Anomaly_Detection_Fraud detection_Credit-Card.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Final_ANN_Anomaly_detection_Client_Obinna.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ML9jnDuumf40"
      },
      "source": [
        "Develop highly accurate models to detect anomalies using Artificial Neural Networks with the Tensorflow library in Python3.\n",
        "\n",
        "**Task:** Xredit Card/Fraud Anomaly detection with ANN\n",
        "For the purposes of this task, the dataset we will be using consists of credit card transactions by European cardholders.\n",
        "\n",
        "**Dataset:**\n",
        "The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in **two days**, where we have **492 frauds** out of *284,807 transactions*. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.\n",
        "\n",
        "It contains only numerical input variables which are the result of a PCA transformation. Due to confidentiality issues,the original features and more background information about the data cannot be provided. \n",
        "\n",
        "Features V1, V2, … V28 are the principal components obtained with PCA,* the only features which have not been transformed with PCA are 'Time' and 'Amount'*. **Feature 'Time' **contains the seconds elapsed between each transaction and the first transaction in the dataset. The **feature 'Amount'** is the transaction Amount, this feature can be used for example-dependant cost-senstive learning. Feature 'Class' is the response variable and it takes value 1 in case of fraud and 0 otherwise. \n",
        "\n",
        "**Goal:**\n",
        "To develop a classification model that can identify, with high certainty, whether a transaction is fradulent or not given the current dataset.\n",
        "\n",
        "Dataset: https://www.kaggle.com/mlg-ulb/creditcardfraud"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Anp9iWZAt3u8"
      },
      "source": [
        "# **1. Let's import Libraries**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QbyltgdRmO76"
      },
      "source": [
        "#Let's import Libraries\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "sns.set_style(\"darkgrid\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X7fb23NbtsbG"
      },
      "source": [
        "We will use the features and classes of these observations to develop a supervised predictive model allowing us to determine whether a new transaction is fraudulent or not. There are approximately 30 features within the dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nn7o1ksduGmD"
      },
      "source": [
        "#### **Data Import from Kaggle into Google Colab**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "92PSPxSXwK3f"
      },
      "source": [
        "#1. upload kaggle json API Token to google drive (in kaggle account)...\n",
        "#to avoid uploading the JSON file every time the notebook is reloaded or restarted.\n",
        "#2. mount drive to notebook\n",
        "#3. install kaggle libray in colab & make a directory\n",
        "#4. copy the “kaggle.json” file from the mounted google drive to the current instance storage\n",
        "#5. download dataset-   ! kaggle datasets download <name-of-dataset>\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w21s5UJny0OL",
        "outputId": "b298b371-a56d-4d69-9ac0-ddf37a4a95e6"
      },
      "source": [
        "! pip install kaggle #install kaggle library\n",
        "! mkdir ~/.kaggle #make a directory for Kaggle"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: kaggle in /usr/local/lib/python3.7/dist-packages (1.5.12)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.7/dist-packages (from kaggle) (2021.10.8)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from kaggle) (4.62.3)\n",
            "Requirement already satisfied: urllib3 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.24.3)\n",
            "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.7/dist-packages (from kaggle) (1.15.0)\n",
            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.8.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from kaggle) (2.23.0)\n",
            "Requirement already satisfied: python-slugify in /usr/local/lib/python3.7/dist-packages (from kaggle) (5.0.2)\n",
            "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.7/dist-packages (from python-slugify->kaggle) (1.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->kaggle) (2.10)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rh27UuNEzHS5"
      },
      "source": [
        "cp /content/drive/MyDrive/kaggle.json ~/.kaggle/kaggle.json #copy the “kaggle.json” file from the mounted google drive to the current instance storage"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lXfRdc1y0IHJ"
      },
      "source": [
        "**Let's download the dataset from kaggle**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kkIBzBt0zfZU",
        "outputId": "e9bb4962-410a-41ca-8576-57a6f0b7a00e"
      },
      "source": [
        "! kaggle datasets download mlg-ulb/creditcardfraud"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading creditcardfraud.zip to /content\n",
            "100% 66.0M/66.0M [00:00<00:00, 95.3MB/s]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HvMqzdTR17K3",
        "outputId": "509b2047-a3a5-4b36-e978-8719d4487efb"
      },
      "source": [
        "! unzip creditcardfraud #to unzip the data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  creditcardfraud.zip\n",
            "  inflating: creditcard.csv          \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ruf91AOd2QoT"
      },
      "source": [
        "**Dataframe**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "yQskqGbbnhyt",
        "outputId": "00ee7e03-79ad-4103-ce25-088ee45d0f7a"
      },
      "source": [
        "df = pd.read_csv(\"creditcard.csv\") #from csv into pandas\n",
        "df.head() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>V26</th>\n",
              "      <th>V27</th>\n",
              "      <th>V28</th>\n",
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              "      <td>0.753074</td>\n",
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              "      <td>69.99</td>\n",
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            "text/plain": [
              "   Time        V1        V2        V3  ...       V27       V28  Amount  Class\n",
              "0   0.0 -1.359807 -0.072781  2.536347  ...  0.133558 -0.021053  149.62      0\n",
              "1   0.0  1.191857  0.266151  0.166480  ... -0.008983  0.014724    2.69      0\n",
              "2   1.0 -1.358354 -1.340163  1.773209  ... -0.055353 -0.059752  378.66      0\n",
              "3   1.0 -0.966272 -0.185226  1.792993  ...  0.062723  0.061458  123.50      0\n",
              "4   2.0 -1.158233  0.877737  1.548718  ...  0.219422  0.215153   69.99      0\n",
              "\n",
              "[5 rows x 31 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gGmp8FaBowYU"
      },
      "source": [
        "## 2. **Let's do some exploratory analysis (EDA) on the Credit Fraud data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GnEdPmphosSO",
        "outputId": "4b6cc43a-efaf-4cfb-e5c9-bcec09ebb7de"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(284807, 31)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OMYzv6N13knR"
      },
      "source": [
        "The dataset is has 284,807 rows of data, and 31 columns"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gxJiPHi1o0yG",
        "outputId": "19c7c695-7c10-46eb-f48b-03cda2b26cc3"
      },
      "source": [
        "df.columns"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Time', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'V7', 'V8', 'V9', 'V10',\n",
              "       'V11', 'V12', 'V13', 'V14', 'V15', 'V16', 'V17', 'V18', 'V19', 'V20',\n",
              "       'V21', 'V22', 'V23', 'V24', 'V25', 'V26', 'V27', 'V28', 'Amount',\n",
              "       'Class'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_3Ec-nbe4F5E"
      },
      "source": [
        "This shows that the data contains about 28 vectors worth of info which is masked as expected to cover sensitive information behind the transactions. There are **two visible features**: *Time* and *Amount* in the data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 320
        },
        "id": "h-RrBR2Io3Il",
        "outputId": "e6311849-4c4d-4ceb-b8c7-c1e7d6dfc843"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Time</th>\n",
              "      <th>V1</th>\n",
              "      <th>V2</th>\n",
              "      <th>V3</th>\n",
              "      <th>V4</th>\n",
              "      <th>V5</th>\n",
              "      <th>V6</th>\n",
              "      <th>V7</th>\n",
              "      <th>V8</th>\n",
              "      <th>V9</th>\n",
              "      <th>V10</th>\n",
              "      <th>V11</th>\n",
              "      <th>V12</th>\n",
              "      <th>V13</th>\n",
              "      <th>V14</th>\n",
              "      <th>V15</th>\n",
              "      <th>V16</th>\n",
              "      <th>V17</th>\n",
              "      <th>V18</th>\n",
              "      <th>V19</th>\n",
              "      <th>V20</th>\n",
              "      <th>V21</th>\n",
              "      <th>V22</th>\n",
              "      <th>V23</th>\n",
              "      <th>V24</th>\n",
              "      <th>V25</th>\n",
              "      <th>V26</th>\n",
              "      <th>V27</th>\n",
              "      <th>V28</th>\n",
              "      <th>Amount</th>\n",
              "      <th>Class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>284807.000000</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>2.848070e+05</td>\n",
              "      <td>284807.000000</td>\n",
              "      <td>284807.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>94813.859575</td>\n",
              "      <td>3.919560e-15</td>\n",
              "      <td>5.688174e-16</td>\n",
              "      <td>-8.769071e-15</td>\n",
              "      <td>2.782312e-15</td>\n",
              "      <td>-1.552563e-15</td>\n",
              "      <td>2.010663e-15</td>\n",
              "      <td>-1.694249e-15</td>\n",
              "      <td>-1.927028e-16</td>\n",
              "      <td>-3.137024e-15</td>\n",
              "      <td>1.768627e-15</td>\n",
              "      <td>9.170318e-16</td>\n",
              "      <td>-1.810658e-15</td>\n",
              "      <td>1.693438e-15</td>\n",
              "      <td>1.479045e-15</td>\n",
              "      <td>3.482336e-15</td>\n",
              "      <td>1.392007e-15</td>\n",
              "      <td>-7.528491e-16</td>\n",
              "      <td>4.328772e-16</td>\n",
              "      <td>9.049732e-16</td>\n",
              "      <td>5.085503e-16</td>\n",
              "      <td>1.537294e-16</td>\n",
              "      <td>7.959909e-16</td>\n",
              "      <td>5.367590e-16</td>\n",
              "      <td>4.458112e-15</td>\n",
              "      <td>1.453003e-15</td>\n",
              "      <td>1.699104e-15</td>\n",
              "      <td>-3.660161e-16</td>\n",
              "      <td>-1.206049e-16</td>\n",
              "      <td>88.349619</td>\n",
              "      <td>0.001727</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>47488.145955</td>\n",
              "      <td>1.958696e+00</td>\n",
              "      <td>1.651309e+00</td>\n",
              "      <td>1.516255e+00</td>\n",
              "      <td>1.415869e+00</td>\n",
              "      <td>1.380247e+00</td>\n",
              "      <td>1.332271e+00</td>\n",
              "      <td>1.237094e+00</td>\n",
              "      <td>1.194353e+00</td>\n",
              "      <td>1.098632e+00</td>\n",
              "      <td>1.088850e+00</td>\n",
              "      <td>1.020713e+00</td>\n",
              "      <td>9.992014e-01</td>\n",
              "      <td>9.952742e-01</td>\n",
              "      <td>9.585956e-01</td>\n",
              "      <td>9.153160e-01</td>\n",
              "      <td>8.762529e-01</td>\n",
              "      <td>8.493371e-01</td>\n",
              "      <td>8.381762e-01</td>\n",
              "      <td>8.140405e-01</td>\n",
              "      <td>7.709250e-01</td>\n",
              "      <td>7.345240e-01</td>\n",
              "      <td>7.257016e-01</td>\n",
              "      <td>6.244603e-01</td>\n",
              "      <td>6.056471e-01</td>\n",
              "      <td>5.212781e-01</td>\n",
              "      <td>4.822270e-01</td>\n",
              "      <td>4.036325e-01</td>\n",
              "      <td>3.300833e-01</td>\n",
              "      <td>250.120109</td>\n",
              "      <td>0.041527</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>-5.640751e+01</td>\n",
              "      <td>-7.271573e+01</td>\n",
              "      <td>-4.832559e+01</td>\n",
              "      <td>-5.683171e+00</td>\n",
              "      <td>-1.137433e+02</td>\n",
              "      <td>-2.616051e+01</td>\n",
              "      <td>-4.355724e+01</td>\n",
              "      <td>-7.321672e+01</td>\n",
              "      <td>-1.343407e+01</td>\n",
              "      <td>-2.458826e+01</td>\n",
              "      <td>-4.797473e+00</td>\n",
              "      <td>-1.868371e+01</td>\n",
              "      <td>-5.791881e+00</td>\n",
              "      <td>-1.921433e+01</td>\n",
              "      <td>-4.498945e+00</td>\n",
              "      <td>-1.412985e+01</td>\n",
              "      <td>-2.516280e+01</td>\n",
              "      <td>-9.498746e+00</td>\n",
              "      <td>-7.213527e+00</td>\n",
              "      <td>-5.449772e+01</td>\n",
              "      <td>-3.483038e+01</td>\n",
              "      <td>-1.093314e+01</td>\n",
              "      <td>-4.480774e+01</td>\n",
              "      <td>-2.836627e+00</td>\n",
              "      <td>-1.029540e+01</td>\n",
              "      <td>-2.604551e+00</td>\n",
              "      <td>-2.256568e+01</td>\n",
              "      <td>-1.543008e+01</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>54201.500000</td>\n",
              "      <td>-9.203734e-01</td>\n",
              "      <td>-5.985499e-01</td>\n",
              "      <td>-8.903648e-01</td>\n",
              "      <td>-8.486401e-01</td>\n",
              "      <td>-6.915971e-01</td>\n",
              "      <td>-7.682956e-01</td>\n",
              "      <td>-5.540759e-01</td>\n",
              "      <td>-2.086297e-01</td>\n",
              "      <td>-6.430976e-01</td>\n",
              "      <td>-5.354257e-01</td>\n",
              "      <td>-7.624942e-01</td>\n",
              "      <td>-4.055715e-01</td>\n",
              "      <td>-6.485393e-01</td>\n",
              "      <td>-4.255740e-01</td>\n",
              "      <td>-5.828843e-01</td>\n",
              "      <td>-4.680368e-01</td>\n",
              "      <td>-4.837483e-01</td>\n",
              "      <td>-4.988498e-01</td>\n",
              "      <td>-4.562989e-01</td>\n",
              "      <td>-2.117214e-01</td>\n",
              "      <td>-2.283949e-01</td>\n",
              "      <td>-5.423504e-01</td>\n",
              "      <td>-1.618463e-01</td>\n",
              "      <td>-3.545861e-01</td>\n",
              "      <td>-3.171451e-01</td>\n",
              "      <td>-3.269839e-01</td>\n",
              "      <td>-7.083953e-02</td>\n",
              "      <td>-5.295979e-02</td>\n",
              "      <td>5.600000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>84692.000000</td>\n",
              "      <td>1.810880e-02</td>\n",
              "      <td>6.548556e-02</td>\n",
              "      <td>1.798463e-01</td>\n",
              "      <td>-1.984653e-02</td>\n",
              "      <td>-5.433583e-02</td>\n",
              "      <td>-2.741871e-01</td>\n",
              "      <td>4.010308e-02</td>\n",
              "      <td>2.235804e-02</td>\n",
              "      <td>-5.142873e-02</td>\n",
              "      <td>-9.291738e-02</td>\n",
              "      <td>-3.275735e-02</td>\n",
              "      <td>1.400326e-01</td>\n",
              "      <td>-1.356806e-02</td>\n",
              "      <td>5.060132e-02</td>\n",
              "      <td>4.807155e-02</td>\n",
              "      <td>6.641332e-02</td>\n",
              "      <td>-6.567575e-02</td>\n",
              "      <td>-3.636312e-03</td>\n",
              "      <td>3.734823e-03</td>\n",
              "      <td>-6.248109e-02</td>\n",
              "      <td>-2.945017e-02</td>\n",
              "      <td>6.781943e-03</td>\n",
              "      <td>-1.119293e-02</td>\n",
              "      <td>4.097606e-02</td>\n",
              "      <td>1.659350e-02</td>\n",
              "      <td>-5.213911e-02</td>\n",
              "      <td>1.342146e-03</td>\n",
              "      <td>1.124383e-02</td>\n",
              "      <td>22.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>139320.500000</td>\n",
              "      <td>1.315642e+00</td>\n",
              "      <td>8.037239e-01</td>\n",
              "      <td>1.027196e+00</td>\n",
              "      <td>7.433413e-01</td>\n",
              "      <td>6.119264e-01</td>\n",
              "      <td>3.985649e-01</td>\n",
              "      <td>5.704361e-01</td>\n",
              "      <td>3.273459e-01</td>\n",
              "      <td>5.971390e-01</td>\n",
              "      <td>4.539234e-01</td>\n",
              "      <td>7.395934e-01</td>\n",
              "      <td>6.182380e-01</td>\n",
              "      <td>6.625050e-01</td>\n",
              "      <td>4.931498e-01</td>\n",
              "      <td>6.488208e-01</td>\n",
              "      <td>5.232963e-01</td>\n",
              "      <td>3.996750e-01</td>\n",
              "      <td>5.008067e-01</td>\n",
              "      <td>4.589494e-01</td>\n",
              "      <td>1.330408e-01</td>\n",
              "      <td>1.863772e-01</td>\n",
              "      <td>5.285536e-01</td>\n",
              "      <td>1.476421e-01</td>\n",
              "      <td>4.395266e-01</td>\n",
              "      <td>3.507156e-01</td>\n",
              "      <td>2.409522e-01</td>\n",
              "      <td>9.104512e-02</td>\n",
              "      <td>7.827995e-02</td>\n",
              "      <td>77.165000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>172792.000000</td>\n",
              "      <td>2.454930e+00</td>\n",
              "      <td>2.205773e+01</td>\n",
              "      <td>9.382558e+00</td>\n",
              "      <td>1.687534e+01</td>\n",
              "      <td>3.480167e+01</td>\n",
              "      <td>7.330163e+01</td>\n",
              "      <td>1.205895e+02</td>\n",
              "      <td>2.000721e+01</td>\n",
              "      <td>1.559499e+01</td>\n",
              "      <td>2.374514e+01</td>\n",
              "      <td>1.201891e+01</td>\n",
              "      <td>7.848392e+00</td>\n",
              "      <td>7.126883e+00</td>\n",
              "      <td>1.052677e+01</td>\n",
              "      <td>8.877742e+00</td>\n",
              "      <td>1.731511e+01</td>\n",
              "      <td>9.253526e+00</td>\n",
              "      <td>5.041069e+00</td>\n",
              "      <td>5.591971e+00</td>\n",
              "      <td>3.942090e+01</td>\n",
              "      <td>2.720284e+01</td>\n",
              "      <td>1.050309e+01</td>\n",
              "      <td>2.252841e+01</td>\n",
              "      <td>4.584549e+00</td>\n",
              "      <td>7.519589e+00</td>\n",
              "      <td>3.517346e+00</td>\n",
              "      <td>3.161220e+01</td>\n",
              "      <td>3.384781e+01</td>\n",
              "      <td>25691.160000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                Time            V1  ...         Amount          Class\n",
              "count  284807.000000  2.848070e+05  ...  284807.000000  284807.000000\n",
              "mean    94813.859575  3.919560e-15  ...      88.349619       0.001727\n",
              "std     47488.145955  1.958696e+00  ...     250.120109       0.041527\n",
              "min         0.000000 -5.640751e+01  ...       0.000000       0.000000\n",
              "25%     54201.500000 -9.203734e-01  ...       5.600000       0.000000\n",
              "50%     84692.000000  1.810880e-02  ...      22.000000       0.000000\n",
              "75%    139320.500000  1.315642e+00  ...      77.165000       0.000000\n",
              "max    172792.000000  2.454930e+00  ...   25691.160000       1.000000\n",
              "\n",
              "[8 rows x 31 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1QQNehvIo7MO",
        "outputId": "78b487c2-5f63-4357-c2e3-44f876b2763f"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 284807 entries, 0 to 284806\n",
            "Data columns (total 31 columns):\n",
            " #   Column  Non-Null Count   Dtype  \n",
            "---  ------  --------------   -----  \n",
            " 0   Time    284807 non-null  float64\n",
            " 1   V1      284807 non-null  float64\n",
            " 2   V2      284807 non-null  float64\n",
            " 3   V3      284807 non-null  float64\n",
            " 4   V4      284807 non-null  float64\n",
            " 5   V5      284807 non-null  float64\n",
            " 6   V6      284807 non-null  float64\n",
            " 7   V7      284807 non-null  float64\n",
            " 8   V8      284807 non-null  float64\n",
            " 9   V9      284807 non-null  float64\n",
            " 10  V10     284807 non-null  float64\n",
            " 11  V11     284807 non-null  float64\n",
            " 12  V12     284807 non-null  float64\n",
            " 13  V13     284807 non-null  float64\n",
            " 14  V14     284807 non-null  float64\n",
            " 15  V15     284807 non-null  float64\n",
            " 16  V16     284807 non-null  float64\n",
            " 17  V17     284807 non-null  float64\n",
            " 18  V18     284807 non-null  float64\n",
            " 19  V19     284807 non-null  float64\n",
            " 20  V20     284807 non-null  float64\n",
            " 21  V21     284807 non-null  float64\n",
            " 22  V22     284807 non-null  float64\n",
            " 23  V23     284807 non-null  float64\n",
            " 24  V24     284807 non-null  float64\n",
            " 25  V25     284807 non-null  float64\n",
            " 26  V26     284807 non-null  float64\n",
            " 27  V27     284807 non-null  float64\n",
            " 28  V28     284807 non-null  float64\n",
            " 29  Amount  284807 non-null  float64\n",
            " 30  Class   284807 non-null  int64  \n",
            "dtypes: float64(30), int64(1)\n",
            "memory usage: 67.4 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "phIhhR9Po90u",
        "outputId": "ff4b6e51-c518-4b9f-a9f9-4f414b587d5b"
      },
      "source": [
        "df.isnull().sum() #are there any null values? missing data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Time      0\n",
              "V1        0\n",
              "V2        0\n",
              "V3        0\n",
              "V4        0\n",
              "V5        0\n",
              "V6        0\n",
              "V7        0\n",
              "V8        0\n",
              "V9        0\n",
              "V10       0\n",
              "V11       0\n",
              "V12       0\n",
              "V13       0\n",
              "V14       0\n",
              "V15       0\n",
              "V16       0\n",
              "V17       0\n",
              "V18       0\n",
              "V19       0\n",
              "V20       0\n",
              "V21       0\n",
              "V22       0\n",
              "V23       0\n",
              "V24       0\n",
              "V25       0\n",
              "V26       0\n",
              "V27       0\n",
              "V28       0\n",
              "Amount    0\n",
              "Class     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AO5sCXQ1pHkt",
        "outputId": "2f25d69b-dcaa-421d-c34d-3d3a9ccce903"
      },
      "source": [
        "df.Class.value_counts() #distribution of the two classes \n",
        "# 0 = Valid # non-fraudulent transactions\n",
        "# 1 = Fraud #fraudulent transactions"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    284315\n",
              "1       492\n",
              "Name: Class, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GYbaimr15lb-"
      },
      "source": [
        "The data is imbalanced, we will tackle this using ANN"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2L9G67K755rs"
      },
      "source": [
        " Let's dig into the content of the data to know it better using -\n",
        " **Correlation via pairplot**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 879
        },
        "id": "FHpeWUHvpKbt",
        "outputId": "fa3614d7-9048-4cc6-906a-570dd8c6cc68"
      },
      "source": [
        "df.hist(figsize=(15,15)); #size of the output image"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 36 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PTzba_T17pgh"
      },
      "source": [
        "Some observations on our plot\n",
        "There's no correlation with one another. Though some data points create a sort of linear line going from right to left when graphing Time vs V1. There are two clusters of data when graphing Amount against Time."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "s3P6H8Ic_T4Z"
      },
      "source": [
        "**Scatter Plots**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        },
        "id": "ifcJfacKpPZW",
        "outputId": "8bebf7a7-c966-474a-b047-025ee85d0bc6"
      },
      "source": [
        "plt.figure(figsize=(20,10))\n",
        "sns.pairplot(df[[\"Time\",\"V1\", \"Amount\"]])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fe8b67f3350>"
            ]
          },
          "metadata": {},
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WJOzreDjR9u1ppba8J29x37Pbuf3SlXh+wIu78rV0TzhAdfo+VUkbdIXm5Ni2DpsO7Q1JrjxrIWXHJwyhaLk88toA/3tZG81pFUEQQYBGQyWpSAyUbUIhpGwHyGIkrkQA2w2ouD71hspAyaY5pWGoErvzLpoS0N6QoGy7UfpmwSWTUNDkyPCqaHmUbA+QSWujRiZCiJYeHrYXMFhyaElrpBMS+YpHEAg0piR25lxUSSQMQ0RECEP6SzaNKZWK6/OJs49noGiTSSjc8tgG1ixvQxJhxew6vvfMNp7ZOsT3Lzu1OgolxCXI/8CIg4qYmJipZbLpBphU/DXh9sHk+zEdf0zGwesOs0/ioDm3weC0jr1/Q9dkevIVvlId3gf4+JkLopEWUeSzP3qFT75jIQ0pnXzFRRQEHC8aYUkoI2mjCpIgYPk+ng+uHzC7LoEfhpiOR3M68quQBYEwFBg0bWbXJ7DdANsT6K8GIKbrYjo+bhgFMSPTFUUT6l/fTHS/CIAsCrh+gOOKzMrK9BdDNvZVIi1FWsUPQgZKDk1plWZZo79oo0gCW/qKzGlM0Vus8Ok/WUxf0UJA4OZfbmBDX4lrz1nK393/At2DlbgE+R8gsaNmldhR88gwndsXO2oeONPuOoqwo+jSV4pSMD3PJ6urY1JXdxdtUrpCvSbhB+GELoGXnzGPkzvqWdKcYKjis2EgOsZPjypDPjIl8ui6PZx/cge3PbmJj50xj/Z6A8vzSWky+YpLo6GSt6JUU02O3DaLlsfcpgT5ik9fMfKwkEWB/qKDrogkVImWtER/MUo7bUpp+IGPIIhUXI+srtJaJ7J72Ke3GB1rWpNrUyCH6qi5Y9inYEU6D9PxyCYUSrZHSpMxVImC5QASfUWL/qLNghaDEIHBksPuXIX7n9vBJas7kKquoyXbRxDglLn1XPWTV+gerIw5z1NmgDVZ6nGVaXefTgHT8ZhiR82YmJhjm1GdSV1SZdNAmZsf3cDFqzr421FpqjdffCKOF4wbkWhvSE4qHn1++3BUgXN3gRPb6/jqI+u55j1LuKZaz2LYdDBUib962wIGixZfOX85AyUHXRWQRCl6m0+pqLJIEIIkCAgIUXYHMFh20WWJlBZ1gH1Fm4yu4AcBCVmkvxgwVI6mIiRBwHQCkqqE5QZk9BAJUESBrK6Qq7goksjhJu6FgOkEpDWBjgadtAYb+wMGSg5UU21FIK3LZBMKlhvwg99sY1l7HR31yVptlDCE257cUtNYnDJ35ZiAYuQ8H5IB1r4BRFKqpRhPdY2ZmKnjiAUVnZ2ddwFrgL6urq6l1WXXAH8J9Fc3+8eurq6Hq+s+C1wG+MAVXV1dv6gufxdwM1Fi9ne6urquqy4/DrgXaASeAz7Y1dXldHZ2asDdwEpgELi4q6tr25E6zpiYmCPMPlMXV5y1gDue3MJlp8+rCTch6rxe7Slwx5Nj/SxufnQjN164YlLxqB9Ab97i5kc38qdLZnDRqg7+49nt3HTRiXhBSF0y0jq8sD1H3vL51pNbuOyPjqMuodBbsMhXXDIJCc/yqU8oDJQcmtN79R1+EKWE1ukKZcejNa3jBSFlP2B33iatS8zK6oiiQMnyGWmiIor4QciuXBTYpHUFyROYitFlAUiqIn4Y0j1oUZ9UaTIUGpMKjh+wZ9ilJaOhKwJeIFCXVLjklHbSCZWBosXcRgNDk7jqJ6/UAorPv3cp2wbL+/EEOQjzswkCiNsvXTmpM2rs2Dl9OJI+Ff8KvGuC5Td1dXWdWP03ElCcAFwCLKl+5ludnZ1SZ2enBHwTeDdwAvBn1W0BvlLd1wJgmCggofr/cHX5TdXtYmJijjZTVA59Xx+LoJpGOpF3xci60VhuwM5hky+du2yc50RjUuWhl3aRUGUsN+CBF3pYu3mAT5x9PF4Q0JzWMB2HPQUbP4SO+gSfPvt4ZtUnGDYtRFEgV3FZ11PEtEOGTZekKiFWi5Blq+6bQQiiKCAIUa2NPYXI7KrBUBgqu5QdH0kEUQRVFBBFSKiRgBIhpLGaqZFUJJLq4T+2ZTEaSclXXOqTKpocUrJ9+koWjhcyqy6apjGdAE2KbLwzCQVRCEgqMkUrOs6r/vQErj9/GXd+eBVrN/dz66+2jCkHrysi1527nGZDZu3OAufdsZYP/euzY71FqkHj6HWvDVTGBRDPbR/erzNqzPTgiIV3XV1dT3Z2ds49wM3PAe7t6uqyga2dnZ2bgFOq6zZ1dXVtAejs7LwXOKezs3MdcCbw/uo2/wZcA9xa3dc11eX/CdzS2dkpdHV1xQNkMTEHw6i3x1kBZCWmpIjXwQ5VT+R7MbrTGr1OEib2szAdn/Z6nXv/4lR2F2yCIGTHsMldT2/l8jPm05Mza5974IUeHnihp1ZE7KGXdnHVmhNYNCPNiztz+AE89NIu/vKt82hOayxuzeD4ASldJqWJSKJI2fbxAh9FjN7GRUFAgGoxMYG2Op0giEynWjM6puvTPWhhaBKGLlOyojLrTSkFQ4OevI8XhCiSGNX/OEzcqsFWSzpK/1VlkCTIVVxCBQZK0TTTrDqdQsWnJx+JR3VZoNcxcf0gshn3A5KqzFd+tp6XdhUAuO/Z7Vx/wQrCMGTHkMlNj3ZR/96lB1R/ZWTdRAFEEE58baekxkzMlPFGjBl9vLOz80PAs8Anu7q6hoE2YO2obXZWlwHs2Gf5qURTHrmuri5vgu3bRj7T1dXldXZ25qvbD+yvUZIkUFc3saRaksRJ173RTOe2wfRu3xvVtv3da9OFIAj5ZVc/n7x/r17hqxeeyDs6m8c5OgZByI5chb6iTUtao70uwY7c+DfNT//wJR76+OnMaXj9Yx+9z+w+vhcjTpf3/m68LXRHY5JPnd3JjY90jdFUGKrEFfe+yLDp8G8fXc1QyaXi+qxZ3saPnt/BB06dy5VnLRzjT/F371jE93/bzftPmcNQKarKeepxDQyXXd6+aEWtdkdSkRksO3hBAEhUHJ+hsk1jSiNXcWlMRamnfhiQ0aIy6K7vU5dQcbwQxw+wXZ/6pILpeiihiOODQDRSkK94CIJUM+MaHVO83n207702WC6OWS8AtufhhyJ+pOEkJGRGRqe3aCMIUTlzURCouJEZlq5KqLJE90CZuc0Gm3rLbOgrAVEnf/GqDr76yHrOObENP4Duwcqkoww526/9POb6TxBAPPjiLr5y3nL+4YGXxtyT81vStXtyOj9vDpVj7ZiOdlBxK3At0bvKtcBXgY8e5TZMiO+Hkypsp6P6doTp3DaY3u07Stkf45bt716bLvRbXi2ggOih/8n7Xxg/fz3JiERWlyfsRLp6iziuT7O+H++CffY5pzHBtecs5aqfvFITTiYViUtWdzC7PsHXLlzBpv4yXhDQV4gcMq88ayGz65MYqsSmvuKYcty/3jTI/c/u5LyTZ9PRkEASm/nur7fy7mUzueGCFUgi1CdVXt6ZY83yNr7/227+9h2LSKkyPXkLQ5XpL9kUTIfjWlLYfnSciijgByFD5SitNKlKyGKUMSFJAp4XYDo+mUQk0hwhrQk0pXTKdkDFCVClgIakEnlDGCqz6lV6cpFnBkRTJCOMvo8O6F6rOmZrskhjSqW/FGWkJGQRFLA8iULFIwhCmgwVVQLTDQnCMPLPsF22DpQxHZ8FzQbrdxf5z+d28q33n8wL1VGc+57dzsWrOrhnbTfnr5wNTD7KUKdJTGR+9uCLu/jyucv47I9ert1Xf3PmQhY0GzzwsdMicWw1xbhQqNRG1XK2T50mv6m8MabjM3Sie22EoxpUdHV19Y783NnZ+W3goeqvu4D2UZvOri5jkuWDQF1nZ6dcHa0Yvf3IvnZ2dnbKQLa6fUxMzOtRfTh35yqTzl+PDiomq9vxg8tOnbATea2nyCfvf3G/UyH77rN7sMItj2/kno+ewm+2DtHRaNBfsJjTaPCVn6+r+SFcedZC7n6mm2HTIQzhSw+vm7AcdxBSc9GcmdX54GlR5c2Xft5VKxhWtj1m1SXJOh6fPvt4ZAm+8PBrOF7IX7z1OH728m4+evp8fr1psDYd8smzO6lPKGSTEglZJme6lGyPGWmNsuNjOj6tWQ3fD3FEkf6SQ1KVSKoylhPghwH1yajXt7ygqssQkIXxvhLohzcFMtr8ytCk6DKEkTjU8V0EQUaRBPwwJAh8mlMaRdsloyl0NCSpSyjYvs+Xf9bFsOngVj3YBQHWLG/jnrV7rwNEQcIX37eMf/rxy2OCz+aEDAJjgsaR0Y5//802br90JQXLZWNfia8+soFh0+Hac5by9uPqIKBWyXaqptpiDp+jGlR0dnbO7Orq6qn+ei7wSvXnnwLf7+zs/BowC1gI/Jbou7Swmumxi0jM+f6urq6ws7PzceACogyQDwM/GbWvDwPPVNc/FuspYmIOgFEP579467wDmr+erM6H5XrjXDJHbLVfT7U/0T67BysMlGxufGRDbdnMrF4bbcjoCtmkzIXubPyAmtvmRBqLB1/cxRfet4x//vHLNafOr110Ipv6SiyfncUPAjw/xPVDegs2XlBhQVOSz7xrMev2FHC8gHNPmk1SFfmj+U0Mlm3etnAFSU1iT8FCUxRyFYf6pIokCuzKW7RlddJaFGjYbhQ82J5PQol8JkLA8UIqTlRITBaj0YEwKmyKKotkq5bfmiwyVVVKBcAPApwAVEmMslMyOtmESH/RxfZ8dEWmUHFJadEUjiyKeEHI3b/urnXy335yE2ce3zpmKmokyBsJEn7w2218/7JTKVnuGPOz/orHLY9v5PoLVrCprzjm+n3se89x+Rnz+MajewPDq37yCt+/7FTajSgAmyywjbNC3hiOZErpD4C3A02dnZ07gauBt3d2dp5I9B3aBnwMoKur69XOzs7/AF4jcqH9v11dXX51Px8HfkH0Lbqrq6vr1eqf+Afg3s7Ozi8AvwfurC6/E7inKvYcIgpEYmL+MHkds6DRjH44T1RrY4xrZXW/iiJOGHyIosiiZoPvfngV24crbB+qjLHVHq3a37dtk9UOGV0LBKIiVnc+tYXLz5jH9qBCWpdIKNIYXUSjoXL1e5bwL1XPiZEOrjGlcPkZ8wiqNTWufeg1hk2HGy9YwfreIgo+y9obEQU4vjXDV36+DscLuXDVbGbV6TQYGoIQ2XKndYVh0yUkpD6hMlhy0FUR2w9IaRINRpKc6VOyHdKaEhUek0UMTWZPwWJ2nY4kguX4pPUo2FCkKIMkJKwGHAF5s2qspUxh0p4AaV3klV0mzSkNRYpkoEOmiypLuH6A6wdocjRqsn2oQkqTUSWBMxY1c9HqDn70++2cv7KD257YxGWnz0MSYdmsLDuHTS5cNZsFLWm+/PA6evJWdepKxPJD1g2YNBkaA2WH7sEKG3qL40aVJitE11u0akHFZIHtIXljxBw2RzL7488mWHznBMtGtv8i8MUJlj8MPDzB8i3szRAZvdwCLjyoxsbEvBk5yGHh0Q/nnrzFPWuj6p1LZ6VZ2JLem/0xar/1SXWcwPHKsxayfk+Ru57eyrXvXcruXIU7n9oyLkgIBaHmcllrW3sGSWTCofK0JvKlc5fxj6Pm2a88ayGtWZ2v/3IDjhfy12+bVwsWRAHSCYXvPrWVj//xAlozOtuHTe5Z201bncaFqzq4+qd7g42r37ME03Z58MVdXLyqg6c39fKOJW3kKw43XLCCobJNg6ERhCE506UuqeAFAZbjk9IlRDEa/keAhCKRM10akgqeL1RLomto1WBiqGzTkNSoTyr0FGyyCZmmlMpAySGly5Qcl/pkpMvYk/exq9MhEOkkDjk/d+ztASH05BxaszoCULACFCkkZ/rUJ0UyCZm+gktzWiUMQVckGgyVEJ9FrWnKjs9JHY384DfdnHNiG/ObU+zOVfjcT19l2HS44syFtYBCV0Q29JUIQ8YEq7d+4ORJs3kmK0Q3I63Xfp8sCI2zQt4YYpvuKrFN95FhOrfvzW7T3W95E1pTTzYs3G/5nHfHMxNuv7A1UztX++53ZlbnwlWzacsm2D5c4YHndzJsOrV0zM/8yfFsGzLHBB5fOncZNz+6YZyd8+2XruRj33uO+qTKhatms7AlxfzGJDtyFlfe9wKLWlL8zZkLGTYdEobtix4AACAASURBVKrMcDmytu4eMpmR0UlpMn4QUrRcWjI6JdvlU/fvFXx+5l2L2dhXwgsClrZlSMhRrY+UFqVxfvOJzVy4sp15TQYpXaa/6NCajTot0w7wAp+UpjBYdmg0VIIwpOJGGSAlxyWlKQyUbJqMKICwPB/XD6k4UTXSsuNRsDxa0xq2H1CseCRUCUUSUGWRiuNTsn0MTUISBXRZwtAEcmZk811vqBiqxIzqbXWoNt3bhyNb8BkZjSZDYlN/pTpdE5U/1+VoKqfR0HADHz+AlBb5U4hiNDq1bneB1mwCTRHpL9pkdYX7n+tmzYp2tg2UWdCSGqN5uWrNCRQqbu0+GGFOY4LLz5jPHU9u5uJVHWMCjk+d3UljSuWzD+wNJMdoKuBNr6mYjs/Q2KY7JuYPkIMdFp6suuhIEa/J9tuTt/jGo5v4+JkLaiXEIXpr7x6sRB2kADdcsALT9ugv2QwUrQntnEdSD0f2qSsid3/0FK6sWnG/tKvA5376Kheums2Ktixts7J86Wevceq8ZoSihSwl2T5YZm6jwYY9BfyQ2ihFf8lm22CUJXJ8a4ZbHt1Ef8nhQ2+Zw+d++motkOloSJJQI/GiHwSs6ymQ0WVmZBKU7AAvcJmZ0bCDcO95EMD1QhwpoC2rY/sBfUWbOkNBCkOSWuSO6QchCSX6OWe6GJpMRpfxw5D+okNClWhMKQQB9BZsZtXphKFASJTW6QfhlHSUiihQl1AYKjuIgkZalwgJEYTIs6K/5JDSFfwwQJclfCKNh+V65E2PQdNldn0CQ5N4dVeevOXz0EvRCM/IyMScxgSfPPt4NvQWa9Vey44/oV6maLmsWd5GW73O9ResYNtAGdsLuPOprTSnVP7tI6sZKjvMSOu0p5W9AQWMKWAXZX9Iccn1N5A4qIiJeZNy0MPCk1UX3efhPNl+Rw96jvyuKyKKJPKln3WN2cdI5c999+GP7W+w3IBtA+UJg5i7/3wV7SmFS087js88MLbWx1DZprUuwVcf6aJ7sMLMrM4//uliugfLLG7NcN2oN+ikIkXTKBmdbELhW7/ayJnHt3Lfs9tZs7yNbEKmvcGgYLk0pVR2DJk0GSqKIGALAm4QRMaQQtT5m66PKkkYmohApNko2wGaHGKoMgMlG1HwmZnVUSUBx4sEmUlVwvEjLwjTixxI/SDEC4Ix1sdT0Ve6QUiu4jIjrdGaFdncF5JNRDqQ4bJLcypy1Nydt0jpMglFpGx7IEjkKhXmNBrc9dRmzlrcSsn20WSRz7xrMdf9fO9Ux+gAY6R428h13ve6Fy2fbz4eBabf+Z+xU2XDpkNakZjXWk1j3OceGTkpzbq8d0QtDijeMI6kTXdMTMwbyMjIw+j56olGHsZQfTgvbkzWRjP6LY/fdQ/XrLYn2u+15yzloZd21X6/4syFPPTSLm44fzkNCaW27QgPvriL6/axzb7u3OW1fYwQVfKUx32+FhyF8EdzMnz7gyu58cLlfOv9JzO/OcWs+gQ/em4nF6/qQFdEevIWNz6ynua0xnU/X8eFK9u56aIVfPcjq5ndmGDprAwNRhRQnDqvGVmEL5yzjEUzDGRRYE/e4sp7X+AT//EiO3MVegoWQjWzRBbFmsbC9aOMDkGAwbKHiIChSihVPUpISKrq4VFxfRwvpGh7DJYcNEUkoUgMlSOjLUUSEAQBQxMJAC+IvCJU6fD1FLIokEnI5CoufYWAMGoeJdujwVCxPQ/T9WnNRtMtgyWLEIFXd0ejEl/5+TouXj2He3+3nW8+volv/WoTfQWLS1Z3cMufncS33n8y9z27vRZQXPOeJTSnNB58cdc4G+/R986DL+7i6jVLDu6ejZlWxJqKKrGm4sgwndv3ZtdUAPtkf0w88rC/z046Vy3AawORU6IfwG+29PM3Zy5CCENSuoLtemR1pdYZ7LufL75vGcvbUpTsqA7GjLROe0Zh7fbCuDTUn7/Sw7uWzhyXiXLa7Ext3zf+dxdrlrcxpyHBzlyF+5/dSU/equk9Frak2dhX5OUdOS5c1Y4bhEiCwB1PbmZDX4kvn7eMYsWl3tBwPJ/WrI7pVA2nQpBlSKoygyWHxpSGKARApCVoSWsgRKMNYQiuH1Ku6iKMql7CdAOGqxVWIaRoeTSnNTw/AAGEUMAOfIoVv1YSXYz+NDPrJHaNaCDSGtmkRLaqUzxUTUVfMaRQLc0eVVgF0wlJqlEGjiBGUyQl26e/qhHxAh9ZkugtRAZghi5QcWCwZNOU1sibDpmEysMv7WTV3EZmNxjsGq6gKRLfeXIz/SWHC1fNZlVHHSlN2Ztaasi81j/2Xvr4mYuwXJ+WlDZ+umM/TOfnzaEyHY9pf5qKOKioEgcVR4bp3L4/iKDiMNif0BM4KBHoSHCzechkY1+J+5+NxJyjDau+dO4yWjMqqiTx5KYBFrakufGR9bXpi/NOno0kwtsXNtOeitIJd5Rc3n/nb8aIRj/0ljljRKFXnLmQx9bv4fyVHbXU0jmNCT5/zlIqjo8qiezOmeQqHkEIJ8xMs6W/hCSKLJqRZlNfkRPaMgTVehkpTUYWBWRJIAwhZ7qkdJkwDEgoMqbrU7Q8DE2m0VBwvZCy41GyfdK6jO1Ff7M+qVCyfXqLNjMzGiECvQWL2XWJqFJoVUg5s06iZzjabkZGoyUtMXKKD1uomdaYkZUwbchbHjkz6ujLjkdGVwiJppsajMhqvOK5bO4zueXxzbTVaXzm3cfj+kTi1JRGEAbkTQ9NEfneM92sPq5x4mBwVFryQNlhRlrDD0IGyg6hIPC5n75Sm546GNHldH7eHCrT8ZhioWZMTMxBsz+h58jPE62bMKiodgif/s+Xxnzu5kc3ctnp8/jm45v4xx+9XMsY+fgfL+TGR9bXsgFGPCluOH95LaBYu7PAxv7SOL3F3c90c+MFK9iZq7B0VgbH91natghDlfj2B1eSq3jUGwp3PrmFwbLDR04/jqLtc8vjm2oBx+fWnMBQOTJ/WtqWZbjiklQkHC9ASkZGUbvzFh0NCbJJhb6Czcysjh+GmLaPoUo0GFHQ0FfYGwz0FR2SmkRKkzGjAh/UJxUGy5FeY2ZWZ0euQqOhMrcxEdl+F6Osk5a0Rl/RRkCjvX5qzK8AKm6ksShXpz5EMaw5ZsqCRFqXKVoeQyWb5ozKvOYU//S/F9dcNtf3lJiR0RksOezMmYRhVCTtma1DrO8tcfkZ81jQnGJBUxJJEFg3YDIjrbGhvzxuFGx+Y3JMsBobWR17xFcpJiZmQvYv9Bxfr+H1vAEmC1JGCmWN/Dxiy33ThSdiu97ELoyWN6nz57DpsG5PsZaJMjOr81dnzGPQdJBFkYUtKf7pRy/X3oRd12fRjBS3X7oS0/XpyVX45x9HPgufeOciCEMWtUZFqxw/8ovoL1goosiw6VKnK7TXJ8hbLpYbkE3KSILIjqEKDYbCrKzOgBlNPyVVCc8PqLgB+YpLQpVoMhQMRaLo+GgyteABVBQpKlGeUGR25ixmpDXqklMXUACoUuTm6fohthegaTKW7zNc9mhIiqR1mSB0SaoqQSgAIc1pFc+PBKmdrWm8IKz5Z8xpTHLXU5trRlgntdczt17lxV0lPlP1GLnirAXc8eSWccHDLX92UmxkdYwTX6WYmJgJeb0U00nXTTJM/XpZI6N/7h6sULJcFjdWqzNW3RNH9j0SoEzk/Hn1e5Zw2xN7U1t78hZ3Pb2Vmy48kZLlkk2q3HD+coZMFwEBWQJFEmv6AiGEvz1rIUOmgy6LpBORC+bXHtnAhr4S15+/lPqkTr7ikJVleosWaV1BEiGbkCmY0UhIg6GQNz2yCYWEIuD6IX4QTZEMVv01QvyoboYgoMkCOdMjoUBzKrL41iQRURIouj6iAH4YUnFC0trhizVHUGTIiiJBoFGsTsc0p1Ta6vRohKIQTfkYqsSevMnmgQqOH7Cyo55duTKff2gd9Um1Nu00kpo7rylFRpe5++mtXLS6oxZQQFR/ZaLgwdCk2MjqGCcOKmJiYibmdfL/DyT9dDQTBSmj60OM1AaBvR1JvzWxxXhaV2pZHSPOn5IIi1rSDJVtLlndMUZXccnqDgxVZFfO4/J/f742zXLxqg4eW7+Hy06fz9aBMrIkosoCdUmFmXU6miIiiwLrdhc4o7OF953URl1SY1NfkfktKfqLNo2GRlIVGSr7lDyvOlIhYLkBSU1EEgVsOyShCDSlNcpWJABNaxKOL1K2fQbLDnMbkghJgT2FSPwpV60kUxo4bjRikK+4qJLI4TpqioKAIglYns9gUUAUBLKJKKW34viUHJ+MJtf0kboisidvkklqdDQINKU0/vPZ7Ty3I8dNF52I7UWl279+0YnkLZeEKvOdqgj2+gtWsG5PYVwQMVHw0KAr4+6R685dTnNSPmCxZswbSxxUxMTETM7+8v+r62rD0q8npJvAB0MSBToakoiCMMbj4Ibzl7Mjb9VMr0bbePebHkMVpzZCMaK3uGrNCXyxWpn0h8/t5LLT5yEIUUbG3c90M7fRqHVWI9Ms96zt5ryTZ9M9VGZRSxo/CDG9kB3DJvf+bjuXrO6goyFB0faZ32TQnI7qYyyYkaZoudQlVbYMlDi+NY2hyViuQxiGKLKI5AUMlV2a0xKZhEQYhmwbMGlOayxoSZKv+BQtl0xCYVZWo+RE2RgtaY2C5ZLW5WoRsoCC5aIrkbYhmAJxfRBGRly6LFG0XAxNoeyALAk0pRQGSy6yJOD7AQ2GSsFyMXSVIAgxNAlZhrcsaOa9J81mw54Cc5pS/K47N652B0DF9saVPv/hczsntHffNlzhtI4Mt1+6spYNctOjXUjv7HzTOGS+2YmDipiYmMPnQAuX7RuIAKfMSjNk+1x37jJMx2dmWkMSBc657Zlxc+4jNt5/8dZ5PPjirjGBQ9lyGTYjEelIafMR9KqL5b5vxj15q7adroh845KT2DZYpimlcc17lrBjyKRseQB8/dENNeFofVLlH/5kERVBpL0hiUD0pq/JOpbr0z1o0mCozKrTq1MrAY7n0ZzS6C/a6HKiWso8RBZBEkUgqPpUONE0jBDg+iFJVcSt2n+ndbk2gnGYlwtRiDQi2aSKKgsoAmwZsGhKqRiaRN6MApuQkEZDY7Bk81pPkRNmZrj1sc08s3WI6y9YwZd+1sVXzl9WO4f7nuOkJtf8KUamqYZNhzkNSa48ayHlauruSBbQ9y87lY9977kx+4nFmscO8RWKiYk5PA639kIIDapEg7pXgLhu0Jxwzn3ExvuHz+3kg6fNGaOluPGCFXzinYv49990j9NZXHHmQnbmzFqn98PndvJ371jETb/cMOZNOVe2kUSBq37ySk0bsLg1w9xmg8UzMxQqDl+7cAW9BYuZdQmCMKSv4GA5ASEyAkKtqqYui7h+yEDJotFQ8QPIV1xaM1Ub74LNjIxOGMKOoQotaY20LpLWI4+MobJLgyGQUGWCMBJSarI0JVVKJVEgqUmYtk82KdGbd6g3FBRZwAtCZAkakir91UJoQRDi+CGLZ6b5+i8jbcnV71nCd57cXDMom2z04dtPbuaS1R3c+7vttWmqlR31JBWB//P9rnFt6y1asVjzGCa+QjExMYfF6JLpMDVpgJOJOkdsvEdrKToaEmwfqrA7Z/Ldp6PpjLZ6nRsvWMGWag2Je9Z2o8pCrcppT97i+7/t5pY/Ownbi2y2E6qIG0BHk8HdHz2F/qJddZf0eX57jjCMXC7rkyrDFZfbfrWZD75lLoosRFVKERmqONQlFAxNwvED8hWPbEImCMELAlK6zJDpkNZlZtdrOF7InqJNc0rD9X2CUKJk26Q1BVmK9BgQRrU6kgrDpoMsapA8vMDCC0IKFS8y00qICKj0FqKiYGXHI6HKVNwoxbRkR54VGV1CFEUuf9t8FFHkm49vHBNcRGXNI8vz5rRGoeLSVp/kjM4WAL7wvmWEflDT3/RXjb5er8T9yPJYrHlsENt0x8TEHBav52dxKExkBb6vjfeIlmL7UFRaPW/5temM637WxfYhk2/9ahPffHwTw6bDxas6qE/KfO2iE7nirAWsWd7Gtf/1GgNFG1EQ6Ootk1Ql1u0uMFByuP4X66u1K2y+/suNfOXnXdz4yAZEUWBlRx0fOG0OSU2i0VAJw5Cy65PSRBRRJKnKlJ0o8yNf8ai4Pg1JNUqfrTpv5kwPVRKZmdGjwl2KFGkdqsZQApHrpx9E9UWIPjrlsgLT3hsspRMSKU2pprtGwtCUJiMQMmR6iIJAS0ahLqlw+dvm890/X017vc5lpx/HnR9eRb2h4Ach/686SnTNT1/llsc2cfOjG/ndtqFRAYVH3nK47tzxNvLtaeXg7eVjpg3xVYqJiTksJk0VFYRo8v4gbMFH6zJOa98nuyQpI72zc5yN933Pbq+VUh+hJ29x37Pbuf6CFWzqK7KgJc1XH1nPp84+nhsfWc+a5W0IAqxZ3sZdT29lzfI2vvn4Jpa3Zfjrty9gT77CF9+3jJLt0ZxSufujp9BXtGk0Iu8ILwhJagKz6iR2DfkMmx5tWR1Vgd05m6Qq0V6vY9ohgS7jeFF1zsGSQ3M1s2Oo7GBoIbIooEjgBTBYdmhJaaiSQFKVo8qckoooiJQsm5Quo0xB7Y/RaDIU7ai8+ZZ+k0ZDoyEpgSDQmtbYmbNoTms0JKPS5/f9rptLVs9l20CZHUOR0+PMbILuwTL5isesugSfffdivvyzvcLbkcyeVe11bB40a9dwTmOC2y9diRCGezOIgoPPLIqZPsQ23VVim+4jw3RuX2zTfeDs91wJ8Ovt+ZoPwejO/tZLTjqwKZAD1WVUA4+twxXCEHbmTEzHZ3adThAKXFO14R7dhotXddT+f2z9Hs49uZ1rH3qttt3n1pzA7U9urpVin5nV+cu3HkdrVicIoGw5tNYlajbbsiSgSiJ9hQo7hy3aGwxCQhoMFT8Icf2A+qRKsVpbY0ZaAwGGyg51SQUBMN0AUQhQJZm+YuRZIYoBhCK250XLq3qG2fUSPfmAgaKDroqkNZlZ2egt/nBsukeCpJQmIQBl10NApFBxySYUZCkkDEWKtodp+zSmVIqWiypLlCs2DalE5GmRVpFE+J+Ng/gBPPTSLq44ayF9Bbsmwnzg+Z01EeZoW3V4HXv3g+R1v9MHKiieRkzHZ2hs0x0TE3PkCGFGWh2TiXHP2m568tYBi+sOWJdR7QA+ef+L4zqmT7xjIddfsII9+QrLZ9cxWLK57rzlrO8psGZ5Wy2w+NHzO7jpohOpuD69BQtZgA+cOoev/feGWmZCQpH58e93cOlpx1G2Pbr2FOmcmWbYdNncX+LlHTkufcscFrSkcH1IqBKSCCICZTuk4vokFYl8xSUkElimdYXBUhRY+EGArkmICFGnLsBgyasGJhBKoFUrkpo2BEFISBiVWJ+CSyaM+Vkgb9losoIigaZIDJsuLWmVEGraixCflKbQW7BoTutsHyqxbchiYx/MzuokFImWjM4//+kJ3P7kJs48vrVWxnxEtFm03TdOhHm4guKYAyIOKmJiYg6brK5y51NbDllctz9dxr6dzWTbFmyfQm+RWx7bxGfe3Uk2oXL9L6KpjkS1Mqrl+cxrno8gCAyXo7RGLwhYXhVn7hgyUWSJu5/ewvkrO9iTq/CtJ6Lshe4Bk/YGnf81v5GFLWkyCQUBgZLtoisSfQWbppTKrKzOcMXF96NKpEOmS0NSwPUDFFlAEgQEIAgEBk2bmRkdBJjTkKBo+RQsn4QqkzUkHD/E0CBfmdopj5Ao+JMEAUMDSdIoWh49eZdGQwUCvACSqkhLWiVXiUq7i2JIvaFQtD1aMgmSmkJaU6h4kTOoIgl84eHXWLO8DVmEOz64ivV7CrRmE3z54XXceMHyN0yEeSQExTHjiYWaMTExh81EwsqDEdeNOGSORldEUroybtsRDce+24rVURJdESlaPsWKE5lX1SeY02jw8q48t/1qE0XL48p7f8+1/7WOT9z/IjuHLW78xXoGSjZJVSYMQq58RyeLW1M0pjWuPWcpS9syzGlMktG1mkFV3oxGIRJqVGhMEaM2WV5AxfEJERCEqDhXf8lGVyRmpHVCwPYiyWV9UiFXcQiCkIGySyj4zMho9BZsCEVkMcR0IntuLwhRJBF1ClJKYa/cpa/kUrI8ZFGkMRVlqlTckDAMCQIYKDlkEjJBELCpt0QQVEdMqkVbRFHAdn1a0jqaBJ9bswRJhLzlc9VPXsbQZL788Looc0US3jAR5pEQFMeMJw7PYmJiDp8J3DIPRlxnud6E3hK26wFjA4vJ7L6TisRdT2+taSku+6PjUGWJq0fpLK5es4T/fm03N110Io7no8oSXhBw1uJWShWXkuNTb6j8btsQ9z+7E1UWuHrNEl7rKVBxA36zpZ8LV3Vw+xObuPS0uQwULWbVJzEdnwZDxXQ8JDEkm5BRZRHT8SnbHo2GiuN5iIKM5QXIUmQ+NWy6kagVaErJlKyA3mI04qHLIiXbJZuonuLqyEJan7JLhgBkE9G0TIjAUNml0dBIqZE9edF2SaoSsigyVHaYVZ8kpcps6C2Qs3yWzsowWLIQBJGtAyVmZHXu+Z+NnDqvGUmEz7xrMbf+alOtzL0ovHEizP0XyIuZKmKhZpVYqHlkmM7ti4WaB86RPlf9ls9f3/t8LSsjDCPB36RCz6rgrqcYZVroisRwxcFQFfqKVrW2RVTHQxJE+qqCQrNqGd2a0Xmlp8DcRoP1PXnylj+mFshHT5/Plv4S85pT/Pj32zn3pI6aBqMtq6EqMgNFi7lNKYqWR0qXUasCTj8MqLghohCiyVEGR1KVIrdM02F2vY7lBBRtD8sNaE6puEEQaSbCqK0tGQ1ZDAlCkZzpkE0qOF5AyfJoSmm01R2+ULO3WpI9rUnsGLYiPUfoIyIyULJpMDQMTWT3sM22oTLLZ2cJwpCK45NQZEq2R52hYLsBZdtjsGRz3+928O5lM5nTaJDSJCw3YP2eIl4QcFyTwQktqTEmZ1PN6wmKj0VNxXR8hu5PqBkHFVXioOLIMJ3bFwcVB84RP1dT9cAfo+5Xmdec4r/X943b76Jmg3Nue4b6pMp5J89Gk0VObM+yua9EY1onZzrMbzYoOz6aLKJJ0Zt6WldwfJ+ULiMisKdg0ZLWyegiRTvAdDwMVaZou1HHa3lkEjKyFGkoLM8jqUQGU5Yb0JSKPC5MJyAIAzK6QtnxKdoeDUmVtCahyFCyAkq2T9mJgorZhxlU9BZDyo7PcNmhJR29wXtBQG/BoTmlYXseSVXB8nxyZuRVkVAjh9Cc6VKfVLBcn+e25/AD+M2Wfv7yrQsoOx7bBsv8an0fa5bPZOGMNINlh6yuIEuwtMk4oh34wWV/HBupqtPxGRoHFQdAHFQcGaZz++Kg4sA5KtfxCDzw6+qS5PLm+P0yPoi5+eITcbxgjIfCv7x3abWzV8mbDqoisbW/RGNKoSWTwHR8LCdKNdUUAc8XatbWluuhyhKaJFJ2fEzHx9AkFElAFUXy1SJhZcclm1CxXQ9ZlGqppJbrkdYUMomoAupAySGly2R0mRnV2+pQg4qe/NggJaGIKDLkTZ98JSpyljOj1NKUHmWDFCouDYbKpr4SRcvDUCXaG5K1CquKJDJQtsnoChXHI6UplGwXRRJpSERTWL1F+4imck7n582hMh2PKU4pjYmJmf4cbNXTw9zvhHP7UFsWCgKf++krdA9W0BWR2y5dyc2/7OL8kzv45P0v12qDLGhJYYTw0o4CcxoNVElkqGxTn4wCA0kQcP0o8ChZHvWGQggYmkhdQkKtliAv2QGGJjArq7OnYFGfVJElEUOFoXIk1pRFYUpSSv0Qyo5HUpVQRNAVKFkh+WrVVNPxSOsyCSXShQyXXRKKiCiEtNUl6C/a9BVtrnnwVS5Z3cGsrM6ld/12zGjQ4sYkGMoxO+0Qc2jE2R8xMTF/mFSDjcWNySjgCPcuazJUPva952qGWJYb8Pz2YZ7tzvOD33bz7Q+u4rPvPp7VcxrQZJEwDFk8K4MkRsLHESeIkKjMeEpTcDyfmVkNgSiICEKBLQMWXhjw/9k78zi5yjLff89+au29O013OtCkUwkkIZCwTgY1UQQHBVmUGRlQUe7MHSRXHZVxRK474zajgiLKqHBHQERFGEQYdoQgYQtLqCQkdNKdTnqrvers5/5xqivd6U5ISAc68Xw/n3zS9dapc96zVJ3nvO/z/H6KJKErArIosj1v0BzXMByXiu3iExiAJXSZQmV6rM/H+iYg4AOWC6YXeHzEVYm6SGCzXrZdTNtjuGAQUSXW7yghiQJF08FwPM5a0sHhTVH+pSp8NnasPnP7WoYqgbvr7ko5x94PObQIg4qQkJCQXZiq/NCrlquu7c/z2dvXkilZPNU7ygv9eZ7qzbB+ewHDcXD9QFVTFoPEzVzFBkBXJLblTCq2iywJCAjoqoAiShiOi2n7eL5PUg8ULiuWCz6MlnyGi0HZY2BLvv8/257v47g+mixiey5l08OwPAzbpWJXjdCiMqIgkDds5rcn2TJSYrBgsj1bob1akjK/LYEgCLXga4zxpZphKedfFmFQERISErILU2lh3Pl8P1eeeRS6IjKQM/jPxzczf1YSVRJRpWDZr9+dZnuuTFKXGS6aCAI0xjRGSha2GwhHJXSJpC4TUSR0WWZ73kCTRBKRoIwzV3HxfGiIyYiiELiHRhRMx8PyPAx7//dPEQXqIjJFywZfrKqISiQ0ueqEKoIPA9kKwwWTouGgKTKqJHLtw6/y4rY8P310E44P6wbyU+qGjJVq7k5XJCzlPDQJg4qQkJC/LAQYMhzWjZQZMtwpda9bItIkB80xie9vnncM1114HF9+30L+7Z51fPe+9Vzz4EZ8Hy79626iqoLt+tVpCgHDDio5ylZgKmbYHtmyQ8lyUCSYldTIVWwEJHw82ut0TMclX/ZQJIHGmBq4xjjeSwAAIABJREFUhioSvu/juN7kDu8jY26njgOqLDC3VcdwfIaKFo0xlT9vGuKZLVkkSaSrKcbm4SLf+mOaax7cyAeXdQX+Hit62JYt86s1fVy+omfCsfra2YtqOSr7K4wWcnARntWQkJC/HKZIGrz6nMUsaI1Nqkz4qzlJrrtwKc9syeB61LxDvnPvK/z7+UswbYf/+MASsmWLmKaQqdgkdRlNgdGig+MF8YoqB1oTUVVGU0Qsx0UUAuOuWUkdSRKoiypULJdgwMOnUNWjyBsWPS0alqsEuhIJjcbY/j8LOp5f8/RoS4gMFWFWUqFkSrgeLOxsoC6isqNgYDoesiTy6dPm0ZLQSFe9VG5a3cu5SzvJlC1uWt1b834RBVg4K74zCXM/hdFCDi7CoCIkJOQvhqmSBq/4zVouPbWb79+/cWJlggdHN0cQgKe3ZGqmZJe9o4dP3vZcrSrkRxcu5aKf/ZmP/XU31zywkfY6navPXcTW0TItCZVMVefBdFxUWcRxfXRFwPV9TNdD9sF2PHzfR5cDDQtFFFEkAV1WGSy6yKJAMiKTKdvIklBzKX2jiIAsCpiux468iI/LcBFUSUAUBOqjCj99dCP3vjxcUzf9yaOBtfxFJ8+p+bzc+Xw/V515NF+66yWufXBjNUhbBMC6kfKEIO2AVPaEzDjCoCIkJOStp6pRsa1gEtMkGnWFRm36tQx2lzTo+Tv/nmAy5cFRTRFaogrDJYuVqZZaQDG2/LNbMrV1juVbrBvIIwoCn7t9Lf/0tiNRRBHHA9/38QHX8ziyJUrR8MgbNu11GhXLw3A8BEHAw8fzIaYJ1OkSWzJubWShLjINiZoEoxWaJBLVBExHQvd9HD84Fo7ncVJ3C2cs7EBXJK6+Zx0DOQNdEYkqEp99d4rWhI4kCtzw2KtcsrwbSYSj2pMIAlz6y2dqQVdYPvqXxQELKlKp1H8CZwKD6XR6YbWtEbgVOBx4DfhAOp3OpFIpAfge8B6gDHw4nU4/U/3MxcAXqqv9ajqd/kW1fSnwcyAC3A2sSqfT/u62caD2MyQkZD+ZYkpi1coeuptjHDcrDowXxdJoiUoMlce93gchpd35P4yv0jRsj95sBeqjk56y142UJ1U6jFWF3P50H/98Wopv35vmF4/38k/vOJKLTz6c+riGLAWBgk/g/AkiGwbLNMVUmmMaI0WbmCYiCgLZskVbQkMQPFxPYKjkUzYdmuJBboWuCsTU6U2HG8ga1EXVQIJblXFcn4QukYjI9A6X+cxp8zEcl83DZa57ZFOQqPrhpTgufPiUbkqmw1DR5Et3vkymbHHJ8m6ufXDjxCAtIk88jwdIACvkreVAJmr+HDh9l7YrgPvT6XQPcH/1NcAZQE/136XAj6AWhFwFnAicAFyVSqUaqp/5EfDxcZ87/XW2ERISMgOZakrie/dv4KWBPEMVh9V9ec65fjUX/XwN51z/BA9tzvKPtzxbe/2nrXmyjjs58VKA3tHyhPapEjBXrezhN8/01fqjKyIvbitwzvVPsLovH6yvmtypKOJuq0IyZYsbHtvMZ9+d4qr3HsWRLTEWd9Yji6BIIp4XlJoKgkjBsOmsj6BKAhXHxfF8ypaLQDAtYbkerge2A5okospBDoauSvjeNNqgC0FQFNVkFFGgIaaiSSIV22NrxuDK373Et+5NkzNsvnPveq59cGNtxKJkeqztz3HZzc/yud+8wLfvXc9AzsCwPYRxXRwrH931PNaObcghxQELKtLp9CPA6C7NZwG/qP79C+Dsce03ptNpP51OrwbqU6lUO/Bu4L50Oj1aHW24Dzi9+l4ynU6vTqfTPnDjLuuaahshISEzkD1NSQwUzEkBx5V3vMiZiztqr6/4zVo2Dlf43G9f3HmzEoPRjzOveWziTYwgAfPHFy7l8pVzuewdc4mpEplyoJkwlj/wm2f6Jog0jd0QP/Wrtaxa2TOpKuTWP2/hkuXdnL+sk+aEzmsjJUZKNtc/soGoGjiTjpWeZks2UU2mbNk4HhQMm8aoSlJXkERojCn4PmTLgeaFD8hi4LuhySJJfRrvxH6QWOl6XrAt36M3U+brd6/D9eD8ZZ388EPHoYhMOEaffOc8+rNlJIEpy0XHj/yMWdiHAlh/GbzZJaVt6XR6oPr3dqCt+ncHsHXccn3Vtj21903RvqdthISEzEB2p2MgChBVpSkDjl2fhNdtz3POcZ21m9XWgj3lTayvZLMxYwA+75jXwpymKIbtctk75vLNcxdxyfJublrdy0DOqH1ufGAzkDO48YleVq3s4Qd/eyz//oEl3LpmC2v789zw2Cbimsw37l7HzX/egiIJvGN+O5+7fS2vDhZwfB9VEomoEvmyjSJJQCBCZboeCIGjqudD3rBJRmQUSaBOB0GojmA4HkVr/+cMxo+ImLZPe51G2XJxvWB7V5y+gCNbYkQUCUGAbNnmh393HD/80LFc9o65/Pzx1/jF4700RtVJQdZXz17IXWv7a6+/de5iTNsJBbD+QnjLEjWr+Q8HdEZtX7YhSQL19dHdvCfu9r23mpncN5jZ/Xur+rana22mciCPVdLz+c75x/Dp256fkFMxtzVOW1J/3RwIXRGp3pOB4GY1WDSnvIm9OlziC797EcP2uHzlXK5/ZFNtuctWzK1VNYxfd0xXJrQN5Az+7Z40P/vIMiRB4DOnzadkBroTXU1RPnRiF11NMf74wgAfPLGLb7x/MaNli7gm4/gemiLSFItQsTwczyOqyowULWY36TU1TkUMpks8H7blXEwnCKSE6nRFoIDB656TXa+1kVIBCMpc66IKmZKFrogMlxyiqkxEFdiWFdiaKXHLU1v4x7fN5doHNrBi/iz+9Xcv8vn3LOCaaq4EwHWPbOIjp8zhhouXYdoesxuizK7XWdJZH1i4JzRm10fYmq1MeR4Pa4hO63U1k39v3igH2z69blCRSqXagK8Dh6XT6TNSqdRRwMnpdPqGN7C9HalUqj2dTg9UpzAGq+39wOxxy3VW2/qBt+/S/lC1vXOK5fe0jT3iuv5uneBmokvcGDO5bzCz+/cmuZROatvTtTZT2adjJbDPCXknHJbgN5eexEDBJKpKNEaq1R/At85dPCGJ8ytnLeSaBzcAO6crbl2zpTYloisirfGpEzK3jJZrbZ7PhPdvfzoQcfr+AxsmGF816NKU63ploEBTVCERUenPVXA9+MUTL/OPb5vLd+59hd6RClsyZT592nxEQaBie0RVkYrlIIwZemkyouDTHFfIlhxGqlbkMU3A9yU0RUAgqBxxKj6iIKBIO03Fxp+TvbrWArNQTMdjpBgkhHbWS/RlIVOyUUSVhpgCQpSvnb2IkuXw9lQbN63uJVO2GMiWJxyjTNmiNaEzr16vneNCwaBOhLo6DYB8vkKdNPk8fuvcxdRJTOt3YSb/3uyRPXxnZuI+TXWtjbE3IxU/B34G/Gv19XqC6oo3ElT8HrgYuLr6/x3j2i9LpVK3ECRl5qpBwR+Br49LzjwN+Jd0Oj2aSqXyqVTqJOBJ4CLgB6+zjZCQkAPNG3Wk3FXHAECCzdnAbvzGj55AybBpi2u0xGRaEwt5epwo1QXHd3HjE7217c1OKJNuYleeeRTXPLBxwmbHBwsDOYNb12zhpo+eQN6w0WSJqCpRtFxWrezhe/fvDDYuX9HDjU/0osoCn3/PUcxvS4AAca2LXz7Zy1lLOki1xYmoMlf8Zi11usInVvSQtV2SEYWCaZPUVcAnpsuUTJdM2eKwOh3H8yhbUDJNQEUUfCRBJKkHJl/BVMP0zVyXrGCaSVckSpaFKIgI+BRNh2/8YV2tNPST75xHU0Ll+/dvqJWQLu1q4KjmSFCjuidCAazdc4i5uAr+6zjepVKpp9Lp9PGpVOrZdDp9bLXtuXQ6veR1PnczwShDM7CDoIrjd8CvgC6gl6Dcc7RaUnoNQQVHGfhIOp1eU13PR4HPV1f7tXQ6/bNq+zJ2lpT+AfhEdbqjaaptvN6BsG3XD0cqpp+Z3L83aaRiUlbdnq61mcreHqshw+Gc61dPeqqv6T7sLTI8uDHLF3//Yu2H9svvO5o5TTrdycDMaueTnYokClVFzHE3KwFyLmzLlInrCmt6R/nu/2yo9a29Tueik+dMCBauPPMorn/k1VqQkilbfPXshXzn3vV86MQuZiV1tmTK3Lamj0zZqo2SfHBZF/e8OMAZi9o5vCmG7wfBwqPp7bzr6MMYLdkkdJmYKuH7MFK2aIgojJbtwH5cEmiIyRQNj5LlUjFdYrpETJWZlRTYknFripqHNUq1p0HJlmqHbG+uNVdxAWrr66jTEUUYKVloskRCl8AXGMgb1EVkLMfj+b48puNx19p+Lji+i6LpIgjwV92NzB03QjETmMm/N7vj9b4zM3GfprrWxtibb3mpeqP2AaqjA7nX+1A6nf7b3by1coplfeCfdrOe/wT+c4r2NcDCKdpHptpGSEjIgWdPjpT7ElRszlq1gGJsHV/8/Uv87MPHM1RxaqMa49fZ2FSddx4nDz2nMUqdCAiwrT46YcQhU81z+PcPLOGlgTy+H1Ri9I5U+F71afzaBzeydbRMpmzx7XvX016nc85xnXzoxC6O6aynZDmctaSjNj1wBvCjhzZyxqJ27l+3nY8uP5I/vTqCKom0JlQWtCexHB/fB9f3aYwq5AwbTVbYljWJKjIVyyURkanYDpokUrQkRAHqowojJQtRVOmsl5gOHM9nVlJCVTQG8xYVW2DrSJkdBZOj2pN86a6XaiMVY6MzYyWl71nQOqMCioOV6frOzBT2psefIphSODKVSv0JaAHOO6C9CgkJOSjZnbjUvjpS7shPnWg5XDSxNXnff2x96GmOsi1b5lvnHUO5Ktb008c2cebijprE9CXLu2vbGkv8/NWaPr5y1kKuvONFBnIGNzy2ictX9PCFO17g48uPYMnsegBUSSSmSlz6tiPRZZEls+eTN2yOP7yRfMWmLanhV3MpBEASRXRFAEElU7KI64FraEtcDazQHR9BF/CriZm+7wfJmtMs7lAxwbJd6iIKiiSiqRLLDm/EdoOASRZFelrjE1Q1V63sQRJDkYnpYLq+MzOF1/1mptPpZ1Kp1NuAFEHCcTqdTk+D+W5ISMihxpgj5a7zw/s6fz4ruZsf2rhGnfrGntIbNYn2ugif+fXEKpOxXIzLV/Rw0+re2rbGZoYzZQvTdvj3Dyxh3fb8hDwO14Nb/vwaf3fiEeQqNg1RhWzFDsSqDJuoEpSNVmyXVwbyHNESI6ZKKJLIcNGkMaZSMoPyUU0WcT2J7XmT5rhKY0xGFCGhQaYM+YpDS0JDU6ZRCUAAQYTRkkMyomK5Nm0JnbJtk9AUTu5uYrho0RBVuPSvu5FFkS2ZCjc+0csRzTHcukiojLmfTNd3ZqawN9UfEoF89uHV5U9LpVKk0+nvHuC+hYSEHGxMU0Le4fUqX37fwkk5FaLg0RLR3tiP7RR9k0SBo2cl8AWBL/7+xQlP4mPBxqfeNQ/Xg6vvWcf5S2fTWq/x5bMWgu+TNxwuPOkIJAHa6zRs10eXJQRBoD6i4Pk+UUVGaxQxHZ+S6aBIEp7v0RRXMW0P0/FJ6IGRl+f7SKKA50PZ8nBlMBxxrPsIgDadI+I+KCJ0NGgYls9w3mFbtkJHfYSnBjIT8k0++c55/PzxV2vHyHZ9zrn+iYM6qXBGcIglse7N5XknYAAv8Po5viEhIX9J7KYUbr8dKR14x9x6bvzoCbUExZaYRFx6g0/F4/qZ0BUUKdDebtQkGtUoCPCjC46t/agbrsecpijNca1ajeHy1bMXUTRsmuMakiSwLWsQU2Xuer6P0xd18ORrI0QUiaQuB8voMrossS1XoTmuIQguTTGNiuNSNj1kUSQZkYmqIq4P2YqNaXvUVfMpkhGFiCIGwldC4FKardhENIGEtv+jFYIQ5HVUbKjYLq4blKsu6qhDFD3ieh3XXbiUoYJJfUThq3e/PCHo6suUJxuwvc6xDz0/dsMh5OK6N0FFZzqdXnzAexISEnJwcaBL4Rw4Iq5yRHzc3PIbDCh27edY1cY/vytV629LJPg53FYwSegyn/rV85OmX275+ImsHyzxxTt2jqB89eyFbMuUiSgSnQ0R6iMq6wZyuD40RGQ6G2NkyjZ1URnX88H3aIwqjJQtBAKjsYrlENMUSqaDKAhEVImhgklTTCURkXB8v+ZSqsvTM/3h+yAKApIIMS0Q4IprCrIEQwWXkmnhIXDlHS/SEFU5f1knXQ1RhoomUUXiukc2AVMbsO3p2IcjG4c2e3N1/iGVSp12wHsSEhJyUDGVEdhM9HOYqp/ff2ADZy7u2Nnf6s3vnOtX87Ebn+azt6/lqvcePUF++itnLWSkZHHtg0FlyGUr5nLJ8m5u+XMvyWgQ+Pzi8c2Yrsth9VEaoyqZioNh2yQjCsMFC4RAzdIjSLgUBCgawZSIJASGXmXLCYIN38fxfFx34v5MU0wBBNMpqgR9GQNVkoipIttzJn2ZMvmKy81P9vIfH1zCFaenWDArSSKiULHdmlPp2LEZb8A2au00dztYrpGQ6WNvRipWA79NpVIiYBNch346nU4e0J6FhITMaA6WUrhthakrSQRhov/E+Jtf70iF6x7eyLfPOwZZEoiqEq8M5NmaCazPr31woojWx0+VaIjIrFqZwnJd2pIao2WBwxoiJDQZ27VpiWs1bYixAg7fh/qoRFRRqNgeluNhOT66AlElEN+yHHA9v1aNYroQUabv+AyXbBoiCq7vUbEhoor0tCYo2y6rVqbYminx40c21bQ4Tl/YPsmA7abVvbWA4dJTu/n+/UE1zbfOW3xQXCMh08fenNXvAicDL1T1JEJCQkIOmlK4mDa1zLbv7+zvVIFH70iFV3YUmNcaJ1e2yZtu7bO7rqt3uEhjXON796f5x7fPJVMeq/yAbMUiosiMloKAwnBc8kYwlYEAoyUXUZCoj4poiophu9iuhySJ7MibtNdpyKJQq0aZzkJOH0hoCkXTxvMFVBmSmsq2vIEiCvSOFElEVC4++XB+8uhmBnIGQ0WLS0/tpqc1wSvbC5MM2LxqPw3bY+Ng8aC4RkKmj70ZSNsKvBgGFCEhIeMZK4UbP0VQK4WbQTTqyiQnzctX9HDX2v5af8cCj/GMOaW2JDRiuowkwJ3P9/PJd86bsK5g3RL//fw2/vfbe3B9SOgSFdsLlDU1mYgiMrtBC3w7BAFRFHA9n+FCIM3t+bB+sEKmbJPQJSRRJFu2qY8q1EWF8XpeONXpEIn9F8ASgKgKubKLJAiICEgStCd1HM/nyNYE/722ryYWBkGJrS5L9GfL3PDYzmmQseMxXqT5V2v6+NrZi2b8NRIyfeyNTPfPgW4CKWxzrP1QKykNZboPDDO5f6FM996z22MlTJTLHrtZHLBs/32sJKivj5LNlXlme5GXBvLIokh3cwxFFpid1Gule6OWy8OvjvDd+9ZP0LBoTWr8af0Q717YTtl22Z4zuOWpLUFpaUKjNamzPVumYnvUR9WgQqNs0ZLQMSyPRCTw1BABw/EZKZk0xzVKpk1Uk5EQKNsOSU2hYLk4rktMUxgumjREVaKqhO+7eL5IwXQwLI+WhMphdeIEiW54YzLdrQmNhpjE1oxBQlOIyCJDJZOEpjCYN+jPVuhuibN1tMzc1gSjZZPGmMYXfvcCluPz9yfNmWDANlaKOz7f4o5/ODkIoEoWcV3BtB3qdPWAVIHM5N+bN8pM3Kf9leneXP2nVv+FhISEBExhBHbAsv33o5Lg8IYISV2mbLm0J7SdOgDVzzVqEnMaAxnvxqgajC6oIt/7nw2sHyzy3iXttCWjdDREOPqwJBXLpSmmkjdtZjfFKBgOs5I64KPKEj4ezQmVkuUyVLCoi8hIoogoCFiOR0NUxfV8ZElAR2a4bNEcVSlagQ9HU0wlqsoIAmTKPkXDpCWhkmoNfoLXbzdZ0LT/dtgCENfg8EadDYMVmmIqbYnADyRbkehpS2B7Pq1JnXUDOSKqzA2PbuaC47v43v0buGl1L5ee2k1XQ5S8YQd26uPyLb517uKa2+yrI2Uu/a9nwiqQQ5y9UdT80pvRkZCQkIOf3WX777Oh2DSt2/P8KQORls7JeeaHN0Sojyr86dURWmIaDbEYF51yOI1RFR8fQRTwHI+84dAUU1EVkQQKo2WLhqjKcMlEkwTqoxqe51F2PAqGHWhT2A6K5NOW0PDxsFyf0ZJFY0xFkXyaoyoFy6VkOtTpMrIoYLkOAiK+H1iei8LOh8PpzEkQgWzZC8pdgZJlIyCiSkFpa77i4AOuDz986FUyZYvzVInrLlzKi/05KrbHDx7cwAeXdXH3k71c83fH8cpAnlO6m5gdV8APTLMO1HURMrPY7dlMpVLXpNPpy1Kp1J1MEUum0+n3HdCehYSEHHQcyIqQ3a17oGDudjpka7by+jezcSMgH/vr7po9+uKOJB879UhGShZdjRFsx6VsOiT1QITK84ORhvqIgmE7NERUbM9jIGcQVSVkSaA1oSEJAq4noEgi23IGjTEVVYKWhIosBNMaZSuQwpYlCRGRoaLF7IYIJdMlV3FoS2rU6TtzPlqi8n5JEcpiVUyrbIPgIwkCnQ0RHM+lYkFCF/GQKBgOMU1GEh1SsxJ84cwF+B5szZS55oH1XLL8SFzPZ3HHAnpHSnz4lG427Cjw7XvXc+OHl0FM2eO5C6tADj32dDYvAi4Dvv0m9SUkJOQg50BWhOxu3c/353aWMJ67mHktMUbLFpois2M35aRjZaRj8/zjA4+xbaztz3P5zc+iKyLfu+BYTNumLRmIP7XGNRzfRRZEKo5HxfaIaT6e55HQZTw/UMwsmg6aLGG5PrIU3Mxdz0eQRCzXw/TsIHdCkTBdl0LFQ1ehNaGhK5Ape8iSgO/7lCyfmBaMVgyVnf26GbueT9l0SegymiQiiAKjJQtVElHlYBuqFByHuCagySKSKFGxXOqiCqIY5RMr5+G4Ht/7n42sHyyyamUPI0WzJm8e1xXWjZRpjmk0xw+OSqGQ/WdP1R+vAqTT6Yen+vcm9S8kJOQg4kBWhLREJb5y1sJJlRe3rekDdo5CPLBhmGf78vzdDU/y0kB+yqoOF4Fzrl/NRT9fw0Mbhmo3u9uf7pu0jctX9PCTRzZSMD0+e/vzjBRMNgwWyJVdipaLpogkdYnBgklDXEUWBUzHw/XAsIOqCgBB8GmKqVTsIFnS8XzKViABHtVFNEkiqkkYlkfRdMhXPBK6RFyVyVWc2vQEUAuK3ih+dfuqJBLVRCKKgCoJ1TYJ34f+bDCqUjAsdhQsPnv787w8UOCp10bRZIk7nulj/Y4il77tSH584VIkAa57ZBOZssXX3r+IT972HBf9fA3nXP8EW7OVg6JSKGT/2dMZbUmlUp/a3ZuHWvVHSEjINHAAzZGGyg7XVNUsBQFSbQm+fve6CSWNhu3RGFW56s6XMGyP25/u4/IVPRMqFK488yj+750v1gIJz985OjGQM7h77Tau/bvjeL4vO8GR9NY/b+GsJR20N0So05VaaWXZdIioMlHVp2x4WK5LTA0qOA6r0/EAs+whiSIJTaQuIlO2HRpiKnlBIFMJTJ+zZRtNEWlJqggIlC2nNv1QF5ERx1mNx/X9V78Sqg6lecMjW7aoj6jYpo3leuQqNrOSWtUbxEcR4epzFzOYN2lLakgiHN6SoLMhytf+ex0XnzKHguFy7tJO/KpJWe9IpXZOVt36HHf8w8mHjGlWyO7ZU1AhAXGmV2slJCTkUGesIiQiM1RxWDdcnpbS0uGSNUHN8rIVc2uVBmPoikhUk2sBw0DO4KbVvVyyvJsF7QnW7yhQMOzaDQ+YFHg8sXmUMxbOYvFhdVQcj1N7FqNIIm1JHVkS+fWaXs4+touqthV5wyGhKyQ1hf6cQVtCoy4qIYkajufjEVR77CiY6LJIXJPJeQ5bRso0xzXaEiqm7eMDcU3Gdn0yJZOGmEpDTGG0ZBPT5AnupKbtAG88sNBkkcaYWgsSYqqI7Xm4vg8+tCc1PB9yhoMmi9RHNQpGoJuxfnuBkuXyw4c2csnybjJli4Lh1s5LoKR5zITtGbbHjkJQsXIomGaF7J49BRUD6XT6y29aT0JCQg4dDoCR1K45Fbc/3ceqlT0T7LlXreyhP1uesNxAzuCGxzbx7fOO4fv3b+SyFXMnvX/rmi1887xjeG24RE9rnKvvWUfvSAVdEfmX0+fTEJdpieuULIePLZ9L0bKJqwqaCm1JnYGcQUtcI6aJSKJApuxQqDjEdRnX89BkEV0Wg6kPAeqjMposUrZcMmWXhC4xu1EnX3EZKpi0JjUEwUMikOoumy5RVWLsGa9uP0cqTMdjpGgFAVBEomKJbM1UaEtqaLLItpwZJJuKQaXJpuECm0cM7lrbzweXdXHrmi188p3z+OWfe7nqvUdz3cM7A4pVK3sY2EVXYSzHIuTQZ09BRThCERIS8oY4EKWlY/kaY+vNlC1iqsRPLlqG73o0x1V6Rytc/cdXJk15XL6ih75qsDHVlMgHl3XxjepUSnudzodO7GJeW5y4pjBSMtFliTuf38qZx8ymL1thdmME0/EYzTrENImOeh3T9VAkiZGSRXNcoT6qMFgwaU8G0tw+oCvBdInn+bheIGRVNiUKpoPluIGxUnV/2xIKw0Wv9nr8D/L+Vn8IUC1b9bAcEdN1mJXUsD0Xo+IFQY8kUrRcsobFnKY49VGN5XObKNsO3zx3MekdRS44vouGqMxZSzrwfBAF6GiI4Pt+LXAbO/6ZioUuiaH1+SHOnr7dK9+0XoSEhBxSHJASQh/mtcS49NRuPD8w4/rRw0Fi4G8uPYlXh8t8+740Zy7u4MjWON8+7xg2DZcwHY+bVveiygJfOWshV97x4gTRpo6GCFf8Zm0tN2MgZ3DNgxu57sKlXP2HdXzs1CMp2w5nHtOJ7bq0JXVGSxYl+93kAAAgAElEQVRxTaYxJuP5AoMFi+a4ioWL7wcjAVFFpjWpkjUsmmJaUBXigS0FEtwxTaZguOhyIIq1I2/THFdpiCpkSza6LKCIgXS2h8+4PM39rv4Yn6ipygJ1MYXtWZeRokNjTEWXJSRJwDUcLMdnfbaAIgpsGCxy/7rtXLL8SBqiKoc3RTFsh+PnNDJatmhNaOTLJtc+tJlLlncjiTC3NcF37n2FMxd3cMNjzwYjVrOTDJUPkOpqyFvKbq/KdDo9+mZ2JCQk5NBh2ktLq/LcvdkK379/46S3BwpmbQTj2gc3srgjyd+eOIcfPrSx9rT8pfcdzX0vb6sleroe/ODBDXz+PUfVFCLHT6OossD6wSKX3/xsbTtzmiKsWjmPXz75Gh/9q24cz6clodEYU7Bdj7gmoskiIyUTSRTJVRzqIgqSCGXTY7Bo0hRT6WqKBFUelkvFdoipCroSTIcUDIfmuIoiCxSMIGmyJaERGVfFMlAw9yuoqOlUVGx0RWBb1kZTJFoTGoNFE0nUaFQlKpaH43rMbU1QMG26W+MsaE8yVDAZLppULIXGmEbRDATBypbD1+9J0ztSCY7dih6+c+8rfHBZ1wQn0x9fuJT/9f+eDtU1D0HCep6QkJBpZ9epigklhPt649hFnGqqYCWqShPa1vbn4clebrh4GcNFC0kQuP3prRx/RNOkaZFrH9jAeUs7ayMgohDYjv/k4U186X1Hc9XvX6ot/w+nzmX1q4N8YuU8hgomjVGVguGQ0EVcz8f1pJqKZq5iE9dkVClwGFUkgbqIQrZsI4kCUVWkWVHIG26tIkIUgqoMw/GI+1Iw5SGA5/sTjLqC/Io3juP55CuBU2p9VCRTDrQrJFlgVlJDFAS2520EAdrrIoCD63ps2FFgIG/WjpNhS2zLVihZLofVR7j6D69wznGdaHLgsaIpImcu7pjkZPr0lkyornmIEp7BkJCQ6WcaS0vH52dMlQ+xamUPMVWeFGysHywyWrL57n1pPrisiyc2j/LKjiKXntpNd3OcgVyFG5/oJVO2SEQULNfDsD2OOizJl+58id6RCooMN1y8jP5MBV2VufHxTZy7tIv/Wr2ZC044nJLpkozIqJJExrRJ6AIJXUIWBeKahOv5DBYs4ppEQpcD1UxRYLBg0pbQiOsSohgEMcNFi4gq0ZbQsFyPgXxg8qVKIrbrYbseY9JCjZH9S3rUZZHmuMpg0QQhcE/VqsZno2WLhKZQtlzqIgoIPo4nggAFw2HBrCSO5xPXZbaOlPB9uOWpLXz5rIUM5IxaFQjAzR8/gRse2zQpCHR3yQcJ1TUPHcIzGBIScmDY1WxsfECxD26j4/MzxpeIdjVG2DIaBAbdLbFJIyOrVvbwk0de5YLju7jlqS1csrybiCJybFc9kuDTGFP49Gnzqjd0k7zhMK81QVNM5YLju2iOazTFVCzXY3ZjhNGSzYdP6Wa0bHL+0jkIBF4e2YqNKAjURxVkUcR0fEqWi2G5NMWD6R7L9ahYHiMlk5a4xpzGCCXLZeuoQTIi16Y+5OoMh+X6aHJgeW45HvURhXhVprs/a9MV1/drqsBwPIaLQQ5EVBURBBHfEyhaTiDa5bg0x1QKpk1MkDFsl4SucGRrPNACiSm81J8jZ7jctbaff3r7XP5r9eYJ29AVkcaIMum8fO3sRXz/gfWTlg3VNQ8NwqAiJCTkzWUfy013zc8YKxG9ZHk31z4YyHO/tC3P3xzVNmFkRBIFUm0JNg4WOH/pbIyqnPbnf/sC3z5vMaM5ky/87sVaHz71rnmMFE1e3ZGlvSHOlXfsfO/L7zuaua0ajivj41MXUYiqPr97tp93L+rA830M28NybeKaQsVyqIsEmhNly6U5riIKAnFdwiNQq+ys1xEFISghrWpb4O/0B6mPapiWRzIiM1q2kEQNSRDpqFfAnrZTQVwTMB2fvOli2m6QKFqx0WWf+qjCL/70Gp1NMeY0RmmOa3zzjy/T3RTjI8uPIFexOfGIhfzumT6O7WrikQ2jO4OH9y/itUyFk7p2jljFdYWv/+FlPrisa8Jo09XvXxSKYR0ihEFFSEjIm8q+lptOlZ+xamVPzWPi8hU93LS6l2Wz6yeKKwEjisTX/5CetM6HN4xw5/P9/PjCpQi+TyKi0J81+Fa1SqElqXDjR05gR8GgNaFjezbrBio0xAK1y6e3ZLjlqS38w9vmcvfz/bx3SQeiLFAyXWw5KG/NG0FOBUDRdGhJqJiOzGDeZHZDUJJasoIkzJGSRVIPBK6iaqB1sS1rENcUDMejMaYS00Si0/ww7wNFEwQEIopUy9UYKVn4+HiewBmLDkOWBKKaxOoNg5y5uIOIImK7Pt++N71Tz2N2A6tW9tCS0GiKq/SPlukdKdES05gdU2jRZdaNlFnTm6M/a9YSZn0f2hJqGFAcIoRBRUhIyJvKPpeb7pKfkYgoPPXaaE0S+qbVQV7EVMPngTHX5MRO3w9kpP/X/3uaH1+4lL/96ZM0RFW+dvZCntmapWj4pLdnqFgun/n1WhqiKn9/0hx++2wfF53STXNc4xvvX8ymoQKxiMaa1zIsaE+iKyJFwyWqSCQ1haLloMkCcU1mpGhTNB1m1WnoqkCuDBXLI6pAU1xGEiSKpoPtgCV7zErqlCwXy/bwdSblIewPAkFCqOf7OK4HCOQqFsmIgueB4/oICCiyiOl6JCIq9724jaWHt7BhsIjleowUDP7+pDm0JnQUScRyXJpEDV0VufaBDZzY3YIgwPa8gS4JwbnTgyqX8bkXuiLyN0edNH07F/KWsidDsZCQkJBpZ8yxcjw1xcXdSe5V8zMWNEXpjCm010X46aObuPbBjWTK1m7NqWbXRyYZWV2+ooffPLPThGysEmEgZ1CyXH766CbSOwrc/OctzG2Ns2plD5myxU2rezllbgv4Pl2NUUzXYU5TnFRbnEWd9RiOhyqLtNcH++fhI4uQ0BSKpkPFcmmOawgCZMoOru+hiCKev1ODQhSCPAp8kKXgKX7sAV7ev4KPCahVme7RkoXl+qiygCCA5fhENZHWpMZQ0aRgOMyuj5Cr2Lxtfju5ssmcpiiLDqvj2odf5av//Qo3PrEZVRZ5dbjEuu0FvnLXy6yYP4u71vYjClAfU2vmbf/ntucmGbaFxmKHFoLvh2NOALbt+tldpGXHqK+Psrv33mpmct9gZvfvzehbS0ti0m1yT9faTGXajpUAz2wvsmm4NEEX4vIVPdy6Zgv//K7U1LkVuyZ2xiVey1rsqCpWqpJAX7bCrKROXBUZyJk0xzSObI2TL1ZIjxr0Zyv0ZyvctqavVt6oK2ItNwPgijNStWqGDy7r4rmtI1x8SjeWE1SGxHUZRRQQBL+qdRFYhjfGVKKqhOO5CL5I0XIwbI/6qIIgeMiCRMlyqVguDTEFz/exnCDforNBx7C9QFXT9miIKTiej2G76IpEvuIQ1yTimkxr9XKS7MkRxt5ca64SOKRuz3kULJeSGYhdVSyHqCrj4WE5EFMkFElgpGyhKxICAvmKTUSVKBo2iiwiSyKFik19TGV7rkJ7XYRnt2Sp2B53re3nguO7mFWnUzJsvnDHy7U+zGmK8O/nL6Fo2NNuLDaTf2/eKDNxn6a61sYIw8OQkJA3jaGKw6pbn6MhqvLN845h42AB16OmYzBlbsUuiZ3L5tTxgWVz+OLvX6QhqnLRyXMmBChXvfdobn6yl/WDRb5z/jHIosDLA3l+91zgWzFmQqYrIl85ayHXPLihtqlfPN7LZ949j7OWdCCK8L5jZmPaLlFNpmS5yKKAKMFzvTl+9ngw7XL5ih6++cdX+Ke3H8mC9iRFMxCwaqvqPeQNj5gqkqvY1dwICdP2sJzgBj9aslEkgVlJlVzFZSBn1jw5JCGwIR8pWSiSSODzuP9Ynk+2bNOW0ACPpK4gSQIDWYuoJoPgY7nBSM6Yu2pXk0627GJ70KgpFA0TD4GX+3Mc0RxnR77CMbPrKRoOS+fU47g+Pj7fvGdiTkvvSIWiYbOgKRo07EtAsQ9VQyFvDWFQERIS8qYxlk8xkDNYv6PANQ9MVMecKrdi18TOi07p5rO/fh7D9jjnuM5aQDH2+S/d+RLfPO8YLr/5WT592/Ncemo3t63p4+9PmsOta7bU5KOXdNZz0xOvTahEyJQtYprMUe1JXh7Is257oWai9cAr27lsxTwKRZtUe5J/OWM+7XU6BdPmy2ctJK7KOJ6HLou016k4XpBP0FpVw2yJa4yWLXzfr5mJ1UVkVFlkuGgBAnkjkOqOqhKuHzh7xjV5gprmdDCmqJkp27QkVDRFwHEhrssUDAdJCAzPdEUkokgMFS0aoiolMyg7yRs2MU2lYBkULZcv/v4lMmWLz58xn9aEzlDeZEumwttTTVM6yb6h8tEDYFIXMv2EQUVISMj0s5snyl3LQ/dGynvXxM6K6dReCwJTJn1WLKf2t+fv1Lc457hOBAF6WhPYnl8TxBqrRBAF2JEziFWDGk0W+fwZR6HIcGzXfAzboTWhM1w0aUvqeHjENYWhgklUkRD9QNiqPqpSsR2SulxLDBXFQAkzbzi01+k0RhW250066nWaYirDRQtdEVElkZIduKA2RBWGi1bVMfTAeDz6fpAEmtAFtozatNfp+PiMloKRlbxho8oiiiiQ0BVKlsGGwSIxVUKs9uncpZ2MdW9H3uC6RwJPlhWp5imdZKU3sC8HwqQuZPoJEzVDQkKml+oT5Vhy3jnXP8HqvjwIO8tDx9xCV63sed2kvbFAZIyoJk94PVXSZ0SVa3+P3b/GKg5++ugmNgwW2DxcrCVhjrXrssSPHt7EzU/2srizHsfz2JopYdgeT2wa4YX+Apbj0prQGCmZCL5IxQ68OjJlm6Ll0ppUkQSwXR9dltiWNTCc4EYoCgKiIGC7HpIkBGWmrkfesKmPBh4hgYS2S8X2GC0FeQwxVUZXx+3nfsYXsigESp2eh+f71EUFBgsOXY1BQDFUVfeUJYHGmEqh4lC2XW5+spfP/HotoiBww58243k+SzrrWTArwbGz6zFstxZQXPXeo3mqN8ONTwRiZZetmMsly7u58Yle+nLGPu/DnqqGQmYOb0miZiqVeg0oAC7gpNPpZalUqhG4FTgceA34QDqdzqRSKQH4HvAeoAx8OJ1OP1Ndz8XAF6qr/Wo6nf5FtX0p8HMgAtwNrEqn03vc0TBR88Awk/sXJmruPftyrIYMh3OuXz1pBKL2RDluFKMtoeF6/p6lvPcjp+KT75yHLot8455XJohcaZLIfz6+mY+ecgRl26UlrrElU+a2NX1kyharVvbwhxcGePv8VroaosiiT2syyo68QVudzmjRpLMhguX4DBVNGmMqkgSKIKIpYk1RUxJBlWWGiyZRVaIhqmDYHoOFQFkzEZFwPTBtD9NxsVwPTZbIVWw66nUc1ydvOpiWR2tSZVYyCCxGC/6kp/N9SdTcknEZLATmZomqPsZAziSiyMhiUP5ZpyvkDZuGqIomi2Qqdi2xs2jamLbP1tESLUmd//if9ViOz/nLOulqiBLTZCzHZcNQiZ8+Olmm+9JTu+lpie/T1MWQ4XLO9U/s/rpiZv/evFFm4j7N1ETNd6TT6eFxr68A7k+n01enUqkrqq8/B5wB9FT/nQj8CDixGoRcBSwjuCyfTqVSv0+n05nqMh8HniQIKk4H/vDm7FZIyF82r6tDsat8N0wt5T3GVD4iMZlfXnIiOwoGbQmdH1xwbNWzQqY5oXJqqpW/ntfKzx9/DYBLlnez8LAkr42UaIqrfP/+DZy5uAPTcTn6sDq2jJY4fk4jc1vi9GcrALz/2A5Ss5IMFw0EQaIvU6I1GSE9kGd+e5LBokVDVKGjXqdsuWSLLhFNwvN9JEGgYntEVAkBn+Z4UL5ZNEU83+OwOh3L9Rgu2lQsl7akiuuLjJZsogmZ+mgwSmC7/vjDMOEY78+QvyQIyGIwYmI7HhXbRVdkHM8FgsoPy/WIaRJedcsRRaJo2gjVz3t4uD787LHNnLWkg66GKNvzBj94cANnLemgpzUxpVfLmFjZmGX93u7HtJrUhRwwZtJE1FnA26t//wJ4iCCoOAu4sTrSsDqVStWnUqn26rL3jVm0p1Kp+4DTU6nUQ0AynU6vrrbfCJxNGFSEhEwve5k3AdPg7bBrIOLC7JjC7JjCkOHyiVuerW3v5o+fOOnp+IbHNnHjJSewebjEzU/28rnTF/DK9jw5w+XKO17gguO72DRU5PZn+nj7/FY66yO01emMlCo0RHWyFZuOhihRVaS9LsK2rEFHg062bON6Pi1xFSkqYNguri9SqFjURxSGSiaarCEIHg3R4Ak/rikMFkximkxSl4ipEttzJlFNprNex3A9smUXWQxKSkVLwPV9XG/nnXN/fTJc369NzyQjIoYt4uHRN+rQFJeIqBK5skMyIiMC/bkKruvTO1rm6j+8wodOnMNdz2/jjEXtfHR5N5uGi3znvvW1UZ6YKtGXKddyWS49tZuOughbMpUJjqX7FBxNo0ndjGfcd+swD+okDpr9fKuCCh+4N5VK+cCP0+n09UBbOp0eqL6/HWir/t0BbB332b5q257a+6ZoDwkJmS72kIn/Zj9R7rq93z6zhS+/byFf/P1E745fP9XLoxsznL+sEwE4+cgmcmWb4w9vYP32fC0X4IxF7SiSyA/uX897F3cwkMvz3fvW16Ze/s87U/iCjyqKJPXA32OkZNMUU6iPqORNB9v1kUSBjjqdih0obDoeqLJEtmzTVPUCyZQtooqCR1ARYroeubJDXJNRJBFdBk0SyXo7BbKAN5ToOCUCVGwYzBskdIXu5ih5wyVbdqiPBh4mniQyK6mTNxy6m+N89exFqJLA7IYovu9TqFgs6aynsz5CRJUZyJZJRBRu+FNgMJYpW7QldX748EZ6Ryq1TU8QPHs9XZKx0tE9mdQdKhzkVS5vVVCxPJ1O96dSqVbgvlQq9cr4N9PptF8NON40JEmgvj66m/fE3b73VjOT+wYzu39vVd/2dK3NVHY9Vr2j5Skz8e+6bDlzGqOcloiw4LLlDFbNsmbXR2qVAgeCd8V1bvn4SWzPG8xK6sxtiXBE8wlszwfb/9OGHZy+sINTU7NoiqnoSiAr3RxXKZkOizrr+Ne/WUBMlYjrMmXL4bPvXkCmYtEQU/nhh47DcjximowiC7SqGq8OFmmKq6iySH1UYaho1co/PU/Ecj1sy6UuomK7Hq7n1xQyXc9HEH3qdJWi5SAJIp4XBBZC9TC5ns9AzkKTZXY9dCMVh+7WxOsel12vtZFSYeICPsQ1iDTpjJZcNg6VmZXUqY/KjBQtWhIasgD92QpJXaE5rrA1U6ExptIYV8gUbTKGS0PcZ1adTsFwWNLVwKuDBb5y1iLW9gViWL99Ziv/cOpcvnTXS7Ub5ZVnHsUnb3uOz757Ae9MtdSuD8/z+Z/0EJ++7bnast85f8mEZXa/v3v+Tnuez9Zs5U27Lt8Ir/fdmum8JUFFOp3ur/4/mEqlfgucAOxIpVLt6XR6oDq9MVhdvB+YPe7jndW2fnZOl4y1P1Rt75xi+T3iuv5uk2FmYqLMGDO5bzCz+/cmJWpOatvTtTZT2fVYbcuUp8yb2JYpU1ctUqgToa5eY6ji8OTmkQMnVrS7J7vZSQqGw6Mbh/npY70Y9mba63TOOa4TSYS5rQlufHwTHzrpcAoVm+GShecHZaVHtsTIYRFVFYbyJjFNQpNFfN9HEQMNiWREpS6iIokE/hi6jO14OJKA5fhoClUfDQ9RECjaDgktUNPMlG1aExrJiIjtBaqZoihQtGwSukzRcIioEpoikS0FbeNLSus1adI1tFfXmjLusAnBNEjJgogMEVUKylkth4Qm090SoWS6FC0PSQiqRfKmTXNcw3Jdvn/Pek7sbkESAw+R7bkKuiLx00c3cu/Lw8xpinDVe49m42CRE7tbuPnPvTWNkHmtCbZmyvSOVPj0bc9NyK0YMpxaQAHBdbXrMrtjj9/pg2QEYG++W281U11rY7zpXUylUrFUKpUY+xs4DXgR+D1wcXWxi4E7qn//HrgolUoJqVTqJCBXnSb5I3BaKpVqSKVSDdX1/LH6Xj6VSp1UrRy5aNy6QkJCpoFdyzxhiryJPZSW7jNCcLNZN1JmyHB3rkOArUV7yie7l4crPN+X5c7n+7l8RU/NyOqGxzbRltT5xt3rWNObY0feYEF7gmO7Gji6PcnJ3U20JTR0RUGVRR5ObydvuFhOkOOwLWdgOT5NcYWybWNVkyklUUCWRPKVoEJCAEzHx/F8VFlEkyUG8gYJTQ4qR1yPV7aXwYeO+iA/I6oEolOaIgZy2KKIrgZCWeOnP6bDK8P3xxI2Ib2jTKUqGR7XZHKGzWjJYaQYiF21xDVsz0VApH+0RN9ohU+snMfCw5KceEQjCV3myJYEz/aOcuYxs/m3cxfx6dPmM1o08P0gp2Vtf54bHttERJEYKZrc+ERv7Xz1Ziu183qgSkd3p3MxVHH2a73TzV59t2Ywb8VIRRvw21QqNbb9X6bT6XtSqdRTwK9SqdQlQC/wgerydxOUk24kKCn9CEA6nR5NpVJfAZ6qLvflsaRN4H+zs6T0D4RJmiEh08re5E1Mm1jRbp4w57fFWLutSO9oacqb0NNbMty2po/LVszl+kderT0lz5+V5LqHNjKQM9CV4IZdtj0+8rOnuOKMFOu2u8iiSKotju16rJjfTsF0EJGwXY/mmMJwyQYfRksmqiTQ0RClUvX6cD0PoapTIYmBrfhA3mBWQkcSBfqzBq1JjbqIjCYF0ySSKFIfCdbbEFUwbY/GmILrQ95waIqpqNK4aGwan6xlEWYldTIVC98PBLokMRixGTMd84GYIiOJ/5+9N4+z7Kzr/N/P85z17rX23k066VRCSCeQhIATMg4BRG1FZVUBXxjNODP84AUOg4LACIIgioIwBgdwhBEFlCVGQDSAkWHfAiShOkkn3em19ruf9Tm/P55bt6uqqzrd6eruqs55v179urfuOffc5yx9ns/5rppq0WWw6PQtEvMxK/967xG+cM8Uf/U1E+o231flk989yMv/0yWMlFxGyi73TzS59c59i/qv/Ohwk1d9/C7e+dzdXDxcXP1AXx4hK8m31kz57/We5XLORcX4+Pg+4KplPp8Gblrm8wz4byts60PAh5b5/NvAE854sDk5OctzCpH4K93ED9QDlPQZdE/txr2SOPnj513F6z/9Q37jaTuXnYRSbQpeNYOY1zzrMh6abnPxSIm3f/5e9k93+9UdRysuYWJu3n/91f285Ck7+imQ1+6o8upnXkaUagaKDnGa8uOJNjtHijiWRCnBQMF0IVVCIEVGrWDTiTRzXdNbI0pTNlddolgTxCmOMm6UMNa0oxQpMoJYgNAM+DbHGqb3R9lXNLopFc+i3o17vT/Ojv9fZybtNYwzDsx2TCdZS3K0ETBQcJASJpshOoNEaw7OtnnJU3byc1dtZaTs8snvHODqbUPced/MopiJv7zzAY7UA/74C3sB00zslhsvXtR/ZT7FdP68fua3nnpWJtWTZSWtKbfIkv9bmwcKefZHTk7OabIeGyU9QiT+fIvzpTfxB6faPDjVZudwkSdtLD3ifq4kTtq9TqDL1UKYn9DANAn7rRt3oqTg7Z+/l+dfs43RsstoxePAdJvJZshkM+xvYz4FcvtAgclWyMGZNtOdGCHMPm2ouDiWpB2aAleBrXjL7fewf7rLC67ZxPOu2cF0O2LbgE+cappBSpYJio4iyzKqBZt612SLuJZkqhWyuWYTp/R6bNhYStCNUsqeQmuodxP0KhYqFJiqmlGq6UYS31F0ohhbqn5NjeGSS9W3++8tJfBsRZJq7jrY4aHpLiMll7/+6oO84qZL+fGRBn/0vKt4aKpNmJjgzFtuvJi33H5P/7y88NrtfOybB/pl0cc2lHnbZ+/tWy2CWLN3qs1Ttq1+6uhKFgAlxdor/73g/9ZajktbjlxU5OScb9ZJANnpogTL9n0AePcd93HLjTvZVvUe8ca90hNmwbH6cRIf+frxIMBLRst84M4H+o3CjtQDPvTVB3nDnsfz2p+6jDSDg7MdXEvyxtvu4eVPvwQl4NPfP8TNN+zkouECnqU41gjYNVJCSBgue8Q640++8GN+4YlbGSw66Cyj6FoMFm3+6LlXMdE0FoZYpwyVnF5r9IySaxHEaS9lNMN3YHPVo5sk6AyGSg7NICGIzfdmO6bXRtVXzHY0M52Iqm9arq8WGaYcuK0kSgqkhCjJ6GYphd7T+7FGwHDJZeuAz/cenmNT1eNYo8tAwWVjxWWiGfKBr+zjRddtpxUmIES/0ZtnS171jEv7AmLHoM/BueM1Kn5wqNGvrDkvKObP630TLS4eLKx+6ugK1rV7p5YPjDzTAmOPVdZILGlOzmOX9RJAdroca4bL9n1oR2m/0depBN8t7BcC9MXJ/77zgRMCMD1L8YefvZcfHGr0hcY7nnsle3Zv4Q2fvpv/+tHvMX6syTs+P46Ust+DZLDg8KLrtvPBr+zjT76wl6lWyDu/MM5vfOQ7vPn2e0i1KT71/910KZuqHp/+3sP4jiIj601AISNlh4IjkUIy3YoIY03FN1kjCBMYKQFbCtpRwlw76ZVeyKj5NsMlh1RnJKkmyyBK6aei2pZcvdoUPYQwbo8oMf0/tg46PZdHSAbsHCkQJimH5gIuGS1RdCyyTOA7kpGKy+OGirzlOU+g6Chu/fIDkGX8xa8+iXe94CpuffE1fPSb+/vBmd0opehYi9we73zubi4dLS86r694+i4+8e2DPDDTOTuenp4F4PKhQr+663oPjFxr5DIsJ+c884hlrdcpw0W336xrnvmOnfONvk7pxr3gCfNIM8R3FLOdmL0TLSZ7ropLRktsrHi85u/v6j/5zguNm2/Y2R/Dwt8/ONvpuzxuvXMfL/uJHfzFr/rVjyEAACAASURBVD6JqVZEN0r48K9fx1wnwbUlZddCCcHRZsBI0eXnr95GJ0oZKDj4tmS46DLZDJEVl4qvAIfZTkSWOXSThNGSSxBrEp3RjlIcSzBYtCl5Jm7icL3LxoqHJQWy55ZIUknRUSSpzVwnxi6tbkzFfPaH70o6oSZOzTW4fbBAM4g5MG3cHgMFSb0b0+x1VxVCcPehBt1Y8419k/z6DRez56rNXLG5wsHpNsMVn/d+cS/Pv2YbG6seB2Y63HrnPhxL8P4XX4PIsr6VYCZMueXGnejMjGe+fPdCa8XZZr0HRq411u8dKyfnAuGslLVeAyx3s37F03fxsW8f4JU37WLncPG0btwPTB8vCrRjyOdPX3A13TjlWCNgrh3xgTuNKX5pc7Fb/+24oJj//Tc/5wm870v3ESUZt9y4k4tHShye6/K6T/2o32HzD26/l41Vhz27t3DP4QbDJdcEM6Ya2xJs8F2SRNMIEjphyrZBnzDWPDTVZbRs4hHqQUzVt5lqh1hSsqnqobOMyaZpcy4QlDxFwfUJIxPI6dvSxFTECY6yjlecXBhTsVwVytNgYUxFGJtOq5ZUtKMEIcCzFLM6JtEZvjBfyMh4cKrNRcMFnrClSr0bccMlQ0y2QsY2lnlwssWGio9vC172H3bSChKa3RjfVrz5569gS8VdfL4zGHQVOwaLvP7TPzyhN8i122rnRlQ/lsp/nwPOS5fStUjepfTssJbHt2a6lK6DmIpHfawWBKCWPJtWaLIYBn37lLM/YOXOp7fcuJNU07dIfPK7B3n+tVvZUvU5VO+a2IBmhG9Ldm+tUu/GHJztMlSwme7EbB3w2VTxmG4HVAsuk82IDRUXJeHgbMCmqkfBkbRDzWQzZKTs4juSJM3oxAkCwWwnZqjoUCtYNLsps52Iai+11LFUz6WRIUSGb1u0wqT33qYbxzjKdDHdWjO1KyaaputpwZamaFaUMt3r6LptQAGr06V0PstkoKhohxoBPDwXMFo2mR8H57oMF12qBUWcwpG5gKP1gA/8v3389jMvReuMkm9Tdi2mWsatMd0KKXs2v/upHy4Kmt056HNJzV/23M5EKf90z7G+teKT3z142s3G5lnL95tHy1rcp7XapTQnJwcu7CelpRkiRXvRshVZkg2zkotIZyY2IIhNbYgj9YD33HE/L3/6Jbz3i+Z13vXx8qdfwgf+3YiPd99xHzffsJPX/P0P+NR/eSr7pjSv/Ni3GCg4vOwndnDpxgquJbnvWBNLwJbBIkoKwiTFs0xtiU5oupCOlByUFEw0QkquTbVg0+gmeLZECYGQMNcxlSiVAMeSpky30HiWxUQzZLjk0o5ibEtRK9g0uwkFx8GyBCIWJxyr1XaNFV3JRDNitOTSiRJSrZBCIAQ0ghiBKUUeJJp3PvcqMqHRWmAp+NuvH+CZV2zi3qMNUg233XWId73gavZNttg5UuJDX3mA1/3041e0rgy6il0jpUWi+u2/eCX1IAbE+siEyumTi4qcnLXAY6FR0qmyjOXmL198zbIuIikg1cdjJeY/n4+bWPrZvPhY+Hr34SZ7j87y4Zc9mWM9a8REo8OnvnuYZ1+5iTfddjcDBYfX/tSlKCHIiCk7Fo8b9jhaj5jrpFR8RcUzqaA2CilMNc15wVD1LVphTNGxiJOUomtqW8SpZlPVAzLiVDDbjqn4Fo4t0BraoWa2HVEr2LgLggnP1DUmhcBWgiBJaYeCME0BQSYyiq6CzCzXWUY30tjKVAzdWHVodGOmWxEDBYc//+J97J1o8R8vG2VD2aXgWFx/0SA/PlKnG2ve8fl7eclTHserPvF9/vszx5a3vi0R1ZkQvPG2H/Vriaw1q13OyclFRU5OzppiuWyYN9z2I97+S7v5nU8eFxqvvGkXBVvxoa8+yCtv2sWHv7b/hLiNhZ995Ov7TxAcni05MNvBdVwmWiH3TzR5TS8tcp4PvPRaZtqmuZbONK1A0w4ChrRDN0opuBaWEiQ6Y7YbUXAsml3Tu2OwZFN0JZ0QmkFK1Rf4wuqV3c4oOPNiw7hLagviMGY6ESXXRimBpQRyQZDmGVuyMtPczLEkic5oBSkVz6YdmbEgNGXX/O3ZFt04YcA38SSdSLOx6lF0LG5+2k5qBZu/+fqDPHH7EO/90gM4luC1z76cYKLFm/ZcQawz9k93T177oSeqgUVurvlMqI/efD3bSnYuLNYBuajIyclZUyzn6tg/3WVDye5ngDi2ohOlPDjV4vnXmH6Dv/zk7Vy1rcpcJ+JF123HsyS//cxLOTDb6WcVzAuOha8f+fp+nnvNVg7OdhgqOotqa3ztwRmed+02Ds116cYp9U5ElGYEiabmW4xtLBHGKVECnq0IYk3ZFRRcia0k9U6MCcc05a+PNUK21DxAMNVKsKQpPCUl2Mq4G6LEpJQOl2yixDQFS1LT1bSf/XGGk6vG1KmQCCqeYrioqAcZE02NZ2e4SjHVjqgWLIQQpIGJd0h7nVR9W9EITVO0qVbIky8aRuuM337WpRytB7zl9nuY7US883lX0YlManQQa440w5MKopXcXF++b5JdI6XcYrEOyEVFTk7OuacXM3G4aTqAFm2Ldmieim1bLuvqqHp230U0GaT85oe/fcI688GaL33qDt7xz+MMFByef+1Wfu9nL2dD2eVoI+A1z7qMg3Md9uze0hcbWQZ/+80DvOKmXQRxyjufdxXdKGGk4mIrgZoT/K8v388Lr93Oe790f99a8oe/eCWdKGHXhiKWUCRuxmw7ZmPN7YuDINb9jA4pBK0wwbMUAwWFoxSWEggE2rJoR0m/IBVo3F6MxXQ7wrUkQwW16qfCVtAIU4IYHCWJEo2Sgk1Vj0P1gIGCzWjFohWmJKnm0GyHil+hE5oeKUVHsbnm4yjJW/7pnkUl0I/MddjYa0Xu2ZK7DtXpROmK4mClTKhUc/6rXOacEvnZycnJObcsEzOx0JXx6z9xEa9+5qW861/29pe/5TlPoJUk1BsJRduiFcW87Rev5HULsgzm3R2znYiio/jLl1xDnGp8W2FbgqqrmG5L9k21F6WdzlstXnjtdv72G/v59RsuZt9ki4tHSkzWAz7+nYf55et38KLrtrN9sMD/edl1TLciyp7FkdkO2weLzLQTBgqmtHbRtWgGCYMFG61hrhvjKEknNJ/ZyuRo6kwy3YkYKjiEaUorSKj4ZvlsO2K47JBozUw7YqjomCJaZ4EohaJjOoeWfYuSq4iSjNlujMiM5UQISclRpk5H2eP9X36AK7fV+qm4n/vhEX75ydt4ztVb+u3ji46i7Nt84M4HFrmg5jM7gBPK0q+UhjzfG2S91255LJCnlPbIU0rPDmt5fGsmpXQdsJrH6lTSQ1950y66ccrWmo/nWPzJF37Ma599Oe/4/L286LrtFGzFP/7gEDffcDHdOGWuE3HxSJFWmCIAx5bc+uX7uenyjX2x8qLrtrNzpMhIyaUbpQSxKV4VxgmubdHspbu2opQo1jw82+HvvnWAX71+B7ffdZifvGyUncMlhoo2tiVNq3LHwrVMhocrFUGSYkkTX9EIEgYLDlGa0gpShooOic6YbIUMlRyKjiJNM1pRSitMGC45OEoy143pRClbah5hknG0ETBUdCg5ivnLSSUnZkScTkrpRNMU4ZpPVR0sKh6eDSk6Fp0owXcskjTFVoqZdkTRtYzFRpoU2tm2CdTsxjETzYhawWGmFeLbFrWiQ8W3qHk2OtPcMT7VTxWdL0z25798Na/5+xVSqHvt7L983ySpPv49z5aPaKlYy/ebR8ta3KeTpZTmZbpzcnLOKaeSHtqOUt5zx/0cmO2y91iT/dNdfny0wZ7dW3j3Hfcx3Ym4fucIr/r493lous10O+Y//9/vMn6syd1Hmrz8o9/j+p0j/XXnv3f34QZf3jvJDw7V6cQpKZqia9MMTdbFVDtiphlQ8S0eN1TkXc+/mmu21/jP//FifuLiIbYMuD0hIYnTDAF88CsPcHS2S5CmRIlmuhUTpxkbyi4ZGZ04pVqwmWpHaDTbBnxSnXF4LiTJTIyCUgK71wZ9njjNKLqSoaLDdDsiSI4vO9MS7onOiFKNIyWuLZhsmqBQS0En1kig7DlMtUwFU8cS7J/pECWaMNEmPVZC1XfoRJqZVshFwyUKriID3viZH2ELI7Q+8O/7eN+X7l/U6vy+idbKZekz2Fay2TVS4oNf2dcXFP0qlzlrmvwM5eTknFNW8psvTQ9d+lmqj4uOhQJkpfcrLYfjDc3um2jh26pvzfhvP3kxWweLHKkHbKx4CKE51ojRmREQ7TBFCk3Zs9hYMUGKv3HDJXTihDjJ8ByJ5yjiJKUbaxpBzFDBIdKagmNKchdsi4JtimLZCuJUkGkI4pQMM86Kb+Hakig2QZpKCoQ4/nB4pm6ARGc0ugkbyi4lV6KEzeE5IyA2VzyUhMP1gLJnc8/hOn/1VeO2eP3PXE4rTBgpuTSCmEtGSziWpBUlHKl3yTK49c69HKkHTLUjLh8unODOeOsvXMkff2F80XhOcG1cyLVbLnByUZGTk3NOWc5vvjCmYmFK6NLP9uzecoLYWOn9csJk/v1yAmPP7i288bZ7+m6YN3zmR7z6GbsYKLq84TM/6pcHf8Oex9MIEoJIU3QtLCnIMBYHrTO6cULFs5lqRdR8m1hr5joxg0WH4ZLNbCdhph2xpeqRpDDVCim5Fp6t0FlG2VOkGg7NBgyXHDxHUg8yFrqqS569wtE9NSwpqPgW9W6MktAKTY+ToqNoRzGJNrUwlBRcvrnKG/c8nqGSQzdKkEIy0wnZVPUpOIqLh4uEiXEXffhr+/uWheGis6w4MC6UxY3kli1Ln9duWZfkoiInJ+fcsqRBWMFRFByLiVbI7zz7cqIk5Xd/+nIGijZ3HZhjz+4t/UDKpWJjpffLCZP597feuW9ZgbGcZaMRpnhOwp+/6InUg5gDMx3e8Om7++mp3394ml+5/iKmWzHfm6nT7IQ86wmbOVw35a67UULBtRguucy2Q8gcMjQjZZdD9YCRssto2cZRFmGS0o5SOlHKcMllsGjTDBKiJMOWpmT3PGGcAI9eWCy0VLi2QEkbncF0O8KxJCXHwrEEc92EVpAwULRJ0pS/+cZD/OITt2NJyY6ax4hvsaPk8PWDjUXBr4saci0VB4K8gdcFTB6o2SMP1Dw7rOXx5YGap845OY+LSnM7jBQsJjsn9g0pOBb1brTs+04Y49pWf92SZzPbDsmEYPxIo2/GXygwZjvRoiDR5d7f/oNDvO5nHk+UaBxLUPVtJhoBtlKEccyGqk+cZnSiFN9RuJbAkYrZbkTNd2iGMa6lqHdNbQdLCjqxCeqMEk0rTNlUdVFC0AxTJpohm6qma+nBuS5DRRPYOdq7nFa790ezmzLVjk379Uzj26ZA13Q7ouRaCExtDktKBgs2m5YKgKXn7pEEwumuf4qs5fvNo2Ut7lPe+yMnJ2fts/SJVq/cN2TzgoC9he/xF69rbsiKe2Y6RGnGq595KcMlh/uONfuC4lQsHy+8djv/8zZjoXj1M3YxVHbZP93pp0/6jmKo6JmYCwTNbsJoRVHyLMI0xbWMZaTkWjSDGN+xmG5FbK35KEfQjlKUFLR6gmK0F+sQp/QDNS3pAqZOxWpMwkJAmmXoDJSSJNq0Zi+5JgNELBhv2bM5OtdlpOyxyfeXLbV9Wq6K3LVxwZKLipxlmQ8Kyy1ZORcCjiX7Ras2VT1uvuFxvP5nL0f2lnWihN//+SfgO5KJRsj//PknQJYRxJrnXH28SNYrb9qF71ik6eLslU6U8Q/fvZ9fuX4HRUdBrxGXb1vMdmOKrkXBFigpmW2nOJZmU8XjaDNgS81na82jGRhBYbJGNGkmCWPNdK9Ohe8sKHy1iv8tUw1KwNiGAs0g476jDYqew+G5LgNFB0tK5joRQgg2VrxcAOSclDylNOcEhBC87V/38rZ/3bso4jwnZ70y6Nm88qZdeLbkSD3gj7+wl5lWiGNJurFpUe47krsOzPHjoy3+520/4t4jTT74lQe4cnOV3/vZy/mzF17Nk7bXqBVstgwUuOGSYXYOF7lktMzffOMhrt42xHu/eD/dJEVJcCxFt5eF4lqSdpTgKEHJs5hpxyRZxnDR6QdGIqDgStIsY66T0I1Mc6+qbzPXiQnidNWOhy0FVc+m3o3pRpqCI+hGJmh0y0ARBIxtrODZisGiw3cfmub1n76bw/Xuqo0h58Ikt1TkLEIIk7pW78bneyg5OavGoKvYOVzklht39l0WAIdmu/3CWI2OTZrBJSNF3vHc3bTChCu3jlF0FEfrAUXHtCkveab5l2MJhksOYaz57z91GfVuwpVbxki15q++8hBPu3SEzTUfz1YIAZ0gpuTYxKmm5JrW4o0gYmPFuE26UULZtftxDJ4taUem0mbJs7Dk6j0DxjpjrhffUXAlk+0YkUk2Vjw6cUzFtZlqhzhS8tZ/uocfHGrg2ZINZW/VxpBzYZKLipw+8xaKcl4GN+dCI4MnbSyxreotyjiZbIe85lmX8fBsh/f92wNGXHRj/uyOvbzouu0UHcXff+cgz7piI5trPr6taAUxtYJDM0iwpWS07NKKkl7XUYVG8txrtzFccii7Jm2zHSTUSh7NMMaxFM0goeqb4lGH5kw9iCjN8DIoOBLHkgwW4dCsiXuwpMCSq2c1nG99HiYpUSzYWLGZ62Q8NNNhsOggRUoYa179qbsWlUrfVrFh9QwmORcg+ezxGGVpzMRCC0XuMs25IFkaHAhsLlr8eCagEzn8j5+6zBTZyuC1P3UZg0WH+ydb7J1o8YNDe9kx5POmPVcQBppvPTTDJ759kNlOxLuefxWOkiSpphOlzHYjHCVxLUkrTPr1MLIMwsRUyZTS1GZoBClpBr4jiVNFJ0rwHEW9E+Naov89KQRqFXuJ6SwjTjM8S1EtSJpBRiMwJbsTnfK2fxrHsQQf/LVrme3ElD2LP79jL54l806hOSclFxVrkJXiGFYraHLeIgHwumdcCrCmLRSnezxONw4kD0pdYyxKNzzebOqsoOGyAY8hz+qnroZxQrXsMlIwVoZbbtyJJSU7h4u0o4QwirliU5VdP1NCILj13x5g70SL3332ZRyc7bK55vPgVJvf/8d7cCzB6376MjxbEaeaii9RAlylOFIPqHgOAtO0q+wqjjVTVKKpFW0qnmSylc4fEs5WheokhWpBMN2CMDHppDc/7SKUMK3b//LfHuDGsVG+vb/Ojw7nnUJzTk5+Zawh5q0Fb/2Xccqe6XQ4/wpGACyc+OYnw+Um0YUWiOV+p96NEQuWL2ehWLj8fE24C10yC4+HAF73zDGyLDvhmCy3/nLff/tzr0JKyVv/xZQMXnp8F24TctFxTlimg+miZlNngxMsGL3UVb3YZXLXoTqf+Pbxplg7hnze/ku7+a2fvBgysCyJLQVlT7Gh4rJ9sMBgyUGKjEwLYq2JU0GYxHiWRaMVU/FgU9UlTjOaYYrT6wEy147xbbVwiIQp9AtpClbneAizmXsPBwwWbKoFxWw7QQrBUMnhDz97L3snWjzt0lHAFAQ70gxPFHznUgjmrGlyUbFGWDgZzk/wjQWvCyf4+fXf+i/jtCLNpoqz7IQLLCtQ5i0SZd/uL1+O+eWw8oR7tlgomJY7HpXe2BaKi5Otv9z3X/fpH1GwTxRYS8dxvo7BY5HJbtIXFHC82dR5ezruCY6pdsR77rh/0aL9013+3wPTKAHvv3MfAwWHlzxlB+/54n39kt5vfs4VKCFphmayRWTMtDIEKVsHfHSWcbQeUivapopnoqn4NsK3ONYwsRauLdFZRhhn4JlrdLKbrM7xyKAdJgyXbAQmxqLeTXAs2RcU863Hwbhs7jpU5z133H9c8G2r8PWHz7EQzFmz5KJiDXGyeIaFAmBeGNS7Ma1IU3TkshPuSgJl4W88UgzF+cgCmRdY9W7M1gF/xfXqS/Z1oWA6FerdmCQ1EfXLHd+Fx3ktWG0eC6zUwXTZBlrn8Ol4pSZoWQYf/85B3rDn8bzl9nv4yNf3c8uNO7l0tMxQyWGyGaCkxHck7/j8vfzmDRcxXPYJE1PR0hTNcgiSBEeZJmNRmpFqzSWjHscaJmCy5gkq/uo1FFtIybXoJpojcxEFRzFUsrnncINbbrwY31G8+fa7+/083rDn8bz3i0ZczQu+j958/doSgjnnlfyMrwHm3R6PxFKBcCrrrgbnY0Ktd2PmOkY0nMq6p3pcTmc7C7d3Pq02jyVWmrxPaDZ1jt0kyzVBm3+CP1IPaAYxf/aCq2lFCQdmOuw9OscVW2r4tkU9iKkVbF777MtphjFRqmmHKQOFeetEilK9/1+YdFfXtrj7cIfhkkvVV73vSLxe8OYJx+NRYnqcwMOzASMlc+y/tm+GS0ZLfPW+YwyVC+zZvQUl4dLRMg/PdvruHzAC4lgzOHUhmHPBkxe/Os/MP5W/598fON9DWZH5CfWxXgyr3o3z+h1nmfnJ27PNrWlRs6kFrOQmmewmZ2dgC5qgffCl13DLjTv7ggLgb795gEjrfoEqLRSIjKGiw0jZpR2mCCHwbWn6faTHi2IJIeiEpg9I1beZbZsOnkNFh7lODAhcW5oCWf3jdGaTtWtJhkoOE82QbpxS621vqhVy9bZaX1B8+Gv7+eBX9uHbiihN+btvHVi0Hc+WfTGy9PMz7aSasz7JZeQaYD2kceaTqSF3g5xllmmVvVyfi9Nyk6zi2EY8ixHfoh4k/fbdni150XXbIdM8bqjIxoqHzqDsWTTCGNdWeLZAAKkWNIOYimdR9RWznZSpVsS2AZ9EZ7SCmKGiy1SvNPdI2dSxsJXEVYvHciaEiWa6FTFadqn4ClAcqYeUXJt2lHDRSIUo0bzqGbsYKbs8PNPBsxWvesYYv/PJxdahLNO84um7+rEk81acM+2kmrM+yUVFzpriVF1B54vcDXIOOIVmU6fsJjlL47tyU4n3/vITmevGDBYcEp2hJMRpgmsrOpFGSdF7ws9IU03VV0hhakQIIQjiDCUEQ0UL3xF0w4ySZzPdiRgqOP2n//mGYmpBQ7HVQgBVD+45GlBybXxboqSNHDRNzsquxXQ7ZLDooqTgP+wonyD4JrspH/v2AW6+YSdCmLoaH/v2AX7ykieu6lhz1ge5qMhZM6yXip651eb8s1yMQ99Nsto6b0FA6IayS6oz6kFMkGgmmyFZBsMlIwJ0BiVXYUnNVCtkuOgSxAmjJZco1cx2YrbUfFKdcaRusjuCRNMJdb90uGMJLCVohglxktEMEzaUTWzF2SCIoeY7ZFlGN9FkZHi2wrVBa0EQa3xHUnYVk+2EehBT8mym2hEgGCkqXnXTpfzOp3549s9Fzppnbd+9z4CxsbFnA+/GSPsPjI+Pv/08D+kE1vpT+VLOhel/PbiCIHeDnHdO0U1yxiwICB0oOLz0qTt49x3GzP8Hz3k8YxvLfP/hOY41Aiqexds+92MGCg6/+bSL2FTzCRITkDkXRJRdm4pvM9EMGSza1Ao27TCh4tnoLCXWknqvH0eaadLUNDpLu6Y9eaIfebintWu91uetEDpRjGfbNLoRnq3QWUon1LzvS+P9vh/vf8k1vPH2u3n6ZRsXuTre8pwn8LFv7efmG3aiJFyzfYDHD/twJuPN616sWy5IUTE2NqaA9wHPBA4C3xobG7ttfHz8nke7TSHEqk4e6+WpfCFn0/S/3gRW7gZZA5yCm+RMWRgQ+ktP2toXFADv+/I+fvenL+WqrTXuOjhHO0p55U272FzzOTzX5ePfPMCvXL+DyWbIxqpHvRuhpGS45NCNTYGpomsjRQYogiih1AucmGnFlDwL15JUPIvZToStXPqx9WdY/EoASghSnZGR9duflz1FmIBrWfzj9/f3BcWrn3kpYax56U/s5H/8/V2LAmTf8JkfcfMNO3nfl0yqqWfLM0snPR8F0HJWjfUzo50eTwbuHx8f3wcwNjb2d8BzgNMWFUIIXvfpH5Gm6apNHuu5z8Zq12xYWkV0PZG7QS58FgaEmvTL44/fR+oBf/i5vdz64ifx1J1DTLcjBgo2kDFccrhouEitaFP0FK0gZbjokGQZc92IkmMz3QnZWiuQak0zTOlGKcMlFyWh4tvMdiLcXg+RdpiS6uP/1860+FUGJDqjYCsSbfqAdOIUKaBoK+Is5eeu3saTd470RdF7v3gfv/qUHcsGyC58HjjTgNk1VwAt57S4UM/QFuDhBX8fBK5/tBurd2N0mq7KRLoeLRRLWa2n9OWqiObkrCWWBoQuDQ6d7UR4UnC4HbP3WLPfVn246PD9A7O84MnbSTWmI6jWtIOEgYJDN05xlSSIU6I0ZajoUHQUrTAhiDQFT7F1wO+1RzcdUBfa8VYryyXRGUMFBZmxniipODjX4fYfHOLFT9lJlsHurVW+8cAkeydaFBxrxSJgC/8+k3TS85LZk7Nq5Geoh1KCWq2w7DIB1Ioub+9VknvbLzzhjH6rFWmk1CilUFKe0atAn/E2Hs1ro9ePpFpdueKlOa5yxeP6SMfCss7uvq3GsTuVY3DiMVn5WlurPNJ5XKuc6bgrOuNPnn81v/2J7/MP3znIK2/a1XeBeLbkHb+0m8cNl9gxVKToWXx7/wwVz2LroE8jSAiilIKjaIWakmcxXHJpBDFBpBks2RQcRRpkHJwNGChYlFyLRhBQFha2EgSRJtUZcolrcPNA4ZT2a+m1Nt1u9t/Px1REKUQ6oeBYZBkUHIvfuOESZnsVbT/xrQN89u5jvGnPFfz1V/edkD76pj1XcOudx10fr3j6LpIse9THfbM+Ubx5tjylfV6v1+nJWG/7dKGKikPAtgV/b+19tiJpmjE31znhcyEEGZBqTaNn7q7Xu8s29jqVJ3YhBGmakmq5Kq/zY1vNbZ7q69JjsbT7ada7sax0XB/pWCRJelb3bTWO3XLXw0JGRsqnRpjXUgAAIABJREFUfK2tZVY6j2ud1Rj3kzeX+OQtT+GBmQ5H5rq8/D9dQpTqfkBio9EF4PJBj2F/lKl2hLIkAwWbVpSipGSwaOMqSTdOCRPNYMlhph0RJJqab5NlkGYaV6p+CqklBb6jaNQDBosOnnM8+6OqOGG/Tula6xkQLCn6pehLnqTe1Qz4GSNlRZzatKOYsivpRimXba6y56ot/K8v38f1O0ewJHzo164jSVJKns3bPncPe3ZvWZJOOvSoj3tVsWxmz3L7vJT1ep2ejLW4T8tda/NcqKLiW8CusbGxizBi4kXAr6zGhpfGEyw3kfbXXaFB1YXCcrEVpxJncCG4gHIeQ8wHhG6pMDlYWJxtopdZz7NAmQJT9xxuMLahjBAgEEy2IkZLLu0oZvugRyNI+43DGl2NRNMIEkbLLqMVxVRTmyJa3QTXkoBE8egzIRSKlBSdQbdnRUlT2FbzyDI4PBehM0HBsZBS0Apjdm+tcvGAy5v3XHFipo2AX3vqRaub2nuuMntyzgoX5F19fHw8GRsbeznwz5iU0g+Nj4/fvRrbLi/pjgnLBy+erAX3hcJyx2I5FmbOrOcg1ZzHOKeTbZLClSMFar1iVo5lU+/EDBVN7ELBsQiTFDJ61TeNFWKiGTJScrGE4MhchCUVnSil6FhIjCjgTOKDY1C2QgpNwTHbLnsWloJ2qLGUxBKmAdpcO2JrxTUTerLCvp8tAXAOMntyzg4Xzgy3hPHx8c8Cnz0b217aHRNWFhsn6xB6IbDcsZgXWPOZMzpNT2jFnpNzwaNhW9FmW7HncygtU+3TA8rm8+GS4qIF69RqVebmOuxY+L3VSDiKYVvBpra5usisXltSXGu41osVeqSbVi4AchaQ393PgKVP28tNsI8V6st09JzP6ig68oRW7Dk5OTk5Fx6PrZnvUVL1bQq9hkBlz3rE1+Z8ZoRvn9L6Z/KqlKZyln/j0bwuPAYFWzyqYwKc1X2zVHZa53WlMebk5OTkGEReCbDPJLD/fA8i54JjCnj2ks/yay3nbJBfaznniuWuNSAXFTk5OTk5OTmrhDzfA8jJycnJycm5MMhFRU5OTk5OTs6qkIuKnJycnJycnFUhz/7oEUVJVq93l11WKrm0WuE5HtGpsZbHBmt7fOdibCMj5ROSRE52ra1V1vJ5PBnrddxw+mM/3WttPR+blcj36dyw3LU2T26p6HGy8tmWpVZcdr5Zy2ODtT2+8zW29ViqfS2fx5OxXscNqzP29Xpfe7Tk+3T+yUVFTk5OTk5OzqqQi4qcnJycnJycVSGPqcg5PQQ0kpR6oAnSFCUEcZoRxCmbKx4j3godFCU83IyZ7UZUPZtOmDBcdBkpKo51UjQZEkGiM4qeIIzMZpQ0vUSkBK3B6V2xOgMpzGuSQpRkpGT9KpfDZclkXeN7Ek+BUhCbop7UO5qiL2nNNQlis81Eg+9AOzC/FSf0WqNnuI6g2UmJdErBtnBtQZJASkYYa2baEZurHltL9uKulTk5axEbHpyNOHa4yYaKy0UDzur0FMnJIRcVZ46AyW7S69DnMuI/+rbEax4bUlKKFhQ904Z50ULM8oVMt5vzi9hck2yueb0lqr/+cAnoywFBmMKxbsglI+5Jh3OskbChYvW/x5LC2Ztriw1xjgP1IFv0uW8v3qZTWPorZpsDnuqPeeGyAzMZOsuIdUaqUtNFMhcWOWsV+8T/o500xbVBJRfwvSvnnJGLipOhYDpMefhQnWaUEMYpW2s+I27vP5+Arx9s8Jp/+AFBrPFsyTufu5unbK0Ax8XGpqpLmIKQ4CjzZCwlRDFYyvyLE/NZloGtIEogTqHgQhCZp/L5p3Uw74WAbrOJsMznQph/Wh//O9Xg9CZOJSCMj2/Hto0s0GZXFk2Zce/mkmVmbMVlGiyeDTTQCvQjCorptl4gKE6NWEPVW70gyW/ub3P/RAudwf0TLY6OlnjyjiJKr6/AqpzHDinpkuu2ycWjJS4e8RkqrEJr9ZzHPLmoWAkFqUyp+VDzJXB8Vp1X+tNtzXWPK/Ll337qoq/OLx8sCwbLZnIsL/MTdm+TGlja1NSzjn9WdCBMwV3uYXnBeBe9VzDb0QwUFj+t+zY0QygvmLOXC6yxjxsOcBw4MJtiSYGjJJ3Y7J9rScJEIwDHkkSJntdaFBxFnGgineH2lhUcRTtK5zfbX9eSxu0hhEAKmGqFtCMH15JkGUSpxrcV3TjFkUY5HWuGhIlLojMsaQab6AxXyb7lwJKCLDO/o7MMKQRZluFYEq0zEp2RAbYUZL3vz49l6Wv/WAmBzjJsKTg02+Uv79zXF5SvvGkXR2o+Wwu5qMhZmxyp62Wv2201n4lmhmenxiqXGnflkUbAYNGh4lqM+rkVLueRyUXFCqQyfcR1hopnHueasrJOmKcTQeE0LQVz3ewEQQHQCKDinbi+ZuWo3SSDiWZI2bNwlGSmHaEzqBVs5joxSor++1RnCAEjJZco0cx1Y4ZKDnOdmKGiw0TT5Ft7liBIMpQUlFxFK0yRAnxHUfFsjjVChkoOaZox140ZLjlMtSJqvo2U4NuKVphQ7yZUfHMZN7oJtYJNlmU0ugll36LbEzFxagRCqjOqBZssg1aYmL99i6z3/Ypv0ewm2JYgSjIqvkWja4IxBKB6IqPq27z7jvsIYnOXDWLNu++4jye85Foo2Cccw5yctUAzTFe8bnWW4dmSB6e6OLbgv/zf7/WFx5t+7goGizZP2ljKhUXOSclFxQocqWuUFIQLnr4BHCVJs6z/9Dr/xA3g9CaceXeCLQWi9xQdJRpbSeJUm9zxLEP2nqTnn6J1Zia+gitpBhrfliTaBAMizFOyLQVCmN/MMuPiCBPd/76jBDqDdpTSDGT/t6B3L8ig0Z0PghTo3niVEFR8SSfKCBPd359YZ9hKMlJ26UQx0+2E0bJLBsy0IjZUjHiYaZsJ3+5ZASaaIZYUbKi4TDRDqr7NRDNktOIeb2veOy7tMKHiWegsoxun+Jbqf09JwWjZZbIZsqXmcawRIgQMlRyme78/24kA2FBxmW5FCAHDZYe5bkzBMZLNsxVhrLGUYK5j7LsVz8K2JLNt853RistcJ2K47BAnGTVfMts1v2FJQZhqksRYOmbaUf/GPE8Qa9pRslqXYE7OqtMOk2Wv21aU0OzGHJzrsqXm88ThCk+9aJAv7Z0iiDW//49388fPu4qHmzHbirlozlmZC1ZUjI2NPRt4N8YQ8IHx8fG3n873W2GKpQTT7Wh+TkZJQdmzUBKmW3H/s7QnMEbKDrPt2Jjygapvo5SZQuc6MWXPQmeabqTJMqgWzFPwwkyGsmsRpxkznYiBgkOaZUy3zKRpScFA0TxlJ9rY9ZUSTLcibGWyMBwl8BxFkmqaQYJnC8JegESqjWUAIM0yyp5FJ0xJdIatBKl2SLKMmd4+13ybZpiYfRYZJcfGtzO6UcKGqourXKq+pBVKPFtS8hRSQDfK2FhxkVIQJQmbKi6WkriWpOgqLAkPTQfsHPboxhLflphhCTzbTNgXj/hIYXw0nq2QwiXRmtGySxCnWBKGSw6eBXbZRQloRwmDRacvzFxLQu/YjlQkEw2BY0lsJZBC4NkCJQW2dFHSCMaC7RKlxr3h2grHconSlFRLyq5FYmlcS2IrF8+Wi27Qni0ZKZ08FiQn53yyobL8dVtyFA/04izedNvdvP8l1/CHvzTGR79R5j1ferAvmI81g1xU5JyUC1JUjI2NKeB9wDOBg8C3xsbGbhsfH7/nVLfRChPSLGOk5BjhkEGcmIm65FlsrJin9TDROJZEAGGsKbkWrm38+rPtmLTnwx8s2sy2YwaLDoIUgSDVJvZA9qreZUArSJjrGpP8RNM8lW/o/VYUa+Ikox7E/XiBNMvYUvNohQmerQjilG6cMlhwCBNjbbFVhpJgyV7cQwaWEjSCmJJn4VqSIE451vu9kbKxJky3IiqeRTNIuGjYY6IZMVRyqfmqZ12h5+oQTLUl7UCTkbK1ZtOOFN04I8sUJU/hKOOyGD8WsrnmMliwcW0ouIIgUsx0EsquIkyM68SxoOwpploRZU8xPKC4+0jAFZs8Jlpm3x1HECWaTRVJmILGwhIS24KSB55lHDq+DfUA2lGMFDYDBfM7JQ8cCbaSNIOMggvdWOJY0Ik0SsJwUXK4DtPtiJKn8G1J0QEvlvzRc3dz/6S5ESsBF4+UGFwFl1hOztlisLj8dVtwBJ/4zsPs2b2FINYcqwfoDJ7/5M2UXMW77thH0bHYUF7Gd5qTs4ALUlQATwbuHx8f3wcwNjb2d8BzgFMWFRurLvQm3yTN8G2J5av+k/SGso+S0I4kvm1Ex4FOzKaqaybZ1nFXCRlIKRgtOxxthGyteYBgrmusEUoJwkjj2JKCo9A6o+AofFshBAwUFLGGQAkmmqERNBnHrQ5aU/EswtS4EYqOxWQrZOuAx9F6yFDRWDwsKfBtC52BawlsJXAtScERtAKJZxsrQhCnbKk5uJaHrcC3Ja0ww7MttIZYZxxrhriWwLU9ppopCJjtxNR8m4lmRjeJAUkQpVR9RZTAVCul5jtMNs16U03dC64UOEqhJCgpgYyJRoqtJLZUeDbMdaHs2RxrZgRJQpRohorGLTHRzNA6w7UlljKWicmGJk4zfEcx2zHBpANFl8lGSJRatMKEVmguf4ERh1EijfhSkqlWZIRZLGgGsbE6CZhtp7RC4+Jph4vD5NthzFxHU8oDNXPWKLNtzWQr5DPfP8Se3VvIhLEE2srihddu5yNf349nS3zHYrIRUHQUe67ewDUXDZLojG3lvBZLzsm5UEXFFuDhBX8fBK4/2ReUEtRqx4sUTMZNtM44VA9I0oyBgoVnW1Q9hWd7PDjdZaTkYitBM9BIAYNFm26ccmhOotE4SlFzJfumAgCGSy6bqh5SCAquINYWYaJxhWCmEzFUcqj6kjiFTpiyoapodCBIMnxboC3JpqoHGaRZihASS8JEK2G46OELG6VgrhkxUnZJNVQLNvUgIk5N7MZoyUUpQTfSWFIQxCkgEFJiZRmDRYtWKJnrZCAgijNKnuL+iQ5gTKVJmjFUsolTaHRTMwEXbWoFm9lOjG8rXEuRYQIaZzspAphshoyUXVqhsaZYStIOk37sxWzbxI5MtyKUEviWIkjSvmtnthtTdhVF10IJzVTPktKNNa5l4j+aocaWgm5sCmolgYl/GSxaRLHGsy2ONkJGyy7HGiZotOBI4jSjGwt8W5Ghqfg2k62QomtRcC0EMNdNmWiGDBZslBTMdZMTouijVC+6jk7lWlsPKCXX3Zhh/Y4bVmfsS6+18bkZPvy1h3jhtdt5zxfv61+7b/3FK7n/WIPZTmSymOY61IOUN952N3/wC1eye2sJJaCeaCaaMaNll201HynXVh+b9Xy+V2K97dOFKipOmzTNmJvr9P+udxOEMHEFxkxorARx6uAoQdGxmGpFQIbXS3ecn/xsZTIHHCshjG0qBYtUw5F6wNYBjyONkFpiMddJSLRxUWysuEw0I+LEZq4b4dmKZA6yXlBo25LM9eIsjjVDNpRdJppdHEtSci0OzHQYKbtksXFzkMFsJ0QKQcVzSLUJgox0ShwZt8m8K2SgYBMkEZ5lMdUyVTJbkcnGyNDMdDOGS26/DkY3SiETNAKTBVLyLCZbEZ4lqXo2M+2IemYEBZlmohlhScFw2WWqZQIhkzSjEcQMl1zCWBMmxvohe8fc6mWZDBRtmmFKvRv3gzKFEIRJQhCbNNR612SWxKmm3o376afDJYfDcwGOJWj30l8bve20wpjtgz5BonuWmASnZ6HIMvAdI3SO1kMcZZNhxM5wyUGIjCjJlo2i/98vvXbRdTQycmIy8dJrbT1QqxXW3Zhh/Y4bTn/sp3KttcKEPbu39AUFmGv39Z/6If/nZdexdajIxqpHHKf81Vf3E8Sa3/v0D/mLF19jBL0jePvn7mXvRIs/fcHV7BjwzP/pNVL4bz2f75VYi/u03LU2z4UqKg4B2xb8vbX32SnTDBN8y7g7yp5iohlScBStMMZSJmjPtky1qrneRCaEwJImW8JWxt1wrBmyoeISJwkl1+JI3WRChImpveDaNkGcEiUZw0WHQ3MBVd+mEyc0uglV36YbJ8x1MoZKDscaJoNiqmWsEQD1bszjhgocmOmS6IyRssNEM2C47JL0SmhLISi5Fkma0QwipIRawUFrM7mXXZs4TWmFKa6t6IQpQsBgwcFyMoLYiCzXUpRci2MNs1/tKMW1BRtsl1RnNLrmKWY+wLTkWmyouISJphsnjJYdgkTTDlOGS64RDgXbWA8qbt/1c6wRMFxyaAQxUZLxuCGfDE3Vt5lqRQwVHSqe5FgjNOmmzQjbktR8mzAxwaXNMOlnp5jzJ3vxIoKCbaxEFU/R6BpLSjOM2VT1TIYOJl5jY9VkoRQdi+GSi5QZWSZpBStkf4R59kfO2qXsmkDz5a7dyWbI03YN8Y7P/ZifHNvAkXrQX/a9A7MAXDRU5E9feCV/cPs4AJ+/dwKdwT/edYhX3XQpA0XbxJB5NoPu+RcZOeeeC1VUfAvYNTY2dhFGTLwI+JXT2UDNt5nrRDSCjBFcCo6FFBCnkmYQ0w4ThkoOQhirhW8rEq2xlWKqFTJccvspj3PdmAHfxpLCBEh2YzxH4FiKZhAzUDBiYmPVZbTiIgVYykJJY52oFRykMJPeaMUlw2RuRGmKa0kqnkU7Sin3UiS11myseLSjlHaUIHqJr45lXDUbqy5ZlmGrjLkoodCLwRgpu5Q9s39DJYewF7zpWoLBokOUalKdMViUdCILITCZFAgsKWkGRng5lmC6fbw+xXDZxo0lzdBkunTClFrBphXEVHyTzTJUdCi7ik6U0gpNFkfRNQGhyhd0Y93L5BCMlF3qnQiv5DJUMkWy5oNZm0FM2bNphTFxmlF0FL4rUcoU+ig4iodnO/2eJYm2mW7FbKy6eIhecGtGNzJWj01Vr18Tw7clQyWXh6Y7jJaXj6IfPFelR3NyHgWOLbh8U2XZa7fmO2Ra8PTLNiIXxBt7tiTtVej93U/9kPe/5Bqe88QtvOrj3++7T17x9F386R172bN7Cx/8yj5eedMudg4XTV2LXFg8prggQ9XHx8cT4OXAPwP3Ah8fHx+/+3S2MdOOKHsWQyVTsGmyGeJZklaQMFxyGS65zLZjplohRUdhW8a3WHQlQ0WXZmAyPQYLippvU+/GNIKYMEkoegrXMkKk7Nn4juzXWIiSBDABlXGaMFR06fRqH7iWIk4T6p0Y35Y4ShHEGVGacqwRYlvCTKK2ohOndKKEoaKD7ygGCg4Fx2ZDxaXsqd6kan6nGcQMlhwmGiFhkjBUcnEt0bcyFBzLNNZSkkaQ0I0zCo6kGST4lqQRmH2zpcR3JIfmAjxb4ShTFOtYI2CqHVLrZbQMFG06UYxnW0RJwlw3ptizAtnSuCIGCopWkFBwFGn2/7P35mF21vXd/+ve73OfdfYskxlIMkwWQljCZpViUIptREEWH6moxR+PfUrhcataBUQqYtFSqa1LQStWRdwFFamAAgqaiLIlmSQkmWSSyaxnznLv2++P75kThkzcnxroeV9Xrmvm3Cdztu+578/383kvMeNVn7Gaz4wTYGmyeP/doFnElCyFqhs2/TAsXaU7bzBlB8SxCCaruRFhLAieWV1lQdGk5kZ0Fwx0RXy2U/WAJJHEe9foDOUNsQ4sXcUJ4oaUVea6c1djauIrZGqN39UX5FeqhRcIVEmm5gZcvWHVnLX7ofPWMFpxGK/73HL/dnobM/zZguHuJ/aRpqJrUXECdk7avPklS7li/XLaLJ1b7t/OhuMWI0kHR4FPj1aZcFudu/9peKF2KhgaGvou8N3f9f+XGq6IhirTkdMhhQnbb/hEpPQUFIJIJWcoxEmKioQqix16GCVkDZVJOyCIxUXb0lV0VUKRhMJgb9mjzdIIkpiqG9KVV4XyI4VpW7hXqrJCEMdYusq0HdKR04gTmUJGqCaqbtToWmj0FFTSVKggJCRqXkQxoxKnMaYmCJFhnNLbZjJZC3GCiCBKWdxmChWFIiEXDCTEeCSjq5CKIimjqY1WqETWUKl7kShcgpi8oWJqogDoKZjESUpnTkeRwY9S/CgiZwheyowX0ZU3mmTOqhfSZmnIUoKmSrihxHjdJ2eoTNuiy6LKMjIK3QUFCYiSBCeIsXSFkqmTpik1LwZSMpro/HTlDFRZGGstKBjsmfY4qiODZaRM1Hyyhkwuo+MEUcPBU3RECpZKGAl1SU/BACQiMyVnykQJ7Jn2iOKExSWTkRmXLzw6zD9esBY3iMjoKrc++AxvOXMZCxccft7YQgt/TIxWPW7+wQ4uPb2fmy5Yi+NHTNR98hmVJ0ZsTl+axQsTvCjmyrOWs7w7z0fv3dpUhvR3ZPCjdA5B+cr1A3z+0WEUWWQNgSgs+totKl5I13MzCFp4QaP1aR8GZoPYN+MGdFhGw29Co+5FyLLMZE0ib6gkpEzZAZ05jSgRXypZlpm2xQVzVvGQpimKJDFpB5iq1CQL5gxNGEaFKTlDfByyJFH1RJdixvaFUVZGWGRPeT5tlhiRRA3J5FQ9oJhVROciipiqR3TmdFIpJYzEa8kbMkEsZJZOEJM1VEqWzJQdkDcE/6Aja1D3IwxVSFlnnBBZ1jFUYeQVRAl5Q+FA1afiRfQ8i3iZ0xVqfsS0HXLsIosZJ8ELRTGlyOAFEY6fEDV4D5oiUciIIkAQScXrbrM0NFlmZMZt2nrLkkRnTm/kiwieSrVR2Piu4H50ZHWQEpJUIWvIjJS9hv+H6LbMjkJMVXQ24jhlxo5YUDCw/Vn5qoxpihFIrTE+6cga2L5w4hQFEI3P22DbeJ0rv/SLg2tGk+nMtsyvWjhy0ZkTZOcP3zPUvM3UZD73plNY21tCU4QB3Z5ph56CiaXLvOr4xXz+0WHKTsDNFx3fHHuAKB5uuX87l5+xlOOXlNg2VuOK9cu56/F9ZHWVshtBG82gn/8xic7/g9EqKg4DWRKdB1NTyBgSji/SPTO6wrQdCkJiQWeyHtKTFxetqhuSklLKahiqRtZQkDBIEQqPshNSsjTiJMFQU0DD0mSqfoipqkIOaodkDZWcIQiCPXlBclQVGVmGgqljqhLTbkRGl3HDqCnvdKKQJBUci5mGIkLRhGrB0CRKGUHMzJmKkGvGEQVTcEcyuooTJGR1tWFDntBm6fhhwowd0V0wMVSZMEkaBl4QxgldecEriWLROekuGEzVY6q+IH8K/oiCqapkVIkwEWZhQRyjpDJJKuScVS9AQhhv7ZvxWFg0mWx0LQD2VzzxegPBF4nShOl6SFdeJ4xTvChBlWQsPSWORZERJQllJ6TNUhivxbRlNbK6ghcmTNkBXXmdgiWzc9yjI6czWffRVTFrLmZUkIXSxQ1j/CihM6chIWbPOVPmA+eu5ppvP93csX3g3NUUMi2PihaOXORNZd51a2oSY5UA2w+5/lXHUvdCPn7/Di45tY/je0v0t1uMVjyemajPS/Jc1pUjZyoc3Zljxgn40Hlr+OYv9rKglKUjq1MyVbZN2PMnOrcKixcUWkXFYZCmKWljpDFZD7E0BT9IkWSpScarOCFdOXGBrbqhyIyIU5JYXJSmHJ+8ruFFIqe8kNEau3PwQqG6sHQTVVYoOwHtWZ2MLjoSFS/A0lXSVJjTlJ2AIFLozqvMOGJksqTNJEogRaLmBWQNFaPB7dBUmaoX0GYJQqGhCs6CFyW0Z3RmvICsruEGokMhNfwhVFmn5gfkDXEfSYK2rBgzqCpMV2c7GqFwE1V04jRhf8VnUdHE1GSGp13aLI2qF5I1VapuSBhL+BEsLBjsmXbJmXKjM6Gzv+LRbumkwN6ySymj4YQxuYaRVxgndKnC6KpgioLHCSO68oLMuXfaIyVFRqJoaYyWXfraM6iJhJ4TLqM5Q2XGEZwNJxAmXJAwXRf26qON519vjDIMRcJrBKIVTA1TEwZe07ZHV0Fnz3RA0VL57BtPbhJzq17A3rJHR1f2j7ZuW2jhV2Gk7FE0lTnr1o8iyk7IR3+wnY9csJbr797ME/uqmJqMGyb8ny8+xmffeDK6KlPMaPOSPCdqHu/62hNcddYAtz8iuhrXnbsaP4rZPeWwr3IwGRVEIfKR/xri5guPp+6Frc7FCwgtVtlhEKcwZfsokkzNjZl2AspuQNkWZEupIW9UZYkDVZ+sKbgViiQcGSfqAaqkoMgyE3WfshNQ9UJqbkzZDrADYatt+zETNV+YRaUJTiC4D3lDJ28KXkbZCTBUMao4UPVxgqQhU4Uwjql5AcWMRt2PIIW6HwIJlq41pbBxEqMpCpamoikSmiwspzO6yrQTiHyMvM5oxaNk6o3HVLAaF/WJeoDjp+QNDdsPMVSlWRAokhjnJCRMO4IPUvMi2iwd24/I6iq6qlCyhKFUd8GgYOpkdY0oSSmYGkiC75DRFExNwfEjTE2m6or3LYwjvDBGkYUvhaEq5E2FIEzozOnkDBVTk0WhVzCoeMJmve4LMqelKxQauS1uGFPxQuJEYrIe4McJOVPFj0UXBcTnbarC4bTihU2+RntO5LvkTZUbvruVh3dMMTRW5+EdU9zw3a3NzkoLLRyJyJsqN9wzNGfdXvvtzciSxFVnHYOqSM2C4sr1A3z9sRG8UEiyR2dcdk/avP+VcwnKV501gCbLtFk6H7tvO3//5ytps3Su/fbTLO3MUcrqDHTnm8TOhUWThUWTi9f18brbfsql/7GJ8z/9CI+OVA8mN7bwvIWUpq3SECAM4/TZBiO/mLDJGeKinzMUZElGkiBJExRJbsoXDVW0uzOazHgtoGSp5A2V/RWfUkYjThNUWaSNypLERN1nYcFsJo2OVjy68waSlJKmIml0qh7QnddxghizUQSIzongbJSdgJ68wVhNOEP6kbChRhKqlc6cyO5I0pS4EWf2Mj+4AAAgAElEQVQchClxGuP4adPpUlPE+ERXBFHRUGWCOCVOhIdGkgr+QJKmdGTFbl74dgg5aRilaKrUMNBS2TXpUsxoWLqCHURoioyMRIow8DJUkXeSNRSqboQfJXhh3IwZ78iKnJXJ2sGkUFWRSNKENBXhblGS0mZpTaJom6URxBGypBAlKWmakjUUdk+6tGUVMpoY70QN/wuQkKQURZIpO6IbVPMEt2J/xUNXZAoZ4WHRU9Cx/YQkbfBQdBVVhoSUJIFt4zbX3XWwjXztK1dzTHeWvmfJSru68oecJp+71p4POBINeH4TPF+fN/xO5le/dq3tsYN51+1Ad5aJmvCveXp/leXdeT703S2MVjxMTeZfXnsCXpQwUnZQJKgHMUkqApAf2jbOmSu6WVzMsHfGpcPScMOEzz86zHv/YiVhnPCerz85h9iZpCkff2DHIR2Pr19+2u9F7Hw+f96Hw5H4muZba7NobasOg7aMBpIInbJUhbFagK5CZ9Zk0vao+wntWY2qGzUIfBJFSygh3CimkFGZcQPiBHoKOjU/wlRlOnM6SDESQnIpHBoTZBRGax797RnUgjCFyugqVS9kQUHHCUCVYbIuCon9FY+8qYqRRpgCKaoq0ZkTctbZpNSevEEpK7NtzKMjq6Mp4uLuBDFlJ6CU0RvFhHC+zBoSTpBiaBJpKpE1FAxFkFa7CwaKJDFt+82LcU9RZ6Im+BCdOZ3JekAQx2R0hbGKT1dBdCvaMmJMpKuwc8KhYIqCqzNnkKQpkZZgqjJeJIqgNIEZN6SYUZEkiZofUsioaLIo7mpeiBuKWPrOnEbNjfHjCEUSRU53QZhxBVGCpsoUNKEeGSl7LCyZqHJKm6WjN9JTy25AZ94gSRIqbkR7VsMLErKGzIGKT4J4XmGcQCri500VPnLBWuwgaoxpIhE130ILRyhkSZp33T42XKYexJy+tIO+douP3ru1WVDMFgE5Q+Fj923nzS9Zysfv3wHAwqLJ60/rn2P5fcN5a+hUUt70on7aLZ16ILqWoxWvSey87tzV83IzJu2gpRZ5nqM1/jgMMppM2Q4xFOGUmdFkVFluuE/qdOeFt0FXQ5VgB0JBIBwrRau+ZOksLBrNubymKOR0hTAWHYsoEXHmmqw0sz9mnIA4ScloKqYm0VPQ8cKUshPghiL6u+aHdOYNihkNQ1Nps1S68gZFQydvKhQzGlldFX4ZfsxYNW60/iWCWPhgWI2RRELCgZrHtBOQ0RRkWXQiolhCksFQxAjAj2PyhkKcJli6ih0ITkOcQM5QmaoH2H5EydKEW2UQ010QXh66opAiot33lcX4I0xisrpQU8RpjKEI9chE3ac9q7Ov4pE3henURM0nb2hkVAVNkVBkMBpGU3UvoubGTNR9FFlGV4X7qaHKTNZ9xqo+pipGU6L7YOCGIX5jdOTFESnCtKxgKo2RjxjBVP2YqbpQsOR0jdGqhyKLnBbxPGS2jdfYW3bZNl5DkUWsegstHKmQJA5Zt0gyR3fl+MqmEZwgYkFBZ8Nxi7li/XIue/FSvrxpD3lTjFJnC4HZ8cf5J/YeYvn99994krxpsGpRkSnb5al9FV5/Wr/ILWrcp7eUaf6NWQj1VMs87vmOVkl4GIzXfYqWyPcwNWHLHSQJbiCizy1ZZm9ZjC5mVQZZQyaIUkqW4FrU/RDZ0MgZGrYfUfdjChkNt9FKr/kRWV3BjxIsXSGvKziSRNkRNtQA03ZI3Y/pzhvMOMKrIgW8MCKOZepBzMKCgRPEpCQ4vkreFCOZOBVR7bIsoavgRSLkbDYfI6srBHFCwRBdmTRNkWWJJBEFUdURLc6qJwqAmh+J+PachiSJIqXqCgdLOQeKJLN7sk5fR5YgSWnTFOScjhtETDsxUSMXxfEj8obGpO3TZumQypimzFhNFBR2ENNTEF4TmiKTN0XhEYXghiLsK6OpzDhBk2S5sCg6E2U7FD4SZZfOXMPG3AtRJZkwjVlUNMGlYZ+uQyqhyBKZjMSME+FHEQVTOIHWPWFNvrw7w7Yxp0HGFA6kdT/i77725CHt28++cR20eBUtHKGwg3jedfup15+ErgozPD9KuO3huT4U07YgdZqazNd+PsKV6we45f7tjRRlnfNP7GW2Sfe1n4+wabjMrQ/t5IPnraEzp3PDd7dy1VkD1P0YRYasrnDTa447RA3SlVFbZM3nOVpnv8MgbwjyoEjeDDA0mfGq8Jyw/bgZh72/4jUsr4Vdd9aQsIOQrC5STQVhU6gShGwzpGCK7seMG6JIKXU/pi0rlCMVN2wYbAnuxIKiiaHFqIrwqpi2Q9wwpt0SEsiSpVNxI4I4Jm9oTNkBbqiAlOD4QvKZpKIjMlH3CcKEhJS6H9FbyuCGKdNugK7KLMib7K94lCyNaTui5oWkqcjA0FUJXZUoZFQMRSaJY/bPeHTlDbwwou4ngEhOnbZDvrJxD395ej9xKsY2eUPDj2K2jlZZ3GY1o8v9MGkklkpYukLRVNgx4dDXbpAmMlN1n668ThAppDJ05UROiGUo6KpIg+0pGGiyRJSk5DIi38TSRfFk6eJzmXFC2rMatifst7tyBqoksb/qic8mVZiyA3pLJoYmgsV6GsXadF3klEzW/aZlseCRHHoyrXsxFP6oS7eFFg4Lx4/nXbdPjlR4/7nHEsQxe6cdLnvxUsH7SuHLm/aw4bjFPLRtnKs3rOL6uzfz+UeHufyMpZx2dDtZXWmG680SN+FgUNntf3UKpx/dTiGjNe/36Qd38rGLj+frl5/W8K3QWwXFCwSt8cdhMFH32TJaI0VkakzUxHhgxgmxG7JDWZaapEVZFqZJj24fI6tpzZ1uMaNiGQplJ8RUZUxNbbTJRbqoLMlYurhQ20FMZ1b475cdUbS4QYKlKSQJ2EFEkibkDbXpI2Fpwi47Z2g4QSRGBkGELgs5phNE2H5InIrRScnSyJsqCwsmSZpi+w3b8ayOHQguwVQ9YLIeUMzoZHVFWHtnNAxVbSSxwmd+vJOuvNGwKRedGUtXmKr7LCgYnLK0gzSFnKHwbw/sIEqi5lihZGl05Az8OMINRQ7IRE2Ej9W8uJE7IjoMwhckYKLuM2X72EFMMaNi+xF5U4NUBL7tnfFEOmkQMVoVipdSRkOWFNoshY6szrQtPrucKZxQa42MkSCKxSw3rxNEKbsmnQb/RBicjdV8DEVYg5cyOsWMRltW49LT+7nt4Z18/P4d3PrQTi49vZ9SVvtjL90WWjgsDrduB3ryzDgioddU5aYttyLDNRtW89C2cZ7YV+Xj9+/gshcv5d2vWMHpSzvYNWnPm9YbJ2nz98m6zxv/5Cg+/eAzc+531Zd/ScWPGnLSVkHxQkGrqDgMuvMiiyOOZcIooWCqHKi4tGd1CqaGrkjYfkhGkzA0mTRNCeOEE47qahAMNdosDb3BSShZGnvLLhU3ZMYJmWxki9S8iLyhEiYJdV9cZKtuiKUrSIi4dS8KKdsh3TkTQ1ExVWHA5ccRTpg0uAsBuio4Ae2WTsUN0TUZWZLRGhkhXhhjB8JzI4xT3DAho6tEcUScQBCnJCksKhosKIhxi67JdOYUoljEj1ddwXs474Q+bn1oBwsKJl4U828/3I4TxLRbGkEsTiy33LcdXZF4zUl9wnI8islnxEU3jBNUSaGYUQnjmI68hgQcqPoUTZWyE5KkQl2SNzXas7oIabMDQYrNaM2ocycQBmRxIiSvPQUDTRGETi+K2DbmMGkHZHShGLH9CDsMhc24qZLRVNosDUORGa/79BRMKl6A7cfEqeiEjNd9dEXCj2KcQFixz3cyDaPkV6yqFlr44yI4zLpNE+Ee+/67nqbqR1x+xjJue3gnt9y3g7/54mOcc+xCFhZNRisetz28k73TDh+9dys5U5uXcOlFB7kXSSJk9h8879gmr2L2fj/eOd2Sk77A0CoqDoP+gs6yrhwVN+Sj925DlSVypsbD28aYrPtIsoShqjw2PIPtCSJmnMBY1SOrK6iyRIKQeNp+jCIlLCyatFu6aPNnNKI4JZ9R8WMxTskbqti5ZzUUWagfFhYNFBTyGXFsvO4zVvPIGSIbZLzmkzPkxi4/ZLTiibyNjIofReiaIDa6QUzFi9BVhTihsfMP0BUJQxUkLNuPqLjCnhpE/knNDxmvRZiqSk/eQFdEIRAnKQM9JbwwZtoOOf/EXuI0bcjOXBGlXA/YNlZHU8CPEt7zjaeI4oQZJ2S0Irw7RL6HgpRK7K94zZGDqclCwinJTDshOUMQKHvyBhN1H10RBjwFUyOKJTQlZf+Mhx2EGIqQi07UAtotna68QXdOdHU6sjo5U4VUpitnUHFD6r4IaZtxA7rzBkEUoytKw9I8oSMr4t4n66KgsRr8kvlOpnU//iOs1hZa+M1Q9eZftwnw2Yd3MjzlUrJ0rr978yFW3Oef2IupyXzw1WtQZIlTl3YxOuPOS7gUpn1iFLK37PDTXdOMzvi85YylzcJi9n5emPDOrz3RCh97gaBVVBwOMZzeV6Arr6OrIjq8mNHIGDrtWWGAVPNCqn7MrQ/tZqLms/VAjQVFk4maLySbdoipKdQayZ62HzXNqKJY/Dwb7JXVNQxNFqRHRCx6VheEy4l6QJomHKj6dOZ0SpZOyRJdju68wbQdYWgyXXkRBW6qqjC7klUkJDKaQs5UaLc0TFW4c3blDRYXTRQZkFIKptrswkzUA2p+SEpMptEVmaz71IMYSRIZJcWMStFUREZJXqO3zeLG722ht91i77SDqclccmofH7h7C7f/ZBg7iBmecvmn/9pOkgqilq7IKJLoxoxVha9HKaMwWvEpZjQm7YAp26cjqxHEomjwIvGaRyseU3ZAzQuRJQkvgp6iga4qHKiJUYiw8AZJSojTlDgBJ4gwVQUniJh2Amp+RCmjkWlYiduB6GBYmoIbRthBRNmJccOIQkYjjFNqXtg023o2BKG3ZdPdwpGLQmb+ddtmqTywbRJTk+nOG/MWHisW5LjqrAEkKW2oSOC7T45y7Ya5ZlhXb1hF3lS4/IylWJrCHRv3ECdw9beeYsoJmsXJrLnW7N+ftIP/njehhf+naBUVvwoxhGHMVWcNMm1HfOlnu1lYzKCrElld2EwrEpy5optnJurESUKcJHTlDWpeI9QrTWnP6U3iZSkjXCVVWez484Zwwpyo+1RcUaiMVj28UDhKzkawy5JCd97AVGVm3BA/TMmbKpAw1SgCZIS8s+aHaLJKxQ1xgwhVlpAl8a/sBpQsYc8dxsJUygmEo6TZiDHPmSqWpiKjNOLZVfKmiDDfMV7H9mN2TdqsXFRkqu4jpSIAbXjKpWyH3LlphPecs4IFRRMvTDh79QIOVMSOZrTiccN3t1DMKkRxypQtCqWugsFoxcENYxYWjUZ4mUqbpaPJQh5azKhIyMgSdOR04aTZGJVIUiI8JxTR4VBkiTiNGat6JImQB5dd4f1xoOqhysIzpCdviNh2RSS7yohxy5QtFDhZXaVsh5QyItys7kdkDZWRaZu3vfyYOSfTt738GNozLU5FC0cuLE2Zd90qstS80EdJMn/3AYkP3zPE33/jKXpLFuv627j8jGXUvICbLljLRy48jr/7s8FmtzFO4DM/2cXlZyxrOnMmKfS3Z/jX153Ixl1TjfTjlpz0hYRWUfFrUDR1DlRFtsSrT+jjQMXFCRKmbZ+MrtCVN+hrt7hz0wjtlk4QCx5AZ97ADWOGDtSYcXzqvogw3zVZF8RMVUFtGDnlTZXOnIGlq40YcwNJkkhSkSqY1RUmaj6mLjUImrMqjwiQ6SkYGKrwVZise+QMjYob0p3XyRsaNT9mX9lhsh5gaUJyKi6cIWUnoN7w1XDCkKwhvDQqbkjFE7wNU5PRVIlSRuOzP9nNVD3gEz/aybQdUPWiZpehvyNDwVQpOwFhkjBZ8+nvyNBTMPn0g7t4x9mDzcIiiSV0VeZj9+0gTROiOGJhySIQTuNMOwE5Q8HQZCZsn6yuEkTC3dQNExSZhqumeH4yiuim+IJsGicpqqSIrpITULQ0coYwC8vqKoYmESciR8RQFQxVJttQ5Uw1VB6z5NOcqTaJroWMIKtmDI28IXZjV6xfzuVnLGVJm0V7q1PRwhEMXZVZUDTnrNsFRRNFlrjpgrXcv/UAeUPj2udYcV+7YTW6IsyuvDDBaHyP3/HVx7nhe0O886uP40cJ//7QLq7+5tPEifDE2HDc4uZY1tTEhiCjq3zg7qe56OQ+Fjbygppy0t8HEgxPO2yZcpjw4hZH44+ElqT016Aro9DblgHgyZEZ2i2NJIHbHxnmivXLKVk6qiy8JT754E7++eK17Ct71D2R2JkAB2Z8Vi4qMFETI4ScIUYiNT9kcTGDoknMNCSqtYZRForYXWd0BRBkzF0TLjlDkD4zmoKiQMUN6Ws3sX2JGTdAk4XSJKcrRAl4YcyMGxInKe1ZnYojOAdBklCy1GZhE0QJqqJQzCikKRQyGhIS0/WABUWVsRmfr27ay9+uHxAOlE7ASNnBjxK6Cgab91V49zkr+YfvbuYdZw+SN1Wm7YD3/fkqntpfoewE3PbwrqZULYgTrrv7aV53Sj//8ZNdvOlPlglORxwhIToRUZIShgl5QyS7Vv0ELxK24QVJZHkYioKmigyPWX8Q2xfjipyhY+kyiiwcOTuzokAThZfJeD3AUCSyhtoIdDMYr/q0NezCa74IInPDCCWSyJkyUsOx01AlYl0F/OZaaVnet3CkQ5CTFdb1t1G2hXw9ThOqXsQ7v/o4Hzj3WDRF4pM/2jFHVvrJB3fwzrNXcMX65dheiKHKXNtIOgUxvrj+7s1cfsZSbrlvB19/bITzT+xFkWFxyaK/I8NrT+7D0hQ+cu9WLl7Xx95pm3+68DiKhvr7qz8keHSk2kpBPQLwvC0qBgcHLwTeD6wEThkaGtr0rGPvAS4DYuDKoaGh7//OD5TC8YsK3Ld9koUli+3jNTKGyt+eNcD+GZ9P/mgHrz25r6nfnqwHDE/ZACzvydJbsviPn+xkeY9FzlDpLVlISIRp3DB6ipiouixsy4oLY2M8IiE8ISpuSGdWx4tiettMxqo+I2WXBUUTWYZ2S2fnhEubpZAzNCQpxdCEmdWUHZAkKZ05ncBUSdMEyxCSUyeICaKIhaUMNT9GV2CsGqJIJnGaojR8NPbPuGR0GVOXeemKbqbrPh05nQ+ceyz/+sPtvPuclahSSn9Hls2jVYIoRZMlQYJ0AiqeGIe89WXHcPMPtvGvD+zA1GSOXXQ8QZTSllG56OSjqHohSQodWQ0vjEW2SJwwZYdi3JEVoWGKIhFGCUkqMeMIfwtFEtJeN4wIYwijhI6cznjNQ1NETovocAgS5RP7apzcr1E0NYIo4bHhMmuXlHCCiI6cjqbAaDVAU2DKjsmbGookcldUWXQ4JmsB139nyx88u6CFFv5fQpEkdk443PT9oebF951/NsgJS0p4YcI1336KT/zlSQxPufzrAwetuM8/sRcnjBmvepiawqbh8ry8i/52UUBcvK5vjnX39a86FjeI+MSPdjJa8bjl/u384wVrCaOEruLvLyedcKNmQTH7XN75tSda38c/Ap7P44+ngPOBB5994+Dg4CrgtcBq4Bzg3wYHB3+vnrSqKiwumgxP2SQpKLKEhMR1dz3N8JTLh+8Z4uP37+DyM5YiSxIPbB3n6M4spqqgKhJ/u36AqpsQpwlhklD1I3K6xk93jOPHMZ35DEEckdPF7j5nqrRltUY0uAjnUWWFkWmHnKHQVRAZFTIicVNwKwTvQEICKaHuhbRlhBTT0kWA1we/sxVDlfHCmKyuYOlCsZLVVTRFpadgYAcRU/WAaSegYKqsWpSn5sXISNhBzD/9YDtv+uwm7tw0zIfPP44FRZ0ZV6S2Hru4yIXrevnQPVvZNl5j5aIie6cddFXCVOU5LdeOrM6F63oZqXg8MTJDnKSYqugqfOGnuxmr+FRdQcpcUDCp+xGWoaDJwgGzbIfMuCFVL6LmR2R0mZyh0ZHVhM9FFLOgYFLMaIKIqSlNSaylC/vvihswWvWo+jE7xuuEcUqYJISx+GLoikhpHat6+HFK1RWuqV4U0Zadn8w2WvPnW0IttHBEwIviZkEBYs3e9P0h/Chu/m43EoLhYLbHbQ/v5O+++gSfenAnhUZo4Hy8i+6CyT+8as0h1t1Xf+spxmpBk0PhhQl7pmxMXf2DjCom7eCwWSIt/PfieVtUDA0NbRkaGhqa59CrgDuGhob8oaGhXcAO4JTf57GSJCWny6xaVECRYOeEzbQdNhfxbCWfpNCe1dhw3EKqriAGduaEo+WWA1Uma74I2PEixqs+xx/VSU7XcMKYiWqI7Qt/CksTktQZJ8BQxAVwyvbZUxY7733TDlrDk8IJhGw0TNKG62OAlMpMVD1mPBEb7oYxbVkNXZWI04SSpRM2uARemBDEEdN2gEzcLFJMTagzZgO7FFmao2/fN+Pzi70zDI3WyBkqe8seI9M2y7pytFmCmDrjBNy5aYR3nbOSD92zlVvu28HH79/BLfft4MP3bGFZVw5VlklSqDkBliGUJq8+fgndBYOsoQIpfhzjRwk1N0RCFFIdOZ02S8hyZUkS3h91H1WWyTZMttwwxg0iFDnF9mMsTSVnqvS3Z8mbatND5K7H91FoRMf7oXAbvXPTMDUvYrLuo6vCgEuWRXckbxz+pGrpLU5FC0cu6l48vxTaE0WFqcnsnrS56qwBTE2eN9vj+rs3E8UpV64fmMO7uHL9AE/vrzBaced9jGdn7ZmazNKuHKNV91CfCgkmvOi34kZ0Zo1WlsgRghdiX2gx8Oizfh9p3PYroSgSpZJ1yO1xnHDPljHe9bUnOP3ods47qVcYKzErxdLnpPTd9fg+rjv3WK799lPcdMFa6n7MRM0nScHSNa759lN85MK1yJLESNlFzwvJ599+6Rfceuk64iShHsSYqkzR0qh4IXlTjEFWLMxTcSMyuuBeRA3vBglEEqhlAjpjNZ8ggjiGA1WHZWqOux8f4aJ1fUxWHTKGMPbKNZQni0omOUPGDQVpVGskd1bdiLovugUV159zojj/xF4+dt92Pv36k3CDGDuI+dh923n3OYNceno/d2zcw7tfsZKyE7BjvH7ISWbTcIX3/UUGXZW58XtbuPH849i4q8xxvUWmg5h9ZZv+jhyjFRHitWfaYeXCPJIk8ckf7uC9f7GSsWrQMKOKWdxmkjOEPLU9q1FzI6IkpSOnN6SkgrNS9yOSNGV/xaGnYCJL8H9fdgxtli7IqoHQyl9y6lENvw6ZNElpy2jMuCG2H9GVN5BIed9frGS88dkqEsIPI2/Ou45+k7V2JENR5Ofdc4bn7/OGP8xzf+5aK9UD1vUXufRFS3H9CMtQ+dxPdlKyNExN5poNq/iXRgLp5WcsZaA7f1hzq7se38enXn8Sj++t4EcJX960h1cdv5gVCwT58rmjwayu8DcvXY4iwwlLSnzpZ7vZsHYJbZaOG0bsqAjvnO68wa0P7eDezULi+s8XHc+yriwTdXFsSSmDLM+tNApJykcvPJ63f+WXzZHLRy88nmXd+UPu+3zD820NH9FFxeDg4A+ABfMceu/Q0NC3/pCPFcfpoZn1EmyecnlXY1b3wLZJto7V+Zszl9JdzHDtK1czWnHnVPLDUy7TdsCG4xYzXvNRJCFVvOvxfaw4ewVBlOIFEZau0duWaXpXeGHCVN1HbQRohbEI6HLCmIwqdsCSJCGpcKDiUcqYxHGCIsuQSo32foTtRyKMLIUoSRjsyVFxY84cXMCHv7+Vm16zlqoX8vEHdnDj+WsYnrLJGkIlMVkPyGgynhQTqmpTPjntBI3uxcEThSTR+FmEkN2xcQ+XvXgpPYUMN96zhYvX9XHj97Zw5foB/Cie9ySTpnDj98R99824IvBMlVlQNPjlnhlKlkhuBXjssSlOWNLGpt1lTl3axaM7y3hhzKlLO4gazpqzTpuqLDVHIF4oiot8Y66aaQS4TdVDlrRlueaep7l2w2o276/SUzDoyBkNwqXEJ380xF+fuRzbj3lmss6KBQXiNCWMUiZqHoaq8OkHDwYvXf+qYyGN56yjrq78b7bWjnCUStbz7jnD8/d5w2//3H+TtWZoMheu6+Pvvvp4c91ed+5qDE2MJ7sLIoRvtOJxy307+ORfnnjYAuFd56zkyZEKA905bnv4GS4/YxlVN2Rk2ubaV67muruebj7Gu85ZQSGj8rFvPDXncX+45QDv/LMB/Aje9B8b5xwLI9g6VmfXlM3/vfNgsXA4AuYpi3LcfcWL2V92mlki1ar7W77rRx6OxDU831qbxRE9/hgaGnrZ0NDQsfP8+1UFxT5gybN+723c9ltjwo14cl9lzhdqtOLxvm9tJq/JrFtSYNXCwpzjC4tmI2YcOnO6UAkkCZeefhQVN+DCdb08vb/GpB0QJQl2Q2FgajKyLCPLEqamkqQwMuPSbul84ae7SVPRwk9J6SmYRCloisqeSZvxmk+cJiQJzejuoqUJgmYMB6ouQZzy2pP7GKt57J12uOTUfr7x2F4WtWXoyhmQwoKCwSd+uANVlpmyfQoZkZFRMDTSNJ2jb1ckcXIxNdFFuXhdH7c9vJOnR6tsOG4xt9y/neEpl88/OoypKVy9YVXz//Z3ZPjMG9YxVvOb9+nOG9z1+D5cX2Sk9BRNMrrKlv1Val7EW/50ORUvZHl3DkUGCYk7N43ghhF1L6JgajwzXqfuh/hRShAnRElCVtcomBpOEKM2zLYsXSh6ql5IEKXUg4ijO7NoqszOiTppI3Dt1KVdBFHK/hmX2x7eRZwk2F6AHUZ0FTJ8eeMw/3jBWj58/hpuumAtX944zKTTcgVs4ciF7cd8ZdOeOev2K5v2YPsxpqpw/d2bOf/EXkB8vzO6cqi89JWr6S4YvO3OX/KRe7fx1jt/ySWnHsUpfUVWL8hzcl8bCwo6N190PDIUgRYAACAASURBVFeeJeLTwyjmvY2CAsSG5NpvP82rT+xFV9RmAfLsY2988dHNjuhzCZjzum+m0N9usbLDEuTMlurjj4IjulPxO+LbwBcHBwf/CVgEDAA/+13+UMULWdaVm7dSL5oaJVWhr5iZc/ySU/u4/jubee+fr8JptBcXtVk4XsiSDotCRmO6HtCV00nSlLasRtWNuOqsAe56fC+vOamP8ZqPKkssKpmUnYBLTj2KzaM1FhUNQkUjTiJSZKI44ZiFBZxA+FAUMjqFjEhCNTWxI3cCYcvbXRDS1+6CwfbxOiNTNqcv7+L2n+zi7WcPAqDJCpecdhRyo5UPQvo5ZQcostwkW846Yl537mrRjZGlOd0aRab582jF48P3DLGwaPLZN6yDNGXGjXh8pIIXxk3fio98f4i3nLGcKJEYrwa85+tPctMFa3HCmJGyQ84o0GHpzLgBKxcWyOrCGdRUFVRJYrLuN1QewnJcUyTufWqUV5/Y2/ALqXPa0hLjtYB/f3An737FCqIk5cJ1vZiqwmjF5ZiePJM1nwMVj6M6RfGyfbzODzYf4PIzlolAMi9kWXeeihtwwUlzd3zvf+VqvLBl093CkYsgiuddt0EU8/lHhxmteEiNDcN7zlnB5v1VFpVMbrpgLcNTNqsWFRg6UDvkQv+ebzzJ1y8/jZUdok3f3pVlvy3I1VU3Iojm53KUnRAvmP/YjBM+qyM699ikHbRUHUcojuhOxa/C4ODgeYODgyPA6cB3BgcHvw8wNDT0NHAnsBm4B/iboaGh3+lMb2gqN96z5RBC0ofOW9M0aunKKNz0muOax7vyBkGUMmP7xCnMNNIvp5yQR3ZOo8gSH7pnK3YQkQITjcyN2x8ZZsPaJeQM4ZzZZomo8K6cQYrEfVsO0Jk3yRoKqqLQZom0TCeIufm/huhts8hoMk+NVLH9hGlbmFq1ZXXiJGXvlI0kwZ7JKif3t/GadUu4+ltPsWm4wmjFZ/ekTcULKdsB7/3mU8zYAWMVDzdIKJoaw5P1Q96fBQURPLZzwm5+8b/28xFWLigcQpoqOwFFQ6VoamwZEyelB7aONzsYT+yr8rXH9hAlosvghUnDvEtwPKbqAU4gipE7f7YHN4i5cv0Ajh+zebTGvrKLIgnfjp4GyXP9ygVU3AhLV4mThOl6hKbIbBuv88RIFT9K6Gu3COOE2368i4m63yCYhqQknLCkhKlKvGLNQj794DN05HS8KCFKhcz0/c/ZXb3/rqfJ6q0TXQtHLixdnXfdWrraNKg65ag23vVng+iaiDS/6o7HeedXH6ctqzMyLVxv57vQD8+4glgpw6N7q1z874/yhs9s5J1ffRxLn98eXJEksub8x0qW1uyIPvdYi4B55OJ5ewYcGhr6BvCNwxz7IPDB3/cx6l7YbM8/2whmQV4/2FpL4bTeAl+//DQm7QBFkblwXS/X3LWZj118Apoq4wQJd2zcwzvOXtG8ANe9mDSFHeN1MprYdW8bq3HqUe08sW+SE47qIvZjZEmQMP+/M5YzWvHoyBq4QULdd8noKkGYsGm4QpSIOf/KhXkm6gGFjFA3VOyQtb0l3vetJ/nAuat5+1e28p+XncyBykEJ1qKiwY4JkZAqnCtTUklqkiBrrk9XwaTmhoDwfMiaGv/7Px/j+nNXs6z7YDdntOLxiR/uaPp2PHsO2pVR2TLpkKTQZumcc6y4WF/24qUoMpxyVDtpCimp+HuRuNi//WUDdBeEsiVJYc2SEqos8eVNe/jb9QNIkpDFDvTkAHhk+xgvOqaH6TSl5oYsKBocv6SAHaR8beNePvyaNWR1lZ0TdZZ25XCCiNed0s++ssuXNu5hw3GLeWj7NMd0W6xYWODyz/8cL0yoeRF2EFP3hMfH4XZQ/bnWCa+FIxOT9fmll1N20BxtjJYdeooZ3tbgMcze5/q7N3PzRcfTXZifiPnU/hpvvfNxbjxvDf/5093NcybAbQ8/wwfPO5bhKadJbG63dD794DNc+qL+QzgYH3jVsSRpwrqj2unryLJnyubOTSOUneCg+2ZrvHFE4nlbVPx3YFamNFrxmkYwpibzF6tOm3vHFLpMlS5TZTqI6Wu38MKEkbLDsu4cNU9wDj5y71befc5KUaHLkiB/bh3nDX9ylAjqQaSa/sP3dvDJvyxQtn0yulBiyJLEZMMDQSQAKigSdOZ1TE2m6ok5//bxOhU3ZLAnj4RQc2wbq3Hxuj7+5f7t3H7ZOiZrYTNYyAsTwjjlH76zhX973Yl0FXQuPb2f2x56hre+fJAnRyrkDIV8RiZbzNDbZqEoEv+7caHNGCp3/mwP17/qWK7+lpiZbhuvUzBVvn75acz4MSVDaZ4EOrMGigQXrjsoVZt9b688azmdWZ3Viwtc+8rV1L2I157ch6aq3PvUPl6xppcP37OPt589SNZQeMufLmey5nNUR5ZbH36GK886htGyw9r+TnZP1llcshiruDhBRFbXSQh56YpukiQRQWKWhhfFdBdMPvpf2/irFx3Na0/ua7Z2+zsyvOcVKw+OdSQhq/2X/3UCWUOZ98SaN1pfqRaOXOSeQ7iGBvHSULn5ouORZRietNlX9ectPp6ZqItu7flr2D158EJ/9YZV1LyQN79kKTfft413nbOyWZTMjlKiOJ1DbH7ry45hoh7w0Xu388+vXcttb1jXcPnU+dxPnuH4JR2HGGgNdudYmFUhee4ra+FIwfN2/PHfgeeONn4Tj/p2Q2FBwaS/I8PKRXmCOKHN0vnyJrEDnqh7XP+qY9k9WReeFmsX8aWfDrOmt8CSdovOnN6QqopEzCiB67+zmZSUjKbQbunkTZWHth1AU2QcP+JtLz8GVZaouiHTjnCwVBWZuhdx60M76e/I8uVNezh1aRckggyapmlTi17zY9osnXoQkdU17ti4h/UrFrB/xuNzjwyzuM3iMw/vxIsSJurClGr2hNOR1ThlaQcff2A7l714KVeetZybLzqeBUWDroxKd95g0g6YcIXevCujsGphoVl4PRtJCp/40U5sP+aBraN05Q2WtFk8M1GnI28RJQmXnNpPKaNyoBpw71OjHN2VJWPIXHLqUXhRQmfBZMoOyJk6I2WH7kIGVZYZq3kEYcqkHaApKv/8g22UnYibvj9E2QnZcNxiPnTPVm5/RHSl3v2KQS4/Yxm7J+3m5z/VMNhRJInRGaf5/s2ujavOGqDTagWKtXDkwtKUedetpSkoskRnVmdRyWKgOz/v2GHFwoIgZ375cT714E7efvYxfOr1J/HpB5/hxu8NcetDO7l4XR8j0/acLseUExxi633zD7Zx/om9lJ2AjbvKXHLrz9g2XuOyz21koKc0r4HWD4bGeXRvtZXrcQSjVVT8KjRGG3df8WJuf+M6vn75ab/eSz6FwU6TK146wIwdEscpuydt/upFR6PIMF4LKNs+xy4uEMYJX/jpMBedtIQwTnn7Vx7n1od2ct25q1FkiRu+t5XJhkIiTeFD92xluMGN2LC2V+SHeBGGIlP3ArryJook+AtpKvTNj+ya5vOP7OaKlw7w050TjNU8wjjhmm8/Tc5QRTyxrnDhul6eGa+zt+w01RtmYyxT8yNevmohH713K3um3SaRC0CRZT523/amre8t9+3grXf+EkWSeXSkyoaPP8yl/7HpoMENcOKCHMs7s4ectHIN8mXVjXj1CX08va+CrsmsWlhgSZtF2Qn57I93o8gKuybrnL6sg50TNpauUvNCLE1h21idPVM2iiRhqApTjZCx7oJJzQtRZRnbj9hw3GK++LNhNhy3WNh/N8ils12pmhdz/d2bSaF5Eh6viZmzE8RISIcEM/W1twLFWjiy4UYhi0tz1+3ikkk9CPGjhB9tn+SKL/2Cj9y79ZBI8xvOW8P1d88tDN73zaf4+XCZ4Sm3edst929nwXN8FZJ0fsKlIsPbXn4MX/jpHkxNZqA71zTKmu/+lq6wfaLO4+N2KzTsCEWrqPh1+G1lShJsHne5+ltPYQcx+2dcBnpyOGHMpx/cycfv38E//WA7bphQcUV7P5/RGW+0Gx/YNsk9T44yUQtoa3QlTE1m82iNNktvkA5TMXrQFNpzBnc9sY+uQoYdYzU6cwZXnTXA9vEaI2WHK9cPNAuLt5w5QE/BxPZFTPlXNu1l9aIili7T127xwNZxFhbN5gX23x98hms3rCajKnzxZ8NN2egHv7OleaGdrM/fJnWCeF4v/glXxJAuzmqHdIGO6y1y1VkDKLLEzok6U05IVpdJSJFlyDeCv6Zt4dS5vCfPHRv3NM23frl3BjuIuXPTCLIE7VmD2x/dTTGjMV4VZldLu7JkTZWiqfC6U4T9sCLByoVzyaWzJzU7iJvdC0WW+ND5a+jKC8LmRNVjoDtPX1uGNYuK9LdbrTlvC0c0LE1k6xzTnWdJW4ZjuvNChaUqpGlCnAhZvEgXDfjU60/iHWcfw7++7kRKltosHmbhhSLO/Lm37WnkH83icITLMwe6+NNlHXz4vGP54mWn0p035pwTno3+jgx5U+PTD+7kzbf//FAnzhaOCLQGwH9gTLgRP99Tps3S6cg2FBph0jSHmiUu+WGCZajN9n5/R7bp0Pnak3tpy2v89Z8uRZZEJU+acunp/eyvuGh1mbW9RUYrLgtLJpecehQHKh71IBJtTEmQGTfunuabv9zHZS9eyooFeZ4YmYEk5qSjOunvyPCaE3vZOVHnjo17+MC5q3nFmoV87ic7ee3JRzUVGfxsmL8+c3mzezG7m7/9keFmhkd/R4YNxy1uvra7Ht+H9xyG+KyV+fCMCyWLrowyh+DamdWZtANuf2SYv//zFSzrEoY66we72DNdxwsjxioe7zlnBQsKBmUnYKoe8NqT+4iShM6cwXjNQ5FgcUnEyD+1b4aL1/UxWfO54bvbuOHVq9BkiYoTsKa31DTb0VSZmhvMIZfmnmXDXXaCJu/jHWcfQ95Qmw6is/Peq84aoGSp0OpUtHAEYzak75pvb56zdtuzEe1Zg4e27ZrjEDzLZfjyxt2cd2LfvHyM5xpWmpo8R4pvNrqNN73muENSRJfkxLhw20TE5V94jDZL55oNq/jUg89w5fqBOc/j2TwNaIWGHalofRJ/YEzaAYYq86YX9TNZ9+gpCJOli9f1NXkVigySJLF7ss6iNotlXTn2Tgu/fTeMKVgGmiRjBzET9YDP/ng312xYxVvv/GXzSxc1uxUaB6q1hueDwm0/3tU0uerI6k3i4ZtfshSAWx8e5n15nWtfuZpf7p1pEqe2j9ebF8kwokm8fGJfVaSWynPbkbOOey9Z1s4VLx1okjT7O4TTaEaTmyeV2VCiZ58gZl3xZgmuAiJCHiRue/gZ3nLmAF6YcN1dT9Nm6Vz7ylWMV71moTVV91nSZmGoCmW7zpI2kxSJdf3tPLanjCTBA1vHeNvZg5SdgL//5maueeUq7vz5Xt78kmXN1/OlR4c5c0U3MxWPmy5YS5omyJI42d6xcQ/vOWcFU45QnnTnDWRJOqRIvGPjHo5bXPxvXGkttPDbI4zTedfutRtWs3m0ykuO6W5+T2c3AnvLDm940VL2lQWP6NnF9FtfdgymKs8pIEQXU5qzYZjloR1yWypyPmaLjdGKxx0/28O7z1nJ3mmbmy86HieIGJ525rX7b3lWHHlofRJ/YHRmDTRZYtWiAk/uq5LRVdosnY/cOzQnDvjd5wzypY17uOG8Ndz8X0P8r1P7sb2I9qzORM2naGl87L7tfPTCtZSdgKdHq3Mkm1e+bIDedou6H/Gx+7ZzTHeOt5y5jIvX9eGGwr2uzRJKjpsuWCvMqu5+mivXD1ALYPP+6pw558yzyJezduSXvXgpxy7Ks7iYQZGleXcpiqxw9bcOPlYho/F/GjuO2RPQfKFE8+0wZomxkzWP9SsWsHW0ytGd2ebr/rcHdvC2sweZqAcYioyfxsiyRNkJyZkiafXGe7bwtpcPoioSnTmdt5w5wFMjFa5cP8D9Ww9gajIXresjStLm6/n6L0cBuPDkPibrAQuKGS79zM+ar0nXDtpxX3XWcjK6wl+96OhmoaFI8FcvOpo4aVHSWziyESbxvGvXDiIGevL8Yk/5sBuBqzes4ntPjvK5N57MpB0gSxI33rOFIEq5/IylLO/O0ZMzKJmq4BY1VHFAcyw4ZxPRuO25CaNP7Kvygbs3c+Nr1vDz4fL/z965hzlV3on/k2Qmk2TuMAEGBlBgeLmLSpW2ahWsqy4rFaXSbrWtWLatVFut26qtttp27c/bYu3a2mq97CpqsWp9XOu167pKFRVRxBcoOjA4wABzn8lkcvn9cU7OJJOTuWYmyfD9PM88k7wnOXnPOe/7nu/5XvHmu/Dmu5g7scR2DZKcFdmF+FSkGb/XRWWZl6D5RFDmc7N5TyPLFkzikU3GE8LaJTPAARd9+ig+qm9jyawJ3PHiDtqCYSpLPfiLC+gws8wVmJJ/vE1yy95mwmE4aCbOiuV8yHM6ueOlHZawEMtm+Z2H3+HaJ97nsiUzeenDfUwo9RAIRZLsnPGv65oC3PPqLqaWean05eHJcySk2o5pG1oDXVZRtY6usGU+iDeRzKm0L0pkV5bYnedk+rgiHtm0m6ljCyn15iccd31LJ4VuF//27If84bUaSr15FLicTCjxsm1fMzWHOnC7HJR58qhvCfJhXTPNnWE27znEykVTeGd3I9c9tZXahsTojWe27mfznkZmVvgIdIasY2jtDCekEH50Uy3jigsSfGR++8ou2rvClHplcROym+KCfNuxO77Uw97DbSyaWk5v1UnXnDIdl9PB//vLh9zw9AcsWzCJ84430nqrikKmlRQwxu0akG+RXYXRhvYgfm8+Z84ax9wJxXxu+lhmj/UOOBpPGHlEqEg3UZg+tpC2zhAXf+Zo9jcbaW9LPS7L0fHOl3by7y/sIM/hYOb4YqtOxi+f1fxgw3s0d3QyxvRVaA+G8eW7KHQn1s/YcaCF+tZOCvKMZFuPbNpNKBKxFgG7STpvQhHXnDWHjw+2sX1fI9PHFVk31lf0AVuhIaainFdRyKKqUv7w1UXcc9HxViRMRWGBlXOip4d3zEQSC5OtLPVw6WkzWLtkBpcvncF4MxV4jPqOEJc/spkd+1u5+DNH09TeSSgS4SdxtQdaO7vYZjqtXrh4Klv3NlHszaMzZDiMefKdtAS6mFReaKhpzWqKX1k8jeuf2kqe03jSuf+1GooK8rji9Gp+9aVj+ek5c5k/qZQxHlfCItfTC72uKcDhtq6kNMXrXtxhVTgVhGylwxyrPcduIBjmR09+wI+ffJ/rl81NMnfGPvvh/ha+cu8bXLBoCgC/fnknd75kRH3tOtz/UuXx9Ba67/fkdTvJR2Dx5BIeWn0id/3zsTy0+kQWT+4jGk8YcUTEGwb8HhdtpR5qGzro6AqT73Qwe2IpP3rivQRb5r2vfcSPzp5Duc/NiuOqrPZfv7yLW1bO5yem38MTm/eybMEkIsC6VcfichhJbH6wYQvXnD2bORNKmHyal0IzFe6Gt2qTnJxuPm8BYwpc7G/pZMueRs6cX8mtz2lWf/ZoHlz9KXYfDnDHi9ut7JbHTylnToW3O8lM1MjBEY5E6QpFiK0cfq+L6nFFlPvcqPHFtupJT56La86aleTceHRFEZ+NWxRiatCqMT521beamhQXwVCYK06vZmpFEZ1dIdx5LkuQueTkaWzZ08TcSSX8+d29XLakGp/bKHEe6Irwij7AmlOms785QKArwtFxoawFLgdOTz5XxdVBuPm8BSye3O1UFjuG+GNqCXSljHgRhGymI2ifCba10xCIaw518JtXdnLD8nm2czka7Q4bXX3StISkgLGMmqmqiFo4jAcIw7eiwNZp2zZjpsNI/93T2bPPMH9hRBFNxXAQhVDIiPiIhX1+VN+dqwK6bZljCvONDJav7mLDW0Yo5EWfOYr2zgguDHV7TMNx/2s11LcE2HGglR9s2MIFi6aQ73TgLXDhzc9D72vm8qXVNLQHeXBjDVecXs0fvraIX606lukVhYChajzv+Mlc/9RWIx13FA62dHHtn95LyDXxL//5FvXxFTcdsLG2mRV3b0zKOzHTX8hFn57K/a/tSoptv3H5PJragzQHQklPSD98PLHaYExDEAob527GuGIOtwZ56t29FHry2fpJE/+64T0eeWM30/1GPPuGt2qZPMZH7aE2vvW5GYbfhNtJsSePqWO9Virw8SXGvvc2GmG2KxdVUdsU4ManP2DmuCLu+NKx/PSf5uJwOmgMhq1F7rNHl3PTufMTjmlimdc2PK6yh+ZFELKNMYXuFLU0Cqgs9QCGYKHrmvmZKVjEPnPZkmoef7sW6M4x0XNbQui4Hb2sIwlaCRshob4jlDpMXcgaRFMxTLQFwyxbMIl7X/uIH//jHKM0d31rQpray5dW4zBTP8fU+fHahbu/cjzuPAcOB9x8/jGU+fJ48+MGax/Pvl/HsVMUDe1h2jpD/OG1Gr55yjQroVWx1823/uvtpKfwXQ3GhFxxXBWH2oMcarevBxDvVZ1qQj++xkhZvu7FHaw9bQa/eWVnQp2UO1/ewb+vXGgVCevtN2Jq0HAkYoSCmuadi0+azhWPbuaSk6dR7nPzqaPHUtfYYaVQv+uvO/nBWbO4/XnNucdNJhKBvQ1tXH3WbL77iBExs6+pgxvOmcfexnae2LyXb39uBnsaO5g5rogvnTA1oWrjDcvncdrRZZZT2Yxyb+JTlC/PNjxO6hEI2U5DexffP0Nxy3M6IYLjqg3v8rXPHMV9r31MQ3uQ6eOKOdQaMJNjednb2MGz79dZGlWXA5aocRxTVUpbMMLHB9s47/gqNrxVS11TIGVERm/rSF8RHD0dOmPfl+iP7EKuxDAxscTDLo/hG/BJYweTxxZawkNsYga6wtSbyaNWHFdlOXLGzCD/+bePrHDNcp+ba8+ebRXjuujTU5kzsQSnw4XTEabQYySG+s0ru1hxXBVTxxTyvRQx3ROKC5g61suUci97Go1kNn15VR9sCyaZaTa8VWs5W5b73Iwv8VjajngCXSEWTSnv23PbzGBa0xLk1ue388OzZkMUtu1rtr4XM3uU+9yWiWfL3ma27m3mVDWeP729hws/fTSH20O4843Im2+fOp1DbV28s/sQX/vsNKrKfdQ2tONywJpTpvN9U6CInafrnnyfh1afyORCu5TbjqQicinVtYKQZZR48olEItxy/jFsP9BCOAL3vfYxdU0Bbn9hO1ecXk31hBKa2oOUeN089oIxl7996nTOml+ZYL6c4S8iz+lMEMgvW1LNI5t2p4zIGIpgENNkSvRHdiNCxTDh97iYP6mM1z86xN2v7OLG5fNstRG//crxRiEq05EzftttX1zIL5/dZiWvwgElBS6+9blptAXDvFXTwLFTyvC5Xexr6uDfVszno4NtRKJYeSxixGLOP2roYIwvj2+eMoNPmoxy4U9s3pvggzF1rJefnjPPFBgc+H0u8vOcXPTpqUkJn8YXFxCOGDf72oZ220lf6snH78vjpnPn88M/vdf7030UukJhLlg0hZv+exvfXTqTAjMOfsNbtVzx+ZlWZEZ89dhFR5Wzt7GDi0+ajt7XTBT4pLGDiz49lfrWTp7cvJcLFk3h4vs2Ue5z8/XPTGVCmZdwNGq7yO1vCRhChamutbPj2oXHCUI2E4qEGFfi5cP9Ldz5UqLwX+5zU15YwLf+8y1rrF/x+Zk8/e4nTCjx8J317yQ9pKw5ZVpC2x0v7eC3Xzkevy+P+nbTb6LIKCK4v6WTYk8+U8d6EzJz9lcwiGkyRUOY3YhQMVyYN8dYRMSBloAVpRGvjag5ZCS9qirzcfNzHyZs29/UYQkal5w8jaICF9MrinjvkyYjVe3J0yjMz+OqDe9y6eemEwxFLNPInV8+NmXyqbv++Th++rSRUOqbp0xj1aemWAlxSj0uxhZ5+GbcwvLbrxzPB3XNtl7jn5s+Fr83j+pxRfzimQ+THER/ce58Y9JH4LNTSvvljIXDCI2dOa6I8aUF1LcEuOLzM7nt+e1W/Y2YYPHrl3ca6X5n+nHg4MN9zTy2qZYbzpnLz575gKvOmMWug21JGUF/8d+aqWO93HL+MbaC0Phiw748FHWtIGQbLqeLcSVOPjqYrJ1cuajKSmIHxli/7fnt3HL+Mbz3SZOt8G2XotsRjSY5VF6+tJoHXq+hoT3IjcvncefLRsTbgAQD0RDmBDm7Kiqlbgb+CQgCfwe+rrVuNLddDawGwsBlWuu/ZKKPsTLfnnwn/7lxN9ecPSsp8Ywnz8nYogIckKSp+N2Fi/jGg5sIdEXw5jt5+I3dXL50piWobHirFjW+iJpDHRxoDXLnyzutiV8bl/2uZ8x5W7A7D8Nf9QG+8blpzK6cR2cogr/QzZfv+VvCwvLW7oaUBYFiasvpYwstB9HVJ02j2OOiqsyHz+2iviOM39udDKe3p/tYmvOYr8P7tU1Ulnk53Bo0VbPF/OwL8/nRE+9R7nOzclEV1eOK2N8cYNfBNsYVFeDOc7CvOcCqT03B43ZSPb6IbXXNSf2vOdQB0UhC2faYc+nk4nyIiB1XGF2U+fLYub+dsYXupOyYdpWDA10RnE6scO2ewrddiu4iTz5rTF+u2D7WvdgdLfJj07zYGugyNZ1Rth1styJB+irYKBrC7CaXoz+eB+ZprRcA24GrAZRSc4BVwFzgTOA/lFIZKcgQK/Mdi8jwul1JiWcOtXcxrcJHmVkePZYc65KTp1k3wspSD0XuPFZ9agoHmgOWoFLXFCDP6eCLx1cyw6zuF+P+12rw5buM6pnl3oRt3nyjrsWCSSWcMbeSi+/bxNWPv8fWT5qobepIWlgsAcjWa9xQW/o9hmqyoT3I42/XEo3C9//4Lhffv2lAhX8OtgUJhCKsOWU6P316KxEMtey9r31EQZ6LD+ta+NVL27l8aTVrl8zg7ld28YtnuJV2LAAAIABJREFUPqTYk0c4EkFVFnHdsrn8/JltPPB6DQV5Lm76723MnlCS1P+pY724nC6OGuPhwYtPsGLfTz26zAqltUvMI3ZcIVdp7ghz83Mf0hYMM29iCf/x5eO4+fwFrD1tBvubA7ZjvSDPxca/13PZksSS6Vd8fiZjfe6EtpvOnU9nl33YakwDG+iK0BroYnaFj+31bcmRIFIgLKfJWaFCa/2c1joWS7QRqDJfLwfWa607tdYfATuBEzLRR6JGme8l1RX84auLKHA5LTNDTHBY/+ZumgMh9L7mhORYv//fXUwe47Oy2/3bsx/ywOs1RIEpY31W0qptnzSy6KgKttU1J2XEvPe1jzi12s+Usd0hkJWlHksdGbtxx3w97n5lF9v3tyYtLH9+dy+zxhcnZKBMymYXp5q8beWCJFNJf0O/KgoL+PO7e4li+DpMKvOxeU8jK4+fTHtX2Cqz3tppZO+0/FRe3M5RYwtpD0b4u1kjoK4pwDu7G6k51MFdf92ZkNxr6lgvV56h+OuOev5n52Fe3XkQp8NhFDiKWw97S8wjCLlGY7tRh2jdizv41w3vsbm2EYcDq05Oz5Dw65bN4Yant7L6pOnWQ89lS2dw1z8fxx/+72N+88ouaz1bfdI0xhe7KfXYh61Go92vKwrdEiI6ShktK+PFwCPm60kYQkaMWrMtM0RhjNvFGLeLDw63J5k4LltSzeG2IBXFHisJExgT7KZnt3HbymNoiUsb/ctnNZWlHi769FR+d+HxFOS5uOgPb1jREPFFyxZNKTfU+NF8y8FpxXFV3PD0B1z8maMtZ85484hd4qzvf16xaFIx08b6WFhVSnswTGVxga2Tpd+TNySTgd/r4pqzZlPiM9Jzf3SwDXeeg0llhrYltt9Ypsv4vgdDH/HdM6otYSzQFSEYNo5hy95mxm7dx28vPJ7G9i4ml3v520eHk0J8jyr3GmmG445J7LjCaKHUm29FT/V0Gr/+n+bickS5+fxjaA+GONwWpKmji5pDHew40MpN586nPRjm3b1NfFDXTIMZih6fAOsf5yy2daiM+VTEC+XbDraPvGnRJvGWzOX0ktVChVLqBWCCzaZrtdZPmp+5FggB/zWU33K5HJSV+VJsc6bcNhBKO0JJjpovfbiPH5w5m799dDgpZPMVfYBAKMInZk6G2ASsawqw7sUdPL32JLbta7EEjmffr2PNKdOt+huefCe3rlzI6crPGbO9zF57EjvrW/n1yzvZ8HYtV58921RvJu475hcxf1IJM/xFTC7z4nQ6KCuBaf04zokRe/vrxHJfn+cxEokS+qSF3fWt/OSf5lLX1EE06sKBg0OtndZ+Y1VQ49Nob9nbTCQMNz27zRKMYunH3919iEVH+fmXBw0H1Du/dKyt4+mxU8qZNq44qV9lpVDdj2PvD72NtWwlXXNgpMnVfkN6+t5zrLXUtyUJ42CM/5/+eStrTpnGHS++bwgZy+by8BuGIBCKRPAXezjQ0skdL+6kstST9PDxsy/MZ/q4YpxOB2cUG+vNgZZO/EUFuJxwTFUZ44oLrPVkYnjw60RPIpEoexo72Lm7AX9R92/0/MwLup4rH9uctD72/Gw2kWtjOKuFCq316b1tV0p9DVgGLNVax+TNvcDkuI9VmW29Eg5HaWxst91WVuZLuW0gdHR2JThqlhS4+Mrio3hndwMLqkpxORNDNm//4kKr3LmdFqI0DyaUdMdunzxznCVQgLFQXPnYZitSodQJU0q9VqbJW5/7kOuXzaXYm5cktNzz6i4eWn0ipU5obu7o7bCSKHVhG/pV6qLP81gfCHHlY++ybtWx7G/qoNDtwl/iYX9zAG++y3IuczocXL60GqPke3ffP6hroeZQBw9urOGas2ZRVugm2BVi+bGTWX3/JstHJYq942lboCst1zqG358soPQ21rKVdM2BkSZX+w0D73t/xlqRJy9JGI8R6IqQ53Rar3/6tCFknDW/kmkVhZS6IFiQZ/lzxR4+XE741NQxTCjOT1grSp1QWtqdZbbYfB37zFDWiQR6CfuO10IYa8vmlOtjtpKNY9hurMXIWZ8KpdSZwL8C52it48/4U8AqpVSBUupojAfMNzLRx574elQIBOMGftsLO9i+vyXJ3+Lv9d2+ATEtxD2v7uKOF3ey5j/fYuOeZmZPKOSGc+ZZC0W5z20V7Vq7ZAblPndCNVC/18UN58zjjpd2sKmmiYffqCHf5UxywrpsSTWdXYO0bUa7C//85ivH8fAACv/ETCehcIR7/u8jmgJhvPkuxpd4LL+S1SdNY4zPbapTjUJrU8d6ufS0GUzzd9f2mFjupbEtyPgSH580BhLCa/eaOTXikVTbwminrTPEZUuqUzpezxhXZKXrDnRFmFNZwumqguMmFBnmTa/LSlsfe/jw5Ln40ZPv0RUyJ7jDuIFvO9RHgbE40+IDX1tkFSkcqDmiv74ZvZllhfSRveJZ39wJFADPK6UANmqtv6m13qqUehT4AMMscqnWOisqPbUHQ5bg4HDAjHHFfPshI/QqFIkm+Vvc/sWFePKdlPvcXHLKdCtzHXRPnPXfWMymj+u592ufwkGUcUWGEBGL2PjW56YlVgONgiMu4dOWvc28t7eJP7+718iXUe6jvTNEQ3uQMb5BRjgMofBPLNoiHO0+H+U+N1f9g0rITbF2yQwa2oP88lnNgkklltmn3GeEynV0hYmY60dbMMSEEo/l9Brb5/dOn8ntL2yXRDrCEUOZ14gyW/WpKdxwzlyue2prgn/XL5/dxorjqqz8Lx/UNdMRDHPS1FJjXkRhfLE7IRX/gxtrulNze/P6pTWwSEOIaH99uIo9+bbmliKPXeZcYbDkrFChtZ7Ry7afAz8f1g4MwuEnGI4kmD/agmFrgE8q86V01Kw53M7OAy22E2dfc4BH36rj0bfquH7ZbAJxCbBiDlI96ZnudsNbtVaWzviKnZPKvGl9cuiPmjHm5FXmcxtVVM3Fy+d2JfQ55itx9yt/TxC46poCPPB6Dd89vZo8p4ODbUGOqihk3Yua65fNpa65w/Jd8bqd/PbC4znQ3MmUMV6mlRYkRH4Iwmgjz+ngX/9hFrsPt1Pqc/PbC4+nvqWTfaY5o64pgMPRra18cKORsOq3XzmeOWO9EIVSj5t7Xt2VdHOuKHRzuDPMjvpWLjnZ8L7a8FbtsCeL62/67kBXKMkPpFsjK4JFushZoSKj9NOG15Myr5v2rhbrpv/DM5WliegMhW1ra4wtdHPFY+9yycnTbCdOZanXareLIFn34g4WVpUmRDT09M5uaA9ytL+IbzywaVCCQE96qxPS575Mlei79W0JmpupY71cv2yuFQJ71vxK/vT2HtacMj1J4KprCrCnoQOX00EkCh980sKmmiaCoRp+ePYsvPku1r+5my+fMNVy3Ey4hoiHuDA6OdjWSSAUSfDd+vGyOcyuLMZf5KahPYgyw8fDkSjnHW9E6ut9zfh9+YZWIVW6bF8er3zclPBQExNMBhTRMcAHtv6m7y71uBMc5aNReGTTbk6dcewQzqjQE0c0KqslQFdXONpfR836QIgVd29MusH3dQPe2RTgh396j2ULJuFwQFGBi1JPHo0dIVwOCEdJqq0xc1wRqx94KynVdmzifH7WOJ7/8ABXbdjCL86dzxWPvpv0uw9evIixXjdNgS4K8vMSMtnFwiQPtgW56L5NSd994GuLmD12YJ7Hh4NhXtpxkPVvdjuWzq4sYcZYL2V5/ctDVtMa5Mo/vmudK4Dt+xq55OQZdHaF+caDb7H6pGnc86qRrvz3/5v45DR1rJefLZ/HppoGAH77yi7KfW6uWzaH7z26mbWnzUjIQArGNXzym59me33boEw3dvj9xUkW5d7GWraSjc5i/SFX+w2DctTsc6zVtAb5yr1vJI37NadMY3yJB2++k4f+VsOSWRMS1pofL5vDtDFeZpR5jS8l3PjduJwODnd08fX7N9nu+8xZ4/onVAzygS3Wn8bOMGUFrpQlAFLum+x9kMjGMWw31mKIpmIQDDYPQzAcSfKb+NWqY/np0+8k3eRiWob1l5xo6219arWfyUX5uFxOy9mpNRRJ0mZMHeulvrWLHz25NenJ/4Zz5pk+VA4qihJViJWlHlYuqiIYiVIfCA9okoUjUda/uTvpWG86dz6fnVLar/3EiorF9/e7S2fy6s6DTCo1clbEPNhT5daYVeElGI7QHAhxzVmzaAuGrYqn/qIC+2vY3iW1PoRRS3Ogy3bcR6Jw49MfcO1Zs/nWqdVc+lBimu0bn/6Ah1af2P2lmC9EnA/FJSdPs9139biifvsqDdp0avanekKJcQNO4b9hm3OGQQoygi2ySg6CwZbgLS7IT8pTofcbqvtAyEjstGBSCZecMp2OzhC+gjwi0agVRhnztr58aTWF+c7uAW9OqLqDbUk31x+cOZsrHt3M6pOmWe2VpR4uWDSFf4krGnbXPx9rVRGNlVaP15oMZJIdbAsmFPACY3H44Z/e6/fNuSA/L+H7qz41hX3NAauQWnykSiqBizBUFhVww9Mf8MMzZ3PPs9v4/hmzTOesPNtrGEs0Bt2VXR0OaAqGxIlTyHkKC/KYOtaboAH887t7iZq1fXwFLoKhiK1w0BrogsJE34OeQoDdnJo+xtfveTPstXZsHEPrA1I0MJ3IGRsEgy3B29kVSioopsYXWzfIRVNLOe+4KZbToSffyS/PW2CFUcbsgA+8XsPcCcWM6WGWGONNthnuMsNSY0/1laUerj57dkIkSbnPzYf7Wq3IlNkTivm+TaRJfydZRaGR7GYoi0NrjyeqqvJuR9aYZuKRTbstISomcN183gJDoMBYLGoaO6g51EHNYcNH45bnPuTqM2fhcTuTCipdvrSaCcUFlp9LvLnp9/8rTy9C7hONRrj0tGquiyugF5/kqtzn5t3axv5FSTigqTNkOWW+og8kPdQMNKJqsA9sQ0GKBqYXOWODYZCpm+PzVMQm3TVnzeLfzp3Pv7+4nRuXz2fNg4nOkrvqW60iXbGn5i8uqkoMEzWpKs5n7WnVCRU37/rn4xLqXVywaEqSY+OK46qsm2ssXHMok8zvdbFoSvmQFoeei0t7nAYhpplYcVwVM8cXWRUP7dSZMa1GfHRNS2eIu17eyZdOnMqaU6YRiYLTAUeN8TGpyEhpvqO+NUnTctWGLTz5zU/H+aJkl+1VEPrC6XRZAgV0J7m64vRqqscXs/WTZtx5Tq4+cxb/9uyHCQ6XrZ1dbAt0GePe50oKG79sSbWZT2cax0wqtU/l3weDfWAbCpkQZEYzIlQMlkHEV/fMUwFwz/99xC3nL+CuVcey63ByhdBHN9Vy8/kLqG3oSHiqnuEvshyM4vtUUZTPLecfQ1swRKE7j3wza90tz2vLFNIzksQuu96QJlkUZld4uX3lMWzb32JpZeZUlvR7cbCLULHL+mlpT+LUsntau/0iYlqNmkNt1nfzXA7DEe3FHZYj6awJJVQU5kHEEBi9blfSOSn3uXl/XyvXPvGe2F6FnKS+pdN2XJf53HzLLFfuyXfyvdNncvnSatqCYWZPKGZvQzt1zZ3saejgz+/u5YZz5iWZDO54aQdrTplGtb+IBeMKrbwWAyIDtXYyIciMZkSoGEHsHDUvW1JNRzDMUUUFdJoVROMnfUN7kMpSL1f90d7mV1bavf/6jhDf+q93bCMa7lp1LLvNrJI9HRtj2fVi39vwVm2SaaDXSZYPHzUE2d/cyfiSAo4ud0MIQpFoglbm5vMW9P9k9VhcxhcXMKnM2/vEN727d5gmH+jWalxj1jkJdEUStBbxxZDiHdFiJZ3jz+XKRVWWQNHzOoiaVMgFxpckP5WvXFRlJcECY1zf/sJ2bj7/GHYeaMGT7+S2FxLXLG06PMcT6IpwzKTSboFisKQhIdZAf0+KBqaPjKXpVkp9PlO/nSmKC7orBF56mpGKuzMUZkxhAfWBEKFImBuXz0twQrxx+TzaU3hs90wvm8o2uL+lE78njyll3iTHxsuWzmCJGpdQ3ruhPci0isL+pc/Nh5d3NHLRvW/wnYff4aJ73+DlHY3Ud6ahrLG5uMwe62OM28XiqhKe/OanefiSE7jzS8cyvaIw4eMxp7FINDEFcV1TgFue+9BKL/zRwTbb89Qa6LIEk+8+tjkpdXn1uKJ+XQdByFbcLidXfH5mwrieXO6zHdd6fwu/fWUXf69vo9zMrhvTSFSW+VKmua/v6EeK7mwjbq3xe0SgGAqZfLy6B5iSwd8fcVoDXZT73HzzlGmWs2ah28W2fS2WH8SiqaXc+9VP0dQRZHyxh8nF+dS3h/tljujLNhiv5ot3bJzoy2Oiz15S7+tp4aOGINc9lWijve6p91m3auGwOD/1lkMiJlSlCjFdPMWoR9IWDKU8T/He7D0jSjx5TrG9CjlNXXOAP/zfx6y74Fi21jURjsCBloDtuI5FhNz2/HZWnzTN0uoFuiLUHGqzosXi5+KepgCXP7LZdn4KRwbDKlQopZ5KsckBjB3O3x4xBpD9raKwgK9/ZmqCs+ZlS2dw2wvdN+VNNU1cfP+b3Sr1SB82vzj6tA32oeYbjMpxf3OyjTbQFcGb70r7DbjXGHZvHjgcqUNMi/PZuNtwLIvVB7Ez72w72J5gOoktpIsmlzG5wie2VyGn8ea7aGgP8uuXd/DlE6fykz9vtZ0PsUyYgBU9FsOT72T+pFLmVHgT1hKX08Hy37wu5sEjnOG+0icDXwFae7Q7gBOG+beHnwFmf/N7XajKEq578n3LWTOWyCmepCf6/tr8+vO5NNsr7Wy0nnwnRQV5ab8B91Vl8MdPvW9pKABcTpjhL8KT56S+vVsgidUHsfNS71XbI7ZXIccpKsizCu7d9T87E5zGL19azeQxPrbvb7HqgIAx/p3mZ2JJ7OZUeI0Hnri1ZNuh9r7XMmHUM9xXeiPQrrX+n54blFJ6mH972Blw9rcoEE2sRnr50hn9e6LvrzAwwk5OR5e7ueGceZYJxJPv5IZz5jG5NJ/JRfms/8Zi6po6mFDsoao4v38Fu0ztT3xa8YrCgqSsn9B9rg62Bak51MGDG2u4fGk1Jd58bnz6g26B5vwFCd+rawpwx4s7eeBrixJsqP3R9oyoE5kgpJESj5NpFT6CYag51GFp4mL86ksLLW0GYI3/mf5CjplUis/tYow333bc9xTIh5KVV8hdhluo+AjostugtT5lmH972Blw0hQHuPNcCQmqvG4XV3x+Jrc9n6MluLvgtOoyHrj4hKToj421zdzyvGbZgklsc7awaEo5s80nnJQ4ur/XM1Jm3QULk2746y5YCEB+vtMyfbR2hi1VLhjXZOeB1n4LbzGH0MMdXbQFw0ws8aT7rAlCRmho6yISdeBwRG3nw44DrTy2qdZan0oKXIwv9bDrcAc1h9q4/3WjaqmdRjZeIB9qVl4hdxnWgmJKqcuBVUAl8CjwsNb6nWH7wSEwkIJiMeoDYVbc/XrSxEylqagPhPhbTQNOhyMhq+akUg9TxxbS2RUesEo9G4vNgHGs31r/zoDrf8SKtcWKhdmFx8aST40vLrAcN+MXsUtOnsadLyU+gVWWevj+GSohx8StKxdywsSigRUeGuB0kYJimSVX+w3DU1Dsk44Q79Y2EugKU+x189M/b7XG+I+XzeHOl3ZaZg+7IobfO30m9732sZGQz26di2kZO0O2xcWG278il693KrLxmDJWUExrvQ5Yp5SaiiFc3KuU8gIPYwgY24fz94ebgSZNOdgWZGK5j131rQn5Gy5fWo2a4GJaiZklc6hy3gBLBw8Hg63/EdP+2CXkioXHxsK+4nP2x/tJnHjUGH5vk+9j3oSiBH+I6eOKaW7uSOrDoIsaCUKWEwyHaQsamryYg+aUsUZtjjyX0zJ7gJFpt+f8vf2F7kgQW42saR6U1NdHLiNydbXWNcAvgV8qpY4F7gWuA/pXB9sGpdSNwHIMZfoB4Gta60+UUg5gHXA20G62vz3EQ7BngI57FYUFfNzQnpRVc/2bu1lYVQreNFyOND5lD4XB1v+I2WWh76yen5jZAeMLfxkpt6NWFtFYxsxFU8oZ43FZzmUATqe9sC0LojBa6QxFLZNEXVOAXz6r8eQb5ckf29QjKV6K+etwxM3FFA8wkvr6yGVEVkilVB5wFoa2YinwV+AnQ9ztzVrrH5v7vwxDSPmm+TvV5t+JwF3m/+FhAI57fq+LulanbVbNrnB/PBj7xu4p+5bnNbevXGg5PI6E5mKw9T9i2p9bntd9FicqLHBZ9UziPzetYj4nH1XK95bOTIqj749wJQuiMFoJdIVtBYVpFUU0tAd59v06bv/iQrbta6Z6XLHtPHA6jNT/fl9eUv2P2ByT1NdHLsOdp+LzwJcwtAZvAOuBNVrrtqHuW2vdHPe2kO6huhx4QGsdBTYqpcqUUpVa67qh/uaQiUJ5j0qiAI9s2s3ilQvT8hM9n7JjZc6/fM/fRlZzYdb/+OWKBfzg8QEsLKb2565Vx9IU6EouFhb3vTGefH545my+9+jmBCHqmj+9x0OrT7QEilh7f00YsiAKo5WJJcmlADz5Tko8eUbdjnHF1nyqLPUkCfa/OHc+c8cXMabAlRCmDclzTMKvj0yGW1NxNfAQcKXWuiHdO1dK/Ry4CGgCTjObJwF74j5Wa7b1KlS4XA7KynwptjlTbhsou1oabDUVoUhkUL/Rs2+V4USzgZ1d9KoNW3h67UlMHZOeY+qNf5xfyNyJJRxo6WRccQGTy7wpzQ7xxNc0SUVJJMrOQ+2U+9yW+QOM2iUHWu2TcjV2hqmeYBRi6+26nlHsZfbakwbc7/7Q21jLVtI5B0aSXO03pKfvPcdacTjCjcvnJVQy/rcV89Fm4T8wCozVNQUSksjNnVhMtb+YKeXd82BHY0Ofc6ys1FAZjxS5fL1TkWvHNNyOmkuG8n2l1AvABJtN12qtn9RaXwtcq5S6GlgLXD/Y3wqHoyk9bNPpfZvvdCbd5O94aQcPrT7R/jf6cLrs2bdIOJyQHS+VXfSThnZKR6DyS1mZj1InlJYaTqh2jpFDYUaFLyl07fKl1UwotjdhlBW4rPPV13VNR7/9/uKktt7GWraSjR7o/SFX+w2Div5Iaus51uoDIe58eQdrT5vBhBIPh9sM4bvn/Hng9RpLsIhVAy5zJc6DsoK8PufYSJPL1zsV2XhMdmMtRlZ7nWmtT+/nR/8LeAZDqNgLTI7bVmW2ZQWtKYqDtQa6Esp3A4Nyutzf0skDr9dY5pVUdtHR4h8QDkeTclKse3EHS7756QQTxtSxXm44Z56ZfdNhCGe9kQURNIKQbmJJ4m55bjuVpR6uPns2/2pW7AVDS+FywM+/MI/6lk4a2oMcXVFoa7oQM6FgR1YLFb2hlKrWWu8w3y4HPjRfPwWsVUqtx3DQbMoKfwqTgTgB1neEuOV5neB/ccvzmrtWHdtr9ISR29/I01BZ6hlYGfMcI1WkxuH2IDP9hfzhq4voCkc43B7iX/7zrYRzcEax136nWRJBIwjpptiTb60/dU0BPmlst9aXogIXhe48WjtDfPuhtxPGvi3DkbZehPmcJ2Olz9PATUqp95VSW4AzgMvN9meAXcBO4HfAtzPUP1ti0n182KRdcTCApkAXF3/maFzmVXI54OLPHE1TwDZJqe3+B1TGPAeJD0GNMXWsl/0tQZb/5nW+9Ps32FrXwg8fT3Yo291gb9JIladiQGXbBSELCXSF+N7pRunzylIPJZ587nl1F3e+tJP2YJj61s4kzV+vYz+dJcNNYX7F3Ru56L5NrLj7dTbWNudO+XQByGFNhdb6vBTtUeDSEe5O/xmAdO8ryLcqmpb73KxcVEWhJw93fp4x0ewmcC/7H431KuxUsDecM8/SSgCM8blttRl7Gtopq0h2gJI8FcJopdTjptDt5PYvLiQcifL9ONNHzFHTbuzXtXQOu/ZAks6NDuRKZYJ+5rZoD4aszHc90+Va6vgh7H9UqBpthKieQoEvzqEslijL5YRCj71wJnkqhNGK3+ti8thCrnvyfb5/xiwuOXkaYERMgaENtRv77+5t4o4Xdw6rKVCE+dGBXKkspi1oJKpJFRb6+JrFRujlYISD0eQ30FOIwpGwMO5tbOfypdWsf3N3Qjjv3a/sSlkYad0FC9la12zVZ5lTWTJq/FCEI5go5DthzSnTucrUUsTC2p99v47zj6/imrNmcbCtuzbRhJIC7njp78Dwag9EmB8d5LJPxagnlqgmVR2Mg21BIpHooOyQffoNOIzws22H2qkPhPu2aw7088NIT7+Sh9/YzaRyL1edMctWOLOzFwdDhtBx50s7+e0ruwiG0pPxVBAyigOCYbjx6Q+SwtpPnTUOT74Td54rYezjSLxNxNaedDMQf7NRRxatn0PlCLhauYvfY0yynfWpy3bvaewYlB2yV1WjN29gWozetB6ZwKZ8+eQyD3saA/1Sr4ptVxit1HeEeHu3fdKqWRNK+KSxnVue254w9n/6561WETEYRu3BcEST5AKjSWuMaCqyG3OSnT1nPD//wnxbCf5Ai33myL6eJOyiJmKLxUCjH4Y1WmIIEvz2+ja+fv8mLnngLZbf9TpulzPlMcfTm8AlCLlMzKxhNw8+3NdMWQqn5lJTWzDs2oN0RpPkCKMt2kweu7KdKIxxuzhlaqmtBD8uRebIvp4kektcs+1g+4Acpnq7CQ8pRW8PCT6WwMoRjfbpO2KX4+OOl7Zz07nzk4qM9XwasrPtTh3rpciTz7ZD7bnr1Coc8VQUFvDnd/fy42VzLBOIJ9/Jjcvn0dEVYlK513Y9mTexlIdXf4pST/6RoT0YQbLSQXUITvwiVOQKKSI6Jpd5B5fVrhdV40AdpobLwSpego8VRuuZwCqVirAp0JVUY+XqM2cxeYyXP3x1Ee3BMFPGFFKWR5+ZAqeO9bL2tOqRL8omCGnG73Wd2c04AAAgAElEQVTx/c8rmjqC/PsFC/mgrplwBO58eQerPjWFQDCUVETssiXVvL+3kZOmjU3WHoyGCLIMk3UOqkM0xziiURkBAF1d4ehI1P5IN2VlPhqb2uMmdnqy2tkOqskl1LfbLCC9DMKy0sGfu22H2rnovk0AXHraDO55dVfSxEvl57CnrcsSAsDILNqzRsitKxdywsSilH4isXNa5MlP2Fdfvx2P31+cZLDpbaxlK9k8B3ojV/sNg6r90b+x5oC9bV2s+n3ymL7l/GO4+bkPWbZgEg4HRKPw9Ja9LFswiROnljF7rC9hP9nmC5CT17uP8zjSx1QfCLHi7o29rnd2Yy2GaCpykbgb3sQIlLr6mZeiv9hpMXx5bNyTeuAPh4NVvATfWwSM3Y29Z42VFcdVJWUKvPKxzakFgzjN0LZDAzMHCUK2s6exw3ZM7zrYxneWVPOjJ95P0FQ8smk3/zhnXMLnxaE5TaRYb2MPcLE1fqQEtaGaY+TK5xoj9XTQw9xS397HAtLfhFsDIN4MAfZJeSwVYQ81bEVRokpxoEJJPFmnnhSEIVDfEWLnAfuIslAkwvwJxfzuokXUNXbgdedR19jONWfNTnpQyEpfgFwlfv100OsD3HAz1PVOoj9yjEx5CmckIiJOgv/s0eXcdK59BIxdzYA9jR2su2Ahly2dwdolM5g1obhfkR92HNHx88Ko42BbkEc31Vo1QACr5PncyhLGeFw0tgW57qmtfOfhd7jthR22eVp6iyDrlVGUk2E4yHQ0yFDXO1kVc4xMPR1k7Gk9ToKfUe61NbHUB5In4S/+exvfO11x9yu7LGfLG5fP48dPdqt1b125sH9mmiM1fl4YlcQqGd/32sesPW0G/qICCgvymFzuZaKpdu+PWWNQpc+z0A8j28i4BmiI650IFTlGpm7ug1pA0k0KE4vdJFy2YFJCZdKaQx3c+fIOHlp9Iq2BLioK3UwfV0xzs32l0v7+tiDkGvFz+ZbntltzeaLPmMv9vqkN4uYjfhh9kxXm1iGsd3IVc4yM3dyz+GndbhK6nMk+FDWHOmgNdFke7E6n6F2FIxBzLj+99iQ+aWhPmssDuqkN8OaT8afwHCArHuCGgFzFXKPHzX1iuW/kPIOz9GndbhIumlKeeWlfELKVKEwd46PU2f0+xnDe1LLiKTzbyeQanwZyXqhQSl0J3AL4tdYHlVIOYB1wNtAOfE1r/XYm+5h24m7uORmXnW5ShGTlsrQvCBljGLWSuf4UPmLk8Bqf00KFUmoycAawO675LKDa/DsRuMv8LxwxOLLaXCMIuUUazYQyL0c9OS1UALcD/wo8Gde2HHhAax0FNiqlypRSlVrruoz0UBh+evEoTzLX2CQOkwVNOOJwQM3hdtOnokd67eGO0MhSM6qQHnI2T4VSajmwV2v9bo9Nk4A9ce9rzTZhlNLvuO4e+SyW3fkqG2ubJU5eOLIw58GyO1+18rrEz4NM50kQcpus1lQopV4AJthsuha4BsP0kRZcLgdlZb4U25wpt2WabO4bjEz/dtQ02HqUN3aGqZ5QYrXVHG63XSyfXnsSU8eM3DnsbaxlK9k+zlKRq/2G9PTdbqz1NQ/6O5+ykVy+3qnItWPKaqFCa326XbtSaj5wNPCuUgqgCnhbKXUCsBeYHPfxKrOtV8LhaEpnmGx2lMnmvsHI9K+sIM/Wo7yswJXw25802Nfw+KShvdsLPs34/cVJbb2NtWwl28dZKnK13zCogmJJbXZjra950N/5lI3k8vVORTYek91Yi5GT5g+t9Xta63Fa66O01kdhmDiO01rvA54CLlJKOZRSi4Em8acY3fSaVjYuJXCxJ3/QqboFYbTQV3ptSUsvDIXROEqewQgn3YkRUvr1zHZHGHZSeZST6HBml6pbwtmEIw2/z5U0D25cPg+/Lw8iSISGMCRGhVBhaitir6PApZnrjZARbDzKe9YE6ZmqO9eSyghCOqhvD3HnyztYfdI0HA6IRuHOl3cwd/yxCfNHIjSEwTAqhApBsMMuJXB8qu5stFUKwnBzsC1IzaEOfv3yzqR2SZUtDJWc9KkQhP4w6NLMgpBFrP3jlrTuT+aFMJyIUCGMWsThTBgNRKLptT3IvBCGExlFwuhFHM4EIZk+qpQKwlAQoUIY3YjDmSAk00uVUkEYCmL+EARByAHS7VshCMOBCBWCIAg5QLp9KwRhOBChQhAEIYuRendCLiFChSAIgiAIaUGECmH0Elf3oz4Qlkc+QYgjEonK/BDSjkR/CKMTR2Ldj1gs/uKqEvF0FwQHvKDrufKxzTI/hLQimgphVFLfkVj3I9AV4aoNW6jvCGW4Z4KQeeo7QpZAATI/hPQhQoUwKrGr+xHoinCwLZihHglC9iDzQxguRKgQRiVS30AQUiPzQxguRKgQRiVS30AQUuP3urh15UKZH0LakREkjE6k7ocgpCYKpyu/zA8h7eSsUKGU+gnwDaDebLpGa/2Mue1qYDUQBi7TWv8lI50UMovU/RCElDidDpkfQtrJWaHC5Hat9S3xDUqpOcAqYC4wEXhBKTVTax3ORAcFQRAE4UhhNPpULAfWa607tdYfATuBEzLcJ0EQBEEY9eS6pmKtUuoiYBNwpda6AZgEbIz7TK3Z1isul4OyMl+Kbc6U2zJNNvcNsrt/mepbb2MtW8nm69gbudpv6O57Xp4r4f/A9pGb69pgkWPKPFktVCilXgAm2Gy6FrgLuBHDEngjcCtw8WB/KxyO0tjYbrutrMyXclumyea+QXb3byT65vcXJ7X1NtaylWy+jr2Rq/2G7r6HQuGE/6kY6FjL5XOTCjmmkcFurMXIaqFCa316fz6nlPod8LT5di8wOW5zldkmCIIgCMIwkrM+FUqpyri35wLvm6+fAlYppQqUUkcD1cAbI90/QRAEQTjSyFmhAvh/Sqn3lFJbgNOA7wForbcCjwIfAM8Cl0rkhyAIucJlf9yS6S4IwqDJavNHb2itL+xl28+Bn49gdwRBENJCJJqYMEIqkgu5RC5rKgRBEARByCJEqBAEQcgiRDMh5DIiVAiCIGQJV/biTyHChpALiFAhCIKQJfT0pxCEXEOECkEQhCxCNBJCLiNChSAIgiAIaUGECkEQBEEQ0oIIFdmKA+oDIbYdaqc+EBadqCAcIfSc6iM29WXNEdJAzia/GtU4YGNtM1dt2EKgK4In38nN5y1gcVWJUT5NEIRRxxVm5IcDuPyPW7j/ksUj9+Oy5ghpQjQVWUh9R8ia3ACBrghXbdhCfUcowz0TBGG4iI/8GOkoEFlzhHQhQkUWcrAtaE3uGIGuCAfbghnqkSAImcLR4/9wIGuOkC5EqMhCKgoL8OQnXhpPvpOKQneGeiQIwkgy0u4MsuYI6UKEiizE73Vx83kLrEkes2/6veICIwijkSv6kUlzOAUNWXOEdCEjJhuJwuKqEh5fs5iDbUEqCt3G5BaHKUEYlaSqTHrFH7fgoPf03WlB1hwhTYhQka1Ewe/Jw+/Js94LgjD6sBMYHMDF971pCRsj4rgpa46QBsT8IQiCkCGu+OOWlAKDS+qACDmIaCoEQRBGmCs3bLFMHE6Hw1IKOOhWEDgcDpwOh9XuGtkuCsKgcERFGo5RD9RkuhPCqOMgcGaPNhlrwnAgY00YKezGGiBChSAIgiAIaUJ8KgRBEARBSAsiVAiCIAiCkBZEqBAEQRAEIS1I9IdJMBiKNjV12G4rKiqgtbVzhHvUP7K5b5Dd/RuJvvn9xUmJEHsba9lKNl/H3sjVfsPA+z7QsZbL5yYVckwjg91YiyGaChOHI3US3Ly87A3myua+QXb3L1N9622sZSvZfB17I1f7Denpe66ua4NFjinziFAhCIIgCEJaEKFCEARBEIS0IEKFIAiCIAhpQYQKQegPDqgPhNh2qJ36QHh461DnInJ+BEFAoj8EoW8csLG2mas2bCHQFcGT7+Tm8xawuKpEKjmCnB9BECxEUyEIfVDfEbJumACBrghXbdhCfUcowz3LDuT8CIIQY8Q1FUqpycADwHiM55i7tdbrlFI/Ab6BUQAH4Bqt9TPmd64GVgNh4DKt9V/M9jOBdRgF/H6vtb7JbD8aWA+MBd4CLtRaB0fmCIXRxsG2oHXDjBHoinCwLYjfI8o+OT+CIMTIhKYiBFyptZ4DLAYuVUrNMbfdrrVeaP7FBIo5wCpgLkZVtP9QSrmUUi7g18BZwBzgS3H7+aW5rxlAA4ZAIgiDoqKwAE9+4lTx5DupKHRnqEfZhZwfQRBijLhQobWu01q/bb5uAbYBk3r5ynJgvda6U2v9EbATOMH826m13mVqIdYDy5VSDmAJ8Efz+/cDXxieoxGOBPxeFzeft8C6ccZ8BvxeeQoHOT+CIHST0VmvlDoKOBb4G/BZYK1S6iJgE4Y2owFD4NgY97VauoWQPT3aT8QweTRqrUM2nxeEgROFxVUlPL5mMQfbglQUuo0bpjghGsj5EQTBJGNChVKqCNgAfFdr3ayUugu4EWMpuhG4Fbh4pPrjcjkoK/Ol2OZMuS3TZHPfILv7N9C+lZVCdVp+N/VYy1b6c67SdX7SSTaPv75IR99zdV0bLHJMmScjQoVSKh9DoPgvrfXjAFrr/XHbfwc8bb7dC0yO+3qV2UaK9kNAmVIqz9RWxH8+JeFwlMbGdtttZWW+lNsyTTb3DbK7fyPRN7+/OKmtt7GWrWTzdeyNXO03DLzvAx1ruXxuUiHHNDLYjbUYI+5TYfo83ANs01rfFtdeGfexc4H3zddPAauUUgVmVEc18AbwJlCtlDpaKeXGcOZ8SmsdBV4Gzje//1XgyeE8JkEQBEEQMqOp+CxwIfCeUmqz2XYNRvTGQgzzx8fAvwBorbcqpR4FPsCIHLlUax0GUEqtBf6CEVJ6r9Z6q7m/HwDrlVI/A97BEGIEQRAEQRhGRlyo0Fq/in0S32d6+c7PgZ/btD9j9z2t9S6M6BBBEARBEEYIyagpCIIgCEJaEKFCEARBEIS0IEKFIAiCIAhpQYQKQRAEQRDSgggVgiAIgiCkBREqBEEQBEFICyJUCIIgCIKQFkSoEARBEAQhLYhQIQiCIAhCWhChQhAEQRCEtCBChSAIgiAIaUGECkEQBEEQ0oIIFYIgCIIgpAURKgRBEARBSAsiVAiCIAiCkBZEqBAEQRAEIS2IUCEIgiAIQloQoUIQBEEQhLQgQoUgCIIgCGkhb6R/UCk1GXgAGA9Egbu11uuUUmOAR4CjgI+BL2qtG5RSDmAdcDbQDnxNa/22ua+vAj8yd/0zrfX9ZvvxwH2AF3gGuFxrHR2RAxQEQRCEI5RMaCpCwJVa6znAYuBSpdQc4IfAi1rrauBF8z3AWUC1+bcGuAvAFEKuB04ETgCuV0qVm9+5C/hG3PfOHIHjEgRBEIQjmhEXKrTWdTFNg9a6BdgGTAKWA/ebH7sf+IL5ejnwgNY6qrXeCJQppSqBfwCe11of1lo3AM8DZ5rbSrTWG03txANx+xIEQRAEYZgYcfNHPEqpo4Bjgb8B47XWdeamfRjmETAEjj1xX6s123prr7VpHz04oL4jxMG2IBMjUOrCMCQJwkgSNw4rCgvwe10yDgXhCCdjQoVSqgjYAHxXa92slLK2aa2jSqkRXZ5cLgdlZb4U25wpt400kUiUF3Q9Vz62mUBXBE++k1tXLuR05cfpdGS6e0lk07nrSab61ttYy1Z6nqtcGYfZPP76Ih19z5V1LV3IMWWejAgVSql8DIHiv7TWj5vN+5VSlVrrOtOEccBs3wtMjvt6ldm2Fzi1R/tfzfYqm8/3SjgcpbGx3XZbWZkv5baRpj4QshZygEBXhCsf28zjaxbj92RU8WRLNp27noxE3/z+4qS23sZattLzXOXKOMzm8dcXA+37QMdaLp+bVMgxjQx2Yy3GiPtUmNEc9wDbtNa3xW16Cviq+fqrwJNx7RcppRxKqcVAk2km+QtwhlKq3HTQPAP4i7mtWSm12Pyti+L2lfMcbAtaC3mMQFeEg23BDPVIOBKRcSgIgh2ZeKT4LHAh8J5SarPZdg1wE/CoUmo1UAN80dz2DEY46U6MkNKvA2itDyulbgTeND93g9b6sPn623SHlP63+TcqqCgswJPvTFjQPflOKgrdGewVYl8/wuh1HMpYEIQjFkc0KrMdoKsrHM0JNaEDNtY2c9WGLZYt++bzFrC4qiRzC3cvfSorzaJz14MRMn8kORj0NtaylaRzleqaTy5h457sGZ9ZNXcHyCDMHwMaa7l8blIhxzQy2I21GCJUmOTU5IuP/ij3ZTz6oz4QYsXdG5OeWh9fs5jqCSXZde7iEKGi/9ieqwSNhBu/N4/6jtRjIRO+Flk3dweACBUDR45pZOhNqMgejyqh/0TB78nD78nLigHXm329OkN9EkaAuHEYe9/bWMgmB05BEIYHqf0hDJmYfT2erPDzEEYcGQuCcGQjQoUwZPxeFzeft8C6mcTs6H6vPJkeachYEIQjG5npwtCJwuKqEh5fszjBvi4e/0cgMhYE4YhGhAohPdjY14UjFBkLgnDEIuYPQRAEQRDSgggVgiAIgiCkBREqBEEQBEFICyJUCIIgCIKQFkSoEARBEAQhLYhQIQiCIAhCWhChQhAEQRCEtCBChSAIgiAIaUGECkEQBEEQ0oIIFYIgCIIgpAURKgRBEARBSAsiVAiCIAiCkBaGJFQopV7sT5sgCIIgCKOfQVUpVUp5AB9QoZQqBxzmphJgUpr6JgiCIAhCDjHY0uf/AnwXmAi8RbdQ0Qzc2deXlVL3AsuAA1rreWbbT4BvAPXmx67RWj9jbrsaWA2Egcu01n8x288E1gEu4Pda65vM9qOB9cBYs38Xaq2DgzxWQRAEQRD6waCECq31OmCdUuo7WutfDWIX92EIHw/0aL9da31LfINSag6wCpiLIcS8oJSaaW7+NfB5oBZ4Uyn1lNb6A+CX5r7WK6V+gyGQ3DWIfgqCIAiC0E8Gq6kAQGv9K6XUZ4Cj4velte4pLPT83itKqaP6+TPLgfVa607gI6XUTuAEc9tOrfUuAKXUemC5UmobsAT4svmZ+4GfIEKFIAiCIAwrQxIqlFIPAtOBzRimCYAoyRqI/rJWKXURsAm4UmvdgOGjsTHuM7V0+23s6dF+IobJo1FrHbL5fEpcLgdlZb4U25wpt2WabO4bZHf/MtW33sZatpLN17E3crXfkJ6+5+q6NljkmDLPkIQKYBEwR2sdTUNf7gJuxBBKbgRuBS5Ow377RTgcpbGx3XZbWZkv5bZMk819g+zu30j0ze8vTmrrbaxlK9l8HXsjV/sNA+/7QMdaLp+bVMgxjQx2Yy3GUPNUvA9MGOI+ANBa79dah7XWEeB3dJs49gKT4z5aZbalaj8ElCml8nq0C4IgCIIwjAxVU1EBfKCUegPojDVqrc8Z6I6UUpVa6zrz7bkYAgvAU8BDSqnbMBw1q4E3MCJOqs1Ij70Yzpxf1lpHlVIvA+djRIB8FXhyMAcnCIIgCEL/GapQ8ZPBfEkp9TBwKkaei1rgeuBUpdRCDPPHxxhhq2ittyqlHgU+AELApVrrsLmftcBfMEJK79VabzV/4gfAeqXUz4B3gHsG009BEARBEPqPIxpNhztE7tPVFY7mou0xm/sG2d2/EfKpcPRs622sZSvZfB17I1f7DYPyqRjQWMvlc5MKOaaRwW6sxRhq9EcLhmYBwA3kA21a65Kh7FcQBEEQhNxjqHkqLBdQpZQDI6fE4qF2ShAEQRCE3CNtVUq11lGt9RPAP6Rrn4IgCIIg5A5DNX+siHvrxMhbERhSj4RkHFDfEeJgW5CKwgL8Xle30UkQjkRkTghCVjLU6I9/insdwojaWD7EfQrxOGBjbTNXbdhCoCuCJ9/JzectYHFViSyiwpGJzAlByFqG6lPx9XR1RLCnviNkLZ4Aga4IV23YwuNrFuP3DFUmFITcQ+aEIGQvQzV/VAG/Aj5rNv0vcLnWunaoHRMMDrYFrcUzRqArwsG2oCygwhGJzAlByF6G6qj5B4yMlxPNvz+bbUKaqCgswJOfeJk8+U4qCt0Z6pEgZBaZE4KQvQxVqPBrrf+gtQ6Zf/cB/jT0SzDxe13cfN4CPPlOKks9XLZ0BjefvwAcDiNRuSAcYcTPCTAEinUXLARg26F26gNhmRuCkCGGqis8pJT6CvCw+f5LGAW9hHQRhcVVJTz5zU/z/r5Wrn3ivQTntDOKvZnuYfoRz36hN8w58fiaxRxsCzK+uIDt9W2suHsj5T43KxdVUT2uiOljCymJyMARhJFkqELFxRg+FbdjLPuvAeK8mW6iEI5ELYECup3TZq89idK0ZRvJAsSzX+gPUfB78vB78qgPGI6b5T43Fy6eyh0v7bDGzq0rF3LCxCIZO4IwQgw1+qMGGHBFUmHgpHJOO9DSSWlpQYZ6lX7Es18YKLG5seK4KkugAGPsXPnYZhk7gjCCDDX642jgO8BR8fsaTOlzoXdizmnxgoUn38m44tEjUIB49gsDJzY3HA5k7AhChhmq4vwJjIRXvwJujfsT0oydc9rN5y1gctno8qkQz35hoMTmhsuBjB1ByDBDFd8DWus70tIToXd6OKdVFLrxe/NwOkeXm3vsBtHTp8LvzRO7uGCPOTdm+guZMqYwwZn51pULZewIwggyVKFinVLqeuA5oDPWqLV+e4j7FeyIc06LvR91pBCeRuWxCukjCmPcLk6ZWpowdqaPK6a5uSPTvROEI4ahChXzgQuBJUDMmBk13wvC4DgShCdheOgxdkabJk8Qsp2hChUrgWla62A6OiMIgiAIQu4yVEfN94GydHREEHIOB9QHQpLF8UhGxoAgJDBUTUUZ8KFS6k26fSqiWutey58rpe4FlgEHtNbzzLYxwCMY4akfA1/UWjcopRzAOuBsoB34WsxnQyn1VeBH5m5/prW+32w/HrgP8ALPYBQ5EyX6kYxdls4h7k+SdGUZ6b7G/fg9GQOCkMhQNRXXA+cCvwBuA94EZvTje/cBZ/Zo+yHwota6GnjRfA9wFlBt/q0B7gJLCLkeOBE4AbheKVVufucu4Btx3+v5W8KRhLn4r7h7Ixfdt4kVd7/OxtpmIkNI4ZwqSVd9RyhdvRYGwjBc476QMSAIyQxJqNBa/w/QjKF1uA/DQfM3/fjeK8DhHs3LgfvN1/cDX4hrf0BrHdVabwTKlFKVwD8Az2utD2utG4DngTPNbSVa642mduKBuH0JRyCpFv89jYOPCugtSZcw8gzHNe4LGQOCkMygzB9KqZkYxcO+BBzEMFs4tNanDaEv47XWdebrfcB48/UkYE/c52rNtt7aa23ae8XlclBW5kuxzZlyW6bJ5r5BdvRvR02D7eJf39rJ1CnlKb7VOxMj2GY4nVju6/N4extr2Uo2XMfeGI5r3BdDGQP9IR3nPFfXtcEix5R5ButT8SHwv8AyrfVOAKXU99LVKa11VCk1olbJcDhKY2O77bayMl/KbZkmm/sG2dG/soI828XfX1Qw6L6VurBN0lXqImGffn9x0nd7G2vZSjZcx94YjmvcF/0dA4NloOd8oGMt26/pYJBjGhnsxlqMwQoVK4BVwMtKqWeB9Qzd73m/UqpSa11nmjAOmO17gclxn6sy2/YCp/Zo/6vZXmXzeeEIJVWWzsll3sEnRpIkXVnFsFzjvpAxIAhJDEqo0Fo/ATyhlCrE8Hn4LjBOKXUX8Cet9XOD2O1TwFeBm8z/T8a1r1VKrcdwymwyBY+/AL+Ic848A7haa31YKdWslFoM/A24CKM2iXCkMlwpziVJV/aQqTT2MgYEIYGhlj5vAx4CHjJv7iuBH2Ck7U6JUuphDC1DhVKqFiOK4ybgUaXUaqAG+KL58Wcwwkl3YoSUft387cNKqRsxIk4AbtBax5w/v013SOl/m3+jH7uQOlnkDGwW/0gkSn1Azteoob83+FTzROaPIAwZRzQqswagqysczUXbo9W3LI2Zz9pz54A3Pmnlysc2D+v58vv/P3vnHh9XXeb/97nOfSaTW5MmTWiaS++FEq6Wgi2yha0ghcpFwUuxiiAsKgruoiIqurDyA3FVFnZX8AZyEWEXBVrcooLSIoXSNk1aSJM2zT0zmeu5/v44M9NJMgnlUmjpfF4vXjQzc86cc+Z7zvf5Ps/n83kCE5bKU421QxWH7O/4Bphw3JPdJzOCPN91aN0/b4FT8abG2uH6m06F4jm9Oyg01rJ4uz4VRRwiKGrmp0AB18P+pJELKKB4vY4UTCo9HdXf+P4pumcWUcQb4u06ahZxiGAqzXwuHXwkIrMyvfWpNlYurEESobUuDLZdvF5HICa7T3pHUwVf7xlNO+RLDs1MYBFFHGooZireJyj3uXArY39OtyJS7lPfoyM6NNCfNLj1qTYuaK3jnj/t4o51Haz9+SZsQSheryMQk90nVQF3wdc374nwfHeUobRZzAQWUcQBoBhUvJd4B9OpWUld9sGYXUllV1lHKgbiGisX1nDH+vYxE8IP1+/g5nMXFK/XEYbJ7pPagDLh9RtWzsWrSnT0x4hqRtE9s4giDgDFJ+gbQYDOoQR7hxPvLCP87RAr81jq0y3HhOeI0cy/SYZ+uc+FJDJmQqgOuVk2u4r/t24Ha5Y0IIlwbF2YueUesCbfVxHvA0x2n1hw4owgP73kWDZ3RWis9PP932+jczCJWxGZUeqlvsxD5+B+z4tiZquIIiaiGFRMhYOoqJiMMPbw2hOnrum/wTG9rzXzUzD3+xOFJYKSCItnhMe4La5aXJvLXPzomQ7AmSDe8NoX8f7AJPdJf8Jg294ohmXxxQfGknj/5bdb+PePLebzv3gxN/a+/ZH5VHjlYiBaRBF5KD5Bp8BbnvgPAPmEseqQm1WLaxEEiGjGlBmGg3lMhzoKnfutT7VxzfJmrnvklUklgs2Vfr5z7nw6BxNYNtSFPUWS5ruJg+X/8A7vdyCuYRZRv54AACAASURBVAN1pd6C42M0pbN2aQOWDaIAibTBUMqkVD3ILdaLKOIwQvEJOgUOpqIiSxgLe1UuObE+t3K++9mpsyFHssqj0LmvXFiTCyhgf5D1yzUn5AKQ/pjGwKjGXRt2kdItrl7eWLBPRDGVfRBwsLJ9B2G/5T4XSX0E3yR9RCRB5I51HWNe+69PtBaDiiKKyEORqDkFDqaiIksYW91aO4FEeOtTbXTF9IIEziNZ5VHo3MfzJcD5u280PabccdvTO3J/P7Cxm6uXNxVJmu8CDpZ/ysHYb4VX4qSGMroG41y1bOz4uOb0ZkIeme+vWsAPLzqGhTVBUrpFQjPf1nkUUcT7DcWn6BSYrEnRO0KAzBDGPKo0gUR4QWsdF9/z18KciYN5TIc4Cp17a114wqqyvsyDzyXlXnfJ4oTAA+A/LmlFM0yqA64j4vq9FzhYmbV3fL8CPN/l+Jlct2IO3/v9NtYsaUAQwC2LhL0yL3QOY9kgCfCZpQ08trmb6oDrLZ9DEUW8H1EMKqZCZuJ//MolGfXHO6yosGF6Rh9fiEQIEPaqtPfH8KgS0wNuKjzSGPb69LA3p/5438N2GPq/XHMCvaMpqgJuaoPKhEDj5nMX0NEX4+rlTdy+rp2Z5b7cNa4OubnkxHpuX9c+NiirDb7XZ/e+RDa79E6Xmg5ov29CuZWf+fjxHztYu3QWNz2+lZRu8bUzWxiM67nymVsRuXp5E5ee1FAkahZRxDgUg4o3gg31pV5C4v6/30mMX33np/OzE+D9G3djWvCyGKG1Lsycck+OvX4o+sIfNGRWk/kBxO0XHE1zhY//+kQrCc3JOkTSBt99Yjthr8qaJQ1YlsVVy5q4Y337hKDtSCK6vhc4WJm1N9zvm+Rc5Gc+Xt4TpX99B1d+sJGmSj8eVWbtfRvHjJnb17Vz6/mL6M9XkbwRig3LijgCUHyKvtcYp5sPuJXcimjV4lru37ibC1rrchOhWxH53rkL+EBd6K09kA7jB9v4OnrYq7JrIM7V949tCpYtKfVEUvzomQ6uXNbIY5v3sGZJQ1H58W7jYPmnvMF+36xKqlDmQxIFrr7/JW45f1HBMRNPGxPHzRQdUIs230UcCSgSNd9tFHLRzOjm55R5qfXvd/YTBAq6QV73yCtvjZCWebCtuut5Lv3vjay66zme744eNo2RxtfRVy2uzZUxYP/EUe5TxxA6H9rUzYXHOTbdXSPJI5bo+p4hb3xXuN/Z8uFk+52Kc1EI4502V7fuH1t90VTBMTOU0PC7lf33zxT3V7HhXxFHCopBxbuJA5nU81ZgH5hVWtANcs2SBjpHkvSnTCzrAJ7QmUCmYyR1+D3Y8oKwgFsZ83AXhMLKj6RmcMt5C6kv83DFBxtZ3VrL0bUhHv7siXxgZpjvFe253z4O8Y6dU6qkJgnss/fdvZ9sZWFNKMfBEQX49kfmjxkzX/xQM15F4prfvHRAgcObDXKKKOJwRfFJ+i7igFOyWcc/j4yep27IcizySyH/tvpojp/un3z1l5d2veyUhnc39f92Lc7HpYzryzzcdM58bnh0Cyndwq9KBcl6IbdCY6mHa05v4bqHnW3vyks3N4Y9PLz2REbSJiUuqaj8eLM4DFL5k3IuvPIEXk4hR9r+lEl9mYeLj6/n+39oI+xV+co/tFAd8uB1Sdi2xQ+ebEcz7ByR2ueSCHtVeiKpCYZ25f6DQ1gtoohDDYJtHyJPgfcYum7akxEe3yky5LbBBJf+98YJr9/7yVbmlHkLbyTCnzsj3LZuB186YzZfeXDzBPnkbauPJpbSC07c/SmDVXc9T0q3uHJZI3c/u2vCg21CUPNO8C7egYkn/9jHn29aNxhJGrw+lJig5DixNkh/cuK2uXP1yPQnjUxQIR9UXklFRWDCGn6qsXaoIv8eKPS7HJI25wJETMYot6YcF/nHLkL7cJrnXxvEsmFDWx8r5lePCei/+eF5eFWRrzy038316uVNPPFKz4TP3n7B0WiGNeZ++M5HFjC/yk+pq/D4e7PPnTc71t6PJO/iOb07KDTWsjiEngDvf7wleZ0FH6gPwfJmOvpGc9surAlyxbImIgltUk8LGFtbfmhTd04FMSkT/x1ahR5QVuYNgpdCKePOwWQmgFL51L2bcgoPQXCsk5srfGDD3jzzqyxSusVAQmPnYOKQXmUf6jhsXF0LKLcO6NgLqIxuWDmXuzbsHDOev/nYq9x6/iI+f1ojM8t97BlJkNRMPn9aI/80rnfI1fe/xKOfO4mH157IzqEE7X0xbn2yjeGEVhx/RbyvUORUvIvIJ4NVh9xctbyRW85f6JADpqhJ9ycMrnvkFSzbCUIW1gS56Ph6Xt0b4eu/e3WCp8XmvjhDmkl/ykBRxFwtuCeS4r7nO1m7tIF7P9XKL9ecQMgt05/cXxOfklD2Jurob1hDPgB+yVR18ez+swqPO9d3cMe6DnpH0wA586vx27oU6fDjlRxiOOxcXcfxcurLPGPeHn/she6Bmx7fysqFNWO2S+kWO/pG+cFTO7j2wc1YFvz2pT2kTavg2O+OpNg7mqajL8ZvNnbTE0kVx18R7zscQssKBy0tLa8Do4AJGG1tba0tLS2lwP3AUcDrwEfb2tqGW1paBOB24CwgAXyyra3txcx+PgH8S2a3325ra/vZu3gahZEhgz36uZPYsi/GP//2lQNaLWcn0Ic2dXPN6c3UlHj48oObx3Ak8vkWYa/KpSc5Bk9hr5ozgUrpFsMJjXnVQSJJg7U/f3HC908WDERS+pta4b9RVuZAMhlTeRGkTbvg/rNsfJ8ijznvbGo6ljIOj1X2IYzDydXVsuwJmbebzpnPnc+059qajz/2ye4BadwSzK2ImNb+9+9Y387Vy5uQBIGrljdi2U52sCfiqEc274lwx7oO3IrIVcuauO/5zlxgURx/RbxfcKiO4g+2tbUN5P19HbCura3tey0tLddl/v4qcCbQlPnvBODHwAmZIOQbQCvOo2JTS0vL79ra2obfzZMoCBtMy84FFFDYNTO/HIEg7GeeyyKGZee2zU6s+aZO+VLLnkiKe59zshOLakI5W+H8unL+hD5ZMOBSZK59aNMB6/7faOKZKngBiKR0vC6FqpCLuy9txbIs/C6FWEqnP2mS0o0JpZyrljVhWibPdye59ak2Pn3yTNYubcCrStSWeEGA0ozctEiYexs4WN4TB8FDpWskOSF4veHRLfxyzQm5Mtr4Y5/sHjh6Rknu9fzAIIvmSj/N0wJs7h7BsuGxzXty5nUXHlfHvc915o7hjvXtrFnSwI+e6SiOvyLeVzhUg4rxOAc4LfPvnwF/xAkqzgHubWtrs4HnW1paSlpaWqozn32qra1tCKClpeUpYAXwq3f3sAtjfNvz8YqO/AxAf9LgjvU7uGHlXHqjKW7+/XZuOX8RbkVkQ1sf31g5j59s6Bhj6jReatkTSXHHug7u/WQrFW6ZbYOJMd+/anEtAbfEqG5imRbfO3ch1z0yNhiIpfQ3t8J/A4vzQg/u+jIPvaMa//Xca6xcVMuePdFctiU/8/Kpk+tpmhbg/o27c3wK24b7N+7mpIajc5PIH9v6+MypDewZTvHlDMG1tT7Edz6yYEKW6FBcZR/SyFNKZP9+WzhIipK+0TRhr5pTYoCTPYil9P3k6HH7LxQQf+PD87jvL6+zZkkDsyp8VARc3P50W26/HkWkKuTmil/uz/7ddM58ntq6l1vOX8SLu4c579jaXOYipVtOX5Hi+CvifYZDMaiwgSdbWlps4KdtbW13AdPa2tp6Mu/vA6Zl/l0DdOVt2515bbLXJ4UkCZSUFFZgSJI46XtvBdOtwhkG2J+18LlkjirzMpjUWTa7irs27OTzpzaS0i3+Y8NOvrFyHj3RJA+9uJu1S2exN5IcM0kXWmlND3spKfHmvj/bdj3r2vmJ/3ohJ92865JWZAEqg25mlHhyplGT7XMylElibvv2kTSVARczSjwEg/Bvq4/mS795Ke8hvIA71rVx+WlNbO4e4dGXHBfM+dODXPPAS7njjWkm33zs1QlOo/9+8TF0DSdJ6RYLa4KcMa+a53cN5RxKq0Nuls2u4o71O1izpAFJhNb6Uo6bEWJPNE3f6P7jE8WDZ7ww1Vg7VPFO3wPj0TmUKFgOe/zKJdSXTv29lmXTNZIs+PtVI+QC0vwyWG3p5OPWsmzcapy1SxuwbIcArBsmp7VU8pMNu/j6yrnc/nQb5x1bx42PvTpmv2Gvk3FYtbiWruEEnzi5Ac0w+N+Xe9jRF8tlN4YTGi3TAqxd2sC86UFKQhOP5Z245u/mc+1QQPGc3nscikHFkra2tj0tLS2VwFMtLS3b899sa2uzMwHHOwrTtCeV7bzTkp6QRG4lJAhO2vSypbOwLQvNtLnzmXY8ikRPNEWF35WbOLMT+8t7ovC3Tj532ixMC256fCthr5orBzy0qTvHJwh7Va44rYGGygBtvaOMpnRqA45rZ3t/LJeGzQ9sOgeTrL1vIw+vPZGQCNHRJKZhFlzhhySmvDbBoIcnt/UWXIEeP90/JoU+ENe49OQGNnePEHIrXHx8PU9t7aGx0jcmALvslAY6B5Pc93xnLlPhUyUEUWRnfwS3InLZ0ll8JY93Uh1yc/1Zc3KS3B890wE42ZFrljdz3SOT8FsyKflISselyJNKdydDRUVgwmtTjbVDFQdb1rZ3ODEmYAUnsGjvG0XTzMmv9xtkOAyTCa6rt69r59RZZZOeT3/K4Au/+vuEAHrt0gZWLa4lrhmc0FCRCyjy93v7hccwEEvzyItdXHpyA93DSWaUevnm2XP52+vDJDWTG8+ex2haZ89Igt9s7KZ1RgmFBHpvQVI64bV387l2KKB4Tu8OCo21LA459UdbW9uezP/7gEeA44HeTFmDzP/7Mh/fA8zI27w289pkrx8ayKtJL59dzqeWzGTfSIISn8qdz7RzQWsdSd3krg070TNM8uqQG58qccPKuTl+hUuWco6bWWXHmiUNfOLkeo4/Ksx9nz6Ob549F59b4fldg2zbN8ofd/TzXFeUE+uCLKwJEfaqU/bDyD60z/nJc9z6ZBtrlzbww4uO5uG1Jx5QarpQTTvHdh9ns1zuc6EZJpYNLVUBfvm3Tj69ZBavD8RztuUp3cKjiNSXecaktINumb/vHuaBjd1cv2I2lmUT9qq0TAtQX+bhkhPrx0hys1i5sCYXUEw4vsy5X/7rv/P37igX3/PXw9Le/HDAZIqSLXtHJ7/eAnTFdNr7Y1x2SgPVIfcENUV/bBJp8RROlpPxfSwbJBEqA64JTrfZz2iGxSMvdnHe4jq+8uBmvvrQK3z6v1+goz9Bc4WXCr+K3yXjkiUW1ZZw+4WL8HsUtg4l6E8fes6kRRTxZnFIBRUtLS2+lpaWQPbfwBnAFuB3wCcyH/sE8Gjm378DLm1paRFaWlpOBCKZMskfgDNaWlrCLS0t4cx+/vCOHqwAQ5pJRyTF5v74gT8QsvK2gQQgICIymtQxbdjUOZzr9SGLIisX1mDjrKY/efJR3L6unfv/tptbz1/EdWfN4VuPv8qC6aGcHfV5xzrcCFEQ+Ng9f+OPOwYRENgXSfHoS3vwqRLzpoco8Sj8vSdOZcDFpSfV50on+agv8+B3K2OsvbPcjGsffNn50AGs1Psm84vIBCz5EtUKr8SMsJfHNu8hmjJYubCG7fuiuUBhdpUTIFT4VD53aiP3/GkXd67v4Pmd/fhdCpYNqiygWzZel8SlJ9Vz65Pb+eqKOdyxvh2XLOau1XVntvDDi47hqDLvpMeXVaisPnZGwc6mRRngO4fxvTeyRMiHX+wufL0zAd/F9/yVO9Z1cPezu7jkxPpcYJENGioDb17+OlmAIwpwWlMF0/wqc6qDBT+TSBtcenIDNz4+Novx9Ue34Pe4qC7x8NfXBvnO/2zjU//9Ajv7E3T0jfL6QILLf/ViMVgt4rDHoVb+mAY80tLSAs6x/bKtre33LS0tLwAPtLS0rAE6gY9mPv+/OHLSDhxJ6acA2trahlpaWm4CXsh87ltZ0uabQib13d45PNZ5UYAX98XYNRAv6OZ4IJbZ2W1+esmxDMQ17tqwiy8sayRtWIS9KnOqAryyN8JQPM2NZ8/ncz93jJ5WzK/myw9u5sYPz6NzMMlQLMXnTm3kJ//XwcqFNdSWeLnlye25jpyyJPDrF3Zzxamz8Lpl+mNpbnp8Kynd4qsrWrh9XTvNlX7+3wWLMEyIpw3CfpVoUufie/76tq29KwMu6ss8rFxYk8sqPLZ5D9MCroJp63K/wqdPnonf5WRhsoFCyrD47z/v4oaV82jvHR2T0r705AZ29o3y2OY93PCPc7nyV3/nn8+ck/tMR1+MsFfNBSM/+b8OLmit49Ynt/PlM2YXJIz63QqdI0nCXpVpQfeEaxD2qkTSh2e310MSedm7zpEkW/aO5iSXMG7MZTIU4zNg2VLePX/alQsaZpR4JrXr7k8U/v0qfBI/+fixbNkTob7MR89IghllPtyywAy/AsBeWeDGs+fxjd/t51RctayJgXiacoGC5NA/dQxQV+plW88Il5xYz33Pd3LjY6/yH5e00jua4stnzObWJ7fz4wuPKcpLizhscUiN3La2tl3AogKvDwLLC7xuA1dMsq//BP7zLR9MJgC49ak2Vi6scUh9dWHmlHvoTxi82hPNEQDhjSWWMNaboTrk5tKT6kloTro/pVuIgsCc6iCfOrmenkiShTUh2vtiDGRSuPmkTq9LdlbtQQ83Pv4qnz55JoMJDRubC1rruH/jbr521lzSusWFx9VRFnChGXYuoACIayZhr8o1pzfSHzP4+u+cnhpXLW/MnZsnY56VPeZVi2uRRAhkuzO+wURaG3LzhWVN/Mtvt+RIoN/88DxGUhN9Km59qo2bz11A2rR4fSDO3OogNz+xja+umMP3f7+NC1rr2DeSpGrcJJ9MGzywsZvPLW3IBWUlXiV3zDPLfaxuraU7kuKuDbtYs6QhR0699cntY6Sp9WUervxgUy6gWt1aS/dwYkzgsbAmyAXH1/Gpn218R5UKRzwy5TBKvFzzwFg7+vxmYM93R2nvjxUMdiWRMWoKURQmyl+n6v8hwB93jeT6y2SDhe89sY0vf6gld5y1ITeRpOGQPsNe2vtGc/LS2z66aAI59IaVc/GrErsG4nzsxJl8/dEtrFpcy4+e6WBfNMW1D76MWxG55vRmIim9GFQUcdjikCp/HEroTxrc+lQbF7Q6LbPvWNfB2p9v4s+dEQbiWi4QyMeB1mqrQ24+t7SBmWU+hmJppIy0TEDgx8900FwV5LtPbCea0qgp8eBRHHdIl7x/Ynt4UxdfOqOFpG5y4XF1JHSTv3T0U+pTuX/jbj598kxsy2ZfNEl9qZekZrFtX3TCMX/q5Hq8LjUXUICTHWiu9PPTS46lscLHDSvn5ngJ2Wtx0T1/PaBUbddIKhdQVIfcXHx8Pd987FV2Z1Qa+Vi5sIbN3RF+8NQOHtzUjSoLfGFZE91DCVYurOH+jbtpqvLjVse6ZXpdMsMJDd2ysIErTmugzK/mjvlnf9nFzHJf7jfLbymfJXx+7czZ3Pvp43INy8JelUq/yqwKPw9sdOzNs06ol5/WOCY4O+LLIW+1Y+kk2xUqhWQDhWxgnnWXzYdbETmtqWJMcGdZds77YlrGo2Vzb5yO/lhOqZH/+3WN6rmAIvveHevbWbmwZsxvPJIy2DUQRxBAFgUayv18tLUWgJ39sQnk0Jse38qOvjg/3bCLvmiab509j4DbGceVQVfuc7c9vQO3Wgwoijh8URy9k2AgruUmnvyHw3WPvMKv1pyQCwQKrqYmQbZWe+lJ9QgCJHSTaMqgKujiW2fPpczvRt0mkNLNzGrbhSIKaJbF1cubmFHqzUlBP35SPYOxNHVlPmwbbslwB/6+eyQXZGzdF+WVrhFWt84gnjZyD+J8tUnIq9IbTY05j8qAykUn1NM5EMO04dcv7J7QzOxAMjMAXXms/o+dUMdtTztyzvGrf3BIcHHNJKVbXHj8DLqHkgTcEs1Vfl7cPcLKhTUk0ibfe2LbmOzCszv28a2z5yOKMBRP0zItyNa9Ea5bMYfvZTIcibSR+82y35X97gq/iiJJrL1vE5ed0uBkb5Y3otvQM5JkOKHlSLCzqwIFg7M3UxJ6X+Gt+ku8wXaFsgv9CYPOkSSXndLAhra+gn1sZviVXIlyKG3y7Kv7+Nojr4zxOsnPQIx3tUzohS22syThgbhGhUemcyjJoy/t4YLWOq55YL8s+oaVc8cE/4X2ccOjW1i7tIGaEg+3X3g02DY/vOgYEmmDgXia0ZQOXuWd/62KKOJdQDFTMQnKfZMzvFO6wdzqIFcvbyq4mpoM2RXYjLCXgbiGKoskdZNf/a2LGaU+/rBlD585ZRZuRWJ1ay1DcQ1FFvnWY1sp8yq4ZJHrV8zmmtMbCXkUFFkiktRzK+/t+6IIAswIe7l9XTteVeKjx9WxeyjBcELj+Z39/GD1Ii46oZ5/e3I7eyMpkppJxTgyW7nPxY2PvUp1ibMfzbBJpie3t54UmUk8u+8Kvyv3cB2/+r9qeSPH1oXxqxKt9SFqw14My+a1wSQ79o0yf3qIkFsmrplj5KTXndnCmQtreGBjJxV+F/G0yVBcY3rYS1I3cxmO2lIPR5X7+OKHmnls8x7mVO0n2l3xwcYxxLrLT20g4FG56fGt/Oy5Tq5a1sRwQuNHz3TQ3jc66Sr5SHRFnLJXzNvZLl8Z5HHKFavuep7Lf/F37n52FyvmV/P7LT2sWdLAVcsb+eWaEzhxhtOddttggm2DSda3D/C1jLIn32U2+313rG9n1eLa3PizBSZkwcD5bX2qxFXLG9Esm+6Yzg8z2Yvxi46bHt+KSy68j2xD6JRuUVPi4d//2EGF34VuQXvfKF0jSR7Y2MVAXC+SNYs4bHGELasOHBUeida6cEGSYcit0Bj2cFTYw9G1IRKaSXXA9caueJkV2Eu9cSwbuocTLKoN4VEkBmJpzl1cx2BM47tPbOFrZ85BFAT6omk0w8awbQTAo4qYtoBm2rw2EGdOVZCRhIYkgleV8CoSZFZEsiiwsz/GpteHOPfYWi47ZRa2DT/5vw6uOHUWug2dg3H2DJl86+z5/OiPzoNSM+2cPC5rOJVvrnVA3IrMSrQnksx5ZnhdMm5FxKOIudX/1cubCHoUbnp8K82Vfv555RyapgWIJg0qAm5iaZOAW8bvEplfE8S0oLU+xKUnN5BMG8wo87B3JMVpLdNo2xelIuDC55JIpE06B+NIohNwpTWbJ17Zw8pFtZxzdA39sRQ3nTOf+1/ozPEwVi2upTKgUlfq48XdwznFS/Y4a8NeygMK1z30Ctec3sxtT+/IrVC/t+rIdEV8qx1L38x2hQKQfFLmLectZEZAGcOTqC/zcO0Zs3PbjHeZze7HJYu5DMaaJQ08/vKeCRmQ75w7n5GEPibLcc3pzaSNwlmNPSOJCX1n8i293YpIJKHxzbPn0T2cZGe/02BsOKFx1bImbl+3g9kXHkNJ6E38EEUUcYigmKmYDDbMqXBIe1np4t3P7uLKDzZR4XUmj1KXRMglo4gCB7y0sKEm5KbM52Qe9kVS3L6undqwh8G4Rjxt0FDmw++W+fb/bqUqQ+iMpQz2jiSpCfu48bFXGc7wOuKagWnZLKotwbbhnj+/RiDTobPC72JBTZCPHlfHvz3ZRkIzGU0bXHhcXW4lvmNflLm1ZTy9bS9fWOacq0sWaK0PUeZXWd3qkEOzmYUD5VZkJ4L/+ksnXkVi7dIGVFnka2fOJuBymn0NJzRiaTNn3vXxE+pI6xabu0co9SsE3DLzagIcVe7HsGBXfwxRtFndmvEAePgVhmI6XUMJKgIu/usvnVT4VQzLwrBtntnex6LaEsp9CpIE5x5Tx1cefJnfbOymN6oxGE/zpTNm41Yd+ek9f9pFb1SjL5rCssnJTz9xcj0lXpVbn9yObcOaD8zEkzFDunJZo3Nu0pG5tHyrHUvfzHaTBSDzpwdyfin9ibEk6Ata62jvGx3zHdnf88plzn/1ZR5OmBnOTf6C4Bi//X5LD/96/iK+v2oBt5y/iLpSD7f8oW1MUHPb0zuYXeUveA61GffDr/xDCz+86Gh+/LHF3L9xd66x2PUrZmMjcPnPX+SqX7/ETzc4ctiwV83xN6bMABZRxCGMYlAxBfrjxgTS1g2PbqE/sd8YaarW3QUhwkA8TXXIzeyqACGPmimpWJT5VEJehcuWNrBj3yiaYWPZFnWlXqpLvNzz59cYimuEvSplfhVJAL9Lpiro4f4XXqc27OHC4+roHEzwxQ81My3kRjNstu2Lohk2XlWiKuhiRtjLzv4YzZV+/nFRDX3RNAtrS/n13zr51/MXEfYqXPOhFu5cv4PGCv+YFfuXzpj9xp4NAuwcSuS2+8mGXZgWvDYQ46hyH999Yjv3Pues/mdXBUjpFpeeVE/AoxJNGrhkEdO0CHsUVFFiz0iSSNIg5HUhiSLf+N2rNFf6ueOiYxAFeGZ7H9UhN6os5OrZFX6F84+tZTCWYu70EC5FYtu+KGGvmiHJujl+ZilDcY14Ss+5j84s99IfS7Nj3wifP83xwjBMm5/8XwcXH19P11CSaMrgu09s5451+1uuf/E3m49IouZUpMq3sp0kChOIm5MFIPUlHierMa5BXVYllV9i29DWN8bb5O5nd3HVsmbiaSNnnAVO4LFifnUuaL32wc10DiZzpM4sUrqFYdkTSqDX/kMLFQGV2rCXyoCbsE8hlja49ozZXLmskTVLGhhNG7ksV3Zf2VJMVsFiCQKWdYSlvYp4X6AYVEyBqVK0b6mWLMDWgSTRlMlrAwlGUyZhr0J9mYfRtIHPJVIdcjEc12maFmB1ay0DozqSKKCbFisX1uDOpGs7+2PUhNxUBFRkGY6eUYZXkZhV7ueeP79GiUfGMG36R3PtGwAAIABJREFUY86q+zOnzOTmJ7aR1E1cipjpOzCLbT1RSn0KTdP8nLe4jn97cjudg04fhX9cMB1VFsc80PO5FdUhN19d0cIt5y9idyTFkG7SnzLoGEnR0RfLbdcTSfHwi90kNJNY3va2DR2Z1WRt2EvXUJwyv0JNyEVcdzqW9kSS1JS4mRZ00TOSpH9Uo7nSz0Un1POVBzfTE0lx8fEz8KoSN587n6Ru8Z9/2oVhOaTPr/9uK0NxjZG4TsitcPWyWYR9MqV+F33RFOUBFbci54KNEo/CAxu7uPSkhpwHQYXfxepjZ3Db0zvwqjKaWTjtfUSuLvNIlfd+svWAnVYLbafKIuf85LkJQXqFV+Kmc+aPmbxvOme+kzHMID/wyJY68l1mP3vqrAm22v/821fYtDuSM87a0NaXM0rL/9y//HYLqzPKjizcisj2faPc+5yz/2zGSgQ6BxNc++BmrvzV39mxL8a1D77M9t5R7n52Fz96poPUJGWTbIOxhbUlfON3W9g9nHwbP0wRRbw3KAYVUyDgVgqukPxuZcqAYzL0Jw1e2RPBwqbc70IWBQbiaf7lrLkEXDJJzSKetijzqyiyQF2pF9Oy8KpOB0SPIjIUS9E8zU9tmQ/LtkloFm5Z5v6Nu/G4RGQZLlvSQNjrIpY2aKwM8PzOfqYF3XQOJunoiyGLAq8NxDBtm4YKH7sH45R41FxzMp9LZEbYw1EVfu5+1mleli17ZLkVWVkswLUPbubGx7ayfscAq+56nj/vGhqzSlxYE+TKZY73xWsZy+3savKZ7X1848Pz0E2L6hIvXUMJygIeStwyCc2kP5YmnjaJpnTmVAcp96tcflojNz72KifNLKWh0kt12MveSArTFujPBENDcY3yDDG0xKvgdYksmhGgqsRLZcCDIkrYtkBHrxP8rG6tJaGbDIymWPOBmQwndMJelW+dPZfpJR6qMk6ND2/q4phMC+zx4+JIJGoCE+zWxwQUU8lN87YDuPr+lyYE6UNpk65Rnd5oilvOX8R1Z7awZkkDdz7T7mQMMyiU+YD9AW1SN6dUZNyxvp1TmivZNYn/RV1GeQVONuPOixcjiyIfP7EOv0sCHCl2dYkHr0vma2fN5qeXHEt1yLHAf2jT/vsh//iyyDp2fvsj80loOp2DSbqGD61+D0UUcSAoEjWnQDStTyBtXbWsiVhan9C6uzrkZnVrLZplO5bT4x0WBRhIaMyq8FPidXpxSKJA0C0zktRJ6iYlXoVI0qDMJzMSN5EECHoUuoaSxNMGJzSE2RdJE3ArJDSDmlIfkYSOJAl8fmkDoiDhVyVsO0kkpVMVdBNN6Xx2aSO65Rz/zt5RZpb7iKZNZkgCtg2mBSNJ53M/3dDBtf8wh5GETsqwOKGhgp9s6OBfzprLF37991zjspRhktDNXD16PLs+n4jZNC3Alb98kbBXJehWuHp5E8mMbPa8xbVIgk11yM2mzmFmlvsYTRl4VYkSr8LmriFmlvupCKiMJnWCXpXBuE1zpZ9LTjoK3bARBIuwRyWWMuiPpZk7PYSATUffCPVlHhKaQdCtoJs20WQa0asynNBwyRJlPhWvKtFU6ccGRAT2RZOU+xW+dEYTugnbeiLMr3Xs0M+cX4Vp2zk/i3w545FI1JwSb0JuGknpueZw4DhQAmzZFxvTxC5r3d0TSY0ldeZlPiIpncbyBbmeLqtba+kamihhHq/IqC/14FHlgp8r8SisXdqAV5UIuBWuzGtxfvXyJh7a5BAtb1g5l7s27ORLH2phJKGxN9MEMD9rEnRJE8bPTefMR5UFQh6VaQGVjx5bjddVfDwXcfhBsO3iUxBA1017fCe4jmiK6x5+hQuPq6M27CWRNhhOaBxbX8JRIRd/7oxy29NtXHhcXU7BkH1I/PhjxxByq/SOpqgJeeiJpvC5ZO59bhfnHjODB17oYu2ps1AkAcu2SWoWSd0k4JIJuGVM28K0bIbiBrpp0TWcYEFNiOG4Uw5xqxI2Fj5VBgQM02I4ruNWRRRRJJrSqAq5MS0YiGmUemV0y8Y0nYfkX18bYlvPCJ9e0shXH9rMbR89ml0DcVRZwrZtxExA80p3hE2vD3Fe6wyu/OXfAcdR8oplTUSTOtc++DLVITdfOqOZL//m5ZxTaGXQRedggqbKAO19o9yxroMvn9HMnc90EPaqfO2sObT3jeJRJJK6SV3YQ3WJh+GETmXARf9omoqgioBAWjeRJaehmIiAZUM0qdPWO8qi2hCiKPDMth7OXFDLzU9s5SsrWhhOGHzzd1u546KFKKJETySNbloE3DJpw8KTkQ4qgkgklcalKAzFNGTJ8QkJuGU0w+aaB17iotYaljRXkjZsXLLAzv44v/hrZ85pdW51kNoSD9MyK9Z8VFRM7D9ZaKwd6ngrnRL7Uwar7np+wgQ9wdtEgD93Rbnu4f3BxzWnNyNg84On2ydsn1V9TOmRkrHYH0mbJDSDGx59lUtOrJ+wQMgqMla31lIT8jAQT+NXZW7+/faciuT6M+dg2TaWDYoocvX9EzuYrlnSwI+e6cj92++ScjydT5581Bil0HfOXcCv/vo6XzxjNi92DjOrws/3fr+NzkEnALn53AXUhF1U+FWG4ya9oymqAm5qAwpYhU8X3vxYOxS7X75dFM/p3UGhsZZFMRSeAqVuhTUfmElcM/nZX3Zx6ckNuFURVZJ4sSeGKgtctbwJlyTx5TxjqOZKP/uiGpf/wnn4fOcj84inDerLfXzshKPwuWQ+elwde4YTVIU8uGSRH67fwdXLm7FsC820UCSRmG7gUkQCHpneaIpI0iCh6VSXeBEFC0VSHMOotEE0ZVIZdGGYNrppMj3kZSCWpDLoQRIETMtGFkVe6R5hcX0JjZU+ppd4iKZ0rjh1FgnNpGsoQWOln8qgC9206RyIcdzMMK31YXTTzhlvrZhfjWXZdA8nqC/zcNmSBkq9joPlBa11/PqF3Vx8fD13bdjFZac4JZL6Mg/1Zb7cNeoeTjCvOkhcM0nrBtUlHhRJoDroIm2Y1JY4PBPLthAFSOsWblVkIKbhc4kYts3sqgA2MBTX+OCcasDm+rPmYFpO11JVFrAtEc22CbplFFlgKK4TcMvs2DdK07QAadvErchEkhq90RS1pV6qQm6iSQPTtjlr3jSOqS9FEgV6IwkapwX4wVPOBJFtn+5WRO75RGvBoOKwx2T9b/Ley/XP8Epj+mlEUvoByUb7k0YuoMh+5rand3DXJccW3F4S4fYLjgZg22CCgFshpRuE3Or+47OhwiOjqjL9MXuMgZlLFmmqdCZyYIIp1o1nz+POi45BECCSNPin+/ebW928akHBYzqqzMv3Vy3A65JRZZGUZuR4Hf/9l9e58oON1Jf5CHpkJNHikx9oYDDmlEqz5lnZfV3/yCvc++nj0Eyb/32lm4V15ezoj5E0PTSVuuHI4wMXcRihGFRMgVKvRH25j//Z3M1Hj6vn3r/s4tzFM+jKEKj2jiQwbSbUay9bOivnPvnB5nKCHoXygJtyn0I0bZLULbqG4hxdV0JCM4jFjQyXQWYkqTE6mibsVdFNk0q/m75YiulhD5V+F0LQhWZaCIKcUYIoeFSnlbJtOwGFR5EZjKcp87vpH03nSis9EYePkdBMynwuekeGOKrMhyIKJDSDl7tG+EBjOXuH48iyjG0LxFMGINA5GOeqZU0IguOw+cXTm3lgYzffOnser+yNML3EzXUr5nDNAy+xZkkDtz29I9d6/Gd/2cXlpzYiCOQCj3Xb9rF4xWwkUcAXcrO9J8q0kIdpARduRSaumyQ0E0UGwwLDtFFlkRKvTNCtoMoGiiQQSe4v8wCIgsBATGNmmZebVy2gdzQNQE2JG8u2M22nRRbWhuiLZTtZqpT6XPhdClv3Rmmu8jMtoJI2bT56vBP87R5MMGd6kJEM1+LyUxtonOZHM2xiKQNJFA6oF8phhanKF0x876Zz5nPnM471eX2ZhxvPns+Xz2gmZVi5ckahEuHeSTrZpjOZgvE+McuaK+gYiOeyINmsw/0bd/PlD7XkenhsHUiyafcwroyU+btPbM9lE65fMZvVx86gvszHteOcYr/xu1e54R/nUBXy5Myzsu+9nuEEjc9UdA0nuGNdB/VlHq5bMQdRFLluRQs/e87JhCR1C9t2fDF0U8AwTUp9So6rUx1y84Vls6gJe4mnDIQM+eTDR0/ngrteGHONT5tZMmXGoogi3ksUg4rJIMIrvQlGE2k+ckwd1z/yco5XcOOH5wFQE/bypd9s5rJTGsY8/Gzbzj10PrO0gaGEjioJJHWLRNqZDBsqHalm0KXidTmlDlUSCHtVLAv6YinKvC5006Lcr5LWbdKGiSQKlPpkXhtI4XfJDMV1pgVVgl6ZzsEUJV6F/tE0ZX6VhGYS9Dh+DyMJjZnlXuJpHZ+qkNANjqmvYG8kiSyKlPtVPrXkKEYSGrYgUuZTUCSRtGEjSw4B7e5nd/LxE2fy2aUNuBSJ4YTGSFLHsmE0ZbJ7KEHYq9Jc6aO50s8Fx9fx2OYuvrC8mc/et4l/Or0pF3j86/mLGBzV6B5OUBP2Mnd6ENO2iWsGoigwkjkv2xawsLFsm6G4RnXIMcTyyBIp0yTkVoikdLyqTCxloFsWlQEXCcPEtGBarq+Ck82ZFnAhiQJpw6LcpyKKjnRPM0xEQeC4mSXE0xYpw0IQbJK6RWXQw33P7aIq5KbUr3DN6Y0ossTmrsib61J7mGEyhdPDa08EmPDeDY9u4erlTYBTOvvczzeNKWd4FJHvPrF9zPVqrvDhksXCPAavMqYZXXZSHUxoudey333H+nZuOX8RHX0OZ6ijL5bjVLgVkX8+aw53X9rKnpEkXlXmPzbs5OU9Ua5a3lgwoPG7Fbb1TLRjzwbSX8/rTnr18ibufa4z54+Rb9v9xQ8145JE/vMvr1F58kz2jKTGjJkff2wx9WUePru0gUjS4FuPbxpzrh9oDHDWvGk8/FJP7hr/cs0JzPAVbbyLODRRVH9Mgq5Rnb3DCapKfPSNprnwuDoiKZ3mSj/15V7CfhUbco2nsp4GD23qpjKg5lQPwwmd3kiKtGER1wzCXoVSn4osisTSBgnddOr6CYOE7gQXuuVkEiJJnZRhYpjgkgVGU07eM5ZyAo2gW6bUp5A2HO5FqU8hktSYHnKjSJDQTFTRaURW5nc5XAJFxrJtVEliMJ7GJUv43TK6ZaJKEpUBF0eVefEoEgGXTEVAIeRRuPvZnfzTh1qIpTRmhH3c/exOblg5F59LQhKc/hluWeD6M5sp9TkKjUde7OKsBTWMJp1U8P++3INpOQFXMm0wmjKQRJGKgAsQcvwK07SoCrnwKDJDCY3RpEHApVAZcIKsgVianmgKw3QmfZ8qE0sbhLzOZwJuCU23SGoGXkUk4BaQRYnqkJuUYZI2TUbTOhYWiiQwENdIGxY2FroBLkWgP6YBIj5VJqEZXHJSA36XjIhIwK3yWl7be3gHmoq91aZcBxFTKZwKvRf2qgQ9CkndnNBw7band4zZJnu9/mdrL1956JUJfg9XLWvi77uHJwQPNzy6haRWWJLZ1jvKb1/aQ18sTXemR0h1yE3Yq5LUTS67dyNffcjxnvjHhdOpL/Mwp3q/XXsWbkVkZ3+MhbWhCe8NJzQaKnz8YPUivn/eAv79Y4u59zmnf0h+F+HsMf3gqR0MJpw+QoMJLTdmqkNu1ixp4NW9Uf71/IUE3eqE8XTDo1voGjL5yooGFtYEc6/3jqbe2g9aRBHvAoqZiknQE00xs8LPvmiKMr+KWxYZiKW4/LRZDMSc8sRwLMWlJ9XjUUVueNRZuVx+qsMhuHnVAir8LqfDaIY8KQkCpm1hWJDSHd7AvmgK03aMqfpH04Q8jrJDFAUqgy5SuolmWugWeFUZ23b8FwAqAwppQ2Aglsa2oTbsPEBFEXRDoCroondUI+CSSBomlgUu2Zkoe6NOVqM8oJDWbNKmhWXZmLYznyV0E1myEQWnA+gFrXXEUgalPhcJ3WTZ7Co27x7k3MUzHAWFS2LO9CC2DVv2RknqJpef1sie4SS1YS/1ZR4+fkId3kxvj6MqfGzdG2FeTRAbm9G0gaILhL0KIGDaNtGUQ9rUTItIUqfEKzOcMKgOudEMi5GkjioLeBQ10xbbQsCR5iU1k8qAE0jZOiR0A5esOuoav0LQrSAgoBsW04JOdkgSBLpHUkwPuakKuugbTeNVRfxumWjSQJUEhhI6tm3jzXhbrFpcO0ax8Jaair3VplwHGeMVTpAvnRUmvLe6tZabHt/KZac0FJz0x3s5ZV/riaS497lObj1/ETv6RjEtuO/5Ts47tjY3AedfZ9O2Ch6XWxa5oLWOz/9ivzLjmtObmVnm46o8cmU2yPnhhcfQPZyYoMTIEjj9qsQ3Vs7L9YVxKyLf+PA8tu6N5jIuVy9vZDjhlNEmswK3bOe9bJfc6pA7RxoNe1XCvolN/bLn/PpgnJTu5q5LFnDujzcxnNCYFnC/5d+0iCIONopBxSSYFnQxnOmQKIrOTDuj1EtCs3ipc4CTmiqpCHho7+2lNlxGc6Wfa85oxi1LvNI9giJLuGRnguscSDA9pFIZ9GLaIoMxjdqwh6RmUuJVGUnoTC9x41EkVBkUSUEWxYzplaPEMG3wu0TiaQvDMkkZNmpSZCShMS3owrIzdVucrIUiCwQCbqqDLmJpnVKvimbYSKJFQjOpCKqokkgibaGbFpGUQYlHJprSEMi2YpeIpQ0qAy68qoRlw0AsTZlbZv32fVy1vBmvAiVelbimE0maGaKow5T3qhJxzaR7OMH1Z85BQGBX3whXfLAR3TSYVxMkrdvE0walPhXbBlUUGEpqKJJAIm0RdCvYts1oysCMWSR1C7cioEoiQY+MW5boG00T8shIoogo2BgWhH3Za2jTOZSkMuAiphlU+F0YlkU0peN3SRgWVAUV9oykkEWJyoDKYFyjzK9S7nfhkUVcioAkCCiiSMjjBF6VQRelvka8qkI8beBzy1xzeiNBz5tPS09VZngvu55mvR/GBztZt8zx783KuK9C4Q6+4rjsS76ksyeSYnvvKHeu7xjzmSwHJ1+18fWVc7l+xeycQiMbCAgCE1b7tz29gxvPnldwso9rBt//Qxv/dHoTa5c2YNmOIdt9z3cynNCIpEx+8bcO/jVTVpldFaQ3kuT7eZbdD2zszvX5mOq8LZtcl9z8jMbHTqjjrg07+fIZs7lqeSOWDRva+jhvcS2DCY2u4SR7R5LE0wEeufxYnu0YZcYbqECKKOK9RDGomAQBt4Rlq3gVkZGUQdAjOz4HiTRnLqhFMy2G4hpnzK/BME0+d9osvKpAf1SjpSrID9fv4CtnzmYkrlPmUyn1e0jpBi5ZIuiRSWmOoZMNVARU0rqFNxM0iIKAKDqKh1h6fzo97PGQ0HQqAyqmBfuiKUo8CqIAIY/E7qEUhuWQEd2yREJzyimKJCEiYFoGkiijmRqlPqcUEE+bWLZFmVdlMO54YIiCQ3jsHU1T4nVKEvG0ybSQikv2sGc4yeeWNuJSBFKGyOMvd/OZUxoJugUUSSDslfnFX1/nhKNKWbdtH5ed0oBLdpqgLawrRzct/C4J07KJ6AbTgiq9UQ3LtnHJonMMgCxaDCd1kprpBE6Wjd8FumWRNk18qhNQlPtVBmIahmkT9MiIgkNzMywnCKkOuhhO6BiWjeC2MW0nCxRNGpiWSSQhEnKr9MfSzKrwZEzFdFyKiGEJWBqkdRPFJeDNfGfALaPIEjsyXUslAY4q92G+hdTCW23KddCR5/0wkjYpcUljvDjGtydHcLIXWaOn/EDgmtObcedxJ9yKyLfOnsfPM5JO2D/pZq/FQ5u6+frKuRPUEd96fCtXftCxvJZEaK4M8J3/3ZbLbOQjpVuEPErByV4WxZw6yafKY2Sf+W3RBWw8ikRvJMlR5b7cNg9t6s5lWW6/4BjShsF3zl3AP+dxOa45vZmwR2YwoTOrws/tFx6NZti5jEVdmZeLj6/PkUXdisi/nreAuGbx6Et7WLmwBlsAQRQYiNuc1lgC+kH7xYso4m2j6FORwXg9967RNIblcBBSuoFXkRlJ6bhkCcOySWkmIa9CNKUTdCvIoo1hCYiCI3FUJRFfxrzGBqIpnWkBF3HNJOSReX0wyfSgo0gAGE5qlLhV+uMaluW4amoZXwTLJkOatJx26ZpJ0OM4Qtq20x/EsJxloEsRwBbojaYQBccDQxIFVFki6JLZG0lR7lcxbRuXJDKSynxvLE1V0MVIUs9lGkIeBWzoi6WpCLgQgZRh4FFkeqNpqoJuBhMaHlkkljYRRUfKKQoCNg45UhJEBmNpqks8AERSBqoEXkVhJKkT9irIooBu2c4kblj0jqbxqCLTQ276Y2mwxYxvhIkqiaiKSG80hW465ZwSj+JwU0SRwXgav9tp8uZkVrJ+HTa6YTnk1mSagKoQ1ww8qsxgXCPodkpLbllEkUVs20YzbdKGhQAokoAsCRimjSILWJkGZ/mZikRap6HCT32es+aBeAf0p0xW3fXchEnvvc5U5OMNtfICDKXNnFlV2Os0o5tZ7sOryHz3ia1ohp0rY4gC+FUJ04Z7n3MyA9evmE3KsMZM7t8/byFX//qlCV/3xQ81Y1gWDeV+gm6Zf/9jO584uYH2vlG8qoRh2qQMC78qUVvqoWsoOYYg+e2PLODXf3udjZ2RnBqkIuhi+z6n/JI12HIrIj/79HG098YYTRkTOo/+fksPZy6oZma5j4BLxqtKDCU0ZMnJSIY8jt/JvmjSyXSmDVRJIpLSmR5yo8oS9/ypg0tOamA0qeN3O5ynO9e3s2x21bhuqQtYPMOPX5EKBhZFn4riOb1bmMqnohhUZDD+5ts8EKcm5GYwruOWRTTTxCXLpA0dzXRWNnFNx6s6aouqoJuUoeN3KcTSJrIokDJMZBE8iohhiSiSwN6RFKU+FUlyJjDTgv6YxrSAC0GwSes2qizQG01jAzUlHvwqpE3YNZCg1KsyFNcp9amUeCU0w0YzbJKGjmlCqU9FM5zJSRZF0qZF0CPRPZTCozolmUhSx7Qg5JVRRRHdcjIaIY/jOikAlu2oPnoiGqVelRKvSG9UQ5FFJJyJPakb2LYTSJmWE7z0jzrH7VMlwl4VzTTwuSR29adQJUdlopk2pmVi2QKQtSaXcckOn8TnkklqjtIlq4oZTZsYlknY62QsbECSnLKEYTp1a1UScCkCe0fSuFWH/DqjzEPXYNZa3MVwwkSADGlWJZpyCJmWZeF1yZiWSZlPZTBuMBjTKPFKJNI2DRVukrqTHSr3qhgZpYoqOVyYioALzTTxqzJ1bzKoOKicivFeEuOdXg/w81M+2AR4cV+MV3uiyKJIQ4UP27bpHEzwm01dXHHqLEyEXO8NtyLyjZXz+NXfOtnRF+OW8xchALc8uR3NsPnYCXU0VPiwLIeL8KXfbJ4QcP3o4sVckedq+Z2PLOBXf3udPSPpCb4TVy9v4m+7Bll9XB3b90UxLXj85T1c0FqXy0a4FZEvnt5Eqd/FD9e3s/rYGVQEXFQF3QTcMn/c0c9dG3aN4XiE3BKlftcYdcrXzpxNMlN2yQZWDeV+ZoTd2JDLqPVGU8ydHkAUBfqiadr7YnhVidoSL5ppUepTuHN9O3tG0nzshDoq/C58bpmakJvqkIjExMCiGFQUz+ndwhEZVLS0tKwAbgck4O62trbvTfX58TffoGmS0iz6RjVM26bC7yKS1JgWdCMKEEsbBFwy/bE0IY+as5bWTIsZpTJtPSnCXicjoEoiA7E0JV4Vn0tkMK5R4lGJpU0iCZ1yv4osCeyLpCn1SZR4FPZENKYFVQJu2DtioUoCHlWgczBFhV9lMKER9qgIAowkNUo8LgzLRhRsx3Uycx6qbGOYzu8/EHM6nNrYKJJASnd6H4Qzbpu6DhY2sigQSWmEPU57dsNyasJpw+lD0hNJUe53k9JNkrqBLIh4Mg6foiAiCSIJ3UQUwK04hlBpw5nMParEvmiKoFtFlQTcioAgwFDcIZ9ato1HdpQpJV6FvlGNqqArl3FIGyZ6hlRaE1bpjZqUeLKqEWdfkpQtf9j/v70zj5Ksqu/456219FLdPTM9uww4cA/DDAxIRlBjQCIhyQguQMDEBT0STyTiklVjiKJGT1CCcckxSkASRUAJ0aCCgFEPoogBEeTCsI3TDLP0XlVd9eot+ePeqqmarurpZnqp7rmfc2aq6tWr9373vdf3/d69v9/3h+fYeA5MBDGVKGEiCAnihI0r0gwVItKeQ7kSEcbQ1+EwNqFGJspxTLceJQhCFVzr6ZGKQqA0Bp7aW5jkCBzT30G/d0AEa9odfcPN3J8dye+ZOisHrX/UsgwfOXczVpKwpjdLzmHy7yx4rhhy71ODk27kHb7DnvGAF/VlGC4EJKgg4yRRN/XtJ67lc/fs4N1nbWRZ1q+NUlTTUquKlJe8fENNcKw6bTJSDPj3e9XUyetPWYdjw28d1YfcM8ZVdzw+yQn59AUn8b4mzolSks1jWxZHL++gO+2yPx/w5L489zy2l+0nrub4NTnypRDLAtdRTnSHr9K5O1IOYRzz+J4819/7LJe87CjSnsOL+zsplCM60w6eYzNcCGoVdJ8dLLB5XTdBCK6tMkpWdqfZOTTR4KB8/HVb2LA8Q1AJsS2XPeMlVnanyWVscmkLJ3IaYiuMU2HaNF8ccU6FEMIBHgdeDewC7gcullI+2uo3B//xVbyIx3aXWNWTxtISfd0Zm7EJKAcxq3I2Y2XoTsFYCQZGSnSlPXqzDh0+hAmMFBM6fAvPg+FCQqDjJjpSFuMTCc8MTrA6l6Y/ZxOG8PxYyLo+l6F8wvJOi7GSChyzrQTbsohiKAZxLT7BsSxsO6FUUSmnlSjCtlRg2P58wPGr0+wejelIKYnriUrC4HiZ5V0etmURhDFrci6jJfBsGJ2I6euzJn2tAAAWA0lEQVS02TsWsabXoVgG34F8WU2v5MsBWd+jw7dxHfBc8PSlta+gVEB7dGC6ar8S++lSUhEUAyiF0JeFXw5McMLaDA5QDqEUoUo9Jwn5IGFNj6OdHLWfkWJMX4fN7pGIShSxOqdGA54fDViV80m7sL+QMFGJ6Mu6TAQJXRmL4UJMLmNTDGLiJCHtOVhAylNtLoWQdmGiAoOFiHU9DpUExooJHSmLtAv5MuwdL5PxPFIe9GVtBgsxb/jXn066SX3jnS+l3z8QrLmQMt3Tlslusn59hkJLh0Q7IZZlNSjKggqwvOzMY5tmVeweVSmRl71qI1/60VNcfeFWBkaK9HWkWNWtnONLb3igtr2/PkcAsKIzxc7hIjf/XNXZqMZp1Ads/uPrt/Derz80qW3XXLR10jTK6lyaT75hC4PakUv5NntGy0r63kroyXg8sbfA53+woybJfvzqblzbojfrUImU+Fp3xiWMYrK+y0ixwlAx4O9vm6xjMVwM+PSFJxFGMQMjJW68fyefvfhkHt9bYO9YqSHItHquPv/GUygEIX95S6PI2EuP6cK3wam8AAdW0443q8PFtGl+OBJlurcBO6SUTwEIIW4EzgNaOhUHMzCshKMKJfUEbVmWFqCKCcKYYFgFFRZKKv6gI+UxWAiIE59K5DBWUk9kxUClaFqWKt41XAgZL9kEYcyKrhSWBbuHIzK+Q6kSsXvYohTGhJFTy/ywLIsoVk/QlTimGCgNilxG6VKAqqjq2haVJGa8FLK8w+c3wxGDeZXJkOjpgVXdahh2b75Eh++xvwDFsiqHPl4OiRKVQprg0+E7jE7EDBcC+rt9fEeJaJVDFTfhOzZhFOPYSuuhJ+NRKKl0UEBlpnSlKQWQ9i2KQUIQxuTLKl7jueHGsEZXpwcMFQJSjlIaxFLLM57NwHDE3vEy/V0phgoxYZzgOi7DBTV9E+hpkMFCBAmUQqUUGoSOGs3J+pR1aq3rqJiL6tSNBVp980CcSyGgFpeS9jwdwGmRL0cMF5sHVw6MBPT3t4cw0UwDQOvXb6a5cHBGSjVr5cOvmZxdsf3EtTWHovr7z9z9REONDNtSsRH78+Xa6ELas7nqgpMatlcd3bjmrl81LL/6+49z6SuPadhHK8VLx25MgV2dS3PJyzfUnJfqzT/rOVx1r6rns3FFJ5//wY5J2Scf2r6JtJvhmrtkLSbj46/bQhiV6M74NYeiatM1d6l2f/MXu7Atix37Ctz24ABve9nR7M8HfPDWh5sew1Il5sFdI7X31dcP3fYrbnjbNrrSDsuWag9uWLQs1UtyLfCbus+7gJfOZAN7xsss61BZBaCGvjtS6knEtS1GJhKWd/pUoqSmK5HxHPaMlSFJ1eShLf2f0qhI8Gw1yuA5Fr2ux3gpIl+O6OvwSevfO7a6kRXLVYcGKpG60VVvvEpNM6Az5ZKQMJgPsG1LFyTzKEUx+8YDerKesgnIZVwqkUMCpF0VbFkt3pXLehQDJY3dm/Vr3w0XA3IZj1Ilqb3fnw9IEujJeOTLKgaiK62cKjhgay6j5LYtYKKi2j+qA0FXdafYlw+I6sQLujMqlqKailo99t0ZlyBSsQvLO5VtuYzL6IRSJ836DgUdKBrHatrDAhzbqtVvyGVUe10dp9Gl95XxHSXCZVms6EqxP1+u2V893lGssko8R6XwhnFCLtO8muXBYkkLydQ6E1Ov30pzod4hqToh+wvlSftx7Oa/t3SGx4e2byKoRKxfluWyrzZqSOxqUlG01fYO1r5opnj57lcdyxf/98kGPYoLTl1Xm1Kpbuuau57g0lcew/YT13LNXU/w4XNPYPuJayc5V1d++1GuOv8k3vyyY/j5s8r2D9z6MF9+y6n89Omhlu1+/SnreHT3GHFCTQxrUDun2VTz6ynScSWTzkM+IEl8lnUtwXozhkXNUnUqZozjWPT0ZGufl42VGdEVM1UHG5EvhTXZZ1BD4o5l0ZFS86auY9Ucg/6uFFgqRoBE3ehc26ISxfS4DlESM1pUKaXdaZd9WmhpWZePa1kMFQO6dEZCQlKLTag+WScJdKVdXMfCsW0ynkMpjCkGIRMViyCKWdmdIiHRrzBcCBjVio8p12Zld4o9Y2WWd/mMFFRbC0FYE52q6j8Ug5BiENOb9dQoSKeqHjpUCOhMK3nsUqhu7qDiKBJtq3Ky1Ii5Zam2pr2qtoSH7x64CQ8XA7K+Q8ZXx7B6rIeKAWMT6thX7R4qKH2Okq4RUnWuUq6jhYYSKmGC64Jj2fpm5lCuxHiuGrbO+o6ug+ITxso5zPoOKVd31BYEev2RYoUwCsllPFKeEjKr6hM0POn6bsN1NJ1rba7ojhM+dcFW3n/zAdnoT12wlRf3qwDBqdaH5poLa3qzNdvXxGrZf9y3k/f+7nENWRsnretp+vtT1vfw9lccw2fv3sHu0RLve/Vxk27C1//kWa54zQm1wM5vPTTAFdtPmJb2xXAxYF1fpqnuRLcuXx4nsDaXaemkVB2qrO+2dGYK5bBB9bRUiRkqKMn6ZnYmdQJYjkrQqjlEac9mYKTI32/fxEfqKh1X65mct3Vtw/7Tnsos2zNe5uT1PZPOYz1TXWtvuvZn3PC2bVP+frHhOPa8/G3NJ4utTUvVqRgA1td9XqeXtSSKkoZ5qw6dKZH2bC15rW6aXRmHMIJlWbBIYdsWNuqp2HEslmUBUnSm1M0tigES/QpxbJPybOLErt2EPdsi5R648al4hZR6So6UU9GdtilHKrCrGCQqaMxWxbaSBDpTFvmyTVdKTZtYliqINl5K6ExblEPw7FTtKV45QDYWSvXTsy1W99jsHXMJY6XwaVspPMciSqArnZDxbLrSDo5t65EAH8+x6fBVBJ+tp3hW52xGSxCEakRC+1XYesQmm7KxrRQpz6Y7bRFoKY60myKKwXNtVnWn6O92KIfgO8ru5Z3qc3fawXVS9GRsxicsOlPugUwRV52vOFE6H7ZtkctYjE3o4FTHwtfqi6AcM8dWdgehku1OeTZxjNIK0ev7jq01Pyx6O2zyJVjTk67dpGxLfU57dsN1tGJF1yGvtblk25rOBi2JFRmXsbGJQ64/WqqwcfmWhvoZ//SGE8k51GzPOQcEsK679xkufeUxHNvfybqeDB+7/dFJWhUf2r6JhIQv//ip2k03iCarYw4XA8YnAq46/yQS4Im943z7oQE++trNDYGM73v1cazKpRu0Ly4/61g+cftjnLN59aQy55+7+wku2vYiPqJVP1s5KZF2lnaPFFs6R0PFgLW92YZlPRmPbz00MMnBqsZUXHjqOv5LT3v06yJ6//XgAFds38S//vBJ3vU7L+bqC7fya52h8vWf7+RNp23QAc2NbUx5Fiu91GFdawm03Vz94dKO8QeHSzu2qdm1VmWpBmq6qEDNs1DOxP3AG6WUj7T6zaSAJg8iojm21LCY+fXzJRzbZrio9DaiOGbzqo6GVL+FDNQ8bOoyUqbK/piUtYIK4LzqTlkLcDx5fS+5jMujz41i2XatNkizgM5q5khP1ucrP3m6ptfQm/V58+lHcdSyLLZl6ampmFzWZ7SoNB6GixX+4uaHGtI5d49O1AIlP3PxyXi2xRN7xunK+A1prtWYimvvfZqLfutFyoaMSylMGqZT3vfq41jZneKGnxzQubjyvM3c+ehznH3CmlpK6qpcmlW5tKovMx5QqoQkWPzL3U9w+Vkb8R2X50YnuOOR3bzjtzfy3EiRTWu7KQYx+8ZK7B0vc/MDv+H9ZwsGhicoBCqjamN/J11ph80rD+9au+ybv+Kzr988SxdLe9CON+DDpR3bdMRlfwAIIf4A+GdUSum1UsqPTbV+0z8+41gYDsHOoYg942qq5uhe/7C1A9qVGXdsLZyNfRMho6UKKc8lX6qo77Iu+4ohu8fLpD0H37Xo9l36OhyeHg6U05bxGC9X6PRdOlIuhXLIWClURfWyLvkg5vmxEqtzGcI4ZjAf6Fgfl1JFxecs71QxI+UwhMSuia8NFytkfIeMZzNequA5Dp5j4TlqRKIv6ysp+4lQTT34LqHWWRkvhSzr9MmXKqQ9l660UrLdny/TmXLpTrtMVCJGiiEZ36Y3qwoA7suXWdOdIkpU0HUUq+mW8XKFrrRXU9Nd1uGzvtdh53BUm1btSjusyB6+ToVxKhYH7dimI9KpmCmLNfWqnW2D9rZvPmw7Yp2KNmGx2g0zt904FYv7fLeiHds0lVPRPqHqBoPBYDAYFjXGqTAYDIYjlHfeNFkozGA4HMz0xwH2Ac8eci2DYWbsB845aJm51gxzgbnWDPNFs2sNME6FwWAwGAyGWcJMfxgMBoPBYJgVjFNhMBgMBoNhVjBOhcFgMBgMhlnBOBUGg8FgMBhmBeNUGAwGg8FgmBWWakGxWUEIcQ5wDUrq+0tSyk/M4b6eAcaBCAillKcKIfqArwMbgGeAC6WUw0IIS9v1B0AReKuU8hd6O28B/k5v9qNSyuv18pcA1wEZ4Hbgcilly9QfIcS1wHZgr5Rys1425/a02sc07fsH4B2oNDqAD0gpb9ff/S3wdn183y2l/J5e3vQcCyGOBm4ElgEPAG+SUgZCiBTwFeAlwCDwR1LKZ1odx6WCEOL9wFXACinl/qnOeTsghPgn4DVAADwJXCKlHNHfNb0W2oX56Hfms297ISxU/zOH7VmP6jdWoirofFFKec1iblMrzEhFC4QQDvA54PeBTcDFQohNc7zbM6WUW6WUp+rPfwPcJaU8FrhLf0bbdKz+dynwBW1zH3AF8FJgG3CFEKJX/+YLqBtu9XdNc4zruK7JOvNhT6t9TMc+gKv1Mdxa51BsAi4CTtC/+bwQwjnEOf6k3tZGYBh1E0K/DuvlV+v1ljS6Qzwb2Fm3uOk5byPuBDZLKU9EFRf8W2h9LSyYlQcxH/3OAvVtM+U6Fqb/mStC4P1Syk3AacC79DFfzG1qinEqWrMN2CGlfEpKGaCeWs+bZxvOA67X768HXlu3/CtSykRKeR/QI4RYDfwecKeUckg/3d8JnKO/65ZS3qc916/UbaspUsofAkMLYE+rfUzHvlacB9wopSxLKZ8GdqDOb9NzrJ8SXgXc0qKtVftuAc7S6y9lrgb+isYapa3OeVsgpbxDShnqj/cB6/T7VtdCuzAf/U479G1TsoD9z1y1Z3d1pEFKOQ78Gli7mNvUCuNUtGYt8Ju6z7v0srkiAe4QQjwghLhUL1sppdyt3z+PGjqbyraplu9qsnymzIc9rfYxXS4TQvxSCHFtnQc/U/uWASN1N6V6+2q/0d+P6vWXJEKI84ABKeXBes7z/fdxOLwN+I5+3+52z4d97X4MWtFu/eELQgixATgZ+ClLpE31mJiK9uEVUsoBIUQ/cKcQ4rH6L3W8QdvIn86HPS9gH18ArkQ5aFcCn0LdUAxTIIT4PrCqyVcfBD6AmvpoO6ayW0p5m17ng6ih5/+cT9sMc0u79YfTRQjRCXwDeI+UckwIUftusbbpYIxT0ZoBYH3d53V62ZwgpRzQr3uFELeihij3CCFWSyl36+GtvYewbQA446DlP9DL1zVZf6bMhz2t9nFIpJR7qu+FEP8GfPsQ9tFi+SBquNHVoxH161e3tUsI4QI5vf6iRUr5u82WCyG2AEcDD+nObx3wCyHENub576MZreyuIoR4KyrY76y6gLUFt/sQzId97X4MWtFu/eGMEEJ4KIfiP6WU39SLF3WbmmGmP1pzP3CsEOJoIYSPCu7677nYkRCiQwjRVX2PejL8ld7fW/RqbwFu0+//G3izEMISQpwGjOohtO8BZwshevXQ/9nA9/R3Y0KI0/T8/5vrtjUT5sOeVvs4JAfN6b8OdQyr27xICJHSWR3HAj+jxTnWN6B7gPNbtLVq3/nA3QsRYT0fSCkfllL2Syk3SCk3oIZUT5FSPk/rc94W6OyGvwLOlVIW675qdS20C/PR78xb3zbLtFt/OG30fr4M/FpK+eml0KZWmJGKFkgpQyHEZaiT6ADXSikfmaPdrQRu1U+DLvBVKeV3hRD3AzcJId6OqjR4oV7/dlSq0Q5UutEl2uYhIcSVqE4D4CNSymqw059xIN3oOxyYY26KEOJrKI94uRBiFyri+BPzYE+rfUzHvjOEEFtR0x/PAH+q7XhECHET8ChqKPxdUspIb6fVOf5r4EYhxEeB/0N1COjXG4QQO1CBZBdNdRyXME3PeRvxWSCFmkoEuE9K+c6proV2YD76nXnu214QC9j/zBUvB94EPCyEeFAv+wCLu01NMVVKDQaDwWAwzApm+sNgMBgMBsOsYJwKg8FgMBgMs4JxKgwGg8FgMMwKxqkwGAwGg8EwKxinwmAwGAwGw6xgUkoNCCGWoYrZgFIojFCVPjei9Of/bKFsMxwZCCHuAT4h6yqGCiHeAwiUANdpwI+llNsXyERDGyOEeC1wK3C8lPKxQ60/Rza8B1V9tHjIlZcwxqkwIKUcBLZCrXx4Xkp51YIaZTjS+BpK86O+DPlFKAErD8iidUcMhiZcDPxYv16xQDa8B/gPlK7EEYtxKgwtEUKcAfyFlHK7djaOBo4BXgS8F/X0+PsoOdjXSCkrQoiXAJ8GOoH9wFvbSWnR0LbcAnxUCOFLKQNddGkN8CNdE+GMBbXO0LboehqvAM4EvoUqB34G8GFgBNgC3AQ8DFyOEod6rZTySX2dXQssR43OXiKl3CmEuA74tpTyFr2PvJSyU2/3H1B922bgAeBPgD9HXa/3CCH2SynPnPuWtycmpsIwE16MKgl+Lsojv0dKuQWYAP5Qa9v/C3C+lPIlqD/Wjy2UsYbFg1YF/BnKSQU1SnHTUpVAN8wq5wHflVI+DgzqBxuAk4B3Asej1CyPk1JuA76EcgJA9VfXSylPRBWd+8w09ncyalRiE+oh6+VSys8AzwFnHskOBRinwjAzviOlrKA8fgf4rl7+MLABNf+9GSWN/CDwdzQWuTEYpqI6BYJ+/doC2mJYPFwM3Kjf36g/A9wvpdwtpSwDTwJ36OXV/grgdOCr+v0NqBGPQ/EzKeUuKWUMPFi3LQNm+sMwM8oAUspYCFGpe4qMUdeSBTwipTx9oQw0LGpuA64WQpwCZKWUDyy0QYb2RgjRhxo93aLLhjuo2j//g+6vNHHd52p/NRUh+qFbCGEDft139duNprGtIwozUmGYTSSwQghxOqhSv0KIExbYJsMiQUqZR1WHvRYzSmGYHucDN0gpj9LVdNcDTwO/Pc3f38uB0bE/Bn6k3z8DVKdRzkUFCx+KcaBrmvtdshinwjBrSCkD1B/5J4UQD6GGBl+2sFYZFhlfQ82F15wKIcSPgJuBs4QQu4QQv7dQxhnajotRqaT1fIMDUyCH4s+BS4QQv0TFXVyul/8b8Du6HzsdKExjW18EvqvTo49YTJVSg8FgMBgMs4IZqTAYDAaDwTArGKfCYDAYDAbDrGCcCoPBYDAYDLOCcSoMBoPBYDDMCsapMBgMBoPBMCsYp8JgMBgMBsOsYJwKg8FgMBgMs4JxKgwGg8FgMMwK/w8Z3WG979hZIQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 540x540 with 12 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "A7qEFYq_pSme",
        "outputId": "b5252e89-1370-44ab-e29f-2acd99a7af48"
      },
      "source": [
        "plt.figure(figsize=(18,5))\n",
        "sns.scatterplot(df[\"Time\"], df[\"V1\"], hue=df[\"Class\"], palette = 'PuRd')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe8a3c55fd0>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "SHQmgS3MpULR",
        "outputId": "e78ab5c4-3125-4efb-d09f-2fae6659ce82"
      },
      "source": [
        "plt.figure(figsize=(18,5))\n",
        "sns.scatterplot(df[\"V1\"], df[\"V2\"], hue=df[\"Class\"], palette = 'magma')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
            "  FutureWarning\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fe8a386e9d0>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "De7rHK2f-BKQ"
      },
      "source": [
        "Looking back at the linearity that I observed in the earlier diagram appears to be consistent, a form of trend for many of the fraudulent cases (pinkish-red), relative to the non-fraudulent ones (purple). There's a chain-together with a hand of them scattered here and there. The consistency between that is indicative of V1 having captured information that can be used to separate class 0 from class 1."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hg6NgPX1pYoz"
      },
      "source": [
        "### **3. Preprocessing**\n",
        "\n",
        "\n",
        "The vector columns are of a much reduced/smaller magnitude compare to their Time and Amount counterparts. This needs to be looked into so as to avoid it affecting our model performance. \n",
        "\n",
        "Let's use StandardScaler library from Scikit-Learn. Then, we will split the data into out X (input) and y (output) sections."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LV5FW_b-CUYN"
      },
      "source": [
        "**Scale & Separate the data**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OL8UfBtnpbMT"
      },
      "source": [
        "import pandas as pd\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "scaler = StandardScaler()\n",
        "\n",
        "X = df.iloc[:, :-1]\n",
        "y = df.Class.values.ravel()\n",
        "\n",
        "X_scaled = scaler.fit_transform(X)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YSFfPjfCplOH"
      },
      "source": [
        "**Train Test Split**\n",
        "\n",
        "For the split data, we use training set to train the model, and the testing set to enforce that the models performance is consistent on never-before-seen data. This helps avoid over-fitting of the model and for generalisation.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5d-gHU3PpgqR",
        "outputId": "797023f3-5dbe-44dc-d749-3af192bbaf9f"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state=42)\n",
        "\n",
        "print(X_train.shape)\n",
        "print(X_test.shape)\n",
        "print(y_train.shape)\n",
        "print(y_test.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(227845, 30)\n",
            "(56962, 30)\n",
            "(227845,)\n",
            "(56962,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GPZ81-ZQpsDE"
      },
      "source": [
        "### **4. Model Development**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "spy6K4ujExCe"
      },
      "source": [
        "Import Tensorflow for our ANN Model dev\n",
        "\n",
        "**Artificial Neural Network using Keras**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wxy8v6Gep9Cz",
        "outputId": "6700e394-1433-48bb-a088-d834a24bc4ca"
      },
      "source": [
        "#Artificial Neural Network using Keras:\n",
        "from tensorflow import keras\n",
        "print(keras.__version__)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JgOLeSrMqGCt",
        "outputId": "44061925-9b1b-4e63-8d6a-a20a7b88febc"
      },
      "source": [
        "model = keras.Sequential(\n",
        "    [\n",
        "        keras.layers.Dense(32, activation=\"relu\", input_shape=(X_train.shape[-1],)),\n",
        "        keras.layers.Dense(128, activation=\"relu\"),\n",
        "        keras.layers.Dropout(0.3),\n",
        "        keras.layers.Dense(256, activation=\"relu\"),\n",
        "        keras.layers.Dropout(0.3),\n",
        "        keras.layers.Dense(1, activation=\"sigmoid\"),\n",
        "    ]\n",
        ")\n",
        "model.summary()\n",
        "\n",
        "#defined by three layers (input for data, hidden layer with their activation function and the output layer)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 32)                992       \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 128)               4224      \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 128)               0         \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 256)               33024     \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 256)               0         \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 1)                 257       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 38,497\n",
            "Trainable params: 38,497\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AMlvTMiKGdfG"
      },
      "source": [
        "We see that four Dense layers surrounds two Dropout layers showing good results. \n",
        "\n",
        "**What is a Dense Layer in ANN?**\n",
        "\n",
        "A Dense layer takes in a number of different arguments in neural networks. Within the scope of this model, it takes in two arguments: **‘128’** which is the *number of units*, and **‘relu’** which is the *activation function*.\n",
        "\n",
        "**Model Summary:** Displays a better good view of the model’s architecture. \n",
        "\n",
        "We also see that the Output shape (middle column) is representative of the layer’s units. We first use 32 (the number of columns in the dataset), then we increase this to 128, then 256, and then sharply shrink this down to 1, which depicts the output of the model.\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4kiS790mHAaE"
      },
      "source": [
        "**Model Build**\n",
        "\n",
        "Let's use a generic Adam optimizer to control the learning rate, and assign the loss as binary crossentropy being a binary dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LscWeSTzqK7M"
      },
      "source": [
        "#build model\n",
        "model.compile(\n",
        "    optimizer=keras.optimizers.Adam(1e-2), \n",
        "    loss=\"binary_crossentropy\", \n",
        "    metrics=[\"accuracy\"]\n",
        ")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rpHRIT-eJjq2"
      },
      "source": [
        "Now that we the model compiled, let's fit the model with the dataset. We will use the training set as input, and assign a batch_size of 2048 which will run with 40 epochs."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jeXDsHBzqO8K",
        "outputId": "04297d6b-6ff9-4305-e875-7caff356872a"
      },
      "source": [
        "history = model.fit(\n",
        "                    X_train,\n",
        "                    y_train,\n",
        "                    batch_size=2048,\n",
        "                    epochs=40,\n",
        "                    verbose=2,\n",
        "                    validation_split = 0.2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/40\n",
            "90/90 - 2s - loss: 0.0258 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 27ms/step\n",
            "Epoch 2/40\n",
            "90/90 - 2s - loss: 0.0140 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 3/40\n",
            "90/90 - 2s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 4/40\n",
            "90/90 - 2s - loss: 0.0128 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 5/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 6/40\n",
            "90/90 - 2s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 7/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 8/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 9/40\n",
            "90/90 - 2s - loss: 0.0133 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 10/40\n",
            "90/90 - 2s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 11/40\n",
            "90/90 - 3s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 28ms/step\n",
            "Epoch 12/40\n",
            "90/90 - 3s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 29ms/step\n",
            "Epoch 13/40\n",
            "90/90 - 3s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 30ms/step\n",
            "Epoch 14/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 27ms/step\n",
            "Epoch 15/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 16/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 17/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 18/40\n",
            "90/90 - 2s - loss: 0.0139 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 19/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 20/40\n",
            "90/90 - 2s - loss: 0.0130 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 21/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 22/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 23/40\n",
            "90/90 - 2s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 24/40\n",
            "90/90 - 2s - loss: 0.0126 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 25/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 26/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 27/40\n",
            "90/90 - 3s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 28ms/step\n",
            "Epoch 28/40\n",
            "90/90 - 3s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 28ms/step\n",
            "Epoch 29/40\n",
            "90/90 - 3s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 3s/epoch - 28ms/step\n",
            "Epoch 30/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 31/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 32/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 33/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 34/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 35/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 36/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 37/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 38/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n",
            "Epoch 39/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 26ms/step\n",
            "Epoch 40/40\n",
            "90/90 - 2s - loss: 0.0125 - accuracy: 0.9983 - val_loss: 0.0136 - val_accuracy: 0.9981 - 2s/epoch - 25ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nzFMYy5DIGV6"
      },
      "source": [
        "Yes, our model trained, we can review the output of the model, call the history’s keys and review the metrics captured. We got a relatively high accuracy, with minimal loss which means the model is working."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o6iNUVzOqR4i",
        "outputId": "71a3e84b-2e3f-4c0d-a177-6137cbbc4c38"
      },
      "source": [
        "history.history.keys()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy'])"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Grc_8FMSqU3C",
        "outputId": "2f75a5a9-6a86-4b82-ca39-88b19208e4a6"
      },
      "source": [
        "results = pd.DataFrame(history.history)\n",
        "results.head(5)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>loss</th>\n",
              "      <th>accuracy</th>\n",
              "      <th>val_loss</th>\n",
              "      <th>val_accuracy</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.025833</td>\n",
              "      <td>0.998294</td>\n",
              "      <td>0.013606</td>\n",
              "      <td>0.998135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.014035</td>\n",
              "      <td>0.998261</td>\n",
              "      <td>0.013598</td>\n",
              "      <td>0.998135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.012589</td>\n",
              "      <td>0.998305</td>\n",
              "      <td>0.013594</td>\n",
              "      <td>0.998135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.012819</td>\n",
              "      <td>0.998288</td>\n",
              "      <td>0.013589</td>\n",
              "      <td>0.998135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.012522</td>\n",
              "      <td>0.998305</td>\n",
              "      <td>0.013587</td>\n",
              "      <td>0.998135</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       loss  accuracy  val_loss  val_accuracy\n",
              "0  0.025833  0.998294  0.013606      0.998135\n",
              "1  0.014035  0.998261  0.013598      0.998135\n",
              "2  0.012589  0.998305  0.013594      0.998135\n",
              "3  0.012819  0.998288  0.013589      0.998135\n",
              "4  0.012522  0.998305  0.013587      0.998135"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IbERZ1rxSEMU",
        "outputId": "310f20bd-cf2f-4c58-ea71-a25de6740dea"
      },
      "source": [
        "score1 = model.evaluate(X_test, y_test)\n",
        "score1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1781/1781 [==============================] - 3s 2ms/step - loss: 0.0127 - accuracy: 0.9983\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.012670069001615047, 0.9982795715332031]"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ezziwSXeSQrG"
      },
      "source": [
        "**Our loss is low and the accuracy(99.8%) us high, it shows our model learned.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 342
        },
        "id": "Xfdcm55FqXfj",
        "outputId": "a326975d-196a-4703-ea2e-5e4a6b67741f"
      },
      "source": [
        "plt.figure(figsize = (15,4))\n",
        "\n",
        "plt.subplot(121)\n",
        "plt.plot(results.index, results.accuracy, label=\"Training Accuracy\", linewidth=4)\n",
        "plt.plot(results.index, results.val_accuracy, label=\"Validation Accuracy\", linewidth=4)\n",
        "plt.xlabel(\"Epochs\", fontsize=16)\n",
        "plt.ylabel(\"Accuracy Score\", fontsize=16)\n",
        "plt.title(\"Training & Validation Accuracy over Epochs\" , fontsize=16)\n",
        "plt.xticks(fontsize=15)\n",
        "plt.yticks(fontsize=15)\n",
        "\n",
        "plt.subplot(122)\n",
        "plt.plot(results.index, results.loss, label=\"Training Loss\", linewidth=4)\n",
        "plt.plot(results.index, results.val_loss, label=\"Validation Loss\", linewidth=4)\n",
        "plt.xlabel(\"Epochs\", fontsize=15)\n",
        "plt.ylabel(\"Accuracy Score\", fontsize=15)\n",
        "plt.title(\"Training and Validation Loss over Epochs\", fontsize=16)\n",
        "plt.xticks(fontsize=16)\n",
        "plt.yticks(fontsize=16)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.01 , 0.012, 0.014, 0.016, 0.018, 0.02 , 0.022, 0.024, 0.026,\n",
              "        0.028]), <a list of 10 Text major ticklabel objects>)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FmD6cnn8NTVK"
      },
      "source": [
        "#### **4. Artificial Neural Network using Keras with Metrics & Weights**:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4rAPBUriqaV6",
        "outputId": "8ef25e7e-ac14-4383-b4ad-e381e957ba89"
      },
      "source": [
        "\n",
        "counts = np.bincount(y_train)\n",
        "wt_0 = 1.0 / counts[0]\n",
        "wt_1 = 1.0 / counts[1]\n",
        "\n",
        "print(wt_0)\n",
        "print(wt_1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4.396551345124884e-06\n",
            "0.0025380710659898475\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uZ37ymr3qi7f",
        "outputId": "6d001887-d6dd-4c4a-99c1-7e88c7c229e1"
      },
      "source": [
        "model_2 = keras.Sequential(\n",
        "    [\n",
        "        keras.layers.Dense(\n",
        "            256, activation=\"relu\", input_shape=(X_train.shape[-1],)\n",
        "        ),\n",
        "        keras.layers.Dense(256, activation=\"relu\"),\n",
        "        keras.layers.Dropout(0.3),\n",
        "        keras.layers.Dense(256, activation=\"relu\"),\n",
        "        keras.layers.Dropout(0.3),\n",
        "        keras.layers.Dense(1, activation=\"sigmoid\"),\n",
        "    ]\n",
        ")\n",
        "model_2.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense_4 (Dense)             (None, 256)               7936      \n",
            "                                                                 \n",
            " dense_5 (Dense)             (None, 256)               65792     \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 256)               0         \n",
            "                                                                 \n",
            " dense_6 (Dense)             (None, 256)               65792     \n",
            "                                                                 \n",
            " dropout_3 (Dropout)         (None, 256)               0         \n",
            "                                                                 \n",
            " dense_7 (Dense)             (None, 1)                 257       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 139,777\n",
            "Trainable params: 139,777\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x9hRMZLoqmQW",
        "outputId": "15492449-1897-4277-f19d-3dfce4cd48cd"
      },
      "source": [
        "\n",
        "metrics = [\n",
        "    keras.metrics.Precision(name=\"precision\"),\n",
        "#     keras.metrics.Recall(name=\"recall\"),\n",
        "#     keras.metrics.Accuracy(name=\"accuracy\")\n",
        "]\n",
        "\n",
        "model_2.compile(\n",
        "    optimizer=keras.optimizers.Adam(1e-2), loss=\"binary_crossentropy\", metrics=metrics\n",
        ")\n",
        "\n",
        "\n",
        "\n",
        "history = model_2.fit(\n",
        "                    X_train,\n",
        "                    y_train,\n",
        "                    batch_size=2048,\n",
        "                    epochs=30,\n",
        "                    verbose=2,\n",
        "                    validation_split = 0.2,\n",
        "                    class_weight = {0: wt_0, 1: wt_1}\n",
        ")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/30\n",
            "90/90 - 6s - loss: 0.0086 - precision: 0.0017 - val_loss: 0.6985 - val_precision: 0.0019 - 6s/epoch - 65ms/step\n",
            "Epoch 2/30\n",
            "90/90 - 5s - loss: 1.2919e-05 - precision: 0.0018 - val_loss: 0.6552 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 3/30\n",
            "90/90 - 5s - loss: 6.1847e-06 - precision: 0.0022 - val_loss: 0.6718 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 4/30\n",
            "90/90 - 5s - loss: 6.0314e-06 - precision: 0.0015 - val_loss: 0.6954 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 5/30\n",
            "90/90 - 5s - loss: 6.0707e-06 - precision: 0.0026 - val_loss: 0.6921 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 6/30\n",
            "90/90 - 5s - loss: 6.0209e-06 - precision: 0.0015 - val_loss: 0.6934 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 7/30\n",
            "90/90 - 5s - loss: 6.0308e-06 - precision: 0.0037 - val_loss: 0.6797 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 8/30\n",
            "90/90 - 5s - loss: 6.0236e-06 - precision: 0.0161 - val_loss: 0.6865 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 9/30\n",
            "90/90 - 5s - loss: 6.0380e-06 - precision: 0.0000e+00 - val_loss: 0.6852 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 10/30\n",
            "90/90 - 5s - loss: 6.0262e-06 - precision: 0.0013 - val_loss: 0.6704 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 11/30\n",
            "90/90 - 5s - loss: 6.0287e-06 - precision: 0.0000e+00 - val_loss: 0.6867 - val_precision: 0.0000e+00 - 5s/epoch - 53ms/step\n",
            "Epoch 12/30\n",
            "90/90 - 5s - loss: 6.0251e-06 - precision: 0.0093 - val_loss: 0.6759 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 13/30\n",
            "90/90 - 5s - loss: 6.0282e-06 - precision: 0.0027 - val_loss: 0.6765 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 14/30\n",
            "90/90 - 5s - loss: 6.0258e-06 - precision: 0.0102 - val_loss: 0.6734 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 15/30\n",
            "90/90 - 5s - loss: 6.0221e-06 - precision: 0.0099 - val_loss: 0.6726 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 16/30\n",
            "90/90 - 5s - loss: 6.0227e-06 - precision: 0.0014 - val_loss: 0.6867 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 17/30\n",
            "90/90 - 5s - loss: 6.0267e-06 - precision: 0.0014 - val_loss: 0.6840 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 18/30\n",
            "90/90 - 5s - loss: 6.0203e-06 - precision: 0.0036 - val_loss: 0.6873 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 19/30\n",
            "90/90 - 5s - loss: 6.0197e-06 - precision: 0.0017 - val_loss: 0.6755 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 20/30\n",
            "90/90 - 5s - loss: 6.0209e-06 - precision: 0.0015 - val_loss: 0.6670 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 21/30\n",
            "90/90 - 5s - loss: 6.0336e-06 - precision: 0.0015 - val_loss: 0.6667 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 22/30\n",
            "90/90 - 5s - loss: 6.0251e-06 - precision: 0.0015 - val_loss: 0.6911 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 23/30\n",
            "90/90 - 5s - loss: 6.0237e-06 - precision: 0.0036 - val_loss: 0.6776 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 24/30\n",
            "90/90 - 5s - loss: 6.1251e-06 - precision: 0.0015 - val_loss: 0.6884 - val_precision: 0.0000e+00 - 5s/epoch - 52ms/step\n",
            "Epoch 25/30\n",
            "90/90 - 5s - loss: 6.0244e-06 - precision: 0.0014 - val_loss: 0.6948 - val_precision: 0.0019 - 5s/epoch - 52ms/step\n",
            "Epoch 26/30\n",
            "90/90 - 5s - loss: 6.0248e-06 - precision: 0.0016 - val_loss: 0.6914 - val_precision: 0.0000e+00 - 5s/epoch - 51ms/step\n",
            "Epoch 27/30\n",
            "90/90 - 5s - loss: 6.0300e-06 - precision: 0.0016 - val_loss: 0.6955 - val_precision: 0.0019 - 5s/epoch - 51ms/step\n",
            "Epoch 28/30\n",
            "90/90 - 5s - loss: 6.0368e-06 - precision: 0.0013 - val_loss: 0.7016 - val_precision: 0.0019 - 5s/epoch - 51ms/step\n",
            "Epoch 29/30\n",
            "90/90 - 5s - loss: 6.0977e-06 - precision: 0.0017 - val_loss: 0.8162 - val_precision: 0.0019 - 5s/epoch - 51ms/step\n",
            "Epoch 30/30\n",
            "90/90 - 5s - loss: 6.0759e-06 - precision: 0.0017 - val_loss: 0.7863 - val_precision: 0.0019 - 5s/epoch - 51ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H0W2gsYmqpRN",
        "outputId": "daed4a9a-332d-4a50-a286-d47a9d8127fd"
      },
      "source": [
        "score = model_2.evaluate(X_test, y_test)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1781/1781 [==============================] - 3s 2ms/step - loss: 0.7859 - precision: 0.0017\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RGaDA0HrQv-w",
        "outputId": "f277d0aa-0bdc-47dd-a913-f329683a858e"
      },
      "source": [
        "score"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.785880446434021, 0.001720717060379684]"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5dpAljnlRQld"
      },
      "source": [
        "The loss here is high and precision is low"
      ]
    }
  ]
}