MLmodel.ipynb

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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/Ecological-Complexity-Lab/link_prediction_project/blob/main/MLmodel.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z5l-u0ecS_wV",
        "outputId": "c5e532be-7b7a-4e65-cc62-7c77ccf43068"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "cfSlEB5mR6fV"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import cross_val_score, KFold, train_test_split, GridSearchCV, RandomizedSearchCV\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
        "from sklearn.compose import ColumnTransformer\n",
        "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, matthews_corrcoef, make_scorer, precision_recall_curve\n",
        "from collections import Counter\n",
        "import numpy as np\n",
        "from imblearn.under_sampling import RandomUnderSampler\n",
        "import plotly.graph_objects as go\n",
        "import plotly.io as pio"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_mandena = pd.read_csv('/content/drive/MyDrive/LinkPredictionProject/Data/ML_rattus_mandena.csv', encoding='latin1')\n",
        "df_mandena.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "j2FloqkIucQb",
        "outputId": "9158dca0-0d9b-45cf-e71e-3e64a935cc20"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   host_ID asv_ID  Link             grid  pca_grid_attr  pca_grid_sm  season  \\\n",
              "0     2010  ASV_1     1  brushy_regrowth      -0.197466    -2.224026       1   \n",
              "1     2011  ASV_1     1  brushy_regrowth      -0.197466    -2.224026       1   \n",
              "2     2013  ASV_1     0  brushy_regrowth      -0.197466    -2.224026       1   \n",
              "3     2014  ASV_1     1  brushy_regrowth      -0.197466    -2.224026       1   \n",
              "4     2015  ASV_1     1  brushy_regrowth      -0.197466    -2.224026       1   \n",
              "\n",
              "   elevation.obs  mass     sex  ...  host_degree host_betweenness  \\\n",
              "0     144.218796  80.0  female  ...           12         0.003539   \n",
              "1     145.284958  51.0    male  ...           13         0.002761   \n",
              "2     118.188316  88.0  female  ...           18         0.004112   \n",
              "3     133.551437  77.0    male  ...           20         0.004784   \n",
              "4     145.232788  65.0  female  ...            6         0.004310   \n",
              "\n",
              "  host_closeness  host_module  asv_degree  asv_betweenness  asv_closeness  \\\n",
              "0       0.003651            1         129         0.050775       0.003051   \n",
              "1       0.003479            1         129         0.050775       0.003051   \n",
              "2       0.003691            1         129         0.050775       0.003051   \n",
              "3       0.003758            1         129         0.050775       0.003051   \n",
              "4       0.003472            1         129         0.050775       0.003051   \n",
              "\n",
              "   asv_module  shortest_path  pref_attach  \n",
              "0           1              1         1548  \n",
              "1           1              1         1677  \n",
              "2           1              3         2322  \n",
              "3           1              1         2580  \n",
              "4           1              1          774  \n",
              "\n",
              "[5 rows x 23 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>host_ID</th>\n",
              "      <th>asv_ID</th>\n",
              "      <th>Link</th>\n",
              "      <th>grid</th>\n",
              "      <th>pca_grid_attr</th>\n",
              "      <th>pca_grid_sm</th>\n",
              "      <th>season</th>\n",
              "      <th>elevation.obs</th>\n",
              "      <th>mass</th>\n",
              "      <th>sex</th>\n",
              "      <th>...</th>\n",
              "      <th>host_degree</th>\n",
              "      <th>host_betweenness</th>\n",
              "      <th>host_closeness</th>\n",
              "      <th>host_module</th>\n",
              "      <th>asv_degree</th>\n",
              "      <th>asv_betweenness</th>\n",
              "      <th>asv_closeness</th>\n",
              "      <th>asv_module</th>\n",
              "      <th>shortest_path</th>\n",
              "      <th>pref_attach</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2010</td>\n",
              "      <td>ASV_1</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>-0.197466</td>\n",
              "      <td>-2.224026</td>\n",
              "      <td>1</td>\n",
              "      <td>144.218796</td>\n",
              "      <td>80.0</td>\n",
              "      <td>female</td>\n",
              "      <td>...</td>\n",
              "      <td>12</td>\n",
              "      <td>0.003539</td>\n",
              "      <td>0.003651</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
              "      <td>0.050775</td>\n",
              "      <td>0.003051</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2011</td>\n",
              "      <td>ASV_1</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>-0.197466</td>\n",
              "      <td>-2.224026</td>\n",
              "      <td>1</td>\n",
              "      <td>145.284958</td>\n",
              "      <td>51.0</td>\n",
              "      <td>male</td>\n",
              "      <td>...</td>\n",
              "      <td>13</td>\n",
              "      <td>0.002761</td>\n",
              "      <td>0.003479</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
              "      <td>0.050775</td>\n",
              "      <td>0.003051</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1677</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2013</td>\n",
              "      <td>ASV_1</td>\n",
              "      <td>0</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>-0.197466</td>\n",
              "      <td>-2.224026</td>\n",
              "      <td>1</td>\n",
              "      <td>118.188316</td>\n",
              "      <td>88.0</td>\n",
              "      <td>female</td>\n",
              "      <td>...</td>\n",
              "      <td>18</td>\n",
              "      <td>0.004112</td>\n",
              "      <td>0.003691</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
              "      <td>0.050775</td>\n",
              "      <td>0.003051</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2014</td>\n",
              "      <td>ASV_1</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>-0.197466</td>\n",
              "      <td>-2.224026</td>\n",
              "      <td>1</td>\n",
              "      <td>133.551437</td>\n",
              "      <td>77.0</td>\n",
              "      <td>male</td>\n",
              "      <td>...</td>\n",
              "      <td>20</td>\n",
              "      <td>0.004784</td>\n",
              "      <td>0.003758</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
              "      <td>0.050775</td>\n",
              "      <td>0.003051</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2015</td>\n",
              "      <td>ASV_1</td>\n",
              "      <td>1</td>\n",
              "      <td>brushy_regrowth</td>\n",
              "      <td>-0.197466</td>\n",
              "      <td>-2.224026</td>\n",
              "      <td>1</td>\n",
              "      <td>145.232788</td>\n",
              "      <td>65.0</td>\n",
              "      <td>female</td>\n",
              "      <td>...</td>\n",
              "      <td>6</td>\n",
              "      <td>0.004310</td>\n",
              "      <td>0.003472</td>\n",
              "      <td>1</td>\n",
              "      <td>129</td>\n",
              "      <td>0.050775</td>\n",
              "      <td>0.003051</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>774</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 23 columns</p>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_mandena"
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          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# count asv_id unique\n",
        "df_mandena[\"asv_ID\"].nunique()"
      ],
      "metadata": {
        "id": "C367p6_dK-gQ",
        "outputId": "a0e84a79-32ec-4868-abdb-e7fedfa02ee1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "514"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_mandena[\"host_ID\"].nunique()"
      ],
      "metadata": {
        "id": "je7-x4RML_MY",
        "outputId": "f15aa058-23bb-4766-8a78-01bc1f0a41f9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "295"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data preprocessing"
      ],
      "metadata": {
        "id": "3QkBbFyWSj_t"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_mandena_filtered = df_mandena[[\"asv_ID\", \"asv_degree\", \"grid\", \"season\", \"elevation.obs\", \"host_degree\", \"mass\", \"sex\", \"Link\"]]\n",
        "df_head = df_mandena_filtered.head()\n",
        "# plt.figure(figsize=(10, 4))\n",
        "# plt.table(cellText=df_head.values, colLabels=df_head.columns, cellLoc='center', loc='center')\n",
        "# plt.axis('off')\n",
        "# plt.savefig('head_of_dataframe.png', bbox_inches='tight')"
      ],
      "metadata": {
        "id": "KDXZkSjFsfA9"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install -U kaleido"
      ],
      "metadata": {
        "id": "DS-FixteKVfd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install --upgrade plotly\n"
      ],
      "metadata": {
        "id": "iInyuWxULwpk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install --upgrade kaleido\n"
      ],
      "metadata": {
        "id": "DuLDRmJlL14q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig = go.Figure(data=[go.Table(\n",
        "                columnwidth=[100, 130, 130, 90, 140, 140, 80, 90, 70],\n",
        "                header=dict(values=[f'<b>{col}</b>' for col in df_head.columns],\n",
        "                fill_color='darkolivegreen',\n",
        "                font=dict(color='white', size=20, family='Arial, sans-serif'),\n",
        "                height=40,\n",
        "                line_color = 'black',\n",
        "                align='center'),\n",
        "    cells=dict(values=[df_head[col] for col in df_head.columns],\n",
        "               fill_color='mintcream',\n",
        "               line_color='black',\n",
        "               height=30,\n",
        "               font=dict(color='black', size=18, family='Arial, sans-serif'),\n",
        "               align='left'))\n",
        "])\n",
        "fig.update_layout(\n",
        "    margin=dict(l=40, r=40, t=5, b=5),  # Margins around the figure\n",
        "    width=1200,  # Width of the figure\n",
        "    height=600,  # Height of the figure\n",
        "    font=dict(size=14, family='Arial, sans-serif'),  # Global font settings for the table\n",
        ")# Save the plotly table as an image\n",
        "pio.show(fig)\n",
        "pio.write_image(fig, 'head_of_dataframe_plotly.png', scale=12)"
      ],
      "metadata": {
        "id": "FDK6GW4rKtsR",
        "outputId": "18adae91-752a-4543-d30c-3a02010701a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {}
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    {
      "cell_type": "code",
      "source": [
        "# Convert \"sex\" column to numeric\n",
        "df_mandena_filtered.loc[:, \"sex\"] = df_mandena_filtered[\"sex\"].map({\"female\": 0, \"male\": 1})\n",
        "# Scale \"mass\", \"asv_degree\", \"elevation.obs\" and \"host_degree\" columns\n",
        "scaler = StandardScaler()\n",
        "df_mandena_filtered.loc[:, \"mass\"] = scaler.fit_transform(df_mandena_filtered[[\"mass\"]])\n",
        "df_mandena_filtered.loc[:, \"asv_degree\"] = scaler.fit_transform(df_mandena_filtered[[\"asv_degree\"]])\n",
        "df_mandena_filtered.loc[:, \"elevation.obs\"] = scaler.fit_transform(df_mandena_filtered[[\"elevation.obs\"]])\n",
        "df_mandena_filtered.loc[:, \"host_degree\"] = scaler.fit_transform(df_mandena_filtered[[\"host_degree\"]])\n",
        "\n",
        "# Get dummies for \"grid\" column\n",
        "df_mandena_filtered = pd.get_dummies(df_mandena_filtered, columns=[\"grid\"], dtype=\"int\", drop_first=True)\n",
        "df_mandena_filtered.head()"
      ],
      "metadata": {
        "id": "MdYP_ApMqV2Q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "47fac310-b6e0-443b-a3d6-cf2b483c3a66"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  asv_ID  asv_degree  season  elevation.obs  host_degree      mass sex  Link  \\\n",
              "0  ASV_1    8.179624       1       0.320651    -0.474878 -0.155948   0     1   \n",
              "1  ASV_1    8.179624       1       0.349677    -0.279223 -0.960616   1     1   \n",
              "2  ASV_1    8.179624       1      -0.388006     0.699053  0.066029   0     0   \n",
              "3  ASV_1    8.179624       1       0.030242     1.090363 -0.239190   1     1   \n",
              "4  ASV_1    8.179624       1       0.348256    -1.648809 -0.572156   0     1   \n",
              "\n",
              "   grid_agroforest  grid_brushy_regrowth  grid_flooded_rice  \\\n",
              "0                0                     1                  0   \n",
              "1                0                     1                  0   \n",
              "2                0                     1                  0   \n",
              "3                0                     1                  0   \n",
              "4                0                     1                  0   \n",
              "\n",
              "   grid_secondary_forest  grid_semi-intact_forest  \n",
              "0                      0                        0  \n",
              "1                      0                        0  \n",
              "2                      0                        0  \n",
              "3                      0                        0  \n",
              "4                      0                        0  "
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              "      <th></th>\n",
              "      <th>asv_ID</th>\n",
              "      <th>asv_degree</th>\n",
              "      <th>season</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ASV_1</td>\n",
              "      <td>8.179624</td>\n",
              "      <td>1</td>\n",
              "      <td>0.320651</td>\n",
              "      <td>-0.474878</td>\n",
              "      <td>-0.155948</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ASV_1</td>\n",
              "      <td>8.179624</td>\n",
              "      <td>1</td>\n",
              "      <td>0.349677</td>\n",
              "      <td>-0.279223</td>\n",
              "      <td>-0.960616</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ASV_1</td>\n",
              "      <td>8.179624</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.388006</td>\n",
              "      <td>0.699053</td>\n",
              "      <td>0.066029</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ASV_1</td>\n",
              "      <td>8.179624</td>\n",
              "      <td>1</td>\n",
              "      <td>0.030242</td>\n",
              "      <td>1.090363</td>\n",
              "      <td>-0.239190</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ASV_1</td>\n",
              "      <td>8.179624</td>\n",
              "      <td>1</td>\n",
              "      <td>0.348256</td>\n",
              "      <td>-1.648809</td>\n",
              "      <td>-0.572156</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c5308a40-37d5-415a-a57d-b141a95bd3c4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\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-c5308a40-37d5-415a-a57d-b141a95bd3c4 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-c5308a40-37d5-415a-a57d-b141a95bd3c4');\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",
              "\n",
              "\n",
              "<div id=\"df-1fe89193-b3a2-478c-9220-4b34efc86cdc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1fe89193-b3a2-478c-9220-4b34efc86cdc')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1fe89193-b3a2-478c-9220-4b34efc86cdc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_mandena_filtered"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Choosing a model"
      ],
      "metadata": {
        "id": "ZBdbyELUkXkc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df_mandena_filtered.drop([\"Link\", \"asv_ID\"], axis=1)\n",
        "y = df_mandena_filtered[\"Link\"]\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n",
        "\n",
        "models = {\n",
        "    \"Logistic Regression\": LogisticRegression(max_iter=1000),\n",
        "    \"KNN\": KNeighborsClassifier(),\n",
        "    \"Random Forest\": RandomForestClassifier()\n",
        "}\n",
        "\n",
        "kf = KFold(n_splits=5, shuffle=True, random_state=42)\n",
        "\n",
        "mcc_scorer = make_scorer(matthews_corrcoef)\n",
        "\n",
        "# Dictionary to hold the MCC results\n",
        "mcc_results = {model_name: [] for model_name in models.keys()}\n",
        "\n",
        "# Perform cross-validation and calculate MCC scores\n",
        "for model_name, model in models.items():\n",
        "    cv_results = cross_val_score(model, X_train, y_train, cv=kf, scoring=mcc_scorer)\n",
        "    mcc_results[model_name] = cv_results\n"
      ],
      "metadata": {
        "id": "o9r9nsaBlSsz"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# create confusion matrix after cross validation\n",
        "lr = LogisticRegression()\n",
        "lr.fit(X_train, y_train)\n",
        "y_pred = lr.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.heatmap(cm, annot=True, annot_kws={'size': 18}, fmt='d', cmap='Oranges', xticklabels=['Predicted 0', 'Predicted 1'], yticklabels=['Actual 0', 'Actual 1'])\n",
        "plt.xlabel('Predicted', weight='bold', fontsize=14)\n",
        "plt.ylabel('Actual', weight='bold', fontsize=14)\n",
        "plt.title('Confusion Matrix - Logistic Regression', weight='bold', fontsize=20)\n",
        "precision = cm[1, 1] / (cm[1, 1] + cm[0, 1])\n",
        "print(\"Precision:\", precision)\n",
        "recall = cm[1, 1] / (cm[1, 1] + cm[1, 0])\n",
        "print(\"Recall:\", recall)\n",
        "plt.savefig('ConfusionMatrixLR.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "Xt_OYuhcSQgO",
        "outputId": "88268f80-d154-46a8-932a-caf5fdf5a3cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Precision: 0.4978540772532189\n",
            "Recall: 0.09250398724082935\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# create confusion matrix after cross validation\n",
        "knn = KNeighborsClassifier()\n",
        "knn.fit(X_train, y_train)\n",
        "y_pred = knn.predict(X_test)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.heatmap(cm, annot=True, annot_kws={'size': 18}, fmt='d', cmap='Oranges', xticklabels=['Predicted 0', 'Predicted 1'], yticklabels=['Actual 0', 'Actual 1'])\n",
        "plt.xlabel('Predicted' , weight='bold', fontsize=14)\n",
        "plt.ylabel('Actual', weight='bold', fontsize=14)\n",
        "plt.title('Confusion Matrix - KNN', weight='bold', fontsize=20)\n",
        "plt.savefig('ConfusionMatrixKNN.png', bbox_inches='tight', dpi=300)\n",
        "# precision\n",
        "precision = cm[1, 1] / (cm[1, 1] + cm[0, 1])\n",
        "print(\"Precision:\", precision)\n",
        "# recall\n",
        "recall = cm[1, 1] / (cm[1, 1] + cm[1, 0])\n",
        "print(\"Recall:\", recall)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "lsqHYkU_UTfu",
        "outputId": "7b7e776a-2d8e-49a3-d60c-d65fef0c3cb1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Precision: 0.3598130841121495\n",
            "Recall: 0.06140350877192982\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Convert results to DataFrame for plotting\n",
        "results_df = pd.DataFrame(mcc_results)\n",
        "\n",
        "# Melt the DataFrame for Seaborn\n",
        "results_melted = results_df.melt(var_name='Model', value_name='MCC')\n",
        "\n",
        "# Plotting the MCC scores\n",
        "sns.set(style=\"whitegrid\")\n",
        "plt.figure(figsize=(12, 8), dpi=300)\n",
        "boxplot = sns.boxplot(x='Model', y='MCC', data=results_melted, palette=\"Set2\")\n",
        "boxplot.set_title('Comparison of MCC Scores Across Models', fontsize=20, weight='bold')\n",
        "boxplot.set_xlabel('Model', fontsize=15, weight='bold')\n",
        "boxplot.set_ylabel('MCC Score', fontsize=15, weight='bold')\n",
        "\n",
        "boxplot.set_xticklabels(boxplot.get_xticklabels(), fontsize=22, weight='bold', color='black')\n",
        "\n",
        "plt.savefig('mcc_comparison_boxplot.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0TXeOfxbbKaU",
        "outputId": "1eed12ae-ae2a-4f04-afa9-d4240ea2bf10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-73-621c2df378b5>:10: FutureWarning:\n",
            "\n",
            "\n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "\n",
            "<ipython-input-73-621c2df378b5>:15: UserWarning:\n",
            "\n",
            "FixedFormatter should only be used together with FixedLocator\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 3600x2400 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# train model on all data\n",
        "knn = KNeighborsClassifier(n_neighbors=9, p=1, weights=\"uniform\")\n",
        "knn.fit(X, y)\n",
        "y_pred = knn.predict(X_test)\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "print(\"Model: KNN\")\n",
        "print(\"Accuracy on test set:\", accuracy)\n",
        "print(\"Confusion Matrix:\\n\", cm)\n",
        "print(\"Classification Report:\\n\", cr)\n",
        "\n",
        "# do the same with logistic regression\n",
        "lr = LogisticRegression()\n",
        "lr.fit(X, y)\n",
        "y_pred = lr.predict(X_test)\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "cm = confusion_matrix(y_test, y_pred)\n",
        "cr = classification_report(y_test, y_pred)\n",
        "print(\"Model: Logistic Regression\")\n",
        "print(\"Accuracy on test set:\", accuracy)\n",
        "print(\"Confusion Matrix:\\n\", cm)\n",
        "print(\"Classification Report:\\n\", cr)"
      ],
      "metadata": {
        "id": "85RcZIQ6OaQs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Training on all data, didn't improve the model predictions"
      ],
      "metadata": {
        "id": "Dobpr4sHSXVl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#count link 1\n",
        "df_mandena_filtered[\"Link\"].value_counts()"
      ],
      "metadata": {
        "id": "cah6-TCKSppZ",
        "outputId": "352d2caf-7ad5-4360-e1a7-0e51f0118bf9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Link\n",
              "0    147374\n",
              "1      4256\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "link_counts = df_mandena_filtered[\"Link\"].value_counts()\n",
        "plt.figure(figsize=(4,5))\n",
        "link_counts.plot(kind=\"bar\", color=['brown', 'orange'])\n",
        "bars = link_counts.plot(kind=\"bar\", color=['brown', 'orange'], width=0.4)\n",
        "for bar in bars.patches:\n",
        "    plt.text(bar.get_x() + bar.get_width() / 2,\n",
        "             bar.get_height(),\n",
        "             f'{int(bar.get_height())}',\n",
        "             ha='center',\n",
        "             va='bottom',\n",
        "             fontsize=10,\n",
        "             fontname='monospace')\n",
        "\n",
        "plt.yscale(\"log\")\n",
        "plt.title(\"Link Counts\", name='monospace', fontsize=14)\n",
        "plt.xlabel(\"Link\", fontname='monospace', fontsize=12)\n",
        "plt.ylabel(\"Count(Log scale)\", fontsize=12, fontname='monospace', rotation=75)\n",
        "plt.xticks([0,1], labels=[\"No link\", \"link\"], rotation=0, fontsize=10, fontname='monospace')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 492
        },
        "id": "RCAJi8ej6XH9",
        "outputId": "c1e63d9a-6601-46a4-9414-41d91a049812"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "we can conclude that the model is not good at predicting links beacause of the imbalanced data"
      ],
      "metadata": {
        "id": "AXhQu49LTe6x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# undersampling to balance the data\n",
        "rus = RandomUnderSampler(random_state=42, sampling_strategy = 'majority')\n",
        "X_resampled, y_X_resampled = rus.fit_resample(X_train, y_train)\n",
        "X_train_resampled, X_test_resampled, y_train_resampled, y_test_resampled = train_test_split(X_resampled, y_X_resampled, test_size=0.3, random_state=42)\n",
        "knn = KNeighborsClassifier(n_neighbors=9, p=1, weights=\"uniform\")\n",
        "knn.fit(X_train_resampled, y_train_resampled)\n",
        "y_pred_resampled = knn.predict(X_test_resampled)\n",
        "accuracy = accuracy_score(y_test_resampled, y_pred_resampled)\n",
        "cm = confusion_matrix(y_test_resampled, y_pred_resampled)\n",
        "cr = classification_report(y_test_resampled, y_pred_resampled)\n",
        "print(\"KNN\")\n",
        "print(\"Accuracy on test set:\", accuracy)\n",
        "print(\"Confusion Matrix:\\n\", cm)\n",
        "print(\"Classification Report:\\n\", cr)\n",
        "\n",
        "lr = LogisticRegression()\n",
        "lr.fit(X_train_resampled, y_train_resampled)\n",
        "y_pred_resampled = lr.predict(X_test_resampled)\n",
        "accuracy = accuracy_score(y_test_resampled, y_pred_resampled)\n",
        "cm = confusion_matrix(y_test_resampled, y_pred_resampled)\n",
        "cr = classification_report(y_test_resampled, y_pred_resampled)\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.heatmap(cm, annot=True, annot_kws={'size': 18}, fmt='d', cmap='Blues', xticklabels=['Predicted 0', 'Predicted 1'], yticklabels=['Actual 0', 'Actual 1'])\n",
        "plt.xlabel('Predicted', weight='bold', fontsize=16)\n",
        "plt.ylabel('Actual', weight='bold', fontsize=16)\n",
        "plt.title('Confusion Matrix - Logistic Regression', weight='bold', fontsize=20)\n",
        "plt.savefig('cmLRafterUndersampling.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()\n",
        "print(\"Logistic Regression\")\n",
        "print(\"Accuracy on test set:\", accuracy)\n",
        "print(\"Confusion Matrix:\\n\", cm)\n",
        "print(\"Classification Report:\\n\", cr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "wtuh8l-POfac",
        "outputId": "f48f832e-e671-4401-9d69-cf1a004a023b"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "KNN\n",
            "Accuracy on test set: 0.6542730299667037\n",
            "Confusion Matrix:\n",
            " [[686 256]\n",
            " [367 493]]\n",
            "Classification Report:\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "           0       0.65      0.73      0.69       942\n",
            "           1       0.66      0.57      0.61       860\n",
            "\n",
            "    accuracy                           0.65      1802\n",
            "   macro avg       0.65      0.65      0.65      1802\n",
            "weighted avg       0.65      0.65      0.65      1802\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Logistic Regression\n",
            "Accuracy on test set: 0.7192008879023307\n",
            "Confusion Matrix:\n",
            " [[761 181]\n",
            " [325 535]]\n",
            "Classification Report:\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "           0       0.70      0.81      0.75       942\n",
            "           1       0.75      0.62      0.68       860\n",
            "\n",
            "    accuracy                           0.72      1802\n",
            "   macro avg       0.72      0.71      0.71      1802\n",
            "weighted avg       0.72      0.72      0.72      1802\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred_proba = lr.predict_proba(X_test_resampled)[:, 1]\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.kdeplot(y_pred_proba[y_test_resampled == 0], label='True 0', shade=True, color='blue')\n",
        "sns.kdeplot(y_pred_proba[y_test_resampled == 1], label='True 1', shade=True, color='red')\n",
        "plt.xlabel('Predicted Probability of Class 1')\n",
        "plt.ylabel('Density')\n",
        "plt.title('Density Plot of Predicted Probabilities (Logistic Regression)')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "n9RdDv2XTvdS",
        "outputId": "d8c959ce-6b35-4a9f-a170-2a00a61dbf79",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 772
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-11-23e97c842d0f>:3: FutureWarning: \n",
            "\n",
            "`shade` is now deprecated in favor of `fill`; setting `fill=True`.\n",
            "This will become an error in seaborn v0.14.0; please update your code.\n",
            "\n",
            "  sns.kdeplot(y_pred_proba[y_test_resampled == 0], label='True 0', shade=True, color='blue')\n",
            "<ipython-input-11-23e97c842d0f>:4: FutureWarning: \n",
            "\n",
            "`shade` is now deprecated in favor of `fill`; setting `fill=True`.\n",
            "This will become an error in seaborn v0.14.0; please update your code.\n",
            "\n",
            "  sns.kdeplot(y_pred_proba[y_test_resampled == 1], label='True 1', shade=True, color='red')\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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e0aNHWbJkCb169eLEiRMcPnyYw4cPc+TIEdq1a8dff/3F3r17U93+/vvvT3V2u0mTJiQlJbFz506AlDORc+bMITEx8brzRkZG0rVrVz799NOUKXJJSUlMmzaNbt26kTNnzmvex+bNm4mKiiIqKopKlSrx1ltv0bFjRz788MM0b/PNN98QGBjII488kuryxx9/HMdx+PbbbzP1/XzzzTdER0dz2223pVwWHBzMI488wsmTJ1m2bFmm7hfMQvIL32f16tX54osvuPPOO1POdF/Qo0ePVKNXGXkefPPNN9SvXz/lLDCYkYg77rjjmvlmzJhBgQIFePjhhy/72rWaLWRXxotVqFCBqKgoYmJi6N+/P2XLlmXu3Lmp1jCFhobSr1+/VLfL6GPcrVs3ihYtmvJ53bp1qVevHt98803KZRePlp05c4bDhw9Tv359gFRTlS546KGHUn1+4Wd+8X1mtZkzZ5KcnEyvXr1SHq/Dhw8THR1NuXLlUkZsLowEzJ8/n1OnTmXoGEeOHCFv3ryZyvfNN99Qt25dGjdunHJZrly5uP/++9mxY0fKFNZ58+ZRtGhRunTpknK9sLCwdLU/z5Mnj1una13P7xCkfi2sWLEio0ePpkuXLkycODHlOul93H788UeOHDnCfffdl2pt2x133JHmY3LXXXelei5v2LCBv/76i9tvv50jR46kHCshIYFWrVqxfPnylCm2efLkYe3atfzzzz9XvO/MPo/S+zy4oF+/fqnWnjVp0gQwsxgulTdv3nRtDSDiDpqqJ5IFTp48ScGCBQHYunUrjuPw3HPP8dxzz13x+gcPHkz1pq5EiRKpvn7hD+SxY8cAaNasGT169OD555/n9ddfp3nz5nTr1o3bb78904ty+/Tpw7Rp01ixYgVNmzZl0aJFHDhw4KrtuS9WqlQpJkyYkNKivVy5cik/g7Ts3LmTIkWKkDt37lSXX5hCc6FQzKidO3dSrly5yxZEX+/9AtSrV48XX3wxpYV2pUqVrjgVMSYmJtXnGXke7Ny5k3r16l329QoVKlwz399//02FChUy1UAguzJebMaMGURERBAcHEyxYsWuOA2qaNGily3gz+hjXK5cucvut3z58nz++ecpnx89epTnn3+ezz777LK1KFdaB3TpfZYpU4aAgIBs3cPqr7/+wnGcK35/8P+NFGJiYnjsscd47bXXmDJlCk2aNKFLly707t37qtP0LnAuWnOYEWk9Ty5+nKpUqcLOnTspU6bMZYVJerr4Pfjgg3z++ee0b9+eokWL0rZtW3r16sWNN96YqczX8zsE//9amJyczN9//82IESM4dOhQqmY96X3cLjyPL/05BAUFpbmX1aWvPX/99RdgCqq0xMXFkTdvXl555RXuuusuihcvTmxsLB06dKBPnz6ULl065b4z8zxK7/Pggmv9DbyY4zg+0YFTvIMKJxE327NnD3FxcSl/6C6cyRs8eHCaTRYu/aOYVtelC29eLuydsmbNGr7++mvmz5/P3XffzZgxY1izZk2mugu1a9eOQoUKMXnyZJo2bcrkyZOJjo5O94LwnDlzZnrxuDcpUKBAur7PS9f6ZOZ5kN1sZGzatGnKeru0ZFd3yl69erF69WqeeOIJatSoQa5cuUhOTubGG29MV9MLG2/ekpOTcblcfPvtt1d83bj4tWDMmDH07duXr776igULFvDII4+krM+60lqZC/Lnz3/FN6yeomDBgmzYsIH58+fz7bff8u233/LRRx/Rp0+fqzYLySqXvhY2atSIWrVq8cwzz/Dmm28CGXvcMiqt157Ro0dTo0aNK97mwvF69eqVsjfdggULGD16NC+//DIzZ86kffv2QOafRxlxrb+BFzt27FiaBaiIu6lwEnGzTz75BCDljeeFM3XBwcFuLyzq169P/fr1GTFiBFOnTuWOO+7gs88+4957773i9a/2xi4wMJDbb7+diRMn8vLLLzNr1izuu+++LG2dW7JkSRYtWsSJEydSjTpt3rw55evpyX6l+/31119JTk5ONSJxpfvNLhl5HpQsWTLlLPHFtmzZcs3jlClThrVr15KYmJhm2+a0fpbZldEdMvoYXynrn3/+mXLW/tixYyxevJjnn3+eIUOGXPV2F3/t4rP7W7duJTk5Oc2RgPTKyHO9TJkyOI5DTEwM5cuXv+b1q1atStWqVXn22WdZvXo1jRo1Yvz48bz44otp3qZixYrMmDEj3ZkuVrJkySs+Jy59nEqWLMnvv/9+2ejBlTqpXUlISAidO3emc+fOJCcn8+CDD/Luu+/y3HPPUbZs2Qz/TK/1O5QR1apVo3fv3rz77rsMHjyYEiVKpPtxu/Dz2bp1Ky1atEi5/Pz58+zYsSNd+wVeGMWNiIhI19+gwoUL8+CDD/Lggw9y8OBBatWqxYgRI1IKJ8j48yi9z4OMOn/+PLt37041xVMkK2mNk4gbLVmyhOHDhxMTE5Oy1qNgwYI0b96cd999l3379l12m6u16k7LsWPHLjvzduFM4tmzZ9O83YW1SsePH7/i1++8806OHTtG//79OXnyZKq9SLJChw4dSEpK4r///W+qy19//XVcLleqP9Q5c+ZMM/eV7nf//v0pXQjB/IF96623yJUrF82aNXNL/ozIyPOgQ4cOrFmzhnXr1qX6+pQpU655nB49enD48OHLfqbw/2drL6wfuvTnmV0Z3SGjj/GsWbNSrSVct24da9euTXmOXThBcOnv1dixY9PM8Pbbb6f6/K233gJI9bzNjLQenyvp3r07gYGBPP/885dldxwnpZV6fHw858+fT/X1qlWrEhAQcNXXDIAGDRpw7NixK64vuZYOHTqwbt06vv/++5TLEhISeO+99yhVqlTKHmrt2rVj7969qdrenzlzhgkTJlzzGJe2iw8ICEgpKC58b9d67btYen6HMurJJ58kMTGR1157DUj/41a7dm3y58/PhAkTUj1+U6ZMSfcoYGxsLGXKlOHVV1/l5MmTl339wu91UlLSZVNSCxYsSJEiRVJ+jpl9HqX3eZBRv//+O2fOnKFhw4aZur1IRmnESSSTvv32WzZv3sz58+c5cOAAS5YsYeHChZQsWZLZs2enms/+9ttv07hxY6pWrcp9991H6dKlOXDgAN9//z179uzhl19+ydCxP/74Y9555x1uuukmypQpw4kTJ5gwYQIRERF06NAhzdvFxsYC8J///Idbb72V4OBgOnfunPKmombNmlSpUoUvvviCSpUqUatWrUz8ZNKvc+fOtGjRgv/85z/s2LGD6tWrs2DBAr766isGDhyYar1LbGwsixYt4rXXXqNIkSLExMRccc48mOYa7777Ln379uWnn36iVKlSTJ8+nVWrVjF27NjL1lRll/Q+D5588kk++eQTbrzxRh599NGUVt8XRlmupk+fPkyaNInHHnuMdevW0aRJExISEli0aBEPPvggXbt2JTw8nMqVKzNt2jTKly9Pvnz5qFKlClWqVMmWjO6Q0ce4bNmyNG7cmAceeICzZ88yduxY8ufPz5NPPgmYs/FNmzbllVdeITExkaJFi7JgwYKU/aSuZPv27XTp0oUbb7yR77//nsmTJ3P77benuSdael3t8blUmTJlePHFF3n66adT2lTnzp2b7du38+WXX3L//fczePBglixZwoABA7j55pspX74858+f55NPPiEwMJAePXpcNU/Hjh0JCgpi0aJFKdsBXGzGjBkpIwcXu+uuu3jqqaf49NNPad++PY888gj58uXj448/Zvv27cyYMSNltLB///7897//5bbbbuPRRx+lcOHCTJkyJeV19GojRvfeey9Hjx6lZcuWFCtWjJ07d/LWW29Ro0aNlDU0NWrUIDAwkJdffpm4uDhCQ0Np2bLlFddhpud3KKMqV65Mhw4deP/993nuuefS/biFhIQwbNgwHn74YVq2bEmvXr3YsWMHEydOvOKasCsJCAjg/fffp3379txwww3069ePokWLsnfvXpYuXUpERARff/01J06coFixYvTs2ZPq1auTK1cuFi1axA8//MCYMWMAMv08Su/zIKMWLlxIjhw5aNOmTaZuL5Jh2dnCT8QXXGgZfuEjJCTEiY6Odtq0aeO88cYbqVpdX+zvv/92+vTp40RHRzvBwcFO0aJFnU6dOjnTp0+/7L4vbTN+aQvj9evXO7fddptTokQJJzQ01ClYsKDTqVMn58cff0x1O67Q0nj48OFO0aJFnYCAgCu2jX7llVccwBk5cmS6fybNmjVzbrjhhmte79I2wo5jWtIOGjTIKVKkiBMcHOyUK1fOGT169GVtfzdv3uw0bdrUCQ8Pd4BrtiY/cOCA069fP6dAgQJOSEiIU7VqVeejjz667HoZbUd+reteaH89evToK349Pc8Dx3GcX3/91WnWrJkTFhbmFC1a1Bk+fLjzwQcfXLMdueOYNsP/+c9/nJiYGCc4ONiJjo52evbs6fz9998p11m9erUTGxvrhISEXPY8cXfGK7nQVvvQoUNXvd7VnlvpeYwvfjzGjBnjFC9e3AkNDXWaNGmSqm244zjOnj17nJtuusnJkyePExkZ6dx8883OP//8c9nP50L233//3enZs6eTO3duJ2/evM6AAQOc06dPp7rPzLQjd5y0H59L25FfMGPGDKdx48ZOzpw5nZw5czoVK1Z0HnroIWfLli2O4zjOtm3bnLvvvtspU6aMExYW5uTLl89p0aKFs2jRoiv+bC/VpUsXp1WrVqkuu/C9pPVxofX033//7fTs2dPJkyePExYW5tStW9eZM2fOZcfYtm2b07FjRyc8PNyJiopyHn/8cWfGjBkO4KxZsybNn9f06dOdtm3bOgULFnRCQkKcEiVKOP3793f27duX6v4nTJjglC5d2gkMDEz1GGT2d+hKrvZ8/e677y57Ll3rcbvgzTffdEqWLOmEhoY6devWdVatWuXExsY6N954Y8p1rtUe/ueff3a6d+/u5M+f3wkNDXVKlizp9OrVy1m8eLHjOKb1+RNPPOFUr17dyZ07t5MzZ06nevXqzjvvvJNyH+l9Hl36vHec9D0P0voeLvweX/r7Xa9ePad3795X/H5FsoLLcTI57iwiPumNN95I2WTx0s5GIuKfVqxYQfPmzdm8eXO2LsQfO3YsgwYNYs+ePak6j/q75ORkoqKi6N69e7qmM/qiDRs2UKtWLdavX59m0wsRd1PhJCIpHMehevXq5M+fP2UfERERMGu3ihUrlmVv1E+fPn3ZXlo1a9YkKSmJP//8M0uO6Q3OnDlDaGhoqml5EydOpF+/fkyePDnDe6f5iltvvZXk5ORUWwqIZDWtcRIREhISmD17NkuXLmXjxo189dVXtiOJiIfJ7IbU6dW9e3dKlChBjRo1iIuLY/LkyWzevDnbGo54qjVr1jBo0CBuvvlm8ufPz/r16/nggw+oUqUKN998s+141nz22We2I4gfUuEkIhw6dIjbb7+dPHny8Mwzz6i1q4hku3bt2vH+++8zZcoUkpKSqFy5Mp999hm33HKL7WhWlSpViuLFi/Pmm29y9OhR8uXLR58+fXjppZcu2xhaRLKWpuqJiIiIiIhcg/ZxEhERERERuQYVTiIiIiIiItfgd2uckpOT+eeff8idO3e6No4TERERERHf5DgOJ06coEiRItfcjNnvCqd//vmH4sWL244hIiIiIiIeYvfu3RQrVuyq1/G7wil37tyA+eFERERYTiMiIiIiIrbEx8dTvHjxlBrhavyucLowPS8iIkKFk4iIiIiIpGsJj5pDiIiIiIiIXIMKJxERERERkWtQ4SQiIiIiInINfrfGSURERETEEyQlJZGYmGg7hs8LDg4mMDDwuu9HhZOIiIiISDY7efIke/bswXEc21F8nsvlolixYuTKleu67keFk4iIiIhINkpKSmLPnj3kyJGDqKiodHV0k8xxHIdDhw6xZ88eypUrd10jTyqcRERERESyUWJiIo7jEBUVRXh4uO04Pi8qKoodO3aQmJh4XYWTmkOIiIiIiFigkabs4a6fswonERERERGRa9BUPRERERERD7BrFxw+nH3HK1AASpTIvuN5OxVOIiIiIiKW7doFlSrBqVPZd8wcOeCPP1Q8pZcKJxERERERyw4fNkXTM89AyZJZf7ydO2HkSHPc9BRO11onNHToUIYNG+aecNfgOA5Dhw5lwoQJHD9+nEaNGjFu3DjKlSuXpcdV4SQiIiIi4iFKloTy5W2nuNy+fftS/j9t2jSGDBnCli1bUi67eI8kx3FISkoiKChrSo1XXnmFN998k48//piYmBiee+452rVrx++//05YWFiWHBPUHEJERERERK4hOjo65SMyMhKXy5Xy+ebNm8mdOzfffvstsbGxhIaGsnLlSvr27Uu3bt1S3c/AgQNp3rx5yufJycmMGjWKmJgYwsPDqV69OtOnT08zh+M4jB07lmeffZauXbtSrVo1Jk2axD///MOsWbOy5pv/HxVOIiIiIiJy3Z566ileeukl/vjjD6pVq5au24waNYpJkyYxfvx4fvvtNwYNGkTv3r1ZtmzZFa+/fft29u/fT+vWrVMui4yMpF69enz//fdu+T7Soql6IiIiIiJy3V544QXatGmT7uufPXuWkSNHsmjRIho0aABA6dKlWblyJe+++y7NmjW77Db79+8HoFChQqkuL1SoUMrXsooKJxERERERuW61a9fO0PW3bt3KqVOnLiu2zp07R82aNd0ZzS1UOImIiIiIyHXLmTNnqs8DAgJwHCfVZYmJiSn/P3nyJABz586laNGiqa4XGhp6xWNER0cDcODAAQoXLpxy+YEDB6hRo0ams6eHCicR8Qn79sEPP8COHVCjBtSubfanEBERETuioqLYtGlTqss2bNhAcHAwAJUrVyY0NJRdu3ZdcVrelcTExBAdHc3ixYtTCqX4+HjWrl3LAw884Nb8l1LhJCJe6/RpGDECJk6EvXvNZUFBcP68+bdmTXjuOejc2WpMERGRdNu503eO07JlS0aPHs2kSZNo0KABkydPZtOmTSnT8HLnzs3gwYMZNGgQycnJNG7cmLi4OFatWkVERAR33XXXZffpcrkYOHAgL774IuXKlUtpR16kSJHLOvi5mwonEfFKCxbAv/4Fe/ZAp05QvbrZcT1/fti+HX77DVasgC5d4I474I03zNdEREQ8UYECZqbEyJHZd8wcOcxxs0q7du147rnnePLJJzlz5gx33303ffr0YePGjSnXGT58OFFRUYwaNYpt27aRJ08eatWqxTPPPJPm/T755JMkJCRw//33c/z4cRo3bsy8efOydA8nAJdz6cRDHxcfH09kZCRxcXFERETYjiMiGZSUZAqm9983I0oDB6a947njmALr7bchPBw+/RRatszWuCIiIpc5c+YM27dvJyYmJtWb/V274PDh7MtRoEDaf0N9SVo/b8hYbaARJxHxGklJ0LevKYAee8yMNLlcaV/f5YJ27cx6p5deMlP2Fi6Ehg2zLbKIiEi6lSjhH4WMt9IGuCLiFZKSoF8/UzQ984wpgq5WNF0sf3548UUoXx46dIBff83arCIiIuJ7VDiJiMdzHLj3XpgyxRRNmZluFxpqiqdChaBNG9i61f05RURExHepcBIRj/ff/5rOeU89dX1rlHLmhJdfhrAw6NgRTp1yW0QRERHxcSqcRMSj/fQTDB4MPXuakaLrlScPDB9u2rA+/fT135+IiIj4BxVOIuKx4uLg5puhdGm4/3733W+JEmbq35tvwuLF7rtfERER8V0qnETEIzmOKZYOHoRnn4X/bTLuNt27m3bmffuaAk1ERETkalQ4iYhH+vRT+PxzePxxKFrU/fcfEABPPgnHjsGjj7r//kVERMS3aB8nEfE4x46ZjW2bN4cWLbLuONHR8MAD8OqrcM890KRJ1h1LRETkmrQDrkdT4SQiHuc//4GEBHjwwaw/Vvv28PXXZkPdtWvNSJSIiEi227ULKlXK3pavOXLAH3+oeEonFU4i4lHWrYPx403RFBWV9ccLCIB//QsGDYJp0+C227L+mCIiIpc5fNgUTc88AyVLZv3xdu6EkSPNcdNROLmusev80KFDGTZsmJvCXd3MmTMZP348P/30E0ePHuXnn3+mRo0aWX5cFU4i4jGSkkwRU7Ys3HRT9h23Rg1o3NjsE3XTTWafJxEREStKloTy5W2nuMy+fftS/j9t2jSGDBnCli1bUi7LlStXyv8dxyEpKYmgoKwpNRISEmjcuDG9evXivvvuy5JjXIkmpYiIx3j3XdiwwaxvCgzM3mPffz/88w+88Ub2HldERMQbREdHp3xERkbicrlSPt+8eTO5c+fm22+/JTY2ltDQUFauXEnfvn3p1q1bqvsZOHAgzZs3T/k8OTmZUaNGERMTQ3h4ONWrV2f69OlXzXLnnXcyZMgQWrdunQXfado04iQiHuHECRg6FNq1g8qVs//4xYtD585m1sLdd2fPNEERERFf8tRTT/Hqq69SunRp8ubNm67bjBo1ismTJzN+/HjKlSvH8uXL6d27N1FRUTRr1iyLE2eMCicR8QhjxkB8PPTrZy/DXXfB/Pnw+uumgBIREZH0e+GFF2jTpk26r3/27FlGjhzJokWLaNCgAQClS5dm5cqVvPvuuyqcREQudeCAaQl+001QsKC9HJGR0KUL/Pe/8MQTkM6TZSIiIgLUrl07Q9ffunUrp06duqzYOnfuHDVr1nRnNLdQ4SQi1g0fbrrb3X677SRw883w5Zfw1lswZIjtNCIiIt4jZ86cqT4PCAjAcZxUlyUmJqb8/+TJkwDMnTuXopfsdh8aGppFKTNPhZOIWLV1q2kKcffdEBFhOw3kywcdO5rpeoMGQe7cthOJiIh4p6ioKDZt2pTqsg0bNhAcHAxA5cqVCQ0NZdeuXR43Le9KVDiJiFXPPWemxHXvbjvJ/7v1Vpg9G8aNgyeftJ1GRET8ys6dPnOcli1bMnr0aCZNmkSDBg2YPHkymzZtSpmGlzt3bgYPHsygQYNITk6mcePGxMXFsWrVKiIiIrjrrruueL9Hjx5l165d/PPPPwApbdEvdPnLKiqcRMSaP/4wm84OHAieNCIfFWW6+736Kjz8MISH204kIiI+r0AByJEje7sT5chhjptF2rVrx3PPPceTTz7JmTNnuPvuu+nTpw8bN25Muc7w4cOJiopi1KhRbNu2jTx58lCrVi2eeeaZNO939uzZ9Luom9Stt94KZP0mvC7n0omHPi4+Pp7IyEji4uKI8IR5QSJ+rHdvWLgQPvkEQkJsp0ntn3+gTx8YOxYGDLCdRkREfMmZM2fYvn07MTExhF286/quXXD4cPYFKVAASpTIvuNZkubPm4zVBhpxEhEr/vwTPv3UFCWeVjQBFCkCzZqZtU4PPJD9G/KKiIgfKlHCLwoZbxVgO4CI+KeRI/+/EYOn6tEDtm2DuXNtJxERERHbVDiJSLb7+2+YPBluucUzR5suqFwZbrjBjDqJiIiIf1PhJCLZbtQos9lsp062k1xbjx7w3XewYYPtJCIiImKTCicRyVa7d8PHH0OvXnDJ+kyP1LQpFCoEb7xhO4mIiPgaP+vRZo27fs4qnEQkW73+umnv3bmz7STpExgIXbvC1Klw4IDtNCIi4gsC/9dx6Ny5c5aT+IcLP+fA6+z0pK56IpJtjh6F996Dm24yW0d4i44dYdIksyFuFm4PISIifiIoKIgcOXJw6NAhgoODCQjQWEZWSU5O5tChQ+TIkYOgoOsrfVQ4iUi2GTcOzp+H7t1tJ8mYiAho2xbGj4f//AeCg20nEhERb+ZyuShcuDDbt29n586dtuP4vICAAEqUKIHL5bqu+1HhJCLZ4vRps5lsu3aQN6/tNBnXtSvMng2zZsHNN9tOIyIi3i4kJIRy5cppul42CAkJccuongonEckWEyeaqXq9etlOkjmlS0O1avD22yqcRETEPQICAgjzhk5JAqg5hIhkg6QkGD0amjWDokVtp8m8Ll1g2TL44w/bSURERCS7qXASkSz35ZewfbvZ8NabNWliphmOG2c7iYiIiGQ3FU4ikuXGjIGaNaFCBdtJrk9ICLRvb/ahSkiwnUZERESykwonEclS338Pa9ZAz562k7hH585w4oTZ10lERET8hwonEclSr78OxYtD/fq2k7hHdLT5Xt5+G7Thu4iIiP9Q4SQiWWb7dpgxA3r0AF/a269LF/jlF/jxR9tJREREJLv40FsZEfE0b74JuXObvZt8SZ06UKgQvPee7SQiIiKSXVQ4iUiWiIuD9983a4J8bYuKwEDTJOLTTyE+3nYaERERyQ4qnEQkS3zwAZw5A9262U6SNTp0gNOnTfEkIiIivk+Fk4i4XVKSmabXogXkz287TdaIijJNIt5913YSERERyQ4qnETE7WbPhp07TVMIX9apE/z8M/z0k+0kIiIiktWsFk6jRo2iTp065M6dm4IFC9KtWze2bNly1dtMnDgRl8uV6iPM1xZQiHi5sWOhalXv3/D2WurWhYIF1SRCRETEH1gtnJYtW8ZDDz3EmjVrWLhwIYmJibRt25aEhISr3i4iIoJ9+/alfOzcuTObEovItWzYAMuXQ/futpNkvcBAs9Zp6lSzKa6IiIj4riCbB583b16qzydOnEjBggX56aefaNq0aZq3c7lcREdHZ3U8EcmEN94wrbqbNLGdJHu0bw+TJsG0aXDvvbbTiIiISFbxqDVOcXFxAOTLl++q1zt58iQlS5akePHidO3ald9++y3N6549e5b4+PhUHyKSNQ4eNKMvXbua0Rh/ULCgmbKn6XoiIiK+zWMKp+TkZAYOHEijRo2oUqVKmterUKECH374IV999RWTJ08mOTmZhg0bsmfPnitef9SoUURGRqZ8FC9ePKu+BRG/9+67EBAAHTvaTpK9OnaEH36AX3+1nURERESyistxHMd2CIAHHniAb7/9lpUrV1KsWLF03y4xMZFKlSpx2223MXz48Mu+fvbsWc6ePZvyeXx8PMWLFycuLo6IiAi3ZBcRSEyEEiUgNhYGD7adJnudPw+33gq33QZvvWU7jYiIiKRXfHw8kZGR6aoNPGLEacCAAcyZM4elS5dmqGgCCA4OpmbNmmzduvWKXw8NDSUiIiLVh4i438yZsH+/fzSFuFRQELRrB598YjbFFREREd9jtXByHIcBAwbw5ZdfsmTJEmJiYjJ8H0lJSWzcuJHChQtnQUIRSa8334SaNaF0adtJ7OjQAeLiYPp020lEREQkK1gtnB566CEmT57M1KlTyZ07N/v372f//v2cvuiUbZ8+fXj66adTPn/hhRdYsGAB27ZtY/369fTu3ZudO3dyr9pZiVjz88+wejV062Y7iT1Fi0KtWmoSISIi4qusFk7jxo0jLi6O5s2bU7hw4ZSPadOmpVxn165d7Nu3L+XzY8eOcd9991GpUiU6dOhAfHw8q1evpnLlyja+BRHBrOspVAgaNbKdxK6OHWHlSrjGPt4iIiLihTymOUR2ycgCMBG5tiNHzGjLnXfCHXfYTmPXuXPQq5fZz+nVV22nERERkWvxuuYQIuK93n8fHAc6dbKdxL6QEGjbFiZOhIuaeYqIiIgPUOEkIpmWlARvvw0tW0JkpO00nqFjRzMKN2uW7SQiIiLiTiqcRCTT5syB3bv9uynEpUqWhOrV1SRCRETE16hwEpFM++9/oXJlqFDBdhLP0qEDLFkCf/9tO4mIiIi4iwonEcmUP/+ERYuga1fbSTxPs2aQO7dZ/yUiIiK+QYWTiGTKuHGQJw80b247iecJDYXWreGDD0ynPREREfF+KpxEJMMSEuCjj6B9e9NJTi7XqRMcOgRff207iYiIiLiDCicRybCpUyE+Hrp0sZ3Ec5UuDVWqwLvv2k4iIiIi7qDCSUQyxHFMU4gGDSA62nYaz9axIyxcCNu22U4iIiIi10uFk4hkyPffw6+/qilEerRoYZpEqDW5iIiI91PhJCIZMn48FC0KtWvbTuL5QkOhbVs1iRAREfEFKpxEJN2OHIHPPzdT0AL06pEunTvD4cPw5Ze2k4iIiMj10FsfEUm3iRMhOdl005P0KVkSqlc37dtFRETEe6lwEpF0SU420/SaNTP7N0n6deoEy5bB5s22k4iIiEhmqXASkXRZsgS2bjVTzyRjmjY1xaaaRIiIiHgvFU4iki7jx0NMDFStajuJ9wkJgXbtzKbBp07ZTiMiIiKZocJJRK7pn39g1iwz2uRy2U7jnTp3hrg4+Owz20lEREQkM1Q4icg1ffghBAdDmza2k3ivokWhbl2zebDj2E4jIiIiGaXCSUSuKjkZJkyA5s0hVy7babxb167w88+wbp3tJCIiIpJRKpxE5KoWLoRdu9QUwh3q1oUiReDtt20nERERkYxS4SQiV/Xee1CmDFSqZDuJ9wsMNAXotGlw6JDtNCIiIpIRKpxEJE3798Ps2dChg5pCuEv79uZn+cEHtpOIiIhIRqhwEpE0TZxoRknUFMJ9IiOhRQt45x1ISrKdRkRERNJLhZOIXFFyspmm17w55M5tO41v6dYNdu+Gr7+2nURERETSS4WTiFzR0qWwfTt07Gg7ie+pUAGqVIGxY20nERERkfRS4SQiVzRhApQqZd7gi/t17w7LlsGvv9pOIiIiIumhwklELnP0KHz55f83MhD3a9IEChaEN96wnURERETSQ4WTiFxm6lSzxql1a9tJfFdQEHTpAlOmwOHDttOIiIjItahwEpHLfPAB1K8P+fLZTuLbOnUy/773nt0cIiIicm0qnEQklZ9/hg0bzDQ9yVqRkWZU7+23ITHRdhoRERG5GhVOIpLKRx9B/vxQr57tJP6hRw/45x+YPt12EhEREbkaFU4ikuLMGfjkE2jb1mx8K1kvJgZq14ZXXwXHsZ1GRERE0qLCSURSfPUVHD8ON95oO4l/uflmWL8eli+3nURERETSosJJRFJ88AFUrQolSthO4l/q1IHSpc2ok4iIiHgmFU4iAsDevbB4sZmmJ9nL5TKjTnPmwObNttOIiIjIlahwEhHA7N0UFATNm9tO4p9atjRNOV5/3XYSERERuRIVTiKC48DEidCoEeTKZTuNfwoJgW7d4OOP4eBB22lERETkUiqcRIQNG+D33zVNz7YuXcy0vbfftp1ERERELqXCSUSYNAny5TNNCsSeiAjo0AHeegsSEmynERERkYupcBLxc4mJMHmyWWOjvZvsu/lmOHEC3n/fdhIRERG5mAonET83fz4cPgzt2tlOIgDR0dCqlWlNfu6c7TQiIiJygQonET83aRKULWs+xDPccgvs2QOffmo7iYiIiFygwknEjx0/DrNnQ+vWtpPIxWJioGFDeOklSE62nUZERERAhZOIX/vySzMdrGVL20nkUrfdZjbD/fpr20lEREQEVDiJ+LUpU6BGDYiKsp1ELlWlClSrBiNHmn22RERExC4VTiJ+av9+WLpUo02e7I47YN06WLLEdhIRERFR4STipz7/HAICoGlT20kkLXXqQIUKMHy47SQiIiKiwknET02dCnXrmk1XxTO5XNC7NyxbBitX2k4jIiLi31Q4ifihbdtg7VqzX5B4toYNoXRpjTqJiIjYpsJJxA999hmEhUGDBraTyLUEBJi1TgsWwA8/2E4jIiLiv1Q4ifihKVOgcWMID7edRNKjWTMoUQJefNF2EhEREf+lwknEz2zcCL//rm563iQw0OzrNHs2/PKL7TQiIiL+SYWTiJ/5/HPInRtq17adRDKiTRsoWhReeMF2EhEREf+kwknEjziOKZwaNYLgYNtpJCMCA81ap5kzNeokIiJigwonET+yaRP8+adZMyPeR6NOIiIi9qhwEvEjX3xhpunFxtpOIpkRFPT/o06//mo7jYiIiH9R4STiJxwHpk0z+wJpmp730qiTiIiIHSqcRPyEpun5hgujTjNmaNRJREQkO6lwEvETX3wBuXKpm54vuDDqNHSo7SQiIiL+Q4WTiB+40E1P0/R8Q1AQ9O4Ns2bB+vW204iIiPgHFU4ifuC332DLFmje3HYScZc2baB4cY06iYiIZBcVTiJ+YPp0M01P3fR8R2Ag3HknzJkD69bZTiMiIuL7VDiJ+IGZM6F+fQgJsZ1E3KllSyhVCoYMsZ1ERETE96lwEvFx27bBxo3QuLHtJOJugYHQpw/Mnw+rV9tOIyIi4ttUOIn4uFmzzEhT3bq2k0hWaNYMSpeG556znURERMS3qXAS8XEzZ5oW5OHhtpNIVggIgL59YckS+O4722lERER8lwonER928KCZwtWoke0kkpUaN4by5eHZZ03reREREXE/q4XTqFGjqFOnDrlz56ZgwYJ069aNLVu2XPN2X3zxBRUrViQsLIyqVavyzTffZENaEe8zeza4XGb/JvFdLhf06werVsGCBbbTiIiI+CarhdOyZct46KGHWLNmDQsXLiQxMZG2bduSkJCQ5m1Wr17Nbbfdxj333MPPP/9Mt27d6NatG5s2bcrG5CLeYeZMqFoV8uSxnUSyWr16cMMNGnUSERHJKi7H8Zw/sYcOHaJgwYIsW7aMpk2bXvE6t9xyCwkJCcyZMyflsvr161OjRg3Gjx9/zWPEx8cTGRlJXFwcERERbssu4mlOnIACBeC++6BnT9tpJDv89BMMHgxffQVduthOIyIi4vkyUht41BqnuLg4APLly5fmdb7//ntat26d6rJ27drx/fffX/H6Z8+eJT4+PtWHiD/49ls4d05tyP1JrVpQs6YZdUpOtp1GRETEt3hM4ZScnMzAgQNp1KgRVapUSfN6+/fvp1ChQqkuK1SoEPv377/i9UeNGkVkZGTKR/Hixd2aW8RTzZoF5cpBdLTtJJJdXC7TYW/jRpgxw3YaERER3+IxhdNDDz3Epk2b+Oyzz9x6v08//TRxcXEpH7t373br/Yt4osREmDtXTSH8UbVqUKcODBkCSUm204iIiPgOjyicBgwYwJw5c1i6dCnFihW76nWjo6M5cOBAqssOHDhAdBqn1UNDQ4mIiEj1IeLrVq2C+Hho0MB2ErGhXz/YvBncfB5KRETEr1ktnBzHYcCAAXz55ZcsWbKEmJiYa96mQYMGLF68ONVlCxcupIHeIYqk+Ppr0xiiXDnbScSGSpXMaOPQoXD+vO00IiIivsFq4fTQQw8xefJkpk6dSu7cudm/fz/79+/n9OnTKdfp06cPTz/9dMrnjz76KPPmzWPMmDFs3ryZYcOG8eOPPzJgwAAb34KIR/r6a9OeOsAjxpTFhn794O+/YdIk20lERER8g9W3VePGjSMuLo7mzZtTuHDhlI9p06alXGfXrl3s27cv5fOGDRsydepU3nvvPapXr8706dOZNWvWVRtKiPiTP/+Ev/7SND1/V7YsNG0Kzz9vuiuKiIjI9fGofZyyg/ZxEl/32mvw9NOmq154uO00YtP27XDPPTBuHPTvbzuNiIiI5/HafZxE5Pp9/bXZz0dFk8TEQMuWMHw4nD1rO42IiIh3U+Ek4kOOH4eVK6F+fdtJxFP06QP79sEHH9hOIiIi4t1UOIn4kPnzTRc1FU5yQYkS0Lo1vPginDljO42IiIj3UuEk4kPmzDFNAQoVsp1EPMmdd8LBg/Dee7aTiIiIeC8VTiI+IikJ5s7VaJNcrlgxaNMGRo6EU6dspxEREfFOKpxEfMS6dXDsmNm/SeRSd94Jhw9r1ElERCSzVDiJ+Ihvv4WICKhUyXYS8URFikDbtvDSS3DRHuMiIiKSTiqcRHzEt99CbCwEBtpOIp7qjjvMqNOECbaTiIiIeB8VTiI+4NAh+OknqFvXdhLxZEWLmg57L72kDnsiIiIZpcJJxAcsWACOo8JJrq13bzhwAN5/33YSERER76LCScQHfPstlC8P+fLZTiKerlgxM+o0ahScPWs7jYiIiPdQ4STi5ZKTYd48qF3bdhLxFr17w/798MEHtpOIiIh4DxVOIl7up5/gyBG1IZf0K14cWrSAl1+GxETbaURERLyDCicRLzdvHuTKBZUr204i3uSOO2DXLpgyxXYSERER76DCScTLffMN1KoFQUG2k4g3iYmBxo1h5EhISrKdRkRExPOpcBLxYkePwrp16qYnmXPHHfDXXzB9uu0kIiIink+Fk4gXW7zYNIdQ4SSZUbEi1KkDI0aYdvYiIiKSNhVOIl5swQIoVQqiomwnEW91xx2wcSPMmWM7iYiIiGdT4STipRzHFE61atlOIt6senWoVk2jTiIiIteiwknES23darqiaf8muV633gpr18KKFbaTiIiIeC4VTiJeasEC00mvRg3bScTb1a8PpUubfZ1ERETkylQ4iXiphQvhhhsgPNx2EvF2Lhfccotpbb9pk+00IiIinkmFk4gXSkyEpUshNtZ2EvEVLVtCdDS88ortJCIiIp5JhZOIF1q3DuLjtb5J3CcoCHr0gE8/NWvnREREJDUVTiJeaOFCiIiA8uVtJxFf0rEj5MgBr79uO4mIiIjnUeEk4oUWLDBNIQIDbScRXxIeDl27woQJcOyY7TQiIiKeRYWTiJeJizNT9bS+SbJCt25mDd2ECbaTiIiIeBYVTiJeZulSSErS+ibJGvnyQatW8MYbpoASERERQ4WTiJdZvBiKFoUiRWwnEV91883wzz/wxRe2k4iIiHgOFU4iXmbRIm16K1krJgbq1IFXXwXHsZ1GRETEM6hwEvEi+/bB5s1Qq5btJOLrevaEn3+GFStsJxEREfEMKpxEvMjSpeZfjThJVqtTB0qVgtdes51ERETEM6hwEvEiixdD6dJmAb9IVnK5zKjT7NmwdavtNCIiIvapcBLxIosXQ82atlOIv2jd2my0/M47tpOIiIjYp8JJxEts3w47d6pwkuwTGgodOsAHH8DJk7bTiIiI2KXCScRLLF4MAQFQvbrtJOJPunQxRdMnn9hOIiIiYpcKJxEvsWQJVKgAuXLZTiL+JDoaGjWCt95Sa3IREfFvKpxEvIDjaH2T2HPTTfDHH6Z4FxER8VcqnES8wO+/w8GD2r9J7KhRw3RzfOst20lERETsUeEk4gWWLIHgYLjhBttJxB+5XNC1K3z9NezYYTuNiIiIHSqcRLzAkiWmaAoLs51E/FWbNpAjB4wbZzuJiIiIHSqcRDxccjJ8952ZLiViS3g4tG0LH34IZ8/aTiMiIpL9VDiJeLiNG+H4cbUhF/u6dIHDh+HLL20nERERyX4qnEQ83HffQUgIVK5sO4n4u5IlzcjnO+/YTiIiIpL9VDiJeLjvvjPrm0JCbCcRgc6dYcUK0+lRRETEn6hwEvFgF9Y3aZqeeIomTSBvXnj3XdtJREREspcKJxEP9uuvWt8kniU4GNq3h48/hoQE22lERESyjwonEQ+m9U3iiTp1gvh4+Owz20lERESyjwonEQ+m9U3iiQoXhjp14L33bCcRERHJPiqcRDxUcjIsW6ZpeuKZOnaEdetMu3wRERF/oMJJxENpfZN4sgYNIF8++OAD20lERESyhwonEQ+l9U3iyYKDoU0bmDQJzpyxnUZERCTrZapw2rZtm7tziMgltL5JPF2HDnDsGMyaZTuJiIhI1stU4VS2bFlatGjB5MmTOaNTjSJud2F9U7VqtpOIpK1ECfMcnTDBdhIREZGsl6nCaf369VSrVo3HHnuM6Oho+vfvz7p169ydTcRvbdqk9U3iHdq3hyVLQBMRRETE12WqcKpRowZvvPEG//zzDx9++CH79u2jcePGVKlShddee41Dhw65O6eIX1m+HIKCoFIl20lErq5ZM8iVCz76yHYSERGRrHVdzSGCgoLo3r07X3zxBS+//DJbt25l8ODBFC9enD59+rBv3z535RTxK8uXQ8WKEBZmO4nI1YWHQ8uWprteUpLtNCIiIlkn6Hpu/OOPP/Lhhx/y2WefkTNnTgYPHsw999zDnj17eP755+nataum8IlkkOOY9U2tW9tOIl4nKYngE0cJSogj6ORxAhPicZ1PxJWchMtJxsFFckgYyaHhJIfl4HzOSBIj8pOUIze4XJk+bPv2MHs2LFoE7dq58fsRERHxIJkqnF577TU++ugjtmzZQocOHZg0aRIdOnQgIMAMYMXExDBx4kRKlSrlzqwifuGvv+DgQTWGkDQ4DiFH95Pz71/Jte1Xcm7fRNj+7YQd2EXI4b0EJJ3P8F0mBwZxPiI/Z6KKcbZgcc5GFeNMdClOFynL6aJlOVOkNMmh4WnevkIFiImBiRNVOImIiO/KVOE0btw47r77bvr27UvhwoWveJ2CBQvygXZGFMmw5cshIMC0IhcBCNu3nTw/LyXPhqXk/XkpoYf3ApAUGs6Z6BjO5i9MXJVGnMtbkPMR+UkKy0lSeC6SwnLgBAbjBASAKwAch4DEswQknsWVeI7A0ycJOhVHYEI8QSfjCI47RMiRfeTa9ishR/YRePY0AI7LxZnCpTkZU5WE0lVIKF2NE+VjOVM4BlwuXC5o29YUTseOQd68Fn9YIiIiWSRThdPChQspUaJEygjTBY7jsHv3bkqUKEFISAh33XWXW0KK+JPly6FcObPgXvxXjp1/ELVsOlHLviDXto04Lheni5UnrkojEmJu4HSRMpzLV9hU2VnBcQg6cYzQw3sJPbSbsP07CNu3g8hNKwmJOwxAYq48nCgfS3yVRtxRohHTEuszbVoE//pX1kQSERGxyeU4jpPRGwUGBrJv3z4KFiyY6vIjR45QsGBBkjx4hXB8fDyRkZHExcURERFhO47IZUqWhLp14aGHbCeR7BZwOoFCi6dS5Kt3yL11A0mhOYi7oQFx1ZpwsnwsSeGeUU0HnThG+J4/ybF7Czl2bSHHjt8ITogjiQD+ylGdigPaQKtW0Lgx5MhhO66IiEiaMlIbZGrEKa1a6+TJk4SpDZhIpu3cCbt2wb332k4i2Sn0wC6Kfz6G6PkTCTx1gvjK9dl+93DiK9bFCQ6xHe8y53Pn5USlepyoVM9c4DiEHtzN0eUbSVj9C2Xf+4CgV16BkBBo3hw6d4ZOnUDrXkVExItlqHB67LHHAHC5XAwZMoQcF51JTEpKYu3atdSoUcOtAUX8yYoV5t+qVe3mkOwRemAXJaaOovA3H5AUmoMjDTpxpEFnzuWLth0tY1wuzhYqQUi3Eoz6pSPb2zn0v3En/PgjrF0LgwbBww+bJ/Ytt5iPsmVtpxYREcmQDBVOP//8M2BGnDZu3EhIyP+fCQ0JCaF69eoMHjzYvQlF/Mjy5aY7WZ48tpNIVgo6eZxSHw2lyOxxJIfmYP+N/TjcuNtVO9d5g+BgqFkT5i9wce99pQgsVQp69oSEBFNELV8OI0bAs8+aK/bpA717Q4ECtqOLiIhcU6bWOPXr14833njDK9cIaY2TeLIKFczGt4MG2U4iWSI5mej5H1P63ScJPHOKA61u43CT7iSH+c46oF274LXX4ZWXzVq9y5w5Y0ahliyB1avN/lFdupj5qW3bZl2zCxERkSvI8jVOH330UaaCiUjaDhyAP/+EXr1sJ5GskGP7b1QcfQ8Rf6zlaK3W/NOlP+cjfW+kpXhxiC4ECxakUTiFhUGzZuYjLg4WLoT5880uumXLwiOPQN++kDt3dkcXERG5qnQXTt27d2fixIlERETQvXv3q1535syZ6brP5cuXM3r0aH766Sf27dvHl19+Sbdu3dK8/nfffUeLFi0uu3zfvn1ER3vZmgCRS6xcaf7Vxrc+JjmZYjPfpPR7T3EuXzR/PfQ6CWVr2E6VZVwuiI2FRYvg1KlrNNWLjDRT+Xr0gN9+g5kzzXDrf/4DDzwAjz0GhQplW3YREZGrSXfhFBkZicvlSvm/OyQkJFC9enXuvvvuaxZjF9uyZUuqobRL26KLeKOVK6FwYYiKsp1E3CX00B4qjrqLvD8v4VDTHvzT8T6ckFDbsbJcbCzM/cYsabrxxnTcwOWCKlXMx6FDMGsWvP02vPkm3HcfPPGEGcoSERGxKFNrnLKCy+VK94jTsWPHyJPJ1fNa4ySeKjYW8ueHZ56xnUTcIc9Pi7nhhV44rkB23fYkJyvUth0pW739ttnE+fXXM3kHJ06YEaiZM826qIcfNr8c+fK5NaeIiPi3jNQGmVqFe/r0aU6dOpXy+c6dOxk7diwLFizIzN1lWI0aNShcuDBt2rRh1apVV73u2bNniY+PT/Uh4mlOnIANG9SG3Cc4DsWmj6X6k+04Xbg0W56Y4HdFE5gTARs2mAGkTMmdG+66Cz79FG6/HcaNg9Kl4eWX4fRpd0YVEU909iysW2dGoMePh+HD4bvvwDPO94ufylTh1LVrVyZNmgTA8ePHqVu3LmPGjKFr166MGzfOrQEvVrhwYcaPH8+MGTOYMWMGxYsXp3nz5qxfvz7N24waNYrIyMiUj+Ka7iEeaM0aSE7W+iZvF3D2NBVH9qHs24M42Kwn2+57iaSc7pna7G2qVzftyRcuvM47ypHDFFCffAItWphW5jfcAHPnuiWniHigb76BypWhXj246SYYMABGjzavAVWqwDvvmDOOItksU4XT+vXradKkCQDTp08nOjqanTt3MmnSJN588023BrxYhQoV6N+/P7GxsTRs2JAPP/yQhg0b8vpV5oI8/fTTxMXFpXzs3r07y/KJZNbKlWadfIkStpNIZgWdOEa1wW2IWj6dHXc+x74u/4LAQNuxrAkPN+9v5s930wnifPng0Ufhgw/MnNZOnaBrV9ixww13LiIeYft2sz1Bx47md/6tt8x03fnz4auvYMwYs+/bI49AmTLwv/1FRbJLpgqnU6dOkft/rWIXLFhA9+7dCQgIoH79+uzcudOtAa+lbt26bN26Nc2vh4aGEhERkepDxNOsWGHeZP6v/4p4mZBDe6nxSBNybd/E3w+O4XitlrYjeYTatWHnLvjrLzfeaYkS8MorMGwYfP+9OSv9xhtmyFZEvNeqVeYP4dq15vf7lVfM53nzmpNQLhfUqgXPPw9Tp5oCqnlz8wdUJJtkqnAqW7Yss2bNYvfu3cyfP5+2bdsCcPDgwWwvTDZs2EDhwoWz9Zgi7pSYaP5OaH2Td8qxazO1BjQgJO4wfz38JqdKVrYdyWNUqAC5c5nW5G7lcpl9oD7+2LTtGzjQfH6Vk2gi4sE2bDCjTBUqwMSJ5vf5amcSCxaEV181o07t2sG332ZXUvFzmSqchgwZwuDBgylVqhT16tWjQYMGgBl9qlmzZrrv5+TJk2zYsIENGzYAsH37djZs2MCuXbsAM82uT58+KdcfO3YsX331FVu3bmXTpk0MHDiQJUuW8NBDD2Xm2xDxCD//bPa7UeHkfXJu30TNhxvjBAbx1yNvcbaQ5lpeLDAQatQwhVNSUhYcIDzcTNl5/XXYts0sEnznHS0eF/Emf/4JbdqY/ThefNH8XqdHjhzw0ktmFKpLF617lGyRqcKpZ8+e7Nq1ix9//JF58+alXN6qVaurrje61I8//kjNmjVTiq3HHnuMmjVrMmTIEMBsbHuhiAI4d+4cjz/+OFWrVqVZs2b88ssvLFq0iFatWmXm2xDxCCtWQFgYlCtnO4lkRI4dv1N9UAsSc+dj60NjScyjDbiuJDYWjh4zJ5SzTI0a8P775s3XQw+ZDXWPHs3CA4qIW+zeDa1bm70LXnrpGjtmX0FIiJnWV6eOaSKzf3+WxBS5wGP2ccou2sdJPM1NN8HOnfDaa7aTSHrl2LWZGgObcT48N38/OMZvO+elh+PAyJFmvdO//50NB1y50nTfioiAzz6DRo2y4aAikmFJSdCwIezaZTa7vp7d348fh3vugfr1Yc4cLRiWDMnyfZwSEhJ47rnnaNiwIWXLlqV06dKpPkQkfRzn/xtDiHcI3/MX1Qe1ICksJ38/8KqKpmtwuaBmTVi+HM6dy4YDNm4M771nFpQ3awZjx2rqnogneu01+OEH+M9/rq9oAsiTBwYPNm3MJ0xwSzyRKwnKzI3uvfdeli1bxp133knhwoVxqbIXyZQtW+DIEe3f5C1Cju6n2hNtcYJDTNGUK4/tSF4hNhYWLDRN8Jo1y4YDFipk1j299x4MGgQ//WT+n961EyKStTZvhueeg5493XfmsEEDs03BoEHQsiWULeue+xW5SKYKp2+//Za5c+fSSFMgRK7LypUQEGA6KotnCzx1gqpPdSDw9En+euQtzufOZzuS1yhUCEoUN00isqVwAtOZ4oEHoHx5031r0yaYNQtKlsymACJyRUlJ0Lev6Yx3993uve8HHzQdl3r3htWrzR9YETfK1DMqb9685MunNw0i12vlStMUIqPrYSV7uc4ncsOwnuTY/Sfb7htFYr5o25G8Tq1asGYNnDiRzQdu1cpsonnggFlAvm5dNgcQkVTGjjW/h088YTojuVN4ODz5pNnjY9o09963CJksnIYPH86QIUM4deqUu/OI+JWVKzXa5PEch/Jj7ifP+iVs7/c8Z4pq+kdm1KxpTjQvX27h4GXLmjblBQuaDTNnzbIQQkTYsQOefdZ0vsyqPTiqVTPT9p57zmyUKOJGmSqcxowZw/z58ylUqBBVq1alVq1aqT5E5NoOHIC//1ZjCE9X/PMxFJ43kd23PsnJ8rG243ityEgzurpwoaUAefLAmDFQty50727WQIlI9ho61EyxcPcUvUvdfbf5A/vxx1l7HPE7mVrj1K1bNzfHEPE/q1aZf7XxrefKt24epd/7Nwda386x2m1sx/F6NWua2TOHD0OBAhYChIbCkCGm69Zjj8G+ffDyy2pdLJIdNm2CTz4xm1ZndaOWsmVNg4hhw8x6J3dPCRS/lanCaejQoe7OIeJ3Vq0yG6VfbxdWyRrhu/+k8gu3El+xHvvaZ/HZUT9RvTpMnw7ffWeaaVkREAD9+5vKbfRoU8W99x4EZerPoYik13/+A0WKQMeO2XO8vn2hXz8YPx4GDsyeY4rPy3S7kePHj/P+++/z9NNPc/R/O7SvX7+evXv3ui2ciC9bsULrmzxVYEI8Vf7ThfO5ItnZ+xkICLQdySeEh0OlShan612sRw945hmYNAluuQXOnLGdSMR3ff89zJ5tipng4Ow5ZvHi0K4djBgBJ09mzzHF52WqcPr1118pX748L7/8Mq+++irHjx8HYObMmTz99NPuzCfik06dMh1TNU3PAzkOFV+6i9DDe9l+93CSw3PZTuRTatWCLX+CR5xja9MGhg+HuXPN/i9qeCTifo4DTz31/9PnslOfPhAXZzprirhBpgqnxx57jL59+/LXX38RdtG80Q4dOrDcSsskEe/yww9w/rwaQ3iiojPfImrlLHbd9m/OFixhO47PueEGCAuFJUtsJ/mfBg3gpZfMni8dOkBCgu1EIr5lwQLTTvPuu7N/X6VChaBtW1M4qcOeuEGmnsE//PAD/fv3v+zyokWLsn///usOJeLrVq6EXLmgVCnbSeRiubf8SJnxgznYtCfxVRvbjuOTQkJM8bRwoTkR7RFq1DBNIn74AW680cJmUyI+ynFMQ5aqVaF+fTsZunc3jWC+/NLO8cWnZKpwCg0NJT4+/rLL//zzT6K00l3kmi7s3xSopTMeI+jkcSoPu5nTRcqyr/P9tuP4tNhY2LXbdAv2GFWrwiuvwIYNZl3EFf7GiUgGrV5tNru97TZ73StLlzYnR958087xxadkqnDq0qULL7zwAon/G/Z0uVzs2rWLf//73/To0cOtAUV8TXKyWSeraXoexHGoMPpeguMOs7PPczhB2bR42U9VqAC5cnrQdL0LbrjBFE8bN5rOX5q2J3J9Ro82Uyvq1bObo1s308p2wwa7OcTrZXoD3JMnTxIVFcXp06dp1qwZZcuWJXfu3IwYMcLdGUV8yu+/m7WqKpw8R/Q3HxK1fAa7b32Cc/kL247j8wIDoVo1WLTIg6brXVCpklnz9NNP0LWruu2JZNZff5lOej17Zv/apks1bgwFC6pJhFy3TD2TIyMjWbhwIXPnzuXNN99kwIABfPPNNyxbtoycOXO6O6OIT1m50mwZU7Gi7SQCEPbPNsq+PZDD9ToQV62p7Th+o1YtOHgIfvvNdpIruOEGGDnSnKHu0QPOnbOdSMT7vP465M1rulfaFhgInTvD1Klw5IjtNOLFMlw4JScn8+GHH9KpUyf69+/PuHHjWLlyJf/88w+Ox506FPE8q1ZBuXJZv3G6pENSEpVG3klSjgj+6faQ7TR+pXRpyBMJixfbTpKGGjXghRdMF4vbb4ekJNuJRLzHoUPw0UdmilxIiO00RqdOZq78Bx/YTiJeLEOFk+M4dOnShXvvvZe9e/dStWpVbrjhBnbu3Enfvn256aabsiqniM9YudKc0Bb7SkwbTcTv37Pr9qdIDsthO45fCQiA6tVh6VIPrknq1IFhw2DWLLj/fg+cVyjiocaNM/926WI3x8Xy5IEWLeDttz34RUc8XYYKp4kTJ7J8+XIWL17Mzz//zKeffspnn33GL7/8wqJFi1iyZAmTJk3KqqwiXm/fPtixQ4WTJ8i1dQOlPhrCwZa3kVBaOxHbEBsLx+M8fL12w4bw5JPw4YegDd5Fru30abOWqF07iIy0nSa1bt1g1y6zwFIkEzJUOH366ac888wztGjR4rKvtWzZkqeeeoopU6a4LZyIr1m92vyrxhB2uRLPUXFUH84UKsn+G/vajuO3iheHqAIePF3vgrZt4aGHzF5Po0fbTiPi2T7/HA4fNk0hPE2FClCyJHzyie0k4qUyVDj9+uuv3HjjjWl+vX379vzyyy/XHUrEV61eDYULQ4ECtpP4txKfvULOHb+z+9Yn1XrcIpfLLCVavtwL+i/07Al33mlGnyZOtJ1GxHONG2emuRYrZjvJ5VwuaN0aZs7URteSKRkqnI4ePUqhQoXS/HqhQoU4duzYdYcS8VUXNr4Ve3Ls+J2Sk4ZzoOWtnC5WznYcv1erFpxMgB9+sJ0kHfr1MwvM770X5s2znUbE8/zyC6xda35PPFWbNmY64cyZtpOIF8pQ4ZSUlERQUFCaXw8MDOT8+fPXHUrEF50+DT//rGl6ViUlUWH0PZzLH82Btn1spxHMCGzRIl4wXQ/M2eqBA81mnj17mr2eROT/vfuumVLRsKHtJGkrVAhq1gStyZdMSLsKugLHcejbty+hoaFX/PrZs2fdEkrEF/34IyQmqnCyqeiX/yXij7VsHfAGTrCHtMgVatQwhdPp017Qpj8wEJ59FgYPhvbtYc0a01tdxN+dPAmTJ5sGDFc5ye4RWreGV1+FPXs8c0qheKwMjTjdddddFCxYkMjIyCt+FCxYkD59dBZX5EpWr4YcOSAmxnYS/xS2fwel33+Gw426qYueh6lZE86che+/t50kncLDYcQICAszncO0oaYIfPopJCRAx462k1xbs2Zmfyk1NJMMytApgY8++iircoj4vFWroFIlc8Jasl/ZNx8mKTwn+zreazuKXKJAAShV0nQIbtnSdpp0ypMHRo2CAQOga1cTPizMdioRe8aNM9NYr7IW3mPkzAmNGsHHH5uGLy6X7UTiJTI04iQimeM4pnDSND078q/8igLfz2Fvt4e00a2HqlkT1q3zskZXRYvCiy+aebh33w3JybYTidjx449mEW/nzraTpF+bNvDHHya3SDqpcBLJBn/+CUePauNbGwJOJ1DurYeJq1SPuGpNbceRNNSoAUlJpjW5V7nhBrMx7qefwpAhttOI2DF+vBlpqlvXdpL0q1MH8uXTnk6SISqcRLLBqlUQEKBW5DaU+mQ4IccOsrf7I5qO4cEiI6FsWS/prnepZs2gf3+z7unDD22nEcleCQkwbRrceKN3zUUPDDS/u198odFiSTcVTiLZYPVq03grZ07bSfxLju2/UezzMRxofQfnChSxHUeuoVYt2LDBjM56nVtuMdOU+veH776znUYk+8ycaTrqtWtnO0nGNW0Ke/eaecIi6aDCSSQbaONbCxyHcm88xLn8RTjY8hbbaSQdqlUzg4JeWXe4XPDII1C9Otx0E/z1l+1EItnjo4/MIsXChW0nybiqVSFvXpgxw3YS8RIqnESy2JEjsGWLGkNkt6hl08n7yzL23vQQTpD2bPIGOXNCxYqmQZ1XCgqCoUMhIgI6dPDSoTORDNi5E5YuhbZtbSfJnMBA011v+nTTxUnkGlQ4iWSxNWvMvyqcsk/A2dOUGfc4cTc05ERFL1qsLNSqBb//Afv22U6SSblzw8iRcOgQdO8O587ZTiSSdSZNMvuaNWtmO0nmNW0KO3aou56kiwonkSy2ejXkzw/R0baT+I/in40m5Mg+9nZ9wHYUyaAqVSAk2JzE9lpFi8Lzz5uuMA8/rDPZ4pscx0zTa9bMFE/eqmZNM0qs6XqSDiqcRLLYqlWmY7EaumWP0AO7KDH1JQ4168m5qGK240gGhYaa4mnhQttJrlP16jBoELz3Hrz1lu00Iu63ciVs3+6dTSEuFhQEDRua7no6ySHXoMJJJAslJsIPP2j/puxU+t1/kxwWzoE2vW1HkUyqVQu274Bt22wnuU4dOsDNN5sCav5822lE3GviRChSxHR18XZNm5qGLr/9ZjuJeDgVTiJZ6Jdf4NQpFU7ZJWLjKgot/Yx9He8jOUy9371VxYqQM4eX7ul0qf79zaagt9wCmzfbTiPiHgkJ8PnnpilEgA+8lYyNhVy5NF1PrskHnu0inmv1aggOhnLlbCfxA45D2XcGcapYeY7W9tIOTwKYmTPVqpnuel4/cyYwEJ59FvLlg06d1GlPfMOsWWbvJm/tpnepkBCoX99M1xO5ChVOIllo9WqoUMG8JkvWilr6ORGbf+Cfrg/4xhlQPxcbCwcO+sjMmZw54cUX4fBh6NULzp+3nUjk+nzyiTm74Y17N6WlaVPzgvPnn7aTiAfTuwuRLHShMYRkLde5s5R5798cr9KIk2Vr2I4jblC6NOSJ9JHpemDWggwbBsuWweOP204jknkHDpjh4FatbCdxrzp1THear7+2nUQ8mAonkSyyezfs2aP9m7JD0Vn/JfTQHvZ1ut92FHGTgADTJGLJEh8aoKlRw7Qnf/NNeP9922lEMmfaNNMm1pv3brqSsDDTmnz2bNtJxIOpcBLJIt9/b/6tXNluDl8XFHeEkpOGc7hBJ84WKmE7jrhRrVoQFw/r19tO4kZdukDXrvDgg7Bihe00Ihk3eTLUqweRkbaTuF+DBmaqyLFjtpOIh1LhJJJFVq2CYsXMmnDJOiUnv0hA0nkOtLvLdhRxs6JFIbqQD+zpdKkBA8xQdPfusHOn7TQi6ffnn2aPjdatbSfJGg0aQFISzJtnO4l4KBVOIllk1SqoVMl2Ct8Wtm87RWe9zYGWt3I+d17bccTNXC7TJGLlSjh92nYaNwoKgqFDTdeYLl1MdzIRbzBlimnb3aCB7SRZIyoKypfXOidJkwonkSxw6pTZw0nrm7JWqQ+HkJQjgsNNe9iOIlmkVi04fcaciPApkZGm097WrdC3LyQn204kcnWOY6bpNW5smij4qvr14ZtvzA72IpdQ4SSSBX74wSxo1/qmrJPz718ptHgK+9v2ITk03HYcySL580PpGFiwwHaSLBATA08/bTbdfOEF22lErm7tWti2Ddq0sZ0kazVoAHFxPni2RtxBhZNIFli92mzdEhNjO4nvKj3hac4WKMqR+h1sR5EsFhsLP/3ko3vHNm4M99wDzz9vCigRTzVlipnKVr267SRZq3x5c8ZmzhzbScQDqXASyQIX1jcFBtpO4psif11B/rXfsL99PwgMsh1HstiF92lLl9rNkWXuuANatIA+fcwcXxFPc/48fPaZeZ76+h+2gAAzXU9tyeUKVDiJuFlyshlx0vqmLOI4lH7v35wqVp7j1ZvbTiPZIFcuM+3VJ6frgemC8cQTpg1nly5w6JDtRCKpLV4Mhw/7bje9SzVoAH/9ZboIilxEhZOIm/35p9kC4oYbbCfxTfm/n0Pkb9+zr+O95syg+IXYWNjyp9lY2ieFh5t1TidPQo8ecO6c7UQi/2/qVChRAsqWtZ0ke8TGmgYY6q4nl9C7DhE3W73anEBWK/IskJxMzAfPcqJsDU5UqG07jWSjG26A8DBYtMh2kixUqBAMG2Z2z374YdPFTMS206dh5kxo2dL8cfMHYWGmpacKJ7mECicRN1u9GsqUMc0hxL2ils8g17Zf2d/+bv/5Ay4ABAebtU7z5/t45+6qVWHgQHjvPRg3znYaEZg714yEtmplO0n2qlPHLFg+ccJ2EvEgKpxE3GzVKrUhzxJJSZT68DniK9YloXRV22nEgtq1Yf8B2LjRdpIs1rGjma73yCOwZIntNOLvpk6FihXNGjx/Uq+eaYqxeLHtJOJBVDiJuNHRo7B5s9Y3ZYVCi6aQc/cW9rW/23YUsaR0aSiQ34w6+bwHHoCaNaFnT7N3jogNx4+bzWBbtLCdJPsVKQLFi8O8ebaTiAdR4STiRt9/b/5VRz33cp1PpNTEoRyv1oTTJSrYjiOWBASYUafvvoMzZ2ynyWKBgfDcc2bOb+fOEB9vO5H4oy+/NI1K/LFwAjNd75tvtN5QUqhwEnGj1ashXz4oXNh2Et8S/e1HhB3Yyf52fW1HEctiY+HUaVi50naSbBARASNGwM6dZq+npCTbicTfTJkCNWqYjW/9Ud26ppXn5s22k4iHUOEk4karVplpeupb4D6uc2cpNekFjtdowZkipW3HEcuioqBMaT+aPVOihBl5+uYbePZZ22nEn+zfb3ad9tfRJjBFY2gofPut7STiIVQ4ibhJYiL88IPWN7lb4W8+IOTIPva3u8t2FPEQtWvD+vV+tE9svXrQvz+89BJMnmw7jfiLzz8382ObNrWdxJ7QUNPOU4WT/I8KJxE3+fVXOHVKhZM7BZw7Q8nJIzhWqyVnC5WwHUc8RI0aEBQECxfaTpKNbr4ZbrwR7r0X1q61nUb8wdSpZo1PZKTtJHbVqQPLl0NCgu0k4gFUOIm4yapVZq+Z8uVtJ/Ed0XM/IOTofg607WM7iniQ8HCz3dG8eX60ZtvlgkGDzAtM166wZ4/tROLLtm0zBbq/7d10JXXrmgYZ331nO4l4ABVOIm6yejVUqAAhIbaT+IaAc2coOWUEx2Jbc7ZgcdtxxMPUqQO7dsMff9hOko1CQuD5500R1aWLzoBL1vnsMwgLg4YNbSexr3hx05pc0/UEFU4ibrNypabpuVPhORMIOXqAA216244iHqhcOciX1/RM8Ct588Lw4abLV9++kJxsO5H4oilToFEjM7zr71wus7BShZOgwknELXbvhr17tX+TuwScO0OJKSM5GttGo01yRYGBZtRpyRI4fdp2mmxWtiw88wxMn25GoETcaeNG+P13TdO7WN26ZvriX3/ZTiKWqXAScYNVq8y/GnFyj8JzJhBy/BAH2t5pO4p4sHr1TNG0bJntJBY0bmwaRbzwgplWJeIun35q9hCrXdt2Es9Rq5bpSDN/vu0kYpkKJxE3WLUKihUzs2jk+gScO0OJqaM4Wqs156KK2o4jHixfPtMrYe5c20ksuf12aNMG+vWDdetspxFf4Dimm17TpqbbkRgXOtIsWGA7iVimwknEDS5sfCvXL/rbjwg5eoCDbW63HUW8QL16sHGTmS7rd1wuGDzYTN3r0kWd9uT6rVkDO3dqmt6VxMaaDYETE20nEYtUOIlcp5MnzR5OKpyunyvxHCWmjORYzZacLah9m+TaqlaFnDn8eN32xZ32OnVSpz25PlOnQlSU+cWS1GrXNn/w16yxnUQsslo4LV++nM6dO1OkSBFcLhezZs265m2+++47atWqRWhoKGXLlmXixIlZnlPkatatg6QkNYZwh+j5HxN6eC8H2txhO4p4ieBgs/xg3jzze+iX8uWDESPMwvU77lCnPcmc8+dh2jRo3tx0X5HUypUzmwFrup5fs1o4JSQkUL16dd5+++10XX/79u107NiRFi1asGHDBgYOHMi9997LfC3WE4tWrYLcuaFkSdtJvJvrfCIlJ4/gePXmnI0uZTuOeJH69eHoMfj+e9tJLCpdGp59FmbPNh33RDJq0SI4dAhat7adxDMFBJjpenrP6deCbB68ffv2tG/fPt3XHz9+PDExMYwZMwaASpUqsXLlSl5//XXatWuXVTFFrmrVKqhc2bymSuYVWjiZsAM72dFniO0o4mWKFoVSJU3N0Lix7TQWNWgADzwAL79sduPu1892IvEmU6aYM4DlytlO4rlq14bRo+HoUTPSK37Hq97qff/997S+5ExIu3bt+P4qpxnPnj1LfHx8qg8Rd0lONme5NU3v+riSzlPykxc5Xq0pZ4qUth1HvFDDhvDDD/DPP7aTWNazp1nr1L+/n/Zpl0xJSIAvvzRNIVwu22k8V+3apvPg4sW2k4glXlU47d+/n0KFCqW6rFChQsTHx3M6jR0QR40aRWRkZMpH8eLaTFPc5/ffIT5ehdP1iloyjfB92zjQprftKOKlatQwHYPnzLGdxDKXCx591Czuv+kmbdgp6TN7time1E3v6qKiICZG65z8mFcVTpnx9NNPExcXl/Kx2y971kpWWbXKrKGtUMF2Ei+WnEzJyS8Sd0MDThfTFBHJnJAQczJ47lx1CyYoCIYNM4svO3Y004pEruaTT8wZwCJFbCfxfBfWOTmO7SRigVcVTtHR0Rw4cCDVZQcOHCAiIoLw8PAr3iY0NJSIiIhUHyLusmqVmQ6extNP0iFqxUxy7trMgdYabZLr07AhxMXDihW2k3iA3Llh5Eg4eBB69IBz52wnEk916JAZQdFoU/rUrm02jvvzT9tJxAKvKpwaNGjA4kvmlS5cuJAGDRpYSiT+buVK7d90XRyHkpOGE1++NqdKVbadRrxcdDSULWNmHQmma8YLL5gXqn/9S2fI5co+/9xM8WzRwnYS71CtmtkHQdP1/JLVwunkyZNs2LCBDRs2AKbd+IYNG9i1axdgptn16dMn5fr/+te/2LZtG08++SSbN2/mnXfe4fPPP2fQoEE24ouf27cPtm/X+qbrkX/NXHJt+1X7NonbNGgAG36B//0ZkWrVYPBg+OgjeOUV22nEE02eDHXqmD2K5NrCw80awnnzbCcRC6wWTj/++CM1a9akZs2aADz22GPUrFmTIUNMO+J9+/alFFEAMTExzJ07l4ULF1K9enXGjBnD+++/r1bkYsWqVeZfFU6Z9L/RppOlq5FQprrtNOIjqlWDXDkhHfup+4927eDOO+Gpp2D6dNtpxJNs2wZr1miaXkbFxpqulZoC63es7uPUvHlznKtMHZg4ceIVb/Pzzz9nYSqR9Fm1yqyjLVDAdhLvlHf9YiI2r+Pv/q+o/a24TXCwGXWaNw/uuQdy5rSdyEP06wd795oCqnhxqFfPdiLxBFOmmBGUhg1tJ/EusbEwYYIpOps2tZ1GspFXrXES8SQrVmh90/UoOWk4CSUqcqJCbdtRxMc0agRnz5rGV/I/Lhf8+99Qtix07gw7dthOJLY5Dnz8sXnjrw5HGVOunJnauHCh7SSSzVQ4iWRCQgJs2KBpepkVsXEVeX5dzsHWd2i0SdwuTx4zZW/GDLNJtfxPSAgMH26G5Tp0gOPHbScSm77/Hv7+20zllIwJCIBatdQgwg+pcBLJhHXrICnJrA+VjCs5+UVOF44h7gZND5Gs0aQJ7P0HfvjBdhIPkycPjBoFe/ZAz57a9MqfffyxaUVZXWtMMyU2Fn78EY4ds51EspEKJ5FMWLnSbJNSsqTtJN4n15/ryb9uHgda3W7O2olkgZgYKF7MjDrJJUqUgOefN4vb1abcP505A9OmQevWeh3OrNhYM6S9dKntJJKN9NsikgkX9m/S35uMKzllJGcKFOV4De0ZIlnH5TKjTut+UGvyK6pZEx5/HD78EF5+2XYayW6zZ0NcHLRtazuJ94qONo1WtM7Jr+htn0gGJSWZqeFqDJFxOXb+QYEVMznY6jYIDLQdR3xczZqQOxd8+aXtJB7qxhuhTx94+mkz+iD+Y+JE80eseHHbSbyb1jn5HRVOIhm0aROcOKHGEJlRYsooEiOjOFZbZzkl6wUHmy7L335rTq7LFfTtC23awF13/f/mdOLb9u83b/Y12nT9atc2e2Ft3247iWQTFU4iGbRqFQQFQcWKtpN4l7B92ym0eCoHW/TCCQq2HUf8RJMmZhnCV1/ZTuKhXC4YPBgqVTJtyv/6y3YiyWpTp5p55i00Xfq61ahhZk9oup7fUOEkkkErV0L58hAWZjuJdyn+2SuczxnBkfodbUcRP5IrF9SpY5pEnD1rO42HCgmBF16AiAgzfe/QIduJJCtNnGiGYnPntp3E++XKZU46qHDyGyqcRDJIG99mXMjhfyj8zYccatoDJ0QVp2Sv5s0hPl4b4l5V7tymTfnx49ClC5w+bTuRZIX162HjRu3d5E61asGiRWYBtPg8FU4iGbBrl9n+pFo120m8S/EvXiM5OITDjbrajiJ+KCrK/M5Om6b3NldVuDC8+KLZ3fvOO7V7sC96/33zC1G3ru0kvqN2bXPCYf1620kkG6hwEsmAFSvMv2oMkX5BcUcoMns8hxt3Izk8l+044qdatDAb4qr/wTVUqgT/+Q/MnAlPPmk7jbjTqVMwZYqZjqmupu5TqRLkzKnpen5ChZNIBqxYYTa9zZPHdhLvUWzGG5CcxKGmPW1HET9WqhSULQOffqr9Xq+pcWMYMADGjIH//td2GnGX6dPNnNX27W0n8S1BQVC9utqS+wkVTiIZsGKFRpsyIjAhnqIz3+RI/U4k5Yq0HUf8XMuW8MdmzahJl+7doWdPePRRtST0FRMmmGllhQvbTuJ7YmNh9WpISLCdRLKYCieRdDpyBH7/XeubMqLI7HEEnkngUItetqOIUKkSlCgOH39sO4mXeOABM/p0222wdq3tNHI9tmwxLWE12pQ1ateGxERYvtx2EsliKpxE0unC2oiqVe3m8BYBZ09T/PMxHK3TjsQ8UbbjiOBymb1ef91o+h/INQQEwDPPQJky0KkT/P237USSWR98AJGRphAW9yteHAoW1DonP6DCSSSdVq40r4vR0baTeIfCc98nOO4IB1vdZjuKSIoqVaBoEZg0yXYSLxEaajrthYebFtba48n7nDtn9m5q08bs2SXu53KZ6Xpa5+TzVDiJpNPy5eZNl8tlO4nncyWeo8SnL3OsVkvOFShqO45ICpcL2raF9T/Dpk2203iJyEizx9PRo9C5s+nOJt5jzhxT8HboYDuJb6tdG377Dfbts51EspAKJ5F0OHUKfvpJjSHSq9DCyYQe3svBVrfbjiJymapVoUhhjTplSNGiMGIE/PKLWfOkDbG8xzvvmF3bY2JsJ/FttWqZfzVdz6epcBJJh3Xr4Px5NYZIl6QkSkwdxfGqTThTWH+oxfMEBEDr1rDuB3OCWNKpUiUYMgTmzoWHH1Zfd2+weTMsXgxdtfl4lsuTB8qXV+Hk41Q4iaTDihWQK5dO2KVHwWVfkGPvVg60ucN2FJE01ahh1jpNmKD3/xnSoAEMGgTjxsFLL9lOI9fyzjuQNy80a2Y7iX+oVcsUTnpR8VkqnETS4cL6pgD9xlyd41Bi8gjiK9bldPEKttOIpCkgwCz52PAL/Pij7TRepmNH6NPHdNzTfEfPdeKE6b3foYOaQmSX2rXhwAEtoPRhehsocg3nz8OaNWpDnh75V39Nru2bONBao03i+SpXhphSZtQpOdl2Gi/Tt695Q37PPTB/vu00ciWTJ8PJk9Cli+0k/qNqVdOJUtP1fJYKJ5Fr2LDB/O1R4XQNjkPJT4Zzskw1EspoMZh4PpfLDJ78+Zf2rcwwlwseewzq1IEePUz3HPEcjgP//S80amT20ZDsERJi3iyoLbnPUuEkcg3LlpkTSBUr2k7i2fL+uJCILT9yoHVv21FE0q1sWahUEd5/X43iMiwwEJ57DkqUgPbttUGuJ1m2DH7/XU0hbKhd25yJOXvWdhLJAiqcRK5h+XIzpSc42HYSz1Zy8osklKjEiQq1bUcRyZCOHWHPXvjmG9tJvFB4OIwcCWFhZoPcgwdtJxKAt9+GkiX/v0W2ZJ/ateH0aVi50nYSyQIqnESuIjnZFE7Vq9tO4tkif1lOnl9XmE562iFYvEyxYlA71ow6nTxpO40XypMHXn4Zjh83I08nTthO5N927YIvvzSjTXo9zn6lS0P+/Jqu56NUOIlcxaZN5r2A9m+6upKTX+R0kTLEV25gO4pIpnTqZE4ST5liO4mXKlzYtCffsgW6ddM0JZvGjoUcOeDGG20n8U8uF8TGwrx5tpNIFlDhJHIVy5dDUJCZqidXlnvzD+T7cSEHWt+ufu3itfLkgZYtYfp02LvXdhovVbYsjBhhpij16aNFYzYcP27aRHbpYqZRih21a8Ovv8L+/baTiJvpXY7IVSxbBpUqmeYQcmUlPxnOmYIlOF5dGyyKd2vZ0mx0/e67tpN4serVTcOI6dPhkUe0EWh2Gz/ejPZ17247iX+r/b+1vosW2c0hbqfCSSQNjmMKJ03TS1uurRsosPprDrS6DQICbccRuS4hIaZRxPIVZhsCyaTGjWHQIHjnHXj+edtp/MfZs2aaXtu2kC+f7TT+LW9eKF9ee5z5IBVOImnYsgUOHVLhdDUlP3mRswWKciy2te0oIm5Rq5bZFPeNN8zm15JJnTrBffeZwunNN22n8Q+TJ5uuhr162U4iYNY5LVig3bV9jAonkTQsX262KalSxXYSz5Rz+yails8wo02BQbbjiLhFQIDZz3XnTpgxw3YaL3fbbXDLLfDoo+q6kdWSk2H0aLPhbYkSttMImM2hDx40a53EZ6hwEknDsmVmpD1HDttJPFOJT0ZwNm80x2q3tR1FxK2KFYMmTeCjj+DAAdtpvJjLBf37mxbld90Fc+bYTuS75s410yRuucV2ErnghhvM/mZqS+5TVDiJXIHjwHffaZpeWsJ3baHgd9M42OpWnCDtDCy+58YbzXsezTK7Ti4XPP44NGwIPXvC0qW2E/kex4EXXzTTIzRFwnOEhECNGlrn5GNUOIlcwfbt8M8/KpzSUnLKSBIjC3C0XnvbUUSyRHi42Y5o1WpYtcp2Gi8XGAjPPgtVq0LnzrB2re1EvuWbb2DdOjOqJ56ldm3Tnj8hwXYScRMVTiJX8N135kRp1aq2k3iesL1/U2jRFA62uAUnKMR2HJEsU706VKpoGpXpfc91CgmBF16A0qXNcJ7WfbiH45j279WqmWYE4lnq1IFz58zcf/EJKpxErmDpUihXDnLntp3E85Sc/CLnc+XhSP1OtqOIZCmXC26+GeLjzfY4cp3Cw2HkSChYEFq3hs2bbSfyfl99BT//DP36mSeseJbixSE6WtP1fIgKJ5FLOA4sWWKmJktqYXv/JnrBJxxseStOiHYFFt+XL5+ZXfb1HPjpJ9tpfECuXPDyy+bfFi1g61bbibxXcrIZbapVS3+wPJXLZUadvvnGdhJxExVOIpfYutWsb9LfoctdGG063KCz7Sgi2aZhQyhX1rzfP3XKdhofkCcPvPqqmb7XsqXp/S4ZN2MGbNoEffvaTiJXU7eueWPx99+2k4gbqHASucTSpWYtsxpDpKbRJvFXAQFw660QF6cpe26TL58pnpKToXlz2LPHdiLvkpQEQ4aYN+VajOvZatWCoCCYN892EnEDFU4il1i61OzflDOn7SSeRaNN4s/y54dOnWD216aBmbhBVJQpns6cgWbNVDxlxEcfmTViGm3yfDlymOJW0/V8ggonkYtofdOVpYw2tbhFo03itxo1Ml32Ro6Eo0dtp/ER0dHw+utmDqSKp/SJi4NnnjENNipVsp1G0qNuXXNW9swZ20nkOqlwErnI5s1w8KAKp0uVnDyC87kiOdxQo03ivwIC4LbbzCypl182J1rEDVQ8ZcyLL8KJE3D//baTSHrVqwenT8Py5baTyHVS4SRykaVLzVRkTRn/f+F7/iJ6wSQOtrgVJyTMdhwRqyIiTPG0dh18+aXtND7k4uKpaVM1jEjLX3/BG2+YJ2FUlO00kl6lSpk2/N9+azuJXCcVTiIXWboUKlY0242IUfLjF0jMnY/DDbvYjiLiESpXhiaNTaMIddN2owvF07lz0LixKRIktcceMwvubrnFdhLJCLUl9xkqnET+JznZFE41a9pO4jly7PyDQouncLD1bVrbJHKRLl3MCf+hQ+HkSdtpfMiF4ikwEJo0gd9+s53Ic8yfD3PmQP/+EKrXY69Tty78+Sds3247iVwHFU4i//Pbb3DkiNY3XazUxGEk5inIkfodbUcR8SjBwaah2dGjMHq01ju5VVSUKZ5y5TLT9tavt53IvlOnYMAAqF7drAMT7xMbq7bkPkCFk8j/LF1q3gzdcIPtJJ4h57aNFPzuc/a36Y0TFGI7jojHiYoyS02WLYfp022n8TF588Jrr0GhQmafp6VLbSey69lnYfduM1XP5bKdRjIjZ06oUkXrnLycCieR/1m0yLymaQaEUeqjoZzNX4SjdW+0HUXEY1WrBi1bmPVOGzfaTuNjIiJgzBioUAFuvBFmzrSdyI5Vq2DsWLj7bihRwnYauR5168LixWpL7sVUOIkAiYnw3Xdmg2+BXH+uJ2rllxxoeycEBtmOI+LROnY0TbOGDIFDh2yn8THh4WbjrEaN4Oab4b33bCfKXqdOmTmhN9wAPXrYTiPXq35985guW2Y7iWSSCicR4IcfzLYYsbG2k3iGmPef4UyhEhyNbWM7iojHCww0721dLvjPf+DsWduJfExwsJmq1rWraYzwzDOmm48/eO452LULnnjCPNHEu5UqBYULw9df204imaTCSQQzTS9XLihf3nYS+yJ/WU7+H+az78Z++kMtkk65c8M998COHfDKK2oW4XYBAfDww/Cvf8GoUXD77b4/3WnpUtMkQ1P0fIfLZUadvv5aLxJeSoWTCLBggWlD7vd1guNQesLTnCpWnrhqTW2nEfEqRYua9/OLl8DUqbbT+CCXy+xfNGwYzJoFLVv67tzI3buhVy8zf7xnT9tpxJ3q1zejiJs22U4imaDCSfzeiROwdq2m6QHkW/MNkb+tZl+He8wZXhHJkBo1oG0bmPC+WTcpWaBZM9Nxb8sWqF0bNmywnci9zp4165kCA80URb8/o+djatQwa/fmzLGdRDJB74zE7y1fDufPq3AiOZnS7z/DiTLVOVGxju00Il6rfXuIrWV6GuikchapXBneeQfCwqBhQ/jsM9uJ3OfRR+GXX+D55yFPHttpxN1CQkzBr3VOXkmFk/i9RYvMZvVFi9pOYlfB7z4n17Zf2d/hHu0TInIdXC649VYoXtw0i9i713YiH1WoELz5JjRubDbUevJJcxbMm33wAbz7LjzyiGnDLr6pfn1Ys8Z3p5r6MBVO4vcurG/y51rBdT6RUh88S1zlBiSUrmo7jojXCw6Gfv3MgMi//w1xcbYT+ajQUHj6aXjwQTN9r2lTs37EG82ebZpfdO5setyL76pf3zSH0Ga4XkeFk/i1ffvg99/NqLk/K/z1e4Tv28a+jvfYjiLiM3Llgnvvhfh4UzydPm07kY9yucweT2PHwvbtUL26aR7hTRYuNN9Do0Zmqp74tnz5oFIlTdfzQiqcxK8tXmz+rVnTbg6bAk+doNTHwzhauy1nipSxHUfEp0RFwX33mTblQ4d6/0wyj1alipnmVqUK3HQTPPCA6f7j6VasMHtU1apl5naqGYR/aNAA5s+Hc+dsJ5EMUOEkfm3RIihbFvLmtZ3EnuLTXiUoIZ797fvZjiLik4oXN9P2fvoJXn7Zf/ZutSIiAl54AQYOhI8/NkXUhTNknmj5cjMtr2JF02Y9ONh2IskuDRqYwn7FCttJJANUOInfchyYN8+/u+mFHN1P8c/HcKjJTSTmLWQ7jojPqlABevc2J2veeUd7X2Ypl8uM4Lz/PuTPD61bm7VDx47ZTpbahx+abGXLwogRZr2W+I8yZaBgQbO2TbyGCifxW7/8AgcOQN26tpPYU/Lj53ECAjnY+g7bUUR8Xs2aZi/T6TPMYIhksSJF4NVXzejTJ5+YAuXddyEpyW6upCR44gm45x5o2xZeecXs6yP+xeUya9pmztSZFC+iwkn81rx55m9VlSq2k9gRvmsLReZM4EDr20nKkdt2HBG/0KgRdO4EEz+GL76wncYPBASY0adJk6BOHTPyFBsLS5bYebO6e7eZmvfaa/DQQ/D44xAUlP05xDM0bgx79ph5vOIVVDiJ3/rmG7MWNyTEdhI7yrz7BOfyRHG48U22o4j4lVatoHUrePsdmDvXdho/kT8/PPUUvP22WYzfqhU0aWLmTmZHAZWUBG+9ZTbu/eknGDXKDD/68z4YYjpARkbCl1/aTiLppMJJ/FJcHHz/vTkB6Y/yrF9CgdVfs6/TfTjBflo5iljUsSM0bmRmki1caDuNH6lc2RRPI0fCkSPQpg00bAhTp8KZM+4/nuOYBhANG5o2461awUcf+fcccfl/gYFmT6eZM20nkXRS4SR+afFi0xbYL/92JSVR9u1BnCxVheM1WthOI+KXXC7o3h3q1TODD8uW2U7kR1wu09HsnXdMm8MzZ+COO8yaqIEDzYjQ9bY+TEw0xVjt2tCsGRw9Cm++ae4/Vy53fBfiKxo3hs2bYcsW20kkHVQ4iV+aNw9KlIDChW0nyX7R8yaSa9uv/NP1AU0TEbEoIMDseVqzpumgvXq17UR+xuUyZ89ef92sgWrb1vxbu7b549CvH0ybBlu3pq+hxL59pgnFnXdC0aKmGAsKMs0f3nvPfxfUytXVqQNhYZqu5yVcjmO/lcfbb7/N6NGj2b9/P9WrV+ett96ibhpDARMnTqRfv9T7zYSGhnImnUPs8fHxREZGEhcXR0RExHVnF+/jOKZoql/frM31J4GnTlC3dzkSYqqw685nbccREcx78kmT4PffTVdqvxwJ9xSJibBpE6xdCz/8ANu2mctDQ01P+VKlTFehsDCzQPbgQdi1yyzwP3TIXLd8ebOAtm1biImx9q2IFxk6FE6dMs85yXYZqQ2st3KZNm0ajz32GOPHj6devXqMHTuWdu3asWXLFgoWLHjF20RERLDloiFNl86aSwb8/rv5G+eP65tKfPoywSePs6/TfbajiMj/BAaaQYqJE+HZZ83UPX/eX86q4GAzBFizpunAd/QobN8OO3bAzp2mUEpMNA0mEhPNhrtFikCNGlCsmLmdP++oLpnTuLFZd7dnj3keiceyXji99tpr3HfffSmjSOPHj2fu3Ll8+OGHPPXUU1e8jcvlIjo6Ojtjig+ZN8+cLKxRw3aS7BW2fwfFPh/DwWY9tdmtiIcJCoK77jJ9A555xiy98bfXKI+UL5/5UCUrWalBA/MiMGsWDBhgO41chdU1TufOneOnn36idevWKZcFBATQunVrvv/++zRvd/LkSUqWLEnx4sXp2rUrv/32W5rXPXv2LPHx8ak+xL99843pAOpvbcjLvD2IpBy5tdmtiIcKDjbLakqVgqefhl9/tZ1IRLJFrlxmtFLd9Tye1cLp8OHDJCUlUahQ6rPfhQoVYv/+/Ve8TYUKFfjwww/56quvmDx5MsnJyTRs2JA9e/Zc8fqjRo0iMjIy5aN48eJu/z7Ee5w4AStX+t80vbw/LiRq5Sz+6dyf5FDtUC/iqYKD4Z57oHhx+Pe/zXIbEfEDjRub1vWHD9tOIlfhdV31GjRoQJ8+fahRowbNmjVj5syZREVF8e67717x+k8//TRxcXEpH7t3787mxOJJFiwwU9MbNrSdJPu4Es9R9s2HOVGmOsdrtrQdR0SuISTEFE9Fi8KTT5p1mSLi45o0Md2rNOrk0awWTgUKFCAwMJADBw6kuvzAgQPpXsMUHBxMzZo12bp16xW/HhoaSkRERKoP8V+zZ0Pp0v7Vhrzol2+RY89f7L1pgNqPi3iJ0FC47z7zWvXEE2abFxHxYXnzmm6Mn35qO4lchdXCKSQkhNjYWBYvXpxyWXJyMosXL6ZBgwbpuo+kpCQ2btxIYX96JyyZkpQEc+aYNZj+IuTIPkpNfJ7DjbpwpmhZ23FEJAMuFE8FC8LgwdofU8TnNW9udsPet892EkmD9al6jz32GBMmTODjjz/mjz/+4IEHHiAhISGly16fPn14+umnU67/wgsvsGDBArZt28b69evp3bs3O3fu5N5777X1LYiX+P5701nWn6bplR7/JAQEsP/Gfte+soh4nLAwuP9+KFAAHn8c/vrLdiIRyTJNmpj9CaZPt51E0mC9cLrlllt49dVXGTJkCDVq1GDDhg3MmzcvpWHErl272HdR5X3s2DHuu+8+KlWqRIcOHYiPj2f16tVUrlzZ1rcgXmL2bNNVtmJF20myR571S4heNJl/OvcnKaemqIp4q/Bw6N8f8ueHxx6DNGami4i3i4gw3as0Xc9juRzHcWyHyE4Z2R1YfEuFClC2rFkv4Otc585S556qJIeGs/XB1yHA+jkSEblOp0/DuHEQFwdjx0JMjO1EIuJ2CxeazXB37oQSJWyn8QsZqQ30bkr8wpYt8Oef/jNNr8RnrxC2bzt7egxU0STiIy6MPOXKBYMGmfdVIuJjGjY0rTU//9x2ErkCvaMSv/D112ahtT9s/h6+dyslJ4/gUPNenCmsU9IiviRnTnjgAciRwxRPu3bZTiQibpUzJ9SvD599ZjuJXIEKJ/ELs2eboikszHaSLOY4lHvjIRIj8rG/7Z2204hIFsiVyxRPISGmeNq713YiEXGrFi3gp5+0oNEDqXASn3fkCKxa5R9tyAstmkK+Hxaw96aHcUJ8vUoU8V+5c5viKTDQFE/799tOJCJuU7++mZs7bZrtJHIJFU7i82bPNptx+/r6puBjByn71iMcrdWK+Bv8oEoU8XORkfDgg+b1beBAOHTIdiIRcYuwMGjUCCZNMr/g4jFUOInP++ILqFbNtCL3ZeXeegRXcjJ7bxpgO4qIZJM8eczI07lzpng6csR2IhFxi3btTFerdetsJ5GLqHASn3b8OCxaBE2b2k6StfKv/IqCS6ex56YBJOXKYzuOiGSjfPnMyFNCgtnn6fhx24lE5LrVrAkFC8LEibaTyEVUOIlPmz0bEhN9u3AKOnmc8mMfIK5yA47XamU7johYUKCAGXk6dgwGD4YTJ2wnEpHrEhgIrVubzXDPnLGdRv5HhZP4tM8/h6pVzZsKX1XmnccISohnT8+B4HLZjiMilhQqZIqn/ftN8ZSQYDuRiFyXdu3MjtezZ9tOIv+jwkl8Vlyc2YDbl0eb8q/+msLffsTerg+QmLeg7TgiYlnhwmaT3F274Kmn4PRp24lEJNNKlIAbbtB0PQ+iwkl81tdfmwXTzZrZTpI1guMOU+HVe4mr3ICj9TrYjiMiHqJ4cVM8/fUXPPuseR0UES/Vti3Mnw/79tlOIqhwEh/2xRdQpQpERdlOkgUch3KvPUDAubPs7vW4puiJSCqlSsG998LGjTBkiFnrKSJeqGVLCAqCKVNsJxFUOImPio83J2iaNLGdJGsUXPwpBZdPZ0+PRzkfmd92HBHxQGXLQr9+8OOP8OKLkJRkO5GIZFiuXGZPp48+0p5OHkCFk/ikOXPg7FnfnKYXenA35cY+xLGaLTles4XtOCLiwSpVgrvugpUr4eWXITnZdiIRybAbb4Tff9eeTh5AhZP4pMmTzTS9QoVsJ3GzpCQqjbgDJziEPT0etZ1GRLxA1apwxx2mWc7YsTppLeJ1YmMhOhrGjbOdxO+pcBKfc+AALFhgtj/wNSWnjCRy4yp29n6GpJwRtuOIiJeoVQtuvRVmfw3vvKPiScSrBAZC584wbRocOWI7jV9T4SQ+57PPTK+E5s1tJ3GviI2rKPXxMA606U1Cmeq244iIl6lXD3r2gC+mw4cf2k4jIhnSvj2cP6/W5JapcBKfM2mSeYMQGWk7ifsEnTxO5RdvI6HkDexv28d2HBHxUo0bQ5fO8MlkNekS8Sp585ozwuPGabGiRSqcxKf88QesXw9t2thO4kaOQ4VX7iHo5HF29n7GDNmLiGRSy5ZwYzuY8D5Mn247jYikW5cu8PffsHix7SR+S4WT+JRPPoHcuaFBA9tJ3KfYF68TtWImu299ksR80bbjiIgPaNcOWraA/75tNgsXES9QpQqUKWMWKooVKpzEZyQnm256zZpBSIjtNO4R+esKyrz7JAda3EJc1ca244iIj3C5zFrzJo3htddg3jzbiUTkmi784s6eDXv22E7jl1Q4ic9Yvhx274a2bW0ncY+Qo/up/HwvTsZUYV/H+2zHEREf43LBTTdB/frwyiuwZIntRCJyTW3aQFgYvPuu7SR+SYWT+IxPPoHCheGGG2wnuX6upPNUeuFWAs6fY+edz2ldk4hkiYAA6NnTbBMzYoQ5ASUiHixHDjPXdtw4OHXKdhq/o8JJfEJcnGlD3q6deSPg7UqPf4I8G1ey487nOB+Z33YcEfFhgYFmj6fq1eH552HVKtuJROSqbr4Zjh1Ta3ILfOAtpohpq3v2LHToYDvJ9Yv+5kOKTx/L3pseIqFsDdtxRMQPBAbCHXeYtedDh8KaNbYTiUiaChc2rclffdXs7STZRoWTeD3HMSPWDRpAVJTtNNcnYuMqyr/+Lw436MThRt1sxxERPxIYCHfeCZUqwZAhsG6d7UQikqZbboHt22HmTNtJ/IoKJ/F6a9bApk2m0Yw3Cz2wiypDbuJUyUrs7f6IWbktIpKNgoKgTx8oVw6efVbFk4jHKl8eateGl182Z5AlW6hwEq83frwZta5d23aSzAtMiKfqM51xAgLZ3vd5nKBg25FExE8FB0PfviqeRDzeLbfA+vWwdKntJH5DhZN4taNH4fPPoVMn720K4TqfyA1DexC2bxvb7x1JUq48tiOJiJ9T8STiBWJjzS/pyy/bTuI3vPStpogxaZJZF3njjbaTZNL/tXfnYVGV7R/Av8MyA7K6sQmCiqgoSVIo7paGhaavlUvmlmapmbmjZWhmmmmZxS+zBbVyN31LfU0jTUPcUNIUAUVwAxURZV9mnt8fT4yNsogCh4Hv57rOBXPmLPecB2bOPc8mBLyWjoV99D4kjpqHXOcmSkdERATgbvLk5QW88w5H2yOqdlQqYOBAYPduWfNElY6JExktnU420+vSBahXT+loHo77mvfhvGsVLg2egczm7ZQOh4jIQFHy5O0tB4z44w+lIyIiAz16AI0by6phqnRMnMho7dwJxMYC/fsrHcnDcf5lJZqsmovk50bj1hO9lA6HiKhYRQNG+PrKeZ727FE6IiLSMzUFRowA/vc/4OBBpaOp8Zg4kdFavFh+C+rjo3Qk5ecQvg5en76BG53/g2s9hyodDhFRqUxNgZdfBvz9gQ8/BP77X6UjIiK97t2BZs2A2bM5wl4lY+JERunIEeDAAdm019hG7a4fuR0tFw5Hmt8zuPKfN43vBRBRrWRqKt9zu3YFPl0G/PAD79GIqgUTE+DVV2Vb2vBwpaOp0Zg4kVFasgRwdQU6d1Y6kvKxP7EXrUNexB3vAFwaPN14hwIkolrJxEQ2j362N/DNt7KfqU6ndFREhIAA2Qxn1ix+o1GJeNdGRichAdiyBXjxRfkNqLGwi/4DPrP6ILOpD5KGv2tcwRMR/UOlAgIDgQH/kdNBLFwIFBQoHRVRLadSyVqnY8eAn39WOpoai4kTGZ1PPgFsbY1rCHL7E3vxWPBzyHL3xoVX50OYqZUOiYjokXTtKvuk790LzJwJZGYqHRFRLefnB7RrBwQH89uMSsLEiYzKjRvAd9/JpiIajdLRPBj7qHD4BAchy6M1Loz+AEJtoXRIREQVwtcXeOMN4OxZ4K235Hs0ESlo3DggLg5YvlzpSGokJk5kVBYtutvG3hjUO/w/+Mzug6ymPv8kTUaS7RERPSBPT2DiRCA9HXj9deDMGaUjIqrFPD2Bfv2AuXOBq1eVjqbGYeJERuPyZSA0FHjpJcDOTuloyuaw50e0eed5ZDZvJ5vnmbN5HhHVTM7OwNtvy/fmt9/mwF5Eiho1Ss5ePWOG0pHUOEycyGjMnw9YWsrEqbprtGU5vD98BbfaPY0Lo95n0kRENZ6tLTB+PNC2LTD/A2DlSkCrVToqolrIxgYYMwb48Udg/36lo6lRmDiRUTh3Dvj2W2DIEKBOHaWjKYUQaPLtu2j+xSRc7z4QlwbP4Oh5RFRrmJvLiXKf7wts2ABMnQqkpSkdFVEt1Lu3HJ58wgSgsFDpaGoMJk5kFEJCgHr1ZLPd6sokPxetPhgK9x8W4GqfsbjabxznaSKiWkelAp56SvZRT0gAXnsNOHVK6aiIahkTEzliy+nTwMcfKx1NjaESonbNknXnzh3Y2dnh9u3bsLW1VTocegAnT8qRmyZPBvr2VTqa4pnfuo42c/rDJu44Lg6ZifTHeygdEhGR4m7fBtasAS5cAIYNA4YPZyV8TZCbK/sdX7wIXLoEXL8O3LwJpKYCGRny+dxcWdFhbi7LXKORfeDq1ZOLmxvg7i4XNzf+XVSar76Sk18ePSrb0dJ9ypMbMHGiak0IoFs3IClJNtUzM1M6ovtZXfgbbWb3hVn2HVx4dT6y3b2VDomIqNrQaoE9e+Ti5QW8+y7QqJHSUdGDyssDYmOBmBg5ynVcnEyaim4ebayBunVlUmRjA1hZAWq1XExNZflrtUB+vpzrKzNTJtQ3bgCZWfIYlhayVZmPj/yi1MeHiVSFyc+XnQ8tLeXkuMYyl0sVYuJUCiZOxuX77+U3lEuWyHndqpuGv29Ay8WvIr++MxJGf4CCek5Kh0REVC0lJsq+6hkZwKuvAi+8wJvj6igzUzatjI6WLT7i44FCLaA2lwmvq6v86eQEODg8Wr/jzEwgJUV+OXrhglyysgFrKyAgAOjUSf7kvf4jOndOtp2dMgX46COlo6l2mDiVgomT8UhPl99O+vgAc+YoHY0hVWEBmn41E26bP0Vau564PHAKdBpLpcMiIqrWcnOBnTuBAweA5s3laMmenkpHVbvl5QF//w1ERcklPh7QCaCuPdCkyd3F2bnyE12dTtZm/f237Jpz5SpgVQfo3h0IDJT3AypV5cZQY61bB3z9tRxlr3NnpaOpVpg4lYKJk/F4801g1Sq5NGigdDR3aa5fQqsPXobtmUO4+vwbSO0ygO/kRETlkJgIbNwIXLsm+66OHAnY2yscVC2h1cqmd8ePy5ZbZ84A+QWArY1MYps3lz8bNFD+o+3GDdk1JyoKuJkGuDcGBgwAnnlGtjyjctBqZWfx27flBa1ON1YKY+JUCiZOxiEqCnjySdks98UXlY7mrgYHtqLF4lchzNRIGvYuspr6KB0SEZFR0mrll9+7d8sBwF55RTbfU3Pauwql1crRDaOjZbJ08qRsDmdpATRtKlt2eHnJpndKJ0ol0elka7OICNmM0NJSJtwvvQTUr690dEbk2jXZZK9tW9npsDp2HFcAE6dSMHGq/nJzZdKUmwusWFE92sCb5GbD8/+mwOWXr5D+WFdcGjgVWiv+/RARParMTODXX4GDB+UAA4MGAc8/zxqFh5WTA5w9K5u6nTwpf2Zlyz5KHh53a5QaN64en6/llZYG/PknEBkpk8LeveUcj87OSkdmJKKjgenTZbOeTz9VOppqgYlTKZg4VX+TJsmE6csv5bdhSrM7eQAtPhoFTeoVXOk/AWkdgqrv13JEREbqxg0gPFw2zbKyAv7zH6BPH6BhQ6Ujq76ys+WACnFxsm9SbKx8rBOyRsnDQ36ONm0qEyVzc6Ujrjg5OTKB2r9fXofnnpO1lo6OSkdmBLZuBZYvB1avliNw1XJMnErBxKl627FDflBOnCjbMSvJJCcLTb+ehUbbvkBWkza4NGg68hzclA2KiKiGS0sD9u6VCVR+vhxVrU8f4IknataN/4PSauUcSVeuyIETiuZPSkgArl2X25iayJHuGjWSCZKHhxzxzhhrlMorP18mUL//Lge66NNHzhlWr57SkVVjQsjhisPD5T9bQIDSESmKiVMpmDhVXykpcsQcT0/gww+VrdSpd2gnmn82Aeq0FKQ8Nxo3uvwHMKkFn0BERNVEbq7s73rwoBxdzdpKDgbWrZuc68fYm/JptbKZ4q1bd5e0NDmJbGqqrIG7dk3+1OrkPiYq2aenYUPZJ8nJSTZRc3Zmd5XcXDla4969Mi8YOFAuVlZKR1ZN5efLJntJScC+ffKfqpZi4lQKJk7VU2Eh8OyzsuPqN9/IyfSUoElJgucXk9Aw4r+44/UELr84CfkNXZUJhoiIIARw9erdeYWuXQfMTIFWreT8fq1ayX47StYw5OUBd+7IAcsyMuTvxS23b8ul6PG9N2Bqc9nPy84OsLWVn4V168rXVr++XGp7glSW7Gzgt99kLZSlpRyxsW9fXrdiZWbK5Ck1VWadLVsqHZEimDiVgolT9SMEMGECsHKlnJdNiYluTXKy4LbpEzT+cSG0lta42m8c0n27sy8TEVE1IgRw/frdPj3nz8uBDwCgfj3ZRM3FRdbAODjIIc7t7QEbG8DCQk6kqlbLUfyKjldYCBQUyCU3V9545+TIn5mZd5c7d0pOivLy74/VRCUnh7Wykj8tLQFr67vrrK3lYmUl47O2ljHyY6dipKcDu3YBhw/Lv4mxY4GuXXl973P7tpwYt6jTWHXoXF7FmDiVgolT9fPpp/J/dupU2Ta5Smm1cNq1Ck2+exfmd27iRpcBuPbMcOgsHmEqdCIiqhJCyP4/ly/LPkA3bsjHqalATm7FncfSwjAB+ndCVNxPKyuZBBUlaKScq1eBX34BYs4Crb3lNCetWysdVTWTliZH5lKp5BCXrVopHVGVYuJUCiZO1cu2bXIQiMGD5bdBVUanQ4M/t8Ej7D1YJ55GWrunkfLcaOTX53imRETGTgjZfC4r6+5SVKuUf0/tkKmpbMZlbi5/FtVMWVjIJEmtrh2DLNR0sbEygbp8BejWVd5zNGqkdFTVyI0bwMyZsrPdzz8DXbooHVGVYeJUCiZO1cdvv8m5Otq3B+bMqaJv5ooSptVzYZ1wChlefrgaNAY5jWtnu14iIqLaQqcDjh0D/vc/2cSyb185GjdH4PtHZibw3nty8q81a+SkarUAE6dSMHGqHn75Rc747esLzJsnv92rTKr8PDiGr4XbhiWwSjqDDC8/pDwzHFnNHqvcExMREVG1kp8vx0IID787At9LL8l+ZrVeQQGweLH8dvu99+Q32zV8ZA0mTqVg4qS8jRuBoUOBjh2Bd9+t3Hk5zNNvwHnHN2j003Jo0lJwu3VHXH9qMLKa+lTeSYmIiKjay8qSydOff8ovcIcMkRMvG/tQ949MCOCHH4BVq+TN2o8/ygnCaigmTqVg4qQcIYBly4Bp04Cnn5ZNaSul3bgQsDv1J1x+XoGGf2wGAKQ90Qs3ug9EnmPN/ccnIiKi8ktPlxUskZFyGPjBg2VXglqfQJ06BSxYIDsMfvMN8MILSkdUKZg4lYKJkzLu3AFGjwY2b5ZvSK+9VvF9mjTXLsLxtx/h+OtqWF2KRW5DV9wM6Iu0JwOhtbar2JMRERFRjZKWBuzZAxw5IkdGfOkloH9/OVx8rZWRASxZAuzfL4c+/uyzGjdkOROnUjBxqnp//SXffJKTgRkzKnagFvO0a2j451Y03LsB9n/9AZ25BrfbdEaaf29kNn+cY8ESERFRuaSlAb//LueAMjMDnn1WVrbU2lH4hJCJ05dfyuq5mTPlUqdmTN3CxKkUTJyqTkYGMHeu/HLCw0P+7ur66Me1vHIO9SJ3oOGBn2B36gCgMkGmpy9u+fVE+mNdOQcTERERPbI7d4CICLlkZQEdOgD9+gFPPllLh6jPyQHWrgU2bJAzS0+bBowbZ/RVckycSsHEqfJptcCmTXJC27Q0YNgwWeP0sINAmGbehv2pA6gb9RvqHdqBOlfOQWdmjkzPx5Hetitut+nMpnhERERUKfLzgago4OBB4NJlwKEhEBQE9OxZS2uhkpNlArVrlxyKcNIk2QfDSC8GE6dSMHGqPAUFwLp1sh9hXJwciGXiRMDJqXzHMb91HbanI2F3+iDso/fCJi4KKp0O+XUdcaelP+54t0dm83bQaWp7r00iIiKqKkIAFy/KBOqvv4DcPMC7lUygOncGHByUjrCK3bgha5927JDZZe/ewJgxsi9UZQ6ZXMGYOJWCiVPFO39ezpMWFgZcuiQTpqFDAW/vsvc1u30T1ueiYRN/HNbxx2EbcwSWyQkAgHy7hshq5oMMz8eR2fxx5Nd3AVSqSn41RERERKXLzwf+/lvWRJ09C2h1QHNPoFMnwN8faNGiFjXny8qSncL+9z8gJkYOTRgUJNs1PvusfFyNGV3iFBoaio8//hgpKSlo27YtPv/8c/j7+5e4/aZNmzBnzhwkJiaiefPm+Oijj/Dcc8890LmYOD06IeSk0rt2Adu2yba/VlZA167AgAGAp+c9O+h00KRegeWlONS5Eo86F8+izoW/YX3hb6hvXQMAaDWWyGnUHDmNPJHVpDWyPFqjwN6BiRIRERFVazk5wJkz8t4oJgbIyQWs6gBt28qlVSvAywuwsFA60iqQkCAHkjh4EIiPl6Nr+PkB3brJG8UOHYD69ZWO0oBRJU4bNmzA8OHDsWLFCrRv3x7Lli3Dpk2bEBsbC4di6jwPHjyIrl27YuHChejTpw/Wrl2Ljz76CMePH0ebNm3KPB8Tp/LLzJRV0keOAEePAn/8AVy9Kt8AHvcVCApIQ9cW12CbcQWa1CtQp16BxfVLsEi5AIvkRGiuX4Rpfi4AQJiYIq9BI+Q6uiPXyQO5Th7IcfVEXoNGgElt+WqGiIiIaiKtVra+iY+X3RaSkoD8AsDURA6U1bQp0KwZ0KSJHDDL0VHmFjVSSoocmvDkSbmkpsr1rq5Au3ZylI2pUxWfMMuoEqf27dvjySefxBdffAEA0Ol0cHNzw8SJExEcHHzf9oMGDUJWVha2b9+uX9ehQwf4+vpixYoVZZ6PiZOhguwCpF3Oxq3LWbh1JRs3kzJx62IG7lzJwK2LGci4fBsiPR32SEd9k3S4W99EI00qHM1SYZt3A+rbN2CiLTQ8ppUdCuo6IL+uI/LrOcmfDRoh18EN+fWcANOa+g5BREREdJdWK/OHxETg8mX5e3Ky7B8FyITK0VH2j3J0BBo2lBUy9vZA3bqAnZ0cf8HaWn5hbbQNcYSQ37rHxgLnzsmquehoWTtVkfPUPITy5AaK3sHm5+cjKioKs2bN0q8zMTFBz549ERkZWew+kZGRmDJlisG6wMBAbNu2rdjt8/LykJeXp398+/ZtAPIiVQuHDwOjRgFXrigWguU/i0tZG+oA/Ouy5cAUqRp75NSxR5baHlkW9ZGtqYdClVpukP3PcjkDwNl/FiIiIqLawwRA038WmAJwBXLygOwsICcbyE4GkCy3zfpnuVhB5+4UAHg1r6CDVRRzc1n9Fh0t565R+J68KCd4kLokRROn1NRUaLVaODo6Gqx3dHTE2bPF32SnpKQUu31KSkqx2y9cuBDz5s27b72bm9tDRk13aYG8m3IhIiIiouol8p+lugoKUjoCvYyMDNjZlT69TY1vMzVr1iyDGiqdToe0tDTUr18fKqOt73w4d+7cgZubGy5dusRmikaKZVgzsByNH8vQ+LEMjR/L0PhVhzIUQiAjIwMuLmW2vVI2cWrQoAFMTU1x7do1g/XXrl2DUwmT/zg5OZVre41GA41GY7DO3t7+4YOuAWxtbfkGY+RYhjUDy9H4sQyNH8vQ+LEMjZ/SZVhWTVMRk0qOo1RqtRp+fn4IDw/Xr9PpdAgPD0dAQECx+wQEBBhsDwB79uwpcXsiIiIiIqJHpXhTvSlTpmDEiBF44okn4O/vj2XLliErKwujRo0CAAwfPhyNGjXCwoULAQCTJk1Ct27dsHTpUgQFBWH9+vU4duwYVq5cqeTLICIiIiKiGkzxxGnQoEG4ceMG3nvvPaSkpMDX1xe7du3SDwBx8eJFmJjcrRjr2LEj1q5di3fffRezZ89G8+bNsW3btgeaw6m202g0CAkJua/pIhkPlmHNwHI0fixD48cyNH4sQ+NnbGWo+DxORERERERE1Z2ifZyIiIiIiIiMARMnIiIiIiKiMjBxIiIiIiIiKgMTJyIiIiIiojIwcaphQkND4eHhAQsLC7Rv3x5HjhwpdftNmzahZcuWsLCwgI+PD3bu3FlFkVJJylOGX3/9Nbp06YK6deuibt266NmzZ5llTpWvvP+HRdavXw+VSoX+/ftXboD0QMpbjunp6ZgwYQKcnZ2h0Wjg5eXF91SFlbcMly1bhhYtWsDS0hJubm6YPHkycnNzqyhautf+/fvRt29fuLi4QKVSYdu2bWXus2/fPrRr1w4ajQaenp5YtWpVpcdJJStvGf7000/o1asXGjZsCFtbWwQEBODXX3+tmmAfABOnGmTDhg2YMmUKQkJCcPz4cbRt2xaBgYG4fv16sdsfPHgQQ4YMwejRo3HixAn0798f/fv3x99//13FkVOR8pbhvn37MGTIEOzduxeRkZFwc3PDM888gytXrlRx5FSkvGVYJDExEdOmTUOXLl2qKFIqTXnLMT8/H7169UJiYiI2b96M2NhYfP3112jUqFEVR05FyluGa9euRXBwMEJCQhATE4Nvv/0WGzZswOzZs6s4ciqSlZWFtm3bIjQ09IG2v3DhAoKCgtCjRw9ER0fj7bffxpgxY6rVjXdtU94y3L9/P3r16oWdO3ciKioKPXr0QN++fXHixIlKjvQBCaox/P39xYQJE/SPtVqtcHFxEQsXLix2+4EDB4qgoCCDde3btxevv/56pcZJJStvGd6rsLBQ2NjYiNWrV1dWiFSGhynDwsJC0bFjR/HNN9+IESNGiH79+lVBpFSa8pbjl19+KZo2bSry8/OrKkQqQ3nLcMKECeKpp54yWDdlyhTRqVOnSo2THgwAsXXr1lK3mTFjhmjdurXBukGDBonAwMBKjIwe1IOUYXG8vb3FvHnzKj6gh8AapxoiPz8fUVFR6Nmzp36diYkJevbsicjIyGL3iYyMNNgeAAIDA0vcnirXw5ThvbKzs1FQUIB69epVVphUioctw/fffx8ODg4YPXp0VYRJZXiYcvz5558REBCACRMmwNHREW3atMGHH34IrVZbVWHTvzxMGXbs2BFRUVH65nwJCQnYuXMnnnvuuSqJmR4d72tqHp1Oh4yMjGpzX2OmdABUMVJTU6HVauHo6Giw3tHREWfPni12n5SUlGK3T0lJqbQ4qWQPU4b3mjlzJlxcXO774KCq8TBl+Oeff+Lbb79FdHR0FURID+JhyjEhIQG///47hg4dip07d+LcuXMYP348CgoKEBISUhVh0788TBm+/PLLSE1NRefOnSGEQGFhId544w021TMiJd3X3LlzBzk5ObC0tFQoMnpYS5YsQWZmJgYOHKh0KADYx4moxli0aBHWr1+PrVu3wsLCQulw6AFkZGRg2LBh+Prrr9GgQQOlw6FHoNPp4ODggJUrV8LPzw+DBg3CO++8gxUrVigdGj2gffv24cMPP8T//d//4fjx4/jpp5+wY8cOzJ8/X+nQiGqltWvXYt68edi4cSMcHByUDgcAa5xqjAYNGsDU1BTXrl0zWH/t2jU4OTkVu4+Tk1O5tqfK9TBlWGTJkiVYtGgRfvvtNzz22GOVGSaVorxleP78eSQmJqJv3776dTqdDgBgZmaG2NhYNGvWrHKDpvs8zP+is7MzzM3NYWpqql/XqlUrpKSkID8/H2q1ulJjJkMPU4Zz5szBsGHDMGbMGACAj48PsrKyMHbsWLzzzjswMeF3zdVdSfc1tra2rG0yMuvXr8eYMWOwadOmatWKhu8CNYRarYafnx/Cw8P163Q6HcLDwxEQEFDsPgEBAQbbA8CePXtK3J4q18OUIQAsXrwY8+fPx65du/DEE09URahUgvKWYcuWLXHq1ClER0frl+eff14/IpSbm1tVhk//eJj/xU6dOuHcuXP6xBcA4uLi4OzszKRJAQ9ThtnZ2fclR0WJsBCi8oKlCsP7mpph3bp1GDVqFNatW4egoCClwzGk9OgUVHHWr18vNBqNWLVqlThz5owYO3assLe3FykpKUIIIYYNGyaCg4P120dERAgzMzOxZMkSERMTI0JCQoS5ubk4deqUUi+h1itvGS5atEio1WqxefNmkZycrF8yMjKUegm1XnnL8F4cVa96KG85Xrx4UdjY2Ig333xTxMbGiu3btwsHBwfxwQcfKPUSar3ylmFISIiwsbER69atEwkJCWL37t2iWbNmYuDAgUq9hFovIyNDnDhxQpw4cUIAEJ988ok4ceKESEpKEkIIERwcLIYNG6bfPiEhQdSpU0dMnz5dxMTEiNDQUGFqaip27dql1Euo9cpbhj/++KMwMzMToaGhBvc16enpSr0EA0ycapjPP/9cNG7cWKjVauHv7y8OHTqkf65bt25ixIgRBttv3LhReHl5CbVaLVq3bi127NhRxRHTvcpThu7u7gLAfUtISEjVB0565f0//DcmTtVHecvx4MGDon379kKj0YimTZuKBQsWiMLCwiqOmv6tPGVYUFAg5s6dK5o1ayYsLCyEm5ubGD9+vLh161bVB05CCCH27t1b7GdcUbmNGDFCdOvW7b59fH19hVqtFk2bNhVhYWFVHjfdVd4y7NatW6nbK00lBOufiYiIiIiISsM+TkRERERERGVg4kRERERERFQGJk5ERERERERlYOJERERERERUBiZOREREREREZWDiREREREREVAYmTkRERERERGVg4kRERERERFQGJk5EREZs5MiR6N+/v/5x9+7d8fbbb1d5HPv27YNKpUJ6enqVn9vDwwPLli17pGOsWrUK9vb2pW4zd+5c+Pr66h9Xl2sPABEREfDx8YG5ublBTOWVmJgIlUqF6OjoCouNiKimYOJERFTBRo4cCZVKBZVKBbVaDU9PT7z//vsoLCys9HP/9NNPmD9//gNtW9XJjoeHh/66WFlZoV27dti0aVOVnLsiTJs2DeHh4SU+f++1r4iE7kFNmTIFvr6+uHDhAlatWlXidufOncOoUaPg6uoKjUaDJk2aYMiQITh27FiVxFmWlStXonv37rC1tVUsESciKgkTJyKiStC7d28kJycjPj4eU6dOxdy5c/Hxxx8Xu21+fn6FnbdevXqwsbGpsONVtPfffx/Jyck4ceIEnnzySQwaNAgHDx4sdtuKvC4VwdraGvXr1y/xeSWv/fnz5/HUU0/B1dW1xJqzY8eOwc/PD3Fxcfjqq69w5swZbN26FS1btsTUqVOrNuASZGdno3fv3pg9e7bSoRAR3YeJExFRJdBoNHBycoK7uzvGjRuHnj174ueffwZwt4nXggUL4OLighYtWgAALl26hIEDB8Le3h716tVDv379kJiYqD+mVqvFlClTYG9vj/r162PGjBkQQhic997mYnl5eZg5cybc3Nyg0Wjg6emJb7/9FomJiejRowcAoG7dulCpVBg5ciQAQKfTYeHChWjSpAksLS3Rtm1bbN682eA8O3fuhJeXFywtLdGjRw+DOEtjY2MDJycneHl5ITQ0FJaWlvjll18AyBqa+fPnY/jw4bC1tcXYsWMBAFu2bEHr1q2h0Wjg4eGBpUuX3nfcjIwMDBkyBFZWVmjUqBFCQ0MNnv/kk0/g4+MDKysruLm5Yfz48cjMzLzvONu2bUPz5s1hYWGBwMBAXLp0Sf/cvU317vXva9+9e3ckJSVh8uTJ+lq2rKws2Nra3nctt23bBisrK2RkZBR73Ly8PLz11ltwcHCAhYUFOnfujKNHjwK427Tu5s2bePXVV6FSqYqtcRJCYOTIkWjevDkOHDiAoKAgNGvWDL6+vggJCcF///vfYs+t1WoxevRo/d9CixYt8Nlnnxlss2/fPvj7+8PKygr29vbo1KkTkpKSAAB//fUXevToARsbG9ja2sLPz6/U2q23334bwcHB6NChQ4nbEBEphYkTEVEVsLS0NKhBCQ8PR2xsLPbs2YPt27ejoKAAgYGBsLGxwYEDBxAREQFra2v07t1bv9/SpUuxatUqfPfdd/jzzz+RlpaGrVu3lnre4cOHY926dVi+fDliYmLw1VdfwdraGm5ubtiyZQsAIDY2FsnJyfob4oULF2LNmjVYsWIFTp8+jcmTJ+OVV17BH3/8AUAmeAMGDEDfvn0RHR2NMWPGIDg4uNzXxMzMDObm5gbXZcmSJWjbti1OnDiBOXPmICoqCgMHDsTgwYNx6tQpzJ07F3PmzLkvOfj444/1+wUHB2PSpEnYs2eP/nkTExMsX74cp0+fxurVq/H7779jxowZBsfIzs7GggULsGbNGkRERCA9PR2DBw8u9+sCZLM9V1dXfQ1bcnIyrKysMHjwYISFhRlsGxYWhhdffLHE2qoZM2Zgy5YtWL16NY4fPw5PT08EBgYiLS0Nbm5uSE5Ohq2tLZYtW4bk5GQMGjTovmNER0fj9OnTmDp1KkxM7v/oL6mWSqfTwdXVFZs2bcKZM2fw3nvvYfbs2di4cSMAoLCwEP3790e3bt1w8uRJREZGYuzYsVCpVACAoUOHwtXVFUePHkVUVBSCg4Nhbm5enktJRFR9CCIiqlAjRowQ/fr1E0IIodPpxJ49e4RGoxHTpk3TP+/o6Cjy8vL0+3z//feiRYsWQqfT6dfl5eUJS0tL8euvvwohhHB2dhaLFy/WP19QUCBcXV315xJCiG7duolJkyYJIYSIjY0VAMSePXuKjXPv3r0CgLh165Z+XW5urqhTp444ePCgwbajR48WQ4YMEUIIMWvWLOHt7W3w/MyZM+871r3c3d3Fp59+qn9tH374oQAgtm/frn++f//+Bvu8/PLLolevXgbrpk+fbnB+d3d30bt3b4NtBg0aJJ599tkSY9m0aZOoX7++/nFYWJgAIA4dOqRfFxMTIwCIw4cPCyGECAkJEW3bttU//+9yFsLw2t/7eoscPnxYmJqaiqtXrwohhLh27ZowMzMT+/btKzbOzMxMYW5uLn788Uf9uvz8fOHi4mLwt2BnZyfCwsJKfL0bNmwQAMTx48dL3EYIIS5cuCAAiBMnTpS4zYQJE8QLL7wghBDi5s2bAkCJ8dvY2IhVq1aVes7iFPe3SUSkNNY4ERFVgu3bt8Pa2hoWFhZ49tlnMWjQIMydO1f/vI+PD9Rqtf7xX3/9hXPnzsHGxgbW1tawtrZGvXr1kJubi/Pnz+P27dtITk5G+/bt9fuYmZnhiSeeKDGG6OhomJqaolu3bg8c97lz55CdnY1evXrp47C2tsaaNWtw/vx5AEBMTIxBHAAQEBDwQMefOXMmrK2tUadOHXz00UdYtGgRgoKC9M/f+3piYmLQqVMng3WdOnVCfHw8tFptiecPCAhATEyM/vFvv/2Gp59+Go0aNYKNjQ2GDRuGmzdvIjs7W7+NmZkZnnzySf3jli1bwt7e3uA4j8rf3x+tW7fG6tWrAQA//PAD3N3d0bVr12K3P3/+PAoKCgyugbm5Ofz9/csVl7inSWd5hIaGws/PDw0bNoS1tTVWrlyJixcvApD9ukaOHInAwED07dsXn332GZKTk/X7TpkyBWPGjEHPnj2xaNEi/d8QEZExYuJERFQJevTogejoaMTHxyMnJwerV6+GlZWV/vl//w4AmZmZ8PPzQ3R0tMESFxeHl19++aFisLS0LPc+Rf1+duzYYRDHmTNn7uub8zCmT5+O6OhoXL58Gbdu3cLMmTMNnr/3ulSExMRE9OnTB4899hi2bNmCqKgofR8oJQagGDNmjL6pYVhYGEaNGqVv2lZZvLy8AABnz54t137r16/HtGnTMHr0aOzevRvR0dEYNWqUwXULCwtDZGQkOnbsiA0bNsDLywuHDh0CIPuFnT59GkFBQfj999/h7e1dZvNSIqLqiokTEVElsLKygqenJxo3bgwzM7Myt2/Xrh3i4+Ph4OAAT09Pg8XOzg52dnZwdnbG4cOH9fsUFhYiKiqqxGP6+PhAp9Pp+ybdq6jG6981N97e3tBoNLh48eJ9cbi5uQEAWrVqhSNHjhgcq+hGuSwNGjSAp6cnnJycHihZaNWqFSIiIgzWRUREwMvLC6ampiWe/9ChQ2jVqhUAICoqCjqdDkuXLkWHDh3g5eWFq1ev3neuwsJCg4ELYmNjkZ6erj9OeanVaoNrW+SVV15BUlISli9fjjNnzmDEiBElHqNZs2ZQq9UG16CgoABHjx6Ft7f3A8fi6+sLb29vLF26FDqd7r7nSxr2OyIiAh07dsT48ePx+OOPw9PTs9hao8cffxyzZs3CwYMH0aZNG6xdu1b/nJeXFyZPnozdu3djwIAB9/XxIiIyFkyciIiqgaFDh6JBgwbo168fDhw4gAsXLmDfvn146623cPnyZQDApEmTsGjRImzbtg1nz57F+PHjS53nxsPDAyNGjMCrr76Kbdu26Y9Z1LHf3d0dKpUK27dvx40bN5CZmQkbGxtMmzYNkydPxurVq3H+/HkcP34cn3/+ub552RtvvIH4+HhMnz4dsbGxWLt2balzBz2KqVOnIjw8HPPnz0dcXBxWr16NL774AtOmTTPYLiIiAosXL0ZcXBxCQ0OxadMmTJo0CQDg6emJgoICfP7550hISMD333+PFStW3Hcuc3NzTJw4EYcPH0ZUVBRGjhyJDh06wN/f/6Fi9/DwwP79+3HlyhWkpqbq19etWxcDBgzA9OnT8cwzz8DV1bXEY1hZWWHcuHGYPn06du3ahTNnzuC1115DdnY2Ro8e/cCxqFQqhIWFIS4uDl26dMHOnTuRkJCAkydPYsGCBejXr1+x+zVv3hzHjh3Dr7/+iri4OMyZM0c/oh8AXLhwAbNmzUJkZCSSkpKwe/duxMfHo1WrVsjJycGbb76Jffv2ISkpCRERETh69GipiWhKSgqio6Nx7tw5AMCpU6cQHR2NtLS0B36tRESVRulOVkRENc29gwY86PPJycli+PDhokGDBkKj0YimTZuK1157Tdy+fVsIIQeDmDRpkrC1tRX29vZiypQpYvjw4aUOUJCTkyMmT54snJ2dhVqtFp6enuK7777TP//+++8LJycnoVKpxIgRI4QQckCLZcuWiRYtWghzc3PRsGFDERgYKP744w/9fr/88ovw9PQUGo1GdOnSRXz33XflGhyiPM9v3rxZeHt7C3Nzc9G4cWPx8ccf37ffvHnzxEsvvSTq1KkjnJycxGeffWawzSeffCKcnZ2FpaWlCAwMFGvWrDGINywsTNjZ2YktW7aIpk2bCo1GI3r27CmSkpL0xyjv4BCRkZHiscceExqNRtz7cRseHi4AiI0bN5Z4PYrk5OSIiRMn6v8uOnXqJI4cOWKwTVmDQxSJjY0Vw4cPFy4uLkKtVgt3d3cxZMgQ/aAR9w4OkZubK0aOHCns7OyEvb29GDdunAgODtZfh5SUFNG/f3/935e7u7t47733hFarFXl5eWLw4MHCzc1NqNVq4eLiIt58802Rk5NTYnwhISECwH3Lg7w2IqLKphLiEXqMEhERUbl9//33mDx5Mq5evWowSAgREVVfZTe8JyIiogqRnZ2N5ORkLFq0CK+//jqTJiIiI8I+TkRERFVk8eLFaNmyJZycnDBr1iylwyEionJgUz0iIiIiIqIysMaJiIiIiIioDEyciIiIiIiIysDEiYiIiIiIqAxMnIiIiIiIiMrAxImIiIiIiKgMTJyIiIiIiIjKwMSJiIiIiIioDEyciIiIiIiIyvD/5uSOtpomRs8AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "knn = KNeighborsClassifier()\n",
        "knn.fit(X_train_resampled, y_train_resampled)\n",
        "y_pred_resampled = knn.predict(X_test_resampled)\n",
        "accuracy = accuracy_score(y_test_resampled, y_pred_resampled)\n",
        "cm = confusion_matrix(y_test_resampled, y_pred_resampled)\n",
        "plt.figure(figsize=(8, 6))\n",
        "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=['Predicted 0', 'Predicted 1'], yticklabels=['Actual 0', 'Actual 1'])\n",
        "plt.xlabel('Predicted')\n",
        "plt.ylabel('Actual')\n",
        "plt.title('Confusion Matrix - KNN')\n",
        "plt.savefig('ConfusionMatrix.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "LvpFO6xVS8_r",
        "outputId": "c55643ab-8d69-4483-e3ae-ff8e7ce2dbbc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "image/png": {
              "width": 800,
              "height": 600
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_prob_knn = knn.predict_proba(X_test_resampled)[:, 1]\n",
        "y_prob_lr = lr.predict_proba(X_test_resampled)[:, 1]\n",
        "precision_knn, recall_knn, thresholds_knn = precision_recall_curve(y_test_resampled, y_prob_knn)\n",
        "precision_lr, recall_lr, thresholds_lr = precision_recall_curve(y_test_resampled, y_prob_lr)\n",
        "plt.figure(figsize=(8, 6))\n",
        "\n",
        "plt.plot(recall_knn, precision_knn, label='KNN', color='b')\n",
        "plt.plot(recall_lr, precision_lr, label='Logistic Regression', color='g')\n",
        "\n",
        "plt.xlabel('Recall', weight='bold', fontsize=16)\n",
        "plt.xticks(weight='bold', fontsize=14)\n",
        "plt.ylabel('Precision', weight='bold', fontsize=16)\n",
        "plt.yticks(weight='bold', fontsize=14)\n",
        "plt.title('Precision-Recall Curve with Thresholds', weight='bold', fontsize=20)\n",
        "plt.legend(prop={'size':14})\n",
        "plt.grid(True)\n",
        "plt.savefig('PrecisionRecallCurve.png', dpi=300, bbox_inches='tight')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "jj69XvYE45rR",
        "outputId": "9d4e0693-f4fc-4e5e-feb1-fd36021c1c21",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 587
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# perform grid search\n",
        "grid = {\n",
        "    \"n_neighbors\": [3, 5, 7, 9],\n",
        "    \"weights\": [\"uniform\", \"distance\"],\n",
        "    \"p\": [1, 2]\n",
        "}\n",
        "gs = GridSearchCV(KNeighborsClassifier(), grid, cv=5)\n",
        "gs.fit(X_train_resampled, y_train_resampled)\n",
        "print(\"Best score:\", gs.best_score_, \"Best params:\", gs.best_params_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D9L-1Pn2IG9i",
        "outputId": "e0c47426-0395-4eb2-df41-0909099bc6f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best score: 0.6796761225298681 Best params: {'n_neighbors': 9, 'p': 2, 'weights': 'uniform'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# perform random search\n",
        "rs = RandomizedSearchCV(KNeighborsClassifier(), grid, cv=5)\n",
        "rs.fit(X_train_resampled, y_train_resampled)\n",
        "print(\"Best score:\", rs.best_score_, \"Best params:\", rs.best_params_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZR9pTc6hJ5lo",
        "outputId": "30837f39-5770-4567-8d8d-5a7cf98cef43"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Best score: 0.6796761225298681 Best params: {'weights': 'uniform', 'p': 2, 'n_neighbors': 9}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Based on the best parameters, create the model\n",
        "knn = KNeighborsClassifier(n_neighbors=9, p=1, weights=\"uniform\")\n",
        "knn.fit(X_train_resampled, y_train_resampled)\n",
        "y_pred = knn.predict(X_test_resampled)\n",
        "accuracy = accuracy_score(y_test_resampled, y_pred)\n",
        "cm = confusion_matrix(y_test_resampled, y_pred)\n",
        "cr = classification_report(y_test_resampled, y_pred)\n",
        "\n",
        "print(\"Accuracy on test set:\", accuracy)\n",
        "print(\"Confusion Matrix:\\n\", cm)\n",
        "print(\"Classification Report:\\n\", cr)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8q188yjDKVRt",
        "outputId": "c791a7f9-afcf-40e0-8152-217242f42a8c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy on test set: 0.6542730299667037\n",
            "Confusion Matrix:\n",
            " [[686 256]\n",
            " [367 493]]\n",
            "Classification Report:\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "           0       0.65      0.73      0.69       942\n",
            "           1       0.66      0.57      0.61       860\n",
            "\n",
            "    accuracy                           0.65      1802\n",
            "   macro avg       0.65      0.65      0.65      1802\n",
            "weighted avg       0.65      0.65      0.65      1802\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.inspection import permutation_importance\n",
        "\n",
        "lr = LogisticRegression()\n",
        "lr.fit(X_train_resampled, y_train_resampled)\n",
        "\n",
        "# Calculate permutation feature importance\n",
        "result = permutation_importance(knn, X_test_resampled, y_test_resampled, n_repeats=10, random_state=42, n_jobs=-1)\n",
        "\n",
        "# Get feature importance scores\n",
        "importance_scores = result.importances_mean\n",
        "feature_names = X_train_resampled.columns\n",
        "\n",
        "# Plot feature importance scores\n",
        "plt.barh(feature_names, importance_scores)\n",
        "plt.xlabel('Importance Score')\n",
        "plt.ylabel('Feature')\n",
        "plt.title('Permutation Feature Importance')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "FWhXNiN70Bth",
        "outputId": "77979787-6ebc-4a77-e31b-a20fc413d2c0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 663
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Feature 0: 0.13784683684794674\n",
            "Feature 1: -0.018479467258601556\n",
            "Feature 2: -0.019866814650388455\n",
            "Feature 3: 0.009933407325194243\n",
            "Feature 4: -0.02197558268590454\n",
            "Feature 5: -0.019311875693673673\n",
            "Feature 6: -0.006270810210876765\n",
            "Feature 7: -0.005826859045504973\n",
            "Feature 8: -0.007491675915649254\n",
            "Feature 9: -0.0023862375138735013\n",
            "Feature 10: 5.549389567147678e-05\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install shap"
      ],
      "metadata": {
        "id": "OlZLcXjy1H6_",
        "outputId": "c32be854-f375-4341-a87a-4b4f4540bc52",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "collapsed": true
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting shap\n",
            "  Downloading shap-0.46.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (540 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m540.1/540.1 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from shap) (1.25.2)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from shap) (1.11.4)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from shap) (1.2.2)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from shap) (2.0.3)\n",
            "Requirement already satisfied: tqdm>=4.27.0 in /usr/local/lib/python3.10/dist-packages (from shap) (4.66.4)\n",
            "Requirement already satisfied: packaging>20.9 in /usr/local/lib/python3.10/dist-packages (from shap) (24.1)\n",
            "Collecting slicer==0.0.8 (from shap)\n",
            "  Downloading slicer-0.0.8-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.10/dist-packages (from shap) (0.58.1)\n",
            "Requirement already satisfied: cloudpickle in /usr/local/lib/python3.10/dist-packages (from shap) (2.2.1)\n",
            "Requirement already satisfied: llvmlite<0.42,>=0.41.0dev0 in /usr/local/lib/python3.10/dist-packages (from numba->shap) (0.41.1)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->shap) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->shap) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->shap) (2024.1)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->shap) (1.4.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->shap) (3.5.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->shap) (1.16.0)\n",
            "Installing collected packages: slicer, shap\n",
            "Successfully installed shap-0.46.0 slicer-0.0.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import shap\n",
        "df_mandena_filtered = df_mandena_filtered.drop(['asv_ID'], axis=1)\n",
        "df_mandena_filtered = df_mandena_filtered.astype('float64')\n",
        "\n",
        "# Check and ensure no missing values\n",
        "if df_mandena_filtered.isnull().values.any():\n",
        "    df_mandena_filtered = df_mandena_filtered.fillna(0)\n",
        "\n",
        "X = df_mandena_filtered.drop(['Link'], axis=1)\n",
        "y = df_mandena_filtered['Link']\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n",
        "\n",
        "# Undersample the training data\n",
        "rus = RandomUnderSampler(random_state=42, sampling_strategy='majority')\n",
        "X_resampled, y_resampled = rus.fit_resample(X_train, y_train)\n",
        "X_train_resampled, X_test_resampled, y_train_resampled, y_test_resampled = train_test_split(X_resampled, y_resampled, test_size=0.3, random_state=42)\n",
        "\n",
        "X_train_resampled = pd.DataFrame(X_train_resampled, columns=X.columns)\n",
        "X_test_resampled = pd.DataFrame(X_test_resampled, columns=X.columns)\n",
        "\n",
        "lr = LogisticRegression()\n",
        "lr.fit(X_train_resampled, y_train_resampled)\n",
        "y_pred_resampled = lr.predict(X_test_resampled)\n",
        "explainer = shap.Explainer(lr, X_train_resampled)\n",
        "shap_values = explainer(X_test_resampled)\n",
        "shap.plots.beeswarm(shap_values)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "7Vh733vASn_i",
        "outputId": "10c94634-ce7b-4737-d12e-bb0f6d08bc59"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x550 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def custom_beeswarm_plot(shap_values, features, feature_names, max_display=11, plot_range=(-2, 2)):\n",
        "    shap_values = shap_values.values\n",
        "    feature_names = np.array(feature_names)\n",
        "\n",
        "    # Compute the mean absolute SHAP values\n",
        "    mean_abs_shap = np.abs(shap_values).mean(0)\n",
        "\n",
        "    # Get the indices of features sorted by their mean absolute SHAP values\n",
        "    feature_order = np.argsort(mean_abs_shap)[::-1]\n",
        "\n",
        "    # Identify the indices of the important features\n",
        "    important_features = ['asv_degree', 'host_degree']\n",
        "    important_indices = [np.where(feature_names == feature)[0][0] for feature in important_features]\n",
        "\n",
        "    # Ensure important features are included\n",
        "    included_indices = list(feature_order[:max_display])\n",
        "\n",
        "    # Add important features if not already included\n",
        "    for idx in important_indices:\n",
        "        if idx not in included_indices:\n",
        "            if len(included_indices) < max_display:\n",
        "                included_indices.append(idx)\n",
        "            else:\n",
        "                # Replace the least important feature with the important one\n",
        "                included_indices[-1] = idx\n",
        "\n",
        "    # Sort the final indices by their mean absolute SHAP values to maintain importance\n",
        "    final_indices = sorted(included_indices, key=lambda x: mean_abs_shap[x], reverse=True)\n",
        "\n",
        "    plt.figure(figsize=(10, 8))\n",
        "\n",
        "    # Plot the features in reverse order\n",
        "    for i, feature in enumerate(reversed(final_indices)):\n",
        "        values = shap_values[:, feature]\n",
        "        feature_values = features[:, feature]\n",
        "        mask = (values >= plot_range[0]) & (values <= plot_range[1])\n",
        "\n",
        "        plt.scatter(values[mask], [i] * len(values[mask]),\n",
        "                    c=feature_values[mask], cmap='coolwarm', s=5)\n",
        "\n",
        "    plt.yticks(range(len(final_indices)),\n",
        "               [feature_names[i] for i in reversed(final_indices)])\n",
        "    plt.xticks(weight='bold')\n",
        "    plt.xlabel('SHAP value (impact on model output)')\n",
        "    plt.ylabel('Feature')\n",
        "    plt.title(f'Zoom in to range: ({plot_range[0]} to {plot_range[1]})', weight='bold', fontsize=20)\n",
        "    plt.colorbar(label='Feature value')\n",
        "    plt.grid(True, alpha=0.3)\n",
        "    plt.savefig('ZoomInSHAP.png', dpi=300, bbox_inches='tight')\n",
        "    plt.show()\n",
        "\n",
        "# Example usage:\n",
        "custom_beeswarm_plot(shap_values, X_test_resampled.values, X_test_resampled.columns, max_display=10, plot_range=(-2, 2))"
      ],
      "metadata": {
        "id": "o2oQ8Ixmj46n",
        "outputId": "10188aa3-1232-4a58-d34c-5f64272b0e6d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 726
        }
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 2 Axes>"
            ],
            "image/png": 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ZL23SRsWKFdXS8k4nz5Hfuc3N1dVVLe29995DlSpVtGpP+/bttdqvONzd3XHt2jXldnFHl/OTkZGBwYMH43//+59Kukwmw86dO9GhQ4cSqVcbpf3e0fe5iY2NVUtzd3fXuX1EZDgMaonI5MjlcgwcOFDtS6SZmRk2bdqU72iTJs2aNVNL27dvHxQKhdp1YXv37i0wv6ayjh07huTkZNja2qqk79+/X+16SC8vL0510wNNo4oFXXuqz9dASXr+/DlSU1NV0urVq6c2W0GhUODs2bMGaVOORo0aqaUdOnRI477btm0rtLxmzZph3bp1anXk3K6qIHK53CAj/y1btsSff/6p3L558yaSkpI0XkNfrVo1nab7Jycno0+fPmq32XFzc8O+ffvQsGHDoje8AKb03imJc6Pp9lmtWrXSuY1EZDjqV/ITERm5WbNm4fjx42rpc+fORdu2bYtUVseOHdUWI7p58ybmzZunknbjxg18+eWXavl79+6t/LtevXrw9vZWeT4hIQETJ05U+WIYGxuLadOmFVgW6U5TUHHlypV899fna6AkaRrRevTokcoU2KysLAQFBeHmzZsGaVOOjh07qk15v3z5stp1pNu3b8eRI0cKLa9nz55qC6J9+eWX2L17t8b9FQoF/vrrL0yZMiXfa+kFQVB5VKtWrdB2FCTvaLBCocA///xTrDJze/HiBTp37qwWtHl5eeHkyZN6D2gB03nvlNS5ybtA2RtvvIEaNWroVBYRGRZHaonIpOzfvx9fffWVWrqVlRWePn2qtrqmJs7OzggODgYA2NraYtq0aZgxY4bKPnPmzMGuXbvQvHlzxMXFYc+ePWoL7VStWhUffvihWr5BgwappP300084ceIE/P39kZKSgj179uDly5cq+9jb22PKlCmFtp0K5+XlpZb222+/4a233oK3t7cyWJo/fz5sbW31/hooKc7OzqhWrRru3LmjTHvx4gXq1q2Lrl27AgCioqJw69Ytg7Qnb9uGDBmCVatWqaRPmjQJW7duRf369XH79m0cOHBAq/KqVq2KUaNGYfny5cq0tLQ0vPPOO/D19UXDhg1RoUIFJCUl4c6dO/j333+V76n8FrvStzZt2sDS0hIZGRnKtL/++ktvU5979uypcRXopk2bFrjoVO7Pt6IylfdOSZ2bvGV26tRJp/YRUSkoxdsJEREVWceOHTXeW7MoD09PT5Uys7KyxO7duxepDBsbG/HMmTMa2zhmzJgilWVmZibu2rVLrRxt7xk5dOhQtf2OHDmitp+np6fafrrS9T61/v7+OpenLblcrvFY8z6ePXumzKPv14A2dDnmsLCwQtslk8nEVq1aFfqa0HSf2rz3i82hzWsnLi5OdHd3L7R9derU0arelJQUsUWLFsV+f+fQdr+i6NOnj0qZLVu2LHaZObR5DRfl+LVhKu+dkjg3mu4zvnfvXp3bSESGxenHRGRSSuI2L2ZmZti+fTsmTpyo1bV4tWvXxsmTJ9G0aVONz//www9YsGCBctGegri7u+PAgQPo2bNnkdtNmkkkEixatEjjvTLzo+/XQEmZNGkSBgwYkO/zMpkM//vf/9SmwRuCs7MzDh48WOBiTn379sWiRYvU0jW9V6ytrXH48GGMHDlS6760sLAw6Oja6NGjVbb/+usv3L1712D161tZfu8UJu/CalWrVsVbb71VSq0hoqJiUEtEhOzrFcPDwxEdHY3p06ejVatWcHFxgYWFBezt7VGzZk0MHDgQv/76K/77778Cr9kSBAHTp0/HnTt3MG/ePHTo0AFubm6wtLSEjY0NPD090bdvX/z000+4ffs2p7iVgPfeew9Hjx7Fu+++iypVqsDCwqLQPPp8DZQUiUSCTZs2Yd26dWjXrh3s7e1hZWWFmjVrYty4cTh//nypfhGvU6cOLl++jBkzZqB27dqwsrJChQoV0KFDB/zyyy/Ytm1bkVb9trW1xY8//ojo6GjMnDkT7du3h5ubG6RSKSwtLeHi4oLmzZtjxIgR+OWXX/D48WOsWbOmpA9TqUuXLqhbt65K2qZNmwxWf0koq++dwvz6668q25988glvNUZkQgRR1GE5PiIiIiId9O3bF7/99ptK2pYtW9CvX79SalHx/Prrr3j//feV2x4eHrh165ZWwSAZh71796J79+7KbRcXF8TExKitWk9ExosjtURERKQXc+fOxb59+5CVlaX2nFwux9dff60W0FpbWyMgIMBQTdS7/v37o3Hjxsrt+/fv45dffinFFlFRhYaGqmx/8cUXDGiJTAxHaomIiEgvOnTogKNHj8LJyQnNmjWDp6cnLC0t8fTpU5w4cQJPnjxRyzN9+nQsWLCgFFqrP1FRUSq3E/Px8cGVK1eKdG0qlY4TJ06gXbt2ym1fX1/8+++/areUIiLjxqCWiIiI9CInqNVW586dsXfvXo334CUiItIWf0IkIiIigzIzM8PkyZPx+++/M6AlIqJi40gtERER6cXDhw+xfft2REZG4saNG4iNjcWLFy8glUrh7OyMevXqoW3bthgyZEiBt/4hIiIqCga1REREREREZLJ4FTyRBgqFAo8ePYK9vT0EQSjt5hARERFRHqIoIjExEe7u7ka3MFtaWhoyMjJKpW5LS0tYWVmVSt2lhUEtkQaPHj2Ch4dHaTeDiIiIiApx//59vPHGG6XdDKW0tDS4W9vhJeSlUr+bmxtiYmLKVWDLoJZIA3t7ewDZH5IymayUW2OaFAoFnj17BhcXF6P79bS8YB8YB/aDcWA/GAf2Q+krS32QkJAADw8P5fc2Y5GRkYGXkGOtWXXYGHhd3hQoMOxJDDIyMhjUEpV3OVOOZTIZg1odKRQKpKWlQSaTmfw/TVPFPjAO7AfjwH4wDuyH0lcW+8BYLxWztTCDjWBm0DoFUY5SGiAuVWXjlUxERERERETlEoNaIiIiIiIiMlmcfkxERERERKRngrkAiYGnRguicU7FLmkcqSUiIiIiIiKTxZFaIiIiIiIiPRMsJBAEw44hCqJo0PqMBUdqiYiIiIiIyGRxpJaIiIiIiEjPJGYCJBLDXuMqUfCaWiIiIiIiIiKTwqCWiIiIiIiITBanHxMREREREemZYCFAMPD0Y4HTj4mIiIiIiIhMC0dqiYiIiIiI9ExizoWiDIUjtURERERERGSyGNQSERERERGVQ6GhoWjWrBns7e3h6uqK3r17Izo6utB8//vf/1C7dm1YWVmhfv362Lt3rwFamz8GtURERERERHomWAil8iiKo0ePYty4cfjrr79w8OBBZGZm4q233kJycnK+eU6ePImBAwdixIgROH/+PHr37o3evXvjv//+K+4p0xmvqSUiIiIiIiqH9u3bp7K9du1auLq64ty5c2jfvr3GPN9++y26du2KadOmAQDmzZuHgwcPYtmyZVixYkWJt1kTBrVERERERER6JjETIDEz8EJR8uz6EhISVNKlUimkUmmh+ePj4wEAzs7O+e5z6tQpBAUFqaR16dIFO3bsKGJr9YfTj4mIiIiIiMoQDw8PODg4KB+hoaGF5lEoFJg0aRLatGmDevXq5bvfkydPUKlSJZW0SpUq4cmTJ8Vut644UktERERERKRngpkAwcAjtQKy67t//z5kMpkyXZtR2nHjxuG///7DiRMnSqx9JYVBLRERERERURkik8lUgtrCjB8/Hr///juOHTuGN954o8B93dzc8PTpU5W0p0+fws3NTae26gOnH5NedOjQAZMmTSrtZhARERERkZZEUcT48ePx22+/4c8//0T16tULzdOqVSscPnxYJe3gwYNo1apVSTWzUBypJSIiIiIi0rNSWSgKRatv3Lhx2LhxI3bu3Al7e3vldbEODg6wtrYGAAwZMgRVqlRRXpc7ceJE+Pv7IywsDN27d8fmzZtx9uxZrFq1Sr8HUwQMaslkZGRkwNLSsrSboXdtex5V2T6x21+rfJ3fP62yfXhzc63r7D5S9T5ie1bnvxhAXu9NvK38u64jEBJSQ6t8o2c+Qkqu7V/mu2td56gFccq/KzsBcz+uoHXeid8mKv/+dqK91vk+/zFNZfurUVZa5527IUv594f+wBtvaPdRe+2aAr9feb09ta/2k2m+/0N1e1w3rbMi4sjrv5tWBOrX1y5f5HkRT1Jfb7/fWvt/pDvOyJV/O0kB/wZmWuc9cDFD+fdbDbX/TDh3PRnJma+329e11TrvmehXyr+rVwAqVnTUKl9CQgLuPE1BStIrxCYCDby0n5p1594jZGRmv5asrSzhUUX7vHdvRiv/dnKtrPUUtCcPHwKJscptt9p+Wtf54lKua7Cc3OD8Ri2t8+oq+fYl4MmN7A2pHWybvKV13tTTe4GkOAAChNa9YWVlp1W+jIwMKI5uArIyAAdXWLXupUPLDSfpyUNgx7LsDVsZ7D6Yrn3enesgv/EPAAHS/uNhVVX7Po2bPw7ITAcsrVBhxjKt82U+uIO45fMgyuWw6/oe7Dv00DqvrlJSUnD/w76AKEJi7wCv1VtKvE4AuDLhEySePw+LihVRf8v/YGFhUeJ1Xp3xDW5/uw5o4ouWi2ehQtMGJV4nGbfly5cDyJ51mVtERASGDRsGALh37x4kktffSVq3bo2NGzfiiy++wIwZM+Dl5YUdO3YUuLhUSeP0YxO2b98+tG3bFo6OjqhQoQJ69OiBW7duAcj+pzt+/HhUrlwZVlZW8PT0VP66MmjQIAwYMEClrMzMTFSsWBHr168vtN7k5GQMGTIEdnZ2qFy5MsLCwtT2SU9Px9SpU1GlShXY2tqiRYsWiIyMVNnnxx9/hIeHB2xsbNCnTx8sXrwYjo6OyufnzJmDRo0aYfXq1ahevTqsrLKDilevXmHkyJFwcXGBTCZDp06dcPHiRZWyd+7cicaNG8PKygo1atRASEgIsrKyYGzyBrTFkTfIzU/egDa/NE1yB7QAcPmVVtkAQCWgBYDBMx9plS93QAsAj19qX2fugFbTdn6OnkxTS8sb5OYnd0ALAGuK0MW5A1oAWLRdoVW+vAEtAGw7op6mSUSe/c4+1y4fAJWAFgA2nxS1ypc7oAWAl+na15k7oNW0nZ8HD1QDWgCIupz/jeVzyx3QAkBMnOb9NLkbq3qSLt18ms+eqp4+i1MGtACQmpaBV69e5Z8hd525AloAeBn7WKt8AFQCWgB4cu28VtleXDqlmvCy5FfATI6Pfx3QAkB6EpL/i9Iq7+uAFgBEiCd/07pexaG12cGaKAKvniLt+DbtG10aduQKKJMTkLRhoVbZUo7s+P+AFgBEpG/5Dmlp2n0Oxs0ZlX2OACAjDXEho7XKl5mZiedLZkBMSwUyM5C0eyNSLv6tVd7iuD+8T3Z/AlAkxuP6sD4lXuelkSOQ8PffEDMykPHoEf7p3KnE64z5/mfc/mY1xCw5FBmZONVmADIytPsMJd0IEqFUHkUhiqLGR05ACwCRkZFYu3atSr5+/fohOjoa6enp+O+///D222/r4YzpjiO1Jiw5ORlBQUFo0KABkpKSEBwcjD59+uDChQtYunQpdu3ahS1btqBq1aq4f/8+7t+/DwAIDAxEv379kJSUBDu77F+m9+/fj5SUFPTpU/gH+bRp03D06FHs3LkTrq6umDFjBv755x80atRIuc/48eNx5coVbN68Ge7u7vjtt9/QtWtXXLp0CV5eXoiKisKYMWPw9ddf45133sGhQ4cwa9Ystbpu3ryJbdu2Yfv27TAzyx7J6devH6ytrfHHH3/AwcEBK1euROfOnXH9+nU4Ozvj+PHjGDJkCJYuXYp27drh1q1bGD06+x/q7NmzNR5Teno60tNff7POubeXQqGAQqFdYKELQVAPArStT9e8mvIVJ29++RQKBURRhEKhwJfLHmucDKNVnVCvc/SC51jxef73T3udV718ber843L+x1Q43erMP68W2TR06ZNU1T4oSl5t6vzvPzGfvFr8MxXVK9h5WoGeTQsfrRU15NXm/N56pb5PlpZ5RVH392neLwna5n0Vn6SW9vR5vFYjrrq29+mjR8ov9kXNK4rqPxrGXTsHJ2/tR3qLSnHjpPprMP6pVp9JikT1Xya07VNF3joT4kr0/0RxJCWpv46Q+FKr9qafPwbk+eSWnz8KRYs3C82bfYpy5c31OVTQ51LqqcMQ89SZsGczrOo3K7TO4hAF1TrFtNQS79Oky5eBXPWKGRklXuf1L5dBlEiyH4IASCR4ELEN1UYNKDyzkTLW9x4ZHoNaE/buu++qbK9ZswYuLi64cuUK7t27By8vL7Rt2xaCIMDT01O5X5cuXWBra4vffvsNH3zwAQBg48aNeOedd2BvX/D0zKSkJPz000/45Zdf0LlzZwDAunXrVFZJu3fvHiIiInDv3j24u2dPMZ06dSr27duHiIgILFiwAN999x26deuGqVOnAgC8vb1x8uRJ/P777yr1ZWRkYP369XBxcQEAnDhxAqdPn0ZsbKxyafJFixZhx44d2Lp1K0aPHo2QkBB8/vnnGDp0KACgRo0amDdvHj799NN8g9rQ0FCEhISopT979kzrX6Z1UcND/YtgbGyshj3VVausPrylTV4P17xjptrnreKsPtKZXz6FQoH4+HiIoog67vFI1DAaFxtbeBDjYpegltaoFhAbW/jIu7N1qlpabKx6Wl5Olpp/uY6NLXyqq8xMrpamzXECgK2GoDY2tvAJNVb5DJDGxr7ug9zThnKz0HAatXkJuroC1+LUK46N1SKoTVc/Tjc77Y5VkZqplhYbW/iUPUlamqZqERtb+GhtuobAIDZWu+HllKRXgCgiIzU5+6u6IGh1fpMS1V/3ZhJBq/dpgsb2Fp5PMDfHy2T194egRd7EFPV+gdQamVp+nukizdwJSMzbXgHJWnwmZcrVv/5ItWxrhpjnc0CQwLIEj7O4UqWOamkpWrQ32dEdSFf9f2Hh6K7VsSbIXNXSsv4/X+5+yPu5lFWxChKcK6ukmb9RU7sPpWJIcq+qlqbt/2JdZfj4AJmqH8AlXad5pxbIuHUPkEiAGlUAQYDQuHaJ11uSEhO1m4FFZR+DWhN248YNBAcH4++//8bz58+Vv1bdu3cPw4YNw5tvvgkfHx907doVPXr0wFtvZV9rZG5ujv79+2PDhg344IMPkJycjJ07d2Lz5s2F1nnr1i1kZGSgRYsWyjRnZ2f4+Pgoty9dugS5XA5vb2+VvOnp6ahQIftayOjoaLVR4ebNm6sFtZ6ensqAFgAuXryIpKQkZTk5UlNTlVOvL168iKioKMyfP1/5vFwuR1paGlJSUmBjY6N2XNOnT0dQUJByOyEhAR4eHsopziXl9n31t6Crq/qXAU3uPL6rU97v57ninY8uq6TtWllXqzofvlAPAPKrU6FQQBAEuLi4oG9fN+ycpToFsmdD7do7b7wrxnz1QiXt3a6Fj9ICwItU9X92rq6FX1c77QNgxk+qP2YsGKHdNbXtW2bh9zwzIF1dtfuoTc4T1FZ3AVxdCw/0hncDlu9TTfu4q2of5BfUCuZA3hBey5cgFLdUg9o69oCra+FB7TuuwK6zqsF/s4baBf6SJ+o/OLi6Fv5jg6srcPyK6uu3XR3trqk1M5OqTTl2dXXQKm9cEpClECECsLZzRFVXazho8Zni6uqKG7fvq6R51fDQqk5LMwkSXr1+z0jMzLX+XBFf5rkswN5Vq7yurq54mWfqr5NXba3q1JmrK5JP7VBJsm2V//Wtud8PGW17QTyVa9qwrSOstTxH6R7VIT54PcVb0vZdWNo7FanphpQkT8m+/jfHoOnKWVoFGhaE+MWv/y/C2gYOPtr9r7Cu2wiZpw4ot6Ude8H2/89vgZ9Lrq6wkFpA/vhe9ralFG6DtZsuXRwpdnbIuP76+g/3GQtgp+0HoY7sZn6BSx8MVm6/Mfojrd+nunL9ORx/yBpCIVcAogjblHR4NmlYonWWtJxL04yVYCaBYGbYqz01zXArDxjUmrCePXvC09MTP/74I9zd3aFQKFCvXj1kZGSgcePGiImJwR9//IFDhw6hf//+CAgIwNatWwFkT0H29/dHbGwsDh48CGtra3Tt2lUv7UpKSoKZmRnOnTunnDKcQ6t/pLnY2qp+6UxKSkLlypXVrs8FoLweNykpCSEhIejbt6/aPvl9+EmlUo03pZZIJPkGA/pwfFcHnfMe2tSi8J3y8fuPWq4ElMf/wmsWaX9BEJTn8Of5VXSqEwBWzaioU77widoFHpp8NUr9xw9tNK5micbVdKuzKAtD5TUun0tZcveBJoHFuIzr/Ta65+3dXLdj7dJI9y8w/vW0XygsNxcXJ+T6ba1I6tZyg0KhQGysAFdX1yJ9nvjU8ix8Jw2cXVzh7KLbl+PKvo11ygcAFRq00zmvruzbqH/OFyTn/WBjYwN0/kCnOq0b+gMNtVvQzxjIRqrPQtKW09RwnfI5dOkHdOmX7/MFfS5VmhqqU53FUWPuYoPXaeflhVZ/lfz1wnl1T7r0/59JsUX+TDJGpt5+0h8GtSYqLi4O0dHR+PHHH9GuXfYXiRMnTqjsI5PJMGDAAAwYMADvvfceunbtihcvXsDZ2RmtW7eGh4cHfv31V/zxxx/o16+fVqvu1axZExYWFvj7779RtWr2dJ2XL1/i+vXr8PfP/ifv5+cHuVyO2NhYZdvy8vHxwZkzZ1TS8m5r0rhxYzx58gTm5uaoVq1avvtER0ejVq2SX3mTiIiIiEgTU7ilT1nBoNZEOTk5oUKFCli1ahUqV66Me/fu4fPPP1c+v3jxYlSuXBl+fn6QSCT43//+Bzc3N5XVhQcNGoQVK1bg+vXrOHJEu6VS7ezsMGLECEybNg0VKlSAq6srZs6cqfJLmbe3NwIDAzFkyBCEhYXBz88Pz549w+HDh9GgQQN0794dn3zyCdq3b4/FixejZ8+e+PPPP/HHH39AEAp+IwYEBKBVq1bo3bs3Fi5cCG9vbzx69Ah79uxBnz590LRpUwQHB6NHjx6oWrUq3nvvPUgkEly8eBH//fcfvvzyy6KdaCIiIiIiMmocszdREokEmzdvxrlz51CvXj1MnjwZ33zzjfJ5e3t7LFy4EE2bNkWzZs1w584d7N27VyX4DAwMxJUrV1ClShW0aaP9PMJvvvkG7dq1Q8+ePREQEIC2bduiSZMmKvtERERgyJAhmDJlCnx8fNC7d2+cOXNGObrbpk0brFixAosXL0bDhg2xb98+TJ48udBrIwRBwN69e9G+fXsMHz4c3t7eeP/993H37l1UqlQJQPZCWL///jsOHDiAZs2aoWXLlliyZInKYllERERERCVJEErhlj6FDBCVVYKoae1/olIwatQoXLt2DcePHy/tpiAhIQEODg6Ij9fuFhqkrixds2Oq2AfGgf1gHNgPxoH9UPrKUh8Y6/e1nHYdbtoEtubaLYSoL8lZcnQ+e87ozklJ4/RjKjWLFi3Cm2++CVtbW/zxxx9Yt24dfvjhh9JuFhERERERmRAGtaTi3r17qFOnTr7PX7lyRTmFuLhOnz6NhQsXIjExETVq1MDSpUsxcuRIvZRNRERERFSaBDMYfKEooZzOwWVQSyrc3d1x4cKFAp/Xly1btuitLCIiIiIiKp8Y1JIKc3Nz3gqHiIiIiKiYBDMBgsFHasvnQlGmfXU4ERERERERlWsMaomIiIiIiMhkcfoxERERERGRngkSCQQD3zbJ0PUZi/J51ERERERERFQmcKSWiIiIiIhIzwSJAEFi4IWiDFyfseBILREREREREZksjtQSERERERHpmcRMgMTAt/SR8JY+RERERERERKaFQS0RERERERGZLE4/JiIiIiIi0jMuFGU4HKklIiIiIiIik8WRWiIiIiIiIj0TBAkEiWHHEAWhfI5Zls+jJiIiIiIiojKBQS0RERERERGZLE4/JiIiIiIi0jMuFGU4HKklIiIiIiIik8WRWiIiIiIiIj2TmAmQmBl25FSi4EgtERERERERkUnhSC0REREREZGe8Zpaw+FILREREREREZksBrVERERERERksjj9mIiIiIiISM8EiQSCxLBjiIauz1iUz6MmIiIiIiKiMoEjtURERERERHrGhaIMhyO1REREREREZLIY1BIREREREZHJ4vRjIiIiIiIiPeP0Y8PhSC0RERERERGZLI7UEhERERER6RlHag2HI7VERERERERkshjUEhERERERkcni9GMiIiIiIiI9y55+bNgxRE4/JiIiIiIiIjIxHKklIiIiIiLSM0EiQGJm4IWi5BypJSIiIiIiIjIpHKklIiIiIiLSM97Sx3A4UktEREREREQmi0EtERERERERmSxOPyYiIiIiItIzQSIphVv6lM8xy/J51ERERERERFQmcKSWiIiIiIhIz7hQlOFwpJaIiIiIiIhMFoNaIiIiIiIiMlmcfkxERERERKRnnH5sOBypJSIiIiIiIpPFkVoiIiIiIiI94y19DKd8HrUJ6dChAyZNmlTazShQtWrVEB4eXtrNICIiIiKicohBbTm2du1aODo6lnYziIiIiIjKnJxrag39KI84/ZhMQkZGBiwtLUu7GVQGHToWiznfXAUAbP/JF66urjqXNf+7Wzh2NhGuFczx8+J6xWrX+0G3kSUH6ntZYPZ4D53LufHoFaavAEQIeP8toGvrSjqX9cWqBMSnZP/93SSZzuUAwBdrMwBk/7I6d5ju7+0LFxQ4cCv77+oVgH4ddP+tdsX+13+P6aJzMQCAjSdE5d/vty5eWb//k6X8u0dj3f9tH72corLtX9dG57LOXX+h/LuJt7PO5QDAtVsPlH/XrvmGzuXcv3FFZdvDq47OZT3/75Ty74r1WulcDgAknt2n/Nu+aVedy0k5ulll28b/fZ3LSvt9ufJvqx4f61wOAKRuDFX+bT1oerHKSvrhc+XfdmO/0rmcl0tmACkvAQBOM5cXsnfBHk0eqPzbfcmmYpV1a0j3/y/IEzW/+kHncpLu38Gtjz8EzMxQc8NvsLOzK1a79OVkp8FIuHAZNb8YD6+gEaXdHCpnOFJrAhQKBT799FM4OzvDzc0Nc+bMUT5379499OrVC3Z2dpDJZOjfvz+ePn2qfP7ixYvo2LEj7O3tIZPJ0KRJE5w9exaRkZEYPnw44uPjIQgCBEFQKTc/sbGx6NmzJ6ytrVG9enVs2LBBbZ9Xr15h5MiRcHFxgUwmQ6dOnXDx4kWVfb788ku4urrC3t4eI0eOxOeff45GjRopnx82bBh69+6N+fPnw93dHT4+PgCA+/fvo3///nB0dISzszN69eqFO3fuqJS9evVq+Pr6wsrKCrVr18YPP+j+j4PKttwBLQD0HXG1gL0LNnDiJRw7mwgAiI3LQpehF3Qu672J2QEtAFy6kYmhn9/WqZxbt2KxJ/L19uYDwJkbT/PdvyCfhL8OaHO2dZUT0AKAIs92UeUEtAAQEwes2avQqZzcAa2m7aLIHdACwOYoMZ89C5c7oNW0ra28AW1x5A5oNW0XRe6AVtO2tvIGtPmlaSN3QKtpuyhyB7Satosjb5CrrdwBrabtosgd0GraLorcAa2mbW29nP+xMqBVbusod0CrabsolAEtADy6i1uj3tWpnKT7d3Br1BAgKwtIT8et995GUlKSzu3Slz3WdfDy+BnIE1Nw/bOF+OudUaXdJCpnOFJrAtatW4egoCD8/fffOHXqFIYNG4Y2bdqgc+fOyoD26NGjyMrKwrhx4zBgwABERkYCAAIDA+Hn54fly5fDzMwMFy5cgIWFBVq3bo3w8HAEBwcjOjoaALT6pW/YsGF49OgRjhw5AgsLC0yYMAGxsbEq+/Tr1w/W1tb4448/4ODggJUrV6Jz5864fv06nJ2dsWHDBsyfPx8//PAD2rRpg82bNyMsLAzVq1dXKefw4cOQyWQ4ePAgACAzMxNdunRBq1atcPz4cZibm+PLL79E165d8e+//8LS0hIbNmxAcHAwli1bBj8/P5w/fx6jRo2Cra0thg4dmu9xpaenIz09XbmdkJD9hV2hUECh0O1LcnmnUCggiqJRn7+QRVcg5Jml82a/SOz/tX2Ry3oZn6VWlq7HLgiqQVBKmm5lhW4Q4SoTIeB1eT9sAH4KLnpZAtTz6N63+ilr0W/qeZ6nAjo1S0PcuX4fMPgtXcrKU5io23thz3nNAawu50oU1fNE/peE9nWKPlor5j0+Hdukz7I0lZO3LG0/k/R5fAo9lZVybIvm8nUoS6HhVKXsXg6r7h8VvSwd2qSpH5JWzMh336ISoT718sX8sXCcvqzoZeX9UNexTRrLykjXqayb40Yh7z+buxM/gu+PP2tdRkn8fxYVIpBrgaLn+08Y5P+/MX/HALhQlCExqDUBDRo0wOzZswEAXl5eWLZsGQ4fPgwAuHTpEmJiYuDhkT09cf369ahbty7OnDmDZs2a4d69e5g2bRpq166tzJ/DwcEBgiDAzc1Nq3Zcv34df/zxB06fPo1mzZoBAH766Sf4+voq9zlx4gROnz6N2NhYSKVSAMCiRYuwY8cObN26FaNHj8Z3332HESNGYPjw4QCA4OBgHDhwQO2XRltbW6xevVo57fiXX36BQqHA6tWrIfz/B3pERAQcHR0RGRmJt956C7Nnz0ZYWBj69u0LAKhevTquXLmClStXFhjUhoaGIiQkRC392bNnSEtL0+r8kCqFQoH4+HiIogiJkX7A1vBQDxpsrAW1H2q0UbVSqlqaLuUAQBXnRL2UVUn2Co42yRCg+kVPl2ZVsFYf6YuN1e294WCRqaEsiyKXYyto/jITG1v015tUQ1F20O1cmWXmDWpFvHqlw3shTa4xOTbWrMhtykpJ15geG1v0EZ60JE2vT/U+1UZyYryGsor+WohPStaYbpmrA7X9TEpIUZ85INfxvZyapv7CStWhrPQsze1N0qGsDEg1plvq0i4z9R/DpYWUo6kfUq2cNO6bokObkuwrakzP0KGseOfKamlmOr4WEt3ULyPR5XM91bM6kKH6Gs2qUqVIZZXE/2fRz0ctTdf/gUWRmKj+eUTlE4NaE9CgQQOV7cqVKyM2NhZXr16Fh4eHMqAFgDp16sDR0RFXr15Fs2bNEBQUhJEjR+Lnn39GQEAA+vXrh5o1a+rUjqtXr8Lc3BxNmjRRptWuXVtlsamLFy8iKSkJFSpUUMmbmpqKW7ey5wlGR0dj7NixKs83b94cf/75p0pa/fr1Va6jvXjxIm7evAl7e3uV/dLS0nDr1i0kJyfj1q1bGDFiBEaNej3tJSsrCw4ODgUe2/Tp0xEUFKTcTkhIgIeHh3IKNRWdQqGAIAhwcXEx2qB2YXB9vDdKdcrx0R1FH6UFABubl7gW8zrIk0ig8/W5D1+ofkGvXsVMp7LmTaiIL5beQGyCozKonRGoW7tS5AlIzfNd39VVt/dGfKZ60ODqWvTraj/urT5a27QG4Opa9NdbuoYsvXUZpQUgv6E+UuvoWPT3QndXzaO1rq5F/9dt/lz9RwldRmkB4EG8etDp6qo5KCnMyyT1YFiX12dGQpxa2hu1fFW2tf1MMnumPt2/go7v5cT76vXY61JWp/c0jtba6FBWGtR/4NBllBYAUuXqP4pYF9Imjf0wbJrG0Vo7HY7PUuYIPLypkqbLKC0AyF88VkvT9XM96cl91YTKnjqVZTN/EW4P6KmS1mD5miKVURL/n81v3oc88fXnjOeEYcVao0JbVlZWJV5HsQiC2si6QeoshxjUmgALC9UvEIIgaD3dYs6cORg0aBD27NmDP/74A7Nnz8bmzZvRp0+fkmgqkpKSULlyZeX059yKutKyra2tWtlNmjTReB2vi4uLcqT3xx9/RIsWLVSeNzMreGRDKpUqR5Zzk0gkRhuQmQJBEIz6HFaqVAnbVgsYMOYqLC2A/b/661xW+GxfRJ17iSU/3UenVg4Y+4GnzmX9L7wmZn17D9F3svDx+zJ0bKF55EEbkwY5KReKWjtH90Wivh7riJ3HE3DoHGAhAIsn6v5jz5fDrPDNrxmITwVqvwEMDtB9oahP35Vg4bbsz8O3agKNGun2WhvTFfhjP3A3Z7sYC0UNagccuCDieRJQ0Q4IaCAgNla390LPJpZ6WSiqQz07letqi7NIVFOfCnpbKMq3lodeFoqq6l0XwOvraPNbJEqbzySX+q31tlCUQ7Nuelsoyq7D+yrX0eq6UJRNz4/1tlCU7aDpOi0UpakfZGO/en0drawe7AYP1qlNzsOC8PLPP4FT/wNQvIWiqizeiEfffA48ugvYyuD+5Uqdy6q17nfcGt0PSEuB2YeTUa1DgE7lyGQyNPrjKK5+PAyCVIra4bq1Sd//n7s9P4db363Hw19+Q73VX8G5vvrIbUkw1u8XZHgMak2Yr68v7t+/j/v37ytHa69cuYJXr16hTp3X/9C9vb3h7e2NyZMnY+DAgYiIiECfPn1gaWkJuVzz9DZNateujaysLJw7d045/Tg6OhqvXr1S7tO4cWM8efIE5ubmqFatmsZyfHx8cObMGQwZMkSZdubMmULrb9y4MX799Ve4urpqHD11cHCAu7s7bt++jcDAQK2Pi8o3V1dXHNmun1+T2zRxQpsmuo1Y5TVvYlW9lAMAPwW76uUff692MvRqp4cGAZg2QH+rmX/6rp6+lBVzxePc3mr0+pdyhaaLGIugOCse51acQDav4q54nFtxVjzOqzgrHudW3BWPcytOIJtXcVY8zq24Kx7nVtwVj3MrzorHuTl16gR06qSXstyn6adNAFBz1f/0Vpbv8rV6K0tfan4yBDU/GVL4jkQlgD9vmLCAgADUr18fgYGB+Oeff3D69GkMGTIE/v7+aNq0KVJTUzF+/HhERkbi7t27iIqKwpkzZ5TXwFarVg1JSUk4fPgwnj9/jpSUglfH9PHxQdeuXfHRRx/h77//xrlz5zBy5EhYW1urtKlVq1bo3bs3Dhw4gDt37uDkyZOYOXMmzp49CwD45JNP8NNPP2HdunW4ceMGvvzyS/z777/K62TzExgYiIoVK6JXr144fvw4YmJiEBkZiQkTJuDBg+xf+kNCQhAaGoqlS5fi+vXruHTpEiIiIrB48eLinGoiIiIioiIRhFK4T205nX7MoNaECYKAnTt3wsnJCe3bt0dAQABq1KiBX3/9FUD2lNu4uDgMGTIE3t7e6N+/P7p166ZcEKl169YYM2YMBgwYABcXFyxcuLDQOiMiIuDu7g5/f3/07dsXo0ePVrlmQhAE7N27F+3bt8fw4cPh7e2N999/H3fv3kWlStlTHwMDAzF9+nRMnToVjRs3RkxMDIYNG1bodRE2NjY4duwYqlatir59+8LX1xcjRoxAWlqacuR25MiRWL16NSIiIlC/fn34+/tj7dq1aisrExERERFR2SCI+a2DT2RAb775Jtzc3PDzz9ovSV+SEhIS4ODggPj4eC4UpSOFQoHY2Fi4uupn6isVHfvAOLAfjAP7wTiwH0pfWeoDY/2+ltOuax+/C3tp0Vd0L47E9EzUXr7N6M5JSeM1tWRwKSkpWLFiBbp06QIzMzNs2rQJhw4dUt6PloiIiIiISFsMaknp+PHj6NatW77P572PrK5ypijPnz8faWlp8PHxwbZt2xAQoNtKgERERERExibnOldD11keMaglpaZNm+LChQslXo+1tTUOHTpU4vUQEREREVHZx6CWlKytrVGrVq3SbgYREREREZHWGNQSERERERHpmSCRQDDwYlyGrs9YlM+jJiIiIiIiojKBI7VERERERER6JkgMv3CTUE6HLMvpYRMREREREVFZwKCWiIiIiIiITBanHxMREREREekZ71NrOBypJSIiIiIiIpPFkVoiIiIiIiJ9k0iyH4ausxwqn0dNREREREREZQJHaomIiIiIiPRMEAQIgoGvqTVwfcaCI7VERERERERkshjUEhERERERkcni9GMiIiIiIiI9EyQSCAZeuMnQ9RmL8nnUREREREREVCZwpJaIiIiIiEjPBIkAQWLghaIMXJ+x4EgtERERERERmSwGtURERERERGSyOP2YiIiIiIhI3wQJYOiFm4TyOWZZPo+aiIiIiIiIygSO1BIREREREelbKSwUBS4URURERERERGRaOFJLRERERESkZ4IggWDga1wNXZ+xKJ9HTURERERERGUCg1oiIiIiIiIyWZx+TEREREREpG8SwfALN3GhKCIiIiIiIiLTwpFaIiIiIiIiPRMkEggSAy8UZeD6jEX5PGoiIiIiIiIqExjUEhERERERkcni9GMiIiIiIiI9EyQCBAMv3GTo+owFR2qJiIiIiIjIZHGkloiIiIiISN8EARAMPIYocKSWiIiIiIiIyKRwpJaIiIiIiEjPeE2t4XCkloiIiIiIiEwWg1oiIiIiIiIyWZx+TEREREREpG8SSfbD0HWWQ+XzqImIiIiIiKhMYFBLRERERESkZ4IglMqjKI4dO4aePXvC3d0dgiBgx44dBe4fGRmpsc4nT54U40wVH4NaIiIiIiKicig5ORkNGzbE999/X6R80dHRePz4sfLh6upaQi3UDq+pJSIiIiIiKoe6deuGbt26FTmfq6srHB0d9d8gHXGkloiIiIiISN8EyevFogz1ELLDu4SEBJVHenq6Xg+tUaNGqFy5Mt58801ERUXptWxdMKglIiIiIiIqQzw8PODg4KB8hIaG6qXcypUrY8WKFdi2bRu2bdsGDw8PdOjQAf/8849eytcVpx8TERERERHpmSARIEiKtnCTPuoEgPv370MmkynTpVKpXsr38fGBj4+Pcrt169a4desWlixZgp9//lkvdeiCQS0REREREVEZIpPJVILaktS8eXOcOHHCIHXlh9OPiYiIiIiISCcXLlxA5cqVS7UNDGqNXM69oF69elXaTcGcOXPQqFGj0m6G0bSDiIiIiChfgqR0HkWQlJSECxcu4MKFCwCAmJgYXLhwAffu3QMATJ8+HUOGDFHuHx4ejp07d+LmzZv477//MGnSJPz5558YN26c3k6bLhjUkkaabr48depUHD58uHQaREREREREenX27Fn4+fnBz88PABAUFAQ/Pz8EBwcDAB4/fqwMcAEgIyMDU6ZMQf369eHv74+LFy/i0KFD6Ny5c6m0PwevqSWt2dnZwc7OrrSbQUREBpaVlYXE81eR9PwpJGIW7KtVhbmTE2wqV0bGixdIibkOKydnyG3sIcQ9gU1dP6TFXAfMzWDlUVOrOjIykoCUFKQqzIG4O0CFapBYWCDxQQwyBQVEM2sIllZIylRALloAohns7KzgZGsOCJZwkmUvgpKaKsfuC0CWHEjPFJCRKUChEJCeLsJCrkCSXI6UVDkyMxXIyJAjM0OOrEw50tOzkJmeBVEUkZ6SjszMLCjkmajukoVL0emAKGLcYAHPXjpi9Ae1Su5kE1HZIRGyH4auswg6dOgAURTzfX7t2rUq259++ik+/fRTXVpWojhSawQUCgVCQ0NRvXp1WFtbo2HDhti6dWu++584cQLt2rWDtbU1PDw8MGHCBCQnJwMAZsyYgRYtWqjladiwIebOnQsAOHPmDN58801UrFgRDg4O8Pf3V1mGu1q1agCAPn36QBAE5Xbeab8KhQJz587FG2+8AalUikaNGmHfvn3K5+/cuQNBELB9+3Z07NgRNjY2aNiwIU6dOlXg+bh37x569eoFOzs7yGQy9O/fH0+fPlXbb+XKlfDw8ICNjQ369++P+Ph45XORkZFo3rw5bG1t4ejoiDZt2uDu3bsF1ktEROpuLVmD/dZ1cbrLAESPmoxbU6bj8rChuNjrHZx/qz1uf/Q+nnwVjLszJiBu7ni8WL4AD8b3w8sfv0TyT6GICxlVaB3JZ/9A5tkDyLxyApLrJ4CEOKQ9vIbk+9chQSYEiSUEARAz0mAGM0gEM2TBAq+SFLjxOBNXHmQg6koS/o1Jxe8Xsss0NxNgbQmYmYlQKEQAIgQAIrJv5SiVSmBnZwFbOwtYWEogCAIsrSyyH9bZAbLEzAI3n/z/7/+CgGW/iFi/9THa9jyKtZtjSuJ0ExGRDjhSawRCQ0Pxyy+/YMWKFfDy8sKxY8cwePBguLi4qO1769YtdO3aFV9++SXWrFmDZ8+eYfz48Rg/fjwiIiIQGBiI0NBQ3Lp1CzVrZv86fvnyZfz777/Ytm0bACAxMRFDhw7Fd999B1EUERYWhrfffhs3btyAvb09zpw5A1dXV0RERKBr164wMzPT2O5vv/0WYWFhWLlyJfz8/LBmzRq88847uHz5Mry8vJT7zZw5E4sWLYKXlxdmzpyJgQMH4ubNmzA3V3/5KRQKZUB79OhRZGVlYdy4cRgwYAAiIyOV+928eRNbtmzB7t27kZCQgBEjRmDs2LHYsGEDsrKy0Lt3b4waNQqbNm1CRkYGTp8+DUHI/5er9PR0lZtSJyQkKNujUCgK6D3Kj0KhgCiKPH+liH1gHEy9H65OXwTBygwSOwsIFgIsHCyVz1naS6FA9iUrokJEZnoWLG2yA8KspDRYOEsBEXi1cy1kPYdoLD8jIwOK9NTXCfIsiJJMKCQWAERkCZZQQABEESIAc0UakkVrZIengJkgQo4syEUz3HxqCVEUIYqAIGQHsVIzIDlLQJZCAQuIyMjIQs5v+oIAWFgA6WlZEP6/PEEAMlLTIAjZ2+lJycq/BQGwsrZEekoqftp4F0P6e+rrNJcbpv5+KAvKUh8Y+zEIggRCEa9x1Ued5RGD2lKWnp6OBQsW4NChQ2jVqhUAoEaNGjhx4gRWrlyJ0aNHq+wfGhqKwMBATJo0CQDg5eWFpUuXwt/fH8uXL0fdunXRsGFDbNy4EbNmzQIAbNiwAS1atECtWtnTpTp16qRS5qpVq+Do6IijR4+iR48eymDa0dERbm5u+bZ90aJF+Oyzz/D+++8DAL7++mscOXIE4eHh+P7775X7TZ06Fd27dwcAhISEoG7durh58yZq166tVubhw4dx6dIlxMTEwMPDAwCwfv161K1bF2fOnEGzZs0AAGlpaVi/fj2qVKkCAPjuu+/QvXt3hIWFwdLSEvHx8ejRo4cysPf19S2wH0JDQxESEqKW/uzZM6SlpRWYlzRTKBSIj4+HKIqQSMrnB2xpYx8YB1PvB7GRNwRLCeQ2EogWEmTILJTPpbjYQMDrHwzTrS1gLn39fKrMFgAgiU9EWmysxvIzMzMhz8hVHwBRrkA60iAIArIkciiEDEDIfk4hSpCWa6acKAJy0QxyUQKkW0IiCv8f1GY/Zy4HrCHAEgpYIh4yMwVE8XWbRYkIhU3a/4/mZrMRU6CQZ2+nWKTmxM/KBmamZwEAYvM5Jsqfqb8fyoKy1AeJiYml3QQyEgxqS9nNmzeRkpKCN998UyU9IyNDecF2bhcvXsS///6LDRs2KNNyfm2LiYmBr68vAgMDsWbNGsyaNQuiKGLTpk0ICgpS7v/06VN88cUXiIyMRGxsLORyOVJSUlQuAi9MQkICHj16hDZt2qikt2nTBhcvXlRJa9CggfLvnOW+Y2NjNQa1V69ehYeHhzKgBYA6derA0dERV69eVQa1VatWVQa0ANCqVSsoFApER0fD398fw4YNQ5cuXfDmm28iICAA/fv3L3Cp8enTp6uco4SEBHh4eMDFxcVg9/gqaxQKBQRBgIuLi8n/0zRV7APjYOr94AAzJJy+AkkFCwhmAsxcLGFmkX0cFi+sIbXPHpmFANhUsIfELPs5cyspLJB9aYzNR1NhZe2Qbx3J984o/xYhQC61QJqVFIJEAoUgQYaZdXaUCiAdUggKa8j//yuMKAJpcguYQYCgsIBCYQ7x/0NtUQRSUgVkSIBMUQ6FHEgRKiAz63VQm5mpQGJWOlJTspBTYEqyNVKTs3/QTEsyQ0Zq+v8/JUKemYmsDHM42JnB1dW1mGe3/DH190NZUJb6wMrKqrSbQEaCQW0pS0pKAgDs2bNHJUgDAKlUilu3bqnt/9FHH2HChAlqZVWtWhUAMHDgQHz22Wf4559/kJqaivv372PAgAHK/YYOHYq4uDh8++238PT0hFQqRatWrZCRkaFWpj5YWLz+1T5nCnBJTxeJiIjAhAkTsG/fPvz666/44osvcPDgQbRs2VLj/lKpFFKpVC1dIpGY/Ad+aRIEgeewlLEPjIMp90P7v7bh0vg5ePLbHxAzkpHxMgPW7vaQulREze9/QOyC6ch8Hgtze2uYSa0AUQFp41aQ3L0MCAJsR3wGK1unAuuQNuuBzEt/ApnpyDKTQiIxg01GAlKsHCGIIszk6cgys/j/qchmMBcyAVFEpkKCLNESEsEMNdws0LauFL+fkSMlC4AIpGYIgCDAwhJQpIkwkwjImXqsUACZmXJkZSkgF7MnHysUIuRZcmTJRYhi9pRqwcwcopgBEUBWeibkmVmo+oYVNi7X/P+ECmfK74eyoqz0gdG33wQWiiorGNSWsjp16kAqleLevXvw9/dXez5vUNu4cWNcuXJFOZVYkzfeeAP+/v7YsGEDUlNT8eabb6r8mhwVFYUffvgBb7/9NgDg/v37eP78uUoZFhYWkMvl+dYhk8ng7u6OqKgolXZHRUWhefPmBR90AXx9fXH//n3cv39fOVp75coVvHr1CnXq1FHud+/ePTx69Aju7u4AgL/++gsSiQQ+Pj7KfXKWJ58+fTpatWqFjRs35hvUEhFR/uovm4P6y+ZofM5+2bpil29paQnLJl3V0vMf281fj2aa14FQKCSIjZXA1dXc+L8IExFRkTCoLWX29vaYOnUqJk+eDIVCgbZt2yI+Ph5RUVGQyWTw9FRdhOKzzz5Dy5YtMX78eIwcORK2tra4cuUKDh48iGXLlin3CwwMxOzZs5GRkYElS5aolOHl5YWff/4ZTZs2RUJCAqZNmwZra2uVfapVq4bDhw+jTZs2kEqlcHJS/5V92rRpmD17NmrWrIlGjRohIiICFy5cUJkaXZiHDx+ic+fOWL9+PZo3b46AgADUr18fgYGBCA8PR1ZWFsaOHQt/f380bdpUmc/KygpDhw7FokWLkJCQgAkTJqB///5wc3NDTEwMVq1ahXfeeQfu7u6Ijo7GjRs3VG4cTURERERUkgSJBIKBf0QzdH3GonwetZGZN28eZs2ahdDQUPj6+qJr167Ys2cPqlevrrZvgwYNcPToUVy/fh3t2rVT3hw5Z8Qyx3vvvYe4uDikpKSgd+/eKs/99NNPePnyJRo3bowPPvgAEyZMULsuKCwsDAcPHoSHh4fGa3sBYMKECQgKClLegHnfvn3YtWuXysrHhcnMzER0dDRSUlIAZE+H2blzJ5ycnNC+fXsEBASgRo0a+PXXX1Xy1apVC3379sXbb7+Nt956Cw0aNMAPP/wAALCxscG1a9fw7rvvwtvbG6NHj8a4cePw0Ucfad0uIiIiIiIyDYJY0N12icqphIQEODg4ID4+ngtF6UihUCA2Nhaurq6c6ldK2AfGgf1gHNgPxoH9UPrKUh8Y6/e1nHY9/u5TyKzV12wp0bpT01H5k4VGd05KGqcfExERERER6ZsgKFduN2id5ZBp/zxDRERERERE5RpHaomIiIiIiPRNIgCGnuJdTm/pw5FaIiIiIiIiMlkcqSUiIiIiItI3XlNrMBypJSIiIiIiIpPFoJaIiIiIiIhMFqcfExERERER6ZkgkUAw8EJRhq7PWJTPoyYiIiIiIqIygSO1RERERERE+iZIsh+GrrMcKp9HTURERERERGUCg1oiIiIiIiIyWZx+TEREREREpG+CAEh4n1pD4EgtERERERERmSyO1BIREREREemZIEggGHjhJkPXZyzK51ETERERERFRmcCRWiIiIiIiIn2TlMI1tYauz0hwpJaIiIiIiIhMFoNaIiIiIiIiMlmcfkxERERERKRvgiT7Yeg6y6HyedRERERERERUJnCkloiIiIiISN8EIfth6DrLIY7UEhERERERkcliUEtEREREREQmi9OPiYiIiIiI9E0iyX4Yus5yqHweNREREREREZUJHKklIiIiIiLSN97Sx2DK51ETERERERFRmcCRWiIiIiIiIn2TCNkPQ9dZDnGkloiIiIiIiEwWg1oiIiIiIiIyWZx+TEREREREpG+CUAoLRXH6MREREREREZFJ4UgtERERERGRvgmC4UdOOVJLREREREREZFoY1BIREREREZHJ4vRjIiIiIiIifZNIsh+GrrMcKp9HTURERERERGUCR2qJiIiIiIj0jQtFGQxHaomIiIiIiMhkcaSWiIiIiIhI3wRJ9sPQdZZD5fOoiYiIiIiIqExgUEtEREREREQmi9OPiYiIiIiI9E0ohVv6cPoxERERERERkWnhSC0REREREZG+8ZY+BsORWiIiIiIiIjJZDGqJiIiIiIjIZHH6MRERERERkb7xPrUGUz6PmoiIiIiIiMoEjtQSERERERHpGxeKMhiO1BqJO3fuQBAEXLhwId99IiMjIQgCXr16ZbB26SolJQXvvvsuZDKZybSZiIiIiIhMD4NaI+Hh4YHHjx+jXr16pd0UvVi3bh2OHz+OkydP4vHjx3BwcCiVdpjSDwFEREREVIZIJKXzKIc4/dgIZGRkwNLSEm5ubqXdlELltLUwt27dgq+vb7GCdLlcDkEQICmnb04iIiq6tj2PqqWd2O2vt/L3WPiopXXPjNZb+UREVHSMFkpAYmIiAgMDYWtri8qVK2PJkiXo0KEDJk2aBACoVq0a5s2bhyFDhkAmk2H06NEapx/v3bsX3t7esLa2RseOHXHnzh2t2xAXF4eBAweiSpUqsLGxQf369bFp06YitTO/tgLAtm3bULduXUilUlSrVg1hYWHKPB06dEBYWBiOHTsGQRDQoUMHAMDLly8xZMgQODk5wcbGBt26dcONGzeU+dauXQtHR0fs2rULderUgVQqxb1795Ceno6pU6eiSpUqsLW1RYsWLRAZGanMd/fuXfTs2RNOTk6wtbVF3bp1sXfvXty5cwcdO3YEADg5OUEQBAwbNkzj+UpPT0dCQoLKAwAUCgUfxXiIoljqbSjvD/aBcTzYD4Z7CIKo9tBnP4gSidqjtI/Z1B58P5T+oyz1ARHAkdoSERQUhKioKOzatQuVKlVCcHAw/vnnHzRq1Ei5z6JFixAcHIzZs2drLOP+/fvo27cvxo0bh9GjR+Ps2bOYMmWK1m1IS0tDkyZN8Nlnn0Emk2HPnj344IMPULNmTTRv3lzrdmpq67lz59C/f3/MmTMHAwYMwMmTJzF27FhUqFABw4YNw/bt2/H555/jv//+w/bt25Uju8OGDcONGzewa9cuyGQyfPbZZ3j77bdx5coVWFhYAMi+Fvfrr7/G6tWrUaFCBbi6umL8+PG4cuUKNm/eDHd3d/z222/o2rUrLl26BC8vL4wbNw4ZGRk4duwYbG1tceXKFdjZ2cHDwwPbtm3Du+++i+joaMhkMlhbW2s8X6GhoQgJCVFLf/bsGdLS0rQ+7/SaQqFAfHw8RFHkaHspYR8YB/aDYdXwyFJLi42N1Vs/iH7qI7WxsbE6l1fe8P1Q+spSHyQmJpZ2EwokCgJEAy/cZOj6jAWDWj1LTEzEunXrsHHjRnTu3BkAEBERAXd3d5X9OnXqpBKk5h2FXb58OWrWrKkcAfXx8cGlS5fw9ddfa9WOKlWqYOrUqcrtTz75BPv378eWLVvQvHlzrdupqa2BgYHo3LkzZs2aBQDw9vbGlStX8M0332DYsGFwdnaGjY2NypTqnGA2KioKrVu3BgBs2LABHh4e2LFjB/r16wcAyMzMxA8//ICGDRsCAO7du4eIiAjcu3dP2bapU6di3759iIiIwIIFC3Dv3j28++67qF+/PgCgRo0ayrY6OzsDAFxdXeHo6Jjv+Zo+fTqCgoKU2wkJCfDw8ICLiwtkMpk2p5zyUCgUEAQBLi4uJv9P01SxD4wD+8Gwbt9X/2rj6uqqt34QzqtPNXZ1ddW5vPKG74fSV5b6wMrKqrSbQEaCQa2e3b59G5mZmcrRUABwcHCAj4/qL7tNmzYtsJyrV6+iRYsWKmmtWrXSuh1yuRwLFizAli1b8PDhQ2RkZCA9PR02NjZFaqemtl69ehW9evVSSWvTpg3Cw8Mhl8thZmam8XjMzc1VjqlChQrw8fHB1atXlWmWlpZo0KCBcvvSpUuQy+Xw9vZWKS89PR0VKlQAAEyYMAEff/wxDhw4gICAALz77rsqZWhDKpVCKpWqpUskEpP/wC9NOddE8xyWHvaBcWA/GI4oqo5S5L6eVh/9IOSZ7sjraYuO74fSV1b6wOjbLwiAYOA2cqSWDMnW1rZEy//mm2/w7bffIjw8HPXr14etrS0mTZqEjIyMIpdV0m3NzdraGkKuN2NSUhLMzMxw7tw5tWDZzs4OADBy5Eh06dIFe/bswYEDBxAaGoqwsDB88sknBms3EREZB30uCqUJg1giIuNj5D9vmJ4aNWrAwsICZ86cUabFx8fj+vXrRSrH19cXp0+fVkn766+/tM4fFRWFXr16YfDgwWjYsCFq1Kih0obitNPX1xdRUVFq9Xl7e2scpc3Jk5WVhb///luZFhcXh+joaNSpUyffuvz8/CCXyxEbG4tatWqpPHKvFu3h4YExY8Zg+/btmDJlCn788UcAUF7PK5fLCz0uIiIiIiIyPQxq9cze3h5Dhw7FtGnTcOTIEVy+fBkjRoyARCJRGYEszJgxY3Djxg1MmzYN0dHR2LhxI9auXat1fi8vLxw8eBAnT57E1atX8dFHH+Hp06d6aeeUKVNw+PBhzJs3D9evX8e6deuwbNkylWt4NbWnV69eGDVqFE6cOIGLFy9i8ODBqFKlitpU5ty8vb0RGBiIIUOGYPv27YiJicHp06cRGhqKPXv2AAAmTZqE/fv3IyYmBv/88w+OHDkCX19fAICnpycEQcDvv/+OZ8+eISkpSetzSERERESkM0FSOo9yqHwedQlbvHgxWrVqhR49eiAgIABt2rSBr69vkS5mr1q1KrZt24YdO3agYcOGWLFiBRYsWKB1/i+++AKNGzdGly5d0KFDB7i5uaF37956aWfjxo2xZcsWbN68GfXq1UNwcDDmzp2b7+1yckRERKBJkybo0aMHWrVqBVEUsXfvXuXKxwXlGzJkCKZMmQIfHx/07t0bZ86cQdWqVQFkj8KOGzcOvr6+6Nq1K7y9vfHDDz8AyF4wKyQkBJ9//jkqVaqE8ePHF3ziiIiIiIjIpAiiKIql3YiyLjk5GVWqVEFYWBhGjBhR2s3Jl6m00xASEhLg4OCA+Ph4rn6sI4VCgdjYWLi6uhr/Qg5lFPvAOLAfjAP7wTiwH0pfWeoDY/2+ltOux3t+gszWxrB1J6egcvcRRndOShoXiioB58+fx7Vr19C8eXPEx8dj7ty5AFDgNNvSYCrtJCIiIiIiyo9p/zxjxBYtWoSGDRsiICAAycnJOH78OCpWrKi38rt16wY7OzuNj6JMUy7pdhIREREREZUkjtSWAD8/P5w7d65E61i9ejVSU1M1Pufs7KxVGYZoJxERERFRuVQaCzeV04WiGNSaqCpVqpR2E4iIiIiIiEodg1oiIiIiIiJ9E4Tsh6HrLIfK5/g0ERERERERlQkcqSUiIiIiItI3iST7Yeg6y6HyedRERERERERUJjCoJSIiIiIiIpPF6cdERERERER6JgoCRAMv3GTo+owFR2qJiIiIiIjIZHGkloiIiIiISN8ESfbD0HWWQ+XzqImIiIiIiKhMYFBLREREREREJovTj4mIiIiIiPRMFCQQDTwd2ND1GYvyedRERERERERUJnCkloiIiIiISN8EIfth6DrLIY7UEhERERERkcniSC0REREREZGeiSiFa2rL6Zhl+TxqIiIiIiIiKhMY1BIREREREZHJ4vRjIiIiIiIifeNCUQbDkVoiIiIiIiIyWRypJSIiIiIi0jdBAAy8UBRHaomIiIiIiIhMDINaIiIiIiIiMlmcfkxERERERKRnoiBANPB0YEPXZyw4UktEREREREQmiyO1RERERERE+iZISmGhqPI5Zlk+j5qIiIiIiIjKBI7UEhERERER6ZkIASIMfE2tgeszFhypJSIiIiIiIpPFoJaIiIiIiIhMFqcfExERERER6ZkoSCAaeOEmQ9dnLMrnURMREREREVGZwJFaIiIiIiIifeMtfQymfB41ERERERERlQkMaomIiIiIiMhkcfoxERERERGRnomCAFEw8H1qDVyfseBILREREREREZksBrVERERERER6lnNLH0M/iuLYsWPo2bMn3N3dIQgCduzYUWieyMhING7cGFKpFLVq1cLatWuLfG5u3ryJ/fv3IzU1NftciWKRy8iNQS0REREREVE5lJycjIYNG+L777/Xav+YmBh0794dHTt2xIULFzBp0iSMHDkS+/fv1yp/XFwcAgIC4O3tjbfffhuPHz8GAIwYMQJTpkzR+Th4TS0REREREZG+CUL2w9B1AkhISFBJlkqlkEqlart369YN3bp107r4FStWoHr16ggLCwMA+Pr64sSJE1iyZAm6dOlSaP7JkyfD3Nwc9+7dg6+vrzJ9wIABCAoKUpZbVBypJSIiIiIiKkM8PDzg4OCgfISGhuql3FOnTiEgIEAlrUuXLjh16pRW+Q8cOICvv/4ab7zxhkq6l5cX7t69q3O7OFJLRERERERUhty/fx8ymUy5rWmUVhdPnjxBpUqVVNIqVaqEhIQEpKamwtrausD8ycnJsLGxUUt/8eJFsdrIkVoiIiIiIiJ9K41Fov5/oSiZTKby0FdQW1zt2rXD+vXrlduCIEChUGDhwoXo2LGjzuVypJaIiIiIiIgK5ebmhqdPn6qkPX36FDKZrNBRWgBYuHAhOnfujLNnzyIjIwOffvopLl++jBcvXiAqKkrndnGkloiIiIiISM9ECKXyKEmtWrXC4cOHVdIOHjyIVq1aaZW/Xr16uH79Otq2bYtevXohOTkZffv2xfnz51GzZk2d28WRWiIiIiIionIoKSkJN2/eVG7HxMTgwoULcHZ2RtWqVTF9+nQ8fPhQOWV4zJgxWLZsGT799FN8+OGH+PPPP7Flyxbs2bNH6zodHBwwc+ZMvR4Hg1oiIiIiIqJy6OzZsyrXsgYFBQEAhg4dirVr1+Lx48e4d++e8vnq1atjz549mDx5Mr799lu88cYbWL16tVa38wGAY8eOFfh8+/btdTiKMhjU3rlzB9WrV8f58+fRqFEjjftERkaiY8eOePnyJRwdHQssb+3atZg0aRJevXql97YWplq1apg0aRImTZpk8LpNlTb9T0RERERU0pSLNxm4zqLo0KEDRFHM9/m1a9dqzHP+/PmiNk2ZNy8h17185XK5TuWWuWtqPTw88PjxY9SrV6+0m0IlbNiwYejdu3dpN4OIiIiIiLTw8uVLlUdsbCz27duHZs2a4cCBAzqXW6ZGajMyMmBpaQk3NzejaIepKcl2Z2ZmwsLCokTKJiKi8mOPhY/KdvfM6CLl9+99DKL4elTgxG5/vbSLiEiNAEAo2YWbNNZpxBwcHNTS3nzzTVhaWiIoKAjnzp3TqVyjHqlNTExEYGAgbG1tUblyZSxZsgQdOnRQTsetVq0a5s2bhyFDhkAmk2H06NG4c+cOBEHAhQsXlOXs3bsX3t7esLa2RseOHXHnzp0it2XHjh3w8vKClZUVunTpgvv37yufmzNnDho1aoTVq1ejevXqsLKyUrYvPDxcpZxGjRphzpw5AABRFDFnzhxUrVoVUqkU7u7umDBhgsr+KSkp+PDDD2Fvb4+qVati1apVyuc6deqE8ePHq+z/7NkzWFpaqq1Kpomm8wcAJ06cQLt27WBtbQ0PDw9MmDABycnJynyPHz9G9+7dYW1tjerVq2Pjxo1qxyoIApYvX4533nkHtra2mD9/PgBg+fLlqFmzJiwtLeHj44Off/5ZmWfq1Kno0aOHcjs8PByCIGDfvn3KtFq1amH16tWYM2cO1q1bh507d0IQBAiCgMjISOV+t2/fRseOHWFjY4OGDRvi1KlThZ4PIiIybnkD2vzSiqJtz6PFyk9ERMVXqVIlREcX7UfK3Ix6pDYoKAhRUVHYtWsXKlWqhODgYPzzzz8q10ouWrQIwcHBmD17tsYy7t+/j759+2LcuHEYPXo0zp49iylTphSpHSkpKZg/fz7Wr18PS0tLjB07Fu+//77KvZRu3ryJbdu2Yfv27TAzM9Oq3G3btmHJkiXYvHkz6tatiydPnuDixYsq+4SFhWHevHmYMWMGtm7dio8//hj+/v7w8fHByJEjMX78eISFhSlvqPzLL7+gSpUq6NSpk1ZtyHv+bt26ha5du+LLL7/EmjVr8OzZM4wfPx7jx49HREQEAGDIkCF4/vw5IiMjYWFhgaCgIMTGxqqVPWfOHHz11VcIDw+Hubk5fvvtN0ycOBHh4eEICAjA77//juHDh+ONN95Ax44d4e/vj9WrV0Mul8PMzAxHjx5FxYoVERkZia5du+Lhw4e4desWOnToADc3N1y9ehUJCQnKdjk7O+PRo0cAgJkzZ2LRokXw8vLCzJkzMXDgQNy8eRPm5ppf8unp6UhPT1duJyQkAAAUCgUUCoVW55JUKRQKiKLI81eK2AfGgf2gP6JE82/x2pzbnH4QBPVrx9g3hsP3Q+krS31g7McgQgLRwGOIhq6vqP7991+VbVEU8fjxY3z11VfFWg/HaIPaxMRErFu3Dhs3bkTnzp0BABEREXB3d1fZr1OnTipBat5R2JyRwbCwMACAj48PLl26hK+//lrrtmRmZmLZsmVo0aIFAGDdunXw9fXF6dOn0bx5cwDZU3fXr18PFxcXrcu9d+8e3NzcEBAQAAsLC1StWlVZXo63334bY8eOBQB89tlnWLJkCY4cOQIfHx/07dsX48ePx86dO9G/f38A2RdzDxs2TOWC64LkPX8jR45EYGCgcjTcy8sLS5cuhb+/P5YvX447d+7g0KFDOHPmDJo2bQoAWL16Nby8vNTKHjRoEIYPH67cHjhwIIYNG6Y8nqCgIPz1119YtGgROnbsiHbt2iExMRHnz59HkyZNcOzYMUybNg07duwAkL3AV5UqVVCrVi0AgLW1NdLT0zVON586dSq6d+8OAAgJCUHdunVx8+ZN1K5dW+N5CA0NRUhIiFr6s2fPkJaWVthpJA0UCgXi4+MhiiIk+XwRpZLFPjAO7Af9Ef00j8pq+mE1r5x+qP5GFvLOz9MmP+kH3w+lryz1QWJiYmk3gYqoUaNGEARBbXGqli1bYs2aNTqXa7RB7e3bt5GZmakS5Dk4OMDHR/UfWk5glZ+rV68qg9Ec2t4cOIe5uTmaNWum3K5duzYcHR1x9epVZfs8PT2LFNACQL9+/RAeHo4aNWqga9euePvtt9GzZ0+V0cQGDRoo/xYEAW5ubsp/vlZWVvjggw+wZs0a9O/fH//88w/+++8/7Nq1S+s25D1/Fy9exL///osNGzYo03J+zYuJicH169dhbm6Oxo0bK5+vVasWnJycCi376tWryinOOdq0aYNvv/0WAODo6IiGDRsiMjISlpaWsLS0xOjRozF79mwkJSXh6NGj8PfX7tqn3OetcuXKALK/tOQX1E6fPl25hDmQPVLr4eEBFxcXyGQyreokVQqFAoIgwMXFxeT/aZoq9oFxYD/oT/eT27HXuq5K2tupl7XKm9MPMQ+eqFxTCwCurq56ayMVjO+H0leW+iDnkj8yHTExMSrbEokELi4uxe5Low1qtWVra1vaTQCguR0SiUTtV4jMzEzl3x4eHoiOjsahQ4dw8OBBjB07Ft988w2OHj2qXFQp7+JKgiCoTLUYOXIkGjVqhAcPHiAiIgKdOnWCp6enzu1OSkrCRx99pHZtLwBUrVoV169f17lsbXTo0AGRkZGQSqXw9/eHs7MzfH19ceLECRw9elTrqeO5z1vOqHVBU1SkUqlyCnduEonE5D/wS5MgCDyHpYx9YBzYD/rTI/2qznkFQUDkb/7sh1LG90PpKyt9YOztFwUBooEXijJ0fUVVlDilKIw2qK1RowYsLCxw5swZVK1aFQAQHx+P69evF+mmvL6+vmojl3/99VeR2pKVlYWzZ88qR2Wjo6Px6tUr+Pr6FpjPxcUFjx8/Vm4nJCSo/TphbW2Nnj17omfPnhg3bhxq166NS5cuqYyEFqR+/fpo2rQpfvzxR2zcuBHLli0r0rHl1bhxY1y5ckU5xTcvHx8fZGVlKacIA9nXE798+bLQsn19fREVFYWhQ4cq06KiolCnTh3ltr+/P9asWQNzc3N07doVQHagu2nTJly/fl3l3laWlpY638uKiIiIiIhK3tKlS7XeV9PAmjaMNqi1t7fH0KFDMW3aNDg7O8PV1RWzZ8+GRCLR+npRABgzZgzCwsIwbdo0jBw5EufOndN4E+GCWFhY4JNPPsHSpUthbm6O8ePHo2XLlmrXv+bVqVMnrF27Fj179oSjoyOCg4NVFpFau3Yt5HI5WrRoARsbG/zyyy+wtrYu8i8YOQtG2draok+fPkXKm9dnn32Gli1bYvz48Rg5ciRsbW1x5coVHDx4EMuWLUPt2rUREBCA0aNHY/ny5bCwsMCUKVNgbW1daL9MmzYN/fv3h5+fHwICArB7925s374dhw4dUu7Tvn17JCYm4vfff8dXX30FIDuofe+991C5cmV4e3sr961WrRr279+P6OhoVKhQQeMS4UREREREpUEUJBAFAy8UZeD6tLFkyRKt9hMEQeeg1viOOpfFixejVatW6NGjBwICAtCmTRv4+voWac511apVsW3bNuzYsQMNGzbEihUrsGDBgiK1w8bGBp999hkGDRqENm3awM7ODr/++muh+aZPnw5/f3/06NED3bt3R+/evVGzZk3l846Ojvjxxx/Rpk0bNGjQAIcOHcLu3btRoUKFIrVv4MCBMDc3x8CBA4s9H71BgwY4evQorl+/jnbt2sHPzw/BwcEqC3StX78elSpVQvv27dGnTx+MGjUK9vb2hdbdu3dvfPvtt1i0aBHq1q2LlStXIiIiQmX01cnJCfXr14eLi4vy+tf27dtDoVCoXU87atQo+Pj4oGnTpnBxcVFZjZqIiIiIiEpfTEyMVo/bt2/rXIcg5r3o04glJyejSpUqCAsLw4gRI0q7OUbjzp07qFmzJs6cOaP1tGV9evDgATw8PHDo0CHlStWmLiEhAQ4ODoiPj+dCUTpSKBSIjY2Fq6ur0V/zUlaxD4wD+8E4sB+MA/uh9JWlPjDW72s57bp+5hjs7ewMWndiUhK8m7U3unNS0ox2+jEAnD9/HteuXUPz5s0RHx+PuXPnAgB69epVyi0zDpmZmYiLi8MXX3yBli1bGiyg/fPPP5GUlIT69evj8ePH+PTTT1GtWrUiXetMRERERFSWiRAgwsALRRm4Pl08ePAAu3btwr1795CRkaHy3OLFi3Uq06iDWgBYtGgRoqOjYWlpiSZNmuD48eOoWLGi3srv1q0bjh8/rvG5GTNmYMaMGXqrS9+ioqLQsWNHeHt7Y+vWrSrPHT9+HN26dcs3b1JSks71ZmZmYsaMGbh9+zbs7e3RunVrbNiwQW2lZiIiIiIiohyHDx/GO++8gxo1auDatWuoV68e7ty5A1EUizVAp3NQ+/PPP2PFihWIiYnBqVOn4OnpifDwcFSvXl1vI6l+fn44d+6cXsrKz+rVq5GamqrxOWdn5xKtu7g6dOigdsugHE2bNsWFCxdKpN4uXbqgS5cuJVI2EREREVFZwIWi1E2fPh1Tp05FSEgI7O3tsW3bNri6uiIwMFB55xNd6BTULl++HMHBwZg0aRLmz5+vvK2Ko6MjwsPDTWp6cJUqVUq7CSXC2to639vyEBERERERGdrVq1exadMmAIC5uTlSU1NhZ2eHuXPnolevXvj44491KlenUP67777Djz/+iJkzZ6rcoqZp06a4dOmSTg0hIiIiIiIqK0RBKJWHMbO1tVVeR1u5cmXcunVL+dzz5891LlenkdqYmBj4+fmppUulUiQnJ+vcGCIiIiIiIiqbWrZsiRMnTsDX1xdvv/02pkyZgkuXLmH79u1o2bKlzuXqFNRWr14dFy5cgKenp0r6vn374Ovrq3NjiIiIiIiIqGxavHixcsHakJAQJCUl4ddff4WXl5fOKx8DOga1QUFBGDduHNLS0iCKIk6fPo1NmzYhNDQUq1ev1rkxREREREREZQFv6aOuRo0ayr9tbW2xYsUKvZSrU1A7cuRIWFtb44svvkBKSgoGDRoEd3d3fPvtt3j//ff10jAiIiIiIiIqO0aOHInBgwejQ4cOei23yEFtVlYWNm7ciC5duiAwMBApKSlISkqCq6urXhtGRERERERkqnhLH3XPnj1D165d4eLigvfffx+DBw9Gw4YNi11ukY/a3NwcY8aMQVpaGgDAxsaGAS0REREREREVaOfOnXj8+DFmzZqFM2fOoHHjxqhbty4WLFiAO3fu6FyuTqF88+bNcf78eZ0rJSIiIiIiovLHyckJo0ePRmRkJO7evYthw4bh559/Rq1atXQuU6draseOHYspU6bgwYMHaNKkCWxtbVWeb9Cggc4NIiIiIiIiMnVcKKpgmZmZOHv2LP7++2/cuXMHlSpV0rksnYLanMWgJkyYoEwTBAGiKEIQBMjlcp0bRERERERERGXTkSNHsHHjRmzbtg0KhQJ9+/bF77//jk6dOulcpk5BbUxMjM4VEhERERERlXUiSmGhKN2uLjWYKlWq4MWLF+jatStWrVqFnj17QiqVFrtcnYJaT0/PYldMRERERERE5cecOXPQr18/ODo66rVcnYLa9evXF/j8kCFDdGoMERERERERlU2jRo0qkXJ1CmonTpyosp2ZmYmUlBRYWlrCxsaGQS0REREREZVrXCjKcHSadP3y5UuVR1JSEqKjo9G2bVts2rRJ320kIiIiIiIi0kinkVpNvLy88NVXX2Hw4MG4du2avoolIiIiIiIyOaIgGH6hKIEjtcVmbm6OR48e6bNIIiIiIiIionzpNFK7a9culW1RFPH48WMsW7YMbdq00UvDiIiIiIiITBWvqdXs559/xooVKxATE4NTp07B09MT4eHhqF69Onr16qVTmToFtb1791bZFgQBLi4u6NSpE8LCwnRqCBEREREREZVdy5cvR3BwMCZNmoT58+dDLpcDABwdHREeHm7YoFahUOhUGREREREREZVP3333HX788Uf07t0bX331lTK9adOmmDp1qs7l6nRN7dy5c5GSkqKWnpqairlz5+rcGCIiIiIiorIge6Eowz+MWUxMDPz8/NTSpVIpkpOTdS5Xp6A2JCQESUlJaukpKSkICQnRuTFERERERERUNlWvXh0XLlxQS9+3bx98fX11Llen6ceiKELQ8CvAxYsX4ezsrHNjiIiIiIiIygJRFCCKBl4oysD1FVVQUBDGjRuHtLQ0iKKI06dPY9OmTQgNDcXq1at1LrdIQa2TkxMEQYAgCPD29lYJbOVyOZKSkjBmzBidG0NERERERERl08iRI2FtbY0vvvgCKSkpGDRoENzd3fHtt9/i/fff17ncIgW14eHhEEURH374IUJCQuDg4KB8ztLSEtWqVUOrVq10bgwRERERERGVPVlZWdi4cSO6dOmCwMBApKSkICkpCa6ursUuu0hB7dChQwFkz4Vu3bo1LCwsit0AIiIiIiKiskcCUbcljIpVp7EyNzfHmDFjcPXqVQCAjY0NbGxs9FO2Lpn8/f2Vf6elpSEjI0PleZlMVrxWERERERERUZnSvHlznD9/Hp6ennotV6egNiUlBZ9++im2bNmCuLg4tedzbqJLRERERERUHokQIMLAC0UZuL6iGjt2LKZMmYIHDx6gSZMmsLW1VXm+QYMGOpWrU1A7bdo0HDlyBMuXL8cHH3yA77//Hg8fPsTKlStVbqJLREREREREBEC5GNSECROUaYIgKO+uo+vgqE5B7e7du7F+/Xp06NABw4cPR7t27VCrVi14enpiw4YNCAwM1KkxREREREREZQFHatXFxMSUSLk6BbUvXrxAjRo1AGRfP/vixQsAQNu2bfHxxx/rr3VERERERERUJuj7WtocOgW1NWrUQExMDKpWrYratWtjy5YtaN68OXbv3g1HR0c9N5GIiIiIiIhM3fr16wt8fsiQITqVq1NQO3z4cFy8eBH+/v74/PPP0bNnTyxbtgyZmZlYvHixTg0hIiIiIiIqKzj9WN3EiRNVtjMzM5GSkgJLS0vY2NgYNqidPHmy8u+AgABcu3YN586dQ61atXResYqIiIiIiIjKrpcvX6ql3bhxAx9//DGmTZumc7k6BbW5paWlwdPTs8TmRxMREREREZkajtRqx8vLC1999RUGDx6Ma9eu6VSGRJdMcrkc8+bNQ5UqVWBnZ4fbt28DAGbNmoWffvpJp4YQERERERFR+WNubo5Hjx7pnl+XTPPnz8e6deuwcOFCjBo1Spler149hIeHY8SIETo3iIiIiIiIiMqeXbt2qWyLoojHjx9j2bJlaNOmjc7l6hTUrl+/HqtWrULnzp0xZswYZXrDhg11HjImIiIiIiIqK0RRgCgaePqxgesrqt69e6tsC4IAFxcXdOrUCWFhYTqXq1NQ+/DhQ9SqVUstXaFQIDMzU+fGEBERERERUdmkUChKpFydrqmtU6cOjh8/rpa+detW+Pn5FbtRREREREREpixnoShDP4zZ3LlzkZKSopaempqKuXPn6lyuTiO1wcHBGDp0KB4+fAiFQoHt27cjOjoa69evx++//65zY4iIiIiIiKhsCgkJwZgxY2BjY6OSnpKSgpCQEAQHB+tUbpFGam/fvg1RFNGrVy/s3r0bhw4dgq2tLYKDg3H16lXs3r0bb775pk4NISIiIiIiKis4UqtOFEUIgnobL168CGdnZ53LLdJIrZeXFx4/fgxXV1e0a9cOzs7OuHTpEipVqqRzA4iIiIiIiKjscnJygiAIEAQB3t7eKoGtXC5HUlKSygLERVWkoFYURZXtP/74A8nJyTpXTkRERERERGVbeHg4RFHEhx9+iJCQEDg4OCifs7S0RLVq1dCqVSudy9fpmtoceYNcIiIiIiIiQqlMBzbW6cdDhw4FAFSvXh2tW7eGhYWFXssvUlCbM2ScN42IiIiIiIioIP7+/sq/09LSkJGRofK8TCbTqdwiTz8eNmwYpFKpsiFjxoyBra2tyn7bt2/XqTFERERERERlgQgBosiR2txSUlLw6aefYsuWLYiLi1N7Xi6X61RukYLanGHjHIMHD9apUiIiIiIiIipfpk2bhiNHjmD58uX44IMP8P333+Phw4dYuXIlvvrqK53LLVJQGxERoXNFRERERCWlbc+jKtsndr+e4nb71i2IoojExES4uroq0/dY+Kjk6Z4ZXbKNJCIq53bv3o3169ejQ4cOGD58ONq1a4datWrB09MTGzZsQGBgoE7lFuk+tUQ5tm7divr168Pa2hoVKlRAQECAciXs1atXw9fXF1ZWVqhduzZ++OEHlbyfffYZvL29YWNjgxo1amDWrFnIzMxUPn/x4kV07NgR9vb2kMlkaNKkCc6ePat8ftu2bahbty6kUimqVauGsLAwlfKrVauGBQsW4MMPP4S9vT2qVq2KVatWleDZICIiY5MT5N6+dUslPeb2bQDqAS0Rkb4pIJTKw5i9ePECNWrUAJB9/eyLFy8AAG3btsWxY8d0LrdYqx9T+fT48WMMHDgQCxcuRJ8+fZCYmIjjx49DFEVs2LABwcHBWLZsGfz8/HD+/HmMGjUKtra2yunr9vb2WLt2Ldzd3XHp0iWMGjUK9vb2+PTTTwEAgYGB8PPzw/Lly2FmZoYLFy4oV0g7d+4c+vfvjzlz5mDAgAE4efIkxo4diwoVKmDYsGHKNoaFhWHevHmYMWMGtm7dio8//hj+/v7w8dH8JSY9PR3p6enK7YSEBACAQqGAQqEoidNY5ikUCoiiyPNXitgHxoH9YBiCoH5HhpxzD2SvC5LzUCgUECXqv+v/LvXF26mXS7yt5RnfD6WvLPVBWTiG8qZGjRqIiYlB1apVUbt2bWzZsgXNmzfH7t274ejoqHO5gsj78lAR/fPPP2jSpAnu3LkDT09Pledq1aqFefPmYeDAgcq0L7/8Env37sXJkyc1lrdo0SJs3rxZORork8nw3XffqV3DDWQHvM+ePcOBAweUaZ9++in27NmDy5ezv4hUq1YN7dq1w88//wwg+4uMm5sbQkJC8r2p85w5cxASEqKWfv36ddjb2xd0OigfCoUC8fHxcHBwgETDl0cqeewD48B+MIzP5v2nlvb1rHp48vgxAEAEkJqSAmsbG1SuXBlnemv+f9Bsx4qSbGa5x/dD6StLfZCYmAhvb2/Ex8frvGpuSUhISICDgwOO/XMbdnaG/R6ZlJSI9o1rGN05ybFkyRKYmZlhwoQJOHToEHr27AlRFJGZmYnFixdj4sSJOpXLkVoqsoYNG6Jz586oX78+unTpgrfeegvvvfceLC0tcevWLYwYMQKjRo1S7p+VlaVyg+Vff/0VS5cuxa1bt5CUlISsrCyVN11QUBBGjhyJn3/+GQEBAejXrx9q1qwJALh69Sp69eql0p42bdogPDwccrkcZmZmAIAGDRoonxcEAW5uboiNjc33mKZPn46goCDldkJCAjw8PODi4mKUHwimQKFQQBAEuLi4mPw/TVPFPjAO7AfDuH1f/SuNq6srkpOSAGT/wAlRhL2dHVxdXSGcV79+lqO0JY/vh9JXlvrAysqqtJtARTR58mTl3wEBAbh27RrOnTuHWrVqqXx/LyoGtVRkZmZmOHjwIE6ePIkDBw7gu+++w8yZM7F7924AwI8//ogWLVqo5QGAU6dOITAwECEhIejSpQscHBywefNmleti58yZg0GDBmHPnj34448/MHv2bGzevBl9+vTRuo15b+gsCEKBU1SkUqnyVlW5SSQSk//AL02CIPAcljL2gXFgP5S847s6KK+jzb1IVM1atZTX1QqCgBo1a0IikaBH+lUAr6+t5SJRhsP3Q+krK31g7O0XxVK4pY+B6yuOtLQ0eHp6qs381AWDWtKJIAho06YN2rRpg+DgYHh6eiIqKgru7u64fft2viuXnTx5Ep6enpg5c6Yy7e7du2r7eXt7w9vbG5MnT8bAgQMRERGBPn36wNfXF1FRUSr7RkVFwdvbWxk4ExFR+ZQ7mM2tRs2aUCgUGmfsMJglIjIcuVyOBQsWYMWKFXj69CmuX7+uXDi2WrVqGDFihE7lGvfPG2SU/v77byxYsABnz57FvXv3sH37djx79gy+vr4ICQlBaGgoli5diuvXr+PSpUuIiIjA4sWLAQBeXl64d+8eNm/ejFu3bmHp0qX47bfflGWnpqZi/PjxiIyMxN27dxEVFYUzZ87A19cXADBlyhQcPnwY8+bNw/Xr17Fu3TosW7YMU6dOLZVzQURERERE2pk/fz7Wrl2LhQsXwtLSUpler149rF69WudyOVJLRSaTyXDs2DGEh4cjISEBnp6eCAsLQ7du3QAANjY2+OabbzBt2jTY2tqifv36mDRpEgDgnXfeweTJkzF+/Hikp6eje/fumDVrFubMmQMge5pyXFwchgwZgqdPn6JixYro27evchGnxo0bY8uWLQgODsa8efNQuXJlzJ07V2XlYyIiIiKi0iYCEA18ix1jXwF4/fr1WLVqFTp37qyygGvDhg1x7do1ncvl6sdEGuSsWmesK8eZgpypfq6urkZ/zUtZxT4wDuwH48B+MA7sh9JXlvrAWL+v5bQr8lwM7OwM266kpAR0aFLd6M5JDmtra1y7dg2enp6wt7fHxYsXUaNGDVy5cgXNmzdH0v8v7ldUpv1KJiIiIiIiMkI5C0UZ+mHM6tSpg+PHj6ulb926FX5+fjqXy+nHREREREREVOKCg4MxdOhQPHz4EAqFAtu3b0d0dDTWr1+P33//XedyOVJLREREREREJa5Xr17YvXs3Dh06BFtbWwQHB+Pq1avYvXs33nzzTZ3L5UgtERERERGRnokQSmGhKOOcfnz79m1Ur14dgiCgXbt2OHjwoF7L50gtERERERERlRgvLy88e/ZMuT1gwAA8ffpUb+UzqCUiIiIiItIzLhT1Wt4b7uzduxfJycl6K59BLREREREREZksXlNLRERERESkZyIARSnUaYwEQYAgCGpp+sKgloiIiIiIiEqMKIoYNmwYpFIpACAtLQ1jxoyBra2tyn7bt2/XqXwGtURERERERFRihg4dqrI9ePBgvZbPoJaIiIiIiEjPSmPhJmNdKCoiIqJEy+dCUURERERERGSyOFJLRERERESkZyIEiDDwSK2B6zMWHKklIiIiIiIik8WgloiIiIiIiEwWpx8TERERERHpGReKMhyO1BIREREREZHJ4kgtERERERGRnnGhKMPhSC0RERERERGZLI7UEhERERER6ZlCzH4Yus7yiCO1REREREREZLIY1BIREREREZHJ4vRjIiIiIiIiPeNCUYbDkVoiIiIiIiIyWRypJSIiIiIi0jNRFCCKBh6pNXB9xoIjtURERERERGSyGNQSERERERGRyeL0YyIiIiIiIj0TxeyHoessjzhSS0RERERERCaLI7VERERERER6poAAhYFvsWPo+owFR2qJiIiIiIjIZDGoJSIiIiIiIpPF6cdERERERER6xvvUGg5HaomIiIiIiMhkcaSWiIiIiIhIz3hLH8PhSC0RERERERGZLI7UEhERERER6ZkIAaKBb7Fj6PqMBUdqiYiIiIiIyGQxqCUiIiIiIirHvv/+e1SrVg1WVlZo0aIFTp8+ne++a9euhSAIKg8rKysDtlYdpx8TERERERHpmULMfhi6zqL69ddfERQUhBUrVqBFixYIDw9Hly5dEB0dDVdXV415ZDIZoqOjlduCULrTnjlSS0REREREVE4tXrwYo0aNwvDhw1GnTh2sWLECNjY2WLNmTb55BEGAm5ub8lGpUiUDtlgdg1oiIiIiIiJ9EwWIBn5AzB4xTUhIUHmkp6drbGJGRgbOnTuHgIAAZZpEIkFAQABOnTqV76ElJSXB09MTHh4e6NWrFy5fvqzfc1dEDGqJiIiIiIjKEA8PDzg4OCgfoaGhGvd7/vw55HK52khrpUqV8OTJE415fHx8sGbNGuzcuRO//PILFAoFWrdujQcPHuj9OLTFa2qJiIiIiIjKkPv370Mmkym3pVKp3spu1aoVWrVqpdxu3bo1fH19sXLlSsybN09v9RQFg1oiIiIiIiI9E8Xsh6HrBLIXcsod1OanYsWKMDMzw9OnT1XSnz59Cjc3N63qtLCwgJ+fH27evFnk9uoLpx8TERERERGVQ5aWlmjSpAkOHz6sTFMoFDh8+LDKaGxB5HI5Ll26hMqVK5dUMwvFkVoiIiIiIiI9U0CAAoa91Y0u9QUFBWHo0KFo2rQpmjdvjvDwcCQnJ2P48OEAgCFDhqBKlSrK63Lnzp2Lli1bolatWnj16hW++eYb3L17FyNHjtTrsRQFg1oiIiIiIqJyasCAAXj27BmCg4Px5MkTNGrUCPv27VMuHnXv3j1IJK8n+L58+RKjRo3CkydP4OTkhCZNmuDkyZOoU6dOaR0Cg1oiIiIiIiJ9K81raotq/PjxGD9+vMbnIiMjVbaXLFmCJUuW6FZRCeE1tURERERERGSyGNQSERERERGRyeL0YyIiIiIiIj0TRQGiaNiFogxdn7FgUEtERERlRtueR5V/n9jtn+9+eyx8lH93z4wu0TYREVHJ4vRjMlpbt25F/fr1YW1tjQoVKiAgIADJyckAgNWrV8PX1xdWVlaoXbs2fvjhB2W+Dz/8EA0aNEB6ejoAICMjA35+fhgyZEipHAcRERlG7oBW03aO3AGtpm0iIn1QiKXzKI84UktG6fHjxxg4cCAWLlyIPn36IDExEcePH4coitiwYQOCg4OxbNky+Pn54fz58xg1ahRsbW0xdOhQLF26FA0bNsTnn3+OJUuWYObMmXj16hWWLVuWb33p6enKIBgAEhISAGTffFqhUJT48ZZFCoUCoijy/JUi9oFxYD8Yhn/vYxA0zLrLOe85/bDHtj4Eifpv+uwfw+D7ofSVpT4oC8dA+sGglozS48ePkZWVhb59+8LT0xMAUL9+fQDA7NmzERYWhr59+wIAqlevjitXrmDlypUYOnQo7Ozs8Msvv8Df3x/29vYIDw/HkSNHIJPJ8q0vNDQUISEhaunPnj1DWlpaCRxh2adQKBAfHw9RFFXubUaGwz4wDuwHw6jhkaUxPTY2FsDrfoCfD0QNX4Rz9qOSxfdD6StLfZCYmFjaTSAjIYiioe+eRFQ4uVyOLl264PTp0+jSpQveeustvPfee7C0tISdnR2sra1VPoizsrLg4OCAp0+fKtNmzJiB0NBQfPbZZ/jqq68KrE/TSK2HhwdevnxZYDBM+VMoFHj27BlcXFxM/p+mqWIfGAf2g+H49z6mlnZ0R3sAqv2wz7a+2n5vp14u8fYR3w/GoCz1QUJCApycnBAfH29U39cSEhLg4OCAXw6/gI2dYduVkpSAwZ2dje6clDSO1JJRMjMzw8GDB3Hy5EkcOHAA3333HWbOnIndu3cDAH788Ue0aNFCLU8OhUKBqKgomJmZ4ebNm4XWJ5VKIZVK1dIlEonJf+CXJkEQeA5LGfvAOLAfDCPvqp95F4rK6Qchz0gtF4oyLL4fSl9Z6QNTbz/pD4NaMlqCIKBNmzZo06YNgoOD4enpiaioKLi7u+P27dsIDAzMN+8333yDa9eu4ejRo+jSpQsiIiIwfPhwA7aeiIgMraDVjnNjEEtEhiBCgAgD39LHwPUZCwa1ZJT+/vtvHD58GG+99RZcXV3x999/49mzZ/D19UVISAgmTJgABwcHdO3aFenp6Th79ixevnyJoKAgnD9/HsHBwdi6dSvatGmDxYsXY+LEifD390eNGjVK+9CIiIiIiEiPGNSSUZLJZDh27BjCw8ORkJAAT09PhIWFoVu3bgAAGxsbfPPNN5g2bRpsbW1Rv359TJo0CWlpaRg8eDCGDRuGnj17AgBGjx6NPXv24IMPPsCxY8dUpikTEREREZUEBQx/i53yuh40g1oySr6+vti3b1++zw8aNAiDBg3S+Nzly+qLfezcuVNvbSMiIiIiIuPBq6uJiIiIiIjIZHGkloiIiIiISM9EMfth6DrLI47UEhERERERkcniSC0REREREZGecaTWcDhSS0RERERERCaLQS0RERERERGZLE4/JiIiIiIi0jOFKEAhCgavszziSC0RERERERGZLI7UEhERERER6RkXijIcjtQSERERERGRyeJILRERERERkZ5xpNZwOFJLRPR/7d15fA7n/v/x9x1kkc0WEYQgREQaQTloS0mLlkOr5bRa4ViqqDqWqpZYuigVW9VSS2hPFa3W0YNuGkpatava0m+stTS0JaS25J7fH36Z4yYi4nYv8Xo+HvN4uOeemesz88ktue7PNdcAAADAbdGpBQAAAAC4LYYfAwAAAICdGYZkZfixQ1CpBQAAAAC4LSq1AAAAAGBnhmGRYVgc3ubdiEotAAAAAMBt0akFAAAAALgthh8DAAAAgJ3xnFrHoVILAAAAAHBbVGoBAAAAwM6sTnikj6PbcxVUagEAAAAAbotKLQAAAADYGffUOg6VWgAAAACA26JTCwAAAABwWww/BgAAAAA7Y/ix41CpBQAAAAC4LSq1AAAAAGBnPNLHcajUAgAAAADcFp1aAAAAAIDbYvgxAAAAANgZE0U5DpVaAAAAAIDbolILAAAAAHZmtV5ZHN3m3YhKLQAAAADAbVGpBQAAAAA7455ax6FSCwAAAABwW3RqAQAAAABui+HHAAAAAGBnDD92HCq1AAAAAAC3RaUWAAAAAOzMKsnq4MrpXfpEHyq1AAAAAAD3RacWAAAAAOC2GH4MAAAAAHZmGIYMB8/c5Oj2XAWVWgAAAACA26JSCwAAAAB2xiN9HIdKLQAAAADAbdGpBQAAAAC4LYYfAwAAAICdGVbJ6uAHxxp36YNqqdQCAAAAANwWlVoAAAAAsDMminIcKrUAAAAAALfldp3agwcPymKxaPv27TfcZs2aNbJYLDp9+rTD4roV+Ylv1KhRqlOnjsNisrdRo0YpODhYFotFy5Ytc3Y4AAAAgENZDecsdyO369SGhobq+PHjql27trNDKbDGjRvr+PHjCgwMvOE2gwcP1urVq2/puGFhYZo8efJtRmcrP18iXGvPnj0aPXq0Zs2apePHj6t169Z2jelW0KkGAAAACje3uqf20qVL8vT0VLly5Zwdym3Jzzn4+fnJz8/PQRHZV1pamiSpXbt2slgsBT7O5cuXVaxYMXuFBQC4i9zXdq3N6+/+c7+TIrnzVhSLsF1RKlCP/rbROcEAgBM4tVJ79uxZde7cWb6+vgoJCdGkSZPUrFkzDRgwQNKVyuNrr72mLl26KCAgQL169cq1crhy5UrVqFFDPj4+evDBB3Xw4MF8x3Do0CG1bdtWJUuWlK+vr6KiorRy5Urz/Z9//lmtW7eWn5+fgoOD9eyzz+rUqVPm+82aNdMLL7ygAQMGqGTJkgoODtbs2bOVmZmpbt26yd/fX+Hh4Vq1apW5T0GGH3ft2lXt27fXhAkTFBISotKlS6tv3766fPmyGcehQ4f0r3/9SxaLxexM/v7773rqqadUoUIFFS9eXNHR0froo49s2rJarRo/frzCw8Pl5eWlSpUq6Y033pAkValSRZIUGxsri8WiZs2a5Xk9R40apbZt20qSPDw8zDisVqvGjBmjihUrysvLS3Xq1NEXX3xh7peT18WLF6tp06by9vbWhx9+KEmaM2eOIiMj5e3trZo1a2r69OnmfpcuXVK/fv0UEhIib29vVa5cWWPHjpV05edHkh577DFZLBbzdW4uXryojIwMmyUnbpaCL4ZhOD2Gu30hB66xkAfHLvf/fY0sFsNmafbY2kKbB8PDw3Y5fdbpMeUZbyHNgzsthSkHrixnoihHL3cjp1ZqBw4cqJSUFC1fvlzBwcFKSEjQ1q1bbTpzEyZMUEJCgkaOHJnrMY4cOaLHH39cffv2Va9evbR582YNGjQo3zH07dtXly5d0nfffSdfX1/t3r3brJCePn1azZs3V48ePTRp0iSdP39eQ4cOVceOHfXtt9+ax1iwYIFeeuklbdy4UYsXL9bzzz+vzz77TI899pheeeUVTZo0Sc8++6wOHz6s4sWLF+xiSUpOTlZISIiSk5P1f//3f+rUqZPq1Kmjnj176tNPP1VMTIx69eqlnj17mvtcuHBB9erV09ChQxUQEKAVK1bo2WefVbVq1dSgQQNJ0rBhwzR79mxNmjRJ9913n44fP669e/dKkjZu3KgGDRrom2++UVRUlDw9PfOMcfDgwQoLC1O3bt10/Phxc/2UKVOUmJioWbNmKTY2VvPmzdPf//537dq1S9WrVze3e/nll5WYmKjY2FizY5uQkKBp06YpNjZW27ZtU8+ePeXr66v4+HhNnTpVy5cv15IlS1SpUiUdOXJER44ckSRt2rRJZcuWVVJSklq1aqUiRYrcMO6xY8dq9OjR160/efKkLly4kI/s4FpWq1VnzpyRYRjy8HC7Ox0KBXLgGsiD41UNzcplraHTp08XyjwYsRHXrUtPT3dCJDfH58H5ClMOzp496+wQ4CKc1qk9e/asFixYoIULF6pFixaSpKSkJJUvX95mu+bNm9t0Uq+tws6YMUPVqlVTYmKiJCkiIkI7d+7UuHHj8hXH4cOH1aFDB0VHR0uSqlatar6X05F68803zXXz5s1TaGioUlNTVaNGDUlSTEyMhg8fLulKB/Gtt95SmTJlzM5lQkKCZsyYoZ9++kl/+9vf8hVXbkqWLKlp06apSJEiqlmzph599FGtXr1aPXv2VKlSpVSkSBH5+/vbDG2uUKGCBg8ebL5+4YUX9OWXX2rJkiVq0KCBzp49qylTpmjatGmKj4+XJFWrVk333XefJCkoKEiSVLp06XwN+/bz81OJEiUkyWb7CRMmaOjQofrHP/4hSRo3bpySk5M1efJkvfvuu+Z2AwYM0OOPP26+HjlypBITE811VapU0e7duzVr1izFx8fr8OHDql69uu677z5ZLBZVrlzZ3Dcn9hIlStw09mHDhmngwIHm64yMDIWGhiooKEgBAQE3PW9cz2q1ymKxKCgoyO1/aborcuAayIPj7T9y/Z83FouhEiVKFMo8WLbtu25d2bJlnRDJzfF5cL7ClANvb29nh5Anw2rIcPDMTY5uz1U4rVO7f/9+Xb582awWSlJgYKAiImy/baxfv36ex9mzZ48aNmxos65Ro0b5jqN///56/vnn9dVXXykuLk4dOnTQPffcI0nasWOHkpOTc723NS0tzezU5mwvSUWKFFHp0qXNTrIkBQcHS7rxt6ZXH/+ZZ57RzJkzc90uKirKptoYEhKinTt35nl+2dnZevPNN7VkyRIdPXpUly5d0sWLF82K8Z49e3Tx4kXzi4U7ISMjQ8eOHVOTJk1s1jdp0kQ7duywWXd1vjMzM5WWlqbu3bvbVJ+zsrLMSba6du2qhx56SBEREWrVqpXatGmjhx9++JZj9PLykpeX13XrPTw83P4/fGeyWCxcQycjB66BPDjWuuXNrrundu2yB5Senl4o89Dm4h6b+2ofvXx9J9eV8HlwvsKSA3ePH/bj8hNF+fr63tHj9+jRQy1bttSKFSv01VdfaezYsUpMTNQLL7ygc+fOqW3btrlWfUNCQsx/XzuZkcVisVl39X2lubn6/uC8qoK5tXOzewnefvttTZkyRZMnT1Z0dLR8fX01YMAAXbp0SZLk4+OT5/6OdnW+z507J0maPXv2dV9c5HTu69atqwMHDmjVqlX65ptv1LFjR8XFxemTTz5xXNAAAJez/vOmNq9d/d672+XqHVkAuJOc9vVG1apVVaxYMW3atMlcd+bMGaWmpt7ScSIjI7Vxo+0Mfxs2bLilY4SGhqp379769NNPNWjQIM2ePVvSlQ7Trl27FBYWpvDwcJvFnp3tq497O8OFPD09lZ2dbbMuJSVF7dq10zPPPKOYmBhVrVrV5hpXr15dPj4+N3x8UM49tNce91YEBASofPnySklJuS62WrVq3XC/4OBglS9fXvv377/u+udMYJVz/E6dOmn27NlavHixli5dqj/++EPSlS8Cbid2AAAAoCB4Tq3jOK1T6+/vr/j4eA0ZMkTJycnatWuXunfvbjNjbn707t1bv/zyi4YMGaJ9+/Zp4cKFmj9/fr73HzBggL788ksdOHBAW7duVXJysiIjIyVdmUTqjz/+0FNPPaVNmzYpLS1NX375pbp16+aSHaWwsDB99913Onr0qDlDc/Xq1fX111/r+++/1549e/Tcc8/pt99+M/fx9vbW0KFD9dJLL+n9999XWlqaNmzYoLlz50q6ck+Oj4+PvvjiC/322286c+ZMgWIbMmSIxo0bp8WLF2vfvn16+eWXtX37dr344ot57jd69GiNHTtWU6dOVWpqqnbu3KmkpCRNnDhRkjRx4kR99NFH2rt3r1JTU/Xxxx+rXLly5n29YWFhWr16tU6cOKE///yzQLEDAAAAcF1OHYg+ceJENWrUSG3atFFcXJyaNGliProlvypVqqSlS5dq2bJliomJ0cyZM20mdrqZ7Oxs9e3bV5GRkWrVqpVq1KhhPjImp7qYnZ2thx9+WNHR0RowYIBKlCjhkmP4x4wZo4MHD6patWrmJEnDhw9X3bp11bJlSzVr1kzlypVT+/btbfYbMWKEBg0apISEBEVGRqpTp07m/b9FixbV1KlTNWvWLJUvX17t2rUrUGz9+/fXwIEDNWjQIEVHR+uLL77Q8uXLbWY+zk2PHj00Z84cJSUlKTo6Wk2bNtX8+fPNSq2/v7/Gjx+v+vXr695779XBgwe1cuVKMz+JiYn6+uuvFRoaqtjY2ALFDgAAANwqHunjOBbDcJ1Tz8zMVIUKFZSYmKju3bs7OxzcxTIyMhQYGKgzZ84w+3EBWa1Wpaenq2zZsi75JdDdgBy4BvLgGsiDayAPzleYcuCqf6/lxDVqwZ/yLu7YuC78laFR8SVd7prcaU6dKGrbtm3au3evGjRooDNnzmjMmDGSVOBqIAAAAAC4AqvVkNXBN7k6uj1X4fSvZyZMmKCYmBjFxcUpMzNT69atU5kyZex2/NatW8vPzy/X5VaGKeN/bnQ9/fz8tG7dOmeHBwAAAOAu4tRKbWxsrLZs2XJH25gzZ47Onz+f63ulSpW6o20XVlc/guhaFSpUcFwgAAAAAO56Lv+c2ttFJ8v+wsPDnR0CAAAA4NKcMXGT68yW5FhOH34MAAAAAEBBFfpKLQAAAAA4GpVax6FSCwAAAABwW3RqAQAAAABui+HHAAAAAGBnVsOQ1cHjgR3dnqugUgsAAAAAcFtUagEAAADAzgzrlcXRbd6NqNQCAAAAANwWlVoAAAAAsDNDhgwH3+NqiHtqAQAAAABwK3RqAQAAAABui+HHAAAAAGBnhlWyMlGUQ1CpBQAAAAC4LSq1AAAAAGBnhuGEiaIc3J6roFILAAAAAHBbdGoBAAAAAG6L4ccAAAAAYGdW48ri6DbvRlRqAQAAAABui0otAAAAANiZYTVkOLh06uj2XAWVWgAAAACA26JSCwAAAAB2ZhhXFke3eTeiUgsAAAAAcFt0agEAAAAAbovhxwAAAABgZ1arIauDJ25ydHuugkotAAAAAMBtUakFAAAAADszDEOGg2ducnR7roJKLQAAAADAbdGpBQAAAAC4LYYfAwAAAICdGdYri6PbvBtRqQUAAAAAuC0qtQAAAABgZ1bDkNXBEzc5uj1XQaUWAAAAAOC26NQCAAAAgJ3lPNLH0UtBvPvuuwoLC5O3t7caNmyojRs35rn9xx9/rJo1a8rb21vR0dFauXJlgdq1Fzq1AAAAAHCXWrx4sQYOHKiRI0dq69atiomJUcuWLZWenp7r9t9//72eeuopde/eXdu2bVP79u3Vvn17/fzzzw6O/H/o1AIAAADAXWrixInq2bOnunXrplq1amnmzJkqXry45s2bl+v2U6ZMUatWrTRkyBBFRkbqtddeU926dTVt2jQHR/4/dGoBAAAAwM6sVsMpiyRlZGTYLBcvXsw1xkuXLmnLli2Ki4sz13l4eCguLk4//PBDrvv88MMPNttLUsuWLW+4vSPQqQUAAACAQiQ0NFSBgYHmMnbs2Fy3O3XqlLKzsxUcHGyzPjg4WCdOnMh1nxMnTtzS9o7AI30AAAAAwM4M48ri6DYl6ciRIwoICDDXe3l5OTYQB6NTCwAAAACFSEBAgE2n9kbKlCmjIkWK6LfffrNZ/9tvv6lcuXK57lOuXLlb2t4RGH4MAAAAAHchT09P1atXT6tXrzbXWa1WrV69Wo0aNcp1n0aNGtlsL0lff/31Dbd3BCq1AAAAAGBnhmHIsDp2/HFBnlM7cOBAxcfHq379+mrQoIEmT56szMxMdevWTZLUpUsXVahQwbwv98UXX1TTpk2VmJioRx99VIsWLdLmzZv13nvv2fVcbgWdWgAAAAC4S3Xq1EknT55UQkKCTpw4oTp16uiLL74wJ4M6fPiwPDz+N8C3cePGWrhwoYYPH65XXnlF1atX17Jly1S7dm1nnQKdWgAAAACwN8MwZHXwTFEFqdRKUr9+/dSvX79c31uzZs1165588kk9+eSTBWrrTuCeWgAAAACA26JSCwAAAAB2ZlidcE+tg9tzFVRqAQAAAABuq9B0ag8ePCiLxaLt27ffcJs1a9bIYrHo9OnTDovL0cLCwjR58mRnh6Fly5YpPDxcRYoU0YABA5wdDgAAAIBCqtAMPw4NDdXx48dVpkwZZ4cCSc8995y6deum/v37y9/f32lxNGvWTHXq1HGJjj4AAADuHgw/dpxC0am9dOmSPD09Va5cOWeH4vays7NlsVhspu2+VefOnVN6erpatmyp8uXLF/g4OXkFAKAg7mu71vy3xWLo4/dq5nvfFcUibF4/enmf3eICANiXSw4/Pnv2rDp37ixfX1+FhIRo0qRJatasmTmMNSwsTK+99pq6dOmigIAA9erVK9fhxytXrlSNGjXk4+OjBx98UAcPHsx3DIcOHVLbtm1VsmRJ+fr6KioqSitXrjTf//nnn9W6dWv5+fkpODhYzz77rE6dOmW+b7VaNX78eIWHh8vLy0uVKlXSG2+8Yb6/c+dONW/eXD4+PipdurR69eqlc+fOme937dpV7du314QJExQSEqLSpUurb9++unz5srlNenq62rZtKx8fH1WpUkUffvjhdecxceJERUdHy9fXV6GhoerTp49NO/Pnz1eJEiW0fPly1apVS15eXlq/fr2KFSumEydO2BxrwIABuv/++/O8bmvWrDErs82bN5fFYjGnAV+6dKmioqLk5eWlsLAwJSYm2uybW14laf369br//vvl4+Oj0NBQ9e/fX5mZmeZ+06dPV/Xq1eXt7a3g4GA98cQT5jVcu3atpkyZIovFIovFcks/AwAA93V1hzbH0Nd+zte+13Zob7QOAPJiNZyz3I1cslI7cOBApaSkaPny5QoODlZCQoK2bt2qOnXqmNtMmDBBCQkJGjlyZK7HOHLkiB5//HH17dtXvXr10ubNmzVo0KB8x9C3b19dunRJ3333nXx9fbV79275+flJkk6fPq3mzZurR48emjRpks6fP6+hQ4eqY8eO+vbbbyVJw4YN0+zZszVp0iTdd999On78uPbu3StJyszMVMuWLdWoUSNt2rRJ6enp6tGjh/r166f58+ebMSQnJyskJETJycn6v//7P3Xq1El16tRRz549JV3ptB07dkzJyckqVqyY+vfvr/T0dJvz8PDw0NSpU1WlShXt379fffr00UsvvaTp06eb2/z1118aN26c5syZo9KlSys0NFRVq1bVBx98oCFDhkiSLl++rA8//FDjx4/P87o1btxY+/btU0REhJYuXarGjRurVKlS2rJlizp27KhRo0apU6dO+v7779WnTx+VLl1aXbt2Nfe/Nq9paWlq1aqVXn/9dc2bN08nT540n6OVlJSkzZs3q3///vrggw/UuHFj/fHHH1q3bp0kacqUKUpNTVXt2rU1ZswYSVJQUFCucV+8eFEXL140X2dkZEi68uWE1WrN85yRO6vVeuX5bFw/pyEHroE8OIfFYlz32mLJXx6MG4xWIoe3j8+D8xWmHBSGc4B9uFyn9uzZs1qwYIEWLlyoFi1aSJKSkpKuG8bavHlzm07qtRW4GTNmqFq1amY1MCIiQjt37tS4cePyFcfhw4fVoUMHRUdHS5KqVq1qvjdt2jTFxsbqzTffNNfNmzdPoaGhSk1NVUhIiKZMmaJp06YpPj5eklStWjXdd999kqSFCxfqwoULev/99+Xr62ses23btho3bpyCg4MlSSVLltS0adNUpEgR1axZU48++qhWr16tnj17KjU1VatWrdLGjRt17733SpLmzp2ryMhIm/O4epKmsLAwvf766+rdu7dNp/by5cuaPn26YmJizHXdu3dXUlKS2an9/PPPdeHCBXXs2DHP6+bp6amyZctKkkqVKmUOCZ84caJatGihESNGSJJq1Kih3bt36+2337bp1F6b1x49eqhz587meVSvXl1Tp05V06ZNNWPGDB0+fFi+vr5q06aN/P39VblyZcXGxkqSAgMD5enpqeLFi990aPrYsWM1evTo69afPHlSFy5cyHNf5M5qterMmTMyDOO2hrOj4MiBayAPzlE1NOuaNYaCy2QrPT39pnkwYnOvyl77xTFuHZ8H5ytMOTh79qyzQ4CLcLlO7f79+3X58mU1aNDAXBcYGKiICNtfMPXr18/zOHv27FHDhg1t1jVq1CjfcfTv31/PP/+8vvrqK8XFxalDhw665557JEk7duxQcnKyWbm9Wlpamk6fPq2LFy+anfLcYouJiTE7tJLUpEkTWa1W7du3z+zURkVFqUiRIuY2ISEh2rlzp3mMokWLql69eub7NWvWVIkSJWza+uabbzR27Fjt3btXGRkZysrK0oULF/TXX3+pePHikq50RHPOLUfXrl01fPhwbdiwQX/72980f/58dezY0SbmW7Fnzx61a9fOZl2TJk00efJkZWdnm+d5bV537Nihn376yWZodc63iwcOHNBDDz2kypUrq2rVqmrVqpVatWqlxx57zDy3/Bo2bJgGDhxovs7IyFBoaKiCgoIUEBBwq6cLXfmlabFYFBQU5Pa/NN0VOXAN5ME5kt5prqbtvzNfWyyG3hpeO195ePT7T7XSJ8pm3SPnd92ROO82fB6crzDlwNvb29kh5ImJohzH5Tq1+VXQzlV+9ejRQy1bttSKFSv01VdfaezYsUpMTNQLL7ygc+fOmVXVa4WEhGj//v12iaFYsWI2ry0Wyy0Nszh48KDatGmj559/Xm+88YZKlSql9evXq3v37rp06ZLZ8fPx8ZHFYrHZt2zZsmrbtq2SkpJUpUoVrVq1yrw39k66Nq/nzp3Tc889p/79+1+3baVKleTp6amtW7dqzZo1+uqrr5SQkKBRo0Zp06ZN13Xw8+Ll5SUvL6/r1nt4eLj9f/jOlDPpGNfQeciBayAPzrFueTPz31ar1azS5icPbS7uuYOR3d34PDhfYcmBu8cP+3G5n4SqVauqWLFi2rRpk7nuzJkzSk1NvaXjREZGauPGjTbrNmzYcEvHCA0NVe/evfXpp59q0KBBmj17tiSpbt262rVrl8LCwhQeHm6z+Pr6qnr16vLx8dHq1atvGNuOHTtsJjtKSUmRh4fHdRXpG6lZs6aysrK0ZcsWc92+fftsnsG7ZcsWWa1WJSYm6m9/+5tq1KihY8eO5fv8e/ToocWLF+u9995TtWrV1KRJk3zve63IyEilpKTYrEtJSVGNGjVsqtHXqlu3rnbv3n3ddQ4PDzdnRi5atKji4uI0fvx4/fTTTzp48KB5b7Onp6eys7MLHDcAAABQEIZhOGW5G7lcp9bf31/x8fEaMmSIkpOTtWvXLnXv3l0eHh7XVRPz0rt3b/3yyy8aMmSI9u3bp4ULF9pMwnQzAwYM0JdffqkDBw5o69atSk5ONu9X7du3r/744w899dRT2rRpk9LS0vTll1+qW7duys7Olre3t4YOHaqXXnpJ77//vtLS0rRhwwbNnTtXktS5c2d5e3srPj5eP//8s5KTk/XCCy/o2WefNYce30xERIRatWql5557Tj/++KO2bNmiHj16yMfHx9wmPDxcly9f1jvvvKP9+/frgw8+0MyZM/N9DVq2bKmAgAC9/vrr6tatW773y82gQYO0evVqvfbaa0pNTdWCBQs0bdo0DR48OM/9hg4dqu+//179+vXT9u3b9csvv+g///mP+vXrJ0n673//q6lTp2r79u06dOiQ3n//fVmtVvPLgbCwMP344486ePCgTp06xYQCAAAAQCHjcp1a6cqkQo0aNVKbNm0UFxenJk2aKDIy8pbGzVeqVElLly7VsmXLFBMTo5kzZ9pM7HQz2dnZ6tu3ryIjI9WqVSvVqFHDnFypfPnySklJUXZ2th5++GFFR0drwIABKlGihDkMYsSIERo0aJASEhIUGRmpTp06mRNMFC9eXF9++aX++OMP3XvvvXriiSfUokULTZs27Rau0v8m0GratKkef/xx9erVy5ykSZJiYmI0ceJEjRs3TrVr19aHH36osWPH5vv4Hh4e6tq1q7Kzs9WlS5dbiu1adevW1ZIlS7Ro0SLVrl1bCQkJGjNmjM0kUbm55557tHbtWqWmpur+++9XbGysEhISzInDSpQooU8//VTNmzdXZGSkZs6cqY8++khRUVfuhRo8eLCKFCmiWrVqKSgoSIcPH76t8wAAAADgWiyGG9SoMzMzVaFCBSUmJqp79+7ODueu0r17d508eVLLly93digOlZGRocDAQJ05c4aJogoo5/61smXLcs+Lk5AD10AeXAN5cA3kwfkKUw5c9e+1nLi6jDggT29/h7Z96cJZvf9aFZe7JneaS04UtW3bNu3du1cNGjTQmTNnzGeMXjt7Lu6cM2fOaOfOnVq4cOFd16EFAAAA4D5c9uuZCRMmKCYmRnFxccrMzNS6detUpkwZux2/devW8vPzy3W5lWHKhVW7du308MMPq3fv3nrooYds3uPaAQAAAHljoijHcclKbWxsrM2svnfCnDlzdP78+VzfK1Wq1B1t2x3k9fgerh0AAAAAV+GSnVpHqFChgrNDcFtcOwAAACBvhtWQYXVs5dTR7bkKlx1+DAAAAADAzdCpBQAAAAC4rbt2+DEAAAAA3CkMP3YcKrUAAAAAALdFpRYAAAAA7MwqQ1YHP2LHKiq1AAAAAAC4FTq1AAAAAAC3xfBjAAAAALAzJopyHCq1AAAAAAC3RaUWAAAAAOzMMAwZDp4oytHtuQoqtQAAAAAAt0WlFgAAAADszLAasnJPrUNQqQUAAAAAuC06tQAAAAAAt8XwYwAAAACwMx7p4zhUagEAAAAAbotKLQAAAADYGY/0cRwqtQAAAAAAt0WnFgAAAADgthh+DAAAAAB2ZlitMqxWh7d5N6JSCwAAAABwW1RqAQAAAMDOrFZDVgc/YsfR7bkKKrUAAAAAALdFpRYAAAAA7IxH+jgOlVoAAAAAgNuiUwsAAAAAcFsMPwYAAAAAOzOshgwHT9zk6PZcBZVaAAAAAIDbolILAAAAAHZGpdZxqNQCAAAAANwWnVoAAAAAgNti+DEAAAAA2JlVVlkNq8PbvBtRqQUAAAAAuC0qtQAAAABgZ4bV8RM3Obgw7DKo1AIAAAAA3BaVWgAAAACwMx7p4zhUagEAAAAAbotOLQAAAADAbTH8GAAAAADszDAMGYaDhx87uD1XQaUWAAAAAOC2qNQCAAAAgJ1ZrVZZrY59xo6j23MVVGoBAAAAAG6LTi0AAAAAwG0x/BgAAAAA7Izn1DoOlVoAAAAAgNuiUgsAAAAAdmYYVhmGYyducnR7roJKrZ0dPHhQFotF27dvv+E2a9askcVi0enTp/N1zGXLlik8PFxFihTRgAEDNH/+fJUoUcIu8eZl1KhRqlOnzm0dIz/XwxFxAAAAACic6NTaWWhoqI4fP67atWvb7ZjPPfecnnjiCR05ckSvvfaa3Y7rLgYPHqzVq1c7OwwAAAAg33LuqXX0cjdi+LEdXbp0SZ6enipXrpzdjnnu3Dmlp6erZcuWKl++vN2O6w4Mw1B2drb8/Pzk5+fn7HAAAG5iRbEIm9ePXt6npu2/U9XQLO0/UlSGYdH6z5s6KToAgL1Rqc3D2bNn1blzZ/n6+iokJESTJk1Ss2bNNGDAAElSWFiYXnvtNXXp0kUBAQHq1atXrsNtV65cqRo1asjHx0cPPvigDh48mK/216xZI39/f0lS8+bNZbFYtGbNmly3nTFjhqpVqyZPT09FRETogw8+sHn/8OHDateunfz8/BQQEKCOHTvqt99+s9nmrbfeUnBwsPz9/dW9e3dduHDhunbmzJmjyMhIeXt7q2bNmpo+fbrN+xs3blRsbKy8vb1Vv359bdu2LV/nmnO+FotFq1atUr169eTl5aX169fnOvx43rx5ioqKkpeXl0JCQtSvXz/zvdOnT6tHjx4KCgpSQECAmjdvrh07duQ7DgBA4TL3mk6uJN3Xdq0TIgEA3AlUavMwcOBApaSkaPny5QoODlZCQoK2bt1q08GaMGGCEhISNHLkyFyPceTIET3++OPq27evevXqpc2bN2vQoEH5ar9x48bat2+fIiIitHTpUjVu3FilSpW6rlP82Wef6cUXX9TkyZMVFxen//73v+rWrZsqVqyoBx98UFar1ezQrl27VllZWerbt686depkdpKXLFmiUaNG6d1339V9992nDz74QFOnTlXVqlXNdj788EMlJCRo2rRpio2N1bZt29SzZ0/5+voqPj5e586dU5s2bfTQQw/p3//+tw4cOKAXX3zxlq65JL388suaMGGCqlatqpIlS17XkZ8xY4YGDhyot956S61bt9aZM2eUkpJivv/kk0/Kx8dHq1atUmBgoGbNmqUWLVooNTVVpUqVyrXNixcv6uLFi+brjIwMSZLVapXVenfecH+7rFarDMPg+jkROXAN5MHxDA/b7+z3V2ohi8UwlxzkxPH4PDhfYcqBy5+DM4YDM/wYVzt79qwWLFighQsXqkWLFpKkpKSk64YAN2/e3KaTem2HM6eCmpiYKEmKiIjQzp07NW7cuJvG4OnpqbJly0qSSpUqdcNhzRMmTFDXrl3Vp08fSVc64xs2bNCECRP04IMPavXq1dq5c6cOHDig0NBQSdL777+vqKgobdq0Sffee68mT56s7t27q3v37pKk119/Xd98841NtXbkyJFKTEzU448/LkmqUqWKdu/erVmzZik+Pl4LFy6U1WrV3Llz5e3traioKP366696/vnnb3quVxszZoweeuihG77/+uuva9CgQTYd5nvvvVeStH79em3cuFHp6eny8vIyr8+yZcv0ySefqFevXrkec+zYsRo9evR160+ePJlrxRo3Z7VadebMGRmGIQ8PBoU4AzlwDeTB8YxY28psNe8L+rViloLLZMswJMkiSUpPT3d8cHc5Pg/OV5hycPbsWWeHABdBp/YG9u/fr8uXL6tBgwbmusDAQEVE2P6irF+/fp7H2bNnjxo2bGizrlGjRvYL9P+3cW1nrUmTJpoyZYr5fmhoqNmhlaRatWqpRIkS2rNnj+69917t2bNHvXv3vi7O5ORkSVJmZqbS0tLUvXt39ezZ09wmKytLgYGBZjv33HOPvL29b+tc87qm6enpOnbsmPlFw7V27Nihc+fOqXTp0jbrz58/r7S0tBsed9iwYRo4cKD5OiMjQ6GhoeYQZtw6q9Uqi8WioKAgt/+l6a7IgWsgD45n2bbP5nVZ7dOBwM6yWKQDv165p3btsgecFN3djc+D8xWmHFz9N6crshpWWR38iB1Ht+cq6NTeJl9fX2eH4BDnzp2TJM2ePfu6TnqRIkXs2lZe19THxyfPfc+dO6eQkJBc7z3O6zFIXl5eZmX3ah4eHm7/H74zWSwWrqGTkQPXQB4cq83FPdete8RqVXp6usqWLUsenIzPg/MVlhy4e/ywH34SbqBq1aoqVqyYNm3aZK47c+aMUlNTb+k4kZGR2rhxo826DRs22CXGq9u4+p5SSUpJSVGtWrXM948cOaIjR46Y7+/evVunT5+22ebHH3+8YZzBwcEqX7689u/fr/DwcJulSpUq5jF++uknm+G69j5Xf39/hYWF3fARP3Xr1tWJEydUtGjR6+IsU6aMXWMBAAAA4HxUam/A399f8fHxGjJkiEqVKqWyZctq5MiR8vDwkMViyfdxevfurcTERA0ZMkQ9evTQli1bNH/+fLvGOmTIEHXs2FGxsbGKi4vT559/rk8//VTffPONJCkuLk7R0dHq3LmzJk+erKysLPXp00dNmzY1h/q++OKL6tq1q+rXr68mTZroww8/1K5du2wmiho9erT69++vwMBAtWrVShcvXtTmzZv1559/auDAgXr66af16quvqmfPnho2bJgOHjyoCRMm2PVcJWnUqFHq3bu3ypYtq9atW+vs2bNKSUnRCy+8oLi4ODVq1Ejt27fX+PHjVaNGDR07dkwrVqzQY489dtPh4gAAAIA9OOO5sXfrc2qp1OZh4sSJatSokdq0aaO4uDg1adLEfJxNflWqVElLly7VsmXLFBMTo5kzZ+rNN9+0a5zt27fXlClTNGHCBEVFRWnWrFlKSkpSs2bNJF0ZYvKf//xHJUuW1AMPPKC4uDhVrVpVixcvNo/RqVMnjRgxQi+99JLq1aunQ4cOXTfBU48ePTRnzhwlJSUpOjpaTZs21fz5881KrZ+fnz7//HPt3LlTsbGxevXVV/M1Idatio+P1+TJkzV9+nRFRUWpTZs2+uWXX8xzXblypR544AF169ZNNWrU0D/+8Q8dOnRIwcHBdo8FAAAAgHNZDMO4O7vzBZCZmakKFSooMTHRnCUYhVNGRoYCAwN15swZJooqICv3rzkdOXAN5ME1kAfXQB6crzDlwFX/XsuJq9mTa1S0mJ9D2866fE5rPm7mctfkTmP4cR62bdumvXv3qkGDBjpz5ozGjBkjSWrXrp2TIwMAAAAASAw/vqkJEyYoJiZGcXFxyszM1Lp16+w64VDr1q3l5+eX62LvYcrO1rt37xue67WPEwIAAADcWc49tY5e7kZUavMQGxurLVu23NE25syZo/Pnz+f6XqlSpe5o2442ZswYDR48ONf37qbhEQAAAADsh06tk1WoUMHZIThM2bJlVbZsWWeHAQAAAKAQoVMLAAAAAHZmGFYZhtXhbd6NuKcWAAAAAOC2qNQCAAAAgJ1ZrZLVwRM3We/OQi2VWgAAAACA+6JTCwAAAABwWww/BgAAAAA7M6xWGQ4eD+zo9lwFlVoAAAAAgNuiUgsAAAAAdmZYDRkOnijK0e25Ciq1AAAAAAC3RacWAAAAAOC2GH4MAAAAAHZmGFYZhoMninJwe66CSi0AAAAAwG1RqQUAAAAAO2OiKMehUgsAAAAAcFtUagEAAADAzgyrVYbVwffUOrg9V0GlFgAAAADgtqjUArkwjCv3I2RkZDg5EvdltVp19uxZeXt7y8OD78+cgRy4BvLgGsiDayAPzleYcpDzd1rO322uJjsr865o0xXQqQVycfbsWUlSaGiokyMBAABAXs6ePavAwEBnh2Hy9PRUuXLltHl1R6e0X65cOXl6ejqlbWexGK761QbgRFarVceOHZO/v78sFouzw3FLGRkZCg0N1ZEjRxQQEODscO5K5MA1kAfXQB5cA3lwvsKUA8MwdPbsWZUvX97lqs4XLlzQpUuXnNK2p6envL29ndK2s1CpBXLh4eGhihUrOjuMQiEgIMDtf2m6O3LgGsiDayAProE8OF9hyYErVWiv5u3tfdd1LJ3Jtb7SAAAAAADgFtCpBQAAAAC4LTq1AO4ILy8vjRw5Ul5eXs4O5a5FDlwDeXAN5ME1kAfnIwcojJgoCgAAAADgtqjUAgAAAADcFp1aAAAAAIDbolMLAAAAAHBbdGoBAAAAAG6LTi2A2/b666+rQYMG8vLyksVikcVi0YULF/K1b1hYmLnP1cszzzxzh6MufG4nD2fPntW//vUvVaxYUZ6enqpWrZpGjx6trKysOxx14XM71zK3z4LFYtHw4cMdELn7WrRokerWrSsfHx+VKlVKTzzxhNLS0m663zvvvKNatWrJy8tLZcuW1T//+U/99ttvDoi4cCpIHrp27Zrrz3zFihUdFHXh8t133+mRRx5RUFCQeS1nzpyZr30L+jkCXEFRZwcAwP198sknOnjwoIKCgnT06NECHSMyMlIBAQHm6/DwcHuFd9coaB6sVqvatm2rtWvXqlixYqpatap++eUXjRo1SmlpaXr//ffvYNSFi72uZZ06dWwetxEaGnqnQnZ7c+fOVY8ePSRJVapU0e+//66lS5dq3bp12rFjh8qVK5frfiNGjNDrr78uSapevbp+/fVXJSUl6YcfftCWLVtUvHhxh51DYVDQPOSoUKGCTUe2bNmydzTewmrr1q36+uuvVbVqVZ06dSrf+91u/gCnMwDgNh05csSwWq3GyJEjDUmGJOP8+fP52rdy5cqGJCM5OfnOBnkXKGgeli5dam7/+eefG4ZhGFOnTjXXbdmy5U6HXmjc7rXM2e7AgQMOiNb9Xbx40ShTpowhyejQoYNhGIZx9OhRw9/f35BkvPDCC7nud+LECaNYsWKGJGPQoEGGYRjGjh07DIvFYkgyEhMTHXYOhUFB82AYhhEfH29IMkaOHOmgaAu3U6dOGX/99Zdx4MAB8/+TGTNm5LnP7eQPcBUMPwZw2ypWrCiLxXJbx+jQoYO8vb1Vo0YNvfTSS8rIyLBTdHePguZh1apVkiQfHx898sgjkq7kI8cXX3xhnwDvAva6lvXr11fx4sUVFRWlt956SxcvXrR/sIXApk2bzGpUznUuX768/va3v0m68fX+5ptvdPnyZZv97rnnHnOECD/zt6agebja5MmT5eXlpdDQUP3jH/9g2GsBlS5dWj4+Pre0jz3yBzgbnVoATufv768KFSooMDBQv/zyi95++221bNlSVqvV2aHdFY4cOSLpyh9DHh5Xfi0EBweb7x8+fNgpcbkje1zLkiVLqmLFivLy8tLu3bs1bNgwdenS5c4E7OZyrrdkO1w155rf6HoXdD/k7navp6enp0JCQlSxYkX9+uuvWrx4se69994C386CW8PnAYUBnVoAuXr55ZdvOGlNzrJ3797bbueTTz7Rn3/+qZ9++klHjx7Vs88+K0nasGGDvv/++9s+vrtzVB6uZRiG3Y/pzm4nD7dyLTds2KDff/9d27dv19GjR9W8eXNJ0pIlS2z+8ETeCvrzy8+9feXneg4ePFi///679uzZo7S0NHNSoz///FNJSUl3OkTkgc8D3AkTRQHIVb169RQfH5/nNoGBgbfdTv369c1/Fy1aVB07dtQHH3wgiW+HJcfkIWcSolOnTslqtcrDw0Pp6enm+5UqVbqt4xcG+c3D7V7Lhg0bmv8uXry4HnvsMX377beSrlRTmDDK1tXX4+rrnPPvG13va/erVq1avvZD7gqaB0mqXbu2zevOnTurd+/ekvgd4Ci3kz/AZTjzhl4AhUteExT9+OOPRkREhBEREWH8+OOPhmEYxs8//2zMmTPHuHDhgmEYhpGVlWVOGiLJSElJcfg5FAa3modPPvmEiaLsJL/X8tNPPzXz8OuvvxqGYRhr1641Pv74YyMrK8swDMM4f/68ERcXZ+6bsx3+5+LFi0bp0qVvOsFNzrV+5513DMMwjOPHjxtFixZloig7KWgeDMMwEhISjPT0dPP17NmzzZ/5N954w7EnUojkNVFU8+bNjYiICOPll182DCP/+QNcGZ1aALft6aefNqpVq2aULFnS/CVatWpVo1q1asbSpUsNwzCM5ORk872cmY5z1nl5eRlRUVFGcHCwuU3z5s0Nq9XqxLNyPwXNQ1ZWlnHfffcZkoxixYoZNWvWNDw8PAxJxtNPP+3EM3I/+b2WSUlJ1810nLPO19fXiI6Otsljt27dnHRGrm/WrFnmdapSpYoREBBgSDLKlCljHD161DCM/80qffUMu8OGDTPX16hRw/Dx8TEkGdWrVzfOnTvnpLNxXwXNgyTDw8PDCA8PN6pVq2ZuU65cOeO3335z0tm4r6VLlxrVqlUznywgyQgKCjKqVatm/h+U8158fLy5X37yB7gy7qkFcNuOHj2qtLQ0/fnnn+a6/fv3Ky0tLc9ZjCMjIzVw4EBFRETo119/VWZmpqKjozV27Fj997//ve0Zle82Bc1DkSJFtGLFCvXv319BQUFKS0tTpUqVlJCQoPnz5zsg8sLjdq7lfffdp969e6tSpUo6cOCArFar6tWrp5kzZ+q9995zzAm4oV69eunf//636tSpo2PHjslisejxxx/X999/r/Lly99wvzfeeEOTJ09WzZo1deDAAfn6+io+Pl7fffedfH19HXgGhcPt5KFx48bKyMjQ0aNHFR4ert69e2vz5s08q7YAMjIylJaWpkOHDpnrTp48qbS0tDwn3ipo/gBXYTEM7gIHAAAAALgnKrUAAAAAALdFpxYAAAAA4Lbo1AIAAAAA3BadWgAAAACA26JTCwAAAABwW3RqAQAAAABui04tAAAAAMBt0akFAAAAALgtOrUAgEJh1KhRqlOnjkPaWr16tSIjI5Wdne3wtpE/t5qTgwcPymKxaPv27XcsJme4dOmSwsLCtHnzZmeHAgB3DJ1aACjkTp48qeeff16VKlWSl5eXypUrp5YtWyolJcXcJiwsTJMnT75u3xt1DH799Vd5enqqdu3aubZpsVjMJTAwUE2aNNG3335rr1NyupdeeknDhw9XkSJFJEmDBw/W6tWrnRxV/lgsFi1btszZYdy1unbtqvbt29+RY+f2efX09NTgwYM1dOjQO9ImALgCOrUAUMh16NBB27Zt04IFC5Samqrly5erWbNm+v333wt8zPnz56tjx47KyMjQjz/+mOs2SUlJOn78uFJSUlSmTBm1adNG+/fvL3CbrmL9+vVKS0tThw4dzHV+fn4qXbq0E6MCbqxz585av369du3a5exQAOCOoFMLAIXY6dOntW7dOo0bN04PPvigKleurAYNGmjYsGH6+9//XqBjGoahpKQkPfvss3r66ac1d+7cXLcrUaKEypUrp9q1a2vGjBk6f/68vv766+u2y8jIkI+Pj1atWmWz/rPPPpO/v7/++usvSdLQoUNVo0YNFS9eXFWrVtWIESN0+fLlG8bZrFkzDRgwwGZd+/bt1bVrV/P1xYsXNXjwYFWoUEG+vr5q2LCh1qxZk+f5L1q0SA899JC8vb3NdddWyHKqcW+++aaCg4NVokQJjRkzRllZWRoyZIhKlSqlihUrKikpydwnZ/jrokWL1LhxY3l7e6t27dpau3atuU12dra6d++uKlWqyMfHRxEREZoyZcp1Mc6bN09RUVHy8vJSSEiI+vXrJ+lKRV6SHnvsMVksFvN1bnbu3KnmzZvLx8dHpUuXVq9evXTu3LnrznHChAkKCQlR6dKl1bdv3zxzknOd5s2bp0qVKsnPz099+vRRdna2xo8fr3Llyqls2bJ64403bPY7fPiw2rVrJz8/PwUEBKhjx4767bffbLZ56623FBwcLH9/f3Xv3l0XLly4rv05c+YoMjJS3t7eqlmzpqZPn37DWHPz559/qkuXLipZsqSKFy+u1q1b65dffrnu/K42efJk8zqPGjVKCxYs0H/+8x9zJMOaNWvylfv58+erRIkSNsdetmyZLBaL+f7o0aO1Y8cO89jz58+XJJUsWVJNmjTRokWLbul8AcBd0KkFgELMz89Pfn5+WrZsmS5evGiXYyYnJ+uvv/5SXFycnnnmGS1atEiZmZl57uPj4yPpyv191woICFCbNm20cOFCm/Uffvih2rdvr+LFi0uS/P39NX/+fO3evVtTpkzR7NmzNWnSpNs6l379+umHH37QokWL9NNPP+nJJ59Uq1atbDoq11q3bp3q169/02N/++23OnbsmL777jtNnDhRI0eOVJs2bVSyZEn9+OOP6t27t5577jn9+uuvNvsNGTJEgwYN0rZt29SoUSO1bdvWrKpbrVZVrFhRH3/8sXbv3q2EhAS98sorWrJkibn/jBkz1LdvX/Xq1Us7d+7U8uXLFR4eLknatGmTpP9V0XNeXyszM1MtW7ZUyZIltWnTJn388cf65ptvzM5xjuTkZKWlpSk5OVkLFizQ/PnzzY7UjaSlpWnVqlX64osv9NFHH2nu3Ll69NFH9euvv2rt2rUaN26chg8fbo4AsFqtateunf744w+tXbtWX3/9tfbv369OnTqZx1yyZIlGjRqlN998U5s3b1ZISMh1HdYPP/xQCQkJeuONN7Rnzx69+eabGjFihBYsWJBnvFfr2rWrNm/erOXLl+uHH36QYRh65JFH8uzIX23w4MHq2LGjWrVqpePHj+v48eNq3Lix+X5eub+ZTp06adCgQYqKijKPffU1atCggdatW5fvcwUAt2IAAAq1Tz75xChZsqTh7e1tNG7c2Bg2bJixY8cOm20qV65seHp6Gr6+vjZLsWLFjJiYGJttn376aWPAgAHm65iYGCMpKclmG0nGZ599ZhiGYWRmZhp9+vQxihQpcl27OT777DPDz8/PyMzMNAzDMM6cOWN4e3sbq1atuuF5vf3220a9evXM1yNHjrSJtWnTpsaLL75os0+7du2M+Ph4wzAM49ChQ0aRIkWMo0eP2mzTokULY9iwYTdsNzAw0Hj//fdt1l3bdnx8vFG5cmUjOzvbXBcREWHcf//95uusrCzD19fX+OijjwzDMIwDBw4Ykoy33nrL3Oby5ctGxYoVjXHjxt0wnr59+xodOnQwX5cvX9549dVXb7j91bm5kffee88oWbKkce7cOXPdihUrDA8PD+PEiRM255iVlWVu8+STTxqdOnW64XFHjhxpFC9e3MjIyDDXtWzZ0ggLC7vuWo0dO9YwDMP46quvjCJFihiHDx8239+1a5chydi4caNhGIbRqFEjo0+fPjZtNWzY0CYn1apVMxYuXGizzWuvvWY0atTIMIz/Xf9t27blGntqaqohyUhJSTHXnTp1yvDx8TGWLFlint+1n5dJkyYZlStXNl/Hx8cb7dq1s9kmP7lPSkoyAgMDbfb77LPPjKv/lMut/RxTpkwxwsLCcn0PANwdlVoAKOQ6dOigY8eOafny5WrVqpXWrFmjunXrXldRGzJkiLZv326z9O7d22ab06dP69NPP9UzzzxjrnvmmWdyHYL81FNPyc/PT/7+/lq6dKnmzp2re+65J9cYH3nkERUrVkzLly+XJC1dulQBAQGKi4szt1m8eLGaNGmicuXKyc/PT8OHD9fhw4cLelm0c+dOZWdnq0aNGmZF28/PT2vXrlVaWtoN9zt//rzN0OMbiYqKkofH/37NBgcHKzo62nxdpEgRlS5dWunp6Tb7NWrUyPx30aJFVb9+fe3Zs8dc9+6776pevXoKCgqSn5+f3nvvPfM6pKen69ixY2rRosXNL0Ae9uzZo5iYGPn6+prrmjRpIqvVqn379tmcY85kWZIUEhJy3flcKywsTP7+/ubr4OBg1apV67prlXOcPXv2KDQ0VKGhoeb7tWrVUokSJczrsmfPHjVs2NCmnauvY2ZmptLS0tS9e3ebXL/++ut55vraa1K0aFGbdkqXLq2IiAib/NyOm+X+dvj4+JhD+QGgsCnq7AAAAHeet7e3HnroIT300EMaMWKEevTooZEjR9rcX1qmTBlzmGqOUqVK2bxeuHChLly4YPOHvWEYslqtSk1NVY0aNcz1kyZNUlxcnAIDAxUUFJRnfJ6ennriiSe0cOFC/eMf/9DChQvVqVMnFS165dfUDz/8oM6dO2v06NFq2bKlAgMDtWjRIiUmJt7wmB4eHjIMw2bd1cNEz507pyJFimjLli02HTPpyrDtGylTpoz+/PPPPM9HkooVK2bz2mKx5LrOarXe9Fg5Fi1apMGDBysxMVGNGjWSv7+/3n77bXOobs4wb0cpyPncietyMzn3As+ePfu6zu+1ub8dN/uZc+ax//jjj5t+DgHAXVGpBYC7UK1atW56H2xu5s6dq0GDBtlUc3fs2KH7779f8+bNs9m2XLlyCg8Pz/cf0p07d9YXX3yhXbt26dtvv1Xnzp3N977//ntVrlxZr776qurXr6/q1avr0KFDeR4vKChIx48fN19nZ2fr559/Nl/HxsYqOztb6enpCg8Pt1nKlSt3w+PGxsZq9+7d+TqngtiwYYP576ysLG3ZskWRkZGSpJSUFDVu3Fh9+vRRbGyswsPDbSqN/v7+CgsLy/PxQsWKFTOfr3sjkZGR2rFjh83PSEpKijw8PBQREVHQUyuQyMhIHTlyREeOHDHX7d69W6dPn1atWrXMba6dhfvq6xgcHKzy5ctr//791+W6SpUq+Y4jKyvLpp3ff/9d+/btM+MICgrSiRMnbDqf1z731tPT84bXP6/cBwUF6ezZszY5uZVj//zzz4qNjb35iQKAG6JTCwCF2O+//67mzZvr3//+t3766ScdOHBAH3/8scaPH6927drd0rG2b9+urVu3qkePHqpdu7bN8tRTT2nBggXKysoqcKwPPPCAypUrp86dO6tKlSo2FbXq1avr8OHDWrRokdLS0jR16lR99tlneR6vefPmWrFihVasWKG9e/fq+eef1+nTp833a9Sooc6dO6tLly769NNPdeDAAW3cuFFjx47VihUrbnjcli1bav369QU+z5t599139dlnn2nv3r3q27ev/vzzT/3zn/+UdOU6bN68WV9++aVSU1M1YsSI6yZ7GjVqlBITEzV16lT98ssv2rp1q9555x3z/ZxO74kTJ25Yce7cubO8vb0VHx+vn3/+WcnJyXrhhRf07LPPKjg4+I6de27i4uIUHR2tzp07a+vWrdq4caO6dOmipk2bmhN2vfjii5o3b56SkpKUmpqqkSNHXvf4mtGjR2vs2LGaOnWqUlNTtXPnTiUlJWnixIn5iqN69epq166devbsqfXr12vHjh165plnVKFCBfOz1KxZM508eVLjx49XWlqa3n333etm9Q4LC9NPP/2kffv26dSpUzbV1rxy37BhQxUvXlyvvPKK0tLStHDhwutuIQgLC9OBAwe0fft2nTp1ymZyuHXr1unhhx/O30UHADdDpxYACjE/Pz81bNhQkyZN0gMPPKDatWtrxIgR6tmzp6ZNm3ZLx5o7d65q1aqlmjVrXvfeY489pvT0dK1cubLAsVosFj311FPasWOHTZVWkv7+97/rX//6l/r166c6dero+++/14gRI/I83j//+U/Fx8ebHaCqVavqwQcftNkmKSlJXbp00aBBgxQREaH27dtr06ZNqlSp0g2P27lzZ+3atcvm3lJ7euutt/TWW28pJiZG69ev1/Lly1WmTBlJ0nPPPafHH39cnTp1UsOGDfX777+rT58+NvvHx8dr8uTJmj59uqKiotSmTRub2ZwTExP19ddfKzQ09IaVu+LFi+vLL7/UH3/8oXvvvVdPPPGEWrRoccs/M/ZgsVj0n//8RyVLltQDDzyguLg4Va1aVYsXLza36dSpk0aMGKGXXnpJ9erV06FDh/T888/bHKdHjx6aM2eOkpKSFB0draZNm2r+/Pn5rtRKV35e6tWrpzZt2qhRo0YyDEMrV640h09HRkZq+vTpevfddxUTE6ONGzdq8ODBNsfo2bOnIiIiVL9+fQUFBSklJcV8L6/clypVSv/+97+1cuVKRUdH66OPPtKoUaNsjt2hQwe1atVKDz74oIKCgvTRRx9JujJ8/8yZM3riiSfyfa4A4E4sxrU3aAAAgDwNGTJEGRkZmjVrlt2OefDgQVWpUkXbtm277lmnKNzudO47deqkmJgYvfLKK3Y/NgC4Aiq1AADcoldffVWVK1e262RGwJ1w6dIlRUdH61//+pezQwGAO4bZjwEAuEUlSpSg6gW34OnpqeHDhzs7DAC4oxh+DAAAAABwWww/BgAAAAC4LTq1AAAAAAC3RacWAAAAAOC26NQCAAAAANwWnVoAAAAAgNuiUwsAAAAAcFt0agEAAAAAbotOLQAAAADAbf0/DJfSxWVLe2wAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Precision, Recall, and F1-score values\n",
        "labels = ['Before', 'After']\n",
        "precision_0 = [0.97, 0.70]\n",
        "recall_0 = [1.00, 0.81]\n",
        "f1_score_0 = [0.99, 0.75]\n",
        "precision_1 = [0.51, 0.75]\n",
        "recall_1 = [0.09, 0.62]\n",
        "f1_score_1 = [0.16, 0.68]\n",
        "\n",
        "x = np.arange(len(labels))\n",
        "width = 0.2\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(12,10))\n",
        "prec0 = ax.bar(x - 3*width/2, precision_0, width, label='Precision Link 0', color='b')\n",
        "rec0 = ax.bar(x - 3*width/2, recall_0, width, label='Recall Link 0', color='g', alpha=0.5)\n",
        "f10 = ax.bar(x - 3*width/2, f1_score_0, width, label='F1-score Link 0', color='cyan', alpha=0.5)\n",
        "\n",
        "prec1 = ax.bar(x - width/2, precision_1, width, label='Precision Link 1', color='r')\n",
        "rec1 = ax.bar(x - width/2, recall_1, width, label='Recall Link 1', color='y', alpha=0.5)\n",
        "f11 = ax.bar(x - width/2, f1_score_1, width, label='F1-score Link 1', color='orange', alpha=0.5)\n",
        "\n",
        "ax.set_ylabel('Scores')\n",
        "ax.set_title('Metrics Before and After Undersampling')\n",
        "ax.set_xticks(x)\n",
        "ax.set_xticklabels(labels)\n",
        "ax.legend(prop={'size': 12})\n",
        "\n",
        "def autolabel(rects, offset):\n",
        "    for rect in rects:\n",
        "        height = rect.get_height()\n",
        "        ax.annotate('{:.2f}'.format(height),\n",
        "                    xy=(rect.get_x() + rect.get_width() / 2, height),\n",
        "                    xytext=(0, offset),\n",
        "                    textcoords=\"offset points\",\n",
        "                    ha='center', va='bottom', fontsize=8)\n",
        "\n",
        "autolabel(prec0, -9)\n",
        "autolabel(rec0, 0)\n",
        "autolabel(f10, -6)\n",
        "autolabel(prec1, 2)\n",
        "autolabel(rec1, 1)\n",
        "autolabel(f11, 2)\n",
        "\n",
        "plt.ylim(0, 1.1)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "BXYfHYkKUiM8",
        "outputId": "64204cc6-fd96-4859-9a11-1e3acc1884f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 1 Axes>"
            ],
            "image/png": 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0hu+++05jx47Vjh07bNb0yWhh+VuDpjQFChSwrh129uxZJSQkqFy5cun6VahQQatWrcq0jjR79+7V9u3b1aNHD5u1foKCgjRjxgzFx8fL09Pzjue53YEDByTJGtLc7vZzOjk55ehUrbt5nmmhR9rzTPv93/48nZ2dVbp0aZu2AwcOaO/evXf9Xczoby08PFxfffWVQkJC5OPjo1atWqlz58566qmnrH1SUlI0bdo0zZw5UzExMTbBUNoUzqzuMe3v79aph2ntKSkpiouLszlPRt+l8uXL69q1azp79uw9v3jhbp952bJlbfo5OTnxNkcAQI4hlAIA4A66du2q3r176/Tp0woJCcn0LWcpKSkym82ZjmLJ7B/JGbl11M79mjJlisLCwvTvf/9b33//vQYMGKDx48fr119/zVbYUKJECVWoUMFm9FNKSopatmypN954I8Njypcvn+36M3L780lbTH3o0KGZjkS6/R/Xt/r555/Vvn17NW7cWDNnzpS3t7ecnZ01b948m0Xj02Q2is1isdztLdzRggULJEmDBw/W4MGD0+3/+uuv1bNnz3s+b9qz+uKLLzIMMm5fwP7WEUF3kjZiLyEhIcP9165dSzeqT8rZ55mSkqIqVaro/fffz3D/7SFQRn9rZrNZO3bs0Nq1a7V69WqtXr1a8+bNU48ePazre40bN04RERF66aWX9M4776hgwYJycHDQoEGDrM/4VpndoxHfpQfpugAA3IpQCgCAO3jmmWfUt29f/frrr1q8eHGm/cqUKaP169erQYMGdwyVMhotcq/Spo/t2rUry8BFkqpUqaIqVaro7bff1i+//KIGDRpo9uzZGjt2bLaunZSUpCtXrtjUcuXKlXSjqu5WqVKl9OeffyolJcUmANm3b591f1bSRss4Oztnq4avv/5arq6uWrt2rVxcXKzt8+bNu+dzSakBpJubm3VU0q32799/x+MtFosWLVqkpk2bKjw8PN3+d955RwsXLswylMrsO5b2vTGbzdn+fWUm7fe0f//+dOHPtWvXdPz4cbVq1Srb5z1w4IDNCK+bN28qJiZG1apVs7aVKVNGO3fuVPPmze/r7yxPnjxq166d2rVrp5SUFIWHh2vOnDmKiIhQ2bJltXTpUjVt2lRz5861Oe7SpUsqXLhwtq+bmYy+S3///bfy5s17T4H33Up75gcPHlTTpk2t7UlJSTpy5IiqVq2a49cEADx+WFMKAIA7cHd316xZsxQZGal27dpl2q9z585KTk7WO++8k25fUlKSLl26ZN3Oly+fzXZ2tGrVSh4eHho/frwSExNt9qWNdoiPj0+3Nk2VKlXk4OCQ7rXzd+vvv//W/v37bYKAzp07a8uWLVq7dm26/pcuXUpXw+1at26t06dP24R+SUlJmj59utzd3dWkSZMsjzebzQoKCtKcOXN06tSpdPvPnj2b5fGOjo4ymUw2U7COHDmS7k1td8vR0VHBwcH65ptvdOzYMWv73r17M3xGt9u8ebOOHDminj17qmPHjuk+zz33nDZu3KiTJ09meo58+fJJUrrvWXBwsDw9PTVu3DjdvHkz3XF3elZZad68ufLkyaNZs2alGy308ccfKykpyfomy3tRq1YtFSlSRLNnz9aNGzes7VFRUenur3Pnzjpx4oQ++eSTdOdJSEjI8m2Wac6fP2+z7eDgYA1h0v5uHB0d040qWrJkyR3XLsuuLVu22KxVdfz4cf373/9Wq1at7rj+XHbUqlVLhQoV0ieffGLz97tw4ULrFD8AAO4XI6UAALgLL7744h37NGnSRH379tX48eO1Y8cOtWrVSs7Ozjpw4ICWLFmiadOmWdejCgwM1KxZszR27FiVLVtWZrM50zV+MuPp6akPPvhAvXr1Uu3atdW1a1cVKFBAO3fu1LVr1zR//nxt2LBB/fv3V6dOnVS+fHklJSXpiy++kKOjozp06HDHayQlJVmnkaWkpOjIkSOaPXu2UlJSNGrUKGu/119/XStWrFDbtm0VFhamwMBAXb16VX/99ZeWLl2qI0eOZDl6pE+fPpozZ47CwsL0+++/y8/PT0uXLtXmzZs1depU60LfWZkxY4YaNmyoKlWqqHfv3ipdurTOnDmjLVu26J9//tHOnTszPbZNmzZ6//339dRTT6lr166KjY3VjBkzVLZsWf355593vHZGRo8erTVr1qhRo0YKDw+3hmyVK1e+4zkXLlwoR0dHtWnTJsP97du311tvvaUvv/xSQ4YMybBP9erV5ejoqIkTJyouLk4uLi5q1qyZzGazZs2ape7du6tmzZrq0qWLihQpomPHjmnlypVq0KCBPvroo2zds9ls1siRI/X222+rcePGat++vfLmzatffvlF//rXv9SqVassg93MODs7a+zYserbt6+aNWum5557TjExMZo3b166NaW6d++ur776Sv369dPGjRvVoEEDJScna9++ffrqq6+0du1a1apVK8vr9erVSxcuXFCzZs1UokQJHT16VNOnT1f16tWt65y1bdtWY8aMUc+ePVW/fn399ddfWrhwYbp6ckpAQICCg4M1YMAAubi4aObMmZJSv2e5IU+ePIqMjNRrr72mZs2aqXPnzjpy5IiioqJUpkyZHBntCQAAoRQAADlo9uzZCgwM1Jw5czRixAjrosDdunVTgwYNrP1Gjhypo0eP6r333tPly5fVpEmTew6lJOnll1+W2WzWhAkT9M4778jZ2VkVK1a0rkFUrVo1BQcH69tvv9WJEyeUN29eVatWTatXr9aTTz55x/Nfv35d3bt3t257enqqdu3a+uKLL9S8eXNre968efXjjz9q3LhxWrJkiT7//HN5enqqfPnyGj169B0XVXdzc1N0dLSGDx+u+fPnKz4+XhUqVNC8efMUFhZ2V8+iUqVK2rZtm0aPHq2oqCidP39eZrNZNWrU0MiRI7M8tlmzZpo7d64mTJigQYMGyd/fXxMnTtSRI0eyHUpVrVpVa9eu1ZAhQzRy5EiVKFFCo0eP1qlTp7I8582bN7VkyRLVr19fBQsWzLBPQECA/P39tWDBgkxDqWLFimn27NkaP368Xn75ZSUnJ2vjxo0ym83q2rWrihcvrgkTJmjSpEm6fv26fHx81KhRo2ytU3Wrt956S35+fvroo480ZswYJSUlyd/fX6NHj9awYcPuen2q2/Xp00fJycmaNGmSXn/9dVWpUkUrVqxIt7C9g4ODvvnmG33wwQf6/PPPtXz5cuXNm1elS5fWwIED72p9s27duunjjz/WzJkzdenSJRUrVkzPPfecIiMjrfWPGDFCV69e1aJFi7R48WLVrFlTK1eu1PDhw7N1f3fSpEkT1atXT6NHj9axY8dUqVIlRUVF5eo0uv79+8tisWjKlCkaOnSoqlWrphUrVmjAgAEZrg0GAMC9MllYzRAAAAB4YJlMJr366qvZHsGWk1JSUlSkSBE9++yzGU6RBADgXrCmFAAAAIB0EhMT062b9fnnn+vChQsKCgqyT1EAgEcK0/cAAAAApPPrr79q8ODB6tSpkwoVKqQ//vhDc+fOVUBAgDp16mTv8gAAjwBCKQAAAADp+Pn5ydfXVx9++KEuXLigggULqkePHpowYYLy5Mlj7/IAAI8A1pQCAAAAAACA4VhTCgAAAAAAAIZ77KbvpaSk6OTJk/Lw8JDJZLJ3OQAAAAAAAI8Ui8Wiy5cvq3jx4nJwyHw81GMXSp08eVK+vr72LgMAAAAAAOCRdvz4cZUoUSLT/Y9dKOXh4SEp9cF4enrauRoAAAAAAIBHS3x8vHx9fa0ZTGYeu1Aqbcqep6cnoRQAAAAAAEAuudOySSx0DgAAAAAAAMMRSgEAAAAAAMBwhFIAAAAAAAAwHKEUAAAAAAAADEcoBQAAAAAAAMM9dm/fAwAAAAAgNyQnJ+vmzZv2LgPINU5OTnJ0dLzjW/Xu+nw5chYAAAAAAB5TFotFp0+f1qVLl+xdCpDrHB0dZTab5eXldd/hFKEUAAAAAAD3IS2QMpvNyps3b46NIgEeJBaLRUlJSYqPj9epU6eUkJAgb2/v+zonoRQAAAAAANmUnJxsDaQKFSpk73KAXOfh4SEXFxedO3dOZrNZjo6O2T4XC50DAAAAAJBNaWtI5c2b186VAMbJly+fLBbLfa+hRigFAAAAAMB9YsoeHic59X0nlAIAAAAAAIDhCKUAAAAAAABgOEIpAAAAAADwwAsLC5Ofn989HRMdHS2TyaTo6Ohcqel+RUZGZnsqXNqx586dy+GqjEMoBQAAAAAA0omKipLJZLJ+XF1dVb58efXv319nzpyxd3kPvKCgIAUEBNi7jExdv35dw4YNU/HixeXm5qa6detq3bp1htbgZOjVAAAAAAB4jDwI659bLPd3/JgxY+Tv76/ExERt2rRJs2bN0qpVq7Rr1y5D3zr4ySefKCUl5Z6Oady4sRISEpQnT55cqur+vP322xo+fLhdrh0WFqalS5dq0KBBKleunKKiotS6dWtt3LhRDRs2NKQGQikAAAAAAJCpkJAQ1apVS5LUq1cvFSpUSO+//77+/e9/6/nnn8/wmKtXrypfvnw5Woezs/M9H+Pg4CBXV9ccrSMnOTk5ycnJ+GjmP//5j7788ktNmjRJQ4cOlST16NFDAQEBeuONN/TLL78YUgfT9wAAAAAAwF1r1qyZJCkmJkZS6ogbd3d3HTp0SK1bt5aHh4deeOEFSVJKSoqmTp2qypUry9XVVUWLFlXfvn118eLFdOddvXq1mjRpIg8PD3l6eqp27dpatGiRdX9Ga0p9+eWXCgwMtB5TpUoVTZs2zbo/szWllixZosDAQLm5ualw4cLq1q2bTpw4YdMn7b5OnDih0NBQubu7q0iRIho6dKiSk5Oz/fxuldGaUiaTSf3799c333yjgIAAubi4qHLlylqzZs0dz3f06FGVLVtWAQEBWU6xXLp0qRwdHdWnTx9rm6urq15++WVt2bJFx48fz/5N3QNCKQAAAAAAcNcOHTo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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install plotnine pandas"
      ],
      "metadata": {
        "collapsed": true,
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "011oo48DOZyK",
        "outputId": "061d01cc-9c0c-413b-e828-1be54d486bda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: plotnine in /usr/local/lib/python3.10/dist-packages (0.12.4)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (2.0.3)\n",
            "Requirement already satisfied: matplotlib>=3.6.0 in /usr/local/lib/python3.10/dist-packages (from plotnine) (3.7.1)\n",
            "Requirement already satisfied: mizani<0.10.0,>0.9.0 in /usr/local/lib/python3.10/dist-packages (from plotnine) (0.9.3)\n",
            "Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.10/dist-packages (from plotnine) (1.25.2)\n",
            "Requirement already satisfied: patsy>=0.5.1 in /usr/local/lib/python3.10/dist-packages (from plotnine) (0.5.6)\n",
            "Requirement already satisfied: scipy>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from plotnine) (1.11.4)\n",
            "Requirement already satisfied: statsmodels>=0.14.0 in /usr/local/lib/python3.10/dist-packages (from plotnine) (0.14.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2024.1)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (1.2.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (4.53.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (24.1)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->plotnine) (3.1.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from patsy>=0.5.1->plotnine) (1.16.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from plotnine import ggplot, aes, geom_bar, theme, element_rect, element_text, element_blank, labs, position_dodge, scale_fill_manual\n",
        "\n",
        "# Data preparation\n",
        "data = {\n",
        "    'Labels': ['Before', 'After'],\n",
        "    'Precision_0': [0.97, 0.70],\n",
        "    'Recall_0': [1.00, 0.81],\n",
        "    'F1_Score_0': [0.99, 0.75],\n",
        "    'Precision_1': [0.51, 0.75],\n",
        "    'Recall_1': [0.09, 0.62],\n",
        "    'F1_Score_1': [0.16, 0.68]\n",
        "}\n",
        "\n",
        "df = pd.DataFrame(data)\n",
        "\n",
        "# Melting the dataframe to long format for plotnine\n",
        "df_melted = pd.melt(df, id_vars=['Labels'], var_name='Metric', value_name='Score')\n",
        "\n",
        "\n",
        "# Renaming the Metric values to group by Class\n",
        "df_melted['Metric'] = df_melted['Metric'].replace({\n",
        "    'Precision_0': 'Precision (No link)',\n",
        "    'Recall_0': 'Recall (No link)',\n",
        "    'F1_Score_0': 'F1 Score (No link)',\n",
        "    'Precision_1': 'Precision (Link)',\n",
        "    'Recall_1': 'Recall (Link)',\n",
        "    'F1_Score_1': 'F1 Score (Link)'\n",
        "})\n",
        "\n",
        "# Reorder the Labels to ensure 'Before' is on the left and 'After' is on the right\n",
        "df_melted['Labels'] = pd.Categorical(df_melted['Labels'], categories=['Before', 'After'], ordered=True)\n",
        "\n",
        "# Define earthy colors\n",
        "earthy_colors = [\"#8FBC8F\", \"#A52A2A\"]  # Green and Brown\n",
        "\n",
        "# Plotting\n",
        "plot = (\n",
        "    ggplot(df_melted, aes(x='Metric', y='Score', fill='Labels')) +\n",
        "    geom_bar(stat='identity', position=position_dodge(width=0.8), width=0.7) +\n",
        "    scale_fill_manual(values=earthy_colors) +\n",
        "    theme(\n",
        "        axis_text_x=element_text(size=16, color='black', weight='bold', rotation=45, hjust=1),\n",
        "        axis_text_y=element_text(size=16, color='black', weight='bold'),\n",
        "        axis_title_x=element_text(size=18, color='black', weight='bold'),\n",
        "        axis_title_y=element_text(size=18, color='black', weight='bold'),\n",
        "        plot_title=element_text(size=22, color='black', weight='bold', hjust=0.5),\n",
        "        legend_title=element_text(size=18, weight='bold'),\n",
        "        legend_text=element_text(size=16),\n",
        "        panel_grid_major=element_blank(),\n",
        "        panel_grid_minor=element_blank(),\n",
        "        # panel_background=element_rect(fill='white'),\n",
        "        plot_background=element_rect(fill='white')\n",
        "\n",
        "    ) +\n",
        "    labs(\n",
        "        title='Metrics Before and After Undersampling',\n",
        "        x='Metric',\n",
        "        y='Score'\n",
        "    )\n",
        ")\n",
        "\n",
        "plot.save('precision_recall_f1_scores_earthy.png', dpi=300, width=12, height=8)\n",
        "print(plot)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 569
        },
        "id": "ozzQ6GLmOgbD",
        "outputId": "3dcbd5ce-f97b-484a-fcdd-7dfdc2f959d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/plotnine/ggplot.py:587: PlotnineWarning: Saving 12 x 8 in image.\n",
            "/usr/local/lib/python3.10/dist-packages/plotnine/ggplot.py:588: PlotnineWarning: Filename: precision_recall_f1_scores_earthy.png\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "image/png": {
              "width": 640,
              "height": 480
            }
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "3EhGlPk9NEPu"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}