From 2156d98d9bb6b6a7b4b97caf2b082f48f0f5b8ab Mon Sep 17 00:00:00 2001
From: smty2018 <74114936+smty2018@users.noreply.github.com>
Date: Mon, 7 Aug 2023 01:17:54 +0530
Subject: [PATCH] Add files via upload

---
 .../ReadMe.txt                                |    5 +
 .../StockTradingForecasting.ipynb             | 1634 +++++++++++++++++
 2 files changed, 1639 insertions(+)
 create mode 100644 Stock Price Direction Prediction(Tesla)/ReadMe.txt
 create mode 100644 Stock Price Direction Prediction(Tesla)/StockTradingForecasting.ipynb

diff --git a/Stock Price Direction Prediction(Tesla)/ReadMe.txt b/Stock Price Direction Prediction(Tesla)/ReadMe.txt
new file mode 100644
index 0000000000..d840155671
--- /dev/null
+++ b/Stock Price Direction Prediction(Tesla)/ReadMe.txt	
@@ -0,0 +1,5 @@
+Aim
+Aims to predict whether the stock price of Tesla Inc. will increase or decrease in the next two days, leveraging technical indicators and moving averages.Performs a classification task on historical stock price data of Tesla Inc. (TSLA). It uses a Random Forest classifier to predict whether the stock price will increase ('1') or decrease ('0') in the next two days based on various technical indicators and moving averages.
+
+Details
+Random Forest classifier is employed for the prediction, and GridSearchCV hyperparameter tuning is performed to optimize model performance. The dataset is downloaded using the Yahoo Finance API and contains columns for 'Open,' 'High,' 'Low,' 'Close,' and 'Volume' prices. It calculates moving averages, Bollinger Bands, Relative Strength Index (RSI), and Commodity Channel Index (CCI) as additional features for the classification.
\ No newline at end of file
diff --git a/Stock Price Direction Prediction(Tesla)/StockTradingForecasting.ipynb b/Stock Price Direction Prediction(Tesla)/StockTradingForecasting.ipynb
new file mode 100644
index 0000000000..1a57ea4b46
--- /dev/null
+++ b/Stock Price Direction Prediction(Tesla)/StockTradingForecasting.ipynb	
@@ -0,0 +1,1634 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Libraries"
+      ],
+      "metadata": {
+        "id": "nwVmgtgY9Nov"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -q yahoofinancials"
+      ],
+      "metadata": {
+        "id": "mADky-fy9cok"
+      },
+      "execution_count": 202,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install -q pandas_ta"
+      ],
+      "metadata": {
+        "id": "IcGd7hT2BCUb"
+      },
+      "execution_count": 203,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 223,
+      "metadata": {
+        "id": "njSour4jW7m6"
+      },
+      "outputs": [],
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import datetime\n",
+        "from datetime import date, time\n",
+        "import yfinance as yf\n",
+        "import pandas_ta as ta\n",
+        "from yahoofinancials import YahooFinancials\n",
+        "import seaborn as sns\n",
+        "from sklearn.model_selection import train_test_split, GridSearchCV\n",
+        "from sklearn.ensemble import RandomForestClassifier\n",
+        "from sklearn.metrics import confusion_matrix"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Dataset"
+      ],
+      "metadata": {
+        "id": "cTLIpKyb-SKz"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df = yf.download('TSLA',\n",
+        "                 start='2015-01-01',\n",
+        "                 end=date.today())"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0ux5LzSQ-Tea",
+        "outputId": "f0b385d7-e5d7-4535-ec7b-c51623d7dc71"
+      },
+      "execution_count": 205,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\r[*********************100%***********************]  1 of 1 completed\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 237
+        },
+        "id": "Dge8OP-E-xrl",
+        "outputId": "48aa1be4-660d-49f4-9fe7-7e0f4e21e593"
+      },
+      "execution_count": 206,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                 Open       High        Low      Close  Adj Close    Volume\n",
+              "Date                                                                       \n",
+              "2015-01-02  14.858000  14.883333  14.217333  14.620667  14.620667  71466000\n",
+              "2015-01-05  14.303333  14.433333  13.810667  14.006000  14.006000  80527500\n",
+              "2015-01-06  14.004000  14.280000  13.614000  14.085333  14.085333  93928500\n",
+              "2015-01-07  14.223333  14.318667  13.985333  14.063333  14.063333  44526000\n",
+              "2015-01-08  14.187333  14.253333  14.000667  14.041333  14.041333  51637500"
+            ],
+            "text/html": [
+              "\n",
+              "\n",
+              "  <div id=\"df-6e7647ac-9e60-4cce-a5f9-33f39778fd29\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
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+              "      <th>2015-01-02</th>\n",
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+              "      <td>14.883333</td>\n",
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+              "      <td>71466000</td>\n",
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+              "    padding: 0 0 0 0;\n",
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+              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: #174EA6;\n",
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+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
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+              "  [theme=dark] .colab-df-quickchart:hover {\n",
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+              "\n",
+              "        displayQuickchartButton(document);\n",
+              "      </script>\n",
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+              "    .colab-df-container {\n",
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+              "        const buttonEl =\n",
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+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-6e7647ac-9e60-4cce-a5f9-33f39778fd29');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
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+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
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+              "        }\n",
+              "      </script>\n",
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+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 206
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.tail()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 237
+        },
+        "id": "DVzd5rjf-2UK",
+        "outputId": "d822d42c-c4af-4b04-d8fa-990f09ea6f7e"
+      },
+      "execution_count": 207,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                  Open        High         Low       Close   Adj Close  \\\n",
+              "Date                                                                     \n",
+              "2023-07-31  267.480011  269.079987  263.779999  267.429993  267.429993   \n",
+              "2023-08-01  266.260010  266.470001  260.250000  261.070007  261.070007   \n",
+              "2023-08-02  255.570007  259.519989  250.490005  254.110001  254.110001   \n",
+              "2023-08-03  252.039993  260.489990  252.000000  259.320007  259.320007   \n",
+              "2023-08-04  260.970001  264.769989  253.110001  253.860001  253.860001   \n",
+              "\n",
+              "               Volume  \n",
+              "Date                   \n",
+              "2023-07-31   84582200  \n",
+              "2023-08-01   83166000  \n",
+              "2023-08-02  101752900  \n",
+              "2023-08-03   97569100  \n",
+              "2023-08-04   99242600  "
+            ],
+            "text/html": [
+              "\n",
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+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Open</th>\n",
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+              "      <th>Low</th>\n",
+              "      <th>Close</th>\n",
+              "      <th>Adj Close</th>\n",
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+              "      <th></th>\n",
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+              "      <th></th>\n",
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+              "  </thead>\n",
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+              "    <tr>\n",
+              "      <th>2023-07-31</th>\n",
+              "      <td>267.480011</td>\n",
+              "      <td>269.079987</td>\n",
+              "      <td>263.779999</td>\n",
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+              "      <td>84582200</td>\n",
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+              "    <tr>\n",
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+              "      <td>266.260010</td>\n",
+              "      <td>266.470001</td>\n",
+              "      <td>260.250000</td>\n",
+              "      <td>261.070007</td>\n",
+              "      <td>261.070007</td>\n",
+              "      <td>83166000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-08-02</th>\n",
+              "      <td>255.570007</td>\n",
+              "      <td>259.519989</td>\n",
+              "      <td>250.490005</td>\n",
+              "      <td>254.110001</td>\n",
+              "      <td>254.110001</td>\n",
+              "      <td>101752900</td>\n",
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+              "      <th>2023-08-03</th>\n",
+              "      <td>252.039993</td>\n",
+              "      <td>260.489990</td>\n",
+              "      <td>252.000000</td>\n",
+              "      <td>259.320007</td>\n",
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+              "      <td>97569100</td>\n",
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+              "      <td>264.769989</td>\n",
+              "      <td>253.110001</td>\n",
+              "      <td>253.860001</td>\n",
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+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80e4982a-f3ad-4c47-ac4d-1432dc2927a6')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-edd991fb-8594-4ce9-8ccd-0f6f160efdc3\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-edd991fb-8594-4ce9-8ccd-0f6f160efdc3')\"\n",
+              "              title=\"Suggest charts.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "    </div>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: #E8F0FE;\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: #1967D2;\n",
+              "    height: 32px;\n",
+              "    padding: 0 0 0 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: #E2EBFA;\n",
+              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: #174EA6;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "    background-color: #3B4455;\n",
+              "    fill: #D2E3FC;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart:hover {\n",
+              "    background-color: #434B5C;\n",
+              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "    fill: #FFFFFF;\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "    <script>\n",
+              "      async function quickchart(key) {\n",
+              "        const containerElement = document.querySelector('#' + key);\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      }\n",
+              "    </script>\n",
+              "\n",
+              "      <script>\n",
+              "\n",
+              "function displayQuickchartButton(domScope) {\n",
+              "  let quickchartButtonEl =\n",
+              "    domScope.querySelector('#df-edd991fb-8594-4ce9-8ccd-0f6f160efdc3 button.colab-df-quickchart');\n",
+              "  quickchartButtonEl.style.display =\n",
+              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "}\n",
+              "\n",
+              "        displayQuickchartButton(document);\n",
+              "      </script>\n",
+              "      <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-80e4982a-f3ad-4c47-ac4d-1432dc2927a6 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-80e4982a-f3ad-4c47-ac4d-1432dc2927a6');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 207
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.shape"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uGfeAO-G_DL8",
+        "outputId": "b877afa5-b08d-4380-dfbf-592eb0c99236"
+      },
+      "execution_count": 208,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(2162, 6)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 208
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.describe()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 300
+        },
+        "id": "6G8t-kgE_FiO",
+        "outputId": "e86889a0-8aa6-4285-9649-8ec93f75943d"
+      },
+      "execution_count": 209,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "              Open         High          Low        Close    Adj Close  \\\n",
+              "count  2162.000000  2162.000000  2162.000000  2162.000000  2162.000000   \n",
+              "mean     96.368932    98.533930    94.024005    96.335532    96.335532   \n",
+              "std     109.297503   111.788750   106.517746   109.181614   109.181614   \n",
+              "min       9.488000    10.331333     9.403333     9.578000     9.578000   \n",
+              "25%      16.507667    16.728334    16.317166    16.513000    16.513000   \n",
+              "50%      22.687333    23.123000    22.307666    22.711333    22.711333   \n",
+              "75%     197.227505   200.780006   191.994999   196.764999   196.764999   \n",
+              "max     411.470001   414.496674   405.666656   409.970001   409.970001   \n",
+              "\n",
+              "             Volume  \n",
+              "count  2.162000e+03  \n",
+              "mean   1.140508e+08  \n",
+              "std    7.873792e+07  \n",
+              "min    1.062000e+07  \n",
+              "25%    6.495788e+07  \n",
+              "50%    9.132640e+07  \n",
+              "75%    1.347308e+08  \n",
+              "max    9.140820e+08  "
+            ],
+            "text/html": [
+              "\n",
+              "\n",
+              "  <div id=\"df-1408af8e-3d7b-48ef-a81c-0344838046df\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <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>Open</th>\n",
+              "      <th>High</th>\n",
+              "      <th>Low</th>\n",
+              "      <th>Close</th>\n",
+              "      <th>Adj Close</th>\n",
+              "      <th>Volume</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>2162.000000</td>\n",
+              "      <td>2162.000000</td>\n",
+              "      <td>2162.000000</td>\n",
+              "      <td>2162.000000</td>\n",
+              "      <td>2162.000000</td>\n",
+              "      <td>2.162000e+03</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>96.368932</td>\n",
+              "      <td>98.533930</td>\n",
+              "      <td>94.024005</td>\n",
+              "      <td>96.335532</td>\n",
+              "      <td>96.335532</td>\n",
+              "      <td>1.140508e+08</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>109.297503</td>\n",
+              "      <td>111.788750</td>\n",
+              "      <td>106.517746</td>\n",
+              "      <td>109.181614</td>\n",
+              "      <td>109.181614</td>\n",
+              "      <td>7.873792e+07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>9.488000</td>\n",
+              "      <td>10.331333</td>\n",
+              "      <td>9.403333</td>\n",
+              "      <td>9.578000</td>\n",
+              "      <td>9.578000</td>\n",
+              "      <td>1.062000e+07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>16.507667</td>\n",
+              "      <td>16.728334</td>\n",
+              "      <td>16.317166</td>\n",
+              "      <td>16.513000</td>\n",
+              "      <td>16.513000</td>\n",
+              "      <td>6.495788e+07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>22.687333</td>\n",
+              "      <td>23.123000</td>\n",
+              "      <td>22.307666</td>\n",
+              "      <td>22.711333</td>\n",
+              "      <td>22.711333</td>\n",
+              "      <td>9.132640e+07</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>197.227505</td>\n",
+              "      <td>200.780006</td>\n",
+              "      <td>191.994999</td>\n",
+              "      <td>196.764999</td>\n",
+              "      <td>196.764999</td>\n",
+              "      <td>1.347308e+08</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>411.470001</td>\n",
+              "      <td>414.496674</td>\n",
+              "      <td>405.666656</td>\n",
+              "      <td>409.970001</td>\n",
+              "      <td>409.970001</td>\n",
+              "      <td>9.140820e+08</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1408af8e-3d7b-48ef-a81c-0344838046df')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-024aaafa-6439-4ddc-8715-3519d6f69a2f\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-024aaafa-6439-4ddc-8715-3519d6f69a2f')\"\n",
+              "              title=\"Suggest charts.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "    </div>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: #E8F0FE;\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: #1967D2;\n",
+              "    height: 32px;\n",
+              "    padding: 0 0 0 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: #E2EBFA;\n",
+              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: #174EA6;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "    background-color: #3B4455;\n",
+              "    fill: #D2E3FC;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart:hover {\n",
+              "    background-color: #434B5C;\n",
+              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "    fill: #FFFFFF;\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "    <script>\n",
+              "      async function quickchart(key) {\n",
+              "        const containerElement = document.querySelector('#' + key);\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      }\n",
+              "    </script>\n",
+              "\n",
+              "      <script>\n",
+              "\n",
+              "function displayQuickchartButton(domScope) {\n",
+              "  let quickchartButtonEl =\n",
+              "    domScope.querySelector('#df-024aaafa-6439-4ddc-8715-3519d6f69a2f button.colab-df-quickchart');\n",
+              "  quickchartButtonEl.style.display =\n",
+              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "}\n",
+              "\n",
+              "        displayQuickchartButton(document);\n",
+              "      </script>\n",
+              "      <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-1408af8e-3d7b-48ef-a81c-0344838046df button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-1408af8e-3d7b-48ef-a81c-0344838046df');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 209
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Analysis"
+      ],
+      "metadata": {
+        "id": "KhfPmTqv_iiG"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.lineplot(x=df.index, y=df['Close'], label='Closing Price')\n",
+        "plt.title('Tesla Inc. (TSLA) Closing Price Over Time')\n",
+        "plt.xlabel('Date')\n",
+        "plt.ylabel('Closing Price')\n",
+        "plt.legend()\n",
+        "plt.grid()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "VtMvXTdr_jqf",
+        "outputId": "ef09454c-f37d-4d66-b8ab-e2e01220e490"
+      },
+      "execution_count": 210,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['MA50'] = df['Close'].rolling(window=50).mean()\n",
+        "df['MA200'] = df['Close'].rolling(window=200).mean()\n",
+        "sns.lineplot(x=df.index, y=df['Close'], color='blue', label='Closing Price')\n",
+        "sns.lineplot(x=df.index, y=df['MA50'], color='orange', label='50-day Moving Average')\n",
+        "sns.lineplot(x=df.index, y=df['MA200'], color='red', label='200-day Moving Average')\n",
+        "plt.title('Tesla Inc. (TSLA) Moving Averages')\n",
+        "plt.xlabel('Date')\n",
+        "plt.ylabel('Price')\n",
+        "plt.legend()\n",
+        "plt.grid()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "JK5HQYzZAMCW",
+        "outputId": "bd039e0d-db20-4610-c1fc-dd4b57336961"
+      },
+      "execution_count": 211,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "daily_returns = df['Close'].pct_change()\n",
+        "sns.lineplot(x=df.index, y=daily_returns, color='green', label='Daily Returns')\n",
+        "plt.title('Tesla Inc. (TSLA) Daily Returns')\n",
+        "plt.xlabel('Date')\n",
+        "plt.ylabel('Daily Returns')\n",
+        "plt.legend()\n",
+        "plt.grid()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "-eN5iJEp__LT",
+        "outputId": "03889859-3d4e-4ae1-af4d-981fc4c76a57"
+      },
+      "execution_count": 212,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.ta.sma(length=20, append=True)\n",
+        "df.ta.sma(length=50, append=True)\n",
+        "df.ta.sma(length=200, append=True)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NIQ07pvGCx-n",
+        "outputId": "f1ca6981-3740-4a07-e540-d0a86d64585f"
+      },
+      "execution_count": 213,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Date\n",
+              "2015-01-02          NaN\n",
+              "2015-01-05          NaN\n",
+              "2015-01-06          NaN\n",
+              "2015-01-07          NaN\n",
+              "2015-01-08          NaN\n",
+              "                ...    \n",
+              "2023-07-31    194.89340\n",
+              "2023-08-01    195.11255\n",
+              "2023-08-02    195.27450\n",
+              "2023-08-03    195.54615\n",
+              "2023-08-04    195.71870\n",
+              "Name: SMA_200, Length: 2162, dtype: float64"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 213
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.ta.bbands(length=20, append=True)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 455
+        },
+        "id": "xjOTWrVgDADI",
+        "outputId": "d03266a7-d839-4d55-ccd6-26d4cc416f2d"
+      },
+      "execution_count": 214,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "            BBL_20_2.0  BBM_20_2.0  BBU_20_2.0  BBB_20_2.0  BBP_20_2.0\n",
+              "Date                                                                  \n",
+              "2015-01-02         NaN         NaN         NaN         NaN         NaN\n",
+              "2015-01-05         NaN         NaN         NaN         NaN         NaN\n",
+              "2015-01-06         NaN         NaN         NaN         NaN         NaN\n",
+              "2015-01-07         NaN         NaN         NaN         NaN         NaN\n",
+              "2015-01-08         NaN         NaN         NaN         NaN         NaN\n",
+              "...                ...         ...         ...         ...         ...\n",
+              "2023-07-31  252.984557  273.505500  294.026443   15.005872    0.351968\n",
+              "2023-08-01  251.578785  272.568000  293.557215   15.401086    0.226098\n",
+              "2023-08-02  249.218048  271.149500  293.080951   16.176649    0.111528\n",
+              "2023-08-03  247.923368  270.288499  292.653631   16.549081    0.254786\n",
+              "2023-08-04  245.882305  269.260000  292.637694   17.364402    0.170626\n",
+              "\n",
+              "[2162 rows x 5 columns]"
+            ],
+            "text/html": [
+              "\n",
+              "\n",
+              "  <div id=\"df-8b50f013-ab86-4ea8-8166-675f6c78aa68\">\n",
+              "    <div class=\"colab-df-container\">\n",
+              "      <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>BBL_20_2.0</th>\n",
+              "      <th>BBM_20_2.0</th>\n",
+              "      <th>BBU_20_2.0</th>\n",
+              "      <th>BBB_20_2.0</th>\n",
+              "      <th>BBP_20_2.0</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>Date</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2015-01-02</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2015-01-05</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2015-01-06</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2015-01-07</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2015-01-08</th>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-07-31</th>\n",
+              "      <td>252.984557</td>\n",
+              "      <td>273.505500</td>\n",
+              "      <td>294.026443</td>\n",
+              "      <td>15.005872</td>\n",
+              "      <td>0.351968</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-08-01</th>\n",
+              "      <td>251.578785</td>\n",
+              "      <td>272.568000</td>\n",
+              "      <td>293.557215</td>\n",
+              "      <td>15.401086</td>\n",
+              "      <td>0.226098</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-08-02</th>\n",
+              "      <td>249.218048</td>\n",
+              "      <td>271.149500</td>\n",
+              "      <td>293.080951</td>\n",
+              "      <td>16.176649</td>\n",
+              "      <td>0.111528</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-08-03</th>\n",
+              "      <td>247.923368</td>\n",
+              "      <td>270.288499</td>\n",
+              "      <td>292.653631</td>\n",
+              "      <td>16.549081</td>\n",
+              "      <td>0.254786</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2023-08-04</th>\n",
+              "      <td>245.882305</td>\n",
+              "      <td>269.260000</td>\n",
+              "      <td>292.637694</td>\n",
+              "      <td>17.364402</td>\n",
+              "      <td>0.170626</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>2162 rows × 5 columns</p>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b50f013-ab86-4ea8-8166-675f6c78aa68')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </svg>\n",
+              "      </button>\n",
+              "\n",
+              "\n",
+              "\n",
+              "    <div id=\"df-e1b869b3-631e-41bd-8f1a-f56899aef25f\">\n",
+              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e1b869b3-631e-41bd-8f1a-f56899aef25f')\"\n",
+              "              title=\"Suggest charts.\"\n",
+              "              style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "      </button>\n",
+              "    </div>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: #E8F0FE;\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: #1967D2;\n",
+              "    height: 32px;\n",
+              "    padding: 0 0 0 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: #E2EBFA;\n",
+              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: #174EA6;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "    background-color: #3B4455;\n",
+              "    fill: #D2E3FC;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart:hover {\n",
+              "    background-color: #434B5C;\n",
+              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "    fill: #FFFFFF;\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "    <script>\n",
+              "      async function quickchart(key) {\n",
+              "        const containerElement = document.querySelector('#' + key);\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      }\n",
+              "    </script>\n",
+              "\n",
+              "      <script>\n",
+              "\n",
+              "function displayQuickchartButton(domScope) {\n",
+              "  let quickchartButtonEl =\n",
+              "    domScope.querySelector('#df-e1b869b3-631e-41bd-8f1a-f56899aef25f button.colab-df-quickchart');\n",
+              "  quickchartButtonEl.style.display =\n",
+              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "}\n",
+              "\n",
+              "        displayQuickchartButton(document);\n",
+              "      </script>\n",
+              "      <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      flex-wrap:wrap;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-8b50f013-ab86-4ea8-8166-675f6c78aa68 button.colab-df-convert');\n",
+              "        buttonEl.style.display =\n",
+              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "        async function convertToInteractive(key) {\n",
+              "          const element = document.querySelector('#df-8b50f013-ab86-4ea8-8166-675f6c78aa68');\n",
+              "          const dataTable =\n",
+              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                     [key], {});\n",
+              "          if (!dataTable) return;\n",
+              "\n",
+              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "            + ' to learn more about interactive tables.';\n",
+              "          element.innerHTML = '';\n",
+              "          dataTable['output_type'] = 'display_data';\n",
+              "          await google.colab.output.renderOutput(dataTable, element);\n",
+              "          const docLink = document.createElement('div');\n",
+              "          docLink.innerHTML = docLinkHtml;\n",
+              "          element.appendChild(docLink);\n",
+              "        }\n",
+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 214
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['RSI(2)'] = ta.rsi(df['Close'], timeperiod=2)\n",
+        "df['RSI(7)'] = ta.rsi(df['Close'], timeperiod=7)\n",
+        "df['RSI(14)'] = ta.rsi(df['Close'], timeperiod=14)\n",
+        "df['RSI(10)'] = ta.rsi(df['Close'], timeperiod=10)"
+      ],
+      "metadata": {
+        "id": "LIfQ_Z6kBb-R"
+      },
+      "execution_count": 215,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['CCI(30)'] = ta.cci(df['High'], df['Low'], df['Close'], timeperiod=30)\n",
+        "df['CCI(50)'] = ta.cci(df['High'], df['Low'], df['Close'], timeperiod=50)\n",
+        "df['CCI(100)'] = ta.cci(df['High'], df['Low'], df['Close'], timeperiod=100)"
+      ],
+      "metadata": {
+        "id": "HDlReMfQCClx"
+      },
+      "execution_count": 216,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "sns.lineplot(x=df.index, y=df['RSI(2)'], label='RSI(2)', color='blue')\n",
+        "sns.lineplot(x=df.index, y=df['CCI(100)'], label='CCI(100)', color='green')\n",
+        "plt.title('RSI(2) and CCI(100) for Tesla Inc. (TSLA)')\n",
+        "plt.xlabel('Date')\n",
+        "plt.ylabel('Indicator Value')\n",
+        "plt.legend()\n",
+        "plt.grid()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "ovSO1fayCPtD",
+        "outputId": "f18af00a-d4d9-4586-ba63-2184a37ac6dd"
+      },
+      "execution_count": 217,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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YO3Ysfv75Z01BKzs7G8888wzq1q2LyMhI1K5dG02bNgUg77NGaNSokehvTmjg+jfnX9m+fXufyyDB+umrNGzYMKxevRq5ubnYuHEjJk2ahPPnz+O2227j21ovLpcLS5YswYABA3D27FmcOnUKp06dQo8ePZCZmYm1a9cq1r8yrky+3qGhGCgVTvfu3Xlfmdtvvx29e/fG/fffj+PHjytqPWrWrIlRo0Zh1KhR6N+/PzZs2IDz58/LnNOF6Z1OJwoKChS1MdOnT8fnn3+ODz74AOPGjVOsb05ODqKioogTNofL5cKQIUOQnZ2NadOmoXXr1oiOjsalS5cwYcIE2STnq1+TEVq3bo19+/bBbrdrTvScw/vBgwdx++23+1SenjbXol69ekStZHp6OgAgMTGRTyc8Lk3LpROi5zkGikCV4Xa7ceONN2L27NnE8w0bNuTL27hxI9atW4e///4bq1atwtKlSzFw4ECsWbNGsb/de++92Lp1K1588UV06tQJMTExcLvduPXWW/0KAqtUnr/CjxI1a9YEANHHiT9ERUWhT58+6NOnD2rVqoXp06dj5cqVuv0dAeDff/9Feno6lixZgiVLlsjOL168GEOHDhUd4+pP8v2khDZUc0UJKcxmM2bMmIHLly9j3rx5uq7hBDPSxMrBCQtnz54lnp8/fz7eeustTJ06FdOmTVMt7+zZs2jTpo1qmoMHD+LEiROYNWsWpk2bhtGjR2Pw4MHESV4vjRs3Rnp6uiwo5vHjx3VdP3LkSJSUlOC3337TTNu7d29Ur14dP/30E9FcoQetNtdDp06dcOLECd5MybFjxw7+PODReFgsFuzevVuUzm63Y9++fXw6IXqeoxKcEC9te7vdjrNnzyoK+f7SvHlzZGdnY9CgQRg8eLDsn1CTZjKZMGjQIMyePRtHjhzBe++9h3///Zc3HUrJycnB2rVr8fLLL2P69Om44447MGTIEDRr1iwo9yK9LwA4dOhQQPILRN9TQs94Q2Lx4sWoU6cOfvnlF9m/++67D8uWLZOZr7n6+9pPKRUHFa4oIUf//v3RvXt3fPrpp7z5JyMjA0eOHJGltdvtWLt2LUwmk2qAx169egGAbPIFPNHCp0yZggceeEBRIyBkz549qoEzAe+XuvDLnGVZzJkzRzN/JZKSkuB0OvHFF1/wx1wul6JvmJQnn3wS9erVw/PPP48TJ07Izl+5cgXvvvsuAM+X+rRp03D06FFMmzaNqGH44YcfsHPnTsXy1NpcL3fffTdcLpdo1aTNZsO3336LHj168Jqa+Ph4DB48GD/88IPIlLlo0SIUFhbinnvukeWt5zkqMXjwYISFheGzzz4Ttc0333yDvLw8jBgxwqd8tbj33ntx6dIlLFiwQHaupKQERUVFADzmPSmcgKm07Q+pzwKeFZPBZujQoYiNjcWMGTP4d55DWJ+srCwcO3ZM00+ufv36aNiwoV99j2SmA8BvSaPXHA94ns3vv/+O2267DXfffbfs3+TJk1FQUIAVK1aIrktNTUV8fDzatWvn831QKgZqFqSEJC+++CLuueceLFy4EE8++SQuXryI7t27Y+DAgRg0aBASEhJw5coV/PTTT9i/fz+mTp2qqjpv1qwZ2rdvj3/++QePPPIIf3znzp0YP348atasiUGDBsliztx8882iL/fU1FRkZ2dj9OjRqvVv3bo1mjdvjhdeeAGXLl1CXFwcfvvtN7/MFCNHjsQtt9yCl19+GefOnUPbtm3x+++/6/aFqV69OpYtW4akpCR06tRJFKF9z549+Omnn3iBCPA8g8OHD2PWrFlYt24d7r77biQkJCAjIwPLly/Hzp07VR17ldocADZu3IiNGzcCAK5evYqioiJesOvbty/69u0LAOjRowfuuecevPLKK7hy5QpatGiB7777DufOncM333wjyvO9997DzTffjH79+uGJJ57AxYsXMWvWLAwdOhS33nqrKK3e56hE7dq18corr2D69Om49dZbMWrUKBw/fhyff/45unXrhgcffNCnfLUYN24cfv75Zzz55JNYt24dbrnlFrhcLhw7dgw///wzVq9eja5du+Ltt9/Gxo0bMWLECDRu3BhXrlzB559/jgYNGoii2guJi4tD3759MXPmTDgcDtSvXx9r1qwJivaHVPYnn3yCxx57DN26dcP999+P6tWrY//+/SguLsZ3330HAJg3bx6mT5+OdevWqW6ZBACjR4/GsmXLwLKsTz5Lo0ePRtOmTTFy5Eg0b94cRUVF+Oeff/Dnn3+iW7duGDlypCj97t27+T4spH///rh06RIKCgowatQoYlk9e/ZE7dq1sXjxYlFIjZSUFIwcOZL6XFVGKmSNIoXCKkdoZ1mWdblcbPPmzdnmzZuzTqeTzc/PZ+fMmcMOGzaMbdCgAWu1WtnY2Fi2V69e7IIFC0TLtZWihc+ePZuNiYkRLTfn6qD0TxreYNq0aZpRnzmOHDnCDh48mI2JiWFr1arFPv744+z+/ftl+T700ENsdHS07HouBICQa9eusePGjWPj4uLY+Ph4dty4cezevXsNRdq+fPky++yzz7KtWrViIyIi2KioKLZLly7se++9J4puzvHrr7+yQ4cOZWvUqMFaLBa2Xr167JgxY9j169fzaYy0ufDeSP/efPNNUdqSkhL2hRdeYBMSEtjw8HC2W7du7KpVq4j3tmnTJvbmm29mIyIi2Nq1a7OTJk1i8/PzZemMPEdSKAaOefPmsa1bt2atVitbt25dduLEiWxOTo4oTb9+/dh27dpplkOCFKHdbrezH374IduuXTs2PDycrV69OtulSxd2+vTp/PNbu3YtO3r0aDYxMZENCwtjExMT2fvuu489ceIEnw8pFMPFixfZO+64g61WrRobHx/P3nPPPezly5eJz0WKWigG6TvO9Zd169aJjq9YsYK9+eab2cjISDYuLo7t3r07+9NPP/HnuWchvY7Enj17WACysBVC1EIx/PTTT+zYsWPZ5s2bs5GRkWxERATbtm1b9tVXX5X1KbUx5J133mFHjhzJRkREqEbmnzBhAmu1WtmsrCyWZVn26NGjfKgaSuWDYVka+pVyfZCXl4dmzZph5syZePTRRw1fb7PZ0KRJE7z88st45plnglDDqoe/bR4M6HO8fhg0aBASExNlewpWBqZOnYqNGzciNTWVaq4qIdTninLdEB8fj5deegkfffSRTyufvv32W1itVlk8Kooy/rZ5MKDP8frh/fffx9KlS2WhMUKda9eu4euvv8a7775LBatKCtVcUSgUCoVCoQQQqrmiUCgUCoVCCSBUuKJQKBQKhUIJIFS4olAoFAqFQgkgVLiiUCgUCoVCCSA0iKhB3G43Ll++jNjYWLqKg0KhUCiUSgLLsigoKEBiYiJMpuDqlqhwZZDLly/zW25QKBQKhUKpXFy4cAENGjQIahlUuDJIbGwsAM/DiYuL8zs/h8OBNWvWYOjQobBarX7nFwrQewp9qtr9APSeKgv0nioHVe2eHA4Hli9fjscee4yfx4MJFa4MwpkC4+LiAiZcRUVFIS4urkp0YIDeU2Wgqt0PQO+pskDvqXJQ1e6Jux8A5eLSQx3aKRQKhUKhUAIIFa4oFAqFQqFQAggVrigUCoVCoVACCPW5olAoFApFAbfbDbvdrprG4XDAYrGgtLQULpernGoWXCrrPYWFhQU9zIIeqHBFoVAoFAoBu92Os2fPwu12q6ZjWRYJCQm4cOFClYl/WFnvyWQyoWnTpggLC6vQelDhikKhUCgUCSzLIj09HWazGQ0bNlTVhrjdbhQWFiImJiYktCaBoDLeExfkOz09HY0aNapQoZAKVxQKhUKhSHA6nSguLkZiYiK/hF8JznQYERFRaQQRLSrrPdWuXRuXL1+G0+ms0BASlafFKBQKhUIpJzg/o4o2L1GMwT2vivYTo8IVhUKhUCgKVCZ/I0roPC8qXFEoFAqFQqEEECpcUSgUCoVC0WTcuHF4//33dafPyspCnTp1cPHixSDWKjShwhWFQqFQKFWECRMmgGEYMAwDq9WKpk2b4qWXXkJpaSmfZsOGDRg4cCBq1KiBqKgotGzZEg899BAfz2v9+vUwm83Iy8vjr9m/fz+Sk5MxZcoUAJ44WNOmTcONN96I6OhoJCYmYvz48bh8+TJ/Ta1atTB+/Hi8+eab5XT3oQMVrigUCuU6w+FywOFyVHQ1KEHi1ltvRXp6Os6cOYNPPvkEX331FS/gHDlyBLfeeiu6du2KjRs34uDBg5g7dy7CwsJUncDnzp2Le+65BzExMQCA4uJi7NmzB6+//jr27NmD33//HcePH8eoUaNE1z388MNYvHgxsrOzg3fDIQgNxUChUCjXEW7WjaZzmsLusuPy85dhMdFpoKoRHh6OhIQEAEDDhg0xePBgpKSk4MMPP8SaNWuQkJCAmTNn8umbN2+OW2+9VTE/l8uFX3/9FYsXL+aPxcfHIyUlRZRu3rx56N69O9LS0tCoUSMAQLt27ZCYmIhly5bh0UcfDeRthjT0raJQKJTriAJbAS4VXAIApBeko2F8wwquUeWAZYHiYvI5txsoKgLMZiAYIaGiogBfF8EdOnQIW7duRePGjQEACQkJSE9Px8aNG9G3b19deRw4cAB5eXno2rWrarq8vDwwDINq1aqJjnfv3h2bNm2iwhWFQqFQKBQvxcVAmUWMgAlAtaCVXVgIREfrT//XX38hJiYGTqcTNpsNJpMJ8+bNAwDcc889WL16Nfr164eEhAT07NkTgwYNwvjx4xEXF0fM7/z58zCbzahTp45imaWlpZg2bRruu+8+WT6JiYnYu3ev/huoAlCfKwqFQqFQqhADBgzAvn37sGPHDjz00EN4+OGHcddddwEAzGYzvv32W1y8eBEzZ85E/fr18f7776Ndu3ZIT08n5ldSUoLw8HDFGFIOhwP33nsvWJbFF198ITsfGRmJYiW1XxWFClcUCoVyHcGCregqVEqiojwaJNK//Hw3Ll7MRX6+WzGNP/80dt+RER0djRYtWqBjx4743//+hx07duCbb74Rpalfvz7GjRuHefPm4fDhwygtLcWXX35JzK9WrVooLi7mVxMK4QSr8+fPIyUlhaj9ys7ORu3atY3dRCWHmgUpFArlOiVUollXBhhG2TTndgMul+d8qG3DZzKZ8J///AfPPfcc7r//fkRGRsrSVK9eHfXq1UNRURExj06dOgHwrDTkfgNewerkyZNYt24datasSbz+0KFD6N+/v7+3UqkIsW5AoVAolPKCZakW63rgnnvugdlsxvz58/HVV19h4sSJWLNmDU6fPo3Dhw9j2rRpOHz4MEaOHEm8vnbt2ujcuTM2b97MH3M4HLj77ruxe/duLF68GC6XCxkZGcjIyBBpuIqLi5GamoqhQ4cG/T5DCSpcUSgUynUEA6qtut6wWCyYPHkyZs6cifbt26OwsBBPPvkk2rVrh379+mH79u1Yvnw5+vXrp5jHY489JgrFcOnSJaxYsQIXL15Ep06dUK9ePf7f1q1b+XR//PEHGjVqhD59+gT1HkMNahakUCiU6wjqc1W1WbhwIfH4yy+/jJdffhkAcMstt6jm0b9/f7hcLuTn5/PHJkyYgBkzZmDbtm3o1asXmjRpokvzOWfOHLzxxhv6b6CKQDVXFAqFcp1Cfa4oeomMjMT333+PrKws3ddkZWXhzjvvxH333RfEmoUmVHNFoVAo1ynU54piBKNO6bVq1cJLL70UnMqEOFRzRaFQKBQKhRJAqHBFoVAo1xFCbRU1C1IowYEKVxQKhXIdQR3aKZTgQ4UrCoVCKWfe3vA2XljzQoWUTf2sKJTgQx3aKRQKpRxxuV14c/2bAIDJ3SejSbUmFVshCoUScKjmikKhUMoRoVmuxFFSoeVTKJTgQIUrCoVCKUeEEdIrQtChZkEKJfhQ4YpCoVAqCDfrLvcyqeaK4i+vv/46nnjiiXIvd9WqVejUqRPc7vJ/b4xChSsKhUIpR4TCTUVokajm6vogIyMDTz/9NJo1a4bw8HA0bNgQI0eOxNq1a/k0e/fuxT333IO6desiIiICLVu2xOOPP44TJ04AANLS0mA2m7Fv3z5RvnPmzMGrr77KH9u4cSNGjhyJxMREMAyD5cuXy+rDsizeeOMN1KtXD5GRkRg8eDBOnjwpSpOdnY0HHngAcXFxqFatGh599FEUFhby52+99VZYrVbRHoehChWuKBQKpYKoaC0SFbSqJufOnUOXLl3w77//4qOPPsLBgwexatUqDBgwAJMmTQIA/PXXX+jZsydsNhsWL16Mo0eP4ocffkB8fDxef/11xby//vpr3HzzzWjcuDF/rKioCB07dsT8+fMVr5s5cyY+++wzfPnll9ixYweio6MxbNgwlJaW8mkeeOABHD58GCkpKfjrr7+wceNGmYZswoQJ+Oyzz3xtmnKDrhakUCiUCqJCNFdCzRk1EVZJnnrqKTAMg507dyI6Opo/3q5dOzzyyCMoLi7Gww8/jKSkJCxbtow/37RpU/To0QO5ubmKeS9ZsgQTJ04UHRs+fDiGDx+ueA3Lsvj000/x2muvYfTo0QCA77//HnXr1sXy5csxduxYHD16FKtWrcKuXbvQtWtXAMDcuXORlJSEjz/+GImJiQCAkSNHYvLkyTh9+jSaN29uuG3KCypcUSgUSgVRIT5XVFvlEyzLothRTDzndrtR5CiC2W6GyRR4g1CUNUp3NP3s7GysWrUK7733nkiw4qhWrRqWLVuGrKwsxX3/qlWrRvRrys7OxpEjR3jhRy9nz55FRkYGBg8ezB+Lj49Hjx49sG3bNowdOxbbtm1DtWrVRHkPHjwYJpMJO3bswB133AEAaNSoEerWrYtNmzZR4YpCoVAoHoTCTYWsFqxgn6/KSrGjGDEzYiqk7MJXChEdJheUSJw6dQosy6J169aKaThfJ7U0JNLS0sCyLK9F0ktGRgYAoG7duqLjdevW5c9lZGSgTp06ovMWiwU1atTg03AkJibi/PnzhupQ3lQan6svvvgCHTp0QFxcHOLi4tCrVy+sXLmSP19aWopJkyahZs2aiImJwV133YXMzExRHmlpaRgxYgSioqJQp04dvPjii3A6neV9KxQKhQKg4h3aqVmw6qGnT/na70pKPHHZIiIifLo+UERGRqK4mKxFDBUqjeaqQYMG+OCDD9CyZUuwLIvvvvsOo0ePxt69e9GuXTs8++yz+Pvvv/HLL78gPj4ekydPxp133oktW7YAAFwuF0aMGIGEhARs3boV6enpGD9+PKxWK95///0KvjsKhXI9UtHCDdVc6SfKGoXCVwqJ59xuN/IL8hEXGxc0s6BeWrZsCYZhcOzYMcU0rVq1AgAcO3YMvXr10p13rVq1AAA5OTmoXbu27usSEhIAAJmZmahXrx5/PDMzE506deLTXLlyRXSd0+lEdnY2fz1Hdna2ofIrgkqjuRo5ciSSkpLQsmVLtGrVCu+99x5iYmKwfft25OXl4ZtvvsHs2bMxcOBAdOnSBd9++y22bt2K7du3AwDWrFmDI0eO4IcffkCnTp0wfPhwvPPOO5g/fz7sdnsF3x2FQrkeoXGuKg8MwyA6LFr5n1XlnJ//9PpbAUCNGjUwbNgwzJ8/H0VFRbLzubm5GDp0KGrVqoWZM2cS81ByaG/evDni4uJw5MgR3fUBPI7yCQkJojAQ+fn52LFjBy/c9erVC7m5uUhNTeXT/Pvvv3C73ejRowd/rLS0FKdPn8ZNN91kqA7lTaXRXAlxuVz45ZdfUFRUhF69eiE1NRUOh0PkLNe6dWs0atQI27ZtQ8+ePbFt2zbceOONIpvvsGHDMHHiRBw+fFjxQdlsNthsNv7v/Px8AIDD4YDD4fD7Xrg8ApFXqEDvKfSpavcDVJ57sru8H3Na40gw7snusIt+l3d7VZbn5HA4wLIs3G63ZtBKTgPIpa9o5s6diz59+qB79+5466230KFDBzidTvzzzz/48ssvcfjwYfz3v//FmDFjMHLkSDz99NNo0aIFsrKy8MsvvyAtLQ0//vgjn5+wDQYNGoRNmzZh1KhR/PnCwkKcOnWK//vMmTPYs2cPatSogUaNGgEAnnnmGbz77rto3rw5mjZtijfeeAOJiYkYNWoU3G43brjhBgwbNgyPP/44Pv/8czgcDkyePBljxoxBQkICX/7WrVsRHh6OHj16ENva7XaDZVk4HA6YzWb+eHn3t0olXB08eBC9evVCaWkpYmJisGzZMrRt2xb79u1DWFgYqlWrJkovdZYjOdNx55SYMWMGpk+fLju+Zs0aREXpV9VqkZKSErC8QgV6T6FPVbsfIPTvyeH2DvJbtm5BVnSW5jWBvKer9qv873Xr1+FYuLL5KJiE+nOyWCxISEhAYWGhbutGQUFBkGulj1q1amHdunWYNWsWnn/+eWRmZqJWrVro2LEjPvroI+Tn52PAgAFYvXo1PvnkEzzwwAMoKChA/fr10adPH0ybNk10L0VFRbxi4b777sPUqVPx6quv8ibQzZs3Y+TIkXz6559/nk/7+eefAwD+7//+D9nZ2fi///s/5OXloWfPnvj5559ht9v59v3iiy/w4osvYsiQIWAYBqNGjcIHH3zAlw14QjjcfffdcDqdouMcdrsdJSUl2LhxY4X6VDNsJTK62+12pKWlIS8vD7/++iu+/vprbNiwAfv27cPDDz8s0jABQPfu3TFgwAB8+OGHeOKJJ3D+/HmsXr2aP19cXIzo6GgkJycrxuggaa4aNmyIrKwsxMXF+X1PDocDKSkpGDJkCKxWq9/5hQL0nkKfqnY/QOW5J7vLjpgPPavONo7fiJ4NeiqmDcY9peWlocX8FgCAoxOPonn18l3OXlmeU2lpKS5cuIAmTZpoOnCzLIuCggLExsYaMuGFMkr3xLIsevXqhWeeeQb33XdfudYpKysLbdq0wc6dO9G0aVNimtLSUpw7dw4NGzYUPTeHw4E//vgD999/P/Ly8gIyf6tRqTRXYWFhaNHCMyh06dIFu3btwpw5czBmzBjY7Xbk5uaKtFeZmZm8I1xCQgJ27twpyo9bTSh1lhMSHh6O8PBw2XGr1RrQgSHQ+YUC9J5Cn6p2P0Do3xNr8n7PmswmXXUN5D1ZLBbR74pqq1B/Ti6XCwzDwGQyaTqpc+YpLn1VQO2e/vvf/+LgwYPlfq9paWn4/PPPVeNbmUwmMAxT4f2rUvcCt9sNm82GLl26wGq1ipzljh8/jrS0NJGz3MGDB0WrEVJSUhAXF4e2bduWe90pFAqFxrmiVEY6deqEcePGlXu5Xbt2xZgxY8q9XF+oNJqrV155BcOHD0ejRo1QUFCAH3/8EevXr8fq1asRHx+PRx99FM899xxq1KiBuLg4PP300+jVqxd69vSo3IcOHYq2bdti3LhxmDlzJjIyMvDaa69h0qRJRM0UhUKhBANRnCka5yoovLvxXaw7tw7J9ycj3ELHd0r5U2mEqytXrmD8+PFIT09HfHw8OnTogNWrV2PIkCEAgE8++QQmkwl33XUXbDYbhg0bxjvSAYDZbMZff/2FiRMnolevXoiOjsZDDz2Et99+u6JuiUKhXOdUtOaqqvL6Os/Gw0sOLcFDnR6q4NpQrkcqjXD1zTffqJ6PiIjA/PnzVXflbty4MZKTkwNdNQqFQvGJiohzJaSqmwVLnaV+51HV26iqESrPq1L7XFEoFEplhpoFQxcuRhINMl254J6XMMZVRVBpNFcUCoVSFRA5lFOzYFDxJyyCxWJBVFQUrl69CqvVqroyzu12w263o7S0tEqtFqxs9+R2u3H16lVERUWJVsVWBFS4olAolAqiwjVXIWJCCRb+3B/DMKhXrx7Onj2L8+fPa5ZTUlKCyMjIKhXnqjLek8lkQqNGjSq8zlS4olAolAqiovcW5H6XOEpw+OphdKnXpcInpVAiLCwMLVu21DQNOhwObNy4EX379g3p2F1GqKz3FBYWFhKaNipcUSjXCVvStuDZ1c9i7vC56Fy3c0VXh4LQcWi/fentWHN6DRaMXIDHOj9WoXUKJIEQFE0mk2aEdrPZDKfTiYiIiEoliKhRFe+pPKl48Y5CoZQLvb/tjV2Xd6HPt30quirXNRXtUE4yla05vQYA8Mn2T8q7OhRKlYQKVxTKdYZw42BKxRIqZkGOIntReVeHQqmSUOGKQqFQKgiX21XuZao5tBfaC8u7OhRKlYQKVxQKhVJBuNjgCVcsyxJNgGqmSCpcUSiBgQpXFAqFUo4IhZtgmgVHLxmNjl92hMOlbAaWClo2ly1o9aFQrieocEWhUCgVhC9mwdzSXF2+UX+e+BMHrxzErsu7RMevpzhXDLyrBUudpUhanIS5O+ZWYI0o1wtUuKJQKJQKwqjmqsBWgOofVkejTxvpvkYoYAAVHyG+oliQugArT63ElFVTKroqlOsAKlxRKBRKBWHU5yo1PRUAkF2Srfsaaaynqq6tUiLPllfRVaBcR1DhikKhBJTnVz+Pdze+W9HVCFmEwo1RzZURoYpDqrki1cVqqvpBIq9XoZJSMVDhqgpzKvsUnG5nRVeDch1xJucMZm+fjdfXvU4nMx0Y9bkqcZToSqfW9iSzYExYjKF6VEauJxMopeKhwlUVZcmhJWg5tyXuWHpHRVelylLiKMH5XPUNXa83Sp2l/G86mWljVHOlN70wnR6zYHRYtM91qixU1fuihCZUuKqizNo2CwDw14m/KrgmVZc289ugyZwm2J+xv6KrEjIITVBUc6WNUZ8rn4QrNYd2Vq65KrAVGKpTKCMULKlwRSlPqHBFofjI+TyP1mr5seUVW5EQQjiZUc0VGX/iXPkiXMnKJ+xtKPS5yrflG6pTKOOPfxuF4g9UuKqiqDmxUijBQtjv6GSmjVGfK71tqlew5YQPYb5CbVq+LR+f7fgMl/IvGahlaEI1qZTyhApXFIqfSH1aKB7oZKZNuZgFpT5XBMFLSZs2OXkynln1DJrMaWKonqECNQtSKgoqXFVR6IRPqQhMjHdIqcpmwUBtuFwuDu1SnyuCWVDp/MpTKwEATrcT53LPGalqyEGFK0p5QoUrSqWh0F6IuTvmIi0vraKrIoKaYL1cD5qCQ1cOIWZGDKavn+53XkEzC+oNxUBIJyzDzJj53+vOrtNVdqhS1YR9qhkObahwRak0vLDmBUxZNQXdFnSr6KqIoFpCMlV18H9+zfModZbirQ1v+XS9P07WgQ7FwAkcStosoSYy3BJuqK6hhlZ/dLNu3PbjbXhhzQvlVCPfsTltaPt5Wzzw+wMVXRWKAlS4qqJURW3KqlOrAABXiq5UcE0oSohCMVQxTQFHIN+tigjFYORaoXAVYYkwlE+oodV2m85vwt8n/+bD2IQyKWdScCzrGH48+GNFV4WiABWuqihVUZsSqmamqijI+sr1YBYM5Lvlj1lQTROjGopBwyyopFkLN1duzZVWf7S77OVUE/8RmmspoQkVriiVBqNf+ZTy53oIIhpIYTpYZkE1rSHRLKiwWtDmsvG/K6NZ0EhokMqkaTWbqHAV6lDhilJpqKqakKoE1Vxp408QUeEHhpowYDQUg9J5m9MrXFX2zZ0rk/CkhcVkqegqUDSgwhWl0hCo5e+BpiqaYH2F+lwZozx8rqQaRJHmSmO1oNBUZvR5phekw+FyGLommFQlYV8oXFVVDXFlhwpXVZSq6AdUlQbHqopo+5sqOuiHis+V3nSqJkLSakHBb4fbKxwZef9SL6cicXYiBnw3QPc1waYqjR9C4crpdlZgTShKUOGKUmkIVZ+rqijI+sr1sP1NqPhcqcayUtFOGYlzpec4if+m/hcAsOXCFt3XBBtf+uP6c+ux4+KOINTGP4QO7ZVduHK4HCi0F1Z0NQIOFa4olYaqOllXVaqqWdBfyjvOlfQ5aGkUlZ6bkboWO4t1py0vNO9bcv5a8TUM+G4Aen7TM+S0sJVRczXm1zEY8eMIWVu2mtcKsTNikVuaWzEVCxJUuKrklDhK8PPhn5FTkiM6XhX9gCqDcJVvy8fuy7tDbjCuCKpqGwhjP/mLPz5Xeh3aVTVXhDwCobkqshfpThtMRGZqg8L+0sNL+d+hpjUXrhYUmm5DlWJHMX4+/DOSTybLdtjgtlXaemFrBdQseFDhqpLz/JrnMebXMUj6MUl0vCqaqkJVuBIO4O0/b49uC7rhrxN/VWCNKg5/VsJVFiqDz5XeVYWc4KVlKjRSNhA6MaN81RKmF6RjUvIk/u9QW0wjNAuGWt1ICLVrSu9PVRsvqHBVyflu/3cAgO0Xt1dwTYJPZXj5LuRfAAD8evTXCq5JxRMos+BfJ/7CoO8HhdyekoHAL82VimZQOOFK3xs928BwPNPjGcV81AhFzbmR+p/OOS36O5RNb5VhXBT2R6UAqFVN002Fq0pOVeuQalSGLzSO6+m5KBGoQX/kTyPx79l/8cSfTwQkP3/xVyvsj3ZPb3qhMGDULCg8ViuqluGyQwlfzYJSB+tQMwsKCeW6cQjrqBQAtar5aFLhqpJTGQc8XwnVl68qmmB9RSuGkj+Eyp6SgdTK+LVaUOV9UDMLkp6RHvOZkY+bUHwnjERol/qMBfLDbtP5TRj761hcLrjscx6Vzfyup/0qw30YgYZ5reQoDbChqJanXF8EWhgOFeE6oEFEg+VzJcjXsOYqAD5XFUkg6l9gLxD9HUizYN+Fffky/r7/b7/zqwwafTVNqtbxygrVXFVylAaMUPxyrKpQQdZLML+oQ2VyD6hDe7B8rnQ6tBsp43ryuSoPs+CZnDM+X+tPOI+KQChcKdU3VD6eAgUVrio5VU3ar4yQBNmqNlD4QlXtm377XJVDnCtVzZWG6TYQca4qEqX6G+mPBbbgaa44AvUBXBl8roThIip7/9ILFa4qOZXhxaJcP4gm7kCbBUNEWKtInyuR0OSrzxXBLKhH42hIc1WBmvNAmAVlmqsQM71VNp8rXZqrEHm/AwUVrioxpc7Siq5CQKmsL1comkBCgUAP+qGiDawMGzerTWZGIpVXtkkcENfZyEbiwvuuVKsFQ0zwI0HNgpRKRWZhpuK5yjbhrzy5EomzE7H61OqKrkpAqKyCor/oCUbpc94h0qahEkRUb5yrithbUKuN8p35uFZ8TXd+RgiE5qrIIV4tGBSzoB/9SHiPoSz4cVCH9hBmxowZ6NatG2JjY1GnTh3cfvvtOH78uChNaWkpJk2ahJo1ayImJgZ33XUXMjPFAkhaWhpGjBiBqKgo1KlTBy+++CKcztANEKdGZdj2QC9JPyYhozADty6+VTFNqDrph2q9Khq6WlAb0sT4UspLGPDdADhc8vc74BHaObOgDnNuoDRXdpcd4w+NR71P6xHvMVgYmbylwlQoT/zloVFcdnQZuv63K45nHddOTEBJc1XZHPONUGmEqw0bNmDSpEnYvn07UlJS4HA4MHToUBQVeb8wnn32Wfz555/45ZdfsGHDBly+fBl33nknf97lcmHEiBGw2+3YunUrvvvuOyxcuBBvvPFGRdyS3wQravDF/IvYm743KHlTrh8CbhYMkQnOX82Vlqnto60fYf259cQtlMrDoT3YPldZxVn8b2nIg0AQCOFQKvSG2sQvvMfyMAve+fOdSE1PxYQ/Jvh0vVCIVur/ofLxFCgqjXC1atUqTJgwAe3atUPHjh2xcOFCpKWlITU1FQCQl5eHb775BrNnz8bAgQPRpUsXfPvtt9i6dSu2b/dsDbNmzRocOXIEP/zwAzp16oThw4fjnXfewfz582G3h8ZeWEZQE66Eg9v8nfMN5Tvwu4Ho/N/O2HR+k891u94hDRQrT66s8tsUBTOIaKgMvoHUXKlN2pxmel7aPNz3+31gWTYwQUQFf3+992vZPoBKzzBQAoaST1SgCIRZUJo2GKa3QN17eQp+eaV5Pl2nqLkKohtBRVNphCspeXmeh1yjRg0AQGpqKhwOBwYPHsynad26NRo1aoRt27YBALZt24Ybb7wRdevW5dMMGzYM+fn5OHz4cDnWPjCoqdSFX9eTV0421HFPZp8EUPV2KQ8WNpdNM82FvAtI+jEJvb7pVQ41Cg2UBv13NryDzl91Rr4t31B+VW3wBbQnRqfbiX+y/8Fvx37DmZwzAddc/XrkV3yy7ZPArxZU0e4F+zmKhDdBPQxprtwhrrmqIJ8rE+ObyHA9mgUrZYR2t9uNqVOn4pZbbkH79u0BABkZGQgLC0O1atVEaevWrYuMjAw+jVCw4s5z50jYbDbYbN7JMz/fMyE4HA44HP77C3B5+JJXib2EmBfgaSMhRaVFCLeEG8rf5Xb5VC9/7knvdYFoeyOo3dOr/76KF3u+KDpWaCtEblEuosOiAQDnss/J8qpI/H1GStgddtFvUv5vrPeY4edsm4OXb3lZd95Ot1O1vsG6JxkC2UCrrKtFV1EtohqsZivxGpdL+R1zOp2w2b1jj81hE01SdrsdVlhJl6LU4V1J7HCKxyqHU1zeurPrxPckSC8UMqT5qCEcf6TXyPqIJXh9UNi+onsh3IfT5ST+BjxtH+i+x7Ksz31V6Ces9J75C+meTIzJp7KE/VFYX6HW1OEKzJyqRHmPu5VSuJo0aRIOHTqEzZs3B72sGTNmYPr06bLja9asQVRUVMDKSUlJMXzN8SKxc2FycjL/+9o18UqcP1f+iSizsfoeP3YcyTnJ2gkV8OWeAPF9CBF+5SilCTbcPUm/vqX1WXFiBap/XB2/dvwVFsaCY0XHFNNWBNx9+PqMlEi3pfO/N27aiLTINMW0B48dRHKe/rbIL8zX1XaBvicply9594RTq0+GLQNPHn0SjSIa4bPWn/HH851ejV1mZqZiHnv37kXYmTD+740bNiIt09ueq1evRoQ5gnjtrtxd/O+dO3fCccw7sezJ3yNKe/XqVRTZvL6rO3ftBHvC079PpJ/gjx84dADJGfqel/BjVXp/c9Pmeu8hZTXiLfG68tSLze0VSPfv34/ki57yM694Fzf9/fffMu3a7vzd/O/L6eJ9/zZt2oTLUdp7ARrpe4WFhT6PBaeKT/G/N2/ZjGsxwVl5CYjvqbDAtzqn5qfyvzds2ICzkWcBAHa3V7jav38/al6o6UdNQ4tKJ1xNnjwZf/31FzZu3IgGDRrwxxMSEmC325GbmyvSXmVmZiIhIYFPs3PnTlF+3GpCLo2UV155Bc899xz/d35+Pho2bIihQ4ciLi7O7/txOBxISUnBkCFDYLWSv0KVqHWpFnDS+3dSUhL/e9aiWYBgNXG/gf1QO7q2voz3ef7X6oZWSLo5STUpCZ/uaZ/3p/A+hJgOmgCXeppgIb0nN+sG9nvP8/XZJ76ua9+uSIxNRPWL1flnVd5159nn/TlkyBCf+50aJ7NPAkc9v2/pfQs61u2oWI8mzZogaYCOtihLHxYRptp2/rxLRvj1z1+BHM9vtfp8suMT4CiQVpomSnet+BpwyPO7Tt068jz2ef7X6aZOGNBkAHDA83e/fv2wZcsWINvz99BhQxETFkMsu/hoMXDO87tLty64tbl3Fa7ptAkQ7LxSu3Zt5GbnAmXzXJeuXZDU0lOn3Rt3A2UySdu2bZHUVV/fXfjbQqDMPUd6f7e/fzv/e+DAgagbI7Ym+Euxo5hvs44dOyKpg6f8L5Z8AZTJtcOThstMXMwphm+X2nVr8/UHgJtvuRld6nVRLNNQ39vn+V9sbKzPY0FqeipQJvf26NkDvRv19ikfNYT3xNW5enx1n+rsOuHi27Z3n95oX8djcSpxlPDP6sYbb0RSx+CNjQ6HA3/88UfQ8pdSaYQrlmXx9NNPY9myZVi/fj2aNm0qOt+lSxdYrVasXbsWd911FwDg+PHjSEtLQ69eHj+XXr164b333sOVK1dQp04dAB6pPC4uDm3btiWWGx4ejvBwuTnNarUGdAD3JT9peuHfjEn8VeY2uQ3nbzab/bpHX9tIzzXBnDy1yrVarTKfDKX6WCwWWK1WmM1mYlq7y44wcxjp0qDC1SHg/djizYu7dyUYhjFUtsPt0N03gtk/zCbys5QiNMML04muYVT6jtkCs8VbVpg1DIeuHhLlo3St8P2XvsfCvsilFfopmUwmPr0wLWPS/7z0tpHZ4t8YQ8LCeqc10b0LhkSzxQyLSTz9WSzev6WLAExmU8D7nonRlycJ0XMxG3uPjCLqOyYfn5dAjhU+cwcEJkedbVxZqDQO7ZMmTcIPP/yAH3/8EbGxscjIyEBGRgZKSjx+R/Hx8Xj00Ufx3HPPYd26dUhNTcXDDz+MXr16oWfPngCAoUOHom3bthg3bhz279+P1atX47XXXsOkSZOIAlSoY2S1ic2p7XQtpSo6EAcKvc6XXDrSyq6nk59GxLsROHHthOxcVUCr/xh1xA1W6BGj6A3FIJ28Sai10Re7v5D1s30Z+3Rdq9ehnVgnhRVcwXA4DoYztuLeggZWpoV6KAYh5Vk3X1fsKjm06w2KWxmpNMLVF198gby8PPTv3x/16tXj/y1dupRP88knn+C2227DXXfdhb59+yIhIQG///47f95sNuOvv/6C2WxGr1698OCDD2L8+PF4++23K+KWgopaVGaK/+htT1I67tnM2zUPLFjM2DzDcPm5pbnYcG5DyA36lwu8filadTMan6c8A06qofejRujELkRv39lw3vfnqzcUA4nyiNDuS556EY59wmelFcZCeF1OSY7oXKi9Z+Ud54rD13ZQitBOVwuGAHqk2oiICMyfPx/z5yvHdWrcuHFIOBSXN9kl2TiXew5NqjWp6Kr4TChFQtc7EHD9VjqImBmBWt+H++q+oDtOZp/EN6O+wSM3PWL4+mAxZdUU/rfWJG5UExUymiudz0uX5kprvzsd0dVJ6NluRCmvQMSJ0kuwBQNFLRbhHoVpt13cJjoXjHsP1DZK5RmKIRDClWKcqyqmAKg0miuKHCMDb4+ve6DpnKa4kHchIPlf7+hVYZMGI5k/hw+xY7hYZEsOLTF8bTC5UnSF/601EBsdqENlu6dAmgWNtJGRyVhkFpRqrjT6rtLkF6gI7UplBQqlcUtrE2e1ugSjnsIPLKNUlMbHV2FYJOwrRWinZkFKqHLy2knP6gsV1p1bV061qdoYNQuqTVL+aORCTQA2MlhWWp8rnc9Lz+RpRNAxcq3ILGjQRSDYewsGO089ggdRc6XSnkERrky+C1dCKoNZUGjSv16CiFLhqhIjHQxazWuFbgu6Ec9xGI2KTSFj1KFdiPTZ+Br1mJRXRWNkr7DynBQCiV4NkvC5+rotkM8+V4K2lebhq0AXDJ+rYDu0CwVyYZ1CQXOlR7OphK8aRX8JuM8VNQtSyov9GfvRbUE3/HPmH5+uP3xVfRsfI3tDhdrEHUrobRslnysh/ghXe9L3aCcqR5RWApEoT1+RQKJXc6U1masd59BqT6V+qObQTqyHgvCnR7OQU5KD2dtmixYz6MXIZM2yLLZf3I7skmzNdBxK2k4tnyspoWYWFFLZfK6U8qtq8w0VrkKMO3++E7sv78aQRUOCkn9l1lwFygFUyHsb38Nb698yfJ1wUFCLU/XN3m9kx6SDuD/3lVOao52oHDGioQkVM59RhM9rQeoCFNmLVFJ7UGoLQ/5PkrT3/XYf2sxvg1JnqfQy9VAMAV4t+MiKR/D8mucx6PtB/DElAVT6zI1M1qtOrUKvb3rhhnk36L5GaI7S8rkStlOkJdLneurFH7NgRZnTAqK5KsdQHxUJFa5CjNzSXN1pfVlJlGczoLki5LElbQseX/E4soqzdOcTqhTZi/DautcwfcN0XC26auhavTFzPtzyoSx9IDVXoYYRNX9V0Fw98dcTeH7N85rpuGeeUZiBdp+3kx1XQk1ztfLUShy/dhxrTq+RXac0mQHy/ioVhIz6XP114i8AwLGsY8TzQqQ+oUZMw38c90TX1hp7hPUXLoLQ2sRZeKw84lwFTHNVjuZ1X99ZJR/AijJvlgdVZ1SvIoSbgxvM1F/NVe9ve+PrvV/jg80fBKhGYojbpQQJ4cAr3EBUD/58cWlNbpUZI+2iZd7RYv7O+Zi3c55fefiCVNO44vgKzWu4SWT6+um4WqxfkJf6sDWOb6zrOqMO7YoruHxdLaigjS1yiLV8RvLU+xESCLOgVGChPlf+laWnT1GfK0pQMbIViprGROmcEc2VGufzzgckHykN4hpoJ/KDnZd2osMXHZBy2r/Nff0RqGSrBYNg7qwojPhQrDq1yudyCmwFmLxyMp5e+bQhbW8wUHpnSZqSYmexKI2RlXtGVr75E4ohmHGuih3i+zeSp15Nj0hzZcAsqKYlDDWzoJBga4CFu3v42g7CPrVw30JdvqiVHSpchRjC/ciCQaAc2gOpiha+VIEacJQYumgoDl45iKE/DPUrHyPmLzfrVk1flcyC5fUlKtQ6knyOgon0eel5Z0mTCelvKXqEVVI7q2mutK436nNF0rwqaWOlwpURwSDomisFcxUQuIlfWEZliXP13YHv/C5LeN2CPQuw9uxaAPrdKyojVWdUryJEWCJ0p/XF5ypQDu2BDOgoFNSCLWj4ornT8s/QQmpyDLRZMJQcw8vDXCFtv/L44i2yF+GPY3+g2FEse156tM2+hjcwsvpSiGooBgPaMmFbKwlCeoXozMJM2YrCYJgFhSj5XFVUKAbhu+qPWVBIsH2urpVc87ssaftx/nm+9u/KQKXZ/uZ6Idg+V4H6yg/khC4ctNUEDS0hxOV2gWGYgApo+bZ8tP+8PQY2GYg7THfwx42sirM5bX6FYvjp4E9YengpFt2xCLHhsbLz+zP2o0tiF9U8yotgL612s270W9jPp43I/eHhPx7GL0d+wZNdnpRNinqEK1IwWdLfUoTt+dvR3zRXuXGo7i2oobUJRJwrKYX2QiTMSvArT92aKwWzoChNBYViEH5o+bVasBx9rpT2ZzSC9DpunlPTFlZ2qOYqxDBiFvRl8jIieGjtXeZm3TiWdczvSTQQmis360b7L9qj45cdfaqPkt/T4gOLcSH/Aq8azyrOwsHMg36tijMaiuH+3+/HH8f/wEdbPyKeL3GqR+UvT4Rtf+LaCUPp9XA25yw2p23Grsu7fM7DF3458gsAj0lD+rx0CVc6zYJqWrnpG6aT8yb0P7W9BTU1V0HwuTqfS/bRNKIJ0eubKKy/UJgxEopBSqAEGKEmrarFucorzcOi/YuI1hFpe3PvDF0tSCk3jJgFfSFQztMOlwM/HvwRbea3weTkyX7lJZwIfP2ayyjMwLGsYzh05VBAHZylGrrETxPR4csOOJB5QHRcyz/Nl+1vXG6X6MtbaXVdKA1Kwro8lfyUofR6IJmjy/OLNzY8VrdZkPTFr6W5kv7N7SGpRqAd2gO9WnBL2hbFj6aga64U3BdIbVAeZkHh+xyoOFehsv3NA78/gPHLx+PB3x/UvO6fs/8gpySHBhGllB9G7PCqPlcKHdWIf49aZ3e6nfh0+6cAgM93f+7Ti+F0OzFn+xykpqfyx3zVXAmvC6SwoWT+XH9uvehvrYFZbRBRuucu/+2CsHfDNNOF0qBktO2Npic9j/K8fzNjln2g6DHlK0Zo1/Af25uxVzW9Ut5GHNqleRiNc6U1poz8aWT5CleC+1U0C2qEo5ASDLNgoPpt0M2Cgv6upiX7++TfAIA/T/wpOyet4w8HfkC/hf3oakFK+RHsmEcB01y5HejZoCf/t3QVkB5+O/Ibpq6eqiuysxZCFbvaAGA0fyXhSvq1qDUwqzluKj2T/Zn7RX8rClch5KtgtC5GB1RSPDJ/BuUtaVtw4xc3yoRlJSwmi37NlUbQStJx6YTrqyZbVXMl+TuzMFO1TlrHSQjbqNhRrNh3jZi0fDGj2d0CYUZDC1cumis3eQNjo4hicoWIWdDodQevGHOvqGxQ4aoSoxrnSqGjBkp4c7NuRFmj+L99WYXny15kSghV7GpqcqPCpaJwZSCCs0xzBVb07PQ+k0B8/QebYGuuAi1c9f62Nw5dOYQB3w3Qld5skmuu/PK50hB8rCar6nlSnoBGEFHJ34X2QsXzvmoWqkdU53/3bdy34syCRhzay8PnyhUY4UpIZQsiqnQ8lMaxQECFq+sMI8KF2peEy+0SDUYFtgLDdakXW89QmWr4MgnoUcsrCVfSLUfUynSxLtkgIpz89E4aSl/uoWQWNEogzILl+eVuZswyYVjPIhRFnysNwUe6x50eZ2HAmOZKWm4gNFc1Imvwv1vVbKU47hjxF/LJLCjQFGmtTCsPs2DANFfl6HMViNWCevbWpMIVJagEO1p3IDVXwknNlwmO9FXpq6AgfDEDaRZUyuvglYOiv7W+eqXClVBI0PvMK4PmyiiGHdoJfaY8HXotJovseUm1Sxykydyo5krqkE0Urgh9T9i/tEyPsvwM+lxp4XQ7K0xzpbStVUU5tAvrU1k0V4FY0ad0HQ0iSglJfHJoD5Dw5mJdqoEK9WB05Zda3dX2BdObBwCcyTmDP497HTL1xvMyYhaU1tHfuFyh6qtQK6qWZpqKNgsaxWySa66UzIKkScmo5srXYL1GHdqFBGK1oPA6tXfI1xWIqmUrOLRr+fdUJrNgefpciT5cAxRElHS8Mn8kkqDC1XVGoFYLutxyU5dRAqm50rPlhR46fNEBo5aMwh/H/gCg7LMhK9+AQzvLsmLNlc5nEhcep5h/oNl0fhN6ft0TOy/t9DkPPfcVCOGq3M2Ckklej7lWLXZUXmmeovClp/9prhbUYRYUnQ9wnCun26mYZzC2vxESapqrQJkFhbyy9hVcyLsQkLxICMcqX8dWRc0VDSJKKS8CJfwoOrQHUnPFlo/myuV24es9X6uuSNT7pazVvkWOIgDA9we+l+Xl65etVBBlwYqj0ut8JkqbWgdDnd53YV/suLTDrxhmevpEIOJcladZ0Gwyy+Ko7cvcR0xL0pRIn1VqeioSZydi3LJxxPN6NFeaca60ApeW/ceh9Ey2XNiCz3fpC7si/dgJhKnRp42by8nnimVZXYKimrnWCNJnMPa3sT7npYaTdeKdTe94y/XVJ1bhOhpElFJlMCS8+RFeQA+kr0rSwP31nq/x+J+Pq+alV3OltL+YtF0OXTkky8sN5Xs04nPFsqxo8iM9E60v6/Z12nvTBvGLT89KOCX09AnShFTiKPFEwSe0AdHnqpw1Vwv2LBAdU9LukZx1SRsCFzuK8ePBH4nny0NzpeYHJjx3LOsYJiVPQvLJZM06CVHTXAU7zlV5aa7u+OUOTD46WXNbpmCZwXZd2qWdyAfSStICko8uzRX1uaKEAm7WXbE+V+4A+FwRJg5SPlsubNHMS3hdIPY95ByH9X5pGvW5EmnECM9RKw5Pea2yaVa9mc/X+qq56v1tb3T4sgOWHVsmO0fS5JTnxtW+BvlVCsUgu0Zy3slq35tRh3YpRsKKAN5Nd1XrJLj37JJsxbEqKKsFFfwv/fG5Onr1qOK53Zd3I/lUMtLt6ZpjVaDeW2n94yPifc5LjXBTYPa6pT5XlEpBbmkuGsxugMdWPGb4Wi3Nld6vByWz4K5Lu/Dg8geRYcvQzCOQW5n4YhZUu1fOBCEyK6gJs0Z8riRmQdKgYkQbEcwvPn+EcV+Fqz3pewAAC/ctlJ0jaSL0+sUFAtKWJfVi5CFFAN8mUulzd7p8ExyFQoUs4K2kv0jDqgS6P53KPlVhmisjYSXU3uHPdn6mmFe3Bd3431rvi7CMlDMpATNpV4uoFpB8pARq/0Oltit1lvK/WbAoshcFpLxQgApXlZDv9n2H9MJ0nM45TTyvNjgainNlMLwAAHT/ujt+PvIz/rwq3wKBI680DyzLBs2hPRBmIm4g1ytcGdFcSc2C72x8BwczD8quUSsjmJqrQE20/vpckQQZUp8pT80VabJpUq0JMS3R58qgM7kunysNQVzaPtL0aporUt7SMYQ0pgjv43LBZVWfKy1TGocvW1wprZo0ahYE9G29ZDTUy7f7vjWUXqnc+PDgaK7UXCEM5aPQtr8d/Y3//dHWjxD3QZwshmBlhQpXlRCtDT+1zIU/HPgBZ3LOGL5WiMut7tC+J38P8br9GftR/cPqmPj3RLLPlUFHU1IavZOtWr5mkxl2l12kPVEbfFVXVrISzQBYWR3v+eUezfyUVOiB9rkKVH568lEVrgiCDEnY8DVcgS+Q3j0jJg+tvilts2sl1zTrpNVXpMKT1n6Gge5PNpdNsY1WnV6FiPci8OHmDzXzEQpXahofJSdpf8yCSmVKn6em5kpSBufb6S/BMgsGSouplM+lgkuiv92sG+9sfIeYtrJBhatKiJaqlmVZxQEyNT0V45aNQ/PPmiteqwen2+mTvfydje+ABYuvUr+SbbthpHy163Q7tKuUZWJMWHZU7PPz2qnXFNMbjnMlmfCkK9A0NVdBXGUTqOXReuqlapolCDIkgbyiNVdGnHW1zEDS9uBMpEYR1qnUWYrDVw57/b4ITvVqf/uCtAwlx/IfDvwAAHh57cuaeerVXOmJXq71fpEgacSl96XpdiFpFyM+fGr5xIbF6r+WlX/cKRFszVX72u1lx/yN+xcqVI27qELoMdtpaa7crDsgXxwrTqxQLcMXh3bhRrTzds2Tnfd1Mg+0Q7uJMSG7JFt07HQJ2QwLGPO5crldsjpmFmUacnIPpo9MoDQXuoQrNe1hmSAjnLBIZsHy9LkiTYaKwhVBADaquTp2zZjzOKlOr/77Ktp/0V62ypHDzJgVffj07MGnp/8JfWt8RaS5UjH9KwXY1DKla/V70jU2l9ikaVRzFSifJq05QUjfhX3RbE4zRYFXSKBW4iq1LUnrrLTjQWWDCleVEK2vHX8mR+G1BzIPKKYj7Zenh7rRddXL1zGYE6/zxaFdpZ1cbheeSn5Ks1wOI5qr1vNb41L+JVm6BakLRNeolRFMzVWg8lMavIUO4FraQyn+rBZ0uBxYfWq14X0whe1hxCwoFPq4OmoKVwESlEl1+mT7J8QyHuzwoOjvN9a/oSqw6tG2SMvQ61elhm6zoAGH9lJnKSYnT8bTyU/7ZBaU3ld5aK4WpC7Al7u/NHwdx+a0zbiQfwF70/dqpg2Yi4BC25LeB1+1eaEGFa4qIVpfO3mleUGvg5bPlRJKUcY5fPa58sEsqFbG2dyzmmUqlS/F5Xbhp0M/iY59uEXuY7Lh/AbV/BQ1V/4I0z4Ks3q5WnRVdkwYO8uoQztxtaBOn6t3Nr6DWxffiqQfk3Sl5/MXCBpGNFfCunK/jWqu9KDXOZsbN6RlCLXJHPsz9yuWZzWLNQt6tO3PrHpGM40WejVXQpRCMXCa96j3ojB/13zM2zUPlwsuq+elwyyohUxzZUDjBACF9kI88dcTIkfwYELqR76scFTq16T3Qdq/Kis+C1enTp3C6tWrUVJSAiC4y8GvJ/SsNtF6IR9c9iD2Zmh/lZAQPscoa5RiOl/3FvR16w0thL4puh3aA9hntTRXa8+uFR0jDcpaQoeic66P91HiKkG7r9physopouOBDPOw49IO1fN6zIJC/Fkt+M3ebwB4vtyNIBTejPhcCa/jnreWIOhLe+uNk8aNGySznvQY9xFEyluP2UZ6na/jkRB/HdqFuFk3ckpzRGm1nk1AzIKSdjFqFlQS5jIKtUPf+ALp+T/252P4dq+xVY6KZkHC+3zdaq6uXbuGwYMHo1WrVkhKSkJ6ejoA4NFHH8Xzzz8f8ApS5Gi9kP4sZdX75awUikHPdYEoX8qb69/kf/tiFvRXiDAapoE0kAuFK6VtgEh5+mrGW5ezDqeyT2Huzrmi44EUOkkTsd5212sW1L3/o4/3JczfiFlQOBFy9daqa0VoroyunKsoh2Oh4CLVIm1J24LX/30dDpdDMSyL1FwoHUc1HdoDYBaUYlSQUGr7rRe26rpe2AZq2kkOUpss3LcQj6x4BDsuqn84aeUDKGiurlefq2effRYWiwVpaWmIivJqNsaMGYNVq1YFtHIUMuUl2WuZunwxC2oKVz6YqUocJbo3F1X7svTH10jtWlJ9/NZcBcAsqMcR21+0VPx6NFfCNKR20xOuwB+Ez480uRkxC6ppRwK1EEWpTkoab+I7Z/BjQU+egUQq6PT+tjfe3fQu5uyYI3ZoV1ktKFvBq2Hu0rVa0KBDu9Gx3KjwJitf0Db/99f/aaZXWy1oxHWC+lzpYM2aNfjwww/RoIF4E9mWLVvi/PnzAavY9UogVgv6g5EI7b5oT7TyNyrgLD20FFHvR+Fk9klv3XT6BJAiVfuK2n09t+Y52TGSBkP4xVZZQjFIo3tL+e2Ium+I0VAMpHZ7fk1wNea+mIsAcV31+FxJw5voRbdZkFEwC6pcb1TwCiZ6AgXvurxL0aFd+s5In4XdLRfcx7Qb4y2TpLmSmgUNOrQbHcv93b7MaP8K1NhiaLXg9epzVVRUJNJYcWRnZyM8PDD7EFHUCdTyXRJGzIJqPldqEZkDUT4HaTd4vWZBabn+LDtWuy/SqkvSoKIVgyvQoRiEbd1qbiukXk6VlaNGiaMEzT5rhjuW3qGY5vPdn+uugxS9ZkG9+CoUCIWk5ceW685XZBZ0aZsFnW5ncM2CJgWzICEunq8Bc/k0QRDA9HxQSBfzqEVol77vJK3o5yM+531PiT5XUrOgQc2VUZSubxTfSPT3katHMOj7Qdh0fpPouGHhysBm9Upj68J9C/l4ZlKImivmOtVc9enTB99//z3/N8MwcLvdmDlzJgYMGBDQyl3vSDtvRmEGbl9ye7ltD6CptfDBLBgsh3YhuoOISuriT3wso5MJaSDffXk3P1iXt+bqZPZJ3PXzXbK81Ug5k4K0vDT8cfwPQ2XpFQxJHxFGV2cFAl81V0bNgk63M7gO7QY0V2r1kKb311SlFz3BQXNLc3WbBaXnSH3LxJj4dgvIakE/xxw9gjwAjPhxBP49+y/6LuwrOm50rDDUDwiCZaG9EA//8bBiHlV5taBhEXHmzJkYNGgQdu/eDbvdjpdeegmHDx9GdnY2tmxR3xGcoo1woJI6XU5KnmR4IjOKEY1IeTm0GxVcfFktKN3vzyhGBy2SBmPLhS24+5e78ed9f2pOmEqClj9cLfaETdA7wetJ169xP/U81HyuCCaTYkexdsUCjJYTuiHhSqfmymqyomn1pjhx7YRm/QKhuVK6Xo/gJTWNKeXpL0rBQYXk2fKw5NAS/m8jZkFSLC4GDH+dHrOg1n1LzxsWrhTyl/arc7nniOmCqbkyMSZdfmx1ouugSbUm2HlpJ/Fj47r1uWrfvj1OnDiB3r17Y/To0SgqKsKdd96JvXv3onlz8pYqFN+QDmwX8i5UaPlS1MyCSl+zvji0GzWD+mIWBMQDttGvcaOTiZIG468TfwEw6NAeoImMaze9q/n0DNS+PG8O0nMvchSp5mdz2/DXyb8CKoRpaa6U9ukUXsf9VjM9CzVXDMP4tWpKTXMlhYU8FIOqWTAUfK5UNFfzd833plNobzfrlp1LL0yXpTMxJn6bLmG+HFKBzOjHY6A0VyQBl0MYNNfoWGFEGCONmaTrw8xhfCDhquzQ7tNdxMfH49VXXw10XSgS9KjvA16mgTLUNFdK+Wh+2RGuiwmL0V0nwLeNm1mI99tiGMbQQBQIzZWoblo+VwEwC0rLiLREKpZNvF5HX9HaZkRLcyWtC2kblXCz19fzu8vfIflAMu5tdy+W3r1Us3560BPqwea0Idwi9jklaa7UtKNCzRUDRvckQ2rD3Zd3y44pxbkyuhWMrtWCQfa5UhKacktz0b1+d2w8vxGA8gcJySwo3e4KEJu65u6ci8+GfyY6LzXHGX0XjQpXSvkX2gvx25HfMKzFMNl4KSwjkJorKSSzIKk8BgzfF9Py0mTnr1vhauPGjarn+/btq3qeoo6auac8ArUaKaO8QjFEW6N11wlQHrCSTyYjz+Z1eFVbLWi0rY1OJr748QQyFANJYIi0RhrKT1iHGh/WQNZLWfI0fvjYkRzaSxwlsmM2lw1zts/BU12ewqosTziYnw//LBOufH1/9EyABfYCXcKVVsgOkeZKp++J3vtSjHOl06xotLxAwrIsDl85zP+tJKRKhW9VnyuJgEa6Z62YXjKzoMH+HiizIADc/cvduLPNnfjtXuUVuoFcLajH944kBDMMw/dFUnyuqhLnyrBw1b9/f9kxUXA3V2A2erxe8UVgCRZG9toKmEM74Txpew41lAasET+OUC5XsnrIqMBi9FlpOcISg4gq1E9v2VaTlRfqSpxyIUVtVRQJYbqc0hxkFmaqpiFhNEI7qd6AJxzDU12eQoQpAsXuwPpl6VmhSDJDisyCLn1mQW4y91dzRSLflo9zueeIGnElgcvXUAyBFsDm7pwrWnmqunGzUhBRDZ8rkiAmFBh6NugpOx8qZkGO34/+rnpeqX4HMw8iLS8NI1qJx0i18mSrBXVqrgD1EBRVRXNl2OcqJydH9O/KlStYtWoVunXrhjVrymcVW1XGl/AGgUSvyQYIkkO7wa9oYh56NS+SdMGKc0VCS7gKhs+VUBNCEgZIZkHVwVU6IetwfjZy3mwyy/IkmQUBr4bB3zhAJPSYBYvscl8wvzVXAf6C33JhC5rOaYqL+RdFxyuD5uqdje+I/tarUVFKRzILkgQ2E2PCuA7jAACDmw6WnTdqFgym5krxGh3t0eHLDrjtp9uwL2Of6LgwvXDDdWm+gILmSkFgVfOjrSrCleG7iI+Plx0bMmQIwsLC8NxzzyE1NTUgFbteEe115XIAgvE11MyCQvQKQP9N/a96+RoaGz34OgCRrmtbuy2OXD2ieX2gg/NpTXj+BnAlaYBIZkHVpdg6fHeI/jwqwpswPVFzRTALAl7hyuTjdqkJMQmK5/RMgCRHe9L2N1o+V9zEYkhzJdVEafR/6X6PekM5qKUHxM8r0B+C0olbdW9BBcd3mc+VZFwhCgIMg1pRtQCQNZiGVwtK2kXv1k1K1+u6RiGoKolDVw6hU0Inb3qBz1WDuAZEp38A+PvE38QxhehzxTCqC1MqanulQBOwu6hbty6OHz8eqOyIbNy4ESNHjkRiYiIYhsHy5ctF51mWxRtvvIF69eohMjISgwcPxsmTJ0VpsrOz8cADDyAuLg7VqlXDo48+isLCwqDW2wjCF0E6qJf3Kh0jA4VeLZvaqhalMv3RKBkpi1RnvasGA/1sjMS5MhL4lSMQmivZM/dB6yg9/9iKx/jfx64dk6VXMgty/UrteandC7dRsdHrOE5ln5IdKy+fK6Mabql2T830Z0TwCubOEVJUzYKSd0OpX+rRXDHwahD1bGOl5QDur+bKlzhvRj7EpPURpuc+vkjc9tNtxONKbXqtWHnLqopajRpoDAtXBw4cEP3bv38/Vq1ahSeffBKdOnUKQhW9FBUVoWPHjpg/X74kFvDE4Prss8/w5ZdfYseOHYiOjsawYcNQWuo1JTzwwAM4fPgwUlJS8Ndff2Hjxo144oknglpvIwg7oz/RqH3F144dKAFIr/ZDDb0TglRDQxqE9ZqZAu0fp3UPer9GHS4Hdl/eDZdbvF1RqbNUphkhaa6MaDCMrjoD5JPNt/u+5X//ePBHXasFhfhqFvR314P7frtPdoy0/Y1mKIay9jKiudIj5KphOBSDQv5mxoys4ix0X9Adn+9Sj8xvFOlz1au5Asgxu0g+V0oO7dxzIGmZytPnas72OWj8aWPd6Ul10qqftF2F9RWuygX09TOl8oK9H2goYNgs2KlTJ+Iy9Z49e+J///tfwCpGYvjw4Rg+fDjxHMuy+PTTT/Haa69h9OjRAIDvv/8edevWxfLlyzF27FgcPXoUq1atwq5du9C1a1cAwNy5c5GUlISPP/4YiYmJQa2/HoQvsPRlLm9fByMTo944V76UGQizoB7hzy/NVYCfjSHNlUrZj654FIsOLMJrfV4TXVPsKEY4Ix4sSQ7tRsyCRs1LSteooWQW5PC136mZInx9tqTtbzRDMfjgc+Wvb6Zhnysls6DJjHc3votdl3cZKt8X9GquuLRmmGXjlV6zIKdB5AShtze8jZQzKVjz4BrDZkEpWpp8IVNXTzWUN4eRgMNqKyilq2H19DOlNlXTXFUVDAtXZ8+eFf1tMplQu3ZtREQYW9EVaM6ePYuMjAwMHux1OoyPj0ePHj2wbds2jB07Ftu2bUO1atV4wQoABg8eDJPJhB07duCOO+R7pNlsNths3hcgPz8fAOBwOOBw+K9Z4vLg/i8ckIttxaIyAq0dIdXfbveWz7Ks6j0K6+NwytvDl/Zxu93yfJzyfNTydrldsvOkSdnusIt++9O+doddVubgpoPxz9l/DOflcDhEdeNwupx8GSLzcdnxTWmb8Nhfj2HOsDm4tfmtAIBFBxYBAGZsniEaDAtKC2SD4/Jjy7H/8n7ER8TL8iZhd4rraLPLJwrS8xTWXes9kp5Tm1QdDodIuFp3eh16N+qtWK4QBoxiPZwufdoF6fVCrUapoxQOh0O1j5XaS2E32/n66PUfszvFfU/Lj4dhtbVAXH8mrf5W6hNmxoxCm+8uFqrjhWQet9ltiullEeTtNjAWsULA7rTDxoj7K6lvOR1Ovr1sTk+Zb65/EwCwaN8iWd+QPgsp0rFs8cHFmN53umxvQH+Qln8y6yRqRXj8xqTvqKzPOrzt6nA4RGZO6Z5/Lpd8nJXma3OQo96TYopxqI05/hCMPNUwLFw1bmxcLVkeZGRkAPD4fgmpW7cufy4jIwN16tQRnbdYLKhRowafRsqMGTMwffp02fE1a9YQN7D2lZSUFABAVrY3VtDadWtxLMLrd8IJdoEiOTlZdqzQWaiZhlSfAwcPIDndm5YFy9+TEXJyc2RlnrtwTpZOrV7Hjx9Hcp74fIlLLlytX7fe+3v9eqK/REF+gewYic1bNuNK9BXRsdIcdROWEsnJybhQKo/Gf+78Of6+hcLXocOHkHw1GXfuuxNuuDFq6Sgs77RcdK104ti+ezvxy7PTgk74uu3X/N8ZmRmKbb0/e7/o73Xr16FtdFscKfIuAMjLz5NdX2rztgup3YQkr1R+zlJSUlJE5qNxv4zD/DZeFwLhh4O0TkWFRYr3uSd/j67ypddn53onkJNnTyI5OVlVONy8dTOqWaoBAJxOJ7Iy5XHDSBw5egTJ17xla7kTXLsm1hp8kfoF/5vb7mXI4iH4ucPPOHf5nOz6o0ePIjlb3lZupxuXLlzSVWcSau+08NkBwLYd21B8hBxyIycnR5zvymREmCNEx3ft3oUIk1ghQPqgWblyJc5keiLwn0s7J6rjngN7kG4TO3jv3bMX5tPKJuY9OfK+NHnJZDzZ8EnFa4wibcd+3/fjx4Or9quqaQ8cOoDkTO8x4cdAZoY41Mr+/fuRfJH8zLh8SeNYcVGxah89efIkkgv0v/ehii7h6rPPPtNOVMaUKVN8rkwo8sorr+C5557j/87Pz0fDhg0xdOhQxMUpO8HqxeFwICUlBUOGDIHVasXrl18HyuSAm/vcjHa12/FpX7v0GuDbfE0kKSlJdiy3NBc45PnNgpWn2ef9GRsby9e1bbu2SOqSJDrP3ZPS9STi4+NlZf6Z/Ccg0SLzaQj5tWrVCkm9xXnklOQAB8XpuvfuDhz1/O7Xv5/nC/6ovD562rzXzb3Qo34PUX2aNGyCzbmbVa+LtkbLVs4kJSV5VihK/LnrN6zP37f5iBkomwvatG2DpO5JcO9zi/IAoNjerdq1wq79ZPPNgIEDgDL5qHad2sR+AgBZB7IAQYDlvv36YunKpThSdASPdnoU3+z7BtEx0bLrI05FAGVj680334zu9bt7T0rqO3z4cEAswykyZMgQMIe9wpU1wioqO+xEGFCmaJC2T/X46or3aTptAsg73IgQXv9U8lM4V3qO/zuxQaLnXvYpX38i6gSe7/k8cAwIs4ahYYOGQK52ua1uaIWkXt6yS52lwAHl9JmsPB4Zh4kx8QKg9QYrmoQ1ASQyXqsbWiHpZkFb7fP8LyI8Ak0aN5G9q3pRan8ACD8Zzj87AOjSrQuGNhsqqwMAxFeLBwRy15ChQxAbHosZV2fwx2/qfJNnAcdpbzo7KxeukpKScHzHcSAdqJtY11PHsrI6tO+AiOwIQCCvdOzUEUltlO+j8EghcF58rHnT5kgaqnwN6R7VENZRdAzA+bzz/LstPM6lv6HNDUjq7jnmcDiQssT7gdwgsQHgjcGMGzvciKSO5HGGy/fQlUOycSw6Opofu0i0aNECSX11tIdBHA4H/vgjuHvzCtElXH3yySe6MmMYpsKEq4QEz1LqzMxM1KvnjceRmZnJO9onJCTgyhXxV7LT6UR2djZ/vZTw8HCEh4fLjlutVrng4AdcfiKJ3gRxGQEO4UOqv8Vp0UzDV0egJWBMjCytT23EyMt0soSd01XyNZlMsvMmh9zEMmvHLG9+FisYt7yB9S4LNpnlZeoJfhodJheurFYrzBby1y9XhtDEwTAMLBb9zw3wTCRKK5uEeTGM/LlymEzitrFYLLw2LMwSVpYBoS6CZjZbzKLzXRO7irZu0dt/hjTzCPJCs6DNZVO8XnrcbDIrprWY9Sn4hdd/ve9r0Tkn64TJot6XvjvwHab1ngbA0+5SHxclpO+eE+pmzMwifcIVy7BgTIR3gvB+AZ74RHrbioSRsUKpDsS0FsJ4YDIR702KxWLFru2e99gNtygfq8UqewcYs/L7AgBms/y9DreEB3wuUTqmOU5I3lehdrtJ9SaipNwzIPmZcXmYzPI+zzAMxrYfK9pgW4jZrPwuViZ0vQlSP6tQpGnTpkhISMDatWt5YSo/Px87duzAxIkTAQC9evVCbm4uUlNT0aVLFwDAv//+C7fbjR49elRU1UVUtEO7EWfYQOxvJ8uTcI9aK8T0QFqVI9xwlxSlGtC/+oxU7zBzmOZ1Slv7kPIThiaQLjdffHCxnmryuNwuxf6kdyUiabUgl55bfacZ50pSB19X7XFOx0LhyshqW1WH9gAsDbe79Pn0+bJaUG2Flz8orWRTWkxhNpmDFqNI2naGHNoJPmUkh3YSmzYBv/5sAUYANonPjokxGY4xRhREdIbcCARa9ZO2s/TvIc2GIOWMfncPpThXC0YuUBSuKiJIbTCoVNG6CgsLsW/fPuzbtw+AR+jbt28f0tLSwDAMpk6dinfffRcrVqzAwYMHMX78eCQmJuL2228HALRp0wa33norHn/8cezcuRNbtmzB5MmTMXbs2JBYKQhItsyogFAMQoGOtPJKaTWWL8JVXHgcJnSaIDpGmhiMrKhRykPPkmdiKAad6kKl3d+1iA4jC1ek/LZe2MpvdCoVgLSCs5LyV9Jc6V1dRJpYuGs5wcDoakFf99PknpNwcpcKalqbRCvWMQCDvcPtMNQH/Vot6Ed9hXVUFK4UYvGZGFPQYl3JhCsDoRh4TZxGKAYS/foBcHmeg90pTm9iTLrCkYjqRuiDesaJYJAYqz3nCccIJcFZ7b0iCbDR1mjEhMVg9A2jddSy8uKTDvfixYtYsWIF0tLSZI6Gs2fPDkjFSOzevRsDBgzg/+Z8oR566CEsXLgQL730EoqKivDEE08gNzcXvXv3xqpVq0QrGRcvXozJkydj0KBBMJlMuOuuuwz5lAUbVc1VOQRXEwZp9CcUgxKN4xt77P5l10uFl2BprrRCMbCsn5orHwdNLnCnnvwAYE/6HjSKbyQLl2A0vpObdSuWoVcjSfrK5TVXZZOs0S95PeEdSHD3L+xPRrbRCHZUaLvLrhlGAvBRc8UGTnMlDLMjDA1Byt/pduLnwz/zx82Mfs1VTWtNXHPod84KtOaKBas/Np/b8xxskpV+RvbSU6M8NyrWCuGiFu9sZKuR2JPudcjX089I7REfEY8NG4BtW81ATfU6VmYMC1dr167FqFGj0KxZMxw7dgzt27fHuXPnwLIsOnfuHIw68vTv3191sGYYBm+//TbefvttxTQ1atTAjz/+GIzqBQShtkoWob0c1KW+CjJ6BxXpoCgdjImaK6dBzRWhnUJVc0XyyxJqgJTylJoFjcZ3crNuXWZB1ThXBK0Td0zNLKiWh5ZZQgkunUhzZUCL4q9ZsH5sfdXzdpddMbq8qKyy9jYxJt8jtPsxTpgYE5+fkuacy3/ujrl4bo13sY/FZNEtXE1tNBWvn35dd70Corny4WPQk9jzHHLyCJorgx8DoW4WVHof29Zui1sa3ULMSy1P0nN65Zb/oH9LAHdbiMJVVcHw59orr7yCF154AQcPHkRERAR+++03XLhwAf369cM999wTjDpeV4g0V+7y11wtO7pMXKbKzue++FwJ0zEMExTNlS9mQTWfKz2Ci9Mpj3KtZ9AkOS27WGV/KF64kkwUvmiulMyCerfWIX3lSs2CxM2cVb6e9WgdSJCerxH/LbW0eoSVhvENVc87XA7ilkNSuPZjGAabNuibdAPpc+VyeNtBqb5cHVecWCE6bjaZdbe52W0sLqIRzZUUUt8gbX+jXLinLx8+Ko+NFgizoJrmKrc0V9U/0h+I76bC+9i5nlxxorZFEoe0PT4c/CHcp4aUZUDuK9etz9XRo0cxfvx4AJ6VByUlJYiJicHbb7+NDz/8MOAVvN4gRXUuT/7z739Ef0tfHH99rqQbqUq/dEn5GPW5ImF0Dy8OvRqhaznyeuv5kpduKQF4nrtSe3LppQIKqZwrRcrxo9zwmgVl2kOdX/gkjYnULGjY50pB66AF93yFgTelZjW1QTvY++LZXXZdGljuQ8LlZLBzW/lsfyO61uVtB4fLwT+f21vfzh+/eImssTAxJt1C/swPehmqlyHNlYKA7ovPlSex5zlYw7U1V75syK6k4T6dfRrVP6yOfgv7Bcz/VtMsKBUWIdcIG0H6/taPrY/UVC7z8tuLsiIw3GLR0dG8n1W9evVw+rQ3UEhWlr6gdxRl1BzaK0Ki17v9STDNgoY1V6TtbzQmaX/3FrTb5ZovE2PSFq4ImiuH26H4NUjyZXKzbqIQuP7cesVyhWZBNcdvI2ZBoeaK+xrX+kDQ2rpFr3YhIUYeSqU8zYJa6F0tyG0dU1rK8OYoLdS2LDGOtx8J820U3gHY+RQAIOsaWWPBsizqRIuDNCuRmx1jqFZGzMV6zYK6tV9lDu2WcPlqQVnZWmZBA36d3O4KWy5s0eWvp8QNNW/wlq+xKbuSDyQ3Rui5RohsWzSGweXL3IUKmqvr1eeqZ8+e2Lx5M9q0aYOkpCQ8//zzOHjwIH7//Xf07NkzGHW8bmBZVvQ1VREO7VLcrBtmeF8ChmFAqoYvmiuGYeCWxJYqJWyXYNTnikRuaa5mGqW9BUl7aUo5kXMEwEDRsdOnGYBVF85IoRjUNFekr3AWZId2NYFBaBa0mCwiQV7vRq8kEwKXvl6sJ9ZcRmEGXG6XoqCj9eVvdF9J4T1zmqs3172J7Ze2q379++vQrtU/1ARmIbFhsQCA0hKG15ho4e/eguKLve1QXOpt+8/mAIjy9LHISOWFEHqFK733xicPsEO7zWnT/cxvaGXBcXi2ZRE+Z59WCxrwB72U7412b/Q90IMezZULnnKJgqSOj31p2zNgcIm7Laq58pCd7dnKYfbs2XxMqOnTp2PQoEFYunQpmjRpgm+++SY4tbxOkL5kFeHQLkXNLOiLz5VwkGBZFitXirvg5atyPw8lzZVSmaTJ5ZE/HlGtFwv/NFfvpj4ju/7rBQychOClonJL41HXfZPsuKJwVdZ+UgHISNgMQKypkwo+Wl+3SnUUaq5OHqzG11do6tbK36iZRS0d97X99sa3seb0GuTblLeP8tfnSosCW4GufCKtntWjDgfDa0y0cEp9rvypr2DCu3xZsuihTPByushmQSXtLxEFrYVitfxwaOfGUWFfe/LvJ3ULLNXjyjZuZh2ia3yKc0V4n5T6+Nd7vYFo/XmmojHXoMO9VHOVLVjgydXbyBgBMNjDLTikPlceEhMTMXbsWJw+fRodOnQA4DERfvnllzhw4AB+++23kN13sLIg/bKuCId2KXo1F8uPL0frea0N5ed2AxfOiwUAkhOtks+VEZ+00zmnNdMoaa60tE8cxLZi1V+xpUsYZC4Rr25VEvQA8leuUigGI5orafnCdEqQvtq5es/8wCI6rphHgBza+VV2giGNYRjV+F9SLYRiugC8dyezTxoz17H6NVcXLwZScyXQUluEbe99D5xO8qSqtCiECOHepqVMU07uj+ZKIa1en6vhwyx8emF/JPUZX0yyeoQJf56pNGyLWp5aPle8YKSzTtK237+PwYULQFQUULcO1VwBABYsWICrV6/i1ltvRZMmTfDWW2/h3LlzQaza9YdUWKiICO1SpFoHIcKXa0/6Hhy/dlwzP+Hg5HYxcuHDShCuFMyCWkvFtRBp4RS+uvNyGbghGZxPDZWlU6yPhnDlsDOAXe5/omYW1Lv8W03rJoxzJfO50huKgaS54OoimDzVJkIt7axRzZX0nv/vr/9TvEbYbnpMRGqawLQL2m2mOpk7PU7NLnfZtax+n6uLlwOouRL0V4dDrnUAAIczAJorgklo5taZysn9CcXAmdIVjqvx/PNAsyae5+BinXLNlYbmValuPRt4XWjsDh3ClR/PVFHDbyDOldlkRoFkD3tec2XA5+rcOU//uvNOIDO9avtc6Rauxo0bh7Vr1+LUqVN46KGH8N1336FFixYYMmQIli5dKgsmSjGOdBIKBc2VVLARTl6+fKWJnGTZfnLhw2KTDXpKZkElzZWv7US6LjdXMKG6TcAHOUiwtNVfHw3hCoBMuBIJKRJcrEu3n4eW5oobFH3VXJHMgvxAK5g81UIFaPVxvc+SF64MxPsS1ktPhHa1oJ7pl72/1Z6dciGe8jMyuDatGJ+ryAhvnzl+UtLXOM2VS9nnyh/NlRp6tVEklD7Cfj36q+a1deoA1WLLdhuAAw6nhllQy+xWdr4kuyZw8D4AwM5d+rdF8gWlHRf0aK64vw/sMyMuDiLN5qV07Wcgffezrnr6UNOmUPS5KvNAqvQY9uJs2rQppk+fjrNnz2LVqlWoU6cOHnnkEdSrV6/CNm2uKkg7onSy9jWcgF5IXyBSzZVw8vJJuCq7xyc6P4GO574FaTdqYbBFN+tWHByNLE++q81dqueVTHEFBYL6ZbXBj/+LwRPjqhPzsDkJHxiawhUD2OVO7UY0V27WTRSkfDYL6vS5UjULufWZBaV93NewAly5Um2kGlIthFbe/gZ7VNWUuLnQFV7NVZjO8kptgdNchVm97XDylCBflkFcHGcWJOevFphWhkGfKylGQjGczz1PPL45bbNmOfHxQGx02XMwOUVO/r5EaOfaZ/9eBnB6Vgrb7Nptpphvnnp8NUAe/ob0W+kYV+6mjWX9wuUNG3HlqnGfq9OnPW3WqRNQP5HcB1JTrzPNFYnBgwdj8eLF+P777wEA8+fPD0ilrlekHTE1PVX0t5qJLhjlA+oxpnwZxLky3h7wNo7vrUkUPoR+V2orBfXsfcZRL6aeZt1Ig0SeUHN1qRvuvptFzehqxOsLin3QXLFys6Caz1V6YTpBY0SO0K6pueLMghKtja+rBUWTq2DylDpcuwR/aoUb0a25csvj8WhdK7w3PWZB1QCZjLZZUK0tGXDO4l7N1eCBCtodW6zozxIbOUyB0aj9gLgvtLrBDeFexbVrSRzaCSaxYGmupHyy/ROcyz1HPMe1P7cSt8hR5HM5TZoAYZayupodcDgFQZA1goim5aXhvY3v4Vqx1wvcm54B92EZHe2HWfCP/2lea0TLp+Rzxb/PgkUWZqvD0AcMAKSV+dh27w60akl+n6KidFc3pPFZuDp//jzeeustNG3aFGPGjEHnzp2xePHiQNbtukPaETMKM0R/V4hwFUCzoHDwfe9dE/bvB9FZ/Nwl72CoJtwZ0eTp+aIkDhQsA/z+PXBmILBmFgCgWkQ1Yh7Zeb5qrvT7XOWW5sq/zM/7prni7tdRqmwWNOJPIRTYwJr4Z1tQKNGsCC4rsambBUVlHL1DsS4nT/uuRQX0rRZUMwuGC8KV+WQWLIPXCrEMIsPlmqvHbnoMmHdMdMxmJ5tdWbfx4b1fzXv53w6nCwWFnrzCI4CoSIlDO0EQ9sfnygjn886j81fk7da4+y/K8zwUbtx0u3XWTUD9+kBkmFdzZXeINVfyDwzv332/7YvX1r2G8cvHe+sm0Exy74dDQRMoRFFo1bmilJQP309UtFn8+8eNYwKheMG5aei2oJuqFlE2RrgY1Kvnaddwq0IfMP5NEJIYevtsNht+/PFHDB48GM2bN8e3336L8ePH49SpU0hJScHYsWODVc/rAmlH5GIFcYSC5kopFIMU0jnh5DL3s7IXiyB89OhdzGs31AKIKmquCGX7HliRAQ6MA75fi0a1PQNLjcgaxJT5Rb4IVwDsYk1EYaFy25KEQIfLTfQZUtNc2B1es2D6ZWWHdiM+VyKTJetdrFBcIte0cRSWGFi0kXaL4qmjR1lZnYx8VesJOKqWxiw4pVSuugM1J4h6NVcjkrx9Z/HtizG2/Vi8P+h91KkpjuhdKtFciZ6BGpk3Ah+IHVzubvZ/qOn2+BQ6XG4Uljkxx8cxsFg0fK4MaK7a3JCrK50aOaU5fLnSegAAXGLhihMUjVCvHhBmLRMoTA5s3a4uIJ87730W3Ab1KadTCCm9miuHPw7tLu39S5WEJ+63mh8Wr7nihGFJeanpqSiwSzzdhdWT9XkGHTsCDANERpDfJ1+E4FBEt3D11FNPoV69enjkkUdQs2ZNJCcn49y5c5g+fTqaNGkSxCpeP0gnK6nmIRQ0V0JUJy/CKdGL5lYWrmAtxooV2uUrCVektRWke2tb2+uYruiMy3oDJz7zjGcdcvPqzYnl2hzi+ljDoMss+N8vxRqR4mLljZtF2qEynE7jmqsrVwVCmltZc1Vaql+AdrEuwVc4wz/johLxAJuXJ/hdLBaeVVdfqZiSTGa5/4fWxtl6zYJcnmqaK1+WpYsok4Ny88p8xxiG1xQBwNBmQ/HTXT+hdnRtbN4gvi+bg6y50qUCKBX7D8bHmNHaNBIAkLrHhZxcz/EaNQCzWSxcqYXi4G/LRd5DsFZN7bGsxFGC3478phqfjCtXCF+vMp+m3XsdyMkBSo3uSb/9GdSoAYRbvJqrhyaI/ZekbVBSKn9vFYWXgGiudAhXSh9qOjRXXkGd01zJNWVGtNtgGX58jolSEK6qhmylX7javHkz3nzzTVy6dAlLly7F0KFDDW8WS1FHKuVzfiQcFSFc6Q3FIKWoWP4SiiYX3ieH0IesxbjzTmD/fnXNldJqwdNXLsuOkSa2DnU7iP4mDxIMbr0VuHTJiebNPVJBXHgcsVypo290FDSFq5gYBo89Jt4Y1e5QHrBIphe7T8KVYONmqXAlyP/8BXGfcLgcGL1kND7c/CExWKNYc+V5xskrpZoV7++9Er9C1W1OVISrqGi3LH33+t0V0wPQjFnkra+2cCWaMxXeC7tDWbhiyiba3Dxu6bv4vRCW3aCe+N2y2X3UXHEUeqOqR8cAVk4Nx7hw7pwnr5gYwFImXJ07x2LsWIj8sQCPNlR6711Kp+HedvdCSp9e5K3ShMv9p6ycgrt/uRv3/HKPavUVF0GUaa4WLbajZ0/AZjM4axfXBMMAVrPX5womcUBOuTCiM0I769UEBltzVVCgrJmSHlPSXFWL9/SJ9m0J47pb+Z5l4y5rgrPsGzRaQbhiq4h0pVu4OnDgAJ555hnUrFkzmPW5rpEOEqvXsNCzRiCy6AbtRDogCVKnzqn4XKm8VMXF8olIdH+sCbfdBowfR+iCZs+oPXmybz5Xy899J9N4kQRHqQlJSXP16queyYVDadWYQ2IuqVMHiItVf8USEz0q8k0Pb+KP5eUpa642bZZPYMUlZOFK7eOnuMSNPXtref6QCC1Cs51Lck/Lji3DiuMr8PLal4lmQe+1DO+k/e57Lhw6RK7HmqPbRX+rObR3vknZLBcbW2YWhLdOWg7dRrcUUQ+oKvitMBEKV5rJKKsqtykypyXiEPY5qUbO7nCJBFZDmisAKK7F/6xdC3DYOOHKjStle39bLF5hICuLxdKl8lVdWdfkK1nDTFbc1/4+WZHdu2ZjQscJsuPz5nl/cxHK15xeg/qx9RWrryiQc4KH2Y4TJwCHwcXWL7zouRdun0yYnADjfYbXrsnHjFKCAEdefcvwwuqZs4HVXEm7X0mJ8BzBLKhD8+R2evpEm1bysY/ba1Ltei8MXx+quaKUG9KOmJnJYvJkICND4YIyIpwJ+GLEF3iyy5M+l51ZmIk6Hwv2BbvaBgDwx9/KPlecCYOEmdCzpGbBrCygIWklMeNph9at1Sc0NYd2zh+DL46Qj76tKxhIZRQlc5NUc1W3LhAfp/6KxZctb4+yRnniaAGYNUt5MC0ukQte+QVuokO2mjampNSNi5fKQkBIhCuhj5TZ6hat7iuyexcbZBWLtQ8u1ju5Rkd7NVcwuXDihDcdY/LeW36RfrNgrRrKmiOHS6650kJ39PeyOl3JUtMcq2sHAGDOXHnd4sLj8EinRzwBdQFs2VIWHsOirLmSbVcEt0jjY0RzNX06RNrVyEgGRYVl1zFuXstgsQDXssrSWUqBuvshtf2ThFWzmUHfxn2JZT/Y/kHZsa+3/E5Mq/auS9ub341BIFwBxn15YmIkGkuTC+j7Hn/+4CEWpZJvP5JwJaqr4NmUlnraOS0tsJqrv/6SHGDI13LtpuanyH2s2Eo9zz7CKheuLlxUHltl7xjLoGyDF8TGUJ8rSjkhWzJc9lJkkTXoPAUFwJNdn8TUnlMNlbd9O/Dvv54vnU+3fyoewGwe01dCffHoIfRnkjoqC9FyaAdrhsWiYHYs+zosLVX/qlIbcPfsVTEvKRxT0lx1lixK4r9kJUh9J2Jj5Ss+pUREyCfA3buVNVeZmW4MT5L6XLGGNx7etRu8ECtduZUvMCPk57GIiwN+/lmexx/H/xDXw+3kB8aiQgasy6sBcQoeleiOTRKti4rmqlocQbgqE0jtZaYxl6DZSlT8xQDx88/LVU7H1clZINfa12FvLEsjTy9lO8EZOuP5DHw9yruHHPfOx8YwIs2j6vNlXKLAi7IVXgokJLB44w1AquGKjhH+Xaa9sQKnTpYd7/YlMLET0GCnOEOTExmZ4nu3WDwLQG5pKF+MwO2jKORMN3I8OrV3XVGgLvO58gpXilkQIcY36+zdPzc6msXJk+L7/fFHBhcvkvMBPL6OHhg0aczwKU6eVO5DFpNF+R4JwtWoUeK/TYKPGdJKYDWzIJfGVup5l6Mj5WNf5hVlUyNJczXLs+gaEWFUc0UpJ55e+bTkiKeX5av7cyKmbDCMsJCdR5Xo1QsYNAho1gxY+qdEgnN68ip1iIUfh10w4JuU3wKW8NUs1VzdeKOCw/qDSQBYTaEy7ZLygDtihPZXtXRQIU2K8fEMIiVzgJJZMCtLPJCEhWkHOo0IF7YT5zCsPEEfP+HG5rRNomMOpxtp543uc8YiNs6jNapbRyy0TJwoKJtxo7gYGDNGnoP03nLzXbiaJfS5KqsT4/KE3eBLFmByIkegZFQLIpqdRRCuyrRj3BYiuXneNMIySQj7xJ/Sr30SBYmioI2TSi/ihZtmAABsNnH8LiImeYJIayQYhvEK2WUCb5jVgD8r48aRI94/9ZoFa5VZA5s1E/ed3pwcJNB4WCwMRt6mnh9jciHlH3G/5cybJOHQyHjlk3DlEgtXJSXGZu2m1ZoCUBZsS+1ukT8TAIBxY+JE8SFhH75SJojExTG46SbumbNo1Qr4WiBjC31NIy2RitpQ8lik/IFCMlGqhmKAV1CPiQFqxMvLe/xx5Q9X6bj78MMM4uM9v5XCn6TuZpGaSjxVqTAkXDmdTrz99tu4KBXNKQFBFjG4bHC7dg04evWo4nU3lLlcVY8kRw7X4tw54OyVq+KDDo9EkV8sFX68A6zTpTJ5E8YC7xe1ZxnyBx+o+FS1+ks1JEFBAXDvGBUnCoYVmVNJA7DUEZO0x5fU9wVQ1lxJHYsJGnQZ4YT55do1Fi6lCaPNMuCBEaJDx467sWWz/FVWXc3JuHkfFGm8mUuXhMKVOA+7QLguLBa3/+V0l8BpmEF0FCdcubFnj6cfywRmk1P0nGQrEAWfsQP6yYUrLsCjvWwfvFKbtx1OnZIll+TtHfiVoo7L6nT0Tv7n3Pfrw8R4tQ8Wi8ckI+uzrFhwIhHB9wNOU6QuyByceBAPdigzq5lcGDECyMz0/Mkv9NCKgVRWRFwsIzjEIJKgTbWYgUaN1OvEMi5s2iTXXCmhtZpTSHGpUsBglX7Oa6707+QAAGPb3Y83+r7Bt6+S797vv7PylckMizNnJHUU9AfO3yg8jOE/irln/sQT3muEgZQjLBGKprJ77iI0sNQMqCFTqjq0s17t9ogRCsIcwezIBVuVjrvCFbBqoU26dgXS0tTrHeoYEq4sFgs++ugjOJ0GPQMpvlE2GF+9Cmzeray+4jpsbFisYhpNogSznjMMtWt4Bqar2coO5Uq2fM85+SH+K4Y14Z13gLg4ldWAdQ5j82blmDrnz8PjYKoIi3r1gLfe8vxFEq5eekmgFclhvVoXAR0bN5EdU3IUz85hJemAXg16qdQRsAp8a7h8LRagqEihbeselB9j3EQTkGp4AMbNCyKJCZIBWvhcBQKB0wk8KXDry80Tt/+OXU7vtSzj8bsqy+/IEY+GtH17yWQoEa6kAq4wNlGDRPlEYjF7I5svWsSAFTgch4WrzypFKmZtIkJtHDzP1yRZ1TdyJHDmjKQfwKvBU4JbHfj0M546iTWactrXaY+BTQaW5eu55mjZ9xe/WbWOlWSAsmbmiSdY/nnm5Hj8sVRhXJDO5BbCxwl/TmH15fnz8mMOF/ldX7JEv+aKq5vWQoehzQdj+oDp/OSv1D5nzrA4fVquuTqq8B2cleXxmQQ8H16xMd73g2PgQODgQfEWYFeLr+JQ2iVinu3bmQn3I9dcXb7s/c0fJzi0K2uuzGjQQOHDkvDR8PU3bqxeLfe5EvYhxcC9Ze0hFVIrG4bNggMHDsSGDRuCUReKDE8ne/RRYPsW5a9Qfl81hkHa1DQMaz7MeFFRAs2VKwxNGnoGpj0HbLLVJ9L6Ec8QTvEvmtuMxo09PxU1V0W1AXj8j0jceCPUhauyF3T69LIiSQ4XgkGtuBgoJuyS8fbdDyiXIeGHH8R1rVULGNOOYE8TYGKEX3Ke/0dGAlevGZj4GTcx4rWqWZBx84Oi3PeBJf6+dk2SzCz+bL+c7p1cn3mGEUxKLNLSPOZtTrvCY3Ji0CCP9hQAsq6K2/CBB733EG4lCVdc3Vk8+qhFNNDHaXxrnDsvHviHDgVOn/aY94RhBkQTjsTcbSKMoDd2UBCuVD8GPLRs6am/iTGph36AYNIvE9oyMjx13XC+bHyOuaJZnqd+4nvihHzhvdlsDMKtGtOFyQnpBxenuSJ9kBAnarcJzz1HGD8U2u6335T7+YC+nHAlHmMahXUkpueQ1lVx1S3Dyu4XYMGynkDAQoYNA2rXBpYu9WomhVpPjnXrPPvuSYWSO1b0I1bh8ccYNIhrIK+XpE71yxZbksyCQu2w9ANxQ05ZXzI5PMKVDjMkAEx5xo1bbwWOnxQ/G16bDe3AvXPmqJ4OeQwLV8OHD8fLL7+MF154AT/99BNWrFgh+kcJIIKX5ORx5YFW+CI2jG+oGORSlTCvZBEVHoZqMZ6v3mKbDY88IqqU4KeKQzsrdyDN57ZBYc24/XbPT8UgoSUe5+FdCsIVAE3NlZCjxwlaA4EmYckSFseOy8sKN4fLjilx+bL4+ho15FH2pUQK99Eqa9qCAlZRqCSipLnSMAt6hSup5krw4AR90OGAWPtiET+7PftcfPoBAxjvpK3ST7hn2KcPsHatOAwEAJwWmPZk9YRA+8GVIaif2pcvwwDffifsEyxSUoAWLYBWrTwb9nIrHEU+TJJ25hVXalpcHe3ATeD8voAMgxEtR6Bj3Y4YVpP8scRPTmX5pqcDi34w0G/KUNLMCLUcNWqoh/bwZCTXXJHM6hxE4ZE14/ffwWtaxHnL+e03oFBBy1uzWpnmruMPwKD/8M8oKlJ92pO2h7Kmi1Bu2bP4Q7zWA2t2lNm4yuoQZhUsWJD0HbdbfzT5iHATRt8wWrteBLjxISfXm/78eYVrO/yA6tX1a664Y7tTxc8tKkqH5qqs/suXK5yuJBgWrp566ilkZmZi9uzZeOCBB3D77bfz/+64445g1PE6xtvRN23QHx1a9+apCsRGWxEfW/YSMS4sXOg9JxpoVCcU4Jh4CzRkXvGqmGPLtApKmquuN3nKz8jwTbjq1l38wh8+ojwAAMCiRcCHH8rLMrRIQDLIxMQAibGJqpc0qC/2d+FYvNig5oogXJ08pU+4slokg5yCWbCkBGL/FYlw5XkenmvrJypPHvJrgIsXgaQkyAdqwbVhBAcefoDmhSuyYEhi+XJyG58547nXjRs9f1/kLDIsg0celWquSBOvRHPFPRsFAUF8pdd0FW4Jx65Hd2Fiw4nEtLwQUJZvejrw0ASDpk6IhSaGYUT9cORIT31636JtTvNocsTl1yv7tpifJA/YR9ZceZ7x+vU6Kl7GHyvI9xwbJTCL9pmBGjU992Ixq2tMlDR58oQsZIJM2f0/KI0ycTenwRYIV2XlvDSNRZs24uQyDa9KXWVjlLTfCzcVF9SXM8ELg6sqCaqwFiM3V7/PFdcOWRINfLRAuNLSzFZ2DAtXbrdb8Z9Lc7kMxRDCTqsSs0ZthZUuWv4NxHlt+mHmMMTGeJ2RAeDee4H33pOo69U0EiyDc+fEdf5pCWcW9HY7JZ+riEhPQXkqsbTUhKvZn3rqZjaXbXtBqqtJrLkgDRLhFv2aK2kZDAPUia6jkLisCqSBm2hu0ChXkv6TT4Cnp+gzC8oHObJZcMUKAKXx3lNOiU8P49VcMRBO0nIzBY/gGXqcg8mTFSCIlC3Aaxoru06HAOO9WD1terrn/6cEy+1r1xQPmREk2Vv27LR9rri2EmqutJAKlh99BHEfdFnx531/auajJDSxLIu6dT2/w8IYfTtySN7Jhg0817Sv0x71YsRaXCXNFUAQTsogaeWnPEPu5xGSd7dO2asYGWFMc6UcBkP+njZspPDOJZQtXeU0V4L2NJtZtG0rTl5UrO/9ZxjScyG/bywrFp64aUMYm+v4cZbsBsKwuOkmoGeDnoRzyh+uuXniPt+qpbZDe5NmngqMGEE8XWmgoRhCBLI8JNQgKL9segIn/nbvb+QTcReAB24THQozh/GOwtxL8ssvwGuvQSLkqQ8AXHTnzZs96vuv/+c1C3Ioba8THuEp91q2tnBF+gKuXceFmBiP/8yxY1AYAKSTnX9mQdIz0loRJdUaeP8wqLmS1P255yA7JrtGSbgS3EezFt56vPCCJA+L5NkJzEIMw8gFH2I9JM+A4C/CF0eYjKWmMWPtJiibUEdOuAqPKDMnRTEyQSSxTDFZqzaL/v3ldQYEwosezRXrFU614No3PEJ4H977N7FhuK3VbXii8xPSS4n58FkoCFF66qT2wSMthzi58h9e5D5D0sqbzOS00neXa1szyVFOgMznSum+CZqrdu0VnrGTk8K9PldcvizLIkwyTBTrFa4g75NKmiunEzh+XH5861Zv+tw8Fr//Li8n+vII9OkDdE3sirf7vy3JX3lsvSoJT8OYvH8raa7uuN0zH8qCoVYyfBKuNmzYgJEjR6JFixZo0aIFRo0ahU2bNmlfSFFEGGGZo1sPsnlGih5NlfSrEfAEuURkjuy40+0UTIzyIHAcJouaZoTFpUsM8vM9/jR33w3UqOl54cIEZiglnytupVeOvHpeOOGKoKp2sy5w+4kfPgyy1kBqQvJXc0UY+H1TfRPMDVrpVVTzJExmNxo2ygNAmuQEX7fSvqW2rF3g0MzA+0X9zf/ceO89kLdyMkkFQ2WTBlG4kpkFJdpINQTCzjCCWxMXysFedsuRkQxBq+G5xwYNgKeektcZ8PjFAOomO5LPlRbcc2sg1JZIhCthOim8ICcU8AXvt3Qzc12BaiXClTA/6Ucg0eeG+/CqRlgySMgDAFwKIWGU3l0tR2q9wibp/eI07jKcYhWnxex9P1iwyM0VJ/94lr7338SYZPW9pTf52uJiSOJysWjYUBLXDiy++KLsl+Dw7bVf5HeqGNFKrFLqdJO8vFv6lLWN5INC+PyUfK4MW15CFMPC1Q8//IDBgwcjKioKU6ZMwZQpUxAZGYlBgwbhxx9/DEYdrwtIwlViohtr15b9oWJS0BNpnDRA9OoFPp6VkPN551WEKy8REeovwfTpZj5gHACYrZ57iAj3vlSKZsEIubOlDBXNlZt1o6knBqAnwKKmWRAworm6o7Xcv3DefHXhirThs3DyEfuz6dfA1G/gxrBbScKVctvd/6ATjZvkyuooLdvNutGli+DcHQ8p5tmgoQu163jKNDEm/n7atWPxn/94VkGR6vX2O2ThwIO6cCVckUi+XgVB2jp1gBkzxKdTUjx+V7aySO9ms/rE3LKl/Njv9/7Oa0pu6mzM50oL7t6josmaq7ho30IxkMoWCstqdOqiLHxLA4FGh0XLzXzcVkyE1a+AwpZFCs9cprmCt2+qIb1/I2bBps2UNFdldSlLb7FApLmSBryV7tuoWFeCWfDvv8na35Mnge++F1tDLl6E+B4Yll8VLFzxOOFBb1tKfbwWLpS3f1g4d0xcF+Hzoz5XEt577z3MnDkTS5cu5YWrpUuX4oMPPsA777wTjDpeF9Qn7Etqc9lwc98y4UNNcyV1aNcp+T/2GBRNFdyAUidBudxiJyF2gQqlNm6ZuQ6zYDinyla5l65fASCb3lysiw/3oGQWbNteouUwoLlaevdSXHvpGnY9vos/dmMHeRnCAYT0XIgTFsExWI2be7tQL5GUXt2UzMWwkX5BCr++WZDNBCSefsbFq/2Fgz7XP2++mRzpvdfNKk7oWporiVkwPMJAwEjJBwu3yEJIv37ePTTDrHLNlZBOnYAvvhBrDm5rdRvfDmpRxv3xuYqKJgun0RH6hCs1nys96YSMHC3RXAnug7RbwXe3fyc+wAlVbvLEK/yQ7BgzpKwQBbOgwrurKVzpNAu+8aZcwxwRqfDeli1qeOL/POkbNBC/H4sWyS5QraOwbtL6WSziazmz6SOPAAckQpy8LJYPwbFmjTffG2/0/pYKV6SP+XXrOE2yRLgSRGxX1Kj6uSArVDAsXJ05cwYjR46UHR81ahTOnj0bkEpRPKw6tQo1Z9bEug0O1clW1x55BO64AxgwiJwvNwBFSgcLHZvBKlFQFopBOLh9O/pbRFujMefWOZgxyKs64CL8Kg4yMelAw20AyJPu9A3TeVX777+D2H5JScpaEg4lzZXVbEWNyBromtgVCTEJAMgmC2HdtHzjxD5X+gcYpa17tPoMd420/b77jhWla9RIXz1cbpfIZ4h7zsK6LVkCVKsmvq6TQKNjlkwMCxcaMwvyQQ8BJNRTbsMlSyD6sGDh2UORRHFZsOywMIJ/C3d92T0++SSwYoW3XIZheI3lDwd/8NSrrL+o5WNEc+ViXfi//+MK9N4/99GhlZeaGUz47PQIfGoCpNo5bxnc8yQ/O+EYwfnCKfVz6UcXdy9awpVes2CzZizatxcfY1kWLVooZNzyb/z3nMdx0Wzyvh9u1o2BA6WLhXw3C8qirJfFsTp4UJov135izRXninFJELdUuPBGOiYKxzV5+BVWMS3VXElo2LAh1vK2Ki///PMPGjZsSLiC4g/FjmI0vvEiduxUniil2h+ihoQwwFoswJw56pqrsAhlnyt1CIND2WQm1JT0atgLeS/nYUqPKXi598v8apTTZwkvvqjyXl8t0ubIvx/9HSI3QIKGTvgV1X+AG//3pOSLjzFp+mcAYvW+FOG9kvY3VHaW1a+5YlmWLFCrDNDCa6Saq2rV5T5Xn32mXQ+n2ykKaCvVxvDVktxyZJS3XVySiPxt26kPxlKneVYgXBG+AXnGjAEWLdbWXAHeXQJMjL6JVySQgEHjeI8KdV/GPgBA4/jGODjxIC495529/PG5crNuwYTuLVvv9jJKiyqEfUoaokEJqQAlvIbflkehbACICpfELZNwb7t78fGQjwEAEdwcr9MsyKEcX6ksOwWzqBQWrCxgrBtu5aDLgoVDwvb0x8eIZBbU2lPUezErPwYWZ896AtLuP+A9Kuz3Ms2VoP5cuhkfKmiuBGZBredQ2TEsXD3//POYMmUKJk6ciEWLFmHRokV48sknMXXqVLwgW05ECQRu1i2aNKRcLbqqeE5P3iS4l8RkEp+vUUNnxqRxuMwMY5EILEIBhpsQ6ieSXnxhXt56KWnqPvqInJ5DeO8fzmRx553i87pWRwkgmWe1NFfkSZRFh47B11xx9ZEKLcK8uDQerY56nVysi/ehE/roaMVhE7ULo5yWJFxxxyKj3GjRglV9T6TUSRBP9qRH0aCBd0NmhmF0CdviPBk0qdZEdqx9nfbEGGi++Fy53C7ev5CkuVJCyQdJqezy0FzVrmnGo496aqdUB07zZw1THyNkmiudPlek80pCtPR5sSyLhQuBBIlyMr6aJD+F98O7v6DvZsESR4nob6XVlPy7xsgFrkaNgEU/CA4LNVcWZc0V13b33ee75uq6dWifOHEilixZgoMHD2Lq1KmYOnUqDh06hKVLl+L/eN00JZC4WJfq10hmkTjiXP04uQOX0sBI0qYA3pekUWOBEMOSJyASNarb5FqxsoE/MkJ5guIGih21JqFFx6v8y17H3EqUrlkL7YGan3AEZQsRfkUJTVr8JTpvlh8kCYOCcAAhOuMK8ym797ffAR59zIBjNpQETOVBqshRxJvQpIOccBIU5auxAW6xoxiFdo8XrDAUg9ZgyfdBkxMIF++hKbxWzeeqWXM39u93iuqrVa5wpSrLsiJzJaf1zM/3+v2ZTPqimUufRcM4sUZfTTPii8+Vm3WjWTMuI/3ClVp9ALlGVM9qQZnmSnAfegLyWi1mfP01FD8MpELJ/PnAY4/rWy2o1yxIanslzRWHUIvYu7c3jAdHzZryMkiaq3fegecjT6dZkKS5umHeDaK/w8LkwpP0Tjg4/z3P9k9iDSyHmhmSf+fB4qWX5KsnlXyuJnadiFf7vEqoW+XFp1AMd9xxBzZv3oxr167h2rVr2Lx5M0aPHh3oulHKcLqdumJZcTzRRT2ujRClCZ97SW7s4MbEicC8eZ7jev25zGY3Jk4UrHYEeNOc1aLc7bhys0quosN/nsQ//3jKq1FdfM2KP731VtruRxTgkSRcCV50j3bQuAOvMB3pGQkHEL1mwXHjWERFGdBcsays7NatgYcfUc4j+VQyf79SoUW4gpPLt7gYsr0EpRzI9NoRhF/UWn3X5XbhrrsAtJF7zmtproSDucXCinyutJCa0/v29awYTE4GOnf2mAnz871xgEyMPBo2cdKVmAWlk7ya4OSrzxVJc8WFKNF6Z6WhGPyJc0Uy/XGsenAVmlVvhj/u/UMxT+6euvVQEK4kQslTTwEvTdNnFjydc1pUBkfrWq2JdZCWK0Xot8hdM2v7LBzPOi5LK8tPQXNVp44nJuDhw8befyF5tjzxeYnZT8rY+7zt1+kmshZZKVwHIPG5Enxofvgh8MKLymZB4fssbPPr1qG9WbNmuCbbwRXIzc1FM/7ziRJIhCYcIdyXa6uaYq0O6YtVaWBUmviEjomffw5MmmSkxl4GDgSeeYbLtMznSsW0InyJd1/e7d34VfpCw/uF/PWor4l5hQvHVkIoC+G9u1i55kovSuYvs8ksGjSk5iHhtdLfUqFXbWIjmQWPHgWGDlMXNJQc2oXCFZfG5YLmxsOi+rMu/u/c0lzV61ysC4sWAS+8lqNYR1I9Aa8JhCQcayHdeolhgJdfBoYPB6Ki5OFRTCYGj3V+DJ3rdcbrfV9XzFfLV4moufLT54rXujHaZhcperRxekMxqPlc9W7UG6ennMbwFsMVr+fq/NVX+jRXgPIYpjfO1TM9nhH9TXo+pDYSavaE5x/4Xd9m76o+VwYWtOj58F6yROkMi48+Fgh3dd2ic3x11DRXBJ8rb7uISxNprgQ+V8RgqJUcw8LVuXPniNvc2Gw2XBIuL6AEDJebbBb89d5f8fItLyP5/mTRcSOdVMssaERjpkS/flymcod2KcK62112xQmTq3dibCJqRdUiphH6PbRpR9BcuTU0V3ptoGVIB0muDXOn5eLKC1cQbY2WXaOk+ZA+FzVTBsuy2JuxV7M+UvhQDJLJ5r1N73nTlD3/G24A9PqBAJ5Jlru325fejsxCr+laWi8360ZkJNCwqTygrMj0Qug3x68d5/OQCqRawpbILEhI69UGec/FhMUg9YlUvD1AHKVaeE9a5mVVzZWPPlcA8P77wE0jUvnznKCi1Q/0CH966+Rktc31ojwlbcH1xZhYfZorQPk5E/cuBCH0iFQb6YtZUJBndkk2sVxpfkofZYAxv6N8W77qeRYsxowB3n0XuPMucb7vvc+CEfTvuHhyWA/h+KPmQC9tJ+m9KWmulFaoVmZ0r4VcsWIF/3v16tWIF0SHdLlcWLt2LZpwIbEpAUXJ5yohJgEzBs+QHScODko+VxpmQV+FK+Eg27EjVwltzZXwJXa4HMQo0oD3C9nMmBWFtdhYj8YtMxM4E+kGxNpy0b0JVfwc/poFuXuJj/C8K5rmGUF5Ug2AiTEpCsLbL26X+d2R6iOkYVxDsG6y5upo1lH+N1fnwYOBjz5m8WKW6i3wuNwu0bNcc3oNxnUcp5gWIAeU1dJcCdMZ7aukuEtCVqwAbrwR4IRKh13/e6UG0ezkp88VALzyCvCf6d4lklItAuD5GLlccNlznOCDJC1XqoXTQs3nSg/Se5JiRHOl9EEi24ZHMn4YcmjX0YYAcCbnjCw/Nc2VES3svF3zVM9z+b/6KrAljcXv33rPTZvGIr1Q8IxNbtStW7ZxtIJZUNo+pPbnBV/ChxSHcB6oalorwIBwdfvttwPwNPJDDz0kOme1WtGkSRPMmjUroJWjeFDSXPnzhcmhNTD5uil0pNkb+V3qD6KquVIY3BkwWDt+LQZ9Pwh1o+vyE7LFZFEdwDlfsU5fqodicLldPmuuFM2COpYaEwdtsHKzoEpdSIIVqT5CrCYr3G7t5+Gd7IGHH2bx4keKSWXCoeK+iRK450DaCknL50pYTyXhU+0aNdq39yzieOxz4JurQKPG+vqDVPukVzME+O5zpZaXkEMTD6HGTPGSX6VnIxWs9Di0q/lckZAFwCx7xorCFcHMqpRW6SNOeB9mxqwraCjRLAhBOBOjq0g1NFdG8Me6IHUpcLNutGlTJlwpmAV1+VyBrFWMtHrnBeH7bDVbA9YeoYJus6Db7Ybb7UajRo1w5coV/m+32w2bzYbjx4/jtttu086IYhiliUPXXl8q/Hn8T6w7t454zlfN1cCmAwEAVsarkmcYYPp08GZBtXoLX1yr2SrSXNWMrMn/5jVXEr8mJYh7kkkd2n31uVL4AjUSIwuQ+ywJ8eVZq92P0AyqpRHif2sMesLzQrMgoC4scM/GH80VyS9R63nqfd49e3rSRaosdiOtUuSepx6zoL8+V2poBQIN5MbNaj5XeuDuSc8Eq6Qd4dCjuSIF4VTTLErLJ2mu9PQrTc1VAE1jaitZpcfcrBtJSVwlFRza1bSbUpOt4D5G3zAad7W5i/9b+FGnZyVpZcNwiFQahT34WEwW0SClZBZUGjz0+gyMWjJKsQ6+Cldc7B7pS/zGG0DHe124fal+h3aLySLSAghXonDCh5pZUAjpPmQO7T6uFuTQ0lzpHTBZliWaBfWS1NIzOqo9O6EDv5bQIqyXGsI6q2mulPwwpA7m0rSqQiBB26eFkbANgHFfHJ80V374XOlBmC+pLNF5H0KT6IllpZanmlmQb0+dZkGlcUE4/phNZvnz0elWIQpBYNB9WdPnKoDaGzV/QKGACHja8skngV9/BVq0c4LbLVhk9lTQXJHuifv/Mz2ewae3fiq6Tvg+R1gieK3ndedzJaSoqAgbNmxAWloa7HbxcuYpU6YEpGLXI3Wi6+BK0RVMu2WayKlYySyoKFwFwH6taBbUeOm5AY2UTigQaZULlAlXAi2A8L64CcVsMqN2dG3VOgEKmiuJQ7sUo2ZBJZ8rPdcCIN6fkbyk+ag9K9HegirCrvSrVg3hxForqpbuOnP9gqS50rtdhtKKWjX0pvd3FakuzVUAfK6MQiqLJGxw9dMVisEtDczqm+ZK7X2Uakf8MQuSNFf+rhbUg9DMquazFAjUxgGhaZOrS2wssGMHkFXgxI+zy+qroGGX1lVJG0dqU+HzCTeHGzYphzqGhau9e/ciKSkJxcXFKCoqQo0aNZCVlYWoqCjUqVOHCld+wE1O0lAKSnGujAxcRgc5XzVXaoEjv9v/HQBgy4UtitcLX0Kp5opDOCCYGBPiwuOQ+kQq7lx6J87nnSfmSzKrlpdDu7DeStdq1dfI4M1/NQbALCjSXGkI1sLBsV2ddrrNgrzmiuRzRVjmrVRPaZtpmjH1ahJ1aJNUVwsa0Fxx7a3neWv6XBH8XoTjAGkyE200DlZ1UiVhWHMlaQtfNFdKz1mPWZDkc6XXLEiKcyWsnxbcOE96DsHyO5LmS9JckdKq3ZNQSFcTvKQI+1q4JRxFjiJiHSsrhh05nn32WYwcORI5OTmIjIzE9u3bcf78eXTp0gUff/xxMOp43cANTNIlxErClRGzoBHCzeE+C1dqE8eK4ysUz/HXS8yCwuPCc0JVNAB0rtcZ7eq0U8yXdB/7M/fzv0kO7XpRitAu/XIm7vmoYG7wxyyo9UUPiCPSq2kSix3F+Hjrx8gszNRtFowJiwGg7qchhPe5chF8rnQ+E19WCwrT/3ToJ81tpIyai6TCgJ58pP1aDb0+V6JyBPlyz0v4XKXCht8R2n30uQqI5kqhX4uEK4LPpi9mQeG7rsvEDIYXrojm8EBqrtTMggTNFSmtHlM26Rj/LhDaT/h8quImzoaFq3379uH555+HyWSC2WyGzWZDw4YNMXPmTPznP/8JRh2vG3jhyuyncKWg1tdLhCXCK1wZiHgtrBPphVOKO0O6HhCbBYUoOZKqTTKkcyeunRCd93n7GwUzXMe6HXVdTyrPH7Og2he9UGhW2v5GyospL2LkTyM1BR2u/5J8jdR8eVRXC2o4Y3P4YhaU3s/In8g7PRud6JTCh3CovYtcG+qZbEg+V0rmK75swqIJJdOr9DpdZkGjqwWD6XOlYBYUTup6HdqDYRbkhCvpTgGAMe1Ng7gGqueNaHCl2nwOLa0xIDYdSx3aSX1HGqFdNahqJcSwcGW1WmEyeS6rU6cO0tLSAADx8fG4cOFCYGsXRObPn48mTZogIiICPXr0wM6dOyu6SoY1V8GKDRJuUdZcaXV8NeHq2Z7PAgBGtByheL2aWVB4juQvoubYq7kFSyAc2gVts/KBlbip3k3i8zrNgqQgor48a7Wo/m54hUk9qxp3Xd6l6QDP+dtwz0S3z5VanCudk4ySWVBtfz1p++y4tIOYTpdZUOXZSq9TMztxAqaefQFJgojaZtDSunDjjTT2kGKIl3KIc6UW+FSqueJQGpMUHdoFx82MGUObDxWXo/PjVBjGwLBwBYbfnockXBmhfqx8L1kliGZBJc2VTrMgSXjXpbmq4nGuDAtXN910E3bt2gUA6NevH9544w0sXrwYU6dORfv27QNewWCwdOlSPPfcc3jzzTexZ88edOzYEcOGDcOVK1cqtF5KX60Ot8P/1YIGBrmf7vrJZ7Mgv5SaMOBxeUq36xEiWy1I0AJIfa441OIcaa2o8ktzJTHpmBkzbm1xq6FrAfLEx+GLWZD0DIRxhPRqrvh8BUJG7Sj5IgKpScuoWZAU1HPBngW660bqq9UjqitfY/AL2ZfI3aTr1NqCMxEpbd0ihORzpWYCkpZNEq6kPld6TUPSPPUi87lSMwsqCFVau0yoHTcxJsSExWDByAXE83zZCkFE+XrrWLEszS9QZkEjWi6iWVDJ50rnsxf5XPmouRK6fVy3Plfvv/8+6tWrBwB47733UL16dUycOBFXr17FV199FfAKBoPZs2fj8ccfx8MPP4y2bdviyy+/RFRUFP73v/9VWJ2EZo1gmAWNcHPDm/32uSK9IHqcdWVmQaHmSsXnCvBPcyV08DaKntV5gDEHaqNhBaTXK9WHG9CEPma6hSvBV7raZEPSMKg6tBPMUxw/H/5ZlMeXI74k5uFm5dvfKOUJALO2zuI38pWy7Ogy3LH0DuSU5ADw3yxoxKGdm2h1aa4IgojWyjNh2ZwJT6S5Ijh4c9f5pLky6nOlZhaUrL7UMgvqcmgva0OhtcCIEO2zWRAMP877axbU0z+V0gREc0VIZ9Tnqipi2Iusa9eu/O86depg1apVAa1QsLHb7UhNTcUrr7zCHzOZTBg8eDC2bdsmS2+z2WCzeb8s8vM9+zg5HA44HP4vHeXyKLV5TSImVvyiljpKiXFUXC4XsQ5Op/zr0eHUX1e3081vjeJ0OUVlaL70rDedtG7COCZKbceVCwBmmEX15q5hWZY/zoDhj0snV2EZWsKVzWEDw8onQS4P6f9J2B2eQZJhGGI60gDndrv5tNwA5HA4/FqWzOVJeubCCZn/unTrG8htDhtfT2J/LGt/Ybvx5wR9VdqHbHYbHA4Hcc9SIQ6HA490fAQv/fOSbD81N+vm219UpsIWNy+kvKBYxp0/3wkAaBLXBDMHz4TTVeb47Zb3W+5dEz5Hvh+UtQMXCZ+HlfcjbvIusXs2orYyVtEYQ+pPLqenvVxub9tKNQ8Oh1jr7XQ6MabtGCw9shTP93ze0+6C98bldPHPweVyify63C7tDy2poEAao4T3JH3mXJuR+i53jruGa3ObXa754c4TEXQ/E0zENpDWmSQ8OV1O/jrpea25gWVZvj2FfUfv9cJ0ej7E7A47TIxJ1q4Oh0P03gj7krQfK8GPCwLXDbvDLur7pHtkXd4H4XB60yrNa/4SjDzV8CmIqNPpRMuWLUXHT548yW+DE8pkZWXB5XKhbt26ouN169bFsWPHZOlnzJiB6dOny46vWbMGUVFRAavX6n9W878PHTwkOrdn7x7iy71xw0acDD8pO25zywebLZuVwx/I6rJqNb+/3KXLl5Cc7N0Y2ulQV/unnU/jf6ekpIjOnb7k0RScP3MeyaXizaY5MjO8W7nk5ebxJuj8vHxs2rQJgEdA3rlrJ3+cq19WtnjjO2G9S0pLVOu9b/8+hDGSEBhOpygP0j0BnrhvALB3317PARay64TphBw/dhzJ2Z603Mu/YcMGnL4q1qoIBXwtrmZdRXJyMg5dPSQ753J4BmKH0wG32TOYHdovT0fi33//BQC4XW5ZfDsAKCwsBODpI8nJycjNyeXP7d27F/nH8uFknbxAYoIJbrixeetmZMdk40qWulk+OTnZE52f0Aftdjs2bt4oOnb0/FHklubK0mqVwbH/5H4k273tmJmRKXuuBwsOAvDcO3cu0+bpw263G8nJyTh2RTyuXL16VZZPcUkxAOBixkUAQMalDFEaUr+7Zr8GwDMhcmmFH2nXrl1DcnKyyBd21apVuMd6D7q16oZmec2QnJyMq1neVZIrV67k63v58mX++NGjRxFniZPVQUp+gVjoPXzkMJKvkN/1lJQUnC4W9/OMDM99Hy08KkvPtWdqnmdz6tzcXCQnJ+NAwQFi/ls3bSUeF45RtlKbJ49sbx7bt29H7sFc0TV2m7y/Hz16FFcKPX22uKiYP15cXEx8/4WcO3cOkVc9W8GkX03HQ/97CF3iuqBFVAsAwImiE2qX8yQnJyM3L1cz3d/Jf8PMmGVttWr1KlxzXOP/zrzi7ePZjmwAHqFJ7X5SUz3Pg2VZflzYtGkTLkRe4Mf8M2fOyMb8Epd3TD5w6AAKnAUAgLQLaZrtVxkwLFxNmDABjzzyiEy42rFjB77++musX78+UHULCV555RU899xz/N/5+flo2LAhhg4dirg47cFGC4fDgZSUFPQb0A8o6/ddb+oKeN9/tLuxncd0c1587YD+A9CsejNZniWOEj4vjt69ewPH9dXpthG34cLuC8AloG5CXSTx+yEAlqMWQGWeb96sOZDl+YIeMmQIrFavun1tylrgKtCiRQsk9U8iXv/Dsh/4DZbr1qqLLl27AGeBatWqoW/fvsAxwBpmRecunYGzQPXq1fn6vb/wfUAgv4jqfdwCqMiF7W9sjyhrlKiNw6xhfB7cc5LeEwDEpMUANqBjp47AeY9mR1g2R9T5KEAyRrdp0wZJPTxpw46FochVhL79+mLvjr2Ad8yDNcwKqMuHPLVq1kJSUhLO7joLXBKfiwyPREFxAWDyajm6dukq61sk+g/oDxwFLBYLIiMiAcmHYGR0JGADwsI87TYzayZQNud07twZY38fK0pvNpnhdrvRo2cP9GnUB5/88AlQqFz+iBGehRDWo1ZZHzRbzOh1cy9AMCfnmHO0b0pCUlISsM/zu0WTFkganoRzu88Bl4B69erJnmv0+WjgNBATE8OfO5t71tNOZguSkpJwaucpwCunoE6dOvJ8zkUDdiC+RjyQD7Rs2hJJQ5NU+116YTpwxLM4gcvPetzK9/MaNWogKSkJy/5aBnjmSQy/dbjMn2vWoll8uyclJeHkzpPAZaBeYj3PR10O0LZNW9SMqikal0hERUcBgnUJ7du1R1IX8b0K76netXqAQI5ISEhAUlIS4i/EA6fEeXPtiVMAzgJx8XFISkpC2NkwgGDh7d+vP3HM48YoAIiJ9jy3nEM5/L3dcvMt6FG/h+iaiFMRsr7Z6oZWuHLhCpAPxMbG8n0yKipK1I9ING3SFJ0bdgbOA8eLj+N48XH8lPET7P/xDBC1LtUC5N/NMpKSkvBW+luaY0PS8CSYTWZEnI0QtdXQoUNxseAiUCb/16xVk+9LaTlpwGGF8Uxwb507e8Zik8mE8LBwwAn07tMbHep0wLp/1gFXgebNmyNpgDiPUmcp4Pk2Qdu2bT0fQhlAo4aNiOOnvzgcDvzxxx8Bz1cJn4KI3nLLLbLjPXv2xOTJkwNSqWBSq1YtmM1mZGaKN7vNzMxEQkKCLH14eDjCw+XOpVarVTbY+QNj8pqkIsLE+yy54eZXaIrqFhZOrIOLkauJw6zaPhwcVqsVVosnX4ZhRGVo2feFK0BkbVR2i1azctsJrw+zhMFi9nRRE2MS3YPZbObTc3lJzU3CMrRCSjAmhi9LKQ/iPQH8s+H+L20zDpJJVVh/vgyLFSyjz1RHhPHUc3fGbtkpzs9D6HMVYdW3r5fFYinLnryJr9C/wmq1ip4lqf+aTWY43A4wJk96rXvm2kkp5pDwHQKgGFBWTxkAEBUWJVodbTFbZM+KaxOuzUXHyvLj+ioH6Zlz2N2eyTXCGiFKQ+p33DjhZt3Ed4BrV2G7hIWFyXw6he1utVq975zJG6bAbDbLriMh7eOkNhPdk0X+LpHaDPD2K/6asjaXPncO6TjKlyu4D+5ZCI+FWcPk7zgpPIPJ63so9R/SmhvMZrPs3oXXmS36/JGsViuev/l5jFs2TjWdxWqBxWSR5WuxWkT9lQUrq4PSeCa8F0Dsl8c9d/5vE6EfCJqUMTHefEzq5VUWDDu0MwyDgoIC2fG8vDxNn4lQICwsDF26dMHatWv5Y263G2vXrkWvXr0qrF5C3xB/g4j6w1/3/SXK2+cI7QRBQsk/QYh0LzligDpBwEiho6nakmZfHNoNx7nyIT6L3iCivjjbLz64WHaMF64E+1XqCcUAiB211eIpce0hCqxIEizLJiTOoV1PHDQlSHGujK5ck8JtJqu2JY2w/2UUZmDC8gnYfnG7KL2Rveu4UAxGVgsK6yhsA70hBZTeDWn0bj3vg69b8QjLBPSFttAKIqp3tSCgvGqXP6bwnpIc2vW8q0ofKGp1VeLBDg/i4MSDqmnUHNrzSvP4v0mrBbXq4LNDu2B88LffhCKGZ+e+fftixowZIkHK5XJhxowZHtNTJeC5557DggUL8N133+Ho0aOYOHEiioqK8PDDD1dYnbiJgLRax2icK3+CiEpjFAVSuNIzmQsnRLW9BUkvfv045XgvmnGu3C7M3zVfdMxom2lF1yYujReuqCMEeFS7Vgm1wV24Cs3JevuckXyVJgapECKacFRCc3DXRVl992EkxbnyNR8OTrjSE+cKAB5b8Ri+2/8dHvj9AVF6PdurcBhaLcjIJyeljxEO0iQnfTe4eq88tVJ0TM/7YDSciS9beEmvUXLo1rO3INeGwnvTu/2NKBSDzg8UPj+NoKxqIQxItK7VWvW82pZYr697nf9NWnmqVQfSGK0nFIP046CqBRE1bBb88MMP0bdvX9xwww3o06cPAI/zWn5+Pu/wGuqMGTMGV69exRtvvIGMjAx06tQJq1atkjm5lydqkZnLc/sbroMHU7hSm1yEA6Xa3oIkbcL8pPloOqepZr4k3Kwbm9M2i44ZbUe1rzSArElR0gD5FYpBZXAiCVd671MzFIPkWQknf6ImQrJtkF7hSGmiC8TXb7HD65jMC1c6v+DXnF4j+vv/2zvv+KqK9P9/7k1uGiEQIBBaIAHpVRQIHQVC08W+WJBdsGADC4quK6CLLNa1u64iuraF/foTl0UgoqwFdBcEkd5FSkIRCDX1/P4I52TOnJk5c849tyXz9sXLm3vnTDlnzswzz/PMM05CMdBBRPUAkyJMMd4qyhHvjzfdA137xQsiqsO7b8fPHcfGwxuZ5fEIWnMlEAIsca7gTZwrgNJcMfo2zwzOPFtQQiCy01yRGjGZ90LWimEJIgoNmw5vMv4mn59erp3g6FZzRaI0V6h0PFu/fj2uvfZaHDp0CCdPnsS4ceOwZcuWmAkiCgB33XUXfv75ZxQXF+P7779Hr1697C8KIaRwRb+cToOIsnAaEJMbod1G5S06uFl/WUX1FmquGGeekXm1rNuSm69MhHa3yK64WGEBZIOIOop7I0hLmt504UoWUqB1qrmS0by6ESj/kvcXI38vBuhTJVVey/q9EpkFdUrLS7lhH9wEEXUS54qsI7mAeXnEy7Z1Ia9hpSEnXjdmQTtBgxcYVCSM0+8bV3PFi9BO3Df9s11MNl5ct2COv5GJeu7UNcEuP9b35MkI5PPTd9rWSawjlbdIu2lXvwqtotoFEXV1WmKTJk3w5JNPel2XGo2d5oo1+bs5u8wOnubqm73foEFKA9vrZc6gkhWu/D4/W3PF8bkSIeNzReO1WZClueIFJwzGLCiCnLRLtUphIC1RbtertFkQVuFKFC3cLhikiFb1WhnXei1c6c9AZBbU28BynucdfyPKx63PlVHX8/d5+93bjZ3EpPBhZ96iMc6LlDxb0CsNhEhzRfcbrzVX0mZBQgiw09I6qR+Zh6zQxtO20eZiVoR2MkI8+fx0Xyxb4UpgipYdt6qj5kpKuFq/fj06deoEv9+P9evZMUV0unTp4knFahomzRXDp4C1OguFWVDPkxSuth/djv5vV5qAUxNSpa4X+lwJfHxMR3kQandycD9RfAJj/2+sqTw7XAlXTh3abQZVO7Og7DmJdogGNFJ41zVXyfHJ+PH2H9H19a5S+fImWnq1beewatFAyJoFifuk96Vgo9rrnC6piuWhPy8ZsyBTcOYtfrzSXDF8rlgLGLJuTnyu6N9caa4c+lyJThfgaa547zavbDufK9GGA1NdOQfIk3XjYefD5vbMQhJSuDLypc2CAs2VvnNVRtAHzNo4N2bBGulz1a1bNxQUFKBhw4bo1q0bfD4fdyUaCzsGoxF9omNprnjnpjk5/iYYh/Y1B9dU1SWIg5udaq5ItbsPPua9oV/aBikNcOTMEUs6u4mbNTE71QDaqfJZUdd5g7YXZsFLsi/BF7u/wKCWg7BizwqjvHh/PMoqyow+5/f50Sq9lble8DH9M/TfZDRX5OQvo3l1IxyRZyUu27XMJrU9pmjm1Nl7ThctbjacODm4mfa5AthaNrtdk7JaA5n3Yf/J/bZpRIg0HlzNFaff8OpL9kt6MUl/Fn1H7jCmF4x2hzHzTOs6bs2NJHaaYx3e8Un6fbXb8MI6XknGoZ3OIxilQDQiJVzt3r0bGRkZxmeF9+gdmeVzxdsJFYpQDCyz4Mlia+gNHl76XNGaK93BmFWeznPDnsO4T8ZZTrp3o7mShTYL8mD6XHF8PYLxAdPvmS7Mkc7RupBKm19p4vxxVgHPLhQDtUrlaU/IupDXuXkG5HE+f/rmT46vp3nuu+eMz4bmSp/oGC6qokmDt7tNRnMl49Bu53OlYydc0X2NF3KC994+PuhxPLbiMeZvTn2udBz5XHHeFSnNle5zZReKwcYsSDu0nywRj5lkTCgWXmiu6E1AZL7k941qNULh6fOnCgTh0E62yY3mSi+nuvhcST25Fi1aGDenRYsWwn8Kd+gDYCAuYOmIvN1j3JWxpFpbdC0pXNHnuIkINhQD2U5Nq/I9ivPFITmQbK0v7c9yvv4ni0/iL9/9BT8f/1lKzeyJQ7vANweQ3y0IWFfjblTlujBHqvX9Pr8lnhRr9x9Pgwq487li9l8Pdgt6ffjre+vfMz4Hq7niIfK50suU0VyxhHFWXT3TXHHa/8eBf2R+7waZ3YJ0PXRtHy89jcmhPQRmQQ2ayXePWTcbzZWOKM0f+v9B+lreRgFN03BRk6rzglma23Bormqsz9Wnn34qneHll1/uujI1GZFDO8vBGXBmFpSFqbmyWYXJ1EnPyy4NrbkiBTIZzZVe/1X7VmHVvlV4/D+P4/DUqrPTlo9bjkvfvZRbNzdYHNo5k5CsXxcriKgT9AFUN02QE7VuFiRhaq4YAyr5/HiTjV4GYJ7E7LR2ZP5OYL0vXkH7XDl9r3jpZSZVmXbpEzTpzM+a7MNpFmTV0c3vIs0VnYb0GZLJ241DO++ZGWZBasFop+239bmyMQveefGd+NMlYk2tTD+jBUGWWdCuL5LaKd4zcuRzVU00V1Ij05gxY0x/0z5XJkdc5XPlii4Nu+DH239EnC8Oe0/sNf1WoVU4cmhnEYzPFTlQSIdiYKSTidBOTwTkNSxTiZ3J5di5YybBtHZCbWa5QQlXQThi8lbMMqYaHrRZ0CRcMXzX/D6/pX+wtIt2ZkGRzxVvAgScmwXJ+jsN3ugEi1mQtYtM8FycOLTT91/23daFK/09YS1geCEidOj7zlsEhMMnRvQO0bsv9bTkbjcZmGZBjnle9B05xtGaRreaqwteugCzLpmFjJQMS11JHhvINsOS0No0gH1/eQ7tpNVAhP6esMqTpTpqrqTe4IqKCuPfsmXL0K1bN3z22Wc4fvy4cTL5hRdeiCVLloS6vtWWWgm10KVRF3Rs2NHy2+xvZjvazRbMIOiV5opVX6kgohrfLMjyu+JprljlAvzJ2IudZrKRvElkg4i68b3gaa7oM+JkNVfBRGgng3PS5drt+qIh2+O1WZAknA7tNLLPW28/veU+GId27u47N5orhz5XQrMg5cOmp3VqFnQVisHGLEiPS3bCFS/PHb/uwHX/vM5Wc1UvuZ6j/EVmQbJ/uPG50t1G0hLTgjIL0m4CsY5jnfqUKVPw+uuvm466ycvLQ0pKCm699VZs3rxZcLVCBtZLF6xDezA+V16bBUUTIvly02ZBoHIQI1daFuHKZqs5r2wvzILBni0omhCdCBH6AKprLBL8Epor6r7Zaa5EK3lDc0XkwRKu6DLdCFfRbBbUkTkSxonTO4ne/8u1clM5wZgFubvvwriby8nZgjzNFa++5Lsk63NFO6xrxH9AZTgTElvNFWeBoqO3jde/ZcYDGU0S7YKw5cgW47PsbkFSuNLHZhWh3UWE9p07d6Ju3bqW7+vUqYM9e/Z4UCUFaxAP1izotGxSuCIHilCHYiDzJzU4+jX0ICYToJF8cbkO5B44tLvRcPB23XlpFiQd2nk+VzJmqWA0V2T8KF6+stpDk+Yq0mZBgcDF1Sx7qbkidkuyjiEB7IUr+p3mxSRzM944jnMlCsUQSc0VuYmCPJD8fD3pWFB2pljeAsXIF2LhSmY84GnF6b/J/lGulWPJjkoLlCFc2bxjerDRoDVX1cznyvHbcvHFF+O+++5DYWGh8V1hYSGmTp2Knj17elo5RRVhC8XA0Fw5ca4W+lxJhGIgMWmufFWaK1Z5OkytHzFp8waK2d/MZpYvAz3YO9FwcH2ugjAL0g7t5O5A2d2CooGZG4qBGkjJ0AWnS63ClWwwSJpwa66CNQvKaKVkFgksDM1VRTl3EWH3/spqEIPZKOMUJ5qrYBza3Rx/YwSuJQSVpLiqcUnmbNBgNVcySO0WZCzk5q6dC0DeLHiiuFK4qpNYx3UohmZpzYS/xyKOZ+e5c+fi4MGDyMrKQuvWrdG6dWtkZWVh//79eOutt0JRxxqHnYBgpJMc7Do37CydlqW5cqKylTILSmobSJ8rPV9auLJMXC41V17gxizIOzqCnhDd1NswC0o4tMv4rjnVXNmZBWlBPFp9rlzvFgyH5orwuXIrXNFlOY14LiIsPlc8syCnbLJfsjRXdsIvGY9Jr0NSIMn0u50mXHaDgGfClWChSPcP/fnLmgU/3vyxkY9+nw6cPIDDpw/bvjuLr1+Me3reg9suuq2qrjXV56p169ZYv3498vPzsWVLpX22ffv2GDJkSLWLsBpNuNVczb50NiZdNAkFpwqkymFprsjOfrbsrCn92tvWovtfu1vq5NahnRwEyCNN9AGNjnUlcw9kfK5YHDp9SCpdMGZBVj4AY7egg4ndjVmQvo8i4YkXikG0W9BLn6uY2S3IeWbh8Lkiy2adDMDKQ4cXTT8cmivhwc2U5krHqc+VSXPF8LmyC8VgOkdQNwvGmWPJ2WoL7TRXNmZBGZiaKxuzIFm27G7Bw2cqQ90s370cF9S7AABw3T+vAwD8rtvvAPCfxYgLRmDEBSOEaWIVV0/O5/Nh2LBhGDZsmH1ihWNYgxjrOAUZwWJgi4Gok1THiMArW7ZJuBKseujDnIU7ASVCMZCQBzTzzIK8IKIkMrsFg4FeSTuBtUpjnZMXjFmQ1lzRuwXj/HFyPlcOI7STkzTLLEjnG61xrrwOIhrvs6+z7PMm6xRqzVU4fK509D4R56vSAvH8s3g+VzwNCOv4G97GEp2Dpw5WXe9nmAWJccnv82NdwTpm2UYZdj5XHpsFjXwZZkFbzZWDMZN+Rm7i9VUXnytXT2758uVYvnw5Dh06hIoK84s4d+5cTyqmMMMaQGQGe8d+IgzNlWjS4wWkdOvQTkL6A/Ac2mXMWeQkH4rVt0Vz5UTLJOmE7EYoZJoFeQ7tDM3JQ30fwpxv51jqamsWPN9+ckEgYxYM5uDmUODk4GYWvHePeUamS58rHfIcTrrsSApXTqHHDb/PXyVcUT5sdmZBnlO5nc8Vq52k5p88LJy1WzDOF4cXvn+BWTavHjS8MwudILVbkOEfpj9//exR2Tp0y+yGs6Vmy8bxc8cByPXncPr0hQPHb8vMmTMxbNgwLF++HEeOHMGxY8dM/xTBwxqU6QHEq2jRvHQ8syBNvD8ed1x0h/G3jHAlell5uwX1QZAO1idjTnEq1LnFS1+BYM2CpIOzjM8Vjd/nt9xrO82Vbn7SNWN2whXdJjeRwsNhFhQJzcLdgpzfZLQR0porVAkaodRcud4t6EJIBAjhgni+hs+VpEN7akIq83u73YJ2C1LmbkHKLGiHD2KfK7t3TQby3utWgHs+u8dcDkNzZRxHJam50st5qO9DljbtOb7HKEeW99a/h0HzBnE1krGCY83V66+/jnnz5uGmm24KRX0UkDMLyr5wrdJbOSvbheaKtY2ZJWi40VzRApndrjaRQ3uotByW3YJBmo8OnT5kDEo6Mvesf1Z/fL33a2jQTKt2SxBRxm5BGh98lvtlOqBV4PCum0iubH8lPtzwIQC2cGVcF4RZMCyaK5fP1ZHmyqXPlRdmwfFdx+OB/AeMM+Z4O91CGfqFhqUt5GquqEl45qCZuK7jdczjsug8ZX2uSJi7BYmyZExhdkITKYzE+eJcvRt0/ou2LcIvRb9Y0nHNgpqz42/ifFb3gqNnjwIA2jVoZ1tfsi//5+f/4OPNH2Ns57G210UrjoWrkpIS9OnTJxR1UQigNVd2A8CeyXtwquQUMmpVHqMgPVgzNFdemQUdh2Jg7Ba0M5/Yaa5C4TQZlFmQ4YQ8NX+qJZ3MPSMFW9KJmRSu/D6/tOaK/l52Na2bSK5qfxUmdJ+At9a+xYxzRU+SshOIaeIJh0O7S7MgDy81VzpktHDA3AftJvspvaega2ZXXNzkYgDh9bmiobfwm4QrjuaKHhvb1m+Ltg3aStVJz58lxPGw2y1oF+NKL0NGg++DD3H+OKk8aWiz4P6i/ZY0R84csWxSouPOyS5g4vxxluetmwXTk9Kl660T64FFHb8tEydOxAcffBCKuijOwxqQ6B0/doNWi7otmEfpyJYt69Ae74+XXvXJhGKgy6K1Tna72kQBWENlFgwmQjuLXcd2ccsgubnrzaa/yfaRmk7SZCFrFvT5fJbnRE54onupr+J9Ph+G5AwBUHnGo6UMl2ZBXiRyHrf1uM02DQsps6CL3YL0hgJWWqfmtH5v9zOZkp1oruL8cRiSMwR1kuoA4J8t6Ob94WmPyHxZBKO5snWiZ5iVHZkFbXYL2u3O1MuQMh/6zEJY/6z+WHbjMtvrAOtuQdY43uONHhazquFzVeHM54rVHl1jnRJIsb2e7vO0W0Ks4Vhzde7cObzxxhv4/PPP0aVLFwQC5oHiueee86xyiirIYwmAEAoKLnyuWAMT60V2+rKSu+ZYvhEyfwOh97miIwu7DsVw/rpagVqW4zPour8+6nX0atYL7/z4jiUNaRakhSmfT+5sQb/Pb3lOpJAhaiMZLkM3QbL8YmihVDZCO9m3ZJ5pbrNc7Dq2C/m78qXy1wmnWXBf0T6pa2n0cCFFxUU4fPow83qnO7a81FzVT67vKD3tcyXSXOnQWh27erI0V06uZ+0WdCLMAvY+bLzNI1P7TMXQVkNt8wfM7aR98kTQZkFZ7TDLLKhDh9CRocYJV+vXr0e3bt0AABs2bDD9Vt3iVEQKVgfd/ut209+Ody7JOrQ71FzRL5TILKivMO1Wszqmg5sZu3rI8oz6i3yuGCEHvMSrIKK1EmoBlBWNFnQS4xP5JllNq4rOHhewbDMPtVmQfL4ymh2nZkES2TPW3IxNQe8WdODQTmv2ZAXNgD9gCBekeYysq1OTEm/Xphvhyu6AYbsgoiJzHctXr3ZCbQxrJQ4RZNJcMfoP67k1S2tmCMCs3YIk9ZLrmUI38BBq8Il3jRX0VAbe/bLD4tDuQHPFe8/oXd4s6GtrnHD15ZdfhqIeCgKZiSCcmivRpEfXlaUy19G1F/Q5XDxkHNplhKWQa6587n2uSPTBW8YsKBKSNFT5XNHO67xQDJbywDcL2q26ZYVnvU369u1QmQXdCtVB7xZ0oLmicSNokuYxJz5XMmWz+oMM9VOcaa50hJorSjuuCwH5N+VjQIsBpkn5sQGP4fGvHjflzQrlYdenftP2N3jlf69UXsPYLeiDD21T2mLrma3oltkNPp8PGw5tsORD1kFWc2U6aNplzCmeWZCFU4d2sm6890HGLEjDMp/HEqEPXKIICV4dxcFLJ2sWpPMWxVbRV9aiyZf2E7CYBe00V4x2OnWkd4pepx3HdnDrwEN2Nclqp0hIImNckffMB7ndgl44tOvl8dB/G79wPPJ35rtyaJeJHB605sqjXaA6XgpX5L0gHZODMQt6uVvQzizICwxKBhE10uo+V5RDu36v4v3xFm3HzMEzrWXa+IiynjNL20UKLD6fD33qVm70YgUBZuUn5dAepOaK1A7LjjVuzYJCzZWEWZB+j2W1t9GKtObqyiuvlEr38ccfu66MohIZwSlaNFfkNYB1tURiaK7i+JoresCxmAVtNFd2oRhCslvwfJ7vrX/PVJ6XsMyfrsyCsporn/NQDDpONVcAcP3H1wvv29EHjzK/l91FGYzmymuzIC3csnCjxdM1gMGODbI+V7deeCtu7nYzM62OG40Fr0yu5srh4smkuSJ2/hm/M56bKXwD4xryOtKdQVQHN5orR8KVr9I3Ut9J6lRgd7oRiPee+X1+V/3ATXT3aEL6SdWpU0fqnyI8hNPnyla4ktRc6cKVtOaK4dAuSk/XRSdcQUR1WEcVueGRfo8Yn1m7JEVmQf2+sXZzyvpcWcyCbjRXkrvpjpw5wp2QkuOTTb47tAnHTmAOVnPl1tzrxCzYL6uf6W+nzsdAleaKrudlbS4DACOOlZM8dehnHu+Px18v+yv6NBeH5XGycw+wCcVgo7mS9Q2y01zZabNYrg/kJg8Z53E7MyvZxz3zuXJqFnR4/A3v/vdo3EPKf4ruK7InNkQr0pqrt99+O5T1UBDITASsre2elM3QXDmJrku+YEfPHMWfl/8ZN3e9Gd0bdzd8QkQ+V/SL/Nx3lbtP1xeuN+pD4sSh3alw1bJuS6l0dJlOhCvRwEUG3pMxC5L9hreaZ5kFeb5EFrOgw1AMTuFNSJZI8ZSWQcYs6AYZs6CbUAws4eq2Hrfhm73fGH/LTizkvdC3vdPtfWfMO3j/p/dxbcdrpfKU0VyFKnirxSzIitDO8bmSfc6mg79ZDu2MZ8rUXFFmQZPmys4s6DIUg5P7bqqTg92ChkO75MHNOrxFTPfM7lLX09QYs6AifIRiR1tIfa44K8EHlz+IDzd+iFf+9woapzZ25XOls3TnUqM+rPry/gbMg6+Te3tp9qVS6egyHQlXgoGL3uVn+s3GLMgzhdoJZWRebkMxmHYLinyuqDx4g78ef0mHqbkSdNFgzYJeaz5D5dDOMwumJ6fjrp53Secjs1tQRpsxofsE2zTcOFeEWcxIS2mudGTi55HogZUB8ztDf0fCEiy/3vs1V1MupbkS+VyRZsFgfK7Ovxt0kFkRtOZK1qG98HQh8z1z65ge62ZBJVwpTLjyueKYBTcd2WR8JrcmywpXLILRXDnd7eTGzECWJ4OoveRvThzaaXMqPUHJRgh37dAuGdOGJ7zR1EnkuxtI+1x5EIohlGbBYPqQjq65CtavUEZzZdeH+mX1w0sjXnJctjAUA8f53anPlemQZcaYYLcrVG/7moNrTL+TWiIZzaPQ54p0aA/G58qF5kqvu9ODm/UyaaR94aj7HutmQbVbMAqJZLwwp3GuAL5DO28AlnVoFx3+zCqbLp++xqnmQVYYC+Z5icoQClcMIYncxWSK7UVprmRWkvQuJcBdKAbRvaHz4EW2rptUl1kPPX+p3YLBOLQz/H+M8kWaOY6mhRmhXVKLJ0L3aQyFQzv9zO0m3CvbXelqh5gwiKh+PymzoBOfq04NO5n+Jhck9HesdABHIPMRPlcSzuOs94uEp7lyFIrBpc9VWUUZ3ljzBuaum+uozEuyL2G+D277o1cnXkQKJVxFIaFQh0o7tLvQXJHIDMAi50aeWVCHtsM79blyIgiFwwFeNCGIhCsNmpTPFR3k1c4cQZZn2S3owqHdrgwS3kpVZBbU6yOCPkVAFotDu8M8aCGArI8lrQeaK90cHaxbgRdmwWAXiEKfK8K3CXDmc0WbtN34XPGEbJPmSiIUQ1g0Vw4EPp2yijLctqjqyKhgfa7c7OIEauDZgorQ49VuMzfQTqNOzYLki8iaRBLjEoUD78AWA43PuplDv06vD69sHm7jXLk1C9rRLK2Z8dmtWVDTrMKV/rdolyU54IoQObR7FYpBdkVMmwV5W+B50DsmZdH7mmuzICc9U7iinknf5n0dlQVUjRvhCMXglUO7xdQHDSeLTxrHOjnSXLkIcsryuWKaBSU08vp1smOmrM/VtqPbLPWVwW2cK3pxL63B5/R315orBxupohElXEUhoVCHyq4k9RfBC4d21hEQdhPvHwf+Eb2a9gJQdaI6ADw++HEA1hffSSgGpxOC2xWXHabdSoKBS7RlXINmaY+e76bDm3DH4juM/GmfOFk/JbehGGQd2mXvL20WdIpbzZUulAvNgi7ytdNcta3f1lVkc6+EK5bWhRWKgWRi94nm9EFozx794lHjHEiWz5VFc+Vg8USbkVnvn6xDOy9fqThXkporwHx8kVPNFZmfrCaINs/H++Rds4MxC3qhvY0mlHAVhURSYncTioH26dHZfXy3Ja3d0TdJ8UmY3GsyALNwNbXPVADAl3vMxy+xdtHRuDXruB0UnJCZmilVPsuZl179kiEW9IO+WQ7tMvVlraxJ86oXoRhk72/thNqmv12ZBQVt5mmJ9PYGaxZk1UdEg5QGjsrRMcyCYXBop4WSG7rcYPpbencyw+fqvZ/eqyqHFaE9CJ8rGlmB2S42FmluXLh1IX49+6uwXDufK15dHDmXE3XaeWyntEVERnPVtVFXa3kcrbhbYV8JVwrPCYnmStbninJoP1t21pioZbB7kZzEQNLNgs3TmnMHaxnNlT6oJMYlOhKE3JgZZPDBhwXXLMCsS2aZgjCOaTfGlM7O5wqwj9nDCsUgM/ExdwuSZkFBHqQA7cShnQctjLgxC4poXLsx83tdg8MKCyADLz0rQjt5n9xuXdcPdw9W0+fGLCizyJFBg8YVZLzwuSLzAeQPbpbZKemkzbaaK06fc6q50jc5XPrupaaDvUVYhCvGPcq/Kd9aHmfhVlN9rlQohigkmjRXIvRzw0xqdpuVlYxwpb9k5BEudmmNvxkvt9MDo3VCZRb0+Xy4usPVjsrnhUWI98cbgyZr0KcPU7Ub1Ml0bs2CsqfZy95fXj10gnVo5+1e1Qd3/SBtx7sFXYZikDkeh8WSHUsAAEOyh7i6Xkdmt6BdrLRgtGdk+SKfKzq9bL8mkdVcyewWdIporBz7f2OZ+Tr1uSIhD/YWIaO5ImOFGeUpzZUJpbmKQiLpc0VrrniM6zoO3/z+G0vedteJwjDQ6L4GoslGRnP1/b7vAQCbD2+WLhsInUO7bD6i+8rSXLEmbXoHj6xZ0E5z5RcMHaRwJSpL9v4G6zxtZxYUCVdrDqwxIqe7FRjosu0c2t1qrvT3JatOlqvrddzsFnSruWKZu7nCFZX22Llj+OMXfzTaLWtmY/lcOXF94Gm7nCyK7RYoZL4kjkIxUPfLreZKNoho0Jor6lrd7y5WUcJVFBJJiV1Wc/XOmHeM41lMmhGbCUhKc3U+P/0lF2quJAb1J795EgBwsuRkSEIxBOMXIcpHpLnS+4idcBXnizP7rcgO6j4fioqLTN9FjebKzW5BwXPn1bdcK8c/Nv5DuhwaR7sFPdBc6YRqt6CTY1iC0VzxYk4ZmiviXv3p6z8F5cgve41MGIqTZSc9L9uJ5mrSRZPM11L9T9fg20E60ANArUAtqeu81lzN3zgfp0tOu7o2GlDCVYzStn7bkOQrq7niYau5cmiaA4LXXLnFrVPu6ltXuytPYLIQmQV1eJorOh9Znyva107W54p8Xl74XPHibcmUoV8v1Fxx+mSFVmGK2eV0tyAZGoP1PS8ft5ormTrJIHNwM71IkjHPs7A4tIOvueKVpSOtaXagaWflzdsteKLshDAPUojXNM0zM6bOX4b/xVInEreaK9nrgg3FwHqutRLkBLtoRAlXUYiMerlXs16O8iQ7flpimm06t1t+vTAL0i9ZsD5Xl2RfAgDoltnNtuxgWXbjMttyeIOQaJVKX6M/fzvhqk5SHXMgRkmzoA8+yyBLHkkSKs0Vz2/MVA+HmqvUhFRXmqsKrULaOZ8Fz5wS7ZqrEa1H2ObbNK2p6TeRSdsJIrMgryxRWrtraed4HqQwyTsyx4lwVaFVyMWbc6C5SohLQO9mvU11IpHVXNHv/cliOY0cbXLVCbY/xio1s9VRjoxZMJgOK3NYsFvHSbuJLj05XTpfHSeaKxaNUyt3g93U5SZHph1Z3zenWgfeoCoycZLXjGg9Ah0yOgCwF66a1W4mNAu+MOwFZl38Pr8l3pHui+PELCj0uWJMUiwTRLAmqDpJdYT1kD0xwOnJCTzzkV2fDVZzFexkNumiSchIsTosC3cLutVcMZ6d3SHKXM2Vi2CXsveKPMqH53OVnZwtzIMWrtxg9y7Q7zqJW4f2q9pfJXUdT6MdjpA20YgSrqIQmUndsf+HpHbJjeaKLkdUN32HoTAP6nrRZCNjFtRXbE7CQADyuzbJ+spqbWTgTWbdM7sbn+0Cksb7462aK+IesXb9AJX3Mbd5ruk7Xdiy034Fo7lKCaRYvrPbLWhXRmpCqjCNqL5kO8kTA1i/0/AmQrvdZsFqroKdpOL8cZawILK7TI30bjVX1KHHsgcrA3Jj1u+7/96cFxUzi4fpsGfOcx3VYJQwD/K5ygpXTkMxiLTd0j5XVBBR2eOseGN/dROaZFHCVRQiM6kH02GFUcHdaK4cbMN2I3zImDF5fwPuhStZnE6MbsyCJn8Non+QwhUdbFP/nd5xRf7Nq6/f57eYh9xorkRImwVpnysHZsG0xDRbPzNRfUnnXjvnWtocrL9nMn00msyCAHvyJ/O1ewZufa7osr3wuSLzuOPiOyy7Z2UghX6ecBzwBzC81XBuHuQiUVq4chiKgXUWo46scEU/W1lNatCaKw/9ZaOBmBGuZs2ahT59+iAlJQV169Zlptm7dy9GjRqFlJQUNGzYEFOnTkVZmVnFuWLFClx44YVITExE69atMW/evNBX3iFSmiunsZUkVeGufK4os6DoWjc7ZETClYzmSnfITIpPcnTf3ITE8NIsyIsrRNaL/J51ZEogLmCJci2jafP7/Ja26OYCu2dsMgs6dGhnfRdMnCv9XEK3mjZSW8XSXJHQ/oQyk71ONDm0A+xwDMJxw6M4VyKfK7tFJ69+TWo34abR/7Z712XMgqI6AO7Mgk5DMYg0V6v2rZIqk0Y2FAOrTLpONYmYaXVJSQmuueYaTJo0ifl7eXk5Ro0ahZKSEqxcuRLvvPMO5s2bh8cee8xIs3v3bowaNQqDBw/GunXrMGXKFEycOBFLly4NVzOkCHUoBs99rugI4IKJzM2LlhJvNRWxygbYL/fnuz4H4CzGFhB+s6BogiIHVbJe5GfWsSkWsyC1XZo3kftgPf7GMAtSmquXR7xsSicrHMgKV3aDu6i/1Uk6L1y51FyRAtXpUqvmisyX3nXIq7edk3Y0aq7oZ24RcN1qrug4V9QBw2QftDtAmyd4WHY2cnwZRZjMggIBR3TvyecqPbY41FyJ4oK5xc0uTF6dnBDr5sSYidA+c+ZMAOBqmpYtW4ZNmzbh888/R6NGjdCtWzc88cQTeOihhzBjxgwkJCTg9ddfR3Z2Np599lkAQPv27fHNN9/g+eefR15eXria4gnB+FzJHBYczAsheqndvDBOBjNR2eEwC8qs8rhmQYHmijXJAMCpklPG53rJ9Sx5xvvjTdfSO/1EZkH6XpKaK/I3Oi4O6zw4FrKrXDuzoAj9KBi3mivSFMgSrkgsmitOgMpQa668EK5YhzeHw+cKEMS5Op+n00lctKhafUAubIqt5kpiUcrTPotw6nMl++45wUlIGi8d2mPdTBgzwpUdq1atQufOndGoUSPju7y8PEyaNAkbN25E9+7dsWrVKgwZYj4aIi8vD1OmTOHmW1xcjOLiql0WRUWVgRVLS0tRWlrKu0waPQ8yr9Iy+3w1TXNUPplWtBIpKytDaWkpysvFp7qT+VVUVK1yy8rKxC+1Btt6W8oWXFNRUWH6rbyMX+94xKOsVH7HV1l5meX5sOpBDpQV5RW27eM9O3rArSgntAfET2UVVfUiA336KhgDG/ym+6lVaKbn5df83LrQ3xeXVr4HPvigVVRV6Fyp2ZeDNMWXlfPvN2sCZw7OMNeR1KqUlpYKB+HkuGSUlpaKJzOBovjQ6UPG51PFpyz3hHxXaUFVrzfdn/V3jP6Ovg4Q9zseMn3QDvq5lZeXm96tCo1676g2iupAtol22/jv/v+aExOPTX/X6WuM38sqUAprmaTwTF+/9/helJaWomfjngCA7LrZzHrHE1Ml00/s/Lv6r23/Mn3/wrAXMHlZ5UH0pp2n5dY+wILut+Vl5cLrnOzc5tG3WV98u+9b42/ZvlRWVgbWukerkJur6D7kg8+TOVbHy7xkqDbCVUFBgUmwAmD8XVBQIExTVFSEs2fPIjnZuiti9uzZhtaMZNmyZUhJ4ZurnJKfXxXq/4djP9im/+WXX7B48WLp/I+VHjM+nz1zlpvui+VfoG6gLvcIDB2y7B0FO4zP3377rWnipdm9e7dtvX84bm7/3p/3cq/ZvnU7Fh+v+m3b6W3cfNf+by0KEguEZQNAn7p9sPL4SrQ+3tpSLvmcdAoLCo3PX634ClsTtwrzP3P6DLM9Bw4cMP393arvqn7bX/Xbzp07sfhc5fVF56qEq5XfrrTkuWv7Lqw8VPX9nj17cDax6vn/sPoHnNxkjWNz+NBhLF68GOMaj8O7B98FAKzfuB4AcOTIEew+tdtIu3HzRuNz59TOpratLVpryVunsLDQ8t3Z09a+uXH9RizeW5XnmdNVprrFixejtMQ8aA5OH4wvj30JADh65CgWL15sun80P/30E/e31T9XaTb2HrT2w91nq+7DscPHTL8dOXwEixcvxoYjG0zff/3V19iRuMP03ZoTa4zPe3buweLT9v2Ox+ZNm7H4sPzYwGLfgX2mv39a/xOW7Fti/F1YUGi6F9vPbDelX79+PRbvF9chPz8fv5b+Kkxz5MgR4/OJEyewePFiHC45zEy7dOlSxPusU9qZInN/2Xeuqm1Hjhwx2vFh5w8R8AeY7+bes3uNzz/v/tny+w+rf0D71PYWLeXmTVVHbp0+WaX53LZtGxYX2T+jw4fMbV3++XLUiuMH1jxyuOp+/fqr+N7S3NX8Lrz8y8s4V3QOfvhRcX7VIdv3PvvsMxw9etTy/ebNm7H4iH1bNxw1vyc++BzNcdFGRIWradOmYc6cOcI0mzdvRrt27cJUIysPP/ww7rvvPuPvoqIiNG/eHMOGDUNaGt/RWpbS0lLk5+dj6NChCAQqV75FG4sA6/trIqt5FkaOHCldTuGpQuD8HJiamgpw3rshQ4agYa2GldqBH/n5kWWv/WYtcF5m6devH+J3x6OktIR5XetWrTFysLjexVuKgT1Vf7fKboWRQ89fs86ctl27dhiZW5VfxoEMwDzOGwzqPwjNajcz7gOPLyd9iXNl50ymANZz0pn7z7nAeRnnkksuQYs6LdgZn697amoq89n9Y+E/AGJ+7tunr9GWllktjWeWnZ2NkUMqr69YV6V26d+/P0DJlh3ad8CgCwYB5+W9nOwctKzbEth/vozefXFRs4tM9QOAzEaZGDlyJEZoI/Du7Erhqm27tsB+oGFGQ7TKaAWcH/dzWucABys/X9rhUqNuABDYFQB2sW9HRsMM477p1E6tDVDheHpf1Bsj21TlmfJzipFm5MiRSNyaiJNnKwXEu5vfjfYd2uPLpZXCVaNGjTBy5Egs+HSB6d6SdO3SFfiF/duB4iqh7O6Bd2NkV/Nz+7HwR+PetmjWAqtOVDkNN8lsgpEjR+KXNb8AhKwyeNBg5KTnmPLx7fAB5+W0Du06YGSfynJE/Q6A5X0AgM6dOmNkD/mxgcW7H78LHK/6u0uXLhjdZbQxJjRs1NDUh9ccXGPqe127dsXILuw6kG06WnxU+D5mNso0+kidOnUq72fRL8Ama9rRI0czTVDP/foctu6tfEgjR47E1qNbgfOHDzRo0EBqHN3x6w7jObdu3dro+zq9evZC0aYiy3VdO3c1nn3dOnWB82uHNm3aYGS/kcznR9KwUUPTOzJ82HDUTrTuCtZ5c8GbRvoG9RsAp7hJLXTr2g34BajfoD6aoRn2Fu3FAy0ekO57o0aOwssfvGwps3PHzhh5kf09LlhXYHoP4/xxjuY4O0pLS7Fw4ULP8rMjosLV/fffj/HjxwvT5OTkCH/XyczMxH//a1Yp6yvjzMxM4//0armwsBBpaWlMrRUAJCYmIjHRarMPBALsDucSMr+4OHsHwri4OEflk2lFfkEJgQQEAgFbnwAyP9InKiGQIFRHx8fF29Y7Pt5cP/KarDpZ2HuiahUZiDc/B5+fX3ZqUqrUPUtISEBCAtsPh/XcyfYnBhJty/D5fMw09HNPCFTVIT6OMEv42deT6XWSAklISiCiS8fFmfJKTkxm5kXecx8qD6XVfOcjtPv9prpWEHY1ul8G4uWj6+t509RKrGXKk9QOBAIBkN3N7/Ob+k+cP86Shobubyw+v+lzDM4ebJm8yfaRwjhQ6TsVCASYz5W+52Q+SYEk6+8Oxpv4ePt3zBbqfsXFxZneCboP0/eQfi9ZBAIBBCpsxgJirNLLZPVz4PzYw+hTSYGq/h8IBEz3mvcu0dRKqtIWsXzieHUylUXGGvT7pcql/U0TE8TjC/lus94lEYmBynmu4vx/ANA4sbF030sIJDDHX5m+AJjrDgBPDH7C0zk23ERUuMrIyEBGBjuIoVNyc3Mxa9YsHDp0CA0bNgRQqc5MS0tDhw4djDQsM09ubq4lv0gS6iCiMrsFnTgTOtmGHex5Wl/e/CVavdiKm1YURdtpKAZZnJ5V5iYUA8+hnZdeJ94fbz7rjwqjwHPmpttUrpVzg4iSDu2OIuAzHDRYbaDrKIqxxLuHoh24dnWum1QXl+ZcKkwD8B3aaWwd2qNgtyDtD2f33rj177G7zsnxN7w60s/FzRhAhoOR3eVKQ5brZicyYB+KIRiHdv3aCq3CeF+c5OHlbsEPr/oQ13W8zvF10UTMhGLYu3cv1q1bh71796K8vBzr1q3DunXrcOpUpQ5y2LBh6NChA2666Sb8+OOPWLp0KR599FHceeedhubp9ttvx65du/Dggw9iy5YtePXVVzF//nzce++9kWyaBakgokEICTJxrpxAT25eh2Igr8lJz8FjAx5j/gaw4/PoOA3FIIvT4zTcBBGViffDE67o8/FkJnKTYHd+QDd2C1J5kBGdnQjadoEqdewO+xaFAjHiGAneKbt3SaTpFYVicBTnigzFEGycKw92if3pkj85Sk/uWvWqDoB9NHudAS0GcPMQ9R/ZetZNqouXR7yMl0a8xIy7pz/TsR3HcutKluXmaC2yHB7BhGLQry2vqFpIeSGouwki2iGjQ8zvFowZ4eqxxx5D9+7dMX36dJw6dQrdu3dH9+7dsXp1pcNpXFwcFi1ahLi4OOTm5uLGG2/EuHHj8Pjjjxt5ZGdn49///jfy8/PRtWtXPPvss3jzzTejLgxDo1qNbNM47fTkiy0Tod0JpGaB3upP40azQ9eXnkxJWDvQdOyOQfGCYAYj1lbku3vejZRACqb2nWp8Tw7MZORo1kQR8AdMQmV5Rbk5FIMgzpWOLiTowVhpAZrUFjrSXDEmGKZwRQnFohhLfviN8AtkfsFormTj/NChPniCXSxorjo17ITVt/DDFNBtOnLmiOlv6e37NulkNVeiZ2TRXLkU/O7seSfu6nkX8ze9HZ0aduKW5YXmyolwxYp7J0IfZ0nNlV9SRPB6QR3sOxANxMxuwXnz5tlGU2/RooXt7oJBgwZh7Vr+DqZoYEjOEDw24DF0adQFVy+4mplGdsBn4bXmij4x3us4V06ENZHmKjUhFcfPHXdcvh2emQUZq9QXR7yI5/KeM2lPSEGhfnJ9I9AlT3NFPh86JlWCnx+hXedsWaUX7qyvZzHLoYVrWWTNK7ZmQUo7oB/UTeYnFK5sJnjZOGv0JM7TeNmVFw1xrgCzDxn93tIC7rBWw0x/e6W5YmlsWfdP9Iy81liL4rPJxnWT1VzxIsrzIO9Ddt1sy+/N0prhlZGv4G8//A2Lti1i5l2ulVeZBT3QHrmJc+UkKny0EjOaq5qEz+fDzMEzcVUH/mnksifAk3nqODnGguSdMe/ggnoX4D/j/2P63iRc+eKCXsU4Wa3RaUWaq2AnLRlkBiPZiUdvNz3QkMKFnWBDmwVLyktM94iruRIJyNRvk3tP5v4maiurD8uYBUUTk9/nR2ZqpqX8YDRXooGeXGHTQqC+AJLpz15GaA9HZG5awKV3sHlVB9azYX0n3KRDPZdg6yYKlOnVMUC8651orljCVXpSOi5vezkapjS0lnX+vmpa1eHZ0por3VdXIHg6IRxjdaiJffGwhhLM6lTo0C6YaIa1GoZxXcdZvicnP1ZkbxI39abrK/JxsovPFQqc+lzJ5CPKixQuRCZSoHKQIieekvISLNlZFa9IxufKrp7pSenc30S41VyJ6uODzyRcHTtXGX9BJJDZaq4E7wtZN9osyDsRgCkwRFmEdsD5Ao5E+vgbm3SsZ8P6TiRcCX2uPBIC9XvuduHK44vdXzhKT/bV7HSrcKULwaKFjYaq8x2dap1kN6kw83B40kW0ozRXMUT3zO7G55CZBV0IRhazYLCaKwerNYtwxdFc6WaLUDhJ8hzPecjuFuTdR3IAsxPs6EGqpLwEJeVVMch4E7mTPiIS8ET3m9WHpXyubMyCpMBTcKoyAJtI6Lb1uRIIGeT9oydxXjwiVhtJ4S9ozZVXzuTkzjOH701IduWCrx3RD+hmYYkpFuT9cWIW5O1klfW5+vWss0CgZN9qWrup5ffaCZV9kiW86M/MzW5BrxfU1cHnSglXMYTs+YDMayW1K24EI1K4snNodzPoOsmPN4l6tZq3yzsozZWkUOkkFAOtPSkpL8EfB/zR+Js3iNn5jvDMzE4mLlmzIJ1O6NBOXX/4dGW0Rzufq/337edO0LKaK1rDxttAwfq+8HRV/L19RfssvzvBq74u0h7Y+QzJah7IfsQKvssSSFhjCKk9pZl00SRMumgSPrnuE6k62eHWLGhyaJf0uXKK3WYVve8xz0ckzIKOhSuB4CvbH8l3tDpormK/BTUIryZxt8IPb5Lx2ufKUq6Dg5t5mqtQCleOHdo590faLAiOWZCRL71tvEKrQG6zXAxqMQjlJ8pdxaYRCYFOfK5kd4JZnKlFYRWotPpORjufqya1m2B0m9F4/6f3Lb/L+lzR74euJSBZNWGVJdgoYO63Q3KGWH53QjSYBd1Mjna7KI3vGH2EdWi5TiAugFdHvSrMM1gMs6BAX+FGcwUAGSkZOHyGfeQPDdkHWeO1LlyJNFcatIiEYiBDulQHnyuluYohgvHtIQeU+3PvlyqDRtosGMIgooDYNs8L9iizm8ctskKvXnb/rP7s311oruz6BD3BV2gViPPHYdkNy3B/S3f9QNb0YYesWdA2gKWN3xkg53PFEyZkhXu6bJaGqnez3sx8yHAW7TPac8uTIRIO7TTSmisbgcPOP00nPZmvufIaUSgI0eLCrebqicFPSKcl+yOr3wrNggzNlaxDu6g/yM5V5DtQHTRXSriKIWSjrNvRpVEXnHz4JNPhNlifK7/P773mStBW+rd6yfVw8uGT2HiH+cAymXK7ZXbDyt9bDz+2Q1a42nrXVswZMgd/HvJnqXx5z4LUwtiVTfv9yDr8O/FzI/8enD3Y9JtQEyppFrQLA0DHuWIhs1uQdegvIO5/aYlpGJozFINaDrL4uIjOgKPxciNGKDRXovvHws3kyBI4vNBcyVzvBGGcQHrhwen/jVLtYxna5cHCJFwx+u3x4uOVvwmCs645uMYI2RLOUAykcFUdfK5iXzys5rw75l2M+6Ryh57dqkQEreFITUhlDphOt84DZofjOF+co4mZWVfqhRbtFmMN4qkJqZaXU6bcv1/xd0sQQBlkNYoX1L8AD/Z9UCofUV5csyBjIGSZBWVwEorB5/Nh3737sP3X7RjUcpBU/oB7zZWdQzsrrUycKzeaK5/Ph2U3LYOmafh81+em31hmQR6iY5ucEgqHdvr+2WleZBd/5LOTHY+c+lx5DauP6ptE7DTX86+ej892fIbbetwmXZ4TLRfZV0WLF9a4ydy9K6u5sgmPIoPSXCnCChnryqst/6LAim4EI9I+bheKwc3A71S4AuRNbE7T2F0Xbod2p2ZBURwwmbL1MmlTYNO0pkzBSiisSwpX9HduBnIZzRVPIJAZ6Fl93smJAF4KV6FwaJftN6xrZWGaBSU1Vyw/Nh52fop2sPqJcXqBjVnwmo7XYO5v5ho7S6/vfL1teU78s+zGopT4yhMdRA7tvPxEeG0WjPWjbwAlXEU9vMnTqVmQ5XTNXCm6MAuSwo8noRio6y1BAInfZQ/H1TVZXm8Zpq8LRmsQrOZKZregtOZK5HPlUaBE2ThXtrGQBD5fuiBGD/6mY4PO158nELjRwgDARU0ukroOcC68iAiFWdCp2dKNz9WI1iOEv4tw22Y6srwMrDGneVpzAM58FQHgvSvew8mHTzLDJui43VnI6rd6vxc5tJu+k7z/ojry4r3ReLnAiAaUcBVDBBOKgez8QuHKhWBEmuDsNFeuYp4Ido5wNVdUO2R2n0Sb5komzpVdetlQFTRuw3U4QdrnysYsKCPc0sIL2W8MzZULs6CpnkTZm+7YZGhT6iTxYzAZ13q4Ug+FQzt9/+y0KW52GrI2epgc3jV+KAYnfZJMe13H65xUEYC1jz6Q+4Dh8yXafMMLiJqakCq8n0783chxPs4fh2l9p5l+1/sk0+eKNX7ICleCMBlN0/iCI4kSrhRhhafCdjqJ85ygReXR8FbwpGapvKI8eM1VkD5XrDz0dF4729PXBTOx0XXjtY0cQK/tcC0AoFV6K2H99RXr0JyhcnVx4HPlNh9pnysbh3byPsmaBU3ClUeaKxLSTHVtx2sxttNYvDryVW7633f/Pdo3aI+H+j7kuCyamNJcOQxjAgRnvhKVLwvdH7LqZHHzc7uTlsSJWZAkzheHxwc/bvrOqebKi75kd8KCTnUTrmLfa6yaw9vKGzLhyoE5SCczNRPDWw8HANRNqutaeOMhOhuMN/HJmgUbpDTAkTNHmNfIEqoYWrwJinyW0/pNQ4eMDhjQYoCwHpvv3Iwvdn8h5eMBuPO9k8nTrh/KHndCQvYPWYd2puYqCJ8rup5kXvH+eHxw1QfCa9MS07Dpzk1S5djWIwQO7RbNFcMMNK7rOLz747sAQhznykUf4aV15XNFaX3IEw9cC1ACs5oTsyApiMX54xCIC6Becj0j0nty/HnNlay/o0P9C+uQbDc+V9UBpbmKIYLxufJCcyW65rMbPsNnN3wGn88nzMONz5VoW66sWVBPR5Y/Y+AMPJ/3vKO6sQiFAzHrbx1yAA3EBXBVh6uQUStDeN+z6mRhfLfx0qtIp74jMmnpPssyTSzZscTynV0QUdHh1XqZ9DWONFcuzILBBOAMFq/6o2gnH0ubMr7reOOztJ+ajTaeGZ4hyjRXPZv25NZDJgabHU7DYOiwnsH4buMBiONcmb5zWGfSl1FHCVeKqIS3ynI6eHuhuZLFa9ObSCBw7NBO1C2rTlZQplYdrzQF9O4ynp+Yk+Nv3OK1AA5YB3RWGTKbLOj2m4QrakjT+4dIc0WntXzvwiwYKm1mpMqWMQuKgvvKwOpXwewg5JYTpKmOvL9PDH4C/VtU+Yq5NQuKTH9uzYJ6PcnzCfVgq6I4V6Y8HIoIrF2bsv3Ry1hv0YASrqIc3uTvdAAlD5UVCSteOMMGrbkKoc+VyD8q0porOugkr211k+qGtB6Ajc8VxNpJXj70gO5GuwGINVe8Z0oLV6Q2VF8x8+ojrbkK0tzkFaHYxi5jFiTb7JXPlWzU9rBqroj+kNcqT7oeorJ4C6bpA6cLdxKK8hH1W1nNlex91d+dpDjrzsCaqrlSPlcxRDA+V/WS6+HF4S8i3h+PWgm1vK6aCa/jXNEaHJlBnLdbUBRGwO2E6JVQQwtNdNveu+I9vL3ubcwcNJN5vZcTejg0V7JCi939JfsHL5wFLVyRApk+qPPK8UoLEy6iQXPlxiwqbRYM0ucqWEgh3NHRTA7fzx1370BOeg40aJjWdxpym+c6ul7UD7wOxaC/T8osWIUSrqIcnkDlxlRxd6+7PamTHUXniri/eW4WdOjQLtq2H2nNVaNaVUdi+H1+S743dLkBN3S5IeT1sMvLK58r6d1hNmZB025BShkvI1zpB8byJko371pENVchKFsmFIMrzZWNWZ58bsZ2fy81V0GaBWWPu7H7jXU/W9VrZZQxe8hsqbrJmhDd7tTlob9PwZgFq5twpcyCUQ43iGgEHWbtOHTmEPc3L4KIkgQbisETnyuPVs3keWNe7bZyi1cO7SRemQVpQYm3o5YsQ+RzZae5cuPQHkmiQXPlVf8lhQX9GQbrc8ULwisL2R/sXAu8CMIZCujnc2OXG4NyaNe1x6yAoTVVuFKaqxjCq2CVkcRVEFFqt6DMIM4zC9I+V+RAG02aq0iborwKxSB6Vm58mQBnQUR5Du1knsYhtZyJsH5yfal6Bjtpe0UoxgaZHWsiLaUMdmbBwlOFlnJE18oQ7PE3osUaIG8WdOu0bslHUkgj3729U/aiWVozrNq3ynW5huYq3qq5kr3H+ntYXYjNGboGwd0t6GLwigZkJh0nDu2yuwUNzRV1P1mR653i1bMgNVfnys45vj5sDu0uBQdLKAaXmitRfXSzYEZKBoAqh2ORtktfMfPaJStc8fIPN5FyaCfxyqGdfG6Fpwst17DycYLXmivXZsEIaq4CcYHKEDpB9Fnlc2VFaa6inFg0C4rw2udK1izI9Lny+aRDVIjwajIjQzG4iW0TTp8rN5OBxSzoVnNFlc0yC66+dTU+3fopftftd8xrSOzMgrL31XSgdjXTXMlMfKTp0JXmlTG5yx7RFU5NvtBvE3yzYLSYjQHzwkZvTzB9VvlcWVGaqxiippgFnZwLyNN+8IKIirb1R9osGCxeDt52scpkY9KIfNpa1Gnhqi60CYWlucqqk4W7et5l7IwVmgXLrWbBaztey0wrS7VzaNfsHdpJ7ZYbPzXWexSIC+CpIU8BAO7peU/lNUEe02ISgoM1C9I+flS7ZYOIemYWlHVo91tNm8H0G33xGozP1a0X3goA6Nu8r+t6RBNKcxXl8F7OaJnQRdDHnejfOcVy/I3EriTLbkFOKAYvzIKheBaudqh5qC0R5VUvuR6Ky4ud50k8t3337kNmaibWF65HbvNcXPGPK6TrIqO5onFqFhRFfZehummuZDSpZBqvHNrrJNbB/X3ux4gLRqB9g/YA2EKAW8EgaLMg7eMneG+FPlcemQVl82Et1IPpN16YBYe2Gopd9+xCs7RmrusRTSjhKoYoLqua0GLB5yqnbg52HNth+i7SQURNaRBdDu0kkTb7ivpXRq0M7Dm+Ryof3uTVNK0yMOKcoXOCnlhknIadOrSzzh6MFUKyW1DC58qNWdBuwVgnsQ78Pj86NezEvEZ0LQ/TxgMXz1YUiNiiuYrSvsNqgydmQYZDu5Nnk52e7boO0Ub0qz8UBqdKThmfwz35is7348J4V10FERWUzbsPMucTeuZzFYIB1M3K30tE96JBSgPLZCsDb/B2OqhbzIKkaYkzpInMJSyfq3gfETvLjeaqujm0S5iBTWZBjzSvdZLquL42VNeJdguS7+3YTmOj1yzI8rki2vJo/0ex6LeLpMv1IhRDdaNmtjpGIYWrcHdYN1HdWROd1z5XsmZBrubKAyfkaDELeomoTRkpGdLOp6Fw6KW1JruP764qg/MMWaZEPSL+8NbDLdeKdoTJUN3MgjLCtJuFip3PFe+oJ5qwhmIQ9A3yvSX99uzKCvduQZZTPtmWW3vcimE5w6Tz0zVX9PmodFk1iZrZ6hjldOlp43M4Jt8nL3nS+Fwr4Fy4ClZ9D1QKRfQ1Mr4dlt2CHAHNC81VKAaPSGuuRJrRBikNXO3s8eo+0avz9YXrjc+8CYzlBL978m6sv309ejbtabnWjVkwWHOTV0TMoZ1I40a49Pv8lrrXSZTUXIXxfos0V+R7Q7cnkgI3DcvnKpiAyrpw1b1xd1yafSm3rJpEzWx1jHK6hBCuwmAWfLj/w8ZnV5orxkvl1OeKZc4jJ3anx9/Q5SifKzai7eYZtTJwc7ebAQA9GvcQ5iNrFvEKrlmQoRmom1QXnRt1Nv7mBTyNNYf2UPQdp2ZBWWifK/q+kb5WJCMvGGn62/VuQZdCIO96JwFGTXXyyCzI2mhid9SN3ganu9HfGP2G8VkXrvw+Pz4f97lpXIgmoTKcKOEqhiA1V+FaDeiq7Wl9pzm+1gefZfJ1+qKxnNllHGdFvhBkmmjVXEWTWZBuX/3k+uiX1Q+7J+/Gygkrw101oQmFaxaUmLxMPlek5kqyz0aL83JiXKLnedIbAljPwE1sNhIfzIEsP772Y3Rs2JGZdtHYRfjgyg+qrnXrcxWkWZB+N+gwDbL18sos2LtpbwD2/ZepuXK4G/2WHrcYn+nx1YtxNdZRuwVjiEj4XP3tsr9hcq/J6NO8j+Nr/T4/vrj5C2Q8nYGS8hLjOycwhSuJeDoyZkGfzxd0zBsAaFm3pavrRHihfXh15Kuur6UHX1Kg1Z1WZdodEp8rgaDE07CIwjewvmM5/DqpVyQFLdHuWrfIHNwsG/uMhDZFkX3tivbi8BxutYvBaolkzYK0sBgODc7vuv8OSfFJGNRykPGdnQWBFefK6ThNLwbJvhDphWKkUMJVDNGoViPsP7kfANC2ftuwlJmWmOZKsAIqX9C0xDQMyRmCxdsXG9/ZQb7kLKGINAsG49AOeHMe3DUdr8HGwxuR2yzX1fUsgh2QkuOTMeniSZ6U7+SIDxFeTS6iVX5afBr7GkHgUdZ3olhGMkTSFBIK4Yr2sbNb9LhBF66cpNcJpzArbRb0+UB2u3CYBRPiEgyTPatOOizNVWJ8IvN3Gej7QPYXZRZURC2rJqzCwBYD8a+x/8L2u7fjf7f8z4gTFM3oL+jOX3davpOFJRTJrIqkQjFQZkG3+H1+PD74cYy4YETQeekE69Ae7IAmMgu6DtgYhgkw0c82iclornhmwVgLxeClcNUtsxsAYFzXcQAq/Wxy0nPw2qjXLGndxCiiTVFO7jUpAIt2FHuNSPCm+024fQ5Z2GquzteLjFHltK70fdBPPajJKM1VDNC7WW+sGL8i0tVwjP6Cbj26teo7iUnHpEFgCE/kClk2dhJXcxXmLdCyBGsWDHZyF2kFnAy8TieXeH+87U5EN6t8mWu4uwVd+M1UF83Vyt+vxJ7je9A+ozI6+i09bjH52pD0btYbb13+FlrXa+2qLCc+SoB5HGCFAJAt0ymyx9/44DMt6iIVikHWLEhGVy8pL3EkHdBlVLdzAt2gNFeKkOHFAaus9DK+HTKxsuggotFEsGbBUGqu3CIj8LEiPNM8kPsAAOCq9ldJly2K0M76TuRXI0N10VwlB5INwUqG33f/PQa0GCCdnuVzJcuZ0jPGZyehYoIVZESaK1ojRAbVDEcQURZ2wpX+uV5yPQxuORh9mvdBo1qNgipDCVdKc6UIIa5DMdg4Vsr4dvh8PtPZhizNVbsG7bCvaJ9tXpEgmuJcBSOohcKh9/HBj2NUm1G2YSBInDq0B2sWjCSh8LkKB06Fq3Nl54zPbs2Cnh9/QwnlrIjlduQ2y8VDfR9yfB0Plhacd/zN8nHLTd+5RQlXSnOlCCFuhSu79LKrPPJaUj2/7rZ1WDR2ETo17BS1ZsFgBzdyZ6kbIqW5kml3nD8OfZr3MTngOq6LzfZ0N2ZBu/xDwRODnwAA3Ny1yok5nP5HwWKJc+VA2DlbdjYUVbJFeregz2fqo7JmwZUTVuI37X7jRVUBsN9fnvbNqWlWh7YmKOFKCVeKEMJ6qWVeXLt4K7ICETkIkpNl18yuGNVmVGVeIVTHB0OkYyZ5tRPLqc8VXZbuUB0sUj5XnN2C0ezQ/uiAR3Hy4ZO4vO3lxnexpmnTcaq5OlvqTrjKqpOFukl10aR2E1eaJdnjb2jNVbSaBb1YCNDWBCVcKbOgIoR4cfyNZ5qrGFrNRwPRorlacsMST8p2ahYkTWuujr8Jo0N7akJq1PoOOsGpcEVG13dCIC6AwgcKK6NQBRuhXaC58vv8ZuEqQgsm1j1t36A9UgIpyEjJ8KQMpbmyooQrRchw69Bu56cjO5GYtmozQjEAQO2E2lJ5hZtIa9TcBNFk4dTniu4zjVKdOdbykIlzRbaTPDDYlVkwzBNpdRGunNzrEa1H4L0r3kPXzK6OywrGL0202YQ2J0trrkLonvDmZW9i9IejMeuSWcZ3ifGJOPrgUc8CfNLClBKulHClCCEh87mSHIh4PjQkOek5juoTLiLtCxYpzVWokLmf5OSXnpRufHZjfgp3KIYujbqEtTyvICf35mnNHfU1n8+HG7rcEIpqCSEXbbRQKzILRkoAHtVmFE4/ctoUagGAK5MoD7ptSrhSwpUihOgD5R/6/wGzvq5cNTk1DQVjFuT5XJFckn0JHu73MNo1aCeVZ02BvO/BDJSOfa5CJJTITGxk30xLrIr0HuzmgHDQrkE7fDX+KzSu3TjSVXGEz+fD0QePorS8FLUSasWEvxg5rliEK9qhnTjnUT8CjEWoNdW0YOUVHTM6YuPhjbi+0/Wm75VwpYQrRQjRB0ry+BwvNFeyK8Bj544Zn7kHPPt8ePLSJx3VqSZA3nfyPgZDRDVXtFmQ5XPFcWh3I1xFoq39W/QPe5leUC+5nvE50hs5ZCDfDbpf0ZorcregULiK0l3LdqyasAobD29Er6a9TN9H2q0hGoj+QHa9gwAAIgBJREFUZQKAPXv2YMKECcjOzkZycjJatWqF6dOno6TE3FnXr1+P/v37IykpCc2bN8dTTz1lyWvBggVo164dkpKS0LlzZyxevDhczahx6AMlGeAvnA7tJF4chFyTIO/Xu2PedZ1PsD5XXnFbj9vM5dj4XJGT5MmSk47Lq6nnqQVLTGiuJM2CGjRTe0TCVaxSO7E2ejfrrfo7g+jvyQC2bNmCiooK/PWvf8XGjRvx/PPP4/XXX8cjjzxipCkqKsKwYcPQokULrFmzBk8//TRmzJiBN954w0izcuVKjB07FhMmTMDatWsxZswYjBkzBhs2bIhEs6o9+lljtRKcCVd2QUTdrPIiHZQz1iDv+01db8K0vtOCznNAln3k7lAN0jMHzcTSG5dWlWOzW9CN5ipWtQ/RRCxM0rJmQbo/iM7bU5qe6kdMzDjDhw/H8OHDjb9zcnKwdetWvPbaa3jmmWcAAO+//z5KSkowd+5cJCQkoGPHjli3bh2ee+453HrrrQCAF154AcOHD8fUqVMBAE888QTy8/Px8ssv4/XXXw9/w6opS69fij9/9mc8ObjS3BYNmislXDmDvu/pyemclPJc3eFq9GzaEz2a8COrh0pzFYgLYFirYcI0PF8/N5orhTtiQXNF1lGkuaLDE5RWCIQrJZhXO2J2xjlx4gTq1auy1a9atQoDBgxAQkLVFtu8vDzMmTMHx44dQ3p6OlatWoX77rvPlE9eXh4++eQTbjnFxcUoLi42/i4qKgIAlJaWorQ0+JO/9Ty8yMsLvKhHv6b9MLnFZNSOr43S0lIk+KqeSVlZmW0Z5eXEwczwWdKXlVc5S8rWt6KsAqWa+7aF+zlVaBVBlyW6ntWe1vVaY8evOwAAWoVm+o18Jk7qRT4rrULDmDZjmHn0bdYX3+77Fjd3vRnPrHrGVVmOrtGs6cg2VpRXoHlac/xS9AtGthoplafbeyQi2sYHLxC1yU8YU6K1zaRApY9xel218iohqaS0xNSG4rJiqTZFS7u96nvR1p5wEZPC1Y4dO/DSSy8ZWisAKCgoQHZ2tildo0aNjN/S09NRUFBgfEemKSgo4JY1e/ZszJw50/L9smXLkJLi3Q6M/Px8z/IKBi990PQ2FZUVGd999fVX2Ju8V3jdltNbjM+Hjh6y1Gn//v3GZ9n6Ll2y1JNVcbie06lTp4J+FjLXk+25vcHteODXykOR16xeA//2qvu19dBWR/nqHCg+YHxe8fUKFKYWMtPdmX4nBicMRtfT5phFbu6BzDM6cuSIJe8fj/9ofF75zUrMypqF3Wd3o94v9bB4n3091p1cZ3z22pczWsYHL2G16ezZqrAX0ewP+3irx1FcUYzV/1lt+v7LL740Pn/3/Xco3ly1MD967Ci3TaTmKtraHWzfi7b2hIuIClfTpk3DnDlzhGk2b96Mdu2qtsnv378fw4cPxzXXXINbbrkl1FXEww8/bNJ2FRUVoXnz5hg2bBjS0tIEV8pRWlqK/Px8DB06FIFAmKOIr7N+NXLkyKCzpdt0ruwccN6t7eLci3Fxk4uF19f9pS6wvfLzzrM7LXX6aOFHwDGJ+q6r+jh61GhnjaAI23NaV/m/WrVquXsW66o+iq5ntefw6cN4YFulcNXz4p4Y0XqEkX7zd5uBA/b50miahjs23wEAuHLYlcium21zBYD1cm0wWGf+U/iMzqdtmNHQkvfZzWeBPZWfBw0chLb129qXTZCwOwHYWfnZi/cIiPD4ECJEbUr9ORWFJZUCuFf3MBSMhLluepvyhuYZ/feiiy9CXqs8o88l1krkt+lHQPd2iJZ2B9X31lV9jKb2LFy4MGzlRVS4uv/++zF+/HhhmpycqiCPBw4cwODBg9GnTx+TozoAZGZmorDQvCrW/87MzBSm0X9nkZiYiMRE6wGxgUDA08HO6/yCqYeXeQUCAcTHV3WzUq3UvgxKwWRJ7xP8JqiLF4TrOfl8vqDLkbmebA+ZPiGQYPrbFO3eYb12T96NAycPoE1GG0fXuSlLv4Z33aSLJuG11a9hxuAZljSB+Kq/EwOJjsuOi3N/j+yIlvHBS1htMh1ZFYPtTUyomivi4uJMbSirKOO2idRcRVu7g+170daecBFR4SojIwMZGXJnG+3fvx+DBw9Gjx498Pbbb8PvN8/Aubm5+MMf/oDS0qrJOz8/H23btkV6erqRZvny5ZgyZYpxXX5+PnJzc71pkIIJ6SicUcv+effN6iv8XTl/hgZTwE/KsTyYXVwt67ZEy7otXV9vR1J8Es6VnUPreq1t07466lU8PfRp0w5WHVMoBhW6IyLEgkO7CPI9oZ3dIxlEVBF+YqIn79+/H4MGDUJWVhaeeeYZHD58GAUFBSZfqeuvvx4JCQmYMGECNm7ciH/84x944YUXTCa9yZMnY8mSJXj22WexZcsWzJgxA6tXr8Zdd90ViWbVKJaPW453xryDDhkdbNPa7exTA1FosAuBEW5kdw5+P/F7/LbTb/HptZ9KpWcJVgAVRNSjM9cUzoiFUAyyOBGuFNWPmHBoz8/Px44dO7Bjxw40a9bM9JuuxahTpw6WLVuGO++8Ez169ECDBg3w2GOPGWEYAKBPnz744IMP8Oijj+KRRx7BBRdcgE8++QSdOnUKa3tqIpdkX+JZXtXhkFo7Ii1A0pNcJCJny060XRp1wYdXfYjS0lJswzb35XHiXCnCRzQI9V5Bh2JQwlXNIiaEq/Hjx9v6ZgFAly5d8PXXXwvTXHPNNbjmmms8qpkiEiizYGiwO9MxXHRu2Bk/HfoJl7W5LKzlRkv7azLV6b4rzVXN1gDHhHClUJBEWqsTC7g5iDpazILLblqG+RvnY1zXcWEt16S5qsGTQiSJhbMFZbFEaBcEEa2u1GQNcPVZJihqDEpzxWdozlAAwIdXfRhUPl46tDslMzUT9/S6B3WT6oatTBo3k4Lql8GjfK6qF9VJE+kUpblSxBw1wefKLUtuXIJjZ4+hfkp9x9eadgtWo0lOFlIjWpMnhUhSne67vkO2cWpjHDx1EL2a9opshSJAddJEOqX69GSFazo37BzpKljo1LByk8FvO/3W8ltNMAu61YL4fX5XghUgNgvWhEGSFNqVWTAyVAfh6qvxX2Heb+bh4qaVwZK//t3XmNJrChZcsyDCNQs/NXGRpqM0VwoMbjkYr4x8RSpOULj48uYv8cJ3L2DihRMtv9UE80ukBcjqMMk5hexXNdlXJJJUh37Xv0V/9G/R3/i7Vb1WeH748xGsUeSoDs/TLUq4UsDv85sGg2igQUoDPHHJE8zflFkwNIiCiNYESIHWjeaqfUZ7L6tTI6nJk3F1pCaOIzpKuFLEnOo20lqd6orQLBhjfcQNpNDuZpLPqpOF/078L9KT072sVo0iPUndu+pETRg3eKhlgiLmVos1wSwYaWKtT3iByefKpVnw4qYXR5V5PdZ4bdRruLjJxfjoqo8iXRWFByjNlaJGE2sTqdJchQbRbsGaMEiafK6UQ3tEyE7Pxn9v+W+kq6HwCKW5UtRoYm3irAk+V5HQzkVLENFIQQrtNXlSUCi8ItbmFi+peSOowkKsTaTKLBh6auKgWBOEdoUinNTkRUpszaqKkBBzwpUyC4YE0dl6NWGQVMKVQuEtsTa3eEnNbbnCINZeADUJhoYabxZUGlGFwlNqogZcp+aNoAoLsaaVqAmTYKS1c3SfaFK7SYRqEj4ifc8ViupGrM0tXqJ2CypiTktREybBiDi0C4KIXtn+SkztMxW9m/UOd7XChtKIKhTeUpM1V0q4UsSecFUDNFeRQGQW9Pv8eGroU+GuUlhR/Uqh8JaarLmKrVlVERJiTbhSGobQE2t9wgtUv1IovKUma65q3giqsBBrL0BNMAtGmpq44lT9SqHwlpo4jugo4UoRc1oKZb4JDaYgmjEmcHuB0lwpFN4Sa3OLlyifK0XMvQBqEgwNiXGJuDT7UpwuPY1W9VpFujphp2ntppGugkJRraiJizQdJVwpYk64qgnmm0i00efzIf+mfONzTWPkBSMxfeB0XNj4wkhXRaGoFtTEcURHCVcKtKzbMtJVcIQyC4aOmjwY+nw+zBg0I9LVUCiqDTVZcxVbKguFpyy5YQmmD5yOqzpcFemqOKImaK4UCkXNYf7V89GwVkOsuHlFpKviKTV5saY0VzWYvNZ5yGudF+lqOKYm+Fwp7ZxCUXO4puM1uLrD1dVOGFGaK4UihlCCh0KhqG5UJ8FqxsAZAIBXRr4S2YpEECVcKWIOWbPg2E5jAQC39bgtlNUJCcr0qVAoYpXpg6bj9COnMeKCEZGuSsRQZkFFzCFrFnzr8rcwvtt4DGwxMMQ1UigUCgVJSiAl0lWIKEq4UsQcsmbB5EAyhrUaFuLahIaa7KugUCgUsY4yCypijsvaXAYAaJzaOMI1CR2BuECkq6BQKBQKlyjNlSLmeHTAo2jXoB0uyb4k0lUJGfF+9WoqFApFrKJGcEXMkRifiBu63BDpaoSUgF9prhQKhSJWUWZBhSIKUZorhUKhiF2UcKVQRCHK50qhUChiFyVcKRRRSK1ArUhXQaFQKBQuUcKVQhFF/O2yv+GCehfg9dGvR7oqCoVCoXCJcuxQKKKIiRdOxMQLJ0a6GgqFQqEIAqW5UigUCoVCofAQJVwpFAqFQqFQeIgSrhQKhUKhUCg8RAlXCoVCoVAoFB6ihCuFQqFQKBQKD1HClUKhUCgUCoWHxIxwdfnllyMrKwtJSUlo3LgxbrrpJhw4cMCUZv369ejfvz+SkpLQvHlzPPXUU5Z8FixYgHbt2iEpKQmdO3fG4sWLw9UEhUKhUCgUNYCYEa4GDx6M+fPnY+vWrfi///s/7Ny5E1dffbXxe1FREYYNG4YWLVpgzZo1ePrppzFjxgy88cYbRpqVK1di7NixmDBhAtauXYsxY8ZgzJgx2LBhQySapFAoFAqFohoSM0FE7733XuNzixYtMG3aNIwZMwalpaUIBAJ4//33UVJSgrlz5yIhIQEdO3bEunXr8Nxzz+HWW28FALzwwgsYPnw4pk6dCgB44oknkJ+fj5dffhmvv64iYisUCoVCoQiemNFckfz66694//330adPHwQClQfcrlq1CgMGDEBCQoKRLi8vD1u3bsWxY8eMNEOGDDHllZeXh1WrVoWv8gqFQqFQKKo1MaO5AoCHHnoIL7/8Ms6cOYPevXtj0aJFxm8FBQXIzs42pW/UqJHxW3p6OgoKCozvyDQFBQXcMouLi1FcXGz8XVRUBAAoLS1FaWlp0G3S8/Air2hBtSn6qW7tAVSbYgXVptigurUp3O2IqHA1bdo0zJkzR5hm8+bNaNeuHQBg6tSpmDBhAn7++WfMnDkT48aNw6JFi+Dz+UJWx9mzZ2PmzJmW75ctW4aUlBTPysnPz/csr2hBtSn6qW7tAVSbYgXVptigOrYpHERUuLr//vsxfvx4YZqcnBzjc4MGDdCgQQO0adMG7du3R/PmzfHdd98hNzcXmZmZKCwsNF2r/52ZmWn8n5VG/53Fww8/jPvuu8/4u6ioCM2bN8ewYcOQlpYm1U4RpaWlyM/Px9ChQw0TZ6yj2hT9VLf2AKpNsYJqU2xQ3dpUWlqKhQsXhq28iApXGRkZyMjIcHVtRUUFABgmu9zcXPzhD38wHNyBSom7bdu2SE9PN9IsX74cU6ZMMfLJz89Hbm4ut5zExEQkJiZavg8EAp52OK/ziwZUm6Kf6tYeQLUpVlBtig2qY5vCQUz4XH3//ff43//+h379+iE9PR07d+7EH//4R7Rq1coQjK6//nrMnDkTEyZMwEMPPYQNGzbghRdewPPPP2/kM3nyZAwcOBDPPvssRo0ahY8++girV682hWuwQ9M0AFW+V8FSWlqKM2fOoKioqNp0YNWm6Ke6tQdQbYoVVJtig+rWJr09QNU8HlK0GGD9+vXa4MGDtXr16mmJiYlay5Yttdtvv13bt2+fKd2PP/6o9evXT0tMTNSaNm2q/fnPf7bkNX/+fK1NmzZaQkKC1rFjR+3f//63o7r88ssvGgD1T/1T/9Q/9U/9U/9i8N8vv/wSlEwig0/TwiHCVR8qKipw4MAB1K5d2xNHet2H65dffvHEhysaUG2KfqpbewDVplhBtSk2qG5t0tuzadMmtG3bFn5/aCNRxYRZMJrw+/1o1qyZ5/mmpaVViw5MotoU/VS39gCqTbGCalNsUN3a1LRp05ALVkCMBhFVKBQKhUKhiFaUcKVQKBQKhULhIUq4ijCJiYmYPn06M9xDrKLaFP1Ut/YAqk2xgmpTbFDd2hTu9iiHdoVCoVAoFAoPUZorhUKhUCgUCg9RwpVCoVAoFAqFhyjhSqFQKBQKhcJDlHClUCgUCoVC4SFKuAqS2bNn4+KLL0bt2rXRsGFDjBkzBlu3bjWlOXfuHO68807Ur18fqampuOqqq1BYWGhKc88996BHjx5ITExEt27dLOXs2bMHPp/P8u+7776L2TYBgKZpeOaZZ9CmTRskJiaiadOmmDVrVsy2acaMGcznVKtWrZhtEwAsXboUvXv3Ru3atZGRkYGrrroKe/bsiek2zZ8/H926dUNKSgpatGiBp59+2vP2eNWmH3/8EWPHjkXz5s2RnJyM9u3b44UXXrCUtWLFClx44YVITExE69atMW/evJhtz8GDB3H99dejTZs28Pv9mDJliudtCXebPv74YwwdOhQZGRlIS0tDbm4uli5dGtNt+uabb9C3b1/Ur18fycnJaNeunelM31hsE8m3336L+Ph47jjCJeQH7FRz8vLytLffflvbsGGDtm7dOm3kyJFaVlaWdurUKSPN7bffrjVv3lxbvny5tnr1aq13795anz59TPncfffd2ssvv6zddNNNWteuXS3l7N69WwOgff7559rBgweNfyUlJTHbJj1N27ZttYULF2q7du3SVq9erS1btixm23Ty5EnT8zl48KDWoUMH7eabb47ZNu3atUtLTEzUHn74YW3Hjh3amjVrtAEDBmjdu3eP2TYtXrxYi4+P11577TVt586d2qJFi7TGjRtrL730UlS26a233tLuuecebcWKFdrOnTu1v//971pycrKpvrt27dJSUlK0++67T9u0aZP20ksvaXFxcdqSJUtisj27d+/W7rnnHu2dd97RunXrpk2ePNnTdkSiTZMnT9bmzJmj/fe//9W2bdumPfzww1ogENB++OGHmG3TDz/8oH3wwQfahg0btN27d2t///vftZSUFO2vf/1rzLZJ59ixY1pOTo42bNgw7hzGQwlXHnPo0CENgPaf//xH0zRNO378uBYIBLQFCxYYaTZv3qwB0FatWmW5fvr06ULhau3ataGqOpdQtWnTpk1afHy8tmXLlpDVnUeo2kSzbt06DYD21VdfeVZ3HqFq04IFC7T4+HitvLzc+O7TTz/VfD5fSIR7klC1aezYsdrVV19t+u7FF1/UmjVrplVUVHjbCIpg26Rzxx13aIMHDzb+fvDBB7WOHTua0lx33XVaXl6exy0wE6r2kAwcODCkwhVNONqk06FDB23mzJneVFxAONt0xRVXaDfeeKM3FRcQ6jZdd9112qOPPio93pMos6DHnDhxAgBQr149AMCaNWtQWlqKIUOGGGnatWuHrKwsrFq1ynH+l19+ORo2bIh+/frh008/9abSNoSqTf/617+Qk5ODRYsWITs7Gy1btsTEiRPx66+/etsABqF+Tjpvvvkm2rRpg/79+wdXYQlC1aYePXrA7/fj7bffRnl5OU6cOIG///3vGDJkCAKBgLeNoAhVm4qLi5GUlGT6Ljk5Gfv27cPPP//sQc35eNWmEydOGHkAwKpVq0x5AEBeXl5Q/VeGULUnkoSrTRUVFTh58mRY2h2uNq1duxYrV67EwIEDPao5n1C26e2338auXbswffp0V3VTwpWHVFRUYMqUKejbty86deoEACgoKEBCQgLq1q1rStuoUSMUFBRI552amopnn30WCxYswL///W/069cPY8aMCbmAFco27dq1Cz///DMWLFiAd999F/PmzcOaNWtw9dVXe9kEC6FsE8m5c+fw/vvvY8KECcFW2ZZQtik7OxvLli3DI488gsTERNStWxf79u3D/PnzvWyChVC2KS8vDx9//DGWL1+OiooKbNu2Dc8++yyASl+fUOFVm1auXIl//OMfuPXWW43vCgoK0KhRI0seRUVFOHv2rLcNOU8o2xMpwtmmZ555BqdOncK1117rWf1ZhKNNzZo1Q2JiIi666CLceeedmDhxouftIAllm7Zv345p06bhvffeQ3x8vKv6ubtKweTOO+/Ehg0b8M0333ied4MGDXDfffcZf1988cU4cOAAnn76aVx++eWel6cTyjZVVFSguLgY7777Ltq0aQMAeOutt9CjRw9s3boVbdu29bxMILRtIvl//+//4eTJk7j55ptDWg4Q2jYVFBTglltuwc0334yxY8fi5MmTeOyxx3D11VcjPz8fPp/P8zKB0Lbplltuwc6dOzF69GiUlpYiLS0NkydPxowZM+D3h27N6UWbNmzYgN/85jeYPn06hg0b5mHtnFPd2gOEr00ffPABZs6ciYULF6Jhw4auy5IhHG36+uuvcerUKXz33XeYNm0aWrdujbFjxwZTbSGhalN5eTmuv/56zJw505iX3KA0Vx5x1113YdGiRfjyyy/RrFkz4/vMzEyUlJTg+PHjpvSFhYXIzMwMqsxevXphx44dQeUhItRtaty4MeLj400duH379gCAvXv3Bld5DuF8Tm+++SZGjx5t0SZ4Tajb9Morr6BOnTp46qmn0L17dwwYMADvvfceli9fju+//96rZpgIdZt8Ph/mzJmDU6dO4eeff0ZBQQF69uwJAMjJyfGkDTRetGnTpk249NJLceutt+LRRx81/ZaZmWnZNVlYWIi0tDQkJyd72xiEvj2RIFxt+uijjzBx4kTMnz/fYsr1mnC1KTs7G507d8Ytt9yCe++9FzNmzPC6KQahbNPJkyexevVq3HXXXYiPj0d8fDwef/xx/Pjjj4iPj8cXX3whV0lHHloKCxUVFdqdd96pNWnSRNu2bZvld93B7p///Kfx3ZYtW4J2lNY0TZs4cWJIdmyFq01Lly7VAGg7duwwvtMdwLdu3epNY84T7ue0a9cuzefzaf/61788qT+LcLXpvvvu03r27Gn67sCBAxoA7dtvvw2+IQSRfJ9uuukmLTc313XdeXjVpg0bNmgNGzbUpk6dyiznwQcf1Dp16mT6buzYsZ47tIerPSShdmgPZ5s++OADLSkpSfvkk0+8bQRFJJ6TzsyZM7UWLVoEVX8W4WhTeXm59tNPP5n+TZo0SWvbtq32008/mXYmilDCVZBMmjRJq1OnjrZixQrT9vszZ84YaW6//XYtKytL++KLL7TVq1drubm5lkF8+/bt2tq1a7XbbrtNa9OmjbZ27Vpt7dq1WnFxsaZpmjZv3jztgw8+0DZv3qxt3rxZmzVrlub3+7W5c+fGbJvKy8u1Cy+8UBswYID2ww8/aKtXr9Z69eqlDR06NGbbpPPoo49qTZo00crKyjxvS7jbtHz5cs3n82kzZ87Utm3bpq1Zs0bLy8vTWrRoYSorltp0+PBh7bXXXtM2b96srV27Vrvnnnu0pKQk7fvvv/e0PV616aefftIyMjK0G2+80ZTHoUOHjDR6KIapU6dqmzdv1l555ZWQhGIIV3s0TTOeW48ePbTrr79eW7t2rbZx40ZP2xPONr3//vtafHy89sorr5jSHD9+PGbb9PLLL2uffvqptm3bNm3btm3am2++qdWuXVv7wx/+ELNtonGzW1AJV0ECgPnv7bffNtKcPXtWu+OOO7T09HQtJSVFu+KKK7SDBw+a8hk4cCAzn927d2uaVilctW/fXktJSdHS0tK0nj17mrabxmKbNE3T9u/fr1155ZVaamqq1qhRI238+PHa0aNHY7pN5eXlWrNmzbRHHnnE83ZEqk0ffvih1r17d61WrVpaRkaGdvnll2ubN2+O2TYdPnxY6927t1arVi0tJSVFu/TSS7XvvvvO8/Z41abp06cz86C1A19++aXWrVs3LSEhQcvJyTGVEYvtkUkTS23i9ctQxMELV5tefPFFrWPHjsbc1L17d+3VV181hW6JtTbRuBGufOcrrFAoFAqFQqHwAOXQrlAoFAqFQuEhSrhSKBQKhUKh8BAlXCkUCoVCoVB4iBKuFAqFQqFQKDxECVcKhUKhUCgUHqKEK4VCoVAoFAoPUcKVQqFQKBQKhYco4UqhUCgUCoXCQ5RwpVAoqh3jx4+Hz+eDz+dDIBBAo0aNMHToUMydOxcVFRXS+cybNw9169YNXUUVCkW1RAlXCoWiWjJ8+HAcPHgQe/bswWeffYbBgwdj8uTJGD16NMrKyiJdPYVCUY1RwpVCoaiWJCYmIjMzE02bNsWFF16IRx55BAsXLsRnn32GefPmAQCee+45dO7cGbVq1ULz5s1xxx134NSpUwCAFStW4He/+x1OnDhhaMFmzJgBACguLsYDDzyApk2bolatWujVqxdWrFgRmYYqFIqoQwlXCoWixnDJJZega9eu+PjjjwEAfr8fL774IjZu3Ih33nkHX3zxBR588EEAQJ8+ffCXv/wFaWlpOHjwIA4ePIgHHngAAHDXXXdh1apV+Oijj7B+/Xpcc801GD58OLZv3x6xtikUiuhBHdysUCiqHePHj8fx48fxySefWH777W9/i/Xr12PTpk2W3/75z3/i9ttvx5EjRwBU+lxNmTIFx48fN9Ls3bsXOTk52Lt3L5o0aWJ8P2TIEPTs2RNPPvmk5+1RKBSxRXykK6BQKBThRNM0+Hw+AMDnn3+O2bNnY8uWLSgqKkJZWRnOnTuHM2fOICUlhXn9Tz/9hPLycrRp08b0fXFxMerXrx/y+isUiuhHCVcKhaJGsXnzZmRnZ2PPnj0YPXo0Jk2ahFmzZqFevXr45ptvMGHCBJSUlHCFq1OnTiEuLg5r1qxBXFyc6bfU1NRwNEGhUEQ5SrhSKBQ1hi+++AI//fQT7r33XqxZswYVFRV49tln4fdXup/Onz/flD4hIQHl5eWm77p3747y8nIcOnQI/fv3D1vdFQpF7KCEK4VCUS0pLi5GQUEBysvLUVhYiCVLlmD27NkYPXo0xo0bhw0bNqC0tBQvvfQSLrvsMnz77bd4/fXXTXm0bNkSp06dwvLly9G1a1ekpKSgTZs2uOGGGzBu3Dg8++yz6N69Ow4fPozly5ejS5cuGDVqVIRarFAoogW1W1ChUFRLlixZgsaNG6Nly5YYPnw4vvzyS7z44otYuHAh4uLi0LVrVzz33HOYM2cOOnXqhPfffx+zZ8825dGnTx/cfvvtuO6665CRkYGnnnoKAPD2229j3LhxuP/++9G2bVuMGTMG//vf/5CVlRWJpioUiihD7RZUKBQKhUKh8BCluVIoFAqFQqHwECVcKRQKhUKhUHiIEq4UCoVCoVAoPEQJVwqFQqFQKBQeooQrhUKhUCgUCg9RwpVCoVAoFAqFhyjhSqFQKBQKhcJDlHClUCgUCoVC4SFKuFIoFAqFQqHwECVcKRQKhUKhUHiIEq4UCoVCoVAoPEQJVwqFQqFQKBQe8v8BXsehNrEppaIAAAAASUVORK5CYII=\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df = df.dropna()"
+      ],
+      "metadata": {
+        "id": "Uh-q0lzBBmWd"
+      },
+      "execution_count": 218,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df['LABEL'] = np.where( df['Open'].shift(-2).gt(df['Open'].shift(-1)),\"1\",\"0\")\n",
+        "df = df.dropna()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "EgiiWmPZDjnG",
+        "outputId": "f5e4b610-3508-4aae-ea84-cd7f887b8eba"
+      },
+      "execution_count": 219,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "<ipython-input-219-590619ea556b>:1: SettingWithCopyWarning: \n",
+            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+            "Try using .loc[row_indexer,col_indexer] = value instead\n",
+            "\n",
+            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+            "  df['LABEL'] = np.where( df['Open'].shift(-2).gt(df['Open'].shift(-1)),\"1\",\"0\")\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "X = df.drop(labels=['LABEL'], axis=1).values\n",
+        "y = df['LABEL'].values"
+      ],
+      "metadata": {
+        "id": "AK8i1JAREy2A"
+      },
+      "execution_count": 220,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)\n",
+        "\n",
+        "\n",
+        "param_grid = {\n",
+        "    'n_estimators': [50, 100, 200],\n",
+        "    'max_depth': [None, 10, 20, 30],\n",
+        "    'min_samples_split': [2, 5, 10],\n",
+        "    'min_samples_leaf': [1, 2, 4]\n",
+        "}"
+      ],
+      "metadata": {
+        "id": "lFZ7p4ZPHYbK"
+      },
+      "execution_count": 221,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "rf_classifier = RandomForestClassifier(n_estimators=100,random_state=0)\n",
+        "\n",
+        "grid_search = GridSearchCV(rf_classifier, param_grid, cv=10)\n",
+        "grid_search.fit(X_train, y_train)\n",
+        "\n",
+        "\n",
+        "best_rf_classifier = grid_search.best_estimator_\n",
+        "y_pred = best_rf_classifier.predict(X_test)\n",
+        "\n",
+        "print(\"Best Hyperparameters:\", grid_search.best_params_)\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Au7d0FTNLK2q",
+        "outputId": "fc75f27d-e776-4c4a-fce8-195491301cbb"
+      },
+      "execution_count": 222,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Best Hyperparameters: {'max_depth': 20, 'min_samples_leaf': 2, 'min_samples_split': 10, 'n_estimators': 100}\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cm = confusion_matrix(y_test, y_pred)\n",
+        "sns.heatmap(cm, annot=False)\n",
+        "plt.xlabel('Predicted Label')\n",
+        "plt.ylabel('True Label')\n",
+        "plt.title('Confusion Matrix')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 490
+        },
+        "id": "4hA_sdHlV7tG",
+        "outputId": "191af357-e562-497b-9a6f-47ad644999f4"
+      },
+      "execution_count": 225,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Text(0.5, 1.0, 'Confusion Matrix')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 225
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    }
+  ]
+}
\ No newline at end of file