Tj+mbkD43VF2r24B0zRRjsNo0uSbfIgXzNX8G/9AnddFXqLEvDQN9AYTO/4kD2DnoHef70CvH9mPdPNjfxh0NqV8i9WBniyrj20Y/oXaFdC1yxccQ1EOIGBFyRkJIi/dw4pIDan4GSXh8P7Tl3L/c/uHZc6HTaO06Dg9v60UVND5wGJ4//Vj/76PUL2h3w2x2Bjsi9H1w+YXRyNp8QvANSLyKr5P5LvB+HeBhmD8GvC7riqlXgLuBX4P/Az4tFLKDTSbzwCP40eL3RvsWxl69vi253LmWG/rCddwqsA9lzt9zzO385Hu2+hub2VnXwjHzuMqRUFZJOmnz6zn750reMI5ZVhiYpWpCFlhDDGI252sbKzi2EWN/ElVL2HLJHSE3+yoZXB8c4LmZKSULHnO156gvXUnKTcQtGYYlELM0IjHUECfivF8eDXtqQLLnD00eodZ4e5msWoLzHEuCvAoiqMgzDfTecTE09c6MwQlxgZltdgewwMZdm6CTFfgG1Fl/4oI1B0LDcdzwE1iY3Gp8+CghNBf7eoasRZbKu8Ll9Pz27gyczt1Xhf9kiRRODy+YqO1K3zTWhkJ0+agDF506Pph84sZSVpUSm0GNgevd+FHYg3dJ8cRsrCUUl8FvjrC+E+Bn07jpR6ZOVbeZCQmXMOpAvdcbmq7pPcBClikvTCiFEgUFHS4VXw8+W2S0RCH+3PE835HxUGJiemw73gW8c05wbXFmo7jxjNP5ObH/sDLbf2l6VUETBEW1URHzF/ZX2imrrcLpI5kVZM/SSuFJyBqYGL3gG6V4FWOoSkZ5Uz3OarcDAYeCgsDBxVoIx6Ci4mJg6E8JBQHDF+z++k1I/rdDBEMU3A8r+SyCRkyWPsrNz9iUBIkYgDi+0zE9P0lQMHxMCVKi9dWOkRRKxhJs1y+xTd/vS/3Y2ws8hLFUwovFPcdV2Np42dd7V9fAX/xYWdpiMK37Yt1/bB5jC6nMl7mUHmTIzHhqsBD7jndn6Ktp4//vf9tk85JKK+A2+K10e+FAVBKYZlCljDLpJ32vhyZgkPINPmPc/t4quWbNEsPyf5dkO+DRDOgfBOPGR7081izqpmffe5tfP/y/48P17/M3eGbeCp8NfdGv8qZ7nPYrh8BVl6+5cHY+wnj0NvXC5FqiDWCYeIavmZmI2QJ4WBSIxmeN04G4Ap5hB6ShE2TiDmgGwjgIniYOITISgzC1f41HiEHZGVjFZ4KInotg7BlYBnC8c0JBlFufgzH/fs3IxCKw6KTwYpBmVYVtgxCKkeb0VIaG00rKOb8NLuHyBPBCwpcNiUivnDoeNkPR/72yf52qKZywvlw4df9yLNcDyRbiF30Lda+7yMTqkitmVvocirjZY6UNxmLCfk4yu452/EaO7J13Bf+MC/HzyA7yWiccqdvm9FClXOYLBFEBFOEqGlzwGsm7yqak1GuPb6VU357kz95JpZAX6v//GuW+/6HTKc/eZaHzBbv1djOmsidpE2TtmwN9U43n7M3cunZN/Hp3zQM8h89F1nNv/FJLsrcz7JcDzS+Ds66ld/f+w8c575CkhwhbBSQIspp3u/4KdDsHiJj1UOyBtIdeK6DgeuHMCO+Ex+hT8WI57og3nBEH9QXLljF39y/nVTOwXE9LMMvllks91Ki3CdR1KIQcPK+UI1UA8GCJxSjJerR0+9wt3UxSqkxtYJiYEXnA4tJFA7jhcqqCqQ7fGE+VCAODUQZoXrDmgn+rmjmFqKOEP44X1m9erXatm3b0b6MOcelG7cOi/zJFByak1HuXnfmKN8cTHl48tnqeT6e+lcKysI1o8SkQAiHW8Lr2FN/NnevO5Puf30n6c799HthDEOIe2kaVCcminTzm/xEvyMJ9DvWDjfTFTKQbOHSwnXjup/eLy8mie8kVgjF1Mw+4lxSfTf/lL6OVVUZqhJ+KtWuw2mq7C7iksMhhIVNQVkcDB/LSaGDkFzsqx5FlPJX73/9Yun5jBkdN/S+cr2QOuQ7+5efMaAtly18th9zGTe/unxiUXfl5rTAXEXvXojWQ7Lsu8Ez5fJHRz/ewmOEIPX5i9ZMNONiunq9l4cT/3f3KbhVn+Ti7I9ZRjvtxiLuti7ml8bp3HjuSjbvaOeEjl2kSYBA3nbJE6XfXEYN/Xyw/1pu9E5kzZFO1rPH9x10vhqEz6rS+LVnt3LVtsYxbfhxcqXXRpmDu5oM54d+i3XO1X6CYiFDyg1hullyyuSLzmd4yjsFF7+szKfPeR0n7btmTB/UuDTHoT4JI+RP5heOoB0EnALcfd7ohx3GSNp4tgsSTYP3m2OBKJrKoIWJZlxMpj/8kRg8YZ7H5h1/yTVlq/Ebgwn9s/c8zwavkSbpJafCCH4BMMvL0x5aNKgUykj920Ggt9XfeuV1rkxO+e1NXHPs57jh94tJF1zeEX6RL9ZsYvnP2v1Ci4HJzC//PhwBru27CbYlINFCKu+Q6uugy2jh++Z7+EX+JAAiplAXD3H/c/tZu/J0Vu7b4CcWmhGI1fq+jYn63aZqcp1I8u1Qc9VI2t54gjLmeMKvZmy0mUszLsrNU+Ur+fE4USeaTV081/6eDH9qbucG4/vklUWOMDGxqaaffqueuMrQ6jXyo/D7sAzh6sJG8sokR4TlCaEqvTeovDsQoAuAGSEdX8aOdJy/rbqJs9XzXJm+nQIWDTW1JE3bd5Rf+HWcuz7gR2INvUgBT0LksWhX9ZjYfMP8BH+sPYtdHf04nsJ1PTzANIS3GS/wFetOFlcZUOjzNSXDgnOugTVfmOyPZeKMZLoK7nVck/tkvj/Vc85dFpSZS0dzacbFZPrDw+SKCZZXI35KncZXvI/SoWqpIY2tTATBUja9qop6erjG3si6wg+G9W/3w2WLmpQEJUdCgKItKyxRbX6Icu4BHAmRlygd6cKg4oh5QkecEQrKv45+FSHnWXyg8BP2dqbJFFzyjoej/PIvpggfk0dIuwapUD00HA8tJ0HNMbD7qcn8OIY943FX/i2PBBujEOSIjBCpNaZQmOo5NXMCbebSjJvJZLtPpphg0T/TlIxwoCfHFk5ls/cn2B7cFbqJEA45N4wh4BIhJMJSbz97Dd/UUuzfTijqawDhKj8nxTDA88AMYRSytFuLAFju7CFKnhAOBc+C3GJSKk62dSdxT428vlQgeBSCP6EcYZZJB705Z9iunoLl0kEPCTr68wMNvMp9DZM0A0243toI2ekT9nlMtM/OdJxTM+vRmommopTnlRQZy3FfzNRPRkMsqY1iGYLj+XP6cqODLOHSvpZpkFX++wh+CRVPKcKW4ed1GJafvKc8cAp+gmMhw2I6eFZO4gP9d1FDHzFyGLiEKeD17iPdc5D9NBOR4cKhiADtqgalIEaBfhXlrtBNbAlfzV2hm3ib8QIAtuvRqppJGAVfyOX7/KCA9pf81f3mr02oB0k5E213PFJ2esWTb4/GOTUzjhYmmooy4RIuDO7vnohYvCf+EneHv8oz0b+m1sjQYvYTsQxMw1cZIuRpNZYSwiHkZVFKUWPZtGU9NnoX87tcI7YZo9RUOBxHReu5xH6QD+fvKkVpCQoLD89zqCPFg7H3Y6COWJ3LwKVZeqinhyRpGo0+mqSHHqpokh5utO7gbcYLKOAnsfcRxqFReqGn1c8JEQOsKr8opF2YlBlowsL6aCTfzoOEX83YaGGiqSjlgkEpfztWGY1y/8wbUlv5nL2RY41D1NJHXGVoVIdpctsxAMvNEhGXm+0Pcr19GT1GPYvDOXbnk3wrtI6Ha/+SqyM38qK7gnTiOFj8J1DVRNTuppoMEgiLYu96hf9fn4qzvycTNMTyGSpUHCwiONRLihxhelUVWSKAkCVCAYv1pp978Wx4Nd8MraPGLPhHsiJQvdTP1/Ac3ylfzjjNQBMW1pPxeUyVo3FOzYyjo7k0Fac8Ee/dZVWCx+UbuGMtdO3C7mvDQ1AYmBQwgG5VzU5vKRvctTzpnYppQH08TENVuNSJscjGrivImtWsTLp+xrhrUy4eVCBWFIKnDA54dbQYvYSxR3SZeIArFvu9BhxMlksHO9VSBjtYFLWk+VP7Fs44rsGPYvvZ231TVnni4uFXwM37Tvki40wEnEqUnabiLKhoLu2A11SckuN+5yZ47DvgTqAnTMfLkD7sm5+CwomeMjBxSTDYlON60NlfoDtjs2pRsjTel7XZ6zXR4HaT6ekmImAOPU8gWAwUHh7LjcOl0aEzQlEEWTgsNzrYp/wkvjgFMkRK+8UosE81cUJL0s+q37nJz1bvOwBWFKqaSFFF3o2R8Aocbu+kJlk9EJo8DjPQhHvK6HwPTYXQmolm5ggS3lJemI7+PAXHI2EUqGpYSt2nHi/tVtRklnQ8xT/a/0SYQqmQSfH3VSE4GOxVLYRxuMG5vNRJUYCVTVXEwxZ9WZsDvVneKi/w9+b3WSydOBhEcEr+EIVfGVgBiOAqwQqqax0JFZxIACUWB1UdliqQJIuJG5Re8eiXJLuN5bzp3PfC9rsg1xe02FV4CN2qCgeTggrTbPQAUKhZSfLdX53+SX7h5nscLbRmotFUhKAt7/6+LIKfzJf2Qhgdu9i+o50X9/Vw+5N/JGv7SYL3xh6kmwTNdEEw8Rf/Oh0Em1Dgo4D15qMlYaKAfd1ZLoz8lkudB1litbNPNbMp9HY+4D5MVOUoYPnajgIT3+dQIESvF6VJUmPeigT/C77Fqi4eIZ22QYGBhykKD4MMUVqk13eym3Fw+sEwUZ4LSlFLPx4GiJBXFv2SQPp7SR7hvNufuA9z623U2wfpCi3GPfMqTjlvxM4Nw5kHDd40sxctTOYpU+rhXSlqV9DbuhshjBH4DGJSoE1auP6h33GgN4fnDWjKK9y9xKWAh99Go9wRrjDoUH6/jmyQ41EkbMC7or/lc/a/k1cWvZJgsdnDsd5/82D4Ys4r/JyMa2Lh0CI9CIoDqh4Qjik7ztgoXDOCWb2EeN8BVHIZe9MNHOMdwMMPKa6jlwMsw3ZsDKcHDAvTDFFQJko5RHABjwJhLDzqVC/dbs2IE/z2J+6j8akvYWORliQJ+zChp77EdhifQNH5HpoKoqO55iGTyTqfEc66GnELxMiDUkRUjhAOP4ldwr7uLEaZUeBc4wWqJUsIG5sQjjJRgSnKQzigGkkRJ0GG4+UAzdJTyu1YUhfnch7BM0IUjCgh08A2YthYnGi/yBfzl9GhajFRvOAdzy3O+4iJPUggAWMaKfpVxHfkd7+GcvPkUl14nsLCxgsMc3FyrHRfw1QuhvLALeA4Dp6CUKlQ/cB9KYQE/WQ7Xht2vppnvkq96mapamOpd4AQHjYW5tbbxvf8J5LvsXPT6D1LNJohaM1kHjKZrPPpotzfMajoYuDofTrxDt7Tfx9RciiEdpooOB6KQPsQPxVhvfkonSpJo/QFjabM0qzbQwIXgyRplkonAPtVA83Swz9G7mSjVNHitZGSBBI0dvKUIqPCNHmHeNI7tWQSe5vxAv9i3UIVR+4ZPxIekCDvC7hA6NTTTZJeQIhQKMkiQw2E7gogno0lJoaokoAcOK4QweHFbB2pHe0DP6+dm1jm7sHFRKGIkGOJOkieMOlC//gueoQOiCM6+st9K+MNlNAseLRmMg+ZTNb5dFDUiFZ0PcPn3e+QsA+zJxMm3XnAn4w2f42LnccCbcPCwaKRTj6fu4XzQ9vxytqYL5MOOqnmgPJDb81gFd5HguvUJ2lXtSySblwxcZLLUJEaXCuGKyHel/sxbUYLIZUjGjJZWhMjZBpYXp79akCYfsZ8gA2hb1El4xckxb7uxT+coTkoITxCuP54sZtu8Jlbtr8RlGLxxO/GaATd4i1x8TC5L/y/Bmex//IWHEIILhZuKT8mTIEE2fFrDuGEb+46vMOvWDyS813X0tJMAq2ZzEOms1z8RChqRJcWHgyKLkYRpWjLGaysNrGf+WeUnccrK+wuGNSaeW6o+QU/bzulNCnvU000SQ8p4vSrOCJC1MtxmDr+WPMW/jF0Dv/e/VF6SbA0FKcpBPt7s2RVmBavjW+H13OVu4HaqEdVxMRwPDoLNhu9tYCvkXzaeggZI2qriCptBxpkBTdQeqFQSNlH5UJHATZhwAbARGEaIXIqSp8XployRMTGw+TeyJ/zu/gZ9JYL/549eFUthNOtZSf2EypVrH5EH0u532xt7CWuzm8gFo1B0ypfK7HTI9/sFH0rs9Jfp6k4WjOZh0wm63w6KGpELV4b+SDKqlh0MeWGELsfAweFUYyDwjQMLOWyXDpYVhcrHWuDu5YwDjHyKBTRwL9yT+jiUh2qdnMRUfKl4olLa2JUGTb7aWJP/dkcfutXqWpYQjbVyY50nBu9K3ha+eat9eajWHi4gU4wImrQxr+fsoz4cqRMkHilsWIypP/axMUAPDHISgyrbjmJsEmdmSEqBXIS5d7In3Nv4kPDhX+kmni+o5SRXzyqZ0aI1rQMmug372jngm89ycd+8Bue39uNKfDO3h/RlvFIeeGxtY0p1NKatf46TcXRmsk8ZMKJbCNQXF3ubOvDdv3Cia9vTo56nKJG1Ga0UOd1kSdaKrrYm+oDYoRwELxAoIDreZiWBbXHoNrgHeEXuVw9zDLpoF9FQYRa0uxTTfy7t5aOxreUJvMHopdwZeZ28nYGVBzD8R32d5kXA9C95G1w3p/z0Y1baTdyvKmwjYeyX+A46yDhoJ+7BdiYhIumqTLcksgbnoul8Ofk8hIsRYzi5wx84J/LxRPD/yTeDJ4NdpqQYfGqdyxR8vyZ/QteSr+OXxqnsz7oNrn1v37Ex7taqaWAgQzUEjNMqFk6aKLfvKOdz9+/na50AU+Bpzz2dWdZFG2jr6xqcSrn0JHyiHa9zP/euHXwz3W8vpUROJr+Os3RRQuTecpkysUXKa4uC45LX1BSPVtw2d3ZP3J58yCr+nu9r/H7bB3PmidzIU/geVlyRGiJevSkCvwkchFrC4+RVH14+M5nQdHtRth7zGWs7XuJD2W+RwGLHqqISYEwDtc7V/CkdyrLaqNEbLc0UT2pTmG/fRkfl0cJHzrIHq+RDc4lbFFvhP5OntvbzafXvI7W7gznmdv568I/kzT6cJUvHvxp3R12/wooYHJANbJcOjCPUOqxlyqqyQwqBlkUIlL2Gim+FgoSgXgz8eo6v3KwmFh4LK2N09+bpdbr4sbc/yHd/Cb2Hvg4V21r5Jb8j8gYSbJejCY6iRRLvIjp92spm+g3PfxDbivcx9KQn5lfLDWzx21kidVHxomQyjns780SVTk6zEXDy9ZPoZPjdLV31sw9tDDRDKO4uuzsd/yVsCF4StGXdVhUYw1eZZZF/sSSDawy+lmWeYKHWMNZoT/40VwNx3Fb6J1ssk/mj6E38Ffp77PM2w/Aq2ox33A+xH//vIp7o/dQUFapJEl5QuKv5DSS0RDpgkum4OC4Hvt7cuzjVLbHV9PRbw+7j7zj8c2fv0LIEC4w7yVqpFFASNwBB/oQOeFgkFYR9tICCDnCRLAx8TBQ5Aj7fU+CYIAqcoMEkjDgK/Gj0AysuhWYRgjSbcSrWnwTU64XCml8D71JstBBUrpxcRFcEu2/4Q3tz/IhuYTF0k6KBJhR9ihfgC22Ur7GkGwZmOh3bmJ90DGyt6xy8Q3O5dzurOUrcgcxEzpSQlTliIjLA9FLRtYeioKjWHqlaA4bQ6AcLX+d5ugzYZ+JiBgiUl2Ji9HMDoq+j4LrleoRikDB9YatMrt//nX29bns6HLZ1ZnBs2K01Faz7pj9nPTFLcT+5iW4/FHOfMcHsV3F03Iq73Vu5mTnB7yxcCc3O5fyUR7hv63PcqL7MtaQ/iFZwiyXDhbXROnPO6Vqwof68limsLQ2RqYwuhPd9hTLpIMQjh8JpcArxvMGGw9fG/EQkpKjAb+Kb4eqwQgECUCUAgYeKS9Cs+rCViauGuxJKZq5CLZOqh08m7wK0dbTx6GDe7G7Wwf0GRFIt+O6DoKLwg+FFuVxufdjUl601KvFEKFXxSG5BFac5ReCLJv4C6WqAIMrFz/pncr19uUccmuIOH30mg38W/yTPBdZDYygPRQXCRPssXK0/HWao8+4hImI3CUi1SJSBfwO+L2I/E1lL01ztCiWNQ+bBsXSbUpB2DQGrTI372gn27GLtBfCNATb9djfmyXlhoZF/pSXlc+7irBp8DbjBW607ij1APEQltI5qIBjjAKtqokDPVnaU3k2bNnF+nNX0pSMcHxTgupYyBd6Y9zTPtVU8n2UlJEyrSRPGA8zyOMQ6iVFjDwxcsPMXAI0GylMHPpUPBA0g/ueFM1crlh4TgGvZy97Cwm+FVoXhCIr/5xi+eYqVCkUwMMkhE0IlzA2UZUhhENE5fA8v57ZSD6MbMdr5AiX6o3B4OoAz3Aal3nXcyH/zDWxr5QECYygPUwyPHiy7Z01c5/xaiZvVEr1ARcDjwHHAX9VsavSHFWKq8tk1MJD4XgenqeojlmDVpkbtuyizWghJgXAXzUL+M72ESJ/1qxq5u51Z3LGsfUsqonyCeNRClillXSbqkMBi6QbAeJSICIOG9y1OB4sqo6U7Pt4Hq929NPUtoU7ja8M6244lA3u2tJrKZ9u1fBorRwhUsTpULU0S+8Rn5OJKpVjKQqzch3JCf68PBSuAtt1eSRzIimq2G0cyx5jOW1Gs5/vERzBxa+IXO5rWUwnm0Ln0Sl1JOmnqmEpnPIhf2IPMtS3P3Efv8/WEQ9+FkWKlYtNAcsQXE8RNmVs7aFnj+98L2ec4cHFn/NTXziPu9edqQXJAmG8wiQkIiF8YfKwUmpwMwjNvKK4ujyuMUFN1CIWMqmJhzi2IVFaZW7e0c5ze7u5NXch4hYIeVlQihh5xB098uctK+vZ151lmQxuwdtPFftVAwaKBjNNJ7Vcb/vVgA1DqI6FiYctbNelrb/AW7zn+Xvz+zRLD91DuhsO5UnvVHZ6y0o920HIF41XgSSwsIlgU0WeOlL80nvjqBrP0M9kyJgBWBSwlIdSHsfJIVY7z7LbaSSkcr7JyotBw/GQWIyH+CVXFIjyQ41FwBO4OP8QS2kn1rSSujeeR/Y3/8G+1t3s6LHY17qb5qeuY7t5MiFlE8fXfGLkCeMLY7/isl9cszERIR4y2Ned5ZX2fsKmMVx7qF0BmcPQsQMObvf/dfwBIkcqQalZ6IzXAb8B2A1sB7aIyAqgb9RvaOY0o0WDFaO9ROAZdRr/4AkfU4+ywuygzWjh8foPcu0RHLWbd7Rz/3P7qYuH2Jf1ExOzRErVdx1l8bx6Pf9Y/38B2HGoD8tQeEqx41AfYdPAdvwS738XvodG1YMpfnZ8h6oZ5CMohe3iT/Jfcy/ln2QDSfHLxHuYpBVEcIlIAWNQLqLiauuBUYXJSL1OiudUgCeCpcDBN10phButO7jPPZcPeFsIAaYZg0KGrDJ5XJ3Ne3l6cFa9gpB4hMlS3XQ82F24W75Br5cgbdRimkJahTFdl1PlRb7sXsE641GWSjut3kA0F4CrFDHDoDNdoDoW4vXNCbK2S7owPKKNY98Ke36JUu7AM3QL2J17CO/cpMuqaIYxLs1EKXWrUmqpUupdymcP8KcVvjbNLKUY7dWSjKKAp7zTuMy9jvPsW7k68hXOfMcHx/xuUzLKT2KXEJayxETyRMXhbuvikglGAMfzf1FNERxXUfDgrTzPStWKESQeWrgskU4sHFaYh6kKm1imEDbAFDCD3/SIOISxCQf+CFdCPOydWTIrIX6tLWOcircasi0eRokRlD0ZKLHSp2IUsDjL+D3X25fTKfUsjuQg2cItkfVc632GjIoEhVWK+e2Bp0ek5LtQnkM1aQwR4l6a5d4BjpF23ui+jGUIl3nXc6P3MQS4yfp+yfx3fFMVy+riVMdCpcTPeNgiZMrg0i0Au58KEjqL2TKCjYHr5On++dfH9Ww0C4tRNRMRuWaM739zGq9FM0co5hJI+P+xd+ZxclVl+v++d6mlq3rvTneSzkIgYYcQWQUBF0ZkGFGEn+LMICgSd9RxYUZERGdGHEeMogIu4AoqoiyDC4oBBAKyIwQSCGTvvbu6umu5yzm/P86t6uq9k3SAQD+fT3V1nbpr1a3z3Hd7XjPRdA8W8UITgJ4q2FpZh/B09dFcAZxRvJF5dJKJz2Po6I9y+rwT6IoKLh3bIghDTnQe4zy5lTbpZJPVTB1ZPJyKoLVgAS3SzxN6KUua0wAcOHQ//6JuYm+3BzXYRRyfAAcvKv6rosBb7AdHWAOl/6dqkCUT/I+AI0Jl37kQi3oZIqfjtEkXw35REQAAIABJREFUd6rldNa8js+evB8n7jeHWy+7g1AVCB277C4bkTBQ0ea3iEscnyo1RLPuMlX2YjLULrau4ZfqeM6w7sTTDoNWNfMkw5U115H8xyM57jf29OpA+jeitCJkOJ4D2mik9YxVNJ7FLKZyc5UcpPsCRwA3R6//CXhgdx3UKwmvRJ2iylqCmqRLTdIl5wXMqU4AcNbVayY839F1CE9XH81vLOFf1E0cVNUHm34EbXWceL5xoxx32R0ck3iIjxavoagderWJjSyWdrp1NQ0yhEM4HLQG/hoewGHFv3F27loWq00oK0aHV8t8KUbCi6YKRIspN6yiiIgNehx3zw6iTEbRtkoWRhCJObZKP4+qfQCTal0qFlxQX8V+g2tIUBjXdWYyvgxyksbRGRp0bzn0L0Cf3QjicB630UUdnsRJuDaN6XqSlgf3rmJB/UXTqwOpW0TQ327aGEdJChaKUCw262b27Ct4FrsD02rbKyJ3Af+otc5Gr6uB/9NaH7+bj2/G8WK27S3FFlxbSLo2eT/ED/Uenyo50XmdsWI+Nzy8ddLzHb3uQbkH+GjxKurSaVKptCnEK2Qg1QRelr/n6on7/UgYUJA4OpKU30dM0eOATtIsAyWZRXwsIz2PkCZv6ja0ybxyJCz7ozwcFBauBaJ9+lWKBomk3EdLAe8gSlIrpRelrpAWChvFquB0jnfWMo9ONqlmvqf+iQedFVytv8gKWYfLcK1Nuc4HgbrFYLvkC3l+WjiOs8MbsFD4xOiROurqGqmO29Dxd2g5aIQ1g9ZQ6Gf1yX+a3jW57nZ6r3s/aTVQdnXZaPpI883Ux/nyZ6ZyWsyCCTriiEgIPIG5mV8LvEdrPa5EgIicCHha63sn3ZHIJcCg1vpro8bnAd/UWp8RbetTWutTReStmCzdr4jI24B1WuundujsRmG62VwtGKWeErxobBaToFKnaFL/9B6GiWoJ7tvQO+X5jl73X9RNhkjS1VEzkwDyPdC7ARL17BUfZC+1uVzMWJrfO3QdLgE1ksfHxsMhwKadJtIUSJHD0iEq0gCzI1IpwSUwYypki2pkkKpyrGJEocZOoLQNHRGJIOWCSdB8xLmJNtrpi6ysS+xrOCJ8mAXSBWj8KFg/ZiYa2AS2S/K0y1l65qWsjx3AVlppd9sMkSQcQ8bx9LBQYyFjZFs6n4RCPydaj02vDmTZSfxv8mM8q+dTcro9q+fz2eADPOi+Zuc/nFkA5LXWy7XWB2Hm0g9MsuyJwGt3dkda621a6zPGGb9Za/2V6OXbgAN2dh8lTDeb68fAAyLym4qdX7urO3+l45WsUzRettdFN/29fL7tmTw9kdjghu4hvvmndXzsTcvK64Ih24bt2+lQNTQ7gZkMBzsBy7iJREilq8llHeboPrK6qjzBhuKyXrexRLYjaDxceqWWrKpiHt3lKvKY9kcE0ys5wiYkwKJWcuVg+VTFj9NBpS6XqYZX2DKcW2Zrn1Z6aJY+isTI6CrOt25lk2qmwcqYOJBEAXhtyiGLVgKdmkeqqgGWncSJAGd8PpKyEXBt8HKmmPHoD8NjP4fsIOS7DashFCRJ5hcf4RbrPGh+HV867aBJLeQ79XL+ml5F96CHFypitkVTbQw1XvbXLHYWdwOHiEgD8ENgCZADzsdkzH4ACEXkX4CPAnXARUAM6AH+WWvdEW3rUBG5D2gCvqq1/p6ILAZujYirDBE5Bzgc+DnwVuAEEbkIeAfwK631imi5pcAvSq8nw3Szuf4TOBfoix7naq3/ezrr7ukYLAZkCz6h2vFb1VIleSVeyTpFpfPd2D1I16AhEjBz2SN/uYHNl78RvnEwfd95M7fe+GM6s0Zo0ArzpnK+EEDoGQvFHq4/yViNxCSg1vGJ2UISjxg+3+DdrHX2Y7vVSq56LwZUlZEviWrWS02kKqGwKEbaxQJkdRVJvGHxxJ3E6GyuABsPU9luE3U7EaciuG5iEA4hTZJhb9nCVeGpZHXSyNzryLQxVESnqmFjVo1o57taHcpX5Dwe6ovR2dVOn91gml2d+FnzXMyYz1MFhGLRVRDyyuZsffO0pOEX1Ffh2BZLmtPs11rDkuY0jm29Yq/fFxsi4gBvwbi8vgg8orU+BPgP4Mda6xeAK4HLI0vmbuCvwNFa68OA64HPVGzyEOANwDHAxZGLa1JE7rObgU9H+3gOyIjI8miRc4FrpnM+k5JJSYMrYs0XgJ9Ej43R2GTrJkTkARF5TESeFJEvRuN7icj9IvKsiPxCRGLReDx6/Wz0/uKKbf17NP6MiLy5YvzkaOxZEblwOie8oyj6IV3ZIpt6c2zP5MnkfYJweg2VXg46Rauf7uSsq9dw3GV3cNbVa3ZrX4mVxy8hk/cZKI4k0BOsR7nEvgYvsx0S9Qz1bOWT/tUcpx/lxsQ7iEtoFGyzBQIsgjBgs5dmQ/cQ2UJATaqK51lAj9RTK0P02/Vcqs7lYfc1/KH2nbRUWRRyWXRUqGcmZFON7jMcuC4FkYNItrFAjLgE0bjeac+WaXzllPelKBGaRYBjak4A24ms1Ii1zDGaFzF87lTL+UywkmfVvHJgvYjLZt3EoE4RU0WeKZimVaXY0+3+wXyh7iucVXU1pw1eyGp16PCBhQVCiVEkhh8oWlUnrbqTA4O/8/X853mtenhSl+vL4fp9hSIpIo8CDwKbgB8Ax2HmVrTWdwCNE2ggtgF/EJEngE8DB1a8d5PWOq+17gb+Ahy5k8f3feBcEbGBd2KslykxlWVS2shDmBMvPUqvJ0MReIPW+lBgOXCyiBwNXIZh2n0wVs77ouXfB/RF45dHyyEiBwDvwnxoJwPfERE7OtFvY5j9AOCsaNndAq01eS+kZ9AQy7b+PJmcjz8JsbzUOkUvdqOiE/ebQ3M6PmJMMKq/Hg5DKsaGnhwDoUsQtdd9OH44V1Z9kIzdSDwY4HnVSoY02nLwg5Ce/j4s5ZE7/vN8teVrnBm/ko/Hvsi9soK+fMDPe5fxh0WfYltQQx1DdOk6fhKeBGgcQtzIlVVJFDF84lHdR4wAhZQD+LDj4ZJSiKXcZwQjCOkSlCs1LA15f+y1YlKbhaKOZPXVck7xL+O9/qfZrOewRTczRBUJKRKTgCu8U4BpxOPuXUUgLn6UsCBobEJc7VMkRr3q5QLvauZ13T3p9zmrs7VbUIqZLNdaf1Rr7U29ShnfAq7QWh8MrAQSFe+NvnR39v7o15h59VTgIa11z3RWmjRmorU+NXrea0ePRps0sSg9Bjd6aIwZ9u5o/EfAJcB3gdOi/wFuAK4QEYnGr9daF4HnReRZhhn3Wa31BgARuT5adpcyEqaLgh9S8EN6hiDmWKTjDlUxh5gzkp93pa/IruKlaFSULQZYAiqSAkGbfu79pBDADxVKw5CK0YJx9T4cP5y/ynK6skWa03GO049yeuHXtKgOtsscro+/kwvfcCbXvQG++ad1rLrjWSwBxzJuw08+0szr5FRW2rey1NrKYdZ6FIKK6lAchoUgjRXhohFqJI+Hg0uAHkEouqLr1cRQmL7uDoZIwnIK8LCLzVS+m/07BCgtZS2vkkUzoKvYqFsBY8WttG81zcFIgtbUW4Ns0XP4njqVv3IYMI14XP9GunQ9jXShUThRhpiFUUL2JYFSec6VWzA3uONj3Os36l9D/0YjuzLNXiezmBR3A/8MfCnKuurWWg+ISBaotFBqga3R/+8ZtY3TROS/gRQmcH8hVOgVTYwsw2UgaK0LIvIHzLz8vgnXGoWpihYnDbporR+eYn0bY8Xsg7EingP6tdal3MctwPzo//nA5mi7gYhkgMZofE3FZivX2Txq/KjJjmd3wQsUvYFH75CHa1uk4g5VMZuEa0+98m7ES5EAsKC+iqGiT18uKGdPlfq5e1YCSwTbAlcV2C5zjMUXpafGHIuka/OwHF5WtNVak8n7lHyYV961gVBpcz8v4FgWr5NHuNS5Fg+HJIVIMh6Ms2lkpm+ITZeuJUmROdJPiJSne8F0V7QlmuynIBRT3Q79OklairioEX3fgRFpvk4kTVLabKeuJUuqrJ9VUlEuNwfDIyYBF/nnlklk6ZxU+XOetF6kbhHF/g10STP1up+Y+Cgt+AhNZIiFPfg4zJXitL9bYET/mhHS9HxtllB2DZcAPxSRxzEB+BJR3ALcICKnYQLwlwC/EpE+4A6M6G4Jj2PcW03Al7TW2yrDBZPgeuB7IvIx4IwobvIz4O3AH6d7AlNlc/3vJO+VrIyJF9A6BJaLSB3wG2C/6R7YTEJEzsdkR7Bw4dR9rHcFfqjoz3n058C1LapiNqm485IQy0vRqOjCfTYTtK+iJd7Opkgb6qrwVC51rkVUEZ8YrvZwtc/V4am0Z/Isbalh5fFLWPPHX/DmzC+YqzvpsFp43D6Yg4LHmU8nXLuMxxa+h5wXHbuY+LQXKla6w+rDLmEkI69wRzivjBWgEVqlD5sQDwcfx4hTYppxBTikGYKypTIxStutk+F+6aP9xoagTGzEjY7FixIEGiVLr67lpvC1fNa+jn2tLQhGmr5d15PFnOv59q2s9pdTm3T47MnmJ7Ty+CVcfPOT5LxgRL1IOZ7x2gtIbv4IeWWz1ZpHm9qCKz6WFhxCNDYJCbHDQUMQ0yWCSml6MM9eND5LJtOC1jo9zlgvJkt29Pg6TGC9EjeNs9wlE+zrBeCg6P/VwOro/2uJMnK11vcwNjX4OOCaaA6fFiaNmWitXz/JY1IiGbWdfgxjHgPURVkMYIJJJZNtK7AAylkOtZjUt/L4qHUmGh9v/1drrQ/XWh/e3Nw83cPeZfihIpP32dafZ2PPEF3ZYjmY+WLgRQ+grrudQ5/4MvulcmQkzZxIxdcS4cv6vXRRS0oN0qVr+U99Luuqj6Yq7poqeesxPjj0XaqDXrqCJM3+Fs4qXs/ccBs6Uc+WzS9Qf+d/lBWBKz/CkvqwIPg4pmo7kksp4lJKDi4FwuNRydSQjpHEK8c6ulU1H/M/TBiF42fqW7IBJzqmIg4hFn4kU7KQDt5n38Y+1rZy5lkcjzbpps7KU5Q4C6wuEq7F3JpE2eU0ZTxj2Um0H/tleqSBtM6y3ZqLxkKLucmJ20ZBmETDlD1KRmAXpOlnsWcgKgE5G9iBC2OadSaR/PwHgVLF+2rgqkiKfqJ1mgFfa90vIkngJExQ/S/AGRjT6j0Ms+zN0ev7ovfv0FprEbkZ+LmIfB2YByzFSLkIsFRE9sKQyLsYjsW87BAqTbbgky34RqAvbpOKGXeYVFYqzyBO3G8Ol2JiJ1v6crRNIucyI7Iv0V1rKl2FPZhFu1WoMM/79S2827+I26MbrJhtMa8uQXVFDOfQ4GtkPPCtBKI0NeQINdTZObpyGRp0Hy4+q5wruCD4CHeq5eXJvuRGK5Kgmzrm0o2NjnqDKDQWnbqalBRJ4KMRsjpOvRh3XylAvdDq5lJ+aCZdpm64NSlGVdELpcwyRQKFh8bHoipyM5kkAeMAEwQLRYPuJxSbXmcu+9SkyeRH/tymiscd+oYzWT3vBD4Zff+3FM4hbQfY2jep16lmiNeQ73qe079xFxu6hwDYq7GKC9+y//ixkkIGBraBk4D0HIjXmALJcfrXzGLPhNb67Tuz3nTlVL6PcQ//KBr6VyDUWp83yTqHRMvbGAvol1rrS0VkCYZIGoBHgH/RWhdFJIFJjTsM6AXeVRFc/xzwXoya98e11r+Lxk8BvhHt44dRPcyk2BE5lR/89XnuWNvBgfNrOWxBHfvMSZu7uRmEycSxo4czZvsvhrbXlLIvkwRcK4/vRu8DJKubqE66bOgeohgoglBRJ4Oc4K0q1520VMc5Of73cpB9K83szRY6dAOWZYzlxeELJn6hFSoKWSuMAu823cjFwTllafVSrMHHIU+MedJDHYOUaKJPp9hGU1SfEjCk42WXUqW2VWnmFxgT+9hhjCPJoiqi+kViWGhiBFAhBRNjOK4SYLNdN/KF4BzWWCvYqynF7z6+CwpG155qYhyxYTfn0GCWpwaTvDP/H2XrTYB03OZbZ60o965Z88df8K+93yImIY2SGf5s0lFzr7fMxkzGwe65S3yZYrpk8liU4jvp2J6AHSGTf/7+Gu55djgrLhW3OTgiluUL6th7Thprhq2KhBtZLHGbe9Z3vyjaXmddvWZMbKUk3HjdidnhgKubNHehyoO3fI3V6tARx/elzL9Tr3pprDO1EBt7cyR0gW7qeU/4ebxQYQm80X2cL0aT/5CKEaPIPN1JHzWE4tJIhgQF42jSxnWlort1H4d23UBMe9RKjrQUGNQJ/qQOY570sdTaSjU5enQ1vdTQwACNkmVAJ3lWt3GvOoBT7AfYX4xbZpg+RhLJLlfDVwTvdcVQCaOLHMGQTQjlIscccTapOaSlwFbdzNXqVNJxh5XO/7G320Oyea9xM6lKBL++M4sXKFxbWNZSw4X7bObQJ7484rvs6B/g3wtnc0e4nNHYryXNhW/Zn4tvfpJVxc/TqPvIE6dKDTHXyeKoIsRScPoPZolkfMySyZiFRB4Gzoyi/ETWxQ3TKbF/uWFHyOTWx7fxxyfb+dsLfWzPFMa8X51wOGR+LcsXGnLZqyk1o+TyqV8+Rm/OIxV3ytstT/LnHz1j+znusjuMpHzFsZeyqO5u+TpkO8iqGF2DRbzA9CBPNc7nQ84XR5DQiuKDrBz6DsqK0dbcwIb2blzt84XwXO63VlAVs+nP+/zY/hJ72x2k9BCuDvDFIa8caiQHCEoMcbja1GV42FFqbRhVbkAchYdddmVZaFYFp/Na66lywy0wYfQEBXxtEiCWWlvxcYjjle+udYUZYSygita5u4jxiGQqKCBLiqJ2GCBFnhhVeNTIEAIMWWlyOkaTDFCrB8hLFbp5f+rf9KkywfthSHfWK++4MRUj5th86/BuDt30IxPjqFvIv209gRuzBzBanFIDccdixcJ6OrMFfjZ0PlnSIILSGte2WNJYBYV++PjjM/BJ7UaoEEIf3MTUy84sXlVkMl1trk8DfxGRUrnsYkyZ/Ssapx4yj2OWNJLJ+7RnCjy6uZ/HtvTzyKZ+OrNFsoWAe57r4Z7njPVSk3A4NLJali+oY3Fj1S7FQ7Zm8tQkHPxAISJYYn7gM53aO2nWV/9GslSzdSBvBBMtYUi5WF0bWG9naa0Z/oE+HD+cK/kgp+VuoK3QTy7WxE+t0+hKHcUSYCDv05/z2Ee2UqMG0ViEYmHrkGrxy3EFWys8YvTqOM0ygIvprBhgEWCToBQ7MPZDiA2EfNC5JUoLVvi4dOpaBqnCJmCx1Y4fBb+tinoSDeVXxirREWFpYlP0M6nsfaJHjBuXVZyQYlSFEivLtegpZxgBMiqJJ7EyKRZIsJAOI7+iMuWdagGtc7R3bcb69QX8ong2W72Dyy16HctCKU22ENBa6/DZx+ZQn7qIzcUcC7wq+qqK6OzghMdSSi/vsFqoV70UMendXqBevrGSMAA/B0HBHGPoG9eeO6W6yCx2AVPVmRwBbNZa/zkS/FqJSV/7I6aF76sGrbUJTq5t5eSDWtFasz0il9Kje9BjoBBw9/pu7l7fDUBd0i2Ty2EL6ljQkNwhcplbk6RnqEjStdFaE2ozyTen4/QNGYtldJHkzmDSNNM1i8hsfgEhVraOkuLRIS14gSLvhyNI6B45jPWtx3Dd+UfT/XQn9978JF62QF/OpxiYqEFcApMyqwXRxr1jAmuaZ/U8Km/o8jrOIunEVLTrSE/XTN4OIWFkX5T6kuSJoREcAuZLD1s1zJMeLDQJPIx2lxNp+BpJeDsilRDwcLHQWBEhuFMQCpjGV0Ek6QgWAzpJN3UspJ24hNj4DFPW5LerXlT0OMfKsF7PL483SR8uY7M0RUNcfCwd0lWwOVvfxB3WIRQDjQ41gsYSk0IdhIoXevIsVrqsiDCQ98tFpiWLpATbEqrjDnk/5MbEO/hA7rugC+R1jLTlg7J5bOF7+Mok/WteFIS+IQ+/YJ7VrBDldCEiJ2Oytmzg+xVKwjuMqSyTq4A3Rf8fhamo/ChGHuVqTNbVqw4iwry6JPPqkpxy8Fy01mztz0fEkuHRzf30Dnn0533uXNfFneu6AGhIxTi0rZbDFtZxaFsdbfWTk8u7jljAqjvWk/dDEq5FwVcESvP/Dl9AX86jLzdcJJmK28SdnatlmTTry7oA+fmHSVqaoo4Tj2QSf5N8B7G8lFOPx6t1OHG/OZyxpZ9vr36OYmAmZdsSitomEbmySim8xsKwSOJVuKiIAtSVGI5tiLFtUNi4KEKEDl3PPOlBR+H1edJDPCIds7zZptHnEp7Xc5lLD46ExAjKgo/ToXyNEEa5X3ak+fUB/xMAXOpcS4Y0TQxE5DR87JPBISRHApdwxGfRRGbCdZQWGujned1qZOy1YIk2EvhK4VoWMduiI1vEtawRighg4nTtAwX8cPj4bMtY2l2Dpgbnr8nl6KoP8Pb8r2nRHSQbl/DYfufx0QebcO2Rcj2Xwu4llJLl4echyJvXs9hhVEhSnYQp+v6biNy8s31NpiITOyqmASP4dbXW+tfAryOhsllgyKWtvoq2+ipOPWQeWms29+Z5ZHM/j0Wusb6cT++Qx1+e6eIvzxhyaUrHyi6x5QvqmFubGEEuRy5p4AKWcv3fNtM+kKe1Jsm7jljAkUuGNTZHF0nubPX9hGmmy07iJw0fHVFMeGPiHdwjy1nakmDl8UsmTT2+b0MvbfVJNvXmsC3T2+M5vYClbKSWXEQoFv26ik5dTypKlc0TI4FHo2Qj9V0Li3CMpRAnjLrAQ4euJUsV2zS0Si9xgjIp2KPWcyIXVK0MkaAYWSumsHC6MHpXpmdJgFPuoLjKuYIqKeLhMqRj1IrpY1KyqCrdY5UojQ/oKjKkqZYCgpDXbpTiPP56PkKMgKT4dNqtqEBjiRBoQygKTXXCZf+hB/ho/P+Y19dV/h4fir0GL1B8718P52PXP0LOC4k7Fk3peLmDpmsJ9ak4f+k7lPUtx5S/4w9dvQbXLux+uZ4wMKTh5w2JvArJY/GF/3cyJtywF/A88D8vfOUff7+Lmz2SGZSkmpJMRMSJ5E/eSFRFPs11X7UQERY2VrGwsYrTlhty2dib49FNw26xgUJA96DHn9Z28qe1RnhxTnV8BLm01iY4cknDCPKYDJXE4lhWuZYl4Vq7FLs5+h/eyQU3H4RrC0Go6MgU8cMcMdvcb4+XDFDKKHrghV7itmCLWVdp+Ku1P69x1hIieJiJslZyXBuezBN6SVmbaotuppZBhkjQJj0T9mQ3abRW2eUFJa0sa9I+7oG26dY1pK18ZF3sGCSqwndQuHgcYa3lNdbT2Bh3VQyPKlFReoCe0uIpZZK5EnKZ/y6A8mcRRNuwx9lODIVGUyuDfDX4V9NmN0qssS2hNuHwtvRa3hP8iKK2yUqaetXLB3LfZVVwPhsbjuXE/eZQk3RZ2DAyzpd0bTJ5n99/Yux3vNvkepQaJg9vyLixXsWIiOTbGPHcXmAu8O3FF/7fh3eRUMoSVhF2SZJqKkK4DrhTRLqBPEaMDBHZByaxu2cxAiLC4sYUixtTvO2w+Siteb57qEwsj2/JkC0EdGaL/PGpDv74lBFAbK1JcOiC4VTkOTXTz0YJlGIgrxjI+2ZC2bqa6oe+g5XZhOygOF/JDfaV363lhZ48tgiOwLrOLCt/+hAfPnHvcuMrGFm3knAsCkFIpbjya62n6NR11EqOGAEeLgXtcp59GwOk2KKb+XxwLneq5fzc/TLN0k+AFXUqHB8ZnaJBsuR0gmbph8j1NFG9SBELWxTLZCs+dkRFO17zPpzWS0RIOornSCSaMtYqgomtEwHcqBb4TrWcu6LizI/YN3KBc2MkLKnL65eysHxstIZiYKgLy8SjLnjDPua7ufabDPkpNg+Z9XLEcULNabkb+GL8cFY/3bnD8jszJtdTJo8o5hF6IyUOZvFpDJGUWDpXMb6r1smMYSrV4P8UkT9jmPCPejiP2MLETmaxE7BE2Ls5zd7Nad6xog2lNc91DvLolgyPburn8a39DBVD2gcKtD9Z4A9PGnKZV5cYYbk0jZJ7nwix5/9M6q7PEVoxAqcWe6Ad67Z/A76Gtewfpt7Auts58Y4v8NrMOnQMNqi5/K8+i79yGKHSfHv1cxzSVjeig6IfhvQMBuS8cMwU3SZd9FBDr641BXKSZ650YQGb9ByaIxmWi4NzyrpedhRfKSnujkaDZNEIzfSTxCNHHKPaa9KIx3wmKDwsCriRVPyuYTjNmHIaM0xsiYw37kW9T+ISsNK+dUSV/xXh6QCcZ99GteSMFSNmz6GO+qlo26znLyfhCE1pl/s29PIxgP6NpFL1zHdCtg8U8PyQQGIssrvxlebim5/kjBXzueHhrRPrfY3ClPpgE6HS8vDzEOyg2OSrD3thLJJK5Bgp8rgzmLYk1XQwpatKa71mnLF1O7vDPQ22JYjIbtXTskRY2lLN0pZqznxNG6HSPNc1yCORW+yJrRlyXsi2/gLb+tu57Yl2ANrqkyPIpSE1vtp07SPfRVsxtGvuGEM7iVKa8M7LybQcX3aHjVvdv+52uOlDkO81U7KGvWUr/y1X8R/qA9wtywmUHuEnX9+ZJZPzsSwpu4KGzxW20kyzZMjrGBqMJaGhEOlVlYLOK+1bebd/ERcH57DKuYK05Cd1E2mgizri+AzoKmrEqPaGkcVQCYFI1jEc8960Mc5qJWshwMJifKtkNFS0ZhhlhNmEtEnXmOWuCE/n2+HpaOBv8Q9SzxBKGwusigJVUiAlBVxbsC2hMRVnfWeWs65ew6cGamjJ9uIm0+UePAk82qWlHOu4b0Mvl771wHIM7B+TT7IyeSv1v98Ga8Zas9OW69F6mDhmLY+dwfOYG/pK/2FVNL4r+BszKEk1G/eYAnVVMeqqYniBwguVeQ4UfqgmbYy1K7AtYVlLNctaqnnnEQsIlWZdR7bsFnvAXTxFAAAgAElEQVRia4aCr9jSl2dLX55bH98OwKKGKpYvqIvSkWupqzLk4g5sRsXrRuxDO0mcgc3kvICcF9BNkWQk6ZKK2ThRPIR7V0ExC2IjAmHUSjZFjvfJLdyllo+pffEC08PcEkGPag0Sd2x+oP+Ji+UabAtyxIjho0XoUrXlbeSJlSfUO9VyLgg+wqXOtTgEzJXeMfUdAtho5kovQzpOs/SjsIiPyQar+AyidWYagnF59esUjTJxDUfJBSdQLqE0sR6bLXpiQVKT5WbSjUsWUKkfSzV5jtWPcE94GD1Dxch9WuCmqjM4f/C7ZAcyKGIkxUjLXOGdwkDepzrhsKUvN5yIse52+N33IZxcan7cxI1K8ggiy2OWPHYF/4OJmYAhlCogHo3vNKJWHx8B/sCwJNWTO7u9aVXAv5KwIxXwU0EpjRcqihUE4wUKtZs/0yBUPFMil039/H3bQDn1thJ7NaVYvqCO12/7Hkfpx6iLD9/Xi58jSM2h/W2/GncfcdcmFbOpveo1SHY7WDahNkRRqvHIkOJZ3cYiq5ve2FwOOuPzsOwkDvrC7xgqqkmn6Tc6j/Gh2G0ckOwjGWbBSbE5SNOXM/GCJEW6dB3v9i8qr1NqHHWYtR6JBBxLBYyG4kqqwaaPSRGXBN5LUoYcRsfiEI6bBFA63pJeV4gNArbW9Oo0nwlWlrXHSijHSIAHEx+knswIyRaJ9vs3tT/v1Rejgfoql+ZqE2ub23U353IzbXSxlTn8QP8Td6nlOLbQWpsYqawwjo4XXg6cGCTrR+q0LX3Ty588YlVQ86IXLc7YpbebsrlmFLNkshvgj7JgisHus2JK+3t6e5ZHtxjL5cltA8Y6qICg2Nfp4MjEFo521nOksx7/xIvIL5q8k0Drb88k0fEIohWIRaA0YWg6dIDFdplDnhgpy8dWHl8Mz+V2f2LJttKE6NrCR18fBYejhktd/YMk1SBxfAIsvh2cVo4VVOIE61G+6lxFteRJRnLypZTbytjHC7qFedIT1b2/eNe5jvbdKkbpuBQwh+HZZZNu4uLgvQB81rmeJWKsyw2qla/zblaHy8s3JWrUodsC1yf+ixXRTaRoHdW8mOy4Xl3DyVyBJZrFjelydtbT7QNYAqEyVqMZ1oQK5tUlR2q+feNgY5FUZgEWMpDZBHVLwE0wNJgllx/i+9aZdDa8hncdvoCjljTO7Ie5q1AhDHbAYDtUNcA+b5p6nZnDrJzKLHYNrm1FNR/DY6OtmJLLbCbI3LUtDm6r5eC2Wv716EV4geKp7QNlt9ja7QP4ocXTwVyeHpzLjzkCQbPPXdUsX/AcyxfUcXBbLen42Mshc9gHif35E9jF/rJbyLIUSgs91ODbSQgVOR3HVYpzuYXbGSaTSheXbZnsrqZ0HMeW4eDwspNg27upXX1Z2W0TIpzt3M4TesmYO3QYOceV9jP6l9sm3VHsYvcQyUQZWYM6xgLpLicr+0hEKMKATvL98JQRJHmnt5yYbVJ/Q6WjOB2kXZtBbziDzQKSMZvm6ji/Dk/nkMI6hJBQbESbMs2MTtFhtzA3nWBLX57uwWLZMonZFl6oiDsWzdVxlmXXcC43s8DpIpXem3rrU5j6NYzVUbJMItcmA9tBHLAdBvMFOnIhcS28Tf7MV4YOYtUd6zm5Y4BHNmdoz+RprU2+OASjtdEI698IfZvMc/9Goz+W2WxiNADzDnuxyeRVhVkyeZFgWULCGllMqLUeEYfxQkXR33U3WcyxykF5gKIf8mRELo9t7mft9iyBgvWdg6zvHORXD23BEljaUs3yNiNcefD8WqpiDvlFb6DrjZdTf+9/EctsABGC+mXYuS7qU3MZ7M9jW6YSPiQ+JnBcTv8TOGDucCtrrfXIeoS1N2Nh5ExKVfF1DPJZ53ru9EaSyUr7VjI6RTsNLJHtVFEYd1I3kpC7r8PlRLedaRntWrMIgGf1fE7xxlerqK9yyRZ8QmUKDm2BgeLIVGgFpGI21QmXv+sj+ZF3Ou/jN1gqoIDDAGmwHW5NnUlVzKEh5dI75JOKOyRdm+qEQ9egR03S4Xh5lPOtayjoaL2erSRu+gTJ0y435H7Uh+D3nzE1Hk7c6FwpD9LzAE1fzpxjIHGaVDcJ1yHvFfnZ/ZtorU1QnXDpHSqy6o71XAAzQyh+3pBD/0boi8iiRBzF7OTriv3yc729wjBLJi8hRIS4M1YGpdJNVrJkArXzbrK4a7NiYT0rFhpp+Lwf8uTWTFn+5ZmOLKHSPNOe5Zn2LL940JDLvq3VESkt56Az/kCygghbf3smzlAnfqixxZBDkuKIwPF4IogljKlH6F6PiF126ajI1ii5f0rxkjbpYo70s13XA3E8bZGaYFYvya342OPqWs0ExnOvyaj3S2rHpXOBkeezRTdzbfGtPFd3DHOqjarA+35sXLGWwOukYtliM9d2vZU/B4ewKXY6Rx3/Jg7d9CMGNj5Dl93KjYl38HD8cFYUH+Q9/jXMc7ZiZWGjzOPX9e+n6sg3c9+GXv5p+w0UtINvJXAtIacENZSn5g//RV3T3tC8DF73aXjkR8YiqZkLlgPKJDR4gcK2hJgu0m01AURkCAm3JNPiAAHXP7h5+mSiArO//kqyiJ4HO6ZeP9VsxCfrFkHtAqhfbF43LYX6RdM7hlnsFGbJ5GWI8dxkodIUg7BMMnc+08XP7t/E9oE8c8eRWZkMSdfm8MUNHL7YLJ/3Qp4ok0s/6zqyKA1rt2dZuz3LdQ9sxiHkEGczR6S7OPDgFcghH6Ttns+RthRD4XB20FXBqeX9VJKI0rC+I0tLTRzHtsbWI0iUhq31CMFBzXDzKw+HflI0kYlEHIUaGdsaYMRnSUhOxwnFSK/sDif25OnKEmWaqUjdePh8HAJqJMdc6eUw/pef5s4gf+gnuequDYTK1NO83n6ML9jXUtTm3Juln8/xQ4qcw52F5Zzx5xQfff3Xuc/rLRcQrig+yMcGL6eGLBqLmCUsZSsXFr8FC/fjY286ic5LO8lIkriEWFqDaAJtE/ZtNHUgAIuPNY8SXrgH7roMfIjZgoQFHFHcHje1Sl6oiY8SHo07Nh2Z/KgPRUOux1gZfS+MtDAyW8qENSHclCGGSrKoW2SeY6nx17Hd8cdnMWOYDcDvgShVmDuWEenLeaZY7JNvWsqKxQ27HIcZKgY8sTXDI5v6eWLDZp7p02WpwhJcS3NgA7ymcD/Liw/SYA3y/eBk/jJOkyWIJh8BP9TMi9wg2WIwrDR7x9ug+xk8FWU4aYVNSFHHiEkQTcaCR4xBHafRGsTXNslICXi8CT3EYpNuIsShhiEKuMyT3kklVnYUE+27hMpGWz4WD6r9qCNLrQzRJANoSqrJCsTmc7HP8kj8cDZ0D6E1ZQWAAvEywSYp4uPQr9O0SRdbaeaG2Nv5be5AXMvi57Evs79ah6BxbRtbMAQhFsw9BN5+JX+/4p00MIAncUKlCJTpPd+rq/n7kZdx9jET1MO9cA888iMKvVt4tlDL792TWJc8hGIQ0p4pUJN0aYjuguK6QF1xG/vEejl7PxlpZXhDk3+wlgO1bRFJRERRIo2qxrFBs6mwh2dz7QmYJZM9EJN1Rvz5+4+a0ThM6rq309nTw4N6Px5Xe/F4uBcbdMsYchGMZaG0HpN9BFGKajpOb85jIO8zvy5JVcymECj8UJumTQ/9B0FhABUGKK1xUPTrNI2SLU+kplbdIiNpavVA1INxrLuplFE1iHGllVKNAY601u6W+pLxUCl7slHPIcBhsbRHEi46asSlyhlng5LiS/FP8qvM/hxvPcqV7uXYBJHmMRSIMaTjNEqWF3QreWIk8ahhiIxVR5XO0UQftoRY4oIIoVJR9CgkTDaTeN9tXPWTn/C2zE/wsBlSLgl8XAJWBafzEAfwnmMWTkwoEe7f0MMv//Y8un8L+1dlOKy6n8z255inO5mrO6nT01BcSreMtCxK5FFyq80UZslkDETkh8CpQKfW+qBd3d6sm2sPxGQCezMeh+nfiCspjrWf4VieASATxnlet/LbBZ/h4U19FHxTUxKMxyIRBvI+zek4Q8WAINSR5LnCtS1qkg6/fHAztV6KuWEfpWrwHl1LreTKMiqlbLJAhFoGUWLTq1M0YIKv5u7fKP92RI2xSigVQSbFi6bl3Y8iViTCCJ26niwpqskhaJL4Y9oDayChC3w4fxVz7OM527mdGH5FxxaI45OSAh52WSnAJqBeslTrHNulFYl0wbQO8LVdLqJU2DxbqGVoQw/Ljz2Fa273+IfCH2iVXtp1A9eHr+dROQAL+NVDW4bJRGsY6q7IkjIB8KP6N3HUwFbQoVHqm4g74tURUSyGugUjrQ03uVs++1lMC9cCVwA/nomNzZLJHoidEdibKA4zTDDhuPUwm3UzzdJHkeEf/RyrH61h7fYBlB6WVp8MoTbZY6XljlKPsNK5hTbpIptP0GQNkLPSbLQWEtMF2vR2Qss1vUe0jVuWkzdbcAjotZro1rUEoUOTZKIOJcIm1YgnI6VlkngM6gQt0rvLOlxTQQNdqpqiJMrJAllSzKGXOZIpk8d4xxFg4eHwAecWYhUS+ohphFVKJDCusRALxRzpxzQEU4Ra02/V0ai7o66TEu3LFHnO19vouv1jLHvzh+Ckt/Fvv9nbvC9QLQX2tzYzl07mh53wh9uGXVN+fpyjrYDlVriiIgujPiKNRN2Ou6VeJiipX7+kzb8ALqkdU7TIJZldKlrUWt8lIot3/eAMZslkD8ROC+yNgm0JyZhNMmYDxtKpTFcuBoqf1ZzJewe+Q0L1Uc0QMXxCLH4TvpaBom8kU6LtlTKUqijwZ7WCG8Lj2U5TeX+VhHN/uC85HeNAeYGTrQfYS2/HowoPwZMkvjg06T68qIrcVJMHSFScJ9qmU1WjtKaLOrqpR2lFHUNcHJ7Lpc615hwJaJV+YgQUxI0q5w1menpT0bFt1K10Uce7vYvKMY80uRFEMh5K75me78XIuVXxRsTaGogRlnW/YhgxzZJy8BAJRJqo1z2AlNUCBqgmS5oavxP+fAlHLTqOf4930qo6WSCd1I+Wflk/9giLyTk8U6ynw2qhx2lls25mi27m3W88kqP2fgkm2d2ISvXrF7X512gYIhkjQc8ltR/eVUKZSczGTPZQlO6YJhXYm6H9rP/VxZwd3oCFoqhdMrqKAIeLg3PKEumVGVclP36MgIuDc8YtOhyNNDkOt9ax1NrOQbKBA3mWRVYXnbqOJin5T4QeXYOPE3UjDMhFrh4LiFdIsJxgPcpn7etYam3Fx6FD1zE/qoYPAJtSh8edR2XwXREp9+LwvG6ljiGO91ZxgvUoq9wrqCE3LfIKsHhBt7BEtk9oQQXRsW/Wcyjgskg6cQkIcLBQBGJjx1J0hWl+r4/mtPCPpMljE+LK1Blt/TqFl57PnAX7GiujlDFV28Ynbnya3qFiOf0XoOAHNKTiXP7/pv6eXzLsRMxkstjkeD18xsHM3K9cUltSbh8t9LidSzJv3JVNR5bJrbMxk1cxJuyMuBv2c2jj87R3tzAQDMdpEhTLMulgCgkNkZjJvVL5t7RM6Zf1K/di7lEH8YRewhNqCR00MEgVq9VyVkfLVpPjQHmepdZWTrEf4ADZRCA2G1UrV4an4ojwBecatB7uyhiT4dTkO9VyPmtfh4+DjaJJBihVr7iYCEQlGUyVlTUVwsiK6NK1xqVGkp+7X+YA64VpEwkYd9QiaZ/UFaexGMKQ+jzpIa9d4uJH4o/GFSaeRxt9nMfmCU5MwLJhrxN4fKiWP7Un2OA30eO28JbD950w+N6eyVOdGBmvGzf99xWA3db8a8exF7tHgn5GMUsmr3JMxydc722jizgiupwVVqnqC6ZHST+pclZXoPSYZRzLhNE9YpxiP8DreQwBsjrOJt3CGnUg96gD6aKeLFWs0QeyJjyQn4T/gCVQFbMZ9E3MIGYLl6pzeZ/cwnxM4d/3QkMkP3e/zD6yhSYZIIhyoZJ4IzK4Rs+vO0MmRqjRFEeqSLRxgXSjgSEdx5WANDs2yRpPltEOnux4qvA41H5hiuODDpqo1lkSFE3Hxyh2EUND/V7wlq9yCHBItM79G3q4/sHN/O7v940rh9JamxxjmRSDkJbaV14gfcaaf+06nmf3SNDPKHZ3LHIWM4jVT3dy1tVrOO6yOzjr6jWsfrpzl7d38c1P0pktjPAJl7Zb2t/f+quRID+ifiWJN6LafYtupgrP6G+5Ni01CWqdgK00D9dZKE2g4KrwVNOznCIazSLp5O323fyPeyVrYh9mdezj/JdzNW+wHiYWCTkqDYMV8iI69BgMXf6m9uUBtR9XBqdyEBu40r2cI6xnaIj8/6V+JZP1FSngYmFcVR42gyTwcChO8fN4Ui/ieT2XLFVYmPa9ARY2IXWSY4FsL7fZHRfjvBFGgfTKt0RGPmIS4sjw+YRayOkY/bqKHmppp5FNtNBJPRfX/ie9VhNKLLRYEVEJYxrNYIhk1R3r6R0qjpBDuX9DT3mZdx2+AD/UFPwArc2zH2redfgCXlYofViWDbZjEgR2ECuPX4IfanKeOdecF+xUbHIG8D8YyfkSi82IBL2IXAfcB+wrIltE5H27tL3ZmMmegcpgYGXQfYTS6w5iMp/wMUsa+Pbq5wiV5jge4YsTxEPu1ssRgX+IPcHXUz8lmUiadE8/D8rjsYMv4sP317MlM7Kb3kfsG6OugebOfVDHSIqPO2rSD7WwWh3KV8N3sTW2F3kvHLeOpZEMR1lPcZS1liPkafaVLWY+mcbn8ITeiyWyPQrwwzN6AWlytEn3pDIshcjV1CwDCJoiDm4kfz8tyLj/jovSzzREKBDD0w4/Dd/EH9URXOpcQ4NkKRJDxFiAMV2kiE3RqmaZWk+Ig7GlNCEOyepmQMF7binv4xO/fHRa8ZCS9dKRydOys2KOpewuiW41RExR5YSP6P3KZZFx3rOGiWQGsIuxyZnL8dgN2VwzjVky2UMwA8HAMTjusjuoS7pliXIw2VztAwWyBVM4aItQCNQYLamrwlO5Uy1nbm0c17YNqVmPmWZa/ZtMwDbqzHfW1Wt4aGMvx+hHWGnfyj6yhRrJ06OrqZUhXILypD3er88Th24a+X71h1h27NtJ3vZhtqp6HldLeFDtSw+1Y9ZpoZejrbUcbT3JMdZTLKRzwvklLDemUjP46x+Lqea30k+xgEmJNq43HfVfhG6dphdTeJmIqtX/LfgQR8haLnBuJBCHIjHi2qPaygFCjiSN9GMTAEIP9VTX1JO2fEg1wtuvLu//rO/dR3Vi7PUwWPD5+fuPGWfCH/3arjChrJETvGVH71tgvWocIntmPvROYjZmsodgdwQDJ/IJlwoaXdtCIm2pO9XyMVlZtiUsbkyXzf6zVlezue+TpGM20i9kfxOwoH4N6zoGOJZH+KJ7LZ52osJBExS3UPg4Jmg8wXG6OiCnbU7q/wUX37OcXzt/JxkOoGyLUAvP67k8pJdxnzqA+9UB9FFNBw3cpI7lJmW0pebRzVHWWo6xnuIY60napHv4PGZQXmU6N8S6/Gf4dYeuw0JRKzk6dD02AU2SxSEgROjQdQxFXo4UeeolS5t08b/Od7g+fD2rgtN5t7OaVumhnUYCZZNyNHXparKDUKd6EDTN9hCOVQ06gCPOh3g6muAdqurnsm3QIxGLMVAI6Rz0yQWKZMxldXfNS1NfMYs9BrOWyR6C3WGZTOQ6Gyr65L2QUJsmSnl/2NUjmL4Yodbs05zi9584YcR2BvIeXYMmqyhuCw3pGL1DPtdal9IsGXI6xr6ymRCJ4gwhATZuudJ7LBTCk3oRdQxxgreKR2LnkZQiIfYIKRIwbrF1egFr1P6s0Qdwv9qfDOkx22yjk2Mit9gx1pPMk9HJMpNjulbG+OdDdP66HE8q4pIjzm+DYznMerZclf6wWsr/s1eTFI8iLkM6Rp3kAB2lPDfgEvCfwT9zvxxmWgRo+J3zb9TVzaE6aSRVKA6Y/iRBARa9dkw/dxi+HvwwpDvrle+rG1MxYo69Sy7VVyleVZbJLJnsIdgdMZPSdkf7hNf88Re8qe96WlQHW/Ucvhv8Y9kqKTW4qopZDBRCmqvjDOR9qmI2r+NR3p7/9QhX2H2ygnTc5qbwQ/TrFBphL9mOS4DCwiWM+peoCQUYzeRrk9NxLgg+wv84V1IrRpbEYSTRjS5IVFp4Wi/kPnUAa/T+3K/2J8uwsmyKPIulnSPlaY6xnmR/axOt0odDuEuEMe7ylIjDJqOraJAsNsMtfrM6yeeC87hTLUchfND+LR92bo6stpK+Vuk8hU5dRyd1Zd2x98sX8ELjkrzcvoJqqwhOAtJzIF5j2u5Wt8A5t054jKuf7uSDP3uIgh8VRDoWNQmHbDFAa1ixsH7KuMHLpmr8pccsmbySsaeSCbxIhYrrbid/0yfoyCnyOo6ri7ja5+LgHJ5OHcWcmgTZgs+WvjyOLezTnGZt+wAnWI9xiX0NRT0ySP8lfS73chg/cr7MHOknE7ikyTFfeijdXWd0KhJzVCTGCXiHGDLp1dXYhKSkSByPyCNfvtMvpf5W1o6MtnaUhn6qKeJSJUXqZAr1Woy1MxPdGteqBdymjuK11lO8xnoaJ0opLhCjS9cSYo8ourzKvRxBEWLhEuBUHIOP0dwynSRNhfvH1CdJxR0+FX6fxriQ8HuHGS89x8iwv+VrYywSGL621nUM0DPk41jgWKZNc6XmWsK1SMcdvnbGoeNee7vrpmcPxauKTGZjJnsQpluouEt3hveuIplI0hiL0TVYxAsSuCJ8xL6NCxPHmgB9xvQQaalOIECVI7yfmylqmyIugo7SbRUr5SYeDPbhnsa38nH9E7ZliwyqGL0qTb0MUiRGu27gG8E7OMu+g/nSTY0MEa/QpRKgM1L8bSzLtpcmUaJoi9CvU9TIUDnNt3LyLVkZtkAjY7vyFbXLZt3Ek3oxz6r5bNDzeF638rxuJU+CvWUrx8hTHB25xkwR5PShgWZrgA/IzcRluC+8iojC9GdpKNflrLRvNdXsUW5YKQg/vD3BIYhiTkaV7HNyDeIpmp1BYn4kI2lZpj+INwin/wCWnTTm+jhmSQM3PLwV15ayRRIoon7xI2tztIL+nM9Xfrd23Gvqqrs24NpSdsdWxRxyXsBVd214NZLJqwqzZPIKw6R6QsuaMOJOatSjYqx3AyTqqLY11fWxaPkYLYPdHJA0vb3nU6A6aVEcDClkFPMFFlvtZKjCjXSiwNw9t0kHLVaWY157IlitpO79AdKziXYa+WZwJver/crLf0JuwMPGRo/ojlgilfpIit4CBnQV9TIYVbQbAfpGa1hbarz03MmM8Bg+e8t2FtLJE9YSEsojo6vYwFwAntPzeU7P56fK3NUvk80cLU+V4y5jdK1GQYBaBnBEjyBJo6tlHFeLpIu8drkrdgFzpJ8w6l9fqZpcWtchiLZh1m7X9STwabV6CZQLjm1IJAzNWr65ARjv+vj26udoSLnUJhN4ocK1BF9pfKVGEJhrW1iWoJXm+Z7xEz9eRlXjs3iRMUsmL2coZeS9x0z+lSQQdfKIXv/yLw8yV/KkbAtRGrEVRRVw0x09nNg0De2k6lYY6gE3MTzmF0g0zOdbbz8QgPN+9Dde6MlhW2Bb5hDadQMNkiXPsFpvAp/tqoETljVFdQjHUrv4WM75zl/JeSGeGlnQ164b2N/aFEmdWCMmz3nSawLWpaDwBJN3iTBGV7SP7neiGL9i15WQFbKeFdZ6PsTNeNrmMb1PlCm2Pw/pZRSJsU4vYJ1ewI/VmwHYTzZytPUUx8hTHGU9Te047jNnFCGUUCIKC01KPCz6AYWLjqjChOolWrtT19AsAxD1Q9mqGxmkijmy3VwKJRNChZTtGbHgd59ijZyHax88wnII/z97bx4nV1Wn/78/595be/W+ZE8IBJKIJiibKBAZdQRxGXcdR3EjqHxFHRe+I6MjoqMjoz9GcYRxFJxRQRBBoviVUQOOEBADEYQQQkLoTnrfu9a7nN8f51Z1VW/pLJ0g1PN6JdV9c29tqTrP+WzPE2hGsi4tqRgRS+H5mohljMwmnqOpl+0Pz6Cp8RqOMGpkcjgRBJhvc7i4TxsFTIoEqo5VEMdBer4PDQ9SH3PChl6DuC1z10466d1la1bsmOn+CVxzPISuXLHD2xv1OXzE/glKIKfNrENEPB5XJ/Cmji/B9SNGaO+kd/Oq9G5OG7qdRVY/ozrJI8EKPCwSUiAW6kuJTH791WFFZZShJ92W6ieVtZPKc0ydRYUCKLMjIj6nyOOcoh4HfkpBOzykj2VLsJZ7g7U8qFdRxGG7Xs52fznXcS5CwNoKcjlFbadOcuUGgekJZeL5RXEJjCMJPhJO1Ztoa1Cn6KWROnLY+HTqlrJvSxSXAg4WmsD3oNwtps0mwS/yodF/5gKVoifXXvaLj9qKvGeiwJZUlH3hZyXumJpJ0ddm04BGa1N3WtU6vT3u4VK0ruEvD7UC/IGiMG78q3UFccCBt/bME+Y6xTwrQmtWRruM491J76bSC/zt/3EvSmAo6+L6GscSzo7u4I2FW1mmTM6/Q7dyV7COc9UWlAjtqRi4WXBzBIEP2md/G12tQwFF0YieWZYkEFOgRwdhymtmrS096edDGZ9zUfja4q7gBTysj+G+YC3b9HG4k/ZoioATZbept8ijnKIeJ13pXV/ZhlZ6bgJaG5Owbt1Ep27lnmAtZ6hHWSJ9jBOnmRFGSZYbHpZLDwB2hTKwBrSKYjUshuEOvCDgSVlOXIo4eHw78UFuy6xhJO9hiRC1FY4l5NyAdMymNRVl71CWoq/xggBbKdIxm6/OUICHI6do/ReA51QBvkYmB4r8KIwfmibWfKKkr+RYxnGx4Jmd4SXnrJqz5EVJLqN7JDdF7O++XQNc8YtHyRUDIrbQmIhwhjzCW3M/pOQUH9Wmk8siwJoSYVRDa8FCSfMAACAASURBVNORlCXK//gno/A5Uz1MjggZoqSUh41PRBdoZHxGkshjVxXtZ8Nkh8ODRel+zK1JQ+V0lK16lWlFDtbyJ70SbxK5WPicKLs4Q5mC/smyg4QUpvY2azMNf5H7sXJr9gb1EBeGSgTjOgYipMgxTpyldJOS4sT1IXqoJ02BCC6BFWW3XohgrIx7dQNvLXyG+phN3vUp+IYwPrzhWD7y8uOBGjkcAmpkcljuWGQpxg6yHfMVuVZrfZWINAE3AiuAp4C3aK2HxGg4XAWch1HHvEBrvTW8r3cDl4V3fYXW+vrw+Isw1pNx4BfAJXo/L+jZTiZwaNpJM5LRy1YSyfXx/35/H21+D01uN0ukjyXSS7sM7fdb46Ow7Ch4eQKEPmki41u42CTI0SqjDOo03bqJh/QqTlJPsIBBukI72XdGNrNW7yy3A1fft+BhVTsTToPJMyiHAyVr3lJ32eT7zugoD+gT2BKs4d7geTyijzFRVAVsPNbJk5yuHuV09Rgvkh3EpYgGunQTe/SCcrvwTJ4xG61NvFDtmPY9yOHgSIBG6KGFSKqRTMGj6PqkGOPN0W/TkpqokR3qMGwNZTynyGQ+ayYe8Pda660ikgb+KCJ3AhcAv9Zaf1lELgUuBT4NnAusCv+cBvw7cFpIPp8DTsasB38UkZ9prYfCcz4A3Ichk1cBd8zja/qLwGlqO6c510NkHziLQL0beMl+r0Nrbr//UdbSwdKgn7Z8D+1BD21eN+139OHgcVLp3GnVDIUCNgVtU8SmngyDUk9BkrhaOLYxiTewCy/QZIjjiSahcywIrXRbZIRGGWeZ7uFfvLfxB72WnI5QkAjDxTRfc64mGaoIVyKPg41mmASNTN815IdFbLUfafcDQYDpJBNmlmRJSoGz5U+sV09iez5ft67miWAxD+jV3Bes4RF9DB42f9Qn8Ef/BK72/wYHj3WykxerR1kh+3iBGKXxjdYmbDyaZRQHL5zRSZQ10yJhh1eJ0kqdXjFcxnSCjI7hoWkc302r8lG2zRNeG82VXs7Uuq9qODjMG5lorbuArvDnMRF5DFgMvA7YEJ52PbAZQyavA74fRhZbRKRBRBaG596ptR4ECAnpVSKyGajTWm8Jj38feD3PdTJ56vemgK4ciNabzqy7vwJ8eqLu4eZgpGPC33toT/nnKwqzz0/4KLp0k7FrDYxl66vVvSxNaeLJOnqH8zhelkaG0WgaGWdUa3JWHbh5MjpGQECMImPapk2GsDH1h1JRvE6yvMf6JTe5LzPLoYZf6VMYCOpIqv6q5xMgPB20M0ya9WonLlZ5Kl4mnWcfRiKB0uyHnrEzrBJpMnzMvhkFrLB6eCVbAdPifH+wmi16DVuCtTyql+Ni84BezQP+agCcsClhc7Ces9RDvIDd+KKw8WmRERzx2RksZon0TRmtNLL6Dh9xL+Zf7GtYLCMEWij6YPlFGmSEVaP3srP+jPI1te6rGg4GR6SbK7SGPAkTQbSHRAPQjUmDgSGajorLOsNjsx3vnOb4cxsPXm+IxI5CUAwH1rLw2y8YM6ThPTDes9+7GZE6utUCeq12OmklE19Mn9XO3d0OeV39senSjXwidyvxaIEWp4jtGf+LQZpRuNQxTp0SSK7kW+PnogReVbyTVgawCXBReFihn7wQaJ9jVA+2Etxgwlt+aUgkpiPKpLYUAWtUR1UtZbq6ynxVBr0wJonOIlUP1WRT+dzqJMvLra28PCSXYZ3k/mAN9+q1bAnWsF0vx8XMbVzrn8+1/vnEKLBednKq2s7p6s+sYi/X+OdzstqOTVBuKAZjtLU7WMBdwXoGqCdNDisU1+zS9WixeUvxp3x8/IU0J6Pz2n1Vk1l5dmPeyUREUsBPgI9qrUcnyVtrEZn3DgARuRC4EGDZsmXz/XBHDlpDbjCMLp4ytz2PhG1QU9NBZPqqf3eS0Lgc6peWfb4fztTz9QcK+Ha8umbyklUA/OqnDwPVC+JW1nCVL3wxuZX46J/wlM2grmdcx4jYSZLROhINbfDG7/DIddt4rN/lSYlzgbqDBTKEFcqBBAi6omurRCSX29eVvUYmHluX0zqTn0/p59JYn4Umsp/FvhJziTRKKA1WztQYcKBokAyvtB7glTxAgNCv09wfrOGXwans0Et4Qi8lT7TsQvlv/huJUSBPlHcVL+Vj9k2sl1044uNiM6yTfMV/OwApcuzUi6qeqdKwTPWTKfjYyp23Avusw7TzTSg77gytEfZAw/JpRS5rOHTMK5mIiIMhkh9orW8JD/eIyEKtdVeYxipVs/cClXZtS8Jje5lIi5WObw6PL5nm/CnQWl8LXAumAH8IL+nooJidSEkN76n+ubh/bSmUA5EErHmt8RlpWGFuE81T5G+fD2ysn7mAb4vghT0OImCF1z+g18DfXATXn48dradNIFHwGch6dGagIdfBo70pBqSJdfwvn7H+myI2LhYRfOPfoSXUmtLktcP9kYvKU+5QvWDPZeE2dlAaL0x9zXWxP5h24cOVPqv8cAqaBsmwwdrGctXLSuliXMe4L1hjhij1GnbrReQxNY8t+kTe6p5IjALr5ElWqi52BEv4oz4BMG6YrTJMjokaSUwX6HPaSds2mz/5sjkNJh4MjprMyo474Y5PgIpArNEoJ9/xCWB6jbIaDh7zRiZhd9Z/Ao9prb9W8U8/A94NfDm8va3i+MUicgOmAD8SEs7/A74kIo3hea8E/q/WelBERkXkdEz67F3AN+br9cw7fBdG901PGpMjiumQajcRhh2F7kfMbSRlpqC1B2dV1Ez2g9NWNs/Y/bW8OVGefi85v/oBrGhKgB0xJDXez5iOsnfcRVDElcteaeezP/szmYLLP9mbKGJj4YdT3QYlFWCNkMehXrKHxWvEC6XqZd6SXXPDbNGLxrRI26He2ETrstCnjflXn65nkfRznnU/x6gu3scdjOkEn/Hey3a9AqUEP9DkiXKfXst9/tqqx7jMew+XWj9imfRQFIc4ZtbkG4XziEYVvVtvR937DRjaQ4du5Vf1b+XUV76Fl69dMO1zPpC01VGTWbnnKkMkkbAGFElAMTxeI5PDivmMTF4C/B3wsIg8FB77BwyJ/Dj0G94DvCX8t19g2oJ3YlqD3wMQksYXgD+E511eKsYDH2KiNfgOnunFd60h019BFCXieBpGO0P5i1kQSZm0VMMKaFhqQvaG5WYBd+IT5+1n6PBgcd+uATJ5F19rPB8KOsKp9g7eFfk1a/0RuHUlHPtXsO2HjIyNIdopD8fdGn8Tjgiur1ksfQzrJCukmwBFAcEJF3uN4CM0SLbcajudNEol9reXtgjK/iFHE9PVcYpYOAT4QIBFMXwvCCVW+nVdecJ9jAT9up4keRrIlGX+H9MraEk6NCYjjBd8RnIuWmtybjUR79KLudD7BAlynCQ7WSldbNfL+KNezbmZ+4j+6npGikKOBA16kL8d/Aaf/+E495z6Wj5w9rFELEXENn/ueaKfz93+6JzTVkdNZmV4j4lIKuHEzXeuhsOK2tDigWIucyaFsYroIiSL4afMrbsfWRPlVBDFsonbxhUQazhs3tYHivt2D3L5L5+kNydkdYScdjhT/YkvONeRTCRorq8v+76z7h388e6fsZg+etSEbEfJEvibxc/RzBDLpLes+KvCdFSUYlU0IlN+oMwm+xs+DIACEUZ1nHYZOeDXfLjqIJOfk6r6XfCBUZ0iJm5Vy+8IKZLkp50rKfvLCCQiFmsW1tM5lKWtLsbbTl7KDX/oYCBToGNo/zI6InCKbOcUeYw18jRLpA9LNHExPinv8v+RL7z2RE5d2VS+5uM/3sZgpkAiYqPEiPfkXI/2uvi08ylHTZr+uvNNaiuMTMbyHiOjI/Toeq5c8K/z3QRQmzOpYQ7wXRjprCCMpyaIIzuwn4vFaCU1LKsgjOUm6kgtMH7ZRxsiRpvLjoET5//b2seTxQa0gLKEKPBB+TlFHPJFm5GBLEUvIKV8ko/+hisX/Ou0O9FVbWm6Gy5k4SNfDFVxDXEImj5dz7JQEqTqWyhVN6GQIWWp+Snnl84DitihKOLcME6MJPnw+pK44uFBifwqn58KVQOaZIxBnQbRRHBpljF+5J3Dw3pleY6kFIlUTsNfHP0Fy1QfTnAM1yTP5/axtey691b+YfgGltDHU05L1TWVsJXgBUZv6369mvsxrciNjHKyepy18hQnqyfwfc0Nf+ioIpOukRx1MZsg0JS0hS0lPNU/TvdInqitiDqKqG1hKWHD6jYuhyM/SX/GJaZGUoQx32FgZJgIHrcl33RkmwCeA6hFJgeCbTfCth/BwBOmvqH3k8+P1U+NMBqWm8jDjs1+7ZGGiAn/7Rg4CVNzqYiCXvqV39AzmscSQcTk5n9t/R+GSAKCYylsJQRBQIseIFu/Cmv0aXpUOz+Nv5Hfy0lVO9G//+JX+Ujh2ywNvdgL2GR0PDTJmp5MqlCOTsJ24klzJKYGYeyy5tLJFYT3Ndlg60hhQoiyNGpojMOu9l7HN/03TDl/g3qIy53rKGobT8WIUCAmHv8T+SteXvw1Wd8iR4TYNNEMGK+SY1uSuL5m70iOl+itPBqsoJfGKY8FELMVH9xwLOuWNrC0Mc7f//hPDGQKxJ2JjU/O9WlORvnaW9dVXetYypCLbYUEo5AjGWGH3Vy9HTvYSxu3xt/E1ujJwLxP+9cikxpmwNBu2PXb6mNWdFL9YulEt1S84ag8zTlBKbDjRmq+RB6zYGljgv7xghE01hrXD+hQE91Bnh8gomjSI6TIMj7WTU7SpL1B3j/2LYLkB3n5a99ZtQO0lKI7aCItWWK4NMp42QneqSy8T9ZBqdj/qPLUSYVVb5g6svFxsdACszWgd+t6GiRLNBwOLD3E4V4JZrtPgXInmxdWiywCLrZv42G9ckpkcaG1yRCJHcfzNa6OoCz4m+JtDEkjuVDystTptdHaVHUfWsNwrkhDIkIQaD7l3MhxspedwSK26LU8EJzAfcEaBjDF/7wX8PX/eQKA5lSEpQ1xRvMurh+QiloUPOPI+LZTljIZrh/g+gHjhbBZWwTHEiIhwZRqMfPVScbxr4DjX8EbvvIbGuJOFZHVpv0PH2pkciBY8VI4+X2QbDHEUb/MeGrLoWjPHiEoa1LkEdn/NRXYeNZKPnHzNoazLn5gisPX+OeHU9X92AR4vsKWgEHqGfUcIjZoO04QwN/kb2GMd5bv7+/0beQDm7ykGND1aGCNPI2PVDkkTsE0/zRV/VfjYNSEtRFknzFdFQB9NNFANpRbmb9IfX9LZanhICi/GiGCy7XOleR0DFccnggWc41/Pkukj2GSKF+XLQHGfIclkmMPbeXHExFyOlJ2cBRMR16u6JEt+vSPGw2wNDn20cIy1cex/Jq3WHfRG9TRSRvvdv+BRMTCthQjOZeB8SID42aOaSTnoQTq4w5/tbqNpc1x9getNUVPU/QCxitmhWylypFLxFZELIVtHb7vVs1rZX5RI5MDwYqXwoIXPOOFHgHj910mj7j5vYSDGOLasLqNK9+0ji/f8Rjbe8zsh6WknAnTpbw5AXltIyKkdJbGYBgHl4W6l6//6kY2rP4/ACzwe+gjURUx5HGI4uKiUPhT5z1mIJLJKF2nNFh45CWKjTttukuANgbLPipHC6XCfElXyyLAwUMTRmlSIE6B5dLN5fZ1jOsYcSlS0LHyexCnSIY4MV0gG0YkAiQoso82orZJRaZjDqmoTfeoWVgjltBZaKVVD7OLheUOurgUiKBZWB8l0PDf7z+NPQNZHnx6mIc6hvlT5zCjeY9AGzuCm7fu5eate2mvi7J+aUP5T3vd3FK6XhDgFQIyhYljljIpVBPFqHI0czCoea3ML2o1kwPFM1E1WASsSDV5zFTErxzicuITHVjnzn2I6+3XbuGpgXG+lvssrQyVFy6A48TMjfbSyCIZKOf/NRYDNLD4HVfD8a/gj5e/hGY9BIFHMyNmaJHS7lxK8/BTCtaVMxhFFD4WMdxZvUl8FKPEaWRiwHM+0lgHi8osnovghaQqoo1lDqYrrdTx1qWbcLFJkscVh6x2yp1et+izeYPcNaUD7HPeBdwjL2RRQ4x0zCFb9OgbK9CajpKI2Kwe28JHCteQ1+a6OuUSEZ9vxjbyO9ZPWwsJtGZXX4aHOkrkMlJOZVViYX2silxa09Up1ft3DXLDHzroGs2xsC7O205ZWlXsnwwRqSKXiDX3OswRltN/pnzEjghqZHKgOBgyKc997Cu7DR7S3Eep06qSPOZa0LzufDID++jJK4peQMRWtMcCks2L4IJNs166eXsvW351I381dAML/B5aZZhumhjTifKCmCLDMumniG0IQUxHVK+0grJZsnQFXLCJL//bN/jA4FepYxxfm+eu0GSJYWuXpBQJoOwFYocDjkUcNrofY6O1ieXSTb1kiVOAsCvqSKJUrTnU1Fjp6j6dpl7yKAJs8VHKJvA9XKyybL1FwON6CQ1k+EfvPVWdXt/lNfzaXcdZoZbZ5A6wVMQoJxe8INzxw4rmVHkRfmHhAV6XvYlWv4d+ewE/jb2BX7nPZzDjkohYrGhOzbrQ+4Hmyb7xKnLJFqdGg0sa46xf2sC6JQ1orfnePU9hKyHmKPJugBcY/53ZCGU6lAr9peglahvP+qOI5xSZ1NJc8425qPjuD5XF8tLtQSLXt5uObAQRs6C4fkDHuGZ5sJvZst2bt/ey6Zbv83H3WjxxGCZJMyMsop990so4CbTWBNjslqUs1ftQaIraZlg1Mi4JFqdj5WGx01/5VgZv/A5JnUeJT1Hb9Ol6PIzHyTF0oQjC9mGzI+/XdezRRrTw+bKLU+ztBAguQmSOC/rhjUgkfH5z1/2aCR4Wn/I+CJhi+cnqcazAN/sG7VMSlHexiVOkU7eWr41RYK08xb+ob/O4LOaecPI9ToHnqT1cqa4xtRbvfP6X9dhiNNDGC5rHu0dpTETIFH22+8dzo7qMlmSEpU1JnugdYyzv0ZSM0JKKMpov8o3f7uRj1ipeuHxq15elhOGMy5YnB+kazbGqNcVLV7Xg+gEPdQzz8N5Rcq5P51COzqEcm/5k9F5tJSSjFp5vEY8Y0pzcijwXlAr9VKTJJhPMvBb6n+Ookcl8o6TiWyIAJ2b81R+8fmYysexq8jjAYvlseNJtJkU/rhjqUCI4Os+TbgsnVpw3WSpjOFvkS/6teOJQkBgiAT26kSXSzwIZ4okgRpwiUfH4Tmojr8veTJ0/SE5HSNo2i1NR0qoIaSO0uWF1G4XIGEFh4otdKhY3kOFq73VcbN+GjU8RmxGdxMPmGv98AM5T9+GjwvSYUAxNqva3TBzeZUSXhR4PBQIMBYmqbqvj1N7QWVJjh/UTH8WAThPB455gbVkAs16ymHxYgeOlg5Pt7YzoRGgNrImBqbU413F1bCO3jj/PkJTSuAH0jhexlfkseL6m4AVsPGsl19y9q6pgnYw6iHj8ZOteXnfSYjIFj/GCR9EznXf37xrkqt88ga2EupjNYLbILQ/u5ZJzVvG2U5fh+QE7eiYil0f2jpD3TCQykvMYyZkUWcQSBsYL3L2jj3VLGqhPVMuwHAimIxhbTUzyl9JkEfsvoInmGY4amcw3RveZiKQSdsxInZRgOabDqkQe1vz9t3xPv4ZPyHdQOk+BKFEKOOLzDf0a/jU8ZzqF16cGsrRHe8hIGgDHEsa9BJ26mUUyRIMYeY+fxt7IY2EP/8bMt4gpxZLmuonazIozzVRy3+NEi0Pleo8VBCwK+nHC6KM0W/F+6xekJI9Hnu/453FXsJ6z1UOsUnvxUeRxQtsrGNIxmuTItXkeLmLyUDSpDGerh7grWM9GaxMjOkmWOK0yjBFdMVIze/QCrvHPZ6Nl9M2aZNSk28RGdECDZPC0kaPxUGgsBE29ZOnWTVyQu57XqxRLpY9xFUdrTUrydOpWrpPXsiN9OpaS8kZiJj0tx1I0dN5Fwz1XoYf24NUv4wfDr8BWLyjPnsQdi8FMgS/8/FFSMbtcD3nHact4x2nLcP2AD//gQXrH8ri+Ju/6ZtDU1xR9zT/d/igAK1uS5XrLuqX1pGMHTy4QFvqLAdkKYW0lgnOQdZgaDGpkMt+oW2RSW5WpKa9g5lHS7fNOHpOxr/VMrhpUvN27lfaghx7Vzo/s17OvaSJK+vIdj9E7lscPNBFL0ZKK4ljCHr+FVhkhpyOICJYSAhweUSfwmfSXGMgUqYs4eLkiN46ewNP63VwSu4PmsQHirccYItn2Q1P8L2bCYoEPXgFLTPF9gRriR+45bFAP8Wbrbvpo4GltCslvtu4uT4S72Nj4OGEtRQNJOTD5+MOFksaWIFWy+HOFFc6Qf9f5Km5Ya+rUzYzqJIHWtMqI8W9HcU+wlo3WJk5V28kRIUoRD8u0OYhpXAjEIaLd8DmZ4xHtYeGxSrp5igV4CMfKXhDYRzNtDPN5+zq+LXH+6LyIzjAinbGVtqKRQ+KNOJle3jv6LdzkRTxgnYIfaMbyLsM5l0DDooYYA5kCV/3mCS7B1EMcS/H+lx5TjmYitjCW88i6AW3pKB1DWVxfs6s/w67+DLc8uBcBjm1LsX5pPeuXNvCCxQ2kYof+/Qm0puD6FNyJSLM0DxN3LJpTs89h1VArwB84DrQAX6qZWFETfXgF0O4BdU8dTuxPI2nz9l7e9/0/YIkYsyoNAZq4LZzkbuULTuhBHi7wrXGh/o1GgXXz9l6+8svt7Ogdx7GE9nQU21IT97/lvRM6Sb2PgljgVWtHBUCXtJMjBoFHVk+k+OIYrShjUevSJsNA9ZzJXMlkvrq5DuV+S/IvETwCFH06TZNkKqpBZmpmRCdpkPHytH6pEaBUX/LDSX5fLAJUaIZlIaFiw069mFXSGfrFawIUnbSiLId+GnmH+xm0NhFB33iB+rhD3LEYyBQYzLikohbXW1dwTHScZCpdfnadvQP00cBnG74MwJO9YxT9AMdSLG1KgJ5+Sr7UzdU9mmNBRTdXwfV5tGuUbR0jPNgxzGNdo3hB9XqlBI5rS5Ujlxcsqa8iv8OB8vM/cDynwppaZDIfUFaYtorDSX9ropN7rjLF54ZlR9WcZ38aSdfcvQtHmf4kkXCOJIDxYsA9sp4r9Ht5Dz9jqfTRrdq5Ofk2Lg1fy4bVbVxz9y5WNCeqvtBl34psqOCaHwml8YsVMiIGgtAcFVR+HztlSdUgSY5IuUNpvdoZSstPzKPM1h48GfP1LQ/frlkFKKdDiRCC0HXSxqdNRnGxINQIM8OMPk0yNuUxwcj3jxMnToFhnSBNHls8LBEGdZIWGaJTt5LCKA4ElN6zgEUyQE/QTKvuxvM1ixtiFH1Tg3KU0D2aZyzv0ZhwaElFaR7qosNNsdj2SIeRQX26DjXSU57jKPpG3ay9LkbEUgQaEgLdo9UbiFNXNk1bbI86Ficta+SkZY1cAORdnz/vGy3XXLZ3j+EHmh094+zoGefHD3SiBE5YkGbdkgZOWtbAiYvqy0X9GuYXNTI5HCiTRzhdbk3K6YZyDs8UbFjdNqvvRHtdlK6RAgHaeJagCTQsbYzTFT+TL3EmYCaZR3Iul066fkbfivbl0P8k5PohjHpKKC28PoLtjWFbirUNDg/3mRmSFFkWyBAKbRwccUMyeeagFJUcbJrNC1+NF9Y5Sh4sLnboZTIQHgsxSV4mCGUjb/NfzMvVg9h4aBTjOka3vYhxP4UtHm3BQEh44QyQCIGGZobYpo9jSWO8qi7RmIzSmIxWpbx6rQXU+wP0jVtlMklbLl7rStrsGJ1DWRIRi2TUKt+XJVDwNCuak7TXxcgWfbJFDz+YW3Yk5li8aHkjLwo7yXJFn0f2jZTJ5fHuMQINj3WN8VjXGDf8oQNLCSe0pzlpWQPrltRz4uJ6Ys4z6VPz7EEtzXWgyI8aq9xKXavJ5PEXjLdfu6VcL+kbK1D0A5PyUsLC+tiUiKMtHSt3/nQMZRnNmZmE1nSM0ZxL/3iBgheQiFj811mjrLvnYhOVKBvtzSyPLk4SIkmeyjgEgcsSMUrMe3UzHjbLpRuQw26bezRhWn8NkZSkVQo49OhGxkhwgjw9dYo/HFc3xfk2Fku/acnGpls3YNsRbO1ydfwiBjMFLtXfZZEYMim9d76YCE80bNfL+F783TyWMsKHpQ2DhipdqxcWHuDCzLfIBTaeRElZLs0xiL/u6+WN03Qp1dGcS3MywnjRLxtqnbaymfGCd0DEMh0yBY+H946wrWOYhzpHeKLHkEslbCWsWZgup8XWLqwjuh9yqaW55oYamdRQhZlqKm964WL+a8se1hX+wPvkdpZKH12qnb1rPsDXnlpePn8gU6B3rEg6apEJB9aCQGOFcuf3Rz5IXPJE8LEqfN2rxkQEJN4MhVGKgY+lNX447a4IcLHxNaQlX5b+OJQ6xTPxG++HNZNmGQdgUKdok5Hpn2uZUMwfN0w4CNArLWhl0xPU8w73Ms7QD3KV/U0SUii/nyXZliIOe3Wrae9Of5it0ZPLGwagKjIZzbmsHLmXjdYmVtj9dEkbP7Bez/lveFdV1Fs5cZ6K2lU1mOk8TXJF/7AQC8B4wePhThO5PNgxzJO941OmkRxLWLuwzpDLsgbWLKib0iZcI5O5oUYmNUzBdJITAD/58ff4pP8diqHkRiycK/mKvI/NwXqKfhD27AujeR/QOEqVi6ZeoPmhcwVtMoxrxVkVPIlVYoMKaADLQQGZIDTM0kFZVbcsszLNtc8GBMAe3c44iXJ6L4pbFqucskJVkImRmbHLXjEeNnvVIpJ6jLOLV2GJcIZ+kM/bppFioQzg4AHCkE6SkgJRXPIqxhejf8896oVc/trnAVRtMnb2jeP5uioltj8591LUO110O901edcvp8JKsyyHgrG8y586TTF/W8cwT/ZlppwTsRXPWxSSy5IGVi9Mk4jYNTKZA2o1kxqmYLqaytuv3cKn5HYCGhvp7AAAIABJREFU5ZDzo4hAXkdBw98Gt/Fz9/lmTdMBRd9EI89bVMfuftONVAgXg2v887ncvg78HKLMJPbkb5yIIR5l20QC02qrBeySLP3kqv1Rgrc/heO5oIIQdcWvbTLCYgZwsenRDSyVfrJEiZq4bMp7pgVcbWETYOPjh4myCB5RCnRJO7YIBV9zF+v5rHcBG61NHCPd5IiQIUpj2DnmiSKm83zMvZa3v+QK1oWfhcrGDa1hcajzVcL+5NwP1Ac+5ljEHIumZATXD8gWfXJFn5zrczCb4HTM4SXHtfCS41oAGMm5bOsc5qFQuPKp0ODtwaeHefBp0ykYsxXPX1LPhhPaeOdpyw9pgPLZjhqZ1DAndAxlWah76Q8SVTJgpQ6rEvxAoxQoJeRcn6IfUFlpvyuoWMjompqmCn9Q+KAtxI6ivdy8bvEONtV1KEQy5TXrid8tIEEe0wsVsFgGyOMwqhO0yOiULrY+GkjoPDYeHhZOOK4IxhulMQI3JN+G7pl4/LuC9dwVrOeHzhW0yjALZRCNKeJHlWDZUdrTdbQ/fT3wZqB6k1GKMioxm5z75u29jOZcukZyxGyL1nSUdMyZswS8Yynq44r6uEMQaHJh1JIr+njBwUUt9XGHs1a1ctYqI00zlC2yrSOsuXQMs2cwS94L+MNTQ2x9eph3n7HioB7nuYIamdQwJyxtTNDV00ZaD5AXk0PXMEUnCsAPoC5m4foaS4S8X73olmRDnqf2UCeZaRfy0mJop9vwxnrBm5qS2B+M0ZbGCYcaTYFbYWGEI48WNCaKiKj9PQeNHc6NDARpEEW/rqNOspj/gYAhnaRbN5Iiy2IZADQFbDRCBJ9dsphbkh/g9Fe+lf/4/h+wlfn/KaEUKUZx8VBYok3qMdVmWttDLbXJ8joL6iJsfXoILwiIWor6hINjWdPKuZfqcImIVd5g7B3K0ZL2Z7xmNiglJKM2yahZvvKuIZXMIabDGhMRNpzQyoYTzOd5MFM0mmKdIwRAKlpbLmdD7d2pAZi6WEyW5t541kp+cMvr+Yh3Deg8eaLEKRDBK+tlgUlRKeB5i+rZeNZKLrv1YTqHzQ727FDN9jjppE5yjOvo7CFBvAWiddhuAcYNmcwWC0z+NytsgPXCSouNT3QGT5MjCQEi4qP19GLPpdehwp99jFXyP4YR3RLMrM09wVrebN1NnALjxOnXdTTJGGMk2Bks5ru8hu7WM0379uo2VrWmeGowi4ghedcPuEdO4oso/lW+QZwcSgCtzGBurADxRoa+9dcc37eLT4UWzHcOPJ/7nzJNFq5vVIgHMy4f3rBs2pbza+7ehWMJ9fEYUdsqd/hlCj7/9rYXHLIEfCkd1piM4PkBmaJPpuCRdw9tw9CUjHDO6jb++nkLDrZm8pxCjUxqmFaL67M/+zOXQ/mLvmF1G7zhXVz7M8Wrx2+akDf3jLy5rQRbCb7WKJEyGS1tStI7VuDF+kEuD4u+cSkiBNSpvJlYn9TJZW4EEo0wuBtc09Gky39NxeS7KE3C++HPc/GBPxIoRUjl3ybVS6bUj4AoAVrrcmoKDAlpTVleZon0sUcv4B+895fPUQLHVMif/Ch6JTl7Fz0lUgjl5bc6L+In1ut4Z/FGPA1aK2y3gOV2QWGcjFdHhhTNeogPZr9Nt3cBv5V1uL5mZWsKMIX0e3cN8pFpXnNlraQu7lAXd8otx4fbS8SuSIf5gSZT9EJiCabUWQ7UR6WG2VEjkxrKO8dSl00iYk9MrVd82U3O/ONs3v5OPnX3LiNRHng0RI1kSskn48MbjgVMXv3+pwYRdFmYMEeUSKiAqzTYM4QFgViowhi4GdAVqYtJHVyVi3BlHaJUTyiGRlOTcbRaggXwICyOm5qGhUahQ+96Hc68V2OhGioLQcJEGaqSYKaD62suPa4D7riCiGfRJ2nS3iDvH/sWfvKDvOKdxko5/ePL6aeeOnLYuOS1TUzA8ouMBxEsJRSIgc7zHn7GXbLO1MNCzFZIP1p2uZYS6mIOdTFDLNmiR6ZgCvj3PTlQpXA8WTeshgNHjUxqOOAum8pC7OQ24hevbOKOR7q56jc7cSwTrRQ8zRLbeJaDaV11Ql0omRxphKu81h6MdoSrpoTHjKsHAoEWPIQIEwvadORQmiKf5iGOGmw0HkIep+wUOaajfMc/j4/atwBT8/4OPlfZ3+QS7+JZyePsScZYD2ZP5Njf/QKfHGiHGA2M6DgazavHbuLTt60nGbH4nu5hTDUyJmYhDbRmZbAHK/CI2ArXD1AiFIiyVPoINERCf/axvEv3SB6N2UBMlyI92na5VmhXnI6ZAv6nbt5GxBIzsKgpP6+D8VGpwaBGJs8A7K9eMd84lJ3jZGL57M/+TO9oHktMQOGGu9dO3UqrDJMjSp+uZ7EMzFoEV5jp67Jm16R2YB+Lx/VSWhlkgYzMeD+TVXznlUgmzXtMh5KNsU1Ap27BD4Udb/LP4gz1KAEyo0RMUnJcbl/HZ70LqgilRCCr1F5SZBnUaQaoY7l0cyqPg9YUtYUlHu26H49mxomzRProGDJ1kq54Gy0Mm+iD0NsEhaMsWlOhgq/WxHSeDlpxfaMk9mjXKEFgXtXSpviMKdLZ9OCONJQSukby5Q1UoA15xhxrim5YDXNHzRHmKKO8AI/lq+oVm7cfOZ/5jWetxPVNGkBrc3swO8dSuswPczBuEJT32Nf45xPBI0GBTFgsnm1RD7QY5eAQlfWSkrpuiiwtsxDJXHHYxlVCIhmgnqd0W1lrqxIBQgEHD4sUeVoZpl7Gudi+jeXSzV7dPONzFIQiNhutCXvll1kP8QXnOlplmDjG8rdFRkmRo06y+HoiDRho0yPXKiNVXXiBhn/Lnwd+EfFyBEGAE+TISwKidSgvhzHZKhARj//wz5/QUgsM4Ysyj5KI2DiW8UOpxIbVbfzowtP53afP4UcXnn7UiKSEpY0Jcq5ftlJwLIUfBCxrSpKK2aiaj8kBo0YmRxmV9QqRmb+M84kNq9u4/LXPoy0dYyTn0paOVUlczBUdQ1nijoUlQtHXVUKOpfmSfhppkAx79AKekOUMSbosAwKUd/e/lDP5SfSN6FJPkw7PEnNur65ngQweUGhdWTkpYLNbt9OjG0M1XoNDJZYO3UqfrmehDE4beWmEQZ1mZ7CIHDH6aAhTcYYESlbA1ddM3FbO9YjARuvnFLVNnigRfPxQmL5VRoiVZ+EDIng4uDj4pMizRPq4J1hbfozNwXo+77+HPl1PIhijj0aePvNKeN3V7C6kaJQMGaeZ/0x/mPusF2FbZgF2LOPdbovQP27sDPc3vPhMwHQbKC+AD204lrZ0jOXNCRbUxwyx1Gx+54Ramuso40DrFfOF2ZSE54pSumwm3BWs5x7/JCwlrGhK8JV1vbi/v4xhH+oYL7sJ/lzO5MrEx+gfL9Kni2xUPyNOwUxnawuLoCwxciAoEKNT19HEGFHxWCZ9EM6gmMqKphjKxGgOfKflYnGTfzZ/Z905rUmWuU+fZhljhNTUhgQMCRjTK7Pwl4hWMPWf42QfTwXtED6/ZaqPQZ1EaxOt2fgECDGKZQfKADEKAiG7+yGhlczG7grWE7UVW9QLudtfb/5/GhL88pyzAbjIsmhITYg8Fv1RlFCWz/ECoy5dKshPTpGWfG529Zv27mOaE1x67pqjGp3sL/VW2tgdbm+UZzNq79RRxtHqdJkPlAqtbhDgKKicH7PE5KqXNSVMh9G5a1i3+mxY0lDl9SJnXMLmmx7in8c+Y4rItHKx91ECrUPPc58mGSVGcYo018x1CoMkeZKSD+MAFc6hmH8f01HSUsDGDSfPDzxGGQoSnGfdzyhJGhnDqSikV97bqI6TIjelISFA4eCxVzezRPopYKPwy5P2HgobnxY1yl9ZD/Fo6jT2Ftto0kNkiVTI1BsS8TFfcD98rVoALXToNsZIEKfARmsTdwXrWVAXoy7c1JTadkuY/BmNWKpMJK3pKPuG8wQYV87JKdLN23v55M3bGMq6lDb4O/syfOLmbVz5pnVHnVCOdrrt2YRamuso43DVK/aHzdt7efu1W3jpV37D26/dMi81mVK6LBmxeals44boF7kn/lFuSfwzL7O3oUSmptCOfwWbT/8ub09cy0t7Ps5nbn2YjxSupVWGGSZJqwzzT9b3+LT1I2w8WkLl3DyRKW3BM0Em/WxhjKQqZz4iEjCo01j7ua+ZoIG0KnC8dGLjUSRS7iMrUUoRhwIRduoldOpW4hgT8j5dHz4vHxcLH4shnaJHN4az7AY+NvtoJWel+VD0FzTEI1zrvRoblzgFxsJalEYhBBSJ0KvrKeKEUYrgi2KcBGmyLJQBTlXb+XHsi2xQ28qvZfJmZvJn1LGk7NneO5onFbVQIsQdNeX/95q7dzGW97CUYCll/ogwXvCOaCq3hvlHLTI5yjhcnS6zdYTNZSjxcL6e/zprlJbfXYeLTUbSNOlBPm9fR/+Zq1h3zrlTnnflc3tN/83l9A9Qvj1O7ZvkqmhqCzZB2dlwNkw3DFi6Jw1EcXmCxQQo+oM6Vqm9E8KSc4ARfTTtziukd6ILreKcKMYXZK3sZp9uoV4yoKmaXs8So083cFtwBm+27sYP4yebgBhF2hlkUDdxXGSQXf0ZHvPWUVQXcJG9icX08TQL+FzwAd4nt7PYHqUgMYYDzWqnB7wCoiK06ALN/kBopQUnsZ1141dwo/tmro+8dcpmpvIz+kTPKDk3oDFhU/TMbJGvfT684Vg+8vLjp7wvHUNZvCDAtib2rSKmcP9Mr6vUcGCokckzAIcabu+PLOY6lHi4sO7p68mkUvTkFb4XYNkJGmIBiytEAwHYcSctt3yBG90ueq0F3KLfyGLpZUgnq+7PxisbOZVgnAjNoF8pJXWwbb+lyCZOkf6gjqQUykQ1F7hhJDBZ+LFykLJU+/AQ4uJSTwatjfdIA5kp0+s/dK6giI2LIhbWhjQQwaU16GNnbnG57fquYD13FdeXHzNiK5QIn9PfQ3yNR4Q+N0YzOexEAwtzw6aFS/sgNlrZ4Lu8pXAT+5JrOf3Vb53Wk6RjKEvR1zQmHFrTE512s02/L21M0D9WqJKO0drMfcwllXu02+ZrmDtqZPIswP7I4kgU+Su/9LcUdxBPt7CypeIxtS6LBgKw40647UMcWxzGJqDBG+Hvx7+Chc9C6YfQtcTDIhKmgyZDwrPyOGiknDY6GGiBiPZwxcbGIxoaRs3avlzx75O/SJWptwIWHk65OK4IqJMs3bqJYZ3iPPfLU65dpvqqSHUipVfqj9ZTXARL5/mB5sHYi7gsp7nQup3lVj+daiG38greFNtN41i3OVNssB0swBIHJ/DYaG/iQ3efwmW3PcLScAj15q17yxuVrpEcOdcnalvlGstsn6WNZ60s10x0OCwUaGiIOvtN5R7JiLqGQ0etZvIsQKkltxKVX/BST30lDmeRf/KszF7aGBgZZixf0dHk5qBh2cTv//M5yA2i0HhasLRHWmeJSCFMvwRY+GFXElW1h8mwCRjVSVNgPsguzkArPutdQIoc9ZIJI57ZUXI0tPYTwQiEBXZzjyWfkcny/SVooFO3EaeIhQ7fgdK1ir26mZSYrjmR6pesBFa1pRjN+9wrJ/F/01/iHYlread7GV/OvYazez/OUOspIKrablprPBUl17eraubp6s1PUvT8cut6zDafs1IbMMz+Wdqwuo2vvmkdq9pSiBjByuNak3Mqvj8T2uZrmDtqZPIswP7IYr6L/JO/9LfG30QEj5HRERORFLMQFOGMSyYuGtxZNnDSiOk2AmxNWeW3tLsvLdXTLe+l2km9ZJhqszWRWpoNpuVY2GhtolWGSVCYMusxGQFCj27i696bmInBpPz8LFxKEY9LDBeLgGZGp8j3l3CNfz4R8cLnoXCx8bDpVu344kxcN6E2Axil2zs+ehat6SjHtRkRxn3DebxAYyshW/T5XP85FAKh6BUpuD6+b1wxh/w4+2ijeyTP4z1jdI/k8fygalPQmjaGaAUvmPNnacPqNu746Fk8fsW5PH7FufzyY2fPKbLY3yaphmcWamTyLMD+yOJwDSXOhMlf+q3Rk/l28oP06HrID0O6Hc69Eo5/xcRFGvzA7P9FqltxPSyKEikf8bDCxVJXrdsawmVZiIpp6Z2YGZlIDe3TzYyQxA0H+ipR+j0mPsulmy7dCFDu9poJ/TrFZ70L+FbwBtywtjHd+WPEGdNx8trGrtAJ00CbDFcNDlbit/46/tG9gD16ATYBWoQeaSEfKBztlmX/NROij00Jh1VtaWBig9E3VjC2ACKgjVbaL/LP59/916OxUPjkA0XeaaKgLb5VfDVeoLGU4AUaX1OWch/Lu/SNFfBDmZvu0fxh/yxVYr4j6hoOL2o1k2cB5tIRNp899dPNyvxeTuKJBS+e0Q+cllVIz2MIAYGW8myHqSmEmlxSohBFXhuyilEEgaJWqHBptiQIzzIqvF75Y61xCNir2/isdz6X2jdwvHRULeilx9XAQhkkQ4xhnaBBsjPGMwEwQCN3B+vRwC69kONkb5UCMEAem0vciwG4yv5mxaT9RAz1fusX5cHBySgV1i9auJNXjd1Es9tNv27mh/Zruav4/KpzNTBW8HhxKFJYmvnJez62EoIAAjRKm1TY1cEbGKo/kTfkf0Kb381A0M7VnMfveAF2+L6LmPmgAOgfz9M/Zt57SwnNyQgR25rXgvgzQSCyhrlDDsZLeU53LPJd4HygV2t9YnisCbgRWAE8BbxFaz0kZrT2KuA8IAtcoLXeGl7zbuCy8G6v0FpfHx5/EXAdEAd+AVyi5/BiTj75ZP3AAw8cplf5HMGOO8PBwj3QsNykqyqijMpCaeWXftYd6447GbrhA0T9TLkwbRMwohNhPUBjhQVbrYVO3YwvDnUYb5MxUkTEo4VhHFwK2iEqRYp6og6gCHCxGdJpzipexYrmBKf7W7kifwUBygzzaQ8nTLGBGSC0ysmz6RNYHoKPzanyA1rTUY4duZcr5N9JkcMKJU3GifNJd2OZJO6OXMIwSdLkWCQDGJlEcAjYp5uniDdWoi5m87xF9WXC3tU3judrXD+oSAGCrWBhQ6L8vm/e3stHbniQbNHnHHsbF9k/p9XvplO38j1eS1frmeH7a4YUs0WP0byHQsp+KQGamC2IKLJFn6itaElFqYs7ZIsebenYzBuGw4DJqtR/Yd1czykdlvkkk7OAceD7FWTyL8Cg1vrLInIp0Ki1/rSInAf8HwyZnAZcpbU+LSSfB4CTMZuvPwIvCgnofuAjwH0YMvk3rfUd+3teNTI5QOy4E+74BKiIsXF1c6b+UZm22nEnQ/9zJe7Abjp0K3c2vI3E2r/m3l2Ds7Z0bvvNTWQ3f40l0se4jpMkS5uMoMSQgKsSdHlpNJo0eTp0azm9c5G9iWOs/vKxdNTmy95XQfuhNInZ/ffrOvboBbzDvQxHQcS2uIlPslL1EFEBBD7ooPytDyr6sLLESJKfgVAUL3Z+zIK6GOMFj2NH7uUDahOLpZdO3cr18lp+WXhB+fwfOVfQEnqtV3Z1udh06yb6dAPvcC+b5pFMJLGoIU5D3EiabO8e5Wz1EO/ldpZIH/to4zvamJQta0pULfCbt/ey6Zbv83H3WjxxGPUdYtoINv6T/x7uUy+kLm6zotnUV3b3jzOW98oT7umYzTEtqXJHYElSBSZI6HefPufAPlPPHTynyGTe0lxa67tFZMWkw68DNoQ/Xw9sBj4dHv9+GFlsEZEGEVkYnnun1noQQETuBF4lIpuBOq31lvD494HXA/slkxoOEPdcZYgkEuapIwkohsePf0WZbBpVBFoX0ObmWJu/hn+8v0Bv9ORZWzrXnfNmXnpfI8eN3cfn7esoEmGXLCEhReLKp/2t3+T8n1r0jRmbV4Fyz+1dxfWsWZCmIREp79j/e+SNvMO9GYeAPA6jOoGHzTX++WWZ9qXSR0bHyRBjX5BiKV3GoCvcU1VWPvp0PUmZXmtMEdCairKzdxxfa46rqD4KQsRSOArcMHT4fbCWi+3biOISQCjIKPTp+hm7ukoINBw7ci8bxzexTPUxZsVplhFGdJJhkrTIMJ+V73GFvJd9zkurCtQbVrexruFOMgMRskEEW0HWN0X0C9Xt/M5fT+9Ykbef0sTu/nG27DYzIUrAiUg5lXXN3bueNbI/NcwPjnTNpF1r3RX+3A20hz8vBjoqzusMj812vHOa49NCRC4ELgRYtmzZTKfVMB2G90CskbG8R994gaIXELGEhfndxGFashkYzvG33MrjEbM7nmlIcvP2Xgq+ZqO9Cbc09R5AVkVpTQjccxVLGy+jcyj0mJi0z3uidwxLGelwWyn+OXgt/yvL+IC6fcJWOIxkSpbBwzpJmxqjjgxpPVbuIptuCzlbp7EC/mnoUlZaHcQpEKdIAYc+aWShNcKl+j+JpS+kb6zAJ+0bOF468ZDykKVFQK+uYzzUyJqpqwuMX0np+Q/pJMfKPmx8MsQAIasjgOYi++d80n0xSxoTk+Z+dlOfbmFJ3GFXfwYN5IMoi+krRx8//sPTdI0VUVLy94DhnMfLTmgt/5/V6hc1zIajVoDXWmuRKT578/VY1wLXgklzHYnHfNagYTmZgX3szYS6VkpQfo5Hc02Mbe9lQ0g2lRj3HRaqau2v6Vo6r7l7F3VxhxV+PwNB0jRriWBbimQyCcNP8+ITm7h31wAw0bUkmMXcC8C2TKdSwTOk8HvrJH7rrqt6nNI0eY4odZKjkRFKCsGK4oxzIu0yNOtbs1R3Ua+yWNo0H9v4LNADdPnNFJXNRe5/EY3maAyG8MLieyAqNP0SUlJgXBeIKY/r/NfM+Dgly+N8KC1jJGSEVhlhTBsSzxGhPeihcyhH72iejf/9RxoTDi2pKHuLbTSODII0UvQCbCUkxWVQLWRlfQqtNX/uGsVWgq0sSjYsXhDw6+0mYnqmGVzV8MzDkSaTHhFZqLXuCtNYpRVnL7C04rwl4bG9TKTFSsc3h8eXTHN+DYcbZ1zC+I0XE9MWrsSI6jyO+NwU+Rv23L2LDQ3LYaxnIjIBUpZLF9WLzHQpkVIevtdaQKMMUhAj0eEHGtwcQ5GF3Lx1L5aCCrtxBDhTPcRF9iaWW/3s8Vv4dlgzcP2pxLBEJiyDWxgOW4iNQm+OCCmmT2U5+5moT0uWQE98if7/9s48TK66zPef95w6tXVVd1d6SUISlggREWURNSIIE8FHJQIuzAwzIChugwKO472DM8goxBFnvCrjVSCjGK4g6jAgGEXlwoByMSOIgCIRkSV7L+m1qms75/zuH+dUdXV6T6VT3cn7eeDp6qruc97q7pzveXcbnzI27QzygreEVdZ2uqzFOOLjYmGFaf/KWPgkRYYjbdyafA9/kuNpHi5S8nyMPzrO3YT2D4b2G4JdLA4u0ZoOmgQlXvLaySQd+nMlip5h11CR/lyJX8eP5UJzB3b/Lg7DYchrwrccnrJfxbrBT9Hp7eKFSDs3eWv5efl4RCBiWVgCudJoaa5O2VWmYn/3mdwDXBQ+vgi4u+b590rAamAwDIf9FHiLiGREJAO8Bfhp+NqQiKwOK8HeW3MsZV+y6kz+xfoAg3YbabL0W4u4Mfk3/C75usDTOPmKICFfGqk2KLbF4Tb7XEZKLicUH+WagSv5dvaDfN39pyDHElLpI7gz/m4cXGKmgO/7pKwS+CVuctfi2MKKTJKIJdXZTqeGYZ8OBujzm1hiDXJNZAOnWU8AQVUTBOGh7zjr6JQBjpQdpBghihtO1TWUidBjWiZ820bAEcGdxI/1CVYCV5ouIci3BNskC7QxhDFQJBZUiBkPx7jV9cNe2Ih4o3sWt/WtYlt/njcf3UEqFqluqqycepvpqO5YgSCXUymDBkNCSjgEGxCNgaI3avRq8xve4t5PP2mKOMTEpYUhnuJozijfT4u3m34TTGe+JrKBN1lPBDPDPB/XMzRFJ1sirChjmTMxEZHbgV8CLxeRbSJyCXAdcKaI/BE4I/wcgmqs54HngH8HLgUIE+/XAo+G/19TScaHX/ON8Hv+hCbf54wdHafyicS1fDBzM1e1fJ7HYyeNehqrzgwqu9KLqw2KiXO+zNp3vZcznd/y4ewNdDBAuqWDjNcXVIaFglJptnxYjueG5EfYLRnSZGlqWwZv+yIb868k4dik4w7LMwmSjo0tQdinmmNByPoxfMvhI5GNxBwLEeH0iuDIADtNhggey6UXDxDjgjH0mBZyJMcEuWqbHRELe5KkSWVZVZxyjZyMfn+nNUi3acHxC/SY1urQyNGx98Juk+Z95h6itrCoyeHXWwY59cg2ovZoGYDF6MrjBEXAVEfUv2iW0EqOXtPK1e7FPOgfT/dwcYydH7Y3UjQRuv0WnveXstkcSpe1mJP9Ryn6Nn4kScS2KVvx6krgynvwTFCWvD9XSCsLlzkrDZ6vaGnw7NmrPhKADWvHhcAojQTCc/HG6rEni8Ofv37TuAqiP3YN83/ty8haacreaMuhCGQkxyUt3+CF3SPcYl3LYmsAMR7tDBCjjOBXh0f2mTS7aSZBieXSE25GNFURsSwb7CimlJv07ZWRMftGRgc7OvSZNIVIMy9rgef6yhzGjmq5cgGHXWYRWRJkyLHG+7eg+ssW8mWf5ZkECcdmd65IX65M2fU5taYarVIOXelLiVhS3cUOY4dMVvpbaofRRCzhKF4k3/oK0gmHzbuGg453z6PJz/Km0vXV46zsaJrZ77oepuljWsBoabCi1LLXydcJkvM4iTHTg6eKw0/YAe37dEcX084AI5EYcS9LO4PBCl+niZ+cVeJB/zUc+r0eoqbMIhmAMOHthRfUr7nncLL1+2rF193eyXw0cjcWPh42ljFYvsGPpYlNISYlYgQrrwKvw8dii+kgSxIwtPsj8Lav03vrP7Fcuikj7DKZ8HVIUGSr6cAWwfUMIyUPS6hTcl05AAAYyElEQVSKZ3sqTjIaYVt/nses17DJOxHDaD6lgucbklGLXMkfIyQQhMg6ZIA8saBHxIBjiuQlweDwEOlEG9GIRdnzabLK7PA7R0fnh3tHKsMV50RMavuY4png5uPeTwJfPFAE5aBBxUSZEXuVfJ0gOT9uevBU57Se5O7U2GbIBztezfeL7+KK0nqW+AM0S7Z6+yflLHz/Ak4/5RMMN2doGvxD5ZWw2sqnRIS3279iwKSq53lGXsbX3HO4PHJXMK4FKBmbbL6AZcCZ4P7SJxijAnCE7MQJk+GjQlFii9/BIavO5JNJi5cNbeKayAa8cJdjghJRXG7y1lL0fcLr/Lix8q7ns9p/nA/LRlbYoVdiRr0SxwJEcH1Y3hKjO1ui5JmqINzkreWayIbQI4oRlxJRytwVO4c3F++H0ggdTVF6BgbAlLnBPWs0xCbCjoECS1ticzdccbo+JmXBoIMelb3j2fuCMNZXXhV8rEmsV5kgOT9uevBUx7/3k2S8Pjo7lvCaTIkrzTf4wnHdPGKdyL32GtLk9ogjGPDK8PCXSJMP5+1CkPUOLpGCz1Gybcxa4H+2buQ8+yFsvOogFUFIm6FJcya1U4UrCXGvkhCnSBSXG9yzeM21P2PHYFAtliPOCunhKNlO1JTIEefayLe4zVnHqfLEuHMMF8qsHNzEtc4GOmvsrRQbVIQkalukYzbr3vlqlrQkWNIcIxkNhmM+5B/PZ/330UuGVrL0mlbWmfdzS/Qv+PaiyyC9mEh5kN2S4ery2JEulgRFD11DxblrThx4KfBWa9nDe1UWBuqZKFVmvNVupqGJVWcGzz1yfXBxaD105vHwSe5Yj9tyC9ecfTPtdz4dDk70qrOkgsyxD74LuS6wY+CVggGSIpSNRRSPAlHyxEgzwhLpIx6u03XD4l07nJxVGYPvM3rXZYAcUeK4JCkyQrSaEN9NC0ukn6gpUyLCRyIb+fei4ImpNh0+a5bRxhCHWH10G58+mqsCcbV7MT/3j6+G9XYNFvi8/UN8y8GTOOIZ8iboNbkifi99mdMAqjOy9gxHrsjY7M6VeMZ+HRcOH1+N4Lc1RYl6htVn/QUcfRnvX7+JbqvAltIIjmWqXftlz8exBdfMYXNind6rMn9QMVGAWW61m0loYs+k6tv/1+zCFlPkW04/uhOS/UACStk9vtFAJB54KIk2yPcGkmDA8l0wsMu0kmaEQ2R3OCcrEIsIPmUsrKDmK+zn8KohI4NQJkIMjx2mjV4yHEIwi2uddwEQdNoP0kSeKO0M8BnrW2QlVm06tERoYQQfoUVG6KeVInGEIh+JbCQhFh8r3sui7E62WB0cZW2nT9qxRIhFBM8YCm6UpaYLY8y4TvQ9w5GVG4SyN1ydXnBEe2rMjUKl3ydqW7iewbEMXrjJ0bKElYua5i75fvIVwY1IibGz32bivSrzChUTBZh+9e8YpkusT+O5zMgDmu6OtfUwcF0o5QBT+Q8DdJeiFCIdLDYuiUQ7lIaw3QK2ZVHwhUNld3XcvexRzRgJxaMy0t6EI/EhWJnrUMZgkTNxLvCuCrvZg2T1t+3RTnuBsHQZVlq7eNYsqx4jSrD0KiqBuBljKEiUVdZ2PmtvIBVrostvpt0fIG2GSfk5LKCMw25a8CMRdkeWMpgvT1sMMZNc14pMkhd6s7i+oegFSXxLIB6x6EzHufJtrwDmaB97Pd6rMq9QMVEAZrcnfroL/RSey4P+cTPzgKa7Y628HstAsR8T7iQZJIWxotwYuRC3bPjH1vvIRHZCNAW5XoZHPFrMQNXjqIR+XGxsPKRGHKK448SGMADWbg1xVFuKE0uPce7IHSylm3YzwC4WUawcwBjyRAFoZ4hmCZomLfGxEQpEcWzBEgvHz+MYF6JxtuYC0UmKF+wfCXfT25RZQg++k+Gwd3+aX+DBI+vgJy/BpulLaicTgzesXMSvXuwLhjuGwyk9A0tT0THj7OdsH/uqM1U8DgA0Aa8As9xqN11ifYqk6oz3eleaIW0HejcHx4ymxr++9JWQbCcnKQZoZUtkJTcm/4anm17Pb2IncWnks0GIbWgb5HeTsfMMkgozLZW1wDaWZWNJBEssbBEsqFlmFVDGooiDwSKGy3Wv7uJzsVt4bVuZ5UsOwYiwXHo40trGKrZwpGxjlWzDxmWJ9BGjhCcSNjx6ONE4jiU4Xp6E5RGLxRksR0LPQGhjEFesYO2viQT7VWyHWOuSwKB7PxmIeq33N1EhBKNhzNr97lff8zQPbu7ml8/30ZmOErUtEKEparO0JUY67nDTz5/nlC88wOXf/Q1lz9N97MqkqGeiALPcajddaGIKz2Vr1yw8IIByDloOG/VOahP9NXe0b/3CA+P2bSQcmz/b9S34/g/ALQBChCJtVol+v4U0w1gYSsllJEs9wW6TzmMCgRzph8IguLlqCM3GJ1hHJYGnsOmrkB71wPJWirjfh4WPKzaxcABkKSwHtkPpMpEEODGixmNlsgytK4Of3yPXw4vPUzYxjPGJSBkjUJYo2+QQjl6SDmwrDMy6pHaqMObW/hHammK0p+LVrx/Kl3i2O8vhbUlaEw67BgvkSx6xSDCRYNrfm3LQoWKiAHvRmDhVaGKKENWKB8ev+J3UA5rFBXOi1cHHjvyKi/w7CcYRW+HqQA/LsmmLliHaCW6OSFQgtRJEyGcHsHNddLGIsnMIy+3t4BbCCi+DS4SsJOmKLKejvBOcpdXzNVtFXN/Cxg/2tiO4CI54VDo/LAzdfjNLWzoDUfj4U9Xvf3LbAJkX/oG4MRQkhotFxHj0SgvRysCxSjhxBg2htUwVxpzoZ9c1VBwjPrGIRcnz6RkuVsVE95kotWiYS6ly+tGd3P6h1fzi79dw+4dW730sfIJ5XZXNjJV5XCMlF2OCj5N6QLPoQZjouOeV7sIRHywbrJr7Jt8LPBUnCu/6ZhAGK+fIjeR5aSSKj8USenHKw3T5LSAWnlgUJE6f3Y6xotweOZc+Z2lwcQ+JmDKWFaEgCVxsSkQwYVhLqkl8nza/B7I948pfr3tuBV92PkgPGVrI8pJZwgApSsamoyk6NpzYetiYcwNTltROFcac8Hfi+yxOx6pf254KHhdcb/rfG0FY7fz1mzjlCw9w/vpNOt/rIEA9E2VumMRzmZUHNIsehImOe4zfj1UOy4StcPqt7wa9KNGm0dXDG9aCFaWrYBDx2S1tdPpdtNPPFpbRRwutZogcUXZ6LdwiZ3N/9hhyUZerBm4mlfRoakqB2NimTLJ1GeR6KJWK1eVbFSrTxCj0wcn/NuY9bO0fYbj5DXyq+Fp6wnH0f2Y9wQcjP+JIhiG9RzhxFiW1U4UxJ/rZOZZQrmnHb044FF2PkZI3bRXZnCbrlXmLDnpU5i8z2T8/FRvWQu+fIN8LSFBh5XuBsPz5raPH+NejoJSjVC7i4tBvZcAY2k0vuyXDi2473zTv4AH3uKowZJIRlrUmOXbkV5xXuotjEv0kUq2Q7YZ4K3hl3IEt2MajRNCNHhE/SOrbMSLxFPyPP44xd6LBlpWGxMpO93E/n1mU1E41VHOir92r4Z578z4OXHTQo6LMC+rtQajkbgh6TXALQbjrlE+Mba4sDoHvYbCxcenwuxmQVjZHXsF7Rq6k7EPMtohFqG50HCl6iAhPN72eR53XjF4owwv84M4/sd0/hEOlmyguJRy2+y1Eki2saCII/e3BrIogKj+f2r6du0ZYkdk0qUhM1NB4/vpNE/aN1LNZcVZl5soBg4qJsv+ZzcjxvelBqD1+rBkcQ95Y/Ik2vmXewY5nT+XDS7qDC+Mj10N8EeR7iViGki/Y+LSYIb4UuZSyD7ZA2ffHDGEseoahfJnmhDP2Qhnae+pnfkre8zjdepJPWzdTwiGPQ7KQg4QzYThqby7gextSmsn37e1mxYkS+pqsP/BRMVH2L3M9cnzP45fz5At5Pl1+H7+JnRTc8ddeOAdeglQHODHsXA8xt0jBRMmbKC8teiP24G68SSLBOwaDBHjElnEXylzJI2LBw5zAtf77uUR+yDLpZpvfwcveds2k73XSC/gkAjyryQU17O33zYRZe1jKAYGKibJ/meuR4xMcf/dAnr/mB/whGsTrx1w4K0n+eAvEW7CAZGmEZHoxt1+8mpdfdS+eO36vPAQB8a7hAp3p+LgLZVM0uIhaEgjKw+YEXM8n4dg8NYv3+eDmbjb97Htc2PdVjB2lJd1MukaAt/bbk4aUphp/MpehqHpCZMrCRcVE2b/Msj9ib48/XHDpyRYpuT6uH2Gx1TXmy6oXzndOPbbF8ycWEgDfGMTIhEnpD5xyBNc/8Byu72NJsKfEN8HzM6USirq++D08yyFvomSHCmSSUcp5j67vfoYh/2o83x/TcNibLTKUd7nk/zyGYwuL07FxYay5DkXtbYhMWbhon4myf5llf8TeHD+Xy7J9ME/Z87EtIU6Jl7x2hvLl6pdNtcN+z2qx06wn+I6zjp9Hr+A7zjpOs4LdI+9p3sx/Jj/P6T9587idLpefsYor1hxJwrFx/UC8rlhzJJefsWrGb6USilpquimGE4eNgZ7hIjnfYRk9JKM23cMlerMFjDH0DBfoyZZwfR9bgiroHYOFYBpwzfiTWfX77CO09+TARj0TZf8y1yPHT76C7Pc+RtzYlCVOzBSwLZf1pXfQNVwgHY+Mj+FPkeQ/3X6ST0uwi6R2OdV/eG/i/OIvaE2lJs39XH7GqlmJx55UQlFd1mIyfh9F4sGud2NISJkuazEd6cAjyRU9IlaZkZJHZzpKb7aEbUkwft8PvJUj2puqYaz9HYrS3pMDH/VMlP3LDDyBeo//L9YHGLTbSJOl31rE+qZLeb5lNcbAYL5MZzo+o34JgEv4YXWsPAh5gt0kH7B/TGsqRVMqHY4YTga5mkeu3ydv48HN3Qzly2zeNczXSm/HNmVipoAxPgkp4eByZ/zdQNCd3pJw+MXfr6E54dDWFCNqW1RayESCvfEVb6ziIVx19+8AuPacY+ubeDADZjzgU1mwqGei7H/mYuR4TbXT+yTDrfa5PN30+urLkZLLiYdmZt00t1x66KdpzHN5oqSkQKQpNfaL91Hup3IX3xSzyZc8/ss7Dte/mEudH7FYuuiyFvPt5Hk8HjspsKcm11HJhXSkY+wYKOATeDK2JZQ9wxtWLmqIh6C9Jwc+6pkoC59KOXA4jv2IWJbLijfxytx/150P2EYHCUpjnksQ7G/f17mfisfw4Vt/TfdwgahtsyyTIGpbPOQfx/vN1dx16o/5RGIdD8vxE763Si7EtoSlLcGSLs8YDl+U5JqzX8kvn+9riIcwqxUHyoJExURZ+NSWA4vQlErTmkpxgX/3rMNae/Kj1HlEcUlQBAwJikRx+UHs3Kl3usyS2n0jnu/j+4Ydg3mMgZUdKV6xpJmWhMPlZ6zimrNfSWc6PuF7O/3ozurrvoETDs3wzfe+lp/87WmcfnQnW/tHSDj2mHPvDw+hEQl/Zf+iYS5lYTBV1/wE5cZNTSmOtQf4xcfX1HXaM86+gHu++wwX+htJSYGsifNtay2vetdnwXpyn62brc0pxCI2rm8QEyTOmxPOmLv46cpup3q9Ud3p2nty4KNiosx/puuan8V04dmS2fEQ7+QheiXDVuOQkDLv5CF273gI1py3z3I/tTmFSr4DDCVv397FN7I7XXtPDmw0zKXMf/YIY42rnJpujXAd2Ju+iisRTCRB3Ak+upUti/uQ2pxCOu6QSTqUPUPZM/QMF3nPicv2yYW4NgxWbwhQUWpRz0SZ/0zXNV/vdOEpWFTeSU7SY54rS5xF5Z11H7uWWo/B9Xx254I+kWWtcSK2xR2Pb+fVy1v3maCoeCj7GhUTZf4zkzDWXJQbA33OUlLlXsoyuvHRMQX6nKUcsg/PU5tTeHxLPxFbWJyO0xyGvvbVEEZFmSs0zKXMf+YwjDUd3urLcHBx/DwYg+PncXDxVl+2z89VWZvckY5xZEeqKiSgPRnK/EfFRJn/zHXX/BQct+Y8ek/9HFmnnSYzTNZpp/fUz3HcmvPm7Jzak6EsRHRtr7Kwmc2irQVy3npW5irzioNqba96JsrCZY/O92rJcM30Xp69L5jo+5VXjZvsO6fnrQOtuFIWIuqZKAuXDWvHJ+ZLI0EY7OKNY/tTaicU1xsim+68ihKgnomizBum8iwGXgpEopbakuHp+lP2lunOqygHISomyvxlunDSdIu25uqiP9cLvhRlAaJiosxf6u18n6uLfnjeXHaY53uyvLizh66BIZ489KL6jqsoC5gFLyYi8lYR+YOIPCciVzbaHmUfMp1nMV3J8Fz1p6w6kydfdRWbc0kS3hCDkTa+7HyIyx5r11W0ykHLgu6AFxEb+BpwJrANeFRE7jHG/L6xlin7hHo73+dwzMp1z62gu2ndmOm7jnapKwcxC1pMgNcBzxljngcQke8C5wAqJgcC+2Jf/ByNWdHNgYoyloUe5loGbK35fFv43BhE5EMi8piIPNbT07PfjFPqpIGd79OhXeqKMpaF7pnMCGPMemA9BH0mDTZHmQ1z5FnUSyP3gijKfGSheybbgRU1ny8Pn1OUOUW71BVlLAvdM3kUOEpEjiAQkb8E/qqxJikHC7oXRFFGWdBiYoxxReRjwE8BG7jZGPN0g81SFEU56FjQYgJgjPkx8ONG26EoinIws9BzJoqiKMo8QMVEURRFqRsVE0VRFKVuVEwURVGUulExURRFUepGxURRFEWpGxUTRVEUpW4Ouh3wItIDvDSLb2kHeufInL1FbZoZatP0zDd74MCxqdcY89a5MGY+ctCJyWwRkceMMSc12o5a1KaZoTZNz3yzB9SmhYqGuRRFUZS6UTFRFEVR6kbFZHrWN9qACVCbZobaND3zzR5QmxYkmjNRFEVR6kY9E0VRFKVuVEwURVGUulExmQIReauI/EFEnhORK+eBPStE5L9E5Pci8rSIXNFomwBExBaR34jIxkbbAiAirSJyh4hsFpFnROQN88Cmvw1/Z78TkdtFJN4AG24WkW4R+V3Nc4tE5D4R+WP4MTMPbPrX8Hf3lIjcJSKtjbap5rW/ExEjIu3706aFgIrJJIiIDXwNeBtwDHC+iBzTWKtwgb8zxhwDrAY+Og9sArgCeKbRRtRwPfATY8zRwHE02DYRWQZcDpxkjDmWYCvoXzbAlA3Ank10VwL3G2OOAu4PP2+0TfcBxxpjXg08C3xqHtiEiKwA3gJs2c/2LAhUTCbndcBzxpjnjTEl4LvAOY00yBiz0xjzePh4mOAiuayRNonIcuAs4BuNtKOCiLQAbwK+CWCMKRljBhprFRBsNU2ISARIAjv2twHGmJ8DfXs8fQ5wS/j4FuDcRttkjPmZMcYNP90ELG+0TSFfBv4noFVLE6BiMjnLgK01n2+jwRfuWkTkcOAE4L8bawlfIfgH5jfYjgpHAD3At8LQ2zdEpKmRBhljtgNfJLij3QkMGmN+1kibalhsjNkZPt4FLG6kMRPwfuDeRhshIucA240xTzbalvmKiskCRERSwH8CHzfGDDXQjrVAtzHm142yYQIiwInADcaYE4Ac+z90M4YwD3EOgdAdAjSJyAWNtGkiTNAnMG/uukXkHwlCu7c12I4k8A/A1Y20Y76jYjI524EVNZ8vD59rKCLiEAjJbcaYOxtszhuBs0XkRYIw4BoRubWxJrEN2GaMqXhsdxCISyM5A3jBGNNjjCkDdwInN9imCl0ishQg/NjdYHsAEJGLgbXAX5vGN8O9jOBG4Mnwb3058LiILGmoVfMMFZPJeRQ4SkSOEJEoQcL0nkYaJCJCkAt4xhjzpUbaAmCM+ZQxZrkx5nCCn88DxpiG3nEbY3YBW0Xk5eFTbwZ+30CTIAhvrRaRZPg7fDPzp2DhHuCi8PFFwN0NtAUIqigJQqdnG2NGGm2PMea3xphOY8zh4d/6NuDE8G9NCVExmYQwAfgx4KcE//C/b4x5urFW8UbgQgIP4Inw/7c32Kb5yGXAbSLyFHA88M+NNCb0ku4AHgd+S/Dvbr+P5xCR24FfAi8XkW0icglwHXCmiPyRwIO6bh7Y9L+BNHBf+Dd+4zywSZkGHaeiKIqi1I16JoqiKErdqJgoiqIodaNioiiKotSNiomiKIpSNyomiqIoSt2omCjKDBCRF3VSrKJMjoqJoiiKUjcqJopSg4gcHu7SuC3chXJHOJsJ4DIReVxEfisiRzfUUEWZZ6iYKMp4Xg583RjzCmAIuDR8vtcYcyJwA/DJRhmnKPMRFRNFGc9WY8z/Cx/fCpwSPq4M1vw1cPj+NkpR5jMqJooynj1nDFU+L4YfPYJR94qihKiYKMp4Dq3ZG/9XwMONNEZRFgIqJooynj8AHxWRZ4AMQY5EUZQp0KnBilJDuA55ozHm2AaboigLCvVMFEVRlLpRz0RRFEWpG/VMFEVRlLpRMVEURVHqRsVEURRFqRsVE0VRFKVuVEwURVGUuvn/i6cnslNfc1oAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.swarmplot(dataset['Potability'], dataset['Solids']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 403
        },
        "id": "AQFldZaDogzW",
        "outputId": "8934a8b3-f9bd-4be5-c18d-1db5ecded3b6"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/seaborn/categorical.py:1296: UserWarning: 66.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
            "  warnings.warn(msg, UserWarning)\n",
            "/usr/local/lib/python3.8/dist-packages/seaborn/categorical.py:1296: UserWarning: 51.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Data Preprocessing"
      ],
      "metadata": {
        "id": "ycOuCfM7xJKT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X=dataset.drop('Potability',axis=1)\n",
        "print(X)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8mEn_XdMxMp9",
        "outputId": "9b663c6c-c471-4554-bb1b-fffc324395f8"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "            ph    Hardness       Solids  Chloramines     Sulfate  \\\n",
            "0     7.080795  204.890456  20791.31898     7.300212  368.516441   \n",
            "1     3.716080  129.422921  18630.05786     6.635246  333.775777   \n",
            "2     8.099124  224.236259  19909.54173     9.275884  333.775777   \n",
            "3     8.316766  214.373394  22018.41744     8.059332  356.886136   \n",
            "4     9.092223  181.101509  17978.98634     6.546600  310.135738   \n",
            "...        ...         ...          ...          ...         ...   \n",
            "3271  4.668102  193.681736  47580.99160     7.166639  359.948574   \n",
            "3272  7.808856  193.553212  17329.80216     8.061362  333.775777   \n",
            "3273  9.419510  175.762646  33155.57822     7.350233  333.775777   \n",
            "3274  5.126763  230.603758  11983.86938     6.303357  333.775777   \n",
            "3275  7.874671  195.102299  17404.17706     7.509306  333.775777   \n",
            "\n",
            "      Conductivity  Organic_carbon  Trihalomethanes  Turbidity  \n",
            "0       564.308654       10.379783        86.990970   2.963135  \n",
            "1       592.885359       15.180013        56.329076   4.500656  \n",
            "2       418.606213       16.868637        66.420093   3.055934  \n",
            "3       363.266516       18.436525       100.341674   4.628771  \n",
            "4       398.410813       11.558279        31.997993   4.075075  \n",
            "...            ...             ...              ...        ...  \n",
            "3271    526.424171       13.894419        66.687695   4.435821  \n",
            "3272    392.449580       19.903225        66.396293   2.798243  \n",
            "3273    432.044783       11.039070        69.845400   3.298875  \n",
            "3274    402.883113       11.168946        77.488213   4.708658  \n",
            "3275    327.459761       16.140368        78.698446   2.309149  \n",
            "\n",
            "[3276 rows x 9 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y=dataset['Potability']"
      ],
      "metadata": {
        "id": "rhJvGOcvy98M"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KXd_4XvCs-sT"
      },
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, random_state=42)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(Y.shape, Y_train.shape, Y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l9RP2P21zl03",
        "outputId": "bc5acbcb-bb24-49c5-e5f0-a56fbb8e3eca"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(3276,) (2620,) (656,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Model Training"
      ],
      "metadata": {
        "id": "7XFo4M95FcCi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = RandomForestClassifier(n_estimators=20)"
      ],
      "metadata": {
        "id": "DLoZcC50Fesh"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X_train, Y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hMDmW1mnFwBT",
        "outputId": "83129373-bb1f-44ca-8a77-e6c1d5defd4c"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestClassifier(n_estimators=20)"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Model Evaluation"
      ],
      "metadata": {
        "id": "TQwd5E7_GJ9J"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "LyeK0r7QGMep"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_test_prediction = model.predict(X_test)\n",
        "test_data_accuracy = accuracy_score(X_test_prediction, Y_test)\n",
        "print('Accuracy of the model:: ', test_data_accuracy )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fcJf1SQ-GYUa",
        "outputId": "0ca1059e-7b39-4b36-f37f-a9ee7c87c294"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of the model::  0.6783536585365854\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Prediction System"
      ],
      "metadata": {
        "id": "vPbqIfHTUG_S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input = (6.347271761,186.7328807,41065.23476,9.629596276,364.4876872,516.7432819,11.53978119,75.07161729,4.376348291)\n",
        "input_numpy = np.asarray(input)\n",
        "print(input_numpy.shape)\n",
        "input_reshape = input_numpy.reshape(1,-1)\n",
        "print(input_reshape.shape)\n",
        "#print(input_reshape)\n",
        "prediction = model.predict(input_reshape)\n",
        "print(prediction)\n",
        "\n",
        "if (prediction[0]==1):\n",
        "  print('Water is potable')\n",
        "else:\n",
        "  print('Water is NOT potable')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1ARJHs-RULEu",
        "outputId": "f6a4be25-00ea-4a33-ff6a-e9ee16f189c1"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(9,)\n",
            "(1, 9)\n",
            "[0]\n",
            "Water is NOT potable\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but RandomForestClassifier was fitted with feature names\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "---\n",
        "---\n"
      ],
      "metadata": {
        "id": "eDc-_qCwpzl7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**1. SVM**"
      ],
      "metadata": {
        "id": "Sb8YRr6qP_kC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn import svm"
      ],
      "metadata": {
        "id": "VuZH9MQBQE0u"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset = pd.read_csv('/content/diabetes1.csv')"
      ],
      "metadata": {
        "id": "YTsi9CH-ilKA"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IFWNPIUFjZYe",
        "outputId": "a073800f-acdd-4b3e-ddd4-0abcddf4254a"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(768, 9)"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "ddsbgBU7i73H",
        "outputId": "150fa2eb-01bf-4d8e-f39e-407db38225e2"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
              "0            6      148             72             35        0  33.6   \n",
              "1            1       85             66             29        0  26.6   \n",
              "2            8      183             64              0        0  23.3   \n",
              "3            1       89             66             23       94  28.1   \n",
              "4            0      137             40             35      168  43.1   \n",
              "\n",
              "   DiabetesPedigreeFunction  Age  Outcome  \n",
              "0                     0.627   50        1  \n",
              "1                     0.351   31        0  \n",
              "2                     0.672   32        1  \n",
              "3                     0.167   21        0  \n",
              "4                     2.288   33        1  "
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    {
      "cell_type": "code",
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        "d_dataset.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MrTluSFSzy4s",
        "outputId": "c3aa052f-8a75-4689-813a-9b3985bca40b"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 768 entries, 0 to 767\n",
            "Data columns (total 9 columns):\n",
            " #   Column                    Non-Null Count  Dtype  \n",
            "---  ------                    --------------  -----  \n",
            " 0   Pregnancies               768 non-null    int64  \n",
            " 1   Glucose                   768 non-null    int64  \n",
            " 2   BloodPressure             768 non-null    int64  \n",
            " 3   SkinThickness             768 non-null    int64  \n",
            " 4   Insulin                   768 non-null    int64  \n",
            " 5   BMI                       768 non-null    float64\n",
            " 6   DiabetesPedigreeFunction  768 non-null    float64\n",
            " 7   Age                       768 non-null    int64  \n",
            " 8   Outcome                   768 non-null    int64  \n",
            "dtypes: float64(2), int64(7)\n",
            "memory usage: 54.1 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset.isnull().sum()"
      ],
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        "colab": {
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        },
        "id": "juiJxl6ijWOT",
        "outputId": "8368b47c-5b63-4149-b0ef-7156e190cde3"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pregnancies                 0\n",
              "Glucose                     0\n",
              "BloodPressure               0\n",
              "SkinThickness               0\n",
              "Insulin                     0\n",
              "BMI                         0\n",
              "DiabetesPedigreeFunction    0\n",
              "Age                         0\n",
              "Outcome                     0\n",
              "dtype: int64"
            ]
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          "execution_count": 31
        }
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      },
      "execution_count": 32,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
              "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
              "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
              "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
              "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
              "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
              "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
              "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
              "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
              "\n",
              "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
              "count  768.000000                768.000000  768.000000  768.000000  \n",
              "mean    31.992578                  0.471876   33.240885    0.348958  \n",
              "std      7.884160                  0.331329   11.760232    0.476951  \n",
              "min      0.000000                  0.078000   21.000000    0.000000  \n",
              "25%     27.300000                  0.243750   24.000000    0.000000  \n",
              "50%     32.000000                  0.372500   29.000000    0.000000  \n",
              "75%     36.600000                  0.626250   41.000000    1.000000  \n",
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              "      <td>21.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>62.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>27.300000</td>\n",
              "      <td>0.243750</td>\n",
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              "      <th>50%</th>\n",
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              "      <td>117.000000</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>23.000000</td>\n",
              "      <td>30.500000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>0.372500</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>80.000000</td>\n",
              "      <td>32.000000</td>\n",
              "      <td>127.250000</td>\n",
              "      <td>36.600000</td>\n",
              "      <td>0.626250</td>\n",
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              "      <td>67.100000</td>\n",
              "      <td>2.420000</td>\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
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              "\n",
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              "\n",
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              "          document.querySelector('#df-cf648914-ef87-4254-8da2-1ac132dd0503 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-cf648914-ef87-4254-8da2-1ac132dd0503');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset['Outcome'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iIIAMaxxkG6D",
        "outputId": "9b97ea9a-2b21-447f-98da-f066ad593490"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    500\n",
              "1    268\n",
              "Name: Outcome, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "d_dataset.groupby('Outcome').mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "5FdINFbRlB6S",
        "outputId": "46b9d795-9567-4045-9c9e-6a510c917e01"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
              "Outcome                                                                      \n",
              "0           3.298000  109.980000      68.184000      19.664000   68.792000   \n",
              "1           4.865672  141.257463      70.824627      22.164179  100.335821   \n",
              "\n",
              "               BMI  DiabetesPedigreeFunction        Age  \n",
              "Outcome                                                  \n",
              "0        30.304200                  0.429734  31.190000  \n",
              "1        35.142537                  0.550500  37.067164  "
            ],
            "text/html": [
              "\n",
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              "    <div class=\"colab-df-container\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pregnancies</th>\n",
              "      <th>Glucose</th>\n",
              "      <th>BloodPressure</th>\n",
              "      <th>SkinThickness</th>\n",
              "      <th>Insulin</th>\n",
              "      <th>BMI</th>\n",
              "      <th>DiabetesPedigreeFunction</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Outcome</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.298000</td>\n",
              "      <td>109.980000</td>\n",
              "      <td>68.184000</td>\n",
              "      <td>19.664000</td>\n",
              "      <td>68.792000</td>\n",
              "      <td>30.304200</td>\n",
              "      <td>0.429734</td>\n",
              "      <td>31.190000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.865672</td>\n",
              "      <td>141.257463</td>\n",
              "      <td>70.824627</td>\n",
              "      <td>22.164179</td>\n",
              "      <td>100.335821</td>\n",
              "      <td>35.142537</td>\n",
              "      <td>0.550500</td>\n",
              "      <td>37.067164</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4d635c7b-1b38-4bf5-af7b-d333ab99330f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4d635c7b-1b38-4bf5-af7b-d333ab99330f button.colab-df-convert');\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4d635c7b-1b38-4bf5-af7b-d333ab99330f');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Data Preprocessing**"
      ],
      "metadata": {
        "id": "_FeyEUkwlWjt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "metadata": {
        "id": "Y7S75SWhkY5f"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X=d_dataset.drop('Outcome',axis=1)\n",
        "Y=d_dataset['Outcome']"
      ],
      "metadata": {
        "id": "YLgQfzYPlY6w"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(X)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9AuD6M7pl0tm",
        "outputId": "40eb5d87-5a52-4b14-c478-c94d79a503a9"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
            "0              6      148             72             35        0  33.6   \n",
            "1              1       85             66             29        0  26.6   \n",
            "2              8      183             64              0        0  23.3   \n",
            "3              1       89             66             23       94  28.1   \n",
            "4              0      137             40             35      168  43.1   \n",
            "..           ...      ...            ...            ...      ...   ...   \n",
            "763           10      101             76             48      180  32.9   \n",
            "764            2      122             70             27        0  36.8   \n",
            "765            5      121             72             23      112  26.2   \n",
            "766            1      126             60              0        0  30.1   \n",
            "767            1       93             70             31        0  30.4   \n",
            "\n",
            "     DiabetesPedigreeFunction  Age  \n",
            "0                       0.627   50  \n",
            "1                       0.351   31  \n",
            "2                       0.672   32  \n",
            "3                       0.167   21  \n",
            "4                       2.288   33  \n",
            "..                        ...  ...  \n",
            "763                     0.171   63  \n",
            "764                     0.340   27  \n",
            "765                     0.245   30  \n",
            "766                     0.349   47  \n",
            "767                     0.315   23  \n",
            "\n",
            "[768 rows x 8 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "khbBqCO2l61E",
        "outputId": "7ec99ea1-eda2-464e-a63a-f4686cb9d879"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      1\n",
            "1      0\n",
            "2      1\n",
            "3      0\n",
            "4      1\n",
            "      ..\n",
            "763    0\n",
            "764    0\n",
            "765    0\n",
            "766    1\n",
            "767    0\n",
            "Name: Outcome, Length: 768, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.pairplot(d_dataset[['Insulin', 'BloodPressure', 'Outcome']]);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "zoHakdI0mixg",
        "outputId": "ebc446f5-dbe3-442c-df75-58b482a0f515"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 540x540 with 12 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correlation =  d_dataset.corr()\n",
        "sns.heatmap(correlation, cbar=True, square=True, fmt = '.1f', annot = True, annot_kws={'size':8}, cmap='Blues')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "m2lkXOJjBBOq",
        "outputId": "7591e607-db75-4ab0-cf24-e0530859588c"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc4a8f78fa0>"
            ]
          },
          "metadata": {},
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.lmplot(y=\"Insulin\", x=\"Glucose\",hue=\"Outcome\", data=d_dataset);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "id": "bATBFhI2CTGw",
        "outputId": "4849f453-473a-4d60-f1ac-c154f5bcd300"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 413.25x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.swarmplot(d_dataset['Outcome'], d_dataset['Insulin']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 403
        },
        "id": "XtEzqd_Rn7a-",
        "outputId": "1db4b1e6-f82c-46df-abd2-6a232c139f59"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/seaborn/categorical.py:1296: UserWarning: 53.0% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
            "  warnings.warn(msg, UserWarning)\n",
            "/usr/local/lib/python3.8/dist-packages/seaborn/categorical.py:1296: UserWarning: 42.5% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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3z7HRCdKLq9lhSF67akggDraqwqRC0V3p6EzhKrOf6UAlcgmpIzwOJJltvwG8q2laFFAK3G0YvxsoNYy/azhOcY55ZEoUOjM/8pXRgVz70V7e2pTC08sTuPPLQ9YzTqFQWJ2O+hTu/D0XF0KEAFcCrwJPGvwRlwI3Gw75GngJ+BgpMi8ZxlcAHwghhNaR2t6KDnNFdCCbnpjI7tQi+ge68/2BTBqa9Mb9e08XczS7nOgQDytaqVCYUVMieyV497S2Jd2CjnZee1MI4S6EsBNCbBFCFAohbu3Aqe8BzwItdx0foMysL0M20NI2KRjIAjDsLzcc39qW+4QQsUKI2MLCwo6Yr2hF7wA37hzXk9GRPrQXfaoiUhUXDDvelC04/zUUvpwpxUHRqXR0+ehyTdMqkMls6UAU8Mx/O0EIMQsoaCmVca7QNG2RpmkxmqbF+Pn5nctLdwuS8yq4+oPdRP55HfM/P8A1Q4NxtDP9GUzs48egYDVLUFwAFJ2Cba+C3lCGJWMP7P/YujZ1AzraT6HluCuB5ZqmlXcgwWkccLUQYibgCLgD7wOeQghbw2wgBMgxHJ8DhALZQghbwAPpcFacQx7/IZ6U/EoAdp0qwsnOhs1PTGLT8TwCPByZMbCHlS1UKAwUp7YdKzp1/u3oZnR0pvCzECIZGRm0RQjhx/+IPtI07c+apoVomhYBzAO2app2C7ANuN5w2O3AasPrNYZtDPu3Kn/CuaWyrtEoCC0cziwlzMeZSX39GNfLB3vb3xylrFB0DuHjwLHVrLXfldaxpRvRUUfzc0KIN4FyTdOahRDVdDz6qDULgCVCiFeAI8DnhvHPgcVCiFSgBCkkinOIm6Md/Xq4kZxnEoboYA9mvr+LE7kV2NkInpjWh4enRFnRSkW3p7kRbOzA0R1uWw3b35Dd14beDIOu/d/nK/4QoqMP40KIsUAEZkKiado3nWNWx4iJidFiY2OtacJFx6n8Sp79MZHjORWMi/IhwN2RJYeyjPt1AnYtuJRgTycrWqnolpScgZ/uhexD0GMwzFkIAQOsbVWXRAgRp2laTHv7Opq8thjoBcQDzYZhDZlspriI6B3gxsqHTA3O7/naMi9Br0FWSY0SBcX5Z+3jUhAA8hJh5f3wwC7r2tQN6aijOQYYoNb4ux7TB/bg16QC43aAuwPDwlTpbIUVyDlsuZ2XCCVpMuKoukj2aO49zTq2dSM6KgrHgB5AbifaorACN8SE0tCsZ/WRswR4OPL41N6qzIXCOoSPhVObTNshl8BXs6DCEKB4fCXc+iNETbWOfd2EjoqCL3BCCHEQqG8Z1DTt6k6xSnFeuWVUOLeMCre2GYruzlXvw89PQPoeCBkB0TfA6ofNDtAgcZkShU6mo6LwUmcaoVAoFLgHws1LTdu5CW2PcfU/f/Z0Uzoakrqjsw1RWI+M4mo2Hsujh4cjVwwKVLkKiguDwCEwbD4cWSy3vSNhzMP//RzFH+a/ikKrjmsWu5CtFVTntYucI5mlzFu0n3pDUbwVvbNZfPcoK1ulUBiY/QGMfkjmKYSNkfkLik7lf/Vodvtv+xUXPjlltby2PomUvEom9vbj2Rl9cbQzOZK/2ptuFASQpS+O5ZSr+keKCweVq3Be6ahPQXGR8uC3cSRmy8qSqQVV6DWNl64eaNzfkSDj2oZmvthzhmM55YyL8uXmkWHodKqUquIPUJkPVfkQMAh0arnyQkKJQhemqKreKAgtbEnO57GpvVl5JAe9XmP2sCA2Hs8z9lSICffiuwMZZJfWctXgIOZeEspTy+NZfzQPgA3H8iiorOfJy/qc98+j6CLs+idsew30TeDbF25bBe5Bv+0auQmQsgG8e8HAOWBjCxW5cHQZ2DrC4Lng5NU59ndxlCh0YTyd7PBzc6Cw0hhFTE9fF676925yymoB8HV14Pt7R3HwTAn+bo78e8tJYjNKAbmUVNfUxMZjeRbX/TEuW4mC4vdRngNbXwHNsGRZlCJFYupfIe5rOXuIvh6Chv3na6RshCU3ma6Rsg4ufwU+mQC1JXJs/0fwwB5wcO3cz9MFUfO2LoytjY43rxuMj4s9AFH+rlwS4W0UBJCzibj0Uh6aHEVvf1cySmotrrHpeD5ujpbOPV83h843XtE1Kc823cxbKE2XSWq//AX2fQCfTYOMvXJf+h744gr44BLY/a4c2/+h5TWOr5RZzy2C0HLN5J8785N0WdRMoYszpZ8/+/48lcKqeoI8HFkWm9XmGBudQNM0eng4YqMTNOtNjoZQL2euGhzEC6uO0azXcLa3YcH0vufzIyi6EsHDwSMMyjNNYz0Gw+53TNv6Joj9Avz6wXc3QGO1HP/1JXANANH6WVaArp0sfKEy838PShS6Afa2OmOBu5nRgXy8/TTpxTUA9HB3JD6zjD4vbsDfzZGrBgeyNjGXZr1GuI8zD0+JItTbmYl9/EjJq2R4mBceziosUPE7sbGD21fLNpvl2TDoOrlUZC4KAHbOkLnfJAgtpP4KYx+D9N1SPACGzINRD0LCErn8BNJXoXov/C6UKHQz3BztWPvoeNYl5tKk1zhbVstH208DMny1+Hg9Gx4fT02DnuhgD2wMUUZBnk4EqcqpinOBdyTM+cRyrN8s03KPo6dMUrOxx5ASZTouYKAMmRswGxprIXqufK3TwUP74fhP0tE84Bqwdz5fn6hLoUShG+LmaMe8kWEA3PnlQYt9dY16iqoaGNvL1xqmKborcxfD8R/l076dC5RlQu/LYMbrsPXv0FANfa8AZ1/47jrTeU31MGiOfO3sDZfcYx37uxBKFLopLX6DmAhvtqUUGsed7W0YGKQS1xTnGU0P2/4BJXLWStJquGkpjH4Aht8G9ZXgFgCfT7c87/QWKM0AL1XQ8VyhRKEb8uG2VD7efppmvcZtY8K5ZVQYq+PPEuDuwIuzBlBe08hnu9Kwt9Fx4yWh+Ls7WttkRVcn64BJEFpI+B5qS2VUUm0pDL4R7F0sjxE2bccUfwglChcxmcU1uDvZ4uls3+FzDqQV89amFOP2wp1pfHpbDK/OiQZk17WZ/9pFZZ104n17IIPNf5qEh5NyLivOAVWF0FQLnmGW4y7tLFfaOcnS2Zqh2WP8dzDyPsjcB40yUIIxD7V/ruJ3o/IULkLKaxu54ZO9THxrGyNf3cKH21IBWHkkm0vf3s6417fy2a60ds9tneEsx8qMr386nGMUBID8ino2tUpeUyh+F5tegH/2hfeiDaGmZjkxfn0h5i7TtnswhI4xCUIL1UXweALMWQT3bpVJa4pzipopXIR8tiuNQ+ky67ihWc/bm1PoH+jGk8sSjLWMXlmXRJS/K5P7WtafHxXp3eZ6wZ5OvPPLSXq4OxqjjcxxtFfx3oo/SNYhmZjWwqnNMoN51P0y9FRnA7PehZi7oTIPIsZLP8KGZ6HZlJFPxHjZU2HIjaax+ipY8ygkrQWvCLjynxA56bx9tK6GEoWLkLQiy9htTYOtSQVtitvtO13cRhQGh3jy+rXRfLg9leZmjcsH9uAvq4/R2CxPHhbqSYiXE9ml8iluQKA7lw8IAKChSU9hVb0x56G2oZm3NqWw93QRA4M8eO6KfvipbGdFexSfajtWmAyfXwbZh+R2z4lwy4/QY5DctnOEud/IpLWaIhh6M4y4U+YqpGwAn94w4nbY/g8ZitryPstug6eS5fKT4jejROEi5PIBAaxLNLXL9nS244rBgXx7INPiOD9XB15cdZRmPdw6OswYVTRvZJgxJPWR7w8bBQHgSFYZS+8bTW55Hfa2Oqb298fB1oYtSfk8syKRkuoG+gS4smh+DAt3pvHDQfmeyXmV5JTVsOS+MZ398RUXI70uBVsn6U9owc7RJAgAZ3ZC8lrQN8Pu92RE0thH4eH9pmMSlsDK+03bp7dCnWn5E5DbRSdlkx7Fb0aJwkXI7KHBVNQ18WNcNr6u9jwxrQ+Dgj14dkZfPtp2msZmPXOGBfPeryepapBrsiuPZLPx8Yn4uzuwNuEs5bWNzBochJ1NW7eSm6Md1Q1NHM+poIeHI9HBHiz4UQoCwMn8Kl5dn0RCluV/xv1pJVTVN+HqoP6sFK1w6wHzV8Kut+WyUMzdMhehNWePwN4PMCasrX4IfHtD6Ei5fehzy+NPbZKzh6wDpjEnb5nRrPhdqP+9FynzR4czf7RlbPZDk6O4b0Ikeg2+P5DBkkMmJ11do57V8TlsPpHP8bMVAPx7Sypv3jCYTcfzqDGIx9R+/qyKz2HRTumo/ucvJ3nxyv4UVTVYvNep/Ep6+blSYFaBNcjDEWc75X9Q/AfCx0D4j6btolQpEk11ctveFXS2tGn2eHqbSRRaVz3V2cL4p2RyW9Ia8OoJM9+SsxDF70KJQhfD1vDk7+3adm2/uLrBKAgAlfVNxKaX8uuTk1gWm0W4jzOX9Q9g+Cu/Wpy35FAWA4PcLc6d0s+fGy8J5d5vYskqqcXbxZ5/XDdYNd9RdBzfKLhzAxz6TBa5G/WAdDK3VENtwdYBvr5KRh6Fj4WMfaZlqNEPglcoXPcp8Ol5/whdESUKXZTpAwMYGeHNwXRZTjg62IOxvXz4Zl+GxXH1Tc088v1hDmeW4WCrI/+y+vYuxye3juAfG2Rbz8l9/XlmumzruePpKWSW1BDo6YiDrZolKH4jwcMh+CPTdo9BsuDdgYWABsNuhZ1vQ0Ol3F9wQpa+cPSUy0ohMVYxuyujRKGL4mBrw9L7R3PwTAnNeo3RkT7oNc3iid/N0Zb6Rj2HM6VvoL5Jz1ubUph3SSjfmTmt758YSai3Mx/dMqLN++h0gghflVGq6CAVuTIh7cxOCBoKV38A/v1M+4/9CPnHof8sGPMoVBfIMtrmZB2AG746r2Z3J5QodGGEEIyK9DFu6xCseGAsaxPPUlHbyJWDA3lx5TGLc5r1GrMGBzFtQAAnzlYwLsqXoaGe59t0RVdl3ZOyXhHIyKMf74EHd8vt5PWwwiyBLW0H3PEzbSql+vX/7+9RlgVbXobCFOgzHSYtkCW7FR1CiUI3w8nehrkxocbtaQMC2JJcYNz2dbVnWJgnjnY2TGmV47A1OZ+fE3MJ8XTiznE98XLpeHkNhQKwjBICyD8qncT2LrKDmjk1RbLY3fRXZQvPxhqImiZLW4Dsx3DgE1kXaeit0pEN8MNN8roAeYkytHXqXzv3c3UhlCh0YXadKiQxu5zRkT6MCG+/iflNI8Oorm8yFMRz5KnL++DYTgTRz4lneeT7I8btrSkFrH1kPEIox7LiNxAyEk5uMG0HRJsK2nmGtj2+LBMOfyNzHIbcLCOLdDpZIuPz6VCRLY+L/wHuXA/uQSZBaCF5vRKF34AShS7KO5tT+NfWVOP2P66N5qaRYRRV1XMks4yBQe7Gpjn3TIjkngmRFuefLavlx7hsdDrBDTEhLIvNtth/LKeCE7kVqsy24r/T3ARHl0NhEvS+HGa9A6vqpE8hYKB0JFcXg4sPjH4YTv0in+6FDobfAZtfNJW5iP0MAvrLngmnt5kEAWSNpPjv4Yo3wdED6sxqfPlGndePfLGjRKEL0tis59NdZyzGPtlxmgB3Bx749jANTXpsdII3rhvMdcOD+WRHGqvjcwhwd+SZ6X3xdXXgyn/torSmEYCv96YT02qmIQS/qTqropuy+iFIXCpf73kf5iyE21bJukc/PyFrG/3yN5j3HURNhXu3ybpI/v2hIAniWjmZ0/dIUXBuW8MLZx9ZQ2nyn2HbqzJJzqc3THu58z9nF0KJQjdB0+CNDSk0NOkB6VB+fUMS1Q1NvLExGZClKo7mlHPXuAijIAAUVNbTy98Vbxd7Y1bznWN7GmsgKRTtUl0sZwnm7P8YBl0Pv/5NrvWDzDnY8rK80S+dD+VZ4Bogn/qFjWWl1GBDBFzYaOh/tUxYA/AMl+Gp7w6CqjxwC5SRTQNmyycYRYdRpbO7IHY2Ou4aH2Exdv+kSIqrLbOSy2oa2WbmZAYoqW6wyFJuIdTbmZ3PTuHT22JY/9gE/nrVgHNut6KLobORN3VzbB2gucFyeQekgKx7WgoCQFW+bMN5zUfg4g86O+lMHnmfXHr6cLQsjBd1Gcz9Fh45BFv+LgUBoDIXdr9jKQj7P4a3+8BbUXLWomgXNXiqDPoAACAASURBVFPoojwzvR8xEd4czS5nTC8fLonwJquklk92mLpbzR4ajK+rPdvN2nHa6gS3jg5nW0oBWSUyazTK35UrowNxcbDlMkPFVHO+2ZfOT4dzCHB34E+X9aFfD3fjPk3T+HRXGusScwnxcubJy/vQy8+1zTUUXRAnT1kau6Vkts4WJjwF9s4w8Fo4tsJ07NCbZSSROcWnwSdKzg6qi+RMQGuWs4mWInipv8iEtwFXySJ45hSabWfuh43PmbZ/+assmBc5+Vx92i6DEoWLHE3T+PFwDntTixgY7MH80eHY2+rIK6/jQFoJ5bUNtDwrPTu9LyFeTuxPK2ZIiCe3j42gpqGJ+KwyDpwpwdnehueu6IdOwMTefmQU1zA+yofbx/bE6T/0VFgem8VfVx83bsdllLJ7waXGCKav96bz2nq5PJWQXU58Vhk7nplsLMeh6OJMfxUipxh8A0Ku8wPM/hB6RENugux9MPx2KE2Ho8tM5/aaAt9ea5pV5ByCmpK2VVEzDVVU+8yAlHWm8b4zzI7Z19a2zP1SFOqr4OAiKDolzxkw+4995oscJQoXOf/aksq7v8onop+O5HA8p5zXro3muo/3klMmn/SXxWaz9L7RxER4c+vocG41K6RXXqtxxaAeTBsQwJxhQTQ0aVz+7k6q6mX3tfisMq4aGkywvcl/kF9RR05ZLYODPfjlRL6FPUVVDcRllDIuSrZI/CXJcn9OWS3HzlaohLjuROwXppt18s9QVSD7LZ89LBPUaoohYoJsjuPoDhl7ZfmLnpNkaWxz8hLbRheFXAK5iXLG0FQnl45CR8tQ17f7yKqp0Te0tSvkEvl72XzT+yR8b2j2c1fb47sJnSYKQohQ4BsgAJmOuEjTtPeFEN7AUiACSAfmappWKmTA+/vATKAGuEPTtMOdZd/FQm55LSfOVjAszAvvdpLFlsVmWWyvTjjLZQMCjIIA0qm8Ii6b6BAP9qeV4O/mQP9Ad7JKapj94R6j8/jHuGxmDw02CgJAVX0TPyec5f5JvQBYuOM0b25KoVmvEezpxMTelv1xdQLCvJ05eKYEIaCnjwt7UouN++1tdIR6KQd1t6G6yPLpHeDIYpnNfGK13D6zA1bcCffvhEnPQU6cXNppqGp7Pf/+srHOuqehLEM+1QcMgEWTTI7rUQ/KcNc1j8jtqnzY8TpMeEaGteoNfRqipsoEuNbCc/gbJQqdRBPwlKZph4UQbkCcEOIX4A5gi6ZprwshngOeAxYAVwC9DT+jgI8Nv7stK+KyWfBjIs16DUc7HZ/cOoLJff3JLa9lf1ox/QPd8XCysxAAVwdbfFzbioeNTjDlre2cLZdlim8eFYa3symaCGT00cjy2jbnehlCT4ur6nl7sxQEkE/9FXWNDA31JD6rDHtbHY9dGsUTS+OJy5DtQoeEeNC/hxtJeZU42ul4fmZ/fNqp4Krootg5tW2u4+QF6bstj8tNgGM/wcoHZF6Czhau+QQmPw873wJ9I4SNlVVRHT3gMbPnxYVmggCy6mr/qy2v39wgZxIL0i3H7V3Axl7uN9rXTrhrN6LTREHTtFwg1/C6UgiRBAQDs4HJhsO+BrYjRWE28I2maRqwXwjhKYQINFznoienrJa/rT7O0ZwyxkT68PLVg/BwtiOjuJrtKYX08nNlXJSPMUNYr9f4x/ok4w24rlHPGxtT0ID7v4mjoVn+J7h+RAiphVU0NOkRAp6e3peRPX2YMbAHG4/LSIxgTyfqG5uNggDw/YFM5l3SNoN0RJgXCVllJGTL6fngEA+uGhIEyNBU8y5tIJeLVj08jvSiajyd7dh8It8oCCD9CO/MHcLQUE983Rxwd2y/Bk1BZR2f7z5Dfnkds4cGM6Wff7vHKS4QEpfBrnek43fMI/LpHeTSUHUh+A+QkT/2LjD5ORmCCmDnDFOehz3/kg1yWvDpDdtfNyWq6Ztk4trTKTDyXulH8DYkWKZsNOUhxNxlKQgAaBAYDcfNejcInSzAZ07OYTljGXozxH0lx+zdZJ5DN+a8+BSEEBHAMOAAEGB2o89DLi+BFAzztZBsw5iFKAgh7gPuAwgLC+s0m881jxrKUwOsij9LswZzY0K466tDxhvt/NHh/P0a2Z+2Ua+nrLbR4hpFVfW898tJoyAArD+ay5YnJ/FLUj6rDufw2roktiUX8Pp10dw7sSel1Y2M7+3LU8sS2tg0OtKH9UdzqaiTy0WRvi4U1zQwMzqQu8dH4uVih4Otjus/2Ut6UTWXDQigl58LpwtNPaKHh3ty9Qe7SS2o4tJ+/kT5t40sKq5qIPK/RBw16zXmLdpPmuG6q+LP8ultMe1GOikuAHIT4Kf7MBapW/uYLGOdsUfe2PVNEDAIbv0J3AJg/BPQd6bMag4fL7OXPcPgx3LI2g9+/WDOJ7D4Wsv3qSmG42tgy0uGHs23ymimpbfKmQPAL3+BkfdD3lGTPcNvk0JVnAoJS6WfYtpL4BVhuvbBT2H906btCU9D4GDp22gvMa4b0emiIIRwBX4EntA0rcK8Vo6maZoQQvuPJ7eDpmmLgEUAMTExv+lca1Hb0GwUhBb2pBZR1OrJ+7sDGTw+rTe+rg442Npw1eBAVsWfNe6/fkQImwxP/y3UNTbj4WzHj3HZxpLYW5ML+MuqYyycH0Njs56K2kauGxHMuqMmfQ3zdsbL2Z5X5wwip7QOBzsd3+xN5//WngBk3+efHhzL3IX7KaqST2+r4s9yY0woY3r5kFlSy/SBAXy07bRx+ernxFyuHhKEk50NtY0y4cjZ3oYronu0+72UVjfg4mBLQnaZURBaWBGXpUThQiVtB226o51YLSN4Wp7a84/JZjmX3COf6suzYOAc0w3XLVBmMdu7mrqkDb3ZFL4Kcgnop7tNSzv7P4TaEpMgtNDcAPf8CqlbZAhrbTH8+hIMmw9XvitnH9tfh0VTZHjrpS/Ajjctr3H4G3jm1Ln4di56OlUUhBB2SEH4TtO0nwzD+S3LQkKIQKAleyoHMF/PCDGMXfQ42dsQ6etCWpHpxjcg0J26xmaL4/QanC6o4qNtp9FrGvdNjKRfoDtHs8sZGubJ1H7++LjY88q6JOM5Vw0JwlYnLLqiARxKL2XD0VxeWHWMkuoGYsK9eO/GoWxLKcDL2Z79acXc/uVBAIaFeXLb6HDOFNcYzy+raeSzXWlGQWjhRG4Fax8dD0BmcQ0vtCq9nZRbwYoHx7B4XwZCwK2jwtmbWsyBM6cYFubJTSPDqKpr4qHv49iTWoyHkx0PTLKsuwSyhMZnu9JIzqtkYh8/rjYsYSnOMZn7IeEHcPaVT+GuhmW7xOWQtk2GjcbcJZPOWugR3fY6zj5tl3FKzsDiOVBu6M2RfUgmobkHwton5NN/yEi4cbHs4XzZ/8nM5Iw98ubtGW65BARyeao1PaJlDkNIjJxttJTm3vch3PgtpKyH+O/k2NnD0rnc3CpBs/X2f6K+Us4ySk5D3yuh30xZLiBxqUyqCxwie0bbXrwlYDoz+kgAnwNJmqa9Y7ZrDXA78Lrh92qz8UeEEEuQDubyruJPAPjn3CE8sTSejOIaBgS68/drBnHibAVxmaVohoeuqf38ueebWCoNyzkr4rLZ+MQEHGx1vL4hmVfXJTE4xIM3rosmLqOUkuoGKuua+P5AJn0CXDmZb4rWiA724JkVicZIotiMUqL8XXl/3jB+OJjJV3vTjcceySxjcEjbwnaeLvYWpS0ABga588/NKSTnVTKhty8B7g7kV5j+Qw0L82RgkAevXzcYgNc3JBsT5n48nE2KweHcEpFUXtvIu7+e4oaYEJYbiu4FuDtQUFHH0kNZxu8hv7yOeye2FQ/FHyB9j2xz2VJG4vhP8NAB2P+RyQcA8mZ+/Reyp/LJjXJtf9yf4MDHUghi7pbd0mK/hErTzJagoXBqo+V7nlgtl3rqDSGl2QdlJvLV/5I3b32jrGjq0wsqzkqHs94UDUfUNJlbsOMNWSk1aqoMT03fI4WlRRAA0ODQp3D2CBac3AgTn4GdZrOF0Q+1/X5KzsDef8vZydBbofc0WHKzvPkDHPkWZn8EFTlyNgRSfM7Gw5yP/8eXf+HSmTOFccB84KgQIt4w9jxSDJYJIe4GMoC5hn3rkeGoqciQ1Ds70bbzzrAwLzY9MYHtKYVE+rnS09eFnr4u9PAYw69JBUT6ulBa02jR26CqvokfDmaycEcaTQaHc2J2OSPCK2nSa/yaJI/dmlzA7CFB2NvqOJZTwehIb+6Z0JMdJwstbEjKlbOJ0hrLchcAwR5OFsLi7WLPLaPCGR/ly4srj5FeLH0KmSU1LDHcrH85kc9NI0M5lF5KWmEVU/r68+yMfuw7XYyboy2Dgj1YcijT4n2WxmYxMsJyzbahSc+NMaHcNa4n+RV1DAhyZ9RrWyyO+eFQphKFc82Rby3rCpWkQfouOPy15XHHV8p6RctuMy3dDJ4nI3k0TWYoA9y+Rt6sK3Jh8A3ySXrXPy2Xe1z9TILQQv4x2VznxCq5/evLcNtq2R9hzkLpcK4pgSHzpNPZxk7Oag59Dpv+LAvoAYx7gjYNeWydpIiZC4NXuFxCChoq+zuEjpJ5DXs/kDOGwfNkhNQXM0xlM46vgms+NglCC4e/hvJWCxpHl8lqsHYXZ+h1Z0Yf7QbEf9g9tZ3jNeDhzrLH2mSV1HDjwn3GCKDbx4Tz8uxBjAj3ZkS4vEmuiMtuc15Ts2YUhBZOF1azN7XIYmz7yUJ+fnQ8r29IIq2ohv1pxQR7OlmEq46O9GFdYi5h3s4429tQ0yBvCG4OtoyJ8mHO8GC2JhdQ09DMrMFBONjpWH80F3tbHTdeEsp9E3ox5Z/bLd734JkStjw1GU3TKKtpZO7CfZwqkMIyM7oHHo52lJkV13N3tGNSHz92m9nv42LPoGAPHO1s8HCSzm0nO5N9AJ5OqnPWOcepnQRCJ0/Z/9gcOxfpLzC/uSculVE68d/KaCDf3jDtb3DdZ7K66ZFvoeIz2fVs51vyZuvXX964cw7LHIMWgodbttxsrpe+hfAx4N1TOq2rC+UyUUsHNVsHuTxkTuyX0sncImq2TtLJXVMCax+XrT2dvOQsZ9ML0p8x+iEZEfXJONm7AeTs4DKzOkoAaLKkRuuZi5OXbBJkXsbb3kUuk12kqIzm88SinWkWIaFf78vgtrERFnWAZg0OZPG+dGM46IBAd+6fFMnKIzkWReouHxDAybxK8ipM1/N3c+Curw4Zb8hJuRXcPDKU7LI60ouqGR3pzfLYLBbuTANgSl8/QrycaWzWk5RbwVX/3oOLvQ3PzezPneN6AvDwd4eNzunkvEoKKupxdbC1SG7zd5NOQiEE3+7PML4/wPqjeTw+tTcfbkulSa+hE7BgRl+uHR5CRV0jaxPOEuTpxHNX9KOwsp57v4klOa8SL2c7ZkYHGkXSwVbHk5f1/eP/CApLRj8oZwGVhlXaAdeYHLE/3GxaZ5/yvOlp3Igmb9yHPpWb+UelGFz/JXw6xZSX4B4Cjx6Gvf+SYZ+LJkHERPn0XnpGziaG3dK2D7O+WS4LfTPHNLPIjZc34ejrDSZY+uTQmmHWe3J/SZoUk3VPymgpBw+4/BUZXfTFDJN9R76V9ZjKzGa0taVSuFrjGS6XyXYbVsPt3WDis1Kwls03OMQFXPoXsLl4b60Xr+UXGYXtVB5NyCrjzz8d5XhOOWOjfHn92mh+emgc3x/IICGrnCn9/PF0sufbe0bxzuaT5JbXctWQIG4ZFYansx1PLk2goVmPk50N90zoyYIfLTtOHckqZ8PjEwB4YeVRSsye2LelFLLh8Qmsis8xilB1QzMvrznO5QMCCHB35NdWJSq2nyzkpasH8tKa4zTrNdwcbblycCAfbD3FkFBPCqvafsYof1d2PjuFuIxShoR4EubjTEFFHcfPVlBYWU+ghxMeTna8viGZ5DxZF6e0ppFfk/JZ9+h4zhRXM6qnD35uKuHtnOMZJm/YKeshYYnM7F04EWa+DU8cldm/WbFy6aXvDLl00nIj7n9V23pChUlw4CPLRLWKbFk+++BC01j6Tpj+Gox5WN78hQ56TzflLehsYfQDstxF66WmlA0mURjzCGx+wbSvxS8QMQF6TpRhs7mGUOz6ctjxllzqaW1fwYm2341XmPQjxH8rt316ywqt7oEw6FpI+lkudy2eAwOvgYcPwdk4CBwq/SEXMUoUzhPXDg82JpMBRPg4s2hnmvFG+MuJfOxtdVw1OIi/rTmOXoMVh7O5MSaUN64fzOUDA1h6KItD6SWMjvRh1uAgRkf6EJ9ZRv9AN7xdHHjl5yQqzZ7ie/m5UFHXiIOtzpiLYE5FbSOn8i1LCTTpNdIKqwlwd6SXnysnck1RTb38XJg/Opxp/f1JLagiKbeCF1eZoo/mXRKKjU4YE+58XGS/5092nCbRUK318am9eX7lUbYafCf70op5fEk8NQ2W9pXVNOLuZMeswSrqqFOxd5Y3/dRf5HZuAiy5BeZ9Dzv/aRKBlPVwywrpGPaOlOGlP90r/QEtOHiASzthxLUlbccKkmDDAjl7sHOGyQvkNTP3y6f8HW9Bn+ltz/PtI4Vkz/tSIHpNlWM9J0mxeS1QruVPfl6+hzn15e0kuiEFJH0XFMrCjbgFwdBbZCTWmIdlWY74H+BfQ2HEHXImcOATU2G+w1/LENspXSPpTYnCeeLygT347LYYVsXn0MPdkXkjQ5n2jqXT6kBaCXnldZi7EJbHZTE60psnzZLP9p4uZveCS/lyzxk+23WGZr3G3EtCeeWaQby46hiV9U308nOloraRIS9vxtXelmuHB6MTGK/dJ8CVmAhvThZUGW/QIB3Mw8I80TSNh6f04v9+PkF+RT3+bg68Niea3PJaHG1tmNDbjwUrEi3s/zkxl2/vGsmyuGxcHWy5e3xPXlh5zOjwjs8qo7KukQNnLG8S8Vll3DO+p0X0VJ8AV0K9nf/Qd67oIBl7LberC+SNznx5pqFK+gGCR0DSWhlxM/EZeeMtTJaCMOsdeYNNXGoKQw0bI5epDn5q+YRu62Qqld1UJwXirk2yE1u94UEkYzcMuUmWv2iul9ce/aB0XrdE+4AMUw0aJqOmjNd7RlZezTP7G/WJgglPSoFr6dsQNhb6XSmjmE6skdFTVfnyPYbfJvtBtFwXpM32bm0rtWbs+W3f+QWMEoXzyLQBAUwzS8hqnR08NNSz3cigra0a4VTWNfH13nQ+3GbqjfD9gUxGR/pw8IVpFFTWsTbhLG9vltVTK+ubWLw/g3/fNIxfkwoorWngykGBaJrGraPCqKhtNLbjfHZ6P/LK67j760OcLqzG1cGGv80awPUxITyxJJ4tyQXY6gR3T+jZ7mccFenDGEOF1LrG5jYRUBuP5TE01JNdp0yO5gGB7jwzoy86nWBLUj69/d3488x+Hf1aFX+UkBgZv9+Ck5csU9GakjTZQrOFU7/CQ/tlBE92rFz2cfKCh/fDyU0ypj/kEnAPgluWywSyunJZEqP1UzzIqJ16y3wbdLYwd7EUKVd/ecNOWmt5TP5RSGtV1A5kzsD4P0HyermkM+QmeZN/+IC0D+TNPWGJLKzXZzp8OFL6CEC2DJ34TNvrVuVJJ7V5wb6WjnBdACUK7VDX2ExseikhXk5E+LoAsm/BkawydEJYlH0+XVhFXnkdMRFeONjKHgJFVfUcP1vB4GAPvNqpbNrC+/OG8fTyBJLzKhnV05u/XzOQxOxyHvw2zvhEPzcm1ND20jJlo/VyC0jn8tVDggj3cTEuS7Wg1yCvvI5Nx/OoaWhme0ohPx/N5eu7RnLvhEiGhXoS4CGXjB5YHGcUq6r6Zt7bcoomTTOGyzbpNRbuSOPeCT0tekHfOyGS3Io6/r3lFNmltcyM7kGghyO5Zg72cB8XXpsTzZPL4jmUXsrAIHfemTsUB1sbnp/Zn+dn9v9f/zztUlrdQGJOOQOD3PE1FNxraNITm15i/FwtxGeV0azXGB7miVCtGmHKC3Kt/eQG6Uyd9S6EjpQ5BVmGXgX9r27rfM3YLWP+f7wXGgx/b5GT4daVkLzO1ESn16Uw7we4cx0UpkBlHji4Q+znpmsJHUReKsNMzbF1gCU3mWYtJ1bLVpzmMwB7V9mzIWGJ2YlCzix8e8sln2+ukc5gnZ0seTFkniyk1xI1tPtdOQupNnuIaaqVMyKhs1x2ipwM/WbB+mfk/v5XtS8eFylKFFqRVljFvEX7jdE+j0yJ4pFLo5j/+QEOpctCb2N7+fDVnSN5c2Myn+2WN8UgD0eW3j+GYznlPL4knoZmPQ62Oj66ZThT+wegaRp5FXX4uToYG8wMCvZg4xMTadZr2OjkzSnQw4m1j45ne0ohUf6uXNY/gOqGJnaeKuRQeik2OsHNI8O4MjqQRTvTLJaaJvb2s3j9c6JJSJztbTiSVWYR5rnjZCG/nsjnb2uOG0NX7x7fk9OFln6G8tpGTrTKmAbo28Od7+4Zxa5ThYyL8mVsL1+mvbODM4bM7d2pRdw2JpyVR3KorGvCz82Bv84aQKi3M8sfGGvxuX8LTc16Cqvq6eHuiBBydvHQd4epb9Jjb6PjvXlDiQ72YN6i/cbPdc/4njw7ox93fnXQmDh3SYQXi+8eZWwI1G1x8oSbvpdr9Tqz7+LuTdLfYOsoS1YvucXyPGEjncgNZg8gadtlqKh5V7XTW+WSUv4xGdoK0sk9+iF5vr2rXLvvP0uWtN73kRSB8HHyWPNlrNoSuSRVkCSjl+ycZS/nIfNkBNHBT6WfZOxjpuzs7W/IY0GG1f76knzKNw8jLT4lBas13j3h2k/NCvDdbXJ0953R9jvrAihRaMUHW1Mtwj8/2p6Kh5OdURBArukv3p/O53tMT8lny+v4aPtpdqQUGAvW1TfpeXVdEhG+Lty/OI7Ugir83Rx498ahxiY0QJsb48AgDwYGmTKM3RztWP7AWGIzSvi/tSdYvD+D1fE5zB8TzqEzpdQ3NTM8zIvSmgYamvTY2+q4ISaEgso6VsRl4+1iz9PT+xozhM1ZHpdlkcvw+e4z3DwyzCK0tH+gO9cMC2blEVOSjqOdjoYmPQ9/f5iymkb2nS7mT5dpRkFo4XRhFQeen0pGcQ1R/q7YmXVc+z2CsCe1iD8tjaegsp4of1cWzh/Bq+uTqG+S33lDs55Xfj7B5H7+lp9rzxmCPB0tejscSi9lTfxZ5rZTLbZb0t7NLWiY6fWEp2QEUssSz+gHZQ5AayrOth07ewTivjRtl2XKG+oVb8LPf5LF6RJ+gBu/gzGPyhuwb5R8gm9Nj2gZNVWYBLVl8nf+cZj0rLRxzWPyehsWyCS3MssESvSN7dvt108KTktUlU9v6XB29jYJQWu6mCCAEoU2tA6r1GuQVVrT5riskhpjeQrjuZV1FFU1tBqr5+W1J0g13GQLKut5ZnkCv/xpEi//fJxNx/OJ8HHmpasHMizM67/atvJwDomG8NGKuiaWHspi3WPjufWzgyyPy2Z5XDZDQjxY/sBY7G11PHJpb/zcHPhgWypPLUtg+sAA7G10RtGKCfeiVV4cALOGBOLtYs/W5AJ6B7hyw4gQjuZUcMfYcBKyynF1tOXeCT156LsjxpyFhOxyVsRlY6sTFsl2IZ7OONvb0j/Q3eI9NE1rd+nGfPxIZikvrTlOenENlw8I4G9XDeCZ5QlG0U4tqOLltScorLD8NyusqqfALIdDXhcyitv+OxZU1rUZ65Ls+1D+6GxkRdARt8sn+E0vyjXywTfKhK3mBplTkBMnn9THPGxKGAscCo8nyJpI3pFSMHLi4NiPppyG4BgZThr3hXT4gpxRBA5ua1NFjryBt8w0cuJg6ysw7nFDfkGiTGDz62eKDOo3Sy7fCCEd5MZKpwKu/rec1bSEkWp6mUsx8n651NWCT285kzi2QlZiBZlPMehaudR0Zjs01knns60DVBXKmUTQMBnZVF0sfStpO+TnmvUuePeCLS/LvAdnH7jsZeh7hazSuv0fsiTHyHtholll1gsUJQqtmDMs2MIJ2jfAjTvGRrD0UJbxadTJzoa7xkWy82SRRZG7OcNC8HaxZ1msaVo6Z3gwm49bxvufLa/jzc3JxuMSssu5b3EcexZcysoj2fx0OAc/Nwcen9qb3gFuxvNah4/WNer5Yne6xZp9QnY5W5MLmDGoB8dyyi1yF77am8Frc6IpqKzD08mO2UOD2Z9WbNFSM8LHmZER3ozt5cvT0/uyPaWAO748ZLzRzxkWzLs3DiW1oNIiiQ0gs6SGp6f35e1NKTTpNcK8nWnW9Fz38V5G9fTmsam9sbfR8dr6JL49kIGzvS1PXtaHW0eH82NcNq9vTKa8tpEbRoTwwsz+3Lc4zpjfsTwuGyd7nUUCIMDJvErmDA/mm32mDNlrDP0YWsqAAPT0deHu8ZEsj8s2LqE52OqYGR1Ilyd1C2x63rS99jFZRnrJrdBo+Pvd/5F0CJ+NNy39nNosE9smLYBVD0rnrE+UrFPUMoPw6Q33bpNtNl39pLjYu8Dta6W4NDXAqPtkyOju9ywzmXtOkueZU3AClt8BBYa+3yc3wsDrZF7D0eVQfFqWvZj8nLzZGtGkI3vwXNrgHSlbfZ5YLX0mkxaAZwg8sAcSl0g/w5B5MiJp51tyFjFsvhSEI9/KmUxzg7zZ37JCCk3SGnnt9F3S3kvuhj3vybGaIlkSZP4qWHk/xrIbW/8Ofn2lD+ICptuKwhsbk/nhQCaujrb8a94whofLp/Rrh4dgb6tjXWIuIV5O3DexF35uDiy7fwxf70tHJwR3jI0gzMeZH+4bzcIdaeRV1HL1kGBmDOrBtAH+9PR15UhmKZdEeHPHuAgamvTGekEgi8bFtyqlXVhZz+e703hjo2ldc39aCbsXTDGueU/q68fBdNO0N9DDEVeHtv+E9U3yptc69BMgs6Sa0upG/r01lTc2pvDIpVEsnD/CGH10x9gIt0DhPQAAIABJREFUfjmRj6OdDRP7+PHprjSLJ/9V8TksmNGPSF9XwrydySwxPX1P7uPHA5N6ce2wYPIq6nj/11OsiJNLTi0F/EZFehv9MHWNDby46hhh3s48a+gwB/DdgUy8nO3aJPzFZ5UzLMyTI2bf3eS+fvxl1gBjC9BhYV7cNT4CB1sbPrl1BGsScujh7sT9kyIJcHdk+QNj+GpPOs2axu1jItr0eXjhp0R+PpqLt4sDn84fQZSZKF+0tA45BZnJ3Gi51MeZ3aZ8hRYSl0Fjjbw5g3xiXn4nPHwQ1jwsk7gc3OWTccydUJohy1Lrm2Q8v59ZJvqd62UJico8eRPufbm8wZoLRcR4KSbmZO6VVUcTfpDb2QflklBjq1leU60smNeScQxyltLrUvDrI8t4t1CaIbOomxtl6KmNHXw1yxRqmr5LisLG502lu2sMJblb+x7yj8HpbZZjzQ1yBtW6xHj6HiUKFyIvrTnGV3vlH2JZbSPXfryXF67oR7ivC1P7BzBrcFCbpKkhoZ68E2rZuSnA3ZG/XmUZuudga8ODky0zGv8yawB2Njp2pxYxINCdF67szyc7ThsziUH2LzicYSkURVX1HEgrJrOkhn1pxQwIdOfBSb3YfCIPbxd7hod50T/QDRd7G6oNT7/Bnk5M6y/DXoe0U/m0pr6ZpYa+zrX6Zt7alMKaR8bx0S0jKKlu4JoP9xhv9CPCvXCw1Vmcr2mg1zQOZ5Yya3AgsRmlFFXVc/mAHkT4uvDw94eJ8HHmjrERbE2xDKXdcCwP+1bXA9h8PM8oCC1kldTi6WxZN2lIiCcPTenFK+uSOHG2gnFRPvz5iv7Y2ei4Z0Ik90ywLJg3Y1APZgyy7OUwMMiDt24YYjFW19jMpuN5LNpxmuO5cimjvLaJy9/bSdo/rmxj70VH8PC2Y70vlxU9zdtQBg+HvART2QuQs4fsWMtzq/Jk4buW0ND6crncEzwCFl9jWpKJ+woe2A3uwXJGUFsql65cDQERdeWyXHb8d7Iiaf9ZMukseZ0sTd1C0PC2YajJ6+QS0B4zn8PI+yFiHEx7Wc4A7FxkXoKrv+yXYGMvo6ia6uDTS+UTfYudl/1f29yDE6vaZlRX5MjPad532idKRkS1zB5AilGfGZYRVi3f8QVOtxQF8+WdFl7dINcspw8MYOH8GJr18sbn7mhH3x6mp8XkvAqq6poYHuaFroOOUhcHW2NHtRaeuqwvZ8tq2ZJcQIiXE69eE82e1CIwC98WAjadyOf7A9JRtv5oHrOHBvH4tD48vuTI/7d33uFRVekf/5yZZNJ774UkhNAhdJCOiiKiiFjQxY5d111X13XBta37U0RxVVRcF1DsKE2QogLSSyD0VJKQAKmQOsnM/f1xJjNzM0F3XRQx5/M8PmbO3Dn3TuG897zl+9qD3zcNSiDAy5288loqa5uZtXQ/94xMITMxmD9e0pnX1+fSYtX43ZBEGpyyj1o5cPw0PWIDWbz9mO7Of2dhFfeMTGFrfqV90b6iZzSf7y7hH6sO26/xhat7YLFqLgV20QF6Qb6EEG/6JQbrXD0GAZf3jGbx9iLdjmRgpxCu7hvLn5fso7iqgVGdw3lkXGcCvN157fr/7B+WucXKjsJKogMcqcUg5UVAGvpmi5Upb262x2qcsWow79tc7hh+YcsWkH4ZDH1YFl4Z3KRIXPp4qUC66nGZhtl1Egy5X97Zf3aHjBGYfKVe0MGleikI/1jZk8AZzSrz+usdgXzMtXKnkbvOkdq67m9w21oZeP7yPrkL8YuC6z+S/vmGahnA3vqG7JyWMATG/wPen6Kvng5KkJpMbh5QXQTpl0LKWFh4NeSskcf0uFbGOF4fLBdzkC6szFscBgHkjunEftfPLawLJFVC/reOsW6Toc80aUAKN8ljrvyn1Fk6eUDGELwCpZFJGweXPC/dWi2N8rzdzhKw/hXRIY2Cyc2gS810ZtX+E2zPr+TPS/bZK2yv6h3DS9f24r4PdrM0S2ZWdInyZ/HtAwnwdqex2UJdU4uuIb3VqnGqVlYCOwdUy2ub8PN0I8Dbnbdv7kezxUq92YJByF4Fm3LLyS45jZtBcO+oFLtBaGXZ3lIOHD+tC3J/tKOIZyZ159V1OQBszoNNORWsf2QEd49IIT7Ym/e+LyC7pIb+SXrZajeDoGdcINX1ZuqaXGsfkkK9eXZSN7bkVTA8LZzx3aPo8zeHi0HTYO76HMLbaBPtPlbNs1d147kVhzjT2EKIj4m/Tsigb0Iw2SU1fLyzGG+TkYfHpjEwOYQXr+nJi18f4XRjM9dmxnFtZhxWTePTuwYT5GPSZS1V15sxuRnwNul/vifPNBLkLY89VlHP1HlSlVYIuGt4Jx4ck8r0d7fzfa5cuAYlh3DT4IR2DUIrUQGeZ33ugmLMX2HUE4AAg+2z7HaVNAbWFkcwueuVUjvo5H5Z/OUZIO+MG2ukCyk0Vfrny/bBwS8c87v7tB9MrjvpMAggdwvb5skU1WbbDciZUtlWc8iDMu21uU7e1U96U7qZQCqyfnmfTEn1DJSP52Y6XE9eAdIgtRoEkOcwuDsMAshMpYp2OqyFpsidx+a50sDF9pOZSwPukNXNJw7IwPOAu2SwfvoKGS9xbqYz8TW4fI58vvXf/MAZcgejWS8YkbwL4yrPMfePSuGpZe1UVNr4fE+JTnLhs90l9IoPtBsEkIViC7cWEuRt4rkVUnNoWGoor93Qh5yTtdz3/m5KqhtICvXhnzf0IdzPgxkLd7GtoJIAL3eemtiVCT2iefKL/Xy0owiDgJsHJbLsvmEcOXGGIG8TYX4erN5/QpciG+jlTotFr99itcKKvfritpLqBnYdq8LNILjvg912I7I1r5IHRqfyZdZxvNyNJIf5cOVrm2i2WBmRFq5rpRnu58GnO4vZnCdjE1lFNQxOCaHFqj9/i0UjxEdvFNyNgoszIrmyVwx5p+pIjfBFIK9l2d7jmIwGbh6UyFV9Ynnj21zmrDlKY4uFizMieWhsGptyy/n9RzLTKD3Sjzen9SXC35OHP9rDyuwyPNwM3D86lbtHpHC8uoE7F+xkX0kNob4mnr+qB2sOnrAHpTUN3vg2lzBfk90ggNRdSos8e+9ok1EwoVfMWZ+/4GgvfVIIh0FoxSdEFn614ukPk9u4QaL7yNjAnvfBJ0wandj+svK4ZKc8JrSzNDDb39a/1lwnjYMzVYWw+i+OOIfFDF8/KXcKH02TOwvvULj4OZkhtOav+ljEln/Kjmdtcd4RtBKeIRf94u3ycUiqbAXqFSSzrRpr9LGQcU+7zgHtd1drb+E3GABXt+mvlQ5pFAraSU1sZWBysEuqKeCSfw9QUF7H7N1H7G6PDUfLefPbXFbvP2F3m+SX1/HEkmwyovztQeKahmb+9Ok+zC1WPtgmdwIW4O2N+QzvHEZ5bROvrM2hsdnCRalh5JXX0thsxWgQPDa+C43NFp0Q3XX941zSO4WA6AAvFm0r1L0fs8VKqJ8H6x8Zwd7iaq6Y69BsWXf4JA+MTqXe3IKnu5HEUB9+7+QSyiuv4+Mdxdw8KNEuwQ0wfUgiQ1JC2VZQSWWdGSHg7hGdeP2bXJbsKSHMz5PHx6dTUFFvN6xNLVZmrzlCSrgvz9tcdwBf7S/j35sLeGdjvt0YHio7w9+WHWBwp1BW7JOigo3NVl746jCj0yOYuz6HfSXybr+81swfPsmiR6y+J4Cmtf+9h/p4uLRKbaXZolFcVU9skNJgckEIuTg3VMusndqTstfyLatlyqqlWQZ9hZCLcKv7yd1b3j1X5uvTRDMmykwfZ+rKYfWTjgY59eWyW1rmLdIgtSWyu7762M1T1i0UbXUYoYA4uUPqPU1eZ3ODLGz7fIZsujP4fmnkVv9FBrZ9I2QQPWXMOf34fs10SKOw9uBJl7HR6eGM7hLBVX1i2FNUzeLtx+yLaYiPiduHJbNkdwlVtsBnq7vn4zaNcQ6VntEVfgEcLjuDsc2i3dBsYWeha3bQxqPlzNuQZz/3hzuKeHlKL840NfPtkXI+313M5L6xvH/bADYcLaepxYLJzUDXqAA2HD1F7qk6DEJWJscGeZEU4uNyjmSbf72tFAZI18yTE7rS0GxhzYETLs9X1ZvpHRfIxV0jcDcamJIZx9CUUOZvyicp1Idu0f7cMzKF7OOnmbNWLgTltWbuXLCTy3u4pn9uzqtwGdtbXKNr8dl6rW13IwCHT5zhcJm+2rqqvpkRaWE63aXkMB9uGZLERzuKaGyWi4aHm4GxGRFc2z+OpVml/OOrQzS2OHZBGlBc1aCMQntYrfDviY76gUPLpBsqurdMFS3ZJe/yJ70Ot3wlJSgaqqD7NVKHaMq/5XEn9kPKKNn4xtIMW5wa53Sd5Cpr3VDlqKtwDuwGJsgsosB42PqmdD8NuV/Kddy1UZ6/9oSsuP57ogy0T/ynDFR//6qc48hKWSmdMMSRAVV3SqbuPnxAFrF1ADqkUahuR3QuLdyXLlF+PL/yECE+Jl67rg/Ls0vx83CjZ1wg+0pqWHTbABZsKeRMYwvX9Y+nd3wgs9ccpabBkSEzonMYZotVV+swPC2MjGh/XTpppL8nk3rHsHi7w6gYhIx3tN2p7C6qYtneUipsvZI35VTwxo19aGi26Hotz7oig4RgH2avOcJbG/JZvreUZyZ1Y1xGBKsPnMAgYGKvGHs/5sGdQnA3CpotjhN6e7gx4Nm1lNc2MTQlhBAfk/28JqOBiloz97zvaG3YJz6Ig6Wnec7pbv/kmSaXhbTebCEmSN+e0GQ0MLVfHJ/sdCzUABd3jaSgoo7sEsdiPzwtjCEpofbMKZCL+sDkYPYVh+ncfSnhvvxuSCLh/p58mVVCdKAXveICeXtjHtf3j6e81oxByGu6/NWNeLgZuGdUCs1t3GIAhRV1DEwOcRnv8JTucRiEVvZ+KN04rT0MCjfC0gelAajIldXQVQUyCOsbDpf9n9Rc8gyQbpexT8lsp4KNslCu2ySZNeRsGELTwFwvq44zJsq/g5NkwZvRHVLHyv/M9TKraO9HMqg+9CF4uYdD2uLIV7LeQdfTGWloLM36sZYG6RJLHXsuP8FfLR3SKLRNfwRZoTz5jc3251LCffnyniHc+M5We41BcqgPn909mGOV9Ty9/CAlVQ0MTwvl1BkzJ840Mjg5hBaLlduHJRPkbWJPUTX9k4KYkhlHQog39eYWVuwrIy7Ym8cuTadLlD8vTenJ2xvycTMKZgzvREyQlz1g3Iqnu9G+MLeyNKtUV3QG8O6mAnrHB9lTXY/XNPLIx3vZ/Nho8streWJJNp/vLmFldimPjOvMbcOSmXdTJq+sPUp9k4XJfWN56esj9pjCxpwKpmTGEuhtoq6phav7xDL1rS26c87flK8LsIO8qx/USb+QmowGru+fQLC3iYVbjuHjYeT+0al0iwlg/s39mL3mCNX1zVzbL44JPaPpFRfI08sPcKjsDBelhnH/6BQ2HC3nyl7RZB8/TaCXO7cMTbIX77X2eIgL9sYgYOBza8lMDOaZSTKr64HFe+zXMiw1lIm9YnjkY7l4tZgtvPBVO7o3QFlNQ7vjHR7fCFehOJ9wmWnkTPF2+OpPsicByEBvTbE0FIuvl4u7uw+Me0rWEQy+V6ZtfnILfPucdPd0v0YuyqGdZZHY26MdQWrfSBnv8GyTfv3RNEfQecc7svjtdJuMqeLt4BcpdxCteIe6ppwa3KRrqoPQIY2Ch5ugbc+ZvIo6nbHIOVnLm9/lscupUCqvvI4Pth3jnY35djmLkuoGfj82jUBvd/7yhSOt7amJXXl8fBdumr+VT3aW4G4U/OHizqx/ZARvb8jjpvnbEMCMEZ1Y8cAwiqvqeW19LmU1DUzsGc26wycxt1i5YUACV/eJ0fnwAeKCvaR2kFMSlcnNQHaJPpOmos7MidONLNtbak9hbWy28uyKg1zcNZKEYG/GdIkgKsCTuGAvu0Fo5VhlPS9Mlnn9zRYr7gaBs3kyGQ3EB3vb0zxB6iLNGNGJilozy/eVEuxj4vZhSTy/8hA1DWZ+Py6NcV0jaWqx8Orao2wrqGRQcggzRqRgNAieWLKPL3YfJyLAk6cmdqN3fCAT526yx3WSQn14++ZMpry5WbdDeP2GPry/7RjfHpG7tOV7S2k0WzjT5svecLTc3kbUGQPQdq8QHahcR+0SECP99d/9H6DJWoThf5SZPa2BZpBaQq2Fb60UbJBpmq0aQ811sPJPkD4B/CJkllFrrURNEVRFwv223emaWQ6DANKVdHilzFKytMhgek2RPgsJYP8S6Vpy1kGKHygNzuLrZfqs0SSNR5cJcheU/al0GY17RhqPDkKHNAqdwv10iz1AZIAXB0rbyk27uhMKyutd9I025JSTd0ofqHxlbQ6Hy87YF61mi8YLXx0mJsiLp5c7Mp9mLT1AeqQff/x0L0WVjrvS2VN6Mq5rJF9mHeejHcVc0TOaZXuPY9Wge0wAV/eJxcPNyJy1Mr1OCLhnZAq7j1XrYhqJId7EBnnZtZcc7w1W7S/lhVVHMNv86IOT9e4igKFOwn3uRrnYt/ZpEALuHZVCSrgve45VUVTVgMnNwAOjU/lwWxGJId58/dBFhPp6MOL/vqHSNu+agydZcGt/vsouY5Et5XbD0XIKKupJj/Jj4RY5duZkLTMW7uShsWm6QH9+eR1vfJurMwgAn+wslrUebb6bIW12LUaDYHCnED7dVawb6xzh6/IbuKydOIjCxqgnpGBcTTHEDZDZOFe9BV/cK/szJAyBCS9LaW1nSeqAeFmD4Iy1WRaseYdIV5Mzp444/vZoJ1vMzROW3C3dV17B0jgJo15d1dMfxtvE904ekjUE4/4mM44ePiBjIBHdHIV1V78lU0wNbo4U3g5ChzQKpxubXcZGpIWRVVRtXxAv7hrBrUOT+WBbkd0IeLkbuXFQPF9mHdfdUWdE+XOoVB/sNLdYdIVgIPsQbDjimiK3NKtUZxBA1iOsPnCCldmOLIunJnYlKsCTf6w6zNjZ3xET6MVTE7tisWoUVdUzd10OQd4mxmaEs7e4hthAbym29+V+ukT56eby93RjR0GV3SAAfJ9XwYtTerJ42zGKqxq4rHsUd9oKt2qbWnh2xUG+zylnUKcQBiaFMCwthH+uz2PNwRP4mIzcNTyZ6/rFc82bm+2ZQ//6voBHL023GwTHez6uux6A5ftKXb6berPr5wjgbjAgBLr4S7CPiYxof10sIiPKn3tHpbI1v9Jem3LToAR6xgXy2Ph03t96DC93Iw+MTuVPn+1rexoOHD9NZmLHCDD+JIKT5H+thHSCW1bqj7n07/JuvLpQZvZc8Yo0Cs7+fJ8wmeZqdJOyFM7PJQ2T0hqle2Taq/Mdf9xAGafYs0g+rjsp3VV9bnKosrp7y34H0b3hjm9c34NnAHQa6TreXsppB6BDGoW2d/UAT365n5ggTx4bnk5KmC/L95Yy6sVviQvyYlR6OH6e7lybGYvZovHY+HReWXuU8lozw1JDeXBMKoHe7ry8xlEUM31IEhH+nrqAc2yQFxd3jdTpIAEMSArmA6dsJ5CyF5/uKtEdt2R3CV4mo/0OuaS6gXc25nP3iE7M31hgP87Pw43lDwxj4tyN7DwmXUae7gZmDE/mmyPlhPl58PuxaXYNIme6RPrzwuSe/GVJNp/uKqbsdCNPX9mNZ5YftGdaFVTU09xixWiANQelP7bObGHed3n4e7rr6ipON7ZwsJ1eDFEBXkQHeHG40XFnHunvSZ/4IL457Lir9HQ38LtBiazcV0a5TcE21NfEzUMSqTW38O4m+b7D/DyY2Cua4Q1hvPT1EVkbEe7LVX1i2H2sivem96O4uoHmFo2Xvj7Cu5sKCPEx8er1vUmP9OfW97brEgZa2ZhTrozC/0pkN7h/jzQK/jFysU0eIeWxsz+VBsHgBrMzIKIrjHxCxixKdkrZirJsqXcEsvtb9ymydsDdWxqQT2/Vn8/aIruo9Z4mjU+nkY7eCoofpUMahfbkogFKqhrZeLSc4soGPrP1DqisM1Pd0Mzndw/mpvnbyC45jRAwbWACj1zcmWVZpYyd/R0NZguXdoskPtiblHBfdhdVszW/gku7RVJRayYmyIthKaHsKKxkQo8oufAJuOOiZEL9PJjaL44Ptxdh1aTL59ahySzZc1wX5/B0N3KojXujsKKedW1SbM80tfDOxjx7+izIOIK7m5HFtw9kV1EVEf6e3DIkkdX7y+zqr61ZUuPnbOCAbeezbG8pbgbBplx96uiOwiqXALNVo912oomhPtwwIN7uKuoS5c+ApGB8PdyYs/YotU0teLkbubR7JPVNLQxPC+P7XOn3v35APJ/vLuHB0alUNci5iyrrGfb39QR5u/PoJZ1Jj/Tjiz2l3PiOXDj6JQSx4NH+zF2fw5O2OI+bQfDWzZnM/voIZTZZ7Yo6M3/+PJuxGRE6kT1nKs+4vh/FT8Bg0O8ohJC6RMMeljUCWe/L8fzvoO5BuNsWbzDXwbN6HTLy1svdR9ZimekU3lUK/LXi5imL03xCIfa30ybzl6JDGgUfk6DO3L5lyC+v00lRg1x4X1mbY3dLaBr8e3MhA5NCePxzh8thZXYZr17Xmze+zWW/093xo5ek4+vpxsMfOwrBpg9O5M7hnZjy5mZetPnoJ/SIYvrQJHrGBlLT0Mx1/ePs/nWT0cA9I1P4ZGexrtlNZkIQXaL9WeWUiWQQ0CnU1fdaVdfEoOfXUm+24GYQPHtVd75+aDhvb8yjoKKO/knBFFfV2w1CK5vzKkiL8NWplsYGeTGycxir9jtcQD4mI7cNTWZjTgUHbXPEBnkR5utBSrgv04ckUtdk4c3vcrn+7a0AdAr14eWpvVi65zhvO7X2nD2lJxYNe4YQyCK9jOgA++fVUGPh/1YfYfaUnizZ4/hMthdW8emuEl1TIdlCNJf8NrvEgoo68tp0mnNmbEbYWZ9TnCMKNugfnzwgC9cQMsMpMEFfvRzaGd4aKd1GIFVa+/5OKrb6hMliM59QFD+NDmkUgn08qDO331xlbEYE1fXNusBsmJ9Hu66F9gqvvjl8UmcQAJbvO05tmwyYRduOgdB0/vKle0u5/aJkHvpwD0v3HsfNIJjQM4pByaF0jvRl5b4yrJrGyM5hHD1ZS/eYACb2iqa4sp7+ScFsy6/Ex2Tk4XGd6Z0QSO+4QHbbsoJSw33ZfczRjrPFqvHcioPMvrYXC7cUYtXguyPlrNh3nMQQb131b/eYAP50aTp32no3R/h7cN+oFBqbLdw0MIGNOeWE+JoY3SWCv391iGEpIdw8KAENeGdDHg98KNNBe8YF8si4NHtVMkBueR07C6tYulffrWv+pgKdQB5IIcNLu+k/R4tV03XFa+V4dUNb0WIsVo0xGRE6ozo6PZyxGRG63gu6edoU0Sl+BqJ7yYyhVgLjpWR19sfSKKRfLmsHzhyXkhSp42DNk47jm05Ld9Mfc13nVvzXdEij4OxWaSXS34Mre8dy/6gUas0tlNU0sjmvgvhgb56b1J2mFotuMQn2MXF13xgWbtXLSAyySTE4B6LjgrxdqpyNQlDejmtiye4SvrRJQTRbNJZmlTK1Xzz3vr/bvoMxCPjwzkF8d+QUdy2UzdSNBsELk3uQEeXHXQt38bdlB/ByNzBjeCf6JQUxLDWM4S/oNd9rGpp5f1uhzp22//gZnr+6O/O+zSOvvI4+8YGMTg/nq+wyXr62F2F+nqw7dELXvOevEzKICfTijgWOVMTUcF9uGBBPjtOdeVZRNWsPulZJV9aaMQiB1emDdDMK2jZmMwpBn/ggXe9pN4Ngav84PttVbJcPNwi4JjOWhmYLX+yRn6UQMH1wEsM7hxHo7c7WvEp6xQfyh3FpBHqbqDdbmLW0TfUs8neh+Jm55Hm5Mzi2WXYw63a1lLMAWQdxYAnc+DmEp0tFVWdXUSuGDrmU/Sx0yE+ytslVITU6yJOiqnq6z1pNpL8ns67oyrvT+/H6NzncsWAHQggm9IjiTFOLveXk08sOMrFnNFvyKqk3tzBtYAKj0sNpurwLs5YewNxilYvlRcnknqrlD5/stRuQ2y9Kpm9CEMv2ldrHYgK92tVdWpldpnNpWTX4cPsxlmY5FkeLVWPB5kIi/D0orpKZTA3NVhZuLeSBMam4Gw1c1SeWuesdqYCXdIt0URoFWaW87pERNJgtPL38AI99LnWWXvz6CHOv68Nr6/V3ZHPWHqVfm2Ds0ZO1HD7h6paJCfQi1Ndkz+gyCJjSLxZvD6M9aGw0yEI+q6Zx96JddqN1/YB4JveNpbiqgY92FBHo7c60gQmUVjcyf3o/FmyW1eaebgb+tuwgveMDeWFyD/LL69hXXM19i3cT6e/JzCu68tcJXZmz5ijDXvgGkLGd9vjm8CmGd45o9znFOSIgVkphmOvB5C0b2bTl1EFpNPLWQ3gX6UIqtxUc+kbKoLLinCC09lahC4TMzExtx44dP35gGxL/tNxlzN/DyGknY+FtMvLSlF7ctXCn7rj3pvfn0U/32oOVIPsJJIf58OCHeyiuaiA90o/nJnXndGMLr647wo7CakJ9PZgxPBkNKZ+9MaccTzfZ3ezoyVqpr3RRMgXlddxg87eDVBt9eWpv7lm0S3cdtw1N4t3vC3SB6NRwGUdouytZeu8QVu0/QXW9GR8PNwor6uka7c+NAxPYU1TNgx/usbvHxnQJ5+KukXSJ8icuyJs+T3+tO0fP2ABKqht0tRreJiMTekbrfPgAi24bwB3/3mG/gw/0dufrh4ZT19TCOxvzqawz09DcQkFFPT1j5Y7kxOlGjtfIgH+4vwdT+sZxsraJ3ceqWH3gBJqmMbVfPLOu6MrfvzpkL+oL8nZn8R2DeG19jn2nBTChZzTxwV46Q+blbuTlqb24c4H+u22PcRkRzLsp80ePU5xDCr+Hdy91PDa4QbdrYO8HjrGEITI+xdSCAAAQsklEQVTttLlByl10EF2ic4UQYqemae3+sDvkTqE9pF6/wyjUmy2sP+TqZ161v0xnEABWZpeSX15nv0M/VHaGl9YcISrAkx22bmrltU28vPYoc6b20hWvZRVXs/bhEewrqWH6u9ukHk/3KAoq66TRSA3jRE0jw50E3mKDvBicEkplndmeJQUyDba0poGjTjIZ3WMCmLFol/3a3I2Cj+8aTFlNA8P/sZ7TjS0khHhzz8hONFuszP76iN2/fu/I9pvL/G5wor2ADeDmwYlMyYxj3aGT9mD0VX1iCPR2Z8k9Q/hgWxG1Tc3knqrl0jnfMTwtnJlXZPDnz7NZd0i+p7xTdZTXNnFptyjesaXKHj5xhn0lNbx4TU/+tszh2lmwpZAuUX68tcFR5V1V38zc9Tms3q+vffgqu9Slh0RDc/vfbXsMS1UBy1+chMEwaZ7UUXLzkA2CVrRpeF+4Caa+LxvaKM4pHdIoTOwRzRdtApsT+0Qzf6Mjw8Hf043xPSJ1Amwg+yR/uKNId/ccE+jFeqfcepD9FqrbxC7ONLawvE3fg2aLxud7Spiz5ojdTVJc1cDbN2Wyan8ZL62Ri6+7UfDUFV0xWyzMXZfDLf/ajre7gelDEjEIQX55HU8vP0Cor4mJvaI5VllPWrgfmYlB/OGTvbrzLd5+jFXZZZy2Bb8LK+rZXlDFydONONWy8c7GAq7pG2uvqxBCGp4rekbTOdKfbfkVHK9uYNGWQj7ZWcyM4Z1IDPVmxb4yPttVzGe7SsiI8mfBrf25dt4We/D+013FmNwMrG/TrnPD0XKX9p/V9c3tqtruK6lxSS2uqjOTEOKtq3ROCPFhQFIIm3IcSQF+nm6M7x7lUi8ypFMwm3IdooUCuK5fvMu5FT8Th1fKTnBnyqDHFLj1a0cB2ea5+mC0T7jsDKc453Ss+m0bL03txajOYRgE+JqMPDepG49e0oXr+sfj7+lGlyh/3pyWyfC0cJ68PINIf0+iAzx5amJXLu4ayR8u7ozJ1gksI8qf+8ek0idef8cyLDXM5S4zJtDLxfcOUN/U4rLArT5QxidOMgzNFo2vD55gaVYp1Q1yMa9vtrJyXxkRfh6sO3TSVv3bwMrsMt65uR9/n9yD+GBX7R6T0eASbM89VUttm85rTS0WHhufzrxpfXlgdCqDO4Xw8Ed76P/sGurNLfRLDGb5PmlcTp1p4qllB2hqtvLJzmL7+zlQepo5a4+6yGxsyiknLcJPN5Yc6qNrfQoyvnBJt0jadj6d1DvWrvbayjWZsTw1sRvBPnIhCfKWzYzuHJ7MDQPkd9vasOeitDBmTsggKsCTqAAZQ1p0+yCu7x9HiLe7rH24dwhu7fSUVvwM1FfKquXKPKlttPNfDhntws2y37GfTXLEwx8uf+mC6WR2odEhYwrngso6MxW1TaTaFraS6gZmfbmf7JIaBqeE8pfLM/B0N/D8ykOs3n+C5DAfnrgsg+QwHx75OIsvs2TK6S1Dk7i8ezQT5m7Uzf/ny7rwzHJ9d7jBnUI4XHZGp00khEyrbJtS+a/p/TAZDeSX17F8X6m941h0gCef3T2E2/69XScHcedFyUQGeOoycCb1jmH2tb0AeHnNEV3Ftslo4Nr+cSxw6rcMcOOAeBa2aSF6eY8odhZW6YLll3WP4p6RKdy1cCfHKuuJ9Pfk1et70znSjxkLd7IppwJvk5FHL0nn5sGJLM06zj+/ycVitXLb0GSm9Iujut7M/I35FFU1ML57FGMzZEC4sdlCfnkdSaE+eLq3021M8esjdz0suFI/lnap3CkcsLX99I2EiXOlyF57GkiK/5gfiikoo3CeqKwz42YU+HvKVohvfJvL3HU5NLVYmJIZx1MTu3HPol18ZfORGwS8OS2T746cYsEWx0I8pksE/RKDdP0MTG4GLu8RxWc2mQyTUfD4+C54uRtZmV3GzsIqukT5EeBlori6gbggLyyaRnSAF11j/NlfcprTjc1sz5eulNsvSmbj0XLWtvHDPzgmVWcoAD65axB3LdypC0S/cWMfAr1N/OGTLIoqG8hMCOLV63sTFeCF1apRerqRCD8P3Jz6MJ883Yivp1u72VGK3yD1lfBSF9ngvpV+t7m28hx4D1zy7C97bb9BlFFohw+2FfLe94WE+XrwxOUZLm6L80GzxYrFqtnvbpstVpZmHSe/vI6xGRH0iA2kqcXC69/ksjm3gh6xAdw3OhVPNyN//XI/n+0qJtzfg3tGpPDY5/t06a2j0qX2yzqnhb1fYhA3D07kXqemOfHB3rw0pSeT39isu7YbBySwcKvDGPl6uLH5sVG8tSGfdzfl42FTR502KJGck2eYuy6Hijozk/vGMtHW51jTNOrNFnw8fr0L/XvfF/DFnhLig715aGwaCe10rlP8TBxaro8pdL4MPrhWf0zP62U3N8X/hDIKbVi4pVDX49jkZmDPk2N/M3elxyrquegf+kK1wZ1CyCqqtqeHtjKmi6vryVmnqJX7RqbQZLGyZHcJEf6ePDY+ncGdfluZOW99l8czKxwuu1BfE1sfHyP7Vih+eVrM8M8BMs4AUg775qVSJK8jUrAJvn1e9sXu+zvZcOgnolJS2/BOG3VQc4uVj3cUcfPgpLO84sIiPsSbkZ3D7BlRQki56Pc0vTRHtxh/ogL0LTKFgMzEIBej0DshkFHpETw+vsvP/wbOE+9u0v8uymvNbMmtYIhKSz0/uJngllWwbZ6seO45VTbG6YjUnoJFkx0NhpY/LJVfu0w456fqkEbB3eh65+f1GwtIvn5jXz7ZWUxhRR3jukbSLzGYLlH+PLB4D3uKqsmI8ufFa3rh6+nGN0dOUlTZgBBwx7BkJvWOpbiygTe/y8Oqadw6NIlR6b/9qt62WksAZotr9bviF8Q3XDbz6egUfKfvOAdwZNVv3ygIIS4B5gBG4G1N057/Oc7z4JhU7l60WzeWHObLM8sPEOHvydT+8fh6uFFa08DibUVomsY1mXHEBXvTYLbw4XbZhObS7pH0TZAppiv3lbI1v5Le8YFc0TMaIQRZRdUs23v8vMypadBisaJp2NM5E0J8uPOiZL7PrSAzMYi0CF+EEMy5tjfzN+UTH+zN3SNTAJicGUuzxYpV05iSGQdwwbz3nzrnZT2i7FIbrQw6Hy6ymW36DT9aIBvY15VLX3tkd7BaZFP60ixIHg6dbRXA+Rvg8AoISYHeN8rir4pc2YTGzUtWAftFQEOVmvNCmjOmj+vvJKzzOf3ZtfKriSkIIYzAEWAsUAxsB67TNM1VpczGuZS5cKZnXCDv3NSXS+ZssGfRBHi589WDw3j4wyy7C0YIeGtaJtnHa3RZOHdclMyItDCmzd9mL3JTc/7652yPgucvO+tzPwvfvwSrZ539eYO71AnavdDRWQxkb2HfCH3Dmc7jZTOaNy+SPYhBNrm5ayO8O17qCak5L4w5z8bMmh9+/iz8UEzBOHPmzJ806blm1qxZA4Eemqa9OnPmTMusWbOCgPSZM2duPNtr5s2bN/OOO+74r8/VNo2yLSdsMhYbnKpgWxvROOvqgFQaXXPghE4V9cDx05xpbNZV1l5QcwrYcPR/mLPpwpyzPV5ec5QHx6T94DHnlHcu+eHnNauUkc5aLP9upTJX9jI+7Sh4pOIooEkhuVaabE2aDi27QOc0Q9aH/8Oc4sKc82yMeOzHj2mHWbNmlc6cOXNee8/9mso1YwBn3YFi25gOIcQdQogdQogdp06davv0OcPPVj+gH3P1tnmbjC4FUp7uBrzayWS6YOb0aGfOdtJIzzqn+4U75wWByUe6HJxx9wF3fdIAwti+FIRHgOvYhTKnu+//OGc7qecXypy/EL8mo/AfoWnaPE3TMjVNywwLO3ddsZwX0su6R3HrsCQ6O8kwJIX6MH1IEtf0jbWPeZuM3Dm8Ew+OSdVp/z80No3bL0r6bc059Lc/Z3v84u6jH3MHeAXDwLth2O8dY8IIw/8ox4xOC1H/2+WxAXGOseg+MPg+SBlzYc456H+d8/4Lc85fkF9TTGEQMFPTtIttjx8D0DTtubO95n8pXnOOK4yNguduHcO6QyeJ9PdkaEooBoOgsdnC2oMnsWgaY7tE4GUyomkam3MrKKqqZ2TncML9PQE4euIM2wuq6BUXSEa0PyCVUdWcF9acyY+vsP8uHk2AGTN+YaMArnGFJyshZy3Ul0sNoFaZ6JJdULYXEodBiE3RtqZYHhuaKtVGAZpqpdicuyekXixTPa0WNeeFNucXv4fDnzl+Fz8xngAXSPGaEMINGWgeDZQgA83Xa5q2/2yvuZBlLhQKheJ8cUEUr2ma1iKEuBdYhUxJnf9DBkGhUCgU555fjVEA0DRtBbDiRw9UKBQKxc/CBRdoVigUCsXPhzIKCoVCobCjjIJCoVAo7CijoFAoFAo7v5qU1J+CEOIUUPijByr+U0KB8vN9EQpFO6jf5rklQdO0dqt/L2ijoDi3CCF2nC13WaE4n6jf5i+Hch8pFAqFwo4yCgqFQqGwo4yCwpl2pXQVil8B6rf5C6FiCgqFQqGwo3YKCoVCobCjjIJCoVAo7CijoEAIcYkQ4rAQIkcI8afzfT0KRStCiPlCiJNCiOzzfS0dBWUUOjhCCCPwGnApkAFcJ4TIOL9XpVDY+RfwI42rFecSZRQU/YEcTdPyNE0zA4uBief5mhQKADRN+w6oPN/X0ZFQRkERAxQ5PS62jSkUig6IMgoKhUKhsKOMgqIEiHN6HGsbUygUHRBlFBTbgVQhRJIQwgRMBb48z9ekUCjOE8oodHA0TWsB7gVWAQeBjzRN239+r0qhkAghPgA2A52FEMVCiFvP9zX91lEyFwqFQqGwo3YKCoVCobCjjIJCoVAo7CijoFAoFAo7yigoFAqFwo4yCgqFQqGwo4yCosMjhIgVQnwhhDgqhMgVQsyx1Wz80Gse/6WuT6H4JVFGQdGhEUII4DNgiaZpqUAa4As88yMvVUZB8ZtEGQVFR2cU0Khp2rsAmqZZgIeAW4QQdwsh5rYeKIRYJoQYIYR4HvASQuwRQiyyPXeTEGKvECJLCLHANpYohFhnG18rhIi3jf9LCPG6EGKLECLPNud8IcRBIcS/nM43TgixWQixSwjxsRDC9xf7VBQdFmUUFB2drsBO5wFN004DxwC39l6gadqfgAZN03ppmnaDEKIr8AQwStO0nsADtkNfBd7TNK0HsAh4xWmaIGAQ0gB9Ccy2XUt3IUQvIUSobc4xmqb1AXYAD5+LN6xQ/BDt/ugVCsV/xSjgY03TygE0TWvV/x8EXGX7ewHwgtNrlmqapgkh9gEnNE3bByCE2A8kIoUJM4BN0sOFCSn3oFD8rCijoOjoHAAmOw8IIfyBeKAa/W7a8xyet8n2f6vT362P3QAL8LWmadedw3MqFD+Kch8pOjprAW8hxE1gb0/6IrINZB7QSwhhEELEIbvUtdIshHC3/b0OuEYIEWKbI9g2/j1SdRbgBmDDf3FdW4AhQogU25w+Qoi0//bNKRT/LcooKDo0mlSEnIRc1I8CR4BGZHbRJiAfuZt4Bdjl9NJ5wF4hxCKbquwzwLdCiCzgJdsx9wHThRB7gWk4Yg3/yXWdAn4HfGB7/WYg/ae+T4XiP0WppCoUCoXCjtopKBQKhcKOMgoKhUKhsKOMgkKhUCjsKKOgUCgUCjvKKCgUCoXCjjIKCoVCobCjjIJCoVAo7Pw/lYgFDlCyxYIAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.swarmplot(d_dataset['Outcome'], d_dataset['Glucose']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        },
        "id": "vFi5n1UQn-dD",
        "outputId": "31dfdf6e-a9e1-4156-80ce-c693286c07fa"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n",
            "/usr/local/lib/python3.8/dist-packages/seaborn/categorical.py:1296: UserWarning: 21.6% of the points cannot be placed; you may want to decrease the size of the markers or use stripplot.\n",
            "  warnings.warn(msg, UserWarning)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.boxplot(d_dataset['Outcome'], d_dataset['Glucose']);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "wwXYepP5EVHP",
        "outputId": "213007fd-5eb7-430d-a6e2-25fe2322077a"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Data Standardization**"
      ],
      "metadata": {
        "id": "0CYy6FtjzUQ9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        " scale = StandardScaler()\n",
        " scale.fit(X)\n",
        " standardized_data = scale.transform(X)"
      ],
      "metadata": {
        "id": "M5CtjwUKzXPU"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(standardized_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gxDAwhSU3o_6",
        "outputId": "7e6009ea-e5a1-4c69-bb41-fa47b4932d81"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.63994726  0.84832379  0.14964075 ...  0.20401277  0.46849198\n",
            "   1.4259954 ]\n",
            " [-0.84488505 -1.12339636 -0.16054575 ... -0.68442195 -0.36506078\n",
            "  -0.19067191]\n",
            " [ 1.23388019  1.94372388 -0.26394125 ... -1.10325546  0.60439732\n",
            "  -0.10558415]\n",
            " ...\n",
            " [ 0.3429808   0.00330087  0.14964075 ... -0.73518964 -0.68519336\n",
            "  -0.27575966]\n",
            " [-0.84488505  0.1597866  -0.47073225 ... -0.24020459 -0.37110101\n",
            "   1.17073215]\n",
            " [-0.84488505 -0.8730192   0.04624525 ... -0.20212881 -0.47378505\n",
            "  -0.87137393]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X=standardized_data"
      ],
      "metadata": {
        "id": "7G28AQRQ4ul9"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(X)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fV4_tS8z48OA",
        "outputId": "e1644607-c891-4130-bd14-fe7c452a7d19"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.63994726  0.84832379  0.14964075 ...  0.20401277  0.46849198\n",
            "   1.4259954 ]\n",
            " [-0.84488505 -1.12339636 -0.16054575 ... -0.68442195 -0.36506078\n",
            "  -0.19067191]\n",
            " [ 1.23388019  1.94372388 -0.26394125 ... -1.10325546  0.60439732\n",
            "  -0.10558415]\n",
            " ...\n",
            " [ 0.3429808   0.00330087  0.14964075 ... -0.73518964 -0.68519336\n",
            "  -0.27575966]\n",
            " [-0.84488505  0.1597866  -0.47073225 ... -0.24020459 -0.37110101\n",
            "   1.17073215]\n",
            " [-0.84488505 -0.8730192   0.04624525 ... -0.20212881 -0.47378505\n",
            "  -0.87137393]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n0RLNBc04-wX",
        "outputId": "22e0a25e-82e9-4910-b401-426e165c655c"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      1\n",
            "1      0\n",
            "2      1\n",
            "3      0\n",
            "4      1\n",
            "      ..\n",
            "763    0\n",
            "764    0\n",
            "765    0\n",
            "766    1\n",
            "767    0\n",
            "Name: Outcome, Length: 768, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Model**\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "dGK3L_FC5CdX"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UAE65Xzw7Tw6"
      },
      "source": [
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.2, stratify=Y, random_state=42)"
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(X.shape, X_train.shape, X_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y-jT-rro9Ohv",
        "outputId": "6e1353e0-a4b2-4f61-b092-81370e59be1f"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(768, 8) (614, 8) (154, 8)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "classifier = svm.SVC(kernel='linear')"
      ],
      "metadata": {
        "id": "QM4VJ3zM9eDO"
      },
      "execution_count": 52,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "classifier.fit(X_train,Y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v7Gkbdjd_-fT",
        "outputId": "4f9d58b0-abb3-4b23-a21d-0ff033345234"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(kernel='linear')"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Model Evaluation**"
      ],
      "metadata": {
        "id": "jLDAsPlTA0ki"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "jTOb2VWEA3lx"
      },
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Training data\n",
        "X_train_prediction = classifier.predict(X_train)\n",
        "training_data_accuracy= accuracy_score(X_train_prediction,Y_train)\n",
        "print('Accuracy of training data:: ',training_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "imQaCnB9f70T",
        "outputId": "0f7580a4-75dd-461d-976c-d8914a05854f"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of training data::  0.7915309446254072\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Test data\n",
        "X_test_prediction = classifier.predict(X_test)\n",
        "test_data_accuracy= accuracy_score(X_test_prediction,Y_test)\n",
        "print('Accuracy of test data:: ',test_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k6PxA-5og_fd",
        "outputId": "61e17220-2594-425f-bfad-5a76609944d2"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of test data::  0.7207792207792207\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Prediction System"
      ],
      "metadata": {
        "id": "5_7Nbnmzh_AU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input = (5,166,72,19,175,25.8,0.587,51)\n",
        "input_numpy = np.asarray(input)  \n",
        "input_reshape = input_numpy.reshape(1,-1)  \n",
        "std_data = scale.transform(input_reshape)\n",
        "#print(input_reshape)\n",
        "#print(std_data)\n",
        "prediction = classifier.predict(std_data)\n",
        "print(prediction)\n",
        "\n",
        "if (prediction[0]==1):\n",
        "  print('Person has diabetes')\n",
        "else:\n",
        "  print('Person does not have diabetes')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zi2VtRyPiCOx",
        "outputId": "01e9d1dc-d5a3-4314-a6a8-0aaffd723bd7"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1]\n",
            "Person has diabetes\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/sklearn/base.py:450: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "G9tDaog_pcGM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "pihw0NvPpgJf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**3. K-Means Clustering**"
      ],
      "metadata": {
        "id": "RJDV_WCgpRlF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.cluster import KMeans"
      ],
      "metadata": {
        "id": "BKzuQ5LBpaOu"
      },
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "c_dataset = pd.read_csv('/content/Mall_Customers1.csv')"
      ],
      "metadata": {
        "id": "XHqoncFXy28I"
      },
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "c_dataset.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KmsljOt0zDC2",
        "outputId": "5ecb473f-2b0a-47e2-b9af-1426f78dab50"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(200, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c_dataset.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "sin-JS8qzTcD",
        "outputId": "e51d79a8-9695-4272-9bd3-4556c2de953d"
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   CustomerID   Genre  Age  Annual Income (k$)  Spending Score (1-100)\n",
              "0           1    Male   19                  15                      39\n",
              "1           2    Male   21                  15                      81\n",
              "2           3  Female   20                  16                       6\n",
              "3           4  Female   23                  16                      77\n",
              "4           5  Female   31                  17                      40"
            ],
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        "c_dataset.info()"
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      },
      "execution_count": 62,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 200 entries, 0 to 199\n",
            "Data columns (total 5 columns):\n",
            " #   Column                  Non-Null Count  Dtype \n",
            "---  ------                  --------------  ----- \n",
            " 0   CustomerID              200 non-null    int64 \n",
            " 1   Genre                   200 non-null    object\n",
            " 2   Age                     200 non-null    int64 \n",
            " 3   Annual Income (k$)      200 non-null    int64 \n",
            " 4   Spending Score (1-100)  200 non-null    int64 \n",
            "dtypes: int64(4), object(1)\n",
            "memory usage: 7.9+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c_dataset.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LTH7j_7Sz8Yi",
        "outputId": "e8d98431-0fcc-41ca-b274-3994423e080f"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CustomerID                0\n",
              "Genre                     0\n",
              "Age                       0\n",
              "Annual Income (k$)        0\n",
              "Spending Score (1-100)    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = c_dataset.iloc[:,[3,4]].values\n",
        "print(X)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kKY2TFIv0EYP",
        "outputId": "f2769f74-6a9c-41f4-faac-0ecf43c32021"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 15  39]\n",
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            " [ 97  86]\n",
            " [ 98  15]\n",
            " [ 98  88]\n",
            " [ 99  39]\n",
            " [ 99  97]\n",
            " [101  24]\n",
            " [101  68]\n",
            " [103  17]\n",
            " [103  85]\n",
            " [103  23]\n",
            " [103  69]\n",
            " [113   8]\n",
            " [113  91]\n",
            " [120  16]\n",
            " [120  79]\n",
            " [126  28]\n",
            " [126  74]\n",
            " [137  18]\n",
            " [137  83]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Data Visualization**"
      ],
      "metadata": {
        "id": "oTj9huCj_29m"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "correlation =  c_dataset.corr()\n",
        "sns.heatmap(correlation, cbar=True, square=True, fmt = '.1f', annot = True, annot_kws={'size':8}, cmap='Blues')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "V7ZCn4JS_5n-",
        "outputId": "f98e0112-b040-4a6c-d4de-74fec41998a5"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fc4a8b030a0>"
            ]
          },
          "metadata": {},
          "execution_count": 65
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Number of clusters**"
      ],
      "metadata": {
        "id": "AHTvH-r4F_1u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# To find the number of clusters\n",
        "wcss=[]\n",
        "\n",
        "for i in range(1,11):\n",
        "  kmeans = KMeans(n_clusters=i, init='k-means++', random_state=42)\n",
        "  kmeans.fit(X)\n",
        "  wcss.append(kmeans.inertia_)"
      ],
      "metadata": {
        "id": "6f5mjeBp9eUp"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set()\n",
        "plt.plot(range(1,11),wcss)\n",
        "plt.title('The Elbow Point Graph')\n",
        "plt.xlabel('Number of clusters')\n",
        "plt.ylabel('WCSS')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "id": "A4epHHkNGrns",
        "outputId": "95d9b688-e90a-4822-8997-14680d57e7f1"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**5 clusters is considered to be optimal**"
      ],
      "metadata": {
        "id": "tvgBbuH2Jlp3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Model Training**"
      ],
      "metadata": {
        "id": "uNd_hASjKWmy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "kmeans = KMeans(n_clusters=5, init='k-means++', random_state=42)\n",
        "Y=kmeans.fit_predict(X)\n",
        "print(Y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x2dEuuAQJ84Z",
        "outputId": "f713c233-4d04-4bc5-a905-bba8b51c3bea"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2\n",
            " 3 2 3 2 3 2 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            " 0 0 0 0 0 0 0 0 0 0 0 0 4 1 4 0 4 1 4 1 4 0 4 1 4 1 4 1 4 1 4 0 4 1 4 1 4\n",
            " 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4 1\n",
            " 4 1 4 1 4 1 4 1 4 1 4 1 4 1 4]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####**Cluster Visualization**"
      ],
      "metadata": {
        "id": "SxiO8CvyMj9Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.scatter(X[Y==0,0], X[Y==0,1], s=50, c='red', label='Cluster 1')\n",
        "plt.scatter(X[Y==1,0], X[Y==1,1], s=50, c='yellow', label='Cluster 2')\n",
        "plt.scatter(X[Y==2,0], X[Y==2,1], s=50, c='cyan', label='Cluster 3')\n",
        "plt.scatter(X[Y==3,0], X[Y==3,1], s=50, c='blue', label='Cluster 4')\n",
        "plt.scatter(X[Y==4,0], X[Y==4,1], s=50, c='violet', label='Cluster 5')\n",
        "\n",
        "plt.scatter(kmeans.cluster_centers_[:,0], kmeans.cluster_centers_[:,1], s=100, c='black', label='Centroids')\n",
        "\n",
        "plt.title('Customer Groups')\n",
        "plt.xlabel('Annual Income')\n",
        "plt.ylabel('Spending Score')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "id": "-JOz-ahDLrCH",
        "outputId": "06bf7754-da99-463f-a730-98e84835bfec"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}