{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DUOMENŲ NUSKAITYMAS (SCRAPING) + ANALIZĖ"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nuskaitinėsime Coinbase keityklos apžvalgas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rating: 1\n",
      "Title: Violation of laws and regulations\n",
      "Date: June 03, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Australians DO NOT USE dont do it\n",
      "Date: June 03, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 2\n",
      "Title: Important information missing for me\n",
      "Date: May 23, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Account verification\n",
      "Date: May 23, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Worst customer service i have ever…\n",
      "Date: May 23, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 5\n",
      "Title: Faultless experience using Coinbase for 18 months…\n",
      "Date: May 21, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 2\n",
      "Title: Wouldn't recommend this platform.\n",
      "Date: April 29, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Arbitrary 60 Day Freeze - BEWARE **UPDATE** - EVEN WORSE!\n",
      "Date: May 27, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Scammer\n",
      "Date: May 18, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Opened an account to buy Bitcoin\n",
      "Date: May 10, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Poor Service. No response to Case enquiry.\n",
      "Date: May 20, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Worst cryptocurrency broker ever\n",
      "Date: May 16, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 5\n",
      "Title: User friendly\n",
      "Date: June 01, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: trading fees are an absolute joke and…\n",
      "Date: May 17, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 5\n",
      "Title: Smooth process no itching best service…\n",
      "Date: June 02, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Coinbase stole my money from my account…\n",
      "Date: April 26, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Steals Deceased Users' Crypto - Heartless and Unresponsive\n",
      "Date: May 30, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Worst company to deal with\n",
      "Date: May 31, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: My sister passed away in December and I…\n",
      "Date: May 24, 2024\n",
      "--------------------------------------------------\n",
      "Rating: 1\n",
      "Title: Devastating\n",
      "Date: May 27, 2024\n",
      "--------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.chrome.options import Options\n",
    "import os\n",
    "import requests\n",
    "\n",
    "options = Options()\n",
    "options.add_argument('--incognito')\n",
    "\n",
    "driver = webdriver.Chrome(options=options)\n",
    "\n",
    "base_url = 'https://www.trustpilot.com/review/coinbase.com?page='\n",
    "os.makedirs('trustpilot-coinbase-reviews', exist_ok=True)\n",
    "\n",
    "def download_image(url, save_path):\n",
    "    try:\n",
    "        response = requests.get(url, stream=True)\n",
    "        if response.status_code == 200:\n",
    "            with open(save_path, 'wb') as file:\n",
    "                for chunk in response.iter_content(1024):\n",
    "                    file.write(chunk)\n",
    "    except Exception as e:\n",
    "        print(f\"Failed {url}: {e}\")\n",
    "\n",
    "reviews = []\n",
    "for page in range(2, 3): # testing\n",
    "    url = f\"{base_url}{page}\"\n",
    "    driver.get(url)\n",
    "\n",
    "    driver.implicitly_wait(0.9)\n",
    "    reviews = driver.find_elements(By.CLASS_NAME, 'styles_reviewCardInner__EwDq2')\n",
    "    \n",
    "    for i, review in enumerate(reviews):\n",
    "        rating = review.find_element(By.CLASS_NAME, 'star-rating_starRating__4rrcf').find_element(By.TAG_NAME, 'img').get_attribute('alt')\n",
    "        rating = rating[6]\n",
    "        title = review.find_element(By.CLASS_NAME, 'typography_heading-s__f7029').text.strip()\n",
    "        date = review.find_element(By.CLASS_NAME, 'typography_body-m__xgxZ_.typography_appearance-default__AAY17').text.strip()\n",
    "        date = date.replace('Date of experience:', '').strip()\n",
    "\n",
    "            \n",
    "        print(\"Rating:\", rating)\n",
    "        print(\"Title:\", title)\n",
    "        print(\"Date:\", date)\n",
    "        print(\"-\" * 50)\n",
    "driver.quit()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.chrome.options import Options\n",
    "import csv\n",
    "from dateutil import parser\n",
    "\n",
    "\n",
    "options = Options()\n",
    "options.add_argument('--incognito')\n",
    "driver = webdriver.Chrome(options=options)\n",
    "\n",
    "base_url = 'https://www.trustpilot.com/review/coinbase.com?page='\n",
    "\n",
    "reviews_data = []\n",
    "try:\n",
    "    for page in range(1, 325): # full scraping\n",
    "        url = f\"{base_url}{page}\"\n",
    "        driver.get(url)\n",
    "\n",
    "        driver.implicitly_wait(0.6)\n",
    "        try:\n",
    "            reviews = driver.find_elements(By.CLASS_NAME, 'styles_reviewCardInner__EwDq2')\n",
    "        except Exception as e:\n",
    "            print(f\"!! PAGE EXCEPTION: {e}\")\n",
    "            continue        \n",
    "        for review in reviews:\n",
    "            try:\n",
    "                rating = review.find_element(By.CLASS_NAME, 'star-rating_starRating__4rrcf').find_element(By.TAG_NAME, 'img').get_attribute('alt')\n",
    "                rating = rating[6]\n",
    "                title = review.find_element(By.CLASS_NAME, 'typography_heading-s__f7029').text.strip()\n",
    "                date = review.find_element(By.CLASS_NAME, 'typography_body-m__xgxZ_.typography_appearance-default__AAY17').text.strip()\n",
    "                date = date.replace('Date of experience:', '').strip()\n",
    "                date = parser.parse(date).strftime('%Y-%m-%d')\n",
    "\n",
    "                reviews_data.append([date, title, rating])\n",
    "            except Exception as e:\n",
    "                print(f\"!! ATTRIBUTE EXCEPTION: {e}\")\n",
    "                continue\n",
    "finally:\n",
    "    driver.quit() # if uncaught except still uzdarom\n",
    "\n",
    "csv_file = 'trustpilot_coinbase_reviews-strip.csv'\n",
    "with open(csv_file, mode='w', newline='', encoding='UTF-8') as file:\n",
    "    writer = csv.writer(file, delimiter='|')\n",
    "    writer.writerow(['Date', 'Title', 'Rating'])\n",
    "    writer.writerows(reviews_data)\n",
    "\n",
    "print(f\"SAVED!\\n{csv_file}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Title</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2024-05-24</td>\n",
       "      <td>200k still locked. WHERE IS MY MONEY?</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2024-06-04</td>\n",
       "      <td>Dishonourable</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2024-05-28</td>\n",
       "      <td>Coinbase tried to remove my review</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2024-06-04</td>\n",
       "      <td>Entrée en matière grâce aux p2e games</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>Okay until you want your money back!</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date                                  Title  Rating\n",
       "0  2024-05-24  200k still locked. WHERE IS MY MONEY?     1.0\n",
       "1  2024-06-04                          Dishonourable     1.0\n",
       "2  2024-05-28     Coinbase tried to remove my review     1.0\n",
       "3  2024-06-04  Entrée en matière grâce aux p2e games     4.0\n",
       "4  2024-05-31   Okay until you want your money back!     1.0"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('trustpilot_coinbase_reviews-strip.csv', sep='|')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Title</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6475</th>\n",
       "      <td>2017-05-22</td>\n",
       "      <td>Very bad.I can't register any of my …</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6476</th>\n",
       "      <td>2017-05-19</td>\n",
       "      <td>Functional platform but seriously lacking in c...</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6477</th>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>No reservations.</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6478</th>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>I HOPE YOU SEE THIS BEFORE You send …</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6479</th>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>Coinbase - the rock star crypto app</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date                                              Title  Rating\n",
       "6475  2017-05-22              Very bad.I can't register any of my …     1.0\n",
       "6476  2017-05-19  Functional platform but seriously lacking in c...     3.0\n",
       "6477  2017-05-18                                   No reservations.     5.0\n",
       "6478  2017-05-18              I HOPE YOU SEE THIS BEFORE You send …     1.0\n",
       "6479  2017-05-16                Coinbase - the rock star crypto app     4.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total: 6480\n",
      "\n",
      "Rating\n",
      "1.0    5428\n",
      "5.0     364\n",
      "2.0     280\n",
      "3.0     233\n",
      "4.0     148\n",
      "Name: count, dtype: int64 \n",
      "\n",
      "Average: 1.4100418410041842\n"
     ]
    }
   ],
   "source": [
    "print(f'Total: {len(df)}\\n')\n",
    "print(df['Rating'].value_counts(), '\\n')\n",
    "print(f'Average: {df[\"Rating\"].mean()}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MGYOcnBwsXboUI0eORJcuXZCTk2N9rNlsBgAMGTIEEydOvOV/9erVq3R9li1bhmXLlmHlypX4+++/sWPHDvj6+uLPP//ESy+9VOLxU6dOxY4dO9C1a1ds3rwZV65cQUFBgbXO4eHhpdbZHqpyXW/VwVLWfTNmzMD58+exZMkSTJgwAVqtFt9++y3Gjx+PFi1a2G30VHGl5fXEE08AuNERdeHCBaxbtw4+Pj5ljlKqjDFjxsDX1xfLly/HZ599Bo1GU+aILnuqyX+fNXluIiKisvDdh4iISAHDhg2DRqNBRkYG1q1bV6nn1qlTB4Bl5EXxkUTFFY0SKnpsTTt79myZ9507dw6AZU2lIqtWrQIAfPfddxgxYgQiIiJsRtGcPHmyzPPVr18fM2bMwHfffYeLFy9i9+7daNq0KeLi4vDf//7X+rioqCgAlilRRR1IZf3Xo0ePKtW7uO7du+Pdd98FALz//vvWawBYRoZt2LABGo0GGzZswMCBAxEaGmpdGysnJweXL1+udhnsoajNFF230tzqvtq1a2PatGnWNb2OHj2Krl274vTp05g5c2aly1NW2yqtXRUZMmQImjZtim3btuHw4cNYvHgxTCYT7r///jJHF1aGt7c3xo4diwsXLmDfvn0YNGhQqeUoLjg4GB4eHgBg0zaKE/3vloiISGnslCIiIlJAo0aNcO+99wIAnn766XLXR0pOTsbx48cBWP4IL5rms2zZshKPlWXZerxv3772K/QtbN68udSpiBs2bEBaWhp8fX2to8MAWOtb2gilTZs2ITU1tcKv3bFjR0yfPh0AsG/fPuvxoUOHArjRASbClClT0LZtWxQUFGDu3LnW45mZmTCZTPDz80NAQECJ53311VdljpAq6qwrvj5STerZsyckScKePXtw4sSJEvcfOXKkxNS9W4mOjsbzzz8PwPb6VNSXX35Z6vEVK1YAsEzrvJkkSZgxYwYA4J133sFnn30GoHoLnN9s6tSpCA4ORnBwMKZNm1bu493c3Kydn6X9uwVuLJ5ur3+3otsOERFRZbFTioiISCEffPABGjdujLNnz6JHjx6lrjVUUFCAL774Au3atcPRo0etx5955hkAwKuvvmrTQSDLMubPn499+/YhICCgQn8s20Nubi4eeeQR5ObmWo8lJibi6aefBgA8/PDD8PT0tN5XtHjyBx98YHOe48eP4+GHHy71NX788Uf88ccf1ml5RQoLC/Hrr78CsO3kevDBB1GvXj18//33eP7552128ity+fLlSu9QeCuSJOH1118HAKxcudLaqVO7dm0EBgYiIyOjRCfL33//jVmzZpV5zqIROIcPH7ZbOW+lfv36GD58OMxmMx555BGb3DIzM/HII4+U2oH2+++/Y8OGDSgsLLQ5Lssyfv75ZwCld0KW58cff8S3335rc2z16tX44Ycf4ObmZu18utmkSZPg7++PL774AsnJyejbty9atGhR6dcvS5cuXZCamorU1FSMGjWqQs8p+vewaNEibNmyxea+ZcuWYd26dXB3d7dOP6wu0W2HiIiosrjQORERkUICAwOxc+dO3H333di2bRt69uyJBg0aoHXr1vDy8sKVK1ewe/duZGdnw8/PDxEREdbnPvTQQ9i1axe+/PJLxMTEoHfv3ggNDUVCQgKOHz8OvV6Pr7/+2rqgek2bMGECfv75ZzRs2BA9e/ZEXl4efv/9d+Tk5KBr1642o4YAYM6cObjrrrvw8ssvY9WqVWjZsiWSk5Px559/omfPnoiIiMCuXbtsnrN9+3a8//77qFWrFtq1a4fQ0FBcu3YNf//9N5KTk1GnTh0899xz1sd7e3vjl19+wbBhw/Df//4XS5YsQevWrREZGQmDwYATJ07g6NGjCA0NtWvn3dChQ9GrVy/88ccfmDt3LlauXAmtVovZs2fjqaeewoQJE/DRRx+hYcOG+Pfff7Fr1y6MHz8ef/zxB86fP1/ifKNHj8bSpUvx3HPPITY2FqGhoZAkCVOmTEG3bt3sVu7iFi1ahAMHDuD3339HgwYN0Lt3b8iyjO3btyM4OBh33nkn1q1bZzPl8sCBA3jqqafg5+eH9u3bIyIiArm5uUhISMD58+fh7++PefPmVbosTzzxBO6991688847aNKkiXVReQBYuHBhqTsBApbdFSdPnoz33nsPgH1HSVXV0KFD8dJLL2H+/PkYOHAgunfvjrp16+LYsWNISEiAVqvF4sWL0bJlS7u83uDBg+Ht7Y21a9eiR48eaNKkCbRaLbp3727doZOIiEhJHClFRESkoNDQUGzduhUbN260Lgy9ZcsWrF69GkeOHEHXrl3x3nvv4ezZs+jUqZP1eZIkYcWKFfj666/Ro0cP7NmzB6tXr4bBYMCkSZOwd+9e6/Q1ERo0aID4+Hj07dsXf/zxBzZt2oTw8HDMnj0bsbGx0Ov1No8fNWoUtm/fjv79+yMpKQnr1q1DcnIyXnnlFWzcuNG61lJxkyZNwsyZMxEdHY0jR47g+++/x19//YWoqCi8/vrr2L9/f4l1fVq2bIkDBw7gv//9L5o3b44DBw7g+++/xz///ANvb28888wz5e4AWBVvvPEGAODbb7+1jnB78sknsXbtWnTr1g3Hjx/H+vXrkZ+fj48++gjLly8v81x33HEHPv30U9x22234/fff8cUXX+Dzzz8vdWqdvURERGD37t149NFHodfr8fPPPyM+Ph733nsv/v77b2RnZwMAatWqZX3O8OHD8corr6Bjx444c+YM1qxZg23btsHf3x8zZ87EoUOH0LZt20qX5YknnsCqVavg5uaGdevW4dChQ+jZsyfWr1+Pp5566pbPHTx4MADL+mIjRoyo9GvXhFdffRUbN27E0KFDcfToUaxatQqJiYkYM2YMdu3ahSlTptjttWrXro2NGzdiwIABOHLkCFasWIHPP/8c27dvt9trEBERVYck18QWL0RERETkkjIyMtCwYUNkZmbiypUrNh1Tjmb8+PFYuXIlXn/99VtOkSQiIiJlcKQUEREREZWwe/fuEsdSUlIwceJEpKenY9iwYQ7dIXXw4EF899138PHxwUMPPaR0cYiIiKgUXFOKiIiIiEro3LkzIiMj0bx5cwQHB+PSpUvYu3cvsrOzUbduXXz44YdKF7FUU6dORU5ODjZu3Aij0YiXXnoJQUFBSheLiIiISsHpe0RERERUwssvv4wtW7bg9OnTSE9Ph06nQ6NGjTBs2DD85z//QXBwsNJFLJUkSdBoNIiKisLUqVPx4osvQpIkpYtFREREpWCnFBERERERERERCcc1pYiIiIiIiIiISDh2ShERERERERERkXBc6LyazGYzEhMT4evry/UKiIiIiIiIiEj1ZFnGtWvXEBERAY2m7PFQ7JSqpsTERERFRSldDCIiIiIiIiIih3LhwgVERkaWeT87parJ19cXgCVoPz8/hUtTdWazGUlJSQgPD79lLyZVH7MWh1mLw6zFYM7iMGtxmLU4zFocZi0GcxaHWYvjKllnZWUhKirK2mdSFnZKVVPRlD0/Pz+n7pQyGo3IzMxEkyZN4ObGZlGTmLU4zFocZi0GcxaHWYvDrMVh1uIwazGYszjMWhxXy7q8ZY6ct9uNiIiIiIiIiIicFjuliIiIiIiIiIhIOHZKEQBAo9EgJCTEqeesOgtmLQ6zFodZi8GcxWHW4jBrcZi1OMxaDOYsDrMWR21ZS7Isy0oXwpllZWXB398fmZmZTr2mFBEREREREamDyWRCYWGh0sUgJ+bu7g6tVlvm/RXtK3H+VbPILsxmM86ePYsGDRqopkdWKcxaHGYtDrMWgzmLw6zFYdbiMGtxmLUYzLnyZFnG5cuXkZGRUennGY1GuLm5lbtwNVWPM2UdEBCAsLCwapWTnVIEwPILPSUlBfXq1eMv9BrGrMVh1uIwazGYszjMWhxmLQ6zFodZi8GcK6+oQyo0NBReXl4V7kyQZRkGg6FSz6GqcYasi8qYnJwMAAgPD6/yudgpRUREREREROTiTCaTtUMqODi4Us+VZRkmkwmenp4O21HiKpwla71eDwBITk5GaGjoLafy3Qq7k4mIiIiIiIhcXNEaUl5eXgqXhFxFUVuqzvpk7JQiAJYV/iMjIznsVQBmLQ6zFodZi8GcxWHW4jBrcZi1OMxaDOZcNVUdfaPT6excEiqLs2Rtj5Fc/NdLAPgLXSRmLY6zZp1+6hR+e/hhLG/bFm+7uWHpbbdV+LnXLl3ChokT8VFICN7T6/FF8+Y4snKl9f6kuDj8OmUKPmvcGO95eeGzJk3wx6xZKMjJqVaZnTVrZ8OcxWHW4jBrcZi1OMxaDOYsjiRJ0Ol0Dj2dzFWoLWv+6yUAlvnFR48ehclkUrooLo9Zi+OsWacdPowzv/yCgMaNEdyiRYWfl52UhK+7dkVOYiIGLVmC//v5Z7R95BGY8vOtjzn+3XdIP3kSHZ97DqM2bECHJ5/EgSVL8OPw4dUqs7Nm7WyYszjMWhxmLQ6zFodZi8GcxZFlGbm5uZBlWemiOKw+ffrgySeftN6uX78+3nvvvUqfxx5Znzt3DpIkYd++fVU+hyhc6JwAWBp+ZmYmf8kIwKzFcdasGw0fjsYjRgAANk6ahMvx8RV63h/PPQffqCiM/vVXaK4vNFivf3+bx3R6/nl4hYRYb9ft0weegYH4Zdw4XN6zB2EdOlSpzM6atbNhzuIwa3GYtTjMWhxmLQZzFkvJzr8LFy5gzpw5+PXXX5Gamorw8HCMHDkSs2fPrvSi7Y7ilVdewdy5cwFYRv1FRERg6NChWLBgATw8PCp8nkmTJiEjIwNr1661HouKikJSUhJq1apl72LbHUdKERE5GKkKQ9Dzs7JwfNUqtJ0+3dohVZriHVJFQtu1AwDkJCZW+nWJiIiIiGrSmTNnEBMTg5MnT+Kbb77BqVOnsHjxYmzZsgVdu3bF1atXa/T1q7OId3latmyJpKQk/Pvvv1i6dCl+/fVXTJ8+vdrn1Wq1CAsLg5ub449DYqcUEZELuJKQAFNBATTu7vi2d2+84+6Oj8PCsP3552Eq54300o4dAICg6GgRRSUiIiIiqrBHH30UOp0OmzdvRu/evVG3bl0MHToUsbGxuHTpEl588UUAwAsvvIDOnTuXeH6bNm0wb9486+3PPvsMzZs3h6enJ6Kjo/Hxxx9b7yua9vbdd9+hd+/e8PT0xMqVK5GWloZ7770XderUgZeXF1q1aoVvvvmm2nVzc3NDWFgY6tSpgwEDBmDMmDH47bffrPebTCY88MADaNCgAfR6PZo1a4b333/fev8rr7yC5cuX46effoIkSZAkCdu2bSsxfW/btm2QJAlbtmxBTEwMvLy80K1bNxw/ftymPPPnz0doaCh8fX0xdepUzJw5E23btq12PW+FnVIEwDJcsGHDhlwkUABmLY6asjZcvgwA2Dx1KmrHxOCuzZvR4amnkPDee9g5e3bZz0tNxa5XXkHjESMQ2KRJlV9fTVkriTmLw6zFYdbiMGtxmLUYzFmsykwps5erV69i06ZNmD59OvR6vc19YWFhGDduHL777jvIsoxx48Zh9+7dOH36tPUxhw8fxoEDB3DfffcBAFauXInZs2fjtddew9GjR/H666/j5ZdfxvLly23OPXPmTDzxxBM4evQoBg8ejLy8PHTo0AG//PILDh06hAcffBD3338/du/ebbe6njt3Dps2bYJOp7NmbTabERkZie+//x5HjhzB7Nmz8cILL2DVqlUAgGeeeQZjx47FkCFDkJSUhKSkJHTr1q3M13jxxRfx9ttvIz4+Hm5ubpgyZYr1vpUrV+K1117Dm2++iT179qBu3bpYtGiR3epXFscfy0VCaDQahIaGKl0MVWDW4qgpa9lsBgDUGzAAfd9+GwBQt29fFF67hriFC9F19my43/RGbiosxM/33AMAGFDNNxw1Za0k5iwOsxaHWYvDrMVh1mIwZztJSrL8V1xgINCgAZCXBxw5AgmAe/H727e3/P/4ceDmXZzr1weCgoCUFODCBdv7fH2BSnwRevLkSciyjObNm5d6f/PmzZGeno6UlBS0bNkSbdq0wddff42XX34ZgKWjpXPnzmjcuDEAYM6cOXj77bcxatQoAECDBg1w5MgRfPLJJ5g4caL1vE8++aT1MUWeeeYZ688zZszApk2bsGrVKnTq1KnC9bnZwYMH4ePjA5PJhLy8PADAO++8A3d3S9ru7u7WdaeKyvvXX39h1apVGDt2LHx8fKDX65Gfn4+wsLByX++1115D7969AVg63u644w7k5eXB09MTH3zwAR544AFMnjwZADB79mxs3rwZ2dnZVa5fRbBLmQBYhgXu37+fO1cIwKzFUVPWHoGBAICofv1sjtft3x+m/HxknDplc1yWZWyaMgWXd+/GqA0b4BMeXq3XV1PWSmLO4jBrcZi1OMxaHGYtBnO2k08+ATp0sP3veqcOLl4seV/xjXEmTSp534YNlvtWrSp532OPVamIFV3Mfty4cfj666+tz/nmm28wbtw4AEBOTg5Onz6NBx54AD4+Ptb/5s+fbzO6CgBiYmJsbptMJrz66qto1aoVgoKC4OPjg02bNuHff/+tUn2KNGvWDPv27UNcXByef/55DB48GI899hgMBoO1zh999BE6dOiAkJAQ+Pj4YMmSJVV+3datW1t/Dr/++T85ORkAcPz48RIdbNXpcKsojpQiANziUyRmLY6asg5u0eKW9xuvf/NSZNszz+D4qlUYtWEDQtu0qfbrqylrJTFncZi1OMxaHGYtDrMWgznbyUMPAXfeaXvs+heeiIwE9uyxZq3X6yFJ0o3HLVtW+kgpABg7Fuja1fY+X99KFa1x48aQJAlHjx7F//3f/5W4/+jRowgMDETI9c187r33Xjz//PNISEhAbm4uLly4gLvvvhsArCN+Pv300xJrT2lv2ijI29vb5vZbb72F999/H++99x5atWoFb29vPPnkkygoKKhUfW6m0+mso7jeeOMN3HHHHZg7dy5mzpwJAPj222/xzDPP4O2330bXrl3h6+uLt956C//880+VXq9oBBYA63U0X59xoRR2ShERuQD/evVQq1Ur/Bsbi/bFvoE6/9tvcNPrbTqt/nnjDex5913csXIl6vXvX63XLSiUsS3BgB37cnDpcjA27L+KHm290ae9F3TuUvknICIiIiJlhYdb/iuNp6dlqp4sw5yTA3h7A8U7pZo1K/u8ISGW/6ohODgYAwcOxMcff4ynnnrKZl2py5cvY+XKlZgwYYK1gyUyMhK9e/fGypUrkZubi4EDB1qneNauXRsRERE4c+aMdfRURe3cuRMjRozA+PHjAVg6ck6cOIEW5XwxXFkvvfQS+vXrh4kTJ6Jx48bYuXMnunXrZrMj382junQ6nV1GCzZr1gxxcXGYMGGC9VhcXFy1z1sedkoRETmYQoMBZ64Pe846fx4FWVk4vno1ACCqd294hYRgVf/+yDp/HlOLTcvr+dpr+HHECPz+5JNoeMcduBwXh7iFC9Hpueegu/5tz9Gvv8afs2ahxfjx8G/QAIl//219fkCjRvCqxAeHnQcMeHN5GrJzZUgSIMseOJechx378/DhqquYOTEY3Vp72SMSIiIiIlKpDz/8EN26dcPgwYMxf/58NGjQAIcPH8azzz6LOnXq4LXXXrN5/Lhx4zBnzhwUFBTg3Xfftblv7ty5ePzxx+Hv748hQ4YgPz8f8fHxSE9Px3/+858yy9CkSROsXr0au3btQmBgIN555x1cuXLF7p1SXbt2RevWrbFw4UIsXrwYTZo0wYoVK7Bp0yY0aNAAX375JeLi4tCgQQPrc+rXr49Nmzbh+PHjCA4Ohr+/f5Vee8aMGZg2bRpiYmLQrVs3fPfddzhw4AAaNmxor+qVimtKEQDLcMXo6OgSwxbJ/pi1OM6atSE5GevHjMH6MWNwYds2XLtwwXo79fBhAIDZZILZaLR5XqPhwzHsm29wPjYWPw4bhgNLlqD73Lno/uqr1sec27wZAHDkq6/wddeuNv+d+eWXCpdx5wEDZn+Sipxcy3D5olHzRf/PyZXx8iep2HnAUNUYqBTO2qadEbMWh1mLw6zFYdZiMGexPD09FXndJk2aID4+Hg0bNsTYsWPRqFEjPPjgg+jbty/++usvBAUF2Tz+rrvuQlpaGgwGA0aOHGlz39SpU/HZZ59h6dKlaNWqFXr37o1ly5bZdPKU5qWXXkL79u0xePBg9OnTB2FhYSXObS9PPvkkli9fjgsXLuChhx7CqFGjcPfdd6Nz585IS0uzGTUFANOmTUOzZs0QExODkJAQ7Ny5s0qvO27cOMyaNQvPPPMM2rdvj7Nnz2LSpEk1ft0lmRNwqyUrKwv+/v7IzMyEn5+f0sUhIqpxBYUy7pp5ETm5Mm71BiIB8PaSsHpBJKfyERERESksLy8PZ8+eRYMGDRTrYCLnMnDgQISFheHLL78s9f5btamK9pVwpBQBAIxGI+Li4mC8aeQF2R+zFodZ14xtCQZkl9MhBQAygGyDjO0JHC1lL2zT4jBrcZi1OMxaHGYtBnMWR5Zl5OTkcFF5AZTK2mAw4J133sHhw4dx7NgxzJkzB7GxsZg4cWKNvi47pciKW6mKw6zFYdb2t3O/wWZ9y1uRJGDHfnZK2RPbtDjMWhxmLQ6zFodZi8GcxWGHlDhKZC1JEjZs2IBevXqhQ4cOWL9+PX744QcMGDCgRl+XC50TEVGlZOWYUdH3SVm2PJ6IiIiIiByXXq9HbGys8NflSCkiIqoUP29NpUZK+XnzrYaIiIiIiEriXwoEwLJzRevWrblzhQDMWhxmXTO6t/Gq1EipHm28arZAKsI2LQ6zFodZi8OsxWHWYjBnsfR6vdJFUA01Zc1OKbLS6XRKF0E1mLU4zNr++rT3go9eQnmDpSQAPl4Serdnp5Q9sU2Lw6zFYdbiMGtxmLUYzLnyzOaqLa2g0bD7QBRnybqqbak4rilFACwLBMbHxyMmJgZubmwWNYlZi8Osa4bOXcLMicF4aXHqLR8nA3ju/mDo3Cs414/KxTYtDrMWh1mLw6zFYdZiMOfK0el00Gg0SExMREhICHQ6HaQKrskgyzIMBgO8vLwq/ByqGmfIWpZlFBQUICUlBRqNplqdw/yXS0REldattReaRrnjxIVCAJa1o2T5xv+LHD9XwOl7RERERA5Ao9GgQYMGSEpKQmJiYqWeW9QJUZmOLKoaZ8ray8sLdevWrdbILnZKERFRpWVcM+HUJUuHlJ+XhFaNPZB4JRN1wvxRN0yHbzZnQZaBlZuy0LSeDj3bsmOKiIiISGk6nQ5169aF0WiEyWSq8POMRiMOHTqExo0bc1RaDXOWrLVaLdzc3Krdcea4NSQiIoe1dY8BRVPI7+jhi8nDfBAffwYxMQ3g5uYGfx8NFv2QAQB4c0Ua6oW5o26Yu3IFJiIiIiIAgCRJcHd3h7t7xT+bGY1GAICnp6dDd5S4ArVlLclyRfdQotJkZWXB398fmZmZ8PPzU7o4VSbLMkwmE7RarcMPEXR2zFocZl1zHv3vZRw9VwAA+PylMNQPd7fJWpZlzF+ahq3xBgBAVG03fPxcGLz1zrFoo6NimxaHWYvDrMVh1uIwazGYszjMWhxXybqifSX864CsCgoKlC6CajBrcZi1/V1KLrR2SDWKdEeDCMvChsWzliQJz4wLQsMIyzdwF64Y8caKNJjN/B6kutimxWHW4jBrcZi1OMxaDOYsDrMWR01Zs1OKAFh2rjhw4ECl5hVT1TBrcZh1zYiNM1h/HtDRG0DpWes9NJj7UC346C3f8Ozcn4uvN2WJLayLYZsWh1mLw6zFYdbiMGsxmLM4zFoctWXNTikiIqowWZYRuzsHgGWnvX4db72AeZ0Qd7w4pRaKRh4v/TkTuw/n1nQxiYiIiIjICbBTioiIKuzY+QJcSrEsvti2qQdCAspffLFzSz0mDfMHAMgy8NrSNCSmGmu0nERERERE5PjYKUVWWq1W6SKoBrMWh1nbV9EoKQAY0Mnb5r5bZT1usB+6tdYDAK4ZzJj9SQpy8801U0gXxzYtDrMWh1mLw6zFYdZiMGdxmLU4asqau+9Vk6vsvkdEVB6jScbYWZeQkW2Gzl3C6jfqwKcSu+ll55ox/c3LuJhsGSXVL8YLL04OdupdRYiIiIiIqCTuvkeVIssyMjIywD7KmsesxWHW9rXnWB4ysi2jm7q20tt0SFUkax+9Bq8+FAK9h6UT6vd4A37Yeq1mC+1i2KbFYdbiMGtxmLU4zFoM5iwOsxZHbVmzU4oAWFb4P3bsmGpW+FcSsxaHWduX7dQ92wXOK5p1vXB3PD8h2Hp78ZoM7DuRZ9+CujC2aXGYtTjMWhxmLQ6zFoM5i8OsxVFb1uyUIiKicuXmmbFzv2XXPD9vDTq10Ff5XL3aeeHeQZYhvGYzMO+zVCRf5cLnRERERERqw04pIiIq1479ucgrsAwh7t3eC+5u1VsHasqd/ohp7gkAyMg2Y86nqSgoVMcQZSIiIiIismCnFAEAJEmCXq/ngsMCMGtxmLX9xMbdmLo38KZd94DKZ63VSHhxcjDCgi07ixw/X4D/fXdVNXPnq4ptWhxmLQ6zFodZi8OsxWDO4jBrcdSWNXffqybuvkdEru5qpgljX7gEswyEBWuxcl6E3d4kT10owIyFV5B/fZTUf+4LwrAePnY5NxERERERKYO771GlmM1mJCcnw2w2K10Ul8esxWHW9rF1Tw7M17++6N/Ru9QOqapm3ThKh//cF2S9/b/vruLI2fxqldeVsU2Lw6zFYdbiMGtxmLUYzFkcZi2O2rJmpxQBsDT8M2fOqKbhK4lZi8Os7SN2t8H684COJafuAdXLemBnb4zqYxkdZTQBc5ak4mqmOnYbqSy2aXGYtTjMWhxmLQ6zFoM5i8OsxVFb1uyUIiKiMv17pRDH/y0AADStq0O9cPcaeZ2HRweidWMPAEBapglzP0+F0cTZ5UREREREroydUkREVKYtu28scN6/o1eNvY6bVsLsqbVQK8Cy8PnBU/lY9EN6jb0eEREREREpj51SBMCywr+/v79qVvhXErMWh1lXjyzLiL3eKaWRgH4xpU/dA+yTdZCfFnOn1YK7m+X2j9uysfmfnFs/SWXYpsVh1uIwa3GYtTjMWgzmLA6zFkdtWXP3vWri7ntE5KoOnc7H429fAQB0iPbEW4+HCnndn3dk452vrwIAdO4SPnimNppE6YS8NhERERERVR9336NKMZvNuHjxomoWU1MSsxaHWVfPlrgbo5QGdrr11D17Zj2shw9u724ZlVVQKGPOkhRkZnPhc4BtWiRmLQ6zFodZi8OsxWDO4jBrcdSWNTulCID6Gr6SmLU4zLrqCo0ytu6x7Lrn4S6hR1txnVIA8PjYIETXt4yOupxmwvwv0mAyc2Av27Q4zFocZi0OsxaHWYvBnMVh1uKoLWt2ShERUQlxR3KRlWN5I+zWRg8vT7FvFzp3CXOn1UKgr+V19xzLw+frMoWWgYiIiIiIapZDdkplZ2djzpw5GDJkCIKCgiBJEpYtW1apc8TGxqJfv37w9/eHr68vOnTogO+++67E49atW4f27dvD09MTdevWxZw5c2A0Gu1UEyIi57QlzmD9eWDHshc4r0khgW6Y/UAtaK6/U327OQt/7DXc+klEREREROQ0HLJTKjU1FfPmzcPRo0fRpk2bSj9/6dKlGDRoENzd3fH666/jrbfeQq9evXDhwgWbx23cuBEjR45EQEAAPvjgA4wcORLz58/HjBkz7FUVp6HRaBASEgKNxiGbhEth1uIw66rJyTVj54FcAIC/jwYxLTzLfU5NZd2mqSceGRVgvf3mijScSyq062s4E7ZpcZi1OMxaHGYtDrMWgzmLw6zFUVvWDrn7Xn5+PtLT0xEWFob4+Hh07NgRS5cuxaRJk8p97rlz59CiRQtMmzYN77///i0f27JlS7i7uyM+Ph5ubpY9yF966SW8/vrrOHLkCKKjo8t9Pe6+R0Su5te/svHfLy27343o7YMn7g5StDyyLOP1ZWnW0VuRoW74+Pkw+OjV8UZNRERERORsnHr3PQ8PD4SFhVXpuYsXL4bJZMK8efMAWKYCltbvduTIERw5cgQPPvigtUMKAKZPnw5ZlrF69eqqFd5Jmc1mnD59WjWLqSmJWYvDrKvGZupep4pN3avJrCVJwtPjgtAo0h0AcDHZiAXL0mBW4cLnbNPiMGtxmLU4zFocZi0GcxaHWYujtqwdslOqOmJjYxEdHY0NGzYgMjISvr6+CA4Oxssvv2xzUffu3QsAiImJsXl+REQEIiMjrferhdlsRkpKimoavpKYtTjMuvJSM4xIOJ4HAIgIcUPz6zvglaems/bUaTD3wRD4elnetv46mIuvfs2qkddyZGzT4jBrcZi1OMxaHGYtBnMWh1mLo7as3cp/iHM5efIktFotJk+ejOeeew5t2rTBmjVrMH/+fBiNRixYsAAAkJSUBAAIDw8vcY7w8HAkJiaWev78/Hzk5+dbb2dlWf4oMhqN1gXSNRoNNBoNzGazTUMqOm4ymWxGb5V1XKvVQpKkEguva7VaAIDJZKrQcTc3N8iybHNckiRotVprGYte22Qywc3NrcyyO1OdyjuuVJ1kWS5Rdmevk6Nep+Lt2lXqVNPXKXZ3NopeYkBHrwrXtehns9lsUx571ik8WItZEwPw4uKrkGVg+S+ZaBLlji636VV1nYrXy1Xq5IjXqej+sn5nO2Odyiu7UnUCUOL8zl4nR71O/LzHz3uuep2KXtuV6lS8jI5Qp+LlcpU6FS+jo9XJFT7vVXQDOZfrlMrOzobZbMYbb7yB559/HgAwevRoXL16Fe+//z5eeOEF+Pr6IjfXsoivh4dHiXN4enpaO5tutmDBAsydO7fE8b1798Lb2zLNJSQkBI0aNcLZs2eRkpJifUxkZCQiIyNx4sQJZGbe2Nq8YcOGCA0NxaFDh6zlAoDo6GgEBARg7969Nhe8devW0Ol0iI+PtylDTEwMCgoKcODAAesxrVaLjh07IjMzE8eOHbMe1+v1aNOmDVJTU3HmzBnIsoyMjAycOnUKLVu2RGJiIi5evGh9vDPWqYi/vz+aN2/uMHVq164dzGYzEhISIEmSS9TJUa+TwWBARkYGEhIS0Lx5c5eoU01fp5//qAXAMjqqf0fvCtcpODgYAHD+/HmkpaXVWJ2QcwgD2/pg814/yDLw+rI0vPtEAFITD6viOmVlZVnbtCRJLlEnR71ORe+LeXl50Ov1LlEnR71OYWFhyMnJsXlfdPY6Oep14uc9ft5ztet05MgRm/dFV6iTo14nWZat5XKVOgGOeZ1c5fNeTk4OKsIhFzovrrILnfv4+CAnJwfnz59H3bp1rcdXrFiBiRMnYvv27ejVqxcWLlyIZ599Fv/++y+ioqJsztGpUydotVr89ddfJc5f2kipqKgopKWlWRfvcpSeySIV6UE2m824fPkywsPD4e7u7rC9rZWpU3nHlaqTJElITExE7dq1rd8QO3udHPU6mUwmXL58GWFhYXB3d3eJOtXkdTp9MQ8PLrC8cUXXc8fHz4dXuE4ArFkXVxN1kmUZ8z5Px84DlmmGDSLc8d5TwdB7uP6/J5PJhEuXLiEsLAwajcYl6uSo16nofbFOnTrWxzt7ncoru5IjpS5evGht165QJ0e9Tvy8x897rnadCgsLkZSUZP394Qp1ctTrVPT7IzIy0nrb2etUvIyOdJ1c5fNeVlYWgoODy13o3OU6pZo2bYqTJ08iLy/PZhTUr7/+iqFDh2Lt2rUYMWIEVq5cifHjx+Off/5Bp06dbM4RFRWFTp064Ycffij39bj7HhG5is9+ysDXmyyjRB8bE4hRfX0VLlHZcnLNePS/l/HvFcubZJ/2Xnj5gWDrt9FERERERKQcp959rzo6dOgAALh06ZLN8aI1okJCQgAAbdu2BYASQ86Khr4V3a8WJpMJR48eLdHbSfbHrMVh1hVnNsvYEmcZYqvRAH06eFXq+aKz9tZrMO/hEHh5WjqhtiUYsCr2mpDXVhLbtDjMWhxmLQ6zFodZi8GcxWHW4qgta6fulEpKSsKxY8dQWFhoPXb33XcDAD7//HPrMbPZjKVLlyIoKMjaadWyZUtER0djyZIlNhd70aJFkCQJd911l6BaOAZZlpGZmQkHHzjnEpi1OMy64g6dyceVq5bfhTHNPRHkp63U85XIum5td8yaGGy9/enaDOvOga6KbVocZi0OsxaHWYvDrMVgzuIwa3HUlrXDLnT+4YcfIiMjwzrCaf369dbFu2bMmAF/f3/MmjULy5cvx9mzZ1G/fn0AwIgRI9C/f38sWLAAqampaNOmDdauXYsdO3bgk08+sZnS99Zbb+HOO+/EoEGDcM899+DQoUP48MMPMXXqVDRv3lx4nYmIlBK722D9eUBHbwVLUjnd23hh/FA/fLUxC2YZePXzVCyeGYbaQQ779kZERERERNc57Kf2hQsX4vz589bba9aswZo1awAA48ePh7+/f6nPkyQJa9euxUsvvYTvvvsOy5YtQ7NmzfDVV19h3LhxNo8dNmwY1qxZg7lz52LGjBkICQnBCy+8gNmzZ9dcxYiIHExBoYztCZZOKU8PCd3b6BUuUeVMvMMfJ84XYPeRPGRmmzFnSSre/08oPHROPRiYiIiIiMjlOfxC547OVRY6N5vNSE1NRa1atWx2CCH7Y9biMOuK2bHPgNlLUgEAAzp54YVJtSp9DqWzvmYw4+E3LiMp1bLw+eAu3nju/iCXW/hc6ZzVhFmLw6zFYdbiMGsxmLM4zFocV8latQudU9VoNBqEhoY6daN3FsxaHGZdMbHXFzgHqj51T+msfb00mPdgLXjqLJ1Qm/7Owbo/sxUpS01SOmc1YdbiMGtxmLU4zFoM5iwOsxZHbVmro5ZULpPJhP3796tmhX8lMWtxmHX5sg1m/HUwFwAQ6KtBh2jPKp3HEbJuFKnDM+ODrLc/+j4dh07nK1aemuAIOasFsxaHWYvDrMVh1mIwZ3GYtThqy5qdUgTAssJ/bm6ualb4VxKzFodZl++PvQYUWma8oW+MN7Taqk13c5Ss+8V4Y0x/XwCA0QS88mkK0jJd5w3dUXJWA2YtDrMWh1mLw6zFYM7iMGtx1JY1O6WIiFQsdnfxqXteCpbEfh4cGYC2TSw7rV7NMuOVT1NQaFTHmzoRERERkTNhpxQRkUolXzVi/ynL9LbIUDc0q6dTuET2odVKeHlqLYQEaAEAh88U4OPV6QqXioiIiIiIbsZOKQIAaLVaREdHQ6vVKl0Ul8esxWHWt/Z7vAFFo4IHdvKu1k51jpZ1oK8Wcx+sBXc3y+2f/sjGr385/8LnjpazK2PW4jBrcZi1OMxaDOYsDrMWR21Zs1OKAACSJCEgIMDltk93RMxaHGZ9a8Wn7vWr5tQ9R8w6ur4HnrznxsLn735zFSf+LVCwRNXniDm7KmYtDrMWh1mLw6zFYM7iMGtx1JY1O6UIAGA0GhEXFwej0ah0UVwesxaHWZft9MUCnEksBAC0aKBDnRD3ap3PUbMe2s0Hw3v4AAAKjcDsJSnIuOa8C587as6uiFmLw6zFYdbiMGsxmLM4zFoctWXNTimyUsuWk46AWYvDrEu3Je7GKKmBnbztck5HzfrRMYFo0cCyXlbyVRNe/SIVJpPzLnzuqDm7ImYtDrMWh1mLw6zFYM7iMGtx1JQ1O6WIiFTGbJaxJc4AANBqgD4dXGPXvbLo3CW8Mq0WAv0sb3l7j+fj058ylC0UERERERGxU4qISG0OnMpHSobl25eOLTzh7+P6iyjWCnDDK1NrQXv9XW9V7DVs25Nz6ycREREREVGNkmRZdt45DA4gKysL/v7+yMzMhJ+fn9LFqTJZlpGbmwu9Xq+aBdWUwqzFYdalW/hVGjbssnTIvDwlGH1jqj99z1my/nHbNXywKh0A4Okh4aNna6NBhE7hUlWcs+TsCpi1OMxaHGYtDrMWgzmLw6zFcZWsK9pXwpFSZKXTOc8fZs6OWYvDrG0VFMrYvtcydU/vIaFra73dzu0MWY/s7YOBnSzTFfPyZcz+JBXZBrPCpaocZ8jZVTBrcZi1OMxaHGYtBnMWh1mLo6as2SlFACwLqcXHx6tqQTWlMGtxmHVJfx/KRU6uZYBsr3Ze8NTZ523AWbKWJAn/uS8IjaMsuw1eSjHitaWpMJudY9Cws+TsCpi1OMxaHGYtDrMWgzmLw6zFUVvW7JQiIlKR33bfWEdpgJ123XM2HjoN5j0YAj9vy1vgP4fzsGJDpsKlIiIiIiJSH3ZKERGpRFaOCbsP5wIAgv21aNvUQ+ESKScs2A0vP1ALmuvT9FdsyMKuAwZlC0VEREREpDLslCIiUok/9uai0Gj5uV+MF7Qa51040R46RHti6ogA6+0Fy9Jw4UqhcgUiIiIiIlIZ7r5XTa60+57JZIJWq3XqFf6dAbMWh1nbeuKdKzh4Kh8A8MmsMDSJst8Cis6atSzLmPtZKv7YaxlBVi/cHR89Wxteno75nY2z5uyMmLU4zFocZi0OsxaDOYvDrMVxlay5+x5VWkFBgdJFUA1mLQ6ztricZrR2SNULc0PjSHe7v4YzZi1JEp67Pxj1wi15nE8qxH+/TIMjf1/jjDk7K2YtDrMWh1mLw6zFYM7iMGtx1JQ1O6UIgGWF/wMHDqhmhX8lMWtxmPUNv8fZLnBu729dnDlrL08N5j1YC96elkz+2JuLb3+7pnCpSufMOTsbZi0OsxaHWYvDrMVgzuIwa3HUljU7pYiIXJwsy/gt7sYi3v07qnPXvVuJqu2OFybXst7+/KcMxB/NVbBERERERESuj51SREQu7vTFQpxPsizg3aqRB8KC3RQukWPq2kqPCbdb5rubZWD+F2m4nGZUuFRERERERK6LnVJkpdVqlS6CajBrcZg18Nvu4lP3vGrsdVwh6wm3+6PLbZ4AgKwcM2YvSUF+gVnhUtlyhZydBbMWh1mLw6zFYdZiMGdxmLU4asqau+9Vk6vsvkdErslklnHPi4lIyzTBTQusfqMO/LzV8yZXFdkGMx558zIupVhGSQ3s5IWZE4OdevcTIiIiIiKRuPseVYosy8jIyHDoHadcBbMWh1kD+0/kIy3Tskhi55b6GuuQcqWsfbw0mPdQLXh6WDqhftttwI/bshUulYUr5ezomLU4zFocZi0OsxaDOYvDrMVRW9bslCIAlhX+jx07ppoV/pXErMVh1jdP3au5Bc5dLesGETo8Nz7IenvRD+k4cCpPwRJZuFrOjoxZi8OsxWHW4jBrMZizOMxaHLVlzU4pIiIXlV9gxp/7LLvueXtK6NpKr3CJnEufDt64e4AvAMBkBuZ+loqUDC58TkRERERkL+yUIiJyUX8dzIUhzzLst1c7L+jcuSZSZU0dEYD2zTwAAOlZZsz9NBUFheoYSk1EREREVNPYKUUAAEmSoNfruZCvAMxaHLVn/dtug/Xnmpy6B7hu1lqthJcfqIXQIMtaXEfOFuCj79MVK4+r5uyImLU4zFocZi0OsxaDOYvDrMVRW9bcfa+auPseETmizGwT7pp5CSYzUCtAi2/nR0CjUccbW0048W8BZiy8jMLrs/eeGReE27v7KFsoIiIiIiIHxd33qFLMZjOSk5NhNpuVLorLY9biqDnrbQkGmK5Xu3+MV413SLl61k3r6vCf+24sfP7+d1dx9Fy+8HK4es6OhFmLw6zFYdbiMGsxmLM4zFoctWXNTikCYGn4Z86cUU3DVxKzFkfNWccK2nWviBqyHtzFByN6W0ZHFRqBV5akIv2a2F1R1JCzo2DW4jBrcZi1OMxaDOYsDrMWR21Zs1OKiMjFJKYacfhMAQCgQYQ7GkXqFC6R65g+OhC3NbIsfJ6SYcKrn6XCZOIseCIiIiKiqmCnFBGRi9kSJ3aUlJq4u0mYM7UWgv0tC5/vO5mPT37MULZQREREREROip1SBMCywr+/v79qVvhXErMWR41Zy7JsM3Wvf4yXkNdVU9bB/lrMmVoLbpZ+Kaz+/ZpNR2BNUlPOSmPW4jBrcZi1OMxaDOYsDrMWR21Zc/e9auLue0TkSI6fz8cjb14BALRp4oF3n6qtcIlc109/XMP736YDADzcJXz4bG1OlSQiIiIiAnffo0oym824ePGiahZTUxKzFkeNWcfGGaw/i5y6p8as7+zpgyFdLRnnF8qYvSQVWTk1u/C5GnNWCrMWh1mLw6zFYdZiMGdxmLU4asuanVIEQH0NX0nMWhy1ZW0yyfg93jKNzN0N6N1OzNQ9QH1ZA5ah1U/eE4SmdS2jo5JSjXh9aRpM5pobgKzGnJXCrMVh1uIwa3GYtRjMWRxmLY7asmanFBGRi0g4nof0LMubV5fb9PDx4q/4mqZzlzD3wVrw97FkvftIHpb9nKlwqYiIiIiInAP/YiEichHFFzjnrnvi1A5yw8sP1ILm+lqUK3/Nwo59hls/iYiIiIiI2ClFFhqNBiEhIdBo2CRqGrMWR01Z5+ab8ef+XACAj15C55Z6oa+vpqxL076ZJx78vwDr7TdWpOHfy4V2fx215ywSsxaHWYvDrMVh1mIwZ3GYtThqy5q771UTd98jIkewJS4Hry1NAwDc0d0bT48LVrhE6iPLMuZ/kYateyyjpOrWdsNHz4XBW6+ODxREREREREW4+x5VitlsxunTp1WzmJqSmLU4aspa6al7asq6LJIk4ZnxQWgQ4Q4A+PeKEW+uSIPZjgufM2dxmLU4zFocZi0OsxaDOYvDrMVRW9bslCIAloafkpKimoavJGYtjlqyTr9mQtzRPABAaJAWrRp5CC+DWrIuj95Dg3kP1oKP3rLA1I79ufhmc5bdzs+cxWHW4jBrcZi1OMxaDOYsDrMWR21Zs1OKiMjJbY03oOg9q3+MNzRFK26TIuqEuuOFybUgXb8MX6zPRNyRXGULRURERETkgNgpRUTk5LbEFZ+656VgSahIl9v0mHSHPwBAloH5X6QhMdWocKmIiIiIiBwLO6UIgGWF/8jISNWs8K8kZi2OGrK+mFyIo+cKAACNI93RIEKnSDnUkHVljRvih26tLbsgXjOYMWdJCvIKqjcMmzmLw6zFYdbiMGtxmLUYzFkcZi2O2rLm7nvVxN33iEhJy37OwIoNljWLHvq/ANw9kL+HHEl2rhnT37yMi8mWUVL9O3rhhUnBkCROsSQiIiIi18Xd96hSTCYTjh49CpPJpHRRXB6zFsfVs5ZlGVviDAAASQL6dVRu6p6rZ11VPnoN5j0UAr2HpRNqS5wBP2y9VuXzMWdxmLU4zFocZi0OsxaDOYvDrMVRW9bslCIAlj9uMzMzwYFzNY9Zi+PqWR87V4BLKZYROO2aeiAkwE2xsrh61tVRP9wdz08Itt5evCYD+0/kVelczFkcZi0OsxaHWYvDrMVgzuIwa3HUljU7pYiInNRvu28scN6/k7eCJaHy9GrnhXsHWYYtm83AvM9TkZLOhc+JiIiISN3YKUVE5ISMJhnb9lim7uncJfRsy133HN2UO/3RIdoTAJB+zYw5n6aioFAd34AREREREZWGnVIEwLLCf8OGDVWzwr+SmLU4rpx1/NE8ZGRbdnLr1koPH72ydXTlrO1Fq5Hw0pRghAVrAVimX/5v1dVKnYM5i8OsxWHW4jBrcZi1GMxZHGYtjtqyVkctqVwajQahoaGqafhKYtbiuHLWsTZT95QfJeXKWduTv48Wcx8Mgc7dsvD5hp05+HlHdoWfz5zFYdbiMGtxmLU4zFoM5iwOsxZHbVmro5ZULpPJhP3796tmhX8lMWtxXDVrQ54ZO/fnAgD8vDXo1EKvcIlcN+ua0CRKh6fvC7Le/t93V3HkbH6FnsucxWHW4jBrcZi1OMxaDOYsDrMWR21Zs1OKAFhW+M/NzVXNCv9KYtbiuGrWO/bnIv/6WkR92nvB3U1SuESum3VNGdjZG6P6+AAAjCbglU9TcTWr/A8ezFkcZi0OsxaHWYvDrMVgzuIwa3HUlrVy+4cTEVGVFJ+6N4C77lVL+qlTiF+4EIl//43UQ4cQFB2NyYcOlfu8JfXrI+v8+RLHn8zNhZunZTHzf7dtw6q+fUs8ptndd2P4t9/i4dGBOHmxEAdP5SM1w4S5n6Xi7SdC4aZVvpORiIiIiEgEdkoRETmRq5kmJBzLAwCEBWvRsqFO4RI5t7TDh3Hml18Q1rkzZLMZstlc4ec2vesuxDz9tM0xrYdHiccNWboUQdHR1tv6WrUAAG5aCXMeqIWH3riMtEwTDp7Kx+If0vHY2KAS5yAiIiIickXslCIAgFarRXR0NLRardJFcXnMWhxXzPr3PTkwXx/JO6CTNyTJMUbVOGvWjYYPR+MRIwAAGydNwuX4+Ao/16t2bUR06VLu42rddhvCYmJKvS/IX4u5D9bCk+9cgdEErNmWjWb1PDCwc+kj4Jw1Z2fErMVh1uIwa3GYtRjMWRxmLY7asuaaUgQAkCQJAQEBDvMHritj1uK4YtZbdhusPw/o6DhT95w1a8kBdjVp0cADj999Y3TU219fxckLBaU+1llzdkbMWhxmLQ6zFodZi8GcxWHW4qgta+U/jZNDMBqNiIuLg9FoVLooLo9Zi+NqWf97uRDH/7V0VjStq0PdMHeFS3SDq2VdEUdXrsS7Hh5438cHP9x+O1IOHiz1cT/cfjve1mqxODIS2559FoW5uSUeM6yHD27vbulkLCiUMWdJCjKzSy58rsaclcKsxWHW4jBrcZi1GMxZHGYtjtqy5vQ9slLLlpOOgFmL40pZx8YVX+DcS8GSlM6Vsi5PozvvRHjnzvCrWxcZZ87gn9dewzc9emDC3r0IaNgQAODh74+Ozz2HyF694K7X49/ff0fcwoW4evQoRv38c4lzPj42CKcvFuL4+QJcTjPhtaVpWPBoCLQa22/J1JSz0pi1OMxaHGYtDrMWgzmLw6zFUVPW7JQiInICsixjy/Vd9zQS0K+D40zdU6P+//uf9efInj1Rf9AgfBEdjbiFCzHw448BALXbtUPtdu2sj6vbrx+8w8Ox5bHHkLR7N8I7dbI5p85dwtxptfDwG5eRkW1G/NE8fLEuE9NGBgipExERERGRaJy+R0TkBA6fKUBSmuUbk/bRngjyV8fCh87CJzwcdXr0wJU9e275uGZjxwJAmY8LDXLDnKm1ULTU1Tebs/DHXkOpjyUiIiIicnbslCIAlhX+W7durZoV/pXErMVxpaxjdxefuud4o6RcKWultWnqiYdHBVhvv7kiDeeSCgEwZ5GYtTjMWhxmLQ6zFoM5i8OsxVFb1g7ZKZWdnY05c+ZgyJAhCAoKgiRJWLZsWYWeu2zZMkiSVOp/ly9ftnls/fr1S33cww8/XAO1cnw6nU7pIqgGsxbHFbIuNMrYlmAZLePhLqFHG73CJSqdK2RdVdmJibi0YwfCOna85eOOffstAJT7uNF9fdG/o2XdsNx8GS8vTsb6P6/hlU9T8cLiLLzyaSo2/5ODgkLZPhWgUqm5TYvGrMVh1uIwazGYszjMWhw1Ze2Qa0qlpqZi3rx5qFu3Ltq0aYNt27ZV+hzz5s1DgwYNbI4FBASUeFzbtm3x9NNP2xxr2rRppV/P2ZlMJsTHxyMmJgZubg7ZLFwGsxbHVbKOO5KLrBwzAKB7Gz28PB3v+wRnzbrQYMCZDRsAAFnnz6MgKwvHV68GAET17g2vkBCs6t8fWefPY+qpUwCAo998gzM//4wGt98On4gIZJ45g38WLIBGq0VMsfeTX8aPR0Djxqjdvj3cPD3x7++/Y8+776LxyJEIi4m5ZbkkScLT44JwNrEQZy4V4lKKCe9+kw5JAmQZkCTgz325+HDVVcycGIxurR1v4Xtn56xt2hkxa3GYtTjMWgzmLA6zFkdtWTtkDcPDw5GUlISwsDDEx8ejYznfKJdm6NChiCnnQz8A1KlTB+PHj69KMYmIhIjdfWNNoQEdHW/qnjMzJCdj/ZgxNseKbo/duhV1+/SB2WSCudiWvP4NGiA7MRFbn3wS+RkZ8AgIQN1+/dB93jwEFPsypFbLljiyciXi334bpvx8+DdogM4vvIDOs2ZVqGyeOg1G9PbFu19ftR6TZdv/5+TKePmTVMx7qBa6s2OKiIiIiJyMQ3ZKeXh4ICwsrNrnuXbtGry8vMqdi1lQUIDCwkJ4e/OPPSJyLDm5Zuw6mAsA8PfRIKaFp8Ilci3+9evjGfnWU+DuuWm0bkSXLrh769Zyz9151qwKd0CVpqBQxqc/pt/yMTIASbasO7V6gR46d6nKr0dEREREJJrjzQGxk759+8LPzw9eXl648847cfLkyVIf9/vvv8PLyws+Pj6oX78+3n//fcElJSIq25/7DNZ1g/p28IKblp0OarEtwYDs3PLXjJIBZBtkbE/gLn1ERERE5FwccqRUdXh5eWHSpEnWTqk9e/bgnXfeQbdu3ZCQkICoqCjrY1u3bo0ePXqgWbNmSEtLw7Jly/Dkk08iMTERb775Zqnnz8/PR35+vvV2VlYWAMBoNMJ4fXqHRqOBRqOB2WyG2Wy2PrbouMlkglzsm/myjmu1WkiSZD1v8eOAZa5pRY67ublBlmWb45IkQavVWssoyzLatWtnvb+ssjtTnco7rlSdNBoNOnToAFmWbZ7jzHVy5OvUrl07yLIMWZadsk6//ZNtvb9vB71N+R3pOkmShJiYmBLlUXPbq26dduzLsa4hVR7LGlM56NvBw6Hr5EzXqej3h0ajKVFGZ61TeWVXqk5ardb6u/rmz1LOWidHvU78vMfPe652nQDY/P5whTo56nWSZRnt27e/ZV2drU7Fy+hIddJoNDbt2lnrdPPzyuJynVJjx47F2LFjrbdHjhyJwYMHo1evXnjttdewePFi633r1q2zee7kyZMxdOhQvPPOO5gxYwYiIyNLnH/BggWYO3duieN79+61Tv8LCQlBo0aNcPbsWaSkpFgfExkZicjISJw4cQKZmZnW4w0bNkRoaCgOHTqE3Nxc6/Ho6GgEBARg7969Nhe8devW0Ol0iI+PtylDTEwMCgoKcODAAesxrVaLjh07IjMzE8eOHbMe1+v1aNOmDVJTU3HmzBkAlsYTFBSE5s2bIzExERcvXrQ+3lnrBAD+/v4OVacOHTogKyvLZvSes9fJka+TyWSCVqt1yjplGTTYd6I2AAkRIW4wZZ9AfLzjXqei9QDZ9uxTp0uXMyHLHqgIWQYuXc5EfPwZh66Ts10nk8mEtm3bwsPDw2XqBDjedapTpw6OHz8Og+HGaD9nr5MjXyd+3hNTJ37eE1Onw4cPIzs72/rHsCvUyZGvU0BAAJo1a+ZSdXLU63TkyBFru3bWOuXk5KAiJLl4V5gDKlrofOnSpZg0aVKVz9O1a1ekpKTg1PXdk8qyadMmDBkyBF9++WWpC6CXNlIqKioKaWlp8PPzA+A4PZNFKtKDbDKZkJCQgPbt28PDw8Nhe1srU6fyjitVJ1mWER8fb/2mwRXq5KjXyWg0Wtu1Tqdzujqt/j0bS9ZaRmNOuN0P9w/1ddjrZDabrVkXfXNZWp3KO+5IdVL639OcJSnYeSCvwiOlurf2xOwHghy6Ts50nYreF4t2vnGFOpVXdqXqZDabERcXZ/O+6Ox1ctTrxM97/LznatcpPz/f2qa1Wq1L1MlRr1PR74+OHTta6+XsdSpeRke6ToWFhTa/P5y1TllZWQgODkZmZqa1r6Q0LjdSqixRUVE4fvx4hR4HAFevXi31fg8PD3h4lPzm2s3NrcR2jUUX92bF35gqcrysbSArc1ySpFKPFy9jUaO+VdmdrU7VOV5TdSo+BPPm+5y1Trc6rmSdiqbsFf1CrWzZyzouqk6/FxsVNaCTt0Nfp+JTbko7j9raXkXLeKvjPdp6Y8f+vFLvu5ksAz3belf4fYi/IypWJ0mSrP+5Sp2qerwm62Q2m8t8X3TWOgGOe534ec8WP+85/3UqLWdnr1NFy1jZ49WtU9HnaVeqU3nHlapTae3a2epU1v03c9mFzm925swZhISEVOhxACr0WCKimnI2sQCnLhYCAKLr6xAZ6q5wiUi0Pu294KOXUN7S9hIAHy8Jvdt7iSgWEREREZHdOHWnVFJSEo4dO4bCwkLrseJzJots2LABe/bswZAhQ6zHrl69WmK4WWFhId544w3odDr07du35gruoMrqGSX7Y9biOGvWW+JurK0yoKO3giWpOGfN2lHp3CXMnBgMSLhlx5QMYOaEYOjcuTOjvbFNi8OsxWHW4jBrMZizOMxaHDVl7bBrSn344YfIyMhAYmIiFi1ahFGjRll3C5kxYwb8/f0xadIkLF++HGfPnkX9+vUBAE2aNEG7du0QExMDf39/JCQk4IsvvkB4eDji4uJQu3ZtAMCyZcswf/583HXXXWjQoAGuXr2Kr7/+GocOHcLrr7+OWbNmVaicWVlZ8Pf3L3eeJBFRRZnNMu6bnYjkqyZoNMD3C+og0Fc9b0xka+cBA95ckYZsgwzp+m58Rf8HLB1Wn70UhgYROkXLSURERERUpKJ9JQ67ptTChQtx/vx56+01a9ZgzZo1AIDx48fD39+/1Ofdfffd+OWXX7B582YYDAaEh4dj2rRpmDNnjrVDCgBatWqFFi1a4KuvvkJKSgp0Oh3atm2LVatWYcyYMTVbOQckyzIyMzPh7+9vnStMNYNZi+OsWR86k4/kq5aRnDHNPZ2iQ8pZs3YG3Vt7YfUCPbYnGLBjvwFXMwsQ5K+DRgNsT8iFDGDxmgy8+Vio0kV1KWzT4jBrcZi1OMxaDOYsDrMWR21ZO+z0vXPnzkGW5VL/KxoVtWzZMpvbADB//nzs3bsXGRkZKCgowPnz5/Hxxx/bdEgBlm1a161bh4sXLyI/Px/Xrl3Dn3/+qcoOKcCyQv6xY8dKTGkk+2PW4jhr1rG7b0zdG9jJOabuOWvWzkLnLmFgZ2+8PCUQ43pewMtTAjFrYi3UDrJ0WMYdycPuw7nlnIUqg21aHGYtDrMWh1mLwZzFYdbiqC1rh+2UIiJSo4JCGdv25AAAPD0kdGutV7hE5Kh07hKmjQyw3l60JgMmk0POyCciIiIiKhU7pYiIHMjuw7nIzrV0LPRoo4feg7+mqWx9O3ihRQPLWlLnkwqxYVe2wiUiIiIiIqo4/rVDAABJkqDX61UxZ1VpzFocZ8w6Ni7H+rOzTN0DnDNrZ3RzzpIk4ZHRgdb7l67PRE6uWaniuRS2aXGYtTjMWhxmLQZzFodZi6O2rB129z1nwd33iMhesg1mjJ55EYVGINBXg1Wv14FWq443I6qeVz9PxdY9lrXI7h3kZzOtj4iIiIhItIr2lXCkFAEAzGYzkpOTYTbzG/aaxqzFcbas/9hrQKHR8nPfGG+n6pBytqydVVk5TxsZAPfr++mu/j0Ll9OMCpTOtbBNi8OsxWHW4jBrMZizOMxaHLVlzU4pAmBp+GfOnFFNw1cSsxbH2bKO3V186p6XgiWpPGfL2lmVlXNYsBtG97N8A1VoBD79KUOB0rkWtmlxmLU4zFocZi0GcxaHWYujtqzZKUVE5ACSrxqx72Q+ACAy1A1N6+oULhE5m/sG+8Hfx/K2vjXegMNn8hUuERERERHRrbFTiojIAfweb7D+PLCTt2oWNiT78dFrMGmYv/X2oh/SwWUjiYiIiMiRsVOKAFhW+Pf39+cfwgIwa3GcKeviU/f6O9Gue0WcKWtnVl7Ow7r7oF6YZXGpI2cLsG2PodTHUfnYpsVh1uIwa3GYtRjMWRxmLY7asubue9XE3feIqLpOXyzAtNcvAwBaNNDhw2fDFC4RObN/Dudi1kcpAIDaQVosnxMBnbs6PtQQERERkWPg7ntUKWazGRcvXlTNYmpKYtbiOEvWW+KKL3DufKOkAOfJ2tlVJOdOLTwR09wTAHDlqgk/bL0mqnguhW1aHGYtDrMWh1mLwZzFYdbiqC1rdkoRAPU1fCUxa3GcIWuzWUZsnGWKlVYD9OngXLvuFXGGrF1BRXKWJAkPjwqA5vrgqJW/ZiL9mklQCV0H27Q4zFocZi0OsxaDOYvDrMVRW9bslCIiUtD+k/lIzbB0GHRs4Ql/H63CJSJX0LCODrd39wEAGPJkLPs5U+ESERERERGVxE4pIiIFucLUPXJMk4b5Q+9hGS71y45snE0sULhERERERES22ClFAACNRoOQkBBoNGwSNY1Zi+PoWRcUytieYJm65+UpoWtrvcIlqjpHz9pVVCbnID8txg22LCpploFP1mTUcOlcC9u0OMxaHGYtDrMWgzmLw6zFUVvW3H2vmrj7HhFV1fYEA+Z+lgoAGNzFG89PCFa4RORq8gvMmDgvCclXLVNE33g0BJ1aOm/nJxERERE5B+6+R5ViNptx+vRp1SympiRmLY6jZx1bbOreACefuufoWbuKyubsodNg2ogA6+3FazJgMvG7qIpgmxaHWYvDrMVh1mIwZ3GYtThqy5qdUgTA0vBTUlJU0/CVxKzFceSss3JM+OdQLgAg2F+Ltk09FC5R9Thy1q6kKjn3i/FC8/o6AMC5pEJs2JVdU8VzKWzT4jBrcZi1OMxaDOYsDrMWR21Zs1OKiEgB2xMMMFpmVKFfjBe0GknZApHLkiQJj4wOtN5euj4TObnq+JBDRERERI6NnVJERAqIjTNYf3b2qXvk+G5r5IE+7b0AABnZZny9KUvhEhERERERsVOKrtNoNIiMjFTNCv9KYtbiOGrWl9OMOHgqHwBQL9wdjSPdFS5R9Tlq1q6mOjlPGxkAdzfLz6t/z8LlNKOdS+da2KbFYdbiMGtxmLUYzFkcZi2O2rJWRy2pXGpr+Epi1uI4atZbii9w3tELkuT8U/ccNWtXU52cw2u5YXRfXwBAoRH49KcMO5fOtbBNi8OsxWHW4jBrMZizOMxaHLVlrY5aUrlMJhOOHj0Kk8mkdFFcHrMWxxGzlmUZsbtvdEr17+gaU/ccMWtXVN2c7xviD38fy1v/1ngDjpzNt2fxXArbtDjMWhxmLQ6zFoM5i8OsxVFb1uyUIgCWP5QzMzMhy9wqvKYxa3EcMetTFwtx/rJl2lSrxh4IC3ZTuET24YhZu6Lq5uyj12DSMH/r7Y9Xp/OalYFtWhxmLQ6zFodZi8GcxWHW4qgta3ZKEREJVHyU1ICOXgqWhNRqWHcf1AuzdIYeOVuA7QmGcp5BRERERFQz2ClFRCSIySzj93hLB4CbFujdnp1SJJ5WK+Hh0YHW20vWZqCgUB3fxBERERGRY2GnFAGwLKbWsGFD1SympiRmLY6jZb3vRD7SMi1zwzvfpoeft1bhEtmPo2XtquyVc6cWnohp7gkAuJxmwpqt1+xRPJfCNi0OsxaHWYvDrMVgzuIwa3HUlrU6aknl0mg0CA0NVU3DVxKzFsfRsraduucaC5wXcbSsXZW9cpYkCQ+PCoDm+saPK3/NRPo1dSymWVFs0+Iwa3GYtTjMWgzmLA6zFkdtWaujllQuk8mE/fv3q2aFfyUxa3EcKeu8AjP+3GeZuuftKaFrK73CJbIvR8raldkz54Z1dLi9uw8AICdPxvKfM6t9TlfCNi0OsxaHWYvDrMVgzuIwa3HUljU7pQiAZYX/3Nxc1azwryRmLY4jZf3XgVwY8izl6N3eCzp3SeES2ZcjZe3K7J3zpGH+0HtY2uLPO7JxNrHALud1BWzT4jBrcZi1OMxaDOYsDrMWR21Zs1OKiEiA2LgbO5z1d7Gpe+S8gvy0uG+wHwDALAOf/JihbIGIiIiISFXYKUVEVMMys03YfTgXABASoEWbJh4Kl4johrv6+SI00LLo/u7DeYg7kqtwiYiIiIhILdgpRQAArVaL6OhoaLWusxuYo2LW4jhK1tv2GGAyW37uF+MFjca1pu4BjpO1q6uJnD10GkwbGWC9veiHDJhM6hgufits0+Iwa3GYtTjMWgzmLA6zFkdtWbNTigBYdmIKCAiAJLneH8uOhlmL4yhZx8YV23Wvk2tO3XOUrF1dTeXct4MXouvrAADnkgqx8a+ccp7h+timxWHW4jBrcZi1GMxZHGYtjtqyZqcUAQCMRiPi4uJgNBqVLorLY9biOELWialGHD5jWTy6YYQ7GkXqFCtLTXKErNWgpnLWaCRMHx1ovb10fQZycs12fQ1nwzYtDrMWh1mLw6zFYM7iMGtx1JY1O6XISi1bTjoCZi2O0llv2X1jxEl/Fx0lVUTprNWipnK+rZEHerf3AgCkXzPjm81ZNfI6zoRtWhxmLQ6zFodZi8GcxWHW4qgpa3ZKERHVEFmWbabu9Y/xUrA0ROWbNjIA7m6Wn7/fkoXLaer4ho6IiIiIlMFOKSKiGnLi3wJcuGL5o75tEw+EBrkpXCKiW4uo5YZRfXwBAIVG4LOfMpQtEBERERG5NEmWZW6xUw1ZWVnw9/dHZmYm/Pz8lC5OlcmyjNzcXOj1etUsqKYUZi2O0ll/+H061my9BgB4elwQ7ujuI7wMoiidtVqIyDnbYMb9ryQiM9uyptSHz9ZGiwYeNfJajoxtWhxmLQ6zFodZi8GcxWHW4rhK1hXtK+FIKbLS6VxzAWZHxKzFUSprk0nG1j2WqXvubkDvdq4/dY/tWoyaztnHS4NJd/hbb3+8Oh1q/f6KbVocZi0OsxaHWYvBnMVh1uKoKWt2ShEAy0Jq8fHxqlpQTSnMWhwls044nof0LMtIk66t9PDxcu1ft2zXYojKeVgPH9QLs0w3PXK2ANsTDDX6eo6IbVocZi0OsxaHWYvBnMVh1uKoLWvX/iuJiEghvxXfda+ja++6R65Hq5Xw0KhA6+0lazNQUKjO0VJEREREVHPYKUVEZGe5+Wbs2J8LAPDRS+jcUq9wiYgqr3NLT3SI9gQAXE4zWddHIyIiIiKyF3ZKERHZ2a4DucjLt4wq6dPBGzp3512gkNRLkiQ8MjoAmuvNd+WvmUi/po5h5EREREQkBnffqyZX2n3PZDJBq9U69Qr/zoBZi6NU1jM/Ssbuw3kAgHefCkWbJp7CXlspbNdiKJHz2yvT8MtOy3TUO3v64Ml7g4S8rtLYpsVh1uIwa3GYtRjMWRxmLY6rZM3d96jSCgoKlC6CajBrcURnnX7NhPijlg6p0CAtWjXyEPr6SmK7FkN0zpOHBUDvYflA9PPObJxLKhT6+kpimxaHWYvDrMVh1mIwZ3GYtThqypqdUgTAssL/gQMHVLPCv5KYtThKZL013gCzZdM9DOjoDY3Geb/dqAy2azGUyDnIX4v7Blu+3TKbgU/WpAt7bSWxTYvDrMVh1uIwazGYszjMWhy1Zc1OKSIiO4qNK77rnpeCJSGyn7v6+SI0UAsA+OdwHuKO5CpcIiIiIiJyBeyUIiKyk4vJhTh2zjLUtnGkOxpE6BQuEZF9eOg0mDYywHp78ZoMmMxckpKIiIiIqoedUmSl1WqVLoJqMGtxRGYdu/vGKKkBnbyFva6jYLsWQ6mc+3bwQnR9S0fr2cRCbNyVU84znB/btDjMWhxmLQ6zFoM5i8OsxVFT1tx9r5pcZfc9IqoeWZZx/ytJSEwxQpKAb1+LQEiAm9LFIrKrQ6fz8fjbVwAAgb4afDk3Al6e/H6LiIiIiGxx9z2qFFmWkZGRAfZR1jxmLY7IrI+dK0BiihEA0K6ph+o6pNiuxVA659saeaB3e8taaenXzPhmU5Yi5RBB6azVhFmLw6zFYdZiMGdxmLU4asuanVIEwLLC/7Fjx1Szwr+SmLU4IrP+TeVT99iuxXCEnKeNDID79T7XVVuycDnNqFhZapIjZK0WzFocZi0OsxaDOYvDrMVRW9bslCIiqiajScbWPQYAgM5dQs+23HWPXFdELTf8Xx9fAEChEfh8XYayBSIiIiIip8VOKSKiaoo/mofMbDMAoFsrPbz1/NVKrm38EH/4eVva+ZY4A46ezVe4RERERETkjPiXEwEAJEmCXq+HJElKF8XlMWtxRGVtu+ueOkdJsV2L4Sg5+3hpMGmYv/X2xz+ku9y6B46StRowa3GYtTjMWgzmLA6zFkdtWXP3vWri7ntE6mbIM2P085eQXyjDz1uD7xfUgbubOt5ASN2MJhlT5yfh3yuWNaVmT62FPu3V2SlLRERERLa4+x5VitlsRnJyMsxms9JFcXnMWhwRWe/Yn4v8Qkvffp/2XqrtkGK7FsORcnbTSnh4VKD19qc/pqOg0HW+53KkrF0dsxaHWYvDrMVgzuIwa3HUljU7pQiApeGfOXNGNQ1fScxaHBFZx6p8170ibNdiOFrOnW/zRIdoTwBAUpoJa7ZdU7hE9uNoWbsyZi0OsxaHWYvBnMVh1uKoLWt2ShERVdHVTBMSjuUBAMKDtWjZUKdwiYjEkiQJD48KQNGSBys3ZiLjmjq2LyYiIiKi6mOnFBFRFf2+Jwfm67OV+nfyVs1ihETFNYrUYWg3yyjBnDwZy3/JVLhEREREROQs2ClFACzfdvv7+/OPagGYtTg1nXXsboP15wEd1Tt1D2C7FsVRc54yLACeHpYyrd+RjXNJhQqXqPocNWtXxKzFYdbiMGsxmLM4zFoctWXN3feqibvvEanTv5cLMWleEgCgaV0dFs8MU7hERMr6amMmvlhvGSXVuaUnFjwaqnCJiIiIiEgp3H2PKsVsNuPixYuqWUxNScxanJrMOjau+ALnXnY/v7NhuxbDkXMe098XoYFaAMA/h/MQdyRX4RJVjyNn7WqYtTjMWhxmLQZzFodZi6O2rNkpRQDU1/CVxKzFqamsZVm27rqnkYB+HdQ9dQ9guxbFkXP20GkwdUSA9fbiNRkwmZ13MLYjZ+1qmLU4zFocZi0GcxaHWYujtqwdslMqOzsbc+bMwZAhQxAUFARJkrBs2bIKPXfZsmWQJKnU/y5fvlzi8evWrUP79u3h6emJunXrYs6cOTAajXauERG5ksNnCnA5zbLDWPtoTwT5axUuEZFj6BfjhWb1LLtQnk0sxMZdOeU8g4iIiIjUzE3pApQmNTUV8+bNQ926ddGmTRts27at0ueYN28eGjRoYHMsICDA5vbGjRsxcuRI9OnTBx988AEOHjyI+fPnIzk5GYsWLapGDYjIlRWNkgKAAZ04SoqoiEYjYfroADzxTjIAYOn6DPSL8YKXp0N+B0ZERERECnPITqnw8HAkJSUhLCwM8fHx6NixY6XPMXToUMTExNzyMc888wxat26NzZs3w83NEoWfnx9ef/11PPHEE4iOjq5S+Z2RRqNBSEgINBr+4VDTmLU4NZF1oVHGtgTLrnueOgk92+jtdm5nxnYthjPk3KqxJ3q10+OPvblIv2bGN5uz8MCdAUoXq9KcIWtXwazFYdbiMGsxmLM4zFoctWXtkLX08PBAWFj1d7K6du0aTCZTqfcdOXIER44cwYMPPmjtkAKA6dOnQ5ZlrF69utqv70w0Gg0aNWqkmoavJGYtTk1kvftILrJyLPO7u7XWQ88RIADYrkVxlpynjQyA+/W31u+3XMOVq843Ld5ZsnYFzFocZi0OsxaDOYvDrMVRW9YuW8u+ffvCz88PXl5euPPOO3Hy5Emb+/fu3QsAJUZTRUREIDIy0nq/WpjNZpw+fVo1i6kpiVmLUxNZb9ltsP7MqXs3sF2L4Sw51wlxx//18QUAFBTK+PynDGULVAXOkrUrYNbiMGtxmLUYzFkcZi2O2rJ2yOl71eHl5YVJkyZZO6X27NmDd955B926dUNCQgKioqIAAElJSQAsUwVvFh4ejsTExFLPn5+fj/z8fOvtrKwsAIDRaLQukK7RaKDRaGA2m20aUtFxk8kEWZbLPa7VaiFJUomF17Vay6LKN48CK+u4m5sbZFm2OS5JErRarbWMJpMJycnJiIyMhIeHR5lld6Y6lXdcqTrJsmzNuugxzl4nR71ORqPRmrVOp6t2nXJyzdh10LLNvb+PBm2buMFoNPI6wfLmmZKSgqioKJtvdZy5To54nYr/ri46r6PW6Z4B3vj1rxxk5ZgRG2fA//XJQ5Mo248djnydirKuW7cuJElSfduryTqZzeYS74vOXidHvU78vMfPe652nQoLC21ydoU6Oep1Kvr9Ua9ePQBwiToVL6MjXSdn+rx3q+MV3UDO5Tqlxo4di7Fjx1pvjxw5EoMHD0avXr3w2muvYfHixQCA3FzLH5YeHh4lzuHp6WntbLrZggULMHfu3BLH9+7dC29vy6iJkJAQNGrUCGfPnkVKSor1MZGRkYiMjMSJEyeQmZlpPd6wYUOEhobi0KFD1nIBQHR0NAICArB3716bC966dWvodDrEx8fblCEmJgYFBQU4cOCA9ZhWq0XHjh2RmZmJY8eOWY/r9Xq0adMGqampOHPmDGRZRkZGBk6dOoWWLVsiMTERFy9etD7eGetUxN/fH82bN3eYOrVr1w5msxkJCQmQJMkl6uSo18lgMCAjIwMJCQlo3rx5teuUcMYbBYX+AIDmdbKwb+9FXqfrgoODAQDnz59HWlqaS9TJEa9TVlaWtU1LkuTwderd0gvrdwcAAD76/irG9fwX13/tOfx1KnpfzMvLg16vV33bq8k6hYWFIScnx+Z90dnr5KjXiZ/3+HnP1a7TkSNHbN4XXaFOjnqdZFm2lstV6gQ45nVyts97ZdUpJ6diuzBLcvGuMAdUtND50qVLMWnSpCqfp2vXrkhJScGpU6cAAAsXLsSzzz6Lf//91zp6qkinTp2g1Wrx119/lThPaSOloqKikJaWBj8/PwCO0zNZpKLfnCUkJKB9+/b85kzAN2fx8fFo3749vzkTMFKqqF3bY6TU8x+mYu+JAgDA+/+pheb1dcLr5KjXqeiDd/v27TlSqgbrVFhYaPP7w9HrZDTJeOiNFFy4YnncS5MD0avdjc0BHPk6Fb0vxsTEWL+1vFVdnaFO5ZVdyZFScXFxNu+Lzl4nR71O/LzHz3uudp3y8/OtbZojpWq2TkW/Pzp27Gitl7PXqXgZHek6OdvnvbKOZ2VlITg4GJmZmda+ktK43EipskRFReH48ePW20XT9pKSkkp0SiUlJaFTp06lnsfDw6PU0VVubm42C6YDNy7uzYq/MVXk+M3nrcpxSZJKPV5URo1Gg6ioKLi7u9+y7M5Up+oer6k6mc1ma9Y3v66z1ulWx5WskyRJ1qyLvqWsap1SMozYd9LSIRUR4obbGumt5xRZp6qUvSLHq3udzGYzIiMj4ebm5jJ1Ku+4EnXSarWl/v5w1Dq5uQGPjArEC4ss39J9vi4LPdr6QOd+49+Oo16novfFot8lam97NV2nst4XnblOjnid+HmPn/cqUvaqHFeqTu7u7qXm7Mx1ctTrVPT7o/jvk4qW3VHrVJHj/LxX9TqVdf/NXHah85udOXMGISEh1ttt27YFgBJDzoqGvhXdrxYajQaRkZGlNlqyL2Ytjj2z3hpvQNEXBwM6epXokFI7tmsxnDHnzrd5on0zy5c5SWkm/LjtmsIlqhhnzNpZMWtxmLU4zFoM5iwOsxZHbVk7dS2TkpJw7NgxFBYWWo8VnzNZZMOGDdizZw+GDBliPdayZUtER0djyZIlNsPOFi1aBEmScNddd9Vs4R2MyWTC0aNHSwzBI/tj1uLYM+vY3TfmRHPXvZLYrsVwxpwlScIjowOta0l9tTETGdccv/zOmLWzYtbiMGtxmLUYzFkcZi2O2rJ22Ol7H374ITIyMqy74K1fv966eNeMGTPg7++PWbNmYfny5Th79izq168PAOjWrRvatWuHmJgY+Pv7IyEhAV988QWioqLwwgsv2LzGW2+9hTvvvBODBg3CPffcg0OHDuHDDz/E1KlT0bx5c6H1VZosy8jMzLSZQ0o1g1mLY6+szyYW4NRFS+d3dH0dIkPd7VE8l8J2LYaz5twoUoehXb2xYVcOcvJkLN+QiSfuDlK6WLfkrFk7I2YtDrMWh1mLwZzFYdbiqC1rh+2UWrhwIc6fP2+9vWbNGqxZswYAMH78ePj7+5f6vLvvvhu//PILNm/eDIPBgPDwcEybNg1z5sxB7dq1bR47bNgwrFmzBnPnzsWMGTMQEhKCF154AbNnz665ihGR09kSZ7D+PKAjR0kRVcXk4QH4fY8Befky1v+ZjZG9fFEvnB28RERERGrmsJ1S586dK/cxy5Ytw7Jly2yOzZ8/H/Pnz6/w64wcORIjR46sXOGISDXMZhmxcZapexoN0DfGS+ESETmnYH8t7h3kh6XrM2E2A5/8mI7Xp4cqXSwiIiIiUpBTrylF9qPRaNCwYUPVLKamJGYtjj2yPng6H8lXLfO5Y5p7ItC39F0p1I7tWgxnz3lMf1+EBFj+Df19KA/xR3MVLlHZnD1rZ8KsxWHW4jBrMZizOMxaHLVlrY5aUrk0Gg1CQ0NV0/CVxKzFsUfWxafuDeQC52ViuxbD2XP21GkwdUSA9fbiHzJgMjvmegnOnrUzYdbiMGtxmLUYzFkcZi2O2rJWRy2pXCaTCfv371fNCv9KYtbiVDfrgkIZ2/ZYpu55ekjo1lpvz+K5FLZrMVwh5/4dvdCsrg4AcCaxEL/+lVPOM5ThClk7C2YtDrMWh1mLwZzFYdbiqC1rdkoRAMsK/7m5uapZ4V9JzFqc6mb9z+FcZOdantujjR56D/7KLAvbtRiukLNGI+GRuwKst79YnwFDnlm5ApXBFbJ2FsxaHGYtDrMWgzmLw6zFUVvW/AuLiKgMW+JujODg1D0i+2nd2BO92llGHqZnmfHN5iyFS0RERERESmCnFBFRKbINZvx10LIIc6CfBu2beSpcIiLXMm1kANyu7xvw/ZZruHLVqGyBXET6qVP47eGHsbxtW7zt5oalt91W6XPsee89LJQkrBk2rMR9F3fswHd9++KDwEB8VKsWVg8diuR9++xQciIiIlIjdkoRAECr1SI6OhpaLXcWq2nMWpzqZL19rwGF1/9G7tvBG1qtZOfSuRa2azFcKec6Ie74vz6+ACzrt33+U4ayBbqJs2addvgwzvzyCwIaN0ZwixaVfn7O5cvYNXcuvEJDS9x39fhxrB40CO7e3hj2zTcY/PnnyLt6Fav690fO5ctVLrOzZu2MmLU4zFoM5iwOsxZHbVmzU4oAAJIkISAgAJLEP7xrGrMWpzpZb9ldfOqelz2L5ZLYrsVwtZzvH+oPP2/LR5HYOAOOnstXuEQ3OGvWjYYPx0MXLmDE6tWo3b59pZ+//bnn0OjOOxHUvHmJ+07++CMgyxj+/fdoMGQIGo8YgWHffou8q1dx7rffqlxmZ83aGTFrcZi1GMxZHGYtjtqyZqcUAQCMRiPi4uJgNHL6RE1j1uJUNesrV43Yd9Lyx3FUbTc0vb5TGJWN7VoMV8vZx0uDiXf4W28v+iHDYRb1dNaspWpsH31xxw6cWrsWvd54o9T7zYWF0Hp4wM3zxnRmD//r168a181Zs3ZGzFocZi0GcxaHWYujtqzZKUVWatly0hEwa3GqkvXv8QbrzwM6eqvmW4rqYrsWw9VyHt7TB1G13QAAh07n44+9uQqX6AZXy/pWzCYTtjz2GDq/+CJ8wsNLfUz0PffAbDRix0svITctDdmJidj61FPwjYpC4xEjqvX6aspaacxaHGYtBnMWh1mLo6as2SlFRHST4lP3+nPXPaIa5aaV8PCoQOvtJWszUFDoGKOl1GTfxx+jMCcHMU89VeZjAps0wdgtW3Dw88/xUa1aWFynDi7+8QfGxMbeGDFFREREVAnslCIiKub0xQKcSSwEALRsqENELTeFS0Tk+rrc5on2zTwAAEmpRqzdfk3hEqlLTnIyds6ejb7vvAOtruzpyldPnMBPo0ej/qBBGPPbb/i/9evhV68efhg6FDlXrggsMREREbkKdkoRAMsK/61bt1bNCv9KYtbiVCXr2GKjpAZ05CipimK7FsNVc5YkCY+MDkTRTNkvN2YiM1vZYeuumnVpds2ejZDWrVGnZ0/kZWQgLyMDstEIs9GIvIwMmK+vafHnCy/AOywMt69YgXoDBqDRsGEY9fPPyE9PR8L771f59dWUtdKYtTjMWgzmLA6zFkdtWbNTiqx0t/h2lOyLWYtTmazNZhlbrq8npdUAfTpw173KYLsWw1VzbhSpw9Culo7gnFwZy3/JVLhErpv1zdKOHcPFP/7Ah4GB1v8u7dyJc5s24cPAQJyPjbU87sgRhLRpY/NcnY8PAho3Rsbp09Uqg1qydgTMWhxmLQZzFodZi6OmrNkpRQAsC6nFx8erakE1pTBrcSqb9f6T+UjNsDy2U0s9/H3U8e2EPbBdi+HqOU8eHgBPD8twqXV/ZuPfy4WKlcXVsy6u33vvYezWrTb/hbRpg/AuXTB261aEdeoEAPCrVw/Je/fa7JCYn5WF9JMn4Ve/fqVft6BQxuZ/cjBnSQoeeu0s5ixJweZ/crimWA1SU7tWGrMWgzmLw6zFUVvWdl0sJSsrC//88w88PT3Ro0cP7lhFRE7FduoeR0kRiRbsr8W9g/ywdH0mzGZg8Zp0vD49VOliOZVCgwFnNmwAAGSdP4+CrCwcX70aABDVuze8QkKwqn9/ZJ0/j6mnTgEAQtu2LXEej4AA6Hx8ULdPH+uxtg8/jLUjR+KXcePQcsIEGPPyEP/22zDl56P11KmVKufOAwa8uTwN2bkyJAmQZQ+cS87Djv15+HDVVcycGIxurfl7mIiIyNVVaaTUp59+it69eyM9Pd16bP/+/YiOjsaQIUPQp08f9OzZEwaD4RZnISJyHAWFMv7Ya/md5eUpoWtrvcIlIlKnMf19ERJgGaX496E87DmWp3CJnIshORnrx4zB+jFjcGHbNly7cMF6O/XwYQCA2WSyrhNVGY1HjMDwVauQceoU1t99NzZPmwY3vR53b92KwCZNKnyenQcMmP1JKnJyLSOiigZeFf0/J1fGy5+kYucBfo4kIiJydVUaKfXll1+ioKAAgYE3tnB++umnkZycjMmTJ+PKlSvYsGEDFi1ahKefftpuhSUiqil/HcxFTp7lL6Kebb3gqePsZiIleOo0mDoiAAuWpwEAFv2Qjk9mhUGr4ejrivCvXx/PyLee/nbPtm3lnqesxzQbMwbNxoypQsksCgplvLk8DZCBskopA5Bk4M0VaVi9QA+dO689ERGRq5JkuZxPLqUICwvDiBEj8MknnwAA0tLSEBoaimnTpmHx4sUAgC5duqCgoAAJCQn2LbGDycrKgr+/PzIzM+Hn56d0capMlmWYTCZotVpOu6xhzFqcymT98uIU7DyQCwB46/FQdIj2FFFEl8F2LYZacjabZTz63ys4/m8BAOCZcUG4vbuP0DKoJWvRNv+TgzeudzhWxKyJwRjYmTuh2gvbtTjMWgzmLA6zFsdVsq5oX0mVhgJkZGQgJCTEevvPP/8EAIwaNcp6rEePHjh37lxVTk8KKSgoULoIqsGsxalI1lk5Jvxz2NIhFeyvRdumHjVdLJfEdi2GGnLWaCQ8PDrAevuL9Rkw5JmFl0MNWYu2c78BFf18LUnAjv2cwmdvbNfiMGsxmLM4zFocNWVdpU6p4OBgJCUlWW9v2bIFWq0W3bt3tx6TZRmFhcrtmkOVYzKZcODAAdWs8K8kZi1ORbPenmCA8fpD+sV4cZpQFbBdi6GmnNs08UTPtpa13a5mmfHtb1lCX19NWYuUlWNGRcfoy7Ll8WQ/bNfiMGsxmLM4zFoctWVdpU6p1q1b46effsKhQ4dw6tQpfP311+jevTu8vW8Mrz537hzCw8PtVlAiopoSu/vGN/EDOnGaCJGjeHBkANwsa55jVew1JF+t/OLc5Fh89BX/6ClJgJ831/cjIiJyZVV6p3/uueeQnp6ONm3aoFmzZsjIyMB//vMf6/1msxk7duxAhw4d7FZQIqKacDnNiIOn8wEA9cLd0TjSXeESEVGROqHu+L8+vgAsC2R/ti5D2QJRlcmyjB37DDh0puK7Kcoy0KONVw2WioiIiJRWpd33+vbti3Xr1mHp0qUAgHvuuQfDhw+33r9z505ERETYrDFFjk+r1SpdBNVg1uKUl/WWuBzrzwM7ejn1YoJKY7sWQ205jx/qj01/5yArx4zY3QaM6pOP6Ppi1n1TW9Y15cKVQnz4fTrijlS8Q0oC4O0loXd7dkrZG9u1OMxaDOYsDrMWR01ZV2n3PbrBVXbfI1IjWZYx5dUknL9smRL09asRCAuuUl89EdWgNVuv4cPv0wEArRp54L3/hLID2Qnk5pnx1a9Z+H5LlnXdPgBoWMcNZy9Zfu+W9SFUkoBXH6qFbq3ZKUVEROSManT3Pa1Wi3HjxlW5cOR4ZFlGRkYG2EdZ85i1OOVlfepiobVDqlVjD3ZIVQPbtRhqzfnOXj6IDLX8+zx4Oh9/7sut8ddUa9b2IMsytsbnYOK8JHyz+UaHVGigFnOm1sKnL4Rj3sO14O1l6VgsrX9x+ugAdkjVALZrcZi1GMxZHGYtjtqyrlKnlJ+fH6KiouxdFlKQyWTCsWPHVLPCv5KYtTjlZR27u9jUPS5wXi1s12KoNWc3rYSHRwVYb3/yYwYKCmv2g5pas66us4kFePq9ZLz6RRpSMyzZubsB44b4YenscPRub5km3b21F1YviMSsicHo3toTDWrno2HEjS8G9p3IV6oKLo3tWhxmLQZzFodZi6O2rKs0LKBTp07Yv3+/vctCRCSMySzj93jLrntuWqBXO73CJSKiW+naSo92zTyw93g+klKNWLv9GsYO4LR5R5Gda8aKXzKxZts1mM03jndq6YnHxgQiMrTkJhI6dwkDO3ujbwcPxMefQes29THp1WSkZpiw80AuTvxbgKZ1dQJrQURERKJVaaTUK6+8gt9//x0rVqywd3mIiITYdyIfaZmWbx8636aHn7d6FhMkckaSJOGRUYHWqV5fbsxEZrY6vkF0ZGazjM1/Z2Pi3ESs/v1Gh1R4sBbzH66FBdNDSu2QKo3OXcK4ITc6Gpeuz6iBEhMREZEjqdJIqd9++w19+vTB5MmT8cEHH6Bjx46oXbt2iUVHJUnCyy+/bJeCUs2SJAl6vZ4LxwrArMW5VdacumdfbNdiqD3nxlE6DOnijY1/5SAnV8byXzLx+N1BNfJaas+6Ik5dKMD7313F4TMF1mM6dwnjBvth7ABfeOgq9t1n8ayHdvXBN5uzkHzVhH8O5+HI2Xy0aCBmt0U1YLsWh1mLwZzFYdbiqC3rKu2+p9FU/EOGq8+D5O57RM4nr8CM0c9fQm6+DG+9hB/eiITOXR2/9ImcXWqGERPmJiEvX4ZGA3zxUjjqhlVsJA7ZR1aOCUvXZ2L9n9kwF/sU2aONHtPvCqz2phG/7MzG2yuvAgBimnvivzNCq3U+IiIiEq+ifSVV+tSwdevWKheMHJPZbEZqaipq1apV4U5HqhpmLU5ZWf91IBe5+Za/pHq382KHlB2wXYvBnIFaAW64d6Aflv6cCbMZWLwmHa9Pt3+nBbMuyWyWsWFXDj77KQNZOTcWjooMdcOMsYHo2KJqa/PdnPXgLt74+tdMJKWZEH80DwdP5aFVY097VUPV2K7FYdZiMGdxmLU4asu6Sp1SvXv3tnc5SGFmsxlnzpxBUFCQKhq+kpi1OGVl/VuxqXsDOHXPLtiuxWDOFmMG+GL9jmykZpjw96E8JBzLQ/to+3ZaMGtbR8/l43/fpeP4+RtT9Tw9JNw/1B939fOFu1vVO/dvztpNK+H+2/3x3y8to6WW/ZKJt59gp5Q9sF2Lw6zFYM7iMGtx1Ja169eQiKiYzGwT4o7kAQBCArRo3ZhrlRA5G0+dBlNHBFhvL1qTDpO50qsRUAVkXDNh4VdpePS/V2w6pPrGeGH57HDcO8ivWh1SZRnYyRt1Qizfne49no99J/Ls/hpERESkvOpN+gdw4cIFJCYmIj8/v9T7e/XqVd2XICKym217DDBdn3XSv6MXNBpO3SNyRgM6emHN1ms48W8BTl8sxOa/czC0m4/SxXIZJpOM9Tuy8cW6DGTn3ujwqx/ujsfvDkTbpjU7ckmrlTDhdn8sWJ4GAFj6cybee8pDNYu+EhERqUWVO6XWr1+PZ599FidPnrzl41x9oXNXIUkS/P39+WFPAGYtTmlZc+pezWC7FoM536DRSHhkdACeejcZAPD5ugz0ae8Fvad9BoGrOeuDp/Lwv1XpOH2x0HrM21PCxGH+GNnbF25a+2ZSVtb9Onph5a+Z+PeKEQdP5SPheD462HmaptqouV2LxqzFYM7iMGtx1JZ1lXbf27ZtGwYMGICwsDCMHj0aH3zwAXr37o3o6Gjs2LEDhw8fxrBhw9ChQwfMmTOnJsrtMLj7HpHzuJRSiPvnJAEAGka447OXwhUuERFV15wlKfhzXy4A4P6hfpg8PEDZAjmxtEwTPvkxHbG7DTbHB3fxxrQRAQjy1wov09b4HLz6hWW0VIsGOnzwTG3VfEgnIiJyZhXtK6nS14lvvPEGfHx8sGfPHrz//vsAgL59+2LRokU4ePAgXnvtNWzZsgUjRoyoWulJOLPZjIsXL8JsNpf/YKoWZ806/dQp/Pbww1jeti3ednPD0ttuq/Q59rz3HhZKEtYMG1bq/ad/+QVfd+uG97y98UFgIL7r2xfXLl6scplvzvr3uBt/aHGUlH05a7t2Nsy5pAdHBsDtel/JqthrSL5qtMt51ZS10STj+y1ZmDg30aZDqnGkO/73dG08PyG4RjukbpV17/ZeqB/uDgA4crbAuiYgVY2a2rXSmLUYzFkcZi2O2rKuUqdUXFwcRo4cidq1a1uPFQ9s1qxZaNeuHWbPnl39EpIQamv4SnLWrNMOH8aZX35BQOPGCG7RotLPz7l8GbvmzoVXaOlbtx/56iusGzUKUX36YNTPP2Po8uWoHRMDY17V/wApnrUsy9ape5IE9IvxqvJ5qSRnbdfOhjmXVCfUHf/XxxcAkF8o4/N1GXY5r1qyTjiWh2mvJWHRDxkw5FkGz/t6afDEPYFYNDMMtzWq+c0gbpW1RiNh0jB/6+2lP2eiCoP86Tq1tGtHwKzFYM7iMGtx1JZ1ldaUMhgMqFOnjvW2h4cHsrKybB7TpUsXLF26tHqlIyKH0Wj4cDS+Pvpx46RJuBwfX6nnb3/uOTS6805knT9f4r7cq1cR++ij6Pvee2j7yCPW443vvLN6hS7m+PkCXEy2jKBo09gDoUHV3ueBiBzE+KH+2PR3DrJyzPhttwGj+uajWT3urHkryVeNWLQmA9sTboyMkiTgju4+eOBOf/j7iJ+qV5YebfRoFOmO0xcLcfx8Af46mIturfnFAhERkSuo0kipsLAwpKSkWG/XqVMHhw8ftnlMWloaFzknciGSpuqLB1/csQOn1q5FrzfeKPX+46tWQTaZ0OqBB6r8GuWJ5dQ9Ipfl66XBhNtvjKb5+IcMjqYpQ0GhjK9/zcSkeUk2HVLN6+vw8XO18Z/7ghyqQwq4PlrqjhvXdxlHSxEREbmMKv2V2aZNGxw6dMh6u2/fvti6dSu++eYb5OTkYNOmTVi1ahVat25tt4JSzdJoNAgJCYGmGh0PVDFqy9psMmHLY4+h84svwie89IXFk/7+G0HR0Ti8fDk+qVcPb7u5YXnbtjizcWO1Xrsoa1mWsDXeMnXP3Q3o1Y7fsNub2tq1Uphz2e7s5YPIUMsIyIOn8q2Ln1eVK2b9z+FcPDA/CZ+ty0RegaVTx99Hg2fHB+GDZ2orNrqsIll3a61H07o6AMCpi4XYsb9611etXLFdOypmLQZzFodZi6O2rKtUyzvvvBP79u3D+evTcF544QX4+Phg/Pjx8PPzw+233w6j0Yj58+fbtbBUczQaDRo1aqSahq8ktWW97+OPUZiTg5innirzMTmXL+Pq8ePY8fLL6PHqqxi9cSP869fH2jvvROpNozAroyjrfScLkH7NMie7ays9fLzUkb1IamvXSmHOZXPTSnhoVID19pK1GSgorPpoGlfKOinViJcXp2DWRym4lGKZxqyRgP/r44MVr0RgaDcfaDTK7WhXkawlyXZtqeU/Z8Js5mipynKldu3omLUYzFkcZi2O2rKuUi2nTJkCg8GAevXqAQAaNGiAuLg4PPzwwxg0aBCmTZuGf/75B7169bJrYanmmM1mnD59WjWLqSlJTVnnJCdj5+zZ6PvOO9DqdGU+TjabUZidjUFLlqDlhAmoP3Aghn//PXwiI7H7zTer/PpFWf/2T4712ICOnLpXE9TUrpXEnG+tWys92ja1jPZJTDHipz+uVflcrpB1foEZy37OwKR5idh54MbIolaNPPDJrDDMGBsEXwfopK9o1p1beqJ5fct7yZnEQvxRzdFwauQK7dpZMGsxmLM4zFoctWVtt08ijRo1wkcffYSNGzdi8eLFaNu2rb1OTQKYzWakpKSopuErSU1Z75o9GyGtW6NOz57Iy8hAXkYGZKMRZqMReRkZMBst39h7BgYCAOr262d9rtbdHZG9eiGtGiOlzGYzLiWmWqd5+OgldGqpr0aNqCxqatdKYs63JkkSHhkdCOn6oJ8VGzKRmV219S2dOWtZlrFjnwGTX03Cig1ZKLT8qkWQnwYvTArGe/8JRaPIsr8oEK2iWZccLZUBE0dLVYozt2tnw6zFYM7iMGtx1JZ1lUdKrVu37paP+fnnnzFlypQqFYqIXEPasWO4+Mcf+DAw0PrfpZ07cW7TJnwYGIjzsbEAgOCWLcs8hzEvr1plOHLB07p2Sp8O3tC5KzdFhYhqXpMoHQZ3sYyIzMmVsWJDpsIlEuvClULM+igFs5ek4nKapUNOqwHG9PfF8jkRGNDJG5LkvL8HY5p74rZGltFw5y8bsW2PoZxnEBERkSOrUqfUsmXLsG/fvls+Zv/+/Vi+fHlVTk9ELqLfe+9h7NatNv+FtGmD8C5dMHbrVoR16gQAaDRsGABYO6kAwFRQgIvbt6N2hw6Vft2CQhmb/8nBvM+vYv1uP+vx3u05SopIDaYM94enztLx8tMf2fj3cqHCJap5uXlmfLo2Aw/MT8LuIzc689s388CnL4bjkdGB8NYrP1WvukqMlvolEyYTR0sRERE5K7eaOnFeXh7c3Grs9GRnGo0GkZGRqllMTUnOmnWhwYAzGzYAALLOn0dBVhaOr14NAIjq3RteISFY1b8/ss6fx9RTpwAAoaVM4/UICIDOxwd1+/SxHqvdvj2ajB6NzQ8+iLyrV+EdHo59H30Ew5Ur6Pjss5Uq584DBry5PA3ZuTIkCZDlG1ubz/00FTMnBqNba+6+Z2/O2q6dDXOumFoBbrhnkB+W/ZwJsxn45McMvPZISKXO4SxZy7KM7QkGLPohAykZN6YqhgZq8cjoQPRqp3f4kVGVzbp9M0+0beKBfSfzcTHZiC1xORjUxaeGS+kanKVduwJmLQZzFodZi6O2rKvca1TWBxxZlnHhwgVs3LgRERERVS4YiVXU8KnmOWvWhuRkrB8zxuZY0e2xW7eibp8+MJtM1nWiKmvo8uX4c9Ys/DFzJgqyslC7QweMiY1FSKtWFT7HzgMGzP4kFbj+pbl805fnObkyXv4kFfMeqoXu7JiyK2dt186GOVfcmP6++HlHNlIzTPjrYC4SjuWhfbRnhZ/vDFmfTSzAB6vSse9EvvWYuxswtr8f7hviB72Hc3yYrUrWE4f5Y9+7yQCAFRuz0K+jN9y0jt355gicoV27CmYtBnMWh1mLo7asJVm++c+20mk0GmtHlCzL5X7rJssynn/+eSxYsKD6pXRgWVlZ8Pf3R2ZmJvz8/Mp/goMymUw4ceIEmjZtCq1WW/4TqMqYdc0oKJRx18yLyMmVcatfahIAby8JqxdEcn0pO2K7FoM5V87mv7PxxoqrAIBGke5YPDMMWk3F/t07ctY5uWYs/yUTa7ZdQ/E1UDu19MRjYwIRGequXOGqoKpZP/u/ZOw5Zpmq+Oz4IAztxtFS5XHkdu1qmLUYzFkcZi2Oq2Rd0b6SCo+U6tWrl7Uj6o8//kDdunVRv379Eo/TarUICgpCv379MG3atMqXnBQhyzIyMzNRwT5KqgZmXTO2JRiQnVt+pjKAbINlusvAzt41XzCVYLsWgzlXzoBO3vhh6zWcvFCI0xcLsfnvnAp3XDhi1rIs47fdBnzyYzrSs270RoUHa/HomEB0beX4U/VKU9WsJ97hb+2UWrEhEwM6ecPdzfnqL5IjtmtXxazFYM7iMGtx1JZ1hTultm3bZv1Zo9Fg8uTJmD17dk2UiYio0nbuN1xfQ6r8x0oSsGM/O6WIXJ1GI2H66EA89Z5lmtfn6zLQp70X9J7OMa2tuFMXCvC/Vek4dPrGVD2du4T7Bvvh7gG+8NA5X52q67ZGHujUwhO7j+ThylUTfv0rG8N7+ipdLCIiIqqEKq0pZS4+VpyIyAFk5Zgr1CEFWDqusnL4e4xIDdo09USPNnrs2J+Lq1lmfPtbFiYPD1C6WBWWlWPC0p8zsf6PbJiL/Y7r0UaP6XcFIixY3ZvKTBrmb91t8KuNWRjcxYdTs4mIiJyI3T7JJCcnY+fOnQCALl26IDw83F6nJgE0Gg0aNmyomhX+lcSsa4apEn1MkgT4eTN/e2K7FoM5V82D/xeAvw/lwmgCVsVew7AePggJvPVHIKWzNptlbPwrB5/9lIHM7Bu/4CJD3TBjbCA6ttArUq6aUJ2so+t7oGsrPf46mIuUDBM27MrGyN4cLVUWpdu1mjBrMZizOMxaHLVlXeFa7tu3D7Nnz8a+fftK3LdkyRLUq1cPd911F+666y7Ur18fCxcutGc5qYZpNBqEhoaqpuEriVnbV7bBjIVfpdlMaSmPLAM92nD3PXtiuxaDOVdNZKi7taMiv1DG5+syy32OklkfPZePR9+6grdXXrV2SHl6SJg2MgCfvRjuUh1SQPWznjTM3/rzyl+zkF/AkbBl4e8QcZi1GMxZHGYtjtqyrnAtV6xYgQULFiAiIsLmeEJCAqZPn478/Hz07NkTQ4cOhZubG55//nls377d7gWmmmEymbB//36YTCali+LymLX97DpgwORXk7BhV06FnyMB8PGS0Ls9O6Xsie1aDOZcdff/P3v3Hd9Uuf8B/HOSNG260k2BAi2gFmTLkiEgiqAsEXGh4kBQr+unXscVB1dF70Wv3ot7sJzIUFmCKBsHlVmmjILQltKVtGnaNMn5/RGatrSlaZs+ycn5vF8vlJ6TnDzP5xxOkyfP+Z5rje4Zkmt/s+DQiQsPZPsi68IiB2Z/noe//fsMDp2wuZcPuywU859viVtGRAbkpWlNzfqiNnoM6u4aqMszObB8S7E3mxdQeA4Rh1mLwZzFYdbiqC1rjweltm3bhr59+yIhIaHa8jlz5kCWZbz88svYsGEDVqxYgZ9++gmSJOH999/3eoOpeciyDKvVqpoK/77ErJvOVOzAK3Nz8dz7ucgzuU7WoSESxg4OgyS5Bp5qI537z9N3xAbkBztf4nEtBnNuvIhQDe64tnJGzXtLCi+Yo8isHQ4Z324swh0vZmLVVou7Pl5yyyC88UgCZtwTV+/lhkrmjazvvK5y3365xgxrGWdL1YbnEHGYtRjMWRxmLY7asvZ4UOrkyZPo1atXjeXr1q2DwWDAE0884V7Wv39/jBgxAr/++qt3WklEBNcJesMfFtw1Mws/bS9xL+/bOQSfPNcSj94Si5nT4hAW6hpwqrgzesX/w0Il/HNaHAZ04ywpIjUae0U4khJcgzt7jpRhy26rj1sEpB8tw/TXs/HfrwtQbHW9+QwLkfDAxCh8+Gwiel4S4uMWKkOHJL17BmxBkRPfb+JsKSIiIiXw+Gu3vLw8REVFVVuWnZ2NU6dO4aqrroJer6+2rlOnTli/fr1XGklElGdy4K2v8rG1yofIiFANHpwYhav7hUE6N/I0sFsoFs8yYOOOEmzeZcHpbBNaJxoxuEcYhvQK5QwpIhXTaSVMmxCFGe/nAgA+WFaI/l0MCNKJPy/kmRz4cFkBfvy9pNrya/qHYeq4KMQYtcLbpHR3XmfEpp0lkGXgqx/NGDs4HIYQddTjICIiUiqPB6UMBgPOnDlTbVlaWhoA4LLLLqvxeL1ej6CgoCY2j0TRarVITU2FVss3wc2NWTeMLMtY86sF7y6unEUAAIN7GPDITTG1fnDTB0m4ul8YruobCpNJD6PR6B60oubB41oMJedccOQI0mbPRuavvyI3PR0xqam4Kz29Qdv44623sP6xx9D+uuswYcUK9/KTGzZg0bBhNR5/yU03YcxXX1VbNqCrAT0uDsauw2XIPGvHtxuLcOPwyBrPba6s7Q4ZyzYUYf5KE0pKK89pHZOC8PBNMejSIdirr6cE3so6uWUQruwdip+2l8BU7MSyjUW49Rpj/U9UESWfQ5SGWYvBnMVh1uKoLWuPB6U6d+6M1atXw+FwuMNZuXIlJEnCoEGDajz+5MmTaNmypfdaSs1KkqQaM+GoeTBrz2Xn2fGfL/OxfX+pe1l0hAYP3xTjUaFyZi0OsxZDyTnn7duHYytXIrFfP8hOJ2Rnw2r+WLKzse2llxB6Xm3LqkbOnYuY1FT3z4a4uBqPkSQJ998QjemvZUOWgYWrTBjRLwzGcG2Nx3k76x2HSvG/r/NxItvuXhYRqsHdY40YPSgcWo06B8+9mfXt1xqxPq0EThlYtK4I466IQJiBs6UqKPkcojTMWgzmLA6zFkdtWXv8W/rWW2/F6dOnMW7cOHz//feYPXs25s6di7i4OFx99dU1Hr9p0yZ06tTJq42l5mO327F9+3bY7fb6H0xNwqzr53TK+G5jEe55OavagNRVfUPx6YyWHt85j1mLw6zFUHLOHcaMwbS//sK4xYvRopYalfXZ+Pe/o8PYsYi5wHuLuC5d0Kp/f/ef6I4da33cRW30uKZ/GACg2Cpj4SpTjcd4M+ucfDtmfpyLJ97OcQ9ISRJw3cAwLHixJcZdEaHaASnAu1m3bRGEq/q69q3Z4sTS9UVN3mYgUfI5RGmYtRjMWRxmLY7asvZ4ptT999+P7777DqtWrcLq1ashyzJ0Oh3efvvtGvWk1q9fj9OnT+OZZ57xeoOp+ajllpP+gFnX7VROOWZ/lo89Rypv1x4XpcX/3RKD/l0NDd4esxaHWYuh1JwlTeNnq5zasgVHvv0Wdx86hBW33OKV9tw9xogNf5Sg1Cbju03FGDskAm1bVC870NSsbeUyFv9kxmc/mFFqq7xULzVZj4cnRSM1WX2X6tXFm8f17aMisW67BU4nsOgnM64fGoHwUM6WqqDUc4gSMWsxmLM4zFocNWXt8aCUVqvFmjVr8Pnnn+PXX39FbGwsrr/+evTs2bPGY3NycvDII49g3LhxXm0sEQUuh1PG4p+KMHeFCbbyyg9voweF477roxDOyy+IVMnpcOCnv/0N/f7xD4TXUxZgybXXojQvD2EtWyL1llswcOZMBBlqH8yOi9LhpqsjMX+lCQ4n8OGyQrw8Pd5r7f59nxVzvinAqZzKbzmN4RpMHReFkZeHQaPimVHNrXVCEK7pF4bVv1hgscpY/LMZU0ZH+bpZREREVAuPB6UAQKPR4Pbbb8ftt99+wcfddNNNuOmmm5rUMCJSj+OZNvxrYT4OnbC5l7WM1eLxybHoxduhE6narnffRbnFgt6PPVbnY4KNRvT5+9+RdMUVCDIYcPLnn7F99mzkHzhQrSD6+SZdFYEVW4qRZ3Jg2x4rdhwqbfI5JyvXjncXF2Drnso7hWokYOwV4bhrTBQiOGNHiNuvNWLtbxY4nMDin4swYVgEIsPUUTCWiIhISfzynVFxcTFeeOEFjBw5EjExMZAkCfPmzWvUtqZOnQpJkjB69Oga65KTkyFJUo0/06dPb2IPlEer1aJbt26qqfDvS8y6UrldxoJVJkyble0ekJIkYMKwCHz8XMsmfzhk1uIwazHUlrMlJwdbn38ew958E9rzSgVU1aJnTwx5/XV0uO46tL3ySgx6+WUMfeMNHFu5Elm//17n8wzBGtw7rvLubO8vKYDD6Zqp2dCsy2xOzFtRiLv+mVVtQKprh2B88EwiHr4phgNSdWiO4zoxVodrB4QDAEpKZXyzjrWlAPWdQ3yJWYvBnMVh1uKoLesGzZQSJTc3FzNnzkTbtm3RvXt3bNiwoVHbSUtLw7x58xASUvcH2x49euDxxx+vtuziiy9u1Osp3fm1waj5MGvg8Ekb/rUwD8dOl7uXtW2hwxOTY716S3RmLQ6zFkNNOW97/nnEd+uG1oMHo7SwEAAg2+1w2u0oLSyEPjwcGl3tb2UumTQJP/3tbzjzxx9o2bdvna9xdd8wLF1fhD//KseRU+VY+5sFoy53DWZ4krUsy9i2x4p3FhcgO6+y/kNMpAbTro/GVX1DIUm8VK8+zXFc3zoyEj/8WoxyO7BkQxFuuDICURHqeIN/IWo6h/gasxaDOYvDrMVRU9Z++ZVdy5YtkZWVhRMnTuDf//53o7YhyzIefvhh3HHHHWjRokWdj2vdujUmT55c7U/fC7x5DVQOhwNpaWmqKqjmK2rP2lYu48NvC/HAv7LdA1IaDXDrNZH48NmWXh2QUnvWIjFrMdSWc97Bgzi1aRPmREe7/5zeuhUZa9ZgTnQ0Tqxb1+TX0Ggk3H9DtPvnT783wVrq9Cjrv86U45l3zmLGB7nuASmtBrhxeATmv9AKV/cL44CUB5rruG4Ro8O1A10DjKVlMr7+0ezV7SuR2s4hvsSsxWDO4jBrcdSWtV/OlAoODkZiYmKTtrFw4UKkp6dj6dKl+Omnny74WJvNhvLycoSFhTXpNYnowtKPluHfn+XhrzOVhX87JAXhycmxuLiter4NICLPXPnWW+4ZUhXWP/oodAYDBs+ahfhu3ep87sGvvgIAJPbpU+/r9Lg4BAO7G7B1txV5JgdenZ8LCcDp7Fis2p2PQT3CMLRXKPRBrgEma5kTn60245ufzLBXeb/Y85JgPDQpBsktg2p/IRLu1msisWqra7bUtxuLceNVkYiJ5GwpIiIif+GXg1JNVVRUhKeeegrPPvtsvYNbP//8M0JDQ+FwONCuXTs89thjeOSRRwS1lEgdrKVOfPJ9IZZtLIZ87sZ6Oq2rEO0tIyKh03ImAVGgKy8pwbFVqwAA5hMnYDObcWjxYgBAmyFDEBofj0XDh8N84gTuPXIEAJDQo0eN7QRHRUEfHo62Q4e6l62cPBlRHTuiRa9e0IWE4OTPP+OP//wHHcePR2Lv3h61b9r1UfhljxVOGdi6uxSSBMhyMDJySrFldynmLMrHU3fGorxcxntLCnG2sHI0KiFai/tviMYVPQ2cGeVn4qN0GHtFBJb8XISychlfrTXjgYnR9T+RiIiIhAjIQamZM2fCYDDgsQvcqQcAunXrhkGDBuGSSy5BXl4e5s2bh0cffRSZmZl4/fXXa31OWVkZysrK3D+bza6p4Ha7HXa7a/aHRqOBRqOB0+mE0+l0P7ZiucPhgCzL9S7XarWQJMm93arLAdSYzlfXcp1OB1mWqy2XJAlardbdxorXdjgc0Ol0dbZdSX2qb7mv+iTLco22K71PF9pPfxywYvbn+TiTX7kuNVmPJ26LRtsWWkB2wG5vnj5VPa557DVvnyr+7nQ6q7VHyX3y1/1UtV9K6pPlzBksv/HGassrfr5h3Tq0GTIEjnP1ogDU2SfAdR6t+js37tJLsf/zz5H2xhtwlJXBmJKCvs88g/7PPutxn05klcNZ+aN7AL3i/8VWGTPez63W/iAdMPHKcNx8dTgMwRr379BAPfaaq0+unKtv35t9uvmqCKzYXIyychnfby7CDcNC0SI2WJX7ie/3+H4vUPdTxWsHUp+qttEf+lS1XYHSp6pt9Lc+KfX9XtXl5z+vLgE3KHX48GG8/fbb+PLLLxEcfOHaNN9//321n++66y6MGjUKb775Jh566CEkJSXVeM6sWbPw0ksv1Vi+c+dO9+V/8fHx6NChA44fP46zZ8+6H5OUlISkpCQcPnwYJpPJvbx9+/ZISEhAeno6rNbKO/akpqYiKioKO3furLbDu3XrBr1ej7S0tGpt6N27N2w2G/bs2eNeptVq0adPH5hMJhw8eNC93GAwoHv37sjNzcWxY8fcy48dO4ZOnTohMzMTp06dci9Xcp+MRqNf9emyyy5Dly5dsHPnzoDpU237yebQ4feMFKzaanEv02llXNfXir/d1gZ5uWeRliamTzt37uSxJ6BPvXv3xokTJwKqT/62n4qLiwHAff5QUp/0LVpg0C+/1OhTYWEhDh48iDNpaUh5/XUYDAYAqLNPgz77DKdOnXK/Rnx8PPo98wziJk2q0SetXo8DBw7U26dyB/CvJa0gAagyLnVBfToH494xocjL2od9e6v3KRCPvebsU+vWrREZGVnt96I3+2TQ29D3oiJs3h8OWznwvy+O4+WHUlW9n/h+j+/3GtMnf9xPFa9ZkXMg9Mmf91NcXBy0Wi2OHTsWMH3yx/2k5Pd7VftksVjgCUmuOhTWQHa7HYcOHUJhYWGNUbIKV1xxRWM3D8B1B70+ffpg7ty5mDJlSr2PHzVqFKxWa7U79iUnJ6NLly5YsWJFvc9fs2YNRo4ciYULF2Ly5Mk11tc2U6pNmzbIy8tDZGQkAP8ZmazgyQiyLMsoLS2FwWDgN2fN3CeNRgOr1Qq9Xl/tMg8l9+n85b+ml+LtrwuRZ6psQ7eOejx2SxSSEoKE9cnpdKK0tBQhISHQ6XSqP/aas0+SJKGsrAzBwcEetV0JffLH/eR0OmGxWBASEgJJkgKiT/6wn9b9XoJ/fVYIT00YGoYHJkZDkiS/7ROgnP0kSRKKi4vdx3Vz9Cmv0IY7XspBqU1GkBZY+FIrxEdrVbef+H6P7/cCbT/Z7XZYrVb3+SMQ+uSv+0mWZZSVlSEsLAyyLAdEn6q20Z/2U6C83zObzYiNjYXJZHKPldSmUTOlZFnG888/j//9738oKiq64GPrGqxqDj///DN++OEHLF26FBkZGe7lFSerjIwMxMTEXDCQNm3aAADy8/NrXR8cHFzrDCydTgfdebelrti556vYWZ4uP3+7jVkuSVKty6ue0Pft24fe52pv1NV2JfWpqcubq092ux179+5F7969a6xTap8qWEolzPmmAD9tL3EvMwRLmHZ9FEYPCodGU/mmTESfZFl2H9cVbwjVfOxdaHlT+2S327Fnz55aj+sLtd2f+1Tfcl/0yel0uo/pquuV3Cd/2E+/pJdBkiov1bsQSQLOFjrdr+WvfarK3/dT1fcg57+Gt/oUFx2M64dG4Mu1ZpQ7gM/XmPHYLTGq2098v8f3e560vTHLfdUnALWeP5TcJ3/dT3a7Henp6e6sA6FPnizn+73G96mu9TUe79GjzvPPf/4Tr7zyCqKionDHHXcgKSnJ4xdsTidPngQATJgwoca606dPIyUlBf/5z3/w6KOP1rmNiulw8fHxzdJGokAkyzI27ijBf78uQGFx5Wh8384heOzWGLSI8f35gYioLmaL06MBKcA1cGW2OOt/IPmdSVdF4LtNRSgplbF6WzFuGRGJxFj+fiIiIvKlRv0m/vTTT9GuXTukpaUhNjbW223yWFZWFkwmEzp06ICgoCBceeWVWLZsWY3H3XfffWjXrh3+8Y9/oGvXrgBcM6GMRmO10cDy8nK89tpr0Ov1GDZsmLB+EClZnsmBt77Kx9bdldcfhxskPHhjNEb0C6s2ZZ2IyB9FhmkaNFMqMqzmt47k/4zhWtwwLAILV5thdwCf/WDCE7f57n0sERERNXJQKjs7G/fff3+zDkjNmTMHhYWFyMzMBAAsX77cXbzroYcegtFoxDPPPIP58+fj+PHjSE5ORtu2bdG2bdsa23r00UfRokULjB8/3r3s+++/x8svv4yJEyciJSUF+fn5+OKLL5Ceno5XX30ViYmJzdY3f3WhabHkXYGQtSzLWPOrBe8uLkCxtfKT3KDuBjxycwxijf7Rx0DIWimYtRjM2fsGdg/F5l3W+h8I18DVoO6hzdwi9RF1XE8cHomlG4pgscr44RcLbhkRidbxQUJe21/wHCIOsxaDOYvDrMVRU9aNKnTeqVMnDBgwAJ988klztAmAqzj5iRMnal1XMQg1ZcqUaoNSF9rW+YXO//jjD7z00kvYsWMHzp49C71ejx49euDhhx/GjefdsvpCzGYzjEZjvcW7iALJmXw73vwiH9v3l7qXRYVr8PDNMRjS08DZUUSkKLZyGROfPgWLVb7g3fckAGGhEhbPSoI+iOc5pVqwyoR5K1x3HbqmfxieuoOzpYiIiLzN07GSRg1K/fe//8Urr7yCvXv3IiEhoUkNVbpAGZSSZRkmkwlGo5EDCs1MyVk7nTKWbynGh8sKYS2rPHVc1ScUD94YDWO4f43oKzlrpWHWYjDn5rNtTwlmfJALyKh1YEo6959/TovDgG6cKeVNoo/rYqsTt83IRFGJExoJmPt8S7RpoY7ZUjyHiMOsxWDO4jBrcQIla0/HShpVFGHcuHG44oorMGDAACxYsADp6ek4efJkrX9IGRwOBw4ePCj0bolqpdSsT+WU4//eysHbXxW4B6TiorR45f54PHtXnN8NSAHKzVqJmLUYzLn5DOgWipnT4hAW6nrzV/EesOL/YaESB6SaiejjOtygwaSrIgAAThlYuMok5HX9Ac8h4jBrMZizOMxaHLVl3aiaUikpKZAkCbIs46677qrzcZIkwW63N7pxROR7DqeMJT8X4dPlJtjKK+cPXDcwDNMmRCPcwIK/RBQYBnYLxeJZBmzcUYLNuyw4nW1C60QjBvcIw5BeobxkL4BcPzQCi38ugqnYiZ/SSnDbyHK0a6mO2VJERET+pFGDUnfccYeip5ERkWeOZ9rw78/ycTDD5l7WMlaLx2+LRa/UEB+2jIioeeiDJFzdLwzDLgtGWtox9O6dAp2uUW+XyI+Fhmhw09WR+HBZIWTZVWdqxj1xvm4WERGR6jTqXda8efO83AzyNUmSYDCwQLUISsja7pDx5RozFq42wX5u1qgkub5ZvmesEYZgZcyOUkLWgYJZi8GcxWHW4vgq63FXhOObdWYUFDmx/o8S3DbShvat9ULbIBqPa3GYtRjMWRxmLY7asm5UoXOqFCiFzokqHD5pw78W5uHY6XL3sjYtdHhyciy6dAj2YcuIiIi865ufzHhvSSEAYHAPA166L963DSIiIgoQzVronAKP0+lETk4OnE6nr5sS8Pw1a1u5jI++LcQD/8p2D0hpNMCt10Tio2dbKnJAyl+zDkTMWgzmLA6zFseXWY8dHI6YSNfb4c27rPjzL1s9z1A2HtfiMGsxmLM4zFoctWXd6EGpoqIizJo1C8OHD0enTp3Qvn37Gn86dOjgzbZSM3I6nTh27JhqDnxf8ses04+WYeqrWfhyrRkVzWrfOgjv/j0R946LUmxxX3/MOlAxazGYszjMWhxfZh2s1+DWa4zun+evDOw78fG4FodZi8GcxWHW4qgt60bVlDp79iwGDBiAo0ePIjIy0j0ty2azwWq1AgBatWqFoCDexYTIn1nLnPjku0Is21iMigt5dVrg9lFG3DwiEkE6ZQ5GEREReWr0oHB8/aMZZwsd2LbHikMnynBJO+XNDiYiIlKiRs2UevHFF3H06FEsWLAABQUFAIDHHnsMFosFv/32G/r27Yvk5GTs27fPq40lIu/ZcbAU976chaUbKgekUpP1+OCZRNx+rZEDUkREpAr6IAm3jaysdTFvRWDPliIiIvInjRqUWrVqFYYPH47JkyfXqAjfp08frF69GhkZGXjppZe80khqfpIkwWg0qqbCvy/5OutiqxOzP8/DE//NQVae69Z6+iAJ0ydE4X9PtEBKq8C585Cvs1YTZi0GcxaHWYvjD1mPGhCOhBgtAOC3faXYd6zMZ21pTv6QtVowazGYszjMWhy1Zd2ou++FhITg4Ycfxr/+9S8AQFBQEJ544gnMmjXL/ZipU6di3bp1OH78uPda64d49z1Skl/2WvGfL/ORW+hwL+vWMRhPTI5BUgIvtyUiIvVaubUYb3yeDwC4LDUE/344wcctIiIiUq5mvfue0WhEeXnl7eKjo6Nx6tSpao+JjIzEmTNnGrN58gGn04lTp06pppiaL/kia1OxA6/OzcU/3jvrHpAyBEt45OZovPloQsAOSPG4FodZi8GcxWHW4vhL1tf0D0PLWNdsqT8OlmLPkVKftqc5+EvWasCsxWDO4jBrcdSWdaMGpdq3b4+MjAz3zz179sSPP/6IvLw8AIDVasXy5cvRtm1brzSSmp/aDnxfEpm1LMvYsKMEd83MwrrtJe7lfTqH4JPnWmLcFRHQaAJ3WiiPa3GYtRjMWRxmLY6/ZK3TSrj92so78QVibSl/yVoNmLUYzFkcZi2O2rJu1KDUiBEj8NNPP6GkxPUhd9q0acjJyUH37t1x4403okuXLjh69CimTJnizbYSUQPkmRx44cNczPw4F4XFrhNauEHCU3fE4LUH45EY26ibbxIREQWsq/uGISnB9ftx1+Ey7DwUeLOliIiI/EmjBqWmT5+Ojz76yD0oNWHCBPz73/+GxWLBkiVLkJ2djf/7v//Dk08+6dXGElH9ZFnGml+LcdfMTGzZbXUvH9TdgLnPt8I1/cNVUzSPiIioIbRaCXecN1uqEeVXiYiIyEONmirRsmVL3HTTTdWWPf7443j00UeRm5uLhIQEfuhVGI1Gg/j4eGg0jRqnpAZozqzP5Nvxny/y8fv+ym92o8I1ePjmGAzpaVDdv0se1+IwazGYszjMWhx/y3pY71B8ttqEk2fs2Hu0DH8cLEXvTgZfN8sr/C3rQMasxWDO4jBrcdSWdaPuvkeVePc98gdOp4zlW4rx4bJCWMsq/0lf1ScUD94YDWO41oetIyIiUpb1aRb881NXrdTOKXr874kWqvtih4iIqCma9e57FXbu3Im///3vGDt2LK666ir38hMnTmDRokXIz89vyuZJIKfTiaNHjyqumFrBkSP4cfp0zO/RA2/odJjbpUuDt/HHW29htiRh6ejR1ZafWLcOy2++GR8mJ+Ot0FB82rkzfv/3v+GocufJxvB21qdzyvH42zl4+6sC94BUrFGLV+6Px7N3xal6QEqpx7USMWsxmLM4zFocf8x6SK9QpLRy3Zl2/3FbtRnISuaPWQcqZi0GcxaHWYujtqwbPSj197//Hb1798bs2bOxYsUKrF+/3r1OlmXceuutWLhwoVcaSc3P6XTi7Nmzijvw8/btw7GVKxHVsSNiO3du8PMt2dnY9tJLCE1IqLFu9wcfwFZUhIEzZ2LCqlW49I47sO2FF7D2vvua1GZvZe1wyli0zox7X8nG7j/L3MuvHRiGuTNa4vKugXGpQVMo9bhWImYtBnMWh1mL449ZazQS7ryuSm2p5YFRW8ofsw5UzFoM5iwOsxZHbVk3alBq7ty5mD17NkaPHo09e/bgmWeeqbY+OTkZffv2xffff++VRhLVpcOYMZj2118Yt3gxWvTq1eDnb/z739Fh7FjEdOpUY91V772HG1auxKV33IG2Q4ei39NPo/9zz2Hf/Pkoyc31RvMb7XimDQ/PPoP3lxairNz1JjkxVovZDyfgidtiER6qjuuPiYiImsug7gZ0THLNljp00oZte631PIOIiIgaqlGfXN9991106tQJS5YsQZcuXaDX62s8JjU1FX/++WeTG0h0IVITir+d2rIFR779Fle89lqt60Pj4mosS+jZE5BlWLKyGv26TWF3yFi42oRps7JxIMMGAJAkYMLQcHzyj5bolRrik3YREREFGo1Gwp2jq9+Jz+lU/mwpIiIif9Kou+/t378fU6dOhU5X99NbtGiBnJycRjeMxNJoNEhKSlJNhX+nw4Gf/vY39PvHPxDesqXHzzu9ZQu0wcEwpqQ0+rUbm/Xhkzb8+7M8HD1VWdOqTQsdnpwciy4dghvdnkCmtuPal5i1GMxZHGYtjj9nPaCrARe31ePwSRuOnirHlt1WXNEz1NfNajR/zjrQMGsxmLM4zFoctWXdqEEpnU4Hm812wcdkZmYiPDy8UY0i8SoOfLXY9e67KLdY0Puxxzx+TsGff2LH22+j+/Tp0Dfh2G5o1rZyGQtWmfDVj2ZUXFas0QA3XRWJO68zQh/EuwHVRW3HtS8xazGYszjMWhx/zlqSJEwZbcSz754FAMxfacKg7gZoNMr83evPWQcaZi0GcxaHWYujtqwbNfTWtWtX/Pzzz3A4HLWuLykpwbp163DZZZc1qXEkjsPhwIEDB+rcp4HEkpODrc8/j2FvvgltLZee1qbMbMZ3EybAmJKCQa+80qTXb0jW6UfLcN+rWfhiTeWAVPvWQXj374mYOj6KA1L1UNNx7WvMWgzmLA6zFsffs+53aQg6JbveLxzPLMemnSU+blHj+XvWgYRZi8GcxWHW4qgt60YNSt199904fPgwpk+fjrKysmrrzGYzpkyZguzsbEydOtUrjaTmJ8syTKbAuLNMfbY9/zziu3VD68GDUVpYiNLCQsh2O5x2O0oLC+G026s93mGz4bvrr0dpQQEmrFoFfVhYk17fk6ytZU7M+aYAj7x5BifPuNqj0wJ3jTbivacScXFbzwbT1E5Nx7WvMWsxmLM4zFocf89akiTcNaayttT8lSY4FFpbyt+zDiTMWgzmLA6zFkdtWTfq8r27774b69atwyeffIKvv/4aUVFRAIC+ffviwIEDsFgsmDJlCiZOnOjNthJ5Rd7Bgzi1aRPmREfXWDcnOho3rF6NlJEjAQCy04mVt92GM3/8gZs3b0ZkmzbN3r4dB0vxxud5yMqrHBm/pJ0ef789BimtOBhFREQk2mWpIejaIRh7j5bhRLYd69NKcFXfpn1JRURERI0clAKAL774AsOGDcOcOXOQnp4OWZaRlpaGTp064eGHH8a0adO82U4ir7nyrbdQWlhYbdn6Rx+FzmDA4FmzEN+tm3v5ugcfxNHlyzFxzRrEd+3apNe1lcvYsKMEW3ZZcDo7Fqt252NQjzAM7RUKfZCEYqsTHywtwMqtFvdz9EES7hptxMQrI6DV8lI9IiIiX6ioLfX4266b+CxYZcKwy0L5u5mIiKiJGj0oBQBTp07F1KlTYbVaUVBQgMjISBY3VyiNRoP27dsrrsJ/eUkJjq1aBQAwnzgBm9mMQ4sXAwDaDBmC0Ph4LBo+HOYTJ3DvkSMAgIQePWpsJzgqCvrwcLQdOtS97NdXX8Xu999HnyefhDY4GJm//upeF9u5M4IjIz1u59Y9JXh9fh6KrTIkCZDlYGTklGLL7lLMWZSP8UMj8MMvFuQWVs6O6toxGE9OjkFSQlBDIqEqlHpcKxGzFoM5i8OsxVFK1j0vCUGPi4Kx688ynMqxY912C67pr6z3vUrJOhAwazGYszjMWhy1ZS3JarlQsZmYzWYYjUaYTCZENmCQgrzDlJGBj1JSal03af16tB06FF8NHQpzRgbuy8iocztfDR0KfXg4JqxYUW3ZqY0bL7htT2zdU4LnP8gFZMCTf2yGYAn3jY/CmMHhir27DxERUSDa/WcpHvuPa7ZUyzgd5r/QEjrOliIiIqrB07ESDko1UaAMSjkcDqSnp6NLly7QarW+bk7AsJXLmPj0KVisskcDUr0uCcYTk2ORGNukSYx0Do9rcZi1GMxZHGYtjtKyfvK/OfjjYCkA4InbYnDtQOXMllJa1krGrMVgzuIwa3ECJWtPx0o8/uTbvn37BjdCkiQcPXq0wc8j8WRZhtVqVU2Ff1E27ChBsdXzTEf0D+OAlBfxuBaHWYvBnMVh1uIoLespo43uQamFq024ul8YgnTKmC2ltKyVjFmLwZzFYdbiqC1rjz/9ZmRkQKvVQqfjB2YiT23dXXKuhlT9j5UkYOtuK0b0U843rkRERGpzaftg9L00BL/vK8WZfAdWbyvG2CsifN0sIiIiRWpw5ayhQ4diwYIFMJvNsFqt9f4hUjOzxenRgBTgGrgyW5zN2yAiIiJqsinXGd1///wHM2zl6vg2m4iIyNs8HpTav38/HnnkEezatQs333wzWrVqhcceewx79+5tzvaRIFqtFqmpqYq+ZtUfRYZpIHk4o1+SXI8n7+FxLQ6zFoM5i8OsxVFi1qnJwbi8qwEAcLbQgZVbi33cIs8oMWulYtZiMGdxmLU4asva40/AqampmD17Nk6dOoUlS5bg8ssvxzvvvIMePXqgd+/eeO+992AymZqzrdSMJElCVFQUJE9HUMgjA7uHNmim1KDuoc3bIJXhcS0OsxaDOYvDrMVRatZTRlfOlvpijRllNv+f7azUrJWIWYvBnMVh1uKoLesGT8vQarUYP348vv/+e/z111949dVXYbFY8OCDD6JVq1aYPHkyTp482RxtpWZkt9uxfft22O12XzcloAztFYpwg4T6TicSgPBQCUN6cVDKm3hci8OsxWDO4jBrcZSa9UVt9BjcwzVbKs/kwPIt/j9bSqlZKxGzFoM5i8OsxVFb1k26VqhFixZ46qmncODAAfz444+IiYnBl19+iV27dnmpeSSSw+HwdRMCjj5IwtN3xl7wMdK5/zx9Ryz0QeoYDReJx7U4zFoM5iwOsxZHqVnfWaW21JdrzLCW+f9sKaVmrUTMWgzmLA6zFkdNWTe5gM327dtx//33Y+LEiTh9+jRatWqFpKQkb7SNKCAM6BaKfufqTlRVMRszLFTCP6fFYUA3zpIiIiJSkvat9Rh6bpZzQZET323y/9lSRERE/kTXmCfl5uZi4cKFmDt3Lvbt2wedTocxY8bgnnvuwTXXXAONhsWaiSqU2ZxIP1IKANBqgd6pwcjJNaN1ohGDe4RhSK9QzpAiIiJSqDuuM2LjzhLIMvDVWjPGDg5HaAjfCxMREXlCkmXPyjA7nU6sWrUKn376KVauXIny8nJ06dIFd999NyZPnoy4uLjmbqtfMpvNMBqNMJlMiIyM9HVzGk2WZVitVhgMBtUUVBNl7W8WvDY/DwAwol8YnrojhlkLwuNaHGYtBnMWh1mLEwhZvzI3Fz9tLwEA3DvWiFtHGut5hm8EQtZKwazFYM7iMGtxAiVrT8dKPJ4plZSUhDNnzsBoNOKee+7B3Xffjd69e3ulseQf9Hq9r5sQkFZUKXw6elA4AGYtErMWh1mLwZzFYdbiKD3r2681Yn1aCZwy8PW6IowbEoEwg3/OllJ61krCrMVgzuIwa3HUlLXHvy2zs7Oh0+nQvXt3ZGRk4Pnnn8e11157wT/XXXddc7advMjhcCAtLU1VBdVEOJ5pQ/rRMgBAcssgXNpez6wFYtbiMGsxmLM4zFqcQMi6bYsgXN0vDABQVOLEkvVFPm5R7QIha6Vg1mIwZ3GYtThqy7pBNaXKy8uxceNGjx+v5KlmRN6w8rxZUvw3QUREFJgmj4rEj79b4HQC3/xkxvVDIxAR6p+zpYiIiPyFx4NSx48fb852EAWcMpsTa3+zAAD0QZL7G1QiIiIKPK3jgzCyfxhWbbPAYpWx+Ccz7hoT5etmERER+TWPB6XatWvXnO0gCjgbd5Sg2Oq6j8Cwy0L5bSkREVGAmzzKiDW/WuBwAkvWF2HCsAgYw7W+bhYREZHf8vjue1Q7d0X5jRsRGR5euSI6GkhJAUpLgf37az6xVy/X/w8dAiyW6uuSk4GYGODsWeCvv6qvi4gALroIcDiA3btrbrdrVyAoCDh6FDCZqq9r3Rpo0QIoKADOm/kmh4TAcfHF0Gq1kHbtAs4/LDp1AgwG4MQJIC+v+roWLVzbLioC/vyz+rqgIFebAGDvXqC8vPr6iy5y9en0aeDMmerrYmOBdu0AqxU4cKD6OkkCevZ0/f3AAddjqkpJce2DM2dc267KaAQ6dHC1Ze9e1NC9O6DVuvpSdF5NiDZtgPh4ID8fyMiovi4sDLjkEtffd+zA6wtycey0q79PTo5Fx2t6ACEhkI8dgyM315V1xeV8LVu6/pjNwJEj1bcbHAxceqnr73v2AHZ79fUXXwyEhwOnTgE5OdXXxcUBbdsCJSXAwYPV12k0QI8err/v3+86Vqtq3x6IigKys4HMzOrroqJc6202ID0dNfTo4dr+4cNAcXH1dW3butqVmwucPFl9XXi4qz9OJ7BrV83tdukC6PXAsWNAYWH1da1aAYmJruXHjgFw3bnC4XBAGxYGqSLDXbtc268qNRUIDXW1Jze3+rqEBCApydWPw4err9PpgG7dXH/ftw8oK6u+vmNHIDISyMpy/alKYecIGAyu8wAA7NxZ4xwhp6bCoddDe+oUpPz86s/lOcLlvHNEDZ07AyEhruwLCqqvO3eOkE0mOA4dqn7+4DmiUgPPEW4hIa78Afc5wn3+0GohderEcwTQpHPEhd5HyAkJcCQmQltSAun834EKPEe8tb8Nvt9mRevC45jQG7h+aETlymY+R9T3PkLevRuOsrLq5xAFnCMK/voLaQsXInPvXuQePYqY1FTctWFDg84Rf3zxBda/8QbaX3cdJvz3v+5zRElBAX79+GNkHjqEs/v2QRMUhEc2baq+3VrOEdXU8j7CfQ5p2RJSmzY8RzThHHGh9xGyTgdH586uYzo9XRHnCF++j2jKZw35r7/gyMqqfv7wk3NENX7yPqKaBn7WcJ8/goMhde/uepwCzxHm06dhHDKk3rvvQaYmMZlMMgDZ5Dq1Vv657TbXA/78s/ryij8V+vevuW7hQte6OXNqrhsxouKFa99uTo5r/ZgxNde98YZr3aJFNdY5e/aULRaL7HQ6ZVmvr/nc9HTXc++5p+a6p592rVu/vua61q0r+9q6dc3169e71j39dM1199zjWpeeXnOdXl+53Z49a65ftMi17o03aq4bM8a1Lien9gxNJtf6ESNqrpszx7Vu4cKa6/r3r2xTbdv9809ZlmXZedttNde98ILreT/8UHNdhw6V242Lq7l+2zbXusceq7nugQdc6/74o+a6iIjK7XbuXHP9d9+51r36as11Eye61v31V+19LS11rR8ypOa6jz5yrfvoo5rrhgxxrSstrX27f/3lWj9xYs11r77qWvfddzWP786dK/saEVHzuX/84Vr3wAM11z32mGvdtm0118XFVW63Q4ea63/4wbXuhRdqrlPYOULu2bOyTbWcI5x797rOIXffXfO5PEe4/nh4jpAvcI5wrl5dcx3PEZV/GnmOkHmOqPzTTOeIC72PcD71lOv88fPPNZ+nwHNEzvE8ecRDJ+Tf21xRc30znyPqex/hVOg54k9Afh+QvwXkua1by59eemmDzhHFgPxfQH4nLk5ect111c4RZwD5HUBekpoqfz5ggPxWSEjN7TbhHOF89FHXOp4jKtvkxc8aztatKz/DKOQc4cv3EU35rOF89NGa6/zkHFHtTwC9j3Aq/BxhAmQAsqnimK8DZ0o1UaDMlLIHBSHNYkHv3r2h27vXdUhVxZlSLh5+e/HVa+ux/o8SAMBNV0fiyt5h7m8v7H/+if3btqFzp07Q6c5dQcuZUi5e/vbCbrdj/4ED6NyzJ3QV30RyplSzfMNpv+gipO3bh97x8dCdv12eI1y88A2nPT8f+5cvr37+4Dmikhe/4XSfPzp1gq5LF54jgGabBWGPjUVaVhZ6X3IJdOdvV6HniP8uNmH7d3sRWl6Mq/uFYeKV574h9vEsCPuOHdi/d2/1c4gCzhGy0wlJ4yqDsPpf/0J2enqDZkqtev55AIC5qAj6iIhqM6Xc227VClvffx9ps2d7ZaaU+xwyZAh0yck8RzTTTCm7JCGtrMz1GebAAcWcI5Q4U8qekYH9GzdWP3/4yTmiGj95H1FNAz9ruM8fXbtCV/FvWYHnCE9nSnFQqoncg1L1TUnzc3a7HWlpaa4TesVJhhql1ObEjc+chsUqIzhIwjezWiO8Sj0pZi0OsxaHWYvBnMVh1uIEYta5hXbc9nwmyu1AcJCEz2e2QozR97WlAiHr1VOmIDstDXfV9kG1Fqe2bMHSa6/F3YcOYcUtt0AfHo4JK1bU+titL77oGpQ6/0NuIwRC1krAnMVh1uIEStaejpWw8jKRl234owSWcwXOh14WWm1AioiIiAJfXJQOY69w1ZIqK5fx5Y9mH7dInZwOB37629/Q7x//QHjLlr5uDhER1YKflslNq/X9N3iBYMWWym/XxgwOr/UxzFocZi0OsxaDOYvDrMUJxKxvuToSwUGuYsDfbypCbqG9nmeIEYhZ12XXu++i3GJB78ce88nrqylrX2LO4jBrcdSUNQelCACg0+nQp08fRU8P9AfHTtuw/7gNANC+VRA6JetrPIZZi8OsxWHWYjBncZi1OIGadYxRi3FDXF9OlduBL9b4frZUoGZdG0tODrY+/zyGvfkmtPqa78eam5qy9iXmLA6zFkdtWXNQigAAsiyjsLAQLDHWNMurzJIaPTi88napVTBrcZi1OMxaDOYsDrMWJ5CzvvnqSIQEu94LrNxajDP5vp0tFchZn2/b888jvls3tB48GKWFhSgtLIRst8Npt6O0sBDO84s5e5masvYl5iwOsxZHbVlzUIoAAA6HAwcPHoTD4fB1UxSr1ObEut9cdy4IDpJwVd+wWh/HrMVh1uIwazGYszjMWpxAzjoqQosJQ121pcrtwBc/+Ha2VCBnfb68gwdxatMmzImOdv85vXUrMtaswZzoaJxYt65ZX19NWfsScxaHWYujtqzVMR+MSID1f5TAUuoazR7WOxThBo75EhERqd2NwyPw7cYilJTKWLWtGLdcE4nEWL4Fb25XvvUWSs+7pfv6Rx+FzmDA4FmzEN+tW7O8rq1cxoYdJdiyy4LT2bFYtTsfg3qEYWivUOiDas6gJyJSO/5GJPKSFZurFDgfVHuBcyIiIlIXY7gWNwyLwMLVZjicwGerTXhicqyvm6Uo5SUlOLZqFQDAfOIEbGYzDi1eDABoM2QIQuPjsWj4cJhPnMC9R44AABJ69KixneCoKOjDw9F26NBqyyu2lbd/P2SHw/1zYp8+MLZr53E7t+4pwevz81BslSFJgCwHIyOnFFt2l2LOonw8fWcsBnQLbWj3iYgCGgelCAAgSRIMBkOtNZCofkdP2XAgw1XgvENSEFJrKXBegVmLw6zFYdZiMGdxmLU4ash64vBILN1QBItVxg+/WnDLNZFoHR8kvB1KzbokJwfLb7yx2rKKnyetX4+2Q4fC6XA0uk5UXdseOXcujFOmeLSNrXtK8PwHucC5EjDyef+3WGXM+CAXM6fFYSAHprxGqce0EjFrcdSWtSSrpXpWMzGbzTAajTCZTIiMjPR1c8hH3v4qH99tcs2UeuSmaIwbEuHjFhEREZE/WbDKhHkrTACAEf3C8PSdnC0VKGzlMiY+fQoWq4wLfbCSAISFSlg8K4mX8hFRwPN0rIRFbwgA4HQ6kZOTA6fT6eumKI61zIl1v7sKnIfoJQyvo8B5BWYtDrMWh1mLwZzFYdbiqCXrG4ZFICLU9dZ73e8WnDxTLrwNaslatA07SlBcz4AU4JpEVVwiY+OOEhHNUgUe0+Iwa3HUljUHpQiA68A/duyYag58b9pQpcD5lR4UOGfW4jBrcZi1GMxZHGYtjlqyDjNocNNVrpnUThlYuMokvA1qyVq0rbtL4OlVNpIEbNnNQSlv4TEtDrMWR21Zc1CKqImWb6kscH4dC5wTERFRHcYPjYAx3PX2++e0EmRkiZ8tRd5ntjjhaUEUWXY9noiIXDgoRdQER/6y4eC5Aucdk4KQ2q7uAudERESkbqEhGtx0tauuhiwDC1aKny1F3teQCr2SBESG8SMYEVEFnhEJgKvCv9FoVE2Ff29ZUWWW1OhB4R7lx6zFYdbiMGsxmLM4zFoctWU97opwREe43oJv2FGCY6dtwl5bbVk3N2uZE3MW5WPPkTKPnyPLwKDuvPuet/CYFodZi6O2rHn3vSbi3ffUy1rqxI3PnkZJqYyQYAnfvNoaYfXUkyIiIiJa/LMZ7y4uBAAM6m7AzGnxvm0QNdjOQ6WY/VkesvIcHj+Hd98jIjVR9N33iouL8cILL2DkyJGIiYmBJEmYN29eo7Y1depUSJKE0aNH17r++++/R69evRASEoK2bdvihRdegN1ub0LrlcnpdOLUqVOqKabmDev/KEFJlQLnng5IMWtxmLU4zFoM5iwOsxZHjVmPGRSOWKMWALBltxWHT4qZLaXGrL2tpNSJ/3yZj8ffznEPSOmDJIy6PAyS5Bp4qpMEPH1HLAekvIjHtDjMWhy1Ze2Xg1K5ubmYOXMmDhw4gO7duzd6O2lpaZg3bx5CQkJqXb969WqMHz8eUVFR+N///ofx48fj5ZdfxkMPPdTo11QqtR343lC1wPnogZ4XOGfW4jBrcZi1GMxZHGYtjhqzDtZrcOs1ld8azxdUW0qNWXtT2gEr7n45C8s3V74H7NoxGB//IxFP3h6LmdPiEBbqGnCq7aqbiVdGYEA3XrrnTTymxWHW4qgta52vG1Cbli1bIisrC4mJiUhLS0OfPn0avA1ZlvHwww/jjjvuwE8//VTrY5544gl069YNa9euhU7niiIyMhKvvvoqHnnkEaSmpjapHxS4/vzLhkMnzhU4bxOES1jgnIiIiBrguoHh+GqtGWcLHfhlrxUHM8qQmhzs62ZRLYqtTry/tACrtlrcy0L0Eu4dF4XxQ8Kh0bhGoAZ2C8XiWQZs3FGCzbssOJ1tQmhoOPYdd91lceOOEtw1xogQvV/OCyAi8gm/PCMGBwcjMTGxSdtYuHAh0tPT8corr9S6fv/+/di/fz/uu+8+94AUADzwwAOQZRmLFy9u0utTYKta4HyMhwXOiYiIiCrogyTcNrJyttQ83onPL/2absXd/8yqNiDV4+JgfPxcS0wYFuEekKqgD5Jwdb8wPH9PDKZek4f/PBaPfpe6rtrIKXDgm3VFQttPROTv/HJQqqmKiorw1FNP4dlnn61zcGvnzp0AgN69e1db3qpVKyQlJbnXq4VGo0F8fDw0moA8JLzKWurET9tdb0xCgiVc2TusQc9n1uIwa3GYtRjMWRxmLY6asx41IBwtYly1pX7fV4p9xzy/i1tjqDnrhioqceK1+Xl49t2zyC101Y4yBEt49OZozH44Aa3iLnzBSdWsp0+IRkXkX64142yh+urXNhce0+Iwa3HUlrVfXr7XVDNnzoTBYMBjjz1W52OysrIAuC4VPF/Lli2RmZlZ6/PKyspQVlb5hsFsNgMA7Ha7u0C6RqOBRqOB0+msdh1oxXKHw4GqNz2sa7lWq4UkSTUKr2u1rjcvDofDo+U6nQ6yLFdbLkkStFpttTa2a9fO/fp1tV1pfbrQ8sb2ad3vxe4C58MuMyA0xPUNWUP61L59ezgcjmqv68s+BeJ+qljerl07OJ1OSJIUMH2q2kZ/6lOHDh3gdDqrtUfpffK3/SRJkvuYrjiuld4nf95P7dq1gyRJNdqo5D5dqO2+7FNycnK1dYHQJ0/2kwRg8qhIvPF5AQDg0+UFeP3BuGbtE9/v1d+nX/aW4j9f5iPfXPn4y1KD8fhtsYgzAk6nAxWb8uT9Xut4CWMGheG7TRaU2mR8/F0hnrwtSmifAnE/aTSaau/1nE5nQPTJn/dTSkpKwPXJH/dToLzf8/QGcgE3KHX48GG8/fbb+PLLLxEcXPd1+VarFQBqfUxISIh7sOl8s2bNwksvvVRj+c6dOxEW5poxEx8fjw4dOuD48eM4e/as+zFJSUlISkrC4cOHYTJVTtFu3749EhISkJ6e7m4XAKSmpiIqKgo7d+6stsO7desGvV6PtLS0am3o3bs3bDYb9uzZ416m1WrRp08fmEwmHDx40L3cYDCge/fuyM3NxbFjxwAAJSUlSExMROfOnZGZmYlTp065H6/UPgGA0WhEp06dvNanxT/louKfTvvoEzCZdA3qU69evXD06NFq2/Z1nwJxP1X0qaSkBKGhoQHVJ3/cT3Fxce4P77m5uQHRJ3/cTwUFBdi1axdCQ0MDpk/+vJ9KSkrQt29fhISEBEyfAP/bT61atcJvv/1W7RthpfepIfupX+olaBmnQ1auHTsP2fDNyj1IaWHj+z0f7CdLqQbr97fCtvTKD3HBQU5c19uM20a3QXS0Dtu3b2/U+72uiRLW6lvAatPgx99KcFHsCSTFlTd7nwJxP1Xt0969e5Gfn+/+vRgIffLn/aTRaNC7d++A6pM/7qdAeb9nsVjgCUmuOhTmhyoKnc+dOxdTpkyp9/GjRo2C1WrFhg0b3MuSk5PRpUsXrFixwr1s9uzZePLJJ3Hy5Em0adOm2jb69u0LrVaLX375pcb2a5sp1aZNG+Tl5SEy0lUXwF9GJit4MoLscDiwY8cO9OrVC8HBwX472tqQPtW3vDF9OnLKjumvZQMAOiYF4d2/xze4T7IsIy0tDb169XI/xpd9CsT9VLHcbre7j2u9Xh8QffLX/eR0Ot1ZV/1gqeQ++eN+Ki8vr3b+CIQ++et+qvi92Lt3b+h0uoDoU31t91WfnE4ntm/fXu33otL71ND9tPY3C15fkA8A6N5Rj38/HMf3ex72qb7lnvZp8y4r/veNCYVFlY/p2zkYj9wUhfhorVfe7y3bUIz3lrq++L60vR5vPhLrnsnNc0Tj+lRWVuY+prXahu8nf+yTv+6nivNHnz593P1Sep+qttGf9lOgvN8zm82IjY2FyWRyj5XUJqBmSv3888/44YcfsHTpUmRkZLiX2+12WK1WZGRkICYmBpGRke7L9rKysmoMSmVlZaFv3761vkZwcHCts6t0Ol21gulA5c49X9WBCE+Wn7/dxiyXJKnW5VXbWHFQX6jtSutTU5bX1vaqBc7HXhFR7fU9bbvdbndnff46X/TpQsuVup8qlsuy7M66ohi90vvkaRsburypfap6+XJt21Fin+pb7qs+1Xb+UHqf/HU/VeRdVxvPf3zV5/lrnxq7vDn7VPXShPNfQ6l9Ahq2n67qE4bPfzDjVI4du4/YsPeoHT0v0dXZ9rqW8/1ew5ebS4C3vyrApp2VswPCDRL+dmM0ru4X5n7/0NC21/Z+7/phRqzYWoK/ztix75gNW/fYMPSyytqkPEc0rk+1nT+U3idP29jQ5U3tU8W/h0DqU33L+X6v8X2qa/35Aqpy1smTJwEAEyZMQEpKivvP6dOn8fPPPyMlJQWffvopAKBHjx4AUGPKWcXUt4r1RBVKqhQ4NwRLuLJ3qI9bRERERIFAq5Vwx7VG98/zVpiqfVtN3ifLMn7absFdM7OqDUgN7GbA3OdbYUR/799dWaeVcP+EaPfPHywrhK2c+5mI1E3RM6WysrJgMpnQoUMHBAUF4corr8SyZctqPO6+++5Du3bt8I9//ANdu3YFAFx66aVITU3Fhx9+iGnTprlHBd977z1IkoSJEycK7YuvaTQaJCUl1TqSSi4/p5XAWuZ64zC8TxhCQxqXFbMWh1mLw6zFYM7iMGtxmLXLsN6h+PwHE05k27H3aBnSDpSiT2eDV1+DWbvkmRx468t8bN1TORgVGabBwzdFY9hloV4ZjKor635dQnBZagj+OFiKM/kOLP7JjFtHGuvYCtWHx7Q4zFoctWXttzWl5syZg8LCQmRmZuK9997DhAkT0LNnTwDAQw89BKPRiClTpmD+/Pk4fvw4kpOT69xWbTWlAGDFihUYO3Yshg0bhptvvhnp6emYM2cO7rnnHnz44YcetdNsNsNoNNZ7nSQp37RZWfjzL1dByvefTsTFbfU+bhEREREFkg1/WDDzkzwAQKdkPeY82cLrs3XUTJZl/Ph7Cd75pgBFJZV1Vq7oacDDN8UgJrL2S1e87XimDVNfyYZTds2+X/hiK8QYxbw2EZEono6V+O3Q2+zZszFjxgy89957AIClS5dixowZmDFjBgoKCrzyGqNHj8bSpUuRn5+Phx56CEuXLsWzzz6Ld955xyvbVxKHw4EDBw7UKFZGLodP2twDUpe01TdpQIpZi8OsxWHWYjBncZi1OMy60hU9Q5HSKggAcCDDht/2lXp1+2rO+myhHf947yxem5/nHpCKCtfghXvj8OLUeK8PSF0o65RWeoweFA4AsJbJ+HR5oVdfW03UfEyLxqzFUVvWfnv5XtVC5XWZN28e5s2b16RtjR8/HuPHj/e4XYFKlmWYTKxfUJflm4vcf7/u3JuIxmLW4jBrcZi1GMxZHGYtDrOupNFIuPM6I178KBeAq7ZUv0tDvDZbSo1Zy7KM1dsseG9JASyllf2+sncoHpoUDWN488xQqi/rKaON+CnNAotVxupfLBg3JAIXteEs/IZS4zHtK8xaHLVl7bczpYj8hcXqxE9pJQCA0BAJw1ngnIiIiJrJoO4GdExyzZY6fNKGbXut9TyD6nIm346n5pzF7M/z3QNSMZEa/HNaHJ67O67ZBqQ8ERWhxe2jXLWkZBl4d3GBaj6AEhFVxUEponr8nGZBaZUC54ZGFjgnIiIiqo9GI+HO0dXvxOd0crCiIZxOGd9vKsLd/8xC2oHKSyBH9AvDpzNaYmB3//iC8fqhEWgd77pwZfefZdiymwOQRKQ+/HRNAFwV/tu3b6+aCv+ekmUZy7cUu38e3cRL9wBmLRKzFodZi8GcxWHW4jDrmgZ0NeCSc/Urj54q99pghRqyzsq144n/5uCtrwrcd02Oi9Li1fvj8fSdsYgMEzM7ypOsg3QSpl0f5f75/aWFsJVzALIh1HBM+wtmLY7aslZHL6leGo0GCQkJqjnwPXXohA1HKgqct9N75Vp/Zi0OsxaHWYvBnMVh1uIw65okScKUMd6fLRXIWTudMpZtKMI9r2Rh1+Ey9/JrB7hmR/XvahDaHk+zHtjdgB4XBwNwDagt3VB0wcdTdYF8TPsbZi2O2rJWRy+pXg6HA7t371ZNhX9PrdhaOUtqjBdmSQHMWiRmLQ6zFoM5i8OsxWHWtevbOQSdU1xfhmVklWPjjpImbzNQsz6VU47H3srB/xYVuEsuJMRo8frf4vHE5FiEG8R/5PE0a0mS8ODEaFTUsv98tQkFRYG1f5pToB7T/ohZi6O2rDkoRQBcl6lZrVYWWKzCYnXi5yoFzodd5p36A8xaHGYtDrMWgzmLw6zFYda1kyQJU6rUlpq/0gRHE2dLBVrWDqeMb34yY+or2dh7pHJ21NjB4fj0uZbo01ns7KiqGpJ1hyQ9Rg0IAwBYSmXMW25q7uYFjEA7pv0ZsxZHbVlzUIqoDj9tryxwfhULnBMREZFgl6WGoGsH16VdJ8/YsT6t6bOlAsXJ7HI88sYZvLekEGXn6jC1jNXijUcS8OgtMQhV2Pu2u8dEITTENV1q5dZiHDtt83GLiIjEUNbZmkgQWZaxokqB8zGDvXPpHhEREZGnzp8ttWCVCQ6HOr45r4vDIePLtWZMfTUL+49XDtxcPzQcH/+jJXpeEuLD1jVeTKQWt4107WunDLy7uEA1sySISN04KEUAAK1Wi9TUVGi1Yu5I4u8OnrDhyClXgfPUZD06JDW9wHkFZi0OsxaHWYvBnMVh1uIw6wvreUmIuxD2qRw7fvzd0uhtKT3r45k2/G32GXz0bSHK7a5lreN1eOv/EvDQpBi/mtXemKxvGBaBlrGux+84VIZf9nrnrouBTOnHtJIwa3HUlrX/nLnJpyRJQlRUFKSKKosqt3KL9wucV2DW4jBrcZi1GMxZHGYtDrOuX9XZUgtXmWBv5GwppWZtd8hYuNqEabOyceiEa3aUJAE3Do/AR/9IRLeO/jc7qjFZ64Mk3Hd9tPvn95cWotzO2VIXotRjWomYtThqy5qDUgQAsNvt2L59O+x2u6+b4nPFVQqch4VIGOqlAucVmLU4zFocZi0GcxaHWYvDrOvXrWMILkt1Dbxk5Tmw5tfGzZZSYtZHT9nwwL+yMXe5CfZzN6Jq20KH/z3RAvffEI0QvX9+nGls1lf0NKBrx8qZcd9tKmqO5gUMJR7TSsWsxVFb1v55FiefUMstJ+vz0+8WlNrOFTjvGwZDsPf/mTBrcZi1OMxaDOYsDrMWh1nXr9psqdWmRs+gUUrW5XYZ81YUYvpr2Tjyl6ukgkYCbhkRiQ+fbYnOKcE+bmH9GpO1JEl4cGI0KiZILFhpgqlYGfvMV5RyTAcCZi2OmrLmoBRRFbIsY3mVS/dGe/nSPSIiIqLGuLR9MPpe6potlZPvwKptxfU8Q7kOn7Th/tezsWCVGQ6na1lyyyDMebIFpo6Pgj4osC9pubitHiP6hQEAiq0y5q00+bhFRETNh4NSRFUczLDh2GnXt3GdvFzgnIiIiKgp7qoyW+rzH8ywlQdWvSFbuYyPvyvEA//Kdr8f02iAyaMi8f7TiUhN9v/ZUd5yz1gjQoJdg2/LNxcjI6vcxy0iImoeHJQiAK4K/926dVNNhf+6VJslNbh5Zkkxa3GYtTjMWgzmLA6zFodZe+6SdsEY0M0AAMgtdGDFlobNlvLnrA8cL8O0WVn4Yo0ZznOzozokBeG9pxJx9xjlzY5qatZxUTrcOiISAOB0Au8vKfBm8wKGPx/TgYZZi6O2rDkoRW56vbpnBRVbnVhfUeDcIGGYlwucV6X2rEVi1uIwazGYszjMWhxm7bk7r6ucLfXFGhPKbM4GPd/fsi6zOfH+0gI8NPsMTmS7ivrqtK5ZYe89lYiL2vhXexuiqVnfODwCCTGuD6W/7y/Fb/us3mhWwPG3YzqQMWtx1JQ1B6UIgKuQWlpamqoKqp1v3e8WlJVXFjhvrru5MGtxmLU4zFoM5iwOsxaHWTfMRW30GNzDNVsq3+zE95s9ny3lb1mnHy3D1FezsWhdEZznrkS8uK0e7z+diNuvNUKnVdbsqKq8kXWwXoP7xke5f35vcQHsjsC6ZLOp/O2YDmTMWhy1Zc1BKSK4CpyvqPKmbgwLnBMREZGfqjpb6qu1ZljLGjZbytesZU68s7gAj7x5BqdyXLOjgnTAveOMeOfJFmjfWj0zBOoz7LJQdE5x5XHyjB3LGzAISUSkBByUIgJwIMOGY5muApKdU/R8M0RERER+q31rPYb2cpUZKChy4ruNyhmo2H24FFNfzcaSn4sgn5v00ylZjw+eaYlbrzFCq+DZUc1BkiQ8eGO0++f5K00wW9Qxe4KI1IGDUkRAtW+dRnOWFBEREfm5O68zQjo3fvPVj2aUlPr3bClrqRNvf5WPx97KQeZZ1+wofZCE6ROi8N8nWiC5ZZCPW+i/OiUH46q+rkFIs8WJBavMPm4REZH3SLIs88LkJjCbzTAajTCZTIiMjPR1cxpNlmU4HA5otVpIkrq+oSouceLGZ06jrFxGmEHCN7NaN1s9KUDdWYvGrMVh1mIwZ3GYtTjMuvFenZuLddtdN2m5Z6wRt400XvDxvsr6j4OlmP1ZHs7kV87w6dohGE9MjkGbFoE5GOXtrM8W2HHHi1koK5eh1QCfzGiJtgGaXUPw/CEOsxYnULL2dKyEM6XIzWaz+boJPvFjlQLnI/o1X4HzqtSatS8wa3GYtRjMWRxmLQ6zbpzbrzVCc+7zyqJ1RSi21j9bSmTWFqsTb3yehyf/m+MekArRS/jbjdH4z2MJATsgVcGbWcdH63DT1REAAIcTeH9Jgde2rXQ8f4jDrMVRU9YclCIArgr/e/bsUU2F/wqyLGPFFrGX7qk1a19g1uIwazGYszjMWhxm3XhtWgTh6n5hAICiEieWri+64ONFZv37Pivu/mcWVm61uJf1uCgYH/0jEROGRUCjUe63/55ojqxvujoScVFaAMCv6aVIO2D12raViucPcZi1OGrLmoNSpGr7jtlw/FyB80vb65HSigXOiYiISDkmj4qE5tw7+m9+MqOoxLe1pYpKnHh9QR6efucszhaemx0VLOGRm6Ix+5EEtI4P7NlRzckQrMHUcVHun99bUgiHg5VYiEjZOChFqrZya+UsqTEscE5EREQK0zo+CCP7u2ZLWawyvvnJd0Wwt+0pwd3/zMKaXytnR12WGoJPn2uJcUMCf3aUCMP7hOKSdq4vUY9nlld7L0tEpEQclCI3rVbr6yYIVVTixPo/XMVBww0Shpy7tbIIasval5i1OMxaDOYsDrMWh1k3zeRRRujORbjk5yKYiuu+5KM5sjYVO/Dq3Fw8934u8kyu1w4LkfD4bTH410PxSIzVef01laA5stZoJDw4Mdr989wVJhT7eHacr/H8IQ6zFkdNWfPue00UKHffU6Ol64sw5xtXkcgJQ8Pxt0kxPm4RERERUeP858t8LN/smjVzy4hITB0fJeR1N+0swdtf56PAXDkw0vfSEPzfLTFIiFHnYJQI//w0F+vTXF+uTroqAtMnRNfzDCIisXj3PWoQWZZRWFgItYxRnl/g/DqBl+6pLWtfYtbiMGsxmLM4zFocpWZdcOQIfpw+HfN79MAbOh3mduni0fNWTp6Mjy+6CG+FheF/0dH46oorkLF2bbXHbH3xRcyWpFr//Dh9eq3bve2aSASdGwNatrEIBUU1Z0t5M+vCIgdmfpyLFz/KdQ9IhRskPHVHDGY9EK/6AanmPq6njouCPsh1OeTS9UU4nVPeLK/j75R6/lAiZi2O2rLmoBQBcFX4P3jwoGoq/O87ZkNGluuXd5cOwUILnKsta19i1uIwazGYszjMWhylZp23bx+OrVyJqI4dEdu5s8fPc9hs6P1//4frv/sO1y5ciJDYWCy59lqc2rzZ/Zhu996LW3/5pdqfK15/HQCQMmpUrdtNiNHhuoGuL9lKy2R8tbZmbSlvZC3LMtanWXDXP7OwYUeJe/nlXQ34dEZLXNM/HJLE2lHNfVwnxupw4/AIAIDdAby/rLBZXsffKfX8oUTMWhy1Za3urzBItarOkhrNAudERETUQB3GjEHHceMAAKunTEF2WppHzxu7aFG1n1NGjcJHKSnYv3AhkgYPBgBEJCUhIimp2uN2v/8+QqKj6xyUAoBbr4nEqm0W2MplfLepGJOuikSs0Xt1SfJNDrz1VT627La6l0WGafDQpGhc2TuUg1GC3ToiEqu3FSPf7MTW3VbsPFSKnpeE+LpZREQNwplSpDpFJU73N3sRoRoM6WnwcYuIiIhIaSSNd95Ga7RaBEdFwWGz1fkYe2kp/ly2DBdPnAitvu7Z3XFROowd7PqyzVYu48taZks1hizLWPe7BXe/nFVtQOqKnq7ZUcP7hHFAygcMIRrcMy7K/fO7SwrgcKrjch8iChwclCIAgCRJMBgMqnhDsfbXYtjKXb+wr+4XhmC92H8Gasra15i1OMxaDOYsDrMWR41Zy7IMp90Oa14ets+ejcI//0T3adPqfPzRFStgM5uReuut9W775hGRCD5Xa2j55iKcLbS71zUm69xCO557PxevzsuD2eKqHRUVrsHz98bhxanxiIlUzx2iGkLUcX1NvzB0bBMEADh6qhw//GJp1tfzN2o8f/gKsxZHbVnz7ntNxLvvKYssy7j75WycOFdP6tMZLZHcMsjHrSIiIiIlq7h87670dI8ev+fjj7F26lQAQFB4OK77/HN0HDu2zsd/N2ECsn7/HdNOnvRohtYHSwvw9boiAMC4IeF45KaG32FYlmX88KsF7y4ugMVa+XFhWO9QPHRjNKIiOBjlL3b/WYrH/pMDAIiO1GDBC60QZuDcAyLyLd59jxrE6XQiJycHTqez/gcrWPrRMveAVNcOwT4ZkFJL1v6AWYvDrMVgzuIwa3HUmHXH8eMxeft23LB6NS6ZNAnLJ03CsdWra31saWEhjq1ahdSbb/b4ksGbro5ESLDrG/ZVW4txJt81W8rTrHPy7XjmnbP498J894BUdKQGL90Xhxl3x3FAygMij+vuF4XginPlKArMTnyxxjuXbSqBGs8fvsKsxVFb1hyUIgCuA//YsWMBf+Av94MC52rJ2h8wa3GYtRjMWRxmLY4asw6Ni0Ni795IGTkSIz/5BCmjRmHjk0/W+tg/lyyBo6wMnW67zePtR0VoMWGo685s5Xbg8x9cgxT1ZS3LMlZsKcbdL2fh9/2l7uVX9w3F3BktMbhHqMdtUDvRx/V910cj6NwtrBb/bEZWrv3CTwgQajx/+AqzFkdtWXNQilTDbHFgY9UC5734xoqIiIh8r8Vll6HwyJFa1x344gvEpKaiRc+eDdrmjcMjEBrimi21eltxvYMU2Xl2PPnfHLz5RT5KSl2zo2KNWrxyfzyemRKHyDDOjvJnreJ0uOFK1+Ux5Xbgw28LfdsgIiIP6XzdACJR1v5mQfm592Mj+odBH6SOwnFERETk305v2QJj+/Y1lhdnZeGvDRsw4MUXG7xNY7gWE6+MwIJVZjicwOsLchEZpsHp7Fis2p2PQT3CMLRXKHRa4PvNxfjw20KUllXWjhp1eRjuvyEa4aH8DlspbrsmEmt+KUZBkRMbd5Rgz5FSdOsY4utmERFdEAelCICrwr/RaAzYCv+yLGPF5iqX7g30zaV7QOBn7U+YtTjMWgzmLA6zFkepWZeXlODYqlUAAPOJE7CZzTi0eDEAoM2QIQiNj8ei4cNhPnEC956bBXV05UrsX7AA7UePRkSbNijNz8eBL75Axpo1GP3llzVe4+BXX0F2OtHJg7vu1WbilZH4ep0ZZTZgzxEbJAmQ5WBk5JRiy+5S/PfrfCREa5GRVTmLKiFai8dvi0GfzoZGvSa5+OK4DjNocNeYKLz5RT4A4J1vCvDeU4nQaJT1b6shlHr+UCJmLY7asubd95qId99Thj1HSvHom667knTrGIy3/q+Fj1tERERESmbKyMBHKSm1rpu0fj3aDh2Kr4YOhTkjA/dlZAAA8g4exOann0b29u2w5ubCEBeHuG7d0O/pp9FmyJAa21nYpw8kjQaTf/utUW3cuqcEM97P9fjxYwaF477ro3jnNgVzOGVMm5WNY6ddN/b5++0xGHm5776MJSL18nSshINSTRQog1JOpxOZmZlo1aoVNB7e2UVJXp2bi3XbXfWknp0Si6v6hvmsLYGetT9h1uIwazGYszjMWhxm3Txs5TImPn0KFquM+t7sSxLw6v3x6NeFs6O8xZfH9Y5DpXjibdeXsbFGLRa80BKGkMD8t8XzhzjMWpxAydrTsRLl9pC8yul04tSpUwFZ4d9U7MDGna4BqcgwDa7o6dsC54Gctb9h1uIwazGYszjMWhxm3Tw27ChBsQcDUgAgy4DZwvy9yZfHda9LQjCwm2uAMc/kwJc/moW3QRSeP8Rh1uKoLWsOSlHAq1rg/BoWOCciIiIV2Lq7BJ6WI5EkYMvukuZtEAk1bUIUdOdumLhoXRHO5F/47otERL7CQSkKaLIsY8WWygLn1/mwwDkRERGRKGaLE54W6eBMqcCTlBCE64dGAHBdyvnRt4W+bRARUR04KEUAAI1Gg/j4eEVfs1qbPX+W4a8zrm+Gul8UjLaJQT5uUeBm7Y+YtTjMWgzmLA6zFodZN4/IME2DZkpFhjF/b/KH4/r2UUb3fv05rQTpR8t81pbm4g85qwWzFkdtWaujl1QvjUaDDh06BNyBv2Jr5Syp0YP8Y5ZUoGbtj5i1OMxaDOYsDrMWh1k3j4HdQxs0U2pQd9/W3Aw0/nBch4dqcNcYo/vnd5cUwOkMrHtc+UPOasGsxVFb1uroJdXL6XTi6NGjAVVMzVTswKYqBc4H9/CPN1uBmLW/YtbiMGsxmLM4zFocZt08hvYKRbhBQn2TpSQA4aEShvTyj/dJgcJfjuvRA8OR3NJ1pcDBDBt+Tgus2mH+krMaMGtx1JY1B6UIgOvAP3v2bEAd+Gt+9c8C54GYtb9i1uIwazGYszjMWhxm3Tz0QRKevjMWkFDnwJR07j9P3xHrN++TAoW/HNdarYT7b4hy//zht4WwlgXOvzV/yVkNmLU4asuag1IUkM4vcO4vl+4RERERiTKgWyhmTotDWKhrwKmixlTF/8NCJfxzWhwGdOMsqUDWp7MB/buEAAByCx1YtK7Ixy0iIqqk83UDiJrD7j/LcCrHNU2qx0XBaNPC9wXOiYiIiEQb2C0Ui2cZsHFHCTbvsuB0tgmtE40Y3CMMQ3qFcoaUSkyfEI3t+7PgcAJf/2jGtQPCEB/Nj4JE5Hs8ExEAVzG1pKSkgCmmVm2W1GD/miUVaFn7M2YtDrMWgzmLw6zFYdbNTx8k4ep+YRjex4DMTBtatYpj3s3M347rtolBGHdFOJZuKEapTcbH3xXimSlxvm5Wk/lbzoGMWYujtqwlWfb0vhxUG7PZDKPRCJPJhMjISF83h+AqcD7p2dMotwPGcA2+fqU1vwUkIiIiIlUzWxy4/YUsFJW46tS88/cW6JQc7ONWEVGg8nSsRB1Db1Qvh8OBAwcOwOFw+LopTfbDL/5Z4LxCIGXt75i1OMxaDOYsDrMWh1mLw6zF8cesI8O0uPM6o/vndxcXQOnzE/wx50DFrMVRW9YclCIArsLgJpNJ8b+YZFnGyq3+XeA8ULJWAmYtDrMWgzmLw6zFYdbiMGtx/DXrsVeEo20LVwWXfcds2PBHiY9b1DT+mnMgYtbiqC1rDkpRQNl1uLLAec9LgpGUwALnREREREQAoNNKmH5DtPvnD74tRJlNHbedJyL/xEEpCijVCpwP9L9ZUkREREREvtTv0hD06RwCAMjJd2Dxz0U+bhERqRkHpQiAq8J/+/btFV3hv7DIgc27XFOQo8I1GNQj1Mctql0gZK0UzFocZi0GcxaHWYvDrMVh1uL4c9aSJGH6hChUNO3zNWbkmZRZu8afcw40zFoctWWtjl5SvTQaDRISEhR94P/wqwX2c79Pr+kfhiCdfxU4rxAIWSsFsxaHWYvBnMVh1uIwa3GYtTj+nnVKKz3GnKu9Wlom45PvC33boEby95wDCbMWR21Zq6OXVC+Hw4Hdu3crtsK/0ylj5Rb/LnBeQelZKwmzFodZi8GcxWHW4jBrcZi1OErIespoI8IMri9x1/xqweGTNh+3qOGUkHOgYNbiqC1rDkoRAFeFf6vVqtgK/7v+LMPps64C570uCUZrPy5wrvSslYRZi8OsxWDO4jBrcZi1OMxaHCVkbQzX4o5rjQAAWQbeXVzg1+2tjRJyDhTMWhy1Zc1BKQoIKzYrY5YUEREREZG/GD8kAq3jdQCAPUfKsHmX1cctIiK14aAUKV5BkQNbdrsKnEdHaDCwu38WOCciIiIi8idBOgnTb4hy//zB0gLYytUxO4OI/AMHpQgAoNVqkZqaCq1W6+umNNiaX6oUOL883G8LnFdQctZKw6zFYdZiMGdxmLU4zFocZi2OkrIe0NWAnpcEAwCy8hxYur7Ixy3ynJJyVjpmLY7asuagFAFw3Ro2KioKkuTfAzrnczplrNhaeenedQPCfNgazyg1ayVi1uIwazGYszjMWhxmLQ6zFkdJWUuShAduiIbmXFM/+8GEfLMyCiwrKWelY9biqC1rDkoRAMBut2P79u2w2+2+bkqD7DxchsxzBc4vSw3x6wLnFZSatRIxa3GYtRjMWRxmLQ6zFodZi6O0rDsk6XHtQFdd1pJSGXOXF/q2QR5SWs5KxqzFUVvWHJQiNyXecnLFFmUWOFdi1krFrMVh1mIwZ3GYtTjMWhxmLY7Ssp4y2ojQENfMjNXbLDh6yubjFnlGaTkrGbMWR01Z+92gVHFxMV544QWMHDkSMTExkCQJ8+bN8+i5mzZtwtixY9GmTRuEhIQgMTERI0eOxNatW2s8dujQoZAkqcafkSNHerlH1FzyzQ5s2VVZ4HxAN4OPW0REREREpEwxkVpMHmkEADhl4J3FBaq5JT0R+Y7O1w04X25uLmbOnIm2bduie/fu2LBhg8fPPXz4MDQaDaZPn47ExEQUFBTgs88+wxVXXIGVK1fWGHBKSkrCrFmzqi1r1aqVN7pBAvzwSzEcTtffRyqgwDkRERERkT+bMCwCy7cUIyvXjl2Hy7Btj5V3tiaiZiXJfjb8XVZWhoKCAiQmJiItLQ19+vTB3LlzMWXKlEZtr6SkBO3bt0ePHj3www8/uJcPHToUubm5SE9Pb1J7zWYzjEYjTCYTIiMjm7QtX5JlGVarFQaDQREF1ZxOGbe/mIWsXNd1tp/NbIVWcX43xlorpWWtZMxaHGYtBnMWh1mLw6zFYdbiKDnrTTtL8OJHuQCA1vE6fDqjpd9++avknJWGWYsTKFl7Olbid5fvBQcHIzEx0WvbCw0NRXx8PAoLC2tdb7fbUVxcXOs6tdHr9b5ugsd2HCp1D0hdlhqimAGpCkrKWumYtTjMWgzmLA6zFodZi8OsxVFq1oN7GNCtYzAA4PRZO77dWOTjFl2YUnNWImYtjpqy9rtBKW8wm83Izc3FwYMH8eyzzyI9PR3Dhw+v8bjDhw8jLCwMERERSExMxIwZM1BeXu6DFvuew+FAWlqaYgqqVS1wPmawcgqcA8rLWsmYtTjMWgzmLA6zFodZi8OsxVFy1pIk4YGJ0aiYoLFglQmFRf7ZDyXnrDTMWhy1Za2s6SUemjRpEtasWQPANcI4bdo0zJgxo9pjOnTogGHDhqFr166wWCxYvHgxXn75ZRw+fBhff/11ndsuKytDWVmZ+2ez2QzANeOq4paNGo0GGo0GTqcTTqfT/diK5Q6Ho1rRwLqWa7VaSJJU41aQWq0WQM2K/HUt1+l0kGW52nJJkqDVat1trHhth8MBnU5XZ9v9oU/5Zge27rYCcBU479s5CHa7vUaf6uqrr/sky3KN/QF4tp/8tU9NOfaas09Vj+tA6ZO/7qeKvzudzmrtUXKf/HU/Ve1XoPTJH/dTxfq6ztlK7FN9bfdVnwDU2L7S++Sv+0lJ7/c87VN9y/l+r3F9uqhNEEb0NWDNb1ZYrDLmLi/Ao7fE1tpXf+hTxWvz2Gu+PlVtV6D0qWob/a1PgfB+7/zn1SUgB6Vee+01PP744/jrr78wf/582Gy2GoF88skn1X6+/fbbcd999+Gjjz7CY489hv79+9e67VmzZuGll16qsXznzp0ICwsDAMTHx6NDhw44fvw4zp49635MUlISkpKScPjwYZhMJvfy9u3bIyEhAenp6bBare7lqampiIqKws6dO6vt8G7dukGv1yMtLa1aG3r37g2bzYY9e/a4l2m1WvTp0wcmkwkHDx50LzcYDOjevTtyc3Nx7NgxyLKMwsJCHDlyBJdeeikyMzNx6tQp9+P9qU+b9kXA4YxwPa+dCbt2nqq1TxWMRiM6derkN33q2bMnnE4nduzY4b5G2NP95K99asqx15x9KikpQWFhIXbs2IFOnToFRJ/8dT/FxrreqJ44cQJ5eXkB0Sd/3E9ms9l9TEuSFBB98tf9VPF7sbS0FAaDISD65K/7KTExERaLpdrvRaX3yV/3k5Le7yl9PwXC+72ebY5j/R8JsNk1WLHVgtGDwtA6Tvar/bR///5qvxd57DVfnyrqHAEImD4B/rmfAuX9nsVigSf8rtB5Vd4odG6z2dCrVy+kpqZi8eLFF3zsoUOHkJqain/+85947rnnan1MbTOl2rRpg7y8PHfxLn8Zmazg6TdnO3bsQK9evRAcHOy3o61Op4wp/8xBdp4DkgTMez4BLWN1tfaprr76uk+yLCMtLQ29evVyPwYI7JF+X/XJbre7j2u9Xh8QffLX/VTxxrtXr17umQ9K75M/7qfy8vJq549A6JO/7qeK34u9e/eGTqcLiD7V13Zf9cnpdGL79u3Vfi8qvU/+up+U8n6vIX2qbznf7zWtT1+uLcLcFa6aUr07heC1B+Oqvaav+1RWVuY+prVaLY+9ZuxTxfmjT58+7n4pvU9V2+hP+ylQ3u+ZzWbExsbWW+g84AelAODZZ5/Fa6+9BovFAoPBUOfjSkpKEBYWhsceewxvvvmmR9sOpLvvORyVlzj5q+37rXhqjmu0t0/nELz+twQft6jhlJJ1IGDW4jBrMZizOMxaHGYtDrMWJ1CyLrM5cefMLOTkuz5kvvpAPPp3qfvzlGiBkrMSMGtxAiVrxd59rzlYrVbIsoyiogvfOaJiKlx8fLyIZvkdm83m6ybUq2qB8+sGKqvAeVVKyDpQMGtxmLUYzFkcZi0OsxaHWYsTCFkH6zWYNj7K/fN7Swpgd/jXnIZAyFkpmLU4aspasYNSWVlZOHjwYLW75eXk5NR4XGFhIZYsWYI2bdogIcE1q8ZsNle7BA9wjUa+/PLLAIBrrrmmGVvunxwOB/bs2VNjCp4/yTM5sG2P6xrXmEgNBnTzn29pGkIJWQcKZi0OsxaDOYvDrMVh1uIwa3ECKeuhl4Xi0vau29P/dcaO7zcV1/MMcQIpZ3/HrMVRW9Z+Weh8zpw5KCwsRGZmJgBg+fLl7sJdDz30EIxGI5555hnMnz8fx48fR3JyMgBg1KhRSEpKQr9+/ZCQkICTJ09i7ty5yMzMrHZHvR07duCWW27BLbfcgo4dO8JqtWLZsmXYunUr7rvvPvTq1Ut4n6l+P/xSDMe5S2JHXR4OnVa5UxmJiIiIiJRAkiQ8ODEaD/zrDABg/koTruobisgwbT3PJCKqn18OSs2ePRsnTpxw/7x06VIsXboUADB58mQYjcZan3f33Xfjq6++wn/+8x8UFhYiOjoa/fv3xxdffIHBgwe7H9euXTsMHjwYy5YtQ3Z2NjQaDTp16oT3338f9913X/N2jhrF6ZSxcqvrWxlJAq4bpNxL94iIiIiIlCQ1ORhX9w3Fj7+XoKjEiQUrTfjbpBhfN4uIAoBfDkplZGTU+5h58+Zh3rx51ZY9+OCDePDBB+t9bkpKChYtWtTI1gWuqncG8Td/HCxFdp5r+mKfTiFIjPXLQ9dj/px1oGHW4jBrMZizOMxaHGYtDrMWJ9CyvndcFDbvsqLUJuPbTcUYe0UE2iYG+bpZAZezP2PW4qgpa7+++54SBMrd9/zd8x+cxZbdrnpSL90Xh8E9Qn3cIiIiIiIidZm/0oT5K00AgP5dQvDqA8q7EzYRicG771GDyLKMwsJC+OMYZW6hHdv2ugakYo1aXN5VmQXOK/hz1oGGWYvDrMVgzuIwa3GYtTjMWpxAzfqmqyMQH+WawfFreim277f6tD2BmrM/YtbiqC1rDkoRAFeF/4MHD/plhf8ffrHAWVHgfECY4guc+3PWgYZZi8OsxWDO4jBrcZi1OMxanEDNOkSvwdTxUe6f311SCIfDdx+cAzVnf8SsxVFb1hyUIr/mOK/A+bUDWOCciIiIiMhXruwditRkPQDgRFY5Vpx7r05E1BgclCK/lnagFGfyzxU476z8AudEREREREqm0Uh4cGK0++e5y00oLnH6sEVEpGQclCIAgCRJMBgMkCT/ujRuxZbKb17GDAqMWVL+mnUgYtbiMGsxmLM4zFocZi0OsxYn0LO+tH0wruztuvGQ2eLEwtUmn7Qj0HP2J8xaHLVlzbvvNRHvvtd8cgvtuPm5TDidrgLnX73cClqF15MiIiIiIgoEZ/LtuPOlLNjKZei0wKczWiIpIcjXzSIiP8G771GDOJ1O5OTkwOn0n6m3q7dVFji/dkBYwAxI+WPWgYpZi8OsxWDO4jBrcZi1OMxaHDVk3SJGh0lXRQAA7A7gg6WFwtughpz9BbMWR21Zc1CKALgO/GPHjvnNge9wyli5rUqB84GBceke4H9ZBzJmLQ6zFoM5i8OsxWHW4jBrcdSS9S1XRyLWqAUAbN1jxY6DpUJfXy05+wNmLY7asuagFPml7ftLkXOuwHnfziFoEcMC50RERERE/sQQosE9Y43un99dUgCHk9VhiMhzHJQiv1S1wPnowYEzS4qIiIiIKJCM6BeGi9q4akkdO12O1dssPm4RESkJB6UIgKvCv9Fo9IsK/2cL7fh1rxUAEBelRf9LDT5ukXf5U9aBjlmLw6zFYM7iMGtxmLU4zFocNWWt0Uh48MZo98+ffl+IYquYy47UlLOvMWtx1JY1777XRLz7nvctWGXCvBWu28recW0kpoyO8m2DiIiIiIjogl76OBcbd5QAAG6+OgL3XR9dzzOIKJDx7nvUIE6nE6dOnfJ5MTWHU8aqra5L9zQScO2AwLt0z1+yVgNmLQ6zFoM5i8OsxWHW4jBrcdSY9X3joxB0rgzskvVFyMy1N/trqjFnX2HW4qgtaw5KEQD/OfC37ytFTsG5AueXhiAhAAuc+0vWasCsxWHWYjBncZi1OMxaHGYtjhqzbhmnw8QrXbMhyu3Ah8sKmv011ZizrzBrcdSWNQelyK8sr1rgfFDgzZIiIiIiIgpUt14TiehI10fMTTut2H241MctIiJ/x0Ep8htnC+z4Ld1V4Dw+Sot+AVbgnIiIiIgokIUZNLh7TJT753eWFMDhZAljIqobB6UIAKDRaBAfHw+NxneHxKptFlT8zrp2YDi02sC824A/ZK0WzFocZi0GcxaHWYvDrMVh1uKoOeuRl4ehQ1IQAODIX+VY+5ul2V5LzTmLxqzFUVvWvPteE/Hue97hcMi4dUYmzhY6oJGAL19uhfjowKsnRUREREQU6HYeKsXjb+cAAGIiNVjwYiuEhqjjAzYRufDue9QgTqcTR48e9Vkxtd/3l+JsoavAeb8uhoAekPJ11mrCrMVh1mIwZ3GYtTjMWhxmLY7as+55SQgGdneV4sg3O/HlWnOzvI7acxaJWYujtqw5KEUAXAf+2bNnfXbgL99c5P57oBc493XWasKsxWHWYjBncZi1OMxaHGYtDrMGpl8fBZ3W9fdF68zIzrN7/TWYszjMWhy1Zc1BKfK5nHw7ft/nujNHQrQWfS8N8XGLiIiIiIioKVonBGHCsAgAQLkd+OjbQt82iIj8EgelyOdWbSuuXuBcE5gFzomIiIiI1GTyKCOM4a6PnOv/KEH60TIft4iI/A0HpQiA6zw7xQAAP1tJREFUq8J/UlKS8Ar/DoeMVdtcd+TQSMCoy8OEvr4v+CprNWLW4jBrMZizOMxaHGYtDrMWh1m7hBs0uGu00f3zO4sL4HR67z5bzFkcZi2O2rLm3feaiHffa5qte0ow4/1cAMCAbga8PD3exy0iIiIiIiJvcThk3DcrG8czywEAT98ZixH9Av+LaPIPBUeOIG32bGT++ity09MRk5qKu9LT633eysmTkfXbbyjOzIRWr0d8167o/9xzSB4xwv2YrO3bsfu993Bq0yYUZ2YivHVrXDxxIvo/9xz0YTzGefc9ahCHw4EDBw7A4XAIfd2VW4rdfw/0AucVfJW1GjFrcZi1GMxZHGYtDrMWh1mLw6wrabUS7r8hyv3zx98VwlrmnQLOzFkcpWadt28fjq1ciaiOHRHbubPHz3PYbOj9f/+H67/7DtcuXIiQ2FgsufZanNq82f2YQ19/jYI//0Sfv/8dE1atwmWPPoo9H36IZWPGNKnNSs26sXS+bgD5B1mWYTKZIHLi3JmqBc5jtOjTWR0Fzn2RtVoxa3GYtRjMWRxmLQ6zFodZi8Osq+vdyYD+XULwa3opcgsd+PpHM6aMjmrydpmzOErNusOYMeg4bhwAYPWUKchOS/PoeWMXLar2c8qoUfgoJQX7Fy5E0uDBAIC+Tz2F0PjKK33aDh2KkOhorLztNmT/8QcSL7usUW1WataNxZlS5DOrtlYWOL9uAAucExEREREFquk3REN77tPn1z8W4WyB3bcNIlWQvFSXSaPVIjgqCg6bzb2s6oBUhYSePQEAlsxMr7yuGnBQinyiWoFzDTByAK+5JSIiIiIKVG1bBGHckAgAQFm5jI++K/Rtg3yo4MgR/Dh9Oub36IE3dDrM7dLFo+etnDwZH190Ed4KC8P/oqPx1RVXIGPt2mqPydq+HT/cfTc+7tgRb4WG4uOLLsKmZ56BzWJpjq4ENFmW4bTbYc3Lw/bZs1H455/oPm3aBZ9zessWAEBMaqqIJgYEXr5HAFwV/tu3by+swv+v6VbkmVzXyF7exYD4KPUciqKzVjNmLQ6zFoM5i8OsxWHW4jBrcZh17e64NhLrfrfAbHFi3e8luH5IGTqlBDd6e0rNuaLOUWK/fpCdTshOz2psVdQ5ir7oIthLS7H3k0+w5NprcdP69e5LyqrWOYq++GLk7duHrc8/j6zffsNNP//c6DYrNeum2PvJJ1g7dSoAICg8HKO//hqtLr+8zseX5OZi24svouO4cYi+6KJGv67asubd95qId99rnKffyXHXk5r1YDz6XWrwcYuIiIiIiKi5LdtQhP8tKgAAdE7R439PtIAkqauMh+x0ui8rq6hz5Mkd4c7ndDjwUUoKUkaOxIgPPwQAlJw9W+OysgNffIGVt92GyWlpja5zFAgamnVJbi7MGRmw5ubi0Dff4MDnn2PcsmVoP2pUjcc6ysuxZNQo5B84gMlpaQhv2dLbzVcc3n2PGsThcGD37t1CKvxn59mxfb9rQKpFjBa9O6mjwHkFkVmrHbMWh1mLwZzFYdbiMGtxmLU4zLpuYwaHo20L11US+4/b8HNaSaO3pdSclVjnSKlZN0VoXBwSe/dGysiRGPnJJ0gZNQobn3yyxuNkWcaau+9G9u+/Y8KqVU0ekFJb1hyUIgCuf0hWq1VIhf9V24pR8TLXDlRfgXORWasdsxaHWYvBnMVh1uIwa3GYtTjMum46rYT7J0a7f/7o20KU2Ty7fO18aszZV3WO1Jj1+VpcdhkKjxypsXzDE0/g0KJFGLdsGRK6d2/y66gta/UU8iG/4HDIWF2lwPmoy1ngnIiIiIhITfpdakDfziH4fX8pcgocWPRTEW4fZfR1sxTBV3WOyDW4Z2zfvtqy3157DX/85z+47vPP0W748CZt31YuY8OOEmzZZcHp7Fis2p2PQT3CMLRXKPRBgTuRg4NSJNQveysLnA/oakCcigqcExERERGRy/QbopF2MAtOJ/DlGjNGXR7GzwYe6Dh+PBJ69HDXOVo+adIF6xytuPlmAMBV770nuql+obykBMdWrQIAmE+cgM1sxqHFiwEAbYYMQWh8PBYNHw7ziRO499wsqKMrV2L/ggVoP3o0Itq0QWl+Pg588QUy1qzB6C+/dG/7wBdfYPMzz6Dz5MkwpqQg89df3euiOnSo9VLKumzdU4LX5+eh2CpDkgBZDkZGTim27C7FnEX5ePrOWAzoFuqNSPwO/9UTAECr1SI1NRVarbZZX2fFlmL330cPCm/W1/JXorImZi0SsxaDOYvDrMVh1uIwa3GYdf2SWwZhzOBwfLexGKU2GZ98b8JTd8Q2aBtqzDk0Lg6hcXEAgJSRI1Gan4+NTz5ZY1Cqap2jmzdvbnKdI6VmXZKTg+U33lhtWcXPk9avR9uhQ+F0OOC0293rozp0gKOsDJuffhrW3FwY4uIQ160bbtqwAW2GDHE/LmPtWgDA/s8+w/7PPqv2GiPnzkWXKVM8auPWPSV4/oNc4NzVevJ5/7dYZcz4IBczp8VhYAAOTPHue03Eu+95LjvPjtuez4QsA4mxWnz2UitoVFZPioiIiIiIXEzFDtz+QiaKra6PpO8/nYiL2+p93CqxmnL3PQD45eWX8evLL+Ox0tJqy9c//jh2zZmDCatWNfmyMmo+tnIZE58+BYtVxoUGZiQAYaESFs9KUsylfLz7HjWI3W7H9u3bYa8yQuxtK7dWFji/bmC4agekRGRNLsxaHGYtBnMWh1mLw6zFYdbiMGvPGMO1uP3aylpS73xT0KDizsz5wnWORs6b55U6R2t/s+D5D3Jw78w/8fwHOVj7mwW2cs5t8ZTDKcNidSLf5EBmrh3HTttw4HgZdh4qxcffFaK4ngEpwDWJqrhExsYdjb9bpb/i5Xvk1py3nLQ7ZKze5rp0T6sBRl6uzkv3Kqjl9p7+gFmLw6zFYM7iMGtxmLU4zFocZu2Z8UMisHxzMU7l2LH3aBk27bRiSC/PL1FSYs5KrnN0/Exg1TlyOmWUlcsotckos7n+X1rmdP29XEZpmYwym9O1vOpjbM4qf69Y7qy5nXIZ5V4aM5UkYMvuElzdL7BuFsZBKRLil71W5Jtdt3od0M2AWKOyrkUmIiIiIiLvC9JJmD4hCs+9nwsA+GBZAS7valDMJUqNwTpHnpFlGbby8wd+KgeErGWuZWXlMqznBpIqB5M8GDSyyYqa8SXLgNni9HUzvI6DUiQEC5wTEREREVFtLu9qQK9LgrHjUBmy8xxY/LMZt15jrP+JCmVMTsYT9VymePOGDdV+jk1Nxfhvv61326PmzcOoefMa3zi4Ltl7fX4eIKPOy8pkAJIMvDY/D+8/FQSnjAvPIipzorS84u/nHlNe8ffaB43KymUorQJ2kA4IDpIQEqxBiF5CsF5CiF5CiF5T5e8VyzXYtqcEJ7I9m0olSUBkWOBVYGKh8yYKlELnsizDarXCYDBAkrz7rURWrh2TX3AVOG8Zq8VClRc4b86sqTpmLQ6zFoM5i8OsxWHW4jBrcZh1wx09ZcO0WdlwykBoiIQFL7RCTD1XVzDn5rH2Nwtem5/n62Z4nUYDGPSuAaNgvYSQIAkhwa4BouAg1yBRxc8hQVUeV20wSVN9YClYg5CgysEnrbZhx2FDs37mzljFXL7n6VgJZ0qRm17fPHe6WMUC5zU0V9ZUE7MWh1mLwZzFYdbiMGtxmLU4zLphOiTpcd3AcCzfUoySUhmfrijEE7fF1vs85uwdDqeMk9nl2HfMhs9/MAl/fUlCjcGfYL0Ew7nBn2C9BEOwBsFBFX8/95igir+fW17HjKSQYAm6Bg4YiTC0VyjmLMr3+O57Dam3phQclCIArgKBaWlp6N27N3Q67x0WdoeM1b+wwHlVzZU11cSsxWHWYjBncZi1OMxaHGYtDrNunCljjPg5zQJLqYzV2ywYf0UEOrape9CJOTee2eLA/uOuu8DtP27DwYwyWEobdxGVMVyDPp1D3ANC1QeTNK5Bo6AqA0vnPSZEr0GQDqqc7aYPkvD0nbGY8UEupDoul5TO/efpO2IDstYa/+VSs9q2p7LA+cDuhnqn4BIRERERkTpFR2hx2ygjPlxWCFkG3l1cgDceTVDlYIU3OZwyMjLLse9YGQ5k2LDvWBlO5XjnlnCSBHTrGIxnp8R5ZXtqNKBbKGZOi8PrC/JQXFJxp0O4/x8WKuHpO5R/p8O6cFCKmhULnBMRERERkacmDI3A8s3FyMq1Y9efZdi624pBPQLzw3hzKSxyYP/xMhw4bsO+42U4eMKG0rILz4KKNWrROUWPzinBsJQ68dlqs0evJcvAoO7cP001sFsoFs8yYOOOEmzeZcHpbBNaJxoxuEcYhvQKDcgZUhU4KEXNJjPXjrQDpQCAlnE69LokxMctIiIiIiIif6YPkjDt+ii8+FEuAOD9ZYXoe6khoD+UN4XDIePo6XIcOF6GfecGok6fvfAsqCAdcFEbPTqlBOPSFNf/E6K17hlptnIZ324oUnWdI1/QB0m4ul8Yhl0WjLS0Y+jdO0UVl6Xy7ntNFEh333M4HNBqtV6bHvvRt4X4cq1rhP3eccaAvq1rQzRH1lQ7Zi0OsxaDOYvDrMVh1uIwa3GYddPIsoz/eysHu/8sAwBMnxCFSVfV/KylxpzzzY5zA1CuelCHTthQarvwR/qEaC06pQS7Z0Jd1EZf7yDftj0lmPFBLlBPnaN/TosL2MvKfCVQjmvefY8azGazwWAweGVb5XYZP7DAeZ28mTVdGLMWh1mLwZzFYdbiMGtxmLU4Ssy64MgRpM2ejcxff0VuejpiUlNxV3p6vc9bOXkysn77DcWZmdDq9Yjv2hX9n3sOySNGuB/jsNmw5bnnkPXrr8j+4w/YS0rwwNmzCI2rWYtIkiQ8MDEa01/LhiwDC1eZMKJfGKIiatanVWLOnrI7ZBz5y4b9x23nLscrQ1ae44LPCdIBF7d1DT51TglG5/Z6xEc1/GO/2usc+VogH9fn46AUAXDduWLPnj1eu3PFtj1WFBRVKXAeyQLnFbydNdWNWYvDrMVgzuIwa3GYtTjMWhylZp23bx+OrVyJxH79IDudkJ1Oj57nsNnQ+//+D9EXXQR7aSn2fvIJllx7LW5avx5JgwcDAMpLSrDno4+Q2KcPkgYPRsaaNRfc5kVt9BjZPwyrf3HdjW/uChMeuyWm+usqNOe65BbaqwxA2XDopA228gvPgmoRo0Xn9sG4NCUYnVL06JikR5DOO7Nr1FznyJcC7biuT+D3kHyiaoHzMYMjfNgSIiIiIiLyRIcxY9Bx3DgAwOopU5CdlubR88YuWlTt55RRo/BRSgr2L1zoHpQKiYrC3/LzIUkS0ufNq3dQCgDuHhuFDTtKYC2TsXJLMcYPCUdKK30De+WfbOUyjp6yuetA7Ttehpz8C8+CCg6ScHE7vbsOVOeUYMQ2893N1VrniMTh0URed/psOf446Cpw3ipeh54XB/u4RUREREREVB9Jo/HKdjRaLYKjouCw2apvv4H1cWKNWtx2TSQ+/t4Epwy8u7gQ/3ooXpF1ds4W2LHvuA37j5Vh//Ey/PmXDeUXrkeOlnE69wDUpe2D0b51EHRa5fWd6EI4KEVuWq13RtlXbrW4/37dwHBoNDxxns9bWVP9mLU4zFoM5iwOsxaHWYvDrMVRW9ayLEN2OFBmMiF97lwU/vknRnzwQZO3O3F4JJZvKcaZfAf+OFiKX9NLcXnXylo7/pizrVzG4ZOuy/Bcf2zILbzwLKgQvYTUdudmQLV31YSKrqWGli/5Y9aBSk1Z8+57TRQod9/zlnK7jJv/cRoFRU7otMDXr7b2u5MpERERERFdWMXle54UOgeAPR9/jLVTpwIAgsLDcd3nn6Pj2LG1PjZ93jz8cNdddRY6P9+GPyyY+UkeACApQYdPnmvptbpJTSXLMs7kO9yDT/uPl+HIXzbYLzwGhaQEHTqfqwN1aUowUloFQctZUBRAePc9ahBZlmEymWA0Gps0HXZrlQLng7qHckCqFt7KmurHrMVh1mIwZ3GYtTjMWhxmLY4as+44fjwSevSANTcXh775BssnTcK4ZcvQftSoJm97SK9QdNlQjPSjZTiVY8f3m4pww5WRPsm5zObEoZPn7oh3rAwHMmzIM114BMoQLKFT8rnL8M4NRBnDlfU5SY3HtK+oLWsOShEAV4X/gwcPNrnC/4rNRe6/jx4U7o2mBRxvZU31Y9biMGsxmLM4zFocZi0OsxZHjVmHxsW5Zz2ljByJ0vx8bHzySa8MSkmShAcnRuH+188AAOavNOGqvmEIC5GbNWdZlpGV53DXgdp/3Iajp2xw1HNTwrYtdO46UJ2S9UhuFQStwkuaqPGY9hW1ZR34PSRhTueUY8ehMgBA63gderDAORERERGRKrW47DIcX73aa9u7pF0wRvQLw9rfLCi2ypi/0oQHbvBu+RRrmROHTtjcA1AHjpe5rwKpS1iIhNTkYFza3jUTqlOyHpFhypoFReRLHJQir1m5tdj99+sGscA5EREREZFand6yBcb27b26zXvGGbFpZwlKbTK+21SMk9k2FBTGYtXufAzqEYahvUKhD/LsM4gsyzh91u6+DG9/RhmOnS6H8wJjUJIEtEsMQucUvbseVLvEIH7uIWoCDkoRANeUWIPB0OhrVsvtMn74xXXXPZ0WuKZ/mDebF1CamjV5jlmLw6zFYM7iMGtxmLU4zFocpWZdXlKCY6tWAQDMJ07AZjbj0OLFAIA2Q4YgND4ei4YPh/nECdx75AgA4OjKldi/YAHajx6NiDZtUJqfjwNffIGMNWsw+ssvq23/2OrVKLdYkJ2W5nru8uXQR0QgtnNnxHXuXG/74qN0GNjNgJ/SSiDLwI5DNgDByMgpxZbdpZizKB9P3xmLAd1Cazy3pNSJgyds7kvxDmTYYCq+8CyocIOEzinB6HzuMrxOycEID9XU285ApNRjWonUljXvvtdEvPueS9U7Ygy7LBQz7qn/LhpEREREROQ/TBkZ+CglpdZ1k9avR9uhQ/HV0KEwZ2TgvowMAEDewYPY/PTTyN6+HdbcXBji4hDXrRv6Pf002gwZUm0bHyYnw3ziRI1tX/7CCxj44ov1tm/rnhI8/0Eu6voEK537z0tT49C2ZdC5ASjX5XgZmeVwXuCTryQBKS2DXANQ5+6Il5Sg4ywookbydKyEg1JNFCiDUk6nE7m5uYiLi4NG0/DR/8ffPoOd5+pJvfFIAnpeEuLtJgaMpmZNnmPW4jBrMZizOMxaHGYtDrMWh1l7n61cxsSnT8FileGND7CRYRp0Tqm8I94l7fQIM3Bf1YXHtDiBkrWnYyW8fI8AuA78Y8eOISYmpsEH/qmccveAVFICC5zXpylZU8Mwa3GYtRjMWRxmLQ6zFodZi8OsvW/DjhIUWxs3HKWRgPatg1yX4qXo0bl9MFrH61RzeZQ38JgWR21Zc1CKmmzllioFzgeG8+RORERERERetXV3CSQJdV66d76YSA0mDI1A5/bBuKStHoaQwP9wT6REHJSiJrGVy/jhV1eB8yAdC5wTEREREZH3mS1OjwekAKBNiyDcOtLYfA0iIq/gcDEBcFX4NxqNDZ7ltGV3ifuuFYN6hCIqQtsczQsojc2aGo5Zi8OsxWDO4jBrcZi1OMxaHGbtfZFhGngapyS5Hk/ew2NaHLVl7Xf/UouLi/HCCy9g5MiRiImJgSRJmDdvnkfP3bRpE8aOHYs2bdogJCQEiYmJGDlyJLZu3Vrr47dt24ZBgwYhNDQUiYmJePjhh1FcXFzrYwOdVqtFp06doNU2bFBpRZVL98YMCvd2swJSY7OmhmPW4jBrMZizOMxaHGYtDrMWh1l738DuoR7PlJJlYFD30OZtkMrwmBZHbVn73aBUbm4uZs6ciQMHDqB79+4Neu7hw4eh0Wgwffp0vPPOO3jiiSeQnZ2NK664Aj/88EO1x+7atQvDhw9HSUkJ3nzzTdx777348MMPceONN3qzO4rhdDpx6tQpOJ1Oj5/z15ly7DpcWeC8+0UscO6JxmRNjcOsxWHWYjBncZi1OMxaHGYtDrP2vqG9QhFukFDf3BEJQHiohCG9OCjlTTymxVFb1n5XU6ply5bIyspCYmIi0tLS0KdPH4+fe++99+Lee++ttuyBBx5A+/bt8dZbb2HkyJHu5c8++yyio6OxYcMG9+0Jk5OTMXXqVKxduxYjRozwTocUouLAT0xM9LjCf9VZUqMHscC5pxqTNTUOsxaHWYvBnMVh1uIwa3GYtTjM2vv0QRKevjMWMz7IhSQDtU2aks795+k7YqEP4mcTb+IxLY7asva7HgYHByMxMdFr2wsNDUV8fDwKCwvdy8xmM3788UdMnjzZPSAFAHfccQfCw8OxaNEir71+oLKVy1jDAudERERERCTIgG6hmDktDmGhrgGniu/EK/4fFirhn9PiMKAbZ0kRKYXfzZTyBrPZDJvNhtzcXCxYsADp6el49tln3ev37t0Lu92O3r17V3ueXq9Hjx49sHPnTtFNVpzNu0pgtrimEw7uEQpjuDqudyUiIiIiIt8Z2C0Ui2cZsHFHCTbvsuB0tgmtE40Y3CMMQ3qFcoYUkcIE5KDUpEmTsGbNGgCugaZp06ZhxowZ7vVZWVkAXJcKnq9ly5bYvHlzndsuKytDWVmZ+2ez2QwAsNvtsNvtAACNRgONRgOn01ntOtCK5Q6HA3KVKn11LddqtZAkyb3dqssBwOFweLRcp9NBluVqyyVJglardbfR6XQiNjbW/fp1tb1i+fLNRe51YwaF+2Wf6lvuq/0kSRLi4uLgdDqrPUfJffLX/VRxXDudTsiyHBB98tf9BADx8fEAUK09Su6TP+4nSZLcx7Tdbg+IPvnrfqo4f0iSVKONSu1TfW33ZZ+qHteB0id/3E8Nfb+nhD7Vt5zv9wJzP+m0GlzdLwxDe+mRkWFCu3ZR0Gg0qKgLrcQ++ft+qjh/BFKfqrbRn/oUKO/3zn9eXQJyUOq1117D448/jr/++gvz58+HzWarFojVagXgulTwfCEhIe71tZk1axZeeumlGst37tyJsDDXJWzx8fHo0KEDjh8/jrNnz7ofk5SUhKSkJBw+fBgmk8m9vH379khISEB6enq1105NTUVUVBR27txZbYd369YNer0eaWlp1drQu3dv2Gw27Nmzx71Mq9WiT58+MJlMOHjwoHu5wWBA9+7dkZubi2PHjrmX2+12dOrUCZmZmTh16pR7edU+7T+Sjz1HWgAAWsYA3S4KxsGDB/22T0ajsd4+id5PrVq1wo4dOwKqT/68n/Ly8gKuT4B/7qejR48GXJ/8aT8VFRUhLy8PeXl5AdMnf99PrVu3Drg++eN+stvt1X4vBkKf/Hk/efJ+T2l98sf9xPd7zd+n/fv3w2q1un8vBkKf/H0/aTQavt/j+z2P+mSxWOAJSa46FOZnKgqdz507F1OmTGnUNmw2G3r16oXU1FQsXrwYALB48WLceOON2LRpEwYPHlzt8ZMmTcLmzZvds6nOV9tMqTZt2iAvL89dn8pfRiYrePrN2YkTJ5CcnIygoKALjra+t6QAS9a7DrDp1xsx6WqjX/apvuW+/Obs+PHjaNu2LTSayrJuSu6Tv+4nh8OBEydOoF27dggKCgqIPvnrfgLgzroqJffJH/eTw+HAsWPH0K5dO2g0moDok7/up4rfi+3bt3c/Xul9qq/tvuoTABw9etR9XAdCn/x1PzXk/Z5S+lTfcr7fC+z9VF5ejoyMDPf5IxD65K/7qeL80aFDB/fPSu9T1Tb6034KlPd7ZrMZsbGxMJlM1Wp5ny8gZ0pVpdfrMXbsWLz22muwWq0wGAzuy/ZqG3jKyspCq1at6txecHBwrTOsdDoddLrqcVbs3PNV7CxPl5+/3cYslySp1uUVbbTb7cjLy0NKSsoF2253SPjxd9foaZAOuOby8Au23Zd9aury5uqT3W5Hbm4ukpOTa6xTap8utNyXfZJl2X1cS5LU4LbXtZz7qeZyu92Os2fPol27drVuR4l9qm+5L/pU9Ziuul7JffLX/VT192Jdbaz6+Kr8tU9NWd6cfaqa9fmvodQ+Af65nzx9v6ekPjV1Od/vKXs/SZJU6/lDyX3y1/10/rk6EPrkyXK+32t8n+pafz6/u/tec7BarZBlGUVFrjpIXbp0gU6nqzHdzGazYdeuXejRo4cPWqkMVQucD+nJAudERERERERE1DiKHZTKysrCwYMHUV5e7l6Wk5NT43GFhYVYsmQJ2rRpg4SEBACuay+vuuoqfPbZZ+6BKgBYuHAhiouLceONNzZ/BxRq+eZi99+vGxTuw5YQERERERERkZL55eV7c+bMQWFhITIzMwEAy5cvdxfueuihh2A0GvHMM89g/vz5OH78OJKTkwEAo0aNQlJSEvr164eEhAScPHkSc+fORWZmJr7++utqr/HKK69gwIABGDJkCO677z6cOnUKb7zxBkaMGIGRI0cK7a8/0Gg0SEpKqnV6X4WT2eXYc8RVT6tdog7dOta8jJHq50nW5B3MWhxmLQZzFodZi8OsxWHW4jBrMZizOMxaHLVl7ZeFzpOTk3HixIla11UMQk2ZMqXGoNQ777yDr776CgcPHkRhYSGio6PRv39/PPnkkzUKmgPAli1b8NRTT2HHjh2IiIjApEmTMGvWLERERHjcVrPZDKPRWG/xrkDw7uICLP7ZNbPsgYlRmHhlYPeXiIiIiIiIiBrO07ESvxyUUpJAGZRyOBw4fPgwLr744loLnNnKZUx69jTMFieCdMA3s1ojMoz1pBqjvqzJe5i1OMxaDOYsDrMWh1mLw6zFYdZiMGdxmLU4gZK1p2Ml6pgPRvWSZRkmkwl1jVFu2lmlwHmvUA5INUF9WZP3MGtxmLUYzFkcZi0OsxaHWYvDrMVgzuIwa3HUljUHpcgjy7dUFjgfwwLnRERERERERNREHJSiemVklWNvlQLnXTqwwDkRERERERERNQ0HpQiAq8J/+/bta63wv3Jr5Syp0YPCIUmSyKYFnAtlTd7FrMVh1mIwZ3GYtTjMWhxmLQ6zFoM5i8OsxVFb1ix03kSBUui8LmU2JyY9m4miEif0QRIWvdqK9aSIiIiIiIiIqE4sdE4N4nA4sHv3bjgcjmrLN+60oqjkXIHzngYOSHlBXVmT9zFrcZi1GMxZHGYtDrMWh1mLw6zFYM7iMGtx1JY1B6UIgKvCv9VqrVHhf2XVAueDI0Q3KyDVlTV5H7MWh1mLwZzFYdbiMGtxmLU4zFoM5iwOsxZHbVlzUIrqdDzThr1HzxU4bxmES9vrfdwiIiIiIiIiIgoUHJRqJgVHjuDH6dMxv0cPvKHTYW6XLvU+pzgrCxv//nfM79EDb0dE4P2kJKy49VaYTpyo8dhTW7bg62HD8L/oaLwTF4fFo0YhZ9cur/ah2iwpFjgnIiIiIiIiIi/ioFQzydu3D8dWrkRUx46I7dzZo+ec+eMP/Ll0KS6ZNAnXf/cdhr75JnL37sXnffui5OxZ9+PyDx3C4hEjEBQWhtFffolrPvkEpfn5WDR8OCzZ2Y1qr1arRWpqKrRaV82oMpsTa3+zAAD0QRKu7hfWqO1STednTc2HWYvDrMVgzuIwa3GYtTjMWhxmLQZzFodZi6O2rHW+bkCg6jBmDDqOGwcAWD1lCrLT0up9TutBg3D3wYPQ6Cp3S+sBA/BB27bYt2AB+jz+OADgz2XLAFnGmG++QZDBAACI69YNH7dvj4wff8Slt9/e4PZKkoSoqCj3zxt3lKDY6rqGdWivUESEcvzSW87PmpoPsxaHWYvBnMVh1uIwa3GYtTjMWgzmLA6zFkdtWXOkoZlImoZHGxIVVW1ACgAikpIQGh+P4sxM9zJneTm0wcHQhYS4lwUbja6/NLIYmt1ux/bt22G32wEAy6tcujd6UHijtkm1Oz9raj7MWhxmLQZzFodZi8OsxWHW4jBrMZizOMxaHLVlzUEpP5d/+DBKcnIQ26mTe1nqzTfDabdjy3PPwZqXh+LMTKx/7DFEtGnjnp3VGBW3nDyeacO+YzYAQEorFjhvDmq5vac/YNbiMGsxmLM4zFocZi0OsxaHWYvBnMVh1uKoKWtevufHZFnGzw8/jPBWrZB6yy3u5dEXXYRJP/2EZePG4bdXXwUARCYn48Z16ypnTDXBiiqzpK4byALnREREREREROR9nCnlx7a9+CJO/vQTRi1YAH1YZaHx/MOH8d0NNyB5xAjc+OOPuH75ckS2a4clo0bBcuZMk16ztEqB8+AgCSNY4JyIiIiIiIiImoEky40sQkQAALPZDKPRCJPJhMjIyFofU1Ho/K70dI+3u+ejj7D2vvtwzSefoOvdd1db993EiTBnZOD2KsXTbcXF+LBtW3SfPh2Dz82eaghZlmG1WrFptxP/WpgPALimfxieuiO2wduiC6vI2mAwcBZaM2PW4jBrMZizOMxaHGYtDrMWh1mLwZzFYdbiBErWnoyVAJwp5Zf+XLYMP95/PwbOnFljQAoA8vbvR3z37tWW6cPDEdWxIwqPHm306+r1+mqX7rHAefPR61mnSxRmLQ6zFoM5i8OsxWHW4jBrcZi1GMxZHGYtjpqy5qCUnzm5YQNW3HILuk2distnzKj1MZHt2iFn505UneRWZjaj4M8/EZmc3KDXs5XLWPubBS98eBZ3vZSB/cddBc6TW+rQOUU9/xBEcjgcSEtLU1XxOl9h1uIwazGYszjMWhxmLQ6zFodZi8GcxWHW4qgtaxY6byblJSU4tmoVAMB84gRsZjMOLV4MAGgzZAhC4+OxaPhwmE+cwL1HjgAA8g4cwHfjxyP6oovQ+fbbkfnrr+7thcbHI6pDBwBAj+nT8e348Vh522249I47YC8tRdobb8BRVoZu997rcRu37inB6/PzUGyVIUmALFcOQmXlOvDLXisGdAttchZEREREREREROfjoFQzKcnJwfIbb6y2rOLnSevXo+3QoXA6HHDa7e71Wb/9hjKTCWUmE74cOLDacy+9806MmjcPANBx3DiMWbQI2//9byy/6SZo9Xok9OyJm9avR/RFF3nUvq17SvD8B7nAuclW51cWs5XLmPFBLmZOi8NADkwRERERERERkZdxUKqZGJOT8UQ9NeRv3rCh2s9dpkxBlylTPNr+JTfeiEvOG/TylK1cxuvz8wDZPSZVgwxAkoHXF+Rh8SwD9EHKLbBGRERERERERP6Hd99rIk8ryvuTtb9Z8Nr8PI8f/8ydsbi6X1gztkhdZFmGw+GAVqtV9N0UlIBZi8OsxWDO4jBrcZi1OMxaHGYtBnMWh1mLEyhZ8+57VKetu0vg6bEtScCW3SXN2yAVstlsvm6CajBrcZi1GMxZHGYtDrMWh1mLw6zFYM7iMGtx1JQ1B6VUyGxx1qghVRdZdj2evMfhcGDPnj2quZvC/7d350FZ3fcexz8PiywiKOKCgltdmKJGovUqNRITrkusuMekGlGxRhO3mYxmtLEoEU3adEytY2PqWuOCJnWJRltJZOJYRWO0qYnGLVhEwS0IiKLAuX944dYLaTTC75TzvF8zJDPnHB4/fuaJ8flyzu9nJ7o2h67NoGdz6NocujaHrs2hazPo2Ry6NsfdumYo5YYCa3s81J1SgbV5mwAAAAAAgKrFtMEN/fQx/4e6U6rHY+y+BwAAAAAAqhZDKTf05OP+CvBz6ftulnJJCvB3KeZxhlJVzdPT0+4IboOuzaFrM+jZHLo2h67NoWtz6NoMejaHrs1xp67Zfe8R1cTd9yTpb18Uas6yq5IlVfYGcP3vP15/MUTRHRlKAQAAAACAB8Pue/i3ojv6K+nFENX2v3e/VNkaU2X/ru3vYiBVTSzLUm5urpgHVz+6NoeuzaBnc+jaHLo2h67NoWsz6NkcujbH3bpmKOXGftrRX+8vDNOs+Pr6aUdftWxUpJ929NWs+Pp6f2EYA6lqUlJSopMnT7rNbgp2omtz6NoMejaHrs2ha3Po2hy6NoOezaFrc9ytay+7A8Betbxd+u//qq1enX302Wfn1KVLS3l58bYAAAAAAADVizulAAAAAAAAYBxDKUiSXC6X/Pz85HJ93558eFR0bQ5dm0PXZtCzOXRtDl2bQ9fm0LUZ9GwOXZvjbl2z+94jqqm77wEAAAAAAFQHdt/DQyktLdXly5dVWlpqdxTHo2tz6NocujaDns2ha3Po2hy6NoeuzaBnc+jaHHfrmqEUJN174587d85t3vh2omtz6NocujaDns2ha3Po2hy6NoeuzaBnc+jaHHfrmqEUAAAAAAAAjGMoBQAAAAAAAOMYSkHSvRX+g4KC3GaFfzvRtTl0bQ5dm0HP5tC1OXRtDl2bQ9dm0LM5dG2Ou3XN7nuPiN33AAAAAAAA/g+77+GhlJaW6sKFC26zmJqd6NocujaHrs2gZ3Po2hy6NoeuzaFrM+jZHLo2x926ZigFSe73xrcTXZtD1+bQtRn0bA5dm0PX5tC1OXRtBj2bQ9fmuFvXDKUAAAAAAABgHEMpAAAAAAAAGMdQCpIkDw8PNWjQQB4evCWqG12bQ9fm0LUZ9GwOXZtD1+bQtTl0bQY9m0PX5rhb1+y+94jYfQ8AAAAAAOD/sPseHkppaanOnj3rNoup2YmuzaFrc+jaDHo2h67NoWtz6NocujaDns2ha3PcrWuGUpB0741/5coVt3nj24muzaFrc+jaDHo2h67NoWtz6NocujaDns2ha3PcrWuGUgAAAAAAADDOy+4ANV3Zklx5eXk2J3k0xcXFunnzpvLy8uTlxduiOtG1OXRtDl2bQc/m0LU5dG0OXZtD12bQszl0bY5Tui6bkXzfMuY193f4HyI/P1+SFB4ebnMSAAAAAACA/xz5+fkKCgr6zvPsvveISktLdfHiRdWpU0cul8vuOD9YXl6ewsPDlZmZyS6C1YyuzaFrc+jaDHo2h67NoWtz6NocujaDns2ha3Oc0rVlWcrPz1eTJk3k4fHdK0dxp9Qj8vDwUFhYmN0xqkxgYGCNfuPXJHRtDl2bQ9dm0LM5dG0OXZtD1+bQtRn0bA5dm+OErv/dHVJlWOgcAAAAAAAAxjGUAgAAAAAAgHEMpSBJ8vHxUWJionx8fOyO4nh0bQ5dm0PXZtCzOXRtDl2bQ9fm0LUZ9GwOXZvjbl2z0DkAAAAAAACM404pAAAAAAAAGMdQCgAAAAAAAMYxlAIAAAAAAIBxDKXcXEFBgRITE9W3b18FBwfL5XJp9erVdsdynMOHD2vy5MmKjIxU7dq11axZMz377LM6deqU3dEc58svv9Tw4cPVqlUr+fv7KyQkRD179tSHH35odzTHS05OlsvlUvv27e2O4ihpaWlyuVyVfh08eNDueI70+eefKy4uTsHBwfL391f79u21ePFiu2M5ypgxY77zfe1yuZSVlWV3REc5ffq0nnvuOYWFhcnf318RERFKSkpSYWGh3dEc5ciRI+rbt68CAwNVp04d9e7dW8eOHbM7Vo33MJ9XTpw4ob59+yogIEDBwcF64YUXdOXKFbOBa7AH7frQoUN66aWX1LlzZ3l7e8vlcpkPW4M9SM+lpaVavXq14uLiFB4ertq1a6t9+/aaP3++bt++bU/wauJldwDY6+rVq0pKSlKzZs302GOPKS0tze5IjvTmm29q//79Gj58uDp27Kjs7GwtWbJEjz/+uA4ePMiH+Cp0/vx55efnKz4+Xk2aNFFhYaE++OADxcXFadmyZZowYYLdER3pwoULWrBggWrXrm13FMeaOnWqfvKTn9x3rHXr1jalca6//vWvGjBggKKiojRnzhwFBATo7NmzunDhgt3RHOXFF19UbGzsfccsy9LEiRPVokULNW3a1KZkzpOZmamuXbsqKChIkydPVnBwsA4cOKDExEQdOXJE27ZtszuiI3z++efq0aOHwsPDlZiYqNLSUi1dulQxMTE6dOiQ2rVrZ3fEGutBP69cuHBBPXv2VFBQkBYsWKCCggK99dZb+sc//qFDhw6pVq1aZoPXQA/a9UcffaTly5erY8eOatWqFT9of0gP0nNhYaHGjh2rbt26aeLEiWrYsGH5n90ff/yxPvnkE+cMAy24tdu3b1uXLl2yLMuyDh8+bEmyVq1aZW8oB9q/f79VVFR037FTp05ZPj4+1siRI21K5T6Ki4utxx57zGrXrp3dURxrxIgR1lNPPWXFxMRYkZGRdsdxlL1791qSrM2bN9sdxfFu3LhhNWrUyBo8eLBVUlJidxy3s2/fPkuSlZycbHcUR0lOTrYkWcePH7/v+OjRoy1J1vXr121K5izPPPOMVa9ePevq1avlxy5evGgFBARYQ4YMsTFZzfegn1cmTZpk+fn5WefPny8/tmfPHkuStWzZMlNxa7QH7To7O9sqLCy0LMuyXn75ZYuxwsN5kJ6Lioqs/fv3V/jeefPmWZKsPXv2mIhqBI/vuTkfHx81btzY7hiOFx0dXeGnM23atFFkZKROnDhhUyr34enpqfDwcOXm5todxZE+/fRTvf/++3r77bftjuJ4+fn5Ki4utjuGY61fv145OTlKTk6Wh4eHbt68qdLSUrtjuY3169fL5XLp5z//ud1RHCUvL0+S1KhRo/uOh4aGysPDg7tHqsi+ffsUGxur+vXrlx8LDQ1VTEyMduzYoYKCAhvT1WwP+nnlgw8+0M9+9jM1a9as/FhsbKzatm2rTZs2VWdEx3jQrhs1aiQ/Pz8DiZzpQXquVauWoqOjKxwfPHiwJDnqMyRDKcAmlmUpJydHISEhdkdxpJs3b+rq1as6e/asFi1apF27dunpp5+2O5bjlJSUaMqUKRo/frw6dOhgdxxHGzt2rAIDA+Xr66tevXrps88+szuS46SmpiowMFBZWVlq166dAgICFBgYqEmTJjlu/Yb/NHfv3tWmTZsUHR2tFi1a2B3HUZ588klJUkJCgo4dO6bMzEylpKToD3/4g6ZOncpj11WkqKio0g/p/v7+unPnjo4fP25DKveRlZWly5cvq0uXLhXOde3aVUePHrUhFVD1srOzJclRnyFZUwqwybp165SVlaWkpCS7ozjSK6+8omXLlkmSPDw8NGTIEC1ZssTmVM7zzjvv6Pz580pNTbU7imPVqlVLQ4cO1TPPPKOQkBB99dVXeuutt/TEE0/ob3/7m6KiouyO6BinT59WcXGxBg4cqISEBC1cuFBpaWn6/e9/r9zcXG3YsMHuiI71l7/8RdeuXdPIkSPtjuI4ffv21euvv64FCxZo+/bt5cd/+ctfav78+TYmc5Z27drp4MGDKikpkaenpyTpzp07Sk9PlyQW769mly5dknTv7rT/LzQ0VNevX1dRUZF8fHxMRwOq1K9//WsFBgaqX79+dkepMgylABucPHlSL7/8srp37674+Hi74zjS9OnTNWzYMF28eFGbNm1SSUmJ7ty5Y3csR7l27Zp+9atfac6cOWrQoIHdcRw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      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def is_date(date):\n",
    "    try:\n",
    "        pd.to_datetime(date, format='%Y-%m-%d')\n",
    "        return True\n",
    "    except ValueError:\n",
    "        return False\n",
    "\n",
    "df = df[df['Date'].apply(is_date)]\n",
    "\n",
    "df['Date'] = pd.to_datetime(df['Date'])\n",
    "df['Month'] = df['Date'].dt.month\n",
    "\n",
    "month_avg = df.groupby('Month')['Rating'].mean()\n",
    "\n",
    "plt.figure(figsize=(12, 7))\n",
    "plt.plot(month_avg.index, month_avg.values, marker='o', linestyle='-', color='royalblue', linewidth=2, markersize=8)\n",
    "plt.xlabel('Month', fontsize=14)\n",
    "plt.ylabel('Mean Stars', fontsize=14)\n",
    "plt.title('Coinbase Ratings by Month', fontsize=16)\n",
    "plt.xticks(month_avg.index, fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.grid(True, linestyle='--', alpha=0.7)\n",
    "plt.axhline(y=month_avg.mean(), color='red', linestyle='--', linewidth=1, label='Overall Rating')\n",
    "plt.legend()\n",
    "\n",
    "# data points\n",
    "for i, value in enumerate(month_avg.values):\n",
    "    plt.text(month_avg.index[i] - 0.15, value, f'{value:.2f}', fontsize=11, ha='right', va='bottom', color='darkred') # x-offset; horiz alig; vert alig\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DUOMENŲ RINKINIAI (BTC kainos), analizė"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- https://www.kaggle.com/datasets/mjdskaggle/5-years-of-crypto-data-as-of-632024 BTC-USD.csv\n",
    "- https://coinmarketcap.com/currencies/bitcoin/ BTC_All_graph_coinmarketcap.csv\n",
    "- https://www.kaggle.com/datasets/prkhrawsthi/bitcoin-usd-daily-price-with-volume-2015-2023 BTC-USD-15-23.csv\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from dateutil import parser\n",
    "\n",
    "btc_new = pd.read_csv('BTC-USD.csv') # 2019-06-03 to 2024-06 ---> daily\n",
    "btc_old = pd.read_csv('BTC_All_graph_coinmarketcap.csv', delimiter=';') # 2013-2019 ---> monthly\n",
    "\n",
    "columns = ['Date', 'Close', 'Volume']\n",
    "\n",
    "btc_new = btc_new[['Date', 'Adj Close', 'Volume']]\n",
    "btc_new.columns = columns\n",
    "btc_old = btc_old[['timestamp', 'close', 'volume']]\n",
    "btc_old.columns = columns\n",
    "\n",
    "btc_new['Date'] = btc_new['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "btc_old['Date'] = btc_old['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "\n",
    "min_date_recent = btc_new['Date'].min() # oldest\n",
    "\n",
    "btc_old = btc_old.loc[btc_old['Date'] < min_date_recent] # remove new data from btc_old\n",
    "\n",
    "btc_all = pd.concat([btc_old, btc_new])\n",
    "btc_all.to_csv('combined_btc_data.csv', index=False)\n",
    "btc_all['Date'] = pd.to_datetime(btc_all['Date']) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from dateutil import parser\n",
    "\n",
    "btc_new = pd.read_csv('BTC-USD.csv')  # 2019-06-03 to 2024-06 ---> daily\n",
    "btc_mid = pd.read_csv('BTC-USD-15-23.csv')  # 2015-2023 ---> daily\n",
    "btc_old = pd.read_csv('BTC_All_graph_coinmarketcap.csv', delimiter=';')  # 2013-2019 ---> monthly\n",
    "\n",
    "columns = ['Date', 'Close', 'Volume']\n",
    "\n",
    "btc_new = btc_new[['Date', 'Adj Close', 'Volume']]\n",
    "btc_new.columns = columns\n",
    "btc_old = btc_old[['timestamp', 'close', 'volume']]\n",
    "btc_old.columns = columns\n",
    "btc_mid = btc_mid[['Date', 'Adj Close', 'Volume']]\n",
    "btc_mid.columns = columns\n",
    "\n",
    "btc_new['Date'] = btc_new['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "btc_old['Date'] = btc_old['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "btc_mid['Date'] = btc_mid['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "\n",
    "# remove new data from older files\n",
    "min_date_mid = btc_mid['Date'].min()\n",
    "min_date_new = btc_new['Date'].min()\n",
    "\n",
    "btc_old = btc_old.loc[btc_old['Date'] < min_date_mid]\n",
    "btc_mid = btc_mid.loc[btc_mid['Date'] < min_date_new]\n",
    "\n",
    "btc_all = pd.concat([btc_old, btc_mid, btc_new])\n",
    "btc_all.to_csv('combined_btc_data.csv', index=False)\n",
    "btc_all['Date'] = pd.to_datetime(btc_all['Date'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pridedame papildomas Features (Open/High/Low)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from dateutil import parser\n",
    "\n",
    "btc2_new = pd.read_csv('BTC-USD.csv')  # 2019-06-03 to 2024-06 ---> daily\n",
    "btc2_mid = pd.read_csv('BTC-USD-15-23.csv')  # 2015-2023 ---> daily\n",
    "btc2_old = pd.read_csv('BTC_All_graph_coinmarketcap.csv', delimiter=';')  # 2013-2019 ---> monthly\n",
    "\n",
    "columns = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume']\n",
    "\n",
    "btc2_new = btc2_new[['Date', 'Open', 'High', 'Low', 'Adj Close', 'Volume']]\n",
    "btc2_new.columns = columns\n",
    "btc2_old = btc2_old[['timestamp', 'open', 'high', 'low', 'close', 'volume']]\n",
    "btc2_old.columns = columns\n",
    "btc2_mid = btc2_mid[['Date', 'Open', 'High', 'Low', 'Adj Close', 'Volume']]\n",
    "btc2_mid.columns = columns\n",
    "\n",
    "btc2_new['Date'] = btc2_new['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "btc2_old['Date'] = btc2_old['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "btc2_mid['Date'] = btc2_mid['Date'].apply(lambda x: parser.parse(x).strftime('%Y-%m-%d'))\n",
    "\n",
    "# remove new data from older files\n",
    "min_date_mid = btc2_mid['Date'].min()\n",
    "min_date_new = btc2_new['Date'].min()\n",
    "\n",
    "btc2_old = btc2_old.loc[btc2_old['Date'] < min_date_mid]\n",
    "btc2_mid = btc2_mid.loc[btc2_mid['Date'] < min_date_new]\n",
    "\n",
    "btc2_all = pd.concat([btc2_old, btc2_mid, btc2_new])\n",
    "btc2_all.to_csv('combined_btc2_data.csv', index=False)\n",
    "btc2_all['Date'] = pd.to_datetime(btc_all['Date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-04-01T00:00:00.000Z</td>\n",
       "      <td>135.300003</td>\n",
       "      <td>147.488007</td>\n",
       "      <td>132.100006</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-05-01T00:00:00.000Z</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>139.889999</td>\n",
       "      <td>79.099998</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-06-01T00:00:00.000Z</td>\n",
       "      <td>128.815002</td>\n",
       "      <td>129.779999</td>\n",
       "      <td>88.500000</td>\n",
       "      <td>96.613998</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-01T00:00:00.000Z</td>\n",
       "      <td>97.510002</td>\n",
       "      <td>111.344002</td>\n",
       "      <td>65.526001</td>\n",
       "      <td>106.089996</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-08-01T00:00:00.000Z</td>\n",
       "      <td>106.212997</td>\n",
       "      <td>140.889999</td>\n",
       "      <td>101.210999</td>\n",
       "      <td>135.350006</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2024-02-01T00:00:00.000Z</td>\n",
       "      <td>42569.761398</td>\n",
       "      <td>63913.131814</td>\n",
       "      <td>41879.189991</td>\n",
       "      <td>61198.382897</td>\n",
       "      <td>8.307219e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2024-03-01T00:00:00.000Z</td>\n",
       "      <td>61168.062429</td>\n",
       "      <td>73750.073850</td>\n",
       "      <td>59323.908942</td>\n",
       "      <td>71333.647926</td>\n",
       "      <td>1.446418e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2024-04-01T00:00:00.000Z</td>\n",
       "      <td>71333.484717</td>\n",
       "      <td>72715.359609</td>\n",
       "      <td>59120.068047</td>\n",
       "      <td>60636.856780</td>\n",
       "      <td>1.016068e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2024-05-01T00:00:00.000Z</td>\n",
       "      <td>60609.497946</td>\n",
       "      <td>71946.462688</td>\n",
       "      <td>56555.294055</td>\n",
       "      <td>67491.417011</td>\n",
       "      <td>8.742915e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2024-06-01T00:00:00Z</td>\n",
       "      <td>67475.431181</td>\n",
       "      <td>71321.775649</td>\n",
       "      <td>67318.447828</td>\n",
       "      <td>70959.476755</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>135 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Date          Open          High           Low  \\\n",
       "0    2013-04-01T00:00:00.000Z    135.300003    147.488007    132.100006   \n",
       "1    2013-05-01T00:00:00.000Z    139.000000    139.889999     79.099998   \n",
       "2    2013-06-01T00:00:00.000Z    128.815002    129.779999     88.500000   \n",
       "3    2013-07-01T00:00:00.000Z     97.510002    111.344002     65.526001   \n",
       "4    2013-08-01T00:00:00.000Z    106.212997    140.889999    101.210999   \n",
       "..                        ...           ...           ...           ...   \n",
       "130  2024-02-01T00:00:00.000Z  42569.761398  63913.131814  41879.189991   \n",
       "131  2024-03-01T00:00:00.000Z  61168.062429  73750.073850  59323.908942   \n",
       "132  2024-04-01T00:00:00.000Z  71333.484717  72715.359609  59120.068047   \n",
       "133  2024-05-01T00:00:00.000Z  60609.497946  71946.462688  56555.294055   \n",
       "134      2024-06-01T00:00:00Z  67475.431181  71321.775649  67318.447828   \n",
       "\n",
       "            Close        Volume  \n",
       "0      139.000000  0.000000e+00  \n",
       "1      129.000000  0.000000e+00  \n",
       "2       96.613998  0.000000e+00  \n",
       "3      106.089996  0.000000e+00  \n",
       "4      135.350006  0.000000e+00  \n",
       "..            ...           ...  \n",
       "130  61198.382897  8.307219e+11  \n",
       "131  71333.647926  1.446418e+12  \n",
       "132  60636.856780  1.016068e+12  \n",
       "133  67491.417011  8.742915e+11  \n",
       "134  70959.476755  0.000000e+00  \n",
       "\n",
       "[135 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc2_old"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-04-01</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-05-01</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-06-01</td>\n",
       "      <td>96.613998</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>106.089996</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-08-01</td>\n",
       "      <td>135.350006</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013-09-01</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013-10-01</td>\n",
       "      <td>204.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013-11-01</td>\n",
       "      <td>1129.430054</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013-12-01</td>\n",
       "      <td>754.010010</td>\n",
       "      <td>20897300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>829.919983</td>\n",
       "      <td>17107900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014-02-01</td>\n",
       "      <td>549.260010</td>\n",
       "      <td>28076100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014-03-01</td>\n",
       "      <td>457.001007</td>\n",
       "      <td>28254000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014-04-01</td>\n",
       "      <td>447.644989</td>\n",
       "      <td>15244900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-05-01</td>\n",
       "      <td>623.677002</td>\n",
       "      <td>15107100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-06-01</td>\n",
       "      <td>639.796997</td>\n",
       "      <td>46422400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-07-01</td>\n",
       "      <td>586.234985</td>\n",
       "      <td>22467900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-08-01</td>\n",
       "      <td>477.763000</td>\n",
       "      <td>44632300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>386.944000</td>\n",
       "      <td>34707300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-10-01</td>\n",
       "      <td>338.321014</td>\n",
       "      <td>12545400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014-11-01</td>\n",
       "      <td>378.046997</td>\n",
       "      <td>9194440.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date        Close      Volume\n",
       "0  2013-04-01   139.000000         0.0\n",
       "1  2013-05-01   129.000000         0.0\n",
       "2  2013-06-01    96.613998         0.0\n",
       "3  2013-07-01   106.089996         0.0\n",
       "4  2013-08-01   135.350006         0.0\n",
       "5  2013-09-01   133.000000         0.0\n",
       "6  2013-10-01   204.000000         0.0\n",
       "7  2013-11-01  1129.430054         0.0\n",
       "8  2013-12-01   754.010010  20897300.0\n",
       "9  2014-01-01   829.919983  17107900.0\n",
       "10 2014-02-01   549.260010  28076100.0\n",
       "11 2014-03-01   457.001007  28254000.0\n",
       "12 2014-04-01   447.644989  15244900.0\n",
       "13 2014-05-01   623.677002  15107100.0\n",
       "14 2014-06-01   639.796997  46422400.0\n",
       "15 2014-07-01   586.234985  22467900.0\n",
       "16 2014-08-01   477.763000  44632300.0\n",
       "17 2014-09-01   386.944000  34707300.0\n",
       "18 2014-10-01   338.321014  12545400.0\n",
       "19 2014-11-01   378.046997   9194440.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc_all.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1808</th>\n",
       "      <td>2024-05-15</td>\n",
       "      <td>66267.492188</td>\n",
       "      <td>3.981517e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1809</th>\n",
       "      <td>2024-05-16</td>\n",
       "      <td>65231.582031</td>\n",
       "      <td>3.157308e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1810</th>\n",
       "      <td>2024-05-17</td>\n",
       "      <td>67051.875000</td>\n",
       "      <td>2.803128e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>2024-05-18</td>\n",
       "      <td>66940.804688</td>\n",
       "      <td>1.671228e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1812</th>\n",
       "      <td>2024-05-19</td>\n",
       "      <td>66278.367188</td>\n",
       "      <td>1.924909e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1813</th>\n",
       "      <td>2024-05-20</td>\n",
       "      <td>71448.195313</td>\n",
       "      <td>4.385066e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1814</th>\n",
       "      <td>2024-05-21</td>\n",
       "      <td>70136.531250</td>\n",
       "      <td>4.693201e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1815</th>\n",
       "      <td>2024-05-22</td>\n",
       "      <td>69122.335938</td>\n",
       "      <td>3.280256e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1816</th>\n",
       "      <td>2024-05-23</td>\n",
       "      <td>67929.562500</td>\n",
       "      <td>4.189568e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1817</th>\n",
       "      <td>2024-05-24</td>\n",
       "      <td>68526.101563</td>\n",
       "      <td>2.919731e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1818</th>\n",
       "      <td>2024-05-25</td>\n",
       "      <td>69265.945313</td>\n",
       "      <td>1.547307e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1819</th>\n",
       "      <td>2024-05-26</td>\n",
       "      <td>68518.093750</td>\n",
       "      <td>1.562843e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1820</th>\n",
       "      <td>2024-05-27</td>\n",
       "      <td>69394.554688</td>\n",
       "      <td>2.587099e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1821</th>\n",
       "      <td>2024-05-28</td>\n",
       "      <td>68296.218750</td>\n",
       "      <td>3.272227e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1822</th>\n",
       "      <td>2024-05-29</td>\n",
       "      <td>67578.093750</td>\n",
       "      <td>2.670707e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1823</th>\n",
       "      <td>2024-05-30</td>\n",
       "      <td>68364.992188</td>\n",
       "      <td>2.950971e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1824</th>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>67491.414063</td>\n",
       "      <td>2.738728e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1825</th>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>67706.937500</td>\n",
       "      <td>1.164150e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1826</th>\n",
       "      <td>2024-06-02</td>\n",
       "      <td>67751.601563</td>\n",
       "      <td>1.711059e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1827</th>\n",
       "      <td>2024-06-03</td>\n",
       "      <td>69212.054688</td>\n",
       "      <td>3.036929e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date         Close        Volume\n",
       "1808 2024-05-15  66267.492188  3.981517e+10\n",
       "1809 2024-05-16  65231.582031  3.157308e+10\n",
       "1810 2024-05-17  67051.875000  2.803128e+10\n",
       "1811 2024-05-18  66940.804688  1.671228e+10\n",
       "1812 2024-05-19  66278.367188  1.924909e+10\n",
       "1813 2024-05-20  71448.195313  4.385066e+10\n",
       "1814 2024-05-21  70136.531250  4.693201e+10\n",
       "1815 2024-05-22  69122.335938  3.280256e+10\n",
       "1816 2024-05-23  67929.562500  4.189568e+10\n",
       "1817 2024-05-24  68526.101563  2.919731e+10\n",
       "1818 2024-05-25  69265.945313  1.547307e+10\n",
       "1819 2024-05-26  68518.093750  1.562843e+10\n",
       "1820 2024-05-27  69394.554688  2.587099e+10\n",
       "1821 2024-05-28  68296.218750  3.272227e+10\n",
       "1822 2024-05-29  67578.093750  2.670707e+10\n",
       "1823 2024-05-30  68364.992188  2.950971e+10\n",
       "1824 2024-05-31  67491.414063  2.738728e+10\n",
       "1825 2024-06-01  67706.937500  1.164150e+10\n",
       "1826 2024-06-02  67751.601563  1.711059e+10\n",
       "1827 2024-06-03  69212.054688  3.036929e+10"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc_all.tail(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "btc_all = pd.read_csv('combined_btc_data.csv')\n",
    "btc_all['Date'] = pd.to_datetime(btc_all['Date'])\n",
    "\n",
    "plt.figure(figsize=(20, 10))\n",
    "plt.plot(btc_all['Date'], btc_all['Close'].astype(float), label='BTC Close Price', color='blue')\n",
    "plt.title('Historical BTC/USD Graph', size=15)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Price (USD)')\n",
    "plt.xticks(size=14)\n",
    "plt.yticks(size=13)\n",
    "plt.gca().xaxis.set_major_locator(mdates.YearLocator())\n",
    "plt.gca().xaxis.set_minor_locator(mdates.MonthLocator())\n",
    "plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n",
    "\n",
    "# Rotate the date labels for better visibility\n",
    "plt.gcf().autofmt_xdate()\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Avg: 28072.281185546482\n",
      "Min: 96.6139984131\n",
      "Max: 73083.5\n"
     ]
    }
   ],
   "source": [
    "print(f\"Avg: {btc_all['Close'].mean()}\")\n",
    "print(f\"Min: {btc_all['Close'].min()}\")\n",
    "print(f\"Max: {btc_all['Close'].max()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Year\n",
       "2013      314.054896\n",
       "2014      502.900248\n",
       "2015      272.070514\n",
       "2016      568.492407\n",
       "2017     4006.033629\n",
       "2018     7572.298947\n",
       "2019     7395.246282\n",
       "2020    11116.378092\n",
       "2021    47436.932021\n",
       "2022    28197.754099\n",
       "2023    28859.448250\n",
       "2024    58581.041961\n",
       "Name: Close, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc_all['Year'] = btc_all['Date'].dt.year  \n",
    "btc_all.groupby('Year')['Close'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16802.355089680517\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Month\n",
       "1     16581.081613\n",
       "2     18429.223664\n",
       "3     21082.083670\n",
       "4     21428.599174\n",
       "5     19728.467045\n",
       "6     13533.243163\n",
       "7     12899.745897\n",
       "8     14303.570023\n",
       "9     13682.792516\n",
       "10    15487.687104\n",
       "11    17005.220142\n",
       "12    17466.547064\n",
       "Name: Close, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc_all['Month'] = btc_all['Date'].dt.month  \n",
    "means = btc_all.groupby('Month')['Close'].mean()\n",
    "print(means.mean())\n",
    "btc_all.groupby('Month')['Close'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16927.799850416148\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Day\n",
       "1     14571.056135\n",
       "2     17337.106689\n",
       "3     17249.737375\n",
       "4     16826.712662\n",
       "5     16866.903985\n",
       "6     16990.074149\n",
       "7     17000.850060\n",
       "8     17135.397201\n",
       "9     17156.519038\n",
       "10    17034.904653\n",
       "11    17038.997118\n",
       "12    16913.913252\n",
       "13    17040.686737\n",
       "14    17087.293796\n",
       "15    17142.969808\n",
       "16    17011.591174\n",
       "17    16997.833359\n",
       "18    16939.968996\n",
       "19    16946.376119\n",
       "20    17124.801709\n",
       "21    16822.517876\n",
       "22    16731.949426\n",
       "23    16770.772555\n",
       "24    16761.818510\n",
       "25    16814.819584\n",
       "26    16885.320838\n",
       "27    16984.972608\n",
       "28    17121.013664\n",
       "29    17125.884724\n",
       "30    16967.141260\n",
       "31    17361.890303\n",
       "Name: Close, dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc_all['Day'] = btc_all['Date'].dt.day  \n",
    "means = btc_all.groupby('Day')['Close'].mean()\n",
    "print(means.mean())\n",
    "btc_all.groupby('Day')['Close'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def is_date(date):\n",
    "    try:\n",
    "        pd.to_datetime(date, format='%Y-%m-%d')\n",
    "        return True\n",
    "    except ValueError:\n",
    "        return False\n",
    "\n",
    "df = df[df['Date'].apply(is_date)]\n",
    "df['Date'] = pd.to_datetime(df['Date'])\n",
    "df['Month'] = df['Date'].dt.month\n",
    "\n",
    "ratings_mean = df.groupby('Month')['Rating'].mean()\n",
    "btc_all['Date'] = pd.to_datetime(btc_all['Date'])\n",
    "btc_all['Month'] = btc_all['Date'].dt.month\n",
    "btc_means = btc_all.groupby('Month')['Close'].mean()\n",
    "\n",
    "fig, ax1 = plt.subplots(figsize=(12, 7))\n",
    "\n",
    "color = 'tab:blue'\n",
    "ax1.set_xlabel('Month')\n",
    "ax1.set_ylabel('Average Bitcoin Price', color=color)\n",
    "ax1.plot(btc_means.index, btc_means.values, color=color, marker='o', linestyle='-', linewidth=2, markersize=8)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "ax2 = ax1.twinx()\n",
    "color = 'tab:red'\n",
    "ax2.set_ylabel('Mean Stars', color=color)\n",
    "ax2.plot(ratings_mean.index, ratings_mean.values, color=color, marker='o', linestyle='-', linewidth=2, markersize=8)\n",
    "ax2.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "plt.title('BTC Price vs Coinbase Mean Rating', fontsize=16)\n",
    "fig.tight_layout()\n",
    "plt.grid(True, linestyle='--', alpha=0.7)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matome kad keityklos reitingas panašu, jog iš tiesų yra **priklausomas** nuo to kokia kriptovaliūtos vertė yra tam tikru laikotarpiu koreliacijos atžvilgiu (kyla/ledžiasi).<br> Galime daryti prielaidą, kad krentant kriptovaliūtų kainoms keityklai tampa sudėtingiau vykdyti savo veiklą ar įgyvendinti užsibrėžtus tikslus ko pasekoje nepatenkintų vartotojų skaičius auga. Mažėjant kainai vidutinis įvertinimo reitingas taipogi krenta beveik iškart su minimaliu atsilikimu. Augimo kriterijai sutampa beveik identišku principu."
   ]
  }
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