diff --git a/docs/src/tutorials/tutorial_scipy2024_part1.ipynb b/docs/src/tutorials/tutorial_scipy2024_part1.ipynb
new file mode 100644
index 000000000..c8f0df1e6
--- /dev/null
+++ b/docs/src/tutorials/tutorial_scipy2024_part1.ipynb
@@ -0,0 +1,61 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4c11a823-27a3-43a5-8b37-a0284a4a1cb5",
+   "metadata": {},
+   "source": [
+    "# Part 1: Introduction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3cbdb898-0bc2-4080-b441-3bb35e477a08",
+   "metadata": {},
+   "source": [
+    "## Preparation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "8cf311cf-99e6-4be3-a192-40ea2524d5be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install temporian pandas numpy \"matplotlib<3.9.0\" ydf seaborn matplotlib statsmodels statsforecast bokeh keras prophet sktime pmdarima hierarchicalforecast -q -U"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e39db004-353d-4db7-aefd-47df79aae01c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Download datasets"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/src/tutorials/tutorial_scipy2024_part2.ipynb b/docs/src/tutorials/tutorial_scipy2024_part2.ipynb
new file mode 100644
index 000000000..9407fb99e
--- /dev/null
+++ b/docs/src/tutorials/tutorial_scipy2024_part2.ipynb
@@ -0,0 +1,1023 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "652da545-82e9-40c1-a38e-56e3d04ddb3e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-11 09:04:27.749357: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2024-06-11 09:04:28.418260: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import temporian as tp\n",
+    "import ydf\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "import statsmodels\n",
+    "import numpy as np\n",
+    "import os\n",
+    "import keras\n",
+    "from datetime import datetime, timedelta\n",
+    "import statsmodels.api as sm\n",
+    "import urllib\n",
+    "import zipfile\n",
+    "import prophet"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "431ffe1a-c87f-43ca-b153-991a78404c96",
+   "metadata": {},
+   "source": [
+    "# Part #2: Statistical Forecasting\n",
+    "\n",
+    "TODO\n",
+    "- Intro stat forecating\n",
+    "- What we will do\n",
+    "- AirTrafic dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6e49d015-55f1-489e-86d6-df397ab1e619",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Month</th>\n",
+       "      <th>#Passengers</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1949-01-01</td>\n",
+       "      <td>112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1949-02-01</td>\n",
+       "      <td>118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1949-03-01</td>\n",
+       "      <td>132</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1949-04-01</td>\n",
+       "      <td>129</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1949-05-01</td>\n",
+       "      <td>121</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>139</th>\n",
+       "      <td>1960-08-01</td>\n",
+       "      <td>606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>140</th>\n",
+       "      <td>1960-09-01</td>\n",
+       "      <td>508</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>141</th>\n",
+       "      <td>1960-10-01</td>\n",
+       "      <td>461</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>142</th>\n",
+       "      <td>1960-11-01</td>\n",
+       "      <td>390</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>143</th>\n",
+       "      <td>1960-12-01</td>\n",
+       "      <td>432</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>144 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Month  #Passengers\n",
+       "0   1949-01-01          112\n",
+       "1   1949-02-01          118\n",
+       "2   1949-03-01          132\n",
+       "3   1949-04-01          129\n",
+       "4   1949-05-01          121\n",
+       "..         ...          ...\n",
+       "139 1960-08-01          606\n",
+       "140 1960-09-01          508\n",
+       "141 1960-10-01          461\n",
+       "142 1960-11-01          390\n",
+       "143 1960-12-01          432\n",
+       "\n",
+       "[144 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# TODO => DL all datasets in one place\n",
+    "\n",
+    "raw_ds = pd.read_csv(\"datasets/air_passengers.csv\", parse_dates=[\"Month\"])\n",
+    "raw_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a8e3f8ad-6f2d-4eed-93a9-28e19c5305fa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.lineplot(x=\"Month\", y=\"#Passengers\", data=raw_ds)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "93859bb9-45b7-4fa7-8c6c-88dab4f36257",
+   "metadata": {},
+   "source": [
+    "TODO:\n",
+    "- Plotting function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23f595f8-a2ea-40a4-86e4-a90873d194c6",
+   "metadata": {},
+   "source": [
+    "Intro ARIMA\n",
+    "\n",
+    "Regressive linear model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cff72ef8-245e-4ba9-98ef-43c217539687",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n",
+      "  warn('Non-stationary starting autoregressive parameters'\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_test_steps = 28\n",
+    "\n",
+    "model = sm.tsa.arima.ARIMA(\n",
+    "    endog=raw_ds[\"#Passengers\"],\n",
+    "    order=(10, 0, 0),\n",
+    ")\n",
+    "model_fit = model.fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "6e10ae7a-9717-4f3a-96e6-201ca81b14c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "const     280.305099\n",
+       "ar.L1       1.146703\n",
+       "ar.L2      -0.460108\n",
+       "ar.L3       0.178722\n",
+       "ar.L4      -0.304246\n",
+       "ar.L5       0.377636\n",
+       "ar.L6      -0.216369\n",
+       "ar.L7       0.226179\n",
+       "ar.L8      -0.402437\n",
+       "ar.L9       0.269720\n",
+       "ar.L10      0.180383\n",
+       "sigma2    629.416809\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_fit.params"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "559ee216-f37b-4c76-8e04-5964562a28a5",
+   "metadata": {},
+   "source": [
+    "Q: What does those parameter tell us? Risk in interpretting those parameters directly?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9337728-8686-4609-bef7-adef28cc5a54",
+   "metadata": {},
+   "source": [
+    "- Train / test split talk + evaluation function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "b63a0eff-d708-4f24-99c9-55b7e6b2823b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "forecast = model_fit.forecast(steps=num_test_steps)\n",
+    "plt.plot(raw_ds[\"Month\"], raw_ds[\"#Passengers\"], label=\"Original Data\")\n",
+    "plt.plot(raw_ds[\"Month\"][-num_test_steps:], forecast, label=\"Forecast\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d81190db-2699-415e-afd0-d2e291ea00dc",
+   "metadata": {},
+   "source": [
+    "Talk increase in model cimplexity?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9deb503d-1b73-4b67-ba9d-83eab5ae37c8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model = sm.tsa.arima.ARIMA(\n",
+    "    endog=raw_ds[\"#Passengers\"][:-num_test_steps],\n",
+    "    order=(10, 2, 1),\n",
+    "    enforce_stationarity=False,\n",
+    ")\n",
+    "model_fit = model.fit()\n",
+    "forecast = model_fit.forecast(steps=num_test_steps)\n",
+    "\n",
+    "plt.plot(raw_ds[\"Month\"],raw_ds[\"#Passengers\"], label=\"Observations\")\n",
+    "plt.plot(raw_ds[\"Month\"][-num_test_steps:],forecast, label=\"Forecast\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "16648773-3e11-4c87-b91e-4daf82ec4141",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mean_absolute_error: 34.82438203045104\n"
+     ]
+    }
+   ],
+   "source": [
+    "residual = raw_ds[\"#Passengers\"][-num_test_steps:] - forecast\n",
+    "mean_absolute_error = np.mean(np.abs(residual))\n",
+    "print(\"mean_absolute_error:\", mean_absolute_error)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "d8552b9e-4982-41cb-9aaa-2b7701dfbac7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Exercice: Improve params of arima model."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de74b238-e811-4564-bce8-2a7593b66269",
+   "metadata": {},
+   "source": [
+    "Discussion:\n",
+    "- When are there too much complexity / regulzatiation / criteria"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17091952-f966-4fbf-8764-b51f9746f005",
+   "metadata": {},
+   "source": [
+    "- Looking at the data\n",
+    "- Intro ACF"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c17ccd73-5a4f-4c75-a471-503a43645737",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f29fe24e090>]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(sm.tsa.acf(raw_ds[\"#Passengers\"]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ee880970-ac06-4b46-b292-9ab72fd187a3",
+   "metadata": {},
+   "source": [
+    "Q:\n",
+    "- What can you tell?\n",
+    "- What does this peak at 0 and 12 tell us?\n",
+    "- => Last value mattern most\n",
+    "- => 1year ciclicity\n",
+    "\n",
+    "Intro STL"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6fb5cd44-9cb3-4578-ac4f-5a656db13b7e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model = sm.tsa.STL(raw_ds[\"#Passengers\"], period=12)\n",
+    "result = model.fit()\n",
+    "result.plot()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "37483919-5d52-4bd2-9d19-289b9a9f3ca1",
+   "metadata": {},
+   "source": [
+    "Intro modeling with STL with ETS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "05be9abb-2eba-4923-8b7b-1200978151de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "num_test_steps = 28\n",
+    "\n",
+    "model = sm.tsa.ETSModel(\n",
+    "    endog=raw_ds[\"#Passengers\"][:-num_test_steps],\n",
+    "    error=\"mul\",\n",
+    "    trend=\"mul\",\n",
+    "    seasonal=\"add\",\n",
+    "    seasonal_periods=12,\n",
+    ")\n",
+    "model_fit = model.fit(disp=False)\n",
+    "forecast = model_fit.forecast(steps=num_test_steps)\n",
+    "\n",
+    "plt.plot(raw_ds[\"Month\"],raw_ds[\"#Passengers\"], label=\"Observations\")\n",
+    "plt.plot(raw_ds[\"Month\"][-num_test_steps:],forecast, label=\"Forecast\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "7fb05a06-f28b-4414-810a-c9cd9f270760",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mean_absolute_error: 10.821295083651334\n"
+     ]
+    }
+   ],
+   "source": [
+    "residual = raw_ds[\"#Passengers\"][-num_test_steps:] - forecast\n",
+    "mean_absolute_error = np.mean(np.abs(residual))\n",
+    "print(\"mean_absolute_error:\", mean_absolute_error)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e02abe9-cc63-4d0e-bd56-53e1a2d4b36d",
+   "metadata": {},
+   "source": [
+    "Manual is good to understand. Automated / integrated tools\n",
+    "- AutoARIMA\n",
+    "- SKTime\n",
+    "- Profet\n",
+    "- VertexAI forecast"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f29012d7-d3f1-4324-bd65-502330af9930",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
+      "  warn('Non-invertible starting MA parameters found.'\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n",
+      "  warn('Non-stationary starting autoregressive parameters'\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
+      "  warn('Non-invertible starting MA parameters found.'\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
+      "  warnings.warn(\"Maximum Likelihood optimization failed to \"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# DOES NOT WORK: Ask or Remove?\n",
+    "from sktime.forecasting.arima import AutoARIMA\n",
+    "\n",
+    "model = AutoARIMA()\n",
+    "model.fit(raw_ds[\"#Passengers\"][:-num_test_steps])\n",
+    "forecast = model.predict(range(num_test_steps))\n",
+    "\n",
+    "plt.plot(raw_ds[\"Month\"],raw_ds[\"#Passengers\"], label=\"Original Data\")\n",
+    "plt.plot(raw_ds[\"Month\"][-num_test_steps:],forecast, label=\"Forecast\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "895dd9c2-23b1-456e-8174-525b10789144",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "09:04:32 - cmdstanpy - INFO - Chain [1] start processing\n",
+      "09:04:32 - cmdstanpy - INFO - Chain [1] done processing\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/prophet/forecaster.py:1854: FutureWarning: 'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
+      "  dates = pd.date_range(\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# DOES NOT WORK: Ask or Remove?\n",
+    "prophet_ds = raw_ds.rename(columns={\"Month\":\"ds\", \"#Passengers\":\"y\"})\n",
+    "\n",
+    "model = prophet.Prophet()\n",
+    "model.fit(prophet_ds[:-num_test_steps])\n",
+    "forecast = model.predict(model.make_future_dataframe(periods=num_test_steps, freq=\"ME\"))\n",
+    "\n",
+    "plt.plot(raw_ds[\"Month\"],raw_ds[\"#Passengers\"], label=\"Observations\")\n",
+    "plt.plot(raw_ds[\"Month\"][-num_test_steps:],forecast[\"yhat\"][-num_test_steps:], label=\"Forecast\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1714a610-bff9-4081-9edc-35c321b6dede",
+   "metadata": {},
+   "source": [
+    "Intro and importance of HTS\n",
+    "Citation ?\n",
+    "\n",
+    "Intro new dataset => australia tourism"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "092616a6-5d0f-4a38-8ec4-b45b93e18f17",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>Trips</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>State</th>\n",
+       "      <th>Quarter</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">ACT</th>\n",
+       "      <th>1</th>\n",
+       "      <td>551.001921</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>416.025623</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>436.029011</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>449.798445</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>378.572817</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">Western Australia</th>\n",
+       "      <th>72</th>\n",
+       "      <td>2382.091755</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>73</th>\n",
+       "      <td>2797.404767</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>74</th>\n",
+       "      <td>2469.394281</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75</th>\n",
+       "      <td>2317.044544</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>2656.330701</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>532 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                 Trips\n",
+       "State             Quarter             \n",
+       "ACT               1         551.001921\n",
+       "                  2         416.025623\n",
+       "                  3         436.029011\n",
+       "                  4         449.798445\n",
+       "                  5         378.572817\n",
+       "...                                ...\n",
+       "Western Australia 72       2382.091755\n",
+       "                  73       2797.404767\n",
+       "                  74       2469.394281\n",
+       "                  75       2317.044544\n",
+       "                  76       2656.330701\n",
+       "\n",
+       "[532 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_ds = pd.read_csv(\"datasets/australian_tourism.csv\", parse_dates=[\"Quarter\"])\n",
+    "#raw_ds = raw_ds[raw_ds[\"State\"] == \"South Australia\"]\n",
+    "#raw_ds = raw_ds[raw_ds[\"Purpose\"] == \"Visiting\"]\n",
+    "#del raw_ds[\"State\"]\n",
+    "del raw_ds[\"Index\"]\n",
+    "del raw_ds[\"Purpose\"]\n",
+    "del raw_ds[\"Region\"]\n",
+    "\n",
+    "def quarter_idx(x):\n",
+    "    \"\"\"Convert a date into a number of quarter since 1998.\n",
+    "    Used to solved some issue between pandas and sklearn:\n",
+    "    https://github.com/sktime/sktime/issues/6499\n",
+    "    \"\"\"\n",
+    "    dti = pd.DatetimeIndex(x)\n",
+    "    return dti.quarter + (dti.year - 1998) * 4\n",
+    "raw_ds[\"Quarter\"] = quarter_idx(raw_ds[\"Quarter\"])\n",
+    "\n",
+    "#raw_ds = raw_ds.set_index([\"State\", \"Quarter\"]).sort_index()\n",
+    "raw_ds = raw_ds.groupby([\"State\", \"Quarter\"]).sum()\n",
+    "raw_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "40199657-32ab-482d-a634-88001826d305",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:84: RuntimeWarning: overflow encountered in matmul\n",
+      "  return err.T @ err\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:84: RuntimeWarning: overflow encountered in matmul\n",
+      "  return err.T @ err\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:84: RuntimeWarning: overflow encountered in matmul\n",
+      "  return err.T @ err\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:918: ConvergenceWarning: Optimization failed to converge. Check mle_retvals.\n",
+      "  warnings.warn(\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:84: RuntimeWarning: overflow encountered in matmul\n",
+      "  return err.T @ err\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:84: RuntimeWarning: overflow encountered in matmul\n",
+      "  return err.T @ err\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/statsmodels/tsa/holtwinters/model.py:918: ConvergenceWarning: Optimization failed to converge. Check mle_retvals.\n",
+      "  warnings.warn(\n",
+      "/usr/local/google/home/gbm/my_venv/lib/python3.11/site-packages/sktime/transformations/hierarchical/reconcile.py:186: UserWarning: No elements of the index of X named '__total' found. Adding aggregate levels using the default Aggregator transformer before reconciliation.\n",
+      "  warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>Trips</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>State</th>\n",
+       "      <th>Quarter</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">ACT</th>\n",
+       "      <th>76</th>\n",
+       "      <td>573.973102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>77</th>\n",
+       "      <td>605.959189</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>78</th>\n",
+       "      <td>616.267520</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>79</th>\n",
+       "      <td>638.615550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>627.324314</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th rowspan=\"5\" valign=\"top\">__total</th>\n",
+       "      <th>87</th>\n",
+       "      <td>28815.134732</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>88</th>\n",
+       "      <td>30425.085016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>89</th>\n",
+       "      <td>33429.118820</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90</th>\n",
+       "      <td>30862.652104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>30259.751012</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>128 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        Trips\n",
+       "State   Quarter              \n",
+       "ACT     76         573.973102\n",
+       "        77         605.959189\n",
+       "        78         616.267520\n",
+       "        79         638.615550\n",
+       "        80         627.324314\n",
+       "...                       ...\n",
+       "__total 87       28815.134732\n",
+       "        88       30425.085016\n",
+       "        89       33429.118820\n",
+       "        90       30862.652104\n",
+       "        91       30259.751012\n",
+       "\n",
+       "[128 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sktime.transformations.hierarchical.aggregate import Aggregator\n",
+    "from sktime.transformations.hierarchical.reconcile import Reconciler\n",
+    "from sktime.forecasting.arima import ARIMA\n",
+    "from sktime.forecasting.exp_smoothing import ExponentialSmoothing\n",
+    "# import warnings\n",
+    "# warnings.filterwarnings(\"ignore\")\n",
+    "\n",
+    "# model = Aggregator() * ARIMA(\n",
+    "#     order=(5, 1, 1),\n",
+    "#     seasonal_order=(5,1,1,4),\n",
+    "#     suppress_warnings=True,\n",
+    "# ) * Reconciler()\n",
+    "\n",
+    "model = Aggregator() * ExponentialSmoothing(trend=\"mul\", seasonal=\"mul\",sp=4) * Reconciler()\n",
+    "model.fit(raw_ds)\n",
+    "forecast = model.predict(range(4 * 4))\n",
+    "forecast"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "7600dac2-c209-446b-a93a-28b9c9917ac1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Feature \"State\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"State\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1024x1200 with 8 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tp.plot([\n",
+    "    tp.from_pandas(raw_ds.reset_index(),\n",
+    "               timestamps=\"Quarter\",\n",
+    "               indexes=[\"State\"]).rename(\"observations\"),\n",
+    "    tp.from_pandas(forecast.reset_index(),\n",
+    "               timestamps=\"Quarter\",\n",
+    "               indexes=[\"State\"]).rename(\"forecasting\"),\n",
+    "], merge=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "818cea0c-27a5-4330-a977-7bff754ec54f",
+   "metadata": {},
+   "source": [
+    "Q: Add \"region\" in the hts"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4453393f-3d29-41be-ad7b-ee56f84174f5",
+   "metadata": {},
+   "source": [
+    "List of all stat libraries"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ce91b781-9cc1-409a-ae48-9455d35372c3",
+   "metadata": {},
+   "source": [
+    "What we learned so far"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/src/tutorials/tutorial_scipy2024_part3.ipynb b/docs/src/tutorials/tutorial_scipy2024_part3.ipynb
new file mode 100644
index 000000000..9e124aa2c
--- /dev/null
+++ b/docs/src/tutorials/tutorial_scipy2024_part3.ipynb
@@ -0,0 +1,4963 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "e3dc5ea9-a780-4642-b511-5c2d02fc2fe0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import temporian as tp\n",
+    "import matplotlib.pyplot as plt\n",
+    "from datetime import datetime, timezone, timedelta\n",
+    "import ydf\n",
+    "\n",
+    "pd.options.mode.chained_assignment = None\n",
+    "tp.config.display_max_indexes = 3\n",
+    "tp.config.display_max_events = 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9fde90f1-23de-4637-a96f-212a7de042b4",
+   "metadata": {},
+   "source": [
+    "## Part 3: Decision Forests Forecasting\n",
+    "\n",
+    "In the previous part, we used statistical forecasting methods to predict the future values of a time-series given its past values. Statistical forecasting methods are sample-efficient, meaning they don't need a lot of data to get results. However, if you have a lot of data, their don't always benefit from it. Instead, when lot of data is available, more powerful machine learning methods can lean more complex patterns and make better forecasts.\n",
+    "\n",
+    "In this part, we replace statistical forecasting methods with decision forests (DF) models. DFs are easy and fast to train, making they suitable for prototyping and learning about methods. They also show good results and provide partial interpretable, so they are worth knowing.\n",
+    "\n",
+    "In the previous parts, the setup was relatively simple. However, in many real-world applications, the setup is more complex. For instance:\n",
+    "\n",
+    "- Multiple variables or interests may be involved.\n",
+    "- The data is not sampled uniformly. Different variables are sampled differently.\n",
+    "- Not all values are numerical; e.g. some may be categorical, free text, or images.\n",
+    "- Complex relationships and hierarchical structures may exist between different types of entities.\n",
+    "- Exogenous variables (variables of indirect interest known in advance, such as holidays) may be present.\n",
+    "- Endogenous variables (variables of indirect interest not known in advance, such as oil prices) may be present.\n",
+    "To illustrate this complexity, we will use the Makridakis Forecasting Competition M5 dataset.\n",
+    "- Features require cleaning, preprocessing and data-augmentation before being consumed by a model.\n",
+    "\n",
+    "To illustrates all those points, we will use another dataset."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d8e9df46-1a99-41cd-88a7-2284d434360a",
+   "metadata": {},
+   "source": [
+    "## The data: The M5 Competition\n",
+    "\n",
+    "The [M5 Competition](https://www.kaggle.com/competitions/m5-forecasting-accuracy/overview) is the 2020 instance of the [Makridakis Forecasting Competitions](https://en.wikipedia.org/wiki/Makridakis_Competitions). The objective of this competition is to forecast the next 28 days of sales of 3k individual items in 10 different Walmart stores.\n",
+    "Walmart's data has a strong hierarchical structure, since each item belongs to a certain category and department, and each store to a certain state.\n",
+    "This means that, besides the 30k individual low-level time series corresponding to the daily sales of a specific item in a specific store (which we'll be referring to as an \"item-store\" or \"level 12\" time series), the data can be aggregated in multiple ways to generate a total of 42,840 time series to be forecasted, as shown in the images below.\n",
+    "\n",
+    "In this notebook, we will stick to only predicting the sales of item-store series, though the data's hierarchical structure will come in handy in the feature engineering stage.\n",
+    "\n",
+    "Details such as the [competition's guide](https://github.com/Mcompetitions/M5-methods/blob/master/M5-Competitors-Guide.pdf) and [Makridakis' analysis of the winning entries](https://www.researchgate.net/publication/344487258_The_M5_Accuracy_competition_Results_findings_and_conclusions) are available online."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b78467b9-e010-414c-8a47-3ba7c37307a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "total 430M\n",
+      "-rw-r----- 1 gbm primarygroup 102K May 28 16:01 calendar.csv\n",
+      "-rw-r----- 1 gbm primarygroup 117M May 28 16:01 sales_train_evaluation.csv\n",
+      "-rw-r----- 1 gbm primarygroup 115M May 28 16:01 sales_train_validation.csv\n",
+      "-rw-r----- 1 gbm primarygroup 5.0M May 28 16:01 sample_submission.csv\n",
+      "-rw-r----- 1 gbm primarygroup 194M May 28 16:01 sell_prices.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls -lh datasets/m5"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "399945f7-ddb7-442a-ac75-4f3715af6ed0",
+   "metadata": {},
+   "source": [
+    "The dataset is composed of 5 csv files:\n",
+    "\n",
+    "- `sales_train_evaluation`: The history of item sales.\n",
+    "- `calendar.csv`: Dates and calendar events related to the sales.\n",
+    "- `sell_prices.csv`: The history of the item prices. **Not used in this tutorial.**\n",
+    "- `sales_train_validation`: Another set of sales. **Not used in this tutorial.**\n",
+    "- `sample_submission`: An example of submission for the competition. **Not used in this tutorial.**\n",
+    "\n",
+    "Let's load and take a look at the historical sales in  `sales_train_evaluation.csv`. Each row contains the sales of a item+store pair (i.e. for a given item in a given store). Sales are aggregated per day. Each day, indexed between 1 and 1914 (5+ years), is stored in a different column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "164ad5ff-e916-4bca-b185-a1941c13329f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "First 5 rows\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>item_id</th>\n",
+       "      <th>dept_id</th>\n",
+       "      <th>cat_id</th>\n",
+       "      <th>store_id</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>d_1</th>\n",
+       "      <th>d_2</th>\n",
+       "      <th>d_3</th>\n",
+       "      <th>d_4</th>\n",
+       "      <th>...</th>\n",
+       "      <th>d_1932</th>\n",
+       "      <th>d_1933</th>\n",
+       "      <th>d_1934</th>\n",
+       "      <th>d_1935</th>\n",
+       "      <th>d_1936</th>\n",
+       "      <th>d_1937</th>\n",
+       "      <th>d_1938</th>\n",
+       "      <th>d_1939</th>\n",
+       "      <th>d_1940</th>\n",
+       "      <th>d_1941</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>HOBBIES_1_001_CA_1_evaluation</td>\n",
+       "      <td>HOBBIES_1_001</td>\n",
+       "      <td>HOBBIES_1</td>\n",
+       "      <td>HOBBIES</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>HOBBIES_1_002_CA_1_evaluation</td>\n",
+       "      <td>HOBBIES_1_002</td>\n",
+       "      <td>HOBBIES_1</td>\n",
+       "      <td>HOBBIES</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>HOBBIES_1_003_CA_1_evaluation</td>\n",
+       "      <td>HOBBIES_1_003</td>\n",
+       "      <td>HOBBIES_1</td>\n",
+       "      <td>HOBBIES</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>HOBBIES_1_004_CA_1_evaluation</td>\n",
+       "      <td>HOBBIES_1_004</td>\n",
+       "      <td>HOBBIES_1</td>\n",
+       "      <td>HOBBIES</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>HOBBIES_1_005_CA_1_evaluation</td>\n",
+       "      <td>HOBBIES_1_005</td>\n",
+       "      <td>HOBBIES_1</td>\n",
+       "      <td>HOBBIES</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 1947 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              id        item_id    dept_id   cat_id store_id  \\\n",
+       "0  HOBBIES_1_001_CA_1_evaluation  HOBBIES_1_001  HOBBIES_1  HOBBIES     CA_1   \n",
+       "1  HOBBIES_1_002_CA_1_evaluation  HOBBIES_1_002  HOBBIES_1  HOBBIES     CA_1   \n",
+       "2  HOBBIES_1_003_CA_1_evaluation  HOBBIES_1_003  HOBBIES_1  HOBBIES     CA_1   \n",
+       "3  HOBBIES_1_004_CA_1_evaluation  HOBBIES_1_004  HOBBIES_1  HOBBIES     CA_1   \n",
+       "4  HOBBIES_1_005_CA_1_evaluation  HOBBIES_1_005  HOBBIES_1  HOBBIES     CA_1   \n",
+       "\n",
+       "  state_id  d_1  d_2  d_3  d_4  ...  d_1932  d_1933  d_1934  d_1935  d_1936  \\\n",
+       "0       CA    0    0    0    0  ...       2       4       0       0       0   \n",
+       "1       CA    0    0    0    0  ...       0       1       2       1       1   \n",
+       "2       CA    0    0    0    0  ...       1       0       2       0       0   \n",
+       "3       CA    0    0    0    0  ...       1       1       0       4       0   \n",
+       "4       CA    0    0    0    0  ...       0       0       0       2       1   \n",
+       "\n",
+       "   d_1937  d_1938  d_1939  d_1940  d_1941  \n",
+       "0       0       3       3       0       1  \n",
+       "1       0       0       0       0       0  \n",
+       "2       0       2       3       0       1  \n",
+       "3       1       3       0       2       6  \n",
+       "4       0       0       2       1       0  \n",
+       "\n",
+       "[5 rows x 1947 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_sales = pd.read_csv(\"datasets/m5/sales_train_evaluation.csv\")\n",
+    "print(\"First 5 rows\")\n",
+    "raw_sales.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "67ca924b-7b0f-4961-b444-ec79a7d4f534",
+   "metadata": {},
+   "source": [
+    "Let's look at the sales of the first rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "398af600-d773-4142-9146-1e1340f29f12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#@title\n",
+    "num_plots = 3\n",
+    "plt.figure(figsize=(12,2 * num_plots))\n",
+    "d_cols = list(raw_sales.filter(regex=\"d_\"))\n",
+    "\n",
+    "for row_idx in range(num_plots):\n",
+    "  sales_ts = raw_sales.iloc[row_idx][d_cols].to_numpy()\n",
+    "  plt.subplot(num_plots+1, 1, row_idx+1)\n",
+    "  plt.plot(sales_ts)\n",
+    "  plt.ylabel(f\"row #{row_idx}\\n sales units\")\n",
+    "\n",
+    "plt.suptitle(\"Sales over time\")\n",
+    "plt.xlabel(\"day (index)\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecddbc7c-4779-4517-afa9-5b8faecd8349",
+   "metadata": {},
+   "source": [
+    "### Question\n",
+    "\n",
+    "1. What insights or conclusions do you draw from the plots above?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "b4f1f236-5a62-4e54-8af7-574008a218c5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#@title Solution\n",
+    "\n",
+    "# 1. Not all products started being sold at the same time. They usually start with 0 sales units.\n",
+    "# 2. Row #0, #1 and #3 show really different pattern. Row #0 and #2 look quite irregular. Row #1 shows some peaks every 365 days approx.\n",
+    "# 3. Row #2 show a period, which seems to be an out-of-stock period, between day 1250 and 1500.\n",
+    "# 4. Sales seem very sporadic for row #1, with several periods of 0 sales.\n",
+    "# 5. any others?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4ce14d06-6a50-4341-9089-1b9323fb6de6",
+   "metadata": {},
+   "source": [
+    "The sales are organized in two hierarchies: products/departments/category and store/state. We can predict the sales of each product in isolations, the forecasts will be better is information is allowed to \"flow\" though the hierarchy. For instance, some products in similar or different departments might have related sales (such as diapers and beer).\n",
+    "\n",
+    "In the previous part, we used hierarchical reconciliation to make hierarchy aware forecasts: Individual models were trained for each time-series (product in the M5 dataset) and their forecasting were normalized together. In this part, we will use a global model: We will train a single model with access to the hierarchy. The model is free to use or ignore the hierarchy.\n",
+    "\n",
+    "To make the execution of the tutorial faster and more interesting, we downsample the dataset. We focus on a subset of 8 food products with the largest sale counts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "13736656-e5df-4232-84f6-4432716115a2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of time series: 80\n"
+     ]
+    }
+   ],
+   "source": [
+    "if True: # Optional downsampling of the dataset.\n",
+    "    \n",
+    "    # The items with the most sales.\n",
+    "    selected_items_names = ['FOODS_3_090', 'FOODS_3_586', 'FOODS_3_252', 'FOODS_3_555',\n",
+    "                            'FOODS_3_587', 'FOODS_3_714', 'FOODS_3_694', 'FOODS_3_226',\n",
+    "                            #'FOODS_3_202', 'FOODS_3_120', 'FOODS_3_723', 'FOODS_3_635',\n",
+    "                            #'FOODS_3_808', 'FOODS_3_377', 'FOODS_3_541', 'FOODS_3_080',\n",
+    "                            #'FOODS_3_318', 'FOODS_2_360', 'FOODS_3_681', 'FOODS_3_234',\n",
+    "                           ]\n",
+    "    raw_sales = raw_sales[raw_sales[\"item_id\"].isin(selected_items_names)]\n",
+    "    print(\"Number of time series:\", len(raw_sales))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4c3b1e3-4fb7-42ba-967d-edb955d6090f",
+   "metadata": {},
+   "source": [
+    "Let's load calendar events. Those are known in advanced calendar events that might have impact on sales. For example, father's day of the NBA Finals might impact purchases.\n",
+    "\n",
+    "This table is complementary to other possibly impactful calendar data such as the day of the week or month of the year."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d10ccc91-4c54-42f6-b8de-6fe52479561f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>date</th>\n",
+       "      <th>wm_yr_wk</th>\n",
+       "      <th>weekday</th>\n",
+       "      <th>wday</th>\n",
+       "      <th>month</th>\n",
+       "      <th>year</th>\n",
+       "      <th>d</th>\n",
+       "      <th>event_name_1</th>\n",
+       "      <th>event_type_1</th>\n",
+       "      <th>event_name_2</th>\n",
+       "      <th>event_type_2</th>\n",
+       "      <th>snap_CA</th>\n",
+       "      <th>snap_TX</th>\n",
+       "      <th>snap_WI</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2011-01-29</td>\n",
+       "      <td>11101</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>d_1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2011-01-30</td>\n",
+       "      <td>11101</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>d_2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2011-01-31</td>\n",
+       "      <td>11101</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>d_3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2011-02-01</td>\n",
+       "      <td>11101</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>d_4</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2011-02-02</td>\n",
+       "      <td>11101</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2011</td>\n",
+       "      <td>d_5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1964</th>\n",
+       "      <td>2016-06-15</td>\n",
+       "      <td>11620</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>5</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>d_1965</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1965</th>\n",
+       "      <td>2016-06-16</td>\n",
+       "      <td>11620</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>6</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>d_1966</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1966</th>\n",
+       "      <td>2016-06-17</td>\n",
+       "      <td>11620</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>7</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>d_1967</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1967</th>\n",
+       "      <td>2016-06-18</td>\n",
+       "      <td>11621</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>d_1968</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1968</th>\n",
+       "      <td>2016-06-19</td>\n",
+       "      <td>11621</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>d_1969</td>\n",
+       "      <td>NBAFinalsEnd</td>\n",
+       "      <td>Sporting</td>\n",
+       "      <td>Father's day</td>\n",
+       "      <td>Cultural</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1969 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            date  wm_yr_wk    weekday  wday  month  year       d  \\\n",
+       "0     2011-01-29     11101   Saturday     1      1  2011     d_1   \n",
+       "1     2011-01-30     11101     Sunday     2      1  2011     d_2   \n",
+       "2     2011-01-31     11101     Monday     3      1  2011     d_3   \n",
+       "3     2011-02-01     11101    Tuesday     4      2  2011     d_4   \n",
+       "4     2011-02-02     11101  Wednesday     5      2  2011     d_5   \n",
+       "...          ...       ...        ...   ...    ...   ...     ...   \n",
+       "1964  2016-06-15     11620  Wednesday     5      6  2016  d_1965   \n",
+       "1965  2016-06-16     11620   Thursday     6      6  2016  d_1966   \n",
+       "1966  2016-06-17     11620     Friday     7      6  2016  d_1967   \n",
+       "1967  2016-06-18     11621   Saturday     1      6  2016  d_1968   \n",
+       "1968  2016-06-19     11621     Sunday     2      6  2016  d_1969   \n",
+       "\n",
+       "      event_name_1 event_type_1  event_name_2 event_type_2  snap_CA  snap_TX  \\\n",
+       "0              NaN          NaN           NaN          NaN        0        0   \n",
+       "1              NaN          NaN           NaN          NaN        0        0   \n",
+       "2              NaN          NaN           NaN          NaN        0        0   \n",
+       "3              NaN          NaN           NaN          NaN        1        1   \n",
+       "4              NaN          NaN           NaN          NaN        1        0   \n",
+       "...            ...          ...           ...          ...      ...      ...   \n",
+       "1964           NaN          NaN           NaN          NaN        0        1   \n",
+       "1965           NaN          NaN           NaN          NaN        0        0   \n",
+       "1966           NaN          NaN           NaN          NaN        0        0   \n",
+       "1967           NaN          NaN           NaN          NaN        0        0   \n",
+       "1968  NBAFinalsEnd     Sporting  Father's day     Cultural        0        0   \n",
+       "\n",
+       "      snap_WI  \n",
+       "0           0  \n",
+       "1           0  \n",
+       "2           0  \n",
+       "3           0  \n",
+       "4           1  \n",
+       "...       ...  \n",
+       "1964        1  \n",
+       "1965        0  \n",
+       "1966        0  \n",
+       "1967        0  \n",
+       "1968        0  \n",
+       "\n",
+       "[1969 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "raw_calendar = pd.read_csv(\"datasets/m5/calendar.csv\")\n",
+    "raw_calendar"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a56385b7-9dc3-4426-96ec-729c50a4077f",
+   "metadata": {},
+   "source": [
+    "## Normalize dataset\n",
+    "\n",
+    "The tables `sales_raw` and `calendar_raw` represents temporal data in a different way. For example, timestamps are stored by columns in `sales_raw` and by rows in `calendar_raw`. The two tables also use a different system to represent dates.\n",
+    "\n",
+    "To prepare, preprocess and augment the data, we use the Pandas and Temporian. Pandas allows to general options on tabular data (called \"dataframes\") while Temporian is specialized for temporal data processing.\n",
+    "Let's normalize all the the raw tables in the same format."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c7457739-9345-4388-9f5a-43134752ba7a",
+   "metadata": {},
+   "source": [
+    "### Normalize sales\n",
+    "\n",
+    "Each sales value is stored in a different column. Instead, we want for each value (which in Temporian we refer to as an event) to be in a different row.\n",
+    "\n",
+    "For example, the record:\n",
+    "\n",
+    "```\n",
+    "id,item_id,dept_id,d_1,d_2,d_3,...,d_n\n",
+    "```\n",
+    "\n",
+    "will be converted to the following records:\n",
+    "\n",
+    "```\n",
+    "id,item_id,dept_id,day,d_1\n",
+    "id,item_id,dept_id,day,d_2\n",
+    "...\n",
+    "id,item_id,dept_id,day,d_n\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a9362215-84fd-47ab-adcc-d946de991a3d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>item_id</th>\n",
+       "      <th>dept_id</th>\n",
+       "      <th>cat_id</th>\n",
+       "      <th>store_id</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>day</th>\n",
+       "      <th>sales</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>FOODS_3_090</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1</td>\n",
+       "      <td>107</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>FOODS_3_226</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1</td>\n",
+       "      <td>13</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>FOODS_3_252</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1</td>\n",
+       "      <td>19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>FOODS_3_555</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1</td>\n",
+       "      <td>23</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FOODS_3_586</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1</td>\n",
+       "      <td>42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155275</th>\n",
+       "      <td>FOODS_3_555</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>1941</td>\n",
+       "      <td>39</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155276</th>\n",
+       "      <td>FOODS_3_586</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>1941</td>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155277</th>\n",
+       "      <td>FOODS_3_587</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>1941</td>\n",
+       "      <td>24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155278</th>\n",
+       "      <td>FOODS_3_694</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>1941</td>\n",
+       "      <td>48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155279</th>\n",
+       "      <td>FOODS_3_714</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>1941</td>\n",
+       "      <td>26</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>155280 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            item_id  dept_id cat_id store_id state_id   day  sales\n",
+       "0       FOODS_3_090  FOODS_3  FOODS     CA_1       CA     1    107\n",
+       "1       FOODS_3_226  FOODS_3  FOODS     CA_1       CA     1     13\n",
+       "2       FOODS_3_252  FOODS_3  FOODS     CA_1       CA     1     19\n",
+       "3       FOODS_3_555  FOODS_3  FOODS     CA_1       CA     1     23\n",
+       "4       FOODS_3_586  FOODS_3  FOODS     CA_1       CA     1     42\n",
+       "...             ...      ...    ...      ...      ...   ...    ...\n",
+       "155275  FOODS_3_555  FOODS_3  FOODS     WI_3       WI  1941     39\n",
+       "155276  FOODS_3_586  FOODS_3  FOODS     WI_3       WI  1941     37\n",
+       "155277  FOODS_3_587  FOODS_3  FOODS     WI_3       WI  1941     24\n",
+       "155278  FOODS_3_694  FOODS_3  FOODS     WI_3       WI  1941     48\n",
+       "155279  FOODS_3_714  FOODS_3  FOODS     WI_3       WI  1941     26\n",
+       "\n",
+       "[155280 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sales = pd.melt(\n",
+    "    raw_sales,\n",
+    "    var_name=\"day\",\n",
+    "    value_name=\"sales\",\n",
+    "    id_vars=[\"id\", \"item_id\", \"dept_id\", \"cat_id\", \"store_id\", \"state_id\"],\n",
+    ")\n",
+    "sales[\"day\"] = sales[\"day\"].apply(lambda x: int(x[2:]))\n",
+    "del sales[\"id\"] # Remove id\n",
+    "sales"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "60fd49d9-47c9-4dd9-8375-3ea439d0efe9",
+   "metadata": {},
+   "source": [
+    "The timestamps are expressed in number of days since `29/1/2011`.\n",
+    "Let's convert them into python datetimes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "f6ff9889-4a67-4f4c-a0e7-7c77379b06b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>item_id</th>\n",
+       "      <th>dept_id</th>\n",
+       "      <th>cat_id</th>\n",
+       "      <th>store_id</th>\n",
+       "      <th>state_id</th>\n",
+       "      <th>sales</th>\n",
+       "      <th>timestamp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>FOODS_3_090</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>107</td>\n",
+       "      <td>2011-01-29 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>FOODS_3_226</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>13</td>\n",
+       "      <td>2011-01-29 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>FOODS_3_252</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>19</td>\n",
+       "      <td>2011-01-29 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>FOODS_3_555</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>23</td>\n",
+       "      <td>2011-01-29 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>FOODS_3_586</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>CA_1</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>42</td>\n",
+       "      <td>2011-01-29 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155275</th>\n",
+       "      <td>FOODS_3_555</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>39</td>\n",
+       "      <td>2016-05-22 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155276</th>\n",
+       "      <td>FOODS_3_586</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>37</td>\n",
+       "      <td>2016-05-22 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155277</th>\n",
+       "      <td>FOODS_3_587</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>24</td>\n",
+       "      <td>2016-05-22 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155278</th>\n",
+       "      <td>FOODS_3_694</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>48</td>\n",
+       "      <td>2016-05-22 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>155279</th>\n",
+       "      <td>FOODS_3_714</td>\n",
+       "      <td>FOODS_3</td>\n",
+       "      <td>FOODS</td>\n",
+       "      <td>WI_3</td>\n",
+       "      <td>WI</td>\n",
+       "      <td>26</td>\n",
+       "      <td>2016-05-22 00:00:00+00:00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>155280 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            item_id  dept_id cat_id store_id state_id  sales  \\\n",
+       "0       FOODS_3_090  FOODS_3  FOODS     CA_1       CA    107   \n",
+       "1       FOODS_3_226  FOODS_3  FOODS     CA_1       CA     13   \n",
+       "2       FOODS_3_252  FOODS_3  FOODS     CA_1       CA     19   \n",
+       "3       FOODS_3_555  FOODS_3  FOODS     CA_1       CA     23   \n",
+       "4       FOODS_3_586  FOODS_3  FOODS     CA_1       CA     42   \n",
+       "...             ...      ...    ...      ...      ...    ...   \n",
+       "155275  FOODS_3_555  FOODS_3  FOODS     WI_3       WI     39   \n",
+       "155276  FOODS_3_586  FOODS_3  FOODS     WI_3       WI     37   \n",
+       "155277  FOODS_3_587  FOODS_3  FOODS     WI_3       WI     24   \n",
+       "155278  FOODS_3_694  FOODS_3  FOODS     WI_3       WI     48   \n",
+       "155279  FOODS_3_714  FOODS_3  FOODS     WI_3       WI     26   \n",
+       "\n",
+       "                       timestamp  \n",
+       "0      2011-01-29 00:00:00+00:00  \n",
+       "1      2011-01-29 00:00:00+00:00  \n",
+       "2      2011-01-29 00:00:00+00:00  \n",
+       "3      2011-01-29 00:00:00+00:00  \n",
+       "4      2011-01-29 00:00:00+00:00  \n",
+       "...                          ...  \n",
+       "155275 2016-05-22 00:00:00+00:00  \n",
+       "155276 2016-05-22 00:00:00+00:00  \n",
+       "155277 2016-05-22 00:00:00+00:00  \n",
+       "155278 2016-05-22 00:00:00+00:00  \n",
+       "155279 2016-05-22 00:00:00+00:00  \n",
+       "\n",
+       "[155280 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "origin_date = datetime(2011, 1, 29, tzinfo=timezone.utc)\n",
+    "sales[\"timestamp\"] = sales[\"day\"].apply(\n",
+    "    lambda x: (origin_date + timedelta(days=x - 1))\n",
+    ")\n",
+    "del sales[\"day\"]\n",
+    "sales"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61c9383f-7398-4193-be1a-890ce6155319",
+   "metadata": {},
+   "source": [
+    "Let's now convert `sales` from a Pandas DataFrame to a Temporian EventSet."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "b95bea12-6c7e-499f-a58e-826bd661787c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Feature \"item_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"dept_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"cat_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"store_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"state_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "  <div style=\"display: table; margin-bottom:11px; padding:5px; font-size:small; line-height:120%; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">features</span>\n",
+       "        <span style=\"\"> [1]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">sales</span>\n",
+       "      <span style=\"color:#009988\"> (int64)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">indexes</span>\n",
+       "        <span style=\"\"> [5]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">item_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">dept_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">cat_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">store_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">state_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">events: </span>\n",
+       "      <span style=\"\">155280</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">index values: </span>\n",
+       "      <span style=\"\">80</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">memory usage: </span>\n",
+       "      <span style=\"\">2.5 MB</span>\n",
+       "    </div>\n",
+       "  </div>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_1</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 1941 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">sales</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-29 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">107</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-30 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">182</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-31 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">47</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-20 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">69</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">67</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">64</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_2</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 1941 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">sales</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-29 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">116</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-30 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">90</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-31 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">35</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-20 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">66</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">63</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">59</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 1941 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">sales</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-29 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">108</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-30 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">132</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-31 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">102</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-20 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">110</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">156</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">99</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_4</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 1941 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">sales</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-29 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">69</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-30 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">49</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-31 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">37</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-20 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">22</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">16</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">38</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <span style=\"\">… (76 more indexes not shown)</span>\n",
+       "</div>\n"
+      ],
+      "text/plain": [
+       "indexes: [('item_id', str_), ('dept_id', str_), ('cat_id', str_), ('store_id', str_), ('state_id', str_)]\n",
+       "features: [('sales', int64)]\n",
+       "events:\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_1' state_id=b'CA' (1941 events):\n",
+       "        timestamps: ['2011-01-29T00:00:00' '2011-01-30T00:00:00' '2011-01-31T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'sales': [107 182  47 ...  69  67  64]\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_2' state_id=b'CA' (1941 events):\n",
+       "        timestamps: ['2011-01-29T00:00:00' '2011-01-30T00:00:00' '2011-01-31T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'sales': [116  90  35 ...  66  63  59]\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_3' state_id=b'CA' (1941 events):\n",
+       "        timestamps: ['2011-01-29T00:00:00' '2011-01-30T00:00:00' '2011-01-31T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'sales': [108 132 102 ... 110 156  99]\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_4' state_id=b'CA' (1941 events):\n",
+       "        timestamps: ['2011-01-29T00:00:00' '2011-01-30T00:00:00' '2011-01-31T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'sales': [69 49 37 ... 22 16 38]\n",
+       "    ... (showing 4 of 80 indexes)\n",
+       "memory usage: 2.5 MB"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sales = tp.from_pandas(\n",
+    "    sales,\n",
+    "    indexes=[\"item_id\", \"dept_id\", \"cat_id\", \"store_id\", \"state_id\"],\n",
+    ")\n",
+    "sales"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dac1b689-bdaa-4078-a44e-498f98705494",
+   "metadata": {},
+   "source": [
+    "Let's plot the sales of the first two products."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "faddeb02-3c13-465f-b86e-3c7a82f85bd7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "'use strict';\n",
+       "(function(root) {\n",
+       "  function now() {\n",
+       "    return new Date();\n",
+       "  }\n",
+       "\n",
+       "  const force = true;\n",
+       "\n",
+       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
+       "    root._bokeh_onload_callbacks = [];\n",
+       "    root._bokeh_is_loading = undefined;\n",
+       "  }\n",
+       "\n",
+       "const JS_MIME_TYPE = 'application/javascript';\n",
+       "  const HTML_MIME_TYPE = 'text/html';\n",
+       "  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
+       "  const CLASS_NAME = 'output_bokeh rendered_html';\n",
+       "\n",
+       "  /**\n",
+       "   * Render data to the DOM node\n",
+       "   */\n",
+       "  function render(props, node) {\n",
+       "    const script = document.createElement(\"script\");\n",
+       "    node.appendChild(script);\n",
+       "  }\n",
+       "\n",
+       "  /**\n",
+       "   * Handle when an output is cleared or removed\n",
+       "   */\n",
+       "  function handleClearOutput(event, handle) {\n",
+       "    function drop(id) {\n",
+       "      const view = Bokeh.index.get_by_id(id)\n",
+       "      if (view != null) {\n",
+       "        view.model.document.clear()\n",
+       "        Bokeh.index.delete(view)\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    const cell = handle.cell;\n",
+       "\n",
+       "    const id = cell.output_area._bokeh_element_id;\n",
+       "    const server_id = cell.output_area._bokeh_server_id;\n",
+       "\n",
+       "    // Clean up Bokeh references\n",
+       "    if (id != null) {\n",
+       "      drop(id)\n",
+       "    }\n",
+       "\n",
+       "    if (server_id !== undefined) {\n",
+       "      // Clean up Bokeh references\n",
+       "      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
+       "      cell.notebook.kernel.execute(cmd_clean, {\n",
+       "        iopub: {\n",
+       "          output: function(msg) {\n",
+       "            const id = msg.content.text.trim()\n",
+       "            drop(id)\n",
+       "          }\n",
+       "        }\n",
+       "      });\n",
+       "      // Destroy server and session\n",
+       "      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
+       "      cell.notebook.kernel.execute(cmd_destroy);\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  /**\n",
+       "   * Handle when a new output is added\n",
+       "   */\n",
+       "  function handleAddOutput(event, handle) {\n",
+       "    const output_area = handle.output_area;\n",
+       "    const output = handle.output;\n",
+       "\n",
+       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
+       "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
+       "      return\n",
+       "    }\n",
+       "\n",
+       "    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
+       "\n",
+       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
+       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
+       "      // store reference to embed id on output_area\n",
+       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
+       "    }\n",
+       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
+       "      const bk_div = document.createElement(\"div\");\n",
+       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
+       "      const script_attrs = bk_div.children[0].attributes;\n",
+       "      for (let i = 0; i < script_attrs.length; i++) {\n",
+       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
+       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
+       "      }\n",
+       "      // store reference to server id on output_area\n",
+       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  function register_renderer(events, OutputArea) {\n",
+       "\n",
+       "    function append_mime(data, metadata, element) {\n",
+       "      // create a DOM node to render to\n",
+       "      const toinsert = this.create_output_subarea(\n",
+       "        metadata,\n",
+       "        CLASS_NAME,\n",
+       "        EXEC_MIME_TYPE\n",
+       "      );\n",
+       "      this.keyboard_manager.register_events(toinsert);\n",
+       "      // Render to node\n",
+       "      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
+       "      render(props, toinsert[toinsert.length - 1]);\n",
+       "      element.append(toinsert);\n",
+       "      return toinsert\n",
+       "    }\n",
+       "\n",
+       "    /* Handle when an output is cleared or removed */\n",
+       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
+       "    events.on('delete.Cell', handleClearOutput);\n",
+       "\n",
+       "    /* Handle when a new output is added */\n",
+       "    events.on('output_added.OutputArea', handleAddOutput);\n",
+       "\n",
+       "    /**\n",
+       "     * Register the mime type and append_mime function with output_area\n",
+       "     */\n",
+       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
+       "      /* Is output safe? */\n",
+       "      safe: true,\n",
+       "      /* Index of renderer in `output_area.display_order` */\n",
+       "      index: 0\n",
+       "    });\n",
+       "  }\n",
+       "\n",
+       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
+       "  if (root.Jupyter !== undefined) {\n",
+       "    const events = require('base/js/events');\n",
+       "    const OutputArea = require('notebook/js/outputarea').OutputArea;\n",
+       "\n",
+       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
+       "      register_renderer(events, OutputArea);\n",
+       "    }\n",
+       "  }\n",
+       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
+       "    root._bokeh_timeout = Date.now() + 5000;\n",
+       "    root._bokeh_failed_load = false;\n",
+       "  }\n",
+       "\n",
+       "  const NB_LOAD_WARNING = {'data': {'text/html':\n",
+       "     \"<div style='background-color: #fdd'>\\n\"+\n",
+       "     \"<p>\\n\"+\n",
+       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
+       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
+       "     \"</p>\\n\"+\n",
+       "     \"<ul>\\n\"+\n",
+       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
+       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
+       "     \"</ul>\\n\"+\n",
+       "     \"<code>\\n\"+\n",
+       "     \"from bokeh.resources import INLINE\\n\"+\n",
+       "     \"output_notebook(resources=INLINE)\\n\"+\n",
+       "     \"</code>\\n\"+\n",
+       "     \"</div>\"}};\n",
+       "\n",
+       "  function display_loaded(error = null) {\n",
+       "    const el = document.getElementById(null);\n",
+       "    if (el != null) {\n",
+       "      const html = (() => {\n",
+       "        if (typeof root.Bokeh === \"undefined\") {\n",
+       "          if (error == null) {\n",
+       "            return \"BokehJS is loading ...\";\n",
+       "          } else {\n",
+       "            return \"BokehJS failed to load.\";\n",
+       "          }\n",
+       "        } else {\n",
+       "          const prefix = `BokehJS ${root.Bokeh.version}`;\n",
+       "          if (error == null) {\n",
+       "            return `${prefix} successfully loaded.`;\n",
+       "          } else {\n",
+       "            return `${prefix} <b>encountered errors</b> while loading and may not function as expected.`;\n",
+       "          }\n",
+       "        }\n",
+       "      })();\n",
+       "      el.innerHTML = html;\n",
+       "\n",
+       "      if (error != null) {\n",
+       "        const wrapper = document.createElement(\"div\");\n",
+       "        wrapper.style.overflow = \"auto\";\n",
+       "        wrapper.style.height = \"5em\";\n",
+       "        wrapper.style.resize = \"vertical\";\n",
+       "        const content = document.createElement(\"div\");\n",
+       "        content.style.fontFamily = \"monospace\";\n",
+       "        content.style.whiteSpace = \"pre-wrap\";\n",
+       "        content.style.backgroundColor = \"rgb(255, 221, 221)\";\n",
+       "        content.textContent = error.stack ?? error.toString();\n",
+       "        wrapper.append(content);\n",
+       "        el.append(wrapper);\n",
+       "      }\n",
+       "    } else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(() => display_loaded(error), 100);\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  function run_callbacks() {\n",
+       "    try {\n",
+       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
+       "        if (callback != null)\n",
+       "          callback();\n",
+       "      });\n",
+       "    } finally {\n",
+       "      delete root._bokeh_onload_callbacks\n",
+       "    }\n",
+       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
+       "  }\n",
+       "\n",
+       "  function load_libs(css_urls, js_urls, callback) {\n",
+       "    if (css_urls == null) css_urls = [];\n",
+       "    if (js_urls == null) js_urls = [];\n",
+       "\n",
+       "    root._bokeh_onload_callbacks.push(callback);\n",
+       "    if (root._bokeh_is_loading > 0) {\n",
+       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
+       "      return null;\n",
+       "    }\n",
+       "    if (js_urls == null || js_urls.length === 0) {\n",
+       "      run_callbacks();\n",
+       "      return null;\n",
+       "    }\n",
+       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
+       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
+       "\n",
+       "    function on_load() {\n",
+       "      root._bokeh_is_loading--;\n",
+       "      if (root._bokeh_is_loading === 0) {\n",
+       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
+       "        run_callbacks()\n",
+       "      }\n",
+       "    }\n",
+       "\n",
+       "    function on_error(url) {\n",
+       "      console.error(\"failed to load \" + url);\n",
+       "    }\n",
+       "\n",
+       "    for (let i = 0; i < css_urls.length; i++) {\n",
+       "      const url = css_urls[i];\n",
+       "      const element = document.createElement(\"link\");\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error.bind(null, url);\n",
+       "      element.rel = \"stylesheet\";\n",
+       "      element.type = \"text/css\";\n",
+       "      element.href = url;\n",
+       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
+       "      document.body.appendChild(element);\n",
+       "    }\n",
+       "\n",
+       "    for (let i = 0; i < js_urls.length; i++) {\n",
+       "      const url = js_urls[i];\n",
+       "      const element = document.createElement('script');\n",
+       "      element.onload = on_load;\n",
+       "      element.onerror = on_error.bind(null, url);\n",
+       "      element.async = false;\n",
+       "      element.src = url;\n",
+       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
+       "      document.head.appendChild(element);\n",
+       "    }\n",
+       "  };\n",
+       "\n",
+       "  function inject_raw_css(css) {\n",
+       "    const element = document.createElement(\"style\");\n",
+       "    element.appendChild(document.createTextNode(css));\n",
+       "    document.body.appendChild(element);\n",
+       "  }\n",
+       "\n",
+       "  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.4.1.min.js\"];\n",
+       "  const css_urls = [];\n",
+       "\n",
+       "  const inline_js = [    function(Bokeh) {\n",
+       "      Bokeh.set_log_level(\"info\");\n",
+       "    },\n",
+       "function(Bokeh) {\n",
+       "    }\n",
+       "  ];\n",
+       "\n",
+       "  function run_inline_js() {\n",
+       "    if (root.Bokeh !== undefined || force === true) {\n",
+       "      try {\n",
+       "            for (let i = 0; i < inline_js.length; i++) {\n",
+       "      inline_js[i].call(root, root.Bokeh);\n",
+       "    }\n",
+       "\n",
+       "      } catch (error) {throw error;\n",
+       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
+       "      setTimeout(run_inline_js, 100);\n",
+       "    } else if (!root._bokeh_failed_load) {\n",
+       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
+       "      root._bokeh_failed_load = true;\n",
+       "    } else if (force !== true) {\n",
+       "      const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
+       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  if (root._bokeh_is_loading === 0) {\n",
+       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
+       "    run_inline_js();\n",
+       "  } else {\n",
+       "    load_libs(css_urls, js_urls, function() {\n",
+       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
+       "      run_inline_js();\n",
+       "    });\n",
+       "  }\n",
+       "}(window));"
+      ],
+      "application/vnd.bokehjs_load.v0+json": "'use strict';\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded(error = null) {\n    const el = document.getElementById(null);\n    if (el != null) {\n      const html = (() => {\n        if (typeof root.Bokeh === \"undefined\") {\n          if (error == null) {\n            return \"BokehJS is loading ...\";\n          } else {\n            return \"BokehJS failed to load.\";\n          }\n        } else {\n          const prefix = `BokehJS ${root.Bokeh.version}`;\n          if (error == null) {\n            return `${prefix} successfully loaded.`;\n          } else {\n            return `${prefix} <b>encountered errors</b> while loading and may not function as expected.`;\n          }\n        }\n      })();\n      el.innerHTML = html;\n\n      if (error != null) {\n        const wrapper = document.createElement(\"div\");\n        wrapper.style.overflow = \"auto\";\n        wrapper.style.height = \"5em\";\n        wrapper.style.resize = \"vertical\";\n        const content = document.createElement(\"div\");\n        content.style.fontFamily = \"monospace\";\n        content.style.whiteSpace = \"pre-wrap\";\n        content.style.backgroundColor = \"rgb(255, 221, 221)\";\n        content.textContent = error.stack ?? error.toString();\n        wrapper.append(content);\n        el.append(wrapper);\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(() => display_loaded(error), 100);\n    }\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.4.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.4.1.min.js\"];\n  const css_urls = [];\n\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {\n    }\n  ];\n\n  function run_inline_js() {\n    if (root.Bokeh !== undefined || force === true) {\n      try {\n            for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n\n      } catch (error) {throw error;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "  <div id=\"c506a044-6db3-4803-9b2b-d2c4d0ef4fc8\" data-root-id=\"p1240\" style=\"display: contents;\"></div>\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": [
+       "(function(root) {\n",
+       "  function embed_document(root) {\n",
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      -                  	                                                               	                                                 #                        &            $   $            +   !   .   #   '       /   H   B   #   :   )   "   1   ?             ;      %   (      !      "      "   '   2         5   /   L   @      $   /      $   ,   .   2   "   *                                        "         *   +   2   )   -   +   )   "   #   &   (   $         (      '   ,      #      &         )   %         !   )   A   B   /   A   (         ,   1      5   ,   )   1   2   1   )         "   !   !                      3   -   !   .   (   "      '            *   "   )   ,   (   "   '   "         "                     (   #   !         '   2   "   *   )   !   %      $   '   -   7   "   .   3   )   -   )   #         /            #   !   &         3      +   9   $   &   )   )   )   )   *   4   /       &      #   %   !   3      $   &   +   2      "         ,      0   !   %   %   $               $      '   $      $                        %   (            !   !            0   .   %   .   ;   :   ,   ,   +   +      '   4   0   (   5   +   *      1   "   6   %   /   '   #   /   /   7   ;   >   /   )   -   -   +   8   ,       (      !                               $         1   *   %   2   /   -   (   #         (   #            !   (   -         '   "                           "   -         (   7   /   2   !   )   &   $       ,      $   !         .   !   #   &   +   +   1                         "      5      0   5            '   %   '      %         &   %   "                                     !   (            )      &   #               (   $   )   "   6       !   (      1       '                              #   *   /   %      $   &      '   '      $       !      7   "   %   +   ,   ,         &   !      "   %      (   *   1       "   &   3   -      -   2   )   1   .   3   "   *   %   !            $   #   5         )   )   2   9   )   (   3   2   *   )   3   $   %   &   %   +   7   /   -   &   )               '         #   +   '   .               '   3   0   1   #       !   %   *   %   "                ,   ,   +   "      !      %      #         &   &   /   &      "       &      *   ,   #   !   #      *   .   !      '   )   (   -   2   .      ,   %                                "   $   2                                             $                  ,               %   ,   9   +   '   !   .      *   )   0   '      *   <   0   (   5      %   %   .   4   8   )            ,   B   D   ;   7   $   3   *   )   6   2   &      !       ,   &                                           $   !         .      )   +   !      (   &   1   -   ,               !      +                   (                  *   &   #   (   -   ,      1       D   (   *            %   ,               #   )                     .      #   -   $      -   !         "         (               (                                              *   1   (   +   !   -   %   $   "   5   #   &   $   '      0   )   0      '            #   '      "         /   >   )   1   #   $   *   /   8   !   0         (   2   "      $                  $   #   #         %   #   &   %   3   )   (   ,   &   0   (   ,   &   /   #   '   '   %      %            "      !                      *      ,   ,   .   !                   &   (   0         $                                                "   6   *   7   "   1   #      $   $         %      )   3   )         !   #      (   %   '          )      #      -      !      #                         #      )   #   &      %       (      "   %       *                  *   -            !      #         +                                                                     #            #   +               !   +   3               %      '                )          %               &   /         #      $                                                            !      '   )                        /      )            "                                  
      !   5   #                  *                      *      %               !                            %            "   ,   "   $      )      "   *   !                  "                                 !   )   *       "   !   -                %   $      &   (   4      -      !   '                           '   #   .   $   &      !   $   )            "   &   *      ,          !      $   $                         !      =   !         $          &          '   !   #   "       %         "   "                                    &   (   $             !   +   $   (   "         %   !       &   $                                     1          &      &      #      #      (         #   '               !   $            +   (                     #   )   *          %          %         "   $            +   !                                  $                           *         "                                                                "   !   $   $               5   7   .   <   0      #   $   (   !   "   #   (   *   -   &   '   '         ,   ,   -   *   (   .   *   -   ,   #   #   5   '   '   1   $      *   (   )      &   "      -   ;   !         %   #   4   ,   )       !   $   %   %   +   "   -   %      -   )   ,   4   &                 !            %   #   )   $                )   )      '            0    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      	                                                                  	                                                               	                                       	                                                      ,                  #   )                  #   '   %                  !               :   )   %               	   !                        $            !      #   (   "         !      6   E   2   '       (      $                                             %                                                                  !                  *   #         #         1   .                  +                     A   %               *   &   (                  (               %      ,   '            !   (   9                  (   !   %                  #                                                               *   !                  &   "                  %                               
         $   *                     (                     ,                        #                     "                *   %   '                           (      "   "   $                     !                  $   '                                          2            #                           &      $   #               $            "         5                        "               )   &                     (                      (                )         $               *   /                      (   "               !      $                  +                  #   ,   !            /   G   -   !                  (                     !                  "   7       *   #             '                     (                                                      	                                                                            %                                       !                                 	                                         
                                  2                                                   
                                                           "                                       %                                                               "                     )                      (                                                                                 '                        5   "               "                         )   "               &      #                        )                                                                                                                                                                         	                                                         #                                     '   "                      #                     !   %                   .   9   (      #   &       &                                     
   
                                                                     $                     "   %                  !   $            	   	   *                     +                      3   &                                                
                  
                                             
                  
   
                  	                                                                                                                                                                                                
                                                                                    
         &            	                                                                                                                                                       	            	                                                                      
                                                                     	                                           /   1                        1                     #                  "      !                                                       
                                 
                                    "                                                                            
                                                      "         	                     	                                                                        "                                                                                     
                         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                                 	                                                                                                
                                                         
                  
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                                                                                                      
      
                                                                  !                                                                                       "                              
                                       	                                                                                   !                  &      \"},\"shape\":[1941],\"dtype\":\"int32\",\"order\":\"little\"}]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1227\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1228\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1223\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#1b9e77\"}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1224\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#1b9e77\",\"line_alpha\":0.1}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Line\",\"id\":\"p1225\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"x\"},\"y\":{\"type\":\"field\",\"field\":\"y\"},\"line_color\":\"#1b9e77\",\"line_alpha\":0.2}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1181\",\"attributes\":{\"tools\":[{\"id\":\"p1206\"},{\"id\":\"p1207\"},{\"id\":\"p1208\"},{\"id\":\"p1209\"},{\"id\":\"p1210\"},{\"id\":\"p1216\"},{\"id\":\"p1217\"},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1218\"},{\"id\":\"p1219\"}]}},\"toolbar_location\":null,\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1201\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1202\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1203\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1204\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"DatetimeAxis\",\"id\":\"p1184\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"DatetimeTicker\",\"id\":\"p1185\",\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"type\":\"object\",\"name\":\"AdaptiveTicker\",\"id\":\"p1186\",\"attributes\":{\"num_minor_ticks\":0,\"mantissas\":[1,2,5],\"max_interval\":500.0}},{\"type\":\"object\",\"name\":\"AdaptiveTicker\",\"id\":\"p1187\",\"attributes\":{\"num_minor_ticks\":0,\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"min_interval\":1000.0,\"max_interval\":1800000.0}},{\"type\":\"object\",\"name\":\"AdaptiveTicker\",\"id\":\"p1188\",\"attributes\":{\"num_minor_ticks\":0,\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"min_interval\":3600000.0,\"max_interval\":43200000.0}},{\"type\":\"object\",\"name\":\"DaysTicker\",\"id\":\"p1189\",\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]}},{\"type\":\"object\",\"name\":\"DaysTicker\",\"id\":\"p1190\",\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]}},{\"type\":\"object\",\"name\":\"DaysTicker\",\"id\":\"p1191\",\"attributes\":{\"days\":[1,8,15,22]}},{\"type\":\"object\",\"name\":\"DaysTicker\",\"id\":\"p1192\",\"attributes\":{\"days\":[1,15]}},{\"type\":\"object\",\"name\":\"MonthsTicker\",\"id\":\"p1193\",\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]}},{\"type\":\"object\",\"name\":\"MonthsTicker\",\"id\":\"p1194\",\"attributes\":{\"months\":[0,2,4,6,8,10]}},{\"type\":\"object\",\"name\":\"MonthsTicker\",\"id\":\"p1195\",\"attributes\":{\"months\":[0,4,8]}},{\"type\":\"object\",\"name\":\"MonthsTicker\",\"id\":\"p1196\",\"attributes\":{\"months\":[0,6]}},{\"type\":\"object\",\"name\":\"YearsTicker\",\"id\":\"p1197\"}]}},\"formatter\":{\"type\":\"object\",\"name\":\"DatetimeTickFormatter\",\"id\":\"p1198\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1199\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1200\",\"attributes\":{\"axis\":{\"id\":\"p1184\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1205\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1201\"}}}]}},3,0]]}}]}};\n",
+       "  const render_items = [{\"docid\":\"9c20c46d-930e-4df1-befb-28d86243e7d8\",\"roots\":{\"p1240\":\"c506a044-6db3-4803-9b2b-d2c4d0ef4fc8\"},\"root_ids\":[\"p1240\"]}];\n",
+       "  void root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "  }\n",
+       "  if (root.Bokeh !== undefined) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    let attempts = 0;\n",
+       "    const timer = setInterval(function(root) {\n",
+       "      if (root.Bokeh !== undefined) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else {\n",
+       "        attempts++;\n",
+       "        if (attempts > 100) {\n",
+       "          clearInterval(timer);\n",
+       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
+       "        }\n",
+       "      }\n",
+       "    }, 10, root)\n",
+       "  }\n",
+       "})(window);"
+      ],
+      "application/vnd.bokehjs_exec.v0+json": ""
+     },
+     "metadata": {
+      "application/vnd.bokehjs_exec.v0+json": {
+       "id": "p1240"
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sales.plot(max_num_plots=4, interactive=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc899556-6887-4eba-89df-f81c064dec92",
+   "metadata": {},
+   "source": [
+    "Note that `sales` is indexed by product/department/category/store and state."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0cfbe43e-4026-4673-8ff2-c72e331dbca5",
+   "metadata": {},
+   "source": [
+    "### Normalize `raw_calendar`\n",
+    "\n",
+    "In `raw_calendar`, timestamps are expressed as ISO 8601 string e.g., `2011-01-29`. Let's convert them into python datetimes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "80caf3ba-314f-4650-831c-bde05c6f526e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>event_name_1</th>\n",
+       "      <th>event_type_1</th>\n",
+       "      <th>event_name_2</th>\n",
+       "      <th>event_type_2</th>\n",
+       "      <th>snap_CA</th>\n",
+       "      <th>snap_TX</th>\n",
+       "      <th>snap_WI</th>\n",
+       "      <th>timestamp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2011-01-29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2011-01-30</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2011-01-31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2011-02-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2011-02-02</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1964</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2016-06-15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1965</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2016-06-16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1966</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2016-06-17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1967</th>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>no_event</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2016-06-18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1968</th>\n",
+       "      <td>NBAFinalsEnd</td>\n",
+       "      <td>Sporting</td>\n",
+       "      <td>Father's day</td>\n",
+       "      <td>Cultural</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2016-06-19</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1969 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      event_name_1 event_type_1  event_name_2 event_type_2  snap_CA  snap_TX  \\\n",
+       "0         no_event     no_event      no_event     no_event        0        0   \n",
+       "1         no_event     no_event      no_event     no_event        0        0   \n",
+       "2         no_event     no_event      no_event     no_event        0        0   \n",
+       "3         no_event     no_event      no_event     no_event        1        1   \n",
+       "4         no_event     no_event      no_event     no_event        1        0   \n",
+       "...            ...          ...           ...          ...      ...      ...   \n",
+       "1964      no_event     no_event      no_event     no_event        0        1   \n",
+       "1965      no_event     no_event      no_event     no_event        0        0   \n",
+       "1966      no_event     no_event      no_event     no_event        0        0   \n",
+       "1967      no_event     no_event      no_event     no_event        0        0   \n",
+       "1968  NBAFinalsEnd     Sporting  Father's day     Cultural        0        0   \n",
+       "\n",
+       "      snap_WI  timestamp  \n",
+       "0           0 2011-01-29  \n",
+       "1           0 2011-01-30  \n",
+       "2           0 2011-01-31  \n",
+       "3           0 2011-02-01  \n",
+       "4           1 2011-02-02  \n",
+       "...       ...        ...  \n",
+       "1964        1 2016-06-15  \n",
+       "1965        0 2016-06-16  \n",
+       "1966        0 2016-06-17  \n",
+       "1967        0 2016-06-18  \n",
+       "1968        0 2016-06-19  \n",
+       "\n",
+       "[1969 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calendar = raw_calendar.copy()\n",
+    "\n",
+    "# Temporian and YDF (see later) treat NaN values as \"missing\".\n",
+    "# In this dataset, a NaN means that there is not calendar event on this day.\n",
+    "calendar.fillna(\"no_event\", inplace=True)\n",
+    "\n",
+    "calendar[\"timestamp\"] = calendar[\"date\"].apply(\n",
+    "    lambda x: datetime.strptime(x, \"%Y-%m-%d\")\n",
+    ")\n",
+    "\n",
+    "# We keep the mapping wm_yr_wk -> timestamp to clean \"raw_sell_prices\" in the next section.\n",
+    "wm_yr_wk_map = calendar[[\"weekday\", \"timestamp\", \"wm_yr_wk\"]]\n",
+    "\n",
+    "del calendar[\"date\"]\n",
+    "del calendar[\"wm_yr_wk\"]\n",
+    "del calendar[\"d\"]\n",
+    "del calendar[\"weekday\"]\n",
+    "del calendar[\"wday\"]\n",
+    "del calendar[\"month\"]\n",
+    "del calendar[\"year\"]\n",
+    "calendar"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0799257-cc9b-4894-84eb-c45b43cbf460",
+   "metadata": {},
+   "source": [
+    "Same as before, we can convert the calendar data into a Temporian EventSet.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ad06b695-1fb3-473f-8bf1-cff6c76c8fea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Feature \"event_name_1\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"event_type_1\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"event_name_2\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"event_type_2\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "  <div style=\"display: table; margin-bottom:11px; padding:5px; font-size:small; line-height:120%; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">features</span>\n",
+       "        <span style=\"\"> [7]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">event_name_1</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">event_type_1</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">event_name_2</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">event_type_2</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">snap_CA</span>\n",
+       "      <span style=\"color:#009988\"> (int64)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">snap_TX</span>\n",
+       "      <span style=\"color:#009988\"> (int64)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">snap_WI</span>\n",
+       "      <span style=\"color:#009988\"> (int64)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">indexes</span>\n",
+       "        <span style=\"\"> [0]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"font-style:italic\">none</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">events: </span>\n",
+       "      <span style=\"\">1969</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">index values: </span>\n",
+       "      <span style=\"\">1</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">memory usage: </span>\n",
+       "      <span style=\"\">117.4 kB</span>\n",
+       "    </div>\n",
+       "  </div>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"\">) with 1969 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">event_name_1</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">event_type_1</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">event_name_2</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">event_type_2</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">snap_CA</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">snap_TX</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">snap_WI</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-29 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-30 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2011-01-31 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-06-17 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-06-18 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">no_event</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-06-19 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">NBAFinalsEnd</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">Sporting</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">Father's day</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">Cultural</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">0</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "</div>\n"
+      ],
+      "text/plain": [
+       "indexes: []\n",
+       "features: [('event_name_1', str_), ('event_type_1', str_), ('event_name_2', str_), ('event_type_2', str_), ('snap_CA', int64), ('snap_TX', int64), ('snap_WI', int64)]\n",
+       "events:\n",
+       "     (1969 events):\n",
+       "        timestamps: ['2011-01-29T00:00:00' '2011-01-30T00:00:00' '2011-01-31T00:00:00' ...\n",
+       "     '2016-06-17T00:00:00' '2016-06-18T00:00:00' '2016-06-19T00:00:00']\n",
+       "        'event_name_1': [b'no_event' b'no_event' b'no_event' ... b'no_event' b'no_event'\n",
+       "         b'NBAFinalsEnd']\n",
+       "        'event_type_1': [b'no_event' b'no_event' b'no_event' ... b'no_event' b'no_event'\n",
+       "         b'Sporting']\n",
+       "        'event_name_2': [b'no_event' b'no_event' b'no_event' ... b'no_event' b'no_event'\n",
+       "         b\"Father's day\"]\n",
+       "        'event_type_2': [b'no_event' b'no_event' b'no_event' ... b'no_event' b'no_event'\n",
+       "         b'Cultural']\n",
+       "        'snap_CA': [0 0 0 ... 0 0 0]\n",
+       "        'snap_TX': [0 0 0 ... 0 0 0]\n",
+       "        'snap_WI': [0 0 0 ... 0 0 0]\n",
+       "memory usage: 117.4 kB"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "calendar = tp.from_pandas(calendar)\n",
+    "calendar"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "45675a74-018c-4858-aacb-6e7f69f6c555",
+   "metadata": {},
+   "source": [
+    "Note that `calendar` is not indexed: All the events are global."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e4be6c9-3cb0-4a82-a4ad-a43543131320",
+   "metadata": {},
+   "source": [
+    "## Feature engineering\n",
+    "\n",
+    "The methods shown in the previous parts were able to consume time series natively. However, generic tabular machine learning models such as decision forests are not. Instead, as the name suggest, those algorithm consume tables of data where each row is an independent observation.\n",
+    "\n",
+    "We could feed each row of our dataset to the model, but it would not be that interesting: The model would be trained to predict the sales of day `t` using all the information available at day `t`. While possibly interesting, this is not much of a forecasting. Instead, we want to predict the sales at day `t+h` (`h>0`) using information available at day `t`. In other words, we want to predict some rows from other rows.\n",
+    "\n",
+    "The simplest solution for that is to use feature preprocessing, and Temporian is specialized for that."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c0bdb6c1-d780-4d0a-9377-de006337518f",
+   "metadata": {},
+   "source": [
+    "### Basic preprocessing : lagged sales\n",
+    "\n",
+    "We have to choose what each row of the preprocessed dataset represents. A good convention which help avoiding future leakage in pipeline is to attache a timestamp to each row and enforce that the row only contains information available at it timestamp. For example, a row with timestamp `2022-09-12` can only contain data derived from observations at or anterior to `2022-09-12`. This include for example, the sum of all the sales in the last week (i.e. the sales from `2022-09-6` to `2022-09-12`).\n",
+    "\n",
+    "This kind of summation, called moving sum, is a simple or powerful way to prepare data. This will be our first preprocessing.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "36a91dd8-f302-4417-a7d5-01fa68c06bed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lagged_sales_list : list[tp.EventSet] = []\n",
+    "for horizon in [1, 2, 3, 7, 14]:\n",
+    "    x = sales[\"sales\"].lag(tp.duration.days(horizon))\n",
+    "    x = x.resample(sales)\n",
+    "    x = x.rename(f\"f_sales_lag{horizon}\")\n",
+    "    lagged_sales_list.append(x)\n",
+    "feature_lagged_sales = tp.glue(*lagged_sales_list)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15919d6e-1a66-46ba-95d8-b9d86c00d4a2",
+   "metadata": {},
+   "source": [
+    "The dataset is too large to be plotted. Instead, we will plot the preprocessing on a single randomly selected product and for a short period of time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "fc70c64a-beab-4820-be17-a0fbb3b1f279",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Selected product (selected_index): (b'FOODS_3_694', b'FOODS_3', b'FOODS', b'WI_2', b'WI')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Select a product.\n",
+    "selected_index = sales.get_arbitrary_index_key()\n",
+    "print(\"Selected product (selected_index):\", selected_index)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "fceca94e-c636-495e-95b6-66661e8c9e72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The number of plots (5) is larger than \"options.max_num_plots=4\". Only the first plots will be printed.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1024x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_options = {\n",
+    "    # Only plot the selected product.\n",
+    "    \"indexes\": selected_index,\n",
+    "    # Optional: Make the plot interactive.\n",
+    "    # \"interactive\": True,\n",
+    "    # Only plot the data for the year 2015.\n",
+    "    \"min_time\": datetime(2015, 5, 1),\n",
+    "    \"max_time\": datetime(2015, 6, 1),\n",
+    "}\n",
+    "feature_lagged_sales.plot(**plot_options, max_num_plots=4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5cf08a30-2838-45c6-affa-f90fb75ef583",
+   "metadata": {},
+   "source": [
+    "### Preparing labels\n",
+    "\n",
+    "The label is the only column that does not follow the future leakage restriction of the features. This is actually the oppositive: Predicting the label should be a forecast, therefore labels at time `t` should tell us something about the future, such as the sales at the `t+1`.\n",
+    "\n",
+    "Our goal in this tutorial is to forecast the sales for the next 28 individual days. Therefore, we create those 28 labels."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "71b932fb-13ce-4565-bd61-3071be191342",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Prediction horizon. In the M5 competition, participants should forecast the next 28 days.\n",
+    "# You can predict less days to make the training section of this notebook run faster.\n",
+    "horizons = list(range(1, 14))\n",
+    "\n",
+    "# For each of the horizons.\n",
+    "label_list: list[tp.EventSet] = []\n",
+    "for horizon in horizons:\n",
+    "    # Leak the sales in the past.\n",
+    "    x = sales[\"sales\"].leak(tp.duration.days(horizon))\n",
+    "\n",
+    "    # Resample the label to the sales data.\n",
+    "    x = x.resample(sales)\n",
+    "\n",
+    "    # Give a name to the label for book-keeping.\n",
+    "    x = x.rename(f\"label_h{horizon}\")\n",
+    "    label_list.append(x)\n",
+    "\n",
+    "labels = tp.glue(*label_list)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75d566cf-67d8-49e5-bc7a-56dd59863163",
+   "metadata": {},
+   "source": [
+    "Let's see what the labels look like. Can you see how they shift more and more to the left while the horizon increases?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "911a0f84-b1bc-4a22-9ad9-db8cc0ed861a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The number of plots (13) is larger than \"options.max_num_plots=4\". Only the first plots will be printed.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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I7149a1rd2d6pU6ey6dOny9x24cIFZmBgwIqKiqSPmzBhgvT+lJQUBoB9+umn0tsqe7Jf7ZWpzqu9QWFhYeydd96R2aZdu3YyvYu5ubns4cOHtf683HsIQKbXsHKfb7/9drU1VZ75Nzc3Z5aWltKfW7duMca4HsraejvFYrF03/7+/tX2OjHG9XgDYF999VW1f4uX/fjjjwwAe/78OWOM6ymytbVlZmZmrEOHDmzRokUsMjKyxpqq88MPPzBLS0sGgPn5+cnVS88Y1zNubGzM/Pz82LFjx9iVK1dYz549mZ+fHyspKWGMMfbTTz8xCwsLdvLkSVZRUcFiY2OZv78/A8AuX77MGON6mpycnFhsbCxjrO5e5OrI83rx9vaW6WVhjLEvvviChYWFMcb+y3vlypXS+8vKypi7u7s0m8qezqysLLlre/mYi42NZQDY9evXpffHxMQwADLH4dOnT2t9XSckJEi33bx5MwPArl69WmWf165dq7amxYsXMwMDA5nXdZs2bRhjjKWmplap52X79++X7vvq1au19gp+9913Mq/X2nqZ27Vrx/r3788YY6y8vJxNmTKFAWAuLi5s6NCh7P/+7/9YTk5OtY+tSeWICwBs+vTprKKiQu7Hvv7666xjx45yb5+ens4ASHu96xrpU52Xe6fz8vKYiYkJ2717t/T+zMxMZm5uXqUXr673wUqVr9+dO3dW2eeuXbuqrany9fXya8XZ2Vl6v5mZWY2Z3rp1iwFgu3btUuh19erf4lVjxoxhAQEB0n9/9NFHzMjIiNnZ2bF+/fqxr7/+mqWmplb72Op8++23zNfXl5WWllZ7f3Wfk+PGjWO9e/eWuW3+/PksMDBQ5nFDhw6V2Uaez9favFzL8ePHmZGREXv27Jn0/qNHj1Y5JhMSEmp9fTx9+lS67eLFi5mhoaHMbUePHmUGBgY1fpZv3LiRWVpasrKyMpabm8uMjIxYWloa2759O+vSpQtj7L8RFk+ePKn2d1FEeno68/T0ZB999JHcj1Em4+oMGDCAvf/++9J/V/ee9sUXX7A+ffrI3JaUlMQASD/naqONnxknTpxgAFhycjJjjDEnJyd2/fp1dvnyZenInvj4eAaAnTt3rta/DyGqIN/pPEIELjIyEnfu3MG2bduktzHGIJFI8PjxYwQEBAAAQkJCpPc7OzsDgPTM98u3paWlVemZqUtMTAxmzJghc1tYWJjMGWFra2uFrzsLCwur8u+6JrLatWuX9HcGINOLzRToGVJk27r2UTkh0IgRIzBgwABcuHABV69exdGjR/H111/jl19+kXsSsPHjx6N3795ISUnBqlWrMHr0aFy6dKlKD/urJBIJysrKsG7dOvTp0wcAN3rBxcUFZ86cQd++fTFt2jTEx8dj4MCBKCsrg1gsxuzZs7FkyRIYGBigoqIC48aNw+effw5fX1+l/y51vV4KCgoQHx+PqVOnYtq0adJtysvLYWNjU+VxlYyMjNC6dWulR3NUV6eRkRFCQ0Olt/n7+1e5jrphw4YK7dfIyAht2rSpss+YmBi0bdu22sf4+fnh0KFD0n+bmprK3M/Ha7vydW1oaIjNmzfjyy+/xOnTp3Ht2jUsX74cX331Fa5fvw5XV1e59rlr1y7k5eUhMjIS8+fPx6pVq7BgwQK5HhsREYFRo0bVeP/Dhw/x2Wef4dq1a8jIyJD20CcmJiI4OFiu56hNfHw8SktL0a5dO+ltdnZ28PPzk9nOyclJ4flIXn6NV+6ztte4tbW1zAgBAwPZgY98vlYAYNmyZZg3b570tbJhwwYsX74c58+fl/lMqsmoUaOwZs0aNGnSBP369cNrr72GQYMG1doLHBMTgyFDhsjc1rFjR6xZswYVFRUwNDQEALRu3VpmG3k/X+URExMDDw8PuLm5SW979TMOALy8vOTeJwB4enrKvAeFhYVBIpEgNja22s/ybt26oaCgADdu3EBWVhZ8fX3h6OiIrl274o033kBxcTHOnj2LJk2awNPTU6FaXpWbm4sBAwYgMDBQoclTlcm4oqICy5cvx+7du/Hs2TOUlpaipKSkzjkNIiMjcebMmWpHycTHxyv0WactnxkdOnSAiYkJzp49i+bNm6OoqAitWrWCRCJBeno6Hj9+jLNnz8Lc3Bzt27dXqBZClEGNekLkkJ+fj7feegvvvfdelfte/kA2NjaW/n/lF6zqbnt1pmJV2bZtW7VD31929OhRdO7cuV7P4+HhAR8fnyq3+/r64uLFiygtLYWJiYnMfcnJycjNzZV+ePv6+tb4pbnydnk+6GNiYiAWi2Fvby+9zczMDL1790bv3r3x6aef4n//+x8WL14sd6PexsYGNjY2aNq0Kdq3bw9bW1scOHAAr7/+eq2Pq2xYBQYGSm9zdHSEg4ODdCZrkUiEr776CsuXL0dqaiocHR2ls+I2adIEeXl5uHnzJm7fvi0dfiqRSMAYg5GREf755x/06NFDrt+jNvn5+QCAjRs3yjSSAEi/fGuT/v37V7l05GVeXl7VziyuCBMTk2pf146OjtIvd9WJiYmBSCSCj4+PtHEVExODYcOGVbutra0tHB0da62loqICDx8+lPmSCXBfVCdOnIiJEyfiiy++gK+vLzZs2IDPP/9crt+x8gRcYGAgKioqMH36dLz//vtyZf7q5QSvGjRoELy8vLBx40a4ublBIpEgODhYJZOhKWLGjBn4448/at2m8vWvLAMDg2pfK4D8722KvK7qEhMTg8aNG8vcZm9vj1GjRmHUqFFYvnw5WrZsiVWrVlW5vKY6Hh4eiI2NxcmTJ3HixAm88847+Oabb3Du3DmZzzRlWFpayvxb3s9XVQoKCpK53OlVnTt3xtGjR5Xev4+PD9zd3XHmzBlkZWVJL3Nxc3ODh4cHLl++jDNnztT7vTwvLw/9+vWDtbU1Dhw4oFA2ymT8zTffYO3atVizZg2aNWsGS0tLzJkzp85jPD8/H4MGDcJXX31V5T55T0gqSt2fGRYWFmjbti3OnDmDFy9eoFOnTjA0NIShoSE6dOiAM2fO4MyZM+jYsWOV70OEqAM16gl5RXWzSbdq1Qr37t2T68uVugQEBODatWuYNGmS9LaXZ1EGgMGDB1dpoL3q1bPXV69erbLPli1bKlXj2LFjsW7dOvz000+YNWuWzH2rVq2CsbExRowYId123LhxOHz4cJXr6r/99lvY29ujd+/etT5fWloatm/fjqFDh1bpKXtZYGCg0msUM8bAGJPrGv3K2W1jY2Ph7u4OgJvdOiMjo0rPkKGhoTSLHTt2ICwsDI6OjpBIJIiKipLZdv369Th9+jT27t1b5Yt7Tep6vTg7O8PNzQ2PHj2Sztpdk6tXr0pngS8vL0d4eLj0hEPllxV5Vwd4lb+/v3SflQ3Y2NjYKkvk/fLLLygqKqpxP69+CS0vL8fNmzelPSyV+1Sk16+SgYEBRo8ejW3btmHp0qUyPXNFRUVYv349+vbtCzs7OwBA7969sX79esydO1emIZyamopt27Zh0qRJdS41tXXrVmRlZUmPl+rY2trC1dVV6RnNK0eWSCQSuRr1ISEhOHXqVLUnEDIzMxEbG4uNGzdKTxpevHhRZpv6vla8vb1hbGyMa9euSRt7WVlZePDggczcAEuXLsUHH3yg0L6vXr1aZZ/KvFYA7r3t448/RmRkpMx19RKJBKtXr0ZgYCCaN28OkUik0OuqJqdPn0ZUVBTmzp1b4zYmJibw9vZW6LVibm6OQYMGYdCgQZg5cyb8/f0RFRWFVq1aVfs5GRAQUGXp0EuXLsHX17fW15cqP18DAgKQlJSElJQUaWPx1c9JADhy5Eitcya8egIrMTERycnJ0hEAV69ehYGBQZVRIi/r3r07zp49i6ysLMyfP196e5cuXXD06FFcv34db7/9tkK/38tyc3PRt29fmJqa4tChQ3WOJKuOohlfunQJQ4YMkS5jK5FI8ODBA5kT2TV9h9q3bx8aNWok9zX/NdGmz4zu3btj586dyMrKklmusEuXLjh79izOnTtXZcQcIWrDw5B/QrTKq9c39e7dmw0ePJg9ffpUOjNrZGQkMzc3ZzNnzmS3b99mDx48YAcPHmQzZ86UPq6668/wynV8ilxT+up15Dt37mRmZmZs06ZNLDY2ln322WfM2tq63rPfOzg4sF9//VW6TwMDA3b37t1qt5en/tmzZzNTU1O2atUqFhcXx2JiYtjHH3/MDAwMZGbFl0gkbNiwYczW1pb98ssv7PHjxywyMpJNnz6dGRkZyfzdNm/ezMRiMUtJSWHJycns3r177Ndff2Xe3t6sSZMm0mvaMjIyWPfu3dnvv//OIiMj2aNHj9ju3buZs7Mze/PNN+v8e8THx7Ply5ezmzdvsidPnrBLly6xQYMGMTs7O+k10HUZMmQICwoKYpcuXWJRUVFs4MCBLDAwUHrdYnp6Ovvxxx9ZTEwMu337NnvvvfeYmZlZjdftMabcNfXyvF42btzIzM3N2dq1a1lsbCy7c+cO27RpE/v2228ZY//l7enpyfbv389iYmLY9OnTmZWVlfTYePr0KROJRGzLli0sLS2N5eXl1Vnbq8dcv379WMuWLdnVq1fZzZs3WadOnZi5uXm9ZjI2NjZmbdu2le6zffv2rH379jU+pq6/cUZGBvP29mbBwcHsyJEjLDExkZ07d4517tyZOTk5sfj4eOm2Dx48YA4ODqxz587s3LlzLDExkR09epQFBwezpk2bsszMTJm/xbRp01hKSgpLSkpiV65cYQsWLGDGxsYyc1ts2LCBzZgxgx0/fpzFxcWx6OhotmDBAmZgYCDXag9//PEH27VrF7t37x6Lj49nu3btYm5ubtKVI+QRGxvLTExM2Ntvv80iIyNZTEwMW79+PUtPT2cVFRXM3t6eTZgwgT18+JCdOnWKtWnTRuY9sKysjJmbm7Mvv/ySpaamysweXpNXryOfMWMG8/LyYqdOnWJRUVFs8ODBzMrKqt6z3wcFBbGTJ09K9+np6SmdB+NVdc1+X1RUxNq1a8c8PDzY7t272ZMnT9j169fZ0KFDmaWlJbty5Yp0W0VeV5MnT2b9+vVjKSkp7OnTpyw8PJwtW7aMWVlZsYEDB7Ly8nLGGGOHDx9m48ePZ4cPH2axsbHs/v377JtvvmGGhobst99+k+vvsnnzZvbLL7+wqKgoFh8fzz755BNmbm7OMjIyGGPVf06Gh4czAwMDtnTpUhYbG8u2bNnCzM3NZWb2ru5zUp7P19q8vM+KigoWGBjIevfuzSIiItj58+dZaGhovWe/t7S0ZL169ZLu09fXl40dO7bWx23atImZm5szIyMjmfkMtm7dyqytrWWux67ud6lNTk4Oa9euHWvWrBmLi4tjKSkp0p/K10FdlMl47ty5zMPDg126dIndu3eP/e9//2NisVjmGJ02bRpr06YNe/z4sfS94dmzZ8zR0ZGNHDmSXb9+ncXFxbFjx46xKVOmyFWvNn5mMMbY6dOnGQBmbW0tcz3+uXPnpBlXzpVT0+9CiKpQo54I3qtvsFeuXGEhISHSyaQqXb9+nfXu3ZtZWVkxS0tLFhISwpYtWya9X92NesYYW7ZsGXNwcGBWVlZs8uTJbMGCBfVu1P/www+sd+/ezNTUlDVq1KjGyaEUqf/XX39loaGhzMzMjFlaWrLOnTtXu3RdWVkZ++abb1hQUBAzMTFhYrGY9e3bl128eFFmu8pJbAAwkUjEbGxsWNu2bdnSpUtlJgorLi5mCxcuZK1atWI2NjbMwsKC+fn5sU8++aTK8mLVefbsGevfvz9zcnJixsbGzN3dnY0bN47dv3+/zsdWysnJYW+++SZr0KABs7OzY8OGDZNZFic9PZ21b9+eWVpaMgsLC9azZ0+ZLwPVUaZRz5h8r5dt27axFi1aMBMTE2Zra8u6dOnC9u/fzxj7L+/t27eztm3bMhMTExYYGMhOnz4ts4+lS5cyFxcXJhKJlFrSLiUlhQ0YMICZmpoyT09P9ttvv6lkeaJ9+/axJk2aMFNTU9arVy+ZCaleJc/fOD09nc2aNYt5eHgwY2Nj5uzszKZMmVLtfhMSEtjkyZOZs7MzMzY2Zh4eHmzWrFnSL8yVXl46qnJZqYEDB0ozqHTr1i02YcIE1rhxY2Zqasrs7e1Zly5dqj2uqrNz507WqlUr6ftXYGAgW758uVwTkb3s7NmzrEOHDszU1JQ1aNCA9e3bVzpJ4okTJ1hAQAAzNTVlISEh7OzZs1XeAzdu3Mg8PDyYgYGBUkva5eXlsQkTJjALCwvm7OzMvv76a5UsaXf48GHp+1Dbtm1rnVyzrkY9Y4wVFBSwjz/+mPn4+DBjY2NmZ2fHRowYIbNUXiV5X1cvLxdmZGTEHB0dWa9evdimTZtkJjyMj49n06ZNY76+vtKlB9u0aaPQslkHDhxg7dq1Y2KxmFlaWrL27dvLLNVZ0+dk5ZJ2xsbGzNPTk33zzTcy+63puK7r87U2r+4zNjaWderUiZmYmDBfX1927NgxlSxpt379eubm5sbMzMzYyJEjpUs51qTy/dPf31/m9oSEBOkkrHX9LjWpfN1W91O5hFxdlMk4MzOTDRkyhFlZWTEnJyf2ySefsEmTJskco7Gxsax9+/bM3Nxcpp4HDx6wYcOGsQYNGjBzc3Pm7+/P5syZU2Up1+po42cGY9wJPFNTU2ZlZSWzhGRxcTEzMzOrcnt1vwshqiJiTAUztBBCCNE7CQkJaNy4MW7fvo0WLVrwXQ4hhBBCCKkGrVNPCCGEEEIIIYToKGrUE8KT/v37w8rKqtqf5cuX812eXtq2bVuNf/OgoKA6Hz9jxowaH0+T4XASExNr/BtZWVlJVwEgqqWr7ye1vVZqm7maCMOFCxdqfY3oq/p+VukS+swgRDVo+D0hPHn27FmNM7Pa2dnVOeMxUVxeXh6eP39e7X3GxsZ1rl2clpaG3Nzcau8Ti8UKr42tj8rLy5GQkFDj/aqY/ZhUpavvJ3FxcTXe17BhwzqX0SP6raioCM+ePavxfj5XpFGn+n5W6RL6zCBENahRTwghhBBCCCGE6Cgafk8IIYQQQgghhOgoatQTQgghhBBCCCE6Su8vUpFIJEhOToa1tTVEIhHf5RBCCCGEEEIIIXVijCEvLw9ubm4wMKi5P17vG/XJycnw8PDguwxCCCGEEEIIIURhSUlJcHd3r/F+vW/UW1tbA+D+EGKxmOdqiDolJSXRCRyBoKyFgXIWBspZGChnYaCchYFy1pzc3Fx4eHhI27Q10ftGfeWQe7FYTI16Pefs7EwZCwRlLQyUszBQzsJAOQsD5SwMlLPm1XUZOU2UR/RGamoq3yUQDaGshYFyFgbKWRgoZ2GgnIWBctY+1KgnesPW1pbvEoiGUNbCQDkLA+UsDJSzMFDOwkA5ax9q1BO9YWxszHcJREMoa2GgnIWBchYGylkYKGdhoJy1j2Aa9Y8z8vkugahZWloa3yUQDaGshYFyFgbKWRgoZ2GgnIWBctY+gmnUf3fiARhjfJdB1Mje3p7vEoiGUNbCQDkLA+UsDJSzMFDOwkA5ax/BNOqbNbTBX3dS+C6DEEIIIYQQQghRGV4b9UuWLIFIJJL58ff3l95fXFyMmTNnwt7eHlZWVhgxYgSeP3+u1HNN7tAI268lIq+4TFXlEy2TmZnJdwlEQyhrYaCchYFyFgbKWRgoZ2GgnLUP7z31QUFBSElJkf5cvHhRet/cuXNx+PBh7NmzB+fOnUNycjKGDx+u1POYGhliVg8frD7xUFWlEy3j5OTEdwlEQyhrYaCchYFyFgbKWRgoZ2GgnLWPEe8FGBnBxcWlyu05OTn49ddfsX37dvTo0QMAsHnzZgQEBODq1ato3769ws/VwccBe8Of4m5yDoLcbOpdO9EuZWU0CkMoKGthoJyFgXIWBspZGChnYaCctQ/vPfUPHz6Em5sbmjRpgvHjxyMxMREAEB4ejrKyMvTq1Uu6rb+/Pzw9PXHlyhWln29hf398dSwWEglNmqdvsrKy+C6BaAhlLQyUszBQzsJAOQsD5SwMlLP24bVR365dO2zZsgXHjh3Djz/+iMePH6Nz587Iy8tDamoqTExM0KBBA5nHODs7IzU1tcZ9lpSUIDc3V+bnZU5iM/Twc8Tum0nq+JUIj6ob8UH0E2UtDJSzMFDOwkA5CwPlLAyUs/bhdfh9//79pf8fEhKCdu3awcvLC7t374a5ublS+1yxYgU+//zzWreZGNYIUzZfR58gF9hZmij1PET7FBYW8l0C0RDKWhgoZ2GgnIWBchYGylkYKGftw/vw+5c1aNAAvr6+iIuLg4uLC0pLS5GdnS2zzfPnz2s9O7Ro0SLk5ORIf5KSqvbIGxqIMK+3L74+dl/VvwLh0aujMoj+oqyFgXIWBspZGChnYaCchYFy1j5a1ajPz89HfHw8XF1dERoaCmNjY5w6dUp6f2xsLBITExEWFlbjPkxNTSEWi2V+qtPS0xaGBiLcTHih8t+D8MPNzY3vEoiGUNbCQDkLA+UsDJSzMFDOwkA5ax9eG/UffPABzp07h4SEBFy+fBnDhg2DoaEhXn/9ddjY2GDq1KmYN28ezpw5g/DwcLzxxhsICwtTaub76izo64/VJx+grEKikv0RftFZQ+GgrIWBchYGylkYKGdhoJyFgXLWPrxeU//06VO8/vrryMzMhKOjIzp16oSrV6/C0dERALB69WoYGBhgxIgRKCkpQd++fbF+/XqVPb+NhTGGtXTH1ssJ+F/nJirbL+FHfn4+3yUQDaGshYFyFgbKWRgoZ2GgnIWBctY+IsaYXq/tlpubCxsbG+Tk5FQ7FJ8xhje33MDy4c3gaqPc5HxEO+Tk5MDGxobvMogGUNbCQDkLA+UsDJSzMFDOwkA5a05dbdlKWnVNPR9EIhEW9g/AiiM0aZ6uy8jI4LsEoiGUtTBQzsJAOQsD5SwMlLMwUM7aR/CNegDwc7GGq40Zzsam8V0KqYeioiK+SyAaQlkLA+UsDJSzMFDOwkA5CwPlrH2oUf+v93o2xU/nHqG4rILvUoiSvLy8+C6BaAhlLQyUszBQzsJAOQsD5SwMlLP2oUb9vyxNjTC5QyP8eDae71KIklJTU/kugWgIZS0MlLMwUM7CQDkLA+UsDJSz9qFG/Uv6BjkjNjUPjzMK+C6FKKGkpITvEoiGUNbCQDkLA+UsDJSzMFDOwkA5ax9q1L9EJBLho9cCsOJIDPR8UQC91KQJLUsoFJS1MFDOwkA5CwPlLAyUszBQztqHGvWv8LS3QLOGNjgSRcNKdE1iYiLfJRANoayFgXIWBspZGChnYaCchYFy1j7UqK/G9K5N8MfVJ8gvKee7FKKA8nLKSygoa2GgnIWBchYGylkYKGdhoJy1j4jp+Tjz3Nxc2NjYICcnB2KxWO7HXXyYgbOxafhkYKAaqyOqVFxcDDMzM77LIBpAWQsD5SwMlLMwUM7CQDkLA+WsOfK2Zamnvgadmjogs6AUMSm5fJdC5PTo0SO+SyAaQlkLA+UsDJSzMFDOwkA5CwPlrH2oUV+Lhf39sfLofUgkej2YQW9IJBK+SyAaQlkLA+UsDJSzMFDOwkA5CwPlrH1o+H0dNl96DEsTI4xu46GG6ogqlZWVwdjYmO8yiAZQ1sJAOQsD5SwMlLMwUM7CQDlrDg2/V5GJ7b1wKDIZWQWlfJdC6hAbG8t3CURDKGthoJyFgXIWBspZGChnYaCctY/KG/Xl5eV6tcyBkaEB5vXxxdfH6cVLCCGEEEIIIUS7qLxRf/fuXTRu3FjVu+VVK09biERA+JMsvkshtfDz8+O7BKIhlLUwUM7CQDkLA+UsDJSzMFDO2oeG38tpfh8/rD7xAOUVNDGEtqKhQJpTXFaBkvIK3p6fshYGoeWcU1QGPZ/mplpCy1moKGdhoJyFgXLWPkaKPqBVq1a13l9UVKR0MdrM1tIEg1u4YeuVJ5jaSb9GIhCiiAoJw6wdt2FiaIB1r7eEoYGI75II0XlRT3Mwa8ctzO/rjwEhrnyXQwghhBAdonBP/b179xASEoIhQ4ZU+9O1a1eli1m5ciVEIhHmzJkjva24uBgzZ86Evb09rKysMGLECDx//lzp56iPka3ccfFhOlJzinl5flI7GgqkGatPPECfQGd093fCV8fu81IDZS0MQsn5UlwGvj0Ri11vhWH79SeCGxEmlJyFjnIWBspZGChn7aNwT31wcDDatWuHt99+u9r7IyIisHHjRoULuXHjBn766SeEhITI3D537lz8/fff2LNnD2xsbPDuu+9i+PDhuHTpksLPUV8GBiJ82N8fK4/GYM3Ylhp/flK72NhYBAcH812GXvvnbipyisowqjW3xOPXx+5j5/VEjG3rqdE6KGthEELOf91JxpGoFGyYEAozY0P0D3bFgdvPpMeYEAghZ0I5CwXlLAyUs/ZRuKe+Y8eOtV5HYW1tjS5duii0z/z8fIwfPx4bN26Era2t9PacnBz8+uuv+O6779CjRw+EhoZi8+bNuHz5Mq5evapo6Srh7yKGo7Upzj9I5+X5Sc0MDGiKCHV6lJ6PbdcS8enAQOltH/Txw6X4TFyOy9BoLZS1MOh7zr9dScDFhxlYN7YlzIwNAQCjW3vgwO1nvM5ZoWn6njPhUM7CQDkLA+WsfRROZO3atVizZk2N93t7e+PMmTMK7XPmzJkYMGAAevXqJXN7eHg4ysrKZG739/eHp6cnrly5otBzqNKcXr748Ww8isuE86VLFzRp0oTvEvRWQUk5PjkYja9GhMDE6L+3DQMDEb4eEYIfz8UjPj1fY/VQ1sKgrzkzxvDdP7FIySnGiuHNYGT43zFlYmSAUa3dsfN6Eo8Vapa+5kxkUc7CQDkLA+WsfXg/zbJz507cunULK1asqHJfamoqTExM0KBBA5nbnZ2dkZqaWu3+SkpKkJubK/OjapamRpgU5oWfzj1S+b6J8uLi4vguQS8xxvDJwWi817MpXGzMqtxvbmKIb0c1xycHopFVUKqRmihrYdDHnCsk3PFkY2GCD/v5QySqOtHk4OYN8c+9VBSWlvNQoebpY86kKspZGChnYaCctY/C19S/LDs7G9evX0daWhokEtmJfSZNmlTn45OSkjB79mycOHECZmZVGwvKWLFiBT7//HOV7Ks2/YJdcDAiHE8yC+Blb6n25yN1MzKq18uZ1ODXi48R5CZG+yb2NW7jJDbDJwMD8P6eSGyYECrTm68OlLUw6FvOxWUVmL/3Dnr6O2Foy4Y1bmdoIMKksEbYcjkB73Tz0WCF/NC3nEn1KGdhoJyFgXLWPiKm5KK4hw8fxvjx45Gfnw+xWCzT2yASifDixYs693Hw4EEMGzYMhoaG0tsqKiogEolgYGCA48ePo1evXsjKypLprffy8sKcOXMwd+7cKvssKSlBSUmJ9N+5ubnw8PBATk4OxGKxMr9qjZ5kFmD5kRhsmBBabW8L0azCwkJYWFjwXYZeufooEzuvJ2L1mBZyvcZP3HuOk/eeY+WIZmo9JihrYdCnnHOLyzBnZwQmhXmhm59TndszxjB58w383+stYWNurIEK+aNPOZOaUc7CQDkLA+WsObm5ubCxsamzLat0d9r777+PN998E/n5+cjOzkZWVpb0R54GPQD07NkTUVFRiIiIkP60bt0a48ePl/6/sbExTp06JX1MbGwsEhMTERYWVu0+TU1NIRaLZX7UxcveEoGuNjgWXf2lAESzHj2iyyFUKTWnGOtOPcSyYfI30HsHOsPHyQob1HxpCmUtDPqSc1peMd754xZm9fCRq0EPcCfHp3dugo3n9eNvUBt9yZnUjnIWBspZGChn7aP02Ilnz57hvffeq9dZGmtr6yrLIVhaWsLe3l56+9SpUzFv3jzY2dlBLBZj1qxZCAsLQ/v27ZV+XlV6q2sTvLH5Bjr7OsLKlIai8MnU1JTvEvRGabkEH+67gy+HBsNSwdf1/zo3xkcHonEsOgX9gl3VUh9lLQz6kHNCRgEW7Y/CF0OD4eNkpdBjO/rYY8vlx0jPK4Gjte7/LWqiDzmTulHOwkA5CwPlrH2U7qnv27cvbt68qcpaqrV69WoMHDgQI0aMQJcuXeDi4oL9+/er/XnlZWZsiLe7eWPtyQd8lyJ4Li4ufJegN778+x7Gt/NEE0fFGiEA18O4dEgQ9tx8iqinOWqojrIWCl3POfpZDj46EIXvxjRXuEEPcMfS2918sP6sfk9IpOs5E/lQzsJAOQsD5ax9FLqm/tChQ9L/T09Px9KlS/HGG2+gWbNmMDaWveZv8ODBqquyHuS9DqG+Zu+8jbe7ecPfRX3PQWoXHR1dZeQHUdy+8Kd4lJGP+X3967WfnMIyzPgjHKvHtKh21vz6oKyFQZdzvhyXgZ/OP8LasS3QwMKkXvt6Z1s4Ph4QiIYNzFVUnXbR5ZyJ/ChnYaCchYFy1hx527IKjasdOnRolduWLl1a5TaRSISKCmGt4b6ofwAW7r+DTZPbwMCAJs3jg7m5fn7h1aToZzk4djcVGyaE1ntfNhbGWD68GT7YE4mfJ4XCwkR1l6dQ1sKgqzkfiUrB4chkbJgQCnMTw7ofUIdZPZri/049xMoRISqoTvvoas5EMZSzMFDOwkA5ax+Fht9LJBK5foTWoAcAFxszdG7qiL23nvJdimA5ODjwXYJOyy4sxbK/Y/D1iBAYqujEVGMHS7zbwwfz996BRKLUQhvVoqyFQRdz/v3qE5yLTce611uqpEEPAAGuYpSWSxCfnq+S/WmT57nFsG5gx3cZRAN08XgmiqOchUFoOZdXSBCXpt2fwepdTBpAs2bNkJSUpO6n0QqTw7zwZ8QzZBWU8l2KIAnldaYOFRKGD/fdwccDAmBrWb+hwq9q38QeXX0d8dXx+yrbJ2UtDLqUM2MMq088wNOsQqwc0QzGhqr9eJ3Vk+ut1yfFZRV46/dwfH0kmu9SiAbo0vFMlEc5C4NQci4oKcfmS48x8dfr+OKve/jrTjLfJdVI7Y36hIQElJWVqftptIKRoQHm9fbFN//E8l2KIFlZKT4RFeGsPfkAPQOcEdzQRi37H93aAyKIsOtGokr2R1kLg67kXCFh+OzPu7A2M8Ki/gFyLwGpiMYOljA3McLdZPVMPsmHVcdjMauHDzKLgYfP8/guh6iZrhzPpH4oZ2HQ95zT8orxzfH7mPFHOBysTPH71Lb4dXJrHI1KxYWH6XyXVy21N+qFJtTLDowx3ErM4rsUwVHnRIj67OS953hRWIrRrT3U+jwL+vrhwsMMXInPrPe+KGth0IWci8sqMGdXBFp5NcD/OjdR63PN6uGD70/rx0z4V+IzUVBagZ4Bzpjf2wcrj96HAvP2Eh2kC8czqT/KWRj0Nee4tDws3HcHi/+8i85NHfHbm20xqLkbjAwNYGRogG9HN8emi48RmZTNd6lVUKNeDRb09cd3/zxAeYWE71IEJTlZe4fEaKuEjAL8dvUJPh0YqPbnMjAQ4euRIVh/Ng6P6nltMGUtDNqec15xGWZuu4XhrRpiWEt3tT+fWwNzuDUwx82EF2p/LnXKKy7DulMP8fGAAACAJD8TbRvb4WDEM54rI+qk7cczUQ3KWRj0KWfGGK4+ysTbf4TjlwuPMbVTY/w4IRTtm9hXGXlnZmyIta+3xDfHY7XuGntq1KuBraUJBjd3w+9Xn/BdiqDo61lDdSksLcfHB6Pw1YhmMDVSzYRedbEwMcKqUc3x8YFoZBcqP/cEZS0M2pxzel4J3v7jFmb28EF3PyeNPe873byx/my8TvdqL/s7BnN6NYWVKbcihlgsxpudGmNv+FPkFAnjcj0h0ubjmagO5SwM+pBzeYUEf91JxuTNN3DhYTo+HxyElSNC0NTZutbHic2M8d2Y5vj0YDRScoo0VG3dqFGvJiND3XHuQTqeZhXyXYpgWFhY8F2CzmCM4ZMD0ZjZ3QeuNppdlsRZbIaPBwTg/d2RKC1XbjQLZS0M2przk8wCvLfjNpYMDkQrT1uNPre9lSmC3cS48DBDo8+rKifuPYfY3BjtmthLb7OwsICxoQFm9/TFdzQnjd7S1uOZqBblLAy6nHNhaTm2XHqMSZuuIz2vBD+Ob4X5ff3hJDaTex9O1mZYOaIZ3t8dqTUTpFOjXk0MDET4fHAQPjkYTcPwNSQ1NZXvEnTG5ksJ8He1RgdvfpYkCW5og9FtPLD4ULRSPY6UtTBoY87Rz3KwaH8Uvh3dHD5OtZ/NV5f/dWmCjRce6VxvfWZ+CTZfeox5vX1lbq/MuW1jOxSWVuDO02weqiPqpo3HM1E9ylkYdDHn9LwSrDoei7d+D4e9lSl+e7Mt3ujYGJb/jhpTlJe9JT4eEIDZuyJQWFqu4moVp/ZG/U8//QRnZ2d1P41W8rK3xLCWDbHmpH4tQ6StbG0122Omq64/foHIp9mYpuZJverSN8gFjewt8fP5Rwo/lrIWBm3L+XJ8Br45Hov141vBrYFmR7i8TGxmjI4+Djh+V3e+VDHGsOTwPXz0WgDMjGUv93k55w/7++Ob47GokOjWCQtSN207nol6UM7CoEs5x6XlY9H+O/j0YDQ6+jjITH5XX0FuNpjZzRtzdkYoPfpUVRQ6NbFu3Tq5t33vvfcAAOPGjVOsIj0zpEVDLNx3B5fjMtDBh59eUaEwNjbmuwSt9zy3GGtOPsDPk1qrZdktRU3v0gQfHYjC8bup6BvkIvfjKGth0Kacj0al4M+IZGyYEApzE83MQVGbyWGN8L/fbqB3oAsMDfg/lutyMOIZfJ2sql028+WcHaxM0S/YBduvJ2Jiey9NlkjUTJuOZ6I+lLMwaHvOjDFcf/wCW68kwNrUGFM7N4ZvHdfKK6tdE3vkFJVh4b47WDWqOQx4+kxWqFG/evVqubYTiUTSRj0BPhsUiP9tvQlfF2s4WJnyXY7eSktLg5OT5ias0jWl5RJ8uO8OvhgaLJ2gim8ikQifDw7G23+Eo2ED82q/8FeHshYGbcl527UniEjMxv+NawljFZzZVwVzE0P0C3LBwdvPMCJU/TPv10dydhEO3E7Gpsmtq73/1ZzHtvHElM3X0S/IBY7W9JmpL7TleCbqRTkLg7bmXCFhOBadil03kxDkJsaSQUEKXSuvrD5BLsguKsPSv+5h8aBAXjrOREzXLspTUG5uLmxsbJCTk8PrTI33knOx9tQD/Dg+lLczOPouJSUFrq6ufJehtZYcuov2TezRL1j+HnFNyS4sxdt/3MLqMS3gYlP3my9lLQx858wYw7pTcSgsLcfC/v5aMbrlZaXlEkzZfB1b3mgLEyPtONnwKomEYfrv4Vj0mj+8Ha2q3aa6nKOf5WDL5QSsGtVcE2USDeDjeC6vkOBFQalGvtQTDt/v20QztC3nwtJy7Ln5FMeiU9Er0Blj2njw0oG14Vw8ysolmNWzqcr2KW9btt7fAkpLSxEbG4vycv4nCNBmgW5idPRxwKZLj/kuhQjQgdtPuZ49LWzQA0ADCxMsGxaM+XsjtWKyEUIqJAyLD92FuYkBFr0WoHUNegAwMTLAiFbu2HUjke9SavT71Sfo3NShxgZ9TYIb2sDK1AhXH2WqqTKib7ILS3E5PgObLj7G/D2RmLL5Omb8EY7390Tiz4hnfJdHCFGD9LwSfPsPN/mdraUJfp/aFlM7NeZtROqMrt7IKynHHzwsa650o76wsBBTp06FhYUFgoKCkJjIfamYNWsWVq5cqbIC9cnE9l64nZSNyKRsvkvRS5mZ9OWvOveSc/H3nVR80MeP71Jq1cTRCm9388aCvXcgqWOSLMpaGPjKuaS8AvN2R6C5ewNM7+LNSw3yGtqyIY7dTUVRaQXfpVQRn56PCw8z6rw2vqac5/XxxbpTD3mffIiohqqO5/IKCeLS8nAoMhlfH7uP6b/dxBubr2PJobuIepoDHycrzO/nhy1vtMUvk9tg85Q2+Ofec5x7kK6S5ye1o89nYeA75/j0fCzaH4VPDkYhzNsev73ZFoNVNPldfS3q7487T7NxJCpFo8+r9GmMRYsWITIyEmfPnkW/fv2kt/fq1QtLlizBwoULVVKgPhGJRFg2NBhv/3ELP08KhbWZdk8yoWu08doevuUUluGLv+7hh/GtdGIyrQ7eDkh6UYhv/onFh/38a9yOshYGPnIuLC3HeztuY3w7L3T31/7XmaGBCBPbe2HrlQTM6Ko9JyDKKyRYcuguvhoRUuclZzXlLDYzxpg2Hvj14mO83U17fjeiHGWO5+zCUsSk5CEmJRcxKblIzy+BkYEIjR0s4e8ixsAQN3g7WcLUqObJK40MDfDtqOZ4Z9stiM2M0NJTd2bt1kX0+SwMfH0+X32Uib3hT2FlaoSpnZrAz4WfpWVrIxKJsHxYM7y38zZszLnVajRB6Ub9wYMHsWvXLrRv315mWGJQUBDi4+NVUpw+amBhgnl9fLH4z7v4dnRzrRzSqavKysr4LkGrSCQMH+67g0Wv+cPO0oTvcuQ2po0nVhyJwe6bSRjd2qPabShrYdB0zhIJw/y9d/Bmp8bo4K07q5X0DXLBpE3XMa6dJ8RacrL4x7PxGN6qoVxL/9WW8+Dmbpj22008zXKFu62FKkskGlZbzuUVEiRkFuBeSh7up+TiYVo+yisksDE3RoCrGP6uYgxs7gpHK1OlvjeZGRtizdgWeOePW1gyOBA+TtrXENAX9PksDJrIWSJhuJuciwtx6bj1JAtGBgZo18QOiwcFwVnL58kwMjTAd6Nb4O0/wmFtZoQQ9wZqf06lxyikp6dXe5amoKBA7jfcH3/8ESEhIRCLxRCLxQgLC8PRo0el9xcXF2PmzJmwt7eHlZUVRowYgefPnytbstZo08gOjR0ssSf8Kd+l6JWsrCy+S9Aqa089RHd/R428kajah/38ce5Beo3X01LWwqDpnL86fh9dfR11qkEPcL0C0zo3wS/nH/FdCgBukrsHafkY2qKhXNvXlrNIJMLC/gFYcfS+qsojPKnMObuwFFfiM7Hp4mMs2Pvfte87ryehrFyCASGu+H5cS2x+oy3WjG2Jt7p6o6uvI5yszerVESI2M8bqMS3w6cG7eJZdpKpfi7yCPp+FQV05p+QUYffNJMzeeRtvbr2BY3dT0MrTFuvHh2LDxFC80bGx1jfoK3EnE1viq2P3EZ+er/bnU7qnvnXr1vj7778xa9YsAJC+0f7yyy8ICwuTax/u7u5YuXIlmjZtCsYYtm7diiFDhuD27dsICgrC3Llz8ffff2PPnj2wsbHBu+++i+HDh+PSpUvKlq013unug+m/3UQrT1v4OCk2gRCpnouL5iaBKy2XIC4tH/dTc3E/NQ/2libo3NQRAa7WWjH64vT950jPL8Hc3r58l6IUAwMRvhkZgum/hcNZbIbGDpYy92sya8IfTea8+0YSANQ4OkTbdW7qgK2XE5CRX8Lr0qnFZRVYfiQG//d6S7nfC+vK2cfJCo3sLXDy3nP0CnRWRZlEQyokDNHPcnDhYTpuPsqF6MZ12Jgbw99VjABXMQaGuMLRWrned2U4WpviqxEh+GB3JH4Y30qnRrHJq0LCsOniY7zezpOXycLo81kYVJVzYWk5rj1+gQsPMhCXng8XsSk6N3XE4kFBenF82pgbY/XoFpi9M0LuFZ6UpfSSdhcvXkT//v0xYcIEbNmyBW+99Rbu3buHy5cv49y5cwgNDVWqIDs7O3zzzTcYOXIkHB0dsX37dowcORIAcP/+fQQEBODKlSto3769XPvTliXtqvM8txjzdkfg18ltYGZc8/VgRD6JiYnw9PRU+X7T80qk1/PdT81DdmEpjA0N4ONkxQ0LdLHG89wSXHiYjpjUPDhYmqBTUwd0auoAJ2vNn018klmATw5G45fJrWu9zlAXpOYUY+6uCGyYEAobi/+GFasra6JdNJXzlfhM/HHtCf5vbEudXnL0ZsILHI1OxacDA3mrYfmRGLRtZKdQ41uenItKK/DmlhvYNKUNzE10+31N3z3LLsKFB+m4GJeBvOJyNGtog85NHWAvyoNP40Z8lwcAiEnJxfIjMdgwIRSWPM2SrQ7FZRWYv/cOXG3MkF9SjuXDmmm8Bvp8FgZlc5ZIGO6l5OL8w3SEJ2TB2JAbUl+5Soo2dIypQ0JGAT46EIX141uhgYViJyvkbcsq/U7WqVMnREREYOXKlWjWrBn++ecftGrVCleuXEGzZoq/iVRUVGDPnj0oKChAWFgYwsPDUVZWhl69ekm38ff3h6enp0KNem3mLDbD1E6NseJIDD4fEsx3OTovNze3Xo9/ufc9JiUXjzMKIGGAg5UJ/F3ECHFvgNGtPWBbzZnDps7W6NSUG7KblleMS3EZ+OpoLNLzS+DvYo1OPg5o29hO7Sdvikor8NGBKHwzsrnON+gBwMXGDB+9FoD390TgxwmhMP53VtP6Zk10gyZyfpxRgB/OxOHnSaE63aAHgNaN7PDrxcdIzi6S61p2Vbv2KBO5RWUK96bLk7O5iSH+17kxvj/zEPP71jyJJtG8/JJyXHuUiQsPMxCfno+GDczRuakjvhgSLPN5GR2t2ZmgaxPgKsasHk0xZ1cEfhjXCiZG/M+YXV+5xWWYuzMCkzo0QldfRyw9fA9n7qdpfMJP+nwWBkVyTs0pxoWH6bgUl4GswjIEuYnRuakjpnZqrBffVeXRyMESH70WgNk7I/DjhFawMFH9yUSle+pVJSoqCmFhYSguLoaVlRW2b9+O1157Ddu3b8cbb7yBkpISme3btm2L7t2746uvvqp2fyUlJTKPyc3NhYeHh1b21Ff68q97aNPYDn2DdHvIUnFZBZYcuouM/BIYGRjA3soEjtamcLDifhytTeBoZQYHaxO1vJhfvHgBOzs7ubat7H3nGvB5yCkqg5GBCD5OVvB3FSPQ1RqN7C3rvTQGYwyxz/Nw4UEGrj1+AQBo29gWnZs6wt9FtUP1GWN4f08kRrZyRwcNzbSpKceiU3HuQTqWDwuGSCRSKGuiu9Sdc3ZhKd7+45bah8Rp0t3kHPxxNRErhmu2hy6/pBzTtt5UamUXRXKeue0W5vb2pcvWePTykPpbidkwMTRAmLc9OjV1QBMHyxo/17Txffvkvef4604yvh3dQidWiKlJWl4x5u2KxAd9/dDCowEA7jvZm1tu4IdxrartjFAXbcyZqF5tOVc3pL5TU0d09LaHPY+Xh2mDK/GZ2HL5Mb4f10raUVUXtffUA1zv+oEDBxATEwMACAwMxJAhQ2BkJP9u/fz8EBERgZycHOzduxeTJ0/GuXPnlK5pxYoV+Pzzz5V+PB/m9/PD/7beRHBDGzTkoXdFFV49Q1xaLkFmQQky8kqRnl+MjLxSxKfnIz2vBBn5JSgu+29N5epPAJjC0cpUoRMAubm5Vd5gSssliE/Plw6ff5xRgAoJg4OVKQJcxQhuaINRodX3vquCSCSCv4sY/i5iTOvSBMVlFbiR8AIHbz/jrsW3MkHnpg7o6FP/ofpbLyfA19la7xr0ANAv2AWPMwrwy4XHmNalSbVZE/2jzpxLyyV4f3ckPh4QoDcNegAIcrNBUWk5HmcUVJmLQp2W/R2D2b2aKrVUqyI5L3rNH0sO3cXGSa31dpimNnqWXYSLD9NxMS4TecVlCHbjhtRP7+Itdy+3Nr5v9wp0RnZRGZYevoslg4N08jX1JLMAC/dF4YuhwTInu8yMDbGwvz8+P3wXa8a21Fg92pgzUb2Xc64cUn/hYQbCn7yAoYEI7RrbY1w7D70eUq+MMG975BaX4cN9d7BqZHOVjhBUuqf+7t27GDx4MFJTU+Hn5wcAePDgARwdHXH48GEEBys3nLxXr17w9vbGmDFj0LNnT2RlZaFBgwbS+728vDBnzhzMnTu32sfrYk89wF1rseTwXfwyqXW9e4c1rbozxIqoPAFQ2eDnTgT89++iUu4EgEjEnQBwsDaRNv5fPgHwKP4BDBo0lPa+V1777v3vte+q6n1Xpcqh+hceZiAjvxT+Ltbo3NQBbRopNlT/RsIL/HblCdaNbaG3b56MMSzaH4WeAc5wlaQr/R5D5McYA2PgbVh6dHS0WnJmjOGjA1Ho5uek8yOkqvMoPR/fn47Dd2NaaOT5TsU8x5X4THyi5LX8iub849l4uDUwwxA5Z9cniiso4daDfnVIfQdve6VPgqvreFaFn8/Ho7C0AnN66dbkstHPcrDiaAxWjWoOV5vqO4XWnHyAJo5WGNzcTTM1aXHORHXOXY9AmoE9LsZlILuwDIFuYnRu6oBQL1vBDKmvj103EhGbmo9PBwbU+b1d3p56pRv1YWFhcHR0xNatW2FrawuAW95gypQpSE9Px+XLl5XZLXr06AFPT0+sXbsWjo6O2LFjB0aMGAEAiI2Nhb+/v95MlPeqg7ef4VF6Pub18eO7FLklZBRg0f6qZ4jVpaS8Apn5pVzj/5UTAHmFRQh0t0eAqzUCXMQaHW6mCowx3E/Nw4WH6biRwC0V0raRHTr7OsDPueah+mm5xZizKwI/T2rNy0y3mlRaLsHHB6JQXFKKGT18EeRmw3dJeqOwtBz3U/NwPyUPMSm5eJpVCJFIhLIKCVaPacHLjOo5OTmwsVF9xj+fj4eEATO6eqt839pi4b47mBTWCIFu6v3ce1FQine338KmKcpP+KpozqXlEkzZfB0bJoZCrMTIAFJVhYThbnIOLjzMwK0nWTAxMkC7xnbo7OtY65B6RajreFaVFUdj4N7AHBPDGvFdilwux2Xgp/OPsHZsi1on3iqrkODNLTfwzcjmGhmVpO05k/rJLynHt//EIvlFPga08KAh9fWw/mwcGANmdvepdTu1N+rNzc1x8+ZNBAUFydweHR2NNm3aoKio7jVAFy1ahP79+8PT0xN5eXnYvn07vvrqKxw/fhy9e/fG22+/jSNHjmDLli0Qi8XS5fMUOWGgS416AFiwNxJDWzbUiXWSo5/lYPmRGHw3WjuuR42Pj4e3t/58Sa8cqn/hYQbup+bB4d+h+p18HOFozb2BllVIMO23m/hkQKCgrjG9cDsGJxIrkJJTjIntvdC5qYPejlBQNcYYnmYVSVdziE3NQ2FpOSxMjODrbM2dFHMVw93WHCKRCA+e52Hxn3fx9cgQeNhZaLRWdRzT/9xNxen7aVgxvJlev2aeZRdh2d/3sH68civRyIMxhtk7IzCtcxM0c1f+S7wyOV99lIlj0alYMjio7o1JtZKzi/6dvCoTuS8NqW/paauWieO0/TO6cjRYp6YOGBiimV5tZR2JSsHhyGR8N7qFXKtBxKXl4etjsfhpYqja3/e0PWeivNP3n2Pj+ceY2d0HrgY5lHM9Mcaw7O8YNHG0wrh2Na8koPZr6n19ffH8+fMqjfq0tDT4+NR+xuHlbSdNmoSUlBTY2NggJCRE2qAHgNWrV8PAwAAjRoxASUkJ+vbti/Xr1ytbsk5YPCgI0367CT9na60+83U5LgM/X3iEH8fLLjXGJ3lOJOkSM2NDdG7qiM5NHQFwPfIX4zKw4kgMMgpKEeBijfT8Eoxp7SGoBj0A2BpXYOmQYLwoKMUfV59g44VHGNayIQaGuOnFLMaqUlhajtjUPMS80vvesIE5/F25FRumdmpc65JOvs7WWDW6OebvicQnAwLV3vP7MlUf09HPcrDrRhJ+nKD+L7Z8a9jAHM5iM4Q/yUKol61anuPPiGT4OFnVq0EPKJdz+yb22Bv+FNHPchDckHoF5XUpLgMn7j2XDqnv1NQBnw8O0sjINm3/jBaJRPhyaDBm74yAjbmx9LNX2/x+9Qmin+Zg3est5Z5oy8fJGu2b2GPbtURMaO+l1vq0PWeiuPS8Eiz7+x6cbcyky4pGR6fyXZbOE4lE+Oi1ACzYdwe2Fsbo38y1fvtTpKf+5eULLl68iAULFmDJkiXSofBXr17F0qVLsXLlSrz22mv1KkxVdK2nHuBmL/7+dBzWj2+llV88j0SlcLPFjpLvDLGm5OXlwdramu8yNKJyqH5qbjG6+2l2uRpt8GrWxWUV2H/rGf6OSkZXX0eMbespqGG5NfW+m5sYws9ZDH9XawS6itGwgbnS18dnFZRi9q4IzOzmjXZN7FX8G1RPlcf089xizPl3KRlF14jVVel5JVi0/45aJpVLySnCgr13sHlKm3rPU6Jszul5JZi3OwJb3mir0zOXa8qvFx/jcUY+3ujYWGVD6hWhK5/RxWUVePuPcMzu5avUPEHqwhjDmpMPUVxegYX9/BXOTyJhmP47N7KvkRon0dSVnEndGGPYc/MpDt9Jxof9/GVOoFLOqlNWIcF7O25jYnuvaie7VsvwewMDA5k3kcqHVt728r8rKiqq7oAHutioB4Atlx6jggFTOzXmuxQZlWeIlw0L1qoJ5wDg4cOHaNq0Kd9lEA2oKWuJhOFkzHPsuJ6Ips7WmNKhES/rdavTy73v91NzkfSiEADQ0NYcAa7if1dbsK61970+zz13VwSGt3LXyARzqjqmC0vL8dbv4fh8cBCaOAprVMuq47Fo34RbbkxVGGOY/ns4Fvb3h7cK/p71yfn3q09gIALGt1Nv76Ou+/XiY6TmFOGj1+qelElddOkzOre4DG//EY7PB2tmvqC6VEgYlhy6Cy97C/yvcxOl9/M0qxAfH4jGpilt1HYiTJdyJjV7nFGAZX/fQ/sm9pjSoVGV7/yUs2oVlVbg7W3heL+3X5XRb2oZfn/mzBnlKiUKm9yhEd7dfhttG9nVe2ijKlSeIS4pl2DlCO28FvXlVQ+IfqspawMDEfoEuaBPkAvCn2RhxdH7MDE0wNROjTU6bFxVKiQMUc9ycCkuA/eSc6W979y172JM69ykXr3virIwMcL341ph4b4oZBWUYmzbmq8BUwVVHNMSCcOH+6LwdjdvwTXoAWBalyaYteM2OvrYq+x9+4+rT9DR214lDXqgfjmPa+uJKZuvo2+QCy+TOeoCbWjQA7r1GS02M8bqMS3w3o7b+G50C15PDpeUV2D+njvo7u+IYS3d67Uvd1sLDAxxxU/n4/FON/kulVWULuVMqiqrkODn849w52k2Fg8KqnEuHcpZtcxNDLF2TEu8sz0cXwwJVur7itIT5ekKXe2pB7jhru9su4WNk/md1VxVZ4jVrbCwEBYWmp3Ii/BDkawTMgq4L7W5xZgU5oVOPto9qd7TrEJceJiBS3EZyC8pR7OGNujo44BmDW3U0vuuDImEYfmRGDSwMMbM7j5q+3uq4pj+6th9NLK3wJg26j0Boc3Wn42Dt6OVSkZXVPbe/DyxtcpOJtU35ztPs/H7lSf4ZlRzldSjT7SlQQ/o5md05Rrw68e34mVFnbziMszZGYEJYV4qu9SOMYZ3t9/GzO4+ajnZrYs5E05EUjZWHY/FqNbuGNzcrdb3DMpZPSovFVwztgWcxdwk5Gqf/b5SYWEhEhMTUVpaKnN7SEhIfXarMrrcqAeA649fYNeNJKwaFcLLB3JxWQUW7FXNGWJ1u3//Pvz9/fkug2iAMlm/KCjF71ee4EbCCwxv1RCDmrvJPcmQOuWXlONqfCYuPEzHo4wCuNv+tx60Nl/7zRjDT+cfITWnGJ8NDFTLaIH6HtN7biYhLi0fi14LUGFVuqewtBzTfruJ395sV68ht+UVEry59SZWDG+GhirsuVTFe/fiP6PxWjNXjc33oAu0qUEP6O5n9N3kHKw8eh8bJoRq9MRqel4J5u6KwLw+vmjlqdrJLjPySzB7521smtJG5WuK62rOQlZQUo5v/3mA/JIyLOofINcJLMpZfR5nFOCTg1FYP46bjFzts9+np6fjjTfewNGjR6u9X1uuqdd1bRvb4Up8JvbdeoaRoZptVFeeIZ4Y5oVuOjAZW3l5Od8lEA1RJms7SxPM7tUUxWUV2HfrKSZvuo5ufo54va0nrDU4qV7lkPqLD9NxKzEbpkYGaN/EHpM7NEJjHiavUpZIJMKMrt7YczMJ7++JxFcjQlS+8kB9jumrjzJx9kE61o1tqcKKdJOFiRH6BLrgUOSzep2c/en8Iwxp7qbSBj2gmvfueX388M62cGzxstWKk3V807YGPaC7n9FBbjZ4t7sP5uyKwA/jWmlkhZXEzEJ8uO8OvhgaBB8n1U9G5mBliontG2H1iYdY2F+1DTNdzVmoztxPw8/nH+Gd7t4KrfhAOatPYwdLLOofgPd23saGCfIvS6t0T/348ePx5MkTrFmzBt26dcOBAwfw/PlzfPnll/j2228xYMAAZXarcrreUw9wjYBpv93ExwMCVHYNY10qzxC/38cXLVV8hlhdiouLYWZmxncZRANUkXXFS5Pq+TlbY0rHRnC1Uc91k8+yi3DhQTouxmUgr7gcIe426NzUES09G+hFA+RUzHPsvJGE1WNaqPRSIWVzTsgowCcHo/HzpFBYmGjHJQt8KymvwBubb2DLG22VapREP8vBhnPx+L/XW6q8kaiq9+4Dt58iLbcEb3UV9trJmy4+RnJ2ET4eoD0NekD3P6P/uZuKo9Gp+HZUc7XOY3I3OQfL/o7BqlHN1X4t/4K9kRjd2gOtG9mpbJ+6nrNQZOSXYNnfMXCyNsWcXr4Kr2ZFOavf5fgM/Hb5CZYN9IaDna36ht+7urrizz//RNu2bSEWi3Hz5k34+vri0KFD+Prrr3Hx4kWlfwlV0odGPcAtHzR/zx38Mrk1zIzVu4xc5TVk6jpDrC737t1DYGAg32UQDVB11uFPXmDzpQSYGRtiaqfGCHCt33tFfkk5rj3KxIWHGdL1oDs3dURHH+0eUl8f4U9eYM3Jh1gzpgXsVTRhmTI55xSW4e1t4fh2dHO1naTRVXtuJqGkXKLwOtXFZRWYuvUG1o1tqbJsX6aq45kxhv9tvYkvhgbr3aoX8tLWBj2gH5/Ru28m4V5yLhYPClTL3/dKfCY2nIvH2rEtNPJZkVtchhm/h2PjpNYqu7RAH3LWZ4wx7Al/isORVZepUwTlrBnHolPwd/gjfD+lU51tWaW7iAoKCuDkxA3JtrW1RXp6OgCgWbNmuHXrlrK7JTVwtTHHGx0bYeXR+2p9nuhnOVi0PwrfjWmuUw16AJBIJHyXQDRE1VmHetnh+3GtMLO7D7Zde4Jpv93ExYcZkPecZ4WEITIpG9+ffog3t9zAB7sj8TSrCJPCvPDbm22xckQIBoS46m2DHuD+hp8MCMS7229Ll9mrL0VzLquQ4P09EVjUP4Aa9NUY1rIhjkanoLhMscvjVp94gMlhjdTSoAdUdzyLRCIses0fy4/EqGR/ukabG/SAfnxGj27tARcbM/zf6TiV7/toVAq2Xk7AhgmhGvusEJsZ493uPlhxVHXHjD7krK8SMgow7bdw5BSWYfOUNko36AHKWVP6BbuihUcDubZVuqe+TZs2+PLLL9G3b18MHjwYDRo0wIoVK7Bu3Trs3bsX8fHxyuxW5fSlp77S0sP3EOZtj96Bzirf9+X4DPx07pHGzhCrWllZGYyNNXdtNOGPurPOzC/B71efIPxJFoa3aoiBIVUn1XuWXYSLD9NxMS4TecVlCHazQeemDmjpaauRay611dOsQizYewefDgys94gHRXJmjOHjg9Ho0tQB/YJd6/W8+uxIVAqeZhViehf5hqhff/wC+8Kf4quR6pv8VtXH81fH7qNNI1v08Ff956S20vYGPaBfn9HLj8TAw84CExUc9VKTbdeeICIxG8uHN+PlkqzPD99FF19Hlcywr08564uyCgl+ufAYtxOz8OnAwBqXqVNon5Szxqh99vs//vgD5eXlmDJlCsLDw9GvXz9kZmbCxMQEW7duxZgxY5QuXpX0rVFfUl6BqVtu4ptRISrtiToalYJDkcn4bnQLha+r0RbR0dEIDg7muwyiAZrKuqiUm1TvSFQKuvs5oYmjZZUh9R287XlZ6kibvSgoxZxdEXi3uw/aNlb+Wk1Fcv7lwiOUVkjUtvayvpBIGCZvvo7141vVOUFkfkk5pm29iZ8nhap1MklVH89FpRV4c8sNbH6jjdovV9MGutCgB/TrM5oxhg/33UFXXycMCFH+JCJjDOtOxaGgtBwL+/mr9Vr92hSXccfM+vGt6t2po08564M7T7Px9bFYjAhtiKEtGqrsPYJy1hy1z34/YcIE6f+HhobiyZMnuH//Pjw9PeHg4KDsbkkdTI0MsXRIED7aH4WNk1rDSAVndP+4+gR3nmZj3est9WLSLkJUxdzEEBPae+H1tp44ce85kl4UYmKYF5ro0Cz1fLCzNMGP41th7q4IZBeWoo8K1kevzcl7z/HgeR6+GqEdS6lqMwMDEaZ2aoxfLjzG3N6+tW67/EgM3uvZVKOrQ6iCuYkh3uzUGD+cicP7ffz4LketdKVBr29EIhGWD2uGWTtuw8bcGJ2aKv69t0LCsPTwXTS0NcfsXvwuu2lmbIgF/fzx+eF7WD2mBa+1ENUoKCnH6hMPkF1UhnWvt4QddT7oPYV66ufNmyf3jr/77julClI1feupr7T/1lM8ySys80tZbRhjWHvqIYpKK7Cwv7/OfyGgoUDCQVnrhtJyCRbuv4N2je0wpo2nwo+XJ+e7yTn49p8H2DAhVNCXPSiCMYapW29i1ajmNX7RO3M/DRfjMvDpQPVPhKSu4/mdbeF4v4+fxlaN0TRda9Dr4/t2cVkFZvwRjrm9fNFczuteAW7U5YK9d9ClqSNGaHi54tp8d+IBfJysMLi5m9L70Mecdc3Z2DT8dO4R3u7mjS6+8i9TpwjKWXPkbcsq9A3o9u3bcv1ERETUt35Sh+Gt3PEsuwhXH2Uq9fgKCcPiQ3dhaWKERVq0jm19xMbG8l0C0RDKWjeYGBlg1cjmiE3Nxw9n4uSeeLBSXTmn5Rbjy79i8O2o5tSgV4BIJMKMrt748Wz1k31lFZTil4uPML+vZnq51XU8L+ofgBVH7iv8utMFmy/pVoMe0M/3bTNjQ6wd2xJfHbuPuLR8uR6TV1yGmdtuYWiLhlrVoAeAWT18sOdmEp7nFiu9D33MWVdk5Jdg3u4IXI7PxK9TWqutQQ9QztpIoeH3Z86cUVcdRAlLBgdh2tab8B1vrdCwmsozxF19HTG8lXZ9oBBC9IuBgQifDgzAj+fisfSve/h0QKBKrhstKq3A+3si8eWwYJrTQAltG9vh14uPkJJTJDM/C2MMSw7fxYf9/HX+enQPOwu09GyAw3dS6tXzqG02X3qMZ1m61aDXZzbmxlgzpgXe23kbq8e0qHW+o/S8EszdFYG5vX0R6mWrwSrlY2xogM8GBuKzP6OxYUIovb50BGMM+249w58Rz+q1TB3RbdS1ocOsTI3w8YAAfHIwSu6eCOkZ4pYN9a5B7+en39dOkv9Q1rpFJBLhnW4+CHAR44M9kSgtl28pnJpylki4SapmdPXW26HVmjCrR1N8/8rSXIcik9HYwRIh7g00Voc6j+dpnZtg5/VE5BaXqe05NGnzpcd4qqMNen1+33YSm2Hl8BDM2xWJrILSardJelGI93bcxuJBgVrZoK/U1NkabRrZYfv1RKUer885a6MnmdwydS8KSuq9TJ0iKGftQ416HRfc0Aatveyw5XJCndum55XgnW238HY3H5UsW6JtaCiQcFDWuml0Gw/0b+aKd7ffQkFJeZ3b15TzdyceIMzbHh19aFLW+ghuaIP8knIkZBQAAFJzirE3/ClmdtfsCgLqPJ5NjAzwbg8frD7xQG3PoSmVDfpPdLBBD+j/+3YjB0t8PCAAs3dFoLBU9v3tXnIuPtx3B9+Obo6mztY8VSi/Nzs2xumYNDzJLFD4sfqes7Yor5Bgw7l4fPl3DD4bGIjpXbxVMnm2vChn7UONej3wRsdGuJHwAtHPcmrcJjGTO0P82UDtPkNcHwYG9HIWCspad/UOdMa0Lk0w449wZOaX1LptdTnvC3+KkvIKvN5W8Yn3SFWzejTFutMPwRjDp39GY/GgQI2vgqLu47mDtwNyispq/YzUdrreoAeE8b4d3NAGb3f1xpydEdIRSVcfZWLlsfv4YVwruDVQ3VLE6mRgIMKSwUFYfOguKiSKzUkhhJz5FvU0B29suQEna1P8PDEUnvb1X3deUZSz9uE1kRUrVqBNmzawtraGk5MThg4dWuXMT3FxMWbOnAl7e3tYWVlhxIgReP78OU8VayeRSIQvhzbDsr9jkF9N79fd5Bws3K87Z4iV1aRJE75LIBpCWeu2No3s8PGAAMzacRtPswpr3O7VnK8/foHT99OwsD+/yz/pEx8nKxgbGODzw/cQ1sQePk6a/4zQxPG8sL8/vj4eC4mCDRRtoA8NekA479th3vYYEeqOhfvu4GhUCjZfeowNE1rp3NwfHnYWeK2ZKzZeeKTQ44SSMx8KS8vx5V/3sPVKAtaMaYHhrdx5e0+gnLUPr436c+fOYebMmbh69SpOnDiBsrIy9OnTBwUF/w33mTt3Lg4fPow9e/bg3LlzSE5OxvDhw3msWjvZWZpgdq+m+PzQXZnbr8Rn4qtjsTp1hlhZcXHVz+RM9A9lrfv8XcT4emQI5u+5g/upudVu83LOTzILsO7UQ3w9MgSGKphoj/xnVk8fZBeWYkqHRrw8vyaOZydrM/QKcMKum0lqfy5V2qInDXpAWO/bfYNc0N7bHucepOP7ca1gYaLQvNRaY1SoO+48zUZMSvXv0dURUs6adO5BOqZuuYnOvo5YNao57K1Mea2HctY+vDbqjx07hilTpiAoKAjNmzfHli1bkJiYiPDwcABATk4Ofv31V3z33Xfo0aMHQkNDsXnzZly+fBlXr17ls3St1L6JPdwamGP/racAgGPRKdhyWTfPECvDyEg3PzSJ4ihr/eBua4Hvx7XEsr9jcCPhRZX7K3POKSrDov1R+HpkCCxNKXtVc7e1wJqxLVWyKoEyNHU8j2/nhSNRKXVe9qEttlx6jMQX+tGgB4T3vj26tQdWjgjR+OUsqiQSifD54GAs+zsGJeUVcj1GaDmrW2Z+Cd7fHYmLD9Px65TW6KrGZeoUQTlrH616p8nJ4a53s7OzAwCEh4ejrKwMvXr1km7j7+8PT09PXLlypdp9lJSUIDc3V+ZHSGb18MHhyGSsPvEAJ2PSdPoMsaI8PekaW6GgrPWHvZUpNkwIxc/nH+HkPdlLqzw9PVFWIcH7uyOxsL+/3o82EipNHc+GBiJ80McPXx/T/gmeKhv0nw7UjwY9QO/busrR2hTj23li7cmHcm1POasGYwz7wp9izq4ITOnQCB8PCNSq7/OUs/bRmka9RCLBnDlz0LFjRwQHBwMAUlNTYWJiggYNGshs6+zsjNTU1Gr3s2LFCtjY2Eh/PDw81F26VjEyNMDy4c1gYWKIr3X8DLGiHj1S7Lovorsoa/1iaWqEH8a1wpGoFOx+aXh0fHw8Pj98F8NbNdToEmtEszR5PDf3aAATI4NqR4ZoC31s0AP0vq3L+jdzRVpeCcKf1H3cUM71l5hZiOm/hyMjn1umrpm79q07TzlrH61p8c2cORPR0dHYuXNnvfazaNEi5OTkSH+SknTr+jlVcLUxx1tdvXkbSskXU1N+ry8imkNZ6x8TIwOsGtUcMSm5WH82DowxHIkrgquNOV5r5sp3eUSNNH08f9DHD2tOPkBZhUSjzysPfW3QA/S+res+HRiIVccf1LkcKeWsvPIKCX46F48v/r6HTwYE4K2uml2mThGUs/bRilfKu+++i7/++gtnzpyBu7u79HYXFxeUlpYiOztbZvvnz5/DxcWl2n2ZmppCLBbL/BBhqOk1QfQPZa2fDAxE+GxgIBgD3vo9HClFBninmzffZRE10/TxbGNhjOEt3bHu1ENkFZRq9Llro88NeoDet3WdjbkxZnb3wcqj92vdjnJWTvQzbpk6BytumTove0u+S6oV5ax9eG3UM8bw7rvv4sCBAzh9+jQaN24sc39oaCiMjY1x6tQp6W2xsbFITExEWFiYpsslWu7Jkyd8l0A0hLLWXyKRCDO7+2BSWCNMDjLVy8YNkcXH8Ty8VUM4Wpvii7/u4Y3N1zHtt5tYefQ+/ox4hofP81Cu4V78rZcT8ORFod426AF639YHnZo6wNBAhHMP0mvchnJWTGFpOZb9fQ+bL3HL1I0I5W+ZOkVQztqH1xkXZs6cie3bt+PPP/+EtbW19Dp5GxsbmJubw8bGBlOnTsW8efNgZ2cHsViMWbNmISwsDO3bt+ezdKKFzM1pEi2hoKz1X6emDoiPz+G7DKIBfBzPIpEIk8IaYdK//QOl5RLEp+fjfmou9oQ/xaP0AlRIJLC3MkWAqxgBLtYIcBWrZSWZrZcTkJBZgM8GBurEl3ll0fu2fviwnz+mbr2BFu4NYGNhXOV+yll+5x+k48ez8XiraxN083PiuxyFUM7aR8QYY7w9eQ0fXps3b8aUKVMAAMXFxXj//fexY8cOlJSUoG/fvli/fr3cwz5yc3NhY2ODnJwcGoqv53JycmBjo32TiRDVo6yFgXIWBm3OOT2vBPdTcxGTkov7KXnIKiyFkaEBfJys4O9ijUBXMRo7WCp93atQGvSAdudMFBORlI3friTgu9EtqtxHOdftRUEplv0dA1sLY8zr46tVs9rLi3LWHHnbsry+iuQ5n2BmZoYffvgBP/zwgwYqIrosKSmJ3mAEgrIWBspZGLQ5Z0drUzhaO6Jz0//Whq6zV9/VGgEudffqC6lBD2h3zkQxLTwa4HSMOf66k4yBIW4y91HONWOM4cDtZ9h/6xkW9PPT6VVdKGfto3unhgipgZWVFd8lEA2hrIWBchYGXcvZxMjg38a7GMNa/nd7Za9+9LMc7L35VKZXv3IIf2WvvtAa9IDu5Uxq926Pppi69QbaNrKDk9hMejvlXL2kF4X44q97aOVli81vtNH5JacpZ+1DjXqiN+jyCuGgrIWBchYGfcm5tl79mJT/evVLyivg62wtqAY9oD85E46JkQE+HRiIz/68ix8ntJK+ljWVM2MMT7OKEJOSi5iUPDxIy4O9pQn8XbjRMn4u1loxrL28QoJNlx7j+uMX+GRAIBo5aPes9vKi41n78P9qJ0RFkpOTYWdnx3cZRAMoa2GgnIVBn3N+uVdf6PQ5Z6HydbZGqJctdt5IwuttPQGoJ+fC0nLcT83D/ZQ8xKTk4ll2EUQAGtqaI8BVjC6+Dvhf58Z4UVCKmJRcXHiYgV8uPEZRWQXMTQzh58xNdOnvYg13W3ONnUyLfpaDr47dx+Dmbtg4qbVencSj41n7UKOe6A06aygclLUwUM7CQDkLA+Wsn97s1Bj/23oDHb0d4GlvUa+cq/S+P8+r0jDv4tsEDRtU3zC3NDWCh50F+gT9N5l2QUk5Yp9zJwTOP0jHs+wiAIC7rbnaevWLSiuw+uQDZOSVYPWYFnCwMlXZvrUFHc/ahxr1RG9YWFjwXQLREMpaGChnYaCchYFy1k+GBiIsHRKMT/+Mxq+T28idc2297/4uXO/7tC6N693YtjQ1QitPW7TytJXe9vLJg/MPVNurf+FhOtaficf0Lk3Q3V+3lqlTBB3P2oca9URvpKamwsHBge8yiAZQ1sJAOQsD5SwMlLP+8rCzQP9gF/xy4RE62hfJ5PxyA/p+ah5iU/NQWFoOCxMj+LlYw9/FGtO7NNHosHiRSAQPO4sae/W5xr5sr35lQ7+mXv0XBaVYfiQGNubG+GVya1ia6ncTi45n7aPfrzgiKLa2tnVvRPQCZS0MlLMwUM7CQDnrt9GtPfDOtluwghnuXEuU9r4DQMMGXKO4c1MHTO3UWGsbvNX16kskDM+yi3DvpV79l09KBLiKkV1YioMRz7Cgrz+aezTg7xfQIDqetY92HlWEKMHY2JjvEoiGUNbCQDkLA+UsDJSzfhOJuGH4m8/FoIWDicZ739XFwOC/Xv2+r/Tq30/Nw/3UXEgkDFveaKvzy9Qpgo5n7SOcVx/Re2lpaXyXQDSEshYGylkYKGdhoJz1n6O1KV5rZIQ+QS7wsLPQ+QZ9bSxNjRDqZYvx7bwwMayRoBr0AB3P2khYr0Ci1+zt7fkugWgIZS0MlLMwUM7CQDkLA+UsDJSz9qFGPSGEEEIIIYQQoqP0/pp6xhgAIDc3l+dKiLo9efIElpaWfJdBNICyFgbKWRgoZ2GgnIWBchYGyllzKtuwlW3amuh9oz4zMxMA4OHhwXMlhBBCCCGEEEKIYvLy8mBjY1Pj/XrfqLezswMAJCYm1vqHILotNzcXHh4eSEpKglgs5rscokaUtTBQzsJAOQsD5SwMlLMwUM6axRhDXl4e3Nzcat1O7xv1BgbctAE2Njb0whMAsVhMOQsEZS0MlLMwUM7CQDkLA+UsDJSz5sjTMU0T5RFCCCGEEEIIITqKGvWEEEIIIYQQQoiO0vtGvampKRYvXgxTU1O+SyFqRDkLB2UtDJSzMFDOwkA5CwPlLAyUs3YSsbrmxyeEEEIIIYQQQohW0vueekIIIYQQQgghRF9Ro54QQgghhBBCCNFR1KgnhBBCCCGEEEJ0FDXqCSGEEEIIIYQQHUWNekIIIYQQQgghREdRo54QQgghhBBCCNFR1KgnhBBCCCGEEEJ0FDXqCSGEEEIIIYQQHUWNekIIIYQQQgghREdRo54QQgghhBBCCNFR1KgnhBBCCCGEEEJ0FDXqCSGEEEIIIYQQHUWNekIIIYQQQgghREcZ8V2AukkkEiQnJ8Pa2hoikYjvcgghhBBCCCGEkDoxxpCXlwc3NzcYGNTcH6/3jfrk5GR4eHjwXQYhhBBCCCGEEKKwpKQkuLu713i/VjXqV65ciUWLFmH27NlYs2YNXrx4gcWLF+Off/5BYmIiHB0dMXToUHzxxRewsbGRa5/W1tYAuD+EWCxWZ/mEZ0lJSXQCRyAoa2GgnIWBchYGylkYKGdhoJw1Jzc3Fx4eHtI2bU20plF/48YN/PTTTwgJCZHelpycjOTkZKxatQqBgYF48uQJZsyYgeTkZOzdu1eu/VYOuReLxdSo13POzs6UsUBQ1sJAOQsD5SwMlLMwUM7CQDlrXl2XkWvFRHn5+fkYP348Nm7cCFtbW+ntwcHB2LdvHwYNGgRvb2/06NEDy5Ytw+HDh1FeXs5jxUQbpaam8l0C0RDKWhgoZ2GgnIWBchYGylkYKGftoxWN+pkzZ2LAgAHo1atXndvm5ORALBbDyEhrBhkQLfHyCSGi3yhrYaCchYFyFgbKWRgoZ2GgnLUP7y3jnTt34tatW7hx40ad22ZkZOCLL77A9OnTa9ympKQEJSUl0n/n5uaqpE6i/YyNjfkuQbNK8oHji4CBawADQ76r0SjBZS1QvOT8LBxIuAh0nK355xYoOp6FgXIWBspZGChn7cNrT31SUhJmz56Nbdu2wczMrNZtc3NzMWDAAAQGBmLJkiU1brdixQrY2NhIf2gSB+FIS0vjuwTNurQWKM4Fbm3luxKNE1zWAqXxnAsygBOLgYcngPKSurcnKkHHszBQzsJAOQsD5ax9eG3Uh4eHIy0tDa1atYKRkRGMjIxw7tw5rFu3DkZGRqioqAAA5OXloV+/frC2tsaBAwdqPTu0aNEi5OTkSH+SkpI09esQntnb2/NdgubkPAOeRwMjNwH3DgEFmXxXpFGCylrANJqzpAL4812g3wogYDDw4Ljmnlvg6HgWBspZGChnYaCctQ+vw+979uyJqKgomdveeOMN+Pv748MPP4ShoSFyc3PRt29fmJqa4tChQ3X26JuamsLU1FSdZRPCv7PLge4fccPue3wCnF4KDFrLd1WE6K7TXwJBwwCXZoC4IXB4NhA4mO+qCCGEEELqxGtPvbW1NYKDg2V+LC0tYW9vj+DgYOTm5qJPnz4oKCjAr7/+itzcXKSmpiI1NVXai09IpcxMgfRWp0QCEHGNDwBwb8399+lN3krSNMFkLXAayznmL6A0H2g+hvu3hR1gYATkp2vm+QWOjmdhoJyFgXIWBspZ+2jF7Pc1uXXrFq5du4aoqCj4+PjA1dVV+kPD6smrnJyc+C5B/RgDzqwAun8se3uPz4Azy7ghxAIgiKyJZnLOiANubgL6LJO9vdkoIGqP+p+f0PEsEJSzMFDOwkA5ax/eZ79/1dmzZ6X/361bNzDG+CuG6JSysjK+S1C/B8cB1+aA2FX2dkt7IGAQEL4FaDOVl9I0SRBZE/XnXFoA/D0XGLoBMDKRva9pb2D7aCDsHfXWQOh4FgjKWRgoZ2GgnLWPVvfUE6KIrKwsvktQr4oy4OoPQIdZ1d/fajIQc5ibwVvP6X3WBICac2YM+Gse0GUBYNOw6v2GxoCDH5AaVfU+olJ0PAsD5SwMlLMwUM7ahxr1RG+4uLjwXYJ6hW/hhgSbWlV/v4Eh0ONT4NRSjZbFB73PmgBQc87XfgKcg4DGnWvepsXrQMQO9dVAANDxLBSUszBQzsJAOWsfatQTvVFYWMh3CepTnMP1wrcYX/t27qGASAQk3dBMXTzR66yJlNpyfnIFeHqj5lEvlVxCgLR73CgZojZ0PAsD5SwMlLMwUM7ahxr1RG/k5ubyXYL6XFwNdJrD9cbXRQCT5ul11kRKLTnnpXLHx6A13Amw2ohEgE8vIO6U6usgUnQ8CwPlLAyUszBQztqHGvVEb7i5ufFdgnpkJwIZDwHvHvJtb2kPBA4Bwjerty4e6W3WRIbKc64oAw7NAgZ8C5hay/eYkNFA1G7V1kFk0PEsDJSzMFDOwkA5ax9q1BO9obdnDc8sB3p8othjWk0C7v+tt5Pm6W3WRIbKcz65BGgxDnD0k/8xVk5ARSlQ+EK1tRApOp6FgXIWBspZGChn7UONeqI38vPz+S5B9Z6GA0ZmgFOAYo8zMOROBJz6XD118UwvsyZVqDTn6P3cf4OGKf7Y4JFA9D7V1UJk0PEsDJSzMFDOwkA5ax9q1BO94eHhwXcJqsUYcG4l0P0j5R7fMBQQGQJJ11VblxbQu6xJtVSWc9p9IHIn0EvJk1x+/YEHx1RTC6mCjmdhoJyFgXIWBspZ+1CjnuiNjAw9G2oecxjwaMsN/1VWz8+44ft6Nmme3mVNqqWSnItzgaPzgSHfA4ZGyu3DyBRo4AWkP6h/PaQKOp6FgXIWBspZGChn7UONeqI3ioqK+C5BdcpLges/A+1n1m8/FnZA0FDg5iaVlKUt9CprUqN658wY8NccoPsn9Ts5BnDX4kdur98+SLXoeBYGylkYKGdhoJy1DzXqid7w8vLiuwTVufkr0HICYGJR/321nATEHgHy0+u/Ly2hV1mTGtU758vrAI/2gGe7+hfTMBR4dkvvRr1oAzqehYFyFgbKWRgoZ+1DjXqiN1JTU/kuQTWKsoAHx4Fmo1WzPwMDvZs0T2+yJrWqV86PzgFpMUDbaaopRiQCmnQDHp1Vzf6IFB3PwkA5CwPlLAyUs/ahRj3RGyUlJXyXoBrnVwGd3+ca46rSMBQwNAYSr6lunzzSm6xJrZTOOecZcOFbbj16kUh1BYWMAe7o4Zr1jAF5z3l7ejqehYFyFgbKWRh4yzk/DSgt5Oe5tRyvjfoff/wRISEhEIvFEIvFCAsLw9GjR2W2uXLlCnr06AFLS0uIxWJ06dKFruMg1WrSpAnfJdTfi0dAzlOgcWfV77vHp8BZ/Zg0Ty+yJnVSKufyEuDwe8DA1YCJpWoLsmkIlOQBxTmq3S/f4k8Dm/ry9t5Ax7MwUM7CQDkLg8ZzlkiAG78Ae6YA/3yi2efWEbw26t3d3bFy5UqEh4fj5s2b6NGjB4YMGYK7d+8C4Br0/fr1Q58+fXD9+nXcuHED7777LgxU2YNJ9EZiYiLfJdTfmeXcUHl1sLADgobrxaR5epE1qZNSOR//GGg9FbD3Vn1BADfx5N2D6tk3HxgDrm0AAocAD//hpQQ6noWBchYGylkYNJpzeiywfTT3eTX5L+62xxc09/w6Qsn1fVRj0KBBMv9etmwZfvzxR1y9ehVBQUGYO3cu3nvvPSxcuFC6jZ+fn6bLJDqivLyc7xLqJ/EaYG4LODRV33O0nAhsGwkEDgWsHNX3PGqm81kTuSicc8QOwMwG8H9NPQUBgP9AYM9kIHSy+p5DkxIuAs5BQIf3gD9nAn79NV4CHc/CQDkLA+UsDBrJubwUuLQGeB4NDFoD2Lhzt/daAuwcx11aqooJpfWE1nR5V1RUYOfOnSgoKEBYWBjS0tJw7do1ODk5oUOHDnB2dkbXrl1x8eLFWvdTUlKC3NxcmR8iDD4+PnyXoDzGgHNfAV0/VO/zSCfNW6Le51Eznc6ayE2hnFPuADGHge4fqa8ggPsCYe3CXSqjD678AIS9y43ksXYBnt/TeAl0PAsD5SwMlLMwqD3npOvAthGAvQ8waut/DXoAMBNzJ6LPLldvDTqG90Z9VFQUrKysYGpqihkzZuDAgQMIDAzEo0fcF6YlS5Zg2rRpOHbsGFq1aoWePXvi4cOHNe5vxYoVsLGxkf54eHho6lchPKt8zeiku/uBxl0ASwf1P1fDVoChKZB4Vf3PpSY6nTWRm9w5F2UBxz8CBv8fYGCo3qIAoPnrQORO9T+PuiVe4y5TqHzfafsWcP0njZdBx7MwUM7CQDkLg9pyLskDjiwAbv3GNeaDh1c/4a1vH6AgE3gWrp46dBDvjXo/Pz9ERETg2rVrePvttzF58mTcu3cPEokEAPDWW2/hjTfeQMuWLbF69Wr4+flh06aarwletGgRcnJypD9JSUma+lUIzypfMzqnrBi4uRloN0Nzz9njE+DsCqBCN4fJ6WzWRCFy5SyRAIfeA3ovBSzt1V8UAHiGcSfFdP11eHkd0GHWf/928gfy04HCFxotg45nYaCchYFyFga15PzgOLDjde4SuiHfcyPIatPnS+Dk59wwfcJ/o97ExAQ+Pj4IDQ3FihUr0Lx5c6xduxaurq4AgMDAQJntAwICap2cwdTUVDqbfuUPEQadnW/h+k9A6BTA2Exzz2lhBwSP0NlJ83Q2a6IQuXK+sArw6cmNQNEUkQjw6gA8uaS551S1Z+GA2I0bcv+y0MlA+BaNlkLHszBQzsJAOQuDSnPOTwf2v8V9po7bDTTpJt/jLO25788Xv1NdLTqM90b9qyQSCUpKStCoUSO4ubkhNjZW5v4HDx7Ay8uLp+qINnv1taITCjKBR+e4BramtZgAPDzOrfmpY3Qya6KwOnN+eBLISQJa8TBpXfOxwB0dHoJ/aR3QcXbV2316A4/OABVlGiuFjmdhoJyFgXIWBpXkzBg3we3+aUD7t7kRd4pOfBc0DEi/z8t8MNpG4Ub9+vXr0atXL4wePRqnTp2SuS8jI0OhdQsXLVqE8+fPIyEhAVFRUVi0aBHOnj2L8ePHQyQSYf78+Vi3bh327t2LuLg4fPrpp7h//z6mTp2qaNk6O8yY6LnzXwNdF1R/vZC6VU6ad/JzzT83IfWVlQBc+R7o/zU/x49tI6AgAygt0Pxz11dqFLfSxssTD1UyMOBm+I85rPm6CCGECENWArBzPFCQBozfC7i1UG4/IhHQdwW3dr2kQpUV6hyFGvXr1q3D/Pnz4e/vD1NTU7z22mtYsWKF9P6Kigo8efJE7v2lpaVh0qRJ8PPzQ8+ePXHjxg0cP34cvXv3BgDMmTMHixYtwty5c9G8eXOcOnUKJ06cgLe3EusPR+1V/DFEp+jckK+MOKAgHfBsz18Nbi25Yf9PrvBXgxJ0LmuilBpzLisCDs8BBq0FjM01WpOMgEG62fi9uAboNKfm+1uMAyK2aaoaOp4FgnIWBspZGJTOuaIcuPw9cHQh0OcLbsSYYT1XWBe7cj32V9fXbz86TqFG/U8//YSNGzfi+++/x++//44zZ85g9erV+Oyzz5R68l9//RUJCQkoKSlBWloaTp48KW3QV1q4cCGSkpJQUFCAy5cvo1OnTko9F+7tB8pLlHss0Qk6N+Tr9BdcTznfun+sc5Pm6VzWRCk15nx0AbcMmy3Pl2IFDgHuHuS3BkWl3edO5Nk2qnkbU2vAwVdjswrT8SwMlLMwUM7CoFTOKXeAbSMB8wbA6zu41VdUpeUE4MllIDNedfvUMQo16h8/fowOHTpI/92hQwecPn0aP//8MxYtWqTy4lSq2WggfCvfVRDCSbgIiBsCdvJfrqI2FnZAs1HAjV/4roSQuoVvBWw8gKa9+K6Ea/yaNwCydWiVlYurgU7z6t6u7XTg+kb110MIIUS/lRUBJ5cAl/8PGPYT1wBX9WVzIhHQbwW3vK1AV2BQqFHv4OBQZYm44OBgnD59Gps3b8aCBQtUWpxKBQ0D7v+lm9c/ErnozJAviQQ4vwro8gHflfynxXgg7oTOTJqnM1mTeqmS87NwIO4k0FmLjh1dmjCvsgdDnt4Ru8ZAWSGQl6remkDHs1BQzsJAOQuD3Dk/Pg9sGwV4tANGbASsndVXlG0joEl34NYW9T2HFlOoUd+pUyfs37+/yu2BgYE4deoUjh49qrLCVM7AEGjzP+D6z3xXQtREZ4Z8Re0Bmvape/1NTTIwAHp8yp1J1QE6kzWpF5mcCzKBE4uBweu416u2aNSFG3nDGN+V1O3id0CnufJv3+Z/wI1f1VfPv+h4FgbKWRgoZ2GoM+eiLODwbG7embHbAb/+mims7TTg/t9AzjPNPJ8WUeib0cKFCxESElLtfUFBQTh9+rTS19drRMAg7oxRcQ7flRA1MNCmL/o1KSsCbv/OfVnWNm4tAGML7pokLacTWZN6k+YsqQAOzeKG1pnb8lvUqwwMgIahwNMbfFdSu6wEoKwYcPKX/zGNOgNPr3OPUyM6noWBchYGylkYasyZMW6umd2TgOavA699A5iJNViYIdB3OXBsoW6cbFchEWP6/Rvn5ubCxsYGOTk5EIvF3LrGSdeAHh/zXRpRseLiYpiZmfFdRu3OrwIcmnITbGmjoixg92Rgwv76z0aqRjqRNak3ac6nvgDsfYAWr/NdUvUyHgJXfgAGreG7kpodngO0mQq4NFPscbd+A0SGQMvxaikLoONZr1WUAc9uAY/Po6RhO5j6dOG7IqJmdDwLQ7U55yYDxxYBjv5A53mAkSk/xQHc9+0GXkDIKP5qUJEqbdkaKP2tPTs7G9evX0daWhokL01IIBKJMHHiRGV3q34+PYHrP3HrC1s68F0NUaG4uDgEBwfzXUbN8tOAxKtA5/f5rqRm5rZAyGjgxkag/dt8V1Mjrc+aqERcXByCjRK50VXa2qAHuBN1OU+5kTh8LrFXk5yn3Ak7RRv0ADeJ5o7XuWXuVD2x0b/oeNYjkgogJZIbFZl0HWAVgFsrwCsMZUcWw9T9T8322hGNo+NZGGRylkiA8M1A7BGgz5eAUwC/xQHcUnnbRgJNugFWjnxXoxFKNeoPHz6M8ePHIz8/H2KxGKKXPui1vlEvEnHXFF5cDfRdxnc1RIWMjLS3ZxkAt2xct0Vq+2KsMs3HAdtHAUHD1TuhST1ofdZEJcyLkoHYX4GxO/gupW7+r3FfaIJH8F1JVZfWcl9wlGFsDjRsxV2W06ijauv6Fx3POkwiAdLucY34xCtAeTHgEgI07gK0e0vmJNeL4KmwOrkEGPgdf/UStaPjWRikOac/AP75mJsratwe7ZnzxtAY6PU5Nxv+CGGs5KLUX/7999/Hm2++ifz8fGRnZyMrK0v68+LFC1XXqHpeHbjrC3OT+a6EqJCnpyffJdQs7T5QWgi4h/JdSd0MDICenwGnPue7khppddZENUoL0Ch6HTBoHWBkwnc1dQsaDkRXnUiWd3mp3Gddw1bK76PN/9S65CUdzzqEMe5L/I1fgD1TuBPAd3YBDr7A0B+B8XuAnp8CTbpWGbXi0GY4wCTcxJJEb9HxLAyeDV2Ac18Dp78ABq7mJqjTlgZ9JbcWgE1DbuI8AVDqr//s2TO89957sLCwUHU9mtPlA+56C6I3Hj16xHcJNTvzJdD9I76rkJ9rc27SvIRLfFdSLa3OmqjGsUVI9BrFfSDrAvMGXCMmN4XvSmRd/j+gw3v124fYjev1yHqimppeQcezlstK4OZW2DeNG856cxNg7cp9kZ+wD+jzBdC0F2BqVetuHj16BPT+HDi7kjvJTfQSHc96riQPuPUbJL8N45ZHHf0bYOPOd1U167oQuLYBKMrmuxK1U6pR37dvX9y8eVPVtWiWW0ugOBt48ZjvSoiKmJryOCFHbeLPAHZNAFsvvitRTI+PgXNfcRMdaRmtzZqoxpPLgJEpyj068F2JYpqNBqJ2813FfwoyuLXpPdvVf19tpnFzbagBHc9aJucZELkTODgT+GMEcGkdYGrNrT4xYR/QfyXgP0DhlShMTU0BMxugwyzucjSil+h41kOMcZ/LB2dyJ/eMzJDaYx13uZm2X1JqbAZ0/xg4uZjvStRO7gtfDh06JP3/AQMGYP78+bh37x6aNWsGY2NjmW0HDx6sugrVqct84Pw3wND1fFdCVMDFxYXvEqqSVACX1nBnMnWNuS0QMga4vhEIe4fvamRoZdZENSrKuZNJo7bCpdyQ72oU490DuPoD1zOuDV90rnwPhM1Uzb482nANsZL8OntkFUXHM8/y04GE88DjC0B2IiB2BRp3BXp8wv2/ikhz9u0L3D0APAvnloMkeoWOZz2SmwJE7gAenQU82nGjnO0aAwCc8/L4rU0Rnu25y+MeneUmztNTci9pJ++6kyKRCBUVFfUqSpXqXAbgwNvcBEKKrN1LtFJ0dLT2zbh663du4qC20/iuRDkSCXfN5JAfAGvt+aDWyqyJalz9ETAVAy3H62bO/3zC9V64teS3jsIXwP7p3DXOqjrBcGcPN8JNxe9nOpmzLit8ATy5xDXiM+MAS0egcWegUWe1jiiTybkgE9j7BjB+r27MmUHkRsezjisvBR4eB+7sBgxNuJVnmnTn1n9/ic7lXJIP7BgLjNsFmFjyXY1C5F3STu7h9xKJRK4fRRr0P/74I0JCQiAWiyEWixEWFoajR49K7y8uLsbMmTNhb28PKysrjBgxAs+fP5d7/3LpugA4/7Vq90k0pyATuHsQ+Pt9NL76MRCxQ3uu1SvJ54bihk7huxLlGRgAPRcDJ7Vr0jxzcy1cNozUX14qEHcKaM4tX6eTOTcfx70P8e3aBqD9DNWOGAgcAsQc4k72qZBO5qxrCjK5E2Z/jACOfAAUpANtp3PD6Yf/BLScoPZLxGRytrQHQidzKxHpq7iT3FwEAkPHs45Kuw8c/xjYPpq7BGfQWmDkr4BPryoNekAHcza14lY/O/0l35WojVrXnWjWrBmOHDkCDw+Pau93d3fHypUr0bRpUzDGsHXrVgwZMgS3b99GUFAQ5s6di7///ht79uyBjY0N3n33XQwfPhyXLqlw8i67xtw1Xsm3+e9ZIXUryuau60m4AKTHAhb2QKNOQNi7KK8wBZ6eBvZM5iZ2ajmRG9rH1zDYK98D7d/hJpjSZa4h3JthwiW1LWmlKAcHB75LIOpw8nNu5YV/R4bpZM7OgUDmQ663g68eyOIc4OkNbglNVTIy4ZYqiz/NTYymIjqZsy6QVHBzukRu5+ZGCRkDvL6Tt8+kKjkHDedm0H9+jztu9MmLx8Dl7wEwbuSOjvUM1gcdzzqkOBe4ux+IOQzYNuK+N/f5Uq7vzTqZs09P7tKfpOuAR1u+q1E5uYffK8Pa2hqRkZFo0qSJ3I+xs7PDN998g5EjR8LR0RHbt2/HyJEjAQD3799HQEAArly5gvbt28u1P7mGLOQ8A44uAMZuk7tOoiGlBdzat4/Pcx/8plaAV0fuej+HpjJvPDJDgTIeArf/AFIiAJ/e3JcZK0fN1Z2bAvw1h/sCpQ3X1tZXUTawexLXq6MFJyl0btgXqVvCJeDen8Br/42c0tmcr/3EnVgMGMTP85//BnAOBvz6q37fBRnA4dkq/bzU2Zy11YtHwO1t3Ikd7+7cyBctuHyq2pxzU4A/3+GG4VfTG6iTSgu5Yb5Dvgee3QJyngId3uW7Ko2h41nLVU56F7ENKMriTjr5D6iyBGVddDbnoizu++z4vYCRbkzqKO/we7X21CuioqICe/bsQUFBAcLCwhAeHo6ysjL06vVfb4C/vz88PT1rbdSXlJSgpKRE+u/c3Ny6n9ymIXeG6skVwCusvr8KqY+yYuDpda4RnxIJGJkBnmFAs1FAz6Ba18C0snpp8iaHptzSORXlQNwJbrihSMR9ufHuCRiq+aV/djnXS6YPDXqAW66r+Vjg+s+qm3irHmSyJrqvooybHO+VCSV1NufgkcDf8/hp1Jfkc+uAd/5APfu3dOAm0Ux/ADj6qmSXOpuzNikt5C6NuHuAu0a+5QRuojst+gyqNmexKxA0jLs0QB8avowBR+ZzczU18ATE7sDvQ4E2UxVuNOkqOp61VG4yELGd+37tGQZ0/bBel9zobM7mttylR+e/4d4j9QjvjfqoqCiEhYWhuLgYVlZWOHDgAAIDAxEREQETExM0aNBAZntnZ2ekpqbWuL8VK1bg88+VuP6301zg4DvcDIla9CGolCdXgDPLABMr7uy8rRfQwOvf/zYCLOy053csLwWSb3ET9jy7CYgMuVmW/fpza0sq0Piu9uyVoRG3L7/+QH4at0zPlR+Ahq24YUb23ir8Zf6VGsVdc+rWQvX75lPIWO5aq6DhKp0RWRm1nakkOuj6Ru6kkXkDmZt1NmdLe+49tiCDawRr0s1NQOs31fse324GcP0nYMC3KtmdzubMN8a4nuDbv3O9wYFDgBG/cMvPaaEac245EdjxOvc5rY7PZE26uQmwa8QN8wW4joiWE7lJc9tN57U0TaHjWYuUlwIPjnKT3hlbcJPedZqrklExOp1zwCBuPq7UKMClGd/VqAzvjXo/Pz9EREQgJycHe/fuxeTJk3Hu3Dml97do0SLMmzdP+u/c3Nwar+mXYenAXTscf/q/N2NdlJfKNehf38EdwHkp3BI1WU+Ahye4/xa94LY1MAJs3LmzydJGvxdgpsYDVVLBDYl/fIG7poVJuAZ24y7cme16XIOanJwMOzu7mjewcgI6vsetkfv0JnBpLff3CRwKBA1VzTVvjAFnlgOvrar/vrSNgQHQazFw6nNg2AZeS6kza6I78lK5991xVdd31+mcg0cCUXu5yeo0payIm5xr4kH1Po9LMNeILMquciJGGTqdMx8KMoA7u4CH/wCuzbm5W1Q0akKdasxZJAL6rwSOfqjbl6w9vQk8PgeM3CJ7e/Bwrrc+dLLODPetDzqetcDze9wlqOkxgG9/YPD/cR16KqTzOfdb8e8KMXvVP3pXQ3j/LUxMTODj4wMACA0NxY0bN7B27VqMGTMGpaWlyM7Olumtf/78ea1rYJqamsLUVMk3zbB3uSVWvHvo5odKRRlwaBbXe1J5pt7Gnfvx6lB1+/JSIPfpf43+5Fvcf0vyuN/fyPS/Br+00e+p2BAyiQRIu8s14hMvc8/pGsI14tvNAIzNVPO7Q4GzhiIRNxrAow13zf69P4E9bwDWztwZdfc2yucfdxJwDuIu6dBHLs245cYSLnITFPJEp88QE1knl3Ani6q5tEanc27aB9gxRrON+vCtQKtJtV6mpDItJ3I9xB1m1XtXOp2zplSUcye/IndwJ8NDxvz7ZZT/OU7kVWvOto249aPDtwCt39BQRSqUn869l435o+rxZ2DI5RWxXTd/NwXR8cyT4hwgeh9w/2/Argl3CY5rc7U9nc7nbOXEHZdX/o8bvaAHeG/Uv0oikaCkpAShoaEwNjbGqVOnMGLECABAbGwsEhMTERampuvezRtw67Te/4u/CY7q48RioMU4wNFPvu2NTLgD366GiQzLirgGf3YikJUAJJzn/r/83zkLTKxeGdr/7/VjWQnc2eonl7kTBM6BXCO+1SRuojs1sbCwUPxBJpbc36zFOCAznjuzeWYZd91987HcQS+vinLg8v/p/4SL3T8Cdk8EPNrx9oVSqayJ9km4yK0+UsPwN53O2cgEcPAFnt/lTvSpW3kJEPu3+nvpK/n153of279T76GcOp2zulV+Lj0L50YR9lvJnYDWQXXm3HY6d4lX0z66dWK8ohw49C6XTU0jV0LGAH8M5xpaOnQiRhl0PGuQRAI8ucRNelecy40KGbNNpR1mNdGLnJuPBXZN4CbXdmjKdzX1ptZG/U8//QRn55o/fBYtWoT+/fvD09MTeXl52L59O86ePYvjx4/DxsYGU6dOxbx582BnZwexWIxZs2YhLCxM7pnvldLurX+v7XpNt2Zijd7H9S4HDVPdPo3NuRMENZ0kKM4Fsp9wDf3n94DYo9yQzAae3MmRgatVMjRTXqmpqfVbYsPem+sxrCgH4k9xQwGZhDvofXrXPTzn9m/c319Lr2dUGfMGQOup3KiWfl/x8uWr3llrO+kIl/Pc6g95qdyasZpoHGpKRRlw7usqk+O9TOdzbv461zvXd5n6n+v2H9zzaepzy8AQaNoXiD1S75PgOp+zqlWOILt7kJsXp+UEbqlHXRxB+JI6czYwBPosA44t5N4XdOX3PfMlN9eMSy0zgRsac98P7uwGWo7XXG08oONZQ4qygAMzuOW4u3/EfffWIL3IWSTiTsb9PQ94fZdmRrmpkdyN+nXr1sm90/feew8AMG7cuFq3S0tLw6RJk5CSkgIbGxuEhITg+PHj6N27NwBg9erVMDAwwIgRI1BSUoK+ffti/fr1ctehFBNLrkEftRdoPka9z6UqaTFA5C5g7HbNPq+ZmOth05JJJmxtbVWzI0MjwLcv95Ofzl27eG0D4NqC+3JV3dm84lzuC9iE/aqpQdsFDQUc/YHD7wG+/bhGvgbfDFWWtbZgDMh4wDXin1ziZjCXjnCZzI2a2fsGNwrEzIbvalXj+s9cI7SWE386n7Nrc25IbkW5eq/ZqygD7h3U/PtPywnAgbfq3ajX+ZxVgTHumuzbv3Mn8QKHACM3qXV0m6bJlbOTP+ASwn0HCxml/qLqK+Ywt/KAPN8XW4wHto3kOgp0qdNIQXQ8a0DOU25y795LeZuUWW9ybuDBjQ66+SvQdhrf1dSL3OvUN27cWL4dikR49OhRvYpSJXnX9pNRXgL8MQKYeED7h0kV5wI7x3Ef/ooMFddDaWlpcHJS09+AMW744+3fgZxn3BeuoGH/feE6tRTw7AA07VX7fvSNRMK9ET44zvVGynvpRz2pNWtNYAzIesw14hMuAoUvuL9do87c/BfVNXSTbgBXvgdGbtb5s8nITeFOCI3bXWtvnM7nDACX1nHZ+vZV33Pc+h1gFUDoFPU9R02OzOeur3cNUXoXepGzsvLTgTs7uflY3FoCLSYADj58V6UWcudcUcY1fkf8qvnVIxSREQcc+xAYu0P+SX6v/QSY2+nGCQslCfp41oTn94CjC7jJ7+zka5upg17lLJEAO8YCA1ZpfMSDPORty8rdqNdVSjXqAeDWb9xM7do8qQljwN43uQnnPNvxXQ3voqOjERxcy/A3VXl1PWDfftwQ29c1PFJCm+Q8BY4tApyDuQlH6rGKgTw0lrUq5TzlJoxMuMD1xNk15hrxjTpzS6DJ48Yv3GQ4nd9Xb63qdmAGNzFpbcNVoaM5vyovFTj+MTDyV/Xsv6Ic+GMYMH6f2o+7amXEAZdWA0N+UHoXepGzIirKuUb8nZ3cv0PGAj699GYG5poolHNyBHB1PTD8Z7XWpLSSfGDn68CwnwCxm/yPKysCto/h5r7Q9ZOzNRDc8axJCZeAC6uA4Rt5P+GldzlnxAEnF3OTXWrZpT/ytmXr9QlSWlqKx48fw9vbG0ZGevZh1HwcNwlQ89c1MuGEUi6tBTzDqEH/L3t7ORtG9WViwQ2faz6Wm8Qoag/Q+3PNPLe2snHnroG8ewDYNgLo8Sng0VZtT6exrOsjP43riX98nmvQ2zQEGnXhro21rnkFj1q1ngr8+S43C7Z3D9XWqymPLwBmDeps0AM6knNdrF2A8mLu+kdzNQxXjN4HBAzmp0EPcL3KxTlcj7OVo1K70IucFfHXbMDeB+j/jdJ/M12kUM5uLQBrV+D+EcD/NbXVpBTGuGtwuyxQrEEPcHMVNe3NdQwEDVVLeXwT3PGsKff+5L5vjvlDNUsw15Pe5ezgw61+FbmDmzxbByl1mrCwsBBTp06FhYUFgoKCkJiYCACYNWsWVq5cqdICeWNoxA1lvKmm3pX6enQOSL+v89d/6Dx7b6DbQr2YNbPeRCJu5tVRW7mRLkcWcKsfCEXhC+DeIeDvD4DfhwMnPuMu5enyATBxPzdULmSU8g16gPsbv/YNcHENkJ2kstI1pqIMOP8N0H0R35VoVvAIIFoN17tLKoCIP7jh73wKfQMI38xvDboiai9g7caNaBJQg14p3RZyvfVF2XxXIuvaBm4uocadlXt86ze540W/B8oSVbq+EXh4grv8Tgsa9Hor7F1uMsu853xXohSlGvWLFi1CZGQkzp49CzOz/3qxe/0/e3ceF1XV/wH8M+w7sgrIooCigOKK+77nnqVPallZLolraWHlkrlk7uaWZVlqWSZmlvuauQAqiruIKIjIzrAzzNzfH/cnSQLODHebud/36zWv54GZOfebHw7Muffcc3r1wq5duzgrTnQhLwN3D7PTrKQk7xHw9wp2P3qJTRERU1ZWltglEACwcQaGfMVeXfnpNfZ+e45JIusSJXD7IDu1+seX2XuLi7KAdpOAMb8BwzaxqxxzfX+WhQ0waDV7T/rT7SUNxYVN7BlwLRf7k0TOXAh6id0dhGs3fmdv/xF7NllAD3ZtiPIyvd5uNDm/SG4yexWo62yxKxGFzjmbWwPdP2anxErFg7PsgobtI/Rvw8KWXQSVj98JEiCb/iwEhmHXbMpPYy8MSGidL6PM2dQM6LMQODRH7Er0otegfu/evfjqq6/QqVMnKJ4ZVIaEhODevXucFSc6ExMgfAJwYaPYlfyrvBTYN4XdLo7O1lViNAt2GAv/buxCaA/+AfZMYKfnckSUrFUlQMIxdjXz7a+w/TD3IbsC+Jjf2HumW7/Fzt7g+2Sbsz+7lsbBj/g9DpeUj9lbEZppv6uI0fRpcyv2FpXMu9y1qdEAl7axV8nFplCwi4fe2KvX240m55po1MCf7wP9l0nqg7mQ9MrZrz1gagEknuS8Hp3lpwEnl7AnVWv7O77Nu0DMFqO8Wi+L/iwEtYr9nGHvCfT8VHIX8Yw2Z4+m7GesG7+LXYnO9BrUZ2RkVBlmYWFhpUG+UQjqDzw4x94PKQWHPgbajGMHDqQSlUoldgnkvyxs2C1X2k0C9rzLLijIwYcYQbN+fIW9Cv/zKCD9BrvrwahfgBHbgLbjAfcm4vyxbdSXXajx8nbhj62Po/OBnvN0+rcyqj7dfDT788+V23+xJ84sbLhrszbC/gdc+Vmv/m1UOVfnn9VA8GBZ/+3WO+eec4HTy4GyQm4L0oVaxa5n8tJywNK+9u1ZOQA+bdkTxUZGFv2Zb2WF7Da2DXtL9jZbo865ywfswsRF2WJXohO9BvWtW7fGn3/+WfH104H8N998g/bt23NTmVQoFEDHqey2RGKL+4n9Q9B4gNiVSFJOjkROvJDneTUHRu8GCjPYwXH2/Vo1x3vWRdnAha+BH4YCV3ax62u8vgfoMIXde1wqqxZ3/ZCdwpkaJ3YlNbt/mr0tQ4vF8Z5lVH3auzWQeom9YltbDMOu99Lmndq3xRULW6BuCJASo/NbjSrnqjy6xG5D1Xy02JWISu+cLe2BTtOB44s4rUcnR+ays7K43La17QT2liQju1pv9P2Zb4WZwK4xQLv32BlQEmXUOZtZAj3mAkc+FbsSnei1ZP3ixYvRv39/3LhxA+Xl5VizZg1u3LiBs2fP4tSpU1zXKD7/bsD5Texq1mLtBf/4Krta6kgDuSonAg+PWixARvhnagZ0nAY0GcRuf1e/I9B2kl7bOPGStUYD3D/JXk1VFQPNRrBX5MVaVVwbJqbsfXa/vMHuPmDjLHZFz1Or2KtsI3/U+a1G1acVCnb7wvungYDutWvr7hF25xMurhhyKfxd4NhCnXe+MKqc/6uskL0n/NVtkps+K7Ra5RzYi91dJTkG8GnDXVHaiN/N/q7lerV6ayfAsxn7O8G/K7dti8io+zPfsu+zU+77LwPqBotdTY2MPmefNuwtZQlH2d8/BkCvy02dOnVCXFwcysvL0bRpUxw+fBju7u44d+4cWrVqxXWN0tB5Jrs4nRiKc9hFGwZ/xf5hIVUqKioSuwSiDWd/4LWf2A80O15hT1jpiNOscx4AJxYDPw5hr6j1/gz43w72DLmUB/RP2TgDfT5nPwhoNGJX87zzG9krXFoujvcso+vTT6eo1wbDANGbgfDx3NTEpTq+AKNmF3PVgdHl/KxDHwNdZknzhJvAap1z74XA8c+EXSA0/Sa7GnbP+fy0324yu8K/ETHq/syn1Djgj2nsIrsSH9ADMsm5+xx2tyED2clJ783lAwICsGXLFi5rkTafcODsOnb12jo+wh1XowH2TWX3Qbc1sj0hOaZUKsUugWhLoWAHeoG9gcOfsHv9dvuIXe1YC7XOWlUM3NwPXN/DnlxoPhroFmm4V9K8mrPrf5z6QlrbxSlT2VXRR+m3K4rR9WlHb6BUye6cYOWgXxuJJwGvFoB1HS4r406bd9l7EXtpv2K50eX81M0/2NkUDbqIXYkk1DpnG2f25+v0l0CPT7gpqiYleex6Kq9s1WtGmVZsXdgtcR+cYxcFNAJG25/5dO84cG4Du1aPtZPY1WhFFjlb2LInZY99xm4nLHF63xiqVquxe/duLFy4EAsXLsRvv/2G8vJyLmuTni6z2D8mQvp7ORDYE6hnpDMgOOTl5SV2CURX9nWB4VsA33bAjlfZaYha0CtrhgFSL7MrUO8aA6gKgWGbgaEb2FsBDHVA/1SLMUDBE162ENTb0fns4E7Pf1uj7NPBQ2u3qu75jey9llLl2w54HMeeONOSUeasfAzEfCvM4NNAcJJz8GAgOxFIi699WzVhGPaqac+5/N922X4KcO4rfo8hIKPsz3y6+gtw6Uf2FjUDGdADMsrZvyugLmO3s5Q4vQb1169fR6NGjTB27FhERUUhKioKY8eORcOGDXHt2jWua5QOz2aAqgjIEmjbvrtHgbxkoOVYYY5n4GRx1tBYBfUH/reTvbK1b+oLd5vQKeuibHZNjB+HsfdGtnmH3YKu1Zv6Xy2Vqv5fsAsv1XIhQk4kngJsXNnF0/RklH26yUDg1n793pv0D+DeWNpTuRUKoOkI9oOqlowuZ43m/7ev+4JdcIkA4DDnvkuAw58Cah4vJP2zGvDrqPP6EHqxr8vO4km5yP+xBGB0/ZkvDMMuwp0cDQz/RuuZilIhq5x7f8ZuZ6nDyWox6DWf6J133kFISAhiY2Ph5MSeVcrJycGbb76J8ePH4+xZ7c5mLFmyBHv27MGtW7dgbW2NDh064IsvvkBQ0POrizIMg5deegkHDx5EVFQUhg4dqk/ptdf1Q+DUMuDlzfweJyeJPXP72k+GfwVRIAUFBWKXQGrDyoGd3vTwPLvwW+tx7H3tVfz8vzBrjRpIPMHuGKEuM4xF77hgZgkMWgvsiwD+95N4252Vl7GzjEbuqFUzRtmnLWwBW1f2xItzA93ee+4rNl+pC30Z2DkCaPmGVn+/jC7nCxvZGXZcrpRuBDjL2b4u0GwkcG4d0GkGN20+K/EUkHkXGLKe+7ar03EacPAjdsFTA2d0/ZkPGg1766GNE/u5xwA/58sqZytHdobcXx8ADfsIf/wC7dYv0OtKfVxcHJYsWVIxoAcAJycnLFq0CJcvX9a6nVOnTmHy5Mk4f/48jhw5ApVKhT59+qCw8Pm9SFevXl2xdZ6oXBsCpubAk+v8HUNVDPwxHRi0xuDO3InJx0fAtQ4If3zbsdvfpd8Efn2TvS/7P6rNOvs+u+3Rj8PYBfj6fM5OaWsyyPgH9E/V8WE/IP41S7ytki5sBFq8UeuZEEbbp8Ne033BvOQYwKk+YOfGS0mcMrMEfNppfTuNUeWcFg8kXwBavy12JZLDac5h/wNSYoHMBO7aBIC8FODMSnY/eiE/czp4sTOb9Fg4VmqMqj/zobwU2DsRcG/C3tYrhbGNHmSXc1B/IGgAu6OJGA8t6HWlvlGjRnjy5AlCQipPq0xPT0dgYKDW7Rw8eLDS199//z3c3d1x8eJFdOny78IycXFxWLFiBWJjY+Hp6alPydzqMovds3TENu7bZhjgwGygfQTg5Md9+0YsMzMTjo66r7BNJMjMkl3wLf0mu6p70EtAq7cq9oevlLWqmJ22f20Pu+hQ8zHsiqUG+oeSEwE92JX8Y7cCbcYJe+y8R+w0cT0Xx3uW0fZp3w7sjC+NpuJn+oXOrgH6S3+hngqt3wYOzNJqqy6jyVlVzK52P/xbef/+qQanOSsUQL8l7G0Or+3Svh/VpLyUvf1rwEpxZjl1ms6uQ/LKVuGPzSGj6c98KMkD9oxnfz826it2NbUiy5wbvyTOcZVKAO++8GVa/xZUKpUVjyVLlmDq1KnYvXs3UlJSkJKSgt27d2P69On44osv9K45Ly8PAODs/O/9gkVFRRg1ahTWr18vnT0RnfzYhVNSYrlv+9I2wNEHaGgYeyJKSXGxtO91IXpwbwKM+hVgNMBPI4GMOwCA4qIidtC6fwaw63WgvIRdcG/IenYFYfpADXSaCdw/xc/vqZocnQ/0ms9JBkbbp01M2H3mH57T7vWplwG7uoCDBE5qa8u+LmBuyy5q9gJGk/PR+UCHqYYxm0IEnOdcx5edChv7LTftHZoDhL8LuARw056u6viyt+ek3xTn+Bwxmv7MNeVj9vNKl1kGP6AHKGcpUjCMdvMzTUxMKk1/f/q2p9979mu1Wq1zIRqNBoMHD0Zubi7OnDlT8f0JEyZArVbjm2++qWi/pnvqS0tLUVr67x6mSqUSPj4+yMvLg4MDh4ti5acB+2cCr+3krs1HF9n9EF/dxs1ZZ5nJz8+Hvb292GUQvuSlAAcjARsXlGfeg1m95uyK73TfavWKc9mV/l/5TpiBRuJJ4O4RoO8iTpoz6j6dfR/4ewUwRItVr399k12op44v72VxKvUycGUX0H9pjS8zipzvHAbuHWMXxyNV4iVnzf+f8B2wonb9I24newJK7N0Ksu4Js24Tj4yiP3Mt8y57EWLgasBV+xnNUkY5C0epVMLR0fGFY1mtp9+fOHGCk8KqM3nyZFy7dq3SgH7fvn04fvy4TvfpL1myBAsWLOCjxMrsPdiOef80N3vQFmYBR+ax9//SgF4vaWlp9AvGmDl6s4sIpcXjvtIcDYOaiF2R9FnXYQcZ+yLYRev42msZ+P/F8VbUenG8Zxl1n3ZuABSks/fKWdhW/7q0a+xe54Y2oAcArxbAicVAibLG9RUMPueCDHYRQw5uOTFmvORsYsKuhn8wEhi5Xb8ZQo+vArf+lMYidS4BgMKEXSvAQAd/Bt+fuZYcDZxYxN6WY19X7Go4QzlLj9af8Lp2ffF9cfqKiIjA/v37cfr0aXh7e1d8//jx47h37x7q1KlT6fXDhw9H586dcfLkyefaioyMxMyZMyu+fnqlnhcdpwN73gXqd67dVFONmv3Q3W+JQe1RKTXPztAgRkqhADyboTTLiLfO5FrdECB0OHB8IdCbxxOe5zew229yuE2g0ffpJgOBm/uBsJHVv+af1ewaEYaq+Sj2Kmi7idW+xKBzZhjgz5lA38W0sO0L8JazayDg3ZpdfLL5a7q9tziHnXY/4gfAxJSf+nTVaQbwzyphV9/nkEH3Z67dPgBc+gEY8aPRbaFLOUtPrS4JFxUV4datW7h69Wqlh7YYhkFERASioqJw/PhxNGhQeXufjz76CFevXkVcXFzFAwBWrVqF7777rso2LS0t4eDgUOnBGxtnwDscuHu4du2cWAQ0GQx4NOWmLpny9/cXuwQiEMpaR81G/LugIB/yUtj7w0OHc9qs0eccPBS48Xv1z2fcBkzMAWcD/ndoPAi4/Sc7TboaBp1zzDfs+ggeoWJXInm85tx+ChD/C5D/RPv3aDTsQqy9P2M/z0mFWyN25lP2fbEr0YtB92cuXdzG/n5/dZvRDegBylmK9BrUZ2RkYODAgbC3t0dISAhatGhR6aGtyZMnY/v27di5cyfs7e2RlpaGtLS0isUXPDw8EBoaWukBAL6+vs+dABBNu0nsFaoaPrDU6Naf7NREXc8uk+c8fPhQ7BKIQChrPfT5nP2QwfUWUACni+M9y+hztnJgH3kpVT9/ZjU/+3ALydQMCOhZ48lvg8054za7jkTb6mchkH/xmrOpGTs4P6TDrJbTX7IL7dVryV9d+uo0nZ2lY4AMtj9zhWGAk18AmXeAIRuMdjtd2ecsQXoN6qdPn47c3FxcuHAB1tbWOHjwILZt24aGDRti3759WrezceNG5OXloVu3bvD09Kx47NplQPelWTmwH1hu7NX9vVn3gJhv2Wl7pNbKy8vFLoEIhLLWg5kFMHgdO1W4tIC7du+dYFdmd+d+jQNZ5NxsBHC1ir95WfcATTl71c7QtXyDnYJaDYPMubyU3X52wApaB0dLvOfs0ZRdq+KGFp9D7x4B8lPZn00pqhvCbn+Wmyx2JTozyP7MFXU5+zfWwpZdMNaIfzfIOmeJ0nr1+2d5enri999/R3h4OBwcHBAbG4tGjRph3759WLZsWaXF7sSm7YqBtaIqBnaOAMZEab8QVVkh8NNrwNCNgGM9fuqSmZKSElhZWYldBhEAZV0LSWfYAdawzbW/sl5eBuwYDvxvJ7uYG8dkkbNGDfw4DHjj98p57JvCXgGuGyJebVzaPwMIH1/lyR+DzPnwJ4BPO3ZdBKIVQXIuLwV2vMJOea5uSn1OEvvz+L+fAHMJ/9ylXmbXo3jpS7Er0YlB9mcuqIqBqIlAk0FA01fEroZ3ss1ZBNqOZfU6hVRYWAh3d3cAgJOTEzIyMgAATZs2xaVLl/Rp0rCZWwPBQ6q+2lIVhgH+fB/o8gEN6DmUmPji/ZCJcaCsa6F+J8CjGXBhU+3bOr+eXRyPhwE9IJOcTUzZ6b8psf9+L/chUJpvPAN6AAifAFyoepsug8s58SQ724UG9DoRJGczS6DHXODIp1U/ryoG/pgODFoj7QE9wO4eoUxlt1A2IAbXn7lQlM1uH9v6LVkM6AGZ5ixxeg3qg4KCcPv2bQBAWFgYNm/ejEePHmHTpk3w9PTktECD0eIN4MpP7FniF4newl6t4GIrPFJBo++6BsTgUNa11H4y8Ogi8OCs/m3kpQAPz3O+ON6zZJNz2Cjgys5/v/5nDbu7ijFxb8xu4VeU/dxTBpVzUTa7dWPfRWJXYnAEy9mnDWDpCCQcrfx9hgH+mgV0mGI4W0R2nAb8s1bsKnRiUP2ZC7nJwK9jgZ7zAP9uYlcjGNnlbAD0GtRPmzYNjx8/BgDMmzcPBw4cgI+PD9asWYPFi2V6f7iZBbt1Tw33DQIAHl4Aks8DHaYKU5eMBAUFiV0CEQhlXUsKBTBwFXByif5XgY7M42VxvGfJJme3RuzVeVUJe2WuIB3wai52VdxrNRa4tO25bxtMzgwD/PUBuyCbha3Y1RgcQXPu8TG70GRp/r/fu/g94OQHBPYUro7a8gkHcu4DBRliV6I1g+nPXHhyHdg7iV2vxrOZ2NUISlY5Gwi9BvVjxozBm2++CQBo1aoVHjx4gNjYWKSkpGDkyBr22zV2zUYCN/cBZUVVP5//BDjxOTBwNa8fhOXq6ewRYvwoaw5Y2gMvrWDv3VardHvvveOAgycvi+M9S1Y5B/UHbv/FXpXrOE3savgR2JtdWPE/P28Gk/Pl7UDdUHZaNNGZoDlb2AJdZgHHPmO/TrkIJJ4AOr0vXA1caT8ZOPeV2FVozWD6c23d/xs4/Cm7foNTfbGrEZxscjYgWq7qBsycOVPrRleuXKlXMQbPxBRoPQ6I2fL8hzK1iv3w3P9Lo9yvkhBigNwaAS3GAEfmAv2WaPee8lLgzCp2cTzCnZCXgV/eACwdAO/WYlfDDxMToPEA4OYfQOjLYlejm6x7bN2v/SR2JURb/l2B63uAm/vZNURGbjfM1cjrd2JvySnKrn7xPyKs61HAtT3AyB9p1g6RDK1Xv+/evbt2DSoUOH78eK2K4pIgq98/S6MBtr8MjNgGWDn++/1DHwP1WhneBxkDolKpYG5uLnYZRACUNccOfwp4hmm3wM/fK9kprDzeS/+U7HKOmsguPOjXXuxK+FOaD/z6FjBmd8W3JJ+zWgXsHAkMXgs4eotdjcESJeeSPODbvsDwbwCPUGGPzaV7x4EH59jbCiRO8v25ti5sBp5cAwas0n7HKyNk9DlLiLZjWa1/Gk+cOMFJYUbPxOT/p0ptALpHst+7HsX+Lw3oeXX79m2EhhrwH22iNcqaYz3nAbtGs6ut1zSlPjcZSI4GOs0QpCzZ5Tx0o/HfmmVpD7g2BB5dYlf9hwHkfOoLdkYLDehrRZScrRyB984Zfr/y7w6cW8+epHj2gpEESb4/64thgKPzAVNzYNBaw/+ZqiWjzdmAGeA8JAMQ2AtIvQQUZgEZt4G4n9gFpQghRIpMzdiFfg7MZj80VufoPKD3Atl/mOGNXP5dw8ezu8AYggdnAeVjOilvyIyhXykUbL+58LXYlciTWgX8PpndNaHHJ8bxM0WMDg3q+aBQsPfUn/icXSl38Dr2zB7hFa3EKR+UNQ/s3IEenwJ/TGOvSPxXwjHAoR7gJty/PeVspJwbAKqiip0XJJtzcS5wYrH2602QGkk2Z0PRsA/w4J/KK/pLkNHlXFoA/Pomu5hpm3FiVyMZRpezEaBBPV/qdwJKlED3jwH7umJXIwu0Eqd8UNY88QkH/DoC/6yu/P3yUvZ7XWcLWg7lbMTajANitwKQcM4HPwJ6zqXFbTki2ZwNhULB9puYb8WupEZGlXNBOrBrDNA+AmgySOxqJMWocjYSNKjn0yvfAr7txK5CNkwMcVVbohfKmkdt3gEy7wKJJ//93rmvgFZvsfdDC4hyNmL1O7PrM5SXSjPnq7+w21T5hItdidGQZM6GJmgAu2hedVsnS4DR5Jx1D9j9NtBvqXEvXqono8nZiFAixGj4+/uLXQIRCGXNI4UCeGk5u21dXgq7OF5KLBAyTPBSKGcjplCw96lf+016Oec8AK7uAjp/IHYlRkVyORsiExOg1Vjg4vdiV1Ito8j50SVg/3Rg2GbAvbHY1UiSUeRsZGhQT4xGQkKC2CUQgVDWPLOwAQauAvZNBQ5/zC70KcLCQJSzkWv6KhD/KxLu3hW7kn+py4E/32dPbMl4uyo+UH/mSPBQ4M4BQFUidiVVMvicE44CJ5cCI34EHOuJXY1kGXzORkjUQf3p06cxaNAgeHl5QaFQYO/evZWeLygoQEREBLy9vWFtbY3g4GBs2rRJnGKJ5JmZ0QcwuaCsBeDsD7SdCHg2F3RxvGdRzkbO3BoI6AG/c5HAP2uB1MuARi1uTWdWAaHD2cX8CKeoP3PExBRoPhq4/KPYlVTJoHO+8jMQtxMY8QNgXUfsaiTNoHM2UqIO6gsLCxEWFob169dX+fzMmTNx8OBBbN++HTdv3sT06dMRERGBffv2CVwpMQS+vr5il0AEQlkLpFEfoPNM0Q5POctAhykwHfk94NEUuLEP2DkS+OUN4Pwm4MmNqndi4EtKLJB5Bwj7n3DHlBHqzxwKfQW4uQ8oLxO7kucYZM4Mw57Qe3QJeHkLYG4ldkWSZ5A5GzlRB/X9+/fH559/jmHDqr5X8+zZsxg7diy6deuG+vXrY/z48QgLC0N0dLTAlRJDkJiYKHYJRCCUtTxQzvKQmJwGBHQHes0DxuwGBn/FzhSJ2wHseIVdrCp2K5CZwN8gv7QAODofeGkZ7UHNE+rPHDI1Y29fufKT2JU8x+By1qjZnS4YBuj/BTsTgryQweUsA5KeO9GhQwfs27cPb7/9Nry8vHDy5EncuXMHq1atqvY9paWlKC0trfhaqVQKUSqRAEtLS7FLIAKhrOWBcpaH53K2cmBniTTqw35dlM3uzx39NZCVANi6AQ06syvoO/lxU8ShSKDrh4C1EzftkedQf+ZYs/8BO4azU/EltP6DQeWsKgH2RQABPYDmo8SuxqAYVM4yIZ3fAlVYt24dxo8fD29vb5iZmcHExARbtmxBly5dqn3PkiVLsGDBAgGrJFLh4eEhdglEIJS1PFDO8vDCnG2c2T2in+4TXZAOJP3NTpfNfQg4eAINurKDfAdP3Qu4vhewcWFPFBDeUH/mmJkFEDwEiP8VaP6a2NVUMJici3OBPeOB8PFAw15iV2NwDCZnGZH06vfr1q3D+fPnsW/fPly8eBErVqzA5MmTcfTo0WrfExkZiby8vIpHcnKygBUTMT148EDsEohAKGt5oJzlQeec7dzZxewGrQZe3wN0mwMwGuD458CPLwP7ZwLXo4DCzBe3lfeI3R6s2xx9Sic6oP7Mg+ZjgCs7xV9g8hkGkbMylV27o9uHNKDXk0HkLDOSvVJfXFyMOXPmICoqCgMGDAAANGvWDHFxcVi+fDl69aq6E1paWtKUEJmytrYWuwQiEMpaHihneah1zo712MXtwv7H3hebk8ReyT80hx3YuzYCGnQB/DpUXtFao/n/7eu+ZK96El5Rf+aBuRUQ9BJwYy97oksCJJ9zxm223w9aA7gEiF2NwZJ8zjIk2UG9SqWCSqWCiUnlyQSmpqbQaDQiVUWkzNXVVewSiEAoa3mgnOWB05wVCnY7OucGQMs32EF+5l0g6TSwfwZQqgTcg9np+o8vA436Aq4NuTs+qRb1Z560HAv8/BoQPAwwEX8CrquLs9glVO/hBeDkEuCVreyMH6I36s/SI+qgvqCgAAkJCRVf379/H3FxcXB2doavry+6du2KWbNmwdraGn5+fjh16hR++OEHrFy5UsSqiVQlJyfD0dFR7DKIAChreaCc5YHXnBUKwK0R+2jzDnt1Pv0GcP80+/9bvcnPcclzqD/zxMKGXejt9p//rjshpLxH7MyY+38D+Y9hUlgIOLoAPuHsOhWezaWxovytP4HLO4CRPwKW9mJXY/CoP0uPqIP62NhYdO/eveLrmTPZ/ZDHjh2L77//Hj///DMiIyMxevRoZGdnw8/PD4sWLcLEiRPFKplImJ2dndglEIFQ1vJAOcuDoDmbmAAeoeyDCIr6M49ajwN+eR1oPJD/LRkLMv5/EH+68kKVPT4GHLyQlZQE+3p1geRo4PYB4ORSwMwS8O3ADvLdQ4SfURC7FUiOAV79nm614Qj1Z+lRMAxfm75Kg1KphKOjI/Ly8uDg4CB2OYRH2dnZcHaW8LQvwhnKWh4oZ3mgnOWBcubZ6S8Bj2bsLSVcKs4Bkv5hB/FPt5Ss34kdoDvVf+7lVeZcWgA8PM/eBvPkBmBpB/h1ZNe6cG3E34kIhmGn25eXAD3nS+L2BGNB/Vk42o5lJXtPPSG6Sk1NpV8wMkFZywPlLA+UszxQzjwLHw/sfhto2Kd2g+TSfODBOXYAnn4TsHJkB+Dh49mF5V7QdpU5W9qxq8w/XWm+OBd4cJbdeSLzDmDt/MyJggbcDPLV5cBf7wNujYF2k2rfHqmE+rP00KCeGA2aiSEflLU8UM7yQDnLA+XMMytHoF4rIPEEe4+9tsqKgOQL7JT6x1fZe/R9OwBhowD3JjoPsLXK2boO0Pgl9gGwu1QknQHOrQey7wP2HkD9zuwg39Fbp+NX/DftnQgEDwVCX9b9/eSFqD9LDw3qidGwsbERuwQiEMpaHihneaCc5YFyFkDbiUDUhJoH9eWlQEosO4h/dAkwNQd82gJNBgPdP671onZ65WzrCoQMZR8AoHzMDvJPLmX3lK/j8/+D/C4vXrW+MAuIGg90nMa+nvCC+rP00KCeGI20tDTaYkMmKGt5oJzlgXKWB8pZADbO7JaNSWfY6ewAOw099TI7nT4llv1evVbswL/z++ygnkOc5OzgCTR7lX0A7IJ89/8GjswFCtLZ2wAadGFvC7B5Zgp4zgNgXwTQdwkthskz6s/SQ4N6YjScnJzELoEIhLKWB8pZHihneaCcBdI+gr1SnXqZXZxOrQK8WrBT2dtHsCvR84iXnOv4Ai1Gsw+GAbIT2YX7/poFlOSy983XDQWu7ASGrGdfT3hF/Vl6aFBPjIa5Obdnm4l0UdbyQDnLA+UsD5SzQOzcgHaT2ZXeW49j75EXEO85KxTslXqXAKD1W+wgP+MWewLj1W2Vr9wT3lB/lh7a24EYjfT0dLFLIAKhrOWBcpYHylkeKGcBNezFTq8XeEAPiJCzQsEu6Nf6LRrQC4j6s/TQoJ4YDRcXF7FLIAKhrOWBcpYHylkeKGd5oJzlgXKWHhrUE0IIIYQQQgghBsro76lnGAYAoFQqRa6E8O3BgwewtbUVuwwiAMpaHihneaCc5YFylgfKWR4oZ+E8HcM+HdNWx+gH9VlZWQAAHx8fkSshhBBCCCGEEEJ0k5+fD0dHx2qfN/pBvbMzu2jGw4cPa/yHIIZNqVTCx8cHycnJcHBwELscwiPKWh4oZ3mgnOWBcpYHylkeKGdhMQyD/Px8eHl51fg6ox/Um5iwywY4OjrSD54MODg4UM4yQVnLA+UsD5SzPFDO8kA5ywPlLBxtLkzTQnmEEEIIIYQQQoiBokE9IYQQQgghhBBioIx+UG9paYl58+bB0tJS7FIIjyhn+aCs5YFylgfKWR4oZ3mgnOWBcpYmBfOi9fEJIYQQQgghhBAiSUZ/pZ4QQgghhBBCCDFWNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQZmIXwDeNRoPU1FTY29tDoVCIXQ4hhBBCCCGEEPJCDMMgPz8fXl5eMDGp/nq80Q/qU1NT4ePjI3YZhBBCCCGEEEKIzpKTk+Ht7V3t85Ia1C9duhSRkZGYNm0aVq9ejezsbMybNw+HDx/Gw4cP4ebmhqFDh2LhwoVwdHTUqk17e3sA7D+Eg4MDn+UTkSUnJ9MJHJmgrOWBcpYHylkeKGd5oJzlgXIWjlKphI+PT8WYtjqSGdTHxMRg8+bNaNasWcX3UlNTkZqaiuXLlyM4OBgPHjzAxIkTkZqait27d2vV7tMp9w4ODjSoN3J169aljGWCspYHylkeKGd5oJzlgXKWB8pZeC+6jVwSC+UVFBRg9OjR2LJlC5ycnCq+Hxoait9++w2DBg1CQEAAevTogUWLFuGPP/5AeXm5iBUTKUpLSxO7BCIQyloeKGd5oJzlgXKWB8pZHihn6ZHEoH7y5MkYMGAAevXq9cLX5uXlwcHBAWZmVU8yKC0thVKprPQg8vDsCSFi3ChreaCc5YFylgfKWR4oZ3mgnKVH9EH9zz//jEuXLmHJkiUvfG1mZiYWLlyI8ePHV/uaJUuWwNHRseJB93vIh7m5uSjH/Sb+G5x5dEaUY8uVWFkTYag0Ksw+NRuFmkKxSyECoP4sD5SzPFDO8kA5S4+og/rk5GRMmzYNO3bsgJWVVY2vVSqVGDBgAIKDgzF//vxqXxcZGYm8vLyKR3JyMsdVE6lKT08X/JipBam4nH4Z31/7HiXlJYIfX67EyJoIZ9XFVbAwtcC+u/vELoUIgPqzPFDO8kA5ywPlLD2iDuovXryI9PR0tGzZEmZmZjAzM8OpU6ewdu1amJmZQa1WAwDy8/PRr18/2NvbIyoqqsazQ5aWlhWL4tHiePLi4uIi+DHXx63HjJYz8FqT1/Ddte8EP75ciZE1EcbB+wdhAhPMaz8P14quiV0OEQD1Z3mgnOWBcpYHyll6RF39vmfPnoiPj6/0vbfeeguNGzfGhx9+CFNTUyiVSvTt2xeWlpbYt2/fC6/oEyKU+Ix4WJpaItApEAF1ArD/3n4k5yfDx55u+SBEH/dy7+GPxD+wpvsamJmYwdvWG3dy7qCRUyOxSyOEEEIIkSxRr9Tb29sjNDS00sPW1hYuLi4IDQ2FUqlEnz59UFhYiG+//RZKpRJpaWlIS0uruIpPyFNZWVmCHYthGGy8shHvNX8PALvNxIxWM7Dq4irBapAzIbMmwigoK8CSC0uwoMMCmJmw55vb2rbFvgSagm/sqD/LA+UsD5SzPFDO0iP6Qnk1uXTpEi5cuID4+HgEBgbC09Oz4kH3ypP/cnd3F+xYxx4eQ3P35nC1dq34nq+DL/wd/XEy+aRgdciVkFkT/jEMg8/OfYaIFhGV+lS4Xzju5NxBuYa2MDVm1J/lgXKWB8pZHihn6RF1+n1VTp48WfH/u3XrBoZhxCuGGBSVSiXMcdQq7Ly1E+t7rn/uuXFNxyHiWATaebaDlRndKsIXobImwvj++vdo7t4czd2bV/p+eXk5Onh1wNnUs+ji3UWc4gjvqD/LA+UsD5SzPFDO0iPpK/WE6CInJ0eQ4+y6vQtDA4fC2sz6ueeszawxuslobL22VZBa5EqorAn/Ljy+gITcBLzW+LXnnsvJycEA/wHYn7hfhMqIUKg/ywPlLA+UszxQztJDg3piNDw8PHg/Rl5pHk6nnMZA/4HVvqa7T3fczbmLZCXdIsIXIbIm/EsrTMOW+C34uO3HUCgUzz3v4eEBNxs3lKnLkFeaJ0KFRAjUn+WBcpYHylkeKGfpoUE9MRpFRUW8H+Prq1/j3WbvwkRRfddRKBSY2WomVl1aRbeP8ESIrAm/ytRlmH9uPua2mwsbc5sqX/M0534N+uFQ0iEhyyMCov4sD5SzPFDO8kA5Sw8N6onRUCqVvLafrExGWmEa2ni0eeFrfRx8EFAngBbN4wnfWRP+fRnzJUY2GglfB99qX/M05+4+3XEi+YRQpRGBUX+WB8pZHihneaCcpYcG9cRoeHl58dr+urh1iGgRofXrx4WOw/ab21FcXsxjVfLEd9aEX/vu7YO9hT26+3av8XVPc7Y0tYSXrRfu590XojwiMOrP8kA5ywPlLA+Us/TQoJ4YDT7PGsalx6GOZR00cGyg9XuszKwwpskYfBv/LW91yRWdITZct7Jv4eiDo5jcfPILX/tszoMCBmHfPdqz3hhRf5YHylkeKGd5oJylhwb1xGgUFBTw0i7DMNh0ZRMmhk3U+b3dfLohMS8RD5UPeahMvvjKmvArrzQPX8Z8iQUdFsDUxPSFr3825zC3MFzLvAa1Rs1niUQE1J/lgXKWB8pZHihn6aFBPTEaPj4+vLR7KOkQwj3D4WzlrPN7FQoFZrScgVUXadE8LvGVNeGPhtFgwbkFmNFqBpysnLR6z7M5KxQKhHuEIzotmq8SiUioP8sD5SwPlLM8UM7SQ4N6YjQyMzM5b7NUXYpf7/yK0U1G692Gj4MPGjo1pIW+OMRH1oRfX1/9Gh28OiDUNVTr9/w350EBg2jPeiNE/VkeKGd5oJzlgXKWHhrUE6NRXMz9gnQ7b+7EK41egaWpZa3aeTv0bey4uYMWzeMIH1kT/px5dAZphWkY3nC4Tu/7b84eth5QlilRUEbT/owJ9Wd5oJzlgXKWB8pZemhQT4yGn58fp+3llOTg/OPz6Fe/X63bsjKzwuvBr+Ob+G84qIxwnTXhT0p+Cn64/gM+Cv8ICoVCp/dWlXMfvz448uAIV+URCaD+LA+UszxQzvJAOUsPDeqJ0UhLS+O0vc1XN2Ni2ESdByLV6ebTDffz7tOieRzgOmvCj5LyEnx27jPM6zAPVmZWOr+/qpx7+vbEsYfHuCiPSAT1Z3mgnOWBcpYHyll6RB3Ub9y4Ec2aNYODgwMcHBzQvn17HDhwoNJrzp07hx49esDW1hYODg7o0qULTfkgVSotLeWsraS8JGQXZ6OFewvO2gSAGa1mYOXFlbRoXi1xmTXhB8MwWBq9FG+EvIF6dvX0aqOqnG3MbeBs5YyU/JTalig5KfkpKNeUi12G4Kg/ywPlLA+Us/FTaVRIyE0QuwzyH6IO6r29vbF06VJcvHgRsbGx6NGjB4YMGYLr168DYAf0/fr1Q58+fRAdHY2YmBhERETAxIQmGJDn+fv7c9bWusvrMKXFFM7ae8rH3gdBTkE4nnyc87blhMusCT9+u/sbPGw90KleJ73bqC7nQQGD8Me9P/RuV4rUGjUijkXgUNIhsUsRHPVneaCc5YFyNm7Xs67jvaPv4ccnPyI5P1nscsgzRB0dDxo0CC+99BIaNmyIRo0aYdGiRbCzs8P58+cBADNmzMDUqVPx0UcfISQkBEFBQRgxYgQsLWu3aBkxTg8fcjOtPSYtBnVt68LHgZ/tOt4KfQs7b+6kRfNqgausCT+uZV7D2dSzGN9sfK3aqS7nVnVb4WL6RWgYTa3al5IjD4/gJf+XjO5khTaoP8sD5SwPlLNxKi4vxorYFdh5cye+6PIFJnhPwBfRX9DMUwmRzCVvtVqNn3/+GYWFhWjfvj3S09Nx4cIFuLu7o0OHDqhbty66du2KM2fOiF0qkajy8tpPW9UwGmy5ugUTmk3goKKqWZlZ4Y3gN7Dl6hbejmHsuMia8COnJAerLq7CvPbzYKKo3Z+Y6nI2UZigpXtLXHpyqVbtS4WG0eC3O7/h9eDX0dCpIa5kXBG7JEFRf5YHylkeKGfjcy71HCKORSDcIxyLOi2Cs5UzXMxcEO4Rjj1394hdHvl/og/q4+PjYWdnB0tLS0ycOBFRUVEIDg5GYmIiAGD+/Pl49913cfDgQbRs2RI9e/bE3bt3q22vtLQUSqWy0oPIQ2BgYK3b+DPxT3Sq1wmOlo4cVFS9rj5dkaRMwgPlA16PY6y4yJpwT61RY+7ZuZjdZjYnfaimnAcFDMIficZxVftE8gm092oPazNrvNb4Nfx862exSxIU9Wd5oJzlgXI2HrkluZj7z1ycTjmNdT3WobN354rnAgMDMbrJaBx5cARPCp+IWCV5SvRBfVBQEOLi4nDhwgVMmjQJY8eOxY0bN6DRsNMqJ0yYgLfeegstWrTAqlWrEBQUhK1bt1bb3pIlS+Do6Fjx8PHhZwo1kZ6nJ4L0VVJegr0Je/Fa49c4qqhmM1vNxKqLq2jqkh5qmzXhx/q49ejt1xtBzkGctFdTzj72PsgszjT421gYhsEvt3/ByKCRAAAvOy+Ua8qRViiflYWpP8sD5SwPlLPhYxgGB+4fwAenP8ArjV7Bh+EfwsbcptJrEhMTYWpiilltZuGLGJqGLwWiD+otLCwQGBiIVq1aYcmSJQgLC8OaNWvg6ekJAAgODq70+iZNmtR4v05kZCTy8vIqHsnJtIiDXDw9EaSvH2/8iP81/h/MTc05qqhm3vbeCHIOwvGHtGiermqbNeHe8YfHkV+Wj8EBgzlr80U5G8P2dn8/+hst3FvA1ty24nsjg0Zi1+1dIlYlLOrP8kA5ywPlbNgeFzzG+6fex0PlQ2zsuRHN3JpV+bqnOQfUCUAjp0Y4mHRQyDJJFUQf1P+XRqNBaWkp6tevDy8vL9y+fbvS83fu3IGfn1+177e0tKzYIu/pg8hDUJD+VwczizNxKf0Sevn24rCiF3s79G3svLUTRaoiQY9r6GqTNeHeA+UD/HL7F8xuM5vTdl+Ucx+/Pga9WjzDMNh5aydGNRlV6fut6rbCtcxrKCkvEakyYVF/lgfKWR4oZ8Ok1qix8+ZOLDy/EBEtIjAhbEKNF7mezXlc03HYc3cPskuyhSiVVIOTQf2TJ0/0Wu0yMjISp0+fRlJSEuLj4xEZGYmTJ09i9OjRUCgUmDVrFtauXYvdu3cjISEBn376KW7duoVx48ZxUTYxMv89AaSLjXEbMSlsEhQKBYcVvZilqSXGhozFN/HfCHpcQ1ebrAm3ilRFWHhuIeZ3mM/5LJcX5WxnYQd7c3uDnap+/vF5hLiEwMGi8slnhUKBAf4D8GfinyJVJizqz/JAOcsD5Wx4EnISMPn4ZJiZmOGrnl/B3/HF2xI+m7O5iTmmt5qO5THL+SyTvIBOg/r8/HyMGTMGfn5+GDt2LMrKyjB58mR4enqiQYMG6Nq1q04L06Wnp+ONN95AUFAQevbsiZiYGBw6dAi9e/cGAEyfPh2RkZGYMWMGwsLCcOzYMRw5cgQBAQG6/VcSUoN7ufdQVF5U7RQjvnXx7oIkZRKS8pJEOT4h+mIYBp+f/xzjm42Hh62HKDUMDBiI/Yn7RTl2bW2/uR2vN3m9yuf6N+iPA0kH6D5FQgghvChTl2F93HpsuroJC9ovwIigEXrvWhPiEgJXG1ecSj7FcZVEWwpGh08MU6ZMwdGjR/Hee+9hz549cHR0xL1797Bp0yao1WpMmjQJQ4cOxaJFi/isWSdKpRKOjo7Iy8ujqfhGTqVSwdxc9yuFM07MwAdtPkA9u3o8VKWdlPwULItZhjXd1wg+W8AQ6Zs14daOmztQpi7DW6Fv8dK+NjmrNWpMPDoRX/f+2qD6TmxaLE4/Oo2ZrWZW+5r1cevRum5rtPVsK2BlwqP+LA+UszxQzobhcvplrL+8HiMbj0Qv3146//2sKueS8hJEHIvAqu6rYG9hz2W5sqbtWFan0zG///47NmzYgClTpmDHjh3Yt28flixZgo4dO6JLly5YtmwZfvvtt1oXT4g+9JnydS71HHwcfEQd0APsonnBLsEGv+iXUGh6n/gup1/GlfQreDPkTd6OoU3OpiamCHEJQXxmPG918GHbjW0YGzy2xteMDBqJX27/IlBF4qH+LA+UszxQztJWUFaARecXYd+9fVjRbQV6+/XW64R4VTlbmVlhUvNJWHVxFRelEh3pNKhPT0+v2H/Sy8sL1tbWaNSoUcXzoaGhtNo8MRhqjRpbr23Fu03fFbsUAMBboW/h51s/06J5RPIyizPx1eWvMLf9XElcHR8cOBi/J/wudhlau5JxBd523nCxdqnxda7WrrAys0Kykv6uEkIIqZ0TD09g2olp6FO/D+a1nwdHS0fOj9GqbiuYKkwR/Tia87ZJzXQa1Lu4uCAjI6Pi6yFDhqBOnToVXxcUFMDS0pKz4gjRha4rru67tw89fHtIZorQ00XztsRvEbsUyaPVdcWj0qgw95+5mNN2Duws7Hg9lrY5+zv6I7UwFaXqUl7r4cr3177X+paFUY1HYeetnTxXJC7qz/JAOcsD5Sw9mcWZ+PD0h7iaeRXre65HG482tW6zppynt5qOzVc3o7i8uNbHIdrTaVDfrFkzxMTEVHy9c+dOuLu7V3wdExODJk2acFcdITrQZcpXkaoI+xP345VGr/BYke46e3dGcn4y7ufdF7sUSaPpfeJZc3ENBgcORkAd/hcs1SXnbt7dcDL5JG+1cOV61nW4WrvC3cb9xS8GEOIagiRlEgpVhTxXJh7qz/JAOcsD5SwdDMMg6m4U5vw9B2+Hvo1pLafBysyKk7ZrytnW3BZvhb6Fry5/xcmxiHZ0GtTv2LEDI0eOrPb5unXrSmqRPCIvJiba/zhvu74NY5qMgbmJ9BZzmdFqBlZdXEWrXtdAl6wJdw4lHQIDBv3q9xPkeLrk3K9BPxy8f5DHarjx3bXv8Hbo2zq9Z0jgEOxN2MtPQRJA/VkeKGd5oJyl4aHyIaYcnwJlmRIbem1AkDO3MyhelHOnep2gLFPiasZVTo9LqqdTz3N2dq403f6/+vfvj27dutWyJEL04+//4n01ASC9KB3Xs66jm083fgvSUz27eghxCcHRh0fFLkWytM2acCcxNxH77u3D9FbTBTumLjk7WjrC3MQcmcWZPFZUO7ezb8PO3A6edp46va+nb0+ceHgCGkbDU2Xiov7MLw2jwe3s29h+YztWxK6AWqMWpQ7KWR4oZ3GVa8qx9dpWLI9djg/DP8TYkLEwMzHj/Dja5PxB6w+w9tJalKnLOD8+eZ7ep9Nyc3Nx+PBhbN++HT/88EOlByFiSEhI0Op1G+I24L3m70liga/qvBn6Jnbd2kWL5lVD26wJNwrKCrD4wmIs6LBA0NktuuY8MGAg/kz8k6dqam/rta0Y13Sczu8zNzFHO692OPPoDA9ViY/6M7cYhsH9vPvYdWsXZp2ahfeOvYf9ifvh5+CHujZ18dOtn0Spi3KWB8pZPDeybmDS0UlwtXbFmu5r4GPvw9uxtMnZ0dIRI4JG0FpRAtHr1M0ff/yB0aNHo6CgAA4ODpUGRwqFAm+88QZnBRKiLTOzF/84386+DTWjRrBLsAAV6c/S1BJvhr6Jr69+LeiVUUOhTdaEGwzD4LPzn2Fyi8lwtXYV9Ni65tzBqwO239iON4LfkNxJu8TcRJibmOv9IeuVhq9g7tm56OLdhePKxEf9ufZS8lMQnRaNmLQY5JTkoL5jfYR7hOOTdp9UWuG6E9MJU45PQVefrrx+4K8K5SwPlLPwisuLsTFuI7JKsrC089IX7qzCBW1z7lO/D46eOorb2bc5vwWAVKZXz3v//ffx9ttvY/HixbCxseG6JkL04uvrW+PzDMPgq7iv8HHbjwWqqHY61euEvQl7kZiXCH9Hms72rBdlTbiz7fo2hLmFoYV7C8GPrWvOZiZmaOjUELeyb6GJi7QWbf322rd4p+k7er+/jlUduFi7ICEnAYFOgRxWJj7qz7p7UvgE0WnRiE6LRkZxBurZ1kO4ZzhmtZkFZyvnat+nUCjwYZsPsSx6Gdb2WCvoyS/KWR4oZ2Gdf3weW65uwdiQsYKe9NUl59nhs/HxmY+xvud6Xm4FICy9pt8/evQIU6dOpQE9kZTExMQanz/z6Awa1mkID1sPgSqqPVo0r2ovyppw40rGFdzOuY1RjUeJcnx9ch4cMBj77u3joRr9PVQ+hIbRoIFjg1q1M7rxaKPc3o7684tlFWfhYNJBfHbuM0w8MhHr49ZDoVAgonkENvXahE/bf4q+9fvWOKB/ysfBB609WiMqIUqAyv9FOcsD5cw/tUaNM4/O4P2T7+Nk8kms7bFW8FlcuuTsau2K/g3648cbP/JYEdHrdEnfvn0RGxtLi2EQSbG0tKz2uXJNObZd34Y1PdYIWFHt1bOrh6auTXH4wWH0rd9X7HIko6asCTfUGjW+uvwVvuzypWhT2fXJOcg5CIl5iVCpVTA3lcbuFluvbdV5xfuqBDoFIqM4A3mleZWmVBs66s/PyyvNQ+yTWEQ/jsYD5QM4WzmjjUcbvB36NrztvWvd/pgmYzD52GR0qtdJ6+0Va4tylgfKmT/J+cnYm7AXVzKuoL1ne3wY/qFg/fe/dM15SMAQTDsxDT2UPeDn4MdTVfKmYLS8BLhv379XPjIyMvDZZ5/hrbfeQtOmTWFuXvmD0+DBg7mtshaUSiUcHR2Rl5cHBwcHscshPMrPz4e9vX2Vz/1y+xcoFAq82uhVgauqvTJ1Gd47+h7W9lgLG3OaHQPUnDXhxk+3foK5iTleafSKaDXom/P2G9vhZeeFHr49eKhKN6kFqVh9cTWWdV3GSXunkk8hITdBrwX3pIr6M1CoKsTFJxcRkxaDu7l34WDugNYerRHuEQ4/Bz9eTqwl5CRgw5UNWNF1hSAn7ihneaCcuVVcXoyjD47icNJhOFk5YWjgULRwbyH6ujH65Pyo4BEWX1iMdT3WwURBWx9qS9uxrNaDem33nVQoFFCrxdkupSo0qJePa9euITQ09LnvF5QVYPrJ6djUa5PB3stz5tEZxKTFYEarGWKXIgnVZU24kVWchY/PfIwNvTaI+odX35yzS7Kx+MJiLO+6nIeqdPP5+c8xvOFwzu7x1zAajD88Hpt6G+7vs/+SY38uLi9GXHocYtJicDP7JqzNrNGqbiu08WiDwDqBgvW7jVc2ooFDA/Rr0I/3Y8kxZzminGuPYRhcz7qOqLtRSC1MRW+/3uhbvy9szW3FLq2CvjnvvLkTZiZmGBE0goeqjJO2Y1mt/2poNBqtHroM6Ddu3IhmzZrBwcEBDg4OaN++PQ4cOFDxfElJCSZPngwXFxfY2dlh+PDhePLkidbtE2EUqYrwz6N/sOriKkw8OhHzz85HXHqc4PeBW1tbV/n9rde24s2QNw36A3Cnep2QWpCKxFy6Vw2oPmvCjbWX12JKiymin0nXN2dnK2doGA1ySnI4rkg3TwqfILskm9NF+0wUJuju2x3HHh7jrE2xyaU/q9QqHHlwBDNOzMBHpz/C7ezb6OnXE1/1+Aoru63E6Caj0cipkaD97p3Qd7D77m5B+ooYORepijDz5EzaHlZAcunPfMguycaPN37EhCMTcDjpMEY3GY2NvTbi5YYvS2pAD+if8/8a/w8nkk8grTCN44qMk0qtwqrYVVq9Vusr9fpo2rQp/vrrL/j4VL1tyh9//AFTU1M0bNgQDMNg27Zt+PLLL3H58mWEhIRg0qRJ+PPPP/H999/D0dERERERMDExwT///KN1DXSlnnul6lJcSb+C6LRo3Mi6ASszKzR3a462nm3R0KkhkvOT8XvC74jPjEcHrw4YFDBIkK2w8vLy4OhY+T7TtMI0LL6wGGt7rOX9+HxLLUjFkgtLBF+xWIqqyppwIy49DvsT9+OTdp+IXUqtcj764CieFD3B6CajOa5Ke19Ef4GXGryEpm5NOW23oKwAs0/PxoZeGzhtVyzG3p/v5tzFnrt7kJiXiK7eXTHAf4Ck1kS4lnkNP936CYs6LeL1OELnzDAM5pyZgzqWdeBh64GxIWMFO7acGXt/5ppao8bZ1LP4494fKGfKMdB/IDp7d4a5iTTWhKlObXK+n3cfay+txcpuK2X/ebYmaYVpmH9uPvp79MfQpkNfOJbl9dJlUlISVCpVtc8PGjSo0teLFi3Cxo0bcf78eXh7e+Pbb7/Fzp070aMHe1/kd999hyZNmuD8+fNo164dn6WTZ6g0KlzPvI4Ljy8gPjMeJgoThLmFoZtPN0wMm/jcFXA/Bz9MbTkV5ZpynE09iy+iv4CG0VT8ouLrinlycvJzv2C+uvwVJjefzMvxhOZl54Vmbs1w6MEh9KvP/1RJKasqa1J75ZpyrI9bL4lp60Dtcu7q3RVTjk8RbVCfWZyJ1IJUzgf0AGBnYQc/Bz9cz7qOEJcQztsXmjH2Z2WZEgfvH8Txh8fh6+CLYYHDJLfN4lOhrqFwsXLB6ZTTvK6gLXTOO27uQGPnxng9+HWMPzIeI4NGwsrMSrDjy5Ux9mc+PFQ+xN6EvbiaeRUdvTpidvhsQS6AcaU2OTdwbIAQ1xDsT9yPQQGDXvwGGTqbehbfXfsOn7T7BE5w0uo9kpmPrFar8euvv6KwsBDt27fHxYsXoVKp0KtXr4rXNG7cGL6+vjh37ly1g/rS0lKUlpZWfK1UKnmv3dioNWrcyr6FC2kXcCX9CtSMGqGuoQj3CMfboW9rvaK0mYkZunh3QRfvLsguycb+e/sx6egkNHFpgqGBQznfe93Ozq7S19ezrsPMxAxBzkGcHkdMY0PGYtLRSehSr4usF837b9aEG7/c/gX96veTzFXE2uRsbmoOXwdf0fZ1/+H6D7xeGRzVeBQ2Xd3E+9VVIRhLf9YwGsSmxeL3e78jvywfLzV4CWt6rIGlqfRXA3+v+XuYfGwyWri3gL0FP4ucCZnzxScXEZ8Zj6Wdl0KhUGBY4DDsubsHo5qIsz2nnBhLf+ZDkaoIRx+yi965WrtiaOBQTGkxxSCvVtc25zdD3sR7R99De6/2BnUyg28aRoOvr36Nx4WPsbbHWlibWWs9lhV9UB8fH4/27dujpKQEdnZ2iIqKQnBwMOLi4mBhYYE6depUen3dunWRllb9fRhLlizBggULeK76xcrUZZh1ahbKmXKYwATuNu6oZ18P9ez+fdSxrCOJjqxhNLibcxfRadG4nH4ZJeUlaOLSBOEe4RjVeBQnZ7adrZzxRsgbeD34dVzLvIbtN7YjrTCtYvEPLgaoz05JYRgGG+I2YH77+bVuV0osTC3wdujb2HR1E2a2mil2OaKhW2m4l1WchdMppyU1pbu2OQ8JGIJ99/ZhZmth+0pOSQ4S8xJ5Pa6Pgw+Ky4uRWZxp8B+IDL0/pxWm4feE3xHzJAat6rbC5OaT4WXnJXZZOrEys8KksElYfXE1Pm3/KS/HECrnjKIMbIzbiDU91lR8xupXvx8mHJ2AVxq9AgtTC0HqkCtD789cYxgG8ZnxiEqIwpPCJ+jt1xvLuiwz+Asztc3ZzMQMM1vPxPLY5VjaeSlHVRm23JJczD83H128u2BCswk6jxFFH9QHBQUhLi4OeXl52L17N8aOHYtTp07p3V5kZCRmzvz3g5RSqaz2nn4+fRnzJYYGDkV33+5Qa9TIKM5ASn4KHhU8wumU03hU8Ai5pblQQAFThSk87TwrDfjr2dWDnQU/ZzsZhsF95X3EPI5B7JNYFKgK0LBOQ4R7hmN4w+G8/qJRKBRo6tYUTd2aVmzTMfv0bLhYu2Bo4FA0d2uu94mO1NRUODs7AwBOJJ9AqGso3GzcuCxfEjrW64jfE35HYm4i/OtwO9vBUDybNeHGmktrMKWl+IvjPau2OQe7BGP1pdUo15QLulDmjzd+xOvBr/N+nBFBI/DL7V/wXvP3eD8WnwyxP5epy3Ai+QT+SvwLNuY2GBI4BO82e1dS/UdXrT1a42DSQcSkxaCNRxvO2xciZ5VGhXln52FOuzmVFhYzNTHFQP+B+P3e7wa5ta0hMcT+zIes4izsT9yPM4/OINglGG8Ev4EGjg3ELoszXOTc2LkxvGy9cOzhMfT07clRZYYpPiMeqy+txgetP9D7Vi3RB/UWFhYIDGSnRrZq1QoxMTFYs2YNRo4cibKyMuTm5la6Wv/kyRN4eHhU256lpSUsLcWd6rbv3j7YW9iju293AOwfEw9bD3jYeqA1Wj/3epVahceFj5FSkILUglTEZ8bjUf4jFJYXAgCsTK1Qz64evOy82AH//1/x12VKX0p+CqLTohGdFo3c0lw0cGiAcI9wfNr+UzhYiHNW1drMGoMCBmFQwCAkK5MRlRCFDXEb0N6rPQYHDNb56tPTs4YqjQo7b+40isXxqjOj1YyKBQClMNtDaHQlgFuX0y/DwtRCcvdn1zZnhUKBDl4dcC71HDp7d+aoqpopy5S4mX0TU1pM4f1YbT3a4tv4b1GmLjPoq4+G1J9vZ99GVEIU7ufdR3ef7vis42eSuV2FC9NbTse0E9MQ6hoKazNuVzEXIueVsSsxrOGwKm/vG+A/AJOOTMLQwKGSX4TMkBlSf+ba07Wk9t3bB4ZhMChgEEY3GW3Quy9Vh6ucJ4RNwOSjk9G6bmuj+l2qLYZhsOv2LsSkxWBV91W1GpNJ7qdMo9GgtLQUrVq1grm5OY4dO4bhw4cDAG7fvo2HDx+iffv2IldZvVvZt3D0wVGs6qbd9gPAv/d++jr4Vvl8cXkxUgtS8ajgEZLzk3Hh8QWkFqaiVM2uHWBnbod6dvXgbe9dMfA3U5gh9kksotOikVGcAW87b4R7hGN2m9lwtpLeGVQfBx9MbTkVao0a5x6fw7KYZSjX6LYKqI0NO8Pg19u/YmDAQIOf2lQTTztPhLmH4VDSIUH2F5aap1kL6elGIcZ2EqVcU44NcRskszjes7jIeaD/QKy4uEKwQf2OmzswqvEoQX5OFAoF+tXvh4NJBzE4YDDvx+OLGP1ZF8oyJf5K/Asnkk+ggWMDDAscZlRrtTzLzsIOb4a8ifWX1+ODNh9w2jbfOR+4fwDmJubo7de7yufNTczRt0Ff/Jn4J4YGDuW1FjmTen/mwwPlA+xN2ItrmdfQ0asjPgr/yOBvi3oRrnK2NLVERIsIrLq4CvM7zOekTUNRpCrC5+c/R6BTIJZ3XV7rzw28Duo3b96MunXrVvt8ZGQk+vfvD19fX+Tn52Pnzp04efIkDh06BEdHR4wbNw4zZ86Es7MzHBwcMGXKFLRv316yK9/nlebhy5gvsbzrcpiamHLWrrWZNQLqBCCgTkCVzyvLlOygP/8RbmffxvGHx6HSqNCqbitMaTEF7jbunNXCN1MTU3Sq1wmd6nVCTkkO/kz8E5OPTkZj58bs4no1TDdPS0uDhYMFTiSfwKZemwSsWhxvBL+BmSdnIq80D68GvWrQ0z51lZaWBldXfv9gMgzz3AwXD1sPzG8/36gG9rtu70L/Bv0leYaci5zdbNxQUl4CZZmS91lJBWUFiEuPw8RmE3k9zrMG+A/AtBPTMMh/kMH+XArRn3WlYTSITovG7wm/o0hVhP7+/bGuxzqDnhGhrc7enXEo6RDiM+I53b2Bz5wTchLwZ+KfWN19dY2vGxIwBO8dew+D/Adx+jmN/EuK/ZlP265vw/XM6xgdPBpTW0w12N/DuuIy5+buzXEo6RDOpp5FB68OnLQpdYm5iVh8YTEmhE3g7HYnrfepX7tW+6nMU6dO1ep148aNw7Fjx/D48WM4OjqiWbNm+PDDD9G7N3uWtaSkBO+//z5++uknlJaWom/fvtiwYUON0+//S6h96jWMBh+c+gDjQschxFVaU1gNHcMwuJF1A1EJUXhU8Khicb1n75cDgEePHmHX413oUK8D2nlK88QP1zSMBr/c/gWnU07jgzYfcL6jgFQ9evQI9erV47zdtMI0dhD/OBqZxZnwtmdnuLT2aA1nK2d8G/8tbM1t8b/G/+P82GLILM7EJ/98gg09N0jypBBXOR+4fwAFqgLe76X9Jv4b+Dv6o4dvD16P819rLq1B53qd0bJuS0GPyxW++rM+Hhc8xt57e3Ex7SJae7TG0MCh8LDV/jOHscgtycUHpz7Ahl4bODuRwVfO+WX5mH5iOr7o8oVWV0d33twJR0tHDPAfwHktRFr9mU8aRoMVsSvgaOmId5u+K5vB/FNc51ykKsKU41Owrsc6o55pC7CfSfYn7sf89vO1WvtL27Gs1oP6Bg20W9xBoVAgMTFRq9cKQahB/aYrm+Bm7YbhjYbzdgzC3opw7OExHLp/CE5WThgaOBQt3FtAoVDgStIVbEvahpXdVopdpuDSCtOwLGYZGjk1wrjQcVpvO2io0tPT4e5e+xkomcWZiEmLQXRaNB4XPEZd27oI9whHG482Vc5wYRgGs0/Pxugmo9HcvXmtjy+2T//5FK81fg3BLsFil1IlrnIuKS/BjJMzsLHXRg6qqlqRqgjTTkzD172/FvzDXVphGlbGrsSyrssEPS5XuMpZX6XqUpx4eAJ/3f8LduZ2GBo4FK09WkvyRJeQDiUdwr3ce5wtxMhHzgzDYNbpWRjTZIzWv5NLyksQcTwCX/f+WvYZ80Hs/iyEMnUZ5p+dj9YerfFyw5fFLkcUfOR8LvUcTqecxofhH3LarlSo1Cosj10OSzNLTG0xVeu1FrQdy2o9/f7+/fvavlR2zjw6g7TCNEwME27KpVxZm1ljoP9ADPQfiOT8ZPye8Ds2XNmAdp7tcD7xPOZ0nSN2iaLwsPXAiq4rcCjpECYdm4QpLaYgzC1M7LJ4o+8fk7zSPMSmxeJC2gU8UD6Ai5UL2ni0wTtN30E9uxefcVYoFJjbfi5mnJiBpV2WGvQ9c5eeXIKVqZVkB/QAdx8arMys4GHrgaS8JNR3rF/7wqrw651f8UqjV0S5WuNh6wETExOkFqQa3FZqgHiDgNvZt7Hn7h48UD5AD98e+LzT56ItHCtFffz6YPaD2biTcweNnBrVuj0+ct56bSta1W2l00lWKzMrdK7XGUcfHEWf+n04rYcY/6C+oKwAkX9H4tWgV9HFu4vY5YiGj5zbe7XHoaRDuJx+GS3cW3DattgeFzzGgnMLMCJoBG+z+bS+Ul+VsrIy3L9/HwEBATAzk9yaewD4v1Kfkp+Cz859hnU91+m0Gj3hjlqjxoXHF3Av7R5eb8X/NlJSl1eah5UXV8LazBpTWkx57jYFY/D48WN4enq+8HUFZQW4lH6J/fnIvQcHSwe0rtsabT3bwtfeV+8BWEJOAlZfWo3V3Vcb5Kq25ZpyTDo6Ccu7LpfkvfRPaZuzNuLS43A65TSmttTu9jBdlJSXIOJYBL7uI96Vv7j0OBx/eBwzW8988YslhsuctXXpySV8d/07RDSPMNpF77iQUZSBT/75BOt7rq/17zqucz7/+Dz+uPcHPu/4uc6/y4tURZh+Yjo2994su2nTfBOjPwsloygDc87MwZQWU9DMrZnY5YiKr5yVZUrMPDET63utN5px1T+P/sH317/H3HZz4eOg+zbr2o5l9fr0UVRUhHHjxsHGxgYhISF4+PAhAGDKlClYunSpPk0apJLyEnx27jPM6zDPaH7wDJGpiSk61OuAXl69xC5FEhwtHbGgwwJ09e6Kqcen4nTKabFLEkxxeTHOpp7F6ourMenoJMw7Ow/J+ckYFjgMG3ttxLIuyzAiaAT8HPxq9UEu0CkQA/wHYO0lw9w2cdftXXipwUuSHtBzLcwtDPGZ8dAwGs7b3nN3D4Y2HCrqVN4wtzDcybmDIlWRaDUYivyyfKyPW48lnZbQgP4F3Gzc0K9+P2y/sV3sUipJK0zDN/Hf4JN2n+j1u9zG3AbhnuE4mXyS89qIcbqfdx8f/f0R5rSdI/sBPZ8cLBwwqskobL6yWexSak2tUWN93HocfXgU63qs02tArwu9PoFERkbiypUrOHnyJKysrCq+36tXL+zatYuz4qSMYRgsjV6KsSFjtZq2S/iXlZUldgmS0t6rPb7q+RVi02Ix5+85yC7JFrskzjzNukxdhpi0GGyI24D3jr6HyL8jcTfnLvrW74uvenyFFd1WYHST0Qh0CuT8akz/Bv2h0qhw5MERTtvlW2ZxJv5+9DeGBA4Ru5QX4rJPKxQKtK7bGjFpMZy1CbA/g8cfHke/+uJuLalQKDAwYCD2J+4XtQ59CP27e2n0UkxpMQV2FnaCHtdQDQ0cikvpl/BA+aBW7XCVc5m6DPPOzsPcdnNhbWatdzv/C/offr79M2oxYZVUwRg/i13NuIolF5ZgaeelaOCo3Rpjxo7PnHv49kBqYSpuZd/i7Rh8yynJwYyTM1DPrh7mtZ8HKzOrF7+plvQa1O/duxdfffUVOnXqVOmDckhICO7du8dZcVL2293f4GnriY71OopdCvl/xnwPl76szawxs/VMjAkeg49Of4Q/7v1h0B9gGIZBfEY8juQfwZRjU/D+qfdxJeMKOtbriDU91mB199UYGzIWTVyaCLJd0czWMxF1NwqJedJZHPRF1lxag6ktphrEAlFc9+nBAYOx794+Ttv8/d7vGOA/QBK3YfT164vDDw4bXB8X8nf3/sT9qGdXzygWuhSKQqHAh+EfYlnMslrNdOEq52Uxy/Ba49fg6+Bbq3bsLOzQ3K05/kn9h5O6CMvYPoudSj6FLVe3YGW3lVqtVC4XfOc8q/UsrIxdCZVGxetx+HAl4wo+OPUBJjefjKGBQwU7rl6f6jIyMqoMs7CwUBb3Jl3LvIazqWfxbrN3xS6FPEOlMryOL5Rgl2Bs6LUBmcWZmHZiGlLyU8QuSSeZxZnYem0rxh8Zj+PJx9HEvglWdFuBdT3W4Z2m7yDMLQzmJsKv+G9uYo4FHRZg8fnFKFQVCn58XV18chHWZtaSXhzvWVz3aU87TyjLlJxlpdKocOj+IQwMGMhJe7VlbmqONnXb4FzqObFL0YlQv7sfFTzC/sT9GN9svCDHMyb17Oqhg1cH7L6zW+82uMh5b8JeOFo6optPt1q3BQCjmozCjps7DO5EmJQZ02exPXf34FDSIazstpJm9vwH3zm7WLtgcOBgbLu+jdfjcIlhGOy4uQPbb2zH6u6rBb+9S69BfevWrfHnn39WfP10IP/NN9+gffv23FQmUTklOVh1cRXmd5hvEFe65CQnJ0fsEiTNzMQMb4W+hQ9af4Avor/AtuvbUK4pF7usaqk0Knbhr5MzK7br29RrE6a1nAZveHO2d3Jtudm44b3m7+Gzc59J+oNhuaYcm65swuTmk8UuRWt89Onefr05u2Xiz8Q/0ad+H1FOKFXn1aBX8eudX8UuQydC/O5Wa9RYdH4RPm77sSRmVRii1xq/hhPJJ5BWmKbX+2ub882smzj+8DjeC+Nmiz2AXYOmiXMTRKdFc9am3BnDZzGGYbD5ymbcy72Hzzt9bvTbBOtDiJwHNBiA65nXDWI2ZKGqEJFnIlGuKceyLstgb2EveA16jUoXL16MOXPmYNKkSSgvL8eaNWvQp08ffPfdd1i0aBHXNUqGWqPG3LNzMbvNbNr2RoI8PDzELsEg+Dr4Ym2PtXCwcMDkY5NxO/u22CVVkpibiBWxKzD56GSkFqTi03afYlmXZehUr1PFlHqpZd2ybks0dW2KH278IHYp1fr51s8GtzgeHzn38u2Fow+O1rodtUaN/ff2Czq1ThvOVs5wsHRAUl6S2KVoTYj+/O21b9G3fl/42PO7UJExM1GYYFabWfgi+gu9TmDWJue80jwsj12Ozzp8xvmtVa8Hv44fb/zIaZtyJrW/z7pSa9RYdGERrMysMKvNLLqAVw0hcn5668+XMV/yssgtVxJyEjDt+DSMaDQCY0PGijZrXa+f1E6dOiEuLg7l5eVo2rQpDh8+DHd3d5w7dw6tWrXiukbJWB+3Hr39etNquRJVVESrPmtLoVBgWMNhWNRpEbZe24o1l9agpLxEtHoKVYX47c5vmHR0Enbe2ol+Dfphc+/NGBM8Bk5WTs+9XopZj24yGreyb3G+EBsXMoszcSb1jEEsjvcsPnK2MbdBHcs6tb4F5WDSQXT37S6ZGSPPGtV4FHbe2il2GVrjuz/HZ8QjMS8RgwMG83ocOfB39EeIa4heCzLqm7OG0WDe2XmY2Wom6ljV0auNmjhZOaGBYwNcenKJ87blSIp/n7VVUl6CD//+EC3cW2BsyFixy5E0oXL2sPVAd5/u+OnWT4IcT1f7E/dj9aXVWNplKVrWbSlqLXqffgoICMCWLVsQHR2NGzduYPv27WjatCmXtUnK8YfHkV+WTx8KJEypVIpdgsFxtXbFF12+QDPXZph8bLKgA1KGYXDxyUV8+s+n+Ojvj2BlZoVV3Vbhk3afIMQlpMYznVLMWqFQ4NN2n2Lz1c14UvhE7HIqWX1xNaa1mGZwVxz4ynlI4BD8kfiH3u/XMBpEJURheMPhHFbFnSDnIKQWpCK/LF/sUrTCZ38uUhVh9aXViAyPlMWaP0IYGzIW++7tQ1axbqtf65vz5iub0cW7C0JcQ/R6vzbGhow1qHt3pUyKf5+1kVeahxknZ2B4w+EY4D9A7HIkT8icX2n0Cs6lnsOjgkeCHfNFytRl+Pz850jMTcTq7qvhau0qdkn6D+rVajV2796NhQsXYuHChfjtt99QXi7d+3Nr44HyAX65/Qtmt5ktdimkBl5eXmKXYLC6+3bHmu5rcDjpMBacWwBlGX+/rNOL0vFN/Dd498i7OJd6DhOaTcC6HuswwH+A1lt+SDVrG3MbfNL2E8w/Nx8qtTQWC4pNi4WNuQ2auDQRuxSd8ZVzq7qtcOnJJb3XQDj64Cg61+ssyBY1+hoWOAxRd6PELkMrfPbnZTHLMDFsokHddiJ15ibmmNlqJr6M/VKn9+mT898pfyO9OB0vN3xZ5/fqwtXaFZ52nojPiOf1OHIg1b/PNXlc8Bjvn3wfU1tMRXsv414bjCtC5myiMMHsNrOxLHqZJNYuelTwCFOOT0Hnep0xteVUyazToteg/vr162jUqBHGjh2LqKgoREVFYezYsWjYsCGuXbvGdY2iKlIVYeG5hZjfYT4tlCFxhnp2WCrsLOzwcbuPMThgMGaenMnJfcdPqdQqHHtwDDNPzsSK2BUIdg7G5l6bEdEiAt723jq3J+Ws6zvWxysNX8GKiyvELgUqjQqbrm5CRIsIsUvRC185myhMEOYWhsvpl3V+L8Mw+PXOr3i10as8VMadbj7dcPrRaag1arFLeSG+cj7y4AgcLR3RxqMNL+3LWROXJvCy9cKxh8e0fo+uOafkp2D7ze34KPwjXcvTy1shb+G7698JcixjJuW/z1W5m3MXn/zzCeZ3mG+QJ7/FInTOvg6+aFm3JX6/97ugx/2v0ymnseDsAnza7lN09ekqai3/pdephXfeeQchISGIjY2FkxN7v2tOTg7efPNNjB8/HmfPntWqnSVLlmDPnj24desWrK2t0aFDB3zxxRcICnr+nnWGYfDSSy/h4MGDiIqKwtChQ/UpXScMw+Dz859jfLPx8LA17IU/5KCgoEDsEoxCC/cW2NBzA7bEb8HBpIOY1XoW6trW1aute7n3sOfuHtzNuYuuPl0xt91cTu6JlHrWPf164mrmVexP3I+B/uJtd/bzrZ8x0H+gwS7syWfOgwMGY+u1rTrfA3cy+STaeraFjbkNP4VxxNTEFJ3rdcaplFPo4dtD7HJqxEfOaYVp+PX2r1jfcz3nbRPWhLAJmHx0MlrXba3VTAhdci4pL8Fn5z7D/A7zYWlqWZsytVbXti6crZxxM+smDe5qQep/n58VkxaDb+O/xZddv4SzlbPY5RgUMXIe3WQ0Io5FQKVRwVTB7YKZ2ribcxcqjQrreq4T7PeSLvQa1MfFxVUa0AOAk5MTFi1ahDZttD8jfurUKUyePBlt2rRBeXk55syZgz59+uDGjRuwtbWt9NrVq1cLfj/czls70dCpIcI9wwU9LtGPjw+taswVC1MLTG4+GXdz7mLe2Xno4dsDrzR6Rat7sgvKCnAg6QCOPTwGHzsfDGs4DE2cm3Dafw0h6yktpmDGiRloWKehKItrZhRl4GzqWYMe1PCZs6+DL9KL0lFcXgxrM2ut3sMwDH6+/TNWdBV/FoY2hjUchjl/z5H8oJ7rnDWMBovOL0Jk20iaYccjS1NLRLSIqNjm90W0zZlhGCyJXoI3Q96El52wU7nfDn0bqy6uwpdddbu1gPzLEP4+A8DhpMM4cP8AVnZbKfmTtFIkRs5mJmb4rONnuJYpzqzw3n69RV8MryZ6DeobNWqEJ0+eICSk8qIl6enpCAwM1LqdgwcPVvr6+++/h7u7Oy5evIguXbpUfD8uLg4rVqxAbGwsPD099SlZZ5fTL+NK+hV80eULQY5Hai8zMxOOjnTfJJcaOjXE+p7rsev2LkQci8CsNrPQwLHBc69jGAaxT2KxN2EvlGVK9K/fH6u7rebtnmNDyNrMxAzzO8zH7NOzsar7KsGvlq++tBrTWhre4njP4jvnnr49cfzhca0XRfon9R80d2sOOws73mrikoOFAzxsPXA7+7akd23hOucfrv+Azt6dq/xdRbjV3L05DiUdwtnUs+jg1aHG12qb8+67u1HPrh461Ku5PT542XnB1twWd3PuoqFTQ8GPbwwM4e/zzps7cSfnDpZ1XQZzEzrxpw+xcna3cZf8iWqxaP1pT6lUVjyWLFmCqVOnYvfu3UhJSUFKSgp2796N6dOn44sv9B8E5+XlAQCcnf+dAlNUVIRRo0Zh/fr1gu19mVmcifWX12Nu+7m0Wq4BKS4uFrsEo2RqYopRTUbh03afYu2ltfj66tcVi8A9KXyCLVe34N0j7yImLQbvNX8P63qsw0v+L/G6iJihZO1i7YJpLadh/tn5gu6xGpsWCztzOzR2bizYMfnAd8596vfB4aTDWr2WYRjsuLkDo5qM4rUmro1uMlry29txmfOt7FuIz4yX/JoHxmRKiyn4Nv5bFKlq3uJKm5zjM+JxLvUc3mn6Dlfl6ezt0Lex9dpW0Y5v6KT895lhGKy5tAaZxZmY134eDehrQco5y5XWV+rr1KlTaYDLMAxGjBhR8b2nqxEOGjQIarXuC/NoNBpMnz4dHTt2RGhoaMX3Z8yYgQ4dOmDIEO32Vy4tLUVpaWnF17ou5KDSqDDv7DxEto00mKsxhOXn5yd2CUbN084TK7utxMGkg5h0bBLsze1haWaJwQGDMa7pOEGvCBtS1s3cmqGdZzt8G/8t3m32Lu/He7o43spuK3k/Ft/4ztnewh425jZ4UvjkhetGRKdFo4lzE4NbRb2BYwPkleYhuyRbsveMcpVzcXkxlscsx7Kuy+iEvIBszG0wruk4rLu8Dh+Gf1jt616Uc3ZJNlZfWo1V3VeJOsPI18EXJgoT3M+7T7M99CDVv88qjQoLzy1EiEsIRjYeKXY5Bk+qOcuZ1oP6EydO8FkHJk+ejGvXruHMmTMV39u3bx+OHz+Oy5e1X6F4yZIlWLBggd51rLm4BoMCBiGgToDebRBxpKWlwd7eXuwyjJpCoUD/Bv3RsV5HMAwj2gDH0LJ+tdGrmHt2Ls4+Osv7lNKfbv6EQf6DDHZxvGcJkfNA/4HYn7gf45qOq/F1229sx2cdP+O1Fr682uhV7L6zG+ObjRe7lCpxlfPK2JV4K/QtyZ68MGYdvDrgcNJhXE6/jBbuLap8TU05qzVqzDs7D7PbzJbE765xTcdh67WtWNhxodilGBwp/n0uUhVhzpk5GOg/EL38eoldjlGQYs5yp/WgvmtX/pbtj4iIwP79+3H69Gl4e/+7vdXx48dx79491KlTp9Lrhw8fjs6dO+PkyZPPtRUZGYmZM2dWfK1UKrVezOFQ0iEwYNCvfj+9/juIuJ6doUH4JfaHLkPLWqFQ4OO2H2PK8Smo71ift8WfMooycO7xOYNeHO9ZQuTczrMdvr/+Pd4Ofbvaq7uX0y+jvmN9OFk5Vfm81HXw6oDvrn+Ht0LfkuR0Uy5yPpV8CmYmZuhYryMHFRF9zGw9EzNPzMT6XuurXBm6ppy/ivsKffz6SGbtB39Hf5Spy5Ccnwwfe8NY+E0qpPb3Oas4C3POzMH4ZuPRqm4rscsxGlLLmei5T/1TRUVFuHXrFq5evVrpoS2GYRAREYGoqCgcP34cDRpUnub00Ucf4erVq4iLi6t4AMCqVavw3XdV7yVqaWkJBweHSg9tJOYmYt+9fZjearrW9RNp8ff3F7sEIhBDzNrKzApz28/F/LPzUarm54/h6kurMb3ldINeHO9ZQuRsamKKYJfgGlfT3XZ9G8aGjOW9Fr4oFAr09u2NI0lHxC6lSrXNObM4Ez/e/JH+fovMwcIBrzV5DZuvbK7y+epyPvbwGIpURRgUMIjP8nQ2ruk4fBv/rdhlGBwp/X1OViZj9unZmNV6Fg3oOSalnAlLr09+GRkZGDhwIOzt7RESEoIWLVpUemhr8uTJ2L59O3bu3Al7e3ukpaUhLS2tYvEFDw8PhIaGVnoAgK+v73MnAGqjoKwAiy8sxoIOCyR5FYNo5+HDh2KXQARiqFn72PtgTPAYLI1eynnbMWkxsLewl8yVLi4IlfOQgCH4/d7vVT4XnxEPD1sPuFq7ClILXwYFDMK+xH1il1Gl2uTMMAwWnV+E2W1mS3LfYLnp6dsTjwoe4Vb2reeeqyrnpLwk/HrnV3zQ+gMhytNJI6dGKFAV4HHBY7FLMShS+ft8Pes6FpxbgEWdFiHQSfuduYh2pJIz+Zdeg/rp06cjNzcXFy5cgLW1NQ4ePIht27ahYcOG2LdP+w8NGzduRF5eHrp16wZPT8+Kx65du/QpSy8Mw+Cz859hcovJBv+hTe7Ky8vFLoEIxJCz7uLdBW7Wbthzdw9nbao0Kmy+uhnvNX+PszalQKic/ev4I6UgBWXqsuee++76d3gr5C1B6uCTjbkNGtZpiKsZ2s+mE0ptcv7p1k9o7dEajZwacVgRqY1ZbWZhZexKqDSqSt//b85FqiJ8fuFzLGi/AOam0ryg8lboW/juetUzQ0nVpPD3+eyjs1h/eT1WdFsBD1thds6SGynkTCrTa1B//PhxrFy5Eq1bt4aJiQn8/PwwZswYLFu2DEuWLNG6HYZhqny8+eabNb5n6NCh+pRdpW3XtyHMLazahV2I4QgMpDOxcmHoWU8Mm4jTKadxPes6J+3tvLkTgwMGi77WAdeEzLmbdzecTD5Z6Xu3sm/B2cr5hSvjG4rXGr+Gn2/9LHYZz9E354ScBESnRWNUY8PaZtDYuVq7YlDAIGy7vq3S95/NmWEYfH7+c0xoNkHS/SvEJQQZRRnIKMoQuxSDIfbf5z/u/YG9CXuxqvsqg9utxJCInTN5nl6D+sLCQri7uwMAnJyckJHB/rJr2rQpLl26xF11PIt+HI27uXfpA4GRSExMFLsEIhBDz9pEYYIFHRZgZexK5Jbk1qqt9KJ0nH98HoP8pXU/KheEzLl/g/44mHSw0ve2xm/FW6GGf5X+KS87L6g0KjwpfCJ2KZXok3OpuhRLY5bik3af0PZ1EjTQfyCuZ15HYt6/2T6b885bO9HIqRHaeLQRozydvBn6Jl2t14FYf58ZhsF3177D1YyrWNJ5Cd2OwzND/xxmjPQa1AcFBeH27dsAgLCwMGzevBmPHj3Cpk2b4OnpyWmBfEkrTMPX8V/j47Yf0wcCI6HRaMQugQjEGLJ2tHTEB60/wLyz86DWqPVuZ82lNZjecrpR/h4TMmdHS0eYKcyQWZwJgL0KbG1ujXp29QSrQQgjg0Zi123hbnHThj45r720FqMbj6bb5iRKoVDgw/AP8WXMl9AwbL5Pc7705BKuZFwxmMUnw9zCkJKfgqziLLFLMQhi/H3WMBosi1mGck055rSdA1MTU8FrkBtj+BxmbPQa1E+bNg2PH7MLh8ybNw8HDhyAj48P1qxZg8WLF3NaIB9UahXmn5uPT9t9ChtzG7HLIRwJCjKeBcJIzYwl6yYuTdDdtzs2Xtmo1/tj0mLgYOFgVIvjPUvonF/yfwl/Jf4FANh6bSvGhda8d70halW3Fa5nXedtBwZ96Jrz2dSzKFWXortvd54qIlzwsPVAd5/u+OnWTwDYnDOKUefRUQAAcnFJREFUMrA+bj3mtZ9nUCci3wh+Az/c+EHsMgyC0L+3y9RlmHNmDho5NcK7zd41qJ8rQ2Ysn8OMiV6D+jFjxlTc996qVSs8ePAAsbGxSElJwciRI7msjxdfxn6JEY1GwM/BT+xSCIeezh4hxs+Ysh4aOBQ5JTk4lXxKp/cZ6+J4zxI65471OuLMozNIykuCQqGAr4OvoMcXgkKhwEsN/j15IQW65JxTkoOt8Vvxfuv3eayIcOWVRq/gbOpZPCp4hOu3rmPe2Xn4uO3HsDW3Fbs0nbT2aI2E3IRa3y4lB0L+3s4vy8fMkzPxUoOXMKzhMMGOS4zrc5ixMNP2hTNnztS60ZUrV+pVjBD+uPcH7Mzt0MO3h9ilEEIIAODD8A8x5fgUNHBsoPVAcufNnRgSMAT2FvY8Vycf5ibmCHQKxKf/fIoFHRaIXQ5v+jfoj4hjERgaONSgrmoxDINFFxZhZuuZsDazFrscogUThQlmt5mNL6K/gHWpNYY0GQL/Ooa5v/WYJmOw/eZ2RLSIELsUAnY9mY/PfIypLaaiqVtTscshRHRaD+ovX76s1euk/AHhdvZtHH5wGKu7rRa7FMIDmgokH8aWtYWpBea3n49Pz36KdT3WvXDAkl6UjguPL2B9z/UCVSgOMXIeFjgMRaoigx14aMPC1AJh7mGISYtBuGe42OVonfNvd39DsEswgl2Cea6IcMnPwQ/hHuFIL0xH3/p9xS5Hb+082+GHGz8gvyyfTqbWQIjf24m5iVh0YRHmtp9Ls25FYmyfw4yBgmEYRuwi+KRUKuHo6IiH6Q8x/9J8LO+6HE5WTmKXRXhw7do1hIaGil0GEYCxZn3+8Xnsv7cfCzsurPEE6Zy/52BsyFijvZf+KWPNWQoyizOxNHoplnddLnYpWuWclJeE5bHLsbbHWpgo9LpzkIjMGPrz6ZTTuJl1ExPCJohdimTxnXNcehw2xG3A4s6LaaFMERlDfzYUT8eyeXl5cHCofuti2fxlXBq9FDNazaABPSFEstp5tkN9x/o1rk4e/TgajpaORj+gJ/xytXaFpaklkvOTxS7lhVRqFRZfWIxP2n1CA3oiqs71OuPik4soVBWKXYosnXh4AluvbcWq7qtoQE/If8jmr2Nbz7YIdaUzSsaMpgLJhzFn/Xbo24hJi0Fcetxzz6k0Knwd/7VRL473LGPOWQpGNR5VsTK5mF6U84YrGzC80XB42HoIVBHhgzH0Z4VCIcltIaWEr5x339mNow+PYkXXFQa30KIxMob+bGxkM6gfEjBE7BIIz2glTvkw5qxNFCaY32E+1l5eW7Fn+lM7buzA0MChsrmf05hzloIQ1xAk5SWJftWxppxj0mKQVZxl0PdiE5ax9Ofuvt1xNvUsisuLxS5FkrjOmWEYbIzbiAfKB1jYcSHMTc05bZ/ox1j6szGRzaBeygv4EW6YmMjmx1n2jD1rewt7fBT+EeadnYdyTTkA4EnhE8Q8icGABgNErk44xp6zFAwOHIzfE34XtYbqcs4rzcOmK5vwYfiHAldE+GAs/dlEYYJXGr6C3Xd2i12KJHGZc7mmHAvPL4SdhR3eb/0+3X4jIcbSn40JJUKMhr+/8a5WTSqTQ9aNnBphQIMBWHtpLQBg9aXVmNZymqxOUMohZ7H19O2J48nHoWE0otVQVc4Mw2Bp9FJMbTmVptoaCWPqz739euNU8imUqkvFLkVyuMq5uLwYs0/PRhuPNng9+HVO2iTcMab+bCxoUE+MRkJCgtglEIHIJeuX/F9CmaYMy2KWwcnKCY2cGoldkqDkkrOYzE3M0c6zHc48OiNaDVXlvD9xP3wdfBHmFiZCRYQPxtSfTU1MMSRwCKLuRoldiuRwkXNuSS5mnJyBkUEj0b9Bfw6qIlwzpv5sLEQd1J8+fRqDBg2Cl5cXFAoF9u7dW+n5goICREREwNvbG9bW1ggODsamTZvEKZZInpmZmdglEIHIKev3W72P0vJSvBcmj8XxniWnnMX0SsNX8OONH/HxmY8RdTcKqQWpgh7/vzkn5yfjz/t/4t2m7wpaB+GXsfXn/g364+iDo1CpVWKXIim1zTm1IBUfnPoAM1rOQFvPthxVRbhmbP3ZGIi6T/2BAwfwzz//oFWrVnj55ZcRFRWFoUOHVjw/fvx4HD9+HN988w3q16+Pw4cP47333sOePXswePBgrY6h7d5+xPAVFRXBxsZG7DKIAChreaCchZVZnInYtFhEp0UjtSAVdW3rItwjHOEe4XCzcePtuM/mXK4pR8TxCHzS9hN423vzdkwiPGPsz3vu7gHDMBjeaLjYpUhGbXK+nX0by2KW4bOOn6GeXT2OKyNcMsb+LFUGsU99//798fnnn2PYsGFVPn/27FmMHTsW3bp1Q/369TF+/HiEhYUhOjpa4EqJIUhMTBS7BCIQyloeKGdhuVq7ol+Dfpjbfi429d6ESWGToGE0WHt5LSYemYjPz3+Ow0mHkVOSw+lxn815S/wWDGgwgAb0RsgY+/Mg/0E4cP9AxYKmRP+cox9HY9WlVVjedTkN6A2AMfZnQyfpuRMdOnTAvn378Pbbb8PLywsnT57EnTt3sGrVqmrfU1paitLSfxcuUSqVQpRKJMDS0lLsEohAKGt5oJzF5WHrgUEBgzAoYBAYhkFKQQpi0mKwLGYZckpz0MChAcI9wtHKoxUcLPSfCfc057j0OCQrkzGx2USu/hOIhBhjfzY3NUdvv9746/5fGByg3QxSY6dPzgeTDuJw0mGs6rYK1mbWPFRFuGaM/dnQSXpQv27dOowfPx7e3t4wMzODiYkJtmzZgi5dulT7niVLlmDBggUCVkmkwsPDQ+wSiEAoa3mgnKVDoVDAx94HPvY+eLnhy2AYBveV9xHzOAYLzy1EviofjZwaIdwjHC3dW8LGXPtpmR4eHigoK8Day2uxuvtqWe3wICfG2p+HNhyKyUcnY0CDATA1MRW7HNHpmvP2G9txL+8elnVZBjMTSQ9LyDOMtT8bMkn3nnXr1uH8+fPYt28f/Pz8cPr0aUyePBleXl7o1atXle+JjIzEzJkzK75WKpXw8fERqmQiogcPHiA0NFTsMogAKGt5oJylS6FQwN/RH/6O/hjZeCQ0jAZ3c+4iOi0ae+7uQUl5CZq4NEG4RzjC3MJgZWZVbVsPHjzArrxdeC/svVpd8SfSZqz92dLUEt18uuHwg8O0Uju0z1nDaLD60mpYmlpibru5dDLPwBhrfzZkkh3UFxcXY86cOYiKisKAAQMAAM2aNUNcXByWL19e7aDe0tKSpoTIlLU1TdmSC8paHihnw2GiMEGQcxCCnIPwevDrUGvUuJV9CxfSLmDnzZ1QM2qEuoYi3CMcTV2bwtzUvOK9Fwsuws3aDa09Wov4X0D4Zsz9eXij4ZhyfAr61u8LE4W8d4vWJmeVWoUF5xagmVszjAgaIUBVhGvG3J8NlWQH9SqVCiqVCiYmlX85mpqaQqPRiFQVkTJXV1exSyACoazlgXI2XKYmpghxDUGIawgAQKVR4XrmdVx4fAHfXfsOCoUCYW5haOzcGKdzTmNTX9qu1tgZc3+2NrNGR6+OOP7wOHr5VX3RSUiFqkLYmNmIcvX7RTkXqgoR+XckhgYORQ/fHgJVRbhmzP3ZUIk6qC8oKEBCQkLF1/fv30dcXBycnZ3h6+uLrl27YtasWbC2toafnx9OnTqFH374AStXrhSxaiJVycnJcHR0FLsMIgDKWh4oZ+NhbmKO5u7N0dy9OQCgVF2KK+lXcDH9Ika5j4K5iXnNDRCDZ+z9eWTQSEw/MR09fXsKPpjOK81D7JNYxKTFICkvCTbmNihSFaGOVR20qdsG4Z7h8LbzFqSumnLOLM7EnL/n4L3m71X8LiCGydj7syESdVAfGxuL7t27V3z99F74sWPH4vvvv8fPP/+MyMhIjB49GtnZ2fDz88OiRYswcSKtjEueZ2dnJ3YJRCCUtTxQzsbL0tQS4Z7hCPcMR1JSktjlEAEYe3+2MbdBa4/WOJ1yGl19uvJ6rEJVIS49uYTotGjczbkLewt7tPFog5FBI1HfoX7F4D27JBuxabHYdn0bUvJT4GrtyvY7j3B42PKz0Fl1OT9UPsSCcwvwcduP4V/Hn5djE+EYe382RAqGYRixi+CTUqmEo6Mj8vLy4OBAC/AYs+zsbDg7O4tdBhEAZS0PlLM8UM7yIIec88vyMevULGzstZHTq+Il5SWIy4hD9ONo3My+CWsza7R0b4lwz3AE1gnU+j7+9KJ0xKTFIDotGk8Kn8DTzhPhHuFo49EGrtbcTKeuKudrmdew+tJqLOq4CHVt63JyHCIuOfRnqdB2LCvZe+oJ0VVqair9gpEJyloeKGd5oJzlQQ4521vYo6lbU5xLPYcO9Tro3Y5KrcLVzKuIfhyNa1nXYKYwQ3P35ujp1xOTm0/We+s8dxt3DPAfgAH+7ALUjwoeIfpxNFbGrkR2STZ8HXzR1qMtWnu0hqOlflOr/5vzmUdn8NOtn7Cy20ra3cKIyKE/Gxoa1BOjQTMx5IOylgfKWR4oZ3mQS85jmoxB5N+RaO/VXuur9eWactzIuoHotGhcybgCMEBTt6Zo79Ue7zR7h7c1J+rZ1cOwhsMwrOEwMAyDh/kPceHxBSy6sAjKUiUC6gSgrWdbtHRvCTsL7aZbP5vz7wm/42zqWazsthKWprQzlTGRS382JDSoJ0bDxsZG7BKIQChreaCc5YFylge55Oxo6YhGTo0Q+yQWbTzaVPkaDaPB7ezbiE6LxuX0y1BpVAh2CUa4RzheD35dlAGwQqGAn4Mf/Bz8MCJoBBiGwb3ce7iQdgG/J/yOovIiBDkFIdwzHC3cW8DarOotzWxsbMAwDL699i2yirOwpPMS2W/zZ4zk0p8NCQ3qidFIS0ujLTZkgrKWB8pZHihneZBTzm+EvIF5Z+dVDOoZhkFiXiIuPL6Ai08u/jtA9gjHq41ehY259AZICoUCgU6BCHQKxOgmo6HWqHEn5w6i06Lxy+1fUKYuQ6hrKNp4tEGYWxgsTC0AAKmPU7Hl3hbUta2L2W1mi7KtHuGfnPqzoaBBPTEaTk5OYpdABEJZywPlLA+UszzIKWdnK2f42vtiQ9wGPFA+QF5ZHgIcAxDuEY5BAYNgb2Evdok6MzUxRROXJmji0gRjQ8ZCpVHhRtYNxKTF4IcbPwAM0MytGa6kXkHfhn0xKGCQ2CUTHsmpPxsKGtQTo2FuTvscywVlLQ+UszxQzvIgt5zHNxuPi08uYlTjUahjVUfscjhnbmKOMLcwhLmFAQDK1GW4mnEVjawaoWsAv1v6EfHJrT8bArrJhRiN9PR0sUsgAqGs5YFylgfKWR7klrOjpSN6+PYwygF9VSxMLdDaozVcylzELoUIQG792RDQoJ4YDRcX+kMiF5S1PFDO8kA5ywPlLA+UszxQztJDg3pCCCGEEEIIIcRAGf099QzDAACUSqXIlRC+PXjwALa2tmKXQQRAWcsD5SwPlLM8UM7yQDnLA+UsnKdj2Kdj2uoY/aA+KysLAODj4yNyJYQQQgghhBBCiG7y8/Ph6OhY7fNGP6h3dnYGADx8+LDGfwhi2JRKJXx8fJCcnAwHBwexyyE8oqzlgXKWB8pZHihneaCc5YFyFhbDMMjPz4eXl1eNrzP6Qb2JCbtsgKOjI/3gyYCDgwPlLBOUtTxQzvJAOcsD5SwPlLM8UM7C0ebCNC2URwghhBBCCCGEGCga1BNCCCGEEEIIIQbK6Af1lpaWmDdvHiwtLcUuhfCIcpYPyloeKGd5oJzlgXKWB8pZHihnaVIwL1ofnxBCCCGEEEIIIZJk9FfqCSGEEEIIIYQQY0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA0WDekIIIYQQQgghxEDRoJ4QQgghhBBCCDFQNKgnhBBCCCGEEEIMFA3qCSGEEEIIIYQQA2UmdgF802g0SE1Nhb29PRQKhdjlEEIIIYQQQgghL8QwDPLz8+Hl5QUTk+qvxxv9oD41NRU+Pj5il0EIIYQQQgghhOgsOTkZ3t7e1T4vqUH90qVLERkZiWnTpmH16tXIzs7GvHnzcPjwYTx8+BBubm4YOnQoFi5cCEdHR63atLe3B8D+Qzg4OPBZPhFZcnIyncCRCcpaHihneaCc5YFylgfKWR4oZ+EolUr4+PhUjGmrI5lBfUxMDDZv3oxmzZpVfC81NRWpqalYvnw5goOD8eDBA0ycOBGpqanYvXu3Vu0+nXLv4OBAg3ojV7duXcpYJihreaCc5YFylgfKWR4oZ3mgnIX3otvIJbFQXkFBAUaPHo0tW7bAycmp4vuhoaH47bffMGjQIAQEBKBHjx5YtGgR/vjjD5SXl4tYMZGitLQ0sUsgAqGs5YFylgfKWR4oZ3mgnOWBcpYeSQzqJ0+ejAEDBqBXr14vfG1eXh4cHBxgZlb1JIPS0lIolcpKDyIPz54QIsaNspYHylkeKGd5oJzlgXKWB8pZekQf1P/888+4dOkSlixZ8sLXZmZmYuHChRg/fny1r1myZAkcHR0rHnS/hzyUPXyI4k8/BaPRiF0KEYC5ubnYJchC3r59yNy4UbTjU87yQDnLA+UsD5SzPFDO0iPqoD45ORnTpk3Djh07YGVlVeNrlUolBgwYgODgYMyfP7/a10VGRiIvL6/ikZyczHHVRIoy1q5DqZMTcrVca4EYtvT0dLFLMHolN29CeegwimJiwIh0uxPlLA+UszxQzvJAOcsD5Sw9og7qL168iPT0dLRs2RJmZmYwMzPDqVOnsHbtWpiZmUGtVgMA8vPz0a9fP9jb2yMqKqrGs0OWlpYVi+LR4njyUHTpMkzr1IHTjBnIP3gI5Tk5YpdEeObi4iJ2CUZNnZeHJ0u/gOfnC2HboQMKz54VpQ7KWR4oZ3mgnOWBcpYHyll6RB3U9+zZE/Hx8YiLi6t4tG7dGqNHj0ZcXBxMTU2hVCrRp08fWFhYYN++fS+8ok/khWEYZG7cCNfJ70FhagrXKRHIWLNG7LIIMViMRoPHn3wK9w8+gJmTExwGDUbeH/vFLosQQgghhFRD1EG9vb09QkNDKz1sbW3h4uKC0NDQigF9YWEhvv32WyiVSqSlpSEtLa3iKj6Rt/wDB2DbNhxmTk7IysqCTYsWgFqN4vh4sUsjPMrKyhK7BKOVuXEjbLt0hnXTUACAeV13MCXFUIuw6CjlLA+UszxQzvJAOcsD5Sw9oi+UV5NLly7hwoULiI+PR2BgIDw9PSsedK880ZSWImfXL3B6/XUAgLu7OwDAbcYMZKxeA4ZO/Bitp1kTbhWcPo3ytCdwevXVSt+379cPygMHBa+HcpYHylkeKGd5oJzlgXKWHskN6k+ePInVq1cDALp16waGYap81K9fX9Q6ifhytm9HnRGvwsTSEgCgUqkAAGbOzrDr2QO5u38TszzCo6dZE+6UpaQg+/ttqPvJx889Z9+zJ/KPHRW8JspZHihneaCc5YFylgfKWXokN6gnRBvlOTkoPHceDi+9VPG9nGcWyHMaORL5h2jRPGOVQ7lySlNSgrS5c+Hx2WcVJ8meZWJlBXMPT5Tevy9oXZSzPFDO8kA5ywPlLA+Us/TQoJ4YpMwNG+H63iQoFIqK73l4eFT8f4WpKdymTkHGalo0zxg9mzWpHYZh8GTRIji/9TYsvOtV+zrHoUOR9/vvAlZGOcsF5SwPlLM8UM7yQDlLDw3qicEpvX8f6qws2LRsWen7RUVFlb62bt4c0GhQfPWqgNURIfw3a6K/3F9/hbmXF+w6d6rxddYtmqPk6lUwGo1AlVHOckE5ywPlLA+UszxQztJDg3picDLWrIXb9GnPfV9ZxercbjOmI2PNWlo0z8hUlTXRXXF8PAr/OQuXCRNe+FqFQgGbNm1QFB0tQGUsylkeKGd5oJzlgXKWB8pZemhQTwxKYXQ0zOvWhYWv73PPeXl5Pfc9M2dn2PfuhdxfdwtRHhFIVVkT3ZTn5CB9+Qp4LvwMChPt/hQ4Dh6MvL3CTcGnnOWBcpYHylkeKGd5oJylhwb1xGAwGg2yNm2G66SJVT5f3VnDOq++ivzDh2nRPCNCZ4hrh1Gr8fjjT1A38iOYOjho/T7zevWgzsuDuqCQx+r+RTnLA+UsD5SzPFDO8kA5Sw8N6onBUO7fD7uuXWBap06VzxcUFFT5fYWpKdymTUXGqtX8FUcEVV3WRDsZa9fBoV9fWDVurPN77fv2Qf7hwzxU9TzKWR4oZ3mgnOWBcpYHyll6aFBPDIKmpAS5v+2B02uvVfsaHx+fap+zDgsDABRfucJ5bUR4NWVNapZ/7Bg0BQVwHDxYr/c79O4t2KCecpYHylkeKGd5oJzlgXKWHhrUE4OQ/f02OI0aBYWFRbWvyczMrLENtxnTkbF2HS2aZwRelDWpWllSEnJ+3oW6H87Wuw0TW1uYOjmhLCWFw8qqRjnLA+UsD5SzPFDO8kA5Sw8N6onklWdmoujSRdj36V3j64qLi2t83szJCfa9eyP311+5LI+I4EVZk+dpiorweMECdmG8Gk6OaUOoPespZ3mgnOWBcpYHylkeKGfpoUE9kbyMr76CW0QEFApFja/z8/N7YVt1Xn0F+YePoDw7m6vyiAi0yZr8i2EYpC34DK4TJ8Hcw6PW7dm0aY3iixfBMAwH1VWPcpYHylkeKGd5oJzlgXKWHhrUE0krTUgAU1wM62bNXvjatLS0F75GYWoKt+nTaNE8A6dN1uRfOdt3wLJRI9i2DeekPYWJCaybN0fxpUuctFcdylkeKGd5oJzlgXKWB8pZekQd1G/cuBHNmjWDg4MDHBwc0L59exw4cKDSa86dO4cePXrA1tYWDg4O6NKlC035kJGMNWvhOmWqVq8tLS3V6nXWzZoBCgWK4+JqURkRk7ZZE6Do0iUUx8XB+e23OG3XccgQ5O3dy2mb/yVGzpqyMpQmJAh+XDmj/iwPlLM8UM7CKY6PF2yL2f+inKVH1EG9t7c3li5diosXLyI2NhY9evTAkCFDcP36dQDsgL5fv37o06cPoqOjERMTg4iICJiY0AQDOSg8exYWfr6w8K6n1ev9/f21bpsWzTNsumQtZ+UZGchYuw4eCxa88PYVXVn4+UGVng4NjydZxcg595df8ej9D3i/tYD8i/qzPFDO8kA580+tVOLxvPnI2vIN0lcsF6UGyll6RB0dDxo0CC+99BIaNmyIRo0aYdGiRbCzs8P58+cBADNmzMDUqVPx0UcfISQkBEFBQRgxYgQsLS3FLJsIgFGrkfXNN3CZMEHr9zx8+FDr15o5OcG+b1/k/vKLPuURkemStVwxKhVSP/kEHp98DFM7W16OYd+rF/KPHuOlbUD4nDVlZcg/ehT2PXui8OxZQY8tZ9Sf5YFylgfKmV/KI0eQMmUqHAcNhPfaNQDDoDA6WvA6KGfpkcwlb7VajZ9//hmFhYVo37490tPTceHCBbi7u6NDhw6oW7cuunbtijNnzohdKhFA3t69sOvZE6b29lq/p7y8XKdj1HllOPKPHqNF8wyQrlnLUfqKlagzdCgsAwN5O4ZDv35QHjrIW/tC55wXtReOgwbBadRryN1FJ/yEQv1ZHihneaCc+aF6ko5HM2ei5MYN+Hy9GTatWwMA3D/4AJnrN/A6a64qlLP0iD6oj4+Ph52dHSwtLTFx4kRERUUhODgYiYmJAID58+fj3XffxcGDB9GyZUv07NkTd+/erba90tJSKJXKSg9iWDSFhcj7Yz+cRozQ6X2BOg5e/l00b5VO7yPi0zVruVH+/9okDv3783ocU3t7mNjYQPXkCS/tC5kzo1JBeeAAHAcPgpmrK0zs7FCWlCTY8eWM+rM8UM7yQDlzi9FokLPrFzz++GO4TJgI92nTYPLMjGVTOzs4v/UmMr76StC6KGfpEX1QHxQUhLi4OFy4cAGTJk3C2LFjcePGDWg0GgDAhAkT8NZbb6FFixZYtWoVgoKCsHXr1mrbW7JkCRwdHSsePj4+Qv2nEI5kffc9nN94Awpzc53e9/REkC6smzYFTExRdPmyzu8l4tEna7koTUhA7t69cH9/piDHcxw0GHm/7+OlbSFzzvtjPxz69av4veM8ZjSyt+8Q7PhyRv1ZHihneaCcuVN6/z5SJr0HprQUPps3wSqoUZWvs+/WDeqsbBTHxwtWG+UsPaIP6i0sLBAYGIhWrVphyZIlCAsLw5o1a+Dp6QkACA4OrvT6Jk2a1HgfR2RkJPLy8ioeycnJvNZPuKV6ko6Sa9dg172bzu99eiJIV27TpyFz3Ve0aJ4B0TdrY6cuKEDaws/h9fnnOp8U05dth/YoOn+Ol4XlhMqZUauRt28fHF8eVvE9q+BglCU/hDo/X5Aa5Iz6szxQzvJAOdceo1Ihc9NmZKxcCY+5n8L5jdehMDWt8T3uH85G+sqVYMrKBKmRcpYe0Qf1/6XRaFBaWor69evDy8sLt2/frvT8nTt34OfnV+37LS0tK7bIe/oghiPzq3VwnRKh10rdQUFBeh3TzMkJ9v36ImfXLr3eT4Snb9bGjGEYpM2bD7dpU2Hm5ibYcRWmprAKCUEJD1cIhMpZ+dcB2PfsCRMLi0rfr/PycOT+9psgNcgZ9Wd5oJzlgXKuneL4eDwcPx7m9eqh3tq1MK+n3Q5QZk5OcHr1VWRu2cJzhSzKWXo4GdQvWLAAmZmZOr8vMjISp0+fRlJSEuLj4xEZGYmTJ09i9OjRUCgUmDVrFtauXYvdu3cjISEBn376KW7duoVx48ZxUTaRmJJbt8CoNbAOCdHr/f89AaSLOq+8goJjx1GelaV3G0Q4tcnaWGVv/Q7WzZvDpmVLwY/tOHQoL3vWC5Ezo9Egd89vqPPqK889Z9+zBwpOnKRZPDyj/iwPlLM8UM760RQV4cmSpcjZ+RPqrVwJx0EDdb7AZd+/P0oTElBy5w5PVf6LcpYeM11eXNWicwzDYNGiRejfvz8s/v8qh7ZXx9PT0/HGG2/g8ePHcHR0RLNmzXDo0CH07t0bADB9+nSUlJRgxowZyM7ORlhYGI4cOYKAgABdyiYGgGEYdj/tuZ+KcnyFiQncpk9D+qpV8Pr8c1FqIERfhecvoPTOHXguXSLK8S0DAlCWnAJNWdlzV7ulLv/wEdh17gITK6vnnlOYmcGuS2cUnDwJ+549RaiOEEKIsSv4+wy7jfO778KuU0e921EoFKj7USQez5kDn683v3DKPjEuCkaHGyFNq/nhYBgGCoWi4n/VErqqoVQq4ejoiLy8PJqKL2EFp0+j6PJluE+bpncbKpUK5rW8j/jx/PlwHDwENi1b1Kodwi8usjYWqrQ0pEZGwmf9epjY2IhWR/aOHTBzcYVDv76ctcl3zgzDIHncOHh/9VW1/3bqvDykfhQJn40beKtD7qg/ywPlLA+Us/bKc3KQvuxLmDo6wm3qFM7+hufu3g11fgFc3nqTk/aqQjkLR9uxrE7T7z09PdG/f38cPXoUx48fx/Hjx3Hs2DGYmJjg22+/xYkTJ3D8+PFaF0/khSkvR9Z338Fl3Du1aoeLqUBu06Yh86t1NN1W4mjaF4spK8PjT+fCc948UQf0AODw0ktQ/vUXp23ynXPBiROwaduuxn87U0dHmHt6oIR+5nhD/VkeKGd5oJxfjGEY5P2xH6nvvw+nUa+h7kcfcvo33HH4cBTFxKDswQPO2vwvyll6dBrUX716Febm5li4cCECAwPRtWtXdOvWDQqFAuHh4ejatSu6du3KV63ESOXu/g0O/frD1M5W7FLYRfP690fOzz+LXQohL/Tki2Vw+t9IWNSvL3YpMHNygsLMDOV6rK8iBoZhkLNjJ5xGj3rha53GjEHO9u0CVEUIIcSYqR49wqOp06BKTYXP5s3s1socUygUqDsnEk+WLOVlZxoiHFVaGrK+/Var1+o0qHd2dkZUVBReffVVhIeH46efftKrQEKeUhcUQHnoIOoMf7nWbXG1Emed4cNRcOIkLZonYbTqKpD3++8wsbOT1L3eDgMHIm//fs7a4zPnwjNnYN2iBUzt7F74Wkt/f5Tn5KA8J4e3euSM+rM8UM7yQDlXjVGrkf3DD0hb+DncZs6A64TxvG49a+HtDdsO7ZH7y6+8tE8580dTVgblwYNIjohA+sqVsAoN1ep9eq1+P2nSJBw5cgRffPEFRo168VUOQqqTteUbuLz9NhRmOq3ZWCWupgIpTEzgNm0a0leu5KQ9wj25T/squXULykOH4TZ1itilVGLXuRMKT//NWXt85cwwDLJ//BHOr4/R+j1OI0Ygd9cvvNQjd3Lvz3JBOcsD5fy8ktt3kDxhIhTW1vDesB6WDRoIclyn0aORf/QoVGlpnLdNOXOv5PZtpC1ejJRJ76E8Kwteixah3rJlsG3bVqv3672lXXBwMKKjo+Hh4YHQ0FBYW1vr2xSRKdXjxyhNSIBd586ctGdiwskOjQAA66ahUFhYoOjSJc7aJNzhMmtDo87Lw5MlS+G56HPJrWyrMDeHZcOGKLl5k5P2+Mq56MIFWDUJhqmjo9bvse3UCYXnz4NRqXipSc7k3J/lhHKWB8r5X5rSUqSvWYOszZvhuXgRnF59FQoB/30Upqao+9GHeLJ4CefT8ClnbqiVSuT89BMevvMucnf/hjrDhsH322/gPHq0Tp9RAB1XvzdEtPq9dKVGzoHzm2/CKqgRJ+2VlJTAqoptqfSlzs1FyowZ8N2yhZOZBIQ7XGdtKBiNBo+mz4DLu+/wch8eF0pu3UJeVBTqRkbWvi2eck6eOAmeSxbDzMlJp/dl79gB0zp14DhgAOc1yZlc+nNZyiMUXTiPouhoOA4bBtt27cQuSVByyVnuKGdWUWwsMr5aD+cxo2Hfq5eotWRu2gTzet5wHDSQszYpZ/0xGg2KoqORFxUFdUEhHAcOgF2PHjCxtKzy9dqOZfUeqeTm5iI6Ohrp6enQaDSVnnvjjTf0bZbIRPG161CYmXE2oAeAhIQEhGp534k2nn54z/npZ52m6RL+cZ21ocjavBm2nTpKdkAPAFaNGyM94R4YlarW9wvykXPRxYuw8PfXeUAPAHWGDkXK9Bk0qOeYsfZn1ZMnKLpwAYUXLqD8STrM69WDbbu2cJ0yFY8//hhWoaFarelgLIw1Z1KZ3HNW5+dX3L7pvW4tTO3tRa4IcBk3DskTJsC2YweYOTtz0qbcc9aHKjUVuXv3oigmBjZt2sBt2jSYe3lx1r5eg/o//vgDo0ePRkFBARwcHKBQKCqeUygUNKgnNWIYBpnr1sFj4WectmvGw9V0x5dfRvL4CXDo3w9mrq6ct0/0w0fWUlfw9xmoUlPhMnGi2KW8kG3nTij4+wzse3SvVTt85Jz13XfwnDdPr/ea2NrCMiAAxVeuwDosjOPK5MtY+nN5djaKoqNReP48VCmPYObuDtt2beE2dSrM69at9FrXSZOQsXIlPObOFala4RlLzqRmcs45/9gxZP+4HW4Rk2HTurXY5VRQmJvD7f338WTpUtRbtoyTNuWcsy40ZWUoOHYMeX/+CVNbWzgOGwbXiRN5uQ1Dr0Tef/99vP3221i8eDFsRN4bmRieguPHYdWsKczd3Tlt19fXl9P2gP9fNG/6dKSvXAWvxYs4b5/oh4+spaws5RGyv/sO3hvWVzqJKlWOAwfiyeLFtR7Uc51z8dWrMPf0gpmbm95tOI0ZjYy1a1GPBvWcMdT+rFYqURQTg8LzF1CWlARTpzqwbdsWLu+8Awtv7xrfa9uuLZQHD6AwOhq24eECVSwuQ82Z6EaOOavS05H+xTKY+/rAZ/OmaqdRi8k6JATmdT2Qf/w47Hv0qHV7csxZFyW3biF3928oS0qCfc8e8Fq8GKY83wau16D+0aNHmDp1Kg3oic4YlQrZP/wIn40bOG87MTGRl6lA1qEhyLOyRNHFi7Bp1Yrz9onu+MpaihiNBmkLFsDjswUwMZD718xcXcGUq1Gek6PXNPenuM4565tvUffjObVqw8LbG0yZCqonT567+kr0Yyj9WVNYiKKLF1F44QJK79yFqb0dbMLD4fTaa7BoUF/nE27u77+PlIgpsG7WzGD6dm0YSs6kduSUc+ndu8j9bQ9K7yfCfeb7nN5SygfXiMlInjARNq1b13qAKaectaXOy0Pen3+i4NhxWAT4o86rr8BKwK3/9BrU9+3bF7GxsfD39+e6HmLkcnb9AschQ2DCwwkhSx7PjLpNnUqL5kkIn1lLTe7u3bDv0f2FV/6kxmHAACj/+gvOo0fr3QaXOZfcuAFTF2dOBuJOo15Dzk8/wX369NoXRiTbnzUlJSiOi0Ph+fMouXkTJlbWsGnVEo6Dh8CyYWCtp0+a2tvD+a03kbFuHerOmsVR1dIl1ZwJt4w9Z3V+PpR/HUD+0aOw8PGB4/CXYRUcbBCz6EwsLeE2JQLpy1fA87MFtWrL2HPWFqPRoOjCBeRGRYEpLobDgIHw3rgBJhYWgtei9ehk3759Ff9/wIABmDVrFm7cuIGmTZvC/D+LIQ0ePJi7ConRUCuVKDh+DD5btvDSvoeHBy/tAv+/aN7AgcjZ+ROc33idt+MQ7fCZtZSU5+Qg/+Ah+Gz5WuxSdGbXvRtSJkfUalDPZc5Z33wD9/ff56QtmzZtkLVpMzSlpZKcZmlopNKfmbIyFMfHs4P4+GuAmSlsWrSAfa/ecJsyhZctJO27dUP+gYP/1959xzdR/38AfyVpkiZtkjalu6XIxjKtUMpWEURki4s9BQtlKALKkFmUUdkUEfEr4kAoIAoOKgVkQwsCAgoI3btJm46s+/1R6c9CR5omuST3fj4efTxocve5d3j1Lve58TmU/PGHXQ+AaQn2kjOxLmfMmWEYFF+4ANX+OBjUashffBFBmzY65PZfGhYG9Y9HoDlzBm4REWa344w514UuNRUFcQdQfOki3MLD4TNrFoT+/qzWZHKnfvDgwY+9tnTp4wOd8Xg8GAyGehVFnFNObCy8Jk2y2rO179+/b9VLgRRDhpQPmvdiPxo0j2XWztpeZH+8Ht5R1ulMWBtfJIIoOAhlf/8NcdOmZrVhqZxLb98G380NwsDAercFlH/Pyfv3h/rwYXgMG2aRNrmMrfWZ0etReuMGNOfOoSTpCmA0QtKuLdwiuqDB5Mn1fnqDqXzmzUXq7NloGBsLHgtnd2yFK9ttrnOmnHWZmVDFxUFz9hykYWFoMG0aREGW+R5hk/esWUiJjISkXTuzr5x1ppxNZSwrQ+Gvv0L94xEIZLLyQe/emmqVQe/MYXIVRqPRpJ+6dOi3bt2Ktm3bQi6XQy6XIyIiAkeOHKl4v7S0FJGRkfDy8oK7uzuGDRuGzMzMun1CjmB0OhQnJiJn2zYkT30LDyZMRO6OHdBnZ7NdGgBAm5ICXXJKvY4K1kYikVitbeDfQfNmzUTW2nVWXQ6pnbWztgclV6+WdzLat2e7FLMphgyB6sABs+e3VM65O3bAa+JEi7T1kPyl/lD/8AMYhrFou1xky/WZYRiUXL2K9MUfIHnqWyg6ngBJ23YIXLcWwVu3oMGUKZA+1cFmHXoAcPH0hOfw4cix0lVs9iD3s10Qxf/GdhnEBhz9+5nRaqE++hNSpk9H1pq1cG3TBg13fgrv6c7RoQcAgbsbvCZNQvb6DWa34eg511XRyZNInjQZxsIiBKyKRsCqaLiFd7KbDj1Qj+fUm6JNmzb48ccfERwcXOX7QUFBWLVqFZo1awaGYfD5559j0KBBSExMRGhoKGbNmoUffvgBe/fuhUKhwLRp0zB06FD8/vvv1izbITAGA0r/vInic+dQnHgZ0Bvg2ro13DqHQzl+PHgCATSnTyMzehUYgwGKgQPg3qOHTXdU/it7/QZ4z4iy6jIa2ODsuSQ0FCqJBMUXL9rV40q4xhZZs4kxGJC9fgMCVlvm0TNscW3dGtkxMWAMBrOuNrBEzmV374HHF0AUElLvtv6LLxbDtV07FJ+/ALdwboxebi22WJ/1ublQHfoempMn4RoaCuXYMRA/8YTVl2sqWb9+UM+ajdLbt+Ha3L4H26orzenTKLt1C4K0VBhLSzkxKCCXOer3c+mt21Dt34eyv+/A/dln4L9sGQQeHmyXZTXu3bpCfeRHlCQlmXXywFFzrivGYEDO5s3Q5+Yh+JPtdn3LBY+x4mkGmUyGK1eu1GlAPaVSidWrV+Pll1+Gt7c39uzZg5dffhkAcPPmTbRq1QpnzpxB586dTWpPrVZDoVBApVJBbuVHCVgTYzSi7K+/yzvxly7BWFoC15at4BbeCZIOHcCv4YiZPj8f6u+/R9HxBIhbtoTHsKEQN2lis9pLkpKgOnTI6s/jvXbtmk0uBTKoVEiZOZMGzWORrbJmS/433wKMEZ6vvcZ2KfWW88kncG3ZCu7du9V5XkvknPbe+/CaOAFiKwzsqsvMQuaqaATFxFi8bS6x1vrM6PUoOnUK6kOHwDAMFAMHwr17d7vdbusys5D+3nsI3h7rkLfcVEWXloa0999H8JYt+HPXLvjL5FCONH+cDWL/HOn72aBWQ/3jjyj89RhEjRrBY+gQuD75JNtl2YyhoAApM2cheHtsnQd2c6SczaXPy0P6goWQPf88PIYMZq0OU/uydvPNZjAYsHfvXmg0GkRERODSpUvQ6XTo3bt3xTQtW7ZEw4YNa+zUl5WVoaysrOJ3tVpt9dqtgWEYaO/9g+Lz51B8/gIMhYUQN2sGt/BOUAwdCoG7m8ltuXh6Qjl6NDxHjULptevI270butRUyJ5/HvJ+L9apLXM+R/aWLQiIjrbaMh5yd3e3+jIAQKBQQPHSAOTv2QPl6NE2WSapzFZZs0Gfn4/Cn39G8PZYtkuxCMXAgchau9asTn19c9YmJ4PRaq3SoQcAoa8P+CIRtCkpDvd0Anti6fVZ+88/KNgfh9Jrf8CtW3f4vveeQ4yDIvT1gbzfC8j73xfwGjeW7XLqzajVIn3hIvgvWQK+RAJpnz4oXL4cHq8MZ2VkaGIb9v79zBiNKD5/Aaq4OBiKiqDo/yKCNm+y6zOw1iLw8IDnG68jZ+tW+MyYUad57T3n+ipOTET2x+vh+958mz6Wrj5Y79T/8ccfiIiIQGlpKdzd3REXF4cnn3wSSUlJEIlE8Hjk0hdfX19kZGRU2150dDSWLHn8MQ0pM2dB5uoKoZ8vhIFBEAYGQhgUBFFQIPgKhV08ikKbkoLic+egOXcOhvwCiBo1glt4J/gtXgSBQlHv9nk8HiRtWkPSpjWMJSUo/PVXpM2ZA4GnJzyGDoEkLMzi/w+FP/0M6dMd4eLlZdF2q2LLKzEUQwaXD5rXrx9cvL1ttlxSzpGvuqlNdszHDjs4XlWEvr4waophKCyEQCar07z1zTl3+yfwmjSpXm3UxnPECOTv/hK+8+ZadTnOzBLrs7G4GOqffkbh0aNw8fGBx7Ch8J410y6+2+tCMWwYUt6KhOy5ZyFq2JDtcuolc+VKeI4cUfE5FJ6e4A8YCFXcAXi++grL1RFrsdfvZ116OlQHDkBz/jykTz8N76jpFhs81ZHJ+/RB4U8/o/TmTbi2bGn6fHaac30xDIP8L75ASdIVBG3aWOf9Fjax3qlv0aIFkpKSoFKp8N1332HMmDFISEgwu7358+dj9uzZFb+r1WoEBwcj6OMYyKRS6DMzoU1NhS4lFUXx8dClpsCgKj+bzxO6QBgQUNHhFwb+2+l3s86ZbF1mZnkn/uw56LOyIAwMhFvncPjOnWv1TjBfIoFiwAAoBgyANjkZqrg4ZG/eDLeILlAMGgShr0+9l2HUapH/1VcIjt1mgYprl5aWBqVSaZNlVQyaty4GAdErbbJM8v9smbUtlVy5AgCQtGvHciWWJe/XD+ojR+D5St125OuTsy4tDYaiQri2sO79yZK2bZG9cROMGo3Vviucnbk5MwyD0itXULBvP/TZ2ZD17YvAmHVmj+ZsD3g8Hnzfm4/MFSsRtHWLwx2UeKhgfxxclErInnmm4rW0tDSEDngJDyZNhsfQIayN8UOsy56+n41aLYri46E6fBgCNzcohgyB15tv2tXgZvbAd95cpM2dV37rj4m3J9lTzpZiKCpCxgdL4BoaioC1axxu+8t6p14kEqHpv487CgsLw4ULF7B+/Xq8+uqr0Gq1KCgoqHS2PjMzs8ZnI4rFYoiruYSG5+JS3mEPDASqGNfIqNVCn5YGbUoqdKmpKElMgi41BUZNcfn8UglE/87/sNMvDAww+ZIdfW4uis+fh+bsOehSUuDi6wu3zuHwnhEFoa+vSW1Ygyg4GN5RUWAMBmhOn0HWRx+B0ekgH/ASZD17mv2Infwv98Dj5WE2GxTH1kcNKwbNu3AB0o4dbbpsrnPGI8SMwYDsDRsRsGY126VYnKz3c0iZMaPOnfr65Jy741N4TbDsiPfVUQwehIIDB6AcQfcKm6OuOetzcqA6eAia30/BtXUbeE0YD1GjRtYpjgWi4GC4RXRGwbd7HfKMdumNGyiMP4ag9esrvS6Xy8ETCiHv1w+q7w/DY+gQliok1mQP38+lt26h4Lt90N67B9lzzyJgxQqLXPHqrFy8vSEfOAB5u3aZ/KQYe8jZkkpv30bmymh4T58GaVgY2+WYhfVO/aOMRiPKysoQFhYGoVCIY8eOYdi/zwG+desWHjx4gAgrPRaNLxJB1KhRtTsHxuJi6FJToU1Jgfaf+9D8fhq6tDQwZWVgwEAgV0AYFFje8Q8KgouvL7R37kBz7jy09+5BoPSEW3g4vCZNtMv7L3kCAdy7d4N7927/Dq53GMlTpkLcvHn54HrNmpnclj4/H5pTpxD8yXYrVlyZlIWzM94zosoHzdu+nc462Aij1bKStbUV7P0Osuefh4unJ9ulWBzf1RVCH19o79+v0yj05uasy8qCPjsbktahZs1fV/I+ffBg0mR4vv46nQEygyk5M3o9ik6chOrQIfD4PMgHDoRyzGi7HfSuvjxHjkTylKlw79kDwhpOZNgbQ0EBMj/8CIEfxzx2C9HDnBVDBiP5zTehGDTQaW4zIv+Pre9ng1oN1eHDKDoWD1GTxvAYNrROl5NznWLQIKRGRaHs3j2TngziTPthqkOHoD5yFIFrVjvE+CvVseq3YWxsLHxrOAM9f/589OvXDw0bNkRhYSH27NmD48eP46effoJCocCECRMwe/ZsKJVKyOVyTJ8+HRERESaPfG9pfKkU4mbNqu3cGtRq6FJSoE1JQemNP6GLj4f4iSfg+frrED3RyKEu4ygfXG8UPEeNROmNG8j/6itok1Mg690b8v4vQlDLABk5W7eiwdQpNt3BzcjIsPkjNgQKBZQjRyI5MhK+8+ZZbUAuLqt0hUtaGgz5+dCMGY0GAwawXZrF6PPzUfjLL04zOF5VFIMHQXXwILyjTH+0pbnrdN6nO6EcP67O85mLJxTCLSICmpMn4d6zp82W6yxqyrns7j2o4vaj9Pp1uHXvAb+FC2wyRgvbeAIBfOe+i8yV0Qhc/7FD7D8wRiPSFy6Cz5w5VR6cfJgzXySC7LneUP94BIoBL7FQKbEmNvbFyv76CxnLV8Dz9dcQtHULDcRoBh6PB9/585G+ZAmCt26tdf+djZwtzVhWhsxVqyBQKBC0aaPDH2Q0uVO/YcMGkxuN+nen7Y033qhxuqysLIwePRrp6elQKBRo27YtfvrpJzz//PMAgJiYGPD5fAwbNgxlZWXo27cvtmzZYnIdtiaQyyF48kmnehwGj8eDJDQUktBQGEtLUfjrMaS9OxcCuRyKoUMg7djxsZ0N7T//QJ+dbfPnuHuydIZT9txzcH3ySWRGr4K4ZQs0mDjR7FsWSPkjA4svXKi4wsXFSwlpp3B4TZoEUVAg9Pn5uDv1LRh69HCay+myYz6G94woh/9CqYnkqaeQvWkTGKPR5IN95qzT+txcaJOTIe3Qoc7z1ofHK8ORvnAhderN8GjORo0G6qM/Qf3zTxD6+ZcPejd7tkN0bC1J3LQpXFu1hPrwDw7R+c3ZshXuvXpWe4XMf3P2eHkYkqdOhbz/i3R1i5Ox9b5Y8cWLyNkWi8CYdXBxsnu8bU0YEAD3nj2R//XXUNbSh2Nrn9tStCkpyFi0GJ6jR0HWqxfb5ViEyc+pf8KESzGA8k7g3bt361WUJTnLc+rtjTYlFaq4OBRfvgS38M5QDBlcMS5A6uy30WD6NJMu37GkrKws+PjUf4A/czEMg8IjR5D/7V74zJwBSfv2rNXiSAxFGpRcugjNufMo++svCGQySDt1hDQ8HKJGVV/hkpaQAOO+/eWXeDr4DmFJUhIK9sfBf+njT+1wNtlbtkD6VBjcOoebNL0563TW2rVw694dbp2qGDjFytIXLoJy7BiImzSx+bIdWVZWFry9vVGSmARV3H7os3Mg7/cCZH36gC+RsF0eqxidDslvvomANWvsusNSlJCAwvjf4L/kg2qneXR9zv1sF4T+/pC/0NcGFRJbseW+mPrnn6H+/nsErFpFA5VaCGM0InnqVPgvWlTj0wHY3ueuj8Ljx5H/vy/gt3QpREH2/wQEU/uyJnfqHRV16q2LMRqhOXMGqgMHwZSWwLVNW+izs+H3/ns2r+XatWto3bq1zZf7KH1+PrLWrAFf6gafmTPoi+YRxpISlCQmQnPuPEr/vAG+RAppWBikncMhbtbMpLNx165dQ+CNG9Dn5MD7rbdsULV1MAYDkidNRsDaNU55L/2jtCmpyNmyBQErV5g0fV3XaX1+PtLmzUPDWHZuYyi9dRv5X38F/8WLWVm+I9Ln5+PWli2Q3bkD17Zt4TFkSJ3GXeCCkuvXkff55wj86CO2S6mSNjkZGR8sQdCWzTUOHPzo+mwsLkbKtOkI/nQH567CcGa22hfL27MHpTduwH/xYhrTyMLK7t1D1tq1CNq4sdp10172uevi4YDEBrUKvvPmmTzQOdtM7cvW6556rVaLe/fuoUmTJnBx0sFqSM14fD7cu3aFe9euMBQUoPDYMdZG6/Wyk/ssXTw9EbBiBTSnTyP5rUh4TRgP9x492C6LNYxWi5KrV6E5ew6l164BLgJIOzwF2fPPm/08di8vL3gMH46MRYtQdPIk3Lt3t0Ll1lewdy9kfftyokMPAKKgQBjy8kx+/Ftd1+n8L76AcvRoc8urN9cWzaHPyIRBpXKaW0OsidHpkPbOHMj690fwvHlOfftJfUhCQyH09UVhfDxkzz7LdjmVGEtLkbF4MfyXLat1B/nR9ZkvlULauTOKfvvN7j4XMZ+198UYhkH2x+sBHuC/bBkdELIC8RNPQNq+PVQHD8Jj8OAqp7GXfW5T6XNykL5wEeQv9IVi0CC2y7EKs65bLS4uxoQJEyCVShEaGooHDx4AAKZPn45Vq1ZZtEDiOAQeHvAYNox2Zv/l1qULgrdugebsOaTNnQt9Xh7bJdkEo9ej5MoV5MRuR/JbkUiZMRPFFy/BrWsXBG3cgOBNm+A1YTwkrUPrtRPP4/Hg+/77yPtsF7QpqRb8BLahz8tD4a/H4PHyMLZLsSlZnz5Q//yLxds1FBai5I9rcOvSxeJt14XH8JdR8N13rNbgKLI3bYbH8JchjOhMHfpaNIiMRN7/voBBrWa7lAoMwyBj2TIoJ0yo8TLdmni+8Qby93wFJ79olFgIo9MhfeFCuPh4w2fmTOrQW5Fy7Fiovz8MfXY226XUW/GlS0h9Zw68Z8102g49YGanfv78+bhy5QqOHz8O1/88g7x379745ptvLFYcIXWRm5vLdgmP4Uul8H13DjxHjUbaO+9AdfCg0+28MEYjSm/cQO5nu5AyfTpSIqehKOEEJB3aIzBmHYK3bkGDKW9C2qGDxS6Re5g139UVfkuXImPRIhjLyizStq1wYXC8qsj79kHhzz+bNG1d1un83bvhOeIN1nfy3Hv2RNHJU2D0elbrsHfFFy5An5MN+Qsv2OW2297wXV3hPX0astasZbuUCgXffAtRcEO4d+1q0vRV5Sxwd4OkQ3toTp2ydHmEJdZan43FxUid/Tbcu/eAcsQIqyyD/D+eiwt85ryDzFUfVvm+I2y3GYZB7s7PkP/V1wjatAmuzZuzXZJVmdWpP3DgADZt2oRu3bpV2oEKDQ3FnTt3LFYcIXVhzwN2SFqHIjg2FrqsLKRMmw5tSgrbJdWLNiUVebu/RMrMWUieMgXqI0chbt4MAR9+iODYbfCOmg63Tp2sdr/Sf7MWBQVCOW4sMpebdp+2PShJSgL4fEjatGG7FJvju7lB4OEBXWrtV1eYuk4bijQovnDRLkae5wkEkD3TC4XH4tkuxW4Z1Gpkb9oM3/nlY6/Y87bbnkjDwsATCqE5c4btUlBy5Qo0Z87Aa/Ikk+epLmflqFHI++ILpzvgzVXWWJ/1eXlIiZoB5ZjRkPftY/H2SdVcW7aEKKQh1FUciLf37bahsBBpb78DnosAAas/gsDd+ce3MqtTn52dXWWYGo2G9bMkhLt0Oh3bJdSIJxSiwaRJ8H13DjKXr0DuZ7sc6myesbQUqu8PI3nqW8jZvBnCgAD4L1uKhtu3w+ft2XDv2hV8qdQmtTyatXv37nDx90P+3r02WX59PByoxXvmDLZLYY1i0ECoDh2qdTpT1+mCr7+Cx+uv2c33j2LoUKj272e7DLvEMAwyli+Hz6yZFTtZ9r7ttifes2YhZ1ssjMXFrNWgz8tD1roY+C9bWqenj1SXs0Auh+uTT6L43DlLlUhYZOn1WZucjNRZs+Hz7hybPyqZAF5TpiB/z1cwFBRUet2et9ulN28iZdp0eI4aCeXo0Xazb2BtZnXqn376afzwww8Vvz/8z9qxYwciIiIsUxkhdZSfn892CSYRhYQgaOsWCOQyJE9+E6U3b7JdUrUYhkHJtetIX7IEKdOjYCwpRsDqjxAQvRKyZ5+BQCZjpa6qsm4wZQo0J0+h5I8/WKjIdAXffgvZC9wZHK8q0k6doDl/vtYzc6as08aSEhT9/jtkzz1nqfLqTSCTQdiwIUpv3GC7FLujPnQIopCQSo/8dJRttz0QuLvBa+JEZK/fwMryGb0e6e8vgO978yGo4xOFaspZOWYM8nZ9Xt/yiB2w5Ppccv060hctQsCqaKe/dNpe8UUi+MycgczVqyu9bq/b7YL9ccjeuAmBMesg7dCB7XJsyqwh61euXIl+/frhxo0b0Ov1WL9+PW7cuIHTp08jISHB0jUSYhI/Pz+2SzAZj8eDx7BhcO/RA5mrPoQwMBAN3poK/n/GqGCTPj8f6u+/R9HxBIhbtIByxAiImzZlu6wKVWXN4/Phv2wpUqJmIPDjGLvsNOvz8lB4LB7B29l55Jq94PH5kLRvj5LEREifeqra6UxZpwu+/Raew4fX6YyhLShHjkBO7HaTH9/HBdqUFKgO/4DgrVsqve5I22574N69G9RHj6AkKanSwRFbyF6/AfJ+L8C1RYs6z1tTzi6enhA1boziS5cgDQurT4mEZZZan4t+/x15//sfgj7+mAZgZpmkfXuojxxF0clTcO/eDYD9bbeNpaXIXBkNlwYNELRhPefGKwLMPFPfrVs3JCUlQa/Xo02bNvj555/h4+ODM2fOIIw2xoQlxSxejmguF29vBK5dA0m7tkh+cwo058+zVgtjMKDo5Emkvv0OMj5YAmFAAIJjt8F37rt21aEHqs9aoFDAd/48pC9YCMZgsHFVtcuOiYH3jBl21wFlg8egQVAdOFjjNLWt08ayMhT+dhyyvn0tWZpFiEJCYNRooM/JYbsUu8Do9chYshR+ixeB98gjcB1x28023zlzkPXxehi1WpstU/3LLzCWlEAxcKBZ89eWs9e4scj97DOz2ib2wxLrs+r776Hatw9B69dTh95OeM+IQu6OHTAUaQDY13Zbm5yMlLfeguz53mY/KtkZmP1w+SZNmuCTTz6xZC2E1Ivajh71U1ey556DNDwc2etioD78A3zeebvOlzaaS5ucjIL9+1GSlAS3Ll3g8+67EPra9wAoNWXt2rIlZM/3RvbGjfCZOdN2RdWiODEREAggadOa7VLsgqhRI+gyM2AsLa32CpXa1umCffvgMWSw3X6Be776CvK/+QbekZFsl8K6nNhYKAa8BFFQ0GPvOfK2my0CDw94vv46crZuhc8M64/PUXbvHgq+3YvgzZvMbqO2nF28vSH0D0DJ1auQtG1r9nIIu+q7Pufu/Ay6lBQErF5tt9t2LuJLpWgwdQqyY2Lgt3CB3Wy3C+Pjkb/nK/gvXw5hQADb5bDK7NNFBoMB3333HZYtW4Zly5Zh37590DvQoF/E+QQ4+MoscHeH36KFUAwaiJSoGVWONmopxpISqA4dQvKUqcjZtg3u3bqh4c6daDBpkt136IHas/YYPBhGdSEK4+1jBHLGYEDOxk3wtsHOtyORPfscCo8dq/b9mnJmtFoU/vwL5P37W6M0i5BGRKD44kWbnk21RyVJSdDevw/5gAFVvu/o2262yPv2ge7+A6uPy2LUaJCxZCn8ly8DTyQyux1TcvaaOAG5Oz41exmEfeauz4zRiMxVH4LRlsF34QLq0Nsht86dweh0KL50ifXtNqPXI2vNGmh+P42gLZs536EHzOzUX79+Hc2bN8eYMWMQFxeHuLg4jBkzBs2aNcO1a9csXSMhJrGXo4b1JQ0LQ/D2WJTdvIWUWbOgy8y0SLsMw6Dkjz+Q/sEHSJkxA4xWi4A1axCwYkX5o5IcaHRQU7L2nTcX+V99De0//1i/oFrkf/MNZP1esMv7/Nkk7/cC1EeOVPt+TTkXHDwIxUv9H7uU257weDzIX+iHwho+o7MzFGmQFfMx/BYsqHYb4yzbbjb4zp+HrI9WW+1JKgzDIH3JEjSYOhVCX996tWVKzkJfXwi8lDTIpAMzZ302arVImzcP4mZN0WDKFIfaH+EanznvIHvjJqhYvLVMn52NlMhpELdsBb+FC8Cvx8FGZ2LW3tDEiRMRGhqKixcvwvPfndT8/HyMHTsWkydPxunTp01qJzo6Gvv378fNmzchkUjQpUsXfPjhh2hRxQAsDMPgxRdfxNGjRxEXF4fBgwebUzpxYkVFRWyXYDF8kQjeUdNRevs20t9fAFnv3vB4xbzBwPR5eVAdOgTNiRMQt2oF5ejREDdubIWqbceUrHkiEfyXLUXa/PkI3rzZZo/be5Q+NxdFvx1HcOw2VpZvzwRyOfgSKXSZWVVeIVJdzoxeD/UPP6KhAww4qBg4ACnTpkM+cCAnd1Qzo1fCe1pkjbcTOdO229ZcvL0hHzAAebt2wWviRIu3n//FF3Bt2Qpu4Z3q3ZapOTeYOBFZa9cicN26ei+T2F5d12dDURHS5rwLj1dfgaxXL+sURSxGIJNBOXo0Hqxahdyu3Wy+fEavh+bMGfgteN/uxntim1md+qSkpEodegDw9PTEihUr0LFjR5PbSUhIQGRkJDp27Ai9Xo/33nsPffr0wY0bN+Dm5lZp2o8//piTO0TEdMHBwWyXYHGuzZsjOHYb8r/6GslTp8J37jyIGz9R63yMwQDNqVNQHTwIxmCEYtBAKGNjwRMKbVC19ZmatdDPDw3enFJ+6eiqaFa2IVkxMfCOiqLB8aqhGDgA6u8PVdkhqS5n1eHDkPftU69LgW2FL5HA9clWtY7074zUR47ApYE3pLXsFzjjttuWFIMHITUqCmX37kH8RO3fD6YqvngRJVeuImDN6tonNoHJ2+3AQPDd3FB6+zY9xswB1WV91mVlIX3ePHjPmAFJu3ZWrIpYkuzZZ+AjlUDC0i0SypEjwH+kn0jM7NQ3b94cmZmZCA0NrfR6VlYWmtbhqMnRo0cr/b5r1y74+Pjg0qVL6NGjR8XrSUlJWLt2LS5evAh/f39zSiYckJOTA4UTjpLKEwigHDkCsmefQWb0KriGPgmv8eOr7NBo799Hwf44lFy9Avdu3eA7fz5cvL1ZqNq66pK1W+dwlF6/hvwv90A5coSVK6us+HIieEIhDY5XA7cuXZD32S4oJ0x47KBLVTkzBgNUBw461JUPnm+8gaw1aznVqdelp6Pgu30I3ra11mmdddttKzweD77z5iF96VIEb91qkQOIuqwsZG/ajKBNmyx2MLQuOXtNnIjszZsR+NFHFlk2sR1Tcy67ew8ZS5bA74PFFj0YRWxD7e0N7yZN2C6D/IfJW361Wl3xEx0djaioKHz33XdISUlBSkoKvvvuO8ycORMffvih2cWoVCoAgFKprHituLgYb7zxBjZv3mx3z0Qk9qWkpITtEqxKGBCAwA3rIQwOxoM330TJ1asAAGNxMQoOHEDylKnI3bED7j17ouHOnfCaMMEpO/RA3bNWjh+PksuXUXw50UoVPY7R65GzaaNNRqZ2ZDyBAOJWLVF67fpj71WVs/roUciefQZ8sdgW5VmE8N+D0br0dJYrsQ3GYEDGB0vgu+B9k64OcvZtty0IAwPh3qMH8r/+ut5tMTod0hcsgN/CBRC4W+5sWF1yFoWEgMcXoOzePYstn9iGKTkXJyYic/lyBK5ZTR16B0XbbfvDYxiGMWVCPp9f6Wjtw9kevvbf3w1mPB/aaDRi4MCBKCgowKlTpypef/PNN2EwGLBjx46K9mu6p76srAxlZWUVv6vVagQHB0OlUkFuo0eEEXYUFhZCJpOxXYZN6PPzkbV6DQy5uWDAQN6nL+Qv9OXM5UjmZG0oKkLKtOkIXP2RTQ525O3+EnxXMTxeftnqy3J0ZX/9hfyvvobfooWVXn80Z8ZoxIMJExC8ZQv4Eomty6yX4suJKPotHj5vv812KVaXu2MH+AoFPIcPN2l6Lm27rYkxGpE8dSr8Fy2CMDDQ7HYyo1dB0qED5C/0tWB1dc+57O5d5H76KQJWrLBoHcS6asu58LffULD3OwR89CEE7u42rIxYEm23bUetVkOhUNTalzX58vvffvvNIoVVJzIyEteuXavUoT906BDi4+ORmGj62bXo6GgsWbLEGiUSO5eRkcGZDYyLpycCVq6AQaWCgIOXrZqTtcDdHX4L3kf6goUI2rTRquML6HNzUZSQ4FCXiLNJ3KwZtMnJMGq1lUaxfTTnwl9/hXu3bg7XoQcASYf2yNmyBcaSEoes31Ql166j9MYNBKxda/I8XNp2WxOPz4fv3HnIiI5G0MaNZl02r/7xR0AgsHiHHqh7zuLGjcFoddAmJ0NE4y44jJpyzt+7FyUXLyHo4xiHGBOFVI+22/bH5E59z549rVbEtGnTcPjwYZw4cQJBQUEVr8fHx+POnTvw8PCoNP2wYcPQvXt3HD9+/LG25s+fj9mzZ1f8/vBMPXF+/71Cgyu42KEHzM9a3LQpFIMGImtdDHznvmvhqv5f1rp18J4xgwbHqwP3nj1RdPw45H36VLz235wZhkHB198gaOMGNsqrNx6PB8XAAVAd+h6er77CdjlWYSwuRtaaNQiMWVenDiUXt93WIm78BCTt2kF18CA86viUoLK//oLq0PcI2rTRKrWZk7PXxInI/WQH/JfSyRpHUVXODMOUH9TUFMM/eiV9NzoB2m7bn3qtVcXFxbh58yauXr1a6cdUDMNg2rRpiIuLQ3x8PJ545L6aefPm4erVq0hKSqr4AYCYmBh89tlnVbYpFoshl8sr/RBuaOzgj2kjpqtP1vIXXwSMRqgfGajTUoovXwZfLIakdWjtE5MK8v4vQv3Dj5Ve+2/ORcePQ9qpo0PfYiJ/4QUU/nQUJt715nAyV6+G16SJcPnPk3FMQdtuy/IaNw7qQ99Dn51t8jyGoiJkrFgJ/+XLwHMxawzlWpmTs2uL5jAUqqFLS7NCRcQaHs2ZMRiQsXQp+FI3+L47hzr0ToK22/bHrDUrOzsbL730EmQyGUJDQ9GhQ4dKP6aKjIzE7t27sWfPHshkMmRkZCAjI6Ni8AU/Pz+0bt260g8ANGzY8LEDAIQ8ePCA7RKIjdQ3a5933kZBXBzK7tyxUEXlygfH2wTvqCiLtssFLp6eAJ8HfW5uxWsPc2YYBvlf7oHnCNs+vcDSeCIRJGFhKD5zhu1SLK4wPh58sSvcu3at87y07bYsnosLfN6dg8xVpg1czDAMMhYtgveMKLg0aGC1uszN2WvCROR+utPC1RBr+W/OxtJSpL7zDqRhT8Nr3Fj2iiIWR9tt+2NWp37mzJkoKCjAuXPnIJFIcPToUXz++edo1qwZDh06ZHI7W7duhUqlQq9eveDv71/x880335hTFuE4vV7PdgnERuqbNU8oRMDy5chYugyGoiILVQXkf/U15P37Q/DILUPENIoBA6A+fLji94c5a34/DUnbthA4wf17nq++ivxvvmW7DIvSZWUhf/dueM+eZdb8tO22PNeWLSFsGAz1zz/XOm3ep59CEhYGaR1OypjD3JwlrUOhz8qCLivLwhURa3iYs6GgAClRUfB85RUoXurPclXE0mi7bX/M6tTHx8dj3bp1ePrpp8Hn8xESEoKRI0fio48+QnR0tMntMAxT5c/YsWNrnKe6ke8JtzVt2pTtEoiNWCJrF29veEdNR8aixRa5HFqfk4OikyegGDKk3m1xlXv37ig6cbLi96ZNm4JhGOR98T8oR49isTLLcWnQAHw3N2j/+YftUiyCMRqRsXQpfOfPrzTIYV3Qtts6Gkydivw9X8FQUFDtNJqzZ1F25y4833jD6vXUJ2evCeORR2frHULTpk2hS0tDysxZ8Jk1C24REWyXRKyAttv2x6xOvUajgY+PDwDA09MT2f/et9WmTRtcvnzZctURUgd3795luwRiI5bKWhoWBkn79sjbWfUYHXWRtS6GBserJ55QCFGTxii9dQtAec7F5y/AtXkLp7r6QTlyBPJ2f8l2GRaRv3s33DpHQNysmdlt0LbbOvgiEbxnRCFz9eoq39elpyN3+3b4LVpo1kj5dVWfnCXt20ObklLp9hxin+7+9hvS3nsf/suXwbVVK7bLIVZC2237Y9beZ4sWLXDr352udu3aITY2Fqmpqdi2bRv8/f0tWiAhpjIajWyXQGzEkll7jhqJstu3oDl7zuw2ii9dAt/VFZJQGhyvvjwGD4Yq7gCA8pzzdu2C0snuxXR98knokpNhKCxku5R6Kb11G8UXLsJzRP3O8tK223qkHTpA4C5D0clTlV43arVIX7gIfosX2+wRi/XN2WvsGOTt2mWZYohVaM6fBz7/HIEx6yD6z9OsiPOh7bb9MatTP2PGDKSnpwMAFi9ejCNHjiA4OBjr16/HypUrLVogIaZq0aIF2yUQG7Fk1jweD36LFyNn2zboMjLqPD+j1yNn82Z4z6DB8SxB3KoVym7fBqPToWFJCUQhIXBRKtkuy+IUQ4dCtX8/22WYzVhWhsxV0fBbvKjeZ3lp221d3jOikLtjBwxFmorXslatgucbb0AUEmKzOuqbs7RjR5Td/gv6/HwLVUQsSX30KPJ3f4kmsbF1fgIGcTy03bY/ZnXqR44cWXHfe1hYGO7fv4+LFy8iJSUFr776qiXrI8RkD68eIc7P0lnzpVL4LV6E9AULwWi1dZo3f89XkPd/CQKFwqI1cRWPx4Nb9+4oOnUKKRs3QTl+HNslWYXsuWdRePw4GIOB7VLMkrV2LZRjxlhktHTadlsXXypFgylvIjsmBgBQEHcAfIUCsmefsWkdlshZOWY08r/4wgLVEEvK+2I3NL+fRuC6tfgrOZntcogN0Hbb/pj8MNLZs2eb3Oi6devMKoYQQtgifuIJeL7+GjI//Ah+CxeYNI8+JwdFp04ieNs2K1fHLYoBLyF58ptgQkIg/Hf8FmfDc3GBe7fuKEpIgOzZZ9kup06KTp4E9AbIevViuxRiIreICKh/PIK8L7+E5swZBK1fz3ZJZpFGRCB31y4YCgud4mkYjo5hGGSvWweeUAi/pUtsMjYDIaRqPMbEYZ+feca0I7o8Hg/x8fH1KsqS1Go1FAoFVCoV5HI52+UQK9LpdBAKhWyXQWzAmllnrYuBuEljKAYNqnXatPfeh3LkCLg++aRVauGyjKVLIR83DtLgYLZLsRqDSoW0+e8heMtmtksxmT4vD6mz30bw1i0Wuxebtt22YVCrkfr2Owj46ENWLo+2VM5FCQkovXEDDaZOtUBVxFyMTof0xR9A0rYNPF97reJ1Wp+5gXK2HVP7siafqf/tt98sUhgh1nLr1i20bt2a7TKIDVgza+8ZUUiZHgVxy5ZwreGeseKLF8GXSKhDbyV+ixbh2rVraO3EnXqBQgGhny9Kb92Ga4vmbJdTK4ZhkLFkKXznvmvRwdVo220bArkcDT/ZztryLZWzW48eyPv8fzCM0kDg7maBykhdGTUapM6dC4/BgyHr3bvSe7Q+cwPlbH/o2UuEEPIfPIEA/suXIXNlNAxqdZXTMHo9crZsgXfUdBtXR5yN58iRyN+9m+0yTFLwzbeQtGtHj6kirOLxePB4/TUUfP0V26Vwkj43FynTo+A1btxjHXpCCHuoU0+cBo3EyR3WztpFqYTP27ORvnARmCoe25K/Zw/kLw2gwfGsjAvrtLhxYxgK8u1+RO+yu3dRlJAA5dgxFm+bCzkTy+Yse+45FP3+O4wlJRZrk9RO++ABUme/Dd/35kMaFlblNLQ+cwPlbH+oU0+cBo3EyR22yFrSti3cunRB7vbKl6vqs7NRdOoUFINrv+ee1A9X1mmP4cNR8O1etsuoFqPVInP5cvh9sBg8vuV3G7iSM9dZMmcenw/P4cNR8O23FmuT1Kzkj2tIX7wYAR+ugrhp02qno/WZGyhn+0OdeuI0+FbY2ST2yVZZe7wyHNqUFBSd+r3itax1MfCZNcsqnRtSGVfWabdu3aA5ewaMTsd2KVXK3rABHq++BqGvr1Xa50rOXGfpnGV9+6Lwt+MwlpVZtF3yuKKTp5CzaROC1q+H0M+vxmlpfeYGytn+UCLEaTRu3JjtEoiN2CprHo8HvwULkLdzJ7QpqSi+cAF8Nze6p9hGuLJO8/h8yHr3RuEvv7BdymM0Z8/BoFJD3reP1ZbBlZy5ztI58wQCeAwZjIJ9+yzaLqlMdfAgVAcOIHDDeghMeIoUrc/cQDnbH+rUE6fx999/s10CsRFbZs13dYXf0iXIWLQIOVu30uB4NsSlddpj8GAUHDjAdhmVGAoKkLN1K3znzbXqcriUM5dZI2d5//4o/PkXMFqtxdvmOoZhkPPJJyj54xoCPvoQfLHYpPlofeYGytn+sNqpP3HiBAYMGICAgADweDwceGSHpqioCNOmTUNQUBAkEgmefPJJbNu2jZ1iid1zcTH5CY3Ewdk6a1FQELwmToDniBEmnakglsGldZrv5gb37j3wYOIkZKxcicL4+GqfvmALDMMgY9ly+Lw9G3w36z42jEs5c5k1cua5uEDxUn8UHDxo8ba5jDEakRkdDTCA7/vvgScQmDwvrc/cQDnbH1YT0Wg0aNeuHcaPH4+hQ4c+9v7s2bMRHx+P3bt3o1GjRvj555/x1ltvISAgAAMHDmShYmLPGjZsyHYJxEbYyNqtSxebL5PruLZOK0eNhOfIEdDevQvNuXNIX7wYxsIiuLZsAWl4OKRPPWX1DvZDqrgDEDdrCknbtlZfFtdy5ipr5awYOBAPJr8JjyFDwKOORr0Zy8qQ/v4CuHXtCo8hg+s8P63P3EA52x9Wz9T369cPy5cvx5AhQ6p8//Tp0xgzZgx69eqFRo0aYfLkyWjXrh3Onz9v40qJI7h79y7bJRAboay5gYs583g8iJs0gfKNNxAUE4Pg7bGQv/QSyu7cQdq8+XgweTKy1q+H5uxZGEtLrVKD9sEDqI8egdekSVZp/1FczJmLrJUzTySCvG8fqA4ftkr7XGJQq5EaNQOKQQPN6tADtD5zBeVsf+z6kGaXLl1w6NAhjB8/HgEBATh+/Dhu376NmJiYaucpKytD2X9GQlWzePkisS2xifd7EcdHWXMD5Vw+iJ5ry5ZwbdkSGDsWjF6P0j//hObsWeR9sRswGODatg3cwsMhadMGPJGoXstjdDpkLF0G/yUf1OmS2/qgnLnBmjkrhg5F8ptToBgwwGZ/t85Gl5mJtHnz4DN7NiRt2pjdDq3P3EA52x+77tRv3LgRkydPRlBQEFxcXMDn8/HJJ5+gR48e1c4THR2NJUuW2LBKYi/8annMCnEelDU3UM6P47m4QNKmTcVON6PVouTaNWjOnkXuJzsAPh+SDu3h1rkzXFu1qvPlyDlbt0ExaBCEgYHWKL9KlDM3WDNnvlgM2bPPQH30KBT9+1ttOc6q7M6d8oN5S5dAFBJSr7ZofeYGytn+2PXo9xs3bsTZs2dx6NAhXLp0CWvXrkVkZCR+/fXXaueZP38+VCpVxU9ycrINKyZsun//PtslEBuhrLmBcq4dTySC9Kmn4P3WWwjethWB69ZC0qYNCuPjkRwZiZTpUcjdtQulN2+CMRprbKv48mXoUlOhGPCSjaovRzlzg7Vz9hg+HAXffVfr3zmprPhyIjJXrETg2jX17tADtD5zBeVsf+z2TH1JSQnee+89xMXFof+/R13btm2LpKQkrFmzBr17965yPrFYTJeEcJREImG7BGIjlDU3UM51x3d1hVvnznDr3BkAYNRoUHz5MtSHD6P01m3w3d0g7dgRbuHhEDVuDB6PBwAwFBYie/0GBG3aaPOaKWdusHbOfIkE7t26ofDXXyHv08eqy3IWhfHxKNi3H4EbNkDgbplBOGl95gbK2f7Ybadep9NBp9OBz698MYFAIICRjsKSKjRo0IDtEoiNUNbcQDnXX/mj8rrDvXt3AOUDYRVfvIj8b76B9u49CDw8IA3vhOJz5+EdNR0CmczmNVLO3GCLnD1few0p06Mge/75igNWbDEUacBoy+CiVLJaR3Xyv/kWJYmJCIpZV++xOP6L1mduoJztD6ud+qKiIvz9998Vv9+7dw9JSUlQKpVo2LAhevbsiTlz5kAikSAkJAQJCQn43//+h3Xr1rFYNbFXycnJUCgUbJdBbICy5gbK2fIEcjlkzz4L2bPPAgD0eXkoPn8Bst69IQ0LY6UmypkbbJEz380N0k4dUZSQAFmvXlZd1qOMpaUoSUyE5tw5lP75J/hiV/BcxTDk5UMUEgJp53C4dewIgYeHTet6FMMwyNm0GUxZKfxXrgCPb9k7cWl95gbK2f6w2qm/ePEinnnmmYrfZ8+eDQAYM2YMdu3aha+//hrz58/HiBEjkJeXh5CQEKxYsQJTpkxhq2Rix9zd3dkugdgIZc0NlLP1uSiVkL/Ql9UaKGdusFXOniNGIHX223Dv2dOqZ+sZrRYlf/wBzdmzKP3jGiAQQPpUB8ie6w3v6dMrRuFnGAa6+/ehOXsOGcuWw6BSQdysGaThnSB9+mkIbPj3z+j1yFi2HOImjaEcPc0qy6D1mRsoZ/vDYxiGYbsIa1Kr1VAoFFCpVJDL5WyXQ6woLy8PSju9zI1YFmXNDZQzN1DO3GDLnLM3bIQk7Cm4d+1qsTYZvR6lN25Ac/YcSpKSAIaBpG0bSMM7Q9KmNXhCoWntMAzK/voLxefOo/jiRRhLiuHaslV5J/+pp8C30r3KxpISpM2bD/kLfSHv188qywBofeYKytl2TO3L2u099YTUVVpaGm1gOIKy5gbKmRsoZ26wZc7K0aOQNndevTr1jNGIslu3oDl3DiWXLsOoLYMkNBTSTuFQjhkNvpmDMvN4PLg2bw7X5s2hHDUSjMGA0ps3UXzuPPK/+grQ6eHaujXcOofDtV078C1wv7s+Px9p786F14QJcOscXu/2akLrMzdQzvaHOvXEadCVGNxBWXMD5cwNlDM32DJngYcHxM2bQ3P+PNw6dTJpHoZhoL17F5qzZ8vPoGs0cG3RAtJO4fAcPhx8N8uMDv8onkAASWgoJKGh8Bo/DoxOh9Lr16E5ew65n+0qvyKgXbvyTn7r1uC51G3XXZuSivQFC+A7by5cW7a0ymf4L1qfuYFytj/UqSdOQyqVsl0CsRHKmhsoZ26gnLnB1jkrx41F+oKF1XbqGYaBLjm5vBN//kL5ve6Nn4A0vDP8ly5l5UkQAMATCiFp3x6S9u0BAEatFqVXrqDo5CnkbN0GnkgISYenIA3vBNeWLSvu3a9K6c2byFz1IQJWLIcwMNAm9dP6zA2Us/2hTj1xGhkZGfSIDY6grLmBcuYGypkbbJ2zi1IJUcOGKE5MhLRDBwCALj0dmnPnUHzuPPQ5ORAFB0Ea3hm+778HF09Pm9VWF3yRCNKOHSHt2BFA+b3xxZcvo/Cnn5G9fj34EimkTz8Nt87hEDVtWjE4oObsOeR++ikCY9bZ9LPR+swNlLP9oU49cRqedvqFTCyPsuYGypkbKGduYCNn5fhxSHtnDkSNGkGXlgahvx+kncLhPWsmhD4+Nq/HEvgSCdy7dq0YL8BQVITiixdRsG8/yu7cgUAuh7BhMLR37yFow3qrDbxXHVqfuYFytj/UqSdOQ2jiyLPE8VHW3EA5cwPlzA1s5Cz08YHPnHfgolTa7PJzWxO4u0PWqxdkvXoBAAwFBSi5fh3ekZF1vv/eEmh95gbK2f7w2S6AEEvJyspiuwRiI5Q1N1DO3EA5cwNbOUvatHHaDn1VBB4ecO/alZUOPUDrM1dQzvaHOvXEaXh5ebFdArERypobKGduoJy5gXLmBsqZGyhn+0OdekIIIYQQQgghxEE5/T31DMMAANRqNcuVEGu7f/8+3Kz0HFliXyhrbqCcuYFy5gbKmRsoZ26gnG3nYR/2YZ+2Ok7fqc/NzQUABAcHs1wJIYQQQgghhBBSN4WFhVAoFNW+7/SdeqVSCQB48OBBjf8RxLGp1WoEBwcjOTkZcrmc7XKIFVHW3EA5cwPlzA2UMzdQztxAOdsWwzAoLCxEQEBAjdM5faeezy8fNkChUNAfHgfI5XLKmSMoa26gnLmBcuYGypkbKGduoJxtx5QT0zRQHiGEEEIIIYQQ4qCoU08IIYQQQgghhDgop+/Ui8ViLF68GGKxmO1SiBVRztxBWXMD5cwNlDM3UM7cQDlzA+Vsn3hMbePjE0IIIYQQQgghxC45/Zl6QgghhBBCCCHEWVGnnhBCCCGEEEIIcVDUqSeEEEIIIYQQQhwUdeoJIYQQQgghhBAHZbFOfXR0NDp27AiZTAYfHx8MHjwYt27dqjRNaWkpIiMj4eXlBXd3dwwbNgyZmZmVpomKikJYWBjEYjHat2//2HL++ecf8Hi8x37Onj1ba42bN29Go0aN4OrqivDwcJw/f77S+7169Xqs3SlTptTa7tWrV9G9e3e4uroiODgYH330UaX3r1+/jmHDhqFRo0bg8Xj4+OOPa23TXlHO1ee8a9eux9p1dXWttV17RVlXn7VOp8PSpUvRpEkTuLq6ol27djh69Git7dojruZcWlqKsWPHok2bNnBxccHgwYMfm+bUqVPo2rUrvLy8IJFI0LJlS8TExNRarz2inKvPeezYsVXWHBoaWmvN9oarOR8/fhyDBg2Cv78/3Nzc0L59e3z55ZeVpqF9MW7k7Ez7YpRz9Tk7036YpVisU5+QkIDIyEicPXsWv/zyC3Q6Hfr06QONRlMxzaxZs/D9999j7969SEhIQFpaGoYOHfpYW+PHj8err75a4/J+/fVXpKenV/yEhYXVOP0333yD2bNnY/Hixbh8+TLatWuHvn37Iisrq9J0kyZNqtTuozvzj1Kr1ejTpw9CQkJw6dIlrF69Gh988AG2b99eMU1xcTEaN26MVatWwc/Pr8b27B3lXH3OACCXyyu1e//+/RrbtWeUdfVZL1iwALGxsdi4cSNu3LiBKVOmYMiQIUhMTKyxbXvE1ZwNBgMkEgmioqLQu3fvKqdxc3PDtGnTcOLECfz5559YsGABFixY8Nh67wgo5+pzXr9+faU2k5OToVQqMXz48Brbtkdczfn06dNo27Yt9u3bh6tXr2LcuHEYPXo0Dh8+XDEN7YtxI2fAefbFKOfqc3am/TCLYawkKyuLAcAkJCQwDMMwBQUFjFAoZPbu3VsxzZ9//skAYM6cOfPY/IsXL2batWv32Ov37t1jADCJiYl1qqdTp05MZGRkxe8Gg4EJCAhgoqOjK17r2bMnM2PGjDq1u2XLFsbT05MpKyureG3u3LlMixYtqpw+JCSEiYmJqdMy7Bnl/P85f/bZZ4xCoahTu46Esv7/rP39/ZlNmzZVmm/o0KHMiBEj6rQse8SVnP9rzJgxzKBBg0yadsiQIczIkSPNXpa9oJyrFxcXx/B4POaff/4xe1n2gos5P/Tiiy8y48aNq/I92herzJlyduZ9Mcr5/3N25v0wc1ntnnqVSgUAUCqVAIBLly5Bp9NVOlLesmVLNGzYEGfOnKlz+wMHDoSPjw+6deuGQ4cO1TitVqvFpUuXKi2bz+ejd+/ejy37yy+/RIMGDdC6dWvMnz8fxcXFNbZ95swZ9OjRAyKRqOK1vn374tatW8jPz6/z53I0lHPlnIuKihASEoLg4GAMGjQI169fr8vHtWuU9f9nXVZW9tjlfBKJBKdOnTLps9ozruRsjsTERJw+fRo9e/a0eNu2RjlX79NPP0Xv3r0REhJi8bZtjcs5q1Sqis/t7Cjnyjk7674Y5fz/OTvzfpi5XKzRqNFoxMyZM9G1a1e0bt0aAJCRkQGRSAQPD49K0/r6+iIjI8Pktt3d3bF27Vp07doVfD4f+/btw+DBg3HgwAEMHDiwynlycnJgMBjg6+v72LJv3rxZ8fsbb7yBkJAQBAQE4OrVq5g7dy5u3bqF/fv3V1tPRkYGnnjiicfaffiep6enyZ/N0VDOlXNu0aIFdu7cibZt20KlUmHNmjXo0qULrl+/jqCgIJM/uz2irCtn3bdvX6xbtw49evRAkyZNcOzYMezfvx8Gg8Hkz22PuJRzXQQFBSE7Oxt6vR4ffPABJk6caJF22UI5Vy8tLQ1HjhzBnj17LNYmW7ic87fffosLFy4gNjbW5HkcFeVcOWdn3RejnCvn7Kz7YfVhlU59ZGQkrl27ZpWjJQ0aNMDs2bMrfu/YsSPS0tKwevVqDBw4ECdPnkS/fv0q3o+NjcUzzzxjUtuTJ0+u+HebNm3g7++P5557Dnfu3EGTJk0QGhpacV9O9+7dceTIEQt9KsdEOVcWERGBiIiIit+7dOmCVq1aITY2FsuWLTOpDXtFWVe2fv16TJo0CS1btgSPx0OTJk0wbtw47Ny506T57RXlXLWTJ0+iqKgIZ8+exbx589C0aVO8/vrrdWrDnlDO1fv888/h4eFR5YB6joarOf/2228YN24cPvnkE4cc7LCuKOfKOTvrvhjlXDlnZ90Pqw+Ld+qnTZuGw4cP48SJE5WOiPn5+UGr1aKgoKDSEaXMzMx6D1gSHh6OX375BQDw9NNPIykpqeI9X19fiMViCASCx0aDrG3Z4eHhAIC///4bTZo0wY8//gidTgeg/BKPh5+rqnYfvuesKOfacxYKhejQoQP+/vvvOnxK+0NZP561t7c3Dhw4gNLSUuTm5iIgIADz5s1D48aN6/Gp2cW1nOvi4ZUbbdq0QWZmJj744AOH7dRTztVjGAY7d+7EqFGjKt1+44i4mnNCQgIGDBiAmJgYjB49ul6fxxFQzrXn7Az7YpTz4zk7435YfVnsnnqGYTBt2jTExcUhPj7+sctXw8LCIBQKcezYsYrXbt26hQcPHlQ6omaOpKQk+Pv7Ayj/g2jatGnFj0wmg0gkQlhYWKVlG41GHDt2rMZlP/wDfth2SEhIRbuBgYEAyo8InjhxouIPEgB++eUXtGjRwikvvaecTc/ZYDDgjz/+qGjX0VDWtWft6uqKwMBA6PV67Nu3D4MGDarX52YDV3M2l9FoRFlZWb3aYAPlXLuEhAT8/fffmDBhQp3ntRdczvn48ePo378/Pvzww0pnB50R5Wx6zo68L0Y5156zM+yHWYylRtybOnUqo1AomOPHjzPp6ekVP8XFxRXTTJkyhWnYsCETHx/PXLx4kYmIiGAiIiIqtfPXX38xiYmJzJtvvsk0b96cSUxMZBITEytGot61axezZ88e5s8//2T+/PNPZsWKFQyfz2d27txZY31ff/01IxaLmV27djE3btxgJk+ezHh4eDAZGRkMwzDM33//zSxdupS5ePEic+/ePebgwYNM48aNmR49etTYbkFBAePr68uMGjWKuXbtGvP1118zUqmUiY2NrZimrKys4nP4+/sz77zzDpOYmMj89ddfdfo/tgeUc/U5L1myhPnpp5+YO3fuMJcuXWJee+01xtXVlbl+/Xqd/o/tBWVdfdZnz55l9u3bx9y5c4c5ceIE8+yzzzJPPPEEk5+fX5f/YrvA1ZwZhmGuX7/OJCYmMgMGDGB69epVUfNDmzZtYg4dOsTcvn2buX37NrNjxw5GJpMx77//vqn/vXaDcq4+54dGjhzJhIeH19qePeNqzvHx8YxUKmXmz59f6XPn5uZWTEP7YtzI2Zn2xSjn6nN2pv0wS7FYpx5AlT+fffZZxTQlJSXMW2+9xXh6ejJSqZQZMmQIk56eXqmdnj17VtnOvXv3GIYp/8Nr1aoVI5VKGblcznTq1KnSoxxqsnHjRqZhw4aMSCRiOnXqxJw9e7bivQcPHjA9evRglEolIxaLmaZNmzJz5sxhVCpVre1euXKF6datGyMWi5nAwEBm1apVld5/+KiIR3969uxpUt32hHKuPueZM2dWLNfX15d58cUXmcuXL5tUsz2irKvP+vjx40yrVq0YsVjMeHl5MaNGjWJSU1NNqtnecDnnkJCQKmt+aMOGDUxoaGhFzR06dGC2bNnCGAwGk+q2J5Rz9TkzTPnBPIlEwmzfvt2kWu0VV3MeM2ZMrftZtC/GjZydaV+Mcq4+Z2faD7MUHsMwDAghhBBCCCGEEOJwrPacekIIIYQQQgghhFgXdeoJIYQQQgghhBAHRZ16QgghhBBCCCHEQVGnnhBCCCGEEEIIcVDUqSeEEEIIIYQQQhwUdeoJIYQQQgghhBAHRZ16QgghhBBCCCHEQVGnnhBCCCGEEEIIcVDUqSeEEEIIIYQQQhwUdeoJIYQQQgghhBAHRZ16QgghhBBCCCHEQVGnnhBCCCGEEEIIcVD/B9rvzUWbG611AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1024x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "labels.plot(**plot_options, max_num_plots=4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8561ab80-a709-45b6-b49b-b311824750ea",
+   "metadata": {},
+   "source": [
+    "### Question\n",
+    "\n",
+    "1. Can you see the \"shift\" of the label when h increases?\n",
+    "2. What would a shift in the other direction mean?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "ff5fcd1d-47d9-4211-9dde-49484898e98b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#@title Solution\n",
+    "\n",
+    "# TODO"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "051bc1a5-dd70-45a2-8adf-667c152017c5",
+   "metadata": {},
+   "source": [
+    "## Train and evaluate a first model\n",
+    "\n",
+    "We can now train and evaluate our first model using only lagged sales as features.\n",
+    "\n",
+    "We use a train and test protocol to evaluate our model. In classical tabular machine learning, train and test examples can be separated randomly. However, because of the time dependency between our rows, and because we want to apply our forecasting model in the future (and not in the past; we are not archeology), it is important for the training examples to be anterior to the test examples.\n",
+    "\n",
+    "The dataset ranges from `2011-01-29` to `2016-06-19`. We will use the data in `2016` for testing, and interior data to training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e84cc5d7-ab28-4438-94c2-386e55edae30",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "end_train_cutoff = datetime(2016, 1,1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46fa34bd-4b65-4d34-b88d-89f74fe5fac9",
+   "metadata": {},
+   "source": [
+    "Our lagging feature dependency on sales in the last 14 days. Therefore, at the start of the dataset, this feature is not available. For example, on day `2011-01-29`, we have no sales records for 14 days before.\n",
+    "\n",
+    "Therefore, we will start the training dataset on 2011-02-15`. Note that interior values will still be available though the lagging features."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "39ae791c-8935-41e6-b763-f89e58b2042e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_train_cutoff = datetime(2011, 2,15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dea2e24d-094c-4f1a-a249-6692525c54c5",
+   "metadata": {},
+   "source": [
+    "Let's split the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b9e97d60-367f-4ea2-9ba4-8a9582b3a3e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of train examples: 142400\n",
+      "Number of test examples: 11360\n"
+     ]
+    }
+   ],
+   "source": [
+    "def split_train_test(data : tp.EventSet):\n",
+    "    train_data = data.after(start_train_cutoff).before(end_train_cutoff)\n",
+    "    test_data = data.after(end_train_cutoff)\n",
+    "    return train_data, test_data\n",
+    "\n",
+    "features_and_labels = tp.glue(feature_lagged_sales, labels)\n",
+    "train_examples, test_examples = split_train_test(features_and_labels)\n",
+    "\n",
+    "print(\"Number of train examples:\", train_examples.num_events())\n",
+    "print(\"Number of test examples:\", test_examples.num_events())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5496136c-395e-445d-8525-7c0700e5ccbe",
+   "metadata": {},
+   "source": [
+    "We train a separate model for each of the labels and aggregate the predictions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "99474cbc-691e-4cfc-bd14-94058758ec8e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "feature_names: ['f_sales_lag1', 'f_sales_lag2', 'f_sales_lag3', 'f_sales_lag7', 'f_sales_lag14']\n",
+      "label_names: ['label_h1', 'label_h2', 'label_h3', 'label_h4', 'label_h5', 'label_h6', 'label_h7', 'label_h8', 'label_h9', 'label_h10', 'label_h11', 'label_h12', 'label_h13']\n"
+     ]
+    }
+   ],
+   "source": [
+    "feature_names = feature_lagged_sales.schema.feature_names()\n",
+    "label_names = labels.schema.feature_names()\n",
+    "\n",
+    "print(\"feature_names:\", feature_names)\n",
+    "print(\"label_names:\", label_names)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "f4318d8d-e338-4417-9802-5e2c3b7f70ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train model for label 'label_h1'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.318819\n",
+      "Train model for label 'label_h2'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.200427\n",
+      "Train model for label 'label_h3'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.166436\n",
+      "Train model for label 'label_h4'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.285532\n",
+      "Train model for label 'label_h5'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.260156\n",
+      "Train model for label 'label_h6'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.209901\n",
+      "Train model for label 'label_h7'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.246518\n",
+      "Train model for label 'label_h8'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.248286\n",
+      "Train model for label 'label_h9'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.296563\n",
+      "Train model for label 'label_h10'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.221976\n",
+      "Train model for label 'label_h11'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.108882\n",
+      "Train model for label 'label_h12'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.245467\n",
+      "Train model for label 'label_h13'\n",
+      "Train model on 142400 examples\n",
+      "Model trained in 0:00:01.213840\n"
+     ]
+    }
+   ],
+   "source": [
+    "models = []\n",
+    "for label_name in label_names:\n",
+    "    print(f\"Train model for label {label_name!r}\")\n",
+    "\n",
+    "    # To train the model, we use YDF. YDF consumes natively Pandas dataframes so\n",
+    "    # we convert the Temporian EventSets into Pandas DataFrames before training.\n",
+    "    train_examples_df = tp.to_pandas(train_examples)\n",
+    "\n",
+    "    # Configure the learning algorithm\n",
+    "    learner = ydf.GradientBoostedTreesLearner(\n",
+    "        task=ydf.Task.REGRESSION,\n",
+    "        label=label_name,\n",
+    "        num_trees=20,  # Increase the number of trees (e.g., 100) for a better model.\n",
+    "        features=feature_names,\n",
+    "    )\n",
+    "\n",
+    "    # Train the model\n",
+    "    model = learner.train(train_examples_df)\n",
+    "    \n",
+    "    models.append(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4039d9b-227d-4ca6-9a0a-67cf5ea45a8d",
+   "metadata": {},
+   "source": [
+    "Looking at the models can help us understand the input features that matter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "9781b347-b352-48d2-b232-857cd3d0677d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  <div class=\"tab_block\" id=\"cd37-7ded-a488-c93e\"><div class=\"header\"><a id=\"cd37-7ded-a488-c93e_model\" class=\"tab selected\" onclick=\"ydfShowTab('cd37-7ded-a488-c93e', 'model')\">Model</a><a id=\"cd37-7ded-a488-c93e_dataspec\" class=\"tab\" onclick=\"ydfShowTab('cd37-7ded-a488-c93e', 'dataspec')\">Dataspec</a><a id=\"cd37-7ded-a488-c93e_training\" class=\"tab\" onclick=\"ydfShowTab('cd37-7ded-a488-c93e', 'training')\">Training</a><a id=\"cd37-7ded-a488-c93e_variable_importance\" class=\"tab\" onclick=\"ydfShowTab('cd37-7ded-a488-c93e', 'variable_importance')\">Variable importances</a><a id=\"cd37-7ded-a488-c93e_structure\" class=\"tab\" onclick=\"ydfShowTab('cd37-7ded-a488-c93e', 'structure')\">Structure</a></div><div class=\"body\"><div id=\"cd37-7ded-a488-c93e_body_model\" class=\"tab_content selected\"><b>Name</b> : GRADIENT_BOOSTED_TREES<br><b>Task</b> : REGRESSION<br><b>Label</b> : label_h13<br><b>Features (5)</b> : f_sales_lag1 f_sales_lag2 f_sales_lag3 f_sales_lag7 f_sales_lag14<br><b>Weights</b> : None<br><b>Trained with tuner</b> : No<br><b>Model size</b> : 297 kB<br></div><div id=\"cd37-7ded-a488-c93e_body_dataspec\" class=\"tab_content\"><pre class=\"ydf_pre\">Number of records: 142400\n",
+       "Number of columns: 6\n",
+       "\n",
+       "Number of columns by type:\n",
+       "\tNUMERICAL: 6 (100%)\n",
+       "\n",
+       "Columns:\n",
+       "\n",
+       "NUMERICAL: 6 (100%)\n",
+       "\t0: &quot;f_sales_lag1&quot; NUMERICAL mean:29.6716 min:0 max:763 sd:31.9632 dtype:DTYPE_INT64\n",
+       "\t1: &quot;f_sales_lag2&quot; NUMERICAL mean:29.6753 min:0 max:763 sd:31.965 dtype:DTYPE_INT64\n",
+       "\t2: &quot;f_sales_lag3&quot; NUMERICAL mean:29.6867 min:0 max:763 sd:31.9706 dtype:DTYPE_INT64\n",
+       "\t3: &quot;f_sales_lag7&quot; NUMERICAL mean:29.7111 min:0 max:763 sd:31.9726 dtype:DTYPE_INT64\n",
+       "\t4: &quot;f_sales_lag14&quot; NUMERICAL mean:29.7353 min:0 max:763 sd:32.0181 dtype:DTYPE_INT64\n",
+       "\t5: &quot;label_h13&quot; NUMERICAL mean:29.6564 min:0 max:763 sd:31.9498 dtype:DTYPE_INT64\n",
+       "\n",
+       "Terminology:\n",
+       "\tnas: Number of non-available (i.e. missing) values.\n",
+       "\tood: Out of dictionary.\n",
+       "\tmanually-defined: Attribute whose type is manually defined by the user, i.e., the type was not automatically inferred.\n",
+       "\ttokenized: The attribute value is obtained through tokenization.\n",
+       "\thas-dict: The attribute is attached to a string dictionary e.g. a categorical attribute stored as a string.\n",
+       "\tvocab-size: Number of unique values.\n",
+       "</pre></div><div id=\"cd37-7ded-a488-c93e_body_training\" class=\"tab_content\"><p>The following evaluation is computed on the validation or out-of-bag dataset.</p><pre class=\"ydf_pre\">Number of predictions (with weights): 1\n",
+       "Task: REGRESSION\n",
+       "Loss (SQUARED_ERROR): 18.9616\n",
+       "\n",
+       "RMSE: 4.35449\n",
+       "Default RMSE: : 0\n",
+       "</pre><div style='display: grid; gap: 0px; grid-auto-columns: min-content;'><div style='grid-row:1 / span 1; grid-column:1 / span 1;'><script src='https://www.gstatic.com/external_hosted/plotly/plotly.min.js'></script>\n",
+       "<div id=\"chart_cd37_7ded_a488_c93eself_eval_item0\" style=\"display: inline-block;\" ></div>\n",
+       "<script>\n",
+       "  Plotly.newPlot(\n",
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+       "y: [29.8634,28.1425,26.6483,25.361,24.2535,23.3076,22.5065,21.8207,21.2438,20.7499,20.3421,19.9921,19.6952,19.4478,19.2441,19.0706,18.9242,18.8005,18.6971,18.6077],\n",
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+       "<div id=\"chart_cd37_7ded_a488_c93eself_eval_item1\" style=\"display: inline-block;\" ></div>\n",
+       "<script>\n",
+       "  Plotly.newPlot(\n",
+       "    'chart_cd37_7ded_a488_c93eself_eval_item1',\n",
+       "    [{\n",
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+       "y: [29.8634,28.1425,26.6483,25.361,24.2535,23.3076,22.5065,21.8207,21.2438,20.7499,20.3421,19.9921,19.6952,19.4478,19.2441,19.0706,18.9242,18.8005,18.6971,18.6077],\n",
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+       "</div></div></div><div id=\"cd37-7ded-a488-c93e_body_variable_importance\" class=\"tab_content\"><p><a target=\"_blank\" href=\"https://ydf.readthedocs.io/en/latest/cli_user_manual#variable-importances\">Variable importances</a> measure the importance of an input feature for a model.</p><div id=\"cd37-7ded-a488-c93e_vi\" class=\"variable_importance\"><select onchange=\"ydfShowVariableImportance('cd37-7ded-a488-c93e_vi')\"><option value=\"INV_MEAN_MIN_DEPTH\">INV_MEAN_MIN_DEPTH</option><option value=\"NUM_AS_ROOT\">NUM_AS_ROOT</option><option value=\"NUM_NODES\">NUM_NODES</option><option value=\"SUM_SCORE\">SUM_SCORE</option></select><div id=\"cd37-7ded-a488-c93e_vi_body_INV_MEAN_MIN_DEPTH\" class=\"content selected\"><pre class=\"ydf_pre\">    1.  &quot;f_sales_lag1&quot;  0.525690 ################\n",
+       "    2.  &quot;f_sales_lag2&quot;  0.304938 #####\n",
+       "    3.  &quot;f_sales_lag7&quot;  0.289027 ####\n",
+       "    4. &quot;f_sales_lag14&quot;  0.225436 #\n",
+       "    5.  &quot;f_sales_lag3&quot;  0.186306 \n",
+       "</pre></div><div id=\"cd37-7ded-a488-c93e_vi_body_NUM_AS_ROOT\" class=\"content\"><pre class=\"ydf_pre\">    1. &quot;f_sales_lag1&quot; 13.000000 ################\n",
+       "    2. &quot;f_sales_lag2&quot;  4.000000 #\n",
+       "    3. &quot;f_sales_lag7&quot;  3.000000 \n",
+       "</pre></div><div id=\"cd37-7ded-a488-c93e_vi_body_NUM_NODES\" class=\"content\"><pre class=\"ydf_pre\">    1. &quot;f_sales_lag14&quot; 153.000000 ################\n",
+       "    2.  &quot;f_sales_lag1&quot; 151.000000 ###############\n",
+       "    3.  &quot;f_sales_lag7&quot; 122.000000 ##########\n",
+       "    4.  &quot;f_sales_lag2&quot; 111.000000 ########\n",
+       "    5.  &quot;f_sales_lag3&quot; 67.000000 \n",
+       "</pre></div><div id=\"cd37-7ded-a488-c93e_vi_body_SUM_SCORE\" class=\"content\"><pre class=\"ydf_pre\">    1.  &quot;f_sales_lag1&quot; 336744478.055170 ################\n",
+       "    2.  &quot;f_sales_lag7&quot; 46290344.836786 #\n",
+       "    3.  &quot;f_sales_lag2&quot; 39095104.026775 #\n",
+       "    4. &quot;f_sales_lag14&quot; 22906672.527053 \n",
+       "    5.  &quot;f_sales_lag3&quot; 5948393.768780 \n",
+       "</pre></div></div><p>Those variable importances are computed during training. More, and possibly more informative, variable importances are available when analyzing a model on a test dataset.</p></div><div id=\"cd37-7ded-a488-c93e_body_structure\" class=\"tab_content\"><b>Num trees</b> : 20<br><p>Only printing the first tree.</p><pre class=\"ydf_pre\">Tree #0:\n",
+       "    &quot;f_sales_lag1&quot;&gt;=51.5 [s:368.031 n:128277 np:20166 miss:0] ; pred:6.0719e-08\n",
+       "        ├─(pos)─ &quot;f_sales_lag1&quot;&gt;=112.5 [s:524.597 n:20166 np:2792 miss:0] ; pred:4.44189\n",
+       "        |        ├─(pos)─ &quot;f_sales_lag7&quot;&gt;=179.5 [s:1077.7 n:2792 np:568 miss:0] ; pred:10.1554\n",
+       "        |        |        ├─(pos)─ &quot;f_sales_lag1&quot;&gt;=218.5 [s:1768.53 n:568 np:234 miss:0] ; pred:16.6514\n",
+       "        |        |        |        ├─(pos)─ &quot;f_sales_lag1&quot;&gt;=298.5 [s:1079.31 n:234 np:85 miss:0] ; pred:21.6756\n",
+       "        |        |        |        |        ├─(pos)─ pred:26.0253\n",
+       "        |        |        |        |        └─(neg)─ pred:19.1943\n",
+       "        |        |        |        └─(neg)─ &quot;f_sales_lag2&quot;&gt;=141.5 [s:530.306 n:334 np:204 miss:0] ; pred:13.1314\n",
+       "        |        |        |                 ├─(pos)─ pred:14.9697\n",
+       "        |        |        |                 └─(neg)─ pred:10.2466\n",
+       "        |        |        └─(neg)─ &quot;f_sales_lag14&quot;&gt;=112.5 [s:298.584 n:2224 np:914 miss:0] ; pred:8.49639\n",
+       "        |        |                 ├─(pos)─ &quot;f_sales_lag1&quot;&gt;=180.5 [s:517.99 n:914 np:206 miss:0] ; pred:10.5651\n",
+       "        |        |                 |        ├─(pos)─ pred:14.7844\n",
+       "        |        |                 |        └─(neg)─ pred:9.33742\n",
+       "        |        |                 └─(neg)─ &quot;f_sales_lag2&quot;&gt;=98.5 [s:175.497 n:1310 np:844 miss:0] ; pred:7.05304\n",
+       "        |        |                          ├─(pos)─ pred:8.03741\n",
+       "        |        |                          └─(neg)─ pred:5.2702\n",
+       "        |        └─(neg)─ &quot;f_sales_lag1&quot;&gt;=74.5 [s:110.903 n:17374 np:6149 miss:0] ; pred:3.52372\n",
+       "        |                 ├─(pos)─ &quot;f_sales_lag7&quot;&gt;=74.5 [s:80.4164 n:6149 np:3206 miss:0] ; pred:4.94658\n",
+       "        |                 |        ├─(pos)─ &quot;f_sales_lag2&quot;&gt;=99.5 [s:49.9688 n:3206 np:837 miss:0] ; pred:5.80577\n",
+       "        |                 |        |        ├─(pos)─ pred:6.99501\n",
+       "        |                 |        |        └─(neg)─ pred:5.38559\n",
+       "        |                 |        └─(neg)─ &quot;f_sales_lag14&quot;&gt;=59.5 [s:49.543 n:2943 np:1518 miss:0] ; pred:4.01062\n",
+       "        |                 |                 ├─(pos)─ pred:4.69258\n",
+       "        |                 |                 └─(neg)─ pred:3.28415\n",
+       "        |                 └─(neg)─ &quot;f_sales_lag14&quot;&gt;=60.5 [s:43.0703 n:11225 np:4245 miss:0] ; pred:2.74428\n",
+       "        |                          ├─(pos)─ &quot;f_sales_lag2&quot;&gt;=54.5 [s:28.6994 n:4245 np:2607 miss:0] ; pred:3.58583\n",
+       "        |                          |        ├─(pos)─ pred:4.01047\n",
+       "        |                          |        └─(neg)─ pred:2.90998\n",
+       "        |                          └─(neg)─ &quot;f_sales_lag2&quot;&gt;=53.5 [s:21.9258 n:6980 np:3420 miss:0] ; pred:2.23248\n",
+       "        |                                   ├─(pos)─ pred:2.71022\n",
+       "        |                                   └─(neg)─ pred:1.77353\n",
+       "        └─(neg)─ &quot;f_sales_lag1&quot;&gt;=24.5 [s:90.523 n:108111 np:35904 miss:1] ; pred:-0.828547\n",
+       "                 ├─(pos)─ &quot;f_sales_lag14&quot;&gt;=37.5 [s:36.464 n:35904 np:14178 miss:0] ; pred:0.520719\n",
+       "                 |        ├─(pos)─ &quot;f_sales_lag2&quot;&gt;=36.5 [s:20.8318 n:14178 np:8046 miss:0] ; pred:1.26823\n",
+       "                 |        |        ├─(pos)─ &quot;f_sales_lag14&quot;&gt;=58.5 [s:18.0053 n:8046 np:2264 miss:0] ; pred:1.66668\n",
+       "                 |        |        |        ├─(pos)─ pred:2.34479\n",
+       "                 |        |        |        └─(neg)─ pred:1.40115\n",
+       "                 |        |        └─(neg)─ &quot;f_sales_lag7&quot;&gt;=51.5 [s:9.95915 n:6132 np:1337 miss:0] ; pred:0.745406\n",
+       "                 |        |                 ├─(pos)─ pred:1.34305\n",
+       "                 |        |                 └─(neg)─ pred:0.578764\n",
+       "                 |        └─(neg)─ &quot;f_sales_lag2&quot;&gt;=31.5 [s:16.1688 n:21726 np:9934 miss:0] ; pred:0.0329104\n",
+       "                 |                 ├─(pos)─ &quot;f_sales_lag1&quot;&gt;=37.5 [s:11.149 n:9934 np:4283 miss:0] ; pred:0.471007\n",
+       "                 |                 |        ├─(pos)─ pred:0.854544\n",
+       "                 |                 |        └─(neg)─ pred:0.180318\n",
+       "                 |                 └─(neg)─ &quot;f_sales_lag7&quot;&gt;=29.5 [s:8.96843 n:11792 np:4038 miss:1] ; pred:-0.336158\n",
+       "                 |                          ├─(pos)─ pred:0.0788322\n",
+       "                 |                          └─(neg)─ pred:-0.55227\n",
+       "                 └─(neg)─ &quot;f_sales_lag14&quot;&gt;=17.5 [s:23.0371 n:72207 np:22708 miss:1] ; pred:-1.49945\n",
+       "                          ├─(pos)─ &quot;f_sales_lag3&quot;&gt;=91.5 [s:26.349 n:22708 np:113 miss:0] ; pred:-0.790817\n",
+       "                          |        ├─(pos)─ &quot;f_sales_lag7&quot;&gt;=115.5 [s:1315.96 n:113 np:40 miss:0] ; pred:6.46772\n",
+       "                          |        |        ├─(pos)─ pred:11.3684\n",
+       "                          |        |        └─(neg)─ pred:3.78244\n",
+       "                          |        └─(neg)─ &quot;f_sales_lag14&quot;&gt;=274 [s:16.1727 n:22595 np:15 miss:0] ; pred:-0.827118\n",
+       "                          |                 ├─(pos)─ pred:14.7759\n",
+       "                          |                 └─(neg)─ pred:-0.837483\n",
+       "                          └─(neg)─ &quot;f_sales_lag1&quot;&gt;=12.5 [s:9.11598 n:49499 np:15562 miss:1] ; pred:-1.82454\n",
+       "                                   ├─(pos)─ &quot;f_sales_lag2&quot;&gt;=17.5 [s:4.51143 n:15562 np:6215 miss:1] ; pred:-1.37868\n",
+       "                                   |        ├─(pos)─ pred:-1.1182\n",
+       "                                   |        └─(neg)─ pred:-1.55187\n",
+       "                                   └─(neg)─ &quot;f_sales_lag7&quot;&gt;=12.5 [s:2.74655 n:33937 np:6239 miss:1] ; pred:-2.029\n",
+       "                                            ├─(pos)─ pred:-1.67981\n",
+       "                                            └─(neg)─ pred:-2.10765\n",
+       "</pre></div></div></div>"
+      ],
+      "text/plain": [
+       "<ydf.utils.html.HtmlNotebookDisplay at 0x7f43e3816750>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Information about the last trained model.\n",
+    "models[-1].describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "222350c3-5844-4740-bfaa-d97eda49a683",
+   "metadata": {},
+   "source": [
+    "### Question\n",
+    "\n",
+    "1. Look at the variable importance of the model. Which feature is the most important? Does this make sense?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "481715bf-0f29-47d1-b894-6dc9ee31bfee",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#@title Solution\n",
+    "\n",
+    "# TODO"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0eb93502-4df8-47f5-8ad5-c78df086d52c",
+   "metadata": {},
+   "source": [
+    "This model is not hat accurate, but it will be a good baseline later."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "6eca90e8-356b-4445-bdd8-4d7b3ff5bb71",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "RMSE for label 'label_h1': 12.9159\n",
+      "RMSE for label 'label_h2': 14.4032\n",
+      "RMSE for label 'label_h3': 13.8355\n",
+      "RMSE for label 'label_h4': 12.5704\n",
+      "RMSE for label 'label_h5': 12.3397\n",
+      "RMSE for label 'label_h6': 12.1684\n",
+      "RMSE for label 'label_h7': 12.2219\n",
+      "RMSE for label 'label_h8': 13.6835\n",
+      "RMSE for label 'label_h9': 14.8256\n",
+      "RMSE for label 'label_h10': 14.3367\n",
+      "RMSE for label 'label_h11': 13.1584\n",
+      "RMSE for label 'label_h12': 12.9200\n",
+      "RMSE for label 'label_h13': 12.8116\n"
+     ]
+    }
+   ],
+   "source": [
+    "def evaluate_models(models, test_examples):\n",
+    "    test_examples_df = tp.to_pandas(test_examples)\n",
+    "    for model in models:\n",
+    "        evaluation = model.evaluate(test_examples_df)\n",
+    "        print(f\"RMSE for label {model.label()!r}: {evaluation.rmse:.4f}\")\n",
+    "\n",
+    "evaluate_models(models, test_examples)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97079a53-9b12-4bbb-a771-9ea227a0e2bc",
+   "metadata": {},
+   "source": [
+    "We compute the predictions into an EventSet. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "ce28d2f5-986c-41cc-bb19-408ae77c7f6b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Feature \"item_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"dept_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"cat_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"store_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"state_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "  <div style=\"display: table; margin-bottom:11px; padding:5px; font-size:small; line-height:120%; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">features</span>\n",
+       "        <span style=\"\"> [13]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h1</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h2</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h3</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h4</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h5</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h6</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h7</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h8</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h9</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h10</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h11</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h12</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">label_h13</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">indexes</span>\n",
+       "        <span style=\"\"> [5]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">item_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">dept_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">cat_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">store_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">state_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">events: </span>\n",
+       "      <span style=\"\">11360</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">index values: </span>\n",
+       "      <span style=\"\">80</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">memory usage: </span>\n",
+       "      <span style=\"\">0.8 MB</span>\n",
+       "    </div>\n",
+       "  </div>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_1</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 142 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h1</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h2</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h3</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h4</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h5</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h6</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h7</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h8</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h9</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h10</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h11</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h12</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h13</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-02 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.527</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.352</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.924</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-03 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.527</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.352</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.924</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">60.49</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">48.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">45.02</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">45.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">48.3</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">57.25</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">60.26</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">59.66</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">48.72</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">44.82</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">46.5</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">49.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">58.56</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">63.96</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">55.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">53.44</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">53.5</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">57.14</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">63.44</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">68.78</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">62.73</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">56.46</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">53.38</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">52.07</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">57.53</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">65.56</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_2</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 142 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h1</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h2</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h3</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h4</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h5</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h6</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h7</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h8</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h9</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h10</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h11</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h12</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h13</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-02 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.527</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.352</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.924</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-03 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.527</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.352</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.924</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">64.16</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">51.79</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">45.78</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">44.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">49.52</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">61.31</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">71.87</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">61.81</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">50</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">45.41</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">44.75</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">48.4</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">60.46</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">58.46</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">53.82</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">49.1</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">50.17</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">53.73</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">59.87</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">60.71</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">58.78</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">54.08</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">50.43</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">49.66</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">55.32</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">62.07</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 142 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h1</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h2</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h3</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h4</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h5</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h6</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h7</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h8</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h9</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h10</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h11</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h12</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">label_h13</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-02 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.195</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.129</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.04</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.736</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.434</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.924</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.57</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-01-03 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.527</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.884</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.18</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.352</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">9.69</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.27</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.45</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.54</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.58</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-21 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">105.9</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">84.24</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">78.26</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">78.89</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">75.42</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">97.62</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">116.3</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">103.5</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">78.34</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">73.62</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">67.89</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">74.55</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">94.64</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">2016-05-22 00:00:00+00:00</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">124.3</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">92.77</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">88.03</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">84.63</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">90.06</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">128.6</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">140.8</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">120.1</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">97.74</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">82.08</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">78.71</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">90.4</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">120</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <span style=\"\">… (77 more indexes not shown)</span>\n",
+       "</div>\n"
+      ],
+      "text/plain": [
+       "indexes: [('item_id', str_), ('dept_id', str_), ('cat_id', str_), ('store_id', str_), ('state_id', str_)]\n",
+       "features: [('label_h1', float32), ('label_h2', float32), ('label_h3', float32), ('label_h4', float32), ('label_h5', float32), ('label_h6', float32), ('label_h7', float32), ('label_h8', float32), ('label_h9', float32), ('label_h10', float32), ('label_h11', float32), ('label_h12', float32), ('label_h13', float32)]\n",
+       "events:\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_1' state_id=b'CA' (142 events):\n",
+       "        timestamps: ['2016-01-02T00:00:00' '2016-01-03T00:00:00' '2016-01-04T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'label_h1': [ 5.9476  5.9476  5.9476 ... 63.819  60.4862 63.9616]\n",
+       "        'label_h2': [ 6.7054  6.7054  6.7054 ... 49.849  48.839  55.8435]\n",
+       "        'label_h3': [ 7.7405  7.7405  7.7405 ... 43.9485 45.0236 53.436 ]\n",
+       "        'label_h4': [ 8.5272  8.5272  8.5272 ... 42.843  45.8437 53.5009]\n",
+       "        'label_h5': [ 8.8836  8.8836  8.8836 ... 45.4961 48.3014 57.1414]\n",
+       "        'label_h6': [ 9.1797  9.1797  9.1797 ... 52.018  57.2482 63.4408]\n",
+       "        'label_h7': [ 9.3523  9.3523  9.3523 ... 64.5124 60.2594 68.7823]\n",
+       "        'label_h8': [ 9.9244  9.9244  9.9244 ... 61.6518 59.6598 62.7326]\n",
+       "        'label_h9': [10.2654 10.2654 10.2654 ... 52.0042 48.7187 56.4638]\n",
+       "        'label_h10': [10.5675 10.5675 10.5675 ... 44.4881 44.8164 53.3825]\n",
+       "        ...\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_2' state_id=b'CA' (142 events):\n",
+       "        timestamps: ['2016-01-02T00:00:00' '2016-01-03T00:00:00' '2016-01-04T00:00:00' ...\n",
+       "     '2016-05-20T00:00:00' '2016-05-21T00:00:00' '2016-05-22T00:00:00']\n",
+       "        'label_h1': [ 5.9476  5.9476  5.9476 ... 61.2635 64.1645 58.4591]\n",
+       "        'label_h2': [ 6.7054  6.7054  6.7054 ... 50.5733 51.7936 53.8177]\n",
+       "        'label_h3': [ 7.7405  7.7405  7.7405 ... 43.9334 45.7807 49.0956]\n",
+       "        'label_h4': [ 8.5272  8.5272  8.5272 ... 42.7147 44.5739 50.1734]\n",
+       "        'label_h5': [ 8.8836  8.8836  8.8836 ... 43.4929 49.5163 53.7319]\n",
+       "        'label_h6': [ 9.1797  9.1797  9.1797 ... 50.6446 61.3077 59.8671]\n",
+       "        'label_h7': [ 9.3523  9.3523  9.3523 ... 59.1238 71.8675 60.7055]\n",
+       "        'label_h8': [ 9.9244  9.9244  9.9244 ... 63.8946 61.807  58.7775]\n",
+       "        'label_h9': [10.2654 10.2654 10.2654 ... 50.1495 50.0046 54.0835]\n",
+       "        'label_h10': [10.5675 10.5675 10.5675 ... 44.1977 45.4099 50.4326]\n",
+       "        ...\n",
+       "    ... (showing 2 of 80 indexes)\n",
+       "memory usage: 0.8 MB"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def compute_predictions(models, test_examples):\n",
+    "    test_examples_df = tp.to_pandas(test_examples, timestamp_to_datetime=True)\n",
+    "    index_names = test_examples.schema.index_names()\n",
+    "    predictions = test_examples_df[[\"timestamp\"] + index_names]\n",
+    "    for model in models:\n",
+    "        raw_predictions = model.predict(test_examples_df)\n",
+    "        predictions.loc[:,model.label()] = raw_predictions\n",
+    "    return tp.from_pandas(predictions, indexes = index_names)\n",
+    "\n",
+    "predictions = compute_predictions(models, test_examples)\n",
+    "predictions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "id": "bcf889c2-373f-4a2f-afd0-58d551bec5fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1024x450 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tp.plot([sales[\"sales\"], predictions],\n",
+    "        max_num_plots=3,\n",
+    "        merge=True,    \n",
+    "        min_time= end_train_cutoff - timedelta(days=30),\n",
+    "        max_time= end_train_cutoff + timedelta(days=30),\n",
+    ")\n",
+    "# TODO: Remove legend."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d804439f-f7a3-4190-a0ce-1f77077196e9",
+   "metadata": {},
+   "source": [
+    "This way of plotting predictions is not ideal (keep in mind that we are predicting future values).\n",
+    "Instead of plotting each prediction horizon separately, we want to plot all the predictions at a certain time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "e8f5d796-62f1-4bf7-80a8-a9903cfe62d6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "  <div style=\"display: table; margin-bottom:11px; padding:5px; font-size:small; line-height:120%; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">features</span>\n",
+       "        <span style=\"\"> [1]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#0077BB; font-weight:bold\">value</span>\n",
+       "      <span style=\"color:#009988\"> (float32)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span>\n",
+       "        <span style=\"font-weight:bold\">indexes</span>\n",
+       "        <span style=\"\"> [5]:</span>\n",
+       "      </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">item_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">dept_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">cat_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">store_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "      <span style=\"\">, </span>\n",
+       "      <span style=\"color:#EE7733; font-weight:bold\">state_id</span>\n",
+       "      <span style=\"color:#009988\"> (str_)</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">events: </span>\n",
+       "      <span style=\"\">1040</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">index values: </span>\n",
+       "      <span style=\"\">80</span>\n",
+       "    </div>\n",
+       "    <div style=\"display: table\">\n",
+       "      <span style=\"font-weight:bold\">memory usage: </span>\n",
+       "      <span style=\"\">39.1 kB</span>\n",
+       "    </div>\n",
+       "  </div>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_1</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 13 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">value</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_2</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 13 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">value</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">5.948</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">6.705</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <div style=\"display: table\">\n",
+       "    <span style=\"font-weight:bold\">index</span>\n",
+       "    <span style=\"\"> (</span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">item_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3_090</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">dept_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">cat_id: </span>\n",
+       "    <span style=\"color:#EE3377\">FOODS</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">store_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA_3</span>\n",
+       "    <span style=\"\">, </span>\n",
+       "    <span style=\"color:#EE7733; font-weight:bold\">state_id: </span>\n",
+       "    <span style=\"color:#EE3377\">CA</span>\n",
+       "    <span style=\"\">) with 13 events</span>\n",
+       "  </div>\n",
+       "  <table style=\"margin-left:20px; border:1px solid rgba(127, 127, 127, 0.2)\">\n",
+       "    <tr>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"\">timestamp</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "      <th>\n",
+       "        <b>\n",
+       "          <span style=\"color:#0077BB; font-weight:bold; \">value</span>\n",
+       "        </b>\n",
+       "      </th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">7.195</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.452e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">8.129</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">…</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">10.84</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>\n",
+       "        <span style=\"\">1.453e+09</span>\n",
+       "      </td>\n",
+       "      <td>\n",
+       "        <span style=\"\">11.43</span>\n",
+       "      </td>\n",
+       "    </tr>\n",
+       "  </table>\n",
+       "  <span style=\"\">… (77 more indexes not shown)</span>\n",
+       "</div>\n"
+      ],
+      "text/plain": [
+       "indexes: [('item_id', str_), ('dept_id', str_), ('cat_id', str_), ('store_id', str_), ('state_id', str_)]\n",
+       "features: [('value', float32)]\n",
+       "events:\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_1' state_id=b'CA' (13 events):\n",
+       "        timestamps: [1.4517e+09 1.4518e+09 1.4519e+09 ... 1.4526e+09 1.4526e+09 1.4527e+09]\n",
+       "        'value': [ 5.9476  6.7054  7.7405 ... 10.5392 10.8409 11.428 ]\n",
+       "    item_id=b'FOODS_3_090' dept_id=b'FOODS_3' cat_id=b'FOODS' store_id=b'CA_2' state_id=b'CA' (13 events):\n",
+       "        timestamps: [1.4517e+09 1.4518e+09 1.4519e+09 ... 1.4526e+09 1.4526e+09 1.4527e+09]\n",
+       "        'value': [ 5.9476  6.7054  7.7405 ... 10.5392 10.8409 11.428 ]\n",
+       "    ... (showing 2 of 80 indexes)\n",
+       "memory usage: 39.1 kB"
+      ]
+     },
+     "execution_count": 123,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "predictions_at_point"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 147,
+   "id": "55037b99-f7b5-4105-971f-665c667e3c93",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Feature \"item_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"dept_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"cat_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"store_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n",
+      "WARNING:root:Feature \"state_id\" is an array of numpy.object_ and will be casted to numpy.string_ (Note: numpy.string_ is equivalent to numpy.bytes_).\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Qn58fvfvuuwrLdO/eXaF0MS8vj2JjY2v8vFx6CECh1LBim++8806Vaap48y8SicjQ0FD+uXv3LhHJSihrKu00MTGRb9vT07PKUiciWYk3APrmm2+qPBYv++mnnwgApaamEpGspMjc3JyEQiH17NmTPv30UwoPD682TVXZsmULGRoaEgDy8PBQqpSeSFYyrq+vTx4eHnT69Gm6fv06DRw4kDw8PKi0tJSIiH7++WcyMDCg8+fPk0QioejoaPL09CQAdO3aNSKSlTTZ2NhQdHQ0EdVeilwVZc4XNzc3hVIWIqLVq1eTn58fEb2I99dffy2fLxaLydHRUR6bipLO7OxspdP28jUXHR1NAOjmzZvy+VFRUQRA4TpMSkqq8bx+8uSJfNkdO3YQALpx40albYaEhFSZphUrVpCOjo7Ced21a1ciIkpJSamUnpcdPnxYvu0bN27UWCr4/fffK5yvNZUyd+/enYYNG0ZEROXl5TRz5kwCQHZ2djRmzBj64YcfKDc3t8p1q1NR4wIAzZkzhyQSidLrTp48mXr16qX08unp6QRAXupdW02fqrxcOp2fn098Pp8OHjwon5+ZmUkikahSKV5t98EKFefv/v37K23zwIEDVaap4vx6+VyxtbWVzxcKhdXG9O7duwSADhw4oNJ59eqxeNXEiRPJy8tL/vf//vc/0tPTIwsLCwoICKBvv/2WUlJSqly3Kt999x25u7tTWVlZlfOrek5OmTKFBg8erDBt6dKl5O3trbDemDFjFJZR5vlak5fTcubMGdLT06Nnz57J5586darSNfnkyZMaz4+kpCT5sitWrCBdXV2FaadOnSIdHZ1qn+Xbt28nQ0NDEovFlJeXR3p6epSWlkZ79+6lvn37EtGLGhZPnz6t8ruoIj09nZydnel///uf0uvUJcZVGT58OC1ZskT+d1X3tNWrV9OQIUMUpiUmJhIA+XOuJlx8Zpw7d44A0PPnz4mIyMbGhm7evEnXrl2T1+yJj48nAHTp0qUajw/DaDPlXiMyDEeEh4cjIiICe/bskU8jIkilUjx+/BheXl4AgHbt2snn29raAoD8zffL09LS0iqVzNQmKioK8+bNU5jm5+en8EbY2NhY5XZnfn5+lf6urSOrAwcOyL8zAIVSbFKhZEiVZWvbRkWHQOPGjcPw4cNx+fJl3LhxA6dOncK3336LX375RelOwAIDAzF48GAkJydj/fr1mDBhAq5evVqphP1VUqkUYrEYmzdvxpAhQwDIai/Y2dkhKCgIQ4cOxezZsxEfH48RI0ZALBbDxMQECxcuxMqVK6GjowOJRIIpU6bgiy++gLu7e52PS23nS2FhIeLj4/HWW29h9uzZ8mXKy8thampaab0Kenp66NKlS51rc1SVTj09PXTu3Fk+zdPTs1I76hYtWqi0XT09PXTt2rXSNqOiotCtW7cq1/Hw8MCxY8fkfwsEAoX5mji3K85rXV1d7NixA19++SUuXryIkJAQrF27Ft988w1u3rwJe3t7pbZ54MAB5OfnIzw8HEuXLsX69evx0UcfKbVuWFgYxo8fX+382NhYLF++HCEhIcjIyJCX0CckJMDX11epfdQkPj4eZWVl6N69u3yahYUFPDw8FJazsbFRuT+Sl8/xim3WdI4bGxsr1BDQ0VGsgKjJcwUA1qxZg8WLF8vPlW3btmHt2rX4999/FZ5J1Rk/fjw2btyIVq1aISAgAK+99hpGjhxZYylwVFQURo8erTCtV69e2LhxIyQSCXR1dQEAXbp0UVhG2eerMqKiouDk5AQHBwf5tFefcQDg4uKi9DYBwNnZWeEe5OfnB6lUiujo6Cqf5f7+/igsLMStW7eQnZ0Nd3d3WFtbo1+/fnjzzTdRUlKC4OBgtGrVCs7Oziql5VV5eXkYPnw4vL29Veo8tS4xlkgkWLt2LQ4ePIhnz56hrKwMpaWltfZpEB4ejqCgoCprycTHx6v0rOPKM6Nnz57g8/kIDg5G+/btUVxcjE6dOkEqlSI9PR2PHz9GcHAwRCIRevTooVJaGEabsEw9o1UKCgowd+5cvP/++5XmvfxA1tfXl/+/4gdWVdNe7alYXfbs2VNl1feXnTp1Cn369KnXfpycnNC6detK093d3XHlyhWUlZWBz+crzHv+/Dny8vLkD293d/dqfzRXTFfmQR8VFQUTExNYWlrKpwmFQgwePBiDBw/GsmXL8Pbbb2PFihVKZ+pNTU1hamqKNm3aoEePHjA3N8eRI0cwefLkGteryFh5e3vLp1lbW8PKykrekzWPx8M333yDtWvXIiUlBdbW1vJecVu1aoX8/Hzcvn0boaGh8uqnUqkURAQ9PT2cPXsWAwYMUOp71KSgoAAAsH37doVMEgD5j28uGTZsWKWmIy9zcXGpsmdxVfD5/CrPa2tra/mPu6pERUWBx+OhdevW8sxVVFQUxo4dW+Wy5ubmsLa2rjEtEokEsbGxCj8yAdkP1WnTpmHatGlYvXo13N3dsW3bNnzxxRdKfceKF3De3t6QSCSYM2cOlixZolTMX21O8KqRI0fCxcUF27dvh4ODA6RSKXx9fdXSGZoq5s2bhz/++KPGZSrO/7rS0dGp8lwBlL+3qXJe1SYqKgotW7ZUmGZpaYnx48dj/PjxWLt2LTp27Ij169dXal5TFScnJ0RHR+P8+fM4d+4c3n33Xaxbtw6XLl1SeKbVhaGhocLfyj5f1cnHx0ehudOr+vTpg1OnTtV5+61bt4ajoyOCgoKQnZ0tb+bi4OAAJycnXLt2DUFBQfW+l+fn5yMgIADGxsY4cuSISrGpS4zXrVuHTZs2YePGjWjbti0MDQ2xaNGiWq/xgoICjBw5Et98802lecq+kFRVQz8zDAwM0K1bNwQFBSErKwu9e/eGrq4udHV10bNnTwQFBSEoKAi9evWq9HuIYZoSlqlnOKuq3qQ7deqEBw8eKPXjqqF4eXkhJCQE06dPl097uRdlABg1alSlDNqrXn17fePGjUrb7NixY53SOGnSJGzevBk///wz3nvvPYV569evh76+PsaNGydfdsqUKTh+/HildvXfffcdLC0tMXjw4Br3l5aWhr1792LMmDGVSspe5u3tXecxiokIRKRUG/2K3m2jo6Ph6OgIQNa7dUZGRqWSIV1dXXks9u3bBz8/P1hbW0MqlSIyMlJh2a1bt+LixYv466+/Kv1wr05t54utrS0cHBzw6NEjea/d1blx44a8F/jy8nLcuXNH/sKh4seKsqMDvMrT01O+zYoMbHR0dKUh8n755RcUFxdXu51Xf4SWl5fj9u3b8hKWim2qUupXQUdHBxMmTMCePXuwatUqhZK54uJibN26FUOHDoWFhQUAYPDgwdi6dSs++OADhYxwSkoK9uzZg+nTp9c61NSuXbuQnZ0tv16qYm5uDnt7+zr3aF5Rs0QqlSqVqW/Xrh0uXLhQ5QuEzMxMREdHY/v27fKXhleuXFFYpr7nipubG/T19RESEiLP7GVnZyMmJkahb4BVq1bhww8/VGnbN27cqLTNupwrgOze9tlnnyE8PFyhXb1UKsWGDRvg7e2N9u3bg8fjqXReVefixYuIjIzEBx98UO0yfD4fbm5uKp0rIpEII0eOxMiRIzF//nx4enoiMjISnTp1qvI56eXlVWno0KtXr8Ld3b3G80udz1cvLy8kJiYiOTlZnll89TkJACdPnqyxz4RXX2AlJCTg+fPn8hoAN27cgI6OTqVaIi/r378/goODkZ2djaVLl8qn9+3bF6dOncLNmzfxzjvvqPT9XpaXl4ehQ4dCIBDg2LFjtdYkq4qqMb569SpGjx4tH8ZWKpUiJiZG4UV2db+hDh06BFdXV6Xb/FeHS8+M/v37Y//+/cjOzlYYrrBv374IDg7GpUuXKtWYY5gmRwNV/hmmSq+2bxo8eDCNGjWKkpKS5D2zhoeHk0gkovnz51NoaCjFxMTQ0aNHaf78+fL1qmp/hlfa8anSpvTVduT79+8noVBIv/32G0VHR9Py5cvJ2Ni43r3fW1lZ0a+//irfpo6ODt2/f7/K5ZVJ/8KFC0kgEND69espLi6OoqKi6LPPPiMdHR2FXvGlUimNHTuWzM3N6ZdffqHHjx9TeHg4zZkzh/T09BSO244dO8jExISSk5Pp+fPn9ODBA/r111/Jzc2NWrVqJW/TlpGRQf3796fff/+dwsPD6dGjR3Tw4EGytbWlWbNm1Xo84uPjae3atXT79m16+vQpXb16lUaOHEkWFhbyNtC1GT16NPn4+NDVq1cpMjKSRowYQd7e3vJ2i+np6fTTTz9RVFQUhYaG0vvvv09CobDadntEdWtTr8z5sn37dhKJRLRp0yaKjo6miIgI+u233+i7774johfxdnZ2psOHD1NUVBTNmTOHjIyM5NdGUlIS8Xg82rlzJ6WlpVF+fn6taXv1mgsICKCOHTvSjRs36Pbt29S7d28SiUT16slYX1+funXrJt9mjx49qEePHtWuU9sxzsjIIDc3N/L19aWTJ09SQkICXbp0ifr06UM2NjYUHx8vXzYmJoasrKyoT58+dOnSJUpISKBTp06Rr68vtWnThjIzMxWOxezZsyk5OZkSExPp+vXr9NFHH5G+vr5C3xbbtm2jefPm0ZkzZyguLo7u3btHH330Eeno6Cg12sMff/xBBw4coAcPHlB8fDwdOHCAHBwc5CNHKCM6Opr4fD698847FB4eTlFRUbR161ZKT08niURClpaWNHXqVIqNjaULFy5Q165dFe6BYrGYRCIRffnll5SSkqLQe3h1Xm1HPm/ePHJxcaELFy5QZGQkjRo1ioyMjOrd+72Pjw+dP39evk1nZ2d5Pxivqq33++LiYurevTs5OTnRwYMH6enTp3Tz5k0aM2YMGRoa0vXr1+XLqnJezZgxgwICAig5OZmSkpLozp07tGbNGjIyMqIRI0ZQeXk5EREdP36cAgMD6fjx4xQdHU0PHz6kdevWka6uLu3evVup47Jjxw765ZdfKDIykuLj4+nzzz8nkUhEGRkZRFT1c/LOnTuko6NDq1atoujoaNq5cyeJRCKFnr2rek4q83ytycvblEgk5O3tTYMHD6awsDD6999/qXPnzvXu/d7Q0JAGDRok36a7uztNmjSpxvV+++03EolEpKenp9Cfwa5du8jY2FihPXZV36Umubm51L17d2rbti3FxcVRcnKy/FNxHtSmLjH+4IMPyMnJia5evUoPHjygt99+m0xMTBSu0dmzZ1PXrl3p8ePH8nvDs2fPyNramt544w26efMmxcXF0enTp2nmzJlKpZeLzwwioosXLxIAMjY2VmiPf+nSJXmMK/rKqe67MIy2Y5l6hjNevcFev36d2rVrJ+9MqsLNmzdp8ODBZGRkRIaGhtSuXTtas2aNfH5DZ+qJiNasWUNWVlZkZGREM2bMoI8++qjemfotW7bQ4MGDSSAQkKura7WdQ6mS/l9//ZU6d+5MQqGQDA0NqU+fPlUOXScWi2ndunXk4+NDfD6fTExMaOjQoXTlyhWF5So6sQFAPB6PTE1NqVu3brRq1SqFjsJKSkrok08+oU6dOpGpqSkZGBiQh4cHff7555WGF6vKs2fPaNiwYWRjY0P6+vrk6OhIU6ZMoYcPH9a6boXc3FyaNWsWmZmZkYWFBY0dO1ZhWJz09HTq0aMHGRoakoGBAQ0cOFDhx0BV6pKpJ1LufNmzZw916NCB+Hw+mZubU9++fenw4cNE9CLee/fupW7duhGfzydvb2+6ePGiwjZWrVpFdnZ2xOPx6jSkXXJyMg0fPpwEAgE5OzvT7t271TI80aFDh6hVq1YkEAho0KBBCh1SvUqZY5yenk7vvfceOTk5kb6+Ptna2tLMmTOr3O6TJ09oxowZZGtrS/r6+uTk5ETvvfee/AdzhZeHjqoYVmrEiBHyGFS4e/cuTZ06lVq2bEkCgYAsLS2pb9++VV5XVdm/fz916tRJfv/y9vamtWvXKtUR2cuCg4OpZ8+eJBAIyMzMjIYOHSrvJPHcuXPk5eVFAoGA2rVrR8HBwZXugdu3bycnJyfS0dGp05B2+fn5NHXqVDIwMCBbW1v69ttv1TKk3fHjx+X3oW7dutXYuWZtmXoiosLCQvrss8+odevWpK+vTxYWFjRu3DiFofIqKHtevTxcmJ6eHllbW9OgQYPot99+U+jwMD4+nmbPnk3u7u7yoQe7du2q0rBZR44coe7du5OJiQkZGhpSjx49FIbqrO45WTGknb6+Pjk7O9O6desUtlvddV3b87Umr24zOjqaevfuTXw+n9zd3en06dNqGdJu69at5ODgQEKhkN544w35UI7Vqbh/enp6Kkx/8uSJvBPW2r5LdSrO26o+FUPI1aYuMc7MzKTRo0eTkZER2djY0Oeff07Tp09XuEajo6OpR48eJBKJFNITExNDY8eOJTMzMxKJROTp6UmLFi2qNJRrVbj4zCCSvcATCARkZGSkMIRkSUkJCYXCStOr+i4Mo+14RGroGYZhGIZpME+ePEHLli0RGhqKDh06aDo5DMMwDMMwDIewceoZhmEYhmEYhmEYRkuxTD3T7A0bNgxGRkZVftauXavp5DVJe/bsqfaY+/j41Lr+vHnzql2fdYYjk5CQUO0xMjIyko8CwKiXtt5PajpXauq5mmkeLl++XOM50lTV91mlTdgzg2G0G6t+zzR7z549q7ZnVgsLi1p7PGZUl5+fj9TU1Crn6evr1zp2cVpaGvLy8qqcZ2JiovLY2E1ReXk5njx5Uu18dfR+zFSmrfeTuLi4aue1aNGi1mH0mKatuLgYz549q3a+JkekaUj1fVZpE/bMYBjtxjL1DMMwDMMwDMMwDKOlWPV7hmEYhmEYhmEYhtFSnKtHI5VK8fz5cxgbG4PH42k6OQzDMAzDMAzDMEwTRETIz8+Hg4MDdHS0t7ybc5n658+fw8nJSdPJYBiGYRiGYRiGYZqBxMREODo6ajoZdca5TL2xsTEA2YE1MTHRcGqajsTERPayhONYjLiPxUg7sDhxH4sR97EYcR+LkXZgceK2vLw8ODk5yfOg2opzmfqKKvcmJiYsU69GRMSOJ8exGHEfi5F2YHHiPhYj7mMx4j4WI+3A4qQdtL3Zt/Y2HGBU4uDgoOkkMLVgMeI+FiPtwOLEfSxG3MdixH0sRtqBxYlpDCxT30xUN6Y3wx0sRtzXXGNERAhLzNF0MpTWXOOkTViMuI/FiPtYjLQDixPTGFimvpkoKCjQdBKYWrAYcV9zjdHu60+x7Og97LuZoOmkKKW5xkmbsBhxH4sR97EYaQcWJ6YxsEw9R0ilhIyCUjxKb5gLn3XQwX0sRtzXHGMUmZSLkMeZODq/FyKScvDXnSRNJ6lWzTFO2obFiPtYjLiPxUjNirMbZLMsTkxj4FxHeU0NESG/tBxpeSVIzStFSm4JUvNLkJZXitS8EpSVSwHIOmewMNRHsVgKb3sTvOPvptZ0ZGRkwNTUVK3bZNSLxYj7mluM8krEWHsyCj9N7QRdHR6+HNMWHx+KAF9PB6Pac7eNYHOLkzZiMeI+FiPuYzFSo6xHwP/1B969Dpio9/nG4sQ0hnpl6r/++mt8+umnWLhwITZu3AgAKCkpwZIlS7B//36UlpZi6NCh2Lp1K2xtbdWRXk4pLZcgNbcUqfklSM0rQUpuCdLyZZn1gpJyVHSiaCTQg62JUP7p5moBWxMhrI0FEOrrKmyTiPD1qYf45fIjvN2nldrSWlxcrLZtMQ2DxYj7mlOMiAifH7mHD4d6wMyADwDQ1eHh69fbYulfEdDX4WFYW3sNp7JqzSlO2orFiPtYjLiPxUhNiIDT/wOGfQPc3A4MWqHWzbM4MY2BR0RUlxVv3bqFCRMmwMTEBP3795dn6t955x38888/2LlzJ0xNTbFgwQLo6Ojg6tWrSm03Ly8PpqamyM3N5ezwD+USKXZff4oLD1Phbmv8X2ZdAFtjIWxNZRl3I0Hd35cQEVadeIBWVoaY5ueqljTn5+dr/fiLTR2LEfc1pxjtvv4EJWIJ5vStXGtILJHigwNhGNOhBQZ5c++FbXOKk7ZiMeI+FiPuYzFSkzu7AHER0H0e8MfrwMQ9AN9AbZtnceI2bch7KqNObeoLCgoQGBiI7du3w9zcXD49NzcXv/76K77//nsMGDAAnTt3xo4dO3Dt2jXcuHGjym2VlpYiLy9P4cNlYYk5eHPnLRgJ9PD7rO5YMdIH8/q5YWxHR/RsbQU3a6N6ZegBWVX85SO8EZNagP1q6pgqJSVFLdthGg6LEfc1lxjde5aL6/GZeLt31bWF9HV18P2EDjh0NwnB0WmNnLraNZc4aTMWI+5jMeI+FiM1yHsORB0Dus0BeDyg/WQgfJ9ad8HixDSGOmXq58+fj+HDh2PQoEEK0+/cuQOxWKww3dPTE87Ozrh+/XqV2/rqq69gamoq/3C1M4ncYjGW/30P+28mYNOkjpjQ1Qk6OrwG2x+Px8MXo3wQnpSDQ2romKq0tFQNqWIaEosR9zWHGOWXiLHmnyisHdu2xnscX08HGyZ2wN6QBFyNy2jEFNauOcRJ27EYcR+LEfexGNUTEXD6U2DIGkDnv+aw3mOAB38DUqnadsPixDQGlTP1+/fvx927d/HVV19VmpeSkgI+nw8zMzOF6ba2ttW+pfr000+Rm5sr/yQmJqqapAZFRPg77Bne3XMHI9o54Otx7WBhyG+Ufev81zHV9UeZOB7+vF7batVKfe3zmYbBYsR9TT1GRIRlR+/hw6HuMFfiPifU18XmyR3x25XHCHmU2QgpVE5Tj1NTwGLEfSxG3MdiVE/3DwO2PoCN54tpenyglT8Qd05tu2FxYhqDSpn6xMRELFy4EHv27IFQKFRLAgQCAUxMTBQ+XPEovQCzd9/B85wS7JjZDd1aWjR6Gio6proQlYrT95LrvJ2EBO0YX7o5YzHivqYeoz9CEuBpb4LOLsrf64T6uvhhSkf8dCked542zHBAqmrqcWoKWIy4j8WI+1iM6qEwE7i7G+i1qPK8zjOBOzvVtisWJ6YxqJSpv3PnDtLS0tCpUyfo6elBT08Ply5dwubNm6GnpwdbW1uUlZUhJydHYb3U1FTY2dmpM90NqkQswYZzMVh3JhorRnrjHX838PXq1FJBLfR0dbBufHuciEjG+QepddpGeXm5mlPFqBuLEfc15Rjde5aLq7EZmFOHUTcM+Hr4cUonbLoQi/DEHPUnTkVNOU5NBYsR97EYcR+LUT2c/RwYuEJWMv8qAwvZsHYp99SyKxYnpjGolFMdOHAgIiMjERYWJv906dIFgYGB8v/r6+vjwoUL8nWio6ORkJAAPz8/tSe+IVyOTcebO27By94EWwM7wclCfb1f1kdFx1R/3albx1StW7dugFQx6sRixH1NNUbydvSv19yOviZGAj38MLkj1p+Nxv3nuWpOoWqaapyaEhYj7mMx4j4WozqKOQsYWgEtOlW/TPd3gJCf1LI7FiemMaiUqTc2Noavr6/Cx9DQEJaWlvD19YWpqSneeustLF68GEFBQbhz5w7efPNN+Pn5oUePHg31HdQiLb8Eiw+E4d+YdPwyowsCfO3A4zVcR3h1wdfTwcZJHbCnDh1TPXr0qIFSxagLixH3NcUYVbSjXzLEvd79hZiK9PHD5I746uRDRKfkqymFqmuKcWpqWIy4j8WI+1iM6qAkD7j+A+D/ac3LWbWWLZtftxqyL2NxYhqD2uuUb9iwASNGjMC4cePQt29f2NnZ4fDhw+rejdpIpITd159g6Z8ReLtPK3w23BuG9RySriEJ9XWxeZKsY6qbj7OUXk+qxl48G8rdhGyk5pVoOhkakZhVhIyCMk0ng6mFNlxHqtp7MwEedibo4qqePkPMDPjYNKkDVp24j7i0ArVsU1VNMU5NDYsR97EYcR+LUR1cWAX0/Ui5cei7vg3c/rXeu2RxYhoDj4hI04l4WV5eHkxNTZGbm9vgnebde5aLb04/xDBfe0xq4CHq1K2wtBzz997FewPaoLOLea3Li8Vi6OvrN0LKVJeWX4KvTz6EkVAPKbklcLIwwDv+brAyEmg6aY2iqKwcb+28DT0d4NeZ3TTafwNTMy5fR3Vx/3kufrgQh62BndR+/0vLL8HCfWH46vW2cLUyVOu2a9PU4tQUsRhxH4sR97EYqejpNSDyT2DEBuWWJwJ+HwtM3g/o172DcBYnbmvMvGdDapa5h/wSMVYeu4+d155gw8QOmNLdWasy9ABg+F/71U0XYhGRlFPr8tHR0Q2fKBVJpITfbzzFkoPhmNW7JVaN9sX/TZc1ffj4rwh8e/ohcoqafun1F8ceYMGA1uhlz8O6Mw81nZwmIT2/tEFqfXDxOqqrgtJyfHmifu3oa2JjLMSGiR3w6eFIJGYVqX37NWlKcWqqWIy4La9EjJvhDzSdDKYW7DpSgbgYCP4KGLRS+XV4PKDdBCDyYL12zeLENAbu1jNvAESEk5Ep2BPyFAsGtEZPNytNJ6lejIWy9qsL9t7FJ8M84eNgqukkKe3es1x8eyYaQ7xtsfPNbtB9KVPR1dUCXWaY41p8JhbuD0NHZzPM6t0SJsKm95bzrztJsDMVoldrK5iWpOCvR4TzD1IxyNtW00nTGrlFYkQ+y0V4Ug7uP89FUZkEloYCFIvLYWkowPz+rWFnqp4hOJsKIsLyo/ewWA3t6GtiZyrE+gnt8eHBcHw3oT0czEQNti+GYdTn61MP0d5UrOlkMIz6XPoG6PEuIFTxt7LvOGDvBKDjNFkmn2E4qtlUv3+aWYi1J6PQtoUpZvdtBYGertq2rWk5RWWYv/culo/wgYedcZXLcKXqT0FpOb4/G4Oc4jJ8MswTNsY1Z7aICMHR6fjt6mP4uVliZk9XGPCbxruo2NR8fH3qIf5vehfo6vAgFosh5eng7V238fW4dmjBMkCVFJWV496zPEQk5SDyWS5yi8UwEeqjnaMp2rYwhW8LU4U+MSKScrAlKA4tzGRNOqyN69ekgyvXUX3tDUlAdlEZ5vdvnB55E7OK8PGhCGyY2AG2Jg3/gqWpxKkpYzHirmvxGThzLwWfv+bBYsRx7DpS0vMw4MZPwOs/1239S98CLToDrQfWaXUWJ25rKtXvm0WmPj69AMv/voe1Y9vCxbJx23Y2lsyCUry3LxSrx/jCzdqo0vx79+7B19dXAymTISKcupeC36/Lakn0aq1aLQkiwtkHqdh9/Qn6e9hgag8XCPW198VMcZkEb+26hY0TO8Dmv0xORYyeZhZi+d/38cuMLtDXbZYtZAAApeUSRCXnIyIpBxFJucgoKIUBXxc+DqZo52iKdi3MYGqg3EPyztMs/BQcj9Y2xpjbtxXM61g6renrSB0ePM/DxvMx2Da1c6M2O3qcUYjPjkRi06SO9X65UpumEKemjsWIm4rLJJi18xa2z+iCJ7EPWYw4rjleR8kFyTj5+CTupt2FHk8P1gbWsDO0g42BDWwNbGFrYAsbAxsY6P/XEZ5EDOwZD4z7RTaMXV0UZgDHFwKT9tRp9eYYJ23SVDL1TaPIswZ5JWIsO3pPIfPUFFkaCbBxUgeNdUxVk4TMIqw5+QDe9qbY8WbXOmXGeTwehvrYYbCXLU5EJmPWzlsY5muHCV2dtLLWxRfH7+Nd/9ZVnpMuloaY0MUJ689E49PXvDSQusZXLpEiJrUAkc9yEJ6Ui+c5xeDr6sDL3gTtHE0R4GtXa62OmnR2scAvMyxwLS4Diw6Eob2TGd7u0zSbdNSkoLQcX/7zAD9M7tjo/Yi0tDLEqtE+WHQgFD9M7tSg1f4Zhqmb789FY06/VjDi8ChATPOTW5qLM0/O4FLSJZgLzPFay9cww2cGCISMogykFqUipSgF0VnR+DfpX6QWpaKkXNavDi8rHpYW1rCJPSjL9Bvayl8AmPBNlBu+2tAKMLAE0h4CNp4N/G0Zpm6adEm9REpYsPcu5vRthY7OtfcQ3xSk5JbggwNh+PaNdnCyeDFchyaq/pSVS7H98iOEJebgs9e81PqioVwixdGw5zh0JwljOjrg9U6OWlOqfehOEp5mFmLxEA+F6a/GaPnf9+DvYY0Bnk27ff2vVx4jODoNvi1M0a6FKdo5mcHBVKjcg7YOiAiXYtLx65XH6NFK1qRD2WEstbkKHRFhyZ/hmNjFCd1bWWosHQ9T8vDliSj8OKUjzAwaJmOvzXFqLliMuCcsMQd/3HiK9ePbA2Ax0gZNOUYl5SUITgrG2SdnAQBDXIagn1M/iPRUaJqYHgPphVXIGrUBqcVpSC1MRWpRKtKKZP/PK8uTL2rCN4GdoR1amraEm5kbWpq2VNxXWhQQsg0YuUnl78L5OJWXAUfmAvbtAL8FgC6H09oAmkpJfZPO1H97+iFaWRvhjc6OakqddkjKLsLSPyMUOqZq7Ko/1+Mz8cPFWEzu5owR7ewbLIMmlkjx5+0knIh4jvFdHDGqfQuFTve4Ji4tH2tPPsT2/9rRv+zVGJWIJZi9+za+GdeuSXYwRkT47mwMdHjAB4PdG+wcqWn/5x6kYvf1p/D3sFaqSYc2V6HbfzMBmYWN146+JhXDiW4J7NQgtSW0OU7NBYsRt5SVS/Hmzpv4cXInefMkFiPua2oxkkglCEkJwclHJ5FVkgV/J38McRkCM6GZ6huTSmUd3I3cCJjWnA8gIuSV5SGlMAWPch8hPicej3IfoVRSCn0dfbiYuKC1WWu4hfyGlsN/hMi0hUpJ4Xyc/lkCtOwHlJcCob8D/p8ALj01napG01Qy9U22ftXx8OcoEUubXYYeABzNDfDNuHZYcjAcGyfJOqbS0WmcUuyMglJ8feohDPm62Datc4NXb9bX1cGU7s54vVML7L+ZgOm/hSCwuwsCfOw4N0xhcZkEK47dx4YJHap88fBqjIT6ulg92hf/OxKJ7dObVvt6iZSw4tg9tLIywqzeLTWSBh6PhyE+dhjkZYuT92RNOgJ87TCxhiYdjXUdqVtUch4uPEzDz1M7azopAADfFqb4cIgH5u+5i+8ndFB7G3ttjVNzwmLELT8Fx2NyN2eF/kZYjLivKcSIiPAg8wFOPDqBuJw4dLfvjnc6vIMWRqplnCu59QvgMazWDD0g+z1gKjCFqcAUHhaKtSjLJGV4kvcEj3Ie4aJtKzw6OxelFi6Kmf2qSvZfwuk43d4BGFgB3qNkf7cZBFz8EgjfBwxcCRhqrmZfVXJKcmDIN4S+TvOqTaCMJllSf/95Ljack3UEpdeEMkKqepRegM+P3sOmSR1hrE8QChuuTwGplHDgdiJORiZj6VAPtHM0a7B91aS4TILfbzzBvzEZmNnTFQO9bBq9BLg6nx6OwGtt7dGnjXWV80tKSqqM0YmI57j3LA+fDGsa7bjKyqX46K9w9GljjXEceukmkRL+DnuGP28nYXQHB4zrXLlJR3Ux4rLC0nK8ves2fpjSEVZGDdtBnapiUvOx4u/7+Gy4F3xbqG9ITm2MU3PDYsQdMan52HQ+Fj9O6ajwvNSGGD0reIatYVvhZuaG1mat0dqsNewNG652INdoQ4yqk5iXiBOPT+BO6h14W3hjeKvhcDdXU629nATgnw+ByfsBdWaoiYDdo4HAP1HG48kz+3E5cVWX7P+X2eeV87gZp4QbsiYF436rfJyS7gAXV8uG9OsQqN7jqAKxVIyI9AhcfXYVDzIfwIRvgo+6fQQrkfqGJW8qJfVam6mXSCQQiyuPoZpdWIYvTzzA8pHeMG2g9pra5ElGITZfiIGzoRQerg6wNBTAyogPKyM+jIX6arl5xqcVYPvlR+jeyhKj2jtwovp7mZSH3TcScPNJNj4d5gkve81epEdCk/AovRBLXmlH/7KaqmctO3oPAzxt0N/TpqGS2CiKysqxaH8YxndxwmBvbvYVIJZIcehOEv4OkzXpGN3hRZMOzlehewUR4cM/IzC+iyN6aLAdfU2yC8vw4Z/hGNfZEa+1tVfLNrUtTs0RixE3SKSEN3fewro32lUablJbYpRdko24nDjE58QjLicOKYUpkJIUViIreUbfzcwNNgbcecmvLtoSowqZxZk4/eQ0Lj+7DDsDOwxvNRydbTtDh6fmjPeBqcCgLwCrBmhudmeXrM15hylVzn65ZD8uJw6x2bEoKSjBW13fQle7rtw5B3OTgKPvynr0F1Q9HDYk5cCt7UD8RdnxtPVulKQl5CXg2vNruJlyE6WSUrSzaoeeDj3hbekNXR31d47NMvUNpLYDS0RISUlBTk5OlfOyCstgItJvUlWV60sqJZSUicHT0YWECBIpQSolSF8KPY/Hgw6PB10dQFeHB10eD7o6POjoyKZXuV0i5JeUQyIlmIr0OZGZf5mZmRn4xhb46C9ZpibAVz0ZBlXFpRVg7cko/N+0mmuOPHz4EJ6eVZfGl4gleHvXbawb3w72ptrZvj6nqAwL94fhHX83zmYwX1ZaLsGBW4k4fS8FU7o74zVfe8TERFcbIy46cCsBaXmleG9gG00npUZiiRRr/omCiUgfiwa2qXfTmZquJYYbWIy44dcrj2Ek0MXErs6V5mlzjIgImSWZiMuJQ1x2HOJy4pBenA4AsDGwUcjsWwotuZPRUhHXY1QkLkJifiIeZj3ExYSL4OvyEeAagD6OfcDXbaCCt7B9QEEq0HtRw2xfXAzsmwxMOwIoed5cjbiKCGkE7qbdRT/HfhjVehRM+BrMPFZ8h+HfAZZutS+f9xw4u0zWlKHfRwBfvSNs5Zfl42byTVx7fg1JBUlwMnZCT4ee6GbXDUb8ysN0q1uzzNT/9NNP+Omnn/DkyRMAgI+PD5YvX45hw4YBkFUDWrJkCfbv34/S0lIMHToUW7duha2t8iVytR3Y5ORk5OTkwMbGBgYGBgo34tS8Ehjo68BYxEroXyWRSKCrW/3bLamUUC6RQkwEiUSKcqmsh/lyCYHw4hTR4fGgqyvL9BeVlcPCkA9DAbfatRARioqKkJaWBjMzM1jZ2GLV8QewMhLg/YGtG/XhXSKWjUf//YQOlUpBXlVUVAQDA4Nq5z/OKMQXx+/jl+ldtK5ZSWpeCRYfDMOnw9RbzboxlIgl+OPGUwRHp6Nva3MYidRbhU5PlwcbYwHsTIWwNRbCzEA9NWgepuThu7OyZkhce+FWnb0hCbgWn4FvxrVTekSCqtR2LTGax2KkeQmZRVh14gG2T+9c5T2nKcaIiJBalCov1Y/LiUNWSRYAwN7QHm3M2sDNzA3uFu6azXQpiQsxEkvESCpIwtO8p/JPalEqAECoK4SziTPczNzQz7EfjPnVlAirS0EacHgOEPgXoNuA3YZdXAO07AO07KvU4hVxEkvFuJR4Ccfij8FCaIHxHuPhY+nTcOmsCpGshL7tG0DrgaqtG3MWuLZZ1kO+R0CdkyCRSnA/8z6uPr+KyPRIiPRE6G7fHX72fnAycarzduuqWWbqjx8/Dl1dXbRp0wZEhF27dmHdunUIDQ2Fj48P3nnnHfzzzz/YuXMnTE1NsWDBAujo6ODq1atKJ6imAyuRSBATEwMbGxtYWiqW9GUVlqKsnGBnysE2KxxQXFwMkah+Jbz0Xyl/+X8vAAz4epzrjO5lmZmZSEtLg7u7O3R1dfH7jae4/SQLX73eFgb8xukj8n9HIhHgY4e+7lW3o3+ZMtXojoU/R1RyHj4O4O6b+Vc9ySjEJ4cjsHZsW7Sybvg3rg2lsLQcB4ND4excuUSrPsrKpUjLL0VqXglS8kqQUyRrVsSDrLNEGxMB7EyEsDURKvy/pkxvYWk5Zu++jc2TudeOvjYhjzKx+WIsvn5dcVhOVWhbldTmiMVIs4gIs3ffwfIR3nC2rPo6a04xkpIUyYXJiM+JR2x2LKKzopEnzoOLsQs623ZGJ9tOam3Dqy6NFSOJVIKUohQ8zX2Kp/myjPuzgmeQkhR6PD04GjvCxcRF/rExsFFvlXplHXob6LUQsGvbsPvJTwVOLQUm7FZq8ari9CT3CQ7GHMSjnEcIaBmAANcACPUaIQ9z7QcAPKDngrqtX1YEXF4PZD0CBq8GzJTLhCcXJOPa82u4kXwDBeIC+Fj6oFeLXvC18tV4p3fNMlNfFQsLC6xbtw5vvPEGrK2tsXfvXrzxxhsAZNWCvLy8cP36dfTo0aPK9UtLS1FaWir/Oy8vD05OTlUe2JKSEjx+/Biurq4KGdTC0nJkFJTC2cJAa6tQNTRt7kylroqLi/HkyRO0bNlS/t2vxWdga1A8vnmjHVo08DBxR0OfITYtH0uHKpcBj42NRZs2tVeT/vxoJAZ62aK/B/fb10cl52H1iQf4bkJ7rW028DJlY6QuRWXlSMt7keGv+H9qfimKSssBAATAVKQPWxMhbE0EsDUR4sz9FEzq6gw/N+43c6hKYlYRPjkcgYUD3dGtpYXK6zd2nLiAiPA4o1ArXpyl55ci/dlTeHu6azopzdbBW4nIKxHj7T6tql2mOV5HLyMiJOQn4E7qHdxJvYPMkkzYGdihs21ndLXrCjtDO00nUe0xKhQXIiozSl7inpifiDJpGXSgAztDO7iausLZ2BmuJq6wN7KHng6HBtGKOg48DwMGLmuc/R2dD/T+QKl2+zXFqbi8GKcfn8aZJ2fgZuaGCR4T4GLiou7UysSdB+4dBkZvUbrpQLXSo2VV8lv2AbrPqzS2fUZxBiLTIxGSEoLHuY9hb2gPPwc/9LDvAVNBHWtsSsqBzFjA3BXQV99vymafqZdIJPjzzz8xY8YMhIaGIiUlBQMHDkR2djbMzMzky7m4uGDRokX44IMPqtzOypUr8cUXX1SaXlOm/uVMWlm5FEnZRXCxNIAul4eM0LDaqt83RVWdL4CsyuEnhyOweLA7uriqnmFQRnx6Ab488QDbVagqn5+fD2Pj2qumaUv7+ttPsrDpQiw2TeoIC8Om0SRG2Rg1JiJCXnE5UvNLZBn+vFKYG+hjoBc3OyJUVmFpOT46FIE+ra0wqZtqtSO4GKeGUFYuxfVHmTj3IAVPM4uQUyTG9xPao40tt7/73N9vI6ewFIuHeKK7FvSv0dSk5pVg6V8R2DGza41Nc5rLdaSK5IJk3EmTZfKTC5NhKbREZ9vO6GzbGc7Gzo1esFSfGJVLyxGfE4+IjAhEpkcivTgdhvqG8LTwREvTlnA1cYWjsSMEulpQ26s4Gzg4XVbtXq+R0psSKes0b/j6WhdVNk73M+7jz5g/kVWShdFuo9HPqZ/6XpxkxgMnPwQm7VVfhpgICN+P4vA9eNBpEu7pSHAv4x4KxAWwFFqirVVbdLXvipYmLVW/NqRSICseeB4KPLsr+z9PV9YHQEoE4DUK6DRdLfFutpn6yMhI+Pn5oaSkBEZGRti7dy9ee+017N27F2+++aZCqTsAdOvWDf3798c333xT5fbqUlJfkUmTSglPMgvRwkwEgX7zyrCqSh3V77VNdZl6AMgvEePjQxHwd7fBhK7qbb9TkeleP769Ss1BVKlG9yi9AKtVfGnQmIIepmFPSAI2TuoAo3q0jeaa5lQdlQukUsLG8zHIKynH58O9lD7X1R2nsnIp+HrcuM5yi8UIjk7Dhag0FJSWo0crCwzyskUrayPceJSJm4+z8D6HO0bMLRbjk0MRmOGtj1OJOigWS/BxgCcstayZiLYiIizYF4r3B7SBh13NmQx2v6tdRnEG7qbexZ3UO3ia/xQm+iboaNsRXWy7wM3MrcGroCsbo4q+BCLSIxCZEYlHuY/AAw+tzVqjrXVbtLVqCxuD/2r/Scobtj16Qzj2HtBhKuDcvXH3u3cSMGYrYFBzAZGq11JuaS6OxR/DpaRL6GzbGePajHsRn7ooyQMOBAJjtgGmLeq+HciaYjzOfYzIjEhEZEQguTAZIujCOysJbfVM4TPwSxibqthMkUg2DOHzUOD5XVktACJZBt6hE+DQEbBo9WJYPUk5EPknEL4XaDseaD+5Uk0BVTSVTL3KV62HhwfCwsKQm5uLv/76CzNmzMClS5fqnACBQACBQPWHORHhWU4xrI0FTSJDHxwcjP79+1eq6aAummiWMHPmTOTk5ODo0aONvu/aGAv18ePkTvjuXDRWHX+A/73mqbbM8aoTD/B2n5Yq9++gykuXVtZGGNOxBTacj1G6en9j+TvsGc5HpWFLYEcI9LT/2nxZc3sxpmk6OjwsHuKBExHPMe+Pu1g/vh3MlBiqVB1xIiJcf5SJfTcTUVAi6+dAxNeFj4Mp2jmaom0LU6XSog5J2UU4/yAVV+Iywdfjwd/DBitGelfKCHd1tcCWoLhGSVNdXXyYigGeNrA2LcMXndwQnpiDRQfCMKKdPcZ3duJ0Py1NwcnIFLSxMao1Qw+w+50yrERWGOI6BENchwCQZcbC0sJwPP444nLiINQTor11e3Sx7QIPCw+1V1evLkaF4kLcz7iPiIwIPMh8gOLyYtga2KKddTuMchuFVqatqh4a7O5u4OomYMLvjTZ8Wb3FBwH6Bo2foQeAzjOBu7tk1fBroOq1ZCowxTTvaZjqNRU3U25i/S1ZbYBx7uPQza6bar/ppVLZS4/+n9UpQ59WlIbI9EhEZkQiLicOBEIr01bwtfLFnLZzYGdo9yI9CSHA0QWyTHb7SdVX8c9PkZW+Pw8FUu8DkjLAzFmWeW83EbDyqPnFkq4e0GGyrLO/sD3AH6/LXuq0fQNogCHvtEW929QPGjQIbm5umDhxYp2q37+qprclL5e85ot5AAjWxk2jnXhDZ+rLy8uhp9cwb14r2q2HhoaiQ4cO8um5ubkgogb5PsqoqaT+ZX+HPcOJiGSsf6M9TA3q11nH32HPEJ2Sj4/q0JFdbm4uTE1Va2f0vyORGOpjh35KdMTXGHZff4Ko5Hx8OcZXa3pcV0VdYsSox71nuVjzTxRWjfaptXp5feKUWyzGoTtJuPgwDV1czTGpq7P8BV1RWTnuP89DRFIuIpNykFsshrFQH21byDL6Pi1M1VIzhYhw/3kezj1IRWhiDuxNhBjkbYvera0g4tf8g+XTw5GY168VXCzVO+SQuszfcxdrxvqCJy6Wx6hcIsXvN57iUkw6PhnmCU877S0p4bLswjIs2HcXO2Z2U6rmidbc74jq3z64gRSJixCWHoY7qXcQmx2Lip/cFaMK6fJ0Ycw3rvJjwjeBkb6R/G8jfaNKGfHc3FwYGhtWWY3ex9IHba3awtvSGwb6SnQ6emWjLLPVZzFw6C1g+PeAFXdr/QAAygqBvROByfsBgQb6E5FKgd/HAFMP1VhSrI5rKbUwFYdjD+NO2h30adEHLYxaQF9HX/bR1Yeejt6Lv1+efn0L9E1aQL/jdOjryJar7qVAkbgI9zPvIzIjEvcz7qOovAg2BjbwtfJFO6t2cDNzq/3FlEQMhGwDHl8GhqwGDK1lpe/PQ4HkCNlweka2QIuOslJ4W5/6V6EvL5U1hXh4AujyJuA1+kWpvhKabUn9q6RSKUpLS9G5c2fo6+vjwoULGDduHAAgOjoaCQkJ8PPzq3dCX1ZYKkaJRBeO5uwtsrLEYnGlTH1ZWRn4/IYradKKHwMARndoAVdLQ8z74w6+HOsLtzp2NPUovQBHQ59h+/QudVo/MTFR5WO2fIQ33tp1Cx62xhod+YGIsPlCHIrE5Vg71rfJdlhZlxgx6uHbwhSbJ3fEh3+GY0ZPFwzwrL7PgLrEKTIpF3/ceIqsojKM69QCO97sCv1Xau8Y8PXQ1dUCXV/qiyO3WIx7z3JxNyEHu288RVFpOSwMBWjnKMvoe9mbQKhEbbKycilCHmfi3INUPM4ohLeDCYZ42+L9gW1UekE2zNcOp+6lYF4/JcYebmSFpeUok0hhZsDHvXsx8hjp6ergzV4tMczXHl+dioKdiRALB7VptFFKmou1J6OwdKin0k1JtOJ+l5sEnPgAGLwKsPHSdGoqMdA3QE+Hnujp0LPK+WKpGIVlhcgvy0eeOA8FZQWy/5fmISk/Cfll+SgQy6bll+Xj1XK4nLwcmJqYws3MDe2s2mFBxwWqV9MmAs6vAPhGQMBXshckr/8iy9iP3KTcOOaacvFLWSm5JjL0gCzj6D0KuH8UaDe+2sXUcS3ZGtrinQ7vQCwV48bzG8gsyUS5tBxiqRhiiVj278sfiRjizFiU5z6DWCiF+PpK2fISceWN82S/4/i6fPhY+qCddTtM9JgIQ/06vBzW1Qd6vgd4jwGC1gBSiawE3qU30ONdtY9xD0D2UqD7HKDjVOD2r8AfY4FucwGPYZx94dcgSAWffPIJXbp0iR4/fkwRERH0ySefEI/Ho7NnzxIR0bx588jZ2ZkuXrxIt2/fJj8/P/Lz81NlF5Sbm0sAKDc3t9K84uJiioi8RzHPMkgikaq0XS4oKSmh9957j6ytrUkgEFCvXr3o5s2bREQUFBREAOjEiRPUtm1bEggE1L17d4qMjJSv/+TJExoxYgSZmZmRgYEBeXt70z///COfHxkZSQEBAWRoaEg2NjY0depUSk9Pl++7X79+NH/+fFq4cCFZWlqSv78/TZ48mSZMmKCQzrKyMrK0tKRdu3YREdGpU6eoV69eZGpqShYWFjR8+HCKi4uTLw9ZB9zyT79+/YiIaMaMGTR69Gilvv/Lx+D8+fPUuXNnEolE5OfnRw8fPpQvExYWRv7+/mRkZETGxsbUqVMnunXrVpXHu7i4mB48eEDFxcVKxSc1t5im/RpCQQ9TlVpeYV9l5TRl+3V6nlOk8roVHj9+XKf14tLy6c0dN0lcLqnzvutDIpHSymP36KfguNoX1nJ1jRGjPiXicvroz3D6KTiOpNKqnwPKxqmotJwO3Eqgab+G0Orj9yk+LV8taUzPL6GLUam04Vw0zdl9i2b8FkKfHIqgvSFP6d6zHCr771rNLS6jv8Oe0cJ9d2nmbyH0U3AcxdUzDWXlEpr+a4g6vobanQh/TntuPCWimmMU9DCVJv18nc7eT2mklDV9QQ9TafXx+yqtozX3u5wkoj/fJDq7nKi0QNOpaVT1jpGknOjY+0Qh/1d5Xu4zoh3DibKe1G8fDSXhJtHRdzWdCtk5t3ssUTXPIyINXUsp94j+GE9UXtb4+9a0kjyiS+uIdo8hij1XY2yIas57ahOVMvWzZs0iFxcX4vP5ZG1tTQMHDpRn6Ilkmah3332XzM3NycDAgMaOHUvJyckqJaimA5uRm0//hoRSbn6hStvkivfff58cHBzo5MmTdP/+fZoxYwaZm5tTZmamPEPr5eVFZ8+epYiICBoxYgS5urpSWZnsghw+fDgNHjyYIiIiKD4+no4fP06XLl0iIqLs7GyytramTz/9lKKiouju3bs0ePBg6t+/PxERicVi6tevHxkZGdHSpUvp4cOH9PDhQzpx4gSJRCLKz3/xQ/L48eMkEokoLy+PiIj++usvOnToEMXGxlJoaCiNHDmS2rZtSxKJ7IfpzZs35Znx5ORkyszMJKLKmfqavj/Ri0x99+7dKTg4mO7fv099+vShnj17yrfh4+NDU6dOpaioKIqJiaGDBw9SWFhYlcdb1Uw9kSxzvuRgGP3fpfhqMwxV+exIBF2sw8uAl1Uch7o4cjeJ1p1+WPuCalZWLqHFB8Jo/82njb5vTahPjBj1kUqltP3feFpyMIyKy8orza8tTvFp+bTq+H2a/msIHbyVUOU21EkqldKz7CI6FZlM35yKord23qTpv4bQvN9v0/6bTyktr0St+1tyMIyeZdf9BWNDeX/fXUrPl33X2mJUXFZO6888pHf/uENJHPwu2iS/REyTfr5OhaVildbTuvtd9BlZJvThKU2npNHUK0biEtnLkIg/q18m+6nsmOYk1n0/DaEiXYUcOUfPrSB6cq3a2Y1+LRVmyo5PQXrj7pdrirKJLq4h+n0c0aN/q12sqWTq692mXt2qa9cglRI+P3wXEzyE8GzjVqmN9GdHIpGaV9Jo6bQ1EWLN2LZKL19YWAhzc3Ps3LkTU6ZMASCrEu/q6opFixaha9eu6N+/P/bv34+JEycCALKysuDo6IidO3diwoQJaNeuHcaNG4cVK1ZU2v6XX36Jy5cv48yZM/JpSUlJcHJyQnR0NJycnDBs2DDk5eXh7t278mXKy8thb2+P77//HtOmTQMATJkyBVKpFPv376/yu2RkZMDa2hqRkZHw9fWttk39yx3l1fb9ly5dKu9X4Pz58xg4cCAA4OTJkxg+fDiKi4shFAphYmKCH374ATNmzKj1mCvbpv5VRITtlx8hLq0Aq0b71lp19lj4c0Ql5+HjOrSjf1l9exr+35FIBPjYoW8jta8vEUvwwYEwjO7ggABf+0bZp6ax3qC55VJMOn698hjr3mgHW5MX13hVcSqXSHE+KhV/3XkGKyM+Aru7oK0jx6sW19H5B6lIyCrCrN4tNZ0UuRKxBPP33MWvM7sCUP5aiksrwFcno9CtpQVm9W5ZqUkEU7sVf9/DUB879GxtpdJ6Wnm/KysCLq8Hsh7L2vOaOmo6RQ2qzjEqzQcOzQa6zALch9S8bNZjWUdrr28HTDjwrH96HQj+Chi1WTZeORfkPQfOfAaM31Hl7Ea9liTlwIGpQP9PAfv2jbNPrivKknUAmR4t6zPCqZvCbNamvpFtvhiLTk7mEOiVVjlflQy2JsTHx0MsFqNXr17yafr6+ujWrRuioqLQtavsh87L/Q9YWFjAw8MDUVFRAID3338f77zzDs6ePYtBgwZh3LhxaNeuHQAgPDwcQUFBMDKq3K4oPj4eLi4uAIDOnTsrzNPT08OECROwZ88eTJs2DYWFhfj7778VMvSxsbFYvnw5QkJCkJGRAalUCgBISEhQ+iZV2/d/WcV3AgB7e9kDJC0tDc7Ozli8eDHefvtt/P777xg0aBDGjx8PNzf1tvfi8XiY09cNQQ/TMPf3O1g3vh1squmQ8XFGIQ7fTcIvdWxH/7L63kiWj/DG27tuw8POWCGD0xDySsRYuC8Ub/Vuhd5tVPuhqM20+WbfFPVzt4ajuQiL9ofhk2GeaO9kBkAxTim5Jdh3MwF3nmZjoJcNvpvQHqai+nWIyXW921jh3T13OZWp/zcmHX1eulcoey21tjHCLzO64EjoM8zccRMfDHJHF9eah49iXrj1JAtlElI5Qw9o6f2ObwAMXA6kPZS1tW/ZF+g+r17DXXFZnWJUlCVrL9/3I8BFiT6vLFoCIzYCR+YA434FjOoxtFp93dkFPAoCJu0BBLWP4NBoTBxk7bqzHsuO16uzG/NaOrdM1r6fZehfMLAABn8BFKQBVzYA1zYDfZbI2vo3IVrxyvv0vRRkFpRhRHsHTSdFo95++208evQI06ZNQ2RkJLp06YIffvgBAFBQUICRI0ciLCxM4RMbG4u+fftC579eIA0NK3dQERgYiAsXLiAtLQ1Hjx6FSCRCQECAfP7IkSORlZWF7du3IyQkBCEhIQBkHe01BH39Fw/fig7XKl4krFy5Evfv38fw4cNx8eJFeHt748iRIw2Sjv6eNlg2wgsL94UhMim30vwSsQTLjt7D2rFt1TIcnoGBEr3T1kCor4uVo3zw6eFIlEuk9U5PddLzS/HuH3excJB7s8rQA/WPEaN+btZG2DatM7YExeHvsGcAAKFIhCuxGViw9y7WnoxCj1aW+P2tbnizV8smn6EHZPcCE6Ee0vIbr/Zabc7cT1Wo0aPKtcTj8fB6J0dsndIZR0Kf4dPDEcgubJjnT1NSIpbg+7Mx+GRY3WqRafX9zsYTmHIQMLAE/hgHJN7UdIoahMoxyn0G/DkDGLxauQx9BavWwLB1spcBhZmq7VMdJOXAqY+B3ERg3G/cytBX6D4XCPm5ylmNdi2F7ZW9XPAd1zj70zZGNrLOIAO+AUL/AP58UzakXhPB+Ux9dEo+DtxKwLIRWjJeZjXc3NzA5/Nx9epV+TSxWIxbt27B2/vFd7tx44b8/9nZ2YiJiYGX14seXZ2cnDBv3jwcPnwYS5Yswfbt2wEAnTp1wv379+Hq6orWrVsrfAwNDVFeXl5t2nr27AknJyccOHAAe/bswfjx4+UZ68zMTERHR+Pzzz/HwIED4eXlhezsbIX1K3rQl0gk9f7+ynB3d8cHH3yAs2fP4vXXX8eOHVVXd1KH1jbG+GlqJ2y6EIvj4c8V5q35Jwpv9W4JBzP1jMKQkpJS7220tjHCqPYO2HwhVg0pkskvESMurQDX4jJw+G4S3t8XipWjvNHhv1LR5kQdMWLUz1Skj62BnRCZlItF+0Mxe08EQhOysXyENzZP7gg/N8smOyJDdYb62OHM/VRNJwOArGf/zMJShRE66nItmRroY83YtnijsxPe2xeKP28nVuoNnHnhh4uxeLOXa51fZGn9/Y7HAzpMAcbvlI1lfXyRrJS6CVEpRhlxwJG5sh7t7epQFdzGExj6FXBoFlCcXfvy6lKUBRycJqsyPeBzlYYqa1QOHYGsR0BJ5UKgRrmWkm4D0SeBAcsafl/azrQFMPw7YNAK4MZPwLH3NZ0iteB09fucojKsPHYfP0zpCL6eDkqqz5dynqGhId555x0sXboUFhYWcHZ2xrfffouioiK89dZbCA8PBwCsWrUKlpaWsLW1xWeffQYrKyuMGTMGALBo0SIMGzYM7u7uyM7ORlBQkDzDP3/+fGzfvh2TJ0/GRx99BAsLC8TFxWH//v345ZdfoKtbc7vwKVOmYNu2bYiJiUFQUJB8urm5OSwtLfF///d/sLe3R0JCAj755BOFdW1sbCASiXD69Gk4OjpCKBRWGrqjtu+vjOLiYixduhRvvPEGWrZsiaSkJNy6dUs+hGJDMTPgY9vUTlhzMgrRKflYPNgd/0Qmw0Cgi/6e6quGZm5urpbtjOnYAp8ejsDl2HT0aVN9+/rScgnS8kqRmleC1LxSpOSVIC2vBKl5Jch/6WIzFOjBzlQIG2MBbE2E2DSpA2wauHo/V6krRoz66enq4PMR3ohJzYegLBcuTk27LW1t+nlY4/19YZjWw0XTScG1+Az0dLNUmFafa6mzizl2vtkVO689waydt/C/17zQxpaDJXcadP95Lp5lF2Pp0Lr39dJk7ncGFrKMbMIN4M+Zsox+u4lNYqgrpWP0PAw4t7z+7eLtfIFBXwB/zZK9LBE2cL8k6dHAP0tk/SNoQ1XpTtOAu78DPRcoTG7waykvGTi/UtYsQaf2IVSZ/5i7AqN/BB6HAtil6dTUG2cz9eUSKT46EoHPhnvBykig6eSoxddffw2pVIpp06YhPz8fXbp0wZkzZxQu9q+//hoLFy5EbGwsOnTogOPHjyuUhM+fPx9JSUkwMTFBQEAANmzYAABwcHDA1atX8fHHH2PIkCEoLS2Fi4sLAgICoKOjI6++Xp3AwECsWbMGLi4uCu3edXR0sH//frz//vvw9fWFh4cHNm/eDH9/f/kyenp62Lx5M1atWoXly5ejT58+CA4OrtP3r4muri4yMzMxffp0pKamwsrKCq+//jq++OILpdavDz1dHawY6YP9NxMw9487KCuX4pcZ9W9H/7KXmx3U1/IRPnh79y3kl5Qjq7Dsv4x7CbIKy1BRsMXX04GtiRA2JgLYGgvhaWeMfu5WsDERwlig1+xKNpWhzhgxDcPd1hhpacWaTobGGfD1INDXQXZhGcwN+RpNy+l7KZjfv7XCtPpeS3q6Oni7Tyu81tYea09GwcnCAIsGtYFAj/2gFUuk+PrUQ2yY2KFe22ly9zvnHsDUQ7KSuX2TZFXQrd01nap6USpGT64CV74HJuwCRGrIXDp0APp//iJj31BV4WPOAjd/lrXjN7ZtmH2om8drwO9j/uvH4UUWq0GvpfJS4O/5wPDvG/4lS1Nlqd6+uTSFs73ff3YgBF3dW2B0hxbyeXXtzZyRlXKLROqpJq4tGup8CUvMgb2pUO2d0am7d9TErCJcicuArYmshN3WRAgLAz50dFhmva60sjfoZojFSebvsGcoFUsxoauTxtJQLpFi1q7b2D1LsbdhdcfoRMRzXIhKw3fj2zf7e9zW4DjYmwoxtmP9aqs06esoJxE4+zlg2Rro+yGgr52/j2qNUfQpWdvh1/8P4FfuU6leEm4Al7+XZez5amwzTiTryCwjRpZR1dOygr0b22QvIXzGyic12LVEBBx/H/AcAbgPVf/2m4mm0vs9RxumyN7Cv5yhZ+qntur3jPI6OJk1SO/ylpaWtS+kAicLA0zu5owBnrbwcTCFlZGg2f/YrS91x4hpGCxOMgM8bXDhoWbb1d98koVurpVLB9UdoxHtHNCjlQW+Pv1QrdvVNvHpBQhPzMEYNfx+atLXkZmTrOS6RWdgz3gg9rymU1QnNcYobB9w7zDwxg71Z+gBWc2Hnu/JOs8Tq6lTTnGJrNSZpwuM+lH7MvQA0DEQCN2jMKnBrqWb/yerQs4y9Aw4nKlfOLCNppPAMAzDMFrLWKgPHnjIKxFrLA2n76Uo9HrfkCZ2dYZIXxc7rj5ulP1xjVRK+PLEAywf6cOaTynL8zVgygHgyb/Aobdl4403BTd+Ap7dBsZuA/QasPlNyz5At9myjH151UNOKy0/Bdg/BfB5XdYmXVvPYYExYO0BJN5q2P08/lfWOV7vxQ27H0ZrcDZTr8tKFNWqpp7pGW7IzNTAMDGMSliMtAOL0wsDvGxwMSpNI/uWSgmPMwrR2sao0ryGitGiQW0Qk5qPU5HJDbJ9LtsT8hQDPG3QQk0jsjSb64hvCAxeBfT+QNYL9o2fZEOoaYFKMSICLq4BijKB19Y3TqdpbgOATjOAw7OB8joONfnsjuylyrBvgDaD1Js+Teg+V9YfwH/Ufi1lPwEufweM3Ki9Lz8YteNspp5RLz09zvaJyPzHxkZ9PekzDYPFSDuwOL0w2MsW56I0UwU/NDEbHasZ+rKhYsTj8bBqtC+Ohj3DrSdNa/iymjzLKcbFh2kI7K6+0Q6a3XVk6yMb255vCOwZByTd0XSKaqUQI6kUOLkUEJnJhn5rzMye+xCg7QTg6DzVX4hE/An8+x0w8XfAqonU0jVzlv2bkwhADddSYYas48Dgb4D9gcCJxcCoHxqmWQWjtVTK1H/11Vfo2rUrjI2NYWNjgzFjxiA6OlphmZKSEsyfPx+WlpYwMjLCuHHjkJrKjbFymzOO9YfIVEEs1lwVWUY5LEbagcXpBXNDPkrFUhSVNX7J46nI6qveN2SM9HV18P2EDth8IRZxaQUNth+uICKsOn4fn4/wVmu/Kc3yOtLRATpNl/W4fmcH8M+HQHGOplNVLXmMystkGeoWnQC/+ZpJjNcIwGukrE28VInaoVIpcP4LIDkMmLBbPT3zc0m3F6X1Kl1LxTnAo2Dgygbg4AzgjzdknTpmP5HVihj3CzDt8IsXBwzzH5Uy9ZcuXcL8+fNx48YNnDt3DmKxGEOGDEFhYaF8mQ8++ADHjx/Hn3/+iUuXLuH58+d4/fXX1Z5wRjWs+j33ZWdnazoJTC1YjLQDi5Mifw9rBEenN+o+iQgPU/LhZV/1cFcNHSNDgR6+m9Aey47eQ1qemjrx4iCJlPD9uRh0dDaHm3XlZg710ayvI0Mr2fjVPmOBg9OAyL8ADhaOZGdnA2VFwF9vAt5jgA5TNJsgn7FA64GyHtlrGkq5JE+WZks3YOgaheHfmgynrkBaFFBaUP21VFYIPL0OXN8KHJoty8D/sxhIjgAcu8rOwal/yfpG6D5Htk0tHamBaXj1GtIuPT0dNjY2uHTpEvr27Yvc3FxYW1tj7969eOONNwAADx8+hJeXF65fv44ePXrUus2ahhVgQ9rVnVgsbnpjztZC286XjIwMWFlZaToZTA1YjLQDi5OitPwSrP0nChsndWy0fUYm5eJE5HN8OsyryvmNFaP49AKsPHYfP03tDCNB08o4PMspxrKj9zC8rT1e79RC7Z3jsevoP+VlwPUfgaRbwJAvOTWmdWZSPCyDPwZ6LwJce2s6OS/c/R14flc2JN2r52XWY1mmv//ngHN3zaSvsdw/AhSkIcNtHKzMjIHUe8DzUOBZKFCQKsug27cDHDoBDh0BAwtNp7hZaipD2tXrCZebmwsAsLCQnYR37tyBWCzGoEEvOrnw9PSEs7NztZn60tJSlJa+6DEzLy+vPkliqiGt6Y0pwwlFRUWaTgJTCxYj7cDipMjGWIi8knKUiCUQ6jfO8Kan7iVjWA293jdWjNysjbBoUBssPhCGLYGdoK/bNLoSOhmZjH03E7B6tC9crRqmXS27jv6jxwf6LJZVfz77OWDjI+tUT1+DhQVSCRB3AYZB64GR3wIOHTSXlqp0mgZIyoBTH8s6v6vI2D/+Vza2/eitsmEFmzrPkcCOABhG/A0Ymcn6bWjRSTauvLGdplPHNDF1frpJpVIsWrQIvXr1gq+vLwAgJSUFfD4fZmZmCsva2toiJSWlyu189dVXMDU1lX+cnJrBRa4BLFPPfeyFFvexGGkHFqfKere2wpXYjEbZFxEhIikX7R1Nq12mMWPU2cUCr3dyxGdHIrW+f5misnJ8ejgCkc9y8euMrg2WoQfYdVSJuSsw4XdZxmzPG0D8xcZPQ2GGrK3172OBtPt43GUZ9zL0Fbq+BVi0kr0IIQJubgfu7gYm7WkeGXpA1qxg5j+I7/ENMHkvMOAzwGMYy9AzDaLOmfr58+fj3r172L9/f70S8OmnnyI3N1f+SUxMrNf2mKrVper9zp07K72g0YSZM2dizJgxmk5Gg3NwcNB0EphasBhpBxanygJ87XD6ftUv19UtJrUAbWyNaqwO3tgxCvC1g4+DKTaci2nU/arTvWe5eGvnbYxo54CPAzzB12vYWgfsOqoCjwd4jwIm7wPiLgCH5wL5DdwZNJGs3fXhucCJDwBbX2DaUaD3B7Bt6dOw+66vHvMAI1vgl0GyDuBe3978emzXE8ChRQtNp4JpBur0RFiwYAFOnDiBoKAgODo6yqfb2dmhrKwMOTk5CsunpqbCzq7qt1ICgQAmJiYKH0b9GqKjvCdPnoDH4yEsLIyT29M2rFSE+1iMtAOLU2UOZiKk55dCLGn4Wlu1Vb0HNBOjGT1dUVouxb6bCY2+7/qQSgn/9288fgqOx5bATujVunHaubPrqAYCY1kHb37zgaPvyEqhlenxXRWl+cCtX2Sl8nHnZKW8E38H2gyW9dIPLYlRr/eBCbuAfkub7ZjqWhEnRuuplKknIixYsABHjhzBxYsX0bJlS4X5nTt3hr6+Pi5cuCCfFh0djYSEBPj5+aknxc1IWVmZ2ralyer36vweTVlBQdMfeknbsRhpBxanqvm5WeJ6fGaD7+fO02x0dql5eCpNxejjAE/cepyFiw+1Y6jdtLwSzP3jDgz4evhxSkdYGPIbbd/sOlKCfTsg8C9ARxfYMx54Hlb/babck41D/tdbsmHephwEBi6vcggzrYmRqWPtyzRhWhMnRquplKmfP38+/vjjD+zduxfGxsZISUlBSkoKiouLAQCmpqZ46623sHjxYgQFBeHOnTt488034efnp1TP901Zfn4+AgMDYWhoCHt7e2zYsAH+/v5YtGiRfBlXV1esXr0a06dPh4mJCebMmQMAOHToEHx8fCAQCODq6orvvvtOYds8Hg9Hjx5VmGZmZoadO3cCkJWAGxgY4PDhw+jfvz8MDAzQvn17XL9+XWGdnTt3wtnZGQYGBhg7diwyM2v+8VfxUqdjx47g8Xjw9/cH8KK6/Jo1a+Dg4AAPDw+l0lnd9iqsX78e9vb2sLS0xPz585vcGLqsPwnuYzHSDixOVRvma4dT9xq2Cv7jjEI4WxhAt5bx0jUVIx0dHr4a1xZ7biQgPDFHI2lQ1oWoVHxwMAwfDfXA1B4uau/dvjbsOlKSjg7QZZZs2LGb/yfrHK5ExZLZ8lIg4qBsSLO7u4Bus4HAg4DvOFlHfdVgMdIOLE5MY1ApU//TTz8hNzcX/v7+sLe3l38OHDggX2bDhg0YMWIExo0bh759+8LOzg6HDx9We8K1zeLFi3H16lUcO3YM586dw+XLl3H37t1Ky61fvx7t27dHaGgoli1bhjt37mDChAmYNGkSIiMjsXLlSixbtkyeEVbFZ599hg8//BBhYWFwd3fH5MmTUV5eDgAICQnBW2+9hQULFiAsLAz9+/fHl19+WeP2bt68CQA4f/48kpOTFeJ84cIFREdH49y5czhx4oRS6atpe0FBQYiPj0dQUBB27dqFnTt31ukYcFlGRuN0YsXUHYuRdmBxqpqLpSGSsosgkTZcZ3HKVL0HNBsjgZ4uvp/YAd+eeYinmYUaS0d1SsQSrDx2H1fiMvDrjK5oY2uskXSw60hFRjbAmK2Ax2vAgUDZcGa1dcyY9Rg4txzYO1E2Zvn4ncBr6wCbqoeCfBWLkXZgcWIag0pD2inTa6xQKMSWLVuwZcuWOieqTk58AOQlN97+TOyBERuUWjQ/Px+7du3C3r17MXDgQADAjh07quyEZsCAAViyZIn878DAQAwcOBDLli0DALi7u+PBgwdYt24dZs6cqVKSP/zwQwwfPhwA8MUXX8DHxwdxcXHw9PTEpk2bEBAQgI8++ki+n2vXruH06dPVbs/a2hoAYGlpWanPBENDQ/zyyy/g85WvKljT9szNzfHjjz9CV1cXnp6eGD58OC5cuIDZs2crvX2uq6jxwnAXi5F2YHGqXldXC9x6koUerSwbZPs3HmVhdp9WtS6n6RiZivSx7o32WHIwHD9O6QhLI4FG01MhOiUfq07cx9u9W6G/p41G06LpGGmtVv0A5x7A1c3AganAkNWyXuArSCVA7Fkg9A9AYCIr5R/0RZ3am7MYaQcWJ6Yx1Gucek5RMoOtCY8ePYJYLEa3bt3k00xNTeXV0l/WpUsXhb+joqIwevRohWm9evXCxo0bIZFIoKur/JjD7dq1k//f3l5WkpKWlgZPT09ERUVh7NixCsv7+fnVmKmvSdu2bVXK0NfGx8dH4bva29sjMjJSbdvnAhcXF00ngakFi5F2YHGq3jBfO+wJSWiQTH1iVhHsTARKjQXPhRg5mImwYpQ3PjgYjp+ndoaIr/zzVN2ICH/ceIrLsRnYMLEDbIw1OAb6f7gQI62lJ5B1DJf1CDj737Bz7SYBEftlY7W3HgyM3AwY1u86ZDHSDixOTGNo2PFQGJUZGqo+1AePx6tUi6Kq9uYvD2tX0TavoTrQq+p7KJvOqrw6JB+Px9No538NISWlcYabYuqOxUg7sDhVr42tMeLTCyBtgCr4Z+6nIMBXufGXuRIjTzsTzOvbCh/+Gd6gzRJqklVYhvl776JMQtg2tTMnMvQAd2Kk1SxaARP/ACxbAxe+ABw6AtP+lvUIX88MPcBipC1YnJjGwDL1jaBVq1bQ19fHrVu35NNyc3MRE1P7eLleXl64evWqwrSrV6/C3d1dXnJtbW2N5OQXTQ9iY2NRVFSkUhq9vLwQEhKiMO3GjRs1rlNREq/scHm1pVPV7TU1paWlmk4CUwsWI+3A4lSz9o5mCEvKUft2r8ZlKD3cGpdi1LO1FYb42OKL4/eVamaoTldiM7Bg7128698ab/VuCZ1aOhhsTFyKkVbj8QCfscC4X4DWg+TD0akDi5F2YHFiGkPTqX7PYcbGxpgxYwaWLl0KCwsL2NjYYMWKFdDR0am1N9slS5aga9euWL16NSZOnIjr16/jxx9/xNatW+XLDBgwAD/++CP8/PwgkUjw8ccfVyrZrs3777+PXr16Yf369Rg9ejTOnDlTa9V7GxsbiEQinD59Go6OjhAKhTA1Na12+drSqer2mppWrWpvh8poFouRdmBxqlmArx2OhT9HJ+eah51TRWpeCcwN+BDoKVeFnWsxGt2hBZJzS/DTpXi869+6wfdXVi7Fd+eiUVBSjl9mdIEBn3s/x7gWI6YyFiPtwOLENAZWUt9Ivv/+e/j5+WHEiBEYNGgQevXqBS8vLwiFNVez69SpEw4ePIj9+/fD19cXy5cvx6pVqxQ6yfvuu+/g5OSEPn36YMqUKfjwww9hYGCgUvp69OiB7du3Y9OmTWjfvj3Onj2Lzz//vMZ19PT0sHnzZvz8889wcHCo1Pb/VbWlU9XtNTUJCQmaTgJTCxYj7cDiVDMfBxNEJeeptVT6zP0UDPFRruo9wM0Yze3bCml5pTgSmtSg+3mUXoC3dt1CRyczrBnblpMZeoCbMWIUsRhpBxYnpjHwqLHrmtUiLy8PpqamyM3NhYmJicK8kpISPH78GC1btqw1M8x1hYWFaNGiBb777ju89dZbDb6/4uJiiESiBt8Pl2jb+XLv3j34+vpqOhlMDViMtAOLU+2+OhmFke0d4NtCPbWh3t51Cz9M7qR0Z3NcjZFESnh/fyimdHNWuilBVYgIeSXlSMsrQWpeKVLySpCaV4Lk3GI8zynBl2N84WDG7WcyV2PEvMBipB1YnLitprynNuHm6+EmKDQ0FA8fPkS3bt2Qm5uLVatWAUCjlUYLBNwYroepXuvWDV/lk6kfFiPtwOJUuwBfO5y+l6KWTH1mQSlEfD2Veo/naox0dXj4bnx7zP39DswN+PB2qPwDr0QsQep/mfXU/zLrFX8XlpbLlzMW6sHWVAhbYyFsTYTo3tICtiZCtDATcartfHW4GiPmBRYj7cDixDQGlqlvROvXr0d0dDT4fD46d+6My5cvw8qq7iUBqigtLW12JfXa5tGjR/D29tZ0MpgasBhpBxan2rV3NMP352rvrFUZ5x6kYrC3rUrrcDlGQn1dbJjYAfP33EUnFzOk5pUip6gMRLI+zwR6urAxEcDWRAg7EyG8HUzQ39MGtiZCGAmazs8qLseIkWEx0g4sTkxjaDpPH47r2LEj7ty5o+lkMBzW1Iboa4pYjLQDi1PtdHR4cLM2QmxqPtrYGtdrWxcfpuH7iR1UWofrMbIw5GNLYCek5pXAzkQIMwP9Wju2bWq4HiOGxUhbsDgxjYFl6psJVv2e+zw8PDSdBKYWLEbagcVJOcN87XDqXkq9MvW5xWLo6vBULqHWhhhZGPJhYcjXdDI0Rhti1NyxGGkHFiemMbDe75sJNkYm90VHR2s6CUwtWIy0A4uTcrq4WuD20+x6beNCVCoGeqlW9R5gMdIGLEbcx2KkHVicmMagcqb+33//xciRI+Hg4AAej4ejR48qzCciLF++HPb29hCJRBg0aBBiY2PVlV6GYRiGYdRAV4cHR3MRnmQU1nkb56NSMbgOmXqGYRiGYdRH5Ux9YWEh2rdvjy1btlQ5/9tvv8XmzZuxbds2hISEwNDQEEOHDkVJSUm9E8vUHat+z32sehb3sRhpBxYn5VVUwa+LwtJyiCUEUwN9lddlMeI+FiPuYzHSDixOTGNQOVM/bNgwfPnllxg7dmyleUSEjRs34vPPP8fo0aPRrl077N69G8+fP69Uol+htLQUeXl5Ch9G/Vj1e+5j1bO4j8VIO7A4Ka9HK0vceJRZp3WDotPQ38OmTuuyGHEfixH3sRhpBxYnpjGotU3948ePkZKSgkGDBsmnmZqaonv37rh+/XqV63z11VcwNTWVf5ycnNSZJIZhGIZhqqGvqwMbYwGe5RSrvO7Z+6kY4sOq3jMMwzCMpqk1U5+SIqvCZ2ur+JC3tbWVz3vVp59+itzcXPknMTFRnUlqllxdXbFx40b53zweD6dOnarXNqvqP4FRL1Y9i/tYjLQDi5NqAnztcFrFKvglYgkKS8thZVS3pl0sRtzHYsR9LEbagcWJaQwa7/1eIBDAxMRE4cOoV3JyMgYMGKDUsitXrkSHDh2q3MawYcPUnDLmZax6FvexGGkHFifV9G5jhatxGSqt829MOvq0sarzPlmMuI/FiPtYjLQDixPTGNSaqbezswMApKamKkxPTU2Vz2OUU1ZWprZt2dnZ1bujPHVsg6mZjo7G37ExtWAx0g4sTqoR6OnCRKiHtHzlO7Q9cz8VAb72dd4nixH3sRhxH4uRdmBxYhqDWs+yli1bws7ODhcuXJBPy8vLQ0hICPz8/NS5K63j7++PBQsWYMGCBTA1NYWVlRWWLVsGIgIgqzK/evVqTJ8+HSYmJpgzZw4A4MqVK+jTpw9EIhGcnJzw/vvvo7DwxfBDaWlpGDlyJEQiEVq2bIk9e/ZU2ver1e+TkpIwefJkWFhYwNDQEF26dEFISAh27tyJL774AuHh4eDxeODxeNi5c6d8Gy9Xv4+MjMSAAQMgEolgaWmJOXPmoKCgQD5/5syZGDNmDNavXw97e3tYWlpi/vz5EIvF8mW2bt2KNm3aQCgUwtbWFm+88YZajrW2atWqlaaTwNSCxUg7sDipbqiPHc7cT619QQBl5VJkFpbCzlRY5/2xGHEfixH3sRhpBxYnpjGonKkvKChAWFgYwsLCAMg6xwsLC0NCQgJ4PB4WLVqEL7/8EseOHUNkZCSmT58OBwcHjBkzRs1J1z67du2Cnp4ebt68iU2bNuH777/HL7/8Ip+/fv16tG/fHqGhoVi2bBni4+MREBCAcePGISIiAgcOHMCVK1ewYMEC+TozZ85EYmIigoKC8Ndff2Hr1q1IS0urtO+KzHRBQQH69euHZ8+e4dixYwgPD8dHH30EqVSKiRMnYsmSJfDx8UFycjKSk5MxceLEStsqLCzE0KFDYW5ujlu3buHPP//E+fPnFdIFAEFBQYiPj0dQUBB27dqFnTt3yl8S3L59G++//z5WrVqF6OhonD59Gn379lXHYdZacXFxmk4CUwsWI+3A4qS6fh7WuBSdrtSy1+Iz0NPNsl77YzHiPhYj7mMx0g4sTkxj0FN1hdu3b6N///7yvxcvXgwAmDFjBnbu3ImPPvoIhYWFmDNnDnJyctC7d2+cPn0aQmHd3+grY/X11UgrqpyZbSg2BjZY5rdMpXWcnJywYcMG8Hg8eHh4IDIyEhs2bMDs2bMBAAMGDMCSJUvky7/99tsIDAzEokWLAABt2rTB5s2b0a9fP/z0009ISEjAqVOncPPmTXTt2hUA8Ouvv8LLy6vaNOzduxfp6em4desWLCwsAACtW7eWzzcyMoKenl6NzSX27t2LkpIS7N69G4aGhgCAH3/8ESNHjsQ333wj7yjR3NwcP/74I3R1deHp6Ynhw4fjwoULmD17NhISEmBoaIgRI0bA2NgYLi4u6Nixo0rHs6nR01P5cmQaGYuRdmBxUp0BXw8CfR1kF5bB3JBf47KnIlOwYEDrGpepDYsR97EYcR+LkXZgcWIag8pnmb+/v7zKeFV4PB5WrVqFVatW1SthqlI1g60JPXr0AI/Hk//t5+eH7777DhKJBADQpUsXheXDw8MRERGhUKWeiCCVSvH48WPExMRAT08PnTt3ls/39PSEmZlZpX3r6+sDAMLCwtCxY0d5hr4uoqKi0L59e3mGHgB69eoFqVSK6Ohoeabex8cHurq68mXs7e0RGRkJABg8eDBcXFzQqlUrBAQEICAgAGPHjoWBgUGd06XtnJ2dNZ0EphYsRtqBxaluhnjb4tyDVEzoWv3QsuUSKZ7nFsPJon73ahYj7mMx4j4WI+3A4sQ0BtZzA4e8nEkGZFXl586dK2/uEBYWhvDwcMTGxsLNzU2lbVdUvxeJRGpLb20qXiRU4PF4kEqlAABjY2PcvXsX+/btg729PZYvX4727dsjJyen0dLHNY8ePdJ0EphasBhpBxanuhngaYMLD2tuV3/zcRa6t6z7S+EKLEbcx2LEfSxG2oHFiWkMLFPfiEJCQhT+vnHjBtq0aaNQmv2yTp064cGDB2jdunWlD5/Ph6enJ8rLy3Hnzh35OtHR0VVmjCtqCLRr1w5hYWHIysqqcp98Pl9ec6A6Xl5eCA8PV+iw7+rVq9DR0VFpLE49PT0MGjQI3377LSIiIvDkyRNcvHhR6fWbGja6APexGGkHFqe6MRbqgwce8krE1S5z6l5KvXq9r8BixH0sRtzHYqQdWJyYxsAy9Y0oISEBixcvRnR0NPbt24cffvgBCxcurHb5jz/+GNeuXcOCBQsQFhaG2NhY/P333/IO6Tw8PBAQEIC5c+ciJCQEd+7cwdtvv11laXxFe57JkyfDzs4OY8aMwdWrV/Ho0SMcOnQI169fByDrhb+i88OMjAyUlpZW2lZgYCCEQiFmzJiBe/fuISgoCO+99x6mTZsmr3pfmxMnTmDz5s0ICwvD06dPsXv3bkilUpVeCjQ1bNhH7mMx0g4sTnU3wMsGF6Oq7p9GKiU8zihEaxujeu+HxYj7WIy4j8VIO7A4MY2BZeob0fTp01FcXIxu3bph/vz5WLhwoXzouqq0a9cOly5dQkxMDPr06YOOHTti+fLlcHBwkC+zY8cOODg4oF+/fnj99dcxZ84c2NjYVNpWRfV7Pp+Ps2fPwsbGBq+99hratm2Lr7/+Wl5bYNy4cQgICED//v1hbW2Nffv2VdqWgYEBzpw5g6ysLHTt2hVvvPEGBg4ciB9//FHpY2FmZobDhw9jwIAB8PLywrZt27Bv3z74+PgovY2m5unTp5pOAlMLFiPtwOJUd4O9bHEuquoq+HcTstHJ2Uwt+2Ex4j4WI+5jMdIOLE5MY+BRTb3eaUBeXh5MTU2Rm5sLExMThXklJSV4/PgxWrZs2eC96aubv78/OnTogI0bN2pk/yUlJVp3zOpL286X+Ph4lftKYBoXi5F2YHGqn7d33cbmyR1gwFfsS3f1iQcY18kR3g4m1aypPBYj7mMx4j4WI+3A4sRtNeU9tQkrqW8m2HAa3GdlZaXpJDC1YDHSDixO9ePvYY3gV8asJyI8TMmDl72xWvbBYsR9LEbcx2KkHVicmMbAMvXNREX1e4a7EhMTNZ0EphYsRtqBxal+hvrY4ez9FIVpkc9y0baFmcKwrPXBYsR9LEbcx2KkHVicmMbAim8bSXBwsEb3r6PD3t9wnZFR/TufYhoWi5F2YHGqH2tjAfJLylEilkCoL+tv5dS9FAzzVV9nTyxG3MdixH0sRtqBxYlpDCyn10xUN2wewx3a3I6nuWAx0g4sTvXXu40VrsRmAJBVvY9MykU7R1O1bZ/FiPtYjLiPxUg7sDgxjUErM/Uc69tPKzTH6vfadp48f/5c00lgasFipB1YnOovwNcOp/+rgh+dmg93W2O1Vb0HWIy0AYsR97EYaQcWJ6YxaFWmXl9fHwBQVFSk4ZRon+ZY/b7iPKk4b7iOvcnlPhYj7cDiVH/2piJkFJRCLJHiVGQKhrVV7zjLLEbcx2LEfSxG2oHFiWkMDdamfsuWLVi3bh1SUlLQvn17/PDDD+jWrVu9tqmrqwszMzOkpaUBkI2Xrs6Sg6ZMLBZrXcl1XRERioqKkJaWBjMzM61pemBgYKDpJDC1YDHSDixO6uHXyhLX4zNxNyEbCwe2Ueu2WYy4j8WI+1iMtAOLE9MYGiRTf+DAASxevBjbtm1D9+7dsXHjRgwdOhTR0dGwsbGp17bt7GSlBRUZe0Y5ZWVl4PP5mk5GozIzM5OfL9ogJSWFDXvCcSxG2oHFST2G+drj40MRcLMxhI6Oel+gsxhxH4sR97EYaQcWJ6YxNEim/vvvv8fs2bPx5ptvAgC2bduGf/75B7/99hs++eQThWVLS0tRWloq/zsvL6/GbfN4PNjb28PGxqZZthOvq9TUVNja2mo6GY1GX19fa0roK5ibm2s6CUwtWIy0A4uTejhbGiC3WIxhvvZq3zaLEfexGHEfi5F2YHFiGoPaM/VlZWW4c+cOPv30U/k0HR0dDBo0CNevX6+0/FdffYUvvvhC5f3o6upqXaZNk0QiEYRCoaaTwdRAW9r+N2csRtqBxUl9Nk/ugJZW6h+OicWI+1iMuI/FSDuwODGNQe29p2VkZEAikVQqFba1tUVKSkql5T/99FPk5ubKP4mJiepOEgPWXEEbsBhxH4uRdmBxUp/WNsbQVXPVe4DFSBuwGHEfi5F2YHFiGkODdZSnLIFAAIFAoOlkNHmWlpaaTgJTCxYj7mMx0g4sTtzHYsR9LEbcx2KkHVicmMag9pJ6Kysr6OrqIjU1VWF6amqqVnVaxjAMwzAMwzAMwzBcp/aSej6fj86dO+PChQsYM2YMAEAqleLChQtYsGBBretXDLtWW4d5jGqePn0KQ0NDTSeDqQGLEfexGGkHFifuYzHiPhYj7mMx0g4sTtxWkefU9qG/G6T6/eLFizFjxgx06dIF3bp1w8aNG1FYWCjvDb8m+fn5AAAnJ6eGSBrDMAzDMAzDMAzDyGVmZsLU1FTTyaizBsnUT5w4Eenp6Vi+fDlSUlLQoUMHnD59Wqkh1RwcHJCYmAhjY2PweOrvnKc5ysvLg5OTExITE2FiYqLp5DBVYDHiPhYj7cDixH0sRtzHYsR9LEbagcWJ+3Jzc+Hs7AwLCwtNJ6VeGqyjvAULFihV3f5VOjo6cHR0bIAUMSYmJuyGwnEsRtzHYqQdWJy4j8WI+1iMuI/FSDuwOHGfjo7au5prVNqdeoZhGIZhGIZhGIZpxlimnmEYhmEYhmEYhmG0FMvUNwMCgQArVqyAQCDQdFKYarAYcR+LkXZgceI+FiPuYzHiPhYj7cDixH1NJUY80vb++xmGYRiGYRiGYRimmWIl9QzDMAzDMAzDMAyjpVimnmEYhmEYhmEYhmG0FMvUMwzDMAzDMAzDMIyWYpl6hmEYhmEYhmEYhtFSLFPPMAzDMAzDMAzDMFqKZeoZhmEYhmEYhmEYRkuxTD3DMAzDMAzDMAzDaCmWqWcYhmEYhmEYhmEYLcUy9QzDMAzDMAzDMAyjpVimnmEYhmEYhmEYhmG0FMvUMwzDMAzDMAzDMIyWYpl6hmEYhmEYhmEYhtFSLFPPMAzDMAzDMAzDMFqKZeoZhmEYhmEYhmEYRkuxTD3DGf7+/li0aJGmk1HJzp07YWZmVuMyK1euRIcOHeq8Dx6Ph6NHj9Z5fUa71Pd8URdlrjlXV1ds3LixTttX5tphtMPMmTMxZsyYGpepzz08ODgYPB4POTk5dVqf0Txl7hX1edZx5b7ZnLH7AMNwF8vUM5xx+PBhrF69Wv53fTIT6jRx4kTExMRoOhng8Xh48uQJAODJkyfg8XiVPlOnTlVYZ9euXejatSsMDAxgbGyMfv364cSJE5W2LZFIsGHDBrRt2xZCoRDm5uYYNmwYrl69qrDczp075fvS1dWFubk5unfvjlWrViE3N1dh2fT0dLzzzjtwdnaGQCCAnZ0dhg4dWmmb1Zk7dy7c3NwgEolgbW2N0aNH4+HDhyocMVl627VrB6FQCBsbG8yfP19h/sGDB9GhQwcYGBjAxcUF69atq3ZbV69ehZ6eXqUflTNnzsTKlStVSldDqMuPoVevOU3YuXMn/P395X+vXLmyynP7/Pnz8mWysrKwaNEiuLi4gM/nw8HBAbNmzUJCQkKl7ScmJmLWrFlwcHAAn8+Hi4sLFi5ciMzMTIXl/P395fsSCARo0aIFRo4cicOHD1fa5qVLlzBgwABYWFjAwMAAbdq0wYwZM1BWVlbr942Ojkb//v1ha2sLoVCIVq1a4fPPP4dYLFY4BjNnzlTi6NVNxf0jLCxM6XU2bdqEnTt3NlialBEcHAxXV1f53y/fj17+/PLLL/JliouLsWLFCri7u0MgEMDKygrjx4/H/fv3K21f2fNq5syZ8n3p6+vD1tYWgwcPxm+//QapVKqwbHh4OEaNGgUbGxsIhUK4urpi4sSJSEtLA/AiFnXFleckANy6dQtz5szRaBpevna2bdsGY2NjlJeXy+cXFBRAX19f4Z4DvLh/xsfHA1DtuP7f//0f/P39YWJiUu09+OXnt6rqmklWJgOuKq7dBx4+fAgej4cbN24oLNOjRw8IhUKUlJTIp5WUlEAoFOLXX38FUPn4cOVZzjB1xTL1DGdYWFjA2NhY08moRCQSwcbGRtPJqNL58+eRnJws/2zZskU+78MPP8TcuXMxceJERERE4ObNm+jduzdGjx6NH3/8Ub4cEWHSpElYtWoVFi5ciKioKAQHB8PJyQn+/v6VSlVMTEyQnJyMpKQkXLt2DXPmzMHu3bvRoUMHPH/+XL7cuHHjEBoail27diEmJgbHjh2Dv79/pcxUdTp37owdO3YgKioKZ86cARFhyJAhkEgkSq3//fff47PPPsMnn3yC+/fv4/z58xg6dKh8/qlTpxAYGIh58+bh3r172Lp1KzZs2KBwbCrk5ORg+vTpGDhwoFL71hZcveZ8fHwUzuvk5GT07dsXgCzj1aNHD5w/fx7btm1DXFwc9u/fj7i4OHTt2hWPHj2Sb+fRo0fo0qULYmNjsW/fPsTFxWHbtm24cOEC/Pz8kJWVpbDf2bNnIzk5GfHx8Th06BC8vb0xadIkhYzKgwcPEBAQgC5duuDff/9FZGQkfvjhB/D5fKXOTX19fUyfPh1nz55FdHQ0Nm7ciO3bt2PFihVqOnoNw9TUlJO1LiruRy9/AgMDAQClpaUYNGgQfvvtN3z55ZeIiYnByZMnUV5eju7duytkBFQ5rwAgICAAycnJePLkCU6dOoX+/ftj4cKFGDFihDwTmZ6ejoEDB8LCwgJnzpxBVFQUduzYAQcHBxQWFjbeQVKCMi+kamNtbQ0DAwM1pEY9+vfvj4KCAty+fVs+7fLly7Czs0NISIhChi8oKAjOzs5wc3NTeT9FRUUICAjA//73P7Wkm8u4dh/w9PSEnZ0dgoOD5dPy8/Nx9+5dWFtbK1zj169fR2lpKQYMGKCBlDJMIyCG4Yh+/frRwoUL5f8HoPCpcPnyZerduzcJhUJydHSk9957jwoKCuTzXVxcaPXq1TRt2jQyNDQkZ2dn+vvvvyktLY1GjRpFhoaG1LZtW7p165ZS6dqxYweZmpoqTPvqq6/IxsaGjIyMaNasWfTxxx9T+/bt6/zdAdDWrVspICCAhEIhtWzZkv78889Kyzx+/JiIiB4/fkwAKDQ0tMrtXb9+nQDQ5s2bK81bvHgx6evrU0JCAhER7d+/nwDQsWPHKi37+uuvk6Wlpfz4VnUsiIhSU1PJysqKAgMDiYgoOzubAFBwcLCyh6BW4eHhBIDi4uJqXTYrK4tEIhGdP3++2mUmT55Mb7zxhsK0zZs3k6OjI0mlUoXpEydOpM8//5xWrFhRKc4zZsygFStW1JgeZc6X7du3k6enJwkEAvLw8KAtW7bI51XEe9++feTn50cCgYB8fHzkx7di/sufGTNm1JgmIsVrjkgWxxEjRpBQKCRXV1f6448/yMXFhTZs2FDrtqpScb4cOXKEWrduTQKBgIYMGSI/9yqW6devn/zvqo7xy+bNm0eGhoaUnJysML2oqIhatGhBAQEB8mkBAQHk6OhIRUVFCssmJyeTgYEBzZs3Tz7t1WNR4bfffiMAdO7cOSIi2rBhA7m6uirz9ZX2wQcfUO/eveV/r1ixotb4Xblyhfr160cikYjMzMxoyJAhlJWVRUREp06dol69epGpqSlZWFjQ8OHDFa6bV8+Vl49/dWbMmEGjR4+W/11QUCC/x9rZ2dH69eurPYbKCAoKIgB04sQJatu2LQkEAurevTtFRkYqLOPi4iL/u7r7UYWvv/6aeDwehYWFKUyXSCTUpUsX8vb2ll/rqpxXrx6LChcuXCAAtH37diIiOnLkCOnp6ZFYLK42jRXXbnWkUimtWLGCnJyciM/nk729Pb333ntEVPNz8q+//iJvb2/i8/nk4uJC69evV9iui4sLrVq1iqZNm0bGxsby862252tNXr1XxMTEUJ8+fUggEJCXlxedPXuWANCRI0eU2t6rKu4N27ZtI0dHRxKJRDR+/HjKyclRWObla8fe3p6++uor+d8fffQRzZ8/n7y8vCgoKEg+vW/fvgrr1eW+V3EOZ2dnV5r38vO7Klu2bJHfI21sbGjcuHFEJDvXXo3x48ePqby8nGbNmkWurq4kFArJ3d2dNm7cqHAcXl2v4vsmJCTQ+PHjydTUlMzNzWnUqFE1pu1lXLwPTJ48mYYOHSr/++TJk+Tj40PvvPOOwrN5+fLlCuu9+l2UeZYzDJexknqGkw4fPgxHR0esWrVKXvoCAPHx8QgICMC4ceMQERGBAwcO4MqVK1iwYIHC+hs2bECvXr0QGhqK4cOHY9q0aZg+fTqmTp2Ku3fvws3NDdOnTwcRqZy2gwcPYuXKlVi7di1u374Ne3t7bN26VWGZPXv2wMjIqMbP5cuXFdZZtmwZxo0bh/DwcAQGBmLSpEmIiopSOX0AsG/fPhgZGWHu3LmV5i1ZsgRisRiHDh0CAOzduxfu7u4YOXJklctmZmbi3LlzNe7PxsYGgYGBOHbsGCQSifw7Hj16FKWlpXX6Di8rLCzEjh070LJlSzg5OdW6/Llz5yCVSvHs2TN4eXnB0dEREyZMQGJionyZ0tJSCIVChfVEIhGSkpLw9OlT+bQdO3bg0aNHdS5JVfZ8Wb58OdasWYOoqCisXbsWy5Ytw65duxSWW7p0KZYsWYLQ0FD4+flh5MiRyMzMhJOTkzye0dHRSE5OxqZNm1RO68yZM5GYmIigoCD89ddf2Lp1q7yacIVhw4bVeF77+PgoLF9UVIQ1a9Zg9+7duHr1KnJycjBp0iSV0wYAUqkU+/fvR2BgIOzs7BTmiUQivPvuuzhz5gyysrKQlZWFM2fO4N1334VIJFJY1s7ODoGBgThw4ECt94AZM2bA3NxcXg3fzs4OycnJ+Pfff+v0HV4VFxeH06dPo1+/fkqvExYWhoEDB8Lb2xvXr1/HlStXMHLkSHlNgcLCQixevBi3b9/GhQsXoKOjg7Fjx8qrht+8eRPAi5o+VTUxqM3SpUtx6dIl/P333zh79iyCg4Nx9+5dhWXmzZtX632wqu1+9913uHXrFqytrTFy5EiFpgmq2Lt3LwYPHoz27dsrTNfR0cEHH3yABw8eIDw8XKXzqiYDBgxA+/btFc6V8vJyHDlypE7PGgA4dOgQNmzYgJ9//hmxsbE4evQo2rZtC6D65+SdO3cwYcIETJo0CZGRkVi5ciWWLVtWqdr0+vXr0b59e4SGhmLZsmVKP1+VIZVK8frrr4PP5yMkJATbtm3Dxx9/XGk5Hx+fGs+PYcOGKSwfFxeHgwcP4vjx4zh9+jRCQ0Px7rvvVpuO/v37IygoSP53UFAQ/P390a9fP/n04uJihISEoH///ip/T3W4ffs23n//faxatQrR0dE4ffq0vGbSpk2b4OfnJ69FlJycDCcnJ0ilUjg6OuLPP//EgwcPsHz5cvzvf//DwYMHAchq6k2YMEFeoyQ5ORk9e/aEWCzG0KFDYWxsjMuXL+Pq1aswMjJCQEBAnWprcOE+0L9/f1y5ckVeQ6aqGFdM11SMGaZRaPilAsPIvfp2t6o35W+99RbNmTNHYdrly5dJR0eHiouL5etNnTpVPj85OZkA0LJly+TTKkqyXy2VqcqrpUF+fn707rvvKizTvXt3hdLFvLw8io2NrfHzcukhAIVSw4ptvvPOO1WmqaJ0RyQSkaGhofxz9+5dIpKVUNZU2mliYiLftqenZ5WlTkSyEm8A9M0331R5LF72008/EQBKTU0lIllJkbm5OQmFQurZsyd9+umnFB4eXm2aqrJlyxYyNDQkAOTh4aFUKT2RrGRcX1+fPDw86PTp03T9+nUaOHAgeXh4UGlpKRER/fzzz2RgYEDnz58niURC0dHR5OnpSQDo2rVrRCQrabKxsaHo6Ggiqr0UuSrKnC9ubm60d+9ehWVWr15Nfn5+RPQi3l9//bV8vlgsJkdHR3lsaiolqs7L11x0dDQBoJs3b8rnR0VFEQCF6zApKanG8/rJkyfyZXfs2EEA6MaNG5W2GRISUmWaVqxYQTo6OgrnddeuXYmIKCUlpVJ6Xnb48GH5tm/cuFFjqeD333+vcL7WVLrUvXt3GjZsGBERlZeX08yZMwkA2dnZ0ZgxY+iHH36g3NzcKtetTkWNCwA0Z84ckkgkSq87efJk6tWrl9LLp6enEwB5aVdtNX2q8nKpVn5+PvH5fDp48KB8fmZmJolEoko1P2q7D1aoOH/3799faZsHDhyoMk0V59fL54qt7f+zd95xTV3vH/8kZBACYU/ZKlscOOveWLWuOnFVq9Wqtdpqh7PW0Vat2tbRn9bVOmvVTveqdYOIKIgCIqggS/YKyfP7I1+iYQYIcKPn/XrlBbn33HPPvZ9z7s1zxvPYqvcbGhpWqOnNmzcJAB04cKBa9ar0vSjNyJEjydvbW/39888/J4FAQBYWFhQYGEjffPMNJSUllXtseaxdu5Y8PDyoqKio3P3lvSfHjBlDvXv31tg2b9488vHx0Thu8ODBGmm0eb9WxstlOXHiBAkEAnry5Il6/7Fjx8q0ybi4uErrx+PHj9VplyxZQgYGBhrbjh07Rnw+v8J3+datW0kqlZJcLqesrCwSCASUnJxMe/fupS5duhDRixkWjx49KvdatKUmz2Aiot9++41kMhllZWWVu1/bke8ZM2aoR/iJyq+nP//8M3l6emrMRissLCSJREInTpyo8hxcfA48ePBA473dpk0bOnjwID19+pTEYjHl5+dTXl4eicVi2rVrV6X3h8HQZwR1323AYOiOsLAw3L59G3v27FFvIyIolUo8fPgQ3t7eAAB/f3/1fltbWwBQj268vC05ObnMyExVREZGYtq0aRrbOnTooNEjbGJiUu21yh06dCjzvSpHVgcOHFBfMwCNUWyqxshQddJWlUeJ06dhw4ahf//+uHjxIq5evYpjx47hm2++wbZt27R2AhYUFITevXsjMTERa9aswYgRI3Dp0qUyI+ylUSqVkMvl+O6779CnTx8AqtkLdnZ2OHfuHPr27YspU6YgJiYGAwYMgFwuh0wmw+zZs7F06VLw+XwoFAqMGTMGX3zxBTw8PGp8X6qqL7m5uYiJicHkyZMxZcoUdZri4mKYmpqWOa4EgUCA1q1b13g2R3nlFAgECAgIUG/z8vIqs36yUaNG1cpXIBCgTZs2ZfKMjIxE27Ztyz3G09MTf/zxh/q7WCzW2N8QdbukXhsYGGDHjh1Yvnw5zp49i2vXrmHlypX4+uuvcf36ddjb22uV54EDB5CdnY2wsDDMmzcPa9aswfz587U69tatWxg+fHiF+x88eIDFixfj2rVrSE1NVY/Qx8fHw8/PT6tzVEZMTAyKiorQrl079TYLCwt4enpqpLOxsam2P5KX63hJnpXVcRMTE42RQT5fcwJiQ9YVAFixYgXmzp2rritbtmzBypUr8e+//2q8kypi+PDhWL9+Pdzd3REYGIg333wTAwcOhEBQ8c+3yMhIDBo0SGNbx44dsX79eigUChgYGAAAWrdurZFG2/erNkRGRsLJyQkODg7qbaXfcQDg4uKidZ4A4OzsrPEM6tChA5RKJaKiosp9l3fr1g25ubm4ceMGnj9/Dg8PD1hbW6Nr16545513UFBQgPPnz8Pd3R3Ozs7VKouu6N27N1xcXNQaBwYGYsiQIVX6J9i4cSO2b9+O+Ph45Ofno6ioqMroAGFhYYiOji7z+6SgoEDtJFBbuPIcaNKkCRwdHXH+/Hn4+voiNDQUXbt2hY2NDZydnXHlyhUQEQoLC9lIPeOVhhn1DL0iJycH7733Hj744IMy+15+IQuFQvX/JT+wyttW2lOxrtizZ0+5U99f5tixY+jcuXOtzuPk5IQmTZqU2e7h4YH//vsPRUVFEIlEGvuePn2KrKwstaHq4eFR4cuyZLs2Rm1kZCRkMhksLS3V2wwNDdG7d2/07t0bixYtwrvvvoslS5ZobdSbmprC1NQUTZs2Rfv27WFubo4jR45g9OjRlR5XYlj5+Piot1lbW8PKykrtyZrH4+Hrr7/GypUrkZSUBGtra5w5cwYA4O7ujuzsbAQHByM0NFQ9/VSpVIKIIBAIcPLkSZ043MnJyQEAbN26VePHEQD1j28u0a9fvzJLR17GxcWlXM/i1UEkEpVbr62trdUdAuURGRkJHo+HJk2aqI2ryMhIDBkypNy05ubmsLa2rrQsCoUCDx480OiYAFSdG+PGjcO4cePw5ZdfwsPDA1u2bMEXX3yh1TWWdMD5+PhAoVBg6tSp+Oijj7TSvPRygtIMHDgQLi4u2Lp1KxwcHKBUKuHn56cTZ2jVYdq0afjll18qTVNS/2sKn88vt64A2j/bqlOvqiIyMhJubm4a2ywtLTF8+HAMHz4cK1euRMuWLbFmzZoyy2vKw8nJCVFRUTh9+jROnTqF999/H6tXr8aFCxc03mk1QSqVanzX9v2qS3x9fTWWO5Wmc+fOOHbsWI3zLzH4zp07h+fPn6uXuTg4OMDJyQmXL1/GuXPnGtR5WknH1Pnz53Hy5EksXrwYS5cuxY0bNyp0Srd//358/PHHWLt2LTp06AATExOsXr0a165dq/RcOTk5CAgI0Oi4KaGqZ2FNqY/nQLdu3XDu3Dn4+/ujadOm6k6Ekin4RIQmTZpotXyPwdBXmFHP4CzleZNu1aoVIiIitPpxVVd4e3vj2rVrGD9+vHpb6XAqb731VhkDrTSlRzyvXr1aJs+WLVvWqIyjRo3Cd999hx9//BGzZs3S2LdmzRoIhUIMGzZMnXbMmDH4888/y6yrX7t2LSwtLdG7d+9Kz5ecnIy9e/di8ODBZUbKXsbHx6fGMYqJSN3bXhUdO3YEoFpf7ujoCEDl3To1NbXMyJCBgYFai3379qFDhw6wtraGUqlEeHi4RtpNmzbh7NmzOHToUJkf7hVRVX2xtbWFg4MDYmNj1V67K+Lq1avqtZbFxcUICQlRdziUdN5oGx2gNF5eXuo8SwzYqKioMuGZtm3bhvz8/ArzKW1oFBcXIzg4WD0qX5JndUb9SuDz+RgxYgT27NmDZcuWaYzM5efnY9OmTejbty8sLCwAqEbANm3ahDlz5mgYwklJSdizZw/Gjx9fZTixXbt24fnz5+r2Uh7m5uawt7evsUfzkpklSqVSK6Pe398fZ86cKbcDIS0tDVFRUdi6dau60/C///7TSFPbutK4cWMIhUJcu3ZNbew9f/4c9+/f1/ANsGzZMnz88cfVyvvq1atl8qxJXQFUz7YFCxYgLCxMY129UqnEunXr4OPjg+bNm4PH41WrXlXE2bNnER4ejjlz5lSYRiQSoXHjxtWqKxKJBAMHDsTAgQMxY8YMeHl5ITw8HK1atSr3Pent7V0mdOilS5fg4eFRaf3S5fvV29sbCQkJSExMVHeyln5PAsA///xTqc+E0h1Y8fHxePr0qXoGwNWrV8Hn88uMDr9M9+7dcf78eTx//hzz5s1Tb+/SpQuOHTuG69evY/r06dW6Pl0jEAjQq1cv9OrVC0uWLIGZmRnOnj2r9ktQWuNLly7hjTfe0PAnUHqkvaLfUAcOHICNjQ1kMlmtysyl50D37t3xwQcfwMfHRyNcYZcuXbB161YQERulZ7z61Pd8fwajIkqvG+vduze99dZb9PjxY0pJSSEilQd0iURCM2bMoNDQULp//z4dPXqUZsyYoT6uvLVwKLWOrzprSkuvI9+/fz8ZGhrS9u3bKSoqihYvXkwmJia19n5vZWVFP/30kzpPPp9Pd+/eLTe9NuWfPXs2icViWrNmDUVHR1NkZCQtWLCA+Hy+hld8pVJJQ4YMIXNzc9q2bRs9fPiQwsLCaOrUqSQQCDTu244dO0gmk1FiYiI9ffqUIiIi6KeffqLGjRuTu7s7PX36lIiIUlNTqXv37vTzzz9TWFgYxcbG0sGDB8nW1pYmTZpU5f2IiYmhlStXUnBwMD169IguXbpEAwcOJAsLC/Ua6KoYNGgQ+fr60qVLlyg8PJwGDBhAPj4+6rWpKSkptHnzZoqMjKTQ0FD64IMPyNDQsMK13kQ1W1OvTX3ZunUrSSQS2rBhA0VFRdHt27dp+/bttHbtWiJ6obezszMdPnyYIiMjaerUqWRsbKxuG48fPyYej0c7d+6k5ORkys7OrrJspdtcYGAgtWzZkq5evUrBwcHUqVMnkkgktfJ+LxQKqW3btuo827dvT+3bt6/wmKrucWpqKjVu3Jj8/Pzon3/+ofj4eLpw4QJ17tyZbGxsKCYmRp32/v37ZGVlRZ07d6YLFy5QfHw8HTt2jPz8/Khp06aUlpamcS+mTJlCiYmJlJCQQFeuXKH58+eTUCjU8G2xZcsWmjZtGp04cYKio6Ppzp07NH/+fOLz+VpFe/jll1/owIEDFBERQTExMXTgwAFycHBQR47QhqioKBKJRDR9+nQKCwujyMhI2rRpE6WkpJBCoSBLS0saO3YsPXjwgM6cOUNt2rTReAbK5XKSSCS0fPlySkpK0vAeXhGl159OmzaNXFxc6MyZMxQeHk5vvfUWGRsb19rrta+vL50+fVqdp7Ozs9oPRmmq8n6fn59P7dq1IycnJzp48CA9evSIrl+/ToMHDyapVEpXrlxRp61OvZowYQIFBgZSYmIiPX78mEJCQmjFihVkbGxMAwYMoOLiYiIi+vPPPykoKIj+/PNPioqKonv37tHq1avJwMCAdu/erdV92bFjB23bto3Cw8MpJiaGFi5cSBKJhFJTU4mo/PdkSEgI8fl8WrZsGUVFRdHOnTtJIpHQjh071PmW957U5v1aGS/nqVAoyMfHh3r37k23bt2if//9lwICAmrt/V4qlVKvXr3UeXp4eNCoUaMqPW779u0kkUhIIBBo+DPYtWsXmZiYEAD1u6u8a6mKxMRECg0Npa1btxIA+vfffyk0NFTj+VIZf/75J23YsIFCQ0MpLi6ONm3aRHw+n+7cuUNERFOmTKE2bdrQw4cP1W18w4YNJJPJ6Pjx4xQVFUULFy4kmUym8excsWIFOTs707179yglJYWKioooNzeXmjZtSt26daN///2XYmNj6dy5czRr1ixKSEiosqxcfA4QEcXGxhIAMjEx0ViP/+jRIxKJRCQSicr4rWFr6hmvGsyoZ3CG0gbGlStXyN/fX+1MqoTr169T7969ydjYmKRSKfn7+9OKFSvU++vaqCdSvSytrKzI2NiYJkyYQPPnz6+1Ub9x40bq3bs3icVicnV1rdApTHXK/9NPP1FAQAAZGhqSVCqlzp07lxu6Ti6X0+rVq8nX15dEIhHJZDLq27cv/ffffxrpShxTASAej0empqbUtm1bWrZsmYajsIKCAvr000+pVatWZGpqSkZGRuTp6UkLFy4sE16sPJ48eUL9+vUjGxsbEgqF5OjoSGPGjKF79+5VeWwJmZmZNGnSJDIzMyMLCwsaMmSIRii1lJQUat++PUmlUjIyMqKePXtqOHQrj5oY9UTa1Zc9e/ZQixYtSCQSkbm5OXXp0oUOHz5MRC/03rt3L7Vt25ZEIhH5+PjQ2bNnNfJYtmwZ2dnZEY/Hq1FIu8TEROrfvz+JxWJydnam3bt36ySk3W+//Ubu7u4kFoupV69eGg6pSqPNPU5JSaFZs2aRk5MTCYVCsrW1pYkTJ5abb1xcHE2YMIFsbW1JKBSSk5MTzZo1S20UlfByeLCS0GEDBgxQa1DCzZs3aezYseTm5kZisZgsLS2pS5cu5bar8ti/fz+1atVK/fzy8fGhlStXauWI7GXOnz9Pb7zxBonFYjIzM6O+ffuqHXSdOnWKvL29SSwWk7+/P50/f77MM3Dr1q3k5OREfD6/RiHtsrOzaezYsWRkZES2trb0zTff6CSU1Z9//ql+DrVt27ZS55pVGfVERLm5ubRgwQJq0qQJCYVCsrCwoGHDhmmEyCpB23r1cpgxgUBA1tbW1KtXL9q+fbuGw8OYmBiaMmUKeXh4qEMPtmnTRsO4roojR45Qu3btSCaTkVQqpfbt22uE6qzoPVkS0k4oFJKzszOtXr1aI9+K2nVV79fKKJ1nVFQUderUiUQiEXl4eNDx48d1EtJu06ZN5ODgQIaGhvT222+rQzlWRMnz08vLS2N7XFyc2glrVddSVblK6sPLH211vnjxInXt2pXMzc1JIpGQv7+/xvs/KiqK2rdvTxKJRB3SrqCggCZOnEimpqZkZmZG06dPp08//VTj2ZmcnKzWEi+FtEtMTKTx48eTlZUVicVicnd3pylTpmjl7JOLz4ESXFxcynWA7OrqWm7HDTPqGa8aPCIdeIZhMBgMRp0RFxcHNzc3hIaGVukIicFgMBgMBoPxesHi1DMYDAaDwWAwGAwGg6GnMKOe8drTr18/GBsbl/tZuXJlQxfvlWTPnj0V3nNfX98qj582bVqFx5cOH/e6Eh8fX+E9MjY2VkcBYOgWfX2eVFZXKot2wHg9uHjxYqV15FWltu8qfYM9BxgM/YVNv2e89jx58qRCb94WFhZVejxmVJ/s7Gw8e/as3H1CobDK2MXJycnIysoqd59MJqt2TNxXkeLiYsTFxVW439XVtdJY14yaoa/Pk+jo6Ar3NWrUqMoweoxXm/z8fDx58qTC/Q0ZkaYuqe27St9gzwEGQ39hRj2DwWAwGAwGg8FgMBh6Cpt+z2AwGAwGg8FgMBgMhp7CubmXSqUST58+hYmJCXg8XkMXh8FgMBgMBoPBYDAYryBEhOzsbDg4OIDP19/xbs4Z9U+fPoWTk1NDF4PBYDAYDAaDwWAwGK8BCQkJcHR0bOhi1BjOGfUmJiYAVDdWJpM1cGleHSIiIuDj49PQxWBUAtOI+zCN9AOmE/dhGnEfphH3YRrpB0wnbpOVlQUnJye1DaqvcM5RXlZWFkxNTZGZmcmMeh2Snp7OWa/LDBVMI+7DNNIPmE7ch2nEfZhG3IdppB8wnbjNq2J76u/CAUa1qCj8F4M7MI24D9NIP2A6cR+mEfdhGnEfppF+wHRi1AfMqOcYS36/g4y8Ip3nm5OTo/M8GbqFacR9mEb6AdOJ+zCNuA/TiPswjfQDphOjPmBGPYe4/ywb1+OeY+flOJ3nzZwPch+mEfdhGukHTCfuwzTiPkwj7sM00g+YToz6gHOO8rRFoVBALpc3dDF0yuEbD/HtUB9svhCNtKwcSEW6k+fZs2cQi8U6y4/rCIVCGBgYNHQxqkVqaipMTU0buhiMSmAa6QdMJ+7DNOI+TCPuwzTSD5hOjPpA74x6IkJSUhIyMjIauig6RUmETrZKICcZE5tJERMTCxNDoc7yLyoqwsOHD3WWnz5gZmYGOzs78Hi8hi6KVuTn5zd0ERhVwDTSD5hO3IdpxH2YRtyHaaQfMJ0Y9YHeGfUlBr2NjQ2MjIz0xmCrivTcItgY8GBiKAQR4fHzPDQyMwKfr5vrUygUejdyXVOICHl5eUhOTgYA2NvbN3CJtMPFxaWhi8CoAqaRfsB04j5MI+7DNOI+TCP9gOnEqA9qZdR/9dVX+OyzzzB79mysX78eANCtWzdcuHBBI917772HLVu21OZUAFSGaYlBb2lpWev8uAIRoSC7GPYWUnUnhTUZIE9JsDLSzZT5goICGBoa6iQvfUAikQAAkpOTYWNjoxcdGklJSXofI/NVh2mkHzCduA/TiPswjbgP00g/YDox6oMaG/U3btzAjz/+CH9//zL7pkyZgmXLlqm/GxkZ1fQ0GpSsoddVflwhu6AYxoYCjVkHphIhHqbmwkIqAl8HsxGIqNZ56Bsl9UQul+uFUV9YWNjQRWBUAdNIP2A6cR+mEfdhGnEfppF+wHRi1Ac18n6fk5ODoKAgbN26Febm5mX2GxkZwc7OTv2RyWQV5lVYWIisrCyNT1W8KlPuS0jPLYKFkUhjG4/Hg5mRUGfh7UQiUdWJXjH0rZ64u7s3dBEYVcA00g+YTtyHacR9mEbch2mkHzCdGPVBjYz6GTNmoH///ujVq1e5+/fs2QMrKyv4+fnhs88+Q15eXoV5rVq1CqampurP6xb2oUCugMCAB4FBWSnMjETIyJPrZJS9qEg3nQOMuiM+Pr6hi8CoAqaRfsB04j5MI+7DNOI+TCP9gOnEqA+qbdTv378fN2/exKpVq8rdP2bMGPzyyy84d+4cPvvsM/z8888YO3Zshfl99tlnyMzMVH8SEhKqWyS9Ji23CJZSMc6fPw8ej6fh1Z/P40EmESIzXz9D902cOBGDBw9u6GLoDcXFxQ1dBEYVMI30A6YT92EacR+mEfdhGukHTCdGfVCtNfUJCQmYPXs2Tp06VaHTtalTp6r/b9asGezt7dGzZ0/ExMSgcePGZdKLxeLXKn76yyiUSsiLlZCIKl7vbWEkQlxaLkwlwlpNJ6/LexwXFwc3NzeEhoaiRYsW6u0bNmx4Ldfy15QmTZo0dBEYVcA00g+YTtyHacR9mEbch2mkHzCdGPVBtUbqQ0JCkJycjFatWkEgEEAgEODChQv47rvvIBAIoFAoyhzTrl07AEB0dLRuSvwK8TxPDjOjymPR8/k8mBgKkFVQu16+8px01PWUfFNTU5iZmdXpOV4lYmNjG7oIjCpgGukHTCfuwzTiPkwj7sM00g+YToz6oFpGfc+ePREeHo5bt26pP61bt0ZQUBBu3bpVrofxW7duAdCfWOF1SWFhIT744APY2NjA0NAQgT27IerOLY00ly5dgr+/PwwNDdG+fXvcuXMHFlIx0nIKERcXh4EDB8Lc3BxSqRS+vr74559/1MfeuXMH/fr1g7GxMWxtbTFu3Dikpqaq93fr1g0zZ87Ehx9+CCsrK/Tt2xdjxozByJEjNcogl8thZWWF3bt3AwCOHz+OTp06wczMDJaWlhgwYABiYmLU6d3c3AAALVu2BI/HQ7du3QCUnX5f+vo7deqEGzduqPeXLEE4c+YMWrduDSMjI7zxxhuIiopSpwkLC0P37t1hYmICmUyGgIAABAcH10wQjqFUKhu6CIwqYBrpB0wn7sM04j5MI+7DNNIPmE6M+qBaRr2JiQn8/Pw0PlKpFJaWlvDz80NMTAy+/PJLhISEIC4uDn/88QfGjx+PLl26lBv67nVj/vz5+O2337Br1y5cvHINTZo0Qb/AQKSnp6vTzJs3D2vXrsWNGzdgbW2NgQMHQqkohlQswLT3Z6CwsBD//vsvwsPD8fXXX8PY2BgAkJGRgR49eqBly5YIDg7G8ePH8ezZM4wYMQLAi+n3u3btgkgkwqVLl7BlyxYEBQXhzz//RE5OjroMJ06cQF5eHoYMGQIAyM3Nxdy5cxEcHIwzZ86Az+djyJAh6ofU9evXAQCnT59GYmIiDh8+XOX137x5E02aNEHfvn01rh8AFixYgLVr1yI4OBgCgQCTJk1S7wsKCoKjoyNu3LiBkJAQfPrppxAKK5/toC94eno2dBEYVcA00g+YTtyHacR9mEbch2mkHzCdGPUC1ZKuXbvS7NmziYgoPj6eunTpQhYWFiQWi6lJkyY0b948yszM1Dq/zMxMAlDuMfn5+RQREUH5+fm1LXa9k5OTQ0KhkPbs2UNERHGpOZSXX0AODg70zTff0Llz5wgA7d+/X31MWloaSSQSOnDgAMmLFeTp40tLliwpN/8vv/yS+vTpo7EtISGBAFBUVBTl5eVR165dqWXLlhpp5HI5WVlZ0e7du9XbRo8eTSNHjqzwWlJSUggAhYeHExHRw4cPCQCFhoZqpJswYQINGjSo3OsnIioqKlJfPxGp78Hp06fVaf7++28CoNbcxMSEdu7cWWHZXkbf6kvJ/WRwF6aRfsB04j5MI+7DNOI+TCP9gOnEbSqzPfWJajnKK4/z58+r/3dycsKFCxdqm2WNWHAkHM+yCurtfLYyQ6wY0kzr9DExMZDL5ejYsSMK5QrweTxIDMVo27YtIiMj0aZNGwBAhw4d1MdYWFjA09MTkZGREBjw8e609/HZXJWjwl69emHYsGHqGRBhYWE4d+6ceuS+9LlLQgUGBARo7BMIBBgxYgT27NmDcePGITc3F7///jv279+vTvPgwQMsXrwY165dQ2pqqnqEPj4+Hn5+ftW+/hKEQqH6+l/m5VkdJcs2kpOT4ezsjLlz5+Ldd9/Fzz//jF69emH48OHlOmBkMBgMBoPBYDAYjNeBWhv1XKE6BnZDk5ZbBEtjUbWPm/3+NLzRpSduXzmHkydPYtWqVVi7di1mzZqFnJwcDBw4EF9//XWZ4+zt7dXT76VSaZn9QUFB6Nq1K5KTk3Hq1ClIJBIEBgaq9w8cOBAuLi7YunUrHBwcoFQq4efnV2eO9l6eTl/i8b+kI2Hp0qUYM2YM/v77bxw7dgxLlizB/v371UsF9Bk2PYv7MI30A6YT92EacR+mEfdhGukHTCdGfVDtOPWMmtG4cWOIRCJcvPgfCouVMBIJIJfLcePGDfj4+KjTXb16Vf3/8+fPcf/+fXh7ewMAhAZ8uLo4Y/ykd3H48GF89NFH2Lp1KwCgVatWuHv3LlxdXdGkSRONj1QqLdf7fQlvvPEGnJyccODAAezZswfDhw9XG9ZpaWmIiorCwoUL0bNnT3h7e+P58+cax4tEqg6K8qIflL7+S5cuqbeVd/3a4OHhgTlz5uDkyZMYOnQoduzYUa3jucrLDgEZ3IRppB8wnbgP04j7MI24D9NIP2A6MeoDZtTXE1KpFNOnT8e8+fMR8t9ZREREYMqUKcjLy8PkyZPV6ZYtW4YzZ87gzp07mDhxIqysrNQe5D/88EPcvHweN+9E4ebNmzh37pza4J8xYwbS09MxevRo3LhxAzExMThx4gTeeeedSo3tEsaMGYMtW7bg1KlTCAoKUm83NzeHpaUl/u///g/R0dE4e/Ys5s6dq3GsjY0NJBKJ2jlfZmZmxdc/bx6OHz9e4fVXRn5+PmbOnInz58/j0aNHuHTpEm7cuKG+BwwGg8FgMBgMBoPxusGM+npk1apV6NP/LUyfMgmtWrVCdHQ0Tpw4AXNzc3War776CrNnz0ZAQACSkpLw559/aoyEf/jBLPR6IwCBgYHw8PDApk2bAAAODg64dOkSFAoF+vTpg2bNmuHDDz+EmZkZ+Hy+evp9RQQFBSEiIgKNGjXSWPfO5/Oxf/9+hISEwM/PD3PmzMHq1as1jhUIBPjuu+/w448/wsHBAYMGDSr3HF999RWGDRuGcePGVXj9lWFgYIC0tDSMHz8eHh4eGDFiBPr164cvvvhCq+O5DpuexX2YRvoB04n7MI24D9OI+zCN9AOmE6M+4BERNXQhXiYrKwumpqbIzMyETCbT2FdQUICHDx/Czc0NhoaGDVTCmpNdIEdekQK2stqVvbBYgWdZhXC2MNL6mPz8fEgkklqdV9/Qt/py584drR0PMhoGppF+wHTiPkwj7sM04j5MI/2A6cRtKrM99Qk2Ul+PpOcWwUJafQd5pRELDMADUCCvelo9Q3/g81lz5DpMI/2A6cR9mEbch2nEfZhG+gHTiVEfsFpWTxQWq8LYCQ10c8utTcRIza7Y+V1pqpp+z2h43N3dG7oIjCpgGukHTCfuwzTiPkwj7sM00g+YToz6gBn19UR6ThEsdTBKX4Kh0ABKAoqKtRutr8z7PYMbREdHN3QRGFXANNIPmE7ch2nEfZhG3IdppB8wnRj1ATPq6wGFklBQrISRWKDTfK1NREjJrptY8Yz6RyDQbf1g6B6mkX7AdOI+TCPuwzTiPkwj/YDpxKgPmFFfD2TkFcHMSKjzfCUiAYqVSsgVyirTlnjQZ3AXZ2fnhi4CowqYRvoB04n7MI24D9OI+zCN9AOmE6M+YEZ9HUNEyMyXw1Sie6MeAKyMtVtbX1TERvS5TmxsrE7zyy6QIzNfrtM8X3d0rRGjbmA6cR+mEfdhGnEfppF+wHRi1AfMqK9jcgsVMBIJwOfx6iR/qViAwmIliqsYrefV0fkZukOXzgyf5xZh+i83MefALa1mcjC0gzmc1A+YTtyHacR9mEbch2mkHzCdGPUBM+rrmLTcQlga1+3UdytjEVJzKh+JFwrrZqYAQ3fY2dnpJJ/03CLM3HcTn7/pjeEBjlj5T6RO8mXoTqO6hIgQlpDR0MVoUPRBp9cdphH3YRpxH6aRfsB0YtQHzKivQ4qKFeDpMIxdRUjFAuTLFVAoKx6RZdPvuc+jR49qnUdaTiFm7buJhf194OMgQ79m9jAUGuBI6GMdlJChC43qmj/CnmLZXxFYcCQc+UXaRcd41dAHnV53mEbch2nEfZhG+gHTiVEfMKO+DknL1W0Yu4rg8XiwlIqQVslofU2m3+/cuRNmZma1KJlumDhxIgYPHtzQxahzJBJJrY5PzSnEB/tDsXiAL7ztZertH/fxxLHwJNx5klnbIr721Fajuia3sBj7rydg35T26Otrh0k7byDiaVZDF6tc8oqKcfxOIpRK0nneXNeJwTTSB5hG3IdppB8wnRj1ATPq6wilkpBfpICRyKBezmdiKEBOYTEUFfxArotwGnFxceDxeLh16xYn89M3rKysanxsak4hZu8PxZKBvvC0M9HYZ8Dn4eth/lj5TySe57IZG7WhNhrVB5vOR2NqF3eIBHx08bDG92Na4rszD7D9v4cg0r3xXFPORSVj8s5g3HmShZn7biK7QLcOHbmuE4NppA8wjbgP00g/YDox6gNm1NcRGflymBmJauWgrjpT5nk8HiykIqRXYLTJ5Q3nBZ1N/deOhISEGh2Xkl2ID/aFYulAX3jYmpSbxlwqwudvemP+b7cr7PhhVE1NNaoP4tPyEJOci+5eNuptVsZibB7bCnweMO2XEKTmVB0poy5JyS7EnAO3cDUmDT9NbI2P+3picid3vPdzCB6m5ursPFzWiaGCacR9mEbch2mkHzCdGPVBtYz6zZs3w9/fHzKZDDKZDB06dMCxY8fU+wsKCjBjxgxYWlrC2NgYw4YNw7Nnz3ReaK5DRKrY9C+FscvOzkZQUBCkUins7e2xbt06dOvWDR9++KE6jaurK7788kuMHz8eMpkMU6dOBQD89ttv8PX1hVgshqurK9auXatxPh6Ph6NHj8JUIkR2gRxKJcHMzAw7d+4EoBoBNzIywuHDh9G9e3cYGRmhefPmuHLlikY+O3fuhLOzM4yMjDBkyBCkpaVVep1ubm4AgJYtW4LH46Fbt24AXkyXX7FiBRwcHODp6alRzpd5uZwV5VfCmjVrYG9vD0tLS8yYMaNBOyrqAmNj42ofk5xdgNn7Q7FskB+aVmDQl+DXyBRvNrPDmpNRNS3ia09NNKovvj5xD/MDPcts5/F4mNjRDR/28sAH+0Jx4X5KvZeNiHDgRjzmHryFyZ3c8Nmb3jASqWYPBbiY49sRLbD49zs4H5Wsk/NxWSeGCqYR92EacR+mkX7AdGLUB9Uy6h0dHfHVV18hJCQEwcHB6NGjBwYNGoS7d+8CAObMmYM///wTv/76Ky5cuICnT59i6NChdVJwLpP3v2n3fP6LUfq5c+fi0qVL+OOPP3Dq1ClcvHgRN2/eLHPsmjVr0Lx5c4SGhmLRokUICQnBiBEjMGrUKISHh2Pp0qVYtGiR2hB+GR6PB3MjEZ7nlT8yvmDBAnz88ce4desWPDw8MHr0aBQXFwMArl27hsmTJ2PmzJm4desWunfvjuXLl1d6ndevXwcAnD59GomJiTh8+LB635kzZxAVFYVTp07hr7/+qvKeVZXfuXPnEBMTg3PnzmHXrl3YuXNnufdAn5HJZFUneonkrALM3ncLXw72QxMb7V4YQ1o6okCuwLHwxJoU8bWnuhrVFxcfpMDRTAJ364rrgbe9DD9NaINTEUlY/lcECovrx4ledHIOJu8KRm6hAjvfaQu/RqZl0tiZGmLr+Nb4+3YifrwQU+ulAlzVifECphH3YRpxH6aRfsB0YtQH1VpoPXDgQI3vK1aswObNm3H16lU4Ojrip59+wt69e9GjRw8AwI4dO+Dt7Y2rV6+iffv2uit1efw1B8iqR0NFZg8MWFfurrScItiZGqq/Z2dnY9euXdi7dy969uwJQHVvHBwcyhzbo0cPfPTRR+rvQUFB6NmzJxYtWgQA8PDwQEREBFavXo2JEyeWOd7USIi4Cqaxfvzxx+jfvz8A4IsvvoCvry+io6Ph5eWFDRs2IDAwEPPnz1ef5/Llyzh+/HiFt8Da2hoAYGlpWSZch1QqxbZt2yASae8osLL8zM3N8cMPP8DAwABeXl7o378/zpw5gylTpmidP9d5+vQpLCwstEr7LKsAH+6/hRVD/Co15Mrj8ze98d7PIWhiY1zl6D5Dk+poVF/IFUpsPh+DH8cFVJlWIjLA8sHNcPxOEt7dFYylb/micTXrj7YUFiuw5Xwsop5l4cvBfmhkVrmjIEOhAb552x/bL8Xho1/DsHJIMxgKa+aThIs6MTRhGnEfphH3YRrpB0wnRn1QY+9pCoUCv/76K3Jzc9GhQweEhIRALpejV69e6jReXl5wdnbGlStXKjTqCwsLUVj4Yp1nVlYNPTVXYGDXN0XFqrByIsGLSRCxsbGQy+Vo27atepupqal6WvrLtG7dWuN7ZGQkBg0apLGtY8eOWL9+PRQKBQwMNH/08nk8mEqEKG+cy9/fX/2/vb09ACA5ORleXl6IjIzEkCFDNNJ36NChUqO+Mpo1a1Ytg74qfH19Na7V3t4e4eHhOsufC2jbk5uUWYA5B25h5dBmcLOSVvs8QgM+vhrWDB/uv4Ut4wIgMxRWfRADADd723dfeYShrRxhUg0dA/3s0NzJFAuO3EGgrx2Gt3aslf+P0lx/mI71p+9jbHsXfNCzidZ583g8TO7khosPUjBldzC+HuYPhyo6A8qDizoxNGEacR+mEfdhGukHTCdGfVBtR3nh4eEwNjaGWCzGtGnTcOTIEfj4+CApKQkikahMCDRbW1skJSVVmN+qVatgamqq/jg5OVX7IrhEem4RLIxrbsxKpdU30ng8nsZ0VXOpCHK5vMwUVqFQqHEMACgriW1fG8q7jtLlBLR34Pdy2UvyqquyNxRGRkZVpknMzMecA7ewqoYGfQk2Job4uK8nPvstvE5Cir2qaKNRfZKWU4gL91MwtGWjah9rbyrB1vGtkZJTiA8P3EJmfu19VGTmyfH5kXD8EfYEm8cG4M1m9jXqLOjc1BrLB/vh41/DcCMuvdrHc00nRlmYRtyHacR9mEb6AdOJUR9U26j39PTErVu3cO3aNUyfPh0TJkxAREREjQvw2WefITMzU/3RZw+RSiUhr6gY0lJh7Nzd3SEUCnHjxg31tszMTNy/f7/KPL29vXHp0iWNbZcuXYKHh4d65Nra2hqJiS+WHsRERyM/Lw/5RdqvmfX29sa1a9c0tl29erXSY0pG4hUK7c5TupwPHjxAXl5ejfN71ais8wsAnmbkY+6BMHw1rBlca2HQl9DK2Rwdm1jhh3PRtc7rdaEqjeqbNSfvY25vDw3/HdXBgM/DjO5NMOENV0z7OaRGBjSgcoT3Z9hTTN8TgiEtG2H54GYwldRuBoiLpRT/N741dl6Ow95r8dU6lms61QVEhMTMfJy7l4xN56Pxwb5QjNl6VS/CVq47dR/bLjzgVJhFRlleh3ak7zCN9AOmE6M+qPb0e5FIhCZNmgAAAgICcOPGDWzYsAEjR45EUVERMjIyNEbrnz17VmZ99MuIxWKIxeLql5yDqMLYCcuMTJmYmGDChAmYN28eLCwsYGNjgyVLloDP51c5ivXRRx+hTZs2+PLLLzFy5EhcuXIFP/zwAzZt2qRO06NHD/zwww/o0KEDFAoFPvnkEwiFQuQUFWv9o+mDDz5Ax44dsWbNGgwaNAgnTpyocuq9jY0NJBIJjh8/DkdHRxgaGsLUtKwTrKrKWdP8XjXMzc0r3PckIx8fHwzD18P84Wypux7fMe2c8dnhcJy7l6wRCo1RPpVpVN+EP86EQqlECyezWufVytkcP44PwNI/7uK/B6mY1aMJBAba9fk+fp6H5X9FwtdBhp3vtNVYelRbjMUCfD+qJTaceYBFR+9g0QAfrfLnkk66IL9IgfvPsnEvKQuRidlISM8DAbCVGcLb3gStXSwQ1M4FV2LS8PutJ5jY0a2hi1wh+UUKhD3OQDNrQ8zYexPLBzeDhVR3S7UYuuNVa0evIkwj/YDpxKgPav3rS6lUorCwEAEBARAKhThz5ox6X1RUFOLj49GhQ4fanobzvAhjV/6Pk2+//RYdOnTAgAED0KtXL3Ts2BHe3t4wNDQsN30JrVq1wsGDB7F//374+flh8eLFWLZsmYaTvLVr18LJyQmdO3fGmDFj8PHHH8PIyAiGAgNkFxRrVf727dtj69at2LBhA5o3b46TJ09i4cKFlR4jEAjw3Xff4ccff4SDg0OZtf+lqaicNc3vVaP0EoMSHj/Pw8cHw/DN27o16EtYMtAH2y89rNDBIuMFFWlU3xAR1p6Kwsd9y/rlqCkyQyG+HdECLpZGeHd3MB4/z6s0fbFCiW0XY7Hk97uYH+iJWT2b6tSgL4HP52FObw90bGKJ934ORmpOYZXHcEWn6kJESEjPw6mIZ/j+zAPM2HsT7+y4jrkHb+HsvWSYSoR4p6Mrto5vje0T22DV0GYY38EVbd0sYCoRooeXDc7c001YwLri+N1E9POzw7i2jfB+tyaYsecmLkWnNnSxGOWgr+3odYJppB8wnRj1AY+qMf/ts88+Q79+/eDs7Izs7Gzs3bsXX3/9NU6cOIHevXtj+vTp+Oeff7Bz507IZDLMmjULAHD58mWtC5SVlQVTU1NkZmaWcSxRUFCAhw8fws3NrUpjuL7JLSxGVoEc9qbaOXXKzc1Fo0aNsHbtWkyePLlOyqRQKhGfng9XSyMUFBRAIqm+wyl9hsv1pTzu3LkDPz8/jW0J6XmYdygMq99uDieLuluT9TQjH/MOhWHr+Nbq+OGMspSnUUNwNPQJkrMLMLVL4zrJ/1FaLhYevYORbZwwwL9slI47TzLx9fF7GNjcAcMDdOtkrzLuJWVh6R93sbC/T7mh8dTl44hOlZFbWIx7SarR93uJ2Xj8PA88Hg+NzCTwsjeBt70MHrYmMBZXrz0u/ysCg1s2qvT+NCSTd97AhtEtEffgHvz8/JBXVIwv/4qEqUSIub096qRjiFEz9KEdve4wjfQDphO3yXqeBlMLq3JtT32iWr8WkpOTMX78eCQmJsLU1BT+/v5qgx4A1q1bBz6fj2HDhqGwsBB9+/bVmCb+KpOeWwRbWcXLCEJDQ3Hv3j20bdsWmZmZWLZsGQDU6Wi0AZ8PidAAuYXFEBnULDQUo/6wtLTU+J6Qnof5h25jzfDmcDSvWycrDmYSzOrRFAuO3MG3I5rXm5Gmb5TWqCHILSzGweAE7HynbdWJa4iLpRTbJ7bBt6fu478HqVg80AdGIgFyC4ux7tR9pOcVYd3IFrAyrt+lU152MmwOCsC8Q2F4q0UjvNW8bIcDwA2dKuJhai5++i8WiRkFaOFkBi97Gbp6WKORmUQn7W54ayfsvfaIk0Z9fFoeLKQiGIsFao2MRAKsGtoM/4QnYvKuG/hykJ9OfIYwag+X2xFDBdNIP2A6cQwiIPU+EHMOePQfkPVqzFStllH/008/Vbrf0NAQGzduxMaNG2tVKH1DrlBCSQSRoHLDec2aNYiKioJIJEJAQAAuXrwIKyurOi2blbEIj5/nw0HGpv7oE/Fpefjkt9tYM6J5lfG9dUV7d0vcfZqFn/57iHc7u9fLORnVZ9P5aEzp4l7nI5pCAz4+CfTC5ehUTN4ZjAHN7fFXWCKmdWuMrh7WdXruyjCXirBlbABW/nMPkYlZ+LiPJwxq6CiwviAiBD96jp2X42AkNMCkTm7wtq+b0QBPOxPEpeWhQK6AoZBbnbmHQhIwvHX5EW7ebGaP5k5mWHgkHAP8HTC0VSPWuchgMBgM3ZCbCsSeVxny2YmAlQfQuDvQcixQqASmcq8jvLqweW46ID23CJZVOPpp2bIlQkJCkJOTg/T0dJw6dQrNmjWr87IJDPiQiAyQrgcekV930tLSAKimPn/y222srUeDvoRJHV0RkZiFyzFsjWt5lGjUUDxKy0VsSi66e9afU8M3mlhhY1ArKJWE7RPbNKhBX4LAgI/FA33gbiXFjD03kVWgGY6voXUqoVihxN+3EzFxxw2cvZeMxQN8sHp48zoz6Evo42uLUxHP6vQc1UWhJITEP0cbV5XDqPI0amQmwbYJbfD4eT4++jWsjK6M+oUr7YhRMUwj/YDp1ADIC1QG/KnFwC/DgBOfA8WFQPfPgXGHgX5fAR59AbFxQ5dUZ7DFs7VESYTcwmLYmHDXg7+NiRhxqcXIKypm66U5jI2NDeJSc/HZ4XB8O7K51v4ZdAmPx8OKwc0wZXcwXCyl9d6pwHVsbBo2QsA3x6MwP9Cr3s9rIRVhXAfXej9vVQxv7YQmNsZ4b3cIvhzshyY2qpdzQ+tUskTiVMQz9PaxxaagVpBWc218bRjY3AEfHwzDwAqWJzQEl2NS8UZjK/Xoe0UaGfB5mN2rKYLj0vHe7hDMC/REK2fmObohaOh2xKia11Wj/OJ83E29C5lYBjupHUyEJpye2fO66lSvEAHP7qgM+fgrqm3O7QG/t4GeSwH+qz+OzSy8WpKZL4eppGwYOy7B4/FgZyLE08wCOFsYQahlqCpG/RKbkoMNl2KxbmQL2Jk2nGM/icgAK4c0w6e/3cbW8a05N4W3IZHLG27k8N/7KXC0kMCNrTfWoKWzOdaPaoF5h25j4hsu6OFl22A6JWUWYOflOEQmZmFEayfsntRW69CAukRmKISxoQBPM/LhwJGOud9CHuPTft7q71Vp1NrVAlvGBWDJ73dwOToV07s14fwyi1eNhnzeMbTjddIoOS8ZFx5fwOUnl6EgBfyt/ZFTlIOkvCTkFOUAAHjgwdzQHLZSW9gZ2cFOqvrYGtnCWNRwI7Kvk071SlYiEHtONa0+NxWw9VVNqW87BRBy491XnzCjvpZk5MnhXIdeyXUGKeFgKsGT5/lwsTTidCfE60hsSg5WnozF1smdYCtreE/9zpZGmNzJDUv/uItVQ5ux+vI/nj9/jkaNGtX7eeUKJbZciMH/jW9d7+fWB2xlhvi/cQFY8vtd3IrPQGPDXFjZ2kFchZ8TXRGZqPJFkS9XYOIbrvgk0LPB28zbrRzxW8hjzOrZtEHLAQAZeUUokCs1Oiu1aUumEiHWjWyBQyGPMWV3MJYP9uNMJ8XrQEM97+qDIkURUvJTkJyXjGd5z5Ccm4zkPNUnrzgPIgMRgryDEGAb0NBFrZRXWSMiQtTzKJxPOI9bybdgKbFEF8cu+LLjlxUa6EpS4nnBcyTlJSEpNwmPsh7hWtI1JOUmIU+uCtPKAw+WEku14W8rtVUZ/0Z2MBLWze/5V1mneufZXSD0FyDlHmBiD7h3B/osB4zZbIhqhbSrD/QppF1eUTEy8uR68SNDLpdDKBQiI68I+UUK2OtBmWsL1+pLRUQn52DR0TtY0scZXq7cmS4LABvPRcNUIsTY9i4NXRROkJqaWufOLctj28VYmBuJMCzAsd7PrU8QEc7eS8alqKd4kq1AUbESJoZCVYg4Oxm87WWwlYl1YnATES4+SMXPVx/BTmaISZ3cODWLQqkkjNt+DT9Pagd+A49w774SB2tjMfo1s1dvq25bik3JwZI/7iKonTMC/eyrPoBRaxrqeVcbiAgZhRlqA73k8yzvGdIK0lDyk1fIF8LayBo2RjawNbKFjZGN+iMVSpGWn4ZdEbsQmxGL8T7j0cauTYN31JWHPmpUGUWKItxIuoFzCecQnxUPTwtPdHPqhubWzSHg62YcUklKpOWn4VneMyTlqoz/kv/zi/NBIJiKTOEic4GrqStcZa5wljlDIqj57+ZXTacGozAb2DcaeHM1YO0F6KhNVmZ76hNspL6GFCuVSM4qhL0Zd43Fl1EqlQAAMyMR8ovykZFXBDOjyp37Meqe6ORsLP79LjaMboGC58kNXZwyTO/aGB/sD4W3vQwBLmxda15eXr2fMzWnEBcfpGLHxDb1fm59g8fjoae3LZpKC+Hs7AxAtUQq6n/x4E9GPMOzrALwADhZGMH7f/Hgm9qYQCLSblS/qFiJP8Ke4mjoE7R1s8DXw/xhUYWj1IaAz+ehraslrj1MR4fGDRtO6XRkMraVmmVS3bbkbm2Mnya0wZqTUbj4IBUL+/torRmjZjTE8666JOUmYW3wWuQX56u3mYpNNQx1Lwsv2BjZwMLQAgZ87eqMpcQScwPm4nnBc+yO2I0dd3dgnM84dLDvwCnjXh80qornBc9x8clFXHx8EfnF+Whj1wZjvcfC1dS1Ts7H5/FhbWQNayNr+FmVHzs+szATcVlxiMuMw/G443iU9QiFikLwwYed1E5t7LuausLOyK7KevUq6MQJTn8BdJ0P2HhXnfY1hBn11aSoWIHUnCIUFSthYSyqt+mdtaXEqAcAO1NDPErLg1hgwH4UNSAPnmVjyR93sWFUS1ibiHHnUVZDF6kMfD4Pq4Y2w3s/h2D9yBaw4cDSgIYkK6v+NVp7Mgpze3s0+GirPvGyTqYSIdq6WaCtm4V6m1JJiE/Pw72kLJyJTMaWCzEokCshERnAy1Zl6HvZm2jEjs/Mk+OXa49wOSYVA/0dsG0C9/1NDAtohHWnHjSoUX/3aSYaW0vLhGCsSVsSCfj4/E1v/Hs/BZN33cDC/j7wcdDfURWu0xDPu+piKbHEF298UWfTps0NzTG71WxkFmbi54ifsTtiN8Z6j0VHh46cMO71QaPSEBEeZj3E+YTzCE4KhrHIGJ0bdcaCdgtgZmjW0MUDoOoYam7dHM2tm2tsVygVSMpLQlxmHOKy4nA+4TyScpOghBJiA7FqdF/mCheZC9xM3WAqVoVJ00edOEfcJYAUgFuXhi4JZ2FGvZbkFRUjNUcVFs7KWMRpL/Kurq748MMP8eGHHwJQjV4dOnQIw4YNU393NJcgPj0PzhZGWjly4vF4OHLkCAYPHlyHJX99uP8sG0tfMugBwMGBW1PvSzAxFGLZID/M/+02/m9c6zqPj85l6luj8MeZIAKaO5nV63n1nap04vN5cLWSwtVKqjGVO6ewWD2qf+F+Cp5kqEb/pGIB8ouKMaadM6Z3baw3HSyO5kbIKpAjq0AOmaGwQcrwa/BjjCgnNn1t2lIXD2v4OMiw6OgdtHWzwMQ3XDlhYL1KXH+YjsxiKcofx+QOQr4QQn7d121TsSlmtpyJrKIs7Incg18ifsFor9Ho4tilQeseV383lKZYWYzQ5FCcTziPB88fwM3UDd2cumGc9zgIDRrm2VQTDPgGaGTcCI2MG6Fjo44a+/KL8xGfFY+4rDhcT7qOg1EHkVmUCQCwFFgiOjoaPpY+cDd119lSgtcFZVEuHl34EpHt30XEjTUY5zMOtlLbhi4W52C1qhKICNkFxUjPLYJIwIedTAyRnozMv0xiYiKMjDR7sQUGfNiZGuJJRj6cLV44zlu6dCmOHj2KW7dulcnD3JxNv9YFUUnZ+OLPu/hudEtYGb8IhZiVlQULC4tKjmw4mtgYY1QbZ6z8JxJL3/Jt6OI0GPWpERFhzckorBnevOrEDA1qqpOxWIAAF3ONpSZEhIw8Ocw5OMVeGwY2d8BfYYkY08653s9dWKxATEpOuaPptW1LVsZibApqhV2X4zD9l5tYPsRP43nKqDm/XH2Eaw/TMb01mwVRGplIhunNpyO7KBv77u3Dnsg9GOk1Ej2cejSIcc+l3w158jw8zXmKp7lP8STnCZ7mqP4WKVQDYs2tm2NQk0Foatb0leyEkwgk8LTwhKeFp8Z2IsK1e9eQIcjAX7F/4WHGQyhIAScTJ/hY+sDX0hdupm5aLw151SlWFiMuMw4R6RGITItEfHY8eClRcLb3hLdAjKFNh8JKwvwTlAdnjfoDwfEIbOEOpwbwLK9UEp7nFSEzXw4TQwEcLSQQ1HN8w6KiIohEuvkRaWdnh/z8/DLbjUQCmBgq8SyrsMoQanZ2djopy+vOvaQsfPlXBL4f3RKWpX6A5uTkNFCptCPQzw53n2Zi7sFbaOlsDm87E3jamcCkgUYAG4L61OjorSfo1MRKPZODoT261InH4+mtQQ8AfXxsMe2XkAYx6s9EJqOPT/mjKbrQiMfjYWJHN7Rzt8QH+0KxeKAPvOyYIVpTioqV+OLPu7CVGWLDyBaIiLjb0EXiLCYiE0z1n4og7yDsv7cfU+9NxQjPEejp3BN8Xv39XqzPd1J+cT4ScxLxJOeJhtFeqCgEoDJqHYwd0Mi4EZxMnNDOvh0cpA4wFLzey/Z4PB6MFcZo79oega6BAFSGfkJ2AiLSIvB7zO94mPkQSlLCReaiNvRdZC6vvKEvV8oRkxGDyLRIRKRF4EnOExjwDOBm6gZvS2+M8hoFp6xk8LO2A302NnRxOQ9njXoLiQibL8Tg8fN8OJlL0LmpFQIc6zbGpFyhRFpuEfIKi2EuFcHVSgq+jnoTu3XrBj8/1US2n3/+GUKhENOnT8eyZcvA4/Hg6uqKyZMn48GDBzh69CiGDh2KnTt34r///sNnn32G4OBgWFlZYciQIVi1ahWkUpWX5eTkZEyePBmnT5+GnZ0dli9fXubcpaffP378GPPmzcOJEydQWFiIJh6e+Hb990h4+ABffPGF+hgA2LFjByZOnFhm+n14eDhmz56NK1euwMjICMOGDcO3334LY2OVRhMnTkRGRgY6deqEtWvXoqioCKNGjcL69eshFKqMwE2bNmHdunVISEiAqakpOnfujEOHDunkfnORiKdZWPFPBL4f3apcx1pOTmWnqHKNub09kJhZgKikbFx7mI7dVx4hp7AYIgM+mtoaq9Yi25nAxVL6SsaUri+NcguL8WvwY+x8p229nO9VQx/aUn1hKDSAs4URHjzLRlNbk3o99++3nuCbYeXPNNGlRt72Mnw/uiVm7g3FlrEBMDV6fToadUVKdiHmHwrDqLbO6Our6sRn7ahqpEIpJjebjNFeo/Hr/V8x9dRUvN30bfR26V0vBpkuNVKSEom5iXiY+VBtsD/Neap2Qig2EKORcSO14d7Wri3sje1r5RX+daG0TjweD84yZzjLnBHopjL0laREQnYC7qbexeEHhxGXFQcCwdnEGb5WvvCx9IGrzLVeO410SaGiENHPoxGRHoGItAgk5SZBwBegiVkTeFt4Y4LvBDQybqQ5i6O4CDgyC3h7R8MVXI/grFHf29cOwzqoetwfpeXi4oNUrDt9H/1cDGCcXQgLngASkYFOjO4CuQKpOYVQKAmWUhFsTXQT8qg0u3btwuTJk3H9+nUEBwdj6tSpcHZ2xpQpUwAAa9asweLFi7FkyRIAQExMDAIDA7F8+XJs374dKSkpmDlzJmbOnIkdO1QVfOLEiXj69CnOnTsHoVCIDz74AMnJZb2oKxQKAKpe3a5du6JRo0b4448/YGdnh+CQEGTkFWLQ0Lfx0Z07OH78OE6fPg0AMDU1LZNXbm4u+vbtiw4dOuDGjRtITk7Gu+++i5kzZ2Lnzp3qdOfOnYO9vT3OnTuH6OhojBw5Ei1atMCUKVMQHByMDz74AD///DPeeOMNpKen4+LFizq931zi7tNMrPrnHn4Y3arCUb/U1NRy7zeX4PF4cDCTwMFMgu5eL2KCFsgViE7OQWRiFvZci8ejtFwolAQbE0NVOLH/Gfv6HnGhvjTaeC4aU7u4v9b+C2qDPrSl+mREayf8GvIYn79Zfx6DEzPzYSQSVGhg61ojS2MxPnvTC/N/C8OmoIBXslOxrrjzJBMr/o7EF4N84fFSx49etKPnccCxTwCRsSpOtdT6f39tVH9LttXxum0joREm+E7ACM8ROHT/EN479R6GNB2CQNfAOjXua6KRXClHQnYCYjNiEZup+mQXZYMHHuyl9nA1dYWTiRNa2bSCg7FDnTkhfJ3QRic+jw8XmQtcZC540/1NACpD/1HWI0SkReDQ/UOIz4pXG/rWRtYwFhpDJpLBWGSs8b+JyASGBoZ1vsyBiJBfnI8ceY7qU6T6ZMuzVX+LshGbGYuU/BSI+CI0NW8KH0sfvOf/HmyNbKsu33/fAgETAWnDRnDRFzhr1L+Mi6UULpZSFBTYIjY2FsZiA+QUFiMluxA8nsqJ0Q9hXyO1IBk8aFeBCQSFklCkUIIHHkQCPgyqUfltjGywqMOial2Hk5MT1q1bBx6PB09PT4SHh2PdunVqo75Hjx746KOP1OnfffddBAUFqR3eNW3aFN999x26du2KzZs3Iz4+HseOHcP169fRpo0q3NVPP/0Eb++yP9xKYrPu3bsXKSkpuHHjhnodVpMmTSBXKJGQngcjqRQCgaDS6fZ79+5FQUEBdu/erZ4x8MMPP2DgwIH4+uuvYWurmm5pbm6OH374AQYGBvDy8kL//v1x5swZTJkyBfHx8ZBKpRgwYABMTEzg4uKCli1bVut+6gt3nmTi6+P38MOYlpUateUtkdAXDIUG8GtkCr9GL15aRISU7EJEJmUjLCEDB24kICOvCAIDPprYGMPLzgQ+9jK4WUm1ctbIBepDo7jUXMSl5WJ+oFedn+tVRZ/bUl3g6yDD18fvQa5QQlhPbe3wzScY1sqxwv11oZG/oxl6etti/en7+KiPZ9UHMPD7rSf463YiNo9tVeb9pBftyNwVGL0fKMoBcpJVn9xkIOMR8CT4f99TAKXixTFCSeUdAIKaL3mSCCQY5zMOwz2G4/CDw3jv1Ht4q8lbeNPtzTpxjlaZRvnF+YjLjFMb7g8zH6JQUQgDngGcTZzhbuaOtnZtMdJzpNpLO6NuqGlb4vP4cDN1g5upG/q79wegMvTjs+KRXpCO7KJsZMuzkZCdoDais+XZyC7KRmFxYZn8BHyB2ug3EZrARGSi/m4sNEahohC58lxkF2WrjXT1//IcEFEZO8tQYKjKQ2gCqVCqzs/c0BzOMmf0d+8PayPr6l/8s7tAyj2g6yc1unevI3ph1L8Mj8eDRCSAuaFqjY5CScgtLMZU33koLFZCyOfB2FAAY7GgXENBSYSsfDnSc4tgJBLA0lhUbz9y2rdvr9Er1aFDB6xdu1Y9it66tWYc37CwMNy+fRt79uxRbyMiKJVKPHz4EPfv34dAIEBAQIB6v5eXF8zMzMqcu2TK+61bt9CyZcsyjlWEBnzYygyRnV9c5XVERkaiefPmaoMeADp27AilUomoqCi1Ue/r6wsDgxc91Pb29ggPDwcA9O7dGy4uLnB3d0dgYCACAwMxZMiQMg799J0Sg/770ZUb9ADg4uJST6WqH3g8HmxkhrCRGaKrx4sHelGxEjEpObiXlIVDIY8Rk5ILicgAn/XzgoMZN6fxyRVKbL0Yi4tRmeid8RADmzvU2Vr31SeiML8vM+hrw6vWlmoLj8dDd08bnLuXjD6+de8fhYhwOSYV07s2rjBNXWk0orUTFh29g5N3k+rlWvUVhZLwzYl7UCoJm4Nalft7SW/aEY8HiE1UH8uK65yaotwXxn5OMpD9FEi89WKbQg7w+EDH2YBzuxoVyVBgiDHeY/C2x9s4Gn0U005NQzv7dpAKpRAZiCA2EENoIISIL4LIQPTib6n/hXzhi/R8YZmRTRcXF2QVZSE2Q2W0x2bG4lHWIyhIAbGBGK4yV7ibuaOnc0+4ylxf31F3IqAw+4XmucmadSA3BVAWA8WFQMcPgMY9dHp6XbYlPo8PV1NXuJq6VvtYuUKuMYpe0gGQVZiFJ9lPIDYQQyqSwtbIFo1FjWEsNFYb/lKBtP7W+CuKgZMLgcGbVe2boRV6Z9SXxoDPg0wihEyiMlqLipXIKSzG08wCKJQEQyEfJmIBDIUGeJ4nR3aBHDKJkJNrfl82kgHVVPn33nsPH3zwQZm0zs7OuH//vtZ5FxerjHWJpGKjSSoWQCjgoVhJWudbGSUdCSXweDwolUoAgImJCW7evInz58/j5MmTWLx4MZYuXYobN26U2ymhj4Q/zsQ3J1RT7rVZ45mUlAQTk/pd89oQiAR8eNvL4G0vA/43OSM6OQcLjoSjc1NrTHjDlVNtMzT+OdacjMLwACcs7GqFJwoJlv0VgaJiBd5sZo8+PnaQiHTzortwPwXOlkZwtZJWnZhRIa9LW6oOg1s2wsKj4fVi6F5/mI7WLhaVhv6rS40WDfDBlN3BaGxjjMbWdeuLRx/JzJdj/qEw9PW1w9BKZlO8su1IJAUs3FSfishNBf5dDVzbDHT7HLD2qNmpDEQY4TkCQ5oMQVhKGAoVhShSFKFIWYQiRRHy5HnqbXKlXLXvpf0v/y9XyoFSP8+yc7NhY2aDxqaN4W7mjsFNBsPZxFmvwsTVGCKgILOUoZ7yv7/PgNw0VVzzEkTGgLEtYGytmp1h7go4tlHN0DCyAgQiVYfPiQVAzDmgxyLVNh3AlbYkNBDCwsACFobciJhQIVc3An7DABPWMVsd9N6oL41IwIeFQAQLqQhEhAK5AtmFqrB0pkYiuFlJGyyUxrVr1zS+X716FU2bNtUYzX6ZVq1aISIiAk2aNCl3v5eXF4qLixESEqKefh8VFYWMjIwyaUum3/v7+2Pbtm1IT08vNwyKqVSC4uJiZBfIK/Rq7u3tjZ07dyI3N1fdEXHp0iXw+Xx4emo/5VEgEKBXr17o1asXlixZAjMzM5w9exZDhw7VOg+uEpaQgTUno/DDmFYwlWj3ci0sLDtV6nWhiY0xfprQBgeDEzBxx3V82s8Lvg4NOx0wu0COtSfvI79IofaFcOfOHfTxs0MfXztk5stxLDwRM/fehJmRCINbOuCNxlY17pCQK5T48UIM/m9866oTMyrldW5LFWEhFcGAz0dydgFsTOrWG/WvIY8xu2fTStPUpUYiAR/fvO2POQdu4f/Gt4ax+JX7qVNjopOzsejoXXzazwvNncwqTftatyOpFdDvayA9Fjj/FSA0Uk0DltnXKDuhgRCt7XT4bE8KB65sQs7TRzDutKTyDopXkTuHgetbAVPHl5ZO2ACW7oBz+xeGukE1275ICgxcD0T8DuwdAfRfq93sjyp4rdtSdUmNBuKvAaP2VJ2WocEr/aYrmaovEXHjMuPj4zF37ly89957uHnzJr7//nusXbu2wvSffPIJ2rdvj5kzZ+Ldd9+FVCpFREQETp06hR9++AGenp4IDAzEe++9h82bN0MgEODDDz8sdzS+ZNR89OjRWLlyJQYPHoxVq1bB3t4eoaGhcHBwQIcOHeDm5obH8Y9w4fINtPJpDEtzM4jFmtOMg4KCsGTJEkyYMAFLly5FSkoKZs2ahXHjxqmn3lfFX3/9hdjYWHTp0gXm5ub4559/oFQqq9UpwFVuJWTg21P3sTGoFWTVCPfm7u5eh6XiPnw+D6PaOqOHtw1W/XMPNiZizO7VFEYN0H5P3E3CzktxmNWjCd5o8iIe6ssamUqEGNXWGaPaOuNJRj6Ohj7Bjxdi4W1vgsEtG8HHXlatDsRdl+PwdoAjM0B0wOvelipiaKtGOHLzCd6rZFp8bckukCMjr6jKcLR1rZGtzBBzenvgs8Ph+G5Ui1cyLnZ1ORP5DLuvPMKGUS1gI6u6Y4e1IwAW7sDQ/wOehgJ/zwVsvFXT8g0boNOZCIg+AwT/BMgcgC4fw0CuAP78AOizHLAvP9LEK0VhDnD8U5Xvgwl/1J0DRJ9BQKMA4K85gM9goMWYWk0DZ21JS5RK4MRnwJtr2LT7GqAf3qleEcaPH4/8/Hy0bdsWM2bMwOzZszF16tQK0/v7++PChQu4f/8+OnfujJYtW2Lx4sVwcHBQp9mxYwccHBzQtWtXDB06FFOnToWNjU2ZvORyOQBAJBLh5MmTsLGxwZtvvolmzZrhq6++Us8WGDZsGAIDAzFuWH80srfDnj17y+RlZGSEEydOID09HW3atMHbb7+Nnj174ocfftD6XpiZmeHw4cPo0aMHvL29sWXLFuzbtw++vr5a58FFQuOfY92p+/hhTMtqGfSAqtOHAdiYGGLdyBZo39gSk3cG48L9lHo7d1JmAWbuvYk7TzKx4502GgY9ULFGjcwkmNG9CX6e3BaDWjTC4ZtPMH77dWw+H4OnGVU7yEnJLsTFB6kY3KKRTq7jdYe1pfLp0tQaFx+kqmdu1QV/307EAH+HKtPVh0ZtXC3QxtUcmy/E1Pm5uAwRYeO5aJyOfIb/Gx+glUEPsHakgUNLYNRewKUjcHA8cGWTav11fVBcCITuAXYPUnUuvPWDegT5UYYSGL4LOLMMiL1QP+VpKJ7eAvaNApoNB3otqfOIBjB1VDlhzHoKHHkPyM+ocVasLWlJ8E9Ak96AuZ748+AaVE0uXLhAAwYMIHt7ewJAR44c0dg/YcIEgmrVj/rTt29frfPPzMwkAJSZmVlmX35+PkVERFB+fn51i93gdO3alWbPnt1g58/Ly6v2MVn5RRSflktKpbIOSlT31Hd9CY5Lp/E/XaOs/KIaHR8eHq7jEuk/uYVyWv7XXZqzP5RSsgvq7DzFCiXtuvyQxv90jaKSsipMVx2N5MUKuhCVTHMOhNKkHdfpwPV4yqygbnz6WxiFJTyvbrEZFcDaUsV8czySQh6l11n+E7dfo/yi4irT1ZdGSqWS5v16iy5EJdfL+bhGbqGcZu+7STsvPaz2u5y1owpQKIjCDhDt6K/6q1DUzXly04gurCbaOZAoZBdRUdnfMmqNCnOJDowjCv+tbsrSkCgURJe+Izo4QXVPGoL4ayq9H12t0eGsLWnB80dEPw+ru/ZUCZXZnvpEtUfqc3Nz0bx5c2zcuLHCNIGBgUhMTFR/9u3bV7MeB4bOKD2FXhtMDIUQC/lIyy2qgxK9WoQ8Ssf3Zx9gY1CrCn0RVEVFvhNeZ4xEAizo74NJndww58AtHLyRoPNRxntJWZi08wb4PB52TGyjEae5NNXRSGDARxcPa3w7ogW+G90SIgEfHx8Mwwf7QnE64hmKilVOI28/zgCgCsfF0A2sLVXM8AAn/Br8uE7yjk7OgYOZBIbCqh1H1pdGPB4Pywb5YevFWCSk59XLOblCQnoepu4Owcg2zpjwhmu1lyCwdlQBfD7gPwIY+5vKod4vQ1TT4nVFeizwzzzg6PuAnT8w7ijQajwgLDvDQq2RyAgYth14eAG49qPuytLQZD8DDoxV+TR4ewdg1EAO3pzaqtZ4B28HLnyjGSJRC1hbqgIi4PhnQOAqVfti1Ihq37l+/fph+fLlGDJkSIVpxGIx7Ozs1B9zc/MK0xYWFiIrK0vjw9A9NXXSYW0sRl6hAjmFVYe6e10JjkvHD2ej8cOYVrVaDx0bG6vDUr1a+DUyxY6JbZBVIMe7u4IRk5JT6zwL5Ap8c/weNp2LwTdv+2Nse5dKvXUDNddIKhZgcMtG+L/xrbFwgDcepefh3d3BWPz7HXxzPIrF1NYxrC1VjKuVFM+yCpBXpPtn+q8hCRjR2kmrtPWpkaHQAKuGNsNnh8ORX1S9H+P6ypWYNHx6+DZWDW2GDo0ta5QHa0dVIBADHd4HRuwGHl0C9o1WTY+vKQnXgUOTgPNfAy2CgDH7AY8+lRo5GhoZCIAB61Xe4E9/oTKU9Jn7J4DDU4Cei4A2kxt+jbWhKTBki2pa/r5RQEaC1oeytlQFYfsAx9aAVeUOVhmVUyfdIefPn4eNjQ08PT0xffp0pKWlVZh21apVMDU1VX+cnLT7QaBvnD9/HuvXr2/oYlQbHo+HRuYSJGcVQP6/kUXGC64/TMfGc7U36AGow/0xykdgwMe7nd3xxSBfrD4ehe/OPFCPdleXS9GpeGfHDbRyNsd3o1vCVss1prrQyMbEEJM7uWH3pLYY194Fc/t4wMq4bmLev66wtlQ5/fzscCw8Sad5yhVKRDzNgr+jdg7E6lsjR3MjTOvaGAuP3qlTnwINDRFh95U47Lsej63jW1fpsLAyWDvSEkNToOdi1Tr3kJ3A4alA+kPtjlUqgIg/gF+GqTyu9/oCGPoj4NBCu8NLa8TjAT0Wqhzp/TELUMirdSmcQF4AHPtUNfthzEGVc0KuwOOpnOYFfqW6vxG/a3UYa0uVkP0MuH0Q6DCroUui9/CoFm83Ho+HI0eOYPDgwept+/fvh5GREdzc3BATE4PPP/8cxsbGuHLlSrmh2woLCzVGkbOysuDk5ITMzEzIZDKNtAUFBXj48CHc3NxgaFi3IXleNZRKJfi1mNJSKFfgaWYBXCyNwG/o3lItqev6ci02DT/+G4vvR7eEVAcey+VyuTpKAaNyiAh/hydi77V4zOntgTau2k3JS88twqp/ImFsKMBHfTyr3RHDNNIPmE6Vk1tYjA/2heKniW10lufpiGeIS8vFu5218/LcUBr9eCEGIgEf73RsmBBg959lIzo5B1bGYlgZi2BlIoaJWKAT7/yFxQos/SMCjuYSvN+tca3zZO2ohqREAedWqmJsd5mnCo9XmqJc4NZelVHoEaiaXm8oK5uuCirV6O5R4M4hYMiPqlBt+kBKFHBsPtBuGuDZr6FLUznFRcC55UBBJtB3ZaX3mJNtSakA8tKAnGQgNxnIf65yUleDelgrDk0COs0B7JrV73lfIisrC6ampuXanvqEzmMnjRo1Sv1/s2bN4O/vj8aNG+P8+fPo2bNnmfRisbja671f5V72uqKwsLDcUHfaIhYawFIqQmJGPhqZ17znvz6py3pyNTYNW/+NxQ9jWuos5FpUVBT8/Px0kterDo/HwwB/B3RuYo1vTtzD0dAnmB/oBVNJ+S9NIsLhm09wJPQJ5vX1rDI+c0UwjfQDplPlSMUCWJuIEZeaC1cr3fzYPxL6BMsGaR+9pKE0mtrFHR8euIVrsWlo516zaek1oUCuwIYzD/DkeT46N7XCo7Q8pOYUIjWnELkvLW/j8XiwlIo0jH7V/2JYm4ghMyy/AyA5uwDzD93G2HYu6OWjXWjZqmDtqIZYewIjdgHxV4Ej0wCndqpp+iKpalTy+v8BT0KAlmOBcUdq5cW9Uo18BwNGlsCBccCwbQ23Hl0biFSzHB6cBAZvAWT2DV2iqhGIgN7LgJhzqun4fVYA9v7lJq23tqQoBvJSXxjqOSn/+5usWpZRkAmAB4AAHl9VJ6Q2gLENIJQA+8eoOlS8B9R9WQFVx5NF4wY16F8l6jwgsru7O6ysrBAdHV2uUV8dSnq58vLyamWgMmqGTCJEvlyB9NxCWEi5P104NzcXeUXF2HElAUrobnZBYbESEU8z8cOYVpCIqnYIxag7TI2EWDGkGW7EpWP6LyEIaueCN5vZafzojUvNxfK/I9HG1Rw73mkDoQFzwsJgDG/tiEMhj/Fx39r7c0jJLgSPB1jqwTISHo+HlUOaYcruYKy1NIK9ad3/lrj4IAWbzsVgcic3fBLoVWnaYoUS6XlFSM0uQkpOIVKzCxGWkPG/DoAiZBe8mE7N4/FgbiSEpbEYt+Iz8OVgXzSxqdjRJ6OecW4PBP0KRP2jMvqkNoCiEGj7nmqKfH3MenTrDEjMgF8nAIM2AmbOdX/O6pKXDvz9kWrJwcg9+ucorXF3lVH691zAqT3QfnrdaEukMs6f3QGSI4CsRJXBXpj9Ig3PAJBavjDUpdZAo4AX3w1NKy+b/0jg3zWqGR59V6qWcdQVeemqEHZBh+ruHK8ZOp9+X5rHjx/D2dkZR48exVtvvVVlnlVNgUhMTERGRgZsbGxgZGSkkylrrwO1nX5fAhHhaUY+LKQiSHQ0Qq1riAhZ2TmITUjEkzwe3F0cdX4OH3uZVh6eqwMnp2fpEYXFCmw5H4t7SVlYOMAHNiZi/N+/sQhLyMCiAT61WltaAtNIP2A6VQ0RYdxP17FrUlsYVOEgsiq2/hsLd2spenprP0Lc0Bo9TM3Fkj/uYuv4AIgFddM5m5ZTiFXH7kFmKMRHfTx0skzrZRRKwvO8IqTmFKKRmaTGkVcqoqE1eqVQFAPZiYCZbv1Gaa3R80fAHzNVa8FttZ9RU+fE/Qec/0o14t2oVUOXpnYQATe2AbHngQHrVEb0/6h2W5IXAKlRwLO7qk9aDEAKVZ62fio/AzJH1Xexie47EZ5FAKcWqZaGtJ4E8OvgGXn0fVXejq11n3c1eVWm31fbqM/JyUF0dDQAoGXLlvj222/RvXt3WFhYwMLCAl988QWGDRsGOzs7xMTEYP78+cjOzkZ4eLhW0+yrurFEhKSkJGRkZFSn2K89RUVFEIlEOslLSYS0nCKYSoQQCbjVo0qkWi+aU1gMa0tz+DZx0ZuOnzt37rCpjjogJiUHK/6ORE5hMYLaOeOt5g46qwNMI/2A6aQdWy7EwMvOBN08bapOXAElnQM732kDQTVmwXBBozORz3D2XjJWDNHt1E8iwm83n/xvWZCn3oar5IJGjMqplka5aSpv8p0/Alw71m3BqkIhBy58reroCPxKZZi+Kjy7qwrP1vEDoEkvAJXoRARkPf2f8X5H9bcwCzAQAdZeqg4YWz/AsnHdGNaVoVQCIduBe/8Afb7UbWfQ/ZOq8It9V+guz1rwqhj11e42Dg4ORvfu3dXf586dCwCYMGECNm/ejNu3b2PXrl3IyMiAg4MD+vTpgy+//LJGcdLLg8fjwd7eHjY2NpDL9dCrZwNx//59uLnpzjGQRW4Rfrkah4z8Akx4wxXOFg3vhCUmOQf/dzEWnZtaYVCAM4RCbs4kYNQtja2N8dOE1igsVup8NgWD8SoxtGUjrPgnslZGfdjjTPg1Mq2WQc8VenrbIvxJJvZfj8eotrqZlvwwNRcr/o5AWzeLand0MBh1itQSGPkzcOQ9lYM0n6pnz9YJz+NU0+2bj1YtQ3jVsPUFxhwATi5UrbfvuVi1vSgPSIl8Mfr+PE5l1MvsVYa7c3vVyLXErCFL/wI+H2jzLuDZHzi5ADBzAbrOV629rw0FWcDl71SRDRg6pVbT7+uCV6W3hGvU1TS6uNRcrD99H1KxALN7NoWNlqHBdEl+kcoBUVJmPj5/07tByqAL2FRH7sM00g+YTtoz/ZcQrBzSDObSms3k+vxIOCZ3ckNja+NqHccVjZRKwsx9NzGlsztaOpvXOJ+iYiW2XtTtcp+GhisaMSqmRhop5MBfHwIOLVVGW31y+1fg9n5V+D9z1/o9d0Nw72/g8vdQiozBFxkB1t6AnZ/K8Ddz1S//Aff+Aa5uArp8DLh3q3k+f80FfIeo/D1whFfF9tSj2sSoDVFRUXWSr6uVFOtHtcSI1k747HA41p6M0nDkU9f8ez8Fk3beQFs3c6wf1VJvDXqg7jRi6A6mkX7AdNKeQS0a4fdbT2p0bH6RAokZ+dU26AHuaMTn87BqqD++OR6FlOzCqg8oh5BHz/HOzutwNJfgx3EBr4RBD3BHI0bF1EgjAyHw1g9A5mNV6L36GNsrzAaOzgBS7wOjD7weBj0AePUH3jmGiBZLgRG7ge6fAd4DAQt3/TLoAcDrTWD0PiDquErL3LTq5/HwIgDilEH/KqFnNYpRU3ThJK8ymjuZYduE1ghwMcf0X25ix6WHKCpW1tn50nIK8dHBMFy4n4JtE1qjh5duQvg0JHWtEaP2MI30A6aT9vTwssGZe8k1Ovb43UT086tZ6CkuaWQqEeKLQb745LfbkCu0f29lFcix6OgdHApJwMYxrTCoRSO98eGiDVzSiFE+NdaIxwN6LQUk5sBfc1SO/HRJXjrw8F/g6maVAbhvNNBiDNBjAWDwmi2N5PFenbYkNgH6faVaJvDbJCBsv/adQkV5Kj8Kvb6o2zK+xrDp968JBQUFMDSsn1FshZLw+60n+DX4MUa1dcJAfwfwa+lduQQiwqGQx/j91lN8EuiFZo6mOsmXC9SnRoyawTTSD5hO1WP5XxEY3LIR/BpV73n67q4bWD+qJYxr4NWdixr9fTsRN+OfY9EAn0rTERFO3E3CrsuPMLtXU7Svx3j39QkXNWJoohONwg8BkX8CQ7ZUf720Qg6kPvjfOvFwIDUaUBar4p/b+r5w9GZcc78drwKvZFtSyFXT8eOvAn2Wq5z5VcaJBYBbV8CjT/2Urxq8KrbnK9J1xKiKkogF9YEBn4ehrRyx4502SMkuxIQd1/Hfg9Ra5xubkoN3dwUjI0+One+0eaUMeqB+NWLUDKaRfsB0qh7DWzvh1+CEah0Tn5YHC6moRgY9wE2N+vvbQ2DAq3Q5wtOMfMzcG4qIxGzseKfNK2vQA9zUiKGJTjRq9jbQ+h3gwDjVCHtF5CQDMWeBS98Bh98D9owADk4Abh9Q7fcfBYzYBQQdVHUQvDELaNzjtTfogVe0LRkIgY6zVfHsTy0GLq5VGfrl8ThEVbc4aNC/Srxmc2BeXwSC+pfaUGiAdzu7Y3hrJ2y5EINdV+Iwu2fTao8GFRUr8X//xiD8SSaWvuX7yqxXLE1DaMSoHkwj/YDpVD087UwQl5aHArlC64gRh0ISMLx1zWNuc1WjeX08Me2Xm2hiYwxfhxfvKoWSsPtKHC7cT8GCN73R1PYVCsFVAVzViPECnWnk3k01Ff/XicDA9UBhzosQa2kxACkBY2vVqLtDC6BFkMqbPkMrXum2ZOEGjPxFNePjl2FAj0WAU5sX+4sLgTNLgeG7GqyIrwts+v1rQl5eHoyMGtYYTszMx4bTD1CkUGJOLw+tjPOQR+n49tR9jGrjjAH+9q/UesXScEEjRuUwjfQDplP12XPtEWSGQgxs7lBlWoWSMH77NfwyuV2Nn8lc1ig9twgz9tzE5rGtYGYkQsTTLKw6Fok3m9ljZGsnnS0n4zpc1oihQucapT8Ezq1QhS+z9QXsmv3PqRsLD1sbXpu2lJcOnF4CCAxVxr2hTOWM0cZb5fGeo7wqticz6l8T7ty5Az8/v4YuBgDg/rNsbDj9ALYyQ8zs0QQW5YRSyiqQY/XxKBQrCZ8GesHU6NUPq8MljRjlwzTSD5hO1SerQI6PD4bh/8a3rjLtv/dTEP4kEzO6N6nx+biu0Z0nmfjuzAO4WUvxLLNAr8Ol1hSua8RgGukLr51ODy8C/34DeAQCj4OBt7ernDNylFfF9nyF54MwXkYsFjd0EdR42JpgY1ArXH+YjjkHbqGtmwUmdXSDRGQAIsLxO0n4+eojzO7ZFO1e4fWKpeGSRozyYRrpB0yn6iMzFMLYUICnGflwMKvcWdbhm4/xaT/vWp2P6xr5NTLF6LbOINArEV2lJnBdIwbTSF947XRy6ww4tgGu/wgEruK0Qf8qwYz61wQ7O7uGLkIZ2rpZoI1rG5y4+wyTd91AX187XH+Yjqa2xtjxThuIBa/XdC8uasTQhGmkHzCdasbbrRzxW8hjzOrZtMI0GXlFKJArYWdau1FrfdCou9fr7eBLHzR63WEa6QevpU5CQ5UjPUa9wbzfvyY8evSooYtQLjweD4F+dtg9qS1kEgHm9G6KD3t5vHYGPcBdjRgvYBrpB0ynmtHe3RJXH6ZBqax4Vd4fYU8xqEXV6+6rgmnEfZhG3IdppB8wnRj1ATPqXxMkkmrGHq1nBAZ8DGnpiCY2r75H4YrgukYMppG+wHSqGXw+D21dLXHtYcVhrU5HJqOnd+2nozONuA/TiPswjfQDphOjPmBG/WuClZVVQxeBUQVMI+7DNNIPmE41Z1hAIxwKeVzuvrtPM9HE2hgiQe1/OjCNuA/TiPswjfQDphOjPmBG/WtCQkJCQxeBUQVMI+7DNNIPmE41x9HcCFkFcmQVyMvs+zX4MUa0cdTJeZhG3IdpxH2YRvoB04lRHzCj/jXB2Ni4oYvAqAKmEfdhGukHTKfaMbC5A/4KS9TYVlisQGxqLrzsdBPuh2nEfZhG3IdppB8wnRj1ATPqXxP0Oe7i6wLTiPswjfQDplPt6ONjixN3kzS2nY5IRm9v3XmDZxpxH6YR92Ea6QdMJ0Z9wIz614SnT582dBEYVcA04j5MI/2A6VQ7DIUGcLYwwoNn2eptf4Q9wVvNG+nsHEwj7sM04j5MI/2A6cSoD5hR/5rAegm5D9OI+zCN9AOmU+0Z0doJv/7PYV5iZj6MRAKYGgl1lj/TiPswjbgP00g/YDox6oM6M+o3btwIV1dXGBoaol27drh+/XpdnYqhBUZGRg1dBEYVMI24D9NIP2A61R6/RjJEJmZBrlDi8M0nGNZKNw7ySmAacR+mEfdhGukHTCdGfVAnRv2BAwcwd+5cLFmyBDdv3kTz5s3Rt29fJCcn18XpGFqQlJRUdSJGg8I04j5MI/2A6VR7eDweunva4Oy9ZFyOScUbjS11mj/TiPswjbgP00g/YDox6oM6Meq//fZbTJkyBe+88w58fHywZcsWGBkZYfv27XVxOoYWmJubN3QRGFXANOI+TCP9gOmkGwa3bISvj99DaxcL8Pk8nebNNOI+TCPuwzTSD5hOjPpA50Z9UVERQkJC0KtXrxcn4fPRq1cvXLlypUz6wsJCZGVlaXwYukco1N1aSEbdwDTiPkwj/YDppBsspCJ0aWqNtwN0O/UeYBrpA0wj7sM00g+YToz6QOdGfWpqKhQKBWxtbTW229raljv9ZNWqVTA1NVV/nJycdF0kBsCWPugBTCPuwzTSD5hOumPpW75wstD9elCmEfdhGnEfppF+wHRi1AcN7v3+s88+Q2ZmpvqTkJDQ0EV6JbG01O16SIbuYRpxH6aRfsB04j5MI+7DNOI+TCP9gOnEqA8Eus7QysoKBgYGePbsmcb2Z8+ewc7Orkx6sVgMsVis62IwGAwGg8FgMBgMBoPxyqNzo14kEiEgIABnzpzB4MGDAQBKpRJnzpzBzJkzqzyeiACAra3XMY8ePYJUKm3oYjAqgWnEfZhG+gHTifswjbgP04j7MI30A6YTtymxOUtsUH1F50Y9AMydOxcTJkxA69at0bZtW6xfvx65ubl45513qjw2OzsbANjaegaDwWAwGAwGg8Fg1DlpaWkwNTVt6GLUmDox6keOHImUlBQsXrwYSUlJaNGiBY4fP17GeV55ODg4ICEhASYmJuDxdBtC53UlKysLTk5OSEhIgEwma+jiMMqBacR9mEb6AdOJ+zCNuA/TiPswjfQDphP3yczMhLOzMywsLBq6KLWiTox6AJg5c6ZW0+1Lw+fz4eio+/A5DEAmk7EHCsdhGnEfppF+wHTiPkwj7sM04j5MI/2A6cR9+PwG9x9fK/S79AwGg8FgMBgMBoPBYLzGMKOewWAwGAwGg8FgMBgMPYUZ9a8BYrEYS5YsYaEDOQzTiPswjfQDphP3YRpxH6YR92Ea6QdMJ+7zqmjEI333389gMBgMBoPBYDAYDMZrChupZzAYDAaDwWAwGAwGQ09hRj2DwWAwGAwGg8FgMBh6CjPqGQwGg8FgMBgMBoPB0FOYUc9gMBgMBoPBYDAYDIaewox6BoPBYDAYDAaDwWAw9BRm1DMYDAaDwWAwGAwGg6GnMKOewWAwGAwGg8FgMBgMPYUZ9QwGg8FgMBgMBoPBYOgpzKhnMBgMBoPBYDAYDAZDT2FGPYPBYDAYDAaDwWAwGHoKM+oZDAaDwWAwGAwGg8HQU5hRz2AwGAwGg8FgMBgMhp7CjHoGg8FgMBgMBoPBYDD0FGbUMxgMBoPBYDAYDAaDoacwo57BGbp164YPP/ywoYtRhp07d8LMzKzSNEuXLkWLFi1qfA4ej4ejR4/W+HiGflHb+qIrtGlzrq6uWL9+fY3y16btMPSDiRMnYvDgwZWmqc0z/Pz58+DxeMjIyKjR8YyGR5tnRW3edVx5br7OaKOBNs+KioiLiwOPx8OtW7dqdDyD8TrDjHoGZzh8+DC+/PJL9ffaGBO6ZOTIkbh//35DFwM8Hg9xcXEAXrz4Sn/Gjh2rccyuXbvQpk0bGBkZwcTEBF27dsVff/1VJm+FQoF169ahWbNmMDQ0hLm5Ofr164dLly5ppNu5c6f6XAYGBjA3N0e7du2wbNkyZGZmaqRNSUnB9OnT4ezsDLFYDDs7O/Tt27dMnhXx3nvvoXHjxpBIJLC2tsagQYNw7969atwxVXn9/f1haGgIGxsbzJgxQ2P/wYMH0aJFCxgZGcHFxQWrV6+uMK9Lly5BIBCU+UEzceJELF26tFrlqgtqYhSVbnMNwc6dO9GtWzf196VLl5Zbt0+fPq1Ok56ejg8//BAuLi4QiURwcHDApEmTEB8fXyb/hIQETJo0CQ4ODhCJRHBxccHs2bORlpamka5bt27qc4nFYjRq1AgDBw7E4cOHy+R54cIF9OjRAxYWFjAyMkLTpk0xYcIEFBUVVXm9UVFR6N69O2xtbWFoaAh3d3csXLgQcrlc4x5MnDhRi7tXM2ryw3nDhg3YuXNnnZVJG86fPw9XV1f195efRy9/tm3bpk6Tn5+PJUuWwMPDA2KxGFZWVhg+fDju3r1bJn9t69XEiRPV5xIKhbC1tUXv3r2xfft2KJVKjbRhYWF46623YGNjA0NDQ7i6umLkyJFITk4G8EKLmsKV9yQA3LhxA1OnTm3QMrzcdsqrGy9/li5din/++QcikQg3b97UyGft2rWwsrJCUlJSlefcvHkz/P39IZPJIJPJ0KFDBxw7dkwjjaurK86fP1+ja6qpkVwXnSAff/wxzpw5o9M8q8vLbebltljex9XVFbm5uWjcuDHmzp1bJh+ZTIatW7cCKPt8YTD0DWbUMziDhYUFTExMGroYZZBIJLCxsWnoYpTL6dOnkZiYqP5s3LhRve/jjz/Ge++9h5EjR+L27du4fv06OnXqhEGDBuGHH35QpyMijBo1CsuWLcPs2bMRGRmJ8+fPw8nJCd26dSszqiKTyZCYmIjHjx/j8uXLmDp1Knbv3o0WLVrg6dOn6nTDhg1DaGgodu3ahfv37+OPP/5At27dyhhTFREQEIAdO3YgMjISJ06cABGhT58+UCgUWh3/7bffYsGCBfj0009x9+5dnD59Gn379lXvP3bsGIKCgjBt2jTcuXMHmzZtwrp16zTuTQkZGRkYP348evbsqdW59QWutjlfX1+Nep2YmIguXboAUBle7du3x+nTp7FlyxZER0dj//79iI6ORps2bRAbG6vOJzY2Fq1bt8aDkl1tXQABAABJREFUBw+wb98+REdHY8uWLThz5gw6dOiA9PR0jfNOmTIFiYmJiImJwW+//QYfHx+MGjVKw1CJiIhAYGAgWrdujX///Rfh4eH4/vvvIRKJtKqbQqEQ48ePx8mTJxEVFYX169dj69atWLJkiY7uXt1gamrKyVkXJc+jlz9BQUEAgMLCQvTq1Qvbt2/H8uXLcf/+ffzzzz8oLi5Gu3btcPXqVXU+1alXABAYGIjExETExcXh2LFj6N69O2bPno0BAwaguLgYgKpjs2fPnrCwsMCJEycQGRmJHTt2wMHBAbm5ufV3k7RAmw6pqrC2toaRkZEOSqMbXq4T69evL1NXPv74Y7z55psYP348xo8fj8LCQgCqNr5w4UJs3LgRdnZ2VZ7H0dERX331FUJCQhAcHIwePXpg0KBB5XYc6TvGxsawtLRs6GKo2bBhg4amALBjxw719xs3bkAqlWLHjh34/vvvcfHiRQCq3z3vvPMOOnbsiClTpjTkJTAYuoMYDI7QtWtXmj17tvp/ABqfEi5evEidOnUiQ0NDcnR0pFmzZlFOTo56v4uLC3355Zc0btw4kkql5OzsTL///jslJyfTW2+9RVKplJo1a0Y3btzQqlw7duwgU1NTjW2rVq0iGxsbMjY2pkmTJtEnn3xCzZs3r/G1A6BNmzZRYGAgGRoakpubG/36669l0jx8+JCIiB4+fEgAKDQ0tNz8rly5QgDou+++K7Nv7ty5JBQKKT4+noiI9u/fTwDojz/+KJN26NChZGlpqb6/5d0LIqJnz56RlZUVBQUFERHR8+fPCQCdP39e21tQJWFhYQSAoqOjq0ybnp5OEomETp8+XWGa0aNH09tvv62x7bvvviNHR0dSKpUa20eOHEkLFy6kJUuWlNF5woQJtGTJkkrLo0192bp1K3l5eZFYLCZPT0/auHGjel+J3vv27aMOHTqQWCwmX19f9f0t2f/yZ8KECZWWiUizzRGpdBwwYAAZGhqSq6sr/fLLL+Ti4kLr1q2rMq/yKKkvR44coSZNmpBYLKY+ffqo615Jmq5du6q/l3ePX2batGkklUopMTFRY3teXh41atSIAgMD1dsCAwPJ0dGR8vLyNNImJiaSkZERTZs2Tb2t9L0oYfv27QSATp06RURE69atI1dXV20uX2vmzJlDnTp1Un9fsmRJlfr9999/1LVrV5JIJGRmZkZ9+vSh9PR0IiI6duwYdezYkUxNTcnCwoL69++v0W5K15WX739FTJgwgQYNGqT+npOTo37G2tnZ0Zo1ayq8h9pw7tw5AkB//fUXNWvWjMRiMbVr147Cw8M10ri4uKi/V/Q8KuGrr74iHo9Ht27d0tiuUCiodevW5OPjo27r1alXpe9FCWfOnCEAtHXrViIiOnLkCAkEApLL5RWWsaTtVoRSqaQlS5aQk5MTiUQisre3p1mzZhFR5e/JQ4cOkY+PD4lEInJxcaE1a9Zo5Ovi4kLLli2jcePGkYmJibq+VfV+rYzSz4r79+9T586dSSwWk7e3N508eZIA0JEjR7TKrzQlz4YtW7aQo6MjSSQSGj58OGVkZGikKa/tVFZXsrKyyMXFhT755BOSy+XUunVrGj58eI3KWIK5uTlt27ZN/d3FxYXOnTtXYfpff/2V/Pz8yNDQkCwsLKhnz56Uk5NDS5YsKaNxST7z58+npk2bkkQiITc3N1q4cCEVFRWpr7f0cTt27CAi1ft58uTJZGVlRSYmJtS9e/cybaQiSj+fi4uLac6cOepnzbx582j8+PHltg9tqOpd93Ka8qisfs2ZM4caN25MOTk5tG7dOjIzM6PHjx+r95d+vjAY+gYbqWdwksOHD8PR0RHLli3T6IGNiYlBYGAghg0bhtu3b+PAgQP477//MHPmTI3j161bh44dOyI0NBT9+/fHuHHjMH78eIwdOxY3b95E48aNMX78eBBRtct28OBBLF26FCtXrkRwcDDs7e2xadMmjTR79uyBsbFxpZ+SHuMSFi1ahGHDhiEsLAxBQUEYNWoUIiMjq10+ANi3bx+MjY3x3nvvldn30UcfQS6X47fffgMA7N27Fx4eHhg4cGC5adPS0nDq1KlKz2djY4OgoCD88ccfUCgU6ms8evSoevSjNuTm5mLHjh1wc3ODk5NTlelPnToFpVKJJ0+ewNvbG46OjhgxYgQSEhLUaQoLC2FoaKhxnEQiwePHj/Ho0SP1th07diA2NrbGI6na1pfFixdjxYoViIyMxMqVK7Fo0SLs2rVLI928efPw0UcfITQ0FB06dMDAgQORlpYGJycntZ5RUVFITEzEhg0bql3WiRMnIiEhAefOncOhQ4ewadMm9TThEvr161dpvfb19dVIn5eXhxUrVmD37t24dOkSMjIyMGrUqGqXDQCUSiX279+PoKCgMiNoEokE77//Pk6cOIH09HSkp6fjxIkTeP/99yGRSDTS2tnZISgoCAcOHKjyGTBhwgSYm5urp+Hb2dkhMTER//77b42uoTTR0dE4fvw4unbtqvUxt27dQs+ePeHj44MrV67gv//+w8CBA9UzBXJzczF37lwEBwfjzJkz4PP5GDJkiHpq+PXr1wG8mOlT3hKDqpg3bx4uXLiA33//HSdPnsT58+fLTGGeNm1alc/B8vJdu3Ytbty4AWtrawwcOFBjaUJ12Lt3L3r37o3mzZtrbOfz+ZgzZw4iIiIQFhZWrXpVGT169EDz5s016kpxcTGOHDlSo3cNAPz2229Yt24dfvzxRzx48ABHjx5Fs2bNAFT8ngwJCcGIESMwatQohIeHY+nSpVi0aFGZ5RNr1qxB8+bNERoaikWLFmn9ftUGpVKJoUOHQiQS4dq1a9iyZQs++eSTMul8fX0rrR/9+vXTSB8dHY2DBw/izz//xPHjxxEaGor333+/2uV7GRMTE2zfvh1r165FUFAQEhISsHnz5hrlpVAosH//fuTm5qJDhw5aHZOYmIjRo0dj0qRJ6plyQ4cOBRHh448/xogRI9QzQxITE/HGG2+oy71z505ERERgw4YN2Lp1K9atWwdAtWzwo48+0pj1NHLkSADA8OHDkZycjGPHjiEkJAStWrVCz549q6zf5bF27Vrs3LkT27dvx3///Yf09HQcOXJEI83KlSurfA6UXuJS0buuNqxYsQICgQBjx47F559/ju+//x6NGjWqVZ4MBqdo2D4FBuMFpUd5yhshnDx5Mk2dOlVj28WLF4nP51N+fr76uLFjx6r3JyYmEgBatGiRelvJSHbpUZnyKN3D36FDB3r//fc10rRr106j9zorK4sePHhQ6efl0UMAGqOGJXlOnz693DKV9FRLJBKSSqXqz82bN4lINUJZ2WinTCZT5+3l5VVhr3p6ejoBoK+//rrce/EymzdvJgD07NkzIlKNFJmbm5OhoSG98cYb9Nlnn1FYWFiFZSqPjRs3klQqJQDk6emp1Sg9kWpkXCgUkqenJx0/fpyuXLlCPXv2JE9PTyosLCQioh9//JGMjIzo9OnTpFAoKCoqiry8vAgAXb58mYhUI002NjYUFRVFRFWPIpeHNvWlcePGtHfvXo00X375JXXo0IGIXuj91VdfqffL5XJydHRUa1My0vn8+XOty/Zym4uKiiIAdP36dfX+yMhIAqDRDh8/flxpvY6Li1OnLRktunr1apk8r127Vm6ZlixZQnw+X6Net2nThoiIkpKSypTnZQ4fPqzO++rVq5WO2nz77bca9bWyUeZ27dpRv379iEg1MjVx4kQCQHZ2djR48GD6/vvvKTMzs9xjK6JkFAoATZ06lRQKhdbHjh49mjp27Kh1+pSUFAKgHvWuaqZPebw8Op2dnU0ikYgOHjyo3p+WlkYSiaTMzI+qnoMllNTf/fv3l8nzwIED5ZappH69XFdsbW3V+w0NDSvU9ObNmwSADhw4UK16VfpelGbkyJHk7e2t/v7555+TQCAgCwsLCgwMpG+++YaSkpLKPbY81q5dSx4eHuoR2NKU954cM2YM9e7dW2PbvHnzyMfHR+O4wYMHa6TR5v1aGS+X5cSJEyQQCOjJkyfq/ceOHSvTJuPi4iqtHy+PpC5ZsoQMDAw0th07doz4fH6V7/KqZnUQEY0aNUpdJ6rL7du3SSqVkoGBAZmamtLff/+t9bEhISEEQOPZ+TKV1beXWb16NQUEBKi/l/e+unjxIslkMiooKNDY3rhxY/rxxx+rPEfpPO3t7embb75Rfy95L71c3rS0tCqfAyWzWbR511VGZc98IqLjx48TAPXznMF4lRDUea8Bg6FDwsLCcPv2bezZs0e9jYigVCrx8OFDeHt7AwD8/f3V+21tbQFAPbrx8rbk5GSt1sy9TGRkJKZNm6axrUOHDjh37pz6u4mJSbXXKpfu1e/QoUOVjqwOHDigvmYAGqPYVI2RoeqkrSqPEgc2w4YNQ//+/XHx4kVcvXoVx44dwzfffINt27Zp7QQsKCgIvXv3RmJiItasWYMRI0bg0qVLZUbYS6NUKiGXy/Hdd9+hT58+AFSzF+zs7HDu3Dn07dsXU6ZMQUxMDAYMGAC5XA6ZTIbZs2dj6dKl4PP5UCgUGDNmDL744gt4eHjU+L5UVV9yc3MRExODyZMna6ztKy4uhqmpaZnjShAIBGjdunWNZ3OUV06BQICAgAD1Ni8vrzLrqKs7siEQCNCmTZsyeUZGRqJt27blHuPp6Yk//vhD/V0sFmvsb4i6XVKvDQwMsGPHDixfvhxnz57FtWvXsHLlSnz99de4fv067O3ttcrzwIEDyM7ORlhYGObNm4c1a9Zg/vz5Wh1769YtDB8+vML9Dx48wOLFi3Ht2jWkpqaqR+jj4+Ph5+en1TkqIyYmBkVFRWjXrp16m4WFBTw9PTXS2djYVNsfyct1vCTPyuq4iYmJxgwBPl9zAmJD1hVANTo4d+5cdV3ZsmULVq5ciX///VfjnVQRw4cPx/r16+Hu7o7AwEC8+eabGDhwIASCin++RUZGYtCgQRrbOnbsiPXr10OhUMDAwAAA0Lp1a4002r5ftSEyMhJOTk5wcHBQbytv5NrFxUXrPAHA2dlZ4xnUoUMHKJVKREVFVftd/jJPnjzB8ePHYWRkhIsXL2LEiBHVOt7T0xO3bt1CZmYmDh06hAkTJuDChQvw8fGp8tjmzZujZ8+eaNasGfr27Ys+ffrg7bffhrm5eaXHHThwAN999x1iYmKQk5OD4uJiyGSySo8JCwtDTk5OmXXx+fn5iImJqfpCXyIzMxOJiYkaz4GS99LLbcnCwgIWFhbVyruu3nU//fQTjIyMEB4ejszMzDLvWAZDn2HT7xl6RU5ODt577z3cunVL/QkLC8ODBw/QuHFjdTqhUKj+v+QHVnnbSnsq1hU1mX5fE5ycnNCkSRP1p8T48fDwQGxsbLnOj54+fYqsrCy1oerh4VHhy7JkuzZGbWRkJGQymcaPBUNDQ/Tu3RuLFi3C5cuXMXHixGpNYzc1NUXTpk3RpUsXHDp0CPfu3Sszta88Sgyrl39QWVtbw8rKSj3Nj8fj4euvv0ZOTg4ePXqEpKQktZHp7u6O7OxsBAcHY+bMmRAIBBAIBFi2bBnCwsIgEAhw9uxZra+jMnJycgAAW7du1ajXd+7c0XDkxRWqO/2+JohEIo16XdJZZW1tre4QKI/IyEjweDz1cTwer9K05ubmsLa2rrQsCoUCDx48gJubm8b2Ro0aYdy4cfjhhx9w9+5dFBQUYMuWLVpfo5OTE3x8fDB69Gh89dVXWLp0qdZOIEsvJyjNwIEDkZ6ejq1bt+LatWu4du0aAN04Q6sONZl+X134fL5GXXF3d1fv0/bZVp16VRWRkZFl6oqlpSWGDx+ONWvWIDIyEg4ODlizZo1W1+fk5ISoqChs2rRJvRSgS5cuNV6S8DJSqVTju7bvV11S3en3dcWUKVMQEBCAv/76C5s3b8aFCxeqdXzJMysgIACrVq1C8+bNtV4CZWBggFOnTuHYsWPw8fHB999/D09PTzx8+LDCY65cuYKgoCC8+eab+OuvvxAaGooFCxZU2cZzcnJgb2+vofGtW7cQFRWFefPmVeuataUm0+/rggMHDuCvv/7C5cuXYWJigjlz5tT5ORmM+oSN1DM4S3nepFu1aoWIiAitflzVFd7e3rh27RrGjx+v3lba+Hrrrbc0eq/Lo/SI59WrV8vk2bJlyxqVcdSoUfjuu+/w448/YtasWRr71qxZA6FQiGHDhqnTjhkzBn/++WeZdfVr166FpaUlevfuXen5kpOTsXfvXgwePLjMSNnL+Pj41DhGMRGBiLRao9+xY0cAqvXljo6OAFTerVNTU8uMDBkYGKi12LdvHzp06ABra2solUqEh4drpN20aRPOnj2LQ4cOlfnhXhFV1RdbW1s4ODggNjZW7bW7Iq5evar2Al9cXIyQkBD1eleRSAQAWhuGpfHy8lLnWTKyHhUVVSZE3rZt25Cfn19hPi93npWUMzg4WN1hUpJndUb9SuDz+RgxYgT27NmDZcuWaYzM5efnY9OmTejbt696VKh3797YtGkT5syZo2EIJyUlYc+ePRg/fnyV4cR27dqF58+fq9tLeZibm8Pe3r7GHs1LZpYolUr1KGpl+Pv748yZM/jiiy/K7EtLS0NUVBS2bt2Kzp07AwD+++8/jTS1rSuNGzeGUCjEtWvX4OzsDAB4/vw57t+/r+EbYNmyZfj444+rlffVq1fL5FmTugKonm0LFixAWFiYxrp6pVKJdevWwcfHB82bNwePx6tWvaqIs2fPIjw8vFJjQSQSoXHjxtWqKxKJBAMHDsTAgQMxY8YMeHl5ITw8HK1atSr3Pent7V0mdOilS5fg4eFRaf3S5fvV29sbCQkJSExMVHeyltdJ+c8//1TaQVG6Ays+Ph5Pnz5VzwC4evUq+Hx+mVki1WHbtm3477//EB4eDhcXF0yfPh2TJk3C7du3y3R8aItSqayWPxkej4eOHTuiY8eOWLx4MVxcXHDkyBHMnTu3XI0vX74MFxcXLFiwQL3tZV8wQMW/oZKSkiAQCGodvs3U1BT29va4du1amfdSq1at1OmmTZtW5cyHl2d0AJW/62rCs2fPMGPGDCxfvhzNmzfHzp078cYbb2D48OH11nHEYNQ5DTHnn8Eoj9JrWnv37k1vvfUWPX78mFJSUohI5QFdIpHQjBkzKDQ0lO7fv09Hjx6lGTNmqI8rb40hSq2zqs6a0tJr8fbv30+Ghoa0fft2ioqKosWLF5OJiUmtvd9bWVnRTz/9pM6Tz+fT3bt3y02vTflnz55NYrGY1qxZQ9HR0RQZGUkLFiwgPp+v4RVfqVTSkCFD1N56Hz58SGFhYTR16lQSCAQa923Hjh0kk8koMTGRnj59ShEREfTTTz9R48aNyd3dnZ4+fUpERKmpqdS9e3f6+eefKSwsjGJjY+ngwYNka2tLkyZNqvJ+xMTE0MqVKyk4OJgePXpEly5dooEDB5KFhYV6DXRVDBo0iHx9fenSpUsUHh5OAwYMIB8fH/Xa1JSUFNq8eTNFRkZSaGgoffDBB2RoaFjhWm+imq2p16a+bN26lSQSCW3YsIGioqLo9u3btH37dlq7di0RvdDb2dmZDh8+TJGRkTR16lQyNjZWt43Hjx8Tj8ejnTt3UnJyMmVnZ1dZttJtLjAwkFq2bElXr16l4OBg6tSpE0kkklp5vxcKhdS2bVt1nu3bt6f27dtXeExV9zg1NZUaN25Mfn5+9M8//1B8fDxduHCBOnfuTDY2NhQTE6NOe//+fbKysqLOnTvThQsXKD4+no4dO0Z+fn7UtGlTSktL07gXU6ZMocTEREpISKArV67Q/PnzSSgUavi22LJlC02bNo1OnDhB0dHRdOfOHZo/fz7x+Xytoj388ssvdODAAYqIiKCYmBg6cOAAOTg4qCNHaENUVBSJRCKaPn06hYWFUWRkJG3atIlSUlJIoVCQpaUljR07lh48eEBnzpyhNm3aaDwD5XI5SSQSWr58OSUlJWl4D6+I0ut6p02bRi4uLnTmzBkKDw+nt956i4yNjWvt/d7X15dOnz6tztPZ2VntB6M0Va2Tzs/Pp3bt2pGTkxMdPHiQHj16RNevX6fBgweTVCqlK1euqNNWp15NmDCBAgMDKTExkR4/fkwhISG0YsUKMjY2pgEDBlBxcTEREf35558UFBREf/75J0VFRdG9e/do9erVZGBgQLt379bqvuzYsYO2bdtG4eHhFBMTQwsXLiSJREKpqalEVP57MiQkhPh8Pi1btoyioqJo586dJJFI1N7Picp/T2rzfq2Ml/NUKBTk4+NDvXv3plu3btG///5LAQEBtfZ+L5VKqVevXuo8PTw8aNSoUVUeW1FdiYuLIxMTE4315Lm5udS4cWOaOXOmVuX69NNP6cKFC/Tw4UO6ffs2ffrpp8Tj8ejkyZNaHX/16lVasWIF3bhxgx49ekQHDx4kkUhE//zzDxERrVixgpydnenevXuUkpJCRUVF9Pvvv5NAIKB9+/ZRdHQ0bdiwgSwsLDSucc+ePSSVSik0NJRSUlKooKCAlEolderUiZo3b04nTpyghw8f0qVLl+jzzz/XKiJQ6efzV199RRYWFnTkyBGKjIykKVOmkImJSa2931f2rquMiurXW2+9RZ06ddLwXfLpp5+So6OjVs8/BkMfYEY9gzOUNjCuXLlC/v7+amdSJVy/fp169+5NxsbGJJVKyd/fn1asWKHeX9dGPZHqJWtlZUXGxsY0YcIEmj9/fq2N+o0bN1Lv3r1JLBaTq6trpc56tC3/Tz/9RAEBAWRoaEhSqZQ6d+5cbug6uVxOq1evJl9fXxKJRCSTyahv377033//aaR7OUwOj8cjU1NTatu2LS1btkzDUVhBQQF9+umn1KpVKzI1NSUjIyPy9PSkhQsXlgkvVh5Pnjyhfv36kY2NDQmFQnJ0dKQxY8bQvXv3qjy2hMzMTJo0aRKZmZmRhYUFDRkyRCOUWkpKCrVv356kUikZGRlRz549NRy6lUdNjHoi7erLnj17qEWLFiQSicjc3Jy6dOlChw8fJqIXeu/du5fatm1LIpGIfHx86OzZsxp5LFu2jOzs7IjH49UopF1iYiL179+fxGIxOTs70+7du3US0u63334jd3d3EovF1KtXL3r06FGFx2hzj1NSUmjWrFnk5OREQqGQbG1taeLEieXmGxcXRxMmTCBbW1sSCoXk5OREs2bNUhtFJbwcHqwkdNiAAQPUGpRw8+ZNGjt2LLm5uZFYLCZLS0vq0qVLue2qPPbv30+tWrVSP798fHxo5cqVWjkie5nz58/TG2+8QWKxmMzMzKhv375qJ4mnTp0ib29vEovF5O/vT+fPny/zDNy6dSs5OTkRn8+vUUi77OxsGjt2LBkZGZGtrS198803Oglp9+eff6qfQ23btq3UuaY2zs9yc3NpwYIF1KRJExIKhWRhYUHDhg3TCJVXgrb1asKECeq6IhAIyNramnr16kXbt2/XMBpiYmJoypQp5OHhoQ492KZNGw3juiqOHDlC7dq1I5lMRlKplNq3b68RqrOi92RJSDuhUEjOzs60evVqjXwratdVvV8ro3SeUVFR1KlTJxKJROTh4aF2UlbbkHabNm0iBwcHMjQ0pLffflsdyrEyyqsrSqWSevbsSX369CmT/uLFi2RgYKBVR92kSZPIxcWFRCIRWVtbU8+ePbU26ImIIiIiqG/fvmRtbU1isZg8PDzo+++/V+9PTk5Wa4KXQtrNmzePLC0tydjYmEaOHEnr1q3TuMaCggIaNmwYmZmZaYS0y8rKolmzZpGDg4P6mRgUFKTxfqyI0s9nuVxOs2fPJplMRmZmZjR37lydhLSr6l1XEeXVr127dpGRkZGGY04iosLCQvLz86N33nmnRmVlMLgGj0gHnmEYDAaDUWfExcXBzc0NoaGhaNGiRUMXh8FgMBgMBoPBIZijPAaDwWAwGAwGg8FgMPQUZtQzXnsq8+a9cuXKhi7eK0ll0QG08Z5emVft0uHj/p+9+45vqur/AP7JaJp0L7onBbpYZS9lL9kgsyxREAVZigsZoogDBEEBfyjD52EqQ/EREBCQTYG2FCgFShfQ0tI904zz+yM2NnSlbZrc237fr1de0Jubm5N8bm5y7jn3nMYqKSnJ5KMNN0Z8PZ7U90wdhN/OnTtXr7MYcFVjO45WNRtB2akOCSHcQ93vSaP3+PHjSkfzrs38qqR6eXl5ePr0aYX3mZmZVTt3cVpaGnJzcyu8z8bGpsZzYzdESqUSCQkJld7v6+tb5VzXpHb4ejx58OBBpfd5eHhUO40eadiKiorw+PHjSu835Yw09amxHUcTExMrnY3AxcUF1tbWRi4RIURfVKknhBBCCCGEEEJ4irrfE0IIIYQQQgghPMW5PkNqtRpPnjyBtbU1BAKBqYtDCCGEEEIIIaQBYowhLy8P7u7uEAr5297NuUr9kydP4OXlZepiEEIIIYQQQghpBJKTk+Hp6WnqYtQa5yr1pYNwJCcnw8bGxsSlaTiSk5PpZAnHUUbcRxnxA+XEfZQR91FG3EcZ8QPlxG25ubnw8vLi/UCQnKvUl3a5t7GxoUq9ATHG6P3kOMqI+ygjfqCcuI8y4j7KiPsoI36gnPiB75d98/fCAVIj7u7upi4CqQZlxH2UET9QTtxHGXEfZcR9lBE/UE7EGKhS30hUNqc34Q7KiPv4kJFKzXD/aZ6pi2FSfMjp1uMcpOfJTV0Mk+FDRo0dZcR9lBE/UE7EGDjX/Z7Uj/z8fFMXgVSDMuI+rmeUmlOMDw9Fw1oqhkggwPsvBcLZWmrqYhkdl3NKySnCZ3/chb2FGQrkKjzLl8PdToYuTR3Q2c8RrraNIy8uZ0Q0KCPuo4z4gXIixkCV+kaCBujgPsqI+7ic0em7afjxfDw+HhEC/yZWuP0kB+/8fBN9A50xuYsPREJ+XytWE1zMSalSY8fFBFx48AwfvBSEFi7/DsjzKKsQV+Mzse7EPaTmFsPZ2hydmzqis58DvBwsTFjq+sPFjIguyoj7KCN+oJyIMVClvpF49uwZbG1tTV0MUgXKiPu4mFGJUo2vjt9FiVKNH6Z1gNRMBAAIcbfFjukdsTc8GdO3X8XigQFo7Wln2sIaCddyup6Yha9PxGJkWw9sm96x3GA8nvYW8LS3wOh2mql0UnOKcSU+A5vPxuFxVhEcLSXo5OeAzk0d4etowfvBfADuZUTKo4y4jzLiB8qJGANV6huJoqIiUxeBVIMy4j6uZZSYUYCPDt9CWGdvDGrpVu5+oVCASZ29MSDEBV8euwuZ2SMsGhAAW5mZCUprPFzJKbuwBF8ci4VAAHw7sR3sLSV6Pc7VVooRbT0woq0HACA9T47whEzsuBCPhIxC2FmYoaOvA7o0dYB/EyteVvK5khGpHGXEfZQRP1BOxBgEjDFm6kKUlZubC1tbW+Tk5ND0DwaUl5fH+fkX5UoVJCIhL3+gGgIfMmrsuJTRkagn+OX6I6wa1RKe9vp10b7yMAPfnLqP8R29MLyNe4P9rJk6J8YYfrn+CL9GPsHC/i3Q3sfeoNvPKijB1YRMXHmYibj0fFhJxejoY4/uzZzQ3IUb+2d1TJ0RqVpRiQp5+XlwdrAzdVFIFehzxA+UE7c1lLonjX7fSKSmppq6CFUqVqgwetNFHL/91NRFMRmuZ0S4kVFRiQofHopGTEoufpjWQe8KPQB0buqIHa90wuPsIsz86Rri0hvm4D2mzOne0zzM2BGOnCIFdrzS0eAVegCwt5RgYIgrlg0Lxs4ZnfDZqFbwdrTAkkO3kJZbbPDnqw9c+CyRyv3f3w/xZ0S8qYtBqkGfI36gnIgxUPf7RkIu5/bUSZ/9EYPZPf2x60oiBoa4NNgWxKpwPSNi+oxiU/Pw8ZHbeKOXP15o3qRW25CIhXizVzMkZxZi9dEYNGtihTd7N9Nei98QmCKnwhIlvjl1HynZxfhsdCu42cqM9ty2MjP0CXTBs3xNC/7Q1tyfE9nUnyVSuWf5ckQ9ysbC9o1jJgY+o88RP1BOxBhq1FK/efNmtG7dGjY2NrCxsUHXrl1x9OhRAEBmZibeeustBAQEQCaTwdvbG/PmzUNOTk69FLwm5EoV9oUnQa5UmbooJtO0aVNTF6FSR6NTIDUTYVgbd7Tztse5+89MXSST4HJGRMNUGTHGsOdqEr46Hov1E9rWukJflpeDBTaFtUdLD1u8sj0cZ2LTDFBSbjB2TifuPMWrO66hS1NHbJgYatQKfVmdfB1wNT7TJM9dU3S8466Np+5jbp9m8Pf3N3VRSDXoc8QPlBMxhhpV6j09PfH555/j+vXruHbtGvr06YMRI0bg9u3bePLkCZ48eYI1a9bg1q1b2LFjB44dO4ZXX321vsqul+zCErzx3xt4nFWEBXsjUaxonBX7pKQkUxehQsmZhdgTnox3BgQAAF7p7osdFxNMWygT4WpG5F+myCi3WIGF+yKRVViC/5vS3uDzzg8IccWP0zvg0sMMzNsTgdQcfnTfroqxcnqUVYg5u27g5qNsbH+lI3oHOBvleSvj42iBxIxCk5ZBX3S846b4ZwXILFSgnbc9ZcQDlBE/UE7EGGrU/X7YsGE6f69atQqbN2/G5cuX8eqrr+LAgQPa+/z9/bFq1SpMnjwZSqUSYnHFTyWXy3W6peTm5takSFVKzCjA+weisWRIEFp62OJMbBrm743ANxNCG1RXU30olUpTF6GcEqUaSw7fwqqRLSERa84v2VlI0NzZCuEJmejo62DiEhoXFzMiuoydUVRyNj4/ehfvDGyB9j7193mwkIjxweAgxKbm4f2DN9GjmROmd/OFWMTPYVfqO6cSpRo/no/H9cRMfPBSEPybWNXr8+lLIBDARmaGnEIFbC24PcMBHe+4af3Je1jYrzkAyogPKCN+oJyIMdT6F5tKpcLevXtRUFCArl27VrhO6SiClVXoAWD16tWwtbXV3ry8vGpbJB3XEzOx5NAtfD2+DVp6aOaG7BXgjCldfDF3dwSKShpXi32zZs1MXYRy1vwZi4kdveDloDvQ16s9/PDDuYcmKpXpcDEjostYGanVDFv/foit5x5i8+R29VqhLyvA1RrbpnWEjcwM07eH43pillGe19DqM6crDzPwyo6rcLeTYuvUDpyp0Jfq4GOPa4nc74JPxzvuiUzOho3UDE3/2acpI+6jjPiBciLGUONKfXR0NKysrGBubo7Zs2fj0KFDCA4OLrfes2fP8Mknn2DWrFlVbu+DDz5ATk6O9pacnFzTIpVzJOoJtv4djy1T2pe7trFHcyfM6OGLubtvoLCk8Zw5e/iQW5Xkv+4+RbFChcGtys+t7WwjhYuNFLcem348BmPiWkakPGNklJEvx5u7bkBqJsTGiaGws9BvbnNDEQoFGNfBCxsnhuKX64/w4aFoZBeWGLUMdVUfOWXky/HuL1H4IzoFm8LaY0RbD04O6NnR1wFXE7hfqafjHbcwxrDh1H3M69tcu4wy4j7KiB8oJ2IMNR79PiAgAJGRkcjJycEvv/yCadOm4ezZszoV+9zcXAwZMgTBwcFYsWJFldszNzeHubl5jQteEcYYNp2JQ1puMb6dFFpp19Fu/k4QCQSYuzsCGyaGwsq84U8CoFarTV0ErZScImw7n4AfpnWodJ1ZLzbFF8disXFiqBFLZlpcyohUrL4zuhSXgQ2n7uOjoUEIcbet1+eqjr2lBKtHt8L1xEzM2X0DY9p5YlQoNyuyzzN0Tj9fS8ZvUU/wzoAAtPGyM+i2DS3A1Rr3jueZuhjVouMdt5yOTUNrT1s0sf739xhlxH2UET9QTsQYBIwxVpcN9OvXD/7+/vj+++8BAHl5eRg4cCAsLCzw+++/Qyqt2aBOubm5sLW11Xbd11eJUo1lv95CcxdrzOjuq9cPz2sJmfj29ANsnBgKaym3rz+sK4VCATMz079GpUqNmT9dw9KhwdoufpVZ/HMUXu/ZFM2crY1UOtPiSkakcvWVkVKlxoa/HiAluwgrhofAkmMnGpUqNTafiUN8RgE+Hh7C+eOlIXPadOYBcooUeHdgIERC7p/QAIDX/3MN68eHQibh7tgxdLzjDpWaYdq2q/h+SnudYw9lxH2UET9QTtxW27on19R5FCS1Wq0d6C43NxcDBgyARCLBb7/9VuMKfW3lFCnw5q7r6BPojFd7+OndktTB1wHz+jbHnN0RyC1W1HMpTSs2NtbURQAAbDh1H8PbuldboQeA2b38seVs4+myxJWMSOXqI6OUnCLM+s91+Dpa4KuxbThXoQcAsUiIt/o2x8RO3pj103VEP+L2pTGGymnDqfsoVqjx/iD+VOgBINTbHhHJ3B4PgY533HHgxiMMbOla7thDGXEfZcQPlBMxhhpV6j/44AP8/fffSEhIQHR0ND744AOcOXMGYWFh2gp9QUEBfvzxR+Tm5iI1NRWpqalQqepvULrkzEK88d/rmNe3OQaEuNb48e287fHOgBaYs+sGcgobXsX+YXo+5u+NwO00009TdfHBMzzNlWNUqKde6/s3sUKJUo3kTH5M0URITRSVqPDDuYd495eb+GhIEEa30+9zYUodfR2wKawdtpyNw4/n41HHjl6cxRjD1yfugTFgUf8WvLjkoKyOvg4Ij+d2pZ5wQ7FChV8jH2NCR8MMUkwIIcQ0alSpT0tLw9SpUxEQEIC+ffsiPDwcx48fR//+/XHjxg1cuXIF0dHRaNasGdzc3LQ3Qwx+V5EbSVl4/+BNfDW2DVp72tV6O6097fDeoEDM2X0DWQX8GhCqMsUKFb7+MxZr/ozFm72a4dQjhl8jH5usPOl5cnx7+gGWDy8/qGJVZr3YFN//HVdPpeKWgIAAUxeBVMMQGRXIldhyNg4zf7oGN1sZdr7SSa+eK1xhbynBt5NCIRIAc3bfQCYHj5l1yYkxhjV/xsJcLMT8fs2rfwAHtfKwRfTjbFMXo0p0vOOG7RcSMLmzD8wqGIOIMuI+yogfKKe6Y4whKTcJhx8cRo6c270FTaVG/Tx//PHHSu/r1auXUVtt/ohOweGIx9gyub1Bru9s6WGLD18Kwtw9N7BhQigcrQwzeJ8pnIlNw/dnH+KV7r5YNEBzIJnTVopDCdlIyijE3D7NjNrypFYzfHgoGsuGBcNCUrOuxS09bPHsrxKk5RbD2cY4l3OYSmxsLFq2bGnqYpAq1CWjvGIFfrqUiMsPMxDW2QezXmgKIY+6dJclEAgwvbsfOvg6YM6uG1jQrzk6N3U0dbG0apsTYwyfH7sLR0sJZr3oXw8lMw6JWAjGAIVKXWFljQvoeGd6WQUluPwwA7N7Nq3wfsqI+/iYEWMMxapiFCoKUagsRKGiEEXKon///mdZuX//Wa+UGmpYmlki2CEYQY5BCHQIhK25aQeYrQwfczI1pVqJ2MxY3Ei7gaj0KOQr8uFt7Y12zu1gJqTxCSrCvYs3q8EYw/d/P0RyZiG+C2tn0B8swe42WDY0BPP2RuCbCaFw4lnFPjWnGKuPxsDVVoofp3fQqUCLhAKsGB6C7Rfi8d6Bm/h0ZCtIxMb5sbfl7zj0DnBGoGvtBp+Y+aIftp57iCVDatbKTwgX5BQqsP1iPK4nZmF6N1+82cufd925K9PSwxZbp3XA8l9v4/LDTMzt04xX156XxRjDp/+LgbudDK/28DN1ceosxMMWt5/koi3HR+snpvPt6QeY09u4J/lJw6FUK5Ejz0G2PFtzK85GljxL5/+5JbkVNvhJxVJYiC1gYWZR4b8OUocKl0vFUggF//52zZHnIDYzFjGZMTh4/yByS3IhE8sQ6BCIIIcgBDkGwUnmZMy3hdRSoaIQUelRiEiLQExGDAAgwCEA7ZzbYVSzUbCS8KdHo6nUefR7Q6tqBEKFSo3lv92Gr6MFZr7QtN6+iB6k5WHZr7exfnxbXrQOK1Vq7LyUiPP30/H+4CAEuJYfLb7syJsn7jzF3qtJ+HpcW9ha1O/ZrmsJmfjv5USsG9+2Tnm9uiMca8a2gb2lcefsNiYaHZX7apJRVkEJfjwfj1tPcvBKdz+82Nypwf54ZozhwI3HOBqdgs9Gt4KLiY+bNf0sMcbw8ZE7aNrEElO7+tZfwYzo/P1nuJOSw9keB3S8M63kzEKsPhqDTWHtK12HbxkxxqBmaqiYCkq1EiqmgkqtgpIpoVKrdP6u7P7S5VZmVghyDIK5iNuNO4bOSKFS4FbGLWQUZSBLnoUceQ6yijUV9dySXOCfGgMDg0gggq25LeykdrA3t4eduZ3mJrXT/t9GYgOR0LizcBQqChGbFYs7GXdwN/MuMooyIBFJ0Ny+OYIcghDsGAwXCxejfh/z7bNkDOmF6YhIi0BEWgQSchNgIbZA6yat0c65HQIdA43aGt9QRr/nTaU+t1iBt/dHYXSoBwa3cqv3csSl52Pp4Vv4elxbuNpyt2J/IykLX/95D8PbuuPldp6Vdue9deuWTtef6Ec5WH00Bp+Pbg1vR4t6KVt2YQne+O8N/N/Uul8ice5+OsITsrCofwsDlY5bzt5Lx9+R9/H64HZwtubu/tbYPf85qsizfDl+OBePe0/z8GoPP3Tzd2ywlfnnPUjLx/LfbuG1F5qid4CzycqhT06l1GqG5b/dRqCbNcI6+9RzyYynsESJt/dHYfPkyittpnLsViqKMh5jVE/ula2xeHt/FGb3bIrmLpVPGVuTz5GpPMp7hC/Cv9D+LRKINDehCGKBGCKh5m+xUFzh8srWy5Hn4E7GHSjUCjSzb4bQJqFo69wW9lJ7E77a8gyRkUqtQvjTcByLP4anhU8R6hwKZwtnbcXcXqqpsFtLrHVayflErpLjQdYD3Mm8g5iMGKQWpEIkFMHf1h+BjoEIdgiGp7Vnvb0+PnyW6hNjDPG58Yh4GoEbaTeQWZwJJ5kT2jm3Q6hzKHxsfEz6O6mhVOp50f3+UVYh3jtwE+8MCECot3EOqP5NrPDZqFZYtD8Sa8a2gbudzCjPq6/swhJ8dTwWagZsnBhabQu2UKh7oGrlaYs1Y9tg8S9RWNQ/AO19DPu+Msaw5NAtfPBSoEHGPOjRzAlbz8Ujr1jB+Tmya+rKwwzsvpKILs4SfPp7DORKFYa2dkf/YBdIzbg7z3Rj9PznqKy0vGL839mHSMgoxGsv+OH9wYFGLBk3NHO2wo/TOuKzP2Jw8cEzLB4YaLTLfMqqKqey1GqGJYdvoa2XLcZ39K7nUhmXhUSMIoUKajXj3NgNu68mQS0vRKYoHjO6+zaak15ccetxDiRiQZUVekD/z5EpeVp7YmOfjfW2fTVT40H2A0Q8jcCX4V8iW54NFwsXtHVui3bO7eBl7WXS/be2GamZGjfTb+KP+D+QmJuIjq4d8WqrV+Fl3TBnQTAXmSPEKQQhTiHaZQq1Ag+zHyImMwa7YnYhOS8ZAoEAQgghFAghEUlgJjTT/msmMoNEKKl0eekyiUgCsVCsXddcZI4Sxr0BZevbk/wn+CvpL9xIu4EiZRH8bP3QzrkdFrZfSJdE1BPOt9RHJWfji2N38cWY1vByqJ8W5aokZWhOKHw1tjU87Y3//M9jjOHgjcc4FPEYC/o1RwdfB70eV1xcDKm0fAtwXrEC7/wchWFt3DG0tbvByrntfDwAYIYBr03983Yq4tIL8EYvbnYnrY27qbn47I+72DK5HYRqJaRSKXIKFfg9+glO3HkKN1spRrfzRAcfe/rhywEVfY5Sc4qx5WwcnmQXYdaLTfX+TDZ0x26lYNeVJKwa2areegNVprLjXVkqNcMHB2+ik58jXm7P/ekEa2PV/+7g5fZeFV6SZSpPc4vx5bFYfDqsBfbdSMWV+EysGtUKDg340iqumfnTNXwyomW1vRD1+Rw1RqkFqYhMi0REWgSS8pJM2m24JhkxxhCTGYNj8ccQkxmDNk3aYLDfYPjbNZzfVIaiUqtQoi6BQq1AiaoECpVC8/c//5aoNPdpl/+znnZ5mb+LVcVIyE5ACSuBucgcfrZ+aG7fHC3sWsDbxhtiIS/aV/WSkJOAk0knce3pNTjLnNHPpx86uHSAhZnp609VaSgt9Zyu1F9MKsQv1x9h7bg2sJWZrnU2ObMQ7/5yE1++bJoTC6XuP83D50fvoqu/I6Z1863RIIFVdf1RqtT4+MgduNlJ8UbPug/idfNRNr4/+xDfTgo1aEVUrWaYsu0KfpzWsUG0YCdnak4YfTupHRwsJRVmFP+sAIduPML1pCx08HHAmHaeRq8gkX+VzehxdhE2n3mAjPwSvN7TnwYkq0ByZiGWHL6Fse09MayN4U4alqVSqaBQKHSW3bt3Dy1aVH6pjlKlxto/76G9jz36BbvUS7m44MKDZ3iWL8eIth6mLorWH9FPIJOI4SHIRosWLXDvaR6+PxOHqd180MbL8D3xJBIJL1qcjeXc/XRcisvAu4Oq70nU2LsM66tAUYCo9ChEpkUiJiMGDAwt7Fsg1DkUbZzbwEZSf5UEfTJ6mP0QRxOOIjItEoEOgRjkNwjBDsHUUGBEpTkVK4vxMOch7mfdx4PsB0jMTYSKqWAtsUZzu+Zobt8cze2aw9XSlRf5MMZwP/s+TiaeRFR6FLysvbQVeT6drKBKfT0pfWM3HI3Ek0IBVo5oyYkpeZ5kF+Ht/VFYPboVfJ0sjfrcRSUqbPjrPh5lFeHDlwLhZlvzSwHu3r2LwMDKv8QZY/jxfDzi0vPr9J7nFSsw66fr2Dy5HewsDN/y8mvkY2QXKjCtm6/Bt21MmQUlmLPrhk4PkKoyUqsZwhMycSjiMZ7mFmNAiCteauVm0pNdjdHdu3dh6eyNTWfikFuswBs9/dHSg5tT6HCFQqXG1yfuIadIgaVDgiGTGOaEHGMMqampyM7OLv+cVQxKxBhDVqECUjMRLAxUFq5SqxmyixScagXPLCiBnYUZVEqlNiM1Y8gpVEAkEsDa3AyG/C0rFArh5+cHiYQ774GpqNUM07ZfxXdh7WCjx2Vs1f1uIBVTqpWIzYpFZFokItMikafIg6eVJ0IcQ+Bu5Q5XS1e4WroaZBC+yjJ6lPcIxxKO4WrKVfjY+OClpi+hTZM2vL0mnu+q+yzlyHPwIPuBtrKfWpAKBgYXCxc0s2umrezbSe2MV+hKMMZwO+M2TiSeQExGDJrZN0N/n/683r+oUl9PSt/YNb/fwKKX6jZiuqGl5hRj0f5IfDqyJZo2Mc7UCqdinuLH8/GY+UJT9A6s/cBThYWFsLCovoX32K3UWveOYIxh0f4ohHX2rrcuyEqVGlO3XcWOVzqZ5FpdQygsUWL2f2/gw5cCdab50zejohIV/ryTiv/dTIFMIsLIth54obkTxBw4+aUvhUqNlOxiPMouxOOsIliZi9E70JmzPTAYY4h+nIMd5x9CBQFm9/RHkBt/D/ym8Pe9dGw5G4cVw0PQopprefWRkpKC7OxsODs7w8LCQue7QqVSQSQqvy+pGUNqdjGspSJYyxpHJe9RViE87GSc+C5VM4aU7CJ42FuUy4gxhpwiBQrkSjjbSA1yMl+tVuPJkycwMzODt7c3J94DUzoc8RgZBSV6T9mo73cSqRpjDI/zHyMmMwYp+SlIKUjB08KnKFFprrMWC8VwsXCBm6WbtsLvaumKJrIm1Y4cXzajtMI0HE84jgtPLsDFwgWDfAeho2tHXrWYNlS1+SwxxvC08Km2sn8/6z5ySnIgFAjhZe0FH2sfeFl7wdPaE26WbjAT1V8jj0qtQmR6JE4mnkRcdhxCnELQz6dfg+nxQZX6esL1NzYttxgL9kVi5YiWaOZcfxX7x9lFWP1HDHwdLTGnd7M6t27VpBtdbccx2HM1SdMC3btZbYup9/OIBAKM68i/AV0UKjXm7r6BGd390Lmpo859tenqmJZbjMORj3Hu/jMEuFhjdDtPBLub/nNTrFDhSXYRHmUV4XF2ER5nFeFRViFyi5UQABCLBHCzlcHDTgZPexmeFZTgVMxTuNnKMKadB9pzZAyBlJwiHIp4jIsPMhDiYYO2NsUY3D3U1MXirbS8Ynx48Bb6BjljQsfaDzClUqlw7949ODs7w9HRsdz9RUVFkMl0ezSpGUNyZiHsLCSNqofL46xCNLE2h0Rs+hNm+cUKFCpUcLaWVpgR8O+xw8nKHDYGyCknJwdPnjxBs2bNGvWUUnKlCtO3hWPHjI4w13NfoO73xlGiKsHTwqdILUjV3lIKUvCs6BnUTA0AsDCzgKulq6bib+EKNyvNv3fu3sEj2SP8/ehvWEusMdB3ILq5d4NE1DhOWvKFIT9LSrUSyXnJ2tujvEdIKUiBUq0EADjJnOBp7QlPK09tpd9GYlPj71uFWoHw1HCcSjyFx/mP0ca5Dfp794e/Xd0v0+Uartc99UWV+lpIz5Njwb4ILB9mmBanshQqNbadj0d4QibeHxxksBMH9+/fR/PmzfVev3TGgcUDA/W6Vvhuai7W/nkP309uX+8jLcuVKryyPRz/ebUzRBwb1bkqajXDuwduon+wCwaGuJa7v6YZlcUYw52UXBy4/hj30/LQs0UTDG/rXm/T4xXIlTqV9Uf/VOCLS1QAAIlYCA87GTzsZfC0t9D+v7rKVPyzAhy88Qg3krLQydcRo0I9jD6GQGGJEsdupeKP6FTYSMUYGeqB7s2cIBIK6pQR0VCrGTafjcODtHx8PCJEr27AzysuLkZ8fDx8fX0rrhg+N3hUaYXe3kJikIoin2QXloAxVDtDijE8yS6Cg6UEUjNRlQN8qdUMKbnFEAJwsZVCWIcfkEVFRUhISICfn1+jHvTth3MP0cTavEbjK9DxjjvyS/I1Ff5CTYW/tPKflZOF4SHD8aLHi5wfjKwxM9ZniTGGjOIMPMp7pK3wP8p/hGx5NgBAKpLCw9oDnlae8LTWVPpdLV21gzvKVXJcenIJp5JO4VnRM3R07Yh+3v3gbdOwZod5Hh/qnvqoUaV+9erVOHjwIO7evQuZTIZu3brhiy++QEBAQLl1GWN46aWXcOzYMRw6dAgjR47U6zn48sZm5Mvx4aFoqNSG3W6JSo3RoR4Y0dbdoGfC8vLyYG1dsxMQucUKvL0/CqNDPTC4lVul6xWWKPHazmv4ZkIomljX/RoxfWw7H48m1ub1NvhWffjsn54XkzpXfHCsTUYVUajUOHc/HYcjnqCwRAnAsCc+GGOQSUTaCrvnPxV2DzsZLM0N081PrWa4mpCJQzceIz1fjgHBLniptVutKoD6Pt/lhxk4GPEYWQUlGNhSM2aB1XOvx1AZEeB6YibWnbgPFxspOjd1QBc/R3g56NdNvLRSX1lFrWzXbrWaITmrEPaWknrbf7isRKlGWm4xPE04yGuph+n58HOyhEAgqPQSibJyikqQkV8CD3uZ3q3Lz6tuX2kMcooUmLv7Bna+0qlGJ93peMd9lBE/cCWnImURnuQ/0anwp+SnQMmUUDM1RAIRurh1QT+ffnC1LN/41FDxpe5ZnRr9Aj979izmzJmDjh07QqlU4sMPP8SAAQNw584dWFrqDh63fv36Btc9oyxHK3N8P6WDqYuht8TExBp3/bGRmmFTWDss+/U2kjILMevFphVmuvLIHczp3cxoFXoAmNjJGzN/uoahrd14sZ9t/fshLCXiSiv0QO0yqoiZSIg+gS7oE8jfUb2FQgG6NHVEl6aO2jEE3tkfBQuJCCNCPfBCM8OMIRCXno+DNx4hKjkHXZo6YEG/5lVOXWmojAjQ3scB/32tM57mFuNKfCa+/zsOyVlFcLSUoJOfAzr7OWgrgDVVUlICmUwGtZohKbMQjlYSWDfCCj2g6TWjUJu+Q55cqYK5WKjNszSjqtjKJJCZifA4uxj2Fmb1MvhqY7DlbBxm9/SvcS86Ot5xH2XED1zJSSaWwd/On6YxbKBqVKk/duyYzt87duyAs7Mzrl+/jhdffFG7PDIyEmvXrsW1a9fg5lZ5Cy8AyOVyyOVy7d+5ubk1KRLRU3U/nipjJhLis1Et8f3fD/HR4VtYMTxEZwCjQxGP0MTaHN2bORmqqHqRSUTo6u+Iv+6moW8QtyuvhyIeISmzECtHhFS5Xm0zauhkEhFGtPXAiLYeeJpbjMMRj7HtfDwCXTVjCNR0wLqsghIcufkEp2LS4OUgw+h2nnhnQIBelUfKyPBcbKQY3sYdw//pdfMsX47w+Ez8dCkRD58VwFZmhk6+9ujc1BHNna30ykkgEECl1nS5d7KSwIonFfozZ86gd+/eyMrKgp2dncG2KxYKoFCpTTKTzPTp05GdnY0f/rtP58SKvidrJGIRfBwt8DS3GPlZhXC3ldX7JV4NSUpOER6m5+M9Paawex4d77iPMuIHyokYQ536yubk5AAAHBz+Hem8sLAQkyZNwnfffQdX1+q7bqxevRoff/xxXYpB9ODkVPtKt0CgGe37j+gUvLnrBtaOawMbqRkepufjt8gn2DrVND0WpnT1wVu7I9An0JmzrfVnYtNw+m461o2vfiaHumTUWLjYSPF6T3/MerEpbj/Jxc/XHuk1hkCJUo3TsWn4LeoJGGMY1tod/ze1fY279FJG9c/JyhyDW7lpL/nJLixBeEIW9ocn40F6PiwlYnT3s0FLGzUqu3pMKBJrKvTW5uUuoWiMLM1FKJQrYVuPLd2l161HRESgbdu22uXffPMNGGPILlbqDLwqFuufi1CgGVgzr1iBhIwCuNvJODtTBtd8c/I+5vdtUavH0vGO+ygjfqCciDHU+teOWq3GggUL0L17d50uJQsXLkS3bt0wYsQIvbbzwQcfYNGiRdq/c3Nz4eXFv1HNuS45ORm2tnWbT/ulVm5wtZXijf9ex6cjW2HZr7fx1djWJptKzUZqhlYetrgUl4FuRu4poI/I5Gz8dCkRm8La6TWgnyEyaiwEAgFaetiipYctFCo1/r6Xjk9/j4FcqcLQ1u7oH+wCc7EQNx/l4OCNR4jPKESfgCZYOTwEjla1v0yEMjI+OwsJ+ge7oH+wpkdObrECEQ/TUFhciMfZRTArVMNCIoaluQgyMxHUDEjKLISbnYXBxnjgO0uJGBkFJbCt4MqSkpKSep3D3dbWFio1Q3Zmoc5xUKFQ1KhiDwDWUjNIzUR4nFUEa5kYDhYSzp7Q5YJ7T/OgVLNaz4hCxzvuo4z4gXIixlDr2ticOXNw69Yt7N27V7vst99+w19//YX169frvR1zc3PY2Njo3IjhWVkZZhT9dt72+Hx0a8zbE4EZPXzhZmvaLkWvdPfFtgsJJi1DReLS87HmeCzWT2ird4uSoTJqbMxEQvQNcsGGiaH4ckwb5BYrMPu/1zH5xys4eisVYV188NOMTpje3a9OFXqAMuICG6kZOjd1hK3MTDNQo70FpGZC5BYpkZhRiPhnBXCyNONshV4ul2PevHlwdnaGVCpFjx49EB4errPOhQsX0Lp1a0ilUnTp0gW3bt3S3peYmIhhw4bB3t4elpaWCAkJwR9//KG9/9atWxg8eDCsrKzg4uKCKVOmIDc7E3KlZlTXXr16Ye7cuViwYAGcnJwwcOBATJo0CePHj9cpg0KhgJOTE3766ScAmsvvevToATs7Ozg6OmLo0KGIi4vTru/np5n7PDQ0FAKBAL169QKg6X4/YsQIWEnFOq/fx8enwtd/5swZCAQCnDp1Ch06dICFhQW6deuG2NhYAJrPe/aj+xg+eACsrTW/Gdq3b49r167VKZeGaP3Je1jQr/YjbtPxjvsoI36gnIgx1KpSP3fuXPz+++84ffo0PD09tcv/+usvxMXFwc7ODmKxWHsWfsyYMdoveGIahjxZ4uVggSNv9eDEQGyOVubwdrBARFKWqYui9TS3GB8duoWv/7lMQV90QqvubC3MENbZBzte6YRdr3XB+4MDDTrtJGXEPSKhANZSM7jaSuHrZIlmzlacvob+3XffxYEDB7Bz507cuHEDzZo1w8CBA5GZmaldZ/HixVi7di3Cw8PRpEkTDBs2DAqFAoDmhLpcLsfff/+N6OhofPHFF9ofjNnZ2ejTpw9CQ0Nx7do1HDt2DE+fPsX48eMhFAAqtaZiv3PnTkgkEly4cAFbtmxBWFgYjhw5gvz8fG0Zjh8/jsLCQowaNQoAUFBQgEWLFuHatWs4deoUhEIhRo0aBfU/27x69SoA4OTJk0hJScHBgwe121KqGaz/qdSXvv5t27ZV+voBYMmSJdqxecRiMWbMmKG9b/LkyWjq442/L17CoRN/Y+E7ixv1HPQVufwwAx52sioH/qwOHe+4jzLiB8qJGEONmjIYY3jrrbdw6NAhnDlzRntmvtT777+P1157TWdZq1atsG7dOgwbNqzupSW19uTJE52xDxqSWS82xcrfb2NTWHtTFwU5RQos2h+JVaNawtmmZtMnNeSMGgrKiPuWHIrGk6xCiIxwWZCLjRSrRrXSe/2CggJs3rwZO3bswODBgwEAW7duxYkTJ/Djjz+iY8eOAIDly5ejf//+ADQVcE9PTxw6dAjjxo1DUlISxowZg1atNM/btGlT7fa//fZbhIaG4rPPPtMu27ZtG7y8vJCaFA97S830s82bN8eXX36pXcff3x+WlpY4dOgQpkyZAgDYvXs3hg8frp2GacyYMTqvZdu2bWjSpAnu3LmDli1bokmTJgAAR0fHcuPpqNQM5mKRzuvv27cvZDKZzutfvHix9jGrVq1Cz549AWh+WwwZMkQ7t31SUhIWL16Mdq1bQqlS43Gz5rCQiMEYo+740PxW23QmDhsmtK3Tduh4x32UET9QTsQYalSpnzNnDnbv3o1ff/0V1tbWSE1NBaC5Zk4mk8HV1bXCwfG8vb3LnQAgxtWQzxK62kphZyFBTEpujUdCN6RihQoL9kbg3YGBaNqk5l2tGnJGDQVlxH2rRrWCXC6HubnxptjUV1xcHBQKBbp3765dZmZmhk6dOiEmJkZbqe/atav2fgcHBwQEBCAmJgYAMG/ePLzxxhv4888/0a9fP4wZMwatW7cGAERFReH06dMVdvVMSU6AT1PNNEbt2+ueABWLxRg3bhx27dqFKVOmoKCgAL/++qvO5XX379/HsmXLcOXKFTx79kzbQp+UlFTlVE0qNdNeS1/29QuFwnKvv6zS1wRAO4tOWloavL29sWjRIrz22mv4z3/+g379+uHll1+G0NUL8c8KYCERwc5C0qgH0vsjOhXd/B3rPAUgHe+4jzLiB8qJGEONmjI2b96MnJwc9OrVC25ubtrbvn376qt8xEAsLGrfBY8PXn+xKf7v74cme36VmuGdn6PwSnc/tPGyq9U2GnpGDQFlxA+lFcaG6LXXXsPDhw8xZcoUREdHo0OHDti4cSMAID8/H8OGDUNkZKTO7f79++jXpxeKFJqKuKWlZbnthoWF4dSpU0hLS8Phw4chk8kwaNAg7f3Dhg1DZmYmtm7diitXruDKlSsANAPtVUWhUkNcwUCh1WVUtjt9aet76YmEFStW4Pbt2xgyZAj++usvhISE4O8Tf8DPyRLWUjNk5MsR/6wAz/LlUKrUVT5PQ6NQqbHrSiKmd/Ot87boeMd9lBE/UE7EGGr0y4cxVuFt+vTpVT5m5MiRdSwmqavSXhUNlY+jJQQCIP5ZgdGfmzGGZb/eQr8gF7zYokmtt9PQM2oIKCN+UCqVpi5Chfz9/bXXspdSKBQIDw9HcHCwdtnly5e1/8/KysK9e/cQFBSkXebl5YXZs2fj4MGDePvtt7F161YAQLt27XD79m34+vqiWbNmOjcrKytU1TG9W7du8PLywr59+7Br1y6MHTtWW7HOyMhAbGwsPvroI/Tt2xdBQUHIytIdx6R0BH2VSqWzXKli2kshyr7+0owqev36aNGiBRYuXIg///wTo0ePxvbt2yEQCGBpLoaHvQV8HC1gJhLgaW4xMgtKcO5eOkqUpqvgq9UMd57kYseFeOy6kogHaXmVTslYF3uuJmFUqIdBeirQ8Y77KCN+oJw4rDATuLbD1KUwCG4OD0wMzt7e3tRFqHeze/rj+7Nx+HxM6+pXNqD1J+/Dz8kSI0M96rSdxpAR31FG/CAScbPrtaWlJd544w0sXrwYDg4O8Pb2xpdffonCwkK8+uqriIqKAgCsXLkSjo6OcHFxwZIlS+Dk5KQ9Ob5gwQIMHjwYLVq0QFZWFk6fPq2t8M+ZMwdbt27FxIkT8e6778LBwQEPHjzA3r178cMPP8BCIoJKXXlFctKkSdiyZQvu3buH06dPa5fb29vD0dER//d//wc3NzckJSXh/fff13mss7MzZDIZjh07Bk9PT0ilUlhaWwMCaE8mlH391tbW8Pf313n9+igqKsLixYvx8ssvw8/PD48ePUJ4eHi5a/6FAgFsZRKYCyxQlGmGpBw5XvvpGnwdLTC6nSfaeNrW6/X3SpUad1JyceVhJm4kZaFYoUKAqw06N3VAiVKN3VeSEZeeD2upGB19HdC5qQNaOFtDqMf0p5XJlyvx5+2n2Dmjk0FeAx3vuI8y4gfKiWOUJcD9P4FbvwBqFeA72NQlMgiq1DcSjWFk4BYu1siTK/EkuwjudsaZau+/lxNRrFRh4Qst6rytxpAR31FG/MDlwdI+//xzqNVqTJkyBXl5eejQoQOOHz+u86Pv888/x/z583H//n20bdsWR44c0WkJnzNnDh49egQbGxsMGjQI69atAwC4u7vjwoULeO+99zBgwADI5XL4+Phg0KBBEAqFsDQXQ1VF63BYWBhWrVoFHx8fnev+hUIh9u7di3nz5qFly5YICAjAhg0bdGa1EYvF2LBhA1auXIlly5bhhRdewOE//oSZSICy/SZKX/+MGTMqff1VEYlEyMjIwNSpU/H06VM4OTlh9OjR+Pjjjyt/jFCAUe08MbFbM9x7moeDNx5jzfFYdPV3xKhQD4N8XyhUatx8lIMr8RmITMqGUs0Q4m6Dzn6OCOviDQuJ7s+tgSGa8YdyihS4npiJQzceI/ZpHiwkIrTztkeXpo4IcrPRjkegj//7+yFe7eFXo8dUhY533EcZ8QPlxAGMAU9uAFF7gYw4oPkAYPBXgFUTIDfX1KUzCAGrj/5fdZCbmwtbW1vk5OTQwBIGdOvWrSoHM2oobj7KxsEbj7FieEi9P9fR6BT8dTcNX77c2iCViMaSEZ9RRtxQXFyM+Ph4+Pn5QSotP8tEUVERZDLjnNjjEzVjSMoohK9T+Wvq60NyZiFcbaQwE5e/0s9YGVW2r6jUDJfiMnAo4jFyikowqKUbBrd0haW5fm0dcqUKkUnZuBqfiahHOQCAVh626OTngFBvu1p3f8+XK3E9MQtX4zMQk5IHM5EAod726OzngJYetjCrZFaHtLxifHAgGj9M62Cwk1p0vDOQzHjgwnogOxkQigGxOWDrBdh5A3b//GvrBcjsarxpyogfDJqTPA/YPR7o+CrQckz16zd2OY+Am/uB+LOAWxug9QTARfdyr4ZS96SW+kbC0dHR1EUwitaedtj41wOk58nRxLr+Rr++FJeBXyOfYOOkUIP9gGosGfEZZcQPXO1+b2rCf45Vxpj6jTEGpZpVWKEHTJ+RSChAj+ZO6NHcCflyJY7dSsX8vRGwlUkwKtQDXf0ddVq8i0pUiEjKwuX4TNx+nAOhUIC2Xnbo6u+I13v6Q1LJ66wpK3MxerZogp7/jM9S+rynY9Px7V8PtM/byc8BrT1tYS7WvI8bTt3HvL7NDZorHe/q6NkD4Pw6QCUHeiwEXP5pbFAUayoa2YlATjLw+Lqmwi//p7VQKAZsPHQr/HY+gIUD8Fy+lBE/GCwntRr47S2g94fA7UNAVgLQY1G5/aLRk+cDMUeAO78CUlugzXig+3xA2LB/G1ClnjQ4r/bww7YL8XhvUKDBt10gV+JiXAb+czkRWya3q7TVhBBCuEhqJkKRQlWuO7ihFSlUkJnx4/hoZS7Gy+098XJ7TzzOLsLhiMfYfPYBWnrYQiQQICYlFxKxEO287dEn0Blv9WlmtGO/TCJCt2ZO6NbMCYCmh0BUcg4ux2Xg+7MPwRhDC1dr5Bcraz3zCjGw9FhNZZ4xTWXe+bnfImZSwKmZ5lYRZQmQ+1hT4c9OAu4d1/y/MENzv0AIWLsCdt6QmHsDrqOpUtdYnP0caNoL8O0B+HQHLn0HHJkPDFkLiBp5F3+1Ckg4B0TtA4qygKBhwJitgLm1qUtmNFSpbyQyMjK0c/02dJ39HPD92TjkFCpga1G3g1xusQLXEjJxJT4Tsal5kJmJ0N7HHhsmtDX4j+LGlBFfUUb88PwI7ORfluYiFMjrv1KfV6yEtbTy4y9XM/Kwk2FO72Z4s5c/bj7KgUgowNsDAgx2nXpdmYtF6OTngE5+DgCAEqUat57kwM/R8JdU0PGuhp7e1lTmRebAC+9UXmmvjlgCOPhpbhVRq4C8FCA7GapLe4CHh4EBnwD2vrUtOalnBvks3flVU1nt/aHmb4EA6DZX0yK9fyowcnOtLuHgvfR7QNQeTY8XvxeA3h9oerg0QlSpbyScnZ1NXQSjEQgEmNrNFzsvJWBe3+Y1emx2YQmuxmsq8Q/S8mElFaOjjz1GtvVAgEvdRiauTmPKiK8oI34Qi+mrrTIWEjEyCwoB1N/lSQBQWKKCcxWXQHE9I4FAwIuW79IeBPWBjnd6SokCzq/XtAj2XlJ5ZdxQhCLA1lNzk/kDwlzg2AeAR3ug2zzNSQHCKXX+LKXeAiJ3A+P/W/6+oGGAjTuwfwow/FvA3qduz8UHhZnArQNA7FHNyay2k4C+yxp9jxVuf6sSg1EoFKYuglH1atEE287Ho0CurHLgo2f5coT/U4mPf1YAW5kZOvo5YEJHLzRztjLqKNqNLSM+ooz4gWPjv3KKSCiAmtXvdfUKlRoioaDK7VNG3EfHu2o8vg5c+AawcAL6f2yS1kGFQgF4NAMm7NZUcnaNAV58V9NiSTijTp+lggzg2PvA2J2Vd7H3aA+M+A74dS7Qdzng2b72z8dlajXw50dA7iOg5cvAxD2agScJAKrUNxpZWVnw8KjbPOp8IhAIMLGTN/ZcTcJrLzTVLk/LLcbl+ExceZiB5KwiOFlK0MnPAVO7+sDPydKkU2E1toz4iDLiB6527eYKc7EQcqW61iO0V0fT9b7qnxeUEffR8a4SyVc1lXkbD2DgasDWdO+RNiOBAGj1MtC8P3D6M0135H4fa6brIiZX68+SSgH8+iYwaDVgWc1ge3bewPj/AIfe0AwMFzyidoXlKrUK+H0B4NUZGPSZqUvDSTWu1P/999/46quvcP36daSkpODQoUMYOXKkzjoxMTF47733cPbsWSiVSgQHB+PAgQPw9m6c1zhwgaurq6mLYHSDQlwxZdsVOFhKcDU+Eyk5xWhibY7Ofg6Y3dMfnvYyTs1n3Rgz4hvKiB+43rXb1CzNxSiQK+utUp9frIS7XfmpBsuijLiPjnfPSbgAXPoWcGiqGZjM2vTvT7mMpLbA4C+AJxHAoVlA4FCg/SuAkB+DVjZUtf4sHV+i6Vru2kq/9aW2wLidwB/vaEbG7zavYXRJV6uA3+ZpeqC0mWDq0nBWjT/lBQUFaNOmDb777rsK74+Li0OPHj0QGBiIM2fO4ObNm1i6dGmFcwkT4yksLDR1EYxOKBTgnQEBEAiAeX2bY+eMTlgztg3GdvCCl4MFpyr0QOPMiG8oI35Qq9WmLgKnWUpEKCypn5ZyNWNQMQZxNaPDU0bcR8c7aEawf3gW2DUOuH8cGLYBGLiKExV6oIqM3EOBsF8ApgZ2vay57p+YTK0+S9d3airpNW1xF5kBQ9dr9t3/LdK09vOZSgkcfhPw700V+mrU+FT54MGDMXjw4ErvX7JkCV566SV8+eWX2mX+/v61Kx0xmNzcXFMXwSRCve0RWk+DCBlaY82ITygjfqAKY9XEIiGU6vq5pr2wRAVLSfU9ACgj7mvUxzvGgLhTwOUtgFsbzcji1XV/NoEqMxKKgE4zgaDhwMnlgNROM3K61MZo5SMaNf4sJV0GHp4Gxmyr3RMKBECPBcDtw8D+acCozZoTBHyjUgCH3wAChwAho0xdGs4zaP83tVqN//3vf3j33XcxcOBAREREwM/PDx988EG5Lvql5HI55HK59u9G/SVSj9zd3U1dBFINyoj7KCN+MDNr5PP16sFMJECJUgWJuOoK+I4dO7BgwQJkZ2frtd28YgXsZNW//zXNaPr06cjOzsbhw4dr9DhSe432eJcSBZz8GPDqpJnnWsbdhgG9MrJ2AUZt0fQ42DsJ6PAKEMLTue0ZA7ITNZdCPLkBqEoMu30zS+CFRYCVYWd+qNFnKeeRZlyECbvqftlEyEjN2A/7pmgG0rPzqtv2jElZAhyeDQSPBIKHm7o0vGDQSn1aWhry8/Px+eef49NPP8UXX3yBY8eOYfTo0Th9+jR69uxZ7jGrV6/Gxx9/bMhikArk5ubCwcHB1MUgVaCMuI8y4geVSkXXbFfD0lyMgpLqK/XVSUhIgJ+fHyIiItC2bVsUlajgalP95XaVZfT89ojpNLrjHWPA1f8DEs4Do7dysmX+eTXKqGlPwLsLcHEDsDdMM7e9I8d70jIGZMQBieeBxEtA4TPNgHA+3TXXi5vJDPt82cnAgVeBF94GmvYy2Gb1zqmkUDOC/bD1mikSDcGrIzB8g2bAvX4fAx7tDLPd+qSUAwdnAa3HA4Evmbo0vGHwlnoAGDFiBBYuXAgAaNu2LS5evIgtW7ZUWKn/4IMPsGjRIu3fubm58PLi0ZkknsjPzzd1EUg1KCPuo4z4oSF17S4pKYFEYvh5py0lYqTlFcPewnDbLlGqIREJKxyv5PnX0ZAyaqga1fGuMFNz/bFnJ2DcT7xpxa5xRmJz4MXFQGY8cGIp4NIS6L4AMOPIuFeMAel3gcQLmkp8cTbg4A/4dgcGfFr/o/lbOQMT92qmkIs/B/T6ABDVvaqkV06MAb8vBLrP1wzGaEj2vpr9+tAbQOhkIGioYbdvSIpi4OBrQOgUoMVAU5eGVww6HKaTkxPEYjGCg4N1lgcFBSEpKanCx5ibm8PGxkbnRgyPTpRwH2XEfZQRP3C1+31eXh7CwsJgaWkJNzc3rFu3Dr169cKCBQu06/j6+uKTTz7B1KlTYWNjg1mzZgEADhw4gJCQEJibm8PX1xdr167V2bZAICjXNd3Ozg47duwAoGkBFwgEOHjwIHr37g07Gyv0f6EzLl26pPOYHTt2wNvbGxYWFhg1ahQyMjKqfE1+fn4AgNDQUJibiTBhpGbMnenTp2PkyJFYtWoV3N3dERAQoFPOshmVLWfZ7QkEAvTq1Uvn+dasWQM3Nzc4Ojpizpw5NJd6PWo0x7vES8D+qZqW365v8qZCD9QhIwc/YNx/AOdgzUB6cX8ZtmD6UquB1GjN2AX7pwG7xgIR/wWs3YGXvgImHwBe+lIzWJyxpueTWALDNwJNAoE9EzSt93WkV04X1gPubTUDwtUHmb2mYn/vGHDpO81JBK5RFGl6SrSfThX6WjBopV4ikaBjx46IjY3VWX7v3j34+PgY8qlIDT179szURSDVoIy4jzLiB6VSaeoiVGjRokW4cOECfvvtN5w4cQLnzp3DjRs3yq23Zs0atGnTBhEREVi6dCmuX7+OcePGYcKECYiOjsaKFSuwdOlSbUW4JpYsWYJ33nkHkZGRaOrfHBMnTtS+X1euXMGrr76KuXPnIjIyEr1798ann35a5fauXr0KADh58iSu3o7DoYMHtfedOnUKsbGxOHHiBH7//Xedx1WWUdntpaSk4GCZ7Z0+fRpxcXE4ffo0du7ciR07dtTqPSD6afDHO7UK+Psr4PoOYMJufnRLfk6dMhIINNcqT9wDPDgFHJgJ5KYYrnAVUSmBxzeAixuBfZOBPeOB6F80LdPDNwCTf9HMLhD4EmBh4ks/Wo/VTA/421tAzO/Vr1+FanO696fmMoPOs+v0PNUSSzQnLBRFwB+LNXlwRUkh8MsMoONrQLN+pi4NL9W4T0l+fj4ePHig/Ts+Ph6RkZFwcHCAt7c3Fi9ejPHjx+PFF19E7969cezYMRw5cgRnzpwxZLlJDRUVFZm6CKQalBH3UUY88PtCmGU/0oz8XN9s3ICh6/RaNS8vDzt37sTu3bvRt29fAMD27dsrHECpT58+ePvtt7V/h4WFoW/fvli6dCkAoEWLFrhz5w6++uorTJ8+vUZFfueddzBkyBAAwJKly9C9YygePHiAwMBAfPPNNxg0aBDeffdd7fNcvHgRx44dq3R7TZpoWs/s7R3g4OyCJk6W2vssLS3xww8/VHj5AKuklah0e46OjuXmdra3t8e3334LkUiEwMBADBkyBKdOncLMmTNr8A4QfTXo411eKnBkgWZU7Rfe4VXrfFkGycjcWlORTr0F/DZXMx2ezMAV6pICICVSM5q5aytNd/r2rwDmVoZ9HkNz9Acm7dMMnBj/N9B/Za0uVagyp/R7wNXvNSeWjLEfCgTAi+8Atw4AP0/TDKJoqOv3a6ukQFOh7zpXMxc9qZUaV+qvXbuG3r3/7RpSej38tGnTsGPHDowaNQpbtmzB6tWrMW/ePAQEBODAgQPo0aOH4UpNaox6SnAfZcR9lBEPDF0HqFSAyAiV+hp4+PAhFAoFOnXqpF1ma2ur7ZZeVocOHXT+jomJwYgRunMVd+/eHevXr4dKpYKoBq+1devW2v/7eXsC0AxyGxgYiJiYGIwapTttUNeuXaus1JcqUihhaa77k6JVq1aVjgdQm3ECQkJCdF6rm5sboqOja7wdop8Ge7x7cBK4sAEY/CXgHGjq0tSJQTNybQlM+hl4dFUzUJkhmcmAbnMNP7CdMYjNgUGfAbFHNT0LXloLODWr0SYqzakoWzOWw5gfNM9jTC3HADaemh4TIzYBth7Gff5S8jxNhb7HQsCnm2nK0EDUuFLfq1evSs+wl5oxYwZmzJhR60IRw0tNTYW1tYnPxJEqUUbcRxnxg0KhqFFFl2ssLS2rX+k5AoGg3HdzRdebl72WXWqmeY8MMWhdQYkK1lLdnxQVvY7ScpbNSN/r4p8fK0EgENCAe/WowR3vVArgr08Aeb6m9ZWPFcznGDwjoVAzQj4pL2Aw4Noa+H2BpkLcZoLeD60wJ7UK+HUO0P9jwNq14gfWN+/OmhPhh2drBiJ0a2Pc5y/O1VToX1ysKQupE4NeU0+4Sy438FlXYnCUEfdRRvxQ3YlnU2jatCnMzMwQHh6uXZaTk4N79+5V+9igoCBcuHBBZ9mFCxfQokULbcW4SZMmSEn593rY+/fvo7CwsMrtlo5Sr1Iz7fNcuXJFZ53Lly9XuY3SFvciuQLm4up/UpSWszSj58tZuj2VSlXttkj9alDHu6xEYPd4TdfyoV83iAo90MAy4gNbD2DCHiDzoaZCLtdv9oEKczr1MRA0DPBob+BC1pBDU2DsTuDvNcDvi4DkcOMMoleUDfw8Hej1PlXoDYQm8m0kmjY18PQYxOAoI+6jjPihPqaAqytra2tMmzYNixcvhoODA5ydnbF8+XIIhRVPAVfW22+/jY4dO+KTTz7B+PHjcenSJXz77bfYtGmTdp0+ffrg22+/RdeuXaFSqfDee+/pPQuAXKmpQM+bNw/du3fHmjVrMGLECBw/frzarvfOzs6QyWS4eOYUurRqAalUCltb20rXLy1n6WUIz5ezdHvHjh2Dp6dntdsj9afBHO/u/Apc36mpzNv7mro0BtVgMuITkRjo/aHmGvu9E4GBn2nGCahCuZxu7geYukat/fXKwgEY/x8gPRaI2guc/hTw7aGZJ97O2/DPV5ipGeW+z1JeDlDJVdRS30hUNqUg4Q7KiPsoI34oKSkxdREq9PXXX6Nr164YOnQo+vXrh+7duyMoKAhSadUDL7Vr1w779+/H3r170bJlSyxbtgwrV67UGSRv7dq18PLywgsvvIBJkybhnXfegYWFhV7lKi7RdGHv0qULtm7dim+++QZt2rTBn3/+iY8++qjKx4rFYqz6ci1279wGd3f3ctf+P6+0nL169aqwnGKxGBs2bMD333+v1/ZI/eH98U5RBPzvbeDRNc3c4w2sQg80gIz4zO9F4OXtwJnPgatbq2zd1snp8Q3NiaZ+HxuhkDXUJADotxyYfAjw7KR5bbvHAxG7NNe+G0JhpqbLfb8VVKE3MAHjWD/F3Nxc2NraIicnh+asN6Bbt26hZcuWpi4GqQJlxH2UETcUFxcjPj4efn5+FVaIi4qKIJNxv3ttQUEBPDw8sHbtWrz66qsmKQNjDIkZhfB1qvl1/KUSnhXA28ECQqH+IzcbK6Pq9hVSOV4f79JjNVN2dZsHNG+402PxOqOGQq0GLn8HPIkAhqzVzAf/HG1OeU81LdTj/1Phepwkzwfu/q45EWFuA7QeBzTtVbsZZgqeaSr0Az/TDMzIEQ2l7knd7xuJZs1qNlInMT7KiPsoI34wNzfyKMJ6ioiIwN27d9GpUyfk5ORg5cqVAGDS1ujSrv9qxiCsxXRKKjWDQIAaVegB7mZE/sXL4x1jQOQuzbzio77XTDvZgPEyo4ZGKAS6vQU8ug7sm6LpUv7cNeLNmjXTzCjw65uVVvw5y9xKc5lAmwlAziPNpQMXN2gG1WszEXAO0m87+WmaExqDvgBcguu3zI0Udb9vJB4+fGjqIpBqUEbcRxnxA5cHj1qzZg3atGmDfv36oaCgAOfOnYOTk5NJyySTiFBUUruB6fLlSliZ17x9gMsZEQ3eHe/kecDhN4DcFGDCrgZfoQd4mFFD5tles9+FbwXOfa1pwf/Hw7g4Tc+RjjM1Xdz5ytYTeGERMOUwEDwCuLYN+M9o4PIWTSt8ZfJSNRX6l9ZQhb4eUUt9I0HT/nAfZcR9lBGpi9DQUFy/ft3UxSjH0lyMAnn5eeb1kVesgLM1dWtviHh1vHsSCZxYCvT6oFHNdc2rjBoDqS0weitwY6dm/vdh6wErZ9jd/xlw9AECBpm6hIYhEGhG7fdoDyhLgPt/An+8oxn8r+UYoMUgQPxPb6zcJ8DBWcDQ9YAT9SypT1SpbyQCAnh8ZrCRoIy4jzLiB+raXTMWZiI8y6t5yzljDAoVg0SPqeyeRxlxHy+Od4wBV7YASZc103JZOJi6REbFi4waG4EAaD9dM9DcgVcB/z5wVT4Cemw1dcnqh1gCBA3V3AozgVsHgL2TNKPmtxis6ao/7BvA0d/UJW3wqPt9IxEbG2vqIpBqUEbcRxnxA3XtrhmhUAAGoKbj5hYrVJCa1e5nBGXEfbw43uWlAAIhMHZHo6vQAzzJqLFyCQYm7gMgQEyz2ZrKfkNn4QB0mglMPgB0fgNIiQJGfEsVeiOhSj0hhBDSyMnMhChW1Oy6+rxiJaylZtWvSEh9sXEHOr/eOCpMhH8kFkCPBWDiRniJUpMWQM/FDXIqSa4yeKVepVJh6dKl8PPzg0wmg7+/Pz755JMatwAQw6IuWtxHGXEfZcQP1LW75izMxSiQ16xSX1CigoWkFtMagTLiAzrecR9lxA+UEzEGg1fqv/jiC2zevBnffvstYmJi8MUXX+DLL7/Exo0bDf1UpAaoixb3UUbcRxnxA3XtrjlLiQgFJUq911eq1BAJBLWaBg+gjPiAjnfcRxnxA+VEjMHgA+VdvHgRI0aMwJAhQwAAvr6+2LNnD65evVrh+nK5XOfLPTc319BFIoQQQkgVREIh1ExzXb1Aj4p6vlwJKymNtUsIIYRwgcFb6rt164ZTp07h3r17AICoqCicP38egwcPrnD91atXw9bWVnvz8vIydJEIqOsPH1BG3EcZ8QN17dbw9fXF+vXrtX8LBAIcPny40vXNxULIlVVPkVW6Dc319LWv1FNG3EfHO+6jjPiBciLGYPBK/fvvv48JEyYgMDAQZmZmCA0NxYIFCxAWFlbh+h988AFycnK0t+TkZEMXiYC6/vABZcR9lBE/UNfuiqWkpFR6gh3QdMEv/KcL/ooVK9C2bdsKtzFo0CAo1Qxmotr/hKCMuI+Od9xHGfED5USMweB95/bv349du3Zh9+7dCAkJQWRkJBYsWAB3d3dMmzat3Prm5uZ0xt4IhEKa6IDrKCPuo4yIsZWUlEAikRhkW66urlXeb2EuRmpOMRwsq95GgVwJC8MUiXAYHe+4jzLiB8qJGIPB97LFixdrW+tbtWqFKVOmYOHChVi9erWhn4rUQNOmTU1dBFINyoj7KCN+4PKJ4l69emHu3LmYO3cubG1t4eTkhKVLl2pniPH19cUnn3yCqVOnwsbGBrNmzQIAnD9/Hi+88AJkMhm8vLwwb948FBQUaLeblpaGYcOGQSaTwc/PD7t27Sr33M93v3/06BEmTpwIBwcHWFpaomvnTrgWfhU7duzAxx9/jKioKAgEAggEAuzYsUO7jf2/HNR2vY+OjkafPn0gk8ng6OiIWbNmIT8/X/sc06dPx8iRI7FmzRq4ubnB0dERc+bM0fmRu2nTJjRv3hxSqRQuLi54+eWXDfZ+k9qj4x33UUb8QDkRYzB4pb6wsLDcGSmRSAS1uurr9Ej9evDggamLQKpBGXEfZcQPXO/avXPnTojFYly9ehXffPMNvv76a/zwww/a+9esWYM2bdogIiICS5cuRVxcHAYNGoQxY8bg5s2b2LdvH86fP4+5c+dqHzN9+nQkJyfj9OnT+OWXX7Bp0yakpaVVWob8/Hz07NkTjx8/xm+//YaoqCi8++67EIJh1JixePvttxESEoKUlBSkpKRg/Pjx2seWqNSQmYlQUFCAgQMHwt7eHuHh4fj5559x8uRJnXIBwOnTpxEXF4fTp09j586d2LFjh/b1Xrt2DfPmzcPKlSsRGxuLY8eO4cUXXzTUW03qgI533EcZ8QPlRIzB4N3vhw0bhlWrVsHb2xshISGIiIjA119/jRkzZhj6qUgNiMU0SjHXUUbcRxlx3yeXPkFKfgpEwtrNn14TzhbOWNp1aY0f5+XlhXXr1kEgECAgIADR0dFYt24dZs6cCQDo06cP3n77be36r732GsLCwrBgwQIAQPPmzbFhwwb07NkTmzdvRlJSEo4ePYqrV6+iY8eOAIAff/wRQUFBlZZh9+7dSE9PR3h4OBwcHAAAzZo1Q1ZBCZgAsLKyglgsrrDLvuif1vvdu3ejuLgYP/30EywtNX32v/32WwwbNgxffPEFXFxcAAD29vb49ttvIRKJEBgYiCFDhuDMmTOYM2cOkpKSYGlpiaFDh8La2ho+Pj4IDQ2t8XtKDI+Od9xHGfED5USMweB72caNG7F06VK8+eabSEtLg7u7O15//XUsW7bM0E9FasDb29vURSDVoIy4jzLivqVdl0KlUkEkqv9KfW116dJFZ9q4rl27Yu3atVCpVACADh066KwfFRWFmzdv6nSpZ4xBrVYjPj4e9+7dg1gsRvv27bX3BwYGws7OrtIyREZGIjQ0VFuhL2VpLkJ6XtU9HWQSTW+8mJgYtGnTRluhB4Du3btDrVYjNjZWW6kPCQnRycPNzQ03b94EAPTv3x8+Pj5o2rQpBg0ahEGDBmHUqFGwsLCosgyk/tHxjvsoI36gnIgxGLz7vbW1NdavX4/ExEQUFRUhLi4On376qcEG+iG18/DhQ1MXgVSDMuI+yogfSkpKTF2EOilbSQY0XeVff/11REZGam9RUVG4f/8+/P39a/UcMpmswuVmIiFKVKzKx0rNanbCxMzMTOdvgUCgPYFhbW2NGzduYM+ePXBzc8OyZcvQpk0bZGdn1+g5iOHR8Y77KCN+oJyIMdBwjI0ElweOIhqUEfdRRvxQthWci65cuaLz9+XLl9G8efNKexe0a9cOd+7cQbNmzcrdJBIJAgMDoVQqcf36de1jYmNjq6wYt27dGpGRkcjMzNRZLhAIIBIKIBabaSvepdT/DOYn+mfcnKCgIERFRekM2HfhwgUIhcIazcssFovRr18/fPnll7h58yYSEhLw119/6f14Uj/oeMd9lBE/UE7EGKhS30hUN5URMT3KiPsoI354vmWYa5KSkrBo0SLExsZiz5492LhxI+bPn1/p+u+99x4uXryIuXPnIjIyEvfv38evv/6qHZAuICAAgwYNwuuvv44rV67g+vXreO211yptjQeAiRMnwtXVFSNHjsSFCxfw8OFDHDhwAJcuXYKlRARXTy/Ex8cjMjISz549g1wuR6FcqbONsLAwSKVSTJs2Dbdu3cLp06fx1ltvYcqUKdqu95UpPfHy+++/Y8OGDYiMjERiYiJ++uknqNXqGp0UIPWDjnfcRxnxA+VEjIEq9Y1EYmKiqYtAqkEZcR9lxA9c734/depUFBUVoVOnTpgzZw7mz5+vnbquIq1bt8bZs2dx7949vPDCCwgNDcWyZcvg7u6uXWf79u1wd3dHz549MXr0aMyaNQvOzs6VblMikeDPP/+Es7MzXnrpJbRq1Qqff/45RCIRLM3F6Dd4OAYNGoTevXujSZMm2LNnD3KLdSv1FhYWOH78ODIzM9GxY0e8/PLL6Nu3L7799ttq34PSKfzs7Oxw8OBB9OnTB0FBQdiyZQv27NmDkJCQardB6hcd77iPMuIHyokYg4CVfrNyRG5uLmxtbZGTkwMbGxtTF6fBiIuLq/W1l8Q4KCPuo4y4obi4GPHx8fDz84NUKq3w/oqWc0GvXr3Qtm1brF+/3tRFqRRjDAkZhfBz0r22/2F6PvycLA1yeYOxMqpuXyGVo+Md91FG/EA5cVtDqXtSS30j4eTkZOoikGpQRtxHGfEDTR9UNwKBAEIBoFL/e85frlTBXCw02HgFlBH30fGO+ygjfqCciDFQpb6RSE5ONnURSDUoI+6jjPhBoVCYugi8ZyERo7Dk3+72ecVKWEsNN1YBZcR9dLzjPsqIHygnYgx0qryRsLKyMnURSDUoI+6jjPhBKOTu+eozZ86Yugh6sTQXIbfo34p8frESXg6GmzueyxkRDTrecR9lxA+UEzEG+lZtJPh8jUhjQRlxH2XED5VNDUf0JzUToVihmdKutBu+SGi4qQIpI+6j4x33UUb8QDkRY6BKfSPx5MkTUxeBVIMy4j7KiFsqG+eVunbXnfCfa+fVjKFAroSV1LAd+4yVEcfGAuYVOt5xH2XED5QTMQaq1DcSdJaQ+ygj7qOMuKF0HvrCwsIK76eu3YYhk4hQVKJCXrEC1gau1Bsro9LpDalnQM3R8Y77KCN+oJyIMdTbNfXfffcdvvrqK6SmpqJNmzbYuHEjOnXqVF9PR6phYWG4ayFJ/aCMuI8y4gaRSAQ7OzukpaUB0ORSdlR2hUJBLbQGIGYKZOfLUShXgsmEKFYarnXdGBmp1Wqkp6fDwsKCRtuvBTrecR9lxA+UEzGGevmW27dvHxYtWoQtW7agc+fOWL9+PQYOHIjY2Fg4OzvXx1OSaqSmptKUGhxHGXEfZcQdrq6uAKCt2JdVUlICiURi7CI1OIwxpOXJITUTQZljuJHvAeNlJBQK4e3tbbCp+BoTOt5xH2XED5QTMYZ6qdR//fXXmDlzJl555RUAwJYtW/C///0P27Ztw/vvv6+zrlwuh1wu1/6dm5tbH0Vq9Ozt7U1dBFINyoj7KCPuEAgEcHNzg7Ozc7nrs58+fQoXFxcTlaxhWbf7Bl7p7gc/H8Pu+8bKSCKR0OUYtUTHO+6jjPiBciLGYPBKfUlJCa5fv44PPvhAu0woFKJfv364dOlSufVXr16Njz/+2NDFIM8pvQaVcBdlxH2UEfeIRKJy10vLZDJIpVITlahhmTcgBIFu1jATGbZiTBlxHx3vuI8y4gfKiRiDwU9fP3v2DCqVqtwZeBcXF6SmppZb/4MPPkBOTo72lpycbOgiEVTcRZVwC2XEfZQRP1BOhtPK09bgFXqAMuIDyoj7KCN+oJyIMZh85Bhzc3OYm5ubuhgNnqOjo6mLQKpBGXEfZcQPlBP3UUbcRxlxH2XED5QTMQaDn353cnKCSCTC06dPdZY/ffpUO7ARIYQQQgghhBBC6s7gLfUSiQTt27fHqVOnMHLkSACaaWVOnTqFuXPnVvv40iluaMA8w0pMTISlpaWpi0GqQBlxH2XED5QT91FG3EcZcR9lxA+UE7eV1jn5PhVuvXS/X7RoEaZNm4YOHTqgU6dOWL9+PQoKCrSj4VclLy8PAODl5VUfRSOEEEIIIYQQQrQyMjJga2tr6mLUWr1U6sePH4/09HQsW7YMqampaNu2LY4dO6bX9DXu7u5ITk6GtbU1zStrILm5ufDy8kJycjJsbGxMXRxSAcqI+ygjfqCcuI8y4j7KiPsoI36gnLgvJycH3t7ecHBwMHVR6qTeBsqbO3euXt3tnycUCuHp6VkPJSI2NjZ0QOE4yoj7KCN+oJy4jzLiPsqI+ygjfqCcuE8oNPxML8bE79ITQgghhBBCCCGNGFXqCSGEEEIIIYQQnqJKfSNgbm6O5cuXw9zc3NRFIZWgjLiPMuIHyon7KCPuo4y4jzLiB8qJ+xpKRgLG9/H7CSGEEEIIIYSQRopa6gkhhBBCCCGEEJ6iSj0hhBBCCCGEEMJTVKknhBBCCCGEEEJ4iir1hBBCCCGEEEIIT1GlnhBCCCGEEEII4Smq1BNCCCGEEEIIITxFlXpCCCGEEEIIIYSnqFJPCCGEEEIIIYTwFFXqCSGEEEIIIYQQnqJKPSGEEEIIIYQQwlNUqSeEEEIIIYQQQniKKvWEEEIIIYQQQghPUaWeEEIIIYQQQgjhKarUE0IIIYQQQgghPEWVesIZvXr1woIFC0xdjHJ27NgBOzu7KtdZsWIF2rZtW+vnEAgEOHz4cK0fT/ilrvuLoejzmfP19cX69etrtX19PjuEH6ZPn46RI0dWuU5djuFnzpyBQCBAdnZ2rR5PTE+fY0Vdvuu4ctxszPTJQJ9jRWUSEhIgEAgQGRlZq8cT0phRpZ5wxsGDB/HJJ59o/65LZcKQxo8fj3v37pm6GBAIBEhISADw7xff87fJkyfrPGbnzp3o2LEjLCwsYG1tjZ49e+L3338vt22VSoV169ahVatWkEqlsLe3x+DBg3HhwgWd9Xbs2KF9LpFIBHt7e3Tu3BkrV65ETk6Ozrrp6el444034O3tDXNzc7i6umLgwIHltlmZ119/Hf7+/pDJZGjSpAlGjBiBu3fv1uAd05S3devWkEqlcHZ2xpw5c3Tu379/P9q2bQsLCwv4+Pjgq6++qnRbFy5cgFgsLveDZvr06VixYkWNylUfalMpev4zZwo7duxAr169tH+vWLGiwn375MmT2nUyMzOxYMEC+Pj4QCKRwN3dHTNmzEBSUlK57ScnJ2PGjBlwd3eHRCKBj48P5s+fj4yMDJ31evXqpX0uc3NzeHh4YNiwYTh48GC5bZ49exZ9+vSBg4MDLCws0Lx5c0ybNg0lJSXVvt7Y2Fj07t0bLi4ukEqlaNq0KT766CMoFAqd92D69Ol6vHu1U5sfzt988w127NhRb2XSx5kzZ+Dr66v9u+zxqOzthx9+0K5TVFSE5cuXo0WLFjA3N4eTkxPGjh2L27dvl9u+vvvV9OnTtc9lZmYGFxcX9O/fH9u2bYNardZZNyoqCsOHD4ezszOkUil8fX0xfvx4pKWlAfg3i9riyvckAISHh2PWrFkmLUPZz05F+0bZ24oVK/DHH39AIpHgxo0bOttZu3YtnJyckJqaWu1zrl69Gh07doS1tTWcnZ0xcuRIxMbG6qzj6+uLM2fO1Oo11baSXB8nQd555x2cOnXKoNusqbKfmbKfxYpuvr6+KCgogL+/PxYtWlRuOzY2Nti6dSuA8scXQviGKvWEMxwcHGBtbW3qYpQjk8ng7Oxs6mJU6OTJk0hJSdHevvvuO+1977zzDl5//XWMHz8eN2/exNWrV9GjRw+MGDEC3377rXY9xhgmTJiAlStXYv78+YiJicGZM2fg5eWFXr16lWtVsbGxQUpKCh49eoSLFy9i1qxZ+Omnn9C2bVs8efJEu96YMWMQERGBnTt34t69e/jtt9/Qq1evcpWpyrRv3x7bt29HTEwMjh8/DsYYBgwYAJVKpdfjv/76ayxZsgTvv/8+bt++jZMnT2LgwIHa+48ePYqwsDDMnj0bt27dwqZNm7Bu3Tqd96ZUdnY2pk6dir59++r13HzB1c9cSEiIzn6dkpKCF198EYCm4tWlSxecPHkSW7ZswYMHD7B37148ePAAHTt2xMOHD7XbefjwITp06ID79+9jz549ePDgAbZs2YJTp06ha9euyMzM1HnemTNnIiUlBXFxcThw4ACCg4MxYcIEnYrKnTt3MGjQIHTo0AF///03oqOjsXHjRkgkEr32TTMzM0ydOhV//vknYmNjsX79emzduhXLly830LtXP2xtbTnZ66L0eFT2FhYWBgCQy+Xo168ftm3bhk8//RT37t3DH3/8AaVSic6dO+Py5cva7dRkvwKAQYMGISUlBQkJCTh69Ch69+6N+fPnY+jQoVAqlQA0Jzb79u0LBwcHHD9+HDExMdi+fTvc3d1RUFBgvDdJD/qckKpOkyZNYGFhYYDSGEbZfWL9+vXl9pV33nkHL730EqZOnYqpU6dCLpcD0HzGP/roI3z33XdwdXWt9nnOnj2LOXPm4PLlyzhx4gQUCgUGDBjAuYwNwcrKCo6OjqYuhtY333yjkykAbN++Xft3eHg4LC0tsX37dmzcuBHnzp0DoPnd88orr6B79+6YOXOmKV8CIYbDCOGInj17svnz52v/D0DnVurcuXOsR48eTCqVMk9PT/bWW2+x/Px87f0+Pj7sk08+YVOmTGGWlpbM29ub/frrrywtLY0NHz6cWVpaslatWrHw8HC9yrV9+3Zma2urs2z16tXM2dmZWVlZsRkzZrD33nuPtWnTptavHQDbtGkTGzRoEJNKpczPz4/9/PPP5daJj49njDEWHx/PALCIiIgKt3fp0iUGgG3YsKHcfYsWLWJmZmYsKSmJMcbY3r17GQD222+/lVt39OjRzNHRUfv+VvReMMbY06dPmZOTEwsLC2OMMZaVlcUAsDNnzuj7FlQrKiqKAWAPHjyodt3MzEwmk8nYyZMnK11n4sSJ7OWXX9ZZtmHDBubp6cnUarXO8vHjx7OPPvqILV++vFzO06ZNY8uXL6+yPPrsL1u3bmWBgYHM3NycBQQEsO+++057X2nee/bsYV27dmXm5uYsJCRE+/6W3l/2Nm3atCrLxJjuZ44xTY5Dhw5lUqmU+fr6sv/+97/Mx8eHrVu3rtptVaR0fzl06BBr1qwZMzc3ZwMGDNDue6Xr9OzZU/t3Re9xWbNnz2aWlpYsJSVFZ3lhYSHz8PBggwYN0i4bNGgQ8/T0ZIWFhTrrpqSkMAsLCzZ79mztsuffi1Lbtm1jANiJEycYY4ytW7eO+fr66vPy9bZw4ULWo0cP7d/Lly+vNr/z58+znj17MplMxuzs7NiAAQNYZmYmY4yxo0ePsu7duzNbW1vm4ODAhgwZovO5eX5fKfv+V2batGlsxIgR2r/z8/O1x1hXV1e2Zs2aSt9DfZw+fZoBYL///jtr1aoVMzc3Z507d2bR0dE66/j4+Gj/rux4VOrzzz9nAoGARUZG6ixXqVSsQ4cOLDg4WPtZr8l+9fx7UerUqVMMANu6dStjjLFDhw4xsVjMFApFpWUs/exWRq1Ws+XLlzMvLy8mkUiYm5sbe+uttxhjVX9P/vLLLyw4OJhJJBLm4+PD1qxZo7NdHx8ftnLlSjZlyhRmbW2t3d+q+36tyvPHinv37rEXXniBmZubs6CgIPbnn38yAOzQoUN6be95pceGLVu2ME9PTyaTydjYsWNZdna2zjoVfXaq2ldyc3OZj48Pe++995hCoWAdOnRgY8eOrVUZGWMsLS2NAWBnz57VLvPx8WGnT5+u9DE///wza9myJZNKpczBwYH17duX5efns+XLl5fLuHQ77777LmvevDmTyWTMz8+PffTRR6ykpET7ep9/3Pbt2xljmu/nV199lTk5OTFra2vWu3fvcp+Ryjx/fFYqlWzhwoXaY83ixYvZ1KlTK/x86KO677qy61Skqv1r4cKFzN/fn+Xn57N169YxOzs79ujRI+39zx9fCOEbaqknnHTw4EF4enpi5cqVOmdg4+LiMGjQIIwZMwY3b97Evn37cP78ecydO1fn8evWrUP37t0RERGBIUOGYMqUKZg6dSomT56MGzduwN/fH1OnTgVjrMZl279/P1asWIHPPvsM165dg5ubGzZt2qSzzq5du2BlZVXlrfSMcamlS5dizJgxiIqKQlhYGCZMmICYmJgalw8A9uzZAysrK7z++uvl7nv77behUChw4MABAMDu3bvRokULDBs2rMJ1MzIycOLEiSqfz9nZGWFhYfjtt9+gUqm0r/Hw4cPa1o+6KCgowPbt2+Hn5wcvL69q1z9x4gTUajUeP36MoKAgeHp6Yty4cUhOTtauI5fLIZVKdR4nk8nw6NEjJCYmapdt374dDx8+rHVLqr77y7Jly7Bq1SrExMTgs88+w9KlS7Fz506d9RYvXoy3334bERER6Nq1K4YNG4aMjAx4eXlp84yNjUVKSgq++eabGpd1+vTpSE5OxunTp/HLL79g06ZN2m7CpQYPHlzlfh0SEqKzfmFhIVatWoWffvoJFy5cQHZ2NiZMmFDjsgGAWq3G3r17ERYWVq4FTSaT4c0338Tx48eRmZmJzMxMHD9+HG+++SZkMpnOuq6urggLC8O+ffuqPQZMmzYN9vb22m74rq6uSElJwd9//12r1/C8Bw8e4NixY+jZs6fej4mMjETfvn0RHByMS5cu4fz58xg2bJi2p0BBQQEWLVqEa9eu4dSpUxAKhRg1apS2a/jVq1cB/NvTp6JLDKqzePFinD17Fr/++iv+/PNPnDlzplwX5tmzZ1d7HKxou2vXrkV4eDiaNGmCYcOG6VyaUBO7d+9G//790aZNG53lQqEQCxcuxJ07dxAVFVWj/aoqffr0QZs2bXT2FaVSiUOHDtXquwYADhw4gHXr1uH777/H/fv3cfjwYbRq1QpA5d+T169fx7hx4zBhwgRER0djxYoVWLp0abnLJ9asWYM2bdogIiICS5cu1fv7VR9qtRqjR4+GRCLBlStXsGXLFrz33nvl1gsJCaly/xg8eLDO+g8ePMD+/ftx5MgRHDt2DBEREXjzzTdrXL6yrK2tsW3bNqxduxZhYWFITk7G5s2ba7290kvRHBwc9Fo/JSUFEydOxIwZM7Q95UaPHg3GGN555x2MGzdO2zMkJSUF3bp105Z7x44duHPnDr755hts3boV69atA6C5bPDtt9/W6fU0fvx4AMDYsWORlpaGo0eP4vr162jXrh369u1b7f5dkbVr12LHjh3Ytm0bzp8/j8zMTBw6dEhnnc8++6za48Dzl7hU9l1XF6tWrYJYLMbkyZPx4YcfYuPGjfDw8KjTNgnhFNOeUyDkX8+38lTUQvjqq6+yWbNm6Sw7d+4cEwqFrKioSPu4yZMna+9PSUlhANjSpUu1y0pbsp9vlanI82f4u3btyt58802ddTp37qxz9jo3N5fdv3+/ylvZ1kMAOq2Gpdt84403KixT6ZlqmUzGLC0ttbcbN24wxjQtlFW1dtrY2Gi3HRgYWOlZ9czMTAaAffHFFxW+F2Vt3ryZAWBPnz5ljGlaiuzt7ZlUKmXdunVjH3zwAYuKiqq0TBX57rvvmKWlJQPAAgIC9GqlZ0zTMm5mZsYCAgLYsWPH2KVLl1jfvn1ZQEAAk8vljDHGvv/+e2ZhYcFOnjzJVCoVi42NZYGBgQwAu3jxImNM09Lk7OzMYmNjGWPVtyJXRJ/9xd/fn+3evVtnnU8++YR17dqVMfZv3p9//rn2foVCwTw9PbXZlLZ0ZmVl6V22sp+52NhYBoBdvXpVe39MTAwDoPM5fPToUZX7dUJCgnbd0taiy5cvl9vmlStXKizT8uXLmVAo1NmvO3bsyBhjLDU1tVx5yjp48KB225cvX66y1ebrr7/W2V+ramXu3LkzGzx4MGNM0zI1ffp0BoC5urqykSNHso0bN7KcnJwKH1uZ0lYoAGzWrFlMpVLp/diJEyey7t27671+eno6A6Bt9a6up09FyrZO5+XlMYlEwvbv36+9PyMjg8lksnI9P6o7DpYq3X/37t1bbpv79u2rsEyl+1fZfcXFxUV7v1QqrTTTGzduMABs3759Ndqvnn8vnjd+/HgWFBSk/fvDDz9kYrGYOTg4sEGDBrEvv/ySpaamVvjYiqxdu5a1aNFC2wL7vIq+JydNmsT69++vs2zx4sUsODhY53EjR47UWUef79eqlC3L8ePHmVgsZo8fP9bef/To0XKfyYSEhCr3j7ItqcuXL2cikUhn2dGjR5lQKKz2u7y6Xh2MMTZhwgTtPlFbKpWKDRkypEafz+vXrzMAOsfOsqra38r66quvWPv27bV/V/R9de7cOWZjY8OKi4t1lvv7+7Pvv/++2ud4fptubm7syy+/1P5d+r1UtrwZGRnVHgdKe7Po811XlaqO+YwxduzYMQZAezwnpCER1/tZA0IMKCoqCjdv3sSuXbu0yxhjUKvViI+PR1BQEACgdevW2vtdXFwAQNu6UXZZWlqaXtfMlRUTE4PZs2frLOvatStOnz6t/dva2rrG1yp37dq13N/VDWS1b98+7WsGoNOKzWrQMlSTdavbRukANmPGjMGQIUNw7tw5XL58GUePHsWXX36JH374Qe9BwMLCwtC/f3+kpKRgzZo1GDduHC5cuFCuhf15arUaCoUCGzZswIABAwBoei+4urri9OnTGDhwIGbOnIm4uDgMHToUCoUCNjY2mD9/PlasWAGhUAiVSoVJkybh448/RosWLWr9vlS3vxQUFCAuLg6vvvqqzrV9SqUStra25R5XSiwWo0OHDrXuzVFROcViMdq3b69dFhgYWO466pq2bIjFYnTs2LHcNmNiYtCpU6cKHxMQEIDffvtN+7e5ubnO/abYt0v3a5FIhO3bt+PTTz/FX3/9hStXruCzzz7DF198gatXr8LNzU2vbe7btw95eXmIiorC4sWLsWbNGrz77rt6PTYyMhJjx46t9P779+9j2bJluHLlCp49e6ZtoU9KSkLLli31eo6qxMXFoaSkBJ07d9Yuc3BwQEBAgM56zs7ONR6PpOw+XrrNqvZxa2trnR4CQqFuB0RT7iuApnVw0aJF2n1ly5Yt+Oyzz/D333/rfCdVZuzYsVi/fj2aNm2KQYMG4aWXXsKwYcMgFlf+8y0mJgYjRozQWda9e3esX78eKpUKIpEIANChQweddfT9ftVHTEwMvLy84O7url32/HccAPj4+Oi9TQDw9vbWOQZ17doVarUasbGxNf4uL+vx48c4duwYLCwscO7cOYwbN65W25kzZw5u3bqF8+fP6/2YNm3aoG/fvmjVqhUGDhyIAQMG4OWXX4a9vX2Vj9u3bx82bNiAuLg45OfnQ6lUwsbGpsrHREVFIT8/v9x18UVFRYiLi9O7zICmR0JKSorOcaD0e6nsZ8nBwUHvXgul6uu77scff4SFhQWio6ORk5NT7juWED6j7veEV/Lz8/H6668jMjJSe4uKisL9+/fh7++vXc/MzEz7/9IfWBUte36kYkOpTff72vDy8kKzZs20t9LKT4sWLfDw4cMKBz968uQJcnNztRXVFi1aVPplWbpcn0ptTEwMbGxsdH4sSKVS9O/fH0uXLsXFixcxffr0GnVjt7W1RfPmzfHiiy/il19+wd27d8t17atIacUqODhYu6xJkyZwcnLSdvMTCAT44osvkJ+fj8TERKSmpmormU2bNkVeXh6uXbuGuXPnQiwWQywWY+XKlYiKioJYLMZff/2l9+uoSn5+PgBg69atOvv1rVu3dAby4oqadr+vDYlEorNfl56satKkifaEQEViYmIgEAi0jxMIBFWua29vjyZNmlRZFpVKhfv378PPz09nuYeHB6ZMmYJvv/0Wt2/fRnFxMbZs2aL3a/Ty8kJwcDAmTpyIzz//HCtWrNB7EMjnLyd43rBhw5CZmYmtW7fiypUruHLlCgDDDIZWE7Xpfl9TQqFQZ19p2rSp9j59j2012a+qExMTU25fcXR0xNixY7FmzRrExMTA3d0da9as0ev1eXl5ITY2Fps2bdJeCvDiiy/W+pKEsiwtLXX+1vf71ZBq2v2+vsycORPt27fH77//js2bN+Ps2bM13sbcuXPx+++/4/Tp0/D09NT7cSKRCCdOnMDRo0cRHByMjRs3IiAgAPHx8ZU+5tKlSwgLC8NLL72E33//HREREViyZEm1n/H8/Hy4ubnpZBwZGYnY2FgsXrxY7zLXRG2639eHffv24ffff8fFixdhbW2NhQsX1vtzEmJM1FJPOKui0aTbtWuHO3fu6PXjqr4EBQXhypUrmDp1qnbZ85Wv4cOH65y9rsjzLZ6XL18ut83Q0NBalXHChAnYsGEDvv/+e7z11ls6961ZswZmZmYYM2aMdt1JkybhyJEj5a6rX7t2LRwdHdG/f/8qny8tLQ27d+/GyJEjy7WUlRUcHFzrOYoZY2CM6XWNfvfu3QFori8v/XGVmZmJZ8+elWsZEolE2iz27NmDrl27okmTJlCr1YiOjtZZd9OmTfjrr7/wyy+/lPvhXpnq9hcXFxe4u7vj4cOH2lG7K3P58mXtKPBKpRLXr1/XXu8qkUgAQO+K4fMCAwO12yxtWY+NjS03Rd4PP/yAoqKiSrdT9uRZaTmvXbumPWFSus2atPqVEgqFGDduHHbt2oWVK1fqtMwVFRVh06ZNGDhwoLZVqH///ti0aRMWLlyoUxFOTU3Frl27MHXq1GqnE9u5cyeysrK0n5eK2Nvbw83NrdajXZf2LFGr1dpW1Kq0bt0ap06dwscff1zuvoyMDMTGxmLr1q144YUXAKBcq2Fd9xV/f3+YmZnhypUr8Pb2BgBkZWXh3r17OmMDrFy5Eu+8806Ntn358uVy26zNvgJojm1LlixBVFSUznX1arUa69atQ3BwMNq0aQOBQFCj/aoyf/31F6Kjo6usLEgkEvj7+9doX5HJZBg2bBiGDRuGOXPmIDAwENHR0WjXrl2F35NBQUHlpg69cOECWrRoUeX+Zcjv16CgICQnJyMlJUV7krWik5R//PFHlSconj+BlZSUhCdPnmh7AFy+fBlCobBcL5Ga+OGHH3D+/HlER0fDx8cHb7zxBmbMmIGbN2+WO/FREcYY3nrrLRw6dAhnzpzR+7uhLIFAgO7du6N79+5YtmwZfHx8cOjQISxatKjCjC9evAgfHx8sWbJEu6zsWDBA5b+hUlNTIRaL6zx9m62tLdzc3HDlypVy30vt2rXTrjd79uxqez6U7dEBVP1dVxtPnz7FnDlz8Omnn6JNmzbYsWMHunXrhrFjxxrtxBEh9c4EXf4JqdDz17T279+fDR8+nD169Iilp6czxjQjoMtkMjZnzhwWERHB7t27xw4fPszmzJmjfVxF1xjiueusanJN6fPX4u3du5dJpVK2bds2Fhsby5YtW8asra3rPPq9k5MT+/HHH7XbFAqF7Pbt2xWur0/558+fz8zNzdmaNWvYgwcPWExMDFuyZAkTCoU6o+Kr1Wo2atQoZm9vz3744QcWHx/PoqKi2KxZs5hYLNZ537Zv385sbGxYSkoKe/LkCbtz5w778ccfmb+/P2vatCl78uQJY4yxZ8+esd69e7P//Oc/LCoqij18+JDt37+fubi4sBkzZlT7fsTFxbHPPvuMXbt2jSUmJrILFy6wYcOGMQcHB+010NUZMWIECwkJYRcuXGDR0dFs6NChLDg4WHttanp6Otu8eTOLiYlhERERbN68eUwqlVZ6rTdjtbumXp/9ZevWrUwmk7FvvvmGxcbGsps3b7Jt27axtWvXMsb+zdvb25sdPHiQxcTEsFmzZjErKyvtZ+PRo0dMIBCwHTt2sLS0NJaXl1dt2Z7/zA0aNIiFhoayy5cvs2vXrrEePXowmUxWp9HvzczMWKdOnbTb7NKlC+vSpUulj6nuPX727Bnz9/dnLVu2ZH/88QdLSkpiZ8+eZS+88AJzdnZmcXFx2nXv3bvHnJyc2AsvvMDOnj3LkpKS2NGjR1nLli1Z8+bNWUZGhs57MXPmTJaSksKSk5PZpUuX2LvvvsvMzMx0xrbYsmULmz17Njt+/Dh78OABu3XrFnv33XeZUCjUa7aH//73v2zfvn3szp07LC4uju3bt4+5u7trZ47QR2xsLJNIJOyNN95gUVFRLCYmhm3atImlp6czlUrFHB0d2eTJk9n9+/fZqVOnWMeOHXWOgQqFgslkMvbpp5+y1NRUndHDK/P8db2zZ89mPj4+7NSpUyw6OpoNHz6cWVlZ1Xn0+5CQEHby5EntNr29vbXjYDyvuuuki4qKWOfOnZmXlxfbv38/S0xMZFevXmUjR45klpaW7NKlS9p1a7JfTZs2jQ0aNIilpKSwR48esevXr7NVq1YxKysrNnToUKZUKhljjB05coSFhYWxI0eOsNjYWHb37l321VdfMZFIxH766Se93pft27ezH374gUVHR7O4uDj20UcfMZlMxp49e8YYq/h78vr160woFLKVK1ey2NhYtmPHDiaTybSjnzNW8fekPt+vVSm7TZVKxYKDg1n//v1ZZGQk+/vvv1n79u3rPPq9paUl69evn3abLVq0YBMmTKj2sZXtKwkJCcza2lrnevKCggLm7+/P5s6dq1e53njjDWZra8vOnDnDUlJStLfnZ92ozOXLl9mqVatYeHg4S0xMZPv372cSiYT98ccfjDHGVq1axby9vdndu3dZeno6KykpYb/++isTi8Vsz5497MGDB+ybb75hDg4OOq9x165dzNLSkkVERLD09HRWXFzM1Go169GjB2vTpg07fvw4i4+PZxcuXGAffvihXjMCPX98/vzzz5mDgwM7dOgQi4mJYTNnzmTW1tZ1Hv2+qu+6qlS2fw0fPpz16NFDZ+yS999/n3l6eup1/COED6hSTzjj+QrGpUuXWOvWrbWDSZW6evUq69+/P7OysmKWlpasdevWbNWqVdr767tSz5jmS9bJyYlZWVmxadOmsXfffbfOlfrvvvuO9e/fn5mbmzNfX98qB+vRt/w//vgja9++PZNKpczS0pK98MILFU5dp1Ao2FdffcVCQkKYRCJhNjY2bODAgez8+fM665WdJkcgEDBbW1vWqVMntnLlSp2BwoqLi9n777/P2rVrx2xtbZmFhQULCAhgH330kV4/dB4/fswGDx7MnJ2dmZmZGfP09GSTJk1id+/erfaxpXJyctiMGTOYnZ0dc3BwYKNGjdKZSi09PZ116dKFWVpaMgsLC9a3b1+dAd0qUptKPWP67S+7du1ibdu2ZRKJhNnb27MXX3yRHTx4kDH2b967d+9mnTp1YhKJhAUHB7O//vpLZxsrV65krq6uTCAQ1GpKu5SUFDZkyBBmbm7OvL292U8//WSQKe0OHDjAmjZtyszNzVm/fv1YYmJipY/R5z1OT09nb731FvPy8mJmZmbMxcWFTZ8+vcLtJiQksGnTpjEXFxdmZmbGvLy82FtvvaWtFJUqOz1Y6dRhQ4cO1WZQ6saNG2zy5MnMz8+PmZubM0dHR/biiy9W+LmqyN69e1m7du20x6/g4GD22Wef6TUQWVlnzpxh3bp1Y+bm5szOzo4NHDhQO0jiiRMnWFBQEDM3N2etW7dmZ86cKXcM3Lp1K/Py8mJCobBWU9rl5eWxyZMnMwsLC+bi4sK+/PJLg0xpd+TIEe1xqFOnTlUOrqnP4GcFBQVsyZIlrFmzZszMzIw5ODiwMWPG6EyVV0rf/WratGnafUUsFrMmTZqwfv36sW3btulUGuLi4tjMmTNZixYttFMPduzYUadyXZ1Dhw6xzp07MxsbG2Zpacm6dOmiM1VnZd+TpVPamZmZMW9vb/bVV1/pbLeyz3V1369VeX6bsbGxrEePHkwikbAWLVpoBymr65R2mzZtYu7u7kwqlbKXX35ZO5VjVSraV9RqNevbty8bMGBAufXPnTvHRCKRXifqSveF52/65nznzh02cOBA1qRJE2Zubs5atGjBNm7cqL0/LS1NmwnKTGm3ePFi5ujoyKysrNj48ePZunXrdF5jcXExGzNmDLOzs9MpT25uLnvrrbeYu7u79pgYFham8/1YmeePzwqFgs2fP5/Z2NgwOzs7tmjRIoNMaVfdd11lKtq/du7cySwsLHQG5mSMMblczlq2bMleeeWVWpWVEK4RMGaAkWEIIYTUm4SEBPj5+SEiIgJt27Y1dXEIIYQQQgiH0EB5hBBCCCGEEEIIT1GlnjR6VY3m/dlnn5m6eA1SVbMD6DN6elWjaj8/fVxjlZSUZPLRhhsjvh5P6numDsJv586dq9dZDLiqsR1Hq5qNoOxUh4QQ7qHu96TRe/z4caWjeddmflVSvby8PDx9+rTC+8zMzKqduzgtLQ25ubkV3mdjY1PjubEbIqVSiYSEhErv9/X1rXKua1I7fD2ePHjwoNL7PDw8qp1GjzRsRUVFePz4caX3m3JGmvrU2I6jiYmJlc5G4OLiAmtrayOXiBCiL6rUE0IIIYQQQgghPEXd7wkhhBBCCCGEEJ7iXJ8htVqNJ0+ewNraGgKBwNTFIYQQQgghhBDSADHGkJeXB3d3dwiF/G3v5lyl/smTJ/Dy8jJ1MQghhBBCCCGENALJycnw9PQ0dTFqjXOV+tJBOJKTk2FjY2Pi0jQcd+7cQXBwsKmLQapAGXEfZcQPlBP3UUbcRxlxH2XED5QTt+Xm5sLLy4v3A0FybqC83Nxc2NraIicnhyr1BpSZmcnZUZeJBmXEfZQRP1BO3EcZcR9lxH2UET9QTtzWUOqe/L1wgNRIZdN/Ee6gjLiPMuIHyon7KCPuo4y4jzLiB8qJGANV6jlm7Z+xyMiXG3y7+fn5Bt8mMSzKiPsoI36gnLiPMuI+yoj7KCN+oJyIMVClnkMSnhXgSnwmVhy5A0NfFUGDD3IfZcR9lBE/UE7cRxlxH2XEfZQRP1BOxBg4N1CevlQqFRQKhamLYVAHw+OxZKA/rsZn4o/IJPQNcjHYtp8+fQpzc3ODbY/rzMzMIBKJTF2MGnn27BlsbW1NXQxSBcqIHygn7qOMuI8y4j7KiB8oJ2IMvKvUM8aQmpqK7OxsUxfFoNSMoaOTEpKiDHR3YcgoyMKDuAKIhAKDbL+kpATx8fEG2RZf2NnZwdXVFQKBYd7D+lZUVGTqIpBqUEb8QDlxH2XEfZQR91FG/EA5EWPgXaW+tELv7OwMCwsL3lTYqpNVUAInIWArkwAAPBQqPMuXw91OZpDXqFKpeNdyXVuMMRQWFiItLQ0A4ObmZuIS6cfHx8fURSDVoIz4gXLiPsqI+ygj7qOM+IFyIsbAq0q9SqXSVugdHR1NXRyDYYyhKE8JXwdLCP+pwEulQAlEKFIL4GBZ927zxcXFkEqldd4OX8hkMgBAWloanJ2deXFCIzU1lfdzZDZ0lBE/UE7cRxlxH2XEfZQRP1BOxBh4NVBe6TX0FhYWJi6JYRXIlbAwF2sr9KWcrMyRU6REiVJV5+cw9MB7fFC6n/Bl7AW53PCzHhDDooz4gXLiPsqI+ygj7qOM+IFyIsZQp0r9559/DoFAgAULFmiXFRcXY86cOXB0dISVlRXGjBmDp0+f1rWcOhpKl/tSmQUlcLSUlFsuEAjgbivFk+ziOlfKJZLy22/o+LafNG3a1NRFINWgjPiBcuI+yoj7KCPuo4z4gXIixlDrSn14eDi+//57tG7dWmf5woULceTIEfz88884e/Ysnjx5gtGjR9e5oA1ViVINCAQwE1UchbmZCNZSMTIKSur2PCV1ezypf0lJSaYuAqkGZcQPlBP3UUbcRxlxH2XED5QTMYZaVerz8/MRFhaGrVu3wt7eXrs8JycHP/74I77++mv06dMH7du3x/bt23Hx4kVcvnzZYIVuSDIK5HC0lODMmTMQCAQVjurvYClBfrESckXdu+Eb0/Tp0zFy5EhTF4M3lEqlqYtAqkEZ8QPlxH2UEfdRRtxHGfED5USMoVaV+jlz5mDIkCHo16+fzvLr169DoVDoLA8MDIS3tzcuXbpU4bbkcjlyc3N1bo2FWs1QVKKChaTqQdwEAgHc7WR4klP7bvj1OUd9QkICBAIBIiMjdZZ/88032LFjR709b0PTrFkzUxeBVIMy4gfKifsoI+6jjLiPMuIHyokYQ40r9Xv37sWNGzewevXqcvelpqZCIpHAzs5OZ7mLiwtSU1Mr3N7q1atha2urvXl5edW0SLyVXaSAnYVEr2u/JWIhbGVmSM+v3WAbFQ3SUd9d8m1tbcvtC6RyDx8+NHURSDUoI36gnLiPMuI+yoj7KCN+oJyIMdSoUp+cnIz58+dj165dBpse7YMPPkBOTo72lpycbJDtcpFcLse8efPg7OwMqVSKAX164v6tSJ11Lly4gNatW0MqlaJLly64deuW9r7c9CeY9PJo2Nvbw9LSEiEhIfjjjz+099+6dQuDBw+GlZUVXFxcMGXKFDx79kx7f69evTB37lwsWLAATk5OGDhwICZNmoTx48frlEGhUMDJyQk//fQTAODYsWPo0aMH7Ozs4OjoiKFDhyIuLk67vp+fHwAgNDQUAoEAvXr1AlC++/3zr79Hjx4IDw/X3l96CcKpU6fQoUMHWFhYoFu3boiNjdWuExUVhd69e8Pa2ho2NjZo3749rl27VsMkuEmtVpu6CKQalBE/UE7cRxlxH2XEfZQRP1BOxBhqVKm/fv060tLS0K5dO4jFYojFYpw9exYbNmyAWCyGi4sLSkpKyl0X/vTpU7i6ula4TXNzc9jY2OjcGqp3330XBw4cwM6dO3H+8lX4+zfD4MGDkJmZqV1n8eLFWLt2LcLDw9GkSRMMGzZMOyXb3LlzIVArsPvwMUTdvIkvvvgCVlZWAIDs7Gz06dMHoaGhuHbtGo4dO4anT59i3LhxAP7tfr9z505IJBJcuHABW7ZsQVhYGI4cOYL8/HxtGY4fP47CwkKMGjUKAFBQUIBFixbh2rVrOHXqFIRCIUaNGqU9SF29ehUAcPLkSaSkpODgwYPVvv4bN26gWbNmGDhwoM7rB4AlS5Zg7dq1uHbtGsRiMWbMmKG9LywsDJ6enggPD8f169fx/vvvw8zMrPahcEhAQICpi0CqQRnxA+XEfZQR91FG3EcZ8QPlRIyC1UBubi6Ljo7WuXXo0IFNnjyZRUdHs+zsbGZmZsZ++eUX7WPu3r3LALBLly7p9Rw5OTkMAMvJySl3X1FREbtz5w4rKiqqSbE5IT8/n5mZmbFdu3YxxhhLyihg+YVFzN3dnX355Zfs9OnTDADbu3ev9jEZGRlMJpOxffv2McYYa9WqFVuxYgXLKpCz1Bzd9+CTTz5hAwYM0FmWnJzMALDY2FhWWFjIevbsyUJDQ3XWUSgUzMnJif3000/aZRMnTmTjx4+v9LWkp6czACw6Opoxxlh8fDwDwCIiInTWmzZtGhsxYkSFr58xxkpKSrSvnzGmfQ9OnjypXed///sfA6DN3Nramu3YsaPSspXFt/2l9P0k3EUZ8QPlxH2UEfdRRtxHGfED5cRtVdU9+URckxMA1tbWaNmypc4yS0tLODo6ape/+uqrWLRoERwcHGBjY4O33noLXbt2RZcuXep8AqIqSw5F42lucb0+R1kuNlKsGtVK7/Xj4uKgUCjQvXt3KFRqqBmDpUyKTp06ISYmBh07dgQAdO3aVfsYBwcHBAQEICYmBgAwb948vPHGG/jzzz/RsXtPTBz/Mjq3bwdA0y399OnT2pb755+7dKyC9u3b69wnFosxbtw47Nq1C1OmTEFBQQF+/fVX7N27V7vO/fv3sWzZMly5cgXPnj3TttAnJSWV2x/0ef2lzMzMtK+/rLLTJLq5uQEA0tLS4O3tjUWLFuG1117Df/7zH/Tr1w9jx46Fv7+/XmUghBBCCCGEkIamRpV6faxbtw5CoRBjxoyBXC7HwIEDsWnTJkM/TTk1qWCbWmZBCRwtJTV+3GuvvYaBAwfif//7H44fP44XunbBmjVrMG/ePOTn52PYsGH44osvyj3Ozc1N2/3e0tKy3P1hYWHo2bMn0tLScOLECchkMgwaNEh7/7Bhw+Dj44OtW7fC3d0darUaLVu2rLeB9sp2py8dRLD0RMKKFSswadIk/O9//8PRo0exfPly7N27V3upAJ9R9yzuo4z4gXLiPsqI+ygj7qOM+IFyIsZQqyntyjpz5gzWr1+v/VsqleK7775DZmYmCgoKcPDgwUqvp29M/P39IZFIcO78eRTIlbA0F0OhUCA8PBzBwcHa9S5fvqz9f1ZWFu7du4egoCDtMi8vL8yePRuHDh3C3PkLsOX7rQCAdu3a4fbt2/D19UWzZs10bpaWlhWOfl+qW7du8PLywr59+7Br1y6MHTtWW7HOyMhAbGwsPvroI/Tt2xdBQUHIysrSebxEojlBoVKpqn39Fy5c0C6r6PXro0WLFli4cCH+/PNPjB49Gtu3b6/R47mq7ICAhJsoI36gnLiPMuI+yoj7KCN+oJyIMdS5Uk/0Y2lpiTfeeAPvLn4X186fRkxMDGbOnInCwkK8+uqr2vVWrlyJU6dO4datW5g+fTqcnJy0I8gvWLAAx48fR3x8PG7cuIGL5/6Gf4sAFMiVmDNnDjIzMzFx4kSEh4cjLi4Ox48fxyuvvFJlZbvUpEmTsGXLFpw4cQJhYWHa5fb29nB0dMT//d//4cGDB/jrr7+waNEincc6OztDJpNpB+fLycmp9PUvXrwYx44dw507dyp8/VUpKirC3LlzcebMGSQmJuLChQsIDw/XOelBCCGEEEIIIY0JVeqN6PPPP8eAIcMxZ9YMtGvXDg8ePMDx48dhb2+vs878+fPRvn17pKam4siRIzot4XPmzEFQUBAGDRqEFi1a4If/24ynucVwcXXDhQsXoFKpMGDAALRq1QoLFiyAnZ0dhEKhtvt9ZcLCwnDnzh14eHjoXPcuFAqxd+9eXL9+HS1btsTChQvx1Vdf6TxWLBZjw4YN+P777+Hu7o4RI0ZU+vrHjBmDKVOmVPr6qyISiZCRkYGpU6eiRYsWGDduHAYPHoyPP/5Yr8dzHXXP4j7KiB8oJ+6jjLiPMuI+yogfKCdiDALGGDN1IcrKzc2Fra0tcnJyyk1vV1xcjPj4ePj5+UEqlZqohLVXVKJEVqEC7nYyg243r1iBvGJlldstKiqCTGbY5+U6vu0vt27d0nvgQWIalBE/UE7cRxlxH2XEfZQRP1BO3FZV3ZNPqKXeiDLyazdAXnWspWZgjCG/WGHwbRPjEQrp48h1lBE/UE7cRxlxH2XEfZQRP1BOxBhoLzMSpUoNpZrB3ExUL9t3tZUhLU8O1T+jxD+vuu73xPSaNm1q6iKQalBG/EA5cR9lxH2UEfdRRvxAORFjoEq9kWQWlsChHlrpS4mEAjjbSJGSU1zh/VWNfk+44cGDB6YuAqkGZcQPlBP3UUbcRxlxH2XED5QTMQaq1BuBpmu8EtZScb0+j5W5GEKBALlF1A2fj8Ti+t0/SN1RRvxAOXEfZcR9lBH3UUb8QDkRY6BKvRHkFithLTWDQCCo9+dytZHiWb4cSpVuN/zSEfQJd3l7e5u6CKQalBE/UE7cRxlxH2XEfZQRP1BOxBioUm8EWQUlsLc0M8pzCYUCuNqW74ZfUlJilOcntffw4UNTF4FUgzLiB8qJ+ygj7qOMuI8y4gfKiRgD9QepZ8UKFcQiAcRGHPnSQiJGrkiJnMIS2FpoWuiN0UuA1A0NZsh9jTWjmJRcfPL7HVhIRBALhWhibQ5na3M425jD2Uaq+b+1FI6WEgiFpj/WNNac+IQy4j7KiPsoI36gnIgx1KhSv3nzZmzevBkJCQkAgJCQECxbtgyDBw8GoJkX/O2338bevXshl8sxcOBAbNq0CS4uLgYvOF9k5MvhaGX8D7OzjTkSnhXAwlwMM5EQZmbG6SlAas/V1dXURSDVaIwZJWYUYOWRO/gurB0cLCWQK1V4ll+Cp7nFSMuV41FmIW4kZiEtV47MwhIwxsCYpteQk5UEztZSTeXfWqo9EeBkZQ4zUf2d6GyMOfENZcR9lBH3UUb8QDkRY6hRpd7T0xOff/45mjdvDsYYdu7ciREjRiAiIgIhISFYuHAh/ve//+Hnn3+Gra0t5s6di9GjR+PChQv1VX5OU6nVUKgYZPU0jV1VhAIB3GxleJJdBG8HC5SUlEAmkxm9HER/iYmJaNmypamLQarQ2DJKyy3Gewdu4utxbbWzd5iLRfCwk8HDrurjiVKlRkZBCdJy5UjLK0Zanhx3nuQiLa8Y6XlyqNQMDMBrPfzQrZmTQcvdUHNSqNRIz5MjLU+uOamSJ0f6P/9mFJRArlTj20mhsJFy/yRuQ82oIaGMuI8y4gfKiRhDjSr1w4YN0/l71apV2Lx5My5fvgxPT0/8+OOP2L17N/r06QMA2L59O4KCgnD58mV06dLFcKXmicwChdGupa+ITCKCzEyE7CIFZLXoErtjxw4sWLAA2dnZhi9cDUyfPh3Z2dk4fPiwSctR3+ikC/c1poxyChVYuD8Sq0a1gns1FfiKiEVCuNhI4WIjBWBb4Tq5xQp8c/I+9oYn473BgdWeKNAX33IqVqiQXqainlb6b54cWQX/jociFgn+ufRB0+vBw06KUC87ONuYw9HSHAduPMJfMWkYGephwlejH75l1BhRRtxHGfED5USModbX1KtUKvz8888oKChA165dcf36dSgUCvTr10+7TmBgILy9vXHp0qVKK/VyuVxnDvXc3NzaFolTGGPIK1bAz8nSpOVoYm2OhIxCSK0NP/p9QkIC/Pz8EBERgbZt23Jue3zj5GTY1kpieI0lo8ISJebtjcAHg4Pg38Sq3p7HRmqGpUODcf9pHpb/ehutPW0x68WmkNaxdxPXc7r3NA8b/3qAQrkSACA1E6GJtbl2rAK/Jlbo4u8IZ2sp7GRmeo9TMCDYBUsO3eJFpZ7rGRHKiA8oI36gnIgx1LhSHx0dja5du6K4uBhWVlY4dOgQgoODERkZCYlEAjs7O531XVxckJqaWun2Vq9ejY8//rjGBee6PLkSVubiOg1QV1JSUuep6AQCATzspEjKKEDTJmKTDGJliNfx/+3dd3yT1eLH8U+696R7M0qBQgtlFdACooCogChDLkNxoCAirp9XEfcEQS+KXkWGiigKwkVB2SKb0iJllE0LpZvuNmmT8/sjEildSZu2SXver1de0OTJeU77zZPkPOc857QGqampuLpW36MpmYbWkJGqQsPs1Yk8PrAdkQFN87t28HHmi8kx/HY8nQeXHeLB/qHc3tmn3u+fpppTfql2ZEJOsZL/M+LIhOvcHGxQqTUU/f35Y8pMNSPpHzIj0yczMg8yJ6kpGDxTUceOHUlMTOTAgQM8/vjjTJkyhRMnTtS7Ai+++CL5+fm6W2pqar3LMiXXilW6a1ABCgsLmThxIo6Ojvj5+bFw4UIGDhzI7NmzdduEhobyxhtvMHnyZFxcXHj00UcB+Omnn+jSpQu2traEhoayYMGCSvtSKBRVhqa7ubmxfPlyANIup9LB15WlX69m0KBBODg4EBUVxb59+yo9Z/ny5QQHB+Pg4MDo0aPJycmp9XcMCwsDoHv37igUCgYOHAhoh8uPGjWKt956C39/fzp27KhXPWsq77r58+fj5+eHp6cnM2bMoLy8vNb6mRsnp8brEZWMo6VnpNYInv/xKPf3DKJvW88m3bdCoWBYpB9fTe3F8bQCHvs6nrOZRfUqy9Ry0mgEPxxK5fFv4hnSyZuPxnc3eoP+utsivNlxKrNRyjYmU8tIqkpmZPpkRuZB5iQ1BYMb9TY2NrRv356YmBjeeecdoqKi+Oijj/D19UWlUlW5/jojI6PWWR9tbW1xcXGpdDN3ynI1FgoFVjfM7jxnzhz27NnDhg0b2LJlC7t37+bIkSNVnjt//nyioqJISEhg7ty5xMfHM3bsWMaPH8+xY8d49dVXmTt3rq4hbIgP3n6NR2c8RWJiIuHh4UyYMIGKCu3wzwMHDjBt2jRmzpxJYmIigwYN4s0336y1vIMHDwKwdetWrl69ytq1a3WPbdu2jeTkZLZs2cLGjRv1ql9t5e3YsYNz586xY8cOVqxYwfLly+v1NzBlLeG139K15IyEEMzbkMQtHby4vXPzrVhib2PJ07eHM/euzizaepq3fz1JYZlhJ/BMKafE1DymLDtIsaqCFQ/1NvqkgDe7o4svv5/IaNR9GIMpZSRVT2Zk+mRG5kHmJDWFBo/P02g0KJVKYmJisLa2Ztu2bYwZMwaA5ORkUlJSiI2NbXBFzUlOsQpPp8q99CtWrGDVqlXcdtttgHYSQX9//yrPHTx4MM8884zu54kTJ3Lbbbcxd+5cAMLDwzlx4gQffPABU6dONahezz/3LP0G3Y6Xky2vvfYaXbp04ezZs0RERPDRRx8xbNgwnn/+ed1+9u7dy+bNm2ssz8vLCwBPT88qJ24cHR358ssvDRp2X1t57u7uLF68GEtLSyIiIhgxYgTbtm3jkUce0bt8U5eWloaHh0dzV0OqQUZBGat2n+bpkS1z0s8Fv58mrI0TY2ICm7sqAAR5OLD4gR7sPpPFY1/Hc19MIKOiA/S6hMgUjqXsIiXzf0tGoYCF46Jp00RLm3o42lCqUlOiqsDBxnSH4JtCRlLtZEamT2ZkHmROUlMw6BP/xRdfZPjw4QQHB1NYWMiqVavYuXMnv/32G66urkybNo05c+bg4eGBi4sLTz75JLGxsU0z8/3Gp6HgauPv5zoXP7hrYZW71RqBskJT6cvU+fPnKS8vp3fv3rr7XF1ddcPSb9SzZ89KP588eZKRI0dWuq9///4sWrQItVqNpaX+E0pFRUUR4G5PSk4Jbby1PXGZmZlERERw8uRJRo8eXWn72NjYWhv1tenatatRr6Pv0qVLpd/Vz8+PY8eOGa18UyDP5JoutUbw77XHoKKCDUfTuCeq6gk5c/bl7vMoFDBtQFhzV6WKWzp40betJyv2XuTB5Yd4bmjHOq/1b85jqVyt4et9l9h5Ootnbg8nKsityeswsKMXu5KzGN7Vr8n3rS/5fmf6ZEamT2ZkHmROUlMwqFGfmZnJ5MmTuXr1Kq6urnTr1o3ffvuN22+/HYCFCxdiYWHBmDFjUCqVDB06lE8//bRRKl5FNQ3s5pBXosLdof7L2Dk6Gj5bvkKhQAhR6b7qrje3trbGysICPzd7zqTkA9qRFo2hut9D33pWx9q68t9UoVA0Wt2bi4ODQ3NXQarBZ7vOMbSLL7eG2DHvt0sEuNkTE+Le3NUyih/jL5OSW8Jr93Rp7qrUyNrSgodvacs90f7M/y0ZK0sLnr2jY6V5S27UXMfS3rPZLN5xltHdA1g+tVezTEwKMLSLL2/+csKkG/Xy/c70yYxMn8zIPMicpKZg0DX1S5cu5eLFiyiVSjIzM9m6dauuQQ9gZ2fHJ598Qm5uLsXFxaxdu7bW6+lbGiEE+aXluNhXboC2bdsWa2trDh06pLsvPz+f06dP11lmp06d2LNnT6X79uzZQ3h4uK7n2svLi6tX/xmlcObMGUpKSmos097aEteb6tipUycOHDhQ6b79+/fXWrfrPfFqtbrO30OfehpaXktT2yoRUvOJv3SNs5lF3N8zkOzMDObfH8WHW5JJza35GDMXvx9PZ8/ZbF69u0uDVupoKt7Odrx/XxRjegTy1OoEVu67SIW66sm9pj6WruSVMuu7BLadyuSzSTHc3zOo2Rr0oF3KtLCsgrJy030vle93pk9mZPpkRuZB5iQ1BYMnypNqVqyswMHWCoubvhw7OzszZcoUnnvuOXbs2MHx48eZNm0aFhYWdX6RfuaZZ9i2bRtvvPEGp0+fZsWKFSxevJhnn31Wt83gwYNZvHgxCQkJHD58mOnTp1fp2b6Zq4O2AV309wRUs2bNYvPmzcyfP58zZ86wePHiOofee3t7Y29vz+bNm8nIyCA/P7/W7euqp6HltTTu7sbt+T2VXsDvx9Mpr6bRI+knv7Sc+b8l89pIbaPX3d0dZztr3hvTjf9b+xcFBk7gZkr2ncvhpyOXeW9Mt2ZtgNZHTIg7Kx7sjY2lBVOXHeLA+cordRj7WKpJWbmaj7edYd764zw5uD1z7+qMi139R2oZU1y4F7tOZzV3NWrUVBlJ9WcWGRVlwcEvIPUgqMz/RKuhzCIjSeYkNQnZqDei3GIVnjUMB/3www+JjY3lrrvuYsiQIfTv359OnTphZ2dXa5k9evTghx9+YPXq1URGRvLKK6/w+uuvV5okb8GCBQQFBXHLLbfwwAMP8Oyzz+o91KdQqe3N6du3L1988QUfffQRUVFR/P7777z88su1PtfKyoqPP/6Yzz//HH9//yrX/t+srnoaWl5LU9eJGEPsOp3Fu5tOkZJbwoPLDvHuplNczC42WvmtgRCCV9Yn8dywjrqG2vWMAt0dePaOjjz7w9Fqe4pN3bHL+Xz+xzkWjeuOjZV5fgxYWCgY3zuYTx7owaakdJ7+PpGr+aWAcY+l6ggh+O14OlOXHaSDtxNfTI6hg49zo+7TUMMifdmcZLq9Q42dkdRwZpGRjSO4hcD5XfDzdPj2flj7GOz7FC7tBWVhc9ewUZlFRpLMSWoSCnHzRc7NrKCgAFdXV/Lz86tMLFFWVsaFCxcICwurszHc1FQVatILlAR76NeYLi4uJiAggAULFjBt2rRGrh2UlpZib191XeRytYbU3BJCPB2xNLPeuro0xuulRFXBvnM5RPi5GH2d6aSkJCIjIxtczprDqew+k83793XDztoSIQQJqXl8fzCV7CIl90T7M7SLL3bW+k+y2Bp9fyiF7CIVMwa11913c0Yb/0rj4IVcXrvHPIavA5zLKuKV9Ul8+kAMrg2Y/8PUnEov4P3NyUT6u+BUkU/PyA54O9vi5WyLrZXxXutnM4t4b/MpOvu5MD2uHfY2pnscPbjsIJ9NijHq728sxnq/kxqP2WZUnAPpRyEtEdKPgaoIbF3AL+rvWzewbxk9p2abUSsjczJttbU9zYnprndjZnJq6aUHSEhI4NSpU/Tu3Zv8/Hxef/11gCbrja5plnxrSwt8XOy4kldKkLu92TRMmlJqbgnbT2Wy52w2AH3aevLVngtMj2vHLR28jLYfT0/PBj1fCMF/tp8lr6ScReOidUOqFQoFPYLd6RHsTmFZOf87epVHv46nbRtHJvQOpqOvafUwmoKzmYVsOZHB55Mqr0Zxc0Z3dfPnYnYxy/de5MH+pjdz/M3S8kp5eV0SH42PblENeoAIXxeWTunJ/vO5/HVexZ4z2WQWKskqVFJxw6SaLvbWeDvb4e1si7eLLd7Odvj8/W9tDfTCsnL+s/0saXmlvHJXZ4L0PIHbnG7p4MWfZ7K5rZNPc1elioa+30mNz2wzcvSEdoO1t+tK8yD9L7h6FBK+hrJ8bS+/b9e/G/rR4NimuWpcb2abUSsjc5KagmzUG4FGIyhVqfF1qb03eP78+SQnJ2NjY0NMTAy7d++mTZvm/xBxtLWitFxNdpEKL+emWUvZlFWoNcRfusb2U5mcuFpAoLsDgyO8WTQ+WrdU4QO9g5m7Pom/LufzxMB2zX4ypEKtYe7647TzcmTWbR1q3M7ZzpoH+gTzQJ9gTqQV8O2BS1zKKeHOrr7c1c0fR1v5llBWrubVDSdYMDZKr9ErMwa15/kf/2L7qQwGR5he4+m63GIVz645yntjuuFdx3uVuVIoFMS28yTUQYWfX9WZ34UQ5JWUk1moJLOwjMwCJfGXrmn/X6ikTKWdWE4ATrZWuoa/hULB9lOZPD7QuCfyGtuwSF8+3HLaJBv1ktSk7N0g7Fbt7TplIaQnaRv6x36EkhywsgWfrtDhdgjo0WzVlSRJMpT8Bm8EeaXluDnY1Nqw6969O/Hx8U1Yq8rqmlHe09GGy9dKKSqrwMmu9b0scotV7Dqdyc7kLPJLy4kJdueeaH/+b3hEtbna21jywX3d+Hr/JWZ+l8C793bFuYETZOXk5FTbEKlLsbKCZ344yl1RftzVTf/10zv7u/D6yEjKytX8euwqT36XgI+LHeN7BdEt0LXZT1Q0l3c3neKhAaH4VNPwrS4jhULBm6Mjmf51PH6u9nTyM72hW0XKCp5ancArd3cm2NP0e5gbqqZjSaFQ4O5og7ujTa0jVIQQFCkrtI3/AiXFygqWP9jb7OYf8HezJ7tIiapCY3J1r+/7ndR0WnxGts4QEqu9XacqgcwTcHgpHF8Hg14Ca9M9CdriM2ohZE5SU2h9rTcj0/b8qAj1NHx9+aZkZVV71AqFAn83ey7lFGNj5WByXwCNTQjBqfRCtp/K5PDFXJztrIkL9+KVuzrj6aTfaAWFQsHk2FC6+Lvw6Mp4Xh/ZpUGTZXl7exv8nKxCJXN+SGTmoPb0aVu/4V121pbc2yOQe3sEci6riB8OpTL/92SGdPJhVHRAixumXZutJzJQKKixx72mjGytLFkwNpoZ3x7ho/HRJtUTXlauZvbqBGYPCSfC1/ROODSG+hxLN1IoFDjbWeNsZ007Lycj1ap59G/Xhr3nshnYsWF/E2NraEZS42uVGdk4QGBP7e3UL7BqLNzxpvY6fBPUKjMyEiEEZeoyClWFulu5ppzu3t2xsjBu80jmJDUF2ahvoBKVGnsbS5NfEkqf+RAtLRQEuNlzJa+UEE+HKkvzmbtSlZq957LZdiqT1NwSOvm5MKijN4/e2hZry/qfxIgJ8eCjCdG88ONf3BcTxIhu9TsbW15u2PJo57OK+Pe6Y7wxMtJoM2+383LixTs7oarQsO1kBs/9eBQnOyvG9Qyid5hHi+69T88vY/neiyyd2rPGbWrLyMPRhjdHR/LMmqP8d1JPk5hArUKt4Zk1R5kUG0pMSMuYGEofhh5LLdmwSF8Wbz9rco16mZHpa/UZRYyAwN6w6TnwiYT+s8HStL42t+aMNEJDcXlxpUZ5oaqQovIiClQFlX4uVBWiUqtQoP0OI9B+J7a3ssfZxhknGydcbFxQa9R8fvRzBgcPZlT7UThYG2dkW2vOSWo6pvXuZIZyi1X4uJj+deh1Db+/ztbaEk9HG67mlRHgbtzZ3ZuDWiNYn3CF7WevoRHQv50n029tZ/QhyN7Odvx3ck/e3XSKo5fzeH5oR6wMPFFw7do1AgIC9No2/tI1Fm45zUfju1c7TLyhbKwsGN7Vj+Fd/bh8rYQfDl/m4+1nuLWDF8Mj/QjyaFmTKqo1gpfWHePVe7rUOlN4XRm183Li8bh2vPDTX5UmK2wOQgheWpfEsC6+xIWbz3XgxmDIsdTSBXk4cLWgjHK1pkEnL40pt1hFZnauzMjEyeMIcPKC+5bB0e+0vfZ3fgCe7Zq7VjqtKSMhBJcKLrH7ym4OpR+iQlOBi60LztbOONtUvoW5hlW538ay5smsbzSt6zS2XNrC7B2zifaOZkLEBNztGnZSvDXlJDUfuaRdA5SrNaTllRJi4kPvQXuW0JB1MtPzy7CxssCjlhn9TZlGCK7mFnDh/AXK7DyJDfdrskng1ideYUNiGu/d1402eg7lB8jOztZr4sTfjqez5vBlFo6LavB1/IZQawR/nM5iR3Iml6+VYqHQNmK7BLgS6e9CqKejyY9Yqcni7WfwdrZjbK+gWrfTN6PVB1NIyS3h+WERxqqiQYQQvP3rSULbODKxT0iz1KE56ZtTa7Fk5zm6BrgyoINp/E2mLjtIUYmSUTHB3N8z0CSX3JPM4zjKK8vjYPpB+vn3w8mmkS+VyUuFX5+D9rdBr4fBBE5sm0NGDVFWUcbhjMPsvrybiwUXCXEJYUDAAHr59sLeqnE7noQQ7L+6n+9OfYePgw+Tu0wmyLn27wg1aek5mbtWuaTdO++8w9q1azl16hT29vb069eP9957j44dO+q2KSsr45lnnmH16tUolUqGDh3Kp59+io9Py5t9N7eOZexMieaGJZ304eNiy6WcEuytLbC3Ma8BHQWl5WQXKXGyUuDpZEtYmBd2TTir+8joADr6OvPkqgReGB5BdJCbXs8rKSmpc5uV+y5y7HI+n07s0eTzHlhaKBgU4c2gCO0wXrVGcD6riGNX8vlmfwqXcooBCPF0JDLAha4BrrT1ctJrBvnmFH8pl3NZxZXWo6+JPhkBjO8dzDu/nmTN4VTu71m/LwH1JYTg053ncHOwaZUNetA/p9ZieKQvn/9x3iQa9Ycv5tLR15lxET4cybXkwWWHGNrFl3G9grCzNq3GfalKjY2Vhcm/hzUWcziOrCysyFfl88reVyhXl9PLtxe3Bt5KqGuo8XfmFgTjV8HB/8LqiTBiPrjoPzltYzCHjAyVWpjKn1f+5MDVA6iFml4+vRgfMZ5Ql9AmHSGoUCiI9Y8l1j+Wkzkn+TTxUzRCw+Quk+ni2cWgslpiTnpRFmmXjjSBE2CtgUE99cOGDWP8+PH06tWLiooK/v3vf5OUlMSJEydwdNT2Vj/++OP88ssvLF++HFdXV2bOnImFhQV79uzRax/m0lNfVFZOdpGKEE8HsxiGXFpair29YWc1K9QaUnJLCPZwMHgoeXNQlqtJLyjD1soSL2dbylXKZn295JeW8+LavxjQ3osJvYPqfJ0kJSURGRlZ7WMajeD935KxtlQw5/Zwk33NaTSCiznFJKUVcPxKPueyilBrBMEeDn/36LvSwcfJZIYB55eWM/3reD6fHIOLHqMeasvoZhqN4MnVCUzqG0Lfek5iaAghBLvPZLNszwX6tPXksVvbmuzrpLEZklNrMWnpAZZN7dXs7+VPfBvPvLu7kJVylsjISNQawca/0vj+UCqDI7yZ2CekWeejEEJwJOUa3x9KJb1AiZu9NQvGRpnMe1ZTMrfjSKlWcij9ELtSd5FSmEJb17bEBcUR4x2DtaWRR7VlnYbNL0D0RIgc02yNFnPLqDoqtYr4jHh2X9nN2WtnCXQO5JaAW+jj18do17Qby+XCy3x94mvSitKYEDGBWP9YvT5nW0JOetNo4Px2SFylXSbSJ1I72aQJfx9pKT31DRp+n5WVhbe3N7t27eLWW28lPz8fLy8vVq1axX333QfAqVOn6NSpE/v27aNv375VylAqlSiVSt3PBQUFBAUFmXSjvrCsnJwiFcEeDiY53Dg0NJTZs2cze/ZsQHu28ccff2TMmDEGl1Wq0i7rFNrGiXXr1jFq1CjjVtYI1BpBVmEZygoNvq52uqGcpvB60WgEi3ecJS2vlFfv6VJrT1Rubi4eHh5V7ldWqHlx7TF6hnjwQJ/gxqxuoxBCcPlaKceu5JN0JZ8zmUVUqDX4udkT6e9KZIALEb4uTT7yQAjB7O8TmdIvlB7B+l0vV1NGNSlRVfDY1/G8PjKSsDaNc5mOEIIdyZks33uJ7kFuPNQ/rFWtWFAdQ3NqDT7ZcZbuwW70a9d8vfVnMgpZ+ucF3h3TrUpGao1gU9JVvjuYwi0dvJjUN6TJLpkC7ci7tUcuszM5i6ggV8b1DCbY04HNSels/CuND8dGt/hVYW5mzseREIJzeef448ofxGfE42DlQD//ftwSeAtt7I10DKjLYfeHkHMWhr8HDk3/tzLXjK4WXWX3ld3sv7oflVpFjE8MtwTcQju3dmZxMvpa2TVWJ68mISOBke1HMjR0aK0z5ptrTgbJvwIJ38ClPdB2IEQ/AM6+cOC/kHsOhr1rsg172agHzp49S4cOHTh27BiRkZFs376d2267jWvXruHm5qbbLiQkhNmzZ/P0009XKePVV1/ltddeq3K/qTbqC8rKuVasIsjdNBv0ULVRn56ejoODg14v1FdffZWff/6ZxMRE3X25xSqupKURHuyHra3pTAoohCC/tJzcYhVtnG2r9LSawuvluh3JmXz15wXeubcrge7Vn3m+ePEioaGhle7LLy1nzveJPNAnmNs6tZxLWIQQXM0vI+lKPklpBRy6kMuUfiEM7eLbZB/oqw+mkFOs0mvY/XXVZVSX9Pwynv4+kSX/6oGbg/Eu1xFCsOVEBl/vv0SfMA8m9wvVa7RBa1CfnFq681lFLNtzkTdGNV9v0fM/HuXRW9vR3tupxow0GsHvJzL49sAl+rb1ZHJsSKPNHaLRCPaey2FNfCrlag2juwcyqKNXldEMW09ksDbhMgvHRbeq6/9b0nGUr8xnz5U97L6ym2vKa0R5RXFr4K108uiEhaKBJ2uuHIGt8yB2JoQPNU6F9WQuGZVryknMTGT3ld0k5ybj6+jLLQG30Nevb+PPhdCISitKWX92PVsvbWVQ8CBGtx9d7egCc8nJYOpyOP0b/LUarB2g+78gZABY3HRMHf4KMo7D8A+qPmYCWkqjvt6nwTUaDbNnz6Z///66ISXp6enY2NhUatAD+Pj4kJ6eXm05L774InPmzNH9fL2n3hQVlJZzrURFkEfjL/emUqmwsTFOA8DX15fS0tJ6P9/D0YbSNt4oNRaYSpO+VKUmo6AMB1tLQts4mvzye4M6etOujRP/99MxHotryy0dqs5GXlRUVOnntLxSnvvxKM8N1f+6fHOhUCjwd7PH382eO7r4Ulau5r9/nOfH+HheGNbRaEv01eRsZiFbT2bw+aSal6+rzs0Z6cPX1Y6XRnTimR+OsuRfMQ3u7dNoBJuPp/PdwRT6tWvDkn/F4NSEPZrmoD45tXRtvZy4mFOMWiOa5Rrxq/mlFKvUtPfWfoGvKSMLCwXDIn0Z2sWH7acymbEqgZhgd6b2D8XV3jiN+4yCMn6Mv8zec9nEtvXkxeGd8HWt+cTvkM4+WFoomPVdAh+N725y1/43lpZ0HLnaunJn2zu5s+2dVGgqOJZ9jC0Xt/CfI//Bx9GHWwNvJdYvtn7DvQN6wAM/wLY3IHmTdqixbdM0VE01o0JVIceyjpGYlcjJ3JMIIYjyiuLOsDt5usfTZtEbrw97K3vGR4znvvD72Jqylad3Pk3XNl2ZEDEBT/t/Lrsz1ZzqLfc8HFkJaQkQPgzu/rj2kSo9H9Ju/8vTMGKhwQ37AlUBiZmJHM44zJlrZ5gXOw9fR98G/hItkKin6dOni5CQEJGamqq779tvvxU2NjZVtu3Vq5d4/vnn9So3Pz9fACI/P7/KY6WlpeLEiROitLS0vtWut7wSlbiYXSTUGk29nh8XFydmzJghZsyYIVxcXISnp6d4+eWXhebv8kJCQsTrr78uJk2aJJydncWUKVOEEELs3r1bDBgwQNjZ2YnAwEDx5JNPiqKiIl25GRkZ4q677hJ2dnYiNDRUfPPNNyIkJEQsXLhQtw0gfvzxR93PqampYvz48cLd3V04ODiImJgYsX//frFs2TIBVLotW7ZMV8ZnK74TZeUVQggh/vrrLzFo0CBhZ2cnPDw8xCOPPCIKCwt1+5gyZYoYOXKk+OCDD4Svr6/w8PAQTzzxhFCpVLptPvnkE9G+fXtha2srvL29xZgxY+r8O5ZXqMWVayUiJadYqCrUtW7bnK+XmpQoK8SzPySKT3ac0WV/XV5enu7/J6/mi/Gf7xMXs4tuLqJFS80tFrO+OyJe/99xkV+qqvsJ9VCqqhAPfLFPpOcb/rq4MSND/X48Xbzw49EqueurQq0RPydcFg98sU988cc5Uawsr3ddWrqG5NSSLdpyWhw4n9Ms+35z43Fx+GKu7md9M9JoNGLHqQwx5asDYv5vp0RukbJe+y+vUIstx9PF498cFrO+OyL+OJ0p1GrDjsVdyZni4RWHRKmqol51MDet5Ti6UnhFrD65Wjy1/Skxc9tM8c2Jb8S5a+dEhboeOZ/fJcSyEUJc3Gv8ilbDFDLSaDTiUv4lsf7sevHa3tfEY1seE8/ufFasPL5SHM08KlQVjfNZboo0Go3Yn7ZfzNo2S7yx7w2Rkp8ihDCNnBpMVSrEX2uE+HacED/PECLloBCGfp9J+FaIn58Qoo5jK6M4Q2w6v0m8ue9N8diWx8RzO58T3574VpzKOVW/47IOtbU9zUm9undmzpzJxo0b+eOPPwgMDNTd7+vri0qlIi8vr1JvfUZGBr6+5ntGJb9ERX5pRYN76FesWMG0adM4ePAghw8f5tFHHyU4OJhHHnkEgPnz5/PKK68wb948AM6dO8ewYcN48803+eqrr8jKymLmzJnMnDmTZcuWATB16lTS0tLYsWMH1tbWzJo1i8zMzCr7vr5OfVFREXFxcQQEBLBhwwZ8fX05cuQIGo2GcePGkZSUxObNm9m6dSsArq6uujI8HG24cq0ULzsYOnQosbGxHDp0iMzMTB5++GFmzpzJ8uXLddvv2LEDPz8/duzYwdmzZxk3bhzR0dE88sgjHD58mFmzZvH111/Tr18/cnNz2b17d41/OyEEuSUq8kvK8XGxa9JrLY3J3saS9+/rxjf7L/Hkdwm8c29X3dDS7OxsXF1d2Xs2m8/+OM/iB7rjacCSeC1BoLsDH43vzt6z2Tz+TTyjogMY0yPQqJe6vLvpFNMGhOHjYvglGdczqo/bO/twMbuYz3ad5/GB+q9zXKHWsOFoGj/GX+b2zj4sndKr1fQU1ldDcmrJ7uzqy7cHUugd1rTXduaXlnM2s4iYkH/mrtA3I4VCwcCO3sSFe7H3XA7PrDlKR19nHh4Qptf7Y2puCd8fSiUxNY+BHb14Y2Rkvd9Xbw33wtJCwcxVR/h4QncczGxlGEO1luPI38mfcRHjGBcxjtKKUg5ePchPZ34ipSCFClGBj4MPHT060tG9I+Hu4bUPFw+7Ffyi4LeXIPlXGPwyWDXe53hzZFRWUcbxnOMkZiZyPOc4pRWlBDsHE+0dzSNdH8HXsekuozM1CoWCPn596OPXh+TcZD776zNUahUdrDswNHIowc7B5ve3yTih7WXPOQMRd8G9/wW7eg5Rj34ALKxg/Uy45z9gaYUQgpTCFOIz4onPiCenLAcvey96ePdgUudJBDnXPdG0pGXQJ5IQgieffJJ169axc+dOwsLCKj0eExODtbU127Zt003KlpycTEpKCrGxscardTXe2PcGmSVVG7MNVa7WUKER2FlboOCfF5W3gzdzY+caVFZQUBALFy5EoVDQsWNHjh07xsKFC3WN+sGDB/PMM8/otn/44YeZOHGi7tr4Dh068PHHHxMXF8eSJUtISUlh06ZNHDx4kF69egGwdOlSOnXqVGXf4u+pE1atWkVWVhaHDh3STdrRvv0/1xQ7OTlhZWVV7UkYa0sLvJ1t+eSz/1JWVsbKlSt1qx4sXryYu+++m/fee0+3fKG7uzuLFy/G0tKSiIgIRowYwbZt23jkkUdISUnB0dGRu+66C2dnZ0JCQujevXu1f7diZQUZBWW42lsT1sbR7A9uhULBpNhQOvu78tjX8bx2Txc6+DhTWlrK+sQr/H48g8//FdOsM0A3t37t29ArzIOv913iweWHeOaOcLoFujW43K0nMlAoYHBE/eYnaMhlLAAP3xLGyz8nsTnpKsMi/WrdtlytYV3CFX5OuMLwrn58NVU25vXV0Jxaqg4+zpzLKkKjEU06J8w3+y/xr76Vl1c0NCOFQkH/9m3o374N+8/n8MJPxwhr48Ajt7bF27nyCTplhZotJzJYn5iGm70143oF8cwdxlk1pH/7Nn837BP4z4TuZnuCWR+t8Tiyt7InLiiOuKA4QPvdKbMkk+RrycRnxLP61GqKyouws7Kjg1sHbWPfoyP+jv7/vL7sXGHkYjj1C3x7v3Y4vl+3RqlvU2SUXpxOYlYiRzOPcrHgIraWtkS2iSTKK4oJERNMboZ6U9FRWPFWqRXZqQfZ4lLIKsscLhVewtHKkSivKGJ8Yujo0bHWCfaajbIIjq+FE+vBPQxipoBvV6MUrY4cw+myTI6sGU2ibzhFFSUEOwfTw6cHs3vMxsuh6uWpkn4MeiXNmDGDVatWsX79epydnXXXybu6umJvb4+rqyvTpk1jzpw5eHh44OLiwpNPPklsbGy1M98bk6ENbH1cK1FRVFZBoLu9Ub4M9O3bt1I5sbGxLFiwQNeL3rNn5et7jx49yl9//cW3336ru08IgUaj4cKFC5w+fRorKytiYmJ0j0dERFSZ0wDA2lrbG5yYmEj37t3rPQunk501F84m0zmyq65BD9C/f380Gg3Jycm6Rn2XLl2wtPynEeLn58exY8cAuP322wkJCaFt27YMGzaMYcOGMXr0aBwc/vlwKFdrSM8vw0KhMJtl9QwRE+LOovHR/N9PxxjTI5AzVy3ILbvGxxO6t9p1kW9kbWnBQwPCuCfan/m/JfPdwRSevaNjvXvZ0vPLWL73IkunGnYd/Y1CQhq27rtCoeDVe7rw+DdH8Hezr/ZEhbJCzU/xV9j4Vxr3RPmz/MHerW7W7YZqaE4tWfcgNxJS8yr1mjemsnI1e89l83hc5dEpDcmob1tP+rb1JP5SLnN/TsLfzZ7Hbm1HkbKc1QdTSc4o5I4uviwYG9Uok0f2beuJpYWCGauOsPiBHi12Tgt5HGnfs30cfXTX3V9XUl7C2byzJF9LZlnSMtKK0lAoFAQ6Beoa+u07DME2sDdseh58I6HfU2Bp3NeKsTIq15RTUl5CcXkx2aXZHMs+xtHMoxSUF+Dr4EuUVxRjO45t8rXizU55GZz8HyT9CE7e0GMKbW57hdG7FmJ38Sjc+QFFtk78lfUXO1J38NnRzwDo5NmJ7t7difKKar6TJEJA2hFtr3zBVYi8F8Z9A9aGLYd9M5VaRVJ2EvEZ8RzLPkaFpoJw93Bigm/hnivHcb73SzD2kpOtlEHvLkuWLAFg4MCBle5ftmwZU6dOBWDhwoVYWFgwZswYlEolQ4cO5dNPPzVKZZtSbrGKEqXxGvT6uLGRDNqh8o899hizZs2qsm1wcDCnT5/Wu+yKigoAg9eqr469tSUaAReziwGwslRQUlSmrbOyghJVBRqNwMq68kGqUCjQaDQAODs7c+TIEXbu3Mnvv//OK6+8wquvvsqhQ4dwcXUlp0hFkbICXxdb7FvwEEdvZzs+nxTDh1tOoy4p5LXRveUH5k3aONny7phuJKbm8fQPRxnUUbvclSEnedQawb/XHePVe7o0aPbq9PR0nJ0bNomftaUFC8ZG8fg38cy/Pwp/N+0xWVau5ofDqWxOSmd09wBWPNS7Va6NbQzGyKmlGt7Vj5/iLzdZo37tkSuM7l71EhpjZBQT4sHnkzxITM3jzV9O4OZgzfhewUQGNP5w5F6hHjw5uAMzvj3Cfx7o3iJXnpDHUc0crB3o5tWNbl7/9MBrhIbLhZdJvpbMjpQdfPnXlyjVSpx9vOlYeomQb4ZiZe+BhUdbLD3aY+HZDktbZywVllgoLLT/WlhU+vn67cb7ddsqLDh/+Ty+Qb4UlxdTVF5ESXkJReVFFJcXV3tfSUWJdsakm1haWOJo7YijtSPutu509erKXW3vwtXWCMdS9ln49Rm4ayF4tG14eaYo4wQcWaFd3rDT3TDmS7D959hJDRxJhy4jYN10nGKm0K/LaPoF9AO0J1RO5pwkITOBNafXUFJRQphLGD18etDdu7vRlmAsUhWRUZJBRnEG6SXpZBRnkFGSQU5pDprSXMg5h4WtM7gGgq8PZO+BP/ZULUhB5dfQjT/f9PVVCIGFwoLINpH08O7B5C6TsbW8oWPm5EZY+yiM/hysjLc6UGtl8PD7utjZ2fHJJ5/wySef1LtSzS23WEmJSk2AkRv0Bw4cqPTz/v376dChQ6Xe7Bv16NGDEydOVBoef6OIiAgqKiqIj4/XDb9PTk4mLy+vyrbXs+vWrRtffvlljWtm2tjY6EYO1KRz586sWLECL3twcHCgQiPY+Mc2LCwsaNuuPYVlFZRVqClVqXUNf4DCsnJUFRqyi5RYWyiwsrTg1oGDGDz4NubNm4ebmxu/bP6d2NvuxN3RhlBPh1bRwLW2tOCFYREkJSW1it+3vqKD3Fg+tRc/HrnMlGUHmTmoA7HtPOt+IrBk51mGdfHVzbxdX0qlskHPv87V3pp37u3K8z/+xaLx0WxITGPbqQzujwli5UO9W9yolKZmrJxaoghfZ06lFyKEaPT3G7VGsPGvNJY/2LvKY8bMKDrIjcUP9DBaefqKCXHn6dvDmfGttsfeWLPzmwp5HBnGQmFBsEswwS7B3B5yu+7+fGU+p6+d5nLYZSrK8tHkp6C+ehDNqXWoK8pQW9mhcfZB7eyDxtEbtZUNaqFGLdRoNBrtv0Lzz31Cg1qj/TcvLw//fH+crJ10jXJHa0dcbFzwc/LD0coRRxtHHK0ccbJxwt7KvuFL+Bki/wpsnA1DXoP/PQVDXoWAmLqeZR5uHKLu0RZ6TK5xiLpSqQTvSO0qCX98oF0Gbtg7YO+OtYV1pRNEQgguFlwkITOBRfGLyCnLwdPOU9fIv3m0hBCCwvJCXSP9xkZ7blmudhsEjtaO+Dr64uPgg6+DL+Hu4fhoLPDcuxgLK2+472Nw1O87ldF0ukt7jf3ah+HeLxp1/onWoOV2gdZTTpGSsnI1AW7G76FPSUlhzpw5PPbYYxw5coT//Oc/LFiwoMbtX3jhBfr27cvMmTN5+OGHcXR05MSJE2zZsoXFixfTsWNHhg0bxmOPPcaSJUuwsrJi9uzZ1fbGXx9+P2HCBN5++21GjRrFO++8g5+fHwkJCfj7+xMbG0toaCgXLlwgMTGRwMBAnJ2dq6xNP3HiRObNm8eUKVN49dVXycrK4tk5s5k0aRIRbYMBcLCxQmWjXW4OtG86jrZWWFkqsLWyYOPGjZw/f55esf1xdHZlx5bf0Gg0BIS2I8TTsVUOP2/btoWewTYiCwsFY3sGMbSLLx9tPcP3h1J4fliErre7OvGXcjmXVWzQevQ1MWZGIZ6OPDWkA0+uSuCBPsGsfKhPq3zdNwZ5LNVMoVDQLdCVo5fzG32pzN+PpzM4wrvay0daSkbRQW48PzSCmauO8J8J3XFzaDm9TS0lo+bmautKL99e9PLtVf0GpXmQfgyuJkLKUSjL16757dsV/KPBLxocq++tLSkpqXTZokkpzoGfp8M9H2sbvWO/hnWPaZc3Cx/a3LWrHyHgyhFtr3xRBnTRb4i67liysoHBL8Hlw/D9JBjwNLS/rdK2CoWCMNcwwlzDuLfDvQBklWSRkJnAD8k/cLHgIjYW2hM/AAoUONk44eOgvUzEx8GHTp6d8HHwwd3OvfqTOOpyOPA5nN+pnczRP7qhf5n66zgMLCzhx4dgzFKwNnwSY+lvzTLnfi2ac0m7rMIyceVaSb2XnKpNXFyceOKJJ8T06dOFi4uLcHd3F//+978rLWl34zJ01x08eFDcfvvtwsnJSTg6Oopu3bqJt956S/f41atXxYgRI4Stra0IDg4WK1eurHZJu9WrV+t+vnjxohgzZoxwcXERDg4OomfPnuLAgQNCCCHKysrEmDFjhJubW5Ul7datW6crQ98l7W701FNPibi4OCGEdqm+uLg44e7uLuzt7UW3bt3E999/X4+/bM1McUm72pw8ebK5q2B2ktMLxLTlB8XHW09Xu8xUXolKjP98n9GWx5MZmQeZU+2OXc4Tb/9yolH3odFoxKSlB0RhWfVLL7a0jJKu5ImJX+wXOfVccs8UtbSMzEpZgXZZvH1LhFg7XYivxwixeqIQO94V4tQmIfLThBAmnFFZgRArRwlx9Vjl+8vLhPjpUSEOfdU89aqvklwh9n8mxIqRQvw+V4isMwY9vdqclMVC/PKcEBufEUJp2PLFygpl/dsqZ7cJsfwuIRK/M3xJusZ0ZqsQqyYIoSpp8l23lCXtFELoMaa+CRUUFODq6kp+fj4uLpWXTCgrK+PChQuEhYVhZ2fcMzlZhUrK1Rr8XO0aZUjiwIEDiY6OZtGiRUYvWx+lpaVGuZ7enDTm66UxJCUlERkZ2dzVMDtCCDYnpbNy3yUeGhDGkE7eKBQKhBA8tTqRqf1D6RFsnOuHZUbmQeZUOyEEk5Ye5OtpjTeHx75zOfx5NovnhkZU+3hLzOhUegFvbDzBR+O708aMlyPNK1Hx1Z6LeGjymTq0ht5lqempSiDzhLZHPy0RijLIrbDHY8JnYGNCvfUVSvhhCgyYDcHVTJKt0cC2V8HSBga9BKZ62aEQcGkPJHwDykLoNhbCh9fr2u9a3+/O7YA/P4TBcyGo6qVKRnPtEmx9VXvNfNzzla75Nxnnd8H+JXDfUrBxrHt7I6mt7WlO5PB7IKuwjAqNaLQGvSm4eQi9ZHpqmjtBqp1CoWB4Vz8GdvRmya5z/BifygvDIjh4IZeOvs5Ga9CDzMhcyJxqp1Ao6BLgwvG0gkabVG753gu8OarmJZBaYkYRvi7Mu7sLs75LYNH46CpL7Zm63GIVX+4+z8mrBTw0IIyegUHNXSXpRjYOENhTe/ub06kt8P2/tNcjN/X10NVRV8C66dDr4eob9AAWFnD763Dgv7BhJty1yLRmPy/KhMRVcG47BMfCoH+DW3CDiqz1/a7dIPDvDr/9G05vhrj/M+6kceWl8OciyEjSzmnQpoPxyja2tnHaofhrHoT7vgLbhs2D1Nq0+tmYMgvKUGsEvi4tt0EPcsIbc3D+/PnmroJZs7exZM7t4bw8ojMfbjnNjuRMpt+0jFZDyYzMg8ypbndG+vHrsauNUvbJqwW0cbLFy7nmk8ktNaNwH2deHxnJ7NWJZBSUNXd19JJVqOSdX0/y3JqjDOjQhq+m9uKWDl5cuHChuasm1eGsJkDbQF4zBXKb+ZgSAn6ZAxEjoMOQurfv8yiED9P26pcVNH796pJzDn56RLsEoXdnmLQOBr3Y4AY96PF+Z+8Goz4FvyhYdT9kHG/wPhFCO4nft/eDXzfttf+m3KC/LnSAdq6BNVMb/3VRXgZntsLvLzfufppIq+6pzygoQwA+TdCg37lzZ6OWL5m/68v9SQ0T5OHQaDNhy4zMg8ypbt0CXfngt+RGmQX/i93nmTW49i+PLTmj9t5OvDW6K7NXJ/LhuCj8XE3z0reMgjI+33We1GslPHJLW168s1Olx1tyRi2FRqMB30jtkmA/Pw5D5jXf7PJbXtE2Hrvep/9zOt0Njt7wwyQY9Rm4+DVe/WqiKobdCyD7jLYn29O4nQFgwLHUeSQE9YVNz2lzjJ2p7bk2VOYp2PYa+PeAiT+a3+RzIbFg8by2YX//MrAz4oiygjTt6gPntoNapT2J0GMq8B/j7aOZtMpr6oUQZBQoUSi0DfrWQKPRYGHRugZmmNs19eXl5bpVCiTTJDMyDzIn/by58QRjYgLp5Ge8awgvXyvh/c3JfDyhe63btYaMLuUU838/HWP+2CgCalmho6ml5ZXy+a5zZBQoeTSubY2XKLWGjMxdpYxK85pvdvk/F2qH3sc9V7/nZ5+BjU/DnfPBu/p5OIxOCO2SdIeXQb9ZEH5Ho+3K4GNJCO21/Cc3wPD3wSNMv+eV5cPO96A4E26bB25mfgnN5XjY8aZ2KL59PS+l1Ki1Kxac+Q2uxIOTrzbrdoN1JwtayjX1ZtnKa8h5CCEE6QVlWFi0ngY9tM7h9yZ2vqpOycnJzV0FqQ4yI/Mgc9LP8K5+bDLyEPylf15g2oC6v4C2hoxCPB15/75uPPvDUVJzS5q7OqTmlvDSumO89ctJxsQE8tmkmFrnHGkNGZm7ShnZu8HYlZD0d0O1qcQvh6IsuPXZ+pfRpoO24bb5/+DSXqNVrUbpSbBqnHbyuH/91KgNeqjHsaRQQI9JcOcHsOkFbZ61fafVaLQnAb6fpD2hM+ZL82/QAwTGaE9OrHkQSnL1f15ZvvY4WPe49vKDM79rL/WY+BOMXgJdRhu3999EmNXw++tnuUpKSuo1k/v1Br2VhQIvM5vARjJcSYn2S5TsaZAkSaqqe5Abi7aeNlp514pVpOaWEBXkZrQyzV2QhwPzx0bx7A9HeXdMV0I8m25G5+su5RSzZOc5ilVqpse1pYt/y/syK/3NyhZGLdEOvd7+ZuPPLn/8Z7h8CO7+T8P34+Stve775+l/rwE/2ihVrKT0Gux4R9vou3sRuPgbfx/G5B4KE1bD/k+1lyjcOR+cfStvcyUetr8FHe7QnqAwpUkHjcE/Gu54A358EMZ8Vf2EkEJoR3uc+Q0u/qk9DtrdBre90jyXdDQTg4ff//HHH3zwwQfEx8dz9epV1q1bx6hRo3SPCyGYN28eX3zxBXl5efTv358lS5bQoYN+kzPUNQTi6tWr5OXl4e3tjYODg97XAgohyCpUYmVpgYejEWeVNBOtafi9EIKSkhIyMzNxc3PDz888Dmg51NH0yYzMg8xJf69uOM7EPsF08Gn48kYfbztDVJAbceFedW7b2jK6ml/KnO+P8va9XQlr0zQN+/NZRXy68xxqjWB6XDs6+hqWcWvLyBzVmtHBL7TL3zXW7PLntkP8ChizFCyN2EeoroBfn4E24RA7wzhlatSQ8DUcXwdxL0BIP+OUqyejHEuZJ2HzixAzRXvCoygLtr+hfWzwXHCq+33XrGUc1/7+Y5Zqf9cKpbYBf+Z3yErWvl7Ch2qvkbcybMWvljL83uBG/aZNm9izZw8xMTHce++9VRr17733Hu+88w4rVqwgLCyMuXPncuzYMU6cOKHXdc11/WGFEKSnp5OXl1drORqNQC0Eao1AIwRl5RpsrCxwsjWrwQlGo1KpsLFpXScz3Nzc8PX1NZtVDVrius0tjczIPMic9HfwQi77zuXw1JCGzYpcqlLzyMrDfD2tt17vua0xo4yCMp7+PpFhkb54O9vh7WKLj4sdXk622FgZ76T7mYxCluw8h0Kh4PGB7WjvXb9loVpjRuamzoxObtQuzzb6M7AzYmPl8mH44wO4f0XjTMImhLb80mtwx1vaZfDqK/UQ7HwbOt4JMQ8a9wSEnox2LFWotH+X9L9AXQ6DX2q+iRGbQ+Yp+PVZcPCEijII6a9tyLcJb9BIkZbSqDf4lT18+HCGDx9e7WNCCBYtWsTLL7/MyJEjAVi5ciU+Pj78/PPPjB8/vkGV1WgEOcUqcoUDmQoF1wpLyC1Sae8rLqdCo+F6pE52Vng42uLpaIuHkw0BXvaEG6EnwlydPn2asDA9J9poAaytrbG0rMeMoZIkSa1IzxB3/rP9TIPL+TE+lft7BprNSdTm4ONix6cTe5CQkkdmYRlnMgrJLFSSVaikQqPRXTLr6mCNt7MdPi62usa/t7P2//Y2NX+unbxawJKd57C3tmTWbR0IbaIRAZIJ63SXdli7MWeXzzypHdo/dmXjzaquUEDc89rrxNc+AiM/MXxfhRmw7XXtmu/3fln9sG1zY2WjbcjnXwFnv4ad7DBH3hFw3zLtyBN7t+aujclp0Oz3CoWiUk/9+fPnadeuHQkJCURHR+u2i4uLIzo6mo8++qhKGUqlstIkbgUFBQQFBfH2ungKNNZkFynRaIRuf56ONroPOK8bPuy8nG2xtZKNuJrIYXSmT2Zk+mRG5kHmZJhX1icxOTa03j26FWoNk786yMqHemNlqd+XTJlR9YQQ5JWUk1moJLOwjMwC5T//L1RSplLrtnWys9I19o9ezsPF3prH49oR5OFglLrIjEyf3hlln4WNsxs+u/y1S7B+hrZh1VTDvc9uhf2fwb3/BQePurdXl8OBz+D8Tu2wdP/oxq5hneSxZNpabU99bdLT0wHw8fGpdL+Pj4/usZu98847vPbaa1XuH9jRi7YBXng62uj9JUGqWXJyshxGZ+JkRqZPZmQeZE6GGR7px+akq8ysY235mvyalM4dnX0M+qyWGVVPoVDg7miDu6NNrdfACyEoUlZoG/wFSkZ088PfyMvmyYxMn94ZtWmvnV1+7aNw63MQ2t/wnRVlahv0o5Y07fXb7YeAQxtYMwXuWQzuITVve267dnm96H9p12c3kZFD8liSmkKzt5ZffPFF8vPzdbfU1FQAugS44uNiJxv0RtJaJskzZzIj0yczMg8yJ8P0DvPgwAUDlgu6gRCCNYdTGdvLsOWTZEYNo1AocLazpp2XE7HtPI3eoAeZkTkwKKPrs8sfWKKdMM4QpXnaYfAjFjTPUmn+0doG/foZcPVo1cevXdIue3ZuB4xfBVHjTKZBD/JYkpqGUV9lvr7aZRYyMjIq3Z+RkaF77Ga2tra4uLhUuknG17Zt2+auglQHmZHpkxmZB5mTYSwtFAR5OHAxu9jg5/55Npsewe442Bg28E9mZPpkRqbP4IxsneC+5XB+F+z7RL/nqEq0Dfrb5oFXR4PraDTuIdrr+Le9oR2Sf71uO96G3/4Ng/6tXfrM1vTmz5LHktQUjNqoDwsLw9fXl23btunuKygo4MCBA8TGxhpzV5KBzp4929xVkOogMzJ9MiPzIHMy3J2RfmxKqv4yudqs2HuJKf1CDX6ezMj0yYxMX70ysrSCuxaCqli7RJhGXfO26nJY9yjEzoSAHvWvqLE4eGhHGyR+B1vmwaqx4Betva9Nw1bwaEzyWJKagsGN+qKiIhITE0lMTATgwoULJCYmkpKSgkKhYPbs2bz55pts2LCBY8eOMXnyZPz9/Ssteyc1PSur1rmUnzmRGZk+mZF5kDkZrk9bD/afzzHoOccu5xPgZoeHo+HLpcqMTJ/MyPTVO6Prs8v7RGqvsy8vq7qNRgMbnoRu46FtXMMqakzWdnDvFxDUW3vdfMSdJjXUvjryWJKagsGvssOHDzNo0CDdz3PmzAFgypQpLF++nOeff57i4mIeffRR8vLyGDBgAJs3b9ZrjXqp8QQHBzd3FaQ6yIxMn8zIPMicDGdtaYGvix2puSV6z56+9M/zPHNH/YbjyoxMn8zI9DU4o+4TwdkHvv9X5dnlhYDN/wehA7TL4pkaCwuIGNHctdCbPJakpmBwT/3AgQMRQlS5LV++HNBO3vL666+Tnp5OWVkZW7duJTw83Nj1lgx0/vz55q6CVAeZkemTGZkHmVP9DO/qy2Y9h+BfyilGoVDUe/k0mZHpkxmZPqNk1H4I3DYXfpisnXAOYOe72gnxuv+r4eVL8liSmoScjrGVsLW1be4qSHWQGZk+mZF5kDnVT792bdhzLluvbb/cfYFpA8LqvS+ZkemTGZk+o2XkFwWjPtXOLv/bS6BWQb8njVO2JI8lqUnIRn0rUdPqA5LpkBmZPpmReZA51Y+NlQVeTrak5ZXWul12kZL0gjIiA1zrvS+ZkemTGZk+o2bkFqydXd4jDG57xXjlSvJYkpqEbNS3EpcuXWruKkh1kBmZPpmReZA51d/wrr51zoK/cu9FptZjxvsbyYxMn8zI9Bk9IwcP6PWwyU88Z27ksSQ1BdmobyXs7e2buwpSHWRGpk9mZB5kTvXXv30b/jyTVePjxcoKElLz6NfOs0H7kRmZPpmR6ZMZmQeZk9QUZKO+lWjTpk1zV0Gqg8zI9MmMzIPMqf5srSxxd7AhPb+aJa6A7w+lMq5XEIoG9uTJjEyfzMj0yYzMg8xJagqyUd9KpKamNncVpDrIjEyfzMg8yJwaZlikL78drzoEv1ytYevJDIZH+jV4HzIj0yczMn0yI/Mgc5KagmzUtxJOTk7NXQWpDjIj0yczMg8yp4a5NdyLP05XHYK/8a80hnf1w9Ki4dfbyoxMn8zI9MmMzIPMSWoKslHfSri4uDR3FaQ6yIxMn8zIPMicGsbO2hInOyuyCpW6+4QQ/Bh/mftjAo2yD5mR6ZMZmT6ZkXmQOUlNQTbqW4m0tLTmroJUB5mR6ZMZmQeZU8MN61J5CP7O01n0DfPEztrSKOXLjEyfzMj0yYzMg8xJagqyUd9KyLOEpk9mZPpkRuZB5tRwAzt6szP5nyH4X++7xKTYEKOVLzMyfTIj0yczMg8yJ6kpNFqj/pNPPiE0NBQ7Ozv69OnDwYMHG2tXkh4cHByauwpSHWRGpk9mZB5kTg1nb2OJvY0lOUVKElKuEerpiJuDjdHKlxmZPpmR6ZMZmQeZk9QUGqVR//333zNnzhzmzZvHkSNHiIqKYujQoWRmZjbG7iQ9pKdXnclYMi0yI9MnMzIPMifjGNrFhy0nMlj65wWm3RJm1LJlRqZPZmT6ZEbmQeYkNYVGadR/+OGHPPLIIzz44IN07tyZzz77DAcHB7766qvG2J2kB3d39+auglQHmZHpkxmZB5mTcQzq6M2qgynYWlkS4GZv1LJlRqZPZmT6ZEbmQeYkNQWjN+pVKhXx8fEMGTLkn51YWDBkyBD27dtXZXulUklBQUGlm2R81tbWzV0FqQ4yI9MnMzIPMifjcLS1IsLXmUdvbWv0smVGpk9mZPpkRuZB5iQ1BaM36rOzs1Gr1fj4+FS638fHp9rhJ++88w6urq66W1BQkLGrJIG89MEMyIxMn8zIPMicjOf9+6Lo6Ots9HJlRqZPZmT6ZEbmQeYkNYVmn/3+xRdfJD8/X3dLTU1t7iq1SJ6ens1dBakOMiPTJzMyDzIn0yczMn0yI9MnMzIPMiepKVgZu8A2bdpgaWlJRkZGpfszMjLw9fWtsr2trS22trbGroYkSZIkSZIkSZIktXhGb9Tb2NgQExPDtm3bGDVqFAAajYZt27Yxc+bMOp8vhACQ19Yb2aVLl3B0dGzuaki1kBmZPpmReZA5mT6ZkemTGZk+mZF5kDmZtuttzuttUHNl9EY9wJw5c5gyZQo9e/akd+/eLFq0iOLiYh588ME6n1tYWAggr62XJEmSJEmSJEmSGl1OTg6urq7NXY16a5RG/bhx48jKyuKVV14hPT2d6OhoNm/eXGXyvOr4+/uTmpqKs7MzCoWiMarX6hQUFBAUFERqaiouLi7NXR2pGjIj0yczMg8yJ9MnMzJ9MiPTJzMyDzIn05efn09wcDAeHh7NXZUGaZRGPcDMmTP1Gm5/MwsLCwIDAxuhRpKLi4t8QzFxMiPTJzMyDzIn0yczMn0yI9MnMzIPMifTZ2HR7PPHN4h5116SJEmSJEmSJEmSWjHZqJckSZIkSZIkSZIkMyUb9a2Ara0t8+bNk0sHmjCZkemTGZkHmZPpkxmZPpmR6ZMZmQeZk+lrKRkphLnP3y9JkiRJkiRJkiRJrZTsqZckSZIkSZIkSZIkMyUb9ZIkSZIkSZIkSZJkpmSjXpIkSZIkSZIkSZLMlGzUS5IkSZIkSZIkSZKZko16SZIkSZIkSZIkSTJTslFvRO+88w69evXC2dkZb29vRo0aRXJycqVtysrKmDFjBp6enjg5OTFmzBgyMjIqbTNr1ixiYmKwtbUlOjq6yn4uXryIQqGoctu/f3+t9fvjjz+4++678ff3R6FQ8PPPP1d6vLy8nBdeeIGuXbvi6OiIv78/kydPJi0trc7fPSUlhREjRuDg4IC3tzfPPfccFRUVlbZRKpW89NJLhISEYGtrS2hoKF999VWdZRtTa86orjqXlZUxdepUunbtipWVFaNGjaqzzMYgM6q5zgBCCObPn094eDi2trYEBATw1ltv1Vm2MbXWjI4ePcqECRMICgrC3t6eTp068dFHH1Xa5urVqzzwwAOEh4djYWHB7Nmzay2zMcmcas4J5GdSc2aUk5PDsGHD8Pf3x9bWlqCgIGbOnElBQYFuG1M5lpoqI6j/+/uaNWuIiIjAzs6Orl278uuvv1Z6fO3atdxxxx14enqiUChITEzU63fPzc1l4sSJuLi44ObmxrRp0ygqKtI9Xt/XlbG15ozeeust+vXrh4ODA25ubtVuo8939KYgc6o9p+qOpdWrV+tVPshGvVHt2rWLGTNmsH//frZs2UJ5eTl33HEHxcXFum2efvpp/ve//7FmzRp27dpFWloa9957b5WyHnroIcaNG1fr/rZu3crVq1d1t5iYmFq3Ly4uJioqik8++aTax0tKSjhy5Ahz587lyJEjrF27luTkZO65555ay1Wr1YwYMQKVSsXevXtZsWIFy5cv55VXXqm03dixY9m2bRtLly4lOTmZ7777jo4dO9ZatrG11oz0qbNarcbe3p5Zs2YxZMgQvcprDDKj2uv81FNP8eWXXzJ//nxOnTrFhg0b6N27t15lG0trzSg+Ph5vb2+++eYbjh8/zksvvcSLL77I4sWLddsolUq8vLx4+eWXiYqKqrW8xiZzqjknkJ9JzZmRhYUFI0eOZMOGDZw+fZrly5ezdetWpk+frtvGVI6lpsyoPu/ve/fuZcKECUybNo2EhARGjRrFqFGjSEpK0m1TXFzMgAEDeO+99wz63SdOnMjx48fZsmULGzdu5I8//uDRRx+tsp2hrytja80ZqVQq7r//fh5//PFqH9f3O3pTkDnVnNN1y5Ytq3QsGdTBJqRGk5mZKQCxa9cuIYQQeXl5wtraWqxZs0a3zcmTJwUg9u3bV+X58+bNE1FRUVXuv3DhggBEQkJCvesGiHXr1tW53cGDBwUgLl26VOM2v/76q7CwsBDp6em6+5YsWSJcXFyEUqkUQgixadMm4erqKnJycupd58bQWjK6UU11vtGUKVPEyJEj9SqvscmM/nHixAlhZWUlTp06ZWBNG1drzOi6J554QgwaNKjax+Li4sRTTz1lUHmNSeb0T07yM8lwjZ3RRx99JAIDA6t9zJSOpcbKqL7v72PHjhUjRoyodF+fPn3EY489VmVbQ14HJ06cEIA4dOiQ7r5NmzYJhUIhrly5YnB5Tam1ZHSjZcuWCVdX1yr36/MdvbnInCrT9z22JrKnvhHl5+cD4OHhAWh7D8rLyyv1gkZERBAcHMy+ffsMLv+ee+7B29ubAQMGsGHDBuNU+ib5+fkoFIoah4oA7Nu3j65du+Lj46O7b+jQoRQUFHD8+HEANmzYQM+ePXn//fcJCAggPDycZ599ltLS0kapt75aS0bmTGb0j//973+0bduWjRs3EhYWRmhoKA8//DC5ubnGqWg9teaM8vPzdb+3qZM5/ZOT/EwyrYzS0tJYu3YtcXFxjVInY2qsjOr7/r5v374qo+uGDh1ar9fHzeW6ubnRs2dP3X1DhgzBwsKCAwcOVNq2KV5XhmgtGelDn+/ozUXmVNWMGTNo06YNvXv35quvvkLb1tePVSPWq1XTaDTMnj2b/v37ExkZCUB6ejo2NjZVPuh8fHxIT0/Xu2wnJycWLFhA//79sbCw4KeffmLUqFH8/PPPeg/x1UdZWRkvvPACEyZMwMXFpcbt0tPTK71ZALqfr/9e58+f588//8TOzo5169aRnZ3NE088QU5ODsuWLTNanQ3RmjIyVzKjys6fP8+lS5dYs2YNK1euRK1W8/TTT3Pfffexfft2I9XYMK05o7179/L999/zyy+/GK0ujUXmVDkn+ZlkGhlNmDCB9evXU1payt13382XX35ptLo0hsbMqL7v7zV9BzNk3zWV6+3tXek+KysrPDw8dGU31evKEK0pI33o8x29Ocicqnr99dcZPHgwDg4O/P777zzxxBMUFRUxa9YsvZ4ve+obyYwZM0hKSjJoggN9tWnThjlz5tCnTx969erFu+++y7/+9S8++OADAHbv3o2Tk5Pu9u233xq8j/LycsaOHYsQgiVLlujuHz58uK7cLl266F2eRqNBoVDw7bff0rt3b+68804+/PBDVqxY0Ww9IzIj0yczqkyj0aBUKlm5ciW33HILAwcOZOnSpezYsaPKZDNNpbVmlJSUxMiRI5k3bx533HFH/X/JJiJzqpyT/EwyjYwWLlzIkSNHWL9+PefOnWPOnDkN+0UbWWNmVNf7e0pKSqWM3n77baPte/r06ZXK1lddr6vmIDMyDzKnqubOnUv//v3p3r07L7zwAs8//7xBx5LsqW8EM2fO1E0oEhgYqLvf19cXlUpFXl5epbNQGRkZ+Pr6Nmifffr0YcuWLQD07Nmz0myMN591qsv1D+ZLly6xffv2Smfbv/zyS90XHmtra0D7ex08eLBSGddnqrz+e/n5+REQEICrq6tum06dOiGE4PLly3To0MGgOjZUa8vIHMmMqvLz88PKyorw8HDdfZ06dQK0s9s29SRfrTWjEydOcNttt/Hoo4/y8ssv1/M3aToyp6o5yc8k08jI19cXX19fIiIi8PDw4JZbbmHu3Ln4+fnV87dqPI2dUV3v74MGDaqU0fUhy76+vlVmBzd036+//jrPPvtspft8fX3JzMysdF9FRQW5ubm1ln3j66qptbaM9KHPd/SmJnPST58+fXjjjTdQKpXY2trWub1s1BuREIInn3ySdevWsXPnTsLCwio9HhMTg7W1Ndu2bWPMmDEAujNGsbGxDdp3YmKi7kPQ3t6e9u3b16uc6x/MZ86cYceOHXh6elZ6PCAgoMpzYmNjeeutt8jMzNQN1dqyZQsuLi507twZgP79+7NmzRqKiop0Z65Onz6NhYVFpQO6sbXWjMyJzKhm/fv3p6KignPnztGuXTtAexwBhISE1KvM+mjNGR0/fpzBgwczZcqUJl9K0FAyp5pzkp9JzZ/RzTQaDaCd9d6UNFVGdb2/W1lZVZtRbGws27Ztq7Tk35YtWwzat7e3d5Wh9rGxseTl5REfH6+bzX779u1oNBr69OlTY1k3vq6aSmvNSB/6fEdvKjInwyQmJuLu7q5Xgx5ko96oZsyYwapVq1i/fj3Ozs66azBcXV2xt7fH1dWVadOmMWfOHDw8PHBxceHJJ58kNjaWvn376so5e/YsRUVFpKenU1paqjub1LlzZ2xsbFixYgU2NjZ0794d0K6Z+NVXX9V5LVpRURFnz57V/XzhwgUSExPx8PAgODiY8vJy7rvvPo4cOcLGjRtRq9W638HDwwMbG5tqy73jjjvo3LkzkyZN4v333yc9PZ2XX36ZGTNm6F6IDzzwAG+88QYPPvggr732GtnZ2Tz33HM89NBD2Nvb1+8PXg+tNSN96gzani2VSkVubi6FhYW6bWpaB7QxyIxqrvOQIUPo0aMHDz30EIsWLUKj0TBjxgxuv/32SmekG1trzSgpKYnBgwczdOhQ5syZo3uOpaUlXl5euu2u/x5FRUVkZWWRmJiIjY1Nk3+BkjnVnJP8TGrejH799VcyMjLo1asXTk5OHD9+nOeee47+/fsTGhqq284UjqWmyqi+7+9PPfUUcXFxLFiwgBEjRrB69WoOHz7Mf//7X902ubm5pKSkkJaWBqC7XOv6SInqdOrUiWHDhvHII4/w2WefUV5ezsyZMxk/fjz+/v4A9X5dGVtrzQi0Pc/Xn6tWq3V1bt++PU5OTnp9R28qMqeac/rf//5HRkYGffv2xc7Oji1btvD2228b1utf73nzpSqAam/Lli3TbVNaWiqeeOIJ4e7uLhwcHMTo0aPF1atXK5UTFxdXbTkXLlwQQgixfPly0alTJ+Hg4CBcXFxE7969Ky3/UJMdO3ZUW+6UKVOEEP8sz1DdbceOHbWWffHiRTF8+HBhb28v2rRpI5555hlRXl5eaZuTJ0+KIUOGCHt7exEYGCjmzJkjSkpK6qy3MbXmjOqqsxBChISEVLtNU5IZ1Z7RlStXxL333iucnJyEj4+PmDp1apMvy9VaM5o3b161zwkJCanz73PzNk1B5lR7BvIzqfky2r59u4iNjRWurq7Czs5OdOjQQbzwwgvi2rVrdf59mvpYaqqMhKj/+/sPP/wgwsPDhY2NjejSpYv45ZdfKj2+bNmyavc9b968Wmb4A9YAAAEISURBVMvNyckREyZMEE5OTsLFxUU8+OCDorCwUPd4fV9XxtaaM5oyZUqdx58+39Gbgsyp5pw2bdokoqOjhZOTk3B0dBRRUVHis88+E2q1us46X6cQwoC58iVJkiRJkiRJkiRJMhly9ntJkiRJkiRJkiRJMlOyUS9JkiRJkiRJkiRJZko26iVJkiRJkiRJkiTJTMlGvSRJkiRJkiRJkiSZKdmolyRJkiRJkiRJkiQzJRv1kiRJkiRJkiRJkmSmZKNekiRJkiRJkiRJksyUbNRLkiRJkiRJkiRJkpmSjXpJkiRJkiRJkiRJMlOyUS9JkiRJkiRJkiRJZko26iVJkiRJkiRJkiTJTP0/pr2mez/eZM0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1024x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def compute_predictions_at_timepoint(predictions):\n",
+    "    index_names = test_examples.schema.index_names()\n",
+    "    rows = []\n",
+    "    for index_values, feature_values in predictions.data.items():\n",
+    "        \n",
+    "        # First prediction for each label\n",
+    "        values = [ feature[0] for feature in feature_values.features ]\n",
+    "        timestamps = map(datetime.utcfromtimestamp, feature_values.timestamps[:len(values)])\n",
+    "        # datetime.utcfromtimestamp(\n",
+    "\n",
+    "        # TODO: use from_struct instead when available.\n",
+    "        # https://temporian.readthedocs.io/en/latest/reference/temporian/io/from_struct/\n",
+    "        index_map = { index_name:index_value for index_name, index_value in zip(index_names, index_values) }\n",
+    "        for value, timestamp in zip(values,timestamps):\n",
+    "            rows.append({\"value\": value, \"timestamp\": timestamp, **index_map})\n",
+    "        \n",
+    "    return tp.from_pandas(pd.DataFrame(rows), indexes = index_names)\n",
+    "\n",
+    "predictions_at_point = compute_predictions_at_timepoint(predictions)\n",
+    "\n",
+    "tp.plot([\n",
+    "    sales.before(end_train_cutoff).rename(\"observations\"),\n",
+    "    sales.after(end_train_cutoff).rename(\"ground truth\"),\n",
+    "    predictions_at_point.rename(\"predictions\"),\n",
+    "],\n",
+    "        merge=True,\n",
+    "        max_num_plots=4,\n",
+    "        min_time= end_train_cutoff - timedelta(days=30),\n",
+    "        max_time= end_train_cutoff + timedelta(days=14),\n",
+    "       )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c102e64e-ac5a-48ca-91b3-c8cb1326c9f3",
+   "metadata": {},
+   "source": [
+    "## More advanced features\n",
+    "\n",
+    "Now that we have our setup in place, we can experiment with more advances feature engineering to improve our model power. We will generate the following features:\n",
+    "\n",
+    "- Moving statistics: Aggregation of past values over a moving window such as moving sum, moving average, moving standard deviation.\n",
+    "- Calendar events: Access to special calendar events e.g. father's day.\n",
+    "- Calendar features: Human activities are strongly related to th day of the week (people don't have the same activity on monday that on sunday), day of the month and month of the day.\n",
+    "- Hierarchical aggregations: Aggregating values from related products e.g. products in the same departments or the same product in other stores."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/src/tutorials/tutorial_scipy2024_part4.ipynb b/docs/src/tutorials/tutorial_scipy2024_part4.ipynb
new file mode 100644
index 000000000..f5934de7e
--- /dev/null
+++ b/docs/src/tutorials/tutorial_scipy2024_part4.ipynb
@@ -0,0 +1,33 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7a7aadd9-5fee-48d5-8231-2d38255af726",
+   "metadata": {},
+   "source": [
+    "## Part 4: Deep Learning Forecasting"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}