{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".. _iris_dataset:\n",
      "\n",
      "Iris plants dataset\n",
      "--------------------\n",
      "\n",
      "**Data Set Characteristics:**\n",
      "\n",
      ":Number of Instances: 150 (50 in each of three classes)\n",
      ":Number of Attributes: 4 numeric, predictive attributes and the class\n",
      ":Attribute Information:\n",
      "    - sepal length in cm\n",
      "    - sepal width in cm\n",
      "    - petal length in cm\n",
      "    - petal width in cm\n",
      "    - class:\n",
      "            - Iris-Setosa\n",
      "            - Iris-Versicolour\n",
      "            - Iris-Virginica\n",
      "\n",
      ":Summary Statistics:\n",
      "\n",
      "============== ==== ==== ======= ===== ====================\n",
      "                Min  Max   Mean    SD   Class Correlation\n",
      "============== ==== ==== ======= ===== ====================\n",
      "sepal length:   4.3  7.9   5.84   0.83    0.7826\n",
      "sepal width:    2.0  4.4   3.05   0.43   -0.4194\n",
      "petal length:   1.0  6.9   3.76   1.76    0.9490  (high!)\n",
      "petal width:    0.1  2.5   1.20   0.76    0.9565  (high!)\n",
      "============== ==== ==== ======= ===== ====================\n",
      "\n",
      ":Missing Attribute Values: None\n",
      ":Class Distribution: 33.3% for each of 3 classes.\n",
      ":Creator: R.A. Fisher\n",
      ":Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)\n",
      ":Date: July, 1988\n",
      "\n",
      "The famous Iris database, first used by Sir R.A. Fisher. The dataset is taken\n",
      "from Fisher's paper. Note that it's the same as in R, but not as in the UCI\n",
      "Machine Learning Repository, which has two wrong data points.\n",
      "\n",
      "This is perhaps the best known database to be found in the\n",
      "pattern recognition literature.  Fisher's paper is a classic in the field and\n",
      "is referenced frequently to this day.  (See Duda & Hart, for example.)  The\n",
      "data set contains 3 classes of 50 instances each, where each class refers to a\n",
      "type of iris plant.  One class is linearly separable from the other 2; the\n",
      "latter are NOT linearly separable from each other.\n",
      "\n",
      "|details-start|\n",
      "**References**\n",
      "|details-split|\n",
      "\n",
      "- Fisher, R.A. \"The use of multiple measurements in taxonomic problems\"\n",
      "  Annual Eugenics, 7, Part II, 179-188 (1936); also in \"Contributions to\n",
      "  Mathematical Statistics\" (John Wiley, NY, 1950).\n",
      "- Duda, R.O., & Hart, P.E. (1973) Pattern Classification and Scene Analysis.\n",
      "  (Q327.D83) John Wiley & Sons.  ISBN 0-471-22361-1.  See page 218.\n",
      "- Dasarathy, B.V. (1980) \"Nosing Around the Neighborhood: A New System\n",
      "  Structure and Classification Rule for Recognition in Partially Exposed\n",
      "  Environments\".  IEEE Transactions on Pattern Analysis and Machine\n",
      "  Intelligence, Vol. PAMI-2, No. 1, 67-71.\n",
      "- Gates, G.W. (1972) \"The Reduced Nearest Neighbor Rule\".  IEEE Transactions\n",
      "  on Information Theory, May 1972, 431-433.\n",
      "- See also: 1988 MLC Proceedings, 54-64.  Cheeseman et al\"s AUTOCLASS II\n",
      "  conceptual clustering system finds 3 classes in the data.\n",
      "- Many, many more ...\n",
      "\n",
      "|details-end|\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn import datasets\n",
    "iris = datasets.load_iris()\n",
    "print(iris.DESCR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sl = iris.data[:,0:1]\n",
    "sw = iris.data[:,1:2]\n",
    "plt.plot(sl,sw, '.k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decision boundaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "t = np.linspace(-10,10, 100)\n",
    "sig = 1/(1+np.exp(-t-4))\n",
    "plt.plot(t,sig, '.b', label=r\"$\\sigma$\")\n",
    "plt.legend(loc='upper left', fontsize =20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Iris-Setosa Classifier based on petal width"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = iris.data[:,3:4]\n",
    "y = (iris.target == 0).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(random_state=42)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "mylr = LogisticRegression(solver='lbfgs', random_state=42)\n",
    "mylr.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Xnew = np.linspace(-1,3,100).reshape(-1,1)\n",
    "yPred = mylr.predict_proba(Xnew)\n",
    "#plt.plot(Xnew,yPred[:,0], label='No Iris')\n",
    "plt.plot(Xnew,yPred[:,1], label='Yes Iris')\n",
    "plt.legend()\n",
    "plt.plot(X,y,'og')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Iris-Setosa petal length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(random_state=42)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = iris.data[:,2:3]\n",
    "y = (iris.target == 0).astype(int)\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "mylr = LogisticRegression(solver='lbfgs', random_state=42)\n",
    "mylr.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Xnew = np.linspace(0,8,100).reshape(-1,1)\n",
    "yPred = mylr.predict_proba(Xnew)\n",
    "#plt.plot(Xnew,yPred[:,0], label='No Iris')\n",
    "plt.plot(Xnew,yPred[:,1], label='Yes Iris')\n",
    "plt.legend()\n",
    "plt.plot(X,y,'og')\n",
    "plt.axis([1.5, 5, -0.1, 1.1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Iris-Setosa Sepal-Length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(random_state=42)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(random_state=42)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = iris.data[:,0:1]\n",
    "y = (iris.target == 0).astype(int)\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "mylr = LogisticRegression(solver='lbfgs', random_state=42)\n",
    "mylr.fit(X,y)"
   ]
  },
  {
   "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": [
    "Xnew = np.linspace(0,8,100).reshape(-1,1)\n",
    "yPred = mylr.predict_proba(Xnew)\n",
    "#plt.plot(Xnew,yPred[:,0], label='No Iris')\n",
    "plt.plot(Xnew,yPred[:,1], label='Yes Iris')\n",
    "plt.legend()\n",
    "plt.plot(X,y,'og')\n",
    "plt.axis([3.5, 7, -0.1, 1.1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiple features classifier"
   ]
  },
  {
   "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": [
    "import matplotlib.pyplot as plt\n",
    "sl = iris.data[:,0:1]\n",
    "sw = iris.data[:,1:2]\n",
    "tg = iris.target\n",
    "plt.plot(sl[tg==0,0], sw[tg==0,0],'.g' ,label='Set')\n",
    "plt.plot(sl[tg==1,0], sw[tg==1,0],'.r', label='Ver')\n",
    "plt.plot(sl[tg==2,0], sw[tg==2,0],'.b', label='Vir')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "X = iris.data[:,0:2]\n",
    "y = (iris.target==2).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-13 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-13 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-13 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-13 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-13 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-13 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-13 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-13 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-13 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-13 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-13 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-13 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-13 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-13 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-13 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-13\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(C=100, random_state=22, solver=&#x27;newton-cg&#x27;, tol=1e-05)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-13\" type=\"checkbox\" checked><label for=\"sk-estimator-id-13\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(C=100, random_state=22, solver=&#x27;newton-cg&#x27;, tol=1e-05)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(C=100, random_state=22, solver='newton-cg', tol=1e-05)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mylrvir = LogisticRegression(\n",
    "    random_state=22,\n",
    "    tol=1e-5,\n",
    "    C=100,\n",
    "    max_iter=100,\n",
    "    solver='newton-cg'\n",
    ")\n",
    "mylrvir.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "x0, x1 = np.meshgrid(\n",
    "    np.linspace(3,8,100).reshape(-1,1),\n",
    "    np.linspace(0,6,100).reshape(-1,1)\n",
    ")\n",
    "Xnew = np.c_[x0.ravel(), x1.ravel()]\n",
    "yPred = mylrvir.predict_proba(Xnew)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(X[y==0,0], X[y==0,1],'bs',label='No Virg')\n",
    "plt.plot(X[y==1,0], X[y==1,1],'g^',label='Virginica')\n",
    "zz=yPred[:,1].reshape(x0.shape)\n",
    "contour=plt.contour(x0,x1,zz)\n",
    "plt.clabel(contour, inline=1,fontsize=15)\n",
    "plt.xlabel(\"Sepal Length\")\n",
    "plt.ylabel(\"Sepal Width\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Path3DCollection at 0x16c24cda0>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =plt.subplots(subplot_kw={\"projection\": \"3d\"})\n",
    "surf = ax.plot_surface(x0,x1,zz, cmap='jet')\n",
    "ax.scatter(iris.data[:,0:1], iris.data[:,1:2], y, 'or')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multiple features and muticlass classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-18 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-18 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-18 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-18 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-18 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-18 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-18 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-18 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-18 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-18 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-18 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-18 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-18 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-18 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-18 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-18\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression(C=100, multi_class=&#x27;multinomial&#x27;, random_state=22)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-18\" type=\"checkbox\" checked><label for=\"sk-estimator-id-18\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(C=100, multi_class=&#x27;multinomial&#x27;, random_state=22)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LogisticRegression(C=100, multi_class='multinomial', random_state=22)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = iris.data[:,0:2]\n",
    "y = iris.target\n",
    "lrmc = LogisticRegression(\n",
    "    multi_class='multinomial',\n",
    "    solver='lbfgs',\n",
    "    C=100,\n",
    "    random_state=22\n",
    ")\n",
    "lrmc.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n",
       "       2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "x0, x1 = np.meshgrid(\n",
    "    np.linspace(3,8,100).reshape(-1,1),\n",
    "    np.linspace(0,6,100).reshape(-1,1)\n",
    ")\n",
    "Xnew = np.c_[x0.ravel(), x1.ravel()]\n",
    "yPred = lrmc.predict_proba(Xnew)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(X[y==0,0], X[y==0,1],'.b',label='Setosa')\n",
    "plt.plot(X[y==1,0], X[y==1,1],'+g',label='Versi')\n",
    "plt.plot(X[y==2,0], X[y==2,1],'*m',label='Virgi')\n",
    "zz=yPred[:,1].reshape(x0.shape)\n",
    "contour=plt.contour(x0,x1,zz)\n",
    "plt.clabel(contour, inline=1,fontsize=15)\n",
    "plt.xlabel(\"Sepal Length\")\n",
    "plt.ylabel(\"Sepal Width\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yPred = lrmc.predict(Xnew)\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(X[y==0,0], X[y==0,1],'bs',label='Setosa')\n",
    "plt.plot(X[y==1,0], X[y==1,1],'g^',label='Versi')\n",
    "plt.plot(X[y==2,0], X[y==2,1],'*m',label='Virgi')\n",
    "zz=yPred.reshape(x0.shape)\n",
    "contour=plt.contourf(x0,x1,zz, cmap='jet', alpha=0.3)\n",
    "plt.clabel(contour, inline=1,fontsize=15)\n",
    "plt.xlabel(\"Sepal Length\")\n",
    "plt.ylabel(\"Sepal Width\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rEREY7qz3Mgzi2eXQU2u5XK54Y+tkYDKZlpGBTkjbhU4as7OzdHd309zczMGDBzd1U7+eI571sNIiq3eDjY2NkUgkcLvdy4hoK63buy3i0Vv5N4LNWkDoc1arubOCQUT3Egzi2cVQVRVZloupNUEQmJ6e5ubNm7S0tNDW1rbsxtop4gEYGxsjGo2uq3SwGtYiHkEQiovFRp/870QEtVVsdrE3m83L7A0kSVpVzFOfIdpI6/ZuI561Ip71sJ4FRHd3d5Gs9VmiciIqdWcFih12eiu84c66e2AQzy5E6U2kLy6KotDT00MwGOTEiRPF+ZNS7MTinEgkSKfTQL5rbav6Zqsdi6ZpjI+P09/fD4DX6y26j75RbA6sVuuy1u1SDbWbN2+Sy+WKM0QVFRVFxYBybGehvxPYTMSzHsotIHSyjkQi61pAQP7czM3Nsbi4yPHjxwEMd9ZdBIN4dhnKLakFQSAWi9HZ2YnD4eD8+fOrFqq3G/FMT0/T29uL2WzmwIED2xLVXIl4crkc3d3dRCKRov9PNBolFAoxNTWFqqrF1EpFRcWyFuXdEvHciWMoF/Ms11ArPS+6YkDpedktuJMRWDlZl1pADAwMkM1mbyMioBjpGO6suwsG8ewilM7m6F08Y2NjDA0NsX//fvbu3bvmjbFV4pFlmZs3b7KwsMCJEyeKw4DbQTlRxGIxOjo6cDqdXLhwoRjFuVyuZTYHoVCoOBmvtyhXVFQgy/KOFeR3M1bSUEskEsVFtlQxQJIkXC7Xrkm53c0IbCMWEHqXXDgcvk15wnBnfW1hEM8uwEqzOZIk0dXVRTKZ5MEHHyw+wa2FrUQF8Xiczs5OLBZLUUR0ZGRkx4hH0zSmpqbo6+tj37597Nu3D0EQihFd6fa6zYHeohyLxQiFQszOzhKNRhFFEVmWl3U9vd6xWuu2Hg3FYjGWlpaKBH2nWrc3gp1MtW0WK1lADA4Okkgk6OnpWdUCAgxTvNcCBvG8xlhpNicUCnHjxg0CgQDnz5/fsGryZiIeTdOKjQp79uxh//79xafVjWq1rQV9Fqirq4ulpSVOnTpV7GDaCErVpYGifpooisWuJ73YXFFRscxd8/WM0tbtVCqFzWajoqJiWeu23W5fNh9ztwh6t9ScdAsIl8uF1Wqlvb2dVCpV7CxcywICDCK6GzCI5zWEqqrMz88TDofZt28fmqYxODjI+Pg4hw4doqmpaVMX9kaJR5Zlent7WVpa4uTJk8VOIh3rabVtBJlMhkwmQzqdXrEutVli022e29ragFvF5nJRzzdao0LpoOa+ffuWtW6XtiWXtm7fCfsHPbrdTQuxnj0oVZ7Q05fJZLJ4nlazgDDcWe8cDOJ5DVA6m5NMJllaWqKhoYHOzk5kWeahhx7C4/Fser8bSbXp/jw2m23VRoXtFvJnZmbo6enBZDLx4IMP7hgBlB5TebE5nU4X60OlBXmdiF6PNtgr/UYrtW7rC2xpN5h+Xjbaur3RY9lNZK+q6orfrTStuxkLiNXcWUuJyHBn3RgM4rnLKE+tmc1mstksL730EvX19bfZC2wGa0U8pbWW9fx5tppqUxSFmzdvMj8/T1tbG2NjYzu2EK13AzscDhobG28ryL+ebbA3EmFYrdZlbcl6N1goFOLmzZtIkrQs5bTVSFG/XnbTQquq6oaiu9UsIFZq6NCjRpfLtaYpnuHOujYM4rmLKLekVlWVqakpUqkUJ06c2JAG2lpYjXhkWaa7u5twOLyhWstWUm3JZJKOjo6imoIkSTvuQrpRMlypIF/aqNDf31+sg+j1oXuxUWErqa3SbrCVWrcVRVnWuu3xeDb0Gfr1spsW1q1aV5RaQOg26joRLS4uMjQ0tCzFWWoBYRDRxmAQz11A+WyOyWQikUjQ2dmJpmk4HI5tkw6snCLT25j1GSDdHXItbDbi0VWrGxsbaW9vx2QyFYdfdwrbuUHLGxVK6yCjo6Mkk0ncbncx/XQvNSps57ys1LqdTCaLRDQ2NoYgCMtSlk6nc8XP3K2ptp04npUsIHTl7bUsIFYioomJCeLxOAcOHHhDu7MaxHOHoc8KlEYQesqrtbWVQCBAb2/vjnxWacSjaRqTk5P09/cva2PeCDZa4yk1hDt+/Hix3rKZfWwGO7W/leogen1Ib1TQ008rKQfslsVhp89vae2jubkZVVWLKUv9SX+1lOVuTbXdiQeI0gcZXRR2IxYQQHFsQr9X36jurAbx3CGUDqjpT16yLNPT07Ms5RUOh3dMX02/mEsVAk6fPl0Uq9woNpJqS6fTdHR0oGnaiqrV6xHPZm+oO3kDWq3WNdNPqqoWFxFJknaFggLcea02k8l0W8pJF/LUF1jd2sDlcgG7j3juRgS2GQsI3fSu9LhKTfHK3Vlfr0RkEM8dwEqzOdFolM7OTlwu17KUlyiKO0o86XSal19+GZfLxYULF7ZUu1gv1bawsEBXVxd1dXVrNkPs1ohnLaylHBAMBgmHwwiCQE9PTzEieq0GNvXjvVsoNbuD5dYGs7OzAFy6dGlZyvJOtG5vFK+VPflaFhDBYBBJkrh06dK6FhClRPT444/z/ve/n8cff/yuf587AYN4dhjlltQAo6OjDA8Pc+DAAfbs2bNssdgpRWm9EycSidDW1rauvM5aWC1aUVWVwcFBJiYmOHr0KA0NDavuYyeGUMuP6bVAeaPCyMgIsVgMh8PBzMxMsVFBX2x1+f67gdd6bqbU2qCuro4rV66wf/9+wuEwIyMjJJPJ21S3t2L/sFW8VsRTjtLzpMthBQIBIpHIhi0g5ubm7uq5u9N4/XyT1xiryd7cuHGDVCrFmTNn8Pl8t71vJ4gnl8vR1dVFLBajpqaGffv2bWt/K6XaMpkMnZ2d5HI5zp07h9vtXnc/O5lqW29/dwuCIGC1Wot1M71RIRQKFeX7SxfbO9mosBvOhw5N0xBFkerq6qJyeqmQZ+mQbykR3Uli2C3EUwpFUXA4HMvO01oWEMlkkqamJlKp1KbdhT/96U/zjW98o2hEeP78ef7wD/+Q9vb2Nd/39a9/nU984hOMjY3R1tbGH/7hH/LjP/7jxf/XNI3f/u3f5m/+5m+IRCJcuHCBz33uc8Xh7o3AIJ4dwEqptaWlJbq6uqisrOTkyZOrPq3okcFWn14jkQgdHR3FGYRyDbStoDziWVpa4saNG1RVVXH69OkNPXnp32Wnnsp3a267vFGhdLHVxSp9Pl8xIlrN4mAreK0jnlKsdCzlQp6ltbOZmRlkWV7WxOF2u3eUKEqzDrsFKzU8rGUB8Sd/8id8+9vfxmQy8Q//8A8IgsAjjzyyoQHz5557jg9+8IM8+OCDyLLMxz/+cX70R3+U3t7eYk2uHC+//DKPP/44n/70p/mJn/gJvvrVr/JTP/VTXLt2jWPHjgHwR3/0R/z5n/85X/7yl9m7dy+f+MQnePvb305vb++G084G8WwT5bM5mqYxMDDAxMQEhw8fprGxcV1Fadh8B46maUXl6ra2NlpbWxkeHi6aYG0HpWQ4PDzM6Ojohr5LKe4E8eymJ/zVsNqcTCgUKkqz6E/8FRUVq7YnbwS7iXg2IhDqcDhwOBxFNfJUKlUkoomJCYBl6abtqk3cjYhHUWREcePL6EbIsFSV4ytf+QpjY2OcPXuWdDrNr/7qrzI+Ps6HPvQhPvOZz6y5nx/84AfL/v2lL32Jmpoarl69yqOPPrriez772c/yYz/2Y/zGb/wGAL/7u7/LE088wV/+5V/y+c9/Hk3T+MxnPsNv/dZv8ZM/+ZMA/P3f/z21tbV885vf5L3vfe+GzoNBPFtE6WyOLo6YTqfp7OxEVdUNp6O2Qjy6cnUikVimXL2T1te5XI4rV66QTqc5e/YsXq930/uA1dNBuvjiZtMH9xJWalTQBxHLFRW2qiy9W4hnswKhpfppumxN+bkp7RbTW7c38313gng0NAQEItEl/L58VBsdeZnM//k888ce4qWP/3dsOQstjz1G8yOP0PTII7jWcOxVFGXTqdfW1lZkWeaP/uiPOHjwIBMTE8RisU1/l2g0CrBml+vFixf56Ec/uuy1t7/97Xzzm98E8vXqubk53vrWtxb/3+fzcfbsWS5evGgQz51EuSW1yWRibm6Onp4eGhoaaG9v3/DFpd8YiqJsqCgdDofp7OzE5/Pdply9U8STyWRYXFykpqZmzTThWliLeBYWFrhx4wayLON0OpcV5lf7rHsl4lkLK03E60Z4etutw+FYttiudU3spvOxXUuElc5N6ZDmwMDAstmYioqKdYehN0M8M1PDeAPVZNIJsqkEjS0HAVj8mbO8euIhRoMx/u9//T78j74FaW6I4FMv8+Sffh8SMq6D7YQGBoiMjfHEhz9M7YkT/NQ//ROWFR6qtkI8kiSRy+WKD7ItLS2bej/kz8VHPvIRLly4UEyZrYS5ubll83gAtbW1zM3NFf9ff221bTYCg3g2AX02JxwO09HRwcMPP1zUJ1tYWLhtiHIj0G/W9QhD07Rid9zBgwdpaWm57Ubf7uKsp++mp6dxu93cf//92+qM0/dZun9dffvw4cP4fL6ilM3w8DDpdHqZ5XO5bthuWmh3Aiu1J5fqg5U2KlRUVNwm6LmbUm07bYmw0pCm3pI8NTXFzZs3cTqdq5K0fq+aTCYy2TR2W36Ac2ZikPnLT2E9dAppoIOTP/PvAVj60p8SevElvq75ON2yB+3kSWrf+z66BBs3/uYb2CIxvvCFb+C1mGh8x3luajY0pwUhkmWpt5emCxeYeOYZKtrbedtf/MWKpANbG2pNJBIAG8qgrIYPfvCDdHd38+KLL255HzsJg3g2iNIGAl2DKZFI0NHRgdVq5fz581sSntQHxdYinmw2WzSFW607DrYX8ejpu3g8TktLC5lMZttPsHCLLLLZLDdu3CCTyXDu3Dnsdju5XG5Zd08mkyEUChUjgFKF6d00uHmnFnuz2bxiV5gu6JnL5ZYV43cT8dxpE7jS2Zj9+/eTy+WKskd9/T3kchoWiwmPy05zywG8Xi8N/+MPeX7gUZampvjZj/4elopKIhODWP/2v/PP42k82SyLn/4Lmh95lFca/Sz2LOKLjjB08TpD//jPtHzyk1w9fJjs/UeomFvE1T9MwKTS9+0XQQMBsDbX0Hj0FJlwmKYLF/iJL38ZZ+H3WwlbaXhIJBLFtO1W8KEPfYjvfOc7PP/88zQ1Na25bV1dHfPz88tem5+fLzaI6H/Pz89TX1+/bJsTJ05s+JgM4tkAymdzRFFEURQuXbp0m4naVrAWYYRCITo7OzdkCrdV4olGo1y/fh2Px8OFCxeYmZkhlUptej+lKCUePUIMBALF1N1K3Xd2u52GhoZi8Xmlwc3e3t5iam4junP3MlZqVNClfSYmJpBlmfHxcbLZ7Jo6ancDd4oEVU3FJOTvrZmJQWKLU1S0HGTh5hWOPfqTVFdXk/vi7yGNjPFtcwXHDhwmvf8g6aZWKuYWufJnX8Axu8h//4v/QVOlD/Xxn+Wq7KVyfhJFUegORoiMfYWYakaqryF432EeuNGFNZ1mLKNSfb0n//2AVhtkVahtrmTWBYyEcTTWMPqDH7DnbW/jXX//91hW6RbTsZVUm95Kvdk1RtM0fvVXf5V//ud/5tlnn2Xv3r3rvufcuXM89dRTfOQjHym+9sQTT3Du3DkA9u7dS11dHU899VSRaGKxGJcvX+ZXfuVXNnxsBvGsgZVmc3K5HDdv3gRY0URtK1iJMEo7ytrb22lubl73xt5sqk0XLRwYGFg23LpTDqQAk5OTjI6OFjvvNtMVVzq4OTk5yfz8PDabjcnJyWJLqP4UfC8Je24FpY0KejH+4sWLOJ3OZTpqOilvpAayk9hqqk0v3ieSMUTRjMPuJJ1JMfQHv0b07JuRuq/ylt/4YwAWuy7h/tPf53MxG9UeD9maL9H0Uz/NTZuXgSuTuBc7GONpxoADVW6+f/QYQqsHcyoD0ThqLMrUX/0tNaqG5Hbi83upX5ojLIOmyHgmZ3BNzSJ6bYxJELCJdJ99AFM2S0VOZuxad/6gJ4LgtcL9dSCrnP5//18e+eQnMW2gFroV4kkkElvq8PvgBz/IV7/6Vb71rW/h8XiKNRifz1fMzvy7f/fvaGxs5NOf/jQAH/7wh3nsscf4kz/5E975znfyta99jStXrvDXf/3XQP46/MhHPsLv/d7vFQfVP/GJT9DQ0MBP/dRPbfjYDOJZBSvN5kQiETo7O4u51tVSXptFOfHoaanNdpRtJuIptUp44IEHinUG2BkHUv28TUxM3Lb/rUDXrdq/f38x1VLuQFqahvJ6vXfkCXw3pftMJhO1tbXFifhSfbDSGohOzHdSUWG9VNvczCh2lwcBgeDsOPsOnQJg+Ff+FdPeCq4nFN75np/nwIU3kUnFEV9+mWf/6RmcU3NM/+kXaTnUxuCHfpXpefBMjJABngMannyKabeP6IG9BA8f4OgrV/GqMiNLCRqeuwSAJggcsENOA09VgKVUFnMqjRDwMph3LUDzuJm97xDZgJfAE88BEM4qVHb0ktjbjLWrjyozuESI11UR9AgIr8xQ9x/fyWP/+fc2dI70utNmiSeZTK46d7MWPve5zwHwpje9adnrX/ziF/m5n/s5IH9/lj4wnD9/nq9+9av81m/9Fh//+Mdpa2vjm9/85rKGhI997GMkk0n+/b//90QiER5++GF+8IMfbKoj0yCeFaB7rZd2xejRR1tbG83NzTzxxBM7Lu4JEAwG6ezsXHfwdL39rIVSq4SV9Ny2G/EkEgmuX78OwKlTp4rt3ttB+aJWPnSnp6FCoRCTk5MAyzqgNtuKe69A/07l+mClNRDdebRcNWCnIsR0JlWMeGanR5h78ftYjzxI9sbLnPq3HwFg9ltfxvO/v85XLNW07WvDfOAA9f/3zzMo2Lj2jRdwzC/x7a/8HxyiQNupY/zA04jLnJ/tWUxK2Lp6SPzSB3EBoSNtHEgmqZifYTwDQihK7SsdaIDXY2MpKVPvsvDqyRO4JmdwBHwMdRQU4BdCaB4X0296iIrBYeossJgDGbDGEjS8dIUo4DJBpd/NC2dOUdHVj6CqLKmgAOloCuYllL//CU789Edhg8uAfm/erYhnI/fws88+e9tr7373u3n3u9+96nsEQeB3fud3+J3f+Z1NHU8pDOIpQakltX4jlRbF9ehD/0H1p/rtwmQyoSgKg4ODjI2NbXpYU8d6qTZN04pPw2u5kG6nO252dpbu7m5aW1sZGRlZ9Sl7pyVzyh1I4/E4oVCIhYUFBgcHi+rAeirqXjR+K8dadRWLxXJbo4JeH1qpUWEtw7dELobb4iUUmsckisV5lpFffgf9595CbGCAh37uPyAIArG5ccQv/jX/PPYZXJLE0p/9HS2PPUZH+x7mhuL4QpMsvHSN/wU0//5/pa+tncihA9hqq6m+cZNqUaP7ShcNhZ9aqwpwMBEmo4LZYUVNpPHfHEJormUoAyKQbd/HQkMtisOO6XvPoAGpZI6qjl4i7fvwTEzTbM3XaRY9PkJ1NTQ//TKRwvcLiDB+cC9Zt5PgsYNUdQ9gM8FiMkPrD/LRD9UVtMVCSEDaLKB+7afgJw9iTW78OirNnmwGqVRqSxHPboZBPAWsNJuzuLhIV1cX1dXVnDp1qhh9CIKwo6rSgiAwMDAAwEMPPbQhOYyVsFbEI8syvb29LC0tretCupVUm6qq9PX1MTMzw/33309NTQ1jY2M7lpraDFGVzoTs2bMHRVGKemq6KKNu/LZSm/K9gs2cW5vNRn19PfX19auqBpS2Jpc2Ksy98G+ZnpZ58Yc2fuTCm7n/x34Ce+teZueCXP+9v8S+FOb/fO4fqa/yYXv3v+FiykHlzCga0L0UJjr290RUkWxTA0tHD3KifwBXJMJ4Flzd/bgoFO/tkFWgIeCiq7oW7/AEYl0Ng93h/JeQ0oQO7SO2t4Wqjm7sAmQ0EGcXcNjtVHVexGyCKjOIbieXjx+j4bnLCMAk4BNB00BMZ5l+9Az3DQ5jXggS18B7tQs9od1gF0DVsHicTLdWERgYQfC5GVkMYTXBof/4Y1z9yfycj1W788SjRzyvJ7zhiafUN0d/gtQ0jb6+PqamplZVYdajlO1icXGRRCKB3+/fsA7aaliNePS2b4vFwvnz59fNxW421ZbJZLh+/fpt3jw7PfS51X2JolhUB4blxm+lT/86Ebnd7nsiLbfVTjJdNUCODlGzvxGL41gxQhx/5Uv8y3/+CyrqndQ8eIr6tz/OxbEapj/xPRzxJC9/62kufuwTHG6o4In2diytFiyJFGSyEI0y9LkvUKVpZCr8+ANemqcnWMyBpih4xyZxT0wjVvsYl6DSDP1nTpPLSihOB8ILr+QPMJTEmVtg8YHj1EdjNNsgKkPC4QRRZM/3nyVEvp25yQodJ46iJFPknA5IpcmqkEnlaHzuMpkKP/baSvaNDJNQIRqK4gtF8Y1MoNUEiKjgEWHkwoMIqQw5hw3xxSsoAEsxKpZiTLz1YfaNTbLXDj8agKfb/cVzGV+K4/K5NnTf6o0Fm/3NdIfc1xPe0MRTbkktCAKpVIrOzk4gX2hb7UljuxFPqcWALqmyXdnzlQhjZmaGnp4eWltbOXDgwIaetjZDGEtLS3R2dlJbW8vhw4eXRQ5r3WCvpRFcufGb/vQfCoUYGxsrDnbqabmtzGfdLWzkvEy+8hWik920PvpzeKoPAzDwxB/yLz/3hyhZmbpzFTS/6RSuhhqu/NpXUVIQnU4zeuUJWp54gtlkJUv3H0FQVfa/co1qUaN3JkTjzEUAFLuN/bZ8ncTndxOMpTAnUsuK96aAj4n7D5NzOXE99QIasCSDq2+IZGMd1V191FrAboKk08NAbQ11l66jAROAXwTR7yXj9zF74QH2XuvGncsQkqHq+cv547BY2OcQUFUNbFbisoY9FMFUXcGEBLIGpoCX6cMHyQa8OJ95mawGWRnqXniV6cceov7iVaoKxxH2+Og9dpiWJ1/E1NrIv6oEtwim2lvNPhNDEwwkBzZUP9uqI2oqlTKI5/WC0tkcvUNoenqa3t5empqaaG9vX3OR3s6wpq7pJssy586do7+/f8c01vT9KIpCX18fc3NzxdTXVvazGjRNY2RkhJGREQ4fPrziYNpOu5DeiY6ycs0wVVWLT/+6y2ap385O1fW2C1nJ3hbx9H3vd+n9n/9Ey5vO0Pro41S1/Qg3/udHeOZXv4QqaSB8jorjTlrevp/p526iqSqqBDPPhdB4ltnnZCxegeqDbqxqHLMZRvrATJCG2SCyzYrfJhLLyjS7zLx65CjuiWlM1ZUMd/fnDyIbJ9XcQPRAK76pWSrMEJJBFcA9M49/YJQ0EDBDhQjPnjhGzZUbiFKOefJpsmQmi3tqlvkH7qMxnaZhcJD5HEhTczRM5VuC3dV+tHCGKgu8ev8JfP0jhI8dxPLSlXytP5tEdTmZePujtI1N4hfzRKeGYygWkT3ffZoUeULzWk08+yNvpv6lK8XjMAG+aju1r3TS80vv5d+caMf9R58CIO3JL5uiJnL+7HkymUwxbXnz5s2iIrlORLoCx1bVsrfa1bab8YYjnpVmcxRFobu7m8XFRU6cOFEsyK4FfYh0s9DdO0sjhJ3SWNP3k0ql6OjoQBCELSkqrEcYpSKla7V772Sq7W6lvkwmEz6fD5/Px969e2/z20kmk1gsFoaHh4v1obstvf/cFz9K58e/SOB+F8pbTrP/R36WiRe/yaX/8i+gwdi3xkH4Os0/7kKKZKk67SI2lCAbBotPouOPu/Lf1SJQedqEs95EYlwDEXIxjZCcpLISJobA5YGFw8eI2F2YcjnMF68BEJZl3NNz5AI+HOk0rTbIqBB3eYgL0PTMRZJAEmiwwExjHSmfFzGZxjM9h1WA6Rw0P/0SqigSPbSf02PDpBUIZXNYVYnaKzcQDu5lWgKrCUzt+5mqrkS2WRGeehFNg6AMta90MPWmc7jmFmi2gaTCvGpi4YHj7P3u08jAEuAUIHHmBIKmEd3bjG90krgCTpPIvu88hSYIJA7s4djkGCIwOh9k9Gd/ghf+++/x/r/9SvH8J93531uv79jt9mX1s5Ws030+X7GhZbMp0kQiseW6727FG4p4VprNicVidHZ2YrfbuXDhwoZ70TdLFqqqMjAwwOTk5G11o50kHkVRePnll2lsbFw3altrP6sRRjQaLfr/rKeksNPE81rM0JT77QwMDJBIJMhkMvT09CDL8rK27e1K+a+G1Pf+LUo2xbN9KkOfeRYtrbH4cozglWeYfOYFwl0K1WfMiFaR5FwWe8DM5HeThXcnsAag5iEzggBVD4pEbiqYHVaUtMzkd/KpZosHqh80Ywm7iU9GAEjGwbQUwScFcU/N4rea8Aoqmt1Gt81KoG8YgHGg1pJv405XVxLb28y+3gEqI2EWZaCrH/2Kb6n2QixGpUVkyO7BEYqQq/Az3JdvMjCJJhZPHiLeWEf79e58C7MK9A2j1VbR8uSLOB02KpUsimji4oXztDz5YvE4RMDbUIktEmP6sYfYOzKGMDmHzwypyx00Fo7D57ZTmcuQFUWSdQFccwtYonHiSp7QGt52hr/8ymdAELBns8XfIunJ/75Wbm8sWEmRPJlMEg6HmZubI5PJ8MILL6zayLESksnkMnma1wPeMMSz0mzO+Pg4g4ODRTfJzSwYm2kuSKfTdHR0oKrqinWjnWhUUFWVkZERAI4ePbqtC3WlRV7TNKampujr62P//v0bstZ+PShKl8NsNuN0Ojl06FBxUdEbFUZGRpbZHOyIekA6DI4A2alhvvX1SUKX4whWgcD9HhzVadBg5hkZVFi8LONsVDE7TSQnFWofNoOqkY3ZkOMZ5l+8JVPkP2LC7HBidsepuE8k3Kvg3iMS7FTIBiMAON3Q2AqXK+uwDuVnoyKSissK83EJT2KG0JE2nA47R3q6mMxALpeh5mo+ojLvaSASDFNrgaHDh5EiMeJ7mqEw2AkK1myc8R99FHc8eWumRlXIuZzs+85T5ACbADVmGDnzAK6pWQCS6SwSUOkUaXnyRSIH9iDXVHLi1auowMzMIlUzi/lP8bqptAACpB64j2wsgZhO4w0GGckC2QyuWIbZh07hEsBxNcg7AjD++L+CwjVeSjyJgmTaRjraBEHA7Xbjdrsxm83Mzs4W7cFLFSfK7R9KsRX30d2O1z3x6Km10dFRMpkMbW1tRavoeDy+5an6jTYXzM/P093dTV1dHYcOHVqxuLjdiEcnNp28NquQXY7yGo+iKPT09GyoFbt8P/d6xFOO0mMoXVRaWlpusznQ1QNKZX0220Di+q/3E1xU+F4oQLqwCmtZDSWtEOlVSM1oWH0CvnYTFp9Ael4gfCNvBpialak8JZKclLBXQd2jZuS0hsmsEbqhIifDxc+pe8yMnNIIHBPJ9FuIzKWpqoWhm1ChXgEgtqeJU0tzZCQZ0SRgkhUCvYPkTh1jJANmAVwNtfS37SXnsLP3+8/mj0MCa88A4bMn8Q2NUe9zYE6nCWsmhk4dp/WHzwMwCzgE8OxpZFo0sXS8naqeAUyaRhawvHQFP5CqreKgmsMejzIn569T/9AY6VQ637mmgKOmgqHDByGXY0//MAsF+xrnlRtkDh1AtVpxWc34FYmQycpY234q+oawpDOc88IRJ3S5bi32tkyeeDSrDcWqp9o291ChKApms7mYytVb/XX7B72mqM+c5XI5/H7/lrrann/+ef74j/+Yq1evMjs7yz//8z+vKWnzcz/3c3z5y1++7fUjR47Q05PXq/vkJz/Jpz71qWX/397eTl9f36aODV7nxFOaWsvlcqRSKUKhEDdu3MDv93PhwoUty4isV+NRVZX+/n6mp6fXjUC2QzyLi4vcuHGDuro69u/fz7PPPrttA6zSVFsymaSjowNRFDfUil2K3dJOfbdQbnOgqweEQiEGBwfJZDJ4vd4iEW3EBntoQuQb342QzcUBEOwm3O+swJlQSS9kYFZDimqYLALzz8soWXA2CHj2ilh8AsGrOXJRyEUhPqxS95iZhYsKvnYRq7eCbCyIvVJg7tkS0VZBZm9+zaZpL/Sla7AvhEg01TM0NpXfBJXF+w6RaK6neWgckXzXmLIUwlJfS9OzlzDbbdSqWUSg+9R91L+UJ7BZ8vUWu0PEHoww/ehZvJEoLT19CAKERqdpHJ0GwFZbSXU4iCBAZk8TtrEpJI+b8NQ0yQyAQqy1kdCRNvzRGJnZeTQgvRDCWh/DOzaJnExTZwGbCa4+8ACerj5ssQSzha9bU+XAGoszf+YE9ve+iyOfzLtvRt23MhNWqUA8JdmKlVJta2Gl5oJSszvIz9vp0kdf/vKX+fznP19co5qamnjsscc29KCcTCa5//77+YVf+AV++qd/et3tP/vZz/IHf/AHxX/Lssz9999/m4LB0aNHefLJJ4v/3mon7uuWeMotqUVRJBaLce3atQ2Lbq6FtchCL+5DXu11vY4Uk8m0olrzWlBVlaGhIcbHx4s1I50It1sv0gljfn6erq6uLdeL1iIePUW10XTUvTBXU45y9YBSG2y96LyqDbam0fEn/xddL8SpC0C4wkdsJIbzrI/49/JDjwDWCqg5ZyYXA3utSHJCITWv4T0AU9/LgQDeAy6cTRksLoGZZ2RUCcJdCiZ7kKoTJpauyFQ9KGJ2CKQXZexZD6MD8eL3EH0Z5s+eAEGg0S6wlNUQrBZMisre7z4D5DNSrVZYatuLOZlGFQTkTJa4WKi5XLpOsqGW6L5mznb1kE2mWUjl8A+N5aOVvc3I5CMex74mJtweEATqB0eZkPLHYR+bYubhB0HT8C8tYJJyxFVI11TR+NxlLKk0WfLzQcnDB1FsVkxSDk2WmQOarVBxuYOc08HcmRM82NeHJZthNBhFcLp56c8+wY8lb6myR0oiHmsh1aaWEs8mhkdhYwKhZrO5OHP2B3/wB3z0ox/lzW9+M6Io8vGPf5z+/n7e/e5387WvfW3N/bzjHe/gHe94x4aPTY/CdHzzm98kHA7z8z//87cdn26NsB287oinfDbHZDKRyWSYmJggm81uSxmgFKvVZebm5uju7qahoYFDhw5taLHebMSTyWTo7Owkl8sts9hez256M1AUhRs3bnD8+PEtX2irEc/c3BxdXV3Y7Xb6+vpuS0etdnPu9ohnPTgcDhwOxzLbh1AoxNLSEsPDw1gsljwJ+X30/+6/4ur/GCy+V4jEcJ3xoSYU3I8GEKYypObS+A6YmfrurYcW7yERb6uJbFTFVgHZEGSCEmYnzD0rY7JAxf0i9moBRapi/sU5UGHpVQVng4DZZSK2lKF5X35/mQwMW300FKKVaaDCDCaPk0xVgIWTR6nu7sevySzlINk9QCWQ9XlorA7gmZwgXDg818w8qZpKFhJZsgr4XHZ6T9+PbLHQ2NFDXIG4AoxMoTx0Et/gGBafi0YlTUKBgVP3U3u5AzGXY7rwfZvqAszYrSzdf4Tqm4OYIzHcIgS7B6nTNBSrBXd9FQ3hJSJK/hqyxeLUvtKB4LEykoXq5lq+ePEbpBrqcL5wuXguIyURj6VAPMo2iGcrczzV1dXYbDY+/OEP8453vIPZ2VmmpqY2tY+t4O/+7u9461vfSmtr67LXBwcHaWhowG63c+7cOT796U9vyRH1dUU8+myOvogLgsDCwkLRydFisexYW2J5jUdRFPr7+5mZmeHYsWObWqw3Qzy6iGhVVdVtSgcbdTNdC7rpHLCM1LaCcuLRO/umpqY4fvw4fr8fRVFuU5n2+/0EAgEqKyuLKgL3YsSzFkptH1pbW4vq0qFQiLmRTt7x8iDHz8DQgpmJmMxSjZvki5Hi+x31NnxtIoIItQ+biQ0riBYzmqQy9S+5wodA7SNmBDFALhbEZAM1C3JaI9KrkpqZw+Iln3bzC2QWNUIdCqAyGYOaBohHgBqN6UfPIGYkTl3vIChDdilK43OFRfpoG5aBQVwWyFTXkZueJ3S4DceVTpYKpJOqr2H+9HFskRimwk8ZTWYQNI3mZy8iCFBjAYcJ5g8doup6D+asRJp8p1qrDVzDEyyePo5qMdN++SoVgsL4XJiGuVcB0EwC+2x5IU/2NSPNLSFmslgsZgYKg6yK28bi0YOkqyup+OGz7LHC4fe+g1RD/n51SlLxHIdKCvq3iOdW4X8rqbatpKZK26n1tu07iZmZGb7//e/z1a9+ddnrZ8+e5Utf+hLt7e3Mzs7yqU99ikceeaS4vm4GrwviKZW90VNrpdphR48eRRRFBgcH19/ZBlEa8SSTSTo7O4tzM5vtQNkI8ZT68xw6dIimpqYVra+3Uy/STef0kHu7nTSlxJPNZuns7ESSJM6dO4fD4UCSpGUq06VmZ7qumslkoqKiAqvVumuGN+8ECZaqS2uBHKICrXNgMat0piA7lcJ5xotgN6FKKupQukASeVTcL6JIIo4qsFdBpE/Be0Ak1KmQiy3kP8MOTT9uRslAalaFWY1cDEyiwPyLMkoaHHUCfo8HpznGwgxkUuAdm8JbSHPN5/IRD3U19FZWkvV5aXrxFWb1S25qjum3XsASTxGor0KemSeqQPjgXvZ+5ymA/ACpCK6GGuYyWWSHHWsiyQJ5gsl09qE5HSycPs7BYJDK2RmGs2DPhqkLhlEsFtxWE+GMQkVNgJ79e3FPzGAPeBnpzmseMjyB5vMw89hZaoZGqCl0zGmCCVHKsfc7T9Hgs/CvvQqXKm/VTJwl3WvBklSbpVDjkUuJZwuptq2I095tyZwvf/nL+P3+25oRSlN39913H2fPnqW1tZV/+qd/4hd/8Rc39Rn3PPGsNJujE4HJZCoSwdLS0o4uXKIoIssys7Oz9PT0bHtuZi2ykCSJzs7ODfnzbKWgr2kaY2NjDA0N0d7eTm1tLQsLCztiBqdpGpFIhI6ODvx+f1FsdaXvW252pqoqsVisqDKdyWS4fPlyUUUgEAjck+Ke68E88AT8PNzsNPPscwrxQhE99UoM53kfmesJbH4ztQ+b0RQNk01j4SUFNacQLeyj7jEz2aBG5UmR9JKbWH+E6rNmpn8goxVOvdVvo/ZhFSmq4agWSExopOc0Aj6B4bzXIYEaM92HTiN5XDQ+ewkF8nM5UwtI+/bkhzz3t9I8MUYiB6Gj7TQ/+RIAQfIKAK0OEzOKyuy5U/gGx/AshXCJMDW5QN3kAorZjHxoP4fGhokpgGjCkkrj7x9B8zgZzuYjoZGzp1Cs+b5oUW/JXgjjz6kkm+pxhMK02iCnwkSgimSln+anXyZYOCc+m5mpk0dBgKv/8Vf4xDe+iCmbI1nygOUoiXiWPLcWe3N2JeLZfFfbZq9XXdLpbikXaJrGF77wBd73vvetS5J+v5+DBw8yNDS06c+5p4mn3JIaKLaxtrS00NbWVnx9J9WkdYRCIebn57nvvvs2JUlTjrWOTbeN9vv9nD9/ft1QfbMRjyzLdHV1EY1GefDBB/H7/eRy+VTNTtRUlpaWmJ2d3bQDKeS/i9/vL/7p6+tj7969hMNhBgYGiuZvpV1ir4uUXHyeZwfguW/JoIHDCqZTPkzVFtJX42hZlcy8RGYh3yI995yCt82ErcqFkk1h9QrMPVPSrGKOUnfBjJzUqH3ETGpaJTGh4jngZ/I788XNPPsEfO0iuX4VhwvSSYiHZcRslr3PX0axmKm15BsAEi3NKC9dRVQUtMEx5oBKC2jj08ydO4Umihzsuok7lWA8rdLwYj4dlqoMUO8UERWFQG0lC/EUOacTeybLkG7KZrcw8/AJcg4ngctXgfwAqWd8GsVhxzc8jtdiwm9SSdTW0+/3U30jz5Tj5FWoVbOIajYz/dhDHOnqRYzGkICGF17hpT/5LW585BcRvvb5/OkuWdTt2VvEs+i8RTI68eSct8hms6m2rdR4MpkMiqLcNeWC5557jqGhoQ1FMIlEguHhYd73vvdt+nPuSeJZSfZGlmV6enoIhUIrWlJvVeJmJSQSiWJX0lYkacqxmvW1HoUcPHiQlpaWDS2qmyGeeDzO9evXcTgcnD9/vviEsxO1IkVRSKfTJJNJTp8+XTQo2yr0Ok+p+ZveHh8Oh4tpudLhzc20fu8W5JJBnvq7JwnPg69OJDqrkFPAqkL820sAWPfY8Tc7sXpjzL+QJ6fYgIp5NomvTWDxZZnKE/l2aimioCgB5p4LFT/DGoDKEyKKArUXzESHFTRZw+w0MfV9GYiDAA0tYPW7mJFyyDYr5qxEwgSyCYJDkygeF0uHDtCQzVLb18ekBEIuQf3Fa8Sa6kHTSKvQ7LbyyrGjWKNxLKk0U8HC/NB8kETbXrIVPuyZLDXmfDQlV1XgHxzDNTNPkny0U++18+yRNgI380/XsZyK1QzxYISqyTkiB/fit1lp6e8nIoN1Zp6qmQKp+t1IGjjtVr7+P/6U0Z95BzYph1B4sColHkeBYDSLlbTtFrGYC6k2yVVCPHegq60cyWRefWKzqbZEIrEsEhkdHaWjo4OKigpaWlr4zd/8Taanp/n7v//7Ze/7u7/7O86ePbvMcVTHr//6r/Oud72L1tZWZmZm+O3f/m1EUeTxxx/f1LHBPUg8K6XWotEonZ2dOJ1OLly4sGJ77k4Rj6727Pf7EQRhR5SLy8lCH3CNxWLFKGSj2GiqTf8ee/bs4cCBA8tITY8Stxrx6O3kiqLQ1ta2bdLRUX485Wm5eDxOMBgsDuI5HI4iCd0LabnExDW+/Z53MNuTLryiUOsDpwPmRTAFzKhhGS2nkZrOsPCCjCBC4JiIowHklI/FSyE0GYIdCq7WPFmng3GqHxIxWQRyCQUpKLD4igLkF2bvfhMWrwmLR6DqQSuRGzJen0o8CvGJJDX0INttzL35HOdfvphPhwHWeBJLIok6M8+klHftXLrvCItVAdyTcyQKKgPRhIQlmcK5GCRTVUGLw4QkqySqq8guBgkMjgKwADRaYLjST8TnJeew4x8exy/CVFwqyuLEWxo5GZxFyqmENQ1B0/APjGI6uJeZHKgaxA4fIF5TiWw2s+/Zi5g1ePBUG5/8mXydwpHWzzEES2b59IhHdS5PbYnZfDgmubdHPJtNxSeTSUwm06bXmStXrvDmN7+5+O+PfvSjALz//e/nS1/6ErOzs0UfJh3RaJT//b//N5/97GdX3OfU1BSPP/44wWCQ6upqHn74YS5durQhbcty3FPEUz6bAzA2Nsbg4CAHDhxYU8ZFT2dt1cNEURR6e3tZWFjgxIkTZLNZZmZmtvV9dJQSj66F5na7l0UhW9nXSlBVlZs3bzI3N7eqIOp22rJ1m4T6+nrMZvO2rR7Kj2k1lIp7wsrDm7s5LZfo+EfGfukjtDrTuA56mFuK4/BZic9IzEeBuSgI4H5LBQhgXswVu9QEEwSvqGRDIcxu8B8WsVcIJGc1wjfyXWqLl6DyhInEKFi8UPeImXQsgNURJNKrERu+dc3U7nWBlMTjBavPwcK0xNLxQ1Rd7shLzACi087QW85jSaSoWgiiAcmCNXT9S1expDN4vE4C2RSCy0VqdgHHUhjHUpgJ8jM16WCM2JE2JK+HxpEJmuZmmMmBvfNmUU+trrkG8/wCVV4HgzYnrrlF4q0NDE9MowHksoTb9xM+uIe23iHQ8k7U3ptDxKsraX7mIm63nf/LmSJ74FZrsE++9RC6aLl1jarRCACKa3mEIRYioazr1v24la62rUQ8W9H/e9Ob3rTm/fulL33pttd8Ph+pVOr2jQtYb3ZoM7gniKd0Nke3pNYVkpPJJGfOnFk3KtB/8K20NMbjcTo7O7FYLEUh0dnZ2R2rGekdcuPj4wwMDGxYC221fa12XLq0jqZpnDt3btWuta2k2kptEo4cOUJjYyNXrlx5zSRzyoc3Sz13JiYmEARhS2m5OzVLtPDnv4c6kMQNuIlTdT8MhgSqvSBpZuaSCo6TXpIvRdCy+d9FdEDzOy3IKQ0lI5ANacgJEG0CM0/LqLl8l5q9oQ5X3SLBDgUpmlc6SE6qeE8KBK+pePaZcJwUycU0RLeFhZeSxQYESDP7lvNY4kmiJ45w4JWrhGWwNdXR+r1nMalqfqEXoc4Cr4oist2GJZ0hHktRYYPxUBKbOUvwWDuZygCPXr7EaAZUJKqv5+VYxGMHWZqGeit0nzyJOLdIfE/TLV03KYlTSDH+o49iTmeot8KSBJKmkaqrZt+3n0IhP6xaa4ZLP/YjeEcnCR09yPv3BqjpuMhgyfXuKmkiyNXceviyZfKRTUJYHpmYChFP1l1CPHch1aa7j+6mh6SdwK4nnpUsqYPBIDdu3KCiomJdhWQdWyEeTdOKzQrlRmo7WTPSNI1sNsvIyMi26yGrKUuXSuscPnx43ZB/Mwt9qfZdadfdbtFXA5YpBq/kuVOaltuKptp2oeUU6t/hIb0QZzDto7MzCmQLHVkyrjcHUMMyrod85BZyZPsTVJ8xM/ndXHEf1korNWdVcjGwVQqk5zTS8xr2ZpGp7+WbDbxtpvygqEdg5skgqgTRPpVov0rdI2YWX8lS2WjDZcuSiIG52g9Pv1z8jDCw1wazGsyfO4VvcBTnYgi/qDGQAd/VLjRBIHikjZOxCNn5RUyCALKM/+YQ8+dOMZwBqwCmPU0MNTehOG20/uA5FGBaAt+VG8ydO4VvaIza2gCWcJigycLI6fuLum4z5EnGcv8hQGPxxBGqu/vRZAWrWWDvd55i5pEzfP9bf8unfvlXAEgvI55b5y1cUuPxF353U8VyPUIlmcACxMy37vm7MUD6evTigV1MPKtZUg8MDDAxMcHhw4dpbGzc8JOAXpzeKFnIskxvby9LS0srNivslJVBPB6np6en2KiwXTXjcoHP0vkfPRLZCDZqf603KDidTs6dO7csNbhbRUJX8tzRo6HXKi2n5RQqKrP8MAT9/TFq28Dm8JAZj2N2WJl55pagp+A0UfWgDzWboO4RM/FRhUxIw9nkZep7S8Xt/IdNuFpF4tMKZjfICUhOq1gDInPPyQgWExUnRGwBAZMVpn+Yb1RYmswStUJ1HSxNJJktdKn5J6Y5MDfDaBYYHKN+cAzJ7cJxcC+MjtBggXGrA00woTgdTPTm5+ZEUWDugROkqwIEhsYBkDRgdgFrRYCa5y9h8rppzCQQgMtnT9NQsMGeByyAt8qJYzHI9GNnccTiNHX04jXDXGdfMS1n8rholZIoosjN9/8Uz/1/v49qsxUbA9IldZvSiCdY0iJt09um3cu7yCyFdSNhv3UdjPSNknZnqKio2FANZqs1HiPiuUvQNI1YLEY8HqeysjJfIC24diqKsqWJ+s0MV8bjcTo6OrDZbKsKY+6ElcHU1BQ3b96koaGB2dnZ7Uvos5wQJUnixo0bpFKpTUsFbWShn52dpbu7e8UGhY3uYzfAbDbfpqmmD7GWp+VkWd7xRcD1Wy3k+pN8r87G0BUJTdGYHwRXIINdhWhIxnnWh2ATkEMSQk5k6XK0+H57nUDgqIiCSPVZM5GbMqJTQNNg+gc5YBbBDLUXRCwegeRU3vRNy6mk5gSUjEC0T8XqF/C2ubHHZJDSTI0C5Ki/eI1kXTWa005SgRYbTLXsIahoYBGx9o+gl6kzNX7iexrRzCIVPifhaAqLxYItEqXu8nUg36VWa4GpI204FvJEqcYShExgF6H+hVeI7msh0VjH6Zt9aJEY80tR/EvRvINpTSUuMe/do544QjgnYwtFqFQVRuNJTgfsPPOFP4bCIm8qjAekSiIeZ/ZWxFOqUGAtEFK23LqkQF5Cza0ZOq/dy9zcHAMDA9hstmXzZeW1Wf1B2oh48th1xKNHObq/yYULF4r6Z/X19ataC2wE66XHSj1nVltMS/e11YhHb1RYXFzk5MmT2O12pqen13/jBqATjz606fP5OHfu3KZVuNeyvy5V3l7LVnu3RjzrweFw0NjYuGJaLhqNYjabEQRhZ9JymsZMX4RnRiEznMPmgooaF/baJMkFKwsjOUCFy1Fsh10oIRnBDNXnfAhaklxWITOb11rTu9T8R0yIDgGLW0C0CoR6VLwHBGLDKum5/Dm0eMF9tBWne5roUP6ekCIa2bBCelEiGQWvH6xNNXRU7cU1s0BgYJQoedsBLZnCIpjIOrw4DrTgHZ9A1iCpKkVdtxD5eovqdzNcU4VJyuEbncRhyhutydd68ADx5npqfR5qBgeYLfCBb2QCTRCIJzKkZPBW+bl59BCClCMwOZ0fYgVMHb2I+1rIuV2YcxJv9sN9h5uKpAMgFkgjUaJE4JRuKRQsuW8XA82UNBcIqoogF8jLfWvtaWttQ2gViorSutpGT08Pbre7+LBSKr651RrP6w27hnjKZ3MsFguyLNPd3c3c3Nym9c9WwlrEo39WOBzekOfMViOeRCJBR0cHFoulGE2lUqkdHW4NBoPcvHmTAwcOsGfPni03Kay00GezWTo6OooCpWvdFK8HW4TytNzAwADpdBpN03YkLTf45Y/T3Zmf8AfIJvNdapPXQc4m8TjAV+0mcthGpjOOPC8BEovTUH3WTHxQw90s4msXiM/5cVSEiHSqyCXNSZ77mrHaZ3DUmDC7VOLDKr52kVDHDOF0fgV3NghUnjSTDtlJzuYL6bEI+GtVaq50YU5lSO9v5dDUeN5eO5HCHUvgnp4jDfgtkNYg2VhL5OBeXNPztC0tEImmyM4FaZzLV6uCD52i5fq1fMuzx4MQiZOp8JMZGMmn8IBw+34i+5uxR+KkR8bRgNhSBFs4imdiGrMkUW8FiwA3Dx/FPjaJJZmm8WffztkXpomXNc2YClFMYlnEk39NEwTCjlsZDUth29J6kKdkqDTlyv9SFs2KQP53LlWUhnymQbe+1vUH9WxDPB7H7/dvOOV2t+Vy7hZ2BfGsNJsjSRKZTIZEIsGFCxd2ZF5mNeKJxWJ0dHQUByk3kvLaSsSjz86Uqyrof2/XR0eWZRKJBLIsb7tJYSXSiEQiXL9+nYqKitsESje6j/L/38zx7AboMxUHDx4Ebk/LAUUSWqtbTlMVXvkv7+SlP79VuPfUiNQdUkhNaVjsIGchnga/KJD4YRAEsB12Yan04LFnmX8hjJqFyE0FboLvtJ1ot4r/iIjZJZCaUnE2mZh7YYq4eut3aHibGSUNrrZqcjMzZJbAe0Bk6gc5NCUEAlTWQEUNzOcETDkZk6riGB5Hs8GUBAgSC6ePk3M7OTS3wFz/KBpQcyUvMDtz4UGSE1PUWCBeXc20rBE9sIe6VzqY0DVMpTjjb38MMZPFVl1JbmIGGchU+Gl58iVEKYdgEqgza0j797KkqViicUyaxizQaAXHzUESDbV8/5//mre98iq88B1yjjLiyeWJI16iRKBL42gOF1rJPaeLgaZKFntvqe21WzeBW72xwGq1UltbWzRkTKfTzM/PE4vFivVcXQh3Pbv0uymXczfxmhPPSpbUk5OTRVe7M2fObGsxLkU58WiaxuTkJP39/Zu2v9Yjgo2QhaIo9PX1MTc3t2JqaieIJ5lMcv36dVRVZc+ePTuiFKATa+l52oz0zUYins3MVe3GetFaabm1uuWEH36aimsvc+Q+B6N9aTIS+OpFBp9XgBQIUN3ixJ9LEcmq+Ts1B9mhJGafh9knw5idUPGAiNkFol1g+l/ycvlLVxQQoe68mWi/gutoC27PFNFhBX+7mZkndDmdGRCh8UfNKNm8mkGoW0PNqri9MNgNsAh2Gwsnj+Lwe0m9cBEVELIS1Ve7mHnsIeL9ozhNEHBaefXE/eQcdlqfeIFU/pvA9CLhNz2EZ3KW2MljHOnoYFGC2AP30fLD5xE0jTT5LrV9lS6mrBYibXvzKgWqitUCc/2jVGmQCfjQWhq5r7+XhRxIVV6+/43/j+CJo1heymvESWUPqUKBZGKlCgXSyoOieiNCsuR1T6bE9tqdv1Y3M8PjcDioqqpifHychx9+mEQiUYyIRkdHlylulFtfJxIJI+LZSeipNb1rTZe96e7uJhKJcPToUbq6unb0SbeUeHK5XPGzthId6Lna9chCn+LXlatXitxKiWcr0Gtgzc3NpNPpHZnQ14m11PZ6s+dpPeLZDOnslohnLWymW25PdJ5TE3CKNPF6+IcZMFk0ag/C4jDYPYAmMDgLkMTkEnE85MbkMZO9mc+jySmIDSq494qEnpOxVLioOJxFE1QEBOZeKBDM3DhZN/gPiaRm8y6kclwgPCISOJjLd7MVYPZYaNlnQctlqaqFpXlA01BtVjzPXGSJfHNA8MQx5htqqb7WDUBKhXRCQtA0Wp94gejeZo6GQ6jJJKnmZni2MI8zPM4M+QaFaDTOzKNnsQXDVPUM0GjVGAkmaSrM7mT8Xg6LCkoiiaXCTy6YT7dl9rcymMkbvv3w6a8RPNIGgKXQRJApIxNTLk8c0ZJ7z1FoLlDKiSer14NKiGdZqq1APFuc4Sm1w9Dt0nUhXP1hxW63k81mGR0dZXFxccOdqDo2a3v97LPPLlM50DE7O7usvPFXf/VX/PEf/3HxAfov/uIvOHPmzKaOTcdrQjwrpdYikQidnZ14PB4uXLhQ3HYrnSCrQSceXR3A5XJx4cKFLUmVb4QsNurguVXiKfe3qa2tpaura0fqRXon4cDAQFHle7PaZ2sRz9zcHGNjY/h8PiorK/H5fOv+zrsx4lkLa3XLLclzePbDdNjKP/VLxHLAlfxiWFVvxVErQdqM3wWRJIg1VqTxLLmJfDebvcZC5QkNEAhey78vF0qSGBcw2QTiIwregyac9Sai843YxMl8JATEBlXstSbsVV60XIS6x8yk51WyQRXR62bs5q3WbWtjgMlDRxCzWeSaSswLQTQNtHSmaHNgD3ipS8XQ3G4yXf0A+EYnmTcJVIkQHZsmeLydTEWAivlFDgwPM5EF5+AozsFRZJsVZ1MNyvw8dRVu+r0BXDPzhA8fYPTitfyBZCN5i+ujbTRMzbHPBj9TBb93aH/xWIvEUx7xFF6PljQROHSbg9siHj06urWtuxDxaDY7imV7xFOOUiFcyKfLI5EITz31FJ/97GcZGRkpLv5vfetbeeSRR9ZNvW3W9lpHf3//MuX70szMP/7jP/LRj36Uz3/+85w9e5bPfOYzvP3tb6e/v39LAsmvCfHoT6/63/rEe2kaRyelrUz7rvW5S0tL9Pf3b0sdAG6RxUo1o1JC2EhThMlkWrOLbCWUu5DqF+NOzRfpfkaNjY0bdlItx0rEo6oqg4ODTE5O0traSiqV4ubNm+RyOfx+P5WVlbfbQLN7Ip7tkF9pWs7x7Sn6quHb11T8DrAoIFeByw9LwzmWZoGCyUHDwQDROg1yGmpSRgnK2GstLL6aRgpreXvrgyY0/wGc1hEWX70lHGoSQZoLIqVVKk+KWLwCckYlOS6QHAqSLBybd78JW6UJzWqj6YCF6GIO0QxJRaX5qZeK36HBCjYB5h02sl4PtlgcTVHynjvBBBZRJHisnWR9DQ+/eoXJSBoNlcquflJVlZi8Lhbl/H66HjiNFomDKGDu6s+n5UIJbLLA4uljYDLR4LYQSeZI2W1kK/zs+d6z5B49w3urwex0LK/P6I0BZTUeCiRT2jZtLwyQ5lzlEU+hsaKEeFy6flup++gdUqY2m81UVVXxnve8h/e85z38zM/8DFVVVUSjUX7lV34FVVUZGxtb837YrO21jpqamlUVYP70T/+UX/7lXy5aYX/+85/nu9/9Ll/4whf4T//pP236s16zVJvJZCKdTtPV1UU6nebMmTPL2g71hU6W5S1FJOXI5XLEYjFkWeaBBx4gEAis/6Y1oM8FlRNP+bzRRguDW3UhfeCBB5Zd0NvtJNMHTlOpFC0tLRw5cmTL+yo/Ft1XKJvNcvbsWSwWS/EGSqVSBINBgsFg0Qa6oqKCysrK4m91r0U8K8H+9+8Gm5vLsxae/DqgyegNaC31EJmCqnoLJq/EwqCJOrfK5HAEbaDw3QVwv3kfVnkJURQIJzVUCeyVAotXRojnZEQ7VJ4UcdSbSE6qKJEEAMHrClUPiET6VESbiO9ELXZ3EFVRifRo5GIaMEcMqG0ERQGxoZKplj0Eeocw1VQQGZskpYLvWg+qKDL5lvPcPz6BeSKJAJgUBTGTpbJngIlIGqsAwp5mBve1Yo3FqXu1EwmYkcA2MYNqFhGzEv6Wetxzs0RtTqLVFdQXIp0Z8uKjWlM9ktfN9f/wyxz+iR/B8v73opQRjE48qZKIR5QVhMI9GiohE0dBGkcqFwMt7CNaYnvtLqTf1G3YXm9leFR/38MPP8wHPvABIH/v36mHMF2D8tixY3zyk58sZp4kSeLq1av85m/+ZnFbk8nEW9/6Vi5evLilz3rNiGdhYYHOzk4qKys5efLkbR1SgiBgNpt3RJZGn2kBaGxs3Dbp6CjvbNNlaWprazl8+PCmIrWNupCOjo4yPDy8qgvpdiKeXC7HjRs3ila7m1HFXuuYId85eP36dbxeLydPnix2LkL+t3a5XLhcLlpaWorp0GAwyOjoKD09PbhcLjRNIxqN4vF4dqzh5K6j7xW++90wnaPgrQNfpRdlNoaUhIm89QwxJBCgaZ+b1GKMqv1eEg6FdG8C1/kAiWdGSBR2Z3ZBw9ssyAkNsdKHPBdEyYDFKzD1/RxoYPK6qTqWweoXCHbIyAmQEwrZ4Dz2h80Er6i4mk1UnhCJL9ZQkZtjZlRFUYC5EWqBmfOnqF0MUW2BlALzqonFk0epfaWDUCJPnRazyMDbHsWczeIdnQTyCgVmRaHmWhf2cBSlqoI9sRAicN1hIzA4BkAEMJkhp6hoJoHpx85iTqQ40tWDpKgIg2NMvf/fcPU//yoH/s8P8vu2LO8+NeuDoiXt0a7cyoOitkLEk72NePIkEylVOSik2tTSQdO7oNMGt7dTrzfmsRXU19fz+c9/ngceeIBsNsvf/u3f8qY3vYnLly9z6tSpoomm3qWno7a2ttgEtlm8ZsSTzWZpb2+noaFhzSHN7RBPqafNgQMHyBSecnYK+iKvqipDQ0OMj49vSpZmpX2thlKrhPLosHw/uZKbbaPQpW9cLhfnz5/n2rVr244w9IhQbyMv7Rxca9+lNtCQv1bm5uZIJBJ0dnYCEAgEimm5e8V3Jz3fxxPPmbhZGPOPzUE2liRgg2AWag6A3QfpGRFLpcJUd6ywYRTsAq4zfrSkgvV0E+bFeTJzOSpOmJkq6rUFcTQIVJ4wI0VUbJWQXcqrApjMZqa+l9/Oe8CEvdaNavay9OoUag7iIyrxERXXfVZmBlWq6sDuhEmtnonGFhpeeBWTqjJe+KTptzyEJZli8dQxDnT2kI4mCVR6aXnyRcTC9ee2mKgXVUbcLtRk3oZAXAqhWGBOBv/QOJGDe0nW13Df2ATpiVkyqQz+wTH8g2MsHW8nrWj4RJj57Y9y9T//KgCVhQxIrmzsQUnm6TjhKE2TlVpZl0jjFAgmc9vMTyEtVxLx6HbYSumg6V1Qpoa7007d3t5Oe3t78d/nz59neHiYP/uzP+MrX/nKHfnM14x4WlpakGV5zW22Qzy6enU8Hi962gwODpItuRC3C1EUiwX4bDa7JSkfHWsRjz5n5HQ617VK2EqqbSVvno1qta0FTdMIhULMzMysaMGw0ZSBzWajtraW4eFhHnnkkVV9dyorK/H7/bvSdyd04zt88z3vIzKtIJqgpsGBqyVNLupm6ma+lrMwBJ5qMGsQG4OGVg/mVJyo3U3WrZF8KVLYWwwCIpWnRAQBqs+JRPsUpIwNZ51cJBgECBw3kTQdQYrfLNooJCZVrBUCSy9NYbJSMI0Ds1Ng6vtjAMxP598vPOCluqOXhTP3U5NK4+vuo8IqLBMOTQP7bBA3iSycPk6gbwh7JEaFTWQwoULvIA5BINy+D3dVAO2Vq6gaCOR9dNJVFYQm5zFp4K2r5GZ7G7JoouHiNXKqxlsq4OV//WPFz3Mo+ftE8PmXnWMhlSe3+ZLr1q0PippMxOy3iEqPeNK3SePkty9Ny+nDpnLJHNDdEAjVNI1kMnnX3EdLcebMGV58Me9/VFVVhSiKzM/PL9tmfn5+y0P9r/kcz1owm83rktNKCIfDdHZ24vV6uXDhQlEuZicVpSF/MfX09FBTU8OpU6e2JZ2ymhKCrue2d+9e9u/fvyFfmo2m2taSvtlss0M5JElibm4OWZY3VetaDaXf2+v14vV6l7UsB4NB+vv7kSSp2Cm33nDeThzLRqCFRhj9rfdhFQsNMyoIAsz2QiYWxWHNtyh774f4gkBwNL/dTCJOhQckRUYBXI/40bIa2UULFjnG4qVbbb6uFgHZX4fFM03FfSLhXgVbJag5kPq6CZG3Uai9kHcmjfbnF15VgtiIgnd/XjjU5HbSUJPBJKiYTDD2aj82oO7SdTSzGZ8ZwgrMPHIGkyThHRyjyWFhZHoRZpeon11CEUXG3/4oLS++TK0F5jQRQVZI1dUQeO4Ss4BZgMWTx4g31OIfHEVTVRQgNheEg/tpfvYVom17+EByggaTTLg0WikMhJYPinoKvjq5ilupdHMynwZU7I78SS/AWohsUmURj1BoLlhaqQPOdSuytmqb01Xcao3ntVIu6OjooL6+HsgPxJ4+fZqnnnqq2JatqipPPfUUH/rQh7a0/11NPJslitIayEp20Tsh7Kl/zsjICJlMhubmZo4cObLtxa08wlAUhZs3bzI/P7+iOvZa+9kIYejSN7Isc/78+du8ebbTpBCNRrl+/TqiKBIIBO5oqqC0ZVnTNNLpNMFgkFAoxMjICGazeZmSwE40qmwWpvgUbxpReBMQ22fixZzKrMWEUCjUpKW8y+hUB8hZjUCFCc8eFVPEy/xUjHQ8AyHITWawn3CjhWUsjSJ1j5nJLmloJo3MrIa6NM5c3syTwPF8B5sgQnTBD6EQjlqB5KRG4iUFkLFW2Kk6JSOIt1qy1USKEOB05Wd41OZaZve2YpJy1IeiTA2MABoNL7yC5HYRPrSf3Og4rTYI+SpYSmUJH22j9V+eLwqHai4bEz/yIOZ0GhprYXoeWQPJ7WRfoSXbZrdSrUgk2g6QHBgjtq+F7373S/zZjzwGGkRL6jZ6tFJOPHqKL+W5tVD7C5ewbF/eYq1G82nMZFmNRx82DZY2IhQinlwp8dylVNtWiGezttef+cxn2Lt3L0ePHiWTyfC3f/u3PP300/zwhz8s7uOjH/0o73//+3nggQc4c+YMn/nMZ0gmk8Uut83iNSOejSzUmyGebDa7zBhupRrITkQ8pYrPHo+HQCCwI0/UpYSxkaHT1bARwgiHw3R0dFBZWcnRo0dXnS/YCvHoabv9+/ejKArpEovh7aDUFXW18y0IQtF3p7m5GVVVi00KExMT9Pb24vF4imk5r9d7l5oUkuAANQMXFZFXJ9X8awJUNjip0FIshEEtXJrhkIp3L4yPxjAJ4D/oJ1cvIFgEEs+FIAeRSH7b6nMiiRENz34TOf8BbOmB/OxOv0Iurn9+iLpHRBBAkUCKgxQGS8BK6EaWzEL+d/YeMJG0HaFa6mFqNP+aaXIeDyKIIkzNUGsBm8PGq21tWJJpaq/cIA7EAXM8SfRwG4KmMf3oWY5evEwqB/GWBlr/5bni2fCaoMLvYlZRSVVX4lwMImUlBAtEeodInDnBd77zBZSAH6FwDZbqqVkLBJMtuy/EQiQULUmJ6fYHgmf5eiBm8tfltLy8HipI+YhncaUOONf2bK83K9Srp9o2++C2WdtrSZL4D//hPzA9PY3T6eS+++7jySefXLaP97znPSwuLvJf/st/KboX/+AHP7it4WCj2PURz0ZSbaFQiM7OTgKBwJrGcNtRlIZbKTxd8bmjo2PHUnd6NLawsEBXV1dRiXuzC+NaEY+maUxMTDAwMLBiRFiKzUY8etqutJ4zPDy84y3Qm9mfLkWidzFms9niAKc+aFvapLATeoArwfLUt5BOw3fGzUSHNaq9sBjLd3E5nBYGCw+nFgfUHbTi0hQWZxU0DRQNIgMR3PUBEk+GEKssiPXN+FzzmN0ZZp9SQIP0vAL043nUTGpSpfKEGTmrEelV0OoOsHB5CLWQmRNMUHGhFjUnY3ObyIYUNBksblD6hhnPaJgtUNcEQwdOk45L1FzNa7DNA36zgnt2EXMyxdxDJzk2PoFpMUjUbqOmoGQAkBOh0gIhl4PQuVP4+0dwSDls2SRjoST1BRXrpePt3B8OI88v4Dp1hG898zVkpwNv+lYzUNhR2hiwCvHordAl0bsjl18/5LLoyF9YI7SShdOcyyEoCop9+XyQHvFI23Af3UqNJ5VKoWnapms8m7W9/tjHPsbHPvaxdff7oQ99aMuptXLsauJZr5261OSsvb2d5ubmNaOPrUY8pd1xpUOu2yWyUgiCwOzsLOFwmKNHj9LQ0LCl/axGPLr0TTAY3NAc02ZqPJIk0dHRgSRJyyy1d9oWYbuw2WzU19dTX1+PpmkkEgmCwSDz8/MMDAxgt9uXNSls14XU3PFVNJuLaDrHNy7B/Mithyh/pZnAfplcCNw2SGTzhKDKAoMD+WvU4zZT4ZRJt9ex1LEIgLKUQwmPwRkHs08qBUdRE1JcJRQ9wvzz+YU/Ppr/7erfZGNhKEPtOTPpRY1In0Ltw2bmXlyAgnCo2QX1P2YmlwDF7kbMpJFz+SDHeakbdyZLuqoCd1WA1pFhQphwzeQLzXWXriMFPOTUvD/O9CNnECUJcyKJu2+Q2Ry4r3ThBmKtjbgtFpyTSar8LuZSOSS/B1HKMT21wEkXCB/7f4pFfEchstHMFrLWWw+T1qI0zspioNEV7A/KB0WLYqDeW4u6p0Bosn35ftVCeJlxlhDPXUi1JZP58V5Dq20Hsd1UWzab5caNG6TT6WV2y1vd32oobWPWu+N07JRKgCRJxONxBEHYtGFbOVY6plQqxfXr1zGbzZw7d25D7ccbTbXp9Ry/339bg8Wd8NDZSSLTNbP27NlTlCoJBoO36apVVlbidrs3TX7WFz7H7LOdfOu6HUcTNB63EuqXcFghp2iMvgK6OkGFR8B3VCMdEjBbQM6BoqikMrD4whyYwH7UhaXOSjrawOIrPUBe/iY5rVJxzIw23k/VKRGLWyA5J+OsNjP7bBaYYnYKEKD+zWbkpIb/ZB2ZmQiZ2TRVD5iZ/E6eFEUWcXuhoQVSSZDtVqyZLI6lEFQHGJNARSJyYA/Jhlpkm4W25y4hqUA4RuMLr7B44gju2UWcprye2o39beQEAedCEGVxOt+SnU0SO7SfbIUf1WLmbTZ4Z2SEz5YQhLMQrWhlkY2lkB5L30Y8+ddL53UcUn4f5YOi+rBpKUnpxIN3eVrOVki1LSi3vCakuITm2LjW4FbdR0VR3BGDyN2GXR3xrEYU+uT+asOnm93fatA13dxu94ptzDtRM9LTdyaTiZaWlm23TpYv9vpQa0NDw5p6cevtZyVMT0/T29u7qu/Pbot41oIuVaI3cZQ2KYyPj2MymaioqECSpA2n5Hr6TXz7aZCVDCwBSDRUgKyAq8qMs0ZhYQiqXBDNaIQuAWQQRdh7Bpi3EQsVamQqKHEZNaUij/Zg8ZjwHzYhujQ0SWD+JRkBCF4Dqw/ce0Sigwo15x2EFxuwZIZx1ovMPq1HXbMIFoGGt5hRZah6UCRyUyGXEKio0RgoZMwspiShwweI7G9l/41e9F/BPzRGsqGG5qdeRkajzgKR/fsYaKyn4cVXMWclFgrb5mw2nDNzxPc2Eaj0Yx8cRvB6yMwv4R8c47nP/VfOPP0DeHmEeGkTQYFIVMdy0rDqrdCr2B9E3LfbH2TLtjXr25YQkrtAMOX6bYFCpGKtvyWQO9QzzFR6upjK1VO1q12nW414XC7XvTssvQZ2NfGYzeZlczeapjE0NMTY2Niqk/trYaNEUWoDsJam23a65ErrLW1tbUT0avE2oUc8pWnIraTu1nMg7evrY3Z2ds2Ou90c8awHh8NBU1MTTU1NRQVhnYjC4TCxWKwYDfl8vtsWh5k/+dfE/uE657wQ8XqYF+PYfHamOjNoGhDNX9ctB3zklqL4vSJZi0J0Li9XM90NUmEuxVJhxf6QBy2jku7Kt8Ll4irZMMiTGqlZDVeLiah2lIbWHqQwhDrz12VmIY3gncfVaCIX0ah7zEwuphEZseJutjLz9C0LbbMHpKaTCFyjug4W5/JGaZnKAPu+8xQa+TZov8/F1UceItA7iElVUYE5FawmE81Pv0ymwkfoxFFOX7+OCVC6+hBlGef8ElmgygoRRWXxwfvo/LVfZOKdP4L4w+8AEC9VkC5EPEpZR5p1BYUCuCUGGl5mf5A/z9my6EhXoQ6XioEWCE1yLU9t6a6kkufWg+eFBy+gxBRCoRALCwsMDg5is9mW2RuUPqhupcbzerVEgHso1aaLYkqStOV01EaIotSJdD0bgK2m2ko/Q6+3dHd370jaTv+O165dI5lMbutcreVAqs/nlLdhl2Ino5TXUiS0VEFYUZSikVcoFKKnpwdFUZYJnDocDsJ/9xyCCrYI1ETiKKdgbDhHU0HxZCkNNYdg/Kq+8Oevy333e5BTcar3wWI/SDlw7HcTfyqMli1cH3X1NJ6II0XSJMbzryUnVKiME72pIUU1AsdFbBUCcspGaNhM5GZ+u+iAirNRwOJ3YTLlqHvMTHJSRYqpOGtF5J5rRXUCjx96HziHmMmSaKjFPTOPooHZamHvt/Nt0Mn6GvZkUwSSCQbGZxA0DUcwgiN4HZMNxrOQ2NdAoqkeczpDayzGTP8oFlHm8n/9DRbOnsyf40L6LFZCJvYCkZQ3BlgK0UpyFdWBUjKxF1Jt5Wk5XYW6dFtdGqc8LWcrEE/adWu5tGHD7DXj9XrZs2cPiqIQiURus7/W2/hlWd5yxPN6xK6OeHTiWVxcpKuri6qqqg05X64Gs9lcjAZWWsh02ZiNOpGKorhpeZpEIsH169ex2WzLPmOn6kWZTIZUKoXT6eTcuXObbuHUsVLEo9dzAoEAx44dW/dG2u4Q6krYDUKhoihSV1dHXV1dseU1FAqxuLhYfPL1W6H1ERehoSQdoovRa0lAIQWIJqhvNZNYkmnZ5yWzFGMpAU0nYORasQcakwkO1MOCFawHHGR7k/kKvi/AzBOzaEp+KLTytIij1sToRZVsuNB+3KVQeVIkNpxBU1RqHhIRzAJKRiUxrpGZXkLvGXPvEXDWi1h9AumqY1SkuzGJYLVC85MvFo/H0lRHy+IcEQQklxNrMoU1HAWnhYEsIKUJHdpPqrYawWrB9MQLAPhGJvCOTDDz2ENkr3Wz3w5Nv/iv+UyBdOBWfSa6jHj0jrSyGk9h23KLayGXQ3M4l3Wk2SWdNMpUqHO3KxToEU/2tkaE/JlKefLXu0kzIbL82hdF8Tb7a72D8ubNm2SzWYaHh4nH41RUVGyoZqjfx7tFmX0n8ZoSz3qpGJPJRDwep6Ojg8OHD9PU1LStzyv1vSlfNHWFgFLZmPUgiuKm9N9mZ2fp7u6mtbWVAwcOLEvP7MQiPTMzw82bNxFFkVOnTm3rgi3/bfTzs1o9Z7V9bOYztrOv1wqCIOB2u3G73UWB00gkwoIZ7BVZXkhCKJGk9iDY7C6kiSSKBlOj+UU1SAyLCSqrzOQyMs3tLuLBJLEoNARMDM2qMBsCwFRhxnXOR3QAXNVm0nMyShos7rwgqEWbwFEn4D0gYvHA0lWZXAwgzcIlqDojEulVsdeYcNTuwWEOgSlGYhQSY/mIy0E3jhqw2cBqN9FX305F7xCpmkoqJInhLLAQRrRYmD13kqzfR/WLl/MnQ9PwTMwgu13UPHcDUYBqu5mrZ06j2Gy0/vB5bM31/KQ6S2dT/bLzaCqMTcRWIJ5cWarNXHg9cZvvjoRalibT7Q/KB0X11uvFEkUEZ4FgyklKb0RIugq211gRWPt6tFqtyx5Onn/+eQKBANFolLGxsTVdR3UYqbbXAJlMhpGREXK5HOfPn9+RH0Anm9JCn6Io9Pb2sri4uCmFANh4lLKWNE3psW1F3FPfv15zaWtrW9evYyMotfbW933q1KlNqeOuVydaWFjA6XRuStZmN0Q8ax2rrfMfaPn27zAQlflfl2wsxfKL5PwAeOsktGy+uaBpvwnBo5KasqKkJBYXZPLV+CR2F9QfsiDM5VNzMzkRTdawH3AS/24QE0HSgKdNwHdQJD2vIdpBSUN6TsPXDlPflxFM4D3oQrLUUdk8zuwzcl6rbUwFRnE+6CfWp+HZJ2K9TyAzrzI9fRBbrI9QBkClmpss3ncY2eWkJhjEFQwRUSBVX41rdpH6i9eJAHYBYqeOM1NTSVXnTQByGoSyMrZ4kurnLjPw3n/FTxxqxv2Fv2Kh7FrXU21R++2pNslZnmorRDxlNR5y0m1WCTadNJzLF3axQDLBkn07s3q3XDnxFOyw3QXi2eQMj/6A1dDQgNPpXNEiXW/l15sVLBbL6zrVtivbJRYWFnjppZdwOBzYbLYdY/1y87ZEIsHFixdJpVKcP39+U6Sj72+9mlEmk+GVV14hFApx/vz5Vd36tppq0/cfDoc5d+4clZWVO7I4C4JALpfj1VdfXbbvze5jJeRyOa5du8bAwABXrlzh5Zdfpq+vj4WFhVUHhndrxFMOIbFI10uLXJ6H+fksPic0t7jYexaUrEY8nZfImRpWycQglcpfP3VNFuoOgb/ags0J0105JhdhKggml4jzpBfBIWI/5kITBMweAavHxNR3ZYJXFFAhFThC80+YSc3mryNNhdhgfhZk+gcyohWqz5ipe9SM5dghglci5OL5RoS552RslSYsmUWq66F5H7h8AvMPHMc3Mk79xaukB8aIKOBvqiW6t4VUXQ3pQL712G4C0/Qce77/LO6ZeTItDey1QaPfha9/hL73/xue+sqfUeXPb6+UCXzKqXyrcqlCgb1wLUi3RTwFl9AS0rDkZARVXZV4ErfVgyQ0m52c5dazt65CnXSXp9q2Rzz6A5z+sKtbpO/du5fTp0/zyCOP0NbWhiAIjIyM8L/+1//izJkz/OM//iPJZHJTwsbPP/8873rXu4qq/9/85jfX3P4b3/gGb3vb26iursbr9XLu3Dn+5V/+Zdk2n/zkJxEEYdmfQ4cObeoclGNXpdp0587JyUmOHj2K0+nk+vXrO/p5et1IT3u1tLTQ1ta2pZbF9QZI9bbvmpqadf15tkI8K0nfxOPxHamrZLNZFhcXqa2t3VA9ZyWsFPGU2i889NBDQL52pGur9fT0rDk/sxsintWgqQqX/vkifTdB/9bRFHgEGLsCgqBQ6we73QoBielRkDMKaYBUjtqDkMuoeGvA22gnPpjBZBKIC0KJMjUoVc3UHQmCKuFsFEhNa4hOQM0V53HsNQL+Qyaw1rBweRaAXBwWr8jUXTCT6+7D2WjDs09BlUB0acw9LWMlyFRB762pzYotmmDx9HEsiRQ1nTdpMMnMzQdpmsoPkKomE40VbqzJBLN+L8JSGFGWQdUIyhALJbnxW7/KK7/760DemwdA9i5veDEX9ILCjlt1VbFARuUKBbrvTqRUGie3sn6bTjyljqKQb0RQyyIbZzE6Kncl1QVF8/+2bGF4FFh1jSlv5d+/fz/hcJi/+Zu/YXp6moqKCh577DHe+ta38oEPfGDNObzN2l4///zzvO1tb+P3f//38fv9fPGLX+Rd73oXly9f5uTJWzW4o0eP8uSTTy475u1g16Ta0uk0HR0dqKpatBeIx+NbUqdeCyaTicHBQUKh0Kppr83sa6WIRxcRHRkZ2XBtajPEo2ka4+PjDA4O3qbYsBNNClNTU0xNTeF2u7nvvvu2HG2Uv29+fp4bN26wZ88e9u/fjyzLaJpWLMq2tbWRTqeLRdnx8fHbvHl2K3LJIE/8wgX6vj8D5NuOa2utOE0ScyEJTQENjfkItNQJTPSB0w91FQ6URBoqrcyPSKiyQjIOkKE+AGkZrPsdWFrsZHoTWBrtKOMJ5p+/NcxYdUbE4hEIXbUiOvIpN03VyAYh3DMLgoDvUF7hwGSFmafy91RqOktqDmrPmZl/TiFwTGR47DTtnldwumB8MIufUfyDeSZyt+1BHRvD3VLPuGjBPzDCwgP3Yb3SiayCo28Yye1k8pGHqYzEEWdneezEPv57gXQAzLLeCl3WMKBpaBYrckkzjFBQll4su8fMK2iyOXXh0LLIRp/5ia0Q8ShlBOModLXF3eXEk0GzO1As+et5KzptwIYf3qqrq/nABz7A1NQUsizzgQ98gCeffJKXX36ZD3/4w2u+d7O215/5zGeW/fv3f//3+da3vsW3v/3tZcRjNpu3bIGwEnYF8czPz9Pd3U1dXR2HDh0q/kC6ZM5awpCbQSqVQpZlEonEuq3AG8FKEU+pi+dGFRVg44QhyzI9PT2EQqEVpW+2QzyqqnLz5k3m5uZoampCkqQdaVAonSk6fvx4seC6EhwOB42NjTQ2NhZFPkOhUFHU8MaNG1RVVVFZWblrnEiz810MfPjfkJuaxeYQyabzOmuqCoNzADn8DeAN+LCGoowtZEGDVBhS4TSNPpgek6hsAafgQDKlsbjtzHRlUDUNXogA4HzIh5pSkAJ7qN+TJNInETgiEh9WyQY13PSgWfPqBCYrJAqyOWgaUih/vqN9KmYXyLX7qdkTxGxLFIko3K3g5xr2mrwfT32bk6u1R/GMThA7sJfG5y7lnU+HJwkAE299GHM6Q7XbRjSeIaVB6MhBmp65iEnT+NEABI7uW3auzIUHyWTZU7sgy7cpFAQKczBameCvVFCWLo2OdOIpb4W2Sren5QAEKYscWP4w4yhGR2WNCNnstm2vdY+rzSCRSFBVVcXx48c5fvw4v/Zrv7ap928Fev2p/EFvcHCQhoYG7HY7586d49Of/jQtLS1b/pzXlHg0TePmzZtMT09z9OjRov+DDp2AtjJ8VY75+Xm6urowm80cPHhw26QDt0c85UoHm2ll3ghhJJNJrl+/jsViWbXdeyMqzishk8kUI87z58+zsLDA0tLSht+/EvRUW0dHB7FYbNMzRaUin/v37+fpp5+mrq6OeDxedCLVo6HKysrXTFpk/OfeifZShL3AHpNCugqGEpDL3bo2MnGwWRUmZkEUBer2atgqQVywMzJRKHSPQ5A0rcdhZkCiLgCiw8acWcDaaif5YgRUcHCdyDTUPSaiSuD3i8SGVdKzKv5DIsHrClIkTzSWCjvWvc34KkYJXi+0JydBI0jGniU2JONsFPDsFVEVGOg4zuRIPr09O5iidvQ6C2fvxzM+hXd/M66JSWYxM33+AVoKrdazhe8487ZHUHM5Fk8eRf2V93Hot36NqTKC0YknUT78KedQyzTSdOWC8nqQTcvfJ4slA5q6gnS5QoHuuxNx3d4BV65QYC+k1G4jnrK03GZ12ra6fqVSqbve1fbf/tt/I5FI8LM/+7PF186ePcuXvvQl2tvbmZ2d5VOf+hSPPPII3d3dW1ZaeU2JR9dAW80obKUutM1CrxtNTU1x7NgxRkZGdqxOUBrx6O3GpfbOm8F6jQoLCwvcuHGDxsbGNaVv1moZXw0r1Yp2woFUkiRSqRRWq5Vz585t2wvHZDJRVVVFS0sLmqYVnUhnZmbo7+/H5XKtqSawE1jpnChRCWudGWlORqpz0hlMkcwCGQWHFWqbnYi1KWZ7ChbKikZ0EdwmgcWJDE4L+PfYMbkyELQx3pUFVGYyAFlcj/qRRtO4LuSN4OLXZBrOqcw9n87P9RQQqXmIuooreKwmIj0KShpsNW5SfZMkkzII4Gs34d5jYrSnmfh4XnE6Na2hKgpWj4gvfYPqenC6ISk56anaT/1LVwGIkbc/sLU3Y43GmH7sIRzzi1T0DdNqA554gVhrE9/5wZd5RI9Ayomn0AodXyHikb3+Za/ZCtuWd6Q5CvdWzHcrm2Ap1IOWyh7edJWD8AoRT3l0ZC9EPJHyelA2g+rZXsSzlWvxbthel+KrX/0qn/rUp/jWt761rARRmrq77777OHv2LK2trfzTP/0Tv/iLv7ilz3pNiae9vb24yK0Ek8mEIAjIsrylRSudTtPZ2YmiKEVyGx8f37GhRp0surq6WFxc3HS7cfm+VjquUpmgY8eO3RYVrrQf2DjxTE5O0tfXt0x1G7Yvd7O0tMTNmzcxmUw88MADO0YC+jEJgrDMiTSXyxVrQ7qagD4nUVlZeccsDwBQVE6/SaZTgsEeK550inQ232DgccDcTIbMMECOSg94vU7UQIrJvvx3SeVAm5dwVUFwKkt1Kzi8HrITcUxOO7PPRwDITWZBhGTFA0iRG9Q9aia9oBLtU6l92AEvXGKuIJAm2qDpx83EFuyY/SpSMgNa3t564aKMNdaF6DThPyFg8QtIQY3gNRkTsDgLLm9etdo/OMbc2ZOoVgt7evqpiEeZ6x9FNzFXzGaavDaUbJahn/4xXvzL3yFVX4vtWp7UyolHVAoRj/P2iEcp+410p9FUWVebmMuhCcIyK2u/ULjuy6IjKRwGIFgS8YiygqAotw2K6hHP7cSTJVt3y7Z9K+6jW3lwvptzPF/72tf4pV/6Jb7+9a/z1re+dc1t/X4/Bw8eXGY2t1m8psRjt9vXfMov7ULbLHRxzNra2mUdZTtpfy1JEpIkkUwmOX/+/IZUn1fDSsRTajq30TSVvsCvRxqqqtLb28vCwsKK0kBbHWgtbXxoaWlhfn5+TdLZTEpwre0sFgu1tbXU1tYW1QSCwWBRR8vhcCyzPNhu6haA0CjmqcsgwPMJO899NwNaBACTAG0NArmcRs5sIpPOn0uLCDOLGbLTBf8dvwmTpCJVm1kYLgw1joPLn8GuQjwk4TzrQ7AKSDNpzH4bXL1CeLFwDCLUv8mMnBZIVd9PpdBJegFqHjIz9T0ZmALAUStQ9aCIFNEwFe56OaWiySJLlxVyMQ1no4XZ6HHuq79GLAzh2VTe9vrydZK1VZhNJjIqiEcPMuN04B6fItncgHi1iz1OE8988b+RK3SrWQr3WHaVVFvMVnavyLnbXEItcmHswVVOPBKaw7XMyrqo6+ZfXg9yqLen5VwFgsmUS+NIt6sZAJikDHLJMdwt99G7lWr7n//zf/ILv/ALfO1rX+Od73znutsnEgmGh4d53/vet+XPfM3bqdfDVuyv9QjhyJEjNDY2bmt/q0Hv0AI4c+bMtp/oy4knFotx/fp1PB7PpqRv9HO6FmlkMhmuX7+OpmmcO3duxWhgK6m2Us+fBx98EFVVmZub29Q+1sNGjqlUTaC1tRVZlgmHw4RCIfr7+5EkCb/fXySircqSmMdfwvpXH6B7CDSrjeb7IDhkJpWUqXQLDE7rxyrjroK6xkqy00H0/FguDZpDYz4BuZiEtxZ8ggWhPkdsxkRwHkBFuhzFXGdF9JpRQjlC/rO07esgMZnF3Swy+4wMyDjpJGOGhreZUSWoPCkS7NYgl6/96K3WCJB272H/IyGy80lyyULkNZ3D7EoxNwmSBP49XnpaD2PKSrinZknNL5EC6BnAU11JuqYSQVE4XePiR2osfKykRdpaII1MecRTIJ5oacSjaQiyTK7sOtTTZIkVIh61bFvHKq3Q7sJ9GSkhJGfBYG6x7B7RNdmCZV1tQjaLvE330a3aXm821bZZ2+uvfvWrvP/97+ezn/0sZ8+eLd6vDoej6OL867/+67zrXe+itbWVmZkZfvu3fxtRFHn88cc3/Z107IqutrWwURdSyM+edHZ2ks1mV40Qtks8qqoyODjIxMQE7e3t9Pb27rj1tW43sJV6kT7gtRrx6PWcqqoqjhw5suoNsdlUm05mQNHzJxwO7+jczVbPs9lsprq6murqajRNW2Z5MDIygsViKbZ0BwKBdWcU9ONIRrN87RmYlICO/KJltii0VkFKghofLEbzNFPZCkNXg4X3a1TvAV+TnXh3hlzhp4rNg7NSJdQPclai1g+WCi+hGsiOpskO5OsYFVwmNWvCUW0CjbzQ55SZyLhIzX0ZZp64db8IDiuek81o2jjuvaZ8p5sGGXMlM98fA8DiAf9hMxa/i9HnEujzipGxGFZvDO/4VL4lu6kW78I84y0tqJkclT0DXP+N/4cfeWIx7xpXgqJZm22ViKeEkGyrSOPYVlEoMMk51LImglvEUy4Gmr0tLecr3P9KWUdoLpRPyy2VRjyaBlKWnKvEensL7qObfTDVo/bNFu83a3v913/918iyzAc/+EE++MEPFl/Xt4d8/frxxx8nGAxSXV3Nww8/zKVLl6iuvpV+3Cx2PfGs50KqIxgMcuPGDSoqKm4zJCvFdohHJzbdadNqtdLb27sjXXf6cfX29jI7O1u0j94KVkrblVo9bMStdTOpttXIbDfaIgiCgNPpxOl00tzcvExVeHh4mHQ6vSEDuHD39/n2h34bq5I3O8tVm5DTKi67g/G5FHpU47RBbZMVWZXw+GzEo1k0DZw+GHox/+RtFaH6iA2HP8vcFRUpDRRmfmo9KpnuNILdhOu8H03QmLzaTJN6k0jvrevYXmci52vF7Bym5pxIpE9BzYFYV0PslWFihe1cLQIVx0Uiz8uYvSbkmEounhcbnXkiik2L4guArwIy/gbSY7PYonnh0mgkhtUMLISQa6p4+m//kL5ffC+m+79+2/yMnmrL2JfXQ/SIJ1IS8RQVCm4TAy2Q1AqGb+WK1bomW6KsEcEiSWhO97K0nKtgZS37lxOPs3DMCyX7cEgSgqYhlUY8dynVlkwmN51q26zt9bPPPrvuPr/2ta9t6hg2gns+1VY6rLkRj56teujoi2spsen72U7XnY5cLkculyMSiWx7xqh8wVcUhZs3b65az1kJG0216d18Bw8epKWlZdm532niuROyOaWqwusNsOrnLfnKl/nBr3+G7C0haQJmDUcNWGUzdT5YjIPNAi4bjBZqN5ClygNer510OoNoASUHkgKiTWPoBQCNihZwO/1YohHG5pKoOQ0SCsmlCI4HvHilMax+Ad8hM9mIiippZENgD/YzXxCTdjQI+A+biEbtOPZXkx5dxOwAR42Jye/K+OlEESFwnwl3q0h85NZDRjQM/kpYuDaD1Wxh6f4jZP0ejo9NEB6fRchkufz7H2P43fl6gKCqyGWRjbVAJuWDoroYaKSk9V23uM7e5ruTP2+3RTw5Ccm9vIlH13UrJx5Ryt2mUODSSaqsluM1CWhmM8mSz3MVPJGCmlR8zaJsTvF9OzWe16tW266PeNZKtZUW3zdjfy1J0rrb6SgtlpcvrqUdZNtBKBQqzqWcPXt22yRWGvGUpsA20wCxXsSzEfHQ3RjxrIe1Blh7e3uxWCy86YdfovEwDEp+RkYipNOQDGmEk0AhtvC6BLx2DdEEFRUmQiEVh9uCIOQYmc5HOmarQGOlhiBDbO7WNR6aBPdBGJ7Nb+N4wIPJKSJYIfFMBIuqEe2HaD9UnRbJzGs4G52EhcNUWW4g2gTklMbCywqQz/d79gm4W0U0GZwNAqkZDcECZruJyW/nF2KL30JMbee+lm5mJgAtX0+p6uxl5pEzhCZmCZjhyhf+uEg6AIKioFiXRzZ6xJNaoatNEwQSJZGQQ68HrRLxRFYwfCuvB+nEE7vNaTR7m36brskWL1ehzmTQnMubFvz6LFbFrcijt6OXuJAoPoys5TwKWyMeVVW3FPHcK7gniGelCEW3jPb5fJsqvq+nr1YKWZbp6uoiGo3y4IMP4vf7l/2/Xk/ZjgupTmr79u1jcHBwR9qOdeIJhUJ0dHRQXV29Zj1nJaxFGpIk0dHRQS6XWzM6uxcinrVQPsCazWbp6enBnFPYMwd7iPBqAJ5OQG1bvhywNCDisyiEUhqxpL4nlfojYJGcKOEoNotANqdhdZiQcgqLMSCq4qkGPybsh1XGX8mHU7KkIl+J4XosQOLJMJZmG6OzD3Di5KuYHTLzLytoMqTnIjiIYD8pIqc0PPtFnI0aS50itioHqhQvNCHksWg+xolHxsiE05jsoGZATskITo3Bgu21vcnP8P5DSG4nzU++iN3l5L3uFN8+c2LZeRIUmVxZxKN3pN1GPLkcmt25bHG3rRLxWPToqCwyEXISUrkmWyF9Fi3bVpRuHxTVI55y/TZLTkJxLl/oPQWS0gK3Xj928Dgs5Dtnh4aGsFgsxdSsrixdiq2k4pPJ/MWz1QHN3Y5dn2orr/GULtblsycbwUZrPOWmcKvNEW2GyEpR6kL64IMP4nA4GBwc3DF5oLm5OaampjZUz1kJq6XaYrEY165dw+fzrVlLg3sz4lkLNpstb+FwxIIWgx8EvbzSlY9wJjvy2zS22MgEU1T4zag5mcUo1DWYCI2rZJN5t1FB0Gg9Df8/e38eJkl+l/ein9hzX2vfq7t6mZ7p2Wd6eiSDQFwt5vEFAz5gvGEDPuCDL5jnHoG5gA9ilYQRBmOEQcLCBoTBHLAtIwESgzSaTTO9THfP9N6171m5Z8Ye94+IzKqKjOruqh5pBh39nmeeno6O/EVkZMTvjfe7vK9Agua17XidY0Hb9Vj4HIiiy2AOpOEitUmPxqd8Tx5rwWCULyDFNdafd8nfL6HmBBqLMUrNKcoXL+JaUL3i35PC2DhKRifV30RKQO2qS2pCoLpQY+kvfBttSYOBpyXQBll6sdI9H32lijhpM/3Jz7L+2Em++fEjDPzZH2Nkdi/OguPQCPnT7CWNIzoOXmhbx3en3cN4gobOcLOpZfVYJcQjhEPBB7pw/im5h0KBYhjYIeBJBYBm7HAfzSfyZCYzTE5O7soR3rp1q9vN32FD2WwWx3H2bcjYAZ6vhtrepLETKCzL4uLFi3sykP3Ot9dYXl7m0qVLd2UKd5BihY70jaqqXembjhfPQSpgdg7HcbBtm+Xl5Ugtt7sdUaCxurrKhQsX7rra7nbA02GL+z2nN3t4lol7fotPNGDueouxIrQaYGagOAFzrwTinU1/MZ0ckrFll4EjQal1w6Y/J7N6xcZo+KCjyTD6BODByhn/ermuR60FsaZJ41N1pD4F7ajPFC584VGEz30W8C0NAIpPJZCXF+l7UgbPo3rFIXtUYv2LSzQWLV9jDeh/SkJSoTo/ykBhEWPLRSsKtNc86jeWUYBkGvqGYGvwCPrFqyx97VP82Z/8R/4/7/8FAKqhggHBdRFCatN6xa8Qq8ghp07bwg0xm05xQTseZk2Bhly42dSy0MPSOB3gCeeUTIN2qKk0HoBJJcIO2w4t9KlAOLSd2gaOnVVtYedRwzB6GpklSSKdTtNsNu+6dL/VaqEoypsmA/WlHn8jgMe27R4dtIPKr9wOKHbmLe62qmy/opwd6ZuxsTGOHj3aBZk3Il/Ubrc5e/Ysruty4sSJA4MO7M7xeJ7XLSHfj6L3nRhPR516P0D7ZjEe6eqn0f78Z0mqj/Lx1yRW5hzAZrHtm1oND0JtHSYmkrS3mmw2YaIP5jq5m3kAm5khMFyB/CCsXwPXgWRMZOmCixGgQ3ESMrEcXrnC3JIPTs6mhW420KYTHOKvyB6TiQ+BUXFRMwJrn19HAta/4M8x9LW+qoE7doyUskrr5iZ9j0mUX3WwWzDB85gVv/lUVKC16oEkgOPhedCsQf3aVRa+/e/wl7/zS3iqihg8N3UtDDxOT/NnWvGfz3L4tzUMnD2Apxm2PwhCYlshFiNYJnoINDrNn+Vkb2jPCKtQd6RxUiHgMQzMMPB0rbO3AfR2VW2apjE8PMzw8HC3JPrixYu0222++MUvdsNynf/2YkKNRmNfBol/08ZbPtQmSRJbW1u89NJLB9ZBC88XBTwdW4ZOU+XdVpXdbZXcnaRv7hV4OvmcgYEBPM/bN7UPj06oraO23Ww2eeqpp/aV7Lwd8OxswO3Ex+8k9PlmPoTi1k3W//ocn/rcOdoOjNwPkpmjvVrBMGApyIuUafqWz/0Klm0xMahSMU1qZRgbT3B9oQVYsA6KJnJowKVhCNgqXeCRFFhZaKC3QI7LqCcTCCkJt2HTfqmOAFSv2DSXIHtMYuucQ+bBATZLg+TFC6SnZVb/2l/MRS7Swlestlsexcdk6jddWksuhYdUNs+YgT02SCmVduJ+DhXOsrEC6X/0tfzFx3+1m48RXRdPEGhq2wuv4Lp+uXEoHNZ5etzi7pcfo9HwFbd3DC0AmHA+SLYtPC2GtxO8PA/BtmiH9u3MEdZkE02jx88n3gW0cD7IoFnYXSST1APZnlSgmO/JiHfpn9lpZI7FYgwMDDA4ONgtVpmbm+PSpUs9YbnOOtABnq/U8eZryt9m2LbN+vo69Xqdxx57jMOHD78hls5hoNjc3OS5554jk8lw6tSpfZUy302OxzRNXnnlFVZWVnjqqaci9dbu1Pi51+jkvF555RWOHDnSNW2710q7zrm88MILXTDeb4XNTqXsned748YNXn31Ve677z4eeughUqkUy8vLfOELX+Cll17ixo0bVCqVPbXr3oyxdGGT//IM1Ntgm7B8CZo1A90Cx4OJx2DkBKRTEtk4rK9bLG/B/JpJsw5TT4CIwEgBpOCp659OcH0FVrccaquQHRaYGRBQ42CbgWFa28apOxgXGrRfqqNOJZjla+h/SiY9JVJ6xcGqQ+3VdZTVKySGZRrzLkNfI1N8TMKVVHKPjbLyVzYbLzqsfd6mteRyjXejpEUyRyXEYA3XBjMolevcvAJPfR3Ef+w7dhUBSLYNWmx3YUBQRBB2Ce2EyeqhooO0qiJldsvaeA0fcavy7pcl2bZ7wnId0AjbU3dKr0uhxVo0TdphTbaAxYSlcSTDQE/uvse7rqRpH3j22zwK2yKhndL8mZkZnnzySd72trcxNjbWLVr5/Oc/z/nz5/mVX/kVLl68uG/Gs1/3UfD7eB599FE0TWNmZqanzwfg137t15iamiIWi3Hq1CleeumlfXz76PGmh9r2eiuu1+ucO3cOoNvQ90aMncUKO31iouR17mbcifHsR/pmvz1GOyVqduZz3ggzuHK5jOu6DAwMcPTo0QMBftiiwXGcbkFFB+Bt2yaXy3WFPkulEqVSiQsXLuB5Hvl8vsuG3izGs/57/5LV//PjnPZAL0hUhqARd1i+aGIFXf7zr0B+HERRQAKGRmIYVR3dFkkXXWa/COAnjBUZpp4CsyKTTxKUYUNmSOT6WQfWfSGAoTxwdJByvY69Eag9z7ZIs0JjzsUsuxQflVBSAtWlDPVqmo2X5gBozLoIChh992O3Vnx1gwWX+k2Xoa9JwOc+zern/ONKMV9QtLKawlvX+NbvrHPycXhe2s0+RdfFDZVNqx1NthBT7TiN1sI9OI6DGwKezlK/KexeB0Rd71Uo6ITlQuE31fSFQys9+SCTduhFstNsGpbGkUyzB9C6igjJwARun82jsHc5dVRYbnl5mT/90z/l7NmzCILAd3/3d/Oud72Ld77znV2H0r3Gft1Hb926xTd+4zfyfd/3ffzu7/4un/nMZ/ie7/kehoeHefe73w3AH/zBH/DDP/zDfOQjH+HUqVP88i//Mu9+97u5cuXKPZlovunAEzU6kjFTU1MkEgkWFhbesLk7i/JBBDijxu3YxX6lb/YDGJ18jiiKXYmazriXajLP87h161ZX7+mgoNM5j86cuq5z5syZ7vlqmtbTn6UoCkNDQ12juJ22B5cvX0YQBJaWlrrK1F8uE7jGXz8LLghAfMvBGBJ57RykUhJDKYemDrFpKM2C0Qi+U0Mnl4R0UiGWMBg9CeuXBUTPI5eWuPGcA1QASMYFRh73aG6JqJKD6fjWCaoMC19cx3M9lBEN9VAcQVGp/lWL9op/n5TOOCQnBRzdRmzXGfxbvk5bc9Em3i/hnXuVxho0XgdEGHmnLyi6wFMcyryAVYO+J2SWPm0jaCt4T///OPn4TwLQkkPA4zh4IQajBb+hEQ+HyfYAHtvCCoXJksGt6oUWsnalTFPY/RsngiKCcD5IjSjTBhBMk9YevjubiXAhgt7DjhJBcUEzdTD3Ubi7Pp5OWO7o0aN85jOf4aMf/Sgf/ehHKRaL/PzP/zzf+Z3fyWuvvcaxY8f2nGO/7qMf+chHmJ6e5t/+238LwH333cezzz7Lhz/84S7w/NIv/RLf+73fyz/9p/+0+5lPfvKTfOxjH+NHf/RH7/pY4fGWAp6OZMz6+jqPPPIIfX19rK+vv2Fq0rBdrNAJre2nByhqRLGUnU6ene9xt3PdDfCUSiXOnTvH0NAQ9913X88CfFDG07F4qFQqPPLII7zyyiv7nmPn6ABPpVLpOofef//9d6WgHWV78OKLL2JZViQb+pJW/9gOk+/NY94s82pd5fxrQUd91aQO9GUE1q95FCdFtIZMdctETqs0qyaVpgF+JTTZtERGsxEEgcIkbM35atWJhMS1z9uAhSjAwFHIkKayUsdzA0HRZQN1Ok7z2U1SiOQflNHy4NoelcsOZqmGCKx9HuJDAmpWxHWg3vcYQ5kbtFcqFE/KgduozTgvYLdg7L0ydgv6npRJ/P3/g/kz93e/djPMeBwbVws3igaNyuH8jLNH86fj9EjjqB2PntC++XgCIcSO1EBJoBoqLlJMAzciRC6YRo9CQcw08WSFlrZ7DtE0aYaBpxNqC6Y4CPAcpI/Htm3Gxsb44Ac/yAc/+EFWV1fviWFEjeeff77HAuHd7343P/RDPwRspwj+9b/+191/F0WRb/iGb+D555+/p2O/6cDTeTvvlBjLsszb3va27hv8G2lj4Hkea2truK7LxMQE09PT9xy+CTOencrPTz/99L58YO4EGDt7mI4fP874+PiB5okaHQYlSRKnT5/ubr8XHbrOtX3llVc4evTovnuudg5FUVAUhYmJCQqFQg8bSqVSXRB6o9mQZzskEiafq8O1ZZNUAQqTYJeSKK0mc5s+OKxddQGToRQ0dJf+DDhijFJdJz0MrWWXhTqAv9AWRxJknBYtV0BLg1H3WZUag+uv+tVsakFDuS+OmJNoPV/Fs1wkXMqvQv8pma1XHZSkQPzEOPVakv7iZfS17T6eNK9gWBqF+yUEGQbeJlG9ItDahJFTAot/ZpG7T+I9n0rz3EuHkKTtZ60VyrmIjoOjhYQ8O6oDPQ2kgQp1uPTatjDCrKkblgvniSy8UF4xGSgJrIV+I9kwesJyeB6CZdII+/yYZo+MDviGb2GQihsGXjyBJ/v3k8r+X3AOolwQVqYeGhra93HvNFZXVxkcHNy1bXBwkFqtRrvdplwu4zhO5D6XL1++p2O/6cADsLKywsWLF5mYmODIkSO7Fo03Cng6+ZCOnfO9LII7x85FvlQqcf78+QMpBYTnCo+w5cDtepj2G2rrVMR1vItEUez2Fd1LyO7atWsAnDx58o4GdvuZN4oNddSm31A2VJkl9aG3Y10x+B8kmF32kzGNLWg3YWhQZKEEubRA9qhHY1MiqXvMr7mAjd+mozM6A7Yo0leQaDVcNmtQmACjZnOrAmAhSDByPEairFNtbJ+CWTVQhDj1T5ZAhNjxPK9ffpC3ves5Vj5r4dngtD3YnMcbmKI5C4kRkdwxAX3LY/HyEH2pKpsvG9055ZTEPG9nVHqOqb+r8rc+mkTLixh/rSKLO4BHCoXJXBcndC01J7oHR+qASQh4RNvuqTJTunI34VJou6doIekG+dnBUFiuVKIRCsvFu5psvb47bqK3UEYwzR4ZnZgRsr2+h+KC/YyvZLkceAsAz+uvv87CwsKe/SGyLN+1LcJeo8OmFEXhqaee4nOf+9wbIuwJPljYtt3Ni9yNUOleY698UavV4ty5c0iS1G04vdM53S3jmZ+f7ypWT0xMdLdHVaTd7bBtm/Pnz3e7r9+owpC9rumdckMHZUOi0WDlao3PXgbdNUjFIJvREPsMbA+WXvdZSaXuUTsPI/dLlK74jIdcgvJai4FinMUbbTzPxfckhfE+EaHPxZFjOC2TtgmZfmhuOSwHDqLxmMhA2qV5cpDyq0GszgX9st+YufznFmpeIHdcAhEqlQm81+cwXQ+z6lB5HbL3iXiIqH1xMtM6tesOnuOh5OJMX/trtKLGO34viRzzr6veju0Cnoa0e5EVHKcHeDq+O61wjsey/XxQOOdi2z3mcB1B0XBYTrJMjNDi2wGTWig/U4wnIGSdHdd9TbxyCPzUCBkdAMHUe2R0YoaBmzw48Liui+d598x4vhRjaGiItbXd3HFtbY1MJkM8HkeSJCRJitznXhnYmw48xWKR8fHxPUuYO4znoFIyq6urXLx4sduw2ZnjjQrfCYLQDd8dVE1h51xhwOjkc4aHhzl+/PhdLZp3Azw7HUijFA7uxlAuajSbTc6cOUM8Huepp57is5/97BtaAn2nud5INtTe3OTPXgY9uAQNHSTFwV2HZhkGBuOoVpu6DbFhWDwfVEABNFu+L4/hMHEfNNsSm7ccJvpgseTibgLUEAQYHY+hDus0ViXAX1hFwT9e6bNrIIB2XxJ5SEWUMkz+5ecBMMse68/bDH2tjPnaLSgMM/TAOmbFRdQ8KpdcUtYC1fNQBVLTAlpeQlA1PnXt+/nuP/wYwo71sNXSSEh69+/1nuKCCE22IMcT7quRHRs37DKKr+sWFgPVumKgvUrWYf22jrxOWHVAtS3cUIFQyvT3DVsRKrreo1Ag2Q6CbVMJAV3MMHF2gJGyz6q2zvOzX+BptVpveE4nPE6fPs3/+l//a9e2v/iLv+iG2lVV5bHHHuMzn/kM3/zN3wz43+czn/kMP/ADP3BPx37TgWdwcPC2IND5wfaba3Bdl6tXr7K4uMgDDzywC6HfqPBdo9FgdXUVURTvioncaexkPJ7nMTs7y/Xr17nvvvsYGxu763nuBDyGYXQVDm7nQNo5j7sdHZAcHR3dBfJvFPAc5MXjbtlQuIEPICls8N3vgi/+Jdhff4T1l65xfc2j4UdrWV9rk46BJ4k0NlzGH4zhLemUKpAZSjC31AJMKAM4TA+BbcNIQaBke7SrMFKA1WUDZwFAJ6bCyGPgzUusbQa/oQfWioGgCDRfncMky/hTTQTZQ47TNX4TSsus/jUMvl2mfNEhf7/MubNPcqhwlkSfSWvFpXHL4fAP9fEXL34AQfrYrmvVbqukxVb37w05lHx3XIyQDbUShNpa4XJq28GL9d5Xgm3R7rFQ6DR/ht1Krd7mzyAsVw0zLNPs0W9LBfNa4bDcxkZQT7hj346aQVgRwdB3Ac9B3EeBfYfaGo0Ghw4d2vdn9uM++n3f9338+3//73nf+97HP/tn/4zPfvaz/Nf/+l/55Cc/2Z3jh3/4h/kn/+Sf8Pjjj/Pkk0/yy7/8yzSbzW6V20HHmw48dxodEUrbtu8aeHRd5/z581315DBlPagnz86xtrbGhQsXSKVSJBKJN6SqqgMYnX6Xra2tA7Go2+V4qtUqZ8+eJZ/Pd5tN95oD7o7xeJ7H/Pw8V69e7QHJO+m17XfcC4jdjg1dvHixhw3Jjr9wxQU4/PZh4uI1avIk5Sdvcu0srDyTYmWhQVt3oQnNLZ1kzNdecxyPyQFoGDLlps3IfRq3LnTyLB6CCIeP57G3ymQKMuVNCzzIpWDpVTCa/rFjR5Ioh2J4pkvjc36YLUaVrfOQPymx/KxDZkakKRzFbhgMH5tn9RkfDDZeshnlOWJDfbi6QeEhiaP/TCN5+knkX+u9/2tVmWFhO6xdCzEewXV6GE8n1NbsyfHYOBGMB8vu8ejZqxBBjNBki+0hBipbFkZo344KdXjfvngcL6Tf1rHDLoWAVTMM7B2AeBDgEQRh38BzEC+e/bqPTk9P88lPfpJ/9a/+Ff/u3/07xsbG+K3f+q1uKTXAt3/7t7OxscFP/uRPsrq6ysMPP8ynPvWpnoKD/Y43HXjuRmhyP9YDnUR5X18fjz32WKR68r109neS5nNzc5w8eZJWq0WtVrvzB+9iiKKIruu88MILyLJ8YBa1F7B2xE9nZmaYmpq6J5HPzuiUjq+tre0ZsnszGc/txu3Y0JUrV5gpX+UEvt2BEMSkREFg8jGY/FvgDE6z8dwFLglptuQ6pbkYzQWdigGsttkENNVh+DCAyFgfbFZBt2DiYbhxphyciUUsA2OHMpgrNSSPTq8pSNA+U8PesBAzMtrhAS6dPcJTDz3L+gtBAv+6C8JVhMljbH7Roe9JCVkTqN9yuLT4dqYvPoucgNO/EmfsXSoLV+PIcu/9XylD0y53/16XwozHweopp+4AT0gV2nZwIpi04Ni0wjkXy8aLxXdL4+ADT7hoodv8mQwDj0kzu7v0OtGR0Qk1imqWhRsCnnTQr7MaehFTdB07tQN4vkzuo41G40vuPtr5TMeva6/xAz/wA/ccWguPNx147jQEQbir0NjO0NSdrAAOGmozTZPz58+j63pXQmZubu6eVQI6w7Isbt26xdjY2F3nc6LGzqo08K/NlStXWFxc3Jel9p1cSE3T5OzZs9i2vWfI7o22RvhSSeZEsSHr88EDKUC1XCFGwAAlfGdrxyGpwrH7U4x9Vx1z8zgrP3+Os6/CipJErzQRRImlKzbg958oEkz1C3iCR99AnM11f/vgUbj+cq17vGIGCklYTInY1wLl8pqNvd6kwC3WX/CZTmJUxKq7bK4fRph9HRvYfMm/t4e+ViG7uMjAO0Y4/aEGfY8E0QNTRVai7v8i+ew2awjneLDtHk22DuNphHpiJMfucSX157Aimz/D0jjQAZ5ow7dyGOgsq0d1IBGoUJfCDMswehpF0x0A7dut1dbe2KCsbLNA1d1/jueg7qNfrWp7k8ftXEiBblNhrVbjySefJBt684mab7/A0wlRdYznOkzqjQjbdUCzUqkwMDDAiRMn7mm+nYu9ZVmcO3euC5b7oe+3A416vc6ZM2fIZDJ7Mss7zfFWtkVQFIVEJ7YvQiZY1FzXBRFcV8Bqt3w2pAYK44LC5ACIIzD0Dx5Gf+4LXF5LM6uUuXlGQrQcEjGB2Q0PNgDaJDTom0rgWi3iSZF20wXPt8y+vgreSh0xKxM7nkTISJjXBXK+1DW16y5mxSXWL8H6AozPMDg1S2PeJjUms/rXFg4KD/7USfoe+UL3u1mWiqL0viw16xpq1v+tPFHtqUjTGw1KIffeTpisEaFcEFasFlwXwXV7PHoU28aN9RYXibZFK2z4Zlt4kkRLDem6mSatUEgtEZxrKaRCrZgm5dDLV8d3ZyO0b1HTILt9Ha6/dh3PpivseaeIxEEZz5ejqu3NHG868NytQvVei3vHsC2RSNy1XcJ+gWdxcZHXX3+dw4cP9zSd3qsgZ8cQrlKp0N/f/4a85XRyRY1GgzNnzpBMJneB5d2OvURLO8rS09PTdxRu/ZvCeCJHkDgXRAEp0NOVRTFgPBo4Np4LVlCJZrRt/4ESRXBc0nF4cCrOE/+8jGk9zNqHXuHqqsL1RZPVCiiKQDbhMX8lSOgLLn15yJ9IULnogxqAW7XB82g9W8Fru5Q4wv1fewvH9GivuFRedxBwYOE6pS3IHZdoLrnM/KM0H/zPX+B7J//lrq9lGlpkqK3ZUBHFoLhF6mUrSU2FkL28GygJ1LTeHI+9h+FbGKQU244Oy9lWz74x08aLJ3tAUbLMHpCKW4F+W08hgkErtKgnO+woXFxgWRj57Wq5IxNHUJe17pqQSqW6IJTL5XqiFAfp4ek01H+luo/CWwB47maEXUg7o6OFdjcL4M5xt8DTKTleW1vj0Ucf7Zo97Rz3wnharRZnzpxBURROnz7NjRs33pBqO1EUabVavPDCC0xOTt7RzO5284SVpW/evMnNmzc5efLkXdXyv5VzPHccQVUUot/DAuDhBX9XUSUB3QMt7b/1Gm2bJOBJAkaziQK+4Y4Egi0z3gejo1m+7uEtWv/E4eZ/mOTqy7OUDRG95SIKEI/DtS/4QBTTBMRHM0gFmfbLdby2DwpFrmGUJFrLLq7l0X9KZnHhPjRrk2Rxjc1XHCb+jsLTvzpK67/0IYi7QcYyVeQIxtNoxJCCPh5P6n2TFx0XLwQ8mufvvyXtXlwly+oJy3UUCuoRDaRhdgR+qK3ZAwRmr0LBHvvGDTMSpGTTpBF2JTUNvFgcS9m9JCqGTi21/dwXkgUGDw9x+PBhTNOkXC5TKpV47bXXcByHXC7XtfmIx+MHZjxfDbW9BUYYKBzH6Sa095Oz2Gu+qLHTn+d20jcHZTwbGxu8+uqrjIyMcOzYMURRfENUpT3Po1QqUavVeOihh+6p0WsnaISVpTOhBehu5og61/06rn45GY/QYTwSEOQyOg7PnqeAbeG5IMX9sE8mkQNAlEW84O3eNgw0Gcyy7QORqAIuqT64/3iaBzXYevsRmqkr3PqDfq6c2fCP4YFueKRU0VctEEA7nkRIDPHamUmO3PosTlCAsPGijZDcANXCteDhH4/z6P8Vx7P9hV8IqT4bRgxFigCeutZtIHUjgEdwHfSQOnUiUAtohxxIm+Uyeohhd/Iz9XioQMG2sfdkPGG5GwsnAngky6QRCrXF95DGkUyzR80goUfvKxsGRmL7e+ysalNVlcHBQQYHB7ssZWtri83NTW7cuIGqqmia1nUF3k/E4auhtrfA2Jnj6XTxC4Kwby20zrgTS+lI3wwMDHDffffd9o1lv2DRUX++ceNGjxVDRwXhoMO27a7IZzabvefu4k6oLUpZej8jCiza7TZnzpxB13WKxSJ9fX3k8/nbCra+0WG7Ow6nw3gEhKBRUqAjpayCbeJ5IMYC4HQDVJJF4sEiI+OH5oyWRRLQTZd4LJgjWIjFmMD4Q9A/l+VrHtmg+vBJZv/tBVbsHC9fDPRzPDAuN1EfFpjiGSRZoPiUhCCBbbqsnW9Ds8rRfxXnkZ/wF2bL9BdJQdh9fxq6ihRRXNCoa12tNici1CY4DnqsFzSgtxQ6E9N6wm9KR3Ug3Gxq2VhRPT+W1SOjo1oWdhTjMU3qPWKge4CUafTsmzRNnGQvw5BNA32H7fVeDaQddelUKsXExASO41CpVJibm6PdbvP5z3+eTCbTZUPpdHpPBu84Du12+6uM50s57iZ80gm1dVjCfrr4o8ZeLGVnZdztRDjDc91teKwDDNVqNbII4l4YTydsp6oqMzMzPTIXBxmiKFKv1yOVpe92RIFFuVzm7NmzDAwMcOjQIcrlMrdu3eLSpUtks9luH82bbv3bAZ6djKc7ZASnieeCqAXXxAn+lEWEYEEWHL8KLpPM+VPJWlctoF2vkQLKlkkOECwXZEhk4jx4SKD+Tf+Ck9/2RVovVan92SbGzTbl37uBiIdZhfUXbPqekKhecjG1Isnv/E4e+Yn/2j1Dz/HBoBd4tMiqtno9hhTsuyfjiWgUBWiEAckDIXR/dxQKNsKhL9vC2oPxhKVxfOCJCsuZPfvG9pDGkUyTWth3xzCw9mA8eiqa8dxuSJJEsVikXq+jaRqHDx9ma2uLUqnUtXnp5IbCChqNwBjvKznH85Z2IO0MURRZX1/n3Llz3HfffZw4ceKe1IejwMK2bc6dO8fc3BxPPvnkXYFO59zuBiyazSYvvPAClmXx9NNPR1beHRR4SqUSzz//PMVikccffxxVVd8QZmDbNlevXmV6epoHHnjgQNc8DDzLy8u8/PLLHD58mOPHj5PJZDh06BCnTp3i9OnTXXvgl19+meeee47Lly+zubnZbcR7c4oLduR4grCV5ypdxiMEWmee4/8pyKIvUcA28CzU/c+XXQ9k8DyBWMCkDcVvXqwYdVCgZnv8wjf9Ph868Y8QRIHkUzmGf2qGqf98kuIffZhPxj7K4e9UGX2XQumMAwLcmPlR1Kee3n36rv+mHsV45IhQW72qIQmB82kU8Nh2jz21Yjs4Sm8FnBghjZMIfrt2bneYtl3aoupG/K621aNYrVo2VgSLESyLarjZ1DSxIsJVkmVS6VGhNrEiGI9k6LSS/u8keAIK+7NQ6eR4YrEYIyMjnDx5kre//e089NBDJBIJlpeXee6553jxxRe5du0aL7zwAhsbGwAHYjz7cQt9xzve0e2T3PnfN37jN3b3+a7v+q6ef3/Pe96z7/MKjzed8dxpmKbJ1tYWjuPck2HbziFJ0q4+l0ajwdmzZ4nFYnddGdcZd1NcsLGxwfnz57t6cXst4AcJ23VsEnYqBhzEQjs879WrVzEMg8OHDzM1NXXguTpg0Wm8nZ+f55FHHqFQKGBZFp7ndcOLsiwzPDzM6OhoN1RRKpW4du0auq4jyzKyLJPP5/dlT37Q4Vo7GU8AJN1Qm+wDjwsN0SMPXcbTlj02Wg2GAC9wkNPtIFQXb4AElidjeQ1kIJ73gUe2/cqqK7LIjw19O+9tnuk9p3ieq/Fv4+t+9314rsfGF22kuMD/+BffgCh+fve+dnAfh4BH17Xe4gJPoNVSu8UFTiTjcWmH+nVkx8ZWep8XyXZ6pHE6pnFhuZuMqvRI4+B5CLbds69q9UrjgM94qmHVAcvCjAzLGRHAY2BGWiUYtFI+8CioCOyPgUcVF4iiSDabJZvNcujQISzL6hYp/OAP/iDXr19HEAR+9Vd/lfe85z2cOHHirpj/ft1C//iP/xhzR3l8qVTioYce4u/9vb+3a7/3vOc9/PZv/3b372+ISss9z3CP43YXtFKp8NxzzyGKIgMDA28Y9dzJeFZXV3nhhRcYGBjgscce2xfodObqKNCGR8da+9y5c5w4ceKO4cH9AE/HtO3WrVs88cQTu2Rq7iVkZ9s2Z86cYW1tjVQqdc/XXBCELptcXV3l1KlTFAqF7vVXVRVJkrpgads2pmnieR65XI6ZmRlOnz7NqVOnUBSFRqPBiy++yPPPP8/Vq1cplUr3Ln9k67xibbHzJ7xkVTnDqwB4ItRNHxy6SmauhOC5eB60Y36W3wgYEiJoir/N7oh+Ss3OBQEJbCQ828BzwRP9hckxZNw1SFT9YylCb25Rb4MUsBVBFBg4pVB8UKbZ1BBDAOM4QY5H9EJzqBHl1CogdIEnivHg9IKJ7Dg4alQFnN2TD+qUU1fDTaGAGFIwjwflzevy7mugmr3SOOBbXIdFRmOmGQ0mpkm5xw7bxIjc16CVCrx4vkTuo4qidPPJzz//PP/hP/wH4vE4n/nMZ3jiiSeYmJjgc5/73B2PtdMt9MSJE3zkIx8hkUjwsY99LHL/QqHQVe4YGhriL/7iL0gkEj3Ao2narv3C6iQHGW9JxrNT++vIkSPYtk2r1brzB+9ydIoVrly5wsLCQo+I6H7ngt4O5Z35nLutArtbwOiYzQE9ttedeQ4SktqpLH369GleeeWVew5tdVQT4vE4p06d2gX6HcDZeQ0dx+kCeedaCIKApmnE43GKxSJDQ0PdN8TLly9jWVY3Vt7UsqiaRn9M5r8su/zvk9u/yQZt/tC5xMPOFKeVPgTBB5hPxP6ITGKDP9XziK0ZRqxxFrKf4R8EujWCBG23Tg5A9aVVTA/i+HI6WtbftiQscAxAEhB0/7p1sEBQfQsF1xFBBsuViVkmrgtqOqgka0v80kM/yH8r/G8AJCKYRLVs4Hm9QNtqKj0A49jROR693dvH43n+vrcDHsGxaYYZj23jRLysiY5NO1QwoNo2nij2Nn/aNvWw3E3Ajpqh58bY2qIS8bIqmCblHt8dC2MPV9JyqFE0ZhjoEWE50TRoBoznoO6j+wlRi6LIyMgIxWKRT37ykxiGwbPPPsvx48dv+7k3wi30ox/9KN/xHd/RU033zDPPMDAwQD6f5+u//uv5mZ/5mcjWkv2MtwTw7Izd27bNpUuX2Nra6mp/zc7OvqH2157nUS6XaTabPPXUU/dUPdK5qXYCT8f/R9O0fYXu7qY0u1wud7Xo9jKbO0ioLawsLYriPYfsKpUK7XabQqHAo48+2gWTvUQTOyXlsO1j0gEiy7LQdYN2UBmVzOb5j2Wbv3N8ko+urfDDSd835A8ra1x7xxaF600yRpHPS5M87YxyVazwicQfkhLKfAH4tJHBqj5IXVllSK0AkI6VWTRWUbNniQN22wd0TxRQBf8NXBD94697VSYBzwVX9B8j1wlyAZqHEjAdIbivPbPzvXzG4yIiWTaeB15QDSeZNnU1wwuKn6sRI275RKwPWe5deOt1Bde1dm2z7egcT6ulIUuhyQMpmE4DqRVV1eY6NCJyPFYU47F6Ndk028GLJSKaP60ekIoFwFMOhc+SktijhO2fsMlWaF/VNGhHAo/JZgTjCcvoAAiGQSPYvF+dNjiYckFHIFQQBGKxWI89ddTo5EEP6hb60ksvcfHiRT760Y/u2v6e97yHb/mWb2F6epobN27wYz/2Y7z3ve/l+eefvyc/s7cE8HRGo9Hg3LlzqKq6SyDzTpI5+xnVapWbN28CHKibPzw6C6XjOCiKwvr6Oq+++irj4+M9bqp3M9ftFvpOt/TRo0eZmJjYM0y5n1Db7ZSlD8qcYNtVVlVVxsbGdvXshM/7E9WryIbCewrjpGQZx/OY1W0OJ/ww3Pe/dh11s8lKQuKH4wU8z6Oi25w9con1tVXigw6fGsvxkHWcqQsJvMYrFB8rAfACz/Lf3SEcJARBQXNUFMmkomcZLL5AXrJxXInV+jAVI8NAYh1F8u81TfRZiiABVkdGICgg6DgWeCAngm7/YC33RBHJ3A08XQCyfcbjuAKy42K5kO73mZUouRji9sIuRtzyliEjRjzvrYZGW2/s3tcMgIfd90K7qSGFcjyuGzxrQXGBFRlqc2nGQppsthOpySY6vYUIqm3jxXr3lW27x0gubtp4gtDjYJpCwOzrC52DjeC6bIaBzrSiwcQ02AwzHt2guce+rZT/m3+pQm3h8Wb08Hz0ox/l5MmTPPnkk7u2f8d3fEf3/0+ePMmDDz7I4cOHeeaZZ3jnO9954OO9ZYDndvbXeykX7HcsLCxw+fJlBgcHaTQa9ww6QHchdRyHGzducPPmTR544IEDWT3vBRiu63L58mVWVlb2VFAIz3M3gHE3ytL7ZTye53H9+nXm5uZ4+OGHuX79epe1/EfjVVbEDR7wZnivNkFCkPhZ469Rh30dsV8yVRorM9RaAxyVJ/jhxDjNZpMlbY3JmWs8OrPEZ50XeYURJqQpZuo3KR7x3TlrrPBp+RbqoyKty320ykmGjq5RUrP0iRvIBOEsQeTq5lFUyaRmZCgmthAEF8tVOd53BYCqnqXULuC0godfAsXbXVxgB+zGc0GMe+D5ifbOMaTOi1IHr3QfBFTV9HM8bsCS8BtO8VVxuJzbDqkIdu9vaBoKoti7vdXSyOV25+O2SkFY0DJI7NpXRZJ2z+F1gcf/vc2wQCg+42mGczy2hR0ZanN6NNk028KJ6NeRbKvHKiFhWZHsSLYsKqGwXNLyQaoeKqc2y2XM0DbBdcF1emR0NNOkGcrxKJYNioInfnmB5yDK1H19fQd2C202m3ziE5/g/e9//x2Pc+jQIfr6+rh+/frfbODxPI/XX3+dxcXFPe2v79W4raN0sL6+zqOPPorruly5cuVeTnvXEASBS5cu0W6399XVHx5RwGOaJufOnet6C91NNdfdMJ6DKEtfr7nMZHYzuGtWlRk5iyD41/nVVy/wB4VlpHfe4LMti4HBNEuvX+Q5Tac49ioJ4CZf5ENWnFLtEK7UYFBPE4vVsSwZO77J1ORrmMBPuwmkdp4pVIaml/3vJtVYw6KSuUZCUFm4OIGiOSSOVEjRQpQ9xh/wRTTLa+PIg03WGSBBkzR1qo1hjvZd7Z5/qVWg2S6gKG1MR0GVLCTBJq01iMvV4IIKeIa/+IgBe+gyGAFESQA7yN8QhNosZ9d+dHDIEXzG4/iPnqPJuPjA8//9Bx/iT2Pfsn39rQjg0eVe4PFkPE/sKS5IxDsvKLu312oSkrw7LOcGPT9iQLPMKMZj29RDrEJ2ej16wC+9bobtD2wnUoVasu0exWrNtvEi7nUlQhonaRiR0jhx12FZ3p1PShkGXrwX0FTTYLOw+8UrbZq4O0qsDxJqO4g69UG8eO7FLfQP//APMQyDf/gP/+Edj7O4uEipVDrQi/XO8aYDjyAIJJNJnn766TvaXx9ktNttzp49iyAI3QW2U579RoxGo9FNip8+fXrfVXE7RxgwarUaZ8+eJZPJ8Oijj941Q7sTU9lLWXq5aTGSVPjT+SrfNOG7cT6zZfNH4gtMryZ4Xc3y5w9NICDg4fGL8mcx1C/QNLPQPEJuPs7yeJmB0Yv+gWJfpJRRuTIyiCC4LFcmSMYqiIKL7sQZL17qntPc3CS2LZNMNnEcAUnyMEUPrbjKSNGhXY+xOd9P8VgDWa4jCQ7xTJvxB+ZZvDRJiiY6MSQ9SW0VWtUUkw/Ndec3kVljkDgiS7Ux+hJrmI6Kh8hE0XdttF2ZG1uH8RAoJjaRghJoJAHFCxbqjuhAAByeJKBKls9Ygj4ex9teaISgP0UWjODvfl+P4/r72IqE0rLhErw4ubsPhwjgsXQZUQgDT3T1mh0UF8RiuxffWlXCtnYX6zhB6XWX8UgR97Hr0OhpILUxI3IuomP3aLKplh2pySZZVo+RXMyyI9mRbJk9+yZNO1K/LSOKLIfcRxMtHV3u/W6qYVIPLfYZw8S9B/dROJhI6EFDbXdyC/3H//gfMzo6ys///M/v+txHP/pRvvmbv7knktJoNPipn/opvvVbv5WhoSFu3LjB+973PmZmZnaZxR1kvOnAAzA5OXnbhVKW5QPleDoJ86GhIe67777uDfBGWV938jmSJHH06NF7Ah3YDTyrq6tcuHCBQ4cOcejQoX118K9bBlbo+/lmZj71/vUzN3nXxAiflzPEGzbHc/5t8P2ZvyD7YhxTazItPAACmLZLurHE4NsvMQj8uJdG8Q7TBhLiq8hASqvSEi+yOJOnGN9gqTaK6sk4YhtVthnLLnTPY6PZh+PK6E4Mx5HoT65Rqw4wNLSCpvkJfF2PsbEeIzFsd9Z5Ykkdx5JJyGU8wPASLJ0dxDFkZk5dQwAS6LiKjW0OUBwvUV4bwxw00NABkRFWIQN5YL05gGFrOJ5ETLBJxSusNwcYyyyiyT5IdFgO4naHfkf3THICxiNts6GOfIwY86CTbglua9cIHjXbZzxBKgVXkPjIf/4e/t7pP6EkhEKoux0IADB0pUd7zfN8YBFDYqCmEQBCuMzazpBM7X6eajUfWG2rDVo04xEch3qP746DGcl4HBohTTbNcXoUq8FnPGGQipkmToRVgmxZPZpsCcvCiSiFVkyLeuhlNmM7CCETOACnUqYUqrZL6wbODgB4K4fa4M5uofPz8z0geOXKFZ599ln+/M//vGc+SZJ49dVX+fjHP06lUmFkZIR3vetd/PRP//Q99/K8JYDnTovqfoFipx5aOGF+kPmi5r9x4wa3bt3igQce4Pr1629IR31Hq+3q1avMz8/vGXrsjOf1NXRcvkYbQgqu4R+1bnKx+EeY75T43IrFfRxhwUlQkGO8u1nn5s2bfPHBOK9XXqMQK5GIjeMIx5hxR8hcanDsbS8D8D84g/FEDKFZIL8Mtikhqw4INnVhjgJlLGTq7X7WW0kSapvh9AoAo5klqs0BFLVB24ozW5kmLrfAUSik1lCk7TDPza1DpJ02a2tDFIsbxONtVleHmZq65V9rYH22SHm5SGF0qwugMgaJTJuhmVWa5SRu3t83bksMH10OZm9QJoeMi47KEsPkW20qToJifBMtub2yz28dxhUdSu0i/Yk1FMlBMAQ8FwTVX2ABCFiN11nLZQFZsMHbwXiC/A3edk5IcHb8GRQXACTkFj/yGx/k177tl9hg9wLlmb33lKHLPcyGAHiE0Iv1XlptzXqMZGq3a64i54AAeICN1m7UEwOtulqst5w67Erq729TD2u1WVakJptkWz3VcjHbwY6IgMi2RS20PWFZ0fuaBrW71GRTTZP1kE5gsq3j7LS9/jJVtd1LccHt3EKfeeaZnm3Hjh3bc+2Kx+N8+tOfPtB53Gm8JYDnTqMDFJ7n3RGk7qSHtt/5wqNjOlev17tKCjdv3nxDXEhd18V1XVZXV3eVef/35iyXWOJrpaOc1voRBPhY8zUWsn+KLFn8hZnGax5Ftftx858lJpsoCriJszw7X2Fscp71ZoH/Fkvyt0YeY2ruNUYefR2ANRb5I17E8JLEvSIrV4bpn17DUSQ80UNLLzNyDMy2wsq1SewjBgX8hL6CTcu1GM0uE5N1Sq0idTOD7UhM524hSQ4JpUUxUWK2Ms1wcpX15hCuJ5CPb1JqDXCocLP7/Q1DZXb2EKLoUqvGyGR1bCREEY497edlTEumpcTx2h75Yf88kvkmLWIo2Miqw8q1YYymRqrPITu2goJNKujJqRjjxGMNVhsjKJJJf2KNcm2MicKN7nm0bY3Z0iEk128QRRGQgoVXDKhKp3TalSQU0QJnG5yEYP0yRRkxaPaU3ECdQbT9YoWgEKFuZ7EsDZHeFyFXv7scj9cphRbC+cEAeNi9f72hMRKWzHF9QMhmgoU6ufu5UQMVh2oIICTbxohgMYJj9wp8Og5WxL6iZfforMUtMxKkZMvqKSKIG2akcKhimj0glTStSE22jChiDexWuZdrNSo7eqYke//L5UFzPPeaQ3mrj78xwAP+28Pt8hx3K32zV9PnnUZn/k6DZWf+O8nm1E2HtOof5/dvbbFuWYhkeM0W+PUT/oPYbDb5jeazrH/NCn3OCZKKwaNein/XfJla/lNIostf8Rn+u56jXTuOFVtgKFhoNLnJsrjJRP8rWI5MrT5CaVMFT2D6kM8cyG7QzJb5JKvkPJXZc9PEkm2Kh6q4kkNSqJN82C8fXnp9lOzxCh6guA6SaLN+c4ihIwvIQX9KmRwVMgyITVTJ77QvxEvUzQwzxeuYVpylhv8gO67EdN4/j1FlAd3WKLX7iMltZitTZOwtZNXDNDUOHdoGoiZxbCRMXcFoKWgJC8NQSCkt5ISDbUqsXB2mvplm/PQsimCDAMNHVpg7N0VxZJEGSTZII2NiojGW98N++XgZ2xVZqo2TkSxWqpMktDKabFBpFzhSvIYqtf0+mx1eM92igo5LguohuQEY2UFxQVCq7MgiUtCo2QnHeSYgQ8HZ9PfNdFSve4en927zgSdUCr1Hjsc0oiVzfBXqkEeP5d+HHWB14rtZgeK6eIJAOxSOkmynx3cH/OKCcCGCYtmYezCesCabtoditWSaPfsm9tBvky2rRxonsYc0jmKZbIXCW32CgNy3XXAwe3UWsSJ1m5UzmcxtX1w7vWgHYTxfycrU8BYBnjuxjg7Y3A54OjmRyclJjhw5cts5d/be3O1Nsba2xoULF7rl3p35PQ9E0WdQZzZbPNrn3+h/OFvmT9vLHNE1rqptfvf+kwC80qoxK13kxJFL9FVH+ffyFA+Xhvif0iukpq+QBxyW+aT7WX6jcgQkA7U5yEByDduVqZlJRvtfAMB2FG6Vx7FclZHUEgCKZGPLTXLZNvlCmVKpSL2eYXiohhCrEkeHvM5UvsbS5RFEwcVAwfQUpLrLxuwAo8cXkYWOKCZce+EosmZRL2XJDW/iItAmzjTzEIeWlWC9MYDpaEzkZgFQlTbF+AYNM0N/ZoPVxhCCHUMQDWTFYDS91L22G2sZbD1Gu51A1zUGBtao12Jk+1okcckebWCbEleeO8rAiWUcJGQcZNXBaGkceeoaguBhoNJYjbN5c5DDj99AED3SNIjTYpM+BlmntjVMWVRJKjVsT2Myt12AUNUzbLb6sV2Z1foQou36oTZl+17qAI8bFAcgC91S7U45dUec0/JU1KDhVBGCvh4bkGDT7mOcNQyCxdmjB30cvZdF6+3ecmrPic7xGEa0ckGzoSLJu1+ULCuoagv2bYdyPJrrghbrqQazGg2aUu8zGamzZveawwGIEftqlh2pySZZFpWw4ZsZrd8mmwblEDtKmhZGRBhL1g1K4WZVw8TNbu974vAJiqt9lEolFhcXAbogFGWD3XkZPUhxwVeB5y0wOqqoUazCdV2uXbvGwsICDz74YE/nbtTYyXh2jk7+YOf4n615Pt/6PMJSjm88ch9HJw/xW2sbfM+g/zb/0kaTn5ppMnJ5jmr6Jr/b9zQqMhXLxuYq0pMXOeZI/Kz8BaacGfJZk/zhQPwxcZMN5vmvAwVi6KwwTLxhoihtmlaaycJ2yXe52UfFSiMJDi0rTkJp09Sz9CVKpLU6niew0eqn3MozpNbJ5f18S7FYotVMoqplHATqJLEWMpTXYkw/MosoeqQw8IDZG9Mksi0WX5tg5KEVZEHHtDMceWq7/LhKhioZNAxMZFRsbFcipTXoS8z6zZiNYeS2hqFZjGZ8gBlKrVJuDBDX6piuwlxlClk0cTyR4fwqirqdc7h1a5pcukSLBBoGGhaLlya64TaAtqky//I0mb4ariMgiV7AxlSOPX0Vs62weqsPe1pAwmMYv79BKazg6lk8T0TwLGYr0+SlJq7ooig6Y5nF7R9fF33GI++sUgvuoeBedEUJ2fPzIZ0qOEkLWI4qdC0QnFbgzyPYIIPhxNDjGj989cP+vD13KTgRoTajLSOGenDcAOjC1W6GHs146rVeyRzb7ITrfPDUQ308im3jRhQRJCQJI9HLTLAtKj3ePU6PYjX49ge9wGNFhvAky6KcCFfAWehRlgamSTnMeEwTPQqkLIPNsDmcYWImt79DUk4yPDzM8PAwnudRq9UolUosLS3tssEuFotks9nu+vJVxtM7/sYAT1RBgGEYnD9/HtM09yV905Fs2Tnf6+Jr/JHwKerNCaacI3yjOsN/01+jUfhzMnkHRuEZ9xX+8/UHqCsCJ4TjnPKOoQjQt7nO9Nf7IPEL3udRvGEYT3BYmEcQPSTRxqLEa3Kd+KE2m7P9NCtJsuNNhKLBIOsAZKlRE3K0nQSmo7FQHac/uUa5XaQQK5NP+uEZ1xO4WjpKRrRQgsVGEDyaZpKZ4nVEwaXRSFHaLKIbMaanbyKILjKQpEnFyzL18BxrN4coThjYWh0PhelHbnWvh+3JtEgge7B0eYSB6TWalRTioMsE/uJsI1GrTLLhyhQT/rlJooPrCeRyy8iKrxBQ1fOYjsxkdg5VtojRJqPVmK1MMZxaZn0pg02GbHaLSqXA9PT2ebjA7LlJEDxWrg0xeHgVVxSxbIljT/vX3GipNFDxFIF42o9PqXELLdEiic96KmRpeQmsaxbFqRYp1S8nLiZKVKrDaGqbUjvPVrtAMb5BqdWPIhg+o1Xdbhl1N9TWqVbbafkcNHzqpr9YuYKIIHeq4IJ7zQQkaCUSfOD//ACfOOH3TkQBj92KYDwtBSnEeDo9OGGL6w7w7KqC8wQMQ+mGADvDNHcwHg9aIcajuh5eBPAorhupceaaZo/qgGrbvSrU+DmeHjDZY1/Jtqj0+O5YkWAiWRalCDvsKDUD2ehVM0gaxi7g2WkCJwhCj8J0x2/n0qVLOI7TDcXpur4vw8qvAs+XadxNgj8sm1OpVDh37hy5XG5fPS4753McBxeXz0nP8AX5WUQgm32NDfcKP1sbJxZr065N0C9WkdQmpVIfk0f9HpW/4gJ/5sWRhtIkaypmW0GNW9iCiCVsEMsaxByR1etDSJ5G4sgGSVogQP/UBtZVhWSqhoXEMkPIONgIDMRKZHboaN0qTxOTdarNQdRYhYxWZb46xdHi9tt/uZ1jvTlIWqvjegKiAIpiIis2x6auYNsyRruIHtcRgMKEX/U1fGQFx47hIiJgM3tuCi1hIMoOxWm/IRMVRo/XWHx9DDwBcdBCwiZJm02KDKSXyAQSM1vtAhuNATKxKmJQuZbVqlT0AkeK1zEshcW1QWwthuNKHA4KC0YntzDNOhvrg6TTdWZnp8llN0nmm1hoTD28HQ5rNmLYKRnB9WhWEiRzLRqlNKmRKho2XgI25vrZWs6T7q8wNOiDeo4quqsyMlXGElQWqhN4+P0407lbiKJHQvNzXLcq06SlGuiSDzCK2C1tFjqI06lu26Gb1ilA0JImlMB0lC7jUYM+Hsl1wYZ6JsW1zNHuZ4WoUFs7GnjCuRzXiWY8eofx7Gog1QABORRq65ReS4IDHrTlsJCngxtRvSY5veZwAJKm4YVCTO1yma2ICirRtiiH5XVMK1JnTbQsyuGeH9OkHbGwy2Zv+CxumrSi9Ntsu0fNIGGYmKkdVte3KadWFGWXDXaj0WBlZYVyucwLL7zQFbgtFArkcrnbsqCvdNtreIsAz92MjmyO53ksLi5y+fJlZmZmmJqaOpBLpSRJNN0G/1P5U+aFeYbcIVZ0jTW3jSR4TAa5CoBWI0e5XMC2FVZWhhkYWMMSNSTBQpHXGTvha2hde/EIA6dWiOG/dYuSi9lWGT2+hISNgYrXSrNwvsDUozdRNAcViNNihWEG2KDeKFDzEmS1MjUz303KA+i2ynx1CvBYrQ8xkFpDt+KYjsaxQO7FsFWqpXHKFYWh4aXg2tm4tkUcExWLZinHxkIOz4XJh5aIYYEAUw/PsnhpnHR/DceN0ZYU4o7B0sVRxu5f2E6UA/OMIeFgtDNoyS08T6BuZDjW7wsS2qbGQmsQ3YoznvOVBDTFopgrUzGLDGVX2Wj207SSxGpVpLjE6JjPpIrFEvVqHBsVB5GFS2P0jW9SL2XIDm+RRIcUuI7AtRdnkGWX+FADT7IRBGjX4hx+7Aay6tAmRoUcBjJDol8mrdAmnplnrjrFdH6WrY08LSdBPNOmbaeYzt1CNU1k0QAPHGG7PFrsLJyBSoEY27GQdtQJAokVT/QFQYEucLmGgDcP8jF3V5WU3m5DqMzXqPcu0npLRgyphzpOp5w6xHjavTmeTgVcuLigAzydHE8v43Fw1KgeHCty0fcilLXTkhQp8Om5To/qtWpbkWE50TJ7WYwVDVKCbfWASTxCGgfAk+Ve5QNDR09s/0baXfbxCIJAOp3uuiafOnWqR009l8t1gSiRSOzIGXs0m82vaPdR+BsEPB3ztosXL7KxsXFXmmW3G+1siz/N/wkl0Q8RrQqriNIgGWW79yShNDFsleHEOsOpSvezt24dYnhyA10QET0PSXBYen2Mw49fRwxiMpaT4OYL4+RHyogBI1Aw0V2bI6evoTc06ptD6KM2IDCKn5PJZzdQjARNK01caTFbmSKpNEmKBjoyUzsAcas+jOFo2IJD29KIKwZlvUAxu0qxX/fzPhv9bG3lmRjbIB5UpCWLFTYXs4yfXAQk6iQRPVh9ZZBDj97qvlGrQNtKE8+0Wbg4SSpfJzdRZlPo64bbSPmMq9TqQ5MNdFslJps4jkhc0ZnMzeN6AmuNQRolBU2zGRvyv2t/cgOaHvGsDpLI/NyknyAXHAb6N1CD803f32Th4jiyZtOoJ3BjOnFMFi5OcOixm11AtJDZuJFHFD0cW0RWHTR0PGCKRRwENhbzNJJZbFfmSKBY0DewhW7UKZt95GNbzFUmyVpVMP28nxRzwQBbFLoOVp4dLBRSsFh52w2knVJrx5V84PFACcqpLUPlw4f+L15/OIZW3V4UlQjG3qoYvfdtUyap7W7+3LY/2A1U7SjG40UDT7cQISiUaEq9+RknKufiOD0CnwBuxPdJiBIUep/Ztu30SthYNq2IqjYQsJTdc2umRSuiqs2TlR7WFTdMGlGhwRDDA5/x6Knt7aq3v6bJTvGSLMv09/fT39+P53m0Wq1uWO7GjRuoqkqxWKTVajE5OUmr1TqQ0eGv/dqv8aEPfYjV1VUeeughfvVXf7VH9LMz/tN/+k9dRYPO0DQNXd8upfQ8j3/zb/4Nv/mbv0mlUuFtb3sbv/7rv86RI0f2fW7h8ZYAnrtlLFevXu0qV4c9aPYzLoivcu6JM3iiR787QNyLIbgis8ocCdEjobQoxEvMVafoS2zQqgxSMzyKxXXW14eZnvZDRDHAQeTGy4eRZIfKao7CaBkbEQ+JY2/zWUirksTK+ZCUSfjhnFjKwLaayDikaLBJAQONxJaFnNQZTPnJ8P7EBsv1YTxsGnaalhVnILnGWmOY4dQqchDSclyRq6WjKKKFhY6i6n7ep5nk6FG/6stCpo1G+/IAI8cWkBQHcEhi0ibF1MOzrN4YwmhqDJ9YwVYlkrE6iWn/nJvlBBUKuAis00+eLdxWHE8QmQkWcceVuLF1mEzDRun3tc5EwcNDYGRwg3jMoG6k2WoXsByZ4fQyyaTftJhKNZmfm2RoeJVqOUFs0EHFZOX8CJMn57qA6AEbpRQgsHp9iIHpNSTVQRc0Rg77tsG2KbF0eRjruEIx6DuSBI9ktoErqAym1qjqGSp6AancQM3YDBd9QExrdaxNCdHx+3jsILZvC3I3dNbpy7GDR8jxhG6TZaeBVNZssMFCQmwEiWbbpSnlWEr3MbqxvSgqEQtfs9wrXdBuqqRi7V3bHDua8eit3uKCjgp1uLjA1DuMJwCecHGB62JHNoo6PZYGeB5exPdRbItKxJu8lurd5lQrlOXecJSr9M6rWSaNZO9CHQUmMXOvfXuXwphh0C5ub99vA2lUu0ZHIiyZTDI+Pr7LafcDH/gAn/70p3Fdlz/4gz9A0zQefPDBL4n7KEAmk9mlWRk+zgc/+EF+5Vd+hY9//ONMT0/zEz/xE7z73e/mtddeu6f1F94iwHOnsbm5Sb1eJ5fL8cQTT+y7PLEzXFyek57lZemLuMHDuEWJAWeQFWUZQU8yq/tJZVeQttlFfxOpmaBcLqIoNnNzU4yNL2OLHiBx+PEdzYduGlOEOB6OLSDJHvVSikKuhIKNh8jS5VFalQQDhzfJ4i/qfWyxyiCZbJm6lWa2MhUwCI2JzDyS6JKkjOfBbGUaVTLZrA2RiW2haS0WaxO78j6lzSKlrSLpdB3X9bXPBFwkPAaP38LSZZYuj1IYNrGzLdJCA2Q/71NZ83XaZGzaRpbKXAJJsYmlDPqEje4x1ukj3pKoyzFkwSITq7PaGGIss4BW8BfNip5jtTFIWm2gKv62tFan1C5yqHATx5VYupHHElPYjsrMjH8t+weruEDDS5IdqDL36iRa0qBvcg1DjdFfbEDR16Wpl1JYqoeShnZdI5420OsxtKTRZZI10lT0NCzajB7zv0M2VsNyVWLFBlrcZqk2iu3KCDgcEa/7v5cLUtyFKtiijNLxKggKCaS4fx/ZyIj2diiy+6cEricSl32wkGQbS/AfWsHcsShF5D4kt3ehb9QFivlo353wY9FudVjMjsN0mk1DjKcdAp5GSM9McRzsCN8dye713VFsBycCpBS71yoBgjBXaMQcj3JEHiQaTCwaEQzBjQCumGlSiUjcO1HzGgbtpH9ukichsb/qtLvRaZMkiWKxSLFY5BOf+AQXLlzgbW97GxcvXuTtb3876XSaX/zFX+Q7v/M7bzvPTvdRgI985CN88pOf5GMf+xg/+qM/GvkZQRD2VK72PI9f/uVf5sd//Mf5pm/6JgB+53d+h8HBQf7kT/5kl13CQcZbGng8z+PmzZvcvHmTTCbDwMDAgUGnSZM/Vv6IedFPVCdbSdJeBkRYiQcSK7EmGVdFECCutFmoTgAeedvAU9uMjKx05zOdDA4WHjK12RR9E5ssvT7OyIll4jgggd6Icf38JLG07ielBf+t1NIVDj9xHVHyKJOjRRwLiUkWESTISRVSao2l+jjDqRWW66OkLRcxVaNm5nblfQwzxkJtEoD1Rj/9yQ0MPQmewNGjPhDpukZ1awCxv0Iy6OBXYjZqwkCJNYnTRvdirJ4fwvNgcHoNJVgo0UxKTop0sU1lNY9VTJAQy1TIMcAGUp9L5331WukIsmRTNXL0iesIgg88HbsBw1BYWsrRThQYyywgCh6iZDMwXmVtNcHU9A1Km0XqjTTJeIXEoEFGaMJwk/xwmWY5Qb0SRx2AcjmJiodtyTiWTKHosxrSMHd+EtuUSfXVfNsB/DBcv7JJ/D4Tw1ZZaQzStmL0JTZIZfzwwqiyxEJ1guH0KtaaCrrnM55AksaTBYSglNk2ApHP4N9sT+oCj5oIWKgpgeybvnX+zZFEKuoQ0ECwth+/qLtar/W2D5i62lNc0Ax04aIM3/x/2Ml4OqG2UIVokA/qKCg0wozHcffQWXN6BT7tPQQ+I1SoIZrFZCSRdrHQs72+IxTUGZppshmhUBIFUppp9sjoADhKBPjpBqV7cB89iFzO6Ogo4DOYRCLBc889d0dbg4O6jzYaja5O5qOPPsrP/dzPcf/99wNw69YtVldXd5nQZbNZTp06xfPPP/+VCzy2bfPqq69Sr9c5deoUc3NzB9ZXWxaW+IL0ecrCVneb6EqUtE0sxSJhJygKfTRsiZaySkLxF93x7Dzz1UnimTLrm32USkWy2QrVao7JyTlUX4yL+Hidm68cRlZtbDeJLNUQPFi7MdQNt3meQIM4cjNDdrDa7cVI0MRCYZQVWsQx1tPUNQ1ZsJnMzgXnsYDeSlF34sii33uS1SpIHsiCuyvvs1AdI2mKWKaNaSqoqsXWVoH+vnWUoF+nttrH6q0CucEKsuZ/15igI4ge4/ctojc1TL2AGdORTY2Ro8uIkkeq2MDzYJlhYuisMUiu0kTLNFisT3CkeK17HrXNGGvCODFZ7+Z9PEBTPSb6ruB6AuvNARpGCmm1weQJvxCi2FdCViw810XDpO4kqVwuoGo6sYxBYSDo98nD2s0BHEvGbKvEii3iMZ3SUobBw6vEUn5+REdjhUE0TJKBcqcmmziuyKH8DUTBY3MlS9tJ0o4lmSleQxSgqPoM1fFACgoILFchJvrzqgHzkRKBVbQnI3WERDsXwfNzQqanoFkm9XiKfzj6cVTtCHAW19jRHxRRUK1Xo6vaVGX3YtZu+59tNKq7t7d6czxukA8Kl1O32x3lAn97I1xcYNuR9geiE2Fp4ESbw8m206NmAOBEAI9i2zQiQEqNsBxxazXKIbkb2IPFmCaViByPHcW6TINWyt/+5XQfBUgmkyiKwjve8Y47fuYg7qPHjh3jYx/7GA8++CDVapVf/MVf5Omnn+bSpUuMjY2xurranSM8Z+ff7mW8JYAnHFtsNBqcOXOGRCLRlaY5qAvpOfEsn5L/F04QQsi7BfJ2gVV3GSvwJGlJLfo8gbJ6C8lRWayN47gititzONDwGh5ewbJkVlZGyGRqmGYRR2ugegZrV0c4/MR2uM1AwTbjCIJHYytBqtDCQUHCI5ZcI5aE8kqe0kKB2JNtRvAZV4I2rqqQj7WJye1u6EfEZii2RX9sO8y1VBslLevorTRVO8FAco2l+hjDqeWug6Zty1y5cgxNM7BtGUU1EACzHePIqWsIoofVStJO+Anx0eMLSIpLMtfC81oYJNGUCivXhjFbKum+KtKwwqi0zfwsTWapNgZ4LNVHGUisYtgaZlvmyLgPRI4rcasyjVe1yad98BcFD1mwKSY2yZ6oUa8m2ar04TgChUKZXN4HibTUpK5kSPc3qG1k0Q3IjusYFZXCyBZKbPueqJLG0iU2q/30T62hJSy2KDDFPALgigKrNzNUMsP0JzaRgpxIYaDKwlKMo33XaJpJSu0+hBoIphcoFwQHkIUu27D1QP0iYOAeArLtW1l3qsw8F5/xeBKVTI5v3PifnFl5gr/rBgKoxg4pntB9qwkerr17q+BJfuNriNloqi/rkkjsXtQr5Q4z2t7fcTqMJ1R63er0/ASMJ2SLIDtOpP2B5Dg0ehQKojXZZNuKBJOo/IpqWT1abwBEnINsmKxLvZzRiQIT3ehpKhVcFzuiCk81DFpJ/7dUvozuo/F4/J5spe9mnD59mtOnT3f//vTTT3PffffxG7/xG/z0T//0l/TY8BYBHtg2Hes4kU5NTTEzM9MFpYMAT5s2m8IGGS9LWdhC9mQ0R+Omeh1U0CyNIXEYGYk5cQ4E/204H/M1x8aT86w1BonXVRqehaI4TEzMd+c3ULCI4dgSi5fG6Z9eRZBlBNUmqdVIPljDcwVufPEwI49ugbTtgdKuxhk7sUgMAwOVMnkMFIbUDTTNf6sezSwxV5lkOLOKXkmzpA+SVBo0rTQT2Vm/byNRwvPgVvkwimSy0hhhKL6OLBksLY1x7Nh28rAV6AAoibYvkAoIso6IRkaqYRgqq9cHsQ2R4aMN0skSCDBydJn6VhK9niAu6CwxjIaBioHUgoni9jVZawxiWCpeuUVsIElKa7LZ6mMgsUYy53//cjvPerOfhNJmJJDOSWebVOuFbjhzdbmP5IiOY3kMTq8jKQ6JrM/OaqSQZZOly2OocZP+qTWaRoJcpk72MEAZU5e59sIRkk81qJMig8/WzLbM8UP+NakZGTabRbwFnYkTfr9PUm0iCjaxrTaKZ2N5YHr+Amh5cjfU1sn1uEG1geXIJO1WICrqXwtVsfxm0ViMt809z1x12v9uKy1ygKvvYDyhFI8m9KZ9hOBxdd3dOR7T6Lib7n6c221/gbVtg47EmhmwLEna/Sy1ekJtofJm14tUoZZsu0dZWtsTeHr12wTXjcwdKZbdI/AJ0WCSl2Ws/l7GU4kIy6mmyVYIeFKGGdkEqxomjY7t9ZfJBK7RaJBMJvfVInIv7qOdoSgKjzzyCNev+0VCnc+tra3tEixdW1vj4Ycfvutz22u8ZYCn4wq6lxOpLMsYRm956e1GnDjf4LyLb3Dexaawwav181wQLiDkBTzBQ3JlKnKFqlBB9mQGnBGeq8bJaDWGUgHVTK3RNPrJxppYlsrs7BSxmE4+ZyLFKmiCxcRJf+Gde3WCwSNlv4rJE5AFk/kLE0w9PNuNqTtOjGsvTJIu1pFVfwFRMXEQmWQRVxNZqQ+j2xqOKzFT9JlUqlAh5tZZro/Rl9hgoTpBSrJIK1usm30c2qGubBpx1ufH8ATY2spTKJRpteIICY88NRiEZiXB6rVhCoM6maChVEuYJLMNBNlFTdRoEUMyE6xdTZAfrtA/6TOuBDU2KQAi1TWJLXmCvsQaW3offfENtJQJeT+8eK10BFm0EQWXhNJCEPwFf6ZwHUl00W2NlWtJdDPL0PQaiuIviIPDm9RJkVOalBaL1DcyxNItRNVgYKICKUg+PIttiiy9Pk5mcoM6SeS6jSQ7bMwOceSp7dBfiTz1qkY83sZxfYmdjtNo/0MbWJbEUm0U3daIyQbHlatIQVWbGIh+eqLQ1Ulz9eCFKLHNJhTLwXG3GY/foQq5s9Uu6ACUtwxywEtfWO9uC4OMhofnhhlP8LiGGI9tdShZuCnUX2CVHaG5et3fxzSbu/ZtN3cDTy0UapP3UKEWbbuH8WhOtBiobPcqVidMCyuCBSkRwqF4XiTwqJbVo8km2Q5ClBNwvc5maN+UYUQ2laqmQSt5b7bXXw4TuHtxH915rhcuXOBv/+2/DcD09DRDQ0N85jOf6QJNrVbjxRdf5Pu///v3dX5R4y0BPK7r8sUvfhHTNDl9+nTkhb8XDx3P8yhd2cJdgL//4D8gmUzyhbXPs5xaZl313xJswUYRJCazc8iiw3pzgJaVwHJkDuduBlVALXK5CrOz08jyFi3iCB6INZv1WyNMPeyHUGL4a86NL84gKQ6lpQL9kxt4AjhOnONv25Z6qcgFGqLKYKAlJkou2VgZ9DzD6RW22gVqRoZss4GZlZgI8j4ptUFTz2DqKQTRY64ySTG+6echXI+h6W3ztfn5CfAkipOr3WR7vZRm+OgKiWzLF/30Eiy+MEJutEL/aBnwjdVMNIZm1jAaMebOT1E40aKmCAyxgYRL5gRApauwsNIYIatWyCcqzFUnmSlc7/aXNBox1uaKaOMOtishiS6KaCJ4GWZO3sJ1BdbWBmk2E+BaHJoJGkrHSqQKNTbnB8iNbFEniVMSwRLQG4ldTqNNV2Pj2giuK7Ix20/f5AZNIYGMw1R+FfKg2zFuVcYQgKGUD7qK4qCaBtlYlZTaoLGaDu4dEDtPieRtl1MHCgZWELoyg8oyz4NYyq/eq9UziEMu6+ndSfJKOXAj3VFccOH8Ojyx/Wap4hF22rCD6mpN2527sO0gPxN6uW42O+XU26gW1/w+mvD6XS77C6yAiyeI6CHhT8WNDrWJrkM9rDpgO5EgFQU8MdvGiAIp0+xp/oxZNkaU/YFl9oqBWhZuRMEBzQZrIXmetGHRivDoESSh2wx8UODZr2FaB3j22xS/X/fR97///Tz11FPMzMxQqVT40Ic+xNzcHN/zPd8D+BGoH/qhH+JnfuZnOHLkSLecemRkpAtu9zLeEsAjiiKTk5MUi8U9pW8OmuMxTZPz58+j6/ouPbfDjSMMrY1w4sETzIq3WBIWOS+d64ZQCvESbSvOkeJ19HqKtVIfkmziOHLXpCyNiS2IrC6NoCV1Zs9NMXZiDU818bwYh5+43j0Py0rRUgQSeFi6jBKzadfjxGNt+ljFRaBEAfe6gt6vMh64dhbiWziuSCLdQtM85quTCLiI2BQTVWK5Gp1HZrnuq017bRWrJZLpL7O4OM7Q0ApqwK5sRJYuTOC6HvT7iXoRDxeJw0/6AFtaLJJISei5NjmliiCAGrNIFerUrFEGWGOTPlxEkutblNWRXZV2tisy+8V+OAKrzSEGEms4nkitluHw/UvBPjLzlQnadoyhIFQnih6pwKBscHANE4W2oVK9WkBLmowe9z8bw6KpqegtHxxmz03Rf2QZKQm4EhMPbof+Vp0+HElBxibhSCiSQ0XPMZpeIq60/SKHuQyVVobMmE1K9XNLedkHX8/dlsWxLKWrRCAHvghK2r9fOozFc7cN2YrWFmcmT/ITo/9y903pBYZx7Z19PCI7+fzGYp1Ma/f93mE84ehNx/4gnLdpNnqLC6yAHSWSu5+zRt1fIFutOjlF7WnolB03WhrHdqiFFnLVibZKkGynRwx0L002xbaphOZNWBZ6JPBYPXmbpGHQjlAoyGsa1VA5tVqvsxbyLPIn3r7Qb3UTuP26j5bLZb73e7+X1dVV8vk8jz32GM899xwnTpzo7vO+972PZrPJP//n/5xKpcLb3/52PvWpT91zDw+8RYAHYHh4+I721/tlPLVajbNnz5JOpzl9+vQuUOvYTMvIzLhHmOEIX+O8g1NXNslnL9OfWOO+/tcAiKUb5FwR21JIpUosLIxTyJqQKSMDYye2FY2tdhoTEJFZvzlA3+Q6m3MD9E1WyWKACpYuc/X5o8iqzWi/n9MQ8XCQyI+VUGI2FT1LRc9ju5LfFyP7r7sT2TnmqpMMJEs09CLt9TxiX51yu8BEdt6vSgqeqxvXZ5Blm42NAQYGVpFlh5aQYPzkLACuI1Jd6ccdNkhidHs7sgNlrGYfeeq4nsLCxREEXBxH7OqmDbKOgUK5FCcx0WS2Mk1SqZNQmjT0DFNPrAF+aG6rladi5JGtBq26QiJt0TQTJNUmE4GcztZahlJtAEWxmZjwj6FiYYsi+eEKWkpn6fVRlESb+GQbVbYojpe6171SjiMmXSrrSWrrWfqn11i7MczA8TWUQMvGEUSuPDuAen+cmNwmrrQRBY92XeHwfUtIkkfdSLHVLpIq+6EozwOpGzkTu3XPHdAw7SAp7+1wJm35/2+iYMsyirD7MRMD2mS3txcl19l974u2gxXqH7WMDvDsYfgmhIEn1rPdtjoeUiE7bMsPSyViCm5Eh75oWehRFtdOtKWBHgk8vYrVMdNG3yMsV+7x3bHQI5SwFcuiFDqHlGHRjFjAPUnCCfX35DyPVgQ7snaELg/CeA6a4zmoQOh+3Ec//OEP8+EPf/i28wmCwPvf/37e//73H+h8bjfeMsBzp7HfUNvy8jKXLl3i0KFDHDp0qIe6Rs0nIGDoI/x1xbfKzt4sc6R4mUfsq6TGlslm/YVufHyBarlIEgcTlflXJ8kMVKiXMoweXyaJA2Kb+CG4+cphJMXGNi2kuImEx/KVUQ4/cR1J9nMIW+SpkiZHtVul5Ytr5pkp3EC3Y2xdH6DRr2G7CofyvnKCllrBjQss1CdIq3Xmq5MklCZFrURlaYDDM9uMq9lM0JYkBMHzmVa6jdlWcB3Rz/sIUFnLUlrow3PELlsTRYvCyCbteoL8yBYblTxWLoaCjorD0H0+Q+lng3I7T8PMoFsqS+dzDDzQoGZkUSXTP+c8uK7Aja3DAORi5e752YbM2NgS8XibVivOVqlAarxGjDaJPr/JdvS+JdbncyQwaLZVVl4fI5FrotdjjN2/iIjXbQ69dWYaWbPZtAtklRoJdNYqBY4+vd5lJOV2nrXmAPn4Kp22z5TaoNTuYzzhM07PA930FzVFtbqMp+OvI8X8BdwMwmauCLmkz5qkjI0jS7ih1KSm+fvWN7e3qbLIrpIBw8a2dgNJecu/N9bXG7u2G0FxQbjarVHvZTy25S/cYXbUCNiRLHkg9LIKu15n3ehN1nui2JN30Ww7EqRk26YSApO4baNHVK/JZq8YaMKI1mSTHIdGCNASlkUzAqSiKujShoVZiOoZ2i4GMmoGuqfv623/IDmeg8rl/E0bf6OA525Cba7rcvXq1T2LFHbOFwVkmR0vKFUjz8vLp4mdO8INN0F+7AZHj75OPNHi8OHrCHjItBl/YI65V6fI9Ndol/sR+irEPZ2581Mcemw76e8gYBh+9U2rFiddaOIhYqL6pmpAqxxjlWEsR+FwwV/8Y7KOOOyguwOMpmdZbfjFBzm5jtQQmBzyGUIxUaJhJGjUBsCDxcUxBgbW0PUYpqnRF9gqeEmYe3USs60yMLnNGlxbom98k+xgFcdUaKsqih5Dbwr0T/kLer9aZos8cdo+6L6cRzui4IgS+ViZfLzsM64iLFTHQfBomGlfLkirs3azwMT0XLfku6pnWDsbJ9HnoATKBolEm80NkQx1kOlaWdumxKHHbyACmbxOJj/L7Nlp+qbWKW8l0fpdlJbBytVxph/dDv05+KKmotOmNJ+iONnA9UTqZsZvbu3zDdYWjRHaVozx7HxX/gYPOoTFsaVt0c8ATKR40LvT0Q6VJZq1JP2UaWtx/urpt9FaDd1nXiAw6my/RTfruyvVMGw8b/fLUqvRscDYDTCvX/IXSM/bvb0VIZljBfYHshI2hwvYkefgSr39L9l4HDGf79luC70Lq2pHMx4APeRgqtl2pMiogEc7JBwas6xI/TZXVnpCgwnTjFQziOrtSZom1Qh2lCtuf1+9qvP8pedJJBJdpYFsNntbYDloqO0r3RIB3kLAczcupHdiPJ18jmEYexYpdMZewJOOuE8ESUC2NF577SSvvXYSQXB459svMv11z5ChRvV6kamHZ7v724joXhpR8lh8bczXEpMFDEUioW0w+RB4rsDipTGShyS0eGXX8bJajWKihGGrrDYGMR2ZfLnCyKGOqdoKW60CsuggKi6zlSkfnASbuGyQLaxA8AK3sjKEbSs4jkS2WEURLKor/fRPrZPI+OXJJgqGm6SxlWL4qH8MSbUABUWtUBj1WLsxSLseRyg2GB0vI+MQRyf7OCyUxsinK2y2BgCP/vga62fTjD251G1IBLh1bRxabcrtAv1JX9mgrBc5evpW8PspLC4O02ykGB2b96NaAgweWmXh4iQzT96gXorjFSWsNZf6ygBTgYdQCv+9fmV+AC1hMntuitxwmWR/gy2x6Iua9gP9+L47rT4SSgvTUVAlCzzQZIPJ3ByuJ1Bv+A+/50I8GTSLSrYfavO2czxm0JDp2IG5oCohai7rxT7+3xt/ysDMHMny7rfxRgAyCtvbtZi8K8ej1yziIeCxzaBnKAQwtZq//aWXFjkZtGZ4rsJ2d9D2/p2wXDhc12h0Gkg9XDm6+dOMeJ6sCAah2A7tCOCJahSNWTatyN6eCNFO245kMVGVbknDpH6X5dgJw6AaoWbADufZ6dFDPJA/2eO5UygUuuZvYTb0VeDZe7xlgOdO406htlqtxpkzZ8hmszzyyCN39OfZm/H0JhldEURLB/wHz/Mk5uYOoeCzmcu/forh+25w9OnX6RurIubaxMU6Eyf9ENHazQEyBQ8718JxVCTJZGO+j9xwhVTcD5s0SbBOkdRmm/xhPwSlySaSYDOc2kDLGKw1BmnbcTwPRtIraLIBMZiizmJtjIzWoqLncRppkol1VjZGGB5e7pYoA1TIYLZimBbEU20EEQw0UkKF9MkKZlth8bVh4nGJ9PRSV4J/8PAas2enmRjbpEGKOmkUTJoveUw96ee4UmoD14OF0gRaosJ8dYJcrExarbFYm2D6yHb1Wc1Is9oY9hf/loiacBEEF88TOHb8Mp4n0PZitBsSW6+NMHPKL41OF9vYCNSFJMNHVli4NI7nChQmVxEzEqPHt0uUm+UEm0YeLy6xSYG8u0V7S8NLSF2VBduVufVyESeu0j/j53VEwUNz9eC33hb9NE2/uMBCRAqARwzcRl3bX/xtWWExOcZ3Ln6Cueo032DNojd231OJhL/417f7gXGsUI7HcntexgR6Q2cApYC0qtr223ejsf1Z13W7FW8dxhN2Me0UFwiCuyfwRFoaRICJXa+z4fRGJyJ11iwrUr8tSsImvocmWxSLiVs29QigjNo3YZpspaKsEravoeqpkZ47pVKJ1dVVrl692sOGvgo8e4+/ccDjeV7PA3mnfM7t5guPKMZTb9aRHSm0bfsGrq/2cev8KM994mt4x7fOMfZ/fJp+t45q1Fm7OcTgoVXUuEUcP8py7YUjyKqNIHqkCj7wVMkwwRLSERfTVllsjNA040H1lb8IDqbWmK1MMZmbo2ZkKTeGiFXrlDNZpnKzCIJHRqvhebBxZQgla7O0NEY+v0U6XcMkS06swhE/L1PfTLFydYSRpxfxEBDwkGQHx5YoTs/hAY16nPVrQziGzJHTweJPgxhtShQZPrHF0uYIjiKT1co0zAyTffPQB1BDtzUWaxN4CKwu5RgYqqC7MVpWsitqapsiC68N0JazDA76ZeWC4CF5FjEVZk5do15KsbVURInVyR1tkR/wr9v4/QtU1zJBWMpj8bUR4mkdUfYQRZfh/HYiZWMrTfOmgnQsQcuKkVB0KnqOgUN1kgWfb2y1C2y2+pgyZgHf9qCTz1EkGyRwPJnAcqmb4+n09yDANz/7x2xUfc0tWRIRQveOEFQoyF5sx7bdI6VI2CHG41hBUYIV8uOxfECw7e1wnWVuP9qu63SBZ34+yE2FtNrqtW1bBFvqXfhUz6UdkYuxwzXcQEZRMCJUqHszRH6zaTSL2UsMNGLfCJBKmNEsJmypAD7juTbYG5J31W0gD1e1dTx30uk0U1NTkQ6kruuytbVFPB6/69xQs9mkEJFv+kobbxnguRNYdN4cHMfpsplO0+nS0hIPP/ww/RHdy7eb724Zj6zK5MQY7MjpVhvbl06Stz9TWcsQpw/bG+UPv/ldTD1yk2Nve50Hv+EScryFaed3NTYaRpIVrUiCFp0EtyxaOK7Esb6rXS8b84KDcSzHTJD3ycUqOGqd8kqBoZEVFmvjgEcutoVVSzNwfHXHMRTm5qYZmSjTIkbc1TFaGvVShqNP+4u/i8jc+QnfEuGY39siAIpqksy2GDy8Rn0zTcOIwygo2AyxDikYTS1TN1LodhxZtJnbGCddLSGNyTiezGQuYDo5KM2mqWX7kEW76yFU34iRLjYZD9xCS6UipVKBoUNLpAOL6nSxgdGIkci1iWFQXstQWy0gKhaFkTLJrA8ciRPLrN4YRPYcauUMekakGK9SJk8mU6X/yTqwheuJXCsdQRIdhEaLZPCst604U7lb9Gs+jXBlkXYtSMjjggiOJ3bdRjt+L3Ygf5N2mhiN7bdny3Spl3e//Teb/uLfrmwvbJ67+76rbbRReyRzOvYHu/dtBf06mcz2PWnukOPZ2ceztOTf8xcvrvLNO+aoVrZzPLYUIUvjuD2NohCtcaa5Lna2t3mzFiXwaVk0IvI20SzGoh4RlnOkKDDptciGPcJ9hkUp0iph+//vVNUWxYZefvllSqUS8/Pzd50b+irjeYuNDth0gMc0Tc6dO3fbptPbDVEU75rxJDIprM2QyZYhIXkCjuDtClvUywrD+BDiWAo3XjrGjZeOYa8/Seq7P8OkZVKe0xiaWaVd13BIMaX5hQUmCuVrOdrZNP35oMxa8EipdVoZhfHCdSp6joqeQxIskpJF333+Yj2enadupGjbKWKKx+blIeShNoLgYVsK09PbyfbKapGtlSxqwti27EYmM1AjP+yH+baWcoijDl7TY2DaZyHpvjrWpoeGi4LJGgNYr1hI4xKprO4buwGkYH0jhe3EaFkJDFtjILnG1lqWZK5BMeefi+OKXC8dQVwsk5/c9pgxDJWJiXlisoFlS6y+PorRUhmYWe3K5uQHazS30gxMrVPbzNBqKiRHDcqXswxMl1A0m74Jn+0sM4SEy1YpQ0pqkh4wWKyOcSh/E0l0IA/VrTgrzgRprYEouIiB4KcnCSRVPwTnWH5xgY2M4vngISd8UEnYPkBuiXnq5vbbvuAJuEZokXH9v6vi9sJoG7vDZylVxgrxoMqWv08isfsm9Tx/nnp9O0sk7MgfiTuAai0QYt9pfe04gh9GBLw9gEdyXZoRAp/JiLdzxbJpRITlUn19Pdvcep1SxCJsR6lFWxFqBoAdASZxy2I1AvysCJCKmwab6QhzOGV3qO1uhyAIpFIpPM/j5MmTyLJ817mh/ye4j8LfIOARRRFBEHAch2q1ytmzZ8nlcjz66KN3zOdEDUmScF23J3SXFnsZD6KAHOqzAAHNk2kJ1i7G06j45+KF3SDrMhJJVktFfv+f/22yg2WmH7nB3/ruMziISLi0iJPoa9KX38D1RNYag9TNNHG5zWjQeJmLVbBdGU0yUCWLtXN9mNNxZNEkrTUZSAZ6TTlYXx/AcwXaegLbkRkYWKMtxIlnmxwa8d/obVOm7mYRPA9pRy7I0mWK1JALbjfMZRkyoycWiQdp8EHWWZazFHINqlaeUruftFpDb6v0T66jJrcp4mxlCsVsoa+l8U60SaptlutjTOVvIp/yF8FyOc/a2iCZTK1b4abIDq4rMP3YTfAENuaKaJMG9WtKVzW7L+jnqZEiN1Rn5eoIoujRP7XGhptlNL3qL+HDfrHAtdIRFMlmq12gL7GBIEC9lOH4EV9RwnQU6tUgn6cIiM42E0XypYDEICdjB/I4fZJ/DlLOwZvbBgbHckmESos77WrN8vaCm06rgTNTcB+VdNTQragEgNBuhw3i/Lf1nU2htVrnnvZ2+fR0nEbxdvzWxvbnlhcrzFd3y+mA39DZjMrxRGzTnF6rBIhmRymgFu+dw4oI4WmWTTXZCzxWFIsxDcqR+0YZvplsROaOtn+Ag5jAgb/O3E1uqFarYZom9Xr9S+4++pu/+Zv8zu/8DhcvXgTgscce4+d+7ud27f9d3/VdfPzjH9/1uXe/+9186lOf2ve5RY23DPDcbV5mZWWFmzdvcvjwYaanp/ctLbFzLs/zdgGPaZpsLa4Cu61dBREwe9mR5sm0sJB33KDVrSAMGOqErpUEUoASlJNW1/Kc+9Tj5I4e49o3rzHGAuMscljze3REwcVyZcYz82iySXU+QTM7QMuWGMsuEAsaSgcf1lmojpOPVygH+YkhtURrIU7+0NauwoK2nseJmTTX02SHSqhxi+XLo4yfnPfDN32wOd/H5nyRvvFNP7SEH+baWixy6NFbOI7AGv24SNiIjD6wjCjBgOozr9nKFIXYJisvZ1Ee1hhIr7NYm2AyO4uQ82DSN0a7unkUVbKo6VkKCV+xulrNcvy4L+Ou6zGatki7JtE/vdaV8e8bL1EnxeiRMuXlPNX1HLFkC9Q2Q5M1yEEyN4/rCMxfmCR5tMoKw6SpkXCaLL5c4MipHfYNRpq15+IkJ2wMW0GTLSTBQQpCX54s4ASNno4hBzkeEdkN7ocgAb3SGuQQSxjC7gVXFAT00DqeTvn7eMb2gmmbu19scgmFRkirzQtALsx4Klv+3w19G5DEjtlcqPTac+PB9u37Wd8hVqrKHobQu5A3tlrUZnoXXzsiJKY6DqV0b7goqgIu6UE5n+vZvtGo92yLWxaL+YhGzyjDN8NiK2IBNyPOV0LAUHu37yfU1vPZHcCzc+yVG/r93/99PvzhD1OtVrFtG9d1ee9738vY2Ngdj7Vf99FnnnmGv//3/37XyfkDH/gA73rXu7h06VLXDwjgPe95D7/927/d/ft+5X9uNw7mqvYmjA47uXnzJo888shdFxHsNXbmjMCvinv++ed39fF0hicJCBHAowR3prjjBtXbfgjOCwFPJQjVabHdN7DVELBQucVhPsfX8pmf/bv89TPfyjOzX09c1ruKBdmJFqIHhws38TyJ+eoEa9VRbn22yFhmkZhsMJxeYTI7S6uZR03pLC2Ns74+gOvC7Ow08ViZNE36p1dB8Lj6/FFfsTlIfrsONLZSHH/7FfomS9jIbK4nufKFo4wcW0KUXBTVoZ8NPGCMZUo3kiwsjLDRLDJXnWIqN0sm2WDya7cYTK+yWJ1AFi0WahM06xqOBYu1cY72XWUqf4tCYovKYoIbL4ygaQaOEyTeZQvPhcH+OrGkyer1IW6dmeLW+TEyQbItP1Jm9PgCtqVQGGxRJ8nCpVFqmylWro4y9fAs/YkyI6wQQ2d5IQ+unzNzPQHDVmiYaY583Tojh0tIosd8dZzrWzPEhaB5UBa7ygeKZILom79JQYJfC3x/HEWlnYjxA61f2/X7Cp6AGgpd1ar+b+q0t+8FL6QSWllrE1Zx6YTadH13z4+s+Owsm91R8BLYFnWqEjtDFHxA0I1tkHJ39BPhOTSdXoBYX6xyeaM3R2NFLNiK3avfBuBGqFCrlkU1KiwXka/1ajW2IuaNAr+YZbKZigKe3gc8qjgBz8PacVnUCDWH243OunKnBtIOG/qhH/ohbt68ycjICMePH+fjH/84U1NT/OAP/uAdj7XTffTEiRN85CMfIZFI8LGPfSxy/9/93d/lX/yLf8HDDz/M8ePH+a3f+q2uqOjOoWkaQ0ND3f/yEX1cBx1vGcZzu2EYBufOncN1XR544AH6ImLF+x07gadUKnHhwgUOHTrEycIkXA3tLAp4utOVu+8M2ZFACZem+iG4MPCYeqrzz7u310M3piCytTjCRfFRPj//TvoTaxwpXmb45Ssc/7Y5BMEjrrQZTi1Rqg8z/rYyKw2/4TSjVWmYacb7/ZxRihqmKTM/P4UouJhGHkmr4BkS6zeHOHp6+4vWDY2VM5Pkh7e6emMiDooCx952FVNXWHp9FFd2EI8IXUvp/qNNDN2gZA1QiJWYq0yhOi3SzhZ1pcjUDg23dlNh8UwR75hAqVWkmCjRtmLoDZnDT/nJB0PXmJ8fwbJkpg755eqi5JIZqCIIHoOH13wbiVspbD2GrDhdySIVG3HMpbGZQVJsZs9NkT+2gRJ30IkxPlWGKf9cSq0iFSOLKlroVYlY1kG3NBJKm4nsAknJzyXZotRlPILr+aE2PKTgjdZ2/ZuiJif5oX/2k/zfP/5tu35Oy3Apb+wuLujYFzjt7cVMD+uy2R5uWJ06CPckU7sXz2oQ3jUta8e+nb6ckNNoEGrb2cdT33EPxmMCegTjqZdamNnePMjl2V5mojq99gcQnbdRI4RDIbq4QLMstmK9zCMKTFTb7lE+ADAizsGLOFZaN9B3hC73G2rrqBbs5+W4I+P1Pd/zPXzN13wN5XKZcrl8288c1H1052i1WliW1VNN98wzzzAwMEA+n+frv/7r+Zmf+RmKxeJdf5/bjbcM8Oz1A+3M56RSqQPlc/Y6niAI3Lhxg5WVla7KwUotYmcRnLYDoZyfaHe0s3aDjOpKtMXdb6WNapC8DQGSUQ8tLoKAYGwvFhutQTZag+R/JMutkb+H03eDmfxVcvEyIzl/wR3RlmkYSVp2krjSorwxgdCoIvXZ6HqCqanZ7nw6KpXZIRxLoFFKkio20U0ZSaQLRI2tFGvXB+l7cp1Uxl9Y1JhFuq+G44rkqLJFnjYxpPNNtDEYKfrAkdbq1JopWrdiuMMi89VJivENbE/GaTpMnioBfj5kuTZM206QdDaxTQFZ9WjrMXK5Cvl8Gc+DRiPO6usjqDGTiZO+jI2GX2nnxF1iqTYLF8dR0zVSk21sXWXw8LYvSV1P0iSJhcrakkPfQJ2anUcWLQ4H0kOOJXDrQj/OaJZivBT8tv7CLKgCMTno6TFFP9Rm71iQMiY04ZI+zQXtMOGhKhJayFRN1108x8PbMQ/hFKLudRUOOqPd9O+VcI5HFHxAsMxt8Gq1At8deTfwlDb9OeOJ7bkde0fIz7Ipe70LuWw7tCNyJpv1CDWRtkUtgplYUczEcSLzNmYEQOQkiVqmN/G+3mz1bEOQuhWHO4cRsX44Eb02acOknfQ/r3hKpEPs7cZBdNpgt2ROPp+/I8s4iPtoePzIj/wIIyMju2yu3/Oe9/At3/ItTE9Pc+PGDX7sx36M9773vTz//PNviEndWwZ4osbi4iKvv/46MzMzTE1N8dJLLx1IoTpqdObZ2NjYpVodGWoTBZxm73HF4IEN2whLloithvokqh0vld1zGD2MR0DQe8N6ggBGXeGS8zjn1x5HFi2eyF+j8IVnGf52l1SszEAyaJ5MlKjU0+h6glYrwdLSCAMDa+AlENU2Q8d8RuS5ArfOTJM9tEksuV0R1a7FGJxZI0UD2xVZvDKC0dTIDFTpn/QrxQqU2SKHNqLjSBJzlSkUyUQUHNJSjYEH2nTqz9caAziejFO18RoexUMt1hsDZGNVRlRfZcFoytycnUaWHQYHV7vf2XFcRgL7hup6lupahuzJLRTZIl2oADD+wAJbqylUXBqNGOWVPJn+GpaukJ3ww4sAjMLSyznsmQyC4KFIJglFZ/NqiuHpCrGUX5VX0XPUtgLlAgWkAIREz/UZT0dNxwOzpsEcKAmXeMTCahkurrX7MYvFVFzd23UzZDIaO995VATMUB9PJrhHwwKf9eClJpvbPn47AB5CjEcQOgv3DpBq7gBSBQwnonpNBTvfG7qKYhCvn1tm6fFHe7ZH5XhUy6YSUU5tq70MQzJNtiJKpOUIgc/WHs3mesT5RpVYZwyDVsAsD2qJcJAF+std1fYLv/ALfOITn+CZZ57ZVV33Hd/xHd3/P3nyJA8++CCHDx/mmWee4Z3vfOc9H/ctCTyu63L58mVWVlZ45JFHuqG1gyhUR41ms8mZM2cAuP/++3fVzacj+ngQBaxGL/B4VjTjsWomQn8IYTyBmCf1WE22qruBR5QEvFbvd3RcB6vegoR/rrarsFg+xvP/e53hE49DYoVjxdc5WryMZookh9ZQEtthkLm5SfqLdRzVxarKJLM6S5dHGT2xiBrz2VltI8PK1WESuSb5ET/h39H0Gj85j6LabCwUsMY1XGCQDZR+/7pkmGWxNkZWq1AuZyi9HKfviRZbZh+DyVW/+TJ4nm5sHUIUPWxPRpN1ZNFl40aa6ftuoSh215dHjrVRBZNExn+jzQ5UaZSSpGnhqL7rq+sKuI6vEC7jdtnO4mtjJLIttupZlIJLgS3WbmUYOFFDSVSAoMihdAR5Ywsl7xBL+dehYaYoJKr+zyYL2EHyXXQ7wNORroEPPv8j3Jw9TvbJi7hm71uxJAg0Qyza1F0Ea/e+tcru/IniChgh4Flf7TR/huYzOwvGjiosxQeJnYUvAEbb3zeR2J5blnYs5p6DEOFNEwNaETmTihGmaiCZNq1s7xxL5XA13t4hsahKNUFSIlmMGwFGethZD8DzaEXkpKJkdFKGSbMDPAe0RNivQKhpmliWtS/guRf30V/8xV/kF37hF/jLv/xLHnzwwdvue+jQIfr6+rh+/fpXFvB0Qm2dfI5t25w+fXpXaeG9mMF1xsbGBufPn2d8fJzV1dWemyOa8YAREVLoAI8YergTUoqmUO3ZX3XlHtePdkXYXeEhgtfu/Y4eHlktusxS9WCuMcZKY4xn5v5ffH17GfOZZ5n83gaTk7MsLIwzOTnXlcd3UwJXXziKqpk0SikKo53enSJHT19FED2MlkoLGX1TJTey1QWn/vEtlhlmhFVaJFj+QobYhEczlWMq59txJwdbMAizSyPEsxZL9TEyao1CYovZzxeYfvst37YbMGyVW3+VI150MU0FRbERRY92O87kwBqCANX1LJWVPEZLYfrRm4h4iDGbsfsXmDs3xfj9C9S3Uoh9LtaKSn0zw8TJuV25t0VGUMQWK2ezFJ/QSaptFqrjzBSuI77D36+qZ1mpD5PWat0+HhSh2ywqOX4DqdVxAvWg6WX57OI38OBpkWSzNx5vGA6ysHvhcmwwm7t/4zDjaZRMwvRYlvwFOtyK4jiJ4M8d0kiVzmd337eNoNm00dgGunZre0JZ8miLvYuzKICdiCh7jmB5btukne29V68sNnq2CfQKh8IeuZgIMALQpd4FPpnv7S+K6zrrESH9qOKEtG7QzNybCdxB5HKAfTWQHtR99IMf/CA/+7M/y6c//Wkef/zxOx5ncXGRUqm0ywb7XsZbBngAKpUKZ8+epVAo8MADD/T8cAc1gwO/aujWrVvcuHGD+++/n5GRkW58dOeIaiD1RIF2tfe4TiBLIoZ6fxQvhkelZ3/V7WU8jarAzjY3UQS3HlFBp8ooe3x1LfR2p7ezvPhLUzwbfxJV1ZmZuUqjnuHIkddQYjYrV4c4+tR2YUGjrmJKMWLJNq4LkgiyamE4CgMjFVxHYO3GIK1qAhePw4/OApCiSeJUk4XrfYwOL7NUG8NDoE9dY+OlJFNfu9w9husJ3Hh1ANmzWW0MMZhcQxBcVhojHHmnP5/rCqyuDlKp5Bjo3+gKDqeLVcrLeY6evobR1GhoMRo3YzRLWQ4/4edpcoO+VNDc5hT5kTILFydR4iYDh5dZl4YZYxkmCcq5Ba6VjqJIFuV2gWLCz+uU9QLH+/24uGD719RyVVKBYUGnuCDp+AuEK8Ffv/51ANQrDlKjwr0HNQAAeOZJREFU9y3bc0Bv7V4YYzEV2d19o9Uqu70TYpKMvtsogXrVvyCaunvxtALGYxjb+2uqn/cJFxd0bBGyue3jV6vb80mChxORn9ms2z0K0BBdnpxIq5HMpC30LjdfPL8J39azGTOi0dPdC3gitptReRvTphZhh93u2eKLjDZTQaPvlwl4Gg0fmPfbx7Nf99EPfOAD/ORP/iS/93u/x9TUFKurfmg7lUqRSqVoNBr81E/9FN/6rd/K0NAQN27c4H3vex8zMzO8+93v3te57TXeMsBjWRZnzpxhenqaqampyGKDgzIex3G4ePH/396Zh8lRlmv/V7337PtkJutkMpns2yRgAiJoWAKEBBSU4/EgchBRVOTIERcWBQ+gHvDwqSBu6AGOCwmJgpElJLJDkpnJvieTdZbu2Xrfqur7o7tqqrtrktmnB+q+Li6SSnf129VV7/2+z3M/97OLzs5OzjnnHPITMWG989lM4BBkQpowhyxAUCdMoBBPJBpAtYMGhLAFKX34WGKWtMLSkNdEvqw2pUQwC0h+vYZ4yaIDLaySnCaMFyMyFpNMJOJgz5557Nkzj8r8Nznv60fwH3bizA9TVNlB0GtHFi0U5XqgxkPQ66Dl0DgiQRvViXoXk1kmv7wTMWamsvY0HnLxkYOZCLHGKJMXx/M+E/NPEI5ZcbkLseeHaDpRQX5JiGybD5e/jOp5p9Tx+SLZNHsrcFgiBLstOPNjiKKZWMzKjBnxQs5g0Irf46DjcIXaH8ieHcYqh/HKDqoWHU24ZmeRX9GKuQjVJTy/rJtYxISrqxRzsUgz5eR52nE4YpwKTqSmuId4O4866HAV4JwZIiaZsJgkLFLCkTpLxKIsdqKAGfLFxN7EBqdb4nUWFqsl3aGAeJ8dmyVFQh+RiaT8xvl5drR75IgnTiKS2NPS2m6LT0iBQPK9GA4nFGyaBZCrLX5+iy2lVYIvYRKqyRPZLD0rbAGRzkj6tCDo7HYA8salh4ViFv2J2qeXoNfZ7QB067xWLyQG0KkzJ+j13cmORPEWpOeD2kPp1OOMRggkRHwDCbUNRFygdB/tb4iuv91HH3/8cSKRCJ/6VDLj33vvvdx3332YzWZ27NjB73//e7q6uqisrOSSSy7h/vvvH7JanowhHqvVykc/+lGsvaxqIJ7jiUajvf67HoLBIA0NDZjNZpYuXZp04c7Ukyek3V2YBAKd6Z8bSEQOrLYUC5OQIiTQMApgjlmQzKmfJ5CFgD8RhBNMAjGdsJ5gEiCUUgyY+L8tJqH3bMiRKGgmAbs9Gx85vPHU+fz9kTJKp7QyecERlnx6MzlyfEEbCdrIL/NQNL4DSRLodGfR2TQOmzPChNlxFV0eXszEiGIjrzrI8b1FCJXZZFt9SJiZMK4NxgF48IWzaPOPIyaZaT2eT2llN0Epi0A0m5riOJmIUYHjWwsJ5ZVSWtJj2Wwyi1itMaYvO0DIZ+f0/jLEmImiuS4qquO7lPLqVoJeO/4uB1mmAMcap2DLCpNX1onHVUhFTbN6vpDZzLHXizHVmVQ5dzhmJei2U31OfNUXjtk47RlHoCNR5GkxYUrkMQQxnuNplsZRxUkiGhfnSFBinI46S5BN+D3pE1DUl/xbdqfseEyigISMdjMbTeSaHI7kiSkUiH9ubl7Ps9PT/iB1FxYnGX+g5/MCgZ73WSwypjyd9gcm/amiLZC+SArrqOIArHnp16dd5/0AO46ky7R1BQexGF67Tt5GR86dE4noFpXmlKYXWUbDAXWHZx3gjqe/BOLz+cjOzh5QfWJ/uo82NTWd8VxOp5OXXnqp32PoDzKGeCAer0wtpNPCbDYT0jEa7A0dHR00NjZSXl7OzJkz026E3h2qZdo0Bo2SAN72dOLpaA9jA5xZyTe+mCAei1kiFut5CE1RC6IlnVSckoA/MUGEI2HE9FB4/BkI6T+kZjHFnifBmqZYDFFDPN6EdDuWeL2rqRxXUzkeUycTLuvEvWYGVQuPMOOju+PvN8lYbVBW3UpOoZ/2E8V423OxLwiSh4cCuqEQJhV20B4QMJskwlEnx05WUCB3IuXYMGfBhLy4DJoCaGnMJTixCKtVIhSz4bBE8DQ7yBsXYtKE+C6ks7OQ9vZiCotaKCyIXwxHTpi8sm6kmJlcUwD3iUJ87fnYskM4nBFKJsbFEJMXNOFtz8HrLiAWsdDiLiG/xIuMiXC3ianLe+Tcbf4yvIEcnEK7KueOSWYc1hAFOfGJL4YVIdF505wgHkkyE3Q6+DfrU+q1zctz0NGWPlkiC8hi8sQVCQORVP+25L+KAYl4BiTuug3gSeRttOFmSRIQE7VE4aSiUGUXlHx/B/zx43aNH49Po6w0ISE69exj9MnEUZxOUl293Kd6Ox5nfi8N40zpr23c2wkfSz6WFY4QLU7P58R0QnXZkQgndXY8emE5h7Pnme5o7mRP8x5KSkooKirqU0nHQEJtH5buo5BhxCMIwlmJp685nuPHj7N//35qa2uZNGlSr+c7WxdSiOd4ZBGcFpmghpAs5gIgvbeJGNA4GmiGK0TMkL7owy4KamfLmBgl5k2/YQUToCM6ALBEpaTz7twZl1VHA2Fw9NzISqgmlYCliAWLzcmOl+rY8VIdLz6ymqq6Q5x/2ysUZHeRUxhfHRdPbCfkc1AstxMTrDQzDmlLEDlboHS6F7slQr6jG3Lh9LY8zFYTQaGQUMxBaVYbruMF5E/2M64w7lYtSmYOddRgOtJByfQeX5lo1Epl5WmysgJEwmZaDownFjFTUNFFUWU8gV8ysRMBE/bsMLGwheYD5eRN6SbYnI09O8K4aT3u3F3kEcKB2BlDDsgUTQvQGSrAZg5TXdoGpRAOWDjum4SEmYqck6qgAIusht2IASbw2x1cJm7g9f0X9ow5LJOlk+8IBmKIKXJqZIFYSnTH4TAntQ2Qgwm5tdxDPFnO+CSv7bsTiZhQRAjZWRrHdHP8tWLK8xIKxu8BSeo57te0+DCZZNw6IUNBZwcB0KHzOOpN+gA5OmG5kKzzWlkmoBP5CMTS54asSJQuvQZ1OuKE7EiUdh0FXNCm49+mIZ7ygjJs7TaOHj3K7t27yc/PV52me9uhDDTHM9Adz1hDRhHP2dAXObUkSezdu5fW1lbq6urO2Nuirz15lGhZdgrxRKJOHKQTTzRBPOYU0YEcSc/xAHHRQGJRnJuXS7NXR/0jgOjXD7WZUny+bFYzMcAsiWi/nTfRHMyUsprMsjoJBrrUv8ciVg6+M5PiT+yj69AUPI0Lmb5sH0UT3Mz86B5MgoSNGFkEORYqonyWB3egnJhkodjpoqs9j4q5rZhtMiREFkc6p2L2dRNtyaZssRerWeS0t5LJ+UexXhifvdrbi3G7i8nN9eJ0xiXUNruI2SoyblozZosUl3tP9hA4nk1RZTf2RP1RQQV4Qw6sjhhdLYV0tRRSMrkVX9ROblGYAjwwO/79jndMJCZYcVqC5No8mE0yPpeDsopWcmx+JFkg5k/0vhEsWERlBylBBMJmJ68fvzDpGvp9IlIXaZBFsKT4t1msFrJT7GNMKbsBU0xAAiRJVrttexNJIFmzPdIWf/r8PdQVTbhNm1I6jYYScuqSkp7Pj4SUHZmMWZCRdJqidQb1dzFCTvqOJadEX5XlDqff+z6dx9kciWIqSxcBtOmIbqIuP0d0ZOwRHeKyQFo7bdC3/TFrdoo5tlymTZvGtGnTCAaDqtP00aNHsVqtlJSUUFxcTGFhoUo2A83xfBhaIsAYI56ziQsUKbYoiixduhSnjoW6Fr21RkjtySMnJmpTLITiBAwQCFhwkB5Hj/j1ZdZyKF1ODRD1BCCRvBXMAqJOxAZBQEqR4CqPm5BCPIFAot5DkpOIx2KLX49YSrdLMWLBatVRIXkk7DYHp/dN5PS+iQDkl3ey6FevMyXnFCAz+aNx5dp44sKBps4qsmxdnHiriPy5EQpLvDR1VVFVcBShMKEUi1nY767FYQkTjtnjNT6Az5tDTc1BTCYZvz+bgN9ENGCieKILmzP+nSqmN9MdzKKsyk13SwHNBytx5gaQJJnyaS5M5SHyy+Mz9IldE7GP89FBEbl4ycXHqS35jFvYgs0SP18oauPQiwU4x4s4K3s6kJoSXmzWLBGL0iIhKiAfBnNhetg1y2nDqZN4zc6yEoskT2yyaKKrNVkgYE6RBMuJFIw2ACAlTEJjGoeCcEjTrEzTuMyVqCW2plhcR8JxUunSOFDb7fFJXlHAeXXk1Dkl6WQkSBJyTvp3dvl1nlFZBp0cj54c2xKM0GlPJzRrfjppZEcieHWsfA43B2BOysFedmJBPeNQzbW0iPE2LIIgYLPZqKioYPz48YiiSFdXF+3t7Rw8eJBwOExBQQHFxcWEw+F+t2pRxAUfBmQU8fSlGVxvoTbFWqewsFBXit3b+fSIJ8UKi0jiM7PNJIXOfAELRYCQ8vpwoklcavGeFLSkyakBsjS9UxBkRH86CURjUfztyfEZ5Uz7GtugsmeFmJ1jxg9E/MkJ61BiArSkxOs7XSKFOoWAUsiEIyUM0d1ayP7gbHbnLMRGmPx/2cGMG11M+lg7ncGSHm+2i0AU4UhnNWZBpMU3jjJnC4Ig09wxjtqyuHJNlgXa9mTT0ZRNyTk+VZmVne3H782jcko30bCFU/vGEwtbiIbNTDsnLqEumtBB0YQOmhqnUDa1BU/Aie9YEWVVrZw+MJ5Jc5JreY6+XwJ+mU5/IaV5LkyCjKu7hOpLWrDYJSTZRItvHN2hPCyJ1taSueeejMUsfFp+lklTU838AFnA70m/hj5PlHAw+XqbTCYscvJk500RF8iJzYss9YTaAokQrCZ6mtTwzW7vGavJpLRp77lhYzEBKRHa0q7JfF5lh57otFqs5wCtMzmHo3Rb04knS4ekTOGobiO5SOrDA9jDUaTy9DH4xfTXyl0BvFPK044fbw+nHdPzfwMI6oTlLFbURZtDcKhtVLTzhclkorCwUPUvCwQCtLe343a76ezspKuri1gsRklJCQUFBWcVGxjEk6HojSiU1teKtU5fY6Rms5lIJF0mnZrjCSTkljk2K2juZ59fCWekSqStmIHU+ywWsiDrDC1LsKOcWDAJBHQC52aLiVDK5BRLWLl0tSR7VQUTYZEsm4D2X2KJJLeYIkYwiTYcdp26B6eTiI7QIdQVwVJqI4Kd3f83gf37JyI+WsfkgiamF+2jNncnTiFAZ1c+UycdVt/nbbfT8l4ejkUiwagDpzWEKJsIe6zMuDy+RPd48mhvLyISsVEzLT7BW+0xKmpOc2LXZKoXH8UfstNxqAhHbgR/Z64qoc4CCmYFOFpfhT07wvFdkymd1kJ2dohTVFB1To/CLRB1cqJ7Etl4iIUELPZ4K4pwzE5N8UHs5vh9EY1qVJAxkdPSBLp1Fg8+bwyrTvI8y2lDTrGgCYckgl0pJKU9ZUwEMbHL1tzL0XD6wkGSenYBWg83KZYQEWg+OqbJNWkXcGLitWYhfqxLZ4JvD6Z/Z1NEhNL0vI27W6cOLRRFLE5/bX5FekjNGgjrdg8N6exY7ALEctJf26Ujft2+pxOmVKYdD+iIBUyWnmiB0+zEZrOpDvmiKCLLMpIkqe0PBEHAbrczfvx4Jk6cSGNjIw6HQw39x2IxlaRSm78pMEJtGYrUHI8sy+zfv5+TJ0/2u/U19L39tTNxM9hTpEdK++vUUFvAYyGX5JbYEM/9mNPcIEEI90wugkkg3C0Sb6ygETJYLFhiyaEGlytOK2JKoFxKEEvIE4ae9hrIpoREOK3BmFN9jxYdbVEknXYQpOyOYgEJMNPUVU1TVzUvvzGL4qcPMeMHbmIF2YzPPUkg6iQSsFBzeVwuLUomTnRPJBh1UlZxXD2XzRbC4YhQVdVENGKmvSWLgLsQZIHJCYLJdoSxT2+l+eB4iie0c2z7FGzZAUqr2ji9ZzJVi3ocsSUJjjMeMxLuI9kUT/GDAG3+cmpL4rsuMSLQsreA7tJxjMs5jUmQVXGBSeiZwUySRAQbNp1CUZNgIVtHDebzRJLyMIlXk2NPniztNkvPmkZzzUWNKbotURQa0ajXwppeOlobnM5EW+1YtOe1EU3DN4ez57VuV8IMM2GPFNVRVkV1IgjmUIRunV2ENS99UrVEogQL0yfV5u70hZ8lGMFTlE5S9sL03YAv/e3xsRWk78ScOvkoALdOEMVk1dgPJeTUyo5Fm8fRkpAylygNK3Nzcxk/fjyyLOP3+2lvb6e1tVVt/pbaCtvn831oiGfM9OOBZKKIRqNs27YNl8vF0qVL+006qefTwikn34lCYoWZ2oW0y6efwA0k6jZSCSnkMREKp4cAhJBmpZz4RbJSFs+CCSIpK0lB2VKlyFftid1LTsouJiopzcGSf/buDpmwTnGq06KvZLIo1bEKWUVSnBvMAu378ti9aSG/a/wSj757Fy8fvhz3yWyiCfNKXySHHJuP6SUHKJgcouNwFocPVXP69ATKy+N5I6tNJLcgiDM/xMS5J2g5NI6mxil4A1Y6TxczcfYJcku8TJ7fRPH4DvzBLExmkeM7J+PvyiIasuBqK2YSpxhPMyVT/XhO2Tl0qgqrKUo00XdGMMmEfQK1JfvId3joCBYRS0iMc3N69oymmESALESdUvdoWCbgTV9UZFntpFrfWC0Wov5ULz/NNQzr16rFEjseSdYsvjQ7npD2N5Tjv7W2gFRxrIbksFxE7Uoan8UDOn1zdDuCxkRkHRGApNO6wBKM4MtKn/idRTphOV+IsM7uqFvnslh0wncAEZ0ckVvHbxHgWHf6M6lt/2pD/zkwmUxYrVZsNpv6n9lsJhgM4vf7sVjiuSFRFHE6nUycOJFFixZx/vnnM2XKFCKRCLt27eLZZ59l9erVvPfee2dU9faGn//850yZMgWHw8G5557L+++/f8bX/+Uvf2HGjBk4HA7mzp3L3//+96R/l2WZe+65h4qKCpxOJ8uXL+fgwYO9nG1gyCji6UuORxRFvF4v77zzDoIgsHTp0gHHRfWIp6urC/fxI0nHlPCYOZY6OQvYZXO8e6cG3i6FkJJf3d4axKTjKyVo5auJz8pKDecIEOpKfnDERKgtL02Vk6j7cKfaxQuIISltd2O3ZOGwp29+PR0S+TqrV6Xjg5zo0ulIKS6MJlbsXW3xGdofzWGXayEvPHg+Pym+jD+uu5S97jlYzT0ziSxBWXkbU6ceIRTK4vjxSTSfzCcSslI2pQ2TWWLctBYKx3dgMZmwOsI0NU6h5fA4PO4cvO155OcEmDDrJJPmxuXap/ZPIBIy0Z0wJQp7zQTaHNRMOMr4vLgY4mRLBQdfLKOkquda5dm7MCc6jHoS75UEgZ9e/TUOMgMxlH6f5uU5sArpE1S3K322DIckPO7ke8muyaXZNJOPpOGySCj+OwuauJxXI0Qp1LhTe7vjk782iqSIEwCCwR4FnMMRz6fYEi0UIjo7nryK9JyLJRqlW0cl1qmTL7RFY7pk0hFKn2hFWUDSybvkVaaTnN6GHCCgs0Oz69zLALEcB+O2dzN7sxvzofgF3b67hem+2ZRKZX2yzDGZTGoOeufOnVRWVlJSUoLJZFLDc7FYjGg0islkorS0lFmzZnH++eezZMkSamtr2bt3L7/5zW9YsmQJ9957L1u2bDnr5yrdR++9917q6+uZP38+l156KW1tbbqvf/vtt7n++uu56aabaGhoYPXq1axevVptgw1xH7fHHnuMJ554gvfee4/s7GwuvfTSftVQng1jLtQG8O677zJlyhSmTZs26C6kWuJRckWTJ9ShdWwUE2wgRNMfKLtsIZoSUvN26ud+iOZg0TM/DCaH2gAcOvq39lPJS22TOV536GlLviFsSthGZ7xCOJ4j0K7xfN0CesmnbEcWXZ3pSR5zQupLgnhCKTuxglx7XESdqrbzRiFk5uTxiRwsmsgrRy5nfO4Jpj6/ierLXBTXxGt0srICOBwh8vMCmM2iKiyw2CLkl3txOsI4x4UpGOeh83QBYZ+TkN+GKTsLpzVGOOBAipmZMr9J/Ww3RXRtE8jOiyKKAmazTFSyYLWEqV0Vb37X5i/DG84BGbW1uGAXiFotfHXhT/ml5yvx66KzI/B5Y2q8XwsxmL7QsFgtZFuTQ21arzYhqt3R9Pwu3oSTeZ6m06g2fObx9pzDZotP8mKsJxYV1ajrsnN6ztumGBtL8dfGctMXcm06SjUhFCOk43Lg0AmJ4QsTmJjewFFPjm3R2TEBtOiMwRvTf/5tpTkEJTl+j1ri160rIENzgDubJN5o76KxxEZwYTFZu7t4oiyHCdXxpmdbDns4LpzHNaZqCKX30OoNgUCAbdu2UV5ezvTp09W5SZsb0hMo1NTU8PDDD3P69GnmzJlDbW0tf//733nggQdYv379GT9T230U4IknnuDFF1/kt7/9LXfddVfa6//nf/6Hyy67jDvvvBOA+++/n1deeYWf/exnPPHEE8iyzE9/+lO+973vsWrVKgD+8Ic/UF5ezrp165LaJQwGY4Z4ZFlWrR5mzJjBxIkTB31ORU4tyzIHDhzgxIkTLFiwgKC5JIl4VB+1sJhmTWOTLGk7G09nIveTQkixcLbuTSxpJ6fEH+1S8uvc7cG0UJvZEs8YmWNCcr2ONz6B5DotpCqzxZBMLGXnZjVnEQykhyEiAYG8Ep1JtiOCvWeoCLHk3HhXZ5wIHabkokhlkGZ1MhU43TWBU/fP4I37Z1DwSDXTZx6gsvIkNdP3YU84Yo+fcYrm/RUUTejA484jjIzstyNGreSWeCjM61I/ovVoGZGADTFmwWQVyS/14CEHB2GmXRiXEIciNpq6JyLLAuNz4vklwQTZVh8mQaLc3gKJ+doXzeLT8/+P5z09vladrTqJBcmEpBPJ0QtXRsMysRRCslnNykcS9vQQiLbmKpawwdHa3ZhNPRO3oNkl+xOSfptmXg9o1JLa9tnmhALOnLBzCuiEqSw6UmhCESLj0ztSdupErqwmAUlndyTkpn+WV+f9AHJ2+vvlxEIu+5gff54FCuPX2yObuOb1bm6fMYFfHWjmVSFMd8zME94cPjq/iC8n3t/cGSBSMwF/dye7d+8mFotRVFTE0pISQqEQDoejT03ggsEg27Zto6ysLIl0IDk3pCxOFBKSZVkVepw+fZrzzjuPz33uc3zuc58762cOpPvoO++8wx133JF07NJLL2XdunUAHD16lJaWlqSmcPn5+Zx77rm88847H0zi6W33omxfPZ44GwxV+1Vlx1NfX4/f71cbwuV2p8igE8OSQunEYxEtae7UAZ8ZQQZRjJBU99Nt1lW1iZp4v3IJ7CnGn7IsQ1iIr+ASk5ES0kotLFUQ8aeHeeSwgJwyiIDHrFvH4+uSiVl1JtnEITGxo5JTd+AJ0jSnfE6W00wACX9HzxtkTd7M05nP++8vA8BuD7Jk3gtMHt8M0WwmzzuG2SpSmh0XJ5xqzSerIIjraDlWR4SyqhZCEQcFZT1FpQAnj46DKhNOgmRLfgQT+INOynNaybH5EEWBlsY8fF02nIvsjM87hTkiYknUtHSezuH57GQzxVQpNEA0CnaLjhLLk77QsFgseNvT83LKlbYLPeLJmKZa32qJE4RTk7uTNHY8do2Hm9eTyAfFeu6BmEacUlDY8x06O2yJ88fHFNHpu9OtEz4TYhIRnR1LbmUe7pRjsV683vTyNian/o4nardhbQ0x/VCAveNtSFNyCMkWSt5288acGkwCPLO1hbUeD4tkCz9YOg2AHyyu4ge6Z4SKvCzIy4LxFciyjM/nw+Vycfr0afbt20dOTg4lJSWUlJSQn5+vO0cFg0G2bt1KaWlpGumkfbcECSn/V5Rxb7zxBg0NDXz84x/v9b2pGEj30ZaWFt3XKw7Vyv/P9JqhQEYRjx4CgQD19fXYbDaWLl3KG2+8MWRdSKPRKKFQiKysLJYuXaoalKbKqaXEikcKipASZraIlrQcDwhYY0Jap0h/t1V3xxPTJpoF5bxSEvFEoyJgwhSNISVMEc1WMyJgkwS09KD0dkn1cAMIecUkiS6AGLMRiaRPLA6rk/zc9PBGlsWKCJiVwaZwk0lIhOJSzqnkxIWYpF4FQer5sxSJxQsogHDYScvJak5vqaTpjY8waV4T05ftZfrSfciOKBXTmzGZZQor4uG5psYp5E1so+N0OSWTXWTlBTm1dzzl1S1YE1stv9vGyfcKcCwykZcTnxrNZhmzTaJijofsvAidwUJEjwUSZJ4TS49rB7rTr6sgm5JbWSdgE3Qq5SMyQorSzatRd8kah1qzRpPv88SvdyikUappwmcmzY5HaX+Qo7HhCPh7/hwM9HwvkymhpJIiRGJmZCF9ERJzpu/cTA67bqsEvbBcL3l9nGU5aW0JfGGQYxIr3/XRHo7SUGIiOCcfISLwB28OH1kYdwTfvK+Dvwfs3P+RauyJnM4XZo3nC1opZz8gCAK5ubnk5uYydepUIpGIWpfT0NCAIAgqCRUXF2O1WgmFQmzbto2SkhJqa2v7Hfo3mUy89957XH/99Tz22GN86UtfGtDYxxoymnja29tpbGyksrKS2tpaNYE3FF1I29vb1YRaXV1dUnFXGvEk7qWYTjhKiFkQdLqWWkVTkt8TxNtf6+14opoQiPLMe1r8MFFTQ2KNh9MkfwQUN14lCZ0yN3oTsYqAjlpHDKXveOSYg5wsnVV8yIzHm77j8bZHyKJH3IAoxLPgiWuYnQjx+VNaSUQTq2ZJo76SYz3kZDMnc1ggIOOUzUiimaaGapoaqnn551fy0e88i3ysgunL9lFZe4pjOyYzed4xBJNMUfFxJNHE/renY3dG8XsdFBTHQ2ydR7OovtiNxSEREa2c8own0AIljg6yS+KfXOjsJMfnI88UD1JuaDkfUvLqOTqy6awsOyFv+uPU3qKz65QFwp7k3yAn24aSTRMD2qLPnusjJAz5tOUsnR09957d0XPOcDBOeFoRgbJjiqPnvD5v/D7LcspEJP0iS3th+m4uLOpPsqKO95myoDB3RBCzzOCIP2QdERi3uY2b3a28ZSugsdRJBwKff8fPfXVT1bcfaQ0QnjaVmaU9K78LJxVx4aTeLbEGC8WloKKiAkmS6O7uxu12c/ToUXbt2kVubi6BQICioqIBkQ7Ali1b+OQnP8kDDzzAl770pX6dYyDdR8eNG3fG1yv/b21tTWr61trayoIFC/o8trMho4hHueiyLHPs2DEOHjzIzJkzmTBhgvqawRKPLMscP36cAwcOUF1dzcGDB9MqilPbXyuPqF77ayFmSRcRAFmCI+24p9Oiu+OJaNyBFU5o2tcOE3seKpPJhIiMTZLUyVlKEE9q7ic7Jz6JmaXk3A9Att2GyZx8c8eidnze9AnS3y1gLkkfb57DTgywaB+ScAwSIRJBuWApMutYKD6awhw7ncpBTS4rEoyApr5FxkzAn77jEAMFvP3MRbz5zEVkFXqpXbaPSNDO1CUHsVgkju+cRO2yHncBD7m0U4TD1oEpEU6ymaNIsompU09hMkm07c0lUFFCidzGjZbfYpbjr/Nnp4eSQjqyaW93lIgvfVcghtLVVYJgJseenID3eXoo1yr3VM3Ha0bi953iXODM6jmnVjDg9/ecw2JN2OBo7sGgRk6dX9Dz6Af98XHHImEiOmFEgC6dvEtvjtWS044QFpm020vTJAdCiYOgZMJ8yMtfbaWMk238qr6ZDZEAOR0St9taqJ5ZxReqquLnlUXMKY4GUwtG17VZcSkoLCykpqaGrq4uGhsbsVgsuN1u3nrrLXU3VFRU1CfnFEVV9r3vfY+vfvWr/SaugXQfXbp0KRs3buT2229Xj73yyissXboUgKqqKsaNG8fGjRtVovF4PLz33nvceuut/RrfmZBRxAPxpNuePXtwu90sWbKEgoKCpH8fTBdSrYHo4sWLycrK4sCBA0iSdMYdj6JqU5pzaSFH03M8EO+9kxqx8HssuonKsLfn2P4DcXt/ISQlUVQ0GrfJj3hCUBJXLFkspniPyhSTRF9il+KwmPCTjO72WFLeIP4lBEQdpaTF5NCVU3e7I2QDkiY/I8REdbyervjJsizWJOcEhcE7W3uOWkwaF6IU0UMsZqZAp/ajs63ndwh05tLw4hIaXlxC3edfoGt3DTMv2E3JJDc5RfE9hJccqjgGCyHQbqUzXIzflsekgibMCSIqm+nleFchzvwg61yruSX0O7IIEzGlT3jejvRrZbVaCKUVioLDkj5+WRLwdyUfy8/vaQQX0uxURc1vpbQ6CGgIxq4hMK1FU2d7enGzT+N6LmtqgRDi91OWE3xh/QnTWZZDqjg/IMZv8MkbTxL1RmieW4JcnUcEE3c2Rvjy3GlEJYk/1bfyYqvMD+aWUZOo2/nWgsnckug4PHVqNZMnT1bPm0o6mYZwOMzu3btVSbQkSXR2duJ2u9m3bx+RSISioiKViPQ8I3fu3MlVV13FN7/5Tf7jP/5jwOrc/nYf/frXv87HPvYx/vu//5srrriCP/7xj2zdupUnn3wSiC/+b7/9dh544AFqamqoqqri7rvvprKyUiW3oUBGEU84HFaLn5YuXaprKzHQHU8kEqGhoYFYLKYaiCoEltq0yWkCM7JKOMr0GuxKJzwxbCYQSp3ewRw16+yEBCxSevw85Ok55vGEABuSP/mzrHYTUWSyzT1kElXk0oHkm9bptBAkPdQFYMGKnjrUIqXfCkGfKUnOqyDHZkMGJM2kaIpqnLATO7FAim9JPJwUwST1XFNJI/m2W4QkmXcsYsKjc81tOvUyAGLQzuEttRzeUgvIjJ95gikfb2DBJ3uK35yFUdynBKaXHCAmWWg5WUzosIwYNVG9PK5ws1piCAK8WrGUJ9+5ElJcVpw2nbBTSMask89JzeUACJiJ+JIn126NFCzHbukJu2lu9Vgk/r1zc3t+q452famvKMYJ06wpbg4Gtb+xRtTRFR93NBpGNCWubVgEjYihPQLOxk7uE3JZ6+6mscxMSDBzzmvt/GnpfKKRKG63m5c2NNHW0c3sIg979ngpKSnh+poy/nVGBVp0dnbS0NBATU3NkChURwrhcJht27aRn5/PrFmzEAQBs9mskkxtbS1+vx+3201rayv79+8nKyuL0tJSPB4Pc+bM4fDhw6xcuZLbbruN73znO4MqCelv99Fly5bx7LPP8r3vfY/vfOc71NTUsG7dOubM6XFU/c///E/8fj9f/OIX6erq4vzzz+cf//iH7nw8UGQU8VitVkpLS6mqqup1q9qX1gip8Hq91NfXk5eXR11dnVoPpPwgoigmdT4VhPiupzPxMcojmjqRAnS1B5HRKbKMWLHohOAsOj5YHs3koTRpy3dYklohKzsevzsAk+OqPkui/QEi8d1CIvShVD/bTKbUvD9+j4jZnNgpaSDE0sdlt2ap0mwtAt0STsCikfqKwZ4z5mRZ8QF2c2q9UPxcstZpQbNrMskpSi+nk+wckeSINERSq/4T6EoqyhQ4tXcSHpOJg59cSG6gg+Lv7KF0tpf5X4g3prOYYpRXtnPsUDHVy924AyX4Irk4/CHWlFzM5x7+Ljkfz1ZJQB1yJP1aOR122l3px2Oh9IWGKMqIwZRHT3OryJq+SxaLpvdOIm+TFFLT7KiyszVy6YCSt9HkfUI993hUY6VTWipxaL+IWYjhDZugNcjjbidlWTZ+1dTK29kSDg9smDeZIqeN62rieYCTngATquMEZ7PZqKys5MbKSiRJoqurC5fLxYEDBwiHwxQWFlJaWkpJSQnBYJDGxkamT5+eFEbPdCjy5by8PGbPnq1LGIIgkJOTQ05ODlOmTCEajdLR0YHL5eLGG2/k9OnTSJLE8uXL+cpXvjIkvXf6030U4Nprr+Xaa6/t9XyCIPCDH/yAH/ygNy3g4JFRxGM2m5k2bdpZX9Mf4mltbWXHjh1UVVVRXV2dpq8XBEG38C9XQzzKp+m1vxZjdvLy0/2Von5JR+2mTzydbTKF6qDi/+tuTtb6OJwWQogQ0vp4aSbtSAwpQTyhxGuiOjJru9mm68uW1hGTeGFpro4aIqbEXDSnsSKrZKYQTNiTvFuxmARiyGTZzOquTbvjEcPJr4/GTHh0rnnQk3YIAKdVJx/jj5OkP5bL4f+pBuDVtvOouUZkevFenO42pl4Yp7aSLDfFDje+Xfl87vffBQQiofQdl6dDp1A0JmDSsVbpbE2/V2XJhOhP3gk5HRZV3eXv7Il7StodT8KwVNviurOj537ShnajsTghBIM91D+1ykFFxQmam8sRNIrL//3fcUSDXt5Y70aSynmqK5uPVcXzi4+XJ5L5qS0GgAl5+nkXk8lEUVERRUVFTJ8+nUAggMvlorW1VZX5lpSUkJOTgyzLY6LxWSQSYevWreTm5vZKOnqwWq2Ul5dTXl7Oc889x/Lly5k6dSotLS1UVFSwZMkSfvOb3zB79uxh/gaZhYwiHhi6LqSyLHPkyBGOHDnC3Llze1V5nNkoNDnUptf+2mrORzClvz/QGSUU9kMPpQBg0tlZRDWTUEGRPT4BpfivhUIxQCDHYlJX4LImMW+Oiuo4c3Ksqrgg9UoJshVBx7ans1WHVCO2NCdrgNzEljuqUafFAj3vz8u148GLSRSSLFFj4fiuzay9XLJWXJA8hlBYwCmlX68ch75FUqA7/ZjNYgMixII9V8Jpy2OXaxK7XPMxPb2dyUdOMP2qFmq+0MmlL20m1+vjJ8JlRJGJBNPvNbtO3iYUkJJcBBRIOsdASLPXiWqk51ZJUElcWSSIIkgJxVlIQyaCZretdae+5Ysd/On/otgcmgWMXMWhg8V0d4fY01LOnq1TKKqoZ5zVTkWpjYuvnIMY/SPTJw6dUkwQBLKzs9X/urq6mDBhAtFolMbGRiBOQqWlpRQVFSVFHjIFyk4nJyenX6SjRVNTE6tWreIzn/kMjz32GCaTiZaWFjZs2EBlZbpj9gcdGUc8Z0NfQm2iKLJr1y46Ozs599xzyctL93hS0JcupEquBwkcZomQqAlpBC3kCOmTdo6tiOxsnap1vSZZkgU5IiLYzHR1hQAH5ggpirQ4EZo0hXxWm1mdoKLeMOTHV6AqWegU53W1i4g6x0WdkBCyg8ICJ02phyPxfplacZxV7pFCexIrdjlFCWW3mQkj4WnX+IRZTT1q8BQTVhmrbnO1ztZeFh7R9ElLTvxW2rVBl6tnMs6y2Tm6sZSjG0t5ac4S/plzKTW2g0QDcZJMco1Wvl9HOhlbbVakWHqOJz8nl64U2yxZNhHoTCbULIdZNcuI+np+IGVtIcXM2KxBIlFn0g592bJSHnjgGH/6k4TD0XP8m/8xke9+20bjnhJ2vvuvhAKFWIR4fUt+voUpkf+ionRcksqyrGr4JsC2tjZ27tzJ3Llz1fyDVqJ8+PBhdu7cSWFhoUpEWTqecSMNhXSysrKYM2fOWXvq6OHUqVNcccUVXHbZZSrpQFy6rIgAPmwYc8RjNpuJRvXdewFCoRD19fWYTCaWLl2KXWfiSj3f2VojaP/VQZSQJqQSDFrI01mkiUErZquegk2fNM1hCclmxpSI6TsxJeUW7A4LYST8mklb1Ox47LKsTpDhRHgoFkz/LKvZlqa2A8jXecjFiI3OjnQdracjSj4WxKhGcaXZGeTm2vCSTjxCQqhgEnt2kSGNu0JuVrLFjyRZkOX0waZKkdXz6xBP2C+RA4ia3ZnN0kOSEa2IQ5LY6ZzHTuc8iLwbf38g/V7LdmT3yMGVt0bNyDq7M9cpvToeE3Ik+b70aPKHkyrgtCVELOZQQ21SzMpLL21hwwYoHu8hHLJid0QJBQv5xu2lfON2eOXdT9Ky4+OcdL/F8o/Er8XMafOw25akjaGiNB4B6IsdzGDR0tLC7t27mTt3LmVlZerxVIlyMBjE5XLhdrs5ePAgTqdTzQv1pZHaUCMajVJfX09WVhZz584d0Oc3Nzdz+eWXc+GFF/KLX/xixL9DpiLjiKcvobbeXFK7EvLMkpISZs+e3acfuXfi6fmzNtqUZzfTpdGVBoNWTI708UYDZl2Z9dED+g1Eot1RzLlWtRBcCiSv/hWO0RYXarf84e4QJMRBdnsiX6BjoCjGLLqhgvbm9F1ELGpP690DYEpU6Ns1iW9tca1fqUmJJn9OyB8PF9qEHg+3uHowDm9XKElBZrbaCeu0IGjvZcejl3uxWixAJKlJWySgISGhx/XBJMs9ocHER+TnOUiN4AV9OspEL6S2PwDIycohkMrdsolY0EpBQTtz53h5f0tu0q5qVnU+v1h3mvff78IiOHEdqMBe2InJBN/97gL2HbYSPnElMZOZ6sqeZ2H5R76OgMDMafPUY3YdQ9ORRHNzM3v37mX+/PmUlKSbhGrhdDqZNGkSkyZNIhaLqUn5nTt3IkkSxcXFlJaWUlxcjM12dsfowUBpu6K0DhgIYbS2tnLllVdyzjnn8Ktf/apPtT0fFmQc8ZwNveV4FGfpmpoaJk+e3K8upGcLtUU1oQ1nilLNH7Ai6FjHRfxW9O4zj17XKUBIEI0t4bcVaE8mKElRfAX0xQW5NrO6WwgquZKozo4raEpKWCtw6uQtkAWIpt8iilIrrNnl5NjN6g5NUqrtYyR5y5mFeEFrRFOIK55BTh0Om7DoFS7q5k3AaUnftcUSoglBI/3OdlhVcYNPI2MWtCKTBGl3d6Yzn19H3GCS9CfCjhYRk9nPdz/Zzts7orx3KAefqYxcRxfvv55HZWV8B/Bvf3Wy/2Q3p8NmqsryufDCj7FgQRdv7jSRFQVPKIIwTqC5uZnqSdN1a0NGYvfSH5w6dYr9+/czf/78fvsrWiwWysrKKCsrQ5ZlPB4PLpeLY8eOsXv3bvLz89WQXHZ29pAKFJSdjt1uZ968eQMiHbfbzcqVK5kzZw5PPfWUqqQ1EMeYuxp6XUi1ztLD0YVU0tzUthTJr89vAZ2dTcSnb6Xj0OlRDyAk+pJYbQm2StnUxfM2AoVZtrQwD4C3LQDT439WQl3IQCQKmn49drtTbb2gRVebPiFaU11RgRyHE4gkiRtkjdouL8eGRyk3jMTAkbBLMZkQkciy9pCU02ZW1VzhlHaSkmBRczRaZNmzdK+BGEm/nYWEijCkcWYQtFtYDSGJYRGcIIgSS5ZEaGwUiUjpZGa1OAgB2SYPfikvcX4TSDG+cekJLj0vi5//0ccbe52Igswfv+/lwnN7Vvu7D7ZTUZJPkcao8+6PQE2Z8vf4IsDhcFBkdpBbkMu5U6eqHSz3799PdnY2paWllJaWkpeXl3HKsBMnTnDw4EEWLFhAUdHgxAqCIJCfn09+fj7Tpk0jFArhdrtxuVwcOXIEu92uklBhYeGgwlnRaJSGhgZsNhvz588f0Lk6OztZtWoV06ZN45lnnslIwcRoI+OIp6/N4CDuWr19+/YkZ+n+QmmNoIUsy8S8nUCcxCTNStKWUn3pDVh1CSbo1TMPBb/ejAnI/vineH0RwI5dSq6BQYgTT+fpnjif1Wbp0Q9ochgBTdjLLIuI9Nz4XZ1iEmGo38usXxwmiOkPjbdDpAiwatRxWglwTLOLMUuSGkqLBGKACZ92N6cZi82SXHckY8XhdJC6weitjqfbnR5qkxMFuxaNLNyn8X+5/toCjnWcpL5eIpTYQQpRmU2b6gB4cI2XJ/d2EwkH6cotA5OJQLfAhZMP88LPKti+z81jz3Tz5m748qeC3H5DPHH+0cWJfjhSPuYUop9dk05mNWXJf/f7/dTX11NcXMzMmTPV+pDJkycTjUbViVfJZyok1Fe7luHE8ePHOXz4MIsWLUpzHhkKOBwOJkyYwIQJExBFkY6ODtxut9rWoLi4WC3oPFuOV4tYLEZDQwMWi2XAO53u7m5WrVpFZWUlf/rTn4Y9JDhWkXHEczYooTblwXQ4HEnO0gM5n1YlJEkSu3fvJtKVDbZ04kltf93ZG8F0Wzh1qhtIthcXRP0b0S4nFGqJjwqnVOw7s6wEEUHTsVHbVyfX2hNqS6rvEWNJ4giLxYle41lTL+Pq0Mn9yFEzICJrdg52oSdMphUMiMEoZMUffpvFQgQpyUMuqNnlOCxCCvFY8Helk0nIpz+x2swOgoBFDhNLyJXFRLixMNvOY/+Xza9+dZrG/CwU15s8ZxGvvBKvqq9aK3FeqJ13A1aUR+OKhU6+doWZbEceB0918T9/78R2gcgjX40XPi6YmcVvH+hdfZVKOn2BUvBcWVmp2+zQarUmmVcqxZr79+8nHA5TVFSkElF/Jt6hQFNTE0ePHmXRokXk56d3LR1qmM1m9bvOmDFDbWtw6tQp9u7dS25uripQyM3NPWPrlfr6eiwWC/Pnzx8QeXu9Xq6++mqKiopYs2bNiF/7sYQxSTyRSIR33303ybV6MOdTdjyKrY4oisydOgtO9rxOsIAcA0sseSKMRC0IOkWWh/eHiKQ1qgEpok+Q3rYwDnLIL7ATIN4OW0tnwWA8MW+K9CjCtIl/WZtvyelxOo76w5DVsxOMxqy6uQC9QkfQr9I3yfHaGO2kGtaEstS2CIBN0CjIQvEdj0nsIR4TPd/H05F+vWQd08pwgniyTV5kMUZAiNdK+ToFSq37efYeF+9vD7P+7QIO+EpBkokErFx11TiuuqqCG9eFmBXoYG+HwJJJPd9h66VQnJ2cO5k3tecRqRnv4Gc3J1u/DDUUgcyUKVOYMmXKWSMAqcWafr8/qZ+MMvGWlpaSk5MzrCG5I0eOcPz4cerq6s5YwjBcSG1rEA6HaW9vx+Vy0dTUhMViSaoZUshF2emYzeYBk47f7+dTn/oUTqeT559/fkjtZT6IyDjiOduD4Xa7iUQizJkzZ0jsNhTi8fl8qh3G3LlzOZ1SZ2G2meIW9dH0CTq+A0iGp8NMfkX6d/F3CCg1OVpYonHy7PaEATtyIGUXlbguTjTGn5prFdT4soU0DgB2k5ycsA+ZVVdrLWxmnQ6TgNPsjLex1g4l4T8W0oT0tI7TMU3YL+qPQCLEH3cugKjmfcUFVr75cDbPPOPioD0rrTdLNGjBKgdYOsXF+4ezCVlKiIWt5FpbeftxG1Mn2vnn+6384s8+IpEIT3w3i337vMyfLjGn+hT5+T58W0vZE+0h39+ucui1kaE4e3Slru3t7Wzfvn3A/mVau5aqqioikYgakmtqalItqYYiF6KFUqx94sQJ6urqyM3NHZLzDhZ2u53KykoqEzY+nZ2daTvD4uJimpubsVgsLFiwYECkEwwGue666wD461//Sna2vtzfQA8yjnh6g+Is3dLSgslkGjKPJ7PZjM/n491332Xy5MlUV1cjSRI5KU3czNb4pCmERVKdUWQdG5xY2Ek06ko7bjNnx/sGyCnEliCv3HxbPC0vCRCO9vTeSeR4JA0hCUKPa42oKUy1mHscC8K+MGgERVZ7lr5Dto5EGOKtEVIhKUSryc90tvQYpZYU2eiy+InFLMgaEnrjnzW8ub6Fv7zbzfvKuCNObrttKrfdNpVrHw1Rnt/KEZeP9715BAtKsUTDrLlX5mPnxMOe7zS08b8vRLj/qwUUF8SvzcfOyeVj5+Sq4deSkhJmzpxJJBLB5XLhcrmo7TjE22/HzRrLysoyLiGvFFjOnDlzyCrZFf+0yspKRFFUJ15tLkQJQw00FyHLMocOHeL06dMsXrx4QHnWkYDJZKK4uJji4mJkWcbv99PW1sbhw4eJxWLk5ORw9OjRfos1QqEQ119/PcFgkJdeeiljSDfTMSaIR+ssvWjRIt57770h8XiSZRmv10t7eztz585VY+aSJJGXYitjscVzGHJIh3h0bHCkaBZ5+da0FsBhnxVBkJBTiCfQHiMb8PqiKP21zVERMUE88QJSkWBHT0jLYtWYfWpUZSHNn7NtQlJrhEDQrFdugqTjogxgM6WHDGKhRJ97p4VxM8Ps2yckFUSet6yc3z8wid/+9hj351jx+SNEs22YTTa+/OUqzl0Z4/9t7eCaaWa2FIooKq6nb7NjtzqA+MO79YCLnE85mTGlJ4eydGEOSxemT27d3d00NDQwYcIE1ZPP4XAwceJEJk6cSCwWy9iE/OnTp9m7d29ageVQQuugPGPGDLxeLy6Xi+PHj7Nnzx7y8/PV65GVldWnZ0tRlCptRsbKSl8QBJxOJ52dneTk5DB37ly1rYFyb2g7jfYmhQ6Hw3zuc5+jo6ODV155ZURyWh8UZBzxpN7wqc7SSnGpKIqD0sZLksSePXvo7OyksLCQiooKRFFUe/PkpZxacSEQg7G0jpQH9qSbhMXCDjye9CKUgMccJ56U4zk2BzKQp+x4ANEXhkRPe5OST9GIC7T+XoVOfZm1vysEmrSEJNh163gskn5MutslginGyjmn2HNM5kh3GbIQD8tZzU62bl1MNCrxxX94ecXlxY8NMWrCajVxyy1VHH8pzA8+GuXFPUEmFcYn97qJFp6aGL/AV83VSL1TnB4WT+/bROZ2u9mxYwfTpk1j0qRJuq+xWCyMGzeOcePGqQn5trY29u3bRzQaHZLV/0CglR33t9ZloBAEgby8PPLy8qiurk6SJx8+fBi73a6SUG+OAbIss3//flwul9rbaqxAFEUaGxuRJImFCxdisVjSOo0q10Kx8VHuDeV7RqNRPv/5z3Py5Elee+01CgsLz/KpBrTIOOLRQs9ZWlGgDYZ4IpEIjY2NRKNRqqqq6O7uTiIdQRDSmsGZrPGHL6bjtXboQHo/HhCQdPzPLEJ23LIm5TT+dpEsSDLVtMQkNWQWLwoVsIpmPQs2OjVu1kVFdsylIVwue1pOKibaERTPHFlSLY273DJYZK6afYQZk8yseR2OeMogKvCTf2/m1uvjoa5oVOa3a07ywusxWs3AeLBaTfxLTRY/qzKRZRPpCvaQyQ8vje+ErpozPLUMym5h9uzZvRrBpkKbkK+trVWVUKmr/7KysmGbUGVZpqmpiaampmGTHfcVqfJkJSGvOAYoCfni4mKsViuyLLN37146OjpYvHixbjFrpkIURbZv344oiixatChtDtHa+CjO2gopHzhwgJ/85CdMmTKFo0eP0tHRwaZNm0ZswfBBQkYSz5mcpRViiMViA5Ir+nw+6uvrycnJYeHChbS2tnLixAlOnjxJWVmZes7U9tfKjkev/bWok+MBfZv+gMeGySSltaQ2J2xo4r1WEqG2SCzNXTrq0dTIWASWnh+lsTGCL9gTfho/voB3m8rZvbubm9abOBLy4bc6wGxBlO0IksS5447wfw8X8V+PH+eFd610RM18cs4bfOFyH6Wlpdx6XSk5uVGONxcyY2rP5Gu1CtzymWJuSRnXxTN6iKUwa2SS9E1NTRw5cmRQu4VUJVQoFFLzQocOHVKbeJWWlpKfnz8keSFZljl48CDNzc0sXrw4o/ICZrNZ1zHg6NGj7Nq1i4KCAkRRJBKJsGTJkjGl3pIkiR07dqgh+74sXLOyslQbn2g0yokTJ3jwwQdpaWkhNzeXb3zjG1x55ZVcccUVo6LkG6vIOOIRRZEdO3ac0Vl6IM3gIB6SaWxsZOLEidTU1KiruVAoRHNzM/v37yc/P5+ysjJKSsuAngnXlCCesE77a2T9yxhLbfYFSFEnkk4Bp5Courc5enrVhLt65MXXfzaH1k2dvPN+VFV+CSYrL720CICfvOHnpy4fVr+MlGiFPXt2Pv92LMKNnxDo9vv46YudrD9gYtmiCL++p5KjR4+y+rwT3HPrPAoKizAJ49UQlNLAq6SkhNOn4xNvplRgKxO3ktAeygc+NS/U3t5OW1sbDQ0NQ5IXUnYL7e3tGZ8XSXUM8Pv97Ny5E7/fjyzL1NfXDzkpDxckSWL79u1EIpE+k04qTCYTW7Zswel0cvToUU6fPs0LL7zAj370I2pra1m0aNEwjPyDCUE+kyPnKKCrq4tdu3Yxb968Xnc0mzdvZv78+f2Kqx47dowDBw4wa9YsVV6ptLxWHhhltdvW1kZnZyfX519OQIjfoOVf3UHrjiAlM524PzMv6dyVnt2crk9v5JSdtR9/oDbpmMkcwmwTiQazMcsRxES7ZNvMwxT83Mqif3Zy/bEsfvWrZhqum4J/fjxn8XO5i88vib923N8Elst+3vfbOHB9fHy7TseoyDdRnG1ClOQzFi4qCsH29nYWLlyou+KWZVkNQbW1teHz+SgoKKCsrIzS0tJRC68oubmuri4WLlw4YhO3tlCzra2NSCSihqD6mheSJIldu3bh9Xqpq6sbc7uFnTt3EggEWLRoEWazWQ3Jud1xCY1yLc6UkB8NKDudcDjMokWLBrSAkiSJb3zjG2zcuJFNmzYxefLkYRjphwcZRzyyLBMOh8+4enrjjTeYMWNGn3zZJEli3759tLS0sHDhQjVUoM3n6CEajVK7M5tWKf4AlXylHveuKORJ8B9Lk15b2nEA147paeewmw4SlmoosHTiCduRzFmAjNniZ0lpK//4RTl//HsXv/1bhIO5Uay/dDLvNYn1H4krmy78vwirJ0q81QK3zjPz8enxB6bVK1GeO7BwViwWUx/ChQsX9nnyUyzrXS6XqgZSSGi4CxMVKPF5ZQIZrcpwLSm7XC68Xu9Z80LKTl4Z+1iyUlEm7lAopDt2bULe5XIRCoXUhHxpaemoEqxCmMFgkLq6ugGTzre+9S3+9re/sXnzZqZOnToMI/1wISOJJxLRbx2g4O2332bq1KlnTSYrXQ6Vh93hcKhy6TORjoK6XQ72JQQCPz59iFefOsi7DSa6v3Jp0uush/cRPTGDMruLXEuIw92lYHFgDh1m5jgTr/+2FJMg8OvnOvjfDVEW1Yr87Lvj0z7vlaYA7WGRz9QqPl9n3rn0F6FQiMbGRqxWK/Pnzx/wqjQajaqTjNvtVlVQZWVlFBQUDAsJKYIQk8nE/PnzMybsByTlhTo6OtLyQqkqqkwa+9mgkH00Gu3zbkFxT3C5XHR3d5OTk6PuhkayfmqoSOfuu+/mz3/+M5s2bWL69PQF5kji1KlTfOtb32LDhg0EAgGmTZvG7373OxYvXjyq4+ovMo54IK6PPxPef/99xo8fz/jx6ZO3Ar/fz7Zt28jOzmbevHlJ1jiCIPTp5r9wr50t/ngcf212N+dW+Hl/awP/uukCLik6xD9bcukomozp6HEmtsO7TxWTl2vDHxD5xf+109oR5Sd39j7GkYTP56OhoYGioiJmzpw5ZFXrWhWUyxUvmFVIaKjqY4LBIA0NDWRnZzNnzpxRN8E8E7R5IbfbjclkQpZlHA7HmNvpKIQpiuKACVNraNre3q7WEw13/ZQS1vT7/dTV1Q3ousuyzP33389TTz3Fpk2bmDlz5jCMtO/o7Oxk4cKFXHTRRdx6662UlpZy8OBBqqurqa6uHtWx9Rdjkni2bdtGaWlprzUb7e3tNDY2Mn78eKZPn44kSWr9T19JB+B7J618gjD/uzXKv1Z1Irt3M336dAqKx5ObFZ9Qjp7s4OmXmrmototoNB73Lysro6SkJGPi3B0dHWzfvp1JkyYxderUYVtxKiGXtrY22tra1PoY5XoMZOJSVIiKCWQmJ7BTEQgE2LZtm9rccCB5odFCLBajsbERWZbVWpfBQmtb43K5iEQiSfVTQxU6HSrSefjhh3n88cd57bXXmDt37pCMbTC46667eOutt3jjjTdGeyiDRkYSTyQSOWMX0sbGRvLz86mqqkr7t+PHj7N//35mzpzJ+PHj+5TP6Q3xIciq+eHcuXN77aKoxP2VSdfv96sPVVlZ2ahNMs3NzezZs2dIrVj6Au31cLlc+Hw+Ne5fVlbWp7h/Z2cnjY2Nw06Yw4FAIEB9fT2FhYVqW4Pe8kJKM7NMgWKaaTKZBuxfdjYotjXK9fB4POTl5anEPNC8oSzLqoBj8eLFAyadRx99lEceeYSNGzeycOHCfp9jODBr1iwuvfRSTp48yT//+U/Gjx/Pl7/8ZW6++ebRHlq/MSaJZ9euXdjtdmpqatRjkiSxf/9+Tp8+zcKFCyksLBwU6UA81LB79266u7tZuHBhv3yolIeqra0Nj8dDfn4+5eXlI6YIk2WZo0ePcuzYMebNmzfqRW6KOKGtrY2uri5VnFBWVqbbQbKtrY1du3Yxffr0IfPlGykou7SysjJqa2t1772z5YVGi2SV7ptKHnCkwprhcDgpJGez2fptaCrLMrt378bj8VBXVzegHZQsy/zsZz/joYce4qWXXuKcc84ZyNcZFiiLtTvuuINrr72WLVu28PWvf50nnniCG264YZRH1z+MSeLZu3cvgiAwY8YMIP6wbN++XVXd9FdEoIdwOMz27dsBWLBgwaB2LKkybe2kOxymioqSz+129yqXHk0orsltbW20t7djt9vV65Gfn69a+s+ZM4fy8vKznzCDoHjGTZw4sc+7NCUvpBDRaPnIRSIRteXzQLtvDgW0zd1cLhexWEz1TustRCnLsiqzX7x48YBJ58knn+S+++5jw4YNLFu2bCi+zpDBZrOxePFi3n77bfXY1772NbZs2cI777wziiPrPzKSeKLRaFJztlQcOHCAaDTK7Nmz1Ti60+lk3rx5ScWl/cnnaKEk4gsKCpg1a9aQPviKIkyZdB0OhzrpDoXiZ6By6dFCqjhBWTBUV1czadKkjBYSpELJpU2dOnXAdR7aeiGXy0U4HE7Kkw1XyDYSibBt2zaysrKYO3fuqJFOKhQjX+V6+Hy+tBCllnQGWh8lyzJPPfUU3/72t3nhhRe44IILhuHbDA6TJ0/m4osv5te//rV67PHHH+eBBx7g1KlToziy/mNMEs/hw4fx+XxMnDiRhoYGKisrVZmj8r6Bko7b7Wbnzp0jklcQRVFd+bvdbiwWS5Isub8PfzgcpqGhAavVyrx588aUbFeWZbXeqqSkhK6uriERJ4wUFG+z2traM6ot+4Mz1QsNZV4oHA6zbds2cnJymDNnTsaQjh6U6IHb7aajowOHw4HJZCISiXDOOecMKIwtyzLPPPMM//Ef/8H69ev5+Mc/PgwjHzz+5V/+hRMnTiSJC77xjW/w3nvvJe2CxgLGJPE0NTVx6tQpAoEAtbW1TJw4Uc3nCIIw4AfnxIkTqrtBRcXwdppMhSRJdHR0qMl4WZb7JUtWdmmFhYXMmjUroyePVCgqJCU273Q6dcUahYWFatFqJu3kWlpa2L17d7+MSgeC4cgLhUIhtm3bRn5+PrNnzx5TAo5oNMrOnTvp6upSZeuphqZngyzL/OUvf+G2227jueee47LLLhuBkQ8MW7ZsYdmyZXz/+9/nuuuu4/333+fmm2/mySef5LOf/exoD69fyEjiicVivXqxybLM1q1bVWfcoqKiQYsIFIv3lpYWFixYMKpOwcp4FM80RZZ8Jpn2SMmlhwOxWIzt27cTi8VYuHBhr6GkYDCoknJXVxe5ubkqCemJE0YKJ0+e5MCBA8ybN69XxeNwYCjyQsFgkG3btqmLlbF03yg75Pb2djW8prgnuN1udaGiXJPedkLPP/88X/ziF/nTn/7ElVdeOcLfov944YUX+Pa3v83BgwepqqrijjvuMFRtQ4XeiEeZpDweD1arlfPOO2/QpBOLxdTq5oULF2acxbsS41ZIKBAIqOGn0tJS2tvb2bNnDzNmzBiyEM9IQUlm99dJQdtZVMmTKbvDkVSENTU1cfToURYsWDCq/VgGkhdScqNKY7ixRjraXkB6z2yqxVN2djYlJSUUFRVRUFCA2WzmhRde4MYbb+Tpp5/m6quvHoVv8uHFmCEepS7Cbrczfvx4jhw5wkc+8hG1E+lAHpxgMEhjYyM2m23M5ESUlr2KTBtg/PjxVFVVZRxpngnK76mEeAYaGlTECcpuSFn5KyHK4Qg5yrLM4cOHOXnyJIsWLcooO/y+5IUUV4/y8nKmT58+5kjnwIEDtLW19bkXUDQaVXeHGzZs4LHHHmP69Ok0NDTw5JNPjjkp8gcBGUk8oigSi/V0ouns7KS+vp6Kigpqa2vxeDxs2bKFcePGUVZWRnFxcb8nmO7ubhobG9Vai7GWE9m/fz+tra1UVlbi9Xrp7OxUw09KbUymQukqW15e3mudy0Cg7SzqcrnUEKVSGT8UCwtltd3W1saiRYuGRQ4/lFC6i7a1tanJ+HA4TFlZ2aAIfzSgtMNoaWkZcNfTSCTCI488woMPPkhJSQmdnZ184hOfYPXq1WMyZDVWkfHEc+rUKfbs2cP06dOZNGkSoiiqORBFlhyLxdRVbnFx8Vnj262trezevVuV7I6lFZ/icpwaGkytjXE6nWo4biSNGc8GJR81ZcoUpkyZMmzj0oYoXS4Xfr+foqKiQTkma1syKCKIsYSuri7q6+txOp2EQiFMJpOaOxzJeqGBQJZlDh06pDbPG2hn2Ndff51rr72W//mf/+HGG2/kwIED/PWvf6WpqYmf//znQzxqA70hY4knGo1y4MABTpw4oXaYVEhHG1pTuiS2tbXR2tqq+mHpJeKVav6mpibmzp3bp7YKmYRwOExjYyNms/mMDs2pRpVamXZhYeGokVBrayu7du0alXxUIBBQFyrd3d393h0qTseK/9dotWQYKDweD/X19aoApbe8kELMmeQjp5CO0vhvoLv5t99+m2uuuYYf/ehH3HLLLRmzGPswIiOJRylm8/l8LFq0iOzsbF3SSYVWgtva2kowGKSoqIjy8nKKi4s5ePAgHR0dGVnNfzb4/X7q6+spKCjoV4hEK9Nua2sDSNodjlSo5cSJExw8eDAjCF8RJ2jDT8ruUE+coLg0n015l6no7u6mvr6eqqoqpkyZkvbvim+asjvMJB85JZ926tSpQZHOli1bWLVqFffffz+33XabQTqjjIwknlOnTnHkyBF1VT9Q+xvlYWppacHn82E2m5k6dSqVlZVjavJQzDInTpxIdXX1gB+a/sq0hwKy3GOyqjTiyyT0JktWwk+iKCYZZmaK43hf0dXVRUNDgxpW7gtS80Kj6SOniDjq6uoGnE9raGjgyiuv5Hvf+x533HHHqJLOfffdx/e///2kY7W1tezbt2+URjQ6yEjikSSJcDiMLMuDdiLw+/00NDSQlZVFYWGh6oSrtHHuq1PyaEEpTqytrR1Ss8xUmbayO1RW/kNBzLIss3fvXtxu95hIxGtt+5XcoSAIOJ1OFi5cOObCa52dnTQ0NFBTU8PEiRMHdA4tMbvdbgRBGLG8kLJgWbx48YDvnZ07d3L55ZfzzW9+k7vuumvUdzr33Xcfzz33HK+++qp6zGKxjGgNWCYgI4knFosRCoXUvw80HKQksidMmMC0adPUmy4UCqkTbldXF3l5eZSVlVFeXp4xCWNZljl27BhHjhwZkfCUVqbt9XoHTcyiKKo9UTKxPupsUOpclIk1EAgkEXOmk1B7ezvbt28fUgufkcwLKc7qgyGdPXv2sGLFCr7yla9w7733jjrpQJx41q1bR2Nj42gPZVSRkcRzww03cPjwYVavXs1VV13F+PHj+33TnDx5kv379581kR2JRNQJt6OjQ3WOLi8vH7XYtiLZbW1tZeHChSNeJ5JKzP1NxCtu4ZIkDdrZezSg5NO0xZWBQEDNgXR3d5OXl6eG5DJNuu52u9mxYwczZswYth5M2n46ymJlqPJCCunU1dUNOBe7f/9+VqxYwY033sh//dd/ZQTpQJx4fvzjH5Ofn4/D4WDp0qU8+OCDfQ6DflCQkcRz8uRJnnvuOdauXcvbb7/N4sWLWbVqFatWrWLy5MlnvIkUrf/p06eZN28eRUVFff7cVOdoRZJcXl4+4MZU/YUoiuzcuZNAIJARO4XURLxyTcrKysjNzU27JuFwmPr6ehwOh9pyfCxBqTGqrKxM2iVrEQ6HkzzTnE6nSkKjLV13uVzs2LFj2H3jUqHkhVKvSX/zQk1NTTQ1NQ2KdA4fPsxll13GZz7zGX784x9nVK3Shg0b8Pl81NbW0tzczPe//31OnTrFrl27xpzgaTDISOJRIMsyzc3NPP/886xdu5bXX3+defPmqSSUOjEok7bf72fBggWDWnXFYrEk52ibzUZ5efmwTi6RSISGhoazyqVHC0q8v7W1FbfbjdVqVUmooKAgqevmWDMqhZ5E/JQpU3S72+ohVbpuNpuTpOsjeQ0Uufpo9zHqLS+kmHf2thhRQst1dXUD3uU3NTWxYsUKVq5cyWOPPZbx92BXVxeTJ0/mkUce4aabbhrt4YwYMpp4tJBlGbfbrZLQa6+9xowZM1QScjgcfOlLX+LOO+/kwgsvHNJJO9WWxWw2qzuhgoKCISEhRQSRl5eX8db0EI/3K5NLW1sbsiwjiiKlpaXMmTNnzO10lJzIYBLxijhBuU9EUUxyThhORZwiQpk3b96oy9W16Gte6Pjx4xw+fHhQpHPy5EkuvfRSLrnkEh5//PGMf4YULFmyhOXLl/Pggw+O9lBGDGOGeLSQZZnOzk7++te/smbNGl566SW1ediTTz5JXV3dsN10qXUxgiBQWlpKeXn5gFe4XV1dNDY2Mn78+F7DO5kMt9vN9u3bycvLIxQKqTJtpX4q0yXIbW1t7Ny5c0jbYSiFzQoxD6c4QenYOtIO2f1Fb3khq9VKR0cHdXV15OfnD+jczc3NXHbZZXz0ox/lV7/61ZhZ+Ph8PiZNmsR9993H1772tdEezohhTBKPFuvWreNzn/scV1xxBeFwmJdffpmKigpWrVrF6tWrWbhw4bCSkFIX09ramtRDp6/FmYp9z2BW2qMJZaWtTNojIdMeSmjbbJeVlQ3b52gnXI/HoyopB5uIP3XqFPv372f+/PkUFxcP4YiHH6FQiIMHD9La2gqQZPPUn7xQa2srK1asYPHixfz+97/PaNL55je/ycqVK5k8eTKnT5/m3nvvpbGxkT179mTUTnW4MaaJZ/v27Zx//vn84Q9/UG3NfT4ff//731mzZg0bNmygqKiIq666itWrV7NkyZJhuyllWaa7u5vW1la1OFMhoZKSEt3PPXbsGIcPH86Iav6B4Pjx4xw6dOiMK+2hlmkPJZTxj/SkrRUntLe3k5WVNSBfPcUNYuHChaPalmGgUHoZKTVeA8kLud1uLr/8cmbNmsWzzz6b8bvrz3zmM7z++uu0t7dTWlrK+eefzw9/+EOqq6tHe2gjijFNPBB/+HrbKQQCAV566SXWrFnDiy++SHZ2NitXrmT16tUsXbp02G5SZdWvkFAoFFKL7kpLSzGbzRw4cEBtPDfQ8MJoQfHOOnXqFAsXLuzz+Acr0x4qKJ59x44dG3U3BUXEoky4fRUnKDmR0R7/QKGQjh5p9jUv1NHRwRVXXMHUqVP505/+lHG7aQO9Y8wTT18RCoV49dVXWbt2LevXr8disbBy5Uquvvpqzj///GFTkClxbYWE/H6/+lmjUaMzWEiSxN69e+no6FB99AaC/sq0hwqK3L65uZlFixZllIRVK05oa2tDkiR1waLNlSkN6BYtWjTmFi3QEx7sy05NmxdyuVycPn2ahx9+mI9+9KO89tprVFVVsXbt2owv6DWQjA8N8WgRjUbZtGkTa9asYd26dYiiyBVXXMHq1au58MILh+0mVsxPY7EYVqsVn89HYWGhOuFm+sOjtGQIhUIsXLhwyEJlqdL1VJn2UJGQYuHT3t4+KNIcCWhd110ul5orEwSBzs7OQam/RhNKTm3BggX9qrFT4Ha7+eUvf8ljjz1GIBBg2rRpqrL1Ix/5SEbndwz04ENJPFrEYjHefPNN/vKXv7Bu3Tr8fj9XXHEFq1at4hOf+MSQFXAqNS55eXnMnj0bs9lMMBhUV7fd3d3k5+dTXl5+xh7xo4VoNKrafCxYsGDYdoiiKKqqQZfLpaoGB9tRVJIkdu3ahdfrpa6ubtTzS/2Fz+dj3759dHV1IcsyBQUF6nUZaG+akUZzczN79+4dMOlA/Dpcc8012Gw2/vjHP/Lmm2+yfv16NmzYwO7du8dkrvTDiA898WghiiLvvPMOzz33HM8//zydnZ1cdtllrFq1iksuuWTAK2RFLl1ZWUlNTU2v1fAKCWm7iZaXl4/6xBIKhaivrycrK4u5c+eO2KoytaNoLBbTDT2dDcpOLRwOs2jRojGXC9D2o6mrq8NqtSaFKbOzs1USGs4w5WCgkM5ghByBQIBPfepTSJLE3//+9yQPN8W93sDYgEE8vUCSJLZs2aKSUHNzM5dccgmrVq1ixYoVfc4NtLW1sWvXrn7JpbX5j/b2drKzs5P840ZyYvH5fDQ0NFBcXMyMGTNG7eFOrYsJBoMUFxerqsHeyCQWi9HY2Igsy8O6UxsuyLLMgQMHaG1tpa6uLm3xkxqmtFgsqohlpJ0TekNLSwt79uwZFOmEQiE+/elP4/P5eOmll8ZkmNFADwzi6QMkSaKxsVEloaamJj7xiU+watUqrrjiil5rDhS57mBqRKLRaNLE4nA4VOue4V7dKju1CRMmDKoP0HDA5/MlFSIquTJtW2vFgshqtTJ//vwxF/+XZZl9+/bhdrupq6s7685XW9zscrmQJElVgvUm6R9uKDY+8+fPH3Bxazgc5rOf/Swul4uXX345o6TjDz30EN/+9rf5+te/zk9/+tPRHs6YgUE8/YQsy+zevVs1Md23bx8XXXQRq1ev5oorrqC4uBhJkvjd737HtGnT+iU3PhtEUcTtdqteaTabTU3CD3WDLpfLxc6dO5k2bVrGO+cGg0GVhJQ2F4WFhbS2tpKbm8vcuXMzYuXfH8iyzJ49e1QhQX9zfkpdmXJdQqHQiBfyKqQzGBufaDTKv/3bv3Hs2DE2btyYUUWyW7Zs4brrriMvL4+LLrrIIJ5+wCCeQUAJg6xZs4Y1a9awY8cOli1bRktLC16vl7feemvYzBqVJHxra2uSf5xS/zEYEjp9+jR79+4dcYfjoUAkElE72EqSpIYpMzn/kQplcdPd3T1kQghta2uPx0N+fr5KQsORQ1RsiAZDOrFYjC984Qvs27ePTZs2ZZRwwOfzsWjRIn7xi1/wwAMPsGDBAoN4+gGDeIYIsiyzdetWrr32WtxuN8FgkPPOO4+rrrqKVatWUVlZOWyTnlL/oZCQLMvqZNtfJVhTU5PadjyTVpd9hc/nY9u2bYwbN46pU6cmOUcPl0x7KKGo73w+H3V1dcMisQ+FQkltHYZanKC0Zpg7d+6AQ8yiKHLLLbfQ0NDApk2bMm4BdMMNN1BUVMSjjz7KhRdeaBBPP2EQzxDh6NGjXHrppcybN48//OEPuN1u1qxZw9q1a3nnnXdYsmSJat0zadKkYS2Q1BYhKo7RihKstzi/trByLBa2AnR3d9PQ0MDEiROZOnVqWsuM4ZBpDyUkSVJ7MdXV1Y1IOEzJISrOCVarVb0uBQUF/b4uCukMpjWDKIp89atf5a233mLz5s1D1kF1qPDHP/6RH/7wh2zZsgWHw2EQzwBgEM8Q4fTp0/zmN7/hu9/9btLDKssyp0+fVts5vPHGG8ybN4/Vq1ezatWqYU3aK0owxTUhEomocmStTb8kSezZs4euri4WLVo06vLtgUBpcz516lQmT558xtdqZdoKOWuvy2gk4SVJYvv27aMq+U4VJ8iynCRfP9t1UVzKB0M6kiRx++2389prr7Fp06az/pYjjRMnTrB48WJeeeUV5s2bB2AQzwBgEM8IQpZl2traWLduHWvXrmXTpk3MmDFDJSGlzfJwfbbP51NJSJEjl5SU0NLSQiwWY+HChRnvnqAHRQhRW1vb79Wx1iFAScIrMu3S0tIRkV+Losj27duJRqMsWrQoIyTfijhBuS69+aUpUNptz5o1a8BhMUmS+M///E9eeOEFNm/ezNSpU4fiqwwp1q1bx9VXX51EwqIoIggCJpOJcDg85tSTowGDeEYJSkhs/fr1rFmzhldffZWpU6eq7Rxmz549rOEfn89Hc3Mzx48fR5IkioqKVJn2WCqwVNoyDFXXTZ/Pp062WksjrUx7KCGKIo2NjUiSxMKFCzPSXbm3PjpKviwQCLB9+/ZBk873vvc9/vKXv7B582ZqamqG+FsMDbxeL8eOHUs6duONNzJjxgy+9a1vMWfOnFEa2diCQTwZgu7ubv72t7+pje3Gjx+vktCCBQuGnISCwSD19fXk5ORQXV2t1gp5PB4KCgpU655MtpZRHI6HqwGaItNubW2lu7t7yHroKIjFYjQ0NCAIAgsWLMhI0tGDIk5QnBMASktLqa6uJicnp9+7dlmW+cEPfsDvf/97Nm/ezIwZM4Zj2MMGI9TWfxjEk4Hwer1JPYVKSkpUJ+0lS5YMmoS8Xi8NDQ2UlpamhfeU1gXayVbZCWWSf5zi0LxgwYIRKSiMRCJq7kPrJlFWVjagyTYajdLQ0IDZbGbBggVjMjzT0dFBQ0MDFRUVqoOCohwsLS3tkzhBlmUeeughnnjiCTZt2jQmdwwG8fQfBvFkOAKBAP/4xz/UnkI5OTmqOm7p0qX9nrA6OztpbGxk8uTJVFVVnXHCVBqWtba20tnZSU5OjkpCo+XsLMsyhw8f5uTJkyxatGhU1HepNjU2m01tf96XQt5oNEp9ff2YdVSA+H3U0NDAjBkzqKysBHqUg4pU+2ziBFmWefTRR3n00UfZuHEjCxYsGIVvYmA0YBDPGEIoFOKVV15RewrZbDZ1J3TeeeedNSmt+MZNnz6dCRMm9Ouzo9GoSkJDseIfCGRZZv/+/bS1taldK0cb/ZVpRyIR6uvrcTgczJs3LyNk3P2FQjpnEnP0Jk7IyspSd9E/+9nPePjhh3nppZdYsmTJCH8LA6MJg3jGKCKRSFJPIUmSuPLKK9WeQqkCASUfMhjfOAXKil+x7nE4HCoJ9ad1c3+glXwPxEJmJHA2mbYoimzbtk11+R6LpNPV1UV9fX2/Fi+KOKGtrY2//OUv/PCHP6SiogK3280zzzzDNddcM8yjNpBpMIjnA4BYLMYbb7yh9hQKBoNqT6GLLrqIH/zgB8RiMb773e8OeT5EFEXa29tVElLckYfSHUCSJHbs2EEwGGTRokVjQvKtJ9MWBIGcnBzmz58/Jr5DKrq6umhoaGDatGl9dlpPhSzL/OhHP+Khhx5i7ty5at3P1Vdfzd13352RbhIGhh4G8XzAIIoib7/9tuqk3dLSgiAIfOc73+ErX/nKsBaHSpKkWtQoYSetf9xAVviK3DgWi2VMjUt/EQwG2bp1KxaLBUEQRkSmPdTo7u6mvr5+0KTz9NNP881vfpO//vWvXHTRRXR2dvLiiy+ya9cuHnrooSEetYFMRUYSz+OPP87jjz9OU1MTALNnz+aee+5hxYoVozuwMYRwOMznPvc53nvvPS6++GI2bdpEa2srF198MatXr+ayyy7rc0+hgUDxj1NW/LIsJ1n39IWEFOWXyWQaU3JjLYLBINu2baOoqIiZM2ciCEJa51lFpp2p3UQV0qmurh6wU7ksy/z5z3/mq1/9KmvWrOHSSy8d4lEaGEvISOL529/+htlspqamBlmW+f3vf8+Pf/xjGhoamD179mgPb0zgxhtvZM+ePbzwwguUlpYiSRINDQ1qO4fjx4+zfPlyVq1axeWXXz7kbRW0kGU5KfehdBItLy/v1YolHA4nJeHHovIrEAiwbds2SktLqa2t7bXzbGo30ZEWbZwJHo+Hbdu29cmK6ExYu3Ytt9xyC3/605+48sorh3CE/YexsB19ZCTx6KGoqIgf//jH3HTTTaM9lDGBo0ePUlpaqqv8kmWZXbt2qSR04MCBpJ5CRUVFw+4fp9QKhcNhlYQU/ziluDUvL2/YHRyGC36/n23btlFeXs706dP7dD21Tf/a29uHtd9SX6CQTlVVFVOmTBnweV544QVuvPFGnn76aa6++uqhG+AAYSxsRx8ZTzyiKPKXv/yFG264gYaGBmbNmjXaQ/pAQZEoKz2Fdu7cyQUXXMCqVatYuXIlZWVlw+4fp5BQMBgkPz8fn89HaWkps2bNGvUV/0CgtGaorKxk2rRpA/oOejLtwebL+gOv18u2bduYMmXKoEjnH//4B5/73Of43e9+x3XXXTd0AxxiGAvbkUXGEs/OnTtZunQpoVCInJwcnn32WS6//PLRHtYHGkpxptLOYdu2bSxbtoxVq1Zx1VVXDWtPIehpHmaxWIhGo2rHzLHkH6dM2HqtGQYKPZl2X1pdDBTKd1CKjAeKjRs3cv311/PLX/6Sf/mXf8nIRYSxsB0dZCzxRCIRjh8/Tnd3N8899xy//vWv+ec//2ncGCMEWZY5fvy4SkLvvvsuS5YsYdWqVaxatWrIewopUt0pU6ZQVVVFMBhUnbQV/ziFhDJVBebxeKivrx/0hH0m6Mm0S0pKVNfowar+fD4fW7duZdKkSYNyh3799de59tpreeyxx/j85z+fcaRjLGxHFxlLPKlYvnw51dXV/PKXvxztoXzooPQUWrt2LWvXruXNN99k/vz5ajuHwa7s29vb2b59OzU1NbpSXcU/rq2tja6uroxUgSnKr8HmQ/oDbWFmqpt2WVlZv2uFlBDhhAkTqK6uHvC43n77ba655hp+8pOfcPPNN2cc6YCxsB1tjBni+fjHP86kSZN46qmnRnsoH2rIskxra6vaU2jz5s3MnDlTJaHe1Fu9QQmvzZo1i4qKirO+XjHrVFRgOTk5SSqw0YCyWxuM3HgoMBiZtt/vZ+vWrYwfP55p06YNeAzvv/8+q1ev5oEHHuArX/lKRpKOHoyF7cgiI4nn29/+NitWrGDSpEl4vV6effZZ1dPp4osvHu3hGUhAlmU6OjqSegpNmzZNbecwa9asMybBT58+zb59+wZs46P4xykqMKfTSVlZGeXl5SMmRe7o6KCxsXFA/nfDif7ItLWkM5iOuPX19axcuZK7776bb3zjG2OGdMBY2I40MpJ4brrpJjZu3EhzczP5+fnMmzePb33rWwbpZDAUU0ilp9DLL7/MhAkTVBKaP39+EgkdPnyYY8eOsWDBAoqKigb9+XqO0QoJDZd/nBIiHEjn05GEVqbtdrux2+0qCVksFurr66moqBiwAg9gx44dXHHFFdx5551861vfymjSMRa2o4+MJB4DYx9er5cXX3yRNWvW8I9//IOSkhKuuuoqVq1axdq1a9m6dSvPP/88+fn5Q/7Zin+cIkU2m81JUuShmBSVVs8zZ87sU4gwU5B6bWKxGDk5OdTU1Oi6afcFe/bsYcWKFdx2223cc889GU06YCxsMwEG8RgYdvj9frWn0HPPPYcoiqxevZovfelLfOQjHxlWVwJJktR6mLa2NrVtQXl5+YDrYZT2EoNp9TzaCAQCbN26lfz8fGw2Gy6Xa0Ay7f3797NixQpuuukmHnjggYwnHQOZAYN4+oGHHnqIb3/723z96183ug32E6Iocuutt/LSSy/xne98h3feeYe//vWv2O12Vq5cyerVq/vUU2gw0NbDtLa2IkmSSkJFRUV9mmhbW1vZtWsXc+fOHXR7idGCYlpaVlamuir05iihtHTQ+10OHTrEihUruP766/nRj340Jh0mDIwODOLpI7Zs2cJ1111HXl4eF110kUE8/cSvf/1r/vu//5tXXnlFTcJHIhFee+01tacQoPYU+tjHPjasRaNKTkqpFYpGo0nWPXok1NzczN69e5k7dy6lpaXDNrbhhEI6Z/KPU2Tara2tuFwufD6fWsyr5M6ampq47LLLWL16NT/96U8N0jHQLxjE0wf4fD4WLVrEL37xCx544AGjv/oAIIoiHo+n135AsViM119/Xe0pFAqFuPLKK1m1ahUf//jHh7VoVJZlvF6vutpXijK1q31FgTd//nyKi4uHbSzDiVAoxNatWykuLmbGjBl9DospMu2mpiZWr15NVVUVra2trFixgqefftogHQP9hkE8fcANN9xAUVERjz76KBdeeKFBPMMMURR56623eO6551i3bh3d3d3q6vriiy8e1qJR7Wq/ra0Nv99PVlYWgUCAefPmjdnwmkI62vYMA8GWLVu45pprcDgcuFwuZs2axdVXX82///u/Z7Syz0BmwViqnAV//OMfqa+v58EHHxztoXxoYDabueCCC3jsscdoamriH//4BxMmTOC73/0uU6ZM4V//9V957rnn8Hq9Q/7ZSpfQ6upqli5dqtr3OJ1OduzYwbZt2zhx4gThcHjIP3u4EAqF0noCDQStra3ccsstXH755Rw/fpy2tjbuvPNOduzYgdvtHuJRG/ggw9jxnAEnTpxg8eLFvPLKK8ybNw/A2PGMIiRJor6+Xm3ncOLECZYvX87q1au5/PLLh7xe59ixYxw5coSFCxdSUFCQ5gyQn5+vyrSdTueQfe5QIhwOs3XrVgoKCgbl9u1yubjiiiuYPXs2zzzzzJhsymcgc2AQzxmwbt06rr766qREsyiKCIKAyWQiHA6PyQZlHwRIkpTUU+jgwYN8/OMfZ9WqVUPSU+jo0aM0NTWxaNEi3VqjcDisklBnZye5ubkqCWVnZw/mqw0ZwuEw27ZtU/saDfR6dHR0cPnll1NdXc2f//znUW8//uCDD7J27Vr27duH0+lk2bJlPPzww9TW1o7quAz0HQbxnAFer5djx44lHbvxxhuZMWMG3/rWt5gzZ84ojcyAFrIss2/fPpWEdu3axcc+9jG1p1BpaWm/Jt3Dhw9z4sQJ6urq+tQePBKJJFn3KPY05eXlZGdnj0ptSyQSYevWrYMmna6uLlauXElFRQVr167NiPYUl112GZ/5zGdYsmQJsViM73znO+zatYs9e/ZkDOkbODMM4uknjFBbZkPpKaSQUENDQ1JPoYqKil4nYeW9p06doq6ubkCmo6n2NA6HQyWh3NzcESEhhXRyc3OZM2fOgD/T4/GwevVq8vPzWb9+fca2o3C5XJSVlfHPf/6TCy64YLSHY6APMIinnzCIZ+xAlmWOHTvGmjVreP7553n33Xc555xz1J5CEydOVCdlSZLYv38/bW1tLF68eEhWzqIo4na7aW1txe12Y7VaVRIarlbWkUiEbdu2kZ2dzZw5cwYsdfb5fFxzzTXYbDZefPHFjM1hQbyQtaamhp07dxpRiDECg3gMfCggyzKnTp1Sewq99dZbLFiwgNWrV7Ny5UoefPBBwuEwTz755LDItbWtrNva2pL84woKCoakFkYhnaysLObOnTvgcwYCAT71qU8hyzIvvvjiqLWb6AskSeKqq66iq6uLN998c7SHY6CPMIjHwIcOSk+h559/njVr1vDaa69hNpu5+eabufnmm1UbmeGCJEl0dnaqzgCyLKskNFCjzmg0yrZt23A6nYMinVAoxKc//WnVXy8vL29A5xkp3HrrrWzYsIE333wzo9pSGDgzDOIZQ7jvvvv4/ve/n3SstraWffv2jdKIxjZEUeTf//3f2bx5M7feeiubN29m48aN1NTUcNVVV3H11Vczc+bMYa3Ml2WZrq4utWB1IEadCuk4HA7mzZs34PGGw2E++9nP4na7efnllykoKBjQeUYKt912G+vXr+f1118ftlbjBoYHhhh/jGH27Nm8+uqr6t+NeoqB47//+7955513ePPNNxk/fjx33nkn3d3d/PWvf2XNmjU8+uijTJo0SSWhwUzqvUEQBAoLCyksLKS2thaPx0NraysHDhwgEokkWffo/dbRaJT6+nrsdvugxheJRLjhhhtobm5m48aNGU06sizz1a9+leeff57NmzcbpDMGYex4xhDuu+8+1q1bR2Nj42gP5QMBn8+H3++nvLxc9989Hk9ST6GysjKVhOrq6oZ9J+Tz+dSdUDAYpLi4mLKyMkpLS7FarcRiMerr67FarWmN9vqDaDTKTTfdxP79+3nttdcy3gD1y1/+Ms8++yzr169Pqt3Jz8/PaBGEgR4YxDOGcN999/HjH/+Y/Px8HA4HS5cu5cEHH2TSpEmjPbQPPPx+Pxs2bGDt2rW8+OKL5Ofnc9VVV7F69WrOPffcYS8k9vl8qjDB5/NRWFhIMBjE4XCwcOHCAX9+LBbjlltuYfv27WzatKlXEs4k9JZ/+93vfsfnP//5kR2MgQHBIJ4xhA0bNuDz+aitraW5uZnvf//7nDp1il27dvWp0NHA0CAYDPLyyy+zdu1a/va3v+FwOJJ6Cg13+NPr9dLY2EgsFkMURQoKClRxQn9qbURR5LbbbuOdd95h8+bNVFZWDuOoDRjogUE8YxhdXV1MnjyZRx55hJtuumm0h/OhRCQS4dVXX2Xt2rWsX78eQRC44ooruPrqq7nggguGvNI/FovR0NCAyWRiwYIFRKNRtZ1Dd3c3eXl5aq3QmcJOkiRx++23s2nTJjZt2mTsmg2MKAziGeNYsmQJy5cvN9yzMwDRaFTtKbR+/XrC4TBXXHEFq1ev5qKLLhp05b8oijQ0NCAIAgsWLEgLr4XDYVwuF62trXR2dpKTk0N5eXmaf5wkSfznf/4nL774opGcNzAqMIhnDMPn8zFp0iTuu+8+vva1r432cAxoIIoib775ptpTyOPxsGLFClavXs3y5cv7XaSqkA7Qp5xONBpVSai9vR1BENiwYQOf/OQnWb9+PWvXrmXTpk3U1NQM+DsaMDBQGMQzhvDNb36TlStXMnnyZE6fPs29995LY2Mje/bsyXgl0ocZkiTx7rvvqiTkcrm45JJLWL16NZdeeulZnQFEUaSxsRFJkli0aFG/hQSxWIydO3dy99138/rrrwNxs9svfvGLLF68eFRMTA18uGE0ghtDOHnyJNdffz21tbVcd911FBcX8+677xqkk+EwmUwsW7aMRx55hEOHDvHaa69RU1PD/fffz5QpU/jMZz7D//3f/9Hd3U3qOlAURbZv344kSQNWr1ksFhYsWMCyZcsoLCzkJz/5CcFgkOXLlzNlyhR27949VF/VgIE+wdjxGDAwSpAkiR07drBmzRrWrl3LoUOH+MQnPsFVV13FlVdeic1m44tf/CKf/exnufTSSweslpNlmUceeYSf/vSnvPbaa8yfPx+I54Q2btzIRRddZNS/GBhRGMRjwEAGQJZl9u7dq7Zz2L17Nzk5OTidTjZs2MC0adMGFBKTZZn/9//+Hz/60Y94+eWXWbx48TCMvn94/fXX+fGPf8y2bdtobm7m+eefZ/Xq1aM9LAMjCCPUZmBQOHXqFP/6r/9KcXGxalC5devW0R7WmIMgCMyaNYt77rmH9957jwsuuIDs7GzKy8tZvHgxl19+Ob/85S9pbm5OC8f1BlmW+eUvf8lDDz3E3//+94wgHYgX486fP5+f//znoz0UA6MEw+jLwIDR2dnJeeedx0UXXcSGDRsoLS3l4MGDFBYWjvbQxixEUeTTn/403d3d7Nq1i/z8fJqamlizZg3PPfccd955J+eee67aU2jChAm6OyFZlvnd737Hfffdx4svvshHPvKRUfg2+lixYgUrVqwY7WEYGEUYoTYDA8Zdd93FW2+9xRtvvDHaQ/lA4Te/+Q1XX301RUVFScdlWebkyZNJPYUWLVrE6tWrWbVqFVOmTEEQBGRZ5n//93+58847+dvf/saFF144Ol+kDxAEwQi1fQhhEI+BAWPWrFlceumlnDx5kn/+85+MHz+eL3/5y9x8882jPbQPPGRZpqWlheeff561a9fyz3/+kzlz5rBq1Srsdjs//OEPWbt2LZdccsloD/WMMIjnwwmDeAwMGEol/h133MG1117Lli1b+PrXv84TTzzBDTfcMMqj+/BAlmXa29tZv349zz77LK+99hpPP/00n/3sZ0d7aGeFQTwfThjEY2DAsNlsLF68mLfffls99rWvfY0tW7bwzjvvjOLIPrxQWnyPlW6cBvF8OGGo2gwMGBUVFcyaNSvp2MyZMzl+/PgojciAIAhjhnQMfHhhqNoMDBjnnXce+/fvTzp24MABJk+ePEojMjAW4PP5OHTokPr3o0eP0tjYSFFRkeGS/SGBEWozMGBs2bKFZcuW8f3vf5/rrruO999/n5tvvpknn3xyTOQXDIwONm/ezEUXXZR2/IYbbuCpp54a+QEZGHEYxGNgUHjhhRf49re/zcGDB6mqquKOO+4wVG0GDBg4IwziMWDAgAEDIwpDXGDAgAEDBkYUBvEY+MBBqeBP/e8rX/nKaA/NgAEDGKo2Ax9AbNmyBVEU1b/v2rWLiy++mGuvvXYUR2XAgAEFRo7HwAcet99+Oy+88AIHDx40um0aMJABMEJtBj7QiEQiPP3003zhC18wSMeAgQyBQTwGPtBYt24dXV1dfP7znx/toRgwYCABg3gMfKDxm9/8hhUrVlBZWTnaQ/lA4ec//zlTpkzB4XBw7rnn8v7774/2kAyMIRjEY+ADi2PHjvHqq6/y7//+76M9lA8U/vSnP3HHHXdw7733Ul9fz/z587n00ktpa2sb7aEZGCMwxAUGPrC47777+OUvf8mJEyewWAwB51Dh3HPPZcmSJfzsZz8DQJIkJk6cyFe/+lXuuuuuUR6dgbEAY8dj4AMJSZL43e9+xw033GCQzhAiEomwbds2li9frh4zmUwsX77caIVhoM8wiMfABxKvvvoqx48f5wtf+MJoD+UDBbfbjSiKlJeXJx0vLy+npaVllEZlYKzBWAoa+EDikksuwYgiGzCQmTB2PAYMGOgzSkpKMJvNtLa2Jh1vbW1l3LhxozQqA2MNBvEYMGCgz7DZbNTV1bFx40b1mCRJbNy4kaVLl47iyAyMJRjEY8DACEAURe6++26qqqpwOp1UV1dz//33j8lw4B133MGvfvUrfv/737N3715uvfVW/H4/N95442gPzcAYgZHjMWBgBPDwww/z+OOP8/vf/57Zs2ezdetWbrzxRvLz8/na17422sPrFz796U/jcrm45557aGlpYcGCBfzjH/9IExwYMNAbjDoeAwZGAFdeeSXl5eX85je/UY998pOfxOl08vTTT4/iyAwYGHkYoTYDBkYAy5YtY+PGjRw4cACA7du38+abb7JixYpRHpkBAyMPI9RmwMAI4K677sLj8TBjxgzMZjOiKPLDH/6Qz372s6M9NAMGRhwG8RgwMAL485//zDPPPMOzzz7L7NmzaWxs5Pbbb6eyspIbbrhhtIdnwMCIwsjxGDAwApg4cSJ33XVXUvvtBx54gKeffpp9+/aN4sgMGBh5GDkeAwZGAIFAAJMp+XEzm81IkjRKIzJgYPRghNoMGBgBrFy5kh/+8IdMmjSJ2bNn09DQwCOPPGJ4yRn4UMIItRkwMALwer3cfffdPP/887S1tVFZWcn111/PPffcg81mG+3hGTAwojCIx4ABAwYMjCiMHI8BAwYMGBhRGMRjwIABAwZGFAbxGDBgwICBEYVBPAYMGDBgYERhEI8BAwYMGBhRGMRjwIABAwZGFAbxGDBgwICBEYVBPAYMGDBgYERhEI8BAwYMGBhRGMRjwIABAwZGFAbxGDBgwICBEcX/B1TwTRQOriW5AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =plt.subplots(subplot_kw={\"projection\": \"3d\"})\n",
    "surf = ax.plot_surface(x0,x1,zz, cmap='jet')\n",
    "#ax.scatter(iris.data[:,0:1], iris.data[:,1:2], y, 'or')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}