[MODELS] Cleanup Jupyter Notebooks.

[thoth.git] / models / failure_prediction / jnotebooks / stacked_LSTM_Correlation.ipynb

diff --git a/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb b/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb
index 3401b39..75c301d 100644 (file)
--- a/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb
+++ b/models/failure_prediction/jnotebooks/stacked_LSTM_Correlation.ipynb
@@ -1,1587 +1,833 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 0,
-  "metadata": {
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_EvHebagXgW4"
+   },
+   "source": [
+    "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
+    "\n",
+    "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
+    "\n",
+    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "you may not use this file except in compliance with the License.\n",
+    "You may obtain a copy of the License at\n",
+    "\n",
+    "    http://www.apache.org/licenses/LICENSE-2.0\n",
+    "\n",
+    "Unless required by applicable law or agreed to in writing, software\n",
+    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "See the License for the specific language governing permissions and\n",
+    "limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
     "colab": {
-      "name": "stacked-LSTM_Correlation.ipynb",
-      "provenance": [],
-      "collapsed_sections": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    },
-    "accelerator": "GPU"
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YQ6lT1e2hrx4",
+    "outputId": "d11aafe6-20e9-4719-a751-0da58234f8c2"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import drive\n",
+    "drive.mount('/gdrive')"
+   ]
   },
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_EvHebagXgW4"
-      },
-      "source": [
-        "Contributors: **Rohit Singh Rathaur, Girish L.** \n",
-        "\n",
-        "Copyright [2021](2021) [*Rohit Singh Rathaur, BIT Mesra and Girish L., CIT GUBBI, Karnataka*]\n",
-        "\n",
-        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "you may not use this file except in compliance with the License.\n",
-        "You may obtain a copy of the License at\n",
-        "\n",
-        "    http://www.apache.org/licenses/LICENSE-2.0\n",
-        "\n",
-        "Unless required by applicable law or agreed to in writing, software\n",
-        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "See the License for the specific language governing permissions and\n",
-        "limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YQ6lT1e2hrx4",
-        "outputId": "d11aafe6-20e9-4719-a751-0da58234f8c2"
-      },
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/gdrive')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Mounted at /gdrive\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "tLhroy5BnMnC"
-      },
-      "source": [
-        "# Importing libraries\n",
-        "import tensorflow as tf\n",
-        "import matplotlib.pyplot as plt\n",
-        "import matplotlib as mpl\n",
-        "import pandas as pd\n",
-        "import numpy as np\n",
-        "import os"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 419
-        },
-        "id": "2-UpMVsSnfCI",
-        "outputId": "8c28f578-4405-4a27-81e4-c0fd00475b96"
-      },
-      "source": [
-        "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
-        "df_Ellis"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe thead th {\n",
-              "        text-align: right;\n",
-              "    }\n",
-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th>ellis-cpu.system_perc</th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-mem.free_mb</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>ellis-net.out_packets_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>0</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.730</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>62.067</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>1</th>\n",
-              "      <td>14-09-2016 0:00</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.790</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>59.567</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>2</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.520</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>61.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>3</th>\n",
-              "      <td>14-09-2016 0:01</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.430</td>\n",
-              "      <td>3949</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>60.400</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>4</th>\n",
-              "      <td>14-09-2016 0:02</td>\n",
-              "      <td>0.5</td>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.440</td>\n",
-              "      <td>3950</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>61.700</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176995</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.030</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>230.967</td>\n",
-              "      <td>2.167</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176996</th>\n",
-              "      <td>13-12-2016 21:20</td>\n",
-              "      <td>0.2</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.018</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>218.433</td>\n",
-              "      <td>0.767</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176997</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.010</td>\n",
-              "      <td>3483</td>\n",
-              "      <td>160.967</td>\n",
-              "      <td>1.867</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176998</th>\n",
-              "      <td>13-12-2016 21:21</td>\n",
-              "      <td>0.6</td>\n",
-              "      <td>0.3</td>\n",
-              "      <td>0.007</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>188.367</td>\n",
-              "      <td>2.100</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>176999</th>\n",
-              "      <td>13-12-2016 21:22</td>\n",
-              "      <td>0.4</td>\n",
-              "      <td>0.1</td>\n",
-              "      <td>0.040</td>\n",
-              "      <td>3484</td>\n",
-              "      <td>229.833</td>\n",
-              "      <td>2.400</td>\n",
-              "      <td>0</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "<p>177000 rows × 8 columns</p>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "               Timestamp  ...  Label\n",
-              "0        14-09-2016 0:00  ...      1\n",
-              "1        14-09-2016 0:00  ...      1\n",
-              "2        14-09-2016 0:01  ...      1\n",
-              "3        14-09-2016 0:01  ...      1\n",
-              "4        14-09-2016 0:02  ...      1\n",
-              "...                  ...  ...    ...\n",
-              "176995  13-12-2016 21:20  ...      0\n",
-              "176996  13-12-2016 21:20  ...      0\n",
-              "176997  13-12-2016 21:21  ...      0\n",
-              "176998  13-12-2016 21:21  ...      0\n",
-              "176999  13-12-2016 21:22  ...      0\n",
-              "\n",
-              "[177000 rows x 8 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 3
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 293
-        },
-        "id": "92xBt43BnjAo",
-        "outputId": "179123d5-8aec-4dda-a400-9096dec19dd8"
-      },
-      "source": [
-        "df_Ellis.plot()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1f910537d0>"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 4
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 879
-        },
-        "id": "RSo-aa-SIoBR",
-        "outputId": "75071f5e-5942-4939-a33b-2dc8780e260c"
-      },
-      "source": [
-        "# we show here the hist\n",
-        "df_Ellis.hist(bins=100,figsize=(20,15))\n",
-        "#save_fig(\"attribute_histogram_plots\")\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 1440x1080 with 9 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "gggaMJ_2LtFs",
-        "outputId": "af5ce749-d888-4cae-ddcd-9a5a5ce6e558"
-      },
-      "source": [
-        "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
-        "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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48DcTVI6MiIhIG9jjh6iHLSkVeH97FvJr2xBf1IDHvzmKpnaL2mERSY55HyLSi9SyJkfSp9vbW9JVioaISBmc1IvEYOKHqIe3f+7dUOyw2LA+vkSlaIiIiMibpJJGp+eMFhawJyIi6sbED1EPdW1mp+cSOEyKghjvBhERUagRBAG7M6uweP9xpJc3qR0OEZHqWOOHiCgECcwIERGRTs3bmonlBwsAAP13GrDk0Wm48cLTVY6KiEg97PFDpDO8nifSL9ZmIiLyrM1kdSR9AMBqF7BoH2c3JaLQxsQPERFRkGhksXkiIo/iCut9eo6IKJQw8UNE5IEgCCisbUNZY4faoRChusWkdghERKQQQRBQVMc2CLlm57h9EoE1foh0hiNBpGOy2vDsd8cQlVkFALh/2nh8cO+l6BfGT5mIiIjkY7ba8ez3iYjM6GyD3DdtPD5kG4R62JtVjXNGhasdBgUJ9vghTcmvacWi/ccRkVCKDrNN7XAoxO1Iq3QkfQBgQ0IpjhTUqRiReALvBhGRzunpMFdU14bF+49jfXwJ2kxWtcMhFe1Ir3QkfQAgIqEUh/ODqw1C8pq3NVPtECiIsMcPaUZ6eRNmLD6M1q6GzsaEUnz31BUI450NUXTU/lXdKxtTnZ77cHsWNv/9WhWiISIiPcutasF9i2LR1NFZy2v90RKs/euV6N+P92lD0X9+dG6D/HdbJrY+d50K0RBRsOOZhDRjdWyRI+kDALH5dUgta1IxIgp1HRbnXmflTUYVIpGewBRhUDrj5CFqh0BEMvnuSLEj6QMA8UUNSChqUDEiUlOrix5fFTppgxCR8pj4Ic1Ye7TE6bnVh4tUiISISJuGD2ZHXSK9WhlT6PRcz2nJiYiI/MXEDxERERERERGRTjHxQ0RERERERESkU0z8EHlhYG1pCmKs5ENEesfzNIUK7upE5C8mfoi80NM0sRQ4NrqIiLSF52kiIiLPmPghIhKB1xekJl7gEhEREZFYTPwQEYUgJhCIiIiIiEID54UlIiKv7HYBWZUt6BdmwPmnh8PAohpERLLjoZaIiKTAxA8REXlktNjwl1XxiM6tBQD8fsrp+OqhX2NAP3YaJSIiUgoTgUTkL7baibwItpMsh/BQT1LsDzvTKx1Jn87HVTjY4zEREREREWkXEz9EXjCRQj0FWR5QEv/+MdXpuXd+yVAhEiKi0MI2CBERSYGJHyIiEUKxDd5utjk9V9tiUiESbRAEAXa7OnuCEJJ7IJFnArMj1EMo3qAhIvKGNX6IdCbYhqYRidFstMBqE3DqsIGqbH9DfAk+i8xBh8WGx66aiOdvPo+FromIiIhI05j4ISIi8RTOdQiCgI92ZmPJgXzY7ALumXoGPrrvUvRXsMB0XnUrXopIcTz+Yncupow7CbdOGaNYDEREFMrUudFQ2tCOorp2TJ1wMoYO5OUjUTDiUC8inWGPd9KjYyWN+Hrfcdi6hlj9eKwMW1MrFI1h0f7jTs+9u5W1johIPuxQSGpbfrAA1364Fw8vO4LffrQPedWtaodERH5g4ofICza6KJjppSbMZ7tynJ57fVOaojEkFjc4PVdS36FoDERERErpMNvw4fYsx+PaVhMW7s1TMSIi8hcTP6Rp7L1CWsM8YCelP4f8Guc7jM1Gq8JREBERhY7IzCqYbfZez/14rEylaIgoEEz8EHnB5BORM6V/Flr4Gda3mdUOgYhcYIF1InkYLc6zehJRcGLihzSNbTnSGi0kIEKRFhKwje0WtUMgIqIQxnYxEfmLiR8iohAUaCJF6banXmoVEZH0BC1khomIiDSMiR8iIiIiIiIiIp1i4oeISIRg62Wtlxvhevk7iIiIiIiUxsQPkRccT03kTOliqsz7EBERERH5h4kfIiIiIiIiIiKdYuKHNE0Lwzu0EIM4QRcwERERkSTYCiIicsbED1GIazZasDe7GlmVzWqHEhTYoCQ1BV8imoiIiIjU1l/tAIg8YX0deWVVNuO2z6Mdj/912wV45vpzVYyoU1ZlM/Zn1+CskcNwy0Wno1+YtDuCzS4gMqMSRXXtuOHC0Tj/9OGSrj8YcHp0ItILHs2IiIg8Y+KHKIT934JDvR5/EZWLx6+eiKED1Ts0HMytxayVcbDYOpvyf778THxw76WSbuNfESnYmFgKAPg0MgffzvoNrjpnpE/vZS6yE5OyREREyuKp1z92u4AfjhYjuaQR0yeeivunjVd8kgoitXGoF5EXWj8vVDcb8a+IZMxYHIvlBwtEvddosfd6bLLacTi/TsrwRFsSne9I+gDA2qMlaGgzS7b+mhaTI+kDAGarHUsOHJds/URERFIx8FJfNH5i1Ne8rZl49ac0rI8vxb8iUvB5VK7aIREpjokfoiAmCAIeXRGH9fGlOFJQj3d/ycDKmKKA1plc0iRRdP45kFPj9Nze7GrJ1v9zcrmL9Ttvk4iIiIiCm80uYMWh3jdGv9jNxA+FHiZ+iIJYWlkzsipbej23xUViQwwtngyl7HW1M71SupWFMK3cUT3nP9uQX9OqdhgUpCw2O9LKmtBitKgdCgVAK8cjObAeG1Fg2sxWtUMg0gQmfoi80PIsOmnl8vTOaTNp6yQp5XcQV1Av3cpIdTa7gH9FpKgdhmI0fDgKOvk1rbjuw72488uDmPpOJH5JCSxpTkRE2qPnxDCRGEz8kKZpOemiBRJPduXgajiUmvr2anKlqtmIFQcLsCq2EHWtJvmD6lLdtd1vYwpRq+B26YT4ogYIPFiQSJ/sykZlsxEAYLULePWnNNjs3I+ISLu0XndSi1jEmagTZ/UiApBS2oh1R0vUDkM0uYo+ljd2yLJefy05kI///GGy29erW4y4Z2EMyrriXnmoED89cw1GDB0ga1w1LSb8qed2YwqxSYHtiuEuH6K3PIkgsEFM4mxL7T3ss6nDgoSiBvxm0qkqRUT+0tnhjIgkxKYBUScmfijk5Va14M9LDqPdbHP5utYuJgVBwJID+diRXoljxY0ybUOW1crm56RyR/IFAPJr27AzoxIPTD9T3u0m995uQW0bdqRXYMblE2TdrhRe3JCMiiYjbp48Gs9cfy7C5Oo+ppAg22VJo4wW1+cBIiIKTlprxxOphUO9SNOUOFh/G1voNumjRSsOFeL97VkBJ33MVrvb14KtmOS8rZnOz/2SIft233WxjXe2iN+uIAiol3DKel9sT6tEUkkjPtmVg6/3i5/OXs6u0w1tZjz17VFc+tZOzFx+BFVdw3E8sbvIVgqCgOM1rbB7GL7D9iBR4GKP1+EPX0Rj+rxIvLc1w+NvjsThdO5EgXH3G7La3LeDldLUbtFEHBQa2OOHQt6aw8VqhyCKq2SDP/ZkVbl9TQ9t9mD5E44VN2D2mgRUNZsweexJWPH4dIwdMUTRGD7emY1nbzhX0W168sqPKYjKrAYAROfW4vm1SV7f0zfvsz+nBo+tiHM8fv+eS1y/z/8wSYMEQUBBbRtsdgHnjg4XnaDk/iBeq8mKJ1YeRUdXb6ml0QU489ShePSqieoGRkQE9zeRjVY7wvuFod1sRWZFM84/fTiGD1ZmqH6byYpnvkvE/pwaDB/cH//90yW467JximybQhd7/BB5EWzDnnx1xMPsVnr9m7Xo+XVJqGruLAqdWdGMt3+Wv6eS1u1M752UjM2v8zoEp28vtZ5JHwD494+p0gRHmmW12fGXVQm48dP9uOV/BzBj8WHRQ7eO5NfJFJ1+bTpW5kj6dHtjc7pK0RDpG3uASUcQBCQUNeCK93bj3q9jMW1eFPZlVyuy7cUH8rE/pwYA0GK0Yu7aY2jV2Iy6pD9M/BCRk2Ab6uWSTH+ClCOcCmrbUFTX3uu5HemVbpbWFqWbnhYvXaF7Jisrm7wPDQtWnL3MvajMakRlnkgaxhXWIyKhVNQ6Shu0Vdg+GGRWNKsdgmRyqlrwRVQuvjtSxIswIp0TAPx3WyZaun7rZqsdb/sxXN8f83fn9npsF4CfEsWdr4jE4lAvohDl8fpRw9eWZY0dWB5dgMZ2M+6dNh7XnHuaotuX8rq71Sj/hYVcSTwN7yJoN/OCLRTNXpPg9Nxrm9LwyJVn+bwOFgENXamlTZixJNZR8++nxDKs+9tV6Bfkhe+JyDVBABKKGno9V1DbhsZ2M04eOlDxeOIKGzCTQ2RJRuzxQ5qmhZvboXgh4KpQrhZ0mG2YsTgWKw4V4MdjZXhsRRzi3AxZ0+ZfQP4yWnzv8RMWij9aFeix9xH3ndC14lBBr4ke4osakFTS4OEdytBFD1wKXnre/dz8bTaVCl1uSS5XZbsUOpj4IdKw6majbCcgTxdtLUarJru578qo7DUUw2oX8OWeXA/vUJ6Yb0uqBn2z0aL496W1y+OeyUo9X7vLOZuarxKK6nHb5wdw6Vu78HJEiscZAomUIEUO8qdjZU7P/RBXEviKiSTk6RRgtdlR3aLfoc5SY1KVQg2HehFpUHWLEU+sPIq0smacNLg/5j84FddfMFrSbbR5mMJ+7dESRCSU4slrJ+GV2y/UxMUmAGxJrnB6Ljq31uWywdAbIdCcnt0u4K0t6VhzuAhhBgNmXTMR//nDZM18X0rq+VGy14Z8zFY7Zn1zFM1dwxTXxZfgjFOG4LmbzlM5Mmlw1yGtYTFf8sWu9Eq8sD4ZLSYrpk44GcsfuxynDpNvuJIgCEHf1ghzM4xT+63H3ubvztXNOZjkxR4/RBr08Y5spJV1FsxsNlrx/LokyXv+tBgtHl+32gUsPpDvcfYvCkygyam92dVYFVsEu9D5fS2NLkCsQrMSaa29J4RIjx+17c6sciR9un0WmaNSNNLjRXZw4m+eQpnJasPctUmOIsXHihvxeZS8x+UguLfm1cB++rgM/iwyB2llTWqHQUFAH3s86ZYWGnNqnNw29JmJprHdgtjj0l7Q+9or4pOd2ZJuVymuvrbyxsBn7JFynwx013ry23in5z7cEZzfV6B6fpbBfhdSywr7zEKnN9x1iEjLBKHzRseW5HK8tzUDkRlV2JtVjQ5L717cq2KLVIqQ1PDVnjy1Q6AgwKFeRBKpazXh633HUdrQgdsvGYO7f3WGpOt/bu0xJL5+i2Tr8zXxk1PV4vJ5QRCw5kgxDuTU4PzTw/HsDedi6EC5DymBpUr6NozUFkhS0d2U5SmljZJtI5j0Lu6sXhxy89RLTBAErDtagj1Z1ThndDieuf4cDB88QMHo1HXS4P5OvZHE0vO+IxcpDzFljR1Ysv84alvN+NPUM3DzRadLuHbxtLA79D2mk3d6T/5/uisHX+3tvNBfGl0g75AuN79wPTctgnHvKahtUzsECgJM/FBIs/swfKpv+8FmF5ymdxUEAY+uiEN6eefwrB3plRAE4P+mSpf8qW8zo9nL8CwxfG0XuWtALdqfjw93ZAEAIjOqkF3ZgmWPXS5VeLKQ4mQuNpFiswsIM7j7HP1rOlltdjy49LDL10Il0eOkx98dqsN1vo0pxFtbMjofZFQhtbQJa566QtJtaLkYphSRheq+owUmqw1/XhKLkvrOnpnb0iqwctZv8LvzR6kcmbrK3ST5KTTZBcGR9OlW32ZWPI7OmxDBfbxsczMphnbPckSB4VAvCmkxIoZP2ewC3tychsve3oVrP9yDnemVjteSShodSZ9uH3UlRaSU0WcbgQj0xPZhn78vKrMata2mANfqTWCNDCnuAhp97DUkCAI+3JGFqe/swtUf7MFPx0pdLONfDNG5tbq9u+Nv3aO6thP7npheG3Wy77PKefuXjF6PD+bVorRB30OztKS8scPn4wM525tV7Uj6AJ3Hx892hebQVSJ3mjqkuwEY6rIqXfdo90d1i9Fr7UwitTHxQ5omd++F+bt9nwr8h7hifBtbhFaTFaUNHfjb6gTHXRZXBZDluEsn5eeRXOJb93ExuRK5khEnYvD9A3D1WUkxjKPZaMX6o+6n+O3e7paUCny97ziajVZUNBnxz/XJKO5TH8Xfr3NfdrWf79Sv4voTn62YBJ8v0zVbbXY8v/aYX3EpydU+n1UhXcNWKwRBQG5VCw7n18FklTbREuZHq6ip3YI/fBGNqz/Ygwtf34GIBOckbyj6JaVc1PK7Mqqcnksu9a1gacj2dKSQo5VdXStxqM1ktWH26uwemB4AACAASURBVAT85r3dmPpOpOxFtYkCwcQPhbS4Qt9nrHptU5rTcwu7uts2tiuT5Q90mEVWZTO+jSlEXEE9ShsCL3QcbKQaxvHKjylo8vKdv/1zeq/HggAsO5jv9Jw/GjVxx09bXbxHDhvk+Hdute/JjoN5NV6X2ZpagU1J4i5i9UrsPlvZZMT3R4qxK70SZqtdgu0LeH1zGm753wH8eclh3DH/IGpapOu15U+vwFc3pSKj4kRvzBc3JKPVzRCCUPLC+mRRPaC0OMxOK6VivJ1vSLz6NjM2xJfgl5Ryt0N+NEnhjIu7Yz6TrZ1+TCzDjq4RAFa7gM+jcpFVKV3vfCIpscYP6Vp2ZQs2JZUhfFB/3D99PEYPHyzp+pcdLMBrd16EDfHeew2obWd6JZ75LlHyaeF70lJDwFUhZ6ka8XYBiEh0fVe/ext1Lsbcp/S5e+1uWFNJfTvOPHWo2+1vFpGE0NBX4hN/d8+R4SeKWy7an+9hSfFe+8k56Uve5VW34oHFsY6ekTdPPh1LH50W0JDL4zVtWHO4uNc2vj9SjLk3n6fazv5LSoXTc0sO5OOft5yvQjTaYbLaEZlRhbsuG+fT8lpJsrhTUt+OiIRSCIKAe6eNx1kjhym27Q6LDSMQOoXa5VbdYsR9X8c6eopOnXAyfvjLlRg8oJ/KkZEWmKx2fBtTiKK6dtx80Whcfc5pvV632wX8ZVU8dme57n29cO9xzH9wqhKhEonCxA/pVm5VC+79OsZx53VjQil+ee5aWWaecnWRL4sALmwW7T/uV9JHTFvcLlPmR0sJpW5S1DNy92dd99FeHH31ZowaPsjNEvKqaOrAgr15qGg04o+/8u2iTSruZpHzpudnWVLve10bX/atFg3dDRb7U1Dzp/NDXHGvoqNRmVXIrmrBhWNO8nudSw4cd3ruf1E5nYkfCUg1q9dXe3JDPvEDiOudqOW8T02LCfcvikVlc+cQ7u/jirFlzrUYO2KIZNtIKPK9BzIF5uek8l7Dg48VNyL2eB1uuHC0ilEFFy0X+g/UM98lOsohfBNTgMWPTMOtU8Y4Xj/7P9s8vp+19UirONSLNM3fO4B2u4Bb/negV3f7/No2RGVqrzaKIAiw2HwbAhHIafZYsfxTwvr6d4h1/7TxsqxXaX2/P09Jh5nLjzj1CDJb7XirzxAyqdnsAh5aegRrDhdjd1Y15q5NcrmclHfnew4B8ncfEgQBX+7OxU2f7hNVa0qLSUW9WH6wwOm52z6PxuzVCahu8a8GWkuA07V7I9VwIxk7VmqOVIcCLfb46d4fNieVOZI+AFDbasb6o9LWcvp6n7Q9FdVkttphsdn9LtYvt3lbM52ee3drhosltUcrCRdXX63VZvdptlyt61kDUxCAz6NO1AP1ZciyFBOJEMmBPX5Il/70dYzL5785VIA/+tjtvNv2NGlqU7iyI60Sb/2cjoZ2M/542Ti896dLMLC/+3ysGm0oMSewI/n1uO486afeHX+K+2FPYnj6UwRBgMFgQJvJitpWEyZ4GGrlr4xy34Z6AZ2zTSQWN2LaWac4nvssMgcrYwolj6unmOO+zRgmxb7Ybrbin+uSsTurCmNHDMHH913qd1f7tXElTlPc+oLtM+XtSK9EXZsJG2ZfLfq9ch8DpdofHpiuj2S1L6T6SrRY46fbJy5mF5OypxnQ2SPOnWA5TmWUN2POD4k4XtN5DhnQz4D377kU9wXBzZuexxZBEFBc347Twgdh2CBtXSop3Q70ZXOCIOCzyBx8c6gQA/oZMPem8/D4NZNkjy1Qvv6setZw8+WmhVQ9R8UIlmMEqUtbRzMiibibscrfE+bKGOc7193KG/0rktzYbsacHxJhsXUGtSGhFBeMGY6nrjvb7XseWX7Er21JrdnNlJX7c2rw4u8vkHx7Up3QPCWxBKFzaMqbP6c5vhNP/NmXLDbBkWDyRUJRfa/Ez6L9zsNcpBZzvM6n5aQY6vbF7lxHUcTi+nY8vOwIwvz8sv1J+gBAh5nTb6vhaGEDalpMooczyn2329/9ry+p68lpSUObGYnFDThnVDgmnqZcnRs1dO9vUu0XevfMdwko7DF7pcUm4KWIZFwx6VSPdeuk5k9Po+73NLab8dg3R5Fc0oj+YQa8+ccpmHnlWT6vx2S1IaGoAYMH9MNl409GP4mzAFrsT7Mnqxpf7jlxDn5rSwYun3QqpowboWJU6lEjia3RznWKqG8zI7GoAeefPhwTRip3nAlGTPxQSGls968Wz3+3Zbl97bqP9vq1zs1J5U4JhnlbMz0mfrTC3XALrXRBdsfTqbipw4LXNqUGPESj3WzzOANLVmULJo/trHHibVN6PJE3tVuwK6MSdkHA4j5FmK12AUo3a/NFDAsLRlIPtZCy92NDu1l84keHv4lgklLaiIeXHXGcA9666yKVI1IGEz/e5VW39kr6dBOEzmGfb/1xigpRibf4QL7j5qHVLuCNzWm469KxOHnowF7LxRXUI7mkEdMmnoJfT+i8QdNstOCRZUccEzncPHk0vn5kGgb0k66yhtLD59zt+T3DcDV07svdeVg0c5pkcTS0mRGZUQUYgFsvOt3p+9AUPw8Xp4Vr+G/SqMTiBjy6PM5R2uO9P12Mh6/wPVEbavxO/BgMhkcArO56+BdBEJZJExLRCWLOb6mlTfhoZxaic2vdLuOqURIof2fJElOHRE2uzl/ubmC1ylR/Q6omt6fG+8bEUlFJH09TSN+/2PVQQ6Cz8dLNWzFsKZp3zSKnfpfz8qapw4L7F8cgp6pVxq0Ev6iMKuzNrsa5o8Px0BUTMKi/dmaaiTnu/vjaU1yB90K1jZyiOujM353XK/H/0c5s3HHJWEnWfbxGe8eF7jv3zPt45+nGWs+hMlr39b7ePWsFAYhIKO11U+6bQwV4e8uJmkAf3nsJZlw+AVuSy3vN3hmVWY24gnpcc27vWaGCiS/tEFft2eRS6epKNrabce+iGOR3DSFcMjocG2dfjRFDlZ/pzpce2/4eLgLJ6YXqMWr+7txe9Vw/2J6FGdPPRH8Jk6164lfix2AwnAngKwCtAMIljYjID2llTbjrq4NqhyFKUV1wJH66tZms+F9kDtLLm3H2KNfd+wvr2kUNZeqr3s3saJ9G5qDZaEG7jMNyalvF9Qbb6GY6dwA+JzasXjJNUtzY2+2hboQrcjYe9mZVM+njxYb4ErwUkeJ4HF/UgAUP/VrFiHo7Wtjg03IrXBR27isyoxK/mXSqqO27+0k8uOSwJLOvSdWzQ0DnsM7lBwuwJ6sa54wKxwu3nq/tu9Q+6FuHpt1sw9FCaWajii/ybd9SUndynj1+9M/T6bauzYwOsw2fR+UgubQRh/N77/Nf7zuOGZdPwKs/pTm997/bMrH1ueski1Pp2snu2iHeenhL2TFpZ3qlI+kDdPYui8qswr0arR3l7+EikMNMqPaG3Zdd0+txi9GK5NKmXmUS6ATRiR9D5xXdNwDqAPwI4EWpgyISa1l08MyGYbN3zuK1t8/Bqtuz3ycqHJFv/rEuCbsyOhv9sfnu68BkVDSjpsWEj3dmo7HdgieunYQnr/WtyN8rG1PcvrY02vuFZCCU6j7dcyulXqYdt/aY4Sqv2veEyZbkctzVVcT89c2+zQJ255fR+MfN8k4//e8fU2Vdvx58tLN3EdmtKRV4+48mnBbeNSRKo407o8XWqzB3d+0mT5ZGF+BoYQNunjwae7KqUdtqxn3TxmPOjee6TR67qy3l6ZgkhtiGt7sen20mG5YcyMf72zuHCcccr0NWZbNfBa21zlsC2xfbUisCer+33pP+SizuTEbJXazVWxuGaSfPOsw2DB4QJutsSi9GJGNriuv91FNvcrlnIpSbu49UyUTDyxud2w4vb0xRJfHjyx7mf6LY//3XaLUFdONVT/wdiREK/Onx8xyAGwFc3/V/ItVtSir3eVm7XUCYGiX30Vk82NvFr7uGhZpajBZH0sebH+KKseZwsePxu79koN1kxRPXTsLA/mHIq27FpNOGOc3eVNdq8nkbYuIePti3rsByXTh44m2LB3JrMOem8yAIAh5bEefzet/bmokLxwzH09/5nkRMK2vG7DUJCJdwBhOT1Yb8mjacMyrc42x1dIKrIYSpZU244YLRfq1Pqb364jd34o5Lx+Lj+y4T9V0nlTQiqUcx/s8iczB2xGDcP/1Ml8sfK5Zu+IArYs8MsW6Kof+SUu7Ui/BoYQOK6tpw1kh9FUSW4tD5323ONUJ8telYmcsaI1Lonp1Kzh4/icUNXuMP9ssYuT69NpMVc9cew56saowePhgf3Xcpfnu+fzOLetqPO8w2v9tmFU3+TQBCCpBpx1Qj91JU144r39+Nj+67DL/z8zdA+ieqJW4wGCYD+ADAF4IgHJAnJNIKk9WG6NwaxOTVyjaduRqkuDvpj2PFDUHZ48FgEDcMqmfSp9unkTmY8uZOnPfqdtz+RTSmvRvpVCvk+yPO7wvUJW/t8nlZpXaLno1Lb3cluofVxBc1oEzE7HGVzUbMXZskqpcQ0DkDS4OfdVfyqluwPbXCMdVpQlEDLp8Xhdu/iMb0eZGOO+ekT1a7gM1J5fg2pjDg3nOvb3YeLqEUsTcFfk4uc/m8u2NmLoc6ulTa4N/FcXWLEc+vS5I4Gmdy3kX/1MVU8X1lVbbItn2pePrVy3V6/XJPHqIyq2EXOs97T69JgMkq/ZBwsbXyevJlltBgpIe/KseP35UvhwI1ZvUCgKpmk2y/AdIHnxM/BoOhPzqLORcD+I9sEZEmtJms+POSw5i5PA4PLTuCmcuPwGhR/kCipx6Lf1rovuCvtkl/Cmsz2/Dapt4Xd3ES1Ynoq+cJ8EiB++Egy32oSSI1b8mmKeM6Z//ypxC4EsU0m7oaw98cKsDNnx3A098l4vqP9yGhqB5vbE5Dc1cX92ajFfcsjEGHCscQX4hNkCltXVwJvo0pRHWzUe1QvHovgJ4b3YwW9W40iD3Wia0NRtJaE1ukyHbk7CR8KM/7MMUyEYkxu13ArvRKLNyXh7SyJu9vCGKL9vcuxNxmtmFXurQ9h0Od2xo/Oigqs6BPIW+pBFrjJ6O8GV/vO44daRWwi7wr2W62YSd/A+SGmB4/bwCYCuBxQRB8PgMZDIa/GgyGeIPBEF9T47qmCWnProzKXl3qjxTUY192tYoRScffKd1DldlqkyUBl1/T1muGK7msO1oCAFhzuAhz18p/Z9ibngURvTWcbrqwc3jPgRxtHjsfWnoYzUYLPt2V43iu3WzD51G5SC8Pnllc1Ej6ibEjvRJv/pyO/1twCFUikz/BmjtX7aIiWD8wFZWrOJTluEKzY6p9ievpHGy22rEsOh8vbkjGz8nleGtLOv66OgEf7cjG3QsOYU+WMheBnn46Sv6sKpo6/Oqh5bFYMY8LTvRQRsXT7Kzu+HIr1N8eggYA+3NqcPeCg/hwRxZmr0nEq5vE94Ct5PBCcsOnxI/BYLgCnb18PhUEIVbMBgRBWCIIwnRBEKaPGsUxh8Hi5QjnIUl9e2gEq5+Tfa8HRJ29Nfzthu+NxX7izr5c13ndF/UL9ubJs4EAePub+4V1HqJ/0WDdJwBIL2/GV3vyek2lCQDRub5N+a0VP8RJP8xQDuVNRrSJnNkuWNvm/g45DJRaXfSDmQ5u/HvlzwWilDztlS9FJGPe1kxEJJTiuR+OYVWPXlA2u4BF+4Jn8gsp2PzsMCjXfjxyWHDP5Ocuh5FT5XmYlLdZvwKl5REBgYS25MDxXsMDf4grFn3DmrOnkjteEz9dQ7xWAcgB8LrsEZEmmF2cOdWYmUCOE7FJR/WKlPLwsiPyrFjo+U95Ggnd9akqmrQ3TMaXgtJiu/kqbcmB0LqoEKPZqE7yQg/E9mySipYvJvxlswtOydmeBEFwDNskbXK3Xza1W7DZy+QWcg2j1io1yhJ4cmqQJ37cNVPuXxSL97ZmyDKDktlqR4fImxxK8anGTwDnEVdDP8XeTItIKPU/ANI1X6ZvCQfQPcev0U33taUGg2EpOos+Py9VcERy0MO4ZL3o+U3YQzAf563Q+Pa0CnwTo+1hSOQsr7oVf10dj/yaNpx/ejiWPjpddzM5yS21rAmTx56k+HbFtte1nifamlKBVzelornDgpsmn475f56KIQNPzKiYVdmMv61OQFFdOyaPPQlLZk7DmacOVTFicsVdT7S8Gu3c2ddKy6qx3RxQMWZXAmk26jGZ3G1pdAHGjhgi6ToX7M3DV3vyYLMLeOiKCXjjzoskXb8SpJ4FUCu/LQp+vgz1MgFY7ua/Y13LHOx6LGoYGGmTVuuJSIV5H+3I6FEHpl2mu3QTNXbB3b3/lTV24OOdnmdzyapsQaNKQ15IHJtdwNHCemxLrcBfV3UmfYDOLtcvb0xRObrg03OKdyXp6SKt2WjB3LXH0NhugV0AIjOqsDS6dw+9f65LRlFdOwAgs6I56IZ0+zvFtq/kLOosilbi8JM/ExT465RhA/FZZI73Bfvw1DbcnuZ9Pyvu+h1JpVKDvZRdeeeXDMnWlVLaiI93ZqPDYoPZZsfKmELsyqiUbP1K2Zddjc1JZciqFFfrUOqEEVFfXnv8dBVyfsrVawaD4S10Fnz+VhCEZdKGRmp5Q8GpdM1WO7amlqOkXrlCZNF5tZhz03mKbY/c61kUNFmmC72bJo+WZb2B+mqP9moOkX8EQcBLEcn4MdH11N6H83sPtSipb8fW1AqED+qPuy4bhxFDBsgYm2yrllV5ozrFKfXU8P4xodSpV+FnkTl4ruv819RucZr9b38Q3fiRY4hJX3f/6gzZt+GL5JJG2O0C6trMuP3iMTh7VLjaIYlSrWCNJAMMkieafJlp8PPd4pNNnvxzvfqTUSjt86hcp+fe2RJ4Yknp4X92AY7JRN686yLMumZSQOvjSAWSii9DvSiE1LWaUCjxXQtP5q49hu1pymbz4wrqsSq2EI9eNVHR7ZI6BvYXM3mh/LpP38FSUJi8K6htc5v06WtHWiVmr0lwPP4hrhgbn74agwf08/Cu0NNfpa4Wcm9VybxSmZfkmckq/8VQVoV8s/sp0StsaNewuAH9DL0KrirtuyMnzheL9h9HxOyrccGY4ZrqoWbxUD9RyTjlLirsjrtzgD8F4+12ATHHnWu96F2Gi9lAy930fPLlc/0lpRxRGVXY5KUOlhjeilr39VlkDmZeeRb69/PeFr10/AhUZgRHTy8KTtq6IiLVeao5InVR5JL6dsWTPt3m73a+q0DKU+LueqvJqqlij0aLjXdvdObGT/f7tFxJfXuvpA/QOTOa3LOg5VW34pnvEnDPwkNYHVuIqmYj/rEuCXcvOISv9uRqsoB4P7USPyKPSbuzqmWKRH5KfOs9ExZSMyl4XD9lqHYK9LYYrVgVWwhA/R59Pc9lRwrcF5FWO041eUtEuWoPfLgjS5ptS/DB+5tIEwT32//pWCkeWBSLp76NR2ppk+N5Xya88NXKQwX4+/fHJE36AMDM5XGilm8xWpFZ4Vuy6KyRrK9G8goo8SMIwluCIBg4zEs/lDw5b031PmZarrxAbau4qREB4LzRwdW1OhgocWm3PbUSb29JV2BLvjEA+CGuRO0wSAWrDxe5fP6rvfIN+7PY7Hho6WFsS61EYnEjXt+cjiv+uxs/HStDckkjPtmVg8USz8wmxXnEXeJn2lmnBL5yD8Scc9SqQ+QrT0kss9XudiavdUddJ2uqW0LvTnT3R6i1vIWcCTVfNLab8dS38bj07V14eNlhlDd2ONWPkltetbSFra12O15XuMbVioMFuOaDPfjdx3t7zcQk1TF5+UFxk0MIgoDaVpMkCaPqFhOu/XAvVscWAujcZyw2O/ZlV+Mf65IRV1iPqMwqPLTssGO6cil/Z29JMERMKjWtRk3eYAk2giCgpkWa/TNUcagX9SJlF9miuja0GK24aOxJCHPRiA+23+3wwfy5SE2JXSC1rAmpZU3eF1TQWz9rJxFFymgzWbHEXWNexoNhZEaV1/oaH+7IwtPXnyPZNr+JKQx4Hf3CXN+XGiLRkDh3DUcxwzK03nPU3V+yeP9xvL/dfY+ClzemYsq4Ebj4jBG9nl/LhLXmqDXU69VNaYjKrALQOf303LXH0C7T9Nsmqw0/JpZh4shhuPLsUx0JzaMST1Nf1Wxym5yXw6G82l6FkV+KSMbFZ5yEC8dIN5vhvK2ZeOq6sz0u02y0ILuyBWEG4LkfklDW2IGzTxuG5Y9fjkmnBTY5RlljB17fnI5PI3PQ2G5B+KD+aDVZey3TYrRiY2IZnrx2kmSnQi318gaAJ1bGY9TwQVj48K9x+cRT3S7n7u8PtuslORTXteOJb48ir7oV40YMxpJHpzudo8g7DvWiXqQ4uNjtAl7akIzffbwPd355EDf/b7/TgV7JeKQidggAkTtmWwjOXR/ipry50+1rch7mArk4stkFxOTV4qdjpaht9b0467sSzPIyQMKhXtXNvXuqGC02PLrCdXd9MYf5PX4M85LrnNZqsmJ7agUiM6ocFz3uzlmekj7dXCW1gnF2Hanw7N9b39nUjhY2yLKdvOpWXPDaDvz7x1Q8uPQwJv17G6xd508ttQ89cZdM/qjPrJ6CoPykD/uyqzF9XhTuXxSLe7+OddQFy69tw6s/pUq2ne7ZSd1dC+zL7j6WSvOldsiUhAwkoVTTYsLcH46xt4qfXtuc5ujlV95kxAvrk1WOKDixCwNJLrm0ERt6dFnNr2nDf7dlYvKY4ahrM+OOS8bivNOH+927qLHdjCUH8rE6tgh/uGQs5t7MGbqCFRvTRNq8gBEEAS+sT3LURzgtfBDW/+1Kxba/T8LZpZYfKsC/b5/seByZUeW2rpLcx6SsymbcfNHpkq6zsd2MGYsPI7ur6Oi0s07BmievCKg3yKE8eetOSUKBE0j3RbsGf6IA9H8OveV/zvXTIjOqcPslY922IbV4PHXF1UymsQoXdH57SwbMbup3xhyvw6G8WnzcJ0Elh+jcWgiCADGjocw2OxrbzTjZRf0tue7TmnyY3c2T8iYjcqpaccGY4aLe525Ybig50KdNkF3Vgvo28WU7Qh0TP9RLs1H8wWVzUhl2pVdhwsihmP27c/D0mkSnZb7vMR596YF8bJh9tV8nZ6PFhtu/iEZFV5X/dfElWBfP7ucUPJ7+zvn3QdqSVdmMb2OKYLXZ8fCVZym23YX7pL/b6+9FUEFtW6+imLWtJkXrirhr0PnToF+8P79X4uc/Hu5ky92xc8He4/j7jdLerNiWWulI+gBAQlEDonO1Oy17Smkj1hwuQr8wA2ZeOTEoLmq0epdem1FJQxAEl8evp79LROEHd7h9n6eaaU+vSfA41CaUVLcYvU57//CyIwpFA0z69zacMnSAqPf86p1IZM+7DYP69x4C7M9Mar6QohxGq0n88e5NlgdwyV3Sktxj4od6+cnHKYm7RSSU4sUNJ7rbHS2oR2Wz5wKQbWYbvo0pxAQ/qtdH59Y6kj5ad/7pLAbtzeSx0o1lDxY2FvjTpPu+jsGsayZh2lmnYMbiw46L0Z69F+WSWtaEmcuPyDK7l7fjcbeYvFos2JcHk8WOx6+ZiDgXM/SILRSqVS1G90OP5R7S2+FhqMCq2EJEJJTitPBBeOHW8zFlnG/1C1wlst7YnI57fn2Gv2GizcVQCbsEbezC2jY8uOSwY/1aL3S/+nARRgwZ4NeEEHqVXSluOmtPjBYbPtiehcP5dbh0/Ai8esdFGDGk8+Lf39p8ns6x29MqFZ9NVswhpa7NjKZ2+ROhgiDgN+/tln07YjX48bdHZVTjjkvH9n5SpsO4FM23p9ckYuPTVwe+IiI/MPFDvXibSWD26gR88sBlCB/Uuet80KdWQHyRb+O818WXYM6N53pdru8sIksOHPdp/VogVRFSPRvc4zM64+QhjvHlREqLL2pAQnEDrjtvlCo9EOSe0t2bWSuPwtR19yyhuEET01e3mawYNkjZZopapdy2JJfjjc0n7uomFjcg5pUbMXSgf39/ZbMRC/cFdr4UBKFXIqzFjzvVfX1zqMBlUknL5Jx1L1Bq7K5ui9T74a2f07H2aGfyL6uyBXWtZix//HIAwEYvSXeNdsLyqrrZiOfXJbl9fe66Y7JtO6uyGS9uSEZaWbNs21DayxtTnBI/ch3HpbhxV91iwszlrntSBekuTUGExZ1JlB3plXhva6bjsZiCn3196UMRu+jcWuRVtzi6WQfriZ68mzIu9Hr/kLYIgvM48mCxI63C+0IemHp0mRYE90OtlFTVbITNLiCltBGZFc2KDLeRa4iAN+/0KYjd2G7BL8mBfaeBkmM2xG9jlZs1ieSxMVGaXpB2u+BI+nTbnVXtKMzr6ddeVNfmslei1rWarLj2w72I8VDLZ1+2tOegHV09nARBwFPfxusq6QO4HoYp11H8s0hp6h0V1rW7fL6iSVs3P1uMFsTk1QZ0rUfawsQPifZDnHJ1HgDg5s8O4N8/psJuF2BXMfOj9yKKauh5V4aTphH5b7aL2mrBrt1sw8PLDuOPXx3C7V9E4+k1ibDIPCOeWg3vmhbnhnWcxNNVi/XOlgwkuShA6y+ph7mKSdJ1mG3YkVaJTcfK0NiuflKzW2aFvi7Cxdjvpg5Vu7lzKGZOlfshZb/7eB9+Ti53+7qWZHUNjUsuacRV7+9WfFbPf6xLgslqQ2pZE0obtJVYkItcQ3blHpq6LVU7MyceK27A1e/vwUPLjuCK/+52msmPghOHelFQWHu0BDOvOgsWm3qJH7FbZuck71iYjYjcufPLg70e70iXv1G8KrYID0w/Exef4Vt9HT2LL2rA/y04hNfvvAhPXjsp4PUlFssz5bc3RosNj6444phy/KyRQ7Fh9lUYPXywKvH09Oku+WdM0or18SXIrWrBb88fhf5hYZj1zVGPy+uprlJlkxGf7Mr2WF9MLh0WG/ZkVqN/P33erG1G3QAAIABJREFU63fV1uZ9xMB9tCMbLabO/dVmF/DOL+n4wyVjZK+DJwWtFuPXAn0eBUiXvtqTJ0vXc1LPcz/IN5adiMgf3xwqVDsEANoZ2vzuLxl4YuVRlNQH1ltA6iSHL9cfm5PKcKSg3pH0AYCiunYs8GGouRKiMqvVDkEx/4pIwdLoAsxcHocHlx5WOxxFrTlcpGodt3oN9XKj4BCb33s4YlWzCcX1roeoqSUIclCawx4/5JfKJiPGjFD2bpnaU77y+CK9/No2lDa0Y/wpQzVzkUNEoW1jYik+feAyx2ObXUC/MAM2JpRi+cEChA/qjzk3eZ+cQIo48mtb8bffnoPbLh4j+/Y82ZPlf4Ji4itbA9r2gZwaXHPuaegXJv4sPHet6yK638YW4eXbL/S7eLYUmo2Bt2mUuvtuswv4JaUcKxSY2S+5tBHLDxYgr7pV9m0pZdlB6Qpi+0vvvSCyKpvx/rYsVDR14NaL1D1e6tXDy45g2MD+uHvqODz9u3M02/tHq3FpARM/5Jc1h4vwwq3nK7pNnZ+zQlZ0bi0e/M0EtcMgIp3LrmwR1cvwSH4dHv/mKGyC4DQsdebyOMnisnqo+XGsuBHPfp+IX+Zci8ljQ7MA/qMrOj/rS84YgS/+/CucPSocHWYb/rwksF4j21Mrce+08VKEKJrNLmCHhup5uFPTYsJzPxxzuvsvpydWxiu2LaUYLRzWLhdB6Cwb8MiyI47hgTlV2ujRpzfdNaI+2pGNU4cOxJ/Zdg86HOpFfvlqbx7uXnBI7TAUxbwTEVHw+v3nB5DtoWBsTxsTSjFjyWF0WGyy1iKLK6jHtHlRHpex2QUs0PCU4kpJLWvCbV9EIyavFpe9vSvg9W1PUyfxklTSiAte245/bUxRZftivPpTqqJJH5KPntuwUZlVuqoJFQxe35ymdgjkByZ+yG8ppay3Q4FjTy4ikltBbZuo5V/YkCxTJL29FJHs0zDmX9zMqCL1TFlaZ7ba8dCyI4rPjCSlVzamwCrB93YgR9ppv13ZlVEl+zZIfoKg77YWr0eUp+ZkO+Q/Jn4oaAhBdr9CzydZIqJgUtVsVDsEJ2WNHSiqC6xY5jGVZsoi/7SbrY7pvQPVPQSOyBs91UvqS4DAIr86IwgCfk4uxxub0/BjYqnu61MpiTV+iHzE84o8uhN6PHETkVy02DPGZLGJWl4QBKeilZ/uypEypJCSUFQf8DoEQcDKmELsza7BuaPCMffm8zBiyAC3y0vR04dIrDaTFXod7GWAge1zlcxenYBHrjwL1553mqTrXbA3D590ndtWxRbpOnGpNPb4oaCh9qFdn6dM7WBCn4jkEpFQqnYIAUsvb3Z6Tu3ZLoNZQ3vgn92SA/l4e0sGDuTUYMWhAsxeneByOUEQYLKKS/T5ghe8FOoECAjjnUNV7EivxKyVcUiVeKjdJ31uaCzcd1zU+9lDyD0mfihoBNtQLyIi0oafjpWpHYITsVPOPrzsiNNzPCuq6/3tWb0ex+bXobSh9/C9qIwqTH5jBy54bQf+4WZ6ebXZ7ALyqltkSU6R+gTo9+aaILDHuJosNvUmH6jzoaB3u9mK/JpWJoO6cKgXEamKx2IiCkVir1WaOizIKG/GReNCc1p3OVQ0dSCltAmXjT9ZsnXmVrdi/ClDAQAtRgueWnVievLdWdWSbUcquVUtmLk8DpXNRoQP6o/FM6fhmnOlHbpB6tqSXI4bLxytdhiyECA+iR4qBEFAbnUrSurbcfmkU3HSYPfDUAOxI733DIm1rSYkFjXgwjEnYcLIobJsEwD+MD/a5fPd+8PGhFK88mMKLDYBF44ZjlVP/gajhw+WLZ5gwMQPBY2aFpPaIRAREanmq725WPjwNMdjLRatDiZXvb8HABAm5XVjj5sZH+3IlnDF8pi3NROVXftRq8mKf0Wk4ODLN/BiWkdMVjssQTwTnidmq13a36+OfLorB1919cY5LXwQ1v71Spw7OtxpOavNjqjMapQ2tOOGC0fjnFHOy/gqrqAej62IQ0dXDbsP770EMy6f4Pf6/NVhtuHfP6Y6Zh/LqmzBV3vy8M7dFysei5ZwqBcFjeM14qbj9cW4EcplfsefMkSxbQUTdvgholDkz3V132mLecEjDblqLq8+XCTPiiW0v8+08GWNHShr7FApGpJL3+9ZT9SuAapFDW1mLNh3YghWbasJy6LzXS77woZkzF6TgHlbM3Hn/INIKPJ/tsj/ReY4kj4A8MH2LNhVKGq/Pa0C5j7JzlWx2j8ey42JHyKZ9K1JxOJzRETUfeddiouV008K7W7rWqRkPUK5mhXdd8lJP5o7rGqHIBs2r51tSipzKqWw9miJ03LljR3YnFTueNxhsWFlTKHf243Nr+v1uKHdglwVZuVqlKB4vx4x8UMhjU0bDeg6M/G7IKJQ8N9tmQG9v9184gKONdK0R8nv5NnvE2VZL3uS6Y9eh3oBnN3OFZPVt+/b1cQHW5LLXSzpP7uGTlRWmx1GS+gWsWfih4iIiEgh3xwqBODfXerShg5c/OZOPLYiDi1G3tEMdSX1vg3Jyq1qQV2r73USDTDgeI3yd+lJPo0d+j1ehDFT6URDuRbF2ewCsitbXL429d1IXPb2Lrz1c7oqQ9DUxuLOFLI4tZ9GsI8uEZHP7EJnvY7Po3LVDoVc0GLT4pb/HQAA/POW8/HcTed5Xf7h5Yd9TipRkNDijkmycTfktM1kxbBB+r78f3DpYbevtRg7e8yujCnE1Akn4+5fnaFUWJrAHj9EPmKiSCZdnyvTP0QUSkzWwLqbLz9YwFm9SJTPInNQ2tDudTkmfSiYsIamM3eXLD3r+QChfe/19U1paoegOCZ+iBSiZMFHIiLStsiM6oDXUddmliASkpLWz/TdQw0ptOh5VEsoJy/EKmvsnfgN5XvazUb9Fjx3h4kfCmliDngGkWeWUD6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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "R_ctvXcQL1Xf",
-        "outputId": "8beab52c-ffb7-415c-c84c-04ed39cd70cf"
-      },
-      "source": [
-        "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
-        "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Timestamp', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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hJBcm+ada67XdzAkAAADAyOo6eKq1npzk5C77zslavoys1nrH2p6v0ffrGfoZUAAAAAC0pO1vtQMAAABgAyV4AgAAAKARgqcNVK1tVwAAAACMdYM5XJwe9evHF+cv/+2Xue2BJ7Lf1BdnnykvbrskAAAAYAwQPI0B7//Wf+UX9z+eJPnhbQ/nh7c93HJFAAAAwFhgq90G7tGnlq4KnQAAAABGkuBpA1VK3/XJJc+2WwgAAAAwZgmeAAAAAGiE4AkAAACARgieNlDX3Dmv7RIAAACAMU7wtIE6/ap7MnveorbLAAAAAMYwwdMG7JD/e3Vunruw7TIAAACAMUrwtIH7wL/+ou0SAAAAgDFK8AQAAABAIwRPPaTW2nYJAAAAAF0TPAEAAADQCMFTDymltF0CAAAAQNcETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwxo6bIVbZcAAAAA9DDBEwN65amX5apZj7RdBgAAANCjBE8M6Kmly/Phf/tlVqyobZcCAAAA9CDBE2s1f9HS3PrAwrbLAAAAAHqQ4Il1enrp8rZLAAAAAHqQ4AkAAACARgieAAAAAGiE4IlG1epgcgAAABirBE806u5HFrVdAgAAANASwRONOvOa2W2XAAAAALRE8MQ6lfUY+/jTzw5bHQAAAEBvETz1kLbOS5px32OtzAsAAAD0NsFTD2nrmO7P/+jOlmYGAAAAepngqYesz5a39bFsxdAjr9JW0QAAAEDrBE8AAAAANELwBAAAAEAjBE806ke3P9x2CQAAAEBLBE80Zv6iZ9ouAQAAAGiR4InGfOun97ddAgAAANAiwRONuf/Rp9suAQAAAGiR4AkAAACARgieekhtuwAAAACAQRA89ZCZDz7RdgkAAAAAXRM89ZDTr7qn7RIAAAAAuiZ46iELFz/bdgmtmP7SrdouAQAAABgCwROj3ote+IK2SwAAAACGQPAEAAAAQCMET4x6pbRdAQAAADAUgqceUtsuYJCGKy+qvfbBAQAAgCSDCJ5KKUeVUr5cSrm2lPJEKaWWUs4d7ISllDmdsf39PLSWcQeUUi4ppTxaSllcSrm5lPLnpZTxg62hZwlgAAAAgB4yYRB9/y7JXkkWJZmbZNp6zLswyRf6aV/UX+dSypuSfDvJkiQXJHk0yRuSfD7JgUneuh61AAAAANCAwQRPJ6UvcLo7ycFJrlyPeR+vtZ7cTcdSyhZJvppkeZLfrrXO6LT/fZIrkhxVSnl7rfX89ainN4zZs44s9QIAAIBe1PVWu1rrlbXWu2od8RN3jkoyOcn5K0OnTj1L0rcKK0n+1wjXBAAAAMA6DGbF03DaqJTyriQ7Jnkqyc1Jrqm1Lu+n7yGd6w/6eXZNkqeTHFBK2ajW+kwj1QIAAAAwaG0FT9slOWeNtntLKcfVWq9eo323zvXONV9Sa11WSrk3yR5Jpia5Y9grZchskAMAAICxreutdsPorCSHpi982jTJnknOTDIlyaWllL3W6L9l57pwgPetbH/R8JYJAAAAwPoY8RVPtdZT1mi6Ncl7SymLknwoyclJ3jxc85VSjk9yfJLsuOOOw/XaVixdtqLtEgAAAAC61saKp4Gc0bketEb7yhVNW6Z/K9sf7+9hrfUrtdbptdbpkydPXs8Sx66RP1N+9blbmxoAAABYD6MpeJrXuW66RvusznXXNQeUUiYk2SnJsiSzmyuNWQ8/OegxpYE6AAAAgN4xmoKn/TrXNQOkKzrXw/sZc1CSFya5wTfaNeufr7qntbkteAIAAIDe1EjwVEqZWEqZVkrZeY323Uspa65oSillSpJ/6tyeu8bji5LMT/L2Usr01cZsnOTjndt/HqbSGcDipctbm3uXbTdrbW4AAABg6Lo+XLyUcmSSIzu323Wu+5dSzu78Pr/W+uHO7y9JckeS+9L3bXUrHZ3kQ6WUazrPnkyyc5LXJ9k4ySVJPrv6vLXWJ0op705fAHVVKeX8JI8meWOS3TrtF3T7Oeg9E8bZtAcAAAC9aDDfard3kmPXaJva+Un6gqQPZ+2uTF9Y9MokB6bvPKfHk1yX5Jwk59R+TrGutX6nlHJwkr9N8pb0hVR3J/mLJF/qbwwAAAAA7eo6eKq1npzk5C77zkk/Z0vXWq9OcnW3c64x9vokRwxlLAAAAAAjbzQdLg4AAADABkTwBAAAAEAjBE90xSFaAAAAwGAJnmhM8WV0AAAAMKYJngAAAABohOCJrli8BAAAAAyW4AkAAACARgieaEx1IjkAAACMaYInuiJDAgAAAAZL8AQAAABAIwRPAAAAADRC8AQAAABAIwRPAAAAADRC8ERjShme9/h2PAAAAOhNgicAAAAAGiF4AgAAAKARgicAAAAAGiF4AgAAAKARgicAAAAAGjGh7QLoTfcveDpn3XBvnli8LEfv8xt59U4vbrskAAAAYJQRPNGVWpOzrr83F9/8YDbfeEKumjVv1bPv/fKB/Nt7989ev/GiFisEAAAARhvBE135zzsezn/e8XC/z5YuX5F/vuqenHHMq0a4KgAAAGA0c8YTw+IHtz30vLaS0kIlAAAAwGgheKIxNbXtEgAAAIAWCZ4AAAAAaITgiWHz5JJn2y4BAAAAGEUETwybV576o/zjJXekVlvsAAAAAMETw2jZipozr5mdn977aJLkoSeeabkiAAAAoE2CJ4bdZ344K0ly3V3zWq4EAAAAaJPgiWF318NPJknGldJyJQAAAECbBE80Ztw4wRMAAACMZYInGjN+mFY8OaocAAAAepPgicZY8AQAAABjm+CJxthqBwAAAGOb4InGdHO4+HEHTmm+EAAAAKAVgieGXekETuO7WPH0kd9/WT7y+y9ruiQAAACgBYInhl2tfceBryt32n/qpJRS8iev2WkEqgIAAABGmuCJYdfJnVatfBrIhPHOgAIAAIANmeCJYffkM8uSrHvF05//zq4jUA0AAADQFsETjVnb4eKv221y9tphyxGsBgAAABhpgicas7bg6cxjpmfCeH/8AAAAYEPmb/40Ztxa/nS9YII/egAAALCh87d/GlPi8HAAAAAYywRPAAAAADRC8AQAAABAIwRPNKamtl0CAAAA0CLBEwAAAACNEDwBAAAA0AjBEwAAAACNEDzRmJIyLO+pjooCAACAniR4ojFleHInAAAAoEd1HTyVUo4qpXy5lHJtKeWJUkotpZw7mMlKKZNKKX9WSvn3UsrdpZTFpZSFpZTrSil/Wkp5Xj2llCmduQb6OX8wNTA67Tf1xW2XAAAAAAyzCYPo+3dJ9kqyKMncJNOGMN9bk/xzkgeTXJnk/iTbJvmDJF9L8nullLfW2u/mql8m+U4/7bcOoQ5Gmb/83Wk59hs/y6JnlrVdCgAAADBMBhM8nZS+wOnuJAenLzgarDuTvDHJ92utK1Y2llL+JsnPkrwlfSHUt/sZe1Ot9eQhzEkPeNVLt8oN/+eQvO/c/8p1d89vuxwAAABgGHS91a7WemWt9a4BViN1+44raq3fWz106rQ/lOSMzu1vD/X99LYtNp6YA35zUttlAAAAAMNkMCuemvZs5zrQXqvtSynvSTIpyYIkP6613jwilQEAAAAwaKMieCqlTEjyR53bHwzQ7X92flYfd1WSY2ut9zdXHUM19LVxAAAAwIag6612DftkkpcnuaTW+sM1nj2d5GNJXpVkq87PyjOmfjvJ5aWUTQd6cSnl+FLKjFLKjHnz5jVROwAAAAD9aD14KqWcmORDSWYmOWbN57XWR2qtH6m1/let9fHOzzVJDkvy0yS/meTPBnp/rfUrtdbptdbpkydPbuhTAAAAALCmVoOnUsr7k3wxye1JXldrfbTbsbXWZUm+1rk9qIHyAAAAAFgPrQVPpZQ/T/LlJLemL3R6aAivWbl3bsCtdrSnlLYrAAAAANrUSvBUSvnfST6f5Kb0hU6PDPFV+3Wus4elMAAAAACGTSPBUyllYillWill536e/X36DhO/Mcmhtdb563jXb5VSnldnKeXQJCd1bs8dhrIZZhY8AQAAwNg2oduOpZQjkxzZud2uc92/lHJ25/f5tdYPd35/SZI7ktyXZMpq7zg2yalJlie5NsmJ5fn7sebUWs9e7f5zSXYppdyQZG6n7RVJDun8/ve11hu6/RyMnNp2AQAAAECrug6ekuyd5Ng12qZ2fpK+kOnDWbudOtfxSf58gD5XJzl7tftzkrw5yT5Jfi/JxCQPJ7kwyT/VWq/tonYAAAAARljXwVOt9eQkJ3fZd0762Wk1mHesNubrSb4+mDEAAAAAtG8wK56ga6/51BWZ+9jitssAAAAAWtTKt9qx4RvO0Kk6LQoAAAB6kuCJUaX4LjwAAADYYAieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieAAAAAGiE4AkAAACARgieGP1q2wUAAAAAQyF4YlQppe0KAAAAgOEieAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheGLUq20XAAAAAAyJ4IlRpbRdAAAAADBsBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANELwBAAAAEAjBE8AAAAANKLr4KmUclQp5cullGtLKU+UUmop5dyhTFpK2aGU8o1SygOllGdKKXNKKV8opWy1ljEvK6VcWEp5pJSypJQyq5RySillk6HUAAAAAECzJgyi798l2SvJoiRzk0wbyoSllJ2T3JBkmyT/kWRmklcn+WCSw0spB9ZaF6wxZt8kVySZmOSiJL9KckiSjyQ5tJRyaK31maHUAwAAAEAzBrPV7qQkuybZIsn/Wo85T09f6HRirfXIWutf11oPSfL5JLsl+YfVO5dSxic5K8kLkxxVa31nrfV/J9k3ybeTHNipDQAAAIBRpOvgqdZ6Za31rlprHepkndVOhyWZk+S0NR5/NMlTSY4ppWy6WvvBSXZPck2t9bur1bMiyV91bt9bSilDrQsAAACA4TfSh4u/rnO9rBMcrVJrfTLJ9elb2bTfao8O6Vx/sObLaq2zk9yZ5KVJpg57tQAAAAAM2UgHT7t1rncO8PyuznXX9RzDBmQ9FtkBAAAALRrp4GnLznXhAM9Xtr9oPcfQo2yYBAAAgA3HSAdPI66UcnwpZUYpZca8efPaLgcAAABgzBjp4Gnl6qQtB3i+sv3x9RyzSq31K7XW6bXW6ZMnT+66UAAAAADWz0gHT7M614HOY9qlc139PKehjAEAAACgZSMdPF3ZuR5WSnnO3KWUzZMcmOTpJD9Z7dEVnevha76slDI1fYHUfUlmD3u1AAAAAAxZI8FTKWViKWVaKWXn1dtrrfckuSzJlCQnrDHslCSbJjmn1vrUau1XJ7kjyUGllDeuNse4JJ/q3J5RffUZAAAAwKgyoduOpZQjkxzZud2uc92/lHJ25/f5tdYPd35/SfrCovvSFzKt7n1JbkjypVLKoZ1++yZ5Xfq2y/3t6p1rrctLKcelb+XTRaWUi5Lcn+TQJNOTXJ/k891+DgAAAABGRtfBU5K9kxy7RtvUzk/SFzJ9OOtQa72nlDI9yanp2z53RJIHk3wxySm11sf6GfPTUso+6VsVdViSzTvznZrkk7XWZwbxOQAAAAAYAV0HT7XWk5Oc3GXfOUnKWp7/Kslx3c7dGXN7krcOZgwAAAAA7Rnpw8UBAAAAGCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMET4x6tbZdAQAAADAUgidGlZLSdgkAAADAMBE8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8AQAAANAIwRMAAAAAjRA8MUB5o/UAACAASURBVOI+fNiubZcAAAAAjADBEyPuhNf9ZtslAAAAACNA8MSIK6W0XQIAAAAwAgRPAAAAADRC8AQAAABAIwRPAAAAADRC8AQAAABAIwRPAAAAADRC8MSoV9suAAAAABgSwROjSiltVwAAAAAMF8ETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPAEAAADQCMETo16tbVcAAAAADIXgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGDCp4KqXsUEr5RinlgVLKM6WUOaWUL5RStupy/G+XUmoXP7+xxri19f3JYD4DAAAAACNjQrcdSyk7J7khyTZJ/iPJzCSvTvLBJIeXUg6stS5Yx2vmJDllgGd7JvmDJLfWWn/Vz/P7kpzdT/vcdRYPAAAAwIjrOnhKcnr6QqcTa61fXtlYSvlckpOS/EOS967tBbXWOUlO7u9ZKeVfO79+dYDhc2qt/Y4FAAAAYPTpaqtdZ7XTYelbsXTaGo8/muSpJMeUUjYdShGllK2TvDnJ4iT/MpR3AAAAADC6dLvi6XWd62W11hWrP6i1PllKuT59wdR+SS4fQh3HJtkoyb/UWh8foM+LSil/kmS7JAuT3Fhrdb4TAAAAwCjVbfC0W+d65wDP70pf8LRrhhY8vbtzPXMtffZK8vXVG0opv0xyTK31liHMCQAAAECDuv1Wuy0714UDPF/Z/qLBFlBKOTh9wdattdYbBuj2uSQHJpmcZPMk+yS5KH1h1BWllJes5f3Hl1JmlFJmzJs3b7DlAQAAADBE3QZPTTq+c/3KQB1qrR+qtd5Qa51fa11Ua51Ra31rkm8n2TrJh9cy9iu11um11umTJ08e3soBAAAAGFC3wdPKFU1bDvB8ZftA5zP1q5Ty4iRvSd+h4ucMZmzHGZ3rQUMYCwAAAECDug2eZnWuuw7wfJfOdaAzoAay8lDxC9dyqPjarNw7N6Rv0wMAAACgOd0GT1d2roeVUp4zppSyefrOX3o6yWC/ZW7loeIDbrNbh/0619lDHE8PqKltlwAAAAAMQVfBU631niSXJZmS5IQ1Hp+SvhVH59Ran1rZWEqZVkqZNtA7SymvTbJ71n6oeEopryilTOyvPck/dG7P7eZzMPqVUtouAQAAABgmEwbR931JbkjypVLKoUnuSLJvktelb4vd367R/47OdaAkYZ2Hinf8RZI3lFKuTfKrJM8kmZbk8CTjk3w1yb92/zEAAAAAGAldB0+11ntKKdOTnJq+0OeIJA8m+WKSU2qtj3X7rlLKVkmOSneHin8nyRZJXpHkkCQbJ1mQ5NIkX621frfbeQEAAAAYOYNZ8ZRa66+SHNdl3wH3THVCqk26fM930hc+AQAAANBDuj1cHAAAAAAGRfAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMETwAAAAA0QvAEAAAAQCMET3TlrD/eJ9O227ztMgAAAIAeIniiK/vvPCk/+POD2i4DAAAA6CGCJwAAAAAaIXhi1Ku17QoAAACAoRA8MaqUtgsAAAAAho3gCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgCQAAAIBGCJ4AAAAAaITgia7U2nYFAAAAQK8RPAEAAADQCMETAAAAAI0QPAEAAADQCMETAAAAAI0QPNGVUtquAAAAAOg1gicAAAAAGiF4AgAAAKARgicAAAAAGiF4oiu1jsw8zpICAACADYfgiUE55Y17tF0CAAAA0CMETwzK61/xP7LT1puuut/9f2zRYjUAAADAaDah7QLoLVtvtlG+874Dc8Wsh7PxhPHZb+qkvPJjP2q7LAAAAGAUEjwxaFu+cGLe/ModkiRLnl3ecjUAAADAaGWrHevFYeAAAADAQARPAAAAADRC8MR6KbHkCQAAAOif4AkAAACARgie6EpN7bfdGU8AAADAQARPAAAAADRC8NRD3vqqHdouAQAAAKBrgqce8u6DprY290CHiNtpBwAAAAxE8NRDdt1287ZLAAAAAOia4In1UpwuDgAAAAxA8AQAAABAIwRPrBfrnQAAAICBCJ4Y9WqtbZcAAAAADIHgia7UjEz4YwUVAAAAbDgGFTyVUnYopXyjlPJAKeWZUsqcUsoXSilbDeIdV5VS6lp+Nh5g3MtKKReWUh4ppSwppcwqpZxSStlkMJ+B4eVscQAAAGAgE7rtWErZOckNSbZJ8h9JZiZ5dZIPJjm8lHJgrXXBIOY+ZYD2Zf3MvW+SK5JMTHJRkl8lOSTJR5IcWko5tNb6zCDmBgAAAKBhXQdPSU5PX+h0Yq31yysbSymfS3JSkn9I8t5uX1ZrPbmbfqWU8UnOSvLCJG+qtX630z4uyYVJ3tKZ/5Pdzs3wKZY8AQAAAAPoaqtdZ7XTYUnmJDltjccfTfJUkmNKKZsOa3V9Dk6ye5JrVoZOSVJrXZHkrzq37y0SEAAAAIBRpdsznl7XuV7WCXxWqbU+meT69K1I2q/biUspR5dS/rqU8hellN8rpWw0QNdDOtcfrPmg1jo7yZ1JXppkardzAwAAANC8boOn3TrXOwd4flfnuusg5j4/yT8m+b9JLklyfynlqBGaGwAAAICGdRs8bdm5Lhzg+cr2F3Xxrv9I8oYkOyTZJMm09AVQL0pyQSnl8OGcu5RyfCllRillxrx587ooDwAAAIDh0G3wNGxqrZ+vtV5ca/11rXVJrXVWrfVvknyoU88/DvN8X6m1Tq+1Tp88efJwvhoAAACAteg2eFq5qmjLAZ6vbH98PWr5WpJlSfYupWw+wnOzDhtNGN92CQAAAECP6TZ4mtW5DnSO0i6d60DnMK1TrXVJkic7t6t/O17jc7N2f3LgThk/zpcGAgAAAIPTbfB0Zed6WCnlOWM6q5MOTPJ0kp8MtZBSym5Jtkpf+DR/tUdXdK5rnv2UUsrU9AVS9yWZPdS5Wbu/ff3ubZcAAAAA9KCugqda6z1JLksyJckJazw+JX0rlM6ptT61srGUMq2UMm31jqWUnUopL17z/aWUyUnO6tyeX2tdttrjq5PckeSgUsobVxszLsmnOrdn1FprN5+Fwfmd3be12gkAAAAYkgmD6Pu+JDck+VIp5dD0hUH7Jnld+ra5/e0a/e/oXFdPLQ5OckYp5br0rVB6NMmOSY5I31lNM5L81eovqbUuL6Ucl76VTxeVUi5Kcn+SQ5NMT3J9ks8P4nMAAAAAMAK6Dp5qrfeUUqYnOTV9296OSPJgki8mOaXW+lgXr7kxyflJXpXklUm2SN/WuluSXJjkzFrr0n7m/mkpZZ/0ra46LMnm6dted2qST9Zan+n2cwAAAAAwMgaz4im11l8lOa7Lvs/bn1VrvSXJHw9mztXG3p7krUMZO5btuu1mOepVO+Txp5/N6Vfd03Y5AAAAwBjS7eHijHL77vS8o7OSJFu98AU5/qCd81eHT+v3OQAAAEBTBE8biOMO3KntEhrj1HgAAADoTYKnDcSEAb55rvTYF9KVXisYAAAAGJDgCQAAAIBGCJ5Yq2nbbd52CQAAAECPEjwxoPHjSv5o/5e2XQYAAADQoya0XQCjz2YbTciWm0zM3xyxe7bZYuO2ywEAAAB6lOCJ53jJizbJNX/1uowrDvoGAAAA1o+tdj3mhNft3Oj7/+rw3TJ+XBE6AQAAAOvNiqcec+z+U3LalfcM2/vesNf22fMlW+Te+U/ld3bfNofuvu2wvRsAAAAY2wRPPWagM5d2336LIb1vk4njcvxBza6iAgAAAMYmW+160MfetMdz7g/adXJe8qJNWqoGAAAAoH9WPPWgY/afkhe+YEKumPlIdt5ms7znoKkD9t1p681GsDIAAACA/yZ46lFvedUOecurdnhO2z/+wZ75P//vlue0Hb+WUAoAAACgSbbabUCOetUOectv7ZDx40o2fcH4nPLGPbLT1puudcxLJ639OQAAAMBQWfG0AZk4flz+79v2yilv2iMbTRiXieOfmyv+7RG75x8uuWPV/fhxJe949Y4jXSYAAAAwRljxtAHabKMJzwudkuTYA6bkyL23z8TxJZM2fUE+f/TeefGmLxjR2koZ0ekAAACAFlnxNIa8YMK4fOHtr8wn3/KKvGD8uIwbN/Ip0KUffO2IzwkAAAC0Q/A0Bm08cXxL847LtO22aGVuAAAAYOTZaseIec1vbj2kcbUOcyEAAADAiBA8Mao4AwoAAAA2HIInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInAAAAABoheAIAAACgEYInRkwppe0SAAAAgBEkeGLEjBc8AQAAwJgieGLEjPOnDQAAAMYUUQAjxlY7AAAAGFsET4yYcYInAAAAGFMET4yY8XInAAAAGFMET4wYK54AAABgbBE8MWKc8QQAAABji+CJETNO7gQAAABjiuCJETNe8gQAAABjiuCJETPUrXY1dZgrAQAAAEbChLYLYOzoZsGTNVEbpkeeWJILZ/wqTy1dnj945Uuyy7abt10SAAAAI0DwxIjxrXZj06JnluVtZ/44cxY8nSQ59yf35TsnHJidJ2/WcmUAAAA0zVY7Rsz0KVu1XQItuOy2h1aFTkny5JJl+Zcb5rRXEAAAACNG8MSIOfzl27VdAi34yjWzn9f2zR/f10IlAAAAjDRb7RgxG00Y38q8dzz4RL5949y88AXj8/ZX75jtX7RJK3UAAADAWCN4YkRM3nyjVua9+5FFeesZP86iZ5YlSf7fL36d75/42my5ycRW6gF6z/IVfd+sOb6bb0gAANiALF66PP/+i1/noYWL87sv3y57bL9l2yXRgwRPbNC+ecOcVaFTksx9bHEuveXBvP3VO7ZYFdArzrj6npxx9T1JkvcevHPee/DOLVcEwEi5b8FTefiJZ7LXb2w5Iiv3lzy7PBf8/Ff51aNP53++bNvsO3VS43PC2tRa82f/8vNcf/eCJMmZ18zOt969b1710he3XBm9xhlPbNDO+cnzzxL6+nX3tlAJ0K1nli1ftcqoTT+799F88tKZefzpZ/P408/mk5fOzM/ufXStY26ZuzDHfP2nOfwL1+Rr185Ore1/DgAG79M/mJmDP3NV3nbmj3P4F67Nw08saXzO/3Xujfnod2/L1667N+/46k9y+R0PNz4nrM3tDz6xKnRKkmeWrej3/FZYF8ET0IorZz7SdgmMMitW1Jz6vduz1ymX5ZWnXpazr283JP7MD2c+r+2zP5z1nPvVA7KnnlmWP/zaT3LtXfMz86En8/Hv35H/uOmBxuvs1j3zFuVffjwn1989XyAG9KQVK2ruW/DUkP/PiSXPLu+q34MLF+f0q+5ZdX/v/KfyjYb/nTRn/lO5cta8VfcravKly+9qdE5Yl3//r18/r+2HtwlEGTzBE2NOcUzLqHDc2T/Pd385ev5S3muWr6hZumxF22UMq0tufTDfuP7eLHl2RZ5Ysiwnf+/23Pnwk63V8/M5jz2v7Wdz+lY83XjfY/mdz12d3T/yg5xw3n9l8dLl+e4vH8gTS5Y9p/+pF9/+nPu2VnLdcPf8/N4Xr81H/uO2/OHXfpo3nXZ9Fi/t7i9g6/KrR5/O+T+7Pz+dvWBUBFq11sx78plRUQtsCFasqLn11wvz09kLWv33zsyHnsj+n7w8B3/mquzzD/+ZX9z//P+OHsjdjyzKYZ+/OtP+/gd502nX58GFi9fa/9x+VsyfeXWzqzyumvX8/0Pul3MXNjrnWDYaVlbDWCJ4Yr0df9DUdfYZTf/7f6RrWbEB/Ytt8dLlw/p5PnfZrHV34nnOvv7e/NbHfpS9/j979x3fVNXGAfx3u/fee1Pa0hYKLWVvBBSQIYiiqCwFHKC+qIg4ECcqiiioTFkCgkwRKLulQBd00b3pnulIk9z3jzShSW6SmzRd9Hz/4UNy781Nmtx7znOe85yPz2PTmdTHpoO94Z9kmce2RmXK3V4goFHF4QIQTs/ris+BooSN1SV77iCzrAFcngCn75Xg+wsPcDtXdhqe6Pzqm1uxZM8d9F9/DlN+uIbUkrpOP9f2dlzLlugwJhXWYsjGC8gqb+jQce/mVWHSd1ex9tg9zNseg01nZbPEulJBVSMmfXcVQzZewNBNF5FYUINWvgB3cquQVd7w2PxWepKGFh5+v56DjadTEKdCIEAZgYDGL1ey8Mwv0XjvWBIqG1o0dmyCPb6AxqoD8Xjyx+uYtz0Gs7fdRG1Ta7ecy/rjySitE34PqjhcvHfsHut93zqUgAelwutdYkENPvj7vsLt66UGEYjHR2pJHab8cA3915/D4t13UN/cPd/nnkgUZI7NqXrsBjeJ7keKixMdtnCoOw7cykd9S+fcpPfF5MPTxgRzB7vAzKB3rEZH0zQelDZg9eEEZJY1YKSvLb6bFwLTXnL+0ppb+VhzOBHnkh/CwlAXn80MwpQBjgCA5OJaHL1bBGN9bcwPd4OzhSHr4+ZWNnbWKXepJi4fJxKKUFLbjMmBDghwMuu010oprsOGk4+yaH69mo2BbhZ4Isix016zM9E0DaotDbGigSvzfEoxc4AmJrsSK/fHSexjb6aPT2YEYXKgg/gxflsjitPCQ5iHJavisFUcLm5lV8p9/npmhTigJPLr1WzMGuQsd59NZ9PwX4owNT21pA7L9t7FlXfGiN+7uuqbW3EprQxcngAT+tvD0liPcbv20zdEGlp42BqVic3PhOJ2bhVic6oQ7GKOkb62rF9/x9UcNLWbuvL79RysGufTbde6j/5JRkaZsHNZWteCl3bdhp2pPtIeCjPnFg51xyczAkFRFI7FFeJiahm8bI2xbLQ3TPRJk0hVNE3jpZ2x4uzAXTdzsfvlcAzztunwsX+5moWvzgkHJ2Jzq5BaUo/jK4Z3+LiEau7mVeP0vRLx/+8V1eJ4fBFeHObR5ecSKxXcT3tYD04LD8ZKfru1ja24VySZOXSJTPfvk2iaxrK9d5FfJWx/Xkgtxedn0rBp1oBuPjPV7Y3Oxd6YPJga6OKtCX4Y4dux6y5fQOP1g/E4nST8vQe7mGPvKxEaOFOCEFKplUVRlAuATwA8AcAaQAmA4wA+pmla6TAXRVHGAGYCmAZgEABXAAIA6QAOAPiRpmmZngdFUYqGKG/RND1UlfdBaJarlREOLB2KvdF5qG1qxbnkhxp/jU9PpeBkYjGOvToMWh1c0rwzp9qV1TdjzeFExOVVg9NuGsuF1FKsOZyIAc7mqORw8VSIE8LcLTvvRDTs9+s54oZnJYeLVQfiEedrg4e1zXjml2jxez0WV4Szb47sNQFCTaBpYfbL9cwKAMJV0PYvGSrx9+ULaKSW1MHZwhCWxnoor28BX0DDwdxA5ddjygD65GRKpwaeuDwBbudWoZUvwFAvaxjodnxln4YWHt49koirDyrga2+Cb+aGsN6Xpmm8fiBeJlBVWteClfvjcGfdRJgb6oLHF2DVgXicvS+8JgU6mWH/4qEwN5L//cworcf87TGo5MgGwQCAAlBULWeKhpw71U+XMrD/Vr7EY/lVjUgtqe9QkJLTwsP87TFIbgvOedoY48jySFib6LM+xrG4IkR4WuF/Rx9lDrz7RD+8NsaH1f7S13u+gMaltDLMCJUfhOtM0p3JKg5XIki4NyYPLw5zx62cKomMh/j8GuxbTBrYqkoqrJWYktrKp7HtcpZGAk+ioJNIQkENsssb4GVr0uFja1oVh4s7uVXwsjWBj53w/Jq4fFzPrACPL8BIP1tWgc1jcYXYG5MHE30dvD7eF0M8JFeNomkat3KqkFPBwXBvG7hZG3XK+2nvW4bM5I/+Se6WwBMTPossxiaWdZ2Ix9+2K1nioJPIgdj8Xhd4ikorw4cnHmWJv7L7Nq6+Oxb2Zqq3K0Xu5lWLg06A8Pp+IqGIlCghNIZ14ImiKG8ANwHYATgBIA1AOIA3ADxBUdRwmqblDxELjQSwD0AVgCgIg1aWAKYD+AbALIqixtM0zbRsRB6AXQyPF7J9D0TnCXI2x5dzggEAHmtPyzyviYtWQkEN4vKrMViqIZZf2QgDXS3YdeBiq46imiY8eFiPUFcLcZbBO38l4VpGBeP251NKcb4t42H/rXwcWDq0S4NPZfXNOJlYApqm8VSIk0o3p6+lCirzBDSO3ClERlmDRICtqKYJZ++VYN4QN7XOsaGFh5xyDvo5mEJPp3fMBE57WC8OOgHC1T5+u5aNMPcwAMICpQt23EJOBUdm36dCnLD5mRDoarN/r9KjtgBQXNt5K+00t/KxaGcsYrKFI83BLub4c3FEhzNaNp5OxZl7wqBFfH4Nlu29K3fbRi4P55NLUd3IxaRAB5TXt6CsnnnaTSufxl93CrB4pBfi8mvEQScASC6uw9/xhVg03FPua/1+PUdu0ElEoOJ0rW/OP2B8vJKjeOpQNYeL9f8kI6mwBhGeVtgwPRBGeo9u21cflIuDToCw+O3Z+w/x/FB3lc5vy0XJYObPUVlYPspb7SC/qP5Y+sN6eNkaK81GECmpbQKnhQdvW5MOZ4Ip8uuVbJn6ctczK1BQ1QhXq87vyD9O1p+Qna4k7x6oCZlligNPLTw+Cqqa4GVjzPj9vVdYi49PJqOopglPBjti7ZT+0O7gYFZSYQ2e++2WeGrWumn9sSDCDc/9dgvx+TUAAH8HUxxaGqkw6H0jswKrDyeK/38ntxpX3hkj0bb54lyauM6Qga4W9rwcgXDPzl3SvCun1WWVN2BfTB54fBrPhrupFZjnC2iZvyktb1Sgh+kdZ9k71TRy8dRP11FQpbi2V2/x0q7bEv9v4QnwZ0weVk/qp/Yxv/tPtq2y/kQyloyU32Yi2MsorceppBJYGeth5kBnmBv2nUF6EVUynn6GMOj0Ok3TP4oepChqM4C3AGwEsFzJMR4CeB7AX+0zmyiKehvAZQDDAKwA8C3Dvrk0TW9Q4XyJx9DxhCJx4Km5lY/X/owTj3AvGuaBj54KULvDcj75IW5mVSLQyQyzB7ko7HQdjM3H2na1BY6+GokwdytceSA7nYUJly/AtstZ+O3FwczP8wSo4nBhaqADY30d/JdSit+vZ0Nbi8LSUd4Y7ad8KkxZXTPyqxoxwMUcnBY+Zm+7Kb7h7ryRi+MrhsPWlH1mhDTposki/zt6D4Z6OojwtFIpuPVv8kOs2h8PLl8AGxN97F8SAT97U7XPr6v8HS+72kf7YMfPUVmMQScAOJlYjClBDpg6wBEltU3IqeAg1NVCIrigCZwWHq5lVEBXm8JwHxtxxtKRu4XYG50LY30drBrni0hva5l9rzwoFwedAOEI2IAN5/Ht3BDMDnNR+5wOxEpmAGWWMdca4gloLPrjtniKxY+XMrFqnOJsnLy2KZzSK9ABwIaTKZgR6iwzJY2maeRXNeLg7QKl595VdYJePxgv7sTnVTaCJ6Cx+ZlQ8fOv/hkns8+64/dVDjwV1Ug2xBtaeKhpaoWVnGl7yqSW1GHj6VRUcrjQ09HCL88Pwjh/e7nb0zSNj/5Jxp5oYTHf4T7W+O2FITDU63hmHZO65la0MNSuSC6uJYEnFdA0rVbh4/rmVghoqNXoVnR/v5xehtf+jEMjlw8XS0PseyUCHjbG4ue5PAFe+OMWqhuFgZQd13JgZ2qAJSzqVCry46VMiXpA35xPh62pvjjoBAgHKM4ll+CZwa5y34P0AE9TKx/7Y/Px5gQ/AG21tK49WlWtuVWAHdeylQaeahq5+C+lFNpaFCYE2PfYjOSy+mbM2XZT/PfZG5OHH58diKdCnFjtz+ML8OGJZJxIKIKtqT42TA/E2H52AISrw/VmiQU1KKtvQYSXlcp/v7/jC3Esrgj2ZgZ4fZxvl2TJaUJ+ZSNOJhXDQFcbM0OdYGWsh0oOF9bGenJ/Q82tfERnVaK5lY8RvjYSA2Q/Xcrs9UGnRi4PZ+49xJl2U1/bu5FVidUdOH51o+JBN2lXH5RjFIv+CCFcGGHOtmg0tJWlOXK3EEdfHdZrBtk1hVXvpi3baRKAXABbpZ7+CMBSAAspilpD0zRzDwsATdMJABIYHq+nKOpbAH8CGAPmwBNBQKvdzeafxGKJaRW7buZiRqgTBrqpnkW060aORN2c5OI6bJgeyLitQEBLBJ0AYPa2aORsmqrSa15IZV6K9EFpPV77Mw6ZZQ2wMdHH4pGe+PrfdPHqG7dzqnH2zZHwVjDq2/79OJobYNoAR4kbblFNE04nFSvM/OiI1w/Ew1hPG3tYzA0/crcQb/+VKPFYRUMLJn13FWP62cLH1gSrxvtKdFIEAhpbozJxKb0MPrYm+N8Uf9wrrEViYQ3CPawwzEe9aR65FRwcuJ0PgYDGvCGu8LHreOBrL8PKOO2tPZqE8voWfNRWWNvGRA8Hlw6Fj50p+AIaR+4WIO1hPUb52Yob0aqobWrF/O0x4mLWYe6W2PdKBOLyqyU+97j8alx5RzZN+6MTsgW/AWDNX4lY07b/1gWDMHWAg0xjkKZp/HEjF2fulcDF0hDvTO4HF0vVGr05FRyJwF0Vh4uPTzIHPaXVySkY+sahBOx5OVziPNefSFb6twKEHd+u6MQ0cnkymSPH4orw5ni/Luk4dCQHZEe7zjGXJ8AHf9/HzbV2cjsLiYW14qATANzIrMTf8UVYEKFe5qS6Sjoxc5Ct+0W1uJ0rrLUV5t65mSwdlSEnWCwPTdP4/Ewq/riRC5qmMW+IGzbODFIps07eljRN490jSWhsy8AtrG7C52dSsf2FR4M7F1NLxUENkY1nUjsceBLVbhNpbhXgjYMyTV387+g9fHkuHc9FuGH1jfULXQAAIABJREFURD+Z30NCQY3MPhdTy8SBpyvp5eBJXXykX1taNYeL2dtuIrvtGurvYIq/lkf2yHqTf90plPn7rDoQj0mB9qxq8+26mSse0MirbMSyvXdxd90EmBro9thFXnh8AWJzq1DF4WKEgnbLjK03AADOFoY4tGwo6/vo2XsleOvQo/t8dFYlot4e0+M7uwVVjXj65xvi7OPPTqfA2lgfFQ0tcLE0xO8vDkE/B8n2mXR2tq+dCQ4vixQPMv12PQe9GY8vwKKdtxGbI7uISWeTd+9+61AC7n44sYvPpufLr2zE0bhCUBQwJ8wFLpZG2H0zTxx0AoSzF2KyK/tc4I7tsPrYtn/P0zQtMUzYFjS6AWFgaiiAi2qei+huI69CtQVFUS8DcABQC+AuTdMxar4W0Uu1v/S9eyRJ5vnvLmRg56IhyCirh5MKRa6/OCe5EtOum7l4b6o/Y2MnoVC2cdgRqSV1WH/iPuPS7RUNLfhCapUoLl84lWvTrGDG43FaeBLZSCW1zYw33A0nUxQGnkpqm7DrRq7aqxRxuHxsu5yldDvpoFN7l9PLcTm9HPeLa3FwaaT48R8vZeK7C8KU4Pj8Gvx1V3LG7aczg7BQxayPsrpmzPklGhVtKyftuJYjzmTrTHXNPHx+JlX8/4oGLn68lIkf5g/EuuP3cCBWmIGz80Yuvpw9QOVpq+ful0isoHY3rxpXM8rxs9TfprlVmIXXPuD6b/JDPKxT3hlfsT8Oq8b5YI1Uive+W/n4tO27eDevGkmFtbi4enSH67R11NUH5RIFaVNL6lkFnURUnWqnDk4Lc02SmT/fwPHXhnd68ElLg1PdSmqF2Zfu1sYSj++8kYOjcYW4XyRbQP79v+9BQNMIdjFHsIuFxs4FkL+y6ccnU1DN4XZoqgIbXJ6AseP3d3whVh9OFJ/fYHdLvDzCExMD7LH7Zi6uPCiHj50J3pro1yOyVjgqLigSk10lEZQ8EJuP2JxKXFg9mnWmsrzN0h7Wy0y/PS8VlEkvrWf1GmV1zWjk8uFubaTxKZ9VHOH13dfeFNNZZvIAwk6nvCwHRc4lPxQHnQDh5xSVXq7Sa3fVQpA7rmUzPn4+uZRV1tNnp1Ml/s/lCfB3fBFeiPTQxOlpHE3TeONQgkRNHWWKapqwLyYfa6f4s9pe+jMpqmlCVHqZxAIcbLXw+DgYW4Ds8gaM62/PKvNeXQdv50tMeadpiNtmhdVNePdoEk5ILTQQnV0pkZ2dUdaAU0nFWNhD//7ypBTXIS6/GqGuFghyNhc/nlBQ0y1BJ0UqOVyU17d0aPZEezy+ANczK1BW14LR/Ww7VK9KVa18ATadScPFtFJ425rg4+mBamVAP6xtxqxtN8Xf1+8vZMDeTF+8Gmd7u2/mksCTHKJWGHOhCiADwsCTH9QPPL3c9u85Oc+HAPi9/QMURSUCWEjTNPv1VIleTVkjMD6vGhM2X0FOBUelug3NrbLTLkprWxg7d1lyRnnVaZzxBTQW7YxlvCAp8k9CMTbNCganhYeC6kb42pmK3+9LO293OCOjicvHvF9jZAowqupCain8HTqeNRSTXSVRf0UUdJLnhwsZeC7cDb9dz8bnZ9LgYW2EXS+FS0y7kHYkrlB8oxCZvS0atz+YAFtTfaQU12Hzf+koq2/BnDAXjTZmpaf9nEgoxmczg8RBJ5Fvzz+QW9hbVFst1NUCR5ZHQqetblT7otEiHx6/z1gjadfNXFzNKMf2hWEorG7C8n3y6y5J+/FSJib0t0egk5n4tT85KZktlVPBQWxuFYZ6yU7p06S9MXnwdzQVr2TGpH3gialguzwU5E/bOMYw7VJd8q5fVRwu3j6SiHXT+mvstRi1vfyVB+W49qAcfg6mmD3IRe16ONLLMh+PL1KaubbuuLB+0KczArus87DlUiarwJNotcSY7ErUN/MwwMUcQz2tcflBGfR1tDHazxb6Olq4X1yLSg4XEZ5WqGlsxfO/3RIHAkb42OC1Md4orGnCxdRS/JssGSi5k1eNO3mSgf9rGRV4UFqPPxf3vjVVnt0hO1aYVc7ByaQSmUCI3KkkmZXYdjkLDS08vBDpIc6Ka+R2vHg0TdP4+GQKdt3MBQCM8rPF9oVhGllMQdqGf5JZBX9ETZ53jyZJrCzH1nvHZK//a48mKX3t8voWXEorhZmBLpp5nVOYO+1hHb44m4aHtc2YOdBZbhvqAcuAIZPscuFvTdFgwZUH5dgbnQs9HS0sGeklzppn26ZraOHhg7/viUs1fDErmNXCIeml9SoFnUR+uZKFopomlNc3Y/YgFzwV4gQBTTNO0ZeeRg0Is54mBzrgQWk9TiQUgaaBxSO9lE6tXn0oUfwd3B2dhx/mh3baIhJboxQPWiYW1KCVL5Coj/kpQ/mHD08k4/mh7p1aM1CTpAcfNs0agGfDhde4364pz9hq0sB1UFV8JR2ORi4PHx5PRky28Pfx2dNBsDOV/X3QNI03DyXgVNtvwtJIF4eXRcK3i0pu/HAhA3/cEH7GeZWNyKvkqDQoInLkboFMX0LVPt7jjG3gSRRylTeZX/S4WsOSFEWthHClvAQAfzBsshnAUQgDX80A/AH8D8AcAJcoigqlaVpzLX6i+yj5gYtG4Ru5zCOt9S081LeNwsq7GFIsJ5HIm6YjrwHTvq4PW5+eSlHrgkRRFE4nleCtQwng8gVwsTTE/sVDQVGyyw2r42JaaYeDTpr2oLQeDuYGCjOkRCoaWvDr1Wx82ZbJllvZiDHfXEbW51Pldpy3XMxgfPyfxGIsCHfDc7/FiKcBJBXWwtxQFzNCnXFKqkixpjwolQ1wltW3wE3JCExCQQ1WHYjHz88NknvDZKpvI5JdzsGaw4kQ0KoHU2dsvQEbEz3sfjkc3rYmaOXLHuBeYW2nB54ASKxYxoSGcITrXpFwiiZbPAGNr6QyJDuDovhObE4Vpv90Q+kxaJpGVHoZUoplM4qUiUorw9f/pkt0XOLzq+VmWqpKXo04JlsuZSrsPNQ2tsJQT1tj00cEAlphVl5zKx+v7L6NG5ny11MZ7G4JJwtDmSLm7V3PrJBYmICtG5mVKKltgqM5+6ze7sbUARZhCsL8eoW54ynqGADCrDhnS0OFmRdRaWW4mVWBACczuQHjhIIahLpaIKGgRhx0AoSZkcfjizA/XPNTPkUrLSr7rtG0sPbRsbiua+IWVjdizrZoVtmu6mrh8fH8b7fEK5NKZ3ZriuiSIe9eFrD+nETQ8kp6Of5bPZp1xrxAQGPDP8k4kSD8nV9OL8eC32Jwac0Ypftuv8qc4cXGybbrSkx2Fd45kgRdbQrPRbhj/ZMBSjOKKQpIf1iPyd9fFT/28+Us3Fg7Ds5t75umaZxPKcXtHOFqtjYm+jKBz2/PP+i21UuZtDAMIAPAgdgCtaZtN3H5uJlVAV1tLUR4WbGa7ikPTdP47kIGjsUVwtZUHx9M7S+zUBIgrEPV/rv606VMzB8ivy6ctJQS2Xt9cU0TLI305NZMrGtuxZmkEjS08ORepzsStvvoRDKOxglnJRTVNOF8Silyv5gms11OBUccdAKA6sZW/HkrX27ZE037SWoAMqucg5SSOgQ6mcvZg5m8xWSY9MwJwJ1LsxVs1UBR1CwA30NYeHw2TdMyvX2aptdIPXQHwFyKoo4AmA3gbQgLnDMdfymENajg5ta19SIIzaMooLKhBfO2qz/LsryBXaDn8J0COFsYyhQhltd4XbFfttCvMu0buargCQRYeywJXL7wRltY3YRv/0tXqVirovvY3xps5CrKOlGFFkXhREKxuIGnzJcMwYFDt+U3QOQ1TD89lQJzQ12Z2hOfnkrFjFDnTltRbvVh2RohAFgFBM/ef4iRX0Xhg6nqZcWoUzBYpKKBi2lbrsNAlzkIsPFMKp4Z7Kr28TWlsoGLF36PZT39pj1FgTtVKArssQ2QK7L5vwf48RL7bK723jwk+/07EFuAD6YFoKaRi9icKviqUANt4ndXEeJijo1PD0CQs7m4481GeX0LKhq4Mun8za18vHEwHudTSkHTwCsj2NWsk56CJU1ZG/98SqnCoBMgzFZCnnrTlNnIKeeoFHjiC2jsjc5FUmEtwj2tMNjDCutP3EduBQcTAuzx4ZMBKq2uyeb12gf597ar4SWtSmJKDY3fr+ewvga9+EcsTr8+AvKa8NIrPzHZfjULPz8Xhh8YBh/WHrsnDjzx+AJoa1HiTmB9c2uHPrNpW64ho6wBo3xtsXleiNztpDPhOtuxuKJODToBwtpUoqBTZxJdR+UNGEpnynG4fOyLycO8Ia4Kp183cfl492gS/kt5KJMxn13OYbVCpnQWaEe08mnsupkLCyNdcU0webQoijHoNfWHa0j8aBIAYVBsk5JgoKK2SEFVIy6mlsLKRB+TAuxhoKuNzLJ6/O/oPWSWNWBsP1tsmhXMGAy5znJVTNFAtEBAo7Re/vf1k1PJrAJPTVw+Pvj7Hv5LLYWVsR6qOFzxogERnlbY/XK42tmPh24XiAc3C6ub8OIfsbj1wQTczavGjcwK9Hc0xYwQZ2SVS5ZJLqppQnOrQK2FNqKzKiWyTAMczXBi5XCJa1ZzKx/jv72CcjmrBLOhbMVI6VIYALAvJk9mERSm39uum7ldFnhiUlDVqHLgSRW9Iw9Ps9gGnkQtAHmfvuhxlYrfUBQ1E8BBAGUAxtI0rWr4/xcIA0+j5G1A0/R2ANsBYPDgwX0xuNirKPsRclp4OBpXKHcFLDaqOFylo4wAsCc6D3ui8xDpZY1fFoaJgzrSxT27Q3OrQKaxcyKhGMMYViWTp30NF5qmcTSuCFFpZfC2M0FTa9en6ypFAe8eUZ7tpMj7f9+TH3hSsF9sjmwns6KhReHqZk//fEOlzrU00cps6iqsbsLKA/EdOkZHME1fFZm3PboLz0TOOfwaLc6O7C5MWZll9c1482ACbmYpDmwoUlLbBGtjfZWmELK1JzoXWy5mKPz7ypNYWItFO2MR/d54lfdlylTcF5Mn0Sn/XUPFY2lacfDpfYbpSz3dhn8eFc+XnhK6JzoP5oa6MjXalFE0Cn8qqVgiG+JEArvBjBMJxTJ1aZSZtuU6IpSs7KbImXvCbOWSGubOq0BAY+OZVByMzYeJgQ7emeyPW9mVOBpX2KHAU3JbJuKF1FJsOqPae9aEu3nVOHy7ADmVHIz2s8XcwS6wMzXAZoYl1Zl8fDIZ/3vCH/XNPMTmVMHDxoh1Jy0hX7O1MuWhKCCvkoNzyewz0n++nCVTA1Ha9xcfiLOOmByPL8Kq8b4Kj6GpQbn2vr+QgVXjfBVOiZZ3naxtejS4pizoJHI3rwqhrpYSr5dRWo+5v0ajpm2wbqSvDXa/FI5Xdt8Rt2uOJxTDwkgPG6YHgqZpZFdwYG9mgH0xeayz3ygIF2NYvPuOwkBpc6sAp5KUD1huOpsqvja2X6USAG7lVOF6RgUmBMhfnVUR0bRxEQ6XjzFfX5aYkpVYwBxsV3WWoEBA42pGORbtlAy6p5TU4ckt1/HvW8Iuc0FVI0Z+FaXawTWEafXdnroAAKFZbANPojVe5YXRRVdX1vllFEXNBbAfwkyncTRNM89zUUy0dr38wi3EY+Vc8kPxzawjYrIrMczHBlFpZUqLZ0dnV+LHixlY92QALqaW4sPjiqfwdCdVih63b5fsjcnDejmrl/UU9wpre9ySyEzT4UTiu6hhrYiyuffdpTMa3Krq7qATIMzG+G5eCIz0dBDmbgkbE328d/Reh4JOABC56RKG+1h3yu9lW1SWWkEnkYoGLpbvZV87TISpH6VqgEJTGnrAd0eVP20rX6C0eP6PlzIlAk+F1Y3YE52HuqZWzAlzYZwWosgbBxMwPcSJ9RSRFh4fNY2t+PikevehW51YdPd4QpG4s87h8iWme2sq+1G6np+qmlv5rLMxGrl8HLqdL1H/LzanCl//m45r745VsKeknTdyEZ1ViaKaJomO+uIRnpg72FVm1bHucDSuEH/cyNF4gfRfrygeJ9984YFM4KmsrhkfnriPtIf1GO5j06EBVEUupJZicqAD8irlLjKuMbO3RWNigD22LwwT/9b3x+ZLtNOvZVTgr7sFMoNpu27mYuU4Hyz8PVZiARS2KAp450gSq+y8lfuVD8LtUZCVCQAf/ZPMGHh6UFqPHVezweHy8Gy4G0b6yk79ZRqwlq4DJG8GxJl7JZg1yEXhubWXV9Uo9/uZXlqPnAoOtl/NFq8A2d1omkZxbXOXtu+Ti2txLaMC3rYmGO9vpzARQSCgkVhYg9K6FkR6W6s0s0SZXlJ6TKPYBp5EIdFJFEVptV/ZjqIoUwDDATQCYDX/iaKo5wDsBlAE9TKdRETVNdWfKE30KpoIOgHCwFNSUS3rkZXfrudgzaR+eGX3HY28fmdpv6KHMu3r73RXB04VhdWdXHNKwU1P3gpjqhTfJggmoqWujfS08dOCgbiYVqaR4yqbCqYuTQTs1HmP/yQWd+nqVJll9dgTnYdTSSUwNdDB5EAHjPCx0WijsyPad6QFAhrJxXWo5LQg3NNKpsjwbZZ1/0TFehtaeJj3a4y43sfB2wVwsTTEL8+HSayypMyVB+UY08+O1bb91slbV6bryJsywlSguys1NCv+zS3YEYPo7Eq4Whphy7MDEeqqvNwq06ITAFTOgGAaRPjteg4O3SnAiRXD4WVrotLx1CUv+1hTbcb20h4qD5Iwnc6rf8bhbtv027zKzuv0L2sL7M8apHr9JS5PgBsq1p37L6UUWeUc+NgJ/9Y7b+TKbCOvjflzVJZaQSdAOAVV3X3VUVTThK//TYO7lTFmDHSCvo42qjlczN8eI85uP59cir+WR4oL1GvCh8eFq16zzdoT0DSis+Xf/+dsuymxYiAbvyqoRxa56RIyN04RLyqjipwKDhbtjO1whr8yXJ4AApqGga42otLLsGT3HXEw8IVId3wyI4hxv6xyDj44fl8iSDehvz2+nD0A1iaaWcmvr2H1LaFpOgvAeQAeAFZIPf0xhBlHe2maFofXKYrypyhKZr1PiqJeBLAHQD6AUcqCThRFBVMUJdPSoygqGMDGtv/uY/M+iJ6vq6K/XD6NHy6olmQX/PG/nXQ23SezTNho1GStgc6iyeXdmYjqZTGRt5pQTkXnjygSfUMjl4+Xd/XswHZ3Wn8iGR5rT2P14QQkFtR0aBqrMvtu5WHC5qvYE52HKg4XeZWN2H41Gy/8EYsZW5UXde8KovoqNE1j7bEkPPXTdSzaeRtTfriG0nYZAPmVjViw4xarY47+KgopxXXYfTNXpshsYXUT5v0ajYJ2dV0KlNSbk57q0VtpKqtJHakldYz1Ctu7mVUJmhZ+J17bd1cchOnOqSv1zTzsi9FMcEXZnX/utmjEdWGGsbIV10T+ji8UT18rq2sWB526ijoF6V/78y6rumjSPvpH8UwA6alrIu0XC1BVdwz8bY3KwrtHk9Bv3TmsOZyIg7cLJO5FPAEt/n7w+AJEZ1XiXxWmeTLhcPkazU5SNejEBlMdJzY2/JPc6UGnrVGZCP3kPEI+Po9NZ1Kx/Uq2RAbanug81DQyfyZf/5su89lfSC1F2GcXWE3fVK7vpTypUlz8NQA3AWyhKGo8gFQAEQDGQjjF7gOp7UXhbfGnSlHUWAhXrdOCMIvqJYY07Bqapr9v9//VAJ6iKOoagAIALRCuavcEAG0AOwAcUOF9EN1A02nOHdXKF6hcx4hpha7ebsLmq5jQX705612tff0BTSuplb/i0uOoMz9LguhMx+KKcO7+Q/z83KBOe42ePu0YEE6PXhDhhsyyBhy+86jRn1fZiD9v5WP1RGFlhAO32XdYimubMXXLNbnPc7h8cUZMiIs5alhcR748l4ZRDFNPCHZUrSlZXNuM5OI62JnqY8Fv7AKOneWPGzlY/1QAmrh8tYojizS18nEqqVhu8CK9tB6zt91U+/iqUlTbqb23DiXCx84Efy2LRKGCVR17kgup6mXciuoTKap7+bgRrdQm7UJqKeZvj1ZpBkJv996xe+LM0P1LIjDM24bVflcelCvd5lJaKcI9rWGizy5kIRDQ4HB5MDXQRVx+Nb7+N138nLzMrdWHVa8fu3J/PIz1dTC2XVavotVbCSHWgSeaprMoihoM4BMIgz5TAZQA+AHAxzRNswnlu+NRltXLcrbJg3CVO5HjAMwABAMYB8AAQCWAswB20DT9D9v3QPR8mljJiY0+dG9U6kJq166Yo66z9zs2aqTIS4/JyDxB9AWNXL7aK4I+LgQCGnH51Zj1s2yHe8vFDDw90BmeNsbYpqRIsrrYrjq37XJWp52DJi3dcwe5FZ08nbuLFFY3dngRFk2ZuPkKMsoaMMDZHL8sDIOzBfuVGEV2XNPMogHdIbOsAZv/e4C/7nashldPJwo4nUxizg7va7oz6NTdwb8FO24h+/OpShdwqmS5wvjLu+7A1coQh5dFwtHcEK18Ae7kVqOplYehXtYSU8vPJz/E2mP3UN3Ixdh+dqwHWS+pWeLgq3PpEoEntuVb+jJVMp5A03QBgJdYbivzjaNpeheAXSq+5nEIg09EL9bTCqipUoSbeDyV1DYhNqcKApruEcWuCYJg73K68pHSx1l6aT1j0Elk0c5YfDgtoAvPqHc7n9I7BmDYWL4vrrtPQSyjLfh1r6gW7x+7h90vh3fzGXU9ZYX9HwccLh8Lf7+Faxmq1YciNG/C5qvdfQr481YeFkZ6KAwuhX12gfXxCqqaELnpEuaEueBEQpF4Bko/e1McXDoUlsZ6aOLysfJAvLh0iLrBJFVI1xhjmw0p0tP6xl1BpcATQXS2rvoRnuvE7Bmi57udW4UXfo9VebolQRBEb5BX2YjFe0jNMKLnYDOthui9SNCJEPnwRDJ+uZKNSg67rCa2jkjVkkovrcfAT//DrffH4+qD8m6pV7t49x21Z470xbIXJPBE9Elsll8lHl8/R2WSoBNBEARBdIMS0gYjiMdaV9Y7ivj8Ype9lrSOlCvhKVjU6HFFAk8EQfQpHmtPd/cpEARBEESfM+WHazDV10Fsbt8pvEwQBMGkLxZ9IYEnokfpg9NdCYIgCIIgHnvSNVEIgiD6KhUXLX0saCnfhCAIgiAIgiAIgiAIguio7l6BsDuQwBPRo/TFCv8EQRAEQRAEQRBE39AXV1gngSeCIAiCIAiCIAiCIIguIOh7tcVJ4IkgCIIgCIIgCIIgCKIrkIwnguhmFCkvThAEQRAEQRAEQTym+H2wujgJPBEEQRAEQRAEQRAEQXQBPsl4IojuxeuD0V+CIAiCIAiCIAiib+iDcScSeCI0L9LLWuax8f52rPaNSi/T9OkQBEEQBEEQBEEQRI9AptoRhAasnuQn8X8dLQpLR3mx2vdWdmVnnBJBEARBEARBEARBdLu+GHjS6e4TIB4/Qzys8O3cEPx+PQd6OlpYMdYHXrYm3X1aBEEQBEEQBEEQBNGt+uKqdiTwRHSK2WEumB3m0t2nQRAEQRAEQRAEQRA9Rl8MPJGpdkSP0vd+ggRBEARBEARBEERf0Ren2pHAE9Gj1DfzuvsUCIIgCIIgCIIgCKJT9MWV3EngiSAIgiAIgiAIgiAIogsISOCJIAiCIAiCIAiCIAiC6Ax9MO5EAk8EQRAEQRAEQRAEQRBdgdR4IgiCIAiCIAiCIAiCIDoFn6xqRxAEQRAEQRAEQRAEQXQGUuOJIAiCIAiCIAiCIAiC6BQCkvFEEARBEARBEARBEARBdIY+mPBEAk8EQRAEQRAEQRAEQRBE5yCBJ4IgCIIgCIIgCIIgiC7wRKBDd59ClyOBJ4IgCIIgCIIgCIIgiC5gYqDT3afQ5UjgiSAIgiAIgiAIgiAIoguQ4uIEQRAEQRAEQRAEQRBEp+iDcScSeCJ6lnmDXbv7FAiCIAiCIAiCIAiiU5CMJ4LoZgsi3Lr7FAiCIAiCIAiCIAiiUwj6XtyJBJ6InkWLorr7FAiCIAiCIAiCIAiiU5CMJ4LoZjT63o+QIAiCIAiCIAiC6BtoEngiCIIgCIIgCIIgCIIgOkN9M6+7T6HLkcAT0aP0weAvQRDEY2egmwWuvTsWW54d2N2nQhAEQRAE0aNcy6jo7lPociTwRPQoj1PcycJIt7tPgSAIKRP623X3KfQoswY6d8pxwz2s4GplhOkhTp1yfIIgCIIgCKL3IIEngugkF1eP7u5T0CgPayPYmup32evteyWiy16rN/v7tWFwsTTs7tPoEmHulho4hpUGzqRr/DA/FFOCHPBksGOnHH9asCM2zwvFH4sGa/zYOtpkoQiCIAiCIAhCiASeiB7lcSm09sxgF1ib6CPQyUyjx31jvK9K26uySOCJFcMxe5CLxGO2pvrwszfB6+N88O9bo/DmhEevr61F4deFYSqdD1sbnw7CCF8bXHlnDN6f6g9PG2NYPsYZZO7WRsj9Yppa+w50s8Q3c0M0fEYdQ1FAf0fNfve3LwzTSDBy/hBXDZyNch0NFs0a6IwZoc7Y9nwYflowCLMGqZaZZGWspzS7K6DtbzTO3x43146Dv4Op2ucrTVtL9eZFzqapGnv93srNyggTA+zhZWPc3aeiEWun+CP3i2lqX9+Ijon0sn4sXoMgegpni74x0MdGyieT8e+bo7r7NIhehASeiB7FzLD3Bxd+eT4Mm2YFAwD+94S/Ro/91kQ/uFsbMT4X8954cWff0kgXB5YMxeW3x+Cr2cFKj7v5mRCEuFrgm7nB+OX5MCwf7Y3fXxyM2x9MwPm3RmP1pH7Q19HGcxHuOPvGSHw9Jxj/vTUKkwMdNPr+AODy22PwXIQ7AMDd2hhLR3kj6u0xiF8/Sa3gkyj4pqPVNRkYp1aNwOIRnirts/ul8A69ZoCCAKeOFoVtzw1C7hfTcPntMSofe4CzOUb72Srd7tu5Ifh0RiCWjvLCgSVDcWrVCKwa5wNPDXWgR/rawlBPm/G5maHsp3NZGuubA4wiAAAgAElEQVRp5HyU+fDJAAxys1C4zcmVI/DmBF9YGevB2cIQIS7mmBRgjzUT/bBp9gCJbb+cHYx+9uwDQ38ujsBvLw7B+beYG4U6WpREEM7JwhAbnw5Selw7U32sfzIA2Z9Pxfm3RuEVOd91dX5uFEXBUJf5b6xJr47xZnz89XE+Sve1MVH+/flPzmfOxlAvK+x4YTAuvT0G0zop062r+NqZYNkoL/H/332iXzeeTfd68NkU5H4xDSmfTMaLke5d8pofTw/E/iWdnzl8YOlQ7H2lY/cwQkh68K83MNHX6ZLXGeJhiQ+m9u+S15JnpK8NotRoR4nMCet5f9/kjyerPeijRVHo52CKO+smaPisei8yyKJY11wtCIIlLxtjuFkZIb+qsUtfd/4QV0wd4IgQFwtEZ1cit5IDQ11t7L+Vj/TSepntZ4Y6wdPGBN9deCDx+Kczg/BE0KNgzCg/W3w6IxAfnkjW2LnKSwpzMDfA2TdGoqy+GTbG+tBq6/m5Wxsj1M0CW6MyUcXhYk6YCx7WNmPLxQxw+QLMCXPFjFBhNgVFUXgiyEHiPUjr72imdjaLFgUI2p2/kZ42XhnhiWWjvVFW1wxPG2NQCtK0Pps5ACv2x0k89t28EIz2s8Oe6FzczatGUmEtHM0N0M/BFOumBcBEXweGetqgaRo0DXi9f0atc2/PzEAHE/rb41h8kcTjSRsmwcxAF4FOZpg1yAWF1Y34O74IZ+8/lHusXxeGwaMtOBPqaoGEghqJ5/e+Eo78qkZ88Pd9Beeji2cGu+DwnULxY9/MDcGTwY7Q19ESf6YCOV+eBRFu2H8rn/G5Q8uGwkhPB8fiCrH6cCLjNp/NDMJshgbVmkn9sGZSP6zcH4dTSSVyzx8AFo/wxCB3S7z2Zxzj86Kg05sTfPH9hQzx40tGeuKtiX44nlAssf2MUCeckHpMlZFKMwMd1DGsOOJiaYhx/nbYE50nd9/5Q1xhb2YAHW35YzsT+ttjgIs5BriYizMZFX33dbW1sHSUF9b8xfw3aG/7wjDxb9TP3hSnVo3Aj5cy8G9yKQDhtNkPpgXA2kRy6qyjueLPx9PGGJfWjBafp5+9KRaP9MTv13NktrVSM8B39d2xGLLxglr7siXvGvp8pDu2XMpUuO/MUGf8xvB+vWyNceGt0eLrriaM9rXFaSW/G1UMdrfEnbxqjR1PETtTfRxcOlTiO/3qaG98dS69S15fkf6OZkgtqeuy19vy7EDo6QivBUZ6Ovh4RhB2K7h+dNSmWQMwb7CrRr+L8iwbLQwsjvS1xapxPvhRye+HUOyrOcE4Glco8/iaiX749r8HDHto4DVnB+Pdo0lq7XvstWEY6GoBz/dUa1c5mRuguLaZ1baLhnlg5Tgf2LTdr8b1t8P4b6+w2jfU1QJ/Lo5AZlkDZmy9wbjNKyM8ce7+QxTVNCk8lq42hSUjvaCno4Uf5ofijYMJrM5BZNloL7w3pT/yKxsRm1vFah87U33UNbeiuVWg0mupQluLktv28LIxxqczg5BYWCNz7fZ3MIVB20CRjYk+Fo/wZLw3EkR7JPBE9CgURWHrgkFYsT+uU4NPBrpaOPP6SNiY6sPMQDKLpn3Q5cVhHriWUY6Fv8eKH7Mz1ceq8b7wtjWBk4UBNp5JBaeFhxmhzozTeBZGemBhpAc81p5mPJfFIzwxP9wVT3x/DTxBx6ca2pkayDzmZ2+KH+ZLri718ghPtPIFMNLrmsvA3DAXfDQ9EHdyq+BkYQhPG2PQNMQNchNbE6XHGOtvizB3S9xt6zyFuFpgYoADTPR18OYEP4X7UhQFikKHA4E/PzcII3xtYGagi+eGuiEmuwpBzuYY5WsjvnlTFIUAJzMEOJlhUqADqjhcHIjNx9f/yna6Rvk+yiZ6c4IvXtp1W9wx9rUzwTBvG4z0pXDkbiHi8yWDUktGPso2+fzpARjkZokHpQ0Y5WeDMf1kp1k5yQm8fP70AKwa54PITZfkvu+pAxzx3rF7aOFJNoDMDXUxXUnGkbxv9Sg/W+RVcjA50AHvTu4HHW0tTB3ggDP35Afq3hjvCxdLI9zJrUKoqwWeaetgZX0+Ffti8pBUWIsITyvMHeyCioYW3MisFO/LNuPCxkQPp1aNxLWMcjS18rHxdCpaeAIY6Wlj06wBCPe0gr6OFqKzKxHoaA4nC0NxENrJ3ACvjfFR/MalKAo4sbF1wSBs/i8dnBY+XhzmgYkB9hLPBzmb49eFwjpOAgEtt0PqZGEo8fuStv7JAJlzdTQ3lAl66mhRmKli0fLVE4W/X1tTfRxfMRwzGToJutoUWvkdv0bScv4wdqYG+GRGID47lQoun7mhP2ewC2Pjev/ioRKfq562ltxjKKLbLlg5LdgRm86morqxVeXjMPlzSQT6rTun0j52pvooq29Rul2AoxkOLBmKlJI6cFp4iPS2hrFUJgRFUcjcOAXXMitQ2cDFmH620KIoDPviYqd2rKSdfWMkDt8uwNbLmeALaBRWK+5wyrNstBd+vZIt8dgQD0sM8bBCbE4VAp3MMDvMBcEuspmPo/xscfVBuVqvK7Jz0RC8tOu2zOPPhrtJ/N/BzAAP69h18lX1zqRH19QXIj3kBp5G+trgemYFDHS00dTKV3hMYz1tcLjM28wa6IzlY7xx9UE5tCgKO65lo4RlAKM9VQI5WxcMgr6OFrS1KHx/MQOJUoNDAPDbC4OxeM8dlc+jPS9bY2jLuTY/EeSAny9nKf3smEzob48LqaWMzx1fMRyhrha4mlGudHBI2oxQJ4S4WKh8//J3MMWhZZGY+sM1pcEeR3MDbJgeKPGYt62JOKskKq0Mqw7Eo6GFB187E3w5JxifnExBYmEN/B3M8N28UBjr6yDE1QKxH4zHxtOpoADMGuSCUe0yuZtb+fiTYfBNT1sLr431hr6ONkb72Yqzy2eEOoOmgTcPsQs+OZkbiLODl4zykgk8WRjpoobhOv/F7AEoqmnGh8flDzx2hKuVoTh4xIgChvvYYLiPDUb42ODFP2JR3dgKUwMdfDpTMkN6YaR7twWevGyNkV3OUWtfRW0eJimfTEZxTRMmbL6q1utJ2xqVidfGeHe4HdhbkMAT0eMMcDHHlXfG4FJaGV7Zrf6NPNDJDOaGuriZJex4zgh1wrdzQxRmITAZ6WuL3C+moby+BXmVHAQ5m4sv1HMHu2LWIBdweQK504AUMdbTxtuT+8FAVxu/LgzDz5ezwOUJ8PxQN6w/kSzRyReNLGoqrVlXW0uik9PZpoc6wURfhzEgwpaRng7+XByBWzlVENA0Ir2sFd80GSyM9ECwiwWSCmsYA1D+DqZwtTLCWxP8cCevCuvbbfPMYBdMHfBo+kuYuxWrYtVWxnpYOsoLJxKK8KC0Qfz47y8OlvjejOlnh52LhuCfxGLYmQobKqKG6B8vDsHULdfEjWwzAx08P/TRlA0dbS3Ml+pwSDPQ1caLke4So+0bngoAoDzbxUBXGz8+OxDvHk0SN5BG+tpg7RR/meCttHH97GQyN/wdTLHnZdnpGSvH+soEntpPAaMoCnPCXGRS1rW1KLw4zEPise0LB2PnjRzkVDRiUqA966mhn8wIgoO5AeYOFgaSF4S7IaucA3drI/H37YNpARL7PBvuioLqRgQ5m0NfR7iNvAAH2p5VlbxMw2nBjqynZSnLgvjl+TB8eioF94trJRpy00OcMNLXhnGfdyb7I7GgFuml9dCigA3TAyW+E1OCHGSy/vS0tfBUiBM4LTwM97GW+C6Hulrg2GvDcDy+CJZGenguwg2WxnrQ1dbC2G8uI6dCvQamiKJaVi9EemBumCtqm1rxU1QG9sU86ox42RrD38EMHz0VgI9PpgAA9HW0sHPREDiYSwb8N80awCo7TdpLwx8Fk431dXBg6VD8cCEDlQ1c2JrqI720HpllDQqOwGzNRD/oqlh366/lkRjiYYXmVj4yyxrgY2cC/w+ZA1eHlg2FqYEuIr0V1/vR0dbCWKl7wJV3xiLi84sSj3nbGmPvKxHQoigs2hmLtIeymccAsHKsD5aP8UZUWhnSHtZha1SWwtePfX88AOCZIa54pm2g6JcrWfjibJrC/dytjeBmZSRe/vrdJ/rhpWGeiM+rEXcig5zNsOulcJmAG5PPZgRh1NdRSrcDgPem+GNTu/PT09HCrffGo7xBeUAQADZMD8DyfcyZpGyZGujg7rqJaOULcD2zAib6OhjqZS0RKLE11cfXc4LxzhHZ7Jm9r0SgkcuDoa42ssobZDptU4IcsHy0N4KczaFFAb9dy8HGM6kyxxndzxZ+9qbwa5t2/EKkO/zWnYX0mN04fztcSitjfC/+DqZ4cbgHLqSWIrGwVuH73vNyuESAYtsV5u+XvZnsgJ+qVimY6quvo41tzw/Cop2ygUZFZg1yxuZnQlHN4YKG8O/Y3MqHqdQ9++Ppgahs4CI2twq+dib4ak4wSmqb0coX4NDtAvH33sxABx9M648BzhbwdzBVej95eqAzPG2MUcXhIruCg5E+NnhlhCfrbLx1UvdZaWP97RC/fiIe1jbDxdIQFEXh+IrhaG7ly7QN7UwNZAZgRZaN8pYJPIV7WGHPK+Fy25gzBzorDTxteCoAPAGNJ4OdxIPCEwPs8d28ELx1SHh/0Nai8OmMIAS7mGP015fF+w5ys8AYPztoaVEw0tXGxbRSeNmY4F5RLa50IGgtmnlAUcAb4xUP2BroPHrvwS4WiP1gArLLOfC0MRYPGnfUO5P7MQ7KsrVuWn9kV3AYA09j+tnicnrHAvzSjPR04GNniiBnM9wvksycbT8YzNbX/6ajv6MpxvnbK9/4MUACT0SPRFEURvraItxTOHLI5OTKEdhyKQP/pUiO5Kye6Ac3KyNMCrSHoa42MsoaoKetBXdrow5FlG1N9RlXddPWotQKOgHAt8+EiG9q4/vbY3z/RxceCyM9/K+tkz/S1wYrxwobJe9N9ZfIwALAqjZLZ1k7xV9pox2A0uAEWwa62qxqDikS4mqBEFcLjOlnh5FfPWr8x384UaIGUICTGexM9XEtowL+jmZ4tgOFqXW1tbB/yVDsi8lDRUMLpoc4I9xTNmg1pp8dY3DO0lgPfy2PxKHbBWjhCTA3zAXu1qrXT1r/VCACnc2RUlyHSG9rlep0TQp0wIT+9qhv4cFchXpsUwY4YNPZNFS06yjJyz7q72iKV8d445crWaBpYQdC3boXxvo6WDlOtiC/tbEeKjlcxn30tLUwSSpjSEdbC/2UFN62MzOAnQqdj/YBBrb6O5oiwNEMKe2mCWm65oWtqT62PPuocZ5XyYEWRcHVirm2nGifs2+MRFZ5A+zNDWR+629P7oe4/GqU1gn//s4Whtj50hBx55HJIDdLDHKTXcXwf0/063AnekqQI9YfT0Z9y6OplOumPfocDfW0Yainjfem9EdNYyuuPChv64wJi/i/NNwTw7xtkPawDkM8rBgzCZ8MccTZ+w/FmQbPRbghsbBGpqHa3sxQJ3jbSv6m/R3MsO15yUUcSuuaMeOnG+IsFksjXcwPd8PyUd54+ucbyJYKzC0a5oFXx3gr7Oz52ZtIBMUDncwQ1vb5G+hqI8jZXO6+lka6Mh1ZVdibGWD3y+FYuucOWngCmBvq4rt5oeLP9cTK4bibVw1zQ13UNrXiRHwxrE30sGiYh/g391SIE54KcWIMPJ1cOQKWxrpwtjBkbAPMH+LKeA+jKOG0TC1K2K6YEeqM5lY+tLUo8aDN3sXhuJNbDQFNY4iHFeuBEDdrI2RunII1fyXiUloZ7Ez14WplxNhJWjrKCxwuH4dvF8DKWA9rp/jD0lgPFka6cDQ3kMj4eYLhei49pVbk5tpx+ON6jsIsBV1tCo7mhvhydjD0dLSgp6Ol8J4xd7ArhnhYYcbWG6htaoWXjTH+XjEcAMTZ1T52psj6fCqSi2tRUtuMga4WMtfOJaO8GANP1saS70VHWwuHlkXipZ230dD2e940awDmD3FFeUMLPjmZghuZFeKsQQczA3wzNwRmBro4+uowJBbWwkRfB7am+njnr0TE5lQh2NUc38wNYRyMWT3RD/O3x0g89sZ4X+jqqN62fH+qP1wtjZD6sB7Dva0RoaBIOw0aY/rZIWfTVHx/IQM/XMyQu63ITwsGYkqQcECifbuGacDR2kQfB5YORStfIH4+uO22+0SgA25mVaKsvgWj/GwYs+qZrJvWH4tHesl9fvFIT3EAX6S/oxnMDXVQzWnFvCGurAZUdLW1ZO5Pqg5Iulkb4ZMZgfjibBpaeAJMD3HCV3OClQ7OulsbIa+SeXbGB1P7Y5Gc+/zTA10wJcgRKSV18LYxgXlb/dLcL6Yhp4IDc0Ndienqs8NcxOUMVsgpR6CMvo4W/lg0BPZmBojPr0aIq4XEPXjDUwHYIPX3eG+qZJ1aXRZtIVW9NsYbLpaGuJVThRAXc0wOdEDoJ//J3X7LswNRUtOErPIGDPexwfQQJ5y7/1CmXISblRG+nRuCsM8UT92fG+aiUsaTyM5F4Ziw+Qpqm1rFr7d2inrtsU1n0vpM4Il6XFYRY2Pw4MH0nTsdS4UlulYTl4/L6WWob+ZhXH872JjoS9wY0x/WY8GOGFRyuNCigO/mhYrrFfU0TFPtfnk+TGE9Jb6ARkMzT3xTAgAuT4Ble+8gqq2BGuRshj8XD1UpEKBJZXXNePLH6+LpGPZm+jDW15EYfTDR10H8+oldmmFFqI7pO5r1+VS56f+qyCxrwNaoTFQ0tGBOmIvS32k1hwsOlwcXS/kBD3UduVuItxmyUaYEOWDrgkEaq42yYn8cY42eEFcLHFkeqdbvoayuGV//m46cCg4mBthj6SivXpGi3coXIK2kHh42Rh0KUgDAqaRinEgohqO5gcJaW0xeHu6J9U8F4G5eFTb8k4KS2mbMCHXC+1P7y/2e0zSt9mecX9kIfV0t2JsZYPpP15HEkGHx6hhvjPGzxWAPK5V+a/XNrTDR15E4t7K6ZuyNyUMVh4unBzpjsIdkcFvelO/0z55AfTMPl9PLYW2sh+E+Nowj2odvF8jUg/n5uUESmaDqauTykFnWAD97U5U7jiIfnbgvkdHpZWOMS0qKAbfw+IxTEC+tGY3EwhqEuFjAi8VUcHWJvl+/XcvGZ6dlgy2KitXezKrAq/vixEGe3S+Hy3TCeXwBBn7yn0Sgdby/HX5fNASAMJCZW8HBkj13JOraHVw6FIPcLNXObOjI7wYA1h2/J5FxaGGki7vrJjL+Rppb+XhQWg9fO1PGgUCaplHe0AJbE32F56TsnLk8AZ77LQa3c4UdVVtTfRxdPgwuloYYsvGCxIDGSF8b7H0lgvE3l7NpqtzXYdo++ePJ4ky6zLIGTNgsW+Po14Vh+CehGHZm+lg+2lsjWVhsrT9xX+JaTFFA3LqJChfzqOJw8cT3V8VtR2M9bZxYOQI+dp33W1OmlS9gzAiT58y9Epm6lCEu5pgc5IBXR3fO9KnX/ryrsByBSJCzGTY9HQxbU32klNQi2MVCXCeLSRWHi2d+jRZn1I7wscHviwaLM7iVyavkSGRssSV9fattakXIx+flbp/26RMy9wcuT4BRX0VJTCkW3Zfu5lVj9rabco93c+04DPtCfpkJRedL0zRyKjiwNzOQyHSVd59le9zejqKouzRND2Z6jmQ8ET2aoZ42pkg1aNt31vo5mOLG2nFILq6Fl41Jl61YpQ5PG2OZKSKD3BWveqWtRUkEnQBhmv2OFwYjvqAGza18lUZZO4OdmQGOvjoMx+KEhbZnDXJGVnkDlu65K65xsmKsDwk69QIrxnpLZAwsGuahkaATAPjYmeC7eaGst7c01uu03/OcMBfo6Wjh3+SH8LA2wsvDPWGkp6N25qI8r43xlgk8+dmbYO8r4Wr/HuzMDPD13BBNnF6X0tXWwgAX+Vkzqngy2AlPBgvrirEJPEV6WSOjrAHj/G3FmXZh7lY4uWoEq9frSOfBTc4qpO2pu/opU+fIzswAaybJr2X2zdwQmaDrnpfDoa+jDX0TbaWrLk0OdMAfN3LEU99CXC06nIEqYqSnw1gPSRVrp/RHXTMPUell8LUzwRcsVnWlIKewrq1JpwacxK/fge/XMG8b3F03AaX1LXAyN2A8lo62Ft6f1h/vHbsHQDjdqn1NRHszA9ibGeDA0qHYdjkL9c08PBvuhqEKMnDY6Gin++1J/ZBZ1oCY7CrYmurj+3mhcu9HBrraCr87FEWxytRRds56OlrY/XI4/kspRV1TKyYGOIin2a5/KgBvHUqAgBZ+xm+3/Q7fGO8rkaG0YqzigMTKsT74KepRrazpIU6spm9ODnTolJWG2Vg6yguX0srE9dJWT/BTev+2asvi3n8rH82tfMwd7NqtQSdA9RIUUwc4YuuCQTiVVAxHc0MsH+PFOiNMXfKyjycF2ONSWhnszQzw9dxgDPN+NDVeeio4EytjPRxfMRzXMypgpKeNCC8r1kEnAHIHCd+f6o/Zg1yUZh6xxdTf0dPRwsGlQ7HlYgZK65vx9MBHZTHC3C1xfMVwHI8vQm1TK/5utyjQmddHwtHcAM4WhkrrjQHCtkR7FEVp7B6x80aOWpnwvQ3JeCKILnIysRirDsSL/z8tWHjDelzlVnBwK6cS/RzMEOrasc4E0TUEAhoHbxfgTp6wcPdzEe4aCzz1RTRN47PTqeJV3yI8rfDHoiGsOhEEO2xGFnvKSKK8jKeuPL9GLg8v7byNW21T2CcH2uOnBYNU6mw1tPDExZ1H+dl02QIVnYXLE8Bv3VmZx7v6e5NV3iCzWleIizlOrGQXIFWmuKYJGWUNCHW16LYMaXXUNbfCVCqzr6cqr29BRlk9gl0sxPU4aZrG8YQi3M2rxkBXS8wa5KzwvQgENP64kYOY7EoEOpnj1THeEp3t5la+TK01XW0KGRunds6bYqm5lY/Egho4Wxp2SqYyIVRS2ySzEIxoWmMLjw89ba1u+61sOpOKX69KLrhw6/3xsDczwOivoxinJaqa8aSJ67J0DbDTSSV4/WA8+AIaBrpa+HRGEGOtOlHdQ2WW772Lc8nKs9KknXl9pLiAfW9GMp4Iogd4KsQJFka6uJRWBi9bE8wbrH69oN7Aw8YYHjaq1yAiuo+WFoUFEW5YEKG4SDnBDkVR+PDJACwd5YX65lZ425r0is5Tb/LFrAFY25bJwcTSqOd0sMf42coEnoKcu7aRaaSng/1LhuJ+US10tbXQ39FU5e+kib6ORqbWEZK8bU0kVrvTooDXx8vWqFOXk4Wh3JVNezJN1YfsCky1QCmKwtMDXfD0QHa1CrW0KCwe6SW3PpKBrjaei3CTKIatbtakJhnoaiusU0VohqO5IT6dGYTPT6eiqZWPyYH24sU5VMlQ6gxrp/hjgIs5vvk3HaGuFnhvan+Vp3zqdcHsCOmsqWnBjhjsYYmUkjqEuFjAylgPJvo6eLXdNMof5oeyCjoBwBsTfHErp1JcW+6zmUFYx2JlwqlbrvWYgbLOQjKeCIIgCILolWqbWrFgRwySi5mLdn8/LxQzB/aMun+ldc0Y/XUUmlsfrVYqvWoW0fVomsaIL6Mkplq4Wxvhyjtju/xcmrh8HLydj/yqRkwKcFC6SiDRN/EFNA7ezsf9ojoM9/l/e3ceZ0dVJnz89yTsCGGRzQEMO4wOqESBICMJijoqi7uyj+uouIz6usyrA867OKPgAjqiIqAoKrggyqZAAGEEUdFxBYSAbAJhEQgkgs/8cU6bm8vd+nbfe9Od3/fzqU/drjrn1OlbT6oqT1ed2vCvjx5r5bHkkUdZvOTRFXqIkUa93vEEsP/xP2z5xsnGsemGpd+x6h5Y8ghX33Qv22y8NpvNWrPncZ+Of/VTp/y/Z+94kiRJ086sNVfljDfO5Uc3LGK1mTOYOSP4+A+u4a4HlvLyOZuz/1NWnAu4TdZdg5MOfwafvOBaHljyCAfvvqVJpxVARPCmedvwL99a9hfpN+29zUj6suZqM1eKcT40MTNnBAft9sRRd0MjtPoqM0d+h9N4zNthY06+fOFyy9oNw/HRl+3CoV+4crk3dq46M3hTfbv3MPV7l/rjVl+FZ273+O4Fm7zlKz+b8omnTrzjSZIkSSu1n910D1f/4V6etuX67OK4hJI0aW5atJj5xyzgkb8syzt85bW7MXfb9smZ397+J77101u4+8GlvGTXzSf8woNRGs+b7qb643be8SRJkiS18dQt1+epW64/6m5I0rSz5YZrccIhu3Lchdfx0NJHOWLP2R2TTgA7brou7/uHqT/YtpYZV+IpIjYHPgQ8D9gQuA34NnB0Zt4zjnY2AD4IHABsBiwCzgU+mJk3D3LbkiRJkiRpOPbZaRP22WmTUXdjJFabOYOlj/6le8FprufEU0RsA1wObAycCfwWeAbwNuB5EbFnZi7qoZ0NazvbAxcCXwV2BI4AXhARe2Tm9U11JmXbkiRJkiRJGp7xvLPw05TEz1sz84DMfG9mzgc+BuwA/N8e2/l/lKTTsZm5T23nAEoSaeO6nUFtW5IkSZIkSUPSU+Kp3nG0L7AQ+FTT6n8FHgQOiYi1u7TzOOCQWv6optXHAzcCz42IrSd725IkSZIkScOSrDwvc+uk1zue5tX5+Zm53AOKmXk/cBmwFrB7l3Z2B9YELqv1Gtv5C3Be0/Ymc9uSJEmSJElDMXNGjLoLK4ReE0871Pk1bdZfW+fbD6Cdydq2JEmSJEnSUPz7S3buqdxG66w+4J6MVq+Jp1l1fl+b9WPL1xtAOxPadkS8PiKuioir7rzzzi7dkyRJkiRJmrj5O27cU7nPHTpnwD0ZrfEMLj4lZeZnM3NOZs7ZaKONRt0dSZIkSZK0ElhnjVW5/L3zO5b59EFP4ylbdLuHZ2rrNfE0dlfRrDbrx5bfO4B2JmvbkiRJkiRJQ/OE9dbk5x/cl2dtv/yNMGusOoOL3rU3//B3mzHECwIAABjOSURBVI2oZ8OzSo/lflfn7cZR2q7O243DNJF2JmvbkiRJkiRJQzVrrVU55R+fMepujEyvdzxdVOf7RsRydSJiHWBPYDHwoy7t/Ah4CNiz1mtsZwawb9P2JnPbkiRJkiRJGqKeEk+Z+XvgfGA28Oam1UcDawNfyswHxxZGxI4RsWNTOw8AX6rlj2pq5y21/fMy8/qJbFuSJEmSJEmjF5nZW8GIbYDLgY2BM4HfALsB8yiPuc3NzEUN5RMgM6OpnQ1rO9sDFwJXAjsB+wN31HZ+P5FttzNnzpy86qqrevp9JUmSJEmS1F1E/CQzW76er+e32tVk0BzgZErS553ANsAngN17SfzUdhYBewCfBLat7ewGnATs2px0msxtS5IkSZIkaXh6vuNpOvCOJ0mSJEmSpMk1KXc8SZIkSZIkSeNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQMRmTnqPgxNRNwJ3DjqfkySxwN3jboTmpKMHfXL2NFEGD/ql7Gjfhk7mgjjR/1aWWPniZm5UasVK1XiaTqJiKsyc86o+6Gpx9hRv4wdTYTxo34ZO+qXsaOJMH7UL2PnsXzUTpIkSZIkSQNh4kmSJEmSJEkDYeJp6vrsqDugKcvYUb+MHU2E8aN+GTvql7GjiTB+1C9jp4ljPEmSJEmSJGkgvONJkiRJkiRJA2HiSZIkSZIkSQNh4mkKiYjNI+ILEXFrRCyJiIUR8fGIWH/UfdP4RMSGEfHaiPhWRFwXEQ9FxH0R8cOIeE1EzGgqPzsissP01Q7bOiwiroyIB+o2FkTECzuUnxkR74iIX9R+3R0RZ0fE3A511oyIoyPidxHxcETcERFfj4id+vuG1E39998uHm5vU2du3Zd31337i4h4e0TM7LCdF9aYua/G0BURcViXvg085tSfiDi8y7EkI+LRhvIee1ZCEfHSiDguIi6NiD/VfX1qlzrT5vhiXPVvPLETEdtFxHsi4sKI+ENELI2IP0bEmRExr02dbsewN7apN+59GhEbRLnOXhjluvvWKNfhm3eo47V6n8YZO9Pu3NRPvGmZccbPyV3iJyPigqY6HnsmyDGepoiI2Aa4HNgYOBP4LfAMYB7wO2DPzFw0uh5qPOrB6T+B24CLgJuATYAXA7OAbwAvy/oPNCJmAzcAPwe+3aLJX2bmGS2281HgncDNwBnAasArgQ2AIzPz+KbyAXwdeCklrs6qZV8BrAG8JDPPbKqzOnABsCdwFXAhsAXwMmApMD8zr+j1u1FvImIhsB7w8RarH8jMjzaV358SVw8DXwPuBl4E7ACckZkva7GNtwDHAYtqnaWU2NgcOCYz39WizsBjTv2LiKcAB7RZvRcwH/heZr6wlp+Nx56VTkRcDewCPEDZhzsCX87Mg9uUnzbHF+NqYsYTOzU58Arg18APKXGzA7AfMBN4W2Z+sqnO4cBJlGvhq1t04buZeVVTnXHv04jYkHLdvX0t/+P6u+wP3AHskZnXN9XxWn0Cxhk7s5lG56Z+4k3LG2f8HAA8pU1ThwBbA+9uvJb22DMJMtNpCkzAeUBSDoqNy4+tyz8z6j46jWt/zqdclM9oWr4pJQmVlJPZ2PLZddnJ49jG3FrnOmD9prYWUf6DMLupzqtqncuANRqWPx1YQjngrdNU5321zumNvw/lAJnAr5p/T6dJiaGFwMIey65b990SYE7D8jUoJ6oEXtlUZ3aNkUWNcQKsX2MqKSe/ocec08Bi6r/qvtivad957FnJJsrF6nZAAHvX7/PUNmWn1fHFuBpq7BwOPLXF8mdR/lO2BNisRZ0EDh9Hn8a9T4ET6rpjmpa/tS4/t8V2vFYfXuzMZhqdm/qJN6f+46dDG+sBi+u+fXzTOo89E91Ho+6AUw87CbapQXNDi+Bch5LZfRBYe9R9dZqU/f3+ur+Pa1jWzwn2i7XOES3WfaiuO7pp+SV1+bxe2qsH9xvr8q1a1GnbntOE42QhvSee/rHuh1NarJtf113cS4x0am8YMec0sHj6u/pd3wzMbFjusWcln+j+H8Bpc3wxroYbO13qnk/TH+Hq8sMZx3/++tmnwOMo//l8gMcmFWZQzr8JbN2w3Gv1IcbOdDo39RNvThOLnw71jqz1TmuxzmPPBCfHeJoaxp5zPz8z/9K4IjPvp2Th1wJ2H3bHNBB/rvNHWqx7QkS8ISLeX+c7d2hnfp2f22LdOU1liIg1KH8NWgxc2ksdysFuS+CazLyhxzqaPKtHxME1Ht4WEfOi9XgqnWLhEso+n1tvCe6lTrv9OoyY02C8vs5PzMxHW6z32KN2ptPxxbhacXS6FgJ4SpQxxN4bEYd0GPukn326O7AmcFm9zv6reh1+Xv2xcRwqr9VHYzqcm/qJNw3G6+r8sx3KeOzp0yqj7oB6skOdX9Nm/bXAvpRnQS9oU0ZTQESsAhxaf2x1YnxOnRrrLAAOy8ybGpatDfwNZayf21q0c22db9+wbBvKmArXZ2arC71WdXqJzeY6mjybAl9qWnZDRByRmRc3LGu7nzLzkYi4AXgS5Zn23/RQ57aIeBDYPCLWyszFQ4w5TbKIWBM4GHgU+HybYh571M50Or4YVyuAiHgisA/lP/yXtCn2tqafH42IzwNvz8yHG5b3s08HVcdr9ck3Hc5NHndWABGxB+Xu72sy86IORT329Mk7nqaGWXV+X5v1Y8vXG0JfNFgfBp4MnJ2Z5zUsXwz8G7ArZQyM9SljIFxEuZ30gnpSHdNPzAyrjibHSZQL802BtSknyxMot5+fExG7NJQd5L6d1TQ3fqael1O+43Mz8w9N6zz2qJvpdHwxrkas3hn3ZWB14KjMvKepyA2Ux2F2oJz7nkA5hi0E3gB8oam8sTM9Tadzk7GzYhi78/tzbdZ77JkgE0/SCiIi3kp508ZvKW9U+KvMvCMzP5iZP83Me+t0CSWDfQWwLfDaoXdaI5OZR2fmhZn5x8xcnJm/zMw3UgYSXBM4arQ91BQydrF1QvMKjz2ShqU+Kv4lyhugvgZ8tLlMZl6cmcdn5jX13HdbZp5OedzkHuBVTX940TTkuUmTKSJmUZJIS4GTW5Xx2DNxJp6mhua//DUbW37vEPqiAaivlf4E5ZXC8zLz7l7q1Vt/xx6N+fuGVf3EzLDqaLA+U+fDiof7mubGzxQSEU+ijGFxM3B2r/U89qjBdDq+GFcjUpNOp1JeM/514OCso+P2ot6tOXYM85i0kpqi5yZjZ/QOpoyD9M3MvGs8FT329M7E09Twuzpv92zvdnXe7tlOrcAi4u3AccAvKUmn28fZxJ11/tdbijPzQeAW4HERsVmLOq1i5veUMV62rmNN9VLH2FzxPCYe6LCf6r7eijKA6/U91tmstn9zZi6GocacJle3QcU78dgjmF7HF+NqBCJiVeA04JXAV4BXtxlTp5txnf+qyYoDY2fFMdXOTcbO6I0NKv6YO7975LGnByaepoaxAc72jYjl9llErEO5JXkx8KNhd0wTExHvAT4GXE1JOt3RRzNjbym4vmn5hXX+vBZ1nt9Uhjog3uWUjP9evdShnJRvAraPiK16rKPBahUPnWLh7yn7/PLMXNJjnXb7dRgxp0lS39hzCOXC+sQ+mvDYI5hexxfjasgiYjXgdMqdTl8EDukjCT5mtzpvPCb1s09/BDwE7Fmvsxv7O4PyOBcsuz5v/Oy1+uhNtXNTP/GmSRIRuwG7UAYVX9BnMx57epGZTlNgorw+MYEjm5YfW5d/ZtR9dBr3Pv1A3XdXARt0Kfs0YEaL5fsAD9d25jatm1uXXwes37B8NrCo1pvdVOdVtc5lwBoNy58OLAHuANZtqvO+Wuf0xj4C+9flv2rVd6cJxc5OwNotls+mvL0igfc3LF+X8teYJcCchuVrUC6qEnhlU1tb1RhZ1BgnlAE8r6t19hhFzDlNWhwdUr/7szqU8dizkk+UgXoTOLXN+ml1fDGuhho7qwPfq2U+38v32hhjDctmNOy3Oydjn1LufEjgmKblb63Lz23RD6/Vhxc70+rc1E+8OfUfP01lT6xl39mlnMeeCU5RO6UVXERsQ7mA2xg4k/JK4t0oA5pdQzm4LhpdDzUeEXEYZfC6RymP2bV6E8HCzDy5ll9AuVXycspYLAA7A/Pr5w9k5v9psZ1jgH+udc4AVgNeAWxIOTgd31Q+KGMrvJQyyPlZtewrKP+JeElmntlUZ3VKtn4uJYl2AbAl5a+XS4H5mXlF1y9FPYuIoygD0V8C3AjcT3nt7wso++ls4MDMXNpQ5wBKDDwMfBW4G9iP8naOM4CXZ9MJISKOBD5JuSD7GmV/vhTYnHJCfFeLvg085jQ5IuJS4JnAfpl5VpsyC/DYs9Kpx4sD6o+bAs+l/CX30rrsrsZ//9Pp+GJcTcx4YiciTgIOB+4CPk35D1KzBdlwF0JEJGVogp9THp2aRfmL/pMpf9U/MDPPb+rTuPdpRGxIOe5tX+teSfmjz/6UZMPczPx9Ux2v1SdgnLGzgGl0buon3rS88Z63ap11gVuBVYDNs8P4Th57JsGoM19OvU/AFpRXqN9GCdYbgY/TkLV3mhoT5Y1j2WVa0FD+NcB3Ka/sfIDyV5abKBfre3XZ1uHAj4EHKQmKi4EXdii/CvAO4L8pt3veQ0lkzO1QZy3gQ5S7bZZQsv6nA3876u96Ok6UVwafRrkIuhf4c/3Ovw8cCuWPCi3q7Vn35T113/533dczO2zrRTVm7q8x9GPgsFHHnNOEY2inepz5Q5f977FnJZx6OEctbFFn2hxfjKvhxA6woEvZBI5qav8jdZ/fSkl0LqacC48Htp7MfQpsQHnxy42U6+7bKK9M37xDHa/VhxM70+7c1E+8OfUXPw11/qmuO62H9j32THDyjidJkiRJkiQNhIOLS5IkSZIkaSBMPEmSJEmSJGkgTDxJkiRJkiRpIEw8SZIkSZIkaSBMPEmSJEmSJGkgTDxJkiRJkiRpIEw8SZIkSZIkaSBMPEmSpBVSRCyIiIyIHHVfJEmS1J9VRt0BSZI0PUTEbOCGSWruiElqZ9qKiKPqx4WZefIIuyJJktSWiSdJkqSp6V/r/GLg5BH2Q5IkqS0TT5IkabLcARzYYf184Mj6+SLgkx3K/tS7eCRJkqY+E0+SJGlSZOZi4Nvt1kfEeg0/3pSZbctKkiRpenBwcUmSJEmSJA2EiSdJkrRC6vZWu4g4fGx9RBxel82JiFMi4oaIeCgiboyI0yLiyU11Z0bEqyPiwoi4LSIejohrIuLDEbFuj/1bLSJeExHfiYg/1DbujYhfRMQxdbD1bm08ISI+FBH/FRF3R8SfI+KeiLg2Ii6NiGMjYq+mOs3fybMavofGae+meutGxEERcWJE/Kz29c91uz+tfd6mhz4vrO0vrD+vERFvj4grImJRRPwpIn4SEW+JiNWa6m4dEZ+IiN9ExIN12+dFxLO7bPPkht9rdl12UET8oGH/LYyIz0fE33b7HSRJ0vBEpm8oliRJg1eTQyfVH0/JzMO7lF8APAsgM6NLe0cAjwM+RuuhBJYA+2fmeRGxDvA14PltNv1b4O8z884OfZsDfB3YqsOvsBR4a2ae0KaNFwBfrf3u5L7M/Otjiu0ScS3My8wFtc5qwJ+A1bvUeQR4e2Z+ql2BmnB6InAjsAfwPeCpbYqfR/nel0TE/sCXgbXblD0yM49vs82TgcPqjzsA/w4c0KadpcCbMvPEdr+DJEkaHsd4kiRJ08ELgRcDdwKfB34JrFmXvYCScPlaRGwFnEJJOl0GnA7cRkmkvLnOd6QksA5utaGI2AP4AbAWkJTkyvnALXWbewCH1PWfiYglzQOlR8TfsHzS6XvA94FbKXekbwzsAjwHmNXUhbEB3L9V578C/neLrv6y4fOM+h3cWrfzC+CPwF+ALYC5wH6Ua8PjI+LWzPwWna0KfIOSdDobOAu4m/L9HQk8Hngu8P6IOBs4A3gI+ARwVW3j+cCrgACOjYgLMvM3XbY7lnS6EfgC8Dtgg7psX2A14HMRcWdmfqdLW5IkacC840mSJA3FgO94ArgSeF5m3tNU7rPA6+qPPwF2Bd6XmR9uKrcxcDWwGfAosEVm3tZUZh1KomcL4F7ggMy8uEXftgUuALYEHgRmZ+ZdDevfBXyk/viezPyPNt9BAM/MzEtbrBu7iLs4M/duVb+h7ExKEuu8bHPxFxE7U5JomwLXA9tl5l9alFtISdBBSbwdmpmnNpXZjvJdrgXcR0kIAszPzD80lf0A8KH6439m5ptabPNklt3xBOWtiPtl5gNN5d4CHFd/vL3+DsuVkSRJw+UYT5IkaTpYCry8OelUHU1JkEBJOp3TnHQCyMw7gLFHvWYCrcYdeh0l6QQl4fKYpFNt6zrK439QHi17fVORbRs+f65VG7WdbJV0Gq/MfDQzz22XdKplfgG8v/64NeUuqG4+25x0qm1dC4wtn0X5fQ9qTjpVHwHur5+f28M27wNe2SqhVB/V+1r9cVPgoB7akyRJA2TiSZIkTQdnZeaNrVZk5i3AwoZFbccvAn7Y8LnVINWH1Pk1mXlWpw5l5oWUR9ugPALWaHHD5yd1amfILm/4vFsP5VuOyVRd1vD5qsy8slWhzHyYZY/ebRURa3TZ5qk1SdjOMQ2fD2xbSpIkDYVjPEmSpOngii7r/8iygcBbJkAayo1Zv3FFRMwCdh4rFxHtBrduNHZXzk5Ny78PvKN+/mZE/H/g9My8uYc2+1bfCHcYsDdlLKb1gHaJns27NPcg5bHDdhq/y07feWPZqH26vUPZC7q0dRVlIPV1gad3KStJkgbMxJMkSZoOFnVZv6THso3lmhMyW7DsbvG96tSr5ZJYmXlORHwFeDWwEXAsZXDtayl3HV0CfLfLnT3jEhFvBz5M9zfbjVm3y/q7Oz26R+/feXPZbnc8XddpZWZmRFwPPAXYICJWz8wlnepIkqTBMfEkSZKmg8cMgt1OqwGze9T8drnxWLXFsoOBCyl3Po09brddnQ4DHo2IrwPvbB7kfLwi4iDKm/rGXApcTHkE8X7KGFlQ3qZ3Qv08s0uz4/ke+/3OW1ncvQgPNnx+HMsntiRJ0hCZeJIkSepN42DWX8zMw9qW7EG9W+hE4MSI2Bp4JmVA7/mU5NNM4FXAMyPi6Zn5x7aNdfdvdf4I5W1w57QqFBEr0nhT7azVQ5m1Gz77VjtJkkbIwcUlSZJ6c0vD527jH41LZl6fmV/MzDdm5vaUt+/9rK7eAnh3v23XpNbY+Fbfbpd0qp7Y73aGaNtOKyMiKG/lg/I4oHc7SZI0QiaeJEmSepCZdwG/rj/uHhHdxkCayLZ+yrI36EG5G+oxxeo8ujS3ScPn33cp+9wu61cE87us35Vl41P9eMB9kSRJXZh4kiRJ6t0pdb4W8N4Bb2thw+dWwyOMPUK2dot1jRrHRNqmXaGI2AI4oqeejdbBEbFRh/X/3PD5m4PujCRJ6szEkyRJUu8+BdxYP783It4dEW2vpyJiVkS8NSKe3bT8gxHxnE51gTc1fP55i/U31PmOEbFmh3Z+w7LBtvePiGe06OcmwLeBdTq0s6JYDzgtIh6TcIuIN1LGxQK4HfjKMDsmSZIey8HFJUmSepSZD0bEAZQ3wq0L/Afwhoj4BuUxvAfq8q2BZwB7A6ux/GNzUB4XOxq4PSLOA66mJEpmAE8A9gP2qmWXAMe26M4FwM6UO57OiohTgLtY9gjelZl5d2YujYgTKHcCrQpcEhFfoDyG9mfgaZQ7ndYDvggc2teXMzzfBg4AfhkRJwLXUvp+IMseFUzgDZnpwOKSJI2YiSdJkqRxyMyr611DpwFPpTy+9r86VFlCSQgt10ydbwocVqdW7gIOysxftVh3DHAwsBGwT50azQMW1M//Uvs6D1gd+Kc6NTqBkkhb0RNP76F8fwey7G19jZYCb87M7wy1V5IkqSUTT5IkSeOUmb+LiF2BFwEvBvagJJHWBu6nPI73c+BC4DuZeU9TE/sBzwaeRRkMe1tgQ0pC5W7gV8A5wImZeW+bPtwSEU8D3kVJOs2u23/MYOOZ+XBE7Au8jnL31ZMpd2LdDlxRt3N+RMwe/7cxdEsz88URcRDlTq0nA+tTfpcfAMdk5q87NSBJkoYnMrN7KUmSJGlEIuJklt0VtlVmLhxdbyRJ0ng4uLgkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsK32kmSJEmSJGkgvONJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkD8T8LpXtnoHpMJQAAAABJRU5ErkJggg==\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 634
-        },
-        "id": "Gkd5ecCmL6Bw",
-        "outputId": "a6c042dc-999a-456c-b233-a1e05612e15f"
-      },
-      "source": [
-        "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
-        "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=30);"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 624
-        },
-        "id": "EycZrQU0MBSX",
-        "outputId": "6f325187-ee1b-4122-97f7-80ffdbf149d2"
-      },
-      "source": [
-        "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
-        "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
-        "plt.xlabel('Year', fontsize=20); "
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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+lOTEJCesu7goikFZEy6tTnJ4WZafKMvyoiSjkjyS5KSiKD7SgZ8DAAAAqKKxY8dm2rRpefnll5Mkr7zySp555plN3jd//vzssssuOe+883L88cdn5syZOeeccyqh07Bhw9a7/qCDDsrtt69ZY3Lrrbfm0EMPTZK89tpreec735kk+fd///fK9WPGjMltt615Wve9996bV199tVkN64KhbbfdNkuXLl2v+fa73/3u9OzZM9/4xjcyfvz4JMluu+2W+fPnV1b5rFt5VC9a1eC6LMv7N3D8xaIork1yeZLDs2a1UZKclGRokpvKsmz4q+uXF0VxcZLpSc6OFUZbrDdWvJGt+2xd6zIAAAC2LBtpPl1te+yxRyZNmpSjjjoqTU1N6d27d66++upN3nfHHXfk5ptvTu/evbP99tvny1/+8kav/973vpcJEybkyiuvrDS4TpJLL700J598cgYPHpwjjjii0mfokksuyamnnpqRI0fmoIMOyk477VQZ6+ijj84PfvCDDBs2LGeddVb23HPPbL/99tl///3Xm3P8+PG56KKLKmP2798/11xzTcaNG5cBAwY0u/7tXnzxxYwePTqvv/56evToke985zt54oknMmjQoE1+f7qior1Ll4qiuCjJt5N8pyzLz609dkuSjyY5rSzL//W263sleS1rtqQNLMvyLxsbf/To0WVDQ8PGLqEK9vr3vdp1//eO+F4O3/HwjikGAACgzs2dOze77757rcuoK0uXLs3AgQNTlmXOOeec7Lrrrvnc5z5X67I2S0s/P0VRzCjLcnRL17fraWhrg59/Wvv2Z391are1r398+z1lWa5K8nTWrGrapT3zAwAAAFTDDTfckFGjRmXkyJF57bXX8ulPf7rWJXWaVm1D24hvZU2T63vKsvz5Xx3fZu3rhtbHrTv+Ny2dLIriU0k+lWS95WMAAAAAneFzn/tcs5VEN954Y7773e+ud+zggw9ucTvekiVLMnbs2GbHp0+fniFDhnRssR1ss8OioijOS/L5JE8m+ViHVZSkLMvrk1yfrNmG1pFjAwAAAGyOCRMmZMKECa26dsiQIWlsbKxyRdWxWdvQiqI4N8l3kzyR5O/KsnzlbZesWzm0TVq27vifN2d+qqvaj+ADAAAAuq42h0VFUVyQ5HtJZmdNUPRiC5fNW/v6nhbu75Vk5ySrksxv6/xU39KVS2tdAgAAAFAjbQqLiqL4YpL/maQxa4Kilzdw6f1rX8e1cG5Mkq2S/HZTT0KjNspYWQQAAAD1qtVhUVEUX82ahtYzkowty3LxRi6flmRxko8URVF5DFtRFP2STFr79l/bXi4AAAAA1dSqsKgoijOSfD3J6iQPJjmvKIpL3/bn4+uuL8vy9SRnJemZ5FdFUfygKIpvZ82KpAOzJkya2rEfhY7SET2LihQdUAkAAABd3YgRI7J48Zr1JAMHDkySPP/88znppJNqWVa7fPKTn8wTTzyRJLniiitqXE3na+3T0HZe+9ozyQUbuObXSaase1OW5V1FURyW5CtJTkzSL8lTSS5MMrnURRkAAAC2SMOGDcu0adNqXcZm+8EPflD5+oorrsiXv/zlqs21atWq9Oq12Q+rr4pWVVOW5aVJLm3r4GVZPpzk6LbeBwAAADS317/vVfU5Zp0xa4PnbrnllkyePDkrVqzIAQcckGuuuabF6xYsWJBjjz02s2fPzpw5czJhwoSsWLEiTU1NufPOO7Prrruud/3SpUszceLENDQ0pCiKXHLJJTnxxBMzcODAnHXWWfnFL36R7bffPrfffnuGDh2aww8/PFdddVVGjx6dxYsXZ/To0VmwYMF6Y1555ZXp27dvzjvvvHzuc5/L448/nvvvvz/3339/fvjDH+bWW2/N2WefnUcffTTLli3LSSedlMsuuyxJKuNPmzYty5Yty6hRozJy5MjceuutLX7WcePGZb/99stjjz2WkSNH5qabbspWW22VGTNm5MILL8zSpUuz7bbbZsqUKdlhhx1y+OGHZ9SoUXnooYdy6qmnZsyYMTn//PPz5ptvpm/fvpk+fXq23nrrNv7NdZw2Pw2NLd+yVctqXQIAAABdzNy5czN16tQ8/PDDaWxsTM+ePVsMT97u2muvzfnnn5/GxsY0NDRk+PDhza75xje+kW222SazZs3KzJkzc8QRRyRJ3nzzzYwePTpz5szJYYcdVglzWuPQQw/Ngw8+mCRpaGjI0qVLs3Llyjz44IMZM2ZMkuTyyy9PQ0NDZs6cmV//+teZOXPmemN861vfSv/+/dPY2LjRzzpv3rx89rOfzdy5czNo0KBcc801WblyZSZOnJhp06ZlxowZOfPMM/OVr3ylcs+KFSvS0NCQiRMnZvz48fnud7+bxx9/PPfdd1/69+/f6s9ZDV1rnRNdwi+f+WWtSwAAAKCLmT59embMmJH9998/SbJs2bJst912m7zvwAMPzOWXX56FCxfmhBNOaLaqKEnuu+++3H777ZX3gwcPTpL06NEj48ePT5KcfvrpOeGEE1pd73777ZcZM2bk9ddfT9++ffO+970vDQ0NefDBBzN58uQkyR133JHrr78+q1atygsvvJAnnngie++9d6vnWGfHHXfMwQcfXKlz8uTJGTduXGbPnp0jjzwySbJ69erssMMOlXvWfa558+Zlhx12qHxfBw0a1Ob5O5qwiGaWrlxa6xIAAADoYsqyzBlnnJFvfvOb6x2fMmXKRu877bTTcsABB+Tuu+/O0Ucfneuuuy5z587NDTfckCS55557Wl1DUax5mFKvXr3S1NSUJFm+fHmL1/bu3Ts777xzpkyZkoMOOih77713HnjggTz11FPZfffd8/TTT+eqq67Ko48+msGDB+fjH//4BsdqbV1//b4sy4wcOTKPPPJIi/cMGDBgs+bqDLah0YwnmQEAAPB2Y8eOzbRp0/Lyyy8nSV555ZU888wzm7xv/vz52WWXXXLeeefl+OOPz8yZM3POOeeksbExjY2NGTZsWI488shcffXVlXteffXVJElTU1OlUfZtt92WQw45JMmaJ7DNmDEjSTbaSPvQQw/NVVddlTFjxuTQQw/Ntddem3333TdFUeT111/PgAEDss022+Sll17Kvffe2+IYvXv3zsqVKzf6GZ999tlKKLSuzt122y2LFi2qHF+5cmXmzJnT7N7ddtstL7zwQh599NEkyRtvvJFVq1ZtdL5qs7KIZoRFAAAAXdPGmk9X2x577JFJkyblqKOOSlNTU3r37r1ewLMhd9xxR26++eb07t0722+/fYtPFrv44otzzjnnZM8990zPnj1zySWX5IQTTsiAAQPy+9//PpMmTcp2222XqVOnJkm+8IUv5JRTTsn111+fY445pjLO888/n09+8pOV1UqHHnpoLr/88hx44IEZMGBA+vXrl0MPPTRJss8++2TffffNe9/73vW2kb3dpz71qey999553/vet8G+RbvttluuvvrqnHnmmdljjz1y9tlnp0+fPpk2bVrOO++8vPbaa1m1alUuuOCCjBw5cr17+/Tpk6lTp2bixIlZtmxZ+vfvn/vuuy8DBw7c5Pe2Woqu/gT70aNHlw0NDbUuo65c9/h1+X7j99s1xveP+H4O2/GwDqoIAACgvs2dOze77757rcvodAMHDszSpV27VcpfP/mtq2rp56coihllWY5u6Xrb0AAAAACosA2NZnoUMkQAAABqryutKlqyZEnGjh3b7Pj06dO79KqizSEsopm3d3EHAACAejdkyJA0NjbWuoxOYQkJAAAAdANdvecwXdPm/NwIiwAAAKCL69evX5YsWSIwok3KssySJUvSr1+/Nt1nGxpVMf+1+Z6GBgAA0EGGDx+ehQsXZtGiRbUuhW6mX79+GT58eJvuERZRFb985peZsOeEWpcBAACwRejdu3d23nnnWpdBnbANjWaKtL/BtSeqAQAAQPfkN3qaKdP+PbA9i54dUAkAAADQ2YRFVIWVRQAAANA9+Y2eqtim7za1LgEAAADYDMIimumInkWH73h4+wsBAAAAOp2wiGaKov1hUd+efTugEgAAAKCzCYtopizb3+AaAAAA6J6ERVSFBtcAAADQPfmNnqroiL5HAAAAQOcTFtHMroN3bfcYHdH3CAAAAOh8wiKaGdh7YLvH6OFHCwAAALolv9FTHRYWAQAAQLckLKIq9CwCAACA7klYRFUIiwAAAKB7EhZRFT0KP1oAAADQHfmNnmbKlO0ew9PQAAAAoHsSFgEAAABQISyiKvQsAgAAgO5JWERV6FkEAAAA3ZPf6GmmLDugZ5GVRQAAANAtCYuoDlkRAAAAdEvCIgAAAAAqhEUAAAAAVAiLaLN/GPEPtS4BAAAAqBJhEc2U2XiD67NHnb3pp521v0c2AAAAUAPCIjbLBe+7oNYlAAAAAFUgLGKzHPfu4zK47+BalwEAAAB0MGERbbZN320ypP+QTBk3JeN3G1/rcgAAAIAOJCyizd7R7x1Jkl3+Zpdc/IGLc+AOBza7ZlN9jwAAAICuSVhEuxVFUesSAAAAgA4iLKJNNLYGAACALZuwiDY5bffTal0CAAAAUEXCItqkf6/+tS4BAAAAqCJhEc2UZcvNqU/c9cTWj6HBNQAAAHRLwiLarYgG1wAAALClEBbRap56BgAAAFs+YREAAAAAFcIimtlQv6Hj331868fYQN8jAAAAoGsTFtFqew/du+UTdqcBAADAFkNYRKuMHDIyPQo/LgAAALCl89s/rTKg94BalwAAAAB0AmERAAAAABXCIprZUINrAAAAYMsnLKJVCl2sAQAAoC4IiwAAAACoEBYBAAAAUCEsopmybH/PIn2PAAAAoHsSFtE6G2lZpJ8RAAAAbDmERQAAAABUCIsAAAAAqBAWAQAAAFAhLKIZzakBAACgfgmLaBVNrAEAAKA+CIsAAAAAqBAWAQAAAFAhLKI5LYsAAACgbgmLaBU9iwAAAKA+CItoN0ESAAAAbDmERQAAAABUCIsAAAAAqBAW0UypwzUAAADULWERrVIU+hIBAABAPRAWAQAAAFAhLAIAAACgQlhEM3oWAQAAQP0SFtEqRdrWs6gsBU4AAADQHQmLaDfNrwEAAGDLISwCAAAAoEJYBAAAAECFsIhm9BsCAACA+iUsonW0JQIAAIC6ICwCAAAAoEJYBAAAAECFsIhmyuhZBAAAAPVKWESrFJoWAQAAQF0QFlEVVicBAABA9yQsot2sOgIAAIAth7AIAAAAgAphEQAAAAAVwiKaKcvm/Yb0IAIAAID6ICyimccXPd7s2MPPPVyDSgAAAIDOJiyimRtm3VDrEgAAAIAaERaxnpa2oAEAAAD1Q1jEeua/Nr/WJQAAAAA1JCxiPf82+99qXQIAAABQQ8Ii1nPfM/d1yDi2swEAAED3JCxiPW+teqvN9xQpqlAJAAAAUAvCIgAAAAAqhEUAAAAAVAiLAAAAAKgQFgEAAABQ0avWBdAxVjatzPce+15++/xv857B78lF+1+Uwf0G17osAAAAoJsRFm0hvjPjO7npiZuSJPNenZcX3nwhN467scZVAQAAAN1Nq7ehFUVxUlEU3yuK4sGiKF4viqIsiuKWDVw7Yu35Df25veM+AkkqQdE6DS81ZNFbi2pUDQAAANBdtWVl0cVJ9kmyNMnCJO9txT2PJ7mrheOz2zAvm2nRskUZutXQmsxdpqzJvAAAAED7tCUs+lzWhERPJTksyQOtuKexLMtLN6MuupOi1gUAAAAAHaXVYVFZlpVwqCikAwAAAABbomo3uB5WFMWnkwxJsiTJI2VZzqzynF1WU9mUHkWr20S1W2HJDwAAANBG1Q6Ljlz7p6Ioil8lOaMsy2erPHeXsbJpZU7+8cn5r9f+K0nynb/7TsbuNLbGVQEAAAA0V61lLm8l+UaS/ZIMXvtnXZ+jw5NML4piwIZuLoriU0VRNBRF0bBoUfd/ote508+tBEVJcsEDF+StlW9VfV7bBQEAAIC2qkpYVJbly2VZfq0sy8fKsvzz2j+/SXJUkv9M8t+SfHIj919fluXosixHDx1am6d5daTfPv/bZse+3/j9qs9rGxoAAADQVp3XQCdJWZarkvxg7dsxnTl3V3PzEzfXugQAAACAZqrdswLfWKoAACAASURBVKgl6/aVbXAbGtX3zOvP5O75d6dvz7457t3HZehW3X8FFwAAANB+tQiLPrD2dX4N5q4rG+pZ9Kc3/pTT7zk9f/7Ln5MkP/o/P8rtx96erftsnZ5Fz6wuV3dmmQAAAEAXUpVtaEVRvK8omj8jviiKsUk+t/btLdWYm0278493VoKiJHn2jWdz3zP3JUl6NP9r2yxlyg4ZBwAAAOhcrV5ZVBTFh5J8aO3b7de+HlgUxZS1Xy8uy/ILa7/+lyS7FkXx2yQL1x7bO8kRa7/+almWzbs+16lXl7+aix++OH946Q/Za+hemXTwpA7ZFrahBtc/nP3DZseun3l9Przrh9OrR6+sbFrZIfMAAAAA3U9btqGNSnLG247tsvZPkjyTZF1YdHOSDyfZP8k/JOmd5KUkdyT5flmWD25uwVuSyY9Nzk6DdsrPF/w8Dz33UJI1T077ykNfyfVHXd+qMV5686VcN/O6DqvpnQPfmaf+/FSHjQcAAAB0L60Oi8qyvDTJpa289odJmi9fYT03zLqhxeOPvPBIVjWtSq8evVKWZea9Oi8vLH0h+22/Xwb1GVS5rqlsyt9P+/sNjr85K372GbqPsAgAAADqWC0aXNMKq8vV6ZVeuarhqtz0xE1JkqH9h+bGcTfmXYPelSS566m7NjrGhhpcd/Q9AAAAwJajKg2uab+yLDNn8ZxKUJQki5Ytys1P3Fx5f8lvL+mw+YREAAAAQCIs6rI+eOcH85G7P9Ls+NR5U1s9xof+94fypQe/lMXLFufh5x7OvFfmpSxbfkrZuuMbOg8AAADUB9vQuqhXlr+ywXO/Wfib7DN0n1aNc/f8u3P3/Lsr78fvNr7dtQEAAABbLmFRN3TO9HM2+94NrUyyDQ0AAABIbEOjWuxmAwAAgG5JWES7FbEqCQAAALYUwiIAAAAAKoRFtMrROx9d6xIAAACATiAsolXOGHlGrUsAAAAAOoGwqMr+svovtS6h3U5+z8nZY8getS4DAAAA6ATCoiq78tEra11Cu+0+ZPdalwAAAAB0EmFRlU2dN7XWJbTKxp5o5mlnAAAAUD+ERQAAAABUCItIkixdubTWJQAAAABdgLCIJMkry1/p0PHKlB06HgAAANA5hEW0W1HoaQQAAABbCmERAAAAABXCIgAAAAAqhEUAAAAAVAiLWI/G1AAAAFDfhEVsUhENrAEAAKBeCIsAAAAAqBAWAQAAAFAhLKIq9D4CAACA7klYRLvpaQQAAABbDmERAAAAABXCIgAAAAAqhEUAAAAAVAiLWE9ZakwNAAAA9UxYxCYVhQbWAAAAUC+ERQAAAABUCIsAAAAAqBAWAQAAAFAhLKIqNMoGAACA7klYRLtpgA0AAABbDmERAAAAABXCItZTxvYxAAAAqGfCIjapiG1mAAAAUC+ERQAAAABUCIsAAAAAqBAWAQAAAFAhLAIAAACgQlhEVXiqGgAAAHRPwiIAAAAAKoRFAAAAAFQIi1hPWdo+BgAAAPVMWAQAAABAhbAIAAAAgAphEQAAAAAVwiIAAAAAKoRFAAAAAFQIiwAAAACoEBZRFWXKWpcAAAAAbAZhEe1WpKh1CQAAAEAHERaxHiuCAAAAoL4Ji9ikorByCAAAAOqFsAgAAACACmERAAAAABXCIgAAAAAqhEUAAAAAVAiLAAAAAKgQFlEdZa0LAAAAADaHsAgAAACACmER7VYURa1LAAAAADqIsIhNKiIMAgAAgHohLAIAAACgQlgEAAAAQIWwCAAAAIAKYREAAAAAFcIiAAAAACqERQAAAABUCIuoijJlrUsAAAAANoOwiCTJkH5DkiRl2faQp0jR0eUAAAAANSIsIkly9C5Hb/BcUQiDAAAAoF4Ii0iS9O/Vv9YlAAAAAF2AsAgAAACACmERSTavVxEAAACw5REWAQAAAFAhLAIAAACgQlgEAAAAQIWwiCRJGT2LAAAAAGFR1Z38npNrXUKbdFRopGE2AAAAdE/Coir7yHs/kkF9BtW6jE3aWLhTpNjovZs6DwAAAHQfwqIqe8/g9+RHx/0oXz/o67UuBQAAAGCThEWd4G8H/G0+vOuHc/Y+Z9e6lA3SswgAAABIhEWdaocBO9S6BAAAAICNEhZ1ov69+9e6hA2ysggAAABIhEWd6vDhh6dPjz61LgMAAABgg4RFnahfr3754vu/WOsyWmZhEQAAABBhUac7ZbdT8qtTflXrMgAAAABaJCyqgSH9h+TIdx3ZIWN9/aCvd8g463oWdVTvIj2QAAAAoHsSFtXIJ/b8RK1L6DhFrQsAAAAAOoqwqEaGbz28Q8bZYeAOHTJOWVoJBAAAAAiLaqYoOmY5zsDeAztkHAAAAIBEWFQzg/oM6pBxihSZuO/Edo+jxxAAAACQCItq6srDrmz3GFv13ip9evTpgGoAAAAAhEU1NW7EuMz8p5m5+8N3b/YYIwaNyLv/5t3trsXKIgAAACARFtVcURTZadBOm3XvFYdckaIoctCwgzq4KgAAAKBe9ap1AbTezf9wc97R7x2ZvXh2DtvxsAzoPSBJ0rNHz3aPve5paJ6KBgAAAPXNyqIu4txR5270/Na9t86e2+6ZnQbtlKN3OboSFHWGjnpyGwAAAND1CYu6iE/t/akcs8sxGzx/wX4XpFePDS8EO2LHI6pR1mbTAwkAAAC6J9vQuoiiKHLFIVfkxTdfzIyXZlSOnzPqnBy7y7EZvvXwjd6/uX2P1mlPuFPEyiMAAADYUgiLupAeRY9cM/aa/GzBz7J42eL8/U5/n13+ZpdOmftnT/8sX3r/lzplLgAAAKDrEhZ1MVv13ion7HpCm+87YIcDMmXOlM2ed8nyJZt9LwAAALDlaFXPoqIoTiqK4ntFUTxYFMXrRVGURVHcsol7DiqK4p6iKF4pimJZURQzi6K4oCiK9j+6i2Y+sMMHsuPWO7Z7nLdWvdUB1QAAAADdVWsbXF+c5Nwko5I8t6mLi6I4PslvkoxJ8h9Jvp+kT5L/meT2zaqUjerVo1d+eNQPc/J7Ts6Y4WPyzUO/uVnj/OpPv+rYwgAAAIBupbXb0D6XZGGSp5IcluSBDV1YFMWgJDckWZ3k8LIsG9Ye/2qS+5OcVBTFR8qyFBp1sB0G7pCvHfi1yvsbZt6Q+a/Nb/X9r/3ltWqUBQAAAHQjrVpZVJblA2VZ/p+yLFvzyKyTkgxNcvu6oGjtGMuzZoVSkpzd5kpps4+P/Hibrn/xzRerUwgAAADQbbR2G1pbHLH29WctnPtNkreSHFQURd8qzM1fGdRnUIeMU6TokHEAAACArq8aYdFua1//+PYTZVmuSvJ01mx/65xnwlMTrVuEBgAAAHQ11QiLtln7uqEGOOuO/00V5uavddKCoKKw8ggAAAC2FNUIi9qtKIpPFUXRUBRFw6JFi2pdTrf17m3e3abrhT4AAABANcKidSuHttnA+XXH/7yhAcqyvL4sy9FlWY4eOnRohxZXT0ZsMyJ7D917vWPnv+/8GlUDAAAAdAfVCIvmrX19z9tPFEXRK8nOSVYlaf0z3dls3zviezlh1xOy73b75vz3nZ8z9zyz1iUBAAAAXVivKox5f5KPJhmX5H+97dyYJFsl+U1Zln+pwty8zTv6vSOXHXRZq6711DMAAACgGiuLpiVZnOQjRVGMXnewKIp+SSatffuvVZiXdnrouYdqXQIAAABQY61aWVQUxYeSfGjt2+3Xvh5YFMWUtV8vLsvyC0lSluXrRVGclTWh0a+Korg9yStJjkuy29rjUzumfDrSv8z4l1qXAAAAANRYa7ehjUpyxtuO7bL2T5I8k+QL606UZXlXURSHJflKkhOT9EvyVJILk0wuy7JsT9F0LtvTAAAAoH60Kiwqy/LSJJe2ZeCyLB9OcnTbSwIAAACgVqrRswgAAACAbkpYRLvZpgYAAABbDmERAAAAABXCIgAAAAAqhEUAAAAAVAiL6lD/Xv1rXQIAAADQRQmL6tCEPSfUugQAAACgixIW1aGdB+3cpuuLwtPOAAAAoF4IiwAAAACoEBbVoVeWv1L1OcqUVZ8DAAAA6HjCojp079P3tun61/7y2kbPF7FNDQAAALYUwqI61JSmNl1/11N3VakSAAAAoKsRFrFJm1pZBAAAAGw5hEV1qK3bxpatWlalSgAAAICuRljEJi1ZvqTWJQAAAACdRFgEAAAAQIWwqA55ehkAAACwIcKiOrSiaUWtSwAAAAC6KGFRHXpiyRO1LgEAAADoooRFVEVZlrUuAQAAANgMwiLarSj0QAIAAIAthbAIAAAAgAphEQAAAAAVwiIAAAAAKoRFAAAAAFQIiwAAAACoEBYBAAAAUCEsqkN7DNmj1iUAAAAAXZSwqA4VKao+R5my6nMAAAAAHU9YVIc6IywCAAAAuidhUR2y6gcAAADYEGFRHbKyCAAAANgQYVEdKgphEQAAANAyYVEdKkvb0AAAAICWCYvqUFtXFg0fOLxKlQAAAABdjbCoDrU1LOpR+DEBAACAeiEFqEdt3IXWp2ef6tQBAAAAdDnCojr00lsvten6PYbsUaVKAAAAgK5GWFSHtttquzZd369nvzbPoYk2AAAAdE/CojrU1h5Em9qGVqRtPZAAAACArktYxCaVbW1yBAAAAHRbwqI61NaVQLaUAQAAQP0QFrFJVhYBAABA/RAW1aG2hj9WFgEAAED9EBbVoTZvQ7OyCAAAAOqGsIhNsrIIAAAA6oewqA61eRualUUAAABQN4RFbFJT2VTrEgAAAIBOIiyqQ23tWQQAAADUD2ERm7SpbWhFIXwCAACALYWwiE3S4BoAAADqh7CITdLgGgAAAOqHsIhNGjN8TK1LAAAAADqJsIhNOmz4YbUuAQAAAOgkwiI2qU/PPrUuAQAAAOgkwqI6tOvgXWtdAgAAANBFCYvq0AdHfLDWJQAAAABdlLCoDvXr1a/qc3iCGgAAAHRPwqI6VKTo0uMBAAAAtSMsqkNW/QAAAAAbIiwCAAAAoEJYVIdsGwMAAAA2RFgEAAAAQIWwqA6tLlfXugQAAACgixIW1aHZi2e3+tpLD7y0eoUAAAAAXY6wqA717tG71deOGT6mipUAAAAAXY2wqA7tNXSvVl+7Ve+tqlgJAAAA0NUIi+pQr6JXq6/d3CenlWW5WfcBAAAAtSUsqkPbbbVdh45XFJsXKAEAAABdj7CoDg3uN7jWJQAAAABdlLCIjbJqCAAAAOqLsIiN2tyeRQAAAED3JCxio6wsAgAAgPoiLGKjrCwCAACA+iIsYqOERQAAAFBfhEV16oRdT6h1CQAAAEAXJCyqUxfud2HrLtzMhUVlys27EQAAAKgpYVGd2qbvNvnJh37SIWPZqgYAAABbDmFRHRuxzYj84KgfZLv+223wml5Fr06sCAAAAKg1YVGdO2CHA3Lfyfe1eO74dx+forBqCAAAAOqJsIgURZHP7POZZse/cfA3alANAAAAUEv2GJEk+fTen85bK9/Krxf+Ou8a9K586f1fsqoIAAAA6pCwiCRJrx69ctH+F+Wi/S+qdSkAAABADdmGBgAAAECFsAgAAACACmERAAAAABXCIqqiTFnrEgAAAIDNICwCAAAAoEJYBAAAAECFsAgAAACACmERAAAAABXCIgAAAAAqhEUAAAAAVAiLAAAAAKgQFgEAAABQISyiKsqyrHUJAAAAwGYQFtFuRVHUugQAAACggwiLAAAAAKgQFgEAAABQISwCAAAAoEJYBAAAAECFsAgAAACACmERAAAAABXCIgAAAAAqhEUAAAAAVAiLAAAAYAvz57dW5Hfzl2TpX1bVuhS6oV7VHLwoigVJ3rWB0y+VZbl9NeencxQpal0CAAAAa/1izos557bHsnJ1mQF9euamT7w/+73rHbUui26kqmHRWq8l+U4Lx5d2wtwAAABQN8qyzGU/eSIrV5dJkjdXrM4/3zsvd3zmwBpXRnfSGWHRn8uyvLQT5gEAAIC6tuiNv+S5Py9b79jvF7xSo2rorvQsAgAAgC3ES6//pdYlsAXojJVFfYuiOD3JTkneTDIzyW/KslzdCXMDQLv8/ulX8uSLr+eAnYdkt+23rnU5AAAb9aM/LKx1CWwBOiMs2j7JzW879nRRFBPKsvx1J8wPAJvl6geeypU/n5ck6dmjyLWn75cj9/jbGlcFALBhNz68oNYlsAWo9ja0G5OMzZrAaECSvZJcl2REknuLotinpZuKovhUURQNRVE0LFq0qMolAkBzK1c35V9/9V+V96ubylz36//ayB1dV1mWeerlpfnTK2/VuhQAALqBqq4sKsvysrcdmp3kM0VRLE3y+SSXJvlwC/ddn+T6JBk9enRZzRoBoCVPvvBGlv5l1XrHGp55tUbVbL7lK1fn7Ftm5IF5a/7nywnve2euPGmf9OxR1LgyAAC6qlo1uL527euYGs1PlZWljA+gK/jZ7BcrQVGS/Oix5/Kf85fUsCIAALq6WoVF6/7VOqBG89OBivi/07ClWrGqqdYl0E7//Uezmh375r1P1qASAAC6i85ocN2SD6x9nV+j+YG3aWoq8/sFr2Thq8tyyH/bNttv06/WJVFDd/3huVwwtbHy/sH/7++y4zu2qmFFbK5lK5s/fPSF15bXoBLoesqyTFMZ2zIB4G2qFhYVRbF7kmfLsnzzbcdHJPn+2re3VGt+6CxlWeaHDz2de2a9kJ3esVUuGvfevPNv+te6rDb72o9n55bfPZsk2bpfr/yvsz6QPd+5TY2rohbKslwvKEqSQ7/9QBZ865gaVUTHs1UYfjb7xUy6+4n8+a2VOWm/4fnqsXsIjUhTU5kefg4AqroNbXySF4uiuLsoimuKovjnoiimJZmb5L8luSfJVVWcHzrFzb97JpPunpvHnv1z7mp8Ph/7wX92u55NL7+xvBIUJckby1d55GY7NTV1r5+Bv3bf3JdrXQJV1o1/PKFDLF76l5x722NZ+OqyLP3Lqkz57YJMffRPtS6LGnr4qcU54qpfZc9Lf54vTpuZlau77zbs7vxvEKDrqGZY9ECSnyZ5d5LTklyY5LAkDyU5I8mxZVmuqOL81InfPrU4l/1kTm56ZEGWt7Ddotq+9r/nrPd+/uI3u90Tk+76w3PNjt352MIaVNL9rW4qc9lP5mSfy36RMd9+IPc98VKtS2qz3j39H9Ut3Stv+s8v9e3W3z2bVW/7hfrL/9G8v1d38Lv5S/L1nzyRGx9+OstWdP6/g7YEy1aszif/vSHzF7+Zt1b8X/buO76psosD+C/p3hPKKFD2EChbtqioCO6FyqviFl8njhfFgaLiBgVBhsoQBGTPMgsFSindg+6998oe975/hKZNM5qdND3fz8eP5Obemydpcsd5znMeOfbEleCPywW2bpbBGIbFymM3EP6l4hrkVHqlrZtE7ExX69AmtmWxYWgsy14EcNFS+ycEACLSKrBkZwJaj3uXc2qx6dlJtm0UgPSyJkwOC7R1M/TWhTvP7M7u68XKrKwWsQxLdsbj2sdzEejlatuGGcDDxcnWTSCEEIvKqmq2dRPM4lxGFV7eHqfMFryQVYNtL0yxbaO6oKPJ5Wr13b49mYnXbhtsoxYZZ2+7IFeLSIb/7kxAzMd3ItjbzcYtI/YiubQJ4/r527oZpIuw1WxohJjFmrM5aB8gP32jCmWNQts1qItiqX6J2Sw/mKbyWCpn8U9ssZa17ROHY77MopJ6AZqEUrPtjxBCzMFROtd/PZejMqz0YnYN8mt4tmtQF5VX6xif2bIOs1/KGBb/XOta1yDEstaczbZ1E0gXQsEi0qVlVraoLbuaV2eDlhCinabvqT0zR4qyQCLDoi0xmPV9JMZ/eRprz+WYoWXGYVnW5mnX1c0iGvpFCDG75NImtWUXsmps0BJirzIqHSOLjphHRSPNhkr0Z7FhaIQQQrqvXdeKcSVXEbhlWOCnM9m4P7wPwoK9rNqOjRfz8MflAri5cPHOncPw6MRQq76+VM7gvb3JOJJcDgB4btoArHjgFrNmbxnDz8PFpq9PCCHEOjiw/vkmv4aHdedzUcMT47GJoXhwXF+rt4FoRqMJiCEos4hYBB2ICOm6zBHI+Op4htoyaxcLvZBVjVUnM1HdIkZJvRDv70tGdpV1s7xOpFYoA0UAsO1qEWLy663aBk1sHKsixOYcZRgaIZ2y8vFeJJXjyU0xOJBYhks5tXh7dxLOdMHJPhwVHfuIIShYRExm6x5yYjo6cZD2LDVkq7LZuqnPq05kqjxmWWBzVL7e25sj6P327iS1ZU9tjjF5v6aiozYhhLSxRfaNtVj7nZ1Kr0R1i1hl2fcRmVrWJtZGl/zEEDQMjRAL6AoBtITiBjQLpbh1YJBB29W0iDH567MAFFOsn39vDvoFelqiiXqTyRlsuJCHmII6jO7rh3fuHAYPV/PO6JVd1YKXtsWhrFGIHx8fi4fH6z+cyf6/DdZh7c8hS0MW0bUC22f1EEKIJXWBSxDiwC5mq9fMyqnuegXEZXIGh5PKkVfDw5zhPTFlYNeZ5VgXhnqIiQEoWESIkViWRbNQpvU5e7b8YCp23pwdY1APL0wfrH/AaN6aKOW/pXIWs76PxLn3bsPgHt5mb6e+vj2ZiS03hzhdya1DXGED9i+Z3ul2fLEM1wrqEODpivBQf3C5mq+wm4RS3L267X2/uycZTlwuHgjvo1f7On4bWl/X/+brOml5XUdjDzcwxfUCvL07EaseGQNPV92nQEfuaSbGkcoZ/BaZi/iiBozv54//3jEEbs7mDUwTQqyPyieQjpYdSMW++FIAwIaLeVj/9ATcO6a3jVtlOju/RSF2hoJFhBihRSTFoxuikV3VNXpKWkRSLNufiui8Wvi4u6C4XqB8Lr+Gj9IGoV77kTMs6jTM6HTnTxdR+O0Cs7XXUFs61MKJL2oAXyyDl5v2Q1xVswgLN15FYZ3is3h4fF/8/ES4xqywr47dUFv21j+JegeL2qtuFmHhphgU1PIBAA+E98GaheO0Bqo0EcvkOJxUjtJ6AeaOCsHYUH+D22GMsGXH4e/pgoWT+uF/80YY1GbAssEXvliGX8/nIKOiBTOHBOGlmYO0rns4qRw+7s746qExKsslMgYf7kvGoaRyvHbbYMwf08ti7bW1rpD9aC0iqRyn0ivh7+mKGYOD4OykfYT+50fSsetmoP1STi0K6gRY+9R4azXVodwob8aWS/kQSuVYdOsAzBwabOsmEeKQ6HhvuEaBRBkoAhQBlg/2pSiDRUV1fGRUtGBCf3/09HW3WrtiC+qx+3oxZgwOxkPj+xrV2WjvHdrEvlCwiDgcaxwEvz2ZqTNQZKsTM8uyqGgSoZevu8qN/OdH0nE8tQIA0CCQqm0nkTF67T+/Rvt7ji2ox9hQP7i72Ecv+6n0SjwyQTFULLmkEX9dKYCMYfHstDBMGRiIf2KLlYEiADiYWIZXZg/CyN6+avv6t90FgzHafxt2Xy9RBooA4EhyOV69bRBu6eOn9/7e+icRp9IVxSI3XMzDX4unGHyjVccTw9PV2eDheo0CKTZG5aNvgAeenRZm0LaW/Fk8uiEamZWKYWdR2TXIqtQdyP07plgtWDTsk5PKf/9+MQ+/X8wzf0O7KYZhkVrWhAaBBFMGBnaa1WUt7YfVtsr9+l6tAaPWQFGro8nlWLNwXLfJDjSXmhYxntocgyah4nx0NqMK+5dMt1rgGzBPJolExmDF0XScTq9CWJAnvn54DIb38jFD64i1OXImqa53JpLKwRPLEOztZrX2dAXXCxvUlvHEitEEe64X43/7UwEA7i5c/LV4CqYZkKFvrD8vF+DLm52XBxLK8NPpLER/dKfB+xHrec1PCEAFrgkxys4ONwwd6RuwYhgWKaWNuJhdA6FEblKbcqt5mPV9JKZ/ex6DPj6BdedzlM8dSCgzad+tNl/SXhz4iY1XMfaL0/izkxmvKpqEOJ1eicomyxY73nBBcaNf2iDAoi3XcCipHMdSKvDMH9eQU9WCNWdztG5jST+fyVZbtt6A1y2q4ysDRYBiKKCuv0t7cobFldxahC07jolfncXIzyLwW2Su3q/d3meH0w3exlLBoga+RBkoarU/wbAAX7WVi2/bWvs/RXWzCGduVKG8Ub8MQ0MxDIule5Pw4G9XsPiv67hv7WXUdCh+aisvbruutmzb1SKD9sETaR6OTLTbG1eiDBQBiuPY+kjjjr8yOYP4ogZE59VCLDPtPGqoX8/lYNe1YtTyxIgrasDiv2LBMNRrT+wLh6M4/x9OKsPPZ7KRUKwIhKw8dgMjPo3ApK/OImzZcZOvQx1JUR1f43KGYfHVsbbZXkVSBmvOql/XWcKXHbLcy5tEaNLQAdyZiiYR9lzXfR9DSCsKFhGiQS1PrDXbRiTV/2QqkTF4fWc8wpYdR9iy4zif2XaTz7Isnt4SgwfWXcFzf8Zi5GcRJt1AfXIoVWU42Y+ns7EpyvTgR3mjEGduVKG6RYTjKRU615XIGHx57AZK2g1za+9UeiVmfReJV3bEY9b35y06larw5t/p75hiZW8QoOhR0TaFu0CiftNnjpuPI8nlaBFpP6G3XqAxDItVJzIwbdU5PLz+CpJKGtXWPZVeqbZMUzHJjmRyBjO+PY9FW66pLP/hVBaK6zT/vczNUhl31wtNL1p9PrPaDC1RpelvZW8is6ox87tIvLw9DrO+j8SJVN2/cWPcqGjGoaRy5eP8Gj72xpVoXb9JKMX5zCqdmYyGquOJsfVKATZH5aOiqe04mVLapLbuSg3DTgHtnQANAvWhuZ1hWRbv7E5E2LLjmPndeZ3HB0d0QEMwNyK90uCbVYmMwSs74vHohmg8vfkanvj9Kpqt+Fmu6xBsr2gSqR2PGgUSg64bzOFchvmPZ0RxjXAhqxo3ypu71FAeDoCPDqTg7d1J+PVcDh5ZH41NUXlq10JLdsab5fXaZ093VXItQd+COj5axKrXiq0TZ4hlctRrKNXQWSRcBwAAIABJREFUSiJjkF7eBJZlcSylHK9sj8Pnh9NQZUJn1UYjr/OXHUjV2VZCWtlHHjghdoBlWUxddQ5VzW0Bm9ULw9Vmvfr6eEbHTdWU38ya+XBfMk6ktt0wvrA1DsfenImRvX1xLqMKMfmqF5XLD6Zi07OTdO6bL5bhQGIZRBI5HpsYigAvVwBQ2xcAfHMiUzkUyxjHUsrx9u4kyBkWrs5cvYerbY0uxKf3jVJbvnRPEmQ3T8BSOYslf8cj95v5RrcPgNZe3LGhimFdO2PUswR2X9d8o6rpxHkhS3cghmFYpJc3o0UkxZAQ7UW+X9+ZgB0v3qpzX1ujC7Hx5tTuFU0iPPTbFWSunKcytE8q1/x+n/njGlY9MgahAaoz08nkDDZfKsB3Oqat3RiVh68fHqP1eX1EZlbjpzNZaBHJ8MzUARrXMVeoKLagHtF5tRjV2xd3jQqBq7Nx/R4sy+Kf2BKcz6zG2Qz9A5c8sQzeOuphAYogzKs7zHPhbUk/RGRBIlf8ruUMi+8iMjHfzAU8NWWv/XAqC/+9fYja8szKZjy1KUY5XNbNmYsRvX0xf3QvvDRrkFHDvZpFUjz++1Xk37yB+eNyAQ6/MQMhBtaZ0JYwYkybHlofjeSbweDSBiHGrDht07pvlsayLGp4YvTwdgOHw9E6AOy9f5OwftFEvfcbk1+nEuhNLm3C8ZQKPDWlv4ktNl5JgxC3QlEM/f1/k3EkuRwuXC7euWsoXp+j/p03RS1PcwfT5dxas76OJYllchxPqcD5zGqwAO4c0RMLxva2u8Lx5Y1CLNx0FSX1imDzM1MHYOVDo5XPNwokSCxuxOAe3ugfZPgMsQ18CbzcnI0+n+nct0Cq1qn0zQn1a4LOrnf0Vd2sX8dnXg0PEWmV6OHthvvCe9vN8GQAWksD5NdoDoTtuFqIr09kQCRlMHdkCNY9PV7l2u37iEytWeSXc2tx+t3bjDqX3KhoNngbQFGDac/1EiyZM9io7bu6juckop39/CqJQ+kqs0ocSS7H+3uTlTdLHb27Jxl3jAiBn4eLctkODcGHjjZF5eOZqQNUetNb3bf2stbtTmvJtOHf7MVw4nJwy+enlMu/PpGB+E/mKrNoNJn01Vmtz3XmjV2Jyn/rGygCgLKbGU4yOYMTaZUoruNj9rAe4HfoNZYxrPLGWyZnEHuzR3ZKWKDOIrPtaRt7fSK1Etfy6/RuMwAkFKtn8ujqeWEYFu/sScKRZPW/c0eXcmq1DvM5n1mNK7m1ainGAPDY79E49uYs5WNtvV2Xcmrx6o54HH+rbV2WZfHsn7GIztP9ObS/iJQzrN69TdlVLRja0xuVzSI8v7VtOM9XWgKqGUZe1Px5uQA7Yorg7eaM6haRSkD39uE9EGnkBe7Aj04Ytd3u2GK8NEt7AW0AWHfeuOF9xpAziqGIcYX1GNfPH6/eNhgunfx+Wq+NOl5oFtUJ9AqGGUJbpkeLSAof97Zjq0Aiw7w1l1TWEcsYJJc0IrmkEWvP5+K3RRPQL8ADA4K8kFbWBLGMwbh+/jpvsE6nVykDRQBQ2SzC6zsTMGdYD43rD9Byo6ftt2dooXcAykBRe3k1PAzu4Y3o3FpcL2xAeD8/zBne0+B925vcah5e2HodxfUC9PX3wB+LtXeInEitRLNICt923wtdnv0zVm3ZRwdS9QoWCaWWqdvR+m04kFCKwzevASRyBt9HZGHuyBAMCzFPTSORVG7S+d1evLkrUeXa53hKBU6kVmDLc5Mt9poMw0IsY+DsxFEeKzu7X9x2tVAZKAIU14IvzxqE/kGeSC1twtNbYtByc0jqlw/egmenhUHOsDiZVoGCGj4G9vDC7tgS5FbzcPuInljxwCi4OTtBKJHjxW3Xlefpbx8ZgyfNHOy8YuXgIVePy7cb5c14YuNVZeb3voRS7H55qlHHU01YlsWmqHzsii2Gn4cLPrhnOGYN1XzM10Rb4OZ4iubrvU/bDc0/m1GFHVeL8PJsxXWCVM7oLDeQV8PHtfw6TB9ieJH/+CL12kr6SitvAsOwZvvMu4qsyha8uO06ShuE6BfogT+fm4yhZjouOyIKFhGLOJZcgek9+BgQ5GXrpmh1OKkMb+9O6nS98C+M6/E1tGaKJkKJHCM/i9C5zkQ7vFhsvVB4YVscom4GIn48rXlM9+jPT2HmkGCtPaHj+/ujskmE6YODsfKhW1R6nkRSuVpx2vYWbooxuO2lDQJldg7Lstioo8jx4xuvGnSi/vhgqtbnOg4Pa5VWpkh3b+35kGoJbAJAenmzsv0sy2LemkvIqmrRun6r0gYhiusEyK/l4Z09SWjUcwz83auj9FqvVV4NHyKpHO4uTqjlifH7hTyUNQpx39g+WDC2N0rqBfjkUJoiCBXig/BQP6ztJOhibKDIFF8dz+g0WGTKBZyhvjp+A39dKQQAnM2oRkJxI2YOCYabCxcLjMgSMvfwiiu5moOVY1acxpOT++Hrh8fAicvBqM9OaVyvFU8sw3MaggMAkLLibq0Bhvf/TVZbFl/UoPVv5KWld1tbsMjQy2xtQ1vjCusRnVurctPx4bzhZs9GsbaPD6QqZ+AsaxSqdEJoUt0s0itYdM6AbMD2WJbFz2eylecmc2sNOqw8ph40X3s+1yyz59XyxCYHivJreChrFGJC/wA4cTk4mVaBiiYR7h4VgiE9rXPjVFTH19hJdjajGvk1PAzqoT1b11gl9QK8sSsByaVN6OvvgV+eHIdJYYGdTie+8aJ6bcCt0YX47P5R+OVcjjJQBADfnczEU1P6Y/nBVOyNU78W/Ce2GN5uTli+YBS+OZGh0qGz7EAq7hwZgh4+5is4LbNyHS2uHpkaf18rUikREFtQj6TSRkzoH2CWNpxMq8Sqk23ZUy9ui8OV/92h9+eq7S3o+0l+fSJDGSzSls3e3lUjg0XTBikKa1/Lr8O1gnqMCfXDnGE99MqWOZ5SgeMpFdj76jRMGRho8Gt3VcsOpCjLdpTUC/HRgVTsWzLdxq2yXxQsIhYRW1iPhRtjcO6923ROX24sqZzRmU2jj9UaCg2bk6YCyobqLFBkr06kViJs2XG919eVMp94M9tnf0IpmoRSbHmurVc6KrtG5WLDHGZ+F6kMDn57MlNlxrSODA0IGJvizbCA083zfmcFqc9nViOzskVt1qbOzP4h0qi2Gerl7XH48fFw3PrNOeWyk2mV+O8u1fUqmkQWu5kzh+uF9ZgcZtrFFcOwuFHRDKFUjmEhPtgclX+z17kHnpjUT+1ir0kghbe7s1qPZ2ugqNX5zGrl0Jzt0doyIbVfSFrzvmL39RJMHxKM+aN7mbSfsVYYxiXXcjepz41Re+0L1LfHAUclUAQAv5zNwWuzB1u15ze/hoc/rxSAJ5Jh4eT+arP8NIuk+P1CHvJr+Jg7KgSPTdQ91Dm2Qw2f3Goe+gV6mNxOY2crjMmv7zQIbYrWzFpN56ajyeVmCRZ9uC9Fr/VEUjkYllUb3rP6TDZ+Oae4RgnxdYOXq7My+27d+Vz88/JUhPez/Mx0R3Vk5R5KKsfSu4aZ/TV/PpON5Ju1ysoahXjs96soWDXfqCB5a9Z3x2HMfIkcp9OrNAaKWm2+VIDlC0ZpzFb/+Uw2Vj1i2tBwW9J2TAxbdhxv3jEE7909XOM1yvboQqOCRXGF9dh1rRhuLk54fkYYhoX4qJWMkMgY7LpWjLfnDjV4/+2dN6IeWGVT55NHNAmluJBVjTF9/RBkwMx0UwYGYndsMZYdaOuMfO+uYXjzTv3f5xMbryL7q3stMgTS3jAMq7yvaBVnxc69roiCRcRiKptFiEirxKOdXEi2J5DIwOVwdE6/viOmCKtOZJhcMFJXEKCj6avO4eibMw06gBPz63hB9oqFasLkVvPQ09dNWT/I1mQMAy6Hi6c2x3R6I2/MLGXWdCmnViVQ1FWtPZ+L7S9MMXr713bEI0JLAeyI9Eo0CaV4edYgcDgc/HouR2UWvV+fGo8Hwvvo9TraMsvkjO4hOHk1PGy9Ugi+WIYnp/RH/0BPfHwwFSmlTfjywVvMWtfok4OpCDFjL7qptMV+tA5DMzCO89Y/mjNrPjmUprZMLGMgkMrNOixQl0aBBAs3xSgnWziRWol9S6bhlj5+uJpXBy83J6w6kakMAEWkV2J3bDG2vTDFoI6h9sN5OtI3WKlpamt9PLXZ8IxTQ2Tqkc1pKn0K8rfvsFk8PQyf3TcKXC4HDXwJfm03W6piWG/b0F6BRI5t0YX4eeE4s7aZZVlczK5Benkzpg4KwsQBATqzeUwNj5bUC9DLz11tSO7BRPXZYXOqeUad7xlWMaOtJrv1mG0qvVy9wD4AnLlRpTVYVFwnwOkblQj0csW9o3vDw1VxvVzeKMT0b8/r2XLTMAyLFpEMfp4uKGsUoqCGj3H9/ZXHKUbHH3bt+VytwdpDSeWYPDAQD4T3AYfDQVJxIwb28EJffw+cSK3A8dQKhPp74NXbBiPwZr3OjIpmPL3lmrJUQkRaBU6/exvKNAz772wyjKpmUafXJx2LW+tDpqXWZHvbrxZh+9UiuDpz8f2jYxHo5YrRff2U71MbD1cnte/u+gt5eF1DTUBd/rxSgNduc7z6RdUtImRVtmBsX3/4ebp0kSIp9oWCRcRk2mrGAMDqs9kag0WJxQ2Iya/HqD6+mD1UkXbZvn7IoB5eWL9oArZfLYJUxmDR1AEY188fpQ0CfKrhgroz6eVNePOfROTX8DFxQAB+ejzcoO3LmxQ1Lva8Os3g1ybmJZExFu/9yKpswUsaptS2lTqexGoXgUQ/Udk1uFHejBG9fMDlclDZJEJEWgU83ZwxT48sGW2BolbfnMjENycyMX9ML5Ui+YAi2ODuzMWwEB/08TcuQ6NBx1DDqOwafH4kXVm76kCHm6vXdyZg1SNj8PjEUKSUNcHd2Un5OURmVmPNuRyIJHI8Nz0MT9/aee2NZpEMz2gZXmaIWp4YwWYI6KeXN0MmZ1TqpklkDN7UEuQxpDjm5RztWZTaaufpIpDIkFTciAHBihsqfbXW89gTV4IgL1d8cM8IDA/xwdHkcpVZOSVyBg+su6JzX3FFDbh/7WWcene22o25MbMinblRpVbXp5YnxonUCni7OeOB8D4o0jLjZmesMUtTYS3f6rOfdWZrdCFmDAnGXaNCcCiprNMhVwcSy8weLFq6N1klULN6YTiO65h9MTKrGu9qySyqbhEhu5KHMaF+KjUlAeBCVjUW/9V2/g4P9cPhN2YC0F4/La1Mc9AGADZcyMPsYZqHBx1OKse/8Zqzhy7p+K23WvCr5hqWs4aqvx7LsogvasCL2+LQJFS8j6V7k5H46V0I8HI124QKkVnVuL1DrTQ5w4IvkcHTxQl3/HRROay0oyE9vZFbbdoslssPpmH5wTR4uzkrs/MmhwWoBIdbgyOZK+dhc1S+Sk3NBoEUh5PUA4KAIotd13nCUh1ZhgQiJTIG7+xpK5Hx6uxBeGnWIK3D57gcjtpxTSiVG1zk/tuTmQ4XLDqaXI63dyeCYQFPVydse2GK2YY5dicULCIm65jO115pgxDP/hmLDYsmKHsdDyWWqRwI3507DJmVqkVW82v4KoVOj6VU4NhbM7FKw+wNHX2wLwV5NXy8MnsQAr1cUVIvUDkhxxc1YM6PF/R9e0qtU2MS25IxDFxh2WDRucwqgzLPLI0CRfZp/q+X4ObMxZl3b8PjG6OVhbf1HSKij46BolbmyKp75g/NdbK0BUXa++hAKvbHl+pM3/74YCqCvXX3irYypIC+NtNXncfZpbfh3/gS5Nfw0dvPHS/MHGjUvg4kluGJSf2Uj3dfL9Y6LLKySaR3HYyfz2QZ3BaRlsyi3GoentwUo5wR69P7RuFFPd/vkeRyZT2P/Bo+nth41eB2tZdfy8eUr89iTKg/Xpk1CDOGBKFFLMO26EKD99VxpryjyeUq38nlBw3vMGp10IBagjUtYpxKr4RIqph51N9Tv+9yenkzRnxquSHk2jLcOvPlsXTcNSrE5CH8xkgra1LL6Hl3j3otsfZSSptQUi9ATnULbh0YBBnDIq2sCZ8eSlMpWL9/yXRMHKC4AWzgS1QCRYBihrywZccxJSxQbUhkq6V7tbflu4hMfKflz2lMgFcfrUONZXIGf14pwF9XClHRpHl69fErz+Dz+0chVUfAyxDP/3Ud15fPVR7TjqWUY/nBNDSLpJ0GGU0NFLXXfhintixCbb+znTqG4U/66iwKVs1XC/KXNljmmq/EyMB2q41R+dh8KR+/PKl5+OpHBzTXwtRW38+SpHIGf1wuQEppI6YOCsJ/bh1gs+LZLMti5bEbykxVgUSOH09lYdfLU7WuT7OiacYxdyFLc5s0aRIbFxdn62YQHYavfhmugapp3aLKByFtaMvC4XKA/FULkFrahPvXaZ8NTJf/TO2Pv2P0r8NySx9fHHtzJt7/N8UsxaYBoPDbBQbV4jFU6+fUypKv1VX9+Hi4skYGfT6EEEsp/HYBGvgSPPtnbKc3YmeX3oYATxfsTyjFNycycevAQDw3PQzv7klSZt8eeWNGp1k6mqy4fxQWz2gLAskZFucyqjQGDPsHeiLE1w1L7xquVmuoPUc/di4Y2xsCsQyers5YvmAkMiubUdMixv/2a59koNUjE/rig3uG486fLkLQbgZPTcM/jfkcjamtxTAsIrOqcSCxDMdTtGfj6PPa6y/k4vuIzoOWxtYAk8gUN4yn0iuRpGHWP0tYs3Ac/rpSoKxF5AiSPrtLUUumynwBGH1NGRiIva9OQ7NIiglfnrF6gWxTubtwIdIx2+GB16djQv8AXMmtxeoz2eCJZejh46ZXNpghLH3PYG6m1v37374U7IlTL+Y9opcPnp2mX6axuZTUCzDre/VanLlf34shy0+qLdcUQOxOOBxOPMuyGqcqpcwiYhUMC2y9UoAVR9WnBteXIYEiQNG7l1DcaLZAkTXoM3ylu/vyaDoendC3Wx/UCSGWx7Isxq88o9e6c3++qPL4WkG9WjaqMYEiAKhqNywMAD46kKK1cG5xvQDF9QI8tTkG6xdN0Fhbyt6GSFlC+4CKrqFOmhxIKMOBBPVhLG/9k4h7bgmBm7P2mor6YBgWO2KKEFfUgHH9/LF4epha0XqWvVn8XiLH+P4BWHnsBrYakaXVUUEtHxyTqwG14Yllallv/9uforEukCW1z1Z3FOO+1O/YYwmxBfWo50twMLGsywWKAOgMFAFAdG4t+vh54IWt15XB/MxKy9cac2RimVxjoAhQfLYfH0zFb5G5mDuyJ56ZFoYhPc0702F1swifH0lHZmULZg4JxqKpmgNT2iaqYNm2eoVyhoVYJlebGKC7ok+BWI0pgSJj6aoPYQx7z8TrDppFMpTUC9E/yBOerk4qPb+EEGIuP1t4xkx9idvd+NTxxDpnWGrv9Z0JeGX2IHw8f6TK8lOd1Msi2g3/pG3Yy7PTBhi1j+8iMpU1TI4ml6OkXoAVD9yifJ5hWAz6+IS2zU3y+s4EvYvj65JV2YIlf8cjv5aPW/r4YuMzExEa4Am+WGb1QBGxjGv5dRYbmmVpwd5uyuG5msgYFv/EFuusudpdxRfV48dT2WgQSPD0rf3x7LQwjeuVNQqxLboQjQIJHpvYDwODvTrdd1mjENuuFuFYSgUi3pmtHOrYJJDi8yNpSCltwuSwQHx2/yiDZ9J+7e94JNwsi1JQy8ee65oDV+2P4Zr8G1eCr45ngC+W4YHwPvjusbFqtfi6GwoWEYembZYKY1k6VkSxKP1Ib87k5GyjsdCEEMdnyenVDfHnlQI8fWt/DOnpjdM3qjrfoJ1NUfk4mlyOiiYR3rh9CN6/Z7jWGhfEMNuvqk95ro+OxW63Rhfi0/tGKbOL1kVa7nuXUdGMjIrmzlcEsHRPEgYEeeHFWQPVsoeW7k1S1g1KL2/Gf3clYvrgIETqMUsb6Rre2ZOEJyf363xFO6QrUAQAa87mYNIAKnTcUaNAgqc2t80s99nhdLAs8Nz0MJX1BBIZFm68itIGxYxzBxPLsPGZiXq/Th1fgn/jS/D6HEVtuqV7k3Du5rEjv5YPiZzBagMK7Fc2iZSBolaG1hPbl1CKAwmliMlvywg+kFiG0kYhxDIGLlwOlswZjDtHhhi0X0fQvUNlxILsI+pxzswXLpZ+VxQs0k9rhhd9XISQ7mDdzanO+UZM29xaGHddZC7+s+UaZWPaofYF3u0lo+1AYhlWn81Wmxm0gS9BerlqwCm5pBEbLuTRUB4HIpYxRs862BV092wRTXZfL1GbbOLzI+kqj1mWxdHkcmWgCACkchbrI/MMeq2tVwoBKIZFd7xXMzQ7saZFd3BQHx/uS1EJFLWKLahHckkj4ooa8OqOeLMWce8q6JdCzICyO4h1UVCNENKdHEoqR1pZE/ZpmaZbX4ZOp0ysg7l5UqvUMuOVLcXk16tMLa9rBkTiWC5kaZ4B0hGUNjpuIMxY0Xl1Gpfn1ygCJFHZNZi26rzGiQKMPS4IzdB5Ya0SpjKGxeYOmaHdAQ1DI8QAlq5ZxIKFRMbAiWvOEpSOh2JFhJDu5r61xs0kSuxfSmkTBgZ7Yeqqc7Zuikb3rb2MuSND4O3mhENJ5bZuDiEmK6kXdr5SN8NoKWb++8U8rHxoNJb8HQ++mTJT2Q7/N4U157s5mVaB7x4ba70XtAMULCLEAIYc1Ib29EaOgemKp9KrMOwT9SkdiSqGUosIIYQ4iKc2x9i6CZ06m2FYvSxCujupgXVzbE3GaG7v3rhSzBzaw2yBIqBthIA5OuG5NDuyRdEwNGIyH/fuE3M05JhmaKCI6K/jmGpCCCGEEELshTE15mxJriWzCABOm30WTfPVHm0QSMywF6INBYuIyfw9XWzdBKthaQCUXXhg3RUs2hKDFlHXOhETQgghhBDHx+liGS+6gkUiqXk7aVs737WNFPjvzgSU6FFgfee1Ijy9+Zo5m0Y66D4pIcRiPFycAKmtW2EdNPrJflzJ1VyIjxBCCCGEEFvidq1Ykdr08+2Zu2YrrzXrSstuj6dWIKOiGefeu00ZdEsqacShxDL4e7pg0a0D4O3mjC+O3DBru4g6ChYRQgghhBBCCOkWQnzdUNVs+pTruiSVaA++dDXmrhUqljE4mlyOKQMDta6TX8tHQnEDJg4IRHJJIx7bEA3Zzeyno8nleHX2YEi6WF2oroiGoRGH19ffw2z7oswiQgghhBBCui5LB4oA4Jk/Yi3+GtYit8D9z5v/JOJSTq3OdTIrWyCWyfHgb1eUgSIAyKvh42gKzcxoDRQsIg4vLNjT1k0ghBBCCCGEkC4no6LZIvt9/99knc+zLPD7hXyNz3UWaCLmQcEiYjLNwWb7ScExZzYQFbgmhBBCCCGEdBc1LZbPxNJm9dlsm702oWARMQMO7LuCm1mDRRQrIoQQQgghhBCL6mITyjkkChYRh2fObCCKFRFCCCGEEEKIZVEnve1RsIg4PPNmFtFRixBCCCGEEEIsKb+Gb+smqGgWyWzdBKujYBExmb2HT8zZPnt/r4QQQgghhBDS1f15pcDWTej2KFhEHB/VLCKEEEIIIYQQQvRGwSLi8GgGM0IIIYQQQgghRH8ULCKms/NYDEPj0AghhBBCCCGEEL1RsIg4PHMWpaYsJUIIIYQQQgghjo6CRcQM7DuAYtbEIvt+q4QQQgghhBBCiMkoWETMgGPrBuhkzgAPxYoIIYQQQgghhDg6ChYRk9l7AMW8mUX2/m4JIYQQQgghhBDTULCIOD6z1iwihBBCCCGEEEIcGwWLiMOjmkWEEEIIIYQQQoj+KFhEHB4FeAghhBBCCCGEEP1RsIiYzs6DMeac7t6c+yKEEEIIIYQQQuwRBYuIwzNrZhHFigghhBBCCCGEODgKFhGT2Xu2jTmDRfb9TgkhhBBCCCGEENNRsIg4PMacs6FRtIgQQgghhBBCiIOjYBGxEMeMqth7FhUhhBBCCCGEEGIqChYRM+DYugE6mXUYGsWKCCGEEEIIIYQ4OAoWEYdn3tnQCCGEEEIIIYQQx0bBIuLwKBuIEEIIIYQQQgjRHwWLiMnsPRZjzvaxFHkihBBCCCGEEOLgKFhEHJ45AzwUKyKEEEIIIYQQ4ugoWEQcHsV3CCGEEEIIIYQQ/VGwiDg+mg2NEEIIIYQQQgjRGwWLiOnsPIBi1ppF9v5mCSGEEEIIIYQQEznbugGEWBpDNYuIo+EK4BoYDY5zE2QtYyHnD7V1i4hJWHDdKsEybmClgbZuDCGEEEIIIRQsIqaz9/iJOQM85gw8EWIcFp79/4STRykAwMU/DsKSxZDzh9u2WcQ4HDE8+m2Fs1cBAEDScCvElQ+CEn8JIaRrcPZNgmtANFjGDZLa2yEXDrJ1kwghxCzoapQ4PHMOHWMoVkRsjOteogwUAQCHw8KtxxkbtoiYwsU/QRkoAgDXgGvgupfbsEWEEEL05eSZB4++u+HkWQxn7xx49P8LHOemTraSw/67WgkhhIJFpBugzCLiSJx9MtSWtQ8eka7FvddhtWVuweds0BJCCCGGcu1xWuUxhyuFS0CMlrVlcO+9B97DP4fXkO/g5J1p+QYSQogJKFhkKywLFF4GYjcDNVm2bo3xyhIQ3nLJ1q3QyZzxHTmlFhFCLIzjzLN1EwghhOjB2bNIfZm3eqcOALgGXYaLfyI4XBm4Lo3w6Ps3wBFbuomEEBNwPYrg4h8LjkutrZtiE1SzyFYurAIufqf4N9cFeGo3MHSubdukS2Ox4v/+/duW8euAzbcjMNAfgK9NmqWPymaR2fa18WKe2fZFCCGEEEK6B7eeESqPOVwZXPwSIW2caqMWEUJ0cQ2KhFvPUwAAlnGCsPQ5AAts2ygro2CRLUhFwJVf2h4zUiD6F/sKFrEscGgJkPyP+nNP7wXc/YA/77F+u4xgzmygQ0lUS4TYGsfWDSCEEEIciAxOXnngOAkh4w8F5F5We2WJTLapAAAgAElEQVSua73VXosQYggZXIMjlY84XDlcgy4AeNdmLbIFChZZi0wC5F8A6nIAuRSQdch2KYjSbx/FVwGZGAibCXCdFEPZpAJg0BzAzcd87f3CX/tzu57odHN/Dg815msNIYQQQgghZiaHR78dcPZuKwnBSH0ha7kF4up5AOtmw7YRQmyF61EGDleisszZK99GrbEdChZZw7WNwMkPDduGZYHabIBXDYROBjgcRZAm/4Liea6LIiOpVfAw4PmTgFew6e1tMr1YbjCniYJFhFgClc0ihBBCzILrUaoSKAIArkszXAOvguPcAlHZf9o9w8DJsxAc5ybI+UPAyvXrpOW6lYHrXmHGVhNCLI1DF9wAKFhkeXV5+geKNs0B+k4EJj4PJGwDYjcplgcNAYbNawsUAaqBIkARWEr9F5i6xPQ2F2ubxUF/bpB2vhIhhBBCCCGWxJHCrccZOHkUQi7sB3HNPQDrCgBwCz6rdTMX3zSIyqUA66JYt/cBuPrHAQAYmReERa92+tIuAZfh3uuYGd4EIcQeSBkpXLgutm6G1VCwyNKu/qb/uuWJiv+ub1FdXpcLXF3X+fYRy4CeIxVD0kzh6m3a9oQQC6KaRYQQYg1c9xK4Bl0AhyuBtGEqZLxbbN0kYgS3XoeVQR4nz2JwnPkQlT+peJIj170xVwIwLNx7HYaLf3zbYmc+XAKiNW/iVgNwpADrBLce5zppHWUvENKV3Ki7gfAe4bZuhtVwbd0Ah1ebbd3X2/4gcPEH0/bBoa8FIYQQQrovjlMLPPtvgYtvOpy9c+Ae+je4HurTpBP71xooauXilwRAESTqrAaJi28ifEZ8phIoUu43UHMmPocjh/ewL+AaFAmOk9C4RhNC7JJELul8JQdCUQFLYxnrv2bkV4CYZ9y2cimw63GTm8CFDd43IYQQQogZuATEguMkVj7mcFidQ5ZIF8Nh4OSZ0+lqxg4h43BlcOt5xqhtCSH261rFNVs3waooWGRpRVds87oZR4zbLv2QWV5eTl8tQgghhHRRzj4p6su8Ow8ukK6B4ySEW8/Ttm4GIaTL6V7lIOiO3lEdMrLQ9bF3zPLyQriaZT+EkI6610mKEEIIMTeP0B1w8iixdTMIIV3M8IDhtm6CVVGwyJGxRhTNkxg5fI0QQgghhJAugAJFhBBjxFbG2roJVkWzoTmyqjQg6yRQEgv0mwL49gESdwIe/sDs9wFnd8C3r+KxmVHuAyGEGImlIyghhBBCiL3ZnfUPlk/92NbNsBoKFjmy32e2/Tu3Q5G9rBNt/75vDTDpebO+9OyhwciqM+suCSGEEEII0YnjUgv33vvh5FYFGX+YrZtDCCFdFg1DI4o6RcbOnqZrt2/O7HwlG0hZcbfG5SN6+eDax3ci48t5ePOOIRZvx/t3D0Owt5vFX4c4Gso6IYQQQrTx6Lcdzl4F4DgL4OKXZOvmEEIczItbr6OOJ+58RQdAmUVEIeMIMO5p8+2PZTG6rx9yvr4Xu6+X4LPDacoSSh/PH4GXZg7CxwdTsft652PGM1fOg6sTF2/tTsSxlAq150f19sVPT4Rjwa+XwLDAHSN6Yv6Y3th1rQgJxY0q647v7w9fdxcce3MmHlkfDYmcgb+nC75/dCzuGhUCDkdxI/7e3cPx3t2KAmbHUyrwzYkMBHi54LEJoRgQ7IVpg4Lg7uKEQ4llWH02GxwA7941DGND/XH7jxc6fU8Jn96FQC9XvHHHUFzMrsHxlHLsjSuFn4cLmoRS5Xperk7gS+Sd7k+T5M/uRnWLCHetjlJZ/smCkXhp1iAIJXK8sycRaWXNeGbaALw6exBkDIvovDpkVjTjsYmhEErl6OXrjpIGIdaez8GBhDIAgIeLE1JW3A0Xp7Z4cwNfgq3RheCJZfjjckGn7dv18q14enPb9JP9Az1x8PXp2BiVj01R+QCAiQMCsHh6GN78J9Goz8Ccpg8OQnSe5dPlBgZ7oaCWr30FI0qR2YPvHx2LD/erzy5ECCGEmAvHtQZObtW2bobeXIMugetWDa57KeSCMIgqHgUYT1s3i8C0a3Di2M5lVuODfSn4c/FkWzfF4jisMUWQrWjSpElsXFycrZthvBV+tm6Bfnz7AnOWAUfeNHjT7wP9scPPV2XZk353YflDP3e6bWWTCFNXnVM+9nF3xtE3ZuJYSjn8PFywcHJ/uDorAhJyhkVSSQMa+FJMCgtAZmULhFI5pg4Mgoerk8b988UyTPzqDERSBq/PGYwP541QPidnWJQ1CNE3wANOXPNma5TUC/DT6SzU8iRIKmkETyxTPnf78B746/kpBu0vrawJz/xxDQ0CRSBpSE9v/PrkePQN8ADLsvD3dEWjQILd10vAssBTU/rB39N2M9JtisrDNycyVZZ9dO8I3DooCEN6esPbTRGnZlkWNTwxfN1d4O6i+W/YqpYnxncnM/FvfKlJbQvxdUNVs2G9AYFeroj/ZC7EMgYjPo3Qe7v37hqGXbHFqGgSaV3nxZkDsXz+SJQ1CtHHX/FdPJZSjjd2aQ6QuQadg1vPM2rLWzK+1atNPm7OuLzsDnx8IBXHU9WDr61il9+JTRfzEV/cgMQOQddWlz68HSwL/BaZi7waHvJr+ajnS9TWe3xiKH54PBzRebWIL2zAT2ey1db597VpePz3qwCAWUODseE/E5XfkyaBFLV8Me786aLGdozp64fUsiaNz90+vAe83Jxx7+jemDe6FzZcyMWPpxWvv+L+Ufj6RAakctXz4G9PT0AdXww3Zy7G9QvAucwqfB+RpeWTUnhqSn9MGRiAZqEMnx9J17mut5uz8pjgM3KZ2vNyQX8Iil5XW75gTG8sXzASXA5H5bhJiLE+WTASI3v74tUd8Srnqa5m+fyR+PpEhkHb/Gdqf4T4uKOOL0F4Pz+8uydZ5XnPgavh5F6lth0v81u8ecdQ/Houx+j2duwYchSPTwxFiK871kXm2qwNTp758BywyWavbypp8xiIyhapLff3dMHsoT1wJLm8030cfH06Hl4fbYnm4aFxfXAoqfM2OILCbxcgbNlxWzfDbP5aPBm3j+iJe1ZHIauqxdbNsXtOHoXwDPtd43Ot19yF3y6wZpMshsPhxLMsO0njcxQssrCuEizS00rPj/DJonvA2TxHucyUYBGgCBiUNgjR09cNbs66AwZdEcOw+D0qD5dzajGyty/emTsUPu4utm6WRQkkMry6Ix6XcmrhxOXgg3uG47XbBptl3xVNQkxbdV5t+YZFE9DLzx1hQV6o5YnVMqpemDEQH80foZIN1YovlmHZgVRcyKrGsBAffHrfKOyPL0VsQT2emTYAi27tr8w6k8kZJBQ3okUkxdRBQYgtrMdL2+IgZxTH0jtH9MQf7XoayhuFOJRUBpYFHhrfF339PVDVLML1wnoMC/HBsBAfje+TZVmklTWjtEGASWGBeGDdZVQ0ieAadB5uPU+rra8tWOTr7oxvHhmD/Bo+3Jy5eHh8X/T0dVdZp6xRiJnfnVdm/215dhLmjgpR29flnFrsiCmEM5eLl2YNxPj+AWrr1PMleH7rdSSXKAJMT07uhy8fHK0M+gKqf8M+fu44/MZM9PDRf0jmqfRKvLM7CUKpHEN7emPHi7eil587qppFWLTlGnKrFcNqHwjvg5+eCNf4N28lkspxKacWBxNLMTzEFw+O64OwYC+19Rr4EnA4QEm9ED+dyUJmRQvCgj2x9K7hmBwWoPx+aNp/TYsYoQEeKusklTRiy6V8XJQ+p7bN2B5jsXP+ThTU8vG/fSmYN7oXnpsephbUjsysxvNbr6ttv+qRMXhqSn9IZAyuF9ZDKmcwpKc3Eoob8VaHLL31iyZg/pjeKssuZFVj8V+q+33/7mGYNjgIm6Ly4ershLfvHIoBQZ5oFkpxLqNaJWtMW2/sy7MG4u25w9AokOD9f5MRk1+vts5LMwdi3uhemBQWqFyWVdmCI8ll4IvlOJtRhdIGofK5lQ/egk8PqwbnFk8Pw9boQrV93ze2N24b1gMf7NOc4Ta0pzd+fDwca85mo1EoxTcPjwEAPP77VZVAyq9PjUdRLV8Z9NywaAJuH9ETY784DYmM0bhvTX57egL+uytBZdkH9wxHYnEDzmZYJzOi9UI3sbgBnx5OQ0m9UGMQY3APL6xeOA5jQ9smxIgvasCjG7TfkI7p64eiOj6aRW2fXbC3K2p5ioByaIAHNj87Ceczq/HDKd3BWEAR+I3MqlFb/uG84Xh9zhAU1wkw+4dI5XJfd2dseW4ynth4VWX95fNHYvGMMLXjwueH07DtapHysbZg0flH4tDDxw01LWJEpFVgRG9fjO/nD7GMwfcRmSr7aG/JnMF4ZdYgBHgpOnJkcgZDlp9UPn/HiJ5YMmewMmgOAAden44J/QPQJJRCLJOjp487qltEmPK1fsHihZP6YeVDo7HzWhG+OHpD7fm/Fk/GyN6+OJxUhrMZVbhe2KBxP+GhfvD1cMGlnFqV5cffmglXJy6yq3iYOCAAvfxUzy3HUyrUvuOtIt6Zhdf/TkD+zUzakb19cceIHpAxLEb19sVHB1Ih6HAc+Xj+CDwyIRRfHL2Bo1qCJl09WAQozucTBwRgyW2DMXVwkLLjBAC2Xy3EZ4c1d0hMGRiIva9OAwDk1fDwW2Qu6vkSPDIhFPk1PMQW1GNMqB82Xsw3ql33je2NdU9PUFueW83DhaxqcDkc/BaZi7p2nUaf3z8Kfh4uSCxuxMHEMq1B6fB+/tjx4hQIJXLc+o1hnSE9fNzw2MRQPD89DJmVLXj2z7bZquI/mYsmoRRL9yYjqUS94yvQyxX1fAkmDgiAE5eDBr4ES+YMxiMTQpXrGBIwat1fRze+vAcccPDr+RxIZQxenDUQF7Jq8NGBVIPea2d6+rihukW9Q7T1WNJePV+CTw6l4kRqpVnb4Ci0BYtYxhm8rK8AULDILlCwyH6MFm0BD57Yv2Q6JvbzBb4fBIgaNQaLnvKdi48fXm2jlhJNmsRNSK5JxkC/gejn088qr1neKISvh4vKhY45NIukOJZcgdIGAe4d3RtjQtV/ZyX1AhxKLIOTEwePjA9Vu4jVhGVZrTf9usQX1ePMjWr0C/TAoxNCO82SMkZFkxA/nMpCOv8AyrkH1Z7/KjwC353MRHmTCO/dNQwPje+LfoH6p7KzLIviegF6+3moBHZM0dnnaeznDQBimRxVTWL0C/RQ20ejQAKJnEFPn87/5rY2ZtsYtWXhPcLx9/y/9dr+2M0hrP4eLnhofB/MGdYTXB2ZkhIZg/JGITgcIMTXXet3dculfHx7MhMyhsWtAwPxx+LJOn/HhbV8pJQ1YVyoP/oHeYIvluHfuBJcyK6Br7sLlswZjJG9Vc8TicUNeGHrdTQIpAj2dsO2Fybjlj6dnzPreGI4cTnw93QFw7B4c3cijt8cohwa4IG9r05DH38PrDiSrgwavXH7ELx39zCV78rSPUk4kFimfPzrU+PxQHgftdcTy+RoFsrg4+6s87d9KLEM7/+bDBmj+7rq4/kj8PKsQQCA9RfysC26EJ6uTnj3rmF4cFxf8MUy/G9/Ci5m1WBIiDd+eGwshvT0UQk8imUMHlx3RaV32MfNGYN6emPF/aPQw8cNoQFtv/+8Gp5aZt5bdw7F0rtUi/+2/iZlcgalDUL0D/TU+X1KKmnE5kv5EEvluGNECB4a3wc1LWL08nNX6fzp7Le+/GAqdl4rVlm26Nb+GBjshemDgzGqT9t3p7JJhIWbrqKoToAfHw/HYxPbburkDIvE4gbU8iSYNjgIfh4uiC9qwB+X8yGRsVg8PQwzhwZrbAPLsjiSXI5jKRUI8XVDEvMJilrUb6pTn9N9c5dY3IDTN6rQx88dD4T3RZNQqvE41aq17kXQzRqGcoZFSb0A/QI9Dcp6bv8Za/q8K5qEWH0mG+WNIiwY2xtPTemvtv226EJsisqHsxMXH907AhMGBMDdxQl+HooOLqmcweXcWgglckwZGKhX3UWWZbHhYh62XilEdYsYd48KwapHxijfrzHnAYZhcTi5DBkVLRjd1w9v/ZMIjmsNXAMvwdnnBrjO5q/DaU0tGd8i8dO7lIHF9ur5Eizacg0ZFc3KZXeO6IkhId54d+4wva4/tlzKx1fH1TPxZg0NxrqnJ0AokcPXwxlR2TU4mVaJYG83zBvdC5PbBfE7o+3vyhPLsPZcDjZG5cPbzRkPje+DFfffAucOwdv220dl16gEgJ6fEYa37hgKGcMi2NtV4+toev1fzuZg9dm2zObz792GQT28O30vf14uwJfH2oKtn903ChwOsCkqH1I5AzdnJ/i4O+M/UwfgP1MH4EZ5MxZtiUGDQIrNz07CXRo631pVNYuwL74Us4f2gJRh0CiQYFJYIHzcnMHhcFDVLIK7ixMqm0TIqmrBrQMD4eHqhAPxpajlSTB1kOI4N6yXt8oxN6OiGcdTKhDk7YpHJoQqf8O6xOTX4ZezOajjizE21B9v3TEUEjmDRzdEq3Ui/PPyVEwOC0BRvQClDUL8FpmL2AL1DqBWI3v7qnxnVbHoPygGfNcrCHAPwIzAZ7HtfFt7pw8Owk9PhCPA0xUSOYOxK9Q7TFvdN7a3xpIlnq5OmDooCPNG98KHWjqMOtIWLJI0ToK44jEAFCyyCxQssh9hol0AFMOJXr1tMMCrASK/xvcFBylYZOdu1N3AS6dfQotEcWPx0ZSP8PRIM9aoIlazKWUT1iauVVve2Q2MvWoUNcLb1RvO3O5ZQk9TsKg1s8jWeGIZGvgSg4KOhpLJGRTXCzAgyMvo4cCt2X71fAmmDwmCr56Zm1I5gwMJpcit5uH24T0xfYjmIIIhhBI5yhoFyK2rQFWDC6qaxXC9mdE3IEg9Yw3QflOlz010RZMQni7O8PN06XT9v2OK8MmhNADA/DG98NvTE4wO1lpCTlULjiSXw9fdBY9M6KsMJtjKw4cfRm6j+nCqrnqstTVTOgc6E/bxfngN/glcZ8cYWtOStQKF3zyq9XmxTI7o3Dq4uXAxbVCQUZ/r6fRKHE+twOGkcni4OGHigAD8/ES4WuaxJRn6nWi9ZzXle8QXy1DPl6hl+3amqI6PpJJGjOnrpwwwWfI73VU18Fs769zUPpuY/Do8tTlGmcXu5+GCC+/PQXTVGSy71DYk383JDWcfOwt/d39oE1tQj5XHbiAs2Auvzh6EXn7uyuB1RFolPtyXjGaRDGND/bB+0QT09W/7e/PEMuyLK0FyaRMOtusw6khbsEhccwcktYrJkgpWzXeI74CuYFH3vDon5uHdA7h/DWrXXwUgUH2u6/9uHMrvyb8rA0UAsCZhDR4f9jhcnBx7OJwj4jjIj0sgFWDphaW4Un4FXi5e+HTqp1gwyDF6aByFt5uz2bMCO3J24urVs9vZPqYM1L/Hu5WLExcLJ/fvfEUDlPEL8MalN1DGK0M/n35Yd8c6DPIfpHMbbRea+lyA9vbz0Hv91l5ve73BGRrio5xYgjgeS37n3rifh23ZjhEoAgDXoEgA2oNFbs5OuH1ET5Ne4+5beuHuW3rhlyfH2+yYYOhrmqONXm7O8DLivDYgyEst4G+Px1Fb05QN12rqoCBsWDQBu2JL4OPujCW3DUaAlyu+jVUtoyCWi7E/Zz9eHPOi1n1NGRiIo1pm3Z43uhdmDAmCUCJHgJer2pBjbzdnLJ4xEACweuE41PHEkDEszmZU4VhyBUIDPPD23KGolmTiuQgNNYu62Z+dgkXEYPadi0Y0iSyJVHkslAkRVxWHaX2m2ahFxFiOcnHyV/pfuFJ+BQDAl/LxyeVPMDt0NnxcNddw6k4cJSDYHX0e/TnKeIqeypKWEqy4ugLb791u41apcpRjCCGtbjRrnvygq3ILtu776YrHBIlcgtNFp1EtqMacfnMwyE93UJ7Yh3mje2PeaNU6iY1i9VpSKTWmzZ7r4+6id31Y5RBg74uo9P8LcvceKBUthVAq1LJF97oTNk9hCkI66l6/oy5JyjjeTCyk6/g9WbW3RsbKcDj3sI1a07WxLIvchlzEVcZBIlcvrKkPqVyK+Kp45DTkwN6Hp9srOSNHSq3qBW5iteZZDYn9o99B10EB9u6FZVksvbAUH136CKvjV+PJY08itYaGhxLjRRRE4Ie4H1ArrEVGfQZePv0yThac1LJ227mhO5wmKLOImEzT74RO24QQQ1XyaUYOQ7Esi5UxK/Fv9r8AgCH+Q7Dl7i0I8gjSex+Noka8dPolZDUoZqR6aMhD+GL6F+ByqD/JEAz0nwmNEEKIcQqaC3CxtC37SigT4u+Mv/Fdj+9s2CpiTqyVsw4+iPpAbdnJQm3Bou6FrgSJGWgIDVG0iBBiIJFcZOsmdDl5jXnKQBEA5DbmYn/OfoP2cSD3gDJQBACHcg8hq77zqcwJIcQexFbGdr4ScRiHcg+pLTtRcMIGLSFdkUAqwPqk9Xj/4vs4knfEiD10g3SidiiziBhMrzhQd8jL6+Ioxb5r4knsY0pglmWR3ZANGSPDiMARcOJ2Pl1vZ66UXTFDy6yPZVnwpXx4u5pWqNkYW9O3qi1bm7gWr4x9Re99rI5Xn7lyc+pm/DznZ1OaZjCGZZDdkA2WZTE8cLjBmU1yRo4LpRdQ2lKKmX1nYrD/YAu1VAsth1R7LShNCOl6hDIhzhefR6O4Ebf3ux19vPvYukmEdCnvX3wfl8ouAQBOFZ5CSUuJQdtzOO2GoZm1ZfaJgkVEL5fko5X/7vjD0HgJTNfFds/aKZ6kjUQuQVptGnp59TL4Qu9g7kGztSG1NhV9vPqgt3fvzjdoR8pI8dzJ55Baq6gR4O3ijfNPnIeHs0cnW+rm7my9KXvNJb4qHh9GfYhqQTUm9JyANbevQYB7gNVev/0sh+bULG62yH61kcglWHphqXJowYw+M/DLHb/AzUn/6dNXXF2h7HFem7gWG+ZuwOReky3SXkOwYLtkTRWpXAoWLFydtM9uQwixHjkjxxvn3lBmUv2e/Du23but2xV37orHU22uV17H4dzD8Hfzx39G/Qe9vHrZukkWw7Istt/YjkO5hxDoHog3x7+JcT3HWbUNVfwqZaCoVccamp3rXkPOaRga0ctv8ocM3IICEfaOMotso4JXgQcPPYjnIp7DPfvvMfgkVS+qN7kN5bxy3Lv/XiyOWIy799+NzSmbDdo+qjRKGSgCAJ6Uhw3JG0xuV3iPcIPWZ1kWUaVR2J6+HbkNuSa/vqEYlsF7F95DtaAaAJBQnYA1CWtM3q89XAhbO5h8ueyySg2KK+VXcLFE/xmB6oR1KkMTxHIxdtzYYdY2dkbbZ9bVjrUsy2Jj8kbM2D0DM/6ZgTXxa7rceyDEEaXXpasMuWsUN2J/tmHDjh2BPZwjzSGpOgmvnHkFh/MOY9uNbVgcsRhCmbYZuOxXUnUSXjz1Ih498ih2ZezSul5EYQR+jPsRuY25iK2MxWtnX0OzxLodU+2H3BP9ULCI6CWGGaX1OY0Frum6khCNtt3YhlJeqfLx+qT1ZgkAGeLra1+jWlitfPxr4q9oFKlPXarNO5HvqC37K+0vk9tl6LCj765/h/+e+y9+iPsBjx97HNHl0QZtz7IsjuQdwbJLy/BH6h8GzySWWpuKOlGdyrIDOQcM2ocux/OPY9mlZdicshkimXXrOVk7WPRt7Ldqy1bGrNR7+7NFZ9WWRZZEGtyOvVl78cTRJ/DiqReRUJVg0LZag0VdrPMkqSYJ65LWQSgTQiQX4Y+0P3C57LLB+6kT1iGhKsHq311HJGNkRs90aC+SqpOwPX272Wet4kv5Zt2fPdN0nt1+Y7sNWkLMYXPqZsgYmfJxGa8MF0ouWL0dOzN24rEjj+Hl0y8b/PtsEjfh1TOvIrYyFtkN2VgVuwrnis5pXLfjOZ0v5SOiIELjupElkdiXvc+gtlhP1zqnm4qGoREzcIwIvyUJpAJk1mdiSMAQ+Lr62ro5NsGyLPbn7MefaX9i7oC5eGPcGwYPbxBIBYgqjQJPysOcfnMQ7BFsodZqx5PwsCNjB0pbSjG3/1zc3v92vbet5FdiZ8ZOlWUsWBzNO4rnbnnO3E3VKqo0Sm3Z7qzdeC38Nau1wVQ8CQ97MvcoH8sYGXbc2IHhAcOxN2svAt0D8fDQh3V+x3bc2IEf4n5QPs6sz8QPt/2gdf2OdA3VkjJS/BL/C84Wn8WooFH43+T/IcQrRK/9MmCwJ3MPvrr2lXJZam0qfr3jV7V1LVUL53rldYzfMR4z+sxAiGcI3JzdsHD4QgzwHaB1m3JeORpEDUbVsKoR1KgtaxTrH8A0x+dwseSiysVs6tlURDwagUD3QL2215Z909WCRWsT16ot+zn+Z8wKnaX3Pg7mHMTn0Z+DBYsg9yD8cc8f1q8h5SC2pG7BLwm/AABeGP0C3pnwjkHf99Zzb3xVPEYHj8bC4QvhzLXu5f+ujF1YFbtK+fjL6V/i4aEPm2XfpwtPm2U/XQHVPlNwlM9B07XYsfxjuHfgvWZ/LZZlkdOYA2eOMwb6DVR+hhEFESqdNWm1aTjz2BllDUYZI8Plssso55VjVt9Z6OPdB3JWrry2Opx7GAKZQOW1for/CXcOuFOtDZqGzSfXJGtt8xdXv0CIZ4hB557ObE//f3v3HSZVdf9x/H1mti9L7yCiFAXFig0rYo/YDfxsGI1GTSzRJCSoiTUxsSuxK9jFAkGwIoqCCEpvSq+7tAW2zu7U8/vjzg5bZnZntsLyeT3PPLN77z13zsw9c+6d7z2lHoKr5ccsspbm/jtYwSKpFWstY2eu4+OFOXTzBSGz0gZqWhSxYNsCbvrqJor9xSS7knnytCc5db9Tmzpbjf4D5r4f7ou0uhizZAxjloxh8Yj472D4g35u/upm5m1z7vY/v/B53jz3zUYf3PHWr29lztY5AHy8+mP+c8p/4jqxP7fguZhdtSo3w8335rPVs5VOGZ1oldoKgNyS3IS65TG4sYgAACAASURBVMSyNHdp1OUTVk5gS/EW+rTpw+V9L68QZAnZEIFQgEmrJ1WYeauykkAJj/30GHO3zuWQ9ocw8tiRVYKj3qA3ZpAlZHf3A8/35vP2z2+zuXgzZ/c8m5O6nVRh25k5MwnYQIVlM7JncNr7p0X+f2j2Q3TK6ESH9A5c0e8KhvYaWmH7yl3GPl/3Ofccf0/kM69J0AajLr944sWsytvdLS67KJsp66fw4dAPmbt1Lj1a9mBQ10ExW1It2r6oymxk32z8hkmrJ9Elswv92vUjM9mpdKNdbCbC4/fEXBcIBSp0Dft0zad8dMFHtEtvV2E7ay1Pznsyctf7oDYH8fJZL1cZu2ld/jo+WPEBvqCPy/pexkFtD6oxf8MmD+PJ055kTf4abp16KwEbYNhBw7j+0OsrjLVVHz8enphbcUDvkkAJ41eO57cDfhtX+ph1aoJVrbWWtQVrCYVC9Grdq9F/GC3JXVJlWfnyXBN/0M+/fvxX5PPYUbqD5xc+z2OnPlZvedxXLNi2IBIoAnhtyWv0a9ePc3qeE/c+nlv4XKS78+Q1k1mbv5Z7jr+n3vMai7WWV5e8WmHZq0terbdgUX2N47eniTYwfnPpflVX6wvWN3UWGkyiXX43Fm7k/eXvUxIo4eLeF3NI+0OqbFPgK+DEd0+M/H/m/mfy71P+TbIrmUd/qniDrMhfxOQ1kxl+8HAA7v3+XiavmQzAv3ACvqnuVC7ufTGjjhvF7C2zo+YpXsmu5GrXPzP/mXoNFkXLb+L2rd+4ChZJrXw0L5v7Jy0DoFu0sdj2kO9R2d3973O+p0+bPvzlmL80emuUJ+Y+EWkm7Q/5eeTHR/bJYFG07jk7S3fGfdd+3rZ5kUARwDbPNiatnsTvDv9dwnnxBX0ku5IT/hG2Om91JFBU5tn5zzKkxxDmbJ2DL+hjm2cbC7cvpF/bfgw7eBjv/PwOj82p/kfSS4teYsQhI2iZ0pKp66dyx7Td3byeG/IcPVv15Lzx51W7j2PfPpZOGZ0YfvBwLu97OU/Pe5oF2xfQu3VvhvQYwrcbv+XrjV+TW5IbNX1OcU5kyvVHfnyEMWeP4bAOh3Hb17fxfU58s5Qd+/axkb9X56/m49Ufc/tRt1f4sVOdj1Z+xNX9r+aAVgdw0nu7g0OVp8lNT0qPu1//Vs9Wtnq2MmrGKL7Z+A2X9rmU0fNHk1uaiz/kr7L9XdPu4viux1fI86jjRtE+vT13TrszrteM9cP6skmXVfi/e4vuMffhDXqrLBs1Y1Rcrx/LT1t+4uFZD7M6f3Wt0u8o3cEZH5zBhAsn0LNVz8jyjYUbK3SPWL5rOeOWj6vQUi23JJcRn4+IdLmcvGYy484fR4+WPZwNDFHPG8t2LOPsj86usGzc8nGMW767Vdkp3U+pc9AMYE3+mirLZuXMij9YVA8ti/whPyO/G8mU9VMA5709edqTe9Ug0z9u+bHK9/OLdV8kHCzaWLCRR356hJANceuRt9K/Xezu8Hs6b9Cb0GDtZa7/4voqy/787Z8TChZVHhdv3PJxjDxmJMnu6n+k1ZeSQElkXLcy9fljv7mOp7Vsx7IKP/yttXy5vu6tqPwhP8/Me4YZ2TPo07oPfzn2L2SlZJHiSon7mshay4bCDfiCPnq37l2rgPb0TdOZsn4KXVt05cp+V5KVklVjmmAoyIuLXozUj/ua7zZ9x9PznubwDodzx9F3YK3l2s+ujQwr8PHqj3nnvHfo3aZ3hXTlA0UAU9ZP4ZLNl3BSt5MqDElQZt7WeQw/eDhbirdEAkXleYNe3lv+Hp+s/YTDOhxWp/dUU734y85f4tqPN+hl+qbp5HnzOKX7KXTM6FinfFVrH2sQoWCRJGzF1kIe+Sy+L29Te3bes7y+7HXA+QGXU5TDW+e91ah5mL9tfoX/NxVtIrckt0m6UJXXmLMdxWq98Pnaz7mi3xVx7SNa14jRC0YnFCwqDZRy94y7+Xrj17RNa8s/TvgHp3Q/Je70P235qcqyjYUbOfqto6ss/3j1x/z7p3/Hve+T3j2Je0+4lwd+eKDC8lum3hJX+pJACesK1vHIj49UaFK8aPuiWo2j85svfpNwmmjiDRSVuWhizYPp13YAyCnrp9R4kTl7y+wqd57+OfuftXq9mpQfu6qhbfNs47ovrqvzfgI2wND/DeWbX38TqcPe+rlqnfrfBf/lpsNvImRDvLToJf674L8V1hf5i/hgxQfcNfCuOuepPgJFDSmRYNEPOT9UKKPfbfqOaRuncVbPsxoia1HV9cd3fYxRtKlwE+dN2B0gn5E9g4kXTuTA1vHP+uTxe3h49sNMXjOZC3tdyN+O+1udZ2xM1PqC9dw17S5W7FrBoe0P5YnTnkhotiNfqGHGKSr0F9LWHd+NGmkaawvWVggWlW/lWdknaz7h3V/eJS0pjRsH3MixXY6Nue2z855l7NKxgHNd/Nm6zyLrXjv7NY7pfAwbCzby7vJ3SXIlcU3/aypcrwZDQe75/p5IEGFQ10E8PfjphGYzrXxTbGbOTF4/5/Uag06PzXks6vmmqRT7i3nn53fYVLSJIT2GxHU96Q16efvnt1mXv67GbT1+D+/88g4Lti2ocPxX7FrBBys+4K/H/rVCsKckUMK7v7zLVf2v4uHZD9MypSW/OuBXUfd981c3M//q+VHXlZm4amK16wt9hXyfHd/NxFje+SX2gNjxCoaC3Pb1bZFxK9ultePNc99kv5b71Xnf0dkofzVfChY1Y98HD6G/az1tTFG97nf8vOwK/8e6l1pfthRvId+bT582fRIeAHfM0oqDAS7cvpDNRZsTniq8vgVD0buvVCcQCuAyroQ/g7rwBr1MXT8Vt8tNmjuNN5a9QSAU4JpDrmFIj4r9kQt8BXy1/ivWFaxjm2cbn6z5pMb992nTp9r132z4hmmbplHkK6q2X3O8xiwZE7kzt82zjTun3cn04dPj/gHRkE3ALbZKoEikLt5c9ib/+ek/DbLvCSsncMNhNwBOl8Hq8lA5UFRm7NKx9RIs2tMlEnyJdrwenPVgwsGivNI8souy6du2b43N/OtdPVSTl358aZVlt31zG5MvrnqXO5bzxp8XGYB+wqoJzN82n0kXT6p75uJQ6CvkvV/e45n5u8cZW5y7mPt+uI8Xzkh0mub6V5tzmT/kJ8kkNdl4MTtLd/LI7EfI8+Yx6rhRkdaNzWX8msr+Nv1vDOw0MBJcfGpu7Jk2/zr9r5G/F25byMcXfRzzOrfydXF5131xHZ9c/Am/mrA7wDBmyRhmXzGbjOQMAOZsnVOhtcnMnJlMWT+lSjfv6oxeMLrC//O3zWfFrhXVdk0OhoJ1DhT5g342Fm4kKyWLDhkd6rQvgD9M/UOktfn4leN54rQnOHP/M6tNc+e0O6u9wVH+5sLQCUOjtvwpE21iiPdXvM/7K96P/F/dDbJYAcjP1n1Ggb+A/m33jtacS3csrTDByY7SHYxfNZ7bj7q9gV5xXwgR7aZgUTN2pf9uXIR4NPkFLnUnPpNJ/KKcqOvh3G2t5bE5j0Vmeji8w+E8f8bzcTVVrc5Wz9YmDxYlwlrLcwuf461lb+F2ubnpsJu4qv9VMbcPhoJ8u+lbiv3FDOkxJHKCr86W4i0U+4s5sNWBkQuv3JJcBr8fffDmBdsX8O6v3qV/u/7ke/MrdBlKhNvEHgR38prJ/G3632q131ieW/hchf+9QS9frvuSC3tfCDT9xbBIfVmxa0WDBYrAGUegLFhUXQC7pi6YGwo20KNljwozwuxREqgKYrUgKvQVxn3XfWvx1irLEhnoG+DDFR/ywA8PYLF0a9GNV856he5Zsbs8VlbXLsr1EVSvPGAqJNZ1KRgKVpmpcF3BuoTyUNvPwVrLxRMvZqun6rGs6134phCyIR796VE+WvkR6Unp3HHUHfU23lC88krzOHXc7u77Q/83lHHnj6N/u/5kF2ZXk3LvduaHZ0bGdoy3+3BpsJSPVn7EH478Q61es3ygqMzI6SO5pv81vLDwBX7c8mOV9f+Y+Y+EgkXRumrPzJlZbbDo641fx73/aLYUb+HWr2+NdGu657h7GHbwsFrtK7som192/FJlWILnFjxXbbAopyinxpawZfXODzk/VBsoqg/RZrYt833293Wqr5btWEa3Ft3wh/zkluTSt03fWu8rGn/IH7kRcuWnV1ZZ/8riV5iZM5Nze57LiENG1O91vQnVvE0z0nhNFPZR7wVOa9LXD+Hi2cDFbLFtat64HgWCdf8irc5bXWFK0IXbF9bLtNSNfpc1ikQuQqdnT+eFhS9Q5C8i35vPv3/6N0t3RB+kOGRD3DL1Fm7/5nZGzRjFce8cF3OMmjL/XfBfzvzwTC6aeBFD/zeUIp/TEu2MD86ImSZkQ4xdMhZrba0DReDclbn606urjEkD1DpQlFuSy8RVE/l247cs37mcnKIcgJg/RnOKcij2FzPg9QEc9eZRHPbGYXy8+uOo2yqIJHuLqz+9utFeqy6tHc+fcH7U7p17o1gtiH7Y/EPcXSfrEqgJhAKUBkr51+zdg0tnF2Xz8uKXE9pPcxgDJtbn3Rjv7ZXFr0QNFO1JEgnofbr2U976+S1KAiXsLN3J32f+nY0F8Q9gG8vM7Jk1bxQWrXXiH7/5I+B0qWvOos0gVZMXF71Yr3mYtnEa131xXdRAERB1/L9EVXceufHLG+MeMzCW0fNHVxj/5qHZD+Hxe2q8UeHxe1iauzQyjuAZH5zBOR+dU6EbXZmaJgKYtnFajfn8Pvt7lu9cXqG12N5o2ORhnPTeSQx+fzCXT7qcw984vNb7Kv+bZ7tnO8MnD+eoN49iwOsDqq1Hlu1YxuNzH+ewNw7jz9/+OTJmYl25knfvp8/dn/HEl8ur2Xrvp5ZFDeyZwCUMT5rW6K+7LrR7iuZ1tgunep9kgFnDetuJn9J+3+CvX1jiJ2RDvLbkNaaun8p+LffjzqPvTKiv/mtLXquy7LE5j9V5ivFEp4wt65Ob5EpiUNdBcbXUqU+VZ2wCeGHBCzw7pOoYPou2L6rQFBOI2ToInHEhyg9+ub5gPSe8ewKLRyyOOdNTmc/WfcZ5B1Y/6HJNCv2FLNi+gAXbF3Dv9/dyUreTuGHADRzQ6oBa7W9j4UZGfDaC7SVVp+GOZd62eVVaHN09425O7X5qlVmxFCySvUW0lhn17S/f/qXCeBe1YbE8MeeJmjespQGvD+Cqflcx8tiRFZbne/N5bM5j/G/V/0hPSueGATdETb++YD3bPNviGiwzVqDn7hl3c/eMu5ly2ZSEzoGxePwe3lz2JkX+Iob2GkrbtLb85bu/xAy6jV85ngHtB7A2fy0DOw1kcI/Y54Tq3sfeJNYPT0/AQ2ZyJsX+Yi79+FKyi7Lp1qIb9w26j+O7HB/Xvp+Y+wRXHnwlnTI7VVlnra3Q9WxPVf5ctqt0F9tLttO7dW+enPskY5eOpVuLbjx+2uMc0u6QKrMlAbyx7A3uPv7uuF4rVnl6bclrDOo2KPJ/yIaw1uJ27W5xnO/NJ8+bx3vL36uSPqfYuRHU3GcIW1+wnkPbH1qnfZQGShk9fzTLdi6rp1zVbPzK8UxYOYE2aW34/RG/Z/+W+7Mmfw29W/euOXE5IRvih80/1Dk/E1dXHX/nuHeOi/xdNl5TeX///u+R2fYykjK4+fCb4w4ElwRKGDphaGT7D4d+GPXGaDQjPh8RmRhHYPjk4XRI78C9x9/Lbd/cVmHd776Kb9zSz9d9ntAsbdVJylxDWpcPKN18CeDmhW/XcOdZNc/uurdSsKiB5RB7EOM8m0lr0zCVwaOBik0rvaQwxx4MwJ/9N/Jo8ksN8rplFrqW8+ayNyOD2y7ZsYRfdv7CsIOG8fKilzm47cE8dNJD1Q7yXFOLmNpKJFiUV5rHtZ9fG2n+e1iHw3jlrFfqPEhmInc3V+5aWWXZtE3T8Pg9VQJX5WckisekNdHHb1ixa0Vc6W/9+taEXq8mM7JnMHfr3IQG/84uysZt3ARCAcavHJ9QoAhg1uZZUZd/tPIjRvQfUeHC1aXGmCIRNQWKBrw+IK79LNlRdar2+vTWz2/Rr10/Luh1AV+u+5KR340kYHffTS4JlMT8gb+leAtDPhhCtxbdmHzxZFbuWsmvJ/8agD8N/BNX9rsSi2Vt/toaB3Y+80One8IFvS7gvkH3kexKxlrLpsJNpCWl0SGjQ7U/fN9f/j4PznqwwrKygWprcv8P9wPOj/zjOh/H6CGj+XL9lzy/4Hk2FW3i5G4n88CJD9A+vX1CwaI5W+ZEBsMf0mMI9xx/T8z3sHzncrpndSczOTPu/Vc24PUB9Gvbj3Hnj6s2eB/rHHb9F9cz9pyxHP/O7sBQdlE2N3x5A8d3OZ5L+1zK6T1OJ8WdEvN9jFkyhjFLxvD8Gc8zqOugCgGOtQVra3wPT819it8O+C0tUlrE3Gbq+qm8+8u7Ne6rzPRN03l49sNc2OtCbjr8pshnE+ta46T3TuLVs17l/h/uZ0Phhirrs4uyGT55ON8O+zbq3fhlOyoGHfwhP1uKtpCenF7l/B2y0Vuaz94ym7FLxjI9e3rUFivJruQaW6xsKNjQLIKb1Zm1eVatbqCd9eFZuIyL7KLG7ab33abv+P3Uijelv9n4TY3pDIbNRZuZtXkW3bO6M7DTQIwxMa/Rolmau5ThnwyP/D/xwomsylsVV+vX6764jgcGPUCnzE78bkrVAIQn4OHxuY/XuJ+n5z1Nj6we/H3m3yssv2zSZaS54+uOrEBRVdtLtlcJFCUqVq+M2khuPZdgaTf8uwbhq4feNHsys6c3Nx44cKCdM2dOzRvuoXr+9RNeTn6cM91zKyyfFjyc5wMXMC71wRgpa+93vjv4IhR7JoSu5DIzLf4v3PjgSdzpjz0j03mdH2B6m9rdxV48YjEvLXqpwkxXV/W7ipTSAl5bG70r0IQLJjBpzSRaJLfgyn5XVtvSJ9qPladOe4oh+1ccnDkQCvDiohd55+d3SEtKY9Sxoxiy/5CoF+ePnfoYSSYJjDOtsQsXk9ZMYk3+Go7scGTkrm3Ihlidt5pLPr6kSh6+uPQLurboCjhjKzw460FmbXamaB7aayjTN03Hbdyc0v0UjnjziKjvLdmVzH9O+Q9n7L+7u1i8P84A7jvhPuZunRszYCQiIlLms0s+IzM5kzZpbbDWcsvUW5iRXXU8xDP3PzPmoKpJriQeOfkRzu55NgW+An7I+QFf0MeBrQ4kyZVEr9a9CNlQ1BkmK/vvkP/Su3VvurboygsLX2Bz8WZCNhT33fv61L1Fd47oeATfbvw27m5REy+cyNilY5mwagJdMrsw6rhR7CjZwRfrvqhzS4oHBj1AyIbwBDwNNnbZFQdfEXMmo1aprRh5zEjcxs1Li16Ke7wd2Xud0OWEemkBJLK38az6G6sfjG9m5z2VMWautXZg1HUKFjWsiQuyef2L2YwvqTgN9Xnef7LM9uQC1/c8k7K7L/ZrXMSsA2/lm2XZBHDxB/f/uCv5w8j6KcGj8ZLM2a6f2EkWYwPnUEoyJ7mW8Ivdj9GBiyih5sj1urT4C/VhpS9TQOw7gXUJFtW37i2686+T/8UHKz5gyvopcY0TcXqHo2mfvYD3U3Z3u3Jby9ctjuHU4sTL3lX7n0uH9gfz5Nwnq93ulsNvJrsoJ2rT2NpIT0pPaErxbkHIjj2+tIiIiIiIiFSjbCD6vZWCRXuKou2way10HgDJ5boxbVlM6YqvSe5yKO7ep0P5ptXWEpj3FmbdDFzdjsAccwNB4+bjhdnkFfton5XGAe0zObhzFkluF0c+8CW7PBWb7d4+pA+DD+7ID6t30KtDJvklfi6fHF//58AFz+M64v9YsCmP575ZxVc/b6NVejK/O/VALjqiG1lpSTw0djCfpseeOllERERERESkuVGwqAk1q2BRIwsEQ1gg2R2lr+59raoui+a+moNAj749hDcCDTu9o4iIiIiIiEhDyQqGGJezmd927kROcnzj3DbnYFGDjtZqjOlujHnNGJNjjPEaY9YZY54yxjTuPO77qCS3K3qgCGBoHLN1HB/frGlTA/UzFaHIviQj1LwHxGvOBnni6+7ZNlj9jILpoRAXFhbVKg/tAsG48xHLwJJSTvaU8Mi2XO7J3cmQYg/vZG/h8oI9Zyrqvl4fn27M5ve78mgbDHJWkQb+FBERkfqzv9/PJxtzWLx2AzM3bGK/QJDPNuXElXbkMSNr3mgv1mCzoRljegEzgY7AROAX4FjgduAcY8yJ1todDfX6UoOjR0DJTvjqvtjbdOof166yCdS8kcg+4N7cnbzWqiXZMe5EzF63kVJjaBMKYYDZaanc1qkDHpeLDoEAYzZv46vMdJ5q68TTOwcCnFdUzJGlProGAlzavUujvI8nt27njHKBiBDwTUY6q5OT6RAM8lC7tvhc1U9XfEV+IXfu2sX81FQ6BIMc6A9UmFvIBxS7XEzLSGd5Sgpvt8qqkP5UTwmtgkGuKigkhCFgYIDXF7nDYYHVyclcXMNn8uuCQk4oKWVSi0x+SUlhYGkpVxcU0tfnZ2pGOluTkjjI5+Ngrw+Py8XrrbKYmZ7G6pSUCvtpFwhySVER1+YX0DJkKTGGF1u35NXWTivNP+3YxVUFhdRmGLD7c3fyaYsM8l1uzij20DkYpMQYXmnVkpUpyRzm9TErPY3Z6WlkBUP8fcdOzil2xolblJrClV1rNx37w7k76BrYHdAaFg5cDdjho5ffz9NtWnNSSSl+YFpm7IkEGsp1efn8cZfTuvWmvAJuyisAwJO7k3+2a8Ps9DT6+vzctiuPg3x+BhzQo9HzKCIiInuv97K3cIjPV2V59Ve5u13V/6r6zdAepsG6oRljvgDOAm6z1j5bbvkTwB+BF621N9W0H3VDayTjb4RF43b/b9wwch2ktawxaSIzcMm+YfFaZyreABAwBoNlYM/m+UOuTTDIdxtiT03rCY9BllEPde0Wt5sxrVqyPcnNeUXFnFRSyqrkZG7s3JHCcCvC9oEguUm7QxY378qn0GXYlJREf58PvzG0CjrBqlJjOLa0lG6BADPS09nldnFGcQk9AtUHgAuNYW5aGl9lppPvcnGU18s1+YVMy0hnQWoqJ5aUcHypN+H3l53kZk5aGqd6SmgdR8srCxwWJUAwIr+Afl4f5xZ76tR81mvAWEipedNGkedykRkKkVxpeW2DJGXf05qEgMObIBAzd+2GhD77q7t0YkFaaoPlR0RERJqX6q6Fbu3YvtqbZRMvmsiBrQ5siGw1qkYfsyjcqmgVsA7oZa0NlVuXBWzGCdh1tNZW26ZcwaJGsnUpjD3faW0EcOpfYfDf4kr6+aNd+HPH9g2YOdmb/HtbLucVV50db0FqClfXsgUEwP825XBR9651yVqD+GjTZvr6/TVv2Ih2ulwsTk3hIJ+fzjV0hdrbRQuUxBsEaS5y3S4G9+ieUJpEAzHLU5K5rFvjtGwDeGbrdgYn2M0uBAzr2plfUveU8J6IiIjsqWas30irUOxYSJ7Lxf3t27IwNYX9/QE6BoN82iKT84uKuWvHLtqHQnDG/XDSHY2Y6/rXFMGi3wIvAy9Za38XZX1Zq6MzrLVTq9uXgkWNyLMT1s+EtgdAx/4VZ2WrRvCJQziiXYMOfyV7kR/XbSQ9Rr1Sl24ii9duoMBlOHH//Wq9j/p2b+5Ofl3LMWekfniM4aT9u+M3hv5eL09vzW32AbJofMDoNq3ZnOSmayCAC5iZnsbRpV6uyy+g0OXCbamx1Vh1PMbwXssWLEtJ4aKiYg7x+siwIVKt0wqr1LiwwOg2rRjX0ulW+PtdeZzqKeHaLp3wuFz08vkYn72FALAtyY0FWoQs93Zox7cZziyhj2zL5VdRAs61YYHtbjeZoRDTM9KZnZbKMaVe+nt9GKB7+LPyGEOytex0u5mamc7KlBSSrOWjrBYEyp0L08Mt3vp7fVyfX0D3QIA1ycns7w+Qk+QmxVqO8PrYkJTE/LRUHmrfFoAefj/vZW8hJymJBWmpnOIpwYXTlbJlKES3QIAdbjf/ateGIPBg7g52ud20CIVwW2gfDJJhLTlJblYnJzvvyVr6+nw82K4tc9LTInm8Pi+fIcUldAwGublzB1ampHCw18c1BQUc6vWxODWV/f1+DvX62O52EzLQLhjk+3SnpeDS1JTI8YtlP7+fjcmV27hVlBUMRVo8VtYiFCIl/HnHY0CpFxewMM6WYxcWFpHrdvN9uEwd4vWyNNVJ67aWjJCN5K2Pz8fKct1Ozy0q5rMWmTH3/eWGbB5o35YZGekxt4mmQyDAxYXFvNQm9gQjnQMB/pG7k3FZLeLq+nl+UTGrkpNZnZKMy1q8Luc9Her1siQ1/lZ2nQMBbtuZR7tQiA+zWjAlgW6nGaEQvX1+FtVwbI4rKWV2uXJak9bBIKd4Svg4q0WF5amhEF6Xi5M8JSxPSabA5eKYUm/M45EVDJFqLaUuQ5HLRZdAgFc3b2V+Whq7XC4Ge0poFQrxcuuWLE9JZoDXx/CCIlKtZVVyMgf4/XhchimZGXyVkUGnYJD9/H5+Tk2hn9dHVsjydNvWABxVWsroLdt5q1UWz7Vxlh1dUsri1FR8LsOZxR728/u5Jr+QJCxLUlN5rnWryGd3fEkJQQxnFHu4qKiYVSnJrE9Ook0wxHOtW7Elyc1tu/KZl5bKj2lpdAsEOKGklB1uF0tSU6u0rOzmD+BxGdJDlouKihhUUsrHLTL5IKsFtoZr/PRQiBKXi+NKSvlH7g5KjYuXW7eMfDc6BQL8aWde5GZxkrW4reVXxR5O85SwJjmJnv4AXmMYGd6mRSjE9XkFdAoGcFmnK/qD4ToymsNKvZzu8dDH52djchKvtWrJtqQk/rpjJ8+0aY3HVbV+eWrrdhalpvBa69jfsx5+Pxuqqb8GF3u4Lr+ARampPNqu5mF2D/F6ubCwmDahEE+1aR0ZimBg2dEFpQAAGwtJREFUSSkel2FVckqk6/6vCwq5pLCINqEQPgyz0tPIc7vITkqij8/PYE8JHmPwuJwW3N0CAc4o9uBxGUqMixUpybzTMitStwGMzdnKV5npvNVqd2+QrGCIIR4P/8tqwQWFRTyQuxM3EAR2uV0EMIzPakGStZxT7CErFOLn1BRSQ5YjvV5CwJrw+anA5eLvHdqyNDWVfl4f6TZE6/D3alVKMucVeejt8/NzajLHlng5wuvFDRS4DEnWaVm/KcnNxqQkDvL5aRUKUWoMqdZGxsMJAHlu5xqibTAU6dLvMYadbhddAkGmZGawJjmZE0tKONxbtdsYgB/nPJFkLYd4fSQBxcZQ6nJa1fuMIcXaKi206yyOCaH2ZE0RLHoU+BPwJ2vt41HWjwZ+D9xirX2+un0pWLQX8BXDP7uyy+Vih9tNh2AQrzF8nplBwMBZxR7aBEO4gHRrscBnmRlMyMokM2Q5tqSUrFCIIZ6SSFedIDCmVcvICbhMb5+P3+YVMD0jnXbBIOcUebiim9NapUsgQFd/gLnhi5HDS71ck19A+2CIgIEf09LY4XaR53ZT4HLhNzA/reYLl35eH3/YlcfvO3essm5YQSEH+vz8K8rJruz17+rUocK+bsjL50ivly8zMiqkO9jro2UoxBPbtuNnd9elEJBpLQbIdxn+0qE9i1NTuSc8bsm65CTWJieT63ZHuhP19PtpFwzyXJtWrApfBHcIBLioqJj9/AEebtcGr8vFFfmFXFFQSOtQkE1JyWxMTqKn38+BPj/LUlP4T9s2bEtyszXJqc7v2OmMy/JlRgajOrZnf7+f3j4/UzMzcFnLZ5tyKoyBUtnSlBSu6NqJUJyBSIDntmzj5JLSCssWhPO2uBZdTjqGL9jXJydxgD/A8+EL97dytnC414fHGFakJFPocnFUqZfMcJksNYZiY5iblkqGtQwqKW3YGQJE9iEW54IuCUjbw2dpFZHqhYAFqalY4EivN+a50mMMBmLeYBIR2SsoWJTwC74E3ADcYK19Jcr6h4FRwChr7b+irL8RuBGgR48eR69fv77e8yj1bOtS+Gwk7FgNhfGNHl8nncLjJLmTIGd+zdunt4UjroAfRlddl9kRznwAeg+BOa/BL5NhSz1NgXjuo84+t/9cdV2/C6Bdb5jxxO5l5z8Jk/+Y2GtkdYHCzVWXn/JnOO5mmDsGvnsMehwPWZ2hIBtO/hO8cUFir1OeOwWClaL6A6+H5HTn89u1LmZSP1ASvtNVJbKfkgW++p+JyY8T7EkvdxcjYtBtkL8Rlk5IbKdnPQTeIgh6YcaT8aU5437o2A9Wfw0bZsFB58G0fzrrkjPAH25N0fEQ2LY09n5+953TEvDNi6Kvb9cbepwASWlQsgvWf1+xjPQ5C7Yvh7xE6lYDB//KOb4A+x0P7mRYNz365ultoUVHOPEO2LEKpj/mLE9tBW17Qt7G3d1eAdr2gp2rK+6jyxFw6avgyXW+uz9Piv5avU6HTofCzCizPB50Hhx1DaycAnNeLZdmCKyu1LD18Ctg4G/g1TOjv06rHs57rpxPgGFvw8ZZkLMADjgVDjwVtv8CU/7uHIPyBt0GnQ+Dn15x0riS4cDTnFadP74U/bXB2ebQywALLTrBO7+OvW1lPU+Grkc6dVtyBiz/pOL666c45aY0D4J+mP2CU3eVd+ilsOSj3f8PvN5JM/OZ6HVQfTn5Lphe5b6TU4f+/PHu/zM7QPH2qtsdcSUseLvh8nfsjTD/bfA3g5naep8J2XOd72ZqK/DW4gI4vU3VMr83c6c69fw+xeCEcPdyKVlw3I3R64+6Ss6EE37vnFc8jThfT6cBsLWaa9TMjnDQuTDv9cTTVufE251rnvLn0eau7YGwc030dQMuh8UfNG5+quTh17D4/fi2daeCyw0pmdD3bJj/VsPmbV/iToV7tzV1LupkrwsWlaeWRc1AKAgYKN9c1F8CAS+ktqy4fE+Uu9L5Ud2xP7Ssw5g51joX0O5kSK2+iX+jCIWgaKtz4igbyLxwq/PDvE1PZ/meytq4u0nuE/I2OGWrfV8nYFefgn7n807aA8aB8RVDab4TiAr5wZVU/+8XIOCDTT85QdHWPZzva0odZwML+gHjBLj3NmXXCXX5zoVCYIPOMTPGCVaunOIEsLse6Vx0J6fDYcMhqxMUbQNvIbTrVXE/AS/YUMMc91h2rYeF7znl4OhrAVv7+jFW3RXtPFmet8jpJt6mJ3ToW3F/NuT8CKhOwOvczElvXbfzWEMpyXMClS06Q3KcXZX8pTD7eeeHev+LofvRDZvHWAI+J2hpQ9BvaHxl0+dx6rC02F1lAKfsBX1OMD1a2bDWuQGUlAaZe8jYkSV5zjHJ6rznXEdY6+TJ5XaCmeXlbXSuSdv1rvgZ71rvBE079IuvTOZtcF6jXR9IbVF1fSjkBOlLC6DvOZDZLlwvhr+/TXFNU5LnXAdmda65LJaxFgq3OJ9J5c+yqSR6TejzOPVNWmvnmjwUaPhzir/EOeclpTpBeZfLuZ7x7ICMds71hjul5rq8slDQuf5LTq/9923Nt7BqCvQ9F3qe6OzTW+DkOWc+LHzXKR+D74GWMcYu9BbCvDdh7XdOgK1DXzj7n841VHUKcpxJlbI6VVwe8IVvWmQ5+96y2LnpVf67uHmRcxy7DXSu0XzFzk3F7HnQ/wLY/8TY5SIUqlqnbpoLu9Y61yTgvJfJcYxFNCpnz6nraknd0ERERERERERE4lGwGV4Z4gTlo7lnmxMA3MtVFyxqqFucy8PPfWOs7xN+XtFAry8iIiIiIiIikriWXeDOZU2diybVUP1/vgk/n2WMqfAaxpgs4ETAA8xqoNcXEREREREREZFaaJBgkbV2NfAl0BOnu1l59wOZwJvW2mYwGqSIiIiIiIiISPPRkCNt3gLMBJ4xxgwBfgaOAwbjdD+7uwFfW0REREREREREaqHBpqEKty4aCIzFCRLdBfQCngaOt9Y24jyTIiIiIiIiIiISjwadw9dauxH4TUO+hoiIiIiIiIiI1J8Ga1kkIiIiIiIiIiJ7HwWLREREREREREQkQsEiERERERERERGJULBIREREREREREQiFCwSEREREREREZEIBYtERERERERERCRCwSIREREREREREYlQsEhERERERERERCIULBIRERERERERkQgFi0REREREREREJELBIhERERERERERiVCwSEREREREREREIhQsEhERERERERGRCAWLREREREREREQkQsEiERERERERERGJULBIREREREREREQijLW2qfNQLWPMdmB9U+ejHrQHcps6E7LXUvmR2lLZkdpS2ZG6UPmR2lLZkdpS2ZG62FfLz/7W2g7RVuzxwaLmwhgzx1o7sKnzIXsnlR+pLZUdqS2VHakLlR+pLZUdqS2VHakLlZ+q1A1NREREREREREQiFCwSEREREREREZEIBYsaz0tNnQHZq6n8SG2p7EhtqexIXaj8SG2p7EhtqexIXaj8VKIxi0REREREREREJEIti0REREREREREJELBIhERERERERERiVCwqAEZY7obY14zxuQYY7zGmHXGmKeMMW2aOm+SOGNMO2PMb40xE4wxq4wxJcaYfGPMDGPM9cYYV6XtexpjbDWP96p5rRHGmB+NMUXh15hmjDm/mu3dxpg/GmMWhfO10xjzqTFmUDVp0o0x9xtjlhtjSo0x24wx7xtj+tXuE5LqhL//scrClhhpBoWP487wcV1kjLnDGOOu5nXOD5eX/HD5mW2MGVFD3hq8vEntGWOuraEuscaYYLntVffsY4wxlxljnjXGTDfGFISP81s1pGk29YvKVN0kUn6MMX2MMSONMV8bYzYaY3zGmK3GmInGmMEx0tRUh90UI13Cx9UY09Y419rrjHPtnWOca/Hu1aTR9XotJVh2mt25qTblTRwJlp2xNZQda4yZWimN6p16oDGLGogxphcwE+gITAR+AY4FBgPLgROttTuaLoeSqHCl8jywGfgG2AB0Ai4BWgEfAZfb8JfKGNMTWAssBP4XZZdLrLUfRnmdx4C7gE3Ah0AKMBxoC9xqrR1daXsDvA9chlO2JoW3HQakAZdaaydWSpMKTAVOBOYAXwP7AZcDPuB0a+3seD8bqZkxZh3QGngqyuoia+1jlba/EKdMlQLjgJ3AUOAg4ENr7eVRXuMPwLPAjnAaH0656A48bq39U5Q0DV7epG6MMUcAF8VYfTJwOvCJtfb88PY9Ud2zTzHGLAAOB4pwjt/BwNvW2qtibN9s6heVqbpLpPyEf9APA5YBM3DKzkHABYAbuN1a+0ylNNcCY3CuhxdEycJka+2cSmkSPq7GmHY41959w9v/FH4vFwLbgBOstWsqpdH1eh0kWHZ60ozOTbUpb7JbgmXnIuCIGLu6GjgQ+HP5a2nVO/XEWqtHAzyALwCLU4mVX/5EePkLTZ1HPRI+pqfjXEy7Ki3vjBM4sjgnoLLlPcPLxibwGoPCaVYBbSrtawfOhX3PSmn+L5zmeyCt3PJjAC9ORZVVKc3fwmk+KP9+cCo2Cyyt/D71qHP5WQesi3PbluHj5gUGlluehnNyscDwSml6hsvHjvJlBGgTLk8W54TV6OVNjwYtVz+Ej8cFlY6f6p596IFzgdkHMMBp4c/yrRjbNqv6RWWq0cvPtcCRUZafivNjygt0iZLGAtcmkKeEjyvwYnjd45WW3xZe/nmU19H1euOVnZ40o3NTbcqbHrUrO9XsozXgCR/X9pXWqd6pj+PU1Blojg+gV/hAr41SoLJwIqjFQGZT51WPejvmo8LH/Nlyy2pzUnwjnOY3UdY9EF53f6Xl34WXD45nf+FKeX14+QFR0sTcnx51KiPriD9YdF34GLweZd3p4XXfxlM+qttfY5Q3PRq0TA0If96bAHe55ap79uEHNf9gazb1i8pU45efGtJ+SaUbZ+Hl15LAj7baHFegBc6PxiKqBgJcOOdgCxxYbrmu1xux7DSnc1NtypsetS871aS7NZzu3SjrVO/Uw0NjFjWMsj7bX1prQ+VXWGsLcSLdGcDxjZ0xaTD+8HMgyrquxpjfGWNGhZ8Pq2Y/p4efP4+y7rNK22CMScO56+IBpseTBqeS6gGssNaujTON1I9UY8xV4bJwuzFmsIk+Pkh15eA7nOM9KNxcNp40sY5pY5Q3aTg3hp9ftdYGo6xX3SPRNKf6RWVqz1LdtRDAEcYZF+uvxpirqxnPozbH9XggHfg+fK0dEb4W/yL8b/lxlXS93jSaw7mpNuVN6t8N4eeXqtlG9U4dJDV1Bpqpg8LPK2KsXwmchdO3cWqMbWQvYYxJAq4J/xvtZHZm+FE+zTRghLV2Q7llmUA3nPFrNkfZz8rwc99yy3rhjBGwxlob7eIsWpp4ymflNFI/OgNvVlq21hjzG2vtt+WWxTxG1tqAMWYtcAhOH+2f40iz2RhTDHQ3xmRYaz2NWN6kARhj0oGrgCDwSozNVPdINM2pflGZ2kMYY/YHhuD8SP8uxma3V/o/aIx5BbjDWltabnltjmtDpdH1ev1rDucm1T1NzBhzAk4L6xXW2m+q2VT1Th2oZVHDaBV+zo+xvmx560bIizS8R4BDgU+ttV+UW+4BHgSOxhnXoQ1On/5vcJpbTg2fCMvUptw0VhqpuzE4F9KdgUycE9yLOM2yPzPGHF5u24Y8rq0qPavs7J1+jfM5f26t3VhpneoeqU5zql9UpvYA4VZobwOpwH3W2l2VNlmL013kIJzzX1ecOmwd8DvgtUrbq/w0T83p3KSy0/TKWle/HGO96p16oGCRSB0YY27DmaHhF5zR+COstdustX+31s6z1uaFH9/hRItnA72B3zZ6pqVJWGvvt9Z+ba3daq31WGuXWGtvwhnMLh24r2lzKHuZsoukFyuvUN0jIo0l3JX6TZzZg8YBj1Xexlr7rbV2tLV2Rfj8t9la+wFOd4xdwP9VumEizZDOTVJfjDGtcAI/PmBstG1U79QPBYsaRuU7bJWVLc9rhLxIAwlPI/w0zvSxg621O+NJF24WW9Zt5JRyq2pTbhorjTScF8LPjVUW8is9q+zsZYwxh+CMybAJ+DTedKp7JKw51S8qU00oHCh6C2da6feBq2x4lNZ4hFtFltVhqpP2UXvpuUllp2ldhTOuz3hrbW4iCVXvJEbBooaxPPwcq59qn/BzrL6KsoczxtwBPAsswQkUbUlwF9vDz5HmttbaYiAbaGGM6RIlTbRysxpnzJIDw2MnxZNG5XPPUqUsUM0xCh/nA3AGEF0TZ5ou4f1vstZ6oFHLm9S/mga2ro7qHmlO9YvKVBMxxiQD7wLDgXeAK2KMEVOThM6BYfVVFlR+9hx727lJZadplQ1sXaV1dZxU78RJwaKGUTbI1lnGmAqfsTEmC6eprgeY1dgZk7ozxowEngQW4ASKttViN2Uj3K+ptPzr8PM5UdKcW2kbwgOzzcSJrp8cTxqcE+kGoK8x5oA400jDiVYWqisHp+Ac75nWWm+caWId08Yob1KPwjO9XI1zMfxqLXahukeaU/2iMtUEjDEpwAc4LYreAK6uReC6zHHh5/J1Um2O6yygBDgxfK1dPr8unK5OsPsavfzful5venvbuak25U3qgTHmOOBwnIGtp9VyN6p34mWt1aMBHjhT5Vng1krLnwgvf6Gp86hHrY7rveHjNwdoW8O2RwGuKMuHAKXh/QyqtG5QePkqoE255T2BHeF0PSul+b9wmu+BtHLLjwG8wDagZaU0fwun+aB8HoELw8uXRsu7HrUuN/2AzCjLe+LMemCBUeWWt8S56+EFBpZbnoZzEWSB4ZX2dUC4fOwoX0ZwBpBcFU5zQlOUNz3qtSxdHf78J1WzjeqeffiBM1CsBd6Ksb5Z1S8qU41eflKBT8LbvBLPZ1u+nJVb5ip37LbXx3HFaWVggccrLb8tvPzzKPnQ9XrjlZ1mdW6qTXnTo3Zlp9K2r4a3vauG7VTv1MPDhDMm9cwY0wvnoqsjMBFn+tnjcAbVWoFTGe5ouhxKoowxI3AGUQvidEGLNor9Omvt2PD203CaEs7EGVsE4DDg9PDf91prH4ryOo8Dd4bTfAikAMOAdjiVyuhK2xucsQIuwxloe1J422E4F/+XWmsnVkqTihMZH4QT+JoK9MC5S+gDTrfWzq7xQ5G4GGPuwxkI/TtgPVCIM73rr3CO0afAxdZaX7k0F+Ec/1LgPWAncAHOrA4fAr+2lSpwY8ytwDM4F1DjcI7lZUB3nJPYn6LkrcHLm9QfY8x04CTgAmvtpBjbTEN1zz4lXF9cFP63M3A2zh3T6eFlueW//82pflGZqrtEyo8xZgxwLZALPIfzw6ayabbcHX9jjMXptr8Qp1tRK5y754fi3EG/2Fr7ZaU8JXxcjTHtcOq9vuG0P+LcrLkQJ0AwyFq7ulIaXa/XQYJlZxrN6NxUm/ImuyV63gqnaQnkAElAd1vNeEWqd+pJU0ermvMD2A9nuuzNOAVsPfAU5SLjeuw9D5zZqmwNj2nltr8emIwzRWMRzt2MDTgX2SfX8FrXAj8BxTiBhW+B86vZPgn4I7AYpznkLpwAxKBq0mQAD+C0bPHiRNg/APo39Wfd3B44U8O+i3PRkgf4w5/3FOAacAL3UdKdGD6Ou8LHdXH4OLurea2h4fJSGC4/PwEjmrq86VEv5ahfuJ7ZWEMZUN2zjz3iOD+ti5Km2dQvKlONV36AaTVsa4H7Ku3/0fBxz8EJUHpwzoejgQPr87gCbXEmH1mPc+29GWeK7O7VpNH1euOUnWZ3bqpNedMj8bJTLs3N4XXvxrF/1Tv18FDLIhERERERERERidAA1yIiIiIiIiIiEqFgkYiIiIiIiIiIRChYJCIiIiIiIiIiEQoWiYiIiIiIiIhIhIJFIiIiIiIiIiISoWCRiIiIiIiIiIhEKFgkIiIiIiIiIiIRChaJiIiIiIiIiEiEgkUiIiKyTzLGjDfGWGPMndVsc4wxxm+MWWuMadmY+RMRERFpKsZa29R5EBEREWl0xph2wGKgLXCMtXZxpfUZwHygN3CqtXZG4+dSREREpPGpZZGIiIjsk6y1O4DfACnA28aY1EqbPA70BR5RoEhERET2JQoWiYiIyD7LWvsFMBoYAPyrbLkx5jzgJmAucJ8xJskYc4sxZpYxpsAY4zHGzDfG/MEYU+V6yhhzrTHmI2PMGmNMSTjN98aYq6LlwxgzLdwlLsUY83djzHJjjNcYM7ZB3riIiIhINdQNTURERPZpxpg0nKBQP+BMYCGwBMgCjgLWAJOAs4HlwDSgFBgMHAa8Za29utI+S4Cl4f1sBtoB5wHdgIestfdW2n4acCowGTgG+AzYBmyz1j5ez29ZREREpFpJTZ0BERERkaZkrS01xlwJzAZeBxYBnYBbrLXLjTH34QSKRgN3WGuDAMYYN/AScJ0x5kNr7cRyuz3UWru6/OsYY1JwgkB/Nca8YK3NjpKd/cNpc+v3XYqIiIjET93QREREZJ9nrV0A3IvT8udc4BNr7fPhLma3AluAP5YFisJpgsBdgAWurLS/CoGi8DIf8F+cm3VDYmTlXgWKREREpKmpZZGIiIiI4zHgj0Bn4M/hZX1xZktbCdxjjImWrgSnC1uEMaYHMBInKNQDSK+UpluMPPxYm4yLiIiI1CcFi0REREQAa23IGOMN/1sSfm4Xfu4D/KOa5C3K/jDGHIgT9GkDTAe+BPKBINATGAFUnnmtzJba5F1ERESkPilYJCIiIhJbfvh5grX2kjjT3IkTZPqNtXZs+RXGmP/DCRZFZTXziIiIiOwBNGaRiIiISGy/AHnA8caY5DjT9A4/fxRl3an1kisRERGRBqRgkYiIiEgM1toA8CzQBXjGGFN57CGMMV2MMf3LLVoXfj6t0nZnA79tmJyKiIiI1B91QxMRERGp3oPA4cBNwFBjzNdANtARZyyjE4G7gWXh7Z8DfgN8YIz5EMgBDgXOAd4HhjVq7kVEREQSpGCRiIiISDWstX5jzEXAVcC1wPk4A1pvB9YC9wJvl9t+kTFmMPAQ8Cuc662FwCU4XdoULBIREZE9mtE4iiIiIiIiIiIiUkZjFomIiIiIiIiISISCRSIiIiIiIiIiEqFgkYiIiIiIiIiIRChYJCIiIiIiIiIiEQoWiYiIiIiIiIhIhIJFIiIiIiIiIiISoWCRiIiIiIiIiIhEKFgkIiIiIiIiIiIRChaJiIiIiIiIiEiEgkUiIiIiIiIiIhLx/1iYlwY4LNZoAAAAAElFTkSuQmCC\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 1 Axes>"
-            ]
-          },
-          "metadata": {
-            "needs_background": "light"
-          }
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "YoQA_MIBMknS"
-      },
-      "source": [
-        ""
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 710
-        },
-        "id": "Pi8UMMitMa3Q",
-        "outputId": "a44c4d8b-e9d2-4978-fb9e-ae179758e6bc"
-      },
-      "source": [
-        "# we establish the corrmartrice\n",
-        "import seaborn as sns\n",
-        "color = sns.color_palette()\n",
-        "sns.set_style('darkgrid')\n",
-        "\n",
-        "correaltionMatrice = df_Ellis.corr()\n",
-        "f, ax = plt.subplots(figsize=(20, 10))\n",
-        "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 1440x720 with 2 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "rkYwyKtXMvpy",
-        "outputId": "c3e3d463-1089-48f7-da23-01a7b92423a5"
-      },
-      "source": [
-        "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "ellis-cpu.system_perc       -0.316956\n",
-              "ellis-cpu.wait_perc          0.886739\n",
-              "ellis-load.avg_1_min         1.000000\n",
-              "ellis-mem.free_mb           -0.335300\n",
-              "ellis-net.in_bytes_sec      -0.681849\n",
-              "ellis-net.out_packets_sec   -0.116851\n",
-              "Label                        0.279330\n",
-              "dtype: float64"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 11
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 235
-        },
-        "id": "5oQK-ddinvCM",
-        "outputId": "7e9b0a07-d2de-4e42-d45f-572a8abeae9e"
-      },
-      "source": [
-        "## ## using multivariate feature \n",
-        "\n",
-        "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
-        "\n",
-        "features = df_Ellis[features_3]\n",
-        "features.index = df_Ellis['Timestamp']\n",
-        "features.head()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/html": [
-              "<div>\n",
-              "<style scoped>\n",
-              "    .dataframe tbody tr th:only-of-type {\n",
-              "        vertical-align: middle;\n",
-              "    }\n",
-              "\n",
-              "    .dataframe tbody tr th {\n",
-              "        vertical-align: top;\n",
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-              "\n",
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-              "        text-align: right;\n",
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-              "</style>\n",
-              "<table border=\"1\" class=\"dataframe\">\n",
-              "  <thead>\n",
-              "    <tr style=\"text-align: right;\">\n",
-              "      <th></th>\n",
-              "      <th>ellis-cpu.wait_perc</th>\n",
-              "      <th>ellis-load.avg_1_min</th>\n",
-              "      <th>ellis-net.in_bytes_sec</th>\n",
-              "      <th>Label</th>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>Timestamp</th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "      <th></th>\n",
-              "    </tr>\n",
-              "  </thead>\n",
-              "  <tbody>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.73</td>\n",
-              "      <td>5413.200</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:00</th>\n",
-              "      <td>10.3</td>\n",
-              "      <td>1.79</td>\n",
-              "      <td>5201.667</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>11.8</td>\n",
-              "      <td>1.52</td>\n",
-              "      <td>5370.733</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:01</th>\n",
-              "      <td>12.9</td>\n",
-              "      <td>1.43</td>\n",
-              "      <td>5292.467</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "    <tr>\n",
-              "      <th>14-09-2016 0:02</th>\n",
-              "      <td>12.1</td>\n",
-              "      <td>1.44</td>\n",
-              "      <td>5318.167</td>\n",
-              "      <td>1</td>\n",
-              "    </tr>\n",
-              "  </tbody>\n",
-              "</table>\n",
-              "</div>"
-            ],
-            "text/plain": [
-              "                 ellis-cpu.wait_perc  ...  Label\n",
-              "Timestamp                             ...       \n",
-              "14-09-2016 0:00                 12.9  ...      1\n",
-              "14-09-2016 0:00                 10.3  ...      1\n",
-              "14-09-2016 0:01                 11.8  ...      1\n",
-              "14-09-2016 0:01                 12.9  ...      1\n",
-              "14-09-2016 0:02                 12.1  ...      1\n",
-              "\n",
-              "[5 rows x 4 columns]"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 12
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 386
-        },
-        "id": "qbqn755fo81g",
-        "outputId": "f8c5d0a8-c26a-4aa5-a530-957480984106"
-      },
-      "source": [
-        "features.plot(subplots=True)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "execute_result",
-          "data": {
-            "text/plain": [
-              "array([<matplotlib.axes._subplots.AxesSubplot object at 0x7f1f90fe5fd0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f9075bb50>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f903483d0>,\n",
-              "       <matplotlib.axes._subplots.AxesSubplot object at 0x7f1f906632d0>],\n",
-              "      dtype=object)"
-            ]
-          },
-          "metadata": {},
-          "execution_count": 13
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 4 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "jJQD1x9psWCH"
-      },
-      "source": [
-        "features = features.values"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "xf8WCiykpUzN",
-        "outputId": "4dca8628-c567-41b0-f262-bc6a3dddb5a7"
-      },
-      "source": [
-        "### standardize data\n",
-        "train_split = 141600\n",
-        "tf.random.set_seed(13)\n",
-        "\n",
-        "### standardize data\n",
-        "features_mean = features[:train_split].mean()\n",
-        "features_std = features[:train_split].std()\n",
-        "features  = (features - features_mean)/ features_std\n",
-        "\n",
-        "print(type(features))\n",
-        "print(features.shape)\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<class 'numpy.ndarray'>\n",
-            "(177000, 4)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "1a0hNDmppnLB"
-      },
-      "source": [
-        "### create mutlivariate data\n",
-        "\n",
-        "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
-        "                      step ,  single_step = False):\n",
-        "  data = []\n",
-        "  labels = []\n",
-        "  start_idx = start_idx + history_size\n",
-        "  if end_idx is None:\n",
-        "    end_idx = len(features)- target_size\n",
-        "  for i in range(start_idx , end_idx ):\n",
-        "    idxs = range(i-history_size, i, step) ### using step\n",
-        "    data.append(features[idxs])\n",
-        "    if single_step:\n",
-        "      labels.append(target[i+target_size])\n",
-        "    else:\n",
-        "      labels.append(target[i:i+target_size])\n",
-        "\n",
-        "  return np.array(data) , np.array(labels)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Z0CivgkitfgE",
-        "outputId": "7747f2fc-9d3d-4e46-9148-39708b9ae947"
-      },
-      "source": [
-        "### generate multivariate data\n",
-        "\n",
-        "history = 720\n",
-        "future_target = 72\n",
-        "STEP = 6\n",
-        "\n",
-        "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
-        "                                            future_target, STEP , single_step = True)\n",
-        "\n",
-        "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
-        "                                        future_target, STEP, single_step = True)\n",
-        "\n",
-        "print(x_train_ss.shape , y_train_ss.shape)\n",
-        "print(x_val_ss.shape , y_val_ss.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4) (140880,)\n",
-            "(34608, 120, 4) (34608,)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "VBdr2epGu3aq",
-        "outputId": "f3dccf5d-76c2-4c9a-898b-9a221f5a491c"
-      },
-      "source": [
-        "## tensorflow dataset\n",
-        "batch_size = 256\n",
-        "buffer_size = 10000\n",
-        "\n",
-        "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
-        "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
-        "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "print(train_ss)\n",
-        "print(val_ss)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None,)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "9eQpwUyGglu_"
-      },
-      "source": [
-        "def root_mean_squared_error(y_true, y_pred):\n",
-        "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "XkGTfQ46NAlo"
-      },
-      "source": [
-        "## Why Increase Depth?\n",
-        "Stacking LSTM hidden layers makes the model deeper, more accurately earning the description as a deep learning technique. It is the depth of neural networks that is generally attributed to the success of the approach on a wide range of challenging prediction problems.\n",
-        "\n",
-        "As Stacked LSTMs are now a stable technique for challenging sequence prediction problems. A Stacked LSTM architecture is defined as an LSTM model comprised of multiple LSTM layers. An LSTM layer above provides a sequence output rather than a single value output to the LSTM layer below. Specifically, one output per input time step, rather than one output time step for all input time steps.\n",
-        "\n",
-        "We created Stacked LSTM model using Keras which is a Python deep learning library. "
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "1cKtTAzqyiyL",
-        "outputId": "eed7670c-b3b2-4a20-82bb-7ff2b5f4a0eb"
-      },
-      "source": [
-        "from keras.layers import Activation, Dense, Dropout\n",
-        "### Modelling using LSTM\n",
-        "steps = 50\n",
-        "\n",
-        "EPOCHS =20\n",
-        "\n",
-        "single_step_model = tf.keras.models.Sequential()\n",
-        "\n",
-        "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:]))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
-        "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "single_step_model.add(tf.keras.layers.Dense(1))\n",
-        "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
-        "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
-        "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
-        "                                                  validation_steps = 50)\n",
-        "\n",
-        "\n",
-        "\n",
-        "single_step_model.summary()\n",
-        "\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 12s 96ms/step - loss: 0.0990 - rmse: 0.1509 - val_loss: 0.0124 - val_rmse: 0.0135\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 4s 79ms/step - loss: 0.0433 - rmse: 0.0542 - val_loss: 0.0210 - val_rmse: 0.0211\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 4s 79ms/step - loss: 0.0397 - rmse: 0.0498 - val_loss: 0.0055 - val_rmse: 0.0062\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 4s 78ms/step - loss: 0.0341 - rmse: 0.0429 - val_loss: 0.0114 - val_rmse: 0.0114\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0325 - rmse: 0.0408 - val_loss: 0.0138 - val_rmse: 0.0138\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0299 - rmse: 0.0376 - val_loss: 0.0076 - val_rmse: 0.0077\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0286 - rmse: 0.0360 - val_loss: 0.0161 - val_rmse: 0.0161\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0282 - rmse: 0.0355 - val_loss: 0.0040 - val_rmse: 0.0040\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 4s 71ms/step - loss: 0.0270 - rmse: 0.0340 - val_loss: 0.0036 - val_rmse: 0.0036\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0264 - rmse: 0.0331 - val_loss: 0.0100 - val_rmse: 0.0100\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0253 - rmse: 0.0318 - val_loss: 0.0046 - val_rmse: 0.0046\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0271 - rmse: 0.0342 - val_loss: 0.0057 - val_rmse: 0.0057\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0236 - rmse: 0.0295 - val_loss: 0.0090 - val_rmse: 0.0090\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0226 - rmse: 0.0284 - val_loss: 0.0048 - val_rmse: 0.0048\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0218 - rmse: 0.0273 - val_loss: 0.0051 - val_rmse: 0.0052\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0208 - rmse: 0.0262 - val_loss: 0.0017 - val_rmse: 0.0018\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 4s 72ms/step - loss: 0.0200 - rmse: 0.0250 - val_loss: 2.3304e-04 - val_rmse: 3.1191e-04\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 3s 70ms/step - loss: 0.0192 - rmse: 0.0242 - val_loss: 0.0069 - val_rmse: 0.0069\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0182 - rmse: 0.0229 - val_loss: 7.9341e-04 - val_rmse: 8.1912e-04\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 3s 68ms/step - loss: 0.0178 - rmse: 0.0223 - val_loss: 0.0040 - val_rmse: 0.0040\n",
-            "Model: \"sequential\"\n",
-            "_________________________________________________________________\n",
-            "Layer (type)                 Output Shape              Param #   \n",
-            "=================================================================\n",
-            "lstm (LSTM)                  (None, 120, 32)           4736      \n",
-            "_________________________________________________________________\n",
-            "dropout (Dropout)            (None, 120, 32)           0         \n",
-            "_________________________________________________________________\n",
-            "lstm_1 (LSTM)                (None, 100)               53200     \n",
-            "_________________________________________________________________\n",
-            "dropout_1 (Dropout)          (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "activation (Activation)      (None, 100)               0         \n",
-            "_________________________________________________________________\n",
-            "dense (Dense)                (None, 1)                 101       \n",
-            "=================================================================\n",
-            "Total params: 58,037\n",
-            "Trainable params: 58,037\n",
-            "Non-trainable params: 0\n",
-            "_________________________________________________________________\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "Pgev0dgzzBVx",
-        "outputId": "25c66158-969a-47c4-d35b-9c34abba211e"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['loss']\n",
-        "  val_loss = history.history['val_loss']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 281
-        },
-        "id": "EnYf6j4okEoC",
-        "outputId": "0a474737-67b6-4ff1-d6b2-37b7623a44ce"
-      },
-      "source": [
-        "## plot train test loss \n",
-        "\n",
-        "def plot_loss(history , title):\n",
-        "  loss = history.history['rmse']\n",
-        "  val_loss = history.history['val_rmse']\n",
-        "\n",
-        "  epochs = range(len(loss))\n",
-        "  plt.figure()\n",
-        "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
-        "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
-        "  plt.title(title)\n",
-        "  plt.legend()\n",
-        "  plt.grid()\n",
-        "  plt.show()\n",
-        "\n",
-        "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "WMegV8mNAwe_"
-      },
-      "source": [
-        "### fucntion to create time steps\n",
-        "def create_time_steps(length):\n",
-        "  return list(range(-length,0))\n",
-        "\n",
-        "### function to plot time series data\n",
-        "\n",
-        "def plot_time_series(plot_data, delta , title):\n",
-        "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
-        "  marker = ['.-' , 'rx' , 'go']\n",
-        "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
-        "\n",
-        "  if delta:\n",
-        "    future = delta\n",
-        "  else:\n",
-        "    future = 0\n",
-        "  plt.title(title)\n",
-        "  for i , x in enumerate(plot_data):\n",
-        "    if i :\n",
-        "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
-        "    else:\n",
-        "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
-        "  plt.legend()\n",
-        "  plt.xlim([time_steps[0], (future+5) *2])\n",
-        "\n",
-        "  plt.xlabel('Time_Step')\n",
-        "  return plt"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "q99i2c-9XKF3"
-      },
-      "source": [
-        "### Moving window average\n",
-        "\n",
-        "def MWA(history):\n",
-        "  return np.mean(history)"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "xFJT1rZDAUVL",
-        "outputId": "8e38f8da-d7ac-40ce-eec9-eee2320fd828"
-      },
-      "source": [
-        "# plot time series and predicted values\n",
-        "\n",
-        "for x, y in val_ss.take(5):\n",
-        "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
-        "                    single_step_model.predict(x)[0]], 12,\n",
-        "                   'Single Step Prediction')\n",
-        "  plot.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "_KXWQVmyCSix"
-      },
-      "source": [
-        "# **MultiStep Forcasting**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Lu7m2Rr4AbMK",
-        "outputId": "7b932e10-bb78-4eac-8757-4aa2d915b96d"
-      },
-      "source": [
-        "future_target = 72 # 72 future values\n",
-        "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
-        "                                                 train_split, history,\n",
-        "                                                 future_target, STEP)\n",
-        "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
-        "                                             train_split, None, history,\n",
-        "                                             future_target, STEP)\n",
-        "\n",
-        "print(x_train_multi.shape)\n",
-        "print(y_train_multi.shape)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "(140880, 120, 4)\n",
-            "(140880, 72)\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "GLRv5D16CrHj"
-      },
-      "source": [
-        "#  TF DATASET\n",
-        "\n",
-        "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
-        "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
-        "\n",
-        "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
-        "val_data_multi = val_data_multi.batch(batch_size).repeat()"
-      ],
-      "execution_count": null,
-      "outputs": []
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "fjXexah9C8yg",
-        "outputId": "72c81185-3db8-4d45-f1f2-9bf5861c3a3e"
-      },
-      "source": [
-        "print(train_data_multi)\n",
-        "print(val_data_multi)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n",
-            "<RepeatDataset shapes: ((None, 120, 4), (None, 72)), types: (tf.float64, tf.float64)>\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 385
-        },
-        "id": "7mtLZ6S-DPU-",
-        "outputId": "a4a392fe-73a5-44f7-ae77-003e7c46a1ad"
-      },
-      "source": [
-        "#plotting function\n",
-        "def multi_step_plot(history, true_future, prediction):\n",
-        "  plt.figure(figsize=(12, 6))\n",
-        "  num_in = create_time_steps(len(history))\n",
-        "  num_out = len(true_future)\n",
-        "  plt.grid()\n",
-        "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
-        "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
-        "           label='True Future')\n",
-        "  if prediction.any():\n",
-        "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
-        "             label='Predicted Future')\n",
-        "  plt.legend(loc='upper left')\n",
-        "  plt.show()\n",
-        "  \n",
-        "\n",
-        "\n",
-        "for x, y in train_data_multi.take(1):\n",
-        "  multi_step_plot(x[0], y[0], np.array([0]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "snN_Flr5DWQN",
-        "outputId": "8b881aff-b91b-4394-bc3d-e52261e546db"
-      },
-      "source": [
-        "multi_step_model = tf.keras.models.Sequential()\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
-        "                                          return_sequences=True,\n",
-        "                                          input_shape=x_train_multi.shape[-2:]))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
-        "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
-        "#model.add(Dense(units=1, activation='relu'))\n",
-        "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
-        "#aDD dropout layer (0.3)\n",
-        "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
-        "\n",
-        "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
-        "\n",
-        "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
-        "                                          steps_per_epoch=steps,\n",
-        "                                          validation_data=val_data_multi,\n",
-        "                                          validation_steps=50)"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Epoch 1/20\n",
-            "50/50 [==============================] - 9s 100ms/step - loss: 0.1700 - rmse: 0.2356 - val_loss: 0.0285 - val_rmse: 0.0316\n",
-            "Epoch 2/20\n",
-            "50/50 [==============================] - 4s 77ms/step - loss: 0.0805 - rmse: 0.1018 - val_loss: 0.0161 - val_rmse: 0.0170\n",
-            "Epoch 3/20\n",
-            "50/50 [==============================] - 4s 75ms/step - loss: 0.0621 - rmse: 0.0782 - val_loss: 0.0116 - val_rmse: 0.0121\n",
-            "Epoch 4/20\n",
-            "50/50 [==============================] - 4s 75ms/step - loss: 0.0527 - rmse: 0.0661 - val_loss: 0.0261 - val_rmse: 0.0263\n",
-            "Epoch 5/20\n",
-            "50/50 [==============================] - 4s 74ms/step - loss: 0.0465 - rmse: 0.0582 - val_loss: 0.0140 - val_rmse: 0.0142\n",
-            "Epoch 6/20\n",
-            "50/50 [==============================] - 3s 69ms/step - loss: 0.0426 - rmse: 0.0534 - val_loss: 0.0165 - val_rmse: 0.0166\n",
-            "Epoch 7/20\n",
-            "50/50 [==============================] - 3s 67ms/step - loss: 0.0387 - rmse: 0.0485 - val_loss: 0.0203 - val_rmse: 0.0204\n",
-            "Epoch 8/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0362 - rmse: 0.0453 - val_loss: 0.0142 - val_rmse: 0.0142\n",
-            "Epoch 9/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0336 - rmse: 0.0421 - val_loss: 0.0165 - val_rmse: 0.0166\n",
-            "Epoch 10/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0321 - rmse: 0.0402 - val_loss: 0.0166 - val_rmse: 0.0167\n",
-            "Epoch 11/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0304 - rmse: 0.0380 - val_loss: 0.0190 - val_rmse: 0.0190\n",
-            "Epoch 12/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0289 - rmse: 0.0361 - val_loss: 0.0196 - val_rmse: 0.0196\n",
-            "Epoch 13/20\n",
-            "50/50 [==============================] - 3s 65ms/step - loss: 0.0274 - rmse: 0.0343 - val_loss: 0.0220 - val_rmse: 0.0220\n",
-            "Epoch 14/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0266 - rmse: 0.0333 - val_loss: 0.0118 - val_rmse: 0.0119\n",
-            "Epoch 15/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0254 - rmse: 0.0318 - val_loss: 0.0094 - val_rmse: 0.0095\n",
-            "Epoch 16/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0243 - rmse: 0.0304 - val_loss: 0.0093 - val_rmse: 0.0094\n",
-            "Epoch 17/20\n",
-            "50/50 [==============================] - 3s 67ms/step - loss: 0.0236 - rmse: 0.0296 - val_loss: 0.0110 - val_rmse: 0.0110\n",
-            "Epoch 18/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0225 - rmse: 0.0280 - val_loss: 0.0157 - val_rmse: 0.0157\n",
-            "Epoch 19/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0221 - rmse: 0.0276 - val_loss: 0.0118 - val_rmse: 0.0119\n",
-            "Epoch 20/20\n",
-            "50/50 [==============================] - 3s 66ms/step - loss: 0.0210 - rmse: 0.0263 - val_loss: 0.0047 - val_rmse: 0.0047\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "Ay5m27doDsTt",
-        "outputId": "70f65cf2-a2fd-4a1e-b9e0-049430410a1d"
-      },
-      "source": [
-        "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
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\n",
-            "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "6ZFP49W4D2wp",
-        "outputId": "f2d25889-8aa1-4405-d607-1ed72a0df675"
-      },
-      "source": [
-        "for x, y in val_data_multi.take(5):\n",
-        "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 864x432 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "id": "DNKMjVoAVqZP",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "d853fe0e-6ca4-411f-aa83-248f61309efe"
-      },
-      "source": [
-        "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "705/705 [==============================] - 17s 23ms/step - loss: 0.0047 - rmse: 0.0047\n",
-            "MAE: 0.004736608359962702\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "YXcsNZ8yu9Ay",
-        "outputId": "0b7ee485-e356-4c5b-8a9c-257d8803d189"
-      },
-      "source": [
-        "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
-        "print('MAE: {}'.format(scores[1]))\n"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "174/174 [==============================] - 4s 24ms/step - loss: 0.0047 - rmse: 0.0047\n",
-            "MAE: 0.004736608359962702\n"
-          ]
-        }
-      ]
-    },
-    {
-      "cell_type": "code",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "uCFgbZEOvZ9A",
-        "outputId": "46302cac-3d92-4970-c100-e5c3a13847f0"
-      },
-      "source": [
-        "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
-        "\n",
-        "plt.figure(figsize=(10,5))\n",
-        "plt.plot(y_pred_test)\n",
-        "plt.plot(y_val_multi)\n",
-        "plt.ylabel(\"RUL\")\n",
-        "plt.xlabel(\"Unit Number\")\n",
-        "plt.legend(loc='upper left')\n",
-        "plt.show()"
-      ],
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "No handles with labels found to put in legend.\n"
-          ]
-        },
-        {
-          "output_type": "display_data",
-          "data": {
-            "image/png": 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\n",
-            "text/plain": [
-              "<Figure size 720x360 with 1 Axes>"
-            ]
-          },
-          "metadata": {}
-        }
-      ]
-    }
-  ]
-}
\ No newline at end of file
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "tLhroy5BnMnC"
+   },
+   "outputs": [],
+   "source": [
+    "# Importing libraries\n",
+    "import tensorflow as tf\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib as mpl\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 419
+    },
+    "id": "2-UpMVsSnfCI",
+    "outputId": "8c28f578-4405-4a27-81e4-c0fd00475b96"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis  = pd.read_csv(\"/gdrive/MyDrive/LFN Anuket/Analysis/data/Final/Ellis_FinalTwoConditionwithOR.csv\")\n",
+    "df_Ellis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 293
+    },
+    "id": "92xBt43BnjAo",
+    "outputId": "179123d5-8aec-4dda-a400-9096dec19dd8"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 879
+    },
+    "id": "RSo-aa-SIoBR",
+    "outputId": "75071f5e-5942-4939-a33b-2dc8780e260c"
+   },
+   "outputs": [],
+   "source": [
+    "# we show here the hist\n",
+    "df_Ellis.hist(bins=100,figsize=(20,15))\n",
+    "#save_fig(\"attribute_histogram_plots\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "gggaMJ_2LtFs",
+    "outputId": "af5ce749-d888-4cae-ddcd-9a5a5ce6e558"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_system_perc = df_Ellis[['ellis-cpu.system_perc']] \n",
+    "cpu_system_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "R_ctvXcQL1Xf",
+    "outputId": "8beab52c-ffb7-415c-c84c-04ed39cd70cf"
+   },
+   "outputs": [],
+   "source": [
+    "load_avg_1_min = df_Ellis[['ellis-load.avg_1_min']] \n",
+    "load_avg_1_min.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Timestamp', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 634
+    },
+    "id": "Gkd5ecCmL6Bw",
+    "outputId": "a6c042dc-999a-456c-b233-a1e05612e15f"
+   },
+   "outputs": [],
+   "source": [
+    "cpu_wait_perc = df_Ellis[['ellis-cpu.wait_perc']] \n",
+    "cpu_wait_perc.rolling(12).mean().plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=30);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 624
+    },
+    "id": "EycZrQU0MBSX",
+    "outputId": "6f325187-ee1b-4122-97f7-80ffdbf149d2"
+   },
+   "outputs": [],
+   "source": [
+    "df_dg = pd.concat([cpu_system_perc.rolling(12).mean(), load_avg_1_min.rolling(12).mean(),cpu_wait_perc.rolling(12).mean()], axis=1) \n",
+    "df_dg.plot(figsize=(20,10), linewidth=5, fontsize=20) \n",
+    "plt.xlabel('Year', fontsize=20); "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YoQA_MIBMknS"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 710
+    },
+    "id": "Pi8UMMitMa3Q",
+    "outputId": "a44c4d8b-e9d2-4978-fb9e-ae179758e6bc"
+   },
+   "outputs": [],
+   "source": [
+    "# we establish the corrmartrice\n",
+    "import seaborn as sns\n",
+    "color = sns.color_palette()\n",
+    "sns.set_style('darkgrid')\n",
+    "\n",
+    "correaltionMatrice = df_Ellis.corr()\n",
+    "f, ax = plt.subplots(figsize=(20, 10))\n",
+    "sns.heatmap(correaltionMatrice, cbar=True, vmin=0, vmax=1, square=True, annot=True);\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rkYwyKtXMvpy",
+    "outputId": "c3e3d463-1089-48f7-da23-01a7b92423a5"
+   },
+   "outputs": [],
+   "source": [
+    "df_Ellis.corrwith(df_Ellis['ellis-load.avg_1_min'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 235
+    },
+    "id": "5oQK-ddinvCM",
+    "outputId": "7e9b0a07-d2de-4e42-d45f-572a8abeae9e"
+   },
+   "outputs": [],
+   "source": [
+    "## ## using multivariate feature \n",
+    "\n",
+    "features_3 = ['ellis-cpu.wait_perc', 'ellis-load.avg_1_min', 'ellis-net.in_bytes_sec', 'Label']\n",
+    "\n",
+    "features = df_Ellis[features_3]\n",
+    "features.index = df_Ellis['Timestamp']\n",
+    "features.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "id": "qbqn755fo81g",
+    "outputId": "f8c5d0a8-c26a-4aa5-a530-957480984106"
+   },
+   "outputs": [],
+   "source": [
+    "features.plot(subplots=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "jJQD1x9psWCH"
+   },
+   "outputs": [],
+   "source": [
+    "features = features.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xf8WCiykpUzN",
+    "outputId": "4dca8628-c567-41b0-f262-bc6a3dddb5a7"
+   },
+   "outputs": [],
+   "source": [
+    "### standardize data\n",
+    "train_split = 141600\n",
+    "tf.random.set_seed(13)\n",
+    "\n",
+    "### standardize data\n",
+    "features_mean = features[:train_split].mean()\n",
+    "features_std = features[:train_split].std()\n",
+    "features  = (features - features_mean)/ features_std\n",
+    "\n",
+    "print(type(features))\n",
+    "print(features.shape)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1a0hNDmppnLB"
+   },
+   "outputs": [],
+   "source": [
+    "### create mutlivariate data\n",
+    "\n",
+    "def mutlivariate_data(features , target , start_idx , end_idx , history_size , target_size,\n",
+    "                      step ,  single_step = False):\n",
+    "  data = []\n",
+    "  labels = []\n",
+    "  start_idx = start_idx + history_size\n",
+    "  if end_idx is None:\n",
+    "    end_idx = len(features)- target_size\n",
+    "  for i in range(start_idx , end_idx ):\n",
+    "    idxs = range(i-history_size, i, step) ### using step\n",
+    "    data.append(features[idxs])\n",
+    "    if single_step:\n",
+    "      labels.append(target[i+target_size])\n",
+    "    else:\n",
+    "      labels.append(target[i:i+target_size])\n",
+    "\n",
+    "  return np.array(data) , np.array(labels)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Z0CivgkitfgE",
+    "outputId": "7747f2fc-9d3d-4e46-9148-39708b9ae947"
+   },
+   "outputs": [],
+   "source": [
+    "### generate multivariate data\n",
+    "\n",
+    "history = 720\n",
+    "future_target = 72\n",
+    "STEP = 6\n",
+    "\n",
+    "x_train_ss , y_train_ss = mutlivariate_data(features , features[:, 1], 0, train_split, history,\n",
+    "                                            future_target, STEP , single_step = True)\n",
+    "\n",
+    "x_val_ss , y_val_ss = mutlivariate_data(features , features[:,1] , train_split , None , history ,\n",
+    "                                        future_target, STEP, single_step = True)\n",
+    "\n",
+    "print(x_train_ss.shape , y_train_ss.shape)\n",
+    "print(x_val_ss.shape , y_val_ss.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "VBdr2epGu3aq",
+    "outputId": "f3dccf5d-76c2-4c9a-898b-9a221f5a491c"
+   },
+   "outputs": [],
+   "source": [
+    "## tensorflow dataset\n",
+    "batch_size = 256\n",
+    "buffer_size = 10000\n",
+    "\n",
+    "train_ss = tf.data.Dataset.from_tensor_slices((x_train_ss, y_train_ss))\n",
+    "train_ss = train_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_ss = tf.data.Dataset.from_tensor_slices((x_val_ss, y_val_ss))\n",
+    "val_ss = val_ss.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "print(train_ss)\n",
+    "print(val_ss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "9eQpwUyGglu_"
+   },
+   "outputs": [],
+   "source": [
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true))) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XkGTfQ46NAlo"
+   },
+   "source": [
+    "## Why Increase Depth?\n",
+    "Stacking LSTM hidden layers makes the model deeper, more accurately earning the description as a deep learning technique. It is the depth of neural networks that is generally attributed to the success of the approach on a wide range of challenging prediction problems.\n",
+    "\n",
+    "As Stacked LSTMs are now a stable technique for challenging sequence prediction problems. A Stacked LSTM architecture is defined as an LSTM model comprised of multiple LSTM layers. An LSTM layer above provides a sequence output rather than a single value output to the LSTM layer below. Specifically, one output per input time step, rather than one output time step for all input time steps.\n",
+    "\n",
+    "We created Stacked LSTM model using Keras which is a Python deep learning library. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "1cKtTAzqyiyL",
+    "outputId": "eed7670c-b3b2-4a20-82bb-7ff2b5f4a0eb"
+   },
+   "outputs": [],
+   "source": [
+    "from keras.layers import Activation, Dense, Dropout\n",
+    "### Modelling using LSTM\n",
+    "steps = 50\n",
+    "\n",
+    "EPOCHS =20\n",
+    "\n",
+    "single_step_model = tf.keras.models.Sequential()\n",
+    "\n",
+    "single_step_model.add(tf.keras.layers.LSTM(32, return_sequences=True, input_shape = x_train_ss.shape[-2:]))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.3))\n",
+    "single_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "single_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "single_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "single_step_model.add(tf.keras.layers.Dense(1))\n",
+    "single_step_model.compile(optimizer = tf.keras.optimizers.Adam(), loss = 'mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "#single_step_model.compile(loss='mse', optimizer='rmsprop')\n",
+    "single_step_model_history = single_step_model.fit(train_ss, epochs = EPOCHS , \n",
+    "                                                  steps_per_epoch =steps, validation_data = val_ss,\n",
+    "                                                  validation_steps = 50)\n",
+    "\n",
+    "\n",
+    "\n",
+    "single_step_model.summary()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "Pgev0dgzzBVx",
+    "outputId": "25c66158-969a-47c4-d35b-9c34abba211e"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['loss']\n",
+    "  val_loss = history.history['val_loss']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train Loss')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation Loss')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 281
+    },
+    "id": "EnYf6j4okEoC",
+    "outputId": "0a474737-67b6-4ff1-d6b2-37b7623a44ce"
+   },
+   "outputs": [],
+   "source": [
+    "## plot train test loss \n",
+    "\n",
+    "def plot_loss(history , title):\n",
+    "  loss = history.history['rmse']\n",
+    "  val_loss = history.history['val_rmse']\n",
+    "\n",
+    "  epochs = range(len(loss))\n",
+    "  plt.figure()\n",
+    "  plt.plot(epochs, loss , 'b' , label = 'Train RMSE')\n",
+    "  plt.plot(epochs, val_loss , 'r' , label = 'Validation RMSE')\n",
+    "  plt.title(title)\n",
+    "  plt.legend()\n",
+    "  plt.grid()\n",
+    "  plt.show()\n",
+    "\n",
+    "plot_loss(single_step_model_history , 'Single Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "WMegV8mNAwe_"
+   },
+   "outputs": [],
+   "source": [
+    "### fucntion to create time steps\n",
+    "def create_time_steps(length):\n",
+    "  return list(range(-length,0))\n",
+    "\n",
+    "### function to plot time series data\n",
+    "\n",
+    "def plot_time_series(plot_data, delta , title):\n",
+    "  labels = [\"History\" , 'True Future' , 'Model Predcited']\n",
+    "  marker = ['.-' , 'rx' , 'go']\n",
+    "  time_steps = create_time_steps(plot_data[0].shape[0])\n",
+    "\n",
+    "  if delta:\n",
+    "    future = delta\n",
+    "  else:\n",
+    "    future = 0\n",
+    "  plt.title(title)\n",
+    "  for i , x in enumerate(plot_data):\n",
+    "    if i :\n",
+    "      plt.plot(future , plot_data[i] , marker[i], markersize = 10 , label = labels[i])\n",
+    "    else:\n",
+    "      plt.plot(time_steps, plot_data[i].flatten(), marker[i], label = labels[i])\n",
+    "  plt.legend()\n",
+    "  plt.xlim([time_steps[0], (future+5) *2])\n",
+    "\n",
+    "  plt.xlabel('Time_Step')\n",
+    "  return plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "q99i2c-9XKF3"
+   },
+   "outputs": [],
+   "source": [
+    "### Moving window average\n",
+    "\n",
+    "def MWA(history):\n",
+    "  return np.mean(history)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "xFJT1rZDAUVL",
+    "outputId": "8e38f8da-d7ac-40ce-eec9-eee2320fd828"
+   },
+   "outputs": [],
+   "source": [
+    "# plot time series and predicted values\n",
+    "\n",
+    "for x, y in val_ss.take(5):\n",
+    "  plot = plot_time_series([x[0][:, 1].numpy(), y[0].numpy(),\n",
+    "                    single_step_model.predict(x)[0]], 12,\n",
+    "                   'Single Step Prediction')\n",
+    "  plot.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "_KXWQVmyCSix"
+   },
+   "source": [
+    "# **MultiStep Forcasting**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Lu7m2Rr4AbMK",
+    "outputId": "7b932e10-bb78-4eac-8757-4aa2d915b96d"
+   },
+   "outputs": [],
+   "source": [
+    "future_target = 72 # 72 future values\n",
+    "x_train_multi, y_train_multi = mutlivariate_data(features, features[:, 1], 0,\n",
+    "                                                 train_split, history,\n",
+    "                                                 future_target, STEP)\n",
+    "x_val_multi, y_val_multi = mutlivariate_data(features, features[:, 1],\n",
+    "                                             train_split, None, history,\n",
+    "                                             future_target, STEP)\n",
+    "\n",
+    "print(x_train_multi.shape)\n",
+    "print(y_train_multi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GLRv5D16CrHj"
+   },
+   "outputs": [],
+   "source": [
+    "#  TF DATASET\n",
+    "\n",
+    "train_data_multi = tf.data.Dataset.from_tensor_slices((x_train_multi, y_train_multi))\n",
+    "train_data_multi = train_data_multi.cache().shuffle(buffer_size).batch(batch_size).repeat()\n",
+    "\n",
+    "val_data_multi = tf.data.Dataset.from_tensor_slices((x_val_multi, y_val_multi))\n",
+    "val_data_multi = val_data_multi.batch(batch_size).repeat()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "fjXexah9C8yg",
+    "outputId": "72c81185-3db8-4d45-f1f2-9bf5861c3a3e"
+   },
+   "outputs": [],
+   "source": [
+    "print(train_data_multi)\n",
+    "print(val_data_multi)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 385
+    },
+    "id": "7mtLZ6S-DPU-",
+    "outputId": "a4a392fe-73a5-44f7-ae77-003e7c46a1ad"
+   },
+   "outputs": [],
+   "source": [
+    "#plotting function\n",
+    "def multi_step_plot(history, true_future, prediction):\n",
+    "  plt.figure(figsize=(12, 6))\n",
+    "  num_in = create_time_steps(len(history))\n",
+    "  num_out = len(true_future)\n",
+    "  plt.grid()\n",
+    "  plt.plot(num_in, np.array(history[:, 1]), label='History')\n",
+    "  plt.plot(np.arange(num_out)/STEP, np.array(true_future), 'bo',\n",
+    "           label='True Future')\n",
+    "  if prediction.any():\n",
+    "    plt.plot(np.arange(num_out)/STEP, np.array(prediction), 'ro',\n",
+    "             label='Predicted Future')\n",
+    "  plt.legend(loc='upper left')\n",
+    "  plt.show()\n",
+    "  \n",
+    "\n",
+    "\n",
+    "for x, y in train_data_multi.take(1):\n",
+    "  multi_step_plot(x[0], y[0], np.array([0]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "snN_Flr5DWQN",
+    "outputId": "8b881aff-b91b-4394-bc3d-e52261e546db"
+   },
+   "outputs": [],
+   "source": [
+    "multi_step_model = tf.keras.models.Sequential()\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(32,\n",
+    "                                          return_sequences=True,\n",
+    "                                          input_shape=x_train_multi.shape[-2:]))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "multi_step_model.add(tf.keras.layers.LSTM(units=100,return_sequences=False))\n",
+    "multi_step_model.add(tf.keras.layers.Dropout(0.2))\n",
+    "#model.add(Dense(units=1, activation='relu'))\n",
+    "multi_step_model.add(tf.keras.layers.Activation(\"relu\"))\n",
+    "#aDD dropout layer (0.3)\n",
+    "multi_step_model.add(tf.keras.layers.Dense(72)) # for 72 outputs\n",
+    "\n",
+    "multi_step_model.compile(optimizer=tf.keras.optimizers.RMSprop(clipvalue=1.0), loss='mae',metrics=[tf.keras.metrics.RootMeanSquaredError(name='rmse')])\n",
+    "\n",
+    "multi_step_history = multi_step_model.fit(train_data_multi, epochs=EPOCHS,\n",
+    "                                          steps_per_epoch=steps,\n",
+    "                                          validation_data=val_data_multi,\n",
+    "                                          validation_steps=50)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "Ay5m27doDsTt",
+    "outputId": "70f65cf2-a2fd-4a1e-b9e0-049430410a1d"
+   },
+   "outputs": [],
+   "source": [
+    "plot_loss(multi_step_history, 'Multi-Step Training and validation loss')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "6ZFP49W4D2wp",
+    "outputId": "f2d25889-8aa1-4405-d607-1ed72a0df675"
+   },
+   "outputs": [],
+   "source": [
+    "for x, y in val_data_multi.take(5):\n",
+    "  multi_step_plot(x[0], y[0], multi_step_model.predict(x)[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "DNKMjVoAVqZP",
+    "outputId": "d853fe0e-6ca4-411f-aa83-248f61309efe"
+   },
+   "outputs": [],
+   "source": [
+    "scores = multi_step_model.evaluate(x_train_multi, y_train_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "YXcsNZ8yu9Ay",
+    "outputId": "0b7ee485-e356-4c5b-8a9c-257d8803d189"
+   },
+   "outputs": [],
+   "source": [
+    "scores_test = multi_step_model.evaluate(x_val_multi, y_val_multi, verbose=1, batch_size=200)\n",
+    "print('MAE: {}'.format(scores[1]))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "uCFgbZEOvZ9A",
+    "outputId": "46302cac-3d92-4970-c100-e5c3a13847f0"
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_test = multi_step_model.predict(x_val_multi, verbose=0)\n",
+    "\n",
+    "plt.figure(figsize=(10,5))\n",
+    "plt.plot(y_pred_test)\n",
+    "plt.plot(y_val_multi)\n",
+    "plt.ylabel(\"RUL\")\n",
+    "plt.xlabel(\"Unit Number\")\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "stacked-LSTM_Correlation.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}