Questions/E_Contract_Salary.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\User\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\fuzzywuzzy\\fuzz.py:11: UserWarning: Using slow pure-python SequenceMatcher. Install python-Levenshtein to remove this warning\n",
      "  warnings.warn('Using slow pure-python SequenceMatcher. Install python-Levenshtein to remove this warning')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from E_Salary_Cities import read,rename_columns,merge,clean_positions\n",
    "from E_Position_YearsOfExperience import clean_position,clean_senior_col,clean_years\n",
    "from E_Age_CompanyType import plt_univariate_histogram\n",
    "from E_Contract_Salary import clean_contract\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"border-width:1; border-radius: 15px; border-style: solid; border-color: rgb(10, 10, 10); background-color: #316B83; text-align: center;font: 14pt 'Candara';font-weight:bold;\"><h1> State & Refine QS</h1></div>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "What is the relationship between contract duration & salary? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Salary', 'Number of vacation days', 'Company type', 'Age', 'Seniority level', 'Years of experience', 'Position', 'Сontract duration', 'Your main technology / programming language', 'Gender', 'Main language at work', 'Company size', 'City'}\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2244 entries, 0 to 2243\n",
      "Data columns (total 13 columns):\n",
      " #   Column                                       Non-Null Count  Dtype  \n",
      "---  ------                                       --------------  -----  \n",
      " 0   Salary                                       2243 non-null   float64\n",
      " 1   Number of vacation days                      2116 non-null   object \n",
      " 2   Company type                                 2188 non-null   object \n",
      " 3   Age                                          2108 non-null   float64\n",
      " 4   Seniority level                              2217 non-null   object \n",
      " 5   Years of experience                          2228 non-null   object \n",
      " 6   Position                                     2237 non-null   object \n",
      " 7   Сontract duration                            2186 non-null   object \n",
      " 8   Your main technology / programming language  2103 non-null   object \n",
      " 9   Gender                                       2234 non-null   object \n",
      " 10  Main language at work                        2223 non-null   object \n",
      " 11  Company size                                 2212 non-null   object \n",
      " 12  City                                         2244 non-null   object \n",
      "dtypes: float64(2), object(11)\n",
      "memory usage: 228.0+ KB\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "e:\\University\\Fourth year\\second term\\Data science\\Data-Science-Project\\Questions\\E_Salary_Cities.py:43: FutureWarning: Passing a set as an indexer is deprecated and will raise in a future version. Use a list instead.\n",
      "  return pd.concat(data_frames, ignore_index=True)[common_columns]\n"
     ]
    }
   ],
   "source": [
    "df20, df19, df18 = read()\n",
    "rename_columns(df20,df19,df18)\n",
    "common_cols = set(df20.columns).intersection(df19.columns)\n",
    "print(common_cols)\n",
    "df = merge([df20,df19],common_cols)\n",
    "df.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Salary                1\n",
      "Сontract duration    58\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "SALARY = 'Salary'\n",
    "CONTRACT = 'Сontract duration'\n",
    "print(df[[SALARY,CONTRACT]].isna().sum())\n",
    "contract_salary = df[[CONTRACT,SALARY]].dropna()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Salary statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Сontract duration    Salary\n",
      "0  Unlimited contract   80000.0\n",
      "1  Unlimited contract   80000.0\n",
      "2  Temporary contract  120000.0\n",
      "3  Unlimited contract   54000.0\n",
      "4  Unlimited contract   62000.0\n"
     ]
    }
   ],
   "source": [
    "print(contract_salary.head(5))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Salaries are all in Euro, no need to unify the currency . we will use it directly"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Just one missing value for the salary column, no need to impute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1 missing salary/ies\n"
     ]
    }
   ],
   "source": [
    "print(\"There are\",df[SALARY].isna().sum(), \"missing salary/ies\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring the salary statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean salary:  300307.1538352403\n",
      "Median salary:  70000.0\n",
      "Standard deviation of salary:  10695071.57177836\n",
      "Max salary:  500000000.0\n",
      "Min salary:  6000.0\n"
     ]
    }
   ],
   "source": [
    "# compute mean, median, and standard deviation of a column\n",
    "mean_salary = contract_salary[SALARY].astype(float).mean()\n",
    "median_salary = contract_salary[SALARY].astype(float).median()\n",
    "std_salary = contract_salary[SALARY].astype(float).std()\n",
    "max_salary = contract_salary[SALARY].astype(float).max()\n",
    "min_salary = contract_salary[SALARY].astype(float).min()\n",
    "\n",
    "# display the computed statistics\n",
    "print('Mean salary: ', mean_salary)\n",
    "print('Median salary: ', median_salary)\n",
    "print('Standard deviation of salary: ', std_salary)\n",
    "print('Max salary: ', max_salary)\n",
    "print('Min salary: ', min_salary)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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mm/Dhhx9iwIABhu82bdqEpUuXYvXq1cjOzgYAPPnkk+jfvz8effRRv0ETAJSXl6O8vFz9X1hY+DvXhIiIiOqbC/qZoOrqaowaNQpTp05Fs2bNfL5fuXIlwsLCVAAEALm5uTCZTFi1alWt8505cybcbrd6JSYmnpP0ExER0YXrgg6CHnroIVgsFtx8881+v8/Ly4PH4zF8ZrFYEBERgby8vFrnO23aNBQUFKjX7t27z2q6iYiI6MJ3Xm+H1WXNmjX45z//ibVr10LTtLM6b7vdDrvdflbnSURERPXLBXsl6PPPP8f+/fuRlJQEi8UCi8WCnTt34rbbbkNKSgoAIDY2Fvv37zf8rqqqCocPH0ZsbOx5SDURERHVFxfslaBRo0YhNzfX8FmfPn0watQojB07FgCQk5ODo0ePYs2aNWjbti0AYNmyZaiurkaHDh3+8DQTERFR/XFeg6CioiL8/PPP6v/t27dj3bp1iIiIQFJSEiIjIw3TW61WxMbGokmTJgCApk2bom/fvpgwYQLmzZuHyspK3HjjjRg+fHitLcNO5sDcfyH6hlFnvlJERERUL5zX22HffvstsrKykJWVBQCYMmUKsrKyMGPGjFOex6uvvoqMjAz07t0b/fv3R5cuXfDss8+eqyQTERHRn8R5vRLUo0cPCCFOefodO3b4fBYREYHXXnvtLKaKiIiIAsEF+2A0ERER0bnEIIiIiIgCEoOgWhyYu+B8J4GIiIjOIQZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQVAdDsydjwNz55/vZBAREdE5wCCIiIiIAhKDICIiIgpIDIKIiIgoIDEIIiIiooDEIIiIiIgCEoMgIiIiCkgMgoiIiCggMQgiIiKigMQgiIiIiAISgyAiIiIKSOc1CPrss89wySWXID4+Hpqm4e2331bfVVZW4s4770SLFi0QHByM+Ph4jB49Gnv37jXM4/Dhwxg5ciRcLhfCwsIwfvx4FBUV/cFrQkRERPXNeQ2CiouL0apVK8yZM8fnu5KSEqxduxbTp0/H2rVr8dZbb2Hz5s0YNGiQYbqRI0di48aN+Pjjj7F48WJ89tlnuPbaa/+oVSAiIqJ6ynI+F96vXz/069fP73dutxsff/yx4bOnnnoK7du3x65du5CUlIRNmzZh6dKlWL16NbKzswEATz75JPr3749HH30U8fHx53wdiIiIqH6qV88EFRQUQNM0hIWFAQBWrlyJsLAwFQABQG5uLkwmE1atWlXrfMrLy1FYWGh4ERERUWCpN0FQWVkZ7rzzTowYMQIulwsAkJeXB4/HY5jOYrEgIiICeXl5tc5r5syZcLvd6pWYmHhO005EREQXnnoRBFVWVmLYsGEQQmDu3Lm/e37Tpk1DQUGBeu3evfsspJKIiIjqk/P6TNCpkAHQzp07sWzZMnUVCABiY2Oxf/9+w/RVVVU4fPgwYmNja52n3W6H3W4/Z2kmIiKiC98FfSVIBkBbt27F//73P0RGRhq+z8nJwdGjR7FmzRr12bJly1BdXY0OHTr80cklIiKieuS8XgkqKirCzz//rP7fvn071q1bh4iICMTFxWHo0KFYu3YtFi9ejOPHj6vnfCIiImCz2dC0aVP07dsXEyZMwLx581BZWYkbb7wRw4cPZ8swIiIiqtN5DYK+/fZb9OzZU/0/ZcoUAMCYMWPwt7/9De+++y4AoHXr1obfffrpp+jRowcA4NVXX8WNN96I3r17w2QyYciQIZg9e/Yfkn4iIiKqv85rENSjRw8IIWr9vq7vpIiICLz22mtnM1lEREQUAC7oZ4KIiIiIzhUGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEnYID817AgXkvnO9kEBER0VnEIIiIiIgCEoMgIiIiCkjnNQj67LPPcMkllyA+Ph6apuHtt982fC+EwIwZMxAXFwen04nc3Fxs3brVMM3hw4cxcuRIuFwuhIWFYfz48SgqKvoD14KIiIjqo/MaBBUXF6NVq1aYM2eO3+8ffvhhzJ49G/PmzcOqVasQHByMPn36oKysTE0zcuRIbNy4ER9//DEWL16Mzz77DNdee+0ftQpERERUT1nO58L79euHfv36+f1OCIEnnngCf/3rXzF48GAAwMsvv4yYmBi8/fbbGD58ODZt2oSlS5di9erVyM7OBgA8+eST6N+/Px599FHEx8f/YetCRERE9csF+0zQ9u3bkZeXh9zcXPWZ2+1Ghw4dsHLlSgDAypUrERYWpgIgAMjNzYXJZMKqVatqnXd5eTkKCwsNLyIiIgosF2wQlJeXBwCIiYkxfB4TE6O+y8vLg8fjMXxvsVgQERGhpvFn5syZcLvd6pWYmHiWU09EREQXugs2CDqXpk2bhoKCAvXavXv3+U4SERER/cEu2CAoNjYWAJCfn2/4PD8/X30XGxuL/fv3G76vqqrC4cOH1TT+2O12uFwuw4uIiIgCywUbBKWmpiI2NhaffPKJ+qywsBCrVq1CTk4OACAnJwdHjx7FmjVr1DTLli1DdXU1OnTo8IenmYiIiOqP89o6rKioCD///LP6f/v27Vi3bh0iIiKQlJSEW265Bffddx/S09ORmpqK6dOnIz4+HpdeeikAoGnTpujbty8mTJiAefPmobKyEjfeeCOGDx/OlmFERERUp/MaBH377bfo2bOn+n/KlCkAgDFjxuCll17CHXfcgeLiYlx77bU4evQounTpgqVLl8LhcKjfvPrqq7jxxhvRu3dvmEwmDBkyBLNnz/7D14WIiIjqF00IIc53Is63wsJCuN1uFBQUoPzVdxB9wygcmLsAQHXNBFrNe/T1489fIomIiMhAf/w+k+d7L9hngoiIiIjOJQZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBaQzCoJ69eqFo0eP+nxeWFiIXr16/d40EREREZ1zZxQELV++HBUVFT6fl5WV4fPPP//diSIiIiI61yynM/H333+v/v7xxx+Rl5en/j9+/DiWLl2KBg0anL3UEREREZ0jpxUEtW7dGpqmQdM0v7e9nE4nnnzyybOWOCIiIqJz5bSCoO3bt0MIgbS0NHzzzTeIjo5W39lsNng8HpjN5rOeSCIiIqKz7bSeCUpOTkZKSgqqq6uRnZ2N5ORk9YqLizvrAdDx48cxffp0pKamwul0omHDhvi///s/CCHUNEIIzJgxA3FxcXA6ncjNzcXWrVvPajqIiIjoz+e0rgTpbd26FZ9++in279+P6upqw3czZsz43QkDgIceeghz587FggUL0KxZM3z77bcYO3Ys3G43br75ZgDAww8/jNmzZ2PBggVITU3F9OnT0adPH/z4449wOBxnJR1ERET053NGQdBzzz2HG264AVFRUYiNjYWmaeo7TdPOWhD01VdfYfDgwRgwYAAAICUlBf/+97/xzTffAKi5CvTEE0/gr3/9KwYPHgwAePnllxETE4O3334bw4cP9zvf8vJylJeXq/8LCwvPSnqJiIio/jijJvL33Xcf7r//fuTl5WHdunX47rvv1Gvt2rVnLXGdOnXCJ598gi1btgAA1q9fjy+++AL9+vUDUPOMUl5eHnJzc9Vv3G43OnTogJUrV9Y635kzZ8LtdqtXYmLiWUszERER1Q9ndCXoyJEjuOKKK852WnzcddddKCwsREZGBsxmM44fP477778fI0eOBADVRD8mJsbwu5iYGEPzfW/Tpk3DlClT1P+FhYUMhIiIiALMGV0JuuKKK/DRRx+d7bT4+O9//4tXX30Vr732GtauXYsFCxbg0UcfxYIFC37XfO12O1wul+FFREREgeWMrgQ1atQI06dPx9dff40WLVrAarUavpcPLf9eU6dOxV133aWe7WnRogV27tyJmTNnYsyYMYiNjQUA5OfnIy4uTv0uPz8frVu3PitpICIioj+nMwqCnn32WYSEhGDFihVYsWKF4TtN085aEFRSUgKTyXixymw2q9ZoqampiI2NxSeffKKCnsLCQqxatQo33HDDWUkDERER/TmdURC0ffv2s50Ovy655BLcf//9SEpKQrNmzfDdd9/hsccew7hx4wDUBFy33HIL7rvvPqSnp6sm8vHx8bj00kv/kDQSERFR/XTG/QT9EZ588klMnz4dEydOxP79+xEfH4/rrrvO0AT/jjvuQHFxMa699locPXoUXbp0wdKlS9lHEBEREdVJE/rul0+RvBJTmxdffPGME3Q+FBYWwu12o6CgAOWvvoPoG0bhwNwFAE50AqnVvEdfP/78JZKIiIgM9MfvM2nkdMZN5PUqKyuxYcMGHD161O/AqkREREQXmjMKghYtWuTzWXV1NW644QY0bNjwdyeKiIiI6Fw7o36C/M7IZMKUKVPw+OOPn61ZEhEREZ0zZy0IAoBffvkFVVVVZ3OWREREROfEGd0O0w85AdQMZLpv3z4sWbIEY8aMOSsJIyIiIjqXzigI+u677wz/m0wmREdHY9asWSdtOUZERER0ITijIOjTTz892+kgIiIi+kP9rs4SDxw4gM2bNwMAmjRpgujo6LOSKCIiIqJz7YwejC4uLsa4ceMQFxeHbt26oVu3boiPj8f48eNRUlJyttNIREREdNadURA0ZcoUrFixAu+99x6OHj2Ko0eP4p133sGKFStw2223ne00EhEREZ11Z3Q77M0338Qbb7yBHj16qM/69+8Pp9OJYcOGYe7cuWcrfURERETnxBldCSopKUFMTIzP5x6Ph7fDiIiIqF44oyAoJycH9957L8rKytRnpaWl+Pvf/46cnJyzljgiIiKic+WMboc98cQT6Nu3LxISEtCqVSsAwPr162G32/HRRx+d1QQSERERnQtnFAS1aNECW7duxauvvoqffvoJADBixAiMHDkSTqfzrCaQiIiI6Fw4oyBo5syZiImJwYQJEwyfv/jiizhw4ADuvPPOs5I4IiIionPljJ4JeuaZZ5CRkeHzebNmzTBv3rzfnSgiIiKic+2MgqC8vDzExcX5fB4dHY19+/b97kQRERERnWtnFAQlJibiyy+/9Pn8yy+/RHx8/O9OFBEREdG5dkbPBE2YMAG33HILKisr0atXLwDAJ598gjvuuIM9RhMREVG9cEZB0NSpU3Ho0CFMnDgRFRUVAACHw4E777wT06ZNO6sJJCIiIjoXzuh2mKZpeOihh3DgwAF8/fXXWL9+PQ4fPowZM2ac7fRdUA7Me+58J4GIiIjOkjO6EiSFhISgXbt2ZystRERERH+YM7oSFOgOzHvmfCeBiIiIficGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlB0O9wYN7c850EIiIiOkMMgoiIiCggMQgiIiKigMQgiIiIiAISgyAiIiIKSAyCiIiIKCBd8EHQnj17cPXVVyMyMhJOpxMtWrTAt99+q74XQmDGjBmIi4uD0+lEbm4utm7deh5TTERERPXBBR0EHTlyBJ07d4bVasUHH3yAH3/8EbNmzUJ4eLia5uGHH8bs2bMxb948rFq1CsHBwejTpw/KysrOY8qJiIjoQmc53wmoy0MPPYTExETMnz9ffZaamqr+FkLgiSeewF//+lcMHjwYAPDyyy8jJiYGb7/9NoYPH+53vuXl5SgvL1f/FxYWnqM1ICIiogvVBX0l6N1330V2djauuOIKeDweZGVl4bnnnlPfb9++HXl5ecjNzVWfud1udOjQAStXrqx1vjNnzoTb7VavxMTEc7oeREREdOG5oIOgbdu2Ye7cuUhPT8eHH36IG264ATfffDMWLFgAAMjLywMAxMTEGH4XExOjvvNn2rRpKCgoUK/du3efu5UgIiKiC9IFfTusuroa2dnZeOCBBwAAWVlZ2LBhA+bNm4cxY8ac8XztdjvsdvvZSiYRERHVQxf0laC4uDhkZmYaPmvatCl27doFAIiNjQUA5OfnG6bJz89X3/0R9s976g9bFhEREZ0dF3QQ1LlzZ2zevNnw2ZYtW5CcnAyg5iHp2NhYfPLJJ+r7wsJCrFq1Cjk5OX9oWomIiKh+uaBvh916663o1KkTHnjgAQwbNgzffPMNnn32WTz77LMAAE3TcMstt+C+++5Deno6UlNTMX36dMTHx+PSSy89v4knIiKiC9oFHQS1a9cOixYtwrRp0/CPf/wDqampeOKJJzBy5Eg1zR133IHi4mJce+21OHr0KLp06YKlS5fC4XCcx5QTERHRhe6CDoIAYODAgRg4cGCt32uahn/84x/4xz/+8QemioiIiOq7C/qZICIiIqJzhUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQGIQRERERAGJQRAREREFJAZBREREFJAYBJ0l++fNxv55s893MoiIiOgUMQgiIiKigMQgiIiIiAISgyAiIiIKSAyCiIiIKCAxCDrL9s97HPvnPX6+k0FEREQnwSCIiIiIAhKDoHMkf+6jyJ/76PlOBhEREdWCQRAREREFJAZBREREFJAYBBEREVFAYhBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQ6lUQ9OCDD0LTNNxyyy3qs7KyMkyaNAmRkZEICQnBkCFDkJ+ff/4SSURERPVCvQmCVq9ejWeeeQYtW7Y0fH7rrbfivffew8KFC7FixQrs3bsXl19++XlKJREREdUX9SIIKioqwsiRI/Hcc88hPDxcfV5QUIAXXngBjz32GHr16oW2bdti/vz5+Oqrr/D111+fxxQTERHRha5eBEGTJk3CgAEDkJuba/h8zZo1qKysNHyekZGBpKQkrFy5stb5lZeXo7Cw0PAiIiKiwHLBB0Gvv/461q5di5kzZ/p8l5eXB5vNhrCwMMPnMTExyMvLq3WeM2fOhNvtVq/ExMSznWwlf+5D52zeREREdOYu6CBo9+7dmDx5Ml599VU4HI6zNt9p06ahoKBAvXbv3n3W5k1ERET1wwUdBK1Zswb79+9HmzZtYLFYYLFYsGLFCsyePRsWiwUxMTGoqKjA0aNHDb/Lz89HbGxsrfO12+1wuVyG17mWP/eBc74MIiIiOnWW852AuvTu3Rs//PCD4bOxY8ciIyMDd955JxITE2G1WvHJJ59gyJAhAIDNmzdj165dyMnJOR9JJiIionrigg6CQkND0bx5c8NnwcHBiIyMVJ+PHz8eU6ZMQUREBFwuF2666Sbk5OSgY8eO5yPJREREVE9c0EHQqXj88cdhMpkwZMgQlJeXo0+fPnj66afPd7KIiIjoAlfvgqDly5cb/nc4HJgzZw7mzJlzfhJERERE9dIF/WA0ERER0bnCIIiIiIgCEoMgIiIiCkgMgoiIiCggMQgiIiKigMQgiIiIiAISgyAiIiIKSPWun6D6Lm/uPwBxHAAgUAUAiJt4//lMEhERUUDilSAiIiIKSAyCiIiIKCAxCCIiIqKAxCCIiIiIAhKDICIiIgpIDIKIiIgoIDEIugDsffoO7H36jvOdDCIiooDCIIiIiIgCEoMgIiIiCkgMgi4ge+dMOd9JICIiChgMgoiIiCggMQi6AO2Zc+P5TgIREdGfHoMgIiIiCkgcRf4C9utT10GIcgBA4k0vnd/EEBER/cnwShAREREFJAZBREREFJAYBNUTu54cjl1PDj/fySAiIvrTYBBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEFTP7Jx9KXbOvvR8J4OIiKjeYxBEREREAYlBEBEREQUkBkFEREQUkBgEERERUUBiEEREREQBiUEQERERBSQGQfXU9icvPd9JICIiqtcu6CBo5syZaNeuHUJDQ+HxeHDppZdi8+bNhmnKysowadIkREZGIiQkBEOGDEF+fv55SjERERHVFxd0ELRixQpMmjQJX3/9NT7++GNUVlbi4osvRnFxsZrm1ltvxXvvvYeFCxdixYoV2Lt3Ly6//PLzmOo/1s9PDT7fSSAiIqqXLOc7AXVZunSp4f+XXnoJHo8Ha9asQbdu3VBQUIAXXngBr732Gnr16gUAmD9/Ppo2bYqvv/4aHTt2PB/JJiIionrggr4S5K2goAAAEBERAQBYs2YNKisrkZubq6bJyMhAUlISVq5cWet8ysvLUVhYaHgRERFRYLmgrwTpVVdX45ZbbkHnzp3RvHlzAEBeXh5sNhvCwsIM08bExCAvL6/Wec2cORN///vfz2Vy/3BbnhqMaq3m72pN1LxD/g+0vOHd85MwIiKiC1S9uRI0adIkbNiwAa+//vrvnte0adNQUFCgXrt37z4LKSQiIqL6pF5cCbrxxhuxePFifPbZZ0hISFCfx8bGoqKiAkePHjVcDcrPz0dsbGyt87Pb7bDb7ecyyURERHSBu6CvBAkhcOONN2LRokVYtmwZUlNTDd+3bdsWVqsVn3zyifps8+bN2LVrF3Jycv7o5BIREVE9ckFfCZo0aRJee+01vPPOOwgNDVXP+bjdbjidTrjdbowfPx5TpkxBREQEXC4XbrrpJuTk5LBlGBEREdXpgr4SNHfuXBQUFKBHjx6Ii4tTr//85z9qmscffxwDBw7EkCFD0K1bN8TGxuKtt946j6m+cK2bO+h8J4GIiOiCcUFfCRJCnHQah8OBOXPmYM6cOX9AioiIiOjP4oK+EkRERER0rjAIIiIiooB0Qd8Oo3Nj7bxLIG80tr3+vfOaFiIiovOFV4KIiIgoIDEIIiIiooDEIIiIiIgCEoMgIiIiCkh8MDrArX7mEgBA9YlHpas1IOfaxeczSURERH8IXgkiIiKigMQgiIiIiAISb4eRX189OxCdrl2ML54dCKGduFV24rvuE5acv4QRERGdJbwSRERERAGJQRCdtuXPDcDy5wZg2fMDAAD/O/FORERUnzAIIiIiooDEIIjOmo+f7w8A+PCF/uc5JURERCfHIIiIiIgCEoMgIiIiCkhsIk/nxNITt8TEif+rITBg/AfnL0FEREReeCWIiIiIAhKvBNEfavGL/TBw3Ad498V+GDTuA7zzYj/VCaPslPHysUvPXwKJiChg8EoQERERBSQGQURERBSQGATRBeeN+X3xxvy+WDi/LwDgPyfeiYiIziYGQURERBSQ+GA01Ruvv9Tnt4eoT7zr/x99zYd/fKKIiKje4pUgIiIiCkgMgoiIiCggMQiiP5WXXroYADB/wcV48cSLiIjIHwZBREREFJD4YDT96T3/ch8Avz1MLTTg2lEfYt6/+uD6UR9i7iu6B661mvcbR/IhayKiPzteCSIiIqKAxCtBRH7MfrXm6lG1Btxy1Yd4/LU+uPWqDzHr379dNao+cdVI//89V36I//tPH0y/kleSiIgudLwSRERERAGJQRAREREFJN4OIzpH/vbfPqhGzT2z4ydunR0/8d1xDXhk6FJMebMvHhuyFDe/2RdVJ6aR75Unpq3QgFcvXYqh7/TFG4OX/mHpJyL6s+OVICIiIgpIvBJEVM8MfKcvFg9ein7vDgaE48SnthPvVnww+EX0e+c6fDD4GfR7ZxI+GDwH/d6eDA3mE9P4vr9/6f3o//Z0vH/p/6H/ont138nzJE39//5l09B/0UN4/7I7MWDRI7/1K+Bn2iWXT8aAt2ZjyeU3Y8BbTxq+M0wrNCwZcj0GvPkMlgy5DgPefFY3bc37kiF/Of3MIiKqw5/mStCcOXOQkpICh8OBDh064JtvvjnfSSIiIqIL2J8iCPrPf/6DKVOm4N5778XatWvRqlUr9OnTB/v37z/fSSMiIqIL1J/idthjjz2GCRMmYOzYsQCAefPmYcmSJXjxxRdx1113nefUEdHZMODNFwAAGjQsHjIOA9+cj8VDxmLgmy9Bf1sNJ6aS74uHXo2Bb7yKxUNHYuAbr2Hx0Ksw8I1/w/t2W820wzDwjYVYPPQKDFz4BhZfMRSXvPGm32llWt4dOhiD3ngX7w4dhEFvvAfvW36a7jfvDO2LwW98iHeG9sHgNz6C5nML8cR8NQ2LhvTEZW+uwKIh3XHZm5/5nZ9czltDOmLIm9/gzSHtMeTN1br5Gt81aFg4pCWueHMDFg5pjmFv/gh561P9RpPTmvH65Sm45q2deOnyZFz31i48c3kSbl60G7YTy7bq3v9xWTz+sWgvZlwWjwcW7cPdl8Xh4UX7YDkxjTzYmE/8bxbA9ZfH4Lm39mPC5R68+Nb+376T0wqZeg1XDonCG28exNAhUXjrjYMwqe9OvIvf3vtfGYWlrx9E3+FR+OjfB2E60V+8Jnyn7X51ND7/1wF0HRWNL18+4Gcaof7PHufBmhf2o+14D757fr9hPjXzPzFtNZB5Qwx+ejofGRNjsGVOPkzVXvOT/1cDSVNi8eusPCTcFou9j+xD/NQ47HtoH6CdaEqhVZ/YJtWInZqCvEe3Ifb2NOQ9+jNib2+EvFlboeuxzPAbQCB2SnPkP/49Ym5tifzH10H1n6+bRv425pb2yP/nKsRM7oD8f66sY1qBmJu7IX/2csTc3AP7n/xUlwZhfNeq4bmxD/Y/tRSeG/ti/1Pv15kGz6RLsX/OIngmXYb9c978bcN5raOmVcM+ciB+j3ofBFVUVGDNmjWYNm2a+sxkMiE3NxcrV670+5vy8nKUl5er/wsKCgAAhYWFqCgthb2wEMdKS+FbmKrVd97vv23AmkIrhGoHBGdhIY6Vlql3iJr5CVSdeD/RDkhUobCwEMdKK9S7EBWGaeR79Yn0HiutRGFhIYpKK3/rvO9EgdF34ienke9C913NfIVh2uIT0xaXVkJ4zU94zVc/rfqNV57L9JaUVvm8/zZkhe9yap3Wz3thYSFKT0xbWlqlS6dmnFbznba2+cp1LCupUu91dZaon7a8pKrO1mFymsLCQlSUVNXaOqzyxLSVJ6aV71UllYCQhwtJnPiuwuu9HP6eBZLvNfMtV+/eB0/9AbdmmjL1XtczQcZpS+EdIOiDFzmN77S+gUet0/oJgmqmKfF59zf/05nWmBZ/03oHLXI7Fqv3uoIg72nrCoJqpilS73UFQd7T+gZBct3MJ8rmMZ93cWLZ1br3mrJ/TPcejLKSYz5BkEkXBBUWOlFacgyFhQ6UlhzzCYJ+C3Q0FBbaUFJyTL3XFQQVFtpQfGLa4pJjtQdBAAoL7SguPabevafRdEFQYaEDRaXH1HtdQVBhofPEtDXv8jAi06IPggoLg3Cs7JjuPRjHyo75DYKCCgtxrOyY13sR6gqC5DRONW3tAUjNNMXqva4gyDBtaTHqCoIcJ6apeS+pMw1yGjVtHUFQeWFhza+F91HnFIl6bs+ePQKA+OqrrwyfT506VbRv397vb+69915xIsf54osvvvjii696/tq9e/cZxRB/imeCTte0adNQUFCgXkeOHMG6devU9z/++OMpvde3aS+ktNS3aS+ktNS3aS+ktPyZp72Q0lLfpr2Q0lLfpr1Q0hIfH48zUe9vh0VFRcFsNiM/P9/weX5+PmJjY/3+xm63w263Gz4zmX6LB0NDQ0/pvb5NeyGlpb5NeyGlpb5NeyGl5c887YWUlvo27YWUlvo27YWQlgYNGhiO4aej3l8JstlsaNu2LT755BP1WXV1NT755BPk5OScx5QRERHRhazeXwkCgClTpmDMmDHIzs5G+/bt8cQTT6C4uFi1FiMiIiLy9qcIgq688kocOHAAM2bMQF5eHlq3bo2lS5ciJibmlOdht9txzz33AABcLhfuvffeOt/r27QXUlrq27QXUlrq27QXUlr+zNNeSGmpb9NeSGmpb9NeKGnxfrzldGhCnGm7MiIiIqL6q94/E0RERER0JhgEERERUUBiEEREREQBiUEQERERBSQGQURERBSQGAQRERFRQPpT9BN0NuhHlQeg+h2Qn9vtdr/TFBQUIC8vDwAQHh4Ot9tdZ58F5eXlarwy79/ol+W97FNNv/e0/tKvn0af/tjYWLjd7pPOt6CgAFu3bsWBAwcQHR2N9PR0uN3uU0rvydJgNptRWlqqpgsNDTWky1969+/fj/z8fNhsNp9tUF5ejgMHDuCNN97AunXrUFRUBKvVitjYWHTq1AmDBw+GzWarK2tPqrY8PFl+yO/LyspqLUN1bR/9/E8lDSfb1v7m662qqgobN240zMfhcOD555/HunXrUFBQALPZrPL3mmuuQXR0dF3Z58NfOv19pt8f9fuU97p5/xaAIb8B+N0f/a1rZmYmrFarmmdFRQViYmLg8XhOax1r473MiIgIxMfHo6ioyO+6+Vs/h8MB4NS3n1ynk6mr7tJPU9uyT0Vd28q7LBw7dkyt00cffYTvvvsOeXl5qK6uRkxMDLp27Woof97pl/OrqKjA22+/jZUrVxqW5V0/1HaM8Jc/FRUVcDqdOH78uGFZxcXF+PHHH3H48GH1eYMGDXDo0KFay9KZbLPa1tV7Gn/rcbJ64nTqkYMHD2LBggV4++23sXv3blRWVsLhcCA1NRXXXHMNRo0ahdLS0lr3R391mfR7+gbSC+h+gj7++GM8/vjj+Oyzz1BcXGz4zmw2Q9M0HD9+HLVlkaZpfr+zWq2IiIhAcHAwiouLcezYMZSXl6sd4mQ0TQMANW+n04lOnTrhrrvuQm5uriH9s2bNwqpVq1BYWAigplOp9PR0AMDWrVtRUFDgk0ZN09T6VVZWGtbD6XQiPj4eFovFUNG4XC4kJCRg7969ageujcPhQE5ODm6//Xa0atUK06dPx5IlS3Do0CGVB2azGRaLBZWVlaiurj6lPDGbzaiqqqo13/XkODK1zVvOw2w2Iz09HRkZGejUqRMuueQSvPvuuz4VYvv27dGhQwe88cYb+PTTT7Fz506Ul5cb5i+3W1BQEI4fP46ysjL1uc1mQ0JCApo2bYqCggKsX79ebbO61lkIAU3T1Lzj4+PhdruxZ88eFBYWqu+rq6sN+WIymSCEqDOfnE4nMjIyMGLECDRo0AAvvfQSVq9erdIVGhqKhg0bwu1248CBA9i+fTtKSkpOmvfh4eEIDQ3F/v37UVlZiczMTDRs2NCQh975m5OTg6ioKCxcuBBbtmwBAJV+f9u7rjKgaRoaN26MDh06YPXq1di8ebNhfqfCYqk5P/Te/y0WCywWi9q2kslkQmZmJh566CH07t271iDf+6Tn888/x6xZs7BhwwaVX3Wl0WQyoUmTJrj55pshhMDs2bOxefNmv7/R1xtt27bF3Xffjddee82n3GmahujoaAwePBgTJ05EdHQ0HnnkEbzzzjvYt28fKioq6kyT3W6Hy+VCaWmpKh9BQUGIjo5GTEwMqqqq1LrZbDZEREQgMjISWVlZGDt2LBo2bIhnn30W//znP7F9+3YAxm2lrw+tVisqKyv9pkO/zeT0mqapetjfOsh6QgiBmJgYpKamokGDBti3bx9Wr14Nt9uNRo0a4fvvv/c5Rsg6SdZjp1q/n4ymaUhKSsLYsWOxc+dOLFq0CAUFBSqdQM0xxuPxIDExEZGRkWjatCkSEhKwZMkSfPHFFygtLfVZz/T0dPTp0wdr167FN998g4qKilNKjzypiY+PR15eHvbs2WPYPmazGU6nE3a7HRUVFSgrK0NVVZVPfkdFRSEyMhLl5eXYu3cvKioqYLFY6jzGAkBwcDCqqqp8gqDg4GB07twZU6dONRwXT9sZjT3/J3D//fcLk8kkgoKCBABhtVpFeHi4CA4OFgAEAKFpmt93q9WqppGvhIQE0ahRIzVNbS/5W03ThNvtNsxXvsxms/rOZrPVOT99Wm02mzCZTD7pl5/J/81ms8/vQ0NDRXx8vLBYLKe0rMjISDUff3nm72UymWqdv6Zpwm63CwAiPDz8lNfd4XAY5u10On2msdvtwmQyibCwMMP6R0VFGfLLOz1Wq7XW700mk9A0TSQmJoqoqCi/665pmoiLixPJyclq3fylTf+un4f3dvOXRu/tWdtyzGazml7mkb9yrF/3upbpnReyDMltd7KXyWQSDodDOBwOv/PUr5P8Xu6r3q/o6GjRoEEDQ1q80+y9D8u/U1NT1fenmnb9y+l0iqCgoFrLye99ud1ukZWVJSwWy0n3TbvdLpo0aSJSUlJOOe1ut/ukaZdlRz+dzO/aysnZeFmt1pOus7+yExUVJZKSkvzmz9nYTna7XYSGhvr9zmQyCZPJJGJjY4Wmaapu0L+CgoL81lNOp7PO9dXvEydbD6fTKVq0aCFSUlLqnKfNZvPZtvIVHh4uNE2r8/e1pSM4ONjvdxEREaJRo0Y+xyC5DzZu3FhERET4nafFYhGpqamiQYMGPmlq2bKl+Pjjj88oFgjIIOj9998XAERKSoqIiIgQV155pZg0aZLa2TVNE82bN1eFSW7sSy65xHBgcjqdIiQkRGRnZ6uN0ahRI9GlSxcBQISEhKjfut1u0bRpU7WTtGnTRgAQiYmJwuPxiLi4OKFpmsjOzlYHdpfLJQCImJiYWguhXIa+UDVo0MBQCcj16t27tyEwCgsLE0FBQaJDhw6GeUZGRtYagISHh6sCaDKZhNlsFrfddpswm80qDY0bN/b5XWxsrCEtoaGholWrVio/zWaziIyMFEOHDhUOh0NcfvnlIjExUUycOFF9HxERIWw2mwgKClI7jKZp4uKLLxaRkZEqMMnMzBSapqkdUdM0YTabxdKlS0VKSopwuVzizjvvVNtRv5N5V+r6dZXbRb9OFovFkPcysIqJifEJaEwmk7BarWo+MnCVO3e/fv1UPlksFuFyuUT79u198rJhw4Y+aW/WrJlo0qSJ+jwuLk5cdNFFqqzJA0pOTo7ajt7lyGq1+hxUUlJSRIsWLVR51AcUMviVee6dXzLv9Xkg88pfwBgaGuo38LvxxhtF586d1f+hoaEiLS1NmEwm4XQ6RaNGjQQAER8fLwCoYNdfgGU2m4XJZBJ2u12VxYkTJ4obbrhB7b+ysjabzYYDp3zv3r272oZyP4mMjDzpCZB8eQdz+gOqy+USAwcOVPuDnFaeFMkDhD5v5d8dO3ZU6ye3k/4Apy+nMlCS6ZcHa/3BRZYHm80mzGaziImJEZ07d1brKuulkJAQYbFYDGVD5o8sd2azWVgsFtGyZUs1f6fTaQhO9fmQkJCg6pTo6GjDNLm5uT71U3p6uoiKihI9e/Y0pH/48OEqX2Ud0axZMxEZGammGzZsmIiMjFT7j796S1+fyr9tNptwu90qkOzQoYMqW4888oiqu2T63W636Nq1q6EsNW/eXMTFxRmOIUlJSYYTllatWqnv5ElOcHCwz74l667U1FTDtvZ4PD4nxPIlt63H4xHjxo1Tf997770iNjZWTS+3r6zbZfAk8zkuLk7N3/vYc+WVV4r09HRx0UUXGdIrj4HeJ13NmzdXy5V5od9eJpNJTJkyRUycOFHExcWJq6++WtVfL7/88mnHAwEZBLVs2VKYzWbx008/CbvdLn766SfRsmVLMX36dGG328WkSZPUTiYDpkmTJgmHw6EK9sSJE1UF0aRJE7WTp6eni+TkZJ/fapomFi9eLACIGTNmqMrm/fffFw6HQxXu999/X2iaJvr16yesVqswm82iZcuW4oYbblCFrl+/fkLTNJWmbt26qXdZcOQOLZct12n69Om1pt/j8QgAYvHixULTNLXMbt26qTOCuLg44XA41E4h53vPPfeowpyeni7++te/qkI7Y8YMYbVaxbBhw4SmaWLGjBmG/AAgpk+fLjRNE0uWLFFpcDqdaj3sdrt6yW3z448/CrPZLJKTk1V69flut9tVBTRp0iTRokUL9Xu5M1955ZWqsnU4HGLJkiWGAFfmq6Zphu0p8zkmJkZYLBZVLuQ0Mg+7desmLBaL8Hg8wmazCZvNpra13AZyG8ltbzabhdVqFU6nU5UlOX+Z3xaLRTgcDrU909PTVRDgXd7k+6xZs9QBSc73nnvuMZRDt9strFar6Nevn1pHOe33338vXn/9dVVBybwaPXq0sFgswmazCYfDISIjI0VERITQNE2MGjVKzU+fhx6PR3g8HmE2m1X+yvnpy5vL5RItWrRQ20ufV3Ibp6eni379+qkKXZaZd999V+1LMtjR57cMhBo3biySk5OF1WpVv120aJEAIF577TUBQIwbN05tm6SkJGEymcQ111wjTCaTGDt2rLBareL6669X07jdbnWCExUVJWJiYoTZbBb9+vUTLVq0UAGk3DfkwV7TNPHTTz8Zgv1+/fqp/E1OThYWi0XtC3I/nDFjhmjUqJFo0KCBMJvNKi2PPfaYqje+//57YbFY1MnE2LFjhcViUXWNvmzKfVS+y/1TX0ZlXsmy/vjjj6u6Qb/NbTabiIqKEpGRkSI9PV0dlC0Wi3jsscdU2dSXOxnUREZGqgOs3H5yu44dO1btu1FRUWp/sVqt6qD64IMPqoO23F80TRPx8fEqUJgzZ45wOp1qOXfffbeql55++mkBQPz000/CarWK0NBQYbFYxLhx49R89XW3XJfExERD/shpZfocDocwm80iJSVF7TOapolhw4YJq9Wq9kubzSZatmwprrrqKhVwyPLw8MMPC5PJ5FM/paenqzLar18/w3FLplfWSfr9Qda9NptN/PTTT2o/tVqtwm63GwKVn376ScTGxqpAVq7jpEmT1PaXQefcuXOFw+FQ9cjll18uNE0TM2fOVEGiw+EQERERwul0CofDIa6//nqf+hSoCdbvvfde0aJFC/HTTz8Jh8Oh3ufMmSMaNWp02vFAQAZBDodDZGZmiqlTp4o2bdqIqVOnqsxs06aNGD9+vABqzmbat28vnE6n+mz8+PEiJCREDB48WBUSi8UiMjMz1WU6edWgZ8+e6reaponOnTsLq9Wq5mWz2UT79u1FVlaWCAkJEXa7XbRv395QoDMzM4XD4VA7s74ikvOR0+orKHmQlMuWVz680y8r1dTUVBVcNGvWTJhMJvHggw8aliej8aysLHU5XKbhkksuEQBEdna2sNvt6rc2m82QTpkWmR/yDGbw4MHqSpjVahXZ2dkqgJABWnBwsGjSpIlISEgQFotFjB49WjRt2lSdHTz44IPCZrOJdu3aqZ28Y8eOAoDo1auXsNlsIjQ0VDRo0EAdyOVZXGpqqkhJSRETJkxQwZzc6WW6R4wYISwWi0q/POsDIO68805ht9tFjx49hM1mE9nZ2cJkMqltY7PZRExMjPB4PCIiIsKwznIb9ezZU2iapi5hd+3aVV2tkPMfO3asyueuXbuq7SjPuPXbPDs7W7hcLtG5c2dhNpvFAw88oMqUDMIHDx4sQkJCRP/+/Q237WS6Zf6HhISIiy++WHzxxReqHGZnZ6vgTp7BxcXF+dyes1qthjyU+aE/0ZDz05e3lJQUYTKZVHATFBSk1q1fv37CZDIJj8cj7Ha7YX+Rt0Xl1SI5P5nfMg89Ho/IzMxUV0+ys7OFxWIRwcHBaj1GjRplCNDk1VmTySQWLlxoqKDltsjMzFTBtnfgK4PNkJAQw37Zrl07dSVl6tSponXr1uqKzuuvvy6AmitQZrNZNG3aVAWR+v1QfzI1ePBgYTKZ1IFGbr/k5GS1fWS69fOXV8BkGZf5LfOuf//+Aqi52iDLm6wvxo8fL9q0aaPSJLeJLFf6wE2ecM2cOVPY7XYxaNAgQ1mQ+5bc9rLO0jRNpKWlqQOv/uplZmamMJlMIiMjQ9VVFotFhIWFiYiICJGSkqLqUbPZLIKDg0VsbKyw2WwiLS1N7RNyGnkMiIuLE1OnThVpaWkq72TA4PF41FWr7t27C6fTKQYNGqSCQZk/DodDXemU+668uidPyvX1/uDBg9VvHA6HeOedd9R6ymm6dOliKN/9+/dXj0R478fjx48XTqdTratcF3193KxZM2GxWER0dLSYNWuWClRTU1NVeZN5OmvWLGGz2dQjA9nZ2SIkJETV9SkpKeoEzWKxqHpW0zRxyy23qDpE0zTRqVMn0bVrV8PjErJeksffZs2aqeOJDHruuOMO0aZNG/UuPz9dARkEZWRkiBtuuEEEBweL1NRUdSaWmpqqboPJAwtQc7laf9nW37M/ERERhsu5shCmpqYaLkH6e2ZHf8la/i93tiZNmhieF4mOjhY9evQQiYmJ6iAiC3TTpk0N0XrDhg1VBa+fd4sWLXzSHx8fb/itLLAhISGiadOmhjywWCx+n8/QNE00bNhQ3UKUzzHIeenzyHv5/l51TSN3IO/P/eWv/pkl75e8LdSzZ0/RvXt3AdTcrggKClIVdrt27dT6ysuz3rd6ZEClX67ValW3DOQOrr/d4+/ZLH/rL9c1IyNDfde2bVsxefJkn9sC8paV/F9/y0pfsevLaW5urioD8vdpaWmGeTdv3lwkJib6rHNdzybYbDbRpUsXkZycLJo3b64CCHlQkxVj8+bNDbedY2NjfW49AjW3eb2XLytN+bncV+TBwGQyiaioKBEWFuZzq9M7//W3jfTLCQoKEiEhIYb8kAcIectMv89MnDhRpKWlCZfLpQJfebLUo0cP0bhxY5Gamqpu15lMJnU1s65yr1+3qKgoERUV5Xeflfmif+5k1KhRonnz5oZ5629pAFABkswXeSvQuw7R55W+PGuaJiZMmCCaNWtm2DbyylVQUJC6VSnrG7PZLO644w6VVnlFR58uk8kk4uLiDLfq5IlKbc/A+SuL/p5tkVce/JU3edCVxwjvvPbeR/XrXNf+7HQ61VVb/fz0wYumacLhcIjU1FS1LeTy5TLkCV27du3Ufu59m0y//+vrQX+PUXi/5DparVYRHBysyn94eLhKr3594+Pj1bIjIiJEWlpanc+M6a/GyrpBv2zvuktuc3m7z2q1ioYNG4qQkBCxYsUKFQydroBsHbZw4UJcddVV6N69OwBgx44d+PXXXw1Pn9tsNvX0enV1Naqrq2EymQytgUJDQxEcHIzCwkKUlJQAgGq2WFsLBknOSzvRwsBsNqO6uhrHjx/3adGknWgJExYWhqNHjwKoeSL/+PHjfltLJCQk4Pjx49i3b5/h95pXixqr1QqbzYaysjKflg0WiwVVVVU+aUhLS0NeXh5KSkpO2kpLNhH11wpBrre+ZYDJZFItQeQ0Mu/l/CwWCyoqKnxaCuh/43A44HA4oGkaysvLUV5ejqqqKthsNmiaVmtrF9nE/tChQ4Z1B2ryOzIyEgUFBbUu22w2IyoqCna7HceOHcPRo0d98tvj8cBms2Hv3r21zkdPvx1kfunLgRQSEoLy8nKfsnCybQTU5Ht4eDhKSkp8WpW43W4IIfy2ZHM6naiurkZFRQViY2ORl5enWvD5Yzab4XA4fFrZyPVs0KABDhw4cNKyZTabVQu8iooKn+U5HA6UlZUhMjISx44dQ0VFhco72SorODhYlQuLxeLTUtLhcMDlcuHYsWM+eeIvbXJ/Dg0NVS0q61oHWdZra1FkMplUWdfP32azoaqqCsHBwbBYLDhy5IhaN2/aiVaFJpNJrWdt20afd3Kb+iP326qqKpUm2TJI3xL1VMqdpmv1JdPq3dpSzkfOy263w2w2q/pWTpeSkgKz2YxDhw6p5tWhoaGorq72W95OhXaiVaemaT6tAfUsFovaBjJ/TbrWqbL1nMlkQlFREYqLi9V6RUZG4vjx4ygpKfHJc6vVCqvValhX72OQ/nO73e5TVuV6CCHgdrsRFRXlc6zzx+TVutTpdCI2NhbV1dXYuXNnrfnlvc3NZjPCwsKQkJCAiooKbNq0CUBNi9CsrCwcOHAAu3fvxsGDB33KsNVqVc3jCwsLDfljtVoRExODhg0bolGjRli9ejW2bduGJUuWoFu3bnWum0+6AzEIAoCvvvoKs2fPNjTVDQ8PV8HPkSNHVKUDQFWQ3tMANRtU3yxd9lXhcDhgt9sRFBSkClFOTg6uv/56pKSkYMeOHZg7dy6+/vprn+bYTZo0wXvvvYdVq1bhwIEDdTYjN5lMsFqt6gAvp5U7sdlsVumPioqCy+WCw+FQO5fsq+LAgQP44YcfcODAAQghVEUthEB1dbUhWImOjkaPHj0wefJkZGdn47vvvsOCBQuwevVq/PzzzygpKVGF2mKxqPV3OBywWCyqyad3npzqtoqJiUFWVhb+8pe/oG/fvrBarX6nk/OfPHkycnJyDPP97LPPcM8992DNmjV+Kw+r1QohhM+Bw2QyITY2Fl27dsXkyZMhhMCMGTOwcuVKQ4UVFBSEpk2bIiwsDBs2bDBsR5mH3bp1w6hRo5CdnY2oqCi/6yFONA2WlazcFhaLBVarVXUbEBsbizZt2iA2NhaHDh3C0aNH1ec5OTm46qqr4HK58Nlnn6muFfbv3284cNlsNkRFRSEqKgqHDh3CwYMHDf2JhISEICgoCEIIlJWVoby8XB0g9GVLHoz0gZl3gKvvf8W7GtKvGwB4PB6kpqbCZrPh559/9tm+w4YNw6pVq/Dhhx9i27ZthvKn325ATcUcFxfnUy7k/ijnUVpaiuPHj0PTNHXCExISAqvVirCwMISGhuLAgQPYu3cv8vPzfbop8F62fl/Sfx4cHIyEhASEhobi6NGjqKiogM1mU+vWrl07LFy4EJ9//rmqW2RwY7FYEBwcjEaNGqFbt2644oorkJeXhyeeeAKrVq0ylEe5PHGia4jo6Gi43W5omqZObLz32eTkZHTu3BmTJ09WdRzw2z65fPlyQ7nWNA12ux1hYWGIiYlBZWUlSktLVX0iTyYLCwtRUFBgCNrNZjNCQ0PhdDpRXl6OoqIiCCEQEhKC0NBQVb8BQFhYGBo1aoTy8nIUFxfjwIEDqjxkZmZCCIFNmzap/SciIgLZ2dlqPSorK/Hdd9/hySefxA8//KCCybi4OJjNZuTn56s8kWkPCQlBeno6evbsiauvvhqff/65T92t38/0+aSvk2qrgzt27Ijo6GgsWrRIdW8i88tut6v9QW4nfYBo0jX1l+vRuHFjlJaW4ocfflCBub4c6Osw77pR+vjjj/Hpp59iz549Kv0mkwkHDhzA/v37sXfvXnWclCeRKSkpaNOmDSIjI9XxUK5j48aNsX79eixfvhxHjhxR5S00NBTdunXD2LFjDfux3AdNJhNiYmLQpk0buN1u7N692yff6zqG1CVggyAiAHjnnXdQUFCA0aNHn++k/Ck9/fTTOHjwIGbMmHG+k0IB6PeWP9YP587TTz+NL774An379j2v+csgqBZjxozB7t27kZiYiN27d2PZsmWGz5ctW1brNLm5udi2bRu6du1q+Fy/Q959993Iy8vD8ePHsXv3bphMJp/f6Jf19NNP49lnn0VERISa36mk33taf+nv2LEj8vLy8OKLLxrSf/vtt/tUILXNNzc3F19++SXi4uKwbdu2U0qvv2lkvuzatUvlx3vvvYewsDCkpaVh27ZtGD58eJ3p/eWXX9RvvLeBTL/Mb5vNhs2bN2Ps2LF48cUX66w06/pOplveFpLp37Ztm0/eeee39/dDhw7FrFmzIIRQ6df/Rq6vft7+to2/7eidBplOf9v6ZNtcrvOLL76Ipk2bYsuWLerMTi47NTUV27dvV2k9lTz0zhf9/PTzkXkkP/PeH+U29s4nf/Pz3mf97Y+SXNdff/0VlZWVSEpKUvNYtWoV2rVrd0r7aF327duH+++/HyUlJYb8vfrqq0+6bvr1uf3220+p3pDzv/POO2vdBkBNvr/++uto1KhRnXWX5K/s6MvAqQQptW0r/brLz2QdIb/r3bs3vvnmG59toq97ZPrlPtCqVSsV+GRkZGDr1q1+bzd6lzfv/Vpf18hy4b3d5DT79u3z2X9OVpa897m68tK73vNXbsaMGYPly5ejd+/eqh7zrs+8615/28h7P/Y+1sn16d27Nz7//HMcP37cJ39r2x/91afex9/TxSDIj7vvvhtLlixBmzZtEBcXh3379iEuLk4VCvl/bdO0bdtW3UbQf75z505s374dXbt2xUcffYSmTZuiY8eO2LdvH7Kzsw2/qa6uxvLly9GrVy/Mnz8fvXv3xpo1a3DZZZcZ0uL9/t///hdJSUlqvv6m9U5/dXW1oTANGTIEBw8exGeffYbt27ergn/8+HGVJu/5tm3bFu+//z7at2+Pe++915Be7/nLd03Tap1GpqG8vBzLli1Dv379EBUVhYMHD2Lbtm2q0N9999349NNP0bdvX0N65W+8t4Fcf5nf9957r6Gi7t27t5rHkiVL0LZtW7WOcvsNHz7ckM/6Hdxf+vXzkdtWX2l6b5tdu3Zh/fr1uOmmmwzlQf5Grq9Mu77i8lcOZb6kpaXh22+/NeR3Xdvau4zOnz8fubm5+Pbbb3H55Zcb1nnt2rW4/fbbMWbMGMM2uffeewH8VmHJba7/vXce6v+X66bfp+S2kHl07733+t1n5TaW5UWf3zJ9cn7e+6y//VHOY9WqVRg9ejQefPBBbNmyBT179sS2bdtw2223qQBBbgPvdfI+qOiDXFmmli1bhqZNm+Knn35Cz549Dfm7efNmn/TVVf4+++wztY/Nnz9f5VPbtm0NBza5TsuWLfO7r+r3WRlU1FZ36fc1uU12796tDmL6wETTNFU2ZX7IbS7Td9tttxnWVW6rzz//XAU+69atw0033VRrHSHLr3c5vOyyy1T65T4gT4x69uxpOLDqA5PExERDXagvI/KAPXz4cJU/slzo6x19mR08eDAKCgpU/g8ZMkT9Zv78+T7lYffu3bj55ptRUFCAzZs3q31C7lveQYt3vVdeXu5Th+mPH97bXZYnfb7m5uaqW46zZ8/2ma/3PGR50ZcFPX1d5m9/fO655xAREWFIryxv+vw/3WCIY4f5sWfPHkRGRmL+/PnqM7nz6KP8k03j/bn+akffvn0Nv/V29913qwAIAD755BOf+cmKT/9eWVmJ5ORkPPDAA36nrSv9d999N0wmEyZNmuQ3/R07dlRp8jdf/e/06ZXzjYuLM7z7W3ZdeeLPnj174HQ61cG2NrVtGwBYsGCBT7rHjBmD/fv3Y8eOHT5nMGPGjFH5vGfPnjp3PP18aisX3tvmZOuhX98GDRrAarUa5l/bus6ZMwddu3atM6/02zo6OtpQlgDgsssuw8GDB7Fjxw5DeTaZTBgzZgwA/9ukQYMGavuOGTMGO3bsQMeOHWEymXzyUJ+G2tbNO7/97bOSTJ9czvHjx1X66ioXtc1DCIExY8YgMzMTJSUl2LBhAw4ePIhJkyapfUC/Dt7L9g6S5feyTAHAyy+/jJKSEnTv3t0nf2vbXvp9y3sf1ueTLI/6A5tcJ7mMU9lna6Mv13KbzJkzBwcPHgRQs4/pAxMA6vvy8nK1zWX6vPNUbiv5m6ioKJ9yLdMPwFB+9eWwLjJ9epdddhnKy8uRnJyMuLg4Q/2sJ9OlT4+/7eGvzG7evFltP/1vZs6ciRdeeAFRUVFqW1x66aWGfJFX9723bW3HJO867MUXXzTk1clcdtllSE9PxzPPPGPYRjKQr61O15cFPX91mXd+7du3z5BePf02Px28EnQWnMmggb93oMGz6UzTX15eDrvdflbW4WQD1dY2bV2f6X3xxRdYtWqV2vnkw3Tt27f/3Wk/leX/nt+f6rzPdADb0+U9gKLT6cTChQvVQ/zy898zQO3JBnGV40Sd6m9ONjjxmQwmea724boGiz3ZYLynkpZTHQCzNue67jqVbeNdR3z55Zf44osvsG/fPphMJqSlpWHQoEGGh7nrSv8333zjt0HFmdQPZzJo9cny9Ey32ZluK/m7ESNG+P1e3r4qKirC8uXLa23lKAenXbRoETZv3oyysjIEBwejefPm+Mtf/oLOnTv7TecfeXwM6CDoxx9/xFNPPaUGxJQtFSwWi2rFJAduk83XZXNOOXBeRUWFofWL1WpFeHg4YmJiEB0djYMHD+Lw4cMoLCxEWVmZ3wFDZSsPOaipbBYul+PxeHDxxRdj8uTJyMzM9Em/987bpEkTADVnFb/++qsaPFC2KLBYLKrVWHFxsWqdY7VaERUVhWbNmsFkMiE/Px/5+flqvgkJCdixYwd++uknv03IZZ7o09uoUSM89dRTWLBgAXbt2oWysjLVjN1ms6GkpATFxcUnbf3mdDphs9nUCPNyOwDw27IoKCgIAFBSUuK3dZdsnhwcHIxu3bqhSZMm6NSpE/r164f333/f74jSnTt3xiuvvILly5dj48aNOHz4sOpeQKYnODhYPWdw8OBBVFZWqlYvzZs3R+vWrXHo0CGsXbsWP//8M8rKyvx2iSCbbctyp2kaXC4XmjdvjvDwcNU6Qjbz1g9aqN++cmBH764X5LbOycnB8OHD0bhxYzzzzDM+6926dWtERERg27Zt+P7777Fv3z6UlpbWmvdy8GC73a6uCHXv3h3p6emGPPSXvykpKZg/fz5WrlyJwsJC1cIyNjYWycnJOHToELZv347i4mKEh4dj/Pjx2LdvH5YtW4bDhw+r/dDlciEnJwfdu3fHihUr1Pxkyxm5L/gjW625XC5UVVX5DFzp8XgQFBSEPXv2qJZKmqYhJCQEPXr0wIMPPmjYR6XaKvWDBw/ixRdfxMqVKw35W1vaQkND0blzZ0yZMgVCCDz++OP46quvVDpl+bZarYiLizPUG3PnzlUDrurXST+Q7jXXXAO3242XX34ZCxYswJYtW1QrLn2TaX1eeTweuFwuHD9+XHXdEBUVhZiYGMTHx6OsrAx79uxBaWkpnE4nEhIS4PF4kJOTg6FDh8Jms/kMBi23FfDbIMgOhwNBQUEoKio6aZN1WYfGxcUhNDRULV+/D8iBP48fP47S0lKEh4cjPj4ewcHByM/Px65du5CVlYWWLVvi66+/xs6dO1X3GrKuDw4Oht1uR1lZGY4dO1Zr1yhWqxUmk+mkA0Z7l6VHHnkEK1euxNatWw3bLDw8HI0aNUJaWprafxo3bowZM2bghx9+UFcWZVpluRkyZAi++OILfPjhhzh8+DCqq6thsVhUuSwpKfEZxNdisSAiIgIulwtFRUU4fPiwoewLIZCenq66WyksLERxcTGqqqoMzdrl9qusrDQMzC1bvMll6fdPh8MBj8cDIYSqT4Ga7kySkpLQs2dP3HjjjX73uVN2Op0K/Zn8+9//Vp22Ab8NsaDvtMlfh2AA/A5+l5ycLBo3bnzSge30nbvpx5DSTyM76ZLp0n8nu7f37oBRDnmg7/RLzsO7Qyx/HViFhISoISD0n5vNZtVrq34dGjRooOavT0tdnW/JtNf2vXeHd6fSoaJ+2XJoAe9pZEdpct1kGvWdh3lvN6vVKoKCgvyOp6VPW2hoqOp0zt92jI2NFQkJCbV26ubd2Z+/ZfjriE1fRvTr7K/TN7nOcj6yUz1/5UB2qtaqVStDp5r6jtr0aZWdBgIQcXFxqrt+73XyXj+73S7CwsJEWFiYzzbz7oxTv96yQ0rvsiu76JfDuuiXqx9qxbt86we4lMv0N7hjbXkaFhYmwsPDfQZ8lUMH1DVgsH57uN1ulVbvdZODvOoHX64tPdHR0X7zyN/y3W63iIyMPGmHg/6WJztP9f6td0eT+vJWW93ob7+RZbm2OlIuy7s8AjX7texhWP95XQMi619BQUGiZcuWasgdf8utLc/k/GVHmN6dAAI1HQn6+zwmJkb06NHDZwBRua+7XC5VzuS77MjQe15hYWGiZcuWolGjRrWWwdDQUJGYmFhrnS33Ge96QtaJskfs2ubtb76tWrUSN910kxrD0HtZsid1f9tcdpSYkJBg2J81TRMDBw4UGzduPKNYICCDoG+++UaYzWY16nVOTo4YNWqU4aAuB1LU9yLbv39/QyF0OBzC6XSK9PR0Q0GWgwTqe0wNCwsTHo9H9bQpB8wLDQ0VHo9HDbipP2Da7XahaZrfoEu/Q3p/5na7Vc+ssjCZzWbRq1cvwwHV7XarsZf0v5e9k/qreBwOh2GARofDIZ544glDb8iye3X9S/bMLH/ncrlEfHy8YYC+Bg0aiM6dO4uQkBDRuXNn0bBhQ/GXv/xF/c7lcqkdT9M0ERYWJsxms8jJyVE90GqapvLS6XSq+dvtdvHNN9+onnxvvvlmn8DFXyCj/867Ag0ODhYul8tQCcn88e5RW6ZNVtyybMn1ad68uWjTpo0a2NJkMonQ0FA1LIg+HXKMI/1niYmJhpHUGzRooIaEkJWGpmlqCA1/By+ZHv3gqg0aNFA9VYeGhhp6cdWfJOgHb5UV5Mny0/szf5W1HB7FO71yn9DPR54cyBMbfwdXuQ3ktGazWYwfP16NrSTLruzN2N9BPSUlxaf33pCQkFM6wOr3WX2PvPK7sLAw0a9fP7UN5HrKd++gQJ/HmZmZasy5ugJQTdPUeurTrB/ew3sbWK1W0ahRI9G4cWM15ps+aPRXDzkcDhEWFmYIiv0NrixfMtiTdZhcN1nm5D6Rnp7uc2Bu0KCBiI6OFllZWYZ9TgZD+h7K27Vrp8oIANG5c2cRFRWlemf2V84aNWqkjg9y/5NjickDvjwBMJlM4uWXX1Z1l8zT0NBQQ/qAmoFivXvr995e+ryVf+tPPvzluz7Iqi2wkPMwnRiaJjc3VwXSvXv3VgNr2+12tZ4yeNGnA/jtBEKOL6kvO506dRJNmjRRY1vqy5vcri6XS+VTZGSkyg+Xy2XoSVsue8KECaJ///4iPj5edO/eXfXwv3Tp0tOOBwIyCOrQoYMwm81i06ZNasywDh06iGuvvVY4HA4xbNgwtVHl2CvDhg0TISEhYtiwYep/GaHL0dDNJwY7lQcE/W81TRPvvPOOAOAzQKv+jEeOA9OmTRs1yF6HDh3E0KFDVYHLysoSmlYz2F5wcLDIyMhQ70DNKO5y5OErrrhCTRsUFKQqe3365dg1cogHmQa5zIyMDHXwSElJMYzArZ+vnKZly5biuuuuU4VWP9Crpv02YJ/MDzmNpmmGcdAcDodaDznooL6i3rRpkxrIUaZXn+82m00Fg8OGDRMdO3ZU85DzlSN2m81m4XQ6xZtvvqnOcIOCglS+6tMry4AcDNJisYgrrrjCsGyZhxkZGWqsJHlFQm5ruQ3ku37cJLm+sizpy11QUJAKZOT2bNmypRqgUD8/ACrd99xzj88go/L377zzjnA4HKJTp07CZrOJhIQEAdQMbigPmNOmTRNTp05V20yOnzRixAh1tc3pdIqIiAg1gOqVV14prFaraNOmjdA0Tbz99tsCgAr8LRaLyl99nslA0uVyiY4dO6oK/+qrr1bpkhV0o0aNDKNMy6tC+n1Jn8/yXQY6rVq1UoMIy3IhBwV99tlnhab9Ngir3L80TRPNmzcXISEhol+/fsJut6v5yko9JSVFxMTEqDy0WCwiKytLdOzYUS1HP6yOrBNyc3MNgUObNm1U/sp0ynGb5H4oBwiWA6jKtNx9990q3Rs2bBBms1lERESIoKAgNeisHM1bXw+lpKQY9tX+/fsLk8mkxrCS+7m+rMsBqGWaRowYoZYdGhoqoqKiRG5urggPD1f5L4OCCRMmCLvdrrZvq1at1OCz/sq13CbypEJeAZRBlgzCP/74Y5W3TqdT3HDDDWqkc3kgf/nllw11jQxe9AGMHJdKzks/OKz3YNtyMFs5P319JLefzKcmTZoIh8OhjjeNGzcWVqtV9OrVS6UhMTFR9OjRQ514y+3VpUsXAfx2NXP48OGq/Ddo0EA4nU41LqWsP2S5ASBiY2OFpmlqoF59Or/88kthsVjEXXfdZRgHT27zH3/8UTRo0ECEh4cLh8NhONbJsipPDBYsWKDqFqAm6NQ0TXTt2lWVDbvdLho2bCiAmsBTpldfn8r9/tprrxUdO3b0GUBVDqx6uk7/Ueo/gfXr1yM5ORnvv/8+UlJSsGTJEqxfvx633norUlJSkJqaipKSElitVsybNw82mw2pqakoKipCSkqK6jlXnOiKfOPGjUhKSkJERAQ2bdqEX375BVarFf/617/UbwHgpZdegtlsRkhIiBqSY968eUhOTobZbFbLA4D77rsPZWVlSExMxPr169GrVy91f/f+++8HAKSmpqK4uBizZs1S7wCwbds2bNy4EVarFWlpaQCArKwslJSUIDQ01JD+6OhobNq0CTExMep+/iOPPAIAaplyvmFhYdi5cydSUlIQEREBIYTKK/mcTpMmTbBlyxa0atVKPdsSEhKCsrIy3HXXXQCAxMRElR/yeSh5j/+pp56C2WzGU089hczMTGzcuFEN62A2m5GYmIiIiAiYzWa8+OKLSE5OxpYtW1R6zWYz5s2bp7prl/eKbTYbvvvuO9hsNkRHR2PDhg0AgLVr10IIgZiYGISFhWHdunXq2YfKykpDvn766acwm83IysqCpmnYtm0bCgoKUFVVhTZt2sBiseBf//qXSj8AzJo1C1VVVTh69Cjcbjfcbrd63iwkJERtRwD417/+BaCmlQQAZGZm4pdffoGmacjKyoLFYlH53aRJEzRr1kw9a7Jp0ybs2bMHVqtVze+pp56C0+lU+Sy7rk9MTFTNU+XD7e+88w7Cw8OxcuVKVFRUqHv5smdYAJg9ezZeeeUVADXPAsyZMwdutxtLlixBRUUFGjduDJfLhcLCQhw5cgRCCCxduhRCCNx3330AgOXLlwMAjh49iqNHj6Kqqkrlrz7PqqurkZ2djWPHjuG7775Tzwhcf/31AKD2hcjISPz6668q78xms+rt/W9/+5valwAY8lsIgfDwcCQnJ2Pjxo345Zdf0KRJE2zcuBF2ux133nknNE1TQwTcdNNNqv7YsmULNE3D//3f/6GoqEh1ZRAaGgohBJKSklBWVoa9e/fi6NGjKCgoUOXk/vvvx7p167Bx40YAQEREBKqrqxEWFqbyvKCgAKGhoWp5f//731FRUYHWrVvjl19+QVJSEsLDwxEeHq72w5CQEGzdulUNPyB/n5CQACEE7HY7Hn74YcTGxqKgoAAlJSW46aabUFFRgb///e8AgNatW8PhcAAA+vTpY8izqKgoaJqGd955R+0vP/74I6xWq6ovKioqDHXDkCFDVG/G8lmRNWvWoKioCGFhYaisrMSECRNgMpmwYMEClJeX47rrrgMAbNiwAUePHkVhYSF+/fVXOBwOlRa5XW+66Sa1bnl5eWjatCm2bt2qnssUQuC9995TvXKHhYWhZcuWqK6uxt69e+FwOBAWFoYbb7wR8fHxqh7p2rWrynv5AP4jjzyC6OhotZ5y2W63Gx6PByaTSdX3e/bswa+//qrq4EceeQQ2mw0Oh0OVs2bNmqltlpSUhIsvvlhtr8rKStU7OgDs378fc+fORUREBMrKynDffffBarVi/fr10DQN8+fPh6Zp6jnII0eO4NChQ6iursb999+vjls2mw0mkwnx8fHQNA2HDh1S+wwAPPzww+r5xQYNGqCqqgphYWGIjY1FeHg4wsLCsGnTJpjNZqxevRoHDx5EcXExYmNj8dRTT8FutyM1NRUVFRXweDwYPXo0qqurMXHiRDidTqxduxaapuGqq66CEAJff/01AKCsrAypqanYsWMHAKC0tFQdp7744gtomoZHHnkEmqahoKAAt956K9atW4clS5YgOTlZvY8YMUI9O3Vafs8VlfoqJSVFTJo0SVgsFtG2bVt1ObBLly5qEE3gt0HmvG/vtGrVyu8lcv108r68HLTQ+2wP+O1SuvczJfJWHQDRqVMndeYP1NxWGjFihIiKilJnXDk5OcJkMqmR0uX85Rm1/pK+pmmiY8eO6n+ZroyMDHUrR6bNZrOJoKAg0atXL8Ml1dDQUJ/71vKVk5OjzgDk7TK5bk2aNFEjKZ/KrQN/l4jlfOVn3n/rL5vK7+oaQDUuLk5omiYuueQScdFFF6k0h4aGCqfTKcxms7j88svVZXHvQSb1y9ePsiy3q/7WqD7t8vaTv1sV8m955inzSz+4b25urpg+fbrPJXGPx2OYh3eacOJMUc7XYrGIPn36qLNQOQCjvCIkf9OuXTsRGRmp9gn9sw+1bUuTySRyc3NFYmKi6Nu3r/qtxWJRt6JNJpO4+OKLVf6azWbRvHlzNXhtXfljMpmE0+kUdrtdXQ2UV4/k7SR59UTeSvX+vb6Med96kq/Q0FCfWxbmEwMWA1D7gpz3jTfeKJKTk4XL5RIej0dER0er/XXEiBEiOTlZREdHi/DwcFUu5NWqusqxXI48+3Y6nYZBm+WArjJ9wcHBatsMHz5cjZgup5dX62TZGDJkiM8zi/orZvo8kWVTvss65tZbb1W3+vW3y6xWq3C5XOpWnRy13eFwiDFjxqh0tm7d2rDe8iUHg9ZvOzk/73LXpk0b0aJFC8Nnssx5l9W4uDi/A8TqlyNvUetv6df2LIx3eryfFZP7pH5flts7ODjYcJtXf9u8bdu26na3vK0XFRUlHA6HCA8P97tcu92uBmrVNE1dMfJXf3rvY0lJSer/6OhoQxmQV3Dl9pPz1d/qTEpKEt27d69zQFmZzoyMDL+DG+fm5hrSJ9epc+fOKj3Z2dnCZrOJN954Q8yaNUs0adLktOOBgAyCnnrqKWG328UVV1whunTp4veA7q9weL/kJb9TfZCyrtepBAX6kYflJUx/D7fGxMQYHvg82Tr4+7y2g09CQkKdzyjpXx6P55Qe0jyd16k+3Cgv3+rX42TbxWaziQYNGvidv3y2xvtZH+9tGB4eLmJjY2vNI4/HI5KTk+scXbmu9AEwPM+g345nUu7kujVo0MDwHJm+zPl7xgv4bQRufZrqevDdbDYbnjfyXreWLVuqZxlOti6JiYni4YcfFs8++6xIS0sz/EYeaBs1aqQCYP2DpDK/TpbX+lHvvfPEez3lAUUfhNa2DnJ+8sTCX57VVsblc4JJSUkiLS1N3ZqqbT00TVPL8bd9vac9Wb7Ulld1nWjU9pInAfL5LP0+4x2s6pflbx90uVwiIiLCEJz4C95O5yVP3PTPgNW1LnWV++DgYFVn67+T+5C/38vjkr7er2s5cvra6p74+HjRvn37OuuwuvIiLi5OPTJxOnVNUFCQ2hdlcN+1a1cxe/Zs0a1bN5Genu63QVJQUJAICgoSDofDb7l0u90iJydH3HLLLWLQoEEqGDpdAdtE/j//+Q8ef/xxrFmzRl1q1zQNTqdTNVuWWaN5DfyonwaouZwoB26TneuJE5frZXNNk8kEj8eDTp064dZbb0VOTk6tA362aNECcXFxWLlyJTZt2lRnk0p9umrblN7p149oLJcZGRmJo0ePYufOnae0PLPZjOzsbEyZMgXZ2dn43//+h//+979Yv369anrpnYaQkBA18rhsBuvxeNC2bVvcfvvthsvQUmVlJV544QU899xz+P7779W2MplMaNKkCUaMGIGRI0ciNTXV7zY1m81o27YtpkyZgmHDhqGyslL1FfT666/jsccew6+//nrS9fVmMpnQsmVL/OUvf4HZbMajjz6KX375xWedZZNqf/lqNpvRvHlzDB06VPX4nJqaildffRWPPfaYWl99OfS3jeX2NZvNSE9PR2RkJIqKilBQUKBGrm/VqhVGjx6NrKwszJ07F88++2ytZctutyM9PR1CCGzevNlveZbL0zcJNplMcLvdMJlM6pbU761e5DqbzWbExsbCarXi119/9dm+AwYMwMaNG/G///0Phw8frnO52omuJ/TlAvhtsMva5uF2uxEfH6+WLYRAYWGh3xGwT4fNZkOjRo0QGRmJbdu2GfpaysnJQbNmzbBkyRJ8++23fpdjOjEYb3Z2NgYNGoT8/Hy88MILtY72rf+dbNouByuV+RMWFoZOnTphwIABSEhIwHvvvQen04l//vOfAH6rP1evXu23DDkcDjU4a2lpqWqebjoxgGtISAhKS0t9mrrL7+V2l3/LWz1yWU6nEzExMYZtIPPMezBrcWIA1ebNm+OGG27AkCFDsG3bNrz33nt4+eWXsX37dhw7dgxCCDidTnTo0AEAfAY9luX/8ssvx+WXX44VK1Zg7dq1OHTokGGgYv1Anv7qJP1+UlhYaNjWvXr1wrJly7Bs2TJVDvTLlt1g1EWW75SUFJSWlmLv3r21DurbqlUrXHfddRg3bhwAqHyMiooCADUw9g8//KC6SzGZTCgoKMCBAwcM3Y9oJwb1jY2NRdOmTREdHW0YeFUIAZvNhuuvvx6vvPKKTz0dFxeHY8eOoU+fPn73QbPZjCZNmsDtdhvmW9cg2aciYIMgqbKyEtu2bcP+/fvVyNUOhwNWq1V9D9TctywtLTVMo2ka9u3bpzoOtFgsSExMRFBQEFwulxoVHKh59kIWnJ9//tkwWnNaWhpcLpfqHyQ2NhYAkJeXh8rKSlitVjidTr/pt1qtsFqtOHTokM+0paWlPukPDw+Hx+OB2+2G2WzGxo0bVWGKi4tDo0aNVJ8j/uZbVVWFrVu3YsuWLSgsLERERATat2+v+nGR6ffXmZe/Dr+Ki4vx448/qr6U9u7dC6vVirKyMjidTiQlJSEmJgYZGRkwm8348ssvceDAAbhcLiQmJsLj8ahO+ux2O9xut9oGMg9++OEHfPzxx/jll19QVFQEu92uRlC+5pprEBYWhn379uHw4cMIDQ1VeSorAlkxuN1ulTdyuqqqKpV+2YlfRESE2gby+YSgoCBDPyJy22iahiNHjqC4uBjFxcWqPHg8HthsNnz77beG9ZXbp7CwEPv370d4eDisVqtPefPOb9lXyuHDh/1ua/lb720UFBSk1j80NBSHDh3CunXr1DQRERHYvXs3PvjgA2zbtg2FhYWwWCyqYrruuuvg8XjUMvT5KZ9bkX2GuN1uHDp0CJs3b1bPOjkcDqSnpyMuLk6t2/PPP4+uXbuqddY0rdZyXFpaii1btuDIkSMICgpSQfjx48dRXl6u+mKSgaTM/8TERBQWFuJ///sfDhw4gJCQECQkJKB9+/Zq/5R5VVJSYtjn5TrKbS3Lkr5O0R9s9HVEXl6eyt/S0lLYbDa0bNkSLVq0QFBQEKZNm4ZrrrkGTZo0UeVPv+4hISFwu92wWq2IjIxESUkJDh8+jIiICMTFxam0VVVVYcOGDdi5cyeSk5Nx8cUXq2dDvNVVd8l9zel0qmfBwsPDkZiYeEod+unzIiwsDFu2bEFeXh6qqqpgtVrVtrJYLIiLi0PTpk191ru8vBzfffcdtm/frsZzS0xMxBVXXIHBgwerbfXrr7+q9AcHB6v5FRQUqL6avPuuuuaaaxAdHX3SDg718y8sLERJSQnKysoQFxcHt9uNqKgo2O12/Pzzz9i1axeqq6vhdDpVH0sFBQU4fPiwOlGW5QioOQ6sWrVKDY8SFBSErKwspKenG/bf6upq7NixA0IIlJWVYefOnTh+/Djsdrvaj6Kionx+I9cBAD766CO0b98eYWFhAGo6Q7Rarep7fb5XVVXB4XAgKSkJcXFx6pktWV6OHDmCn3/+Gf/+979VX17V1dWwWq2IiYnB4MGDMWbMGNVTuMViQXR0NKqrq9WxJCoqCtHR0aq+lEFzaGjoGXX06U9AB0HPP/88HnvsMfz000+/+4zVm91uh9lsRlVVlU/nU2ciNTUVd9xxB8aOHas+mzNnDubMmaMeKJPL8Hg80DQN+/fv9+ng7GTkFRuTyaQOTnIe4eHhOHbsmE/ng/7Ex8dj7NixaNmyJR566CFs2LDB0HHWhcTlciElJQXt2rVDv3798NFHH2HVqlXqzCcyMhLNmjVDixYtsHz5cnz99dcoLi6udX4mk8nv2bHT6URqaiqOHTuG3bt3n1Ya5Zmx3W5XBxz9MpKSkpCWloajR4/il19+QUlJyUmvTmiahujoaPTr1w92ux0ffPAB9uzZA+C3shQTE4OQkBDs379fnbUCUJ17evfcC9Rc2XC73SgqKkJpaSnCwsLQoEEDtGjRAs2aNcPy5cuxZs0aNb/Q0FBkZWUhJCQEK1asUFcoZRpMJhOCgoJUJ4mHDx9Gr169cM8992DZsmWYM2eOT6eGISEhyMzMVJ39nen+ZzKZfIK3du3aqTGb9PONiorCgw8+iPHjx6t80QfJ+iDX4XCgtLQUq1evxuuvv45vvvnG0OGhP+np6fjll1+wZMkSREZGYvbs2XjnnXfUfupN0zSkpKTg5ptvxldffYXmzZujQ4cOWL16NWbOnKk6qJPTtmnTBuPGjUNycjKeeuopfPnll7XO25vNZlNBn8yT4OBghIaGoqqqSu0vcsiSyMhING3aFOPHj0f37t1x++23Y+HChapj19rIq0IyiD3ZdjWdGEbhZFe3TSYTIiIi0KRJE2RlZeHYsWP4+OOPceTIEQQHB6urPadylfxsCA8PR9++ffHjjz/ihx9+UOmrqqpSjQ7k1ba4uDjk5OTAarXirbfeqvXKttPpxOjRo9GzZ0/Mnz8fX3zxhaEek/WWpmk+6yoD+SNHjtSa7/pOKr1pmob4+Hg0bdoUJSUl2LJli9+hM/yprT4FgLS0NNxyyy2Ghgun7bRvoP1J/OUvf/Hp30Lf3LGul7/7slFRUerBtbpe+mc3ans+QjZX1z9QfTZf/u7nOhwOtcxTmYfMJ03T1MPCZ7psuc4yP2TzbLfbXesDxHJe8pkj+RyIv/vh8pmDjIwM9QCn2WwW8fHxJ32e4mTloHXr1qprAn+vyMhIkZCQUOty5MPX8hkufw/Ens6rtuXon1ORz4bUNf8zKXf++h86Wf6d6XNM+ldMTIy46qqrVFP7U/2dpmmiWbNmwmKxCLvdrpoM+5tWPhMin/nRdzJX20Oyp5t3v3dfdzgconPnzqJ9+/anlA+mE52s1pU/+r/108pGF6ea3263WyQmJv7ufDrVcuWvM0L5PNWpdA55smcq5UPn/tbfbDaL9u3bC5vNpp6h8U5fbf0qXXTRRX6f+ZO/8/4sJCTE7zN78mHyk9XpdX3n3Z/VyV6nUhbMZrO46KKL/PbJBNQ0MKrrucHk5GQRGRnpsyyPxyOef/75M4oFAjIIeumllwRQ0/IqMjJS3HXXXWLKlCmGztFkHw/6B8H69u1r6CBOts7o2bOn2hhZWVmqtY08mMsO3GT/H3a7XTRr1kwAENnZ2SI6OlpNe/nll6vKRrbikS1f9IVRFgK5s3pXULJVEvBbR33dunUztDgICwsTwcHB4qKLLjLMMyMjQz1UrO+vRK6TrERkfl155ZWq3wsAon379oYWaWazWVWAslVBUFCQGDhwoKEzw5CQEDFp0iRhtVrFxIkThcfjETfccINah6ioKDWdpmmiR48eAqjp60e2/NA0TbUqkK3q5Hq8/PLLIikpSbhcLnHbbbf57Liyczd9BaXvBMy7QklLS/PpTK9Zs2bCZDKpvqP020sebPWdv8l+e2JiYsTYsWPVw42ygzK5jvr5yLKjfyUlJRkq95CQEPHAAw8Ij8cjLr30UpXnsvWNvmNFWfnIBzf169O0aVPRvn179Rt9xS/nYbVaVSCo7+1b9uGirwD1HRl6P/wqWwx5V7x9+/Y1tKYBjCcQcj6y1YxsGRQTE+NTfuVJiL6/lEmTJonx48er/VfuA8HBwWLEiBE+D8XKecl5/9///Z/fg4D3suUrJiZGPexpMpnUNpf1xKxZswzlAIDPQd1isah9Sra+kq1DZd7KMifTr2+kIH8ry3dUVJThJEL+Xna+KFsODh06VAXRskPZxMRE1ZpUbj+5TLl/6Le3Pj/kvuZ0Og29PDdr1kz1CSb7CZIPeU+ePNmn93TZ90zfvn0NB82xY8eqkyWPxyOsVqtISkoSDRo0UMu67bbbREREhJg4caJqsSjnITsMnD17tiq7sr8e2UGfDGpkK7eMjAwxfvx4VXfJVoRut1sdG+R6d+rUScTGxvq0XJMt0vStcvXrGxoaKgYMGGD4XG7LSy+91NDbdWJiopqHDAT1+S//l/0OaZomLrroItGpUydD6z99IyDZKtHhcIjY2FhVnrQTDRLkupjNZnHXXXeph/j1y5atCGUDI30Zlyc0N954o2F5ch5PPPGEmDVrloiNjRXTp09XHbk+8sgjpx0PBGQQJHsc/fHHH4XD4RA//vijSE9PF0899ZRwOByGpsfvvvuuACCmT58urFaruOeeewQA1QmZ3EmtVqvawWSPmYsXL1a/1bTfOtubNWuWKiTvvvuuauYr/9c0TYwdO1ZVbunp6WL69OmqgIwbN05omqbSNGzYMPUO1HSCJSsOuewZM2YIi8UiZs2a5Tf9FotFBVSLFi1S89c0Y+dykZGRwul0qsBK5tXDDz+s5peUlCQef/xxld5Zs2YJs9ksJk+eLACIxx57zJAfANTv5WfvvPOOCA4OVush80ifV99//72wWq3qDF7mkdxmTqdTHahlB2Z2u12lEYAYNWqUOljLTr9kABUaGqryVdM0Q2do8mAmewGXy5YdCMpO5YYNG6au9Mhly/TLbSDzWXbQJ4dbCA4OVmVJzl/mtzzYPfPMMwKoCYJk0CwDeNnZpszT5557TjULly1OHn74YZVu2dzWbDaLsWPHqrIk07B69Wrx+uuvq7Ir13HUqFHqpMDhcIiIiAgRFhamvrNarWp+Mg+joqJEVFSUMJlMhs5E9eVt2rRpqrsIWck++OCDAoB45ZVX1P/eZ/ayqfgbb7yh9iVN03zyW5Zjuc/qD7ivvfaaMJlM6gCmvzKg7x4AgPjhhx/UNpABQGhoqIiLixNhYWGqU02TySTGjRsnGjVqpDqGk+VTBo3yoKnvxf3KK680tJ6SAa0s/5qmiVmzZonExEQRGxsrTCaTmDZtmtA0TTz33HNqPq+//roKvMxms7j77rtVmkwnemP2zstZs2YJTdPEggULDOXbYrGovJL1xTPPPKPyFKjpwVofNMh5ywO7HJoGqGkabzKZxJNPPilsNptITEwU4eHhamgPAOIf//iH0DRNbVfZqaE8oTOZTOqkVabho48+Ugd/h8Oh6p7o6GgVANx3332Gk0F983q5DrKzSPn5k08+aQi29Hnz+uuvi7i4OEP+yDTIchYUFKQ6eZR1mqZpqo6cM2eOKhfh4eHi7rvvVsuT21ae0MiTKrn89u3bi6SkJKFpmhg3bpzhuCWDWn1v+n/9618FAPHVV1+pZaxbt07ExMSoANfpdIqgoCCVvz/99JOqp0wmk6pPpk+fruoY2YP2gw8+aOgq5corrzTsP3L94+LixJgxYwQA1SGkLN8yDyMjI8XkyZNFr169xMaNG4XT6VTvr7/+ukhMTDzteCAggyC73S6ys7PF6NGjRZcuXVS3/D/99JPo2rWrGDRokNpZ5TALgwcPFgDE4MGDRUREhOr9UlZu2dnZ6sqAPKNr1qyZ+q3JZBKNGzcWDodDzd/pdIq0tDTRsWNH1UeEjJjlgSs7O1vY7XbVU6+maWLJkiVC0zSVJu9eimW/MiEhIWLw4MFC0zR1pjto0CBD+mWaMzMz1Y4oh7O488471cFfVjRATV9AslmyTIM8Y+rWrZtwOBzi9ttvV5fb5frqAzyZH/JqiOzrKCUlRTgcDpGamqoqHovFIiIjI0VQUJBo2rSpSEhIEFarVVx00UXqCoFMr9PpNAR18sw+MzNTBRb62x7yTC4zM1NkZGSIQYMG+VwpkPnao0cPYbfbxfjx41U+ywpw/PjxapvL9JtMJrVtrFar8Hg8wuPxiIiICNXfhdyO8gqPpv12e1F2Yy+3n+ydGIDo3r27MJlM4rPPPjNcddFv8z59+oiwsDDVC+2UKVNUmZJXRGQXEdnZ2aJx48bqQCUDMnm1LyIiQmRlZYk33nhDlcOUlBRDz7uZmZmGoVDkelutVjW/Hj16qPyVy5LlS/ZSLPN76tSpPuPWffnllwKo6ek6ODhYXHzxxcLhcIgXXnhBAFAHN5vNpnqOXrx4sTCZTCq/ZR5GRUWpg6/JZBLdunVT3Ry4XC6haTW3FGQwB8DQL48sHzIIkldasrOzhdPpVOsox5fTB5vyf1k+5QFTBrETJkxQ/8v59u/fX+Vz//79xcUXX6x+N2jQIMN8u3TpIsxms9rmKSkpIiEhQSQnJ6uy//e//10AEA888IAKtiIiItSBR9M0MWjQIGEymUTXrl1VPScDNZPJJIKDg9Vt5UsuuUR069ZN1SkycE1NTVX9GsmgKDU1VQQFBYlbbrlF2O12tY4xMTHq4Cl7sJa3WV955RVhMpnUdl20aJFPf10yKJD100UXXaS2aXp6upg6daoq18HBwWo/lWUPgOpNXT/fPn36GK5iPvXUU6rekScdsj+qnJwcdbtM5o/T6VSfdevWTfTv319d+cjKylJBiTyBa9Wqlcovq9Uq/v3vf6v96ssvv1TrIAM/TdNUuZP7nD4wkvV0UFCQGqpD5p28avTQQw+p9fvqq6/UlfRmzZqJrl27Gh4fueGGG1TfWfJz/XGyadOm4rHHHlPz03ehcMkll6i/AagTAqDmKhYA0bNnT+F2u9WdA1mv2O12sWHDBhEZGSlGjx4tunbtKkaPHi26deumgqHTFZBBUJs2bcSYMWNEbGysGj9LXjLVP9fjfQldfubvPq++ApI7h4xcT+Weam3TyO72ZeURExMjmjVrpi7XA1Bn79HR0YbLxLGxsT79K2iasSMs+dJfjtWnRY5tpq/8ZZ74Wwf9uC9yJ9Lf8vLXn4j35d5TeZ3Ob+p6BkCeobRp08bQyZscP81ms4mkpCSVbhn0+ttm/sbj0j+jJJ//Odk2r+2l327ynnpaWprKb5PJpAa2lUFabdtJnyZ5uys0NNQwLpv+NlBycrLPGHMnK8Py9ltKSoqIjY1Vlb68qiE71YyJiVHBqPyd9xhZcj3kbWOLxSLmzZungmDZ10pqaqrPOFtycGF/HbLVti767+QB03saeVCUaZKvsWPHirS0NBEaGipat26tbqXKsaxatGihhtWQZ9L6MbZOlr89e/YU27ZtUx2x+ptWXi2Uvxs7dqy6Ilvb/OXQE3KeMjg8WVnV142DBw9Wt3K8b7vo68fmzZur56v+9re/qbyUgYJ+efKKuHcHjVar1W++NWjQQMTGxp5yHaAfE8+7DNTVt5IM5k9nH9aXf3/lTZ9nISEhhmcv5TT6bSg73ZR5cCrz1ZeR2p6Dk4NHAxC9e/cWXbt29XsbTf+Zvq6RHc7WVd7kNmnevLno0KGDTyCrH2dNXyblMVoOwhwXFyfWrVungqHTFZCtw5YvX46BAwciOTkZsbGxOHToEHbs2GFoneFyuXDs2DGYzWb1xLvNZjO0cIqNjUVoaCgOHjyII0eOAKhplaJpmk+rCpNXK4WQkBCUlJSoFj82mw3V1dWGIQv0vxUn+ljwbo1j8vPkfIMGDXD8+HHVpFM70bLIarUa+nUJCQmB1WpFcXGxzzK9p5XLSkpKUt0CmM1mHD9+XL3raSdaGIhaWqdZLBbYbDbVygOoab1gsVgMrROqq6tRXFyshsGwWCwoLy9HUVGRaqWmneifQqbF7XarJvJlZWUoKChAZWUloqKiVB4WFxf79FFisVgQHByMY8eO+eSp6UTX+3W1ujKbzaopbFFRkWrFoc9T2SQ6Ly/PJ89lE+Xjx49D0zRYrVbYbDbVYkbmZ3h4uCpvcv1btGiBgoICQ98w/raB7GvEe1s5nU5UVFT4fBcZGQkAqsmqntVqVXmenJzs00cWAMP6m0wmn76F9N+5XC7DdpUcDgcqKioM2+SKK65A27ZtkZeXh//+97/Yu3ev2ldl2ZXv+ryT+3BkZCQKCwtRWVmJ8PBwAFCtyOR0ZrNZ9XOjnWhJd+zYMbz55pv48MMP8eSTT/qUBf1+Y7fb/bae0+e7yWSCpmlqnR0Oh6oLZOut6upqBAUFqb7JZDmRv5Pr5m/+soXqqfJXPiSTyQSn06n6GJN1j81mQ1BQEAoLCw194VRXV9c5P7PZDCGEWqfg4GBDC0SbzQZN0wx5aLfbYbVaVQtCoCbPY2NjVXNuOcxLREQEgJpm3vp9Tb9cf+svy7Bcvtw35PbQl21/9aSmaXA4HDCZTCgpKYHD4UB0dDSsVitKSkpU30VATavOyspKFBYW1tniVJ+ndZFlwd+0VqsVwcHBKC4uVt1zWCwWVFZWIiIiAgUFBTh+/DgaNGgATdNw/Phx5Ofnq+0o+8eT66s/pvk7BshlRkREIDIyEj/++KPKu8aNG6Nfv35Yvnw5wsLC1DHYX2vEqKgoFBYWqnIk865hw4aqC4KVK1fCZrPho48+QvPmzevMI588C8QgCKjp1HDu3Ln4+uuvVbAQFhamCtHRo0dRWVlpKCxWq9VnGqAmGMrMzIQQAps2bUJeXp4qgA6HA+Hh4XA6narvlKuuukoFWa+88oohDXKazp0745VXXsHy5cuxdetWdfD1DipMJhMcDgccDgfsdjuKi4tVpSErJ4vFotIfFRWFkJAQhISEGDpLbNy4MQ4cOIDVq1fj559/NgQIsim0bD7pdDrRqFEj9OzZU3UMJtfl888/x7p163D48GF18HA6nQgPD0ezZs1UkKPvU0ifJ6e6rfx1THYq0+n79tixYwcefPBBLFmyBAcOHDDs3E6nE0FBQaioqEB5ebmqROXBukmTJujSpYsay0rO59ChQ6q/oKioKHTt2hWhoaH47rvvsHXrVpWv/vKwtvWtrq5W45jJQMVkMsFqtSIoKAg2m00dCDp27IimTZti+/btPnlw8cUXw2Qyqfl/8cUX2LJlC4qKilRHdi6XC0lJSYiKisLOnTtVPyxmsxkOhwNRUVGqyfjhw4dRUVGhKl05vltwcDCKioqwb98+FBcXo7S0FEIIVYnJfkfkOFXFxcUoKSlR+4zNZoPdbvdZN+99TL9uV199NT7//HP873//w9q1a3H48GGUlZWpAEjml9VqVX1JeZcfWYblPORBQfb9NGTIEJ/y9uCDD+LLL7/Er7/+ipCQENVBpBxPT9Yf8qAot6Xcl4KCgpCQkIDLLrsMYWFhWL9+fa11wRdffIGff/4ZpaWlKlAODg5GZGQkWrdujW7duuGqq67C4cOHVXnU91ck88BmsyE4OBjJyckICQlR/dfs378fFRUViIiIQKdOnZCeno4tW7agsrISl1xyCcaMGeNTRmX9JPPaYrHA5XIhOjoamZmZSE9PR05ODlJTU3H11Vfj22+/xV/+8hdD/2DyZNBms6k+teQ+J08SQ0NDYbPZ1EEyJiYGLVq0QHFxMQoLC1V3FrGxscjKykJ1dbXfvNTXM8eOHcOCBQvw2WefqX7ioqKi0LZtW5jNZnz77bdYt26dqufDwsIM+bxnzx4sXrwY27ZtQ3V1NeLi4tC5c2fk5uaqg72/Oqm2OjgnJwfdunXDP/7xD2zYsAHFxcWwWq1IT09Hp06dcODAAXz66aeqCXxCQgIaN26MqKgofP3118jPz1cdpLZq1QqZmZkoLy/H559/jry8PFX3+KvDUlJSUF1djWPHjsHlcqn0V1RUYOTIkfjwww/VuIM9e/bEkSNHsH//fuzYsUONs+lwOJCQkIC0tDTk5OTA4/GoPq8qKiqwceNGjBw5Ep06dcIbb7zht56++uqr8cILL6iyIdezT58+uOqqq6BpGsaNG4ft27erE7RTOYbUJWCDIEl2RLV582Zs375d9a0heyOVHT8VFBTAZDLh4MGDahqTyYTS0lLs379fnYk2bNgQOTk5yMjIUBX/kSNHsHv3bmzevBm7du3CsWPH1IEhODgYMTExcLlcaoDN6upqHD16FBUVFXC73UhLSzN00uYv/fqO4tq3bw8A6nOZfnn1Sfa8WV1djfz8fBw4cEB1TtimTRtcdNFFKC0t9TvfXbt24fXXX8f333+P4uJiBAcHq04Lg4KCak3vli1bVMdzbrcbycnJcLlc2LhxIzZt2oSjR49i3759aqBJuaOGh4cjPj4emZmZiIyMNKRX9jkSFxeHiooK7Ny5ExUVFYiLi0N2drZK7wsvvIAPPvgA+fn5qKioUAef5s2b4y9/+Qu6du3q0/GWv87RgN86C9uzZ4+66pKUlAS3240NGzZgz549SE5OxhVXXAG73Y6XXnoJmzdvRkxMDPr06YPmzZsbOjT86KOPsGjRIpSWliIiIgLJyclo3749oqKisHv3bqxbt87Qg3CnTp3Qrl27Wsvz+vXrsWbNGkRHR6Nbt24IDg7GunXr8P333yMsLAwejwerV6/G1q1bER8fj9GjRyMpKanOshQVFYWNGzfiq6++wtatW5Gbm4uLLroIK1euxKOPPopDhw7h119/xa+//mrodbhRo0YYPXo0hg4d6jcP9cuRneDpbd++HT///DNCQkLUWX1sbCxCQkJgNptRUFCAhQsX4quvvkJMTAwuvfRSJCcn4+WXX0Z1dTUGDBiAFi1aAABefvlldbBMTk6GzWbD0KFDERQUhMrKSuzYsUN1IlpZWYktW7Zg9erVPgfS2NhYTJ48WQVwekII7N69W+Xn6SgvL1dBCgD88ssveOGFF7Bp0yY0btwYffr0QYsWLbBs2TKUl5ejf//+hg71jh49ivnz5xu2q7xiK/uQ0fPeBmFhYSguLkavXr3UNPp9ICYmBvv370daWhomTJiAe++9F6tWrUJ5eTk++OADzJo1C/Hx8T7rpZ+Hw+FQHU/KM3i9bdu24YsvvsC+fftQUlICk8mEcePGITExEfn5+ViwYAGqq6vRv39/hIaGIjExERaLBYsXL8Zzzz2H9evXq6A5LS0Nl156KUaNGoVNmzapwUgjIyOxfPlyFBUVoUmTJoiKisK6devw9NNP4/vvv1dXolwuF3JycjBlyhTk5uYCqLlCKzsk9Hg8+Omnn1BeXo63334bWVlZ6uqYrH+io6OxY8cOREVF4dixYzhy5AhWr16NjIwMvPDCCxg9ejT++9//QgiByy67TA1aO3bsWPzf//0fqqurkZSUhGXLlql8MZlMSEtLQ8+ePREcHAyg9s5pAeCqq65CVlYWCgsLkZycjF69eiEtLQ0HDx5EVFSUoeyXl5djw4YNaNu2LYKCgnD48GGV53369EFWVpahvC1cuBC7du1S9V1RURF++OEHHDlyRPU0v23bNnz00Uc+fQKZTCZkZmbi8ccfV/kr9/e4uDjMmjUL1113HY4dO4a4uDg0b9681vrJ33HxtJz2DbQ/iaKiIjFixIiT9nVxOs+enMmzLafzateunZg1a5Z48sknVWsn+eyHy+XyuX+tf3C3rldt9/s1raZJqr9+K/QP39X2Sk1NFW3btj2j++Znkt7f89I0TSQkJIhu3bqJhIQEQ7mQD4s3atTopOsSEREhPB6PofWF/hUcHCyuvPJKMW7cOL/3y2u7dx8cHKxayVgsFpGamio6deokjh07JoQQYs6cObX2L3KyV2RkpGjRooW6zx8aGmqYl7/18Ne/THBwsKGVmn6dTCaTaNKkiejXr5966Nh7Ha+55hpRUFAg/vWvf520z63w8HC/5U/2/ySfN5o1a5aYN2+eIY2yeb18SF4+tyYfAtXPNzo6WnTr1k0MGjRItG3b1lD+u3TpIubPny8OHDggqqqqRF5entA0TQghxBdffCFeeOEFsXjxYrF06VKxfPlyMXfuXHH33XeLGTNmiJkzZ4pHHnlE3H777aJjx44iMjJSTJkyRYwePVpMnjy51n6D5LM1skn2mjVrVIuiurbvzJkzxaeffirmzJkjOnfubOgOQb8tBgwYoB7a9f7Oe1/RNx6IiooSzZo1E3/729+EEEL885//VIMT11bGw8LCRNOmTUXPnj1F27Zta11ex44dRVhYmIiMjFTbzmQyiUaNGom33nrLZ/ouXbqIK6644rT6rJLzbNiwobjrrrvEE088oR6WHjZsmOFh6dN9ye2o7yJC/9yTfJbmzjvvFOvXrxcWi0XMnz9fAL91uSGfS9U/k6ivnyIjI8XAgQNFy5YtxYwZM8S3334r3nzzTVXO9eMVNm7cWG1D/bM2+sFz5T4rW7EBNc8b3XLLLWL27Nnq4XmXyyVcLtcp9RMXHx8vbr31VjF16lRDs/0uXbr47dfJu36QaYyOjjY8C9avXz9RVFR0xrFAQAZBx48f9+nH5fe+ansI1XvHB357aEz/MJ53WuLj4895UOWvoJ3ubxwOh7j55ptPWojryg+g5iHAJk2aCIvFIho3biwsFoto2LBhnR0a6lthyZ22rnRec801aqeOjY1VD5SfaX4FBQWJ3Nxc1UrCZrP5PPxss9nEPffcI26++eZa5yNbpOn7WgJqDiyhoaE+D+Lr8y4oKEiMGDFCAL89BLlw4UK/zcblb70f5PU3TV1lRD5IXVs+ywf49Z+faSCclZVlCO5lwO+dTpfLJaxW62kN5KkP5Bo2bKg6nbNYLCIjI0P1JeX98i5nMnj8PWXJO4/1y5Dl6mT7p2ypU1tnc/r06+efmZl5RgOg1vaSzcpldwlymbJfm7rK18nyUB+g6vs98u4zx+Vy+ayn9zJOpbyfab6c6gnoqb7O5bEgKChIhIWFqfzo1q2biIyMVPuZbCZ/KkGl7NZD3/WDyVTTF9bv2T/k8bVFixbq4W/9tg0JCRHvvvvuGcUDARkEyWaSU6dOFS6XSyxbtkzceuutIjIyUo0eLSN/2bw7LCxMtG3bVhUM2dokODhYTaNpNR31DRw4UAAQw4cPF8BvZ60PPPCA0LSa3mblgejGG28UbrdbtWaYM2eOqsxkB2a9e/cWISEhhp3WdKJfD9kfREREhNpRevTooSoFh8MhrFarcLvdonnz5qrPl7CwMDVK75AhQ4Sm/dYj7I033qiaW8szEBlotGnTRrXEkRVuixYtVLNW7UTTbH2rg4SEBNWsXTZ3tFqtYubMmWqapKQkYbVaxVNPPaX6CwkJCRFXXXWVqvyio6MNLcweeeQRdbVKNtEEIJ5//nn1G7njud1ucccdd6genGWT59tvv91wBtq0aVNV0WqaplpEaZomhg4dqq6UaJqx08KZM2cadkw5D9lnjcxbm82mKm+5PWUfNLUFJ6dTmQG/NdmWy3ziiSfUFQTvziBP9srMzDzlCthut6uDnr7rAP26yuDI+0B/qusmX/5aYsqX/gzZ3+f+Xt4t35xOpzqQ2mw2w5UpuY7du3evc57Z2dkiKipK2Gw2FWBpJ1qXyr5oZH9J+jwKCgoynFTo11325aNpv/UnBdQc2N9//31Vb8ltf8cdd/i0tJOv0znpadKkibpyo/9cn/eXXnqpeO655wxXF042X1kfRUdH+5zMZGZm+r266S/Pva+OyJe8YiH70woODlZdVMhpVqxYoZatbwkM/LZfBwUFqZHgZfmT21JO+8Ybb6hgQrbskldL9Gk5lfyWHVHKkxZ9env27Gm4Uu1yuYTH41GtR3Nzc33ywt/ftQVpDzzwgE9LL/m3rKMuvvhiAfzW6aac1/+3d93hURVf+72bze5md9N7Ib2ShJCEltATQggaOgqKMSIgxQIqKCgiiiCKIKg/UBRBFAQBad9HL0rvTSC0JNQQIZQQUgjkfH/kN8O9m00DBPmY93nmgezunXtm5szMmZlz3rG2tiZPT0/OC6XRaGj69Onk4uLCmcxZ3oxbqKq2DQ4OJqCcooAtdJo3b05A+Q6hJEn0yy+/cP61VatW1doeeCKNIFdXV9Lr9bRr1y6ysbGhXbt2kaurK61cuZJsbGxoypQpvDEYu/SUKVNIpVLR5MmTSZIkTjLHOpVeryeNRkMODg68486ZM4c/K0kSz4tN0ix/GxsbrkQzZ84kSZI4SRkjqGKdGLhLNshkGjNmDP8XKLeK2UA9ZcoUAkBTp04lSZLo+++/ryC/o6MjZ2IGQNOmTVMMHGPGjCFJkjiXEZOXySBJEicPY8dyjMyOlVeSJJo6dSoBoFmzZinqAygnH5MkifO9/PDDD+To6MjLwd5pa2vL5fz777/5oCSXd9WqVTxfFko+depUcnFx4aRpbLU8aNAgvpJXq9Wcp4MR0qnVaj6IMcKuqVOn8q1tpicfffQRAXdXp8yoHT9+POe3AMqNT/Z/Zoj9+uuvimdZeWxsbLjBx94zd+5cXidy/QTurnD/+usv3rbSf0OQgbt8HFqtlk+WjIBOTm4pSeXkeIy/hRkICxYs4DxB7HeSdJevys7OTkGABtw1GNjWO8srICCADAYDWVhY8DB3Vkb5pK9SqSg9PZ1TNCQkJJg1buSfsXIzgkY26M6YMYMAKIhHAVR4vzwxeeU6xdK2bdtIku6GSTOdYjxVjCJB9V+eGvacfCtfzh5ubkICQMuWLeN1yn4nn5gkqZzPJy4ujh9FMn6gFStW8N+98MILislt2LBhFXaw5GH1coPryy+/JDc3N+rVqxfXNUmS+HU1rPzycri7u/PFANvNYvKq/suhw+RjfezNN99UHJeZ45dhBmRVemDKks2OMl977TU+lrHn+vXrpzAqZs+eXaENNBoNzZkzh0/AjGBQbpz8/fff/BYBNjZIkkTPP/88/43ciHzhhRfIyspKYYCbGnPmrgFasWIF2dra8vGDtSEr0/vvv1+hbj744AP+melO2G+//abQJ7k+sLpiR7AsDxa+zsZXZhSx79VqNcXHx5ODgwOlpaWRwWDgR6xyoklnZ2fFosV0vGP1wfRy4cKFfBzbvXs3AaDNmzeTjY0NffTRRxQXF1dre+CJNIL0ej21b9+eoqOjKSUlhaKjo0mn09HBgwfpueee4zwXzs7OZGVlRe7u7vxagLp161JQUBBfvbFdgfbt2/MjNkkqv3vGxsaG6tSpw++sYorAiLzs7OzIysqKYmJi+A4HO05hBGbt27cnvV7PO59araY5c+aQhYUFl4lNTAsWLOBbwJJU7sfC7viJi4sjoJyOXC4/839p3rw55+hgCp+amkoqlYoWLFjAGZWBcqr3qKgoxaTGjiy6d+9ONjY21LRpUz7QMWt+5syZpFarqXHjxpyFlL3PycmJk6Ix5uGnnnqKd3BGAubv788NjA4dOvAVtkql4oOkh4cHn3TYDhnjLDL1U9Dr9XyrNTo6mvz9/UmlUinO0FkdMQbguLg4vmJkecn5VbRaLR9gGKkaS/Xr1+cDG2uDfv36cV2Sr85at27NBwU2AH344YckSRIvK6tbeRo+fDh/hvFXWVlZ8WMKrVZLDRs25HVr7r6egwcPUosWLcjCwoLz2lhZWVH//v0Vv/Px8VHscpk7upMkiV9pwf5mux1arZYz9bIkv9tMq9USEfH73xYuXMh1XH40Ip/cmQ5pNBry8/Pjgzo73kpMTFS02SeffMKNXvZONnkyWZgBLE8bNmxQTLRsgmvZsiVFRUUp2pL9X04aCJQb4cBdkjgAFfxP2CQ6ePBgfozOyEmZ7rMdJzYpOzs7k7u7O18tA+VM82wckaRyBm1XV1eF8S3XA0asx3xxNBoNn3hZHmwHmDF7mxpa7N2MSJB9HhgYSE5OTtShQweys7PjcjVr1kxhDMvrkB0px8fHk0qlUrAoy5OlpSU/so2PjycLCwuup4wskh3RmPrusd1upjNy4khJusvSzO41lBsMn3zyCbm4uJCNjQ3fCbGxseFkioDy+hNnZ2cyGAz03Xff8c/Y4pSlBg0akEaj4cYnSxYWFtxv6Ouvv652d1e+sJdfj8F0k52CsHFIvnNpMBg4aaHcqJX3N61WS0FBQQrST3YKweRln8t3gNhpgunuLWujX3/9lerVq8d1ys3Njfbv30/A3R2vevXq0fPPP0+HDx8mvV5fa3vgiTSC2rdvT61bt6aEhASu6JUpz/34DdXkzLm6JFceOzs7cnZ2JqPRSLGxsXwSZQpjzlfBnPzVlUm+umF+KjWpB/lWNhv4zDlr32td1DRVtg1cVR2r/ktgxgwieZnlJGXyFWNtz7jlqyTTFbhpMj3+kdef0WiktWvX8qMq021t0zpmk5S5/OSrc/nn8gFMkiQKCwur1j+iMgf6yuqKrQzZ1j9L8vdIkkSdO3fmPlfyVXOdOnUqkMTJy2E0GhX3h5kmV1dXsre356SFzIALCAigtLS0SsvJdKBhw4Z895fVEVBuvI4fP54kSVLcNyWXCSg3OJ5//nl+BG/OoGX6YjAYaMyYMRQcHEzOzs7cj6wy/dbpdHw3gpHK2draKth5gfJJRf5ec759bKdbrmvseJCxDYeHh5Otra1i0q/KJ4b1MUtLS76TWNnv5PXI6tDNzY1++umnCk74QPnuRHp6eoU2a9u2bYX6YtdYmOujrHzMAG/RogXZ2dlxck9GqCrXdXn+ISEhFBgYyOujqgAU9n9mRDB9YYzlpnrNyEZZm7GxqU+fPtUGFZheZGtOh8ztsvXp06fSI1RHR8cKRmFlx9Ts/8zJuVWrVmZ138nJiXr37k1XrlxR9HtmtLP8UlJS6OrVq3To0CGyt7evtT3wRBpBZ86coYiICFKr1RQWFkYRERH8ckimgCz6Qd4Z2V1H7DeBgYEUGRmpWP06OjqSq6trhQFATv/v5OREKSkpfEeDrTzlLL3mLOOqFFueDAZDhegdZnHLGURZxIW8I1fFMCqPbpAP6hEREbV2ILSysiJbW1teT46OjtSqVStKSUmh1NRUHqXSpk0bvtvm4uJCgYGB5Onpyd+n0WgoPDyc4uPj+TGDh4cHBQcHU6NGjahevXqkUqnIy8uL+vfvTykpKZSSkkINGzY0K1dNI0qqMmCGDh3Kj7hMB4GAgABKTk6mNm3a8FW3Tqej0NBQioqKoueee47Onj1LREQ7duwgd3d3PvBotVry9PTkOygqlYqaNWvGfcfGjh1b6e3MKlX51QC+vr78KFO+Cq7McGS7c/IBjRkkQPl1DE2bNq3AmF5ViomJMTuYmpM9Li6O0tLSyN7engIDAykuLo7q1KlDmzdvphEjRtBbb71Fzs7OvA4MBgO98MIL/Eiqfv365OPjo2hXtoo/dOgQHxNefvllfieffNJhx3Cs/JXdhG5tbU0DBw6k+fPnU0REBPfBqqzfst0xpgPsPWq1mgIDA8nLy4vrWEJCAi1evJi0Wq1iZ8tgMNCBAwcoNDRU4csiL2tlt8Sr1Wry9vau1jeL5eno6EiffvopjR8/nhwdHSk5OZkkSaK33nqLYmJiaPfu3bRgwQKzbPqs/mrSt0x1z1RPXnnlFbp8+TJ16NCBunbtSmlpabRx40a6ceMG3bhxgzw9PalOnTr8iL9Tp07Utm1batSoEbVt25bq169PBoOBwsLCFPKYHruwMcqcocnGImYUsiNzZogHBQXRjh07iIjotddeI0tLSwUrOnuXv78/xcXFUUxMDD9+ZMfHbm5uNGjQILp58yb9/PPPCsMmODiYRzWaG1fNtadGo6Hg4GByd3dX6NzVq1d5H9i2bRutX7+e/92yZUuu802bNqXp06fT9OnTFQsLg8FAbdq04dfPuLi4UGxsLL/pXZLKfddML24FyndO2RzA5iAfHx+KiIggb29vWrJkCa1cuZKIiE6dOkUTJkxQ6Ctztmf4/PPPKSEhodb2wBPLE1RWVoZVq1YpCJtcXV05A2hubi6ICAUFBZyUTJKkCr8BynkaGjduDCLCzp07eX5ygjlJkjipU2hoKJfj6NGjZkmjgoODsWrVKmzbtg27du1Cbm6ugk2VkbBptVp4eHjAzs4Obm5uyM7O5oypLi4usLe3V8jv5uYGLy8vqFQq/jsm/+nTp7F9+3ZkZGQgNzeXM/zqdDpcv36dM5q6urqiQYMGiI+P5wR88rIcPHgQZ8+eRX5+PiRJgrW1Nby9vREZGQlXV1fk5uZWKK+8TmrSVqYEgNX9LiEhQUGy5+7ujpCQEKxfvx7bt29HTk4Ozp49i8LCQhgMBnh6euL48eOcEffcuXO4desWrK2tERYWhtDQ0ArvN4fly5dj7969nNtHLlt+fj4iIiIwfPjwSvO4desWXn75ZaxduxZDhgzBnTt3kJOTg4KCAgwbNgyhoaH466+/sHDhQowaNQpAOVfQN998g8TERE7iFhsbC2tr6wr1dPbsWVy7dg0hISG4du0azp07h5YtW+Lq1auc++fGjRvQ6/UIDw9Hamoq2rZtiylTpmD+/Plo3LgxCgsLUVhYiNLSUri4uCAsLAyenp4KDo/t27dDq9UiOjoay5cvh4WFBTIyMnDw4EFkZGTA2toacXFxqFevHqZNm4aMjAzMnDkTiYmJAMqJGVUqFTZv3gxLS0vOqcKwYsUKXLhwASqVCi+99JKijAcOHICFhQVcXFxw7do1uLm5YePGjVi0aBH8/PwAAKdPn0ZGRkaFfIFytuySkhKsWbMGjo6O+OuvvxAREYG4uDg4OjoiKysLmZmZOHPmDH/3Rx99hJMnT6KgoAA3btzg7MFPP/00rl+/zhm/79y5gwYNGqBfv36YP38+MjIyoNVque7m5uZiyJAh0Gq1OHDgAObPn4+CggIEBwfjxRdfhNFoRHFxMX755RcUFRUhKSkJQUFBWLFiBX755RccO3aMjxuurq6Ij49Hu3bt0LBhQ1hbW+PatWv47LPPkJeXB19fXxAR1q9fj1OnTqFp06YIDAysQAB48OBB7NmzByqVCj169ODysvLMnz8fixYtQpcuXbjuabVavPvuu1i/fj3S09Oxfft2zolmb2+PsLAwPu4NGTIE69evR0xMDMrKynDhwgUEBwdj0KBBNWYD3rlzJ+cCk0Ouh8DdMev8+fPYt28fvL29ER4eDicnJ1y+fBlnzpzByZMnUVpaijp16qBevXpo2rQpgoKCkJGRgW3btlU7lh09erRKUsUpU6Zgw4YN+Oqrr+Dl5YU//vgDTZs2hVqt5nmUlZVh8uTJWLJkCQIDA2FhYQE3Nzd4enrCwsJCMZbLZVi+fDkWLlyIuLg4BUFtcXEx/P39zeq7HKNHj8bQoUM5Az+TZdWqVZg4cSKcnJxgY2NjdjzOz8/Hnj17kJGRgePHj+Py5cvQaDRQqVTw8vJCaWkpLl68iBMnTvC2+uSTT5CRkYE9e/bgpZdeqiAPG9v++usvjB49GklJSdUrQzV4Yo0goHyCWbx4sUKRXV1dYTQacfHiRVy6dAmWlpbIyclBUVERrKys4OXlBXd3d87O2apVK3Tv3h1HjhzBN998g7KyMiQmJiI4OBjnz59HZmYmWrRoAS8vLxAR8vLykJGRga1bt2L79u1wcnKCr68vXFxcuIGyb98+uLq6wtnZGaWlpdi9ezd0Op2CUKsy+Pv7Y9WqVbCysoKdnR1KSkpw8OBBREVFwc7ODrm5uRg9ejScnZ2h1WqRmZmJCxcu4NatWwgPD0fbtm0REBAAT09P2Nra4tSpU5gxYwbOnDkDe3t7vPjii4iNjQUADBo0CKdOncKZM2eg0+mg1+sxbNiwCgRWFy9exPTp07Fr1y5cv36dGxn5+fk4d+4c/P39cefOHVy+fBk3btyAra0t6tati4yMDNy5cwe+vr745JNP0KlTJzRq1AidO3fG5MmTsWvXLuj1evTs2RO9evXCuHHjsHjxYvj6+iI7Oxvr16/Hjh078NVXX+HIkSMV6PutrKzQs2dPTJ8+XWGEVEfKRUTIzs6GXq9Hu3bt8N133yEzMxOXL19Gbm4ujh8/jmHDhiEmJkZBAMYG5HPnzsHOzg5WVlb8CoTvvvsO7u7uyM7ORv/+/XH+/HkMHjwYdnZ2OHr0KJycnHD9+nUMHDgQzz33HJe1qKgIc+fOVZCpMfLBl156CXZ2drhy5Qp++OEHlJSUoHv37ggLC0NZWRmysrJw9epV7N69mzNfm9OloKAg/plpeW7evIlXXnkFv/76KydKtLe351dQ9OzZE99++y0GDRqE+Ph4PP/884oBtSbYuXMnVq9ejZUrVyI8PBynTp2Ct7c3MjIyEBAQgPr166NDhw4KOb/44gt069YNPj4+vM7ZguTWrVsYN24cpk+fjitXrsDa2hoBAQEoKyvD6dOnUVpaipCQEAwePBgdO3bEvHnzMG3aNJw5c4YbwW+++SaaNm2K9evXY8KECdi4cSOGDx+OkSNH1qpsTJcY8d/48eOh1+tx584dpKSkICQkBACwZMkSjBw5khONDho0CLGxsXz8OnLkCK5du4bw8HCkpKSguLgYCxcuhIuLC7p27VrpuMFI744dO4YrV65g0qRJsLW1Vej4kSNH8PXXX0Ov1+Po0aPIycmBTqdDkyZN0LVrVxw9ehQHDhzg10sAd4k9O3bsCI1Gg7Nnz2L58uUoKSnhBKeVEd0REX744Qds2rQJzZs3x4svvojjx4/jm2++QX5+Pjp06IBnnnkGALBp0yaMGzcOO3bs4GzSlpaW8Pb2hoeHB5o0aYJ69erhzJkznG25tLQUjo6OiIqKQmRkJD777DPk5uaiqKhIIYetrS1effVVjB49Grdv38a7777Lx0srKyvUr18fXl5esLW1RbNmzbB9+3bMnz8ff/31FywsLFC/fn30798fbdq0wblz53Do0CG4urpi6NChsLKywvnz52FlZYWQkBAMGjQITZo0wcaNG3Hy5EnodDqcPHkSo0ePrlR3cnNz8e233+KDDz7gn7GxxWg08rrcuHEjjh07hmXLluHLL79EUFAQPv30U1hYWODKlSucrbtdu3YoLi7GH3/8ga1bt4KI0KJFCzRr1gx37txRjGEsXzYWBAUFYceOHahXrx6uXLmCP/74A5s2bcKRI0f4ZoEpNBoNmjZtih9++IEzTjMCULm+a7Va+Pn5Qa1Wc7JIeX+/evUqli1bhrS0tErrqkrUeu/o/wlOnDhBnp6eJEkSeXp6UmhoKEVERFTYPmZbeCxcVu70aprkDrnAXX+I6vxgTM+hWZL707i7u5NKpaLnnnuOvLy8qGnTptS5c2d6+eWXKSkpiRo0aEBt2rQhSZJ42Clw99iGHWGYvkvue2IancRutLe1taW6deuSTqcjtVpNr776Kg0ePFghq+kxmqOjI8XGxlZ6fGD6nDyx8+Hg4GBq3bo1ATB7nl9dqorQkTktsrrNzc2lRYsWKbadDQYDv8lYpVKRra0tffDBB9wPQS6P6TEm0wd5fcbFxVW4FLBhw4aKz/DfrXC2Lc6OH+Vn4i4uLjRp0iQaPnw4Pxpj2/jybWe2Fc3+dnV1JSsrK9qxYwenHmDfBQQEUPv27alx48bUpEkTatGiBQHlx10xMTHUqFEjTnAm94mKiIggZ2dn6tq1K5evQ4cONHToUGrTpg0ZDAbuc8Oesba2ppCQEOrduzcNGTKE0tLSKDExkRITE+nFF1+kL7/8kjw9PWnLli3cUbaqPsTK2K1bN/rwww952VQqFQUFBdGAAQPIz8+P6tatSxs3blQc2Zjzp2Kyqv5LFqdSqSgyMrJCeDjzBZL7pURGRlJaWhp17NiRmjRpQs7OztSvXz/q2rUr9ezZk1JTUyk+Pp46depEPXv25H479vb29Mcff1Qo24gRI2jevHm8/K+88gp17NiRH5/I64b9X66DrM/36NGD/vOf/1C7du1o9OjRVFJSQh9++CF3imW6yni6WN416XPyI0RPT0+ytbXlgQ729vYVLmxmfoaSJPGjj127dhER0YoVKypERLGAAU9PT97P4uPjFRQV8hQREVGBkJP54FVHC6DRaCgtLY1ef/11CgkJIScnJx7QItcRue6Y8xGUv6dJkybcodrUmV+lUvH6YXOH/Dfdu3enqKgoSk9Pp+XLl1OHDh3Ix8eH/Pz8eJDEhx9+SJ07d+Z6yAJdJk6cyHVWPrbLZWNOz5W1q+nfrVu3pl69evGIypr6RUqSRP369aPCwkI6efIktWzZUuHnpdPp6JlnnqGVK1fyqEX5+MfyiI2N5UeBQ4cOJSLiQR73iifSCMrNzVUYGNHR0eTi4sL9TJh3v7wRTR3w2CDEOqzcmDAlc2MTmnxQqex83NSxLCkpid5+++1q/S2qY29mgwBzQmUTgdForOCUxhwx5c/Kvf7lydXVVRGpYi6xgXnIkCEUEBDA65758Mgd6h40uzSrU1ZeSSpngDXXwc21AVC5H4i5xKJSTH0j5O0jN1LkUXfM8JAnFgHIEnNQNf2dPHLD9D3M3wQAv9W8srKaS9VNHJXJVNs2YrLIuZacnJx4SDRQHgki/01VyZw/DPMns7Gxoe+++47atGlDTZs2VYT/Pki9Y/Uj/5w52rK/fXx8FBN/u3btKsgib8PK/HzYdywqsyrZTPWqtkkun06n40EaldW/Xq+nTz/9lBuW5vp5o0aNKuijOd0zvSHeXGIcSmzRyuStbWAG6/tyP5SQkBA+lnt5eXHnaQsLC+rWrRsPuJHPGez95vooI8+V6011Rr9pG5j7m6Wa+GsywkSgfJE1cOBACg8PJ51ORzExMQSA+vTpU6nPIXs/WzQGBATwxVnjxo2pTZs25OjoSB9//DFf9JlbTJr2HYPBQKmpqXxhHxUVRXPnzqX33nuPDAYDpaWl8b67ZMkSWrJkSa3tgSfSCOratSupVCpaunQpSZJEubm5pFKVU6ZbWlry8EDgboizSqXiTMbA3VUgSxqNhlutrPMz0jrW0Kzz6vV6hSLLd4/YTkRtGZhrmhgfDOsYrq6ulJKSouh8jLCQKae8Pmqa5A6lNjY2lJaWRnZ2dooJgPFxMAOtpoMUW+WNGTNGEU7MBuIhQ4YoBgzTFeGpU6coLCxMQWLIUnR0dI0nQznfk2lipGktWrSgoKAgRZ61GYjlgy8zmgDwkFV5pBEbsNmukfzZ6t4jd2JkA9e96picKFLOkQKUc3uwSeJ+dFy+iDFHulaTdPjwYbKysqJDhw5xHWSRPHIuJqZbbMKSO2dqtVpOjloTvZFztDCDvDYyazQaxQ6Qu7s7WVlZUWJiIiUnJ/PfhYaGkkajoW+//bbWesDaRm5Msc+/+uoratCggeIZV1dXPgZWx1ZtmuLj4wm4O2aaXtdSWcRcdfKzxPJjDrgs5N/0GWaEajSaKhdier2ennrqKdq4cWMFg41NxrWp5weRbG1tSafT8f4vbx9G3Cifb5jc5nboWL0vWbKEgHKyU0Z86+Xlxdvr1VdfrdJ4cXV15bozcuRIcnNzo08++YT0ej1v09qMgzXdkVSpVLW2B55II8hoNJKTkxMtW7aMJEmiv//+mySpnNvH2dmZGysqlYqT9w0YMIDvkKhUKs7+LA+fNo0k2bhxo6JDs44uj0ySG0QqlYqWL19OADh3Cpv4TAnkDh8+zI0B1oHXrl2rUGaNRkNZWVmk1Wp5KCubRNngIEkSz5utIt99910C7kbrMAJBZlB4eHjwMjJSx//85z+8Y9W0g5v73YABAwi4a9CwupGvZtgW/8yZM+nYsWP8c8b/smfPHt4mTk5OZGlpqTCM9Ho9L3/Dhg0rREiZHhV+/fXXihVpgwYNSKfTUVZWliJPSZK4DCzFxMSQi4sLLV68uEJZ/fz8FLuDLKJMPsHLV4gAFDtybm5utHr1akV7yvNhaeDAgQSUM0fL69Dc4MXSypUrK7TTa6+9xj9nx0TsN0w3TNmxw8PDFXV35swZTmbI+hIbFCWpPJybDeJ6vZ60Wq1iYj18+DABoI8//lhRR4xA1Jyeff3112bD9xlXDCOcdHZ25u80/S3jOTJ3TxLr58yAmjdvHllZWSn6LJPt888/N0uAV1Vq0qSJ2YmZTdjOzs70ww8/KCa12tybNXToUP7/efPmKZ43HdP++OOPCgYiS8OHD+fcS/JjWVtbW5IkqUJ4vrxezCVTTqUXX3xRsWPH9EbOnC3XR5VKxa+UAcqPKk135eR6y3alGcGsPLH8a+riAJT3Y0mSFPUl3+EAyvut3Ihnfbcm+Ve2i8sW98BdItDXXnuNv4/VOzOaWF9i/db0SLUmiRHh1kbv5MeIpu3H9J39K99BGzp0KG3cuJHmzJnDbwUQx2G1hKOjIw+7lSSJE3XZ2NgoVlP16tXjSiPnMvH29uaKzRQdKB+s5Mppep7JvmMrR6A8/FVOpMYGisaNGys4SEyNGA8PD4qPj6dx48bx5xmLKZtEPTw8aN26dRQSEsKNOdMBWN7Z/Pz8yGg08g7KJvTu3bsryhATE8PPmps2bUoAeDjlmDFj+PPMkGFb788++6wiH/ngJV+FMJp4+eRn2rnYhMTqi61EgXImXKB8NV+3bt0Kg0VISAj/TG7QtW3blvz9/StwG/3++++Kqy6YLPIdsp9//pkkSeK+MaaDLfM/MxgM5OHhQW5ubnzwY6RfbBeQEbzJ64pdesgmJbbqZgYDC0O1sLCgL774QtGurI6YgSnXUfmVCnKD3JSwz8LCgvR6PSd2ZHQLpkaaXGamA/JJoFmzZrzfMVI2ZqR16NCBRowYwf9mOwxyPWD1y8pibW1Nzs7OtGbNGgLKDRn5DiwA2rFjh2IQZRO16UDP+gYbD0yNPPlnjK8JuEt0yMrZp08fio6O5jrAJhVra2tq3bo1OTo68s9atGhR4Yjk999/5wzkQPnFmnIZWd+T70axsHzTNmP9k+kV0zUA1K1bNwKguCON6SBbNMj9btRqNc2YMYMbC0yf2fdDhgzhZKTyumM7V3JDTqfTka2tLTfc2HvkbeLi4sKpBoDyxYfc1YDtYMsXo0D5QoERnLKrdtRqNXXq1KnCOGLKB2VOL+TfMd1kOsHKynb61Wq1gsC1cePGFRiYTXWLjS1arZbzSzFSUrbgGzFiBH/2iy++IACV3kcoLyObE9juF5uj2K6vhYUFLViwgCRJ4ovz0NBQTqwqpzaQG0em7hGff/65gvi0NkbUhx9+SGPHjlXUCXs+NDSUrK2tSaVSKdwSXFxcaPv27bzOgXs3ZZ5II2jgwIHk4+NDvXr1qvWqzFTRvLy8FD4Lpp1G/jfjEDL9nF0MJ59QJKmcIMyUyItZ9DExMfT555+TjY1NhYmIDSy9evWiuXPn0muvvUaJiYlkb2/PFcYcoRZbxSckJFS6Eqlfvz49++yzFSZ5lUqlcERWq9XUu3dvs/4LNbmzyN/fXzFoVrb6lCSJfH19OS+Q/Lvw8HCF/41cVvn/GRtuVFQUtW7dusoOHB8fT998800FbqTc3Fxq2bIlZwP39PQkjUZDc+fOJTs7O3rmmWe4P1SHDh2od+/e9P777ysmU2aAMyZxuRzy++mcnZ3J3t6eoqOjFXWk1+vJ1taWrK2tydramnNPyfmIgPKBlbVf8+bNKTAwkEJDQ8loNCocnFlidyYx5lZJkig6OppUKhU1aNCAvvnmG07qxtqX8RIx40k+eLHysh1OZ2dnaty4Mbm7u1NSUpLiDrXqVsS//PILde7cmRITE0mSJOrZsyd32meTREpKCuc2qe64w1SnK/uM9UtTMlP5PWCmhhPbWZVft6JWq6lHjx6UkpLC+0Xr1q35ri6rf/n7tVottW3bloYPH262LPKjd5asrKxo8uTJnG3XtE+wv6Ojo8nGxobef/990uv1FBQUVIEBmjmKszJVxg3EUmUyAuUGQFxcXJVH7qZHbFXxLwGgI0eOUGpqKul0OurSpUuVv2W6Kb/4WH4EyBzzmVFgKr/8CNk0b7VaTQsXLqSPPvqoynlGr9fz41a2c+Tv78/Hf2ZAs36zfv16AsqvEXF2dqbZs2dz3iJAaVCyZ9gc4ezsXGG+MB2P2emD0WgknU5H4eHh1KxZMz5HqVSqCvWRnJxMzZs3V/RdGxsb3h99fX056z+rq9dff50kqdwd5fr161USlLK66dOnDy1ZsoScnJyoZcuW9NZbb5FaraaBAwfesz3wRBpBxcXF1L9/f+6fIu9U7LgnKCiImjRpQlFRUVS/fn1OSte6dWvKzMykjz/+mFq0aEHXr1+nvLw8evHFFxU7HPKO17x5c+rRowdvyMDAQPr++++pcePGZDQaKSkpia5du0avvvqqouO/9dZbNGPGDFq+fHmFyclcx2afscH2zz//JCKiK1eu0ODBg6l9+/b0559/mvV7Ybd/V7YSsrS0pMDAQJo+fToREY0dO5YSExPp5ZdfJl9fX8UFrmywtrOzozVr1tCHH37Iifri4+Np0qRJ1KdPH1q3bh3Nnj2bvv/+e1qwYAG9++67VFRURPn5+UREVFRURFeuXKGpU6dy8i25TFqtlgYPHky3b9+m1157jVq3bk3btm2jVatW0YQJE+jKlSt0/Phx2r59O7+8b9KkSTR79mz64osv+AAREhJCL7zwQqUTrvw6gtGjR3M9YufmAOjixYtERJSZmUk7d+6kGzduUJ8+fWj69On06quvUrdu3SgjI4OOHDnCnx83bhy1adOGYmNjSZIkKikpoWPHjlGXLl0Uq0x5+3p4eNDkyZO5/prTAUtLS2rVqhVt27aNn91LUvkVJ927d6f//Oc/dPLkSb7STk5OpjVr1tCzzz5bpV7JB0h279e6deuIiOjixYvUuHFjHnXn4uKi0Od7SV27dqU+ffpww9Lf359CQ0OpTp061LFjR/7ukydPciPZwsKC7OzsaPXq1UREJEkSxcfH83utmjdvTmVlZXTx4kXavn07/fnnn7R161Z64403aPLkyTR79my+axcWFkZLliyp1M/FtK5q63QrH9w9PT3pyy+/pLKyMn79Avvu4sWLlJaWRp9//jnduHFDMXbJSSolSaKoqCh6+eWX+R2G7Mixb9++RFROFNu4cWMKCgqiN954g5KTkxVGKeuz48aNo/bt29OPP/5Ibdq0oU6dOtGff/5Jhw4doh49etDnn39OzZs3pxYtWlCrVq2ocePG/KZwFmGXnp5OLVu2pMLCQh4txvqtp6cnbdq0iZKSkshoNJKvry8lJCSYDQ4wl0x32W1tbWnNmjV8Uv3888/pmWeeISKinJwcWrFiBX3xxRc0fvx4Wr16Na1atYof07E+3qtXL+rVqxf98ssvJEnl0ZwsEunw4cOUnZ1NAwYMoODgYHrjjTfor7/+oqKiIiorK6PS0lLau3cvHTp0iLZs2UIDBgyg1NRU+vLLL4mIqLS0lPbs2UPbt2+nb7/9liIiIhRzDjNYzO0aseTr60uSJNGhQ4fo9ddf5wsPCwsLsrW1pR9++IFmzpxJREQhISHk6enJjS93d3c6ePAgvfLKK4p5atKkSfTss89So0aNKCcnh1auXEnLli2jv//+mxYtWkTNmzenPn36UFlZGR/z7OzsFC4jYWFhVFBQQEVFRTRx4kQKCQmhvn370qVLl/iYeOHCBfrkk0/o/fffp5deeokvlHQ6HXfD0Gg0iiNdefkdHBxozJgxRERUVlZGhYWF9Morr1BQUBBvn3vFE80TlJ+fj927dytID2NjY2FjY8N/k5OTg6lTp2LNmjXIzc2FJEmoW7cumjZtip49e3IeEgA4f/48fvvtN7i6uiryu3nzJs9j+/btCAgIQFhYGDp16oT09HTOFQMAmZmZOHnyJFq3bg1LS0sA5XwKBw4cgF6vxxdffIETJ06gY8eOcHV1ha2tLefdcHR0xN69e3H9+nUsWbIEY8eO5bJkZWVBp9PB3d0dAHDp0iW4u7tj9uzZiIuLg6+vLye3unjxIvLz83Hnzh0EBwcjMDAQwcHBOHDgAOzs7DB16lSsXbsWly5dgiRJ8PHxQefOneHv74+CggIQEaysrNCkSRPO+2AKVqawsDDk5OTA09MTHh4euHr1Km7fvg2NRgN/f3+8+uqr6N27NwBAq9Xis88+g7u7OzQaDXbu3Ildu3YhJycHRAQ3Nze88MILFeoUADZs2IBFixZx/gw3NzdERERAp9OhadOmXB+mT5+OixcvwsHBAZGRkVCpVGjfvj2WLl2KDRs2YPjw4XBxceH5btq0CWq1Gi1atMDBgwcRFhZWoayWlpZYuHAhunXrxssMADt27MCvv/6KvXv3Ijs7G0ajEf7+/ujUqRPi4+Mxbtw4zJ49G05OTjAYDAgLC0O3bt14+fLz87Fjxw5s3rwZzs7OCA8Pr6C/TKcKCwsRGhqqIGC7evUqLly4gPDwcK7ny5cvR15eHoxGI2xtbeHn54cBAwbA09MTmZmZKCoqQlxcHLKzs7F582akpaXB3t5e8b79+/fj2rVraNWqFfbt24cVK1bgpZdewtGjR3H48GEUFRWhoKAAjRo1AlDOd5KVlQWgnJvowoULyMnJwahRo+Di4oJly5Zh/fr1vO7lusN0acGCBSgoKICNjY1C706fPg1vb28sW7YMixcvxpAhQxAZGWlWJ+XIy8uDo6Mj/3vOnDk4e/Ys6tWrBycnJ3h5ecHJyQlFRUW8zzC9io2NRVZWFr7//nucOHECiYmJKC4u5vXv5uYGjUaD27dvc/I8X19f/i6NRoM5c+bg/PnzaN26NSIjIzlRIYO8rwIAEaFBgwYIDg4GUD5uMV6ehIQE1K1b12w5NRoNFi5ciF27diE2NhZNmzaFk5NThfGiJigsLMSWLVtw+vRpNGnSBHq9HhqNBl5eXgDA+9CAAQNQWlqK8PBw/uzNmzc5Meu+ffvw+++/IzQ0FJIkwd3dHT4+Pvj7778V9XXlyhX8+eefUKvVaNKkCezt7XH58mWoVCo4OztXKifTHx8fH2zZsgUlJSUKncnKysKWLVsQFRWFCxcuYOLEiSgqKuLjnZ+fH7p06cL7IcuPjY1yzi7Wn82NSatWrUJeXh78/PwUOpCVlaXQJ8b9ExYWhvPnz8Pb2xuSJPH6NpVfDnPtmJmZiWPHjiEsLAy+vr7IyspCSEgIDhw4gKioqCr/ZeP18uXLkZOTg65duyrasSqQjFto8uTJeOedd/h4JJ97T58+DSsrK2RlZVXaP5gslY3LtcETaQS99tpriIqKQmJiIq5evQp7e3v069cPFy9exPnz51FYWMgn1cuXL8PFxQXnz59HaWkprKys4O3tjezsbADgBFKMBLG0tBTFxcUAyidtjUaD69evQ6/XQ6/X4++//0adOnU4W6ZKpYJer4elpSWKi4tRVlYGIoKDgwNiYmIQEhKCL7/8Ek2aNEFeXh5UKhVSUlJgaWmJ1NRUjBw5EiUlJTh27BgsLS35QFJUVIR+/frByckJ48aNw/Xr16HRaKDX65GXlwe1Wo2bN2+iffv22L59O65evQoiglqthqenJ3x8fJCXlwciQmhoKBYtWgR3d3fk5ORAq9Wifv362LFjBywtLVFWVgZJkmBvb4/Q0FAcOXIEABAcHAxLS0sEBgZi9erVMBgMyMvLg0ajwfnz5+Hq6oqioiLOaCtJEifc02g0KC0tBRFBpVLBYDDgxo0baN68ORwcHDjrsIWFBYqKiuDk5MSZiy0tLeHk5ISSkhIUFxejpKQEd+7cgYWFBSRJgoWFBVQqFX8uPj4excXF6NWrF4qLi5Gdnc3ZwZOSktCmTRt07twZ27Ztw8mTJ+Hg4AAAUKvVKCsrQ0xMDH777TeeP1BOusnKmp+fj7CwMGRkZMDFxQUODg6ws7PDgQMHIEkSioqKUFZWBp1OB61Wi+vXr/P8GcGjo6MjysrKcPv2bej1ejz//PM4ceIENm3ahBs3bsDf3x9WVla4c+cOTp8+DUmSEBwcDG9vb5w8eRIXL16Em5sbOnbsiPbt2+PQoUPYt28fcnNzcfLkSWRkZECv1+P27du4efMmQkJCEBYWhg0bNqBOnToYNmwYmjVrBrVajVGjRsHPzw+LFi3CmTNnuPHr4OCAM2fO4M6dO+jSpQv++usvGI1G/M///A+WLVuGp59+Gvn5+fjpp5+QkJCAqVOn4sKFCxg8eDAMBgP0ej127tyJtLQ0PPfcc1i3bh1u3rwJtVoNJycnFBQUwNLSEufOnUNISAjy8/NRUFCAgoICtGnTBiqVCnv27EFpaSksLCzg5eWF8+fPw8vLCzExMTh37hx27twJIoKzszMaN26MrVu3oqCgAMXFxbyuLS0tYWlpibCwMHTu3BkODg7w8/PDxIkT8frrr2P06NHIyclBeHg4Ll++jIMHD6KgoABWVlaIjo5Gq1atcOHCBUiShF69eiEhIQE3b97E/PnzceTIEeTk5MDFxYWzLjOW8tLSUuTl5eHo0aPw9PSEtbU1srKyYGVlhYKCAqjValhaWiIyMhJJSUnQ6/W4dOkSsrOzkZmZifPnz6OsrAx+fn4ICAhAaGgounfvjilTpmDv3r1o1KgRjh8/jmvXrsFgMCAkJATfffcdnn76aRQUFKCkpASNGzfGsWPHcP36dZw7dw5EhFu3biE4OBgpKSmQJAmjR49GSUkJ76fSfxnp27Zti8TERPz999+YNWsWrl+/jsLCQjRs2BDJycm4efMmtm3bBldXV6SlpfF6+eSTT7Bx40ZkZWWhWbNmuHHjBo4dO4aLFy+iTp06+Oijj9CjRw8UFRVhzpw5cHV1xeTJk/HBBx8gOzsbI0aMwPnz5xVjvEqlgiRJsLOzQ2BgIOrWrQtbW1vcuHED33//PZydnXHt2jXcuXMHAQEBiIqKQp06dTBv3jxcuHCB56NWqxEQEABra2vs2bMHRqMRhYWFuHPnDje2cnNzERAQwNsqLCwMe/fuhdFoRFFREdfHoKAgjBo1Cj169MDs2bPx7rvvIi8vD1qtFgkJCdixYwfy8vJQWloKJycnTJo0CVevXsXOnTvh4+ODn3/+Gc8++yyWLl2KoqIizrTt6enJF65arZaPe4ylubCwkN8scPnyZZSUlHBS1dzcXF4eCwsLxb8sLwcHB1y9epWPXX5+fliwYAHeeecd/Pjjj/D09ERqaioSExP5GJmfn4/i4mL07t0blpaWWLt2LdatW4eTJ0/C2toaN27cgLW1Nfz9/dGwYUMMGDAAGzduxBdffIHc3FxYWFiAyk+qoNPpUKdOHRQXFyM4OBhr1qxBr169+CJl7NixmD9/viBLrA3YNpunpye5ublxZ0+YbMOxrcbKOHgsLCz4tmCdOnXMcrXIE9u2lpOxARXPvOWJOaDJtwar45Ew52Am9z2paZIkqUIYM8u7Kq6S+0mmhI1V+Q+5urpyh+zaJFYGdqxjel5f07LVpg7k5WDtzeQwx0Nk6kvD2rGyNpTrB7vnrip5qvJRYHpqMBgUviWRkZHcAVnumBobG0tAub/Uhx9+WGm+bm5uFS4/lLcJ8wupSdh4VX4e5r5jdW2qz0ajkbcNaxcXFxd+uSNrC/lRjrz/mYYZyxNzRo2IiODOwfJoJPY7dmQlbxdzZWB5sIgfc1FRNakb5vNi7oJn06AAuT5W1R7yiFQAVfZLdszr6elZY3qDiIgI7m9izs/PtK1ZKDdLer1eQSNR1fhp6oNlMBho3rx51Tr7sjxffvllMhqNirFMnjp27FhhDqgsqdXqCvccMr/S6p6tqXNydb+Ttz2LtpXrXVVjTU3kZLpcmZ6Ze97d3Z3i4uKodevWdPHixXsKjWd4Yo0grVZLL730UoWKtbKyquA4JkkSJ8iqjHPD0tKSwsLCeEeVX6jHEmMNZXlKkkS9e/fml94xJ115R2T/tmrVij/XokULhYHAnJwru/xU7jvCOGvkYaC+vr703nvvEVDRIHN2duYDvaWlJZ06dYq2bt3K38fqgdWZKemh3MfI29tbUQfys2CWf2ZmpmLC+vHHH6vtsExm5jfFotqYszYboENDQ/kZMvMhMfWrqcyBWt5R2TOsfU1/x/QLuEtbwNoqIiKCXzYoSeURM//7v/9bodNHREQo9IeVhU3irN5MJx8A9NJLLynq39ramht8zHBjZZFH2+h0OkpNTa3g9MgmDh8fH4URxqJUapPMTWCVBRawW+LlfiasvIwniYWnM/nDw8P5pCFvd3kbsGg5VnZPT09q164dqdVqat68OTd6mJOqRqNRGG+vvPIKAXcjRtl37du3r9COrG1Yvdnb21N2dja5ubmRXq8nnU5HkZGR3GAyZ1jLw5pZvsyYsbW1JUtLS34pqOkirConcFYv/v7+FBUVpZjMGPkfM4pMHcKrSxYWFtwQMednyIxr5iTOdE6v1yv4r8zpD4tqk48dLDH6hdatW5OTk1OFhScztOVjZe/evfn46+npqQgakS9C5UbN2rVrFcz8TI/ZHPHTTz9VkF0uK4sQNP0N838zLZfcOJWzrwN3DXEWWCEfi5lemS68mJ7Y2dlxqg72WxZZ99VXX5EkSXyTICkpiQICAqokj7WyslJEljLfOnldyilZTMvKxjzml8f0hvVVxl/GxsMOHTrQTz/9RJIkQuRrBTa47d69mxwdHSusruWhxCx16NBB0ZFHjRpVoWMzZmI2IC9atIiAu1wNpjs0kiTRl19+yf9vaWnJn2HRQOy3bFUqSRJ99dVXisGRKT3jojHtQA4ODhVWZunp6fz/RqORTpw4QZIkKRwYWTglSzqdjsaPH08HDhwwOzjJ/y+f2Nl3fn5+dOTIEZo2bZqiY7N6MRgMFfhp2ErRlC/CaDTyXQmWNmzYQAAUBh7rPGxAYI6kbBCWT+RPPfWUYhKSO5CrVCrav38/qdVqGjt2rGIQkpdhzJgxCpliYmIUO2ry0FM2kY0bN05Rf2wiqOlKzrTNX3rpJXJ0dFSEaAPltzab01n2f7mj6L0k5lgr/4zVFatX0wFcrluMn0qemjVrRt7e3mYNfBsbG9q9e7dCL9zd3emzzz5TlJv1F2bom15/IY/Wup+0bds2RdvKDYZ27dpxne/fvz/Z29uTtbU1N6hqklhov2m7S5JEH3/8sWKnhPWbWbNm8d+yeqlJYhPL6tWrSZLuXsVjbndy1KhRZvNgxkpNokFNdZBNhvKopweZ5Mb49u3ba/18TEwM2dnZmWWCB5TjijneIfnva+tQz+YL011NOzs7zlfG8h4/fjwBdznCpk2bVoEklkWTMRJTOYVLTRNrLzmVTHWJGZusDwN3DTpGbTB//nyuB6yuJEmidu3akaOjI1+0AOVXzJw4caLW9sATawR169aNXn75ZerVqxePpmrTpg3pdDpe4XIlYwYHs9Tj4+MVuzGmk1ZYWBiNHTuWHBwceD7y+5+Acovb39+frzrt7e35pPHUU0/VWhFNJwR552KDIisrU1q2uj558iQfuNmEKucYqS6Z7vzs3buXy8CYoVnHW7VqFQHg9OmmofB2dnZka2vLWWuBu1uurBx6vZ6Sk5MVq9fvvvuOgLukdVZWVopOqVarydramnx8fPg72YoCKGf4lg/ypsbkkSNHyGg00p9//ml24GKrEYPBwNu6NkdmbKXJJhy5PsXHx1OvXr14fozmnjGay/WQ6Sqju2dkaGzQkU9KcvnkO5HMcGdcVar/EgvKCUBrklg4LzPCGVeUucR03lTv2Opao9HQhAkTFN916dKFACX/SU0nTbkhZmVlxXc/PDw8OG8JC8GdOHGi4nfAXf4sVt8jRowg4O5xhZww8H4SM5zZ3W0qlUrBjwWAnn/+eUVbMnoAeej5oUOH+E4JAHrjjTcU75kxYwb//9q1a0mSyglJVSpVpfwvFhYWlJ6eTiqVqsIxJns3qw82RpoeB8onZTmPEatDRgqbkJDA/2VtASjHO7mxLEkSX9yxNjM9opIkiVNrsLKx/mJhYcFvEWjfvn0FkltWNqB8AccisuR5A+VEgvKrMeTymNYpG8N/+eUXTjNhbW1tdj5gfVVeJtNxiYWd9+nTh4Dy3fLIyEjFIpXVI9uRZfc1yvmZgHIDSpKkCvQojI6DySTnEwJQYcdszpw5vO/qdDpuLLN6BMrHJXk/ZAsXufE6aNAg8vLyot9++42A8p2mezkWe2KNoAMHDpCvry81btyYGymss1Y1cKlUKoqKiuINXdk9Lr6+vmRpaUnff/99hTNdpkTmzj9ZPlVNnqZb3mwbnl0FIX8P23J3dHTkx26MeE/eadigyiYCJp/pypvtSLFU2fa4fOeKKfBPP/1Ew4cP50dRNjY2ZleJWq2WX+xnypZtNBrpzTffrJFxUZMVqFz+F198kR8tmP7OwsKCfvrpJzp06BCtX7+enJ2dzbZf3759KTY2lreRvB6A8tUa4y8ype+Xl8lUn0JCQhRhtUlJSbx+TAcke3t7BR8H45Zhg1yjRo0qHOuaDp6TJk0iS0tLsre3pyZNmlBKSgrp9XqzvkSsfeS6w8rAiAsZIRsrM2MaZ+VhvEPA3UFdpVJRdHQ0P2bo1q0b150BAwZQjx49+DNV+bs5OTnxCdh0gDY3gcjDd9VqNTVq1IgfCZhOAKZjgySVcxXJF0jyvOU8YVZWVvT111+TRqOpcD2E3BerMpZiNpkyvyaNRqPg6TI9wlmwYAFFRkbyNpT7ORmNRlq2bBmfkNq0acN5p9i4UVmZ5Xkxw1CtVvMFV7t27ah+/fpmdxrZ4o99Lt8BZ2VnO/eMFZy985VXXqm0j+v1eoqOjuZHfsxYMS0HM7CCgoL4/1mdeXl58cUAoPQVatSokcLINRgMld6rZWFhQV5eXoq2qUyHWLuzHT5bW1tycHBQjBWmnErMqDStS9PEjKbk5GTu+iHfUWJ1w+hImLxM51kfM10cyg1M+QKGHTGbO5lgzzGyQ3O+YawfyjmcWPszqpZBgwbxOyjLyso4NUZtoMITCB8fH3h6emLfvn1o1aoVDx/Mzc3l0UkWFhZwdXVF37590bFjR1hZWQEAIiIisHnzZiQlJXEvegD8OYbs7GzcuXMH/fr1w65du6DVajFo0CB06dIFnp6ekCSJPwuARxWp1WrY2trCaDTC3t4ecXFxsLe3557wrVq1gpubG1xcXBAcHAwLCwscPnwYAHDs2DEAgJ2dHbRaLYYMGYIRI0agbt26uH37NiRJQlhYGAoLC2FtbQ1vb28e6XTq1CkAwK1bt1BWVgaj0YjWrVvD398fnp6eqF+/PoYMGYLGjRtj9OjRaNSoEQIDA3kYv7u7O2xtbfH0009Dr9fj6tWrPJKlsLAQarUat27dwtixY9G9e3c0bdoU4eHhsLe3xzvvvIN58+ZhypQpcHd3hyRJsLS05NFXRUVFcHFxga2tLZycnDB06FB8+OGHPBRcrVYrQogbNWrEI6VY3VpYWMDOzg42NjbQaDQ8XJVFuQDlYdANGjRASUkJJEmCVqvl30VFRWHu3LmIiIjAmjVreKSVVquFVqvl71+9ejVCQkKwdetW+Pr6Yt26dXBxcUFYWBgWLVqEN954A35+fmjbti00Go1CZ1hUoSRJsLGx4RE5PXr0QM+ePdGtWzc0bNgQFhYWOH36NI+gUKlU0Ol0UKlUuHHjBq5evYrS0lLcunULAHjkmbW1Nd5991188MEHaNasGQAgJiYGANC0aVPExcXh2WefhdFoxJ9//gkHBwfodDp89tlneP3113H69Gl4eHiY1VmVSqWIwGP9jIW3btiwAREREbzep02bBltbW1haWuLZZ59FUVER2rRpAwAoKCjg7zh//jwiIyPxzjvvID09Hd27d4ePjw9OnTqFuXPncloC1tYqlQoqVfmwNnDgQFhZWSEwMBBdunRBaGgoAHAZUlNTeWQjqycAuH37NgwGAwICAjBy5EiMGDECYWFhGDRoECwtLeHt7c2jogDwdjQYDPD398fZs2cRFRUFf39/6PV6qNVquLq6wtfXF/Xq1YO1tTXs7Ozg6uqK7OxsNGvWDK+99hoAwMXFBfXr10dAQACv49LSUi4fi0hKSUnBsGHDEBQUxOue9XFWxri4OB5ODQBz587FsWPHcPv2bbRs2RL169eHvb09OnbsiA4dOiAtLQ2RkZHw8vLC+vXrUVhYiOvXr/PoRUtLS1hbWyt0tqysDNbW1jAajWjfvj3mzZuHli1bQpIknD17FgDw1FNPISIiAk2aNMGoUaNQp04d6HQ6GI1GREZG4qmnnsKQIUMAACtWrFDol6urK7799lt06NABv/32G1xcXJCeng6gnPZCrVYrdM5oNPJI26NHjyIoKAi//fYbMjIyEBERAYPBoJD/xo0b0Gg0OHv2LPLz80FEaNasGWxtbdGyZUssWbIEJ06cwNmzZ/HKK6/A29sbALBv3z5YWVnBxcUFn332Gd5++22Eh4dj9OjROHPmDDp06MDfwSLJOnbsiKioqAqUEgD4HMRC493d3bFhwwYMGzYMnp6eSE5OhiRJePrpp1FcXMypFiIiIlCnTh34+vpi2LBhcHZ25jQgctjZ2aFdu3YYOHAgj9j18fFBy5YtYTAYYG1tjY4dO+LXX3/F1q1b8fvvv2PmzJn44IMPsG/fPkyYMAE6nQ4AuA6o1WpotVquA6w/sf4QERGBbt264eWXX1aMz1evXoUkSYiOjoafnx/S0tLQpEkTBX0HqzdXV1cEBwejcePGsLGxQXJyMhYtWoSePXsCAL7++mv07NkTRARJkpCUlFSh7NXiAW6wCMiQmZlJW7dupa1bt1JmZma1vy8tLaXr16+b/W7RokU0c+ZMys7ONvv9lStXOEnWg5Z30aJFNHv27Eqfq+zdN2/epOLi4irfyQi2qsOnn36qOCJiK253d3caP348/11paWmldWQOw4YNUzC1wmR1ZWlpSfXq1aPevXvTlStXapyvKaqqw8zMTFq5ciW9//77NdKT6lBbvWOQt9ewYcOobdu2Zn9XWlrKdzYr+z47O7tSfSwtLaUjR45Q3759KSIigvr160clJSX0+eef89Vvq1atKDc3t8aym+JedZaB6RvTtcr0zRxyc3OpSZMm/FkfHx/au3cvl+m3336jKVOmVJDRVKb76dOffvqp2etMgPKdwsrKYFpu1iccHR3pnXfeuSdZzKGyfp+enq5I8+bNU3w/dOhQSk5OrtE7qhpP2fdsV3fOnDk0Z84c+p//+Z/70jtTVNePmJ/p44LCwkIKDg7mUYqdOnWqVRuxdm3ZsiX3PWVjr1qtJnd3d4qKinoIJVFCGEEPEWfOnKGXXnrpoT97r/in5a1t/tVN8JXlV1hYSJs2bTLLKlpUVEQTJkzg+W7atIl69OhBFy5coFu3bt2XvPeKB/2e2rZFTSYQubFZXf3OmjWrRrLI2cKrw8Noi3s1KImIjh8/TocOHaLS0tJ/SLrqkZmZSdOmTaP4+HhasGBBjctQVbkfRL3L86hNftUtmk6fPk3bt2+nnTt30uXLl6vMa926ddSsWTM6evQoFRYW0s8//0xPP/00BQUFcSZyoor6WxvUth/dLx7W+LR06VIaPHiwWYPRtI2++uor6tmzJ40aNYoOHz5MP/30E4WFhVFISAgNGzaMTpw4QZMnT6Zbt27VeFH8oCGMoIeI/fv33zOfQVXP/lPKXxN5K3t3TZ69n/ow935z+R07dox8fHz46rZFixZ0/vx5/r0pxwTLw9xA/SDkra4MlZXjfvCg20Iur7n63bVrF/++svqtaf4PQt57yf+feLaq500/f1B92rSezpw5Q126dKH27dvXyGg1ledB6KY8j3vVOzm++eYb8vb25rt2LDVt2pR2795d4fcrVqxQ0F2Y+tioVCrFdTD/RJ+vqjz3in9qfJKjoKCAZsyYQSNGjKCvvvqqgrEpL9PHH3/M7x1ku+tqtZreeecdGjt2LDk7O/P7w0yffZhQVzwgE7hXLF26tMrvMzMz/5Fnr1y5glmzZmHGjBlVC/gA38mezcrKwsyZM9GpU6cKzxJRle+oKv+q3imH/P3m8nvnnXcQERGB3bt349q1a+jZsyeio6MxduxYzhrL5NyxYwf3C1u0aBHPl72jXr16tZK3puUwrcMHUS9yPOi2kOubufpNTk7GlStX0KlTJ0X91vQ9V65cMatT9ypvVfI/zGeret7085q+p7Z9eN++fVi0aBEAYOXKlWjWrBl+/fVX7pMyf/58pKenw87OTvFcbfqAXKYdO3ZU+J71saVLl96z3jFMmDABkyZNwvDhw6HT6TBx4kT07NkTd+7cwR9//IH4+HiMHTsWQUFBXJZZs2ahbt26OHjwILy9vZGVlYXU1FRERkZi7NixsLa2xqhRo5CQkFBj2e4FtdWl+xmv7xV169bF5s2b4eDggLNnz6J58+a4du0agoODcerUKXz88cfYvn07/Pz8ACjLNHPmTISHh8PZ2Rlvv/02EhMTERERgVmzZiE0NBSFhYWYMmUKAMDe3h7h4eHYunXrPfete8UTeW3GPwXVf6naq6pSU4fomjzLPpMkCYsXL67wfWZmJt566y2z+d6vvADMvrNTp078WfqvU5o5uVUq1T3VB4O848vfafoe9n7T/FxdXbF27Vp+XxRzmq2p2rN82Tuqk7e6MlRWDtM6rM17atKOtWmL6gbbpUuXYsaMGVi8eDHS0tLw0Ucf8bt9OnXqpNBXc2UDzOsUQ2ZmJoYMGXLPulOTyaKy/nI/z1b1PJuAc3NzMWPGDAwfPlzxPfuc1UtN+7Rp21dWXyNGjAAA/PLLL/xalePHj2Pw4ME4cuQI3nvvPTg7O/P2q6w/16QPyGWqrv3YvzXRO3N14ufnh//85z9ISUkBABw/fhzx8fG4cuUKJEnizu41GeeYPN27d8eCBQtw4sQJGAwGeHh41LrPA/evS6a4n/nlXqFSqXDx4kW4uLigV69e2LNnDz744AMYDAYUFRVh3LhxsLGxwdtvvw1AWSa9Xg+DwYD169cjMjISarUaPXr0wJw5c/i1T0uWLMHt27fx+uuvY/Pmzdi7dy9++uknvPDCCw+sDNXin91oerLg4eFBixcvrvT7ffv2VbpdWdWz8rBQ5khmmu5lG7Qm8gJ3Q3/lCTIHYnPvZs/ea30wmAtrrqzs5vKztrZW3NzOyizPCzAfrip/l0qlqpG81ZWhsnLI863te2rajjVtC1N5q2p707LI687Ly4tzKpnKUlX+LJ971Z3q5K+qv9zPs1U9X5WOmdO3mvZp07av6btY3mVlZdS/f39FiHRl40xN+4BcJnO6Kc+jNnpnrk70ej1lZWXxv8vKykitVpObmxstXryY9u/fT0ajUSGLjY0NLV26lFQqFVlbW5Ner6dTp05xWbKzs3lYu6n+1gb3q0umuJ/55V4hSRL3/fH39zdbpsr01s/Pj6ysrOjIkSN0/PjxGut9YGDgAy1DdXgiQ+T/KcTGxmLPnj2Vfl+VFV/Vs+7u7vjiiy/4ysY07d279x+TFwAWLVpU4Z3s8tbK3s2evdf6YHB3d+fvZ++srOzm8gsNDcXu3bsrlNnDwwMpKSmwtbUFUL4zkZqain79+kGSJOzbtw8qlUrxjprIW10ZzJXDtA5r+56atmNN28JUXtPk7OzMdbFhw4b46aefFGXr27cvDwmWhwrLZakqf1Yf96o71clfVX+5n2eret7DwwOLFy/mesX+pv/ulsj1rTZ92rTt3d3d4eDgwPPev3+/YlfGNERckiRMnToVBoMB9vb2iI+PB4BKy10T3ZTLZE435XnURu/M1Qm7UJNhw4YN0Gg0aNiwIfbs2QOdTsd1jsni6+uLs2fP8suh33//fU4lQEQ4c+YMvL29zepvbXC/umSK+5lf7ges/oqLi+Hs7KwoE7ul3lyZnn/+eZSWlmLAgAFITk7mofujRo3CtGnTYDQaodVqK4yz586de+BlqArCCHqAGDp0KB9EzCEwMBAbNmyo9bOxsbG4ePFipc/eq/LXRN74+HizHY89W9m7AwMDMWXKlHuuDwZ5xzcnr/z95vLr3Lkz5s6dW0Hu2NhYNGjQgPNN7NmzB0OHDkVKSgo2bNhgdqCuibzVlcFcOUzrsLbvqUk71qYtqhts69aty+U1V7/169cHESk4POTvqUynGNige6+6808tRqp7tqrn2efsedPfmeZb0z5t2vaxsbFwdHTkeZvWEzu2NM07ISEBfn5+OHjwoNmjsNr0AblM5nRTnkdt9M5cnQwfPhyDBg3Cs88+ixdffBEdO3bE66+/zt+7ceNGREREKGQZMGAAXF1dsWHDBnTu3BmbNm2CWq3msqxYsQIJCQlm9bc2eNBGy/3ML/eDxMRExMTEID8/H97e3ooynT59mnPYAcoyjR49GgkJCThy5Aj69u2L1q1bw87ODhMnTsR7772Hbt264YUXXqgwztatW/eBl6EqCJ+gxwCbNm3CzZs30a5dO7Pf37x5E7t370bLli3/X737n3y/PF9z75Dne79lfNR1WFtUJ+/q1auxf/9+DBs2zOz31ZXnn66P+8n/fmWr7Hn2efPmzbF7926oVCrF70zzvR+93rFjByIiIsyWYfTo0Vi+fDkmTJigyJvJt3TpUkybNo370tS03A8C91r3K1aswM8//4ySkhIkJyejb9++/Lu8vDwAUEzUDwuPW783h9GjRyv+NhqNCA8P52UaOnQozp07xxdC1fWtbdu24aOPPoK/vz/atGkDV1dXAOU+cWvWrMGpU6ewcuVKtGjR4h8u2V0II0hAQEBAQEDgoSA7OxtTp07F9u3bOUO2m5sb4uLi0L9/f75b+bAgjCABAQEBgccaN2/exJ49e5CTkwOVSgV/f3/ExMSYPdoTEJBD8AQJCAgICDyWKCsrw7vvvouvv/6a3wPI1vXe3t746quvkJqa+ihFFDCD27dv4/Dhw4q70sLCwvhdlA8TwjFaQEBAQOCxxIgRI7B8+XLMnz8fq1atQrNmzfDpp5/iyJEjSEtLQ/fu3bF69epHLabAf1FWVob3338fzs7OiI6ORkpKClJSUlC/fn24uLjwqNmHCXEcJiAgICDwWMLDwwPz5s1D8+bNAQDnz59HaGgoLl++DK1Wi48//hgrVqzA1q1bH7GkAgAwbNgwzJw5Ex9//DGSk5MVjtGrV6/GyJEjkZ6ejvHjxz80mYQRJCAgICDwWMLGxgb79++Hv78/gPKdBq1Wi7Nnz8LNzQ1HjhxBw4YNcfPmzUcsqQBQ7gA9a9YsJCcnm/1+1apVSEtLQ25u7kOTSRyHCQgICAg8loiMjFTwVM2fPx9GoxFubm4A7hpFAv8O3LhxAx4eHpV+7+7u/tANVuEYLSAgICDwWOKjjz7CU089haVLl0Kn02Hr1q34/PPP+fcrV65EdHT0I5RQQI5WrVrh7bffxi+//AInJyfFd5cvX8Y777yDVq1aPVSZxHGYgICAgMBjiwMHDmD+/PmcLDEpKelRiyRQCc6ePYv27dsjIyMDkZGRCp+gQ4cOoW7duli+fDnq1Knz0GQSRpCAgICAgIDAQ0FZWRlWrVplliyxbdu2UKkerpeOMIIEBAQEBB5rZGZmYvPmzQqyxKSkJNjY2Dxq0QT+5RA+QQICAgICjyVu3ryJ9PR0LFy4EED5JZwuLi64dOkSrKys8Omnn2LQoEGPWEoBU+zcuRPbtm1T7ATFx8ejYcOGD10WYQQJCAgICDyWePPNN5GTk4ODBw9Cp9Nh+PDh8Pf3x6hRo/Drr7/itddeg729PZ577rlHLaoAgL///htdu3bFli1b4O3trfAJGjJkCJo2bYqFCxfCxcXlockkjsMEBAQEBB5LODs7Y+XKlYiNjQUAXL16FR4eHsjLy4Ner8c333yD77//Hvv27XvEkgoAQLdu3XDhwgX8+OOPCAkJUXx37Ngx9O7dGx4eHvjtt98emkzCCBIQEBAQeCxhb2+PnTt3IigoCABQWloKvV6PCxcuwNnZGSdOnEC9evVQVFT0iCUVAABra2v8+eefldIW7NmzB61atcKNGzcemkyCLFFAQEBA4LFEw4YNMXnyZP735MmT4ezsDGdnZwBAQUEBjEbjoxJPwARarRb5+fmVfn/jxo2HTm4pfIIEBAQEBB5LfPrpp0hKSsLChQuh0Whw8eJFzJo1i3+/detWtG/f/hFKKCDHs88+ixdffBGTJk1CYmIij97Lz8/HunXr8Oabb6Jnz54PVSZxHCYgICAg8NgiJycHy5cvR0lJCRISElC3bt1HLZJAJSgpKcHgwYMxY8YM3L59GxqNBgBw69YtqNVqvPzyy5g0adJD3Q0SRpCAgICAgIDAQ0N+fj727NmjCJGPjY19JLxOwggSEBAQEHissX79+gpkiR06dOAO0wL/Tty8eRPz58/HyZMn4eHhgR49esDR0fGhyiCMIAEBAQGBxxJ///03UlNTsXv3bqhUKpSVlSE6Ohrnz5/HpUuX8Oabb+Kzzz571GIK/Bd169bF5s2b4eDggLNnz6JFixa4evUqgoODcerUKajVamzfvh1+fn4PTSYRHSYgICAg8Fji9ddfh4eHB65evYqCggIMHDgQ4eHhyMnJwerVqzFjxgxF9JjAo0VGRgZu374NABg+fDg8PDxw+vRp7Ny5E6dPn0a9evXw3nvvPVSZxE6QgICAgMBjCVtbW2zduhXh4eEAyo9X7O3tcfnyZdjY2ODnn3/GmDFjkJGR8YglFQAAlUqFixcvwsXFBQEBAZg2bRqSkpL491u3bkWPHj1w5syZhyfTQ3uTgICAgIDAA4RWq4UkSfxvlUqFO3fu8N2G+Ph4ZGdnPyLpBMyBtVdxcTHc3d0V33l6euLSpUsPVR5hBAkICAgIPJZo1qwZPvjgA9y8eROlpaUYMWIE/P394eDgAAC4dOkS7O3tH7GUAnIkJiYiJiYG+fn5OHbsmOK706dPP3THaEGWKCAgICDwWGLChAlo27Yt7OzsIEkSDAaD4t6po0ePIj09/dEJKKDAqFGjFH+bsnkvW7YMzZs3f5giCZ8gAQEBAYHHF4WFhdi8eTNu3bqFJk2awMnJ6VGLJPAYQRhBAgICAgICAk8kxHGYgICAgMBji6KiIsydO7cCWWKnTp2QmJj4qMUT+JdD7AQJCAgICDyWOHnyJNq0aYOioiJotVqcO3cO7du3x+XLl7F792506dIFc+bMgVot1vsC5iGiwwQEBAQEHku8/vrraNeuHS5evIgzZ85g3LhxKCsrw/bt23H06FHs2rULY8aMedRiCvyLIXaCBAQEBAQeSxgMBuzfv5/fEXbr1i0YjUbk5OTA0dERS5YsweDBg5GVlfWIJRX4t0LsBAkICAgIPJaws7PDjRs3+N+FhYW4ffs2NBoNAKBevXrIycl5VOIJPAYQRpCAgICAwGOJpKQkvPnmm8jIyEBWVhb69++P+vXrw9raGgBw5swZuLi4PGIpBf7NEN5iAgICAgKPJT777DN07NgRdevWBQB4e3tj0aJF/PtLly5h6NChj0o8gccAwidIQEBAQOCxxokTJ1BSUoKwsDBYWFg8anEEHiOInSABAQEBgccWOTk5mD17tlmeoPT0dGEUCVQJ4RMkICAgIPBYYvfu3QgLC8P//u//orS0FCdOnEBsbCwMBgPefvtttGjRQuE4LSBgCmEECQgICAg8lhg8eDCGDBmC3bt3Y9OmTZg5cyaOHz+OX3/9FZmZmSgsLMT777//qMUU+BdD+AQJCAgICDyW0Ov1+Ouvv+Dv7w8AKCsrg06nw9mzZ+Hq6oo1a9YgPT0d58+ff8SSCvxbIXaCBAQEBAQeS7i4uCh4gHJzc3H79m3Y2NgAAIKCgnDlypVHJZ7AYwBhBAkICAgIPJbo1KkT+vfvj5UrV2LDhg14/vnn0bJlS1hZWQEAjh07Bk9Pz0cspcC/GSI6TEBAQEDgscSYMWOQk5OD1NRU3LlzB3Fxcfj555/595IkYdy4cY9QQoF/O4RPkICAgIDAY43i4mLcvn0bRqPxUYsi8JhBGEECAgICAgICTySET5CAgICAgIDAEwlhBAkICAgICAg8kRBGkICAgICAgMATCWEECQgICAgICDyREEaQgIDA/zvMnDkTdnZ2j1oMAQGBfzmEESQgIPCvw6VLlzBgwAB4e3tDq9XCzc0NycnJ2LJly6MWTUBA4P8RBFmigIDAvw5du3bFrVu3MGvWLPj7+yM3Nxfr1q1DXl7eQ5Ph1q1b0Gg0D+19AgICDx9iJ0hAQOBfhWvXrmHTpk0YP348WrduDR8fHzRq1AjDhw9Hhw4dAAATJ05EZGQkDAYD6tSpg4EDB6KgoKDSPE+dOoWOHTvC1dUVRqMRDRs2xNq1axW/8fX1xccff4y0tDTY2NigX79+SEhIwKuvvqr43aVLl6DRaLBu3boHX3gBAYGHCmEECQgI/KtgNBphNBqxePFilJSUmP2NSqXClClTcPjwYcyaNQvr16/HsGHDKs2zoKAA7du3x7p167Bv3z60a9cOqampOHPmjOJ3EyZMQFRUFPbt24eRI0eiT58+mDNnjkKOn3/+GZ6enkhISHgwBRYQEHhkEIzRAgIC/zosXLgQffv2RVFREWJiYtCyZUv06NED9erVM/v7BQsWoH///rh8+TKAcsfowYMH49q1a5W+IyIiAv379+c7Pb6+voiOjsbvv//Of1NcXAwPDw9MmzYNzzzzDAAgKioKXbp0wahRox5QaQUEBB4VxE6QgIDAvw5du3bFhQsXsHTpUrRr1w4bN25ETEwMZs6cCQBYu3YtEhMT4enpCWtra7zwwgvIy8tDYWGh2fwKCgrw9ttvIywsDHZ2djAajTh69GiFnaAGDRoo/tbpdHjhhRcwY8YMAMDevXvx119/IT09/YGXWUBA4OFDGEECAgL/Suh0OiQlJWHkyJHYunUr0tPTMWrUKGRnZ+Ppp59GvXr1sHDhQuzZswfffPMNgHJnZnN4++238fvvv2Ps2LHYtGkT9u/fj8jIyAq/NxgMFZ7t06cP1qxZg3PnzuHHH39EQkICfHx8HnyBBQQEHjpEdJiAgMBjgbp162Lx4sXYs2cPysrK8MUXX0ClKl/HzZ8/v8pnt2zZgvT0dHTu3BlA+c5QdnZ2jd4bGRmJBg0aYPr06ZgzZw6+/vrr+yqHgIDAvwfCCBIQEPhXIS8vD927d0fv3r1Rr149WFtbY/fu3fjss8/QsWNHBAYGorS0FF999RVSU1OxZcsWTJs2rco8g4KCsGjRIqSmpkKSJIwcORJlZWU1lqlPnz549dVXYTAYuCElICDw+EMchwkICPyrYDQa0bhxY0yaNAktWrRAREQERo4cib59++Lrr79GVFQUJk6ciPHjxyMiIgK//PILxo0bV2WeEydOhL29PeLj45Gamork5GTExMTUWKaePXtCrVajZ8+e0Ol091tEAQGBfwlEdJiAgIBANcjOzkZAQAB27dpVK+NJQEDg3w1hBAkICAhUgtLSUuTl5eHtt99GVlaWuLZDQOD/GcRxmICAgEAl2LJlC9zd3bFr165q/Y4EBAQeP4idIAEBAQEBAYEnEmInSEBAQEBAQOCJhDCCBAQEBAQEBJ5ICCNIQEBAQEBA4ImEMIIEBAQEBAQEnkgII0hAQEBAQEDgiYQwggQEBAQEBASeSAgjSEBAQEBAQOCJhDCCBAQEBAQEBJ5I/B+TEVUJ8QEwcQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_univariate_histogram(df,SALARY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 5))\n",
    "sns.boxplot(y=SALARY, data=df)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1-Expectation :\n",
    "I guess the mean of the annaual salary of an IT engineer in Germany is around 50-60k in euors as Google says so.\n",
    "\n",
    "2-After collecting:\n",
    "The data says that the mean of salaries is 4487k, but median is 70k \n",
    "\n",
    "3-Comparing Data and expectations:\n",
    "the median is not much far from the expected mean, but the mean is much more larger than the expected.\n",
    "As we know it, mean is sensitive to outliers .Let's remove outliers and double-check."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### There are outliers that needs removal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from E_Salary_Cities import remove_outliers\n",
    "contract_salary = remove_outliers(df,SALARY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "contract_salary = contract_salary[contract_salary[SALARY] != 'nan']\n",
    "contract_salary[SALARY] = contract_salary[SALARY].astype('float64')\n",
    "contract_salary[SALARY] = contract_salary[SALARY].astype('int64')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Repeat the cycle "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean salary:  69135.70384615385\n",
      "Median salary:  68375.0\n",
      "Standard deviation of salary:  15808.153332636693\n",
      "Max salary:  110000\n",
      "Min salary:  30000\n"
     ]
    }
   ],
   "source": [
    "mean_salary = contract_salary[SALARY].mean()\n",
    "median_salary = contract_salary[SALARY].median()\n",
    "std_salary = contract_salary[SALARY].std()\n",
    "max_salary = contract_salary[SALARY].max()\n",
    "min_salary = contract_salary[SALARY].min()\n",
    "\n",
    "# display the computed statistics\n",
    "print('Mean salary: ',mean_salary)\n",
    "print('Median salary: ', median_salary)\n",
    "print('Standard deviation of salary: ', std_salary)\n",
    "print('Max salary: ', max_salary)\n",
    "print('Min salary: ', min_salary)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now Expectation meets the reality,\n",
    "As expected the outliers affected the mean heavly, so after removing them we can see that the mean and median are close to each other and to what we expected ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.histplot(data=contract_salary[SALARY], kde=True, binwidth=10000)\n",
    "plt.xlabel('Salary')\n",
    "plt.ylabel('Count')\n",
    "plt.title('Distribution of Salary after outliers removal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot boxplot\n",
    "plt.boxplot(contract_salary[SALARY])\n",
    "plt.xlabel(SALARY)\n",
    "plt.title('Boxplot of Salaries')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Contract duration"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### To know the different categories of duration:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is 8\n",
      "The categories are: ['Unlimited contract' 'Temporary contract' nan 'unlimited' '6 months'\n",
      " 'more than 1 year' '1 year' '3 months']\n"
     ]
    }
   ],
   "source": [
    "unique_duration = contract_salary[CONTRACT].unique()\n",
    "print(\"There is\",len(unique_duration))\n",
    "print(\"The categories are:\",unique_duration)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are missing (nan) values that need to be processed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are  38 missing values in duration\n"
     ]
    }
   ],
   "source": [
    "null = contract_salary[CONTRACT].isna().sum()\n",
    "print(\"There are \",null,\"missing values in duration\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### For the missing values, i think it's proper to remove these rows as its a personal choice that we can't impute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Unlimited contract' 'Temporary contract' 'unlimited' '6 months'\n",
      " 'more than 1 year' '1 year' '3 months']\n"
     ]
    }
   ],
   "source": [
    "contract_salary = contract_salary[~contract_salary[CONTRACT].isna()]\n",
    "print(contract_salary[CONTRACT].unique())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apply data cleaning to unify similar (mis-spelled) categories "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is 6\n",
      "The categories are: ['unlimited' 'temporary contract' '6 months' 'more than 1 year' '1 year'\n",
      " '3 months']\n"
     ]
    }
   ],
   "source": [
    "contract_salary= clean_contract(contract_salary)\n",
    "unique_duration = contract_salary[CONTRACT].unique()\n",
    "print(\"There is\",len(unique_duration))\n",
    "print(\"The categories are:\",unique_duration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mode duration:  0    unlimited\n",
      "Name: Сontract duration, dtype: object\n"
     ]
    }
   ],
   "source": [
    "mode_duration = contract_salary[CONTRACT].mode()\n",
    "# display the computed statistics\n",
    "print('Mode duration: ',mode_duration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unlimited             1900\n",
      "more than 1 year        56\n",
      "temporary contract      45\n",
      "1 year                  34\n",
      "6 months                 6\n",
      "3 months                 1\n",
      "Name: Сontract duration, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# count the frequency of each category\n",
    "duration_counts = contract_salary[CONTRACT].value_counts()\n",
    "# plot bar chart\n",
    "duration_counts.plot(kind='bar')\n",
    "plt.xlabel('Contract Duration')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Distribution of Contract Durations')\n",
    "plt.show()\n",
    "category_counts = contract_salary[CONTRACT].value_counts(normalize=False)\n",
    "\n",
    "print(category_counts)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1-Expectation :\n",
    "After searching i found that,the indefinite (unlimited) contract is the standard contract type.\n",
    "\n",
    "2-After collecting:\n",
    "The data says that most frequent category is the unlimited . \n",
    "\n",
    "3-Comparing Data and expectations:\n",
    "We found what we are expecting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot boxplots by contract category\n",
    "contract_salary.boxplot(column=SALARY, by=CONTRACT, figsize=(15,5))\n",
    "plt.xlabel('Contract Category')\n",
    "plt.ylabel('Salary')\n",
    "# plt.title('Boxplot of Salaries by Contract Category')\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Expectations : \n",
    "In general, longer contract durations may be associated with higher salaries, as they can provide more job security and stability for employees . However, this relationship can vary depending on factors such as job role, industry sector, and company size. For example, some companies may offer higher salaries for shorter contract durations to attract top talent or fill specific project needs"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Collecting information\n",
    "The graph shows that there is variation in the average salary in different contract categories.\n",
    "For example, 6 months category has the highest average of salaries.\n",
    "Average salaries in the unlimited category is close to the mean & median (expected as it's the\n",
    "majority)."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing Data and Expectations\n",
    "I believe Expectations match collected information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сontract duration\n",
      "1 year                63741.176471\n",
      "3 months              54000.000000\n",
      "6 months              78833.333333\n",
      "more than 1 year      65407.142857\n",
      "temporary contract    59282.222222\n",
      "unlimited             69420.981053\n",
      "Name: Salary, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# calculate mean salary for each contract category\n",
    "category_means = contract_salary.groupby(CONTRACT)[SALARY].mean()\n",
    "print(category_means)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Is there a Relationship between Contract duration and salary ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kruskal-Wallis H test\n",
      "Test statistic: 27.608562189681496\n",
      "p-value: 4.3405931086896265e-05\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import kruskal\n",
    "# group salary by contract duration\n",
    "groups = []\n",
    "for name, group in contract_salary.groupby(CONTRACT):\n",
    "    groups.append(group[SALARY])\n",
    "\n",
    "# perform Kruskal-Wallis H test\n",
    "stat, p = kruskal(*groups)\n",
    "\n",
    "# print test results\n",
    "print('Kruskal-Wallis H test')\n",
    "print('Test statistic:', stat)\n",
    "print('p-value:', p)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
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   "source": [
    "The Kruskal-Wallis H test is a non-parametric statistical test that compares the median values of the independent groups to determine if there is a significant difference between them. Specifically, it tests the null hypothesis that the median values of all groups are equal against the alternative hypothesis that at least one group has a different median value."
   ]
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   "source": [
    "#### Expectations :\n",
    "I expect from the graph and other search i did that, the salaries varies in different contract durations based on different point of views"
   ]
  },
  {
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   "source": [
    "#### Collected Data:\n",
    "The hypothesis test kruskal resulted in a p value that is smaller enough than 0.05 to conclude that there is enough evidence to suggest a significant difference in salary among the contract duration categories."
   ]
  },
  {
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   "source": [
    "### Comparing Data and Expectations\n",
    "Collected data meets our expectation and we can say that there is some relation between the contract duration and salary, indeed it's not the only affecting factor.However , on average it has some effect"
   ]
  },
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   "source": [
    "# Interpretaion\n",
    "Based on the results of the Kruskal-Wallis H test with a p-value of 4.3405931086896265e-05, we can conclude that there is a statistically significant difference in salary between at least two of the categories of contract duration. This suggests that contract duration may be a factor that influences salary for IT engineers in Germany.\n",
    "\n",
    "However, the Kruskal-Wallis H test does not identify which specific groups have significantly different median salaries. To determine which groups are significantly different, we should perform post-hoc tests such as the Mann-Whitney U test or Dunn's test.\n",
    "\n",
    "It's important to note that statistical significance does not necessarily imply practical significance. Therefore, it's important to interpret the results of statistical tests in the context of the data and consider the practical implications of the findings. Additionally, correlation does not necessarily imply causation, so it's important to consider other factors that may influence salary for IT engineers in Germany, such as experience, education, skills, job role, and company size."
   ]
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   "source": [
    "# Business value\n",
    "Recruitment and Hiring: Understanding the relationship between contract duration and salary can help businesses attract and retain top talent by offering competitive compensation packages that align with industry standards. For example, if there is a positive correlation between contract duration and salary, businesses may need to adjust their salary offers for temporary or short-term contract positions to remain competitive.\n",
    " In a positive correlation between contract duration and salary, it's possible that shorter contract durations may be associated with lower salaries. In this case, businesses may need to adjust their salary offers for temporary or short-term contract positions to remain competitive.\n",
    "\n",
    "One reason to do this is to attract top talent in a competitive job market. Even for short-term or temporary positions, businesses may need to offer competitive salaries to attract qualified candidates who have multiple job offers or options. Offering a lower salary for short-term positions may make the position less attractive to potential candidates, which can make it harder for the business to fill the position and complete the project on time and within budget.\n",
    "\n",
    "Additionally, offering fair and competitive compensation packages can help businesses build a positive reputation as an employer of choice. This can lead to higher employee satisfaction, better retention rates, and increased productivity and profitability in the long run.\n",
    "\n",
    "Therefore, even if shorter contract durations are associated with lower salaries, businesses may need to consider offering competitive salaries to remain competitive in the job market and attract top talent. Ultimately, the decision on how to adjust salary offers for different contract durations should be based on a thorough analysis of the data and the specific context of the business and industry."
   ]
  }
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