diff --git a/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_exogen.py b/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_exogen.py
new file mode 100644
index 000000000..3eb15a55a
--- /dev/null
+++ b/examples/automl_example/api_example/time_series/ts_forecasting/ts_forecasting_exogen.py
@@ -0,0 +1,32 @@
+import numpy as np
+import pandas as pd
+
+from fedot_ind.api.main import FedotIndustrial
+from fedot_ind.api.utils.path_lib import PROJECT_PATH
+
+if __name__ == "__main__":
+    dataset_name = PROJECT_PATH + '/examples/data/forecasting\monash_benchmark\MonashBitcoin_30.csv'
+    horizon = 30
+    metric_names = ('smape', 'rmse', 'median_absolute_error')
+
+    train_data = pd.read_csv(dataset_name)
+    variables = train_data['label'].unique().tolist()
+    exog_var = ['send_usd', 'market_cap', 'median_transaction_value', 'google_trends']
+    exog_ts = np.vstack([train_data[train_data['label'] == var]['value'].values for var in exog_var])
+    exog_ts = exog_ts[0, :]
+    ts = train_data[train_data['label'] == 'price']['value'].values
+    target = ts[-horizon:].flatten()
+    input_data = (ts, target)
+
+    api_config = dict(problem='ts_forecasting',
+                      metric='rmse',
+                      timeout=15,
+                      with_tuning=False,
+                      pop_size=10,
+                      industrial_strategy_params={'exog_variable': exog_ts},
+                      task_params={'forecast_length': horizon},
+                      industrial_strategy='forecasting_exogenous',
+                      n_jobs=2,
+                      logging_level=30)
+    industrial = FedotIndustrial(**api_config)
+    industrial.fit(input_data)
diff --git a/examples/real_world_examples/industrial_examples/sentiment_analysis/ts_regression/__init__.py b/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_forecasting/__init__.py
similarity index 100%
rename from examples/real_world_examples/industrial_examples/sentiment_analysis/ts_regression/__init__.py
rename to examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_forecasting/__init__.py
diff --git a/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_forecasting/bitcoin_forecasting.ipynb b/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_forecasting/bitcoin_forecasting.ipynb
new file mode 100644
index 000000000..3c52a6a05
--- /dev/null
+++ b/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_forecasting/bitcoin_forecasting.ipynb
@@ -0,0 +1,633 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Predict historical prices of Brent Oil, Crude Oil WTI, Natural Gas, Heating Oil from 2000-2022 with Fedot.Industrial"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "Dataset published on Kaggle3 consists of historical prices of Brent Oil, CrudeOil WTI, Natural Gas, and Heating Oil from 2000 to 2022. This sample of DailyOilGasPrices was created by using 30 consecutive business days of **Crude Oil WTI close prices** and **traded volumes** as **predictors** and the **average natural gas close** price during each 30-day time frame as the **target** variable. The final dataset has 191 2-dimensional time series of length 30, of which 70% were randomly sampled as training data and the remaining 30% as testing data. This type of model could help companies and governments to better analyse and predict economic situations and correlations regarding oil and natural gas.\n",
+    "Link to the dataset - https://www.kaggl.com/datasets/prasertk/historical-daily-oil-and-natural-gas-prices"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from fedot_ind.api.main import FedotIndustrial"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "outputs": [],
+   "source": [
+    "def evaluate_loop(train_data, api_params, finetune: bool = False):\n",
+    "    industrial = FedotIndustrial(**api_params)\n",
+    "    if finetune:\n",
+    "        industrial.finetune(train_data)\n",
+    "    else:\n",
+    "        industrial.fit(train_data)\n",
+    "    return industrial"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "outputs": [],
+   "source": [
+    "from fedot_ind.api.utils.path_lib import PROJECT_PATH\n",
+    "\n",
+    "dataset_name = PROJECT_PATH +'/examples/data/forecasting\\monash_benchmark\\MonashBitcoin_30.csv'\n",
+    "horizon = 12\n",
+    "metric_names = ('smape', 'rmse', 'median_absolute_error')\n",
+    "train_data = pd.read_csv(dataset_name)\n",
+    "params = dict(problem='ts_forecasting',\n",
+    "                             metric='rmse',\n",
+    "                             timeout=15,\n",
+    "                             pop_size = 10,\n",
+    "                             with_tuning = False,\n",
+    "                             task_params={'forecast_length': horizon},\n",
+    "                             industrial_strategy='forecasting_assumptions',\n",
+    "                             n_jobs=2,\n",
+    "                             logging_level=50)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "         datetime    value       label\n0      2009-01-03      1.0  difficulty\n1      2009-01-04      1.0  difficulty\n2      2009-01-05      1.0  difficulty\n3      2009-01-06      1.0  difficulty\n4      2009-01-07      1.0  difficulty\n...           ...      ...         ...\n82453  2021-07-15  32109.0       price\n82454  2021-07-16  31750.0       price\n82455  2021-07-17  31556.0       price\n82456  2021-07-18  31763.0       price\n82457  2021-07-19  30593.0       price\n\n[82458 rows x 3 columns]",
+      "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>datetime</th>\n      <th>value</th>\n      <th>label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2009-01-03</td>\n      <td>1.0</td>\n      <td>difficulty</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2009-01-04</td>\n      <td>1.0</td>\n      <td>difficulty</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2009-01-05</td>\n      <td>1.0</td>\n      <td>difficulty</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2009-01-06</td>\n      <td>1.0</td>\n      <td>difficulty</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2009-01-07</td>\n      <td>1.0</td>\n      <td>difficulty</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>82453</th>\n      <td>2021-07-15</td>\n      <td>32109.0</td>\n      <td>price</td>\n    </tr>\n    <tr>\n      <th>82454</th>\n      <td>2021-07-16</td>\n      <td>31750.0</td>\n      <td>price</td>\n    </tr>\n    <tr>\n      <th>82455</th>\n      <td>2021-07-17</td>\n      <td>31556.0</td>\n      <td>price</td>\n    </tr>\n    <tr>\n      <th>82456</th>\n      <td>2021-07-18</td>\n      <td>31763.0</td>\n      <td>price</td>\n    </tr>\n    <tr>\n      <th>82457</th>\n      <td>2021-07-19</td>\n      <td>30593.0</td>\n      <td>price</td>\n    </tr>\n  </tbody>\n</table>\n<p>82458 rows × 3 columns</p>\n</div>"
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "Now we must download the dataset. It could be done by using `DataReader` class that implemented as attribute of `FedotIndustrial` class. This class firstly tries to read the data from local project folder `data_path` and then if it is not possible, it downloads the data from the UCR/UEA archive. The data will be saved in the `data` folder."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "dict_keys(['difficulty', 'sent_addresses', 'send_usd', 'market_cap', 'confirmation_time', 'transactions', 'median_transaction_size', 'mining_profitability', 'fee_reward', 'top_100_percent', 'median_transaction_value', 'av_transaction_value', 'block_size', 'hashrate', 'active_addresses', 'google_trends', 'tweets', 'price'])"
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_split.keys()"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "outputs": [],
+   "source": [
+    "id_list = train_data['label'].unique().tolist()\n",
+    "data_split = {id:train_data[train_data['label']==id]['value'].values for id in id_list}"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "Lets check our data."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "Lets visualise our predictors."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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octdNIiIiahpSU1PRqlWrWss0yYBSfsOy1NTUWqcqJyIiIvnQarXw9fU1uPFoTZpkQCm/rOPs7MyAQkRE1MTcT/cMdpIlIiIi2WFAISIiItlhQCEiIiLZaZJ9UIiIiJoiIQTKyspqvcdSU2ZtbQ0bG5sGmQKEAYWIiKgRlJSUIC0tDYWFhZauilk5ODjA29sbSqWyXtthQCEiIjIzvV6PlJQUWFtbw8fHB0ql8oGbaFQIgZKSEty8eRMpKSno2LFjnZOx1YYBhYiIyMxKSkqg1+vh6+sLBwcHS1fHbOzt7WFra4srV66gpKQEdnZ2Jm+LnWSJiIgaSX1aFJqKhjrGB/+dIiIioiaHAYWIiIhkhwGFiIiIZIcBhYiIiOq0YsUKtG3bFnZ2dggJCcGRI0fMuj8GFDPanHgde5MzLV0NIiKievn+++8RGRmJuXPn4vjx4wgKCkJYWBgyM833GcdhxmZy7XYh3lyfCAC4vGikZStDRESyI4TAnVLLzChrb2tt1DwsS5cuxeTJk/Hyyy8DAL744gv8+uuv+Oabb/Duu++apY4MKGZyK7/E0lUgIiIZu1OqQ8CcHRbZd9KCMDgo7y8ClJSUICEhAVFRUdIyKysrhIaGIj4+3lxV5CUeIiIiqllWVhZ0Oh28vLwMlnt5eSE9Pd1s+2ULChERkQXY21ojaUGYxfYtdwwoREREFqBQKO77MosleXh4wNraGhkZGQbLMzIyoFarzbZfXuIhIiKiGimVSgQHB2P37t3SMr1ej927d0Oj0Zhtv0YFlFWrViEwMBDOzs5wdnaGRqPBtm3bpPUDBw6EQqEweLz22msG27h69SpGjhwJBwcHeHp6YubMmSgrK2uYoyEiIqIGFxkZia+++grffvstzp49i6lTp6KgoEAa1WMORrUttWrVCosWLULHjh0hhMC3336LJ598Er///ju6du0KAJg8eTIWLFggvabiXRt1Oh1GjhwJtVqNgwcPIi0tDRMmTICtrS0WLlzYQIckDw/YXbSJiOgh9uyzz+LmzZuYM2cO0tPT0aNHD2zfvr1Kx9mGZFRAGT16tMHzf/7zn1i1ahUOHTokBRQHB4car0nt3LkTSUlJ2LVrF7y8vNCjRw988MEHmDVrFubNmwelUmniYRAREZE5TZs2DdOmTWu0/ZncB0Wn02H9+vUoKCgwuAa1du1aeHh4oFu3boiKikJhYaG0Lj4+Ht27dzdIXGFhYdBqtThz5kyN+youLoZWqzV4EBER0YPL6O7Dp06dgkajQVFRERwdHbFx40YEBAQAAJ5//nm0adMGPj4+OHnyJGbNmoXk5GRs2LABAJCenl7tOOrydTWJjo7G/Pnzja0qERERNVFGBxR/f38kJiYiNzcXP/30EyZOnIi4uDgEBARgypQpUrnu3bvD29sbQ4YMwcWLF9G+fXuTKxkVFYXIyEjpuVarha+vr8nbIyIiInkz+hKPUqlEhw4dEBwcjOjoaAQFBeHTTz+ttmxISAgA4MKFCwAAtVpd7Tjq8nU1UalU0sih8ofcCWHpGhARETVd9Z4HRa/Xo7i4uNp1iYmJAABvb28AgEajwalTpwzufhgbGwtnZ2fpMhEREdGDSjwE314b6hiNusQTFRWF4cOHo3Xr1sjLy0NMTAz27duHHTt24OLFi4iJicGIESPg7u6OkydP4q233kL//v0RGBgIABg6dCgCAgLw4osvYvHixUhPT8fs2bMREREBlUrVIAckFxxmTERE5WxtbQEAhYWFsLe3t3BtzKt8cEz5MZvKqICSmZmJCRMmIC0tDS4uLggMDMSOHTvwxBNPIDU1Fbt27cInn3yCgoIC+Pr6Ijw8HLNnz5Zeb21tjS1btmDq1KnQaDRo1qwZJk6caDBvChER0YPG2toarq6u0hUEBwcHKB6wb7JCCBQWFiIzMxOurq6wtq7f/X6MCihff/11jet8fX0RFxdX5zbatGmDrVu3GrNbIiKiJq+8r2XFbg4PIldX1wa5R4/871JERET0AFAoFPD29oanpydKS0stXR2zsLW1rXfLSTkGFCIiokZkbW3dYB/iDzLezZiIiIhkhwHFTBR4sDo/ERERNSYGFCIiIpIdBhQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikh0GFDNR8F6BREREJmNAISIiItlhQCEiIiLZYUAhIiIi2WFAMRMhKv4sai5IREREVTCgEBERkewwoJgJR/EQERGZjgGFiIiIZIcBhYiIiGSHAYWIiIhkhwGFiIiIZIcBpRFwlDEREZFxGFCIiIhIdhhQiIiISHYYUIiIiEh2GFCIiIhIdhhQiIiISHYYUBoBB/EQEREZhwGFiIiIZIcBhYiIiGTHqICyatUqBAYGwtnZGc7OztBoNNi2bZu0vqioCBEREXB3d4ejoyPCw8ORkZFhsI2rV69i5MiRcHBwgKenJ2bOnImysrKGORoiIiJ6IBgVUFq1aoVFixYhISEBx44dw+DBg/Hkk0/izJkzAIC33noLv/zyC3788UfExcXhxo0bGDt2rPR6nU6HkSNHoqSkBAcPHsS3336LNWvWYM6cOQ17VERERNSkKYSo30Tsbm5uWLJkCZ5++mm0aNECMTExePrppwEA586dQ5cuXRAfH48+ffpg27ZtGDVqFG7cuAEvLy8AwBdffIFZs2bh5s2bUCqV97VPrVYLFxcX5ObmwtnZuT7VN5vT13MxavkBAMDFhSNgbaWwcI2IiIgsy5jPb5P7oOh0Oqxfvx4FBQXQaDRISEhAaWkpQkNDpTKdO3dG69atER8fDwCIj49H9+7dpXACAGFhYdBqtVIrTHWKi4uh1WoNHk1JPTMgERHRQ8fogHLq1Ck4OjpCpVLhtddew8aNGxEQEID09HQolUq4uroalPfy8kJ6ejoAID093SCclK8vX1eT6OhouLi4SA9fX19jq01ERERNiNEBxd/fH4mJiTh8+DCmTp2KiRMnIikpyRx1k0RFRSE3N1d6pKammnV/DUHBKzpEREQmszH2BUqlEh06dAAABAcH4+jRo/j000/x7LPPoqSkBDk5OQatKBkZGVCr1QAAtVqNI0eOGGyvfJRPeZnqqFQqqFQqY6tKRERETVS950HR6/UoLi5GcHAwbG1tsXv3bmldcnIyrl69Co1GAwDQaDQ4deoUMjMzpTKxsbFwdnZGQEBAfatCREREDwijWlCioqIwfPhwtG7dGnl5eYiJicG+ffuwY8cOuLi4YNKkSYiMjISbmxucnZ0xffp0aDQa9OnTBwAwdOhQBAQE4MUXX8TixYuRnp6O2bNnIyIigi0kREREJDEqoGRmZmLChAlIS0uDi4sLAgMDsWPHDjzxxBMAgGXLlsHKygrh4eEoLi5GWFgYVq5cKb3e2toaW7ZswdSpU6HRaNCsWTNMnDgRCxYsaNijkoGKA3c4hoeIiMg49Z4HxRKa2jwo5/85HLbWvKsAERE93BplHhQiIiIic2FAMRMOMyYiIjIdAwoRERHJDgMKERERyQ4DChEREckOA0ojaHrjpIiIiCyLAYWIiIhkhwHFTBTgMB4iIiJTMaAQERGR7DCgEBERkewwoJiJ4B14iIiITMaA0ggYVoiIiIzDgEJERESyw4BiJhzFQ0REZDoGFCIiIpIdBhQiIiKSHQYUIiIikh0GlEbAe/EQEREZhwGFiIiIZIcBhYiIiGSHAcVMFBxlTEREZDIGFCIiIpIdBhQiIiKSHQYUM+HIHSIiItMxoBAREZHsMKAQERGR7DCgmAlH8RAREZmOAYWIiIhkhwGFiIiIZIcBhYiIiGSHAaURcMgxERGRcRhQiIiISHYYUIiIiEh2GFDMhMOMiYiITMeAQkRERLLDgGIm7BhLRERkOqMCSnR0NHr16gUnJyd4enriqaeeQnJyskGZgQMHQqFQGDxee+01gzJXr17FyJEj4eDgAE9PT8ycORNlZWX1PxqZEmBaISIiMoaNMYXj4uIQERGBXr16oaysDO+99x6GDh2KpKQkNGvWTCo3efJkLFiwQHru4OAg/azT6TBy5Eio1WocPHgQaWlpmDBhAmxtbbFw4cIGOCQiIiJq6owKKNu3bzd4vmbNGnh6eiIhIQH9+/eXljs4OECtVle7jZ07dyIpKQm7du2Cl5cXevTogQ8++ACzZs3CvHnzoFQqTTgMIiIiepDUqw9Kbm4uAMDNzc1g+dq1a+Hh4YFu3bohKioKhYWF0rr4+Hh0794dXl5e0rKwsDBotVqcOXOm2v0UFxdDq9UaPOSOo3iIiIhMZ1QLSkV6vR4zZszA448/jm7duknLn3/+ebRp0wY+Pj44efIkZs2aheTkZGzYsAEAkJ6ebhBOAEjP09PTq91XdHQ05s+fb2pViYiIqIkxOaBERETg9OnTOHDggMHyKVOmSD93794d3t7eGDJkCC5evIj27dubtK+oqChERkZKz7VaLXx9fU2rOBEREcmeSZd4pk2bhi1btmDv3r1o1apVrWVDQkIAABcuXAAAqNVqZGRkGJQpf15TvxWVSgVnZ2eDR1PCIcdERETGMSqgCCEwbdo0bNy4EXv27IGfn1+dr0lMTAQAeHt7AwA0Gg1OnTqFzMxMqUxsbCycnZ0REBBgTHWIiIjoAWXUJZ6IiAjExMRg8+bNcHJykvqMuLi4wN7eHhcvXkRMTAxGjBgBd3d3nDx5Em+99Rb69++PwMBAAMDQoUMREBCAF198EYsXL0Z6ejpmz56NiIgIqFSqhj9CIiIianKMakFZtWoVcnNzMXDgQHh7e0uP77//HgCgVCqxa9cuDB06FJ07d8bbb7+N8PBw/PLLL9I2rK2tsWXLFlhbW0Oj0eCFF17AhAkTDOZNeRAowGE8REREpjKqBUXU0ZnC19cXcXFxdW6nTZs22Lp1qzG7JiIioocI78VjJpzenoiIyHQMKI2AUYWIiMg4DChEREQkOwwoREREJDsMKERERCQ7DChmwmHGREREpmNAISIiItlhQCEiIiLZYUBpBHVNcEdERESGGFCIiIhIdhhQiIiISHYYUMxEwUE8REREJmNAISIiItlhQDET9oslIiIyHQNKI2BWISIiMg4DChEREckOAwoRERHJDgOKmXAUDxERkekYUIiIiEh2GFCIiIhIdhhQGgGHHBMRERmHAYWIiIhkhwGFiIiIZIcBhYiIiGSHAcVMOMqYiIjIdAwoZsJ+sURERKZjQGkMTCtERERGYUAhIiIi2WFAISIiItlhQCEiIiLZYUAxE47iISIiMh0DChEREckOAwoRERHJDgNKIxAQ+P3qbfz9xxPIzCuydHWIiIhkz8bSFXhY/GXlQQBATmEJ/jWxl4VrQ0REJG9sQWlkl24WWLoKREREsmdUQImOjkavXr3g5OQET09PPPXUU0hOTjYoU1RUhIiICLi7u8PR0RHh4eHIyMgwKHP16lWMHDkSDg4O8PT0xMyZM1FWVlb/o2kCOKksERFR3YwKKHFxcYiIiMChQ4cQGxuL0tJSDB06FAUF91oF3nrrLfzyyy/48ccfERcXhxs3bmDs2LHSep1Oh5EjR6KkpAQHDx7Et99+izVr1mDOnDkNd1RERETUpBnVB2X79u0Gz9esWQNPT08kJCSgf//+yM3Nxddff42YmBgMHjwYALB69Wp06dIFhw4dQp8+fbBz504kJSVh165d8PLyQo8ePfDBBx9g1qxZmDdvHpRKZcMdHRERETVJ9eqDkpubCwBwc3MDACQkJKC0tBShoaFSmc6dO6N169aIj48HAMTHx6N79+7w8vKSyoSFhUGr1eLMmTPV7qe4uBhardbg0ZQIXtchIiIyiskBRa/XY8aMGXj88cfRrVs3AEB6ejqUSiVcXV0Nynp5eSE9PV0qUzGclK8vX1ed6OhouLi4SA9fX19Tq21xgmmFiIioTiYHlIiICJw+fRrr169vyPpUKyoqCrm5udIjNTXV7PskIiIiyzFpHpRp06Zhy5Yt2L9/P1q1aiUtV6vVKCkpQU5OjkErSkZGBtRqtVTmyJEjBtsrH+VTXqYylUoFlUplSlWJiIioCTKqBUUIgWnTpmHjxo3Ys2cP/Pz8DNYHBwfD1tYWu3fvlpYlJyfj6tWr0Gg0AACNRoNTp04hMzNTKhMbGwtnZ2cEBATU51hkRcG7BRIREZnMqBaUiIgIxMTEYPPmzXBycpL6jLi4uMDe3h4uLi6YNGkSIiMj4ebmBmdnZ0yfPh0ajQZ9+vQBAAwdOhQBAQF48cUXsXjxYqSnp2P27NmIiIh4KFpJ2AOFiIiobkYFlFWrVgEABg4caLB89erVeOmllwAAy5Ytg5WVFcLDw1FcXIywsDCsXLlSKmttbY0tW7Zg6tSp0Gg0aNasGSZOnIgFCxbU70hkjKGEiIjIOEYFlPsZgWJnZ4cVK1ZgxYoVNZZp06YNtm7dasyuiYiI6CHCe/EQERGR7DCgNDJOg0JERFQ3BhSz4TAeIiIiUzGgmA2bSoiIiEzFgNIIOL09ERGRcRhQGplgywoREVGdGFCIiIhIdhhQiIiISHYYUIiIiEh2GFDMpvphxuwvS0REVDcGFCIiIpIdBpRGwEYTIiIi4zCgEBERkewwoDQy9kEhIiKqGwMKERERyQ4DitmwqYSIiMhUDChEREQkOwwojYD9ToiIiIzDgEJERESyw4BCREREssOAQkRERLLDgNLIBDukEBER1YkBhYiIiGSHAaURCM6JQkREZBQGFCIiIpIdBhQiIiKSHQYUIiIikh0GFDOpabAOe6MQERHVjQGFiIiIZIcBpTGw2YSIiMgoDChEREQkOwwojYwTyRIREdWNAYWIiIhkhwGFiIiIZIcBhYiIiGSHAaWR8b48REREdTM6oOzfvx+jR4+Gj48PFAoFNm3aZLD+pZdegkKhMHgMGzbMoEx2djbGjx8PZ2dnuLq6YtKkScjPz6/XgcgZIwkREZFxjA4oBQUFCAoKwooVK2osM2zYMKSlpUmPdevWGawfP348zpw5g9jYWGzZsgX79+/HlClTjK89ERERPZBsjH3B8OHDMXz48FrLqFQqqNXqatedPXsW27dvx9GjR9GzZ08AwPLlyzFixAh8/PHH8PHxMbZKRERE9IAxSx+Uffv2wdPTE/7+/pg6dSpu3bolrYuPj4erq6sUTgAgNDQUVlZWOHz4cLXbKy4uhlarNXg0VZwHhYiIqG4NHlCGDRuG7777Drt378ZHH32EuLg4DB8+HDqdDgCQnp4OT09Pg9fY2NjAzc0N6enp1W4zOjoaLi4u0sPX17ehq93gmEOIiIhMZ/QlnrqMGzdO+rl79+4IDAxE+/btsW/fPgwZMsSkbUZFRSEyMlJ6rtVqm0RIISIiItOYfZhxu3bt4OHhgQsXLgAA1Go1MjMzDcqUlZUhOzu7xn4rKpUKzs7OBo+mhJd1iIiIjGP2gHLt2jXcunUL3t7eAACNRoOcnBwkJCRIZfbs2QO9Xo+QkBBzV8fimFWIiIjqZvQlnvz8fKk1BABSUlKQmJgINzc3uLm5Yf78+QgPD4darcbFixfxzjvvoEOHDggLCwMAdOnSBcOGDcPkyZPxxRdfoLS0FNOmTcO4ceM4goeIiIgAmNCCcuzYMTzyyCN45JFHAACRkZF45JFHMGfOHFhbW+PkyZMYM2YMOnXqhEmTJiE4OBi//fYbVCqVtI21a9eic+fOGDJkCEaMGIG+ffviyy+/bLijkplbBcXSz4XFZRasCRERUdNgdAvKwIEDIWrpVLFjx446t+Hm5oaYmBhjd91kleruvV86dkghIiKqE+/F0whqC3RERERUFQNKI2A8ISIiMg4DChEREckOA0oj4BUeIiIi4zCgEBERkewwoJhJxVYThaL65URERFQ9BpRGwFBCRERkHAaURsGEQkREZAwGlEbGqEJERFQ3BpRGYHCJhwmFiIioTgwojUwwoRAREdWJAaWRscMsERFR3RhQGgGv8BARERmHAYWIiIhkhwGlkfHOxkRERHVjQGlkjCdERER1Y0BpBBUbTdiAQkREVDcGFCIiIpIdBhQzqTjfCfudEBERGYcBpRGcz8y3dBWIiIiaFAaURjB702lLV4GIiKhJYUAhIiIi2WFAISIiItlhQCEiIiLZYUAhIiIi2WFAISIiItlhQCEiIiLZYUAhIiIi2WFAISIiItlhQCEiIiLZYUAxE95+h4iIyHQMKERERCQ7DChEREQkOwwoREREJDsMKERERCQ7DCgV5BSW4I+MPNwuKLF0VYiIiB5qRgeU/fv3Y/To0fDx8YFCocCmTZsM1gshMGfOHHh7e8Pe3h6hoaE4f/68QZns7GyMHz8ezs7OcHV1xaRJk5Cfn1+vA2kIW0+lY+iy/QhZuBup2YWWrg4REdFDy+iAUlBQgKCgIKxYsaLa9YsXL8Znn32GL774AocPH0azZs0QFhaGoqIiqcz48eNx5swZxMbGYsuWLdi/fz+mTJli+lE0EJXN3bejRKdHSlaBhWtDRET08LIx9gXDhw/H8OHDq10nhMAnn3yC2bNn48knnwQAfPfdd/Dy8sKmTZswbtw4nD17Ftu3b8fRo0fRs2dPAMDy5csxYsQIfPzxx/Dx8anH4dRPeHArfH0gBUlpWnAaEyIiIstp0D4oKSkpSE9PR2hoqLTMxcUFISEhiI+PBwDEx8fD1dVVCicAEBoaCisrKxw+fLja7RYXF0Or1Ro8zEWhMNumiYiI6D41aEBJT08HAHh5eRks9/Lyktalp6fD09PTYL2NjQ3c3NykMpVFR0fDxcVFevj6+jZktaslOBUsERGRxTSJUTxRUVHIzc2VHqmpqWbbV3kLCuMJERGR5TRoQFGr1QCAjIwMg+UZGRnSOrVajczMTIP1ZWVlyM7OlspUplKp4OzsbPAwFwUa5hoPG2CIiIhM16ABxc/PD2q1Grt375aWabVaHD58GBqNBgCg0WiQk5ODhIQEqcyePXug1+sREhLSkNWpHwYMIiIiizF6FE9+fj4uXLggPU9JSUFiYiLc3NzQunVrzJgxAx9++CE6duwIPz8//OMf/4CPjw+eeuopAECXLl0wbNgwTJ48GV988QVKS0sxbdo0jBs3zqIjeMrdu8TDhEJERGQpRgeUY8eOYdCgQdLzyMhIAMDEiROxZs0avPPOOygoKMCUKVOQk5ODvn37Yvv27bCzs5Nes3btWkybNg1DhgyBlZUVwsPD8dlnnzXA4RAREdGDwOiAMnDgwFpHuCgUCixYsAALFiyosYybmxtiYmKM3XWjKO+Bwj4kREREltMkRvE0qnpMhFKq00OvZ7IhIiKqLwaUGhjbglJYUoZHP4jFM/8Xb54KERERPUQYUCqRLvEY+brDl7KRV1SGhCu3G7pKREREDx0GlEo41T0REZHlMaDUgFPdExERWQ4DSiWmXuLhvClEREQNhwGFiIiIZIcBpRLFn51QjL3CwytCREREDYcBpZKG6iPLSz5ERESmY0CpkXEBgy0oREREDYcBpRLpZoEMHERERBbDgEJERESyw4BSieLPXihsQCEiIrIcBpTKTLzEw0BDRETUcBhQGghnniUiImo4DCiV3JtJloGDiIjIUhhQiIiISHYYUCoxdZgx21uIiIgaDgNKJRzFQ0REZHkMKA2EfWSJiIgaDgNKJfcu8RibOAzLM7AQERGZjgGFiIiIZIcBpRJFA9zOmHOiEBER1Q8DSiVSJ1lmDCIiIothQGkgFQMNww0REVH9MKBUInWSNXKgsajh58r6dvAwuk5EREQPGwaUGpirFcTJzsY8GyYiInqAMKCYATvJEhER1Q8DSiUKhWmdZA36oDRgfYiIiB5GDChmUFu4YeMKERFR3RhQKimfBsX4eWSZPIiIiBoKA0olpk91f09tYUVA4HxGHv6x6TQytEUAgNPXczFn82ncLigxeZ9EREQPEg4paSDGzIMycvkBlJTpcS5dix9fewyjlh8AANwqKMGK5x81Yy2JiIiaBragVGLqJR5jlJTpAQCnrucaLD+XpjXjXomIiJoOBpSamCmh1NbSwl4sREREdzGgVKIw8W6BBjPJmpg0OMKHiIjorgYPKPPmzYNCoTB4dO7cWVpfVFSEiIgIuLu7w9HREeHh4cjIyGjoapjs3iUeI6e6r5Auau8ke3/bICIiepiZpQWla9euSEtLkx4HDhyQ1r311lv45Zdf8OOPPyIuLg43btzA2LFjzVEN2ascRxhPiIiI7jLLKB4bGxuo1eoqy3Nzc/H1118jJiYGgwcPBgCsXr0aXbp0waFDh9CnT59qt1dcXIzi4mLpuVZrvs6k94YZm76N2l5bVKoz6XVEREQPE7O0oJw/fx4+Pj5o164dxo8fj6tXrwIAEhISUFpaitDQUKls586d0bp1a8THx9e4vejoaLi4uEgPX19fc1TbQH2yQm2v/e18Vo0FOdkbERHRXQ0eUEJCQrBmzRps374dq1atQkpKCvr164e8vDykp6dDqVTC1dXV4DVeXl5IT0+vcZtRUVHIzc2VHqmpqQ1d7QpM6yRbkal9SdiCQkREdFeDX+IZPny49HNgYCBCQkLQpk0b/PDDD7C3tzdpmyqVCiqVqqGqWKuGuMRzvyq3mDCgEBER3WX2Ycaurq7o1KkTLly4ALVajZKSEuTk5BiUycjIqLbPiiUZP4qn4mtN3CcTChEREYBGCCj5+fm4ePEivL29ERwcDFtbW+zevVtan5ycjKtXr0Kj0Zi7KvfFlAs8By9kYcb3idLz+80ZnKiNiIioeg1+iefvf/87Ro8ejTZt2uDGjRuYO3curK2t8dxzz8HFxQWTJk1CZGQk3Nzc4OzsjOnTp0Oj0dQ4gsdSjGnMeP5fhxt9n0RERA+yBg8o165dw3PPPYdbt26hRYsW6Nu3Lw4dOoQWLVoAAJYtWwYrKyuEh4ejuLgYYWFhWLlyZUNXw2QmTiRrSJgWNvRMKERERADMEFDWr19f63o7OzusWLECK1asaOhdNwjFnxd56jfM+P5ezYnaiIiIqsd78dSkHq0Z998HpfpRPLmFpewwS0REDzUGlEoa5BKPyQR2n81A0IKdWLAlyZIVISIisigGlEqkeVDqsQ1TX6sXwMKtZwEAq/93uR41ICIiatoYUGpQv3vxmNgHRQgoLNuEQ0REJAsMKJUoGmCq+/tV3TwojCdEREQMKDWqTydVky/x6IWF+8AQERHJAwNKZQ0QEEzNNndbUJhQiIiIGFAqKY8HjTEPCgC8t/FUxReyBYWIiAgMKDWq7zQk2qLS+yoXc/iq9DNnkiUiIrqrwWeSbeoaYhTNuP87hEtZBUa/rkzPgEJERASwBaVG9YkKpoQTACgu03OYMRERERhQqqgtHhy8kIX/tzMZZTq92fZvxXxCRETESzyVSTPJVtMf5Pl/HQYA+Lja47nerc26fyIioocZW1BMcPmWaZdw7geHGRMRETGgVHFf8cCMfVnZgkJERMSAUqPaRvyac6wNRxoTEZElbDuVhuGf/oYLmXmWrgoABpQqykfR1DbZmt6Mw4FPXc8127aJiIhqMnXtcZxN0+Kt709YuioAGFCquJ8rLGzkICKiB1XOnRJLVwEAA0qNarvUwhlfiYjoQaU330waRmFAqew+mlCYT4iI6EGlk8ms5gwolZQP863r9KRmFyJ621lkaIvMXykiIqJGIpfbrnCithrUdYln/L8O42p2If4v7lLjVYqIyAwSU3OQml2I0UE+lq4KyUB1E5VaAgNKJeXzkHy0/Rz6dvBA91YuVcoIAVzNLmzkmhERmcdTK/4HAPDzaIZuLav+z6OHi04mAYWXeGox+vMD1S6vbQiypd0p0WHD8WvILpBHL+z60OsFCorLLF0NoiZv+e7zmLP5dJVvxkIInK4wtcGVW/zi1VBy75Tijwx5zCdSUVZ+MTYcv4aiUl2NZXIKSxuxRjVjQKmkuj6yeUWluFrhDzct5/77nfxnUojJdTGlme2fW5MQ+cMJTPzmiNGvLSyRVxjov2Qvus7dgZX7LsimyZGoqRFC4P/F/oHv4q/g4s18g3Ubjl/HqOX3vojZWnMq64byyIKdGLpsv0EArK8ynR5TvjuGd346YfL/xFGfHUDkDyfw9o935zop/7+fkmW+W7iYigGlEk9nlcHzwpIydJ+3E/2X7JWW7T6XWed2PByVuPDP4ejb0eO+9vtq/3ZVli3ZkXxfr61oy8k0AMZP+LZkxzkEzNmB+Iu3jN6nuVy7fQcAsHh7MgLn7TR5O0IIpGQVmK1nenGZDuuOXEXClWyzbJ+oPip2eKz8f+E/h68YPLe1kc9HwtZTaWj77q+Yu/m0patitM2J11H+tsf9cVNavv+Pm3jmi4O4kJlfwytr968DKdiZlIEfjl0zeRvpfw7s+PVkGr45kIKAOTuw7VQaFm49a9L2zEk+v40y4aA07JazfM8Fo7ex7+8DceS9UNhY3317+3dqAS9nFdZN7oPF4YFImB0KABgZ6C29JqSdW5XtrNx30eh9m9o0t2Lv3X19sCVJWlZQXGbQclSbkZ/9hrbv/ooD57NM2j9wd2RUXtHd+l+pdEPGvOIy3MwrxrBP9mNz4nXM3nQKyenVN59evJmPlfsuoLCkDMVlOrz94wkM+ngf3t94CgBw+NIt7K/wT6M+rt0uhP/s7YjacArhq+Jx5VYBXvn2GL6Lv9wg22/qist0Vb616/XCqNmYt5y8gaU7kyGEaJThj+beR5lOj/MZeY3WKlhcdm9Si7d/OIGC4jKU/Lms8nlQWlf/kVBUqqv1kkBtbheUIC33Tp3lLt7MxwdbkvDNgRTcyi/G62uPAwC+jb+CX0+moVR3/5NzZOUXIzPvXkt37p3SKsda0/t/8lqOFCoKS8pw4HyWUfsGgDfXJ0o/W1W4wdqEb47g6OXbCF0aV+U1ZfexjxV7730eFZXqsfp/KfX6YrTgz//3U9ceR2xShsnbMRd2kq0kp9Cw78YqI0NC5BOd0NajmcGyb1/uhTK9gK21FTTt3QEAlxeNBAD8evJXAEBHTydse7MfFm49i98qfMjHX7yF41dvAwAiBnW4t5/vE7Hh9+vY+/eB8Ku0v3JbT6Whb0cPONvZVlknhIAQgJWVYZNu7p17AeeJpXG4kVuEXZH90cHTqcZj1haV4swNLQDgha8P49S8oXCqZp/VKSrVYeHWs+jZ1g1vrPu91rK9/rkLwL0//v8cuorLi0Yiv7gMttYKqGysAQBDl+2HTi+weLthC9T6o6kYFeiDF74+DAB4+fG2mDu6a511FEJAoVBgb3ImhBAY5O8p3RKhYvM4AAxYsg8AsOtsBp7v3VoKqbUp0+lhpVBUOReNLfdOKf53IQuDO3vCzta62jJCCNwuLIVbM2W164tKddh7LhOPd/RAaZkeT38Rj5SsAnzwZFe80KcNSnUCnWZvAwA82cMHJ1Jz8N3fQtDa3QHZBSVwUFpj3JeHkJiag9FBPnj7iU6YFnP390JbVIY1By/j2Z6++OjpQGRqi6C0scKdUh1yCkvRxdsZAHAkJRtezipo75TB0c4GLV3toayhZeBCZj6+PpCCiEHt0aq5A/712yV8+OtZ/PCqBr393BCblIFmKmv0buuGCzfz0aq5A1759igu3SzAnVIdNr7+OFq62sPO1gr7z2dh4jdHYGOlQP9OLTBtcAcIIfBo6+ZQKBT49WQaZm86BQ9HFc5n5iNqeGdM0LSFysYKF2/mo30LR+l3oEynx66zmQhu0xwtnO616qbnFuHQpVtwsbdFhrYIf3m0pfR7DwD7kjPx0uqjiHyiE0YH+cDPoxmKKwQLvQC6zt0BAPh0XA+D8AIA1tX8Dur0AiELd6OkTI+T84bC9s/f6Su3CmCvtIabgxJJaVps/P06XnqsLdwdVXBU2SA1uxCXsgqky83tWjTDty/3hq+bw93ft8JSnM/MQ8+2bsgtLMWQ/3fvQ3tBhS9KABARcxxvDumIN4d0xIU/36tSnR79Fu9FZ7UTPh33iPQ7ueH4NUT+cPfyxbRBHfBYe3c8/6+7f/NH3hsCT2c77P/jJiLWHsfcMV3xZA8fJFy5jUdau0JlY40xn9/tMHxg1iDM/yUJsUkZGB/SGi/0aYN3fz6JN4Z0xNHLtzG4syd6+939YllSpsenu/+ATg/8tWcrg7pfu12IC5n5aN/C8P/02TQttp1Kw9PBvvjfxSxEbTiFhX/pjuHd1PjfxSy42Nuih68rHJQ22Jx4HXdKdcgruncZPjYpHZ/9+QX64LuDcSu/BN1buaBUp8fU/yTgxLVctPNohpcfb4u+HVvAUWXcx/3WU2kY0d277oJmpBBN8OK+VquFi4sLcnNz4ezs3KDbXrnvQpUPNmOkRI+QPrzux8Wb+cgpLEFwm3stKFO+O4ad1aTZryb0xBMBXrh0Mx+DK/wxl4edq7cKDS5FlTs9P8zglzP3TimeWBqHPu3cMaK7N9Jy72D+L0lVttf23bvh6Z1h/gh/tBW8nO1w5kYuvF3sobKxQrM/t/nCvw7jwIV7oWqipg1aNrfHmKCWULvYVanPtduF6PvRXnRr6YySMj3+yDCtqRIAYl4Jkf75hPi54XCKcd8mngjwqvabQ/TY7sjKK0ZRmQ5fH0hBUanxUys+1t4dbwzpiB6+rvh8zwVcz7mDMzdyMXVge7jY2yLxag6Ky/RYffAyuqidsCnicew4kw4XeyU07d2h0wvcKiiGp1PV97AiIQSWxv4BXzcH/LWnr7T8SEo2vvrtEpb+NQhOdrY4l65FYYkO7T0csSnxOo6kZGNK/3b49uBljAryxt/WHAMAPNfbF82UNjhyORv/GBWAtYeu4HxmPtq6N8Ovp+5eQlz8dCCOpmSji7czRgf5SOGxLq4OthbpgPfvSb2x9VQaYpMysWhsd3TycsLyPefxY8I1qcz5fw5Hx/e3NXrdKmrfohme7eWL385nGXxR6dmmOY5duV3j63a/PQBOdjbo/c/dBss/eLIr/rH5zH3vf1SgNz4b9whCl8bhUlYBTswZCiiAoPn3LrEuDg+EgMCsn0/VuJ0X+7TBvw9dqXG9v5cTki3UgXSgfwvsS66+BXVGaEd8suv8fW9LoZDXxJ3Ph7RGzOGrDba9w+8NgZdz7f9/jGXM5zcDSiWZeUVV/sgB4MTcoRj08b5aR8eUf+uqr4Qr2QhfFV/tun9P6o0v918y+Of1zjB/9GnnjrErD9a4zZ5tmmNGaCd09nZCn4W7a52IZ/VLvTCgUwu0e29rrfVc83IvDPT3lIJMdc59MAx2ttZYvP0cbKyt8EhrV7y8+mit231YffNSTykkDOuqxvYz6QCAhX/pjqFdvfDNgRT8lHANvm4O+GpCT+QVlaKFkwpn0/IQvuruuX+hT2u8PyIAdrZW8Iu6d/7auDtwhAbdl6BWLjhxjTctpbtf4L6a0LNBt8mAUk/z/nsGaw5elp7/d9rjCGzlCuDedUIbayvcKdFh5b4L+O18Fj4KD4S/uubLIMY4m6bF8E9/a5BtmapvBw+DVhEiInr4lLeoNxRjPr/ZB6UOlU9OxT4F9kprvD3UH28P9W/QfTZTWv60yCGc/PpGX3T1cUFiao40kZRc9e/UosE63hIRsO3NfuisdsLPx6/j738OiSXzOjVvKK5mF2LkZ3f71n3zUsO2nhjL8p+EMtT6z05cluKgqr6D4oPK180e3/0tBCdSczAmyKdKZ9Eevq64tHAEzqZr8fWBFGw4fh3RY7vj3/FXkJSmlcrNDPOH2tlOGt9f7skePvh03COI2nAS646k4v0RXTC5fzvsSsrA3P+eQd8OHhjWTY0Vey9Ue53f180efh6OSLqhhV4IBLZywbherRHW1QsLt56FXgD/GBWA7+Iv49ClW4h8ohNCl+43z5tlQb393HD8yu0aLw/ODPPH8G5qqX/UiblD4WJvi9sFJVDaWGHJjmQkpubgu0m9cTQlG9PX/Y6/9vTFxMfaws+jGTYnXseb6xOx5uW7lxhvFZRALwS+P5KKjl5OeO0/CZg7OgA+rvaY+eMJzBreGY4qG7Rv4YgSnR7eLnY4kpINlY01Nv5+DUMD1CjT63Hqei6c7Gzvu8P7Z889gmZKa7Rxd8Dus5n4KeEaevm54aXH2uKDLUmIv3gL9rbWGODfAmduaPF0cCupA/vlrAJ89dslvDagPXacSceSHckGHVE3vP4YUm4WSL+jz/X2xbojqQDu/g79eCwV5yqMTlPaWKGtuwMin+iE+Iu38G38FahsrDBvTFdEbajaB+Tbv/Wudg4kO1urWvtR/eWRljh6OVsa2l8Xt2ZKHH5vCHacSZc6MX/ybA9czS7E0tg/DMqO6K5G1PAu6Lf4Xv+49i2a4eLNAjzZwweD/D2RV1SKvzzaClZ/9ulQKO6NqHw6uBUSrmRj3ZFUuDdTYtub/QAFsGLPBTzT0xe+zR2QV1yKOZvP4O9D/RHg44z03CL0id4NJzsbDA1Q478nruPtof5YtO1clWMJ8XPDyvGPYmnsH1j7Z/+NIF9XfPHCo0jJKoCNlRVu5NzBvw9dQUtXe0zq64evfrskTenww6sa+LjaoVVzB5SU6RG+6iD81U74+Jkg/HLiBqav+x2vDmiHUd19EHPkCib19TP4/7Dx9cdQqhMIbtMcZXo9rt++g6z8ElhbKaRLt2OCfDBtcAcocPe9KX/91IHtMWtYZ+j1AkHzdyKvuAz/nfY41C522HfuJsY+2rJKR/34i7ew749M6TYtkU90wvBuajRT2cDJzhZdfVzw70m9UVCsw+DOXvf1+2AuvMRTjdw7pZj/3zMYFeRtkRNUVKpD539sBwD0aeeGlq4O+Pn4tSrlxoe0lv6gysVMDsHzXx2Wnp+YMxRBC2qeQ8TWWoFS3f39CowO8sHSvwbhbJoWtwpKqu1LMjPMH0t2JOP1ge1rHSbd0dMR74/sgv4dWxg9ekWvF9Jr7pTooLKxqnEbhSVlVYaON4bLWQXYdTYDDkobvLfxFAZ39sSeP+fP8XBU4puXekmXDQEY9ONJWhCGqf85jgxtES5k5ht1465ebZvj6OXqO1Oum9wHz311CAAQHzUYb6z7HUcv34ankwrTh3TEqO7e+PXPnvtZ+cU4cyMXpWUCPyVcwwdPdZMuYZbq9FgW+wf81U7o2dYNdjZWcLKzlUbKZOYVoVQn0NLV3qj3zBjlI6uMpS0qlebU6d7SBZFPdMKgzp64eDMfk787hqd6tMQbQzrWug29XqBEp69xpFN1cgpL4OpQ/cin3DulKNXp4eF4d7TO9Zw7uJxVgBKdHoP8Pe9r+5ezCpCSVYBBnT2RqS3Cir0XMLSrGo93uDcP09VbhVi57wIG+nsirKsXLmUV4OeEa3BrpsRfe/nC2c4WJWV6JKbmwNneBp3Vzjh2ORvp2iKE+LnDxkqB5jWM3qpO5XNU8e+2rvekIRSV6mBrbVVlZNLtghJcz7lT7ZT+Nb2moV3OKsD3x1Lxav92Jr0HuYWlcLKzqdfIP21RKbR3StHS1d6kvyWT98s+KE3foUu3YKVQSJ1uV+y9YDBx29+HdsK0wR1RVKpD0PydKC67+w/u2OxQ6PQC8385gyd7tERwm+YAUGNH1ksLR2DEZ7/hXHoeXunrh38dSKlSRtPOHYG+Loga3sVguRAC3ebuQEHJ3WGM3Vu64JfpfaX1pTp9jaMitr7RDwE+D+a5q8mxy9m4dLMAz/RsVeUfgk4vkF9UBheHqsOzC0vKkKktRrq2CMVlerja28Jf7YQ31v0ujfZaN7mPNIQdAPacy4CTnS16tXWr8cNcpxcoLCm77yHhD4rbBSVQ2VpZJLgSPewYUB5AxWU6/HoyDZr27tDeKUMnL0fpQye3sBS5d0rR2r3mS1MVA0p81GB8uf8SJmraVpmz5bv4y3C2s4WVlQKp2YV4UdOm2nlUygkhsGRHMhKu3MZH4YFVtldcpoP/7LutQf8YFYBLN/MxrJsa/Tq2MPo9IENCCFy8eXf47/3Mt0JEZGlNJqCsWLECS5YsQXp6OoKCgrB8+XL07t27ztc9jAGlvioGlIbulX0/dHph9mZTIiKSN2M+vy32tev7779HZGQk5s6di+PHjyMoKAhhYWHIzKz7PjdkPM8/Z6N0sbdMcz7DCRERGcNiLSghISHo1asXPv/8cwCAXq+Hr68vpk+fjnfffdegbHFxMYqLi6XnWq0Wvr6+bEExwvWcO1i68w/MHRNQ6yUbIiIic5F9C0pJSQkSEhIQGhp6ryJWVggNDUV8fNUZVKOjo+Hi4iI9fH19q5Sh2rV0tcf/+2sQwwkRETUJFgkoWVlZ0Ol08PIyHMLr5eWF9PT0KuWjoqKQm5srPVJTUxurqkRERGQBTWKcnUqlgkqlqrsgERERPRAs0oLi4eEBa2trZGQY3kU2IyMDarXaElUiIiIiGbFIQFEqlQgODsbu3ffuGqzX67F7925oNBpLVImIiIhkxGKXeCIjIzFx4kT07NkTvXv3xieffIKCggK8/PLLlqoSERERyYTFAsqzzz6LmzdvYs6cOUhPT0ePHj2wffv2Kh1niYiI6OHDqe6JiIioUch+HhQiIiKi2jCgEBERkewwoBAREZHsMKAQERGR7DCgEBERkewwoBAREZHsNIl78VRWPjJaq9VauCZERER0v8o/t+9nhpMmGVDy8vIAAL6+vhauCRERERkrLy8PLi4utZZpkhO16fV63LhxA05OTlAoFA26ba1WC19fX6SmpnISOAvieZAPngt54HmQB56H+hFCIC8vDz4+PrCyqr2XSZNsQbGyskKrVq3Mug9nZ2f+8skAz4N88FzIA8+DPPA8mK6ulpNy7CRLREREssOAQkRERLLDgFKJSqXC3LlzoVKpLF2VhxrPg3zwXMgDz4M88Dw0nibZSZaIiIgebGxBISIiItlhQCEiIiLZYUAhIiIi2WFAISIiItlhQCEiIiLZYUCpYMWKFWjbti3s7OwQEhKCI0eOWLpKTdr+/fsxevRo+Pj4QKFQYNOmTQbrhRCYM2cOvL29YW9vj9DQUJw/f96gTHZ2NsaPHw9nZ2e4urpi0qRJyM/PNyhz8uRJ9OvXD3Z2dvD19cXixYvNfWhNSnR0NHr16gUnJyd4enriqaeeQnJyskGZoqIiREREwN3dHY6OjggPD0dGRoZBmatXr2LkyJFwcHCAp6cnZs6cibKyMoMy+/btw6OPPgqVSoUOHTpgzZo15j68JmXVqlUIDAyUZiHVaDTYtm2btJ7nwTIWLVoEhUKBGTNmSMt4LmRAkBBCiPXr1wulUim++eYbcebMGTF58mTh6uoqMjIyLF21Jmvr1q3i/fffFxs2bBAAxMaNGw3WL1q0SLi4uIhNmzaJEydOiDFjxgg/Pz9x584dqcywYcNEUFCQOHTokPjtt99Ehw4dxHPPPSetz83NFV5eXmL8+PHi9OnTYt26dcLe3l783//9X2MdpuyFhYWJ1atXi9OnT4vExEQxYsQI0bp1a5Gfny+Vee2114Svr6/YvXu3OHbsmOjTp4947LHHpPVlZWWiW7duIjQ0VPz+++9i69atwsPDQ0RFRUllLl26JBwcHERkZKRISkoSy5cvF9bW1mL79u2Nerxy9t///lf8+uuv4o8//hDJycnivffeE7a2tuL06dNCCJ4HSzhy5Iho27atCAwMFG+++aa0nOfC8hhQ/tS7d28REREhPdfpdMLHx0dER0dbsFYPjsoBRa/XC7VaLZYsWSIty8nJESqVSqxbt04IIURSUpIAII4ePSqV2bZtm1AoFOL69etCCCFWrlwpmjdvLoqLi6Uys2bNEv7+/mY+oqYrMzNTABBxcXFCiLvvu62trfjxxx+lMmfPnhUARHx8vBDibti0srIS6enpUplVq1YJZ2dn6b1/5513RNeuXQ329eyzz4qwsDBzH1KT1rx5c/Gvf/2L58EC8vLyRMeOHUVsbKwYMGCAFFB4LuSBl3gAlJSUICEhAaGhodIyKysrhIaGIj4+3oI1e3ClpKQgPT3d4D13cXFBSEiI9J7Hx8fD1dUVPXv2lMqEhobCysoKhw8flsr0798fSqVSKhMWFobk5GTcvn27kY6macnNzQUAuLm5AQASEhJQWlpqcC46d+6M1q1bG5yL7t27w8vLSyoTFhYGrVaLM2fOSGUqbqO8DP+GqqfT6bB+/XoUFBRAo9HwPFhAREQERo4cWeX94rmQhyZ5N+OGlpWVBZ1OZ/CLBgBeXl44d+6chWr1YEtPTweAat/z8nXp6enw9PQ0WG9jYwM3NzeDMn5+flW2Ub6uefPmZql/U6XX6zFjxgw8/vjj6NatG4C775NSqYSrq6tB2crnorpzVb6utjJarRZ37tyBvb29OQ6pyTl16hQ0Gg2Kiorg6OiIjRs3IiAgAImJiTwPjWj9+vU4fvw4jh49WmUd/ybkgQGF6CESERGB06dP48CBA5auykPL398fiYmJyM3NxU8//YSJEyciLi7O0tV6qKSmpuLNN99EbGws7OzsLF0dqgEv8QDw8PCAtbV1lR7aGRkZUKvVFqrVg638fa3tPVer1cjMzDRYX1ZWhuzsbIMy1W2j4j7ormnTpmHLli3Yu3cvWrVqJS1Xq9UoKSlBTk6OQfnK56Ku97mmMs7OzvymWIFSqUSHDh0QHByM6OhoBAUF4dNPP+V5aEQJCQnIzMzEo48+ChsbG9jY2CAuLg6fffYZbGxs4OXlxXMhAwwouPsPIzg4GLt375aW6fV67N69GxqNxoI1e3D5+flBrVYbvOdarRaHDx+W3nONRoOcnBwkJCRIZfbs2QO9Xo+QkBCpzP79+1FaWiqViY2Nhb+/Py/v/EkIgWnTpmHjxo3Ys2dPlUtiwcHBsLW1NTgXycnJuHr1qsG5OHXqlEFgjI2NhbOzMwICAqQyFbdRXoZ/Q7XT6/UoLi7meWhEQ4YMwalTp5CYmCg9evbsifHjx0s/81zIgKV76crF+vXrhUqlEmvWrBFJSUliypQpwtXV1aCHNhknLy9P/P777+L3338XAMTSpUvF77//Lq5cuSKEuDvM2NXVVWzevFmcPHlSPPnkk9UOM37kkUfE4cOHxYEDB0THjh0Nhhnn5OQILy8v8eKLL4rTp0+L9evXCwcHBw4zrmDq1KnCxcVF7Nu3T6SlpUmPwsJCqcxrr70mWrduLfbs2SOOHTsmNBqN0Gg00vryIZVDhw4ViYmJYvv27aJFixbVDqmcOXOmOHv2rFixYgWHVFby7rvviri4OJGSkiJOnjwp3n33XaFQKMTOnTuFEDwPllRxFI8QPBdywIBSwfLly0Xr1q2FUqkUvXv3FocOHbJ0lZq0vXv3CgBVHhMnThRC3B1q/I9//EN4eXkJlUolhgwZIpKTkw22cevWLfHcc88JR0dH4ezsLF5++WWRl5dnUObEiROib9++QqVSiZYtW4pFixY11iE2CdWdAwBi9erVUpk7d+6I119/XTRv3lw4ODiIv/zlLyItLc1gO5cvXxbDhw8X9vb2wsPDQ7z99tuitLTUoMzevXtFjx49hFKpFO3atTPYBwnxt7/9TbRp00YolUrRokULMWTIECmcCMHzYEmVAwrPheUphBDCMm03RERERNVjHxQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikh0GFCIiIpIdBhQiIiKSHQYUIiIikp3/DyGAD9uhCAyNAAAAAElFTkSuQmCC"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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jREREPsbREAsOYCUiIiJFMRghIiIiRTEYISIiIkX5xJgRIiIiXySEQFVVFQwGg9JFkYVWq0VwcLDHy24wGCEiIpKBXq/HuXPnUFpaqnRRZBUREYFGjRohNDTU7TwYjBAREUnMaDTixIkT0Gq1SExMRGhoqN8t2imEgF6vR15eHk6cOIHWrVvbXdjMHgYjREREEtPr9TAajUhKSkJERITSxZFNeHg4QkJCcOrUKej1eoSFhbmVDwewEhERycTdlgJfIsVr9P93iYiIiFTN5WDkjz/+wPDhw5GYmAiNRoNFixY5PGft2rW45pproNPp0KpVK8yfP9+NohIREZE/cjkYKSkpQUpKCubMmeNU+hMnTmDYsGEYNGgQdu7ciSeeeAIPPvggli1b5nJhiYiIyP+4HIwMHToUr7zyCm677Tan0s+dOxfNmzfHrFmz0L59e0yYMAEjRozAv//9b5cLS0RERPKbM2cOkpOTERYWht69e2Pz5s2yXk/2MSMbN25EWlqaxbH09HRs3LjR5jkVFRUoKiqy+CEiCgT6KiPWH8lHeaXlIlkGo3Dq/PJKAzK+3Ymv/j4lR/EoACxcuBAZGRmYPn06tm/fjpSUFKSnpyM3N1e2a8oejGRnZyM+Pt7iWHx8PIqKilBWVmb1nJkzZyI6Otr0k5SUJHcxiYhU4bUlB3DPZ5vQbupSCCHw884s3P7BX2j5/BL8tvusKV1OUTlyi8prnf/xH8fx4/YsTFm0F+sO53mz6OSAEAKl+iqv/wjhXCBbbfbs2Rg3bhzGjh2LDh06YO7cuYiIiMC8efNkemdUus7I5MmTkZGRYXpcVFTEgISI/NL8v05g5YFcfDK6B8JDtZi/4aTpuf9tysSURXtNjyd8vQOpLepj3eE8ZHy7CwCw8KE+6N2ivinNjsyLpt/HzNuMk68Pk/9FkFPKKg3oMM374yX3v5SOiFDnqnu9Xo9t27Zh8uTJpmNBQUFIS0uz26PhKdmDkYSEBOTk5Fgcy8nJQVRUFMLDw62eo9PpoNPp5C4aEZHiXvx1PwDgm82ZuL9/c4vnTp0vqZW++ysrLR6P/PhvHHl1KEK0lxu6g/xslU/yrvz8fBgMBqs9GgcPHpTturIHI6mpqViyZInFsRUrViA1NVXuSxMRqdbURXvxpdm4Dr3BWCvNwexip/L6eedZjOjeBAD8bslxfxIeosX+l9IVua7auRyMXLp0CUePHjU9PnHiBHbu3InY2Fg0bdoUkydPRlZWFr744gsAwMMPP4z3338fzz77LO6//36sXr0a3377LRYvXizdqyAi8iFCCItABABCtUE4mG05WP/PI/lO5XexRG/Kd+WBHAepSSkajcbp7hKlxMXFQavVWu3RSEhIkO26Lg9g3bp1K7p164Zu3boBADIyMtCtWzdMmzYNAHDu3DlkZmaa0jdv3hyLFy/GihUrkJKSglmzZuHTTz9Ferr3o0MiIjWwNp6wrNKAk/m1u2WcUXVlps1rSw64fK7RbJbO0dxilFRUuVUG8g+hoaHo3r07Vq1aZTpmNBqxatUqWXs0XA7RBg4caHdkrrXVVQcOHIgdO3a4eikiIp91sUSPiQt3Iq5OKF6/owtCg4NwLO8S4qPCrDabv7XskNvXqjIYcSi7GJ/8ecKl8wpK9Rg8ax3Ol+jx0LUt8PEfx9E4Jhx/Tbre7bKQ78vIyMCYMWPQo0cP9OrVC++88w5KSkowduxY2a6p7vYiIiIf9fR3u/DHlam1PZvHolNiNIa/vx71IkKw5YU0B2e7ZtaKw5i14nCt46lms2wAYM+ZQkxcsAPP3tgObeIjcf2sdabnPv7jOAAgq6AM+iojQoO5dVmgGjlyJPLy8jBt2jRkZ2eja9euWLp0aa1BrVJiMEJEJIP1R6+O98gpKse5wstrglwsrTT97m0Pf7UNWQVlePirbXbT3fjuH1j91EDvFIpUacKECZgwYYLXrsfQl4hIZsFBljNcBry5xivXNZ+ho68yIqvA+kKTNR3Pc2/sCpG72DJCRCSzy9NtXVsFUwpVBiOEEBj3xVasPOD6Ut5z1hyFRgM8OrCVDKUjuorBCBGRDGqGHoqs/qHRoFRvcCsQyS0qNw2qvadPM0SFhUhdOiITdtMQEclMowH2nS1U5Nrutsf0es18aqf3W3UosDAYISKyQQiBvOIKAMDMJQdw65y/au2ma4t5S8iCzafdap3wlAbStMholGnX8QuublLni6R4jQxGiIhsmP7LPvR8dSV+3H4GH/1xHDtPF2Dx7nMu55N5oVSG0jnnWN4lzzNhLOKykJDL3Vqlpcrde2+pfo3Vr9kdHDNCRGTDFxsvL9levUMuAFRUWe4hU6Y34GxhGVo2iPRKmf7ZuynWHszFWSenB7+3+qjjRA5wuxvXabVaxMTEIDf3cotYRESE3+0bJIRAaWkpcnNzERMTA63W/T1wGIwQEbnAUKNJeth7f+J4Xgm+GdcHqS2vLjImR+P81ilpqF8nFH1fXy1pvsM6N8Kgdg3x9He7HCcmp1Xv5VIdkPirmJgYj/etYTBCROSCrzdl4t4+zUyPq9fk+HX3WYtgRA5xkToAgNHJPnqNxrkeluEpjZAUG2E7H6euRjVpNBo0atQIDRs2RGVlpdLFkUVISIhHLSLVGIwQEbngwLkiq8flrrAf7N/c9PuE61tj6qK9Tp1nr2fg2jYNcHOXRkjvmACNRoOZt3fG5B/31EoX5KB7YW9WIU5fKMXQzo2cKlOg0Wq1klTY/ozBCBGRBBxV2J7qkBhl+v2e3k2dDkas+XxsTzSKDkO7hCiL43f3amo1GHHk5vfWAwDGDWiOp4a0RZiVjQCJ7OFsGiIiCQTJ3DRiHuu4MhDSWo9OTHhIrUBECp/8eQLtpi7FxmPnJc+b/BuDESIiCcg9U6Jmy0tcZKjDc7wx1sPaGhN3f/K3F65M/oTBCBGRBGrGIvoaU4A9z9/yAt+M6+PwnMwLpVi+P6fWcSln+qxSYDE3ANh68gKeWLADucXluFRRhetnrcXLv+1XpCzkOY4ZISKSgNxjRkK1lt8dQ7SOv0vmX9JbPe7qgpn2kucUO7feidRGzN0IADiadwntEqJwPK8Ex/NOYOrNHRQpD3mGwQgRkRsuluhRoq8yPTYPReRYArxrUozF44ToMA9y858lyvdmFWFvlvUZTu4qrzTAKAQiQllFegu7aYgoYAkh8N3W09hzxrVN7IQQuPm99ej/xhrTsSCzEay/ubFkvCM1g4+wEC2GdrK+0NQNHeLt5uXqvnffbjnt2gkqkVVQhpP5JS6dYzQKdJq+DB2mLXPY1ZZ/qQID31qD91cf8aSYBAYjRBTAnvp2F575fjeGv7/epfOEuFzRmTNvGflmc6YEpXMsJsL6INYLJda7Z6q52nDz0m/7UVBqP0+1KNNf3sjwWN4l9Ht9NQa+vRZHc53fn6e8yoCqK9FaroMuqDlrjuLk+VK8vfywxfF5609gzSH/XnVVagxGiCggVRqM+HFHllvnOqrLPRk+Mveea2oda93Q1r431kviaJqxO+V75vvdrp/kgr1Zhfjq71Mut2TU1PPVlejxykoMnrXOdCxt9jo7Z7iv0lC75WTLyQt46bf9GPv5Flmu6a8YjBBRQDK42ldhRs5t4a0ty/752J4u5SHHNOMVVmblSOXrTZm4+b31mLJoLwa+vRZnLtrf6XZvlu1utUsVVci/VFHruKtdcQAw9vMtLt/r0w52aDYaBX7YdgbHreymLITAh2uPYd3hPJeu6Q6jUSCvuPb7pBQGI0QUkKSOJ8yz23Xa9YqvmsbK6iBN6lnfN8bWa3AUisgYS5mUVFQ5TnTF8z9Zrvr619F8u+kddZ9YM/z99bW61hw5knvJ6Qo7edJinCsssxhnYi0w+XlXFp76bheun7UOP2w7gz/MAo+1h/LwxtKDGDNvs91rHcu7hJyictzz6Sb8b9MpJ1+Npce+2YGer67En0fkD3ycwaHCRBSQhAczShydecmFirim8iqD8+WwFYyoYGe7/6w+gslD2ztMV1jm+gZy7k6jXncoD//s3dRuGmvBoLMemL8Vd/dKMj0e8OYaPDqwJSamtYYu+PIS+VtOXjQ9/9SVXZLrhgUjuX4dNK1vGXRWGYzYeuoiuibFoFRvwMItp9E2IRL3z99qSrP+aD5G9kjCoZxitE+IshhIbc/iPZcHWX+07jgGtG7g3guWEIMRIgpInrQOWDtXqq4bV6pCWwGVo8raG8HKmQvOtUJUDzg150lAYI9Ur/u33Wex8dj5WrsnF5ZV1ur++2DtMXyw9hjaN4rCgXNFuCUlsVZ+xeVV2JNViD1m3U//23QKL/x0ef+hf3RNRHmlAcv2We8qu37WOmReKMVzN7bDIwNbWjx36nwJEqLDTMGQwSigNQtYPOmulBKDESIKSDUrEld40qriiKf7zlzOw73zpOTse2S1rA7K3yg63PUCSWjC1zsAALrg2iMdbL3q6t2ef9l11qlrVAciAPDzzrOI1NmurjOvdAe9sfQgRvVpik//OA6DEOjerJ6pFeXk68Pw6Z/H8criA/j3yBTTuQZv/DE4gcEIEQWkskrb3SG7ThfgVzuVhvWWESlKJU0LiydZPHtjW7y59FCt48O6NPKgRNJyt4XDmdNcCTQraqxDEiTjKExnu/66vLjc6vFtpy7ilcUHAABPLtxlOm5UScsIB7ASUUD6eYftYOMfc/7Cp+tPeLE0V7lSNchRjYxJTbZ6vEmMa60RRie35nG2YSTzfClunfMXlu51f0G5OWuPYuRHG1FuJxD1hFzdS1K448MNVo970kIoJQYjRBSQ9FbWiFADV1pG5KhHtDYGQLp6qaX7sj0vjJlHv96GnacL8PBX293O4/SFMmw6cQE/bre+voy+yoj1R+zP5LFHo/FOF5iUDCopL4MRIgpIngxmlLPCUboyszX41TxIKiyrdKp14e/j5x1f0In7cDin2GL/GU8CBsD6YmUAMPP3A3joy21u56vedhHb2E1DRKQgT3bZlXMAq2vdNNZTexLQhAYHIb1j7b1tqvMsLK1Eyozl6DNzlcO89p91vIGdta6NmoN4v/rbci2Nl37b7zBfe5bsOWd1SvHnf520e96WkxfsrlUix2JzcmM3DRGRgjypNqx9mZTqIz1SF4z7+iY7l9jGRT0Nlj66twceH9za6qV2nikAABSUur4+iDXO1N9SV/GbTlzAuP9udZzQzO4zBbhz7kb0e321zTQ+GIuoZmovgxEiCkht4uu6fa61D/DP1p/AA/O3oMrDsSjtG0Uh2MmFq7xZjbjzBVqqylmOFofNJy+4lH77qYsO0/hgLILDOcVKFwEAgxEiClCRYe6vbGBrkOmqg7lYeUD53VrlmNUhV9eUtbeyZul9pcVBo9HYHI+iVkYBrJRx3yFnMRghooAk9Qqs1VzZk8VTtoIiOSpvOYYW6KuMVoOcmuVX85RZcxoAM38/qHQxXPZljTE5SuCiZ0QUkDxZXMzeoD9vfjNWR2+/e85fqkDf11ejY2KUw7RO9lq57K1lB3EstwS3X9MYQzom2E3rTFeRJ4OileSNXYIdYTBCRAHJk4rc3pi/Sg8GBD6T3hYAEB8V5nYegDPLwTsuY80sqs+Rag+en3ZkoaLKiO2ZBbWvXePizm7+5qo5a44BuLwmyrHXbpLlGuQcdtMQUUDypE61NwOhssr9lpHxg1oBAG5OcW7pdW/OypT6Uq4MSvVGe8ORXM8HcirRMLL7xSHev6gMGIwQUcA4W1CGiQt2YNfpAo8GZH69OdPmc3vNdl51l9bJWs3WK3A0xsKd2SlSBz4ulcBG4uAgDTZMul6K4khCiXVGosJCPM6jaWyEBCXxDIMRIgoYTyzYiZ93nsU/5vzl0Vf9/6w6YvM5e4tiSc3dAaxSdbU4Yq8Y9sr4y86zKNNfXeG1ysaa5bF1QpHo4p457nImzpBrbIs19SJC8PadKY4TOmFA6zhJ8vEEgxEiChjH80tMv6tt8Gf/Vq5XCF5dZ0Tiq9mrt9ccysNLv+1HpcGIUn0VTprdNzXzZsPI9qk3YET3JpLkpYZVWBmMEFHAMP/mKtfnr9vb25ufp8JJGd6ur37ddRbXz1qLDtOWoWtSjOzXk2L6sDenIDvTJdS6YaRTeQUHKR8KKF8CIiIvsbUjrZTcrZDcGm9gI0CQYuxCzSy8PYBVg8u77ALAHhvjcLzREvHD9izMXXfMqbRqm9mrDdLgp0f7OkzHdUaIiLzIfB0Ia90ORqOQbRqpI1JeVY5X4N5y8LZL4rDiNm/FcvJ6EaFalOod7ybsijeWXl7E7N4+zSTNV0p1dcEotrLYnkajQbem9RQokesYjBBRwDBvja5ZuW44lo8H5m/FjFs6enSNiir3KkPzGMjZ1hU5dw+2djUpuRCL2B6oWyOXAa3jsGyfPEubny+pcJhm9xnPZ1K5Y+VT12HPmULkFJdjcLt43PL+euQWVyCtfUNFyuMOBiNE5BMKyyqx63QB+rWKc7u7RWvRMmLpX19sQ1mlAc/+sNuDUsLqIl7OkHK6ra8sB2+P+fuhgvGV0Huwfozc4qPCEN/h6kJ5vz7WH38eycdwJ9er6ZmsfOsJx4wQkU8Y8eEGjJ63GZ//dcLtPCy6aWrWcAr397sTX9kMRjwrCgCgR7NYh9d67JsdOJHn5kwXR2NGVDb+okLFwUhN8VFhGNG9CXTBWqWL4jQGI0TkE47kXgIA/LzzrPuZ2BmHUFzuvQ3urHGnb99WN40UA1j7tarv8Fq/7jqLT9e7Fxy61E1jK42EG+qpLfjxJjW0PDEYISKfItmaCCr4ADb34IDmpt/VWDG6N4DVvecA9W06p8Tqqt6ihn8KDEaIyKd4sA+dxaeudwd/OuZOk7qc3TS1riVxfo6XrL/6++qDuTbyIClw0TMiIhdJtZS5Cj5/ZSPFl/iaLQGS703jsIwMNbxFDf8WGIwQUUBSwwewLc5Ww2pfDn5HZgEKSvVWn3P0Guvo1DX4UqHlZyRRvUbKPX2aWn1eDf8UGIwQkU+Rqkn5WN4lSfKR29BOCTafs/1WyDG31/VTftqRha4vrcAlKwtyORLmRLeVlOM4HP1ZKRWL3No10eM8pg3vgB8eScX04dbX0PHWxon2MBghIp8i1efmzN8PSpORzJ5Ob2vnWeUrEWfstbKcu9rGg6ptDFG1BnV1HucRog1C92axCNEG4U4rm+upIBZhMEJEvkWi8at+wd1Fz9x5Hzx57yoNtdfo8Oamcs4wKryMyI0drbeAST2raIiV63AAKxGRi9TwwSk3Z7sfvDpmRPIRrNJm5ylHLSNyT+21lb3U17U29kUN/6TcCkbmzJmD5ORkhIWFoXfv3ti8ebPd9O+88w7atm2L8PBwJCUl4cknn0R5eblbBSaiwKaGD061sBUgOBps6U715lGLlJWTP/njuIPrefdGO9pgT+7YyVbM4Y2Bs2r4J+VyMLJw4UJkZGRg+vTp2L59O1JSUpCeno7cXOvzwL/++mtMmjQJ06dPx4EDB/DZZ59h4cKFeP755z0uPBEFHjUMtvMme3WRzZVJHVSdbnXTSPy2V6+o68n1aq3A6kHF/criA+6fLAFb98zdfZhsXsdqy4jy/6ZcDkZmz56NcePGYezYsejQoQPmzp2LiIgIzJs3z2r6DRs2oF+/fvjnP/+J5ORkDBkyBHfffbfD1hQiImtKPNgiXg0fus5wemqvF1+OJ5d6a9khr17PHbtOF9h9fpWNhdc88cMjfa8+sNVNI/lVa1PDPwuXghG9Xo9t27YhLS3tagZBQUhLS8PGjRutntO3b19s27bNFHwcP34cS5YswU033WTzOhUVFSgqKrL4ISICgLziCpRXuh+Q+BNfGTOyp8Zsmv1nHX+mO1MJq21GjquaxkaYfvfWS7HWAqOGmUTBriTOz8+HwWBAfHy8xfH4+HgcPGh9mtw///lP5Ofno3///hBCoKqqCg8//LDdbpqZM2dixowZrhSNiALIifwStG8UpXQxFGcrQJCjkpayunruh90S5uYfvLb3jZXLeLTFgkRkn02zdu1avPbaa/jggw+wfft2/Pjjj1i8eDFefvllm+dMnjwZhYWFpp/Tp0/LXUwi8iFVBhV8enqJvUrK3am9bpHwLZdrRlR0eIgs+crF/D7ZumXe+EtXQ/elSy0jcXFx0Gq1yMnJsTiek5ODhATrc6SnTp2Ke++9Fw8++CAAoHPnzigpKcFDDz2EF154AUFBteMhnU4Hnc7zhV6IyD9VKb0ohMycDSa82bwu5bWk+iZes8uhR3Is6oYF45M/T0hzAZmZl97WPffGjGrlQxEXW0ZCQ0PRvXt3rFq1ynTMaDRi1apVSE1NtXpOaWlprYBDq728zK8aojEi8j0GN2szpT9xUpJiJM3PqwNYJbpWpcGIA+fkGQeoAfDCsA6y5K0UbwScaqiKXWoZAYCMjAyMGTMGPXr0QK9evfDOO++gpKQEY8eOBQCMHj0ajRs3xsyZMwEAw4cPx+zZs9GtWzf07t0bR48exdSpUzF8+HBTUEJE5IoqO8HIX0fzIQTQv3VcredOnS+Vs1gOJdePcDhrwxW2KpGIUJc/2t2+lqs+drC+iCuknNqrBK+NE3FwTTU0DLj8Fzty5Ejk5eVh2rRpyM7ORteuXbF06VLToNbMzEyLlpApU6ZAo9FgypQpyMrKQoMGDTB8+HC8+uqr0r0KIgooRhvBSJnegFGfbgIA7JuRjjo66StlTzhb9Zh3P9hfZ8T6+5Daoj6+33bG9nlu1D1SfUNf7eQUWXfqaV8LRszZHDPihThB+VDEjWAEACZMmIAJEyZYfW7t2rWWFwgOxvTp0zF9+nR3LkVEZDP4qKlUX2X2u0F9wYjEtaVXB7BKRI1rqKhZclwdSfOz9v6rYYsF7k1DRKp2NLcYXV9abnlQxZWtPVIX+9kb27lXDjcKooL6qpaaL0Ntm+9JQRcchFYNIyXLz/oKrJJl7zYGI0SkajN+3Y+i8irLg058eKphISe5dW9Wz+pxh7v2utVN47nZKw5j66mLTqVVc+uOs+7qmWT3eWfHauiC5a2qGYwQETmQVVDmdFolBgS6wunPfPP1J1TykjytsPacKcR/Vh2RpjBX1LzfQd7YVc5JocFBeP2OLrLknXFDG7fPtboCqwqiEQYjRKRqx/NKPDq/pKIKH649hhP5nuUjBTV86APuBjjC7P9dl1Ug30ymUb2bol1CXQzpEO84sZfoq+RZC6db0xg8Pri1pHmq4a9SXaO7iIgk9sbSg/hi4ym8vdz1zdqk5q0PfYe79rrTTVN9jhpqrhpeva2z0kVwi/lbaatVr+a9CvKwqcza6RzASkTkDmd2OL3y+br15OUxCu4ulCYlZz/z1dI1Y+5qLKL8+1jN0dvULqGuV8ohNyn/HqyuwKqCW8pghIj8WrBWhTW7zKRe6RW42sXkbsX18FfbJSxNYDF/z1W+7ZDbGIwQkc8prTDgtg/+wpw1R22mqf6A1apoUKO3PvSbS7w2BaCOCqsWB7dW9QOaZQ4yrLI6tVf5u8tghIh8zlebTmFHZgHeWmY5DsTaR2qwmoIRJz/01VPiq6qL7q16S4rrqOjWq5oKYhEGI0Tkeyoqrc9UsFbZ+3rLiFoW8vL2+NUjuZc8zkPlDSMI1V6tgr31d2p1aq9XrmwfZ9MQkd+w9qGqpmBEFZ/6bro6ZkQ9L0JFd9Yt0REheDKtDTQaoKC00qlz5AiwOJuGiMgN5h/I64/km343/0yt/l0tLQuAPDNRHhnYUvI87fl262mvXs8eRxW4mu69LRPTWku+bog9XA6eiEgG93y2ybTAlHllr6YpqK5yZeDls+ltMbhdQxlLc5kQQHmlASsPOLfrrjua1At3Kf35Er3d59XeTeMs89fhaYBl7ezCskpsPnHBo3w9xWCEiHye3nBlDIlZ/FG9rIiaKiQ5voFqNBo0jNJJn7EVtsbqSKVjYpSk+ano1qve/320UdHrMxghIp9TM8Co7vM2r+vVNLahmgqL5DQBAYMvvwCV81ZLnlqnOzMYISKfU7NOtDbtVI31prMVjnl14Uzd4Y3XKoQ6VrF1hW+VNrAxGCEin2evFaS80uDFktinlgDJnW/h3ghGpB5wqoZZIlIb3N6z8UEqbRhhMEJEvqd2N83l/1oMYL3y696sIi+Vyr/5UjdNeIgWADCwjfwDe20Z1LaBJPnUDBwf6N/co/xUGotwnREi8n3W9k2p/hBX06wauUpi/ro7NHI8CNSdFgghAKPcLSMS1ZR/PDsIB7OLEFsnFO/b2TJATlKNzai5S2+w1j/bEPzzVRGRX6tZmVpbHVSNwxu8sWvvNw/1cVwOd7pp3CmMQhrU1WFA6waq6RZTE3bTEBHJxGhldVBPd5n1VdHhIQCANvGRFsffHNHFs4yF/O+lWitKd0j1Umq2jPgrBiNE5POszqap8V918F5p/tG1cY3HiR7lJ678T05SD2D1h0BU+lhEncENgxEi8nnWZk2osSJSY9eRs4QXWkZCg6WtkpQcLyRVEMGWESIilar5+Vw95dSyshQW//FVUtVFnrY6CMg/VbZtQl1J8/Pl4K+a1KGIWmMbBiNE5PNyisoBWJ/aq5bZNH8+O8jpVWFdrfOtvUapV6AVQv53UgOgbbx0AYkaV+G1xVZRpQ4eVBqLMBghIt9T84N71vLDtY6r7VtxUmyEomGRp5WagHcGsFYapdv/Rtk/AWmqfbUu3y41BiNE5HNqfj5Xr7JqsTcNrHXdBA69QeqWEeA/q45ImmdNnRpHS/rN3R/uvfTdNOoMbhiMEJHfsJzae+W/CpXFGncqR2cqD2v5DqyxAqh5LtUrlLrCYBT4ZddZl89zRd+WcZIGEErWuxzA6hquwEpEPs/aNF41fit2ZwCou+Mermlar9ax525sh9MXS9E1Kcbl/Ly1z4uUV0lpEoPuzeph26mLEubqXRwzQkTkQ/IvVeD91VeX/hYQqDQYJd3crXfzWMny8jaNRoNHBrbEa7d1dqupXu5Y5K0ri7JJOehUG6TBD4/0lSw/JQRpNJKvv6JGbBkhIp+3I7MAPV5ZaXFMCKD1C79Lep1grfcrBae6abxQjnOFZbLmf2ePJADq6lbzhFR/Ke2d2GvIH7BlhIj8khzf5D1eq0PBmtbTyvFiaaUk5XDX1Js7YPeLQ9w6d0DrOIlLI78pw9pj9VPXISE6TOmieAWDESLyS2pZX8TcXb2SZMm3W9MYWfJVgq2xKRoAUWEhbuX59p0pHpTIPZ6O9WhQV4cWDSIdJ/QTDEaIyC+pcQDrsM6NsOyJax2mc7Xod/Vsitdv74yVGdfZTOMrkzJs3bcgD8qv5IwUJQIhX8RghIh8jlLjKFyp0xY+1MfK+RqXlzx35pLaIA3u6tUUrRr67zfpET3cb1VSIhap7tJLbVnf+xf3QQxGiMgv7c0qVLoIDvVoVnv6LQDozDaMiw53r2uiJrUuduWsSF1gzbcIlPVFqgXW3SUiv+DM9M8pi/ZKfl2pK/RpwzvgzMUytK7RohGiDcLvEwfAYBSoE2CVcEqTGJy5KO3MHSWq9eo/FVvXfia9rc1zOyZGYUjHeOkLpWKB9VdORH5BqW/5rlzVmW4iDTS4qXMjq88FypTOmuSYPq3E34ujS44f1Mrmc4sfHyBxadSP3TRERE4KsJZzv6HkbePfjHMYjBCRz+HnO7lCyQGs5BwGI0RETpJ+B1WJM5RYopcW3Kq5qZ8/YVDiHAYjRERO8vUZKa5a9+wgfDq6h+zXmf1/XU2/y/EOMyBQPwYjREQyUOOia64K0QbJPpvnoWtbILZOqOmxLG+bItNprvzHyWtLuUGgPWqNpxmMEJHPUeoD1ZNVQH2V3O/15KHt5L0A1FsBK23KsPZKF8GEwQgR+RzlWh2krdUSY8IlzU8OctfjNbu+5Omm8T5Njf86TK9AxHRXr6Zev6YtXGeEiHyOL/SA2Nuob83TA1Gqr7LonlCrQBsn46xhXRph8e5zkuXnrW4a88uo6c4yGCEicpJU9XLzuDrSZOQF/hCLyBFQefNt8Yd74Ai7aYhI1aLC1POdKQDqhFr84TXL8Rpu7JRg/5p21oPv3ypOhhI5xzywUVOQw2CEiFRr3eE8FJVX1Tquos9Qv6emCstdcryGnsmxbp97Q4fA2nfGGQxGiEi1nvt+t9XjSo0Z8YeK2XW+/6LlWGfEUY5XB7DWTunq+BC5hpOoaf0VBiNE5HO8NdivJpc+vH1hlK0TvB2AccBsYGIwQkQ+R7Fde128bJcm0QCAuioa9+IqfwgNZPlzcZCnachIjXQxESG4rVuTWunjvbT0vjk1xX2++y+EiPyeremxUraM9GkRi7+PX3Aqrasf3nPv6Y45a45ibL/mbpRMHeQM/F67rbNT6d68o4tsZXCXo1ayhnV1Vo9vm3IDtFZWz7u/X3OczC9BWvvAHE/CYISIAlpEqPMfg6500whcXtTsVScrXLWS88uzoxVt60WE4K9J17t0j6xRogXgscGtL1+7xnFrgQgAhIVo8eaIFKvPJcWGY09WoZTFUx0GI0REbkprH4+VB3KULoasvD5mpMZjTwORy3nKMIDVQZZRYSGSXWvGLZ2gDQrCPyVeMVVN3TQcM0JEAc2Vz+Mm9SyXb/9kdHfc1zdZ0vLQVa3j6ypdBI9J0c3VoK4O793dDakt60tQInViMEJEqiX3pJluTWNcSj88JdHisUajwXM3yr/Rm5KUnP757l1dJcnHlXggpUk0RvV23AKhokYFt9W8t/mXKhQqiZvByJw5c5CcnIywsDD07t0bmzdvtpu+oKAA48ePR6NGjaDT6dCmTRssWbLErQITEUmlQ6Mop9Pe06cpOibWTh8eqrWaXrnN/KSlZFN+o2hpNhJ05SUISDsr25eClswLpYpd2+VgZOHChcjIyMD06dOxfft2pKSkID09Hbm5uVbT6/V63HDDDTh58iS+//57HDp0CJ988gkaN27sceGJiDxhFM5Xtq/c2tlmk/vXD/aWsFSBw1uBjitdJUI4N1vLH2JNNY0ZcXlk0OzZszFu3DiMHTsWADB37lwsXrwY8+bNw6RJk2qlnzdvHi5cuIANGzYgJOTygJ7k5GTPSk1EJIGuSdFYsb/cYbpGDtaAuKZZPamKpDpqqrDc5VrLiIDRKOG1fej9U7KoLrWM6PV6bNu2DWlpaVczCApCWloaNm7caPWcX375BampqRg/fjzi4+PRqVMnvPbaazAYDDavU1FRgaKiIosfIgo8cn/7HNE9yWGa8BAtfp84QOaSyKutBwNB1bRkuFQax9ju/hHC9vo2NdP5OjXdWZeCkfz8fBgMBsTHWy7KEh8fj+zsbKvnHD9+HN9//z0MBgOWLFmCqVOnYtasWXjllVdsXmfmzJmIjo42/SQlOf7AICJy1eU1H65+JFv7Fpvasj5iIkJdztuZCs1bPJmFIec3e28FOuavISYiBP+9v5fNtF2TYmBUz62TVc3uKyWX4pd9No3RaETDhg3x8ccfo3v37hg5ciReeOEFzJ071+Y5kydPRmFhoenn9OnTcheTiHyIP3wr9RW+1M1gi3kl+8Goa9CqYaTNtJNvau/U35ezwaYvtSwpWVKXxozExcVBq9UiJ8dykZ+cnBwkJCRYPadRo0YICQmBVnt1xHn79u2RnZ0NvV6P0NDa3zh0Oh10OutL6RJRYDh/qQJ5xcpNNaTLvF2ZtrQTKHhDpC5YsY0YvU1NYZJLLSOhoaHo3r07Vq1aZTpmNBqxatUqpKamWj2nX79+OHr0KIxmI4IOHz6MRo0aWQ1EiIgA4O3lh7xyHX/45i8nWd8fK3k/OKA5HhnYEt89bL1O8QanQhFn4xUf+vtS8t+Cy900GRkZ+OSTT/Df//4XBw4cwCOPPIKSkhLT7JrRo0dj8uTJpvSPPPIILly4gIkTJ+Lw4cNYvHgxXnvtNYwfP166V0FEfqeovMrmc3KNx3Dms/ifVxbEuq3b1eUJrH2Iq+nLtSff9OWsnyKsrNGiC9biuRvboWdyrDwXdeKtMKrp5slITYG4y1N7R44ciby8PEybNg3Z2dno2rUrli5dahrUmpmZiaCgqzFOUlISli1bhieffBJdunRB48aNMXHiRDz33HPSvQoiIpnUrMhfHN4RN3dphO5+PJ3XnJwV1o0drXfve1PjmHBkFZRZHHNmAKsA0LJBHRzLK8HAtg2w9lCe1XRqqvAB+91uSo5vcWsHogkTJmDChAlWn1u7dm2tY6mpqfj777/duRQRBShvfSw6uk5YiOW399DgIPRtGWdxTKu2GkdS8ry2iFAtgrXK70jSu3ksftyRZXHM2Zakr8f1wU87sjCyRxK6vbxCjuLJqvZsGoUKAu5NQ0QqtXjPOa9f0/zD+Y07OqNdQl1MubmDw/OCtUH44v5e+Pje7qZjgdHQ7339W8U5TuSm/9zdDQBwV8/LXXGO9i6KjwrDw9e1RL06tsc/+nOYKiUGI0SkSt7qtq8e+9GyQR2L4yN7NsXSJ661u0CWuWvbNMAQFXQ7SE2ub8vu3t83R3SRtiBmrm/XEADQv3Uc/nhmEBY+pNwgWrmoaf0bcwxGiMjnSBmo3NgpAb9O6I9fJvSX9FusvbUsvC0oyP1XprZv9p4GR7X+dMzyM++eaVo/AqHBtqtIZ/8GlVxIzJe4NWaEiMhfaDQadG4SLVl+fzwzCAVleqdbVOT01A1t8P32Mxg/qJXbeaitMpV6kGVCVBiuaRqDEG0QInXOV4n16oQ4lU5ta5bYHcCq4K1mMEJEdIUUH8ZN60egKSI8z0gCjw1ujccGt/YoD7nqJ3e7CzxuGalxWY0G+OGRvld+d5z5tilpELg8Bdmp67laQAX53GwaIiIlqezLpl9TWcOI5IRwrfWnfqT7q4P/9lh/t8/1dxwzQkRENsn1bdndgNLXYiPz11k/Ut2rjnNqLxERqZK/t4zIoWNi1NUHZsGIGjbNi49W575v7KYhooBzTdMYjO3XvNbxRwe2wrurjuAfXRMVKFVgUaqnzRtTW+fd19Pq9dQQ2DWsG4YFD/WxOliXA1iJiLzox0f7WT0+cXBrpLWPR7tGdb1cIvVSQwVqQeLySB2aPH59K8RHhV3NX4Xjm/q0qG/1OAewEhG5QK5vt0FB0k7z9QeyTe1VYSUthZovKyr86hTgWDsrtQY6BiNERGST2hpG6uqcW9+jptg6obhQokeXJjHSFqgGbY0F5rRBGux/KR0AEKKCvXjsYTcNEZEL1DAQMFDI1zDiXtNIeKgWUWHBKCqvcum8jZOvR0WVEVFh7gUzjjw+uDUW7z6LsX1rj0WKCGVV64i6wzQiIivUur+GP1Jj4Lfgyp4x/7q2hdPn6IK1VgMRqcZ0ZNzQBqueGojoCHmCHW9Q8k4zXCMiVRFCYN/ZIgdpvFQYUqUOiVE4/MpQu3vHkG/hnSQiVfl262nc/N56u2lUN8PDj6n1vWYgIj0uekZEdMWXf59SughkRra9adi6pULKRSMMRohIVZwZo+BKRabWb/Y+w8/fP44/UgcGI0SkKlIHD35el8pOtr1pZMmVPMFuGiKiK6T+PKy5aNfix7lzqisCvWUpRBvgb4CXMBghIr9WsyrpmMgVVl0h35gR32gbefKGNkoXwWuUDLsYjBCRujjxVdyVaizQv9l7Srbl4FWiZYNIu88/cl1LL5VEeUrea64zQkR+zUe+gKuWbC0jMuXrrB8e6YtNJ87jjmua2E2n0WigDdLAYFS6xP6NwQgRqYrUlR+rEM/4a8NI92b10L1ZPaWLoSrspiEiv3ehRI/zlyocpnOm8tt84oIEJSJnyDabxoeiRD+Nx1SFLSNEJLsqgxHXvLwCAHDolRuhC9baTMsPfpXhDQmY1jVO7SUiv1ZSYTD9frGkstbzQggUlOplubavzNpQK3/tpiF1YcsIESmu0/RlKNEb8MGoa/x+9gb5Hv5Fyo/BCBHJ6oO1R/HfDSdNj2vGGgezi1Civ9xy8uriA2gUHSbp9dku4hlWxPwb8gYGI0QkqzeXHrL7fHZhucVjORtGRnS3P42TamNLFXkDx4wQkaJqfuuUYvZGywZ1rB5vHBPucd6BRspQJCrMN7//MhyTH4MRIlJW7WjEY+brU3H8qmekbBhZ/PgANI+7HCgOaB0nXcbk83wzTCUin2UUAkIIU/N/zS3cpVhDxGgjAmFc4jop1xnRaICvx/XGj9uzcHevppLlK7dA+btRMnBnywgRSabKYITRwbLZw99bjzs+3GCacivHB6AumB9tUpF6yEij6HCMH9QKsXVCpc2YPBYRanv9H7mxZYSIJFFeaUD/N1YjKTYCPz3aD0IIjJ63uVa6/Et65F/So1RvQB1dMKTc8uOunkkoLq9CwygdDudcqp2AfTaK8tXBsL5ZatdFhYcodm1+fSAiSew+U4j8S3rsyCwAABzLK8GfR/Jtpi+vNOD13w9iyZ5zkpVh/KBWmDPqGtmWMA9EPho/SMqfQ9i7eyUBAB66tgXCQtgyQkQ+rmalZWvcRrVZKw7j602ZspSl5jgUcp+kY0Yky4mkMvP2Lph2c0eEK9hFA7BlhIgUst5Kq4mnS7dXB0S2KlCGKK5jy4j/B1FKByIAgxEiksG1b65BVkGZ3TSZF0pluz4rUOnwrWQQ6w0MRohIEuaNGpkXSvH6koNeL4OvDpBUM76n5A0MRohIFpUGo8vnePoN1FG1yck0rpMyFPHVuMZHi+1TGIwQkTwU/AQ3v3RdH12CXO0e6N8cXz3QW+likJ9gMEJEsnAnFjlXY9M8l6+psfwvAPzvwasVJmfZuM5aa8ao3k0x9eYOaBMf6fD827o1Nv0eqmWVQ9bxKwMRyUItYw26NIkx/a5VSZl8ibX7aFocy4m3MyxEi2dvbIsqg0D9SJ3EpSN/wWCEiPxG9ZTemhXo49e3wq+7z+H+/s2VKJbfcnYNkkcHtpK5JOTrGIwQkd+pWUVmDGmLjCFtFSmLPwuUhqa4SB2yizzrQiT72IFHRJKoWTEpUU8FSuWoFoHydn8+tid6NKuHb8b1UboofovBCBHJQonAoPqSfVvFef/iAaR6irRaxgXJrX2jKHz/SF+ktqyvdFH8FrtpiMjvXNemAb58oBdaNXQ824PcFxihCHkDW0aIyH+Y1Y4DWjdAo+hw5criR97/ZzeLx9amUJvjFF5yFf9iiIjIrpu7JEIXfLW6MHXT2GgbCdGyzYRcw2CEiHxaj2b1TL9Lud09OYFvN0mEwQgRycJb+8BE6Dj0zRus3c4AGb9KXsBghIgkUTP4UGLh9SBWjl7Ft5ukwmCEiCSx8kCOxWPhpaYR8+sE8au6fIT5r5cfODO196bOCXKViPwIgxEiksTSvdkWj5VoGWEsIh9rmww683YPaN1A+sKQ33ErGJkzZw6Sk5MRFhaG3r17Y/PmzU6dt2DBAmg0Gtx6663uXJaIVExbo4/EYPROOHL7NVd3hQ2URbjUwtbbzftArnI5GFm4cCEyMjIwffp0bN++HSkpKUhPT0dubq7d806ePImnn34aAwYMcLuwRKReNeufU+dLvXLdBpFhNstA0rHW62Zr9pK3uujIf7gcjMyePRvjxo3D2LFj0aFDB8ydOxcRERGYN2+ezXMMBgNGjRqFGTNmoEWLFh4VmIjUSQ3jNdRQhkDCt5uk4lIwotfrsW3bNqSlpV3NICgIaWlp2Lhxo83zXnrpJTRs2BAPPPCAU9epqKhAUVGRxQ8RqZsaZrKooAh+i20dJCeXgpH8/HwYDAbEx8dbHI+Pj0d2drbVc9avX4/PPvsMn3zyidPXmTlzJqKjo00/SUlJrhSTiBSghlYJNZQhkPDtJqnIOpumuLgY9957Lz755BPExTm/i+bkyZNRWFho+jl9+rSMpSQiKaghEFBBEfyWxTgQB8vBE7nKpaUL4+LioNVqkZNjuZ5ATk4OEhJqzyU/duwYTp48ieHDh5uOGY3GyxcODsahQ4fQsmXLWufpdDrodDpXikZECosOD1G6CAxGZMQVWElOLrWMhIaGonv37li1apXpmNFoxKpVq5Camlorfbt27bBnzx7s3LnT9HPLLbdg0KBB2LlzJ7tfiPyAEAJ/Hc1Hv1b1lS4Kv6l7Gd9tkorLmzpkZGRgzJgx6NGjB3r16oV33nkHJSUlGDt2LABg9OjRaNy4MWbOnImwsDB06tTJ4vyYmBgAqHWciHzT6oO5eOC/W2W9RlykDvmXKhymU8MgWn9ldWqvlaaRFnF1kFNU7oUSkT9xeczIyJEj8fbbb2PatGno2rUrdu7ciaVLl5oGtWZmZuLcuXOSF5SI1Gn90XzZrzH15vZOpeNiW95l7d2ed19Pr5eDfJ9b211OmDABEyZMsPrc2rVr7Z47f/58dy5JRCrljcXN7AUZ5suUMxTxLvPbUi8iBM3q10HT2AjlCkQ+i3tvE5FHSvVVsl/D2SCDDSPeZR4kfvVgb3RoFMXWKXILN8ojIo94YwsaZ6cNsyKUz5RhV7vKbN1yvv/kLgYjROSWrScvYOvJC2jVMFL2a9kbmNq6YV3E1glFay+UI5A9OMD+Vh7cjoY8wW4aInJZeaUBI+Ze3gLixeEdZL9ekJ1oJESrwabnB6ti0bVAFh6qVboI5MMYjBCRy0oqro4TKdEbZL+eo0AjRMtGXqVMGtoO5y9VoGUDtkyR+xiMEJHq2Ys1OE7B+xrWvbpC9sPX1V5FOz46DMfzSrxZJPJx/DpB5Oem/bwX76w8rHQxPKILZheAGnx8b3fc3asp7k1t5iBdD/RvFYeFD/XxUsnI17FlhMiPHc29hC82ngIAPJHWxuP88oorEBcZajGbYvYK+QKdSF0w7uubjLhI23tVcdVV7xnSMQFDOtbeh6ymVg0j8dWDvb1QIvIXbBkh8mPlldKN5/h6UyZ6vroSby07ZHHcIOPc3idvaIOn09uiWX3bC2nFRITKdn0i8g4GI0TklGk/7wUAfLD2mNemcVY3eoSFaLH/pfRazz86sPZ4BSLyPeymIQoQQgjJBnsKm8teScu8uBGhwVj6xAD8vicb/+zdFPvOFqJ/qwZeKQcRyYvBCFGAMApAK9H4Ck9bRvq0iMXfxy84TFezuO0SotAuIQoAEB8V5lkhiEg12E1DFCCEhxGEeSuFp8HIIwNbOXlNjk4lCgQMRogChKcdKxqzdor31xzxMDcnr8lYhCggMBghChBGCUedfvV3pkfnm7fSPGJnECpjEaLAwGCEKEA4E4sYjAJrDuXiYole/gJdEWxvoRA2jRAFBAYjRGTyxcaTGPv5Fgx/f72s1zGPi+ztO8NQhCgwMBghChDOdNMs2XMOAHDmYhkAYMOxfPyw7czlJ6WMDMyKUj8yFLekJGJ4SmKtZGwYIQoMnNpL5MdcnQGjqRFx/POTTQCAdo3qSlksi3VKNBoN/nN3NwDAr7vO2i0PEfkntowQ+THzAMSp4as26v7TF0qlKI5V3FuGiBiMEAUIZ7ppbMUFD3+1XdpeGrOi2B0zwkCFKCAwGCHyQXnFFZj0w27sOVNoN53L3TReqPz/r0cTi7LYuyRjEaLAwGCEyAdN/nE3Fmw57dqsFzfGjJirqDI6fy0bWjaog9dv72JRFHsBEFtGiAIDgxEiH3Q455LL5+w4fdFhGrkr/8SYcAQFaWAwmg1gNQuAvh7XG1OGtbf6HBH5LwYjRAHivs+3OEwjdzBS3T1jtNFP07dlHB4c0MLqc0TkvxiMEAWo8koDSiqqLI7J3RJRPaW3yqJlxDbGIkSBgcEIkR+zN2i1xysr0XH6MhzPu4Q/j+QB8N4YDaNZMNK/dZzNdNy1lygwcNEzogAjhIBGo8GlK60i189aBwD48oFesl/beGUMrHnLSKPocJvpGYoQBQa2jBD5IGcbDGquLbJwSya6vbwCO08X1Eq7+cQF2VsihHNLrxFRgGEwQuTHanbTPPfDHhSUVuLWOX/VSquB/C0R1eUZ1rkRWjSog1G9m9pNz14aosDAbhoiP+ZSO4RGY1H5l+qrbKd1U3V5wkO1WJVxncOWmLphIZKXgYjUh8EIkR8rLq90+9y3lh2SsCSXCWG5QZ4tM27piN1nCjG4XUPJy0BE6sNghMgHObO0OwDc+9lml/I1Dw+2nnS8SJqrnJ06PKZvsuTXJiL14pgRIgJwZcyIWWuF+YwXSS9CRFQDgxEiH1Rl8HyfmJp+3XXWIlYwGKW/BmMRIrKGwQiRDzpbWC55nsfzS7DucJ7psTv73wBAv1b1LR5f0zTG9HsQp8cQkRUMRojIRIqumQ9Gdbd4/NmYnqbfGYsQkTUMRoh8XE6R9K0knogOt5yOW69OqOl3BiNEZA2DESIf98z3u5UugkmnxlF2n5d7Iz4i8k2c2kvk447mFCtdBADA3hnpCA/R2k2TFGt7HxoiClwMRoh8nBwzcN0RqbP9cfK/B3vjh21n8NyN7bxYIiLyFQxGiHxczc3wqlnbDE8p/VrFoV+rOKWLQUQqxTEjRD7OWsuIEMLqZnhERGrEYITIxwkrLSNZBWUKlISIyD0MRoh8nLVumhX7cxQoCRGRexiMEPk4a900M37d7/2CEBG5icEIkY8rLKuEQeEpNa/c2knR6xORb2MwQuQHftt9VrFrN44Jxz19mil2fSLyfQxGiPxAblGFYtfmEu9E5CkGI0Q+Zm9WYa1jagsIRnRvonQRiMiHMBgh8jGjPt2kdBEsWFtzLTGGy74TkfMYjBDJyGAUqKgySJpnYVllrWMaBZtGEqLDFLs2EfkHBiNEMrrxnT/Q4+WVKK+UNiCpqToUEULgy40nZb1Wta8f7I3r2jTAOyO71n7SxhL1RETWcG8aIhkdyb0EAFh3OA/pHRPwxtKDOJJzCR/d2x3aIOlbM1YeyMXUn/dJnq81fVvFoS/3myEiCbBlhMgL/vXlNgDAh2uPYeWBHPx9/Lyk+Ws0wMUSPXapZHM8tosQkSvYMkIkE2ONhcjMZ8FIPY6kVG9At5dXSJonEZG3uNUyMmfOHCQnJyMsLAy9e/fG5s2bbab95JNPMGDAANSrVw/16tVDWlqa3fRE/sJQY9zEze+tN/0u9ZCKzPOl0mZIRORFLgcjCxcuREZGBqZPn47t27cjJSUF6enpyM3NtZp+7dq1uPvuu7FmzRps3LgRSUlJGDJkCLKysjwuPJGaWdvATi7nS/ReuxYAJETZn0HD8atE5AqXg5HZs2dj3LhxGDt2LDp06IC5c+ciIiIC8+bNs5r+f//7Hx599FF07doV7dq1w6effgqj0YhVq1Z5XHgiNTpzsRQ/7TiDSoPtGlnqynrlAe/u0vvjo33tPi84aoSIXOBSMKLX67Ft2zakpaVdzSAoCGlpadi4caNTeZSWlqKyshKxsbE201RUVKCoqMjih0iNdmRexMiPNlqMBxn41lo8uXAX/rvhpM3zfL2qrh8ZqnQRiMiPuBSM5Ofnw2AwID4+3uJ4fHw8srOzncrjueeeQ2JiokVAU9PMmTMRHR1t+klKSnKlmERec9sHG7DpxAXc9fHfAIAyvQFVVwaubjiWr2TRZKWB/WnJ7KYhIld4dWrv66+/jgULFuCnn35CWJjtPufJkyejsLDQ9HP69GkvlpLIdZcqqnCusAyTftxtOhYcZPufl/Dx2lpte+EQkW9zaWpvXFwctFotcnIs+6dzcnKQkJBg99y3334br7/+OlauXIkuXbrYTavT6aDT6VwpGpHiUmeutni8/qjtlhHfDkWAIAfRiK+/PiLyLpdaRkJDQ9G9e3eLwafVg1FTU1Ntnvfmm2/i5ZdfxtKlS9GjRw/3S0vkQwxG7w1g9TY2jBCRlFxe9CwjIwNjxoxBjx490KtXL7zzzjsoKSnB2LFjAQCjR49G48aNMXPmTADAG2+8gWnTpuHrr79GcnKyaWxJZGQkIiMjJXwpRN5TXmnAyfMlHuSg/mjkm3F9cCzvEqLDQ/DvFYdxPP/q63XUTdMtKUbewhGRX3E5GBk5ciTy8vIwbdo0ZGdno2vXrli6dKlpUGtmZiaCzPrKP/zwQ+j1eowYMcIin+nTp+PFF1/0rPRECvh5ZxYmLtiJgW0buJ1HQWntnXerffrncXy39Qz+N6434iKV665Mig1Hasv6AIA5a45aPOdol+AbOsRjzj+vQYfEKNnKR0T+QyN8YCRdUVERoqOjUVhYiKgofriRe95adhD7zhbh09E9EKx1f+x28qTFkpTn5OvD7OZ/Z/cmeOvOFI+vHxUWjKLyKrtp1j0zENe9tdZm+W7/4C9szyyw+hwRkS3O1t/cKI8Cxpw1x7D2UB7WHc5TuihO+W7bGeRfqvA4n0bR4Q7TNKtfx+Lx2H7JFo9fGNYeANA8rg6+eqC3x2UiIjLHjfIo4JRXGpUugtNe/m0/3r2rm9ev+0x6W4vH3ZvF4sBLNyI8VOv1shCR/2PLCAUcb+4ZY09xue1xI9XOFpR5oSS1RYTW/p7CQISI5MJghAKOWoKRV3474DBNlVHgwLkiWRdJe/W2TrLlTUTkDAYjFHDsrf/hTZtOnHeYZkdmAYa++ye++vuU5NffOiUNh165EaN6NwNweRBrUmw4XvpHR8mvRURkD4MRCjgqiUVQVF6F77aexsUSvcO0U3/eh399udXtFpJJQ9vVOhYXqYMu+GrXS7P6dfDns9djdGqyW9cgInIXB7BSwFFLN82FEj2e+X43ujWNwU+P9nOYftm+HDz4361uXSvEbCpz7+ax6JgY7VY+RERyYDBCAceolqaRK3aYrd/hyKqDuR5fb+G/bG/dQESkBHbTUMAxqKRlxNzrvx/EqgM5jhO6yQfWNiSiAMZghAKOJw0jcrWqzF13DA+42QVDROTrGIxQwLHWSuBsy0GVyrp4iIj8AYMRCjg1p/a+ufQg+r+xBuedWHq9yijv6q1ydKdc0ywGUeEhkudLRCQVDmClgFMzGPlg7TEAwCd/nrA6Bdacsy0jwUEat1pRXlvieCE0Z6166jos3n0OY/slIyxEiz+P5KPflV14iYjUhMEIBZzqxocyvQFTf95rOl5lcNzq8e2W005dIzo8BOedWD+kpk/+POHyOdasePJatGwQiccHtzYde+9u7+9xQ0TkDHbTUMCpnk3z2frj+H7bGdNxZ1oyXlnsestFXGSo6fcIL+3v0qJBpFeuQ0QkBQYjFBCyC8tNv1cvepZdVG6RxnwxNH2VETsyL7q9dLx5q8i1rRuYfte4lZvrgrx1ISIiCTAYoYDQ743Vpt+rp+dqaoQG5i0jGd/uxG0fbMC7q454fnGzy2g0GtzXN9nzPB1dUsNohIh8B4MRCgjmLRzVQ0Nqth4UlF5tzfht9zkAwEfrLg9uFUJYPO+KkKCr/8w0AG7oEO9WPkRE/orBCAWc6u6Ymq0HecW1p/ZWVBlxPO8S3lh6CF1fWuFU/mntLYMNAbOuHg1QXmlwscSuSe/IYIeIfAtn01DAEaZgxPL41lMXkVdcgQZ1dRbHr5+1zmGeTw9pg3p1QqGvMuLOHknoNH2Z6bkHB7TAt1svD5Qd0iEB4TIPYv3o3h6y5k9EJDUGIxRwqmfT1BwzIgTQ89WVODHzJpfznHB9a5vPtYmvi3XPDMSfR/Jxa7fGqCNxMNKgrg4pTaKx8oDnm+gRESmB3TQUcM4VXJ5FY2uM5/L90m9Y16x+HdzTpxkidcHQaDT4j0RrfqzMuA6bnx+MAWYzdoiIfA2DEfJrVQYjZq84bHHsxx1ZyDxfis/WW19g7F9fbpO9XJE6z1tH1j0zEK0aRkKj0dgMrIiIfAGDEfJr/9uUif9YmZ770m/7FCjNVTW7iNwRorWcpUNE5KsYjJBfW3c4z+rxA+eKvVwSS7pgz//pBZvNTea6IkTkyxiMkF9bfdD6oM6sgjLJruHOgNTeLTzfsE4XcvW61dOJWzfkMvBE5Hs4m4bIQz2bx9p8rn2jKKvHtR6s1353r6bo0yIW0eEhpmMJ0WHYNX2I1/a+ISKSEoMR8muh2iDondiN11UD2zbA2kOXu4DeGpFiM11idJik140OD8Frt3Wy2i1jHpwQEfkSdtOQX+vZvJ4s+aY0iTH9XnORNHP2xnLc3q2xy9dd+sQAjg8hIr/DYIT82l9Hz8uSr7PxgL10s0d2xdBOCTaff/kfHU2/fzamB/bOSEej6HBni0hE5DMYjBC5ISHKue4XRzHL/f2b23zu3tRk0++dm0QjUsdeVSLyT/x0I3JDv1ZxGNkjCT2S7XcDBTloQqlfJ9Tu87umD0FJRRUa1pV27AkRkZowGCFygzZIgzdGdHGYzlF3TosG9qfiRoeHcGAqEfk9dtMQucFRkNE8rg4A4JaURJfynTy0HQCgLrtkiCiA8BOP/Ja4sjuvHBwt5/7LhH44nleCLk2inc5zWOdG+Nd1LdG7RX0k14/wtIhERD6DLSPkt2SMReBozbK6YSFISYpxahruq7d1QssGdTDpSqtI16QYxETYH0tCRORP2DJCfssoZzQi4VIfo3o3w6jezaTLkIjIx7BlhPyWUeJY5N27upp+56BSIiLpsGWE/JaAc9FIt6YxeO22zlh9MBdvLTtkNU1YSBD+0bUxCkorERUeDF0w94AhIpIKgxHyW6fOlzqV7qZOjdC+URTaN4pCasv6eGD+FlwsrcSA1nH480g+gKvjT8b0TZaptEREgYvBCPmtrScvOkzz6egeGNi2genxNU3rYce0IbhQokd0eAhaPr9EziISEREYjJAfqzLa36134+Trbe71EutgZVQiIpIOgxHyW1WG2mNGejSrh7t6NUWnxlEubTon47wcIqKAx2CE/NbuMwW1jgUFaTCiexOX8wpxtLAIERG5jVN7yW8t2nm21rHr2jSwktKx8FDG7UREcmEwQoqSc8l2a8YNaOFS+ll3pqBeRAg+ure7TCUiIiJ+3SPFvPDTHvx1NB+LHx+AOl7aGC402LX4+47uTXD7NY2dWtadiIjcw5YRUsz/NmXi5PlS/GylO8VT5i0uSbHOD1S1hoEIEZG8GIyQrC6W6LFifw6qDLan2bq7h8y5wjJ8tO4YyisNFsdzi8rx2pIDpsfXNK3nVv5EROQd7KYhWezNKsTIjzaiRH81UPji/l7o1TwWx/Iu4eC54lrnZJ4vRVzdUETYGCwqhMDPO8+ic5NotGwQidSZqwEA2zMv4qN7ewAAdp0uwD/m/GVx3jPpbXF/v+Ze6woiIiLX8NOZZHHPZ5ssAhEAGD1vs9W0UxbtxfbMi/hxexYax4Tjr0nXW023Yn8Onli4EwBw5NWhpuPL9uUgY+FOPHNj21qBSKQuGE3qRaBJvQgPXg0REcmJwQjJoqC00qX0P27PAgBkFZTVei6nqBwPfbkNu04XmI61fuF3y/N3ZOHHHVm1zr1UUeVSOYiIyPsYjJDqJE9ajC8f6IUGdXV47OsdOHW+FHo7Y06IiMi3MRghAECpvgqjP9uMQe0aYvygVh7lVSlB4HDvZ9a7dIiIyP9wNg0BAH7ZeRZbT13EW8sOeZzX4t3nJCiRNB4Z2FLpIhARkQNsGSEA7rVmlFcaoAsOMq3DUWkwwmAUpkGm1bo0icYvE/rj9IVSPP/THowb0ALXtmmAF3/Zh/kbTkpQ+to2vzAYBqNAQlSYLPkTEZF0NMLb63G7oaioCNHR0SgsLERUVJTSxfFL7ab+jvLKywHJvhnpDqfBbjl5AXfO3Yg6oVrsmj4EXWYsR2mN2TMA8OezgxAXqUN4qNZqPgajwP6zRWgdH4ngIA0qqowY+/kWbD55AWnt4/H+P7vhgzVH8Z/VRwEAk4a2Q8/kWOw5U4CRPZtCG6Qxrar6884s5F/S4/5+yVyojIhIBZytv90KRubMmYO33noL2dnZSElJwXvvvYdevXrZTP/dd99h6tSpOHnyJFq3bo033ngDN910k9PXYzAiv+RJi02/PzqwJZ69sZ3pscEoMGv5IfRuUR89k+vh0f9tx9pDeQ7zfDKtDSamtXarPOWVBoSFXA1gissrcamiCo2iPVtNlYiIvMfZ+tvlMSMLFy5ERkYGpk+fju3btyMlJQXp6enIzc21mn7Dhg24++678cADD2DHjh249dZbceutt2Lv3r2uXpquOH2hFE9/twuHc4pRqq9CblF5rTSHc4rx4i/7kDJjOfKKK1BQqrdYIj3zfClK9danvR7OuYQqgxGnzpdg1vJDuPvjv/HB2mMYM28zOkxb5lQgEh6ixfhB7o/XMA9EAKBuWAgDESIiP+Vyy0jv3r3Rs2dPvP/++wAAo9GIpKQkPPbYY5g0aVKt9CNHjkRJSQl+++0307E+ffqga9eumDt3rlPXlKtl5KN1x3D6YimCNBpo4HgPErla/gtKK6EBEBUeYnFcCAGjlbvz5d+nah3r27I+kupFoLCsEkv3Zdu8Vs/kethy8qLpcXiIFi0a1MG+s0Vul7+m5U9eizbxdSXLj4iIfJOz9bdLA1j1ej22bduGyZMnm44FBQUhLS0NGzdutHrOxo0bkZGRYXEsPT0dixYtsnmdiooKVFRUmB4XFUlXUZpbui8bOzILZMnb2zYcOw/gvMN05oEIAJRVGtwKRGLrhGJVxnX440gejuZewiMDW0IXrIU2iGM1iIjINS4FI/n5+TAYDIiPj7c4Hh8fj4MHD1o9Jzs722r67Gzb395nzpyJGTNmuFI0t9zVMwnXtWkAo6huhRC43EYCCHhvXG+Z3ohDOUXollSvVuuLRlNdoquEEFhxIBfXtolDYWkl8oorcE2zq5vB/bb7HHKLylE/MhTA5W4XAEhr3xDdrmwat/9sEVKSonG2oBwN6uqQU1SOTccv4IYO8YiPDkNRWSXaN6qLDo2iEaQB4iJ1KNFXoW6YZevNP7o2lvbNICKigKPKqb2TJ0+2aE0pKipCUlKS5NcZ2bOp5Hl6S8aQtjaf83TRMltqBiJERERScCkYiYuLg1arRU5OjsXxnJwcJCQkWD0nISHBpfQAoNPpoNPpXCkaERER+SiXZtOEhoaie/fuWLVqlemY0WjEqlWrkJqaavWc1NRUi/QAsGLFCpvpiYiIKLC43E2TkZGBMWPGoEePHujVqxfeeecdlJSUYOzYsQCA0aNHo3Hjxpg5cyYAYOLEibjuuuswa9YsDBs2DAsWLMDWrVvx8ccfS/tKiIiIyCe5HIyMHDkSeXl5mDZtGrKzs9G1a1csXbrUNEg1MzMTQUFXG1z69u2Lr7/+GlOmTMHzzz+P1q1bY9GiRejUqZN0r4KIiIh8FpeDJyIiIlnItgIrERERkZQYjBAREZGiGIwQERGRohiMEBERkaIYjBAREZGiGIwQERGRohiMEBERkaIYjBAREZGiVLlrb03V67IVFRUpXBIiIiJyVnW97Wh9VZ8IRoqLiwEASUlJCpeEiIiIXFVcXIzo6Gibz/vEcvBGoxFnz55F3bp1odFoJMu3qKgISUlJOH36NJeZVxjvhTrwPqgH74U68D54RgiB4uJiJCYmWuxbV5NPtIwEBQWhSZMmsuUfFRXFPzKV4L1QB94H9eC9UAfeB/fZaxGpxgGsREREpCgGI0RERKSogA5GdDodpk+fDp1Op3RRAh7vhTrwPqgH74U68D54h08MYCUiIiL/FdAtI0RERKQ8BiNERESkKAYjREREpCgGI0RERKQoBiNERESkqIAORubMmYPk5GSEhYWhd+/e2Lx5s9JF8ml//PEHhg8fjsTERGg0GixatMjieSEEpk2bhkaNGiE8PBxpaWk4cuSIRZoLFy5g1KhRiIqKQkxMDB544AFcunTJIs3u3bsxYMAAhIWFISkpCW+++abcL82nzJw5Ez179kTdunXRsGFD3HrrrTh06JBFmvLycowfPx7169dHZGQk7rjjDuTk5FikyczMxLBhwxAREYGGDRvimWeeQVVVlUWatWvX4pprroFOp0OrVq0wf/58uV+ez/jwww/RpUsX08qdqamp+P33303P8x4o4/XXX4dGo8ETTzxhOsZ7oQIiQC1YsECEhoaKefPmiX379olx48aJmJgYkZOTo3TRfNaSJUvECy+8IH788UcBQPz0008Wz7/++usiOjpaLFq0SOzatUvccsstonnz5qKsrMyU5sYbbxQpKSni77//Fn/++ado1aqVuPvuu03PFxYWivj4eDFq1Cixd+9e8c0334jw8HDx0Ucfeetlql56err4/PPPxd69e8XOnTvFTTfdJJo2bSouXbpkSvPwww+LpKQksWrVKrF161bRp08f0bdvX9PzVVVVolOnTiItLU3s2LFDLFmyRMTFxYnJkyeb0hw/flxERESIjIwMsX//fvHee+8JrVYrli5d6tXXq1a//PKLWLx4sTh8+LA4dOiQeP7550VISIjYu3evEIL3QAmbN28WycnJokuXLmLixImm47wXygvYYKRXr15i/PjxpscGg0EkJiaKmTNnKlgq/1EzGDEajSIhIUG89dZbpmMFBQVCp9OJb775RgghxP79+wUAsWXLFlOa33//XWg0GpGVlSWEEOKDDz4Q9erVExUVFaY0zz33nGjbtq3Mr8h35ebmCgBi3bp1QojL73tISIj47rvvTGkOHDggAIiNGzcKIS4HlkFBQSI7O9uU5sMPPxRRUVGm9/7ZZ58VHTt2tLjWyJEjRXp6utwvyWfVq1dPfPrpp7wHCiguLhatW7cWK1asENddd50pGOG9UIeA7KbR6/XYtm0b0tLSTMeCgoKQlpaGjRs3Klgy/3XixAlkZ2dbvOfR0dHo3bu36T3fuHEjYmJi0KNHD1OatLQ0BAUFYdOmTaY01157LUJDQ01p0tPTcejQIVy8eNFLr8a3FBYWAgBiY2MBANu2bUNlZaXFvWjXrh2aNm1qcS86d+6M+Ph4U5r09HQUFRVh3759pjTmeVSn4b+h2gwGAxYsWICSkhKkpqbyHihg/PjxGDZsWK33i/dCHXxi116p5efnw2AwWPxhAUB8fDwOHjyoUKn8W3Z2NgBYfc+rn8vOzkbDhg0tng8ODkZsbKxFmubNm9fKo/q5evXqyVJ+X2U0GvHEE0+gX79+6NSpE4DL71NoaChiYmIs0ta8F9buVfVz9tIUFRWhrKwM4eHhcrwkn7Jnzx6kpqaivLwckZGR+Omnn9ChQwfs3LmT98CLFixYgO3bt2PLli21nuO/B3UIyGCEKFCMHz8ee/fuxfr165UuSkBq27Ytdu7cicLCQnz//fcYM2YM1q1bp3SxAsrp06cxceJErFixAmFhYUoXh2wIyG6auLg4aLXaWqOlc3JykJCQoFCp/Fv1+2rvPU9ISEBubq7F81VVVbhw4YJFGmt5mF+DLpswYQJ+++03rFmzBk2aNDEdT0hIgF6vR0FBgUX6mvfC0ftsK01UVBS/BV4RGhqKVq1aoXv37pg5cyZSUlLw7rvv8h540bZt25Cbm4trrrkGwcHBCA4Oxrp16/Cf//wHwcHBiI+P571QgYAMRkJDQ9G9e3esWrXKdMxoNGLVqlVITU1VsGT+q3nz5khISLB4z4uKirBp0ybTe56amoqCggJs27bNlGb16tUwGo3o3bu3Kc0ff/yByspKU5oVK1agbdu27KK5QgiBCRMm4KeffsLq1atrdWt1794dISEhFvfi0KFDyMzMtLgXe/bssQgOV6xYgaioKHTo0MGUxjyP6jT8N2Sb0WhERUUF74EXDR48GHv27MHOnTtNPz169MCoUaNMv/NeqIDSI2iVsmDBAqHT6cT8+fPF/v37xUMPPSRiYmIsRkuTa4qLi8WOHTvEjh07BAAxe/ZssWPHDnHq1CkhxOWpvTExMeLnn38Wu3fvFv/4xz+sTu3t1q2b2LRpk1i/fr1o3bq1xdTegoICER8fL+69916xd+9esWDBAhEREcGpvWYeeeQRER0dLdauXSvOnTtn+iktLTWlefjhh0XTpk3F6tWrxdatW0VqaqpITU01PV89lXHIkCFi586dYunSpaJBgwZWpzI+88wz4sCBA2LOnDmcymhm0qRJYt26deLEiRNi9+7dYtKkSUKj0Yjly5cLIXgPlGQ+m0YI3gs1CNhgRAgh3nvvPdG0aVMRGhoqevXqJf7++2+li+TT1qxZIwDU+hkzZowQ4vL03qlTp4r4+Hih0+nE4MGDxaFDhyzyOH/+vLj77rtFZGSkiIqKEmPHjhXFxcUWaXbt2iX69+8vdDqdaNy4sXj99de99RJ9grV7AEB8/vnnpjRlZWXi0UcfFfXq1RMRERHitttuE+fOnbPI5+TJk2Lo0KEiPDxcxMXFiaeeekpUVlZapFmzZo3o2rWrCA0NFS1atLC4RqC7//77RbNmzURoaKho0KCBGDx4sCkQEYL3QEk1gxHeC+VphBBCmTYZIiIiogAdM0JERETqwWCEiIiIFMVghIiIiBTFYISIiIgUxWCEiIiIFMVghIiIiBTFYISIiIgUxWCEiIiIFMVghIiIiBTFYISIiIgUxWCEiIiIFPX/D73fMBS0aqcAAAAASUVORK5CYII="
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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11mkVCYurqyuAWzdc3/blREREJB+FhYUICgqSvsfr0yoSluphIDc3NyYsRERELUxjpnNw0i0RERHJHhMWIiIikj0mLERERCR7rWIOS2MIIVBVVQWdTmfvUKxCpVLBwcGBy7qJiKhVahMJS0VFBa5evYrS0lJ7h2JVLi4uCAgIgFqttncoREREFtXqExa9Xo+srCyoVCoEBgZCrVa3ul4IIQQqKipw7do1ZGVloUePHg1uwENERNSSmPWtlpiYiLvuuguurq7w9fXF+PHjkZmZ2eB5GzduRK9eveDk5IQ777wTP/zwg8FxIQQSEhIQEBAAZ2dnREVF4fTp0+bdiQkVFRXQ6/UIDAyEu7s7nJ2d4eTk1Kpezs7OcHd3R2BgIPR6PSoqKizyuyMiIpILsxKWHTt2YObMmdizZw9SU1NRWVmJUaNGoaSkxOQ5u3fvxuTJk/HUU0/h8OHDGD9+PMaPH4/jx49LdRYvXoz3338fSUlJ2Lt3L9q1a4fo6GiUlZU1/c5qaQs9Dm3hHomIqG1SCCFEU0++du0afH19sWPHDgwfPtxonYkTJ6KkpATff/+9VHb33XcjPDwcSUlJEEIgMDAQL774Il566SUAQEFBAfz8/JCcnIxJkybVabO8vBzl5eXS++qd8goKCupsHFdWVoasrCyEhITAycmpqbfaIrSleyUiopavsLAQ7u7uRr+/a2vWP8kLCgoAAF5eXibrZGRkICoqyqAsOjoaGRkZAICsrCxotVqDOu7u7oiIiJDq1JaYmAh3d3fpxecIERERtW5NTlj0ej3mzJmDe+65B3379jVZT6vVws/Pz6DMz88PWq1WOl5dZqpObfHx8SgoKJBeFy9ebOptEBERUQvQ5IRl5syZOH78ONavX2/JeBpFo9FIzw1qC88PWrlyJYKDg+Hk5ISIiAjs27fP3iERERHZVJMSllmzZuH777/H9u3bG3wctL+/P3JycgzKcnJy4O/vLx2vLjNVpy3bsGED4uLiMG/ePBw6dAhhYWGIjo5Gbm6uvUMjIqJW5ExuMT7aeQ5llfLcYNWshEUIgVmzZuGbb77Btm3bEBIS0uA5kZGRSEtLMyhLTU1FZGQkACAkJAT+/v4GdQoLC7F3716pjqUJIVBaUWWXl7lznJcsWYLp06cjNjYWvXv3RlJSElxcXLB69Wqr/G6IiKhtilqyA//3w69Yvs0y24pYmlkbx82cORNr167Ft99+C1dXV2mOSfX+JgAwdepUdOzYEYmJiQCA2bNn495778V7772HsWPHYv369Thw4AA+/PBDALceKT1nzhy8/fbb6NGjB0JCQvDGG28gMDAQ48ePt+Ct3nazUofeCT9ape2GnHwzGi7qxv3aKyoqcPDgQcTHx0tlSqUSUVFRJickExERNcehC/n2DsEosxKWVatWAQBGjBhhUL5mzRpMmzYNAJCdnW2wH8iQIUOwdu1avP7663j11VfRo0cPbNq0yWCi7ty5c1FSUoIZM2YgPz8fQ4cORUpKSptfmpuXlwedTmd0QvKpU6fsFBUREZHtmZWwNGY4Iz09vU7ZhAkTMGHCBJPnKBQKvPnmm3jzzTfNCafJnB1VOPlmtE2uZezaREREZJ5W/ywhYxQKRaOHZezJ29sbKpWKE5KJiMhmBJq8n6xVcS93GVOr1Rg4cKDBhGS9Xo+0tDSrTUgmIqK2ren731uX/LsZ2ri4uDjExMRg0KBBGDx4MJYuXYqSkhLExsbaOzQiIiKbYcIicxMnTsS1a9eQkJAArVaL8PBwpKSk1JmIS0REZAky7WBhwtISzJo1C7NmzbJ3GERERHbDOSxERER0m0y7WJiwEBERkewxYSEiIiLZY8JCREREEu7DYmfmPnSwJWoL90hERJZX8/ujvEpvx0hMa/UJi6OjIwCgtLTUzpFYX/U9Vt8zERFRY1Tobicpl2/ctGMkprX6Zc0qlQoeHh7Izc0FALi4uEChUNg5KssSQqC0tBS5ubnw8PCASsXnFRERUePpa3SqKJXy/I5s9QkLAOm5O9VJS2vl4eHBZwwREZHZNuzPln5WyfQf9W0iYVEoFAgICICvry8qKyvtHY5VODo6smeFiIiaZP53J6WfZdrB0jYSlmoqlYpf6kRERP+z99x13CitsHcYjdKmEhYiIiK6beKHe+qU6WW64LTVrxIiIiKixtPJdIsMJixEREQk0cu0i4UJCxEREUn07GEhIiIiuZNpBwsTFiIiIrqNPSxEREQke5zDQkRERLIn03yFCQsRERHdxiEhIiIikj0mLERERCR7HBIiIiIi2cgrLjdazh4WIiIiko0D5383Wi7TfIUJCxERUVsk18TEFCYsREREbVALy1eYsBAREbVFcp2rYorZCcvOnTsxbtw4BAYGQqFQYNOmTfXWnzZtGhQKRZ1Xnz59pDrz58+vc7xXr15m3wwRERE1TgvLV8xPWEpKShAWFoaVK1c2qv6yZctw9epV6XXx4kV4eXlhwoQJBvX69OljUG/Xrl3mhkZERESN1NJ6WBzMPWHMmDEYM2ZMo+u7u7vD3d1der9p0ybcuHEDsbGxhoE4OMDf39/ccIiIiKgNsPkclo8//hhRUVHo0qWLQfnp06cRGBiIrl27YsqUKcjOzjbZRnl5OQoLCw1eREREZFxpRRWuF5djzc9ZOHGlAEDLGxIyu4elOa5cuYItW7Zg7dq1BuURERFITk5GaGgorl69igULFmDYsGE4fvw4XF1d67STmJiIBQsW2CpsIiKiFi1swVZU6m5nKOcXjoVoYeuEbNrD8sknn8DDwwPjx483KB8zZgwmTJiAfv36ITo6Gj/88APy8/PxxRdfGG0nPj4eBQUF0uvixYs2iJ6IiKhlqpmsVCut0NkhkqazWQ+LEAKrV6/GE088AbVaXW9dDw8P9OzZE2fOnDF6XKPRQKPRWCNMIiKiVq+wrBKvfXPc6LFJdwXZOJrGsVkPy44dO3DmzBk89dRTDdYtLi7G2bNnERAQYIPIiIiIWq/corI6ZU8nHzBZv53GprNFGs3shKW4uBhHjhzBkSNHAABZWVk4cuSINEk2Pj4eU6dOrXPexx9/jIiICPTt27fOsZdeegk7duzA+fPnsXv3bjzyyCNQqVSYPHmyueERERFRDZ/sPl+nbJ+J5wgB8p2Ma3YadeDAAYwcOVJ6HxcXBwCIiYlBcnIyrl69WmeFT0FBAb766issW7bMaJuXLl3C5MmTcf36dfj4+GDo0KHYs2cPfHx8zA2PiIiIanBUmdc3IdfJuGYnLCNGjICoJ/1KTk6uU+bu7o7S0lKT56xfv97cMIiIiKgRzE5Y5Jmv8FlCRERErZmjSmHvECyCCQsREVErZn4Pizy7WJiwEBERtWL+bk5m1dfLM19hwkJERNSaOTmqzKov10m3TFiIiIhIItMRISYsRERErZm5PSYyzVeYsBAREbVm5vaYsIeFiIiIbM78BESeGQsTFiIiolbM3PSDPSxERERkc+buq8KEhYiIiGzulLbIrPp6mWYsTFiIiIhasSWpv5lVX57pChMWIiIiqkGmHSxMWIiIiForfRP22RdCYMdv13DsUoEVImo6B3sHQERERJZXXqVD6OspZp/39eHL+PrwZQBA5tujoXEwb2t/a2EPCxERUSvz85m8JiUrtZVX6S0QjWUwYSEiImplpvxrr0XaUVikFctgwkJERERGKRTySVmYsBAREZHsMWEhIiIio+TTv8KEhYiIiEyQ0YgQExYiIqKWRgiBD3acRXpmrlWvo5BRHwv3YSEiImphfj5zHYlbTgEAzi8ca+dobIM9LERERC3M37dm2jsEm2PCQkRE1MIcuZhvk+sIGT0KkQkLERERyR4TFiIiohYkp7CsTtm+rN8x/dMDuHSj1A4R2QYn3RIREbUgxeVVdcoe/yADAFB4sxIb/hJpsWsJ+YwIsYeFiIioJalvofGVgps2i8PWmLAQERG1IDLq9LApJixERESthKU3epNTcsSEhYiIqAWpLyWR01b6lmZ2wrJz506MGzcOgYGBUCgU2LRpU73109PToVAo6ry0Wq1BvZUrVyI4OBhOTk6IiIjAvn37zA2NiIioVcstqrtCqKZWnK+Yn7CUlJQgLCwMK1euNOu8zMxMXL16VXr5+vpKxzZs2IC4uDjMmzcPhw4dQlhYGKKjo5Gba91nJBAREbUUH+w4i8H/l4ZV6WdN1lGY2cWybFJ4M6OyHbOXNY8ZMwZjxowx+0K+vr7w8PAwemzJkiWYPn06YmNjAQBJSUnYvHkzVq9ejVdeeaVO/fLycpSXl0vvCwsLzY6HiIioJal+dtDGg5dM1jG3h0WlrP8MIaN1zTabwxIeHo6AgAA88MAD+Pnnn6XyiooKHDx4EFFRUbeDUioRFRWFjIwMo20lJibC3d1degUFBVk9fiIiopZg7pe/2DsEq7B6whIQEICkpCR89dVX+OqrrxAUFIQRI0bg0KFDAIC8vDzodDr4+fkZnOfn51dnnku1+Ph4FBQUSK+LFy9a+zaIiIhk6WrNvVcUwBcHTPfA1GbpVUXWZPWdbkNDQxEaGiq9HzJkCM6ePYt//OMf+Oyzz5rUpkajgUajsVSIRERELdaUf+2VfjYn/VjyeFiDdeQzIGSnZc2DBw/GmTNnAADe3t5QqVTIyckxqJOTkwN/f397hEdERNRinLtW0qTznBxVFo7EuuySsBw5cgQBAQEAALVajYEDByItLU06rtfrkZaWhshIyz0PgYiIqLVTmrFKSIiWtW+L2UNCxcXFUu8IAGRlZeHIkSPw8vJC586dER8fj8uXL+PTTz8FACxduhQhISHo06cPysrK8K9//Qvbtm3D1q1bpTbi4uIQExODQYMGYfDgwVi6dClKSkqkVUNERETUsNO5xY2ue0eAK05pi6T3Q7t7Y9eZPIM6MlokZH7CcuDAAYwcOVJ6HxcXBwCIiYlBcnIyrl69iuzsbOl4RUUFXnzxRVy+fBkuLi7o168ffvrpJ4M2Jk6ciGvXriEhIQFarRbh4eFISUmpMxGXiIioLSqtqPuE5uZ44u4u6OrT3iBh8W6vtug1LM3shGXEiBH1rstOTk42eD937lzMnTu3wXZnzZqFWbNmmRsOERFRq1elt2xXR3iQBwDDSboOKnk/rUfe0REREZFNFh+rjE1okdGQEBMWIiIiglLmGYHMwyMiIiJrqdmpYu5ziGyNCQsREZHMWXgKi1ENPFbI7piwEBERyZ0NEhZjc1hOXpXPw4WZsBAREcmc3sIbotzOTRQ1yuomLJM/2mPR6zYHExYiIiKZs8ViHXN2ybUHJixEREQyV6XXW/0anMNCRERETSaEwIPLdlml7ZqdKkqZZyxMWIiIiGTmTG4RJiTtxq7TeSiv0iOvuNzq15T5iBATFiIiIrl59vND2H/+Bv788V6rtN8n0L1OGeewEBERkVms3aMS6u8KwHDLfycHlVWv2VxMWIiIiOzgdE4Rvj96pd4HCtvSgC4e9g6hXmY/rZmIiIia74F/7AQAtI91wIhQX5P1vvvlik3i4ZAQERERmXT8ckG9x1/+8mizr+HVTm20XO7PD6qJCQsREVErN6iLZ4N1jl8uwNqnI/D8fd1tEJH5mLAQERHJiBACN0orLd6uqoF9Vqr0AkO6e+PFUaEWv7YlMGEhIiKSkbc3/2qVdo2lKy1nQIgJCxERkV3Vnkfy8a4su8Qhl9VKpjBhISIisqKcwjJZJAMeLsYn3laTQYj1YsJCRERkJZsOX0bEO2l4fdNxe4eC5Ni7cGdHd3z+VIRUVrNzR8+EhYiIqG1anHIKAPDvvdl2jgTo29Ed3z0/FEN7eBs9LiDvjIUJCxERkZXIOwUw5O7saO8Q6sWEhYiIyErMnRdyKPuGdQIxoeaQ0Ng7A2x6bXMxYSEiIrISvZkZy6P/3G2lSIyrGZ6ygX1a7I0JCxEREcl+TxYmLERERFZSu39Frxf49WohSiuqbHJ9PzcNACC6j3+DdeX+XCE+rZmIiMhKao8ILU07jffTTtvs+imzh+Pk1UJEdu1g9Ljc916piQkLERGR1RhmBLZMVgDAs50a93Q3voy5Nnn3r3BIiIiIyGrk3oNRVWO3OJmPCDFhISIishaZ5ytIPZlj7xAazeyEZefOnRg3bhwCAwOhUCiwadOmeut//fXXeOCBB+Dj4wM3NzdERkbixx9/NKgzf/58KBQKg1evXr3MDY2IiMiuaj8zqLHPEFq45RT+88sVa4RUr7IqnfSzQuaDQmYnLCUlJQgLC8PKlSsbVX/nzp144IEH8MMPP+DgwYMYOXIkxo0bh8OHDxvU69OnD65evSq9du3aZW5oREREdlNWqcP97+1A3IYjUlntdMXYsMuOzGtI2nEWf113uO5Ba6sZoLzzFfMn3Y4ZMwZjxoxpdP2lS5cavH/nnXfw7bff4rvvvkP//v1vB+LgAH//hpddERERydG2U7k4l1eCc3klCPV3xYzhXRs1hyWvuNz6wZmgk/sTD2uw+RwWvV6PoqIieHl5GZSfPn0agYGB6Nq1K6ZMmYLsbNMPiiovL0dhYaHBi4iISC4St5zCztN5dYaEjHVimLsbriXVfOAhJ93W8ve//x3FxcV4/PHHpbKIiAgkJycjJSUFq1atQlZWFoYNG4aioiKjbSQmJsLd3V16BQUF2Sp8IiKiRrmSfxOFZYYbxBnbnE0unRwyz1dsm7CsXbsWCxYswBdffAFfX1+pfMyYMZgwYQL69euH6Oho/PDDD8jPz8cXX3xhtJ34+HgUFBRIr4sXL9rqFoiIiCxK2HEtkVySpcaw2cZx69evx9NPP42NGzciKiqq3roeHh7o2bMnzpw5Y/S4RqOBRqOxRphEREQWYazHwlhZU0aEPF0ccaO0st46vq4Nf0/WHLKS+9b8NulhWbduHWJjY7Fu3TqMHTu2wfrFxcU4e/YsAgLk/ahrIiKiao35ujeWEzQlYfn303c3WOf7vw5tsE7Na8s7XWlCD0txcbFBz0dWVhaOHDkCLy8vdO7cGfHx8bh8+TI+/fRTALeGgWJiYrBs2TJERERAq9UCAJydneHu7g4AeOmllzBu3Dh06dIFV65cwbx586BSqTB58mRL3CMREZFsmTvpdvb9PdDdt32D9XxdnSx+bXsyu4flwIED6N+/v7QkOS4uDv3790dCQgIA4OrVqwYrfD788ENUVVVh5syZCAgIkF6zZ8+W6ly6dAmTJ09GaGgoHn/8cXTo0AF79uyBj49Pc++PiIjIJmr3nvyWU1y3jpF+DHvmDK5OjtLPMh8RMr+HZcSIEfXu3JecnGzwPj09vcE2169fb24YREREsrb656y6hUaSAnN7OTp6OFssuZh2T7C0w67cd7rl05qJiIgsov4vfL2JJTnmdrA8OqCjmWeY1k7dctKAlhMpERFRC6YXwiKrhBxUynp3qO3s5YKIEC+Tx2uq2VPT6oaEiIiIyHw6IUysErLcJJbUF4aju2972S9Rbgqb73RLRETUGjWUI+j1QFmlvm55ExIWU5fq4edq8WTFkglVczBhISIisoCG0gRTiUlT0gFjOUnKnGHmt9NAm4B8dsNlwkJERNRMBaWVeH7d4Xrr6EwkLKYm45qrl79bs843tUqIPSxEREStxOIfT6G8qu5wT02mEpPaD0hsDEsN+zSmGXmkK0xYiIiImu1K/s0G68hlaMUUU8mLTDpYmLAQERHZQn1LkeXAVGeLPZ8mXRMTFiIiombSNeI7vVJX/5CRMT3qeWbQB08MNLu9uhoeE2IPCxERUSux87drDdZJ3n3e7HaVtcZpxocHmjzWXKbmxTBhISIiakP+c+SK2ee0dzLc33XxH8Okn625NdzkwZ2lnzkkRERERPWKe6CnwXu1w+2vbUt0sPi5aW63V6M84aHe0s9y6WHh1vxEREQy5dVObfKYJRIWVydHpL4wHI4qJZTK2w3WbFsm+Qp7WIiIiJrj5zN5jaqnLSxrVL3oPn6Nqmdqozdz9fBzRbB3O5PHuXEcERFRKzDlX3st2p6rk6NF22uKmhN65bIamwkLERFRI5y9VoxFKadwo6TCqtdRGSQLt7OFf0wMM6xoxVm3BsNNMklYOIeFiIioAV8cuIi5Xx4FAGRdK0GSRfZAMU5Zoyuh5mjMI/07GdSz5iohw3xFHhkLe1iIiIgaUJ2sAMDhizeseq2a+6F0920PpQLwbq+pt541YxACOH65AEVllVa7XmOwh4WIiMgMlt6wrbaarTs5qnBiwWg4qOpe01Y9LP/eewF/3/ob3JwccHR+tBWvWj8mLERERGawesJSq3lntapR9awVw9+3/gagaU+VtiQOCREREclIY5crW2pZs9G2rZyUNQUTFiIiIjMIIay6N4lK2ciExco5hdxyFiYsREREZrhSUIbIxG1I/jnLKu3X3H7fnmSyX5yEc1iIiIjMpC0sw/zvTqKHn6vF23Y0MsGW2MNCRETUZJbe5RYAXNSN60vQy60LxMrYw0JERCQjw3v4YG/W77jDv/7eG51c9sy3ESYsREREMqJSKvDpk4MbrNfWelg4JERERCQjykZ+M+v11o1DbpiwEBERyUhj91fRsYeFiIiIqmkLymx6vcbuf2LNvWDkiAkLERGRCdeLy3F3YprF2x3Q2cPkscYuatZxSKh+O3fuxLhx4xAYGAiFQoFNmzY1eE56ejoGDBgAjUaD7t27Izk5uU6dlStXIjg4GE5OToiIiMC+ffvMDY2IiMiiVqWftUq7Xz93j8ljje1h4ZBQA0pKShAWFoaVK1c2qn5WVhbGjh2LkSNH4siRI5gzZw6efvpp/Pjjj1KdDRs2IC4uDvPmzcOhQ4cQFhaG6Oho5ObmmhseERGRxVTZYemwd3tNo+rpa8T2cHigtcKRDbOXNY8ZMwZjxoxpdP2kpCSEhITgvffeAwDccccd2LVrF/7xj38gOvrWY6qXLFmC6dOnIzY2Vjpn8+bNWL16NV555ZU6bZaXl6O8vFx6X1hYaO5tEBERNaipT2b+KW44opbsNPu8r58bAg8XdaPq1tyHZdFj/cy+Vktj9TksGRkZiIqKMiiLjo5GRkYGAKCiogIHDx40qKNUKhEVFSXVqS0xMRHu7u7SKygoyHo3QEREbVZTHwDY3dcVHi6OAAAXtapR54y9MwADOns2+ho192FxcmzcNVoyqycsWq0Wfn5+BmV+fn4oLCzEzZs3kZeXB51OZ7SOVqs12mZ8fDwKCgqk18WLF60WPxERtU25RWX4eFfTH3C4c+5IpMwZhtIKXaPqOzcysanW1jaOa5E73Wo0Gmg0jRvjIyIiaooPd5xr1vluTo5w83dsdH2NmU9pbmM781s/YfH390dOTo5BWU5ODtzc3ODs7AyVSgWVSmW0jr+/v7XDIyIikoU5UT3Nqq9sYw91tvqQUGRkJNLSDNewp6amIjIyEgCgVqsxcOBAgzp6vR5paWlSHSIiIltr6vyVpgjxbgcfV/NGDv4Q1hF3BLhh+rAQK0UlL2b3sBQXF+PMmTPS+6ysLBw5cgReXl7o3Lkz4uPjcfnyZXz66acAgGeeeQYrVqzA3Llz8eSTT2Lbtm344osvsHnzZqmNuLg4xMTEYNCgQRg8eDCWLl2KkpISadUQERFRa2Fs2XJTekuc1SpsmT3MAhG1DGYnLAcOHMDIkSOl93FxcQCAmJgYJCcn4+rVq8jOzpaOh4SEYPPmzXjhhRewbNkydOrUCf/617+kJc0AMHHiRFy7dg0JCQnQarUIDw9HSkpKnYm4REREtqKwUhfLV8/WHT1o6vJpWxoXZt+9XsxOWEaMGFHv8wuM7WI7YsQIHD58uN52Z82ahVmzZpkbDhERkVUUlVVapd0uHdrVKZNjwnJvTx/s+O2a9L69xr5Lp/ksISIiIiPW7bPMlhmN2YVWhvkKovsYLnyx9ypqJixERERWpFY1/FUrxx4WbcFNe4dggAkLERGRFcXe0/AqnpNX5feImdpzeOzdw9IiN44jIiKSI1cnByQ81NugzNu1cc8GkpvavT4C9s1YmLAQERFZyC8Jo6CstUZZjsM9jVF7JEsB+94Hh4SIiIgspHayArTchKX2kJCxe7MlJixERERWpGqhCYuqVoLSiLnDVsWEhYiIyIoULfSbtnaHir17ilror5GIiKhlsPcXfVPVjtve98GEhYiIyIpqDgnZe3t7c9ROUMx9OKOlMWEhIiKqpdCC2/LX/N5/8p5gi7VrbbWHhJ5sxH4y1sSEhYiIqBadznJ7jtTsqbDz3mtmqb0qyFnNZwkRERHJiiUTi9qrbahpmLAQERHVIiy4D33NfMXe29ubo2aaFdzBxW5xVGPCQkREVEtWXonF2qq5AZslEyFbclHbf2N8JixERES1/DEpw+rXmDWyu/RzV592Vr9ec8hhZTYTFiIiIhup2b/Sof3thyLKIB+oSw5ZSg1MWIiIiGykZgrwp4jOdoujJbL/oBQREVEr99iATrhwvQT9O3tKZRoH+y4Tboi8+leYsBARETXKsyO6YVX62Sad+97jYUbLXTUOKCqvwpBu3s0JzerkMDrEhIWIiKgRuvm0t3ibP8wehtSTOZg0OMjibbc2nMNCRETUCOPDAzFtSLBF2wzycsGTQ0NksWy4PgoZDBAxYSEiImoEB5US8//Qx95h2EzNYSA5DAkxYSEiImqGyK4dAABhndztHEnrJu8+KCIiIhsSQhjsTNsYK/7UH18duoRH+neyUlQEMGEhIiICABSXV2Hs+/+Fu7OjWed1aK/BjOHdrBSV/chh3kpNTFiIiIgAfJZxAReulxo9FuDuZONo5EUOqQsTFiIiavOEEFiUcsrosTlRPfDYgLY33COHibY1MWEhIqI275S2yOSxOVE9bRgJmcJVQkRE1OZVVOkbXTcmsosVI5EPgw4WGXS3MGEhIqI2TzRcRTJvXB8MDvGyWixyUfN30s2nnd3iqNakhGXlypUIDg6Gk5MTIiIisG/fPpN1R4wYAYVCUec1duxYqc60adPqHB89enRTQiMiIjKbEMZTlkAjk22VSgV6+btaOyRZSXiot71DMH8Oy4YNGxAXF4ekpCRERERg6dKliI6ORmZmJnx9fevU//rrr1FRUSG9v379OsLCwjBhwgSDeqNHj8aaNWuk9xqNxtzQiIiImsRUD8vyPw2waRxyUnMQyMNFbbc4qpndw7JkyRJMnz4dsbGx6N27N5KSkuDi4oLVq1cbre/l5QV/f3/plZqaChcXlzoJi0ajMajn6elptD0iIiJLM9XDMqCzh20DIZPMSlgqKipw8OBBREVF3W5AqURUVBQyMjIa1cbHH3+MSZMmoV07w/Gw9PR0+Pr6IjQ0FM8++yyuX79uso3y8nIUFhYavIiIiJrKRL5i9q63rYncbt2shCUvLw86nQ5+fn4G5X5+ftBqtQ2ev2/fPhw/fhxPP/20Qfno0aPx6aefIi0tDYsWLcKOHTswZswY6HQ6o+0kJibC3d1degUF8bHcRETUdOeuldg7BGqATfdh+fjjj3HnnXdi8ODBBuWTJk2Sfr7zzjvRr18/dOvWDenp6bj//vvrtBMfH4+4uDjpfWFhIZMWIiJqsrlfHTWrft+Orf9Bhy16a35vb2+oVCrk5OQYlOfk5MDf37/ec0tKSrB+/Xq8+eabDV6na9eu8Pb2xpkzZ4wmLBqNhpNyiYjIIkzNX6nPHwd0QnmVHoO6cL6lrZg1JKRWqzFw4ECkpaVJZXq9HmlpaYiMjKz33I0bN6K8vBx//vOfG7zOpUuXcP36dQQEBJgTHhERkVkuXC9BSPwPZp+nVCrwxN1dcEeAmxWiImPMXiUUFxeHjz76CJ988gl+/fVXPPvssygpKUFsbCwAYOrUqYiPj69z3scff4zx48ejQ4cOBuXFxcV4+eWXsWfPHpw/fx5paWl4+OGH0b17d0RHRzfxtoiIiBr2ZPJ+e4dAjWT2HJaJEyfi2rVrSEhIgFarRXh4OFJSUqSJuNnZ2VAqDfOgzMxM7Nq1C1u3bq3TnkqlwtGjR/HJJ58gPz8fgYGBGDVqFN566y0O+xARkVUVlVXZOwRqpCZNup01axZmzZpl9Fh6enqdstDQUJNjhM7Ozvjxxx+bEgYREVGzVOnNn7/SZshrzi2fJURERG1Xpa7xDz0k+2LCQkREbRYTFtNk1sHChIWIiNquKh2HhFoKJixERNRm1TeHxdPF0YaRyI/cHkvAhIWIiNqkvOLyeo8feP0BG0UiT06O8koRbLo1PxERkVw0NH9FpZRXD4OtRffxx4hQHwzoLI/dfJmwEBERUR2OKiWSYwc3XNFG5NXfQ0REZCNNeIQQ2RETFiIiapP0zFhaFA4JERFRm6QzsULooX4BCPFuZ+NoqCFMWIiIqE36995so+Ur/jTAxpFQY3BIiIiI2qQPd56zdwhkBiYsREREJHtMWIiIiP4n0N3J3iGQCUxYiIiozSksqzRaLrft6Ok2JixERNTmLPjPSaPlSn4ryhY/GiIikq2ySh2OXy6AsPCeKV8fvmS0XAH2sMgVExYiIpKt2DX78dDyXdiw/6LF2vzulysmd7lt688PkjMmLEREJFsZ564DAD7fe8Fiba5KP2vyGKewyBcTFiIikj2lBTMJF7XKJtchy2LCQkREsmfJNMJRZfqr74Wonha8ElkSExYiIrK7Peeu43xeCQBACAF9ref8WGq58Xe/XJGGmYy5r5evRa5DlsdnCRERkV2dvVaMSR/uAQD8d+5IDFu8HQCw7cV7pTqWGql5ft3heo9zREi+2MNCRER2lXWtRPp56U+npZ/ve2+H9LMl5pbU7rUxhgmLfDFhISIiuxFCoKSiSnpvcgdaC1yrqjEJC/dhkS0OCRERkd3MWnsYm49dld6nnswxWs8SPR/6Rmw+x21Y5Is9LEREZDc1k5X6NHfS7deHLuGxVbuNHhvYxdNi1yHrYQ8LERHJnragrFnnx33xi8ljNXtV2MMiX+xhISIi2cv+vdRqbXu1U0s/s4dFvtjDQkREbZp3ew0+fGIgXNT8SpQzfjpERNSmKRUKjOrjb+8wqAEcEiIiohYhU1vUqHo6vcCj//wZz3x2sFH1OQrUMjQpYVm5ciWCg4Ph5OSEiIgI7Nu3z2Td5ORkKBQKg5eTk5NBHSEEEhISEBAQAGdnZ0RFReH06dMmWiQiorYo/uujjaqXqS3Coex8pJzQQgiBGyUVVo6MbMHshGXDhg2Ii4vDvHnzcOjQIYSFhSE6Ohq5ubkmz3Fzc8PVq1el14ULho8JX7x4Md5//30kJSVh7969aNeuHaKjo1FW1rxZ4UREJF8VVXqz6jdm4zfAsMdEL4Cblbp66/MJzS2D2QnLkiVLMH36dMTGxqJ3795ISkqCi4sLVq9ebfIchUIBf39/6eXn5ycdE0Jg6dKleP311/Hwww+jX79++PTTT3HlyhVs2rTJaHvl5eUoLCw0eBERUcuyKv2sWfV19SQs207l4NOM8wAAVY21yVV6vcF7YzrUWCVE8mVWwlJRUYGDBw8iKirqdgNKJaKiopCRkWHyvOLiYnTp0gVBQUF4+OGHceLECelYVlYWtFqtQZvu7u6IiIgw2WZiYiLc3d2lV1BQkDm3QUREMrDpyGWz6teXsDyZfAAJ355A8CubMeofO6Xysgp9g3NUYoeGmBUH2YdZCUteXh50Op1BDwkA+Pn5QavVGj0nNDQUq1evxrfffovPP/8cer0eQ4YMwaVLlwBAOs+cNuPj41FQUCC9Ll68aM5tEBGRDDiqzBuKaeyQUE1/TNqNwf+XVm+d9houmG0JrP4pRUZGIjIyUno/ZMgQ3HHHHfjggw/w1ltvNalNjUYDjUZjqRCJiMgO6usxMcbU05ZFPc8IOp1bbNY1SL7M6mHx9vaGSqVCTo7hw6lycnLg79+4NeyOjo7o378/zpw5AwDSec1pk4iIWp6z10rMqq8zkZhU6MybvEstk1kJi1qtxsCBA5GWdrt7Ta/XIy0tzaAXpT46nQ7Hjh1DQEAAACAkJAT+/v4GbRYWFmLv3r2NbpOIiFqWgtJKs8+5cN349vzmrjaq6cl7OH+lpTB7SCguLg4xMTEYNGgQBg8ejKVLl6KkpASxsbEAgKlTp6Jjx45ITEwEALz55pu4++670b17d+Tn5+Pdd9/FhQsX8PTTTwO4tYJozpw5ePvtt9GjRw+EhITgjTfeQGBgIMaPH2+5OyUiItkw1VvSECEEFAoFdHqB5N3nMTjYC4EeTg2faETUHb5IGNe7SeeS7ZmdsEycOBHXrl1DQkICtFotwsPDkZKSIk2azc7OhlJ5u+Pmxo0bmD59OrRaLTw9PTFw4EDs3r0bvXvf/ksyd+5clJSUYMaMGcjPz8fQoUORkpJSZ4M5IiJq226UVsKrnRpfHbyEt74/CQCYMbyrWW389f4eAIBpQ4ItHR5ZkULUN1uphSgsLIS7uzsKCgrg5uZm73CIiKgBxy8X4KHlu4we++CJgXj284MwNsd258sj0bmDC+Z9exyfZFyoW6ERFv+xHx4fxO0w5MCc728+S4iIiGziTG4R/vTRHuzL+h2PrdptcGxkqI/0c3Qff4T6G//ymrZmH3IKy5qcrAD1ryoi+WLCQkRENjHj04PYffY6Hv8gA+W1Jsp6uBjuNrviT/2NtnEurwRPf3KgWXE0YTsXkgEmLEREZBPaQtPPh6v9PJ9uPu0R3MHFaN1jlwuaFYeePSwtEhMWIiKyidIK0w8hVBn5Niqpp35z8NlBLRMTFiIisroL1+vfJM7YE5NnjuhmlVhG9eampC0RH6BARERWtf1ULmKT99dbx9FIF0vMkGAM6e6N4A7t0PP1LRaJpZOnM5QNPL2Z5Ik9LEREZFWf7Wl4Rc/z93VHoLsTZv9vjxTg1saiPf1coXaw3FfVxme4g3pLxR4WIiKyqsb0Z/i6OeHnV+6DwsjQUFM9PqgTvjhwSXof6O6EAHdni7VPtsUeFiIisqqGkhBHlaJR9czVr5MHuvm0a3QcJG9MWIiIyKoamjKyfoZ1hmk8XByx4k8DpPfMV1o2DgkREZFVNZQoDOjs0exrDOnWAbvPXgcAvD72DpzOKcaYvgFQ1ciWmLC0bExYiIjIqowtWa627cV7LTJU89b4vnByVKG92gHuLo4GxyYM7ISNBy9h9v09m30dsh8mLEREZFX1JSxdfdo3qo2oO/zw0685Jo9rHJTo6GF8Qu2ix/phdlQPdPI0vnMutQycw0JERFZVWlHV7DaGdu9Q7/EO7TQmjymVCiYrrQATFiIisqrtmdea3YaLuv4BAWe1qtnXIHljwkJERLL3cP/AOmV/CAvEnyI646e44XaIiGyNc1iIiMhqfrmYb5F2NA51e1B2n72OA69HWaR9kj/2sBARkdUs+O6EvUOgVoIJCxERWUWVTo9D2fkmjyf9eWCz2vdur27W+dSyMGEhIiKr+Obw5XqPj+7r36z233n0zmadTy0LExYiIrKKdfuyrdb2osfuxIDOnlZrn+SHCQsREVlURZUev5dUGB0O6ubTDmoHJVZPG2R2u78kjEKXDi7o7tse4/t3tECk1JJwlRAREVnUY6t249jlAqPHvnp2CNprHOCgMv/fy+4ujtjx8kgIIfjk5TaICQsREVlMlU5vMlk5+86DBg8jbComK20Th4SIiMhiSsp1Jo9ZIlmhtosJCxERWcz2zFx7h0CtFBMWIiKymDkbjtg7BGqlmLAQEZFFVOn0Jo8lPNTbhpFQa8SEhYiILCLj3HWTx/4U0dmGkVBrxISFiIgs4uWNR00ec2zCMmaimvg3iIiImuXYpQIMSUyDtrDMZB2uEKLmalLCsnLlSgQHB8PJyQkRERHYt2+fybofffQRhg0bBk9PT3h6eiIqKqpO/WnTpkGhUBi8Ro8e3ZTQiIjIxsat2IUrBaaTFSJLMDth2bBhA+Li4jBv3jwcOnQIYWFhiI6ORm6u8aVs6enpmDx5MrZv346MjAwEBQVh1KhRuHzZ8KFYo0ePxtWrV6XXunXrmnZHRERkMwcv3GiwTk+/9jaIhFo7hRBCmHNCREQE7rrrLqxYsQIAoNfrERQUhOeffx6vvPJKg+frdDp4enpixYoVmDp1KoBbPSz5+fnYtGmT+XcAoLCwEO7u7igoKICbm1uT2iAiIvMt2ZqJ97edMXk8K/FB7kxLJpnz/W3W1vwVFRU4ePAg4uPjpTKlUomoqChkZGQ0qo3S0lJUVlbCy8vLoDw9PR2+vr7w9PTEfffdh7fffhsdOnQw2kZ5eTnKy8ul94WFhebcBhERNdOV/JvI/r3UaLLycHgglAoFHujtx2SFLMashCUvLw86nQ5+fn4G5X5+fjh16lSj2vjb3/6GwMBAREVFSWWjR4/Go48+ipCQEJw9exavvvoqxowZg4yMDKhUqjptJCYmYsGCBeaETkREFpJTWIYhC7eZPH5HgBueubebDSOitsCmDz9cuHAh1q9fj/T0dDg5OUnlkyZNkn6+88470a9fP3Tr1g3p6em4//7767QTHx+PuLg46X1hYSGCgoKsGzwREQEADmfXP2/lyXtCbBQJtSVmTbr19vaGSqVCTk6OQXlOTg78/f3rPffvf/87Fi5ciK1bt6Jfv3711u3atSu8vb1x5ozxcVGNRgM3NzeDFxER2YaD0vRXh5+bBmoH7phBlmfW3yq1Wo2BAwciLS1NKtPr9UhLS0NkZKTJ8xYvXoy33noLKSkpGDRoUIPXuXTpEq5fv46AgABzwiMiIhtwrCch8XHV2DASakvMToPj4uLw0Ucf4ZNPPsGvv/6KZ599FiUlJYiNjQUATJ061WBS7qJFi/DGG29g9erVCA4OhlarhVarRXFxMQCguLgYL7/8Mvbs2YPz588jLS0NDz/8MLp3747o6GgL3SYREVnKLxfzTR5bOrG/7QKhNsXsOSwTJ07EtWvXkJCQAK1Wi/DwcKSkpEgTcbOzs6Gs0V24atUqVFRU4I9//KNBO/PmzcP8+fOhUqlw9OhRfPLJJ8jPz0dgYCBGjRqFt956CxoNM3UiIjmpqNJjSepvdcrXz7gbd3c1vrKTyBLM3odFjrgPCxGRbcSs3ocdv12rU35+4Vg7REMtnTnf35wZRUREjWYsWXlvQpgdIqG2hgkLERE12fjwQDw2sJO9w6A2gAkLERE1ys0KXZ2ySl2Ln1VALQQTFiIiapSKKn2dMgEmLGQbTFiIiKhRjl7Or1M26a7Otg+E2iQmLERE1Cgz/33I4L2niyOG9/SxUzTU1jBhISKiBun0AoVlVdL7cWGBSI27144RUVtj04cfEhFRy7T0J8PN4pZP5o62ZFvsYSEionp998sVLN92+2G0XX3a2TEaaquYsBARkUmX82/i+XWHDcq+nXmPnaKhtowJCxERmfTaN8fqlLk6OdohEmrrmLAQEZFJ6ZmGW/H/d+5IO0VCbR0TFiIiMiqvuLxOWZCXix0iIWLCQkRENQhxe+faA+d/t2MkRIa4rJmIiAAARWWVGL30v4js1gG9/F3x9uZfDY4/eKe/nSIjYsJCRET/0//NVFTpBb48eKnOseMLotFew68Msh8OCREREQpuVqJKb/pBhkxWyN6YsBARtXFVOj1mrT1k8viXz0TaMBoi45iwEBG1ce/+mIn/ns4zeXxQsJcNoyEyjgkLEVEblrTjLD7Yec7k8Z/ihtswGiLTOChJRNQGVer06PHalgbrdfd1tUE0RA1jwkJE1EYUllXi6U8O4O6uHdBOrbJ3OERmYcJCRNQGFJVV4u530lBaocO+LG4IRy0P57AQEbViOr3Ajye0uHP+VpRW6Bqs7+bEf8eSPDFhISJqhW5W6FBWqcO7P2biL58drLdukJczAGBKRGccnR9ti/CIzMZUmoioldmemYvYNfsbVferZ4dgYBdPK0dE1HzsYSEiaiWKyioR/MrmepOVrS8YLlNmskItBXtYiIhaoPIqHU5cKcTytNPwbKdGeaUem49drfecl0b1RE+/hpcpvxwdind/zMScqB6WCpeo2ZiwEBHJXGlFFZb+dBof1rPBmzFqByUqqvTwdHHErr/dh3b/ex7Ql89E4o9JGRgcYnwH2+dGdMMfwgLRydO52bETWYpCCGH6aVctRGFhIdzd3VFQUAA3Nzd7h0NEZBF6vUDXV39o0rlH54+Cm5OjyePlVTqoVUooFIqmhkfUbOZ8f7OHhYjIxnafzYOvqwaBHs44d60EHT2cUVxehXN5JYhZva/J7c4Y3hWvPnhHo+pqHLhxHLUsTFiIiJpACIHSCh0u59/EVwcvIdTfFdrCMuQUlOGXSwV4oLcf+gd5YPm2Myit1MHFUYWMc9ebfd2OHs7Y+EwkAtyd2DtCbUqTEpaVK1fi3XffhVarRVhYGJYvX47BgwebrL9x40a88cYbOH/+PHr06IFFixbhwQcflI4LITBv3jx89NFHyM/Pxz333INVq1ahRw9O+CIi29DrBZRKBa4Xl+P7o1cx7z8nmtXekYv5lgkMwP7XouDdXs0Ehdo0sxOWDRs2IC4uDklJSYiIiMDSpUsRHR2NzMxM+Pr61qm/e/duTJ48GYmJiXjooYewdu1ajB8/HocOHULfvn0BAIsXL8b777+PTz75BCEhIXjjjTcQHR2NkydPwsnJqfl3SUQ2I4RAeZUeQgB6ISDwvz/1hu/1QkCvB5QKoFIvIISAEEBZpQ7F5VVwUTugSq+Hg1KJ/NIKuDk7QqEAKqsEnNVKVOkFruaXwclRBQ+XW3M1SiuqUFapR+HNSjirVXBQKnH+egnKKnVQOyhxOqcYv5dUYEj3DrhwvRRbjt9aVXPx95v2+4X9T3ff9ng5OhQ9/VxRXFaF7r7t4czn/RBJzJ50GxERgbvuugsrVqwAAOj1egQFBeH555/HK6+8Uqf+xIkTUVJSgu+//14qu/vuuxEeHo6kpCQIIRAYGIgXX3wRL730EgCgoKAAfn5+SE5OxqRJk+q0WV5ejvLycul9YWEhgoKCLD7ptkqnx9ubf23SuQ39Wus7Wt+pot4zGzq3fvWHbPpgQ3+D7HE/DcZU39kNnlvfdev5PdXfbDM/u6Zft/5fhUCVTqBSp0eV/tafFVV66PQCOiGg09+6dlmlDpU6geLyKpRV6lBepW/oqq3CiFAfhPq5IiuvBH5uTvjLvV1RVFaFrj7tcLNCh/PXS9HRwxmlFVVwdXKEq5MDHFXc/oqomtUm3VZUVODgwYOIj4+XypRKJaKiopCRkWH0nIyMDMTFxRmURUdHY9OmTQCArKwsaLVaREVFScfd3d0RERGBjIwMowlLYmIiFixYYE7oTaIXQPLu81a/DlFbpFAASoUCOr1hxlS9FNf9fz0qCgA3SivhqFLA1ckRVbpbvTclFVWoPtXDxREOSoXUq3LpRimCO7RDlV4gK68EPf3aQ+2gxPHLhQCArj7tcO5aCQLcnaDTCxSVVaGdxgEzhoegh68r2mkcTC75bSyNgwrhLurqd81qi4jMTFjy8vKg0+ng5+dnUO7n54dTp04ZPUer1Rqtr9VqpePVZabq1BYfH2+QBFX3sFiaUgHMGtm93jr1DSk3ONpcz8n1ndvQMLainrMbPrdp123O2Lq17qehiOo/t/6zmzOVoL7fVfM+96Zds6G2VUoFHFVKOKpu/emgvPWzUqmASqGAQgGoVUo4OargolZB46CCZztHqJQKKKCQEpPqP5UKw3gqdfpbx/8XB+dpEJExLXKVkEajgUZj/X+xOKiUeCk61OrXIWrLOERCRI1h1v8pvL29oVKpkJOTY1Cek5MDf39/o+f4+/vXW7/6T3PaJCIiorbFrIRFrVZj4MCBSEtLk8r0ej3S0tIQGRlp9JzIyEiD+gCQmpoq1Q8JCYG/v79BncLCQuzdu9dkm0RERNS2mD0kFBcXh5iYGAwaNAiDBw/G0qVLUVJSgtjYWADA1KlT0bFjRyQmJgIAZs+ejXvvvRfvvfcexo4di/Xr1+PAgQP48MMPAdwar54zZw7efvtt9OjRQ1rWHBgYiPHjx1vuTomIiKjFMjthmThxIq5du4aEhARotVqEh4cjJSVFmjSbnZ0NpfJ2x82QIUOwdu1avP7663j11VfRo0cPbNq0SdqDBQDmzp2LkpISzJgxA/n5+Rg6dChSUlK4BwsREREB4MMPiYiIyE7M+f7m9HwiIiKSPSYsREREJHtMWIiIiEj2mLAQERGR7DFhISIiItljwkJERESyx4SFiIiIZI8JCxEREclei3xac23Ve98VFhbaORIiIiJqrOrv7cbsYdsqEpaioiIAQFBQkJ0jISIiInMVFRXB3d293jqtYmt+vV6PK1euwNXVFQqFwqJtFxYWIigoCBcvXuS2/3bEz0E++FnIAz8H+eBn0XRCCBQVFSEwMNDgOYTGtIoeFqVSiU6dOln1Gm5ubvyLKAP8HOSDn4U88HOQD34WTdNQz0o1TrolIiIi2WPCQkRERLLHhKUBGo0G8+bNg0ajsXcobRo/B/ngZyEP/Bzkg5+FbbSKSbdERETUurGHhYiIiGSPCQsRERHJHhMWIiIikj0mLERERCR7TFiIiIhI9piwNGDlypUIDg6Gk5MTIiIisG/fPnuH1GLt3LkT48aNQ2BgIBQKBTZt2mRwXAiBhIQEBAQEwNnZGVFRUTh9+rRBnd9//x1TpkyBm5sbPDw88NRTT6G4uNigztGjRzFs2DA4OTkhKCgIixcvtvattSiJiYm466674OrqCl9fX4wfPx6ZmZkGdcrKyjBz5kx06NAB7du3x2OPPYacnByDOtnZ2Rg7dixcXFzg6+uLl19+GVVVVQZ10tPTMWDAAGg0GnTv3h3JycnWvr0WZdWqVejXr5+0Q2pkZCS2bNkiHefnYB8LFy6EQqHAnDlzpDJ+FjIgyKT169cLtVotVq9eLU6cOCGmT58uPDw8RE5Ojr1Da5F++OEH8dprr4mvv/5aABDffPONwfGFCxcKd3d3sWnTJvHLL7+IP/zhDyIkJETcvHlTqjN69GgRFhYm9uzZI/773/+K7t27i8mTJ0vHCwoKhJ+fn5gyZYo4fvy4WLdunXB2dhYffPCBrW5T9qKjo8WaNWvE8ePHxZEjR8SDDz4oOnfuLIqLi6U6zzzzjAgKChJpaWniwIED4u677xZDhgyRjldVVYm+ffuKqKgocfjwYfHDDz8Ib29vER8fL9U5d+6ccHFxEXFxceLkyZNi+fLlQqVSiZSUFJver5z95z//EZs3bxa//fabyMzMFK+++qpwdHQUx48fF0Lwc7CHffv2ieDgYNGvXz8xe/ZsqZyfhf0xYanH4MGDxcyZM6X3Op1OBAYGisTERDtG1TrUTlj0er3w9/cX7777rlSWn58vNBqNWLdunRBCiJMnTwoAYv/+/VKdLVu2CIVCIS5fviyEEOKf//yn8PT0FOXl5VKdv/3tbyI0NNTKd9Ry5ebmCgBix44dQohbv3dHR0exceNGqc6vv/4qAIiMjAwhxK3kU6lUCq1WK9VZtWqVcHNzk373c+fOFX369DG41sSJE0V0dLS1b6lF8/T0FP/617/4OdhBUVGR6NGjh0hNTRX33nuvlLDws5AHDgmZUFFRgYMHDyIqKkoqUyqViIqKQkZGhh0ja52ysrKg1WoNft/u7u6IiIiQft8ZGRnw8PDAoEGDpDpRUVFQKpXYu3evVGf48OFQq9VSnejoaGRmZuLGjRs2upuWpaCgAADg5eUFADh48CAqKysNPotevXqhc+fOBp/FnXfeCT8/P6lOdHQ0CgsLceLECalOzTaq6/C/H+N0Oh3Wr1+PkpISREZG8nOwg5kzZ2Ls2LF1fl/8LOShVTyt2Rry8vKg0+kM/vIBgJ+fH06dOmWnqFovrVYLAEZ/39XHtFotfH19DY47ODjAy8vLoE5ISEidNqqPeXp6WiX+lkqv12POnDm455570LdvXwC3fk9qtRoeHh4GdWt/FsY+q+pj9dUpLCzEzZs34ezsbI1banGOHTuGyMhIlJWVoX379vjmm2/Qu3dvHDlyhJ+DDa1fvx6HDh3C/v376xzjfxPywISFqA2bOXMmjh8/jl27dtk7lDYrNDQUR44cQUFBAb788kvExMRgx44d9g6rTbl48SJmz56N1NRUODk52TscMoFDQiZ4e3tDpVLVmQWek5MDf39/O0XVelX/Tuv7ffv7+yM3N9fgeFVVFX7//XeDOsbaqHkNumXWrFn4/vvvsX37dnTq1Ekq9/f3R0VFBfLz8w3q1/4sGvo9m6rj5ubGf0nWoFar0b17dwwcOBCJiYkICwvDsmXL+DnY0MGDB5Gbm4sBAwbAwcEBDg4O2LFjB95//304ODjAz8+Pn4UMMGExQa1WY+DAgUhLS5PK9Ho90tLSEBkZacfIWqeQkBD4+/sb/L4LCwuxd+9e6fcdGRmJ/Px8HDx4UKqzbds26PV6RERESHV27tyJyspKqU5qaipCQ0M5HPQ/QgjMmjUL33zzDbZt21ZnCG3gwIFwdHQ0+CwyMzORnZ1t8FkcO3bMIIFMTU2Fm5sbevfuLdWp2UZ1Hf73Uz+9Xo/y8nJ+DjZ0//3349ixYzhy5Ij0GjRoEKZMmSL9zM9CBuw961fO1q9fLzQajUhOThYnT54UM2bMEB4eHgazwKnxioqKxOHDh8Xhw4cFALFkyRJx+PBhceHCBSHErWXNHh4e4ttvvxVHjx4VDz/8sNFlzf379xd79+4Vu3btEj169DBY1pyfny/8/PzEE088IY4fPy7Wr18vXFxcuKy5hmeffVa4u7uL9PR0cfXqVelVWloq1XnmmWdE586dxbZt28SBAwdEZGSkiIyMlI5XL+EcNWqUOHLkiEhJSRE+Pj5Gl3C+/PLL4tdffxUrV67kEs5aXnnlFbFjxw6RlZUljh49Kl555RWhUCjE1q1bhRD8HOyp5iohIfhZyAETlgYsX75cdO7cWajVajF48GCxZ88ee4fUYm3fvl0AqPOKiYkRQtxa2vzGG28IPz8/odFoxP333y8yMzMN2rh+/bqYPHmyaN++vXBzcxOxsbGiqKjIoM4vv/wihg4dKjQajejYsaNYuHChrW6xRTD2GQAQa9askercvHlTPPfcc8LT01O4uLiIRx55RFy9etWgnfPnz4sxY8YIZ2dn4e3tLV588UVRWVlpUGf79u0iPDxcqNVq0bVrV4NrkBBPPvmk6NKli1Cr1cLHx0fcf//9UrIiBD8He6qdsPCzsD+FEELYp2+HiIiIqHE4h4WIiIhkjwkLERERyR4TFiIiIpI9JixEREQke0xYiIiISPaYsBAREZHsMWEhIiIi2WPCQkRERLLHhIWIiIhkjwkLERERyR4TFiIiIpK9/weGAZZ4jBRNoAAAAABJRU5ErkJggg=="
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from matplotlib import pyplot as plt\n",
+    "for ts_type in data_split.keys():\n",
+    "    pd.DataFrame(data_split[ts_type]).plot(title=f'Bitcoin - {ts_type}')\n",
+    "    plt.show()"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "Next steps are quite straightforward. We need to fit the model and then predict the values for the test data just like for any other model in sklearn.\n",
+    "\n",
+    "At the `fit` stage FedotIndustrial will transform initial time series data into features dataframe and will train regression model."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "industrial_model =  evaluate_loop(train_data = input_data, api_params=params, finetune=True)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "labels = industrial_model.predict(train_data)\n",
+    "metrics = industrial_model.get_metrics(target=target,\n",
+    "                                         metric_names=metric_names)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "metrics"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## AutoML approach"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-04-18 13:43:01,653 - Initialising experiment setup\n",
+      "2024-04-18 13:43:06,888 - Initialising Industrial Repository\n",
+      "2024-04-18 13:43:06,889 - Initialising Dask Server\n",
+      "Creating Dask Server\n",
+      "2024-04-18 13:43:15,943 - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy\n",
+      "2024-04-18 13:43:16,069 - State start\n",
+      "2024-04-18 13:43:16,136 -   Scheduler at: inproc://10.64.4.32/19528/1\n",
+      "2024-04-18 13:43:16,136 -   dashboard at:  http://10.64.4.32:8787/status\n",
+      "2024-04-18 13:43:16,137 - Registering Worker plugin shuffle\n",
+      "2024-04-18 13:43:16,195 -       Start worker at: inproc://10.64.4.32/19528/4\n",
+      "2024-04-18 13:43:16,196 -          Listening to:           inproc10.64.4.32\n",
+      "2024-04-18 13:43:16,196 -           Worker name:                          0\n",
+      "2024-04-18 13:43:16,197 -          dashboard at:           10.64.4.32:62391\n",
+      "2024-04-18 13:43:16,198 - Waiting to connect to: inproc://10.64.4.32/19528/1\n",
+      "2024-04-18 13:43:16,199 - -------------------------------------------------\n",
+      "2024-04-18 13:43:16,200 -               Threads:                          8\n",
+      "2024-04-18 13:43:16,201 -                Memory:                  31.95 GiB\n",
+      "2024-04-18 13:43:16,202 -       Local Directory: C:\\Users\\user\\AppData\\Local\\Temp\\dask-scratch-space\\worker-76qmxn5n\n",
+      "2024-04-18 13:43:16,203 - -------------------------------------------------\n",
+      "2024-04-18 13:43:16,264 - Register worker <WorkerState 'inproc://10.64.4.32/19528/4', name: 0, status: init, memory: 0, processing: 0>\n",
+      "2024-04-18 13:43:16,266 - Starting worker compute stream, inproc://10.64.4.32/19528/4\n",
+      "2024-04-18 13:43:16,267 - Starting established connection to inproc://10.64.4.32/19528/5\n",
+      "2024-04-18 13:43:16,268 - Starting Worker plugin shuffle\n",
+      "2024-04-18 13:43:16,269 -         Registered to: inproc://10.64.4.32/19528/1\n",
+      "2024-04-18 13:43:16,270 - -------------------------------------------------\n",
+      "2024-04-18 13:43:16,271 - Starting established connection to inproc://10.64.4.32/19528/1\n",
+      "2024-04-18 13:43:16,274 - Receive client connection: Client-7695494d-fd70-11ee-8c48-b42e99a00ea1\n",
+      "2024-04-18 13:43:16,276 - Starting established connection to inproc://10.64.4.32/19528/6\n",
+      "2024-04-18 13:43:16,277 - LinK Dask Server - http://10.64.4.32:8787/status\n",
+      "2024-04-18 13:43:16,278 - Initialising solver\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Generations:   0%|          | 12/10000 [04:27<76:17:45, 27.50s/gen]"
+     ]
+    }
+   ],
+   "source": [
+    "fred_results = {}\n",
+    "for index, ts in data_split.items():\n",
+    "    input_data = (ts,ts[-horizon:].flatten())\n",
+    "    industrial_auto_model = evaluate_loop(train_data=input_data, api_params=params, finetune=False)\n",
+    "    auto_labels = industrial_auto_model.predict(train_data)\n",
+    "    auto_metrics = {}\n",
+    "    for forecat_model, predict in auto_labels.items():\n",
+    "        industrial_auto_model.predicted_labels = predict\n",
+    "\n",
+    "        current_metric = industrial_auto_model.get_metrics(target=ts[-horizon:].flatten(),\n",
+    "                                                metric_names=metric_names)\n",
+    "        auto_metrics.update({forecat_model:current_metric})\n",
+    "    fred_results.update({index:(industrial_auto_model,auto_metrics)})"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n",
+     "is_executing": true
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "border = 100\n",
+    "baseline = labels\n",
+    "ridge = auto_labels['lagged_ridge']\n",
+    "eigen = auto_labels['eigen_ar']\n",
+    "cgru = auto_labels['cgru']\n",
+    "plt.close()\n",
+    "real_values = train_data\n",
+    "if len(real_values) > border:\n",
+    "    real_values = real_values[-border:]\n",
+    "indicies = np.arange(real_values.shape[0])"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "<matplotlib.legend.Legend at 0x244520d5e20>"
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": "<Figure size 640x480 with 1 Axes>",
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.xlabel('Time index')\n",
+    "plt.ylabel('Series values')\n",
+    "plt.title('Forecating by Industrial')\n",
+    "plt.plot(real_values)\n",
+    "\n",
+    "real_last_value = real_values[-horizon- 1]\n",
+    "plt.plot(indicies[-horizon- 1:],\n",
+    "         np.insert(baseline, 0, real_last_value), label='Finetune')\n",
+    "plt.plot(indicies[-horizon- 1:],\n",
+    "         np.insert(eigen, 0, real_last_value), label='Eigen_AR')\n",
+    "\n",
+    "plt.grid()\n",
+    "plt.legend()"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Compare with State of Art (SOTA) models"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "df_sota = pd.read_csv('./Monash_forecasting_SOTA_results.csv')"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "df_sota"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  }
+ ],
+ "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": "3.8.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
\ No newline at end of file
diff --git a/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_regression/__init__.py b/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_regression/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/examples/real_world_examples/industrial_examples/sentiment_analysis/ts_regression/bitcoin_analysis.ipynb b/examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_regression/bitcoin_analysis.ipynb
similarity index 100%
rename from examples/real_world_examples/industrial_examples/sentiment_analysis/ts_regression/bitcoin_analysis.ipynb
rename to examples/real_world_examples/industrial_examples/criptocurrency_analysis/ts_regression/bitcoin_analysis.ipynb
diff --git a/examples/real_world_examples/industrial_examples/economic_analysis/ts_forecasting/federal_reserve_economic_data_forecasting.ipynb b/examples/real_world_examples/industrial_examples/economic_analysis/ts_forecasting/federal_reserve_economic_data_forecasting.ipynb
index 73b64c034..b7561f75b 100644
--- a/examples/real_world_examples/industrial_examples/economic_analysis/ts_forecasting/federal_reserve_economic_data_forecasting.ipynb
+++ b/examples/real_world_examples/industrial_examples/economic_analysis/ts_forecasting/federal_reserve_economic_data_forecasting.ipynb
@@ -62,23 +62,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:14:45,775 - PyTorch version 1.12.1+cu113 available.\n"
-     ]
-    }
-   ],
+   "execution_count": 3,
+   "outputs": [],
    "source": [
-    "from datasets import load_dataset\n",
-    "dataset_name = 'fred_md'\n",
+    "from fedot_ind.api.utils.path_lib import PROJECT_PATH\n",
+    "\n",
+    "dataset_name = PROJECT_PATH +'/examples/data/forecasting\\monash_benchmark\\MonashFredMd_12.csv'\n",
     "horizon = 12\n",
     "metric_names = ('smape', 'rmse', 'median_absolute_error')\n",
-    "train_data = load_dataset('monash_tsf', 'fred_md')\n",
-    "forecasting_metrics = ('smape', 'rmse')\n",
+    "train_data = pd.read_csv(dataset_name)\n",
     "params = dict(problem='ts_forecasting',\n",
     "                             metric='rmse',\n",
     "                             timeout=15,\n",
@@ -87,7 +79,31 @@
     "                             task_params={'forecast_length': horizon},\n",
     "                             industrial_strategy='forecasting_assumptions',\n",
     "                             n_jobs=2,\n",
-    "                             logging_level=40)"
+    "                             logging_level=50)"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "         datetime        value label\n0      1959-01-01  2437.295898    T1\n1      1959-02-01  2446.902100    T1\n2      1959-03-01  2462.688965    T1\n3      1959-04-01  2478.743896    T1\n4      1959-05-01  2493.228027    T1\n...           ...          ...   ...\n77891  2019-04-01  3608.839111  T107\n77892  2019-05-01  3622.253174  T107\n77893  2019-06-01  3651.351318  T107\n77894  2019-07-01  3673.951416  T107\n77895  2019-08-01  3725.410400  T107\n\n[77896 rows x 3 columns]",
+      "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>datetime</th>\n      <th>value</th>\n      <th>label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1959-01-01</td>\n      <td>2437.295898</td>\n      <td>T1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1959-02-01</td>\n      <td>2446.902100</td>\n      <td>T1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1959-03-01</td>\n      <td>2462.688965</td>\n      <td>T1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1959-04-01</td>\n      <td>2478.743896</td>\n      <td>T1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1959-05-01</td>\n      <td>2493.228027</td>\n      <td>T1</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>77891</th>\n      <td>2019-04-01</td>\n      <td>3608.839111</td>\n      <td>T107</td>\n    </tr>\n    <tr>\n      <th>77892</th>\n      <td>2019-05-01</td>\n      <td>3622.253174</td>\n      <td>T107</td>\n    </tr>\n    <tr>\n      <th>77893</th>\n      <td>2019-06-01</td>\n      <td>3651.351318</td>\n      <td>T107</td>\n    </tr>\n    <tr>\n      <th>77894</th>\n      <td>2019-07-01</td>\n      <td>3673.951416</td>\n      <td>T107</td>\n    </tr>\n    <tr>\n      <th>77895</th>\n      <td>2019-08-01</td>\n      <td>3725.410400</td>\n      <td>T107</td>\n    </tr>\n  </tbody>\n</table>\n<p>77896 rows × 3 columns</p>\n</div>"
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data"
    ],
    "metadata": {
     "collapsed": false,
@@ -110,15 +126,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "outputs": [],
    "source": [
-    "data_split = {}\n",
-    "for split in ['train', 'validation', 'test']:\n",
-    "    df_pandas = train_data[split].to_pandas()\n",
-    "    id_list = df_pandas['item_id'].values.tolist()\n",
-    "    ts_list = [df_pandas[df_pandas['item_id']==id]['target'].values[0] for id in id_list]\n",
-    "    data_split.update({split:ts_list})"
+    "id_list = train_data['label'].unique().tolist()\n",
+    "data_split = {id:train_data[train_data['label']==id]['value'].values for id in id_list}"
    ],
    "metadata": {
     "collapsed": false,
@@ -245,330 +257,108 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:15:06,492 - Initialising experiment setup\n",
-      "2024-04-18 13:15:06,629 - Initialising Industrial Repository\n",
-      "2024-04-18 13:15:06,631 - Initialising Dask Server\n",
-      "Creating Dask Server\n",
-      "2024-04-18 13:15:07,199 - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy\n",
-      "2024-04-18 13:15:07,230 - State start\n",
-      "2024-04-18 13:15:07,232 - Found stale lock file and directory 'C:\\\\Users\\\\user\\\\AppData\\\\Local\\\\Temp\\\\dask-scratch-space\\\\scheduler-aoyohjql', purging\n",
-      "2024-04-18 13:15:07,234 - Found stale lock file and directory 'C:\\\\Users\\\\user\\\\AppData\\\\Local\\\\Temp\\\\dask-scratch-space\\\\scheduler-xcz2_owm', purging\n",
-      "2024-04-18 13:15:07,235 - Found stale lock file and directory 'C:\\\\Users\\\\user\\\\AppData\\\\Local\\\\Temp\\\\dask-scratch-space\\\\worker-nmaaw9wm', purging\n",
-      "2024-04-18 13:15:07,237 - Found stale lock file and directory 'C:\\\\Users\\\\user\\\\AppData\\\\Local\\\\Temp\\\\dask-scratch-space\\\\worker-wrl08xfw', purging\n",
-      "2024-04-18 13:15:07,247 -   Scheduler at: inproc://10.64.4.32/428/1\n",
-      "2024-04-18 13:15:07,248 -   dashboard at:  http://10.64.4.32:8787/status\n",
-      "2024-04-18 13:15:07,249 - Registering Worker plugin shuffle\n",
-      "2024-04-18 13:15:07,264 -       Start worker at:  inproc://10.64.4.32/428/4\n",
-      "2024-04-18 13:15:07,265 -          Listening to:           inproc10.64.4.32\n",
-      "2024-04-18 13:15:07,265 -           Worker name:                          0\n",
-      "2024-04-18 13:15:07,267 -          dashboard at:           10.64.4.32:61327\n",
-      "2024-04-18 13:15:07,268 - Waiting to connect to:  inproc://10.64.4.32/428/1\n",
-      "2024-04-18 13:15:07,269 - -------------------------------------------------\n",
-      "2024-04-18 13:15:07,271 -               Threads:                          8\n",
-      "2024-04-18 13:15:07,271 -                Memory:                  31.95 GiB\n",
-      "2024-04-18 13:15:07,274 -       Local Directory: C:\\Users\\user\\AppData\\Local\\Temp\\dask-scratch-space\\worker-64u04zzs\n",
-      "2024-04-18 13:15:07,275 - -------------------------------------------------\n",
-      "2024-04-18 13:15:07,282 - Register worker <WorkerState 'inproc://10.64.4.32/428/4', name: 0, status: init, memory: 0, processing: 0>\n",
-      "2024-04-18 13:15:07,284 - Starting worker compute stream, inproc://10.64.4.32/428/4\n",
-      "2024-04-18 13:15:07,285 - Starting established connection to inproc://10.64.4.32/428/5\n",
-      "2024-04-18 13:15:07,286 - Starting Worker plugin shuffle\n",
-      "2024-04-18 13:15:07,286 -         Registered to:  inproc://10.64.4.32/428/1\n",
-      "2024-04-18 13:15:07,287 - -------------------------------------------------\n",
-      "2024-04-18 13:15:07,288 - Starting established connection to inproc://10.64.4.32/428/1\n",
-      "2024-04-18 13:15:07,292 - Receive client connection: Client-87dee5d3-fd6c-11ee-81ac-b42e99a00ea1\n",
-      "2024-04-18 13:15:07,293 - Starting established connection to inproc://10.64.4.32/428/6\n",
-      "2024-04-18 13:15:07,295 - LinK Dask Server - http://10.64.4.32:8787/status\n",
-      "2024-04-18 13:15:07,296 - Initialising solver\n",
-      "2024-04-18 13:15:07,377 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 36\n",
-      "2024-04-18 13:15:07,413 - AssumptionsHandler - Memory consumption for fitting of the initial pipeline in main session: current 0.5 MiB, max: 0.9 MiB\n",
-      "2024-04-18 13:15:07,414 - ApiComposer - Initial pipeline was fitted in 0.1 sec.\n",
-      "2024-04-18 13:15:07,415 - AssumptionsHandler - Preset was changed to best_quality due to fit time estimation for initial model.\n",
-      "2024-04-18 13:15:07,427 - ApiComposer - AutoML configured. Parameters tuning: False. Time limit: 5 min. Set of candidate models: ['ar', 'stl_arima', 'ets', 'cgru', 'glm', 'lagged', 'sparse_lagged', 'smoothing', 'gaussian_filter', 'ridge', 'lasso', 'eigen_basis', 'wavelet_basis', 'fourier_basis'].\n",
-      "2024-04-18 13:15:07,459 - ApiComposer - Pipeline composition started.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 0/10000 [00:00<?, ?gen/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:15:07,475 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 36\n",
-      "2024-04-18 13:15:07,588 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 54\n",
-      "2024-04-18 13:15:07,715 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 90\n",
-      "2024-04-18 13:15:07,974 - IndustrialDispatcher - 1 individuals out of 1 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:11,236 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 36\n",
-      "2024-04-18 13:15:11,341 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 72\n",
-      "2024-04-18 13:15:11,443 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 126\n",
-      "2024-04-18 13:15:13,007 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 36\n",
-      "2024-04-18 13:15:13,110 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 36\n",
-      "2024-04-18 13:15:13,222 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0 to 72\n",
-      "2024-04-18 13:15:14,833 - IndustrialDispatcher - 13 individuals out of 13 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:19,347 - IndustrialDispatcher - 8 individuals out of 8 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:20,988 - IndustrialDispatcher - 3 individuals out of 3 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:22,644 - IndustrialDispatcher - 3 individuals out of 3 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 1/10000 [00:15<42:11:02, 15.19s/gen]"
+      "Generations:   0%|          | 11/10000 [04:41<71:07:00, 25.63s/gen]\n",
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      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:15:27,940 - IndustrialDispatcher - 10 individuals out of 10 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:31,329 - IndustrialDispatcher - 6 individuals out of 6 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:32,572 - IndustrialDispatcher - 2 individuals out of 2 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:34,156 - IndustrialDispatcher - 3 individuals out of 3 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 2/10000 [00:26<36:10:21, 13.02s/gen]"
+      "Generations:   0%|          | 11/10000 [04:42<71:08:22, 25.64s/gen]\n",
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+      "Generations:   0%|          | 11/10000 [04:52<73:47:17, 26.59s/gen]\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:15:41,494 - IndustrialDispatcher - 12 individuals out of 12 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:49,139 - IndustrialDispatcher - 15 individuals out of 15 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:15:51,739 - IndustrialDispatcher - 5 individuals out of 5 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 3/10000 [00:44<41:57:18, 15.11s/gen]"
+      "Generations:   0%|          | 11/10000 [05:11<78:30:50, 28.30s/gen]\n",
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+      "Generations:   0%|          | 10/10000 [04:39<77:39:27, 27.98s/gen]\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:16:03,025 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 36\n",
-      "2024-04-18 13:16:03,134 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 54\n",
-      "2024-04-18 13:16:03,253 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 108\n",
-      "2024-04-18 13:16:07,234 - IndustrialDispatcher - 28 individuals out of 28 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:16:21,253 - IndustrialDispatcher - 26 individuals out of 26 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:16:21,288 - IndustrialDispatcher - 53 individuals out of 53 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 4/10000 [01:13<57:46:17, 20.81s/gen]"
+      "Generations:   0%|          | 9/10000 [04:41<86:46:34, 31.27s/gen]\n",
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      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:16:27,184 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 36\n",
-      "2024-04-18 13:16:27,295 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 54\n",
-      "2024-04-18 13:16:27,412 - SparseLaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 72\n",
-      "2024-04-18 13:16:42,495 - IndustrialDispatcher - 36 individuals out of 36 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:16:52,152 - IndustrialDispatcher - 17 individuals out of 17 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 5/10000 [01:44<67:52:32, 24.45s/gen]"
+      "Generations:   0%|          | 10/10000 [05:00<83:26:03, 30.07s/gen]\n",
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      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-04-18 13:17:10,100 - IndustrialDispatcher - 33 individuals out of 33 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:17:17,936 - IndustrialDispatcher - 16 individuals out of 16 in previous population were evaluated successfully.\n"
+      "Creating Dask Server\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Generations:   0%|          | 6/10000 [02:10<69:07:24, 24.90s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:17:38,952 - IndustrialDispatcher - 40 individuals out of 40 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:17:45,162 - IndustrialDispatcher - 12 individuals out of 12 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 7/10000 [02:37<71:13:39, 25.66s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:18:05,220 - IndustrialDispatcher - 42 individuals out of 42 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:18:08,028 - IndustrialDispatcher - 5 individuals out of 5 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:18:11,076 - IndustrialDispatcher - 6 individuals out of 6 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 8/10000 [03:03<71:26:56, 25.74s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:18:29,500 - IndustrialDispatcher - 37 individuals out of 37 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:18:37,965 - IndustrialDispatcher - 15 individuals out of 15 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:18:38,012 - IndustrialDispatcher - 53 individuals out of 53 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 9/10000 [03:30<72:26:37, 26.10s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:18:57,463 - IndustrialDispatcher - 35 individuals out of 35 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:19:08,040 - IndustrialDispatcher - 19 individuals out of 19 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 10/10000 [04:00<75:49:58, 27.33s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:19:22,849 - IndustrialDispatcher - 28 individuals out of 28 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:19:36,969 - IndustrialDispatcher - 29 individuals out of 29 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 11/10000 [04:29<77:11:04, 27.82s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:19:55,789 - IndustrialDispatcher - 36 individuals out of 36 in previous population were evaluated successfully.\n",
-      "2024-04-18 13:20:04,216 - IndustrialDispatcher - 17 individuals out of 17 in previous population were evaluated successfully.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 12/10000 [04:56<76:41:58, 27.65s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:20:04,451 - GroupedCondition - Optimisation stopped: Time limit is reached\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 12/10000 [04:56<68:39:52, 24.75s/gen]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:20:04,595 - ApiComposer - Model generation finished\n",
-      "2024-04-18 13:20:04,602 - LaggedTransformationImplementation - Window size of lagged transformation was changed by WindowSizeSelector from 0.0 to 36\n",
-      "2024-04-18 13:20:04,619 - FEDOT logger - Final pipeline was fitted\n",
-      "2024-04-18 13:20:04,620 - FEDOT logger - Final pipeline: {'depth': 2, 'length': 2, 'nodes': [ridge, lagged]}\n",
-      "ridge - {'alpha': 1.7448092528362018}\n",
-      "lagged - {'window_size': 0.0}\n",
-      "2024-04-18 13:20:04,622 - MemoryAnalytics - Memory consumption for finish in main session: current 2.8 MiB, max: 4.5 MiB\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:20:04,786 - AssumptionsHandler - Memory consumption for fitting of the initial pipeline in main session: current 0.6 MiB, max: 1.2 MiB\n",
-      "2024-04-18 13:20:04,788 - ApiComposer - Initial pipeline was fitted in 0.1 sec.\n",
-      "2024-04-18 13:20:04,790 - AssumptionsHandler - Preset was changed to best_quality due to fit time estimation for initial model.\n",
-      "2024-04-18 13:20:04,800 - ApiComposer - AutoML configured. Parameters tuning: False. Time limit: 5 min. Set of candidate models: ['ar', 'stl_arima', 'ets', 'cgru', 'glm', 'lagged', 'sparse_lagged', 'smoothing', 'gaussian_filter', 'ridge', 'lasso', 'eigen_basis', 'wavelet_basis', 'fourier_basis'].\n",
-      "2024-04-18 13:20:04,829 - ApiComposer - Pipeline composition started.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Generations:   0%|          | 0/10000 [00:00<?, ?gen/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "2024-04-18 13:20:07,065 - IndustrialDispatcher - 1 individuals out of 1 in previous population were evaluated successfully.\n"
+      "Generations:   0%|          | 10/10000 [04:30<97:02:46, 34.97s/gen]"
      ]
     }
    ],
    "source": [
     "fred_results = {}\n",
-    "for index, ts in enumerate(data_split['test']):\n",
+    "for index, ts in data_split.items():\n",
     "    input_data = (ts,ts[-horizon:].flatten())\n",
     "    industrial_auto_model = evaluate_loop(train_data=input_data, api_params=params, finetune=False)\n",
-    "    auto_labels = industrial_auto_model.predict(train_data)\n",
+    "    auto_labels = industrial_auto_model.predict(input_data)\n",
     "    auto_metrics = {}\n",
     "    for forecat_model, predict in auto_labels.items():\n",
     "        industrial_auto_model.predicted_labels = predict\n",
     "\n",
-    "        current_metric = industrial_auto_model.get_metrics(target=target,\n",
+    "        current_metric = industrial_auto_model.get_metrics(target=ts[-horizon:].flatten(),\n",
     "                                                metric_names=metric_names)\n",
     "        auto_metrics.update({forecat_model:current_metric})\n",
     "    fred_results.update({index:(industrial_auto_model,auto_metrics)})"
@@ -670,8 +460,7 @@
    "metadata": {
     "collapsed": false,
     "pycharm": {
-     "name": "#%%\n",
-     "is_executing": true
+     "name": "#%%\n"
     }
    }
   },
@@ -685,8 +474,7 @@
    "metadata": {
     "collapsed": false,
     "pycharm": {
-     "name": "#%%\n",
-     "is_executing": true
+     "name": "#%%\n"
     }
    }
   },
diff --git a/fedot_ind/api/main.py b/fedot_ind/api/main.py
index 162234e5b..77bf9173b 100644
--- a/fedot_ind/api/main.py
+++ b/fedot_ind/api/main.py
@@ -179,7 +179,7 @@ def fit(self,
         """
         self.train_data = deepcopy(input_data)  # we do not want to make inplace changes
         input_preproc = DataCheck(input_data=self.train_data, task=self.config_dict['problem'],
-                                  task_params=self.task_params)
+                                  task_params=self.task_params, industrial_task_params=self.industrial_strategy_params)
         self.train_data = input_preproc.check_input_data()
         self.target_encoder = input_preproc.get_target_encoder()
         self.__init_solver()
@@ -207,7 +207,8 @@ def predict(self,
         self.predict_data = deepcopy(predict_data)  # we do not want to make inplace changes
         self.predict_data = DataCheck(input_data=self.predict_data,
                                       task=self.config_dict['problem'],
-                                      task_params=self.task_params).check_input_data()
+                                      task_params=self.task_params,
+                                      industrial_task_params=self.industrial_strategy_params).check_input_data()
         if self.industrial_strategy is not None and not self.is_finetuned:
             self.predicted_labels = self.industrial_strategy_class.predict(self.predict_data, predict_mode)
         else:
@@ -245,7 +246,8 @@ def predict_proba(self,
             predict_data)  # we do not want to make inplace changes
         self.predict_data = DataCheck(input_data=self.predict_data,
                                       task=self.config_dict['problem'],
-                                      task_params=self.task_params).check_input_data()
+                                      task_params=self.task_params,
+                                      industrial_task_params=self.industrial_strategy_params).check_input_data()
         if self.industrial_strategy is not None and not self.is_finetuned:
             self.predicted_labels = self.industrial_strategy_class.predict(self.predict_data, predict_mode)
         else:
diff --git a/fedot_ind/api/utils/checkers_collections.py b/fedot_ind/api/utils/checkers_collections.py
index fe91a2150..bd366ae72 100644
--- a/fedot_ind/api/utils/checkers_collections.py
+++ b/fedot_ind/api/utils/checkers_collections.py
@@ -31,8 +31,10 @@ class DataCheck:
     def __init__(self,
                  input_data: Union[tuple, InputData] = None,
                  task: str = None,
-                 task_params=None):
+                 task_params=None,
+                 industrial_task_params = None):
         self.logger = logging.getLogger(self.__class__.__name__)
+        self.industrial_task_params = industrial_task_params
         self.input_data = input_data
         self.data_convertor = DataConverter(data=self.input_data)
         self.task = task
@@ -98,8 +100,9 @@ def _init_input_data(self) -> None:
             features_array = self.data_convertor.convert_to_1d_array()
             task = Task(TaskTypesEnum.ts_forecasting,
                         TsForecastingParams(forecast_length=self.task_params['forecast_length']))
-            features_array = features_array[:-self.task_params['forecast_length']]
-            target = features_array[-self.task_params['forecast_length']:]
+            if self.industrial_task_params is None:
+                features_array = features_array[:-self.task_params['forecast_length']]
+                target = features_array[-self.task_params['forecast_length']:]
             self.input_data = InputData.from_numpy_time_series(
                 features_array=features_array,
                 target_array=target,
diff --git a/fedot_ind/api/utils/industrial_strategy.py b/fedot_ind/api/utils/industrial_strategy.py
index 616dbdfef..b4144a582 100644
--- a/fedot_ind/api/utils/industrial_strategy.py
+++ b/fedot_ind/api/utils/industrial_strategy.py
@@ -2,11 +2,17 @@
 
 import numpy as np
 from fedot import Fedot
+from fedot.core.data.data import InputData
+from fedot.core.data.data_split import train_test_data_setup
+from fedot.core.data.multi_modal import MultiModalData
+from fedot.core.pipelines.pipeline_builder import PipelineBuilder
+from fedot.core.repository.dataset_types import DataTypesEnum
 
 from fedot_ind.core.ensemble.kernel_ensemble import KernelEnsembler
 from fedot_ind.core.ensemble.random_automl_forest import RAFensembler
 from fedot_ind.core.repository.constanst_repository import BATCH_SIZE_FOR_FEDOT_WORKER, FEDOT_WORKER_NUM, \
-    FEDOT_WORKER_TIMEOUT_PARTITION, FEDOT_TUNING_METRICS, FEDOT_TUNER_STRATEGY, FEDOT_TS_FORECASTING_ASSUMPTIONS
+    FEDOT_WORKER_TIMEOUT_PARTITION, FEDOT_TUNING_METRICS, FEDOT_TUNER_STRATEGY, FEDOT_TS_FORECASTING_ASSUMPTIONS, \
+    FEDOT_TASK
 from fedot_ind.core.repository.industrial_implementations.abstract import build_tuner
 from fedot_ind.core.repository.initializer_industrial_models import IndustrialModels
 
@@ -21,10 +27,13 @@ def __init__(self, industrial_strategy_params,
         self.industrial_strategy = industrial_strategy
         self.industrial_strategy_fit = {'federated_automl': self._federated_strategy,
                                         'kernel_automl': self._kernel_strategy,
-                                        'forecasting_assumptions': self._forecasting_strategy}
+                                        'forecasting_assumptions': self._forecasting_strategy,
+                                        'forecasting_exogenous': self._forecasting_exogenous_strategy
+                                        }
         self.industrial_strategy_predict = {'federated_automl': self._federated_predict,
                                             'kernel_automl': self._kernel_predict,
-                                            'forecasting_assumptions': self._forecasting_predict}
+                                            'forecasting_assumptions': self._forecasting_predict,
+                                            'forecasting_exogenous': self._forecasting_predict}
         self.config_dict = api_config
         self.logger = logger
         self.repo = IndustrialModels().setup_repository()
@@ -66,6 +75,36 @@ def _forecasting_strategy(self, input_data):
             industrial.fit(input_data)
             self.solver.update({model_name: industrial})
 
+    def _forecasting_exogenous_strategy(self, input_data):
+        self.logger.info('TS exogenous forecasting algorithm was applied')
+        self.solver = {}
+        init_assumption = PipelineBuilder().add_node('lagged', 0)
+        task = FEDOT_TASK[self.config_dict['problem']]
+        train_lagged, predict_lagged = train_test_data_setup(InputData(idx=np.arange(len(input_data.features)),
+                                                                       features=input_data.features,
+                                                                       target=input_data.features,
+                                                                       task=task,
+                                                                       data_type=DataTypesEnum.ts), 2)
+        dataset_dict = {'lagged': train_lagged}
+        exog_variable = self.industrial_strategy_params['exog_variable']
+        init_assumption.add_node('exog_ts', 1)
+
+        # Exogenous time series
+        train_exog, predict_exog = train_test_data_setup(InputData(idx=np.arange(len(exog_variable)),
+                                                                   features=exog_variable,
+                                                                   target=input_data.features,
+                                                                   task=task,
+                                                                   data_type=DataTypesEnum.ts), 2)
+        dataset_dict.update({f'exog_ts': train_exog})
+
+        train_dataset = MultiModalData(dataset_dict)
+        init_assumption = init_assumption.join_branches('ridge')
+        self.config_dict['initial_assumption'] = init_assumption.build()
+
+        industrial = Fedot(**self.config_dict)
+        industrial.fit(train_dataset)
+        self.solver = {'exog_model': industrial}
+
     def _finetune_loop(self,
                        kernel_ensemble: dict,
                        kernel_data: dict,
diff --git a/fedot_ind/core/repository/model_repository.py b/fedot_ind/core/repository/model_repository.py
index 19297a58b..ec000fc16 100644
--- a/fedot_ind/core/repository/model_repository.py
+++ b/fedot_ind/core/repository/model_repository.py
@@ -80,6 +80,7 @@
                             'one_hot_encoding': OneHotEncodingImplementation,
                             'label_encoding': LabelEncodingImplementation
                             },
+    'FORECASTING_PREPROC': {'exog_ts': ExogDataTransformationImplementation},
     'INDUSTRIAL_PREPROC_MODEL': {
         'cat_features': DummyOperation,
         'dimension_reduction': FeatureFilter,
@@ -187,7 +188,8 @@ class AtomizedModel(Enum):
         'lagged': LaggedTransformationImplementation,
         'sparse_lagged': SparseLaggedTransformationImplementation,
         'smoothing': TsSmoothingImplementation,
-        'gaussian_filter': GaussianFilterImplementation
+        'gaussian_filter': GaussianFilterImplementation,
+        'exog_ts': ExogDataTransformationImplementation,
     }
 
     NEURAL_MODEL = {
diff --git a/requirements.txt b/requirements.txt
index 1a93e982e..0db7d4cf6 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -42,6 +42,5 @@ hyperopt~=0.2.7
 statsmodels~=0.14.1
 xgboost~=2.0.3
 seaborn~=0.13.2
-datasets
 librosa
 pywt
\ No newline at end of file