Project 4/finalProject.ipynb

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  "metadata": {
    "colab": {
      "name": "finalProject.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "J8luR7MDI_mR",
        "W0qc-Eb1JLiC",
        "I_CzlBlvfCKT",
        "SjK_X2SwFoBZ"
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Preprocessing"
      ],
      "metadata": {
        "id": "J8luR7MDI_mR"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "TURoB2Td-dZF"
      },
      "outputs": [],
      "source": [
        "#read from csv\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.model_selection import train_test_split\n",
        "from xgboost import XGBClassifier\n",
        "import numpy as np\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.metrics import classification_report, confusion_matrix\n",
        "from xgboost import plot_tree\n",
        "from matplotlib.pylab import rcParams\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.metrics import precision_recall_curve\n",
        "from sklearn.model_selection import *\n",
        "from sklearn.metrics import roc_auc_score\n",
        "\n",
        "df = pd.read_csv('diabetes.csv')\n",
        "df = df.iloc[: , 1:]\n",
        "# pd.set_option('display.max_rows', df.shape[0]+1)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت مقادیر نام ستون هایی که بین آنها فاصله است تغییر میکند به حالتی که اسپس بین کلمات حذف شده است و کلمات پشت سر هم بدون فاصله قرار میگیرند.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "6jwR11FFChGa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#rename column names\n",
        "columns_names_dict = {}\n",
        "columns = df.columns.values.tolist()\n",
        "for col in columns:\n",
        "  if \" \" in col:\n",
        "    columns_names_dict[col] = col.replace(\" \", \"\")\n",
        "\n",
        "df.rename(columns = columns_names_dict, inplace = True)\n",
        "columns = df.columns.values.tolist()"
      ],
      "metadata": {
        "id": "CmwxCtVe0jYK"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت مقادیر Null را با مقادیر مناسب جایگذاری میکنیم. یکی از راه ها این است که به جای مقادیر Null از میانگین، میانه، واریانس، مد و یا یکی از داده های ستون به صورت تصادفی و یا مقداری ثابت استفاده کنیم که در این جا مقادیر Null را با مد پر کرده ایم.\n",
        "    <br/>\n",
        "    همچنین در ستون Income یکی از سطر ها مقدار Unkown دارد که آن را با NaN جایگذاری میکنیم تا بعد بتوانیم مقدار آن را با مد پر کنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "6rF79WpuDzGo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#handle null values\n",
        "for col in columns:\n",
        "  if df.isna()[col].sum() > 0:\n",
        "    df[col].fillna(df[col].mode()[0], inplace=True)\n",
        "\n",
        "for col in columns:\n",
        "  if df.isna()[col].sum() > 0:\n",
        "    print(\"True\")\n",
        "\n",
        "df.Income.replace(['Unknown'], [np.NaN], inplace=True)"
      ],
      "metadata": {
        "id": "PSZQ2YsZ0l0r"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت کار نرمالایز کردن ستون هارا انجام میدهیم. چهار ستون BMI, MetalHealth, PhysicalHealth و Age را نرمالایز میکنیم.\n",
        "    <br/>\n",
        "    برای ستون BMI بدین صورت عمل میکنیم که ابتدا این ستون را به یک فیچر categorical تبدیل میکنیم. سپس در ادامه از روش OneHotEncoding استفاده میکنیم.\n",
        "    <br>\n",
        "    برای ستون های Age, MentalHealth, PhysicalHealth که به اندازه ‌BMI توزیع مقادیر متفاوتی ندارند و همچنین بازه ی مقادیر آنها کمتر است از روش Min-Max برای نرمالایز کردن ستون استفاده میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "0sZxQH96E6Fh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#normalize data\n",
        "\n",
        "# field = 'BMI'\n",
        "# print(df[field].min(), df[field].max())\n",
        "\n",
        "BMI_Category = pd.cut(df.BMI.astype(float).astype(int), bins=[11, 19, 40, 53, 98], labels=[\"Cat1\", \"Cat2\", \"Cat3\", \"Cat4\"])\n",
        "df = df.drop('BMI', 1)\n",
        "df.insert(4, 'BMI', BMI_Category)\n",
        "\n",
        "df[\"MentalHealth\"] = (df[\"MentalHealth\"] - df[\"MentalHealth\"].min()) / (df[\"MentalHealth\"].max() - df[\"MentalHealth\"].min())\n",
        "df[\"PhysicalHealth\"] = (df[\"PhysicalHealth\"] - df[\"PhysicalHealth\"].min()) / (df[\"PhysicalHealth\"].max() - df[\"PhysicalHealth\"].min())\n",
        "df[\"Age\"] = (df[\"Age\"] - df[\"Age\"].min()) / (df[\"Age\"].max() - df[\"Age\"].min())\n",
        "\n",
        "# df.iloc[:100, :]\n",
        "\n",
        "# df['BMI'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mXA0qC2o00oD",
        "outputId": "8630c408-dc9a-4912-881b-e90ab1689e73"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n",
            "  import sys\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت فیچر هایی که categorical هستند را به ویژگی های عددی با استفاده از روش OneHotEncoding تبدیل میکنیم. ۵ تا از ویژگی ها categorical هستند که این ستون ها عبارتند از: GeneralHealth, Sex, Education, Income و BMI که در قسمت قبلی آن را تبدیل به یک ویژگی دسته بندی شده تبدیل کردیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "ciW0b_9TGEmH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#OneHotEncoding\n",
        "\n",
        "encoder_df = pd.get_dummies(df.BMI, prefix='BMI')\n",
        "df = df.join(encoder_df)\n",
        "df.drop('BMI', axis=1, inplace=True)\n",
        "\n",
        "encoder_df = pd.get_dummies(df.GeneralHealth, prefix='GeneralHealth')\n",
        "df = df.join(encoder_df)\n",
        "df.drop('GeneralHealth', axis=1, inplace=True)\n",
        "\n",
        "encoder_df = pd.get_dummies(df.Sex, prefix='Sex')\n",
        "df = df.join(encoder_df)\n",
        "df.drop('Sex', axis=1, inplace=True)\n",
        "\n",
        "encoder_df = pd.get_dummies(df.Education, prefix='Education')\n",
        "df = df.join(encoder_df)\n",
        "df.drop('Education', axis=1, inplace=True)\n",
        "\n",
        "encoder_df = pd.get_dummies(df.Income, prefix='Income')\n",
        "df = df.join(encoder_df)\n",
        "df.drop('Income', axis=1, inplace=True)\n",
        "\n",
        "df.iloc[:100, :]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "xCiSzOVtDVNk",
        "outputId": "075ca42d-9c55-47bf-9215-7cdb625281ba"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    Diabetes_binary  HighBP  HighCholesterol  CholesterolCheck  Smoker  \\\n",
              "0               0.0     1.0              0.0               1.0     0.0   \n",
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              "\n",
              "    Stroke  HeartDiseaseorAttack  PhysicalActivity  Fruits  Veggies  ...  \\\n",
              "0      0.0                   0.0               1.0     0.0      1.0  ...   \n",
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              "\n",
              "    Education_Cat5  Education_Cat6  Income_Cat1  Income_Cat2  Income_Cat3  \\\n",
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              "    Income_Cat4  Income_Cat5  Income_Cat6  Income_Cat7  Income_Cat8  \n",
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              "\n",
              "[100 rows x 42 columns]"
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              "      <th></th>\n",
              "      <th>Diabetes_binary</th>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>97</th>\n",
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              "      <th>98</th>\n",
              "      <td>0.0</td>\n",
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              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>0.0</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 42 columns</p>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در نهایت در آخرین قسمت Preprocessing ستون جواب نهایی و لیبل را از دیتاست جدا میکنیم که همان ستون Diabetes_binary است.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "dPvU0oZVGpCg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Spli label\n",
        "\n",
        "label = df[[\"Diabetes_binary\"]]\n",
        "df = df.drop('Diabetes_binary', 1)\n",
        "\n",
        "df.iloc[:100, :]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        },
        "id": "bkxg_WwrJQPp",
        "outputId": "1b5d04e3-8e79-475e-e707-20f4b5e3b7b9"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n",
            "  after removing the cwd from sys.path.\n"
          ]
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              "    HighBP  HighCholesterol  CholesterolCheck  Smoker  Stroke  \\\n",
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              "    HeartDiseaseorAttack  PhysicalActivity  Fruits  Veggies  \\\n",
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              "\n",
              "    HeavyAlcoholConsumption  ...  Education_Cat5  Education_Cat6  Income_Cat1  \\\n",
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              "    Income_Cat2  Income_Cat3  Income_Cat4  Income_Cat5  Income_Cat6  \\\n",
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              "99            0            0            1            0            0   \n",
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              "    Income_Cat7  Income_Cat8  \n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</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",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 41 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-808758b6-5da1-462c-a3c2-d95d035ae513')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\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",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-808758b6-5da1-462c-a3c2-d95d035ae513 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-808758b6-5da1-462c-a3c2-d95d035ae513');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Build Model"
      ],
      "metadata": {
        "id": "W0qc-Eb1JLiC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت باید داده های آموزشی و داده های تست را از هم جدا کنیم و از دیتاست اصلی درصدی را برای تست کردن مدل درنظر بگیریم. که از متد train_test_split برای این منظور استفاده میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "efcdZwLDG6qy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#split train and test data\n",
        "df = df.iloc[:, :].values\n",
        "label = label.iloc[:, :].values\n",
        "X_train, X_test, y_train, y_test = train_test_split(df, label, test_size=0.3, random_state=1)\n",
        "y_train = y_train.ravel()\n",
        "y_test = y_test.ravel()\n",
        "print(df.shape, X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WNJuwqxSKURK",
        "outputId": "ac487b10-defe-4ed5-f500-637cc3db15cd"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(70692, 41) (49484, 41) (21208, 41) (49484,) (21208,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت مدل Classifier‌ خود را که همان XGBClassifier است میسازیم. سپس آرگومان های ورودی آن را با مقادیر مناسب پر میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "FOomme2UHQW_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#build model\n",
        "model = XGBClassifier(learning_rate=0.1, max_depth=4, n_estimators=200, \n",
        "                      subsample=0.5, colsample_bytree=1, random_seed=123, random_state=123, eval_metric='auc', verbosity=1, early_stopping_rounds=10)\n",
        "print(model.get_params())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MCTzoAJCPN8Y",
        "outputId": "f46d0ae3-3dc5-466e-c85c-67cf7b4c3607"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'base_score': 0.5, 'booster': 'gbtree', 'colsample_bylevel': 1, 'colsample_bynode': 1, 'colsample_bytree': 1, 'gamma': 0, 'learning_rate': 0.1, 'max_delta_step': 0, 'max_depth': 4, 'min_child_weight': 1, 'missing': None, 'n_estimators': 200, 'n_jobs': 1, 'nthread': None, 'objective': 'binary:logistic', 'random_state': 123, 'reg_alpha': 0, 'reg_lambda': 1, 'scale_pos_weight': 1, 'seed': None, 'silent': None, 'subsample': 0.5, 'verbosity': 1, 'random_seed': 123, 'eval_metric': 'auc', 'early_stopping_rounds': 10}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت داده های تست را طبق مدل بدست آمده پیش بینی میکنیم و دقت مدل را چاپ میکنیم که دقت آن 74.6 درصد است.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "fycQSFmcHnYP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#predict test data\n",
        "# print(X_train.dtypes)\n",
        "\n",
        "model.fit(X_train, y_train)\n",
        "print(model)\n",
        "y_pred = model.predict(X_test)\n",
        "\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "accuracy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9SC_dP-KRPdP",
        "outputId": "0e824f06-c72c-4e22-ba8c-c8d671c1d3a6"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "XGBClassifier(early_stopping_rounds=10, eval_metric='auc', max_depth=4,\n",
            "              n_estimators=200, random_seed=123, random_state=123,\n",
            "              subsample=0.5)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.7463692946058091"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ماتریس درهم ریختگی را چاپ و آن را رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "1NKZmbOUJd8u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_confusion_matrix(y_test, y_pred):\n",
        "  cm = confusion_matrix(y_test,y_pred)\n",
        "  print(cm)\n",
        "  plt.figure(figsize=(15,10))\n",
        "  plt.clf()\n",
        "  plt.imshow(cm, interpolation='nearest', cmap=plt.cm.Wistia)\n",
        "  classNames = ['Negative','Positive']\n",
        "  plt.title('Confusion Matrix')\n",
        "  plt.ylabel('True label')\n",
        "  plt.xlabel('Predicted label')\n",
        "  tick_marks = np.arange(len(classNames))\n",
        "  plt.xticks(tick_marks, classNames, rotation=45)\n",
        "  plt.yticks(tick_marks, classNames)\n",
        "  s = [['TN','FP'], ['FN', 'TP']]\n",
        "\n",
        "  for i in range(2):\n",
        "      for j in range(2):\n",
        "          plt.text(j,i, str(s[i][j])+\" = \"+str(cm[i][j]))\n",
        "  plt.show()\n",
        "\n",
        "plot_confusion_matrix(y_test, y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 686
        },
        "id": "FxxR9Y1RbV7K",
        "outputId": "53b3056c-5acb-477c-8737-59387c280e04"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[7479 3202]\n",
            " [2177 8350]]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت درخت تصمیم ساخته شده را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "lasmkmMAJxGg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rcParams['figure.figsize'] = 50,20\n",
        "plot_tree(model)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        },
        "id": "Xf4mg5MLeqeD",
        "outputId": "3fcccacc-3262-4d43-f39d-1a0eb613e01b"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 3600x1440 with 1 Axes>"
            ],
            "image/png": 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cnTgRSkqgsBAKCiA3940FeF9LKpWiqamJW2+9lZycHP72b/+W6dOnk5OTM6wbbKMooquri9/97nfcfffdLDzvPK6/+mpKDhwgtmQJLFsGXV0wcyZcdBGcckp4YgsKXqoxliRJkiRJkjScvG5Dr4FeSZIkSZIkSRIAySS0tobW3dbWENrdsQM6OqCzE/LyQmC3rg4aG6G+Pvw78Qfngnurc7aD4df77ruPX/7yl8ybN48PfehDzJw5c1iGevv6+liyZAk/+9nPOHToEP/zf/5PFi1aRFZWFkceTSYD69fDkiWwfDm0t4fK47POCiHfU04JqWlJkiRJkiRJw4WBXkmSJEmSJEnSS6276TSkUtDTA5s2hcbd9etDgPfw4ZATHT8+hHcbG8O/y8qgoiJcZmUNzfyTySQbN27kxz/+McuXL+e8887j6quvpq6u7oRu7I2iiEwmQ29vLytXruRHP/oRe/fu5YMf/CDvfe97GTt27GvPPYrCD2X37vCDWrIENmwI1cjz5sHFF8O0aZCdHZLVJ+hzIEmSJEmSJMlAryRJkiRJkiSdlDKZkAU9cCCMPXtgyxbYujU08HZ0hPBuXV3IhDY2wqxZUFoK8fhLA06cnGgURaTTabZv384999zDihUrmDp1Ku985zs55ZRTqK2tJTs7e6inCbzULLx582aWL1/O4sWL6evr4/3vfz9XXnklxcXFxGKxNx5EjqKQxu7rg5Ur4dFH4bnnQpi3sRHOPRcmTQojN/f4PjhJkiRJkiRJR8tAryRJkiRJkiSNRC//eDeKwti/P7TuPv88bNwYil17e6G4GEpKoKEhNO9WV8O4ceGysPDECewejVQqxdatW1m6dClLlixh7969NDQ0cM4553D++eczZswY4oOJZDiuDb4v/6x9sEn40UcfZcWKFbS3tzNjxgwuuOACzjjjDKqqqt6auUQRtLWFH/SaNbB8eUht19bC/PlwwQXhhz14X8PxhyxJkiRJkiSNHAZ6JUmSJEmSJGkkiCJIpaCrK7TrdnbCrl0hvLtlC+zYAd3dUFkZgruNjTBjBtTXQ15eKHLNyYGsrJGT7YyiiCiK6O3tZf/+/Tz22GMsWbKE7du3U1FRwezZsznttNOoq6ujtLSUoqIiCgsLycvLe0XY92jvM5VK0dvbS3d3N4cPH+bgwYNs3LiRVatWsWnTJtLpNKeddhoXXHABc+fOpbi4mJycnOMXKk6nQ3K7owOWLoXFi2HzZhg9GubNg4ULYezY8HUicXzmIEmSJEmSJOn1GOiVJEmSJEmSpOGqtzcEdbdvD6Hd7duhpQX6+sLtZWWhhLW+Hurqwhg3LoR2T1aZTIZdu3axadMm1q1bR1NTEwcPHiSdThOPx6moqKCqqoqxY8dSWlpKSUkJJSUl5Ofnk0gkyM7OJisri2QySTqdpr+/n56eHjo6Ojh8+DAHDhxg79697N+/n66uLmKxGNnZ2YwfP54ZM2YwY8YMGhsbKS0tPa6twK8riuDFF2HlytDcu3FjuG72bDj99BDyHTt2aOYmSZIkSZIknZwM9EqSJEmSJEnSiSqKYGAA+vvDaG+HpqaQv3z+edi5E5LJ0Lo7bVoI7s6ZA6NGQUEBFBdDfv7JHeB9PZlMhr6+Prq6ujh8+DBdXV3s3r2bnTt30tLSQmdnJx0dHXR2dtLX10cymWRgYIB0Ok1OTg5ZWVnk5eWRn59/JPxbUVHBhAkTqKurY8yYMRQUFFBcXExhYeHxbeE9VgMDcPAg7N0LTzwBTz0F+/aFX6gLLoCzzw6/SEVFcIytxZIkSZIkSZL+JAO9kiRJkiRJknSiyGTgwIGQrdy1KwR2t28Pl319IdRbVRWCu5Mnh8zl9OkhvPtyJ1pmdLj4E5+JH5MTLsD7WgYfexSFX7rFi2HZMtizJyTG58+HWbNCi29FxZBOVZIkSZIkSRqBDPRKkiRJkiRJ0tslisLIZCCdhlQq5CXXr4c1a6C5GVpbQyC3uhrGjoXGRqirCxnK0aOhvBxycw3t6m3Q0xPS5Fu2wJNPhl/SeBzOPBPe+U447TTIzoZEwl9ISZIkSZIk6c0x0CtJkiRJkiRJx0sUwcAAtLXB/v2hfXfnTmhqCkHe3btDDnL06NC0O3NmKEAdNy7kJOPxMGIx85IaQlEUEujJJGzYAA89BCtWhF/uadNg4UJoaIBJk6CwcKhnK0mSJEmSJA1HBnolSZIkSZIk6c14+ceoUQTd3aFpd9OmENzdujUEeuNxKC4OzbtTp8L48WGMGxfad7Oyhu4xSEft8GF4/nlYuxaWLQsJ9aoqmDcPzj0XZs16KYVuGl2SJEmSJEn6Uwz0SpIkSZIkSdLRyGRCaLe7O2Qa9++HF14I4d1t26C1FXJyoK4uBHdnzAjZxuJiyM0Nt+XkmHHUCJHJQG8vdHbCs8/Cgw+GFt+SEpg7F9797pBcHzUqvAAkSZIkSZIkvRoDvZIkSZIkSZL0elIp2LcPtm+HLVtCaHfHDmhvD6272dlQUwMTJ0JtbQjx1taG7KKhXZ2UDhyAFSvCWL8+vIgaGuDMM+H002HSJF8ckiRJkiRJ0isZ6JUkSZIkSZJ0cosiSKchmYT+/lA2uns3rF4NW7eGPGJHBxQVhaLRhgY47TQYOxbKysL1xcUh2CvpZVIpOHgw1FavWAGPPx5eXA0NsGABvPOdUFoKBQWQSAz1bCVJkiRJkqShZKBXkiRJkiRJ0sklikJot6UlZAtbW0Pz7u7d0NYGhw6FgG5tLUyeDLNmwZQpMGZMaOR9OUtGpTfg5X9r2LsXHn4Ynn461F2XlcHcuXDqqTBzZnih+cKSJEmSJEnSycdAryRJkiRJkqSRZfBjzUzmpdHZCevWQXNzuNyxI4R6i4tDfrChIYR3q6uhshJGjQrFoeYKpeOkvx927Qpp+meegVWrwnWnngqLFsFZZ0F+PmRl+UKUJEmSJEnSycBAryRJkiRJkqThL52Gjo7QsHvwYGjbbW6GrVvhxRehpycEdCdNghkzwpg+/aW8YFZWaN81Nyi9zaIovICTSdi+HR58MLT3dnaGpP1550FjI9TUhDZfX6SSJEmSJEkamQz0SpIkSZIkSTrx/eFHlclkCO1u3hzGpk3h62QSCgqgpASmTYPaWpgwIYxx4yA7e2jmL+ko9PRAUxOsXg2//32o1C4qgjPPhAUL4LTTXnoxG/CVJEmSJEnSyGCgV5IkSZIkSdKJJ4pgYAC6u6GrCw4fhi1bYOPGl5p3k0moqgqtu3PmwOzZMHo05OVBbm64tHVXGsYyGejrC229L7wAv/sdPPcc5OTAqafCRReFDUBFRXjB+2KXJEmSJEnS8GWgV5IkSZIkSdKJobMTtm2DnTvD5Y4dsHcv9PaG8G51dWjanTo1ZPgmTYJRo8zwSSeVri5YsQKeeQbWrQuB35qa0N576qmhmjsra6hnKUmSJEmSJB0tA72SJEmSJEmS3h6ZTAjmDgyEy717Q+Pu88/Dhg3h6yiCMWNgypQQ2J05E8rKoLg4XFrCKQmAdBoOHYI9e0Kw97HHQn33mDGwcCFceGH4d14eJBJuOCRJkiRJknSiM9ArSZIkSZIk6fgYDO3u3w8vvhjG5s3hsrs7BHurq2H6dJg8GRoboaEBsrNfmb0zhyfpNQ3+HSOK4OBBeOIJWLIEmpqgqAhOOQXOOCNsYCZMgHh8aOcrSZIkSZIkvToDvZIkSZIkSZKOTRS9NDKZcOb7nTth/frQvNvUBPv2QW4uVFSE8O6sWTBuHFRVwejR4fo/DPBK0puSSkFLS9gIrVoFy5dDZ2fYAC1cCOeeCyUlIdwbi7kBkiRJkiRJ0onAQK8kSZIkSZKkNyaKoKcH2tuhrQ0OHIAtW0LrbksL7N4dzm4/fnxo3Z01K4yKinDG+6yscAnm5yS9DQaPNhgYCHXhjzwCjz8Oe/ZAfT2cfTa84x1hozVqlO29kiRJkiRJGkoGeiVJkiRJkiQFf/hx4OAZ7DdvDqO5GXbsgI6OkHsrLAw5uClTwmVtbbgsKTl+gd1MJsMjjzxCT08Pl1xyCdnZ2W9oua1bt/Lggw/yoQ99iIqKiuMzOUknvoGBcCTCihWhvXfr1nCkwRlnwPz5cOaZUFAQvtcjDyRJkiRJkvT2ed1Ab+JtnIgkSZIkSZKkIZBKQW9vaN7t7oZ9+2DDBnjhhRDgPXAgZNsaGkJw95xzwmVhYWjjzc+H7Oy3L/cWRRFbtmyho6ODiy+++A0v197ezooVK7jsssuO4+wknfBycqCxMdSIX3VVOEJh2zZ4+GH45jdD4PeMM+Bd74KpU6G8PGwEDfdKkiRJkiRpCNnQK0mSJEmSJI0gUQR9fdDaGpp2d+4MObbt26GzM5yZPjs7nIl+0qRwOdi++waLcEecTCZDU1MTo0aNYtSoUUM9HUnHU28vrFsHTz4Jq1dDVxeMGRMCvqedFoLAubmGeyVJkiRJknQ8vG5Dr4FeSZIkSZIkaZiJotC6m0pBMhlad5ubYe3acPnCCyGzVlEB1dWhgHL2bKisDEWUxcVQWgpZWS+t86c//Sl33HEHo0eP5itf+Qr79u3jO9/5Dqeeeip//dd/ze7du/nhD39IS0sLZ5xxBv/jf/wPenp6+Jd/+RfWr19PXl4e//iP/8jo0aNfdc7t7e18+9vf5plnnmHSpEm0tbWRSqUYP3483d3ddHR0cN555/GpT32K7du384UvfIFp06Zx4403snfvXu68806am5spLS3ln/7pn2htbeX73/8+LS0tVFdX8/nPf54f/OAHbNmyhVtuuYUVK1Zwzz338JGPfISVK1fS2trK9ddfz4IFC8hkMixfvpz777+fvXv3EkURDQ0N3HTTTZSWlr5NP0VJQyqTgcOH4cUXoakJHnsM1q+HsjI491y48EKoqwvh3re4onzdunV8+ctfZvbs2eTm5rJy5UoWLVrExz/+cbKysmhtbeUHP/gB69evp7i4mD/7sz/jwgsvJJHwpIuSJEmSJEnD3OsGev30R5IkSZIkSTrBDebO9uwJo7UVNm+GlhbYty8075aXQ20tzJgBV18NDQ0htBuLvXK8lve973389Kc/ZcqUKdTV1TFp0iQmTpzINddcQyKR4O/+7u9417vexSc+8Qk+/elPU1BQQFdX15FQ75NPPknWyxPCf6CsrIyFCxfy61//mnvuuYe8vDz+4i/+gqKiIr785S+zfv16/uZv/obLLruM+vp6LrzwQh599FH6+/u56667KCsr49577+WRRx5hYGCAb37zm8yfP59bb72Vhx56iLKyMj72sY9x5ZVX0tPTw4IFC/j+979PQUEBt956K7fffjv/+I//yJlnnsn+/fu5+eab+au/+isWLVrEzTffzKFDhygpKTkOPz1JJ6R4PGwkS0pCK+9ll4UN7TPPwMMPw2c/G8K8M2bA/PkwfTpMnAiJxJsO986cOZMJEyawZ88evvKVrzBz5kxuvPFGrrrqKioqKrjpppuoqKjge9/7HitWrOCmm25i9OjRnHbaaW/NY5ckSZIkSdIJyUCvJEmSJEmSNMQGT6IVRWGk0yGou3EjbNoUzg7f0gI9PSF/NnYsTJkCc+bAuHEwalS4Lj//2HNmeXl5XH755dx+++383d/9Hfv27aOkpITa2lqam5vZs2cPCxYsoKamhne84x0sXbqU008/nd///vcsX76cRYsWUVBQ8Jrrj8VixGIxsrKyqKqqIisri8bGRgoLCyktLWXq1Knk5eVx8OBB6uvricfjR5ZLJBI88cQTnHPOObznPe8hHo+TSCR4+OGHmTVrFpdeeik5OTlHlhlcDmD8+PEUFxcze/ZslixZQm9v75FG4JkzZ1JZWUljYyNLliwhiqIjy0k6SQy+5mOxsIG96KLQzju4EV67Fn7yE9i/HyZNggsuCA2+o0e/VHN+lNuNwe1hZWUl5eXlNDQ0UFRUxKFDh8hkMqxZs4ZvfOMbVFdX8+53v5sf/vCHPPzwwwZ6JUmSJEmSRjgDvZIkSZIkSdLbLIogmYSODjh0KIzdu0N4d/Pm8O/+/hDUnTIFzjkHZs4M5ZA5OeHs74lEKJh8q/KnsViMc845h7vvvptHH32UAwcOcPHFFwNw+PBhWlpauOmmmyguLgrMA0sAACAASURBVKavr49TTjmF//7f/zuZTIZbb72VRCLB97//fRobG4/qPqP/SjMPBmkHvx6USCS4/vrrufPOO/nc5z5HaWkpd9xxBzfffDPf+c53uOGGG6ipqeH2229/3fsaDPtGUURFRQX19fXcf//9zJ8/n6eeeor3vOc9hnklBVlZUF0djpQ477ywQT54EJYuhQcfhDvvDJXoZ58Nc+fC+PFQVXXMG+WXb/86OjqIooji4mIgHGxRUlLCoUOH3tKHKEmSJEmSpBOPgV5JkiRJkiTpbdDTA9u2wdatIbS7ZUto3Y2iENKtrITJk+E97wk5sQkTQpZssADyeIvFYtTW1rJw4ULuuusuLrroIurq6ojFYowePZoJEybwjW98g7lz5wKQyWRob2/nk5/8JNdccw2f/exn+fnPf87NN9/8ls4rnU6TSCT4/Oc/z8c+9jE+9alP8Ytf/IJrrrmGr33ta+zYsYO//Mu/ZPHixSxYsOANrbO0tJQzzjiDrq4utm/fzp//+Z9z4YUXGuiV9EqxWNgIFxSE8d/+G1x5JezYAStXwqpV8Nvfhg357NmwYAGceSaUlx/z0RajRo0iHo/T1tYGQFdXFwcPHnzD2zdJkiRJkiQNXwZ6JUmSJEmSpLdAJgMDAyG429sbWnc3bgxj0ybYtSt835gxIbh77rkwY0bIfeXnh6xYXl4oeBwqWVlZfOhDH+K+++7jiiuuoKKiAoDKykpmzJjBvffeS1ZWFvn5+RQUFPDQQw+Rn59PY2MjiUSCuro6HnjgAe655x6+/e1vM3HixCPrTqVSHDp0iIGBAfbv309BQQGdnZ0MDAzQ2dlJW1sb/f39tLe309HRwYEDB+jq6mLPnj08+OCD1NTUUFtbS25uLqNGjeLuu+9m7ty5lJaWUlhYyKhRo2htbaW/v5+9e/cSj8fp6+tj//799PX1cfDgQXp7ezl8+DCdnZ0sWbKEa6+9lhkzZgBw6NAhEokE2dnZQ/HUSxouEgloaID6erj88pcq1h9/HO64A77+dTj9dFi0KIR8y8uhsDAEfP8r5Du4LUomk3R3d9Pe3k5/fz9tbW3U19dzySWX8H/+z/+hrKyMlStX0tXVxaWXXjq0j1uSJEmSJEnHXdYtt9zyere/7o2SJEmSJEnSySqTgQMHQmB35Ur4f/8P/u//DePnP4dHHgm3l5WFM7Z/+MNw/fVw9dVwwQUwa1YI95aWhjBvdvYxFzq+pSorK3n++ee5+uqrGTNmDACJRIKzzjqLtrY2nn76aVpbW5k8eTKFhYWsXLmSNWvWMG/ePK666ip6e3v55S9/yezZs6mvrz+y3u7ublauXElFRQWZTIb+/n52795NTk4OlZWVbNq0iYKCAnJzc8lkMrzwwguUlZWRlZVFfX09zzzzDOvWreOCCy7g8ssvp6+vj6VLl7Jx40be//73c8opp/Dwww9TVVVFT08PEFqHBwYGGD9+PGvXrqW8vJxRo0ZRU1PDpk2b2LBhA2vWrGH58uX8x3/8B1VVVUyaNMmmXkl/WiwWwr1FRVBdDWedFdp758+Hjg549NHwZrBkyUt17KWlkJPDjp072bZtG7m5udTU1LB582by8/PJysqisbGRs846i4GBAZYuXUp2djY33HAD9fX1bpskSZIkSZKGv07gn17rxlgURa+38OveKEmSJEmSJI1UURRGKhVGMhladpuaYPXqEOT9rzOiM2FCKGucOhUmTgyZrYqKUMyYk3NiBHX/lN7eXnJycti9ezf3338/n/3sZ0kkju4EX5lMhubmZr797W9z2223UVlZeZxme+yiKGLlypX827/9G1/60pcoKyujt7eXT3ziE5xyyilcf/31xIeyJlnS8BdF0N0NL74ImzeHUO+aNeHIjXPOgXe9C6ZNC7XsJ8rRHJIkSZIkSXo77AZqXuvGo/tEXpIkSZIkSRrBenth377QrLtnT8hibdoUyhUPHoSsLBg3DmbOhI98JJxNffx4iMfDGMxkDcds1v33309/fz+7du3i4x//+FGHeQH6+vrYtGkTN954IxUVFcdhlm+NwsJC9uzZw49//GNKS0vZsWMH3d3dLFy40AZMSW9eLBaae6dNC0d6XHwx9PTA2rXwu9/Bl74Uvm/69BDwnTEDamtDwNdtkCRJkiRJ0knLhl5JkiRJkiSdNAY/Chts3+3ogG3bYMOGENzduhX27w85rLKyENadMQPGjoUxY8JZ1cvKQrB3pNm0aRPPPfcc06dPZ/bs2WSNxAf5X5LJJBs3bmTjxo0kk0lKSkqYM2cONTU1BnolHV+ZDLS3h5r3tWvh2WfDUSOjR8PChXD++VBT89IbjdskSZIkSZKkkeR1G3oN9EqSJEmSJGnESqfDWc87OsLYvx+efx6am2HXLmhtheJiqKsLRYlz5oQAb35+OAt6djYkEuapJElvscEjS/r6QsB31Sr47W/Dm9To0XDWWWHU1EBVVXhD8s1IkiRJkiRpuDPQK0mSJEmSpJNDOg179oTW3ebml4K7hw+HHNRgeLe2Noy6upCVys83JyVJGmLpdDjSZOVKWL48VMenUjBlCpx9NsyfHyrjfcOSJEmSJEkargz0SpIkSZIkaWSIopBt6uuD3t7QvrtrF2zYEEoNm5qgpweKikLjbkMDzJwJEyZAYWG4vqAgnMncPJQk6YQURZBMhmr5lhZ45hlYvBj27g018hdeCKedBhUV4c0tHvdNTZIkSZIkaXgw0CtJkiRJkqThKYpCu+6ePSG4u2sX7NgB27eH6wcGQkB3yhSorw+X06dDZeUfZ5vMOkmShp3Bv+Gk07BzJyxZAk8/HcK95eVwyikwd244eqWiwjc7SZIkSZKkE5uBXkmSJEmSJJ24oijklNLp0L57+DCsXx9GUxM0N4eiwtGjoaoKGhth2rQQ2q2shNJSKCkxwyRJOglEUaipb2mBTZtg2TJYtSq8gc6dC+95D8yZA/n5kJ0dlvENUpIkSZIk6URhoFeSJEmSJEknhsHw7qFDsG8ftLWF1t2NG6G1FXbvht5eGDMGJk4MZxafMQMmTw5NvPH4S2cWN58kSTqpRRFkMtDfH8K9Dz4YAr59feHIl3POCc29EydCYaFvnJIkSZIkSUPPQK8kSZIkSZLePi//uCmKQrvuzp2hbXfTJtiwAfbvD2WCpaWheXfKFKipgbFjw6iuhpycoXsMkiQNO1EUau6bmuC552DNGti+HYqL4eyz4Z3vDG+4iUT4fgO+kiRJkiRJbzcDvZIkSZIkSTp+oiiUA3Z0hBxRRwds3RrCu5s2wYsvhu8ZOzYUBg627o4dG0K7g8PWXUmS3iKDzb2dnbBuHfzmN7B6NZSUwFlnwYIFUFcHVVWQm+sbsCRJkiRJ0tvDQK8kSZIkSZLeOlEU8kHbtsGWLWFs3w6trSEPFI+HsG59fTjLd11dGBUV5oUkSRoSUQQHDoTm3mXLYONG6OkJb9Dz54eA74QJ4U1ckiRJkiRJx4uBXkmSJEmSJL1xURSK/QYGQrlffz/s3QsbNoT8z8aN4evsbKiuhoYGaGyEqVOhrAwKC6GoCPLyDPBKknRCiSJIp0OdfksLPPssPP54OEpn0iR417tg3rzQ3FtYCFlZvplLkiRJkiS9dQz0SpIkSZIk6fUlkyGk++KLId8z2Lrb1gaHD4c8z/jxIeszY0a4nDIFEolXrsfMjyRJw8Tg34eiKNTsP/UUPPYY7NoFxcUwZw6cfjrMng2jR9veK0mSJEmS9OYZ6JUkSZIkSTrZRdFLpXzpNPT1hdBuUxOsXh3+ffAg5OSEM25PnBgad8ePh/LyUNRXXv7HAV5JkjRCRFGo529thU2bYMUKWLkSurpg1ix4z3vgjDNCDX8iEY7i8UgeSZIkSZKko2GgV5IkSZIk6WQTRSF/09YWxp49sGMHvPBCaOA9dAgKCkJ4d/bs0LY7e3YI7cbjoZF3sIjPrI4kSSeZKIJMJgR8t22DxYtDe29HB0yeDAsWwMyZobK/tNSdBUmSJEmSpDfGQK8kSZIkSdJI84cf6URRaNjdvBnWrYPm5hDgPXwYCgvDmbPr6qC+HqqroaYGxo0LJXtmcCRJ0uuKIujtDZX+q1fDqlUh6JuTA6efDhdeGFp8c3JeWsYdDEmSJEmSpD9koFeSJEmSJGkkSCahuzs073Z2htbddetCtmbbtlCaV1oKDQ0wdWrI1UyeDPn5kJsbMjaDZ8iWJEk6JlEE/f1hZ+T55+GRR+CZZ8JOxplnwvnnh52RqqqwE+KOhyRJkiRJ0iADvZIkSZIkScNNFIWzXO/eHcK627bB1q2wa1coyIsiKCkJrbsTJ4ZRXx9ad7Ozh3r2kiTppBFFIdy7di0sXQrr14ejj8aPDwHfs8+GSZPcQZEkSZIkSTLQK0mSJEmSBkVRRDKZJJVKkUwmSafTpFIp0uk0XV1dHDx4kK6uLgYGBkilUvT19RFFEQUFBcTjcfLz8yksLKSsrIzi4mKysrLIysoikUiQSCTIzs4mkUgQj8eH+qEOC1EUWncHBsLo6Ahtu+vXh8K7rVvD9eXloXF38uTQultZCcXFYRQVheI7y+8kSdKQS6dDuLe1FdasgSefhA0bYMwYuOACWLgQqquhoOCEPm1AFEWv2F8evEyn0/T19dHe3k5HRwd9fX1Hrkun0+Tm5pKdnU12dvaRfeaSkhKys7Nfsc88uN+clZU11A9VkiRJkiS9vQz0SpIkSZJ0skomk+zbt4/du3ezd+9e9uzZw7Zt22hra6Onp4e+vj76+vpIJpMkEgkKCgrIyckhOzubWCxG9n81qSWTySPBhv7+fnp7e0kmk2RnZ5Obm0t+fj75+flUVVVRW1vL+PHjGTNmDOPGjaO6uppEIjHEz8SJIZOBQ4dg717YuRNaWkKAd9euUGTX0xPCuw0NoW135kyYNi0Ed1+edzlBsy+SJEnB4N+eoggOHoTly+Ghh8KOT14ezJkDp54aLseNC+He15PJhGUnTz4uO0JRFNHW1kZLSwt79uyhtbWVHTt20NLSQnd3N319ffT399Pf308sFiM/P5+8vLwj+8yDB7QNhn4zmQwDAwP09PQwMDBAPB4nNzeXvLw88vPzKS0tZeLEiYwbN46xY8dSXV3N+PHjyc/PJ+aOniRJkiRJI5mBXkmSJEmSRrooioiiiHQ6TXd3NytXrmTVqlWsWbOG1tZWCgoKGDVqFNXV1UyePJkxY8ZQUlJCUVERRUVF5OXlHQkZDLaFDYYTAFKp1JH1J5NJ+vv7j4SBu7u7OXz4MF1dXbS0tLBt2zZaWlrYt28fvb29VFdXM2PGDObNm8epp556pNk3FouNyMBCFIVyuiiCVAoOHAgFdc8/Dxs3wosvhkzKmDGhaXfmTKirg6qqMCorIT/f0K4kSRphUqnQ3Lt5cwj4Pvcc7N8fQrrvehecey5UVEBW1h+ffmDnTvjLv4Srr4YPfvBN7Sy9fJ9248aNLFu2jHXr1rF161aiKGL06NFUVVVRX19PbW0tJSUlFBcXU1RURH5+Prm5uUdGVlYW8Xj8yL5tJpMhnU4fOSvGYAi4t7eX3t5eDh8+zOHDhzl48CDNzc20tLSwd+9eDh06RHFxMTNnzmTOnDmcc845jB49+sj6R+I+syRJkiRJJykDvZIkSZIkjVSDbWLbt2/n97//Pb///e/ZuXMno0aNYtasWcydO5c5c+YwatQosrKyXhEKeKuDAYOh4sEgQyaToa2tjVWrVrFu3TpWrVpFZ2cntbW1nHrqqZx66qlMmTKFysrKYXu64SiC/n7o6Ah5lPZ22LEjnFm6tTU072YyMH78S427s2bBhAmQmwvx+KtnViRJkkasKAo7SMkk7NkDS5bAww/Dvn0wcSKcdRbMng2TJoWAbywG//7v8IlPhGU+8hG48cbwvfH4G77b7u5utm3bxoYNG3jiiSdoamoikUgwc+ZMTjnlFObOnUtNTQ3Z2dmvCOkejzDtH+4zd3d38/zzz/Pss8+yZs0adu/eTXl5ObNnz2bevHlMnjz5yNwkSZIkSdKwZqBXkiRJkqSRZDA4u2XLFn7zm9+wdOlSkskkjY2NzJkzhxkzZjBt2jTy8/OHeqpHRFHEwMAAO3bsYMOGDSxfvpz169cTj8c566yz+OAHP0hDQ8MJ2dr7hx+d9PVBc3Mol2tqgk2bwpmkowgKC18K744fH4K71dUwduxR5U0kSZJOHlEUgrrbtsHq1aG9d8eOEPqdMwcWLICf/ATuuSd8bzwOixbBTTfBwoXh61fZfxz8+1d7ezsPPPAAS5YsobW1lQkTJnDGGWcwdepUZs2aRXl5+Qm1/5nJZHjxxRdpamri2WefZcWKFXR2dnLqqady8cUXc8455xw5GO5EmrckSZIkSXpDDPRKkiRJkjQSRFFEZ2cna9as4X//7//Nhg0bOO2007jyyiuZMmUKJSUl5OTknPB/2B8M93Z2dtLU1MQDDzzA8uXLmTx5MldffTVz5syhrKyM+DEkYAcGoKsLysuPvfE2kwmh3e7usK62thDabWoKY8+esO4JE2DKFJgxIzTvVlSE1t28vHB5gv8YJEmSTjyDpz84fDjseC1eHMbq1XDo0EvfF49DZSV84Qvw0Y9CWdkrdr76+/vZvHkzv/jFL3j88ccZP348l112GWeffTYlJSUUFBQMi33mdDpNV1cXra2tPPDAAzz22GMUFRXx/ve/n/POO4+xY8eSSCSGeqqSJEmSJOmNM9ArSZIkSdJw193dzeOPP85//ud/0t7ezvnnn8/73vc+6urqjin4eiKJoogXX3yRhx9+mF/96lfk5+dzxRVXcMkll7zhluEoCkVu//7v0N4OX/oSFBW9sftPpUJod8eOUAy3dSvs3AkHDoT1xmKhbbeuLjTvTp4cLk+gAmRJkqSRKYpCoPfSS6G3949vLyiAD3wAbr4Zpk8nncmwcuVKfvnLX7JhwwZmz57N+973PubOnTsigq9dXV0sXryYX/3qV7S2tnLRRRdx1VVXMWbMmBM+oCxJkiRJkgADvZIkSZIkDU9RFJFKpWhubuab3/wm+/fv58///M9ZsGABo0ePPnKq3ZEiiiJaW1t56qmnuP/++6msrOS6665j1qxZZGdnv+oymUxo0v3Zz+D22+H55+GMM+C++2DixMH1QjodzuQ8MBDG7t2wdi288EIofzt4MORBxo+HSZNg9uzQwFtWBsXFYeTk2LorSZL0tspk4Lbb4ItfDDt1ryaRgDlzOPz5z/ODzZv57aOPctFFF3H55ZdTV1dHTk7O2zvn4yyKIg4fPszatWv50Y9+xJ49e/jrv/5rFi5cOCyahyVJkiRJOskZ6JUkSZIkaThqb2/n3nvv5Xe/+x2XXXYZH/7whykvLx/Rf6Qf/Jyiq6uLe+65h1//+tdceumlfPjDH2bUqFGveOy9vfDww3DXXfDIIyGoC6E99957QyC3tTWM5mbYvj008ba1hfbemhqYMgUaG0Prbm1tCOy+/OkdwU+1JEnSiW9gAC68EFavDkdX5eVBbm44VUJODuTkkIrF2NjcTGsUseW97+WiL32Juv86smuk7jcP7jOn02keeugh7rjjDmpra7nhhhuYPHnyiH3ckiRJkiSNAAZ6JUmSJEkaTqIoYs+ePdx66610dnZy3XXXMW/evBHXyPunpFIp1q9fz7e+9S2ysrL46le/yrhx48hkYmzaFBp5f/UraGl55XJ5eXD66eGyoACqq0PzbmMjjBsHFRUwdiyUlkI8PjSPTZIkSW9AOg2PPQapFGRnhzBvTg5kZxNlZ9PV38+//vu/8/TKlfzl9ddz5qJF5FVVnVSB1iiK2LVrF/fccw8rV67kM5/5DAsWLDjp/u8gSZIkSdIwYaBXkiRJkqThIooiNmzYwK233sq0adP4zGc+Q1FR0UkVSni5KIo4dOgQd911F888s4LrrvsWzzwzke99L0Z7e8h4vJq//Vv43OdCoDeRgKysMMDWXUmSpJGgvb2db3zjG2zbto3bbruNSZMmET9Jj9aKoohkMskDDzzA97//fW644QYuvvhiEonEUE9NkiRJkiS90usGev2fvCRJkiRJJ4goiti7dy9f/vKXmTNnDjfccAOFhYVHFeb9EwfuAq889fDLv//N3s+rLf9a83mj9xWLxSgvL+eGG27g7//+p1x99VY6O2tIJrOIx2PEYvCHdxGLQU9PaODNyXlDdyNJkqRhIooiuru7/z979x0nVXX/f/w1Mzuzvffel7KgSFGJoFKMBbHEgl9jjAl+1ViS/IwxMRqNiYkxIYo1ttgxxihqIkbkKwFEBUSQzrK9s8v2Pjs7c39/HHcXUBSQssD7+Xicx9075c6dRfdx7znv8zk8+OCDbN++nfvuu4+0tLQDes28p2Pt67XzobxmdrlcnHfeeYSFhfHHP/6RgIAApk2bdsyGnEVERERERESORAr0ioiIiIiIiAwRLS0tA5V5b775ZoKCgvb5GB0dHTz88MOsWLGCGTNmUF5eTkFBAX19fcTHx3PNNdcwbtw4bDYbPp+PHTt28PTTT5Obm8ull166V5/h9XpZu3Ytjz/+OA0NDYwaNYr/9//+H9HR0V947bPPPss999wzsB8XF8e///1vYmNj9+l7+fv786tfXUpQ0HN88MGr3HDD/VRVBbNhA2zdCnV10NMDvb3Q2gobN5qVmRXoFRERETm6eL1eXnrpJdavX88jjzxCUlLSPh/D4/Hw1ltv8cYbb5CamsovfvELHA4H77zzDps2bdrl+rWfZVl88MEHzJs3j3vuuedrr2cty6KyspKnn36aDRs2EBsby4033sjo0aO/ENRdtWoVP/7xj9mxYwcAwcHB3HfffZxzzjn79L38/PyYOnUqbrebOXPmkJiYSH5+/jG72oeIiIiIiIjIkUaBXhEREREREZEhwOfzsWDBAhobG/n973+/X2FegPfee49Nmzbx6KOPUlNTQ0FBAXPnziU0NJQ5c+bws5/9jHfffZeAgAA2btzIa6+9xssvv8zPf/7zrzyu2+3m008/JTs7m56eHu666y6uv/56Tj75ZH71q1/x0EMPcfvtt+PaLUHrdruZNGkSiYmJAISFhREQELDP38tU6g3gpz+dRWHhMtraXuWmm76P3W7HsqC5GSorobwcSkpMhV6HY58/RkRERESGuLKyMl5//XXuueeegWvMfVVRUcFLL73EPffcQ29vL62trbzxxhv84x//ICcn50vf09TUxCOPPMKOHTvwer1f+hqfz0dBQQFer5dhw4bx0EMP4XK5eOaZZ3j55Ze54447ePnllwkJCdnlfT09PeTk5HD66acDZjJbSkrKfn03u93O9OnT2bBhA4899hgPPvggTqdzv44lIiIiIiIiIoeWAr0iIiIiIiIiQ0BXVxevv/46P/jBDwgLC9vn91uWRW9vL5s3b8bPz4+goCDGjBlDcnIyycnJ2Gw2xo0bx5tvvklHRwcBAQEkJSVx9dVXs2LFij0es7u7m82bNzN//nyGDx/OiBEjWLt2LR0dHUycOJGoqCguvfRS7r77bn7wgx+QkZGxyzECAgIGgr8HQmRkJDfddBN/+MMfmDZt2ufLK0NUlGnHH29e5/WCVhcWERERObr4fD6effZZJk2axAknnLBflWf7+vqorq6msbERu93O8OHDsdlsXHDBBezYsYOqqqovvKe3t5d//vOfjB07loULF+7ynGVZeDweqquree2117Asi0svvZSuri6WLl3KvffeS0REBDNnzuT5559nzZo1nHrqqV/4jJkzZzJr1qwDUk3X39+fK6+8ktmzZ7Nq1SpOOeWUb3xMERERERERETn4FOgVERERERERGQI+++wzACZPnox9P5Ooq1at4r333qOuro5bbrmFW265hfz8fMAEDbZv305ycjJRUVHYbDZiYmLw+Xw4ditla1kWLS0trFmzhs8++wyXy8WNN95IQkICAMXFxURERAxU+srJyaG2tpaGhoYvBHo9Hg/Lli2jrKyM0NBQ8vLyyMrK+sJn7ovRo0cTFRXFunXrSE1N/dLQg6rzioiIiBx9qqqqWLlyJU8++eQXVobYW7W1tbz44osUFhZy9913853vfIfLLruMrKwsAgMDv3Bt6fP5+PjjjwkMDCQtLW2XQG9vby9r165l/fr11NXVMXPmTPLz83E4HGzatAmPx0N0dDQ2m43k5GT8/PzYunXrlwZ6N23axKuvvorT6SQ9PZ38/Pz9WtmiX2JiImeddRZvvfUWJ510En5+GhIUERERERERGepUq0ZERERERERkCFixYgXHH388ERER+/V+m83G5MmTmTFjBqeffjrPPPPMLmHehoYGVq5cyXXXXfe1geGenh5uv/121qxZw8yZM7nhhhtISkrCbrdjWRZtbW24XK6BsIPT6cTr9eJ2u79wrDFjxhAREYHX62X58uXceOONFBQU7Nd37BcYGMhxxx3Hhg0b9rjcsYiIiIgcfQoKCoiKiiI1NXW/j5Gamsq1117LsGHDeOCBB7jsssu+8vUdHR0sW7aMKVOmDExoAxP0feKJJ3j11VfJz8/n5z//Occffzx+fn7YbDba29ux2+0DQVqHw4HT6aS9vf0Ln5GRkUFGRgZer5eqqipuu+025s+fT19f335/T5vNxtSpU9m6dSstLS37fRwREREREREROXQU6BUREREREREZAiorK8nIyDggS+zurq2tjXnz5jF58mTOOeecr329v78/1113HZ2dnSxdupSNGzfS3d2NZVkDz3u93oF9n8+HzWb70qpf48ePZ/bs2Vx++eX84he/ICIigueff/4bfR+73U5SUhJ1dXX4fL5vdCwREREROXLs2LGD+Pj4/V7RYl+53W5eeOEFpk6d+oUQsc1mY9asWaSmprJkyRJWr15NU1PTLtfMlmUNXK/6fD76+vrw9/f/wuekpaVx1VVX8T//8z/8DwoCmAAAIABJREFU6Ec/4vzzz+eJJ56go6PjG51/XFwcfX19tLW1faPjiIiIiIiIiMihofV1RERERERERIYAm802MPh/IDU2NvL3v/+dlJQUzjvvvL1amthut3PccccxcuRIPvnkE5YtW8bChQuZMmUKxx9/PMnJybS1tQ1Ux21oaCAsLIzQ0NAvPVa/8PBwoqKiqK+v/0bfqT/0fDDCzyIiIiIydB3q679Nmzbx+uuvU1xczPz586moqKCoqIj777+f2267jbi4OH784x9TWlrKkiVL+OCDDxg5ciRnnHEGiYmJeL1eOjs7ATPJrq+vj6SkpC/9Xg6HAwA/Pz9SU1Npamr6RhV6RUREREREROTIo0CviIiIiIiIyBCQkpJCeXk5lmUdsKBCR0cH9957L7m5ueTn51NeXo7dbicxMZGgoKCvfb+fnx8nn3wyY8aMoaqqiv/+979ERkaSl5eH2+2mvr6e4OBg3n//fUaPHk1KSgq9vb3U1dURFRVFcHAwc+bM4frrrycgIIDa2lpqamqYOnXqN/peXq+Xmpoa4uLiDll1NhERERE5/GJiYqivr8fr9Q4EYA+m4cOH88wzzwwEaz/88EMqKiq4+OKLCQkJAcwEtqysLNLS0mhoaODDDz9k+fLlTJo0iZycHLZu3cqECRNYvXo1DoeDk046CcuyqK+vx+FwEB0dzfz588nPzx+4zt6wYQMjRoz40mq++6Kurg6n00lYWNg3/l2IiIiIiIiIyMGnQK+IiIiIiIjIEDB58mTuueceGhsbiYmJ2ef3W5ZFZWUla9asoba2lkWLFhEVFcXDDz9Mb2/vwOsiIiL45z//ydSpU9m8eTOrVq2ivLycZcuWERUVxfTp04mMjBx4vc1mIzAwkJycHHJycrDZbPT09DBr1izmzJlDSkoKGzZs4JZbbiEsLIyCggJmz57NbbfdxowZM6itreW3v/0t0dHRlJeXExMTw2WXXfaNflddXV2sXr2aK6+88pAEOURERERkaBg5ciSNjY2UlpYybNiw/TpGV1cX77//PtXV1bz99ttceOGFACxatIhVq1ZRX1/Pc889x+TJk8nKyiIzMxMw19tlZWUEBQWRlpaG0+kcOKbNZsPpdJKQkMBFF1008PobbriB5557jurq6oHr5KSkJDweD7/4xS+Ii4vjd7/7HT09PTz00ENkZmbS3t7O1q1buemmmwgODv5Gv6///Oc/jBo1apfrexEREREREREZumxfs5zngV/rU0RERERERES+oL29nSuuuIKrr76ac889d5+r9FqWRUtLC5s3b8br9RIfH09cXBzr16/H5/MNvM7Pz4/8/HwiIyPZvn07FRUVdHd3Y7fbCQsLIy8vb6+q93Z1dbF161Y6OztJTEwkKysLu90+8Hh6evpAiLe6uhqPx0NQUBCZmZlER0fvdxViy7L4+OOPuffee3n00UdJS0vbr+OIiIiIyJHH5/Nx++234+/vzx133IGf377Xrent7WX9+vV0dHQMXP9alkVBQQFdXV1YlkVgYCBZWVm7XLdalkVzczPl5eXk5+fjcrm+9rM8Hg+lpaXU1dURFhbGsGHD8Pf3H/g8l8tFZmYmLS0tFBcX09XVhZ+fH6mpqSQnJ+/35DXLsqipqWH27NnceeedfOtb39qv44iIiIiIiIjIAVcFpO7pSQV6RURERERERIYAn8/Hm2++ybx583jkkUdITEw83Kc0JNXX1/OjH/2ISy+9lEsvvXS/g8EiIiIicmSqrKzk6quv5tZbb2XKlCnY7fbDfUpDTnd3N/f98Y+0d3Tw5z//Wb8jERERERERkaHjKwO9uoMXEREREREROYQsyzSfD7xe6OuDHTtg1So7VVVTKS2dwQMPPD5QHUwMy7Lo7Ozk0UcfJTo6er+qGIuIiIjIkS8xMZGLLrqIhx56iO3bt+uaeTeWZbFo0SJqn3+en5SVYXvoIXjzTdi6Fbq6zE2Izzd4Y6Lfn4iIiIiIiMiQoQq9IiIiIiIiIgeRz2fGzdvaoL0dmpuhshI2b4aqKqiuNs+FhEB2tkVGRjcffvhDxo4dyY9//GPCw8MVXAXa29t5/PHH+eSTT/jTn/5Eenq6fi8iIiIixyDLsuju7ub++++noKCAu+++m4yMDFWhBdxuN4sXL2bu3LncfumlTLYsbAUFUFpqbkQsCxISIDkZ0tIgNxdiYyEsDIKDzTYoCPS7FBERERERETlYvrJCrwK9IiIiIiIiIgdQT48J6VZUQHExlJWZ4G5zsxkXd7kgOhqyssw4ekqKaQkJEBAAYFFUVMSdd95Jamoqt956KzExMYf5Wx0+lmXR0NDA3LlzKSoq4u6772bYsGEK84qIiIgc4zo6OrjvvvvYsmULd955J6NHjz6mrxH7+vp4/vnnefXVV/nJT37C2WefPfj7sCwzu7CmxswurKkxNyyVleZGxecDj8fcqKSlmRuVzEzzc0YG+Psf1u8mIiIiIiIichRRoFdERERERETkQLAs6OsDtxu6u822rs6sXrttmyl8VV1tVrGNihocA8/LMwHeoCDTAgNN21PewLIsamtruffee6mvr+dnP/sZY8aMweVyHdovfBhZloXH42Hbtm3cfffdREdH86tf/YrU1NRjOqghIiIiIoZlWbS3t/Piiy/y1ltvce211/Ltb3+bkJCQY+p60efzUV1dzV//+le2bNnCzTffzLe+9S0cDsdXv9HrNbMRu7rMzU1np7mhKSw0sxKLi03Y1+mEmBhzU5OTY1pamgn5+vubWYn+/nu+uRERERERERGRnSnQKyIiIiIiIrI/+vqgocFU2K2tNWHd6mpT0Kqjw4x/O52QmAjp6Sa0m5kJ2dkQGvrF4+3LGLdlWbjdbl544QXmz5/PlClTmDVrFunp6cdEQKGqqooXX3yRJUuWcPHFF3P55ZcTFBR0THx3EREREdk7/WNcy5Yt44EHHiAxMZH//d//5bjjjsPPz+8wn93B19bWxjvvvMO8efPIzc3ll7/8JbGxsft3zfxl44VtbaaSb1mZaaWl5maoqwv8/EyYNzbW3AglJJgbo5QUiI83Mxl17S4iIiIiIiKyOwV6RURERERERHZnWaZ5vab19UFrK5SUQEGBKUy1bZt5zG43Y9KJiaYwVWamKVIVHg6RkRASYoK9B4PH46GgoIC//e1vbNmyhUsuuYQLLriAiIgI7Hb7URNwtSwLn89HW1sbCxYs4JVXXiEtLY2rrrqKsWPHHhOBDBERERHZP/1Vav/1r3/xxhtvcOKJJ3LNNdeQnJyMn5/fUXXNbFkWvb29rFy5kqeffpq2tjauu+46Jk2adPCrE3u9ZmZjS4sJ+zY2QmWlCfpWVsL27ea5kBBISjLVfIcNg9xcSE0FlwscjsEGCv2KiIiIiIjIsUaBXhERERERERGfz4w9Nzaaqrs7dpjKu4WFUFdn9t1uiIoy1Xb7x56zs02xKbvdNJttsB0qlmXh8XhYvXo1Tz75JPX19Zx99tmcdtpp5ObmEhAQcESHFNxuN1u3buWjjz7inXfeISoqiquuuorJkyfjcDiO6O8mIiIiIoeO1+ulpKSEF154gRUrVjBhwgTOOussjjvuOMLDw4/o60qv10tVVRUrVqxgwYIFtLS0cMkll3D++ecTGhp6eL5b/xijz2d+9vmgs9NU8y0oMNutW80Nl8djbrbCw00V35wciIszMyWjo81zwcEK+IqIiIiIiMjRToFeERERERERObrtfGvb/7PbbcaPi4vNWHJJiSkY1d1txonDwkzF3awss0psQoKpwhsfbwpHDcVxZMuy6OzsZOXKlfznP/9h48aNpKenM3PmTE455ZRdQgpDNazQ3w9hWRYdHR0sWbKERYsWsW3bNkaMGMGMGTM4+eSTCQ0NPcxnKiIiIiJHKq/Xy7p161i0aBEff/wxAQEBTJ06lbPPPpvk5OQhf80Mg9fNvb29fPbZZ7z99tt8+umnxMfHM3XqVKZPn05iYuJhPsu94POZqr0NDSbYW19vqvlWVJj9tjZz8xYRAcnJpppvRoYJ/GZkQP9KHf3/VkP430xERERERERkLyjQKyIiIiIiIkcXyzJjvh0d0N5uWk2NWem1pMRU3q2pMWO/MTFmTDg7G0aNMiu9BgSA0znYjrQxYcuycLvd7Nixg8WLF/Pvf/+bpqYmxowZw+TJkxk2bBhxcXGEh4cPmSWG+/r6aG5uprGxkYKCApYuXcq6deuIiopi+vTpzJw5k6ioKPz9/YfE+YqIiIjIkc2yLLxeL62traxcuZJ///vfbN26ldTUVKZMmcKYMWOIi4sjOjp6yFyD+nw+Ojo62LFjB1VVVSxbtoyVK1fi8Xg47bTTmDlzJllZWQQGBmK32w/36e6f/kq+fX3Q22sq93Z1QVGRWT6loADKy00AGMyMy6QkE+7NyzM/h4SYFhwMQUFH3g2diIiIiIiIHMsU6BUREREREZEjm8djxnPLykwxp5ISs62rM+PADgeEhkJammkpKZCebsK7x8KqrW63m4KCApYvX85nn33Gjh07cDqdZGRkMHLkSHJzc8nLyyM6OvqQDfz7fD6ampooKipiy5YtbNu2jaKiIjweD7GxsZxwwgmcdNJJjB49GpfLdUjOSURERESOXT6fj7KyMj755BNWrlxJeXk5Pp+P5ORk8vLyGDlyJDk5OSQnJ+N0Og/JOfWvwFFaWkpBQQGbN2+mqKiItrY2goKCGD16NCeeeCLjx48nLCxsSISOD4n+qr61tWa2ZlmZ+bmyElpbwesFux0iIyEz09wApqYONn//o/8mUERERERERI5UCvSKiIiIiIjI0GVZZjy2t9e0nh6z6urWraZA07ZtZvy2u9uEdpOTTbXdnByzDQ01od3+4kx2+7E7dmtZFl1dXTQ3N1NTU8O6detYt24dRUVFdHd3ExYWRlZWFtnZ2aSkpJCenk5MTAz+/v44HI6BZrPZBoK//Vufzzew7W9erxev14vH46Guro7q6mrKy8spLS2lpKSE5uZmAgICGDZsGCNGjGD8+PEkJiYSGRlJcHDwsRNIEBEREZEhw7Isent7aWlpoaGhgfXr17Nx40Y2bdpEU1MTgYGBpKWlkZWVRWZmJsnJySQnJxMYGLjLNbPdbsdms+3SLMsaaP3Xy/3bvr4+WlpaqKyspLq6mqKiIsrKyqitrcVms5GWlsbo0aM5/vjjyc7OJjIykrCwMBwOx+H+lQ0NXq+5KezsNBV929pMJd8tW6C62izX0tJilmNJTDQzPIcPNy0hwYR8XS6z7V+mRfcjIiIiIiIicugp0CsiIiIiIiJDh2VBc7OprltdDdu3m3HYykpob4eODlOQKT7ehHezskx4NyvLPLb7mKvGYL/czvf7Pp+PysrKgaBtSUkJ9fX1NDU10d3djdPpxOl04ufnh9PpxG63DwQH0ux2HEDpToHevr6+gebxePB4PAQGBhIREUFiYiLp6elkZ2eTlZVFcnIyfn5+A+eiEK+IiIiIDBU7XzNbljWwwkT/dXNVVRXNzc20t7djt9txuVz4+fkNtMFQbzg2WyY+32cAu4R4+5vb7cbpdBIREUF0dDSZmZlkZGSQk5NDWloaQUFBu5ybrpu/xu7jm5ZlbibLyqCoyCzrUlIC9fUmBBwcPBj2zcoy29hYSEoygd+AAN1cioiIiIiIyKGgQK+IiIiIiIgcGv23mD6fKaDk9ZriSWVlpuJuaanZ1tebarwxMWYMNSsL8vLMz1FREBFhti7XYf06RzWPx0NHRwednZ10dnbidrsHWn/owLIsIl57DXt3N03f+x42m20gvODv7z/QgoKCCA0NJSgoCKfTqfCBiIiIiBwVvF4vXV1dA9fNPT09uN1uent76e3tHbhm3rTJxQsvxHLvvZUDk+P8/PxwuVwD18yBgYGEhIQQEhKCv7+/rpkPBa/XzBptaoLWVrOtqIDiYqitNbNM29shLMwEfPPyIDcXRo40IV+n0ywB43Ac20vBiIiIiIiIyIGkQK+IiIiIiIgcHJZlArtNTWZ108ZGqKkxhZAqKkxwt6XFFENKTjZjo3l5Znw0KWlwpVO7XeOjQ5Jlwdy5ZpD7zjsP99mIiIiIiAxJK1bAXXfBwoWH+0zkK1mWaT7f4LalxcxALSw0lX2Li82NrMdjZqCGh0N6OgwbZvajoyEy0mwDA3UTKyIiIiIiIvvqKwO9fnt6QkRERERERGT3OaBerwnsFhebsc5t26C6GpqbzQqloaGmsm5WFpx5phnv7F/BNCREY50iIiIiIiJymNhsgzNK+8XHm3bSSWbf6zUh37o6E+zdvh0qK2HpUjOTtb3dhH2jo83Nbna2mbmanm6an98XP1NERERERERkLynQKyIiIiIiIoAJ7/b1mYq7HR2mNTSY0G5JCVRVmXHMvj5TkCgrCzIzYfp0GDECgoLA5Rps/WOlIiIiIiIiIkcEh8OEdaOjzdIyYEK+vb0myOt2m5vlkhIoKDDbhQtN2NfhMLNZMzIgNdW8PybGLFkTGmpumgMCdKMsIiIiIiIie6RAr4iIiIiIyDHK5zNjjpWVg2HdkhJThKi72wR3XS4zDpmSAuPGmW16uhmT1BikiIiIiIiIHPUcDggMNA0gNtbMbp02zez7fKaqb0WFWdKmrAzKy2HFCmhrGzxG//uSkiAtzdxgJycPzogVERERERGRY54CvSIiIiIiIkcpn2+wiFBvr6m8W14OmzaZ4O62bdDYCE6nGU9MTYX8fLjwQlOMKCgIQkJMczo1vigiIiIiIiLyBXY7REWZNmaMWf7G6x1c/qazE1pbTeC3oMAEfV991cywDQw0s2bT0yE31yx/Ex8P/v7mRtzl0g25iIiIiIjIMUSBXhERERERkaNEZyfU1ZlWU2NacbGpuNvTY6ruRkSYQkBZWaaYUHa2CfI6nV88nsYLRURERERERPaRzQZ+fhAWZhqYkO+4cYOv8fmgudksl1NYaGbdLl4Mr7xibuCDgyE01My+zcgw27g40+LjISBAN+0iIiIiIiJHIQV6RUREREREhjjLGtz6fKZ5PIPjflu2QFER1NaaUG9YGERGQmIijB9vttHRpkVGmnFBjfuJiIiIiIiIHCK734Q7HBATY9rOVX3b2kzl3sZGsy0vNzf8y5ebxzo7TSXglBQzQzc721T1TUoyx7TbzWf1b0VEREREROSIokCviIiIiIjIEGNZ0NtrVuRsajLbujooKzOtttbs94//5ebCpEkwfLj52d9/cBzP4dAYnoiIiIiIiMiQ1l/VNyrKtJwc0znQP7PX6zXbtjZTzbd/du/HH5ugr89nZvEmJJhw78iRZj8iwszsjYxUVV8REREREZEjgAK9IiIiIiIih1h/xd2d91taoLh4sJWUQEODGbMLDobwcEhPN4V7zjnHrLKZlGTG+ez2w/M9REREREREROQgsdkGq+36fT6kGxgI8fEwcaLZ9/nMTODaWtO2bzfL+fz739DRYZrXC7GxkJZmWm4uZGZCcrKZBfxlnysiIiIiIiKHhQK9IiIiIiIiB5nXC93d0NVlVsdsbYXSUti61ayeWVZmHg8ONqHdnByYORPy8kxg1+UyVXf7K+9qbE1EREREREREsNvN0j0xMTB6tJkx7PWC2w0ej9l2dJhZw5s3w8aN8Pbb0NxsOhhSUkzLzjbL/sTFmdBwcLBpLpc6IURERERERA4hBXpFREREREQOIMsyY2XV1VBRYQrjVFaabXu7GVezLLPyZUYGnHIKXHEFpKaa4jh+uksTERERERERkf1hs5mOhZ07F+LjTWD3jDPMvtdrAr3l5YOdFlu2wOLFJgDs85kgb1KSaWlppsMiLc0Efv39FfIVERERERE5SDRULCIiIiIisg8sC/r6oLfXFLvp7YWaGigoMBV3i4rMvtdrquumpZmquxdfDAkJEBoKISGmBQZqDExEREREREREDiGHY7Cq77hxgx0dnZ1mhnJHBzQ1meWEiovh//7PdHS0t5uqvamppqMjLw/y8yE21gSAnU7T/PzU2SEiIiIiIrKfFOgVERERERHZA8syxWmamqCuDurrTeXd8nJTfbe1FdraTDg3IcGMZV10kdmmpppxLth1HEtjWiIiIiIiIiIyZNhsJogbEWGaZZnHJ040W8syrbnZBHxLS6GwEN55B55/3sx2Dg2FsDCzFFF6uqnkm5BglieKi4OAgMP29URERERERI4kCvSKiIiIiMgxq39MyrLMipI+HzQ2DlbaLSgw4d3WVrOiZHS0KTyTmQkTJphiNv2PhYaaIjciIiIiIiIiIkes3Wci9+/3V/U96SSz7/FAS4sJ+u7YYTpUKipg3TozM7q+Hnp6zPJFqalm9nNWltkmJYHdbprNNthERERERESOcQr0ioiIiIjIMcPrNRV1W1vNeFNzsxlrKi42lXdrakxF3vBwSEuD4cPh7LNh5EhTaMbhMCtHOhwaaxIRERERERGRY5jTaWY4x8aakG7/bGmv12z7+kwHzLZtpqrv1q2waJF5zLLM+5KTTQdMXp4JC0dEmE6Z8HAzs1odLyIiIiIicoxRoFdERERERI4K/StC7qy11YR0+1eELC42+93d4HJBYKAZN0pPNxV3k5MhMdGsBumnuyURERERERERkb1js5kZ0DsvXxQSYjpbpkwx+319ZnZ1dTVs3w5VVaajZv5804nj8ZhAcFyc6axJSzPLJGVmmg6bL+usUehXRERERESOIhqiFhERERGRI5LPB7290NVlArrt7WY8aOtWE9wtKzOrOzqdZuwoKwvGj4f8fFP0JTDQFHsJCDCvOVDjPz09PdTV1ZGYmIjL5dqr9/T19VFbW0tERAShoaEH5kRERERERETkmOT1eqmrqyMwMJCIiAhse3HDa1kWra2tdHZ2kpCQgGPnUKbIgeLnN1jVF8zsbK8XenrMkklutwn8lpebDp7Vq+GVV6Cz03TgJCVBRobp5Bk+3HTwBAWZ54KDD2wHj4iIiIiIyGGgQK+IiIiIiBwRentN0ZbqaqisNK2mBnbsMM95vYOFX/Ly4IwzIDsbUlJMePdQjeds2bKFm2++mSeffJLc3Ny9ek9DQwM33XQTV199Neeee+5BPkMRERERERE5mnV2dvLrX/+aE088kWuuuWav3/fWW2/x/vvv8+CDDxIZGXkQz1DkczabCfmGhJgGJrSbnw/nnGP2fT5oajIzt0tKTMfQ6tWwYIHpEHI6zTFSU01LTDSdQ6mpkJCgJZhEREREROSIYrO+bF3aQV/5pIiIiIiIyIFgWWZ8xuMxqy96PKa67rZtZqxmyxaoqDDVeIOCzNhOWhrk5prQbmgohIebbXAw2O2H77t0dHRQWlpKTk4OgYGBe/We3t5eiouLiY+PJyoqaq8/y7IsvF4vPp9vr6sBi+wTy4K5c00J7DvvPNxnIyIiIiIyJK1YAXfdBQsXHu4zMfr6+igtLSU0NJT4+Pi9rtBbX19Pa2srWVlZ+O1lCNKyLCzLwuPx4HQ6sR/OG3I5NliW6Tjq6IC2NrNtajJVfUtKoLTUzAB3u01IODXVzPzOzDRB4dhYE/LtDwI7HKrqKyIiIiIih1IVkLqnJzUlUUREREREDinLMqHdlhYT2m1ogLo6U2ilvNzsNzebUG58vFlJ8dRTTXA3Lw/CwsxxbDbTGhsbWL58Od3d3eTn55OVlcXy5cvp6Ojg9NNPJyoqijVr1lBSUkJYWBgnnngiERERbNu2jU2bNuHz+Tj++OPJzc3d4yDnli1bWLt2LcHBwbjdbrxeL2FhYfh8Pjo7O4mMjGTixIm4XC4+++wzGhoaSEpKwuVysXnzZrZu3YrNZmP8+PEkJSWxadMmCgsLcTgcTJw4kba2NtatW8f48ePx+XwsX76ciIgI/P39qaqqIjMzkxNOOAGHw0Fvby+rV6+mqqoKu91OTU0NY8aM4dRTTz1k/4ZybOkBVmzcSNP8+eTl5VFYWEhoaCgnnXQSoaGhWJZFUVER69evp6+vj9zcXEaNGqWQuYiIiIgcQywaGj7ipZdKiYyM5PTTT6esrIyNGzeSk5PDmDFjqK+v59NPP6Wnp4cRI0YwYsQI2tvbWbFiBc3NzURGRjJt2rQ9Bmmbm5v5+OOP6ejowOVy0dXVRUBAAIGBgXR0dGBZFieccAI5OTlUV1ezZs0aRowYQXx8PE1NTXz00Ud0dHQQHx/PqaeeSkNDAytWrKC7u5v09HRGjhzJJ598QmBgIElJSWzYsIGKigpGjx5NYWEhTqeTiRMnEhkZiWVZlJeX89lnnw3cI3d2dnLJJZcQERFxiH/3csyx2cDlgqgo08B0Nk2ebLb9xawaG6GwEIqKoLgY3nwTnnzSvD842Lw3NRVycszP8fEm7BsTY8K+Qzzk6/F4WLlyJTU1NeTn51NUVIS/vz8nn3wyERERA/+frl27FrfbTUZGBmPGjCEgIOBwn7qIiIiIiHwFx29+85uvev4rnxQREREREdld/7hJf9Vdr9cUTNm8Gf77XzN+8swz8NJL8O675vH6eoiOhuOOg9NPhwsvhO9+F2bNgmnTYPRoSEmBwEAT9LXbBwO93d3dPP3008ybN4+ZM2cSGxvL22+/TUFBAZMmTeKTTz7h97//PfHx8SxbtoytW7eSm5vLHXfcQXh4OI2NjbS2tjJq1Kg9VhKqrKzkl7/8JQCJiYksWLCAV155hREjRuB2u3nsscdISEggJyeH4uJibrvtNk477TQsy+Kuu+4iNjaWiooKLMuir6+Pv/zlLyQmJrJ582YiIiIICAjg7rvvJiIighEjRvDYY4+xePFiRo8ezaeffsrjjz/OeeedR3BwMG+++SZPPvkkqamprFq1ijfffJOf/vSnhPQvTSlygPWtWMH/vfce97z3HpMmTaK5uZk5c+aQmJjIsGHD2LRpE3fcccdA4P2JJ54gIiKCvLy8vaoEJiIiIiJypKuqgueeW8sYzl9AAAAgAElEQVT77/+M3NxcJkyYQGNjI0888QT5+fmEhobym9/8hpqaGnp6enj22WeZOHEir7zyCuvXrycmJob333+fqVOn7nFinNvt5pVXXuHZZ59l7Nix1NbWcu+99xIcHExMTAxLly5l8eLFTJs2ja6uLu6//36ampqYPHkyc+bMobKykoiICJYuXcqkSZO45557aG9vJzAwkJUrV3LiiSfy/vvv8+KLL3LmmWeyfv16br/9diZMmIDb7ebhhx/GZrMxduxYysvLuf322wfCx3PnzmXMmDFMmjRJ9wByePR3Etlsgx1HwcFmeacxY2DKFDj3XPj2t82s8dGjIS7OLAW1cSN89BG88w7Mn286qz75xISB29pMFd/AwF3Dwjt/7mHi8/n44IMP+PWvf83JJ59MV1cXc+fOJTAwkOOPP56ioiLuuOMObDYbNpuNv/3tb9jtdkaOHKlK2iIiIiIih1cb8MCenlSFXhERERER+UYsCzo7obXVjHM0N0N1NRQUwPbtZmCzudmMo6Smmoq7F18MI0aY4if9Kxz6+Q0GdfdFdHQ0N95440C1IafTSXBwMLNmzSI0NJRnn32W8ePHc+ONN7Jp0yZmz57NCSecQElJCddeey3jxo3D5XJ95WBGZmYmcXFxTJs2jXPOOYfExER+/etfc/755xMWFsbmzZtZt24dM2fO5IQTThgYgK2pqaG6upqxY8cyatQonE4nCxcupKmpiZNOOonLL78cl8uFx+MhKSlp4PtkZmbicDiYPn06OTk5vP/++1RXVxMbG8sbb7zBuHHjmD17NmvXruW///0vfX19+/vPJ/K1AoDcmBiC29o49dRTcTgcfPzxx2zatImzzjqLf/7zn4SFhfHTn/50YKDwqaee4vTTTyc8PPxwn76IiIiIyCFgIy1tKiNHnkVFRQWBgYGEhoYyfPhwpkyZwocffsjatWv5+9//TnJyMqtWreLVV19l06ZNnHDCCZx11llcdNFFBAYG7vET+ifNrV+/nlmzZtHe3s7y5cuZMGECF154Ifn5+Vx//fXU19eTlpZGVlYWAF1dXXz66aecd955zJgxg0suuYSenh7WrFnD9ddfzxlnnEFAQAABAQGMHTuWRYsW4XA4yM3NJSQkhG9961tER0dTWFjIunXrcLvdbNy4kdLSUh577DFCQkJYvXo11dXVh+qXLbJ/nE5ISDANBmei9/WZ2egej1lOats2E+YtLob//Afa2817Y2LMbPPsbNOio80yUhEREBpqqgYfwoCv0+kkNzeX4OBgJk2aRGhoKBs3bmT9+vX09PSwYMECenp6uPnmm3G5XERGRvLEE08wffp0Evp/ByIiIiIiMuQo0CsiIiIiIvuku9uEdMvLTSstNfstLSaU63CYMY3sbDjlFDPWkZwMiYkQEHBwxjby8vIYNmwY//3vf8nOzqajo4OsrCw6Ojqor6+npqaGW2+9lba2NpqamoiMjOS4447jl7/8JSeffDI//OEPGTVq1Nd+Tn9Y0d/ff6DqkN1ux+VyfWmoNjs7m/T0dG6++WYmT57MD3/4Q0aPHk1wcDA33ngjU6ZMYfbs2URHR+/xs/z8/HA4HAPHj4yMpLy8nNbW1oGB4j1VcBI5kGw2Gw6HA7vdjr+/P319ffT09FBZWUlmZiZ+fn7YbDZyc3N5+umn8Xg8h/uURUREREQOmZCQEM466yzuu+8+6uvrWbBgATNmzMBut1NVVcX27dv585//TFBQEEVFRWRnZ3PRRRfx5z//mQ8++IALLriA7373uwNVb7+K3W7H4XDgdDqxLAubzYbL5cKyLHw+3y6vDQ4O5pJLLuHRRx/l3Xff5bLLLuP888/nwgsvZM6cObz11ltceeWVTJ8+fY+f1X8f7PV6sSyL4OBgenp6qKqqIiEhgdraWkaPHq3qvHJksdlMJ5bDMfhYeDikp8MZZ5h9jwcaGqC2FmpqTAdYZSWsXAkdHSYIDKbab1oaZGUNhn7j4nY99kH7Grveq3d0dNDb20tFRQVpaWk4nc6BkH59fT1dXV0H/ZxERERERGT/KdArIiIiIiIDLMuMVfT0mNbdbarsFhebAiVFRWbswueDyEjIyYHMTLNyYUaGWYEwIGCwHaoV/BwOB9/97ne57777GDVqFAkJCURGRtLZ2UlAQADjx4/n0ksvBeC2224jPj6e/Px8qqureeSRR/jd737H448/TlRU1AE9r/DwcB544AEqKir4y1/+wr333ssDDzzAY489RmFhIX/84x954IEHuPvuu/f6mFdffTU33XQTV1xxBTExMfz6178+4Octsrf6Bwy7u7sBsCyLnp4eQkJCtISniIiIiBxjbEyfPp1HHnmE559/ns7OTo477jjAhH1TU1P5/ve/T3R0NNdddx3h4eGEhoYyduxYli5dykMPPURycvIeg7XfxHe+8x0mTZrE+++/z5/+9Cfi4+OZPXs2M2bMYMGCBfz2t78lPj5+r483fvx4TjnlFG655RYCAwOZMGECl19+uQK9cvRxOs0M9cREGDvWdJz19Q12mrnd0NRkKvqWlsKSJWbb1QX+/ibkm5kJeXmQm2tmwO/ceeZ0HpSZ73a7nYCAABobGwFzr+52uwkMDMTpdB7wzxMRERERkQNHgV4RERERkWOY1wuNjaa4SG2t2VZUmKIjPT3Q22uq7iYnm8DuhReabXa2KVqyu8M1dmez2Rg7diz+/v689NJL/PWvf8VutxMcHMyIESPYsmULwcHBxMXF0dPTQ21tLVu2bGH69OlcfPHFPPTQQ7S2trJw4UKOP/54RowYcUAGIouKiqioqOC0007jvPPO47XXXmPdunXYbDZOPPFEzjzzTNasWYNlWXt9zOXLlzN9+nRuv/32gcCkBk3lcOkfvH/llVeorq4mICCAt99+m4kTJxIUFHS4T09ERERE5JAKCwvjO9/5DnPmzGHOnDn4+/sDkJGRQW9vL62trYwbNw6Px0NXVxfvvvsuEydO5IILLuCNN96gpaWFlStXsn37dr797W8TGBj4jc+pvb2dRYsWMW3aNC655BJef/11KioqqKmp4ZxzzuGyyy7jX//6Fx0dHXt9zLKyMqqrq5k3bx6RkZHf+BxFjhg2mwnhOp0QGmoeS0mBz8P7gJkFX19vOtmKi03Ad9kyePVVM4ve39+EelNSTOA3KckEhpOSID7edMR9Q06nk3HjxvHggw9SVlZGTEwMb7zxBmPHjiUiIuIbH19ERERERA4eBXpFRERERI5iPp8pHOL1mm1bm6m0u3WrGU8oLITW1sGCI/HxJqz77W9DVBSEhUFEhBmjcDgOX2B3byQkJHD66afT3t5OYmIiYCqS/OhHP+J3v/sd1157LdHR0ZxzzjmMGDGCp556imeeeYbAwEC+973v4XQ6efDBBznttNP4wx/+gGOnZRGXLFlCSUkJzz77LJGRkbz00kvU1tYyb9488vLyWLJkCf7+/ixevJglS5bQ0NDAY489xuWXX87DDz/M448/TnBwMN///vfp6+tj7ty5+Pn5ERoayg9+8AP+/ve/s3HjRpqamrDb7XzwwQc0Njby4YcfsmHDBmpqapg3bx7Dhg0jKCiI5557jtWrV2O32weOMWXKFAV75aBoBd4tKqLJ6eT5559n+PDhfPTRR/j7+3PFFVdw4YUXUlNTw0033YRlWaSlpXHttdcOhBdERERERI4VNpuNc845hzfeeIORI0dis9mw2Wzk5uZyzTXX8Nhjj/H000+Tl5fHlVdeycaNG3n++edxOBxkZmYydepUnnrqKV5//XVycnLIz88fOHZ5eTkLFy6kuLiY1157je7ubjZv3szLL79MXFwcb731FnV1dSxYsIC4uDiWLl2K0+lk2LBhrF27lpdffhm73c6ECRM45ZRTuPfee3nllVdwOBycddZZ+Pn58fDDD1NcXMxDDz1EcHAwLS0tPPHEE5x55pm89957NDU1sWHDBsLDw3G73QP30k6nkxNPPJGrr76aiIgI3ZvKsWX3/94djsGqvieeaB7zeEwHXFub2TY1mbBvRQWsWGGWw/J4zOz51FQYPtx00A0bBrGx5ph+fmb7eQddd3c3CxcupKWlhaeeeopJkyaxePFiurq6KCgo4IwzzqCiooJbb70Vn89HXFwcP/3pTwkJCTn0vyMREREREdlrtq+pBLX3ZaJEREREROSw8vnMuEBDA+zYYbY1NVBUZH6uqzNVd6OjzdhAbq4ZH8jJgYQEM/5gs8HnRV+HdHh3Z/33NF6vlyeffJLTTjttYOC0/3mfz4fP5wNMyNdut+P1erEsC5vNht1up6+vj6eeeorAwECuuuqqgeq3AD6fD6/XO/Ban8+HZVnY7XZsNhterxcAh8Mx8Nzur7XZbDgcjoHz2fmx3c/Psiwsy9rl9TabDcuyuO+++5g4cSKnnnoqlmXx1ltv8cQTT/DOO+/gcrkO5a9ejgWWhTV3Lt7WVqzPq0Lv/N+83+eVgyzLGnis//8xDeKLiIiIyLFixQqLu+6yWLjQTllZGfPnz+eGG24YmOTWf4/3dfeCdrudiooKfv/733PnnXeSkpIy8Bn919z996LAwL3i7vep/c/1H3f3/f7X9z/WP6F15/Oz2Wz4fL4v3AP0T0L96KOP+MlPfoLL5WL79u388Ic/5I477uDUU0/VvYDI1+kfn7cs07xeaG6GggLTkVdQYCr8Njaa10VHmxn3aWmmQy86Gis6Gl90NL6ICOz+/l/on+rvR9r5b4Pu1UVEREREhoQqIHVPT6pCr4iIiIjIEWDneXj9ff1ut+nbLyw0/fzFxVBdDZ2dpqJuRAQkJ8Po0RAXBzExpqhHXJxZ2e9oUVZWRnNzM263m+7ubtLS0nYZnOgfKN254i4MBhH7bdy4EbfbzYUXXviFwY3+QY+d93d/fm+e6z+f3R/7svPb/XmArq4uFi9ezIQJE+jt7aWuro6PPvqI9PT0r3y/yDdhA/zsdlPK+3N789+1iIiIiMixpLd3EdXVo/jHP/7BtGnTdlmxoj8g+3X3gk1NTSxYsIDLLruMpKSkXV5rs9m+cB+783u/7Nhft7/7Y191jJ2DwVu2bKGqqoru7m68Xi+ffPIJPT09REREICJ7ob/fqX/rcJhls+Lj4dRTzWMejwn01tWZir61tWbm/pIl0NCArbkZB+CIiYH0dMjOxp6VBXl5pgPw8/Cuvf//YwV5RURERESOCKrQKyIiIiIyBFkW9Paairvt7WZbW2uKdBQVmb787dvNanvx8aavPiMDRo40ffgBAeY5p9Nsj+Y++8LCQubMmUNoaCg33HADGRkZ+1VtpLe3F5/Ph//nVU2GIsuy+PDDD3nxxRepr68nJCSEsWPH8r3vfY+YmJjDfXpyNLIsmDvX/CG6887DfTYiIiIiIkPSihUW//M/DzNhwnKuuOIKzj333P2a8Ob1enG73QQEBAzZCXOWZVFXV8eLL77IqlWr8Pl8ZGZmcvHFFzN+/PgvhI5F5ACxLLM8l8cDfX1m29RkZvpv3gzl5abTsL0d/P3NLP/4eLM8V1YWREZCWJipAhAWdvR3GIqIiIiIDF1fWaFXgV4RERERkSHA44H6eigthYoKKCkxRTfq683zfn4QHAypqWZ1vaQk83NKiumDV/+7iBwUCvSKiIiIiHytFSvgrrtg4cLDfSYicsyyLNPBuGOHWcKrpgaqqszPtbXmvt7nM7P/ExNN52Jmpgn+ZmWZJb20+pOIiIiIyKHwlYFeTZMVERERETnILAu8XnC7oafHtNbWwWq7hYUmyNvZCUFBJqibkwPTppkiGiEh5vHAQFN51+FQgFdEREREREREREQ+Z7OBy2UCusnJ5jHLMtV8u7uhq8tsGxoGOyXfe89U9u3pMZV7k5MhOxtyc80yYKGhpjMyIMBU/VVVXxERERGRg06BXhERERGRA8yyTGB3+3ZTCKO21lTdraiA5mYT7AWz6l1aGkyeDN/7HqSnm+IYu1M/uYiIiIiIiIiIiOwTm81U5HU6zRJfABkZMH784Gt8PtN5WV4OZWUm6Pvuu/DCC6ZCQUiIWTasv6JvfLwJ/sbFmZ9V1VdERERE5IBSoFdEREREZB9Ylmk+n+nT9npNcYvycti82VTbLSiAxkbzXFwcJCSYvvJzzzX7EREQHg6RkaZwhgK7IiIiIiIiIiIictDt3hHpcEBKimmnnGI6Pt1uaGszFQva2kxV3+Ji2LIFli6FmhrweCAqyiw1lpcHI0aYyr6RkeaY/c1uV+eniIiIiMg+UKBXREREROQrWJYJ7DY2mrZjhylaUVYG1dWDjwcFmUIVubkwa5ZZlS4lZTCw2993rf5rERERERERERERGZJsNggIMC0uzjzWX+Ggv8pBXx/U10NJCWzbZiocLF5sAsB+fhATA7GxZmmyzMzBCgcxMSbw6+enTlIRERERkT1QoFdEREREjmmWtevPPh/U1ZnV5QoLTZ90VZUpROFymcq6MTEmuDt69ODqcrGxZuU69UWLiIiIiIiIiIjIUWPnKgUOBzidkJ5u2pQpplO1txeammD7dlP9oLraLGn27rsm6NvSYioe9Ad9c3MhOxuyskxn6+6VfNXJKiIiIiLHKAV6RUREROSYYVlmNbiuLmhvh44O079cWGhWjeuvumtZplhEVpZZMe7ss802MND0V7tcZquKuyIiIiIiIiIiInJMs9nA3x8SE00D08Ha12eax2MCvzt2mE7YrVvhgw/g5Zehs9NUA05NheRkyMkxHbHh4RASAsHBZutyHd7vKCIiIiJyiNisnUuSfdFXPikiIiIiMpT5fKb4Q3m5CetWVJiV4HbsMH3IdrvpC05NNX3NaWmm3zg9HaKjTcEJEZFjTm8vLFtm/lgCLFoEPT0wc6bZDw+HM8/UH0kREREROWb5fLBxI2zaZPZLSuDNN+Hmm82+vz+ceqopOikiInvg8ZiKvtXVpuO2psZsd+wAt9u0gABISjIduOnpZpuSYjpzVWlBRERERI5MVUDqnp5UoFdEREREjlg+n8md9ffvdnZCVRVs3mwG0woLTQVeu9308aanw7BhpsXEQFCQKfIQHAx+fuoDFhEBwOuFm26Cv//d/KH1eMzj/dVwZs2CRx4xpcpFRERERI5BlmUKS/7852YVIK/X9E8EBprnx4yBv/3NrCYvIiJ7ybLMH9PubtPR29lpqjVs3Woq+5aWmtCv220mG2dkQGamqeo7ciSEhpq+i4AAs3U41OErIiIiIkPRVwZ6/Q7hiYiIiIiIfCMdHVBXB/X1JrhbWztYcbejw/T3RkYO9uWeeSZkZZmqu35fcuWr/lwRkS9ht8OMGfDMM2aQrF93txkQmzLly/+oioiIiIgcQ8aOhdhYWL9+8LHeXtPXkJ9v+iJERGQf2GymxLm/P0REmMcsCyZMGHxNX5/pIC4shMpKKCqCt94yfRiWZd4bGWkqOyQnQ0ICxMebag8xMQr5ioiIiMiQpxE4ERERETns+heN8PlM83pNq66GbdtMEYaCArPf3Q1hYaYPNjERJk40/bIRERAVZbYhIeqXFRHZbzab+eMaH2+WutzZiBEwerT+yIqIiIjIMc1mMwUhR42CDRsG+zXA9FlMmWIKRIqIyDe0e/+D0wkpKabBYFXflhZobjZtxw4oK4M1a8zybdu3m9fFxpoqEBkZpn8jL89U+nU4zOTm/rCv+jxERERE5DBSoFdEREREDjnLMiu4t7SYPtWmJtOvWlIC5eVmv77eFICMijJLVE6eDMOHQ24uBAWZPtb+pj5WEZEDLDQULrkE7r9/MJ1gt8PJJ2vdYBERERERTKbsssv4/+zdd3hUVf748ffMZDKTTDLpvTcTelMIBKRIFQTssvZdFUX5rm1XZXV1d/XZdVFXwRWVtaAoLoqgUlREAYEACQQhlARIIT0hhdSZTLm/P+5vBiLgAqIh4fN6nvuE5M7ce2bGx3Pmcz7nc1i2rOPGFuHhMG5c57VLCCEuKq6qvmFh6gFqHENRjlePcFX1zc9XK/rm5cGaNdDUpO5EFBKiPjclRa3qGxysVo0IClKr/couRUIIIYQQ4lcko08hhBBCCHHenViZBtS4aX29Gi8tLlZ3RCsogKNH1ccajWpsND5ezRWLiFBjqJGRauxUq+2UlyGEEBcvDw8YNQrefFOd4AIwmWDMGCk1JoQQQgghxP83bBiEhqq7voOaVzZ+vFqlVwghRCdxVdl1BZU9PdXKvAkJMGGCGpBuazteZaK6Gioq1Kq+27ZBS4taicLTUw1UR0erZdkTE9Wk34CAkytMSMUJIYQQQghxnkhCrxBCCCGE+NkcDmhtVWOdzc1q7ldhoVr04MgRNXm3uVkt+BgTo+5mNn06pKaqFXj1ejU+6ul5fGczIYQQnUijgT59YMAA2LhR/VtYmJQaE0IIIYQQ4gRmsxrfePVVNT/MYIDrruvsVgkhhPhJGo26BZy3t5qsC+r/xO12aG9Xt5Zrb1eTffPz4fBh+OYbKC0FiwW8vCAuTq1OER+vBrvNZvDxUa/p4yNVfYUQQgghxDmTkaQQQgghhDgriqIm57qKFhQXq0dJiZrI60rIDQ1V45ojRsCMGWpsNDpaTd4VQgjRBURFwZAhsGWLunJj0iS1bLoQQgghhBACUPO1xo2DRYugsREuvVQt3igLlYUQoovRaNTA9YnB69BQ6Nv3+O+uJN+SEigrU4Pi27bB55+rcRNFUStWxMaqlX1jY9WE38hICAmRbeiEEEIIIcQZkYReIYQQQgjRwYnFCNrb1aIDZWWQl6cWIygoUGOVAMHBamwyIQEuv1z9t6+vuiu7j4+6K7tMYgkhRBfl4aEm8S5cqJZhnz69s1skhBBCCCHEBUWjgV691M0tMjNh5EgICursVgkhhPhFuJJ1Y2PV3xUFrFZ127rWVnVlR02NGkQ/dAi2b1er+iqK2jnExqrVfJOSjlf1PXHrOq1WgulCCCGEEEISeoUQQghx/imKgs1mo7W1FavVit1ux+l0YrPZANDr9Wi1Wjw8PPD09MTLywuDwYBGglWdor0dqqvV4gI1NWrybkmJGmtsalLjkEajWl03MRGmTVPjjfHx6g5iPyYfoxBCXPgcDgd2u93dT7t+dzqd7sc4nU5s4eGEhYaieHtz1GhEW1KCTqdzP0aj0bj7dU9PT/R6PXq9vsNjhBBCCCGE6C4URcHhcNDa2orFYsFms6HTKaSleXPwoA9paUepqVHc42MvLy+MRiNaqcoohBDdj0ajBs6NRjVhV1HUv48cefwxdrsaeM/PVxN9i4pg82Y4dkxN5vXyAj8/tWJGVJRaMSMsTK0OHBioLrYWnUpRFCwWC21tbVit1g4xNA8PD3Q6HXq9HqPRiLe3Nx7ymQkhhBDiZ9IoroHlqf3kSSGEEEJcXBRFwel0ug+r1UphYSFlZWWUlpZSUVFBVVUV9fX1HZJ5HQ6He8JDURQ8PDzQaDTodLoOSb3+/v6EhIQQFRVFREQEsbGxxMfHYzKZ0Gq17kMSf8+coqiH03n8qK+HAwfUIgH79qnVdhsa1PhheLh6JCWpCbuBgeru6oGBalxR8rOEEOLX5/re7nQ6URTlpMPhcFBfX09dXR11dXU0NTV1OI4dO0ZLSwstLS3uCQibzeaegHA4HB369xPv67DbufHwYUyKwruJifD/k3ddXP25a6GOTqfrMJFhNBoxmUz4+vp2OMxmM2azGT8/P4KDg/H393ePD048Tuz3pf8XQgghhBC/FNfY2ul0usfJZWVlFBUVUVFRQVlZGVVVVe7xdnt7O+3t7e5YV2VlTyoqbiUt7c94e9s7LGQ3GAzucW9ERATR0dFERESQlJSEv7+/O97lWhQn414hhOjGFAXa2tQqGrW1arC+qkpN9C0sVP9dW6sG4oOCIDlZDdYnJ0NqqlrVV6s9fmg0UmHjZzhxzstut1NbW8uhQ4coLi6mtLSUsrIy6urq3PNdNputw1zXiX24a57L19eXsLAwoqKiiI2NJTExkfj4eAwGgzuGJgt9hBBCiIteKRBzupOS0CuEEEKIn+RwOKiurqa6upry8nL27dvH4cOHqayspL6+HoPBQEBAAJGRkURERBAeHk5AQAB+fn4EBgZiMpnclUi8vLzQaDS0tbXhcDiw2Ww0NzfT0NBAQ0MD9fX1VFdXU1ZWRkVFBbW1tbS1tWE2mwkLCyM2NpZ+/fq57xMaGoqnp2dnv0UXDFfiblOTGgesq1OPggL1KCtTK/Ha7WqCblycGgtMSYGePSEgQI0T6nQSCxRCiM7gqnD/4yTc5uZm6urqKCsro6amhmPHjtHc3Ow+19bWhk6nw2AwYDAY3Am0ZrPZ/dPHx8fdJ7sq47seazAY3JV1T+xXdTodRqMRfXU1mvJy2vv3x2Kx4HA43I+x2Wy0t7djt9tpa2vDYrG4D1flkpaWFhobG2lubnb/dL2+9vZ2LBYLdrsdb29vTCaTu61+fn6EhoYSERFBcHBwh3O+vr74+fmh1+sl4UEIIYQQQpwTRVGor6+noqKC6upq9u/fz8GDBykvL+fo0aNotVr8/f3dSTnh4eEEBgbi7++Pv78/fn5+7piXh4c3GzcaGTmyyZ3o29LSQkNDA8eOHaO+vp6jR49SXl5OWVkZR48epampCaPRSHh4OFFRUfTp04f4+HhCQkKIiIjAy8urs98iIYQQvzRXroarGofDoR5lZXDwoFqZo7AQjhyBlhZ1y7zAQLUqR2oqxMaqFTkCAtSKHK4gvzgtRVFoaGigtLSU8vJycnJyOHToEOXl5VgsFvz8/IiKiiIqKoqYmBgCAwPdi9F9fX3d8TKtVusuamO1WmloaKC2tpb6+noqKyspLS2lpKSEmpoa2tvb3cVsBgwYQHJysntOTea4hBBCiIuSJPQKIYQQ4sycOC4oLS0lMzOTrKws8vLy0Gq1BAYGkpSURFJSkjupNiIiAh8fnyXHB7gAACAASURBVPO+olhRFFpaWqiurqaiooKKigqKi4vZv38/DQ0NtLW1kZCQwODBg8nIyCAuLq7bVzI51bCtuVmtsJufr8b0Dh9Wd/CyWtXdugwGiI5Wq+1GRBw/wsJkty4hhPg1neq7d0tLC8XFxRw5coQjR464K3/U1tbicDjcSbeenp74+fkRFhZGcHAwfn5++Pj4uKvduv5tMpncVe3Pc+PVSaXzPCHkcDiwWCw0NTXR3Nzc4WdTUxONjY3U1NRQXV1NQ0MD7e3tWK1WrFYrOp2O4OBgwsPDiYuLIyoqiri4OOLi4vDx8TnpXt11bCCEEEIIIc6ca0ze0NDA1q1b2bZtG7m5ubS3t2M2m0lISCApKYno6GjCw8PdCbxnMr5WFDX/6kxjLVarlaqqKvfC9tLSUg4cOEBVVRXNzc1ERkbSv39/MjIy6NWrF3q9HpBxrRBCXLQsFqipUYP/ZWVqJd/iYigvVyt8WCxqJxQdrSb5xsdDYqJa0SMg4OTrXUT9iav/t9vt7Ny5k/Xr17Njxw4sFgsBAQH07NmT5ORkoqOjiY6OJjQ01L2L1Pm4d2NjIxUVFZSUlFBSUsKePXsoKyujpaWFxMREhg0bxujRowkLCwOkrxdCCCEuEpLQK4QQQoifpigKbW1tVFZWsm3bNr755hsOHTpEaGgow4YNY/z48YSGhuLl5YXRaESn03VKUMGV+GOxWKirqyM7O5tNmzaRm5tLQEAAEyZMYMSIEe5knq4e+HA61cTclhb1aG5W43T796uL8ouK1N/1ejVJNzFRXZTfs6easOvlpZ4zGNSfXfztEEKILsfpdNLS0uJOTq2uriY/P59Dhw65E3hdiakxMTFER0cTHx9PYmIioaGh6PV6PDw83D89PDw6rQ/uDK4tDO12u/uw2WzY7XaOHTtGQUEBJSUlFBcXu5Mg2tvb8ff3JyEhgfj4eHr16kVsbCxmsxmz2Yy3tzdarfaieQ+FEEIIIQS0t7dTVVXF/v37WblyJbm5uZhMJgYNGsSECRNISkpy72RxvhJ4zpbT6cRqtdLW1kZrays5OTnuhfY6nY5hw4YxefJk4uLizjjJWAghRDemKGCzQXu7Oolgsajb8+3de7wCSGmpet5shqgoSE5Wj6Qk8PFRq/2aTOpPna7bTSC45r3Kysr49ttv+frrr2lqamLQoEGMGzeO3r174+Xl5e7/f602ufr7+vp6Nm3axPr16ykoKOCSSy7hxhtvpHfv3gQHB7sL2AghhBCiW5KEXiGEEEKcXmNjI5s2bWLNmjUUFhYSGxtLeno6I0aMID4+/oJPeFEUhcrKSrZu3eoOfERERHDFFVdwxRVXEBQUdMG/Bher9fgC++JiteJuSYmatGu3q48xm9XF9bGx6hEXp8bivL27XbxNCCG6HFd1+cOHD5OXl8fhw4c5ePAgx44dQ1EUfHx8iIqKIjExkZiYGBISEoiOjsbb27vL9FUXKtckTWlpKcXFxRQWFrqTfZuamtBqtZjNZpKSkkhNTSUxMZHU1NRTVvMVQgghhBDdg9VqZceOHXz11Vfs3LkTf39/MjIyGDp0KL169frVknfOlauq3/bt29m0aRO7du3Cy8uLsWPHMmbMGOLj4yWxVwghxOlZLGoF35IS9XBNOFRXH3+Mt7c6yRATo1YNcf3b3x+6cB9jtVrZtm0by5Yt4+DBg/Ts2ZNRo0Zx+eWXYzabO7t5HTidTg4cOMD69evZsGEDdrudcePGMWXKFKKioiRmKIQQQnRPktArhBBCiI5cFQO3bNnCwoULsVqtTJ06lREjRhATE9MlE4tcK5srKyvZsWMHn3/+OTU1NVx//fVceeWVhISEnPUkh6KoSbYeHme+ZeJPXcvpPL5o3maDo0fhwAF1sfzBg2osra0NfH3VmFlUlLpYPiVFXTBvNqs/TaYuHUsTQohuQVEUbDYbFouF+vp6cnJy2LZtGzt37sRqtRIdHU1SUhIDBw4kKSkJf39/zGYzJpNJKsT+ShwOh7tCckNDA+Xl5eTm5pKXl0dhYSFOp5OkpCSGDx/OkCFD3LsR6PV6+XyEEEIIIboo10KvvLw8FixYQEFBASNHjmTq1KnExsbi7+/fJcd6drudqqoq8vLyWLFiBXv37mXMmDHccsstREZGdlplYSGEEF2Ia0vApiZ1S8CmJrWayMGD6naAJSVqArBGoyb0uir6pqVBQoI6caHXHz+02guqyogrVpefn8+///1vCgoKmDZtmnsRjNFo7Owm/iRFUTh69Ch79+5lyZIlFBUVceONN3Lttdfi6+sri3iEEEKI7kUSeoUQQghxXGtrK2vWrOG///0vWq2W3/zmN4wdOxYvLy+ALh/8d41tHA4H33//Pe+++y61tbXMmDGDiRMnEhgYeEavsa0Ntm2Dzz6DG26AoUPPrh0OB9TXqxV3q6qOV949cgTq6qCxUX1cSIi66D0lRU3eveQSNVYGHWNhXfxjEUKIbsNms1FUVMT+/fvZtm0b+fn5NDU1ERUVxaBBg0hPT6dHjx4YDAZ3f9PV+9bu4MTYh2uCJzc3l+zsbLKzsyktLcXb25u0tDQGDRpEnz59iIuLw9PTsxNbLYQQQgghzkZ7ezs7duzgP//5D5WVlVx99dVcffXVBAYGAt1jXK4oCk6nk7y8PN566y327NnDuHHjuOmmm4iOju4Wr1EIIcSv5Md5Iq4KJxUVcPiwehQWqtsJHjsGBoNadcRsViczIiMhLAxCQyE8/PxU9VUU9V6trWrF4DPs1xRF4ciRI7z33nts2rSJiRMncuuttxIUFAR0rTGAoijY7XaysrJYuHAhzc3N3H777YwfP17iVEIIIUT3IQm9QgghhFCDAIcPH2bevHkUFxczY8YMxo0b5w5odEeKotDU1MT27dt588030Wq1zJkzh969e6PRaE4K4riq6BYUwL/+BWvWqMm4b70FN910PHbkGj45neq/HQ51MXtxMeTlwaFDauXd2lqw2yEoCIKD1cXs8fFqjCswUP27vz9IDEYIIS5crgnzxsZG1q9fz6pVqygqKiI8PJz09HT69u1LfHw84eHhElTvglzJvZWVlZSUlLBz506ys7MpKysjJiaGSZMmMW7cOMxms1RWFkIIIYS4QCmKQkNDA6+++iobN27kmmuu4corryQmJqbbVrNTFIX29nZ2797Ne++9R2FhIffddx/jx4+Xar1CCCHOH0VRq5/U1R0/ysvVRN+yMnUCpa4OjEZ1EiQxEVJT1Yq+l1yiVvXVaI5X83UdP3W/L75QJ2geeACuvFK9NpzyeYqioCgK2dnZPPfcc8TExDBz5kx69uyJTqf7hd6UX09DQwNffPEFH374ISNGjGDWrFn4+flJPy+EEEJ0fZLQK4QQQlzsLBYL69at4+WXX2bkyJHcf//9+Pn5ddtJjR9TFIXGxkY+/fRTPvzwQ2688UZuvPFGfHx83IEPpxPy82H5cnjtNbWirt2uPv8f/4D77lOTdhsajsesDhxQY1bl5WrFXV9fiIlRE3dTU9Wqu5GR6u5TOp16XGC7UAkhhDgNRVGoq6vjhx9+4LvvvmPr1q0EBwdz5ZVXMmbMGIKCgtDr9ZLk2Y24krdtNhu1tbV8//33rFy5kqqqKgYMGMDkyZPp2bMnwcHB8pkLIYQQQlwg7HY7u3bt4vnnnyc8PJwHH3yQ+Pj4bpHEcyYURcFqtfLdd98xf/58hg4dyl133UV4eLiMWYUQQvwyXFVOnE51EsVmUydJ8vLURN/9+9WJk5YW8PFRJ0lCQ9UJk7g48PODgAC10q+fnzpx4uJwwLPPwjPPgMkEw4fD//0fZGSoj/9R32a1WlmyZAkffPAB9957L5MnT+6wa1ZX50pYrqio4Omnn8bhcDBnzhxSUlI6u2lCCCGE+HkkoVcIIYS4mFksFhYtWsTy5cv5/e9/z+jRozG6VjRfZBRFYePGjbzyyiv07duXxx57DKPRSH29ho8+gnffhZ071ZjRiQYNgrQ0Nf5kMKgLwgMD1dhTWBhERakxqchI9Vw3iRUJIcRFx/X9uLW1ldWrV7NixQosFguDBw9m9OjR9OnTBy8vr05upfi1nFj1bNOmTWzcuBFPT0+uv/56JkyY0GFhkBBCCCGE+PUpisLXX3/NSy+9xPTp07nlllvw9fXt7GZ1CkVROHToEC+88AIWi4Xnn3+esLAwGa8KIYToHG1tUFEB1dVqcm9ZGZSWqom/ra1gtaqTKTExEBurVvSNj1d/f+gh+OCD41slBgbC9Olwxx1qYq9Gg4La97377rt88sknPProo4waNarbFrFRFIXa2lrmzZtHXl4ezz//PHFxcdLPCyGEEF2XJPQKIYQQF6v29nZef/111q1bx1/+8hf69u3bbQMaZ8rpdFJaWsqTT/6ZsLA0Lr30QebONbJ/vxpH+jGNRk3mfeUVdQG5l5caZzIY1EPiJUII0T0oikJzczMbN25k4cKF6PV6br75ZkaMGIGfnx86nU6C5Bcxh8NBfX09WVlZvP3227S1tXHPPfcwevRoSewVQgghhOgEdrudb775hpdeeonZs2czceJEPDw8LupxmWuXkXnz5pGfn88///lPoqOjL+r3RAghxAXC6VQr+VosajJva6ua5Lt/Pxw+rFb2LS9Xq63k5UFtbcfn63RqYu9118E992BPSWHJp5+yZMkS5s6dS48ePS6Kua+2tjZefvll9uzZwz/+8Q9iYmKknxdCCCG6JknoFUIIIS5GdrudZcuWsWjRIl566SXS0tLO+hpOp5Pt27ezfft2+vXrh81mIy8vD6vVSnR0tHvLcY1Gg9VqZevWrezatYuwsDDGjx9PQEDAGQUTGhoaWLt2LWVlZaSlpTF27Fg8PDxOetwPP/zAV1995a6g6O3tzS233EJAQMBZv7bCwqNcd9137Nt3GTZbHA6HBq1WjSv9WFQU7NoFwcFnfRshhBBdgKIo7N27lwULFlBWVsZtt93GxIkT8fb2Pi/XdzqdfP/99+zatYthw4Zx6aWXoigKW7duxWw207t3b0Dtu9esWcO+ffvcz42JiWHGjBln1J/W1dWxevVqjh49Sr9+/bj88stPudXwF1980eEeAFFRUdxyyy3Y7XZ27NhBVlYWvr6+XHHFFURFRaHRaLDZbGzevJnc3Fx8fHzIyMggKSkJrVbLzp07yczMxGq1Eh4ezogRI9zJAzk5OWzZsuW05zIzM7FYLISHhzN8+HD3ZITrXFtbm/t5rnNr1qxh9+7dHV5DeHg4t99+O7t27WLLli2nfN750Nrayrp161i0aBEhISHcddddDBw4UCZQhBBCCCF+JYqikJmZyTPPPMMf//hHxo4de07XOHjwIN999x1hYWFERESwa9cumpubCQoK4vLLLychIcE9xlMUhcLCQg4dOsT48ePP+D5tbW3uMXRkZCQTJ07E19f3pLHjkSNH+Pzzz2lpaQHA09OTSZMmnVM8z2q18te//pXq6mqef/75M47PCSGEEJ1GUdQk37w8GDkSmptP/TiNBiUiguopU/hrQQG/efpphmVknHU/19bWxurVqyktLeWaa64hOjqatrY2Nm7cyKBBgwgJCTnDZisUFBTwzTff4HA4GDly5CmTi202G6tWrSIvL8/9t/j4eG688cazajdAc3MzTz75JAaDgWeffRa9Xn/W1xBCCCFEp/vJhN7uv0xJCCGEuAgpisKBAwdYtGgRc+bMITU19Zyus2fPHubPn09ISAhFRUUsWbIEs9lMjx49WL16NY8//jgOhwNFUfjyyy954403iI+PZ9u2bTz33HPY7fbTtq+trQ2bzUZrayv/+te/yM7OJikpibfeeoulS5fiPEVmbXZ2Nv/4xz+YO3cuc+fO5bXXXqOhoeGcXltUVBDz5g1mwIDnePbZTN56S2H2bBg9GiIiwM8PfH1Br1d3hTp27JxuI4QQ4gJnt9tZuXIljzzyCImJibz66qtMnz79vCXzAmRlZbFw4UKCgoIoKiqioaGBBQsWMHPmTLKysjq0ZdmyZR36uiVLlpz2uk6nk9bWVux2O42NjTz33HMcPnyYhIQEXnnlFVatWsWpFvEuXbqUf/7zn+57PPvss3z33XcA5OTk8I9//IPQ0FCKi4t56qmnaGxsBODLL7/khRdeIDQ0lOrqah588EFqamoAWLFiBQB9+/YlJyeH+++/n/r6egCWL1/uPrdr1y5mzZpFXV2d+3lOp9N97v777z/pXL9+/di9ezezZs2i9v9XaPn0009Peg1r164F4LPPPnM/Lzc3l1mzZnH06NFz/PRO5u3tzZQpU3j55ZdJSUnh8ccfZ9WqVdhstlO+30IIIYQQ4vxqampi/vz5XHPNNYwaNeqcrlFVVcVLL72El5cXFRUVLF68GLvdTv/+/SkoKOD++++nvLwcRVGw2Wx89dVX/O53v+P999//yesqioLVasViseBwOPj00095//33SUpKYv369bzwwgunjHkVFhby8ssvu8e3r7zySoekn7Ph6enJ7NmzsVqtLFu2TMaoQgghLnwaDZhM4OkJp5pX0uvV876+ONrbKVq6lFuTkhjcs+c5LVpZsWIFGzZsQK/XU1JSQmVlJU888QSPPPIIlZWVp32eoig4HA5aWlpQFIXKykoef/xxNBoNJpOJP/3pT+Tm5p7U99psNpYuXdoh5vfxxx+fdbsBTCYTDz74ILm5uWzYsEH6eSGEEKIbOrn0nRBCCCG6PKfTybvvvsvw4cMZPHjwOVfh2LFjBxqNhuuvvx4APz8/pk6dikajwel08vDDD1NTU0NwcDCvv/46N998M1OnTiUlJYU777yT3NxcBgwY4L6ea+u/rKws8vLymDBhAlarlW+++YbFixcTHx+PoijMmzeP0aNHExER0aE9Xl5eLFu2jMsvv9z9t3PdRsnTU8OwYbE89NB4Pv74ZRYsSOWOO4JQFGhvV3d4ys+HPXugoEBdHC6EEKJ7cTgcfPbZZyxYsIDHH3+c0aNHo9Vqz3v1qs2bN+Pn58fNN9+M0+kkKyuLqKgo/P39Twq6DxgwgD/96U8kJia6//bj9iiKQk1NDdu2baOgoIDp06dTWFjItm3bWLFiBUFBQTQ0NPD2228zbNgwgn9UYn7atGksXLgQvV6P3W5n4cKFjBgxAkVReO2110hPT+f666+ntLSUO+64gy1btjBp0iQ++ugj+vfvz/XXX09JSQlr1qwhKyuLKVOmMGjQIK688ko8PDwICgpixowZHDlyhMDAwA7nQkJCuPHGGykuLiYoKIiBAwee0bnQ0FD3ueDgYCZOnMi8efPw9PTE4XDw9ttvc+mll7rfw4kTJ6LX6wkPD+eGG26gsLDwjKurnAmNRkNUVBQPPvgggwcP5tlnn+Xo0aPccsstp9xlQAghhBBCnD/Lly/H09OTm2666ZQ7UpyJyspKDh8+zJNPPklkZCRffPEFkyZNQq/XExsby/Lly8nLyyMyMpKamhpqa2vp0aOHe7Hbj7kWr+/cuZPdu3fTs2dPLrvsMt566y3+7//+jylTphAbG8tdd93FjBkz6NGjx0nX+Otf/8oNN9zgHv+fa8xLo9EQFhbGAw88wBNPPMH48eOJi4s7p2sJIYQQv6oDB9SfAQEQEwOhoRAWBpdcAj17Qu/efL13Lwvfe493/v53PPz9z+k2a9asYfjw4dx9991YLBa+/fZbBg8ezMaNG0+bIOt0OikqKmLLli00NDRw9913s3TpUjw8PLjrrrtob29n27ZtLFu2jB49epxUOdcVP/q5fbJGoyEuLo7f/e53LFy4kEGDBp3TLpZCCCGEuHBJhV4hhBCiGzp69Cg5OTlMnToVT0/Ps36+oihs376dxYsXs3nzZu6880527NjB9OnT3ZMJTqcTDw8PvL29qa+vp7y83L2ddUJCAiaTiezsbBRFQVEULBYLq1evZt68edTV1TFlyhSSk5MpLi7G09MTk8mERqNhwIABlJWVceTIkdO2zel0nrKaydnSaDSMHz8em83Grl270GgUdDrw8lJjQ9Onw1NPwX/+A6eYZxFCCNGFKYpCTk4Or7/+On/+858ZPXo0Op3uvCbzKorC+vXr+eSTT1i7di133HEH+fn5pKenc9VVV2E0Gk/5HFdfpygKGo3G/TdXksCyZct47bXXsFgsTJ8+naioKAoKCvDz88NgMKDRaBg4cCCHDx+murr6pHtcd911GI1GtFotpaWlWCwWkpKSaGpqIj8/n+TkZHcSQFRUFJmZmQB4eHh0eH80Go07gWLatGnuRFaHw+EeI5zqnF6vx2QynfW5E6957bXX4uXlhVarpaKigubmZlJSUgCYOnWqe9LE4XCg0+nc1zyfNBoNWq2WYcOG8cgjj/Dhhx+yd+/e834fIYQQQghxXHNzM8uXL+eWW27B39//nMbvR44cYd68eezevZvf//73fPTRR0ybNq1DDE2j0eDj4wNAZGQkN998MxEREadcbNfe3s6OHTv45z//yYEDB0hPT2fYsGEcPXqU2tpa9/OSk5PR6XTs2rXrlO068bvAz+X6TuDaZUuq9wkhhOgSEhLgzTdhyRJ4/331eOcddaLmuutoT0zkyw0buHLKFPwDAs56HGCxWFi8eDGbNm3i7bff5p577kGj0TB58mTS09NPWijk6pdramp44403+PjjjwkJCeGGG25AURT27t1LcnIyWq0WT09PevfuTVZW1k/uXnlizO9caTQaRo0aRVtbG/v375d+XgghhOhmpGyMEEII0Q2tW7eOhISEU1b7OFP9+/dn8uTJZGZm8vLLL+Pr6+s+Z7PZ2LlzJ5MnT8bHx4eSkhI0Go07ycZoNGI0GqmsrERRFFauXMn69esZMmQIDz30EL6+vu7E4IqKCry9vd2BErPZTHt7O8eOHTupTSaTiQULFvDaa6+h1WpJSUlh9uzZhIWFnXPww8fHh/T0dLZu3crIkSNPWVXvHIu9CCGEuIC1trby3nvvMX36dDIyMs65stf/MnToUMaMGUNFRQUvvviiOyngVLRaLS0tLfzpT3/C6XSi1WqZMGECt956K1qtluXLl7N161ZGjRrFww8/jMlkQqvV4nA4qKiowMfHx92/+vn50dLSQktLy2nv53Q62bJlC2lpaZhMJoqLi7FarZjNZgD0ej2+vr6UlZUB8Nvf/pbnnnuOxYsXc/jwYfz9/RkyZIj7epWVlWRlZbFy5UqmT59OTEzMSedWrVrF1KlTO5yrqqpi+/btrFq1iquuuuqkc67nTZky5aQqJoqikJmZSVJSkrvdJz5v9erVTJ48mfj4+J/6mH4WrVbLmDFjKCws5JVXXuH1118/pwVVQgghhBDif9u9ezft7e0MHz78nK8RFRXF7bffzoEDB3j22WdPGivu27ePlJQUEhISfvI6iqKwY8cOPvnkEyIjI5k5cybBwcHuhXCVlZXodDq8vLwA8Pb2Rq/XU1VVddK1fHx8WLt2LStWrECj0RAcHMy9995L7969z7lSr4eHB1dffTULFy7klltu6RDbE0IIIS5IAwbAwIFwmvmeiooKDh8+zEMPPXROlzcYDFx77bUsWbKECRMmcPvtt2MwGE75WNeOkx9//DFFRUVMnz6dPn364O3tjUajob6+nrq6OlJTUwE1ydbPz4/q6mocDkeHa2m1WhobG3n88cfdMb8pU6YwY8aMc44h+fj40KNHD3Jzc0lPTz/vO44JIYQQovNIhV4hhBCiGyooKCAtLe2ck5M0Gg2enp4YjUY8PT3x9/d3BxUURSErK4vKykpmzZqFVqs9qXKIRqNBo9G4K+kWFBSg1+sJCwvDx8enQwVEp9N5yuomp1pRPHbsWN58800++ugjnnrqKbZu3cqHH354Tq/RRavVkpqaSmlpKTab7WddSwghRNfR0NBAaWmpuzLvL0Gj0WAwGNyHn5/fKReOuOj1eu6//37eeecdPvjgA+644w7mzZtHdnY2DoeDw4cP4+XlRWhoKCaTqUN/errKHj9VoaOhoYGcnBx30P/H/e+J/TmoSdBms5mDBw9SVVWFr68vFovF/fi6ujr27t2LXq/HZrPR1NR00jkPDw/sdvtZncvNzUWn0+FwODqcA2hsbGTr1q1kZGR0eP319fXs3bvXPU453dbI54tOp+Oaa66hqKiI4uLiX/ReQgghhBAXs4qKCmJiYk7axvps6HQ6vL298fDwwGw2uxNuAUpKSli1ahWPPPIIwcHB/zM55siRI1itViIiIvDz80Ov13cYowPu3388vj5R7969efHFF/nwww+ZP38+NpuNF198kba2tnN+nQBpaWk0NDTQ0NDws64jhBBC/Cq02tMm8wIcO3YMo9H4kwvmf4pGo8HLywu9Xo+3tzd+fn4/2dc3NzdTXFxMcHAwwcHBeHl5dejnTxVHO1UsztPTk9mzZ/Puu++yePFibr31Vl588UV27tx5Tq8D1IU7SUlJlJSUnJRALIQQQoiuTRJ6hRBCiG6osbHxF6m6Ybfb2bp1K2vWrGHOnDnExsai0WgICgrC6XS6k3qsVisWi4Xg4GB0Oh2zZs3igQceoLCwkGeeeYYtW7bQ0NCAoiiEhITQ1tbWIVlIr9efMiBjMpkICAjAw8ODXr16MWjQILZu3fqzXpMrgGO1Ws/LloZCCCG6BtcijhMn7zubRqPB398fHx8fjEYj48ePx2AwsGfPHgwGAw899BD33HMPOTk5/O1vf2PHjh00Nja6++KWlhb3pEFLSwtGo/G0r8/pdLJs2TLS09MJCgoC1Cr5er3eXdXXZrPR0tJCaGgojY2NvPTSS1x77bX8+c9/5vnnnwdg0aJF7mv27NmTP/7xj/z5z3+moKCAt95665TnioqKOpzr0aOH+1xxcfFpz5WUlLBw4cIOr+HTTz/lsssuIyQkpMPrS0tL4w9/+ANPP/00paWlvPnmm+f0mZwNs9mMp6fnKXcZvDhZDAAAIABJREFUEEIIIYQQ50dra2uHZJrzRVEUDhw4wMKFC7nvvvsYMmTI/7yHRqNh2rRpPPbYY3h7e/PMM8+wevVqqqqqcDgcBAUF4XA43PEyi8VCe3u7e/x9IoPBQFBQEHq9ntDQUCZNmkROTk6HBXTnQq/Xo9PpsFqtP+s6QgghxIXAZrOh0+nOuXr92dBoNMTGxvLkk08yYcIEPvroI+bPn8+hQ4dobW3FaDRiNpvdi8+dTifNzc0EBASc1D6tVktAQAAmkwkvLy8mTZqEVqtl3759P6t9Pj4+NDc3y9yWEEII0c1IQq8QQgjRDYWEhFBTU3Ner+l0Ovnqq6/IzMzkwQcfJDo62h2UCAkJISgoiPLychRFoaSkhJaWFgYOHOiu9hsTE8Mdd9zBzJkz2b17N++//z4lJSUkJCTQ2tpKa2sriqKQm5tLeHh4h+22XTIzM92BCZvNRmtrK4GBgT/rdSmKwrFjx9yVDoUQQlwcjEYjGo2G2tran6xi+2uy2Wxs377d/burb3RVCzEajcTFxXHvvfdy++23s2XLFhYvXkxNTQ3JycnU19fT3t4OqFsRx8fHExoaesp7FRcXs2PHDiZOnOhOVAgICCAuLo7CwkIURaG2tpby8nIGDx5MS0sLx44dIygoCA8PD3x8fPD19XVXuN+2bRugVjsLCAjAx8eHkpKS0547cuTIKc/5+vqe8lxgYCC+vr6UlJS4X0NpaSnbt2/nyiuvdL+GE99D1zXNZnOH5/1SXO9FeHj4L34vIYQQQoiLlZ+fH8eOHTuvY3hFUcjJyeGzzz5jxowZ9O/f/4xjRDqdjvDwcK688krmzJlDQ0MD7733Hrt27SIiIgIfHx+qq6tRFIXCwkIcDgd9+/Y96Tp79+51V9FVFIWmpib8/Px+dsJSa2srTqcTb2/vn3UdIYQQ4kJgNBqx2Wy/WkVajUaDyWSiT58+PPHEE2RkZLBs2TKWLl2Kh4cHqampFBQUoCgKNpuN/fv3M3DgwJN2ErBarWRlZbl/dy2mN5vN59w2p9NJbW0tgYGBMrclhBBCdDOn3+tTCCGEEF1Wr169WLRoERaLBaPReNbPVxTFXUHElTh77NgxHn30UTw8PFixYoV7G/Gnn36aoUOHcsMNN7B69Wr69evH8uXLiYuLo1+/fh2uq9FoiImJ4e6776a8vByz2YzZbKZnz558+umnTJ48mffff5/JkycTGRlJVVUVf//737nqqqsYM2YMn3zyCTabjdTUVLZt20ZOTg5//etff9Z7Zbfb2bVrF8nJyT9ru0YhhBBdS0BAAH379mXZsmX07dsXT0/P834PRVGw2+1YrVba29tpa2tzTzy0trZit9tpa2ujubnZXS1+4cKFeHl5ERAQwEcffYTZbGbUqFEdrqvRaEhISOC+++6jrKwMX19f+vbtS3R0NMuXLycjI4OPP/6YqVOnEhwcTFFREXPnzuX2229n8ODBOBwOvvrqK4YMGdKhIr5Wq+W2227jjTfeYNSoUeTk5KDVasnIyCAoKIgePXqwZs0akpOTOXLkCDk5OTzyyCMoisKCBQswGo2Eh4eTmZlJbm4uf/nLX1AUhddffx2DwUBERARbt25l9+7dPPPMMwCnPPf000+fdG7btm3s2rWLp556CgCHw8G6devo37//SZMfr7/+Onq9nsjISLKyssjJyWHOnDnn/fM98XNub2/n3XffZfDgwURERPxi9xJCCCGEuNjFxcVRUlJCc3Mz/v7+53QNp9PpHo+3tLRQX1/P3/72N3Jzc1m1apV7sdhvf/tbbrvtNhwOB62tre4Ku42NjRiNRvR6vfuxrt02ZsyYQU1NDYqiYDQamTZtGp9//jkpKSksWbKE3r1707NnT2w2Gy+88AIBAQH89re/ZfPmzRiNRsaNG0dlZSX//e9/ufrqq895S3GXrKwsIiIiCAgI+FnXEUIIIS4EgYGBOBwOqqqqTruI/acoioLVasVms9HW1obFYsHT0xOr1UpTUxN2u53m5mZ3Bd4TF9bodDoGDRpEz549qaysRKfTMW3aNNauXcu3336LwWBg9+7dPPXUU3h4eLB161YWLVrEnDlz8PX15T//+Q/e3t6YzWY++OADQkNDGT58+Dm/FzabjQMHDjBs2DBJ6BVCCCG6GZ1rEu00fvKkEEIIIS5M4eHhLFq0iOTkZGJjY89pG8KioiLWrFmD0+mkoaGByMhIiouL3dXzfH198fPzY/jw4URGRtKjRw9sNps7+eixxx4jMDDwlPfWarX4+flhNBoxGo0MHjyY7OxsVq9eTXp6OjNnzsTT0xOLxcLevXtJSUkhJiYGRVH47LPPWL16NbW1tcyePZuMjAy0Wu05b7VYU1PDG2+8wa233kp0dPR537JRCCHEhUmn0xEfH8/ixYuxWq2kpaX9Igs79u3bx8aNG2lvb6e5uZnExESysrJ46623ADh69CiFhYVccskl+Pj4UFZWxqpVq1i3bh1ms5mnnnrqtP2TVqvF398fT09PTCYT6enpfPvtt6xdu5bx48dz22234eHhQXNzM/v376dPnz6Eh4fT1tbGgQMHGDNmDP7+/h2uHR8fj4+PD0uXLsVqtfKHP/yB+Ph4d2JvcXExK1asIC8vj5tuuomrrroKT09P6uvrWbVqFV9++SWNjY3ce++9jBo1Cr1e3+HcsWPHuPfeexk9ejQeHh4nnZs5c6b7XENDAytXruTLL7+koaGBe+65hyuuuMK9ZXBubi5jxozpMN7QarU0Nja6n1dXV8c999zD2LFjf7HJDbvdzttvv82GDRt49tln8fPz+0XuI4QQQggh1ESe7777DrvdTt++fc8pjtPU1MTixYtRFIWKigpiY2Oprq7GYDC4Y16+vr4MHDiQHj16UFpayr///W9KS0vRarXs2rWLkJAQIiIiTrq/q5Kfj48PGo2GPn360NjYyNKlSwkNDeUPf/gDZrMZRVHYt28fZrOZ3r174+npyfr16/n888/Zs2cPN9xwAzfddBOenp7nHKtqaWlh7ty5XHXVVef8XgkhhBAXEpPJxIEDBygoKGD48OFn3bc5HA6++eYbioqKaGhoQKfTERUVxRdffMGKFSswmUwcPHiQxsZGkpKSMBgMHZ6v0WjQ6/UEBASg1WoJDg6mZ8+efPLJJ+Tm5jJr1iyGDx+OVqulpqaGoqIi0tPT3btOrVq1im+//ZaAgACeeuopIiMjz7l/rqqq4r333uM3v/kNYWFh0s8LIYQQXUsj8K/TndT8j22JLox9R4UQQghxVpxOJ//6178oLi7m73//OyaTqbObdEFyOp28/PLLHDp0iLlz58r7JIQQF6Hs7GyefPJJJkyYwH333YfBYJAAuDgjrqouixYtYsWKFTzxxBPuSRshhBBCCPHL+eabb5g/fz6vvvqqLM4+DUVRWLlyJW+88QbvvfcegYGBnd0kIYQQ4rzYuXMnjz/+OAsXLjzngjZdnaIozJ8/n/379/Piiy/i7e3d2U0SQgghxNkpBWJOd1JmmYQQQohuSKPRcP3111NeXs6KFSuw2+2d3aQLjsPh4Msvv2TNmjU8+uijkswrhBAXqUGDBvHKK6+wZ88e7r33XjIzM7FarZ3dLHGBs9ls5OTkcP/99/P111/z8ssvSzKvEEIIIcSvJCMjg/j4eBYsWEBra2tnN+eCoygK+/fv54033uCBBx4gICCgs5skhBBCnDf9+vVj0KBBvPbaa7S0tPA/Cth1O4qikJWVxRdffMEDDzyAl5dXZzdJCCGEEOeZ7plnnvmp8z95UgghhBAXJo1Gg9lsJi4ujrlz5xIVFUVCQoIkmZzghx9+4Pnnn+fOO+8kIyPjolzFLYQQQu0zg4ODGTlyJDU1Nbz55psUFxcTFRVFQECA9A+iA0VROHz4MAsXLuSdd95h6NChPPbYY8TFxck4SwghhBDiV+Lh4cEll1zC4sWLaW1tpW/fvuh0us5u1gWjqqqKZ555hv79+3PTTTfh6enZ2U0SQgghzhuNRkNKSgrvv/8+Wq2Wvn37XlTxu6qqKp5++mkmTJjApEmTJB4lhBBCdE2NwL9Od1ISeoUQQohuSqPREBkZSVhYGC+88AIBAQEkJiZe1BMciqLgcDjYsmULf/nLX7j22mu54YYb0Ov1nd00IYQQncxgMDBw4ECGDRtGdnY2CxYs4ODBg0RFRWEwGPD09LyoJgfEcYqi0NLSwsGDB3njjTeYP38+fn5+PP7440yaNAk/Pz/5b0MIIYQQ4lek0WgICAigf//+vPrqqxw9epSePXtiMBgu6nGZoijk5eXx1FNPERUVxaOPPoqPj09nN0sIIYQ4r1wFbWJjY3n11Vcxm80kJiai1Wq79ThAURSOHj3KnDlziIyMZNasWRiNxm79moUQQohu7CcTejX/YwuCi2t/AiGEEKIbcjgcbNy4kblz53LFFRO57bbfEBwcdFF+yW9ra2Px4sV88skn3Hnnndx4440AF+V7IYQQ4tQURUFRFA4dOsR///tfMjMzCQsLY8yYMQwdOpSEhISLenHMxURRFAoLC9m8eTMbN26koqKCfv36ceutt5KamgrIGEIIIYQQojMpikJ+fj5PP/004eHh/P73vyc+Pv6iHKO1t7ezYcMG5s2bR3p6Og8//LAk+QghhOjWFEXh+++/57nnnmPatGn87ne/w2AwdHazfhGKorBv3z6W/eUveFZVcf+CBfikpqKRGKUQQgjRVZUCMac7KQm9QgghRDekKOphs0FrK2RnO3nrrUNs3JjJ5ZdnM2fO3fTo0QMPD4+LIrDvcDgoKCjg3//+N0eOHOHhhx9myJAhUplXCCHET7Lb7RQVFbF7925WrlxJUVERvXr1YsKECQwePBg/Pz/0ej0ajeai6E+7O6fTic1mo6Wlhc2bN7Nu3Tpyc3OJjY1lwoQJXHrppcTExMiWxUIIIYQQFxBFUSgvL2fBggXk5ORw//33c8UVV1w0O2w4nU7q6+t5/fXX+e6773jggQcYO3asVOYVQghxUXA4HGzdupUXXniBfv36MXPmTMLCwtBqtZ3dtPNCURRsNhuZmZk8//zzXBcYyC0tLXg2NEBqKowbB0OHQkAAeHqCVgsXwfhHCCGE6AYkoVcIIYS4WDidUF0NxcWQkwNZWeq/AwMhPV0hI6OV3buXsmzZfxk8eDDXXHMNvXr16raJrQ6Hg8LCQlavXs1nn33GyJEjmT17Nv7+/hfFpI4QQojzQ1EUHA4HZWVlfPnll2zcuJHa2lri4+MZMGAAaWlpxMbGEhUV5U7wFV2DzWajsrKS0tJSDhw4wPfff09RURHh4eFkZGQwadIkYmNj3VWZ5bMVQgghhLgwWa1W1q5dy9tvv01ERATXX389gwcPxtvbu7Ob9otQFIXKykrWrVvHkiVLSE5OZvbs2e4tx4UQQoiLhaIo1NTU8Nxzz1FQUMBdd93FyJEj8fPz69JxHKfTyeHDh3n77bfZuXMns2fPZuKECegUBU1VFWzcCGvXQmkphITAoEHqkZIC4eHg4dHZL0EIIYQQpycJvUIIIUR35OrCFQXq62HrVti0CXJz1b9fcon63b1nT/X7u7e3ujBXURT27t3LRx99xNatWxk2bBi33norSUlJ7uBGVw5yuLZKr6qqYsmSJaxdu5bExERuu+02BgwYIFX1hBBC/GwWi4WioiJ++OEHsrOzyc/Pp62tjdjYWC699FIGDhxIr1698PLy6tCnduX+tatzxT4URaGtrY38/Hy2bdtGTk4OR44cwdfXl+joaC677DIuueQSevTo0W2TP4QQQgghurPy8nKWLFnC119/TXJyMrfddhsDBw7E4/8ntXTlMblrTNvY2MiqVav4+OOPMZlM3HDDDYwdO1bGr0IIIS5aiqLQ0tLC2rVreeeddwgMDGTmzJkMGTKkS817ufr6hoYGPvjgA9asWUO/fv249dZbSU1NPXnRTns7HDkC+/dDdjbs3QvNzZCWBiNHQkYGBAcfr9rbBd4DIYQQ4iIhCb1CCCFEd2KzQW0tVFWpFXizsiA/X63CO2wYTJgA0dHg5aXusHOq7+eubXpKSkp45513yMzMJC0tjSlTptCnTx9CQkK63NaEdrud6upqCgsL+fTTT8nJyaF3797cfffdJCcnYzQau9TrEUIIceFz9adtbW3U19eTlZXF5s2bOXDgABaLhcjISFJTU+nTpw+JiYn4+fnh4+OD2Wzucv1sV6IoCu3t7TQ3N9PY2EhjYyOFhYX88MMPHDp0iJKSEvR6Pb1792bw4MGkp6cTGBiI0WiUz0UIIYQQootz7a5RX1/PRx99xBdffEFwcDDTpk1j0KBBREZGnrTw7kLndDqpr6+nqKiIdevW8c033xAcHMxdd93lrkIsVXmFEEIItc+sra1lxYoVfPLJJ8TExHDdddfRv39/goOD3Qt8LjSKotDa2uru61euXElcXBz33XcfvXr1+t/xKkUBux3a2qCyEr7/Xq3eW1GhVvzJyID+/SEyEoKCQKeT5F4hhBCic0lCrxBCCNHVKQqUlMCOHbB9u5rACxAfr34Hv/RSSE4Gvf5crq1QWFjIV199xebNm2lubiYlJYXLL7+cwYMHExISckFPCtTV1ZGdnU1mZia7du1Cp9ORkZHBuHHjSEtLu2ADNEIIIbqv1tZWCgoKKCwsJD8/n0OHDnH06FEcDgdarZaIiAhiYmJISEggNjaWqKgoQkNDpYr8OVAUxb2op6ysjCNHjlBcXExhYSHV1dXY7Xa0Wi3BwcGkpKSQlJRESkoK8fHxeHt7d6lEDiGEEEIIcXZcW3CvX7+etWvXUllZSWxsLOnp6WRkZBAXF4dOp+vsZp5Wa2sru3fvZvPmzWRnZ2OxWOjVqxeTJ0+mf//+eHl5dXYThRBCiAtWeXk5X3zxBevXr6e9vZ1BgwYxbtw4+vbti8Fg6OzmAbh3m9ywYQMbNmygpKSElJQUpk+fTnp6+s+LFba3Q1GROrGYlQUFBWoib8+eMGQIXHYZhIZKYq8QQgjROSShVwghhOhKFEWtwtvSAtXVsGmTehQWQliYWoV35Ej1e3ZgIBgM5+f7ttPppKGhgZKSEjZv3sy3335LTU0NCQkJjBgxgssuu4ywsDC8vLwwGo3o9fpfLQnGVV3FYrG4qyBu376dLVu2cODAAUwmE8OGDWPChAlERUURHBx8QU/ICCGEuHg4nU4sFgtNTU3uirEHDhzg0KFDFBQUUFpaisViwWAwEBYWRnx8PNHR0SQkJBAdHY2/vz96vR69Xo+Hh4f7p06nQ6PRdLuEVEVR3P2+3W7HZrN1+OkaqxQXF1NcXExpaSnl5eVYrVYMBgPR0dHEx8eTlpZGcnIyAQEBmEwmfH198fLyuqAXKQkhhBBCiF+Goig0NzdTVVVFZmYm3377Lbm55YSEJDFmTAqXX55BdHQ0JpPpV9+1QVEUnE4nVquVtrY2mhob2bt3L+s3bGDPnj04HA4uvfRSxo8fT2pqKsHBwb9qTE4IIYToylxV+/Pz81mzZg1btmzBZDIxdOhQxo4dS0xMDCaTCS8vL3es7ZfidDppb2+ntbWVxsZGtm/fzrp168jPzyc8PJxJkyYxfPhwIiIizu+Ok4oCVivU1cH/Y+++w6Mssz6Of2fSew/pCaHXQOiIgtiwrVjYXQuoq7sWFnXFAoqigiioWEABEbEhYF9X5bWggqCAAooiXWpIgIT0Nu15/7h3BrCwIGDa73NdcyVkUu6ZROfc5zn3OXl58NVX8PnnZhRohw7mgmPv3hATA2FhYLeryFdEROTEU0GviIhIQ+A9LLtmDXz3HWzaBOXlZhpOr15mIk76QS/pJ2o/7Y0NPB4P27dvZ8WKFSxbtoytW7dis9mIiIggMzOTrKwskpKSSE5OJi4ujtjYWMLDw4+5UMZ7kaW0tJTCwkL27NlDfn6+r3CnuLgYp9NJZmYmubm59O7dmzZt2vgKeHVBQ0RE6rOf78Ety6KwsJCdO3eSl5fH9u3bycvLo6CggJKSEpxOJ4GBgQQGBhIUFER4eDjx8fFER0cTFRVFREQEYWFhREZGEh4eTmhoqO/wTWhoKMHBwSf8gsSRcrlc1NTU+A7oVFVVUV1dTVlZGZWVlb6i59LSUoqLiykqKqK8vByHw0FtbS0OhwN/f39iYmJITEz0dTfOzMz0Hej5tTikPjx2EREREal73lh80ya4774a/P33kZLyIps2fYvD4SAiIoLk5GSys7NJSUkhKSmJxMREoqOjiY6OPi6Hx6urqykpKaG4uJj8/Hz27NnDzp072bp1KyV79pC4ahWe7GzaXHghPXr2JCcnh+DgYEBxrYiIyO9xcC6usrKS5cuXs2TJEr777jtcLhexsbFkZ2eTnZ1NWloaSUlJJCQkEBUV9bsnQFqWRXV1NUVFRezdu5fdu3ezfft2Nm/ezK5du6iuriYlJYU+ffrQr18/WrVq5fvaE/p6730uXC5zQfKzz8xY0D17ICrKjATt1s108VX3XhERkRNJBb0iIiL1jWWB222KePPy4MMP4csvYd8+SE2Frl1NEW9Kirn9zpzBceNyuSguLmbPnj3s3buXjRs3smXLFvbu3UtBQQE1NTUEBwcTFRVFYmIiMTExREVFERMTQ0hICCEhIdhsNsJDQrABlbW1uN1uamtrqaqqorS01Fe8s3fvXkpKSqiuriYgIICEhASSkpLIysqiVatWpKSkkJCQQHx8vEaTi4hIo2RZFrW1tVRWVlJRUUFlZSVVVVVUVFRQUlLCnj17KCoqorS0lPLycl9nj/LyKoqL0wgKchISkufr7BsWFkZ4eLiv45j3FhQUREhICEFBQb4uZMHBwb6iWJvNRlBQkK9wwbIsqqqqDllndXU1lmX5im69r+3e92tqaqisrKSsrIzq6mpiq6oIqq5mvd2OBwgJCfGtLTw8nPDwcKKiooiPj/fFFGFhYYfcwsPDCQoKUkGDiIiIiBwVl8vk3yZONAfnr70W4uPNxKrCwkIKCgrYvn07GzZsID8/n71791JWVkZgYCAREREkJCQQFxdHVFSU73CddwqEN252OBy4XC4cDgfV1dWUlpZSVlZGcXEx+/btY//+/VRWVmKz2YiPjychIYHMzExat25NRlISbT7/nKBFi/B79FFs7dqZLnkiIiJyXHk8Ht81r507d/qmaeXl5bF//34CAgKIiIggJSWFmJgY4uLiiImJITQ0lICAAIKCQvDzC6C2thKXy2W67JeXs3//foqLiykoKKCwsJCqqiqCgoJISkoiIyPDN1GqWbNmJCUl+Q7t1BnLgpoac6Fy0yZYvtx0HSovh06dYOBAMzY0LAwCAkyBr/JxIiIix4MKekVEROoDy4Lqati+HTZvhlWrYPVqqKoy++K+feGUUyA6Gvz86u++2DsK2+Px+G5VVVXs3r37kI6C3osV3g58lmWRsXEjMWVlfNutG35+fgQFBREaGkpkZKSv20lCQgLp6ekkJycTGRmJ3W733RrjaHEREZGj4X0d/vmtvNxi/nyL116zcfvtNXTsWEJJSQnl5eWUlZX5CoO9HXIP7pRbW1uL0+n0HbY5uFt/bW0tHo8H4BcFv4Dv0E5gYOAhRcIHv+99rQ8PCyNtwwYSZ8/G8Y9/EHLRRfDfQuLfunl/roiIiIjIsSgrg9dfh7lz4cYb4bzz4OfnxA/OeXnf1tbW+op99uzZw/79+yktLaWkpISKigqqq6txu92+Qt6goCD8/f0JDAwkJCSEqKgoX94rPj6e1NRU0tLSiI6Oxt/fH5vNdiDvBabqeO5ceOUVuPVWOP30uj/pLyIi0oh5X//dbjcejwen08nu3bvZtWsXO3fupLi4mP379/sa0TgcDvLyYtm0qT0nn7wIf39/34H12NhYoqOjSUpKIi0tjYyMDKKiorDb7fj5+R1yiL7esSzweEwnou3bD3QiKi4240P79IGcHPN+YqIOHYmIiBwbFfSKiIj80Q5+eXU4YP16WLjQFPDu3w9xcWZqTU4OtG4Nycn1s3j3uHv+eVi7Fh57rK5XIiIi0ih4Dww9/DB89x2MGgW9e9fjuMLphEWLzIKHDoW//tVUUtTbBYuIiIhIQ2ZZUFQEEyaYydKjR0NurjlMX2+5XDB/Prz0kqk+/tOfzMcVM4uIiNQLn38Ojz8O//53Xa/kBKupgS1bTNfeb76Bn34ycUpurhl30KcPhIcf+HzFKiIiIkfqsAW9OtYrIiJyHHk8ZhLNvn2mC+/ixaaI1+WCrl3hL3+B7t3N/jYkxBxg1f5WREREfg+PB7ZuhUmTTEzxxBOQlVXPY4uAADOuLz4e7rkH9u6F666DyMi6XpmIiIiINDIuF/z4IzzwAGRnw1NPQWpqPY+XwXTk/ctfICMDxo83icbLL4fg4AaweBEREWk0goOhQwdo3x4uuggqK2HHDvjoI3j6aXjoIXPfgAHQubPJ98XEqHuviIjIMVKHXhERkWNkWaaI9/vvYfly+PZbKCmB2Fizf+3e3XTijYxUzl0dekVERI6flSvN9f127Uxn3gZVE2tZsHGjeQBJSTByJDRrpmBJRERERI4LjwfefRemT4dzzoG//90crm9QLMskGydMgFNOgREjICiorlclIiLS5DWZDr2HU11txpN+/TWsWgV5eRAaai6Kdutm3kZEKNcnIiLy6w7boVcFvSIiIkfBsswFgepqKCszo60XLTKTZvz8oEsX6N8fWreGxETTiVcHUQ+igl4REZFjYlmm09hnn5mX04svhssug7CwBpof37ULxo0zwdWkSSrqFREREZFjYllQUQFz5sBbb8Hw4TBoEAQGNtAw0+02B+HGjjWdA4YPh+joBvpgREREGgcV9B7EsqCqykzh2rHDJC1XrACn0xT1nnKKKfANCzswulRERERU0CsiInKsPB7Yswc2bTLd8NasgcJCiIqCrl3N5Oj27c3FAS/MBoNYAAAgAElEQVTl1X+FCnpFRESOSVUVzJoF771nmtqecYb5eIONOyzLjDaYMsWMOxgzBjp1UnJfRERERH6XvDyYONG8HT8e2rZtwLGyl2VBQQHceacZyzFmjJlyISIiInVCBb2/wVt75HCYa4GLF5uOSCUl5hB/795m1FjHjuYCa4MP0kRERH43FfSKiIgcDcsyN7cbiovNQdLPPjNFvGFhkJMDubnQqhVkZDTgjnh1QQW9IiIiv4tlmbhk6lQzxe7uu82hIn//ul7ZcVJRYeYhf/opPPigCbhU1CsiIiIiR8jjgXXrTCiZlAQ332zydo0mZ2dZsHs3PPQQ1NbCPfdAenojeoAiIiINhwp6j5B3dMLWrbBlCyxdaq4R+vsf6N7bs6fpluTvr7hGRESaksMW9DaWS38iIiLHzOk0XXh37jRdeL/91uwxmzWDk0+Gv/8dMjMhIAD8/LSvFBERkT+GZZmc9/jxJr/97LOQkNDIYpGwMLjpJlN1cccd5v0zz4SgoLpemYiIiIjUc04nLFwIkyfDn/5kcniBgY0sXrbZICUFHnnEFPX+618wdqyZbtGoHqiIiIg0GjYbRERA584mZjnvPHMwae1a+L//gyeeMN18W7SAAQOgZUuTG4yJUXwjIiJNmgp6RUSkSTq4Qf3u3bBsmZn88tNPEBxsuu+eeabZY2Znm4sAIiIiIn80yzKHjB54wDSuuO46iItrhDltm80EXJdcYk5PTZ1qxvFdccWB+0VEREREDmJZpgbkjTdg9mz45z9h0KBGfCbMZoOQELjtNnjuORg9GsaNM6M7FC+LiIhIfWazmZxfQAD06mVuFRWmuPf77+HDD82Uz/Bw6N0b+vSBbt3M53u/XkREpIlQQa+IiDQptbVQVGQ68X75JSxZYgp6mzeHvn1h+HCIjzf7xYAA7Q9FRESk7rhc8MUXpjPvX/8KQ4eag0eNms1m2qqlpJgHvn8/XH216eahwExERERE/suyzPmvp582B/UnToQuXcxUrUYvMtIkMRMTzXSLUaPg1FObyIMXERGRRiM83BT29ugBl15qCnzXrTPFvfffbz6nUydzYqtFC4iNVY5QRESaBBX0iohIo+dymc67X39tOtxt3gweD3TsCBdfbLrdZWSA3V7XKxURERExamvhP/+BZ5+FESPgnHOayMQAm80UIvTqZcYJ33035OWZt1FRdb06EREREakHLAu2bYNJk8DphMmTzbStJlXbERQEf/4zhIaaJ6KyEs4+u4lsGkRERKRRsdshLMzcmjWDAQNMbLN6tbm4O3u2KfaNjTU5wy5dICenCXQ+EBGRpkoFvSIi0qh4R+1VVUF+Pnz0kenCu38/ZGVBz56mu11CgunE653UIiIiIlJf1NTAiy/C22+bOtZ+/Zpos63WrU1xwoQJ5okYPdp07m1SlRoiIiIicjC3GzZsME1pO3eGm24yjWqbpMBAM90iPt5MtygpMaM9goLqemUiIiIixyYszCRF+/aFsjLYtw/Wr4eFC+H11yEkBHJzTffetm1NcW9wsPKGIiLSKNgsyzrc/Ye9U0REpL6orISNG01C/5tvzJ7OsswBzZ494eSTISbmwD5O+7k68vzzsHYtPPZYXa9ERESk3rEsKCyEadPghx/g3nuhQ4cmHrdYlgn0xo41p7XuuQfatavrVYmIiIhIHXA64eOP4YknzFTmSy81tatNOl4GEzOvWmVGUw8YAH/7G0RH1/WqREREGq3PP4fHH4d//7uuV9LEeGubampM597Fi00M5HSaUawnnQRt2pjcYWho3a5VRETk8HYB6b91pzr0iohIg2NZphuHw2GKeP/v/2DlStOEIjPTHNa85BKzd0tKMpNaREREROozyzKxzL33mpz0Qw9BixZ1vap6wGYzHTnGjIHnnoO77jJFvV27HrhfRERERBo1ywKPxxTNTJ8O114LF1+syVs+NpvpUDdpktlQ7N1rJlyEhyteFhERkcbDG9eEhMApp5huTkVFsHUrrFsHixbB7NkQG2u6PZ12minu9fc3F4sVF4mISAOhDr0iItIgeDxQWgp5ebBpEyxdahq9Wpap5zjlFOjTx+zhAgLMnkz7snpIHXpFRER+weMx0wXGj4fmzeFf/4K4OMUyh/Ce6HrpJZg7F0aOhDPOAD+/ul6ZiIiIiJxAlgXl5TBrFnz0kTnn1bu3ajJ+lWXBzp1mYxEYaA7DJSfriRIRETnO1KG3HvJ4TKfeqipYscIU965aZS4ad+4M/fubTlDp6aZ7r+IjERGpW+rQKyIiDcvBZ03Ky2HNGvjiC1i92uzDUlJM04nBg80Y6uho7btERESkYbIs+PZbuO8+U5hw882mIa38jM1mumlcfjlERsLkyaaV8bnnmo8rGBQRERFpdCwLKithwgRzwH/CBOjSRaHfb7LZTKHKgw+a2513mictLU1PmoiIiDRudjsEBZnbWWfBmWea7r0//ADffQdz5pgpBikp0KOHGffavv2BZgGKlUREpB5RQa+IiNQL3tF55eVQWGj2V0uXmsOTgYGm++4//wktW5oaDu/hSe2vREREpKFyOmHhQtPRY+hQMzY4OLiuV1XPBQWZU11paWaccH4+XHmlCQ5FREREpNGwLNixAx5+2OQMn3gCUlOVCzwi8fEmVn76abjpJpg40SRV7fa6XpmIiIjIH8NmMzHRgAFmzGtFhRkFu3Kl6SI1f7654Nyrl5kClpICsbEmOauAU0RE6pgKekVEpE55PLBvH6xdC8uXw48/QkkJJCZCt26mCVvbtqZ2Q/snERERaSw8Hpg3D155BUaMMI1mFescIX9/k2yfNMm0Ni4uhuuvN0l3EREREWkUtmyBMWNMEe/YsabeQo6QzWZi49tug5kz4dZbYdQo04lORb0iIiLS1NjtJpiMjIT0dLjgApNP/OYb+Oorc4LM4YDsbHNxunt3aNUKAgLqeuUiItJE+d13332Hu/+wd4qIiBwNywK3G6qrzVSTTz+FadNMs4jvvjOHH889Fy67DIYMMTnm5OQ/bopybW0tTz/9NOvXr6dTp07YjzDBvWTJEp5++mlyc3MJVXe4w1u92lRwn3VWXa9ERESkTlgW1NaaKW9z55opuKeddmC6W13zxkMbN26kY8eORxUPPfPMM+Tm5hISEnKCV4kJDps1g969TWX0ihUm2e4d4yAiIiIiDZLHYyZ33XOPqae49VZTe1EfQjzLsnjnnXd45513yM3NJTAw8Ii+bvPmzdxzzz106tSJqKioE7zKgwQEQE4OuFwmAZudbRKwKuoVERE5Jtu2wbJlcOmldb0So6ysjIceeoiamhpatGiB7QgCJ8uyeOutt3j33XfJzc0loCkVr9psEBICLVrAySfDwIFmVKzNZsbHvvwyLFgAeXkQFXWg65TdXj+CUhERaQzKgMd/60516BURkRPO5TJ7no0bTT3njz/Crl3mEORJJ5mudFlZppDFuw+qi/2QzWYjPj6eiIiII9rseoWFhZGcnIy/v15WRURE5PCqqmDKFJMbnjwZ2rWrX3lgbzwUGRl5VPFQaGgoycnJ+P2Rlck2mwkin3jCjBEeOdK0b8vOrl9PqoiIiIgcEcuCxYvhkUfMWfDhw+tf3URkZCQJCQlHfPANIDAwkNTU1LoplAkKgquuMl0Txo0z49D++lc4wmJkERERqf/sdjuJiYlEREQc1ddFRkaSmJh4VHFNo+PnZ8bGJiRAhw5wxRVQWgpffgmffQa3326Kf9u0Mc0E2reH5s0VS4mIyAllsyzrcPcf9k4REZGfsyxz83igoMBMKvnkE9i+HSIioFMns99p2dIU9AYGuvF4PAD4+/tjWRZutxu73Y7dbseyLDweD5Zl+T4G4Ha78b6G+fv7/2bBiff7/fz1zmaz+T5mt9vx8/PD4/Ec8rMP/jk2m81XoOJyuXzfw8/PD7fbDeD7Hh6PB7vd7ntcfn5+vsfiXQ+A0+lk5cqVtG3bloSEhOPzC6jnrOefx/3991iTJvmeI+/z6P2dHPwceX8XR1NQJCIiUh9ZFlRWwpNPwsqVcO+90LmzKVBwu5tuPORwOFi5ciXt2rU7tniouBimToVVq+DBB/9npfTBj9O7poMf88GP27t+m82mmERERETkBPDmEz//HB56CIYNg0suMbUT3rgN8MWibrf7kNjUG7cdHM95Y1I49lj553Hwr/1s78/5tY95/33w1xwchx4cKx/89ZZlsXr1ahITE2nevPmxPMUmWfvJJ+ZU4ZAhcOWVh3ZXOMzzciQ5vIPvExERaew+/9xi8mQ3b755IF92cD7M+7r+82td8Ms82+FiFG/+7WAHxygHvy5744uD83vez/fz8/vV9Rwc1xzN635FRQVr1qyhW7duhIeHH98ntz5xu83F7q1bTUJ31SrYvdtMPOjTB84801zs9sZUJygO8v4teHOTB/+deX8/B8e+ymOKiDQIu4D037pTrQRFROS4qKmB/HzTiXfFCvj6a/PvFi2gXz+44w7TCCIw8NBc8fTpMxk/fjw9e/ZkypQprF27lvvvv5/Bgwdz3XXX8X//93+88cYbOBwOsrKyuPvuu9myZQvPPvssZWVluFwuXnjhBaKjo391XXv27GHs2LF8+umn9OvXj8LCQrZu3UqHDh3w9/dn9+7d9OnTh/vuu49169YxYsQIevXqxYQJE1i6dCmzZs2iuroaf39/Zs2axaeffsqrr76Kw+EgLi6Oe++9l4kTJ7Jx40amTZvGggULmDx5MqNGjWLVqlWsX7+ekSNHcu6551JdXc2rr77KJ598gsPhYMeOHZx//vn06tXrD/xN1a0q4OF583h9wQJGjx7NokWL2L17N/feey99+vShrKyMmTNnsmzZMlwuF4mJidx000106NBBG08REWnQ9uyBSZNg3z6YNs00fvC+tD377LM8+OCD9OrViylTpvD999/zwAMPcOGFF/KPf/yDBQsW8Oabb+JwOGjevDl33XUXW7ZsYcaMGZSXl+NyuXjxxRd/c3xvQUEBY8eO5fPPP+ekk05i3759bNu27bDxUJ8+fRg/fjxLlixh1qxZ1NTUEBAQwHPPPcenn37KnDlzcDqdvnjo4YcfZvPmzTzzzDO8//77PPHEE4wePZqVK1eyfv16brvtNs455xyqq6uZM2cOCxcuPCQe6t2797E9wdHRpkPvCy/AzTfDffdBz55mzPCvWLlyJTfccAOnnHIKERERLF26lN69e3P//fdjt9tZunQpzz//PMXFxQCcc845XHXVVU1r/KCIiIjIH8TlgjffhFmzTA5x4ECTPwT46KOPuOWWW4iPj2fKlCkAjB49mg4dOjB69Gh+/PFHpk+fTlVVFYmJidxyyy34+/szdepUdu/eTVVVFY899hht27b91dxSdXU1Dz30EC+99BKnnnoq5eXlbNq0iczMTGJiYigoKCAxMZFp06ZRVlbGrbfeis1m4+mnnyYvL49p06axb98+qqqqmDFjBnl5eYfkLadMmcL8+fOZN28ezz77LPn5+dx2220MGzaMwsJCVq5cyZAhQ7jxxhtxu9289957vPnmm1RWVlJQUECLFi149tlnj/1Jttvh9NMhNRXuustsTK6/3oyR/pXnxeFw8NhjjzF79mzuvvtuli5dytatW7n77rsZMGAAFRUVvPjiiyxatAin00lMTAw33XQTOTk5TbvLn4iINBEevvzyPjIyZnHRRRcxbtw43n//faZOncr111/PJZdcwty5c/nwww9xu9106dKF22+/nS+++IKXXnoJh8NBeHg406dPJzg4+Fd/wk8//cTtt9/Oli1b6NKlC/n5+RQUFNClSxecTif5+flcdNFF3HDDDSxatIg777yTq666iuHDh/P222/z2muv4XK5SElJYdKkScybN48FCxbgcrno2LEjV111FXfeeSf+/v48+uijzJgxg9dee43Ro0ezePFidu3axb333kvfvn0pKytj+vTprFy5EqfTyfbt27nuuuvo16/fH/y8/8H8/Ezs5C3gdThM915vN6vXXoPYWNPJqndvM0nMezH8OF7T3Lp1KyNHjgRgwIABfPLJJ8TFxTF58mRiY2PZunUrjzzyCHv27MHj8ZCbm8uIESOIiYk5bmsQEZE/lnbVIiJy1A7uwrtunambuPVWuOkmM/G4stJMbps9G559Fq6+2hT2hoaCv/+he5hLL72Unj170q1bN5KSkujfvz89evTgmmuuoaysjMmTJ3PppZfy9NNP89NPP/HWW28xf/58cnJymDNnDqNHjyYoKOg315qUlMQ555xDQkICjz32GLNmzSI9PZ0+ffowc+ZMxo0bxyeffMLOnTvp2LEjZ599NtXV1dTU1PDCCy9w5plnMmfOHG6++WZqa2uZOXMmQ4cOZc6cOVx99dU0a9aMv//971RWVmKz2TjjjDOIiYkhJyeHxx9/nP79+/P666/jcDjYuHEjzz33HLfffjsvvvgiOTk5lJeX+7p3NAVhwKDMTAICAhg4cCBTpkwhKSmJjz/+GJfLxYIFC3j//fd55JFHmD17NuHh4UyePJmKioq6XrqIiMjvlp9v6kurquDhhw8t5gUTD/Xo0YNu3brRrFmzQ+Kh0tJSHn/8cV88tGnTJt5++23mzp1Lbm4uc+bMYdSoUYeNh5KTk38RD6Wmpv4iHtq1axcdOnRg0KBBvnho9uzZnH322cyZM4ebbrrJFw9deeWVh42HoqOjffHQKaec4jugtXHjRmbNmuWLhzp16kRFRcWxx0M2mwk2r70WrrkG7r8f3n/fdNL4FV27dqVz586Eh4dzxx13MHLkSP7zn/9QVlZGbW0t48aNo1OnTrz44ov885//ZPr06axevfrY1igiIiIiv1BbC3PmmPziqFFw6qkHinkBzjzzTM4//3xatmxJy5Yt6dSpE507d+bWW28lMjKSBx98kO7du/Pcc88RFBTE7NmzWbhwIS6Xi9mzZ/Pwww+TmJj4mz8/NDSUc889l+joaMaNG8crr7xCv379SE1N5cknn+Txxx9n48aNrF+/npSUFIYNG0ZlZSUul4v33nuP2NhYXn75ZcaNG0dISAjz58+nc+fOvrxlfHw8V199NWA68vXr14+srCySkpIYP34811xzDfPnz6eqqorS0lKeeuopzjnnHF5++WXOPfdcSkpKDhvrHxW73YyJfvhh02Hu4YfNJuVXBAUFcdZZZxESEkLfvn156qmnaNu2Le+99x5Op5NFixYxb948HnjgAV588UUyMjKYOHEiJSUlx2etIiIi9Zof6el/p3Xr1px00knExMQwaNAgBg4cyCWXXMKPP/7IrFmzuOOOO5g8eTIff/wxH330Ec899xxDhgzhlVde4R//+Ieve/+vadGiBaeffjotWrRgypQpTJkyhdDQUC666CJeeOEFRowYwbvvvkthYSEnn3wyPXr0oLa2lsrKSmbOnMl1113HK6+8wuWXX05lZSWzZ89m5MiRvPjii5x//vlkZGRwxRVXUFVVRUhICIMGDSIgIIBTTz2VKVOmkJqa6itI/uqrr3jnnXd49NFHmTVrFklJSdTW1jadQzw2mwlQQ0IgKQkuvBCmTIGXXoK//c0U+s6YAf/8J9x+O7z6qunq63YfuKh+DLKzs+nfvz82m40rr7ySCRMm8MMPP7Bt2zbcbjePPvooAQEBvjzvZ599xvvvv3+cHryIiNSFJvIKKyIix8qyTH43Px+WLzfj7y65BIYPhyVLoG9fU8w7Y4ZJvl9wATRvfmgC/tdERERwwQUX8O6771JVVcXSpUvp3LkzMTEx/PTTT1RXVxMeHk5FRQXx8fGsWrWK9PR05s+fz8svv0xCQsIRJbX9/f0JDw8nPDyclJQUgoKCCA4OJj3ddLGvrKw85PMDAgLIyMhg1qxZzJs3j9TUVMLDw0lLS+Opp57inXfeISsr6zeLT+Li4ggODiYrK4vq6mocDgfV1dU4nU5iY2MJDg4mOjqa2traJtl51m63ExsbS0hICBkZGVRUVFBTU8PKlSvp0KEDGRkZREdHc8EFF7By5UpdDBARkQbJsmDzZhMbRUfDxImmocPPX/ojIyMPiYe+/PJLOnfuTHR0tC8eioiI+EU8NHfuXF5++WUSExMJDAz8n+v5rXgoLS0N+PV4KDMzk5kzZzJ//nzS0tIIDw/3FTe88847NG/e/Dfjofj4eF88VFVVhdPp/EU8FBMTc3zjocBAE6SOHAnTp5vqkKqq30ycR0ZGEhISQnJyMoGBgVRWVrJjxw727t3LSSedRGRkJP379yc2NpalS5cenzWKiIiICGDCtOnTTXOzRx+FAQNMM4CD2Ww2LrroIlatWsWuXbtYu3YtSUlJJCUlkZ+fz86dO0lOTmb//v0kJiby7bffkpiYyFdffcUzzzyDv78/kZGR/3MtNpuNyMhIX/waEBBASEgIiYmJhIWFUVZWdsjn2+12UlJS+PDDD5k5cybh4eFERkYecd7SGw9nZmbidruprq7G7XZTXl5OfHw8QUFBxMbG4nA4fu/T+1sPFNq0gcmToajIbFZ27frNeNlmsx2S56ysrKS2tpZVq1bRsmVLsrOziYyM5KKLLuL7779n3759x3e9IiIi9VRqahpnnXUWc+fOxel0snjxYnr27ElYWBjr168nMDAQu92O0+kkIiKCtWvXkp6eztNPP82bb75JZmbmER1wDwoKIiQkhJiYGOLj4wkJCSEwMJCsrCxqa2upqan5xecnJSUxefJk3nvvPbKzswkPDyc6OppJkyaxaNEiWrRo8avFxN5rd8HBwb5rd263m7KyMvz8/IiOjiYsLIyIiAicTudxey4bJLsd0tLg7LNh9Gh4+ml47DHTrffzz+HKK+Hyy2HmTFi71kxHcDiOqbg3NDSUiIgIYmNjiYmJoby8nMLCQtasWcPAgQOJi4ujQ4cO5ObmsnDhwuP3WEVE5A/XdFoCiojI71JZabrwfv+9adywfbtJrHfpYpqf9e0LxzKxw263c+qpp/Lcc8/xwQcfsGnTJq688kpsNhsul4uioiJef/11IiMjiYuLIzc3l/POO49mzZrx7rvvMmvWLKZPn05OTs5R/Vzrf2yY/Pz8GDlyJBkZGfz73//mhRdeYMaMGTzwwAO8+uqrzJkzhzlz5jB16tTDfh+bzeb7WdnZ2bRv356HHnqI9PR0fvrpJ26++eYmWdB7MO9z5PF4qKmp8V3osNlsx68DiYiISB3YvBnuvttcL7/zTggP//XPOzgeWrBgARs2bODqq6/2xUP79+/n9ddfJyIigoSEBLp168a5555LUlLS746HDo4/vO//PD7y9/fntttuIyMjg3feeYfZs2czY8YMxo0bd9TxkPf7Z2dn065dO188tHXrVm655ZbjGw/5+8NZZ5mOGWPGwE8/mQLfiIgjWmNNTQ02m42AgID/fjt/AgMDcf9Gt18REREROXrl5aYxwBdfwKRJ0KHDr08mttlstG3blnbt2vH222+TmppKz549sdvtuFwuKisr+eCDD1i5ciUA559/PoMGDSIsLIw333yTYcOGMXbsWM4777wjXtuvxcc/j5Xtdjt//vOfiY6O5q233uKll17iscce4+9//ztJSUn8+9//ZtasWUybNs3XUOB/iYiI4NRTT2XGjBksX76c7777jqFDhx7/7nfeApRJk2DsWLjrLjPhonnzI/pyb8wcFBSEzWbDZrMRGBh4SB5URESksfPz8+Oiiy7ijTfeYNGiRaxYsYIxY8YA4HK5KCgo4OWXXyYwMJCcnBx69uxJ9+7dmTdvHq+99hovvfQS06ZNIzs7+6h+7v96rQ0ICGDixInMmTOHF154gXnz5vHEE08wdepUXn31VZ588knefPNNHn744SP+md27dycqKop7772X6OhoPB4PAwcObPLXNwETwAYEQGysubVpA1dcYTpkrVhhumJ98IGJv9q1g9xc6NoVMjJ+eZLtiH/kgefd6XTidrt911PtdjtBQUHKY4qINHAq6BURER+PB5xOqK6G9eth4UL4+muTYG/Vyoy8u/ZaUxuRkGD2HsdDWloa/fv3Z8qUKVxyySXEx8cDZjx0s2bNuPHGG8nJycGyLFwuF7t37+bCCy9k0KBB3HTTTSxZsoS2bdvicDgICws7Lkluh8NBUVERV1xxBRdccAHXXnstixYtYuDAgdxwww0MGTKEoUOHsmbNGjIzM4/oewYHBxMbG8vAgQOJj4/nL3/5Cy1atDjmtTYWgYGBZGZmsmzZMt/J3o0bN5KamkpISEgdr05EROTIWRb88IO5Nt6zJ9xww28X83qlp6fTv39/nnrqKYYMGUJcXBwAKSkpJCYmcuONN9K5c+dD4qGLLrqIs88+mxEjRrB06dLjHg/V1tZSVFTEsGHDGDx4MNdccw2LFy/m1FNP/UU8lJGRcUTfMzg4mLi4uD8mHurcGSZMMKMlHnzQdMuIjPz1SpGDeDsW7969m5ycHAoKCigtLaVVq1YnZp0iIiIiTUx5OUydaqaAPfootGhx+BAtOjqaQYMG8eSTT3LZZZdxxhlnYLPZSExMJD4+nr/+9a+cffbZ2Gw2PB4P+fn59OrVi5NOOomHHnqIhQsXMmjQIKqrqwkLCzvseOsj5Xa7KSwsZODAgQwYMIAxY8bw8ccfk5mZyeDBgznrrLN8ectLL730iL6nn58fCQkJZGVl0blzZwYPHnxiY9DoaLjvPpg2zXTqveceaN/+fyZ9/fz8yMrK4ttvv6W2thY/Pz82btxIYmIiEYc5RCciItLYtGrVio4dO/LYY49xySWXEBYWhs1mIyUlhZSUFEaNGkVycjKWZVFbW0t+fj7XXnstF198MVdeeSWrV68mOTkZj8dDSEjIccnnVVdXU1FRwYgRI/jzn//M0KFDWbFiBV27duW2225j8ODBXHfddfz0009H/D3Dw8OJj4/nT3/6E8HBwVx11VVHnABJQNMAACAASURBVAtskux2SE2FwYPhvPNMd94dO0znrP/8B556CjIz4Ywz4OSTzUX3oCAz9vYoi6Tj4uJ8U2/dbjcVFRXs3LmT9u3bn6AHJyIifwQV9IqINHEeD5SWwpYtphPv11/D1q1mr9G1K9x8M/TqZfYRdvtR7yOOiN1uZ+jQocybN4+WLVsSHBwMmGKKPn368MQTT3DaaacRGRlJu3btePPNNwFITEzE5XLRvXt3Zs+ezcsvv8zs2bNp3bq173tXVFSwYcMGioqKWLNmDf7+/uzYsYPg4GC2bdvGmjVrKC4uZv369fj5+bFu3TqKiopYvXo1CxYsID4+nvDwcIKCgmjVqhVPPfUUbdq08SXY4+PjWbZsGUVFRSxbtozw8HBKSkr4+uuvCQ8PZ926dRQUFLBr1y7cbjcbNmygZcuWVFdXs3v3boqKiujSpUuTKVh1ABuLiylzOFi1ahVZWVls3ryZ6upqiouLOf/88/n666+ZPHky0dHRfPDBB1x77bXExsbW9dJFRESOiGXB6tXmWviZZ8L115s46n/xxkPz58+nRYsWv4iHHn/88UPioTfeeAO73U5CQgJut5tu3br54qEXXnjhkAv/5eXlh8RDfn5+bN++nZCQELZt28Z33333i3iouLiY1atX88EHH5CQkEB4eDjBwcG0atWKJ598krZt2/4iHiosLGTZsmWEhYX54qGQkBDWrVtHfn4+eXl5uFyuX8RD+/fvJycn5/jHQzYbdOxokuRjx5ouvXfdBc2b++Izu93Onj17WLduHSUlJaxdu5ZTTz2VYcOG8eqrr7Jr1y7WrFlDq1atOOuss47v+kRERESaoP37YfJkM0ThySdNc7L/lW+02Wycd955TJs2jaCgIJKTkwEICwtjyJAhPPfcc+Tl5ZGYmEjLli1ZtWoV33//Pe3bt6egoIBBgwbx8ccfM2rUKGbOnEmvXr1839vpdLJx40ZKS0tZsWIF2dnZrF+/nj179rB582YKCwspLCzkxx9/JCsri5UrV1JQUMCKFSvYvn07BQUFZGdnU1xczOmnn87cuXOBA3nLtm3b8tVXX1FSUsKKFStwu93s3buX1atX06dPH9auXUtxcTEbN26kTZs2fPXVV3Ts2JHY2Fjy8vLYu3cv3bp1Iyoq6vj/Mmw2M3rtjjvg2Wfh1lvNRqZfP1xuN5s2baK0tJRvvvmGTp06sXHjRnbu3ElhYSFnnHEGixcvZvLkyTRr1owPPviAv/3tbyQlJR3/dYqIiNRTdrudq666iuuuu47u3bv7Oqd27tyZjIwMHn74YXr37k1UVBStW7dm+vTpZGVlERQURFRUFO3bt2f8+PGsWbOG6dOnk5qa6vve+/fvZ9OmTeTl5bFhwwYKCwvZs2cPq1evpl27dqxatYqioiI2bdrE/v372bZtGw6Hgx9++IEXXniBnJwcPB4PqampJCUlMX78ePr27UtlZSWtWrUiICCAlStXkp+fz/Lly9mzZw9lZWWsWrWK7OxsNm/eTGVlJUVFRWzYsIHdu3ezbds2QkNDffm8Tp06+SZcya/wdu9NSYHkZNP54R//gIICWLoUPv4YXn7ZxGO5uebWtq353IO69xYXF7Nlyxby8vLYunUreXl57Nu3j++++47evXszfPhwnn32WTweD/v27aOsrIzLL7+8Dh+4iIgcK7/77rvvcPcf9k4REWlYvFNYLAsqKsykj5degunTzZ6hstLsJYYMgb/9DQYNMpPWAgJOXDGvZVnYbDZCQkLYsWMHQ4YMITIyEjAdW3v06EFcXBxOp5PIyEhatGhBWloalmXh7+/P2WefTffu3YmIiOCLL76gd+/eh2x4a2trcbvddO/enYSEBAICAkhLS6Nly5YkJyfjcDjo3r07GRkZhISEEB0dTefOnUlOTqZjx444nU6CgoK44IIL6NatG82aNcPhcBAaGsoll1xCRkYGZWVl9OrVi/j4eBISEsjJySEhIYHExET8/Pzo2rUrGRkZhIWFsWXLFpKSkvD396eiooLZs2eTnp5OZmZmkxhN4169mpq9e+nxr38RFxdHZGQkERERdOzYkezsbDIyMujevTtut5vg4GAGDx7MySefrISAiIg0CB6PORw1dixcfDEMGwZHUqPqjYeCg4N/NR7q3r078fHxOJ1OoqKiaNGiBenp6Xg8niOKhxwOB263mx49ehAfH09gYCDp6em+eMjpdB4SD8XExNCpUyeSk5Pp1KnTIfFQbm4uiYmJv4iHysvLffFQfHw8Xbp08cVD/v7+dO3alczMTMLCwti8eTPJycm+eOj5558nIyPjxMRDNpv5JfTqZSqt33wTunen3N+fhIQEWrVqRUZGhq8oOjk5mdTUVLp06UJKSgoul4sOHTowdOhQoqKimkS8JiIiInIiWJYp5p040UwgfvDBIyvm9Y6VDg0N5ccff+Syyy7zTfcC6NKlC2lpabjdbkJDQ8nKyiI9PZ3AwEBsNhsnnXQSAwcOJCIiglWrVtG6detDmgG43W6qqqro3r07cXFxREREEBER4YuHLcuiY8eOZGVl+eLBHj16kJiYSE5ODn5+ftjtdgYOHMgpp5xCs2bNDslb5uTkUFhYSI8ePUhKSiI2NpbWrVuTkZFBenq6L05PSUkhPj6erVu3EhERQVhYGC6XizfeeIOamhpycnJOTCxqs5lucB07mpOITz0Fycl4MjOprKqiW7duxMfHExsbS0hICJ07d/Y9xz169ADMaO/zzjuP0047jcDAwOO/RhERkXpm2zaLZcvg0ktt2Gw2amtrOffccwkJCcFmsxEREUGPHj0IDQ3F7XYTGxtLixYtSE1Nxel0EhwczMUXX0z79u0JCgpi+fLl9O/f3zexC0yn3YCAALp06UJSUhI2m402bdqQlpbmOzjUs2dP0tPTsdvtZGRk+GKM1q1bU1tbS3h4OEOGDKF9+/a+3GJMTAx//vOfiYmJ8cUhMTExxMfH+67JRkVF+a7dNW/eHD8/P7Zs2eKbWLpv3z5mzZpF7969iYmJUb7sSNhs5ma3mwliHTrA2WfDgAGQng47d8KCBfDGG/DVV2acblwchIRQXV1NYGCgL1/p/VvwXl9u3bo1rVq1wu12k5aWxtChQ5vMdWcRkQasDHj8t+60eZMhv+Gwd4qISMPgdkNJCezaBT/+CMuWwdq1prahb18YOBDatIHgYAgM/J9T1Y6rXbt2ERcXx7Jly9i+fTtXXnnlUW8wHA4HX3zxBUuXLuXOO+8k6Eja4P3BLMvirbfe4osvvmDcuHGEhISwa9cubrrpJq6++moGDx7cNDZWzz9v/vgee6yuVyIiInJcud2waBE89BBcc40p6D3S8yjeeOirr75i586dDBs2rFHHQ0uWLOGBBx4gJCSEnTt3cvPNN3PNNdfwpz/96cTFQ5YFNTUwYwZ88gncfrsZafdHBr4iIiIiTdiePebgm8tlinmbNTuyrysoKCAiIoJNmzbx6aefcssttxz1OGq3282qVat44403GDNmDBEREb/jEZx469at45577uGpp56iWbNmlJaWMmbMGNLT07njjjvw8/M7sQtwu02s/MgjBzY1KtAVERH5hc8/t3j00Txefz2OBQsW+A63HG1eq7q6mg8++IDdu3dz/fXX18vmNm63m8cffxybzcaIESOw2Wz88MMP3HrrrTzxxBN07ty5aVzfPJEsy8RhNTUmaF6yBD76yJyCy8gwjQq6dTPvx8WZ7r16zkVEGrpdQPpv3en/W3eIiEjDZllQVATffGPi/i1boLYWkpKge3e46ipTxBsSUrcx/7x589i2bRsxMTHceuutv2vT53K5CA4O5uabb66XxSteLVu25L333uPee+/Fz8+PiooKOnbsSO/evbXZFRERacDcbli4ECZNguHD4dxzj7yYF2Du3Lls376dmJgYRo4c2STjoZ49e57YeMjbqffGGyEszFRe19bC6aerqFdERETkBMvLg/vvh/BwuPPOIy/mBfjss89YsmQJYWFhXHfddb8rZvR4PNjtdkaMGEF4ePhRf/0fJS4ujpiYGCZMmEDIf7uxAVx44YUnvpgXTKfe0083XR8mTICqKrjssiMbOyIiItKkuNmw4RnuvLOCtLQ0hg8f/rtiFIfDQWJiIuecc069LOYFsNvtdOnShVdeeYXRo0djs9koLS3ljDPOoHnz5rq+eTzYbKZINzzc3Fq0MDHYzp2wcqUZufvJJ2Y8XOvWpltXz57mor+efxGRRkkdekVEGgHLMt0tKiuhsNDE9p98Ahs3QkKCien79YOsLIiOrvsi3oMVFhZSVFREQkJCox/L4na7KSoqoqSkBMuyCAoKIiEhgdDQ0Eb9uA+hDr0iItLIuN3w4Yfw6KNw221w5pkm/3o09u3bx/79+xUP/VGP2+Ew7ZQnToQrr4QhQ0zRgoiIiIgcV5ZlmozdeadpJjZmDMTGHt33KCsro6CggKioKBISEo66O29D4vF4KCkpYf/+/bhcLgIDA4mNjSUqKuqP3SN4PCZ/N3q0SSoPHw71tKuxiIhIXfj8c4vx4wt45plykpKSiIyMrOslnVBOp5PCwkLKysoACA0NJT4+nuDg4Eadx6wXLMvkMktKYPdu+Oor+Owz2LvXdO7q39908I2PN8XAfn71pwhAREQO57AdelXQKyLSgLndsGsXrFkDq1bBpk2wfz+kp0OfPubWooWJ3b0Uw0udUkGviIg0Ik6nKeZ9/HEYORLOOuvQuEvqMcuCpUth/Hjzi/vHP0znXhERERE5LiwLduyAe++FtDQTL8fEKDfZYFiWSTaPG2d+gTffbLrAiYiICJ9/bvKB//53Xa9EmhRvbZfbDdu3w+LFsGyZGYcRGQmdOpkxvR06mLitER+EExFpBFTQKyLSGFiWic8dDtPZYvFicwBv505z6K57d9OJNzPTjK0LDlaCXOohFfSKiEgj4XLBe+/Bk0/C3XfDgAFH35lX6pjbDevXm1ZxXbvCiBFmnIWCaBEREZFjYlmmgdgdd0BGBowaBVFRdb0qOWreX+TYsSZGfvBBMw5O8bKIiDRxKuiVesGyoLYW8vNhyxYzwnfFCiguNkW9Z55puvdGRkJAgCnwVRwnIlJfqKBXRKSh8k7R2LHDxOHLl5tayOJi03m3Xz9TPNKs2YEJGorDpV5TQa+IiDQCDgf85z8wfbop5j3lFDU8aLAsyyS977kHQkJMtUlaWl2vSkRERKTBsizTMGzUKGjXDm65xdQQKGfZQFmWGQk3ebJJUD/wALRsqQ2QiIg0aSrolXrHsszN6TSFBZ98AkuWwN69JtfZowd06QLNm5vCAsVyIiJ1TQW9IiINhTfW9k40W7LETALOzzeJ7x49oHNnkwxPTdVIZ2mAVNArIiINnNMJb70FM2bAfffBSScpJmvwLMsktx95xHQge+ABc3pOVSciIiIiR+Xnxbz/+pfJaUojUFoKU6earm8TJkD79oqXRUSkyVJBrzQINTWwbRt8/z18+y2sW2c+1qkTDBx4oHuvN6ZTbCci8kdSQa+ISH1mWVBRAfv2mZh68WJYvRoqK6FVKzjtNFMoEhEBwcEHOvGKNEgq6BURkQbM4YDXXoMXXzQ1n716qZlBo1JeDk8/bU7VPfggdOyoam0RERGRI2RZJrd5660mTh4+3OQzpZGwLKiuhpdegrffhvvvh27dzPhmERGRJkYFvdKgeDv3Vlcf6N67eLEZCdy2rRkJ3LUrJCVBTIxGAouI/DEOW9Dr/wcuREREDlJTAz/8ACtXwtdfQ2EhhIebQ3HXXw/du0N8vOJlERERkfqgttYU886Zo2LeRisiAm66CRIT4c474fbbYcAAFfWKiIiI/A+WBZs3w113QZ8+cOONJs8pjYjNBqGhcM01ppPbPffALbfAoEGKl0VERETqM5sNAgPNrVMnc7vhBhPAL18OX31lEt+hoWZUcK9ekJsL0dEqVBARqSMq6BUR+QN4PObQW0UFbNgACxeaIl6n0zT+Ou88EzvHxkJUlIpDpBHxeMwfvsNh/l1ZaarZCwvNv+12syHUH72IiNRjDge88orJa44fbw5eKZfZSIWGwhVXmPhkwgTTtfecc0zCW0RERER+wbJg504YNco0bFUxbyMXEABDhphf8pNPmqT3+edDUFBdr0xEROSEsawDl7cAysrMNV7vpS6bzVzf9Vf1jTQUwcGmSKFDB7j0UigqMt17P/sMJk823S26doWTTzZBfmQkhIWpe6+IyB/EZlnW4e4/7J0iIvLbLAtKS+HHH2HNGli9GgoKTG4zNxd69zYH3IKDD3yN4l9pdBwOGDcOPvjgwH8UtbWm8x1ATg5MnWo2gSIiInXMuz0+OCarrDTFvO++azrz5uYqZmv0LMvcli41Fdznnw9XXaXKFBEREWnyXC7z1lusYlmwaZPpzNu7t2n0FRqqeLnR826cVqwweb9TTz3wyxcREWmE3G6YPRtmzDDvV1VBcTGkppr7mzc3NZCZmXW7TpFj4o3xnE4T5C9cCN98Y4p9mzUzifGcHGjf3nQpU9AvInIsdgHpv3WnzgiJiBwH3mv+Lpcp+vjuO1iwAL7/3jQtaNECzjoLWrUym7uYGMW40kQEBEB6OqxbZzp2eOXlmbdnn62OdyIiUi9Ylonhdu0yU2P9/c0ZlBdegPfeg4ceMvlKxXBNgLfTRL9+pqB3wgQoKYHbbjOn87x/BN5NgDpTiIiISBPgdMKrr5pBBueeC35+JnYeMwa6dIHrr9d57SbDG/v27Aljx5p42eGAW24x3SsUL4uISCNjt0NKiol9CgoOfHzvXvO2bVsTI4k0aN54LTDQdO5t394UPuzYAZs3w5dfwvvvm8/p3t107+3d28R//v6K+UREjiN16BUROQZuN+zfb2LYdetg2TLYssUU7J50EvTtawo//P1NklsxrDRJBQVmLMvBWQ6ApCR4+WU47TT9xyEiInWuthb++leTl5w6Fc48E158ET79FB580OQv9XLVBFkWbN9u2jNHRMAdd5grOGBasSxcCAMHQlxc3a5TRERE5ATLy4P+/U0INH06dO4Md98NPXrA8OEHJvBKE2NZsHs3jB5tOrWNGmU6uIH5Y1m61HTw1bQLERFp4EpL4ZxzTO7wYOHh8PjjcM01ioWkEbMsUxjhcJiiiA8/hJUroaLCdDbr2xfatTPtqtXZTETkSBy2Q68KekVEjpD3f5eWZRp0LV9uCjw2bTInM9PSTKzatq3pxKvxciL/5XbD5ZfDa68d+A8JTPHLnDmmsFdERKQOWZY5mHXOOSbOy8oyDQbKykyzqXbtFNc1efn5pqi3ogImTYLERDNeeNo0U9EyeLD+SERERKTRsiwT8owYAR6PyYNmZJhDcLfcApGRdb1CqVOWBTt3mukWYDZRMTHmZOSMGfDKKzBggOJlERFp8O6917y8eTwHPta8OXz0EbRsWXfrEqkTFRWwfj388IMp7t2yBUJCzIm/k082XXy9U1oVB4qI/JwKekVEfi/LMuPkiovNNfxvv4VFi+Cnn0yjgb59TS4yM9PEpwdP4BWR/7IseOcd+MtfzH9QAAEBZibjmDGmIl5ERKQOVVbCDTeY68zeibARETBxIlx7rZm2IE2c91Tf1KmwZo05xffMM2ajkJsLH39sihZEREREGqH8fLjgAvj6a/Nvm81cm586FYYNO3CdXpowb7w8caL5g2nRAh59FMrLzXSut982mywREZEGbO1aU6tYXX3gY5ddZoZR6lKXNFkejxl/V1kJGzYc6N7rdEKnTiYWbNPGTDiLilIxhYiIoYJeEZGj5XabybqrV8OKFbB5s4lFs7LMYbLcXHPSMiCgrlcq0kBs2gRDhsB335l/R0bC4sWQk1O36xIRkSbPssyBrWHDTFMpL5sNUlJgyhQ4/3wV9cp/1dTAddfBvHlmxByYU32TJsE//6mrNyIiItLoeDzw/PMwcqSZYHGw/2fvzuOiKvcHjn9mYWCGHWQRERUFRFTcQXFDU1tM81JWXq9lZVl5bTHLW93M2/VW2uJyrfy1XNs0l2wxcl/LNTfCBUXZRBTZGZh9zvn9Mc1JhEqxUvF5v168BM7MmTN45jnf5znf5/uEhLhyNu+80xUSCQLV1fDoo/D55z9nO/n5uTpWY8eKeFkQBEG4phmNrklOmze7flapXPVsRoy4ssclCFed2lpXUYQffnDdGy4pcSXzJie7Ei26dHFVSxMEQbh+/WpCr7glKQhCkyPL4HC4vr+YhFtZdt2LN5vh7FnYvt2V1JGXBy1awIABMHo0NG/umjim04mJY4JwySIjXSWtf/zR9aFLTHRVthMEQRCEK8xqhaVLobCw7u9l2VVY6l//csWBSUkiBrzuOZ2wf7+rs+BO5gXXSfTJJ65qEx06iBNFEARBEIQmQ5ahrMyVm2k01t9eXQ3vvgu9e7uKH4gw6Drnjpc3bapbutBohI8+gtRU1xihOFEEQRCEa5TBAMOHu+rVOJ0QE+PKTRQE4QLe3q5OQlKSK7m3pASOH3etcvbll67qGd27w7BhrvvF3t6uBF8RJwqCIAAioVcQhCbo3DlYtMjVgbrhhobjPll23XfPyYGsLNi9G06edI0ztmsHN98M/fq5kjfczxfxoyBcBi8v1wfys89cy+/ddZcocS0IgiBcFY4fh8WLXfGhm0oFQUHQvz/cf78oKC/gOkH274eJE6GgoP72fftcnZCZM8Wa04IgCIIgNCk7d8LGjXXjZa3WNY/p9tth/HhXUQThOidJsGsXPPiga2bk+WQZtmyBlSth8uQrcniCIAiC8HtQq105iq1bu+4x33gjNGt2pY9KEK5iajX4+rq+2rRxJfBaLD8XTZg715WgERkJKSkQH+/qaHh7X+kjFwRBuKJEQq8gNDHyTyOr8vkjrA38fDFU52Ww/tL3VxOn01X8c+ZMSE+Hxx93VdfV6Vxjhk6nq3LviROwY4drOZTiYmjZ0rW6w803Q9u2EB4ullQWhMtxYTuktD99+qBq1gyVwYDUo4fywXS3KRf+KwiCIAhuv3htaYBKpbroa4okwfvvQ02N+7muOSjDhsGECdCrl2uFBnFpEgDXwHNqqitBoaoK7Paft0mSq+rYPfdAQsJFnTTnn8eyLP9u57UgCIIgCNen82Pl34orGvq3IU4nvPPOz2GPVusaO33kEdfS0nFxYhxV+IlKBT4+rioZxcWuSmxO58/bnU54++2fl8K7SBdzXotYWRAEQfgjXXgtat8e4uJUlJWpSE6W8PAASfr5OiSuRYLwC9yfDb3elbzbpw+Ul0N+Phw9Ct9/7xpfDQiAnj1h0CDo1MnV4dBomsQg/cXe5xDxrSAIqt9I8rv0DEBBEH43sixjt9sxm81YrVasVit2ux2bzYbVasVms2Gz2XA4HNjtdhwOBw6HA7PZjNlsxmKxYLPZsNvtWK3WOvs1mUx1Xkur1eLp6an8rFKpMBgMqNVq9Ho9Xl5eypdWq1W+dDpdg1+enp7K4zUazR/8d3LdT//8c3jxRSgqcv0uOdlVDNRk+jmJ9/Bh1ySv+HgYOtS1yoOvr6tQqErVJOJAQfjDOZ1OamtrqampwWw2YzKZlHbH3T5VV1cr2y0Wi9KeJS9fTqDZzPq//AVVYCAAnp6e6PV6fH198fHxQa/Xo9Pp8PLywmAwoNfrMRgMeHt74+Pjg0ajEZ0XQRCEJkqWZWpra5XrSE1NDbW1tVgsFmpra6msrKSqqgqr1YrT6VT+9fDwQKfTodVqMRgM+Pv74+/vj16vR6/X4+3tja+vL97e3vj7++Pl5YUsw549cPfdrjHDiAhXRd4HH3Ql8np5idhQuIAsu2YIFhe7loZbudLVwSgpcW1Tq10JCu+9V6eKhCzLmM1mqqqqlHO6pqZGOa+rqqqoqqrCbDYjSRIWiwWn06n00TQaDQaDAT8/P/z9/ZX4yB0b+fj44Ofnh16vFzGSIAiCIDRxsixjs9mUuMIdW5hMJiwWixJX1NTU4HQ6lbFktVqNl5eXMtbrjiu8vb3x8vKqE1e44w2VSs3q1TB2rGs8tX17V0XeceNcsbNaLeJl4QKy7Mr+PnkSliyBNWtcy+MZja7tOh1MmQLTp8N59yJcT5Wprq5WvoxGo3JuV1RUUFlZicViweFwYLFYANDr9Wg0GiUeDgoKUuJkPz8/fH19CQgI+Ol8FierIAiC8OtkWa4XTxmNRiwWC5WVlVRWVlJTU4PdbmfjxnYcPtyVu+76ivBwB15eXsq1yNvbG4PBgK+vL76+vvj7++Pn54darRbXI0H4JZLkmgBmNruq965fDwcOuDodCQmuSWNt2kCrVq5JZNcAp9NJVVWVEttWV1djNpupqamhvLycmpoaTCYTDocDq9WKRqNRcnF8fHwICgrC19cXg8GgxLvu+NbT01O0J4Jw7SsEWv7SRpHQKwh/kl/6rFmtVkpKSjh79iylpaWUlZVRUVFBeXk55eXlSjKDyWRCkiQ0Gk2dhFqtVotGo0Gj0aBWq5ULvaenJ56enuh0OjQaTb1kXS8vrzoXebvdjv28ClOSJNVJlDj/S5IkJEnC6XQqScQXfq/T6fDx8VE6KsHBwQQGBhIUFERwcDChoaGEh4cTEBCAWq1u8G9zMUGILLsSMF55xTVGWF398zZ3dTWAkBDXUsnt20Pnzq6fRYwjCPVd2FY5HA6KiorIzs7m9OnTnDp1ijNnzlBSUoLRaESj0dRJ5tdoNHh4eCgdDHd7pFKp0Gq1JJjNBOfn8318PLaf2hx321JbW0ttba0yEcF908k9ccFgMBAcHEyLFi2IiIggKiqKNm3a0KpVK3QXLG0tOjGCIAhXrwurkhYVFZGVlUV2djYnT56kqKiIiooKtFqtch1xTxjz8/PDz89Puea4/3VfNyRJwmw2K4Nk7klwVqsVi8WCSqUiJCSEli1b0qpVLNu2DWTVqhbcdRfcdpsrSLT7IgAAIABJREFUodfLS1xDhIsgy1Ba6po1mJ6OvHIlVFS41ll8913OJSVx5MgRTp48SXZ2NkVFRZSVlSnJNF5eXnh4eODp6an0mdzJux4eHmi1WqUv5k4Idg/8nn9eu/tnQUFBSmwUGxtLfHw8wcHBopKDIAiCIFyjzo+Zq6urOXbsGFlZWeTm5pKfn09JSQmSJOHl5aXEyjqdTkkcMRgMSlzh4eGhjPW6E1Vqamqorq5WCkJYLBalmIS/v/9P4y4JrF17IydOhPDAA1pGjlQRF+c6JhFbCL/JPXC/ZQusWAEbN4LVCjExyJ9+Ct27U11dTWZmJkeOHCE7O5u8vDxqamrqFAtxJ0idHy+773W4iwi4E66qqqqw2WxKgQG73U5wcDBRUVHEx8fToUMHOnTogJeXl3KY4lwWBEG4/pwfZzkcDo4dO8bhw4fJysoiJyeH0tJSZfzGXYDGPSbp7e390z35Vuzfn0j37t/icLjuZVVXVysTUNxfVqsVLy8vIiMjad++PbGxsXTp0oXg4GDlGMS1SBB+QVkZHDkCmZnwww+uVdNCQ6FHD+jb15X84c4zudjPkfvz/zt+7s5vU86dO8ehQ4eU+LawsBCz2ay0J56enkpBEh8fHzw9PZUiek6nU7knbjKZlEkE7nsbFosFSZIICQmhXbt2tGvXji5duhAdHY2Hh4dyDKJNEYRrhkjoFYQ/mzuR4Pyv6upqcnJylGS4srIyzp07h/Gn2emenp4EBgbSrFkzgoKClK9mzZoRGhqqzC5Xq9VK4q77e/eXu/S++/vzZ/pdmDR74ZIfkiTV2e5eNuT8L0mS6n3vdDrrJPhKkoTD4cBoNFJaWkpxcTEVFRWUlZUpScqlpaUYjUYcDgdarZZmzZoRHBxMWFgYzZs3p02bNrRo0UKpyumu0qnT6ZRjlmVX5d0tW+CZZ+D48bor3rreM0yaBP/4h2uilsHwc0wnCMLPJEnCZDIpswSzsrI4dOgQJ0+epLCwEJvNRmBgIJGRkURFRREZGUmbNm2IiIhQOhruyQYXtlHutkZJJpEkVGYz0nlV69ztibstcbcn7okC7g5McXEx+fn55OXlUVRUREFBAaWlpQBERkbSqlUrEhMTiYuLIzg4GD8/P3x8fMQSR4IgCFcJu92uxIWZmZns3r2b7OxsKisrCQoKIiYmhnbt2hEbG0ubNm2UhMfzJ7D90vUFqBOnnn8tcVcmc8eox48fJzs7m6ysUg4cSKSqagXx8RoSE+Po2zeFtm3bEhQUpFTOEIRf47DbqSoupuzgQUoXLSJk7VrOBgbyaosWqJo1o23btsTGxiqDrHq9XkmsuXBi5q+d1+6+1/l9LvdKLbW1teTk5Cg3nk6cOEFVVRVhYWHExcWRnJxMfHw8gYGBBAQE/OErqAiCIAiC0DiSJCmJIDk5OezcuZOjR49SUFCAl5cXbdu2JTo6mri4OGJiYvD391fi5QuLPpw/LvzzeKqsvM6F8bI7rrBareTn53P8+HEOHapi3z5vqqu/JjxcRYcOsfTq1YtOnToRGhpKQEAAHh4eYsxF+HWShGw0Ys/IoGLOHOzp6ZT06cP8iAhyTp/GYDAQFxdHXFwcnTt3JjIy8hf7ghfGy7/UB3RP+DSbzWRnZ3P06FEOHz5Mbm4uDoeDuLg4evbsSe/evZX7MSJGFgRBaPokSaKqqoqSkhIOHjzId999x/Hjx3E4HERFRdGhQwcSEhKIjY3Fx8en3vjN+eOSoKKqCvz9G46vzo+tzpw5w5EjRzh06BDZ2dlUVFQQHh5Ot27d6N+/Py1btiQkJKTOfXBBEM4jSa7EEKMRMjJgwwZX9V6DwZXcO2QIREa6Ci3o9b+erFtTA3l5EBfnWsK5kdwTJcvKyigoKGDz5s1kZmZy+vRpgoODad++vTKZLCIiQmlPGuq3AQ3Gtxfe37Db7VRXV//UVzvE8ePHycnJwdPTk4SEBFJSUujUqRNhYWH4+vqKexuCcPUTCb2C8EdyLyN/5swZTp06RX5+Pvn5+eTm5lJVVaXccNVoNErCanh4OMHBwTRr1oyQkBCCg4Ovu0Ejk8lEWVkZpaWllJSUUFZWRklJCefOnePcuXNUVVUpSclqtZrQ0FAiIyN/qqbWCk/PVnz0USgffaTip3y+elQqGD7ctRquiFcEoS73MnaHDh1i//79ZGRkUFxcjCzLREREEBMTQ3R0NK1btyYqKopmzZpddQMJsixTVVWlJPnm5+dz4sQJzp49iyzLeHt7ExcXR0JCAp06daJ169ZX3XsQBEG4HlRWVrJz50527drFjz/+iNVqpVWrVnTp0oWYmBji4+MJDQ39U2NhWXZ92Ww2CgsLOHr0KMeOHePIkSNUVVVhMBhITEykV69e9OzZE71e/6cdm3BtqKmpYe/evXz//ff8+OOPGI1GIpo3p1/Hjgzy8MCzf3+adex4Rfp4drudoqIijh49SlZWFkePHqW0tBSdTkenTp3o0aMHvXv3xtfX908/NkEQBEEQ6nM4HBw5coTt27ezY8cOKisr8fX1pVOnTnTo0IH27dv/NB765y+rKssyxcXFHDt2TLlxXFxcjFqtJioqij59+pCcnExISIgYcxEaZDab2bt3L+vWrePIoUO0kyTubtWKwl69iO7WjXbt2tVbeeuPYjKZyMrKIjMzkx9//JGcnBx0Oh3dunWjb9++9OjRQyRTCYIgNEGSJHHs2DG2bt3Kd999R2VlJS1atKBXr15KEq+/v/+fcixOp5Pc3FyOHj3KwYMHOXz4MDabjejoaFJSUhg4cCCBgYF/yrEIwjWtvBz27XNV7v3xR1eiblQU9OzpSvJt377hhN2vv4ann4bHH4d773Ut+XwJZFmmvLyc3bt3s2HDBk6cOKHEkx07dlQmqGm12t/nff7GsVRWVpKVlcWPP/7I/v37KSkpwdfXlx49ejB48GDi4uKuqxwkQbjGiIReQbhc7s+Je0lTk8lEbm4u+/bt49ChQ+Tm5mK1WgkMDKRVq1bKEk7NmzfH29sbg8GAXq/H29v7igy8XkskScJisVBbW4vZbFaqhrorqeXn51NQYKC6ejInT7bGZHLicDjRaFRoNB6AFknSIMsqJElFu3awdi20bn2l35kgXFnumYJVVVVkZGSwatUqjh49ire3N507dyYpKYk2bdrg7+9PUFAQBoPhmmurZFnGZrNRVVVFRUUFp06dYseOHfzwww9UVlYSFxfHDTfcQP/+/fH390ev14vqvYIgCH8A92oVp06dYunSpezYsQODwUBKSgr9+/cnLCyMkJAQpR2+WsiyjNFopLy8nJMnT7J27Vr27duHv78/N910E8OHDycoKEjc4L1OybKM2Wzm3LlzrFixgs2bNwOQkpJCv379iIyMpFmzZsrqAEjSVTGrUJZlTCYTpaWlFBYWsnbtWnbv3o1Wq2Xo0KGMHDmS8PBw0U8VBEEQhD+Ru0BEWVkZGzdu5KuvvqK6uppOnToxbNgwWrduTbNmzfD397+qqiq5x10qKiooKipi+/btbN68mcrKSvr06cPdd99Nq1at8Pb2FnHFdcy9skRVVRXffPMNX375JXa7ndTUVKUKYVBgIB5aLaormFxgtVopKSnh1KlTfPXVV+zZs4fw8HDGjRtHUlLSVff5EwRBEC6NJEnU1tZy8OBBPv30U7Kzs0lISGDEiBG0bduWkJCQKxqzuCtwVlRUUFxczNatW1m3bh1Wq5WbbrqJtLQ0QkJCxGoIgvBbJAkqKqCkxFW19/vv4ehRCAiA5GS46SZX9V6DAXQ6ePBBeP991/bRo11LQbdq9ZvjuDabjTNnzvD111/z9ddf4+fnx4033kjv3r0JCwu74sX7zh+7Pnr0KGvWrCEjI4O4uDjuu+8+EhISMBgMIr4VhKuLSOgVhMaSJElZ4j0rK4uMjAwKCwupqKjAYDAos/bi4+Np164dfn5+AHUCaxFkX77z2ylZlrFaneTklHLoUAEnTpwlJ6eUM2eMVFdDdTVYrTo8PcNo1qwN7dpFM3lyAB07XsE3IAhXkLuSyq5du9i0aRPHjx/Hz8+PQYMG0b9/f2JiYurMEmwqbdb57YYkSZw6dYrNmzezY8cOzpw5Q0REBH379qVPnz60bt36T5kpKQiCcD2orq5m8+bNfPXVV5w+fZrevXtzyy230LVrV2VA61q41rivIyaTiS1btrB69Wry8/Pp0KEDN998M0lJSXhd4ux94dpVW1vLrl27WLFiBSdOnKBr166MGDGCnj171qkmdrWf2+7z2mazsXPnTlatWsWxY8do164dQ4cOpX///vj4+FzhoxQEQRCEps1ut7Nv3z7S09P54YcfiIiIYOTIkQwaNEi5Dl/tMQX8HFc4HA6OHj3KqlWr2LNnDwEBAQwfPpz+/fsTGhp6TbwX4fcjyzL5+fmsXLmSTZs2ERYWRlpaGqmpqUr/6Wo7J9znclVVFd9++y0rV65EkiTS0tIYMmSIqD4tCIJwjXFP2N+4cSNffPEFlZWVDBs2jNtvv53Q0FDg6r0WOZ1Odu7cyfLly8nOzqZPnz6MGjWKhISEq+6YBeGq474vLMuuhJGdO2HrVlf1XpUKOnSAbt3gn/+Ekyddj1WrITERZsyAoUPB07Pebh0OB1lZWaxYsYKdO3cSGxvLuHHjSExMxOOnCsBX0+fT3Z7IssyZM2f48ssvWbNmDUFBQYwaNYohQ4bg7e19hY9SEISfiIReQbgYsiwrs8eLiorYuHEje/bsITc3F4PBQOvWrenSpQtRUVGEh4cTGhpKUFDQVXWBvh65/8/Ky8spLi7m9OnTHDlyhAMHDlBUVIS3tzeJiYkMGDCApKQk9Ho9Go1G/L8JTZp7Zm9BQQFLly7l+++/JyAggNTUVLp166ZU4r0ePwdWq5W8vDwyMjJYu3YteXl5dO/enXvvvZfY2FjRPgiCIDSCu8LY+vXr+eSTT5AkieHDh5OcnEx0dHSTWNLJarVy7Ngx1q9fz5o1a4iLi+Ohhx6iQ4cOqNVqce1ogtz9jF27dvF///d/VFdXc8stt9CnTx9iY2OVAdtrmd1uJzc3l/Xr1/PNN98QERHBAw88QI8ePdBqteK8FgRBEITfkdPp5Pjx47z//vtkZmbSr18/hg0bRnx8fJOoaCtJEkVFRezZs4fFixdjt9u55557GD58uKgsdx1wVwT76quv+Pjjj2nbti1/+ctf6Nmz5zU1YUyWZcrKyvjhhx/48MMPsdvtTJo0iX79+okxQ0EQhKuc+75YZmYmc+bMoaKigrvuuouBAwcSFhZ2TVWltFgsZGZmsnLlSvbt20daWhqjR48mICBAXIsE4VJIEpw5A3l5sH8/bNoEGzZATU3dx7VsCRMnwiOPgL8/qFTIskxNTQ3vvvsuq1evJikpidtvv5327dtfUyudybJMYWEhW7ZsYcWKFYSFhfHoo4/SsWPHJnHfRhCucSKhVxB+jbt6ZW5uLjt37mT37t2UlpYSGxtL7969SUlJoXnz5mi1WuWm5rVygb4euTtsDodD6fDs2LGDXbt2YTQaiY2NZeDAgcTHxxMdHY3BYLjShywIvyubzUZGRgarVq1i+/btdO/enbFjxxIbG6ssES7asJ+XiSwoKOCLL75g/fr1xMTEMGbMGLp06XJN3WwQBEG4khwOB/v27WPRokUUFRVx7733MmTIkCa5fJM7ziwrK+OTTz5h9erVDBo0iLvuuotWrVo1ufd7PZMkiUOHDvHxxx9z6NAhxo4dy80339wkl911n9c1NTUsXbqUzz//nG7dunHvvffSrl07MbArCIIgCJdJkiTOnDnD0qVLSU9PZ/Dgwdx///0EBwc3yQRBWZapra1lx44dLFy4ED8/P+677z569+4tVkdqohwOB8ePH2fOnDmUl5czefJkkpOTr+lEbvd5vHHjRt555x26du3KhAkTaN269TX7ngRBEJq6kpISPvzwQ9asWcPdd9/N7bffjq+v7zV7T0yWZeUaO2vWLEwmE1OmTKF79+5NYpK5IPypZBnsdnjpJXj5ZXA66z9Gq3VV6f33v3G0b8/WHTt45513CA4OZvLkycqKt9diewKufqnRaOSjjz7iyy+/JC0tjTvuuINmzZpds+9JEJoAkdArCOdzn/OSJHH8+HHWrFnDd999hyzLdO7cmR49etCpUyeioqKa3M3a65nJZOLIkSNkZmaya9cuTp06RcuWLRk6dCiDBw/G398fuLqWRBCESyHLMkVFRXzwwQds376dlJQURo0aRfv27cUNk98gyzInT55k7dq1rF69mrZt2/LII48QGxsLiHZBEAShIbIsY7Va+fTTT1m6dClDhw5l7NixhIeHX+lD+1NIksThw4d59913ycvL46mnnqJfv36AuG5cy9zVptPT01m4cCFJSUncc889REdHX+lD+1NIkkRubi6LFi1i7969PPjgg4wcOfKavfklCIIgCFeaLMvs3r2b2bNnEx4ezgMPPECnTp2ui3EaWZYpKSlh2bJlrFq1ilGjRjFmzBglsUZoGiRJYs2aNcybN4/Bgwczbtw4QkNDm8z/sSzLZGdn8/bbb3Pq1CleeOEFOnXqBIh+nyAIwtVClmVycnJ4+eWXAXjkkUdITExsMhOUZVmmsrKSL7/8ksWLFzNu3DhGjx6Np6fnlT40Qbi2lJXBhAnwxRe/+BBZrYa4OH5ITWV6djZpo0dz1113NakiUE6nk4MHDzJ37lw8PDz417/+RUREhIhtBeHKEAm9guAmyzIVFRUcPHiQJUuWcOLECbp27cro0aOJiYnB19cXnU53pQ9T+APJsozJZKKyspJNmzbxzTffUFZWxo033sjw4cNp06aN6AQJ1xyz2cz69euZP38+nTt3ZtKkSbRo0eKaroRxJTidTk6fPs2nn37Kxo0bGTNmDGlpafj5+Ym/oyAIwnlkWebs2bPMnj2bgoIC/vnPf9KhQ4dreoZ6Y7jjynXr1vHWW2+RlpbGuHHjxAoQ17DKykrmzp3Lrl27eO655+jZs6eywsH1wp2s/9133zFnzhz69+/PQw89hL+//3X1dxAEQRCEy+G+nn7++ef873//45577mHkyJHXZTKrw+EgOzubF198EX9/f1588UWaN29+3f0dmiKr1cqKFSv48MMPmTx5MkOGDGmS4+qyLGM2m/nss89YsmQJzzzzDIMGDRLFYARBEK4Csixz5MgRpk6dSkpKCo8++miTHb9wOBz88MMPzJw5k4EDB/LII4+IMUhBuFiyDCdPwl//CmfPgkbz85dWC3o9+PpSq9GwNzub6sBA2r/4Im1uuaVJTsZ0T75855132L9/P6+88gqxsbEivhWEP59I6BUEWZYxGo1s2LCBzz//HIvFwtChQ7n11lvFAOJ1zm63c+DAAZYvX87hw4fp1q0baWlpdO7cucnM3hSaLlmWKS0t5a233mLfvn1MmjSJgQMHiokJl0mWZfbs2cPrr79OSEgI06ZNo2XLX4ylBEEQrjtFRUVMnz4dT09P/vnPfzapCkyNIcsyBw4cYMaMGaSkpDB58mS8vLyu9GEJl6i0tJTZs2dz9uxZXnjhBaKjo6/r8xogJyeH5557jsjISF544QV8fX2v9CEJgiAIwjXB4XAwf/58Nm7cyPPPP09ycvKVPqQrrqSkhDlz5pCfn8+LL75I27Ztr/tY61rmcDhYvHgxn332Gf/617/o0aPHlT6kP5zD4eCrr77inXfeYfr06aSkpIhzWBAE4QpyJ/NOmzaNESNGMHbsWPR6/ZU+rD/ciRMnmDZtGn369OGhhx7C29v7Sh+SIFz9ZBlMJjh+HLy9XQm8ej34+IBOB2o1FouFefPmsXfvXl5++eXrYmzYbrezYMECtm7dyssvv0xcXFyTf8+CcJURCb3C9UuWZRwOBydOnOCVV16hurqae+65h+TkZEJCQi47YVOWZWw2G7W1tXh4eODt7Y1KpcJms+FwOOoE0WazmdraWuVntVqNv7//RR2DJEmYTCasViseHh74+Pg0OEPGZrNhMplwOByo1WoMBgOenp6oVCplJrnZbEalUtXZ5n4vTqcTs9mMj49PnYu1JEnU1tZis9nqPff8bQDe3t6Xvc1qtSp/Ky8vL/R6PSqVCovFQm1tLRe2W0FBQZc1Y8hdNSMvL4/ly5ezdetWbrvtNsaOHYufn5+YjSRclWRZpqqqimnTpiFJEk899RQxMTGNCrTPbx+8vLyUWb0WiwVAGQSRZZna2lrl9wAajYaAgICLel2n00lNTQ0OhwNPT0+lzWzoeJxOJ7W1tdjtdtRqNb6+vmi1WqxWKyaTCUmS0Gq1GAwGpRKxxWKhpqZG2Y9KpSIgIKBRbb0sy5w5c4a33nqL3NxcXnzxRdq1ayc6MoIgXNdkWaa8vJwZM2bg5eXFtGnTCAwMvKS2UZZl7HY7tbW1aDQaJe602+3YbLYGl69yXxdMJhPe3t4XHT+bzWYsFgtarVaJny88VrvdjtFoRJIk5Xc+Pj6XnJArSRInT57kmWeeYdiwYYwfP15Uyr9GuOOb2bNnc/r0aWbOnHnJSerufuf5fRiz2YzT6azXL7PZbBiNRqVPo1KpLnqlmPNjNo1Gg7e3d4OVsR0OB0ajEafTqfzOYDBccuUWWZYpKChg+vTpxMTE8OSTT+Ll5SXOa0EQBEH4FQ6Hg2XLlrFkyRJmzJhBly5dLnls0R2fWK1WDAYDDodDGUO9cGz4/DHWXxs3/qVjrampwel0otfrlTHYC4/FZDJhNpuV36nV6kvuBwBUV1czZ84ccnJymD17NiEhIZf0fOHqIMsye/fu5bnnnmPatGkMHDjwks5x91i8yWRCp9Mp91CsViuSJF1SzHr++OGvnf9WqxWj0aj8rFKp8PPzw8PD46JfC1z3X1atWsWiRYuYPXu2SHoQBEG4QmRZ5ty5czz11FN0796diRMnNmosr6amBrvdjre3NxaLBYfDoWzX6/UXlSzrHut035u68P77+Y8zGo1KTAeuuM7f3/+Sjhvg8OHDTJs2jfHjx3PbbbeJ+9iCcJmcTidLlixh2bJlzJ07l9atW19SjHd+e+Ln56fk9kiS9Kv3wy90YXvi7e3d4Opxv1d74u7rvfnmm2RnZ/PWW2+JSQKC8OcSCb3C9au6upr33nuPNWvWMGrUKO6+++7fdakNo9HI22+/zZEjRwgLC+Ppp5+moqKCDz74gNraWubOnas89u2332by5MlKskB4eDi7du36zaqPkiTxww8/8O6772K327FYLDzwwAPccMMN9d7HF198wbJly5QbyBEREUyZMoUWLVqQn5/PzJkzMRqNqFQqWrRowZQpUwgPDwdcFak+/vhjNm3axMqVK+sMZm3cuJElS5YgSRLV1dUMHz6cv/3tb2g0mga3jR07Fq1Wy6ZNm1i8eDGSJGE0GrnpppsYN24cWq2WzZs38+mnn9bbZjQaefPNNzl58iQ6nQ5PT0+mTJlCu3bt+PDDD3nsscfqJOyFhoZy8OBBwsLCLvv/U5ZlZFkmKyuLN954g6qqKiZPnkzfvn3FwJxw1SktLeX555/Hx8eHf/zjHwQFBTX6PC0uLmbWrFmcOXOGnj17MnHiRI4fP868efPo2rUrkyZNAlwdmscff5y33npLeW5iYiJ79uz5zSVHHA4Hq1evZvny5UpS/7Rp00hISGjwsZ9++inbtm1TBmaeffZZevfuzbx589i1axeenp6YTCYSExOZPHkyvr6+/O9//2PixInKoEtYWBjbtm2jXbt2jfq7uDtOs2bNIiMjgzlz5tCiRYtG7UsQBKEpcDgczJ49m2PHjjF37txGDTibzWY++OAD9u7di4+PD88++yx2u50PP/yQEydO8OGHH9Z7jizLrFq1infeeYeFCxf+ZvwsyzKHDx/mv//9L2azGavVyh133MFf/vKXetfKXbt2MWbMGPLz8wHXINn8+fO55557Lvm9uePIxx9/nMcff5wbb7xRxJDXAFmWWbRoEd988w1z586lRYsWl/z/5nA4+Oyzz9i0aROSJNGxY0f27dun9Mvcfa+IiAg2bNjAmDFjKCsrA8Df35+PP/6YW2655Tdf59SpU8yaNYuqqirsdjupqalK8vj5jh49ytixYzl48CAAOp2O6dOnM23atEt6X+D6+xQXF/PQQw9x2223MW7cOLGSiSAIgiD8AlmW2bJlCy+//DKzZs0iMTGxUfFgQUEBM2fOpLy8nNTUVPbu3YvdbgegtraWCRMmcNNNNyFJEjt37uSDDz7A4XBgsViYOHEiqampv/kaNpuNZcuWsXr1ajQaDQaDgWeeeYY2bdrUe08zZszgpZdeUn4XHR3N/v37L7l6vyzLVFZWMn36dHx9fZkxY0aTXMK2qTtz5gwPPfQQf/vb30hLS7vkJKKysjLmzZtHTk4OMTExPPHEExQWFvL2228THBzM9OnTL2o/TqeTLVu28MknnyBJEjabjSeeeIJevXrVe+zKlSsZN26ckpgeHBxMeno6PXv2vKRjB9dn55VXXqG4uJjXXnvtuqgGKQiCcLWRZZlXX32V/Px8Xn755Ubd+9+/fz9z5szBaDRy2223sXDhQnbv3g2AVqvl6aefrhP//BKz2czcuXPJzMxEpVLRunVrHnvssXoTl0wmE/fddx/Lly9XfjdkyBDWrFlzSccNrve/efNmZs6cybvvvkt0dPQl70MQBBdZlsnMzGTq1KnMmDGDpKSkS25P9u3bx9y5czEajdx///0cPHiQzMxMpeDHs88+S3x8/G/ux2QyMWfOHA4fPoxKpSI6OprJkyfTrFmzOo+rra1l/PjxfP7558rvbrzxRtLT0y/puMH1/qurq3nqqaeIi4vjscceu+RJb4IgNNqvJvSK0RKhSXJXMZg1axYnT55kxowZ9OrV63e/8ZiTk8O2bduYP38+KpWKsrIyli9fzq5du2jbtm2dx3p6evLCCy++nwTcAAAgAElEQVQQFxcHuKo2BQcH1ztucFUK27lzJzqdji5durBgwQJ69eqlXJhff/11evbsSUBAQJ3nV1RU8Pjjj9O1a1cKCwu54447SExM5M477+SDDz6gurqaBQsWKEnB33zzDePHj6e6upolS5awe/duSkpK6uwzNzeX1157jalTp5KSkkJ5eTlWqxWVSkVeXl6D29RqNXl5ecyePZunnnqKvn371ts2a9asBrdt2bKFtWvXsnLlSry8vHj44YdZuXIlTz75JBqNhpdeeklJQs7Pz6e0tLTBSm6NoVKpUKlUxMfH89prr7Fs2TL+/e9/88wzz1xypQFB+CM5HA6WLl1KTU0NL730Ur225FJt376d06dPs2DBAmpqasjMzGTt2rXs37+fjh071nls8+bNee2115TE1oCAgHqfDXdyvNlsZuPGjbRv3x5PT0/eeustnnrqKZKTk3njjTeYM2cOc+bMqTfbb9++fcrnr2PHjuTn5yvtXXV1Na+88grNmzdn+/btPPLIIwwbNozu3buj1WrrdIq8vLyU9qIxVCoVOp2Ov//977z44ovMnz+ff/3rXxdVQU8QBKEpys7OZtOmTcyaNQs/P79G7ePcuXOsWbOGmTNn4ufnh8ViYenSpezatavB9tWdTPjZZ59RVVVVb6UG92McDgf79u3DZDIxYMAAFi5cSEREBE8++STr1q1j3rx59O/fv95guizL3HHHHXTr1g2VSoVWq6Vbt26Nem8qlYrY2FjGjBnD+++/z4ABAy65Iqrw5zt9+jRLlizh+eefb1QyL7hu3qxYsYJJkyYRExPDF198wRNPPEGXLl04deqU0i8bO3YsAPfffz9du3YFXNUT3N+fz12Z+siRI+Tl5XHrrbfy8ccfI8sy8+bN48CBA7zwwgukpqYSExNT77mDBw/mySefxMPDA7Va3eAkqouhUqkIDQ1l4sSJzJ8/n5tuuumy4itBEARBaMqMRiOLFi0iLS2Nzp07N3py17fffotGo+Htt9/mzJkzlJeXM2nSJLRaLa+//jqvvfYa/fv3R5IkFixYQGpqKn/961/57LPPeP311+nWrVudyXfucZqqqio2bNhA//79KSoq4r333mPBggVERUUxbdo0PvjgA55//nk8PT3rHE9AQAAvv/wyrVu3BlyT4C61Ch644orAwECmTJnCAw88wM6dO0UhhWuM0+lk1apVNGvWjFtvvbVR4+UZGRlkZGSwcOFCLBYLeXl5fPnll+zZs4fBgwc3+Bx3P9Bms7F582aaN29OixYtWLBgAXfeeSe33nor77//Pq+99hrvv/9+vWRzlUrFE088QadOnQDXvZoL799cLA8PD/72t7/x6KOPkpGRQXJycqP2IwiCIDReTk4O69at480332x0Ia8lS5aQmJjImDFjKCgooF+/fjz88MNKdd327dvXe44sy0iSxOnTp9m+fTtpaWls2bKFTZs2sWjRImRZ5uGHH2bNmjX89a9/rXedjImJYf78+UpyXmOLValUKvr160dSUhL/+9//mD59upgkJQiNJMsyS5cuJTk5ma5duzaqPVm8eDFdu3blzjvvZPXq1Xz77be8++67REVF8cILL7BgwQJmz55dZyLYL7UnW7duZdGiRTidTiZOnMi6deu466676rUnsbGxddqTxo7XqlQq/P39eeyxx5gyZQo333wz8fHxoo8mCFcBcWUXmiSz2czrr79OYWEh//3vfy+rcuUvMRqN7N69m9OnT3Pw4EG6dOlC27ZtefLJJzEajVRUVNR5vFarJTU1lb59+za4P0mSKCsr4+DBg3z33Xe0bt2atLQ0Kioq+PHHH5k0aRIGg4Ebb7yRuXPnsmfPHoYOHVpnH+7KuGq1mrCwMAIDA6mqqqKqqoqMjAwGDRpEUFAQTqeT/v37s3HjRsaMGYO/vz8PPPAAQUFBLFy4UNmfLMukp6fj4+OjJLQ2b968zjZvb+9f3GYwGEhNTa23bfXq1ej1+nrbwHVD3c/Pj4iICJxOJ9HR0RQUFOB0OrnzzjvRaDSo1WokSWLZsmV07dr1d0+UUKlUBAQEcP/99xMdHc2rr76KTqcjJSVFBC/CVeHEiRN88cUXzJ49u96svEshyzIlJSXs2LGDsrIyMjIy6NixI127dqVz587s37+/3nP8/PwYNGgQHTp0aHCfkiRRWFjI/v372bVrFykpKURGRrJz505qampISEjA29ubv/zlL4wdO5aTJ0/SuXPnOsf04Ycf0q1bN7p06YJKpapTYXfq1KnKgErLli3x9PRUlrfWaDQMHDiQAQMGNPpv0hA/Pz+ef/55xo8fT3p6OrfddptoCwRBuO44HA7efvtthg8f3uhKY7W1tezdu5e8vDwyMzPp0aMH7dq147HHHkOtVrNnz54Gn7N06VJuvPHGOnEquK4ZFRUVZGZmsnXrVoKDg7n77rupra1l+/btvPrqq0qs+uabb7Jt2zbS0tLqvUbHjh254447fpfJWxqNhrS0NNatW8eqVau48847L3ufwh/H6XTy4Ycf0qNHj0Ynk5jNZjIyMjh27BjHjh0jJCSERx55ROmXhYeHExgYSHV1tZKI0L17d9LS0hp8PXdVhKysLDZv3oxarWbs2LHYbDbWrFnDo48+ir+/Pz169CAkJIS1a9fWS+gFaNu2LWlpaY1KtrmQWq0mNTWVtWvXsmzZMiZPnnzZ+xQEQRCEpmjv3r1KlbfGxBWyLFNYWMiOHTuwWq0cOnSIbt26MXXqVGWp1ejoaNLT07Hb7VRWVnL06FGmTp2KXq/nlltuYf78+ezbt49BgwYBrngnNzeX/fv3s2/fPoYNG0ZAQACrVq3C19eX6OhovLy8GDlyJC+99BIPPvhgvRUx9Ho9AwYMaHASUmNERUUxbtw4PvroI7p27fq7FWsQ/nilpaWsXbuWJ554ol7i98WoqKhg165dFBcXc+DAATp27Eh8fDwxMTHk5eU1+BxJkjh79iwHDhxg+/btdOnShb59+5KTk8OpU6fo2rUrer2ekSNH8t5773Ho0CF69+5dZx8qlYqUlBRuvPHGxrztevtq3bo1o0aN4n//+x89e/YUK1gIgiD8iSRJYsmSJfTr149OnTo1apWl3Nxc9uzZQ8+ePcnOziY8PJxWrVoxatSoBuMSWZax2WxkZ2eze/ducnNzGTVqFCqVinXr1tGpUyeaN2+O0+mkb9++fPvtt9xxxx31xmSaNWvGzTffrEySuhweHh5MnDiRCRMmkJWVVa84jyAIF6egoIAdO3bw7rvvXnJBJ3d78sMPP6DRaDh+/Di5ublER0fTqlUrfHx8uO2223j66acpLCwkJiYGWZaxWq2cOHGCXbt2kZeXp6wsuHbtWjp37kx4eDhOp5OUlBS+/fZb0tLS6sXeISEh3HLLLbRq1ep3+TvExsbSpUsX1q9fT1xcnIhvBeEqIBJ6hSZHlmUOHjzInj17eOONN/6QZF5wlbzPz8/HaDRy+PBhwsLCaNOmDXq9vsFkAPdSwqtWrSIoKIiUlBSSkpLQarWYTCa++eYbCgoKaNGiBQ888ACRkZGo1WqOHTuGRqPB29sblUpFs2bNUKlUFBYW1nuN84MMq9WK0WhUKmPq9XplSSmNRkOLFi1IT0/H6XSiVqvR6/X1LswOh4MTJ05QVVXF66+/Tnl5OdHR0YwYMYKgoCBOnDhBdXU1b7zxBmVlZb+6rU2bNowYMYLg4OBf3BYWFkZiYiJLlizh2LFj+Pn5kZWVxfDhw/Hw8KhzfJWVlfz4448888wzf1hinUajYcCAAWRlZfF///d/9OzZs1EDlYLwe5JlmZUrV9K7d286dux42ed/VVWVUu0lIyODli1bEhoailarbXDfZWVlLFiwAB8fH8LDw7nhhhuUgYJz586Rnp5OZWUlbdq04amnnlKqBxcUFODj46Ms0xEeHk51dTXl5eV19m82mzl27BgtW7bklVdewWg00rlzZ0aMGIFer1cGQNzLNHp6eio3mhwOB5988gnffvstgYGB9O7dmz59+lz20iAqlYqgoCBGjx7NmjVrGDJkiLjZJAjCdaegoICsrCymTJnS6MRXq9VKXl4eNTU1HD16lPDwcOLi4hqMQ8HV1u/Zs4egoKA6A1PuQa+1a9dy7NgxwsLCGDt2LK1bt1biZ6fTqVToCAgIwMvL6xdvEG/bto3Dhw/j6elJ586dGTJkSKMrEAP4+PgwfPhw1q9fz2233Sbix6tYaWkp+/fvZ9q0aY0+r202G7m5udTW1pKdnU3z5s1JTExUtlssFoxGI3FxccprrFmzhr1796LX6+nRowcDBw7E29sbu93Otm3b2Lt3L0FBQYwcOZLY2Fg0Gg2FhYXU1tYq/Vtvb2/8/f05efJkg8d18OBBTp48iU6nIzY2lltvvZXAwMBGvUdwrXwwfPhwFixYwIQJE8TSwoIgCIJwAXeBgwEDBhAaGtrohN7S0lJKSkqwWCxkZGTQoUMHJTaVJImcnBwSEhLw8/NTlnE1GAzKuLEsy5w+fRpZlsnPz2f16tXYbDbatWvH888/j6+vL3a7ncLCQgIDA5X4pHnz5pSUlCiTps9nNBpZuHAh/v7+hIaGMmDAALp163ZZE+L69+/PsmXLKCwsbLACnnD1kWWZs2fPIssybdu2bdQ5bjQaOXXqFFVVVWRmZhIeHk5kZKQyGe7C16usrOSbb77h3LlzREVF8fe//12pPnbq1Cm8vLzw8vJSVpWwWq0UFxc3eOwrVqxg8+bN+Pn5kZSURN++fRs9+U2lUjFs2DAWL15MUVFRvSR4QRAE4Y9TXl5+WWM5kiRRVFREVVUVp06dIjMzk9DQUA4fPsyMGTPw9PQkOjqakSNHEhwcjNPpJCsri7Vr16LT6ejcuTN/+9vf0Ol0VFdXc/bsWaU4jUajITw8nPz8fJxOZ73XPn36NG+++SYGg4HmzZtzyy23EB0d3ej7fCEhIbRs2ZKsrCwSEhJEIRpBaITvvvuOtm3bNuqz6K6wW1lZSUFBAZmZmfj4+GC1WpVVUqKioigvL6e6uhqn08nRo0dZt24dOp2OxMRExo0bh06no6qqirNnz9KjRw+lPQkLCyM9PR1Jkuq9dmFhIW+88YbSngwfPpw2bdo0uh3w8PCgX79+LF26FJvNJsZ+BeEqIBJ6hSZp1apV3HDDDbRr1+4PC17DwsIYNmwYO3bs4KGHHqq3fO+FBg8eTHx8PAEBAezevZsnn3yS//znPwwaNIjZs2djsVj461//Svv27eskn5lMJtRqtZLk4L6Au5NzG2Kz2Vi+fDmpqamkpKSg1+u56aab+OSTT0hKSsLPz4+DBw9is9kaXLbYzW63U1tbi06no0+fPuj1eubNm8ehQ4d48cUXqa2txcPDg969e9fZNn369Hrb/vvf//7i8/773/+SmZnJrFmz6Ny5Mz179uS+++5Dp9MRFBTEoEGD6nTKJEli5cqV9O3bt87ycX8EDw8P0tLSSE9P59ixY3UqiQrCleBwONi5cydTp079XRJVY2JilKoVkydP/tUZd2q1mttvv53a2lr0ej3p6ek8+OCDfPTRR7Rq1YrnnnuOuLg40tLSlKQqcH1mTSZTnSRhjUajzGo+n9lsxmq14ufnx+DBg6mtrWXWrFlUVlby0EMPKY+zWCysXLmScePG0bJlS1QqFQMHDqRt27YEBQWxb98+nn76aV544QVuvvnm3+Va0KNHD7744gvKy8tFQq8gCNedvLw8goODG70UHEBQUBA333wzn3/+OePHj//NJU7PnTvHtm3b+Pvf/87x48eV38uyzDvvvENOTg7jx4+nQ4cOdZJmTSaTEjOD6/rlnkR3obi4OO69914CAwMpKSnh1VdfJTMzk2nTpl1WZdP+/fvzwQcfUFJSQmRkZKP3I/yxzp07h0qlIioqqtH78Pf3Z/jw4cybN4+77rqrzpK7NpuNZcuWMXjwYPr06YNKpSIxMRG9Xk9QUBAFBQW88sorZGdn8+ijj7Js2TI2btzIxIkTSUhIUJJzwBUjSZKkxH9qtRoPD48Gk25atmzJPffcg4+PD0ajkXnz5rF7927+85//XFb/KTk5mZdeekmpKCEIgiAIws+cTieHDx9m9OjRjR6DUKvVyqpJkiTx2GOPKdtkWebw4cMcO3aM5557DrVaXW/cWK1Wo1arMZvNVFZW8uyzz5KamsqIESNo3ry5Mk4jyzImkwkPDw9UKhUqlQqtVovD4cDhcNQ7rhEjRlBeXo6vry8bNmzg4YcfZuHChXTr1q1R79M96S4gIIBz584RFxcnElCuEdnZ2URERBAUFNSo50dFRZGamkpBQQGPPvror668J0kSM2bMUCbZx8TEKOe6LMvU1tYqq/mBa6xRpVJhsVjq7SspKYnQ0FCCgoI4evQo06dP5+GHH2bMmDGNTkyPiIggMDCQnJwckdArCILwJyopKUGSpEZXpdTpdAwYMIDWrVszZMgQHnjgAWpraxk3bhwGgwGTycQ777zD9u3bmT17NqdOneI///kPY8eOpU+fPnUKiTkcDqxWqzJWo1Kp8PDwwGKx1Lv/7unpyZgxY3A6nWg0GlasWMGDDz7IokWLGn0d0el0JCQkkJ2djdPpRKsVqT+CcCncfazu3bs3KibU6XQMHDiQVq1aMXToUMaPH8/evXtZvXo133zzDQkJCRw4cEDpZ/3444+88sorjBs3juTk5AbbE3cBP3d7Yjabf7E9kSQJtVpdpz1p7L0I9xh5WVkZdrtdJPQKwlXg8tcUFYSrUE5ODh06dLiqSsG3bt2aPn360KFDB8aMGUOXLl1Yvnw5arWaqVOn0r17d9auXcvSpUspKChQZtp4e3vjdDqVmXySJOF0On9xsMtms/H1119z7tw5nn32Wby9vVGr1dx9991MmjSJzZs3s3r1ampqaupUYWiIVqvF09OTqKgo+vTpQ9euXUlLS2P9+vVYrVa8vLzqbLv99ttZv349NputwW0bNmzAarXW2+ftt9/Oxo0bMRqNLF26lKKiIlauXMnnn39OdHQ08+bNqzMQl5+fz+HDh0lNTf1TBnubN29OZGQkWVlZf/hrCcJvqaqqoqam5ndbQuNSqFQqEhIS6NWrF506deLRRx9Fp9OxevVqPDw8mDlzJiEhIXz11Vd8+eWXlJaWIsuyUkXObrcrnQ6Hw4FKpaq3fImnpyc6nY4OHTrQq1cvBg4cSL9+/fjyyy+Vx1RXV/PJJ58QGRnJfffdpwyWREVFkZKSQnx8PKNHjyYpKYlly5b9bu/dXSm9oRsDgiAITV1VVRX+/v6XVYXrUtTW1vLRRx8xatSoejeL1Wo1Dz/8MDfccAMbN25k8eLFnDx5sk78LMuykozgdDqx2+14e3vXex33yhkdOnSgf//+TJgwga+++orKysrLOn5fX180Gg3V1dWXtR/hj2UymdDpdJc9SaohVquVr7/+mtLSUv7xj38o519ISIgSrwwZMoTRo0ezYsUKLBYLo0ePZuzYsWzdupVPPvmEo0ePKv1A90owdrsdcPULbTZbg5OMfH19SU5OpmPHjvTu3ZspU6awYcMGCgoKLus9GQwGDAYDZWVll7UfQRAEQWiKqqursVgsSvXQ31tBQQHLli1jwoQJxMfHA/XHjd3fGwwGAgICePnll5EkiRUrVpCeno7RaARcYxwGg0Ep9iDLMna7Ha1WWy8RRKVSERsbS3JyMgkJCUyYMIGIiIg64zSNodPpCAgIoKSk5LL2I/y5zp07R0BAwCUvR9wYarWa6dOnEx0dTXp6OitWrODMmTPK2KKPjw8Oh0PpBzqdTmRZbnBiZkREhBKDjxgxgiFDhrB06dIGq51dLHdi+uX2HQVBEIRL4x7L+T2TV729vUlKSqJTp04kJSXx9NNPs23bNrKzs+nYsSMvvPACJ0+eZPHixWzdulUpVKPVavHy8sJqtQIoRWzc1ePPp9Fo6NKlC927d6dLly5MnTqV0tJStm3b1ujjVqvVhIaGKknOgiBcGlmWKSsrIzQ09HfZn0qlolu3brz22mvk5uaycuVKioqKMBgM6PV6OnfuzD//+U+ys7NZvHgx27ZtU9oTDw8PPD0967Uner2+Xnui1Wrp2rUr3bt3p2vXrkydOpXi4mK+++67yzp+Pz8/LBZLg5M8BUH484lpOkKT5OXlRU1NjZJIdjUwm81KAO/h4YFer1cGe7y9vbn99tspKysjIyOD9957j1atWpGWlkZkZCSSJCnvp6SkBFmW683Wcw+8fv311xQXF/PII4/g6+urbPfw8GDEiBGMGDECu93OjBkz8PHx+dWb1x4eHrRs2ZIdO3Yof0udTqdUg4qMjOT777//xW3fffedss3Dw0OpjtayZUu2bNlSZ5tKpcJsNrNnzx4SEhKU6m8DBgzg3//+N2azGb1ej9PpZMOGDSQnJ19W1bRLYbfbMZlMDSaBCMKfzf1Z+rUq3X8UWZaxWCzKrDy9Xo9Wq8VqtaJSqQgLC2PcuHGcPn2aAwf+n737Do+q2h4+/p2ZJJNeSC8EDJCEFggdRQUkAiIgCKjYsBdQUbkX/V0LouBVEQQbVxRURC4iKEVKUFAp0kIPLTQhhJCEJKRNpp73j/3OmAh6KYG09XmeeShph2Fmn73XXnut7UyaNImuXbvSq1cvYmNjKSkpcS1MsrKyCAgIICQkpNLP8Pb2JioqihMnTrgC9Eaj0RWMKCkpYc6cOQQEBDBo0KBKJwQrjrNubm54eXmdt83epXJew9VKZhNCiJrE3d290sGMK+3QoUMsX76cX375BYPBQEFBAfv27eOZZ57ho48+IjIykv79+1NYWEh6ejpz5swhKCiI4cOHExkZicFgoLCwEE3TKCgooLy8nGuuueacn2OxWDAYDK6DgH5+flgslssOgjscjkrVVEXN5Obm5vq/qirOddmSJUvIyck5Z13mrNyi1+vR6XSuNmyg3mc9evSgQ4cOHDx4kCVLlrBkyRLuvvtuQkND8fHxcR2YKi4uprCwkM6dO59zDc6kX+frz9/fH6vVet52j5fyb6tYEVsIIYQQitFoRK/XV/khYE3TOHDgAPPnz2fIkCG0atXKFZdo2LAhNpuN0tJSNE0jJycHvV5PTEwMOp2ORo0a8fDDD3Ps2DG2b9/OG2+8QUpKCt26dSM2NpYtW7a45kEnT54kPDz8nMNCf44FGY1GjEbjZf87HQ4HZrNZKj/VMkajEavVisPhuOLFVHQ6nWuNl5OTw/bt23n//fdJSkqiX79+NGzYkPLyclfVsuzsbIxG43mT6svLyzEajeh0OvR6PT4+PlXyXrVYLFcluVkIIcQfnLGcqoxROg+IOMd0f39/V0VNg8FAixYtaNq0KYcPH2bTpk2sWrWK2267jbZt2xIZGcnp06fRNA273c6pU6eIi4s75z6paZqrWBbg6sr05y6WF8M5TztfArEQ4n/T6XRVsrapyGAw0LFjRzp27AjA0qVLiYmJITQ0FIPBQMuWLWnWrBmHDx9m48aNpKamMnjwYJKSkv5yPPnzvrSz0INzPHEWpLqc8QRUTLliBwwhRPWSd6Kok7p168bq1avP2360uowfP57Tp09js9nYt28f+/bto0ePHq6P63Q6goOD6dmzJy+//DJNmzZl//79BAYG0qZNGzZt2kRZWRnLly8nNDSUjh07YrPZ2LBhA7t378ZqtTJr1izmzp1LQEAAqamp/Pe//+W3337Dbrdz8OBBzpw5g8ViYc+ePWzatIkBAwb8bcBJp9ORkpJCTk4OW7ZsoaysjB07dtC8eXM8PT1JSUkhLy+PzZs3n/djZ86ccV33zp07SUxMxMvLi169epGfn3/Ox/z9/YmMjOTIkSMUFRVRVlbG7t27iYyMdG1G5+TksHv3brp27XpVFieaprFt2zZOnz5Np06drvjPE+J/8ff3JzY2lrS0tKv+s+12O6+88goFBQVYrVZ+++03iouL6dq1q+tznBtH/fv355VXXkGv15OVlUXTpk3x8/Nj9+7dlJaWsnDhQjp06EBcXBylpaWsXr2a33//HZ1Ox7Bhw9i0aRMHDhwgPz+fPXv20KVLFywWCxMmTGDr1q1omsb333/P3Llz2bNnD5qmMWHCBLKysrDZbBw6dIg9e/ZUGmcvh6ZpnDp1Cr1ej7+/f5V8TyGEqE3CwsLIycm57KDQhUpKSiI1NZXvvvuOb7/9lokTJ5KYmMjkyZNdG7TODd7rrruOF198kU6dOrFr1y68vb3p1q0bGzZsoKSkhDVr1uDm5sb111+Ppmls2bKFtLQ0bDYbCxcuZM2aNVitVs6ePUtqaiqdOnWqlIB5KY4ePYrRaCQ4OLgqng5xhfj7+2Mymap03Wi325k5cyZz587F39//nHXZzJkzXa3WcnNz+fXXX+nWrVuldmr+/v60b9+e559/nltuuYUdO3bg4eFB3759Wbt2LWfPnmXr1q3k5eWRkpICQHp6Ohs2bMBsNrN+/Xrmz5+P2WympKSEH374gVatWl12xcATJ05gt9uJjIy87OdJCCGEqGu8vb0JCQkhIyOjSr9vZmYmY8aMQa/Xs3fvXr755hu+//57cnNzCQ4Opnnz5q647Q8//EB0dDTt2rVzfb3BYCAuLo7BgwfzwgsvcPbsWc6ePUu7du0oLS3l0KFDFBcXs2jRIm688UbCwsIoKCggNTWVnJwcAF566SVX69Vt27Zx8uRJbrzxxsv6d5WVlVFQUEBoaOhlfR9xdTVu3Jjs7Oyruu+i1+sJDw+nT58+vPrqqwQFBXH06FGioqKIjY1l27ZtlJWV8f3335OYmEjLli0xm8388ssvHDx4EE3TmDx5MocPH8Zms3HixAk2b95Mjx49LitZwWw2k5ub6ypMIoQQ4urw9/d3xTuqyvbt25k9ezbl5eWUlpaydOlS4uPjiY2NBf5I+mvevDn3338/jz/+OIcPH0bTNDiQRekAACAASURBVFJSUtizZw9ZWVlkZ2ezbt06+vbti4eHB1lZWaSmplJUVERRURETJkygqKgIs9nM6tWr8fDwIDk5+ZKv2263c/ToUWJiYmpU12IhagudTkdMTAxHjhypsu+Zm5vLoUOHsFqtHD9+nDlz5nDbbbe55owVx5MRI0bw+OOPk5GRgaZp9O7dm127dpGVlcWpU6fYsGEDffv2xd3dnaysLFatWkVxcTFFRUVMnDjRNZ789NNPeHp60rZt28u69ry8PHx9fau0AroQ4tLJO1HUSSkpKSxevJhVq1YxcODAK3KKpLCwkNmzZ5ORkcEHH3zAI488gtlsZtasWaSmplJeXs6LL77I8OHDad26NZ6enjz77LN4eHhgtVrp0qULAwYMqPQ9nQmq7u7urqCow+HgySef5JNPPuHxxx/HYrEwZswYV8n7Dz/8kGbNmjF69Gg2b97MokWLWLRoket7Dh8+nLZt2/Lzzz+zZs0aVzXcBx98kM6dO6PT6cjLy2P27NmsXLmSw4cPM3bsWHr37s1NN91EUlISI0eOZPLkya6k2qeffhovLy9at27NyJEjmTJlCu7u7miads7H3nvvvUof8/b2plWrVjz11FPnfCwgIIDhw4czZcoUnn76aVd75FGjRuHt7Q3AmjVraNSoEdHR0Vc8oddZ+eo///kPKSkpBAUFXdGfJ8SF0Ol09OnTh6VLl3Lrrbfi7+9/ye8FTdM4cuQIP/zwA0ePHmXGjBkMHTqUjIwMvvvuO3bu3EleXh6lpaU88MADhIeHU1hYyKhRozAYDFgsFu67775zkt2d1+Pt7U3//v0BdcJ55MiRfPHFF3z55ZfodDpefPFFvL29OX78OBMnTuSRRx4hNjaWXr16kZ6ezvjx43E4HPj6+jJixAhKSkr49ddf2bRpE1988YXr540fP56WLVvi4+PDmDFjXONscnIyt99++yU+0+c+V8uWLaNVq1YyFggh6qVmzZoBXNbBqpKSEmbNmsWxY8f48MMPGTVqFEajkc8++4zU1FSys7MZO3YsgwcPplOnTq7AkaZprva/bm5u5/xsZ8cHZ6VSTdN47LHHmDZtGk888QQ2m42nn36a4OBgHA4Hn3/+OW5ubrz55pv4+fnx6aefMnv2bBwOB97e3owePfqcymQXQ9M0VqxYQXJyMoGBgZf8fcSVFxkZSXBwMGlpacTGxl7S67qsrIzPP/+cEydO8MknnwCcd1129913k5ycTEBAAO+88w5GoxG73U6DBg144oknzjlo6ew40Lp1a1q3bg3Avffey1tvvcXIkSOx2+2MGDGCRo0aAfD999+zb98+pk6dipeXF4sXL2bFihVomoZer+eFF164rPZxmqbx008/ER8fL4k3QgghxHnodDq6devGr7/+Sp8+fS5pE1TTNNLS0li3bh0Wi4WvvvqKqKgoUlNTWbFihevzIiMj+e9//0vXrl0ZNWoUM2bMcH3NP/7xj3MOIut0OtdhOGecJCgoiIcffpgJEybg5uaGr68vDz74IB4eHuzdu5dx48bx9ttvExoait1u56mnnsLd3R2LxcKAAQPo3r37JT9XzkPTFouFyMhIqShXizRu3JjCwkJyc3Px8/O76P+7U6dOMX/+fPbu3cvHH3/M3XffTW5uLl9//TUbNmzA29sbvV7PiBEjaNKkievrnD/HaDTSu3dvQCUxjRo1is8//5xly5Zhs9kYM2YMfn5+nDlzhnfffZc+ffrQtGlTAgMDeemllzAajdhsNq655hruvffey4qp7t69G71e71orCyGEuDrCw8MJDQ0lLS2NRo0aXfRYbrPZSE1NZd++fZjNZiIiIoiJiWHVqlX88ssvaJqGpmn83//9H1FRUZW+1jmnatiwIXfeeSegOs3u2LGD559/Hr1eT7t27ejduzd6vZ6dO3fyxhtv8PnnnxMREcHRo0d58skn0ev1mM1mnnrqKVq1anXJz4XZbGb//v306NFD5lNCXKKOHTsybdo0V7Xri2Gz2Vi5ciUHDhzg22+/JTw8nAYNGvDOO+/g5+eHw+GgTZs2DB8+/Jx8pfONJ927d2f79u2u8aRjx46kpKSg1+vZsWMHEydOZNasWYSHh3P48OFK48kzzzxDy5YtL/l5cDgc7N+/n9jYWOk6KEQNofsf7QiuTj9VIaqYw+Hgl19+4c033+TJJ5+kd+/eVd5uwuFwUFxcjN1ux83NzZVwWlpa6mplajAY8Pb2xt3dnfLycsrLy13tqLy8vFzJtRfys0wmExaLBTc3N3x8fNDr9WiaRmlpKXq9Hk9PT8rKys6pmubh4YGPjw9ms9nVfsr5PZyn9ex2O2VlZdhsNteGr6enp6sNld1ud/273N3dXYE159dW5cc0TcNkMlVqO+vl5eW6VpPJhF6vv+JtXp2B5TfffBOAV155hZCQEFkQiRqhsLCQRx55hJtvvpkHH3zwkk/eOlt2lJSUuNoJeXl5YbPZMJlMrraLFccd5zjjHEu8vb0xGAwX9N6o+L738PBwtRRy/r3RaHQls1itVtc1GI1GvLy80DSNkpISbDZbpe/r5eWFp6cnZrO50jjr6emJh4fHZb9vHQ4HP//8M2+//TbTpk2jWbNmMhYIIeodTdP47LPPWL9+PVOnTr2kauUOh8M1jhsMBlcrqNLSUtfYrtfr8fLyqjR+O+9XZWVlleaw/+tnlZeXYzabXT/LOQ8tKysD1METm81GWVkZdrsdnU6Hp6fnZa0bNE1j//79PP3000yePNmViClqJk3TWLx4MZ9//jkzZ868pEM7zjWZxWJBr9fj7e2NxWL5y3WZc45jt9vPWXddyM9yriuda03nPMz5Pb29vXE4HK71nU6nc83xLvWgq6ZpZGZmMmrUKJ555hl69ux5Sd9HCCGEqOuOHDnCE088wYQJE2jfvv1Fzyk1TcNqtbqqn3p4eODu7n5OBTqdToevry/u7u6u+77Vaq0Uv7kQNpuN0tJSHA5HpXmw8++9vb1xc3NzxWo1TXPNQc530O5COQtWNGzYkGeffVYqQNUiJSUljB07ljZt2vDII49c9GvAbrdTXFyMw+Fw7Qk4X8MV91R8fHwu6HVR8fXv7u7uWmM6HA5KS0txd3fHaDRisVhcccbzrTkvlslkYuzYsTRp0oSnn35a4oRCCHEVaZrGwoULmTdvHjNnzrzoQ/nO2IrJZHLFAj08PCrt7/95T/t/fT+r1eqKN1a8x1gsFsrLy13zs9LSUqxW63n36i9Famoq06dPZ/r06Zd1iFuI+qysrIxhw4bx+OOP069fv4ua151vPHGu3y4lJ+hSxxPnmHU548nZs2d5+OGHuffee+nfv7/Mb4W4OjKBhn/1QUnoFXWWpmmsXr2aqVOnkpyczKhRo6SSkLggmqaxceNGJk+eTFRUFP/6179kISRqFE3TWLduHePGjeO1116jW7du1X1JdZamaaSnp/OPf/yDRx99lEGDBlX3JQkhRLUpLCzkgQce4Pbbb+euu+6SVm7nUVZWxssvv4yXlxevvfaaPEe1QHl5OY899hjt2rU7b6VcoZJ9Jk+ezKFDh3jvvfdch1mFEEIIUZnFYuGdd97h5MmTTJ48+aIrPNUHDoeDFStWMHXqVGbNmnVO5TtRs2maxs8//8xbb73FZ599RnR0dHVf0lWnaZqrmMzMmTPr5XMghBDVrbS0lHvuuYc77riDYcOGXZFOvTVdXl4ejz32GMOGDWPYsGGSfCfEJdI0jTlz5rB8+XLef/99GjRoUN2XVC3mzZvHwoUL+fDDDwkJCanuyxGivvjbhF7DuHHj/u6L//aDQtRkOp2Oxo0b06FDBzZs2MDMmTPx9vYmIiLigisgifrFarW6WuV+9tlnDBgwgJEjR9KgQQN5vYgaRafTERUVRUhICO+++y5hYWHExsZK0lAVs9vtHDhwgH/+85/cfPPNDB8+XKrGCCHqNaPRSFhYGNOmTSMxMZGoqCiZI1VgsVj4+uuv2bp1K2PHjiUoKEien1rAYDDQtGlTPvjgAxo0aEDTpk3r5UbQX7FaraxcuZL58+fz4osvEhMTI69rIYQQ4i/o9XqaNWvG0qVL+f3332nfvv0FdzWqDzRNIy0tjX//+98899xztG3bVp6bWkan0xEdHc2RI0dITU2la9euVd4ZsabLycnhlVde4fbbb+e6666TtYMQQlQDd3d3IiIi+OCDD2jTpg1hYWH16l5kMpn46KOPKC8v55lnnpHD6UJcppiYGNasWcOpU6fo0KFDvdpvdzgcbN26lUmTJvHiiy8SHx9fr8ZTIapZETDlrz4oCb2iTtPpdDRo0ICUlBS8vb2ZM2cOq1atwm63ExERgZeXl9yQBHa7nfT0dGbPns1HH32Eh4cHr7/+OjfddFO9C0iK2sNgMNCsWTP8/PyYNm0aZrOZhIQEWbhXEbPZzHfffcdbb73F4MGDeeihhzAajdV9WUIIUa10Oh2xsbH4+PgwZcoUGjVqRExMjGxgoirzzp49m4ULF/L666+TkJAgc8haQqfTERoaSkREBFOmTCEkJIRrrrmmXgVu/4rVamXhwoVMnz6dl156iY4dO8rrWgghhPgbOp0OX19fkpOTmTFjBqdOnaJ9+/a4u7tX96VVO2cy72uvvcbgwYO57bbb5NB0LWUwGGjbti0LFiwgIyODrl271pv/y1OnTvHqq6/SuHFjHnvsManCLYQQ1USn0xEZGUlJSQlffvklHTt2JCgoqLov66qw2WzMnj2bH3/8kfHjxxMeHi6xGiEug06nw8vLi2bNmjF9+nTc3NyIj4+vF/NbTdPIyMhg3Lhx3HrrrQwcOFD2eoS4uiShV9RvOp0OvV5PQkICN9xwA15eXnzzzTcsWLAAk8lEaGgonp6eUi2hHtE0DYfDQVlZGTt37uT9999n5syZ+Pv789RTTzFs2DDXAkheE6Im0+l0NGnShBYtWvDFF1+wceNG4uPjCQgIkNfvJXCODdnZ2UyZMoXly5fz5JNPMnjwYEnmFUKI/89Zdczd3Z333nuP4OBg4uLi0Ov19fK+o2kaZWVlvP/++6xatYpXXnmFdu3a1cvnojZzJqtHRUUxadIkdDodCQkJuLm51cv/S03TMJvNfPXVV3z11Vc8++yz9OjRQwK6QgghxAXQ6XQEBgaSkJDA3LlzOXToEG3atKnXRQMsFgs//fQTr7/+OnfddRd33nmnJELWcp6enrRs2ZJ58+aRmZlJUlISHh4edfY1rmkaubm5jBs3Djc3N1588UUCAwOr+7KEEKJec3Nzo3nz5hw7doy5c+eSlJRUpzuuappGeXk5c+fOZd68eYwfP54WLVpIrEaIKqDT6QgJCSEuLo4pU6bg7u5OYmJinS744HA4OHz4MC+99BLJyck88sgj0uVciKvvbxN6dZqm/d0X/+0HhahtnK93s9nMhg0bmD9/PocOHSI+Pp4bb7yR1q1b07hx43odYK3LHA4H+fn5HDhwgLS0NH799VdMJhPdu3dn6NChNGzYsN4mo4jaTdM0CgsL+c9//sNPP/1E37596devH82aNZPF/AVyOBycOnWKZcuWsWDBApKSkhg9ejSRkZEAMi4IIUQFzgMQv/76K5MnT6Zdu3bcf//9XHPNNfVqvLTb7WzevJmPP/4YT09Pxo4dS1xcXL16Duoah8PBtm3beOutt4iOjuaxxx4jPj6+Tgdv/0zTNHbv3s306dPJz8/npZdeomXLloDMh4QQQoiLoWka2dnZjB8/noKCAp588km6du1ar6r1OhwOsrKymDNnDmvWrOGpp56id+/e9aLaVX2gaRpZWVm88MIL+Pj48Nxzz9GsWbM6N2e0Wq3s3LmTf//73yQkJPDss88SHBxc5/6dQghRW5lMJj788EN+/PFHxo4dy7XXXlvnCrRomsapU6f46KOP2LVrFxMnTqRly5ZyLxKiijkcDrZu3cqECRPo2LEjDz30EBEREXXuvWaxWFi+fDnTp0/nlltu4fHHH6+3hS2EqGaZQMO/+qAk9Ip6zWKxcPjwYTZs2MCGDRvIzMwkIiKC6667jl69ehEbG1spwVNuYrWHc2zTNA2TyURaWhqrVq1i165d6HQ6mjdvTvfu3UlOTiYkJESSHkWdYLVa2bFjB19++SUHDx4kJSWFO+64g+joaKnYex6apqFpGkVFRXz99dcsX76csLAwhg8fznXXXScnEYUQ4gIcOHCADz74gKNHj/Lwww/Tp0+fOj9+aprGmTNn+PLLL1mxYgU333wzDz74IA0aNKjuSxNVJDMzk48//pitW7dy5513cscdd+Dl5QXU3TWhc0707bff8s0339C1a1ceeeQRoqKi6uy/WQghhLjSNE3j7NmzzJ07l++//57u3bvzwAMPEB4eDtTNeYUzJmu321mxYgUzZswgIiKC0aNHk5CQIDHYOqZigtHOnTt54okn6NWrF+7u7rX69e18HVutVmbNmsW3337LwIEDuf/++/Hz86vmqxNCCPFnZWVlLFu2jP/85z/06NGDkSNH4u/vD9Tu+ZazqMLGjRuZOnUqoaGhjB49mqZNm9bqf5cQNZmmaWRkZPD2229TVFTE2LFjSU5OrhP77JqmkZeXx2effcYvv/zCiBEjuO222+rcIQghahFJ6BXi7zgTusrLyykqKmLr1q389NNPbNu2DW9vb9q2bUuXLl1o2rQpISEhBAYG1un2UbWZw+GgtLSU/Px8srOzSU9PZ9u2bWRkZGAwGOjcuTO9e/cmMTERb2/vWh9YFOJ8nC2Sjxw5wowZM9ixYwft2rVjwIABJCQkEBoaWq+qzJ2Pw+GgoKCAI0eOsHz5cjZs2EBMTAz33Xcf7du3x9vbW8YGIYS4QM55dFpaGu+++y5ubm6MGDGCzp0706BBgzqzYa9pGna7naysLFatWsWCBQuIjo5mzJgxxMXFyQn2OkbTNCwWC3v37mXy5MkUFRVx11130b179zo3l7Lb7WRnZ7N+/Xq+/vprvL29GTNmDK1atZL1khBCCFFFbDYbJ0+eZOrUqezatYtbb72VW2/tT6NGsXWqYq/D4aCwsJC0tDTmzp1LTk4Ojz76KD179sTHx0fmFXWUc+68fv16Jk+eTExMDI899hgJCQl4eXnVyv/3oqIidm3axIIZM8jT6Rj9z3+SlJQk6z4hhKjB7HY7hw8fZtq0aRw7dowRI0bQvXv3WltV3VmUbP78+axbt457772XwYMHy/6VEFeBpmmUlJTwww8/8Omnn9K5c2fuvvtumjVrVivXb84u1pvXreOzWbMIDAnhlVdeISYmpk7FuYWohSShV4iL5XA4yM7OZt++fezatYu9e/eSl5eHXq8nOjqaxMREmjZtSvPmzYmMjJQ2YdWotLSUQ4cOcfDgQdfj7NmzeHh4EBsbS5s2bWjZsiWJiYm1NoAoxKWyWq0cPHiQ1NRUNmzYgN1up0OHDnTt2pVOnTrh4+NT3Zd4VZWXl7Nnzx5++eUXtm7dislkomPHjvTo0YOOHTvWykWYEELUFM6qtStXruT775ei013DTTe1oF+/7q5K8bWV1Wpl3759LFq0iM2bNxMdHc3QoUO59tprXVVbRd3kDN6uXLmSxYsXU1paSrdu3ejfvz9xcXG1OmHdbrdz6NAh1ixbRllqKkf8/Ohz333ceOONUnVMCCGEuELMZjPr1m1h/PifKStz49ZboV+/XrRp06bWxyROnTrFsmXLWL16NWazmd69ezNw4EDCwsKq+9LEVaJpGidPnuSbb75h1apVJCQkcOedd9K+ffta8/o2mUysXr2aRYsWoR08yKP5+bTo1Qufe+6BpCSQfSAhhKjxTCYTP/zwA/Pnz8dgMDBo0CB69epFYGBgrYhP2mw29u/fz7fffsumTZto3749999/v1TlFaIaaJrG3r17+eqrr9ixYwfdunVj4MCBtGjRotbEhQsKCli+fDmLFy+m0Y4d9GrcmGvfegufpCSQMUWI6iYJvUJcDofDQVlZGWfPniU3N5e9e/eyc+dODh48yJkzZwgICKBZs2Y0a9aMhIQEmjRpgpeXF0ajEQ8PDzw8PORkyyXSNA2bzYbFYsFsNmM2m8nPz2ffvn1kZGRw4MABTpw4gcPhoHHjxiQmJtK+fXtiY2Np0KABfn5+Uk1Z1HvOljz5+fkcPXqUFStWsGnTJux2O+3atePGG2+kVatW+Pr64u3tXScqTTirKJpMJkpKSsjIyGDdunX89ttvmEwmOnXqREpKComJiYSEhNSaTQUhhKjJNA3KyuDAAY1Jk/LZuvUsrVrNoKBgI23atHEFuvz9/fH09KzR95qKXR82bdrE0qVLyczM5IYbbqB///7Ex8dLwmM9o2kahYWF7N69m0WLFrFt2zYSEhLo378/7du3x8/Pr8ZXSHE4HJhMJgoKCtixYwdLlizhwIEDdG3RglGZmQScOYPPvfei69MHIiNBWq0JIYQQVcZuh4ICWLcO5s7VKC62c8stZ8jL+5R169YQHh7OrbfeSufOnQkNDcXb2xu9Xl9j5xbOLh0lJSXs37+fpUuXkpaWRqNGjRg0aBCdOnUiODhYYuL1lNVq5dixY67EgaioKIYMGULnzp0JCAjAaDTWmNe2w+GgvLyc3Nxc1q5dy3fffYfVamXw4MH06dmTMLMZ/YIFsGoVNG0K990HrVqBv78kQAghRA3m3BPbsGEDs2fPpqSkhAEDBnDTTTcRGRmJj49PjUnG0zQNq9XK2bNnSU9P55tvvmHfvn3ceOONDBs2jLi4uBp17xSivnGufQ4fPsycOXPYtGmTa7+jVatW+Pv716guZw6Hg5KSEnJycli8eDE//vgjgYGBDB8+nBsaN8bv66/RbdoEPXvCkCHQqBF4elb3ZQtRX0lCrxBV5c/vl9OnT3PgwAEOHDjAoUOHyMzMpLCwEKPRiK+vL0FBQcTExBAREUFoaChhYWEEBwcTHBxcoxYLNYHVaqWwsJAzZ86Qm5tLTk4OZ86c4cSJE2RnZ1NcXExZWRkAERERNGrUiPj4eNfD808TjZoyaRKiJnGOYVarlS1btrBx40a2b99OQUEBgYGBNGvWjKZNm9KkSRNiY2MJDw+vNRXI7Xa7K2n5+PHj7N+/n0OHDpGfn4+npyetWrXi+uuvp0OHDvj6+rq+TsYKIYS4PJoGxcWwcSMsXAjHj6tY0LBhGtHRGhkZB1m1ahVr167FZDIRFxdHcnIyiYmJJCQk1JjqGDabjZycHPbu3cvevXvZvn07OTk5REZGctNNN9GzZ09XdbGacL3i6qu4Fvz9999JTU1l7dq15Ofn07BhQzp06EB8fDzNmzcnODi4Rqz1HA4HeXl57N+/n/T0dHbs2MHJkycJCgqie/fu3HzzzcTExIDdjm77dvjiCzh4ELp0gb59oX178PCo7n+GEEIIUWtpmrq1/vgjrF4N7u5w660waBB4e6u5RX5+PqtXr2bVqlWcPHmS0NBQWrduTVJSEgkJCURFRdWI2IymaRQVFXHgwAEOHjzI1q1bOXr0KB4eHnTu3JnevXvTqlUr1+fLnLl+c86d8/LyWLFiBampqRQUFJCQkECXLl1o2bIlTZs2xaMa5pqaplFaWkpGRgbbtm1j27ZtHDt2jOjoaPr160dKSoqrE4vrVZydrRa8qang5we33w7XXw/BwZLYK4QQNZimaZjNZjZt2sTChQvJyMggIiKCTp06kZSURMuWLfH396+WeYvNZuP48ePs2rWLnWlplK5dS46XF50HDKBfv340bKjye2ROJUTN4JzfnjhxggULFrB+/XocDgetWrWiQ4cOtGnThujo6GpZuzmLUTgLE27atImcnBxatWpFv379uPbaa13FrXSaBhkZ8PnnsH07tGkD/ftDhw6S2CvE1ScJvUJcDc5KXgUFBa7E1JycHI4ePcqpU6c4c+YMeXl5lJeXYzR64eUVQVhYM+Li9ERERBAdHU14eDihoaH4+fm5qjA4fz3fA2rGRN45jmiaVunhcDgq/d5ms5Gfn8/p06c5deqU65GVlUVeXh6lpaXY7XYCAgIIDQ0lODiYRo0a0bBhQ0JCQggMDCQoKIigoKAaddJJiNrK2Ub65MmTZGVlsXv3bg4ePMixY8cwmUw0aBBCbGwyLVvG0qpVUxo1aoSfnx8GgwG9Xl9pnIKqH4+cY4tzLHE4HK6HyWTi999/5+DBg+zfv5+DBw+Sk5ODwWCgYcOGJCYm0rJlSxo2bEhMTAz+/v41IrFGCCHqAk1Tj/JyVWXss8+gtBQGD4YbboBrroGKxbg0TaOgoIDff/+d3bt3s2XLFjIyMgBo3Lgx7du3JykpiWbNmuHl5YVer8dgMFSaC1/+NVe+j9jtdlfli507d7J9+3aysrIIDAwkMTGRLl26EB8fT2xsLF5eXjLvFOfQNI3i4mKOHj3KwYMH2bBhAxkZGVgsFho2bEhycjLJycnEx8fj6+vrmjtVnENVxTX8+XVdWlrKvn372LVrF2lpaRw/fhxvb2+aN29Ohw4daNGiBY0aNcLX17fyNWgamEwq62jZMlizBhIT4cEHoUULldgr7wMhhBDif9I0sNng2DGYNw9+/lkV9rz9dmjXDho0OPeW6qz6lJmZyf79+0lLS2P37t0UFBQQERFB27ZtSUpKonXr1gQFBVWKy1RFTKZibLfivKK8vJyjR4+yfft2tm/fzpEjR7DZbMTFxbmSMq+55hqCg4Nlviz+kjMZ/NChQ2zbto1169aRmZlJcHAwbdu2pUuXLrRu3RpfX99zYo6X+rqquCdht9tdhQB27NjBxo0b2blzJyaTiebNm9OlSxfatm3LNddc8/drP4cDsrJgwwaYPx/MZrj7bujdWyX56vUyXxZCiBpK0zQsFgvHjx8nPT2dtWvXkp6ejsFgICEhgWuvvZbk5HZERKgiNxVjk1VxL3Lej0wmkyuGtG3bNrKysoiIiKBLcjKDdu4kCT45FAAAIABJREFUsLgY3ylT0DVurO4rQogayVkFfP/+/WzZsoUtW7Zw6tQpoqOj6dy5Mx06dKB58+YYjUYMBoNrjguXvm77cxzYZrNx+vRpNm3axJYtW9i3bx8ALVu2pHv37iQkJNC4cePzd6nVNLBa4dAhWL4cVq6E+Hh47DH1q8SBhbhaJKFXiOpwvkQ0q1UjPb2E2bMLWL8+iKSkM8THf0t2djbZ2dmUlpZiMpnQNA1vb2+8vb3x8fHBx8cHT09PfHx88PPzIyAggICAALy9vTEajbi7u+Pu7o7BYMDNza3Sw7ngqDhRAM75s81mqxS8tdvtlRJxnQ+73Y7NZsNqtWK32zGbzZSXl1NcXExRURHFxcWcPXuW8vJyysrKKC0tpaysjJKSEqxWK+7u7nh7exMUFERkZCQRERFERUURERFBTEwMYWFhrsXSnxOahRBXzp+T73//PZdp007y22+NaNXqCwoK1lNSUoLRaCQgIICgoCACAwMJDg4mIiKCwMBAfHx88PDwwGg04uHhUWlscr6XnScTnWOOpmmuscVsNmO1WrFYLJSXl1NeXk5BQQE5OTloubkcKSwkv7CQgoICysvL8fHxITIykoSEBJo3b058fDwNGzY8J/gvhBCi6jgckJOjEhO+/Va1D777bkhJ+WMP869UvNdYrVYOHjzoSjo8cuQIxcXFBAQEEBISQlhYGOHh4a5DGc55r6enJx4eHpWC63q9Hrvd7gqO22w21xzVbDZTWlpKfn4+mZmZ5OTkuDpBmEwmgoODSUxMdJ2ij4yMdAXZ5B4iLpRz/WS32zly5IgrSXz//v0UFRXh5+dHcHBwpdd1UFAQXl5eeHp6YjQaMRqNrte187XtfF073zPOOZLZbKasrIyCggJOnjxJdnY2ubm55ObmUlZW5uq80L59e5KTk4mJiXHNyeB/BI41Tb3Rc3NVosLSpRAdDUOHqiyksDAJ6AohhBB/oaAA0tJgxQrYsUMVu3/oIXXgzVmo6e9vw3/Ek202G7m5uezYsYO0tDT27dtHbm4u7u7uhIWFERIS4ppXNGjQwBU/ds4rnPd+ZyzGOVd2xmHMZrNrzlxeXk5hYaGr+EJubi55eXkUFhbi5eVFkyZNaNu2LW3btiUxMbHS95Y5s7hQzvWg3W6nqKjIlfywc+dO8vPz8fPzIyIigvDwcBo3bkx4eDh+fn6uObOnp2eldSCo+KJzrmw2mzGZTJhMJoqKisjMzCQzM9P1mjaZTISHh9O+fXu6dOlCq1at8PHxubA5cuV/iDoI99tvMGsW5OXBLbeoxN64OFWKWwghRI3knGvZ7XYsFgvp6els3bqVX3/dzG+/FRMXZ6ZhwwaEhYURGxtLdHQ0QUFBeHp6uu5HznmQMybpvBdVjEc6981zc3M5fvw4WVlZ5OTkkJ+fj6+vL61bt6ZDhw507tyZkJAQ3AwGdKWl6L74An74AUaMgIED4f9XjBdC1EwV97lPnz5NWloaGzZs4MCBAxQXF7viwVFRUTRs2JCwsDB8fHzw8vLCy8vLtZf+5zWb3W7HarW6xpPS0lLOnj3LiRMnyMzM5PTp0+Tk5GC322nUqBHt2rWja9euJCQk4OHhcXF7G3a72vD55htV5KFhQ7jrLhUHDgyUOLAQV5Yk9ApRnZxvsRMnYPZsWL9exXUGDIDrrgMfH/VxZzWlkpIS16Pin00mk+vPzuTZ8vJyrFarKxnO+ah4s3cmFNvt9grXpP4cCrTWNFb//+CrM3ilaVqlZDjnwqTiAsUZPHN3d8fDw8OVbOzr64u/vz+enp74+vq6EpL9/Pwq/d7T01MCvkLUQJoG+fkwbZrahPrHP6BrVw2rtYz8/HzOnDlDQUEB+fn5rl9zc3NdY5Iz4b/iIQDn+ONMSAFcY4ymaa7xxM3NDXd3d9ev7u7uKrHL15fWX39N+YABBPTpQ3BwMEFBQYSEhJxbXU4IIUSVc85ni4tVEu/ixeDr+0dF3svtMupseZqdne1KuHU+srOzXQfDLBZLpbmvw+Eg0OGgncPBTxUOcxgMBtd9xDlXDQwMJDIyktDQUFdXjPDwcMLCwjAajVXzRAlRgaZpmEwm1+s4Nze30uu6qKjI9Zp2PpxJNna7Lw5HZwyGH9Hrda7X9p9f1/7+/kRGRhIWFlbpNR0eHu5qE3xZHA44flxl8C9erP5uyBDVhs3XVwK6Qggh6j3nPLm0FFJTYcECKCmBHj2gb19Vmbdi54rLYbFYyMnJITc3t9JhnqysLFdxhYrzCmd8GIeDznY7x3Q6sv//nLliUQgPDw9XbDc8PJyIiAhCQ0MJDQ0lIiKCsLAw/Pz8JPYirghnK/SKnfxOnz7NiRMnXN0OK64F/9j7SAYKcHP73ZUA4ebm5kpm9/b2dhUScRYViY6OJjQ0FA8Pj6q6eCgrg61bYdEiSE+Hjh3hgQdUFr9OJ/NlIYSoBTQNVq608/77NkaPPojFcpzTp0+TmZlZKS7pLEhTcR9e07RKB6gMBoNrbmU0GgkODiY6OrrSvSgiIgIfH5/zz61sNnUybPp06NIFnnlG4i9C1DLOvY6srKxzOlafOXMGs9mMxWLBYrG49jk0TYfN1gm9/hgGw2nXms2Z8Gs0GvHx8SEqKoqoqCjCw8Nd40loaKgrx+eyOByqzczq1arAg5eXSuzt0+ePA2syFglR1SShV4jq4GxDnJEB330Hv/6q4jnDh0OzZuDpeXH3vIoVGs73cFY7c54EOt/jz9/PsHkzxvfeo3TOnHMqKjh/7/z7P1fL1VVIAq6Y+FuVrZGFEFeXzaa6LL/2mjp0969/qYN4f/V2rljRt+IhgvONS87Pd/6+4phTcYyp+HAdJNDrMSxdim7WLHjzTdX2WcYYIYS4KqxWyMxUCQqLFqninPfeq+a1fn5Xbjh2HkCreEDkz/NfAP2uXRjHjaNswYJz5q0V7yXODV6Zp4rq9OfXtXMDqOLcSdM0Dh3S8eyznixYUIaHx7mv6z8n4lzxitIOBxQVqdNen34KZ8+qvuEpKRARoYK68r4SQghRz1it6tzL2rWqqL2XFwwbBjffrPIuDIYre3v8c2e1isklFecVWK14jh6NdcgQ7D16ALjmFYYKCb4V5xbOzxGiOpyvY2DleCO88oqRli3t3HmnrdJcuWIxEmfRALjCr2dNA7NZJUDMm6cOw7VooaorJiRc2YWzEEKIy3bkCDzxhOo0P3CgmsM5K26eb5715733P8cjK96LKsZtLpjDASdPwoQJ6tTYs89C27Z/3xZNCFFjna8jdsXxRHWbgNGjPRkyxEqPHvZz8nCca7WKnVKuGLtdtZ5Zt051o/DyUglOXbpASIiMRUJULUnoFeJqs9lgwwaVyHvgAHTurCrytm1bw2I369fDG2/A8uXVfSVCiGpms8H338OMGXDrrXDffRAQUN1XVYHJBO+8o6IrU6fWsIsTQoi6R9PUIY8FC2DjRoiNVfPZ7t2hqgoaVYlt2+D552HNmuq+EiGqzP798PDDqiBCjXq/OU+trlunJo4nTqhe4kOHQmKiBHSFEELUC3Y77NqlihZt2qQOQg8YADfeCN7e1X1152GxwEMPwT33QO/e1X01Qlw2TYPnnoM2beD++2vYfovDoRbSy5erxN6QEBg0CG66SdqmCyFEDZSTA2PGQFISPP10DYrBaJpqlfbpp6pi72OPQb9+qlqYEKLOqZFLNk2DwkJYtkzNbc1mdXp18GDVslEIURX+NqHX7SpeiBB1msOhDsrt2AFffKH2Nvv1g1GjVGC3xiwChBCiAk1TRdZmzFC5UM8+Cz171sAxy9NTDagvvABTpsA//1lDd8qEEKL2chYWOnoU/vtflbPXvr2q3B4fr4bdGrVZKoS4unQ6lYiQkgJdu6p2NEuWwMiR0K6dijw3bqw+RwYLIYQQdYimQUkJ7NsHX38Nu3erW+G//61ufT4+cusTQqAOuCUmqhaNQ4aoEt6ffAKzZ8Pdd0O3buDvD26yNSuEENWtvFzlyxqN6lB1jdoT0+nU/WLkSNUmbcIE2L5dbeA1aCATTyHElafTQVAQ3HUX9O0LW7eqxfDCherA2oAB6vCazGuFuGLk3SXEZdI0OHNGJcItW6Z+37u3KiQZGKg+R+bVQoiaSNNgzx6YNEm1EZo+XR1AqJGcC4fXX4fHH1eB8IcekoWCEEJUkfJy+O03+OEHdW/o2FHtO8bFqY/LfFYIUYmvr2pB06aNKh8xf76qlt2kCfTpo8oU+vlV91UKIYQQl0XTVOW2tWtVRd4zZ6BXLxg7FiIi1OfIPFkIcQ6DAWJiVALEwIFqAPnvf2HmTDWI3HILXHONDCBCCFFNNE3t6a9dC9Om1eCGkEajOgwyY4bayBs1SpWpb9dO3WuEEOJK0+vV/nxKiuo6sW6d2qNfskTNa2++WR1ok3mtEFVOsmCEuEQOBxQVwY8/wpw5Kqfs9tvh+ushMlK6jQohai5NUy0i166Ft95S8YBHH4XQ0Bo+39bp1EU+8wxMnKj6IHXpUsMvWgghai5nRd5t22DWLNVhondvVZWiSRNwd6/uKxRC1Gg6nXrExakelYMGqdbCn3wCX30Fd9yhknuNxj8+VwghhKjhNE3Ffc+cUTl4CxaoCrzDhkHnzhAVJfkTQogL4Jz7OgeQm2+GzZvVwLJ4sUqAuOceCAtTg4rMlYUQ4qrQNNVtd/p01RCySZMaPgTrdKoSz7hx8OWX6qIffVQlJcj9QwhxNTjHGYMBbrhBHSrYtg2++w6eflol+t55pzrQJuOSEFVGEnqFuEh2u2pD/Msv8P33qjDRY49B9+6qHYfsUwoharrCQpW4tXy56tBz8821aH6t16vFQlERjB+vTiW3aFFLLl4IIWoGZ4eJtDSYOxeys1UM+J13VEFNvV6GVSHERTIYVGvhpk1h+HBITVUDzJw5cOutqmJvbKxkQAkhhKixNE11rThwQMVLfvlF5U68/LIqSu88nyKEEBfN2Xns5puhZ0/Ytw8+/xxGjFDFCvr0UQONt3d1X6kQQtRpmgYnT8Kbb8LQoWpvv9YU6AoMhJEjoVMn+Pe/VVbyE0+oCatMUoUQV4tOpzaRbrgBrr0WjhyBTz+FRx5R8d9+/dS+vdFY3VcqRK0nCb1CXABNU79mZqrOSKtXQ6NGqrNF167g71+91yeEEBdC01T1xUmTIC9Prfnbtq2FeRV6vWpNl56uIi9Tp0KDBhK0EEKI/0HToKREzWXnzlUJCwMGqMJAMTG1KIAthKiZnKdbfX1h8GCVrLB6tepj+c030KOHajscHf3H5wshhBDVTNPAalU5EV9+qfYjO3SA116DNm3A07O6r1AIUWfodKoVTlKSapuWng4//ABvvKG6XgwbphIjnMFamS8LIUSVcjjgo49UI8ihQ2tZLFSnU+2Cu3aFyZPVY8wYeOklaN36j88RQoirwTmvTUhQc9k9e1Q1xBdeUGPSvfdCq1ZSPUaIyyAJvUL8DU0Dkwl+/x3mz4c1a1Ty26RJ0LixOjAt9x8hRG1gsahKjG+8oWLGr75ay3NgDQZVHn3cOHjvPfjXv2SXTQghzkPTVIeJnBz49Vf4+mvVVeL+++G661Rxh1oVvBZC1B6BgXDbbdC7N2RkwBdfqMGnZ091mqBJE6lCJoQQoto4HGqOvG2bKiiflwcDB6r9x7AwtTdZa2MmQoiaz91dnRpo2VK10PnuO1W4ICwM7rgD2rdXGWeyYBdCiCphtarDW/v2wQcfQEBAdV/RZYiLg7ffhm+/VW04R4yAQYPUAWshhLjajEZo104l8GZnq7HpuedUN7eHH1ZJv76+ssAW4iJJQq8Qf8Fshu3bVSGhfftUB4upU1WFeDd55wghagnnwYSvvlLz54cfhv79wcuruq/sMul0KiN5zBh45hmVoXbPPSpLTQghBPBHZfaFC9XBtOBgePRR1U5O4rtCiKtCrwcfH3UyNikJdu+GefNUtlR8vGrDdsMNMocTQghx1TgccPy4Kor500/qFjRwoOpaERIie4xCiKvIWdksIkK1TR86FBYvVoHcmTNVELd3bwgPl8FJCCEug6bBb7+p4l3jx//ROKjW0ulUrOWeeyA2VhW92btX3UsaNpR7hhDi6tPpVGJvo0bqoMHQoerA2rhxatAdMgS6dasDCQpCXD2SlihEBZoGZWWqIvynn8KxY2p/8fHHVUVe2WMUQtQmDoeqMDNxokroeu01dTjB2bWtToiNVdV5X3hBLRJ69pRghRCiXnO2DD59Wu0B/vQTNG8OY8eqwj/+/jJMCiGqiV6vknoTEyEzE1asgHffVWUR77tPVSHz9ZUqZEIIIaqcpqniDSdPqvPAP/+sigWNHq2KNwQHyxxZCFEDhISoKosDB6ry4bNnq0FryBC45ZY/yocLIYS4YJqmujK8+67KL2vXrrqvqAoZDHDjjWpiO3myKn7z6quqSqZUJxNCVBe9Xu3fjxql5rW//KLGqJkz4aGHoEsX1bVNYsBC/C25kwuBmswXFKhg7pIlkJurDj9PmKC6GoEEdYUQtYumwfr16mBukyYwfbqKCddJyclqUfD22+r0cXx8dV+REEJUC4sFduxQBX22bFHdO999V8Vw9XqZzwohagBntYa4OHjySVVNZuFC1Q7Hywtuuw2uu05VbpBBSwghxGXSNCguhq1b1Rx53z51fuS991Qir8yRhRA1jl6vThn06qXa66SlqeSH+fPh+uuhb191SM7dXQYwIYS4AAUFKse1XTu4++46VvAG1H0jOlolNcyfr7pa3nMP3H67tLgXQlQvg0EV47rvPhg0SCViTZ8OX3yhqiredJO0yRHib0hCr6i3NE09ystVQHf+fDXnve02Ve09NlbuHUKI2kfTVELXokXwySdqTLv/fvDzq+4ru4IMBujTBzIy4I034K23VKs6GcSFEPWApoHdDgcOwKxZsGuX2vObOBFat5YOE0KIGso5TwsIUJPVvn1hwwb45hv4/HM1iR08GBo0kGwrIYQQF6VizHfVKlXcsrRU3WoeeQQSEqRgmRCiFtDpVNJu585qcb93LyxbBi++qE7tPvig6nzh5iZzZSGE+AtWK8ydC4WF8Prr4OlZ3Vd0heh06pD08OEqeW7KFNi5E15+GYKC5D4hhKg+zvHH31+dqkhJUVUWFy2CefNUDPj221XFXp1OxishKpDQlaiX7HY4fly1IF68WCW6PfQQ3HCDVHcXQtRup07BBx/A7t3w73+r4rX1Ykzz9ISRI+Gf/1TBildfBR+f6r4qIYS4ooqKVLWxJUtgzx7o2VMV7omIUGcdJPYhhKgV9Ho1cA0apFoJ79mjqjUsWKCCvH37qvaRHh4ysAkhhPhbViucOAE//ghLl6qi8HfdBT16qP3DOleRTQhR9+l0KsbZoYMK9J4+rQ7BPfec6lQ2fLhqzyPVzYQQohJNU13eFy2Cd96pwx0sK3JzU8kOCQmqJcVDD8FTT6m/kxNtQoiaICwMhgyBW29VrYZnz4Zvv1V/vvlmdSihXiQ2CPG/yZ1b1Buapn7NzFSHPX7+GWJiVGWGHj1U1wkhhKitNE21jpw4URU6mzIFmjSpZ3FcLy94/nkV0P7vf1Wlinr1BAgh6jrnfNZiUQfTFiyAvDxVkffJJ6FpUxn2hBC1mE6nDml16KBOqO3YAQsXqvld69aqikNSklTsFUIIUYlzjnzokNoL3LZNdV579FHVnd7fX24bQog6QKdTyVjR0fDMMzBwIKxeDR9/rE4rDBmiDsf5+MigJ4So9zQNDh6Ed9+FUaNUSKHeDI06nTo0/eqranL81luqytmdd6rTbvXmiRBC1Fh6vaqymJIC114Lv/4K33+vKtekpMDQoRAZqT5XxixRj0lCr6gXysvhyBF1D0hNVR2Jxo9XB9Sc1duFEKK2Ki+HlSth2jTVmWLECHVIod6NbTodNG4Mr70GY8ZAVJQ6zScleIQQdYDDoZJ3N29WsViTCYYNU8NcgwZSZEEIUcd4eqr2wm3bwsmTqrXO88+rkwsPPaQW8wEB9XDCK4QQwsnhgOJiOHAAvvwS0tNVAu/EieqAs8R8hRB1ll4PcXEqDnrbbbBli2rXM3u2ChT07Kmqn7m5yUAohKh3NE3FUN9+Ww2HffvW02KPXl7wwAPQqROMGwe7dsHTT6vql3JvEELUFD4+0KePWszv36/mtPfeqwbv/v3VfNdorO6rFKJayLavqNNsNti0SSXy7t6tTuBNmqQ6ENXLybsQok7RNMjPhxkzVOugF15QVRrd3av7yqqRTqcG+5Ej4f33VXCieXMJUAghai1Ng1On1MGNH35QHedvu011IPLzq+6rE0KIK8hZsbdJExg9WlVnWLxYZWoFBqqBsGdPCA6u7isVQghxlRUWqqINK1aouEj37upWUe86FQkh6je9XvWQ79NHDYQ//6w6XMybp6qdDR4M8fGyGSaEqFccDrVnBuo8cL3eL3N3V0kRH30EU6eqhN4xY9Q9QqpDCCFqCp1OVSrr0AGSk9UBhDlzVFeKLl1g0CBo2VLGLVHvyCte1DmaBmVlsHcvfP65aqnRqxdMnqzyuqSbhBCiLnA44MQJeOklVYB20iSVtyrxWdQg37u3ugFMmKBaNgcGyuAvhKhVbDbIzYWlS2H+fNUp7YknVLHKoCAZ74UQ9YxOBzEx8PjjqjrDb7/BN9+oKmRDhqi/8/NTE2OZ8wkhRJ2jaWp+fPYsLFqkunH6+Khcta5dVYMeac4jhKi3dDpVibFvX7juOrU5tmQJPPmk6nrx0EPQsKE6ISxzZSFEHWa3q3PA69bBe++pGGq9p9OpyfLLL6t7w7hxcM89cNdd6hC13BeEEDWJwaA2wZo3Vy3Y586FZ59Vyb4PPqgSvmTsEvWEbAOLOkPT4MwZWLZMFWZ86SXVhXPuXPjnP9VB5Ks9tmuaxpEjR1i7di1ms/mCv66wsJCVK1dSWFh4Ba9OCFFbWa0qwevJJ9Wcdto0aNGiepO7zpw5Q2pqKsXFxRf8NWVlZaxevZqTJ09W/QUZjfDUUxAZCa+/DkVFVf8zhBDiCrDZVGeh996D++5TnTPfeAM+++yPQpRXe7zPzMxkzZo1mEymC/6aoqIiVq5cSX5+/hW8MiHE1eBwONi1axdbt27Fbrdf8NedPn2aVatWUVJSUnUXo9erxN6hQ1Uy79NPw5o1asD84APIyFADqRBCiDrDbIZt2+Ctt1TnzS1bVDXe2bPV7SAm5uom89rtdrZs2cLu3btxOBwX/HUnTpy46Dm1EKJ2sNlsbN68mfT0dDRNu+Cv+/333/n5558pLy+vuovx91dJvK+/Dp98At7easPshRdg1Sq4iNitEELUJpoGaWlq6HvxRWjWrPrzvS41T+Ds2bNVnyfg6wt33KEqoKWmwtixcOiQeuKEEOJPLiVfyWw2s3btWo4cOXJRc+JzOLu2NW8Or70GX3yhCneNHg3PPw/r10NpqYxfos6ThF5R62kalJSoE3ePPKL28G64AT7+WMUpQkLUmF9dk/aNGzcyY8YMSktLL/hrTp06xdtvv82pU6eu4JUJIWobZwXy6dNVh5z771c5q/7+1R+YOHbsGJMmTSInJ+eCv+bs2bNMmzaN9PT0qr8g52T/mWfg+HF1uuMiElCEEOJq0jQ1RB0/rgqLP/MMZGaqWMWUKdCxo+qQVl1j/c6dO/nwww8puojDETk5OUyaNInjx49fwSsTQlwNDoeDJUuWMH/+fGwXkSybkZHBlClTqj6x37nA9/RU7XimTVOVGo4fV0GAl1+Gw4fVwCqBXSGEqHU07Y+KvFu2wD/+oQo32GxqiJ8yBW666Y/58dWeI1ssFubNm8eyZcsuapNy586dfPTRRxc1pxZC1A4Wi4Wvv/6alStXXtS4sG3bNqZPn35RBRIuiE6nDsI1bQr/939q4IyPh/ffVxUi/h97Zx5WZbX98c9hnkGQScAJQRQ0UcMJ1BxwRBxTxNTKRq1r83R/di2zrDRL07qVmRMKIqAoojiDY6I4gUOKIhxknmfO+/tjX05qoaBWlPvzPDwOwHv2OXDWXu/a3/Vd0dGiW6Iu4EokEsnfHEUR/QpffAH+/qKv4a8+M6vjyJEjjdYJZGRk8Omnn5KRkfFgF6OjI1yCPv9cOLvPng2HD4uRoHI/kEgkN3EveqXS0lK+++47jhw58mAWUZfTuriIJoQlS8DDQxyivfSSEPZWV8ucVvKPRXWXm0v5Wy9pstTWglot4nRoqCjqTp0qzvPMzZvGGGJFUaiurqampgYjIyN0Grio2tpaysvLMTY2RrcRFhOKopCbm4u+vj6WlpZ3/4aEBGH5FhPT4MeQSCR/DYoCFy6I5tnCQmGy0LZt0xkpWVtbS0VFBcbGxg2OdRqNhvLycgwMDNDX12/wYymKQnFxMVVVVTRv3vxuXyzast99V5wCDhjQdF40iUTy0KMoopH4/HmRz/78M/TsKXLaNm3+WhHvzVRXV1NVVdWoGF+3LxgZGTU6n83Pz0elUtGsIXPxEhNFV/aePQ1+DImkqZOSAjNmwO7dYiruX42iKFRWVqIoCkZGRqgaGJhqamqorKxsVOyoe7ysrCzMzMwwNTVt6DeJAu61a7BuHezfLw6pxoyBzp2FE01TCKgSiUQiuSMaDWRlwaFDEBkp/j5kiDATa94c9PT++nCuKAoVFRXo6OhgYGDQ4H2xurqa6urqRtWIQeTV2dnZWFpaYmxs3PgFV1XB00+L0cpDhjT++yWSJoaiwKuvwiOPCLODvzomiDX9NXHBysoKIyOjhixQBNiSEnEWFBoqCg6jR0Pv3n++1blEIpE8YIqLxXF3dTV88AGYmjad/aFJ6gQURTR2bN8unNJGjoTp08HSsmm8cBLJQ0ZTvGW7lzik0WioqKhAT08Pg0YUtRVFobS0lLKyMmxtbe+cS9fW/jq2PTQUrK1h8mThilPn9CiR/H24DrjU90nO2tJ5AAAgAElEQVQp6JX8raj7dc3JgY0bITZWiHfHjROuvM2aQWLiccLCwtDV1WXSpEmYmJiwYcMGzM3NmTx5Mnp6emzcuJFffvkFT09PRowYgYGBATt27ODo0aMYGhoyffp0WrZs+bubRVVVFRs3biQxMZHmzZtTUFCAjo4OdnZ2lJSUUFxcjKenJ0FBQRQVFbFixQrtY6tUKrZt28bJkycxNjbm+eefR19fn8jISM6fP4+FhQUzZsxg3759nD17lmnTppGXl0dYWBi9e/cmLS2NzMxMAgICePTRRwHIzMxk8+bNpKamYmhoSGVlJc8//zytWrW6++uZkMD2Z55hb0AA/v7+JCYmUlFRweTJk2nbti0Aly9fZvPmzWRmZtKmTRsmTpyIlZVVg4tSEonk/qmtFU2yn34Knp5isnB5+RXWrFlDSUkJgwYNomvXrqxevZqCggKefvppWrRoQWRkJImJiTg4ODBu3Djs7e2Jj49n9+7daDQahg8fTo8ePX63iKAoCnv27CEmJoZmzZpRWlpKdXU19vb21NTUkJ+fj7OzM0FBQRgaGrJp0ybS09N54oknsLOzY+/evRw4cAAdHR3Gjh2Lu7s7O3fu5MiRI+jr6xMcHMz169fZsWMHY8eOxdbWltWrV+Pi4oKhoSFnz57Fx8eH4cOHo6enR2lpKRERESQnJ6Orq0tJSQlTpkyha9eud38BFUUUqxcvhs8+E6KO22JYbm4u69evp7S0FC8vL44ePUqbNm0YPXo0lpaWKIrCzp07iY+PR1EU+vXrh5+fH4aGhg/qxyyRSB4i6hx5Dx2CtWuF/qxfPxg+HDp2hHPnTrN+/Xo0Gg1jx47FwcGBdevWoaury9SpUzEzMyMsLIzz58/j5uZGQEAAZmZm7Nq1i4MHD6Kvr09QUBDu7u6/m7PV1tYSFRXFwYMHad68OYWFhQDY2dlRXl5OYWEhbm5uBAcHU1FRwerVqwEIDg7GyMiIHTt2cOzYMQwNDXnyySexsrIiOjqaU6dOYWpqytNPP82xY8c4duwYU6dOpbq6mnXr1uHt7U1+fj7Xrl1j8ODB+Pn5ASIGR0VFcenSJQwMDCgrK+P555/H1dX17q9lYiL7nniCmJEjGThwIGfOnKGoqIjHH3+cDh06AGK88ebNm0lLS8PZ2ZmJEyfevTAkkfyFpKRAcPBOfH23Y2VlxowZM8jNzSUiIoK2bdsybtw4ioqKiIiIQK1W061bN4YNG0ZFRQWbN2/m3LlzmJubM2vWrHoPcIqKili/fj2XLl2iWbNmFBQUYGhoiLW1NQUFBVRUVNC7d28CAgK4fv0633//PW5ubjz++OMUFxcTHh7O5cuXsba25qWXXqK4uJiQkBDUajVOTk5MnjyZiIgI8vPzmTJlCmfOnCEuLo7Bgwdz8uRJysrKmDRpEm5ubsCv951ZWVkYGBhgYGDAM888g52dXeNfQEURL+KWLRAfD/b24nBq2LB77pS4fPkyq1evpk2bNujo6JCSkkLv3r0ZMmQIOjo6lJWVERUVxZkzZzA3N2f48OF06tSpUcIMiUQieZhRFMjMhPBw0adlbCxceIcNAwcHiIiI4MCBA9jY2PDss89y6dIloqOj6dy5M4GBgajVaqKiosjNzaVXr14MHjyYoqIiNm7cyJUrV7CxsWHWrFn1CmJzcnJYv349169fx9zcnMLCQkxMTLCysiIvL4/q6moGDRrEgAEDuHjxIj/99BPdunUjMDBQW0/IyMjAycmJ5557jhs3brB+/Xpyc3Nxd3cnICCAkJAQVCoVkyZNIiEhgUOHDjF06FCOHj2KRqNh8uTJtGrVCkVRSElJYcuWLeTn52sFGU899VTDGt5up6qK/KlT2WBsTL67O97e3hw5cgQXFxfGjBlDs2bNUBSFvXv3snfvXmpra/Hz86Nfv34NEwpKJH8yQtCrUFi4CSurBGxtbXnmmWc4f/48W7duxdvbm1GjRpGenk5kZCT5+fn06dOHQYMGUVBQQFhYGFevXsXW1paZM2fW+3uelZXF+vXrUavVmJmZUVhYiKmpKZaWltq44O/vT//+/Tl//jyrV6/Gx8eHgIAAsrOzCQkJITMzExcXF5599lnUajUhISHk5+fj4eHB8OHDWbduHXp6ekyaNIn9+/dz9OhRhgwZwtGjR1EUheDgYFxcXFAUhXPnzrFlyxYKCwvR19fH2tqa6dOnY2Vl1fgXMT9fjFuPjRWdE4MGwYQJ0KLFPeXKmZmZhISEoKOjQ5s2bfj555/x8PAgMDAQU1NTamtriYmJ4ciRI+jq6jJgwAB69erVKIMHiUQiqY+aGli9GqKixGRLtfrOOgF9fX3CwsLuqBOYNm0arVq1eiA6gR9//BEzM7M76gSioqJISUn503UCKIoYibF4sRDCvfkmODndcS+oy5vLy8vp2LEjR48exdXVldGjR2NhYXHLWRpAv3798PX1lWdpEskdqKqC4OBM9PV/wskpBz8/P/r378/q1avJyMhg+vTpuLq6EhsbS0JCAlZWVowfP55WrVpx7NgxYmJiqKqqYuDAgfTv37/eeuTRo0fZuHEjFhYWVFRUUFVVha2tLQB5eXnY2toyceJErK2tiY6O1sahli1bkpCQwK5du9BoNAwbNoxu3bqxd+9e4uPjtVqAyspKIiIiGDJkCG5ubqxduxZzc3Ps7e05ceIEnTt3JiAgACMjI6qqqoiKiiIpKQmVSkVZWRmjRo2ib9++DTu3qSsi7Njxq3nh2LEQECCmujUip607Lzty5Ij2Hl1RFCZPnkzLli1RFIXz588TFRVFfn4+7du3Z9y4cVhYWDT4MSSSerijoFeeLEj+FtQ1il27JsZlTJ4MJ07A66+LxrHAQNF8oVKBu7s7V69eJS0tjRYtWuDo6EhZWRnu7u6Ym5vz8ccfk5CQwNChQ9m2bRsrV65k3759bNy4kbFjx+Ls7HzHEUd6enq0aNGCbdu24e3tTXBwMOfPnyc+Pp7BgwfTq1cvlixZQnJyMhYWFri6uhIeHk5JSQnR0dHs2rWLSZMmYWNjQ3FxMWvWrOHs2bMEBwdjaGiIoih07dqVLVu2kJGRQcuWLUlKSuLkyZMMHDgQQ0ND3n33Xa3b0fvvv09qairjx48nKyuLc+fO4eJS73v+N7jU1hIXF0d2djYjR47k+vXrfPbZZ9TW1nLt2jVeffVV9PT0GDduHKdOneLtt99+8COgJBJJvZSUwIoVYrzklCniT3t7cHR0REdHh/3799OuXTssLCwwMzPDwcEBW1tb1qxZw4oVKxg0aBA3btxg3rx5XLhwgQULFuDn50ePHj3Iycm54xi4Nm3acOjQIUxNTZk8eTK6urqEhITQo0cPRo0aRWRkJLGxsRgZGdGtWzfCwsLIzs7m4sWLLFu2DH9/f7y8vMjLy+PIkSOEhIQQGBhI69atKS4uxsPDg6SkJJKTk3FwcCA/P5/t27fTuXNn3NzcmDNnDjk5OQB8++23xMTEEBgYiJmZGXv27GlYQQLE5jB4sBByfPyxKFTfhoWFBSYmJoSGhuLk5MSAAQP4+uuvOXLkCIqiEBUVxcKFC/H19aVXr17MmzePzZs3o9Fo7unnKpFIHk40GigoECKFGTPEZKDu3eGbb4TDUKdOwhSnTZs25ObmkpycjIuLC7a2ttTW1uLq6oqVlRWLFy8mNjaWoUOHcvDgQb7++muOHTvGypUrGTlyJO3ataOgoKDedejo6ODi4sKOHTu0wt2MjAx27NhB//79eeyxx/j+++9JTEzEzMwMLy8vQkNDKSwsZP/+/WzatIlx48bh5OSkFRXGx8cTFBSEpaUl1dXVPPLII8TFxXHt2jVcXFy4cOECBw8exNfXl2bNmvHOO+9QWVlJbW0t8+fPJykpifHjx1NaWsrx48dp2bJlg1/XlhoNBw4cIDU1lWHDhlFSUsKHH36odS167bXXKC4uZvz48aSmpvLKK69oRcwSSVNFo/Hk6NFj1NTUYGNjg6urq/bwH+Dtt9/m2rVr2vdrTEwM69evJzExkeDgYExMTCgvL6/3+iYmJtjY2LB161b69+/P+PHj2bVrF5cuXSIwMJAOHTowf/580tPTad68OWZmZmzfvp3Kykq+++470tLSmDJlCiqVitLSUj777DNqamoIDg6mvLwcfX19vL292bBhA3l5ebi4uLBnzx7UajUjRowgKyuLjz/+mNraWrKysnjzzTe1952nT58mKyvr7pMY6kOlgg4d4JVXRID19RUJ9ZQpEBEBN26IropG4OjoSFZWFnFxcXTt2pXWrVvz3nvvaWPt559/TmxsLCNHjsTCwoIXX3yRX3755d7WL5FIJA8JigLl5ZCcDAsWiDB9+rRoYl66VDhvOjiIr/X09GTfvn2YmJhgYWGBh4eH9iCtpKSE119/ndLSUnr37s3ChQuJj4/n22+/JSMjgylTpqAoClVVVfWuxdLSEjMzM3bs2MHgwYMZOXIkkZGR5ObmMn78eFq2bMm8efPIysqiRYsWVFdXs3fvXqqqqvj888+pqqoiODiYsrIyysrKmDt3LpaWlgQFBZGXl4eRkRGenp6EhoZSUlKirS2XlpYSEBDAuXPnWLp0KbW1tVy+fJnXXnsNR0dHxowZw6FDhygrK7s30d7/MNfTwwzYsGEDDg4ODB48mO+++479+/ejKAoxMTHMnz+fXr160bdvXxYsWEBYWJiseUiaMCqcnDqyZ88ezMzMtHGhoKCA9u3bU1BQwGuvvUZ1dTW9evXi008/5dChQyxbtozs7GymTJlCbW3tHeOClZUVpqam7Ny5E39/f4YPH86mTZsoKipiwoQJODk58dFHH5GdnY2TkxPl5eXs27ePqqoqFixYoBXklpaWUlpayvvvv0/z5s21ccHY2BgPDw/CwsIoLS3F0dGR6OhoKisrCQgI4NSpUyxbtoza2louXbrEa6+9RsuWLRk9ejTx8fFUVFQ0bErj79GsmRDwfvklzJkDly6JoLtwoRghVFHRqMtZW1ujo6NDeHg4rVu31sbis2fPoigKISEhfPPNN/Tv359OnTrx3nvvsWfPnjvWpSUSiaQhKAqcPCkG9bz2Gjg6/qoTuHbt2i06ATc3tz9UJ3DgwAEGDx5M796976oTmDhx4i06gTNnzvyuTiA9PV2rEzhx4kSDdAJnz55tuE5ApRLF6a++EnvDs8+KcVF3yZuNjY0JDQ3F2dmZxx57jCVLlnDs2DEURSEiIoJFixZpzyE//PBDoqOjZV4pkdwFAwNrqqvN2b59O+3bt8fExAQ7OzusrKxwdHRky5YtLFy4kH79+gHw3nvvcfnyZd5//326devGwIEDycrKuuN7rXXr1pw+fZrKykomTZpEs2bN+PHHH/H29mbChAns3buXsLAw9PT0btEr3bhxg08++QRfX1969uxJTk4O58+fZ/ny5fj7++Pp6Ul+fj5t2rTh2rVrHD9+nObNm1NTU0NkZCTu7u5069aN+fPnc+XKFW1+uGbNGkaMGKE9q3J2dm74C6ZSiaD/xBPw9dcwaRKEhQkhWWioEPs2sP6ro6ODo6MjW7duvSUXX758ObW1taSkpPDKK69gZ2fHmDFj2Lt3Lx9++CGlpaUNX69Ecg9IQa+kyVNTI5LxefPg+echI0OMy1i2TJzL3T79wczMjCeffJJz585RUFBASUkJGo0GPz8/ysrKtG6Qfn5+DBkyhG3btpGVlUV6ejplZWUEBwfj5eVVb+eHjo4OVlZWGBgY0KVLF7y8vBgwYACWlpZ4eXnh5+eHjY0N165dQ09PT9vVUjc+OD09naqqKmbMmEHLli3Jzc0lIyMDgJdeegl7e3tsbGzQ09MDwNTUFGNjY1q3bk379u0ZOHAgxcXFFBQUUFVVRVJSEv369aNbt24MGDAAtVrd4EKIClHQNTQ0pEOHDnh4eDBw4EDS09MpLS0lKSmJgoICJkyYgI+PD6+//joHDhzg7Nmz9/4DlUgkDUJR4OpVmDsXdu4U7rzjxoGJiYh5RkZGTJkyhbKyMlJSUqipqaG4uJh+/fqh0WiIiorSduIFBQVx5MgRLl26REZGBtnZ2fTt25eAgIB6x2SoVCrMzc0xNjamY8eOdOzYkaFDh2Jqaoqnpyddu3bFy8uLy5cvo6OjQ/PmzbUdf8XFxaSnp5OXl8fw4cPp378/RUVFpKenU1xczMSJE+natSuWlpaYmJgA4vlYWFhgZ2eHh4cHvr6+mJqakvU/8W1CQgLdunXDx8eHAQMGUFVVRXV1dcNfUH19UZh2chIuvSUlt31aX3uAV/f8XF1duX79OmVlZWzatAk/Pz/8/f3x9/dnyJAhrF+/npqamnv46UokkoeRvDxRXH7pJZHH+vkJd96nn4aWLUWYqsPMzIynnnqKK1eukJmZSVlZGZWVlfTr14+Kigqio6MJDAzEz8+PUaNGERcXh1qtJj09naKiIsaNG0ePHj3qzWdVKhWWlpYYGhryyCOP4OXlhb+/v1a826tXL5ydnbl69Sr6+vq3iOoKCgq0efOUKVPo0KEDeXl5pKenU1NTw3PPPUerVq2wtrbWjlUyMTHB1NQUFxcXPDw86N+/P5WVleTn56PRaDh27Bi+vr7afDY3N7dR+ayZri5GRka4ubnh4eGhbWYpLi7mwoULpKWlMXHiRB599FHeeOMNTp48yfHjx+/5ZymR/BkYG9sTFBTEwYMHqa2tJT8/H1NTU3x8fMjOzubEiROMGzeOxx57jO7du2tdCTMyMtBoNMycOROHOhXU76Cnp6c9hPH29qZLly706NEDe3t7vLy8GDRoECCcXuqce0E4FuTk5JCRkYGuri6zZ8/G1NSU7OxsMjIyMDIy4rXXXsPCwuIWJ2xzc3MMDQ1p37699n2akZFBaWkp+fn5XL16lcGDB9O9e3f69u3LtWvX7v9F1NcXLmPTpokAPH68EPS+8AJ8953oGG5grDEyMsLMzAx7e3s8PDy0kxqys7MpKCggOjqaCRMm0Lt3b6ZPn46trS0RERH3/xwkEonkH0pFBcTFwbvvCvFFQYHov12+XEyusLKCm02F6ibo7N27Fx0dHXJzc7G1teWRRx7h2rVrXLlyhXHjxjFkyBDat2/P5s2bb9mvXn311TsK3/T19bGyssLc3JwuXbrQrVs3unTpgrOzM15eXgwdOpTS0lKys7MxMjLSimtramrIzs5GrVZjZGTE66+/jp6eHllZWajVaiwsLHj11VcxNze/Jae2sLDAwMAAT09POnbsSP/+/UlLS6O8vBy1Wk12djb+/v74+Pjg4+NDWlrafQnf9FQqLE1NMTExwdPTE29vb9q3b8/169cpLy8nMjISHx8fhg4dysCBAwkICGDDhg1UVlbe82NKJH80LVu6EhgYyJ49e7Rxwd7enk6dOpGamkpaWhpjx45l6NChtGvX7pa4oKenx6uvvnpHVy0DAwMsLS2xsLDgkUceoVu3bnTu3BlnZ2c8PT0ZNmwYRUVF5OTkYGxsrI0xN8cFY2NjXnvtNfT09Lhx4wZqtRpLS0tmz559S1you0e/OS7069ePtLQ0KioquH79Onl5efj7+9OjRw+6d+9+33EBHR0x/tLHRwi5PvtMCB9eeUWIfPfuvaOgq77XqmPHjjz66KM4Oztr8/2NGzfi7++vjS99+vQhJCRECnolEsl9k5oK//kPPPkk9O4tzs7qdALJycm36AT69u17V51AaWkpwcHBdOrU6Z51Ar6+vtjY2HD16tUG6wTS09OBB6MTyMzMbFx81dER7rzvvSfqJwsWwLffCjf33+H3ztLatm2rPUsLDw+nb9++DB48mCFDhjBo0CBCQkKobWRjtUTysKGjY8CoUeMxNjbmxIkT2pjRp08f9PT0iI6O5tFHH2Xw4MHaaWhnzpxBrVaTlZVFly5dmDRpkjZ2/B5mZmaYmJjg5uaGp6cn/v7+WFhY4OnpSefOnfHx8dEKbm+OQ2VlZVp9ga+vLwEBAZSWlpKRkUF+fj4jRoygf//+WvMx+DU/bNasGR06dKBHjx7Y2tqiVqsBce5fdxb12GOPoa+vT0Ujm8r+98KBjQ2MHi3s2qdOhe3bhbBs+XIhtrhLTKwvF7927Rrl5eVa86+6c7dXXnmF2NhYrly50vj1SiSNQAp6JU2SOkfeM2fgrbfgjTfAwEC4mM2bB716wR32Ijp16oSVlRUHDx7k5MmTdOrUCUNDQwoKCsjNzeWTTz5h9OjRfPPNN1RWVuLr60vXrl154403ePrppzl//nyjkl0dHR3t16tUKlQq1W+6X3R0dBg2bBitWrVi5syZPPfcc2RmZjJx4kT09fWZMWMGL7/8Mrm5uXd8rLobCEVRtF2Ahw4d4vLlyxw5cgRPT8/7GutZ91wURUGtVmtvSgBsbW3RaDQUFRXd8/UlEsndqa391ZUGYNEi0SR7+1vbyckJHx8fdu3aRVpaGrW1tbi4uFBaWkpRURGrV69m9OjRvPLKK9TU1ODk5MSkSZNYsmQJwcHBxMXFNaorti621MU7HR2d3/3+Dh06MHz4cD7++GOmTp3KoUOH6NGjBz179uTdd9/lqaee4syZM3d8rNtjafv27UlMTOTChQv8/PPP2Nvb1zsqs14sLcXIoCtXYNUqUZS+Q6yve35lZWXk5eXh6OgICAGMvb09WVlZsvAskUjuSG2tECds2ABPPQXbtom6wtKlotBsY1P/5B93d3dcXFw4cOAAycnJtGzZEnNzc4qKisjPz2fx4sWMHj2azz77jKqqKry9venXrx/vv/8+06dP1xZ9GsrtMf738lmVSkXfvn3p0qULr7/+OjNmzOCXX35h1KhRODg48MILL/DCCy9om9Xu9Fh111epVLRu3ZrDhw9z+fJljh49ipubW70NJw19Ljfns3UNKgA2Njbo6OiQX09RWiJpKujo6NCnTx9KSkpISkpiz549+Pv7A2iFu2+99RZjxoxhy5YtVFZWMn78eMzMzHjmmWeYOXMm2dnZjX7Mm/M84DdxQF9fn6lTp1JaWsr06dN5/fXXqaqq4sUXX+TixYs88cQTvP/++5SVld31sUDEHFNTU8zNzUlISOCXX37h+PHjdO7cuWHj1RqKqalwIfvqK5g5E44fFx0Vn34qTgDvkhfezs25ak5ODrW1tdjY2PzvoUyxtrbWFqglEolEIqithcJC2LpV5MaLF4Orq6h5zJ0rNGX1lTT19PQYOHAgaWlppKSkEBMTw6hRo1CpVGRnZ5OamspLL73EmDFjiI+Pp7q6munTp1NUVKTdrxpbz7y55lHfvmhkZMQLL7xwyx6oUqmYPXs2CQkJBAcHs3DhwrseTOrq6mrz12bNmqGnp8fBgwe5ePEiZ8+exdPT88Hui9xa88jNzdXWPHR1dbG3tycnJ0c6qUmaNPr6+gwaNIjU1FQuXLjAtm3bCAwMBCA7O5srV64wc+ZMrdN1TU0NTz31FLm5uUybNo233nqLktsa/u9EXf538z0z/H5cmDlzJsnJyUyZMoUPPvgAHR0dXnnlFfbt28fkyZP58ssv7xoXbr6vrbuPPXToEBcuXCA5OfnBxgUdHejSRRy+LVwo7NE/+UTkzQkJUFra6Fy5LsYUFxdTVFSkjTEGBgbY2tqSmZn5YNYukUgeShRF5JVffgmdO4sp6zeXEm/WCSQlJTVYJ/Dmm2/y9NNPk5KSct86gdu//2adwKxZs3juuedQq9VMnDgRAwODBusEbs5L9fT0cHJyukUn0LFjx3vTCRgYCFehhQvh8GFxlpaeLkbO3YGbY35paSkFBQXaBvO6s7Ts7Gx5liaRNABbW1sGDBjAzp07UavVZGZm0qFDByorKyksLGTz5s0EBgby1FNPUVNTg6WlJc888wwrVqwgKCiIzZs3N8qI6mbdUd2/f++96uzsTFBQEEuXLtXqCzw8PBg2bBjz589n6tSpHD58+I7v89vP/T08PDh16hTJyckkJiZiamp6x2a7BmFkJA7gFi+G2bOF2OyZZ+C//wW1WjhJNpC6uF5bW4taraZ58+baMytbW1sqKyvvWv+WSO4XKeiVNDmKiiA2Voh4X3sN7Ozgp59EY5i3t4jDd0KlUmFnZ8eIESNYuXIlFy9e1CavlpaWNG/enDlz5hAeHs7+/fvZtWsXDg4OzJs3j40bN6Kvr8/SpUsfeGKpKAq2trYsWrSIkJAQSkpK+Pbbb3F2dua///0vK1as4MqVK6xdu7bB1zQyMiIoKIhz584xf/58bGxsmD9//gNbs42NDSUlJVoXzKKiIq2Tk0QiefAoiqiPrlolzBDGjxeO5E5Ovy/40tXVZdKkSezdu5e4uDjc3d0x/Z/jipmZGc899xzh4eFs27aN48eP06FDB1566SW2b99Oz549WbRo0R8iaDIwMOCtt95i69attG3blkWLFqGrq8vcuXOJjIzEzMyMr776qlEduUFBQRQUFLBgwQIyMjL48ssvMTc3b/zi7OzEixoVJTabBmBkZIS5ubm2kFLnkufg4PDAD9QkEsk/A0WBX34RE96fego2b4YZM0ROO3Ys2NvXL1aow8LCgrFjx7JhwwZOnTpFx44d0dPTw8LCgmbNmvH2228THh7O7t27SUhIwMnJiTlz5hAVFYWNjQ2LFy9+4C7iiqJgZWXFRx99xMaNG9HR0WHp0qXY2dnx5ZdfsnbtWvLy8vjhhx8afE09PT2Cg4NJTU1l/vz56Ovrs3DhwvtqULsZGxsbrcMxoB2ZV+c2KpE0XVR06NCBPn368NVXX5GdnU2HDh1QqVRYW1vTsmVLPv/8c8LDwzl69CirV6/GycmJ5cuX89NPP5GRkcGqVase+KoURaFNmzb89NNPfPvtt5w6dYrQ0FA6dOhAWFgYX331Fbt27WL79u0NvqaDgwMBAQHs2bOHBQsWaKfDPPA8S6USlo8DBsA338AXX0BWFjz3nMgPDx9u9HhhEOMmdXR0tJpKPOUAACAASURBVEKxiooKioqKcHJyerDrl0gkkr8pGg1cuAA//CCa2n78EYYPF01vL74I7duDoeGdr6FSqejevTteXl588cUXlJSU4O7uDkDz5s1xd3dn6dKlhIeHk5iYyBdffEGbNm1YtWoV3377LSdPniQ8PPwPeG6aW/bA3bt3s3XrVrp3787mzZv55JNPCAsLY//+/Q2+pqurK/7+/kRGRrJw4UJGjhzJs88++4fVHwwNDbGwsNDWPDQaDQUFBdjZ2T2wnFwi+WNQ4ePjg4eHB1988QXl5eW4ubkB4j6wffv2LFu2jPDwcE6cOMGnn36Kq6sra9asYfny5Rw7duwPmaig0Wjw9PRk48aNfPnll8TGxhITE0OPHj3YsmUL8+fPZ926dSQkJDT4mu7u7gwcOJDw8HAWLVrEmDFjePLJJx9sXBAj4cDDQwggQkJEp8XHH4t8edMmIexq5LmZiYkJJiYm2hhTU1NDQUEBLVq0eHBrl0gkDx2KIuqsWVkiZN2cS9bpBEaOHMnKlSu5cOHCLToBGxubenUC4eHhf6pO4L///e8tOoHU1NRG6wQmTZp0i07g448/vvdF6umBl5dohm7dWgjhtm0TLmwNXI+ZmRl5eXnAr2dp9vb28ixNImkAKpU4D09MTCQyMhJXV1esrKwwNDTE3NycSZMmER4ezubNm0lKSqJnz55MmzaN2NhYRo8ezeLFi7WO3w+aWbNmsX37dvr06cOiRYsoKSnRagHatGnDokWLKC8vb/D1xo8fj0aj4bPPPuPkyZMsWrSIFi1a3H+sUKnAwkKM/vn6a9GwlpgoihELF4rR8I0UPdvY2FBYWKjVNRQWFmJsbIypqen9rVUiuQuyIiP5y1GUXx15t2+HWbPE2Vr79sK97I03hJhNR6d+B7Pb0dXV1Y7wvHbtGm5ubqhUKiwsLHBzcyM6Oprs7GwqKiooLCzk4MGDxMXFYWFhQdu2bTE2NiY5OZl33nmHq1ev3rZeRds5otFotF3Sdf9f9391f9bW1qIoCtXV1VrBhY2NDa1atUJXV5etW7eSlJSEo6MjTk5OGBgY3PK9t1/v5seqqKhgy5YtBAUFsXz5cl5//XXt6I4GvfZ1H/U8J09PT6qqqkhISCArK4sVK1bg4eGhLZhLJJIHh6JAcbGokUZGwttvQ3AwGBvXH/tUKhUdO3bE1taWrVu34ufnh0qlwtjYmO7du7N9+3YuX75MdXU1hYWFXLp0ifXr12sPnExNTSkoKOD9998nISHhNwWK2+PY7fHo5nhx89eePXuWiIgI9PT0aN++PSYmJhw7dozY2FhMTExo164dxsbGt1ynLt7V9xhhYWH06dOHZcuWMWfOHDp06HBvL7RKJTaYWbNEIp+SArc9h5vXoSgKJiYm9O/fn71793Lx4kVSUlLYvn07Q4YMuePoEolE8nChKEKskJEh3CFmzoSffxZ1z6+/hpEjxfR3laphOW2dO2d5eTmnT5/WjnozMzPDy8uLLVu2oFartd3ZiYmJREdHY2RkhJubGyYmJly5coV33nmH8+fP37ZW5Tf55s0ft+e2N3/twYMH2bVrlzZvNjAwYOfOnRw5coTmzZvTqlUrDA0NfxNT64vxNTU1bNq0iVGjRrFs2TLeeuutRovgbs5nb//Tzc0NAwMD9u3bR3Z2NitXrsTZ2ZlOnTo16jEkkr8CPT19xo0bR0JCAvr6+loHWFtbW5o1a0ZMTAwlJSWUlZWRn5+vbeKyt7fH2dkZQ0NDDh48yJw5c8jJybnl2nXvc6De+9i6z90cK8rLy4mIiCAlJQUXFxccHR2prq4mJCSEtLQ0WrduTfPmzdHT09PmkLff1958XY1GQ2ZmJgcOHOCVV15h2bJlvPDCC5iYmPwx7i11QVhXVxxSzZ8vxgsbGYk5nbNnQ3y8KFDc9Pg334vfHmeaN29O165d2bZtGxkZGezcuZPU1FQGDx784NcvkUgkfxMURTjyXr4sTB5nzfrVHP3bb0W9w8yscfVeAwMDJkyYwLZt22jRogUmJiYAtGjRAl1dXeLi4qioqKC0tJS8vDwiIiI4f/48zs7OODg4YGBgQFxcHB999NFvmpvryyXrq8vW/V9JSclv9sDy8nJWrVpFbm4ubm5uWFlZoaen97vXur0WoigKv/zyC4mJicyZM4elS5cyffp0DAwM7mtfVABNPbUPY2Nj+vbtS3x8POfPn+fSpUts2bIFf39/7dQ2iaSpoq8v4sKWLVto1aoVRv9zg3F2dgZg165dVFRUUFJSQm5uLuHh4Vy6dImWLVtib2+PgYEBsbGxfPzxxxQUFNxy7bvFg9+7d1YUheLiYtatW0d6ejpt2rTRxoWffvqJvLy8340LN+fLN/+97uPChQskJSUxd+5cli5dytSpU+87LtSLSiWCc7NmvwbtkSMhNFQIe1euhLw8UQD53+PXVyfWaDSYm5vTr18/duzYweXLl0lKSmL//v0MGzZMirskEsk9oSiwf78wUHj9dbC1/W0+qaury8CBA39XJ+Du7l6vTsDc3LxJ6QTutv/cr07gd1GpxFi5116DJ56AJUuEYKO8/I5naRqNBlNTU/r168eePXu4ePEiycnJ7Nixg6FDh97XNDaJ5OFBRatWrXB3dyckJAR/f39UKhWGhoZ069aN/fv3k5KSoj33T0tLY9WqVVRVVdGxY0dMTU2prKxk3rx5bN++/TeTJOqLJ7ef4dx+JpSamkpISMgt+oLk5OTfaAHqO1e6/e8AmzZtwtPTk6+//poPP/wQb2/vB5cb3lz/9fERjr1z54oc9s03xVj4y5dF0eJ3dA43x1mVSkWXLl3Izc3l6NGj3LhxgxUrVuDt7Y2Li8uDWa9EUg+6//nPf+70+Tt+UiK5XxRFiB527hSGOEePitrA229D794iX7xXIwBbW1tOnTrF8OHD8fDw0Nq4+/j4cPLkSdauXcvhw4dxcHBAX1+fNWvWEBYWhrm5OTNnzqSoqIglS5bg6OhI586dtdetqqoiNDSU9PR07YiIqKgocnNzMTU15dSpU5w9e5aSkhL09fVZt24dRUVF5Obm0qpVK1avXs2mTZu0Y4kzMjJYuXIlUVFReHh4MHbsWFasWIFareb69euUlZWRmJiIWq3Gw8ODLVu2kJWVhaGhIZ6enpw/f56wsDAiIyMJDQ0lIiICOzs7WrdufddNT0lLI3r9es45OHDjxg2cnJwIDw8nLy+PFi1a8Oijj+Lp6UlERARhYWEYGxvz73//W7pSSiQPGI1GNIe995749yefiDFBDYl/pqamqNVqOnToQN++fbWxztvbm4yMDNauXUtcXBzGxsa0aNGC9evXs2HDBrKyspg5cyZ2dnZ8/fXXFBYWMnDgwFvGa8TGxnL8+HHS09OxtbVl06ZN5OXlUVtbS15eHnFxceTn52NjY0NoaCg5OTmkp6fTsWNHNm7cSGhoKJWVlcycORMDAwNWrVpFWFgYhoaGPPfcc2zZsoXTp0+Tnp5OSUkJx48fJzc3l5YtW3Lo0CEuXbpESUkJjz76KAUFBaxZs4bo6GhCQ0NZv3491dXVPPLII42PRzo60K6dsEP+8Ufw8eFGZSVhYWHk5uZiYmJCZmamVvzl5+dHz549qaio4Mcff+TAgQMEBgby+OOPY2hoKOOhRCKhogKSk4UzxGefiTDz7rtCqODhIZoz7gVra2tSUlLo37+/Nt6pVCoeffRRzpw5o3X1sba2xszMjLVr1xIWFoaOjg6zZs2itraWJUuWYGZmxqOPPqq9bm1tLeHh4Vy+fBm1Wo2RkRERERHk5+djYGDAxYsXOX78uLbTeN26dRQWFpKZmYmbmxvr1q0jLCwMS0tLXnzxRfLz81m1ahWbNm3C2dmZKVOmsHr1aq5du8b169cpLS3l+PHj3LhxA3d3d7Zv345arUalUtG5c2dSU1PZsGEDmzdvJjQ0lI0bN2JhYUG7du3uns+q1ewMCeG4jQ1qtZq2bduyadMmcnNzsba2plu3bnTp0oWYmBhCQkJQFIU5c+bg4uIi47ekyZKTIw6mpk0DZ2dHjh8/zoQJE7S/twYGBnTp0oWEhATWrl3LyZMnadeuHYWFhaxatYrIyEjatm3Ls88+y+XLl1m+fDmdO3embdu22scoKChg/fr15OTkUF5eTm5uLjt37uTGjRvY2NiwZ88e0tLSqKmpobS0lE2bNlFYWEh1dTWmpqb8+OOPbN68GW9vb6ZNm8a5c+f44Ycf2LZtGwMGDKBnz55888035Ofnk56eTnFxMSkpKWRmZtKyZUvtfaednR2urq4cP36csLAwwsPDCQsLIyYmhrZt2/7xLi56emKCQ+/eMHQoFBSIMWxxcUJpZm4OpqacS05m8+bN5OTk0KZNGw4cOMCVK1coKyuje/fu+Pr6cvbsWVatWsWVK1eYNWsWPXv2lM6GEonkoaSgQIh3v/5amDbY2MC//w2TJkGHDmBi0nAR7+04ODiQlJREUFCQdo8wNTXF09OTnTt3EhISwtmzZ+nYsSNqtZoVK1YQHR1Nt27dmDZtGqdPn+b777/Hx8fnlsO3zMxMQkNDtQ6SV69eJSEhgczMTJo3b87WrVvJzMxER0eHrKwsYmJiyM3N1Taw3LwHTpgwgZ9//pkffviBHTt2MHbsWNzd3fn2228pLCwkIyOD/Px8UlNTycnJwdbWVrsvtm7dGhcXFw4fPkxYWBhhYWGEhoaye/duOnbsiLW1deP3xdpacsLCCMvIINfQEAMDA/Ly8ti1axc5OTn4+vrSs2dPAFasWMHu3bsZMWIEkydPxsjISObMkiZJbCw4OECXLiIunD59mqCgIGxtbbWNsB07diQ2NpaQkBCSk5Px8vLi+vXr2rjQo0cPnnjiCU6ePMmKFSvo2bPnLc2larWaDRs2kJeXh46ODpcvX+bQoUPakbvR0dHcuHEDPT091Go1O3bsICcnB0NDQ6qqqvj++++JiYnB39+fsWPHcuTIEX744Qfi4uKYMGECbdu21cYFtVpNbm4uV69eJS8vD2trazZu3Eh+fj6urq60aNGCgwcP3hIX9uzZg6enJ82aNfvj3qd1DmcdO8KIEeDuDuHhQtRbUADW1mBmxnW1mo0bN5KXl4eVlRW//PILR44cITc3F19fX3r37k1ubi4//fQTR48eZdKkSYwaNQp9fX0ZYyQSSaNQFDFB/YMP4OWXwc+v/nO0Op3AsGHDtBOP6nQCJ06ceGA6AYCoqCjy8vLq1QkUFhY2SCfg7u5er04gMzPzgesE7oiuroj/PXtCWBjs2AGurtzQaAgNC9M+34yMDPbv309OTg59+/alV69elJWVsXLlSuLj4xk9ejQTJkyQZ2kSyR2orRW14M6dwdPTkMLCQhwcHBg6dKg2dnl5eVFaWsrq1auJiYlBR0eH1q1bExkZybp167hw4QIvvvgi7dq147///S+pqam/Mabav38/+/btIz09HUdHR22ts27C4ebNmykoKMDW1paoqChtHGrfvj3R0dFs2LCBzMxMZs6cia2tLWvWrNFqAV588UXi4+M5ePAgmZmZFBcXc+LECW399+zZsyQlJZGXl0efPn2orKxk9erVbNu2TXvun5OTg4+Pz4OPFfr6wkGyXz+xcRw7BsuXC9Ov5s2pNTEhYutWrly58ptcvG3btvTo0UN7LlYXv99++21sbGxkXJPcL0XAF/V9UnWXDs4/oL1TIhEJd1aW2Ji2bRPnZCNHwpAhYgLm/aDRaFCpVJSUlPDpp5/y9ttvN9ruXFEU8vLy+M9//sOzzz7bZB28srKymDt3Lm+88QatW7dGo9Ewb948cnNztSPu70hCgrCZj4n5cxYskUh+Q3W1eAsuWyam/77wgtAN3I26WFdVVcXy5csZNWrULSKNhlDXwbtkyRLatWvHmDFjmmTiWVlZyZtvvsnUqVPp1q0biqIQERHB8uXL2bp16707xpSUCBW1SgULFtx9xqdEIpHcRk0NnDoF69fD6dPQtSuMHSsKL/r6937duhhfVlbG559/zr/+9S+sGpkkK4pCUVER8+bNY9y4cdpD+qZGUVERb731FrNnz6Z9+/ZoNBqWLl1KYmIi33///d2d0BMThWPEnj1/zoIlkj+BlBSYMUPD7t0qiovzWLJkCe+88w6GjcxVFEUhMzOT//u//+P9999vkq4BiqJw+vRp1qxZw9tvv421tTWVlZW88MILdO3alRdffPHPFcXWFStiYyE6WnTeBQYKsW/z5veuQJNIJJJ/OHVTh3btElOH8vLEWdnIkeDmJvQA90Ndfpyens6aNWt49dVXG10LUBSFtLQ0PvjgAz788EMcHR3vb1F/AIqisH//fnbv3s2bb76JqakphYWFPPnkkwQFBTF+/PjG122qqoTL5pQpovgukfzNURR49VWFzp0Vpk9XkZaWxvr165k9e/Y9xYXU1FQ+/vhjPvjgAxwcHP6gVd87iqJoHR3feOMNjI2Nyc/PZ9q0aTz11FMEBgb+ufXcigoxjig8XHQ2d+0KEyeK6RfSfVEikfzBlJbCSy9BmzbCZPH3yiQPu07go48+Iicnp2E6gYaSmyu69Y4eFUrqAQNEg7REInkgiFs2heBghYEDa1m9ejXe3t506dKl0XledXU1K1asQE9Pj+nTpzdJd+yqqirmzJnDiBEj8PPzQ1EU4uLimDNnDnv37m10DbzR1NTAhQsQFQUHDkDr1jB5snDzlVNqJH8u14F6D23kTiv5U6mqEo68MTHift/FRYzD8PQUjb4P4pxu586d6Orqcu7cOXr37q0dv9YYampqiI+P13btNVVqa2s5f/48J0+epLS0lMuXL3P48GGmTp0qnYAkkiaOokB+vmgA279f6Ep9fMS034Zw9uxZLl26RFVVldZ99144deoUjo6OTXoksKIoXLlyhaSkJIyNjVGr1YSHh+Pn54f+/SjmTE1F1eeNN8T4uOefl4m6RCK5K3VihfPnYcUKcd8/dKhozGjRQoSR+z1Li4+Pp6ysjKtXr+Lp6YmFhUWjr6HRaDh06BC9e/ema9eu97egPxCNRsPFixdJSkrSjm/atWsXAQEBTbLYJJH8WdTUhHHwoCMHDuwjICDgngqZZWVl7Nq1ixkzZmjHDjdFKioqSE5OJikpCVtbW06fPs3169d54okn/vxmM5UK7O2F6GnECDh5UgT71ashIABGjxaf19eX4l6JRCJBNClnZoozsLVrxWSKoCDo00f0QejqPphwuXbtWtq0acOOHTsICgq6p8bewsJC4uLiePnll5ukaK+OkpISzp07x6lTpzAzM+PIkSOUlpbi6ur6Vy9NImlS7NmzBje3tsTGxvLEE0/cU1woKChg165dvPzyy9jb2/8Bq3ww1MWFpKQkTE1NOXToEFVVVbRp0+bPX4yRkQjyXbvCtWtCCDF7tnBxnDFDTEUzM5O5skQieeBUVsLSpeLvL7xQ/1GO1Akc5oknnniwOgFra3GWtmcPfPopJCXBU0+J/5fxXiJ5IJSWpvLzz8eorjamqKgINze3e6qLpqSkoKenx9ixY5usXkhRFK5fv86pU6ewtrYmNzeX0NBQevbseX/n/g1FT0/krm5uQsi7cyf85z/QqhU8+6wYLWRuLuOb5C9HOvRK/hSqq+HcOdiyBQ4ehLZtxflY9+4PrrBbx5kzZ1i/fj2dO3cmICAA43uccVz33miKbpV11NbWcvjwYXbv3k1hYSHW1tb069ePXr16NWyDlg69EslfgkYjYuLixUIY9tZbImdsTLi5fv06a9aswcLCgokTJ2JjY3NPa7k5D2iq8U5RFC5cuEBkZCTZ2dmYm5vj7e3NkCFD7r9LT1Hg0iXR1v3MM0KkIQVkEomkHkpKID4eQkOFgePQocKRt87c60GF0fPnzxMSEkK7du0IDAzEvCHW7b/D3yGfVRSF48ePExsbS35+PlZWVvTu3Zt+/fo1TNArHXol/0BSUiA4OJ4BA6IZMKAfgwcPvrtb9e/wd8jzQExj2LdvH/Hx8ZSXl2Nvb8+QIUPw8vL669etKKKgkZgolGq//CLGTY4eLYq7f0aRWSKRSJogNTViQsX27SI/dnSExx+Hvn2FU9qDDt/bt29n7969DBs2DD8/v3s6mPy77ItlZWXs3r2bQ4cOUV1djZOTE8OGDbvnA13p0Cv5p1Hn0FteHkOzZgcYPnw4vr6+9/T++LvEhdLSUnbt2sXhw4epqanB2dmZ4cOH4+rq+teuu+71S0uDiAghhnBwEPbsffsKoZdEIpE8AGprRT12zRphqtCyZf35Zp1OoFOnTowaNeofrxM4cuQIu3bt0uoE+vbtS+/evf8YIZ+iiKLV55+LH8obb4jaSBMVDUokfxeqqmDKlGwMDFbTtSsEBwdjZ2f3j81v66bnbNy4EbVajbGxMZ07d2bYsGGYmJj8ueuue71u3BDjhrZtAxsbYewwaJBwpZRI/jju6NArBb2SPwxFEZtPair88IM4/+rRAyZMAHd34djQRPeQhwcp6JVI/nRqaoQj7yefiKk0M2aIvFDGw78QjQY2bxaVoMWLRQFC/kAkEgkin1UUMVEyIQG+/164844fL2J4y5ayXvmXIwW9kn8gKSkiR9y9Ww4PaDIoCpSXi7HCmzcL9ZqXl/hBubn9Meo1iUQiaWLU5cXnz8PKlXD2rJg0NG6cqPWamspQ2CSRgl7JPwwh6IVHHoFp02TcaTJoNHD1Khw+LMS91dUwcaKYemFiIoon8oclkUjuAUWBixfh5ZeFL8uwYbIe+5eiKJCXJ6YZxcWJUcz9+wvHSxnnJZJ7Qt6yNRE0Grh+XRwGhoYKI4epU+Gxx34Vt8k4J3mw3FHQ23iLF4nkLtSNIT5xAsLCRJF3wAAh6nV2lvftEonk4aTuHnfNGoiOhn/9C/z95bTeJoFKJZwjcnPh3Xfhq6+ESk8ikTzUaDRifPDu3WKCpEYDkyaJgoqZmSwcSyQSyUOFSiWECF27QpcuoFbDxo3CjcbJSXQu+/hAs2YyuZdIJP84FEXkxceOCY2WWi0mVbz1FtjZyVqvRCKRSBCbQevW4iMwEPbtExMuQkLEpjFoELRpIwRfEolE0ggyM+G998SUtCFDZE32L0elEg7ss2dDp06waJG4UXj6aXFzIG8MJBLJ3xUdHXBxEQeBo0fDjh2wapX4GDFCiN6cnWWck/xpyDsnyQOhzui5ulrcp//0ExQUiLj20kvQrp2cYC6RSB5eFEVMavi//4PSUuHO27WrzPeaDCqVKCZPniy6UBYtgg8+AHNz+UOSSB4y6nLaggJYv14MMWjWDIKCxLRI6agukUgkDzkqlShuODuLDr3AQNH58d13wq5yzBgYNQqMjH79eolEIvkbUjepIi9PiHi3bBGGNIGB4Ov7q2mDRCKRSCRa6nJfExNhodmnj3A427oVNm2C3r3hySeFkYJ0OJNIJHdBUaCsDL7+GuztIThY9gQ0GVQq4VY0ZIhocl64UExQmzsX2rb99WskEonk70Zd7KorgPj5wd69sG2bcLMcMQIef1w0Ntz89RLJH4BMeyT3TW0t5OTAoUOi2basTCTVAweKOCaFvBKJ5GGmuhr274fFi6FnT3j+eREbZX7XBDEyEl3Fb7whbOVnzRJFCYlE8lBQVQWpqbB9uzhratUK3nxTGDHK8cESiUQi+Q0qlXAZmz5dWAXt3y/GcaxZI1wcBg0SB1vyxFEikfyNUBQoLxd5cVSUmKLburXIix95ROTFUsgrkUgkkgZhYSHcefv3FxvL2rXCwbFHD5E/d+ggxL+y4CKRSH4HRRGNZcnJwoPFxOSvXpHkN6hU4OUFX34pmpxnzoQZM8REzLpGZ4lEIvk7Y20t6rxDh0JSEqxYIYolY8cKx97WrWXtV/KHIX+zJPdFdrZorN25U+RlY8aIEfJyyqREIpGIBofVqyEyEiZOFM0OUh/ahFGpwNER3nlHdBO3ayc67eRppUTyj0ZR4MwZCA+Hn38Gd3cRBnx95X24RCKRSBqArq4oggQGwuDBsGeP6AyJjBSuZBMmgKvrX71KiUQiuSsVFXD8uJhUcfEidOsGH30E3t5gaPhXr04ikUgkf0tUKuFw1qEDfPghnDsn8uS5c8VI4+HDxaGigcFfvVKJRNLE+PlnoRGdO/dXY29JE0SlAktLYZDj6grLl4ubiWefFePuJBKJ5O+Ojo7oKunVSxRIDh0SB4qRkWK055gx4OYm9QSSB448opY0CkWBmhoxOj4qSoxbc3aGF14Q4+OtrGRCLZFIJIoC6enwxRdw5QosWCBqllLM+zdApQJPT6Hm++gjsLMDHx+5uUkk/zAURQgWfvkF1q2DI0eE5mrBAjEVzMhIvu0lEolEcg+YmAhRQr9+kJICoaHwzDPChSw4WGwyxsZyk5FIJE0CRQGNBgoKIDFRGM3k5oqzqNmzRc1XCnklEolE8sCoq7u6u4NaDbGx8M03wrk3OFiIJJo1k2IIieQhR1Hg8mX4+GNh6t2zp7yF/lugqwvDhok4P2+ecOv997/F4agc5yyRSP4pGBmJ6RM+PkIEsmqVGM/s6wtTpojRn4aGcuOSPBCkoFfSYDQaOH1aGM0kJIjJku++K8QPdffXMi5JJJKHnZoa0Tn82Weia3j5cqEJlfHxb4RKJTa3ceOEum/pUmjR4q9elUQieUBUVMDhw//P3nuHt3me9/5fEAAnwAkQBMC9JA6REqk9rS05tmPZsbzqedw2w62TNk1P0l/PSU/Tc6U9TeP0NG5P7MR27ai2bCmWYg1rWJZE7UWKFCnuTQwSAAf2en9/PHkevQAp2ZLNBT6f68JFghDFl3xv3M+9b+Djj4ltu2wZ8OtfEz8b4Pqaw+FwOF8SiYTspK+uJo+bN4H33wf++q9vbYBYs4YU9nI4HM40EQgAvb3AkSPAoUMkx/7wwyQHn5pK/g23izkcDoczKcjlZDrvSy8BHG+2RwAAIABJREFUTz4J7N9P1ty9/TY5iDZsIEEafhBxOBGPIBC7VLwlzeUCXn0VmD+f2Ke8FnQWIZWS9fO/+AXpFvze98hUuO3beQyEw+FEDjT2W1YG/PSnpAvlzTeBV14hE3wffhhYuJB3SHO+NBJBEO70+h1f5EQ+ggD4fEQHvfMOmV62bBnw0EPAggVk+AxnFhEIAJ99BtTUkOf9/aSi5dFHyXOFggRQeOEah3PXUH25dy/wq18BzzxD3lqJidN9ZZx7ZnSUTOn1+YAf/xhQKknF9vHj5BDU66f7CjkczheETuStqwNefx3o6yMDFLdtI01qfLPjLCIYJCuNjh0jz00mYt8+/jh5Hh9PDuD8/Gm7RA7nbhEE4MYNsqkLAKxWMqxq506SC4mOJjWgFRXTe52cL4HPB3R1kRt76BCgUgFPPUWayOLj+RQyDoczJdDNa0YjifN++imxhXfuBCorAbWa105FDL29wIcfkrhGIAAcPgyUlpIbDpDzZ+NGfsM5swa3m8RbbTaiy06cIAMUysvJ6/PmAY88wn37WYsgkBHxFy+SDRcDA6T467HHgIwM4hRxfcXhRCSCAPzylyTdsmoVeau/+SZpOvuXfyEpGP72n6V4vcCpU2SVaXU18Fd/ReoQ+A3lcAB8vsu2ejXpceJvmVmAIBCd19oKHDxIDrGCAuBP/oQccHI5v5Gc29EHIOt2L/KCXs5tGRsjUyb37weuXSOG9J/+KTGeo6K4zpmVCAKZDPSd75B9evT9T2/m+vWkC5oXqXE4tyUYBHp6yBAB2hksCCTO+KtfkWKx//7fgSVLeOdwRDA6SlZllJYCzz1HRi7/5jfA3/0dMcT5YcjhzGgEATCbb+WE6Arhxx4jDRcSCX8bzzoEgRTDvfACMDREvhYM3iqGW7qUVKgUFk7fNXI4d4kgEBvyoYdIzyUQKtYFBcSNW7Ro+q6R8xUgCOThcJAuwI8+Ijf5kUdIwIVPIeNwOJOEIBDXtq4O2LcPqK0lAxuefppsPZfJuPqJOKxW0sF46RJ5Lo4By+Ukc/y1r/Ebz5k1uFzAt79NNtoC40X6b/6GbPXmIj2LoTfV7ycbLl5/nXxcvZroswUL+JQzDicCsdmAqirA6QR++ENSw//mm8C//iuxU7len+UIAtDdDfzzP5PA/He/CyxeHJo8DQRIUUpy8vRdJ4czDXyey7ZnD3md68FZhCCQoP7QEPC735FHbi4ZRlNVBSQl8RvKCeeOBb3SH//4x3f65ju+yIk86ITJs2fJdPCPPyZ+8ve+B3zjG0BKCi/mndVIJGT6z6FDZBwHRRDIjX30UeDBB3kVIodzGwQBaGwkjaSlpYBGQ77e1ESKeAWB1HlWVPAhWxFDdDQpCnvjDeDAAVIRODJCpvVu2cIDyRzODEUQSBxw3z7gH/8RuH6dFMr92Z8B69aRDV+8mHeWIpEAsbFkKm93961IlyCQ1+6/H3jiCW7PcmYVNFB79SqxNcViLQik6Orll0NXUHJmIfTgiYkhozC3bCGB3EOHSGHV2BjpGkxIuPXvORwO5x6hZ4nbTSb9/NM/AUePkuaQb36TmEsaDR96GLHExZHpQGfPkoQiRRDISNPvfAdITZ2+6+Nw7hKplDQmHDxI6j0pgkBMp5/8hC8dnPVQW1kqJQfU+vXEZm5sJJXcV6+SBKVGw5OUHE6EIAhkAdeuXaSwraaGNKD98R+TRQI8xxYBSCSkUHfVKrJl7fXXSc6tpOSWHj98mFQuLlvGOw05c4q4OKClhSwj5C5bhCCRkMNLoSCTyZcvJ52Jv/0t2f4bHU1GMNMDjus7DjAK4Oe3e5Gng+YI4YNYJ3rdYiE+8a5dgMFAppf99KfEzuL2UwSRm0sOj/r6W4IBEIvga18jmWQOhzMhFguZ9nDwIDGu/+//Ba5cAf7jP0jTw5NPkjpPTgQRDJKMgcVCxhhRr+riReJpVVfzA5LDmUKCQdK0P5G5IgjktYEBEgzes4dM4f32t8nUdKWSB4IjBr2eBILPnSM3nZKQADz8MN+zypmVpKaShoNDh0icjyKTkSb+2NjpuzbOJCCRkJv+8MOksLexkTSQ7d5NMpdf/zoZzRwXN/H33+lA5HA4EQ1t9rhTc5rPR2K7n31GBoJLJCRecd99RPXwBpE5wpNPAr/4BeDx3PpaVBQxOPh2Ns4sIyqKLGMpKyM5LDELFpAHJ8KIjSVdKOXlwOAgOdD+x/8gldvPPUduelraxIehIJBxn/HxPG7L4cxgfD4SAxkbI88dDjKY+z/+g7zFFy7kLm/EkJhIJm2sXEm6cG7eJBswjUbgRz8iAf3iYhIA40MaOHOIJ58kE8m5yxaBSCRAURGQn0+KSE6cIE0N//mf5MavXk1s2YmSlh4PifvSyUScOYtEEBf0jeeOL3JmB4EAacbX60nBv/g9LwhkncUnnwD79wNeL5letm0bkJ7O9UPEcvw4sH078ZYo1dXA6dO3TxhyOHMcnw/4938H/vZvSX2nREJq4AEy3YavvYhAPB6yDuNv/xZoawt9TSIB/u3fyM3nFYIczpQQDBITxu8nZowYQQB6e4H/+i8yzSEzkzSnrV7Nfd6I5cIFYNMmwG6/9bXiYuDyZd5dw5m1NDUBW7cSfUZRq0nRQmbm9F0XZ4rweknj7Z49pJGsrIwEfBctCm1UEASyum3vXmDnTjKpjMPhzAkEgQxdNRqBNWvG27jBIDlL9uwhJpFeT+zmjRtvDf/mzCFGRkjg6syZW19LTSVJxEcemb7r4nDuEY8H+Na3gLffvtVvL5EAr75Ktlnw8FyEIwhkuuOBA2TaRnQ0SWZu3jy+sNfhAP73/yaFv0VFPCjE4cxQ2tuBZ54h/fpioqLI0sSf/YzYsry+M4IQBKCrC/g//4fodI+HVHUHg2T16UcfkWIWDmeOMJHLlpYG/OpX3GWLSEZGiB378cck0bl1Kxn2IB7FHAySyeUXLpCV0QrF9F0vZyroA5B1uxe5ixvhBAKk2P+554DXXiPPBYHoB7MZePdd4OmnSb3S88+Tf/PMM2RrDfdxI5iqKjLthyKREKuAj33icG5LSwvwz/9MinkBoktPnCADAjdv5jozInE4gFOnyIEZjiCQLKnXO/XXxeHMQQIB4uO+/DLw85+ThjRBIDG/nh6yVeL550kR3N/8DVkpvGULH8YS0VRUAPPm3XoukZCJlrxahTOLKSoiW2XFbN1KArmcOUB0NPHV/+f/JKtAtFpyqL38MunSHhm5tWXnwAHgBz+41W1452Z9DocTAQgCKdb91reA73+fDB4ESK7H4SDNH9//PvDnf07+7Y9/TPLkDz7IzaM5S0ICEQBxlaNWS6rBOZxZSEwM8MADofNIdDoy7I/7/XMAiQTIyABeeOFWIvPAAeCP/ohUvRiNZCKHIJBCiV/+kqxsamvjtjKHMwMRBDKktb5+/GuxsUBpaehWck6EIJGQTcJ///ekWOXIkVtdOg0NJMjvdk/rJXI4U8lELltGBnfZIpakJDKJ/F//lSQ0T5wgtuybb5I1S34/0YGvvkq6Wv7X/yJj7LktO2eR/vjHP77T63d8kTOzoasq/vRPSaFDayuZVGazAe+8Q/TA0BAZLvjKK2SglULBgx9zApmMFKjV1JDnycmkY5lXcnM4EzI8DHzve8ClS6E2k89HiseWLSNT0/jbJ8KIjSUVgTk5ZLVbf3+oAJjN5GDVaKbvGjmcOYC4mLeri+jk/Hzi177+OlnDlpxMChief57o45iY6b5qzqQjlZJgxrFj5HliIqlcycnhBzJn1hIVRUR7zx7yPD4e+Iu/IGsmuVjPESQS4q+npAArVpD1SQ4H8JvfkNVKgkAKf3/0I6Cjg0zyHRoiG3d4QIfDiViCQaCuDvjjPyaTe2w20tek15OapddeA/btI+fFj35EBhZqtcQm5mphDiORkHPj00+JEyWRkAK4hx/mgsGZtej1ZEiNzUaeb98OPPssXzo4p5BIiN1bWEgqvIuKSCL07bdJIYRUSookGhpIEOnKFWDxYr6SlMOZYfj9ZCPm6dO3vhYVRWzcv/xLUtep1fK3bUQSDAJHjxIBGBu79XVBADo7gawssrGIV3Nz5gATuWzPPkvmlnD9F6FIJMR5KSwkN1qvB37/e1LANzoKNDeTpKfLReK+NhuwfDmpWeBCEYmMAvj57V7kBb0RCrWFvvtdoLubHAR0e+OhQyTf/eKLpOhh3jySL+Lv/zlEVBQRiE8+ISM9NmwgY5zj46f7yjicGYffTwLF/+//TdwYarORWOFDD/ECsohDIiFB4PJy4L77yOc3b5KRoBSNBli7lh+iHM4k4feTYt4f/OCWTet2AzdukClkpaXAn/wJaWrV68lbkb8d5xASCREQh4OMZfpv/404OhzOLCYhAdi7l8TvysqA73yH5J45cwx6oCkUpEJv3TpAqQR27wbefx+4fp349MEgGdlpMBB7lQd3OZyIIxgELl8mwxguXSLP/X6S4/nsM2Ijb95MBjZs3Uoa3bhNzAFAhCApiQhKeztJAPzjPwLZ2dN9ZRzOPSOTkYGrly+TPPgLL/Cw3JyFNsJlZZH81vz5JAH6+uvEVna5yL8zGEhxLy/q5XBmFC4X2SRutZLn0dGk5+jnPyfTKrlrG6HQot3vfpcc6OG4XKQZY8sW0ujMhYAT4XCXbY5CgzZRUWRq+YYNZPrm8eNkqANdUerzkWSo3U5iw7yoLxK5Y0Evb22JQDweYP9+Uqzb3n5rmKDfT2yj738f+MlPgNWrST6Iv+fnIBIJ2eVaWUm8pE2bSMSfw+GEIAgk/vezn5GiCopEAqhUpCHqlVdIoRmvh49gpFIyDvSnPyVdctu3kxvu85HJkGbzdF8hhxORBAKkqC18Q6IgkKGEf/7ntyZXRkdP77VypgGJhAQ5VqwA5HIS0OAT0zkRQHo6GcoaFUVyzkVF031FnGknKop0rTz6KPAv/0K6CMVTbJxOYNeuW+uZ+Bo2Didi8PvJ1LKnnwbOnyf2MXDLHt6yhdQtPfEEWVLAh1hxxpGURGIYMTEkiDVv3nRfEYfzpYiKIsuy4uMBtZqIN9d9cxzaBLdiBfDDH5I91RbLrdf9frKp8qmnyLReephyOJxp5cwZ4r5KJMCiRWRY65tvks95nDfCCQRIHHftWtKUIZWGFqvU1QF///e3GjM4nAiHu2xzHImEDKlZvZokBdxu0slNcTjI1Lm//muypY3HfecUsum+gKlEuAfh9nq98Hg88Hg8cLlcCAaDcLlcIf+Xx+NBQOQESqVSxIjGNEZFRSE6OhoymQwxMTGIjY1FTEwMoqOjIbnLatrP+/eBAHDgAOlqGxwc/342mcjwlo0beSHvTOVe5JR+n8/ng9frhdvthtfrhd/vh9/vh9frDfl/A4EAPG43NDod0lQqdCQmwlNbi7iw3VRRUVGIjY2FRCJBbGws5HI5YmJiEBMTA6lUes+/493KPWf2cy9y7ff7mf71eDzw+XzscScdTOVVLGdyuRxyuXycHpbL5Xe8Bp+PFPO2tJDgsExGCse2bZOgqooEFzIzeeA4krijrMpkZALkG2+QNW6vvUaE49o1+DduhNvtnlBexYTbEFTPUiQSCZNVuVzOZDUmJgYy2b2ZbVznRh53q1OpjeB2u5mcBgIBeDweBEWOYbg+DZdPAIiLi2Nfp7IZExPzldq0gkBs2v37iY9qNI63aen09O3buU07U7lXm5barh6Ph30MBoNwu90h/2cwGITH5UKaVouM5GS0q9Vw19WNs2epbyaRSBAXF4fo6GhER0cjJiYGUfd4gHO9One5V7kOBAIhfhqV63A9TL+WkZEEpTIL+fmdqKuzIz6scyzcT6NyHRsby+U60qEj6cLx+8nBGQySFcOfs5v0XmSZyifVz263e0I5nsgGDo8hSKVSREdHMx39ZWwKgMvvXOBe9a/X62V61+12h8TJxFB5pkgkknG2QrhNQWMK4fGHL8oXifEePUoaiDs6QvM5AMlvNzWReASPScwu7lWeKWK59nq98Pl8E9rLAIlBROn1KJfLYSgqwmBbG+QDA+PiCzR3QeU8OjoacrkccXFxX0rHcv08N/mydgZ9TCTXPp8PDgeQm5sDpdKH4eFu1NePtzOoDqdxYOoDcjsjgpFIyNTH48fHv0a3Wrz8MmmQW758wsPzy+hnGmejPp/X653QVqa+YXh8OFw+w+WY2h1fRi9zWZ573KtM+3y+EHn2+XwT2tAT5eaon0eZSJajo2Pw+9/HQC6X4LHHgL/8S6Ci4pYLe6fL5nI8y6EDGv7pn0hh2vXrJMZx7Bhw/jwEhwMQBEg++gjCli3Ak09+bvBfEAS4XK6Qmh6qk8XvgXCfb6LcHI1dULuB5kDuJdbGZTXyuJe8nDgecbu8nNfrhV4vQC4vR1GRAW1tQzAab9kF4rwxjf9S+eSyGUG43WQb5URDxFwu0vUCkOFjcXET6sYvGzujcjpR7IzKc/i5f7vYGffFvhokn3NTZ115d3iiTPzweDwYHh6G2WyG1WrF2NgYnE4n7HY7HA4HHA4H7HY7E1TqcEkkEvYAxguN+DWACHP435U+p6/R51SAY2NjER8fD4VCAYVCgYSEBCQkJEChUCAlJQUqlQoqlYoVVdKgmriYwu+Pwu9/L8G3vkUaUMWXIJHcer5gAbGL+NrO6YHKKJVJcdEXLWAcHR2FxWKB1WqF3W6H0+mEy+ViHx0OB5xOJ5NVWsgLYEJZnUjRRUVFodTlwpNGI/4uOxu+qKgJlfxEsisIAlPCVAHHx8cjLi4O8fHxSEhIQFxcHOLi4qBQKKBUKpGWlobU1FQkJCSw4kqx8UH/H7lcPucV82xDEAQEg8EQ3Utlmn5ut9sxNDQEi8WCkZEROJ1OJsdU/7pcrhCnixqzX7UOFv8bGmCgejQhIQHx8fF/kOMk9PSswp49ZQgGLVi5chSPPipFWVkC0tKiER9/SxeL/w+pVMpleAYjCAJzmMR6mDZBeDwejI2NwWKxYGhoCHa7HXa7HS6Xi+ljp9MJx/Aw4gYG8J2hITTGxOBdlQoB0b2fDHkV611qN1DbIS4ujslvUlIS0tLSoFKpoFAoQuwGsb79ss0ZnMmDyqnYJqX6lOraoaEhDA0NwWq1Mj1K9SqVW3HRDdV5k2XTioNc1BYQ27MKhQKJiYlQq9VQq9WssDJcLkkQTYb33pPghz8EBgZuH8TNygI++ABYtuwr+sNzvjBURsMLCcQPt9sNq9WKoaEhjIyMMD9LfO5TnSoOuIb7X59nzxa63XhpYAD/X07OhPas+Hm4PUvtUSp7sbGxUCqVzI6lelWhUCA5ORkqlQpJSUnMZqXySxuGxIEJbgvMTsQ2gljvUl/N7XZjeHgYg4ODTK6pj0btBbFcU9s4EAh8YbmWSCTw+bLQ1/cKsrL+B2Qy5135aWL/isq1QqFg/hqV64SEBCbXKSkp7HvEvhqV6ejoaERFRXG5nm4CATKF9803Qyv7xAEfuRzYvBnB116DT6OBZwI9TWXTYrHAYrHAZrMxuaUyTfW0w+EIiat9ETmeSAfejU1BZS9cfsW+mlKpRHJyMtLT05GUlMRia+Gyy2MMs4dgMMgKByaKl3k8HlitVvYQ279UVqktLI65AV8sTjaR3AbDKmjvZFOIdWhoXCEh5HlycjLS0tKQlpYWYg+H28QSSTSOHInCN78pgcl0+7d8Sgpw8SJQWPiV3AbOVwSVZ7H+9Pv9IfFfl8sFm80Gi8WC0dFRZkdQeaZ2s8vlCom1eTyecTL9eXaFXBDw/b4+HEtOxmWlEgLGJ/ruJN9i2yI6OprFf8W2BfUDk5KSkJSUFBKPCI8DU93MYxKzFyrj4hzcneyM8BgwtTvEOvtu7AxBkGJg4E+gULQhOfnYXdsZ1EYI9/mobCuVSqSkpECtViM5OTmkyJ3bGTOYYBD40Y+AX/6SFET4/aGvS8haYyE/H4Ff/xr20lJ4RLqZPlwuF6xWK8tjhMcwqAy7XK4Q3/Fufb4vGn8Tvx6ul8VxOJqLE8czaH45NTUVqamp43RyeF6O+3yzD3GxmNh+FtsNw8PDGBoags1mY/UQ4faz0+kMkWdxHBn4crkO+nXx6z5fGoaG/gISySGkp19FamoM4uJix9nPVK7F+Y5wG1qs13nsYuZD88khw5xcLnhtNvj6++H9+GMI+/cjyWRCXEEBTu3ciZuxsSF2RLiNfK+xiruxH6gNK7YfxLmPcPuBxtnCc3PiAmEupzMP8WCc8Pyxz+eD0+nE4OBgSCxNrEtp7ZlYvoEvVucgCHL09X0fycnHoFRe+lzZBIhNLpYtqjOpbUt1Kq3TUavVSExMDLFtxTFkrkOnmbY24P77AauVbGPzeMYHg2JjIbz0Elx/9VdwxMaGyCc99202GwYHBzE8PBxa1yCS1fA4w2Sf++ExX2rDhsfMqOyKz31xzDe8LidCZLYPQNbtXpy1Bb2BQACDg4MwGo0wm82sqEFc3CCuDqdCmJCQgKSkpJDCWbGBqFAoQgw/sWNOJy6EV5nL5fKQAi4aoKPQQjf6UWwUU2XudrvZG0mcQHE6nRgdHcXo6CjGxsbY70GRSqV/CJLp4PE8jF27KmAwSAAIkMvJiHaNRgK1mnyelgakppIVxVm3FQvOlyUQCMBisWBwcJDJ4/DwMCwWC4aHh2G1WjEyMjJu0ii9v3FxcVAqlSEFBdR5oYZiXFxciAILLyygxQVUZsVyw74WCABXrwJLl7KijPDfgzpv4oS2+GBwu93MiAkPPNPPXS4XxsbGMDY2Br/fHyLHVPHHxcUhNTWVBRhSUlJYokOlUkGj0SAhIWG2K+RZj91uh8lkYnrXZrMxGafyHQgExhUkRkdHIzExEUqlctzBTPWvWKapPIs/p0Gl8Onm4To4EAiMe2/RhIm4+Egsz1QXU6PG5XJheNgPm20xgsEheDxnMTZmwMjICOvqFF9DVFQUkpKSkJqayorXVSoVUlNTkZ6ejoyMDCiVynuemMa5e4LBIOx2O4xGI0wmE5NV+pEmzSayFWJiYpi8ipsUwothYmJikCAISLFa4c7Lgyw+nskrnWwTHbYfStyhLi6GF0ODwLT7TSyz9CO1G2jhhbiAyOFwMLuBJvsoEolEZDuoWNMQ/ajRaJCeng6FQsH17RQgCALcbjdMJhMMBgOTzcHBQVitVpjNZtjt9pBiAlrcTWWU6lWx40M/D7dpw50c+pFCZZcSbhsIgsB0YLg9G65LxQE28WNkZCTkvSe2BxISEqBS6RAV9Q288cZCWK1AdLQPKSkB6HQyaDQyJCdLkJZGihfUarJ1oqxssu/U3IQW7VosFpjNZhYEoOc9DVyNjIwgGAyGnP0SiQRRUVGskJvKprgZQVwIEJ5EEgfm6eaTcB+M2bPBIJnksGzZhPYs9c3Echtu09Kks9h2FetVsW4Nn7ROr0Uul4ckysQ2bXp6OtRqNZKSkrgtMAMIBAKwWq0YHByE2Wxm/pnVag0prKF+i5ioqCjEx8eHyPVExSxUricKkNLPaWNZeCELkfkoXL4MLF4MAEEWABb/DlTWqT8WXjhE7QWxLId/brfbMTY2BofDEdLwBhC5lslkSE5ORkpKCtLS0ph/RhMU6enpSE5O5sU4U0UgQLZE9PUBw8OAzYaA1QrHwAB8g4OQWSyIcbkQA8C+ejXeXLAAl4aHx02lEQQBUqkUSqWSNeCKfbNwPS0u4hI/aJxhomli4uIWGk8In0xGJ0qGN+KL5VccKwsvpLDb7axZVPz70Z8bHx/PZJXqZhpfyMjIYEUNnKmF2r6Dg4MYHByEzWZj8QSqgyeSWYlEEiKz4iIssU1xO7tCHCebyE8Lt4OpnS7mdjYFtYFpg2i4rhUnTKjepfExINQelkqlSEnRQCp9HB9+uAxGYxQkkiBiYnxITAwiPV0GtVoGpVICpRJITgaeew5YsmSy7hjndgQCAYyOjsJkMjH5tdlsGB4eZp/TJC8wvjBLKpWO08FiO4I2ndNp0LeL/9LPgfH2MvCHGIREQrYLaTQQkpPh8/nGxULo16h+Fjc9i+0MKuP0QQuPxba0w+HA2NgYew+FJ/1kMhmLodH4L/1Ih5qoVKp72m7I+Wrxer0wm83MH6T6mg4isVgs4yaNiu0McX5jIjsjISEhRLbDE7R3sjMaGiTIyQGUytvbGfSjOKYWbmeIi43v1s4Qx3/p52I74143bXHuEb8fOHUK6OiAf2gIlrY2jPT0wG0wIGCzQeZwIG5sDEmBACSZmdi9dClOSaUIIrTogOrnxMTEEPsivJlB7POJ4xdi3TxR7I36geKv3SmWQe1lcaFGeCwjfCBQeCxD7POFx4nlcjlSU1NDfD3q/9FYcWJiIo9lTCPU9hwcHITJZArJcdBiXavVOqENTWMYSUlJIXHj8OFM4fIcbk9/URuayqv4OsR5Ziq/NhvgdPoRFzfK5FqcX57Ilh4bG2OxGiDUvpBKpUhOTma6WNxEp1arkZGRAYVCweV4CqH322w2w2g0htTv0ByIzWabMD+niI3FkqQkbFMo0BoIoEmrRVxY3kNsI4fH36jtEL55MLzwa6Lch7ieR+zr3S7OFl4kPzY2xuwHINTXo3lklUrFZJPGLDQaDTQazbjNc5zJIRgMYmRkBEajEUajMUQuqayKt0SIC7sTExORmJgYUjA7UV5OLJfheTla10AhOlZOXTYkJY2PBdNBKGIbIDxHJx5MJbZxab3ZyMgI+73C/TN69tMYmlqtRlpaGrRaLdRq9Tj9z5kErFagvh6C1Qp3VxcGb96Eta0NHoMBsNkQPTaGRKcTqdHR6Fq8GL/UajEi+nZ67ickJLDchThuFu6LieUzvCbny5z74TasOKYgltlwm1V87lN9Gh47o3JLcxbh5764LichIWG2nPuzr6CXJo/FB2VXVxfa29vR0dGB7u5u9PX1wW63Qy6XhwR6NBoNdDoddDpNePVnAAAgAElEQVQdC36FK0oqlLPhBtKA2kRK2ev1wul0wmw24/p1G06fzoPX64bD0YyhoXrY7b2IiRGQl5eB+fNzUViYjcrKYhQVZSMxMT4kCMiDY18MQRBYgRUNag4NDaGtrQ29vb3o7+9Hf38/TCYTM9aoA0wPwtTUVOh0OqSnp7OgVXiHt/jjpHYVCAJ5TOJ7Qfw3C+8ODe8SHRgYYBO0xQl1t9sNuVyOxMRE6PV6ZGZmQqfTITc3Fzk5ORNO/eUyfXdQvSu+JyaTCc3Nzejr60N3dzd6e3thtVrh8/kQHx/PnA2VSgW1Wg2dTgetVsucf7GOESfQZssEWxoHlkiEcdNVwguC3W43zGYzBgYGYDKZWFB7aGgIo6OjzMjPzs6GXq9HdnY2CgoKkJmZOW7y+kSTgTihhOsVj8eDnp4edHR0oKurC/39/ejp6WEF5omJiSFBdo1GA71ej/T09JD16xPJ7BfSwdSWmgH3TWxDiYsjxA+n0wmTyYSBgYGQxpOhoSE4HA4WyM3MzER2djYyMzNRVFQErVY7riCJy+rtuTVx4NZ5NzIygtbWVrS3t6Orqwt9fX0wGAzwer1QKpUhwRyNRoOsrKyQ6V3hdi0992bDfRC/bycqVKfTXJuaBlFfn4axsVGMjDTDaGzD8LARcrkfWm0qCguzUFKSh+LiHMybVxwyVTJCujGnBHo/xLaZxWJhNi21aw0GA9xuNyQSSYg9S4tUtVot06UTFSyKJ9hOmu81yfYsbb64nR1L5XlsbAwmkwlGo5EVKNHg9OjoKKRSKbNl9Xo9srKykJmZiYKCgnHTy7gte2+Iz0B6b4aHh0PkmupdmswM99NUKhV0Oh3UavU4X20in20yYwrBIDEtJkMUJjqjxMUO9OsOh4PJtdlsZoV3tGFVKpUiPj6e+WdZWVnIyspCfn4+kpKSxk2A4nJ9d4TL88jICJqbm9HT3Y2ejg70tLbC1NuLgMOBBLkc2Wo1stLTkZuejmyFAk61GvKqqpDpGxPZvbPx3oj9s9vZvVarFQaDAQaDgRUf0eS3IAiIj48Pkdu8vDzk5uZCqVTevT/AGWdb0KKDlpYW9PT0MD08NDQEj8eDmJgYliiiScyMjAzodDoms+GxhPACmdkG1bsTya64kKG93YKLF5Ph8XgxOtoOq7UbRmMXRkYGIZUGkJqagLw8PQoLs5GXp0dpaSGyszOZPSb+G3HZvTvo+egPm9hoMpnQ3d2Nnp4eDAwMMDvZ6XQiGAxCqVSOG05Ak0h0uudERbhTYiuTX4w8JsuwYD9GCFnNGS7vYvticHCQ6WdqX9Bi6GAwiOjoaGaX6fV6aLVa5ObmIisrC3FxcZDJZOzvN1vijDOJiXyc4eFhYmf09LCHyWRicXkaU6NxC5qDUyqV4+yMcJ09GfdnMm3lz7Mz6NT4cDuDFjoDpOCX5jGys7OZnaFQKEL8C66r7447xTK6u7sxMDCA3t5emEwmuJxOyAIBpCclISM1FbrUVGRrNMjWaJCTkYFAYiJGk5MhD4vNT1ksYwoI9ycmkmuHw8FyGuHNVna7nRXo01iGXq9HXl4ecnJymN3MYxn3TvjZ6fV6YTKZ0NrayvJy/f39MJvN8Hq97HykzYq02Eqr1SIpKem2ung21UWEEx5TnqiZ2eFwsMI8OtyF+n8Oh2Ncfo7GLahdwW3ouyc8Zzo8PIz29na0tbWhr68PXV1dMJvN8Hg8iIuLY3U8qampzO/TaDTjGuJDHnI5ogIBsoloht8T6kfcLidHi9eMRiN7T9O83ODgIFwuF6Kjo5Geno7s7Gxm986bNw/JyckhdhW3fe9MeL2D1+tFX18f2tra0NHRgZ6eHvT19bEhJeLmb5VKBa1Wi8zMzJBtUOHN7ZNx5k2myzZRM724uNLhcDC71mg0wmazwWw2w2KxwO/3IzY2FhqNhsllYWEh8vPzx8XOZ+MZM9WIbVkqowMDA2hvb0dvby96enqYjvD5fIiXy5GRkgJdSgqy0tORrVajUK+HOi0NJoUCksTEcbUNkX7uU5md6Ny3WCzs3E9OTkZWVhary8nLy0N2dnbI34ra+tOsU2dHQa/b7WYJNvqxr6+PdbbT4rHMzMyQYLtOp7ttUGAuHGah3XYhr2B0dBTd3d1oa2tjQZje3l6MjIwgJiYGCoUCOTk5mDdvHjIzM5GbmwudTsenoIrweDxMGdBi097eXhiNRrjdboyMkL4HWtCoVquZQ6DVapGRkcG6qeaqjH4RbqeH6Ne9Xi/6+/vZ395gMLBCk+HhYchkMjZxOzMzE3l5ecjMzGROQUpKyqw8sCYTQRAwMjIS8nelf1M6PVEmk7GkWk5ODgtAZmVlQaFQAOByTbnTOgGfz8ecNBqA6ezsZMUk0dHRUCqV0Ol0LIiQmZkJvV4PlUrFZRfE2bBarejr62ONE729vTCbzWwSLQ1mabVa6PX6EJlNSEgAwOWVcid5dblcGBoaYk5Dd3c3C4jb7XbExcUhOTkZWq0WxcXFLDlBHdy5Lq/BYBAWi4UVLPT29qK7uxuDg4NskjKdOkQL+6kTnJycfNuC/rkgp3eSS4fDEaJDu7q6WHLR7/cjOTkZarUa+fn5zAbIzs5Geno6nxqJW8lamjTv6+uD2WxGX18fe2+H27SZmZkhvhf1uQCuSyfi82xZj8fDAmL0HnR3d7OEmUQiYVtk9Ho9iouLkZGRAb1ezwqb5rp+nQiqcw0GA2uqpAlcKtd+v581Suj1emg0Gmi1WuTk5ECn07FpHVyuJ+aL2LhUrqmeHhgYgMViYU1VCoWC2Q1arZYV5vDJvqHQaaBGoxE9PT1MV/T09LApGl6vl03JoMFIGstRqVS3TerMRVm+k16mvoXJZAopNO3o6GBFOLTRqqCgANnZ2cjOzmbyy6eSEOjfcWBggNkUNLYwOjrKJhrSSYU0iJ6eno6cnByo1erbBs3nosxS7qR3vV4v+zuLEz1GoxEjIyNsq0xaWhqKiopYbIEmy/lE6vEIgsASQbSYieoGi8XCJsUFAgHmx+n1emRkZLBEr1arvWPM4U5fn4t8nt0sCALGxsbQ39+Pvr4+DA4OslwRjQHJZDLExcUhKSkJ+fn5IXF4rVaLtLQ0bmOEIQgCKyKhdgb9u46MjLBNgrSYQZyDy8nJ4XZGGF/EzjAajWwwUU9PD7q6umCxWBAVFcXsjPz8fOTm5rI4MG2k59yCbmql/obBYMDAwACzN+hWK9pUodPpkJOTw2xltVrNtv5MKL/khan9pWYYn+fzDQ4OMjnu7e1l98JmswEAEhISkJKSwvJyVJb1ej2PZUxAMBjE8PAwy3NQvUwbaEdGRiCVSllhGc0301xHWlraHQfCzEWdDHy+HJtMppAC6a6uLhiNRtjtdkRHRyMhIQFqtRq5ubnIzc1l8biMjAyul/+A3+9neU7q91EfemxsDC6XC6mpqez9T3PJWVlZUKvVczrvQbmdnAqCALvdPi6nRO1fgMQo0tLSkJubi4KCAuh0OmRnZ3M/7w+4XC5WWyY+s4aHh2G32yGTyZCWlsZiE3l5eSgsLIRWq+WxYdxZh46NjaG9vZ01uFIfwmazsanTGRkZLAZBY5WpqancBgCxZYeHh9Hb24uBgQHmh9Fzn/q3tCmYxnHouZ+SksLP/Qn4vNiZ0WhkuoCe/0ajkdXlJCQkQKPRICcnh9VIZmZmQqPRTMeWlZlT0Et/VjAYZAf/5cuXceXKFbS0tMBmszHDv7CwEHl5eWyct0ql4uvKvyQ0IEan8A0NDaG7uxvNzc0wGAwwm81ISEhASUkJKisrsXjxYuTk5EAqlbIgeyQqBRpoCQbJ+PqWlhY0NDSgoaEBnZ2dsFqtiI+PZ0FB6pTSMd7Jycls+hBn6hAEAU6nM2SVncViQVdXF3MmzGYzZDIZtFot5s+fj/LycpSXl0Oj0SAqKooFIiNRrili+Xa5XLh+/Trq6+tRX1+Pzs5O+Hw+ZGRkQKPRoKioCNnZ2WxCWWpqKpKSkvh6sEkgGAwyfUynkdAkMp0iIAgCMjMzMX/+fCxatAgLFixghQ80MRFpskvlla6urK+vx7Vr19DY2Ii+vj4IggCNRoPMzExW/CyWV6VSyZM2k0AgEMDIyAibnE4DuW1tbTAYDDCZTJBKpcjOzkZFRQXKy8tRWVmJ+Pj4EBsikqCBlkAgAKfTicbGRly6dAkNDQ3o7u6GRCJhBWOFhYXMgaVd6OErIzl3B51uJl73aTAY0NbWhq6uLgwMDMDr9UKv16O8vByLFy9GeXk5EhMTI1YmgVtySX0tg8GAa9euoampCU1NTTCZTJDJZOzcLygogF6vZxN3k5OTWcc/Z/KhxXt0Ghn10ejE+cHBQZjNZsjlcmRnZ6OsrAwlJSVYuHAha6CIVHtAjFiuA4EAhoaGcO3aNdy4cQM3b95Ef38/JBIJW01HO62pbUBXONMkLmdyoSsVqUzT9Z99fX1ob2+HyWSC2WxGVFQUdDodysrKMH/+fCxcuJAVikRy7AEYr6vb29tDZHpkZAQpKSnIyMhgiRoaF0tJSWF2BOerhRY6iaerm0wmNuGbNsCoVCoUFxejsrISixYtYg0vkSq34jguTULU1dXh+vXraGpqQm9vLwRBYPGy/Pz8EB1M7QseU5g8aGyB6l06MbK1tZUli9xuN9RqNebPn4+ysjJUVVVBp9Ox2EIkyq4Ysd6lRTTXr1/HzZs3cfPmTXR1dcHpdLImQVqQpNFomAynpKSwKYSR/LeayQSDQTgcDhYHpjJPN9/QODC1C4uKilBaWorS0lLk5uayyTuR6gtSxLGKQCCA1tZW1NbWoqGhAc3NzRgdHWWbq2hDLLczJp9wO4MW/NJJXAMDA3A4HFCr1SguLsbChQuxcOFC6HS6kKlRkSq74fbxwMAAy2G0tLTAaDRCKpUye4NubRTn53gsY+qg8hzu83V1daG7uxsGgwFDQ0OIiYmBXq9HWVkZysrKUFFRgeTk5BBdHKkyDYzPc1y9ehWNjY2or69Hf38/gsEgNBoNMjIyWOxYpVIxXcxt6MklGAzCbrczvUw3yNL8nNFohMvlYnq5srISCxYsQGZmJltDHqkyLJZdq9WKK1eu4Pr162hoaIDJZEJsbCybclxcXAyNRsOmRdP4WyT+XaYDuhGA5kBMJhPa29tDBkalp6ejrKyM2Q5qtTrEz4skaHwiEAjA7/ejr68Ply9fxrVr19Da2sriaTR/nJeXh/T0dLZpOCkpieePvwJofY44N9ff34/m5mbWfAUAOTk5qKysREVFBSorKxEbGxvxuTmqO202G6ttqK+vx8DAAACwQSP03Bf7YLweZ3KhsTO6icJms6G/vz+kLsftdkOj0bBzv6KiYqr8sekv6KVdqXQqYW1tLerr62Gz2aDX61nxR9UfVgHOlQDLdBMe4CFr3Ugyqba2Fq2trZDL5cjLy8PSpUtRUlKCnJyciOhy9/v97IAxGo0sONDT08OKkubPn8+Si+IiurngbM5WxAF6Ktcmkwl1dXW4efMmKwqMjo5GXl4eK/ClHYORMp06GAxidHSUTTy/ceMGS7bFxMSgoKCAJSDz8vIQExMzZxI5M5XwYhXa/X7jxg00NDTg6tWrMJvNSEpKwvz587F06VIUFBRAq9WyyUazFUEQMDQ0hIGBAXR3d6O2thZtbW3o7++HUqlESUkJysvLsXDhQuTk5EAmk82JYPZMJtx+oBP6GhoaUFtbixs3bmBoaAgqlQolJSVYunQpcnJykJWVNaun+NLiu4GBAfT09ODGjRu4ceMGuru7ERUVheLiYpSVlaG6uhoFBQVs9edcKLibbsTBHPowm82oq6tjjQFDQ0PQaDSoqKjA0qVLWafwbD/7aQc/XYnU1tbGmtLsdjsrrqGBEzpZYq40Ns02wm1Zr9cLg8EQksw0mUxQKpUoKirCokWLUFhYyCbvRUdHR8T9pAlCOtW4vb0dDQ0N6OjogM1mg1qtRkFBAUpLS1FdXQ29Xs9WznG5nnmE2w20ubuxsRF1dXVobm7GwMAA4uLikJ+fj6qqKhQVFbEJiLGxsbP+foptiL6+PlZc09XVBZ/Ph6ysLJSVlWHRokUoKSlhDSiRHOie6YhtC1pc4nA4cPPmTTQ0NKCurg6tra2QyWTIz8/HwoULUVFRETFTfP1+P8xmMwwGA7q6ulBfX4+bN28yn7S4uBjl5eWorq5GZmZmiN3LdfD0I9a5gUAAdrsdN27cYLZxZ2dniOyWl5dDp9NBp9NFTAKe2sh0/WJHRwdaWlrQ0tKCoaEhKJVK5OTkoLS0lDWXKBQKpne5Dzc7mCgOPDg4iIaGBrS2tuL69evo6+tDIBBgK4tpkaROp0NqampEJE2p7UztjJaWFtTV1aGrqwt+v581B1ZVVWH+/PmsGZ7bGdPHRHaG3W5ndkZtbS3a29shl8uRn5/PBj1otVpotdpZb2cAtyak05XCra2trEl+ZGQEaWlpIY0oWq2WxYO5vTGzEDeAUX3s9/vR39+P+vp61NXVoaWlhdmROTk5WLJkSUgsI1IaCfx+P2toHRgYYL/7wMAAEhMT2fu5srISubm5PI4xg5gotjw2NobGxkaml7u6uiCTyZCXlxcSZ9Xr9WzC52wlGAzCZrOxKYa0EG1oaAgpKSkoKipCZWUlqqurQ5paI7FodCYjziH7/X5YrVYWn7h+/Tr6+/uhUChQXFyMFStWhBQNztacHEDel3SjCo2ntbS0wG63Q6fTYcGCBViwYAGqq6uhUCh4ndk0MFE+o7a2FnV1dWhsbMTIyAi0Wi0WLFiAxYsXs9xcXFzcrL5HPp8v5Nyn9XUGgwFJSUkoLCzEokWLUFFRweob+Lk/Mwivy6GDzcTnfnd3N2JiYpCXl8diZ/Tc/4pt16kv6BWvFq2trcXJkydx6dIl+Hw+aLVa1pE3b948ZGRkzPri0EhEEASYzWY0NzejpaUF165dg8FggCAIqKysxLp167B06VLEx8cDmNkBTvHKroGBAZw/fx4XL15Ec3MzoqKikJqaipKSEhQUFLDV10qlckb/Tpx7gyal6AS/xsZGdHd3Y2xsDCkpKaioqMCqVatQUVHB1uUBs0O+AbAJvJ999hlqa2vZipPi4mKUlpaioKAA+fn57H3LmR3QSZS9vb1obW1Fc3Mzbty4wSaPVFRUYMWKFVi2bBmSk5MBzA6ZtdvtOHfuHC5cuIDa2loEAgGoVCqUl5ejqKgI8+bNQ1ZWVsQUJ80l3G43Ojo60N7ezpopbDYboqOjUVFRgXXr1mHRokWfu5Z0uhHbDz09PTh9+jROnToV4oyVl5dj/vz5TLfO1N9lLkOnRfb09KCxsZFNq7VarUhLS8Pq1auxatUqzJs3jwW2ZvJ9pHLpdrtRW1uLixcv4tKlSxgeHkZiYiJycnJQUlLCtp3QrQScyMDn86GnpwednZ1obW1FU1MTm7yXmZmJFStWYMmSJSguLp4V8kyhcu33+1FfX8/k2mg0QqlUIisrC/Pnz0dRURHy8vLYVEFOZBAIBFhHPC3eNhgMsNvt0Gg0WLZsGZYvX4758+eHbMWZybItTgZ2dHTg9OnTOH/+PAwGAysiW7BgAQoKClBUVITU1NQZ/ftwxhMMBmE2m9He3o7m5mY0Njaip6cHTqcTubm5WLlyJVasWIHc3Fz2PTP1HotjCkajERcuXMDZs2fR3NzMpuGVlJRg3rx5KCgoQFZWFp9SOosJBoMwmUzo7OxEc3Mzmpqa0NPTwxrBVq5ciWXLls0a2xgIlWG73Y4rV67g6tWruHr1KoaHh6FUKpGZmYni4mIUFhay9b+RUBDHuTO0OKWjowNdXV1obW1Fa2srhoeHAQCFhYVYtmwZlixZgszMzBC/aSbLvdh27ujowMmTJ3HhwgWYTCYkJiYiNzcX5eXlzM6ga1o5swdanE7jwI2Njejt7YXL5UJ+fj5WrFiBlStXIjs7m33PTL/H4Tnjc+fO4dq1a7BYLKzQkdoadEMF9/kiB6/Xi/7+frS2tqKzsxMNDQ1sAiot8F21ahXy8vJmTVONOG5sNptx8eJFnD59Gi0tLZDJZFCr1SgrK0NxcTHy8/ORk5PDbY9ZTCAQgMViQWtrK9ra2tDY2Iiuri7Y7XZkZmaiuroaq1evnjU2NJVfp9OJ2tpanDhxArW1tfD5fNBoNGzLQUFBAStC48xsaCPFzZs30dbWhrq6OpjNZkilUixcuBCrVq3CsmXLZnxdj9i3s9lsOH/+PE6fPo0bN25AJpMhOzubyWdRUdGsH3g1F3A6nWhra0NbWxvq6+uZP0ZjvuvXr58V57/43DcajTh//jzOnDmD1tZWREdHIz09ndU3iGNnnNmJ2B+j5353dzccDgeys7OxePFirFmzBgUFBV/FuT91Bb10VHFnZyeOHTuG48ePIxgMYunSpdi+fTsKCgqgVCoRGxvLlessgnZ5O51OdHV14dixY6ipqYHX68XSpUuxY8cO5OTkIDU1dUbdV1pJ39/fj7Nnz+L48eMwGAzIzc3FihUrsGrVKuh0OsTFxSEuLo4HCOYYtEjS6XTCbrejoaEBZ86cwaVLl+D1elFRUYEtW7agrKwMarV6RnYJ0UnTra2t+OSTT3Du3DlIpVIsX74c69evx7x586BQKJh8z7Tr59wbwWAQLpcLDocDfX19OHr0KM6fP4/h4WGUl5fj/vvvR0VFBdLS0mbMdB1BEOD1emGxWNDU1IT9+/ejvr4eSqUSS5cuxebNm5Gbm4v4+HjEx8fPqLOEc+/Q7jan0wmHw4HW1lacPHkSZ8+ehcfjQXV1NR544AEUFRVBpVLNGOeGFoAaDAZcvHgRH3/8MXp6elBYWIitW7di8eLFSEtLQ3x8PGQy2Yx4j3G+GHRamdPpxOjoKGpra3Hw4EE0NTVBpVJh27ZtWLt2LXQ63Ywq0KYyabVa0dzcjE8++QRXrlyBVCpFRUUFNmzYgLKyMiiVSsTHx/MimzlCMBiEx+OB0+mExWLB5cuXceLECbS1tSEpKQmrV6/Gxo0bkZWVxbaNzCS5oLY4XZV88OBBXLp0CX6/H6WlpbjvvvvYBp/4+Hje4DNHoPqOriSura3FZ599hhs3biAmJgarVq3Chg0bkJ+fz6bqzSS5oDGx3t5enD59GkeOHIHVakVZWRnWr1+PxYsXIyUlhevqCIP6Og6HAzabDTU1Nfjss8/Q2dkJrVaLTZs2Yd26ddBoNFAoFDPmvtPJeGazGefOncOxY8fQ0dEBrVaLNWvWsGtOSEjgcdwIhcqu0+mEzWbDlStXcPz4cbS0tCAxMRFr167F5s2bodfrZ+R6UkEQMDY2BovFgqtXr+Lo0aNobm5GQkICG0ZRWlrK4mLcluD4/X64XC64XC709/fj/PnzOHv2LLq7u5Geno41a9ZgzZo1zH6eiXbG6Ogoent7cerUKRw5cgQjIyMoLy/H+vXrUV1djeTkZG5nRBjUPqZ2xqlTp3Dq1Cl0dXVBr9czO0OtVs8oO4Pi8XgwNDSEtrY2fPzxx6irq4NEIkFVVRXWrFmDyspKJCQkcLmdQ9DtJS6XCxaLBRcuXEBNTQ2ampqQnJyMdevWYd26dcjJyWG6eCZBV40bjUZcuXIFhw4dQnt7O7RaLdatW4dVq1ZBr9cjPj6e29ARitiGHhsbw7lz51BTU4OGhgYkJiZizZo12Lp1K3Q6HVJSUmaUDAQCAVitVrS1teHw4cM4c+YMZDIZi7UUFhYy25lPj5y9iHPIXV1dOHLkCM6fPw+Px4Oqqirs2LEjJK42ExAEgU05b2howMGDB3Ht2jWkpaVhzZo12LRpEzIyMqBQKGZM3ptzd9B77HQ6MTIygkuXLuHEiROor6+HSqXC1772NaxZswZarXZGbdWksTODwYDLly/j4MGD6O7uRlZWFtauXYtVq1YhIyODn/sRjDjuOzo6irNnz6KmpgaNjY1ISUnBfffdh02bNkGr1SI5OfleZGBqCnoNBgMOHDiA06dPY3h4GAsWLMCWLVtQVVUFhUJxF9fLmQ243W5cu3YNJ0+exPnz5xETE4N169Zh27ZtyM3NnVZlFQgEWEfZlStX4HK5UFBQgHXr1qGqqgo6nY4rU86E0GBCS0sLzpw5g/Pnz2NkZARZWVlYuXIlNm7cCI1GM92XiUAggEuXLuH48eO4evUqoqKiUF1dzQp6ZlIREmdq8Pv9uHnzJk6fPo0zZ85gbGwMxcXF2Lp1K1asWBEycXqqcTqduHTpEg4fPozGxkbEx8dj9erVWLlyJcrLy2dMESdnaqCJiBs3bjAbwuv1oqqqCuvXr8fy5cunVSZcLhdOnDjBEtkZGRnYsGED1q5dC61Wy+2HCEQQBAwNDaGmpgYnTpxAZ2cnMjMzsWHDBmzduhWJiYnTem3UQTx+/Dja2toQFxeHpUuXYuXKlaioqEBcXNy0XR9n5iEIAqxWKy5fvowzZ86gvr6eTUffsmULKioqpn2VJU1+Xbx4EZ9++ikaGhoglUqxZMkSLF++HFVVVVAqldN6jZyZBdWFdXV1OHnyJK5fvw5BEFBSUoJNmzZh6dKl064LBUFgSZIzZ85geHgYRUVF2LhxI5YsWQKVSsX9szkG3RBFg7zt7e3QaDS47777sHnzZmg0mmmTCTpF7NixYzh58iQMBgOLeaxevRpZWVkzrnCTM3VQW+LixYusMCEhIQFLlizBtm3bUFxcPO3yEQwG0draitOnT+Ps2bMYHBxERkYGVqxYgcWLF6OkpITHGThfGDpx/cqVKzhz5gxu3rwJqVSK0tJSrF+/HkuWLJnWmBpA3pcdHR04cuQIzp49i9HRURQXF2PTpk2orq5GWloatzPmGIIgoK+vj9kZnZ2dLH61ceNGpKenT6tM0IYLWnx88+ZNxMfHsw1zlZWV026/c2YWgiDAYrGwhs7GxkbIZDIsWrSINUbOhKIzs9nMfL7+/n5kZFULUR0AACAASURBVGSwYp7s7Oxpt5E404c4HldTU4O6ujrExcWxvHJJScm0yocgCGhoaGCFncFgENXV1di0aRPKy8v5Vtc5gNfrRW1tLWpqanDmzBkAYAMZS0tLp1XH+v1+XLlyBQcPHkR9fT1iY2OxYsUKbNiwAcXFxdy3i2BofOrChQs4evQoOjs7odfrsXnzZmzYsGHaN40YDAZ27huNRuh0Otx3331Yvnw5j53NcWhe+fLlyzh16hRu3LiBhIQErF69GuvXr8f8+fPvpp5g8gp6A4EAhoaGsG/fPvzud7+DTqfD17/+dSxatAgajYavj5gDBAIBGI1GNDc3Y+/evWhqasK2bdvw9NNPIz09fcomQQWDQTgcDly6dAnvv/8+2tvb2dTHwsJCpKen80kMnLuCTlfq7+/HlStXcOTIEZjNZqxfvx6PP/44dDrdlMoULX6oq6vDu+++i9bWVqxatQrbtm1Dfn4+0tLSuOHAgSAIGB4eRldXF86ePYsDBw5AoVDg2Wefxdq1a9mkhsmWW6qTz58/jzfffBNWqxVbt25l3fV8rTAHIHJisVjQ3d2Nw4cP4/Tp08jKysIzzzzDGsKmQk4EQYDdbsf58+fx9ttvY2RkBPfffz/WrVuH7OzsGdUNypk8aFNPb28vLly4gP379yMQCODJJ5/E5s2bkZiYOCUF3XSKsM1mw+HDh7F7925ERUVh+/btWLZsGZtQwovLOZ+Hz+fD4OAg2tvbceLECZw8eRJZWVl49tlnWWHCVE7bCAQCGB4eRk1NDd59913Y7XY2TSo7OxsqlYrLNedz8fv9sFqt6OjoQE1NDY4ePYrU1FQ8/vjjWL9+PRQKBaKioqbMfvD5fOjt7cUHH3yAY8eOobCwEA888AAWLFiAjIwMHoPgACANY319fbh+/Tr2798Pg8GAr33ta3j88ceRlpY2JRMgxdNu3nvvPRw6dAgZGRl44IEHUFlZiaysrBm5lYgzvfh8Phbz/eSTT3D58mUsXLgQL774IgoLCxEbGztlMkNjDE1NTdi9ezeuXr2K4uJi3H///SgpKZlxU3w4sxOfz4ehoSF0dnaypsr4+Hg8+uij2LJlC5KSkqZsai+1M7q7u7F7926cOHECRUVFePDBB1FeXs5yb1zmOU6nE319fairq8O+ffswODiIhx56CN/4xjdYvmCq5ITaGsePH8fu3bshkUiwefNmtgmJx4M5nwe1WQcHB9HR0YGjR4/i7NmzyM7OxhNPPIFly5Yxn28qr8dsNmPv3r04ePAgVCoVtm/fjsWLF0On03H7gzMOakO3t7fj97//Pa5du4ZFixbhmWeeQXFx8ZT5XXSiYFtbG3bt2oXz58+jqqoKDz74IIqLi6FSqWZEoTxnaqHNbB0dHThw4ADOnTuHhQsX4qWXXkJ+fv6UTb+luZjGxkb85je/QXNzMzZu3IgNGzagqKiI5z/mGFQe+vv7cenSJezduxculwvPPPMMNm7cOGVb4um5bzAYsGfPHhw+fBharRb3338/qqqqoNVq+VA9zji8Xi+MRiNaW1uxb98+NDQ0YNmyZXjqqae+aOzsqy/oFQQBNpsNH3/8Md577z2WGFy+fDl7M3FBnlvQ4oObN2/irbfewvXr17F9+3Y89dRTkz7RdHh4GIcOHcK+ffvg8/mwefNmPProoyHd6VweOfcK1ZHBYBBXr17Fnj17cO3aNVRWVuKxxx5DVVXVpBbSUqfr7NmzeOeddzA4OIgtW7bgySefZEEwLt+ccKjc2u12HDlyBLt374bf78fjjz+O+++/f1In5zscDhw/fhzvvPMOgsEgHnvsMWzbtg1JSUkAuD7mjIfK68jICHbv3o2DBw9CoVDg+eefx6pVqyY1UezxeHD27Fn8+te/htPpxI4dO/Doo4+ySSFcXuceVB59Ph8rqHW5XHj66aexdevWSXXY6ZQdGizQ6/V48sknsXLlSi6TnHtGEAQ2KeTAgQPYt28foqKisHPnTmzdupWdz5P5800mEw4ePIgPP/wQycnJ2LlzJzZu3MjsES7XnLuF6uqxsTEcPnwYH330ERwOBx566CE89NBDUKvVk/rzg8EgWlpa8P777+PMmTMsOVdaWspjEJwJoTLr9/tx7do17Nq1C01NTdiwYQOeeuopZGZmTqp90dnZiV27duHUqVMoKyvDE088gaqqKpbA5fLKuRPUlujp6cGHH36I48ePIzc3F8888wyWLFkyqROTqA3z6aef4qOPPsLo6CjWrVuHnTt3svcNl1/OVw3V2Q6HAydOnMDvfvc7DAwMYO3atdixY8ekT6oOBAJobm7Gf/3Xf+HChQuorq7Gs88+i3nz5nE7gzMh4jjG1atX8e6776KtrQ2bN2/GE088AZ1ON6kyEwwG0dPTg/379+PgwYPQarV44oknsG7dOrYhhsss526gMk2Hl+zduxeHDx+GVCrFjh07sH379imJZXR0dODDDz/Ep59+innz5rGiYl4HwfkiUBt6YGAA7733Ho4fP46srCy8+OKLWLRo0aRu0KK2xDvvvIOrV69i5cqVeP7555GVlcXtZw6AW/LZ19eH999/H8eOHUNpaSlefPFFlJaWTqqtGwwGcfnyZWavbNmyBU899RSL5XH5nNvQupiamhq89dZbsFqteO655yY9jxEMBtHW1oYPPvgAp06dQmlpKZ566ilUVVXxc5/zhaB6tbe3F7/97W9x6tQpFBQU4IUXXkBFRcWdhuF+tQW9dK3VP/zDP8DlcuGb3/wmli9f/qVXDwUCAfz2t7/F0aNH8eyzz2Lz5s139f10JPfrr7+OgYEB/OAHP0Bubu5dfX9TUxN+85vfYGxsDA8++CC2bds2YXcSLV49dOgQ5HI5tm3bxr5O1xbU1NTgW9/6FntjBwIBHDhwAEeOHIFcLmeT3+RyOfbs2YMPP/wQgUCA/YyUlBS89tprLNBvs9mQnp6OHTt2YMmSJZDJZOzn3bhxA6dOncK3v/1t9vO8Xi927dqFM2fOID4+Hjt37sTy5cshlUrh8/mwa9cu1NTUjHvtq8Dj8eDy5ct46623MDo6ildeeQXLli37Sg9/eg8uXryIf//3f4fb7cbOnTtx3333fWXrLHt7e/HGG29gdHQU3/ve95CdnX1X3x8MBnHu3Dm8//77KCwsxIsvvnjbIjrqmH7wwQe4ePEiCgsL8dJLL0GlUk34b69evYp33nkHXq8Xjz32GNauXQupVDrutW984xtYt24dpFIpGhoa8O6778JoNCIlJQUPPvgg1qxZA7lcDr/fj48++ghHjx5lTvH69eshk8lw9OhRvP322/B4POwaYmJi8Nprr0GhUOD06dPYu3cvAoEANm7ciO3bt7MOrmAwiPb2dhw4cAAvv/wyez/V19fjvffew8DAABQKBR544AFs2LABcrkcgiDg+vXreOutt+B2u7Fjxw5s2LCBfW8wGERHRwc+/vhjfOc73wlJHIyOjuI///M/ce3aNcjlcjzyyCPYuHHjVyp7fr8fzc3N2LdvH06cOIENGzbghRdemJSVmYIgYHBwEL/4xS9w+fJl7NixAw899BAyMjK+kk6k9vZ2vPHGGxAEAa+88gq0Wu1dfX8gEMBnn32GPXv2sCR2bGzsF/peOnF43759+Oyzz6DX6/H8888jOzt7wr+juMjppZdeYu+l9vZ2vPrqqzAajQCA6OhoPPfcc9iyZQsEQUB7eztef/112Gw2bN26FV//+teZLAmCgP7+fuzZswcvvvjihOudvV4vfvazn7FJW/R33rt3L7xeLzZv3owdO3Yw2a2rq8OuXbswOjqKZcuWYefOnYiPj0cwGMTJkyexd+9eeDwebNq0CY888gjkcjmuXr2Kf/u3f8PY2Bj7uTKZDD/5yU9QUFBwV/fkdn9rm82GEydO4N1334VGo8Gf/dmfoaSk5CvtaKN/71dffRXd3d34oz/6I6xfvx5qtforeW8cPHgQ77//PjZt2oSnn376rq/d4XDgV7/6FRoaGvDyyy9j0aL/n7fvDqviet5/KSLE3hCjRmOJvWABRSx0xa4gCmIsUWNFjCVVjaJGsceo2DuKXaxYULEBKiiiAtKl985t+/7+8HvPzytoxOBnnuf+c2dnztnd2XNm3pndMf5kWbWt7Nq1C0lJSejbty+cnZ3LTVzK5XJcunQJV69eRe3atTF+/HhR3FFaWoqTJ0/i3r17qFWrFkaMGIGePXtCR0cHcrkcly9fxpUrV1C7dm24uLigQ4cO0NLSQn5+Pvbt24dnz57B0NAQ48aNQ8eOHaGtrY2rV6/i/PnzKC4uxjfffIPRo0cLnrog8dKlS6hVqxZcXFzQsWNHaGlp4cqVK7h48SIKCgrQpEkTODg4oHPnztDW1sa1a9dw9uxZoXPUqFHo1KkTtLW1cf36dZw5cwbFxcVo2rQpRo8eLXiVQeo3hK9evYpjx46hXbt2WLhwIYyMjCp1jSWJvLw8bNiwAYGBgXBycsKQIUMqxV5zc3OxZ88evHz5Ej/99BPatWtX4bk9f/4cR44cgYGBAWbNmlWuP/AhUqlU8Pf3x9mzZ6Gnp1cm6Hx/rKKiIhw7dgxmZmZo3769+D8+Ph5Hjx5FXFwcWrVqhSlTpqBu3brIz8/H5s2bERYWBuBtEDtgwADMnDlT8J49e1Yub//+/Xj69Cl0dXXRpUsXuLi4oFatWmK/O3LkCMLDw9GxY0ex1hcUFGDfvn1CrnPnzhg/fjxq1aqFgoICbN68GU+fPhXn1K9fP8yZM6dC1/xjlJubi2vXruHgwYNo2bIlFixYgMaNG1e6PSoUCpw+fRqHDx/GN998A2dnZxgbG1dKATFJnD59GufOncOIESMwcuTICuvMy8vDjh078Pr1a/z0009o27ZthcaPjY3Frl27kJmZqbF3vn9caWkpfH19cePGDTRs2BATJkwQe6GPjw9Onjwpjm/YsCE8PT1hYGAg5K5fvw5DQ0NMmDABrVq1EmvvuzxXV1e0bt1a8C5cuIDr16+jQYMGH+TVr18fEyZMEDyZTIYLFy7g2rVrqF+/vvjKxqfw1DFhvXr14OrqKhLzGzZswIMHDzSuSceOHbF06dIK3at/uxeZmZkICAjA0aNHUa1aNcyePfuLvKBGEpIk4dq1a/Dy8kKNGjUwceJEdO/eHTVr1qyUZ+jmzZs4dOgQ+vTpg4kTJ1b4yyKlpaXYvXs3QkJCMHXqVPTq1euTZUkiJSUF+/btQ2xsLExMTPD999+Xm5BRKpW4evWq6Jzg4uIi9k65XI4zZ87g9u3bqFatGoYNG4bevXuLeD82Nhbe3t6IiopC9erVMXfuXLRu3RolJSXYt28fQkJCUKdOHYwbNw5du3aFtrY2bty4gZ07d0KSJABArVq14OHhASMjI431PTIyEtWqVcOcOXPQpk0b+Pv7w8vLS0NuxYoVaNSokdhX8vLyYGRkBAcHBxgbG0NHRwcBAQHw8fFBQUEBGjdujJEjRwreu9crOjoaZ86cwQ8//IA6depU6F79G+Xm5uLevXs4fvw4ZDIZpk+fLmLdyiSSkMlkOHXqFA4ePIguXbqI57gyOlQlJSVh9+7dyM7Ohru7e4UwLeCtHxUYGIhjx47h22+/xZQpU8qNcT5EH1uj3if13u3j4wNHR0eNF7nlcjlOnDiB27dvQ5IkWFhYwNHREZmZmTh48CAiIiKgr68Pc3NzjB49Gvr6+iLe2717dxl/OyUlBQcPHsSrV6+gr6+PPn36aLyApVAocOrUKfj7+0OlUqFfv35wcnJCTk4ODh48iJcvX0JfXx9mZmZwcHCAgYGBSKzu3r0biYmJMDMzw/jx46GnpyfGi4yMhI6ODnr16gVnZ+dPjnU/9Vo/efIE3t7eiIuLw9SpU2FnZ1epnc7U++rZs2dx6NAhtG/fHo6OjjA2Nq6UcRQKBQ4cOIDbt29j6tSp6NevX4Xnl5ycjD179iAzMxOLFi1CkyZNPni8SqXC9evXcf78eRgYGMDZ2Vmse+/rTUtLw4EDBxAVFQVjY2NMnjwZBgYGSE5OhoeHBzIyMsTx2tramDFjBrp06YLNmzcjPDwcAMRXBadOnQrg7VqujqFkMhm6d++OyZMnQyaTYf/+/QgLCxOtoV1cXMSz966/3adPn3JjA6VSiX379qFFixawsrJCbm4u9u3bh5cvX4IkOnfujIkTJ5Z5npVKJfbv34/mzZvD2tparPHe3t6IjY1Fy5YtMWXKFI0PHvxXUhe3XLhwARcvXkS/fv0wbdq0Sov73x1HnejdtGkTFAoFnJycYG5ujoYNG1Za/HnlyhUcO3YMFhYWGD9+fIX9oeLiYuzcuRNhYWGYNWsWunXr9smyapxhz549SExMRJ8+feDi4lLu86lQKHD58mVcvny5DF7wLq9WrVoYP3684BUUFGDv3r149uwZGjRoAGdnZ4EXvDuP58+f4/r165g6dSqqV6+OHTt24MaNGxpzaNGiBdasWaMhFx4eDj8/P0ydOhU1atSAQqGAn58fLl68iBo1aggMQltbG7t27YKfn5+GzubNm2Pt2rXYvXt3GV6zZs3g6emJ69evw9fXF/n5+fj666/h4OAgnv2P+UqVaY9FRUV4+vQpfH198fjxYwwZMgRTpkyp9Jc91X7GsWPHcPToUXTv3h3jx49H69atK2XdTkhIwO7du1FUVIR58+ahadMP5gzLJUmScO/ePfj4+KBNmzaYNGnSJ+cE1eemjssaNmwIV1dXEbOVd3xqaipOnjwJZ2dn1KtXT/wfHx+PXbt2iU56jo6OwueTyWQ4fvw47t69C5KwsrLCqFGjEBERgc2bNyMvL0+MoauriyVLlqBt27Z48eIFDh8+jJycHHTr1g3Ozs5lvrqpUCiwefNmWFpaimddLpfDx8cHd+7cAUlYWFjAwcEBenp6ZfwhS0tLwXtX55YtW9C/f3/06NGjQvfjY1RaWopHjx7h6NGjSE5OxvTp02Ftbf1FfGOFQoFz585h//79aNKkCSZOnIjOnTtX2vMRHByM3bt3o02bNpgxY4bw/z6V1LnQgIAAODg4wM7O7pPnpY6fjxw5gufPn6NDhw744YcfyvWvJUnC3bt3ceLECWhra2PcuHEC832XkpOTceDAAUyePLnMh5DUvEmTJsHIyAiSJAmsWEdHB4MGDYKFhYXI56lzvAYGBhgzZgx69+4NHR0dnD17FsePH4dSqRS6a9asiR07dgAAvL29ERAQAAMDAzg6OsLMzAw6Ojp49OgRNm/ejNLSUgBA9erVsWjRIrRr1w6SJMHPzw+XLl2ClpYWBg4cCEtLS2HPGRkZOHz4MJ4/fw59fX24urqiV69elep/ZGVlwd/fH8ePHxdxrLGxcaV3aFGvVxcvXsSePXvQsmVLuLq6okuXLpVSgJmVlYU9e/YIfK1NmzYVnp86B1WzZk3MnDkTdevW/eCxn5qDI4moqCjs3r0bubm5GDRoEIYOHQpdXd1yc3ATJ06EjY0NSIo6hqKiIvTu3VvEXAA+mJ+LjY3FoUOHEBMTg2rVqsHa2hr29vaoWrWqOMcjR46gsLAQpqamcHR0LLOuyOVybNiwAfb29ujcuTNiYmJw5MgRxMbGQk9PD5aWlhg+fHiZ+/a+3IfycytWrECrVq0qdH8+RCqVComJibh48SLOnj0LU1NTuLu7V/qXy9Xr8rFjx3D48GGYmJhgwoQJaNGixX/+Gm9xcTH27NmDR48ewc3NrUJ+r3pu0dHROHDgAORyOdzd3WFkZPTB49/Ns9WpUwfjx49Hu3btPug3ZGVlwcfHByNGjMDXX38N4O26eujQIURGRkJXVxe9e/fG2LFjoa+vXybu7927N8aNG1cu711MICUlRejU1taGqakpXFxcoK+vj9TUVCGn5jk7O8PAwOCjPHX8quaZmJjAxcVF8NQ4yvu8yiJ17depU6dw+/ZtODg4wNnZ+Yv4uoWFhThy5AhOnToFKysrODk5oVmzZv85vlMqlTh48CD8/f0xefJkWFhYVHhuqamp2L17N9LS0rBo0aKP1gWpVCrcvHkT586dq1AO7l1MIC8vT3wkUVdXF127doWLiwtq1qxZ5tz279+Pb7/9FlZWVkhLS8Py5cuRnp4ujtHW1saUKVNgY2Mj9uQXL16gU6dO+OGHH4TPrt4Xjh8/jp49e6JTp07if5VKhTt37iA7OxsODg5CtyRJePnyJY4dO4bExETUrl0bixcvhpGREc6fP48rV66gtLQULVq0gKOj4wdxxIoSSeTn5+PBgwfYuXMn6tSpg8WLF1d6rKfGzs6cOYODBw+iffv24qMNlbHvp6WlYc+ePXjz5g1++umnCtd9SJKEx48fw9vbG0ZGRpg+ffoHC5vVz9jp06dx9+5dNGvWDJMnT0ajRo3K3ffVX8guLCzEsGHDYGdnB11dXURERODw4cNITExEjRo1YG9vDysrK+jp6SEgIAC7du1CSUmJ0FWlShVs3LgRDRs2RGFhIQ4dOoTHjx9DR0dH6H39+jW8vb2RkJAAAwMDDBw4EAMHDoSenh6ioqJw+PBhxMfHo0aNGhg4cCBsbGygp6eH+/fvw8vLC8XFxRrjrV+/Ho0aNUJRUREOHz6M4OBg6OjoYMiQIRg0aBDi4uJw+PBhxMXFoXr16rCzs4Otra24p+rC29OnT2Pq1Kn/udb1fVKpVIiPj8e5c+cEdjZ37lzUqlWrPPv9aEGvKAr9wE+DFAoFz507R1tbW27bto05OTmUJOn9wz6LJEliZmYmx4wZwx07dnyW/O+//05PT09evXqVr169qpB8dHQ07ezsePHiRT59+pR2dnY8deoUVSpVmXHevHnD1atXs2XLlty4caPgFRcX8+jRozQxMaG9vb3Gtbl48SLNzc354MED+vv7s3fv3vT396ckSfTw8GC/fv1oYWFBCwsLdunShePGjaNSqeTGjRt54sQJJiUl8cSJE+zUqRMfPnxISZJYXFzM48ePs1evXrS1tRXjKZVKbt68mfb29gwNDeWVK1dobm7Ohw8fUqFQcMuWLbS3t2dISIjgPXjwoNLupfo6FRUV8dChQ7S0tKS3tzdLS0srTX9OTg49PT1pbW3NAwcOsLCwsMy9+q+kVCr54sULdu/enc+ePauwfFRUFEePHs179+7x4sWLzM3N/eCxMpmMS5cupZubG1+/fs1ffvmF06ZNo0wmK3Psy5cvaWVlxZs3b/Lhw4e0srLitWvXKEmS4N24cUPw/Pz8KEkS9+/fz7179zIpKYnXrl1jp06deOHCBSqVSh44cIAWFhYMDg7mvXv3aG5uzkuXLlGSJHp5eWnYZ48ePThw4EDm5eXx/v377NWrF/39/RkSEsL+/fvzyJEjVKlULC0t5ZUrVzhgwAB269ZN4/7v27dPzOXGjRvs3Lkzz549S0mSGBERQWtra/r5+fHx48e0trbmhQsXKEkSS0tL6efnRwsLC3bt2pUlJSVCZ0FBAadPn85Vq1YxMTGRd+7c4aVLl6hQKCp87/6NJEmiQqFgTEwM58yZQ3t7e967d69Sx5IkiXfv3uXw4cO5aNEiJiYmUqlUVupzqlAoGBwczF69ejEyMrLC8qGhoRwxYgSDg4N56dIlFhUVfbKs2rZcXV356tUrenp6ctSoUSwoKChzrEwm4927d2lvb8/vvvuOmZmZghccHEwrKysOGDCAFhYWtLOz4/nz50mScXFxHDJkCE+fPs3w8HAOHjyYhw8fpkqlolwu5/379zlkyBB+9913TE9PLzOuXC7nwYMH2apVK16/fp2SJPHSpUs0MzPjzZs3+ezZM9rY2HDfvn1UKpV8/vw5zc3NeebMGUZERHD48OH09PSkXC7nlStXaGZmxhs3bjAsLIw2Njbcs2cPlUolL168qPGMmZmZ0dzcnNHR0RW+Jx8jlUrFnJwcrlu3jpaWljx//nylrcsymYx+fn60trbmqlWrmJGRUelrcmFhIRcsWMCFCxdSqVRWWH7Hjh10d3fn7du3+ejRowrJpqam0snJiXv37mVERAQdHR25devWcudx/vx5Dhs2jKGhody3bx/t7OyYlJREkty5cycHDx7Mp0+f0tvbm6ampnz9+jXJt37C0KFDGRoaygMHDtDOzo5v3ryhXC7n/PnzOWHCBL58+ZK7d+/mgAEDmJiYSJL87bff6Ofnx6SkJG7atInGxsaCd+XKFQ4ZMoQhISE8dOgQbW1tBW/RokW8efOmkOvWrRvj4+NJkn/88QevXLnCpKQkbtmyhV27dhW8JUuWCN7ff//Nrl27Mi4ursL3499IpVIxKSmJy5Yt45AhQ3j9+vXPuu/lkSRJfPbsGceOHUs3NzfGxsZW6vqqUqmYmJhIExMT3rlzp8Lyubm5dHV15blz5+jr68vk5OQKyd+/f582NjYMDAzk+fPnaW1tzefPn5c5P7WfM2vWLDZr1ow3b94UvIyMDI4ePZpr1qxhdHQ03dzcOGXKFJaUlDAtLY1jx46lubk5LSwsaGlpybVr15Ik09PTy/DWrFlDkkxISOCiRYv4/PlzvnjxgqNHj+bs2bOpVCpZUFDAOXPmcPny5YyOjubMmTP5yy+/UC6XMzExkQsXLmRYWBhfvnxJBwcHzpw5k0qlkpmZmXR2dmafPn3EGrpy5coKX/OPkSRJVKlUTE9P59KlSzl06FAGBARUagwUHx9Pd3d3jhw5kjdu3GBxcXGl++W5ubmcNm0aV65c+Vm6PT09+fvvv/PGjRt8+vRphWQTEhI4fPhw+vj48OXLlxw6dKjYO9+f5+HDhzlmzBiGh4dz69atHDp0KLOzs0XM1KNHD3GvnZ2dxbU6evQoHR0d+fz5c/7zzz8cMmQIs7KyKEkSvb29NXiDBw8WvGPHjtHBwYHPnz/n9u3bOXjwYGZmZlKSJB4/fpyjR4/W4GVkZJAkfXx8OHr0aIaFhXHHjh20t7cXvBMnTgiel5cXA+ReuAAAIABJREFU7e3thZ9x8uRJjho1imFhYdy5c6cG7/vvv2f//v3F+bVr145Lliyp8L36FFKpVMzNzeXOnTtpbW1NLy8v5uXlVapdp6WlcdmyZbS3t+f58+dZUFBQqXZNvo2/ly1bxpkzZ5YbN/0bHTx4kDNmzODdu3f58OHDCslmZmby+++/59atWxkVFcXx48fT09Oz3Hjgxo0bHDRoEB8/fsxjx47RxsaGMTExJMnDhw/TxsaGT5484dmzZ2lqaspnz55RkiQmJiZy+PDhPHToEFNTU3ns2DGGhYVRoVDwjz/+4NixYxkeHs6jR4+yX79+jIyMpCRJ3Lt3L7t37y5sadSoUcIXSUpK4ogRI3jgwAGmpqbSx8eHT58+pSRJ3Ldvn4bcyJEjhd+wZMkSXr16lcnJydy9eze7du3Kly9fUpIkrly5kr6+vkxKSuKePXvYpUsXwVNTUVERp06dyv79+1d4X/tUUmMQx48fp52dHf/66y/xrFeW/jdv3nDu3LkcPXo0AwMDKZPJKtWulUolIyIi2L17d4aGhlZYPiYmhg4ODgwICOCFCxeYk5NTIflTp06VWaPS0tLKHKdQKPj48WM6OTmxRYsWwp8lyZKSEq5YsYJubm6Mjo5meHg4Dx8+zOLiYj548EDs9SEhIezXrx89PT2pUqk+6m8HBgbyzz//ZHR0NENDQ9m/f3+uXbtW4A6rVq3inDlzGB0dzZcvX/LgwYMsKipicHAw//zzT75+/ZqhoaEcMGAAV69eTZVKxbS0NI4bN447d+5kZGQkx44dy82bN1OhUDAwMJDLli1jTEwMQ0NDaWlpydWrV1eaL6omSZJYUlLCy5cv097ensuXL2d2dnal6U5OTua8efM4cuRI3rlzh6WlpZXuX6Snp3Po0KE8dOhQheVVKhUXLFjAv//+m5cvX2ZUVNRHj79z5w7t7OwYFBTE06dP08bGhq9evSpzTjk5OZw2bRrXrVvH169fc/LkyVy+fDkVCgVfvXrF/v37C/ygf//+NDY25q1bt5icnExHR0cNP1aN+crlcm7fvp0TJ05kREQE4+LiuGvXLubl5TE6Opo///wzX7x4wfDwcA4fPpzu7u5UKpVl/G1/f/9yr8PNmzfZtm1b7ty5k+TbZ3nhwoV89eoVw8PDOXLkSM6bN09jj1GpVPT392fbtm25fft2kmRWVhYdHR25evVqRkdH093dnZMmTdLAziqD1JhYbGws586dy6FDh/Lx48eV+oxkZWVx9erVtLa25pEjR5ifn0+VSlXpvkRhYSF//vlnuru7fxamt2vXLs6dO5d37txhcHBwhWTV69CuXbsYGRlJJycnbtmypdx5XLx4UcT27+IFJHnp0qVy4365XM6FCxfS1dWVL1684N69ezlgwAAR26spLy+PTk5OtLOzE2vQzJkzNfzSDh06cP78+Rpy+fn5dHZ2pq2tLbOyskiS165do729PR8/fkxvb2/a2toyNjaWJDl37twyOt3c3ChJUrm8uXPnUpIk/vrrr7x27RqTkpK4bds2Ghsb8/Xr1x/1lSrbTsi3di+TyRgSEsJJkyZx3LhxfPLkSaXiFHFxcZw1axadnJz46NGjL+JnhIeHs0ePHgwLC6uwfEREBEeNGsUHDx7w4sWLzMvL+2RZdcw2ZswYPn/+nFu3buWQIUPK3ffkcjmDgoI4atQotmzZkgkJCYKXlJTEkSNH8siRI3z16hVHjBjBXbt2UalUsqSkhEuWLOFPP/3EmJgYhoWF0dvbmyUlJbx+/brG+t+nTx+amZnx5cuXjIiIoIWFBb29vRkVFUVHR0cuX76ccrlcjKtQKOjj48OWLVvywoULJN/6PH/++Sfd3d0ZExPD8PBwHjlyhMXFxcIfmjdvXhneuzpPnjzJli1bCiy7MkntZ5w/f56DBg3iX3/9VWHf8N/0x8fH083NjSNGjODt27dZUlJS6c+fTCbjzp07OWbMmArZnJp8fX3p4uLCoKAg3rp1q0LzKywspJubG5ctW8bo6GjOmjWLixYt0rANNT158oRWVla8d+8e/fz8aGVlxeDgYI3xSkpKuGDBAg08+H2eiYmJ4F29epV9+vTh/fv3eefOHZqZmdHPz69Mjvfq1as0Nzfn/fv3KUkS16xZo5Fr6Nq1Kx0dHVlSUsKtW7dy0KBBDAkJoZ+fH/v06cN79+5RkiSeP3+epqamQm7YsGEC/7l+/TrNzMx49+5d3r9/n2ZmZrx48aLAm5ydnbllyxYmJSXx0qVLvH37dqXnBtT4XEFBAXft2kUrKytu27aNhYWFlTpOcnIy3d3dOWzYsC/iQ6tUKiYkJLBHjx68d+9eheUzMzPp4uLCixcv0tfXl6mpqR88VpIk7tix45NycHFxcbS3t+eZM2f4/Plz2tvbi1zvx3JwT58+ZZ8+fXj+/Hm+evWKgwcP5saNG6lQKBgfH88hQ4bw1KlTIj936NAhqlQqXr58mevWrWN8fDyDgoLYs2dP7tq1iyqVimFhYTQ3N+fZs2cZERHBoUOHcv369Ro+klwu56FDh9iqVSteu3aN5FufaN26dUxMTGRwcDBNTEzo5eWlYYtyuZyHDx9mq1at6OfnJ+TKy8+9/5xWBimVSkZHR3PhwoUcPnw47927V6m+RHJyMufPn08HBwcGBQVVqi+h1t+/f3+xF1aESktLOX36dB48eJAXLlwo45O+T+o829OnT7lv3z4OHDiwXDxJoVAwJCSEzs7ObNGiBV+8eCF4Dx8+5J9//smYmBiGhIRwwIAB/OuvvzRwBnXcb2FhIeL+j2ECQUFBXLp0qeBZWVlx5cqVVCqVfPToURmeh4eH4C1ZskTgGtbW1lyxYgWVSiUfP378Qd6TJ0/4xx9/MDo6mk+fPqWNjQ3//PPPL4JPyOVyPn78mGPHjuWsWbOYnJxcqetffHw8p02bRmdnZ7548YIKhaJS7TMjI4MjR47k3r17P0v+559/5saNG3nlyhVGRER89PjPzcG9iwnExsZy8eLFDA8P54sXLzhy5Ei6ublp3Nt38QIvLy+Sb/GCd/3aAQMGsEuXLrx27RoLCgo4e/Zsenh4MDo6mj/++CN//fVXyuVyqlQqvnr1im5ubmzWrBmvXr2qce02bdrEtm3b8tdff9W4Ls+ePeOwYcN4/vx5pqamcu/evYyLi6MkSVy4cCFv3rzJxMRErlixgiYmJiI2rCxS1xBu2rSJNjY2vHr16mflAT5ECQkJnDVrFkeNGvVFsF6VSsXY2Fh269aNQUFBFZZPTk6mk5MTb9y4QV9fX5GDKo+USiU3bNjAH374gZGRkfTw8KCzs3O5mNDr169pa2vLS5cuMTQ0lLa2tjx9+jRVKhVPnjzJrVu38s2bN7x79y67du1Kb29vEdO9u2eamprS0tKSaWlpLCws5OzZs7l8+XImJCTw/v37PH/+POVyOX18fPjPP//wzZs3vHfvHo2NjUXNzpkzZ7hlyxYmJiby/v37NDY25qFDh0SO7v3xLCwsmJycLHz1pUuXMj4+noGBgTx79ixlMhnPnz/PTZs2MSEhgQ8fPmS3bt24f/9+qlQqymQyBgQEcNCgQWzTpk2lYbHlkUKhYGRkJN3c3Ojg4MDAwMDy1u9EfqRm95MLeiVJ4u3bt2ljY8OTJ09WujNOvg2QXFxcREGvJEllfh/6X5IkDho0iD4+Ph/kv6vj/XPbtWsXhw4dSqVSSZVKxbVr13LixIllHFtJkhgdHc0HDx5w0KBB3LBhg+Dl5ubS39+ff/zxB4cNG6Yx1uLFi+nq6kpJkpiXl0dnZ2eRuAgODhaFcEqlkt7e3rx58yYlSeKTJ0/EQ5aWlkZTU1PxwOTl5dHf35/Lli3j4MGDxXhpaWkcOHAg//nnH5JvCx1dXV3p4eHB1NRUDho0iFu3btXgqR2DyialUsl79+7R1taWPj4+lVLwmJOTw99//52Ojo4MCwv7Iraopri4OPbo0UMU9FbEHu/du0dra2umpaX9q01mZWWJwlhJkhgeHs7u3buXKZiQJIlr167l+PHjBZC4aNEiurm5sbS0lJ6ennRxcRGO1+LFiwUvPDycubm5ItFpY2PDDRs2MCsri+PGjePSpUuFTjc3NyEXFhYmEqGSJNHPz48nTpygUqnkli1baG1tLcZzd3fnvHnzWFpaysLCQt66dYtbtmyhmZmZRuHgixcvxAsBJSUltLOz4+rVqwUY4ejoKBIES5cu5Y8//sji4mIWFhby9u3b/Pvvv9m7d2/xbEiSxAsXLtDS0pL5+flfzB7Ko8LCQgFSX758uVKeI/WzP3DgQG7fvl0D7Ktsev78uSjoreiae+HCBdrb2zM/P7/C665CoaCVlRWPHj1KSZIYExPD3r178/bt22WOLS4uZkBAAA8cOMBu3bqVKejdu3dvuUVBR48epa2trQBdtm3bRicnJ+bk5LC4uJh3797l4cOH2a1btzIFvWondc2aNWzTpg2vX7/O0tJSzp8/n5MmTaJcLqckSdywYQPHjBnD7Oxsnjp1it26dWNRURElSeKmTZvo5OTEtLQ0Lly4kBMnThSO4KZNm+jg4MDs7GzGxsYyPj5eXCt1wVFlvgTxLsnlcl6/fp3W1tY8ceLEf16XVSoVL1y4QGtra+GYfQmSy+X87bffREHvp9qr+r8pU6Zw48aNn+UjXLt2jebm5iIQOXXqFG1tbcsACCqVimPGjBHjpKamcuDAgTx+/DhJ0snJiUuWLKEkvS0IsbS0FA7y2LFjuWHDBkrS2yIoe3t7ent7MzY2lj169KCvry9J8s2bN7S2thY633X+wsLC2L59ewYFBVGlUtHFxYWenp6UpLfJ9iFDhvDIkSMkyQcPHoj98/nz52zfvj3v379fRmd4eDg7dOjABw8eCJ7aZl6+fMkOHTp8Fvj4qSSTybh3717a2try7t27/zmQkiSJSUlJHDVqFJcvX14ugFkZlJmZyV69eomC3n+zu3d/KSkpNDc3Z0hIyGfZ6+zZs/nLL79Qkt6C6i4uLty0aVOZ49Vg161bt9i9e3eNgt7IyEh27NhRFHldv36dvXv3ZkxMDNPS0rhly5ZyA8f09HRu2bKl3Jck8vPzNUCNf/75hwMGDGBeXh6joqJoamoqkq+BgYE0NTVlREREGblt27axX79+zM3NZWZmJjdv3vxR8LoyqaSkhF5eXhw0aFC5AM3nUGpqKp2dnTlv3jxRcPclqKSkhLNnzxYFvRXd88eMGcPdu3d/lk2ePHmSlpaWYn/cs2cPR40apbGfk2/XUHt7ezFOQkIC+/fvz8uXL1OS3iYhnjx5UmYMlUrFIUOGcNeuXZSkt4n9AQMG8NKlS4K3c+dOwbOwsODFixepUqk4dOhQenl5iXXZwsKCFy5coEql4rBhw7hjxw6NNdvX15cqlYrDhw/n9u3bxZpiZWXF8+fPU6VSccSIEWV4586dE7x//vmHkvQWBLe2tubZs2dJUuPlMJlMRk9Pzy+SPHj/2j169IijR4/mihUrKq3gp7CwkDNnzuTEiRM/66WxTyWFQsHVq1eLgt6K2vXcuXPp4eHxWXb98OFDmpmZiWIa9YuM7yckVCoVJ06cKJ69zMxMAS5LksTJkydz/vz5Yv8fPHgwDxw4QEmS6OnpyalTp5a5LwkJCezduzdPnDhBkmKPVz87R44c4a1bt8qd94YNGzh58uRy7/XRo0fLLTYjNff/6Ohodu7cmVeuXKEkSQwODhb+X2xsLI2NjXn16lVx7VQqFX18fLhw4UL269fvixX0qkmS3r4k+v3333PBggWVUrggSZIoEpw1axbfvHlTKXtAeZSQkKBR0FsRm1YnWtVJl4rYtUql4siRIz+4Rr1LpaWlfPjwIc+cOSMKq9QUEhLywZcTk5OTGRsbK8ZfsGABXV1dWVxcXK6/bWdnx+TkZKakpDAmJkbILVq0iC4uLiwqKuKzZ8/Yt2/fctea1NRUDbnFixdz3LhxLCoq4q1bt9inTx/hs5w7d47W1tZMSkpiamoqo6OjhdzPP//MMWPGVHqxgJokSeLr16/5/fff8+eff/7oy+Cfqi8lJYWTJ0+mu7v7F/Uv8vPzOXLkSFHQWxGfV6lUij3yU46fPn26wK1ycnLo5OQk7PXdc3/69Cl79eol7uGtW7doZmbGmJgYZmdn8/nz5yIOyszM5LJly1hQUMDk5GT+/fff5SafEhISaG1tLQpe3qXc3Fy+ePFC/L9x40ZaW1szLy9P+Nv+/v5l/G015eTk0MPDg927dxcJury8PIaHhwudmzdvpoWFhYZtqOV69OghCnqjo6PZsWNHPnnyhJIk8caNG+JafCkqKCjg7t27aWtrKz5A8V8pOzubixYtorOzM0NDQ78o7iuXy7l06VJR0FtRX0JdPP45voS/v7/GOnT27Fna2NiUeWZVKhXHjRsnxlH7C0ePHi3DS09P5+DBg3nkyBHGxcWxZ8+eouAmOTmZNjY2PHr0qIbugwcPcvbs2bS1tRWJrPv374u9XS6Xc+vWrRoFoCqViocOHeKcOXNoY2PDrKwsqlQqTpgwgatXr6YkvU0KDx8+nPv27StX57Zt20S8+T5v+/btDA0NFT6XGp+IiIhgx44dBX7+IV/pS1NeXh43bdrEQYMGlbsuVJQkSWJ2djYnTZpENzc3pqSkfDE/IyYmRhT0VtTeAwICaGNjw4yMjM/yMwYPHiz8VXXMdvny5TLHlpSU8P79+/Tx8aGxsbEo6JWktwWHAwYMEFj0oUOHOHToUKanpzM4OJjm5uYaBcBqSkhI0PAJIiMjuWnTJvFiTefOnYXPuGvXLg4bNkxgHup9+q+//mLbtm1FEdOTJ09obm7O2P8rWn+X1Dz1S3zvkyS9zTGuXr2abdu2/SIFve+OFRkZSRcXF/7++++VkjtRr0UTJkygm5sbExMTv5jNSpLEgwcPioLeitrtypUrxQsCFbFb9T0yNTUVa1VQUBBNTEzKfExKkiQuXrxYjFNYWMgpU6bQw8ND7GEqlYq+vr78448/2LNnTw3/WY2tv8/7/fffOXbsWEqSJPK4q1atKjfHO2HCBC5fvlwUhqnxTpVKxRMnTtDPz0/sH1u2bCH5Nm6fOHEily1bRqVSSV9f3w/a4vLlyzl69GhK0tvc4qRJk4Tc0aNHOXTo0Ap97OW/klKpZHBwMEeOHMm1a9dWmp+enp7OH3/8kbNmzRL5mi9BGRkZNDExEZh6RWw6Pj6effv2Fb7ix34KhYKWlpb/moOTpLcv2NvZ2QlsZevWrRw7dixzc3M/mIMjyWPHjrFHjx6ioH/t2rV0dnZmbm4uvb29aWNjo5GfGzNmDHNychgbG6sRt06cOFHklk+cOMFu3bqJl/g3bNjAsWPHinVakt7m0NS5O3VBb1xcHJOSkoTOSZMmcdasWRp55PDwcCGnLuiNi4vTyM+Fh4d/0fwc+Tam3r59O+3s7BgYGFgptlZcXMxZs2Zx2rRpX2xdzsnJoaWlpdgLP2VtVf8KCwvZt29f8XLFx34qlYqOjo4ip6HOs6lxsHeptLSUgYGB9PX1pbGxsUZB7/tYwsKFCzl27FgWFhaW4S1evFjE/R/DBN7n/frrr3R0dGRhYSHT0tLEi2dqnoODAwsKCsrwfv/9d44ePbpc3h9//CGK79PT0xkVFaXBGzly5BfLa5FvsZT58+dz6tSp5eZ5KkqS9BYPnTJlCn/66SdRN1PZVFBQQEdHR1HQWxH7VKlUoqDxU46fPXs2f/31V0rSp+XgysME3o/7t2zZQktLS40XmD6EFzx9+lT4GLm5uVyyZAnz8/MZGRlJU1NToffhw4c0NTVlZGQkFQoFQ0NDeefOHfbo0YNXrlwR1+nNmzcMCAjguHHjyhT0LliwgL/99luZ3L9av3oeDx8+5HfffceXL19Wyv18n5RKJU+fPk1bW1vxEbb/Quq1ZdKkSQI7+1L7fmpqKnv06CEKeiuy7798+ZIDBgwQ69XHfiUlJezbty/PnDlDSZIYFRXFnj17MjAwsMy5e3l5cfjw4eJl9L/++ouTJk1iYWEhIyMjRcynUCg4cuRILlmyhHK5nBEREUxNTRVj3r9/n/v376dCoaCfnx/79+9fLhb/vs7Ro0eLjzq9fv2a6enplKS3WKGjo6MoRI+MjNTwFwIDA7l3717K5XLeuHGD/fr1KxfHi46OFvNU4yaLFi2iTCZjUVERAwICxMdNvmRBr5qKi4u5YcMGDhw4UMQW79BHC3o/+fv6ycnJWLNmDX788UcMGzasUtt0f4jevHmDtWvXIiEhAY0aNcKMGTPQqlUr7Ny5E3fu3IFCoYCFhQUmTZqEgwcP4tGjR0hNTYWvry/GjBmDbdu2ldHZvn17rF27VmP+crkcERERaNq0KbS0tKClpYUOHTrAx8cHRUVForU78LblWosWLfDtt9+WabdXq1YtDBgwAE+fPi3zqeSGDRvi9evXKC0tRUlJCUpKSlC/fn1oaWlptNPJzMxEQkICLC0toaWlBWNjY/GZ89zcXJBEo0aNALxtkzJgwADRDk5NCoUCcrlctNnQ19fHd999h9DQUMhkMsjlctHi8l2eJEmV3mpV3abgt99+g4eHBzp06PDBlgifQiqVCnv37kVcXBw2bNhQ6S2PP0bqVqnq1iEmJiZwc3NDeno6VqxYgaysLOjo6GDRokWoX78+PD098eTJE7i4uMDZ2RlhYWF49eqVhk49PT1MmTIFzZs3R2lpqWiD17JlS0iShPDwcHTu3FkcX1JSglevXuHbb78F8PaT4u3atcO+ffuQn5+PiIgIwdPV1UW7du2wd+9eKBQKtG/fXrSsy8/Ph0wmQ5MmTcSn5NX2oquriw4dOuD48eNQKBTo2LGjGL+oqAjBwcEYN24cdHR0UK9ePSiVShQXF4MkCgoKRGuEatWqoX///khPTy9zj95tMShJEkpKSmBkZASFQoFXr16hWbNmAN7aT/v27eHn5weZTIbatWujX79+yMjI0NBJEsHBwahXrx4yMzORkpICAwMDGBoaQk9P74vaSLVq1eDo6IgaNWrA09MTzZs3r1Ab6vLozZs38PDwgIuLC8aMGVOpbTc/RgqFAr6+vjhx4gRkMhn69euHGTNmICEhAX/++ScKCwthYGCAxYsXo0qVKti8eTNCQkLg6OiIyZMn49q1a0hKStLQaWBggJkzZ8LKykrj//T0dGRkZIhnuEmTJqhZsyYeP35cplWngYEBzM3NoVAoyr2Xubm5iIqKgo6ODmrUqIH69euDJCIjI9GoUSOx3nfq1AleXl7Iy8tDs2bN0KdPH0iSVK7OoqIiXLt2DZaWljh69CiA/2+rderUETJdunTBkSNHUFBQgJo1a0JbWxuFhYXQ1dVFTk4O6tatCx0dHRQXF6N27doacgcPHkReXp5GK12VSoVLly7Bzs6uUlo5lEdVqlSBhYUFtLW1sXLlSrRr1w4dOnT4bH3x8fHYuHEj3NzcYG9vX+n7yIcoNzcX69evR1hYGGrWrClaZR8/fhxnzpyBXC5H165d4ebmhkuXLuHGjRu4f/8+bt26hZ9++gmrV68uo7NRo0bYuHGjRksTknj9+jXq1KkjWtN16tQJ8fHxSE9PF3syAOTk5CA+Ph7Ozs7Q0tJCvXr18PXXXyMwMBBjxoyBkZER8vPzIZfLUVhYCJVKhbp16yInJwdxcXFwcnKClpYW6tati8aNGyMwMBDGxsaQJAm1a9cGANSvXx9NmjRBSEgIxowZAxMTE5CEUqlEZmYm9PX1Ub9+feTm5iI2NhajRo2ClpYW6tSpI3Q6OzuLtuLqPUBbWxsNGjQAgDI6q1at+kGevr6+4H0J0tPTw/jx41GrVi2sXr0af//9t9jnPodkMhlWrVqFTp06Yf78+fjqq68qcbblk/R/7a937dqFrKwstG/fHnPnzoWWlhbWr1+PqKgoKJVKTJ06FSYmJli1ahXCwsIwZ84c2NnZoVq1arh27ZqGTm1tbQwbNgzTpk3T+D8/Px+RkZHClqpXr47mzZsjMDCwzLzUbXyysrLK+PV6enqoUaMG8vPzoVKpkJWVhRo1aoi2I8XFxYiJiUF2djb09fXRsGFDsWYVFxcjNjYWOTk50NfXh6GhIfT19VGjRg106NABJFFSUoKUlBQ0bdoUBgYGiIuLE2u4lpYW2rVrh9zcXMTExOC7777TkEtNTUXTpk3x1VdfIT8/HyUlJYiNjUVeXp7GeF+C9PX1MXHiRGhpaWHlypXYtGkTDA0NP1ufTCaDh4cHmjZtisWLF4vn/H9BmZmZWLNmDaKiolCvXj1Mnz4dXbp0wYEDB3D16lXI5XKYmppi5syZOHnyJO7du4eXL1/iypUrmDFjBtatW1dGZ/PmzbFx40aN/UulUiEyMhINGzYU+0OnTp2wadMm5Obmitap6jmlpKSI1n9GRkaoV68egoODYWdnB6VSicTERFSrVg16enqoU6cOatasiczMTCQlJQm5hg0bokGDBggODkaPHj2QnJyswatfvz6Cg4PRs2dPDTlDQ0M0aNAAQUFBMDExwZs3b9CsWTMNnUFBQTA1NdXgGRoawtDQEEFBQejVqxcSExM1eA0bNkRQUBDMzMzw5s0bNG/eHFpaWmjQoIHgDR8+HGZmZgD+f9tjAwMDNG7c+Ivagba2Nrp16wYPDw/8+uuvOHXqlNjDPpcUCgU2btwIhUKBv/766z89IxWlgoICbNq0CU+ePMFXX32FKVOmoF+/fjh79iy8vb1FTOTu7g5/f39cvnwZWlpaCAoKwqJFi7By5coyOg0NDbFu3TrUr19f4//o6GhUq1ZNrDcdO3ZEUlKSsCk15eXlISYmBgMHDoSWlhZq166Nb775BoGBgZg4cSKMjIyQkZEBmUyGoqIiyOVyEWPdunULvXr1QnJyMlQqFapXrw5DQ0PI5XKoVCqxZtSqVQvNmzdHSEgIgLd7vxA8AAAgAElEQVQ2lJKSIloK1q5dG7Vr14YkSbh16xa6deuG5ORkKJVK1KhRA4aGhqJtdXly6pZ+at1yuVzYNwD06NFDYBbqmFjdPlZtzxkZGejbt2+5+1Flk5aWFlq3bg0PDw/8/vvv2LNnD9zd3f8ThiWTybB582bo6Ohg5cqVqFmz5v8Eh1Aqlbh27ZpoNdqjRw+4ubkhKysLHh4eyMjIgLa2NhYsWIBGjRphzZo1CAkJgaurK5ycnBAZGVkGL6pSpQomTZqEESNGaPyfnZ2NxMTEMmtUYGAghg8frnFs1apVYWpqirCwsDJxeVRUlIibIiMjUaVKFTRs2BAGBgZo1KiRACOLi4uRkZGBZs2aQVdXt1x/Oy4uDunp6ejSpUu5cnp6eoiOjoZCoUBpaakYz9DQEF999RUaNmxYrlyVKlXw+vVr1KpVS8TanTp1QkJCAlJSUtC9e3eNc8rLy4ORkdEX8y/UOOOKFSuwaNEinDhxAlOmTPlPuNmWLVtQvXp1/Pbbbxp77ZemmJgYrF+/HklJSWjatClmzpyJJk2aYMeOHXjw4AHkcjns7e0xduxY7NmzB6GhoVi+fDl8fX1hZ2eHvXv3ltHZrVs3/PTTT3j9+jX69OkDLS0t1KhRA82aNUNQUBBmzJhRZg76+vqiPWiHDh2QkZGB+Ph4fPvttwIPlSQJp0+fxoABA1C9enUUFBSgqKgIMTExyMrKEn6lnp4eUlJSkJmZCQB4/fo1tLW1YWhoiOrVq6NWrVqoVauWsLPU1FR88803+Oqrr4S/nZmZWe4apFAocOLECZiZmWmsjzVr1kT79u0BvLXB3NxcNGjQQMQuarnevXsjKChIyFWpUkXDh8/Ozkb16tUrvXXgu1S9enW4uroKfGHPnj3/KT4sLS3F33//jYyMDGzZsqXS2xD/G+Xl5WH9+vV49uwZatSogalTp8LMzAw+Pj44deoU5HI5OnfujHnz5uHKlSu4fv067ty5g4CAACxYsACrVq0qo9PIyAgbN27UaIupxhlq164tfGc1zpCamiraBAMQeIGjo6MGXhAUFARbW1vExcXBwcGhTNzfo0cPDSyhbt26AksYN26cwFJLSkrQu3dvREZGijF79+6tMU+FQiGwK5J49OgRiouL0adPH4F1q+O3wYMHi7k0bdpU+Dzv6oyJiUFpaSm+/fZbaGlpleGVlJSgRYsW0NLSgqmpqeDJZDKxR33MV6rs9uvvU40aNTBjxgzUr18fy5cvh5eXl8CyP4dkMhnWrVuHmjVrYvny5SIu/tKkVCpx5coVeHt7o7i4GL169cKcOXOQlpaGFStWIDs7G7q6uli0aBHq1q0LT09PPH78GM7OznBxccGTJ08QFRWlobNq1aqYMmUKhgwZovF/ZmYmkpOTRf7t3bhs4MCBGsfq6+ujd+/eePTokcZ1kP6vHXT9+vVF2/BOnTph9erVyMrKwqtXrwQuGxkZCT09PRgaGsLAwABNm/7/DqYqlQrnz5+HpaWlwCqqVKmCgoICVKtWDdnZ2ahTp47wEWQyGXx9fTFgwACcOnUKAATuDLzFkN8fLyoqSuwL7/tDWlpakMvlQueZM2cq6Y6WT1paWmjVqhVWrFiBxYsX48yZM3B1df1PNlZYWIjVq1fDyMgIv//+O6pXr/4/W6uLioqwZ88e3Lp1Czo6OnBxccHQoUNx69YtbN++HXK5HM2bN8eCBQsQHh4OHx8fgZEuXLgQa9asgSRJGjrr1q2LP//8s0wL5Pj4eGhrawvfv127dsjPz0d0dDTatGmjcT0iIiJETtfAwACtWrXCw4cPRe4hOjoasbGxsLCwwJUrV4Qs/68FfUxMTBmeoaEhwsLCUFJSgtLSUhQXF6NevXoi/6v2aQwMDPDdd98hJCQEkiShW7duQkd2djZev36N77//HkqlskzeuE2bNggKCoJKpQLwNmejbjFfq1Yt1KlTBzo6OmjQoIHIbavnUr9+fUiShLt376Jx48ZIS0uDQqFAtWrV0KBBA1SpUuWL2YWOjg66d++ODRs2YO7cuWjYsCFcXFz+U16ipKQEW7duBQCsWrXqf7YWS5KEe/fuYe/evcjJyUGHDh3g5uYGpVKJtWvXIi4uDiqVCjNmzECXLl2wcuVKPHv2DDNmzIC9vT0A4Pbt2xo6tbW14eDgAFtbW2RmZv5rDk6pVCIiIgJff/218Fk7duyI3bt3Iz8/H0D5OThdXV3ROrqoqAja2trIzc0V/tvH8nPNmzcXsVpRURFyc3PRqVMnVKlSBbVq1RLruY6OjtCpjhWLi4tx9epVWFpawtvbW5zHu3uxOg/eokULsZ6/K3fs2LFy5VQqFS5evPhF83PAW+x98uTJqF69OpYvX45du3Zp5JkqSkqlEjt37kRhYSE8PT1F/cmXJDXe8/fffyMtLQ2tWrXC7NmzUbNmTWzZsgVPnz6FQqGAk5MTBg0ahM2bNyMsLAyLFy+Gubk52rdvj5MnT5bRa2FhgcmTJyM+Ph7jx48XebZGjRohMDAQDg4OGsdXrVoVJiYmePXqVZlzNjIy0pjvu7H9uzHSf+Hl5uaiYcOGgqfGyt7nqf3Ud3lqnf/GU8dX6rmodX4patiwIX755ReBqS1cuPA/ra9yuRzbtm2Dnp4eli1bhmrVqv1P1tf4+Hh4enrizZs3aNy4MWbMmIHmzZtj586duHv3LhQKBWxsbDB+/Hjs378fT548gYeHB3x9fTF8+HB4eXmV0dm5c2f8/PPPFc7BlYcJqOP+9/Nl78f95eEF6tohSZJw5swZ9OvXD9WrV0d8fDx0dXWFb/Zunq1169bo0qULcnNzNeaipaWFxo0bo3Hjxjh48KDGHBUKBe7evQtXV1ckJCRAkiTUrFkTDRo0gLa2NkxNTUESCoUCGRkZqFGjhvAzKpt0dHQwdOhQqFQqrF27Fh07dhT48+dQcXExNmzYgNq1a2P58uX/M7tUqVS4desWDhw4gPz8fHTp0gXz5s1DUVERVq1ahaSkJJCEm5sbWrdujVWrViE0NBSTJ0/GyJEjkZWVheDgYA2durq6Iu+vXq+0tLTwzTffQF9fH6GhoQLbBz5cG3nq1CkUFxejdevWoqasoKAAhYWFaNKkCXR0dPDdd99p6Ll16xZGjRoFbW1thISEoHbt2sjOzkZ6errA1apWrYrWrVsLOfXeb2RkBB0dHbRs2VL4BAUFBSgoKEDTpk2ho6OjIadQKHDz5k2MGDECOjo6CA0NRY0aNZCTkyPqFdTjtWjRQkNnXl4ezMzMoKurCz09PZibmwt84X9B+vr6mDlzJmrWrIlly5Zh+/btn2y/n1TQK0kSzp49i2bNmmHEiBH/k2JeSZKwcuVKVKlSBTt37sSePXuwYcMGrF+/Hr169YKLiwuePn0Kd3d3TJw4EW5ubjh79ixmz54tNvP3gYMPkVKpRG5urgiAtLS0UK1aNRQWFkKpVFbK+Tg5OeHGjRtYuHAhJEmCtrY2rK2tyxjJ/fv30bhxYw3wMyUlBfv378eLFy9gb28PY2PjjxpX3bp10aZNGwQEBMDOzg46OjooKSlBTk4O6tSpg7Zt2yIgIACDBg3S4H0p0tLSQq9evWBmZoaTJ0/ijz/++GxdycnJuHDhAtavX48mTZpU4iz/neLj4+Hh4YGff/4ZHTt2xNSpU9G+fXuYmJhg2rRp6Ny5s3C8vby8MH/+fOTk5ODIkSP/msj29/dHlSpVRECip6cHXV1d5Obmahwnk8kEuAS8vbZfffUV8vLyUFJSgvz8fAE8vMtTgxR5eXnw8vLCq1ev0LNnT1haWooCmwcPHsDFxQX6+vooKirSkFNTUFAQatasKUDcgQMH4sKFC3B3d0fNmjXx5s0bzJs3T5zHp5AaJO/fvz8UCgXy8/OF/avPQZ2M+BDJ5XJkZmYiLi4Oe/bsQUlJCaKjozFixAi4uLhUaD6fQzo6OrC1tUVYWBi8vLywYcOG/5R8u3r1KurVqwdHR8f/WTEvALx48QJr167FX3/9ha+//hqTJk1C586d0bp1a8ybNw8dOnTA/PnzceTIEaxZswYzZ87Ejh07cPLkSVSvXh1jxoz55LGys7MBQATFVapUgb6+PrKysio057p16yI/Px/79u2DTCZDXFwcJk2aBCsrK+Tk5IgkntqWiouLoVAoPqpTkiT4+vqidevWaNOmjbiXenp66Ny5M06dOoWUlBTUr19fODIKhQImJibo3bs3FixYgCZNmuD+/ftYtWoVateujc6dO8PHxwcpKSlo0KCBkJPL5Rpjh4WFobS0FJ06darQdagoaWtro2/fvrCzsxP76+cQSezduxd9+vTBwIED/2fFvCTFWrZ9+3bcuXMHK1euxO7du9GuXTv07dsXhYWFmDBhAhwcHDBhwgRcvXoVpqamcHNzAwD07dv3k8fKysqCgYGB8H8MDAwgl8tRUlKicWx+fj4UCoUIuHR1dfHVV1+J5O+UKVMwf/58/PrrrwLk6N69OzIyMsqVy8rKEoHUnTt30KVLF8hkMshkMvEMAW+f3VOnTiEsLAyTJk3C119/jZSUlDI6q1WrhtTU1DLn9+DBA/Tv318DNHr16hVOnDiB58+f4/vvv9fYcyMiInDixAmEhYXB1dVVIzHyJahKlSoYPnw47t69i1OnTmHevHkieVNRCgwMRExMjAjQ/hdUXFyM3377DSNHjsSoUaOwcOFCeHt7Y8KECRg+fDi6du2Kw4cPY/Pmzbh69Sp++eUXBAYGYuvWrejSpQsAwN3d/ZPGKioqQmlpqbjvOjo6IiFF8pP3JiMjIzg6OmLdunXo1KkTAgICMGPGDBgaGiIvLw9Vq1bFyZMnoVQqERsbi/79+2P69OmoWrXqB3kGBgbA/+PtzMOqKrc//jkDh3lGQARFEEVRBhVREUnLOSstTRs0LecGS0vrestsut0sh0oT01JMHFJRUZwnFBBBcB5QBJlBZeYwnv37g2e/Pw6gKV74Ps998u7Fu/c+e797vetdw3cB27ZtIzo6mrS0NJYsWYJarRaJ4/J7ldeGkpIScU/bt28nOjqa1NRUFi9ejIGBARqNBiMjI3bu3ElNTQ2pqakEBgYye/Zscb3/NTQaDa+//jrHjh3j1KlTvPzyy81e86OiokhJSWHjxo1iH9IakCSJn376ifz8fNasWcPu3bv5/vvvWbVqFb6+vowaNYqMjAymTZvGG2+8wYwZM4iIiGDMmDFMnToVgMGDBz/WtXQ6HQ8ePGi0Hmu1WiorK/X+trCwEJ1OJxySBgYGGBsbC9vAycmJkydPEhUVRU5ODkZGRnzzzTdinPzO5XH37t2jsLCQ2tpaPZmsl5saJ8tkO1iW1dfnRUVFeud8EllNTU0jWUPbp6amhpiYGHr06NGiwQMZCoUCT09PPv74Yz7//HMGDx78VEGECxcuEBUVxdq1a5/KqfakkCSJP//8k7i4OH777TcSExP5+uuvWb9+Pe7u7vzwww8ATJw4keeff54JEyZw/PhxXF1d+eyzzwDYv3//Y1/r3r17GBsbC9vH2NhYFDrWR0lJCZWVlXp62cTEhIyMDADeeust5syZw6effiocbv369aO0tJSCggLi4+PFfj0zM5MFCxbg4+ODq6srp06dok+fPtTU1FBRUUFZWRkA7dq1Y+/evZw/f54HDx6g1Wr54osvaNOmDQUFBSQkJFBVVUVhYSEZGRl8/PHHBAYG0q5dO/bs2UNiYiIFBQWUl5fz+eef07lzZz09JycJyUk4UJdAt2XLFi5dusS4cePw8PBAoVCg1Wo5dOgQI0aMIDc3t7mv94khByvnzZvHe++9x8svv6xXRPckkCSJGzduEBsby6pVq/QSsloamZmZLFmyhPnz5+Pn58f06dPx9PSkf//+vP322/j4+PDdd9+xZs0a1q9fz7x588jLyyM0NPSJv+OH6a8n2Z9JkkRubi55eXls3LhRJGb5+/szZ84cUSwfEhLCxYsXqays5J133kGhUDyWvb127VouXLiAVqtl2rRpKJVKcnNzyc/PJzQ0FIA7d+7g5+fHe++9h7m5OQC///47SUlJlJWVMX36dJRKZZPXq66ubmTfp6amcufOHZYsWdKiex2FQoGLiwtz5sxh8eLFvPzyy822DZKTkzl79iwhISGtmsyr0+n48ssvcXBwICQkhJUrV7Jy5Uq+/fZbBgwYwNtvv010dDT/+te/mDRpEvPmzWP37t0sXLiQ0aNHAzQKzsrIyMigoqJC2O+yjSvvs+pDduLL78vIyAidTkdpaane36WmppKamsqkSZOAujlgYGDAtm3bqKmpISUlhSFDhjB16lTy8vK4d+8e27Ztw9DQkLS0NFxdXUWSG0BYWBixsbGkp6fz9ddf/+N+RZIkoqOjkSSJvn37PtSezM7OJikpiVmzZmFgYCD2bzqdjn79+rFy5Urxtw4ODrz66qssW7aMI0eOEBUVxfTp01t8PdZoNIwfP57Y2Fh27tzJjBkzmn2u5ORkzpw5w88//9zqybySJLF27VquXLnCqlWriI6OFn6GLl268OOPP1JRUcEbb7zBmDFjePPNNzl8+DB+fn589NFHwJPZErIekn/jw/RQSUnJQ/0MTclMTU3Jzc3FyckJZ2dnTp06ha+vL1VVVXq+hJKSEk6ePMnYsWO5cOFCk/cpJxl5enqK76+0tJQTJ04wZswYvaKRkpISqqqqGtk8d+7cafTbz5w5Q5cuXfRIVGRZdHQ0nTt3blIWGxtL//79ad++/SNtJTlBuKWgUCjQaDRMnDiRGzdusHbtWr744otm+Z/lZJjExERCQkL0CsxbGqmpqXzzzTcsWrQIT09P3nnnHby8vOjZsyczZszA29ubxYsX8/vvv7N69Wo+/PBDiouL2bx5M3Z2dkyePPmxr/WoPdvjQqfTcf/+/UZ7Szm5MC8vj9zcXDZs2IBOp+P27dv079+fmTNn6vl/rl69SklJCb6+vkAd6cLgwYNZuHAhrq6unD59miVLlmBhYYFOp2P//v20a9eO7t27i+9Vp9ORm5tLbm6uns3Tp08fZs6c+VDZ7NmzMTExITIyEkdHR3r06NEqek6hUNCxY0dmz57Nt99+y4svvthsm1YuBrh16xbr1q0T9lZrQJIkdu/eza5du1i/fj3Z2dl89NFHdO7cGUdHR7766ivs7Ox49dVXiY6OZsKECcTGxlJUVMSKFSuAx/cHQ51NIcfp4P99VXKCo4zy8nLKy8vFPJPJbmR9W1NTQ0REBAMHDmxkT9bU1LBv3z6CgoIaycaNG8fhw4f5+OOPUSgU6HQ6hg0bhp2d3WPHeKOjo3F0dMTR0ZHKykoxTiblKC8vF+OcnJyIiori5s2blJSUcO/ePebPn4+/vz9jx47lwIEDzJ8/H7VaTUVFBSNGjKCyspL79++Tm5vLunXrKC0t5c6dO7z11lu8+OKLLTq/FQoFHTp04P3332fp0qW88MILzS6UlySJ1NRUzp49y8qVK1stmRfq1s9FixYJX8WHH37I9u3bGT9+PK+88gp+fn6sW7eOlStXsnfvXj799FOSkpJYvXq1KABbsGBBk+e+fPky8M8xuJqaGgoKChrFncvKyqiurn5oDG7UqFH069cPf39/PvroI5ycnIiNjeW7775Do9E0ec768bmamhp+/fVXrl27hrW1NRMmTBAJYn379mXevHk4OzsTExPDt99+i6mpqYjdderUSS+xviFu3rxJcXGxyGnR6XRERETg5ub2yHFyEn1Lx+fq2xJnz54lLCyMuXPnNjv/5s6dOxw4cIAff/yxRclX6qOmpoZFixbh7+/PkiVLWLx4MWvXrmX+/PkMGTKEjz76iH379rFs2TImTJjAwoULOXjwIP/9739FQrnsZ26IlJSUJn2oT2I3NERqaqrI82iob+V9/1dfffVQWVM+gbS0NFJSUvjyyy8fKWu4N0xLS+P27dt88cUXTcpu3brVpOzu3bskJyfz+eefNzs+9riws7Nj1qxZzJ07l8mTJzfbVyxJEnfu3CEmJobly5e3WtKkTqfjq6++wsLCgpCQEFavXs3y5cv573//S79+/Zg0aRLx8fF8/PHHTJ48mQ8//JDw8HDmzZsnCuAbFrfLyMzMbNI/8aQxOBlbtmwhNjaWtLQ0vvrqK9RqtdgX6XS6R/oL0tPTSU5OFvkZTcXZ5ITG5qCoqIiCggKioqLIyMggPz+f+/fvC7IwgMTERHbv3s3ly5eZPXt2iyX0Qp0ukGPFmzdvfuy4aUNIksS1a9e4fPkyq1evbrV5CXD//n0+//xzZsyYQXBwMHPmzGHPnj0MHz6c119/HT8/P1auXMmvv/7Ktm3bWLBgAbdv32b9+vX/SHaVkJCAUqkU675Go0Gj0ejlE0BdYmxRUZEgMJFzI0tKSkRupFar5ddff+XGjRt4eHg0SfiakJCAWq2mc+fOIqn77t27rFu3jsrKSm7dusWoUaOYPHmyXr7T1atXkSSJ4cOHi3NWVlbyyy+/cOPGDVxdXZvMSU1MTEShUNClSxdxvYyMDNavX09VVRW3bt1i2LBhTJkyBUNDQ6qqqoSd4ezszMsvv9wqea5NQaFQYGhoyOTJk4mJiRG+s8e5n8fS9lqtlosXL4oK69ZAQUEBFy5cYObMmRgYGODl5UV4eDi1tbX4+vqKoJharaa8vFxPOcisMXJAqz5kx1ZZWZmYkLW1tahUKiRJEuPlysn/xe+VJImkpCQMDQ0ZOHAgWq2WnTt3cvPmTT2G2cLCQg4fPsw333yjd11TU1P69OmDmZkZZ86c4eLFi4KVoikYGxvz0Ucf8d133/H2229jaWlJeno6xsbGGBkZMXfuXP7zn/80krUk5Ez3X3/99anOc+7cOTp06KDHGttauH37NjqdDjc3Nz2WgdGjR2Nubk5lZSWOjo6kpqY2SgSXF8uGx+WK3frzr/6Yhh+xQqEQmw/5b+S/k/9Xfx43NBwMDQ3p3bs31tbWHDt2jJiYGEaOHMm0adP44YcfmDZtGmZmZoLlrv7YkpISwsPDWbhwIQqFQix2Wq2WUaNGodFouHPnDpcvX8bT0/Mfg13yJnnTpk0sWrSIDh06iCrOhr/vcb9DLy8vPv30UwwMDNi8eTNr1qxh9OjRrRLEMjAw4IUXXuC9994TbK3NQVVVFUlJSTz33HOtmswrSRLXr1/HyMgIFxcXrK2tsbe3Jz4+nuDgYKysrMQcz8nJaZRgLUlSk4nX8kZdoVCIAFrDeSr/V5KkJw6SdujQgY8//hhDQ0MqKytF4NDPz+8fv4eHPYcLFy6Qk5PDzJkz9b5ZlUrF2LFjyczMZO7cuSJIaGhoiFKpJC0tjezsbIYOHYqDgwNpaWkkJibSq1cvXnrpJTIyMvjwww/1xtX/vRUVFezevZsxY8a0ylqrVqsZMmQI8+fPp6KiolkVnRUVFZw/f77ZgYvmorS0lHPnztGzZ0+MjIzo2rWrYE3q3r07lZWVaLVazMzMGgVuZXbZpjYwKpUKMzMztFqtSLaWdatOp2s0bxu+J5kFpql5LTu8HRwcGDBgAOnp6Rw9epT09HTxjdTXfXLxj5mZGYsWLWL58uW89dZb2Nracv36db0qejs7O/r06YNKpeL06dMMHTpUvM+mzimjtraW8+fPc+3aNebNm6fHVmtjY0NAQABqtZro6GiGDRsmnF02Njb06dMHtVpNTEwMQ4cO1WNebwkolUpGjhzJpk2bKCsra1bgQV63vL29WzUZJysri7y8PLy8vDA2NsbDw4PY2Fg++OAD/Pz8qKqqws7OTgRYG95zeXl5o+NQl5yg0WgoLS0VdqvMmtjQpn2STYqsz69du0bv3r3x8/OjuLiYc+fOMXLkSMzNzZk+fbpIKDhz5gwffPCBcODWl0VHR/P+++/Tr18/wawkz6Oamhp27NiBu7v7Q+2g+t+YPK66upodO3bQqVMnTE1NmTZtmrhebGwsc+bMoV+/foLttCVgZGTEwIEDuXDhAi+++GKzA7fnzp0jMDCwRZ0cTaGoqIjz588L+83Ly4vffvuN0tJSvL29qaqqQqPRYGxs3Gg/JVdcN9St8P86tL5zXqFQoFKpGtl2sqw+5HnaUIfKx0eOHMmIESMEs+K0adPYvXu3SC5uSt81pZfryxpeT+5Y8r+WaTSah95LQwdsVlYWd+7cYfLkya2axNK7d2+srKy4fPnyUzlpr127RufOnZ8qKbg50Gq1xMfH06NHD0xMTOjSpYtgAuvduzcVFRXcu3cPCwuLJm2D2traRoFZqJuX5ubmVFRUCF0sv+v68/lJbQN5rsTHx2NjY8OAAQPIz89n//79IlFMqVTy7LPPMm3aNGpqali4cCFr165l/fr1fPbZZ/zwww9MmTIFGxsbLl26JPbI/fv3JyAgQLBKfvDBB2zcuJF58+ahVCoZPHgwM2fOpLa2ln/961+EhIQQGBhIv3796NOnjxj34YcfsmHDBsFcrNPpuHTpErGxsXzyySd6a6mVlRX+/v4YGhpy7tw5bt68ibe3N/v376dDhw54enq2akKvjG7duuHu7k5cXFyzE3qhLpjk6uraqknqUOeDqKmpwd3dXbA7x8bGMmbMGOGDsLe359q1a42KFh/HB1FaWirmo7yPa6ijnnSNk5k9PvzwQ+zs7IiPj+edd95h+PDholDJ29sbc3Nzjhw5QkREBFOmTBG2wKO+KW9vb8zMzMQ4mcXWycmJDz74AAcHBxITE3nrrbcYNmyYYNr19vbG1NSUo0ePsnfvXt555x29vWJT15MkiYKCAjZu3Mgbb7yhx3TWkvD398fExIQrV64wYMCAZp0jJiaG7t27P1VXi+bg/v37gojAwMCAbt26sWrVKpRKpUgmlFlitFqt3t5DkuqYNxsWRQCC3a2p/VJT/oP6dkf989e3h2tqajh+/DgBAQFijltYWAgftE6n49SpU8yfP1/YsG3atGBTbzkAACAASURBVGHGjBl06tSJu3fv8sILLzB48GCGDh0K1HWiUiqVnDx5kh07duDq6vrQAkI5+T0uLk6w+jSFsrIytmzZwuDBgwkODkaSJPLy8kQHmIYM2cXFxVy9epVevXrRs2dPSkpKSEhIEH7LloSpqSnDhw/n77//Zvr06c22YeLi4vDy8tIrGmktlJWVER8fj4+PD8bGxnTt2pWcnBzy8vKEnyEnJwdzc/On9jPItkT9ufowW6J+AqH8d/9kz8q+hH/9618sW7ZMz5fQv39/kQzTtWtXOnbs+NCE3nv37nHx4kUx3+Rxnp6euLm56SX0/pPNU/+ciYmJjeIfsuz8+fONZLW1tVy4cIHz588zf/58zMzMBLNUU7ZSSyf0ylAqlUyYMIFPP/2Ue/fuNdv+TU5OxsPDo1FHiJZGcnKySPS0trbG2dmZs2fPMnLkSCwsLKisrMTBwYGMjIxmxTrk76Ghr1/+75P6KoBGvgPZbyDPFxcXF+bNm4e1tTXR0dG8++67DB8+XHQmk9l2ZSIgSZLIzMzk7t27BAcH4+zsTEZGBvHx8QQEBHDnzh1SUlIadUeSf6uzszMfffQRtra2xMXFMWPGDIYOHSpksj107tw5pk+fLhgf5f1sa6Nv376o1WquXbsmOnc9KXQ6HYmJiQQEBLS6L6O6uprExETc3d2xtLTExMREBO9HjBiBVqulrKwMW1tbYec2vPeioqJGx2WdWVVVRUVFBVDnN5d1WsM511TM7mF+XZ1Ox+HDh7Gzs8PHx0ckWMr3c/jwYWxtbRvJ5BiFgYEBAwcOpKqqir///psbN27Qvn37x4rxFhUVceDAAb766isUCgVGRkZ88MEHeuMyMzPFuB49euDp6YmhoSGFhYX861//4rfffsPX15eLFy+iVCoZOHAgtbW13L17l+vXr9OmTRsUCgX+/v589tlnKJVKVqxYwerVqxk5cmSLFynL15b9RPW74T4pLl26hLu7u+i41FrIyMjgwYMHdOvWDRMTE8HuPHPmTGFD29nZUVFR0YgcRpIk0emnPuSkEdlW/qcYnOy7k/eUDWNpTcXgfv75Z/r27UtOTg65ubmMHDkSW1tbERPz8vL6x1iv3DXKxsaGQ4cOcfjwYSZOnCg6FgwbNow2bdqIc/bs2ZNr166RlZUlfBoNIUkSOTk5/PHHH8ydO1ewX166dInMzExmzJjRaK8go7Xjc1D3DMaOHSsS4psbV75z5w5t2rR5qo4BT4q8vDxSUlJ455130Gg0dO3alf3792NqakrPnj2pqqoS3aLkDpEyJEkSjN8N8TAfanPix/LYgoICNmzYwOTJk/Hz82sk27hxI5MmTdLb9z/KJyBJdSy6Gzdu5PXXX2/U5eefZKGhoUycOFFPZ0lSHftuaGgoEyZMeKjs1Vdfxd/f/4mfQ3Pg5eVF27ZtRRyhuUhLS6Nt27a0bdu21b6tBw8ecPnyZd5//32RZyaz4Mu61dTUVBTFNOza+ij/xKPiDc2Bp6cnSqVSxL3c3NwoLS39R39BbW0tUVFR+Pj4iHhwQ1+XfH9Pk8So0Wh4/vnneeWVV9BqtUyfPp3Q0FDRncbBwYGAgAAUCgVHjx5lyJAhLUoCZWBgwIgRI/jzzz9FHKs5uHDhAl5eXoLNtrWQmppKWVkZXbp0wdzcHDc3N2JiYnjjjTcwNTUVvt76/gMZkiQJkrn6kO28pnyrD1v3G67RDTtaGxgY0Lt3b2xtbTly5IgoBpZjWWVlZezatYtZs2Y1iuMuXLhQEDEtXbqU0aNH4+joiCRJZGRk8Oeff7JgwQI6deokxqlUKnr37o2dnR2HDh3i+PHjjBs3TlyvvLycnTt3CmIIGR4eHixYsABjY2P27t3Lt99+y+jRo2nXrh0qlUrYGYcPH+bYsWOMHz++VfNZGkKlUvHCCy8QERGBVqt9LOKxx0rora2tbaTMWhoyE0doaChHjx5FkiT69+9PTk4On376KRUVFZSWljZimpNx5swZ/vzzz0bHO3fuzMyZM1m9erVoCRQcHEybNm30zlVQUICtre3/5IWWlJQQEhLCyJEjGTduHDqdjry8PFavXs3AgQNRq9XU1tayY8cOBgwY0KiK0MLCgmeffZbg4GAKCgpYtmyZ2Hw/DO7u7oSEhIig+5dffikMJnd3d9asWaMn02q1LZ6RLldMPw1kdtqWrjxqClqtlrt377JkyRKMjY2RJAl3d3d2797N5s2bMTU15ebNm3otVmXU1taybNkybt++rXfcwMCACRMm4Orqqsc+I7dibxgwNDY2xsbGRjD3ygalg4MDpqam2Nraiora+rL6zCSDBw/mmWeeQZLq2NmCg4NxcXFh+fLlQmH//PPPJCUliees0+k4cuQInTt3FmzDFRUV/PXXX/To0YPXXntN/M7ffvuNESNG/KO+uH79On///TdTpkyhZ8+eYpNpa2urx0xcUFCAvb39I9+5RqOhTZs25ObmiqBQx44defDgwT+ysf4vYW5uLhiymqsvZUOxNdrAN4RWqyUlJYVFixah0WiwsLCgffv2bNmyhV27dmFmZsbly5dFW936qKmp4Ztvvmmkk42MjJg0aRJqtZpVq1YBCPZhhUIhEoW0Wi3l5eV6bQUfBzLjB9R9H3379mXVqlXC6XzhwgVxrwUFBVhZWT0ycbW8vJzQ0FAsLS3ZtWuXqG4/duwYnTp1on379nz55ZfCyNmzZw95eXkYGhoSFhaGubk5kyZNQqPR4OjoyOzZsxk5ciSurq4sXrxYjIuIiCAnJ0cs1LKTTtbRrQUzMzPRpqs5Cb1VVVVUVVW1KhsDIFqE7du3jxs3bgCIgPfHH39MXl4ekiQ1av0n4/bt2022wrS3txdtbuUWJj169MDe3p6SkhLx/goLCzEzM2vEGGNtbY2hoSFFRUVA3fMpLi7G1dWVBw8esG7dOj777DNGjhxJbW0tV69eZf369Xz++ecYGRmJRCJ5nMyK6+/vT2hoqDDWZ86cqWfo2tvbM2zYMIKDgwVz9pdffomxsXGje5HPKQexY2JiWLx4caM2TPb29gwdOpTg4GDeffddUcEKdcFsWfbee++xevVqPWaoloKpqSnV1dUPdbo9Duqz17YWtFot+fn5LF++XDixfHx8OH36NL/99hsGBgZkZWU1aSPpdDo2b95MVFSU3nGFQsHQoUMJCgriP//5D6WlpWg0GsaOHSuCm1D3nouKivQKyB4HCQkJohLcycmJwMBAgoKCGD58OM8995zeMwwICBA2uVKpbFKWnZ0tjvn4+ODj40NwcDDPPPMMAwYMwMnJSW+DWlRUhEql0gsOeXt74+3trTdu2LBhja6n1WrJysp67N/aHCgUCpG42nA9fBKUl5f/YxeHloBsq+zYsYP4+HgkSSIwMJCysjI++OADwSiampra5O+7ePFik9+8HMzcsGGDSArw9/fH3t6eW7du6a3HlpaWjYJNdnZ2eoFfeb/Xq1cvYSfK8PDwwNHRkevXrzN+/HjUanWjcT4+PqIFYENZjx49GskqKyspLS2lW7du2NraolarhV6WZZ6enmKPWF9WUlJC586dsbOzQ6PRNJJ16tTpoePkBDf53fz555+88MILrcYiLkOlUmFsbNyIFe5JITsiWjsJp6amhsrKSo4cOUJmZiYAgYGBaDQaPvvsM9LT01EqlVy/fr3JeZ2RkcHnn3/e6LitrS2ffPIJERERQhfLSSzyng3q9JaxsXGjghErKytMTEyEXpYr4J2dnSksLCQkJIQ5c+YwduxYamtruX37tgiOWVpaUl5ejpGREZIk4ebmxt69e4E6nbhhwwZR+DF37lxhG9R3ZLZr1w4PDw+uXbuGubl5o3N27NiRxMTER46DuvUoKiqKEydOsGjRIpycnPTesY2NDUOGDCE4OJiFCxeycuVKPvnkEzZv3szo0aPZunUrV65cIS8vj8jISMaPH9/IjmoJyO1Amyr2fhJotVqMjIxavYq/oqJCsH2amJig0+nw8PBg7969bNq0CVNTU27dutVkonFtbS0rV67Ua6EOdT6I8ePH4+zszA8//IBOp8Pc3Jzx48c3qb/kNn6PA4WiroW2/LzUajXt27cX9oiMfv360a9fP7p168Ybb7xBUFAQjo6O/2hv9+3bl759+9K9e3cmTpxIUFCQuJ6xsbG4npysISMgIICAgAB69OjBhAkTCAoKom3btpSUlIhvuLCwEBMTE7GvycvLY/Pmzfj5+TFixIhWe/cya9bTzNnS0lLMzMxafb7Ka+Uff/zB/v37kaQ65tk7d+6wYsUK0R3tYaxKx44d02t9K6N79+7Mnj0bU1PTJm3chnByctIrLpK7S9T3tebl5XH9+nVGjBghdFlDO1ZuVZibm4uDgwM1NTVoNBoMDAxo164dhoaG5Ofni7/39fXF19eXAQMG8NxzzxEUFMSgQYMe+rzCw8O5desWUVFR1NTUkJGRQVxcHP7+/nh7e1NYWMj27dtxdHTk5ZdfFv7p8PBwbt68yenTp8W4c+fOERAQINpkL1q0CGdnZ4KCgggMDGTYsGEi8bglYWFh0WTQ80kgz9/W6v5TH7ItceDAAeG/HTBgAEqlkk8++YTc3FwkSWqkV2XcuXOHr7/+utFxe3t7Pv74Y3bu3ElMTAxQFxx3cHDQsyUKCwsxNTVt5F+xsbHByMioyb29tbX1I/f9vXv31vMlzJo1Cw8PD65cucL27dt5+eWX2bp1K3FxcWRnZ3PgwAFefPFFTExMqKmpYcOGDTz//PPinq5evcr27dsZO3YsW7duJT4+nuzsbCIjIxkyZIjevdS3eeo/440bNzJq1KhGv7O2tpaNGzeKItL6x+UuHV988QUODg4oFIom7Zr6tlJrQV6fm+t/lhNa6rPGtxa0Wi1paWksXrxYsEW7ubmxa9cutmzZgqmpKTdu3GiyQKS2tpYff/yxEQOzzDZoZ2fHTz/9hCRJWFpa8uqrrzbal5WVlekl1fwTVCoVjo6OXLx4URTdFxQUYG5ujpmZGQ4ODpSXlwuboEOHDlRVVYkEfEmSuHr1KlVVVaIDRW1trUjumDx5MsbGxri5ufH666/z3HPPsX37dmpra4mIiBBMpCdPnhQxkoY2j1z82pR9Ul1dzf379zlx4gSVlZXs27ePyspK7t27x8mTJ/H09KRTp04tuo+Suxw9rW1cVlaGhYVFq89ZnU5HZWUlcXFxzJ07F4VCQa9evbCysuK7777j0qVLGBkZcf78+SbXvcLCQj766KNGfkUrKyvmzp1LXFycYFp3dXUlMDBQz1dVXFyMSqVqRB4j6yPZTqmtraWwsBAnJyfu3r3Lpk2bGDx4MNu2bSMtLY0HDx4QGRnJwIEDCQ0N1ZPdv3+fyMhIxowZw++//87gwYMZP348klTXJWb16tUMGjSoUYx3yZIllJWV6RWBhIeH069fPz3fmpubG7/99psY9/XXX1NUVIRSqUStVgt7w8bGBm9vb/766y9KSkpYt24dAwcO5NVXXxUJafK9yAnUJiYmQhdv2rTpqfy3T4L6hAdPg9LSUvHNtiYqKirIzc3lxx9/xNLSEp1Oh7e3NydOnCAkJARDQ0MyMjKoqqpqMkl948aNxMbG6h2XiTGeffbZx4rBqdVq7O3tBWMeIDr+yglCTcXgioqKCA8Px9ramjfffBO1Wo2dnR0ffvghw4cPFwWXD4vPyV0k5f3ZggULGDBgALt37xZxNgMDAxwcHHjvvfd45plnCA0NxdzcnPDwcCoqKkTszsPDg/bt25Oens7mzZsZOnQozzzzDEqlEq1Wy6ZNmzAxMWH37t1i3PHjx/Hw8BBJsHLiemvG5wAsLS2prKx8qo7RclJba+rlyspKoQu2b9+OTqejd+/eJCUl8fPPP6NQKMjPz6e4uLjJBMM9e/Y02d2if//+vPbaa3r+CdnGbc67yc3NZfPmzfTq1UuPDVKWhYWFNbnvf5RPQJb5+PgwcuTIRrKwsLBHynr06MGoUaP0ZPn5+f8o8/Ly4vnnn2+19yx/+/8Ln1pDgquWhkz8uGHDBg4ePIgkSfTr14/09HRWrFgh5lReXl6T40+dOsWmTZsaHe/atSvvv/8+ZmZmIh+nuTE4GbIvISgoiMGDBxMUFERycjLJycnCX5CZmannL1CpVDx48IDExEQ++OADcV3ZH1LfdlGr1c0uwpL92lVVVRgaGqLRaOjQoYPeHsDJyQknJyeCg4OZNGkSf/zxR5M+9v8lZPIN2U/THJSVlWFiYtLqvoeKigqysrL4/vvvMTMzQ6fT4e/vz6FDh/jjjz8wNjYmNTW1yd+l0+kICQlpVJCrUql46aWX6NOnDzqdTvhlZLKohoWncl5VfZ9WQUEBdnZ2whZUq9U888wzBAcHY2ZmxrJlyxg0aBBt2rRBkuqInuzt7YVfTrYlrl+/jomJCUqlko4dO1JUVCRIUuQOf6+88gr9+vXT02VqtZrg4GAGDhyIpaUl//nPfxg0aJBIBI6NjcXGxkYki8vXS0pKEu/R1dWVkpISEWtXqVTinLa2tixZsoRBgwY9cS7S/xqWlpZotdpHdqevj8eyTE1MTOjYsSPnzp0jODj4qW7wcWFlZYW1tTVTpkwRyYJQ16Y3Ly+PVatWUVBQ0CQdv0KhYPDgwY9sBfvvf/9b/FuSJDZv3kxcXBy1tbUolUoSExPx8fHBzMxMMPaoVKpmKWKdTqf3QuRzyMpUZli4cuWKaAUOdY6vw4cPM2jQIGHgSpLUKBv/YdeUP4KCggIuXrwoWhLWlxUWFnLx4kXBUNJSkNmanoYVB+oCl2FhYeTk5LR6xYSjoyMdOnTg+++/F46soqIipk+fzuDBg5k6dSobNmzg+PHjjcaq1Wq++OKLh567sLAQKysr4Ry+du0aKpWK7t27iyRbQLCoHTt2TMyFS5cu0bt3b8zMzPDy8uLIkSNiQ37x4kV69+6NSqXi+PHj+Pj4iLaN9edS/eqcyspKYmNjGTJkiFgsZDbM+lTkMvtEQ1RXVz8yuUVOXJRbN3fu3JmamhqUSqVgcdm9ezc6nQ6dTseFCxcEC+fDoFQq8fb2JjIykqKiIiwtLSktLcXS0rLVNuCSJHH27FkcHR2fqjrdwMAAV1dXLl68yPDhw1vt/hUKBY6Ojri7u7NixQqRYHTv3j0mT57M66+/zssvv8yKFStISUlp8r7/+9//PvIa9Sv/a2pqcHFxIS0tDUmqY2suLi7G399fb87LlW4PQ0JCAlZWVri5uQF1rS7atGmDqakpnTt35sCBA1RXV6NSqUhISMDLy+uRzJxyZZccZJSvLVfay3NbZv05fvw4ffr0wcrKqtHcVygUIvmw/jhJkjh+/Dj+/v5irsgBCl9f31ZLNpSkOvZ4JyenZidUmJmZ0b59e86dO4enp2er6WRTU1Osra3p378/CxcuFMfPnTtHfHw8ISEhWFlZNdn+T6Goay2+cePGh55/zpw5zJkzB6h7TqdPn6a4uJiKigrMzc2Jj4/Hzc1NGJKy7WBubk6XLl1ITk4W7fcyMjKYOHEitbW1TRpnMlNVly5duHnzpij6ycjIEG1S6q/bGRkZZGZmCnaG/fv388ILL+ixicnn7Nq1qzjnvXv3uHv3Li+99BKSJHHgwAGSk5OZMmUKVlZW1NTUoFKpqKmpITIyktGjR+uds7KykqqqKiIjIxs5DR7HLnlaSJJEYmIi7dq1a/Y3olDUtTLeuXPnQxm9WgIODg44OjqycOFCwRRUWVkpEqIWL15MVFQU3333XaOxKpWKadOmPZK5RS6WgLrndOrUKa5fv45Op6O4uJhbt26JNsby2vpPNm1NTU0jfVZbW0tNTQ15eXlcvXpV7Amys7NFwVF+fj6XL1/mmWeeaSTLzMwkNTVVMOfKur6mpkZUSxYUFODq6sqFCxewsbHBw8ODrKwsUlJSCAwMFOPke7l//z5JSUnC5s/OzsbQ0LDFmY2qq6tJSkrCw8Oj2eu0QqGgc+fOHDt2rFXnI9Q5PKysrBg6dCizZ88Wx48ePUpycjJr1qwBeKgO7d279yN16Lx588S/JUli//79hIeHC+dyQkICXbt2xcbGRm+fZWFhgZubGykpKaJa9969ewQEBCBJEtu3b2fcuHFAnTOqtLQUFxcXLCwscHd3F+MyMzPJz8+nb9++Qnb79m0hy8vLE7JOnTqJLhyyrF+/fk3KcnNzhczDw0PIsrKyyM3NpW/fvpibmzeS5eTk6Mlu3bqFTqcjOztbdASQn9XVq1e5f/8+/v7+rbrPkaQ6psDMzMynClwoFArat2/PgQMHqKysbNVAmKxrOnXqJBiIoI5lJyoqit9++w0nJyemTJnS5H27uro+cl7X18XymiQnItja2pKQkICLiwvOzs56toGpqSndunXjxo0bok1wamoqU6dObWQbyLZmVVUVKpWKgIAALl++THl5uWBJkh1w9W2D/Px87ty5I+5vx44dvPjii4Jl4sGDB7Rv3/4fz7ljxw5eeOEF1Go1Wq2W+/fvi2LVo0ePkpSUxOTJk7G3txf7NzkJYsSIEXrvW2ZimTRpknAiNrSrWxqSJPHgwQNu3Lih51NqDmT7oaysrFlFcM2Fo6Mj7du357vvvhMJ28XFxcyaNYuBAwcybdo0Nm/eTGRkZKOxarWaRYsWPfL89YvgJUlqUkfNmDEDQMzVR+3P5G+purqavLw84aCUO2XJTI5ya1jZpyAXSxcVFenZ2+7u7jg4OHD16lV0Op1g15PH6XQ6kcCbk5ODtbU1Wq1WtDu8du0aNTU1eh2e5OvJSflarRZLS0sSEhJwc3Ojbdu2ZGRksGnTJvz9/UXR4NP4BB8XkiSRlpZGfn4+np6ezT6P7DMqLi5u1XbBNjY22NjYMH36dMaOHQvU/ab169dTWlrKzz//TEZGhphT9aFQKBg5ciQjR45s8tySJNG9e3ehSwsLC0lJSRF2QX0b18XFhdraWkpKSoS+dnR0FP5ISZI4duyY2M/Jzyc7O5tbt26Jd56dnS32nfb29piZmZGeno6bm5sIuFtbW3P37l2ysrIEky8gbNVHwc/PT/gmGupHmUGqU6dODBs2TOhblUqFr6+vKCBv+G7l76I+ZHu7paHT6YiLi6Nbt25PNee8vb1ZtWoVDx48wNbWtlXtIfl99+rVS09/JiQkEBcXx5o1a7C1teWtt95qNFa27R9lS8yaNYtZs2YBdfMwJiaGkpISPT3UsWNH2rZtq2dLmJmZ4enpKfwMeXl5pKen88orrwiZvO/Pz88nPT2dMWPGAPr2QlZWFhkZGQwcOBAbGxsmTZokAmv156B8f7dv3yYjI4OZM2eK4/I4OUAmz1mFQtGkzZOWliaYTSVJIiUlhbt37zZi1XmYTJIkDh06xNWrV5kyZQq2trbCd6FWqx9p17QGZF+wvb19s7vDyfbzwYMH0Wq1rdqtTdaNP/zwg0hmKiwsZNq0aQwZMoTJkyezfv16Tp8+3WisWq3myy+/fOT5N2zYIP4tr/X192zyvgwe387o1KkTYWFhVFVVYWxsTEJCAl26dKFNmza4ubmJgmpTU1PKy8vRaDTChyT7Y3v06KGXNN5UMrZ8bPDgwaLLRP37kpmNKysrycvLw8LCAq1Wi4GBAaampoK8paHM3NycQYMGCUKM+t9QS0OS6lpeP3jw4JHt5v8JSqWSrl27cuDAAcrLy1ulSE+GgYEBdnZ2BAQEsGbNGqHf7ty5Q0REBMuWLaNHjx5C1zaEjY1NkyRQMtzc3JgwYYL4/3fv3sXAwICCggIR07KyssLDw0OPyczIyIgePXoI/VdWVsaNGzfo27cvlpaWvPbaayLZtL6+NTc3b1IGD1+/ZR9swxjvhQsXePvtt0XsIT8/n0uXLjV6FvXHFRUVkZSUJLpl7N+/n6CgIEEAkpubq0cM0dS9KJVKevfuzaZNmwQZk9zCubXmdUpKCkVFRXTu3PmpztW1a1f27dvHvXv3sLe3bzUbxN7enrZt27Jo0SLByFlRUSGY6z777DOOHDkiiDbqQ6VSMXv2bD3fXn08bgxOpVLRpUsXjhw5ItbZ8+fP0717dywsLB4agzM0NHyoDpVto8jISGpqalCr1SQkJNCtWzcsLCyIj4/H1tZWL2dAtmWbYn+XY3zDhw9vMnYHcOvWLbZt28Zzzz2Hn5+fiMupVCqGDRsmEpeaere1tbWcOHGiVeNzMk6fPk3Hjh2fijTHwcGB7OxsUdjSGrCzs6NNmzbMnTuXIUOGAHXP8YcffkCj0bB06VIuXbqk5yeWIXc5qK9z60OSpEZxtszMTN544w0A8W4fZTfI9kZoaCgBAQEitiDvqzIzM9m0aRN9+vR5qKwpn0BWVhahoaFPLMvOzmbjxo307t2boKCgJmW9evUSnTllWU5ODhs3bqRnz56NZC3tn8jLyyMtLU34cJqLdu3akZOTQ3Fxcat9X3Ke2TvvvCP8BgCbNm2ioKCAX375hdzc3CbjbjKZzsOKYhv6J5oTg5NjH+np6SJmWD/u1ZS/oOH4Y8eO0aFDB5FILEmSiLMVFhaKHABbW9tm+/vVajW9evXiypUrVFZWinM7OTlRWVlJZGQkL774ot59NdVt9H8JSarrfOnm5vZUPlpPT0/+/PNPioqKsLa2brV138HBAWdnZ7788kvhrywrK+PDDz/E19eXuXPnsmfPHr29lAyVStWkTpUhd9rOyMhAkiRu3bpFZWUlPXv21Fv31Wo1Xbt2JSEhgdraWhQKBYmJifj6+mJsbMyZM2eEbwL+P+9AHl9RUUF0dDSDBg0SCcBKpRIvLy+2bdtGYWEhNjY2lJaWYm5ujoGBAVeuXGHXrl2MGjUKLy8vamtrRQw6Li4OFxcXkRws57nJ8qqqKk6fPs2AAQPEflmpVNKtWzf++usvkYxcVlYmiEHPnj1L27ZtcXFxEd/HP+WwtQYkqa6zrbu7+2PrQ9XiMuvFtQAAIABJREFUxYsfJV8M/89CFRISQp8+fVrEoSYz6YWHh2NiYiIYO3fs2IFaraaoqIiysjJqamo4duwYLi4u3L59mxMnTohWUX/99RdOTk64u7uLNm6PA4WirkVfdHQ0aWlppKenc/jwYWbPnk3Hjh2JjY1l6tSp9OrVS2SrX79+nfDwcIyNjWnbtq1g5rx69SonTpwgJSUFb29v1Go11tbWlJaWcvDgQYyMjEhKSmLnzp288cYb9OjRA4VCQWRkJDqdjiFDhugF9ENCQsjKyqKoqIjTp08TERHBrFmz6Nq1KxUVFVy9epWTJ0+SnJyMj4+PCFz89NNPZGdnk56ezl9//YW9vT1vvvkmRkZGLFu2jMzMzCZlLaGs5E3VypUrmTp16lO1TbOxsSEmJobbt2/Tp0+fFqXELisrIzExkT179uDj40O3bt04d+4cV69excDAgOzsbDQaDZcvXyY/Px9zc3NiYmJIS0tj4MCBJCYmcurUKfz9/QVb18Mgt/DZv38/CoWCsLAwAgMDGT16NJWVlcyePZvr16/Tt29fOnbsyMGDB8nPz+fmzZvExcUxe/ZsnJychANQlp09e5Y5c+bg5OQkWJHkdrRbtmzhzTffpFevXvz5559cvnyZ3Nxctm7dCsCMGTPEdxQbG0tycjLjxo3Tq8yoqakhIiICY2Njbt68SWhoKKNGjSIwMJDq6mpu3LhBdHQ0CQkJgl3NwMCA77//nhUrVhAaGsqPP/7I0qVLSU5OZujQoXTs2JETJ06IBJ6oqChmz56Ni4sLVVVV3Lx5k5iYGOLj4+nVq5dwbnfo0IErV64QFxeHVqtly5YtjBgxgqCgoBZPkpGTsJcuXcqMGTOeynkgB/7Xr1+Pt7d3iyaul5SUEBcXx6FDh/Dz86Nr165ERUWRkpKCUqkkOzsbIyMjEhISKCsrw9DQkFOnTnH//n0CAwPFe+jTpw/W1tZP9D0qFAqsrKzYsWMHSqWS3bt34+Liwuuvv45SqeTf//43kZGRYtNz69Yt4uLiiIqKws/PD7Vajbm5OXFxcURERAjDdMOGDUycOJHAwEDatm1LYmIiycnJ5OTksHfvXmbOnEnnzp2prq7m9u3bnDt3jlOnTolzWllZ0alTJ3r06EGPHj3o1KkTW7ZsYcaMGfj5+bF//34OHjxISUkJ4eHhpKamMn/+fOGk2r9/P2q1mszMTNatW0fv3r0ZOXIkx44dIzIyUoxLSUnhk08+wcbGBoVCQXJyMnv27GHmzJkt3ooK/l8v//jjj0yZMqXZc1apVGJtbc2aNWvw8/NrUWddRkYGe/fupbi4WLR1CwsLQ6fTUVpaSmFhIRqNhn379tG2bVvy8vIEs7iNjQ3btm3D0NAQT09PLCwsnshGsLGx4c6dO5w/f57CwkK2bdvG22+/jY+PD7du3eLNN9+kbdu2uLu74+zsTFhYGJIkcfToUQDeeecdrK2tSU9PJyYmBgMDA06ePMmJEyd477336NChg964Y8eOUVtby7Rp0zAyMuLTTz8VOjU0NJT+/fszcuRIVCoV3333HdXV1aJNd1xcHPPnz6ddu3a4uLiwefNmEbSorq5m2rRplJeXM23aNLZu3cratWtZunQpS5cuxdzcHH9/f77//nsqKyvFOWNjY8U5v//+e9G2PDIykpiYGObNm6fHuvO/hsyCtHz5cqZPn/5UdoSdnR27du3CyMgIDw+PFilmqqqq4vLly+zYsYPOnTvj5eVFSkoKZ86cwdjYWBTvZGRkcP36dRwdHUlKSiIhIYFnn32W9PR0du7cSffu3XFxcXmiTakcVNq6dSuVlZWcPXuW3NxcZs6ciYWFBdu2beOLL75gwIABmJqakpGRweXLl9m9ezcdO3bE0tJSsNscPXqUkpISSktL2bBhAyYmJrz11luUlZWxatUqsSEMCQnBz8+PiRMnUlBQwK+//grUMWGvWbMGX19fXnvtNfLy8li+fDmGhoakpKSwdu1anJ2dRfvX4uJijh8/Tm1tLaGhobz00ksEBweTnZ3NsmXL9Ma1a9eOKVOmUF5ezs8//yx0WkhICN27d+fNN99sMRtRkiTi4+PZvn0706dPF+0Fm4N27doJBgNPT88Ws1fkBKE9e/ZQU1ODv78/ZmZmbNmyBYVCQUlJCcXFxSiVSiIjI2nXrh0ZGRkcPXoUPz8/jIyMCAsLw9ramk6dOj2xDrW3t+fy5ctcu3aNvLw8du3axfTp0+natSsXL15k0qRJdOnSBWdnZ+zt7dm+fbtYU62trXnrrbdQq9WsWLGCoqIi8vPz2bp1K7m5uXz66aeCjWnr1q1inIWFBW+99RYGBgY4Ojo2kk2ZMqWRLDIyEjMzsyZlBw4cwNTUlClTpqDRaGjbtq14fgcOHMDExIQpU6ZgaGiIo6OjYBiU939Tp07F0NCQtm3bClv70KFDGBoaMnXqVDQaDVVVVWzYsIG+ffvi5eXVak4kSapr0f3tt9/SsWNHxo0b91S6sU2bNpw4cYLs7Gx8fHxaNKk3Ozubffv2iYRqBwcHtmzZQk1NDeXl5Tx48ABjY2MiIiJwcHCgoKCAw4cP0759e5ycnNixYweSJImA0uP+boVCgYWFBVlZWcTGxlJWVsbmzZuZNGkS/v7+3L17l8mTJ4uCnQ4dOhAWFiZaoZWWljJjxgxsbW3Jy8vj5MmTaDQaoqOjOXjwIDNnzsTd3R0PDw/Cw8NFwu6BAwd4//33cXV15YsvvqC8vJzbt2+zceNGvL29GTNmDAYGBvz555/cvXuXwsJC9u/fz/nz51mwYAH29vZ07tyZ3bt3k5ubS2pqKpGRkbz77rt07NiRDRs2kJaWRlFREZGRkSQkJPDJJ5+g0Wh4//33+euvv1i3bp2wG5RKJYGBgSxfvpyioiIKCgo4cuQIx48fZ+7cuXTv3h1PT0969OhB9+7dUSgUxMfHs3DhwhZvzyuz3f3yyy9IkvRUBcxysP3EiRMUFxcLv0tLoLy8nKSkJHbv3o23tzdeXl4kJCRw+fJlNBoNWVlZaDQarly5Qk5ODpaWlsTGxpKSksIzzzzDxYsXOX78uPBdPUlSkOwXk/VXfR1laGjIsmXL+OOPPwgKCkKtVpOamsr58+c5fPgw3bt3x9DQEDMzM+zt7SktLWXv3r2oVCrCwsLo0qULL7/8MhcvXmT79u2oVCquX7/OmjVrGDBgAC+88AKOjo4PtbfPnz/Pli1bUKvV3LhxgzVr1hAYGMiLL76Io6Mj5eXl7N69G7VaTVhYGO7u7owbN45r166xefNmVCqVGNe3b19eeuklHBwcSEtLIz4+nuLiYrZs2cKUKVPw9fVlx44dfPLJJ+zcuZOffvqJpUuXcvToUYKCgkSB9P8aklTHtr1ixQocHR0ZO3Zss+esk5MT+/bto7CwEF9f3xabrzqdjps3b7Jz506sra1F28rdu3ej0WgoKCgQLGBRUVE4Oztz8+ZNTp48SXBwsGDK6tChA25ubo9kd5eTxbds2UJ1dTXR0dHcv3+fmTNnYmZmxl9//cU333wj2L3u3bvH6dOnqaysFC1L+/fvj0KhIDs7m1WrVjF//nw9NvysrCzBdHfr1i1+++03+vTpw6uvvoqlpSVKpZLt27djaGjI33//jampKVOnTiUvL49ff/0VjUYjWNbd3NxE55769rabmxsWFhaYm5vToUMH4Xfo0qULhw4d4plnnmHkyJFERUUxffp09u7dy7Jly1i6dCk7d+4kICCAXr16NRoXHBzM888/j4mJiUjmLi0tZePGjRgaGjJlypQWTbjS6XRER0ezYcMGFixYQJs2bZp9LisrK44ePcr9+/fp2bNni/vzMjMziYiIoKCggL59+2JnZ8eWLVuora2lrKyMwsJCDA0N2bdvH46OjuTn53P48GHc3d2xt7dn27ZtqNXqZvkZrKysSEtLIyEhgeLiYsLCwpg6dSp+fn7cvn2bSZMmYWdnh4eHBy4uLsL/Ud9fYGxsrCc7ceIENTU1QvbZZ59RXV3NzZs32bhxI3379mXUqFHY2NjQtWtXsUaXlZVx8+ZNFi5ciIWFBTU1NWzevJnOnTsLfy7UFQbWH6fVarl27RoLFy7E0tKS9u3bi3s5deqUaMlqYmJCbW0tW7Zswc3NrVHxWm1tLVu3bsXV1RV/f3+h/x48eMCsWbMICwvj999/FzaIRqOhb9++j7SVWtqW1ul0XLlyhe+//55333232cyqsp1x+PBhqqqq8PLyarF5X1ZWxvnz54mIiMDHxwcvLy9iY2O5fv26Xqzj0qVL3Lt3DzMzM2JiYkhPT2fgwIEkJCRw+vRp/P39sbW1feLkY/mbUSgU7Nu3TxTiq9Vq/vOf/7BlyxYGDBiASqXizp07xMfHc+zYMby9vdFoNJibm2Nvb8+1a9e4dOkS9+/fZ8eOHUybNg0vLy/atGlDQUEB+/fvR6lUsnnzZrp3786LL76IRqMhJSWF7du38+677wo/i0KhQK1WC5benJwc1q1bh5eXF2PGjBG2bI8ePfDw8GD79u1MnjxZ6Ivi4mIiIiJQKpWEhYXRtWtXxo4di5OTEyUlJXoy2R7q0qVLo3O++eab9OvXr8XmrSTVsXT/9NNPdOzYUY8YoDmwsLAgPDwcIyMjunTp0qJEQffv3+fw4cNcv36dgIAA2rdvz65duygtLRX+SRMTEw4cOCCY4g8fPoyFhQWenp5ERERw//59/Pz8MDc3f6Lvy8jIiNLSUo4ePYpOpyM0NJTRo0czaNAgCgsLefvttykoKKBnz564ubmxY8cOysrKSEpK4vbt28yePZt27drpvXMzMzOOHDnCwoULcXNzayQ7evQoCxcupEOHDpSVlREZGYmxsTEXL17k77//ZuLEifj6+rJ8+fJGMd5JkyaJuX348GG0Wm0jwpgVK1aQnp5ORkYGmzdvxtbWlkmTJmFsbEx4eDgXLlygvLycU6dOcfDgQT744AMRi46MjMTIyIgrV66wdetWxo8fT69evXB3dycqKorr169TUFDAjh07eO211/Dz82txXSzPa1dXV0aNGvVU+lN+/qWlpfj5+bXYvK6srBR+465du+Ll5cWNGzeIjY3FyMiI3NxcFAoFqampJCcnY29vz/nz50lKSuK5557jzp077NmzB29vb9E14mF43BhcUFAQLi4uomNbVlYW+/btY+bMmXh4eHD27NlGMbjXXntN6Oz9+/djYGBARkYG69evJyAggOHDh+Ps7ExiYiI3b95sFJ87duwYhw4dQpIkrly5wu+//86IESMYMmQIBgYGeudct24d/v7+jBo1Sk8vy7G76dOn4+3tze+//86SJUvYunWriDvHxcXx3HPP4e3t3WjctGnThJ3T2vE5qLMlLl26xC+//ML777+Ps7Nzs78Za2trzp8/T3JyMr17924RX5ycA7Nz505cXFzo3r07+fn5HDlyBENDQ+7duyfY6BMSEmjXrh1XrlwhJiaGZ599lvv37xMWFkbnzp1xdXV9ZCKTQqEQ8TKAI0eOoFAoeOeddzAyMuLnn39mzZo1BAUFYWBgQFpaGomJiRw8eJBu3bphbGyMmZkZO3bsYMGCBezYsUPs7Y8dO8aAAQM4cuQIn3zyiZ7s6NGjDBgwgKNHjzbpEwgMDOTYsWOi+4YsO3LkCIGBgZw4cYL58+c/tuzw4cMEBgZy6tQp5s2bx65du5qUffTRR3qyQ4cOERgY2OyCssdBVVUVa9eupba2lsmTJzdbvyoUCkxMTIiKiqKkpARfX98W0a+yfyI8PBwLCwv8/Pyora0lPDwctVpNYWGhYCs9ceIELi4u3Lp1ixMnThAUFER1dTWbNm3C2dn5sfwTzY3B1fcJZGVlsXLlShH3CgkJwdXVlcmTJ+Ph4aG37z948CCDBg0SZEu5ubn88ssvzJ8/X+z15WddVFTEiRMnqK6uJjQ0lDFjxhAcHCxIS65cuUJ4eDiurq5YWVlhbm5OSUkJV69eZf/+/VRXV9O+fXtMTU0xNDQUv1Wr1ZKUlER0dLTwMy9evBiFQkFubi67du3i6tWrT+0TeBQkSRJ6c968eU/FtGpubi4IErp3795i675Wq+XixYsi5uvl5cXFixdJTEzEyMiI7OxsVCoVycnJpKWlYWtry7lz57h27RqDBw/mxo0bHDhwAF9fXxwdHR+5Rsmdp8LDw1GpVPz9999069aNcePGodPpmD9/PmfOnKF///506NCBM2fOcPfuXe7evcuRI0eYPXs2rq6uREREEBsbS3V1NRcuXGDDhg288sorYt2/cOH/2HvzoLbvO3384RYSum8hbgTivsHGN7bj244dx63jOL4Sd7O73c50d2eaNv1O23Q7sz2SNtv0SI8cTdM2aVLndGIncWI7sfGBuW+EAAkhCXQgJCHQ8fsjv/e7Ej5ix2Bj/HlmGPBgQKBHr/fzfh3Pqwlnz56leS+C5ORk9PX14fTp05iamsJf/vIXrFq1CkuWLMEzzzyDH//4x3j55ZfpGd3c3Iw1a9bgo48+wunTpxEIBNDS0oI//vGP2L59O5YvX47Y2Fi0trbi5MmTtDZHoFKpoNfr8cknn9AcxvLly7FmzRp8+OGH+OSTTxAMBtHc3Iw//OEP2Lp1K1auXIlgMIje3l7U19fj9OnTNPfE5XLn9F4TDAbR0NCA3//+9/iP//gPKJVKEmfGATx1ta+77oZehUIBh8OBF154AdXV1eDz+bMqxokjEZfLhVAohFwuR11dHYRCIQwGA1wuF5KTk1FQUACRSASLxYLs7GyUlJQgFAphcnIScrkcHA4HIpGIrl+6XrDZbFRXV9OftXfvXlRWVtLpHoFAgJKSEnA4HAwNDeHixYtIS0uDWCyGx+NBamoqAoEAzp49i7i4OOTk5MDpdEIsFkMqlaKoqAhSqRR6vR4ejwfbt2+nDqjEOaampibCUSw6OhpisRgmkwkGgwFxcXF48MEHsXTpUsTGxmJiYgJnz56l03NOpxMikQhSqRRxcXHo6uqC1WpFcXEx9u3bB4FAQJMU3d3dsFgsl31uLuB0OvHDH/4QKpUKDzzwwE2J4ZiYGGRlZeGFF16A3W5HaWnpnBWJx8fH0draCo1Gg/j4eJSVlaG2thaTk5MYGBgA8PnUZnFxMTweDzweD3XtEovFGB0dhUajQVTU546A11qbGx0djZycHPB4PPT19aGioiLib0WSwykpKUhKSkJFRQUGBgYwPT2NgwcP0oMmKSkJlZWVGBgYwNTUVMTnhEIhdWoIBoO4//77cc899yA+Ph6xsbHo7e2F2WxGZmYmHn744YgGFbPZjOrq6oiDkUzFEyc1u92OdevW0dVsHo8HFy5cwOTkJAoLC6k7jEKhAIvFQkFBAZYvX05XqixduhS5ubng8XiorKzE4OAgvF4v9u/fTwWe1+vFxYsX4fF4UFRUBJfLhaSkJCiVSiQkJKC2thYTExMwGo1YsWIFfSxzDZ1Oh+9973soKirCnj17bqqJKCoqitrVP/PMMygqKpqziWC73Y6Ojg7k5OQgPj4e1dXVqKmpgcvlwtDQEGJiYlBQUICioiI4HA74fD4sXboUiYmJkEgksNlsyM7ORnR0NNRq9Q1NfhIHCpVKhd7eXuTm5tLGh6ioKERHRyMzMxNZWVnUCdFms9HXW2JiIlQqFQQCATweD42tO3bswMaNGxEXF4fExERUVVVhZGQEdrsdu3fvRm1tLaKjozE5OYmmpiaMjo7S78lisaBUKiMuJmSgpby8HAKBADExMRgaGoLRaIRMJsPXvvY1Ot2jVqtRVFSEgYEB6sa3e/du8Pn8a34d8HlDSmlp6RXX2M0FRkdH8b3vfQ/JycnYv3//TTmAKJVK9Pb24siRI6itrb2pSeJroa+vD1NTU1CpVBAKhVi5ciVSUlJgNBoxOjoKuVwOrVaL5ORkWCwWyOVyLFq0iK7cYLPZEIlE4HA4SE5OviFRlpCQgMrKSrpyddu2bVizZg3VCBwOB0VFRdS9ibg6KhQKHDp0CFKplDoWsFgsDAwMICoqCnv27EFNTQ2io6Pp1+l0Osjlcvp1ZHKsq6sLDocDq1atwo4dO+g6RoFAAIPBgOHhYYhEIhw8eBDFxcWIjo6GVCqFRqOBTqeDVCrFoUOHqD7icDioqamhMZjEYbVaHfE9hUIhDh48SJuyiC4bHh6GQCDAwYMH5+wSDoD+7o899hjWr19PHQe/LDgcDuRyOX72s58hIyMDqampsx5fJycn0dzcjPT0dLBYLGRlZWHlypWIi4uDXq/H1NQUsrOzI1bjlJaWQq1Wg8PhYHR0FJmZmXSd77Vcxa8EgUCAwsJC9Pf3g8Ph4NChQ/T3jIr6fBV2QUEBbYrp7Oyk/yaxTCwWo7q6GjabDUNDQ0hNTcUjjzyC5ORkxMXFITo6GgaDAXa7HTU1Ndi/fz84HA7i4+NpvLPZbKiursaBAwfo5T8QCGB4eBg2mw0lJSU4fPgwxGIxYmNjqV4hg1H33XcfYmNjkZCQQJ1ObTYbioqK6NfFxcUhJiYGBoOBupoePHhwzhoWSMLgu9/9Lvbt24fly5ffFPfZbDaSk5Px9NNPg81mIy8vb870eFdXF2JiYiCTySCVSrFy5UooFAoYjUbY7XYolUrk5eVBLpfDYrEgJSUFVVVVdFJWIBCAz+eDx+NBpVLd0ONksVioqqqC2WyGzWbDrl276N+ONEaWlJSAx+MhOTkZqamp6OvrQ3p6Og4cOEBfA+GxKSUlBY8++iidQFepVEhLS0Nvby/9OnK/udbnlEol0tLS0NfXh7S0NBw8eJBOZCuVSmRkZKC3txepqakRn1MoFMjIyEBfXx9SUlJw8OBBOqSjVCqRnp4OnU53xc+Rr1Or1RGfm56eRiAQQHV19TXvDbMNr9eLH//4x9Dr9Xj88cdvOObMBIvFQk5ODp555hlMTk7SWDcX0Ov11KmZz+djxYoVyMzMpC7NUqkUWq0W6enpMJvNEIlEqK2tRSAQAIfDQVxcHKRSKRITE6FWq2/occbHx6O8vBxerxfDw8NYv349XaUXFRWFxMREFBUVQSwWQyKRIDc3Fzqdjp7VSqUS0dHRKCsrQ1JSEvR6PYLBIL7yla/Q+35SUhKqq6thNpvhcrmwa9cuLF68mMbrrq4uOmi3a9cummwWi8UwGo0wGAwQCAR45JFHkJeXRwcHa2pqYDabMT4+jp07d6K2tpauxiRfx+fz8cgjj1CnRTabTV1EwnVDamoqdWE3Go3gcDjYt28fqqqqLvt7xsbGQqFQoKioaM7d5/x+P5599lmcOnUKjz/++E3fpxITE5Geno6f//zn4HA40Gg0c8LrmTmI0tJSLFmyBFNTU9RVieQgvF4v3G43df4iTvlkYIkk328E4bFtZoyKjo5GSkoKcnNzEQwG0draCoPBgOLiYurAnpycDBaLhYqKCsTFxUGn00Gr1eKhhx6CUCgEh8OB1+vF0NAQXC4XVqxYgT179iApKemqepsMrft8PgwNDWF8fBzLli3Dgw8+iKSkJMTGxqK8vBwJCQno6+uDRqPBgQMH6M/z+XwwGAwRX8flchEfH4+KigqMj49jZGQEmzdvxj333IPo6Gi6pm1mvqK4uHjO3I4CgQCeffZZnDt3Do899thNGSnExMRArVbTFb0365h6NZBEu0gkAp/Ph1KpxKpVq8Dn8zE0NISJiQl6R+bz+bBYLNBqtbTBf2JiAiqVCmw2G1Kp9AuHpIRCIfLz89Hf3w8ej4eHH36YFr3JGZufnw8Oh4OSkhL4/X4MDQ1h7dq11H0cANXaM3UXyb8NDQ3BbrejtrYW+/bto6v7CgoKIJFI0N3dDYVCgcOHD0Mul4PFYlGNa7fbUVZWRgc6A4FAhN4mDj1qtfqyOMhms1FcXAy5XI7o6Gi6sjI87paXl1+mc9lsNgoLC6FUKum54XA4MDg4iNTUVBw+fJi6nMwV2tra8IMf/CDidfRlwWKxkJ6ejt/+9rfw+XzQarVzemb09fXB5/MhOTkZQqEQK1asQFpaGs0zyGQyaLVaqNVqWCwWyGQyLF68GH6/HywWC4mJiRCLxVTX32ieITwObdmyJeLvx+FwUFxcDJFIBJlMRu/2JF9AzraZ9/6DBw/Se394LmHlypW47777rhjHYmNjad0lNjYWgUAAXq8XNTU11BH6Sgj/OuKcSTSPWCzGoUOHqFFBIBCAx+O54vcM/1y4FiUapKqqKuK1sGTJEqjVanC53KtqpblEKBRCQ0MDvvvd72LDhg03PRDH4XCQmppK161nZ2fPic5wOp1oa2uDRqNBQkICysvLUVtbC6/XS2sd+fn5KCoqwsTEBDweD83zhdc6iCa4kZx7VFTUZXe9gwcPQiAQAPi8NpKeng6NRkPPF5PJhOLiYkxOTiIhIQEqlQocDgdVVVUYHR2F1WrFzp076Ur12NhYWs/r7++nw76EUyMjIygqKopwKCPnR2lpKYaGhmAymVBWVoa9e/deNoBGcmnl5eUQCoX058XGxkKn0yEvLw8PPfQQBAIBdTMjn9NqtbQGN/N7JiUloaysbE4H3vx+P5555hk0Nzfjscceu6laILnDJycn46c//Sk1x5irO5/RaMTIyAgyMjLA4XCwfPly5Ofn0204AoEAWq0WOTk5sFgsYLFYWL58OUKhEIRCIaanp6FSqRAfHw+1Wn1DdRuSqyLDbMuWLcPOnTvp9yA6S6lUgsfjobi4GHq9HnFxcTh06BCysrIu+ztHR0dDIpGgtLT0sgH+8M8lJiaioKAAcrmc3nvvvfderFu3jtbzSI23qKjoshov2XY0s6Em/OsKCwuxf/9++nVk4HRwcBCxsbE4cOAAvdeR37O/vx8ulwtbt27F+vXr6frt2tpaOBwOmM1mbNy4kT7OuYTL5cL//d//0YEUcm/5MoiK+txpOSUlBb/85S/n9M5HGnuIs2BOTg5WrFhBeTZdDvMwAAAgAElEQVQ1NQWNRoPi4mIAnzswV1RUUGMxq9WKrKwsqvmvdU7fSA2O6Mjh4WE4HA488MADdB02aZafWYOLj4+njZ16vR5msxm1tbX46le/Ch6Ph8TERFRXV1+xPsfj8Wgd0uPxYP369di5cyfYbDa9Q5DvGV5nm/n7cblcWruLjY2FRqO57B5XWFgYwceZNT8AdCiduBDPNUgj83e+8x1s3boVW7ZsuSktERcXh+zsbPz6178G8Pl5Ptv8nZ6eRktLCz2PU1NTUVdXh8TERFrPT0tLo/fm0dFRFBYWIjs7mw58pqWlUcODLzr3ZDIZ3bqmVCpx6NAhaihE+i6I43xbWxsGBgZQXFxM64EqlQoJCQmX3e2XLVuG4uJisNnsK977SS/Q1XICV/oc+Z4cDgdpaWlX/J7EmOxqP+9Kn7vW9yRnxVyAbMo7cuQIvvWtb91wLWAmWCwW1Go1nn76aYhEImRlZc16PZHkqQQCAQQCARQKBerq6sDn82EwGDAxMYHk5GQUFhbSjdk5OTk01no8HigUCnA4HIjF4i/MI37ZGlx4ToDL5UbkEkpLS/Hwww9f8bXBZrNRVFQEhUIB4POBp/T09MtMQWJjY6mZ5ODgIFauXIkdO3bQO15XVxc6OjqQn59P9YxarYbNZkN9fT3kcjmUSiVcLhdSUlLoPYBo5enpaezdu5fm+7lcLoxGI4aHh6FQKPDII48gNzd3To2/Hn/8cSxduhTbt2+/KfMG0ivw1FNPQSgU0rN1tuF2u9HS0oLs7GwkJCSgoKAAy5Yto875fr8fWq2Wxi+n04nq6mpIJBIIBAJYLBb6miF9Ytf6vTIzMyGTydDb24vCwkI6uEXOfY1Gg4yMDCQlJaGqquqKvZECgQB2ux1DQ0Pw+XzYtm0btmzZQrWryWRCZWUlUlJSIn5+XFwcFi1aRHO/tbW1uO+++8BmsxEfHw+tVntZLMvPz4dYLIbT6aRnydatW7F161Ya40wmE8rLy+kmwZk/z+fzYXBwEDU1Nbj//vuRlJQEHo8X8T23bNmCe++9F4mJibQ53W63o7i4GG63m/YdzaXpEskh7NmzB2vXrg3n7zUbeqO+wFY44pMulwtPPvkkLl26hCeeeII2gd0q9yAGdxYCgQC6u7vxk5/8BBwOB9///vdnxbKcdM1/+9vfRnJyMv71X/+VNr4wYHCrEAqF4Ha78dFHH+FXv/oV1q5di8OHD9+QO/i1MDk5ieeeew6vv/46/uu//gtLliy55kQYAwbXg6mpKTQ2NuLJJ59EamoqvvWtb910XA6FQnA6nfj5z3+OlpYWfPOb30RFRcUtXUfMYOGBDGtduHABTzzxBO655x48+uijs9Lk5vf78dprr+F3v/sdvv71r2P16tVMfGVwTZCVMvX19XjiiSewY8cO6lh4swgEAjhx4gSefPJJrFq1Cnv27IFCoZjTSVAGDABQt7ann34aPp8Pjz/++BULjl8GxMn6Rz/6EbRaLR599FGaEGFiLYO5RCAQgF6vx29/+1v09vbiBz/4AfLz82clppKVWD/4wQ9wzz33YP/+/RAKhUy8ZnBTCAaDMBgMePbZZ9Ha2krj5s3yyu/3o76+Hj/84Q+xevVqPPDAA+HODwwYzAqIa+EzzzyDnTt34sEHH6SFoptBMBhEV1cXvv3tb0OlUuGb3/wmUlNTmbwvg9uOUCgEh8OBd955B88//zx2796N3bt3zxrvT548iR/96EfYvHkzHnzwQQgEAkZnMLgpBINBDA4O4je/+Q16e3vxxBNPzJqjbjhnV69ejQMHDkAsFs+5szoDBtPT0+jt7cXPfvYzeL1e/O///i8d9r5ZBINBXLx4Ed/5znewatUqHDhwADKZjInFDGYNZDPL6dOn8bOf/QxbtmzBoUOHZsWYKhQK0dz1qlWr6OAMw18G1wtiQPjyyy/j7bffxv/7f/8PixYtmpWzPRgM4tNPP8X3vvc97Nq1i27CYXIUDL4IoVCIDhT8z//8D0pLS/GNb3zjhjbkXA2BQACfffYZvv/972Pjxo3Yu3cvxGIxEzcZzBpIP9mJEyfwi1/8Art27YrYqvH/wwAg5Srf4sYaegHQVfZ//etfsXLlSjoRzoBBOMbHx/HWW2/h5ZdfRlVVFf7zP/9z1hodgX+Kil//+tc4c+YM6urqsH379ptaw82AwfWCNPX87W9/g9FoxL59++gE5Wzyb3p6Gh999BF++ctfIiUlBfv3779sLR0DBteDUChEV2mdOHECGzduxNe+9rVZG8oJhUIIBoN46aWX8PLLL6OyshL79u2jDs4MGNwIiIvQc889h+bmZhw6dAhbtmyZ1XVXZC3sU089BblcjsOHD6OkpISJrwwuQygUwuDgIJ5//nnU19fj4YcfxubNm2fVaYRM4/74xz+GwWDAV77yFWzYsGFO12YxuHsRCoUwNDSE1157De+//z6WLFmCb3zjG+ByubO+gcdsNuOpp55CS0sLNm/ejPvuuw9yuXzWfgYDBgSEb2+//TaOHDkCrVaL//7v/571TSehUAg9PT148sknYbVa8ZWvfAVbt25lBtkYfCm4XC4cO3YML774IlJSUvCtb31r1poRgM/5qtPp8NOf/hQjIyN48MEHsWbNmpt2YmfAYHp6Gs3NzXjuuecwODiIw4cPY+PGjdSNaDYQCoUwNjaG5557Dh9//DGWL1+O7du3001oDBjcakxMTOD06dN46aWXMD09jX//93/H0qVLZ11ndHV14ac//SmcTid2796NTZs23bLV3wwWFsbHx3H06FG89NJLyMjIwGOPPUYds2cLoVAIvb29+MUvfoGhoSFs27YNO3fuvKZjKAMGXxakvvH3v/8dx48fx7Jly3D48OGbcua92s/R6XR4+umnMTg4iPvvvx9btmyZs62EDO4eBAIBNDU14bnnnsPAwAC+9rWvYf369bM6CEH4+5Of/AR2ux179uzBhg0bmME4Bl+IqakpnDt3Dr/5zW8QDAbxne98Z9a3/YRCITQ3N+Oppz43oty7dy91KGfA4Gowm8144YUX8NFHH2HHjh04cOAA3V43GyB3sKeffhoWiwW7du3C5s2bb8kGcAYLG4FAABcuXMDzzz+PkZER/Nu//RtWrVp1pXN/dht6gc+dHi5duoRnn30WY2NjOHDgAFasWIGkpCSmcecuRSgUQigUgs/nw9mzZ/G73/0OwWAQX//611FWVjZnQc/n86GtrQ2///3v0dvbSy24FQoF4uLimCQvg1lDMBiEx+NBa2srXnzxReh0Omzfvh2bN2+mK3PnAqTJ569//SuOHz+OtWvXYteuXUhJSWE4zuCaCIVCCAQCsNvteP3113HkyBHk5ubi8OHDdM3NbMPv96Ovrw9/+MMf0NDQgM2bN2P37t0QiUSzKrAZLDyEQiH4/X6YTCa88sorOH78OJYuXYr7778fOTk5cxJjSVPbn//8Z3zwwQfYunUrdu7cCblczrhIMkAgEIDNZsN7772Hv/zlLygoKMD+/fvp2vrZRigUgsvlQn19PX77298iFArhgQcewNq1a+mqZ4aTDL4syCT72NgYXnnlFRw9ehS5ubmU0wkJCXPCr1AoBK/XiwsXLuCPf/wjxsbGsGPHDmzbtg08Ho/hNYObAtEOdrsd7777Lv7+979DKpXi8OHDKCoqmlP3fYfDgffee482Yu7bt4+uzWVyYgyuBpI383q9OHPmDP74xz/C5/PhX/7lX1BTUzPrgxXkZ7pcLpw6dQq/+tWvwOfz8fDDD6O6uhpsNpvhK4PrBsn56vV6PP/887hw4QK2bt2K7du3z+laQrJl6KWXXkJbWxvWrl2LHTt2IDU1FfHx8QyHGcwZSE7N5XLho48+wt/+9jf4fD7s3r0bq1atmvWhoXDYbDYcPXoUf/rTn5CZmYmHHnoIxcXFjM5gcE0QnUGcH59//nkEAgE8+uijqKysnBOdQTA+Po6TJ0/ihRdeQHR0NHbt2oXVq1cjKSmJufMxuCmQXAYZ3nzzzTeh0Wiwf/9+FBQUzOnAg8vlwokTJ/Dcc88hKSmJmu0wfRAMbgRk65ter8cLL7yA8+fPY9OmTdi2bRvS0tLmjEskT/Liiy8iLy8P+/btm9P8H4M7E4SfOp0Ozz77LNra2rB3716sW7cOUql0znLFo6OjeO211/Dqq69i8eLFeOihh5Cens70PDAA8E8DsYmJCbz11lt45ZVXkJaWhoMHD6KwsHDOeg2cTieOHz+OF198ERKJBA899BAqKyuZ3BmDGwKJqz09PXjxxRfR2NiIe++9F5s3b0ZKSsrVuDv7Db3kwfj9frzzzjv485//jGAwiO3bt6O6uhpZWVnMapW7CIFAAMPDwzh79iz+8Y9/wO1246tf/So2bdo0p4kCAsLFpqYmvPjii+js7ERBQQHWrVuH/Px8qNVqJtAy+NLweDzo7u5GQ0MD3n33XUxOTmLTpk3YsWMHFbS3guNk4p00SpaUlGDdunUoLi6e0yQygzsPoVAITqcTXV1dOHbsGE6fPo2MjAzs27cPFRUVc34pIjG5sbERf/rTn9DZ2YmamhqsX78e+fn5EAgEDF8ZUBDnpebmZnzwwQc4f/48ioqKcODAARQUFMx5jCXxtbW1Fb/73e/Q3d2NlStXoq6uDoWFheBwOHP2sxnMT0xOTqKrqwunTp3Cu+++C5lMhocffpiul7oVZ77b7cYHH3yAV199FQ6HAytXrsTKlSuh0WiYVVQMbgjBYBAjIyPo7OzEO++8g+bmZuTn52PPnj0oLS29ZYlSksj4+OOP8eqrr8JgMGDx4sVYvXo18vLyIBQKmfsag+tGKBSC1WpFd3c3jh07hvr6eqSkpGDv3r2oqam5JQUqkkdzOp3485//jKNHj0IgEGDLli0oLy9HRkYG4zDCgILEwP7+fpw5cwZvvfUWQqEQvvrVr2L9+vWzsibweh6Dw+HA0aNH8corryA6OhpbtmxBTU0NMjMzmcIug6siEAjAYDCgpaUFb7zxBgYGBrBy5Urs3r17TpsQwkEKeu3t7Xj55Zdx8eJFZGRkoK6uDmVlZUhLS2McTBnMGojrf09PD06cOIEzZ85ALBbj/vvvx6pVq25ZrQP4vBnnpZdewvvvvw+JRIJNmzahoqIC6enpTO2NAQUZuNDpdPj000/x7rvvIiYmBrt378batWtvCWfDH8dbb72FI0eOYHx8HCtWrMCyZcug1Wpvid5hsHAQCoVgMpnQ1taG48ePo7GxETk5Odi3bx/KyspuWX4OANxuN44cOYLXXnsN0dHR2LRpEyorK5GTk8NsamFwVQQCAZhMJly8eBHvv/8+ent7sXTpUjz44INIT0+/ZTUPsvHio48+Qnp6OjZv3oyysjKoVComJt/FCAaDsFgsaGxsxBtvvIG+vj6sXbsWu3fvhkqlmvM7HuGn0WjE73//e5w5cwYFBQXYtm0bCgsLIRaLGX7epfD5fOju7sYnn3yC999/HyKRCHv27MHKlStvSW8D8PlAz6uvvoo333wTCQkJ9NzXaDRzYpTGYGHA7/fDaDTSc39gYADLly/H3r176Ta2a/B3bhp66X8IhWC323H69GkcOXIERqMRZWVl2Lp1KyorKyNs/JnguzBAOBMIBNDR0YFXX30VFy5cgFgsxoYNG1BXVwe5XH5bnm/S8X7ixAmcPHkSLpcLJSUlWL16NZYuXUqLFAwXGVwJhNtESB4/fhwff/wxLBYLsrKysGHDBlRWVt42fgOfrzbs6enB+++/j1OnTiEQCGDJkiXYtGkTtFotFdoMx+8eEN4Gg0EMDw/jvffew7Fjx+DxeFBVVYV77rkH5eXltyXBRNx0jh8/jrNnzyI+Ph51dXXYvHlzxLAFw9e7B+Fxtre3F2+99RZOnz6NUCiExYsXY8OGDdBqtbflYjQ5OUkL1RcvXoRcLsf69euxbt26iCZKhq8LB+F89Hg8OHnyJG1U0Gq12LFjB8rLy+fU5fFacLlcOH/+PD788EM0NjYiMTERdXV1WLduHdLS0iKKuAwvGYTzeWpqCs3NzXj33Xdx/vx5JCQkYMWKFVi+fDkKCwtv66o9r9eLhoYGnDhxAufPn0dUVBRqa2uxefNmaDSaiMIcw2sG4bwOBAJoa2vDsWPH8OmnnyIUCmHRokVYs2YNioqKwGKxbgtngsEgzGYzTp48iaNHj8JkMqGoqAjr1q3DsmXLEB8fz+Qg7jKE85asaH/jjTeg1+uRkZGBTZs2YdGiRZBIJLecF8QNp76+Hu+88w76+/uhVquxadMmLF++HEKhkInBdzHCuevz+XDp0iW89dZbaGxsBJ/Px7p167B06VJkZWXdtkEcv9+PgYEBnDx5EqdPn4bBYEBaWhrq6upQV1cHsVjM5BkYXDdm6ueLFy/iww8/xPnz5xEdHY3q6mqsXLkSJSUlt+1OGAwGYTKZaFF7ZGQEJSUlWL9+PZYsWUIL2wzf7x6E83Z8fBynTp3Cm2++icHBQWRlZWHjxo1YvHgxRCLRbeMFyWV88MEHaG5uBpvNxtKlS7Fp0yakp6czcZrBZSDNXWQ18bFjx3Du3DmwWCwsXboUa9asQU5Ozm0b4CGNkefOncPbb7+Nvr4+pKWlYc2aNVizZk2EgQnD67sThMPT09NoaGjAG2+8gaamJohEIixfvhx1dXW3TUMHAgEMDQ3h2LFj+PDDD+F2u2kerqCggInJdwHC+3r6+vrw+uuv47PPPgOLxcLq1atRV1cHjUZzWzjg9/tpz8NHH32EmJgYrF27Fhs2bEBqairDzwUOEjsnJyfx4Ycf4t1334VOp0N+fj697yQlJd2Wx2W1WnHmzBm8++670Ov1yMzMpOd++MAcw827E4S7U1NTOHfuHN566y20tLRAKpVixYoVqKuri7j3fAHmtqE3/EF7vV6MjIzg73//Oz7++GMkJCRg8eLFWLJkCdLT0yGVShm79DsYfr8fVqsVRqMRn332GU6ePEldw7Zt24bMzEwkJibedncl4tzg9XphNBpps5DH44FWq8WSJUuQn58PqVQKiUTCOOfc5SBNPBaLBSMjI/jss8/Q2NgIg8EAjUaDDRs2YOnSpeByufPGtYYkN7xeL9rb2/H666/j4sWLEIlEqKysxLJly5CcnAyZTMZMCS9QEBfcsbExGAwGNDY24vTp09Dr9dBqtdi5cyfKysrA4/HmbP3EjT5Wl8uFpqYm/OMf/0BLSwtUKhWWLVuG8vJyqNVqSCQSRiMsYPh8PlgsFphMJnz66ac4d+4cLBYLysrKsG3bNpSUlIDNZt/2VXwk8UbWqh05cgQmkwklJSVYtmwZCgoKoFAobpnDCYO5ATn7zWYzdeO9cOECuFwutmzZgnXr1kEoFM6Lcz+ck83NzThy5Ai9GFZVVaGqqgqpqamQSqW3rcjM4PYiGAzC4XBQx9L6+npcunQJgUAAy5Ytw5YtW5Ceng4OhzNvnLyINpiYmEBHRwfefvtt1NfXg8fjobKyEjU1NUhPT4dMJmPWWd6lIBsnRkdH0d/fT+9oExMTqKysxPbt25Gbmws2m31bG9TDHy9JQJvNZrzxxhs4ceIEfD4fSkpKsGLFCmg0GshkMsadbAEjGAzC6XTCZDKhs7MTp0+fRnNzM/h8PrZs2YK6ujpIpdLb1nweDsJXm82GTz75BG+++SYsFgvy8/OxePFiFBUVQalUQigU3nZ9zmDuEQwG4XK5YLFY0N3djbNnz+LixYsIhUJYvXo1HcidL6smw2Pu2NgYTp48iffffx9DQ0NISUlBdXU1ysrKkJycDIlEwmhkBpdhenoaY2NjGB0dRXt7O86dO4fW1lbExMRg0aJF2LJlCzIyMuadziC1tyNHjuCTTz6B3+9HSUkJVq5ciczMTMjlciZXsYARCAQwPj6O4eFhdHZ24tSpU2htbYVAIMC9996LFStWQCqVzos8BvDPXMbExAQuXryIo0ePorGxERKJBFVVVVi0aBGSk5Mhl8vBZrPnxWNmcGtBchkWiwU6nQ4nT55Ea2srgsEgFi9ejG3btiEjIwOJiYnzRo8S/TE+Po7jx4/jvffew/DwMLRaLRYvXozS0lLIZDKIxWKm7nwXgKyEHxkZQX9/P06ePInGxkYEg0GsXr0aGzZsQFpaGuXw7UR430Rvby9effVVnDt3DiKRCNXV1Vi2bBlUKhVkMhlTo1tAmJ6ehtVqhcFgwLlz53Dq1ClYrVYsXrwY9957L3Jzc+dNvtjv98PtdqOlpQV/+9vf0NraivT0dCxZsgQVFRVQq9VMfmKBgAy/j4yMoK+vDx9++CGam5vB5XKxceNGrF+/HmKxmBok3O7HOjk5CYfDQc3ULBYL8vLyUFtbS7doi8XiefE6YjC3ILmzkZER6HQ6fPLJJ2hqakJMTAzWrFmD9evXIyUl5cv0S96aht6ZsNvtqK+vx/nz59HR0YGpqSmkpKSgpKQERUVFKCwsZNZh3QEIBAIwGo24cOECLl26hJaWFvj9fhQWFmLJkiWoqqq6rW6l1wuPx4Ompia0traisbERJpMJUVFRyMrKQnZ2NoqLi6HVapk1xncJAoEALBYLWlpa0NHRgdbWVphMJrBYLBQUFKC4uBhlZWU3MjlxWxEKhTAyMoJz586hqakJ7e3tmJqagkqlQl5eHkpKSlBYWMjw+w4HmfTp6+tDa2srzp8/j56eHoRCIWRmZqKmpgZVVVXzfvVeMBjEwMAAGhoacPHiRej1evh8PqSmpqKwsBBFRUXIy8tDUlISw9c7HG63G52dnWhpaUFzczN6enoQHR2N4uJilJeXo7KyEmq1el4/z1NTU2htbUV9fT2am5thMpnA5/NRWFhIzwqpVDqvfwcGn4MkCjo7O9HU1IT6+nr6fJaXl6O2tpY2ls9nEIemhoYGNDY2orOzE263GyKRCFqtFoWFhdBqtXeMhmHw5TA9PQ29Xo+2tja0tLSgvb0dExMTEIlEKCkpQWVlJYqLi+8Y7RcKhWCxWNDU1IRLly6hvb0dTqcTfD4fGo0GxcXFyMnJQXZ2NlMUW8Dw+/0YHh5Gc3Mz2tvb0dLSAofDAS6Xi9LSUpSWlqK8vPyOWb3ndrtx8eJFNDU1oaWlBVarFTweDwUFBdBqtSgtLY3YWMHgzkQwGITBYEB7ezvNmTmdTigUClRWVqKqqgoFBQXzoon3WiBrDc+fP4/W1lYYDAYAQFZWFvLz85GXl4eCggIkJibe5kfKYLYQDAZhNBrR3d1Nz1+bzQaBQICysjLU1NSguLj4jhlCCAQC6O3tRUtLCxobGzE0NASv1wsul4usrCzk5eUhPz8fWVlZjJa4CxEKheByudDV1YWWlhZ0dnaiu7sboVAIKpUKxcXF9I3L5d7uh3tdmJiYwIULF9Dc3Izm5maMjY2Bz+ejoKAAeXl5KC0tvSUrkxnMLYirItEZra2tGB8fh1KppAO+eXl5815nAP/ciNjY2IhLly6hq6sLXq8XQqGQ1udyc3PnfV6bwc1hamoKBoMBzc3NNJ/hdDppUyHJGfP5/Nv9UK8L09PT6OjoQENDA5qbm2EwGBAKhZCdnQ2tVkvrzoyGXjgIBAIwm81ob29HY2MjWlpaYLPZwOVyUVFRgYqKCmq0M5/jcigUgtlsRn19PRobG9HW1ga/34/09HQUFBTQmjJjGHXnwefzob+/P+K8jYqKooMHFRUVUKlU85qfRP+cOXMGDQ0N0Ov1iIqKQk5ODoqLi1FUVASNRsPc6+4wENOvS5cuobGxEcPDwxAIBJSXFRUV8z7mTE9Po7W1FZcuXUJzczOMRiPlZm5uLq1hMOf+wkEgEIDJZEJbWxvN8TscDvB4PFRVVaG8vBxlZWU329Nyexp6Cfx+P5xOJ4aHh3H+/HmcPn0afX19SEpKQllZGaqrq1FYWAgulws2mw0Wi4Xo6Oh5fZAsRJDJLDJd2NvbSx0ZHA4HMjMzUVpaimXLlkGhUEAkEs2LyYgbBZlmdzgcMJvNOHv2LFpaWtDV1YVAIICsrCyawMvKykJiYiJYLBZYLNZtd7lkcP0ItzknvHY4HGhtbaWNZTabDXK5HHl5eaioqEBBQQEEAgH4fP68cF/4svD7/XA4HLDZbDh//jzq6+vR2dkJv9+PzMxMVFdXo7S0FMnJyUhMTERiYiISEhKYBO88Qjh3vV4vxsbGcOnSJZq4DQaDyMrKQmVlJSoqKqhz0nxxYLheEHe+cI1w/vx5dHV1ITo6GoWFhbRxQyaTUb7eiWfPQkYwGIzgq8lkQlNTE86dO4fe3l5ERUUhPz+fFoVFIhFEItEdF2eJo6vVakVnZyedvHO73dBoNKioqEB1dTWUSiXYbDbD1dsI4gJDOGm1WnHhwgU0NDSgra0N8fHxKC4uxuLFi1FYWAipVAoul3tHFoyIQ8/o6Ci6urpw5swZtLW1YWxsDDKZDEVFRSgvL0dubi4EAgHVtAw37wwEg0H4fD6qZS0WC9ra2nDx4kV0dnbC6/UiJSUFRUVFWLRoEVJTUyEUCu94R9tAIICJiQnYbDbqONzc3Ayz2QyhUIjCwkKUlZWhoKAAQqGQ3tfuNB10tyJcNxB30Pb2djQ0NNAGheTkZOoSmpmZCaFQeMfGaeDzc8ntdmNsbIy6tra2tmJ0dJQ2fVZUVCArKwtcLhcsFmteOPgw+CfIvWVychJerxcTExNob2+nDdtjY2NQKBSoqKhAVVUVMjMzIRKJwOFw7rh4TO6idrsdg4ODOHfuHM6fPw+9Xg8Wi4X8/HyUl5ejtLQUYrGY5nGZGDw/QXQx4e74+Di6urpw4cIFtLS0UM1YUlKCmpoayt07PeaSLQA2mw2dnZ04f/48HazgcrnIzc1FaWkpCgsLaa6B8JhxfLozEZ4HnpycxOTkJN0EQRpuTCYTEhMTodVqUVBQgKqqKkgkEqon79TnPRgMwu12U0316aef0uYi0vRZXhpIs3sAAB89SURBVF6OrKwsJCUlMTpjHmKmznC5XGhra6NDvHa7HSqViuqMjIwMqjPuRN6SzYMulwt2ux0tLS20OT38XCopKUFBQQG4XC6N00wuY/6DxOPwXIbVakVzczNtGpycnER6ejry8/NpLkMgEIDH491x2pmA/M52u51up2tsbERfXx8SEhKg1WpRVVWFoqIiSKXSiLocw+n5BxKXSW6Z3P8aGxvR2NgIq9UKhUJBB+pzc3PB5/PB4/HuyPPV7/fDbrfDYrHg7NmzOHv2LHp7exEfH4+CggI66CcSiWg8Zlx8by9mctThcKCpqYnmKHw+H3JyclBWVoba2lrI5XIIhcI77nkLz0/o9XqcPXsW9fX1MBqNEIvF1DQoLy8PHA6H6TObBwjXAB6PByaTCZcuXcKZM2cwMDCAxMREFBYW0s1QQqEQfD7/jjv/w517jUYjTp06hebmZuh0OiQmJiI/Px9VVVUoLCyERCKhdzDm3J+fmBlTXS4XWltbI4bfVSoVSkpKUFVVBY1GQ8/9WeLu7W3opd8o7Oe4XC5cunQJFy5cQHt7O0ZGRsBisSAWi6ljanJyMlQqFRQKBeLj42frYTDAP0lptVphNBphMBgwODiIjo4OjI2Nwev1QiAQID8/nzb/icVi+vULJdCEc3Jqago6nY521uv1ejgcDiQmJoLL5SIlJQWZmZlQKpWQyWRQKpW0IWmh/D3uZJAiqdlsxsjICCwWC4aGhqDT6WCxWODxeBAMBqFSqaDRaFBaWoqCggLIZLKI528hPZfh/J6enkZnZyeam5tx6dIl6PV6TE1Ngc1mQyaTITc3F2q1msZcuVzOJMhuIfx+P8bGxmA0GjEyMgKDwYCenh4MDw/D5XIhKioKqampyM/Pp83n4Q6SC+F5Cuer1+ulRbf29nYMDAwgGAwiKSkJSqUS2dnZSE1NhUKhgEqlgkQiueOaQ+9kTE1NwWw2w2w2Y3h4GENDQ+jp6cHIyAg8Hg9iY2ORmpqKsrIylJSUIC8vL0LH3el8DedqIBCATqej7uh9fX2Ynp4Gl8tFcnIycnNzkZqaCqVSCbVafUdeTO8EELclg8GAkZERDA4Oore3F3q9Hi6XCwCQnp5Omx41Gs2C4iQQyUvi2k82U3R0dMBqtSIuLg5sNhsqlQrZ2dlQKpVQKpWQy+WQyWTM5pR5AJfLBbPZDIvFguHhYRiNRvT09GB0dBRerxfR0dFQqVR0201RURF4PF7E91gIfCaYmacYGxujdzWSQ4iOjgaHw4FMJoNGo0FycjIUCgUUCgVkMtkd4VS10OHxeC7jdV9fH0ZGRuD1ehEKhaBQKOiWlMLCwojcA7BweT00NITm5mY0NDSgq6sLTqcTLBaLOlOnpaVBpVJBpVIxK7RvMYLBIMbHx2EymWAymTA8PIze3l4MDg7C4XBgamoKUqmUNgWWl5dDIpEsuNxCOF/J6kuiL4j7GIfDgVwuR05ODpKTk6m+kEqlTE7hFoOs0bXZbBgZGcHw8DBGRkbQ09ODoaEhuFwuTE9PQyKRIC8vjw5+yWSyiO+zkJ6zmVqCNI51dHSgra0NRqMR09PTSExMBI/HQ1ZWFtRqNc39ymQySCQSxvlpHoLcAS0WC0ZGRugq4f7+fpjNZrjdbvj9fkilUmRkZNDGwJnOnwuJ70Ak5wcHB9HU1ISGhgb09PTA6XQiMTExQmeEa2dmS9atA9EZJE4bjUaqM5xOJ6ampmi+vqysDGVlZZBIJBHfY6E8VzNzGWazGU1NTWhqakJPTw/MZjNiY2ORlJQEhUIBjUZDtTGjN+YHSF1uZGSE1uYGBweh0+lgtVppLkOtViMvLw9lZWXIy8uLcOBdaM9fOK89Hg9tCGlqasLw8DCCwSDYbDblNOmFkMvlkMvlTH7uNiAQCMBut2N4eBhmsxlGoxE6nQ4DAwNwuVw0Lms0GpSVlaG0tHRB1pZncrepqQmNjY1oamqCyWRCdHQ0eDweUlNTkZubC6VSSfnL5XKZusccIhQKReQohoaG0N/fj76+PnrPU6lUdGiNGCkS3On8vFKO+OLFi2hoaEBnZydGR0eRmJgIkUiE7OxsZGZm0nyaUqlk4uocIhgMYmxsDCaTCQaDAUajEZ2dnRgeHobb7UZcXBzS09Ope7lGo1lw97Fwfk5MTNBt8S0tLRgeHkYoFIqoy5GcAzn3mT7IWw8yyELOfYPBAJ1Oh8HBQRpTiU4rLy9HSUnJXOd950dD79VAnLPGxsZgMBjQ1taG3t5eDA8Pw+PxQCAQ0Gm9zMxMZGVlQSqVIiYmBtHR0fR9VFTUgnjR3yzIBGQwGEQgEKDvyfRKd3c3enp60N3dDbvdjoSEBCiVSqSlpVHXTpKwZLPZd+XflKxkttlsdCqtt7cXvb29NEno9/vB4/GQnp6O9PR0ZGZmIiUlBWq1mrqwzHwDFsbBdKsQzuXwt0AgQBO1er0eer0efX19MJvN8Hq94PP5kEqlSElJoc1UxBHyTpxAm20EAgE4nU6MjY1hdHQUQ0NDaGlpgdFohMlkgtfrpdzOysqCRqNBamoq1Go14uPjL+M1E3uvDHK2hvM2GAxienoao6Oj0Ol06O/vR29vL/r6+mC32xETEwOZTAa1Wo38/HxkZGRAKpXesY6mswEiqghfdTodOjs7MTQ0BLPZDL/fD4FAgIyMDOTk5NB4LJPJEBcXF6ETmDh8dYTzlXCV8NVoNGJwcBB9fX3o7u7GwMAAHA4HWCwWFAoFkpOTaWFMLBZDIpGAz+ffdUVPorXGxsZgNpvR19eHtrY2GAwGWCwWxMbGQiqVQqvVQqPRICsrC+np6WCz2RGalsRUhqdX5+Xk5CQGBgbQ39+P7u5udHV1wWQywefzQSwWQ61WIzc3F1qtFnK5HBKJBCKR6K7jJBDpEDI2NoaxsTH09/ejo6ODFlomJyfB4/GgVquRlZVFNW1qaiqjaW8SRMuG69lAIIBAIACHwwG9Xo+hoSH09vaiv7+fNjjyeLyI+JqcnAyRSASxWAyBQHDXO8cRt0G73Q6bzYbR0VEMDg6ivb0dJpOJNnFwOByo1WpkZGQgKysLqampSElJocMVDK+/HGZq3HBuj4+PY2BggBZw+/r6YDKZ6PNBeK3VapGWlhbB67v5jkaK4DabDVarFRaLhQ4ZDw8PU92lUqmQlZWFnJwcpKWlIS0tjTpyh+tdRkdcHVfLlzmdzgjednd3w2Kx0MZd0rCam5tLN1YRd9q7EeEx2Gq1YmhoCK2trTQRHp5TyMzMpAOZarWaOqAyOYXrx9VyC4FAIKJppq+vDzqdDmNjYwAAmUwGuVwOrVaL7OxsyGQyiMViiESiu37ghbhDOp1OymWLxYKOjg4MDQ1hZGQEY2NjCIVCEAgEUKvVtPBGmiCTkpKuyuW7+W/7ZUF4PjMPHAgEMD09TZseSR64v78fVqsVk5OTNA+cnJyMnJwcpKamUn3B8D1yU8Do6CjMZnOEziCNvlfSGeQ+yOiM68PV6hhOp5PylugMq9VKhyyUSiVycnKQk5MDuVwOsVgMsVh816/qJds87HY7rFYr9Ho9bRAhjaJcLhepqakRdz61Wk018pXqGAyuD8Fg8Kp15sHBQZqX6+npoYY6AoEAMpmMNvuRLUIkJt+NeTmC8E2Fo6OjsNls6O/vR3t7O23uJxo6JSWF5o5JHoPR0DeOq2lov9+P0dFR9Pf307jc19cHm82GUCgEiURCjaFycnIgk8no/e9u1BQkB0fyb2azGd3d3XTQ3mq1Ij4+HkqlErm5udS0LyUlBRwOh+HtF+BKfRCBQABerxd6vR4DAwPo6uqiBlCk/pGcnIzs7GwUFBRAKpVCIpFALBbfdUMuZKvm6OhoRJ+ZTqeDyWTCxMQEbULPy8tDRkYGsrOzoVAoEBsbexk/ASY3THClmkYwGITT6cTAwAB6enrQ29tLdS0AasJVVFSEzMxMSKVSSKVSmou/m/625Nx3OBz03NfpdOjo6KDmblNTU+Dz+fTcz8zMRFpaGu3HYeLnjSG8Fjezz8FqtaK/vx96vT6iLycqKgoSiQTJycn03Cd9OWKx+FY6Ks/vhl76g65QGHI4HOjo6EB3dzc6OjpgMBjgcDgQCoXoRUAikSAlJQVyuRw8Hg9cLhdJSUng8XjUXn2hFYfCbZ8nJibgcrkwMTGB8fFxTExMRDgx2O122O122oBKgkJeXh60Wi0kEsllSRkGkbiSoCIvfFKAHxgYgM1mg9vtBovFApfLhUAggFAopM4OAoEASUlJYLPZ9D2Hw6ErKu62QBy+TsrtdsPj8WBiYgIejwdutxsulws2m40maRwOB8bHxzE+Po7o6GgkJSVBpVIhLS2NTlyR5qioqChGgF0nZnLb4XDQxn/Cb4fDgcnJSSQlJUEoFEIoFEIul9MGExJ3yRuJvQv98hC+1t3j8cDlcsHtdmNiYoIOBZhMJloMcjqdcDqdiImJoSItOzubXnQVCgVt0mHE2eW4UmOU2Wyml4aenh4YDIaIM4/EYTKJSVbShXOWxOGFphVmgqyn8Xq9ETwlOoJMo5lMJjgcDthsNkxMTCAhIQF8Ph9paWnQaDTIzs6GVqulTWWMfrgcM3nq9/uh1+vR09ODjo4O9Pb20oYzsqFCIBDQqWGJRBKhZ8N5uhAb+UiSiuiA8fFxuN1ujI+Pw263w2AwwGQywWazYWxsDG63G2w2GxKJBFlZWcjLy0NOTg6ysrIiBk+YGHo5wrlJ3jscDnqJ1el00Ol0sNvtdIJaIBCAz+dDJBJBpVJRTcvhcMDhcCg/ORzOXblyOxAIRKz1dbvdNMaSBj2z2UxjK9GzAMDj8SCRSKiOzc7ORkZGBl35y8TX68OV8ggul4s2/ZPhv9HRUUxMTCA2NhZ8Ph8CgYDGXrlcTu9qhNfhd7WEhIS7ymkkGAzS9WiE0+G8ttvtGBkZwcjICGw2G8bHx+FwOBAIBMDlciGRSCI4nZ2dfdmAAMDc0a6GmXGaFHI6OzvR19eH3t5eWK1WuN1uxMfHU71LEpAymYzqh3C9S+L0QufyTF0RrnudTifdMjE6Okrjst/vp85vmZmZyM3NRXZ2NtLT0xlt8QW4Ugy22+30jkYGWe12O7xeLzgcDvh8PoRCIaRSKVQqFaRSKdW+4dqCrMu8E9fW3iiCwSCmpqbg8Xgodwl/yV3NaDTCbDbDbrfT3EJsbCzN9WZmZtICBClQMty9fsyMvYFAABaLBX19fVRLGAwGmvsleoLkHWQyGW34JzGXaInw3O9CzztcC0Q3+3y+iPwvyQmTJqfh4eEInrvdbiQkJIDL5UKlUtFhgaysLKSkpFymnQFGY1wLM7nu8XjQ39+Prq4uqjOIbmaxWBE6Q61WQyqVRuQpuFzuZSuOFzKupDNIPtjpdGJkZAQmkwlWq5UODRCNTHSGVqulQ97EjICJ1dfGlXIZdrud3vlIYx7JGbFYrMvywuH1Y1KfI9y9G1cgBwIB+Hy+CO0RfvcbGxujrrvhMRkA5XNaWhpycnKQkZGBzMxMJh7fIGbW5ZxOJ7q7u6m5lF6vh91uh8fjQWJiIoRCIQQCAR1ikUgktA9iZl3ublk5H77aPTxnQeIy4THJXTidTlpf5vP5UKvVyMzMpHlltVrNDLF8AWbWPXw+H2067ezshE6no3UPNptN47BCoaCOlBwOh3I3XEcsVJ1M6sgk3pKeHlIHsdlsGBoagsVioYMsHo8HSUlJEIvFyMnJoTW5jIwMmqNkOBqJK+UmxsfHaUN0R0cHBgcHYbfbMT09TesdIpEIarUaCoUCQqGQxlOSoyA6YSFq3PCacXi/GXlPHMstFgvtN5uamqL3MsJLrVYLpVJJX8MMNy/Hlfob7HY7urq6oNPp0NPTg4GBAZo7Y7PZEAqF4PP5kMvltG4cfu6T9yTXcLec++G1uPC8r9vtxujo6BXP/djYWAgEAjoMQQankpOT50vT9J3R0Hs9mJ6epu5SY2NjsFqtsFqtMBqNGB0dhdvthtfrhdfrxfT0NL2Y8Xg86kJAJlx5PB74fD4Nylwu95ruh7P55F3rbx4IBOByueByuWiDrtPppE0MY2NjsNlscDgclKAxMTH0QGGz2ZBKpXRdEvl9iTvZ3XYxvVUIBoNwu91wOBy0cY8ILzKl5nK5aJCZnJzE1NQUWCwW2Gw2FbaksEGKzHw+/7JmiaSkpC906pzL5/ha/CUCnlyYwsWpw+GgiSzyscvlogncUChEG0FYLBa9pCoUCspfIv5FIhH4fP6CbxidDyBuWyT2kFhE1uY6nU54PB5MTk5eFns5HA4VxMQZQyAQRFzWiDi+VpFuLp7jL+Kx1+ulMZhwOPx1TeIw+T9utxsxMTGUu2SNHVmZIJFI6CAK4fDdPJU+VyCOvsSNkvCVJCBJczrhayAQoLE1PNFLHL1nXuC4XC5tqrwabgdfwxtzwxshSWMu4Wx4cjYuLo4KfTabDT6fD4VCEeEGQjjL4/EYvs4iiEMOmcwkE8RkAIAkbYimBUDPf4FAQJ8bElf4fD7lJ4mrt5KjV+Mn0UbhsZTogLGxMdjtdoyOjlI9MDExQbVAeBwlq5vD9axUKqWOKwxmF6SoS8458lyRIRVS3PV6vTSe+v1+2qjA5XKpniUNk0KhMCIJxuPxrisZNlca7wvuvwgEApc155IkK2n+mqkDPB4PfD4f1bHkjRRbSFIw/HwRCoXM3ewWIRQKwev10jORcNput9OCu8vlgtfrpcUgsoKb6NrwuxrhNdG04UWI26ETwn/Pq4HohZnNBy6XCw6Hg+oGu90eoW8nJycRHx8fwWsej0edH8Md8AivSSGXwdyAOJCQ/FD4NgvSqBp+P/P5fIiNjaUcJfwNd8sijTlES3A4nGuuJLzVepcUGQg3wxt0STwmd9Vw/vr9/ghdweFwKHdlMhn9GxD+MtydG5BCGnmOCGetVitNshPtS5r9yHptktMlOaArcTY8X3Yt3GreAoDP56NaInxojWji8Dfy/7xeb0TcJZpYoVBEuOyG51piY2MZ7t4CkHtc+JlJ3hOHdafTGZH7nZycRHR0NNUIRFPweLyI/C+JveFvbDb7C+/ht0tXEJBaDInLXq+X1jRI7pfoZ5KvIK91kpMg+jkpKQkikQhKpTJCLxP9RfISDNfnFuGbA8LzakRnjI2NRegMohVJzA7XGSRGkfpGeM7iWqtlb4fO8Pl8NE6H5y9IIZhoLtJkPjExgWAwSOM04TC5+0ml0oi8DeMWPfeYWZ8L14ekPkfilM/nw+TkJK1jkLgbHnNm5jJIXObxeF/YvH47cxnhOQxSmyMxmfCZ3PnI/52amkJCQgISEhIonwUCAeRyOaRSacSdj7yumVzG3IMMK4fn5chWAbPZTIeMZsZjwtVwHoe/J/Ga8PmL7kC3Q0NPTU1F1DrCc3KEx+QeSGrMHo8H8fHxETwWCoURuYvw+hzZ5spgdkE2IJO8f7izr9lsxujoKK15hMdhcu8TCAQRZyfRySQWk/rc1XAr+Ur0A8lNzNQP4XU5oh/IYCDhKMnREBON8PoH2aTN1D9mD8QxNbzXjGhci8WC8fFxGlO9Xi/NpRGNS/rMCDeJ6Un4UP2t1AfXiqWTk5MRdTmS/yW8JEPu4dyMj4+n+bPExESqa8NrxuT1yeTPZh+kR/B6zn3ylpCQQLXslc590gtJtCzRsfPp3Cc535nnPjF+nFmPIznfmbkzFosFkUh0zXN/Hvc5LJyG3iuBTM37/X76RiZlrVYrzGZzRGAmb+Pj4/D5fBGWyyT5QAJWXFwcFYDx8fGIj4+niaPw4kZ0dHTEv6emphAIBCL+HT6t5PP5MDU1hampKfrx5OQkTYZERUXRKbD4+HiavCbBkpBRLBZDqVQiMTERsbGx1B6efMxMP9x+EFtv8kb4SVaGhTdph1+oSXByOp206Szc1j4uLo42YRGexsfH04/j4uIQFxdHeUm4RBAVFYW4uLiIYvNM3hIxCvyzUXdqagrT09OYnp6mHxMukwIMAMrfqKgo+roKd3gjQocUzmQyGW1AIhwO/5jh8vwCmSAifA7n9eTkJEZHR+nEFuE3KVKRS3b4qqbwBi4WixXBZxJ/w/lMYhxBTExMBL+np6fh9/vpv4nbDXGFDo+95N/k8kjEEAA6kUMuWOETe4S7RMDKZDKw2ewI/pLHeTdMRc1nhPM1nKvE6d5isWB0dJReYMIv22Qazu/30xgMAAkJCeBwOFQshsfc8Bh8pVgbGxsbkSyaGXvJ4wQ+LwCHx1nyRpyhSeKDTD2SuEnEe3gRhbzJZDJIpVIkJCREcJW8Z/h6exDuBBWuaf1+PyYmJmCxWChXw4e8SBJ+eno6YvUNaVohOjacmyTOhmtNgi/StNPT0/RnhMfScF1LGhfCYynhJilcEz1LEgDE0YoM2IXHUIaX8wNE086Mo8TVxWq10tXbM/UsGSjw+XwRPAVAnUPCORquAwhniRac2WBGuPz/tXc/S010TRyAT/irUpYLtLz/a/luRgsX6iIFhsC7+o09nUnEbwEIz1OVCoFNFk1PT58+Z6LHbGJ1jDFd8/v1//b2dpZXb25uZjtzs3ny/fv3s4ZIfq6N1p5X5dbnrd6r9djebDbThotv377NhnbSnM+GzXqfNsaY6tpexyamk5vT5H3z5s3se52ens5q3V7bptGV71/jOnm4xnjiup6WdHR0NA3h14GZy8vL6T11bv7Pemy/xFPj/2W1jqjvm81mfP/+feqN1UWlDDuklqh9h9wD5ckrvdatcbyUn2uDON+jPlK9x/BS3Zthi/V6Pbbb7ey0pPPz86lXVhdWcvJrHuvXe2V5H8OJYU8pJ5Ms1RWbzWY6TbnGbB3QyUJbrStWq9W08FT7uDUH53djjJ37tF4H51pQv3PvK9T7s/o5pzdut9tZ3j07O5s90avfr6XXm8cqu1f7N/R7udoHzkax1Mr1kIPcyyWmUyvXV90sVmP45ORk9nNqiaV83Htm6fFWtQ+RuiN5OfGd3yXGr6+vx/39/SzGM4zfB5bzqotq+R/sL0O7z1PtA9dY//Xr13Qyba8z6ibIpTojmzxrrk6v6lCdkc8PqTOSy/fVGcnXd3d3O3VGXceofbX0gT98+LCTp9UZz89SLyOf08vI/V5dn0u+/vnz52x9t97zXVxcTD2Lmpdrvt5XK/dexr71jDHGYhzX9zwBc7PZ7NzzZWizHraSXsbl5eU0fF57cXoZz9u+dbkcdHJ1dTX1jesATGK61hvb7XasVqtprbnOQzx0reP4+Hh2smqvoccYU484PcS6zpx1uZxgmrWYGsenp6dTDV3zcjZOJJbV0M9TvffrsXt9fT2+fv06y8V5z+v6+nq2nlw3yy3Fa+I4szZ1La7XxfvW5vKY9r720euHfJ/UEG/fvp0OGax17+Xl5bQul5meuv5RZyp4XL1OSAykL/Hly5epP1wPPUuNkBycpwjUk//7+vGf1uXqIXY9l6beHWPM8mYOEKyzOr2Hdnx8PM7Pz2e9h48fP04HkXz69Gl8/vx5yqG9j2ZG5+n03ll/z6aJxGjf+PLjx4/F6376vYnLv5lx+Jvr/lLvbOm633tnue7nWr/vup//pxdQv77sgd7/V38UQ04TzY7EBFMdVsgAcE2aY4ydz33YLMM7GW6sTbj8XE9qrbvx7XQkp4XmVU/t6xftJM16Q5THOdSidIzfyTR6YTvG2GmcJYHXweG8p0jJRSDDmWKY7u7ublqYra96wvrSAGOasWmiRV14GGM3lnPxz+LCvsXos7OzKQ8njh9y0hovW32cXuI0J4v34jNDNGnC5sa/xmvPx0vxmhu3mmN7zGZYKDGb12t5LC2/5TEjicvUs+v1ejZkmzyamE0D+FBN2+OzDtj2TW/1c320bE6GePfunXrgFUs9moWmXtcuXfNrbh1juTlwc3Mz2+F7qJ5N3NYhiLpgnGGJWgskz/6DTQAeQRpqNZZrjPchxcR04roOM1a91u1N3jF+LwDX+7STk5OdxtuhuDaQS+QeK7VEjen1er2zUFA/j7Gbn+sAwhhj6oUl3lar1aymWNrImXxdYza1xUt+HCcPk/zb79H21RU1F9/e3j6or7CUe5dqijq0k8/1Pq3Gr6dMcUjyau351hN4ag2R+qEO3Kau6PVy70H0nDzGvA+Rerr3fVNnJMYT2zkV6DU+sp6H+VOdUXP1Up1xaNBxjOU6IwvPNV8vveo6RnoXOehHLBPZyJC15OTo1Mk1R/eeRh0sj/RHah3S15QT1/vqjrpGV59IUeuPDBpDlQGaPK669udqD6PORySGH1JDLw2w9xq69uJqbPeexcXFxdTTkJNfrzr0lbWP2nfrB+jVnluvg3u8Lh0elbXkuna81Keoa3J57L2Naa9LZh0Sl1mXy8EKvS/8N+tyhwZ+a96sM2c5oTz5s8aoE8lfr6U6tvbOlq77h2Yc/tQ7W6ph64xZ3XDf69dX3Fcw0AsAAAAAAAAAAAAAT+jgQO/RI34RAAAAAAAAAAAAAKD50/M2/vco3wIAAAAAAAAAAAAAXq6rQ39c3d/fP9YXAQAAAAAAAAAAAACao6f+AgAAAAAAAAAAAADwmhnoBQAAAAAAAAAAAIAnZKAXAAAAAAAAAAAAAJ6QgV4AAAAAAAAAAAAAeEIGegEAAAAAAAAAAADgCRnoBQAAAAAAAAAAAIAn9B+YpTCMLsDhcQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت recall و precision را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "e4YYmF5MJ6wH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def print_recall_precision(y_test, y_pred):\n",
        "  precision, recall, _ = precision_recall_curve(y_test, y_pred)\n",
        "  print(precision, recall)\n",
        "\n",
        "print_recall_precision(y_test, y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dQL7K-A3euGS",
        "outputId": "55ee4cd1-4a18-4296-d7a8-b20dd0eef60d"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.49636929 0.72281856 1.        ] [1.         0.79319844 0.        ]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Set Hyperparameters"
      ],
      "metadata": {
        "id": "I_CzlBlvfCKT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت به کمک GridSearchCV کار Parameter Tuning را انجام میدهیم. یعنی چهار پارامتر learning_rate, max_depth, n_estimators, colsample_bytree را با مقادیر مختلف تست میکنیم تا ببینیم به ازای کدوم عملکرد مدل بهتر است.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "N1aAVHp4KG02"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_roc_auc_score(model, x, y):\n",
        "  return roc_auc_score(y, model.predict_proba(x)[:, 1])\n",
        "\n",
        "parameters = {'learning_rate': [0.02, 0.05, 0.1, 0.3],\n",
        "              'max_depth': [2, 3, 4],\n",
        "              'n_estimators': [100, 200, 300],\n",
        "              'colsample_bytree': [0.8, 1]}\n",
        "\n",
        "clf = GridSearchCV(model, parameters,\n",
        "                   cv=3, \n",
        "                   scoring=my_roc_auc_score)\n",
        "clf.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mYmj4Y3jfK8Z",
        "outputId": "674491af-701b-4f68-84fe-566b6fda6eb7"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GridSearchCV(cv=3,\n",
              "             estimator=XGBClassifier(early_stopping_rounds=10,\n",
              "                                     eval_metric='auc', max_depth=4,\n",
              "                                     n_estimators=200, random_seed=123,\n",
              "                                     random_state=123, subsample=0.5),\n",
              "             param_grid={'colsample_bytree': [0.8, 1],\n",
              "                         'learning_rate': [0.02, 0.05, 0.1, 0.3],\n",
              "                         'max_depth': [2, 3, 4],\n",
              "                         'n_estimators': [100, 200, 300]},\n",
              "             scoring=<function my_roc_auc_score at 0x7fa50ce0f7a0>)"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت بهترین پارامتر هارا که از GridSearchCV بدست آورده ایم را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "XtwZBl9qKjoG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "best_parameters = clf.best_params_\n",
        "best_score = clf.best_score_\n",
        "print('best score:', best_score)\n",
        "for param_name in sorted(best_parameters.keys()):\n",
        "    print(\"%s: %r\" % (param_name, best_parameters[param_name]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g3fPCh92-Vwa",
        "outputId": "2939e1c7-8f5d-42a1-b477-8f02a559c94d"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "best score: 0.8174449324727447\n",
            "colsample_bytree: 0.8\n",
            "learning_rate: 0.05\n",
            "max_depth: 4\n",
            "n_estimators: 200\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت دقت مدل را بر اساس بهترین پارامتر های بدست آمده بدست می آوریم که مشاهده میکنیم دقت آن نسبت به حالت قبل کمی افزایش یافته است.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "It-901N2Kt-E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = clf.predict(X_test)\n",
        "\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "accuracy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K3z7Our0_EqB",
        "outputId": "68ed5c77-b675-410a-bc26-8aaa748f50a7"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.7464635986420218"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت نیز ماتریس درهم ریختگی را چاپ و آن را رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "9hI8Qj9RK392"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plot_confusion_matrix(y_test, y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 686
        },
        "id": "Yn9hr6uuAuP5",
        "outputId": "d8d4b7d2-efea-48c8-8db9-064866fdb6c1"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[7433 3248]\n",
            " [2129 8398]]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت درخت تصمیم بدست آمده را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "o3INT0vOK9mu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "rcParams['figure.figsize'] = 50,20\n",
        "plot_tree(model)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        },
        "id": "kaB0U-IyHcuP",
        "outputId": "1b0a140e-ce41-47ba-f5a7-65c334a48cf2"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 3600x1440 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت recall و precision را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "Dq65WlMkLJiG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print_recall_precision(y_test, y_pred)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "El6V0QXUA1DK",
        "outputId": "d5299526-6d24-4405-b09f-135e62953d12"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.49636929 0.72110596 1.        ] [1.         0.79775815 0.        ]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Plot Metric Changes"
      ],
      "metadata": {
        "id": "SjK_X2SwFoBZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت نتایج بدست آمده از Parameter Tuning را چاپ میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "B0B0-1LFL_hH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "clf.cv_results_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U7wiptNQFuW4",
        "outputId": "e0b87cf2-6a51-4f79-feec-bb8558ba5161"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'mean_fit_time': array([ 6.10543187,  6.54072618, 10.40146359,  4.50428279, 10.42788688,\n",
              "        15.00214609,  6.53325923, 12.16931335, 17.23256493,  3.5642062 ,\n",
              "         6.76341844,  9.75688195,  4.48218028, 10.14894342, 14.4548258 ,\n",
              "         6.75377369, 11.44320099, 18.88907838,  3.31934516,  7.1946036 ,\n",
              "        12.06807812,  4.45929869,  8.81118409, 13.36486983,  5.70592705,\n",
              "        11.57264256, 17.14989026,  3.29925013,  6.50032663,  9.67085663,\n",
              "         4.67276017,  9.03345998, 13.14862347,  5.72207991, 11.27198521,\n",
              "        17.09480572,  3.8427159 ,  7.54277992, 11.15741277,  5.21592379,\n",
              "        10.29707972, 15.62189102,  6.77137891, 13.35018055, 20.13372095,\n",
              "         3.78389978,  7.48126268, 11.13555137,  5.2208306 , 10.24976786,\n",
              "        15.57907041,  6.716959  , 13.26170071, 20.04331199,  3.77513329,\n",
              "         7.42376018, 11.16591271,  5.21769563, 10.53051337, 15.38838466,\n",
              "         6.73004619, 13.26750755, 20.01857678,  3.77900235,  7.45566058,\n",
              "        11.13131897,  5.18309108, 10.52216379, 15.31948582,  6.68165223,\n",
              "        13.28748488, 20.01110029]),\n",
              " 'mean_score_time': array([0.06386097, 0.0798316 , 0.18081125, 0.05792912, 0.13134265,\n",
              "        0.21021899, 0.07631302, 0.16470186, 0.21737583, 0.04932372,\n",
              "        0.09802787, 0.11899614, 0.06415621, 0.19233147, 0.16151643,\n",
              "        0.09801022, 0.1469845 , 0.21017249, 0.05089974, 0.08455531,\n",
              "        0.13434672, 0.06479971, 0.11611255, 0.16347384, 0.07961957,\n",
              "        0.14537112, 0.21035139, 0.04913831, 0.08185871, 0.11855737,\n",
              "        0.06341203, 0.11336295, 0.1626904 , 0.08086117, 0.14309168,\n",
              "        0.20655004, 0.04497552, 0.08192476, 0.11934582, 0.05805421,\n",
              "        0.11093783, 0.16795985, 0.07389696, 0.14614964, 0.2161746 ,\n",
              "        0.04981327, 0.08716162, 0.1224908 , 0.06722752, 0.11573354,\n",
              "        0.16495554, 0.0841879 , 0.15129336, 0.21237342, 0.05179516,\n",
              "        0.08656796, 0.11919014, 0.06737645, 0.11568801, 0.16463621,\n",
              "        0.08331418, 0.14938108, 0.21532885, 0.04817001, 0.08258724,\n",
              "        0.11979159, 0.06189617, 0.11499564, 0.162769  , 0.08227666,\n",
              "        0.14780005, 0.21088131]),\n",
              " 'mean_test_score': array([0.79853118, 0.80848523, 0.81243508, 0.80572256, 0.81299917,\n",
              "        0.81539322, 0.80987376, 0.81529002, 0.81691018, 0.8109767 ,\n",
              "        0.8151812 , 0.81634279, 0.81456565, 0.81696901, 0.8173467 ,\n",
              "        0.81607349, 0.81744493, 0.8171963 , 0.81507513, 0.81647858,\n",
              "        0.81675468, 0.81681363, 0.81719665, 0.81698021, 0.81703297,\n",
              "        0.81631652, 0.81504797, 0.81629452, 0.81644511, 0.81610533,\n",
              "        0.81418139, 0.81195363, 0.81030507, 0.81134525, 0.8066913 ,\n",
              "        0.80342555, 0.79946034, 0.80876505, 0.81265652, 0.80559687,\n",
              "        0.81299157, 0.81540951, 0.80936014, 0.81514747, 0.81681335,\n",
              "        0.8109832 , 0.81528346, 0.81629624, 0.814491  , 0.81690426,\n",
              "        0.81710416, 0.81596503, 0.81723254, 0.81688719, 0.81513603,\n",
              "        0.8166512 , 0.81682487, 0.81668133, 0.81686632, 0.81638161,\n",
              "        0.81687772, 0.81577903, 0.81435321, 0.81628082, 0.81612378,\n",
              "        0.81565691, 0.81422246, 0.81239615, 0.81078364, 0.81113387,\n",
              "        0.80675628, 0.80302254]),\n",
              " 'param_colsample_bytree': masked_array(data=[0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,\n",
              "                    0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,\n",
              "                    0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8,\n",
              "                    0.8, 0.8, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
              "                    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
              "                    1, 1, 1, 1, 1],\n",
              "              mask=[False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False],\n",
              "        fill_value='?',\n",
              "             dtype=object),\n",
              " 'param_learning_rate': masked_array(data=[0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.02,\n",
              "                    0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05,\n",
              "                    0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.3, 0.3,\n",
              "                    0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.02, 0.02, 0.02,\n",
              "                    0.02, 0.02, 0.02, 0.02, 0.02, 0.02, 0.05, 0.05, 0.05,\n",
              "                    0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.1, 0.1, 0.1, 0.1,\n",
              "                    0.1, 0.1, 0.1, 0.1, 0.1, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3,\n",
              "                    0.3, 0.3, 0.3],\n",
              "              mask=[False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False],\n",
              "        fill_value='?',\n",
              "             dtype=object),\n",
              " 'param_max_depth': masked_array(data=[2, 2, 2, 3, 3, 3, 4, 4, 4, 2, 2, 2, 3, 3, 3, 4, 4, 4,\n",
              "                    2, 2, 2, 3, 3, 3, 4, 4, 4, 2, 2, 2, 3, 3, 3, 4, 4, 4,\n",
              "                    2, 2, 2, 3, 3, 3, 4, 4, 4, 2, 2, 2, 3, 3, 3, 4, 4, 4,\n",
              "                    2, 2, 2, 3, 3, 3, 4, 4, 4, 2, 2, 2, 3, 3, 3, 4, 4, 4],\n",
              "              mask=[False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False],\n",
              "        fill_value='?',\n",
              "             dtype=object),\n",
              " 'param_n_estimators': masked_array(data=[100, 200, 300, 100, 200, 300, 100, 200, 300, 100, 200,\n",
              "                    300, 100, 200, 300, 100, 200, 300, 100, 200, 300, 100,\n",
              "                    200, 300, 100, 200, 300, 100, 200, 300, 100, 200, 300,\n",
              "                    100, 200, 300, 100, 200, 300, 100, 200, 300, 100, 200,\n",
              "                    300, 100, 200, 300, 100, 200, 300, 100, 200, 300, 100,\n",
              "                    200, 300, 100, 200, 300, 100, 200, 300, 100, 200, 300,\n",
              "                    100, 200, 300, 100, 200, 300],\n",
              "              mask=[False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False,\n",
              "                    False, False, False, False, False, False, False, False],\n",
              "        fill_value='?',\n",
              "             dtype=object),\n",
              " 'params': [{'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 0.8,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.02,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.05,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.1,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 2,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 3,\n",
              "   'n_estimators': 300},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 100},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 200},\n",
              "  {'colsample_bytree': 1,\n",
              "   'learning_rate': 0.3,\n",
              "   'max_depth': 4,\n",
              "   'n_estimators': 300}],\n",
              " 'rank_test_score': array([72, 64, 52, 67, 49, 36, 61, 37, 10, 58, 39, 24, 44,  9,  2, 31,  1,\n",
              "         5, 42, 21, 18, 16,  4,  8,  7, 25, 43, 27, 22, 30, 48, 54, 60, 55,\n",
              "        66, 69, 71, 63, 51, 68, 50, 35, 62, 40, 17, 57, 38, 26, 45, 11,  6,\n",
              "        32,  3, 12, 41, 20, 15, 19, 14, 23, 13, 33, 46, 28, 29, 34, 47, 53,\n",
              "        59, 56, 65, 70], dtype=int32),\n",
              " 'split0_test_score': array([0.79933115, 0.80983282, 0.81422685, 0.80579925, 0.81446016,\n",
              "        0.81763245, 0.81025889, 0.81719524, 0.81942921, 0.81220599,\n",
              "        0.81753015, 0.81912605, 0.81641657, 0.81947157, 0.82017986,\n",
              "        0.81853741, 0.82043876, 0.82024542, 0.81726413, 0.81928506,\n",
              "        0.81980399, 0.81951579, 0.82027734, 0.82059835, 0.82018196,\n",
              "        0.81993451, 0.81881529, 0.81856876, 0.81876858, 0.81858428,\n",
              "        0.81687909, 0.81528224, 0.8140249 , 0.81421558, 0.80892822,\n",
              "        0.80603403, 0.80024056, 0.80987297, 0.81433516, 0.80620574,\n",
              "        0.81437668, 0.81761369, 0.81008752, 0.81719678, 0.81955741,\n",
              "        0.81245471, 0.8177005 , 0.81913892, 0.8164276 , 0.81964276,\n",
              "        0.8199587 , 0.81832319, 0.82008013, 0.81997277, 0.81763929,\n",
              "        0.81957948, 0.82006215, 0.81953771, 0.81963668, 0.8198531 ,\n",
              "        0.82011342, 0.81895557, 0.81804446, 0.81904056, 0.81816659,\n",
              "        0.81827826, 0.81774084, 0.81535701, 0.81482222, 0.81411215,\n",
              "        0.81004011, 0.80689832]),\n",
              " 'split1_test_score': array([0.79871321, 0.8084625 , 0.81199382, 0.80633377, 0.81266488,\n",
              "        0.81458493, 0.80988444, 0.81450819, 0.81582709, 0.81053148,\n",
              "        0.81407655, 0.8148911 , 0.81379061, 0.81585652, 0.81615305,\n",
              "        0.8149777 , 0.81610548, 0.81575183, 0.8143596 , 0.81527747,\n",
              "        0.81542455, 0.81556482, 0.81585272, 0.8155377 , 0.81515349,\n",
              "        0.81462101, 0.81353392, 0.81521136, 0.81522752, 0.81489073,\n",
              "        0.81259312, 0.81073415, 0.80853805, 0.81023721, 0.80671418,\n",
              "        0.80340543, 0.79926553, 0.80858001, 0.8120454 , 0.80594254,\n",
              "        0.81266785, 0.81463982, 0.80943655, 0.81449914, 0.81578091,\n",
              "        0.81074458, 0.81438885, 0.81505576, 0.81383114, 0.81564348,\n",
              "        0.81575315, 0.81481665, 0.81601361, 0.81558432, 0.81418703,\n",
              "        0.81532857, 0.81520947, 0.81568021, 0.8158568 , 0.81509107,\n",
              "        0.81525183, 0.8144258 , 0.81282919, 0.81502684, 0.81523736,\n",
              "        0.81415186, 0.81376721, 0.81194756, 0.80992949, 0.80964222,\n",
              "        0.80510151, 0.80070758]),\n",
              " 'split2_test_score': array([0.79754919, 0.80716038, 0.81108457, 0.80503465, 0.81187247,\n",
              "        0.81396226, 0.80947796, 0.81416665, 0.81547424, 0.81019262,\n",
              "        0.81393691, 0.81501123, 0.81348977, 0.81557894, 0.8157072 ,\n",
              "        0.81470536, 0.81579056, 0.81559165, 0.81360164, 0.81487322,\n",
              "        0.81503552, 0.81536027, 0.8154599 , 0.81480459, 0.81576346,\n",
              "        0.81439404, 0.81279471, 0.81510345, 0.81533923, 0.81484099,\n",
              "        0.81307197, 0.80984449, 0.80835227, 0.80958295, 0.80443151,\n",
              "        0.80083721, 0.79887493, 0.80784215, 0.811589  , 0.80464234,\n",
              "        0.8119302 , 0.81397502, 0.80855635, 0.81374648, 0.81510172,\n",
              "        0.80975031, 0.81376103, 0.81469403, 0.81321427, 0.81542655,\n",
              "        0.81560064, 0.81475525, 0.81560387, 0.81510448, 0.81358175,\n",
              "        0.81504556, 0.81520298, 0.81482607, 0.81510548, 0.81420067,\n",
              "        0.81526792, 0.81395571, 0.81218597, 0.81477506, 0.8149674 ,\n",
              "        0.81454061, 0.81115932, 0.80988389, 0.80759922, 0.80964723,\n",
              "        0.80512723, 0.80146171]),\n",
              " 'std_fit_time': array([1.66204776e+00, 4.06601480e-04, 7.18846426e-01, 1.08784923e-02,\n",
              "        1.34498254e+00, 7.13752175e-01, 1.02878662e+00, 7.14452151e-01,\n",
              "        2.87105885e-01, 3.06048690e-01, 1.29275199e-01, 5.05168287e-02,\n",
              "        5.81613382e-03, 1.47952009e+00, 1.87129306e+00, 5.69981266e-01,\n",
              "        1.15206676e-01, 5.88093450e-01, 8.19272653e-03, 9.91412023e-01,\n",
              "        1.75351299e+00, 1.89177477e-02, 2.56495314e-03, 3.53882210e-01,\n",
              "        1.22466651e-02, 3.12469082e-01, 2.65289135e-01, 1.10608933e-02,\n",
              "        3.34991530e-02, 2.51657032e-02, 2.85558712e-01, 3.38155604e-01,\n",
              "        2.64075686e-02, 7.58697724e-03, 1.83579699e-02, 3.43512568e-01,\n",
              "        8.15814072e-03, 1.40550452e-02, 2.81146883e-02, 1.70247343e-02,\n",
              "        1.08252571e-02, 3.15045791e-01, 1.84384445e-02, 3.70657545e-02,\n",
              "        3.81350190e-01, 3.08324915e-02, 1.64979172e-02, 1.83274806e-02,\n",
              "        2.56503927e-02, 1.14915768e-02, 3.15421765e-01, 8.53004437e-03,\n",
              "        3.34008105e-02, 3.49943567e-01, 1.37039637e-02, 1.35372201e-03,\n",
              "        3.26116593e-02, 1.78226392e-02, 3.30906952e-01, 6.76228033e-02,\n",
              "        1.13885975e-02, 3.24880202e-02, 3.53762214e-01, 1.88672611e-02,\n",
              "        9.69175625e-03, 1.90678362e-02, 1.87456105e-02, 3.26745566e-01,\n",
              "        4.99277122e-02, 1.97358001e-02, 2.53810324e-02, 3.08464138e-01]),\n",
              " 'std_score_time': array([0.01591467, 0.0010823 , 0.0869734 , 0.00061137, 0.02622213,\n",
              "        0.06566066, 0.00252935, 0.02211675, 0.00386061, 0.00034868,\n",
              "        0.01548173, 0.00043155, 0.00088318, 0.10963915, 0.0006159 ,\n",
              "        0.01210074, 0.00271614, 0.0028763 , 0.00052564, 0.00088978,\n",
              "        0.0170397 , 0.00113638, 0.00232943, 0.00031148, 0.00021637,\n",
              "        0.00077545, 0.00178564, 0.00204192, 0.00176228, 0.00622711,\n",
              "        0.00067966, 0.00129506, 0.00503603, 0.00110553, 0.00228403,\n",
              "        0.00011383, 0.00036899, 0.00185965, 0.00144117, 0.00092337,\n",
              "        0.00187663, 0.0010809 , 0.00044984, 0.00119533, 0.00511432,\n",
              "        0.00066517, 0.00223828, 0.00164008, 0.00208313, 0.00068678,\n",
              "        0.00225468, 0.00198056, 0.00265428, 0.00208021, 0.00054066,\n",
              "        0.00304461, 0.00149968, 0.00231182, 0.00146057, 0.00165742,\n",
              "        0.00251971, 0.00289905, 0.00192151, 0.00040003, 0.0018672 ,\n",
              "        0.00258856, 0.0017975 , 0.00110368, 0.00145242, 0.0017111 ,\n",
              "        0.00376078, 0.00185356]),\n",
              " 'std_test_score': array([0.00073878, 0.00109114, 0.00132023, 0.00053313, 0.00108254,\n",
              "        0.00160366, 0.0003189 , 0.00135439, 0.00178704, 0.00088018,\n",
              "        0.00166193, 0.00196867, 0.00131455, 0.0017732 , 0.00201159,\n",
              "        0.0017458 , 0.00212085, 0.00215705, 0.00157849, 0.00199133,\n",
              "        0.00216202, 0.00191254, 0.00218427, 0.00257586, 0.00224055,\n",
              "        0.00255999, 0.00268093, 0.00160873, 0.00164357, 0.00175299,\n",
              "        0.00191755, 0.00238154, 0.00263141, 0.00204713, 0.00183584,\n",
              "        0.00212164, 0.00057428, 0.00083934, 0.00120151, 0.00068345,\n",
              "        0.00102467, 0.00158205, 0.00062743, 0.00148131, 0.00196006,\n",
              "        0.00111689, 0.00172822, 0.0020155 , 0.00139235, 0.00193843,\n",
              "        0.00201943, 0.00166766, 0.00202049, 0.00219061, 0.00178724,\n",
              "        0.00207383, 0.00228911, 0.00204964, 0.00198281, 0.00248148,\n",
              "        0.00228799, 0.00225434, 0.00262329, 0.00195414, 0.00144868,\n",
              "        0.00186035, 0.00270611, 0.00225679, 0.00301   , 0.00210597,\n",
              "        0.00232204, 0.00275783])}"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    max_depth\n",
        "    و\n",
        "    learning_rate\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "qOw3u3LqMKDQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "max_depth = [2, 3, 4]\n",
        "score1 = []\n",
        "score2 = []\n",
        "score3 = []\n",
        "score4 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['n_estimators'] == 100 and res['colsample_bytree'] == 0.8 and res['learning_rate'] == 0.02:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['n_estimators'] == 100 and res['colsample_bytree'] == 0.8 and res['learning_rate'] == 0.05:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['n_estimators'] == 100 and res['colsample_bytree'] == 0.8 and res['learning_rate'] == 0.1:\n",
        "    score3.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['n_estimators'] == 100 and res['colsample_bytree'] == 0.8 and res['learning_rate'] == 0.3:\n",
        "    score4.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(max_depth, score1)\n",
        "plt.plot(max_depth, score2)\n",
        "plt.plot(max_depth, score3)\n",
        "plt.plot(max_depth, score4)\n",
        "plt.legend(['Learning_rate = 0.02', 'Learning_rate = 0.05', 'Learning_rate = 0.1', 'Learning_rate = 0.3'])\n",
        "plt.xlabel('Max Depth')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(max_depth)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "F7UZm00IJ1PX",
        "outputId": "db740364-73a2-437a-fe09-b3ded20dd80b"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    max_depth\n",
        "    و\n",
        "    n_estimators\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "C8yK2s6IMXM2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "max_depth = [2, 3, 4]\n",
        "score1 = []\n",
        "score2 = []\n",
        "score3 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['learning_rate'] == 0.02 and res['colsample_bytree'] == 0.8 and res['n_estimators'] == 100:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['learning_rate'] == 0.02 and res['colsample_bytree'] == 0.8 and res['n_estimators'] == 200:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['learning_rate'] == 0.02 and res['colsample_bytree'] == 0.8 and res['n_estimators'] == 300:\n",
        "    score3.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(max_depth, score1)\n",
        "plt.plot(max_depth, score2)\n",
        "plt.plot(max_depth, score3)\n",
        "plt.legend(['n_estimators = 100', 'n_estimators = 200', 'n_estimators = 300'])\n",
        "plt.xlabel('Max Depth')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(max_depth)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "pLxfNZ9_roqE",
        "outputId": "66794caa-4027-494c-ca11-65b888a3a744"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    max_depth\n",
        "    و\n",
        "    colsample_bytree\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "amewvh3kMdNm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "max_depth = [2, 3, 4]\n",
        "score1 = []\n",
        "score2 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['learning_rate'] == 0.02 and res['n_estimators'] == 100 and res['colsample_bytree'] == 0.8:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['learning_rate'] == 0.02 and res['n_estimators'] == 100 and res['colsample_bytree'] == 1:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(max_depth, score1)\n",
        "plt.plot(max_depth, score2)\n",
        "plt.legend(['colsample_bytree = 0.8', 'colsample_bytree = 1'])\n",
        "plt.xlabel('Max Depth')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(max_depth)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "vaf-UCoMsqxU",
        "outputId": "2081b1b1-69e0-4630-fef1-e59d52209619"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    learning_rate\n",
        "    و\n",
        "    n_estimators\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "PxgApaKSMg8f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "learning_rate = [0.02, 0.05, 0.1, 0.3]\n",
        "score1 = []\n",
        "score2 = []\n",
        "score3 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['colsample_bytree'] == 0.8 and res['max_depth'] == 2 and res['n_estimators'] == 100:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['colsample_bytree'] == 0.8 and res['max_depth'] == 2 and res['n_estimators'] == 200:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['colsample_bytree'] == 0.8 and res['max_depth'] == 2 and res['n_estimators'] == 300:\n",
        "    score3.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(learning_rate, score1)\n",
        "plt.plot(learning_rate, score2)\n",
        "plt.plot(learning_rate, score3)\n",
        "plt.legend(['n_estimators = 100', 'n_estimators = 200', 'n_estimators = 300'])\n",
        "plt.xlabel('Learning Rate')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(learning_rate)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "id": "PXVtT66AtdL7",
        "outputId": "70f0b9b3-dbea-4327-9332-0e85377e0fc8"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    learning_rate\n",
        "    و\n",
        "    colsample_bytree\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "ANcCFS63MrWF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "learning_rate = [0.02, 0.05, 0.1, 0.3]\n",
        "score1 = []\n",
        "score2 = []\n",
        "score3 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['n_estimators'] == 100 and res['max_depth'] == 2 and res['colsample_bytree'] == 0.8:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['n_estimators'] == 100 and res['max_depth'] == 2 and res['colsample_bytree'] == 1:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(learning_rate, score1)\n",
        "plt.plot(learning_rate, score2)\n",
        "plt.legend(['colsample_bytree = 0.8', 'colsample_bytree = 1'])\n",
        "plt.xlabel('Learning Rate')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(learning_rate)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "-wSS943yuRy7",
        "outputId": "415d6d07-b65d-4171-f182-d15f9c4b8996"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<div dir=rtl>\n",
        "  <font color=\"yellow\">\n",
        "    در این قسمت ارتباط بین \n",
        "    n_estimators\n",
        "    و\n",
        "    colsample_bytree\n",
        "    را نمایش و رسم میکنیم.\n",
        "  </font>\n",
        "</div>"
      ],
      "metadata": {
        "id": "GDtJaCvWMvsn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "n_estimators = [100, 200, 300]\n",
        "score1 = []\n",
        "score2 = []\n",
        "for index, res in enumerate(clf.cv_results_['params']):\n",
        "  if res['learning_rate'] == 0.02 and res['max_depth'] == 2 and res['colsample_bytree'] == 0.8:\n",
        "    score1.append(clf.cv_results_['mean_test_score'][index])\n",
        "  if res['learning_rate'] == 0.02 and res['max_depth'] == 2 and res['colsample_bytree'] == 1:\n",
        "    score2.append(clf.cv_results_['mean_test_score'][index])\n",
        "\n",
        "width1 = 10.\n",
        "height1 = 5.\n",
        "width_height_1 = (width1, height1)\n",
        "plt.figure(figsize=width_height_1)\n",
        "plt.plot(n_estimators, score1)\n",
        "plt.plot(n_estimators, score2)\n",
        "plt.legend(['colsample_bytree = 0.8', 'colsample_bytree = 1'])\n",
        "plt.xlabel('N Estimators')\n",
        "plt.ylabel('AUC')\n",
        "plt.xticks(n_estimators)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "id": "zj6lntkGuhyR",
        "outputId": "fa593697-8503-49f0-a33b-5617de0f0018"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}