Springboard_Decision_Tree_Specialty_Coffee_Case_Study_Tier_1.ipynb

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        "<a href=\"https://colab.research.google.com/github/neetinds/Springboard/blob/master/Springboard_Decision_Tree_Specialty_Coffee_Case_Study_Tier_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-iuRLRs_27ki"
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      "source": [
        "# **Springboard Decision Tree Specialty Coffee Case Study - Tier 1**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JqX4KRR327kl"
      },
      "source": [
        "# The Scenario\n",
        "\n",
        "Imagine you've just finished the Springboard Data Science Career Track course, and have been hired by a rising popular specialty coffee company - RR Diner Coffee - as a data scientist. Congratulations!\n",
        "\n",
        "RR Diner Coffee sells two types of thing:\n",
        "- specialty coffee beans, in bulk (by the kilogram only) \n",
        "- coffee equipment and merchandise (grinders, brewing equipment, mugs, books, t-shirts).\n",
        "\n",
        "RR Diner Coffee has three stores, two in Europe and one in the USA. The flagshap store is in the USA, and everything is quality assessed there, before being shipped out. Customers further away from the USA flagship store have higher shipping charges. \n",
        "\n",
        "You've been taken on at RR Diner Coffee because the company are turning towards using data science and machine learning to systematically make decisions about which coffee farmers they should strike deals with. \n",
        "\n",
        "RR Diner Coffee typically buys coffee from farmers, processes it on site, brings it back to the USA, roasts it, packages it, markets it, and ships it (only in bulk, and after quality assurance) to customers internationally. These customers all own coffee shops in major cities like New York, Paris, London, Hong Kong, Tokyo, and Berlin. \n",
        "\n",
        "Now, RR Diner Coffee has a decision about whether to strike a deal with a legendary coffee farm (known as the **Hidden Farm**) in rural China: there are rumours their coffee tastes of lychee and dark chocolate, while also being as sweet as apple juice. \n",
        "\n",
        "It's a risky decision, as the deal will be expensive, and the coffee might not be bought by customers. The stakes are high: times are tough, stocks are low, farmers are reverting to old deals with the larger enterprises and the publicity of selling *Hidden Farm* coffee could save the RR Diner Coffee business. \n",
        "\n",
        "Your first job, then, is ***to build a decision tree to predict how many units of the Hidden Farm Chinese coffee will be purchased by RR Diner Coffee's most loyal customers.*** \n",
        "\n",
        "To this end, you and your team have conducted a survey of 710 of the most loyal RR Diner Coffee customers, collecting data on the customers':\n",
        "- age\n",
        "- gender \n",
        "- salary \n",
        "- whether they have bought at least one RR Diner Coffee product online\n",
        "- their distance from the flagship store in the USA (standardized to a number between 0 and 11) \n",
        "- how much they spent on RR Diner Coffee products on the week of the survey \n",
        "- how much they spent on RR Diner Coffee products in the month preeding the survey\n",
        "- the number of RR Diner coffee bean shipments each customer has ordered over the preceding year. \n",
        "\n",
        "You also asked each customer participating in the survey whether they would buy the Hidden Farm coffee, and some (but not all) of the customers gave responses to that question. \n",
        "\n",
        "You sit back and think: if more than 70% of the interviewed customers are likely to buy the Hidden Farm coffee, you will strike the deal with the local Hidden Farm farmers and sell the coffee. Otherwise, you won't strike the deal and the Hidden Farm coffee will remain in legends only. There's some doubt in your mind about whether 70% is a reasonable threshold, but it'll do for the moment. \n",
        "\n",
        "To solve the problem, then, you will build a decision tree to implement a classification solution. \n",
        "\n",
        "\n",
        "-------------------------------\n",
        "As ever, this notebook is **tiered**, meaning you can elect that tier that is right for your confidence and skill level. There are 3 tiers, with tier 1 being the easiest and tier 3 being the hardest. This is ***tier 1***, so a gentle introduction to classification models using decision trees. \n",
        "\n",
        "**1. Sourcing and loading** \n",
        "- Import packages\n",
        "- Load data\n",
        "- Explore the data\n",
        "\n",
        " \n",
        "**2. Cleaning, transforming and visualizing**\n",
        "- Cleaning the data\n",
        "- Train/test split\n",
        "  \n",
        "  \n",
        "**3. Modelling** \n",
        "- Model 1: Entropy model - no max_depth\n",
        "- Model 2: Gini impurity model - no max_depth\n",
        "- Model 3: Entropy model - max depth 3\n",
        "- Model 4: Gini impurity model - max depth 3\n",
        "\n",
        "\n",
        "**4. Evaluating and concluding** \n",
        "- How many customers will buy Hidden Farm coffee?\n",
        "- Decision\n",
        "\n",
        "**5. Random Forest** \n",
        "- Import necessary modules\n",
        "- Model\n",
        "- Revise conclusion\n",
        "    "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3zTlwi4M27km"
      },
      "source": [
        "# 0. Overview\n",
        "\n",
        "This notebook uses decision trees to determine whether the factors of salary, gender, age, how much money the customer spent last week and during the preceding month on RR Diner Coffee products, how many kilogram coffee bags the customer bought over the last year, whether they have bought at least one RR Diner Coffee product online, and their distance from the flagship store in the USA, could predict whether customers would purchase the Hidden Farm coffee if a deal with its farmers were struck. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XekYMG6ylfO6",
        "outputId": "364381de-e19b-4b3f-9f93-697c470663ff"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GuKgPSPS27ko"
      },
      "source": [
        "# 1. Sourcing and loading\n",
        "## 1a. Import Packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GsP21kkU27kq"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn import tree, metrics\n",
        "from sklearn.model_selection import train_test_split\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from io import StringIO  \n",
        "from IPython.display import Image  \n",
        "import pydotplus"
      ],
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eLV5cfvy27kx"
      },
      "source": [
        "## 1b. Load data "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "iaAFg7J127kx",
        "outputId": "43ac2c9f-85d7-4e76-a253-59f5a3595d37"
      },
      "source": [
        "# Read in the data to a variable called coffeeData\n",
        "coffee = pd.read_csv(\"/content/gdrive/MyDrive/Springboard-master/Decision_Tree_Specialty_Coffee_Case_Study/data/RRDinerCoffeeData.csv\")\n",
        "coffee.head()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_week</th>\n",
              "      <th>spent_month</th>\n",
              "      <th>SlrAY</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>Decision</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>36</td>\n",
              "      <td>Female</td>\n",
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              "      <td>24</td>\n",
              "      <td>73</td>\n",
              "      <td>42789</td>\n",
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              "      <td>20</td>\n",
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              "      <td>30</td>\n",
              "      <td>107</td>\n",
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              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>36</td>\n",
              "      <td>14244</td>\n",
              "      <td>0.965881</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Gender  num_coffeeBags_per_year  ...  Distance  Online  Decision\n",
              "0   36  Female                        0  ...  0.003168       0       1.0\n",
              "1   24    Male                        0  ...  0.520906       0       NaN\n",
              "2   24    Male                        0  ...  0.916005       1       1.0\n",
              "3   20    Male                        0  ...  0.932098       1       NaN\n",
              "4   24  Female                        0  ...  0.965881       0       1.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tJJHzGb127k1"
      },
      "source": [
        "## 1c. Explore the data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8B-HKvF627k1"
      },
      "source": [
        "As we've seen, exploration entails doing things like checking out the **initial appearance** of the data with head(), the **dimensions** of our data with .shape, the **data types** of the variables with .info(), the **number of non-null values**, how much **memory** is being used to store the data, and finally the major summary statistcs capturing **central tendancy, dispersion and the null-excluding shape of the dataset's distribution**. \n",
        "\n",
        "How much of this can you do yourself by this point in the course? Have a real go. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "5JmlDkE027k2",
        "outputId": "02273ed7-ce21-453f-d90e-8c247d0d13bd"
      },
      "source": [
        "# Call head() on your data \n",
        "coffee.head(8)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_week</th>\n",
              "      <th>spent_month</th>\n",
              "      <th>SlrAY</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>Decision</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>36</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>24</td>\n",
              "      <td>73</td>\n",
              "      <td>42789</td>\n",
              "      <td>0.003168</td>\n",
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              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>24</td>\n",
              "      <td>Male</td>\n",
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              "      <td>164</td>\n",
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              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>24</td>\n",
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              "      <td>39</td>\n",
              "      <td>119</td>\n",
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              "      <td>1.0</td>\n",
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              "      <th>3</th>\n",
              "      <td>20</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>107</td>\n",
              "      <td>13166</td>\n",
              "      <td>0.932098</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>36</td>\n",
              "      <td>14244</td>\n",
              "      <td>0.965881</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>20</td>\n",
              "      <td>female</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>14293</td>\n",
              "      <td>1.036346</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>34</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>55</td>\n",
              "      <td>202</td>\n",
              "      <td>91035</td>\n",
              "      <td>1.134851</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>24</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>34</td>\n",
              "      <td>17425</td>\n",
              "      <td>1.193188</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Age  Gender  num_coffeeBags_per_year  ...  Distance  Online  Decision\n",
              "0   36  Female                        0  ...  0.003168       0       1.0\n",
              "1   24    Male                        0  ...  0.520906       0       NaN\n",
              "2   24    Male                        0  ...  0.916005       1       1.0\n",
              "3   20    Male                        0  ...  0.932098       1       NaN\n",
              "4   24  Female                        0  ...  0.965881       0       1.0\n",
              "5   20  female                        0  ...  1.036346       1       1.0\n",
              "6   34  Female                        0  ...  1.134851       0       1.0\n",
              "7   24  Female                        0  ...  1.193188       0       NaN\n",
              "\n",
              "[8 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XBGDWgCR27k6",
        "outputId": "d37bf6dd-0fd7-43f1-a6ca-3b451cb80f76"
      },
      "source": [
        "# Call .shape on your data\n",
        "coffee.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(702, 9)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UZH6lJWU27k8",
        "outputId": "49c23ee0-259b-4e9d-aea2-51bfbe7fa9ee"
      },
      "source": [
        "# Call info() on your data\n",
        "coffee.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 702 entries, 0 to 701\n",
            "Data columns (total 9 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   Age                      702 non-null    int64  \n",
            " 1   Gender                   702 non-null    object \n",
            " 2   num_coffeeBags_per_year  702 non-null    int64  \n",
            " 3   spent_week               702 non-null    int64  \n",
            " 4   spent_month              702 non-null    int64  \n",
            " 5   SlrAY                    702 non-null    int64  \n",
            " 6   Distance                 702 non-null    float64\n",
            " 7   Online                   702 non-null    int64  \n",
            " 8   Decision                 474 non-null    float64\n",
            "dtypes: float64(2), int64(6), object(1)\n",
            "memory usage: 49.5+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "jqSVLUm327k_",
        "outputId": "7044913e-067f-46e0-edbe-7f2fb72164b6"
      },
      "source": [
        "# Call describe() on your data with the parameter include = 'all' to get the relevant summary statistics for your data \n",
        "coffee.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>Age</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_week</th>\n",
              "      <th>spent_month</th>\n",
              "      <th>SlrAY</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>Decision</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>702.000000</td>\n",
              "      <td>474.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>34.243590</td>\n",
              "      <td>2.710826</td>\n",
              "      <td>32.853276</td>\n",
              "      <td>107.923077</td>\n",
              "      <td>43819.843305</td>\n",
              "      <td>4.559186</td>\n",
              "      <td>0.531339</td>\n",
              "      <td>0.639241</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>13.927945</td>\n",
              "      <td>1.593629</td>\n",
              "      <td>15.731878</td>\n",
              "      <td>55.348485</td>\n",
              "      <td>26192.626943</td>\n",
              "      <td>3.116275</td>\n",
              "      <td>0.499373</td>\n",
              "      <td>0.480728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>16.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1617.000000</td>\n",
              "      <td>0.003168</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>23.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>24.250000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>22812.250000</td>\n",
              "      <td>1.877812</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>28.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>113.500000</td>\n",
              "      <td>41975.000000</td>\n",
              "      <td>4.196167</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>46.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>150.750000</td>\n",
              "      <td>60223.000000</td>\n",
              "      <td>6.712022</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>90.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>210.000000</td>\n",
              "      <td>182058.000000</td>\n",
              "      <td>10.986203</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Age  num_coffeeBags_per_year  ...      Online    Decision\n",
              "count  702.000000               702.000000  ...  702.000000  474.000000\n",
              "mean    34.243590                 2.710826  ...    0.531339    0.639241\n",
              "std     13.927945                 1.593629  ...    0.499373    0.480728\n",
              "min     16.000000                 0.000000  ...    0.000000    0.000000\n",
              "25%     23.000000                 1.000000  ...    0.000000    0.000000\n",
              "50%     28.000000                 3.000000  ...    1.000000    1.000000\n",
              "75%     46.000000                 4.000000  ...    1.000000    1.000000\n",
              "max     90.000000                 5.000000  ...    1.000000    1.000000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IKleHghD27lC"
      },
      "source": [
        "# 2. Cleaning, transforming and visualizing\n",
        "## 2a. Cleaning the data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rrXQN3jK27lF"
      },
      "source": [
        "Some datasets don't require any cleaning, but almost all do. This one does. We need to replace '1.0' and '0.0' in the 'Decision' column by 'YES' and 'NO' respectively, clean up the values of the 'gender' column, and change the column names to words which maximize meaning and clarity. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HZVP2hxf27lG"
      },
      "source": [
        "First, let's change the name of `spent_week`, `spent_month`, and `SlrAY` to `spent_last_week` and `spent_last_month` and `salary` respectively."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iiR6dxn427lH",
        "outputId": "6f18543d-f98e-4fb7-b593-43793f92e710"
      },
      "source": [
        "# Call .columns on your data to check out the names of our data's columns \n",
        "coffee.columns"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Age', 'Gender', 'num_coffeeBags_per_year', 'spent_week', 'spent_month',\n",
              "       'SlrAY', 'Distance', 'Online', 'Decision'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AcGZ5jU527lK"
      },
      "source": [
        "# Using .rename(), make the relevant name changes to spent_week and spent_per_week.\n",
        "# Remember: you can either do a reassignment, or use inplace=True. Both will change the value of coffeeData\n",
        "coffee.rename(columns = {\"spent_month\":\"spent_last_month\", \"spent_week\":\"spent_last_week\", \"SlrAY\":\"Salary\"},\n",
        "            inplace = True)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V4CHOpkA27lM",
        "outputId": "0f2b6ab4-5233-43c3-f68e-961ee4f9b4f3"
      },
      "source": [
        "# Check out the column names\n",
        "coffee.columns"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Age', 'Gender', 'num_coffeeBags_per_year', 'spent_last_week',\n",
              "       'spent_last_month', 'Salary', 'Distance', 'Online', 'Decision'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6XuI18FV27lQ",
        "outputId": "155c5685-e4d8-41f0-a5b2-85b3896090d6"
      },
      "source": [
        "# Let's have a closer look at the gender column. Its values need cleaning.\n",
        "# Call describe() on the gender column \n",
        "coffee[\"Gender\"].describe()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count      702\n",
              "unique       9\n",
              "top       Male\n",
              "freq       355\n",
              "Name: Gender, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZPe4W_pM27lU",
        "outputId": "b9ef2ca0-a167-4571-b295-c0780dbf78a0"
      },
      "source": [
        "# Call unique() on the gender column to see its unique values \n",
        "coffee[\"Gender\"].unique()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Female', 'Male', 'female', 'F', 'f ', 'FEMALE', 'MALE', 'male',\n",
              "       'M'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NwEMG7MB27lY"
      },
      "source": [
        "We can see a bunch of inconsistency here.\n",
        "\n",
        "Use replace() to make the values of the `gender` column just `Female` and `Male`."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "II50etW127lZ"
      },
      "source": [
        "# Use the function .replace() on the column \"gender\"; replace all alternate values with 'Female'\n",
        "\n",
        "coffee['Gender'] = coffee['Gender'].replace(['female', 'F', 'f ', 'FEMALE'], 'Female')"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5N3wcWjO27lb",
        "outputId": "4be1bc8e-2b2d-4321-a2a4-4fcb23d30240"
      },
      "source": [
        "# Let's check the unique values of the column \"gender\"\n",
        "coffee[\"Gender\"].unique()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Female', 'Male', 'MALE', 'male', 'M'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nlpMhrAR27le"
      },
      "source": [
        "# Use the function .replace() on the column \"gender\"; replace all alternate values with \"Male\"\n",
        "#coffeeData[\"Gender\"] = _ _ _._ _ _([\"MALE\", \"male\", \"M\"], \"_ _ _\")\n",
        "\n",
        "coffee['Gender'] = coffee['Gender'].replace(['Male', 'MALE', 'male', 'M'], 'Male')\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nAoMxGNb27lh",
        "outputId": "6549a6c1-eb4b-4ad4-df16-e133c2041111"
      },
      "source": [
        "# Let's check the unique values of the column \"gender\"\n",
        "coffee[\"Gender\"].unique()\n",
        "#coffee[\"Gender\"] = pd.to_numeric(coffee[\"Gender\"], downcast=\"float\")\n",
        "coffee['gender_factor'] = coffee['Gender'].astype('category').cat.codes\n",
        "coffee.info()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 702 entries, 0 to 701\n",
            "Data columns (total 10 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   Age                      702 non-null    int64  \n",
            " 1   Gender                   702 non-null    object \n",
            " 2   num_coffeeBags_per_year  702 non-null    int64  \n",
            " 3   spent_last_week          702 non-null    int64  \n",
            " 4   spent_last_month         702 non-null    int64  \n",
            " 5   Salary                   702 non-null    int64  \n",
            " 6   Distance                 702 non-null    float64\n",
            " 7   Online                   702 non-null    int64  \n",
            " 8   Decision                 474 non-null    float64\n",
            " 9   gender_factor            702 non-null    int8   \n",
            "dtypes: float64(2), int64(6), int8(1), object(1)\n",
            "memory usage: 50.2+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VOurxC7n27lj",
        "outputId": "86384802-92d3-4be8-f357-b574093fd231"
      },
      "source": [
        "# Check out the unique values of the column 'Decision':\n",
        "coffee['Decision'].unique()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1., nan,  0.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "13DjAqVR27lm"
      },
      "source": [
        "We now want to replace `1.0` and `0.0` in the `Decision` column by `YES` and `NO` respectively."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PZH3aTEt27lm",
        "outputId": "6d505ed6-20f3-4a17-c5fb-802bdc0cd253"
      },
      "source": [
        "# Call replace() on the Decision column to replace 1.0 and 0.0 by 'Yes' and 'No'\n",
        "coffee['Decision'] = coffee['Decision'].replace(1.0, 'YES')\n",
        "coffee['Decision'] = coffee['Decision'].replace(0.0, 'NO')\n",
        "coffee.info()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 702 entries, 0 to 701\n",
            "Data columns (total 10 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   Age                      702 non-null    int64  \n",
            " 1   Gender                   702 non-null    object \n",
            " 2   num_coffeeBags_per_year  702 non-null    int64  \n",
            " 3   spent_last_week          702 non-null    int64  \n",
            " 4   spent_last_month         702 non-null    int64  \n",
            " 5   Salary                   702 non-null    int64  \n",
            " 6   Distance                 702 non-null    float64\n",
            " 7   Online                   702 non-null    int64  \n",
            " 8   Decision                 474 non-null    object \n",
            " 9   gender_factor            702 non-null    int8   \n",
            "dtypes: float64(1), int64(6), int8(1), object(2)\n",
            "memory usage: 50.2+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EfyWNmGu27lt",
        "outputId": "7d46dcc3-6958-4c9a-f08e-814425ea33e8"
      },
      "source": [
        "# Check that our replacing those values with 'YES' and 'NO' worked, with unique()\n",
        "coffee[\"Decision\"].unique()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['YES', nan, 'NO'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uSpkk4Er27ly"
      },
      "source": [
        "## 2b. Train/test split\n",
        "To execute the train/test split properly, we need to do five things: \n",
        "1. Drop all rows with a null value in the `Decision` column, and save the result as NOPrediction: a dataset that will contain all known values for the decision \n",
        "2. Visualize the data using scatter and boxplots of several variables in the y-axis and the decision on the x-axis\n",
        "3. Get the subset of coffeeData with null values in the `Decision` column, and save that subset as Prediction\n",
        "4. Divide the NOPrediction subset into X and y, and then further divide those subsets into train and test subsets for X and y respectively\n",
        "5. Create dummy variables to deal with categorical inputs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UuNUdVC027ly"
      },
      "source": [
        "### 1. Drop all null values within the `Decision` column, and save the result as NoPrediction"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "kYEjdjQi27lz",
        "outputId": "f4999236-dc1b-4ad1-b4af-e5a07962c549"
      },
      "source": [
        "# NoPrediction will contain all known values for the decision\n",
        "# Call dropna() on coffeeData, and store the result in a variable NOPrediction \n",
        "# Call describe() on the Decision column of NoPrediction after calling dropna() on coffeeData\n",
        "NOPrediction = coffee.dropna()\n",
        "NOPrediction['Decision'].describe()\n",
        "NOPrediction.describe()"
      ],
      "execution_count": 18,
      "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>Age</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_last_week</th>\n",
              "      <th>spent_last_month</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>gender_factor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>474.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>35.417722</td>\n",
              "      <td>2.590717</td>\n",
              "      <td>32.592827</td>\n",
              "      <td>106.727848</td>\n",
              "      <td>44731.892405</td>\n",
              "      <td>5.102898</td>\n",
              "      <td>0.512658</td>\n",
              "      <td>0.491561</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>13.604135</td>\n",
              "      <td>1.585211</td>\n",
              "      <td>15.758109</td>\n",
              "      <td>56.101085</td>\n",
              "      <td>25567.674430</td>\n",
              "      <td>3.354891</td>\n",
              "      <td>0.500368</td>\n",
              "      <td>0.500457</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>16.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3150.000000</td>\n",
              "      <td>0.003168</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>27284.250000</td>\n",
              "      <td>2.077965</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>29.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>113.500000</td>\n",
              "      <td>42791.500000</td>\n",
              "      <td>4.832168</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>49.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>61621.750000</td>\n",
              "      <td>7.869086</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>90.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>210.000000</td>\n",
              "      <td>172658.000000</td>\n",
              "      <td>10.986203</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Age  num_coffeeBags_per_year  ...      Online  gender_factor\n",
              "count  474.000000               474.000000  ...  474.000000     474.000000\n",
              "mean    35.417722                 2.590717  ...    0.512658       0.491561\n",
              "std     13.604135                 1.585211  ...    0.500368       0.500457\n",
              "min     16.000000                 0.000000  ...    0.000000       0.000000\n",
              "25%     25.000000                 1.000000  ...    0.000000       0.000000\n",
              "50%     29.000000                 3.000000  ...    1.000000       0.000000\n",
              "75%     49.000000                 4.000000  ...    1.000000       1.000000\n",
              "max     90.000000                 5.000000  ...    1.000000       1.000000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3pppAJIZ27l1"
      },
      "source": [
        "### 2. Visualize the data using scatter and boxplots of several variables in the y-axis and the decision on the x-axis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "GpJlIyNU27l2",
        "outputId": "4d4b4eab-7217-4f9e-caa2-9683d5c1cb3b"
      },
      "source": [
        "# Exploring our new NOPrediction dataset\n",
        "# Call boxplot() on our Seaborn object sns, and plug y=\"spent_today\", x= \"Decision\", data=NOPrediction\n",
        "# Don't forget to call plt.slow() after that \n",
        "sns.boxplot(y=\"spent_last_week\", x= \"Decision\", data=NOPrediction)\n",
        "plt.show()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LcmUXn78bjR3"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ulje1R9b27l4"
      },
      "source": [
        "Can you admissibly conclude anything from this boxplot? Write your answer here:\n",
        "\n",
        "\n",
        "*   People who decided to buy coffee (Decision - \"YES\") spent more than the ones who didn't buy (Decision - \"NO\") over the course of the survey period of 1 month\n",
        "\n",
        "*  The median spend of people who decided not to buy over the last week was on relatively higher over the last week than the preceeding 3 weeks of survey period\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "HWrGiTkW27l5",
        "outputId": "965df531-0519-4d70-f5ac-67b1dc415e7d"
      },
      "source": [
        "# Call scatterplot() on our Seaborn object sns, and plug in y=\"spent_last_month\", x= \"distance\", hue = \"Decision\", data =NOPrediction.\n",
        "sns.scatterplot(y=\"spent_last_month\", x= \"Distance\", hue = \"Decision\", data =NOPrediction)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f563875b350>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JRNoE4Tb27l8"
      },
      "source": [
        "Can you admissibly conclude anything from this scatterplot? Remember: we are trying to build a tree to classify unseen examples. Write your answer here:\n",
        "\n",
        "\n",
        "\n",
        "*  The decision boundary is smooth and there is a clear demarcation between 'YES' and 'NO' decisions of surveyed people\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XL6yGmQY27l8"
      },
      "source": [
        "### 3. Get the subset of coffeeData with null values in the Decision column, and save that subset as Prediction"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "EO9pctLS27l9",
        "outputId": "3ce81e45-638b-4ba1-f767-01042415dbdc"
      },
      "source": [
        "# Get just those rows whose value for the Decision column is null. There are lots of ways to do this.\n",
        "# One way is to subset on pd.isnull(data['Decision']). Use square brackets, and plug that in as parameter.\n",
        "# Store the result in a variable called Prediction \n",
        "# Call a head() on the result to see it's worked out alright \n",
        "Prediction = coffee[pd.isnull(coffee['Decision'])]\n",
        "Prediction.head()"
      ],
      "execution_count": 21,
      "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>Age</th>\n",
              "      <th>Gender</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_last_week</th>\n",
              "      <th>spent_last_month</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>Decision</th>\n",
              "      <th>gender_factor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>24</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>44</td>\n",
              "      <td>164</td>\n",
              "      <td>74035</td>\n",
              "      <td>0.520906</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20</td>\n",
              "      <td>Male</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>107</td>\n",
              "      <td>13166</td>\n",
              "      <td>0.932098</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>24</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "      <td>34</td>\n",
              "      <td>17425</td>\n",
              "      <td>1.193188</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>24</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "      <td>153</td>\n",
              "      <td>84803</td>\n",
              "      <td>1.655096</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>21</td>\n",
              "      <td>Female</td>\n",
              "      <td>0</td>\n",
              "      <td>38</td>\n",
              "      <td>122</td>\n",
              "      <td>42338</td>\n",
              "      <td>1.714179</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Age  Gender  num_coffeeBags_per_year  ...  Online  Decision  gender_factor\n",
              "1    24    Male                        0  ...       0       NaN              1\n",
              "3    20    Male                        0  ...       1       NaN              1\n",
              "7    24  Female                        0  ...       0       NaN              0\n",
              "11   24  Female                        0  ...       1       NaN              0\n",
              "12   21  Female                        0  ...       1       NaN              0\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "LAEU5mem27l_",
        "outputId": "d69691d7-7bdd-4106-887d-158aa0b5b5bf"
      },
      "source": [
        "# Call describe() on Prediction\n",
        "Prediction.describe()"
      ],
      "execution_count": 22,
      "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>Age</th>\n",
              "      <th>num_coffeeBags_per_year</th>\n",
              "      <th>spent_last_week</th>\n",
              "      <th>spent_last_month</th>\n",
              "      <th>Salary</th>\n",
              "      <th>Distance</th>\n",
              "      <th>Online</th>\n",
              "      <th>gender_factor</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "      <td>228.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>31.802632</td>\n",
              "      <td>2.960526</td>\n",
              "      <td>33.394737</td>\n",
              "      <td>110.407895</td>\n",
              "      <td>41923.741228</td>\n",
              "      <td>3.428836</td>\n",
              "      <td>0.570175</td>\n",
              "      <td>0.548246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>14.302293</td>\n",
              "      <td>1.585514</td>\n",
              "      <td>15.697930</td>\n",
              "      <td>53.786536</td>\n",
              "      <td>27406.768360</td>\n",
              "      <td>2.153102</td>\n",
              "      <td>0.496140</td>\n",
              "      <td>0.498762</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>16.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1617.000000</td>\n",
              "      <td>0.010048</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>22.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>25.750000</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>15911.500000</td>\n",
              "      <td>1.699408</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>25.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>113.500000</td>\n",
              "      <td>40987.500000</td>\n",
              "      <td>3.208673</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>39.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>44.000000</td>\n",
              "      <td>151.250000</td>\n",
              "      <td>58537.000000</td>\n",
              "      <td>5.261184</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>67.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>210.000000</td>\n",
              "      <td>182058.000000</td>\n",
              "      <td>10.871566</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              Age  num_coffeeBags_per_year  ...      Online  gender_factor\n",
              "count  228.000000               228.000000  ...  228.000000     228.000000\n",
              "mean    31.802632                 2.960526  ...    0.570175       0.548246\n",
              "std     14.302293                 1.585514  ...    0.496140       0.498762\n",
              "min     16.000000                 0.000000  ...    0.000000       0.000000\n",
              "25%     22.000000                 2.000000  ...    0.000000       0.000000\n",
              "50%     25.000000                 3.000000  ...    1.000000       1.000000\n",
              "75%     39.000000                 4.000000  ...    1.000000       1.000000\n",
              "max     67.000000                 5.000000  ...    1.000000       1.000000\n",
              "\n",
              "[8 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c3HLaOFk27mB"
      },
      "source": [
        "### 4. Divide the NOPrediction subset into X and y"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bkD9WISM27mC",
        "outputId": "2003deb1-cca6-4130-903e-7cef207c2253"
      },
      "source": [
        "# First of all, let's check the names of the columns of NOPrediction\n",
        "NOPrediction.columns"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Age', 'Gender', 'num_coffeeBags_per_year', 'spent_last_week',\n",
              "       'spent_last_month', 'Salary', 'Distance', 'Online', 'Decision',\n",
              "       'gender_factor'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8ndj3ZB27mE"
      },
      "source": [
        "# Let's do our feature selection.\n",
        "# Make a variable called 'features', and a list containing the strings of every column except \"Decision\"; that is:\n",
        "# [\"age\", \"gender\", \"num_coffeeBags_per_year\", \"spent_last_week\", \"spent_last_month\", \"Salary\", \"Distance\", \"Online\"]\n",
        "features= [\"Age\", \"gender_factor\", \"num_coffeeBags_per_year\", \"spent_last_week\", \"spent_last_month\",\n",
        "       \"Salary\", \"Distance\", \"Online\"]\n",
        "\n",
        "\n",
        "# Make an explanatory variable called X, and assign it: NoPrediction[features]\n",
        "X = NOPrediction[features]\n",
        "\n",
        "# Make a dependent variable called y, and assign it: NoPrediction.Decision\n",
        "y = NOPrediction.Decision"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dzZUinX-27mK"
      },
      "source": [
        "### 5. Create dummy variables to deal with categorical inputs\n",
        "One-hot encoding replaces each unique value of a given column with a new column, and puts a 1 in the new column for a given row just if its initial value for the original column matches the new column. Check out [this resource](https://hackernoon.com/what-is-one-hot-encoding-why-and-when-do-you-have-to-use-it-e3c6186d008f) if you haven't seen one-hot-encoding before. \n",
        "\n",
        "**Note**: We will do this before we do our train/test split as to do it after could mean that some categories only end up in the train or test split of our data by chance and this would then lead to different shapes of data for our `X_train` and `X_test` which could/would cause downstream issues when fitting or predicting using a trained model."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GdigaqRI27mG"
      },
      "source": [
        "### 6. Further divide those subsets into train and test subsets for X and y respectively: X_train, X_test, y_train, y_test"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E8aJs3PL27mG"
      },
      "source": [
        "# Call train_test_split on X, y, test_size = 0.25, and random_state = 246\n",
        "# Make new variables called X_train, X_test, y_train, and y_test\n",
        "X_train, X_test, y_train, y_test=train_test_split(X, y, \n",
        "                                                  test_size = 0.25,\n",
        "                                                  random_state = 246)"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SSMUc1xFdFjT"
      },
      "source": [
        "# One-hot encoding all features in training set.\n",
        "# Call get_dummies() on our Pandas objet pd, and pass X to it. Reassign the result back to X. \n",
        "# One-hot encode all features in training set.\n",
        "\n",
        "X_train = pd.get_dummies(X_train)\n",
        "\n",
        "# Do the same, but for X_test\n",
        "X_test = pd.get_dummies(X_test)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cp0ibTlP27mN"
      },
      "source": [
        "# 3. Modelling\n",
        "It's useful to look at the scikit-learn documentation on decision trees https://scikit-learn.org/stable/modules/tree.html before launching into applying them. If you haven't seen them before, take a look at that link, in particular the section `1.10.5.` "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4TxsvBr-27mN"
      },
      "source": [
        "## Model 1: Entropy model - no max_depth\n",
        "\n",
        "We'll give you a little more guidance here, as the Python is hard to deduce, and scikitlearn takes some getting used to.\n",
        "\n",
        "Theoretically, let's remind ourselves of what's going on with a decision tree implementing an entropy model.\n",
        "\n",
        "Ross Quinlan's **ID3 Algorithm** was one of the first, and one of the most basic, to use entropy as a metric.\n",
        "\n",
        "**Entropy** is a measure of how uncertain we are about which category the data-points fall into at a given point in the tree. The **Information gain** of a specific feature with a threshold (such as 'spent_last_month <= 138.0') is the difference in entropy that exists before and after splitting on that feature; i.e., the information we gain about the categories of the data-points by splitting on that feature and that threshold. \n",
        "\n",
        "Naturally, we want to minimize entropy and maximize information gain. Quinlan's ID3 algorithm is designed to output a tree such that the features at each node, starting from the root, and going all the way down to the leaves, have maximial information gain. We want a tree whose leaves have elements that are *homogeneous*, that is, all of the same category. \n",
        "\n",
        "The first model will be the hardest. Persevere and you'll reap the rewards: you can use almost exactly the same code for the other models. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dn_gV-_k27mO",
        "outputId": "de979aae-f3cf-4f3a-9ebc-3f2ed9b9dad7"
      },
      "source": [
        "# Declare a variable called entr_model and use tree.DecisionTreeClassifier. \n",
        "entr_model = tree.DecisionTreeClassifier(criterion='entropy', random_state=1234)\n",
        "\n",
        "# Call fit() on entr_model\n",
        "entr_model.fit(X_train, y_train)\n",
        "\n",
        "# Call predict() on entr_model with X_test passed to it, and assign the result to a variable y_pred \n",
        "y_pred = entr_model.predict(X_test)\n",
        "\n",
        "# Call Series on our y_pred variable with the following: pd.Series(y_pred)\n",
        "y_pred = pd.Series(y_pred)\n",
        "\n",
        "# Check out entr_model\n",
        "entr_model\n",
        "\n"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='entropy',\n",
              "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=1234, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 912
        },
        "id": "Bk61p9Bu27mQ",
        "outputId": "e006cbd7-02cc-4f43-f6ed-f4dc1c9c344f"
      },
      "source": [
        "# Now we want to visualize the tree\n",
        "dot_data = StringIO()\n",
        "\n",
        "# We can do so with export_graphviz\n",
        "tree.export_graphviz(entr_model, out_file=dot_data,  \n",
        "                filled=True, rounded=True,\n",
        "                special_characters=True, feature_names=X_train.columns,class_names = ['NO', 'YES']) \n",
        "\n",
        "\n",
        "# Alternatively for class_names use entr_model.classes_\n",
        "graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
        "Image(graph.create_png())"
      ],
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G4KbEX0827mV"
      },
      "source": [
        "## Model 1: Entropy model - no max_depth: Interpretation and evaluation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O7wTOJqo27mW",
        "outputId": "757fa10e-a324-400c-af32-f360eca19e3a"
      },
      "source": [
        "# Run this block for model evaluation metrics \n",
        "print(\"Model Entropy - no max depth\")\n",
        "print(\"Accuracy:\", metrics.accuracy_score(y_test,y_pred))\n",
        "print(\"Balanced accuracy:\", metrics.balanced_accuracy_score(y_test,y_pred))\n",
        "print('Precision score for \"Yes\"' , metrics.precision_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Precision score for \"No\"' , metrics.precision_score(y_test,y_pred, pos_label = \"NO\"))\n",
        "print('Recall score for \"Yes\"' , metrics.recall_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Recall score for \"No\"' , metrics.recall_score(y_test,y_pred, pos_label = \"NO\"))"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model Entropy - no max depth\n",
            "Accuracy: 0.9915966386554622\n",
            "Balanced accuracy: 0.9878048780487805\n",
            "Precision score for \"Yes\" 0.9873417721518988\n",
            "Precision score for \"No\" 1.0\n",
            "Recall score for \"Yes\" 1.0\n",
            "Recall score for \"No\" 0.975609756097561\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ptzUYFpt27mY"
      },
      "source": [
        "What can you infer from these results? Write your conclusions here:\n",
        "\n",
        "*   Since there is no max depth, the decision tree doesn't stop till the max depth is reached which would make the model more complicated, tend to overfit and have an increased variance. This would also increase computational time and impact performance, while at the cost of getting great prediction\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oe4kkpM027ma"
      },
      "source": [
        "## Model 2: Gini impurity model - no max_depth\n",
        "\n",
        "Gini impurity, like entropy, is a measure of how well a given feature (and threshold) splits the data into categories.\n",
        "\n",
        "Their equations are similar, but Gini impurity doesn't require logorathmic functions, which can be computationally expensive. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9d4WO4lt27ma",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "59138fe6-38d7-4bdd-a5f3-8dfffda7350a"
      },
      "source": [
        "# Make a variable called gini_model, and assign it exactly what you assigned entr_model with above, but with the\n",
        "# criterion changed to 'gini'\n",
        "gini_model = tree.DecisionTreeClassifier(criterion='gini', random_state = 1234)\n",
        "\n",
        "# Call fit() on the gini_model as you did with the entr_model\n",
        "gini_model.fit(X_train, y_train)\n",
        "\n",
        "# Call predict() on the gini_model as you did with the entr_model \n",
        "y_pred = entr_model.predict(X_test)\n",
        "\n",
        "# Turn y_pred into a series, as before\n",
        "y_pred = pd.Series(y_pred) \n",
        "\n",
        "# Check out gini_model\n",
        "gini_model"
      ],
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
              "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=1234, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cdWfcr7n27mc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "9f2360f1-885a-4aec-b792-139481c12766"
      },
      "source": [
        "# As before, but make the model name gini_model\n",
        "dot_data = StringIO()\n",
        "tree.export_graphviz(gini_model , out_file=dot_data,  \n",
        "                filled=True, rounded=True,\n",
        "                special_characters=True, feature_names=X_train.columns,class_names = [\"NO\", \"YES\"])\n",
        "\n",
        "# Alternatively for class_names use gini_model.classes_\n",
        "graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
        "Image(graph.create_png())"
      ],
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yCgKCQEM27me",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8f83f9c1-e254-432d-d416-a74d7fd159a6"
      },
      "source": [
        "\n",
        " # Run this block for model evaluation\n",
        "print(\"Model Gini impurity model\")\n",
        "print(\"Accuracy:\", metrics.accuracy_score(y_test,y_pred))\n",
        "print(\"Balanced accuracy:\", metrics.balanced_accuracy_score(y_test,y_pred))\n",
        "print('Precision score for \"Yes\"' , metrics.precision_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Precision score for \"No\"' , metrics.precision_score(y_test,y_pred, pos_label = \"NO\"))\n",
        "print('Recall score for \"Yes\"' , metrics.recall_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Recall score for \"No\"' , metrics.recall_score(y_test,y_pred, pos_label = \"NO\"))"
      ],
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model Gini impurity model\n",
            "Accuracy: 0.9915966386554622\n",
            "Balanced accuracy: 0.9878048780487805\n",
            "Precision score for \"Yes\" 0.9873417721518988\n",
            "Precision score for \"No\" 1.0\n",
            "Recall score for \"Yes\" 1.0\n",
            "Recall score for \"No\" 0.975609756097561\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FgCPZf0c27mh"
      },
      "source": [
        "How do the results here compare to the previous model? Write your judgements \n",
        "\n",
        "*   Accuracy, Balanced accuracy, precision and recall score - everything is same compared to \"Entropy model - No max depth\" since the decision tree stops when the node purity is sufficient"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "88xuZI4927mi"
      },
      "source": [
        "## Model 3: Entropy model - max depth 3\n",
        "We're going to try to limit the depth of our decision tree, using entropy first.  \n",
        "\n",
        "As you know, we need to strike a balance with tree depth. \n",
        "\n",
        "Insufficiently deep, and we're not giving the tree the opportunity to spot the right patterns in the training data.\n",
        "\n",
        "Excessively deep, and we're probably going to make a tree that overfits to the training data, at the cost of very high error on the (hitherto unseen) test data. \n",
        "\n",
        "Sophisticated data scientists use methods like random search with cross-validation to systematically find a good depth for their tree. We'll start with picking 3, and see how that goes. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sIqsFSm127mj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0cdee910-8511-4b9f-90ec-f911483462ff"
      },
      "source": [
        "# Made a model as before, but call it entr_model2, and make the max_depth parameter equal to 3. \n",
        "# Execute the fitting, predicting, and Series operations as before\n",
        "entr_model2 = tree.DecisionTreeClassifier(criterion='entropy', max_depth = 3, random_state = 1234)\n",
        "entr_model2.fit(X_train, y_train)\n",
        "y_pred = entr_model2.predict(X_test)\n",
        "y_pred = pd.Series(y_pred)\n",
        "entr_model2"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='entropy',\n",
              "                       max_depth=3, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=1234, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jQMihcyY27ml",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 594
        },
        "outputId": "3f1f417e-0ffc-4fee-9f5f-f705eafbfdc5"
      },
      "source": [
        "# As before, we need to visualize the tree to grasp its nature\n",
        "dot_data = StringIO()\n",
        "tree.export_graphviz(entr_model2, out_file=dot_data,  \n",
        "                filled=True, rounded=True,\n",
        "                special_characters=True, feature_names=X_train.columns,class_names = [\"NO\", \"YES\"])\n",
        "\n",
        "# Alternatively for class_names use entr_model2.classes_\n",
        "graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
        "Image(graph.create_png())"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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rYFaUm93cSIt+cCsi0E/faoegmNSvXyn43cHMVgD+LEQS18HgJzdOHTq6zbS6vISTwi0xetz2Y1fUlugxYzjw+C0eZ4O8Xb6kvaO30cdPVbHY7cN8hEdWQdn9auStM1571i5oqKXyCoqoLdPX2+TE+oBJ92ZrG8c9uXPSeSMXhfvI7ejefxphsFjHE9cCDzntNp6Hw3GMU1TZfvQKiYv87UPKEWsjHUt7462u3V/dT5+6lyZMm3ngyqMbpzyc9NUaGxoExSTn6q5dtXknDtfbf2zbZdinsz+6eu6ih0Onh0aNn+wd3n4d1SveLhGBJ5g/BnnvDvLejRDS0DKyO3IRIaS52pJHQPhB0GmHlTNbmpsFRSVkFZRXbXZm3CNBCBlvdRUbOTby5qVHV8820Wg8gsKTVObY+waJSo/pNA1uXn73a5HXfPe7GM9rqKWKj5JZv+uwppFlny4TDFcwLAfA8GFoaJhf02LvG/QrnXhs0s1Kig1KLO45FIBBFPMozNfeDD6zhjEYtQEAtAf/5gMABh9UJAAAAABgP5hHAgBgm/dRTz02rewmQFZB+VDoi2F2agBAp6AiAQD8x+6AO4N2LkX1RTcz2bPmFRtPDQDoFIzaAAAAAID9oCIBAAAAAPtBRQIAAOxRmPP16DYTi1kjjafw2y1TDA/woXe2fx5Tdkbyob/01qmIr1EUcFw583nYla4iG+pqrTUnGchTcv+7oGp25ntPK/11KuKrFfhslygEH93bADvFgCEDKhIAwG+pvLjAQJ5SWpDD7kR+UlVZ8Z61C+prazxDX15JKDR1dA8L8L7gbt9VfHzkXWejOSQu8uGbUYGxuXN11p51telqt5rLXjtL8r+3a/yanuSyeh6JTPG+HRMYm7fe+fDz238f3LCi+zIIgEEDFQkA4LeUEf+G3Sn8klv+XrT6um0+l0WkRuMJROX5WvpWO59ev1iQ/anT+OCje/mFxGwPXxCVHkPkJGutt5230vTGSY/a6sp2kUmvHj2//ffMDuvWXzu+H8fBscXDX1hyFCeZojR36Yr1dp9TEz4ktV/LFQC2gIoEAMAe37NSj9isNleVMp7Cb6056Yq3C+uGw4f+0rNZPLkw5+tha6P1MyXNZojtNVn0JS2RcdRjk+7JnZYIoS2LJq5RFGC02C5R+P4xzUFXZY2iQFtrK0IoKynOY9PK9SoSqxX4Ni+Qu+huz9jHmMHVVNNq/oRvH1L2rVtioiRiMk34gPly5i59+8wWm0wTbqilsuYcHuBjIE9JiX7265cf8/D2RGUNbl5+ZovKQm06nR73JLxjcF1NVWHO1/FTVfAEIrNRbYleI60+6dUj1khqVYX/Xmu1pfqTVee166S8KJ9HQJi5GwBCSER6DEKoJO/br18OAL8OKhIAABt8TU/avWYBnd7mce15YGyehYv36/+FHLTUZu4tx4EnUKvK/ZzMFxlZnHvx0f3qs8rSoiO2xs2NNITQ7oA7K8ztEEJnnmZce1+OEOLAExsb6i+5OyjP11q/6zAGi01/+2r/uiVcFG7P668ux+XbeAa8jYzYv34poweEEJ5ArKksO+NiZWi9+2L0t0OhL4pys93Ml1MryxFCCw0tGmn1UQ/+s0Fd9MNbgmJSCh0+7KmV5QbylK6+Ot72KC/Kp1ZVSMpMYG0UlR6D48BnZ7zv+Hb9s3Q6BsPaSOHhQwixbnSMEDp/YGtra8uG3Uc7diItO7GqrJi17CvK/YoQapcGAOwCFQkAgA3+PuxM4eGz9w0SHy1L4iIrzV26xv7Al7TE2IdhzJh6ao22+dZpsxcTOcnSsvKLV2+sLCnM+ZTeaYcYDKamokx5vtZqu72aRpYYDCb46F4yD6+NZ4DYKBkSF3niDA0Te7fcTxnRD24xXoLF4ZobaTobtk+coUEkcUmPm2jq6E6tqnh55ypCaKamLjcv//Pb/24SVJD9Kedj+jw9Uwy2/b+c3HwCNzNru/qSGDOuXXxVWQlCaASvwH8uAYul8PBVlZd0vDoKD5+o9JiPSXEtzU3MxqykWIRQdXkps+XNveuxj8Mt9xwbwS/YsZNVm50JBOJJ543lxQUtzU3voyLvXT6ptlRfZvL0Tt9SAAYZVCQAgMHWUEvNSo6bNGM26xjEVPVFCKHPqQmskaxDD3xCogihipLCrrptbW1RW6bP+L6upupretJEZQ3WHYkZvaXHv2Z91RT1hczvJ6rMRggxih48gThHZ82XtETm4ypRD25iMJh5K036eLmdaGqkIYQ48IR27Rx4QlNDfacvMXXyKC8uOLnTsjjvWz215mV48OPQ8wih1pZmRkBF8Y+L7g4zFqxQW6rfaQ/S4yY6ngj5lPLWat544yn8Hpt05aarWx049euXA0C/gIoEADDYKkoK6W1tryNCWYc2Ns2VRQiVFRUww7A4HOs0C8adCcYEkU5hMBg+QVHG9+XFP9D/FzFMvALCCKGK4h/MFhwHnvUUjHGQ6v+/S7HQwAIh9OL/H7KNeXhrsuo8IXHpn7nm/yKSOBFCrDc8GFqaGgmcXJ29As1YsMLlXNiP71+2aSlZa05MfvPEwTcYIcRJ5mYE+O/dghDauO94Vyd9fTfEfaPOfD2zM5GZISkVh0JflOR922moUVNR9utXBMCvg1XkAQDssWDVeiu3/vwDHYPFYnE41pZ2O9czfsSwzMbAtht/+Sfgn0aJMePkp896HRFq4uie+ynjx7fPhta7+yVVRqlUXfmfUqC1taW2ulJOWKyrV03V0Jyqocn8kXHzRkRyFELoediV91GR249d4RUU6fS1ra0tFw5ul1NSXWvvxmiRVVC29jznpKf2v0vHTR3df/WSAPhlUJEAAAabgKgEBost/ZE7cKcQFJXEYDCVpf8Z4qksK0IICYhKMluamxrrqTVc3CMYPzKexOERFGYGLDLc4LfDIjXmeXrcKwoP34yFKzo9HbWy3GLWyK6SOX4vqd1UEj5hMV5BkfwvH1gbC75+bG1tkZms1Mtr/JQchxCaoKSGEMr5mI4Q8rU387U3Y41x0JmBEApNqyr7kddQVysxZjzrUfFRsgihguyPvTwjAAMKKhIAwGAjcZHllNQy4t9UlRUz/6b/8C7m3D5bW6/zYydN600njDsZ7e6CMHFxjxinOCMj/k0TrYFA4mQ0pkRFIoQUWSaOIIRSY5/P1NRlfJ/+9jVCaOJ0deZRFU0d7kP8ryNCM+LfaGgZsU58YcWY2dqbtJnUtQwfh5yvqShjzkKNfngbh+OYtWxVp/GXvXa+e/nw+L13OA48Qoje1vb0ZqDEmPHjp85ECJnvOmK+6whr/JPrF84f2Hb0f/HSsvIIIV5BYTyBmPffJVxzv2QihIQk+mEcCoBfB/NIAABsYOJwEIvDeW5eVZD9qbmRlhH/5qTzRjyByPj47A0BEXGE0OfUxOZGGvOZ4f+ewqOhrvb0bquS/O+0+rrU2Bchfm4Tps1UYVk6jEDivOXvlRrzvJFWn/MxPfjoXl5BEdWleswAPIE4R3dt9INblSWF81et+7WL/g+9TU4jeAV8HcyKcrObG2nRD25FBPrpW+0QFJNiBKTGvjCQp1zxdmH8qKi+qDj/+4WD9tSqiqqy4rP7bPM+Z1q5ncb895HgrhA5ySvMt2YmRl87vr+8KL+RVv8pJf6cqy2Zm2e5qXU/XhcAPw3ukQAA2EBWQdn9auStM1571i5oqKXyCoqoLdPX2+TE+mhM92ZrG8c9uXPSeSMXhfvI7eiOAROmzTxw5dGNUx5O+mqNDQ2CYpJzddeu2rwTh/v33z0OPH6Lx9kgb5cvae/obfTxU1UsdvuwriGGEFpkYHHv8skx8oqjxk/+lUtuh5uX3/1a5DXf/S7G8xpqqeKjZNbvOqxpZNlVvKL6QqcT18IDjm5ZKIfBYscrzjwY/LSX95MYjLe6io0cG3nz0qOrZ5toNB5B4Ukqc+x9g0Slx/THBQHwqzBd3fMEAPx2DA0N82ta7H2Deg4FCHls0s1Kig1KLO4+LPdzpoPOjM0HT8/X7897JKCvYh6F+dqbwWfWMAajNgCAP1dvPt3uXjrOKyiioWU08OkA8EeDURsAAOhEW2trc3Pj0+uXXv3vmr1vUO+HkwAAPwcqEgAA6ETMw9snnC0Z2+2qLl7J7nQAGP6gIgEA/KF2B9zp5qi6lqG6luGgJQMAgHkkAAAAAGA/qEgAAOA/PDbpmih1vhY7AGDgwKgNAAAMXV/S34UHHP2cmkCtLBcQlVBZpLNqszMnmcI4evfS8SCfPR1fFZpWxVh2pccAAIYO+I0EAIAhKjMx2t1SW3mBlsfVSAoPf3LU0zMuVlnvYtyvRjJ2Qq6rqUYIXX5bQObm6bSHHgMAGDpg1AYAAIaokOP7RvAJ2nqdF5IYyUnhVluit9h446eU+K+ZyYyAOmoVQojERe6qhx4DABg64B4JAIDNaqsrb/l7Jb54UFFSyEmmjJ04zdDGRWbydGZA+ttXYee8v6Qltra2ColLzdY2XrHejrnp3aG/9H58/+x0IiTQ0+lLWhIHB4fS3KWWrseTXz8OD/D5kfOFV1BkuZn1MpPNjHhXU82Sgtydp69f9tr5NT0Z0emyU5TXOXt1tUj896zUG6cOfXgXTauv4xcRV1mkvcrKmbldcI/J/4qZmit5BIQ58ARmi5SMHEKotCBXZpISQqiOWk0gcXYz/tJjAABDB/yaAgDYzNdhXf7XLAffoNFyUypLi654uxwwX37kVrTYKBmEUFZSrLuljsoibb/7yVzcI+Kf3Tu507K6vJS51S0HnkCtKr9wcJvZDk8pGfknoeeDfPaUFeUTiCSnkyFkHr5L7g6Bh5xkFabLKigjhPAEYk1l2RkXq/W7jsgoKBXnfvPcvMrNfLnf/WRuPoF2uX1NT3I1W6ygOs/j2nN+EfGM+Nf+e7Z8SIxxvxbJ+JjvPnlW1Mpyi1kju3oTjt9Lkhgzrl3jcrP2e+B9/5iGwWAYdQlCqL6mmpOL0s1722MAAEMHjNoAANipuZGWFvdyqobmOEUVPJEkLDnK2uMcnkB8Hx3JCEh4dg9PJJo6efAJixE5yRpaRvLK6i/vBLN2Uk+tWbnRUVZBmcRFXr7OhsRF/pj8dovHWWHJUWRuHh1Le4RQetwrRjAWh2tupOls2D5xhgaRxCU9bqKpozu1quLlnasd0/v7sDOFh8/eN0h8tCyJi6w0d+ka+wNf0hJjH4b1JnlW3HwCNzNru/rqWI60U11ecjfQ7+HVs/qbnSXHTmA01lGrcHj89VMe21dMXzNVcNMcmYvu9rXVlcxX9RgAwNAB90gAAOzEgSfw8AvFP4uYNltTae5SHAeek8J9KSaXGWDq5GHq5MH6EmGJURnxb+pqqsgjeJmNE6apMb7B4TgoPPx4AoFPSJTRwisgjBCqKvvPjnpT1Bcyv5+oMhshlPMpvV1uDbXUrOQ4jeWGzBEihNBU9UUIoc+pCepahj0m3y+KcrNtlygghEhc5LX2bqw3Tuht9OamRhIn177A+wQiZ2rs8wtu25PfPPUOi2U8j9NjAABDB1QkAAB2wmCxzmdu+u2w8LZbQyRxjVOcoaixaL6eGYWHjxHQ3Eh7HHI+7umd4rzvtdWVbW2tba2tCCHGfxmwOBxzYgdCCIPBUHj4WX9ECLW1/RuP48Bz8/4bwDhXdXlJu9wqSgrpbW2vI0JfR4S2O1RWVNCb5PuFqPSYm5m1dTVVGfGvL3o4Rj+45XoxglGNeYQ8Z42cqamLwWB9tq65c+GY8VbX3gQAMHRARQIAYLOxk6b53U/+mBz3PioyJSoyyHt3eICP66V7o+WmIISO2a979/KBwZZds7WNeQWFOQjEgH12z8Ou/MoZsdj/DljT6QghDKbzUewFq9ZbuZ36ueT7EXkE74yF2oJiUjsNNMLPHzVxONhpmKLGQgwG8yU1oat+egwAgF2gIgEAsB8Gg5kwTXXCNNXVdns/vX/rarr45mnPHadCK0sKE1/cn7VslYG1CzO49MevDos0NzXWUxbDUVMAACAASURBVGuYt1WoVRUIIR5B4XZhAqISGCy2x9N1lXy7sL7ObC0rzLt52lNeWX2OzhpmI2MGSf7XLIRQS3NT7udMTjK32MixzICWpiY6nc7YqbjHAACGFJjZCgBgp8yEqL/mjfv+MY3ZMk5RhVdIlFpVjhBqbmpECLE+AlOQ/TEzIQohRKfTf+W8qbH/Dmekv32NEJo4Xb1dDImLLKeklhH/hnUOyod3Mdu0lL6mJ/WYfDt9ndk6gk8w+sGtB0Fn6G1tzMbszBSEkIjUaIRQc1PTXpNFZ13/8zxO0uvHCKFJKnN6EwDAkAIVCQCAncZOnobDcZx23vQ5NaG5kVZbXXnv8snyovwF+usQQkLi0iJSo+MjI3I/ZzY30pJeP/a2M1ZdshIh9CX9HetUkj4hkDhv+XulxjxvpNXnfEwPPrqXV1BEdalex0gTh4NYHM5z86qC7E/NjbSM+DcnnTfiCURpWfkek/9FBBKn2Y5D2Znvz7ralBbkNNLqMxOjz7puIXPzMNZW4SRTjGx2ZyZEXfbaWV5cUE+tiXkUFui5Y9T4yYuMLHoTAMCQAqM2AAB2IpK4DgY/uXHq0NFtptXlJZwUbonR47Yfu6K2RA8hhMFiHU9cCzzktNt4Hg7HMU5RZfvRKyQu8rcPKUesjXQs7X9ueiYHHr/F42yQt8uXtHf0Nvr4qSoWu32IJK6OkbIKyu5XI2+d8dqzdkFDLZVXUERtmb7eJifGqEf3yf86zdWWPALCD4JOO6yc2dLcLCgqIaugvGqzM+MeCUJI22KbsOSo+1dOO+mpNdRShSSkFxqYr9zoyLyWHgMAGDowv3jnEwAwdBgaGubXtNj7BrE7kSHNY5NuVlJsUGJxz6FgKIl5FOZrbwafWcMYjNoAAP448KEGwBAEFQkAAAAA2A8qEgAAAACwH8xsBQD8WXYH3GF3CgCATsA9EgAAAACwH1QkAIChyGOTromSCLuz+MeJHRsM5CmMr9KCHHanM+C2Lp/KuFgLNWl25wL+IDBqAwAAPcMTiNfe/2cl1pbmJv+91q/vhpg6eWibb20X/yX9XXjA0c+pCdTKcgFRCZVFOqs2O7Nut1uY8/Wa776MhDeMZULm6ZroWtpjsL39K/HHt88hfvvT4l41NzUKiUurLtHTsdhG4iL3MuDupeNBPns6dhuaVoXDcfjdT0YIHbFZnZUU08t8APh1UJEAAECf1dVUedsZtzQ3dXo0MzHa3VJbeYGWx9VICg9/ctTTMy5WWe9i3K9GMmqOqrLiPWsXjJqg4Bn6kl9E/H3U0xM7NpQV5W90Pd6bs+d/zXI2nDNGfopb0BMhcenk149P77bKTk/adfZ2LwPqaqoRQpffFpC5efrh7QCgP8CoDQAA9E1dTdXuNQvkpqub7fDsNCDk+L4RfIK2XueFJEZyUrjVlugtNt74KSX+a2YyI+CWvxetvm6bz2URqdF4AlF5vpa+1c6n1y8WZH/qTQJXj7m2tbY4nQiRlpXnJFPUluprrrZMev04MzG6lwF11CqEEOs9FQDYDioSAED/czXVXDtNiFZfx9oYcvyAgTyFsU8eQij97Ss3Cy0zZdG104S2aU0LC/Bm7KvX0V6ThZYaY1hbHl09ZyBPyYh/w2z5npV6xGa1uaqU8RR+a81JV7xd6qk1/X1Z/6gqK9Eyszay2d1VwEzNlSaO7hx4ArNFSkYOIVRa8M82wjEPb09U1uDm5WcGqCzUptPpcU/Ce5OAgtr8tfZurBsQjpWfihAqyfvWy4A6ajWBxInDwW1yMITAryMAoP/N0Vnz4V1M4osH6ssNmI3RD28JS46Smz4LIZSVFOtuqaOySNvvfjIX94j4Z/dO7rSsLi8133XkJ073NT3J1Wyxguo8j2vP+UXEM+Jf++/Z8iExxv1aZMcPXWplucWskV11dfxeUsdteNuRGDOu+5jlZtbtWr5/TMNgMIy6pLwon1pVISkzgTVAVHoMjgOfnfG++1MzLF1r1a6louQHQkj4//e76TGgvqaak4uCABhKoCIBAPQ/1cV6Fz0cYx7eZlYkn1Lii/O+GVq7YDAYhFDCs3t4ItHUyYNPWAwhpKFl9OzW5Zd3gn+uIvn7sDOFh8/eNwhPICKElOYuXWN/wH/PltiHYepahu2CufkEbmbW/tLl9UV1ecmruyEPr57V3+wsOXYCQqiqrAQhNIJXgDUMg8VSePiqykt+7hT3rpyWlpWfMHVmLwPqqFU4PP76KY+4x+HF+d8pI3hVFmkb2e6l8PD9RAIA9AsYtQEA9D8u7hHK85a9j3raUEtltETdu4HBYOborGH8aOrkEZRYLCgmxXyJsMSoempNXU1VX8/VUEvNSo6bNGM2oxxhmKq+CCH0OTXhly7j1xTlZhvIUyw1xtw8fWitvduqzTsZ7U2NNIQQ65gOAwee0NRQ39ez1FZXHrY2qqfW2Hidx+JwvQygt9GbmxpJnFz7Au9feJ1tsdsn9lG4s+HshrrBq9UAaAfukQAABsQcnTUxj8Lin0XM0VnT1toa8yhMXlldWHIU42hzI+1xyPm4p3eK877XVle2tbW2tbYihBj/7ZOKkkJ6W9vriNDXEaHtDpUVFfzydfw8UekxNzNr62qqMuJfX/RwjH5wy/ViBHkEL5HEiRDq+JxOS1MjgZOrT6cozvvm8dfK6vKSXf63RstN6X2AR8hz1rCZmroYDNZn65o7F44Zb3XtUw4A9BeoSAAAA2KK+kIefqGYR2FzdNakv31VXV5i4nCQefSY/bp3Lx8YbNk1W9uYV1CYg0AM2Gf3POzKT59uwar1Vm6n+iPxfkYewTtjobagmNROA43w80dNHA7yCYkihKory1jDWltbaqsr5YTFet/zx+S3h20MSVyUg8GR0rLyPxHASlFjIQaD+cLWu0rgDwcVCQBgQOBwHLOWGzwOOV9HrY66f5PERVZdrMs4VFlSmPji/qxlqwysXZjxpT9yu+oKi8W1tf3n3gnrfAsBUQkMFtvNy9v59Zmt3SsrzLt52lNeWZ05RIUQYswgyf+ahRDiExbjFRTJ//KB9VUFXz+2trbITFbq5Vk+pcS7b9SWHDPB+ewtHn6hPgW0NDflfs7kJHOLjRz7b2NTE51OxxNJvb5QAPoZVCQAgIEyR2fNg6Az7148iH8WMXPxSiLnP6tfMJ7yZX02tSD7I+OpYDqd3rEfHgHhD0mxzY005udlWtxL5lESF1lOSS0j/k1VWTGv4D8Lz394F3Nun62t1/mxk6a1622gZ7aO4BOMfnDre1bq7BWrmWuwZmemIIRE/v9RF3Utw8ch52sqykbwCzJaoh/exuE4Zi1b1ZtTlBbkHNq0Unz0ONfA+6zrwPYyoLmpaa/JIpnJSgf+fsRsTHr9GCE0SWVO364WgP4DM1sBAANljLyilIzcjdOH6mqq5umaMNuFxKVFpEbHR0bkfs5sbqQlvX7sbWesumQlQuhL+ruOU0mmztakt7XdOONZT62pKiv++8iuemo1a4CJw0EsDue5eVVB9qfmRlpG/JuTzhvxBGKPQxUDgUDiNNtxKDvz/VlXm9KCnEZafWZi9FnXLWRunmUmmxkxepucRvAK+DqYFeVmNzfSoh/cigj007fawZzqm5UUayBPuehu3+kpLrg7NDU1OvgGdVqO9BjASaYY2ezOTIi67LWzvLignloT8ygs0HPHqPGTFxlZ9Md7AMDPgHskAIABNFvb+OoxV+YyJAwYLNbxxLXAQ067jefhcBzjFFW2H71C4iJ/+5ByxNpIx9K+3eTKOdprSgpyX/3v2v2/T/EJiy0yMDfets/b1pi5opqsgrL71chbZ7z2rF3QUEvlFRRRW6avt8lpgMYgrni7RASeYP4Y5L07yHs3QkhDy8juyEWEkOZqSx4B4QdBpx1WzmxpbhYUlZBVUF612Zl5j4Sbl9/9WuQ13/0uxvMaaqnio2TW7zqsaWTZ7kTYzlYwa6TVJ716hBCy1pzU7tB8/XWbD57uMQAhpG2xTVhy1P0rp5301Bgb6yw0MF+50ZFI6tvUWgD6EabTe6QAgN+RoaFhfk2LvW8QuxMZbk7s2BD35E67nfYGWpDPHm4ePt2NDoN5UlaMnfYuxfR2gs5Ai3kU5mtvBp9ZwxiM2gAAwJBTV1MVff+miqYuuxMBYPDAqA0AAAw55BG8Z198ZHcWAAwqqEgAAKBnzU2NBvIUhNCZpxlCEl0+PDw8bF0+9ce3zwgh1r0AARhoUJEAAEAP7I5cZExZ/UP43U9mdwrgTwTzSAAAAADAflCRAAB+bx6bdE2URNidBQDgV8GoDQAADLj0t6/dLJbPWLjC0e9au0M1FWXbtKaRyNy+d+OJnOT7V05f9trZVT9rtx9gPg9cR61+djMw7sn/SgpyaqsqCCSS+OhxMzV1l5tZs26DDMDvAioSAAAYcJNUZi8y2vAk9EJ85N0ZC7VZD1322llbXWnvG8RcZR8h5HA8eGa3j/421FJdVs+tKP6xdrub2lJ9Lu4R5UUFz29fuXrMNS32xd6LEQN1JQAMGBi1AQCAwWDq6CEkLn3B3aGeWsNsfB8V+ebe9UWGG/q6ocyb+9d/fPtsZLt3ydq/RvALcuAJIlKjjbft01xtmRr7IiX6WX+nD8CAg3skAIDfwJf0dzdOenx6/5aO6NKyE/WtdiiqL+o0Mv3tq7Bz3l/SEltbW4XEpWZrG69Yb8ccxaitrrzl75X44kFFSSEnmTJ24jRDGxeZydN7c/QXkbjIVm6nDlpqBx/du2m/H0KosaEu4MBWIXFpE0f3vvZWW1WBEOq4j6ChtYumkaXk2PH9kjMAgwnukQAAhrovaYl71y6SGDPO507c6ScZYydNO2Slz9i6pZ2spFh3Sx1uXn6/+8mXor/rW+0M9XMLPrqXGeDrsC72cbjd4Qt/x+V7hr4kkEgHzJcXfv/Sm6OsqJXlBvKUrr4Ksj91eiEKavMXGphH3rz04V0MQij0pHtpQY7VwdNdbZjXDXllDYTQy/Dg1tYW1nYeAeGR4yfhOPB97RAAtoOKBAAw1AX57OEXETdzOiQoJkXh4Vu3w1NAROJxyPmOkQnP7uGJRFMnDz5hMSInWUPLSF5Z/eWdYMbR5kZaWtzLqRqa4xRV8ESSsOQoa49zeALxfXRkj0fb4eYTuJlZ29WXxJhxXV2LmdMhfhGJs67WH5PfPgg6s9DAXEF13k+8JxOmqZo5HXpz77rtYoW/DzvHPflfZUnhT/QDwNABozYAgCGNVl/3ITFafbkhBvvPX1AYLNb/2YdOg02dPEydPFhbhCVGZcS/qaupIo/g5cATePiF4p9FTJutqTR3KY4Dz0nhZu4k1/3R/sJJ4bZyO+mxaaXbBi0+ITEzp0Odhh3dZtKxkZuXnzWfFeZ2s7VXxzwKS4158SbienVFqYjUaNUleivW2Y7gF+zftAEYBFCRADB8kEiklvIKdmfRz6rKiul0ei8/YpsbaY9Dzsc9vVOc9722urKtrbWttRUhxPgvBot1PnPTb4eFt90aIolrnOIMRY1F8/XMKDx8PR7tR4rqi2Zq6sY9ubPe+TAnhbvTmB6ftWHgERBeutZq6VorhFBx3rfEFw/Czx99GR7sfjVSRGp0/6bNdk20BhInJ7uzAAMIRm0AGD74+fmplWXszqKfYbFYhFBzU2Nvgo/Zr7vi7TJFbYH71cjLcXnX3pfP1zNjDRg7aZrf/eSDwU+11ts21FKDvHfbLlH49iGlN0f7kZCENEJISFyqH/sUkRq93Mza49qzqrLisHPe/djzEFFbVcHHB/vsDGdwjwSA4UNOTu7CxUA6nY7BYNidS78REJXAYLFVpcU9RlaWFCa+uD9r2SoDaxdmY+mP9sMuGAxmwjTVCdNUV9vt/fT+ravp4punPXecCu3NUSZqZbnFrC732zt+L6mbqSS/rqW56UGwPwcHfpnplnaHhCVH4XAchTmdzMb93eV+zpSXk2N3FmAAQUUCwPAxc+bMutqarxlJMpOU2J1Lv8Fx4McrqqS9fdncSMMTSYxGB10VAoHkeeMVayTjPgo3nwCzpSD7Y2ZCFEKITqcjhDITovx2WOw6e3vU+MmMgHGKKrxCotSq8h6PtsOY2drvF9tLHHhC3OM7uZ8zlecvb7cR8buXD1tbW6Rk5NmV28DJTHi9cb0pu7MAAwhGbQAYPhQUFCSlpN8++R+7E+lna+0PNjc2nti5obq8pI5aHeLnlvspY9HqDe3ChMSlRaRGx0dG5H7ObG6kJb1+7G1nrLpkJULoS/q7ttbWsZOn4XAcp503fU5NaG6k1VZX3rt8srwof4H+OoRQ90eHmk0HThA5OfebL4+6d6O2urK1pbm8uOBxyPlTzhsFxaT0rXawO8F+9iX9XXF+zooVK9idCBhAGMafDgCA4WH//v1+p86ceppBJHGxO5f+lJUUd/3kwa8ZSYhOlxwrp22xlTnx02OT7od3scHvihFC3z+mBR5yys5IxuE4ximqrLV3I3GRPTfrF+Vk61jaG291LS/Kv3HqUErM8+ryEk4Kt8TocUtNNqst0WN01f3RfnTF2yUi8ITXjdcdlzjrfl8bEanRpx6nMb4vK8yLuHwyLfZFSX5OUxONk0wRHzVOac7ipaZbyNw8/Z4ze53ZbVX86X1Gehq7EwEDCCoSAIaVkpISWdlxmms3G9nuYXcuAPSP71mpOw00/r582cSkk4eiwbABFQkAw82xY8d2uez2jUgUlhzF7lwA6AcH1i8lY1tiY6KH05Rt0BFUJAAMN83NzZMmK5D4RFwC7sBq4uB39yDY/2+vnfHx8UpKw2e+NugUzGwFYLjB4/Fht299y0gOOLCV3bkA8EveR0VeObLLw8MDypE/AVQkAAxDEydOvHo1+GV48O2zh9mdCwA/6Utaoq+9mYmJibOzM7tzAYMBt3//fnbnAADof+PHjxcWFvY54FJR/ENRYxEWi2N3RgD0QdyTO962q+fOmX31ajAOB7+9fwSYRwLAcBYREWFsvGbsZCWrg2faLaUFwNDU3EgLC/C5ffawjY2Nr68vlCN/DqhIABjmUlJSDI1W5+TkrDDfqrvRfpitUwKGmfjIu8Heu2sqSn18vK2srNidDhhUUJEAMPw1NzefPHnywAE3LAd+zkrTmYt1x06cBg9SgqGjvKgg8cWDF7cvZ39IXbN27ZHDh8XFxdmdFBhsUJEA8KcoKSnx9/e/cPFSfl4umTJCSlaOm1eAg0Bkd14Dgk6nIzodgx0Ok/fbWluxw3Tkoq2ttb6mqijna2lRARcXedUqfVtb2+nTp7M7L8AeUJEA8MdJSUmJi4vLzMysrKyk0WjsTmdAfPnyJTs7e+HChdjfvChJT08vKyubO3cuuxMZEFgslpeXd8yYMdOmTVNXVyeRSOzOCLATVCQAgOGmvLx8/PjxlpaWXl5e7M7lV717927GjBlBQUFr1qxhdy4ADCyoSAAAw82GDRseP36clZVFoVDYnUs/2LRpU0RERFZWFg/PcNs/DwBWv/f9TAAAaCcxMfHy5ctHjx4dHuUIQsjLy6ulpcXd3Z3diQAwsOAeCQBg+Ghra1NVVSUSia9evRpODxP5+/vb2dklJSVNnjyZ3bkAMFCgIgEADB9nz561tbUdfp/cjEqLQqE8e/aM3bkAMFCgIgEADBMVFRXjx49ft26dj48Pu3PpfwkJCTNnzgwNDTUwMGB3LgAMCJhHAgDoGxsbG0y30tPT2ZLYrl27cDjc3r172XL2gaasrGxmZmZvb19bW8vuXAAYEHCPBADw88rKyoSEhHR0dO7cucPeTN69e6eiovL333+vXbuWvZkMnJKSkvHjx1tZWXl6erI7FwD6H9wjAQD89tra2mxsbFRVVYf3oh3CwsIHDhw4duzYx48f2Z0LAP0PKhIAQP9bsmSJrKxsSkqKgoICiURqbW1VV1cXFRVljTl16hQGg3n58iWz5f3797q6ugICAkQiccyYMY6OjtXV1b05XWBgYEJCAqPD/r2Qocba2lpOTs7W1pbdiQDQ/6AiAQD0PyKRWFdXZ2trq6Ojc/z48d4s5Z6YmKimptbW1hYTE1NeXn7ixImgoCBNTc2WlpbuX1hZWblr1y5ra+spU6b0U/pDFw6HO336dGRkZHh4OLtzAaCfQUUCAOh/GAymtLRUR0fn4MGDVlZWvbl1YW9vz8/Pf/PmzfHjx1MoFC0tLU9Pz/j4+Bs3bnT/wj179mAwmAMHDvRT7kPdrFmz1q5du3Xr1rq6OnbnAkB/gooEADAgWlpajIyMehlcU1MTHR09b948IvHfvYiXLFmCEHr79m03L0xLSwsICDhy5AgvL++vZPt78fHxqampOXz4MLsTAaA/QUUCABgQGAxGTEysl8E/fvxoa2sLDg5mfYpYQkICIZSXl9fVq+h0uo2NDeOx2P5J+jchIiLi6up65MiRT58+sTsXAPoNVCQAgAGBxWJxOFyfXmJpaUnvICwsrKv4K1euREVF+fn5DfsJrR3Z2dmNHz/ezs6O3YkA0G+gIgEADAYcDtfa2sraUlxczPxeUlISi8Xm5OT0vsOamppdu3ZZWVkpKyv3W5a/Dw4OjlOnTj158iQiImJAT7RkyZJhs2chGOKgIgEADAYREZGKigoajcZsYd2ihUKhaGhovHz5sqioiNn45s0beXn5xMTETjt0dXVtampyc3MbuJyHOA0NDSMjo23btrG+q6yOHz/e1bq6EyZMGORsAegRVCQAgMGwdOnStra2AwcOVFdXFxUVOTg4tFtr5PDhwzgcTktLKysri0ajvXz50szMjEgkTpo0qWNvGRkZZ86c8fLyEhAQGKwrGIp8fX3LysqOHDnSTczNmzc7joVlZWUNWpIA9BJUJACAwWBmZubq6hoaGioiIqKmpiYkJOTh4YEQamxsZASoqKhER0dLSkrOmjWLm5vb1NRUX1//2bNnJBKpY282NjYKCgoWFhaDeg1Dj6io6O7du728vL59+8buXAD4ZR1rZwAAGMqCg4OxWGxcXBy7ExkSGhsb5eTkdHV1Ox7y9fVFXdwjYfXs2bMFCxZwc3NzcnJOmDDBw8ODRqMxjy5evJhMJjO+Ly8v37Zt25gxY0gkkpCQ0NKlS9++fcvaVXJyso6ODj8/P4FAGD16tIODQ1VV1S9fIvhTwD0SAMDvhEql7tixw9LSUkVFhd25DAkEAuHkyZN37tx58ODBT7w8Kipq8eLFAgICWVlZpaWle/bs2bNnz86dOzsNXr169c2bN4ODgysrK9++fcvJyblgwQLmE8g/veouAP9gd0kEAAB94ODgwMfHV1payu5EhhZ9fX0ZGZmGhgbWxt7cI3F0dKRQKDk5OcyWuXPn8vDwMH9k3iNpaGjAYrGsT2hXV1cLCAicOHGC8aOGhoaEhATr/ZWLFy8ihK5evfprFwf+FHCPBADw28jMzDxx4sShQ4cEBQXZncvQ4uvrW1hYeOzYsY6HDAwMOj5rs379esZRb29vKpUqLS3NjB89enR1dXVlZWW7fggEgrCw8J07d8LDw5ubmxFCI0aMKCsrY2z799Or7gLABBUJAOC3YW9vP3ny5I0bN7I7kSFHSkpq165d7u7u379/b3eo03skly9fZhyl0WjHjh2bNWuWmJgYkUjk4OAIDAxECLVbPAYhhMViIyIi+Pn59fT0eHl5Fy5c6OPjU1FRwTj6c6vuAsAKKhIAwO/h+vXrT548OXXqVF+Xgv1DODk5SUtLOzk59elVRkZGjo6OmpqaUVFRjAVjunmCafr06VlZWW/evLG3t6+pqXFycpKVlU1OTmYG9HXVXQBYQUUCAPgN1NfX79y509zcXFVVld25DFEEAuHEiRO3bt169OhRL1/y48ePu3fvGhkZ7du3b+zYsWQymYODo/uVczEYjLq6+sGDB+Pj42NiYmpqahi7Lv/EqrsAtAMVCQDgN+Dm5lZZWenu7s7uRIY0TU1NHR0dOzs75iov3WOEsU7K+fDhw6tXrxBCdDq9XfCrV68kJSVTUlKYLaqqqmJiYuXl5einVt0FoB2oSAAAQ93nz5+PHz/u4eHR+82E/1gnTpwoKCjw8/PrTfDIkSPHjBkTHh6enp5Oo9EePHigp6dnYGCAEEpISGg3lURZWZmDg2PdunVv376l0WgVFRXHjh3Ly8vbsGEDI6BPq+4C0BFUJACAoW7r1q2ysrJWVlbsTuQ3IC0tvWPHjoMHDxYUFPQYjMViw8LCZGRkGHc7Tp06df36dXd39wkTJujo6Ozbt481mIuL682bN0pKSgYGBjw8POPHjw8PD79+/TrzsZ0+rboLQEeYjrfmAABg6AgLC1u1atWLFy/mzJnD7lx+D42NjZMnT1ZSUgoJCWF3LgD0AVQkAIChq6GhQV5eXkND48qVK+zO5XcSERGhra39/PnzefPmsTsXAHoLKhIAwFBRVlYmICCAwWCYLXv27Dlx4kRWVpa4uDgbE/sdaWlpffv27f3793g8nt25ANArMI8EADBUeHp6qqurp6amMn78+vXr0aNH3dzcoBz5CX5+ftnZ2adOnWJ3IgD0FtwjAQAMFWpqanFxcRgMxtra2s3NzcTEBP7K/xV79+718/ODO0zgdwEVCQBgSGhra6NQKA0NDQghDg4OTk7Otra2u3fvzp8/n92p/a4aGhomTpyorq4Os3DAbwFGbQAAQ8KHDx8Y5QhCqKWlhUql1tfXOzg4wD5tP42Tk9PHxyc4OJix6BkAQxxUJACAISExMRGL/c+/SHQ6PT09XVVV1dTUtLS0lF2J/db09PSWLFliY2PT0tLC7lwA6AFUJACAIeHdu3ccHBztGltaWuh0enBwsIaGRn19PVsS+92dOHHi8+fP/v7+7E4EgB5ARQIAGBJiY2Obmpo6tuPxeBkZmXv37nFxcQ1+VsOAjIzM9u3b9+zZU1hYyO5cAOgOzGwFALBfS0sLmUzuWJHgcLjZGbDxDAAAIABJREFUs2eHhYXx8vKyJbHhob6+Xl5efv78+ZcuXWJ3LgB0Ce6RAADYLz09vWM5gsFgLCwsHj9+DOXIL+Li4jpy5Mjly5djY2PZnQsAXYKKBADAfomJiTgcjvkjFovFYrF+fn4BAQGwGEm/MDQ01NTUtLa2brejb1FREbtSAqAdqEgAAOzH+qANHo8nk8lPnjyxtbVlb1bDjK+vb3p6ekBAAOPH0tJSc3Nz2PgGDB0wjwQAwH4KCgppaWkIITweLy4u/vDhQzk5OXYnNQw5OjpeunQpMzPz1q1bLi4udXV1dDq9qqpqxIgR7E4NAKhIAADs1tTURKFQmpubcTicurp6eHg4Hx8fu5ManqhU6tixYzk5OfPz89va2hiNL168mDt3LlvzAgAhGLUBALBdSkpKc3MzQmj9+vVPnz6FcmSAFBUV2dvbl5WV/fjxg1mOEAiExMRE9iYGAEP79YgAAH2SkpISFxeXkZFRWVnZ2NjI7nR+S1+/fsVgMIqKijU1NWvXrh2085JIJD4+Pnl5+ZkzZ06ZMmXQzjv4WlpaTp8+vXv37qamJjqdzrp+a0tLS3x8PBtzA4AJRm0A+BklJSX+/v6XLl3Mzc0bwU2ZOGEcPx8PiUhkd16/pZSMD8KCgmIiQoN8XlpjY0VldUbWpxpqrbS0lIXFhs2bNwsLCw9yGoNg06ZN58+f7+qolJRUbm7uYOYDQKegIgGgb5qbm0+ePOnmdoCIx68zWqmntXiawkQMBsPuvH5jNdTaEdwUdp2dTqcnpWaE3Xv89/XwxuZmV9d9tra2w+yRYxqNZmlpGRISwhysYYXBYMrKyvj5+Qc/MQBYQUUCQB+kpKSsXm2U8z3HfrO5k80mLk4SuzMC/aa+geZ9KuCYf+DIUSNDQ68Pv3EcPz+/7du3YzCYjnXJkydPFi1axJasAGCCma0A9FZERIS6+iwxQb7UV/f2OdlBOTLMcHGS9jnZpb66JybIp64+KyIigt0Z9bOtW7feu3ePRCK129EQJreCIQIqEgB6xd/ff+XKlUY6y+9dPT9SSoLd6YCBMlJK4t7V80Y6y1auXDn89stdtmxZbGyssLAw67BUS0tLQkICG7MCgAFGbQDoWUREhK6urqujjcu2zezOBQySQ8f93XxO3blzZ8WKFezOpZ8VFhZqaWmlpqYyH7oRFRWFnYEB20FFAkAPMjIy1NRU9ZZpBhxz768+lxiav0vNKM2Cpy6HNBvnA9fCIqKiooffnJLGxkYLC4vQ0FDmnJLi4uJh+ZwR+I3AqA0A3Wlubl61Sl9JYeLpw/t7DD5x/gpBXI75xTt26gS1xaZbHB8+ez3wmf4eEt+nGWywHTl1DmWkwgS1xbvcfai1dV0FHz1zkfX9ZH61tPy7V9ynr9+MNm4VkVPhGTNVYY6Wm8/J2rr6Tnuj1taNm7mIIC6XkfW5l9n6HtytrDh59WojxgJuwwmRSAwODt63bx8Gg2E8KQZTSQDbQUUCQHdOnDiR8z0n4Kg7Ht/b5QRDA443/fjQ9ONDfmp08BkfYUEBffMtumZWdfUNzJhHNwJ7eYOkoLCIIC6Xk1fwM9kPMW/iEufpmhDw+Nd3r/1Ij3F33uYfeHWZ8YZOH0lFCFXXUBFCJVnxjPeT+cXB8c8uwR8+fVVZrF9aVv48PDg/NWqvg/XRM5fWWm3vtDfHfZ7fc/P7lDAez3HxuGduTu7Jkyf79MLfAgaDcXV1vXHjBoFAQFCRgCEA1mwFoEslJSUHD7rZbzb/uamsFDLXdMXJ0xUnL1s0V9tkk+kWx7DLp/vayauY32xkJ/9H0ZUb4QnJaeF/n2l3aK+nr6AAf+DJwwQ8HiG0SntpYkr6Mf9LSakZ0xUnd+yqqqYGIUTh4urqXC4eR1taWm9cPCnIz4cQMtBempCcevzc5TdxiRozp7NGPoh8FRhye+VyzfD7T/p0OZLiotut1ru5HTAxMRnMQY3BXAtYQ0PjzZs3586dS09PH9AT/S64ublFRESmTJkyd+5cERERdqfzB4GKBIAunTlzhojHO9ls+sV+Fmio/mVmfOpi0Mvot3NnqaD/ziOpqKo+5Hsm4smLwqISbgpZacqkvQ7WylMVEEJaazY+eRmFEJJVWUgkEKjfUxBCL6LiDp84l/A+raWlVVpSfO0q7e1W5kQCgXEubZO/PmV/v3c1YMeBI9FvE1vb2ibLjT+ybwejQ4bE92luPqfiEpPpCE2aMM5561+L52kwj6ZkZLn5nIp+m1hbVy8uJrJy2SKXbZt5RnB3f41Nzc0Rj55dDg17+ipaREjQbqNZxxg9rcUiQgIElqc85MfJIIRy8go6r0iqqZwkEvOOSEcL56jNU5/JKEcYpilMRAh9y8ljrUjKK6usHPcYaC+dozajrxUJQsjJZtP5oBv+/v779u3r62v7irEWcMCFiz/y8whc3BTJCRguXsQx0GsBk7gmaJTlpD3/1tBz7J+gqaylKpbq7UNva52homqzxWr16tXtHpkGAwHeYgA6R6fTAy9dWme0sl/WHVmjv+LUxaCw+48ZFQkrEyv7zE9fQ88fV5wkV1RcusPtyGJD87ePb8uOGXXv2vmdbkd8zwZ+fhvJuE8THf9u+RpL3WWa6W8ejODmvvsocr3tztKyiqNuuxi94fH48opK0y2Oro62QWd8vufm61vYrLKw/Rj3hLHIfUJy6jxdk83ma04f3k8mcx3yPaNjahV2+cyyhXMQQu9S0uevNJ2vofo6IkRcVORVTPxfDnui3r579b9rXVUGaR8+Xg4Ju3b7bjWVunje7NuBp5bMn43DdRLcsUxJzczCYDDy42U77bm6poabQu7mXbW2MGnXUlBYjBAaPVKKtdHG+UBLS+txjz0/UY4ghLg4SeuMVgYGXhrQioSxFvC+A26tGDy/mtFk8+WUkQpoENcCbmtqwOKJCAND+f9oa2qo/hCVHXt7vbnFIa/DZ06dhB2SBxr88gHQudTU1Ny8PD2txf3S2yS5cQihj1++tWunNTY+j4pbMl9jppIiiUgcJS15wfcQkUBg3BrpKOLxcxKReHivk5iIMJmL01hvxWxV5Ss3wlljqmuo9pstli6YTebinDhB9i+z1YXFJWmZHxlHd7n7iIuJHHbdISUhxs/Lc2TfTgkxkXN/X2McddrvxcfLE3r++Lixoyn/x959RzWVdAEAn3RK6L2jIAIioggCimBFFEFBURALVmzYRUXUxYpdsXfdtWEF7F2ULlKk994hkARIz/dH/GIMASKEos7vcPYkMzfzbrYxvpl3R1JiygT7PdvWxSem3A9/3jqZhORUa8eZ5uOmPX3zYc2yBXnx7x9dPzNlwhiB0xE+VTV1R89eOX3lpv+65UYGegJjGhpJaDQ68HDwEHsn6X5mOkNHr/HfXd/Q2M6YJy/eGGQ4wMZiKLfx9sPwB+EvTuwLUFLofJX06VMmFhUVp6SkdHqE9iUnJxubmPpt85e18zY9EKM9Yxted0hPTkcAAEisOJyO8EJixeWGTND3OWca+L4GozZmzJjZHp5kMrm38/qTwX//IEiw6OhoaSk8ZxWg68RwOBQK1fq5EiwGo6woH/bibejzN3Q6AwAgLYWvSItu/ad/jgMBm+pzErQ01LgtulqajUQSoZHIGzbW1pr7mnOCXUVVDQCA3NT8KeaL9fChSOT3//aRSGRe/LvQf88DAIgkclR8ov3IEdw1IAAAZ0En7quAX8bJaZlfU9K2rV2e/vn5Ft9lQh6Vl1dYjFU30hoyas/R03u3rd+2dkVbkSw2i0ajSUhIvAy5VpL86dhu/wfhL60dZwp8PKe+odHNewWRRLp6Mog7JSqvrFrrv8d50riZzo7C5NYW8yEm0lL46OjorgzSlvDwcOuRo+rRiqaBH7SmbUJixbvjKlCnian0G7D6muGaf0Ofv7YeOaqkpKS3M/pjwRkJBAmWkZFhZKAvqiP0iCQyk8lUkJPla0cikY+un5WTlZm5aLWSocUkd++jZ6+0cxuAQqUeP3/NztlT28wWr2MqrmVy/e5DAACT+eOBWBQKxXshzuSDUwurqqaWzWYrKci1GhgAACqqqlks1q0HYbyP2uoMtQMAlJQLKJ9lZmJkMXTwvuNnB41yDAq+wJn0dEhPV5tWnlGVEXv1ZNDJizdGOc3im05xfQq/U54atXHFIlVlRRlpKVcnh1MHdhYUlRw+fYkvMr+w2NZpdlZuweMb58xMjLjtS9dvBwCcOrBLmMTagUAgjAz0MzMzuzhOa2fPnp02fbrMcBeDtTdxilodfwDqJXKmY423PSkiUM0tRqSlpfV2On8mOCOBIMHq6uqUFEV2GmpCcir4/75LPuZDTFI/PXv/+L+1y7yJ5KYtuw8Z2zgkpWYIHMdz2Xq/wIPj7UZ+eHyzKiOWVJC8YLab8GmgkEgAAJXWXnWNhZ4z+J62pZVn3Lss4PHXYaaDPj+5m/Q+3GnimBPnr+lZjHFdsPLp6w+806O2yMlIuziOf3jt9NeUtEPBF4TMf+IYWwQCEfc1mbcx+kviKKfZNDr9w+ObdjaW3PZrdx68+vD5dNAuVWVFIcdvh6KCXF1dXdfH4RUeHr5y1SoN5w395h1EoOCuvr4Op6hl5PeYLqM1afKU6urq3k7nDwRnJBAkGI1G41286KJrdx4iEIi21g4QCMRIS/Ndm32jnoVEhN8mksm7jwh4TriiqvrJq3cznR0DNqzsr6stKSGORqOKS3+hVImGmioSiayoEvw/U05vcWm58AMCAIwH6h/ataUw8eN/Z47Q6XQ375V6FuOOnr3CF1ZSVrF0/fb/7oXyNnJ2kGTk5LUelkanJ35Lzy0o4m2k0mhsNltM7MezJ7EJyVM8Futqa0Y+vTvI8Kcdst/SswEAnj7rufd7Vm35BwAwdKwzX5k1YYjhcBQK5Zc+0r60tDSPOV7KI901ndaIcFioW6HEpQasutpAR01ynNLcLLgWH9RpcEYCQd0u7MXbO4+eeHu4cfa38oqIjtcdZp+S/mM5wMrcTFVZqZ7QwHnLWXPhnPZApdIAALwPu2bm5EXExHMDOoTBoK2HD/0QGUvhKXExbJyLzWR3AABeUmLUCPOP0XGV1bXc3s+xCaZ2Tpx7PO3AYjCuTg7hNy/kxb9dMnfWpxj+cluKCnIhoU+DL93grYeW+C0dANBfR7v1gFQqzd5ljs/GAN7GF28/AgDsR1px3haVlE2ds8RAr9/LkKvKigp8IxwJ3Mp3p+fUgZ0AgMR3Ybxl1noFnU6f5joDp2Xab25QL6bxW6NUFWSfXRq/ZnDMMt3EbbZlz4IBW3Cpvc7FtwUtKau/8mp6Vs7u3bs7mzskGJyRQFB3odHpaZk5m3YdmL10jYvj+BP7AlrHDDcbjEajFvpujfuaQqFS6xsaj5+/Vlpe6e3xfS1GXVUZABCXmEKhUtXVVPrpaD1+/iYtM4dCpT5/GzFzka+b0yQAwJekVGHWSgAAe/3XUyjU+as2V9XUNRBJO4NOpGZkL503i9O7z38jComaNs8nKzefQqV+jIrz9vXDYTF8tx/aoaGm6r9ueevyaOJiYkE7Nid+S/fZuKOopKy5hfIp5suyDQGy0lKrFn3fxvv2UzRW3cgv8CAAQAovuWPjqojo+I0795dVVDYSSffDnm/Ysd/U2HDJ3O/ZrvHfTaHS7lw43v5Dwn3QyZMnC4sKdecf7q3FGhqhInqRBrX2d92kSW+sTt3vwmgmDd7+xPJ0ts7M7WVPgvNv+osqvn3iavrq0zYdPnI0Ozu7s98AEgCuXEKQiM1eupbzgrPD1GKo6Z0LJ5wnjRMYLCEu9uHxzcDDp2YvXVNdUycthR+o3//WuaMz/r++M2eGy6Onr7x9/aTx+LhXD+9dPrk+YJ/t1NloFMpq+NBb54/iJSSSUjPcvFdsWrnkH7+O7//bWAx7df/aP4eCB42axGazjQz07lw4zn3I2XKY6cewW3uOnrFz9iSSySpKSu4ujn6+yzi1TPicuXpzrb/g0wdNjQ2/vHnE17hsvoeKkmLwpRvm46fRaHRNdVXLYUP81y3nKx/CtWHFon7amsGX/rWY4EokkXW0NBbNmbl59VJOhZjmFsqzNx8BAAZWE/g+6O3hdv6IyI5FFLnq6updgbtVJ/r04lbWxsyo3rq0SJSGH2dSmwyWnUHj5QAA8kMdNKauKX6wX23cInE1/a7Hd0jFfm5dxH/rNmx8Gh7Wxe8CccGzfyFIMHd3dxaFdPv8sd5OBOoTPJatQ4pJhYSEdH2oXbt2HTx+2vRATFce9G0qTisNO0LMjmVSm7CyagrmjppT16HEv5fWzTg+l1KVZ7T2ZmFIICk7ls1mSWga6c7aie9nBgDIODanIfUDJxKJxo44X5BxbA6lutBgxcXcS6splfmWZ3MRSBQpN740/AQ5P4FJbcbKqMiZTdBy2cj5jQ4ASAtypdSWGK6+WnhnF7kwGbDZUnrDdGbtktQyBgCkBbmRC5OHH03kpgQAKHsWXPzggNH6W7KD7Dr9xTni15jg+w01Wvsvt4VSlZ+4zVZr+maB+3J+NV4YhJR3mSfmpqamDhokmhoBELxHAkEQ1HPYbPbFy1fkbWZ1ZTpCLkxOC3KVMbI12RaGlVMlZkbnXdtAzI412RaKQKIBAEg0hk6qz7mwUtNlo8HS05Ta4qxTC7NOLRx6IBqJwRmtu1kUElj+8vywoBjOfRoEGsuiNhfe2i5v5oCVU0MgkI0ZkRlHPeXNHQdvf4qRVWkqTMm5sJKYHTN4+zMkBsf5CINUl3dlna5HIL6fGaW6KPPEvPTD7kP3RqDx8ip2c4jZMbVxoSp2Pyrr1MaG4uQ1ZI1t+b4Og1wfv0bAMQIcZns+8t3GoNWXM8gECfWfVhLFlHURKHRToYDCOb8aLyS5wWPwqrpXr149fPhwpweBeMF9JBAEQT0nJSWlvLREfviUrgxSdPcftKSswYoL4qp6KJyk3JDx2m5byQVJdfHh3BhmC0ndwUfOdCwSJyGhYahiP5/WUNVcKvipcgQCQSfVy5k5aE3frGI/FyAQxff3oiVl9BedEFPpj8JJSg+01p6xrbk0sy7u+9NSCCSKRaeqO66QHmiNxIpLaBrqzNzOIBOqI+8BAOSHO6HxctWfbnMv0VKR21yaoTRqVuvKsGi8vPXlsrZ+Wq+q0Ig1nE/9/B2QaEk5OlFAUZxfjRcWAiE9dPLDULhqIzJwRgJBENRzoqOjsRJSeB3TjkPbwGwhEXPiZQxHItE/nk6XNRkDACDnJ/JGyvDcjcDKKgMAaA2VbQ3LZjEULZ05rxnNjeTCZOmB1pzbIf8fbTQAoDEzkvdTsoPsua+lDW0AAM2l6QAAJBqrZDODXJDUXPb9ObLauMcAgVAeNevXvq0gLBqFcwm+dgQaw6IJOCzwV+OFJ2NoU5CbU19f35VBIC64agNBENRzMjIyJDUMunJmDa2hCrBZNdEPaqIf8HVR63/UkkEgUdw9H5z3AAB2Ow9kIRAYGeXvlyBUAACwsiq8/VhpRQAAjfBjToNAoXkvgcbLAgDoxO+PjquM9qp4dbH68x3dWbsAAHVxYTJGtjgFTaG/aJtQOHEAAItB42tnM2gC18J+NV54EhqGAIDMzEwbG5uujANxwBkJBEFQz6mrq0Pi+UundILyaE+9+Ye6Pg4XAoFEIH+q0cL33MP3tzxzKQTf+gsn/P+N4mr60gZWtdEPdWZuby7NbKnM03TZIJJUMTIqAAA66acSumwWg0FuwBrwn63diXjhoaUUAAC1tbUdRkLCgDMSCIKgnkOj0QCqS7WAsfJqAIGk1paKKqXWcPIaAIGgN1TxNtIbqwEAOHl1bguLQWO2kLhP0zDI9QAAjPSPmv0q9l45F1Y1pkU0ZkSiJWXlhwmuWfyrO1uxsioYGeWW8p9qgbSU57JZDLyuWesRfjVeeJyVINEW8/2bwX0kEAR1o9yCotlL16qb2OB1TDkH8vHWbG3ta0qas9cyJUNLKd0h5uOmXbvDvzDRYQAAgEane/v6YdWNWhez/wOgcJLSBiOIWVGcKQIHMTs2abs9uTC5nQ/+5PudDMHVH1DiUlJ65o1ZUZwdGBycB4Z5N44AABrSIrivOTVOZAb+OHda3nwKGi9XE/2wNvaRopVr650cHL+6sxUAoDhiGjErmve2R218KAKJVhjhIvASvxoP9Qo4I4GgvqusohKrblRU8gsn1/QpldW1ds6eRCIp8undupwvBwI2Bp08v6aNomoAgNDnb2wmu0tKSsS8uF+ZHjPXfZrPxh28s4oOAwAAhEbiFI/F+YW/azVSYejM8EcgURkn5rdU5LLoVGJWdO7lNUgMlrOtQRhYOVUAACk/kUWnslkMAZeYuZ1JIedeXUetLWZSmxrTPxU/OiilbyE/fDI3BokVKw0/1pgewaK1NJdmFN3fi5FRVrCY+iMAjVWymVkbF0prqFK29ejal/6J5hRfNF4+55wPpbqQRafWxoVWvDinOXUNTl6DE9CY/il6kUZRSKCQ8VBfAFdtIKjv+hgV19spdMm+42fITc3/nj2iICcLAJjqMG7r2uXb9x1dtchroH7/1vFb9xxWU1G+FhzEOeNw7bIFGdm5gYeDF3i4ycvKCBNAaCTaOXvOmOrgMGa07dTZPfptexC+/1CTraGl4cdS97swW8gYGSVFS2eNKb68j8a0T8l6Rn3Cs9xLvihxKdOdL1sHSOlbDPJ7WPr4cPKuiSxaC05BQ9lmpubUtZx6JxwIFEZ/4bGikEByQTKbzZLSH97PczffXlEVO6+KVxckdQZzKqeJChovZ7IttPjBgW97pzIpJHEVPV2PQBX7uaKKh3oFnJFAUDdKTssMPHwqMvYLualZXU1l+uQJ29Yul5H+vu7u7LUsO7/wyc0Lm/85GBn7hcliDTYaeHDnZouhpgAAJ88lrz58BgAMGDEeh8WSCpOdPJfkFRbfvXRiwWq/nLzChryvKBQqKv7r/uPnYhOSmlpaVJWVnCaO2bFxNWcGAAAYO92rsKTs4bUzG3fuT0hOZbPZI8zNDu3yMzU2BACMc52bkJxanPRJWgrPzTko+ELA/mNPb1+aYDeyi1//XuhzOxtLbjIAgGmO4/33Hnnw5OW2tcv5ggmNxNyCohnOjrxHLs9wdrx6+8HzNx/nzHDuMAAAUF1T67tk3mIv99gEodcvfk+SOoMHrmpzTap1l6Kli6LljxUKtKTsIL+H7cQDAKT6DzNaf6u9JFgsSZ3BxpvutRPCZtIBAKpj5rc3Tqfg5DUGLAluq1fG2Nb6cpnw8VBfAFdtIKi7JCSnjp7qwWKxIsJvV6bHHNvtf/N+2GSPxQzG9ycwMRhMXT1h7oqNS+bOyk/48DH0VkV1zYyFqzkH8z65dXGdjzcAICf2DakwGQCAxWKbW1rW+u9xdhh3JHArEol8/zlmvNs8KSl85LOQqvTYKycOPH72ZsKM+dyjfXFYbG0dYfHabQEbVpV9i/r85G5uQZHDTO/aegIAYLGXe3ML5e7jp7xphzx+pqWhNs7WGvystp6AVTdq6ycrN58vvrS8so7QYGSgx9uop6uNwaC/pqS1/tvFeZSD76FYzp0PztnIHQYAAAbq91/s5d7GPxBIxNhtbEPhVf7iLEZGWdHKtQfygX53cEYCQd1l064DcrIydy4eN9Drh5eUmDLBfs+2dfGJKffDn3NjGomk9csXOo4bLSkhPshwwLJ5syuqqr+lZwkcEIFA1NTVT3UYt2uz79J5sxEIxLa9R+RkZK6c2D+gvy5eUsLOxnKf/4bUjOyQx884H0GhUBQqdePKRXY2lhLiYiZGBgcCNtURGv4NeQwAcHVyUJCTvXbnx5+Vs3Lzv2VkLZjtikTy/89BUV6OVp7R1k/rVZiqmloAgIK8HG8jEomUl5WprqkDrcjLyujpakfFJ9LodG5jZNxXAEB1bZ0wAVDfwWYxWbSWilcXa6Lu9/PcLfxyEvQ3gzMSCOoWRBI5Kj7RfuQI3iUGhzG2AIC4rz8dpTGW526EmooSAKCiqs3K1gwG093l+yOUhEZiQnLqaBtL3oN5OaN9iIrl/dQE+1Hc13Y2lgCAbxlZAAAcFus10yU+MSUtM4fTe/fxUwQCMX+WCP5E20KhAgCwGAxfOwaDaW4R/LRk0I7NZRWVC1b75RcWNxJJN+4+On/9NgCATmcIGQD1EXXxYbErDMpfnddffFJhuFNvpwP9HuCMBIK6RUVVNYvFuvUgjHdpQ2eoHQCgpLyCG4ZCoXi3WXDuTDAYbf5+RSAQqspKnNflFVUAALX/v+VQUVLgdnFgMGjeS8jLygIAuHcpOGsc3GdoQ0Kfj7O11tb8UXOi0yTExQAAvPczOGg0OqerNedJ48L+O5+TV2Bq5zTQasKL95/uXDwOAJDCSwoZAPUYo3U3R5zJaatXccR060sl5oe/KFm79WRW0G8N7myFoG600HPGucO7RTggEolEoTourIngKayJ/LmwJieAuygzUL+/rdXwWw/C92/flJqZnZ1XsGPjKpGkyrnfU1v305EfDAazvqFhlNXwtj41aezoSWNHc99ybt7009ESPgCCoN8UnJFAULfQUFNFIpHFpeUdh3aWproqAoEor6rmbaysrgEAaKqrcVuoNFojkcR9wKeO0AAAUFb6Uch8ydxZ81ZuehMR+SEyVl5WxsVxvMDL1dYT1E3aPLzjW8RTvq0kairKqsqK6Vm5vI2ZOXkMBnO4WZsFOvlEf0kEAIy0HNbpAEiEMo7NIebEtXNrBIK6Aq7aQFC3wEtKjBph/jE6rrL6x5kXn2MTTO2cEpJThRyEcyeD7y4Il4y0lJW5WURUXAtPEetXHyIBABPHjOKNfBsRxX39MSoWADDayoLbMn3KRAU52VsPwm8/fOLhOpV34wuvX93ZCgCYPd0pIjq+huc2yb2w52g0apbL5NbBAICNO/cb2ThwN4WwWKxL/4UYDtAbV0ntAAAgAElEQVSzsRgmZAD0V2Ez6LmX1kQv0ih/ea51b0tlXvaZpfGrjWOX6yVtty8JPcykNv3SCFAPgzMSCOou+/w3opCoafN8snLzKVTqx6g4b18/HBYzyHCAkCOoqyoDAOISUyhUKveZYV77AzaSyE2L124rLC4lNzW//RS9M+i4jcWw6ZMncmPExcT2Hjv7JiKquYXyLSNr657DqsqKM5x/nDCCw2Lnuk8LCX1WUVXt7SnKVX8/32UK8nJzfNbnFRZTqNSQ0GdHz17Zuma5lsb3WzhvP0Vj1Y38Ag9y3k4cY1tQXOq7LbCO0FBZXbt80460zJxzhwO5i1AdBkB/D0ZzY/pRD0pNocDelvLslMBJdFLtoC0Phx9L1nJeX/7ibM45H+FHgHoenJFAUHexHGb6MeyWhpqqnbOn/ADzBav9XKdMfHnvGu+jMe2bM8Nl1Ahzb1+/fsPsK35eneGwsRj29uG/DY1Ei4muKsYjVvrtmjtz2tPbl9DoH3tNsFjMpeP7DgZf0DQdaes0e6Bev1f3rvHtLV3s5c5isYYONuZUThMVBTnZiLBbairKtk6zFQ0s9p84dyRwa8CGlW3FT7Qfde/yyW8ZWQMsx5nYOpZXVn8Ivcl7/6PDAL/Ag5xNxJyCrVt2H+K8nb9qswi/F9TrGM2NqftcpAda6czaKTCg6P4+wGQMXHlJQsMQJYZXsHRWsZ9HSHlHzI4RcgSo58F9JBDUjYYONn5w9VRbva273F0mu/OsaMjLyrx79F878QCAEeZDnt6+1E4OTCZz6GDjV/eutRPDWQfxWeDZTkznaGmoXT91sK3ecbbWtPIM3papDuOmOoxrZ8D2A4J2bA7a8edMPhhNDaXhxwlJr2gNlSgxvKTuEC2XDfh+P46rbcyILHt6klyQxGYxcAqaStZuag4+3APtMo7PpVTlDVx5ueBWALkwGYlCyw2Z0M9rX0PKu7JnwS1V+RhpZbUJi9XGL+LEpwW5UmpLDFdfLbyzi1yYDNhsKb1hOrN2tVUAvqk4rTTsCDE7lkltwsqqKZg7ak5d9+Mo4I6S7wp6Y43ahMUqdl6k/K8CA2QHjZYxGonGy3Nb8LqmAABqTTEwsBJmBKjnwRkJBP3h2tqGwuvI2cuqyooerrBuRN+SfW55S0W2wfILktom9Maqwru70w+5m+58IabSHwBAyonLOOopb+5otjcCLS5Vn/gi55IvnVin6/EP5+NINIZOqs//d6vurJ3iGgZV728U3dtDrS9HYnADV11GScgW3tpeeHuHVP9h+P5DAQAINJZBqsu7sk7XIxDfz4xSXZR5Yl76YfeheyN4f7VzkAuT04JcZYxsTbaFYeVUiZnRedc2ELNjTbaFcs6+aT95XgxyffyaNjc7m+352Pr4X3E1fYFnAnOpjlvI10IjVAIAcEraQo4A9Ty4agNBfy8mk9ncQjlx4fp/90KP7fYXfjkJ6gEsOrUx47Ps4LFSeuZIDA6nqK2/8CgCg21I/cAJqE98icTgdNwDsLIqSJyEopWrtIFVdeRd3kGYLSSNKavx/YeicJJqE5egcJKk3Hi9hcdwitpoCWl1xxUAgMbMz5xgBBLFolPVHVdID7RGYsUlNA11Zm5nkAnVkQJOrim6+w9aUtZgxQVxVT0UTlJuyHhtt63kgqS6+HBhkueFxstbXy5r60ck8wY6sabi9UUJDUMpfYuOo6FeAmckEPT3uhf2XH6A+fHz164FB7lNndTb6UA/QaIxGGnF+q8v6r8+ZzMZAACUuJTFiVTun/513AMsz2Tj5DW4HxFT0ma2kBjNjbzjSA+w5LxAINFoSVmcohZWRpnTgpFWAgDQG3+qESw7yP7HZw1tAADNpel8uTFbSMSceBnDkdwVIgCArMkYAAA5P1GY5HsSo6khM9ib0ULSX3wCgUR1/AGol8BVGwj6kz25dbGd3tnTnWZPhys1fRUCaeh7LefCqqzTi5FYcSk9c9nBY5RHzUZLfq/Ay6JTq95fr0t4SqkpZjQRAIvFZjEBAIDF5BkDxd3YAQAACAT34+D/lfTYvPEoNBr/4ygiNF4WAEAn/niCnYPWUAXYrJroBzXRD/i6qPXlwiTfYyjVRRnHvejEGqM1NyS1TXr46tAvgTMSCIKgPgqvO2To3ghSbnxD6oeGtI9FIbvLngYbb7zL+c2afc6HkPxay3m9opUbVkYJgcHmX/er/nynK1dE/Fzh9/vhvgjBd9OVR3vqzT/UueR7Bin3S2awN0pM0mTrYwkNUT5HBnUHOCOBoL+Rk+eSyLgEQi58yqDPQyCkBlhKDbDUmr6ZlJeQdsC1NOzowFVXaA1VhKRXipYums7rubHUutIuXo3FoDFbSD+elyHXAwAw0op8YVh5NYBAUms7ulwbyfNFdWJnqzBI+V8zjnqKqw8w9L3e+itAfRCckUAQ1Muy8woCDhz/8DmGQqXpaGnMmOqwfvkivKQEN+BL0reg4AtxX1Pq6gmaGmrTJ0/Ytna5wNP1SOQm8/HTCotLE9+FCV+Jrm8iZkXnXFxluOZf7sO3UnrmGFllOpkAAGAzqAAA3kdgWipyiFkxQLinq9rRkBahMHwK53VjZhQAQGagNV8MCicpbTCCmBVFb6zG/H9XCjE7Nv+Gn/7iE3jdIe0nz4ezs7UrObdGrS3JPDZHTFXPeONdlBhetIND3QTubIUgqDdlZOeNcHCrqa179+i/0pTPARtWHjlzZY7POm7Ap5gvY6Z5YTGYiLBb5alRe7asPXv15mSPRSwWq/VoG3fuLyzu6n2CPgLfzwyBROddXkPOT2TRqYymhopXF2j15Sq2HgAAnIKmmJJOfeLz5rJMFp1KSHmXdXqxgoUTAIBckMy7NeSXILFipeHHGtMjWLSW5tKMovt7MTLKChZTW0fqzPBHIFEZJ+a3VOSy6FRiVnTu5TVIDJazONJ+8j2g4KY/i04duOI8nI78RuA9EgiCetO2vUcYDGbI5WBFeTkAwExnx/jElOPnr32K+WJrNRwAELD/mKKC/NXgICwGAwCY4ez4JTn16NkrX1PS+E7se/bm49XbD6ZPmfjo6ate+S6ihcSKm2x5VBJ6JOvsUjqxBiUmJa6mb+Bz7vv8AIE0WHmp8PaO1L3OCBQKrzfcwOccEifRVJyaFeytPnmF9nS/TlwUgcLoLzxWFBJILkhms1lS+sP7ee5GYsVbR+L7DzXZGloafix1vwuzhYyRUVK0dNaY4ovE4DpOvsuKQgLLX57nebu7KGQ3AEDRynXAkmAWrYWQ8hYA8NWP/+6Osq2H3oLDHY4gkiShXwVnJBDUE+obGvcdOxP+6n1FZbUUXtJ8iEnAhpUWQ025Ae8/xwSdPB+f9I3BYGprqs+Z4bzOx5t76J2z17Ls/MJ7l0+uD9j3JekbBo2ePGFM8P4dL95FBJ28kJNfqKKs6Ltk3qpFcznxY6d7FZaUPbx2ZuPO/QnJqWw2e4S52aFdfm0ViU9Oyww8fCoy9gu5qVldTYWzLMI9LrjD5LtivJ3NmFFWnOkIxzDTQQCAgqISzozE1clBRUmBMx3hMDbQBwAUlZTxzkjqCA0+G7fPdHa0s7H8M2YkAACsvLqe95G2eiW1jAdtvs/XaLbnI/d16x0bww7G8r4VsFzCYknqDDbeJKAACQDAaN3NnxLQGdz6EkIm30U67jt03He01YvEine4DNT+CFCvgKs2ENQTvHzW3w9/ef3UwerM2Mind8XEcA7u3jn5hZzeyLiEKZ6L5eXlUj89K0+N2rbWZ2fQiW17fvzfHIPB1NUTVm8J3LttQ0nyZz/fZbcehE2fv/z6nYf3rwQXJUXYWAxbH7Av7msKJx6HxdbWERav3RawYVXZt6jPT+7mFhQ5zPSurRewip+QnDp6qgeLxYoIv12ZHnNst//N+2GTPRZzz/ZrP3letfUEzjkyAn+ycvNbf2TlQi/fJfN4W8oqqgAA/XS0OG99l8ybNW0Kb0BKeiYCgTAe+NM2kVVb/mEwmMf3bm/7HwLUMTbo0h4UCOoKOCOBoG5HoVLffY6ZNNbWytxMDIfT1da8dGwfDot99eF7rczwl+/EcLiggE1qKsqSEuIerlNHW1vcCHnEO0gjkbR59VLLYaZ4SYk1SxfgJSWivyRePLZPV1tTVlpq08rFAID3kd9PEUOhUBQqdePKRXY2lhLiYiZGBgcCNtURGv4Nedw6vU27DsjJyty5eNxArx9eUmLKBPs929bFJ6bcD38uTPK8FOXlaOUZbf0M1OcvH95aVU3dyYs3BhkOsLEYKrD36Nkrp6/c9F+33MhAj9t++2H4g/AXJ/YFKCnwFzuHIOh3AVdtIKjbYTEYZUX5sBdvHcfZTR5vj8GgpaXwFWnR3IADAZsOBGzi/YiulubHqDhCI1FORprbONLy+yG3aDRKTlYGh8WqqShxWpSVFAAAVdU/VbKaYD+K+9rOxhIA8C0jiy83IokcFZ84e7oTd4UIAOAwxhYAEPc1ZfZ0pw6TF6H6hkY37xVEEin033Mo1E+1NfMKi41sHAAAeEmJvdvW+y6Zz+0qr6xa67/HedK4mc6O3ZEVBEE9A85IIKjbIZHIR9fPzlu5aeai1RLiYlbmZhPH2C7wcJOXleEEUKjUc9duP3r6qqC4pJ7QyGSxmEwmAIDzVw4UCsXd2AEAQCAQ8nIyvG8BAEyeJywwGLSC3I/6mPKysgCA6po6vtwqqqpZLNatB2G3HoTxdZWUVwiTvKjkFxZP9VpWXVv3+MY5MxMjvl49XW1aeQahkRgRFbfGf09I6LPnd69wpmtL128HAJw6sEu0+fyF+LaJQFAPg6s2ENQTzIeYpH569v7xf2uXeRPJTVt2HzK2cUhKzeD0ei5b7xd4cLzdyA+Pb1ZlxJIKkhfMduviFZE/19nk1KhAIgX/J7/Qc0brRZZ7l4OFSV4kor8kjnKaTaPTPzy+ybmdI5CcjLSL4/iH105/TUk7FHwBAHDtzoNXHz6fDtqlqgxLYEHQ7w3eI4GgHoJAIEZamo+0NN+12TcmIWnsdK/dR04/uHqqoqr6yat37i6TAzas5AYXl3a1YBSVRmskkri3VeoIDeD/izu8NNRUkUhkcWl555LnC6utJ6ib2LQ1yLeIpwK3ksQmJE/xWGw4QO/xjbPKij9lWFJWsfvI6dHWFl4zXbiNnB0kGTl5AIBv6dkAAE+f9Z4+63k/OHSsMwCguTgVjf4bT1bLODaHmBM34kxObycCAAA5F1fXxjzkvB4WFINT1OrdfNqX5D+6pTIPAIDGy1mcSO3tdP4u8B4JBHW7iOh43WH2KemZ3BYrczNVZaV6QgMAgEqlAQB4H3/NzMmLiIkHXS6++TYiivv6Y1QsAGC0Ff9R7HhJiVEjzD9Gx1Xy7EH5HJtgaueUkJzaYfJ8OrGztaikbOqcJQZ6/V6GXOWbjgAAFBXkQkKfBl+6wVsPLfFbOgCgv442AOBI4Fa+q5w6sBMAkPgujFae8XdOR/ogJBprfbnM+nIZZzpCqSrIPrs0fs3gmGW6idtsy54FA7aAenftYDPouZfWRC/SKH95rnVvS2Ve9pml8auNY5frJW23Lwk9zKQ2CTmC2d4I68tl8kMdfvErQiIAZyQQ1O2Gmw1Go1ELfbfGfU2hUKn1DY3Hz18rLa/09nADAGhrqvfT0Xr8/E1aZg6FSn3+NmLmIl83p0kAgC9JqbxbSX6JuJjY3mNn30RENbdQvmVkbd1zWFVZcYagvZ/7/DeikKhp83yycvMpVOrHqDhvXz8cFsOpwt5+8l23xn83hUq7c+G4wKrw4mJiQTs2J35L99m4o6ikrLmF8inmy7INAbLSUqsWeYkkAaiH0RurU/e7MJpJg7c/sTydrTNze9mT4Pyb/sKPwGhuTD/qQakpFNjbUp6dEjiJTqodtOXh8GPJWs7ry1+czTnnI/wIUG+BqzYQ1O0kxMU+PL4ZePjU7KVrqmvqpKXwA/X73zp3lDM/QCKRnNJntlNno1Eoq+FDb50/ipeQSErNcPNesWnlkn/81nTiolgs5tLxfX6BB78kfWOxWNbDhx7b4y8hLtY60nKY6cewW3uOnrFz9iSSySpKSu4ujn6+y8RwuA6T76LmFsqzNx8BAAZWE/i6vD3czh/ZAwBYNt9DRUkx+NIN8/HTaDS6prqq5bAh/uuWcwuWQL+X0vDjTGqTwbIzaLwcAEB+qIPG1DXFD/arjVskzIl6jObG1H0uChZOsoPHpu4VUAG26P4+wGQMXHmJc+iPgqUzqSCx4tUFYnaMtIGVMCNAvQXOSCCoJ2iqq144uqetXlNjwzcPbvA1fot4yn3desdGbtxb3rec5RLeFiaTOXSw8at71wRe8cmti7xvhw42bn0JIZPvCglxMb60BZo2ecK0yfxTlrYsnTd76bzZXcurl6UFuZILk4cfT0Hhftw3Kn4YVPb05KDN96UHWgMAGjMiy56eJBcksVkMnIKmkrWbmoMPEo1tPVrq/mmU6sLhx5K4LZXvrhbc3M4dCgDQVJxWGnaEmB3LpDZhZdUUzB01p67jngAsWrXxYdIDbTjTEQ6FYY7F9/fVJTzVdOp48k1vrFGbsFjFzouUL/jkatlBo2WMRvKeQYjXNQUAUGuKgYGVMCNAvQXOSCDoz9TFPShQL1KynkHMjiUkvVYcMY3bWBcXilPU5vwpn5QTl3HUU97c0WxvBFpcqj7xRc4lXzqxTtfjn05cjlyYnBbkKmNka7ItDCunSsyMzru2gZgda7ItFIHk/x3BINfHrxkscBwAgNmej+3f56DVlzPIBAn1n+rtiinrIlDopsIUYbIVV9Nv/xKq4xbyX5RQCQDAKWkLOQLUW+CMBIIgqG9RsJhacGt7XXwYd0ZCyv9KqSnSctkAEAgAQH3iSyQGp+MegJVVAQAoWrlWRdyqjrzbuRlJ0d1/0JKyBisucG6xyA0Zr+22Ne/qhrr4cMUR0/mCBRyF8ytoxBrOID+1IpBoSTk6sabTw7aDTqypeH1RQsNQSp9/WzfU18CdrRAEQX0LSlxKzmxiw7f3zBYSp6U25hFAIJRsZnDe6rgHWJ7JxslrcD8ipqTNbCExmht/9VrMFhIxJ17GcCTvio+syRgAADk/sUtfQxAWjQIAaL26hEBjWLQWkV+O0dSQGezNaCHpLz6BQMIHr/o6eI8Egv5AfNtEoN+Oks3Muvjw+sSXSjYz2CxmXXy4tIEVTvH7ugOLTq16f70u4SmlppjRRAAsFptTrpf1y09m0RqqAJtVE/2gJvoBXxe1voMqNZ2AwokDAFgMGl87m0FDYsVFey1KdVHGcS86scZozQ1JbRPRDg51BzgjgSAI6nNkTeww0op18WFKNjOImZF0Yo3OzB/Px2af8yEkv9ZyXq9o5YaVUUJgsPnX/ao/3+n05ZRHe+rNPySKxDuAkVEBANBJP51mwGYxGOQGrMEIEV6IlPslM9gbJSZpsvWxhIahCEeGug+ckUBQb3LyXBIZl0DI7RN7/uev2nz7YTjndU7sGx0tjfbjf3cmtpOz8woAAApyst10dmCnIZBoRctple+vMZqJtbGPUThJBfMpnC5aQxUh6ZWipYum848ytdS60raHQrF/vndCb/yxYwMrrwYQSGptmx/n08WdrVhZFYyMckt5Nm9jS3kum8XA65oJmUOHSPlfM456iqsPMPS9jpGGxwv8NuA+EgiCfsBhsZzKp9zpCI1O9/b1w6obHT17pXX8l6RvMxet1hlqh9cxNbRx2LrnMIn8U3HM3IKi2UvXqpvY4HVMB41yDAq+wFt9VRjtJyD8+CRyk4HVBKy6UVrm99rqqZ+e0cozpjqM+6V8eoySzQw2k0FIflX/9YX88ClInASnnc2ggp83h7ZU5BCzYkAbD1hhpBUZTQ0sOpXb0pjxmfsahZOUNhhBzIqiN1ZzG4nZsUnb7cmFya1H4+xsbetHmGdYFEdMI2ZF894mqY0PRSDRCiNc2vmU8Ki1JZnH5oip6hlvvAunI78XOCOBIKhNhEbiFI/F+YUlAns/xXwZM80Li8FEhN0qT43as2Xt2as3J3ss4s4JKqtr7Zw9iURS5NO7dTlfDgRsDDp5fo3/L5Q2aT+BXxp/4879hcXC3gnoCyR1BkuoDywNO8poblQe6c5txyloiinp1Cc+by7LZNGphJR3WacXK1g4AQDIBcnsVltJZAePBWxWadhRZguJ3lhdePcfxv83zHLozPBHIFEZJ+a3VOSy6FRiVnTu5TVIDLabFjs0p/ii8fI553wo1YUsOrU2LrTixTnNqWu4G3VJOXHRizQKfqWKK6+Cm/4sOnXgivMoMbzosoZ6Aly1gSBIMEIj0c7Zc8ZUB4cxo22nCqg5FrD/mKKC/NXgICwGAwCY4ez4JTn16NkrX1PShpsNBgDsO36G3NT879kjCnKyAICpDuO2rl2+fd/RVYu8BJ5x86sJCD/+szcfr95+MH3KxEdPX3Xqb0bvULRxK76/j1uG5DsE0mDlpcLbO1L3OiNQKLzecAOfc0icRFNxalawt/rkFdrT/XgHUbKZQa0rqYm6X/HqAkZWVcVujrarX9apRdy7Jvj+Q022hpaGH0vd78JsIWNklBQtnTWm+CIxuO74Umi8nMm20OIHB77tncqkkMRV9HQ9AlXs5/KFtS6FwlEUElj+8jzP291FIbsBAIpWrgOWBLNoLYSUtwCAr37WfB9UtvXQW3C4wxFE8A2hzoIzEgjqvLHTvRKS08q+ReIlJbiNOw4cP3Dy/JsHN0ZbWwAA3n+OCTp5Pj7pG4PB1NZUnzPDeZ2PNw4roLamvcucvMKikuQfd9TPXL251n/P6/vX7WwsOS3JaZmBh09Fxn4hNzWrq6lMnzxh29rl3AN+Rau6ptZ3ybzFXu6xCQLu3gMAXJ0cVJQUONMRDmMDfQBAUUkZZ0ZyL/S5nY0lZ7rAMc1xvP/eIw+evNy2dnnXExBy/DpCg8/G7TOdHe1sLH+vGYmG40oNx5Wt2yW1jAdtvs/XaLbnI/e10bqb3NcIJErLZaOWy0beYL6aIpI6gweuErAo1k1w8hrt/O6XGmCpPmk5WlJWYK+O+w4d9x1tfRaJFe+wXEr7I0C9CM5IIKjzvGZO+xyb8PT1+1nTpnAb74Y+09XWtLUaDgCIjEuY4rl42uSJqZ+eSUtJhb14s2C1X01t/ZHArZ24XEJy6tjpc8faWkeE31ZXVfkYFbdsw/bPsQkfQ2+1PuS2tp6gbmLT1lDfIp52eJdioH7/9mN8l8zja0lJz0QgEMYDBwAASssr6wgNRgZ6vAF6utoYDPprSlr7lxYmAeHHX7XlHwaDeXzv9t9rOvLXYjQ31sY+HrTpXm8nAvU0uI8EgjrPzclBDIcLCX3ObYlNSC4oKpk7cxoCgQAAhL98J4bDBQVsUlNRlpQQ93CdOtra4kbIo85dbtOuA3KyMncuHjfQ64eXlJgywX7PtnXxiSn3w5+3DuacdNPWjzCLJr+kqqbu6Nkrp6/c9F+3nDNLqKqpBQAoyMvxhiGRSHlZmeqaOsGj/NoVhRr/9sPwB+EvTuwLUFKQ5x8C6pPQEjLmh7+IqfTr7USgngZnJBDUeTLSUk4OY1+9/0QkkTktdx49QSAQc2d+f2rgQMCm+pwELQ017kd0tTQbiSRCI/FXr0UkkaPiE+1HjuBd8XEYYwsAiPsq1IEg3SSvsBirbqQ1ZNSeo6f3blu/be0KTnsLhQoA4F3T4cBgMM0tlK5fV5jxyyur1vrvcZ40bqYoTiqGOo3FoEUv0ohepEGtFbxJue9I8h8dvUijPvFlbyfyN4KrNhDUJV4zXO6HPQ978dZrpguTybwf/ny0tYWutianl0Klnrt2+9HTVwXFJfWERiaLxWQyAQCcv/6SiqpqFot160HYrQdhfF0l5RVd/yKdpqerTSvPIDQSI6Li1vjvCQl99vzuFTkZaQlxMQAAjU7ni6fR6JyuLhJm/KXrtwMATh3Y1fXLQZ02YEnwb7Rj1GxvRG+n8PeC90ggqEsm2o9SVlTgrJu8j4ytqqmb5/7jcDLPZev9Ag+Otxv54fHNqoxYUkHygtluXbncQs8ZrZdg7l3u/f/dy8lIuziOf3jt9NeUtEPBFwAAaipKAIDaunreMAaDWd/QoK6m0vUrdjj+tTsPXn34fDpol6oyLEoBQb8BeI8EgroEjUbNmjbl3PVbDUTS3UdP8ZISrk4OnK6Kquonr965u0wO2PDjcYni0jYfBEChkEzmT9W9ePdDaKipIpHI4lJhjxrp+s7W9pWUVew+cnq0tYXXzB+FrTg7SDJy8gAAairKqsqK6Vm5vJ/KzMljMJicJ3G6qMPxv6VnAwA8fdZ7+qznjRk61hkA0Fyc2no78J8n49gcYk7ciDM5vZ0IBHUMzkggqKu8ZroEX7rx9NX7sBdvXJ0cJCW+HxhGpdIAAIo8Wy8zc/IiYuJBG7U1lZUUI+O+UqhUMdz3OhDvPv0obY6XlBg1wvxjdFxldS33D/2fYxNWbN559eQB8yH8B4lxdraK7Eu2oqggFxL6NDktw9NtKhL5/W5r4rd0AEB/ne8Hws2e7nTu2u2aunrurtJ7Yc/RaNQsl8kiyaH98Y8EbuV7punCjTurtvyT+C5skOEAkSQAiURjZlT6YXf5oY4DV/KfEEkn1SVtt0OJ4c0C3yFxEhWvLxbe2dXWONpuWzUmr+K8ZjQTqyNu1iU8pdaWMsgEJFZMXFVPfvgUtQlLWp88DPURcNUGgrpq6GBj44H6u4+eJjQSeZdstDXV++loPX7+Ji0zh0KlPn8bMXORr5vTJADAl6TU1ltJJo21ZbFYe46cbiSSKqtrN/8T1Ej6qbbmPv+NKCRq2jyfrNx8CpX6MSrO29cPh8X0yu9XcTGxoB2bE7+l+2zcUVRS1txC+RTzZdmGAFlpqVWLvDgxfr7LFOTl5viszyssplCpIaHPjp69snXNcpKImt0AACAASURBVO5W38i4BKy60Rr/3Z3LocPxod+CjKGNiv3c+q/P6r/yPzVWeGcXo6lBb8ERbhF9AIDB8gsCa9hzpyPMFlLqXqfSsGNK1m5DAt+OOJtruvOVzCC74vv7Mk/wP7IO9R1wRgJBIjBnhkt+YTG3DAkHEom8d/mkfj9t26mztYfYnr1689b5o4F+awbq93fzXhF4+BTfIF4zXLavX3E39Jmm6ajRzh6KCvK7t6wDAFBp349utxxm+jHsloaaqp2zp/wA8wWr/VynTHx57xr3nopo+QUexKobYdWNOPVSt+w+xHk7f9VmTsCy+R4hl07mFRaZj5+mamy1bMN28yEmkc9C+ulocQIU5GQjwm6pqSjbOs1WNLDYf+LckcCtvGtYHGiU4Ju1HSYg5PhQ36czcztOQbPgpj+Tp8J9Q+qH2piHKnZeMkYjf2m02tjHLZV5WtM2qY71xkgpINAYMWUdbVc/lTHzGtM/NaR97HgIqDcgBN49hiDI3d2dRSHdPn+stxPpOfNXbX745CVJ0Plq3WfrnsNysjKbVy3pyYvycvNeFRWX0OHZvx7L1iHFpEJCQrp4OXd393cFLQbLz3ccKjRyQVJJ6BFy3hc2my2haaTp5CtrMobTxbePpDEjsuzpSXJBEpvFwCloKlm7qTn4cFcxGE0NpeHHCUmvaA2VKDG8pO4QLZcN+H5mwvR2XWN6RPoRDxU7r/7zggAALGpz0o6xgM0eEviWe0INZ9XGYPkFheFT2hmq7MnJ4kdBg/weShuM4G2nE2voxFpxtQGINibBnRC9SOPu3bvu7u4dh0IdgftIIAjqNYRG4p1HT1/fv9bbifzGyAVJqQemqY5d0H/eARROsjT8eMbxeYa+1+RM+c80JuXEZRz1lDd3NNsbgRaXqk98kXPJl06s0/X4hxOQfW55S0W2wfILktom9Maqwru70w+5m+58IabSv8NeXgxyffyaNjcvm+35KPCIYBnj0Sqj51RF3FS0cpU2GFH8+BC1tsR4w51OHJgnPdAKAFATGSKlb857Pg5GWgkjrfSro0E9Bs5IIAjqNXIy0gUJ73s7i99b0b09WFk1XfcdAIEEAOjO2lGf8KzqvYAZSX3iSyQGp+MegJVVAQAoWrlWRdyqjrzLmZGw6NTGjM/KtrOl9MwBADhFbf2FR79usW5I/aCq0r/9Xr4LofHyHR4uI5COewAh9X3+9U163kcr31xWGT1Hxti2E+NIDbDUcd9R8vBAY8ZneXNHKX0LKb3hnG8N9WVwRgJB0A9UGg2rbgQAyIl9o6Ol0dvpdC8T28nZeQUAAN6z+n4vTGoTMTtGccR0znQEAAAQyGGH4gQG67gH6LgH8LaIKWkTs6IZzY1oCRkkGoORVqz/+kJu8Fi5IRMQKDRKXMriRConsv1eUUGJS+nNP5hxzCv9yCyMrApftlzZZ5e2bkTj5XjzUXdYpmTtWhcf3pD+qTbmEZ1YK6asozB8qtrEpRgpBdGmDYkKnJFAEPTd9VMHr5862NtZ9JzUT896/qIIBAIAke3eozfWADZbyF+xLDq16v31uoSnlJpiRhMBsFhsFhMAADh/RSANfa/lXFiVdXoxEisupWcuO3iM8qjZ38/gbb9XdGRNxigMn1L35anu7F0occGHWne4j4QDI62kOm6h6riFAABKdREh+VXZs9PVkSEmWx+LKemIJl02G3z/ZwqJAHzWBoIgqOfg8XhAaxHVaAgkEgDAYlCFCc4+51MYEig7yM5ky2PLk+kjzucrj5r9U266Q4bujTDZ8kh94lImhVwUsjtx68im4lRhekUIp6DJ/auoiCnrqE1YYrItlN5YXfbkpKiGZVLIAABpaWlRDfiXg/dIIOj34+S5JDIugZD7tbcTgX6ZqqoqoyFKVKNh5dQBAklvqO4wktZQRUh6pWjpoun8o4Itta6UPw6BkBpgKTXAUmv6ZlJeQtoB19KwowNXXRGq9/86t7NVVNgMesXbywgUWm38Yr4uMUVtBBJNqS4Q1bVoDZUAAFVVVVEN+JeDMxIIgrrLyYs3Nu7cr6GmmvLxiRRekrfrzNWba/338JVPbSSSzl2//fTV+6zcfHJzs7yszDDTQbOnO7m7TEah/pCK76ampqTyQyxaCxIr3vXRECi0lP7wxsxIFp2KxHwvS5O8cxwSIzZ4+1PeSDaDCgBA4+W5LS0VOcSsGPD/CsLErOici6sM1/wrqWXMCZDSM8fIKtPJhA57+XR6Z6tIINCYui9Pmsuy5M0ccIpavF2ElDdsFkNc3UBU12oq+oZGYwwNDUU14F8OrtpAENS9yioqA/Z3XNbla0qaqZ3T1dsPfBZ4pEQ8I+R+jQi7PcrKYtWWf8ZOn1tbL+A33+/Izs6OzWI2pn8S1YA6M7ax6JTci6vpxBpGM7H4UVBzaaaK/Vy+MJyCppiSTn3i8+ayTBadSkh5l3V6sYKFEwCAXJDMZjHx/cwQSHTe5TXk/EQWncpoaqh4dYFWX65i6wEAaL+3r+k/7yAKK552yL029hGjqYHNZNAIFZXvr+de8sXJa2g6rRXVhRpSP4ywtsF1T4nCvxC8RwJBUPeaPmXiueu3Pd2cLYeZthVTU1c/bZ6PjLR0RPhtOZnvq/L9dLQ2rVw8dpSVvcscj6VrX9+/3lMpdyNVVVXLEdb5MQ/lzCaKZEApfYtBm+6VPD6UuM0WsNni6gMEb/xEIA1WXiq8vSN1rzMChcLrDTfwOYfESTQVp2YFe6tPXqE93c9ky6OS0CNZZ5fSiTUoMSlxNX0Dn3MKFlMBAEiseDu9PUzgszYAADFlnaH7owAAklrGg3c8r3h5oexJcN61TSw6FSUmKa6qpzZhqer4RWgJ0Wz7YFLIjUkv3Q/sFcloEIAzEgjqs74kfQs8fCrmSyIbABNDgy1rljmMEVyb4f3nmKCT5+OTvjEYTG1N9TkznNf5eOOw3wtx1jc07jt2JvzV+4rKaim8pPkQk4ANKy2GmgrTKxLb16+Ijv/qsykg9sUDDEbw/3OOn7taWV17+cQB7nSEy3yIyarFc4+cufz8bYTjuNEiTKy3rFrhs8B7IaWqQEyln0gGlNK3MN4ouJis0bqb3NeSWsaDNt/nCzDb86OkOlZeXc/7SFtXab9XhHTcd+i47xDYpTZhidoEocr74uQ1uJXfuknVh3+RgDV3Lv/tKKjT4KoNBPVF8Ykp9i5zBur3S3gbmhXz2nzIIJe5Ps/eCDiPIzIuYYrnYnl5udRPz8pTo7at9dkZdGLbnh+/Obx81t8Pf3n91MHqzNjIp3fFxHAO7t45+YXC9PKqrSdwjpUR+JOVm9/Wd5EUFz8auC01I/vI2cttxTx8+kpBTnb8aBuBvbOnOwEAHj552dbHfy8eHh6GRkYlId37+xLqVnRiTcWzk36bN8nJyXUcDQkHzkggqC/auuewuppK0I7NWhpq8rIyB3f6aaipnL9+q3Vk+Mt3YjhcUMAmNRVlSQlxD9epo60tboQ84vRSqNR3n2MmjbW1MjcTw+F0tTUvHduHw2JfffjcYS8fRXk5WnlGWz8D9fkLd3KxAZjh7Dh5vN2+Y2fzCotbB9Do9LzCYsMBem3VdTAxHIBAIL5lZAnzt67vQ6FQp06eqE16TUh519u5QJ1U8mC/opzM5s2bezuRPwqckUBQn0Nuav4U88V6+FAk8vt/oUgkMi/+Xei/Ao5nOxCwqT4nQUtDjduiq6XZSCQRGokAACwGo6woH/bibejzN3Q6AwAgLYWvSIteudCrw17RCt6/E4VCrti8s3UXidwEAMBLSrTu4kChUBLiYkQSWeRZ9RZ7e/tZsz0Kr62j1pb0di7QL6uJulcdGRJ84riERJv/0kKdAGckECQYAtFrJ2NX1dSy2WwlBaHuBlOo1OPnr9k5e2qb2eJ1TMW1TK7ffQgAYDKZAAAkEvno+lk5WZmZi1YrGVpMcvc+evZKfUMj57Pt94qWlobars1r3n+O4aTHSxqPRyAQDURiW5+l0xnNLRTZVltMehKbzRZtac4rly8Z6ffLOTmX0dzmF4f6IFJOXMENv61bt7q6uvZ2Ln8aOCOBIMHweHxzs8hqa/4SFBIJAKDS6MIEey5b7xd4cLzdyA+Pb1ZlxJIKkhfMduMNMB9ikvrp2fvH/61d5k0kN23ZfcjYxiEpNUOYXtFatchrmOkgv38O1tTVI8CP3+4YDNrIQC8tM4dzn6a11MxsNpttZmLUHVkJiUxukpISXNS8cyQkJEIfPRBjkHNOzWcIquoB9UHE7Nic0wudpzrt3r27t3P5A8EZCQQJpqqqWlJe2SuX1lBTRSKRFVUdF+KsqKp+8urdTGfHgA0r++tqS0qIo9Go4lL+4lQIBGKkpfmuzb5Rz0Iiwm8TyeTdR04L2cvV6Z2tXCgU6tzh3Y0k8oYd+/keunFzmkRuan78/LXAD94LfQYAmOns2OEluk9ZZbXIS3NqaWm9f/sa31KVsX9qS0WuaAeHRK4m6l7mkdmTJ4y9+d+/3BVVSITg31MIEszU1DQ7L7+5hdLzl8Zg0NbDh36IjKVQf5xXMmyci81kd75IKpUGAFCU/7G+k5mTFxETD/5fiDMiOl53mH1KeiY3wMrcTFVZqZ7Q0GEvn07vbOVlZmLku2TenUdPPscm8LavWjxXU13VL/Bg63lYUmrGqcv/TZkwZswoK2Eu0R2amluy8/IHD26zMnqnDRo0KCE+zlhHNWO/c+W7q2yW4LtEUO+iE2vyr67Pu7Ju86YND+7fExcXQb1dqDU4I4Egwezs7JhM1rtPIjuC5Jfs9V9PoVDnr9pcVVPXQCTtDDqRmpG9dN4svjBtTfV+OlqPn79Jy8yhUKnP30bMXOTr5jQJAPAlKZXJZA43G4xGoxb6bo37mkKhUusbGo+fv1ZaXunt4QYAaL+3m+zYuFpHS+P2w3DeRjkZ6bB/zyMQCGtH9xt3H1XV1NHo9KKSsmPnro53mzdqhHnvHkr8/nM0k8myt7fvjsGVlZU/fni3bvXy0nu70wMdCCnvAJvVHReCOoFJIZe/OJvib4sqjHrw4MG+ffvgSb/dp9f27kFQ3zdq1EhVeenb5zuugN4douK//nMoOCE5lc1mGxnorfdZ6OrkwOniPWkvJT1zfcC+rylpaBTKavjQvf7r8RISznN98gqLNq1c8o/fmtLyysDDp95ERFbX1ElL4Qfq91+5cM6M/6+AtN/bRZxzbTKiXurpavO2v3gX4ey1DADAd64Nuan57LVbYS/eZOcWcM61GW422GuGi6uTQ+/+Gpi9dG11A/nTJwEPRYtQbm7uuvUbnoSH4VV1pYdOljG0kdAwROPluQfWQD2D2UKiESqailMbUj80Jr1EApbf5k2bN2+GT9Z0NzgjgaA2/ffffwsXLkz+EK7fT6e3c4F6TW5B0RD7qVeuXPHyEv1D0a2lpaVdvXr1UWhYfm5OD1wOagsKhbYeOXKmm+vcuXNhGbSeAWckENQmJpNpPmyYporCo+tnejsXqNdMm7e8qLw6KTkZje7RYzfq6+vT09MJBAKF0gubmf5mUlJSKioqxsbG8Ai9HgZnJBDUng8fPowZMyb03/N/xokq0K96/jbCZe6y9+/fd9MmEgiCuOCMBII64Onp+fb1q8ind3W0NHo7F6hHFZWUjZwya9yEibduCajfD0GQaMEZCQR1oLm52d7ejtRAiAi/LSstyhpZUF9GIjfZucxBY8U+ff6Mx+N7Ox0I+vPBp38hqAMSEhIPHjxsJDdNn7+8TlChDujPU0docJ67rK6hMSw8HE5HIKhnwBkJBHVMS0vr9es3ZZW1o5xmC1OcFPqtZeXmj3KaXVZZ+/r1Gy0trd5OB4L+FnBGAkFCGTRoUGxcnLKqmu1UjzNXbzIYzN7OCBI9BoN55upN26keyqpqsXFxgwYN6u2MIOgvAmckECQsZWXld+/e+yxf4Rd4yGKi6/O3ESwWrK35h2CxWM/fRlhMdPULPOSzfMW7d++VlZV7OykI+rvAna0Q9Mtyc3M3bFgfFhbeX1fbdfIEu5EjTAwHKMjLicHqBb8VCpVaV09Izcz5GBn78Nnr/MJiZ+epR44c1dfX7+3UIOhvBGckENRJnNqa4WFh2TmwtubvzWDAAGcXF29vb2Nj497OBYL+XnBGAkFdJfLamhcvXvz06dORI0eUlJREMuCfoaamZsOGDba2tkuWLBHJgDgcTk5ObtCgQfLy8iIZEIKgrujRosgQ9EeSl5cfNWqUqEYLDg5+8+bNnTt33N3dRTXmH0NdXd3Nzc3Z2XnVqlW9nQsEQSKG2rVrV2/nAEHQd69fv543b96ePXt8fHx6O5e+yNDQEIPB+Pn5DR8+fMCAAR1/AIKg3wdctYGgviIrK8va2nr8+PF3795FIBC9nU4fxWaz582bFxYWFhUVBZ/OhaA/CZyRQFCfQCAQrKyspKSkIiIiJCQkejudPo1CoYwZM6a6ujo2NlZRUbG304EgSDRgPRII6n0MBmPmzJlkMjk0NBRORzokJib26NEjOp3u9j/27jusyeMPAPi92ZCw9wYRBEEUkamCuAfgBnHb4UDqqqsOEPdoi3VSF+KsuFHBPdggypAtYcmeSSBkJ78/wi9EQAhDonKfp0+f8Obeu+9FQi43Z89ms9nSDgeCoN4BWyQQJH1r166NjY29d++ejg48XlgimpqaYWFh79698/HxkXYsEAT1DtgigSApO3ny5OnTp4ODg21tbaUdy/dk2LBhly9fDg4OPnXqlLRjgSCoF8C1NhAkTZGRkQsXLgwICFi1apW0Y/n+mJubo9HorVu3Ojk5DRgwQNrhQBDUI3BmKwRJTX5+vr29vaurK1xc020CgWDRokXh4eHx8fGmpqbSDgeCoO6DLRIIkg4ajebo6CgjIwMX1/SQcOlNfX19XFyckpKStMOBIKib4DwSCJICHo/n7e1NoVDg4pqeEy69aWpq8vLy4nK50g4HgqBugi0SCJKCdevWvXr1Ci6u6S2ampr379+PjY3dsGGDtGOBIKibYIsEgvrahQsXTp48eeHCBbi4phdZW1tfunRJuHBJ2rFAENQdcK0NBPWpqKgoLy8vf3//1atXSzuWH425uTmCINu2bYNLbyDoewRntkJQ3ykoKLCzsxszZkxoaChcXPM1CASChQsXPn78OD4+Hh7FB0HfF9gigaA+QqPRnJyc8Hh8VFQUnM369TCZzDFjxlAolPj4eEVFRWmHA0GQpOA8EgjqCzweb/78+XV1dXBxzdcmXHpDp9Ph0hsI+r7AFgkE9YUNGza8fPny3r17urq60o7lx6elpRUWFhYTE7Nx40ZpxwJBkKRgiwSCvrrg4ODjx4+fP3/ezs5O2rH0F9bW1iEhIceOHQsKCpJ2LBAESQSutYGgrysqKsrT03Pnzp2+vr7SjqV/GTx4sEAg2LZt28iRI42MjKQdDgRBnYAzWyHoKyooKLC3t3d2dr558yZcXNP3BALBggULnjx5kpCQMHDgQGmHA0FQR2CLBIK+loaGBicnJywWGxUVRSQSpR1OP8VgMMaMGUOj0eLi4uDSGwj6lsF5JBD0VfD5/Pnz59fW1oaFhcHmiBTJyMjcu3evsbFx3rx5cOkNBH3LYIsEgr6K33///fnz53fv3oWLa6ROS0vr/v37UVFRmzdvlnYsEAR9EWyRQFDvu3jx4j///HP+/Hl7e3tpxwIBAMDw4cNDQkKOHj3677//SjsWCILaB+eRQFAvi46OHj9+/JYtWwICAqQdC/QZPz+/gwcPPnnyxNXVVdqxQBDUGmyRQFBvKiwstLOzGz169M2bN1Eo2Af5bREIBPPnz3/27Fl8fDxcegNB3xrYIoGgXtPQ0DBy5EgMBgMX13yzGAyGi4tLY2NjXFycgoKCtMOBIKgF/A4HQb2Dz+cvWLCgurr6/v37sDnyzRIuvaHRaF5eXjweT9rhQBDUArZIIKh3bNq06dmzZ3fv3tXT05N2LFBHtLW1hUtvtmzZIu1YIAhqAVskENQLQkJCAgMDz5075+DgIO1YoM7Z2NhcvHjx77//PnPmjLRjgSCoGUbaAUDQd0YgELTaDz4mJmbFihXbt29fsGCBtKKCumru3Lmpqam+vr6mpqZjxowRf6rtPzEEQX0A9pFAUBckJiZ6eno2NTWJrhQWFs6aNWvq1Klwre93Z8+ePbNmzZozZw6ZTBZdZDKZixYtevv2rRQDg6D+CbZIIKgLLl26dOvWLUdHx9LSUgBAQ0ODh4eHtrb25cuX4Vrf7w6CIMHBwQMGDHB3d6dSqQCA0tJSe3v7q1evhoSESDs6COp34OpfCJIUi8VSV1en0WgYDEZJSenBgwf79+9PTExMTEyEs1m/X2VlZXZ2dkOGDNm1a5e7uzuFQuFwOPLy8lVVVXg8XtrRQVA/AlskECSpW7dueXp6Ct8yaDQaAIBCoSIjI+Fs1u9dfHy8s7Oz8F9WeBofgiA3b96cPXu2tEODoH4E9jNDkKQuXLggbIgAAHg8Ho/H43A49+7d4/P50g0M6gmBQPDmzRsul8vj8USHA6NQqPPnz0s3MAjqb2AfCQRJpLKyUkdHp+2eWigUysPD48qVK3BXtO8Rk8lctmzZjRs32v4lRKPRJSUlmpqaUgkMgvoh2EcCQRK5evVquytC+Xz+w4cPHR0dS0pK+j4qqCdKSkrs7e1v3brV7hczBEGuXbvW91FBUL8FWyQQJJGzZ8+2u+k4giA8Hk9WVpZCofR9VFBPUCgUWVlZHo/XbluTx+OdPXu276OCoH4LtkggqHPv37/Pzs5u+00ag8HIy8sHBgbGxsZaWlpKJTao2ywtLWNjYy9evKisrIzBtN4uUiAQZGdnJycnSyU2COqHYIsEgjoXEhKCw+HEr2AwGARB5s2bRyaT165dCzcj+U4hCLJ48WIymezj44NGo1u1S3A4HNyYBIL6DJzZCkGdYLPZGhoaokEZYQ//sGHD/v33X1tbW6mGBvWmtLS0FStWJCQkAABEfxgVFBQqKyvhxiQQ1AfgFzsI6sSjR4+EG3oCADAYjLKyclBQUFJSEmyO/GCsrKxiY2Nv3Lihrq4u6iyh0WgRERHSDQyC+gnYIoGgTgQHByMIgsFgUCiUj48PmUxevnw5HKb5ISEIMnfu3JycnNWrV6PRaCwWiyAI3JgEgvoGHLWBoI5UV1draWnxeDwHB4d///3XyspK2hFBfSQtLW3lypVxcXFoNLq8vFxNTU3aEUHQDw62SL4WBoMRERHx5MmTxKR3BfkFDTQK3NkT+npQKJScvKLRACO7ETaTJk2aMmWKjIyMtIMCAICSkpKwsLCXL16kpLyvqqpuaKRLOyKoX5MjEdXV1YYNGz523DgPDw9dXV1pRwS1gC2S3kelUg8cOHD63zONNJqqqbXCwBFETUMcSQlBYD//96c6I1Z5oDUa/018undAIOCzG+vpFYXUvKSa3GSSvPyqFcv/+OMPBQUFaYWUlpbmt3PHw0ePZPC40ea6VoZqWkokORlc53d+Yxhs7ntyxUhz+NH1I2hgsMvrG9MKq6OyShgsttu0abv37IV9n98I2CLpTXw+Pzg4eMvWbQwu32jKcsOx3ngF2NML9TUWtbrw5fWCiDMyGNShg/uXLVvWx7Ne6urqdu7c+e+/QUONNFdPsZ5iY4zDoPsyAAjqFJvLi3hHPhmRnFpQsWLFyj179igrK0s7qP4Otkh6DYVCmT3X8/WrVwMmLTWfuwlLlNp3UwgCAHDo1KybR/KfXBzj6nr7ZqiiomLflBsXFzdzugfCY++Y6+g1anB7u6FC0LdCIAA3ojP33owToHF374c5OjpKO6J+DbZIegeZTJ4yza2ilma7KUTRaIi0w4GgZpSCD4lHlmgpy0eEPzQ2Nv7axV2/fv2nZcvGWOqdXjnpexyggfqnBgZ71enHrzM+XQi+6O3tLe1w+i84s6EXkMlkOwfHeh5h9L5w2ByBvimKRkOc94XX8wl2Do5kMvmrlnX27NkFCxb8NNYyZK0bbI5A3xE5GVzIOvefxg5ZsGABPMxIimAfSU9RKBQ7e8d6PsHJ/w4GLyvtcCCoHVxWU2zALEUU821C3Fcavnnx4sWUyZPXe4zYPAv2e0Pfq8N34gLDkiIePx43bpy0Y+mPYB9Jj/D5/Nlz5pbX0ew2XfwBmiMx+7zDFg2QdhTSEXdk6d15OtKO4mvB4GXtNl2sqKPNmjP3a6xCz8vLmztntoedyaaZP0JzxPPwHf2fT0g7CulYFBimsfiotKOQmk0zHd3tBs6dPTsvL0/asfRHrY+7hLokODj49evXY/ZHEJQ0pR0L9E1rKCNnXj9QlR7F57Bk1fR0HT1MPHwwBGLblFxG44tNY+lVxeP/ei2vZ9Zubrlhp9Kv7G57feb1EgTd/puaoKRptynk9bYpwcHBP//8c0/q0pbvah9dJZljv46H81ihTrG5vHXnnoVGZwV4O6+eZtPq2fwKyt7Q6JiskgYGW09V3tt58Bp3W9Tnv1gd59CNDEUQBBz/dcLk3Td9V/s8fvK0J9WEugH2kXQfjUb7Y9uOAZN/+mbnjjBqy+94ajZVf+pXRUuoLyOkleS+2jKBRat22X1/2tl087kbc8NOJgYubzdxWogfvaq44ww5dCoAwD04Z1Zohfh/X2qOCCkaDRkwadmWrdtEpwb2ivv37z999nz/Amc89hv9hlNW16i6MLC4mtavipZQH0dIoTPnHrpTWElt99kqKn3K7v9oTeynAd6FZ1fv8h4dGJa4JeSV5Dl0I8NW8FjMocUuT589DwsLk7xeUK+ALZLu279/P53NNZ/zu7QD+aLqzJh+WLSE2omwZ1/wGbVl2bcD4w4tbvtUxtW9fD7XYWOwvJ4ZRoak6zR9wMSlFckvarLiW6WseP+88OU1HXu3jsviNFEBAO12sXTMfO5GBpd/8ODBrt74JTweb+OG9bOczBzNuxfKDQAAIABJREFUvt0xr5gsqbWMpVi0hNpGiPTsjVBa2/DXvYQFf99v+xSFzpwacMPJTHf3Aud27/3zbgKdyTnjO9VAXQGHRU+xMf59uv3FF6kfy+okzKGrGbbLzkR7lpPZ7+vX8Xg8SUqBess3+p3m28dgME7/e8ZoyqoO9h1hN1Kyb/9dnvSEWVeBkSEpGg8dPHeT0kBr4bOR/tPpVZ8cN4ekhfhRyKkCIFA2sbFaEqBgYCHKgVqYnnnzz9qseC6TLqOspW0/zWz2eqysvPDZmAPzG8vyR2679uFyQE1WPODz5Q0GWy3eJSwiZp93ZeorAMDj1bYoLG7G1U6+drdVnR6dc/efurxkAY8rq6ar7zzXxG0VCovrtHbdKFpYF4eNF9Iu7qjPS0EwWK3hE4b9crAi+UXO3WON5WSCovrAacuNp/wiuqU2JzH79tG6j+94zCaCkrqmzcTBnptxckrdfnFQaAy9svDDpYDqjBgeh6lgYDFk0S5Vc/uOI+dzOeVvHxe+ul6V+hqvqD5wWjs9H+pWLmqWo3ByLfsvKQ6wAgDQK4tUzR1EF9kN9e+DNug6TVezcCpNeNhBoRw6DY0jdNwj0i4sUcFoyvKgM0H+/v69ss38o0ePyAWF11cv7SBNfSPzr3sJEe/JFfV0kgzW2khj8yzH4cbNA51ue0I/1dCurPfYfvVNSn6lQCAYMVBr70IXC/2W3QXTi6oP3YmLzymlMzlaSqRptgM3zrCXl8ULn5135G5eBSV000y/a5HxOaU8Pt9CX233fGdhEZ6H77xMKwIADF9/HodFlwWv6WodozI/Bd5PfE+u4PL5eqrynqPMV0+xwWHRndauG0UL6xKy1n3b5VfJ+ZVYNGqi9YAjy8Y+Syk4GvaWXFGvoUBcMdl6+SRr0S0JuWV/30tIyitvYnE0FImThg/YMttJmUTo9ouDQaMKKyl+1yKjs0qYHK6lvtru+c4OgzppcQo3HLv2JuPVhyJ1ReLKydZt01RTm1ZOHr547JCkvPJ2M7kXnzPKXFcUPABgmu3A3TeiwxI//j7DXpIcuprhl2yd5WC38WJ4eLi7u7skBUG9AvaRdFNEREQjjWY4tqOV64lHV5TGPbD97aTbxdwx+yPQOJmo3XMay5tXYKIweDat9t2pdeZzN007l+G6L5xeURC1ew67obnxXk9Ofb3DDfD5LnsfuV3IHrpsX3Hkzei9XgIe9/854NgNdW+PrTKasHhKULLL3gfM+sq4I8t4HBYAYOT26ybuqwAAk0++7UZzpDY7IXrfPBxJaeLR6GnnM81mrc/472D61T2S1K4bRQvrknJuq8X8HVPPfhg0c21x1K3YQ4uKXv3nsCl46r+pKoPsUoN31H18L0xfnR4duWsWVobkuj/cLTjbZvXxssSIyIBZwrp378VBEFTiP6sMxy+cEpTsui+c00hJ+PsXPof9pZipRZlpF3eGr7BKPLYKhcY4bL445fQ7Uw+ftimNp/zcqqXCqKsAABA1DMQvJp/bzOdxh/60v9OXi0OnYmRInSZrl+FY7wYq9fHjx927vZXr166NsjAw0uho/c6vJ8LvJ+QGrZqSf2bV0wBvAg4z88AtckW98Fk8Fl1DY/ieebpllmPO6ZVPArwLKikz99+qbWAIE6QUVE4O+I8vEET4z/sYtOrA4jGh0VlzDt3h8pqn6GIx6LoGxvKT4UvHDkk79ku4/7wKCn3x0QcsDhcAELp5ls9UGwDA+8Cfu9Ecic8pnXvojjKJEH9kSe7plb9Pt99/MybgvyhJateNooV12Xzxhd+80VknV6yfbnczJmv+X/evR2ZcWu+ecWK5nan2tsuv35ErhOmjMj9N33dTTgb3dLd33r8+J1dOfpREnrHvprDu3XtxUAiy/FTEYtchH479+nSXd30jc9mxh2zOF3sLMoprtl9+bel7ZsWpCAwGdXm9R+o/v/hOG9E2pYm28uKxXxzjLq1tqGtkmuqoiF800lDEolGpBZWS5NCNDL/ESENx5GD969euSVgW1Ctgi6Sbnjx5ompq3cEm8TwOq/pDlIb1WGXTEWgsnqiub+NzFIXFVaa8FiZAUGgeh2U6fbWahRMaLyOvb2650I/dUF/0+oYwwYdLfjiSkv2Gc3LaxhgCUdNmgsX87fV5ySVxLaObnCaaibuPpvU4DF5WXs9swMQlzPoKWlFmzytY9vYJGou3XORPUNLE4GX1Rs9WG+woiq3T2nUDp4k2aOYaZZPhGALRZNpyDIFYl5Nk43OUqK6PJSqYzvAFAFSnRwsTp1/dgyMq2PgeJ2kZYwhENQsnywXbacVZJTH3xDPs0ovDZTWZCtMTiAqGlkYTFrOo1fX5KW1T1pNTX/0x6cWmseXvnpm4rZxy6p3jlktaNhMRlER7pbOo1XmPzsjrmakMshVd/BR1uzTuwbCfD+DlVTq4V1Q1FBqbFXrk+Qbn+wsMwlcMTTn/B7tRotkheAU1VVPrXmmRCASCJ08eTxpm0EEaFocbmVE8fqihrYkWHosxUFM4vnwSHoMWfjUHAKBRCIvDXeM2YqS5rgwOM1hP1d97dF0j80ZU87/UjitvlIiE4N/cBmopEQnYidYDdnqNek+uuJ+QKyqF1sRaPc1m/DAjWTzWXFflp3FWFfWNGcU1Pa9jxHsyHoveNd9ZU4kki8fOGWnmZKZ7/f+xdVq7bqA1sdZ52NkYaxIJ2JWThxMJ2Le5ZceXTzJQU1CQxa9xtwUARGU0N6MDrkcpEPEnV04y1lQiErAjzXX9vEZlfqq5E5cjnmGXXpwmFmf1VJvxw4yIBKylgdqycVbV1Kbk9j7CUwoqx++85rLt8pOUglVTbVL/+eXqhumThg9Ao7oz7lNNawIAqMh91nWHQhBFEkH4VB9nOGmY4ePHEXCDjL4EWyTdFJ/4VmFgO18CRFAYLF5BtSwxoiwxnM/jAACwMnJu57OMp3y2zEFjqKvosZrFSAAAtTgLAMBhNNRmv1WzGCkaJQEAaA5zBQCI+gmE1Ie0jKcSlDQAAIz6ih7UrNmQRX4el8iyqi1dtbLq+pwmmnBOpYS16yoVMzvhAwSNwZEUZdX1hDUCAAgbf0xKFQCAQ6fWk1NVLZzQWLzoXuHrUJ3x2eyQrr446lZi6RXVAQAsajt/uKmF6fX5aWaz1088Fjto5lpRkJJgN1LiDi/hNtFG+B4XtWAYdeUpF7Zp207RdZouSSYCPp/HYaHxsqP8bk09+2Hosn2l8Q9e/TGJy2iU5HZ5Y5u37953nq4z+fn59RSqrYl2B2mwGLSqvGz4O/KjpDwOjw8AkJPB5Qat+nXiMPFkrlaGosejB+sBAIQfmQ0MdmJu2ajBeqJREgDAOCsDAICon0DIxbKlYaShSAQAVFB64ZzhAG/nonO+uipyoisGagq0JhaFzpS8dl1lb9r8kmLQKCUiQU9NXlgjAIC6vCwAoIraBACg0JkpBZWjzPXE5xS7WOoDAKIzS8Qz7OqLM2ZIS3p1BSIAoKa9j/APRdWphZW/z7BP/HPpeg87UZDdw2RzAQBYTOtPJRwG3cTi9n2GtiZa9RRqYWFhN4qGugfOI+mmosIioxFeHSRAEJTjlstvj/nE//kTGi+jYjpCY5irget8HKmlfxuFxormPQAAhE+xKNUAAGZdpUDAL466VRx1q1XOjNqyllJQaPEchMcLC3pjNhaPw8p/ElyW8IheWcRurBfw+QI+DwAg/L8ktesqBIUWTZEBAAAEEc9NONtOWDqjrhwAQFD8rB2AV1QDADDrWkaXu/riICi0+KwgYXNB0N7uHYpGQ5QHWmffDiyJuWfg6m0wxkvCRgm9sjBm/wIWtdpx6xXxJVrvT28AAAz79ZAkmQAAxux7JP6jjoMbgiDxf/2ce//E4HlbO72dpGVUENv696obCgoKAAAdD9mgEOTaxukrTkYsOfpABoexNdEeZ2U438VCSWxoH4tGiY/0KxIJAIBqGh0AUFHfyBcIbsZk3YzJapVzaW2D6DEahYjnIFzbKRrW6QkWh3v+eerDxLzCKiqFzuTx+Ty+AAAg/L8ktesqNAoRTZEBACAIokQUyw0BAAAenw8AKK+ng/+3METUFGQBAOX1LW3Trr44aBSiIBaAsMNDWN9WrAzUhg/Q/Otewp24nAUuFt7OFj1plMjgMAAADrd1YCwOTxbfnY+qHmY4QFMJAFBQUGBkZNSN0qFugC2SbmpspHV6lp6S8dCJR6NrcxIrU19Xprz6cHl3zt1jo3bebPko+rxvUwAErS4ajlswfMVfvRu5hBIDl5e/e2o+53d95zl4RXU0Bpd8ZlPhq+uiBJ3X7qv7/E9kc+dqX2yIoTjAasy+cNqnnMKX1z4+DMoMPaxpPc5o3EIN67EdDNzU5ryNO7wEQyC67AkT32ik8NX1ytRXduvPCHtlukdj2FiAIK36z74ES1RoaJBo8WTHaDQaAEC+sw3jhxlpxB9ZmpBb+upD0cu0Qv/rkUcfJN7ZOnuIYXN9kdZvBAD+/8EptGiMZeAvE3oecDf8fDz8STJ500xHz5Fm6opEHAb9+4XnV99kiBJ0WruvrdWwgvCnvtkYZqiRxpMA7+yS2qtv0k9HvD94O278UKPFrpbjhhp1Y+BG2JqppTHEL3J5fAqdqaXUnZVcPcxQ+Ivdu0vloY7BUZtu4nG5Ek0aQBAVM/vBXltcDzwes/chh9GYdaulhcHnsDlNLdsAsBvqAQAEBTUAgIyKFoKgmqpL2mbZB5j1FeVJT3SdppvP3UjUMMTgZRE0pqmmTTAd1u7rkVHRBgjCrPtsYJtZXwUAkFHtaAShd8nrDbJaEjD131S7tUF8Lifu8JLHPiM+PjjVbuK6j+9i9s0jquu77o9ote+ZcGpLYuDyO56awv+Sz24BADz/fcwdT03RRGYRPpdDKfjQWJ7/+UU2EAhQODyQAIJC87jd6QZvhcvlAgAw6M7/jCAIcBik88ccp2e750f4z2tgsA/fbVn5zObwaE0s0Y/1jQwAgJoCEQCgrSyHQpBPNQ1t8+wDFfWNj9+TZzgM2jzLwVBDURaPxaBRbYPpuHZfj44yCUFARf1n4y+VFDoAQEdZ7gs39T4zXZU9C1w+HP/1zOqpHC5v4d9hw9aeO/noXVfz0VQiqSsQs0s/GyfNLavj8vjWA7qzBWUPMxT+YnN7450CSQi2SL6Wmsy4iJXW1KKW71LKpiMIiurCZodIVVqk6LFwDoTqYCcAAIZAVDG3r8mIFc6caM4zK+HZ+tH15FQJY2ge6ej6zCwehw0AwIutVm0o/VidGSfKrdPadbtoSWBl5VVMR1RnxvDYTNFF4Wpe8Xk5HeutCFEYrI6D28ht1yafemc0YVFNZjsfRU3Vn2L2zydpG4/2u4VXUG31rNXSPa02OrP+9RAAYPxfr9vd9IzPYb3Z6f7+3882wql4/xwAoG45qofV6XWxWSVDfjubUVwtumJroqWhSKxvZIone53esiZLOAfCyUwHAEAkYB3MdGKyPlVRWz5343NKnTaHpHS2XEJE2N0iAF3+t2ZxeQAAFVLL1MjcsrrY7BIAmntyOq1dt4uWhLws3nagdkzWJ+GECaGXaYUAAFerjqYbi+utCHEYtIedyY3NM1P++WXJOKvYnO58m5rjZBaTVSreq3EvPheDRs10HNS9qHo9Q+irgi2Sr0XJeBiCRiedWFP38T2Pw2I3Uj4+DGLUlhmOnS9Kg8YRsm//XZX2hsdiUIsy06/sISiq6zp6CJ+1XLATQaFiDy5sKM3jcVjVGbFJJ3xRWLy8fvs7i7dFUNYCANR/fM/jsNp+1e6ArJouUcOgLDGC9imbx2FVJL+I/3OZroM7AKCenCLg8zqtXbeLlpDlwp1cRuO7U2vpVcVcJr3qQ2TmfwdVBtnp2E+TMIdej1BGRcts9gbHLZfaPpVy/g8+m2m/4Vy3l+xWfYi846n54XIAAAAjQzL33FyTGZcW4seoLec00UriwlIv7lQwsDAa387+bNJlbayJQaN8gp68I1ewONz6RuapiHeltQ0LXFr23SHgMH/di3+dXsRgczOKawL+i1JXIM5waP7M8J83GoVCef95/2NZHYvDjckq8Ql6jMOizXU7X5QkpKVMAgC8z6tgcbhdmlyipypvoK7wKCkvq6SWxeE+TylYcvSBh50JACA5v4LHF3Rau24XLSF/79GNTM5vZ54WVVPpTM6b9OL9N2PtTbXdbU0kzKHXI9RWJm2cYX91g0RztFtZN91ORY7w84lHBZUUFod7Ny7nRHjShun24jOLO/YmvVh1YaDftcjeyhDqS3AeydeCxsu47A7LCj2S8PcvLGo1RkZOTsfEbv0ZUYMDAIDC4Gx8/vlwaVc9OUUg4KuY2g79aR8a3/yFTNlkuMveh1m3/nqz043DaCQoquk6zRg0c634ApOO6TvPLUt4mHTiN4wsaeyh5+ILZzqGICiHjRdSg3e83j4NQWOUTW3s1p3BEIiUwg9xh5cMmu47eN7WjmvX7aIlpDLIzjngXlbokZebx/NYDBlVHX0XT7M5GyTfNKxVhF0qnfz4QuqFbe0+pWBgMe7IC/ErPBZD2IHxxNeuVWLDsfOHr/y7S0ULmXr4ENX188LPvtg8jstokFXTNxq/cNCMNaJfnm+HDA7zcKfn4TtxPx17WE1tkpPBmWgrn/tt2gx7U1EaHAZ9fPkkv2uRyfkP+HyBnan2gcWuwmmJAAAbY80If68jd+On7r7RwGCrK8jOcBi03sNO8k3rPUeaP0j86BP0WE4G93LfQsk/jVAIcmmd+x+XX0/edR2DQtmaaJ3znUYiYD8UVS8MDFvjZrttrlPHtet20RKyN9UO2zH30O041+1XGSyOjqr8POfBG2fYSzKU1m6EXSr93LOUrV/Ykd1CX+3N/ta5+V2LPBXeMprjfz3S/3okAGDOSLOgVVMAAMokQrj/vL2h0ZN3/dfAYBtrKu5fOGbpOCvJc2il0wyhbwoCF1t3D4IgrZoXXRWzz7s2J9HjErkXo4IgSZTEhSUGLu/5ez80NNTLy6vmyvqeZOJ5+E5CblnROd8eBgNBvU51YeCNGzc8PT2lHUh/AUdtpAo2ByEIvg8gCAIAwBYJBEEQBEHfAjiPpF+oTHkZs39+BwmUTYaP2Rf+gxUNQa28SCv0Ony3gwQ2xppPAjo6rOp7LBqCvhewRSI1I7df7zxRL9EYNnZWaC9sLf99FQ19F0I3z+qzssZZGfZw1sv3WDQEfS/gqA0EQRAEQdIHWyQQBEEQBEkfHLWBfkCN5fkZ1/dXZ8QK9+owGONlOsNXeNJeW7lhp9Kv7G57feb1EvHdTfhczvugDcWRN4cs8jNx92mVuKGMnHn9QFV6FJ/DklXT03X0MPHwwRB6dBQqBPWu/ArK3tDomKySBgZbT1Xe23nwGndbVHtH4LA4XJ1lx9vNRHTG0IlHSbuuR7VNUBGyVrQbSmpB5YFbsYkfy5kcromW0vJJw8V3xoOgVmCLBGqNUVsescp68sm3smp60o6lO5iUqjc73RUMLV33R8goa1WmvHx7fDWjtmzYLwfbTc+hUwEA7sE5HRydyKFT4/9cxudy2n2WVpL7+o/JigOGuOy+L6uqW5H84t2ptfXkFKc/rvZKjaBvQVldo9Was+8Df9ZXk+889benikqfsvu/IfrqTwO8tZRIL9IKV56OKK1rPLJ0bNvEeCym7ayXiHfkRYFhor10qXQWAIB8xkf8oGBxj5Lylv3z0N3O5MWe+RqKxIsv09afe0ZpZK6eZtOrNYN+HHDUBmqtOjNG2iH0SPbtv7lMut3aIKKGAQqL07KdbDZ7ff6zkIbSvHbTc5qoAIAO+jM4dOrrHW6q5o5DFu9qN0HG1b18PtdhY7C8nhlGhqTrNH3AxKUVyS9qsvriuDWob8RkfZJ2CD3y590EOpNzxneqgboCDoueYmP8+3T7iy9SP5bVSXI7ncnZeunVTIdBLpb6wivUJhYAgIjHfumWgP+iNJWIp1dONtJQlMVjfabYzHexOHg7ttWRRhAkAvtIfkDUwvTMm3/WZsVzmXQZZS1t+2lms9djZZu/2MUcmN9Ylj9y27UPlwNqsuIBny9vMNhq8S6lgdYAgJh93sIj6x6vtkVhcTOuFsfs86ZXFtr/fu7tcd/GcvL0ywUICl2bk5h9+2jdx3c8ZhNBSV3TZuJgz804OSVhEZH+0+lVnxw3h6SF+FHIqQIgUDaxsVoSoGBgAQCI9J9Rn5869UwaVqZlR+2cu8cyru8fuf0/jaFjelj9ktj7qhZOomAAANp2U9Kv7i2Nf2A2u53FDhw6DY0jdLD9PJNSPXDacqPxi+o+tn+cqbqVi5rlKJzYwYSKA6wAAPTKIlVzh+7XBOpV6UXVh+7ExeeU0pkcLSXSNNuBG2fYy///+/28I3fzKiihm2b6XYuMzynl8fkW+mq75zsPN9YEAHgevvMyrQgAMHz9eRwWXRa8xvPwnYJK6sW1bqtOP86rqP90/jc0CknILfv7XkJSXnkTi6OhSJw0fMCW2U7KJIKwCLc9oZ9qaFfWe2y/+iYlv1IgEIwYqLV3oYuFvhoAwH1vaEp+ZebJFXIyOFHMR8MS94bG3Nwyy3WIpCfnfcm9+JxR5rqiYAAA02wH7r4RHZb48fcZ9p3efvB2LJXO2rPAWXSF2sQi4DBf2q6eQmfmV1Bm2JvisC1npE+3N73yOv1ZSoHnKPMeVAX6YcEWyY+mnpwa6T9dfYizy95HMsqaNRmx74LW12TFj9nzQPihi8Lg2A11b4+tMvfcbLv2dFNVcdzhpXFHlk06kYDG4kduv/7hcsDHB6dFozYoLI7Lakq9sE3bdrKMsiaCoKrTo6P3zdOxm+q6P5ygpFlPTn17zKcmK971wGPhmTsoDJ5Nq313ap3V0j3KA63plYWxBxdG7Z4z8WgMTk7ZaPyimuPxJdF3jSa0HAtXEntPVlVH3cq5VXXYDXUPfx78pcpOCIyW0xkofoVRW8ZuqJfX/exgT6KmEQqNpeSntZsJh07t+AA8OZ2BrUppxXjKz62uMOoqAABEjZ5+ikC9JaWg0m1PqIulfoT/PC0lUkzWpzVnn8XnlIb7eQk/U7EYdF0DY/nJ8K2zHc+snlJUTVsUGLb46IN3fy/DYzGhm2cJT1QRjdrgMJgmFmdLyKspNsZaSiQUgkRlfpp76I7biIFPd3trKpJSCipXnIqIyy59tttbeAQPHouuoTF8zzzdv2jMcGPNgkrK/D/vzdx/K+7IUhU5mSWuVnHZEXfispeMbTl15W58jq6KnKhbQqS2gTFoVdCXKht3eImJtrL4ldLahrpGpqnOZ2cTGmkoYtGoVAmOUP5UQzv3NGWtu62mUss7hdrEIhFwX7pFuA8v8vkkFSUSAQCQXlztCWCLBGoHbJH8aD5c8sORlOw3nENhcQAATZsJFvO3vz+9viQuTG9U88YPnCaaibuPpvU4AIC8ntmAiUs+XA6gFWUKu0laQxAWrdbEbaWJ+yrhhfSre3BEBRvf48L2h5qFk+WC7UknfiuJuWcwxgsAgKDQPA7LdPpqNQsnAIC8vrnlQr/EoyuKXt8wcV+l4+CeenFH4avrohZJQ2ketSjTfO7GtpNPcXLKXdrOhEmpFt71eQ1QWJIik1rd7i2cJhoKjc0KPVIa/4BeWYQlKWrbTR3stQVHUpS8XHEsanXeozPyemYqg2y7lwPU63ZceaNEJAT/5ib8yj7ResBOr1Frzz69n5A726n5MG1aE2v1NJvxw4wAAOa6Kj+Ns/K7FplRXCPsJmkFQUBtA2P1VBufqc2zIgKuRykQ8SdXThK2P0aa6/p5jfIJenwnLsfb2QIAgEYhLA53jduIkea6AIDBeqr+3qN/PRF+IyrTZ6qNh53Jtsuvrr7JELVIPpbVZRTXbJ7l0HbyqYqcTJd2N6mmNQnvEr+IQhBFEkH4VMf+vpeAx2JWThkufpFGZ2HRqEO348ISPxZWURWJeDfbgVtnOwmbHUokgpGGYkJuKZvLw2Gau0nic0oBADUSlAj1T3AeyQ+Fw2iozX6rZjFS2BwR0hzmCgCo+/hePKX6kJbeCIKSBgCAUf/FD34Bj6vrNKO5CDq1npyqauEkfgSxMLfqjM8moGgMdRU9VrMYCQCgFmcBAFBYnL6zZ31eMu1TtvDZkpi7AEEMxszrYnXbwWMzAQAoTOuxbRQGy2Mx2r1FwOfzOCw0XnaU362pZz8MXbavNP7Bqz8mcRmN3QiA3UiJO7yE20Qb4XscQaE7vwH6+hoY7MTcslGD9cRHEMZZGQAA3pE/+7V3sWzp1tJQJAIAKij0L2XL5fFF0zwpdGZKQeUocz3xE4mFfRvRmSXid7laGYoejx6sBwDIKK4BAOCwaK/Rg9+TK7JKaoXP3onLQRAgbM30EJPNBQBgMW1a/Bh0E4vb8b0ltQ3/RWX+OnGYIpEgfp0vELC5PFk89u622Vknlx9Y7Ho/4eN4v2uNTLYwQcB857K6Rp/TjwsrKbQm1vXIjODnaQAADo/f8xpBPyTYR/JDYdZVCgT84qhbxVG3Wj3FqC0TPUZQaPFpFsKeCQGP98V8EYSgpN6cT105AICgqCH+PF5RDQDArCsXXUGhseJFCPsbWJTmXgqj8YvyHv1b+PK61ZIAAEBJ7D31Ic6yarpdqOoXYPAyAIC2i2L4XDYaL9PeHWDMvkfiP+o4uCEIEv/Xz7n3Twyet7VLpdMrC2P2L2BRqx23XlE0GtKle6Gvp6K+kS8Q3IzJuhmT1eqp0toG0WM0ChGfZiHsmeB++eMTQZpbLQCA8no6AC0/CqkpyAIAyutbmrZYNEq8COFnfDWtudGz2HXI6Yj3196k71ngAgC4G5/jYmGgp9oLS3tkcBgAAIfbui4sDk8W38mnwI2oTC6fv8i19e/z412ffYXwsDNBIcjSfx4ce5C0ba4TAGCqjfF/m2buDY122nKJSMBByBqfAAAgAElEQVS6WOhfWOPmsu1yB2M9UD8HWyQ/IMNxC4av+KsXM0QQVJuv+5+f1tp8eKtY3zIK+Ty1QPyinM5AVXOHT1G3hizcSS3Oaigjm8/d1CuhCltObFrtZ6XzuOxGiqp5O33v7dIYNhYgSKtepU7V5ryNO7wEQyC67AmT1zPr0r1QHxBtpNFbUAiCbvV7/vkpxv+fS9FyBWn9vmjOR/ijibayo5lOaEyW/7zRWZ9q8srrt8xy7JVQhU2lWtpn3YRcHp9CZ2op6XR8b1jiR+sBmpKseR431BBBwDtyyzeT8UMNxw81FP0o7P4xVP/iMnuon4Mtkh+KjIoWgqCaqks6T9r9IrQBgjDrPpsNx6yvAgDIqGqLrvA5bE4TTbTAh91QDwAgKKiJEhhNWPz2mE9VWmRVejSOpKhtN7Xd4ro6s5WgpElQVKd9yhG/2FD6UcDjKhm3M0uGz+XQPmVjCESS1gCxi2wgEKBw7e+y0K66j+9i9s2T0zFx2noFr6Aq+Y1QH9BWlkMhyKeahs6TdpeOMglBQEX9Z0M8lRQ6AEBHuWVNGZvDozWxRAt86hsZAAA1hZaelaVjrVacinidXhyVWaxEIkwb0f6U6q7ObNVUIqkrELNLa8Qv5pbVcXl86wEdtdSLqqgZxdXrPOxaXWdzedkltSQCboBmy3QrFocrEADxcatW3uaWAQDsTbW/lADq52CL5IeCIRBVzO1rMmKZlCqCYvM4S01WQvKZjSN8TygZD5UkE+H0+Fbf9kSwsvIqpiOqM2N4bCYa19z/LFwwLD5xBABQlRap4+AmfCycYqI62En0rI69W6rc9uKoW9UZsXqjZ4tPfBHX1ZmtAAC9UbPynwSzaLV4+eaVBSWx9xE0RnfkjLaJ+RzWm53uSgOtnXe1nMta8f45AEDdcpSEJTZVf4rZP5+kbTza71bHy3YgqSASsA5mOjFZn6qodPX/f/zH55RuOP/81KrJw4w0Or5dSNiTIQDtvy/kZfG2A7Vjsj4x2VwCrvnv6su0QgCAq9VnS65epxd72JkIHwunmDiZtfRSuNua/EF6dTMmKyarZI6TmfjEF3FdndkKAJjjZHb+eWotjaEi3zx8eS8+F4NGzXQc1MFdCbllAABLA7VW19lc3tTdN4Yba4Ztnyu6+DylEPx/cgwAYMeVN0+S82MPL8GiUQAAvkAQ8uqDqbayvWknvTJQvwVntv5oLBfsRFCo2IMLG0rzeBxWdUZs0glfFBYvry/pOAJBWQsAUP/xPY/DEvDamfVmuXAnl9H47tRaelUxl0mv+hCZ+d9BlUF2OvbTRGnQOEL27b+r0t7wWAxqUWb6lT0ERXVdRw9RAhQWZ+DiVRJzj1lfYTh2fs8q/ZlBM9fi5JUTA5c3VhTwOKySmHu5D06ZzVonq9r8d7DqQ+QdT80PlwMAABgZkrnn5prMuLQQP0ZtOaeJVhIXlnpxp4KBhdH4xR2W0yLl/B98NtN+wznYHPlm+c8bjUKhvP+8/7GsjsXhxmSV+AQ9xmHR5roqnd8MAABAS5kEAHifV8HicNudXOLvPbqRyfntzNOiaiqdyXmTXrz/Zqy9qba7rYkoDQGH+ete/Ov0Igabm1FcE/BflLoCUTQ9FgCAw6Lnjba4G5dTUd+4cIxlzyr9mXXT7VTkCD+feFRQSWFxuHfjck6EJ22Ybq+r0tyF8ya9WHVhoN+1SPG78srrQXvjLCQCbutsx9iskh1X3pTVNdKaWPcScrdfeW2hr7Z0XPNaobFWhkVV1M0XX9Y1Mquo9A3nn2eV1AT+MqG9beshCADYR/LjUTYZ7rL3Ydatv97sdOMwGgmKarpOMwbNXCu+NKZj+s5zyxIeJp34DSNLGnvoedsEKoPsnAPuZYUeebl5PI/FkFHV0XfxNJuzQXyTMRQGZ+Pzz4dLu+rJKQIBX8XUduhP+1rNLTUcv+jjwyBFoyHCndN6C05OyWXPw4zr+19vn8ZlNJC0jIcu3WM0YcmX0pt6+BDV9fPCz77YPE54Do7R+IWDZqwRRSvcoEWU/sPl3R8u7wYA6I2ebfvbSR6LIexTeeLbumfbcOz84Sv/7sWqQd1mY6wZ4e915G781N03GhhsdQXZGQ6D1nvYdTDE0IrnSPMHiR99gh7LyeBe7lvYNoG9qXbYjrmHbse5br/KYHF0VOXnOQ/eOMNefA8xHAZ9fPkkv2uRyfkP+HyBnan2gcWuMrjPYlg8dsipiHdWhurCndN6izKJEO4/b29o9ORd/zUw2MaaivsXjhG1Hr6EQmcCAMQ3bRPxnTZCX03hzJNk1+1XhAflLHIdss7DVlSdsVYGIevcj4YlWq87h0IQOxPtcD8vCXukoP4J+VLnPNQxBEHs1p8R/9IPicTs867NSfS4RO44Ge1T9vPfxwxf+Xfv9pFAnSqJC0sMXN7z935oaKiXl1dXhw/6Lc/DdxJyy4rO+XacLKukdvTWS0d/mdC7fSRQN6guDLxx44anp6e0A+kv4KgN9HVI8GmXG3aKoKiuN3p2H4QDQd8CSRqBJx4mqSsQ546Ey7WgfgeO2kB9TcDn8TnsgueXit+E2q8/K/lwEgT9wHh8AZvLu/gi7UZ05vnfpkk+nARBPwz4Sw/1tZLY+0nHfQnKGiN+O6Hj6C7tcCDom3AvPmfV6ceaSsTTqyZPtzeVdjgQJAWwRQL1vpHbr3fwrN6oWaITdiCo/wjd3NGv/WwnM9EJOxDUP8F5JBAEQRAESR9skUBSE7PPO2zRgM7TQdAPzfPwHf2fT0g7CgiSPjhqA/V3PA7r/gKDdp8SPyGIkp+WceNgXU4Sj8OU0x5oPPVXQ1fvPgwTgvoIm8tbd+5ZaHRWgLfz6mk24k+deJS063pU21sqQtYKt13pNAEEdQC2SKD+Do3Ft92ovvzt47gjS3Wdpgt/LEsMT/jrF22Haa4HnxCUNAqeXUoO+p3TWG/i7tPn8ULQV0ShM5ccfdD2lGAhKp0FACCf8VGQbX+JXKcJIKgDsNEKQa1xmfSUC9t0naarD3EWXkm/upegrGHre5KkaYTBy5q4rTRwnZcZeoTdSJFuqBDUiyh05tSAG05mursXOLebgNrEAgAQ8dgv5dBpAgjqAOwj6UfYjZTs23+XJz1h1lVgZEiKxkMHz92kNLDlRNzq9Oicu//U5SULeFxZNV1957kmbqtEZ+DFHJjfWJbvsPFC2sUd9XkpCAarNXzCsF8OViS/yLl7rLGcTFBUHzhtufGUX4TpI/2n06s+OW4OSQvxo5BTBUCgbGJjtSTgS3vGUwvTM2/+WZsVz2XSZZS1tO2nmc1e33J6cGfB96LMG4c5TTSrJQHCHzl0amN5vq6jh/hxgDqOHoUvr1W8f6bvPPcL2UDfqPpG5l/3EiLekyvq6SQZrLWRxuZZjsONW47Ajcr8FHg/8T25gsvn66nKe44yXz3FRnTo3bwjd/MqKCFr3bddfpWcX4lFoyZaDziybOyzlIKjYW/JFfUaCsQVk62XT2r+5XTbE/qphnZlvcf2q29S8isFAsGIgVp7F7p8aZP49KLqQ3fi4nNK6UyOlhJpmu3AjTPsxY4L7iT4nqimNq2cPHzx2CFJeeXtJqA2sQg4TAfjL50mgKAOwBZJP5J4dEVDSa79hrMKRkOY9ZUfLgdE7Z4z9tBTkpYxAKA2OyF63zwdu6kTj0ZjZOXLEyPenvBlUWuslu4R3o7C4NgNdSnntg5ZvEteb1D+05D0K7ubakvRWILDpmAcUSH1wvbU4B1KA4crmwwHAKAweDat9t2pdVZL9ygPtKZXFsYeXBi1e87EozE4OeVWsdWTUyP9p6sPcXbZ+0hGWbMmI/Zd0PqarPgxex4Ij8vpOHhx7Ia6hz8P/tKLMCEwWk6n/RPehZqqS/IfXzCd8RtBqfmvfPNu65+fD4YjKQEAqEWZnb7s0Lfm1xPhOaW1F9a4WRmqVVDo/tciZx649XLvAmNNJQBAfE7p3EN33EYMjD+yRF4WH55EXhUUUUNt2rdojPB2LAZd18DYfPHF7gUuZjoqwS9Sd12PKq1rIGDRl9a7KxIJW0Nebbv82maglo2xJgAAj0XX0Bi+Z57uXzRmuLFmQSVl/p/3Zu6/FXdkqYqcTKvYUgoq3faEuljqR/jP01IixWR9WnP2WXxOabifl/BjvuPgxdU2MAatCvrSixB3eImJduu3oYm2ctuL4qhNLBKh/WO6JUwAQR2ALdn+gsdhVX+I0rAeq2w6Ao3FE9X1bXyOorC4ypTXwgRlb5+gsXjLRf4EJU0MXlZv9Gy1wY5Fr2+IZ8Jpog2auUbZZDiGQDSZthxDINblJNn4HCWq62OJCqYzfAEA1enRwsQICs3jsEynr1azcELjZeT1zS0X+rEb6lvlKfThkh+OpGS/4ZyctjGGQNS0mWAxf3t9XnJJXJgkwYvDySnPCq340n8dN0cAANl3AlE4vInbipYMSYokTaPanEQ+lyO6WJudAABgUWs6feWhbwqLw43MKB4/1NDWRAuPxRioKRxfPgmPQb9MKxImiHhPxmPRu+Y7ayqRZPHYOSPNnMx0r0d91vSkNbHWedjZGGsSCdiVk4cTCdi3uWXHl08yUFNQkMWvcbcFAERlFAsTo1EIi8Nd4zZipLmuDA4zWE/V33t0XSPzRlQ7zdkdV94oEQnBv7kN1FIiErATrQfs9Br1nlxxPyFXkuDFqcjJ1FxZ/6X/Om55fAmNzsKiUYdux43cckln2XEL3zNbQl7WNzIlTwBBHYAtkv4ChcHiFVTLEiPKEsP5PA4AACsj53Y+y3jKz8IEQxb5eVwiy6rqiG6RVdfnNNE4dKp4PipmzSfcImgMjqQoq65HUGo+zBOvoAYAYFKqxNNrDHUVPVazGAkAoBZntYqNw2iozX6rZjFSfFhEc5grAKDu43tJgu8tTTWlxa9DjSf/jCV+dvy65SI/Rm150vHV9MpCThOt6PWN/KchAABhMNB3BItBq8rLhr8jP0rK4/D4AAA5GVxu0KpfJw4TJgjwdi4656urIie6xUBNgdbEEp6CK2Jvqi18gEGjlIgEPTV5DUWi8Iq6vCwAoIraJJ7e1cpQ9Hj0YD0AQEZx6+ZsA4OdmFs2arCeaIQIADDOygAA8I5cIUnwXxtfIGBzebJ47N1ts7NOLj+w2PV+wsfxftcamWwJE0BQB+CoTX+BICjHLZffHvOJ//MnNF5GxXSExjBXA9f5OJKiMAGPw8p/ElyW8IheWcRurBfw+QI+DwAg/H9zJii0aGKHMFPR7QAABEFapUehsTi5ls5kYWIWpbpVbMy6SoGAXxx1qzjqVqunGLVlkgTfW4rfhPL5XKPxrc+a17adMvKPa+nX9z9bPxpDIKoPcbbfcPbFprEYAql3A4C+NhSCXNs4fcXJiCVHH8jgMLYm2uOsDOe7WCiRCMIELA73/PPUh4l5hVVUCp3J4/N5fAEAQPh/ITQKkRdbS4IgiBKR0FIGAgAAPH7LchUsGqVMakmgSCQAAKpp9FaxVdQ38gWCmzFZN2Nat9pLaxskCf5re7xrnviPHnYmKARZ+s+DYw+Sts11kiQBBHUAtkj6ESXjoROPRtfmJFamvq5MefXh8u6cu8dG7bypaDQEAJAYuLz83VPzOb/rO8/BK6qjMbjkM5sKX3W0H3znUJ/NvRAAQduLIuKbf3Q1+N5SGv9QyXiYrJpe26c0rMdqWI8V/Uj7lA0AIGq0v5EJ9C0bZqQRf2RpQm7pqw9FL9MK/a9HHn2QeGfr7CGG6gCAn4+HP0kmb5rp6DnSTF2RiMOgf7/w/OqbjJ6UiLR+IwAAAApp/42waIxl4C8Tuhd83xs31BBBwDty+zNhJUkAQSKwRdLPIIiKmb2Kmf1gry11uUlv/Gdk3frLcdNFZn1FedIT3ZEzzOduFKVtqinpYWl8DpvTRGtZL9NQDwAgKLReYiCjooUgqKbqzor7QvCtUnV7Ziu9sohalDFo5ppOwgAAAFCb8xYAoPr/MSzo+4IgwGGQjsMgnT/mOL39WO6+N/Tw3fjL6z0q6hsfvyfPdBy0eZaDKPGnmoYeFsfm8GhNLLH1MgwAgJoCsVUybWU5FIJ0WtyXgm+VrBszWzupBZeXXVJLIuAGaLb0TbI4XIEACE8q7jQBBHUM/pb0FzWZcW+P+Tj9cUW0+FbZdARBUV3YSuBx2AAAvNgSmIbSj9WZcUC00qS7qtIidRzchI+rM2IAAKqDW3feYghEFXP7moxYJqWKoNj8Va8mKyH5zMYRvieUjId2HHwrwpmt3Qi1NicRAKBgaNn2qbQQv4p3z8YHRqLQWACAQMAveH5ZTsdEZRBskXxnYrNKVpyK+G/TDNHiW1sTLQ1FonD2JYvLAwCokFqWwOSW1cVmlwDw/56N7nqdXuxhZyJ8HJ1ZAgBwMtNplYZIwDqY6cRkfaqi0tX/316JzyndcP75qVWThxlpdBx8K8KZrT0K+nNsLm/q7hvDjTXDtreseH+eUgj+PzOm0wQQ1DE4s7W/UDIehqDRSSfW1H18z+Ow2I2Ujw+DGLVlhmPnAwBk1XSJGgZliRG0T9k8Dqsi+UX8n8t0HdwBAPXkFPGpIV2CxhGyb/9dlfaGx2JQizLTr+whKKrrOrb+MgcAsFywE0GhYg8ubCjN43FY1RmxSSd8UVi8vL5Zp8H3lsYyMgCAqN7OQIzGMFd6ZVHKuT/YDfVMSlXyvxtpn7KHr/wLfKHjHfpmWRtrYtAon6An78gVLA63vpF5KuJdaW3DAhcLAICeqryBusKjpLyskloWh/s8pWDJ0QfClkRyfoX4VJIuIeAwf92Lf51exGBzM4prAv6LUlcgznAY1Dal/7zRKBTK+8/7H8vqWBxuTFaJT9BjHBZtrqvSafBfG4mA2zrbMTarZMeVN2V1jbQm1r2E3O1XXlvoqy0dZyVJAgjqGOwj6S/QeBmX3WFZoUcS/v6FRa3GyMjJ6ZjYrT8jbB8gCMph44XU4B2vt09D0BhlUxu7dWcwBCKl8EPc4SWDpvsOnre1G4WiMDgbn38+XNpVT04RCPgqprZDf9qHxrfegwEAoGwy3GXvw6xbf73Z6cZhNBIU1XSdZgyauRaNxXcafG9h0ykAAKxsO5NVNYa6Omy8kHPv2OPVIxAEpTzI1mX3AyXjob1YOtQ3ZHCYhzs9D9+J++nYw2pqk5wMzkRb+dxv02bYmwIAUAhyaZ37H5dfT951HYNC2ZponfOdRiJgPxRVLwwMW+Nm273pmTgM+vjySX7XIpPzH/D5AjtT7QOLXWVw7fz5tTHWjPD3OnI3furuGw0MtrqC7AyHQes97ISjHh0H33N+1yJPhb8T/eh/PdL/eiQAYM5Is6BVUwAAvtNG6KspnHmS7Lr9SgODracqv8h1yDoPW1FdOk0AQR1Aetgn328hCNLrn4g/mJh93rU5iR6XyNIOBGqtJC4sMXB5z9/7oaGhXl5evTs08OPxPHwnIbes6JyvtAOBukx1YeCNGzc8PT2lHUh/AUdtoK8JtnchCL4PIEgysEUCQRAEQZD0wRYJBEEQBEHSB2cbQV/LyO09210Ngn4IoZtnSTsECPo+wD4SCIIgCIKkD/aRQJ2L2eddm53gcTlf2oEAAMDb46s/Rd0WPp588m27O773mWfrRjaUkQEAODklt/OtzyKBvmueh+/E55QVn/8m1sisPB1xKyZb+Ph94M/6avIdp//GOWy6mFdeDwBQJhFyg1ZJOxzoWwFbJND3B4XFzbhaLPqRkp+WceNgXU4Sj8OU0x5oPPVXQ1dvSfLhcVj3F7R/MI34ITuN5fkZ1/dXZ8RyGQ2yavoGY7xMZ/giCAoAMOFoDAAg7sjS2uyEntYKgjqEw6LLgj874oDN5a079yw0OivA23n1NJtW6fPK6/eFxkRlfmJyuPqq8tPtTX2njSASsJLn0LHk/MqjYYnvyBV1DQxtFTm3EQM3zrQnEXBtUzYy2S5/XCmqpkYdXCzc6i3+yFIAwKLAsISc0i4VCv3YYIsE+r6VJYYn/PWLtsM014NPCEoaBc8uJQf9zmmsN3H36fReNBbfdr/58reP444s1XWaLvyRSal6s9NdwdDSdX+EjLJWZcrLt8dXM2rLhv1ysPcrA0ESo9CZS44+4HD57T6bU1o7we+6laH6g52eeqpyz1IKfjvzNLmg8r+NMyTMoWNx2aWzD92eZjMw3M9LiUR4kVb4279P4nNKw/292p4guOPKm6JqajdKgfobOI8E+r6lX91LUNaw9T1J0jTC4GVN3FYauM7LDD3CbqR0Izcuk55yYZuu03T1Ic7CK9m3/+Yy6XZrg4gaBigsTst2stns9fnPQhpK83q1HhDUBRQ6c2rADScz3d0LnNtNsPtGNJfPD1nnbq6rQiLgZjoM+mnc0OcpBXHZpRLm0LG9odGqcjInV07SV5OXk8HNsDf9acLQpLzy1IKqVimfpRRceZ3ubmvSjVKg/ga2SH58kf7T7y805DLp4hczrh+446lZkxkn/LE6PTp6z9ywJQPvLzR8tn5Uzt1/+Bx2u7m92enx6Nch4lfIjy/c8dSszogVXaEWpscdWfrwJ7N78/We+Np9uBzAaaL1drUAAIBDpzaW56uY2qKwLX3FOo4ePBaj4v2zbmSYeeMwp4lmtSRAdKUk9r6qhRNOTkl0RdtuChAISuMf9CRy6Gtz2xOq+9NxOpMjfnFfaIzqwsDYrOZTpqMyP806cNvwl5O6Px133BwSGJbI5rR/hNO03TfMV/8rfuXcsxTVhYExWS0HVqcXVS8KDDNZeVp76TGb9Rf8rkXSmli9Xa1m1dSmlZOHb5nt+KUEYywN/LxGqci1nNgw1EgdAFBYRZEwh46525ns8nbGYdCiK2Y6KgCA4s/7QuoamWvPPpvpMMjFUr97BUH9Chy1+fHpO3vWZCWUv3uqN3Km6GJJ7D2iur6quQMAoDY7IXrfPB27qROPRmNk5csTI96e8GVRa6yW7ulGcfXk1Ej/6epDnF32PpJR1qzJiH0XtL4mK37MngcIuvXvG7uh7uHPg7+U1YTAaDmdgR2U1bwP+ue9xDiSEgCAWpTZ1cibqkvyH18wnfEbQUlTeIVRW8ZuqJfX/exENKKmEQqNpeSndTV/qC95jR4cn1P6JDl/lmPLP9+d+BwDNQVHM10AQHxO6dxDd9xGDIw/skReFh+eRF4VFFFDbdq3aEw3ikspqHTbE+piqR/hP09LiRST9WnN2WfxOaXhfl4YdOsvfrUNjEGrgr6UVdzhJSbayl96VshEW7njNL9OHNbqSnl9IwDAUF1Rwhw6tnLy8FZXMoprEASY6aqIX9wU/ILH5x9c7Prg7cdulwX1H7BF8uPTcXRPvbCtJPa+qEVS9/EdvbLIfO5G4Wd52dsnaCzecpG/8JNYb/TswpdXi17f6F6L5MMlPxxJyX7DOWG/habNBIv529+fXl8SF6Y3qvXGDDg55bYzOSSHIymSNI1qcxL5XA4K0zxlTzjJlEWt6Wpu2XcCUTi8idsK0RUmpVoYpHgyBEFhSYpManW3w4b6wHQ7k60hr+7G54haJEl55UVV1M2zHIUt2Ij3ZDwWvWu+s6YSCQAwZ6TZ5dcfrkdldq9FsuPKGyUiIfg3NxwWDQCYaD1gp9eotWef3k/Ine1k1iqxipxMHx8GVE1tCnqcbK6rYmeq/TUyD43OOvs0eeMMh0E6LS2SWzHZ9xNyz/pOVZFv53BNCGoLjtr8+LCy8lojJlWmvOQwGoRXPkXfAQii79J8fNSQRX4el8iyqjqiW2TV9TlNNA69y5PROIyG2uy3ahYjxYdRNIe5AgDqPr7vUTW+wHKRH6O2POn4anplIaeJVvT6Rv7TEAAAn8fp9F5xTf9j767Dokz+AIDPu8mSSy7dSJgooKiAiAoGWIAdZytne2d3t3fe+bPOOLtQUEFUDJAUlZDubpYttnd/fyxHLCGxsIDzeXx8YN/Zeb/Au7PfnZl3pqIw78NDE7elWDmlugf5HBYAoC7XqYPCYPlsZqdjh7qQoix+4lDj4PgcGrN2/PFJeAqCgFkOlqJv989xzL36q66qQt1TDNSVqDXsagarveeiMTnRaUWjrfRE6YiIyyADAMCXzI4n3JJCprPmn/Gj1rAvrHJDo8SnnXZGdmm12vyzlj6XTjyN2DPLYfO04XWHisn0bf++nzTMZPoI81ZqgKCGYB/JT0Hfybsgwr84OlDfyVso4BeE+6tb2ctp1I7s8rnsrKDrRVEvGaW5HDpZKBAIBXwAgOj/dmFVlQqFgrzQx3mhj8UOMSuLOv+DNKVtO3HU9rvf7x15s9EBIyOnMdBx+KYrwb+NxcjIt6uevI8PBQKe0bj5DR/E4AkAAAFPPLkR8DhoPPzY19PNcrB6FpUW8CVj1mgrvkD4LCptpIWugXptxsnm8v55G/ciOiOnjFLNYPEFAr5ACAAQ/d8uJWS6QCh8FJb8KEx8TZrCSlrnf5DOyCmtnnXyWTm15t6WaQMNNSRbuRGJWHF7YzWDFZZcsO3me9/I1CfbZhDlZAAA66+8BgCcWuIi2TNCfRvMSH4KpMFj8EpqBRH++k7e5d8/sSnl+vN31x2NPrui+MtrS8/N+o6eeKIGGoP7dvm3nPcdXwO+4WIe3YBkPZZkPbbuW2p+CgBAjtT8QiMtKYx8oWwyRGy9NRllDQAAh1rZ8EEhn8ehV6tZanY8YqhbOA80UFOUfRaZNmu0VWhSXjmlZu9sh7qjS88HBH3L/G26vfcoCw2iHA6D3nzt7Z2PiR0+3YIxA84uGy+JwCUmOr1owRl/ORnsyz2zLBvP8JAgopzMZBtTXVUFl913/3j+ee9shzsfE9/F515dO1lDSa6LTgr1STAj+SkgaIzeqOlZQTe4DEp+2FOMjJzOiCmiQyxySXFMkO6oaZZeW+rK11QUtFATQFAosb4TdoMZFQRVLQRB1ZS3+HQxnZzZ2ustSAMAACAASURBVKzK1M8AADULu7Y/hVGaS8lNNJ++TuxxGWVNGaIGNT+14YO0wnQhn6dsYt3ewKBuhkGjZtqbX3sbR6lh+4anyslgPexq70EtIdNffc2cbm/++4wRdeXzK1rsz0ChEEHjvpNySk3d19oqCigEaeXpYjo/s7UtYjKKvY779tNWubdlmpqibOcrrFNQSTvpGzHSUnfW6PoXr2gGSWphFQAgKa8cALDs/Mtl5182fKLDtn8BACU31zed7QtBAGYkPw99J++MgCvFX14XRQfqjJiCwde2UHwuBwCAbzB5k1aYXp4UAeruZGkMT1TnpkTzuWw0Fi96pCwhtO4oRkZO1XJ4RWI4q7pMhljbRVyRHPXt8habX/9SNhksVlsnZ7YCAOJv7in58mbc2RAUGgsAEAoF2W9vKeiYqZq3IyOpTI0GACgZDmh6SG/0jKyg62xqJV6x9iNmQbgfgsbojprWtDDU08xysLoU9C3oa1bAl0wPu36y+NopQWweHwCgKl8/9JZWVBWeUgAAAM0N2mgoyUWlFrG5PDy2ts0MSaxfNVhOBjvCQicsOb+MwqjrFYhMLdz0z9sLq92GGJHEauuGma155dRZJ56aaqk83eHZ7DqqnaGmQPCNSE3ILfcaZVm3HlpcThkAwEhDCQBweMEYsQnCN4Ljt1wPrluzFYKaBRPVnwXRaKCinnnyo9NcBsVgzOy6x2XVdeVIBkXRgdT8FD6XXfItOPLUL7oj3AEA5MzYplNJNIe4CIWClEenuDVUVnVZwr/7eI3XGhkwbzeCQoUfm08rzOBz2eWJ4TF//YrC4hX1xe84kAjSEGdGaW7s1e0cGplVXfbt0hZqfsrQVafrbgmuTIny9daM/Wd7K5XQizIBAHIazQz0mE9fj1NUiT67gl6SzeeyC8KepT2/YDFjQ8OJwFCPNchQw0JX9cTTyGoGa45D/Qd6PTVFAw2llzEZyQWVbC7vbWz2onPPRT0o37JKmk4lcRlsKBAKT/hGUmvYZRTGnjsh1JpGC/bsne2AQqHmnPJLL6pic3lhyQVrLr7CYdHSegPeevMdi8u/tm5yh9ORyNRCtflnt9581/SQDA5zYK5jfE7Zxqtv8sqpTA4vIqVww9U3SrL4Fa6w7xDqONhH8hPRd/T6fudQ3TIkIgiCGrHlWtz1XR92TkbQGJV+w+w2XMbIyFXnJEScWGQ+9Ver2dsaVeLkVVOen/vxYfrLSwRlTcNxC6zmbI88+YuAV7sYlIrZUKdDL5Ifn/64ewqXSZchquuOnGY+fX1dn4pkkQY7j9hyLfXZn698bBAEpWJu63TgedPOGFSTpVAa4jCqAQBY2WYmw+IUlJ0Ovki8d+TDzsk8Jk1ey2Tw4oNG4xdJ8EeAupT3KMsDDz7VLUMigkKQfze4b7/1wW3fPQwKZWumdfXXyfIy2ITc8vln/ddNsd3hNbJhJbNGW+WXUx98Svrfq69aRPmFYwfu9B618Kw/+78V1YaZaAbunXXyaeSkAw9oTI6Gkuy0EeYbPezq+lQka8/dkAsBX+q+3XsvZO+9EACA5yiLi6snMjm8N7HZAIBhG6+JPXH+mAHnlo3/YQ11j2NQzX9q/WXcYHUluUtBX5123OLwBDqq8sNMtLZMH26godRseQhqC6TZnnnohxAEsdt4WdfeQ9qB/HQ+n/cpjHzecKe9H/p++wBWXtl82touCkm0014v2vu3IMI/+uyKzr/2Hz58OGvWrG5eWuPntOp/gf7R6WI77XW1ffdCleVl1rvbdlH9op32evLev2rzzz548MDb21vagfws4KgN1MeJJvPqDJ8s7UAgqDepZrB8I1LgfjRQd4KjNlAfh5VTmvi/b9KOAoJ6GaKcTPyfy6UdBfRzgRkJ1PsIuBxfb00AgNvfn8VWEOlmbzaMohVlAgAabsUHQV2Bw+WrzT8LAPh6dqm+uqK0w+mUEb/dyCgmAwBU5GWkHQvUg8CMBOplbNf+bbv2b2lHUWv8uTBphwD9FC6unthwwmlvF3lysbRDgHoiOI8EgiAIgiDpgxkJ1KKww3P8FxhLOwoI6tG8T/jqL/1L2lFAUF8AR22g3q08MSz0gKe23aQRm/8RO8SmVr7ZOBojIz/uzEcMXjbj5eX4m3taqqf/3J11twdzGZTs4DtFUS8YZfkcOhmNk1HQNtEZ4W46aUXDPY0hqBe5+OrrrtsftVXkw08sEls27eqb2G0334stqEqtYV97Gxf0LSu9iMxgcYjyMoONSJ72FtPtzSW7gTAE1YEZCdS7qfcfZTx+UdbrG0XRAdp2kxoeir+5h0OvHr7xSt2S+QCA4Zuu1u3p0ywuk/Zh5yRmVUn/uTt1R07FyioyKwtz3t37fudQWXzI6N0Pu+ongaCuV1RFP/Qg7Ngi59aLxWWXzjvjL4PDbJ0xYswAAyU5fHEV3S8qbcv14Gtv425t8lBVgHtfQ5IHR22gXm/A/N2y6rqx/+zgNljPvjTufX7oE6NxC9UHjG5XbQWffGlFmVazfjdxW4JXVEVhsHIkw/5zthtPWFyWEFIa90HC0UNQN3K3Nbv2Nu5LZmubSVVSmXNO+SkQcG8PzPEaZamuJIvDoA00lNa52z7b6RmbU7rkzxfdFjD0U4F9JD87cmZs0sMTVWlfgFCoqG9pMWM9acjYZkuWf/+U+vSPqoxvQj5PVl1X39HLbMrqulEMDr065cmZ4pggVlUJhiBPNBls5fWbsql1W452EkZGbujK058Ozfp+55D18hMAAB675tvl32XVdQfO393e2tg0MgCAaDxE7HFLr81G4xcq6MIFo35G37JKjz8J/5xeLATASk9t41Q7l0GGzZYMTco/6xf9NbOEJxDoqSl6j7b0mTgMh0WLjpLprNPPogK/ZpaQGfIErLUR6fcZ9kNNNNtyVCK2TB8RlVa08eqb4EPzsC1swPt34JcyCuPvVa5EOfFbc4cYkVZMsP7rZczb2OxxQ4wkGBgEAZiR/OTIGd8+7vEwdl1ivfwkRkYu5cmZ8KPz7bf+qzl0nFjJypSoT4dn69hNmnDuE0ZWsTg68PNfv7IpFYMWHxQViD63klaQNnzTFSWjgSxyacKt/aEHPMcefy2vZfLDow1xaFUvllqBFow/+0lBx7Tp4xqDnAxd5me/vaU3eqaa5fDkBydqyvNH736IITSzVU3r1K3sAQB5H+6r9huGNNgNB6+kjldSb29tUB/wNbNkysGHS8cPPrVknBwee/pZ1JyTz+5snjq+yVtyZGqh13HfKTamkScXKcriA2IyV18MrKDU1G2Eu/yvgNTCymvrpgwyVC+pZuy9GzL96ON3h+aZaCr/8GhDlTSm+eqLLQUccWKRmbZKs4fk8JgjC8csO//yr5cxGz2a3x/7eXS6irzMmAHNbDwJAPAcafHXyxj/6HSYkUASBzOSn1rC7QMEFa2BC/ciCAoAMHDhvqKol1lB15tmJEWfg9BY/IAFe2WUNQEAeg4zc97dyf3wQJSR8Lns8oRQg7FzVPrZAADkNPSHrTkX9KtdaewHeS2T1o+KnQinoDLjYWtdyi0ZuHBvaey7b5c2DV19LiPgiqHLfI2Bjh2oR9Vi+MAFexPvHy37HqptN1nVwla1n43op4Z+Tvvuh2opy++f64hCEADAgXmOLz6n//M2rmlGEvg1E49F75vrqKksDwDwHGVx60PCvdAkUUbC5vJCEvPmOfW3NdMCABioK51f4Tps4z/v4nNNNJVbPyp2IlUFQse2ExICMG14vwehSaeeRk0b3s+IRBQrwOHxs0urR5jrIC3MXrXUU0MQkJhf0YGzQ1DrYEby8+KxGBXJkXqjZ4jSEQAAgqDcLnxptvDABXsGLmh0o4qshn55YjiXQcHKKaEwWLySWlF0oKa1i+aw8Sg0FktQqNt5rvWjkoIlKAxdeSrsyNxPB71klEkDF+5ttljUmWVNH8QpKDeMx8x9tb6jZ0G4f1lCSP6nJ2xKhRzJUNfe3XTKKryidDaXh6SFweJGpBTMHGmB+u8tGoUgsX80cxUBAPbPcdw/p1EebKCuFJZcUM1gEeVksBi0mqJswJfMcUOMJlgbY9EoBQKubp+51o9K1slfXEb+fnPTP2+f7vAUO0RncQEAcnhsS89FoxACDktjsrsiMOgnBzOSDkJjMEIBX9pRdAqrugwIhW18i+Vz2VlB14uiXjJKczl0slAgEP34ov8RBGW/9dbnP9dEnlqCxhNU+9mQhjgbOM/FyRN/eFSCSEPG6oyYUhj5YtDiA1iCQrNlfnivjQheSd1k4lKTiUsBAIzSnOKY16nPzud+eOB08Lkcqfne7F5EKOCjMRJ47WMwGAAAXyDsw7eDllEYQiFQU5D9cVEA2FzeP2/jXkRn5JRRqhksvkDAFwgBAKL/UQhyd8vUlX8HLjr3nIDD2JppuwwynOvUX1le5odHJUtXVWG758jddz7eDUmc69i/4SEFAg5BAKWmxYSDyxcwOVwlWbzEo+ppeHwB+O8ih7oHvNemgxQUlHgN7uzojRAUGgAg4HLaUjj67IqEW/s1Bjk5HfSfcj112p1cQ+c5DQsomwyecO6T0wE/symruDW0hFsHXq8bUZ2d0JajEiTa5kZWTZKb3ciRDE0nrxhz6AWruizV95wEa5YWLoOioKDU+XqUlJQAANSW3736ABQKAQCweW36+LH0fMDeuyFjBhoE7PHOuLS68Pq6eU6N3u+HGJEiTy5+sdt7zaRhNCZ7770Quy3XE3LK2nJUsla4Wg82Iu29G1JJZSKgPqHEolHmOqrJBRVcvqDZJybnVwiFYKChRldE1aNQmRwAAJEo4Q9OUCtg9tdBhkaGtKIsaUfRKQRVLQRBscilPyzJIpcUxwTpjppm6bWl7sGaigLxcgiiajFc1WK41aytVWkxH/dOS3582v63G206+p+OzWyVFAGPmxl4BUFjTSeJ73oqp6GPoDH0kt79RxehF2cZm0hgNV4jIyMAQGYJ2cZUq/O19UzaKgooBCkl039YsoRMf/U1c7q9+e8zRtQ9mF9BEyuGIGCEuc4Ic53tniM/pxe7H3p44mnkrY0ebTlap8MzW+ugUci5pePG7bm74/aHURa6DQ952PU74Rvx4nP69BHmTZ/4NDIVANDsoT4mo7gKAGBsDNet7j4wI+kgO5thz0Kan3LRW6DQWBVz2/Lvn/hcNhpb2wf7doszGot3PvqqYUk+lwMAwCvUt3G0wvTypAgAgFAoBABUJEV8/nPNyO23lQxqPxGq9LORIWpwaOQfHhXT4ZmtEoHCYAsjX1DzUrRt3cR2FS7++kbI5ynoWkgrNgmiZn4d6zi08/UYGRkpE5U+pxf34YwEi0bZ9dMOTcpnc3l4bG2D6bj9Fh6LfnNgbsOSon4UVfn6pcPSiqrCUwoAAEAIAADhyQUrLwTe/21af/3am7ZszbRIRDkynfXDo2I6PLO1oYGGGivdhl4I+IJqPIt1heuQOx+/77sXam+uI5qiWychp+xyUKzrUGMHK2nuud09vmSUKBOVDAx6/ShtLwJHbTrI1dW1Iu0bm1Iu7UA6ZcC8nXwuK+ZPHzalnMugJN0/Rs1LNpqwSKyYrLquHMmgKDqQmp/C57JLvgVHnvpFd4Q7AICcGSsU8JVNhiBodMxf66rSv/K5bA69Ov3FRWZlkeHYuQCA1o/2NNYrTqLxhND9M/M/+XLo1QI+l1lZnBV0I+avtbJqOhYzN0g7wM5iVZeVp311c3PrfFUIgri6ugXF5nS+qp5s96zRbC5/1YVX5ZQaSg37yKPwpPyKxS6DxYrpqSkaaCi9jMlILqhkc3lvY7MXnXvuYWcGAPiWVcIXCK1NNDFo1JqLQV8yS9hcHpnOuhD4pbCSJhrZaf1oF9k2015fXfFxeKNp5kQ5mXtbpiEAjN9z715IYjmlhsPj55VTLwR88Tj8yN5cpy/tQtyKV7E5bm4TkZZuOoK6ACL6jAu1F5PJ1NTW0Zu42nz6OmnH0imVqdFJD05UZ8YJgVBRt5+Z+5q6iZ9hh+dUpkR53MoCAFByE+Ou76rOikfQGJV+wwbM3YWRkQs/No9ekmM+9Ver2duYlUXJD0+Wxn9kU8oxBAUFHTOTiUt17Wt7m1s/KkEJt/anP/+f89EgZRPxN4zW97WRIxm6no8UfV1TUZjx4mJZQgijLE/AYWMI8vLaJppDx5lOXIaVk8D0C+lKffpnwauLxYUFBIIEFgL39/efNm1a9KnFTe8j7Uui0oqOPQ6PzS4VCoG5jorPZBtRqgEA8D7hG5lalPfPrwCAxLzy7bc+xGWXYlAoWzOt3bMc5GWws089yy6tXjfFdofXyMJK2gnfiA/f88opNQoEnJm2yrIJQ6YN7yeqqvWjnSTa1+bz6V/E/lJv43Jmn3wKABDb14bB4v7zJjbgS2ZGce2+NtbGmrNGW3rY9fsZ3qOzSqqH/3bDz8/P3d1d2rH8RGBG0nHbtm07f+kfl7NhfeBdCvpJcBmU4I2j1q5ceuzYMYlUyOfzLfqZDdaSubRaAp0uENRDrPzfq7hiVkpaOhqNlnYsPxE4atNxO3fulMdjkx+dknYgENRWyY9OEjCo7du3S6pCNBp9+uw53/CUiJRCSdUJQdIVnV7kG55y5twfMB3pZjAj6TgFBYUjhw9mBV3virtYIUjiqrMTsoJuHD92RHTXrqR4eHhMGD9ux50QNpcnwWohSCrYXN7Wfz9OGD8Ojtd0Pzhq0ykCgWD8BNfouCTHwwFwoXGoJ2ORS0J2TrIdbPX2dRAKJeGPIhkZGXa2NmOttC+udvsZJhlAfZVQCFb+L/B9YnF0TIypaRcuNAA1C/aRdAoKhXry+JGWimL0ycU8do20w4Gg5vHYNdEnF2uqKPo+fiTxdAQAYGpq+ujxE//o9JNPIyReOQR1m5NPI55HZzx68gSmI1IBM5LOIhKJgQEvBNWF4ftnsMhSW0gDglrCIpeE758hqC58FfCi6xagdHFx+fvChZNPo/bcCREtmg5BvQhfINxzJ+Tk06i/L1xwcXGRdjg/KZiRSICJiUl0ZIQymhW6cxKcUwL1KNXZCSE7JymjWNGRESYm4jstS9by5cvv3Llz7d33RX+8oDHbtDsBBPUENCZn0bnn194l3LlzZ/ly8fWaoW4D55FITHV19Uwv7w/v3xu7Lrb0+g3eEgxJF5dBSX50Mivoxhhn5yePHnbb9hwRERHTp3ogfM4uL/tZo63gtBKoJxMKwYNPSYceRQjRuKd+/vb29tKO6KcGMxJJEggE169f37ptB5MnMJq4wsB5tgyx7+9HBfU0rOqy3Pf3swMvEzCo48eO/PLLL10xd6QVVVVVu3fvvnTp4mAjzTUTrScNM8Fh4F2UUM/C4fEDvmReCPwWl12ycuWqgwcPqqj8YDMgqKvBjETyKBTK0aNHL16+QqVUq5lZK5nayGsZ4eSIor12pUsoFCAIHKrrg4QCPodeTS/JpmTEVKR/U1QirlqxfPv27ZK90bdd4uPj9+ze9eLlSwIe52CpO9BAXVtFXoGAk1Y8kLTwBUI0qqf0ldGYnKIqekJueWhyAZPNmTJ58oGDhwYNGiTtuCAAYEbSdZhM5qtXr4KCgqI+x+Rk51Cp1QJ+mzY0h6AOQKFQCopEI2MjO5thbm5uEydOlJGRkXZQAABQUFDg7+//Ljg4Pu5baVk5lfbjTXQhqOsoyMuRNNQHDxk61sVl6tSpOjo60o4Iqgczkp8Fn89fsGCBv7//8+fPnZ2dpR1OB23YsCEqKioiAt5iCvVlr1+/dnV1rays7APjCBwOZ9GiRb6+vrdu3fL29pZ2OFCPBjvwfwpcLtfb29vf3//Fixe9Nx0BAJiamqanp0s7CgjqWllZWUpKSn0gHQEA4HC4u3fv+vj4zJ079/Lly9IOB+rRMNIOAOpyXC531qxZr1+/fvHixZgxY6QdTqeYmZlVVlZWVVX1jcYagpqVlZXV1bdqdycEQc6cOUMikVatWlVUVLRv3z5pRwT1UDAj6eNEvSNv3rx5+fKlk5OTtMPpLNFCihkZGXZ2dtKOBYK6Sh/LSES2bt0qLy+/bt26qqqqc+fOdfP9X1CvAK+JvozD4fSldAQAYGhoiMPhMjIypB0IBHWhzMxMY2NjaUcheT4+Prdu3bp48eKiRYu4XK60w4F6HNhH0mdxOJxZs2a9efMmICDA0dFR2uFIBhqNNjQ0hFNJoL4tKyurT2YkAIC5c+eSSKRp06ZRKJQHDx4QCARpRwT1ILCPpG8S9Y68e/fu7du3fSYdETEzM4N9JFAfVlFRQaVS+96oTR0XF5fg4ODw8HA3NzcKhSLtcKAeBGYkfZAoHfnw4UNQUNCIESOkHY6EmZmZwT4SqA/LzMwEAPTVPhIROzu7kJCQzMzM0aNHFxUVSTscqKeAGUlfw+FwvLy8Pnz48OrVq76XjgAATE1N09LSpB0FBHWVrKwsDAajp6cn7UC6lpWV1adPn9hs9ujRo2GvJyQCM5I+RZSOfPz4sU/2joiYmZmRyeSqqippBwJBXSIzM9PQ0BCD6fuT/AwNDUNDQ5WUlBwcHOLi4qQdDiR9MCPpOzgcjqenpygdGT58uLTD6SqiG4DhwA3UV/Xhaa1NkUik9+/fm5mZOTs7h4WFSTscSMpgRtJHiNKRkJCQ169f9+F0BABgYGAAbwCG+rA+uRhJK4hE4ps3b5ydnSdMmBAYGCjtcCBpghlJX8DhcGbOnBkaGvr69es+v3QYGo02MjKCfSRQX5WZmWlkZCTtKLoVHo9/+PDh7Nmzp02bdv/+fWmHA0lN3x+q7PPYbLanp+enT5+CgoL6fDoiAm8AhvoqNptdVFT0U/WRiKDR6KtXr6qoqMydO7e4uHjjxo3SjgiSApiR9G5sNnvmzJlhYWGvX7+2tbWVdjjdxMzMDA45Q31Sdna2QCD4eeaRNIQgyMmTJ9XU1DZt2lRaWnrs2DFpRwR1N5iR9GI/ZzoCADA1Nb1x44a0o4AgyfsZFiNp3datW0kk0vLly+l0+p9//gm3v/mpwIykt2IymR4eHjExMW/evLGxsZF2ON1KdANwZWWlqqqqtGOBIEnKyspSV1dXVFSUdiDStHjxYiKROGfOHDKZfOPGDSwWK+2IoG4C089eSZSOfPny5SdMRwC8ARjqu36qW39bMW3atICAgOfPn0+aNIlOp0s7HKibwIyk96mpqRGlI69fv/4J0xEAgIGBAR6Ph5Nbob7nZ7v1txXOzs7v3r2Li4tzcXGprKyUdjhQd4AZSS9Tl478nL0jIigUCt4ADPVJmZmZsI+kjo2NzcePH4uLix0dHQsLC6UdDtTlYEbSm9TU1Li7u8fHx3/48GHYsGHSDkea4A3AUN8jFAqzs7NhRtKQpaVlaGgon88fPXo0/BDS58GMpNcQpSMJCQnBwcGDBg2SdjhSZmpqCpsnqI8pKSmpqamBozZiDAwMwsPDNTU1HRwcYmNjpR0O1IVgRtI7NExHBg4cKO1wpM/MzAxmJFAfA2/9bYmKisqbN28GDRrk7OwcGhoq7XCgrgIzkl6gpqZmypQpMB1pyMzMrLq6uqKiQtqBQJDEZGVl4fF4bW1taQfSE8nLyz9//nzcuHHjx4/39fWVdjhQl4AZSU8nSkcSExNhOtKQ6AZgOJUE6kuysrKMjIzgmmAtwePx9+/fX7hwobe397Vr16QdDiR5cIW0Ho3BYLi7u4vSkQEDBkg7nB5EX19fRkYmPT19xIgR0o4FgiQjMzMTTiJpHRqNvnTpkoqKyrJly6qqqrZs2SLtiCBJghlJz8VgMKZMmZKUlATTkabgDcBQ35OVlfWT30PXFgiCHDt2TEtLa+PGjRUVFXD7m74EZiQ9VF068u7du/79+0s7nJ4I3gAM9TFZWVleXl7SjqJ3WL9+vbKy8tKlSykUyt9//w2HuvoGmJH0RAwGY/LkySkpKTAdaYWpqWlISIi0o4AgyaipqSktLYWjNm23cOFCIpE4e/bskpKSe/fuycjISDsiqLNgXtnj1KUjwcHBMB1pBbwBGOpLMjMzhUIhvPW3XTw8PAIDA9+9ezd58mQajSbtcKDOghlJz0KlUsePHw97R9rCzMyMQqGUl5dLOxAIkoCsrCwEQYyMjKQdSC/j5OT07t2779+/u7i4wOUAejuYkfQgVCrV1dU1Kyvr3bt3VlZW0g6np4M3AEN9SWZmppaWlqysrLQD6X2GDRsWERFRVVXl6OiYn58v7XCgjoPzSHoKCoXi5uaWk5MD05E20tPTIxAIaWlp2tra6enpGRkZGRkZixYtgqu2QL1CYGBgVFSUiYmJsbGxiYlJVlYWHLLpMGNj49DQUFdXVwcHh6CgIHNzc2lHBHUEIhQKpR3DT+fQoUOrV69WVVWte4RCobi6uubm5r57987S0lKKsfVwRUVFycnJGRkZ6enpaWlpYWFhVCqVx+MBAFAolEAgKCgo0NHRkXaYEPRj/v7+U6dOFV23AAAsFquiomJnZ2dqairKUYYMGaKlpSXtMHsTMpk8ZcqUlJSUgICA4cOHNzxEpVITEhJGjRolrdigtoAZSXdLTU21srKytLT8+PGjKCmB6UjbnTp16rfffsNgMCgUisvlil29KioqlZWV0ooNgtqlqKioafaMIAgWixUIBDweLyQkxMHBQSqx9V4MBsPT0/PTp0++vr7jx48XPchiscaPH19SUpKcnIzBwJGBngvOI+luR48eRaPRaWlpTk5OlZWVonSksLAwNDQUpiM/5OPjo66uzufzORyOWDqCIIiNjY20AoOg9tLW1lZTUxN7UCgUcjgcAICzszNMRzpATk7Oz89v8uTJ7u7ujx8/BgDweDwvL6/IyMisrKwbN25IO0CoNTAj6VZ5eXm3b9/mcrlcLjctLc3R0XHs2LGFhYXv378XzdOEWkcgEPbu3dvsakg4HE6snxaCejh7e/tmL2Yej3fgwIHu634P8AAAIABJREFUj6dvwOFwd+7cWbx48ezZsy9fvrxy5crAwEAejycUCnfs2FFTUyPtAKEWwYykWx0+fLiuAeJyuenp6aWlpc+ePYPpSNutWLFCW1u7aTvO4XCGDh0qlZAgqGPs7OyaDiJgMJgJEyaMHj1aKiH1DWg0+uLFi9u2bTt9+vSNGzf4fD4AQCgUksnkv//+W9rRQS2CGUn3KS4uvn79OpfLrXuEy+WWlZUtWrSoqqpKioH1Llgsdv/+/U3nPwmFQpiRQL2Lra2taIymIR6Pd/DgQanE08fIycmlpaWJJg6LiDqfYHvbY8GMpPscP3686YOi4RsnJyf4Imm7hQsXmpiYiHWTKCoq6uvrSyskCOoAW1tbBEEaPoLFYidPnmxnZyetkPqMmzdv7ty5s+njLBbr1KlT3R8P1BbwXptuUlZWpq+vz2azmz2KIIi1tXVwcDCRSOzmwHqpBw8ezJkzp+HVO3bs2ODgYCmGBEEdoKurW1hYWPctgiDR0dFwjnYn+fr6enl5NewdaQiPx2dnZ8M7q3sg2EfSTc6cOdPSywONRhMIBDc3N9FgJ9QW3t7eVlZWaDRa9C0ej4fTWqHeaOTIkXWXMRaLnTp1KkxHOqmsrGz16tUCgUCs/6mOQCDYv39/N0cFtQXMSLpDVVXVn3/+2XAGiQgajSYSibt27SooKDh8+HDDNdOg1iEIcvTo0bocjsPhWFtbSzckCOoAW1vbuvFHHo+3b98+qYbTF2hoaOTm5t68eVO0cmvTucNcLvfq1aspKSnSiA5qDcxIuoNYOoIgCAqFUlFROXz4cGFh4b59+5SVlaUYXi/l7u5ua2sram6EQuGwYcOkHREEtZutra2occBisZ6enoMHD5Z2RH2BjIzMwoULk5OTQ0NDPTw8UCiUWF6CQqH27NkjrfCglsB5JF2OSqXq6uqKdspGoVBCoVBHR2fLli0rV66UkZGRdnS9W3Bw8Lhx4wAA8vLyVCq1pU5aCOqxqFQqkUgUCoUoFOr79+9wmcSukJmZeeXKlQsXLtTU1AgEAtG7HoIgnz9/hp9kehTYR9LlLly4QKPRRB2zZmZmt2/fzsnJWb9+PUxHOs/FxcXR0REAYG1tDdMRqDdSVFQ0MjICAMyePRumI13ExMTk2LFjBQUFp0+f1tPTAwBgsVgAwO+//y7t0KBGOthHwmazExMTy8rKRB/9oZaw2ezVq1fT6XQjIyNPT08bGxsEQfB4vLKycv/+/VVUVKQdYDOEQmF2dnZ2djaZTO75XWhpaWm7du1yd3dfsGCBtGORmB5+hUhRn2x5/vrrr0+fPp09e7ZX3P2hoKBAIpGsrKzweLy0YxHXlrZLKBR+/fr1xYsXiYmJAIA9e/YMGDCge8Psyzrbdgnbo6qq6ty5c04OozD/TQ6HOsPMxGjz5s3fv39v11+hi/B4PD8/v1mzZisqwUktPYWRqVnPuUKk6L+WZzRseXoIDBrt5DD63LlzVVVV0r46atuu2bNnE+GEvB7DzKxfB9qutvaR1NTUnDhx4uSJ4yihwM2cOMZUaaC2nKYCTh4PG4jW5JJZBsriozMcnqCqhpdcVhOeTQlMpWaX0z2mTDl99qwU15L39/dfv3FTbnaWsuVIpUHjFU2GyZAMsXJEgPSCcT1GXiIKRyBoGks7EIkR8Dg8WhWjIJmSEk75FkgryZ7i7nH2zOmfcLeB+pYHCNwsVJzNlAdqy2sq4vtSyxNXSFMiYAxVCNIOpE3obH4JlZ1QRH+fTn6VUiUAqN9+3/r777/LyspKJR5/f/9NmzZnZWUOtXccNW7ywGHDdQxNFInKzW4Y1BS1mozD42UI0gm+7+Fy2NVVlZkp37+Gf/z4yi8/O9Pdw+PM6ba2XW3KSJ4+fbph3a/kyor1DloLbEh9qS2QOqEQvM+oPvy2ILuKtXHT5r1793bz/JKMjIzVa3yC377RGDFNb+oWGQ3D7jw79GNCIfn7+/zHh5ml2Zs3bez+K0SKnj59umHdWnJl+Xon3YV22rDl6WnobP6/0UV/fCxQVlE7d/6v6dOnd+fZMzIy1vj4vH3zZsJU76Wbd+samnTn2aEfEgqFkR9eXziyMz87Y9PGNrVdP8hIhELhzp07jx075m2tsd1FT10eK9GAoVo8gfDW59KTH4qsBg5+5v9cQ0Oje84bHBw8Y6YXoqxjMOegohlcuLrnEgp4Je9vFfidHNzf6rn/s267QqSlvuUZqrljgqG6PE7aEUEtKqdzjrzOefi1ZNu2bYcPH+6eOebBwcGeXl4a2vobD54ZbDuyG84IdQyfx3t6+8qVUwf6W1n6PftB29VaRsJkMhfMn/fc3/+Eu5HXEPUuCBVqJKOCufh+hkCG+DLwVf/+/bv6dFeuXFmzxkfVZrLJL2dQ2B43SQ1qilmckXp+MREneBXwshuuEGmpb3mmmnkPJUk7HKhNHn4t/d0v3d3D49btOwRC145AXblyxcfHx3ny9B2nLuHwP0uXYa+Wm5H6+5KZKAH/5csXrbRdLWYkAoHA28vzXVDAP7NMhxsodlmcUCPkGt6SB+n5TGzU5y+iu9S6yL179+bNm6fnsVHfYxOA9832Hjw6OfXvJZjq/C+fo7r0CpGW/1qewGtzLYYbKkk7HKgdonIoS+6mjHWd+PDR4zZO4+gAUdu1ZMOOJRt3wnv+exEKuWr7Mq+S/OzoqBbbrhYzkh07dpw6ceLuAvORRrBR6FZ0Nn/a9RScmv6n8Ah5efmuOEVMTIyDo5Oa0wJDb7hqYe/DZ9ETj03TJ+Iiwj510RUiRbUtz+IBo4zhrpO9T3QuZdb1hM2/bT18+HBX1B8TE+Po5DRt/vK1u491Rf1Ql6qh01bNGCuHw3z6FNps29V8RuLr6+vp6Xl2mgkcrJGK/Gr2lKtJ4ydPvXvvvsQrr6ystLDsj+gOMv/1Wq+4lQZqilWRn3h4isfE8ffv3ZV2LJJU2/LMMIeDNb3Xw6+lG31THz9+PGPGDMnWXFlZadW/f79BNseuPuy6PhioSxUX5C53d5gwfty9u820Xc1kJDU1NZbmZvYa/DNT+87tlBKXXck6+jYvIodCY/P1iHhvaw2f0TqolnsQ21v+XTp5we2U9+/fjxkzRrKRr/HxuXnvyeBDH9EEBcnW3GcwS7NznxylpETwWDQZNT3SKG/dST6tZ29CHjf9xpay8MdG3rt13Fa1vUIBlx2+svkXmqbjXNPFJ1s6Izn+XeK5BV1xhUhLbctDEp6d0U/asfRc2ZXMo6+zw7OqaWyenrLMrKGaPo76rbQkAAAuX7j5aerjb6W73YxXO4j3lscX0k68zYnJo7J4AhM1wvKRurOHabarhqY2+qZFlCDJaemSvSXYx8fn0RPfux/i5OThRILm5WdnXDy+51tECING09IzmOS1YP6aza1kbykJ366c3J8QE8lmswxM+nkv9Zkya5HoEIfNGmPa/PouHnN+2Xbiwg9raEnEu1ebF01vtu1qJtDjx49XVVRsG6vbeqWdUUzl6OyNyK9md90pulQZnTv1n+80Nu/FioFpO+x2TTA4H1K482WWpMoDAMaaKY+3UPVZvYrH40kw8sTExMuXLuvO3NF16QibXPxpiQ6rIr+L6u9qHEpZ/JGpPCZt8O4X9hfSDL125b84n3l7ZytP4TEo38/MYZXldKBCFBY/+lqh2D/LtdcAAGp2Hq2cVHnQWLUh41et8ZHsFSJFx48fr6qs2DbesOtOUUxha+/8mE9mdd0pulQZjeNx6RuVxXu5emj6ntG73Yz//JC383l6K0+hMHlzrsfnVDKbPRqYVDHpf1/lcOhXa4Ym7RzpPVRzy9PU/4Xmt72GZu10NaomV544caLtT/mhxMTEy5cvr9p2qOvSkbLiwpF6hOKC3C6qv6tVlpeunO7MoFKvPg99m1Lms/Pwzb9OnNm1saXyH1/5L5symiAndy0g7FVC4USv+cd+X3P30jnRURxeJjyfKfbv+D8PAQAu7p5tqaEl9mPdRo+b5OPza9O2SzwjIZPJp06e2OCopaHQhbfbhWdTuq7ybnDuYwGDw7/g2c9AWQaHQblaqKx30rkVU5pR0fyLtr3lRfZO0E9Pz7h/X5IDN9u271AwHKhhP1OCdYqhpIR3XeXdIP/5OT6bYbHygoy6AQqDU7V21XNfX/zhFrM4o9nyPAYl/shUpX4jjGbtlUiFfDYj684uNTsPopVD66EazNqbkZ4u2StEWmpbHiddUte2PNVdV3k3OPc+l8Hh/2+WpYGKDA6DcrVU2+Bs8G90UUZ5TbPlKUyex6VvI4yU9k5qfq2OQ6+ySIr4814WhqoEWRx65SjdWcM0TwXnVDN5bayhWWpy2HWOOidPHCeTye39GVuyfccO8wHWbjPnSqrCpr5FhHRd5d3g+rmjTAZj/9//ausbYXF4hwnuv6zb9vT2ldyM1GbLXziyU42ktfePa7qGJgRZuTnL1032Xnj19EFqdfN/NSaDfmb3pnHunrYOYztWQ521e46npac1bbvEM5J///0XJRQssPnBIG5iCWPJvdT+xz4bHoi0P/f1QFAujcWvO7rgdvLIP75lV7J+uZtideyzxZHo6f98jy2ki47Ou5W8zjcDADDi7Fejg1GiR0b98S2phOFyIc7oYBRfIAQAfM6jzb+VbHn0s8GBSLszX3e+zCbX1OdTM64l2p758r2Y4Xk90exwlOmhKO8bSUklDNHRmdcSTQ9F0dj1IQEAzocW6uyN+JgpgSbJ/3vFSENFZdn67a0nWqoKheBlYqVEyosYqcq4Wapc+t/fnQ9YpKCgICDgpeaEVa3fXMPIS0w+vyRybf+wFYYxv9tnPzjAY9bvIZJ4dkHMtpHM0uykP3+JXGsV4WMRf3Q6LTu29uiZeWlX1gEAYn4fEb7CSPRIzLZRjPykb3tcwlcYCQV8AAA1/XPi2fmRv1qGLTf4/Jtd5u2dPHr9FRx/bMbnLbb0vO8Jxz0jVpuFrzL9ftKbkZ8kOppwbGb4KlM+s9G2JgUvz39aolOd+LHzv6XyaH8l85EY+fruStWhE4FQWBHzstnyXGq59oRl+tO2SKrCvKcneTVU49n7fhgqgWSkOtTt7/9d+mHJnu/ff/9FAcFCO+3WiyUW03+5nWh1KMxgT8iIU1EHAjOprPpmYf7NhJGno7MrmYtvf7c8FGZ+4NO0y7HfCmovlbk3EtY+SgEADD8VZbg3VPTIyDPRScV0lz9jDPeG1rY8uZR5NxMsDoYZ7AmxPRm583k6uYZbd4rpV2JtTkR+L6LPvBpnuv+Tyb5Q73/ikoprG7cZV2JN9oWKtzwf87R3fvyYLoH3Zr+E8pFGRGXZ+nWhJlqpCYXgxffyZsuX0znLR+lucTFs9iiFycuuZNrqK+Iw9W8EHgM0mFzB25TKttTQioV22igguHXrVnuf2KyCgoKAly/nrNzQ+s016YnxW5d6uw3UdjJW8hxpef7gNjqt/tPv5oXTvEb3z8/O2LrEy3WA1nhL0uoZLkmxMaKjG+d77F+/BAAw097CyYQoesTbYUBGUvyC8bZOJkQBnw8AiP8csWnB1An9NR2NFKeP6Hd610YKuaruFKtnjps+3Czte5yP1wQXc7Wx/VTXzp6YkRQvOrrGc/zYfqoMOrVhzP/+dXKkHiE65G3nf0vBzx8NtXdUUq7fUMbRzUMoFL4PeNq0MI1SnZ+dMdBmBBZXv/SDi/tMFrMmPDiw2fqvnD5Ao1LW7T3R4Rrq6BmZOrm6X7wk3nZhxL5/+uSxmzmx9bUR44roM64lOhgr+S8boKmIi8ihbn6WGZVL9Vs2AINCAABYNKqqhuvzOH3LWN2/PfvlVbOW3Etdci81YoM1HoO6s8DyQFDupfCiyI1D9Yh4AAAOjdRwBbsCclwtVLQUcCgECcumzP03eaKVyssVA0kK2Pgihs/j9MhcasCKgXgMSvSUSgZv47PMAxMNh+jI51axFt5J8b6ZFLLWWkUWM8+GFPmE6pdQMb9BauWXUKGjhHdoMoG/qoY38Pjnln7Yj2uHmKo1ure+iMIh1/DM1BuNjxqqyGDQSHwRo2kN7S3f0IxBqkvvR5WWlpJIEpjo5+fnh8HLqlq7tlKGnhMXf2wG0cph8E5/nLImJSUi/fpmalrUoJ1+CAoDAEBhsDxaVeolH4NpW8xX/s2uyEs6vyT5/BKb4xEoLL7/pjvZDw4UBl2yOREpo6YHAEAwOAG7JvPOLhVrV7yyFoKgqpPDEk/PVR02cfCulzhlEj07PvWyDzUtcvDuANGyKCgMjkurTP9no/GcAwrGQ5hluUl/LEw46T3sSAhWXkVzzDzK5cjyKD/NMfPrwi6P9sOr6jTtVODSq6LWDWzphx12+CNBq9HaxuyqIh6dLKtt1vBBAskQQWPoufHNVkLQMhWrpDMVsisLioKv6076FUds019cbcSMqL+WSuoKkaKnTx67Waj8oOUppE2/Eutgovx8lbWmIj48q3qzb2pUDsVvpXXDlmfNg+QtLoYXvC3zyKwltxOX3PkeuXk4HoO6u3jggcDMi58KorYM11OWAQDgMAiTw9/5IsPVSk1TEYdCkE9Z1XOvx0/qrxaweihJERdXSPN5mByZTQlYM/S/lgdVyeBu8E09MNnEWlcxp4q58N8Er2vxoRttVWSx8+20Ix8mP4srW2BXv2fes/gyHSLeocmQfFUNd8DhFjsUQzbYmjZuNIoobHINt59G45ZElYBFI/FF9GYrMVWXFaukoWZvsyTKYgAASSV0AEg/rKEV8ni0m4WK7+NH69at68DTxfj5+RFk5Rxcp7RSJiX+6+qZ42wdxl5+9kFdU/trRMiR31bFRYddevoejcEAADBYHKWqcu+vi5Zv3r3vrxvF+Tlbl3pvW+b9OCwJh5c5e9v//MFt9y7/8SQiRUvXAACAw+GZNYzTuzc5TJiirqmNoFBfwj5smO8+ZuLUq89D1UlayfFf961dHBv16Z8XoaJlUXB4PLmy4tDmFRv2nbQaYlOYm7Vl8Yy1syfe+xBPVFGdOm9pbNSnN88eTpu/rC7st/6PSDp6NqPHiv041VWVkwa3OHfi3vtYA1Pzho+UFhVQyFWGZhYNH9Q1NMFgsCnxX5vWIJpCioBGGZ4iUQUAkJ4U37QvqqQg7/H1iwt8tqiRtDpWg5gJM+ZsXzZLrO1q1EfCYrHCIyLHmP7gdt/9r3KJBMxl734magQ5HHpcP+Xt4/RjC+nPv9d/4qex+KtGaY81U5bFoSw0ZBfZkkppnOTS5rsWEQSpYnBdLZR/H6u3wJaEIODw6zwlAuaP6abGqjJyOLS9oeKO8foppTV+CbWnQKMQNk+wZpS2vaEiAYuyIMnummBAruE9ii0DAEyxUlGWxdz7WlZ3iowKZnJpzSxr9aZTwFRkMYX77Vv6J5aOAADKGRzRsxo+iEKAMgFTzuCCJtpbviEHYyU0gnz48KH1Ym0U/O69osVIBNPawrtZ9/dj5IgWay4TNE3QeDmVweMMZ26nZcdWRD+vK8Nj0nTdVikPGovGy8rqWGg5L+JUlzIKkputEEEQLq1K1drVYPrvmmMWAATJeXQYI6fUb9kfBE1jNF5OycLe0HMHoyClPNqv9ikotIDL1p24RsnCHoUjyOlaGHnt4tHJZWGPAACqNlMw8sqloffqTsEszmDkJ5NGz2o6+RQrr9J0lkbdv6aZBJdaDgDAKjTetRJBYeSUOZTmP4a2rr0V5j//A4WV0Zmwoo31E60cEBRaUleItIhaHmezH2yTti8gk0jAXpljZaImK4dDj7dQ3eFq/K2A9jyh/jdJZfFWO+i5mKvI4tAWJLmFw7VLqZy63lMxCEAqGVxXS7XfxxkutNNGEHD4VZYSAfOHp4WxGkEOhx5pRNw5wTi5lPEsvrYxEbU8Pg56I42IBCzKkiS3282EXMN9+LUUADClv5qyLPb+l+K6U2SU1ySXMGYP1Wyu5cEWHXZq6V/TPKCcLmpJGr1+UQggErCiQ+1FJGAMVQmf86hcfn1yEp1LAQBU/KhpaosxZsrhEZFstgTmC75//37oSCcstrURvT/2/65IVD588Y6+ST+CnPyocZNWbzuYFBsT/OJJXRk6jTJ31Ub7sW4EWTlj8/4zFq6oKC3OSP7efI0IUl1V4ejqvuK3vdMXLEcQ5O8jOxWUiLvPXtU3NiPIyQ+1d1yz/VBmyvc3/o9Ez0Ch0Bw2a/7qTUPtHWUIsiYWA3x2HqGQqwIf3wYAjJ08XUlZ5cWDm3VnyM1IzUhOmOK9sOnkU6KKatNpHHX/xNIRAAC5ogwAQFRRa/ggCoVSJCpXVZSBJhSJyrqGJvExEVxu/cUTFx0OACBXNtM03fjzGE5GZvbydR2uQYzt6LEotHjb1ei3kJyczOXxBmjJtVILjc3/nEcdZaTUsKPP2YwIAPhW2ChPdzCuz2w05HEAgBJaiy8bnkDoMaD2V0lh8uKK6PaGivgGp3A0VgIAhOU0moAyxrS+w2OkkSIAIKm0BgCAw6A8B6vHFtJTympzoGcJFQgCZllLYO1tFlcAAMChm7z5oREmV9D58g0RsCgTkkJCQkLHw23gW2ycrF5r+27zmTRq+meixSgUpv6VrzzQGQBAy/rWsGTD3gickgYAgEMuaalaoYBXN0mTx6DQc+KULOwbrhJL7O8IAKAkhzV8lvKAMXVfK1mMBACIBm5QGBxppCctO7amMEV0tDzqGUAQ0uhZrfxobSTgsAAACFq84UNhsAJOO2b2daxCdmVhadhD7XFLMHJtXQQIhSMoaptI6gqRltqWR7u1tVVobP7nXMooY2LjlkcFAPA1v1E3uINJfbMgmpVSSm3xTZEnEE4dWLvGAYXJiyukjTQiNmx5RH0b4VmNRnvHNEieRhoTAQDJJXQAAA6D8rImfSugpZTW5kDP4ssQBMxqcvdKB4haEiymIy1JS/a4GRdT2GsfJedUMaks3oOvJTejigAADXOUDhuoLc/l8VJSUjpfVVxcvFn/wa0UYNCpCTERQ0c6NRxBGDFmAgAg8VujLnDbBr0RqhqaAICK0mLQAj6PVzeLk0apTon/OtTeseEqsaIZFV/DG40XD3caX/f1MHsnAEBGcgIAAIvDT/SclxQbk5WaKDr6xu8hgiCTvRe28qO1EZvFBABgcOJNDRaHYzGbb7t+3XW0rLjwwPolhblZdBrl5aNbT29dBgDwuOL5aGlhfsCj216/rFZQInashqZkCLKGJv3E2q5GH9yLi4sBANpKreWhpTSOQAiexJU/iRNPgooo9S97NAppOG1C9PlANEzbLAQBGv9tmlNM44D/mpI6aqKchlqf02DQjU5BJGAAABX02l/EfBvSlYji+1/L9rkZAgD8v1c6GCvpEiWwVjoBiwYAcPjiTQCHJyRgm7l3qb3lxWjJY0R/l84rLSnWdWptnJ5TXQqEgrKIJ2URT8QOsauK6r5GUOiGsyJEPROiCSLNQxBR1gIA4FQXAwBwSo2GGHCKagAATnV9ToOgMQ1PgZEnAgC41ArRt5pO8wtfXykNvW80ex8AoDzan2jlgFeVwN1hKBwBACDki6fOAh5HdKhLKywLfywU8EmO7Zu7hyFqSeoKkZb/Wp7WXp6lVLZACJ7Elj6JLRU71KTlqe9FELU8vNZbnv+ammIqGwAgNqlftKVOcYOWB4tudApRy1Ne1/LYal0OK7j/pWTfJBMAgF98uYOJsi5RAiudi5oLLq9pSyJoS0vSLDcrtduLBh59ne107rMcDu1oqnxlTn+X8zES2dRQSxEPACguLh48uLVkoi2KiotI2q29wCtKigUCQZDvvSDfe2KHyorqbx1CodENp1mIeib4Ld+thiCImkZtNlleUggAUNXQalhAWU0DAFBeUt88YjDYhqdQJCoDAKrKa3spps5dev/K+RcPbq7bcwIA8Pb5Y9vRYzV19Vv50doIT5AFAPA44k0Nh8OWaWFRf0dX99P/Prt4fM9cZ2uCnJytw9hDF+8snGAnKy9+J2bgkzt8Ps9j7pIO19AsdU0dsbarUUbCYDAAALLYH1+Lc4dpnPSQ5EaLKARBN+7WFFso5b8hq0ZPaVSFUPRg7XemaoQRBoq+8RW7JhiklNZkVjA3j5HM/cwkBSwAoLKmUQ7IEwirmbzhzd0m0N7yYmQxgE5vfpC4vVjMGjT+x0PCrS+D0QEIgkJQYhdVM3/chn9eRGz8pfZ47YMELVOlfiPKInwNvXcxClKYJZn6UzdLJFTR7A0urdGMY6GAx6NX4/sN7+oKK2JeKBgOFs2/ac85ZCV1hUhLO1oeG61T0yW5WkkzLU/jAk1bHrHJlUKxlkdddoSh0pPY0l1uxikljMyKmi0uBhIJlaSABwBUMpppSUYodvyz1th+KmP71b+Dinp3DJQlkELJ4dAAABqN9sOSP8SsqZGRba3zXqThOhkSgaBQKHTjy1JsBS/R5dHgkkAaj78IgRD8l/oAAAxMzYcMH/3K957PjiOZKYl5mWnLNu2SSKiizKm68XAJn8ejVpOHDG/xg6i9s6u9c/3MQlHnjY6+kVixdy+fWg4eJppe07EamiUjJyfWdjXKSGpfe60utqOliEMhoKArlxLRUcQjCCilNXrhldG5oPGnKA5PQGPxFWRqL5cqJg8AoNZgd+L5NqRfn6SHZFLCsilEAmaiZeOx/P+0d2YrSQGnIY9NK2vUD5ZRzuQJhEN0mul2bm95MQginpx1mFAobP2vi1PRAgiKVVkgkdO1cAodgCAccqOPuRxKGQAAr1L/shHwODwmDfPfoilcehX4rytFRHPM/NTLv1YnhlQnh2HkiKrDJjZ7uvbObMURSTgljZrCtIYP1hRlCAU8eaMhbfwZO1YhqzyXkZ+kO3ltu8+B/GAH756vTS2PEh6FgILqLlxKRFsJjyCglNroU2YZjQMA0CY2anmoLJ6iTG3jKboTp+HuxAvstH0eJodkkMOyqokEzES9upp5AAAgAElEQVSrRkP7ddo7s5WkiNNQwKWWNZqNl15ewxMIh+hIbHmhmDwqAMBOEjsKif6gErk4hUKh2AxKMRpaOigUqqQgr/PnavEU2roIgpSXFjV8sKKsBACgoVX/cZfLYdNpFHmF2l+g6E4cFbX6CQPT5i/bt3ZxdGjwl7APikRlJ7fmlx1q78xWNZKWqjopK63RfL6cjBQ+j2c52KaNP2NCTCQAYJBdo72Ui/KyM5LiF/76W4draAnSpO0Sv9fmh+Rw6OEGiuE51DI6t26cJSqXuvV51h8zTAe3OhJcB1V7pTZ/VEEGPUxXITyHwuIKZP7rjfyQUQ0aTxwBAIRkVU+2UhV9LVrjxN6g/oU02UpldyDGN748PJs6Y5Aarsn4q4hoZmtbwq4zbZDazejSSgZXVa72N+D3vQKDQqYOVJVIeWlB4+WU+g2npIRzKGV14yzUtKiMm1v7Lf9D3rBNXa//dW80/9fFEBQUTYZVp4YLOCwUrvZzWPX3D6DxxBEAQHViiJrNZNHXojVOFC3q/0yqNpMxd3eXRfhSUsI17Gc0nPjSkGhma1vCrqM+Ylrxu5tcWiVWofavUxHth6Aw6nZT21VPeyukpn8GAMjr99kdfTtJDocebkiMyK4uo3HqBlaicii/P0v708ticNvekkUdqy29QyrKYIbpKYZnVzdqedLJ4L8JK3VCMshTBtTOPhGtcTKiwf5fk/ur7ZLFPoktDc+unjGE1HLLgy067NSWsOtMH6RxI6qoYUviH1+GQSFTB3Vwhtzel5lvUis/rrfFohEAgEAIbn8uNlOXtdXvZduZEeTkB9uN+hoRUlleqqpeOygcFx12fOuve/74x2LQ0LZUIurJaCmFkldQGjBs+LeIEDaLiZep/Zga9fENAGD4mPENS34Oeec8ebroa9EUkyH29RPvnCdNO7tHJcj33teIENfpcxpOfGlINLO1LWHXmTBt1pN/L1dXVhBVa5PgYP/HaAxmvIdXs+X/2P9b2NvAu++/YTBYAIBAIPC784+hqcUgm0ZviPGfIwAAZlbNtP9trKHtOjL6uHO8ARpBFt1JzqhgsnmCiBzqet8MHBplodHWm8Q0FXEAgG8FNDZP0OwQ764JBnQ2f+OzjDwym8Hhh2ZRTgTn2eorTLKqbxdksKizHwpCMilMriC5tObwm1wNeaz7gPr3eBwG5TVE3S+hopTGmTNUAnNa66xz0FWRxax6lJ5TxWLzBH4JFRfDi9c76er814UTmkXR2RtxICi3jeV7DkOvnQgKnfTHImZxhoDLpqREpF1dj2BxsjoWP34yAAAAnLImAICW+U3AZQsFzQzQGnrt4rPoadc2siry+GxGdVJoru8JRTNbVZtJdWVQOJn852erE0MEHCYjPznn0WGckoa6rXt9AQyONMqrPMqPU11KcpjTuR+6Eb3J67DyKin/W8UqyxFw2eVRfoWvLuq5r8er6ogKVCeFflqik/3ggKQqFGGWZAIAZNQlMKLcV+10NUIhyMJb3zPKa9g8QXh29brHKTgMyoL04/58EU1FPADgWz61pZZnt5sxnc3b8CQlj8xicPihmeTjb7NtDZQm9a/v55DBos6+zw3JIDO5guQSxqFXWRoKOI+B9S0MDoPytib5xZeVUjlzJTGntc66MfoqcthV95NyKplsnsAvvux/nwrWOxvo/NeFE5pJ1t758UBgZhsrdO6nnFfF3PE8nVzDLaNxfnuWmlLKODW9X2/cUnfNjsMoNPq3RdNzM1I5bNbXiJAD65di8Thjc6s21qCuqQ0ASPr2mcNmNTu5xGfHkRo6/fCmFUX5OUwG/XPou8sn9g2ytXeeOK2uDF6GcP2Po9GhwSxmTUZywoUjO1XVSS5T6helxOLwkzznv/V/VFFa7D77Bwuut8vCtVuJKqq71swvyMnksFlv/R/duXRu8bptJJ3ageDPoe9G6hHOH9wm+nbEmAlFedmndm6gkKsqy0uPb/XJTE3aduKC2LhkXmYaAEDHoJmBmDbW0Hbt7iMBAFjryvstG3D2Q8HUq9/pbL66PNZjgNo6Rx18Cx8FmvIcrB6QVLXuaYZCADpo1aCmBWz1FXyX9D/1rmDCxTgmV6CjhPcaorHBSRfTYMQXi0bOTjc9EJQbV0gXCIU2egoHJxmJzfCaP4x0Obx4oJaclWZb26y2UJbF+C0bcOxtnvuVBBqbb6JKOOBmuMC2xQUh2lteihSMrQft8Mv3Pxt3ZCqfSccpqavZeehNWdfw1pjWaYz0rPgSkHZ1HZqgYL03qGkBRTPbQVt9c5+dit07gc9h4lV1NEZ56blvEK13IoJCY82WnM1+cICeHScUChRNbYznHRSbCqrpNL8w6LK8wUA5vba2OG2BkVcetMMv58mxuEPuPBaNQDIxnntAc8yClsqL1l+p//bhweyHBwEA6iNmmK843/YKeTUUAABaBm421KKheor+K63PvMv1uPSNzuarK+CmDlRfN8agHS2PNellYvm6xynyeMxrn2FNC9gaKPkuH3IqOGfCX1+YXL6OkoyXNWmjs0HDlgeHRp2baXEgMDO2gCYQCm30lQ65m4q3PHZal8IKBmrLW2lJcnNmZVms/wrro6+zplz8RmPzTNRkD0w2aWVZOdH6K3XfHnyVdfBVFgBgxmCNv7wtAQBjzFT+mdf//Md8u5NRKATYGCj5rRjSsMPphzX0HP2tbS89fX/t3JGV050ZdJqqOsnF3XPR2q0Nb41pndvMee8Dnh1Yv1ROQeFGYGTTAoNs7S88fnPl9P/ZO++4pq4vgJ+XHTJIIGHvLTLFgVr3xIGCitvWvXfrKOJerXX7q6tWrRv3Bq2KqCCgCMjeGxmBTCD790doCJElxEGb74c/yL3n3Xdexnnn3XvuOdt+GOZdW1NtaGruM2HazOXrFflOFGCxuMC9Jw5vX5cS/1Yuk7l29V65dS+B2OBxfczU2ZdOHnJ09bBzbuT212Z06XrHbz479svGeWP6CXg8cxv7FZv3+E2f25R8j35Ddp28/NeRPf49HVEIyrWr9/GbTz+eT+Jy2ADQaLBqK0doPQ1WcYKDgydOnPipSxhfhannUmLyeemB3ZsXSy2rHvS/+N/G2Gp2juRLMj84neg8MDg4uP1DIQjitPAYQ2Wm4dskad9UbkZMz6PpzYtVF6XGBg2yn/mbZudIOhypR+cPsCJq5BvytVBYnk9dwvgqTDnzPiaPk7Hpu+bFUksFAw+92evnOLmrJudIOhwmgc+vXLkSEBDQznEQBNn2+/lBoz9j+QuNsHKab8KbyCepLWTjyE5Lmja46/o9R0dP+uGL6PWNsmHhVH0iWtV2deCCzvIml4PrOfqq2ICM9XdrPLJMyzdMyx9u4cOjOF0DpreGK55r0dI8rQnUPPqiwICC8/foqA9CWtpOKyJ5Lxzbr880HOY36Quo07Foy6rNt49UJhdJ5efflF6LKz8e4ND6SV0t3z5ymVQuEZWEnS+LuOa08Hjrl5O0aPncKCzPuejiq+9Kj0921loeLarIpFKRSHjr/KmH1y5sP3qh9ctJ/x3+nR7JnUTWshsZhhTcIX+7UZ2/rf0sWtpJRfSdtJPL8DRDh7mHGN2aq3OhRcsX5s778qVXUxTVdEf/sxlHixYFf9+9tnX5LEWx3IGjtJO7jdBRPZIL05sLqvJzY/hpV2o6LJ1XXWiml+ntx/T2+2LKaNGiysUfmkxvAwB+7gZ+7tqVmv8u+8/faaZ36NiJQ8dqoNjFvxjtpKIWLVq0aNGi5evzb/NIpp5Lsd8R9bW10PKFSNo3NXKh/dfWQosWmHLmvd2Wl19bCy0dhpXTfAc5aify1emoqzYdgvclgl+fFMQUcGvEMjNd/AhnveV9zTRSwkrLN4VMLIyYb9Nol1qRILlEnHHmx7KIa9YBQabDF3wpBbX85xBL5atvpl17Vxo03GZhH/VKSTmsml2PciKy2TyhxJxOmNjFaHFfC9XyPlkV1bsf5b7MrhJKZOY0wmhX5sI+5oo6NVr+ZVw4tv9/O37+uP1FDk+ZZyUl/u1fR35NehfDqWQZmJj19xkzc/n6VpbT+yS0HsnnIr6Y7/tH4ohOeo8WuOvpYF7ncVfczIzM5d6Z44rqgPkQtTQDCov/OFc9611oyuFZjO71RSskAk7K/2bLJS3X6daipT1waiSzLyR9XG9cQRlP5Hv8XWdj8v2FXYypuGcZlUuCU4s5wl2+ddON6WXVI47GupqQb871MKMRnqZXrrieGl/EOzejuRgaLR0UPpcNAI+SPpCpjZcOiIt6uXzKqH7DRh+/9YxKo79+9njH6nlx0a+O33yGQml4meXftmrz7bD773wMCtk31s6Cjifj0YMd6PN7mbwr5Efnc7+2alo+O1KhIPvCBkZ3X5pzXT0LiYCTsHOMroO39cRNX1c3Lf9uODUS3+PvvK11N41ovDz7gWd5ApH06MROlnoEHAY1rBNjxQDLv6KLM8vravjtCM2WyOSnpnZ2MiSR8WhfV+b33U2epFW+zuV8wevQ8oXgcTgAQGy6tPKxXzbS9RlBB08Zm1mSyNRBo8f5z5iXFBud9v6dxpVp7xwJu0Zy4Hnho9SqDzwRGY92NyGtHmCuWtL2VQ7nUHhRXBFfIpOb6eLHuTMX9DJWlp6afj4li1V7apJj0IOc+GI+BoUa4kjfOdL6aQb78IuibFaNARk7x9t4trexQt7/z6QCdu3pyU6bQ3Lji/lyOXQxo2webtlUkvikD4K9zwqj8rgCkdSYivPppL+yn5myXHCLyreHYo6IScKq5pa2ohMAIL9S6K2Z4uRfAYmAnX/nQGXcIxH7A5pAJlu5W4xdTVGpYctOeVV4/xAvO04uk+D1zQx6jjMdvkBZBi9p//Sa0qxOi09lXwri58QjaIye+xDb6TurEp4W3D9cU5qNoxqYDJ1jMni2Qj5ht7+woqDTstM5lzbzc+PlcjnVtov1pM1NpY0X5Cfl397LSY+SCgV4mrG+l4+570plAeEWldcg+Tf3SKq5NpM2K1vE3HKToXOM+k3jZcV+jjP+12DXSPY/zXuUWvGBKyLj0e6mlNWDrDzN6qeRX2azD4XlxxVyJTK5GY0w3sNwwXdmSssz7ez77IqaU1M7B93LjCviYVDIECf9Xb72T9MrDz3Pz66oNiDj5vY2m92zrvaQ38m4gqraM9NcNj3Iii/iyeVyL3Pq5hG2TSWJTyrh//YkLyqXLRBJjan4EZ0ZKwZYKssFt6h8eyjni+b2NpvWzfhtQeMPP7ffl/eyptF16suk+zgzdoRm30ssXzHAEgD62dG/s6XpqQi4mVIAIK+yxlsTNYG/Clx21emDO188ul9RWqJDJndy85q9aoOzR31R3Levws4e+TU57o1UIjEysxjuP2XK/OXKMnirZ4zNz87YdfLygU0/psS/RWMwvQeP+GnHwYhnoX8d2VOQnaHPNJw4Z8mEWYsV8gvHDf5QmPfLqWsHt/yUmhArl8s7d+m+fOMvTaWNz0hK+GPf9vjolzUCAdPIpJ/PmJkr1isLCLeofHvgc9l4AlE1Eb4aA0b46zENsNj6aqbWjs4AUFKQ18m9kVIM7aG9HsnCq+np5TUnAhxcjEmlPPG20NyAM8khC9xs9AkAEJ3Pm/JXio+zXvhSDwoeE5JauexGBksg3uJjpTgci0ZVVovX38veNMzKwYD4V0zp9kd5xRwhHoM6NcmRRkRveJC78WFuFzOKpxkZAHBohCWQrLyVtdXHysOUnFdZO+NCasDZ5PClnno66tcSX8z3/zOpj43unTkuRlRcZC539a2sqDzu7TkuiioVzSuvSmW1xPWXmKbehOdLPewYRLVGJ0Odx2lVvFqp0gHKqawFAAcDdckOROqxhdXF6Z0WnSBZuIg4pTlXtiX+GuCxKYRoZAMA3IzopL1T9L18vHaGo4mUynchaSeXiXksm8lbFIejMFgJrzLr/HrriZt0TB1Knv2VG7xdWFmMwuI7LT2F0aFlX9iQfXEjxaYLxcYTAFAYnJjHyji10mbyVoqNR01ZXvLBGe/3BHjtDMeS9dR04+fGJ+z2pzn3cQ+8g6MbcVIjM06v5qZHuQXeVlTMaV55VcT8yqhlTU5Qe+14TjS2a+ZdErIKi5+cNhuxBEerL11ENLZr/igtn8SCy8npZdUnJzu7mJBLeaKtD7MCTsWHLvayYRABIDqPM+V0wojOjBcrulMI6JAU1tKrKRUC0daRdR+BwvKsu5OxycfG0ZB0Nqp4e0i2wvL8ObUzjYgJvJsZdC/T04zSxZwKADg0iiUQr7iRtnWkracZNbeyZsZf7yf8mfBiZTfVO7eC+CKe38m4Prb0uws8jaj4iGz26htpUbmc2/M9FZaneeVVqawWu+yIaOpNCF/RzY6pXt/UjqnzcaOSYo6wqlrs0LAqqpU+EYtGEor5ipezepqqHVXCFQKApV4Htl0bF03PyUjZceyig4t7RdmHI9vWLZ3kc/pBhIWNPQDEx0SsmDa6v8+Yy2HxJAo1PPTu1uWzqljlKzbXBYFhsDhOJeu3wOVLg36xceh049zJ/+34uay4EIcn7P7jClWXvjdo5f5NPzp7du/s2Q0AcHh8Fati++p5KzbvcfboWpSX/eMP/ksn+VwKS6DpqafISk2IXThucLc+A0/cCmMamcRGhu/8aUF89KvjN58pHIXmlVeFXcka4W7W1Jtw6VmcpZ2jWiOPy9EhN/ccPnHOErWWzOQEBEGsHTVf2KhdqzZCiexlNmegPc3LnILHoCzo+H1+djgMEpbJVgiEplbiMaigoZaGFJwODuXvxvC2pF6JK1MdhFcrXdrH1NOMTMKh5/Y0JuHQMQW8/WNtLeh4KgGz6DsTAHiZUzdbiEYhQolsUW+TnlZUIhblZKizYahlVbXkasMxFWwJyaMRMScCHGwZRBIOPdiBvn6wRVwR/24iqzXKq6Kngyna0rOpv4/dEQBY2c8Mj0Etu5FRwhWJpfKwTPaJyGJfF31NzcF8eWRiITv5pZ7rQIqtFwqLJzAsHGbtQ7C4qsQwhQDrXSgKi7cOCMLRDNF4Haa3v66jd9nLK6qDSGp4ZiOXUmw80XiS6dC5aDyJmxljP3s/gWGB0aGajVgEAJyUuj0LCAotEwvNfBbpOvVE4YgkMyfrCRsk/KqyV1c/Vi/78hYMiea06ATRyBaNJ+m5D7Yat56XE1cRfbc1yquCJet992dRU38tOhYFdw+isATTofM+9R3W0kqEEtnLrKqBDnpeFlQ8BmVBJ+wf54TDoMIyKhUCoSksPAYVNNzWkIrTwaH93Q16WtGCY0tVB+HWSpb2M+9iTiXh0PN6m5Fw6Df5nP3jHC3oBCoBs7ivOQC8yq6zBgrLs7iPeS9rGhGL6mRIChpuW1UtVhtTweYHWTQi9uRkZ1uGDgmHHuKk//Mwm3eFvLvvy1ujvCp6OtjiHf2a+mvG82iKcr5IMaxqIwoBGhGr6Gr0kJMRhU6GpG4W1E893TeCSFj75tWzngOGuXj1wOEJJuZWgftO4HC4qOePFQIvQu/i8IQlgbsYhsZEHdIwv0me3n0eBJ9THYTP48xY/FNnz25EEnnSnKVEEvn9m9cb9p0wMbciU3WnL1oNAG9fhSmEUSi0SFg7beGqLj37Eog6tk4uiwN3cqoqH147/7F6B7esodLoO45dsLB1IJLIvQePWLhuW3Lcmyf3rrdGeVVoevoRBTVN/X3sjgAAn8vGYLB/7N02dWCX/nb00V7Wezes5LKrGn0nKyvKLh4/cPX00ZnL11vba94jadccCRaNYpCwISmVA+3pQxzoGDRCwaMT13ZTCgQNtQwa2mCJwoJOiMzlcmokusT6U3f/54uOQSE0IgaHQQwodRNETBIWAMr5DYIB+9vRlP/3sqYCQHJptZpuPKE0Jp/r58bEqSRyHmBPA4B3RXw/N0aLyrcTJ0OdU5McFlzN6Lr3raLFp5Per76Nr+x2CFAYLI7KYMWG0N0G6rkPQdAYNJHifShRKWAdEGQdEKR6CIFhwUmNlAg4GFL9ZC/Vvq4+IoLCYMg0FAaH061LKoWlMgFAxGlQp4ru0l/5v65TLwAQFCSr6Sat4XEzYgy8/ZQrRABAdx0AALzsd0xvvxaV1xRCVlHpq2Azn0Wql6xFs2DRKAYZF5JcMchRb7CjPhaNUPDopMBeSoGg4TZBwxtMfZnrESJy2OqWx7LuM8KgEJoOBodGGSotDxkHAGW8Bjfp/vZ05f+9bGgAkPKBr6YbTyiNyeP4uRs2tDx6ABBbwPVzN2hR+c9KrVgGANiP0ttj0UiNuJFIWHaNZOb5JF6t9Nx0V3SHjcnHYHF0fWZ46J2eA4f3HuyDwWBJZOrDhPpo9CUbdi3ZsEv1EGNzq9jIcB6HTdGtv924da/7mNAYDJVGx+Hw+gZ1lRT1GIYAwCpv4KH26DdE+b9Xz34AkJnyXk03AZ/7/k3kkLETlStEAODdfygAJL2LGTp2YovKtxOZTCYWCQk6pENXHuIJhJjwp79tWB75LPSv0CjV3TSFuVkBfVwAgEgiL1q/feJs9YkTjdAujwSFwJmpTkuuZcy5nEbEorzMKQPsaJO6GND++c0LJbKz0aX3k1n5VbVVNRKZHKQyOQBIVUoRoVGIcl0DABAEaComA0EQgLqj6jRGI3SVBRqFcAVfff9CKU8kk8P1+PLr8eplGIs5wtYo306uxZevvp01v6fJjG6GhhRcYolgzd3sEccTbs120SepT/N2DBCU8/IzaSeWpByZg8IRqXZedJcBhn0mYUh1v1iZWFjy9Czr7f3a8nyxoApkMrlMCgByuVRlDLQysEPRoDwcAABBAEBxVF0DGoMh198GMGQaAIi5FWqqidilIJeVRV4vi7yu1iWsLG6N8pqiLOKaXCY17DtFs8NqUQWFwNnpLouDU2ZfSCJiUV4WugPs6ZO7GqtanjNRxfcTy/OraquqxSqWp96SoFGIMrADABBAVEMrEAQAQKYij0U3EFCcq/xjy8MVyuRwPa70epz69InS8jSv/GdFEdkmlqg7HyKJTDXoTUFuZc20s+8r+OK/Zri4mHTUyV0AQKFQe87c2Lz0h/VzJxKIOi5ePbz7Dx018Xsqrc62iIS11/86EfbgZnFeDpddJZVJZVIpAEil9bYIhUYrAzsAAEEQ5eGK1wAgU5HHYLC69PrFZYVwZbn6dH7FhxKZTBZ641LojUtqXWXFBa1Rvp2cvP1c9eWAkX4ICvXzvEnnf987b81mZbuZlW1EQQ2Pw46NDN8XtPLv28EHLz1Qddc0Qnt/A+4m5PClnjEFvLBM9vNM9rZHeYdfFF353tnFmAQAC4LTH6dXrepvPs6NwSTjcBhk7d3sy7GNrLC0HhTS0E+XKxobF57iZbCn6WmJ5pVvDxKZPPB+TncL6s9DLBQtnmbkA362Q48mHH1VvGFoRw1tJVu5e+0I52bGVCWGVSU+zwneVnD/sMtPV8gWLgCQenRBZfxjC99VBj3HYXWZKCwu8+za0heX23NGBGloJRU3CKTx1Ua15B+fpLymqHhzj2LlTmCoZ4DQolncTSkvVnSPyeeEZVSFZVRuC8k+/Dw/eJa74sY5/3Ly41TWqoFW4zwMDMg4HAa15lb65bcf2nNGpKHlkTdveboa/+bn0DblPyuGFDwAsAQNHCmJTM6ukXhTGxStfJPP/eFcIgmPvjXPw8mwvSbxq+Pk1uVSWHzCm8iosMdRzx8f2b7+ryO/Hrr00MHFHQCCFk5/+ff9WSsDh/tP1mMa4nD4X9YtuXflbHvOiDTcGasoVt/UdlnfyTPX/fp725TXON79hyAIkhTXSOgkRZfWb7ivoan5rBG9zv1vz6Kfd2j21BrwyhEEultQultQ1gw0f1vA8/8zaV9Y4Z+THUt5okdpVWNcGav61wfaFLKF7TydSCJTDRetrJEAAIOsPutgTMWhkJZP15TyamKfGtlaxBbyhVJ7ZoNGW30iAGSU1zSv0rcOglDtu1Ptu1v6reFlvU3Y5V9we1+npX+K2KWVcY+YPcZYjFmllBWyCtt5NplEJKnhKadVxPxKAMBR1XMd4vSMAUHVtni6JpRXk2pzZGtteZ6gINls5NIW1NCiCRAEulvqdrfUXTPY6m0+1+9k3N6neaendS7lih6lsMa4GaweWO/6a8TycGslymmVqmox/LO4o4qxLh6FQCG7tm3Kq4m1IbK1eQypOAMKLq2swTJ3Rnm1RCb3MK2fvHxbwJ18OsHeQOevGa6MDjqn+xEIgrh36+Xerde8nzYlvo1aOH7wqf07fjkVXFFa8uLxvcG+E2avDFQKfyjKb+fpxCIhn8dRTqtwqioBQI+hXvbIwNgUhUJ9KGzhdE0pryb2qZGtYrEoOzVZh0w2t663aWKRSC6XK0oTlxYVnNq/w9O7j8/4qUoBa3snAMjJSG1e5zbQLo8kMpe75HrGualOys23XuYUAwpW8VsVSuQAoLoFJqO85nUuFwDkKnOhbSA8mz3SuS5cOSKHAwA9LdXX7Ek4dA9LakQut4wvNvjHX4nK4669m33Q387dhNy88mooIltbryGTjMNhUGkNo1tSy6oBwJyOb+Kgbx1OWmTaiSWdV5xTbr6l2HrhaAZifhUAyCRCAMCobIGpLsngpL4G+Odxsq2wk8IZXUfW6ZAaAQBUJ/XPAo0n6Tr04KRGiDhlyqgUbnpU5tm1DnMPkq3cm1deDUVkaxtU5WbEAADZQv2+okWzROawFwennp/hotx862VBNaDg6iyPVAYNgzczyqtf57Chvd9ECM+sGvVPRd+IHDYAeFs3ZnmsaJE57DKeSBkPF5XLWXMr/dAEJ3dTSvPKq6GIbG2X0h/h52ZwJqqYJRArl4/vJJRhUMgYt7ofTkFV7dQz722ZOsGz3P8dOabfvX6xeekPe8/eVG6+dfHqwTAw4laxAEAkEgIATa/+OSc3M/Xd6xcA7UGA+qkAACAASURBVP3GxIQ/HTCyrixobMRzAPDo2UdNhkgiu3fvHRsZziov1WfW7c6Lj371y9olGw+ecnLr0rzyaigiW1uvoVgoXOA/0Nmj6/+uPlI2RjwNAQCvXv0BgKbP+PvO1Yzk+GH+k5UTPGnv4wDA1LLxRNXtoV17bTxMyRgUsvxm1rtCvlAiY9dITkSUFHNEk7sYAoAZDW9JJzxMqUwtqxZKZE8zquZcThvVWR8A4ov5qqEhnwQBi9ofVhiexakRy1JKq3c8zjMgY0e7qO+nAoDAIZZoBPn+QkpmRY1QIovM5S6/kYlDo5wMdFpUvp3o4FALehm/zuPu/ju/mCOqEctiC3lr7mRTCZg5/+RW6XBQrD0QFCb9j+W87HcysVAiYBeFnhBWFhv2nQwABH0zAtOSFfuwuihVJhZWJTxNOTKH0W0UAPBz4lVDQz4JFI5QcHc/OylcJqoRFKTkXt2B0zVgdhv9saTVhEAEhU4++H1NSaZMLOSkRqb/sRzB4nRMnVpUXlPUfMgCAALTQoNjavkYDzMqBoUsu54WW8BV/HiPvyos5ggndzUCADMawVKP8DC5IrVUIJTInqRVzr6QpPAk4gp57bI8z/LCM6tqxLKUD4LtIdkGFJyvayOVfgOHWaMQZMa5xMzyaqFEFpHDXnYtFYdBKdY+mlf+C7Csv4UeCbvgcnIuq0Yokd1OKDv6snD5AEtTWt3DUuDdTKFEdmKy87/DHQGATu5eaAxm68q5Se9iRMJaLrvq0slDpcWFoyb/AABGphYmFtbPQ25npyWJhLWRT0PWz500cKQ/AKTEv1ENDfkk8ATi6YO7ol88qa2pzkx5//vOQH2m4aBR4z6WXPTzDhQa/dP3fnmZaSJhbWxk+Nbls7F4nI2jc4vKtxMdMmXO6qB3r18c3PJTWUkRn8d5cvf6wc0/2jm7jZ02W3EVS4J2pb2P271mUUlhXm1NdVzUy11rFpKpugGzFrVfATXaNUdCxKJuznLZG1YwLzitnC+m4NF2DOKxCQ4K/wCFwB+THDY+zPU9mYhGIV3NyccCHHRwqMQSwcyLaYu+M1k7qC2GG4tG9vvZbQ3Niy/iy+TyruaUbSOsP47JAgBPM/LtOS77wwrH/JHIF0qZZKyvC2NZX1M8BtWi8u1n7SALG33i+Telp6M/1IplDDL2O2vd4wEOVnrqyU46Cigc0W39zfzbe1N/nyfilmMIFKKxndPCYwyFf4CgOi35I/vixvjtvggaTbHt6rTgGJqgw89PTD4002zEIkv/tW05KRprP2t/zpWt/Jx4uVxGtetqM3UbCtfIdmuKjafbz7cL7uyP3zlGWsPH6TIZ3X3NRy1DYfEtK68hJNUcAEATGkl1lXNla1Ho8fqXwdtygrcBANPb33HeYQ3q8F+AiEXdmufx25PceZeSy/kiCh5jx9Q5NsnZ15UJACgETk3pHHQ/a/Sxd2gU0tWCenySsw4OnVjCn3k+cXFf87VDrNtwUhwadWCc09aHWXGFPJlc3tVCd/tou0YtTxdz6p35nvue5vkef8cXSpkU3BhX5rL+lkrL04zy7Wfrw6xjL+uXL7eFZG8LyQYAf3eDIwGdAICug70zz3PXo+xRx97xhBJbhs7WkbYzupso5GvEsr/TWADg/Zt6ydLJXY32+jWyffTbh0DUOXr9yal92zcsmFJZXkaiUCxtHbf9fn7Q6HEAgEKhdp+8vH/Tj3PH9Eej0a5e3tt+P6dDIqcnxa+ZPWH6wtWqAZ6tB4vFBe49cXj7upT4t3KZzLWr98qtewnERlbZOnt2O37z2Z8Hds73GyDg8/SZhoNGj/9+6VrFuknzyrefqQtWmphbBZ868sPwHgIez9jc0nfKrBmLf1Kq6j99nh7DMPjUkRlDuovFIkMTM2fPbjOXrzexaMvvqHkQ1QWU4ODgiRMnftLyxBdm6rmUmHxeemD3r63Il2N+cDrReWBwsPp6YRtAEETj9+DPStK+qdyMmJ5H07+2It80qUfnD7AiauQb8rVQWB6NL09okCln3sfkcTI2ffe1FelgmAQ+v3LlSkBAQDvHQRBEg/fgL8DKab4JbyKfpKrv9NSiyoaFU/WJaFXb1fHq2sihfUvBWjoY2o9byzeB9ouo5dNoZ9TSf5KO55Fo0aJFixYtWv59aD0SLVq0aNGiRcvX50tkCdQgF6ZrPpG+lm+WzqsufG0VtGgBALj4Q5P5abRo+Zj95+98bRU6JNo5Ei1atGjRokXL1+frzJFMPZcSnc/NCOzxVc6uxtLrGTcS6uqkvF7ZxZz2GTOY9T0cl1VRAwB0HYwGq/p9+yTtm8rNiO55NONrKwIAkHZiafnrG4r/u/76+utmfH/7c19FFhMMmf45Kv9paZ4pZ95H53Eyv41NNEuCU27E1xXZiPqxhzn9a2YK6LM/JquiGgDoOtgvVgjwq7Nymm9CTMSTNPXKWV+FLctmht6sq8JxPTLV2OybLj8yqb97flY6AOjS9dpcCLCDrdp8JnAYVE5QvXv0vkTw65OCmAJujVhmposf4ay3vK9Z65MF5bBqd/2dH5nL4Qml5jR8gKfB4u9MFfUvwpd6AMCsS2nR+dzPcB1aWgsKg+t1Ike1RS4RZ5z5sSzimnVAkOnwBa0cRyYWRsxvPHGhapGdmtKcvOu7OKmRkloegWFu2DvAbMRiRXUer53hAJByeBYnI7rt16Pl3wIOg8rdUp/WM6GI9+vfuW/yubUSmS2DOLeX2SSvBonUWhRonrhC3uHn+bGF3EqB2FSXMKIzY8UAS4Wte7GyGwDMPJ8UncfR0MVp+WSwOPzzLLbyZX5W+rFfN719FSYSCo3NLAeO8p+6YCWRRG69QPOkxL/968ivSe9iOJUsAxOz/j5jZi5fr1oBGADEYtGunxaGXL+4ZMOuKfNXKNsvh8UDwNrZAQkxr9p8vVqPRJ34Yr7vH4kjOuk9WuCup4N5ncddcTMzMpd7Z45ra2pxl/HFY04ldjbSuTfP1ZiCe5bJXno9s5gj3DVK8wl3tWgKiYCT8r/ZckkjabybB4XFf5xvnvUuNOXwLEZ3X8VLEacsYecYkkVn96B7OLpx1ftn6SeWCiuLbafv+mg8LVrqeZhcMfdi0sjOzJBFXQwouHMxJT/eTKuqFi/sY95KgeZ5ncuZdDpheCf9O/M8aTrYZ+mVK6+nRuVybs/3bI2t0/KFyclImTOqj4OLx9HrfxuZWkQ8C92xal5KQuzeszdbKdA8cVEvl08Z1W/Y6OO3nlFp9NfPHu9YPS8u+tXxm8+U+eN5HPb6uRPFYtFnukZtHIk6u//Ox6CQfWPtLOh4Mh492IE+v5fJu0J+K2c1DjwvFIikv493sKQTcBjUMCe95f1Mz70pzazo4AX2/r1IBJyEnWN0HbytJ25q/2hSoSD7wgZGd1+ac92TbsHdA1KhwGn+7wSmJQqD0/ccZj56eUnYuZqSzPafTsu/mO0h2YZU/OEJTlb6RB0cen5vs4leRr89yWXXSFop0Dy7HuXok7CHJ3QypxMoeLSvK/MHb9O3BdyEIt7nvCwtbeToriCJRLLr5BUbx846ZMrg0eP9p8+NfBoSF/WylQLNc+yXjXR9RtDBU8ZmliQyddDocf4z5iXFRqe9f6cQ4HHY88cO8Ojx3bKgXz7TNbbFI/H/M8l2e5RA1CDb/y9P8k03RUbm1t22X+VwJp5NdtwZbbs9qt/huEPhRSKJrNHRxp5K9NjzRrXldNQH1aEAIOmDYNaltM67Y6y2vu55IHZraB6vto21BlqkmCNikrCqyaGt6AQAyK9sVe3QO4kVvayodJX6gj6d9OVyuJ/USFWkjkLCbv+IBbZSoUC1Me/GLy9nmXLSIhUv2SmvEn+bGLnIMWKB7dvAfgX3DskkjfvRCbvGRq3wUG0peXL65SxTTmqkskWQn5RyeNbrpZ1fzbN6s6ZnzpWtkprPZSXF3HKToXMsxv6okdHyb+6RVHNtJm1WtpRH39F17IUh05Ut+l18QC6veHNfI2f8L+N3Ms5m8ws1W7T7cY5J4PPInLq57pfZ7IA/Exy2vrTZ/KLvgZhDYflN2aIxJ+Lcd0Wqtpx+XWQS+Dwip37aPKmEP/N8kvP2V5Ybw71/i9r6MItb26rb/6fCqZHksGq6WVBxmHpb5OtiUCOW/Z3Kao1Ai4xyYQQNt8Gi6+dDHAx0AKCgpcLF3ywLxw0eYK9XI+CrNh7/dVMvc2Jd5TyAt6/Clk0eMbiTwQB7vckDPM4e/lUsaty2L/AfOMqzQejGtTNHe5kTYyPDlS0ZSQlrZwcMdzXpZ6M7vlenw9vW8Xmfa5GrW5+Bi9Zvp+nV1zlxdOsCAEX5Oa0UaJ4BI/wXB+7EYuvLWVs7OgNASUGe4mVleenEOUvmrA5q75U0TVtWbca7M6PyuI/Tqsa61hdLvP2eZUHHe1tSASA6nzflrxQfZ73wpR4UPCYktXLZjQyWQLzFx6oNp4sv5vv/mdTHRvfOHBcjKi4yl7v6VlZUHvf2HBfMR3OLldUS119imhrq+VIPO0YjJVFUcTLUeZxWxauVUgh1gSM5lbUA4GDQwoEAUMwRVVVL7BvWB7fSI2DQSEKxoKmjvn0Meo3npkdVxj1m9hirbCyPuk1gWOg6eAMANyM6ae8UfS8fr53haCKl8l1I2sllYh7LZvKWNpyOnxufsNuf5tzHPfAOjm7ESY3MOL2amx7lFngbQal/Y8X8yqhlTe7M9NrxnGhs11SvAqKxXYsyrUTIKix+ctpsxBIcra5eo7CyWMKv0jGxb3BGQysEjeHnJWjkpP9lJngaRuVyHqeyxrrVV7y7nVBmQSd4W9EAIDqPM+V0wojOjBcrulMI6JAU1tKrKRUC0daRbfnE44t4fifj+tjS7y7wNKLiI7LZq2+kKZY5GrNFYpcdEU0NFb6imx2zkRInShrN90nTwQBA8gc+gGGLAi1dDcztpV62PrlEgCDgaEBq8dhvE5/xU+OjX738+8GQMfV56x/fvmpibuXR4zsAiI+JWDFtdH+fMZfD4kkUanjo3a3LZ1Wxylds3tOG06UmxC4cN7hbn4EnboUxjUxiI8N3/rQgPvrV8ZvP0Bh1S8WuZI1wV3/DlVx6Fmdp10LNoAkz1SvblX8oBgDTf+rLtCjQPBPnLFFryUxOQBDE2rEu6YalnWOLSraTtngkozvrb3iQcyeRpfRIYgt5eVW1qweYIwgAQGhqJR6DChpqaUjBAYC/G+Pi29IrcWVt80i2hOTRiJgTAQ6KR4HBDvT1gy1W3866m8jyc2OoCevpYNpZl2dlP7PwLM6yGxk7R9kwSNhXOZwTkcW+Lvoepi0HB5ULRAodVBtRCNCJmHLBJ8cofDswuo3OvrChIvqO0iPhZcXWludZjFkNCAIArHehKCzeOiBIcSdmevt/CL9Y9vJK2zyS7MtbMCSa06ITKAwOAPTcB1uNW59xenVF9F2mt5+aMJas93Ekx9ei4O5BFJZgOnSeskXMLQcALEWvgRyCwpDoIo625kV7GeXCDLybeTuhXOmRvC3g5lXWrh5kVWeLUlh4DCpouK0hFQcA/u4GF2NKgmNL2+aRbH6QRSNiT052VtiiIU76Pw+zWXUj7e77cj939SLAejrY9lTqoRExVvrEmHyuWCpXTmMogkwrBOLWCHwS5XzRtXelf74uWjnAUjFT0hEZOMp/X9Cqv+9cU3okSbHRxfk5s1dtQBAEAF6E3sXhCUsCdzEMjQFgmN+ku5dOPwg+1zaP5OCWNVQafcexC1gcHgB6Dx6xcN22nT8ueHLv+tCxE9WEaXr6EQWaXLuvrCi78sdhG8fObl0bv+W1KND84CHXL149fXTm8vXW9l8uDVhbVm0oBPRQJ/qzTDZPWDdZejOhAkFgvHtd7cqgoZbpgd1Ndeu30VrQCbxaKad1q5uq8ITSmHxub2td1ZnJAfY0AHhXxG/6uLbjZKhzapLD20J+171vrba+nnouxduS+quvbWuOrRXLAACHVn9XsWikRtz4RHGHAEOk6HkMrXr/TPrP0kl51E1AEIPe4xUvrQOCeh5Nx+ubKg8hMCwkNTyJ4JMnMKU1PG5GDM2pt8IdUUB3HQAAvOx37bqMz4yQVVT6Kthk8CwMSVfZKBPVAgCCxqkJozBYmUgbWtReqATMsE76zzIq621RfBmCwATPuhmCoOE2GZu+M1XZ0m+uR+DWStpoi/I4vW1oDW2RHgDEFnyWrXMbh9uUcIRLr6bkVtZwayVXYj+cjSoGALFU3kqB1pDLqjEJfO6+K3Lf07yfh1qvGPBNbzFtHjJFt8/Qka/DHgn4dZ/Io1tXEATxGT9V8XLJhl1PUssNTesjf43Nrfg8Do/DbmS4ZhHwue/fRHbp1U/hjijw7j8UAJLeNTlPrym47Kq1s8YLeNyNB06h0I3sA21RoCkKc7N6mRNHeVqe2r9j0frtM5ev15zWLdPGvTYT3Jl3E1mhKZXjPZhSmfxuEsvbkmpBr/tghBLZ2ejS+8ms/KraqhqJTA5SmRwAPuVnUkcpTySTw/X48uvx6g+UxZxWBXZ8Ktfiy1ffzprf02RGN0NDCi6xRLDmbvaI4wm3Zrvok7DNH0vEogFAJFV3PkQSeaNVyzsQBr0nVMTcZb0LNeg1Xi6Tlkff1XX0JjAsFL0ysbDk6VnW2/u15fliQRXIZHKZFADk8k8O9xGxS0EuK4u8XhZ5Xa1LWFnc/gv5fJRFXJPLpIZ9p6g2onBEAJBL1UNqZBKRoktLOxnvaXjnfXlIcsUET0OpTH73fXlPK5rFP5k8hBLZmaji+4nl+VW1VdViFVv0ycaolCuUyeF6XOn1uFK1rs9ki4Y7M85/77rrUU6/AzEkHLqvHf3k5M6DDr9RZiJoUaA1WOkTi3f049RIInLYgXczb78vvzLTTZfYUbdh+oyb+uTu9fCQuz7jp8qk0id3r3l69zExt1L0ioS11/86EfbgZnFeDpddJZVJZVIpAEiln2ypKj6UyGSy0BuXQm9cUusqKy5o93U0R1Fe9uoZYyvLy/acueHg4t4GgWYws7KNKKjhcdixkeH7glb+fTv44KUHFF2ahnRvgTZ+7frZ0Rgk7J0k1ngP5qscbjlfHDik3rNeEJz+OL1qVX/zcW4MJhmHwyBr72Zfji1rs5ZTvAz2tG6Wop1IZPLA+zndLag/D6m713qakQ/42Q49mnD0VfGGoS08PRhSsADAqm4wZSqRydk1kh4U9afkjgXdpR+WyqiIvmPQazwn5ZWYW244IVDZm3p0QWX8YwvfVQY9x2F1mSgsLvPs2tIXl9t8OtVkHh2Fijf3KFbuavnWFMtYYl6DSEO5TCLhs/EO30SGwI5Of3s9Bgl79335BE/DV9nscr4ocFj9Tvv5l5Mfp7JWDbQa52FgQMbhMKg1t9Ivv/3Q5tNN6Wr8m5+DJhRvFQMd9AY61C/5pZYKAMBSJXNaiwKtRJeI8XFmmOrih/8eezg8f8OwjpqtoEe/IXQG88m96z7jp76JCKusKFv08w5lb9DC6S//vj9rZeBw/8l6TEMcDv/LuiX3rpxt8+l8J89c9+vvmlC8tbx/83rt7PFEHfKxm09sHDu3QaA1UHRp/Yb7GpqazxrR69z/9qi+h5+VNnokGBQy1pVxJuYDt1Zy630FCYce6VwX31vKEz1KqxrjyljVvz6Kp5Dd5DMEGkEUTy1KVEMujKk4FNLc4Wq0M7K1iC3kC6X2zAYytvpEAMgob3mO3ZCCMyBj08saSGaW10hk8taEoXzLICgMs8fYkqdnJNXc8qhbaDxJv+tIRZeIXVoZ94jZY4zFmFVKeSGrsMmhEDTIGjyRiLj1E2A4PWNAULVNH65G+yNbNUJteZ6gINls5FK1dhzNEKdrUF2UrtpYXZwpl0nI1h6gpd1gUMhYd4OzUcXcWsnNhDISDj3KpS68rJQrepTCGuNmsHpg/bNEs7YI1G0RX8UW6eJRCBS2eh9KOyNbG+VNPhcAulvptllASRFbuPdpbk9rmnKFCwAcDEgAkFFW/amKfTugMZghYybeOHucz+U8vhVMJJEHjKwLPqsoLXnx+N5g3wmzV9Y/TX0oym9qKBQKLWtoqSrL65+rDYxNUSjUh8ImD1ej/ZGtAJAUG71i2mgrO8ffztykM5htEGiK0qKCU/t3eHr3Ua5wAYC1vRMA5GSktn6cdtL2qbnxHsw/Xpc8SqsKSa0c2VlPB1e3KiGUyKFhdGdGec3rXC4AyBubKWWQsdH5EqFEhv9ndfZldn3wAQmH7mFJjcjllvHFBuS6RZOoPO7au9kH/e3cTdRv8+2MbGWScTgMKq20wQ8ytawaAMzprcouP9aNcTa6lCUQK5d4bidWYFDIGFf95g/89jHoNb748R+VcY9Y70IYXUei8XX2VCYRAgCGXP+gVl2SwUl9DQDQ2CeO1WWIM6JlYiEKW/eWspPrt8uj8SRdhx6c1AgRpwynWxctyE2Pyjy71mHuQbKV+gzkNxLZys2IAQCyRSNPJEzvsSVPz4p5LCyl7jtQEX0bQWGY3cd8URX/vUzwNPojouhRCiskuWKUC1MHV7dmIZTKAEBPp36xNaO8+nUOGxr/YgKTjIvO46jaohdZVcpeEg7dw4oWmcMu44kM/pnyjMrlrLmVfmiCk7spRW20dka2AsCm+1mP01jPl3dTBK7K5HA+psSeqdPNQreVAs2gT8LeTihLKuGP8zBU7hN6X8wDAEu9r5m9vv34jJsafOrIy8f3w0PvDBzhR9Sp2zokEgkBgKZXvx8iNzO1bldwY18IPaZBQkyESFiLw9e9IW9ePVP2Eklk9+69YyPDWeWl+sw6ry4++tUva5dsPHjKya2L2mjtj2wtKcxbOd3X0sb+8OWHanlUWynQDDR9xt93rmYkxw/zn6zMh5b2Pg4ATC2/3IRZ24MbXI1JjgY6+8IKOTWSAI/6OHMzGt6STniYUplaVi2UyJ5mVM25nDaqsz4AxBfz1R5BAGCgPU0mh31hhbxaaRlfvCU0l9dwf3/gEEs0gnx/ISWzokYokUXmcpffyMShUU6fISBcB4da0Mv4dR5399/5xRxRjVgWW8hbcyebSsDM8TZWyETn80w3RQbeb3yH97I+Zno6mAVXM3Ira4US2e33FcciSpb3M1ON8+2gkC1ddUwd8+/skwg4Bt/Vb64j6JsRmJas2IfVRakysbAq4WnKkTmMbqMAgJ8TL5epL9DSXQeCXJZ/e5+khifilOVc2SJtmGvEakIggkInH/y+piRTJhZyUiPT/1iOYHE6pk5f4DI/hpsR/XKWadb5wGZkFLVpCEyLj7vMRy7DkvVSjy6oLcuViYXlUbeLQo6Zj16uGgispT24mpAdDUj7nuZxaiQBXeqf+M1oBEs9wsPkitRSgVAie5JWOftC0igXJgDEFfIasUUOejI57H2ax62VlPFEWx5kqduiYdYoBJlxLjGzvFookUXksJddS8VhUE6Gn2W77AAHen5lzc93M6qqxWU80U+30lJLBb/5OSBIawWi8zgmgc8D7zZST4qARW30sX1fzP/xZlpBVW2NWPY6l7P6ZjqVgJnds8lH+Q6Bo6uHtYPzqf07eBz2iIDpynYjUwsTC+vnIbez05JEwtrIpyHr504aONIfAFLi38g+CiXpOWCYTCY7tX8Hn8dhlZce3rpWwG0Qwrzo5x0oNPqn7/3yMtNEwtrYyPCty2dj8TgbR+fPcV17N6wUCYXbj19syttoUSA+JqKXOXHvhpUfd+EJxCVBu9Lex+1es6ikMK+2pjou6uWuNQvJVN2AWeqbij8f7QpfGufO2Pk4X5mGRAEKgT8mOWx8mOt7MhGNQrqak48FOOjgUIklgpkX0xZ9Z7J2UAOrPd6dWcAWXosrPxFZYkTBTvUyXDvYYvalNOE/WYw8zci357jsDysc80ciXyhlkrG+LoxlfU3xmM8SK7p2kIWNPvH8m9LT0R9qxTIGGfudte7xAAerhs8NH6cfUEDXwdye47L77/zRJ9/zhFJbfeLW4VbTu7WcG6BDYNBzXO61nco0JHUgqE5L/si+uDF+uy+CRlNsuzotOIYm6PDzE5MPzTQbscjSf22DQXqNF1YUlEVcK350AkczMuo/1dJ/bcqR2Yq5FgCg2Hi6/Xy74M7++J1jpDV8nC6T0d3XfNQy5ZyKZsm5srUo9Hj9y+BtOcHbAIDp7e8473D9VaKb+7FIqjkAgCY0YggwZLrbz7dzr++O3z5aUssjGtraTNlq1H/6x5Ja2sx4T8MdodnKNCQKUAicmtI56H7W6GPv0CikqwX1+CRnHRw6sYQ/83zi4r7ma4dYqw1SwK69+q70xKtCIwpuWjfjdUOsZ11IUmZU62JOvTPfc9/TPN/j7/hCKZOCG+PKXNbf8jPZov72eqemdj78vKD7nigUAl0tdW/P81CdjGlRQAG6CWP1fQ8TJhn3R0Th4MNvRFK5iS6+izl15QDLjj5HAgA+46b8vmuDMg2JAhQKtfvk5f2bfpw7pj8ajXb18t72+zkdEjk9KX7N7AnTF66et2Zzw0GmlhTkPbx24fLJw0xD4zFTZ89fu2XdnABlRrXOnt2O33z254Gd8/0GCPg8fabhoNHjv1+6VjmnokFqa6ojnjwEgPG91Pfijp70w/o9R1sUUL78OFeKAv/p8/QYhsGnjswY0l0sFhmamDl7dpu5fL3JP+lMDm9bd+nEQaX8ke3rj2xfDwDD/CZtOnS6vVcIAACI6kpKcHDwxIkT25nPo8Ox9HrGveRK1Up7LbL9UR6NiFnSp43PuIpKe62s/Ts/OJ3oPDA4OLht51IFQRCnhccY3Ua3f6gOTdqJpaw399Qq7TVPbvB2DJlmNkI9g5CmUFTaa1vt39Sj8wdYETXyDflaKCxPO9c4/gUsCU65l1ShWmmv/WwPyaYRMUv6NTJ71xoUlfbaXPvXJPD5lStXAgICWhZtmCSOMgAAIABJREFUFgRBtv1+ftDoce0cp2OxZdnMp/dvqlbaaz//2/EzlaY3fbFmUlR/jKLSXitr/25YOFWfiFa1XR17S+pXgVMjufW+QhnJq+Vfj0TAKY+6pe818msrokXLp8GpkdxMKBvp8gkRjlr+xfA47Me3g/uPGNuy6Feio246/4roEjFvVnt9bS20fDkwJN1ue9+0LKdFyzeGLhHzdo13y3Ja/htQdGm3or/pAp9ajwQAQCSRmW6KBIDXK7uY0z5jCGrfw3FZFTUAQNfRvvNfE5lE9HKWKQB0/fW1WgaRL8zbn/sqomJVS/Fp+c8ikshMAp8DQNSPPcw/Pa2IBumzPyarohoA6DotZIbU8vkQi4S9zIkAcD0y1djsm06nO6m/e35WOgDo0vVaFG4K7X0RDo+zPzzOvmU5TRC+VJuC4uvjOO+wasjq18VrZ3jLQlr+GxwJ6HQk4MvVEGmeFytbFeim5fOx6dBpTUWMfgEuh8W3fxBtHIkWLVq0aNGi5evzRT2SqedS7HdEfckzavm6JO2bGrnwC80/adHSZqaceW+35WXLclr+M6yc5jvIUb22vJbPjXbVphFORpZsDsk1puLClnio1aw6HfVhw4OcJ4vdVfOz8WqlZ2I+PE6ryqyoEYikdCLG1Zjs58YY46LfVCYALd8OnNSI93sC9Lv4dFp8Uq1LzGO9DeyHIZA9tz1F43WKH5/MvrS5qXGsxq9Xbg+WVHM/hF9gvblfW1Eo4VehcASikS2j60iToXNVaxpr0fJJnIwo3HQ/y1gX/3x5N3XT9Loo8G7m02VdVdO1cWslZ6OKH6WyMsurq0VSGhHrZkr2czcc48rUmqZ/AbERz5dO8uk33HfnCfUiYmxWxeQB7jokyvknb4k6pCt/HDm45aemxlm4bptyPzCfy7l98c+wBzdLCvI47Eo8gWhhYz9wpP/EOUtUqxx/JrQeSZOUcEW7n+RvH2HdvFhCseCHi6kELGp1f7O+tjQaEVPMFd5LYq2/l302+sPpKU562iDWbxtdp17G/aeXPPuLFftQv4uPalf2pc0SAdtp4XFlynwAcFp0gtG1uZ3A0hpe/PZRoqoPVuPXM7r7YohUYWVx6cvLudd2spNfuPzY9gKEWrQAQAlHuOtRzo7RLRRsSijifX8+kYhBrx5k2deOTiNiiznCe4nl626nn3lddGa6i542ZLWD06VXP79pc2+cO/E85E6/4b6qXQe3/MRlV20/ekGZRB8Adhy7qKzy0ygCPneOb9/yD8UL120dPHoCiUotKy68d+Xs77s2xLx8evDi/c91Jf+gjSNpkpHO+mejP7wr5DcjwxKIv7+QQsGjH85zHefOZJKxWDRiSScs/s40+AfnhBLBvCtpX0xhLW3GKmADXt8s63ygRCWffVViWPnrG0b9ptE69f6k0cqjbtV8yLLw+8l40EwsRR/BYAkGlpb+a40HzGAnv2AnPde0+lr+W4zszDwbVRRbwG1GhiUQzziXSMFjHi7qMs7DkEnGYdGIpR5hcV/zq7PdE4r58y4mfzGFtXw+FgfuMDKz2LthBZ9XXw8u6vnj0JuXx06b49W7/yeN9ujmlfys9LmrN47/YSFNn4HF4kwtbeav2eI/fV7Mi6fR4X9rWPuP0Pzje1wRf++zgjcFfDnIOxnoLOtnNsCO1qjkqxzOofCiuCK+RCY308WPc2cu6GWM+ycfM7tGcuB54aPUqg88ERmPdjchrR5grqyg23yvRljZ3ywmn/vjnazQ+W4YdOMznMcjSsr44gP+drpE9XfS3YQ8u4fR0VfFTzOqBtr/mzd28nPi8m7t5WW9Ablcx6yT+ahldNcBjUqyU14V3j/Ey46TyyR4fTODnuNMhy9QrmJIBOz8Owcq4x6J2B/QBDLZyt1i7GrKPwVym+9tJ2g8yf6HPYl7J+de3W434xcAkAqrs/5ah9c3sw7Y8KmjiflVAECxclNrtxizyqj/DB0TbWDN1yGukPfbk1xFdVwnQ9Ly/hYDHBrfpvgym30oLD+ukCuRyc1ohPEehgu+M1M1Tfuf5j1KrfjAFZHxaHdTyupBVp5mlNb0aoRVAy1j8jk/3UwPWeyFbcI0HXtZUMYTHRzn1IhpMqXM6Wn6+4uCJ2mVgxzbvlHzX0BK/Ns/9m57//Y1yMHWqfP3y9Z69x/aqOTbV2Fnj/yaHPdGKpEYmVkM958yZf5y5SoGl111+uDOF4/uV5SW6JDJndy8Zq/a4OzRtTW97YRIIq/79fcVU0b9vnPDml2HAaCmWvDruqVGZhaLf97xqaNx2JUA0MldvUzgrFWBY6fPsbL/7JXFNOyRxBXxx55K/KG70e7RNiQc+sDzwhnnU85McRrkoH5Ljs7nTfkrxcdZL3ypBwWPCUmtXHYjgyUQb/GxUggsvJqeXl5zIsDBxZhUyhNvC80NOJMcssDNRp/QYq8qldUS119imlL4+VIPOwax0S4dLGqrj/WCq+m/vype1rfxhPH3k1l0HUxfm8ZdLj83xtFXxfeSKv/FHgkvJy5h11iTgT/YzdiNJpDy7xxIOjDDefkZPbdBapLcjOikvVP0vXy8doajiZTKdyFpJ5eJeSybyVsUAqnHFlYXp3dadIJk4SLilOZc2Zb4a4DHphCikU2LvaqI+ZVRy1ybUthrx3OicSPT3bTOfY36Tf3w/IKBtz/VoUf+rT21FQUuP15GEz7ZzdV19AaA0lfBFDsvBFX/E8NSmViqNnvm1+FdIW/siXczvU1/GeNAwqP3P82b/tf7M9NdBjuqJ1+OzuNMOZ0wojPjxYruFAI6JIW19GpKhUC0dWTd12bB5eT0suqTk51dTMilPNHWh1kBp+JDF3vZMIgt9qpSWS122RHRlMLhK7rZMRsvJkrEobaOtFtwOfnoi4Jl/RtPD38/qYKug+1r17jl8XM3+P1Fwb2k8v+yR5Ic92ah/6BxP8xfs+swkUQ+fXDnj9/7/frntV6DfNQk42MiVkwb3d9nzOWweBKFGh56d+vyWVWs8hWb9ygENi6anpORsuPYRQcX94qyD0e2rVs6yef0gwgLG/sWe1VhV7JGuDdZ5vDSszhLO8eP27v3GeQ7ZdbtC6eG+U1y7977j9+2lhTmHbx4/1PL/wKAp3cfALgffM6lSw/V8jd6DAM9hkHTx2kMDXsk2x/lGVNxG4dZKaKmNg6zepBceSa69GOPJDS1Eo9BBQ21NKTgAMDfjXHxbemVuDKFRyKUyF5mcyZ1MfAypwCABR2/z8+u54HYsEy2jb5R871qJ9LTwbStUo8cYLSL/tV4+oHnhb4u+lYfVZ8SS+W5lbXdLShIEyFiTgY6CAIppYI2nL2jkBu8HU8ztp64ERAUANhM2siKfVDytBGPhPUuFIXFWwcE4WiGAMD09v8QfrHs5RWFRyITC9nJL436TKLYegEAgWHhMGtfzNqeVYlhRCOb5nvVToQl6333Z6uqKqhhHRBU9f5Zxpmf7GftK358yqjfVJpzWyqMUO27W0/cmHd9Nzv5JcPLh2LfjWrbVXHVWr4W20Oyjan4jT62CtO0aYTtg+Tys1HFH3skoSksPAYVNNzWkIoDAH93g4sxJcGxpQqPRCiRvcyqmuRl7GVBBQALOmH/OCfv36LCMiptGKbN96qdSE8H28ZSPnLwdWVee6e//1meryvTSl/d1xFL5bmsmu6Wuk2aJkMSgkDKh3+zaWqR/+34mWlksmTDbhQKBQBLg34Je3j7+l8nPvZIXoTexeEJSwJ3MQyNAWCY36S7l04/CD6n8EhEwto3r56Nmvi9i1cPADAxtwrcd2J8r05Rzx9b2Ng336t2IpqefkRBTRuuZWnQrqiwR7vWLAr87fiVP//nO2VWtz4D2zCOe7deS4N2H/tl05tXz/r7jHHr2svFq4fiqr8MmvRIBCLp6zyunytDGcSNQiB6lfr8j4KgoZZBQxtkoLOgEyJzuZwaiS4Rg0WjGCRsSErlQHv6EAc6Bo1Q8GhlabrmezXLrlHW/Y/ErbmTHfyDeoFpvlAKACQcurHjAADQKISIRfGE6kWu/zVIhQJO+mtmDz+FOwIAgKC67YluVNg6IMg6IEi1hcCw4KRGSgQcDEkXhcHiqAxWbAjdbaCe+xAEjUETKcrKc833ago0kWL3/a9J+6cl/jYRRzNU01ZJ6u/zPm7EkOmq+pgOm2/Q0788+i47+UXZ65tibgXBwJLRdbTpsHlYirYi0pdGIJK+zmX7uRmomqaYnxpPrx403CZoeAM311yPEJHDrjdNZFxIcsUgR73BjvpYNELBo5WF6Jrv1Sy7fO37HYxZcys9eLa7WhdfKAEAEr5504Tm1Uo+h2IdghoBPy7q5dCxExXuCACgUKibr9MbFV6yYdeSDbtUW4zNrWIjw3kcNkWXhsHi6PrM8NA7PQcO7z3YB4PBkshUZam55ns1BYlMXfvL/1ZNH7Ns8gimofHSoF2NigUumPJxoy5dT1WfyfOWD/Of/OTutTcvnoXevFxVUW5qaTNwlP/kuctp+p99O3QDj4RAIACASCLDtam4djlfLJeDPqlV8dtCiexsdOn9ZFZ+VW1VjUQmB6lMDgBSOQAACoEzU52WXMuYczmNiEV5mVMG2NEmdTGgETEt9moWU138moEWm0Nyr7wrm+jZYNqKgkcjCHBqm3Q4JFJ5jVimS2iXVkIp6BEbX1f6VHB4gkws1MhQCsSccpDLW3mLlYmFJU/Pst7ery3PFwuqQCaTy6QAIJdLAQAQlPPyM2knlqQcmYPCEal2XnSXAYZ9JmFItJZ7NQfddQCj68iKN/etJ29GExuf82xxr40CLJVpMniWyeBZAFBbllcZ/6jg/v/KXgW7/XyLwNRoNmixkEjs2HPv7bQ8LVLOE8nloE9q1b5roUR2Jqr4fmJ5flVtVbVYxTTJAQCFwNnpLouDU2ZfSCJiUV4WugPs6ZO7GitNUzO9msWUhl8z2Grzg6wrbz9M9GowN0zGYxAEuDVNOhxiqbxGLP04xESz1IplAEDUhPnCEwhikSZtF6u8VC6Xt/IWKxLWXv/rRNiDm8V5OVx2lVQmlUmlACCVSgEAhULtOXNj89If1s+dSCDquHj18O4/dNTE76k0eou9GsS7/9ABI/2e3b+5fNMeEpnaqEyLe20U6DEMJsxcNGHmIgAoyst++fjBuf/teRB87vitZyYWLWw+/SREtbVEvQYfQYPfv76+PgBUVrfRcUYhCAAIJbLWCC8ITt/6KLefHe3WbJfkdd2zg3pM6tLgfu9uQg5f6nlztsu8XiZ8oXTbo7zeB98llgha06tZZvUwcjMhbQ3NYwnEqrOgGDTiwNRJK6uWKNyoj0gpq5bLwcWY1GhvK6mskenpaeZ+Q6PTFUGXGgOFAgC5pFWWIvXogpzgrbTO/dzW3/I+nNzrRLZhn0mqAmQrd68d4W7rb5oOmyep4ecEb3uzrjc/P7E1vRoEr28GAAT9Jldz2wDBwNJkyFz3wNsiTlnBvUMaHBkAZIJKTX1Dvhb/WB7xZxofhUIAQCRtlWmafzl568OsfvZ6t+Z5pGzonbOlz6SG93t3U8qLFd1vzfOY/505XyjZFpLda29UYjG/Nb2aZXZPUzdTypaHWSyBGKDeNmHRiAOTlFoqEDdhmlJLBXI5uBhrcivAx1RVi+GfD7ed6NH12JWs9o+jBIVGA4BYKGqNcNDC6Ue2reved/Cxm09DEoufZ7JHTfxeVcDJrculsPijN55MmrtMwOMe2b4+oE/n9MT41vRqECNTCwAwMms8tKhtmFraTJyz5MTtMFZ56ZlDv2hwZADgVFWo2a4GPrKTkxMApJRVG1HbksTJhIpDIVDGa9mslPJEj9KqxrgyVvWvt/uFbPUbG4JAdwtKdwvKmoHmbwt4/n8m7Qsr/HOyY2t6lbQ5slUJGoXs8bUdceL9ppBcb8sGvueozvp7nxU8+H97dx7W1JU2APxkIYQl7GtYAiLKpmBdEIp+flXHOoLW6uhnEVe0RcFq7UjRVpB2nqlVtFirA7hRwK0jKJVFKhSrIAqCgEDYIyGBsISQfbnJ/f4IMhARaLghOL2/P++5nnufx+Ob47nveU8de7XXCP/qMl/0AABGbBonGAYNXYJdbshkOHu4u9cxqIh0paRrSgYYrLS/a8w7pRwW+3mepe8axzWfDV6U9Lar3ofBGLkuMHJdQFl7iNf8rOqfH9LvnHKPuDSu1lfUy2xFCgzJmPcvYnB48vJQlSaihSMGixexWhF9HsxnNLi57UKyz0k3EHk6BTZGGinBZGuki8UAFm/snx8WV5pX17tmttXB9/6zjjVyaKIYL6AYH1rm9KyNuzbpeVzBy8ubPcfTOkjtzNZBOCzm5AczVp4vP5rV5Oc8bL0wcJZlXD4tp7Zn9awRkqnvVHcBAFbP1myuIpUlAK/+cifI3d29pb5m4v0MsrK1w2KxPV0dY97Zw+p4+OvdZav/tvPAkcGLnYw2ldswGIz3fH/v+f67/x794tmTsPXLLp7+x/GLN8fTOki9zFakyGTSny+dw+PxG3aGqzTZOjjh8Hh6K5LnBsMw3NpAddu1Y+jFYTMSc3NzVxfn4tb+N+3XHR0eh5nnQCpq7ZdACt1Xq69Lz1US8dis3cN+ISQQDAAYWjqssVtUQuMq3xIA8JjGDb/VmBLs5mEzsMAw14FkRdJRTrpHb1WhdmbrUF62BqELbROKmdjhqWI7fW2ulbO+zqP5UkjKFN1BLzoEF0s6l880fdfZWO3nVjL5PJHUz2+i768U8K5/WWIyIl0pYXB4o+nzOHVFCpkEqzPwW1JxdClGh+jz1bBaOgpIAgDAG/5nOizsaOynlgAAAAwDAPrrH9cnhnvuTzFwGMjXIbnMJZhYKRd1Rm9VoXZmKyIweJ2esrtCRr3ZnBUqpwqzK+/DCkifPAPBx/FplVIhD6kRoi3m5uauLtOKWjlv2o47QTo4zDxH46LmvmGh6UyZrg42O2xYoptErgAADC0d1tgtLGnlgIFxCh63cvbepKZu8fJ4tcAw19HIikQYCE2jtqpQP7N1CC+y4S5/u389alcJTaF+dtfKOmJzmn0pxtbD/4f5gsm/WMxY7mYe8IZNgkgpauG4ukxDZAHP39/vUnLKxPsZhMfrzJq78FnRA6lETNAd2LUQsnw+QVf34t1h5wlIpRIAgMmQjwu0JmpFyUMABsZERcnDmIhtcckZ0z0GNvx7zfW1sLLh9vWO2apC7cxWROjoEH7LSm+pr120IkjlnOGi+9lyCJo2UzWZciKoVeV8Hlcldql+tQ1aszabyoVHXuob2+HlFDGkiLjV1M2XccXQ8fw2KksYMk91l4G9iS7FlJhTx6Z2CSWQoqCxL/R6faCnOQCgksmXK2AfO0M8FvNpRnNFO18CKTgiKLG4g9kv3fSONQBg9FYN+fx/HRxMdNOruodeNNbDpwS7YwDmr4nVNyu6u/kymRymcyQJxcz1l2t8KaQJniqcVdtLsbebPVu1soV6AgMD+V10Pg3J1UKn9YcVMnFDYoSM2w0JuS/TjwvaqbZLQlRuI5rbEy0pveU5QgZVIZP0VRXUnQ21mB8IAOC3VsIKOcnZB4PFN1z4lNdSoZBJIAGHcS9RwmZaL94EABi9daqZvvU7LEHvxXcbuksyIAEHlkOSvo6OguSGC/t0ze0cg/Yj+Kyesiw7BwpSI0SLgtZ8kF3HUTvyjOnICmcxpAi/Se3mS7li6PivrXUswZYFZJXb7E2IFDNiTm0PlSWQQIr8evbOtJpAL0sAwPN2nlwB+9gb4bGYfbfqy+lcZfBJKGpn9ks2zbMBAIzeqiGfL3VyMCWmV7KGXjTWw6dsnYXBgJXny2+Ud3bzpTI5TO8T/+tR+7oLz32djDV9yLACBtlUzuoPxs5aGI/AwEAm/SW1qhyR3pTCor6RSsQx+7aze7r43P7E72KaqS/WhqguN9rYOZIdnR/k3mmpr5FKxI8LcqN2/d97qz4EANRVlinkcnfvuTg8PvbArpqKUqlEzOX0XUs6w2K2B27aBgAYvXWqifz2rK6eXsSG9/Nu3+By+iBI1tXBSP8pIXb/Tms7h237vkDwWb9lpTs6qsYuDDw8BtTU1Hh5eaVsdlO7hEZpG+9EAb2KyYcBcLXUC3uXvMpj4LNFcErd0zZu4xFfAEBtp+BoDq2KKcBhMfMcDA8vp+gTsFtSqTS2eE8AOXKpI7NfGldI/72Z082XkXRx0y30dvjaBr36AjJ66wQpz7Up+nSOyo7fgkZOSGodAEDlXBuBVH7laWduXV9z78C5Nt5kw7/5WK7yMH/T7rvxEMkUvvGVEQe/iI6OVr+X4dw8PDnmXq47TiPVIQCA21jadvsEj1YFYFif7Gr3fthg4mfNqWBu41O/840AAAG9tuXqUT6tCoPDkVzmOa0/jCPq13y/Rcyi2f91D+XDSAmb2XYnjlPzu5TbjSeS9Gynk5ftsJgfpOxq9FYEtd6IZdxL8DmabeikuoVh9HNtiFaUed8OLMJLehmMvERO7UNxd5tCJsETDfRsXEy9l5GX7cTrj5x0pgaFVFQR6Rt5IALBEaItA5FnyyzNVcgofdl/4j6tksGDAZhhZfBJgL1yqgEA+OhK9dOX/U3RAQCA2g7+V1nNVQweDouZ52h0ZMU0fQIu5KdqWq9o72KHyOXOzH7JyXza70193XwpSRc/3VJ/h5/d4MeR0VsnSHmuTfFnC1R2/BY0sDcnVwMAVM61EUjlV0qYubU9TT0D59r42JPWz7EO9LScSGgaj/x6dshP1S9evPD0VP1cpR5PTy9nz3eOnEpEpDelqtLHSXGx1MpyGMDOrm4ffXxgMPHzwObVVaXF+fU9AICm2qrT0Z9TqytwONysuQvDor7WNzA8uHVtO605JOzg7kMxLGb7xVPflD7MZ3d3GZBIFJeZ67fvWRq0TtnV6K0I+uHrL64lxl/KKnKbrbrFdfRzbewo035+NPBRjMWgX0s6U/qwoINOk0rE+gYkRxdX/6UrN+zYa2ik/nq/CrFIuM7P7dOIvSqxS3VGAgBYHRTY+Ozhvd0eePQoJq06UUC/XM5paGq2skLsc29qaurWrdu8j+YYOCITJlBa9DLjRF/h5eamBgRHiBatDgpsLH+UF+aNRp63HaSA/3Luues7izLv3kWqz9TU1G3btl3KKnb1fOtXBFFJJ2NvXTnX2KAau0bYa3f6+3gaW5xSynq9CTVpGP2ShBJW9LFYZH9sgoODF/r5064eAZpbH0dNCkkvozMvIfZY9H/HdAQoI0+vKOUpU9svgpqon54wW3qEJ0+dQrDP4OBgP3//U1/tf/1/0ai3C4tBv54YHxM9QuzCxcTEqFwyMzMTCITxN35d4WaCHg6pFZAc/vjnZoKJ7eXkZBzujWWO1IDBYHy8Z/9wPBZvYEyaNnLxOtTUB8uhhvMf2xoRkq9cRnaEaNFA5Ll+7313M7PxlTVCTUFN3cLwfzfuO3Bw48aNCHaLwWC8Z8/+R2yMkbGJ55wFCPaMmkwQJPvyk4/0dHBXRopdI8xIAAABAQHZOTnJD6hrvcz031yTFKUhh7NphS387Ht5ZLJq5t3EkclkAoGQfibagDLr9RLsqLdCS9phfm1hXm62JkaIFr2KPHVrZ1uikedtxBFBG67U2E+beflKso4OwtNKZez6NubwTC+f10uwo94KcV8eeFKYl5MzcuwauUIikUi8nfkLxsA09GbTf3ER9Kkp/kF72jPW1es3vL1VMyuREhUVtTkkpCkpnNf6XEOPQGkO/Zf4zgdpN65d1dwI0ZaByKNvEnqNikaetw5PIt+WVivXNc7KydXXH6OYinqioqJCQkKO7dte+7xME/2jNOrKmW/vpF28dvWNseuNNZutrKyysnPpIsIHl6n01woEoTQBksOHMlviChlnz/4YFIT8LpKhkhIT3vufRbXfre8pyxr7btTUAMuh5uRD9My4H8+e1fQI0RZl5GkT4tckVdP7xNp+HdR40fvEa5Kq6EJ8Vk6uRnObEhISFi0KCN+w4resDM09BYUsCJIdj9x78dQ3Z0eNXaOdIuHp6fmktEzX0jHwQm1BI6LVx1GvoXMkwWn1d+q4Gbdvh4WFafpxBALh7i+Zn+wOrT//8cuME8ied4PSBHEPve50MKfszu2MjEkYIVqkjDxES4dViVX59Wxtvw5qbPn17FUJVboWjk9KnyG13fdNCATCL5mZu0J3fhkWnHQyVipBp61TXUf7y882r76feTNjrNg1ch7JIGNj480hW2qpDbFXH1R3ir3JBqb6mj2c6U9IJFN8/6A9PL2ZYErOvpe3ePHiyXkuFotduXKltbV1RsLx7qKbOmZkfVv00+xUpJCK2jK/b7oQbmtEyMvNnrQRokWvIk99bFpBVYfQx87QFM2yn5Jae0X70xtP5reu+XBdxp1MS0tkKq+MbjB2nT7+Tc7PqVZkBydNlldHqU0sEl6O/+exiO16BHxOztixa4R6JCMqLCyMCN9TT21Y4Wa6ztti0TRjPR2NnNL55wHDoJLJz6rtvVHJhgD+aMyxiIgIxHPBxoPJZP79UOS1q2lGFC+LgE1mc/6ia2o7+a+BUgXDfFplT1lWb/ENHAwdiz6qrRGiRQORp75hhbv5em+rRdNN0cgzFYhkiodNff+u7LpX1ztz5owfzp5bsmTJ5L8Gk8mMjIxMS0ub4ekdtGlbwPJAK1u7yX8NlAoYhqlV5b9lpWfdTJFD0uij441d452RAAAgCLp+/XrC+R+LS57gMBgXa5KNId7wzxUekSGRA7ZI0dAl4ImkFHu77aG7wsLCtF5VoqysLD7+zK30dJFQYGBhR7RywuibAE1XdkSNCJIo+Gw+o0Eq5Nk5UHbt3D4VRoi2DI88WBdrkg1Jh4RGHi3hyUAHT9bC4slhhf9C30/2hG/cuBGP1+baeVlZ2ZkzZ26lpwsFAhuyvZ2TC8nEFIvXkg+wAAAAqElEQVRFZ65aIJVI+tndrQ1UPo/r6EjZseOPxa4/MCMZxGKxCgsLKysrWSwWj8f7o38cRSQSTU1NPTw8/Pz8ptqJJGKx+NGjR+Xl5a2trX19fQrFuA5wRyFrKo8QLUIjz1RAIpGsra29vb2XLFliba3Bo8T+KDR2TQUTjF3qzEhQKBQKhUKhkIWua6FQKBQKhdI+dEaCQqFQKBRK+9AZCQqFQqFQKO37f78pS0ZUhoByAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FUnwNy3w27mn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "db8eb631-7ba3-4982-fa2f-7800625921eb"
      },
      "source": [
        "# Run this block for model evaluation \n",
        "print(\"Model Entropy model max depth 3\")\n",
        "print(\"Accuracy:\", metrics.accuracy_score(y_test,y_pred))\n",
        "print(\"Balanced accuracy:\", metrics.balanced_accuracy_score(y_test,y_pred))\n",
        "print('Precision score for \"Yes\"' , metrics.precision_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Precision score for \"No\"' , metrics.precision_score(y_test,y_pred, pos_label = \"NO\"))\n",
        "print('Recall score for \"Yes\"' , metrics.recall_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Recall score for \"No\"' , metrics.recall_score(y_test,y_pred, pos_label = \"NO\"))"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model Entropy model max depth 3\n",
            "Accuracy: 0.907563025210084\n",
            "Balanced accuracy: 0.8658536585365854\n",
            "Precision score for \"Yes\" 0.8764044943820225\n",
            "Precision score for \"No\" 1.0\n",
            "Recall score for \"Yes\" 1.0\n",
            "Recall score for \"No\" 0.7317073170731707\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d5U22BCW27mv"
      },
      "source": [
        "So our accuracy decreased, but is this certainly an inferior tree to the max depth original tree we did with Model 1? Write your conclusions here: \n",
        "\n",
        "\n",
        "\n",
        "*   Accuracy, Balanced accuracy, precision and recall score - everything is lower compared to \"Entropy model - No max depth\" since the decision tree stops after reaching 3 nodes since the model determined that the node purity is sufficient. However that doesn't mean it is optimal and there may be a need to adjust the number of nodes if higher prediction power is needed.\n",
        "Depending on the dataset size, having 3 level of nodes in the tree may be a \n",
        "simple model of performing training on the dataset, however this application is just for comparing all models\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Iy9DmgIG27mw"
      },
      "source": [
        "## Model 4: Gini impurity  model - max depth 3\n",
        "We're now going to try the same with the Gini impurity model. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QB-UrxQv27mw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9c684dd9-bf40-4ac6-aa39-14de3d427c43"
      },
      "source": [
        "# As before, make a variable, but call it gini_model2, and ensure the max_depth parameter is set to 3\n",
        "gini_model2 = tree.DecisionTreeClassifier(criterion='gini', random_state = 1234, max_depth = 3)\n",
        "\n",
        "# Do the fit, predict, and series transformations as before. \n",
        "gini_model2.fit(X_train, y_train)\n",
        "y_pred = gini_model2.predict(X_test)\n",
        "y_pred = pd.Series(y_pred)\n",
        "gini_model2"
      ],
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
              "                       max_depth=3, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=1234, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xgAGJ8Aw27mz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 594
        },
        "outputId": "59737314-5eea-4198-ebce-a50e15cc3378"
      },
      "source": [
        "dot_data = StringIO()\n",
        "tree.export_graphviz(gini_model2, out_file=dot_data,  \n",
        "                filled=True, rounded=True,\n",
        "                special_characters=True, feature_names=X_train.columns,class_names = [\"NO\", \"YES\"])\n",
        "\n",
        "# Alternatively for class_names use gini_model2.classes_\n",
        "graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
        "Image(graph.create_png())"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HKNGp4-127m0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4261d352-9966-4c39-9503-4fa724631e36"
      },
      "source": [
        "print(\"Gini impurity  model - max depth 3\")\n",
        "print(\"Accuracy:\", metrics.accuracy_score(y_test,y_pred))\n",
        "print(\"Balanced accuracy:\", metrics.balanced_accuracy_score(y_test,y_pred))\n",
        "print('Precision score for \"Yes\"' , metrics.precision_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Precision score for \"No\"' , metrics.precision_score(y_test,y_pred, pos_label = \"NO\"))\n",
        "print('Recall score for \"Yes\"' , metrics.recall_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Recall score for \"No\"' , metrics.recall_score(y_test,y_pred, pos_label = \"NO\"))"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Gini impurity  model - max depth 3\n",
            "Accuracy: 0.9747899159663865\n",
            "Balanced accuracy: 0.9691994996873046\n",
            "Precision score for \"Yes\" 0.9746835443037974\n",
            "Precision score for \"No\" 0.975\n",
            "Recall score for \"Yes\" 0.9871794871794872\n",
            "Recall score for \"No\" 0.9512195121951219\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KCgp_QEh27m2"
      },
      "source": [
        "Now this is an elegant tree. Its accuracy might not be the highest, but it's still the best model we've produced so far. Why is that? Write your answer here: \n",
        "\n",
        "\n",
        "\n",
        "*   'Entropy - no max depth' had the highest accuracy and scores, however the decision tree didn't end at 3 steps like in this mode - Considering this level of performance was achieved only with 3 max depth, significantly higher than Entropy - max depth - 3 model, this is the best model so far from performance, accuracy and prediction standpoint\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XNwLDdpq27m3"
      },
      "source": [
        "# 4. Evaluating and concluding\n",
        "## 4a. How many customers will buy Hidden Farm coffee? \n",
        "Let's first ascertain how many loyal customers claimed, in the survey, that they will purchase the Hidden Farm coffee. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pxCzly1T27m7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b01b5d5f-db78-4bd5-f314-0411d93baacb"
      },
      "source": [
        "# Call value_counts() on the 'Decision' column of the original coffeeData\n",
        "coffee['Decision'].value_counts()"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "YES    303\n",
              "NO     171\n",
              "Name: Decision, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a01RQxef27m9"
      },
      "source": [
        "Let's now determine the number of people that, according to the model, will be willing to buy the Hidden Farm coffee. \n",
        "1. First we subset the Prediction dataset into `new_X` considering all the variables except `Decision` \n",
        "2. Use that dataset to predict a new variable called `potential_buyers`"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sN4Z56Sb27m9"
      },
      "source": [
        "# Feature selection\n",
        "# Make a variable called feature_cols, and assign it a list containing all the column names except 'Decision'\n",
        "feature_cols = ['Age', 'gender_factor', 'num_coffeeBags_per_year', 'spent_last_week', 'spent_last_month', 'Salary', 'Distance', 'Online']\n",
        "#features= [\"Age\", \"gender_factor\", \"num_coffeeBags_per_year\", \"spent_last_week\", \"spent_last_month\", \"Salary\", \"Distance\", \"Online\"]\n",
        "# Make a variable called new_X, and assign it the subset of Prediction, containing just the feature_cols \n",
        "new_X = Prediction[feature_cols]\n",
        "#new_X  = feature_cols = Prediction.drop('Decision', axis = 1)"
      ],
      "execution_count": 93,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hJtAgLwI27m_"
      },
      "source": [
        "# Call get_dummies() on the Pandas object pd, with new_X plugged in, to one-hot encode all features in the training set\n",
        "new_X = pd.get_dummies(new_X)\n",
        "\n",
        "# Make a variable called potential_buyers, and assign it the result of calling predict() on a model of your choice; \n",
        "# don't forget to pass new_X to predict()\n",
        "potential_buyers = gini_model2.predict(new_X)"
      ],
      "execution_count": 94,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sRHlWr6227nB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cc980426-77b1-43b0-b515-0c354f53b49d"
      },
      "source": [
        "# Let's get the numbers of YES's and NO's in the potential buyers \n",
        "# Call unique() on np, and pass potential_buyers and return_counts=True \n",
        "np.unique(potential_buyers, return_counts=True)"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array(['NO', 'YES'], dtype=object), array([ 45, 183]))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WluA9I93mXIU",
        "outputId": "a0d84b1e-8e22-4433-9909-1af875a9d6d9"
      },
      "source": [
        "\n",
        "# Actual Coffee buyers\n",
        "coffee.Decision.value_counts()[0]"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "303"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k0Dyzotrmny0",
        "outputId": "c23838a4-c2a4-4519-9bbb-60d384183be0"
      },
      "source": [
        "#Predicted Coffee buyers\n",
        "potential_buy = potential_buyers[potential_buyers=='YES'].size\n",
        "potential_buy"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "183"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "80ZWqWGs27nD"
      },
      "source": [
        "The total number of potential buyers is 303 + 183 = 486"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lMCYZ27Y27nD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb8f41a2-9663-4afa-d99e-1eff14a43f68"
      },
      "source": [
        "# Print the total number of surveyed people \n",
        "print(\"The total number of surveyed people was\", coffee.Salary.count())"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The total number of surveyed people was 702\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oYM3t5JF27nF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0c6eabdf-f8bc-42f6-bcf5-821f1de5462c"
      },
      "source": [
        "# Let's calculate the proportion of buyers\n",
        "486/702"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6923076923076923"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3jJDAZaC27nH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "06883109-2057-4a4a-b70c-5d7de06278eb"
      },
      "source": [
        "# Print the percentage of people who want to buy the Hidden Farm coffee, by our model \n",
        "print(\"Only \", round((486/702)*100, 2), \"% of people want to buy the Hidden Farm coffee.\" )"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Only  69.23 % of people want to buy the Hidden Farm coffee.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kZwXNtjh27nK"
      },
      "source": [
        "## 4b. Decision\n",
        "Remember how you thought at the start: if more than 70% of the interviewed customers are likely to buy the Hidden Farm coffee, you will strike the deal with the local Hidden Farm farmers and sell the coffee. Otherwise, you won't strike the deal and the Hidden Farm coffee will remain in legends only. Well now's crunch time. Are you going to go ahead with that idea? If so, you won't be striking the deal with the Chinese farmers. \n",
        "\n",
        "They're called `decision trees`, aren't they? So where's the decision? What should you do? (Cue existential cat emoji). \n",
        "\n",
        "Ultimately, though, we can't write an algorithm to actually *make the business decision* for us. This is because such decisions depend on our values, what risks we are willing to take, the stakes of our decisions, and how important it us for us to *know* that we will succeed. What are you going to do with the models you've made? Are you going to risk everything, strike the deal with the *Hidden Farm* farmers, and sell the coffee? \n",
        "\n",
        "The philosopher of language Jason Stanley once wrote that the number of doubts our evidence has to rule out in order for us to know a given proposition depends on our stakes: the higher our stakes, the more doubts our evidence has to rule out, and therefore the harder it is for us to know things. We can end up paralyzed in predicaments; sometimes, we can act to better our situation only if we already know certain things, which we can only if our stakes were lower and we'd *already* bettered our situation. \n",
        "\n",
        "Data science and machine learning can't solve such problems. But what it can do is help us make great use of our data to help *inform* our decisions."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "crWWrpdox8i-"
      },
      "source": [
        "## 5. Random Forest\n",
        "You might have noticed an important fact about decision trees. Each time we run a given decision tree algorithm to make a prediction (such as whether customers will buy the Hidden Farm coffee) we will actually get a slightly different result. This might seem weird, but it has a simple explanation: machine learning algorithms are by definition ***stochastic***, in that their output is at least partly determined by randomness. \n",
        "\n",
        "To account for this variability and ensure that we get the most accurate prediction, we might want to actually make lots of decision trees, and get a value that captures the centre or average of the outputs of those trees. Luckily, there's a method for this, known as the ***Random Forest***. \n",
        "\n",
        "Essentially, Random Forest involves making lots of trees with similar properties, and then performing summary statistics on the outputs of those trees to reach that central value. Random forests are hugely powerful classifers, and they can improve predictive accuracy and control over-fitting. \n",
        "\n",
        "Why not try to inform your decision with random forest? You'll need to make use of the RandomForestClassifier function within the sklearn.ensemble module, found [here](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html). "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fI4fiVWq0IH9"
      },
      "source": [
        "### 5a. Import necessary modules"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vSRTnHnD0D-O"
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.datasets import make_classification"
      ],
      "execution_count": 102,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jKmFvvjb0WB9"
      },
      "source": [
        "### 5b. Model\n",
        "You'll use your X_train and y_train variables just as before.\n",
        "\n",
        "You'll then need to make a variable (call it firstRFModel) to store your new Random Forest model. You'll assign this variable the result of calling RandomForestClassifier().\n",
        "\n",
        "Then, just as before, you'll call fit() on that firstRFModel variable, and plug in X_train and y_train.\n",
        "\n",
        "Finally, you should make a variable called y_pred, and assign it the result of calling the predict() method on your new firstRFModel, with the X_test data passed to it. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OQEeTiRG1aSm"
      },
      "source": [
        "# Plug in appropriate max_depth and random_state parameters \n",
        "firstRFModel = RandomForestClassifier(random_state= 1234)\n",
        "\n",
        "# Model and fit\n",
        "firstRFModel.fit(X_train, y_train)\n",
        "\n",
        "# Predict\n",
        "y_pred = firstRFModel.predict(X_test)"
      ],
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GPkibrwGfAbV",
        "outputId": "ebba05d3-7ce8-486b-a804-8d5860588804"
      },
      "source": [
        "print(\"Random Forest model\")\n",
        "print(\"Random Forest model\")\n",
        "print(\"Accuracy:\", metrics.accuracy_score(y_test,y_pred))\n",
        "print(\"Balanced accuracy:\", metrics.balanced_accuracy_score(y_test,y_pred))\n",
        "print('Precision score' , metrics.precision_score(y_test,y_pred, pos_label = \"YES\"))\n",
        "print('Recall score' , metrics.recall_score(y_test,y_pred, pos_label = \"NO\"))"
      ],
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Random Forest model\n",
            "Random Forest model\n",
            "Accuracy: 0.9747899159663865\n",
            "Balanced accuracy: 0.9749843652282677\n",
            "Precision score 0.987012987012987\n",
            "Recall score 0.975609756097561\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sCIt6pyn1zpb"
      },
      "source": [
        "### 5c. Revise conclusion\n",
        "\n",
        "Has your conclusion changed? Or is the result of executing random forest the same as your best model reached by a single decision tree? "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Im4kEt60fgNM"
      },
      "source": [
        "**bold text**\n",
        "*  Yes, The accuracy & Balance Accuracy is alomst of Entropy Decision - max depth  tree is almost at par for 'Random Forest model', it might be worth to execute random forest considering the best model was reached by a single decision tree by taking a random subset"
      ]
    }
  ]
}