diff --git a/mimic-iv-ecg/notebooks/ECG_rate_classification.ipynb b/mimic-iv-ecg/notebooks/ECG_rate_classification.ipynb
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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "LfmKH4j0UtEY",
+        "outputId": "e58bfe57-63d1-46bf-fd0c-a2fb03473bba",
+        "collapsed": true
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting wfdb==4.3.1\n",
+            "  Downloading wfdb-4.3.1-py3-none-any.whl.metadata (3.8 kB)\n",
+            "Collecting neurokit2\n",
+            "  Downloading neurokit2-0.2.13-py3-none-any.whl.metadata (27 kB)\n",
+            "Requirement already satisfied: aiohttp>=3.10.11 in /usr/local/lib/python3.12/dist-packages (from wfdb==4.3.1) (3.13.4)\n",
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+            "Collecting pandas>=2.2.3 (from wfdb==4.3.1)\n",
+            "  Downloading pandas-3.0.2-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.metadata (79 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.5/79.5 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+            "  Downloading pandas-2.3.3-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.metadata (91 kB)\n",
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+            "\u001b[?25hRequirement already satisfied: pywavelets>=1.4.0 in /usr/local/lib/python3.12/dist-packages (from neurokit2) (1.9.0)\n",
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+            "Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.2.2->wfdb==4.3.1) (1.5.0)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.2.2->wfdb==4.3.1) (26.0)\n",
+            "Requirement already satisfied: pillow>=8 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.2.2->wfdb==4.3.1) (11.3.0)\n",
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+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests>=2.8.1->wfdb==4.3.1) (3.11)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests>=2.8.1->wfdb==4.3.1) (2.5.0)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests>=2.8.1->wfdb==4.3.1) (2026.2.25)\n",
+            "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn>=1.0.0->neurokit2) (1.5.3)\n",
+            "Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.12/dist-packages (from scikit-learn>=1.0.0->neurokit2) (3.6.0)\n",
+            "Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.12/dist-packages (from soundfile>=0.10.0->wfdb==4.3.1) (2.0.0)\n",
+            "Requirement already satisfied: typing-extensions>=4.2 in /usr/local/lib/python3.12/dist-packages (from aiosignal>=1.4.0->aiohttp>=3.10.11->wfdb==4.3.1) (4.15.0)\n",
+            "Requirement already satisfied: pycparser in /usr/local/lib/python3.12/dist-packages (from cffi>=1.0->soundfile>=0.10.0->wfdb==4.3.1) (3.0)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.7->matplotlib>=3.2.2->wfdb==4.3.1) (1.17.0)\n",
+            "Downloading wfdb-4.3.1-py3-none-any.whl (163 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m163.9/163.9 kB\u001b[0m \u001b[31m14.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading neurokit2-0.2.13-py3-none-any.whl (688 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m688.9/688.9 kB\u001b[0m \u001b[31m38.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pandas-2.3.3-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (12.4 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.4/12.4 MB\u001b[0m \u001b[31m86.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: pandas, wfdb, neurokit2\n",
+            "  Attempting uninstall: pandas\n",
+            "    Found existing installation: pandas 2.2.2\n",
+            "    Uninstalling pandas-2.2.2:\n",
+            "      Successfully uninstalled pandas-2.2.2\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "google-colab 1.0.0 requires pandas==2.2.2, but you have pandas 2.3.3 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed neurokit2-0.2.13 pandas-2.3.3 wfdb-4.3.1\n"
+          ]
+        }
+      ],
+      "source": [
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "sw-8zDBwx753"
+      },
+      "outputs": [],
+      "source": [
+        "import wfdb\n",
+        "import matplotlib.pyplot as plt"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "collapsed": true,
+        "id": "3DiIsYWQ-jwQ"
+      },
+      "outputs": [],
+      "source": [
+        "#loads neurokit\n",
+        "\n",
+        "import neurokit2 as nk\n",
+        "import numpy as np\n",
+        "import pandas as pd"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "rec_path = '/files/p1000/p10000117/s45090959/45090959'\n",
+        "recordid = \"45090959\"\n",
+        "rd_record = wfdb.rdrecord(recordid, pn_dir= f\'mimic-iv-ecg/1.0/{rec_path}\')"
+      ],
+      "metadata": {
+        "id": "i2mRFMBq8Ry_"
+      },
+      "execution_count": 4,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "collapsed": true,
+        "id": "8eL04bdQID8i"
+      },
+      "outputs": [],
+      "source": [
+        "#10 seconds of ECG material\n",
+        "rd_record.p_signal.shape\n",
+        "ecg_signal = rd_record.p_signal[:,1]\n",
+        "#Processes the raw ECG signal\n",
+        "signals, info = nk.ecg_process(ecg_signal, sampling_rate=rd_record.fs)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "collapsed": true,
+        "id": "34YmBSFG7Q7k",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "c8419530-cd65-4c46-b635-9984bc785636"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Signals:\n",
+            "ECG_Raw\n",
+            "ECG_Clean\n",
+            "ECG_Rate\n",
+            "ECG_Quality\n",
+            "ECG_R_Peaks\n",
+            "ECG_P_Peaks\n",
+            "ECG_P_Onsets\n",
+            "ECG_P_Offsets\n",
+            "ECG_Q_Peaks\n",
+            "ECG_R_Onsets\n",
+            "ECG_R_Offsets\n",
+            "ECG_S_Peaks\n",
+            "ECG_T_Peaks\n",
+            "ECG_T_Onsets\n",
+            "ECG_T_Offsets\n",
+            "ECG_Phase_Atrial\n",
+            "ECG_Phase_Completion_Atrial\n",
+            "ECG_Phase_Ventricular\n",
+            "ECG_Phase_Completion_Ventricular\n",
+            "\n",
+            "Info keys:\n",
+            "method_peaks\n",
+            "method_fixpeaks\n",
+            "ECG_R_Peaks\n",
+            "ECG_R_Peaks_Uncorrected\n",
+            "ECG_fixpeaks_ectopic\n",
+            "ECG_fixpeaks_missed\n",
+            "ECG_fixpeaks_extra\n",
+            "ECG_fixpeaks_longshort\n",
+            "ECG_fixpeaks_method\n",
+            "ECG_fixpeaks_rr\n",
+            "ECG_fixpeaks_drrs\n",
+            "ECG_fixpeaks_mrrs\n",
+            "ECG_fixpeaks_s12\n",
+            "ECG_fixpeaks_s22\n",
+            "ECG_fixpeaks_c1\n",
+            "ECG_fixpeaks_c2\n",
+            "sampling_rate\n",
+            "ECG_P_Peaks\n",
+            "ECG_P_Onsets\n",
+            "ECG_P_Offsets\n",
+            "ECG_Q_Peaks\n",
+            "ECG_R_Onsets\n",
+            "ECG_R_Offsets\n",
+            "ECG_S_Peaks\n",
+            "ECG_T_Peaks\n",
+            "ECG_T_Onsets\n",
+            "ECG_T_Offsets\n"
+          ]
+        }
+      ],
+      "source": [
+        "\n",
+        "# Extracts clean ECG and R-peaks location\n",
+        "rpeaks = info[\"ECG_R_Peaks\"]\n",
+        "cleaned_ecg = signals[\"ECG_Clean\"]\n",
+        "\n",
+        "# List signals and info keys\n",
+        "print(\"Signals:\")\n",
+        "for key in signals.keys():\n",
+        "    print(key)\n",
+        "\n",
+        "print(\"\\nInfo keys:\")\n",
+        "for key in info.keys():\n",
+        "    print(key)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 430
+        },
+        "id": "OsvX3PGJ7Wqy",
+        "outputId": "006d28cb-989c-45cf-f345-701e46a9c21a",
+        "collapsed": true
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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td2ltamnFYADpKk5pwQ5414tIu4W9rixmbqOkMTICHHyw8/qBB/RR5uuWmZLc4Y2D+Ov3LgQAbFn0KMrTJycrUHMbc5VR3j7rk0uQGzeQqDx7eITLu+c1f0pUFoMx4sq0L3oImKTJxD0y7I6dd/4TQMJjh8Agsv9z0q3a5DKUahUuH5c+oWWumvQ5v+d+AOMTlwkAxar+tgJOeQAm9yf7/0KLTApz1F077Hf/C7r6Wxcy5SVp2LZTk4a97lWZKcm1bRt7rF8KAFhtabC/a25jMWfw9o3UG0h62bXtJpd3j6bjGn2GyzQTvTC5D2svD+DKfiwFv5FB2p7GXH3K1tdmA/rb6ohKR65K/hM9aHrJ3EYZtmpYljsp643eCx7IkSSBho4FKA3ytJRcKGma1Xudg0OFsRCDkRaDc9rISOoyZBhjqBNrS6/HDmipA6lZnkemHpEeaakG7Pb2sOWgXWyl1OgeXyIE9DopYKa8ZNiqIbKkpngjiUEz+2wK1oi0glfTzTZKJ8MqTYyFDVTrLaSebURej4G+jxuZ8pJhqwbdYHudqVSP7pLGpprOCXGsLO49Pmw5tpFmcqTuJuvx+lmZ8pJhq8ZYoJZPEpQYU4d1II2q0qKcbcTy0oNjtR3GghtjW4p5sUXtpeeQZRslDcMAdtrJfd2rMlOSaxsGXp4w3XmtQ6DmNtpw26eDUp32p65n2DRAnqFO+nZXblN3eQBoHreyfPKcd0hjrmrsbtrXM3SWB0hhLgnySbt1lfrQiUx5SRr9/cCLL/a+zJTkNvv6ceT/XA8A+IsOannNbbT7+3j77u9Pnv+k2efK+0hJD229VXaf4a0a6dstMnZ+WNZLn077+fIUqOOrxTKXr4syv1FyZf5OYzmGGpH7tMbyEzZ5xm9LqTwAk/9bzeNbBzK3UYatHL0d+KjbjZOK20h4hvpgp2hV3yarSo+BZmotP0Ffp9D2NMe3DmTKS4atGkLcgiaal/tf2IDzf/gAlq4fSVxWqhT2uuSkoDABYycmoBc3FhXSS4kncjVzdvLXKbQ49YDhhJG5jZLG6Chw9NHO67vuAnRU90xDZlpyR0fxu//7EADAftddACYkLq/0ysPwfgCLNnwLv1r0mmTljZD2feA+YGKyfWqQ/vzHUb9OVBaXWXFl4j3/gC4ac5O0dePb/qpFJgd5ro++9nd6ZQMo1qpun1/2ai1z1RytuGP5vDsBTEpcJgAUaq5cfOIYoDBOi1x7dITLvWHfH2uRSUH7u/HOO6Cz/IUOZMpL0mg2gQcfdF/3qsyU5NrNJvZf9QwA4L86ZBJ5S9dtSVycbVtc3nIr+cKTtuW27x9NTYUuSZ8+qXG80rFzh47SElQ2ea6PplAewLTdtmubqym12bRtLndU53Mm4+vGNFIhyTN+qAdLl2duowxbNUTTqN4FoqahHIH2mJeUTc1pmfW1YxuPeUktVVqn+ybt9o6B1PQkkSkvGbZqpBmUpqPWUKoBu8mL88jUiTQVtR7cSzpE75cHEGN80oh5Ia97UHvJlJcMWzXSJBrTwZxAFz0tJHUB75KTmU7GWLrZRr19KlZhLGygqZUHyLKNYkemvGTYqpGm20iHNN0LkLCpapDnyFS/Tlyu7xu9snsxxV+FMeE20smwmxIFAJfZ4wpyprxk2KohWl50y9YrULvlRRfPyxjYyNLledEsPCWk2d9pyE2by6fXFeQs20gHpk3bNmSmJHd9n5Me3dSkvTB5OmDbrjxdMS9cnja3kd42pi2XSXf7OR0w+VM1yUutvw2Dy82nNb70iXXlk7ncg7pLprwkjoEB2GvWwNBZW2JgAFi7Vp+8FOU2+wZw0Pt/BgC4oX8geYEDrjwdj7TZ38/l6aDOtwdceReWNNHGl/u4zN9rLA9Ax851GkovUFhE9kdToG6vlNw+f3FAw7wBUC+7Y+tGjTT9NdLWf+tYI1qgc/fkNMoD9Lnyf6qx3bqQuY0SRrNp4/Tr7sX5P3wg7VvpSegOaNUN3W6xVLKNNMnxyh0b2UY9OGyVGBMMu9tIQLgssxfHWGZ5SRgvrB/Ggy9tBADUrSYKuUxfjBNpxg7o4V2hr/XGvGjrz7QCdlPNNtIscAxgTGQbjYH4qjRkZjEvGTrHyChu+NnHAQD1S45GYaIG6vPRUeANb3Be//nPessD6JZbcfvXOuuPycsbdeWde/rlGuSNcHn2BX9D4uUPyHj9x2E/SlZWCyZ5hjj/r9BFG2+QZ7npVM0U/eS5PnLMz/TKhlMegPe5rvIAlQqXaZz958TlMRRqrlz7I0cCA0Utcun4umHet7XIpMhV3XY3ztSwNmpGprwkDMNu4rBl/wUAbKo1oMXT22wCf/+7+1oX0pBrWbx//6GD+rvpPk9Tx2mKyHtcB10/Ga93ayzxwGT+W0MJBJXcWyzNJ1Mi+xHNpQkApzwAk6+vbIk7V+/TVXoCgGHbXO56nePLcvv4Rt3jCwCI/H9k5QEydApququlsEj1OnqdRVJ/LEYKPC8+r3UK1m1WTzseIg3YaT3olFK00yJfVMrvwbUxU14SBlW4e3D8pI5e58ugi44WnpcUuCnGAkmd9piXlGtIpYExEbCbVkxVCg3udQU5U14SRjPlEbRk5WZtsv71/Hptslz0eLaR75uE5KWw4KYVTJjq1EzR6pMWxsL01Jpt5PM6FfljofNjRqa8JIw0a+8AwI/++ZI2We/8gf508DQZdnVA9/hJxW2kW0NTyEqztETa+4o2C1tK1qa03FVpZ/ukbflJGpnykjDS5iEp5DSS46WAsbQJJAHRbaRDnvq1LqS2qWnGWDLpa7OwpWRtSqvGUNprU6+7JrNso4Rh28BIocRf6wKTqZXZl8jVxZ+ZRv8yeTpgC/L0NJD3p8al3pWpD7Rv0wiMTqOfKZh8XaPZtu1U+puuEXotL+mM67EiP2lkykvCsPsHsNeiXwMA7tJF0TzgyjyjqI+WerRY5nJ1UY5bff1cphaKd9K3OmD1ufJ+2Zd8nzaJvHdqLA/AZP5CQxu5XDJ2vqqLC6kF+lwv0tTPFJWS2+fPairJUC+7/f1/GunqK0W3rfcO6Otre8Bt73Ea12EGOr6/o7Ecgy5kbqOEkXbMi9WL9kKCtE2zSUO36TedlE7yWuNDTDNQVgzDSHfgaottoq9Tes7prRFpxLyk4y7ThUx5SRhp+Vu5zF4ctQS9HrArUuf3fqq0TqRbWmIsbKh65afdTkCzWzLltSnt+LWkocVtdO211+LLX/4yVq1ahf333x/XXHMNDjnkEOW1v/nNb/CFL3wBzz77LOr1OnbffXd8+MMfxtlnn63jVuPHaAXX//LTAAD7fX8GoMFcWnFl3rLPN5KX10KpUcO3fvsF582nXwOUy8kLrY7ytlZOvTF5eaRv/+fNn0heXtWVh3NvSl4ead/dB12XvDw4tPFa29iCQfp288k/1yZXlv3wK7+nVTYAFOpVd1365LHAuOTXJbPmttk4U5/rNV8jbf3A4cAkTS4cMq5//rGr9MgkMEm7G6f/Qrv8pJG48nLjjTdi0aJFuO6663DooYfi6quvxvHHH4+nnnoK06dP91w/ZcoU/L//9/8wb948FItF3HzzzVi4cCGmT5+O448/PunbjR221cCrn38QAPBco6FHqGVxmX/VSAttNptcLnTRcDfctv5JB4Mx6VtTR9+S9t2vo0/JeL1b1zNsum38V0MffTt9lr/VTZ9OZD+ikbKeIUfmakVXn5Ox/HeNz9kgbX1Zo1ybPOMb0qDnJ/3910bvsbsn7ja66qqrcMEFF2DhwoXYa6+9cN1116G/vx/XX3+98vpjjz0Wb37zm/GKV7wCu+66Kz7wgQ9gv/32w9133530rSaC1GMyetBcSDGWUk6TQJr+el2xGGml0Ir3oL1zyct0OUC0yUyLLj8tt+SYiLVpyU9XfCJIVHmp1Wp46KGHcNxxx7kCTRPHHXcc7r333rbft20bt912G5566ikcffTRymuq1SoGBweFf2MJgt8zvdvoWfR6/Q7dG3saynZaHHXNFAMabYwdrTuN56y3DET65HjpnFvHjvKUBBJVXtatWwfLsjBjxgzh8xkzZmDVqlW+39u8eTPGjRuHYrGIE088Eddccw1e+9rXKq9dvHgxJk6cyP/NmTMn1jZER7okdT04ZgX04qSk0L2xp7HgpqV0plYoEOlvbBTarCApBZCmRo6Xstl9LFg0k8SYzDYaP348Hn30UTzwwAP4/Oc/j0WLFuHOO+9UXnvJJZdg8+bN/N+yZcv03mwbpJ0q3eugPdqL/as/3THd01pa2SCpVpVOedz2fA0r+joli08aSFE314JEA3anTZuGXC6H1atXC5+vXr0aM2fO9P2eaZrYbbfdAADz58/HE088gcWLF+PYY4/1XFsqlVAq6WM87RSpx7z0OMZSymkS0D1+0qgzNCaqSqcX8pL6uNVnYdMv05Gbjnsw/VTljOelaxSLRRx00EG47bbb+GfNZhO33XYbDj/88NC/02w2Ua1Wk7jFxJH+AO5tjKVNIBFsA5tqWoGcqVo8UuYAodBXmNHvjT6k5qLchsgfdSHxVOlFixbh3HPPxYIFC3DIIYfg6quvxvDwMBYuXAgAOOecczB79mwsXrwYgBPDsmDBAuy6666oVqv405/+hB//+Mf41re+lfStJgKrrx9zP3YzAOB3uiiaBwa4zFNKGrhWWhgtlrlcXeUBmn1uW6/U0b+kb3XA6nfHz4810LhbpD/P0ERbXy+7bfyR5vIATO5izfTpDfJcF5b1U8dXSn1c/mOa5mqt5Lb525pKEgBiW2/T1FYAsPvdufTKFMoD1El/X13uvfIAiSsvZ5xxBtauXYtLL70Uq1atwvz583HLLbfwIN6lS5fCNF0D0PDwMC688EK8/PLL6Ovrw7x58/CTn/wEZ5xxRtK3mgiaKZlKtxVsU9lGWtxG+q0gqfnmU7SKjiWLbCoWtrQCdrcBuVxmWqnpmqCFYfeiiy7CRRddpPybHIj7uc99Dp/73Oc03JUe0EGTZRvFj7QXiKShO04gFbdRWi6EVBf3MTRYtQW9aJITKFajWzJl5aHX18asqnTCMCoVXHuT4xLDwl8AmJy8UCLz9r2uTF5eC6VGDVfd/BXnjabyALR/R05SEx/GCiJv0UkfTlycUXXlGWf+LHF5tH3/2FcPpblZ09zGFujY2fyG72uTK8t++KCvaZUNOOUBmHz7o0cB/YXEZeZqrkzz9B8nLo+hQMYX/ucQAOP1CB515f78Iv0HcpP0d+3kH2qXnzQy5SVpWBZOfOoeAMDDumjAicw7dFDmt2A2m1yurvIANmnrLzWVB2DyPnLCh5KX13Dl/V1TeQAm725dY0d3GxnIeP259vIAruyHm+mUB2DyN2qizDea7nPWSVdvkLY+o3V8ue1NozyAQdYq7eUvNGBM8rz0EtKuLNrz6PGYIu1tSpvYKqWYBN129bFk0teXKj0GUpa1yk13cer1eMBMeUkYWcxLsuj1VGndC2Aa6axpBAnLsvRHvIydYEptqdJjQGHTO77Skau6gR5cGjPlJWmMhQnby+h1CuxUWWB1ydkGs0HSVrrTyPBKazPf1rKcuEzfN72BTHlJGELxt0x7SQDpLEy6oHuTS32R3UaQWno4k9njzNQUaSsRwBh4xj04yzLlJWHQIZNGzEuvK0xpFz9LGtp5XlLwk6e2uaR4sLBTPtSkYQVJL/aEytUqmdxDliodNzLlJWkIAbs9OIJSRton2KShOy4jlarSKcWejJWxk/qyoCu2aSw857TcRvrEKmWmPcSSQJYqnTCsvj684kO/AgBcp4uCvL+fy3y1zvIAhRKX+4Qm+u9G2e3fj5c0UHCTvh0tJF8QlLbv6xrGj9Xntu+1RT1jp15y2/g1jVT5VO7FOsYOQYPIPjkF6vjRQpnLv1PTXK0V3TZfoXFdqpB16Zcay0DQubRnQV97Gej4/pTm8a0DmfKSMGwYGG1tAtq0X8OVCcPQJTUVubYBvf1L26gBtqF3/Ngg/antGRraZQLptJXLpuNWr2hHJui80XQDY2Bd0tZWSGu/5vHlla9dfOLI3EYJI3W/Yy/aCwnSNs0mDd3cGKKJXVuutOpl8mKFW9Ad86J+rU2+8LoXZ46LtGJe0o9r6u2g7MzykjRqVVz5x686r8/UQF8PAFVX5j/m6aOlLjbq+MJfvuG8ufw4oJS8W8Ug/Tv0um8kLo/27SeOV9frihMmHT9vTZ7C3qBj5xV6xo5Zq3GZhoY2MtC2Dr72Gm1yZdkP7LdYq2wAyNfdPrc/dAQwMXm3Ah3Lxpu/k7g8hkLDbSvetUCbXLpW/HThJ/TJbYHOq+oJ39QuP2lkykvCMOoNnPbf2wAAd9QbeoQ2XJn3WJfrkQkg17S4XDQaWpQX2tYfNjT0L5H3qdf+jwZ5bp/eqqV9dXfsNPSMHcNq6G0jl+v27Q80UeRzENkP6ZYNwGy6fb5CU5/T5/x7S99zNoncxzTKpWvFz5sf1Se3Bdrun2ucV7qQuY0SRjNl83CGrRu6Tb9pmNjTIxFLjwcjbQ4O0W3V2ynxabQVSN9tQ9vai6VpMuUlcaSTHujK7MFRS5B27EDS0M78mkJ/9nrckgq27xtN8tN4zmkpqT6vdQpOPa6pBxfHTHlJGHZqM2fbwFiqEZMEdG/saQzXMcHDoXvobIMKG4VWnpcxwCacysG1x8dYprwkDDpo0mHY1S9TJ3re8kJf67bCpMK8mpJZX5tUhexU2Ff1b+hjQ3HQOb7I6yzbKHZkykvCEAdND46glEH7txf9utpjI1J2J+hEqoUZUx63aaRKp72ZO3J7U1Y7+T24NGbKS9JIW/vtxUFL0dS9uWuGbjdOKl7OlBbZNDZwtWz92JZim9Lq67G09vdizEuWKp0wGuU+HPi/PwUAfK5PD0Wz3deHg1oyD9HIBjtaKPG2PqyxPACTeb6m8gBMno7yAFbJbd+nNVDn0/48UBOleU1zGxnqJc1jh6BBZL+yqIFSQAKdq7/WNFfrpTKXqaWURwuVgiv3urLG8gBld62YlsIzrhXdMXahxnmlC5nykjBsw8CG/onOa03U1DZcmbppuPXL1SyTtlEDbAOa20flJS8OcE6I7hzRB+19S0HXhZSo47X3udBmXULTHF9ue6dqLEvAYUD73qMTmdsoYaTB59B7BkJ/pB34mDR0c1Sk7U7QibT4PwBpLUjbpaBLZkoxRqm5jTSX9vDKJ697cFfILC8Jw6hW8Zm/fst5faoeCvJmpcJlPrDn/9MiE3DKA3zy9u85b3SVByD9O3TMFxOXByLvc69+V+LijJorz3zL17XKu3vXSxKXBwBmvaa1jVxuTfPYIaDj9sF5+uYoQ570uf2+wwCMS1ymWSPP+aSvJi6PgbYV5xygTS7I+PrZGe/XJ7cF2t/V13xJu/ykkSkvScNq4JxH/ggAuLmhZ8LadVfmQ9bHtcgEnPIATK628gCWK/PaxueTl9dw+3bxsQs1yHPb9wcd46fuyrvHujh5eXBozLW2sQWDPMtvWRrGDpVNxu1DDX1zlCHXdNv+XKOuRaZBnvMvrCu1yAScUghM7n2WnrYCTmkYJveG096nTS6XT/r7e5b++llJI3MbJYx0osx7z0Toh143jeom4UuD+yS9qr9UrmaMJZdCGtlGaaUs994S4Yte58DKlJeEkfoioUdkakg7HTFp6B4/Ynpl8vIcmek8wzTaqpSdRm0jn9f65Pe+kpomCaKMXjzYZcpLwkh7kep19LyippkJdZsK5EzRapf2qTjteTMWgrR1yko7maAXD3aZ8pIwtiUa7vTRew3X3SI75V11WyERS7vibxqHqrGwLm0LFh+V/F5EprwkjLTN8D2PlGMHkkbaC6AOjAWqeO1KYsA73TfQ6+tSWoUZ03RLOvKJgtyDtVMy5SVhiCesbeeEowviAtF7DRcX3vRcG4nKEWRqPBkHvEtcdupuoxQ29JR289Tie9JOJujxg0+WKp0wGsUyjnzv9wEA7y/poVtvll2Z+2qgsGeoFIpc7t2aSiHUSf+erIPOvq+Py6sUiomLq5f0jh86XudqaB8A1Av65wgANIolLvfNGstoAOJz3VPjHGUYJXP122U9ba+T/n63xudcyblyP6dzfJF12MilUR7Abffpmse3DmTKS8KwTRMvT5zhvDH0GLqozH1z+oxrtkHaampqq2FwmbYOmfR5aoDQpxrGj226/bmjpvHaJDJ1zRFAnCe2RrmOPLfNu6dSHkB/25sp9XfTNLBS5xrRAp27szWPLwBoCmtjVh4gQ4dII6MhbZO0TqTtV04augMr00/tTyegMk2kk6qcgsyUXKDp8byk5/IVpY+dsR4nMstLwjDqVVxyx/XO6zdqoiCv1rjMx/bUw5IKAAWrjo/c9WPnTe21QDF5t4NRc9u66ZWXJi4PRN6VR5+duDij5o4f82QN44e0764dP5C8PABmva5/jgAA6dstR16mTy7EcfuvXRZplQ0A+UYNl9zxQ+fNuw/RItNsuM/ZfP0XtMgEgByRizP30ybXqLvP+CcnXaBNLgOdV6NHX65dftLIlJekUW/gPff/BgDwCx309QDseo3LfP8FH9IiEwDylsXlol7Xo7w03P69svGJxOWhXufyrj7izMTFmaR9v6wnP35of95zlh5Kc6Ph9ukvNc0RwClLwOR+taG3vhBt8wPv1F/3Jkfm6n8aeupJmWQt/HHjM1pkAkC+6cq9o/5lbXKNmiv352/QUEpEAl07vt74pHb5SSNzG2lExvMSP9LI5tIJ3em86VTCTSfdPdVU6ZRt+mlT5qdHFqdRrvA6jWfc2zQSmfKSNNJIldYiZeyhB3UX7URqtu+bBGWOgRitNMsDpIFUalj5vNYpOTXlOGUiwtQHXALIlJeEkQp7Zi/u4j7odRI37cGsaQeYa7X32MrXWmSnvbEJ8nU9520rYDf12kZp88wkjEx5SRhp0K2nba7UiZ4vzEhfa9Fd9Pdnah6UFF0nAvtp2pkoKcjUibQec9rZPr2+NmbKS8JIY+I07d4etBRpFtfTAf01d8jrFGTqRJphH2lbXtIoD5DW9BwLMS9pNL7XrdKZ8pIwUpk4RE4PlrQQkPbpJmmkqZD1uvsxzdILwn2ksbGlqrptG0pEWjWVuEzhXvTLTxpZqnTCqJfKeO151wIAzirqoYi2+/q4TF0U74BDl8/k3qqxPACTeYQOmnXSt1rKA5D2naNh/DTIeB2viba+VihpbaMr123rsbrLAxTdNk/Np1AeIO/O1cUlPXO1VnRlnl7SWLYk58pdpLE8gEXmUiWFZ1wn8+rVGueVLmTKS8KwDQPPbLcTAKCpqzyAYXKZuijeZbnaygOYbv8erqk8AG+jDhB5OqjN6TOcr7E8gM42cpC+PUZ7eQBX9mSdbW6haegdVx6ZmstApD2+JqdQAoLOq1enUJ4gafRei8Yw9HmNUo5y14jUYwcShm7TcypjZwzEJGiPefF9o0l+Ci6NtGIw0nLfpB1zQuX3IgdWZnlJGEathg/e/VPn9es00NcDsKuuzP/uqoclFXDKA7zv3l84bzSVBzDrbls3HvSRxOWBPM9rD39r4uKE8fP6y7TK+8dpeijNzUZdaxsZaFu3HPJRbXJl2f/a4T1aZQNA3qrjwn+25uo7D9Qi02y4bTaP+5QWmQCQs+r44N0/c96cvrc2uahXeXt//Kqz9Mltgc6rkUP1jm8dyJSXpFGv44P3/BwA8EMd9PWSzHe/Q9/CmLcsLhf17+opD0Da+un3fSBxebRvv33IqYmLMxoNLu8nGijsqbx73qyH0twkffpjjTT9puXK/cIH9JXRAJzyAEz2Waedr1U2AOQa7ly9v3GFHpmWO7a+W79Ei0wAKJC2/qmuryyBUXfb+/Ojz9Aml8Ekc/mKD+qvn5U0tLiNrr32WsydOxflchmHHnoo7r//ft9rv/vd7+Koo47C5MmTMXnyZBx33HGB1491pBHxnXaUu06IptH07iMpaDc9p+FO0CPGKzdFl2O6pQmk/JtU3EYas358XicuN/VU5d7eBxJXXm688UYsWrQIl112GR5++GHsv//+OP7447FmzRrl9XfeeSfe/va344477sC9996LOXPm4HWvex2WL1+e9K0mgjQmbPqTRh9EhaX3Wqubs0dc6FMYr733CJUQDzV6Gy2L0/acA+4hUblpMfv6vtEkPyVlURcSV16uuuoqXHDBBVi4cCH22msvXHfddejv78f111+vvP6nP/0pLrzwQsyfPx/z5s3D9773PTSbTdx2221J32oiSIWxtNcT/Al6nUVS96kxDUUivZNxmjwvrjzdFkOPuDTWJY1Iz7KXbuJEr28DiSovtVoNDz30EI477jhXoGniuOOOw7333hvqN0ZGRlCv1zFlyhTl36vVKgYHB4V/YwlpuDV6fUOn6P1Tu94NNp0slDSViJbcVKSmI1vuY33K0xh4zmlls6VSObwnF0SORJWXdevWwbIszJgxQ/h8xowZWLVqVajf+NjHPoZZs2YJChDF4sWLMXHiRP5vzpw5ke87KfR6obs0kGa6qw6kmcKrS3ZqJ+OU5Hpk63Ybed734sxxkdp6mHaqNH3dg4rMmOZ5ueKKK3DDDTfgt7/9LcplNTPiJZdcgs2bN/N/y5Yt03yXwUjlJCvI1yMzPfS4lSnNQNIUBmxqPBwpaon6LS/B73XI1WsBSWeNSNsC3uuxj4mmSk+bNg25XA6rV68WPl+9ejVmzpwZ+N0rr7wSV1xxBf72t79hv/32872uVCqhpJFqulM0CiWcfM5VAIDXa6JobpZcmePy+soDVPMFLvf3Pspm3KD9u4eOUgjlMpdXzRcSF1cvFLm8kzXQ9TeKbn82NJWWqBXdcXOyRhpz2rf7ayyjIcs2NM5RwNlU6Vz9sCbK/Bpp82s1PudKzm3ruZpKXgBAk8ylSl4/Kwnt7/kplCdIGon2aLFYxEEHHYTbbrsNp5xyCgDw4NuLLrrI93tf+tKX8PnPfx5/+ctfsGDBgiRvMXFYZg6Pbb8HAOB1uijzc67MwzTSYTdJW5HLaZe5m462kr7VAdq+k3IaygOQ9u1paHqGht42crmkb/c19bRVJXsfzeUBbFuUr7M8AJP5Go39TddgW9O6BIh9XEqBnp/2934a55UuJK4OLlq0COeeey4WLFiAQw45BFdffTWGh4excKFDgHXOOedg9uzZWLx4MQDgi1/8Ii699FL87Gc/w9y5c3lszLhx4zBu3Likbzd2pJ1t1JOuFAI7bcdywtDtAhQzJHo7VTrNeKmx5NpNI7YptdiTlFKl016a0h5jSSBx5eWMM87A2rVrcemll2LVqlWYP38+brnlFh7Eu3TpUphE8//Wt76FWq2G0047Tfidyy67DJ/+9KeTvt3YYdRqePe/fu28OebDeoTWqlzmf3Z4px6ZcMoDLHzw96170FMegPbvhn3/J3F5dtXt2x8sODlxebR9xnEXJy7PrLvy/vGGMxOXBzi08TrbyJCr17nckQP8LcFJgD7X+056h1bZti3OVePM/bXIzTXc/jaO1sf4mrdqeOe/fufIfdM8bXLpM/7JoW/SJpfBJON79EC941sL7B7D5s2bbQD25s2b074V27Zt+2u/e8S2nfXCvub3j2iR+fRzK7nMs67+mxaZtm3b8z70Ky7X3rJFi8yv/PYhLvPiH9yTuDxrcIjLm/ehXyUu78u/eZDL+86fHktc3vW3/IfLO/ELf05cnm3b9vu+c5fWNjJ86qf3cbmf+um92uTatvhc3/TFv2iVPVytC3P1joee0yL3Xd+8k8v8+u8e0SLTtm17nw//msv91d+f1Cb353cs4XL3+fCvtcllWPiN28n4vk+7/G7Qyf7de46wMYcs2yhJ6I6o196durONUuDiSG+IppgNkpIrw5EX/D4xuT6vdUJrWYK0U6XFfPwU7iBZZMpLwkiHN4PGLfQ2aFt1kG1p32iE18nLTmPBTa3mTYqxYWnOS1m2trbb6agvY+Ewp3vdkNFspio+EWTKS9JIQftNhasjLWhuq35ODr3WgXRGS0o8HClODfG5Bt9Iw2rizqfWoFK3YpcNpGQV0CkrLZr+tMsD9HYuQ6a8JI00rCC9PmgpOjnLrdtSxRFX3I5FNz7avTzdJ/QU5aVyINeINN0YnVh9vn/3C3jnDx7AZ25eEo/sth+IWL+lis/8YQkeWboxFvlhZMaJtCwvaVt80ibJSxqZ8pIwmimskL0+aCnsDnbbvy1ZjeWbRvGbR7qvUK6bSl1cAINl1xpNPPTSRtSt7m3EaVDFd9LGWOWOEbdRO9G/eNBhDf/Zv5bGI1uOeWlz/bfveh7X3/MCLvrZI7HK1YVtqVwKRa+v/ZnykjDEwoyZ2yhudLIwVRvupt6tCT5VS0gb2df9/Tmc+q1/4jt3PR+TPF3jddtRthk66efRWjzuIleg/72o8M/n1gEAlm8ajSjWVr7WiTTdkqnGy/XgvNLPWbyNoV4o4m1v/wIA4EBN1NR2qcxl1jTSnlfzBS73Bk3lAeqFEpc5pU1bDcN9PVRpoFzonG2T9q2u8gBM3hFtKNW/21JavvyXp/C+V+3WlTyrWCLt0zN2aBuP1FkeoOjK3SGF8gC8nzuQ3WzaME2j/YUBYOUBmPx3loLlD1fjUZ6qebfNB2miq7dtsa0ntRlfG4Zr+OYdz+Idh+2EudMGIslu0GecL8C2xTUoadRIf88uJr9W6UamvCQM28zhvh2d2kzzNVFiU5n7aqJ4Bxw6bCZXZ3kAJvP4NhTc1NoyVKlju/GdL6B2znTbqAG0fa9s06dD1UYM8tz27airPEAHbazULXzj9mdx0v7bY97MCdHkGq7ct2im6Kdt3qVNPxtkxxus1DGpP5qixcoDMPnntlmX6LypNZoo5rvrK9rfB2haH+S2ntjmOV/9t6fxo3tfwr3Pr8cf339UJNnNXE5YK3QbP5qmiQfY+Na4D+hC5jZKGLpTXQHRPdXrPt5O4ntGalR56W6jTzdDRbO8MVge4P/++SK+ccezeP3V/4gud4yUlmgn2iKBc5tH67HLayefKi9xubDGQpC2Cje14uEeXzEYXVbabqOxMbwTQ2Z5SRhGvYazH74ZAGC+Mnn6egCw63Uu898z3qpFJgDkrQbe/u9bnDf11wGF5E2VBmnr2j3ODbyWLrwjXS7CtG9/vv/ru/qNTkDHj3Fs8hTftD/vOvbNba+3bVuwDHQDs9EI3ca/PL4qkixBLmnryL7nxfa7YUCf6z9f/ZbAa2skALvbcUth27Y4V0/f1/faZtPGIFH0axGCwU3L7W/jCE1rIaR16YTgoqqlQg7o8mDjQUNcK3QrEKblzqvhfRZqlp48MuUlYZj1Oj5763UAgC+/911aZBq1Kpf55uPab0BxoWA1uFzUrtSivOQadVzaknnhacG1eOjCX2l0qbxU3b791T7HxbJ5B8FsuOPnmovek5gcBoOM19cceVLgtRuHa3jTtfdgjxnj8b1zu6/+nmvUQrexEGN13FzDHa8fPfPs2H43DOhzPf6YNwZeW2vErLxAnKt//ox/zbXBSl2w/ETJZMuRsXXl/+hZC23bFtr6k48GK8dxWkfMWk1aK2L76VDI1V35F2se3zqQuY0SBh2vTR0UsJBdVb0NcbEJbq2gvHRrefHI7+pnwssLafqVF1264XUrrx3+9sRqLN0wgr89sRqbR6K7M4DOxmucG027X6o2LHzqpv/iz/9ZGY+8DlxltRiy5PxkA8FtX7elJryPloYfUmiM6FSMmeBBJF2ahfbX163mVpWdmikvCUOMP9GDbSpVmr5u09TRumsO7try0iFHRlQ0Qypnsjl/uMvg3U5qG1FlcO2WSlfyHDnhr6VWgGqXCporN3y81A/ueRE/vu8l/M9PH44kk8sTylr4C7dtO363kTSOgpq+RRpHUZSXNEKMOp2veZLJ1e0BwFd2mjQLba5lBJ5v/+59id5TnMiUl4SRDhHWtsOb0QmPDl34R2tdLkyag/DC/rq8kcubTmh5HSx4G4bdU3mUQFJxMw2WWo9TeQktFVhBOE6sGCyoYdcFuY0jtRjiMToYw7KyUrfiGe/6in5KilobsXniloydX6cNqg0rloBsBvFgF9zw+55fjzVDVdz3/AYMVeK7hySRKS8akUb2hq4zjqdeSgqLUzuJdDHqmqSug1NrHAirTFTr4iYz2nX71LJV2DgSk/LSgcJUJe2qRnShdGKhpH8ejkGBCDtuZItaLG6jDq6VrQ9xsTfrOlR1anmhB6Coz7lTxens79+Po754e2QyQJXAdu1eM1jlr9cOVQOuHDvIlJeEkQZ7aKe+zlhkpmQi7cSyRTf0rjd37e0Mt7NXJTdY9yZvuuAFN24jiXOJS3lpt8pSi1Klrs/yQjeykRhI28IqTvJzjCfbKPi9IN9jeYmgvIwBK3CYEhsM3a4RrizpfcAo2zxSx/0vbMBgpYEHX9wQSa4rz++NF3RebYrR+pMkMuUlYaQxX2lgsDbfcpv3OuS2k0kX/m5P7d52Juw2EnSX8JucrMyElucjWwVqXu7aDQfZehYslMbydNtGLqsDkw8NSI7D8iIqif5IRHnxWA/Dj6tao/vx3slcTQtUWWtEdJF51oqAn6NWTNmK2rX8DlzqdF51m8ygG1mqdMJo5ItYeNplAIC5GujkAYfincms5vTIbNo2avkCl/vdoh66ddq/zVzwcKZuo3qXcQt20ZVXa1F+Jwnavr0C6Prl2IhuF0Aqr5YLfoZxuOEcOYVQbQREqvqolpd6wZU7UAgeOzTAu9tgaAqhn80OnmvEOB/A2dToXD05oM/jdBvVcnkucxdNpSfkth7RRi5tb6TgZDjlAYS1IuBaSpq5abQWcGV41PJuf/e12Xuo5SUOBVkHMuUlYVi5HO7Y9WAAwNlm++5mp8Eo3CF2Ls9l7qKRhtsy3bbaeT1Di8o8qo3yQoMdG10uTHbe7VsdoONnXkD74trkmkTetA5o46NsqhYZr0FtbFhN4WTcbcYYQ5PIfUObuUk3tThq/VimK3tGAHdNnMoDgw1x3pwU0OfegN3u5dP+nqtrXYIttPXwfLBc2t9RCPkAcS4BwS6roWo8VkxRvtvfx7fpb6q8RHWX6ULmNkoY9IDfziS+eaSOY758Jxb+8IFIMlMJjOswOC02uR2YRumJotusCVmGTp6XIMhusK7dRh04yqnlI5ILJ2Tckif+IqoVooNnJ8ZCxBGwG26OepSXWCwv4YPOvW6jeHhexmIsntW00aCEfHGnSgdcSy0vUZVylfx2/U2tibqzrLpFZnlJGEa9jtP+8zfn9UHBLIcPvrQBSzeMYOmGEWwaqXVdgM2ouTIfOeqEttcvWTGIZ9YM4U3zZ3clD3AmR95q4JQldzrv668B8slXljYaNd7W1Tud6nud1bQF60DXpyrStzftdWziMS9Gg4yfI3b0vy0rHsuLSeT94+DXBV5LT2hRXDimRds4x/c6z0YeMWWZ9u3Inm8LvFYYOzEoEHRduPvQ432vq1niRhKL5UWaqzjlFQHy4+tzs9HgbTYPObfr3+kENsS2Gq/d1fdar5Ur2viic+mmvY6FHfDoqPISl/JA+3vLHmcEXrs1Wl4y5SVh5Bo1XPmnqwEAl70jeIFcNegSfb28cbT76rF1V+bxr3xt28tP+LpT5G7mhDIO3WVqdzLhUI4zuZXq5UBf8sqLWXdlvvP1J/teJ0/Ibk9Vds3t2z/ueSSSJk3O1Rv4Ukvele96h+91coxLFOWFte+VB74q8FrRbdT9gperuzKvPN+/jfLm0q3rTyX3f98cXF+IKg1xxJ3kGg18sSX7yINe7XudLKsWE88Knau//vh7fa+Ls89zZGx9/tzgUh5xgZUHYHK/e5F/DSuvchztORvSWhF00NlCgt+jBqIz0P6+8E3B43trjHnJ3EYJoxPT3arNrvKyKQLdeicy6WJ01zNrY5GZFoIWB5ncq+sTrMcMnXC2UehU6XiUl25Tz6Ns6GGzUGQZjYiaYyduDGqBiMPy4n8nIuQ2x2V5CSneY3mJlIEj0EboWTA6yQ6sylaumJ9zUJNHyeEjaiC6Ky98fheN44p/fCeDTHlJGJ3EEAyS/HqaOtexzA5ST2lOf5SFaSzEvAQuDjXZ/N5ltpFmkrqwlOryaa37VPBwKbyAaHmJkm1kh9zU5I07eipr+LbSBT2ujB+GIB0smYDd8KnSdSk1Oqo1wpWZDjqKL4o6vjqIeRFiqhKwfLQ9iBCZsqtyrCJTXhIGHTPt5v0QJQqKorx0cHreGBfFu2ei6jpZhduAZFNot5uAbpI60TrgL8zL8xKDZSmgbQ2rKSzusVleOrECxLSRtpMLSFkocSgv3QbsJmB5Ce7z+KwRYyFgNwhx97XH6hM0f0k/JxKw2+baZC2LySBTXhJGJwNoCwnaGqx0n9EgFINsI3Q9UV6i+Dq9E7Xrn+pacNDiEJvy0vaDeBHWvB6b2yik7EpMvDKOHLV8GcmejIN/K84UWllcZ9k+0QdcB14jb8xLBFddWMLFWNGBm1d+rlGfc7eWlzhKQMgSO2EWjqt+VdLIlBeNaLcPidTn8SgS7QbtRkF56V5h6iT9Mk6EPc3F5jbytDPpmBcq2/+6uMoDCC6cgOvk/owSZBja8iK1yYpoeUkz5iWs3pRMzEt4F688T6JsbJ1SOGwaqUUuRNmJOzt+y0t3skcTYNjtxPISh1tUBzLlJWG04x6hiEt5CXuqA8T6NFEsL/KBTFtAXsjNVl4Euz1VaXcbdXlCj4XnJUCgPD4jLXjCMwx/Mo7T8hL0S82mLciKRXkJGedTa8RjMRRke977y/cESWuqbbR6sIKjvnQHTv3WvZHWkm6tH0ASPC/hxnbUgqOuPP97Ea6z7djdojqQpUonjEa+gAvf9HEAwEA7iuZKPLn2zWKRywyiHgdEcqLhKIFitkOBzeReUSp1/1sdoF5wZdYCmEI9qdLdKi+lkiuvDeV3HKDt276D8gDdZizUC+7YqQaMV1l5ibKp0XEzswOq+qip0o18nsutB4wdL4dO9M2FPtegfmay+4s5jNSs2GJeaJ8HUebHaY2oE5lTCsHr0v0vbMBQpYEnVg5i3ZYathvf3XpiQ2zrvAC5cbslG3QdzhdCW9iiZtHx38y57a4HjDG5nbG4RTUgU14ShpXL40/zjgQAvKUNRfNQTBVzm0RmEPW4LHM0itsIDg03k7u4DVV/XLBMt60HBCkvLcUsbxpoNO3ulRfSt0DyFibapwsDxk9cJ+Qm6c8Bw3/syMpglAWXPsN3BikRMadKW2Yef23JPbYD5SWOkylt83jD/7kyWQOlPEZqVkw8L+JcPTyglAebJ4bhKD1RSOpom9/ephzDS+uH+euVm0e7V15ssa17dDCHIse8ELlAsNWHKhBxKKiAU1qEyT8qoNRH7MzVmpC5jRJGJ5Vr47K8dEsLHaVmSyfcEXGCiglaV9nCNL7sLJrdptnqTpUOHfPSGi/lgjOluw9IDueGk5Xr+GIhNLqN6OsOYiHiOJmG9M5x2eNKzriNpzxAuw+88geKbN7Ek23UbuZQd3akdUl+rzG+qBPZ1D0Ym/IQcnrI8jLLSwYAgGE1cMKTdztv9vVnOWxYTZFuPYoLp+HKfPjAYwMvpcpLlEFrA8g1LRz/9L3O+8arACRf0dpo1HlbV27vT7POTP0DpTw2jtS7j3mpu337lz0OTzzmxSTP0jx0B9/rWHvGlfKo1Gtdn5ANIu+uvY/0vS5OFw6VaRziX6JC3kyiBuyaZG6O7PpG3+tiS0MnoOP27n38+7nKLS/OyTmumBc6V3Hinr7XMnl9xRy2VBuRFEbaZuPA0wOvpTFqUWtJCW09dmff67zKcbS+pmv/X/Y4PDjmhWb7xOQ2MiyLy9+y80n+shOwLOpAprwkjFytjm/+7goAwMWn+C+Q8ukiSq6/Ua1ymUfu98rAa6nbKFLRNdtGseG2dWPlo8CEft/rf/3Qy7jp0eW48vT9MWNC92UEcvU6vt6SefpRATTrdekE263yUqnwNr7iQ79KPNsoV6/hmpa8z5/pr/yy9g2U8li3pdb16S1Xr/H2HbDnb3yv8xDGRVhw83V33HzmbW/2vS7umATa1ne9LqC+UIzFCV3Z7rg9aN5vfa+rSpaPuGJe6Fz96f/611xjG9tAMYe1iMatUyAyP3X6mwKvpethJAoHqa1fP++tvtfGPr5qNXGtCLK8kOcal9uo0HD3gYXH+dcpS2J860DmNkoYYU3TtCQ64GW27F5m8O9Qy0tc6a6q9zIu+c1/8I9n1uHrtz3TtUxZUBiTsGt+79Zt1O4DEXc9vRbX3PYMrC43d9EF2D4rhJv3Yzi9hVlsTcN5H2XBFV0o4U6nQHSSurA9FCtFvkJ4UEYik83cnXFwcHhTeNuPq/5itHnjuYc2P0MtLyOR3EbhnVVxb+Ldyo7LbRTa5Zy5jTKoEDaVl6ZJAxFdOCFlApLbqNGEbdswDKMLmf73oAJr39OrhzqWJcgRYjSCFmFnARxXjmh56SD10rZtXPjTh7Gl2sCOU/u7qtrdDBmDEl/7wsmjsRBD1Ua00hIhSRW9QckRY15CKr5xK01AeM4TGrALxBRv08EYZuOIu60itL0T3hHR8hLBbdTBqSrutPRO1sQk3EaC7ICGy+3MLC8ZAIQ/OW+RGHUjnWQ7CNilpdibdvcn9k5OGbQfzC4UJfG31K9lyIGP3W8C8qnV/8rNo3WulK4kRTc7ktatZSkOBuEAeez3+1ubWlxU/cEbqR34PoqsTrhOYrF+hNzIq5Lyor08gGR5iaYwhlPYAGCYWl5iIux03ncSEK4vYJeOsbrVjCWLsVvlfGuxvGTKS8IIm70xVI1RefF5rcKwdKqJpSYO2rnIXJmRlRfyOky2Edvcu8428pxa/X9ncJSmoXdbKDGcLO8mF4ObKoQLh7sTIlle1K/9ZDJEDdhFSItPMsUR/d7IslsWtTizjbpwZ/QXoyupnezHskU4LpmdPef4LHvtQBUG20bXbmZBfsi9Z2sN2M2Ul4QRlrGUTdZcK4ggrs2gk/RsoPuB62HYDRC8adiN74lK+BU2zTYRywTCxzF1WyU87ALotq+1ycSRKh3G8lKMJo9JVb8W4SkSGKN5PWwwJRBPzEtYd6esPMTR5k7cGe5zjkFJDbgHGTRIN1rRz/CKWuw8Lx1YaeMMgFfK68TykikvGQDZMuA/ghhvxoRWzEKk00bIDR3wZjl1TSvvMb34X0s38iiVrIFONncxJqTRtNHsYoHowIUuKIabRrptZzhlgvG8jIvV8hIgL8ZNtevYkxjN250ECkeJ++DywrbZEpXuONscBm7MTXyp2mEQl+VFRqj4Ijamo8rt4ECXCJdQWCtqS1Yxb8YmWweygN2EUc/l8ZETPth6HUADTsz+UXhIAMDKF7jMIMr8asOKzWRo22JbLy7603BvIMpLlOrZANDIFUL1r5wqDTibUCmAeVKFZoHKywfHMcVQq6phuvLKIWjko8ZGNOjYCegbphz1x0BeViMyCwHPkMks5U1UG83IFpC6GW7seJWm6KdiOm6D5qjsnmu2XArMQtsN5Lk6L3Bcyc+5+7bXiEzkg+cd5byK6jaibd0ugE2Yul6Ha1Zk6wedS85a4X9t3HWVHJmdje9xpTw2NGraFNSoyJSXhGHl8vjVvscBAI4PmLBV2bcdYQA1CwUuc1wADTe1ukzsK2DzaL1rE60NoEHa+pGABXETUV6iln+nMoOov+XNHXA2w1KHM8DOu30LBJ/kqPLSLWNyI++27+0dKGfdLrxWzm1fUDiS7M5o2k4BQ7OLTbVh5rjMt4bYXPqLOVQbzcgulEbelXtIYHmA+Isj0nEb1GUySR2Tn+tQ6aZo2rYg/xMBfc5ibrg1IkLbqcy3BIzlOAthyuvSe4I2cbpGDFUjP2e69rN78ZUdc+kLQJxXB4VQkAdKOWwY1mddi4rMbZQwwvp5Zfr6KJp32Iq1zDTbV8ihr+AsTt1bXmTfsr/cjULMS9SJEtatorC8dCG7kwBAmslV7bJWlR3ScS0H7Ha/4Hca8yJasqJJ7CzzJWrAbqcxAXFs4CqBYTa1AdLPUTe2TuK2eGHIiEqxLLiTANJI/FOedSlAbsIusk5KX8RSuTysbA8RYnyxZEkis7wkDKPRwKuee8B5vefrfa+T+RwiDaC6K/PBPQ/2vYxZBgZKeZRaNXG6jnmxHRruo1942HlfP9r3Wmp5icItA4j9+/KUo3yvY+3qL+ZgGo6loJvN1m7Uuby7dj4wUEmLw/JiWGT8HLi973VyVkq3WSG0P+/a+UDf6+SAXeezzi1ZAGA2LLeN82f6XleTZEZdZGlbR+b4szNzpSkmd4IsO6if5XUBiB73Ytu2MFfR2M33Wtc9GD0w27DIc953uu91cQbOyusSXjnH99p408IBSM/Yb9jIliYgHsWJzqvB2a/yvU6ey1bTjuya1IFMeUkYuXoN3/nV5QCAC1/7Gt/rZLdRzep+UzfqVfygJfPAj/7W9zoW0d9fzKGYY8pL95Om2KhzuSuuvgjAeOV1cpxLtdFEudCdGTzXqOO7LZknHPAn3+tYu0r5HAo5J2aiq82v6vZtO8rvOApt5upu+z75Jn/ll2cbRWRiNWs1qX3qMchdOMSd0e3GVrBcmZe80b+N9YZkBYi4wOcbrtyzjghSfF2r3dqhaizxCHTchunnPklJjAIb4lz97nmnKq9jmxjgbmxRqloXyXO++ER/unr5ABXVCkHb+sUzAmr8xJSRyJCri3PJz+5DlbNizkTNasaiIOctd6064/CAOmVKl3o016QOZG6jhBHWdMfcCuPLrk82aa4OWonYtbx0H7Arvg9nkXDuIx4XWRC48lIwuaIWD2eGPwTLSww8L77X2Lb2VHBesK8QfVMVWX3bm9b7C4xzJD7zdhg3RrzpyuHSaNlzLeZMFHKOchO5LELILBiqNMRSVbpLXp1IqdLhkyBjt+yFdTFT5YW5rGJxG4V100lrBxDv3EoKmfKSMMLSrcsxL0A8FPZh4mzKhRxK+YgxLx1wGsjcMnHVVAozQYs5E/kc49LpvK1yunuQ8kRjXroOTA4xfugiy5SJuPz1fjJ5f+ZN5M14NtVAgYAnSDhO+vZOYgLiSFf2KIm+sp1x4/Sz2ZIfdWMJN1fppuoyKXcvO+w3Y1VeOliXvLEfEcdXSI4Zeojqj7MAp/CmfbycEL+2FXC9aFFerr32WsydOxflchmHHnoo7r//ft9rH3/8cZx66qmYO3cuDMPA1VdfreMWE0O3QVNAPKfnoAWDbajlfHS3USeBrB7LS0wnq2CSOqetpYKJQi4Cn0EHJ7nhGFKlBVk+wqjSMBA3g7CPUDY2qTLYtUyf1zLk4NGoLKSdKr4DnAAwDsuL/D7YpVDKu/0cmTwt5O1TJSIOpTi0JSBBxtcw9c8G4ghORueWl7xpoNTiWombpC7o19gzLRdMQpKaKS+48cYbsWjRIlx22WV4+OGHsf/+++P444/HmjVrlNePjIxgl112wRVXXIGZM/2D97YWhCf9cuNPmOu720UqbLZRhWzo3G3U5SbrsUgEtFYuhRBXNkFg/9bFmBegO7NwWLcK4A3Y7aZeSZivqCwvjaYdT30Un88psVXBZP0Zh6UwjIIfj1lfyH4JY/GJszhim/ey7FLedXdGLkgpv2+noOZdhT9SAc6wbNj1+JSXbsoDjEsq26iNe65IFNR4LB+uvMDK5Q36nONRkHUgceXlqquuwgUXXICFCxdir732wnXXXYf+/n5cf/31yusPPvhgfPnLX8bb3vY2lEqlpG8vcYiWF//rXBeOGWlz7URmhWzoxSjWCHS4qVdEttlKhJgXiqAJWqWbADvddNFW76IbTklj5GIdywuRukwX2agxKKFPiw3nDwVqeYmhqGcYCwjPBoka+xFSLq+sXIwx1iZEzEvDavIMFWFji73asfo66mp116Rk3ZFAzKnSHVxblZTU6P0c0j3X8CqJsTPshlDaqPytIV06UeWlVqvhoYcewnHHuUQ9pmniuOOOw7333huLjGq1isHBQeHfmEJIywAdQFyRiKFIYrA1wg3YZRt6txp/J4FxXrdRFMuL/z0wNJu2aCmIcLqIoqR1JU94lmph7DScNw3+HIHuFl+vnz7YneG4jeK0vPhf52ZFMPr2GM36ITg4Boi7qpvSEoH3ouhn6k4VYl4iuzPkZ6wGnTNxKE6d8uowRIqz6SBGTX7O8Vu41NdVFUpiPPWz2ssGRBdw3Epqkkg0VXrdunWwLAszZswQPp8xYwaefPLJWGQsXrwYl19+eSy/lQQauQI+9dr3Oq8D2G7FVN5oC4VVyHOZQRTvFSKTTeruNX4b9Zwrd2HBn8mSBewymvcolhcqs2aqZdI2lSKeLqx8kcur5/IdKWn1hg34V01Qok7Hjw8TKhsn+ZzBNxmguwWwQfoziNKcKbmFvImCGS3mpWa6bawHsL16igRGtLw08lRuAHuxKh6ti9ISFHXaZp9+ppu4kG0UOZBUnDfTfdrO5BdyBncNRlEkwj7nOKny5bbmgkohxExGaOWlZ9zuIEAOVnEoD3UzH2p81wTlpXWw2woCdrd6npdLLrkEixYt4u8HBwcxZ44/EZFu1HM5/PhAh1vgyDZ1hgBxc+12AFm5ApcZRBNTIZYXtvFESc9u5PJc7jt9lBeraWO4lTY8daCIFZsrkSYKlTnbp3/pCbaUz7mWgm7kFlx5QPCJZkRKj+5GMWyQ8eNHqc4WukLOzfzpVp6VLwjt84PK8tKtG8ciz/CNITaXuGIS6NjZN+Bg4ca8UE6b7gj5GKx8vm0/sz7OmQbygoUrusWJtv2DPoqEyvISxSJAn/MbAtdC9pzz2FJtROKWkdt6dsj6ckD0fqbrMLuXILlxu41ou+cFKNpVpdtoG1depk2bhlwuh9WrVwufr169OrZg3FKpNKZjY8JyrvDAPBLz0nUMQUgzPLN4lAs51IymcB8dywy4B4rhmmuNmDLOUV6SzjZiiqFhOKfIYoTTTViODMCbYRRVnp8kNk4KOROGYaCQM1C37K6UibB+ejeY0yAuhW7Ha7hAzrgZUEPzy6h4MCK7FNr3M405ARBbSnrY9GEVvUAU8sywPC9u1k8OW6qNiBtpODcoQNxGCcRUBUEVWxS32yiUfBoUvhXwvCSqvBSLRRx00EG47bbbcMoppwAAms0mbrvtNlx00UVJih47sCwctvQx5/XOR/te5vo9o7uNYDW4zPt32DuAvdO1vLDFpPsMJ8BsWjjk5cdb93CE8jq6oY8vFSLJBAA03bYu2/sg5SVuphHb3Ls/3djkeTp9q76ubnkZfLt6nk0yfvabobyEu41am1shZ6JuWd3FhDSl9rXLkMjlXJdClwuuQdu4jz9tfNy1Z6jc4ZmH+8tVEPJFPhnL40gZ8+JyvACIb2PzzNVdlJdRix7b1ADHekrdk2Fh0uf8imm+11FlcTWiFUj0rEsLZreV219ys9milC5BI/xaAcgu7eiWD4OMsc3bHeZ7HX3OhShWac1I3G20aNEinHvuuViwYAEOOeQQXH311RgeHsbChQsBAOeccw5mz56NxYsXA3CCfJcsWcJfL1++HI8++ijGjRuH3Xbzr8ExVlGoV/F/P/8EAOCdh9/uex1lgI0aAGlUq7ihJZNR2KvmH802Ypp21wG7sFFq1LncZz+3UHkd1fKjpmcDQKFWw49aMo+57PfKa6rSCTbKJmBUKp6+VYG6jAaKOQzXrK6sWsVaDT9uybv4dccor2HtKEgn9G5iQvLVWqj21fiCRywvXZ5UC3VX5ode46/guwyo8Zj18zVX7pvn/8VfrpRK2q1Vi6JQq+GnpJ9VB11qzgcQH88LIMzVr79NXZKBpmnnifLSaNrIdxHuU2i4/X3Rq+7yvY61Ly6aftrWy97oX8NKZqkGnLYWulDUACBXl9bhNgeBQi7emJcimVcn7/dn3+uE8Z3felKlE1dezjjjDKxduxaXXnopVq1ahfnz5+OWW27hQbxLly6FaboTY8WKFTjggAP4+yuvvBJXXnkljjnmGNx5551J327s6JSqvxQTp4JwD21klgsm6lZ8GSNBMlW8FZEKrwXcg0dm6+Qc5XQTtno2KweQMw0MtAr6dZfd1N7UXieKBOBudt1lGwW/98jMRz+tiSnLaom2bXuyQaIzoKpfyxA2cdOxasXvNvL+HpULxGd5CTtX/WKp6lZ3tcg6paunsSddu6oC7oFCVccJcPq6y7JrHZPUiTEv+rKNakrLzzbuNmK46KKLfN1EskIyd+7cWMi1xgo6HUCxRJwr0wP9i76VCznuWoniNhLe+1xHJwrbZCNFtodYEGkwNODEaQAxbe4+Qlkhxv5CjigTnY/rTkjq8tzy0v0mFza1VPTTR+R5CRGj5ZDuOa/jchsJNAYhUmh54Go9Aa4VlVzJ8hJbbaOQNNGqQE4gCpNy2JgXUXkBnGdQ6sLc45UTPJ4B0fJSs5roQ7dZZfJBRw1VP8dRgiIsZYYwlyMSTupEVtsoaYQMnqUMsNzsHwNJneo9Ay0PUOCKRHcywzLs0onCFuW4ape041Fgygvb3Ls53YTVq0dagcllUrE7ai0lP9FsM2MLX5ymX/9TufMXyj+SZDkLVZFAdiJPGjS+pxjTyTSMEkwzugCQfo7b8tJmruYd2nhmfInHOhugLLI6b0KV4+gKk/cevDIBscZPtEKU8vswa2J8biPx4ByknLtu50KM8pNGprwkjDAmcUDcYKMGbYU1V1YU9X7iGrR+h0Mh5iViMUgg3ILonmwScBv5WV5qbrmHKKnvYRYg2W0UJYA2rGVJlYkSRz0lvzlCn5Vg1o+pUGBYBtK4WG7DnDBooDlALC8xusuAIHeku6kBrmUvnqra/n+T3UZAjOSZfgccS8xIdDO7IoyvsNZoZap0HH3c/uDjK38rCNjNlJeEEcYkTv35gumwS/NwWCuIUB4gQpwEEP40VxWUl+gTJcwGROOJHNnd1w/x7jlqocxt1FfIRbKEhIkT4G4jkm3kfN5Fv4Y02/GA3RjGKxXSTlkyDQjxFpFq7YS0BNAxGxvLbYgUXtfF6rSXW150MezK2U5mNOUpjIUNINldxVzM1p4QCkSLbiCfAFlbmJiXqFZMQV7I6+hz3ppiXjLlJWGEMfuLJGo05iX6SVb13pVLygNEnKydmmepwhQpYJcI8lvTaZwNQDb3bmoNhexblm3UR91GUZUlH1kNOeYlCo9NiCXPtm3R8hLVzRlCQfOLv4gW7N1eaaIyYmW5DTGO5JiXvGbLi8dtFbXmmnCQC1AWW4o/dS13X3Ots3XJVdSiK6nebwa7jUok2yeOVOXQAdJEeSpGPojow1bPsDvWMFqzUC6YPDK+kcvjC8c6acMNH5ZDXwbYbssD5InMXM7fbaSotBwlYLeRy3G5b/JhSlVZXqKkStP+rfv1L2tnDNlGTalv/YpBUrdRFPZiy3T7tOETsFiXNpkopydhvOZySmWGLugisVZ3Y6du0jkSzPZK00mjyGSy+NgJYHwV3UbxnEy9/RwsF4iX54XO1VxOPa682U7RAoYbdCwH9beU/VKpezmTOpJL2mq1YRPmbc2bQDWaBcSSn7Gve84d23GSxNVzpju+Df+gY8YHlZUH2Ibx/NoteMPX/oG3LpiDz56yDwCnNs13Dj0VAHBAmxoiLgNstEXKyrsygSC3kWt5iRxnA7Gtbyyoi/jQ01wcqdJU5kQf6m85YDdKam+zUJT6Vg3XbZRH1XBe16zOlbQ6eZYn+IwfWtsIiBYb0chJY0fRQDpGBOr4Lhfcei7PZR7Xpn4TIxrMmwYaTTvSpkbHzq5hlBfByhRtcadtBtSWCE5SJ/H3ROd5sYW2vyevnqs0GxGg86bb5+zKPCaApp8ecKIEuwPO+KVyT/WR68dmHOU5NzzrsBoqht04gu1rpit/x6CyCIqQhcxttI3h+nteQLXRxI/ve4l/FiomgyxS1N8aW/n5NpaXMknn7dpt1Gm2UT6ubCP/e2DwMpUmnyo9ogjY7WbRD5tGDLgxEZEYhEOkd9IxUsgZkRe8MHPEs7nEPUcC/iaY1fPxmNXDhBZR4koAPCNQF89LRYoVi0pGGEYmkGwAaZhYPCAeK1d4971CeYjDbSS89m+HoDxFjH3UiczyEiNUE8y0Gthv5dMAAGPWgcrv+aXydq39Niwu878zdm3Lf1IuRE8BteHQcO+z+jnnfUNNR00ViTiUF9q/L+20p49MteWlq1TpRkPoW79leLSVKt1XyPFx0Y0yYTRdeXjFdspraJ0hwI1N6GrhtaSxoyJPs9zg2XwMcSAGkYk9piqvUblQHHdC92PHaLpyR6bsp7yGkpc5AZXR4nu4bE8/e6+RY04KcdU2ssW5isaOyus88yaGMhD8Oe862fc6YTOPmLort9Ww1DX1/Dh1Im3iTXGt8HMxJ1VV2rQs7LfyGQDApon7+F7HGX5JhfhMednGoNqE8/UafvujRQCA0/f7q/p7UkwG24S63QzMWgW/b8l0KN59ThskFTOO9OxSo87lPvaJtyqviztVmvbvIR+/KVBmKYZUaaMq9636Ou42KuYw0nrdjbx8rYbftOT971F3Ka9xs41a2VQRFsB8vSa2T3ENpTOncrsdO0Ui8z2H36m8RpYZtXgpAORrVfyuJfcNn/9ToFxAjHmJav3I193n6jdH3XUhnoBZBhviXP3iGx9QXievS1EDhgvkOb/r0Dt8r6PzNarlhZUtYXI/9up/tpUJxNPXhWot1FqhsjTF4bYpNlz5r7n8ZuU1QqZrzG6rpJG5jWIEnWBsMQpj9vcno+pekRDeK66xmu6gjcNtJEtpR8gUF8MuFeN3spEZdiNZCkKa3IUMgghBcKHcRp6Ylyg8NsHvnd91A/yo3G5TeG2f1xT0dAog9sDCduMVkNmEo1o/2rvnGA9TOR+P8tCJbCrfYxGO4zkH/ISqynF8mZeduY0iFYX0vG/jSs/Fy7fVCTs3wCxd0eKadCJTXmIEtbyweJIwJHWch6QgTZwYFglAPYjZhg6wgN1owYDyrYbZ1GNRXoT+VUMm+4pE199F6mWUtMswG3uc2UYeJVTFP+IbH9Dlcwyj4Mtpw3GkslK5PtdUSZC1Q14Wk/UjhJJYqbluXSCe9F0gfNyWJ0uPb2wxPOegGAyFJSAO9mbVe5VMIJ5SDB5Fqc3YLsXsNgoTD0jX+7irWieNTHmJEcPVBn/NBkWYk3PV49aIluvvIakLMEkzubpYfekiwVOlG92nSnfWvzEEtIY8yQkLcJRaSkL9HfU1bm0j0fISR/tUCy5N7QQQazmLsJtLVFJFWVoYpckwjBhZbtsriW5AfbxByuEJJSWLZUwxN6p78JMb9VAVlhHbqxxHj23qVHEqEF6buLN92h0mAZYBGt8zThqZ8hIjhiqu8sIWmGaIzdWXjCqGQnd+cplJuJAzkDONyJPGu4m3N8/GQ1JHJbZZhJnvPkJQWnjGTucvhVhZM9XS2ELDY17iJLpSfMaeYUEOEO5ywbNDaKD+m0uyY4efimWXbmSW2+D3AHEbSanK0avNh9vQ5VRpV3mKvkaEcRvFEovX5r0sM1a3UcgDnRtwb5K6a3EoiOGV87xpwDQNEmOUuY22KWwerfPXbIERGWCDN3QPD0mCaaD8VNey9nDOla4D46T3IRS1UocyNwzXcMGPHsQt/12llNue1Tf6qT10OymfTYQU1zCWJVokkcmk99CRvAD5DHLasksbH4+bU4V4XWOKe2j3HOV04YiKYRglmKcqx6B0B8n2g5wqHbUMhGhhC3AbKQ448VmE/ZRUmU4hhlRpz/v2B7rE3EYhqCuA+PeeJJEpLzFiw3CNv+7k4XsDSqNO2BBuI8kaUYhoBZFF+B1MqYus01Tp3zz8Mm5dshrv/clDRC45Xfh8z5+kLpoy4chsvxhGIxdr3z5OUmdGdxuFqYsl19wpRLbaqV8LMn1SWSNV/fW5hyC5cdGne5XEALdRDGUtOpUNqCgcIrpSQjxnwCdgt2tLgDye1ajKFrYYlIiOXVaEZyW6dS3kvLIkpS3jedn2MFqzeHos4C7wDTOPq494O3+tgjeVN9pJ1soRmT7U4xWfirV1qwnbtnl5g7CwYaORy3G5r/RhLI2SKr1kxaDnM9rWuqnWxX0zCbrYgKy82LftgvBE+vzOn2ddGD9qim+5thE/rXax4Avj1YfS3M+F0+2GXs+Z7jP0oapPIhukbuZCz02P5SVqeQAq26efXQZseV2Ibnmhc9Vqy0wdnWIAAGpEZlA5BhVpW9SyJW5b1XI9hIAxWPYa+fbrMOCXKh1deaDtrvuMb+4ClqyomfKyDWH9cFV4z+vZ5PO4+sizAAB7+FCf+5LUdXnCsgpFLhPw8aeT0gCAe6K0bSfWhtaPCQXboeFmcg8rhigP0GG2ES3Ix0Blsk1UhmvZkn33XbhVCgWxb32uo66cKKbget6Vd2yb8gBFT8Bu+0DojcM1TOgrIMcUkHz79sVdc6dmujJf6UffLgcJx6BE0L6d1U7ZlooTRj0Zy/2sQsUTcxJTplOrPACTf7ZvHTJxjYj6nBtE5iFBdPWU5yWq2wjiGnGCzxrsusgkRTGChc3KSXMpBEldXDEvti0+42khyyJEIfDUjcxtFBPWbakJ79lkC5cNo+Yh6davHsa1IZ/q2EYEJBsLwivGdsGwa9H4oZZi11WqdJxuoxDuhiinuM6yjTqzvPx72SYc9LlbcfGv/q2Up3oPuEqRhzY+hqBK3zY2XGUQiMk3bytfCqjK/DIxstwGvQfcucKzjZKS7dN6WrgViOE5Cy5e/7FJ+zxqDEjY+epXxykuGgfnvRo0Ji+pjDI/6WztKMluo6ww47aDZ9dsEd5zzbnZxO5rW7WOpr1C+V2ZSTNyYFzT4jKfnTbHh+dFPVmB1kahNpz4y7QBw25it3XLWvdwsPI6esoodWh5oRO6ZjVRNnOwLbd/n99uTqBML49OF0oaeZ7PTpvjH4RHLEyRqoTT8bObmjrfzTYyuEyg/ent67c9g6YN/Obh5bjqrfMBAIbcvlABu9EUCSoTcycpr+G++ZyogEaygBC5W8btrryk7nEbxWT9sMQ5qgrm97qN4rH62BDnKqwdlNfJ/FORuXVs8pznTFRfYtvC+IqcSGDbUlunK6+TLdFx8AjBEudSOxdzIWfCNNjBNd5nvLFv10DZbkxX5jba5vD8WlF5YQtMsVbBH69/HwDgRD8KcplhtwPTnW3b+OE/X8TEvgLecqCzCOUqFdzakulHS+0pukZcLg4xl79ZV3kfsFGu17jc+z5wovI6JUldyDgbuoDVrKbDDEz6d69Fv1J+jymHxVz0E6Q52r5vAXfTK+SjcSeU6lX8qSXvXQfdobymIWUbheXGqCj4dQq1qtA+FeT4k6ip/aW6K/Oc/W9TXiNnjOUj8n8AQKlRxZ9bco+57PdquZ65GU/cSbFexc10HCmukTMC4zuVi3P1suPuU17nDXSPZhEu1VyZZ+77N+U19HmKMS9dBoMDQlv/9/C7lNfRIrVAPPFFuZq0VvgF95MDnYH4GJxpu1/5yd/5yFZnWUUNCteBTHmJCUs3jAjvuduIfNY20r2LifP06i24/A9LAAAn7rc9SvlcKAKsqjRZDcPheqk1ml2dKqMw7ALOBGbmaT9Q9xL7nTAuBzezKga3UVhTsMLy0g13QphvMFkuz4vTj+02mS2El6jZtGGaRigGYW8Qa3zprO3GjVzbKFppifYuOU98T1wstyHcc5WG2hoQ96lY1Xbbtn2ts90zf9P+9tnIyfOMq+Za0HsGtxRD97EfDauJnGnwQ1honhfJkglEL3shi/J7ZH4xL1uD2yiLeYkJawbFgN1aJ8qLH59CiIkzVHG5ZTYO15Vyggmw3CFQjDBwQ6cFklMGnaxh4l4og7HfYqZOCxdPsFHcct6+DV6E6emxK3khNlhvbaNwVolNhJeI9VGYeAhvteEYeV58x41oXeKZanGlSvtck4TFRyVPNa4Y6eX4smMFLUS0cLm/3e5uxPkotz2q1Ukt0YGnllREwsWwh42q5KLrtK2VuoXXf+0feMPX/sGrkIeOA7S8a0Xc5Sf8Gp5EFp8uZJaXmEDTpAE1SV27aHPZhRNmgdxCNnTmCpIHqkpqVQrGA6KVgffOlTabei7H20s/D8JwjZRfUFhegFbsjeR9qsi++yiFEtu8Z6CkalH6VWBo9mXYdT5ncsISe20acZWXSt1CX9GbstuR5aVrRuj2gZyyTPYs4yrqGZakLnIdpxD3AgBD1QbfBCf1M+UlvmyjINmArLzISn+3zzlYJkCzyhzG12LUzTSs5cXjNuqsrY8s3cTjHldsGsWcKf2hiAiFGJ+8CXa+iewa9Dzj4HnF2luMUMpENzLLS0yQlZeO3EZ1aYHMhz+pD1dduewewgxcOUANcAdw2OwfUYj0NoSmbxhGRwF51M3BlRcPqZq/TE+2UcTsH1+BUFteohaC9BsOngUoRJ9W6pbACO07dlTyuGIWT3xAGNefp7YRH6sR6mKFmJ1es3o0K5O/NPGTzS3Fslwwu7YG+MoOMVdZvxqG2+aoDL8drYUxpe6262cGL5twZwectVtcy/vGEZZ52n4dpmtCKZcTrGt+CkcYhFymvAzSMRUe1YFMeYkJo60KsAPFVrxBR6nSohWEZ2+EiJHYUhVPzyo5QW4janmJRpsfzjzriW7vIF16C1HUVG45oI3byHOqin668Cv5QNsZVy2l9paX8Av+ui2im5MpL57YJVWqdMw8L+FiXlq1uCTLCy0wGkluSLN6fLWNgq0fbAOc3O+m/UW1fPjJCrLMlvM5HsMRNbYpjJbqZgaKFA5hZf7u0eV467fv5eO745gXXoqhszVi7RBVXupq2YrveQKUBcqKGBUIn5+Ss+mikgLqRKa8xAR2UpnQ55h42cATeUjUI8g3qj/ExKHFIJkCFcbXKptJgc4sEvc9vx7fv/sFvgh7F4lwbe0kXZoqaq7lRZIrfaduNbn53ctL0vnpJjRvBDF/R6H8DrPB1oksgPK8+Pfp4GhDeN+Jy9G3SGIs1YbVjeR8FK0xWophke0kUDjOsgQqefJ75tKb2Odm/cVW20h+H2B5KQkxcVFjm+haqIZvAGnINn/ghkdx/wsb8KN7X/LIDJJbkegqOmWppsrLaMu9Haaf6Rwt5AwhDjDWopA+13FlcSt0G2UxLzGBKQ7jy3ms3Ow+/LqRx7cPeQsAoObT3VWpKFgnLJ4jNXVJAibToaVWWSNEMynQWQbH277jpFduP7GME/bdntNwM7l7+rB2ygXQwrLsNqwmX2Do9XUzJ7RVtoQE+e4BZ1NkEzYMrHxO6lsvbNsWKsWG5UFZsmIQV9zyJD7yuj2w3w6THBnkWfpRqrON3Wt58ZdHA70BV3mhz9CPtl4eO1FYZ23blmSGo+lnJ/Molhehbw11ppvsIuuW50WmAqDrgqqfmeWFxbsAMfK8SH1uKVhn5fIhQHSOG+E5t6Grj8o7wqgr5HXJr8SGzKnTqUJOLZmsDQ1pbVKpEGx8mYbTv4bhXhNJeYH4jP1Kp/gWZtwKso0y5SUG2LbNqbzHlZwu5cpLroDFrzoPADDbl4ZbdBt1EqQmZuA4A98quDKd+/N+T2l56cJt9OTKQUd5gdjW6wvt2iopL22o7GlgsnO98zs1M7itVRKLJMe8AI5ZuNiBAdLKFSV53s51/NUtmblcaH6Oj//mMTz28mbc+9w6PPP5E5zv5PJcnh+luluYMfzpiVrsADeNmz5DB/5uI9lS2I01wrZFmfPb0ZhLzzCK5aWRd+VO8lW21VamTlyOa4YqeOM1d+OEfbfHZW/c2/ld8lwBr4WAxSNRt5HLp9NZm//w7xW4/ck1+Myb9sb4csEzV09V9LnsagWiM/zSubqPb6kUNe9IpzQDNvmfttWvxIaXU6czRZEqL/wgkG+/Dsvjy0m1dq6N6rqh7e73qRnmq7xsBTwvmdsoBtQtm7smWFqj6nTSzpXSTfE3moHDNo8wJkN1wG4XaaCc0yDYh8+ukQPEeOBlmxO0vNmGVbCqxAxt8qrL5ATc5aLo9x6Q0j07CNh97OXNnuuEMAG/mBfep4xht33By0HJ8qIKMAd8FlyfIL846qH4/YLrhpNiXqIE7HbD89JF3MetS1Zj9WAVP7jnRV958nvmNqKWF97PHZ6K//fnj+C3jyznrhSva1Bhma37W2bjSIlv198ybUSYNYmOBfb9sBQOcimGTi0+1G3kTzugumfRTQbEk1XWqXtb5aaLEjCsA5nlJQbQTKPxZadLuSJhWdhh82oAQHO8mr5enjidpNYOq4JYiczlE7YLDGIVU6XDLY6qDcOGQ0c9e3Bt6x68vyFbJACyCbVpq7zZ8nv0tFX8npxFAIAXIQQ6P914+9Z7DX1uhZwRLU7CanJ5sCYqL+G1jVqbW6ELywu/Vm6f4ru+GThd8ubQcWPMGq+8Tg4sZM8zitsITbdvh0rbKy/x43npZGPZOOzWPavULZQLORhE9vIJ23ncna7biAbsds7zQscc22Cbti32ueVtu2p9iMxx07Sww2ZHJmaMU17iURY7qLVDs+e48gJxfKGpLrEhW5o6dZGpLC+QnnGw5UWMPaw1mpHiquR2r586Q3kdz1SUDpO2DVhNmz/zsYhMeYkBTPkwDaC/lW3EFphivYo7rzsfAHDsZX9Qfr8mLRSdcElQtxE7EeWrFdzdkulPPa4gqQvpNqIKEwOjo2Zybzv/Oc81VckiAYRL6wW8my0v5U76V0XBLbMXA+Ap2jWrGdhW27ZxwY8eQrVh4QfvPBj5nAlT6tsgtwrzY0dJ9yw2Kvh7S96ZX1VTqtclq0SYPpVjXvhv1Kvi2FHGvMiWwmgxL3TcnH7lX5XXeVKlSWmJbkHn5iGX3BRKbjc8L/Q5DFbqTlmLegW3B/QzS5We1Bct5oW6W0dIICnt848d9k/P94Ji4rrdVEtE5ilf/IvyGm9KfPiD3OYRGtDf6iNbbOu7rr3D8z2r6VqE5ZiXMAp5s2ljPSnMyxTqQk1cK1SZiaxdYj9HD5qV59X8i3+jvM5zECHxf3XLRhvS81SRKS8xgFle+go5TzphJ9lGnAa8A78jdRt1YvqXywMA4WNtqMLEqzuH8KfI7hT6f7tUaVl5aSiyuVT3IcfYMBRyBmpW8EawYbiGvz3hnJxeXD+M3aaP95rcQ2zukSwTNn2tvle/bKNKoPIixxCpn6NqzPpl4CRZjdwTsJuPHrArtK2NXNbGbqwf66jlpaaeozIY+7HgNuogC5GBWiOYIhMmM1DOvgHiY/j1kwlEc9PRttYU668fqCW5LGcbhZA7VGkIfaKqGebcixc1ae46r7uL8wmS5fdL3pgu93nXrCb6MHa1lyzmpQu8tH4Yy0gtI668FHMeBSBMqqvr2hBJvzp1G9X9FAnF0FWVBwhrIaAbn6/CpPgemyh50+CuG07z3q4OT9UnRkMS5Mk2kth1Gdzil/5yXbIpd2EMk3opW0KiRPDbPq8pGlK2UV/B7dOmz0bjiXkJYCyWIfvpo/CPyM+rPTOzFCsVU0qn7+LO43tE/o9O3EbrSDwEm3ftYhIGR72p0ixrjZn0w4CmxLPMRG+fe0EPZAxRayuFCaHwcF51YLWkjNHVTjiviAJc7uI5bxqtCe+ZQh1GSZSVByAeiv4wh0kqQw6+jypfBzLlpUOM1Bp41ZV34qgv3cGVjgqh2s9LdV7omPFbb7y1YsIvUkK2UUN92lD9hLI8QMi0ZWrt8Q1OU256YiYBfd2p24hNrHYFISsNbzuBcAvEhmFF3agQ7fSUewhhSfM7iYZRfnlhxtbC01d02+p3Chz0i3kJEeDol4FjhWAFvevptTjx6//APc+uU/5+Oy4buTxAta5uXxiEsWp5SyF0Hr+0ZsgbD9GueCqzkgyUXON4vouNhSqpIx3wQDHqh76iKz8udmE/mYB/wG63lhfv+qCyMrXWJUVQf6dyAbImhrD6qJWXzi2Zdz+zDsd/9S788zlnXoUJyga8wfeGYcTittKBTHnpEEs3jPAJ8eSqIQB0ouc8gV7iJPVzG6lr7zi/EzyAKM8Lc0t0wrCrLMzYRuYWRYFE7+TwP2WUlMpL8Cbk5+aQ5filSpcly0sYwq0N1Nzf8Fn4g9wqUkBrUL/SPi0IQXK24pUIHl/VklcmitpoTd2v4ZVBRfssUSFkY975neAF+1t3PofHVwzist8/rvx7p26jsDEvjyzdiFddeSd+8/DLriwq1+d7vmzCHViZVm4e5a8rvqdy8T0bD+NKVHlw+zms/EFaAoKNhY4sL/FYBLzKYThlsRP3jVBolPdze2VcFdTfSXyRrLz4EmiGsGJS2Z1Y975xxzN4avUQzv/hgwAU1jW/g7OCz8e1FEdXUpNEprx0iJWbK/z1qtaiRBUBb3wD2XwUY8Fq2nyQylWPgU4VCZ/Te8BpQywPEK6C6xaV26iTiUomCmN2bBfz4pfa61nDZeXFJ+alU7dR2E0HUGx4ISxpG4mVh5KZCb+vEGY13TR91ibTNLiyJtfcYmCbGncxhYwhAvxjXoD2cT33Pr8eAHgRu7BMoFVLvamFjXn5yl+fxgvrhrHoF/92ZXVg1WKbS6cst3Wr6WN5ESG/H1YoL3mSJRfW8kPnTSclIJii01+klp/ON1VXRvB7Br8aVmFcrpvIfPUvH+L9nhvf482sCqU0jUjKC1+b2rtEZYsi0J2SeN/zGwDQGmUi/J7YqETOJ8iPgTE7SWTKS4dYuclVXpgiU6m5/mHZVyoskIrfE7gJeKo0OWG1WShGVAG7oU4bYpAwldvuNEtdVb7VnRXfk02UQPjqwB5LgS+XgviBSkkDwllDqOWl2vAz93vhBuGxCP72yugGuvA2XI6FdtYBOS2bgSkl/pYXZ8GdOq4o/E6YuARP+rBJ29fZxhamiCitvMvayFOlQ8YRrSDWDyrd7z4YXEWNuRM621jWDFWFPnXrjwW3m1teyq7y0E2KvzI+LYTlhVl0hU2tgwwcq2nj2TVD/u5Qn+8xS6mbKs3Ss9uPK+V8DeM2Coj/68Zt1InlRZUqXejA2uQHud/9arCpYpviiLnRgSzbqENQEzBTXqj2KnNsNMwcfnTAic5rw6sr0pMjO2XkTAOm4ZyQggZQtWEJmwVTdBpmnsu0zHYU7wqely6sPbZtwyJt3U7B6Ki09oSUOVJVuzkaphnY1opicgLhzMIC8VTrOTVJGx15AW4jKSaE3Xe54O0bygXiXOeULWgYbvvqivFD3QdU6e0r5LARdV/LC9vUpg4U8fLGUa4MNjzt835XVkKjBPnZNoRx01SMG9pGxg8U1t1I5Xh+18iRvlVnVfCTcU60ioaN+1i5SVSa2POgsi1TLDNB5zWNeaEp/mHlU+WOBmULfa6gzGf32V+k1ojwbb/6b0/jmtufxeffvA/OOnQnj8yGD109s7B5SOpCPOeN0gHAgbguNRTPWS4N4MgNn1nlF/PS0Vyi2UYx1LBqSvNK1W5ADHlg4OnpY9xtlCkvHYK6jZa3FiZKtc9cBMysW80VcOnr/geAmoKcDfS8aQixA/kWUVFQkKfMt8I39IIrE1CfbgPLA7QZtFR5oUpHLe/K/Uax6PmeXHmbymx3gh4h1q3RusVPYlVTbKt8wlAtwkC408WaIfdZs/uziiVBngp+cRKOPB+30YiovNSsJop5E7V8kcvbO+/tU7GwmyunXAy2vDB3wpQB0fJSJ/KAcDE9LMivbtmB/alS9Jq2LYybPXPeNqpS7Du1vKgCe2nfFvPqzdQvYDfsxkLXC/p7NbmfSdfQeT1QFJfofIgUfwrabhrESvv8BEUpD1ZcsE/lSglhebnm9mcBAJf97nFHeZGe8y6KsQz4l4EIY9GjfU0t31TuIQWv3GqAFbqTmJepA0WsH665NeY8c8mLoGyjKIzVNsT+9oOyDMRWUlk6cxt1iOUbRz2vRZ4XNsG9biNV2mq14dX6AWKiDRhAm0a8p3VZpuo9XfC7MZUq3UYhTKTDCj962FRp1scTedXucO6qEcXJAghXCmHNIKX89gl2DDhNFSRLGuD/PDdIlhdVv6pksY3EMES3AncbKTbtuuUWuZw6rtS6Z9eCRhE2aywM7woNLmfWKO/z81eWqExKUheGxrytkuPzEx7OHnY4CRkw61eTK8htxGLK+os54ZkCnRcMpO12x1T7Z0zpHxjc+JPwm+qMCWVHhvwHv5iXCDwvL64b9vxOGLnc8kLZhM3wGzgjx9tufGsu+bmYg6y0NGCXV6EP94xpHB0/pCnaGRTb1KewOmVuox7Df1ds5q8fXbYJS1YMCmy1rmm1NXmaTUwZadWsKU3x/J6qeivQGsA1K3RMBkCCWJs2l7mhb4IiA8f9TdGF09rQ23KueP3oTdsGbBtTRgdb9+D9Deb66e/C8sL6eEJfHqsGycRq01Y38LBzt9FqYnlhz8nTtyGzqgo5E9VG03cx9FheGt7xY9te6ny5ojQDa29FobzQOAhmeeELpS23T0STBJiLyouJLdXg50jbyFJSbRvCuLGbA57v0cq7Mj+QbbsutiDIm3gxbwp9OzRuovJ7noDdDtOFRyTLF1Ug/PpZlSbN0KnbSnAb0e8Ife6ljh9RbGphC0PSMccOG/Jzht0feL9egkcbzabNx42MTSM1bCSBs0IMF22rPcl7v4oDZCclPZjlZbvxJTy5aojM3eC5BKjjADutq0QzytjB0AaEdrO10ZC6LzBgN1Neegc3P7aCL/yzJ/Vh+aZRfPbmJVgwdzIAZ6IXJJ6Xcr2K+685CwBwyMdv8vymioYbCEeSJCsvbFEpVEfwcEummjLfLWdA4xXCpiUO+mQb9dWrXO7Nb3/a8z22IPaTRTkszwubZBPKouWlVKvgwYC2qhZhoP0EtW1baXnJjUp9GxCEp1Je/DYdyilD76tcc8fPm664xfM9trgWpEW9HGB5YYvdQDGHsvTMi9WK1D7xfqnyVZKUFyC4UOLqQVcZ5EHJ0rg56Qt/9nxPZVqnsqsNy9ftQ69hGK0515fqVdzXkrvvh3+t/J5fwC6z+BjybiBBVh7Z75Vrrmx5HKnSpBk6dVtVlG4jW+jz//3uXb7fE2JeQhK30XWJ0j5QmW/4/J+U3/WUSqHB7s0mSor4HAB4cf2I8J5SOFC5ZylKbAS5jcIUwWQkddzywuZSTZxLKu0lDrcRDfZnbnP5GfuViVFa2GIIGNaBzG3UAf75nJPmOX/OJHzhLfsCAB58aQPXvMvFnDfolR52FL+pqr0DhNO+PdwnLXOufDDyBrG6fk66+IYN2KVyfbONFI1lmVEDClN0u+rATAmZ0DrJsba2Mwu7k1PcCNq5jQZHG8KptdpBO1WnqXamWLnWkF+qpwzO5itt3kxZU9WhYs9vfLmgWCglU7f0XdpfYtZYy20UsNgv2yAGr9asZjjTumT9kF+322AqdTGwnSt0beYm4A3YpRtcmHgbmg1IvxPkNlKlSTPkO3Rb0XtkafVhXLwqd2tYawQtUjjKifHaP2fAP+YFCFaamAvfdd34uLMV3+WJBGQNZu2uNNq7JTe3WIynjy9LsuW5FDS2vTEnYRm56aHAj1lYdT9W083iU2UbRSlPoAOZ8tIBXlrv+FTPPmwnHL37NEzuL6Bu2Xhk6SYAjs9UNivTx6+s7uzjNgrDqTAineo4SZ10nfxeZSYFwp82tpCNlm16YTgNhhULYthUaZaO7ol5abM4des2WjkobrQNH3mqFESVH7vd8/QjjaNjRm3lcT7MS9kbTMmTf9f5rN66Ju9Jy2y3sQnxJ6R9Yao8L90gno6rjWaozUWVTmqaBlF8g8eOnA3CuTCEvg23mdI5o3LJyRitifcWhlrAdRt5rQydViiXDwV1qxmK1kAVCxGW54UWKeSsviGeM0AIEKXSE0DwZs6yQHec0i/co/ew4ZXMWLhpzAt7zrRoox+YJXNai3agkwOdW9WZHiI7s669TOIwgw498meqmk5Ufje12HQiU146ACMSmzKuCMMwsPcsx0/+n+WOX7OPWF5ctluyQCp+U6X1A+FoyCuSP73hG7AruY18FKawDLsq7ggPHbUqCJBnGxG3UUhrj+s2ygtyZeVBfs9Ovt6A3eC2ylkivouh4rsqMr52fesJ7Gyw9gVL49YsaaNj7jV54wbcTCNqefELgJY/oYoZtdq5lhf/DX2ZrLzUm778ExSu9UN00YR1OXpIxBSbi+oumk3bZS8mAaRscfdLQ6cYrasDdoPmi+s28mYBdZoJUpGUyZrl7fOggN1+RXmAdsHCa4nlZbjmVZ79ZALeYPAcqYMWtC6taylMsyf1AXDdemE4bWjMIgM97FRqwe1lc5DFj3Vi9eFuMoVVMax1jc6ruuXEBqmSQ/ziAQFRcdtaYl4y5aUDsOyeyf3OIN1hcp/w93LeJAycKsuL9zf9GGDDbOqeYMCQ1gg/y4vr6wyeNGq3UfsFkZnD+0te/2o7plSuvLTLNpI+GPa1vAQviGsGpRRXnywR1YqkUl7aBTtu8bO8tGFo5qd0yS3GLFRq5YW5jfIe92S7jU3lowfCpS4v2+iNSwijDEaRCQDryWZKf0+QG+D+k2W3IwCkkC0Y/pYXldtIZXnpNGDXG3PjbatKKWZWUnIiD1lzbTVR/P0tL8GWrpLC5Rq8FooKBKDe/FXPuaKq80aU1JG6WgFjYK5Zti90wu4bxLAbJt4GAF4gWVZUvgy5z9maWsqbQiB0N1llaSBTXjoAi2af3CpTP2uSqLwMlILN8KpTpl/AbinEqVK2RjQUG558D4C6lgfQgduIWAn83CmqYc8DdonSFKZGTbPp8tIwi4Jvaq/0XWbSZd9jaFc/xI/RV0ZwtlF4P7LX8uK1oqm+yRZOOT5iYp/zflChvLDUzkl9hbb35TU1t1Mkgiwvoiuubqk2Ui/8lJewlheaNQYANcsb86ICVYoE9uKWIiwfHlQYkdydrH88a4HC8qLONurMpC9bXlTKenCqdOeFIVcOVoTr1KzJ6u8GV1n2f2BsHkwgVbhV4yus5cV5315JrZEMwsktxYmPmxCudDVBXmfWNZpYwOSrY17UsmWrdD6EsjgWoEV5ufbaazF37lyUy2UceuihuP/++wOv/+Uvf4l58+ahXC5j3333xZ/+pI5M14lK3eITelJLw95+Ylm4ZqCUJyR1zkihi1SQi0G2gjAzvLz4yPcEOOZ/wD1ptHMbqWp5AO4G5FeJGHBOXEKqdJO1M1gm4J6OaLZRGCWN3s+E1qbsWx5A+oApIXRRA6j/3i+AViTp6qSGk2oBzrehVmeuHLaAqixLqj4d9omPmNhSsOWaUIBrjZnUX2zrNvK1vORk5SV4vFpNWwgsZDLDBHLKdY1cmeGCvV9Y53VXAe3jIejYoO3t43MzjNuIrRlMeWmv7DMrnDpgV7TstoPK8iK7FORf8gvkpP0ftLFRZmrbdtalMJZZ5379Xa7BBzmnzyaReV5reMeXSrAf11Z/CCWVcl6xQ20nMS+qVGVm7Qpj2QO867VqXqnA4rE6zcQcK0g8VfrGG2/EokWLcN111+HQQw/F1VdfjeOPPx5PPfUUpk+f7rn+n//8J97+9rdj8eLFOOmkk/Czn/0Mp5xyCh5++GHss88+Sd+uL5jfPGca3NIxW2F5kVko62YOv9rnNQCCqan9LC9BCzNTBib0FbB806hAmc9kytTj9DfLksy+AG4QBtmHTd0bFmkrFDTvKhdOmNMzncTjpVTpBpGpouBmloeJkvLSLpuLKWhTBoqtvnV+2MoF9y3gnuyF7JiA9EPbdhXCqQMl8VkarryGok/9TulBMS8stXNCX8FjKaTyVOUPWNtK0imVvVcx2QKO66bRtGEazrPYOFJ3rD02hHHTUKTCtlOY2rmN/rZktfCeKUN1w/CMHZr57Bffw6wRoWJeJMsL+816a47mc4Zn3LJ5orK8dELRD3jdscxVZ5k5/Gbf49C0bVhS2Qnarn4pM5CVLanULI81k4EWogTcNlvSXFVBSdoWYjNlCsb4ch6G4SgKtZblpd34UtV5A1i8TzXwObP1sJQ3+frJ4m0ahiM3Zxq+a8Vo3atAdKIcA+pn3LS9/e2xvLQJHwjLXp0WElderrrqKlxwwQVYuHAhAOC6667DH//4R1x//fX4+Mc/7rn+a1/7Gl7/+tfj4osvBgB89rOfxa233opvfOMbuO6665K+XV+wBX9SX4EvZNvLyksxxxc/trjUcwV85MQPARBNzwxVhYsBcAdUkOWFDfzx3G3UkpkvcpmAylyotvawyRskc0RKvaVBwrW829YvFUre79a88RnFEEraKDHrlqTNtpLLC22lsJo2hlqb+4SynCodbIpmp9/JA45iyE6aVqEU2LdAsOVFJW+kZvHf4fJav1El42cXBXW+X1qtKuZlS7WBW/67Ci+2LBGT+goeJa4mjx1JXtVXkQhe8FgA9PTxZZgGsBF1NJrORkrHzY6KNvrNkbBuo+fXORWsp40rYt2WmkDRH9RWP3dVX2uehHEbyZYXLrv1XMeX86hVGsqYl1jcRtK8Yi6FWr6AS05ehGqjiWMlynw2Tw1DPFQZhoH+Yh5bqo3Atq+V48UaTRTypvCcZ+XUio+KOsItzth+Xeov5lFgpVUs27Mu7asoS6By3dD3QRYQ5q4aKOV53S1mbaoXHLn9xRxqNUu5WFQUGZhBHE0qeCwvDSdQmT1jN/5SinlRFN8E3LVkuBoc65M2ElVearUaHnroIVxyySX8M9M0cdxxx+Hee+9Vfufee+/FokWLhM+OP/543HTTTcrrq9UqqlVX0x8cHIx+4wrsNGUAN73vCOFkKbuN+ot59wQbMuCSZ/7IJ1nmwgkYwKz+iEzc1s4c7ufjdU3//jLl2Az/SrX+QYD0NBfKbUTKL8i8JEGpy5Q7ZXy5M7cRaycPwgsRaMmgCsIOOj0yF1XONDC+xGJ6FG4j1X3W1BudSnn5+m3P4Dt3Pc/fT+oveOKcwqZKe104wVYQ5r6a1F/gi3JdlfkSEEPUjduoYbmlEKaNKwnKi9rl6K3c7FFeQlgoGeSyFjJfEMukoZ6coIDdsERxDN5Tuc37PEdZjgkqxJ0gk/CVC7lA5cW2bSHbyJHZFOJlgPap0krLS8AawYJq+0s5lJjy0lAFhAfEnUjKcRi3EU1rF9xqJO7ENNSlMAB1VWc2vsK6jeRnXLOa/BDtPD/1WunKFsc3OwyraBbGEhKNeVm3bh0sy8KMGSL99IwZM7Bq1Srld1atWtXR9YsXL8bEiRP5vzlz5sRz8xL6ijnMnzMJh+4ylX9WLuSE6PaJ/V7SL7tpo69WQV+tovbnN9QTp1wI3gzo39z0YSazyWXC9k5XVXVnKjPQTFp1N1qAxNkAgE3aqoj0p6cjBlqjxg+UJZcqAQ5Dqy22lYhd32L6HFfK+258fhvQkKS8cCWt6S+PISjoUGXu31Kte+6TPcsmeZaqkgt+p3QW4zM4WucxDj+45wXhmokkYNeNxZDHjuQ26lKRoCdUGiRs22g7bvyC2sOYtylJnzeVNXiecA4OaePtK7TcRh1kG02SlGC0xlF/nY0jYnlhsWHFAMtLaJ4XtdsIto2BelW5LjFFQI6FcO4peI3YNFLnY5etETSANeg5A+rxFaY4I19bCjnBFcrWiIG6v9yKzwEyjPtmmGT7ycpL0/OMvd9XxrxEtLy47NU2xrWeMWzbc1DwC9hlBz1VvNxYwlafbXTJJZdg8+bN/N+yZcu0ymdBWgCw3biSx6xbrlfxxFdPwxNfPQ2lWsXzfb+JE8bywjRutnHx8gCVCpfZV696Jo0bJKw+UQalLbOFlbXbanEK2LZD/83kmpVRz3fdgF0Fw26Qe4yYVhlNO8skoDL76lVhA2JR+NPHe11YLMDVbwPa4lN1OVcZ8ZXH0Gm65xBNXZbcYuVa8Phxs42kgN2W8tK03WfGGEAZpo0reZTHUk0cO3IDfd1GheDnyJ99MUdcaM5G2tdmjkRJlR5qKYalvMmVAdZWz9jxa6uP5aUTtxGPeWHPte708z8/9ybPOPLLIAOo5SWk26jOuJXcVG3bdqjjH7jiFDzx1dNQrIpzdVThymBolybOLH3jSnlXpuo5173rA6BWVDuJeXHcRq7SxOQ+ftVprbZ6xxcj+5SVxTDPeYRYPiknTc1qolgdxRNfPQ33Lz4FffWqMttU1ddBdclUkK+ja+PDX3qz71rF3UbSIZaNu23a8jJt2jTkcjmsXi0GzK1evRozZ85UfmfmzJkdXV8qlTBhwgThn06cdehOAIB5M8ejmDc9AXXtGFL9TpVhLC9M4+bKi49v01PbyM/HSzYyPx4HZUpi05sO6eULsfkiQGNeOLlZwMJE629QE7LqDul9rGmlyG6nUF7YQkUDkJtNG3c/sw6jNcvjNvKr2K16qCp3Q1Cg5RDJLinKliUqStFiv4DdcsE1Y7MNRa5QvNPUfk/cSLvU0m7dRtRlyL7bUIwbFfzTs5my3d6sP66UJyzA4bhHqgqTPvstINziPsItL1ImitefwREY8xKSi8mRYfO+G192lad2Xa5i12Xoa2N5GSZKajFPFSb53tSy1VbL8Dwv/SXROutJNlJ8d5TcM4XrNvJ/zluq4hoclBkVtP7Tg2QnMS/0GTNlUcWfpJLP3WUeywsb32rLS6Vu4aX1w6lbZhJVXorFIg466CDcdttt/LNms4nbbrsNhx9+uPI7hx9+uHA9ANx6662+16eNd75yLr506n74xpkHAIBwqgTaUkn4LhRu8Gx7yws7dbuF18TrvFHmXsuAI9O9Bz/zP5vINCWxYdltZdasJncx9RW9lhdu6iRyPvarx/DDe17wjXlR8keQ18s3Oac7mY8HcC0v9FR1/T0v4B3f/xc+98clPGB3yoC86cgKhReudcLbTtXpkW2w48vuqTHsgh9UB0eOe5Ezjyb2FdqmoaqeI9B5dhwN1va4jQR5/jEvspuTWfCGg2ISmGJIrFph60a55SzEvmWKiCqTi4KmHMs8L0GxGGw8yJsp4BbgDBOwSzd7tiGp0oflLlfFpjGwdcpvQ+cHlJJLgFhrhFMiGq0sGSB8pp7qnqmbKUwqvqqOE9CZ24itwdSVGYZjRrX+d0KCSJXRCX1tFFRPzIs30wlwYygHR9XP+MlVQzjmy3fiDVf/o+39JYnEs40WLVqEc889FwsWLMAhhxyCq6++GsPDwzz76JxzzsHs2bOxePFiAMAHPvABHHPMMfjKV76CE088ETfccAMefPBBfOc730n6VruCaRp468FunI2HN0OxONMgOJeGW+ZcCRPzIpqXfS0vfhq3T3Q94Ewclc+dLazMhw/4a/oUdCKqUqWd37G5W+jGB5bhxgcdF+ClJ+3F74/2r8o4RNvKSNHmtOqdUHDLS6s9tm3jc398AgDw038t5X06WXIbhVEoghh2lcqLslCiItgwQHmRGXYBJxZq7VAVm1txL/SktOeM8TAMw5O91S6A1k+RaOfCYRY752Ts3xdh3XBAuKwIannxKGptnqWqkCjgKiIsA9EP9OQ8qU+MeQliMmabaXBV6faWF5o1OJ6U1fAcNHyYV+X1ASAxLz4b6zBRvJiioObz8X5XqFiuqPDsp7zUGu7BqL8gul5DGPZ865+1cxtV6paH4Vq0ZAYrTrZtRw7YlZ/xys2teBvlwU79nGXlhTHHv7R+2LNfAcDGVizh5AF1xpguJK68nHHGGVi7di0uvfRSrFq1CvPnz8ctt9zCg3KXLl0KkxSVe+UrX4mf/exn+OQnP4lPfOIT2H333XHTTTelyvHSCdjC3LTVFNoylwSbGH5py0EmcW4ulGJe2i1OVZ9U6Vyr2F3NanLrjIxhRepxXWUFkd6zU2wxbwrF1uiGVG1YfPLf8dRa/vlTq4YAOJNMcKsotjp6H6zmx5zJXssL2xhY/6+VuCk4z4scsBsgj2FUsekFpWYzpUII2G2oLUsygthYJ5Kg3aFqgz+SV8+bjrMPc9ydbd1GsuXFz4XD3H8+MS+0Vo4YdB0sD/B3rbI2yxlwFILbSCoC2o7Iy29Tm0T6Ncz3DUO0fAD+/dxs2tz1onqm3J0cwqXA+s0w3N8KY9GjMVgyJnDFTd126hrm6fcN1UHD38IGqCuI+9HVUysQdS2HPQC4zN9ie4Oyjf742Epc9POH+e+NK0tuoxCKU40oktR100nALn3GzELIUsRl+B1iZYvT3GkDKOQMDNcsvLxx1HP4Y2vl1AGvO14nEldeAOCiiy7CRRddpPzbnXfe6fns9NNPx+mnn57wXSWDfI5aEtqfLN0FUnwU4SwvzG0kZRu1dRupNwPAOfHUrCYf2E+uGoQBA3vOHA9AzhoxULfsVuxCcDtHfEzhdJFii9dza7fgrqdd5eW5tVv4dwtSwK4M+hGrpbOj0vLi3Afb3J5Zs8X7Y6CWF5++VXzHtTJ4i9qpskT4BluWNnbpOjXDrv8p3VVeGnyjLeVNXP/Og/k1XldKsFtMlcoKuPFS/tlG7vMXrWft43r8FKZQlhehjlPrHkNa0fzcRtzyMhJOeekr5FzFybfujIOhiqtkysSK7LeAcMHCtACr4J5tYwVh7jCZlRpwg99lZZ+B1i8bqbv97bU6eL/LnrNpiOtoQXpuMlhfFHJG63Dk73qVR3SzaQsxdRSu+0R8zg2ric/c/Ljw22wsUuqHdooTLfhIrR+dxLzwg2g+x4s7+h7spPduwK44rwo5E7tNH48nVg7iyVVDHuVlVYvHZ+YEMQFAN7b6bKOxhkKb+h/yJPZzG6liXh56aQN+9q+lPPWVnb7cgF0mL3gD8qtkDYj+1tWDFZxy7T048ev/4NYPGmNRICeisH502b1hmoYnIO++59cL1zzfKjwmBOxa3tQ/Kte2baxqEaOpY17EjU+1GJuG6EcG2rvknLYGWV783UbU8qKs/usV5VseABBjXvw2JBofwLLGxPbJVjs2dsSlw3XDqRdcWlG8QFwfYU7GfsVLWf/6yQREy5THyiTL9pB4+biN+oOtD/z7ZG5zxamhDlJmn21oFX8dr0jvB9oHzFJQ2vsgV4rc7s0+rNSAG/wuz5dVmyt4atWQMM8ph5DXGqy6X7WSyoOUpYPcyxtH8Lqv/h0f/dVjANwxWAjYxOW2+7EJA25sk/ycH122CaulekJMeaFjrF3APZOdNw3BGu3yCHlLOcjgVsmC2f5g55MqLQfsAsAeM8YBcA+ODDc9shxX3fo0AGDGhG3A8rItIU9cYLVGE03TxB/3PAIA0DRNzyRmG52nthEjjGMBfraN8374IDaP1pFvxdnIbiNmHWgYokzPBsRSpRWLo5vlZOHmx1Zyn+qf/7sSe84cL5i0eXByy/IitFWiHB/2iegHnA20bln8FPHo0k3C3ze0fKw05gVwlCYmM28aTltbC8SWaoO3c+o4L6smDbq0mjbWbfEqLxNIQCvL/mmaObFvPd8iZRCINYSnuCoWI9Y340p5vhixUyPtUwti39m2LXxXdf+sjTQomEKuV2MZTvuMVvtk+PnJ2e/6ZSCw++wrerl6hDYqSmj4Wl5aJ+OwbiNZeWkYhjRP5HtWn8iDKnZT0LktB3KyNg+U8sI4YmN9kk88QScuhQq1vORF5alpmrhj36MxUrM85QG6UV7O/v6/8MyaLXjLAbMByIGzjhIhjmXv2PKz6vnFSN382Eo8vXoLnl7tWmYBeBS1pmnir3sdhbrVREMa09SCJY9pFte3cUSMbaJWYYYBWXmxLDRaa0V/MaccX36xRXSNrDaaypR1hgqxvIgKstPu2/c5GqN1S7lW+c1lwLWq0KKPjyzdiA/e+Ch/v9csvZm9MjLlJWaIlhcb1XwR7zvFZRj2o2j2s7ywDX31YJUvKg+8uAFvOXA2D1LjwXisnpJHpgg/Wmgqt1Jv4q+Pu8SAruXFvV9KvGYDQlsvK4la+UhV3U7AsQAN1yyubPxn+WYAwAE7TsIjRJGhMS+Ao2AxmeNKeVRJXMf6LTUuTxV4PHWgxOu0rB+uYt0Wb/AlzcaxWzFMjWJJ7FtpRapbTb45CpYXdipSuAFpqjSztrCFmvbpjIK4mYzWLa4MB8W8bB6tu3EMpWDlhcnLm0aroJ4IvwWXKUp+6cNuFoq8qYltnKagb6/6bGoswyOM24hmG7FxVsmFmyeytZBtaptH6sqARv59Ynkp0bRhuG3eZbsBVNcO83HEgiGn9Hv7gf0Wvbcg0LIKcixGNV/EZe/4NJZuGMEhUikPv3pggMNlBUBg0d00UuNu17uecTZ22dLFZLL+nlTw/rarpKpdy7LyIisVbJMXLcKO3I+d8UlsHKljN6mt1LVnSlQCjCZBdg/++b/OujhloMiVzfFyzEujydfhHaf0o7phxDO+hn1c6eV8jq9NQ5V6G+XFTbWWLU7VfBGfPPNSrGhZoH1jXhT7AFdSyXO+hewHr9pzOxy7p7c2oU5kbqOYYRiGJ12awuNOaZNtxCwv1Hz33Notgu+cbVxsg21X4dnPVQXQmkoWVmx2iaQC3UYqF4dvO72bLLsPdjpfvtGRe9COkz3XUeWQxgOxdYfdB7OkTBunNm3mTIMT0K0bqmF96/p5rdgewPF5M6XDaaftT1DB2ilkVZGYF1ZtXGV5qXo32DB9yqwKhqF+ljzmpVLnLL5ymQRvzJEjhFGae9Ira+pgbxbA7RfESknEaMZMu5gEgJbQEGV2ErA7Xso2CnLduPfsWosoKOFcYO0xsjGKWXXud3KMOr4lmrmNJg+olZfO4iHcjY0qEmwIct4fn5iXsJYXqvivI4eGkiAzfMyL7B6UWcu5rCFReWExKqKiJo5nPzZh1fxhRJxUSXph3TCeWbMFhZyBcw7fiX8uZxsxgjxHtrrNfjQHpmlwxWnDSHBGG1VQqXuNyTIMA+5UVu8DKuXIfc6O4rN6sIJv//15AMDVZ8zHDxYeojz86kSmvCSAfAhSJQY/NkuZsZQqLy9vHBWyOsaRTVId6BlOJiAujhuH3Y1o6YYRNKymEENA03+7DdgFSOZP1cJozeLU/PO2F82SfUWHxZJNRtq/cp0WV3lRbwLO35wJunqowq9fMNdVmCb05QU3VZjsBbbhseBBhsCYF0U6r2pj957cXMuA6vQ/QWF5kRdKwzCkTZ19zmRKfvIG25DFpYPJ2lJrKP30fgG73nRSz1d93QlhlJchMl6Z8qMO5FT0r49VdICwBAelS9PNgW7INI5NrnvTzvLSSRqtsLEpAnb9nnEY5WXzaJ27ODcr+mBAit8Kw+fjG/PiM3cYCSUDG4MFRXyP4VNfyI/jBXBjm5hrGQD+/tQaAMChO0/FvJnu+uRxGzUUipMkPSirjCmvzLLjB2p5EeLXSP/ylcEnDlGlhLC1kSmjLK4IAI7YbVrgPelCprwkAHbKrjWc2ikvfvEkvPjFk1p1RNzrrKbLjiib7qjlZdmGEVz6u8f53zYM14RgLxo82WjaKFZGfGUCYq0gGWwgD1UawqbQaNpYubkimP+524iRz5G25kaGhd9VxYEw0MwfdqIr5U3MnSpGuTvl7t3gtmrd7d9HLjveqeHRApt0U30sL4DL//LyhhFeB+kwUruq2XRJB4FWgblRsW/lE+Wwon4TQBRahdtoC8kYEjcZsU9LEo17ULAu4J5EN4/W8dfHHdZqVforXXBLtVG8+MWT8NTnT1COHVUVXPq7tq12HYn07dS6JLWx5qWN9wsS7iTbaFwpz7MxWDB00NwE/N1GhmFw19F6hbtRbrPs7qyQcfuXRccIsnnMSzu3UQcBu6W8WI3dbvX57R95FV784kkoSqU8gpQX6kplc0yVdSW7yuT+LgeVgZBjXnxcrnLcDbP+idlGjtwHP/VaR65PKQTVoYpx89i2yzb7Uot+Ye/ZEzgfCuAW6aVp2mwu3X7xq5Tjy2Xn9cqeElp5ca2SgsUJzjO+55LX4PkrWuNb+i6zkk4oe5+z6zJz5P+9Feczc0JZyVieBjLlJQEEbVRU+xYj3aW6GiTr53N/XCL8rdG0+cT1BrG2t4JUAlw4LCZiaWuSmgawy7QBAMBL60cEUjTqHmsXFe+XuQG4J4+RWoOfpqZPKHkUjwkKLgUZcsxLkOWFKUcvrh/hiwTNTBrXUpaCuGW8JzkfPzY79SstL84iIhQtVLiNZGlBHC+Au/k8snQT7n52HW+TjOATsvjeL+allM/xIGjqbmQQYl4IxX0Ynpd2lpegbKNhEqiscp2IwuV7VruNAGB2a+N6eaO6Rg8gzjPTdN3JqnRyNq5cVmh1Gmq5EN7yUiF8TsFZMCKClBfDMPjmtaaVMqtSXsaXCwJxYZuh7Nyb5XJBUfjFvMhB9uMlt5HSCi29Zxu47E5l98EU5I2tNq5oPZ/Zk/qw2/RxmDmhjFkTy3w8yHE+QQhix54SQjkGRAWVKXm+lkXpM3bImNCnsvy4dACUR+fPHzgq8H50IlNeEkCQi4AumnQBkosksgE1ONrAXx4Xaz0BwMrWBlHKm4Irpd5UpQfKvnx/ywsbtM+1AvAm9xexU2uTf3njiLBh0rTldu4Uv8wNwD3ZDhPLy3bjSh4Nf1yptTgFFK1kd7JhuD2REuN/WbphRDDXX/bGvbDHjHH41IkOsy/PdlDS2Uvt9AlMZs9Xtemw79DyACpXnLzhBi1+gHrzUTHxBpYkkK71Y2cGgJ2mOkruC+uGPX/jSl1BKoHQRhkEXNepH89LjQRJy3BdcgVxY1HyYKjniepkvANXXkaUcun3WV8FsRCzfmfK0A4KYkWgQ54XsrHJp3JRtvsJZWJWjR8AmNaal5+5eQls2/YEzgKislitW6H4kfyyyoqKmJeG1eTWUgbGQSOWEJHkSh8wpYQW2KVgFpA1gxX8+N4X+Vq8/cQ+lAs53P6RY/C3Dx/DZQZxrciyg2pYsTRkxqniB6qgyll8MuT7Yc85yPLSaNrY69K/AHDGg18sVhrIlJcEUAi0DBDLC1Ei5JgFuQotAHzhzftya8HyTc6gZgsiDwi1bMhlT+iQFSipFYrElNZm/2wrxmbyQBHbt6wRKwS3kbsJNZQbrbQRBNDY8xN0zcKaIVYJuoyBYk5QsJhrIqjiNo95GWZuI//Jtv1Ep11L149w5WryQBELj9gZf/3QMdix1dcFYplox1484uPHDkpxZa4NGiegLCrnE7Cr6lNAfaI667AdPZ/JabSiTDnIT+3mBIBXtIKd//3yJuHzZtMWFIE8D14OeyJXlyQYV8pzpd0vRXuIZhvxVFLvZgr4cxP1Fbz9OGcyU+hFy8tvH3kZH/3VvzFUqXtcEsFKN4Tf22Gyl1jR+a2872/I4DEvBTlVWi0bEEnyVCR1gBuA+sjSTXhk2SZlyvj4cl60vLTZyOn9et1G3sPg+uGapx1zpzl9JqRKSzLk9yxmyc9Nt3PL6nzGd+7Dp4jrnh3o+ot5wYIdZHnxnb8K5YWtuYyryg8qBdWvXAtdu6oNiys+KuWlXMh55rhfsd60kCkvCSCo/gj9JCjSfaCYB83cm9xfwJmH7sgDqVhGDgtCzHNFIpgwjmZHqOROaZ1Anl873HpfxKyWP3fFplESZJbjLJjKAmjS7/KYB8UpdoCkvDLLy/QJJcFEDbguD5oRJaNp27CaNv742EoAwSyQM1vtemq1k0mVMw2h7AFDJ6RXfkGefkXeqg2Lb85CwK6K+E+6r2Gpoq2MKdIp6dozD+QKG0VRirMJkulHKQ4AC+ZOAQA8+OJG8T6J2VlQ0DoszCifyJ3nFcx2O6QovVD1rf0iIijInFlGWAkKdu+X/OY/+MWDL+Pzf3wCv2jV5uqTlBe15cVGpW5xV0g7y0s4nhfGoCoG7AZl/rCT/sS+gm82ycGt5wwAz67ZonYblQoCS3gYkroaUbYo6L0zsHWCPpsD5kwWrq8rlXFRJrv3ST6K2oKdJns+22W7Aa7UyAhUXqRrgyyn25M1Nwgqy4u/28j9kMalqVzJgHf9uPBVuwbei25kyksCYL7tdmXRg6K9TdMQTj7Mp8osCcxczU43lDAuKFWaLnrKKHPJVTOpv8A3vOfXbuH3LzKlqmSK7936IV6ZlJ2Vx7y07oOaKdlGxdqsWsBtAL97dDl/P3/HSZ5rGNgCwTC5v6jM2hF87m0OH34WprJPoOVP7lsKwMn8oAG7VVXhSV+3kXqT6S/mMZvE8MzbfrzyOsarUQth7XEpxb0y58+ZCAB4YuWgMOaYkpU3nUKQgmssjNsooJwFZ0GVXBdPrBzEZb/7LwZbi/TUgWJgbI/TVsmKVnetRTJ4sDexvCzfNMo3kxseWIaVrVPzeCkTxc9qsrqlOJQLpq/Lplx0x3672lduirkZ2hrB7kGeGxQXHrsrP1it3FRRMg1PHVeUYl6ClQjAP7apqCCpY8rLztMG8IeLjsTPLjgUc1sKRTEg21Meb5vapKa/+5hdhPcLdpqMP73/KCHOULxXd/62a/OWAO4rtuaubGN5EbKN+PhW10WjH1Hep5zpXfMAd24BwCdOmId3H7WL8rq0kCkvCSCwCqpiAPmZZ+kCtsMkZ7Gc0bIkLNvoxrwAUoG9AI2fuTVYrIyM3aeLG9yk/gK2bwUPPtuKg2G8Im62UdMzM/3SAlXZRuMUlhdmYSoSXpeprQXGDVpUK4f/XT4IwDFdqywNDFMGikIA8RQfVlMxRkOWJ7dTnVWlKnM/XG3gszcv4fedMw2JqyHY1N4uYBcAFh4xF4CT4jp3aojTouev4ic8VbroXTrmTOmHaTiKKiW3ogHJNFtMqUSoNjUf/g/APTHLp/9P/PY/+L97XwLguDkm9hUCeUdUot00Wm//csvLxhH+XJ5YOeS9eVB3p3+wrW1DcJn6Ed8xRd+2g+ueARJJXVAgKfmAxa9M9nGjAI6L5f2v2R0A8NW/PY0//HsFAGC36eP4NTMnlImlyWrrbmX3BoRLlWaHnO3Gl7DvDhPxyl2nKa9v57phMS9+ymIpn8P/nXcIf/+qedMD+U2C5pJnTQxheVm1uRKYDKFKh1cdJmW4gcr+a0eDeA7OPHQnod7UWEDGsJsAhEFkmrh9lwUAINDXA67W72eypL5IZnlhysvS9Y5bhy2I1JVimYYoU3Ab+Zv9AWDX7QZQzJt8IZlQLmBWSwFgp1jGK+JmGzmtEtsq/r5fbSOAWF5qDR6Ex5SXnaYO4IGWG4IxYLJNaKTWcGjOd12AciHXorN3AwgvetVuyjYyGIaB4/aagd896iy+c3ziDOhm24Dp27cAtbz4uY3cBXgZCfZkCpLst6Z9KlObtwvYBYB3HbULjtx9GiaUC74nrBIxNzcMZ+wU86anfbZt8/gcVaZaKZ/D9hP7sHzTKJauH8H08c5YZUGO7D7lzSWojYA//wcATGQpneT0X6lbAjNz03bGjpxtJM9NqtA0fJiSGZhFa6RmYcNwDVPHlbBKkWXl3KOYBVNpuOvC5P4iXxd4sHpAKiqNQxitWYEbaYWkmJcEq5ND1f/Q3oc7HCakz1ng+mQfRZ5hluJQ8O6jd8Hnbl6CE/bdHmbLygaw52eLz9nwPst2ygsN2OXuZUVf8Ri1luu1aZq4b96hTikEqcTGphDK2it3nYrZk5xxfWQbjhM6xizkcPsuCzChr6BeKwJ4XmZMKMMwnOe1frjmOyZEhl0xEL5pmvjXKw5DhZUHIPJ5sK7P3gMAr99nJp5aPYTZk/oC15i0MPbuqAfABlG17tCtn3f6p/nf6ABigW6TfCLdBctLS3lhk1XO3imTzbGaL4kyicIU5L4BnGquc6f283ohE/oKmDOlH+NKeYFMzWkn1fRtoa0XF6XyAAG1jShfB7e8tNr5toPn4FcPvYzX7jWDX08VtWq+iHefcTlmTepDdf0IbNvlRggTGX/+kTtz5WXv2ROV19CsqnpB7lsRfkzCqoJ6lATwB+90TnfFPHXFiX06Pif+5nAtOOaFgZJpqUDrsTB5MyeUUR0UuSFG6xbn9PE7qc6d1o/lm0bx4voRLJg7BRuGa/jyX54C4KYBF6T4LNrGgZx3fPhtagC1vLhuI1ZeguGVuzrcPXQDh43AuTlCnpMfmeP08SWsGari5Y2jmDquxC0nMtiBg7uNam4/H7nbNFSfXYdmE0KmnR9yLSWs1mhiuNYIHOPK8gCEqv+Ki67EAy9uxL55Vx6zRPgFsDJsL6Vy9xdzOO4VM3DqgTtwJZnF41XrjrJI+1v1LH0ZdhWFGYMUvaKkHFfzRXzygi/i2TVbMLsgtovHvPiswYAz/29492FYM1TB/nMm+V5H21VrNFEtFHDe6Z/GgTtOQnXpJs9aEWQ5LeZNTBtXwtqhKlZtrvgqL65LVSy+ycb3py64Ass3jqJas4R9YHC0ZfVXBOsyLDxiLqymjVNa9arGGjLlJQEEUXjT0127iUM3CHbSW0CC5QDX7EcDQoN8rTxmIaBextypA67yUnZ8oifsOxO/ePBlAG6Al1DbqE3g5YhPICvgBvH+Z/lmrNtSg2m4ytqCuVPwt0XH8LRmgKQdt/rXgMFZJG24pm8/llKK/XaYhAuP3RW3LlmNsw71ZuIA4uLZNmDXhzhO5TZizKQH7TQZR+7unOiE4MQ2AX9h3EZhoAqgVVGaswUvZxrK5wgAO04ZwD1Yzy2DzNUIACfvPwsAAt1GchurDVdhUrWTWeg+98cnMKFcwFsPnsNTtXeY3IezD9sJb2zJLeZE0jQGVseJZlOw55QzDU8MBsOcKf1YM1TFso0j2H/OJF7Eblwpj7rVxOzJfdhxSj8W7OTMWa68EJ4XZk20ASFYPQgDxRxqjWbbdGluecmbYjBnq5cNBfMrO1D5pQ4zHLDjZMyd2o+mDdzw7sNQyJmeAE/R2iP9gMKtMewTA6iKeVkToOgJDLutz9zxLAreGEJ5AZxnPWeK2jIr3qu3zW6pDdltxMgp1XNp1sQy1g5VsWLzKPbdQX2wqvKAXTHbiA1lA4b7nIWQBWZ58V87JvUX8ZHj9/T9e9rIlJcEwCYfzbJgoMOXLRR+prsdprimWeY22nnaAPaYMY4rF4xcyS2oqPIvu/CrpURBFQV2b+cfuQtXXpgZXSgPIP2G153iT4zHNiXG2HnsntOFmkTUlw54Y14Mw10gmk27I8sLAHz09fPw0dfP8/17MbAMghSHUlErFFShZcX8VBwTAkeFdB+emJdKe791GAhBhgEbG+X/8IvJYKn8z7UUCJqNc8kJTh8Xct7NhcET1EiyIlQuxz1numPjC39+Am89eA4Poj1q9+3wnmPcDAm/bKOcQnmh5Qz82rrD5D489NJGXPSzRzC5v8jjfD554itw+oI5HjednOJvGC51u23boSwvgDO2No7UA5mFWTsBiaTOcmufyXWVALcQ35QAfiTAUdD+8qGjUTBNT0FDBsrz4slwUmgvfvwyqpgXV9HzBhYXFbxFchkGwOlzdoAIcht1gpIi5kUlG4BA+KnCrEl9+PfLm4Wg8IbVxAU/ehAPvbQRP3/3YVwRFrKNSPanMMbIbw/ytSNYaRvLGFsROD0Cesruq1Ww5KpTseSqUz0U0W6annri7L/DJP6aav2XvXFv/pptfHRzLFZHJZmu0Ap3G/lveFQWMyvusp0b7MmUrjwpNmjbENqaGxXJu9yAXX+SOoaT9tve994AN9NltO707yNfejP++Ik3cApsTjgXE6EStRTkRod9nyfgvwBTEkK2qWziwYLufcquONqnMqU6LToYBdTUXa468v526Yme9q1rbRhBp9T9WmP2rqfWYku1weN63nbwHB48LZAbetool0BwlW1VzM6+syfx15tG6li3pcoz8eR0Y9ZOq6WoMLmPfOnNnrYGWQoZqJL//p8/wot7Th1XUt6rq7w45QEe/8qp+M7/HMPHLQ1CDQKbL+0sLwIHCH/GFp+rP/jfV2HJVacK5QEYa24QxYDbHm8lZvnvzn0oxnLVm0Xjx+xbynst2SyFWBnzIhDyOXJv+tjxWHLVqUKJjeGaxeks2llewkIotdFah3/0gVcrS4m0s5yyQ9szq91A8N88shx3PLUWg5UGfv3Qcrc8QN4ksT7uM77pY8fjX4vf5NkHXLfR1mu/2HrvfAyD8RTwBbDu+sLpiWPVoDOR/IjUjt97Jha9dg/MnFAWfJOH7jyFx6Dsup0zwGnMi23bokwyZ9iECSqzvieprMyUFpoayMz4RVJzhE0MJpfKbDbtwI1WDgbbaWqwebbE2WobgkwArVgAp9/DuI3CQNxs5ecpws+XTAMtR1qBlm6woHutXIMGUPcpQNIdI56e5AwJv/a9TKjR/XDozlOw87QBvLBuGLc/uQbLNngZYym5YbNdG6suT4sKe82agOvecSDe+5OHAQBPrhziG5usvIjFEZuCXACwiPCgAHOGty6Yg5/fvwzrtlSxfrjGn4fffJZTpals2K7Vo53bqJ9k5wVBWR6AWNeYMky7nPG8zGhzD2GgKg/An7Pier9aO6w/GVX+huEaVrRSiPcgaxWDKtvIbas3YaKYN5Wki91ATMf3X4eB9gH3e8xw2vbkKld5oTQQT6wcBIu1LhdyxELstpIeeKj4oRABu2MdmeUlAbgU3orFpTWCbNvmqZV7zlDzb+RMA+9/ze5468FzhM/zORPXnnUgLj5+T5w8f5Ygc1RJxe1+wFwqUwOsEofMnYL3HLML3v+a3bHLdq5Z/q0LdgAAXNDK92eWl3pT4eIgnwxVg1k7ZQvJtDZmc9ct5z15sniXnGlEdqcwyNYQAdL7QR9fcj7nLpDMFbJRwTER6FKRPqHssVEQWPeGvF/ehroecGI4jtjNCZB9fMVm7jai1jwxeyQ4hmiLTzVsitfvsz3esM9MAM6CvqLFPj1rktryAqjrCzUF5aW9kj9nSj8e/ORx2K8Vj8B4Rab5uFyYe07NT0TdRsFWDx7grlpfCJTlAZTMrzb/f3UrbmdGCMtLO5QkS4BKJsWgj+WFWaI2jNTQsJo8IHuXaQPKgFNaO0uG2vLt7wbtFCyuqh0xX7Nptw24n9dSzJ5ZPcTTpdlhAACeWDUocIUFrlOQ4tcq6kPW1oTM8pIA+OaqKBjHxs/aLVVsGHaCU/fwUV6CcMwe2+GYPbYjMt1TXVBQ6foQLhXTNHDJG17h+fzTJ++N0w6agwNbxG95oTyAv0y2KJXypjK1U07LbKu8MJI6hfLCq/L2FQJN2p2AWkPaMYUGVWqd0JfHaN3iCs4mBcdEgZyeZH4HL8lV+409DNwgQ2+8FMXyEJYXwM1uemrVEJ5Z4yjouxIlOIiHw5I+YBt0OwVt3swJ+PN/V+Hzf3qCfyYTreVbNcBsW0xZZ2gqAnaD3EYMR+++HR572c1wmu2j3BWJ20hG3bJ5zFc7txG7p6CClADNNjIDFVSGTSN1nvHTzvoTBkJJghBkhIM+vFeT+4swDSflfcNwDf9plZ/Yxyc7UMw28pcbhtOmUwTx6dDxRRVPv/k7d9oACjkDwzULyzeNYtakPoFxd9NIHUvXO4eDgWKe97Eq2N8BdRu1D9gd68gsLwkgyPLCNGJmdZk7bSDwdNepzErd8tY2ospLa4GcElDzxw/9xTwO2XkKJytSRbdzmeR1UJVawFuzpl32TCkgIJplIcRZQKwgVAkPVij8FmDAVWjYwrGJB+wSy4tgHRAfpBxsyJSXqH7rIPI2+pZZXvw2ZwbmanzoxY3YOFKHYYjKC00Hl9dYuX7KUAjLCyC6OhlkLhJaIbyisLxQxckt89C+b99DWFh3njbgz6fDYkAUlpe/PL4KVtOGYQTX4wJozEsHbqMQRVRXt2JupgwUPXOyGwSWB1Bsrn6Wl5zplglZsbmCF1sb9h4zxEB+hiCafKXlJaZ4F0BUXuS5VFNkS40r5X3X/0LO5PPmqVVDWD1YQaNpo5AzuGudHUb7ijlPrI8MFc9LFrCbQQCzgigtL60B9OTKQQDAK9pwcISX6QYJe90NLtxqy9E3d1rDKchV1U556RSsrSOK/mXBbX61R7oBjXnxFr1029mwmoEKBVNo2MLBYhymkc2KpuXK5SXkMg9so4/XbST+jbZvOY8lCY5JYky+Q62+2FlS0MXaM97vq0oLtFNejthtqhBAO3tSn9LyFkTRT5/tCKnh1Q7jywU8/bk34LI37oUfn3+I73WqVGmGfzyzDoATp+VHPc/AlPstbS0vqoBdFfuq8wErAqgKgu0GLDatGqKUgZP5428NYPP5+bVbAjONAHLYUDLNemNeYlVeAmgAKGMt6+t2sUVMKb/yr0/h6dbaNmtSH/aeJe4b/UWRRVlepwA55mXrdxtlyksCKAdYXtgAYkFY8xQnxigyKw0Vz4s35qVdKmQYCNWBA0hJOlFe/E6tFJxht+7t3/ue3wDAP46oGxSC3EbkPUt9Ngw/y4uzKDPrDKsjQxdhunHJtVmEwOvWb5iGusJzJ3AZi/2VbatpY+XmcG4jSg0PACftN0v4uxArpdjUqPVlS5uAXYbx5QJu//Ax+Nuio3H0HtvhC2/ZV3ldKcB1Q0/KnD69FG5xL+ZNLDxi50DFrhjg7mRo5zIC3IDdkXap0ry2UU7gXGn4jKtnWvQLO4bgMwkDKlPljpSVcZYIoNpQmQXi+bXDbZmIxfnqb0lUWT6jIsjy0iAaBVNegsqXAGLQ7jt/8AAAJ+bsnMPnCtf1F3Pcnag6wAJqV/7W7Dbaeu98DMNVXiw0DQMP7LSvQ0duGHzCMuVFZe6OInO01kQTJu6bsw9Mw3BkkuvcmJfoGjclN8ubTvvum7MPAOc1Qxjl5fwjd8b3734BHw1BisQCcTeN1NE0DDy8837ImyaahoHR1oJ+wr7B6dadQHCPmWIbad+yzX27cSXl6Xk8cRttqTa4skBPujnTQM40YDVthx+D9KlF+nSQuFOiBhv2kdRbJm+glG+NV+eaNUMV1C0bedNoG8xpmgZ23W4cnmhZF88+bCfh7yKLsNOPD83dz3lvGLBsmy9MWzoISs7nTOw2fTx+dF6A9YNx2jSctt6/07587FClya07Ft8SyV1W9WZrXdgP5YIpzJUwyssAL6cRzvJSLpiCK3ZLtYGmYeCZVxyE9VuqvDzACy1iwbgOVELMi23ztdBq2nxssaazLL28DwEiC75esXmUV97248MRKrO35C7Z4wAMjtbRJGUJeF2jGC0v1AXbAHDfnH0wY0IZTcNArUEsLzyrK3gu7acgp9thUj8O22Uq5s+ZhEeXbQLguI0Yn8xwrcHb/d/d5jtuO8MQlfMesLxkyksCoMpLtVDCBeddidGaxVMGbdvGS62FYtfpar9tp+gruCbpSqGIt515BQaKOYcWOjHLi1vJumybqBZKeNuZVwAALiy6kzKM8nLJG+bhdXvNwEGKEvQy2ElpqNIACiX877u/iol9BVRbm+V+O0zEXrPicccBohm6RtoIiKcZluWyvY9lgm2Eg5UG59MYKOY8MT6FXEt5aTSFPqVGKcopEhU8C6ra4PIO2mkyqi9t5Asei3eZObEcyjr21gU74DM3L8EHXrO7Z0MW3EawUS2U8L/vvoqnv4qkaTGTiNEyGoUSzjv3y5g8UEB1w6i0uMcfE8BcZ6yf33P+lZhQzqO63uVEakdQB7huo3YxL9zyks/xQqxW08ZgxZF/7aXfxU2PrsCueadvWTBou5imsGAxL7bN6PJLeM/5X+FrkGXbMFsUapSwU6WMM96ZlZsq/ADmp+gVJUtptVDC5y/+Ju55dj0m593nuSlmgjoqu2Y1MZp35tJ5R+yM6j0vKC0vMycGP+8jdp2GMw/dET/711L+Gcv2o4kNE/sK2GI446FSbzrrR6GESz/0DSzbOIrqUFWwonLqiq2Y5yVzGyUAdnJgufSmYYDOx/XDNYzULBhGexN8WHC3ETEZcmbH1geVusVP+3EQuLHA3YYqCJC8bsckzH7r0F2mhqpcKt+7aULo39e30mbjQoGc5DzeMbLhMcvLrInq0xQN2GUBe6qTl1AigMoir3lmSgzKSz/ZVBnY6ZWZ8sNmGjEsPGJnPPnZ1+ODx+3h+RuNIWKNypHq4dQCwvt0UvTUXYBaP1hpCcLOrDyZxre4szpMbPM2DeDCY8XioX5xHBQDPNsoHMNuKW/CMFyLxlBrPuZaFhfWaqa8yCnm3YISM7L0cKr4qpRFvwPOzNacemLVIA9s9lvDVKUQVCy3mxQM11EhpqQ70phCI8S8MDLANm4j0zTwhTfvi6+cvj//jDGv04ywUj7nsa4BTpC6y7DryKes1VnAbgYBzA0wyOMSDEGRWNrivpgxvhxYFbYTsFMdjXnhJTVa17ATSyFnxLIoB9LmdxnzEgZyJlGO9C8AHLRje+tNJ1DxJ7BFmDbbPU35KC+t9g9VGjzeRXV6FKvxuhAsEiHZWMOgT7EZuguucw8vh8w0ovDLWOH92XSzjfKksjHN+lm5KVxsQFgUpb41DJcmn4aC8JiXGBd3FhjKArUNw8DpC3bAl07dj18ztw1BIwD080Km/m4jq2nzmCm2xrC4IaYoMMspbOc5s2ccl/JSzJncWshcXHmivAhrxAijGFCvS0zJZwpHUGCzKmBXPsgBbqr0RB+G826gCowWCoK2sLoDJmMAOHG/7TnBJ2OxPu+IuSjmTM5xVMqT/mbKC9w+Z4cC9vz7CHnh1oit12Y0hkHdBn21Cm5dfBZs2DjiPdejaducuCuuwDhAzDYqVUfx0NfPhGEYOOI93+cTdgMxwcdBypSnWTgt+u+7rzsPAPCDQ2/n1zG57VJAw4Iy5/bVKrjp8rNgGMBhF3wfo8VyLK4UCmqGzo+2+hbAEe+9XrC8tFuQxpfdzSMoY8JNebSEPj3yvdfza9gGGIvyQlLPmbxi3sQh7/oeJ/oKm2kUBmxzsW2nT/tqFfz202fBato48r3XwyZKxIqW5UXmbOkWNNuor1bBndecD9MADn/39wVLALNCTIsp8wZwKzXXGk6b//qFs2BcXcCJTz2Lr04so5AzQ1kNWSG/ILcRtdqxzZNZXgYrznO+9Pxj8dG6hXd88gY8smwTRmoWJvYVsFNM65Jj7XGYwEeqjsw/ff4sNFvPWWV58bPOygeCIC4o6rpptspAfOMDx6NmNXHCB3/Er9uchOWFyGZzqf+6HL5z3neFQGl+0AmpvJQLOfz83Ydh00idBy/vNn08/nnJq7lSahgGBop5DFUbGG6Vprn+oyeiads4/N3f53M57sNkWsiUlwQwc0IZsyaWuQ9/8ohLYGUDStbRqGAL00grxmXq6CCR6QzadcOs6Fo8SgTT6BvkBM3k0hPOhpjJoPqKOcycUOam10nDm4W/T4tJSWKgJzkDEPtWiM8IpndXuY0Ca7O0NiBRnlPUkSk/cbRVJj2j8pifnsVozYkhHqKgSAenz5BZXoYqdR4462fN6hSy22gKmZuMRGxLtYHnW4Ul99o+vtipXaT0/ckjm4ERJ4bljo8cC8BbUVmF/hABu5TFlykvbJOrNZroAzAwuBEDcMbUXU+vBQAcu+d2oVy3YVEu5LCl2uBujMnkOdMMpME2ruVxpTzGl/I8/T6IRI+107ZdLqjxWzY5n5HrNvJU6fgtLwxTRweBFq8cc8HWrSZfKzoZ1ypSPlmJ6y/lMFRtuAHnrXYDrhW1FzKNgMxtlAhypoHzjtxZ+TfbtrnbaM6UeMyzgLgxykRfbINtx4/QKQo05kVyG1E2yTAlCTqFH7smEH8EPVUmvNVxXbSjd3d5XtyAXbXy4ihLstsI8D7LpNxGDOy09twaZzOXK3x3g6B0cMA1bzMix5kTyrG5b2S3EQUbsk+vHoJtOxwccfQvw/QJZfzPsbsq/1Yu5EK7kHm2UUDMC7PKlPImV0b8CPdsAPc9vx6AEyAaJ+ihSgZdpzb71ASj2J7EPQU9l75CjrtPWBYTBwla3dTaxOM6zAEiT5MMpqivbQXPFnJGrGsi4I4NRjFA0ZDcRltzphGQKS+JgTKKUtgA/rPcOdl2UxbAD8wEuHm07qWVb/2/NuC03w0oo6McyUrjFniGU4wWkVfuOtX3b3GVBWAQ6ez9eSPaKRSc52W0HlhDhsmrKrhI+LNMwG2k2tDrLeI9ZuXaxWdcd4ICCc6Vg5IBNwia1bAJUlQ7RRBJHRuzLM5mTgwuMhmnHrhD5N9gsTPrh2ue8Xj7k6vxlm/egyO/eAcAsbyB3/xr2jYeX+GsSQfuNCny/VFwq56K86qDgF1AjHsKGveGYfDgVfa7XGbr/82jdT53kyCpU4EpD6v4waUc+1rFOIBoUC5DjVte/FnAtyZkyktC8NPmhyoNPLnKWSgWhEgLDgs2EIdrloLczJk0cZ7WAQQyOjIFymra3Dwb5wknTgbddhCo1eXAZFJPhPFG+CovPGC3jjVD/pYXVYAflyc/yzZF/MIgiAK/Ydl4fq1DXrbd+FIsfnLDMLjLUaW8MCXivy3lZd8YlZdSgPLCxizLcPJLeY+CqHWoAMfVYBpO3zH3I8Plf1iCh5du4u/ps/XLTFuxsYKRmoW8aWCnqfHOqyA2bHrGCmLXZaAxgu2y7FhwK3ORMDBrDztQTSjn2zIadwLTNHyDYOut+RyWXbcb9HPLi1d5YdlOruUlcxtlUMCPVOvhlzbCth2XUVzuG0AciJtGxIHLNtwXWn78+NKzCQmVj+Vl00iNy4+TTyGOqrdhUaCkaj61jda34onypsFTYmVMIm6jZYQ3xSMv5+/asOFssmGL+IVBEENvvelmocQVyAnIVjsRbINhlpd9d4gv7iTYbdQ6GXP20/jHWNRSDoDTd6wEw7f//jzfFB3+qBHp2vYEeEyJcAoBxrslBFleVIzGQcrxHoQ874BWcVg/sH4ekiwQLIYriQMVg18bmEIRll23Gwxwmg6V8iLHvGSWlwwK+JH/PPCiQ19/8E5TYpWXz5l84HpjXpwKxY+vcDYDuS5Gt6CF5jzVgVv3wBaJuE84ciXqJCHGvKivcQNoS76m4Mn9RZ5izSwOqgXMVV7UdP0bR2q8f+PI4BpXzsMv+azesEmsVHwnRR7Xo3KN2U48x3Mti0+cbiM2ZlUU/axPV3aYxtoJ+mOiRnhvK3bm+ntewGu+8ndU6pY3vgPgSQNAe0V3txhcgjL6giwvZDKFicM4eO5k5EwDMyaUsH8rXdgPclo4g2M9tbnlJc4Crgx+hxeW3bQ6JLtuN2Bp9Crlpc5jXrZ+dl0gyzZKDKwmStMw8MTsPTgN+gMvbgQAHDQ3Xi4SwNH4h1sU7/+euTv6CjlOYX/fC+uxbksN48t5vCKmDArKR8La999Zu8NqAg3b2ZzW8zTpeE2kzIrTNAw8PWce+opOW4/dc7tY5QASz4vp9G0hZwjlHrjyMt5/MTRNJ0CPV77uLygryrLaLNUWjTzrU+dZ2jzeZcpA+yJ+YZAzDUzpL2L9cA1Nw8B/tndYcZuGgUazSVxU8T1DGnvSNAw8s+M8TtlvNW28uH4Ytu20cfr4+BZ5ejJlc7OQMwX69CQtL0yxZf287+yJDstihzhpv+3x0V89BsDhjfrnc+t4Gvuk/gLnQ6FuOeqibBoG1r1iPyzfOMrLE8R1qKHoI5YX9pxHW89cdBu1j8OYN3MCfve+IzCpv9A2I4rHvIw6clfstjfWbnHGd81qYmUrFT6u+D8KFkPD1uE9Z45H0zBacTY2VoZk1+0GfHxXndIpL+z8Ctittbne6K1so6377scwuEulUMLbLrgGedNAdbiGamvjWRCz5QVwJv6KzRVUCyW86dyvYr8dJqL68mbYNvDvZY7V5dg9p8dGjMerxraI8aqFEs5977VYP1zDqQVn4XfLEcR7wmFtqBZKuOB/v4lfvvdwfPK/q3DaQXNilQOIMS+1fqdvZ04oozpY8QRDt9vgtxtf4sqLn9mYVqatFkp4+wXX8JOUbQPrhuJj12WYMuAoL9VCCaed9zW871W7oXrr06hbduyxUoD7/IZbJTQu+fj38dTqIVQrDVi2HchAHAXjCNdOtVDCuy76FmZP6kP1xQ18M2UbW1zp2SpUCyW8+Z1X49kvnNDV9/uLebx63nTc/uQaAMBjL2/miuyM8WXMnFDGk6uGsBMhvaOxQ9VCCXf++I/4yC//zT971bzpXd1L8H2KpVI+cvF38cSqIU/mHit3MaWNazmsFY5ZvkfrFlAo4SfX/ArfvPM5AM48Xrqh5QqNOcYHcEnv2Dr86KWvRfUztwJNG5tG6vj9v1cASMbywrLyNg0743vxp3/klAp4cg13mWXZRhkCQUngqg3LY5bfPaaaRhTyqYWywD7TKqe+54z45Jbzbp0YthDlcyLV+vqElBeK4aqF6ePLOPvwuUpLRlQEMux2mLpM/+7HVssKFzKXisxKunZLfOy6DNT9ZBoGf44Nq8mDi+OUJ5v1TcMgfWpj7WC8mXEMbHFnyqBhuIYPq2mj1mjybJC4YsP80PDzQYbEpSftxV8v3ziKNYOue+/bZx+EU+bPwrfPPohfM3VcSShdQWOdSnkzGcsLU1IJXT0bzmwuUd6T7WMqAyHzn1C253qj6fIWxRjHxSCnP/cX8zyA+E3X3sM/3316fNmmDGydZXw4dC4z2gNmlctiXjK0hWO6dTeg+XMmxZ4iB3gDxdim9+9lm3DPc+sAOKyMcYFaXljZDrbRy1H9cfMZUIy2KVAXFUJ13NZnbukFKU6iTRAetZb4pdMXJCK1HHEr2EjGEjKVFOo0DVp9uRlrWjbDgJQNItP0c8K/uJWXAKWpadt4evUQmrZjfo+zvUlg7rQBXPXW/QEAyzaOYPWQm4K709QBXP22AzBvpqiQ7D9nEn9N4/JmTeqLhXVbBq1YDrSURVZLquXRWj1YgW07Y66d5SUs5BIH+Zz7nP/53Hrc1rJYJRHnM18KJs6ZBleSGMfXlIEiXrF9/MqLnBSRMw3ChO50+LoE5nMayJSXhFGuV3DXN8/D77/yDpTrzuLyvlft1uZb3YEt9OV6BXd/6zx885Onolyv4Pf/XsF5ReIgGWNgp5m6ZaNhNVGuV/CrL56Ju791HsyKM0mTchsxlOsV/OVr5wJz5wIjI22v7wbM9D1as5CvOH37yy+eiXK9wi0vYeMk6IIxf47aBM4sWsO1hvP8vvIO3P2t87i8RJSXluWlXK/gr18/F2eecQzK9QqWbxqNNS2bwbW8OG38xv97C/5w1dko1yto2jYn8Yt7gR1HuHbK9QpuvOLtuPrjb0G5XkHDsnFHa1M7aO6URDZzBjZHo45b5va47/kN+NItTwEIDqxm3FLlegWHvuYgPq7iKnwpg5Uy2Nzq729/6jTc+vVz+XMGSOrwRP9g904xj2QmlesVnP32Y3HXNxeiXK/ghgecCs2zJpZx6M7xu++P3mM7Lvfub50Hc5edscuA2K5/fvzViYwvWuqgXK/gMx88CZ/9wEl8fAPhXdxjHVnMS8IwbGCHwTX8NRAvsy4F4z5RyWSIs55SifAZjNYtGDYwc+NqAIBt6XEb8bYOAp6Up5jArATDtQZg54S+ZRJXhIyT2J247fwCp5nra6Tq9OmsTau5vKZtY1UCLhX2fAwbmL15DbDZef3w0o28W5NwGw1V6jBsYLv1q7h8q2knZnlhcpu2I2v7jW7fVhoWlm10FIk4OZhUiGvcqviOZgT0GXuGhg2UXl6GHVqvk0jbBYApLYve5tE6+mxg+gb3OTPlZWUCqcM0G8mwgQmrl2NC6/WLLZfRe47ZNRELOHM30mc8Z1IZwGb+97jiDmXQ7CnDBqauW8lfj9YtDLfqHgHx1u1KA5nlJQX0F5LRGcMQt8VZRZQqLzL9N+N5YWbSJOIHDtsl/lOTCgMk6NBTHoBZXlqWglltFuAT9t0eB+44Ca+ZN91XkWQLm4poqtkEXm5tsDvEUGeIQZUNttt2A8K+GldhTQAYaJ3IZRIxAC3LS7ylLBiCeFZGaxYvQJl0vEtcmNxfwB5SHFtQn/kpg7MSCk4OOrTwAOmYi28CTsbPgE/827JWsC61zsQNWSeisTU7hagc3i2C+nuoUucuo75Czrd/thZkyksKKBeT6fZ2KdAX+tRV6Rb5nMnjamTejKbt8Cm80OLq2Hm7+KP6v/62A/CR1+0R++/KYNwJVtNGxcNLYuP//fY/PAiuneWllM/hNxcege+/82BfszHnxlDE8li2zUnjZk+KbxGcplj0jtjdrXMzNaa0bIZxJZewT0bTRmDhyigYH8Bw+9N/LcWKVmkAOWZirMIwDHzvnIMFioAgpdbvtH1gQpamIIU3ScuLYRhtLQtJrEkMMvEjVYaTyHBiCKq2vX5LDV+77RkAjgUuSbeoDmTKSwoIomOPglmT+nzJ8T7zpr3x4dftGbtMZn0ZlejWraZDBMU2p7kJTNjpE8o4/6hdYv9dGXQhkmuGNJvOpscQB+U2i7HZoiD2Gqk1uM86acsLrR8Ve+xJgOXlmdVDicT1AMGWlxfWDXMW6jj7VsYp82fF+ns7Tu3Hde84CLtuN4Cdpw0E1kybNuDtz3cfvTOO3j1+fiQgOFCfKy+bkuHVacfonWTMh5z1SMdTkpaXyf0F3/pKv3lkOX7z8HIA8VSjTxtZzEsKCKJjj4rZk/rw0uAWz+c7Txvg0fZxolTIYbhmeSwvlg189uYlAJyJm5SPVwdypoG+Qs7xGUvWEBbTAwBH7T4tltNMOaDKMzN5DxRzsRaUUy1mB891lZe4nx9TIqqNJmQ14eIW+RqAWAnqgHDcFoaRLMfLl07bH6/ZcRzw1fh+s1zI4S8fPBqmYQTGcew4tR+fPPEVmGY0uPwPvXZPr58jJuwQUNySZRu5mXrx9nm7OLskLQ99xRyGyfvZpB9kN1+cMAwD0yeUuHXWD0lSV+hCZnlJEEfupi4vn4QSweBXVyMpa0+5ZXmRXRxLVmzGTY86ZEyv3WtGIrJ1YsCnWuuqQXeR+PrbDohFFlNuZWsWACzdwCwD/bEuvirLS18xh9MOcqogn7jv9rHJAtxAziCML+Vj5+0ZKOWFjAyGg0g15enjS7HX+KEo5k28cf94rS+A48YNE4D6rqN2wSkHzI5dvgrFvOkbW+FaXpw51C5erFOolPtzDt8JALDwiLmxypIhxzWWCzl86dT98J6jd8Exe8RPBkgRpqxFnCU30kJmeUkQV711f9xwZwn1P78CL6wdhq3BxTi+nIdtAE9P3RET+/JcJtt840ap4AazGgawfNbOGK5a2DBSB1p/O/fwuYnIBuAck/fay32dEBzlr4YtdQtPT90R5YIJ2wBWbXbcG3ttPyG2OinUMmcbwNKZcx2OGQO88F7cbg3m7rIN4NntdnT4LwwDV7xlXyw8Yq6HLyQqqKXHNoAVs3fBlkpDmCPbJVB1F3Ay7jaObOZ9u+OUfuw9exLuXulkwmiJd9E0bseC/B+/61C85Zv/dJ7zrJ1RaY3lpm0LBHVxW16Y28g2gE07745JfQV86HV7Yp89ZiVSRoSiXMzxdXiPGc5ceuvB8bN/qzCj1Y+2AayZsysGSnlhXp2xYA4u0OBuTxqJHS82bNiAs846CxMmTMCkSZNw/vnnY8sWrzuD4jvf+Q6OPfZYTJgwAYZhYNOmTUndnhZMn1DG+0+ej8ITS/C6d30TlULylZDHlfKoFMp43bu+iau/9lsuM6kMJ1rfqFIo47NX/FJo67fPPghzQ2RBdY3+fuDxx51//cn5knl13FwJr3vXN/HBT/0ElUKZR+/HWd6+jwR0VwplfPBTP8Ep//NtVAplnr0Vt/LCrDiVQhnHnfdN3p/5nIm9Z02M3VpIAwsrhTI+98VfeOZI3CdxBhbYXimU8eHLfgo8/jjm7uhuZknJFaBp3I4F+WysVgplfOaKX+KcRdejUiijaTsUA4ygLm4iS0ZxUCmU8dcbbwMefxzliePxxv1ncablpNBXMPk6rPsZM8tLpVDGtdfchGduv4/Pq3LBxBWn7sv7ZmtGYsrLWWedhccffxy33norbr75Ztx1111497vfHfidkZERvP71r8cnPvGJpG6r5+EXkNifkOVFjoUoSKnYSZ9wdEGe7PJmHmedEtn1lzPdOAZmefErLbC1QM5CMQ0Db5ZcGYeTgOE48fp9ZvLX7DnSOIQFCRRN3ZZB44yqDctl2LVtPLHSKVuy2/RxsXOujCNrHqPI14Uk4xrbgR6kCjlTcJPOnFDe6rOMGBJRv5544gnccssteOCBB7BgwQIAwDXXXIMTTjgBV155JWbNUvt7P/jBDwIA7rzzziRua5vA/jtMwk/gZL9USVrvQFIxLwVRWSmQReLi4/cUaopszeiX/PbyAhAnH8lUKR7EIBT2/1nuEF3FyZScBuSAQdMwcMWp++KMg+fgnO/fj5rVFLKd4gR1C+VbpRf232ES3nLgbJTyJs48dMdE5G6rkMksmY6y6MZHcVQry2mvBOoq0QNHknGGKuiWR0EPUoW8KbjjtubECRmJWF7uvfdeTJo0iSsuAHDcccfBNE3861//ilVWtVrF4OCg8G9MYWQE2Htv/PV7F/LyAEnizQfMxvsO2R5Lfv1hXPzhU7lMWcmIC7uQ2iDlegUf+/CpvK1JlJv3oNW/2HvvxMoDAMDGESerqFyv4K/fuxBXXX6W8DzjbCvlpyjXK7jq8rPw62+8W5A3f0781gHTcNuXdH+W8jmeGluuV3DJxaehtP9+OGxmH7537gJ8+bT9cMCOyVhAWCBnuV7BFZe9Hdh7b+SrFVz11vlY/Jb99CjcmsbtWJDPFP1yvYIvXXYmfvgVh6b/xfUj+PF9LwFIhjCOsSmX6xW8+rRXa+3rD712D4xvVvHAzz6g/Rkzl2y5XsH5730jSvvvx9eOJAPRdSOR4/iqVaswfboYUZ3P5zFlyhSsWrUqVlmLFy/G5ZdfHutvxgrbBpYswR5wKJqTUiIY8jkTFx+/J3DqU+iHWx4gKVPhx46fh5+1eE4MG5jx8vOY0XodNzuqEq3+/f/t3XlUVPfZB/DvBWYGcBxGArIoCBQiogKiguCWBFJcXrU5JnF7U60Jvho8jW/dML4ubY8Hs9S0yUk1XRKaYwwntkpMo6YUxK0ukQhKtEQNKioI1bAp+zzvHwPXGdlh7r0zw/M5Z47D3J/z3N9zZ/nNvb9FvC+RZ0K9UHC7CgIBT957VN9WllwbZoDaERonB9Q3GYxTjJcUmcWLDnCXZKjjwhh//O3Yd8b63YOk+QSMw/dLKuuM09Pf/h64bYzZujaMVFo7cgoEDL1TBNyB5HVtQ6bXrTXFFwjwL70u3jfVndnBe6r1bLNAwMBr3xkflKmuI33dcGZDPFzfuiZrXMD89e1x4yoAYOKrTyCr+IFdnVXs0TdpSkoKBEHo9Pbvf/9bqn1t14YNG1BZWSneiouLZY3fU0peC5WCm6sKSycGtrvNkp1YlbZ8aue98711lp0dNKiT1W5T5462WCxTr8U/iVcmt38spbBsijIjHuzp16e9kGLiNqU7pUo1PUVX2vths+PFSHy0ZDxeaJn6wB70KLurV6/GkiVLOi0TFBQEb29vlJWVmT3e1NSE+/fvw9vbu4P/2TsajQYaje18SdrTNcdWOpf2X0aWnmBMSa5qJyyI9kPGiStttnlo1RafeCruR0/gckn7l0C7mjm0tzwHaiSZhbkjHc1JxPqfziaz6y2tHYyo6Y1BA9q+r9xcVXjaUy//zkioR0fX09MTnp5dn9KNjY1FRUUFcnNzMXbsWABAdnY2DAYDYmJierendsIeGy8dDTvU29mXU0ednkcNcYOThX/NB3Wy7opUc/bIraOlLJj9GTxQg+p7Hff5k+Jz0V7eJz1lL4MkuiLJ+dMRI0Zg2rRpSEpKwtmzZ3Hy5EmsXLkS8+fPF0ca3b59G6GhoTh79qz4/0pLS5GXl4erV43X6S5evIi8vDzcv39fit1UhBKNl4nB0ozaaKVt50Pi85UTJVluXkmuHfySk+L0dEcrTgP28+Ek9VwbzHr8efF4LIhuf5I2S69f1aq/nnnpLyS7+PvJJ58gNDQU8fHxmDFjBiZNmoQ//OEP4vbGxkYUFhbioUkv7F27dmHMmDFISkoCAEyZMgVjxozBgQMHpNpN2UndYfdxny6LwZ8Xj5c0Rntf3p0tDmerOprmXIp+TLayqnFfKPnl8sok+fr2MGD0UDdsnjWyzeNODoLFV7tvpXSfFyYtyY6uu7s79uzZ0+H2gIAA0GM9sLdu3YqtW7dKtUvKEARg2DDc+qEWJKDDFT+liAkAkf7u4jT9Umn9EiIBaBjqZ6yjXBMhmdRV6piuLdNs39INhqvGUZxyW4oGaeuvURKAex4+qG1olmV5CVnz2dIYJAH4wdPXOJmWTK+bNYnDMf1HOtC+YRAA+afolzHPVhP/sc9CACj4ZaJkZ6MHaJwwc7QPHvxQBRqmwHFW8Bgf/PlknL10S7nXtwy4aSo1V1fg+nVMSvnS+KeFF5rrLKZctCbTcN849y1C5DzrImNdB6gdUadyxqQVH2JBtD/qzhqHTEtx5mWgSU7/940MHPuu3OIx2iVjPk2XJPjVe1/inXmRssQFjJdvx44YKuv7xIzM71GriP/YZyEg/WX09xdFGe+svN5lWYPBgIaGhi7LdZuDA2A6+rZO+nm+WgW5qxE0KQj1CsXvjFqthoND33/wceNFJv83cwQ+OPY9Nv1XmNK7YnGmp2fteRiq6dBHtclMwlJ8AJvOy1NV22jx57c21XX2X0dmvRoaGlBUVASDwdB1YdYnDg4OCAwMhFrdt1GT3HiRySuTg/DypEC7WVfClGnfBbWT/TZeBpitlfKonlL/eqwy+WK3sz7QouESzLDKrJulF2LsLSJCSUkJHB0d4efnZ5GzAqx9BoMBd+7cQUlJCfz9/fv0fciNF6nV1gJTpgAAhGPHABcZOmKaxIQMMXUtQ6I1jfXwTpgCCPLEBSBrXV3VTtA01uOzPSkYvE+D3bN+iXqVRtLGi6axHh+8uwYPG5rx4sLtcJB6dVqZXzsZyRORmVuE1RtfAv5PnpgimetqNbGVit8SM7+2EU/N+iXemDuu6/9jwbgA2q1rU1MTHj58CF9fX7ha8v1lMDy6bBQaaryMJCel43fA09MTd+7cQVNTE1Sq3o845MaL1AwG4Ny5R/ftMKabiwq7/nssBjTVwWGH/dZVq3GCAxEiSq8ApYBDS4dzqWZN3rkoCrsOXkDITeMHkAMRNFKPVpP5tRPpp0ek+5PAczK/blpjyf3etIbYSsVviekG4JvT8RC0Mi0u2kVdm5ubAaDPlzHaIHq0ppFSS0AoGb8DrXlubm7mxgtT3rRR3sCDB0rvhqQ6uiTmopamQTF9tA+mB+mAlEeP2elVI9bPWOPlc2vcJ3tkqTxbx3kkxmxARzN2Oss4adzDhmbZYjHGmLXixgtj3TR4oDO2zG47WsxZjuHvLX4eHyJbLMaYbRPGj0dGTo7scQMCAvDb3/5W0hjceGGsB+aPb7ukvFxnXj77nwlYPlWa2UgZY7anvLwcK1asgL+/PzQaDby9vZGYmIiTJ08CAEoOHcL0uDiF91Ia3OeFsT5ykenMy+ihevsdK80Y67G5c+eioaEBf/nLXxAUFIS7d+8iKysL9+7dAwB4e3govIfS4TMvcvDwMN7sPaZSceWO6eGBer27+Kfk61UpUD+7P4ZKx1U6tlLx+9txdnIy3iRQUVGB48eP44033sDTTz+NYcOGITo6Ghs2bMDs2bMBtFw2On5c/D//+te/EBkZCWdnZ4wbNw4ZGRkQBAF5eXkAgJycHAiCgKysLIwbNw6urq6Ii4tDYWGh+BzXrl3DnDlz4OXlBa1Wi/Hjx+Of//ynJHXsDJ95kdqAAUC5TFO7KxlTqbhyx2yJ90XuLdTuzQcg3VBp03iy6Q/HUOm4SsdWKr6NHGciQm2jhTrGh40y/ttMQHNTl8VdVI7dHo2j1Wqh1WqRkZGBCRMmQKN5bHVux5bPpcBAwNERVVVVmDVrFmbMmIE9e/bgxo0bWLVqVbvPvXHjRvzmN7+Bp6cnli9fjqVLl4qXompqajBjxgxs27YNGo0GH3/8MWbNmoXCwkL4+7e9rC4Vbrww1gumw6alnmGXMSaf2sZmhG3+SpHYl36VaLYMSWecnJyQlpaGpKQk7Nq1C1FRUZg6dSrmz5+P8PDwNuX37NkDQRDwxz/+Ec7OzggLC8Pt27eRlJTUpuy2bdswdepUAEBKSgpmzpyJuro6ODs7IyIiAhEREWLZX//619i/fz8OHDiAlStX9rLmPceXjRjrBUeTX0dy9XlhjDFTc+fOxZ07d3DgwAFMmzYNOTk5iIqKQlpaWpuyhYWFCA8Ph7Ozs/hYdHR0u89r2vjx8fEBAJSVlQEwnnlZs2YNRowYAb1eD61Wi8uXL+PmzZsWrFnX+MyL1GprgenTjfcPHZJvGm65YyoVV+6YLfFiauqhmboW9SoNBnTzl1Jf4gGQtX6yxVMqppJxlY6tVHwbOc4uKkdc+lVi3+MaDMDVa8b7wT/q1vT8vbkE7ezsjGeffRbPPvssNm3ahFdeeQVbtmzBkp/+1Fjg9u0ez6JsOvNt62Ws1kUr16xZg8zMTLz99tsIDg6Gi4sLnn/+ecuuyN0N3HiRmsEAHD366L69xlQqrtwxW+J5AHCYYpxy21HKEUAK1U+2eErFVDKu0rGVim8jx1kQhG5fuulUczNQ1zLruMrxUR8UiYWFhSEjI+PRkgC1tQARhg8fjt27d6O+vl7sH/P111/3+PlPnjyJJUuW4LnnngNgPBNz/fp1C+199/FlI8YYY8zG3Lt3D8888wx2796NCxcuoKioCHv37sWbb76JOXPmtCm/cOFCGAwGLFu2DJcvX8ZXX32Ft99+G0DPpuwPCQnBvn37kJeXh/z8fPF55cZnXhjrpTefD4efn6fSu8EY64e0Wi1iYmLwzjvv4Nq1a2hsbISfnx+SkpLw+uuvtymv0+nwxRdfYMWKFYiMjMTo0aOxefNmLFy40KwfTFd27NiBpUuXIi4uDh4eHli/fj2qqqosWbVu4cYLY700K8LXOAyTMcZkptFokJqaitTU1PYLNDeDHrssFBcXh/z8fPHvTz75BCqVShzi/NRTT4EeW4E6MjLS7LGAgABkZ2eblUlOTjb7W47LSNx4YYwxxvqBjz/+GEFBQRgyZAjy8/Oxfv16vPjii3CRu8O4BXDjhTHGGOsHSktLsXnzZpSWlsLHxwcvvPACtm3bpvRu9Qo3XuTg6to/YioVV+6YHM8+YioZV+nYSsXvb8e5G8Oj5Yy/bt06rFu3TqGdsSxuvEhtwADgwQP7j6lUXLljcjz7iKlkXKVjKxW/vx1nR0cgKkr+uNYSX2I8VJoxxhhjNoUbL4wxxvq9x0fZMGlYKs982UhqdXXA3LnG+3/7G9CD8fQ2FVOpuHLH5Hj2EVPJuErHViq+lR5nlUoFQRBQXl4OT0/PHk3Y1imDAWhd78ffX/7+L0rHbwcRoby8HIIgmC1B0BsC2Vlzs6qqCm5ubqisrIROp1N6d4zXWrVa4/2aGnnmBVEiplJx5Y7J8ewjppJxlY6tVHwrPs41NTW4deuWZc++GAxAcbHxvp+fMo0XJeN3QBAEDB06FNrWY2KiJ9/ffOaFMcZYv6bVahESEoLGxkbLPenDh8DMmcb733wj/4gnpeN3QKVSwdEC6zxx44Uxxli/5+joaJEvVVFzM3DjhvG+RiP/pUGl40vMOs4jMcYYY4x1EzdeGGOMMWZTuPHCGGOMMZtid31eWnuLK7FEd7tMZ3asqjJeh7THmErFlTsmx7OPmErGVTq2UvH723Huj8e4j1q/t7sz6svuhkrfunULfn5+Su8GY4wxxnqhuLgYQ4cO7bSM3TVeDAYD7ty5g4EDB1pusqEWVVVV8PPzQ3FxsXXMIWOnOM/y4DzLg/MsH861PKTKMxGhuroavr6+cOhiXhq7u2zk4ODQZYutr3Q6Hb8xZMB5lgfnWR6cZ/lwruUhRZ7d3Ny6VY477DLGGGPMpnDjhTHGGGM2hRsvPaDRaLBlyxZoNBqld8WucZ7lwXmWB+dZPpxreVhDnu2uwy5jjDHG7BufeWGMMcaYTeHGC2OMMcZsCjdeGGOMMWZTuPHCGGOMMZvCjZduev/99xEQEABnZ2fExMTg7NmzSu+SVTt27BhmzZoFX19fCIKAjIwMs+1EhM2bN8PHxwcuLi5ISEjAlStXzMrcv38fixYtgk6ng16vx8svv4yamhqzMhcuXMDkyZPh7OwMPz8/vPnmm1JXzaqkpqZi/PjxGDhwIAYPHoyf/OQnKCwsNCtTV1eH5ORkPPHEE9BqtZg7dy7u3r1rVubmzZuYOXMmXF1dMXjwYKxduxZNTU1mZXJychAVFQWNRoPg4GCkpaVJXT2rsXPnToSHh4uTcsXGxuLQoUPids6xNLZv3w5BELBq1SrxMc51323duhWCIJjdQkNDxe02kWNiXUpPTye1Wk0ffvghffvtt5SUlER6vZ7u3r2r9K5ZrYMHD9LGjRtp3759BID2799vtn379u3k5uZGGRkZlJ+fT7Nnz6bAwECqra0Vy0ybNo0iIiLo9OnTdPz4cQoODqYFCxaI2ysrK8nLy4sWLVpEBQUF9Omnn5KLiwt98MEHclVTcYmJifTRRx9RQUEB5eXl0YwZM8jf359qamrEMsuXLyc/Pz/Kysqic+fO0YQJEyguLk7c3tTURKNGjaKEhAQ6f/48HTx4kDw8PGjDhg1ime+//55cXV3pF7/4BV26dInee+89cnR0pMOHD8taX6UcOHCAvvzyS/ruu++osLCQXn/9dVKpVFRQUEBEnGMpnD17lgICAig8PJxee+018XHOdd9t2bKFRo4cSSUlJeKtvLxc3G4LOebGSzdER0dTcnKy+HdzczP5+vpSamqqgntlOx5vvBgMBvL29qa33npLfKyiooI0Gg19+umnRER06dIlAkBff/21WObQoUMkCALdvn2biIh+//vf06BBg6i+vl4ss379eho+fLjENbJeZWVlBICOHj1KRMa8qlQq2rt3r1jm8uXLBIBOnTpFRMaGpoODA5WWlopldu7cSTqdTsztunXraOTIkWax5s2bR4mJiVJXyWoNGjSI/vSnP3GOJVBdXU0hISGUmZlJU6dOFRsvnGvL2LJlC0VERLS7zVZyzJeNutDQ0IDc3FwkJCSIjzk4OCAhIQGnTp1ScM9sV1FREUpLS81y6ubmhpiYGDGnp06dgl6vx7hx48QyCQkJcHBwwJkzZ8QyU6ZMgVqtFsskJiaisLAQP/zwg0y1sS6VlZUAAHd3dwBAbm4uGhsbzXIdGhoKf39/s1yPHj0aXl5eYpnExERUVVXh22+/FcuYPkdrmf74HmhubkZ6ejoePHiA2NhYzrEEkpOTMXPmzDb54FxbzpUrV+Dr64ugoCAsWrQIN2/eBGA7OebGSxf+85//oLm52ewgAYCXlxdKS0sV2ivb1pq3znJaWlqKwYMHm213cnKCu7u7WZn2nsM0Rn9iMBiwatUqTJw4EaNGjQJgzINarYZerzcr+3iuu8pjR2WqqqpQW1srRXWszsWLF6HVaqHRaLB8+XLs378fYWFhnGMLS09PxzfffIPU1NQ22zjXlhETE4O0tDQcPnwYO3fuRFFRESZPnozq6mqbybHdrSrNWH+VnJyMgoICnDhxQuldsUvDhw9HXl4eKisr8de//hWLFy/G0aNHld4tu1JcXIzXXnsNmZmZcHZ2Vnp37Nb06dPF++Hh4YiJicGwYcPw2WefwcXFRcE96z4+89IFDw8PODo6tulpfffuXXh7eyu0V7atNW+d5dTb2xtlZWVm25uamnD//n2zMu09h2mM/mLlypX4+9//jiNHjmDo0KHi497e3mhoaEBFRYVZ+cdz3VUeOyqj0+ls5sOur9RqNYKDgzF27FikpqYiIiICv/vd7zjHFpSbm4uysjJERUXByckJTk5OOHr0KN599104OTnBy8uLcy0BvV6PJ598ElevXrWZ1zM3XrqgVqsxduxYZGVliY8ZDAZkZWUhNjZWwT2zXYGBgfD29jbLaVVVFc6cOSPmNDY2FhUVFcjNzRXLZGdnw2AwICYmRixz7NgxNDY2imUyMzMxfPhwDBo0SKbaKIuIsHLlSuzfvx/Z2dkIDAw02z527FioVCqzXBcWFuLmzZtmub548aJZYzEzMxM6nQ5hYWFiGdPnaC3Tn98DBoMB9fX1nGMLio+Px8WLF5GXlyfexo0bh0WLFon3OdeWV1NTg2vXrsHHx8d2Xs8W6fZr59LT00mj0VBaWhpdunSJli1bRnq93qynNTNXXV1N58+fp/PnzxMA2rFjB50/f55u3LhBRMah0nq9nj7//HO6cOECzZkzp92h0mPGjKEzZ87QiRMnKCQkxGyodEVFBXl5edFLL71EBQUFlJ6eTq6urv1qqPSKFSvIzc2NcnJyzIY9Pnz4UCyzfPly8vf3p+zsbDp37hzFxsZSbGysuL112OOPf/xjysvLo8OHD5Onp2e7wx7Xrl1Lly9fpvfff79fDS1NSUmho0ePUlFREV24cIFSUlJIEAT6xz/+QUScYymZjjYi4lxbwurVqyknJ4eKioro5MmTlJCQQB4eHlRWVkZEtpFjbrx003vvvUf+/v6kVqspOjqaTp8+rfQuWbUjR44QgDa3xYsXE5FxuPSmTZvIy8uLNBoNxcfHU2Fhodlz3Lt3jxYsWEBarZZ0Oh397Gc/o+rqarMy+fn5NGnSJNJoNDRkyBDavn27XFW0Cu3lGAB99NFHYpna2lp69dVXadCgQeTq6krPPfcclZSUmD3P9evXafr06eTi4kIeHh60evVqamxsNCtz5MgRioyMJLVaTUFBQWYx7N3SpUtp2LBhpFarydPTk+Lj48WGCxHnWEqPN1441303b9488vHxIbVaTUOGDKF58+bR1atXxe22kGOBiMgy53AYY4wxxqTHfV4YY4wxZlO48cIYY4wxm8KNF8YYY4zZFG68MMYYY8ymcOOFMcYYYzaFGy+MMcYYsynceGGMMcaYTeHGC2OMMcZsCjdeGGOMMWZTuPHCGGOMMZvCjRfGGGOM2RRuvDDGGGPMpvw/nPydjg5+N6QAAAAASUVORK5CYII=\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Visualize R-peaks in ECG signal\n",
+        "plot = nk.events_plot(rpeaks, cleaned_ecg)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "jRZ7tqAD7tTd",
+        "outputId": "6c2db58f-7f76-4b29-e2bc-e8651fc840a3",
+        "collapsed": true
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "# Plotting all the heart beats\n",
+        "epochs = nk.ecg_segment(cleaned_ecg, rpeaks=None, sampling_rate=250, show=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "tachycardia_count = 0\n",
+        "brachycardia_count = 0\n",
+        "sinus_count = 0\n",
+        "\n",
+        "#Get list of ECG records from dataset\n",
+        "records = wfdb.get_record_list(\"mimic-iv-ecg/1.0/files/p1000\")\n",
+        "\n",
+        "num_ecgs_to_process = 100;\n",
+        "\n",
+        "#Loop through the first __ ECGs\n",
+        "for full_recordid in records[:num_ecgs_to_process]:\n",
+        "\n",
+        "    #get record ID from path\n",
+        "    record_id = full_recordid.split(\"/\")[-1]\n",
+        "\n",
+        "    #get folder path\n",
+        "    folder_path = full_recordid.rsplit(\"/\", 1)[0]\n",
+        "\n",
+        "    #Load ECG record\n",
+        "    rd_record = wfdb.rdrecord(record_id, pn_dir=f\"mimic-iv-ecg/1.0/files/p1000/{folder_path}\")\n",
+        "\n",
+        "    #Sampling frequency\n",
+        "    fs = rd_record.fs\n",
+        "\n",
+        "    #to store heart rate from each lead\n",
+        "    lead_hrs = []\n",
+        "\n",
+        "    #Loop through all 12 leads\n",
+        "    for lead_idx in range(12):\n",
+        "\n",
+        "        #Get signal for current lead\n",
+        "        signal = rd_record.p_signal[:, lead_idx]\n",
+        "\n",
+        "        #remove nan values\n",
+        "        signal = signal[~np.isnan(signal)]\n",
+        "\n",
+        "        #Clean ECG signal\n",
+        "        cleaned = nk.ecg_clean(signal, sampling_rate=fs)\n",
+        "\n",
+        "        #Detect R-peaks\n",
+        "        peaks = nk.ecg_findpeaks(cleaned, sampling_rate=fs)\n",
+        "        rpeaks = peaks[\"ECG_R_Peaks\"]\n",
+        "\n",
+        "        #Calculate heart rate if enough beats detected to get a heart rate and hrv\n",
+        "        if len(rpeaks) > 2:\n",
+        "            rr = np.diff(rpeaks) / fs\n",
+        "            hr = 60 / np.mean(rr)\n",
+        "            lead_hrs.append(hr)\n",
+        "\n",
+        "        #If this is Lead II (where hrv is calculated), compute HRV\n",
+        "        #****Note that RMSSD for 10-second ECGs is extremely discrepant.****\n",
+        "        if lead_idx == 1 and len(rpeaks) > 2:\n",
+        "            rr_lead2 = np.diff(rpeaks) / fs\n",
+        "            rmssd = np.sqrt(np.mean(np.diff(rr_lead2) ** 2)) * 1000 #a short-term hrv measurement\n",
+        "\n",
+        "\n",
+        "    #After iterating through all leads: compute average heart rate of all 12 leads\n",
+        "    if len(lead_hrs) > 0:\n",
+        "        avg_hr = np.mean(lead_hrs)\n",
+        "\n",
+        "        #BPM classifier\n",
+        "        if avg_hr > 100:\n",
+        "            label = \"tachycardia\"\n",
+        "            tachycardia_count += 1\n",
+        "        elif avg_hr < 60:\n",
+        "            label = \"brachycardia\"\n",
+        "            brachycardia_count += 1\n",
+        "        else:\n",
+        "            label = \"sinus\"\n",
+        "            sinus_count += 1\n",
+        "\n",
+        "        print(f\"{full_recordid}: Avg HR={avg_hr:.2f} BPM, RMSSD={rmssd:.2f} ms, {label}\")\n",
+        "\n",
+        "    else:\n",
+        "        print(f\"{full_recordid}: Not enough peaks detected\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "wGmktsI74Ikd",
+        "outputId": "8a2b1cd8-ec87-4fcb-8608-31dc173e3a24",
+        "collapsed": true
+      },
+      "execution_count": 9,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "p10000032/s40689238/40689238: Avg HR=91.13 BPM, RMSSD=9.78 ms, sinus\n",
+            "p10000032/s44458630/44458630: Avg HR=83.30 BPM, RMSSD=18.64 ms, sinus\n",
+            "p10000032/s49036311/49036311: Avg HR=100.24 BPM, RMSSD=7.37 ms, tachycardia\n",
+            "p10000117/s45090959/45090959: Avg HR=91.29 BPM, RMSSD=21.92 ms, sinus\n",
+            "p10000117/s48446569/48446569: Avg HR=90.93 BPM, RMSSD=12.45 ms, sinus\n",
+            "p10000285/s42709053/42709053: Avg HR=72.41 BPM, RMSSD=24.71 ms, sinus\n",
+            "p10000560/s41445586/41445586: Avg HR=64.70 BPM, RMSSD=88.68 ms, sinus\n",
+            "p10000560/s42695383/42695383: Avg HR=65.44 BPM, RMSSD=35.04 ms, sinus\n",
+            "p10000635/s40067704/40067704: Avg HR=65.55 BPM, RMSSD=558.01 ms, sinus\n",
+            "p10000635/s42947358/42947358: Avg HR=65.25 BPM, RMSSD=359.23 ms, sinus\n",
+            "p10000635/s43522917/43522917: Avg HR=57.46 BPM, RMSSD=42.11 ms, brachycardia\n",
+            "p10000635/s44095784/44095784: Avg HR=63.94 BPM, RMSSD=32.33 ms, sinus\n",
+            "p10000635/s45386375/45386375: Avg HR=63.00 BPM, RMSSD=94.86 ms, sinus\n",
+            "p10000635/s48339811/48339811: Avg HR=57.70 BPM, RMSSD=101.19 ms, brachycardia\n",
+            "p10000764/s40539087/40539087: Avg HR=74.95 BPM, RMSSD=305.66 ms, sinus\n",
+            "p10000764/s43681375/43681375: Avg HR=88.93 BPM, RMSSD=226.61 ms, sinus\n",
+            "p10000764/s44069449/44069449: Avg HR=123.16 BPM, RMSSD=10.95 ms, tachycardia\n",
+            "p10000764/s44837313/44837313: Avg HR=112.88 BPM, RMSSD=4.36 ms, tachycardia\n",
+            "p10000764/s47218930/47218930: Avg HR=90.39 BPM, RMSSD=6.97 ms, sinus\n",
+            "p10000826/s40695233/40695233: Avg HR=96.50 BPM, RMSSD=3.89 ms, sinus\n",
+            "p10000826/s40894787/40894787: Avg HR=127.73 BPM, RMSSD=2.11 ms, tachycardia\n",
+            "p10000898/s40746075/40746075: Avg HR=80.52 BPM, RMSSD=4.90 ms, sinus\n",
+            "p10000898/s42413061/42413061: Avg HR=81.25 BPM, RMSSD=4.83 ms, sinus\n",
+            "p10000898/s43492795/43492795: Avg HR=80.27 BPM, RMSSD=6.08 ms, sinus\n",
+            "p10000898/s44986768/44986768: Avg HR=81.86 BPM, RMSSD=14.70 ms, sinus\n",
+            "p10000898/s46049322/46049322: Avg HR=74.30 BPM, RMSSD=8.72 ms, sinus\n",
+            "p10000898/s48575806/48575806: Avg HR=78.90 BPM, RMSSD=10.63 ms, sinus\n",
+            "p10000935/s40761639/40761639: Avg HR=106.60 BPM, RMSSD=1.03 ms, tachycardia\n",
+            "p10000935/s41557927/41557927: Avg HR=84.11 BPM, RMSSD=16.47 ms, sinus\n",
+            "p10000935/s41798696/41798696: Avg HR=112.25 BPM, RMSSD=1.50 ms, tachycardia\n",
+            "p10000935/s45594411/45594411: Avg HR=80.82 BPM, RMSSD=16.24 ms, sinus\n",
+            "p10000935/s48142435/48142435: Avg HR=101.35 BPM, RMSSD=7.60 ms, tachycardia\n",
+            "p10000935/s48582094/48582094: Avg HR=105.31 BPM, RMSSD=3.27 ms, tachycardia\n",
+            "p10000980/s40742173/40742173: Avg HR=54.27 BPM, RMSSD=358.73 ms, brachycardia\n",
+            "p10000980/s40816324/40816324: Avg HR=76.66 BPM, RMSSD=112.55 ms, sinus\n",
+            "p10000980/s41309390/41309390: Avg HR=72.33 BPM, RMSSD=22.51 ms, sinus\n",
+            "p10000980/s41366957/41366957: Avg HR=71.41 BPM, RMSSD=59.96 ms, sinus\n",
+            "p10000980/s42178586/42178586: Avg HR=69.00 BPM, RMSSD=291.61 ms, sinus\n",
+            "p10000980/s42368611/42368611: Avg HR=68.00 BPM, RMSSD=8.46 ms, sinus\n",
+            "p10000980/s42546971/42546971: Avg HR=65.68 BPM, RMSSD=350.71 ms, sinus\n",
+            "p10000980/s42742896/42742896: Avg HR=73.52 BPM, RMSSD=60.43 ms, sinus\n",
+            "p10000980/s42855628/42855628: Avg HR=68.44 BPM, RMSSD=7.67 ms, sinus\n",
+            "p10000980/s43013697/43013697: Avg HR=66.66 BPM, RMSSD=21.00 ms, sinus\n",
+            "p10000980/s43143228/43143228: Avg HR=83.50 BPM, RMSSD=112.71 ms, sinus\n",
+            "p10000980/s43744967/43744967: Avg HR=59.03 BPM, RMSSD=263.09 ms, brachycardia\n",
+            "p10000980/s44669583/44669583: Avg HR=85.13 BPM, RMSSD=57.80 ms, sinus\n",
+            "p10000980/s45105401/45105401: Avg HR=62.30 BPM, RMSSD=28.77 ms, sinus\n",
+            "p10000980/s45832921/45832921: Avg HR=66.69 BPM, RMSSD=25.37 ms, sinus\n",
+            "p10000980/s46293961/46293961: Avg HR=77.78 BPM, RMSSD=62.54 ms, sinus\n",
+            "p10000980/s46543372/46543372: Avg HR=70.06 BPM, RMSSD=262.40 ms, sinus\n",
+            "p10000980/s46642833/46642833: Avg HR=78.39 BPM, RMSSD=134.87 ms, sinus\n",
+            "p10000980/s46857734/46857734: Avg HR=68.85 BPM, RMSSD=64.06 ms, sinus\n",
+            "p10000980/s47004256/47004256: Avg HR=71.67 BPM, RMSSD=33.70 ms, sinus\n",
+            "p10000980/s47499371/47499371: Avg HR=61.10 BPM, RMSSD=331.21 ms, sinus\n",
+            "p10000980/s47544594/47544594: Avg HR=64.08 BPM, RMSSD=19.75 ms, sinus\n",
+            "p10000980/s48132909/48132909: Avg HR=77.51 BPM, RMSSD=9.96 ms, sinus\n",
+            "p10000980/s48150809/48150809: Avg HR=79.16 BPM, RMSSD=17.03 ms, sinus\n",
+            "p10000980/s48288896/48288896: Avg HR=81.42 BPM, RMSSD=12.68 ms, sinus\n",
+            "p10000980/s48376834/48376834: Avg HR=81.39 BPM, RMSSD=19.80 ms, sinus\n",
+            "p10000980/s48778222/48778222: Avg HR=83.65 BPM, RMSSD=105.32 ms, sinus\n",
+            "p10000980/s49144190/49144190: Avg HR=71.32 BPM, RMSSD=128.42 ms, sinus\n",
+            "p10000980/s49202548/49202548: Avg HR=72.15 BPM, RMSSD=85.76 ms, sinus\n",
+            "p10000980/s49245181/49245181: Avg HR=70.65 BPM, RMSSD=10.41 ms, sinus\n",
+            "p10000980/s49560547/49560547: Avg HR=55.32 BPM, RMSSD=428.61 ms, brachycardia\n",
+            "p10000980/s49961002/49961002: Avg HR=74.67 BPM, RMSSD=281.44 ms, sinus\n",
+            "p10001122/s47286409/47286409: Avg HR=85.42 BPM, RMSSD=8.94 ms, sinus\n",
+            "p10001176/s40925049/40925049: Avg HR=94.38 BPM, RMSSD=5.81 ms, sinus\n",
+            "p10001186/s41997536/41997536: Avg HR=94.64 BPM, RMSSD=5.35 ms, sinus\n",
+            "p10001186/s43468501/43468501: Avg HR=95.78 BPM, RMSSD=6.49 ms, sinus\n",
+            "p10001186/s45986118/45986118: Avg HR=101.90 BPM, RMSSD=5.53 ms, tachycardia\n",
+            "p10001217/s43576724/43576724: Avg HR=67.00 BPM, RMSSD=21.99 ms, sinus\n",
+            "p10001217/s49758073/49758073: Avg HR=71.71 BPM, RMSSD=34.43 ms, sinus\n",
+            "p10001338/s46440135/46440135: Avg HR=79.28 BPM, RMSSD=14.10 ms, sinus\n",
+            "p10001338/s46743816/46743816: Avg HR=55.86 BPM, RMSSD=32.24 ms, brachycardia\n",
+            "p10001401/s40341634/40341634: Avg HR=73.54 BPM, RMSSD=134.78 ms, sinus\n",
+            "p10001401/s42790963/42790963: Avg HR=55.34 BPM, RMSSD=84.18 ms, brachycardia\n",
+            "p10001401/s44102194/44102194: Avg HR=63.37 BPM, RMSSD=388.59 ms, sinus\n",
+            "p10001401/s48531703/48531703: Avg HR=65.10 BPM, RMSSD=2.31 ms, sinus\n",
+            "p10001401/s49368993/49368993: Avg HR=70.18 BPM, RMSSD=341.39 ms, sinus\n",
+            "p10001401/s49466912/49466912: Avg HR=60.99 BPM, RMSSD=278.05 ms, sinus\n",
+            "p10001401/s49500365/49500365: Avg HR=63.58 BPM, RMSSD=220.97 ms, sinus\n",
+            "p10001492/s41103859/41103859: Avg HR=76.18 BPM, RMSSD=9.48 ms, sinus\n",
+            "p10001492/s42186899/42186899: Avg HR=73.79 BPM, RMSSD=8.44 ms, sinus\n",
+            "p10001492/s45842645/45842645: Avg HR=69.06 BPM, RMSSD=5.16 ms, sinus\n",
+            "p10001492/s47226536/47226536: Avg HR=70.94 BPM, RMSSD=17.73 ms, sinus\n",
+            "p10001492/s47863823/47863823: Avg HR=81.82 BPM, RMSSD=8.54 ms, sinus\n",
+            "p10001629/s43749278/43749278: Avg HR=73.12 BPM, RMSSD=20.30 ms, sinus\n",
+            "p10001629/s46034277/46034277: Avg HR=82.42 BPM, RMSSD=41.52 ms, sinus\n",
+            "p10001663/s42060926/42060926: Avg HR=69.66 BPM, RMSSD=7.10 ms, sinus\n",
+            "p10001663/s43742645/43742645: Avg HR=63.43 BPM, RMSSD=9.48 ms, sinus\n",
+            "p10001725/s41420867/41420867: Avg HR=59.52 BPM, RMSSD=23.74 ms, brachycardia\n",
+            "p10001757/s41800350/41800350: Avg HR=70.49 BPM, RMSSD=19.53 ms, sinus\n",
+            "p10001843/s43647002/43647002: Avg HR=51.47 BPM, RMSSD=47.38 ms, brachycardia\n",
+            "p10001843/s44042658/44042658: Avg HR=53.10 BPM, RMSSD=333.27 ms, brachycardia\n",
+            "p10001843/s44881309/44881309: Avg HR=53.68 BPM, RMSSD=447.96 ms, brachycardia\n",
+            "p10001843/s45896667/45896667: Avg HR=55.12 BPM, RMSSD=7.71 ms, brachycardia\n",
+            "p10001843/s47843381/47843381: Avg HR=108.62 BPM, RMSSD=280.18 ms, tachycardia\n",
+            "p10001860/s45808859/45808859: Avg HR=56.43 BPM, RMSSD=261.21 ms, brachycardia\n",
+            "p10001877/s40056908/40056908: Avg HR=69.88 BPM, RMSSD=213.97 ms, sinus\n",
+            "p10001877/s41316269/41316269: Avg HR=77.19 BPM, RMSSD=161.18 ms, sinus\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "rec_path = '/files/p1000/p10000635/s40067704/40067704'\n",
+        "recordid = \"40067704\"\n",
+        "rd_record = wfdb.rdrecord(recordid, pn_dir= f'mimic-iv-ecg/1.0{rec_path}')\n",
+        "wfdb.plot_wfdb(record = rd_record, figsize=(24, 18), title =f'Study {recordid} example', ecg_grids='all')\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 959
+        },
+        "id": "8acPVHai3kwS",
+        "outputId": "b3ed2404-2bad-4348-feaf-171ee95b8cea"
+      },
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "wfdb.plot"
+      ],
+      "metadata": {
+        "id": "t4dYg3oz5d9P",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "collapsed": true,
+        "outputId": "dd99b398-753e-4446-b447-5bf765eb7b56"
+      },
+      "execution_count": 11,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<module 'wfdb.plot' from '/usr/local/lib/python3.12/dist-packages/wfdb/plot/__init__.py'>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 11
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(f\"tachycardia count: {tachycardia_count}%\")\n",
+        "print(f\"brachycardia count: {brachycardia_count}%\")\n",
+        "print(f\"sinus count: {sinus_count}%\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Lvi-Amdgw796",
+        "outputId": "cf8ed189-0056-4bc5-bf0e-bb2113411439",
+        "collapsed": true
+      },
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "tachycardia count: 10%\n",
+            "brachycardia count: 13%\n",
+            "sinus count: 77%\n"
+          ]
+        }
+      ]
+    },
+    
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/mimic-iv-ecg/notebooks/README.md b/mimic-iv-ecg/notebooks/README.md
new file mode 100644
index 00000000..98670fe9
--- /dev/null
+++ b/mimic-iv-ecg/notebooks/README.md
@@ -0,0 +1,12 @@
+
+# ECG Signal Processing with MIMIC-IV
+
+This project demonstrates how to process and analyze electrocardiogram (ECG) recordings from the MIMIC-IV ECG database using Python.
+The notebook loads a 12-lead ECG record with the WFDB library, preprocesses the signal using NeuroKit2, detects R-peaks, and extracts cleaned ECG waveforms for further analysis. The processed signals can be used as the foundation for heart rate and heart rate variability (HRV) analysis.
+
+## Features
+
+- Load ECG recordings directly from the MIMIC-IV ECG database
+- Process raw ECG signals using NeuroKit2
+- Detect R-peaks and cardiac waveform features
+- Prepare data for HR, HRV, and rhythm classification