diff --git a/C3/L10_bayesian_information_criteria.ipynb b/C3/L10_bayesian_information_criteria.ipynb
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@@ -0,0 +1,495 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "L6_density_estimation.ipynb",
+      "provenance": [],
+      "collapsed_sections": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3",
+      "language": "python"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.8.5"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "eDRfJeA9i540",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "eb115cb0-2826-4f8c-a203-4bc491b7726a"
+      },
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt \n",
+        "import pandas as pd \n",
+        "import seaborn as sns\n",
+        "import arviz as az\n",
+        "from statsmodels.tsa import stattools\n",
+        "import statsmodels.api as sm\n",
+        "import pymc3 as pm\n",
+        "import pymc\n",
+        "\n",
+        "import sys\n",
+        "sys.path.insert(0, '..')\n",
+        "from utils.plot_lib import set_default\n",
+        "\n",
+        "set_default(figsize=(6, 4))"
+      ],
+      "execution_count": 1,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "WBG3Vsj2S3xV"
+      },
+      "source": [
+        "### Bayesian Information Criteria (BIC)\n",
+        "\n",
+        "The galaxies dataset. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "V7VdfuBLShRW",
+        "outputId": "df4dcdf3-0ad0-4702-a075-2ae02a5d4e04"
+      },
+      "source": [
+        "!wget http://www.key2stats.com/Velocities_for_82_Galaxies_1152_58.csv -O galaxy.csv --no-check-certificate"
+      ],
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2021-05-24 11:56:45--  http://www.key2stats.com/Velocities_for_82_Galaxies_1152_58.csv\n",
+            "Resolving www.key2stats.com (www.key2stats.com)... 52.207.128.24\n",
+            "Connecting to www.key2stats.com (www.key2stats.com)|52.207.128.24|:80... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 1221 (1,2K) [application/csv]\n",
+            "Saving to: ‘galaxy.csv’\n",
+            "\n",
+            "galaxy.csv          100%[===================>]   1,19K  --.-KB/s    in 0,004s  \n",
+            "\n",
+            "2021-05-24 11:56:46 (321 KB/s) - ‘galaxy.csv’ saved [1221/1221]\n",
+            "\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 223
+        },
+        "id": "j76qLqfXTOgJ",
+        "outputId": "4ddc701b-df98-4eb3-b8ca-da13f60812e1"
+      },
+      "source": [
+        "# Read dataset - galaxies\n",
+        "galaxy = pd.read_csv('galaxy.csv')\n",
+        "galaxy.pop('Unnamed: 0')\n",
+        "galaxy.pop('X')\n",
+        "# Checking dataframe\n",
+        "print(\"The shape of the dataset is: {}\".format(galaxy.shape))\n",
+        "galaxy.head()"
+      ],
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "The shape of the dataset is: (82, 1)\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "    dat\n",
+              "0  9172\n",
+              "1  9350\n",
+              "2  9483\n",
+              "3  9558\n",
+              "4  9775"
+            ],
+            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>dat</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>9172</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>9350</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>9483</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>9558</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>9775</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+          },
+          "metadata": {},
+          "execution_count": 3
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "P_alHv5ljLpp"
+      },
+      "source": [
+        "This data set is contained in the package mass which comes to standard with R and contains the velocities of 82 galaxies that come from six well-separated conic sections of the Corona borealis region of the sky. When we fitted this model before, both in the case of using EM algorithms\n",
+        "and in the case of using MCMC algorithms, we selected the number of components K to be exactly equal to six. That selection came from the fact that well, we knew that the data was collected from\n",
+        "six well separated conic sections so it made sense in that context to use that number of components.\n",
+        "Now, what we want to do today in this example is to use the BIC the Bayesian information criteria to\n",
+        "verify that that choice is actually supported by the data that we have at hand. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 381
+        },
+        "id": "1EF48VnKjPkY",
+        "outputId": "eeea79d3-b421-4c7d-bd33-b42bcd7fa994"
+      },
+      "source": [
+        "from scipy.stats import norm\n",
+        "\n",
+        "## Clear the environment and load required libraries\n",
+        "np.random.seed(1)\n",
+        "\n",
+        "### Loading data and setting up global variables\n",
+        "x          = galaxy['dat'].to_numpy() # Data\n",
+        "n          = len(x)\n",
+        "KKmax      = 20       # Components used to compute BIC. From 2 to 20\n",
+        "BIC        = np.zeros(KKmax)\n",
+        "\n",
+        "sns.histplot(x, stat= 'density', bins = 6)\n",
+        "plt.title('Approximate density of the data')\n",
+        "plt.show()"
+      ],
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "zE6mgAt8VwfV",
+        "outputId": "a25b5ff2-bfc3-4070-bd91-832ca9d77181"
+      },
+      "source": [
+        "# Initializing constants\n",
+        "w_sum = []\n",
+        "mu_sum = []\n",
+        "sigma_sum = []"
+      ],
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "FqZi45dOUNKC"
+      },
+      "source": [
+        "### MLE EM algorithm"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "eH5GGs5RAl4o",
+        "outputId": "bab4817a-27f8-4f80-87fa-297b909ebb6d"
+      },
+      "source": [
+        "from scipy.stats import lognorm\n",
+        "\n",
+        "\n",
+        "for KK in range(2, KKmax + 1):\n",
+        "  print('Computing EM with {} components'.format(KK))\n",
+        "\n",
+        "  ## Initialize the parameters\n",
+        "  w     = np.ones(KK) / KK # Assign equal weight to each component to start with\n",
+        "  mu    = norm.rvs(loc = np.mean(x), scale = np.std(x), size = KK, random_state = 1) # Random cluster centers randomly spread over the support of the data\n",
+        "  sigma = np.std(x) / KK                  # Initial standard deviation \n",
+        "\n",
+        "  s  = 0     # Counter of the current iteration\n",
+        "  sw = False # Decide when the algorithm will end\n",
+        "  KL = np.NINF  # Value of Q to monitor convergence\n",
+        "  KL_out = []\n",
+        "  epsilon = 10e-6  # Stopping criteria\n",
+        "\n",
+        "  ## Checking convergence of the algorithm\n",
+        "  while(not sw):\n",
+        "    ## Expectation (E) step\n",
+        "    v = np.zeros((n, KK))\n",
+        "    for k in range(KK):\n",
+        "      v[:, k] = np.log(w[k]) + norm.logpdf(loc = mu[k], scale = sigma, x = x)\n",
+        "    for i in range(n):\n",
+        "      v[i, :] = np.exp(v[i, :] - max(v[i, : ])) / np.sum(np.exp(v[i, :] - max(v[i, :])))  # Go from logs to actual weights in a numerically stable manner\n",
+        "    \n",
+        "    ## Maximization (M) step\n",
+        "    # Weights\n",
+        "    w = np.mean(v, axis = 0)\n",
+        "    # Mus\n",
+        "    mu = np.zeros(KK)\n",
+        "    for k in range(KK):\n",
+        "      for i in range(n):\n",
+        "        # Update Mu\n",
+        "        mu[k] = mu[k] + (v[i,k] * x[i])\n",
+        "      mu[k] = mu[k] / np.sum(v[:, k])\n",
+        "\n",
+        "    # Standard deviations\n",
+        "    sigma = 0\n",
+        "    for i in range(n):\n",
+        "      for k in range(KK):\n",
+        "        sigma = sigma + (v[i,k] * ((x[i] - mu[k])**2))\n",
+        "    sigma = np.sqrt(sigma / np.sum(v))\n",
+        "\n",
+        "    ##Check convergence\n",
+        "    KLn = 0 # Value of Q function at current iteration\n",
+        "    for i in range(n):\n",
+        "      for k in range(k):\n",
+        "        KLn = KLn + v[i, k]*(np.log(w[k]) + norm.logpdf(loc = mu[k], scale =sigma, x = x[i]))\n",
+        "    \n",
+        "    # If relative error is less than epsilon stop\n",
+        "    if(np.abs(KLn - KL) / np.abs(KLn) < epsilon):\n",
+        "      sw = True\n",
+        "\n",
+        "    KL = KLn\n",
+        "    KL_out.append(KL)\n",
+        "    s = s + 1\n",
+        "\n",
+        "  w_sum.append(w)\n",
+        "  mu_sum.append(mu)\n",
+        "  sigma_sum.append(sigma)\n",
+        "  \n",
+        "  # Computing BIC\n",
+        "  for i in range(n):\n",
+        "    BIC[KK - 1] = BIC[KK - 1] - 2 * np.log(np.sum(w * norm.pdf(loc = mu, scale = sigma, x = x[i])))\n",
+        "  BIC[KK - 1] = BIC[KK - 1] + ((KK - 1) + 1 + KK) * np.log(n)  ### KK-1 independent weights, one variance, and KK means\n",
+        "\n",
+        "## Plot the BIC with different components\n",
+        "fig, ax = plt.subplots(1, 1)\n",
+        "ax.plot(np.arange(2, KKmax + 1), BIC[1:], 'r-', lw=1, alpha=0.6, label='BIC') # BIC plot\n",
+        "ax.legend(loc='best', frameon=False)\n",
+        "# plot density estimate of the posterior\n",
+        "plt.title('BIC plot over components')\n",
+        "plt.xlabel('BIC')\n",
+        "plt.ylabel('Components K')\n",
+        "plt.xticks(np.arange(2, KKmax + 1))\n",
+        "plt.show()"
+      ],
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Computing EM with 2 components\n",
+            "Computing EM with 3 components\n",
+            "Computing EM with 4 components\n",
+            "Computing EM with 5 components\n",
+            "Computing EM with 6 components\n",
+            "Computing EM with 7 components\n",
+            "Computing EM with 8 components\n",
+            "Computing EM with 9 components\n",
+            "Computing EM with 10 components\n",
+            "Computing EM with 11 components\n",
+            "Computing EM with 12 components\n",
+            "Computing EM with 13 components\n",
+            "Computing EM with 14 components\n",
+            "Computing EM with 15 components\n",
+            "Computing EM with 16 components\n",
+            "Computing EM with 17 components\n",
+            "Computing EM with 18 components\n",
+            "Computing EM with 19 components\n",
+            "Computing EM with 20 components\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "source": [
+        "It is possible to see that for small values of K, so for values around two, three, the BIC is relatively large. Then, as you start adding components to the mixture, BIC decreases. We can see that actually the optimal, so the minimum value of the BIC does coincide with K equal to seven which is great, that means that this confirms what we had expected or at least something very similar (Galaxies = 6). Then, as you add more components to the mixture  because now, you have more complexity but you are not necessarily explaining the data better, the value of the BIC starts to increase. You can see that this is not a strictly monotone, you have some local modes in a couple of places. But you can overall see that the global minimum is clearly located at K equal to 7. "
+      ],
+      "cell_type": "markdown",
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+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {},
+      "outputs": [
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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "## What happens with the variance (bandwidth) as K increases\n",
+        "fig, ax = plt.subplots(1, 1)\n",
+        "ax.plot(np.arange(2, KKmax + 1), sigma_sum[:], 'r-', lw=1, alpha=0.6, label='Sigma') # BIC plot\n",
+        "ax.legend(loc='best', frameon=False)\n",
+        "# Arrangind data\n",
+        "plt.title('Value of sigma over components')\n",
+        "plt.xlabel('Sigma')\n",
+        "plt.ylabel('Components K')\n",
+        "plt.xticks(np.arange(2, KKmax + 1))\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "source": [
+        "We discussed that the value of sigma is related, in some sense, with the number or there is a trade-off between the value of sigma and the number of components in the mixture. In particular, as you use more components, those tend to be more localized and therefore, the value of sigma becomes smaller. That is, in some sense, the intuition that we get by comparing kernel density estimation with mixture models. "
+      ],
+      "cell_type": "markdown",
+      "metadata": {}
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "## Method to compute density estimates for various values of K\n",
+        "def compute_density(xx, w, mu, sigma):\n",
+        "    KK  = len(w)\n",
+        "    nxx = len(xx)\n",
+        "    density_EM = np.zeros(nxx)\n",
+        "    for s in range(nxx):\n",
+        "        for k in range(KK):\n",
+        "            density_EM[s] = density_EM[s] +  w[k] * norm.pdf(loc = mu[k], scale = sigma, x = xx[s])\n",
+        "    return density_EM"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Estimating densities\n",
+        "xx = np.linspace(5000, 37000, num = 300)\n",
+        "KK = 8\n",
+        "mdeKK8 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])\n",
+        "KK = 7\n",
+        "mdeKK7 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])\n",
+        "KK = 6\n",
+        "mdeKK6 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])\n",
+        "KK = 5\n",
+        "mdeKK5 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])\n",
+        "KK = 4\n",
+        "mdeKK4 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])\n",
+        "KK = 3\n",
+        "mdeKK3 = compute_density(xx, w_sum[KK - 2], mu_sum[KK - 2], sigma_sum[KK - 2])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
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+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "## Plot the final result distribution for various samples\n",
+        "fig, ax = plt.subplots(1, 1)\n",
+        "# Bayesian plot (K = 6)\n",
+        "ax.plot(xx, mdeKK6, color = 'white',  lw=2, alpha=0.6, label='$K = 6$') # Trace plot of data\n",
+        "# EM algorithm K = 3\n",
+        "ax.plot(xx, mdeKK3, '--', color = 'blue', label = '$K = 3$')\n",
+        "# EM algorithm K = 4\n",
+        "ax.plot(xx, mdeKK4, '--', color = 'red', label = '$K = 4$')\n",
+        "# EM algorithm K = 7\n",
+        "ax.plot(xx, mdeKK5, '--', color = 'yellow', label = '$K = 5$')\n",
+        "# Plotting original data\n",
+        "ax.scatter(np.array(x), np.zeros((x.shape[0])), label = 'Original data')\n",
+        "ax.legend(loc='best', frameon=False)\n",
+        "# plot density estimate of the posterior\n",
+        "plt.title('Estimated distribution with different components')\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {},
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
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BNtHR0QY/86ivpUWLFkWy53FQ12loKOSlS5e4efMmdevWpXLlyjqjaZKTkw3eF3UTtJubm0n179mzh6FDh/L000/z77//EhgYSHR0NMeOHePEiRMEBQUxdepUPD09adKkCTt37iy2Z+/SpUukp6cbvQZXV1eDx7V55plnANi/f7/esbS0NE6dOkXnzp0f31gjlC9fnmbNmpGQkKD5hPYo2dnZ+Pv76+2PiooiPj5eb7/6ue/cuTOtW7fWO16lShXs7Ozw8/PjxIkTOsfCw8P18pvrEwXRpk0bAHbs2FHoVAgF+TbArl27aN++Pc888wxhYWE6xx7nffwoubm5HD58WG+/oee+NJ5HS7i/xflOttogxhTy8/MJCgri008/pW/fvnz11VcApKamsmLFCqZMmUJGRkax1GXoP331N+xHh2JqH3NwcNDsq1OnDkePHsXNzY2wsDB27txJamoq9+/f13xvd3JyMtkmDw8PAPr161dgvooVKwJoJt6Ki4szmM+ckTHFWdb8+fNJSEhg5MiRjB49mnHjxpGfn8/evXsZP348J0+eNLmsgmwq6nnqa1Fi4jJ1ncb0jI2NpXbt2novTUM+CQ/90s7OzqT6d+/ezdChQwkKCiIiIoJOnTpp+nzs3r2bjz76CBcXFwIDA7G1tS2wP4y5FMc1FKefFgU3NzdsbW2pUqWKSf2QtDFmm/q5nzBhQoHnq597bQp6j5nqEwXh6uoKYNI0Aab4tnY+bQp655r6PlaTkJBAfn6+3n5Dz31pPI+WcH+L851sdZPdmUtKSgrjxo2jVq1a1K9fn6FDh3Lx4kVGjx5tduejkmbcuHF4enoydOhQunTpwujRo/n000/57LPP2LFjh9nlqR+MV155BRsbG6NpxowZOvmrVq1qsDxvb2+z6y6OsgBWr15N27Zt8fDw4MUXX2TZsmV07tyZnTt34unpaVZZhf0CNEZh16L9IlK/9Ozt9X9nFGewo67TmJ7VqlXTs6042bNnDwBBQUG0bNkSNzc3TaCye/du7O3t6dKlC0FBQTr5LYXi9tOi1n/ixIkCn1FDLc/G/FhdpouLS4HlHThwoOQuzAgpKSmAaS3KSvu2Gk9PT2xt9f+rNfTcl4bNlnJ/i+udLIMYM4iMjGT58uV06tSJu3fv8uqrr2qO3b9/HyieXxtFpX79+gD8/vvveseMjeZR223oIfv7778B6NChg0n1X7hwgXv37tG8eXNcXFz0jpvTrJ6ens7ly5fx8fGhbt26j1WWNqmpqWzbto1hw4axYsUKPD09da6vID0el1q1ahmc8l99Ldq/PtTTzdesWVMvf0BAgMHyi+KD6joN6VmvXj1q1KjB1atXS+xFHxcXx9mzZ+nQoQPdu3cHHgYqBw8eJCsri6CgIAIDA0lKSjL5F9r9+/dL5VlUN7cber5cXFxo3rx5idZ/7949IiIieOqpp4rlcw2Y/9wXlaLcI7VtXbt2LTRvQb6tvf/RTybFjYODA+3atTNav7ZPl8bzaGn3t7B3cmHIIKYAfH19ady4sd5+Nzc3nJycdKb8Tk5OJj8/3+B/OqWFur+Feoiqmm7duvHuu+8aPEc9MZshuzdt2sSVK1d4//33eeGFFwye36ZNG8qXLw+omhXXrFmDi4uLXtN2y5YtGThwoDmXQ0hICHZ2dnz55Zc6vyR9fX0ZNWqUyeV0797d4MNUpUoVAJ37WJAej4u9vb3Ra8nNzeXnn3/W7A8PD+f+/fsMGDBAoy+ofO/RYfWPY/vy5csB+Pjjj3V+/dja2vL1119jZ2fHsmXLTC6vKOzZswcXFxf++9//cu7cOU0zf1ZWFkeOHKFfv37Ur1+fffv2mdwKlpiYiJeXl1mfT4vCpk2bSEpKYsCAAbRs2VLn2PTp0zWfP0qSefPm4eTkxPLlyw220rm6uprV3+r7778nJyeH+fPna/q9aePg4MBzzz33WDaD6h6Z+5ydOHGCQ4cO0bJlSz766CO94+7u7pp7fujQIS5cuECHDh3o06ePTr4+ffrQqVMnLl68yMGDB4t+ESYya9YsHB0dNX+7ubnx8ccfA+gsVVMaz6Ml3F9z3smFYbV9YgpahHDjxo2cPn2aZs2asXHjRsLDw4mIiODWrVt4eXnRs2dPHB0d+fLLLzXn3Lt3j3/++YeOHTuyevVqLl++zP3799m8eTNnzpwpjUti0aJFDBkyhPXr1/P7778TExNDkyZNeP7551m/fj2vv/663jm7d++mX79+bNiwgW3btpGZmcn169f5+eefycvLo3fv3uzYsYOtW7dy6NAhTp06RUZGBjVr1qRVq1bUq1cPb29vMjMzAZgyZQpBQUGMHTuWgIAAzTwx/fv3Z+vWrfTs2dPk65k7dy69evWib9++nDhxgh07dlC5cmX69+/PgQMHTC5r3bp1ZGVlcfDgQaKiorCxsaFDhw60bt2a48ePs2vXLpP0eFxOnz6tqXPnzp2aa3Fzc2P8+PE6HfNu377NqlWrGDJkCKdOnWLLli24uLjw4osvcuDAAU2HUm327t3L/fv3mTVrFk2bNtW05sycOdOoTUeOHOHLL79k4sSJRERE8Ntvv3Hv3j1eeOEFmjZtSlhYmKYvWEmxe/duPvjgA6pWrcr69ev1jqmDcnP6w6jnF9q2bRthYWHk5ORw+vRp/ve//xWr7ffu3WPYsGGEhoYSFhamM09MkyZN2L9/f4mvZRUSEkLLli15//33iYyMZMeOHURHR+Pu7k6dOnXo2LEjISEhjBgxwqTyLl68yDvvvMPy5cs5e/Ys27dv59KlSzg4OFCrVi06dOhAfHw8jRo1eiy71fMEbdy4kZMnT5KXl8eBAwf0Otk+yptvvsm+ffv46quv6NevH/v378fGxgY/Pz+6deuGv7+/Zp6YQYMG8ddffxEaGsqmTZu4cOECDRs2pFevXqSlpfH222+X+Fppt27dwtHRkYiICDZv3oyDgwN9+/alevXqLFy4UOd6S+N5tIT7a8472RQee4jTk5RMQT1c08fHR8ycOVMcPHhQM6vgjRs3xNatW8Xzzz+vV3a9evXE5s2bRUJCgrh//75OWYUNsTZka0EzrBobTtu2bVuxe/dukZSUJNLS0kRYWJjo2bOn0fptbW3FzJkzRWRkpGYel0eHxXl5eYlZs2ZpZse8e/euuHTpkvj111/FwIED9eaZqFq1qli2bJm4c+fOY8/YW6lSJTF37lzNTJdFmbH3vffeExs2bBCRkZHi3r17IjExUZw4cUKMHz9ebxhtYXoUNnTXlBl7V69eLeLi4kRmZqY4fvy4wRl7AeHg4CBmz54tbty4IbKzs8Xly5fFpEmThJ2dndHhiwMHDhQnT54UGRkZGn82xZ/69+8vwsLCRFpamsjMzBQRERFiypQpBc4Qas71F5QqV64s8vLyhBBC9OrVS+dYmzZtNNehPW+HOhkbYu3s7CwWLVokbty4IXJzc/V8paDhnwXpZCwFBweLsLAwce/ePZGUlCQ2btwoGjZsaPKMvQW9Iwo6Rzu99NJL4s8//xRxcXEiOztbxMbGin/++Uf83//9n2jYsKFBfyzompo0aSJCQkJEVFSUyMrKEomJieLMmTNiyZIlelNCFPQeM3aPvLy8xJo1a8Tt27c199/Ud4O7u7uYPXu2uHDhgsjMzBTJycni5MmT4vPPPxfly5fXydugQQOxatUqcevWLZGTkyNu3bolVq9eLRo0aGCW/xY07YGxe6c9Y+/3338vbt68KbKyssS5c+cKnLG3NJ5HJe+vOe/kwpLNgw2JRCKRSCTFiHol9Tp16ihsSdlF9omRSCQSiUTyRCKDGIlEIpFIJE8kMoiRSCQSiUTyRCL7xEgkEolEInkikS0xEolEIpFInkhkECORSCQSieSJxGonuzMVDw8PzURuEolEIpFITKd8+fKa2cRLAhnEFICHhwehoaFKmyGRSCQSyRNL//79SyyQkUFMAahbYPr371/srTFVq1YlLi6uWMt8EpE6qJA6qJA6qJA6qJA6qHhSdShfvjyhoaEl/jXDrCl+rSk5OzuLXbt2CWdn52Ive+rUqYpfnyUkqYPUQeogdZA6lE0dSvL/UHWSHXslEolEIpE8kcggRiH+/PNPpU2wCKQOKqQOKqQOKqQOKqQOKqQOxpFBjEK4u7srbYJFIHVQIXVQIXVQIXVQIXVQIXUwjgxiFKJ9+/ZKm2ARSB1USB1USB1USB1USB1USB2MI4MYiUQikUgkTyyK92C21FSSPasdHR0Vvz5LSFIHqYPUQeogdSibOsjRSWWYIUOGKG2CRSB1UCF1UCF1UCF1UCF1UCF1MI4MYhTC09NTaRMsAqmDCqmDCqmDCqmDCqmDCqmDcWQQoxBRUVFKm2ARSB1USB1USB1USB1USB1USB2MI5cdUIjt27crbYJFIHVQYc06BNGCVrhwnRzCth5Q2hyLwJr9QRupgwqpg3FkS4xCDB8+XGkTLAKpgwpr1eEp6rGdf5nFftZyhF/vVVXaJIvAWv3hUaQOKqQOxpFBjEQiUYx+1MCe+5q/W+eEUxsfBS2SSCRPEjKIUYgdO3YobYJFIHVQYa069OC23r4XqKuAJZaFtfrDoxRFBw8PDz799FNyc3PZvHkz77zzjubYsGHDSE1NZenSpfj5+T22fUOHDmXq1Km8/fbbJTqCSPqDcWSfGIVwcnJS2gSLQOqgwhp1qEk1WnARgDzsuEAdwir4c+TeZYUtUx5r9AdDFEWHxMREVqxYwWeffcawYcO4fVsVKFevXh0HBwf8/Py4c+fOY9s2bNgw6taty6RJk6hfvz7h4eGEhIQ8drmGkP5gHNkSoxCdO3dW2gSLQOqgwhp16EF9zfZ0nqMpV4gZ04zTDwIba8Ya/cEQRdUhODiYiIgITQATGBhImzZtWLhwYbEEMI6OjsyaNYtFixYBcOXKFZo1a/bY5RpD+oNxZEuMRCJRhEByNNv/45aClkhMYfLkyVSuXLlU63zmmWeYOXOm2ecFBweze/duHB0dmTNnDuvXr2fDhg0G87q5uTF+/HhsbGyMlpeZmcmMGTM0f7dr1w53d3f8/Pxo06YN/v7+7Nixg+vXr5ttq+TxkEGMQnz77bdKm2ARSB1UWKMO0ThylrrUIJ4zXAGsUwdDWKIOlStXxtXVtVTrjIiIKNJ5gYGBzJkzh8GDB/P8888TGxvL4cOHDeZNTk5mypQpZpVfrVo1AHJycli/fj0eHh6cPn2aRo0acffu3SLZXBCW6A+WgvycpBD9+vVT2gSLQOqgwhp1GEcYTbiKG3fJRwDwWt/XqI4nftRU2DplsUR/SE1NJSUlpVRTrVq1zLazadOmuLu7c+XKFX788Ufmz5/PBx98gL198f1mT01NBeDYsWOAqh+Ora0tzz33XLHVoY0l+oOlIFtiFEIdyVs7UgcV1qyDePBvJSqyYMV6KnKP3bQgmBuK2qUklugPs2bNKvU6p06davY5wcHBHDt2jM2bNwOwcuVKZsyYwRtvvMHq1av18ru7u/PRRx+Z9Tnp5MmT5OfnY2dnp9knhND5uzixRH+wFGQQoxAxMTFKm2ARSB1USB3gLulk4U5F7tHAwNBra0L6g4qi6BAUFMSuXbs0f2dlZbFo0SI+/PBDg0FMUlKS2Z+TYmNj2b9/P+3bt2fnzp14enoihGDPnj1m22sK0h8KRvHlui01leQy4pUqVVL8+iwhSR2kDtrpEE2FACFAOFNecXukPzw5OgQEBIhZs2aJrKws8ccff4iuXbsKQPj4+IgNGzYIIYT4+eefRc2aNYvFtpo1a4rly5eLMWPGiO+++060aNHCInSwpFSS/4dqJeUv1FJTSd6AqVOnKn59lpCkDtapwzd0EmeoL36jjfDBW7N/o9vLmiDmafwUt1P6g9TBEtKTqkNpBDGyY69EIil1mpFCE67Qh79JJ0OzP97VS7PdEHclTJNIJE8QMohRiJL6dvqkIXVQYW06NCQWgDg8SSVNs//frBTNdgOsd5ZSa/MHY0gdVEgdjCODGIXIy8tT2gSLQOqgwpp0qEgFqqGaNfUi1XWO3XTO1Gw3wHo0eRRr8oeCkDqokDoYRwYxCtGtWzelTbAIpA4qrEmHmlTVbF+jks6xxq88owfhsYkAACAASURBVNmur9VCY21Ykz8UhNRBhdTBODKIkUgkpYoPD6euj3l0lgdnG+LxAKAGSaVplkQieUJRvAezpaaS7Fnt7u6u+PVZQpI6WJ8Og2ivGYE0kg56OpygoRAgsnEQNhZgr/QHqYPS6UnVQY5OKsO89NJLSptgEUgdVFiTDjW0Wl9iyNY59tJLLzGQPOpQi0rYIUrbOAvBmvyhIKQOKqQOxpFBjEIUZU2QsojUQYU16eBDvmY7Bt3F8mrVqsV5IokimhyySts0i8Ga/KEgpA4qpA7GkUGMQsTHxyttgkUgdVBhTTr4aAUnMSTqHLMmHQpC6qBC6qBC6lAwin83s9RUkt/zype33inVpQ7WrUNHmoqRtBcz6SBssbFaHaQ/SB3Kug6yT0wZZty4cUqbYBFIHVRYkw4HOMMiDjGVMPIROsfGjRuHF+68Rztm0IGetFLISmWxJn8oCKmDCqmDcWQQI5FILIpqeLCEw3xCGD2seNZeSdHw8PDg008/JTc3l82bN/POO+9ojg0bNozU1FSWLl2Kn5/fY9Vz/fp1kpOTddL8+fMf13yJmdgXnkVSEoSFhSltgkUgdVAhdVARFhZGDAmav33ILCB32UX6g4qi6JCYmMiKFSv47LPPGDZsGLdv3wagevXqODg44Ofnx507dx7LLi8vL7755hs2btyIEAIhBBMmTGD69OmPVa4xpD8YRwYxCpGWZr2zkWojdVBhLTp44IYfNYghmVjiyCNX53haWhqJJJOFE+XIxodUhSxVFmvxh8Ioqg7BwcFERERoApjAwEBcXV1ZuHBhsdhla2vLypUrSUpSTcg4YMAAVq1aRWpqyfir9AfjyCBGIV566SVOnTqltBmKI3VQYS06dKEhv/I3ABPpxBz26xxX63CLKtTlBj5arTLWhOX6w1jAlP4ZJ4Cej+zbBDxjIO+jzANUn2WKqkNwcDC7d+/G0dGROXPmsH79ejZs2GAwr5ubG+PHj8fGxsZoeZmZmcyYMUPzd1xcnGbbx8eHBg0asHbtWrPtNBXL9QflKVKfmBEjRnD16lUyMzMJDw/nueeeKzB/x44dCQ8PJzMzk8jISN577z29PL179+bs2bNkZWVx9uxZevXqZVa99vb2zJ49m3///Zf09HRiYmJYuXIl1apV0ynD0dGRBQsWEB8fT3p6Ops2bcLHx6coMkgkEjPxwVGzHfNIK4w2MbgB4E4K5WS/GAvCBahhQvIycK6Xiee6PLaVgYGBREdHM3jwYJ5//nk6dOhgNG9ycjJTpkxh8uTJRpN2APMoX3zxBStXrnxsmyVFx6zhTP369RPZ2dli6NChwt/fX8yfP1/cvXtX1KxZ02B+X19fkZ6eLubPny/8/f3F0KFDRXZ2tujdu7cmT5s2bURubq6YNGmSaNiwoZg0aZLIyckRrVu3NrleFxcXsXPnTvHaa6+JBg0aiGeffVYcOXJEHDt2TMeeRYsWiRs3boigoCDRvHlzsXv3bnHy5Elha2tbqsPDqlSpovjwN0tIUgfr0mEWnTRLDgTS3KgO62ijyVeXWorbLf1BncYKuGFC2mTg3E0mnjv2sXRo2rSpyMnJEa+88ooAxHvvvSdu3rwp7O3ti12PqlWriujoaCv2h4JTaQyxxtwT/v77b7Fo0SKdfefOnRNffPGFwfyzZ88W586d09m3ePFicfjwYc3f69atE1u3btXJs23bNrF27doi1wuIgIAAIYTQCXSys7NFv379NHmqVasm8vLyRLdu3Ur1BvTv319xB7OEJHWwLh2Waa2b1IR6RnWYR0dNvnY0Udxu6Q9Pjg5jx44Vhw4d0vxdrlw5ERcXJ9566y2D+d3d3cUXX3whZs2aZTR9+umnBs8dNGiQOHHihEXqYAmpNIIYs/rEODg40LJlS2bPnq2zf+fOnbRr187gOW3btmXnzp06+3bs2MHQoUOxt7cnLy+Ptm3b6g1N27FjB2PGjClyvQCVK1cmPz+flJQUAFq2bImjo6OOPbGxsURERNCuXTs9O9VUrFgROzs7zd/Z2dnk5OQYrdcU6tev/1jnlxWkDiqsRQcvHj43dwx02lXrEI+N1jnOJW+YhWEt/lAYRdEhKCiIXbt2af7Oyspi0aJFfPjhh6xevVovf1JSElOmTCmSfU899RQZGRlFOtccpD8Yx6wgxtPTE3t7e51OTaDq5OTt7W3wHG9vb4P5HRwc8PT05Pbt20bzqMssSr1OTk7Mnj2btWvXcvfuXY0t2dnZmqDGlHIAYmJisLd/KNWePXtYsWIFW7ZsYcSIEYAqoLK3tycwMBCABQsW0KdPH3x8fIiNjWX9+vWMHj0agH379mFvb8/UqVMBWLJkCc8//zy+vr4kJCQQEhLC+PHjATh06BBJSUn06NEDgGXLltGxY0f8/PxITU1l0aJFTJ48GYCjR49y8+ZNevfuDcCqVasICAigcePGZGZmMm/ePCZPnoytrS0nT57k0qVL9O/fH4BffvmFRo0a0bx5c/Ly8vjyyy/58MMPKVeuHGfPnuXkyZO8+eabAPz+++/Url2bgIAAAGbOnMmoUaOoVKkSFy9e5NChQ5q5GTZt2oSXl5cm2JwzZw7vvvsu7u7umv5Nah22bduGs7MznTp1AmD+/PkMGDCAqlWrcvPmTTZt2sT7778PoHlJBQcHA7Bw4UJ69uxJjRo1iIuLY+3atYwdOxaA/fv3k5GRwQsvvADADz/8QNeuXalbty5JSUn89NNPTJgwAYDDhw8THx9Pz56qTonLly+nffv2NGzYkLt377JgwQKNveHh4Vy/fp0+ffoA8PPPP9OiRQueeuopsrKymDt3LhMnTsTe3p5Tp05x/vx53njjDQBCQ0Np0KABLVq0ID8/n+TkZMaNG0f58uU5d+4c4eHhvP322wBs2LCBGjVq0Lp1awBmzZrFyJEjqVy5MpcvX+bAgQMMHToUgD///BN3d3fat28PwFdffcWQIUPw9PQkKiqK7du3M3z4cED1Q8HJyYnOnTsD8O2339KvXz+qVatGTEwMv//+O6NGjdL4fF5eHt26dQNg8eLFvPTSS9SqVYv4+HhWr16tmZArLCyMtLQ0zaJ1S5cupUuXLtSvXx+fL/8Hearn6D8T3+Pv8L+5ffu2pg9cTk4OvXv3purlqnBG1ek38KmWNOnVlePHj3P16lVee+01ANauXUvTpk1p2rQpOTk5fPXVV4wfPx5HR0fOnDnDmTNnGDBgAAC//vordevWpWXLlggh+OKLLxgzZgwVKlTg/Pnz/PPPPwwePBiAjRs34u3tTZs2bQCYPXs27733Hm5ubly5coW9e/fyn//8B4AtW7bg4uKi6XMxb9483nrrLby8vIiOji7yO8LR0ZGAgAC6d+8OWO87wsPDA09PT00/yoLeEQ4ODlSuXJnu3btTp04dEhISOHr0KL179+bll1+mcePGHD58mIMHD3Lp0qVieUe0aNGCmzdv0rdv3xJ9R9SuXRvgiXtHGOrbWhKY3GxTrVo1IYQQbdq00dk/ZcoUcf78eYPnXLx4UUyaNElnX7t27YQQQlStWlUAIjs7W7z++us6eQYMGCAyMzOLVK+9vb34448/xPHjx0WlSpU0+9944w2RlZWll3/nzp1i8eLFRpvCqlSpIipVqqRJjo6Oj90EZmdnp3hTnyUkqYN16RBJTSFAxONeoA5deUacpKHYQUvRk2cVt1v6g9RB6mB+srhlBxISEsjLy9NrtahSpYpeK4kadUvLo/lzc3NJTEwsMI+6THPqtbe3Z/369dSpU4euXbtqWmHU9Tg5OeHq6mqy/QDp6encvXtXkx73UxLApEmTHruMsoDUQYW16FAF1bwa8bgaPK7W4S9O0IKLdOc4m/in1OyzFKzFHwpD6qBC6mAcs4KY3Nxcjh8/TteuXXX2d+3alcOHDxs858iRI3r5u3XrRnh4OHl5eQXmUZdpar3qAMbPz4/g4GDNRERqjh8/Tk5Ojk453t7eNGnSxKj9EomkeChPOSpyD4A7VFLYGolEUlYwq+lGPdR5yJAhwt/fX8ybN0/cvXtX1KqlGgb5xRdfiJUrV2ryq4dYz507V/j7+4shQ4boDbFu27atyM3NFRMmTBANGzYUEyZMMDrE2li9dnZ2YuPGjSI6Olo8/fTTomrVqprk4OCgKWfRokUiOjpaBAYGiubNm4tdu3YpMsQ6KChI8aY+S0hSB+vRoSbemhFHvxr5RGQNOkh/kDpYiw4WOcQaECNGjBDXrl0TWVlZIjw8XHTo0EFzLCQkROzdu1cnf8eOHcXx48dFVlaWuHr1qnjvvff0yuzTp484f/68yM7OFufOnROvvvqqWfXWrl1bGKNTp06afE5OTmLBggUiISFB3Lt3T2zevFnUqFGj1G/AU089pbiDWUKSOliXDo7YCR88RQ0Mz3thLTpIf5A6WIMOFhvEWEsqyRswdepUxa/PEpLUQepgTIfVtBUnaSBO0kBxu6Q/SB2kDuYni5snRiKRSEqLRiTTnEvkYYcNqjeWRCKRPIri0ZqlppKMIn18fBS/PktIUgepgzEdthKg6UPjjqvitkl/kDpIHcxLFjfEWlJ8PPvss0qbYBFIHVRYgw69acPndGY0nfHC02AebR3itRaL9DIyJLusYg3+YApSBxVSB+PIz0kK0ahRI6VNsAikDiqsQYeXsWcI+wDYST3iSdDLo63DHa3XUxVcuFjiFloO1uAPpiB1UCF1MI5siVGIe/fuKW2CRSB1UGENOlQhS7MdT7LBPNo66K6fVL7kDLNArMEfTEHqoELqUDCKfzez1FRKw8Nkkskq0lEaCQEiD1thi02h+QdrrXg9nA4lYpNMMslUckn2iSnDFHXV1LKG1EGFNejgRRoAibiRjzCYR1uHeLI121W0WmWsAWvwB1Moig4eHh58+umn5ObmsnnzZs1CkwDDhg0jNTWVpUuX4ufn91i2+fr6MmLECIYMGcLkyZNp3rz5Y5VXENIfjCP7xCiEjY11vZSNIXVQYQ06eKJaPT6BykCiwTzaOtzhYRO6l5Ggp6xiDf5gCkXRITExkRUrVvDZZ58xbNgwbt++DUD16tVxcHDAz8+PO3fuPLZtw4cP11nTaPXq1bz11luPXa4hpD8YR7bEKMTx48eVNsEikDqoKOs6OOKgWTcpkYpG812/fp1XX32VoUOHYuP5sB+MB3klbqMlUdb9wVSKqkNwcDARERGaACYwMJA2bdqwcOHCYglgAHr37s3TTz+t+Ts7O7uA3I+H9AfjyJYYhbh69arSJlgEUgcVZV0Hd1yBeACScDKYp3Hjxrzwwgualef9azZkxueexOVlc+7BpyhrwVL9YSwwzoR8J4Cej+zbBDxjwrnzgPkPtouqQ3BwMLt378bR0ZE5c+awfv16NmzYYDCvm5sb48ePL7C1IzMzkxkzZujs+/777wkPD+e7774jNTWVBQsWFMlWU7BUf7AEZBCjEK+99hozZ85U2gzFkTqoKOs6eOCCOohJ1Jr/RY2dnR2vv/46fn5+nDhxAoBK3i7cndKGH2bO5P79+6VpruJYqj+4ADVMyHfDwD4vE8910douqg6BgYHMmTOHwYMH8/zzzxMbG8vhw4cN5k1OTi5Sn5N169bRqlUrevToQcWKFQkLCzO7DFOxVH+wBGQQI5FIShx3Kmi2E7HTO96xY0eqVKkCQHp6Ora2tjg7O1O9enWefvppTp48WWq2SoyTBtw0IV+8kX2mnPu4bW5NmzbF3d2dK1eusHnzZmxsbPjkk0+YO3cueXnF81myYsWKLFmyhIEDB5Kfn8+kSZP4448/aN68OVFRUcVSh8Q0ZBCjEGvXrlXaBItA6qCirOuQQTbbeQZ3MrmCfqtKcHAwAJcvX2bBggU4OzszZswYANq3b291QYyl+sN8Hn7qMZdHPy+ZQlF0CA4O5tixY2zevBmAlStXMmPGDN544w1Wr16tl9/d3Z2PPvrIrM9JXbt2Zf/+/WRmZgLw2Wef4eDgQKtWrUokiLFUf7AEZBCjEE2bNuXatWtKm6E4UgcVZV2H41zkBSPHfHx88PDwACAjI4Po6GgAkpKScHOohH+5OrQv34wjmf8aHZpd1ijr/mAqRdEhKCiIXbt2af7Oyspi0aJFfPjhhwaDmKSkJLM/J125coVXXnlFZ5+dnR3//POPWeWYivQH48jRSQrRtGlTpU2wCKQOKqxZB+35NbR/DR85coTGn23g/a8/5GDmadxwU8I8RbBmf9DGHB0CAgKYNWsWwcHBPP3003Tt2hVQBcnNmjWjWbNm/Pzzz9SsWfOx7Tpz5gyhoaF8/fXXjBkzhokTJ7Jr1y5NAF7cSH8wjmyJUYicnBylTbAIpA4qrFkH7WGq2v8J/P3339xzagvpqr/dcSGRpNI2TxGs2R+0MUeH8PBwwsPDmTx5ss7+mJgYevfuXdymsX37drZv317s5RpC+kPBKD41saUmueyATDKVbHJ1dRVLliwRS5YsEVOmTNE7vs77dc3SA+1sn1bcXplkksn0JJcdKMOMHz9eaRMsAqmDirKuww905Az12Ucz3HDV7Nee+v3ff//V0yFRCM12PddqJW+ohVDW/cFUpA4qpA7GkUGMQjg66s+VYY1IHVSUdR0akEoTrtCJ02SSqdlfp04dzXZkZKSeDrdzHs6CWquie8kbaiGUdX8wFamDCqmDcWQQoxBnzpxR2gSLQOqgoqzr4PFgyYFMypGltbBj3bp1NdtRUVF6Oty4l6LZ9nYsj7VQ1v3BVKQOKqQOxpFBjEJIp1QhdVBR1nVwR7WUQKLWpyQ7Oztq1FDN4RoXF0dmZqaeDrdy7mq23bDFzk5/orzSwglH3KhcKnWVdX8wFamDCqmDcWQQoxADBgxQ2gSLQOqgoqzr4PFgBetErUnla9asib29aoCkeg6MR3VIIkOz7ZyRjo+PT0mbqkc5HNlDM7LIIYlUlvJciddZ1v3BVKQOKqQOxpFBjEQiKVGcKU+5B5+QknDW7NfuD2NsIq8k9fhqwDkrnVq1apWQlcapREUiqEj6g6UT3uUg9Sh9OyQSiT4yiFGIX3/9VWkTLAKpg4qyrIO71ieYRK0VrH19fTXb6iDmUR2SSNVsV8i+q0gQE08SozjEbzTT7HuHOgWc8fiUZX8wB6mDCqmDcWQQoxDaHRqtGamDirKsg4fWJyTtFazVn4by8/OJiYkB9HVIJY2W9k34bsK3nJrWX5EgRs0kLpH3YPHKwVzArgRfn2XZH8xB6qBC6mAcGcQoRMuWLZU2wSKQOqgoyzq4a31CSnrwyrGxscHb2xtQdeq9f1+1KOSjOgjgRF4EyRVScHCxpUaNGtjaKvPaiiOB/6GyrzpxBNK8kDOKTln2B3MoTR1q166NEIJmzZoVnvkBgwYNIjk5ucTtMEWHa9euMXr06GK15UlABjEKIbQm8bJmpA4qyrIOHpTTbCehuk4vLy9Np95bt25pjhvTQb0cgb29PdWqld6kd01piIvWiKpQrVdmWyqVWL1l2R/MwVwdatSowU8//URMTAzZ2dlERUXxzTff4O5e+BxDN27cwNvbm4iICJPrCw0NpUGDBmbZWBRKwh9KIgBTAhnEKMQXX3yhtAkWgdRBRVnW4SQ3GUF7ptCBA8QD6Iwy0g5ijOmgvaZSaX5S2ssdUknhMKoF+I7x0NZntCbtK27Ksj+Ygzk61KlTh/DwcBo0aMAbb7xB/fr1GT58OEFBQRw5cgQ3N+MLiDo4OJCfn6/TKmgKWVlZxMfHm5y/qEh/MI4MYhRizJgxSptgEUgdVJRlHSK5yRIOMYswjnIegOrVq2uOawcxhnTowtM8e8SeynOPcT8lr9RaYmpQFQ9Uv1RTH/TluUo0qQ/6+LTgZonV/aT7g61TeWq+8j5NJ/3M01PX0XTSz9R85X1sncybsNAcHRYuXEhOTg7dunXjwIED3Lhxg+3btxMcHIyPjw8zZ87U5L127RpTp04lJCSElJQUli5davAzTo8ePbh06RIZGRns2bOHt99+GyEElSurOqs/2poxbdo0Tp48yZtvvsm1a9dISUnhl19+oWLFipo83bt3JywsjOTkZBISEvjzzz8L7fPyqA5eXl5s3ryZjIwMrl69anAI9tixY/n3339JT08nOjqahQsXUqGCaoRdp06dWLFiBa6urgghEEIwbdo0AAYOHMixY8dIS0sjNjaWNWvW4OXlZeptKHVkEKMQameydqQOKqxNB+1AJDY2VrNtSIchVOT/0rfx+uVl5Mdk6wRAJUkLamq2T6L6T0gAJx+MTKrFLTzxKJG6n2R/sHUqT6P3v6NK2544uVfDsbIXTu7V8Grbk0bvf2dWIGOqDm5ubnTv3p1FixaRlZWlcywuLo41a9bQv39/nf3jx48nIiKCli1b8n//9396ZdauXZvffvuNjRs30rx5c3744QedQMgY9erVo1evXrz88su8/PLLdOrUiUmTJulc07x582jVqhVBQUHk5+fzxx9/YGNjY7TMR3VYsWIFvr6+BAYG0rdvX0aOHEmVKlV08uTn5zNq1CiaNGnCoEGDCAwMZM6cOQAcPnyY0aNHk5qaire3N97e3nz99deAaomDTz75hGbNmtGrVy/q1KnDihUrCr1upbBX2gBr5fz580qbYBFIHVRYmw7qz0l5eXncuXNHs9+QDklarymb5ByqNSqdlpgWWh2ST5Kj2f6JSmwhkBPc5S7/lkjdT7I/+HR/h3JetbB5ZHZlWzs7nLxq4dNtCDf+XGRSWabq4Ofnh62trdH858+fx93dHS8vL83nnz179jB37lxNntq1a+ucM3z4cC5evMiECRMAuHTpEk2aNOHjjz8u0BZbW1sGDx5MerpqjqPVq1cTFBSkOW/Dhg06+YcOHUp8fDyNGzfm7NmzRu3XvtYXX3yRZ599lqNHj2rKuHDhgs453377rWY7KiqKTz75hMWLF/P++++Tm5tLamoqQgji4uJ0zgsJCdFsX7t2jVGjRnHs2DEqVKjAvXv3Crx2JZAtMQrxzz//KG2CRSB1UFGWdahDLepSG/cHrRZ2dnZUrVoVUP1Kzs/P1+Q1pEMSD3+h2iRn4+HhUSoL4rXg4S/6k1p9YdZwkK/Zwx6Oka21DlRx8iT7g2vjtnoBjBpbOztcG7czuazi0kHdyqHdQTY8PLzAcxo2bMixY8d09qmDhoKIiorSBDCgamnUbiWpW7cua9asITIyktTUVM0cSQX19dLWoVGjRuTm5urYf/HiRb1Oup07d2bnzp3cvHmTtLQ0Vq1ahaenJ87OzhRE8+bN2bhxI1FRUaSlpbFv375C7VMSGcQoxODBg5U2wSKQOqgoyzosxpNIrpNIIq644OHhoRkmrf0pCQzrkMTDIMf+riqwUA/PLknUfV7SqEQk10u8Pm2eZH+wsSu4gb+w49qYqsOVK1fIz8+ncePGBo/7+/uTlJREQkKCZl9hrQo2NjZ6o4IK+uSjJjc3V+dvIYTOtAB//vknHh4e/Oc//+HZZ5/l2WefBQpeqVpbB0MB2aPUqlWLrVu3EhERQZ8+fWjZsiXvv/8+oOrEbAxnZ2d27txJeno6b775Jq1ateLVV18t1D4lkUGMRCIpUVwftGjkY0MqaZpWGEDnU5IxksjTbDumqdZSKunOvZWpRO0HrS+nqYMc8Gw64n5ewcfzCz5eFJKSkvjrr78YOXIk5cqV0zlWtWpVBg4cSGhoqFllXrhwgVatWunsCwgIeCw73d3dady4MZ9//jl79uzhwoULBY6aMsT58+dxcHDQsaVBgwY65QQEBGBvb8+HH37IP//8w+XLl/X6kuXk5OgtqOrv74+XlxeTJk3i4MGDXLx4Ua+vjaUhgxiF2Lhxo9ImWARSBxVlWQe3B4s4plEJATojHR4NYgzpkKj1ycbxnmpYc0kHMfV4OAT8vIGVqz2oSBsaMIBWeseKgyfZH1LOHSHfyDDl/Pv3STl72OSyzNHhv//9L05OTuzYsYMOHTpQo0YNunfvzl9//UVMTAxTp041uSyAH374AX9/f2bPno2fnx+vvfaapkWkqPO2qEckDRs2jHr16tGlSxfmzZtX6HnaOly6dIlt27axdOlSWrduzTPPPMNPP/1ERsbDxVIjIyNxcHDggw8+oE6dOrz55psMHz5cp8yoqCgqVapEYGAgHh4elC9fnujoaLKzszXn9ejRg08++aRI11payCBGIUqjOfxJQOqgoizr4MpdAJIfDE3W/mX3aBBjSIckrflYymWo+hqUdBBTV2uCu6sGXpMr8ecIl1jDMbwp/l+qT7I/xOxYTnZ8tF4gk3//Ptnx0cTsDDFypj7m6HDlyhUCAgKIjIwkNDSUyMhIfvzxR/bu3Uvbtm3NntgtKiqKvn370rt3b/79919GjBihGZ2UnV20vlBCCF5//XVatmxJREQE8+fPZ/z48YWe96gOQ4YM4caNG+zfv58NGzbw448/6jxLp0+fZuzYsUycOJGIiAgGDhzI5MmTdco4cuQIixcvJjQ0lISEBCZMmEBCQgKDBw/mtdde49y5c0yaNImPPvqoSNdamgiZDCdnZ2exa9cu4ezsXOxlT506VfHrs4QkdSj7OuRgLwSIEzQUgBg1apRYsmSJWLJkiahYsWKhOtSjlhAgBIit7i+LJUuWiBkzZpSozaN5TlPna7TVO/4tHTXH29NU+sMjydapvKjZY6RoOvFn8fSUdaLpxJ9FzR4jha1T+SdahylTpojo6OhSr9fSdDA1leT/oeokh1hLJJISwxlnHB58TkpGNT+IuiUmKytLZxSHMZJI0WxXyFRte3p6Gux4WVx8y0F+wom6VOMG+sNer2pt18WFQyVixZNLfnYmN/5cZPJQaktlxIgRHDt2jMTERNq3b8/48eP5/vvvlTZLooUMYhRi9uzZSptgEUgdVJRVHdxwgQdBTAqO2NnZ4eGhGmptqFOvIR1SSSOSWiRTKBriVQAAIABJREFUgRvlVP1pbG1tcXd3JzExscRsv0c2Z4gyeCxS6xNXvRJ4jZZVfzAXpXXw8/Pj448/xt3dnejoaObOncusWbNK3Q6ldbBkZJ8YhXjvvfeUNsEikDqoKKs6uPFwuvVkHPHw8NAMETUUxBjSIR+oTzStOM/vnR/uV3LUxFUeBk/1yC0gZ9Eoq/5gLkrrMG7cOHx8fChfvjwNGzbk888/N2ttpeJCaR0sGRnEKIS5w+rKKlIHFWVVB1ceTjGfjG2BnXqhcB20z1EyiLlGjGa7LmnFXn5Z9QdzkTqokDoYR35OUogrV64obYJFIHVQUVZ1cOPhnB0p2BQaxBSmg/Y5JbUoXQ28mYYfkdizj0T+NrC0QCbZ3KIq1YmjHreL3Yay6g/mInVQIXUwjgxiFGLv3r1Km2ARSB1UlFUdtnGc6njgSkWSiKCTZ5DmmPbsqWoK00G97g2UXEtMY6rxLmEAzKITfxvJF0kVqhNHVRKoQAXuUXzrypRVfzAXqYMKqYNx5OckhfjPf/6jtAkWgdRBRVnVIY98YknkPNeJIxFPT0/NMUNBjDEdRtGBPTRjX4oXmedU886UVBBTj4crBkdivP/DVSpptutQvCtrl1V/MBepgwqpg3FkECORSEoN9cik+/fvk5KSUkjuh9TDhi6cphmXSb+m6lSrHmZd3NTWei1eK6B15ToO5GNDDN64aPX9kUgkpYcMYhRiy5YtSptgEUgdVFiLDuogxtjQaGM6aK9knROrCn7s7e1LpMNjDa3RRjcxHmjNJhxHHKnBbQ4b6DfzOFiLPxSG1EGF1ME4sk+MQri4uChtgkUgdVBRVnXoTRt8KUcK9/mz3HnN4nzGghhjOiTxcFI7kfhwgjwvLy+SkpKK0WKoodX6EoPxBSozi7EPzKOUVX8wF6mDCqmDcWRLjEJ06NBBaRMsAqmDirKqwyDuM5d9LCMMH9eH/UYM9YcB4zpor2TtkPYweCiJfjE1UK2xk0zlYu2saw5l1R/MReqgQupgHBnESCSSEsNVawVqBy8nzba5M+0maZXjlJGl2S6JYdY+D1pfblIyQ7glEknxIT8nKYQpy69bA1IHFWVVB7cHSw5kUo7KVStr9hsLYozpkMzDwMU55+F2cbfEeOBKuQf9YG5qrWRtjGm0py73ycGW/3C42Owoq/5gLlIHFVIH4xSpJWbEiBFcvXqVzMxMwsPDee655wrM37FjR8LDw8nMzCQyMtLgFMq9e/fm7NmzZGVlcfbsWXr16mV2va+++irbt28nPj4eIQTNmjXTK2Pv3r0IIXTSL7/8YqYCj89bb71V6nVaIlIHFWVVB9cHn2OSqVzo8GowrkOy1mcdl/s55OWpPi8VdxBTQ6v15aYJI47eJpq3+ZvenCtWO8qqP5iL1EGF1ME4Zgcx/fr145tvvmHmzJm0aNGCsLAwtm3bRs2aNQ3m9/X1ZevWrYSFhdGiRQu++OILFixYQO/evTV52rRpQ2hoKKtXr6ZZs2asXr2a9evX07p1a7PqrVChAocOHWLSpEkFXsOPP/6It7e3JimxLkVJzTb6pCF1UFFWdXB7MCV/ChU0I5PAeEuMMR2SuKvZdidHEwQVt27Z5LCGNuzjaU6bkD/mQWuNOymUL8Zh1mXVH8xF6qBC6mAcsz8njRs3jmXLlrFs2TIAxo4dS/fu3RkxYgRTpkzRyz98+HCio6MZO3YsABcuXCAgIICPPvqIDRs2ADBmzBj++usvzUqds2fPplOnTowZM4YBAwaYXO/PP/8MQO3atQu8hoyMDOLi4sy99GIlOjpa0fotBamDirKogz12VNS0xDwMYvLy8khLM7zekDEdkrWGOruRxZ07d/D29sbBwQFXV1ez5pwpiAtc502um5z/ptYClz5U4YoZ5xZEWfSHoiB1UCF1MI5ZLTEODg60bNmSnTt36uzfuXMn7dq1M3hO27Zt9fLv2LGDgIAA7O3tC8yjLrMo9RbEwIEDiY+PJyIigq+++oqKFSsWmL9ixYpUqlRJkxwdHc2u81HkuH8VUgcVZVEHVx72gUnGSRPEFDQk2pgOedznSzrzMV1YiIvO8gNK/kqN0fod6EPxzVlTFv2hKEgdVEgdjGNWS4ynpyf29vZ6rRhxcXF4e3sbPMfb29tgfgcHBzw9Pbl9+7bRPOoyi1KvMdasWcO1a9e4ffs2TZo0YdasWTRr1oxu3boZPScmJkYTcAHs2bOHFStWsGXLFkaMGAGoAip7e3sCAwMBWLBgAX369MHHx4fY2FjWr1/P6NGjAdi3bx+9evXS/HpcsmQJzz//PL6+viQkJBASEsL48eMBOHToEElJSfTo0QOAZcuW0bFjR/z8/EhNTWXRokVMnjwZgKNHj3Lz5k3Np7pVq1YREBBA48aNyczMZN68eUyePBlbW1tOnjzJpUuX6N+/PwC//PILjRo1onnz5uTl5fHll1/y4YcfUq5cOc6ePcvJkyd58803Afj999+pXbs2AQEBAMycOZNRo0ZRqVIlLl68yKFDh3jnnXcA2LRpE15eXppgc86cObz77ru4u7tz9epV/P39ycnJAWDbtm04OzvTqVMnAObPn8+AAQOoWrUqN2/eZNOmTbz//vsA7Nq1C4Dg4GAAFi5cSM+ePalRowZxcXGsXbtW0/q3f/9+MjIyeOGFFwD44Ycf6Nq1K3Xr1iUpKYmffvqJCRMmAHD48GHi4+Pp2bMnAMuXL6d9+/Y0bNiQu3fvsmDBAqZOnQpAeHg4169fp0+fPoCqJbBFixY89dRTZGVlMXfuXCZOnIi9vT2nTp3i/PnzvPHGGwCEhobSoEEDWrRoQX5+Pra2tmRmZlK+fHnOnTtHeHg4b7/9NgAbNmygRo0ams+rs2bNYuTIkVSuXJnLly9z4MABhg4dCsCff/6Ju7s77du3B+Crr75iyJAheHp6EhUVxfbt2xk+fDj8P3tnHh9Vdf7/dyb7RpLJTkII+y4EkH2TAmqtIKioaFXUlqIWt4KK32prFa1UBFol1F0sFCz+ilZxQdlkEcMiEDAsYTH7CtmXIff3x525uSG5yWzhzkzO+/W6L+7MPffcJx+eTJ455znnQf6i4O/vz6RJkwBYsWIFs2fPJj4+nuzsbDZu3MiCBQsUnzeZTMrvyapVq7jhhhtISkqisLCQNWvW8PjjjwOwc+dOysrKmN73Ovi3PLpqCjYyevRoamtrycjIUDTcu3cveXl5Sg5cQEAABw8epF+/flRWVrJ8+XIWL16Ml5cX2/bvJzMzk1tvvZVu3boRGBiI0Whk4cKFnDx5kqVLl7Jw4UL8/Pw4cuQIR44cUUZyP/roI7p3786wYcOQJIklS5bw6KOPEhwczPHjx/n++++59957Afjvf/9LXFwco0aNAuSR4Xnz5hEREcGpU6fYunWrsg18+T9+hIsAMD1lPPt+yuDXv/410dHRnD9/3u7PCKPRyLp167j22muBjvsZkZCQwLPPPqtM+XfUz4hevXpx77338vjjj7vVZ0RLua3tgWTtER8fL0mSJI0aNarJ+4sXL5aOHz/e4j0ZGRnSU0891eS9MWPGSJIkSbGxsRIg1dbWSrfffnuTNnPmzJGqq6vtem7Xrl0lSZKkwYMHt/kzDR06VJIkSUpJSWl2LSgoSNqyZYsUExMjhYaGKoefn5/VmmkdzzzzjMN9eMIhdPBcHa6mnySBJIG0yucXUmpqqpSamirdfffdDuvQv39/pb+ZM2c60W4vm9rfwkjlZ1zEROEPTj6EDu6tg+VvaFBQULs9w6bppKKiIkwmU7PRj5iYGM0cE8tIy+Xt6+vrleQ+rTaWPu15rrUcOHCAuro6evXqpdmmoqKC8vJy5bCMHDjC5VNjHRWhg4wn6nCJBvbRjxN0pci8Uy+0Pp1krQ4FBY076TpzOukwPTlPZ75mmFXts1QJx4lITrPDE/3BHoQOMkIHbWwKYurr69m/fz9Tp05t8v7UqVPZvbvlPRL27NnTrP20adNIS0tTlklqtbH0ac9zrWXAgAH4+fmRm5vrUD+2op6e6sgIHWQ8UYcDZDCS4/ThHFuGNZYKaC2IaU0HLyCMYJKJp6yojIaGBsC5QUwX8ulCDklYtxlfrnl3X4A4HP9yY8ET/cEehA4yQgdtbF5ivWzZMh544AHmzp1L3759WbZsGUlJSaSmpgKwZMkS3n//faV9amoqXbt25dVXX6Vv377MnTuX+++/n7/97W9KmxUrVjBt2jQWLVpEnz59WLRoEVOmTGH58uVWPxcgIiKCwYMH079/fwD69OnD4MGDiY2NBaB79+788Y9/ZNiwYXTt2pXrr7+ejz76iAMHDrBr1y5bpXAIy7x4R0foIOPpOqgLNbYWxLSmw2rGcYFKzpBLL5KUftRLtx3BHz/CzUvC87CuVk2+KtiJM2/s5ww83R+sReggI3TQxubwbsOGDURGRvLss88SHx/P0aNH+eUvf6ksAYuPjycpKUlpf/bsWX75y1/y2muv8dBDD5GTk8OCBQuU5dUgj8TcfvvtvPDCC/zlL3/h9OnT3Hbbbezbt8/q5wJMnz6d9957T3m9fv16AP70pz/x5z//mbq6On7xi1/wyCOPEBISws8//8xnn33Gn//8Z+VbnUAgcD5Go1E5Ly0tbaWlNhdU37mMBFFUVERUVBRBQUEEBgZSXV3tkI2xRAE5AOQTZNU9NdTxb8ZwEV+OiiouAoEu6J7846pHeyYlhYaG6v7zucIhdOgYOjzxxBNKIm5rifGt6fA0E5Uk2umMkO68806lz6SkJIdtHKFKRP4744U/uMAhdHBvHVwusVfgPCxL7jo6QgcZT9Th/5jEDq5iEyOIKJenZyorK1tNjG9NhxIaR0uN+DYpXaAuaWAvsQQr53k6j6p4oj/Yg9BBRuigjcgW0omEhAS9TXAJhA4ynqjDIGoYz2EAzoXeDrSeDwOt61BKvXIegQ9HnBzExNG4gioffaeXPdEf7EHoICN00EaMxOjElV4N5aoIHWQ8UYdw1Wod7yh/oO18mNZ0KKVWOTfStIikM1Yoxao+DvNVVbOtJQADfng7bAd4pj/Yg9BBRuigjQhidGLDhg16m+ASCB1kPFGHCORE20sY8Ar1AtoeiWlNhxIaE3cjaGhSesA500mScp6nqprdFvMYwwVCqaaBG6zcX6YtPNEf7EHoICN00EYEMTph2V68oyN0kPFEHSLMgcAFwjD4yB81bQUxrelQSuNeM0ZMVFVVUVMjj5g4YyRGvc9LPtYXlKwFwsyb3sXh77Ad4Jn+YA9CBxmhgzYiJ0YgELQL4eag44JXYyFIR6pNl9JY+TrCHHAUFhbSpUsXjEYjXl5eSJKkdXubvEgx/2EEsfiSx762bzCTp5p6ihXfCwWCK4oIYnRi27ZtepvgEggdZDxRh3BzZcQyQ2OV+LZyYlrT4SJlNOCFAQmjeWqpqKiILl26YDAYMBqNSikTezjEKQ7ZcV++qvRAnJMSgj3RH+xB6CAjdNBGBDE6UVtb23ajDoDQQcbTdAghGB/zdFK5d6jyflsjMa3p0ACMZxBl1FBo3in38rwYR4IYe8lTTT3F4Zz/R0/zB3sROsgIHbQRY586ce211+ptgksgdJDxNB0iVNv2V/k17r/S1khMWzrs5jBHOUE+jcVhLTgjudceCimmATlxOU6Vt+MInuYP9iJ0kBE6aCOCGIFA4HTCaZxCqg6QR2IqKyuVoq/OwllBTCghXMcIUuiPEdtqMZlooAi5rEKseQpNIBBcGcR0kk6oC1d2ZIQOMp6mQxEXWMx4IoCQwf0wYF1Sr606qKeTHFmh1J8kNpuTeVcygUfYYdP9eRiJoZg4itpubAWe5g/2InSQETpoI0ZidOK6667T2wSXQOgg42k65FLIS+zk+ZCDGG6VC8JaU/ixLR2G0Zt7GMWjjCOCMEpKSpQVSY6MxMSpSg7km6eGbCHfPPIUQC2drKyA3Rqe5g/2InSQETpoI4IYnUhOTtbbBJdA6CDjqTqEh4cr59aMxLSlwwPE8B57eY3vSCaOS5cuKcGRIyMxsar9XfK4ZPP9haqSBTGEt9LSOjzVH2xF6CAjdNBGBDE6oZ7L78gIHWQ8VYeIiAjl3JqRmLZ0KFFt6x9BYJN7goODCQgIaPG+tohV9Ztvxwqj5ZRzPaMYxiB+NicdO4Kn+oOtCB1khA7aiJwYnXj33Xf1NsElEDrIeJoO4YRjwJvwUKPynjUjMW3pUKoqDWA0j34UFhbSu3dvQJ5SysrKstle9f4u+XasMPqBozbf0xqe5g/2InSQETpoI0ZidGLhwoV6m+ASCB1kPE2HP3MVxRSzY/d26nfJwYs1IzFt6VCqmuqJMH8Hc8YKpVhVyYE8G0oOtBee5g/2InSQETpoI0ZiBAKB04mgcSm1V7gv4FjJAQsl1KueIU8BOWOFUpyq4GMB1m+Y5+/vz/Tp0+ncuTMZGRl89913VFQ4Z68YgUDQNiKI0Yldu3bpbYJLIHSQ8TQdwlXBBhFyEGPNSExbOpSq8lUsE1XqXXrtH4kpM/cfRp2Ve73ExcXx+9//nsjISBoqTPTLi+SGIf34ZN8Ovq7bb5cdFjzNH+xF6CAjdNBGBDE60VY1346C0EHG03SIUBVFNBh9qK+vp7q6us372tKhhCrVM+SppctLD9hDLPJz84gEK4IYLy8v7rvvPiIj5Y3xGnLqmb/+WQC6hU5jS71jxSg9zR/sReggI3TQRuTE6MSNN96otwkugdBBxtN0iDAHG5UEYQgwWDUKA23rUKpKurVMWVVUVCi1ZeyZTgrAT0kXzie01bYWJk+eTFKSvP9NXl4e73z6vnIt8lIFY8eOtdkONZ7mD/YidJAROmgjghiBQOB0ws3BxgUvec8UZ+TDAJSoRkmMqqklS3Kv0WjEy8u2zepqqCOMCoLw4VbOttne399f+aMiSRLvv/8+B04eotq8Wiq8roQpU6bYZINAILAPEcToxNtvv623CS6B0EHG03SIMOeYlHvLu9daOxLTlg6VVJFPNKdJIpcg5X1LEOPj40NYWJg9JlONiSIrppJGjhyp7EezZ88ezpw5A0CBOUsn8lIxcXFx9O/f3y47wPP8wV6EDjJCB21EEKMTEyZM0NsEl0DoIONJOvjhSxBy/ku5jxzEWDsSY40OcRTSk/P8msZkR2fVULKGSZMmKefffPONcl6AHDwZpWIkk8TkyZPtfoYn+YMjCB1khA7aiCBGJ3r16qW3CS6B0EHGk3QIp3EkpMpXrilk7UiMvTo4q5p1W/Ts2ZPOnTsDcPr0abKzs5VrBeb6S940YCqop3///gQGBtr1HE/yB0cQOsgIHbQRQYxOXLxo3TJOT0foIONJOoSrkmMr/eVza0di7NXBkZGY2YxhFRN5jmvoQkKrba+++mrlfPv27U2uFajqL0n5dRgMBgYMGGCTLRY8yR8cQeggI3TQRiyx1ok33nhDbxNcAqGDjCfpcJaf6U9Xpl19Db2GD8AH60di7NXBkZGYSXjzO+SA5FP68nMrbVNSUgAwmUwcOnSoybUCVf0l7+IaIIQhQ4aQlpZmkz3gWf7gCEIHGaGDNmIkRieefvppvU1wCYQOMp6kQx0mjnOO+quD8Bls20iMNTo8wFj+H1ezjatIQp7acWTDuzjVKqf8VkoOdO/enU6d5Byf9PR06urqmlwvUJ035MmJzQMHDsTb2xtb8SR/cAShg4zQQRsRxAgEgnYhPFxeXt3Q0EBZWZnT+r0Kb27iByZymFjkZ5hMJiVQsnU6KVa1gV4B2tWChw4dqpwfOHCg2fVC6qnDlyziKS6Ug6qAgAB69uxpkz0CgcB6RBCjE/v27dPbBJdA6CDjiTpEREQA8ny+tbvXWqNDCY37wETSmDhbUCCPhYSGhipLoK0h1rysupgI6lU1ny5nyJAhgByUHT58uNn1f7EPfy7RhVw+69R43Z6kTE/0B3sQOsgIHbQRQYxOZGVl6W2CSyB0kPEkHUYwgPuZSPCX5Zjy6m3a6M4aHYppDIgiVcm0liAGICYmxupnxpkLPuYTodkmKipKmaY6depUiyUUGrgENABw8uRJ5f3evXtbbYsFT/IHRxA6yAgdtBFBjE7MmjVLbxNcAqGDjCfpcAuRvMV25m95Hq/j5TYFMdboUKwqLmlUrU2wJ4gJJohg83RSHp0026k3rjt27Fib/V64cEFJNu7evbvNeTGe5A+OIHSQETpoI4IYgUDgVCLMoxEADWG+Vq9MspYSVSJupGpqSR3ExMbGWtVXLJHKeT7ae7qol0qnp6db1feJEycAeRfhbt26WXWPQCCwDRHE6MQHH3ygtwkugdBBxpN0MKpGSjD62jQSY40OxapE3EhVwJSfn6+cWzsSE6cafcnHt8U2BoOBPn36AFBeXs7PP2svwn6BcfyLkbzH6CZTSrbmxXiSPziC0EFG6KCNCGJ0Yvjw4Xqb4BIIHWQ8SYcI1UiJd5RtQYw1OhRTqZxHqhJx1XvFWBvExJp32QXIo+XCkcnJyUqi8PHjx1vt71Z+Zg7fM4N0ZSQGoEePHlbZY8GT/MERhA4yQgdtRBCjE44Uh/MkhA4ynqRDhHmkpAZ/vIIMNk0nWaNDsapIY6QqYKqvr1eeZW0Qk0c5axjF1wzhuGqER41lFAbgp59+arW/AvPITjhllBeXUVEhV/NOTk62yh4LnuQPjiB0kBE6aCN27NWJllY3dESEDjKepIMR+Q/3Ba9wvAxeNo3EWKNDGWVcwoA3DUReFngUFBQQERFBcHAwQUFBVFW1HJhY2MNx9rTxPPXqIvXoSksUqPJqoonk7NmzDBw4kJCQEIxGIyUlJW08TcaT/MERhA4yQgdtxEiMTixbtkxvE1wCoYOMJ+kQgbyxXZm3XAjSlpEYa3SQgFWM51Um8TZNE3jtXWathcFgoHv37kDTFUdaFOLX+HzCOHfunPLaltEYT/IHRxA6yAgdtBFBjE6IbaRlhA4ynqKDD96EmkdiynzCqKqqwmTS3kDucqzV4fds5w9sYxVNizCqk3utXaHUGklJSfj7y3vRqBN1tShQfaTGEMzZs2eV17YEMZ7iD44idJAROmgjghidMBiE9CB0sOApOkSYywAAVPp2smkqCRzXIS8vTzmPi4tzqC+wbSoJoEC1WiqGALtHYjzFHxxF6CAjdNBGKKMTBw8e1NsEl0DoIOMpOgTgRwbJFHlFUR4YZvMeMY7qkJubq5zHx8e32f4EXckhhm8Z0uJ124OYxuXl0fhSVlamBHJJSUlt3m/BU/zBUYQOMkIHbUQQoxPWfCB2BIQOMp6iw8/kMiXRxMZVL5D9/DSbR2Js0cELiCAEXxp3wy0pKaG+Xg4krAliEiggngJiKG/ev5eXUryxrKysyVSVFgU0JmBaMnIsozEBAQFW5+l4ij84itBBRuigjQhidOK2227T2wSXQOgg40k6WKpXg21JvWC9Dn9mAvUYKKGCUTQuP5UkSQk2oqOjW93uP5RggsxBRz6hza536dJF2R/GmnwYgAJzPhBADJcAmmyOl5CQYFU/nuQPjiB0kBE6aCOCGIFA4FTUQYytIzHWUo0X3ub8E+Nl5QIsU0oGg4Ho6GjNPmIxKud5LZQcUO+ya+034VyK2MAYXmcSX5vfUxfvS0xMtKofgUBgHWKfGJ1Yt26d3ia4BEIHGU/SwZEgxlodSsyjHACRqmXN0DS5Nz4+vslrNbGEA/IoSUslB9T5MNaOxJRSxm3sbvKePUGMJ/mDIwgdZIQO2oiRGJ3o16+f3ia4BEIHGU/R4R7G8fstZSQ+8wX1P1bYHMRYq4O6knXkZR9j1q5QiiOo8Z4WSg5Y8mEqKyvJycmxyq6WKCoqorZW3lnY2iDGU/zBUYQOMkIHbUQQoxNDhrS8GqKjIXSQ8RQdhmBgWs0Obij+L15l9TbnxFirQzE1ynnkZQGItSuUYlUjOPk03csmISGB4GC5rpK1ozCtkZ2dLdsaGank2bSGp/iDowgdZIQO2oggRids2QDMkxE6yHiKDhGqaR5TqDeVlZWttG6OtTo0LQJ5qcm1/Px8GhrkfJnOnTtr9hGr+vjLUwVF0LReUkZGhlU2XU4QPkp4pZ5Ssia511P8wVGEDjJCB21EEKMTf/3rX/U2wSUQOsh4ig5G6pTzcl/b671Yq0Oxakl0pOqZAJcuXVKmlOLj4zVXKMWpgp/8y5ZY27o/jJq/M5YKgqjERFe6ALbnxXiKPziK0EFG6KCNCGJ04oknntDbBJdA6CDjKTpEqEY0LniV2Xy/tToU0VhIMZrmwZIlaPD29tbMi4lVVcDOo2nujiWIqaysVKaCrKUBb4LNhSljzFWt1X1Ys3+Np/iDowgdZIQO2oggRiesmRfvCAgdZDxFB6P5j3c5IVysumjz/dbqUEc9F80BQnQLG9VZM/LxHCXcwtU8zBgKKVbeT0hIIChITvq1Z5OxAlWOTgxyXo06T6e1KS4LnuIPjiJ0kBE6aGNXEDN//nwyMzOprq4mLS2NcePGtdp+woQJpKWlUV1dzenTp5k3b16zNrNmzSI9PZ2amhrS09O56aabbH7uzJkz+eKLLygsLESSJAYPHtysDz8/P1auXElhYSEVFRVs2rTJ6g2onEl6evoVf6YrInSQ8RQdIswBxUWvcJuTesE2HQrNdZqiab4CSh3EdOnSpcX7f+Q0G/mB19nNJdXUkjofxr4gprGvGOTikVVVVZSXy9pYU9PJU/zBUYQOMkIHbWwOYmbPns3y5ct58cUXSUlJYefOnWzevFnzgyI5OZnPP/+cnTt3kpKSwpIlS1i5ciWzZs1S2owaNYr169ezZs0aBg8ezJo1a9iwYQMjRoyw6bnBwcHs2rWLp556StP+5cuXM3PmTG6//XbGjRtHSEgI//vf/654gS1RC0NG6CDjKToYzQHFRZ9wuza6s0WH3xDJeIYwhqhm19S75Nq6wZzjQUxjjk7iUwp1AAAgAElEQVSM6iPWMhrTqVMnZaRHC0/xB0cROsgIHVpHsuXYu3ev9MYbbzR579ixY9KSJUtabP/yyy9Lx44da/LeqlWrpN27dyuv//3vf0uff/55kzabN2+W1q5da9dzu3btKkmSJA0ePLjJ+506dZJqa2ul2bNnK+/Fx8dLJpNJmjZtWrN+goKCpC1btkhBQUE2aWTN8cwzzzi9T3c8hA6eo0MgAZIEkgTSnsDR0rBhw3TV4ZVXXpFSU1Olv/3tbzbdt2zZMik1NVV69dVX7XruaAYqOixjgvL+HXfcIaWmpkqpqalS9+7dPd4fnHEIHdxbh/b8G2o5bBp+8PX1ZdiwYXz11VdN3v/qq68YM2ZMi/eMHj26Wfsvv/yS4cOH4+Pj02obS5/2PLclhg0bhp+fX5N+cnNzOXr0aKv9hISEEBoaqhx+fn6abQWCjkoEjTv1Vvp1sms6yZlYppRCQkIICwtrci2cTvyKUVzNIKJoLMqYmJjoUD4MQCGNuUAxqv1nbK2wLRAI2samsgNRUVH4+Pg0q+aan5+vOc8bFxfXYntfX1+ioqLIy8vTbGPp057natlSW1vbbJi7rX6ys7OVgAvg22+/5b333uOzzz5j/vz5gBxQ+fj4MHnyZABWrlzJzTffTEJCArm5uWzYsIFHHnkEgG3btpGens4zzzwDQGpqKtdddx3JyckUFRXx7rvvsnDhQgB27dpFSUkJN954IwBvv/02EyZMoFevXly8eJE33niDp59+GoB9+/aRlZWlTNV98MEHDB8+nP79+1NdXc2yZct4+umnMRgMHDx4kBMnTiiFxdatW0e/fv0YMmQIJpOJv/71rzzxxBMEBASQnp7OwYMHueuuuwDYuHEjXbt2Zfjw4QC8+OKLLFiwgNDQUDIyMti1axf33XcfAJs2bSI6OloJEl955RUeeOABjEYjmZmZfPPNN4oOmzdvJigoiIkTJwLw2muvMWfOHGJjY8nKymLTpk089NBDAGzZsgWAKVOmAPD6668zY8YMEhMTyc/PZ+3atTz22GMAbN++naqqKq6//noAVq9ezdSpU+nevTslJSW89dZbLFq0CIDdu3dTWFjIjBkzAHjnnXcYO3Ysffr0oby8nJUrVyr2pqWlce7cOW6++WYAPvzwQ1JSUhgwYAA1NTW8+uqrPPnkk/j4+HDo0CGOHz/OHXfcAcD69evp3bs3KSkpNDQ0sHHjRh5//HECAwM5duwYaWlp3H333QB8/PHHJCYmKtOrL730Eg8++CBhYWGcPHmSHTt2cP/99wPw6aefYjQaGTt2LABLly5l7ty5REVFcfbsWb744gt+97vfAfIXBX9/fyZNmgTAihUrmD17NvHx8WRnZ7Nx40YWLFig+LzJZGLatGkArFq1ihtuuIGkpCQKCwtZs2YN991zH//9Nh//ygpKkpO57/rxVFdX8+abb3LNNdfQs2dPSktLWb16tTLlu3fvXvLy8pQcuB07djBr1iz69etHZWUly5cvZ/HixXh5ebF//34yMzO59dZbAVi7di2DBg1i0KBB1NXVsXTpUhYuXIifnx9HjhyhpqaGoUOHAnDNNddQU1PDsGHDkCSJnUs+5VP2yv/HYTN4NiSNe++9l+7duxMSEkJQUJDyGfXyyy8zb948IiIiOHXqFFu3buU3v/kNAJ999hmdOnVi/PjxACxbtoypM38Ja1cDEOtVyzOLZX85ceIEsbGxJCQk0KlTJw4fPqz5GXHixAmGDx/Otdde26E/I8rKyoiKilLyKDvqZ4QlsHa3z4iWclvbA6uHbeLj4yVJkqRRo0Y1eX/x4sXS8ePHW7wnIyNDeuqpp5q8N2bMGEmSJCk2NlYCpNraWun2229v0mbOnDlSdXW1Xc/Vmk664447pJqammbtv/rqK2nVqlWaQ2ExMTFSaGiocvj5+Tk8BHbttdfqPtTnCofQwbN0ePLJJ5UpE29v73bVIZ5o6VcMle5jtNSP5GbXBw0apNhy8803N7l2CyOVKZ+FTFTenz9/vnJPQkKC3TrU4CdJIB2kj/JeWFiY0vfvf//7DuEPjh5CB/fWweWmk4qKijCZTM1GLWJiYpqNkliwjLRc3r6+vp7i4uJW21j6tOe5Wrb4+/s3KVBnTT8VFRWUl5crR11dnWZba7F8Q+noCB1kPEUHy+9WeXk5ly5daqN1c2zRYQq9+JQDvM0efkHzhQWZmZnKeY8ePZpca6nkgMFgcGh/GDUFRAIQo1o5dfHiRWpq5H102hpB9hR/cBShg4zQQRubgpj6+nr279/P1KlTm7w/depUdu/e3eI9e/bsadZ+2rRppKWlKVspa7Wx9GnPc1ti//791NXVNeknLi6OgQMH2tSPQCBojpeXl5J7Ys/KJFspVG2sF93CR1llZaXy5SQpKanJzr1xqr1cLCUHevToQWBgIADHjh1zyLbfkcQ0RnC9OZixYMmLiYyMFLl1AoGTsGnoZvbs2VJtba00d+5cqW/fvtKyZcuk8vJyKSkpSQKkJUuWSO+//77SPjk5WaqoqJBeffVVqW/fvtLcuXOl2tpaadasWUqb0aNHS/X19dKiRYukPn36SIsWLZLq6uqkESNGWP1cQIqIiJAGDx4sXX/99ZIkSdLs2bOlwYMHK9NWgPTGG29I58+flyZPniwNGTJE2rJli3Tw4EHJYDDoMhQmDnF4yhEZEi29vlKeLnnwwQfb/XnD6KNMCb3B+Bbb3HPPPcoUTrdu3ZT332Sccu9gekuANGvWLKXtyJEj28Xmu+++W3mG+rNLHOLwxOMK/Q21/ab58+dLZ86ckWpqaqS0tDRp/PjGD5B3331X2rp1a5P2EyZMkPbv3y/V1NRImZmZ0rx585r1efPNN0vHjx+XamtrpWPHjkkzZ8606bkgf2C1xHPPPae08ff3l1auXCkVFRVJlZWV0ieffCIlJiZe8f+ABQsW6O5grnAIHTxHh1f8pkkSSBfoJD067L5216EL8Uog8h9aDjrGjRunBA1Tp05V3v+MYcq9UURKgPTcc89Jqamp0qpVq6SQkJB20Wjq1KmKPeovaZ7oD844hA7urcOVCGJsWp1kYdWqVaxatarFa3Pnzm323o4dOxg2bFirfW7cuJGNGzfa/VyA999/n/fff7/VPmpra1mwYIGSUa0XoaGhuj7fVRA6yHiCDkbzDE0YZZTV21a92oItOhS2UT8J4NSpU8p5v379+PrrrwHobN5ZuA5fiinGaDQqy57PnDlDRUWFzbZbg6UwJbS+zNoT/MEZCB1khA7aiNpJOpGRkaG3CS6B0EHGE3SIoF45LzDZlxNjiw411FJhrk0UTctBR15eHiUlcrDTu3dv/P3lMgCdzbWScolBgiZfso4cOWKP6U2IIYIpDGQOV9NLlXRs7V4xnuAPzkDoICN00EYEMTqxa9cuvU1wCYQOMp6gQ7jUmGibV1tkVx+26lBIBNBy/SQLhw8fBsDHx4d+/frhgzcx5iAmx3y/usTJ/v37bbKhJa6nH19zlH/xA1PoprxfXFxMfb0c7LUWxHiCPzgDoYOM0EEbEcTohGWjp46O0EHGE3QIb5CnkBrwIrsix64+bNWh0FzJ2kgpBtWKIzXqkZVBgwYRSThF5uAlh2Di4+OVGmxnz56loKDAHtObUECtch6jskuSJGXFVHR0dJMVU2o8wR+cgdBBRuigjQhiBAKBUwhrkPNMLhDOhbL2X2INUIi8k6kBiajLljNbyMjIUPZ2uuqqqyjyvkA0pQTgzQMcY9SoUUrbvXv3OsWuAtX0VjRSk2uWKSWDwUBMTAwCgcB+RBCjE5s2bdLbBJdA6CDjCTqENZQBcNEQRnV1y4m2bWGrDrkEcIEwjtOdEFquDG0ymZTRmNDQUGXjsFouURtoUkoGNDQ0kJaWZpfdl1PQpH5S080x1XkxWpveeYI/OAOhg4zQQRsRxOhEdHS03ia4BEIHGXfXwQuIQC74WObdye5+bNVhHruJ4CL9ySST85rtvvnmG+XcUksHYPLkyUpdmr179zptVZJ65VTMZSun1CuUtIIYd/cHZyF0kBE6aCOCGJ2wpfq2JyN0kHF3HSJ9o/CmAYCL3iF292OrDg3mZ7ZFZmYmZ8+eBaBLly6MHDmS2NhYZffuhoYGPvvsM5ue3Ro11FGGvCw2xryc24K6xIlWEOPu/uAshA4yQgdtRBAjEAgcJimks3JeZmh5WkdvvvzySwD83jjOM5mJLAu+EZ9yeausPXv2KLXcnEWBOXk4xjxCZSE/Px9JkvNkYmNjnfpMgaCj4QWXZZ0JFIKCgvjkk0+YPn06VVVVTu3b19dXWWrZkRE6yLi7DgN7DmT+yDkYLtTyY84pUg/+y65+2luHOXPmMH9TNuMqtwPw+vN/J7c2j2XLltmdx6PFLgYyhqMA+OKDyVxoEuDFF18kMjKSmpoaHn300Wb3urs/OAuhg4y76tCef0MtiJEYnXjggQf0NsElEDrIuLsOodGheI834nVjPD+F2V/92VYdQglmNWP5hOG8zIQ2269bt46IGnk6pwZ/MgpOsGLFCqcHMACFBCrnURibXLPkxQQEBLS4G6u7+4OzEDrICB20savsgMBxjEZj2406AEIHGXfXISIiQjm37JBrD7bqUEstv0XeCCySgW22lySJuEtyEJNDDH//x99tN9JKCvCnmgDyiSIUX/JU1/Lz8xkwYAAg58WUlzfNm3F3f3AWQgcZoYM2YiRGJzIzM/U2wSUQOsi4uw7qD1lHghhbdajDRLE59yS+lV17LQTiT6Q5RyWHcNsNtIEH2UcQNXQji5OcaXKtreRed/cHZyF0kBE6aCOCGJ2wFKLr6AgdZNxdh8TCSBo+yqZ+Swl1RXVt36CBPTrkmqdq4ilss20XGgOGc7RvUT0T2jqol1m3lNzr7v7gLIQOMkIHbUQQoxPz5s3T2wSXQOgg4+46XPVjPvO/+QsP/2cxPWvs34XWHh1yzaUHAqglnNb3qEmicdrrPL42P8tZtLVXjLv7g7MQOsgIHbQRQYxAIHCYsPrGlQfFGhWl24tcVQJtPFGttk2icQ+b81buMdMeXLx4kdpaub6S1l4xAoGgbUQQoxObN2/W2wSXQOgg4846BAUFEVJbprwuUm25byv26JCrWp8Q3+ZITGPBxfM4f0WSmigi+DtjWM8I/sD4ZtcteTGRkZHNCkG6sz84E6GDjNBBGxHE6IRlq/OOjtBBxp11MBqNdKqTA5cGvCi1IsFWC3t0yFVtdRWvUT/JQpJqr5bzDthpDQa8eZjdzGYf41VVrS1YppS8vLyaFYJ0Z39wJkIHGaGDNiKI0YmJEyfqbYJLIHSQcWcdjEYjYSZ5xU8p4TQ4sH+mPTrk0rgJWHwbeS5bucQ7jGELQzhPfqttHaW4Sf2kymbXW1uh5M7+4EyEDjJCB23EPjECgcAhjEYjEQ3nACj2igCptI07nEuWqjZRlzYCqDXsZU17G2TmEg0UYSSKEmIoa3a9rRVKAoGgbUQQoxOvvfaa3ia4BEIHGXfWIbJTJOHmPJgS7C/+CPbpcIo81jKGs/ix47Jii3pTQLg5iGm+d05rIzHu7A/OROggI3TQRkwn6cScOXP0NsElEDrIuLMOMd6NK4KKVCuF7MEeHQoo5k528wzb+JL9Dj3f2RSY96IJoZLAy7RRBzGXj8S4sz84E6GDjNBBGxHE6IQYPpYROsi4sw6RqhVBhZJje6+0pw5++OPfRuKvsykkQDmPJrLJtfr6emV348tHYtzZH5yJ0EFG6KCNCGJ0IisrS28TXAKhg4w769DJJ5ACr2hMeFPk4EdKe+ownRRqqCKPaO5pYclze1CAn3Ie08Lyb8toTGBgYJNCkO7sD85E6CAjdNBGBDE6sWnTJr1NcAmEDjLuqoO3tzehk+P5f6v+wv8t+gPP8J1D/TmigzdeJBFLiMZoSw/8AYilkGrVUuv2pAAv5TyG4GbXtZJ73dUfnI3QQUbooI0IYnTioYce0tsEl0DoIOOuOoSHh+PlJf+hLr1QSr2Du+Daq8PDjKMGA+fIZyqDWmzTRxW4nKDYrufYSoFKjxhzEKVGq/yAu/qDsxE6yAgdtBGrkwQCgd04q3q1o5RwCR8uAZCsykNR01u1zPkkV2Z4Pp0y1jGWQnzJoPnS87aqWQsEgtYRQYxObNmyRW8TXAKhg4y76uDsIMZeHc6qApRkjb1i+pANQBZxVJLXYhtns5PD7GzlutZ0krv6g7MROsgIHbQRQYxAILAbo9GI/+tHicn5mVsr/TlIuENlB+zlDIXKeTI1za4bCSPKvFfLCeLgCgUxbXHhwgVqa2vx9/cXK1AEAjsQOTE6MWXKFL1NcAmEDjLuqoPRaKTHmaP8sngTv6vZjEGVyGoP9uqQRwG15pVAyS1M2/QmQTnPILTZdT0pKCgAIDo6WikE6a7+4GyEDjJCB21EECMQCOzGaDQSWiePvDha/NERJOAsnQHoSVazYKo3Ecr5CQcDLXsJ1hj4VheCjI6OvpImCQRujwhidOL111/X2wSXQOgg4646GI1GIkzyNE0xRoeKP4JjOhxBno4JopoedG1yrQ/eynkGVXY/wx720Zca/PiJqBavt7RCyV39wdkIHWSEDtqIIEYnZsyYobcJLoHQQcZddTAajUQ1FAFynSBHcUSHw6olzFfRdKVPb2qV8xMU2P0Me/ClAX/qiNFY1t1S+QF39QdnI3SQETpoI4IYnUhMTNTbBJdA6CDjjjoEBgbiU+tDsHlko8AJuSaO6HCYauX8qsv2ZLmXQwylJ7czgrNXaHm1hQJzUUw/6gknrNn1lkZi3NEf2gOhg4zQQRuxOkkn1N++OjJCBxl31MFoNNKQV6e8LtDYn8UWHNHhR3KU8x6X7chbSS0HOcVBu3u3nzyVLvFEccFc8duCJbEXGkdi3NEf2gOhg4zQQRsxEqMTa9eu1dsEl0DoIOOOOkRFReFV2DhNk6+qE2Qvjuhwjmyu5Wriiecudjlsi7PIUX1X7NxC/aS6ujpKS+UVVZaRGHf0h/ZA6CAjdNBGBDE68dhjj+ltgksgdJBxRx2ioqIwFDdO4RQ4YdWPIzpIwFf8QB65DtvhTHJUyc6dNeo6WaaUgoKCCAkJcUt/aA+EDjJCB21EECMQCOwiKioK35JK5XWBedt/V+N5JvF/XMMvGK7L4uocVVJxZ40ZfFF+QCCwD5EToxPbt2/X2wSXQOgg4446REdHU0cEn5y7lUt55/lJutj2TW3gbB28gAUcIIwycokx7yRzZcmmQjnvrLEE/fLyA+7oD+2B0EFG6KCNGInRiaqqK7tXhasidJBxRx0iIyPxviaS84snMEv6np0ccbhPZ+hwDYNYzVj20J/h9CPMXFdpD90c7tseclQ7CHemrsU2lwcx7ugP7YHQQUbooI0IYnTi+uuv19sEl0DoIOOOOkRFyZu3FRUVOa1PZ+jwDN78ll2M4hhrVMuuv8DX4b7tIU9V16mzalRGzeXTSe7oD+2B0EFG6KCNmE4SCAQ206lTJ3x95aDAmUGMM9hACL8wn/fhLAD5RLGGH3Sxpw4TsxlPITWcp+VK36WlpdTX1+Pr60tcXBy1tbUtthMIBE0RIzE6sXr1ar1NcAmEDjLupoNlFMZUJVFY6Lwgxhk6fMwx6i/7fraCAdSgX2DwETvZxg9kclqzjWVKKSoqirfeeutKmebSuNvvRXshdNBGBDE6MXXqVL1NcAmEDjLupoMliLnlied4a8NnbGewU/p1hg5FlHA/IzhvTuPNpAurdNnmzjYsU0oGg4GZM2fqbI1r4G6/F+2F0EEbMZ2kE927d9fbBJdA6CDjbjpERUXRYGogSirCmwYCNRJWbcVZOqxhN//Ci370IIciLpiTe10ZdXLvgAEDdLTEdXC334v2QuigjQhidKKkpOW58Y6G0EHG3XSIiopCKr6ENw0AFBDslH6dqUMDEumtTN9cSWIxMpgEOhPETnI4zc/N2qiTeyXJsWrgnoK7/V60F0IHbcR0kk6IOW8ZoYOMu+kQGxtLQ25jjknBZQUX7cXddLCWm+jPlxzhXb5nIl1bbKMeiTl06NCVMs2l8VR/sBWhgzYiiNGJRYsW6W2CSyB0kHE3HWJiYjAU1CivC5w0qOtuOlhLDo1aJeDdYhv1SMzs2bPb3SZ3wFP9wVaEDtqIIEYgENiEv78/oaGh+BQ17nmSo7ETrUDmZ1Xl6i7mKbjLqaur48KFCwCEhIRcEbsEAndHBDE6sXv3br1NcAmEDjLupENMTAwAAcXlyns5TkrsdScdbOE8Bcp5Etq7r1qmlEpKSggOdk6ekTvjqf5gK0IHbUQQoxOFhYVtN+oACB1k3EkHSxATVNY4upBLpVZzm3AnHWyhhItUmitYJ6nKEFyOJYipqakhNjb2itjmyniqP9iK0EEbu4KY+fPnk5mZSXV1NWlpaYwbN67V9hMmTCAtLY3q6mpOnz7NvHnzmrWZNWsW6enp1NTUkJ6ezk033WTXc5977jmys7Opqqpi69at9O/fv8n1rVu3IklSk2PdunU2KuA4M2bMuOLPdEWEDjLupIMliOlU0bhiIocLTunbnXSwlfPI1amTyNNsY8mLSU5OJj4+/orY5cp4sj/YgtBBG5uDmNmzZ7N8+XJefPFFUlJS2LlzJ5s3b6ZLly4ttk9OTubzzz9n586dpKSksGTJElauXMmsWbOUNqNGjWL9+vWsWbOGwYMHs2bNGjZs2MCIESNseu6iRYt4/PHHefjhh7n66qvJy8vj66+/bja//M9//pO4uDjlaCmoEggELWMZIYioLlbey0V8U2yL84QDEEwVRiJabJOTk6Ocd+6sR81tgcD9kGw59u7dK73xxhtN3jt27Ji0ZMmSFtu//PLL0rFjx5q8t2rVKmn37t3K63//+9/S559/3qTN5s2bpbVr19r03JycHGnRokXKaz8/P6m0tFT67W9/q7y3detW6bXXXrPqZw0KCpK2bNkiBQUF2aSRNUd8fLzT+3THQ+jgfjosXLhQSk1NlV5/+G/SDYbh0q8Z1SF1sPX4J+MkCSQJpCH0abFNSEiIlJqaKn3wwQfSY489prvNeh+e7A8dQYf2/BtqOWwaifH19WXYsGF89dVXTd7/6quvGDNmTIv3jB49uln7L7/8kuHDh+Pj49NqG0uf1jy3W7duxMfHN2lTV1fH9u3bm9l25513UlhYyNGjR1m6dGmbKwFCQkIIDQ1VDj8/v1bbW8PYsWMd7sMTEDrIuJMOlumk8kQTnzWksYa9TuvbnXSwlfOqpdVJhLXYpqKigrKyMuLi4khISLhSprksnuwPtiB00MamzR2ioqLw8fFpsp8ByPO4cXFxLd4TFxfXYntfX1+ioqLIy8vTbGPp05rnWv5tqU3Xrl2V1//61784c+YMeXl5DBw4kJdeeonBgwczbdo0zZ87OztbCbgAvv32W9577z0+++wz5s+fD8gBlY+PD5MnTwZg5cqV3HzzzSQkJJCbm8uGDRt45JFHANi2bRsjR46kT58+AKSmpnLdddeRnJxMUVER7777LgsXLgRg165dlJSUcOONNwLw9ttvM2HCBHr16sXFixd54403ePrppwHYt28fWVlZylTdBx98wPDhw+nfvz/V1dUsW7aMp59+GoPBwMGDBzlx4gS33XYbAOvWraNfv34MGTIEk8nEX//6V5544gkCAgJIT0/n4MGD3HXXXQBs3LiRrl27Mnz4cABefPFFFixYQGhoKBkZGezatYv77rsPgE2bNhEdHa0Ekq+88goPPPAARqORzMxM+vbtq+iwefNmgoKCmDhxIgCvvfYac+bMITY2lqysLDZt2sRDDz0EwJYtWwCYMmUKAK+//jozZswgMTGR/Px81q5dy2OPPQbA9u3bqaqqUsrZr169mqlTp9K9e3dKSkp46623lH0Ydu/eTWFhoTIH/c477zB27Fj69OlDeXk5K1eu5JlnngEgLS2Nc+fOcfPNNwPw4YcfkpKSwoABA6ipqeHVV1/lySefxMfHh0OHDnH8+HHuuOMOANavX0/v3r1JSUmhoaEBg8HA448/TmBgIMeOHSMtLY27774bgI8//pjExERlevWll17iwQcfJCwsjJMnT7Jjxw7uv/9+AD799FOMRqPyobd06VLmzp1LVFQUZ8+e5YsvvuB3v/sdIH9R8Pf3Z9KkSQCsWLGC2bNnEx8fT3Z2Nhs3bmTBggWKz5tMJm644QYmTpxIeno6Xbp04ZlnnqGwsJA1a9bw+OOPA7Bz507Kysq44YYbAHjzzTe55ppr6NmzJ6WlpaxevZqnnnoKgL1795KXl6fkwAUEBNDQ0EC/fv2orKxk+fLlLF68GC8vL/bv309mZia33norAGvXrmXQoEEMGjSIuro6li5dysKFC/Hz8+PIkSMcOXKEOXPmAPDRRx/RvXt3hg0bhiRJLFmyhEcffZTg4GCOHz/O999/z7333gvAf//7X+Li4hg1ahQAL7/8MvPmzSMiIoJTp06xdetWfvOb3wDw2Wef0alTJ8aPHw/AsmXL+PWvf010dDTnz59v8hlRvTqdqqJAsgwJjLl6LFuPHW/xM6J///7ExsbSrVs3nn/+eWprazvsZ0RCQgLbtm1Tpvw76mdEr169+M9//uMWnxGWv6WrVq1qMbe1PbBpSEuSJGnUqKbDx4sXL5aOHz/e4j0ZGRnSU0891eS9MWPGSJIkSbGxsRIg1dbWSrfffnuTNnPmzJGqq6utfu7o0aMlSZKkuLi4Jm3++c9/Sps3b9b8mYYOHSpJkiSlpKRoDoXFxMRIoaGhyuHn5+fwENiCBQt0H+pzhUPo4F46dOvWTUpNTZVSU1OlOXPmdFgd7DkMeEvg1Wa7W265Rfruu++k1NRUqW/fvrrbrefhyf7QEXRwuemkoqIiTCZTs1GXmJiYZiMgFiwjLZe3r6+vp7i4uNU2lj6tea5laTwGLsAAACAASURBVKIttgEcOHCAuro6evXqpdmmoqKC8vJy5airc3xPjJUrVzrchycgdJBxFx0sK2bqTtbQeZuJiaQQTbTT+ncXHeyhgUvIn7utk52dzdGjRwFITExsZ6tcG0/2B1sQOmhjUxBTX1/P/v37m5UFnzp1quZmPHv27GnWftq0aaSlpWEymVptY+nTmueeOXOG3NzcJm18fX2ZOHFiqxsFDRgwAD8/P3Jzc1v70Z2OZbixoyN0kHEXHSxfEvx/yGdpzga2cZA76Oe0/t1Fh/YkOzuboUOHAnT4vBjhDzJCB21sLniybNky1qxZQ1paGnv27OG3v/0tSUlJpKamArBkyRISEhK45557ADnf4+GHH+bVV1/lzTffZPTo0dx///3KvB/I82w7duxg0aJFbNq0iRkzZjBlypQm+8C09VxAmT8/efIkJ0+eZPHixVRVVbF27VpALmd+55138vnnn1NUVET//v159dVXOXDgALt27bJPQYGgA2EZiQkoKVPey3XSbr0CmZycHKWKdUcPYgQCa7B5Dmr+/PnSmTNnpJqaGiktLU0aP368cu3dd9+Vtm7d2qT9hAkTpP3790s1NTVSZmamNG/evGZ93nzzzdLx48el2tpa6dixY9LMmTNteq7leO6556ScnBypurpa2rZtmzRgwADlWmJiorRt2zapqKhIqqmpkU6ePCktX75cioiIuOLzeddee63u85WucAgd3EuHF154QUpNTZU2JN6pLBcey6AOp4O9x4OMkT5muHSInlIAAZrtPvzwQyk1NVX6xz/+IXl5tZ1H46mHp/uDp+twJXJi0PuHdOWjPf8DOnrCntDB/XTw8fGRVq1aJaWmpkqfh05TgphuJHYoHRw5PmCMolt/emi2e/bZZ5UEassCiI54eLo/eLoOLpfYK3AeliV3HR2hg4w76BAbG4uXlxcAUdVyQcMGvMhGO3HeVtxBB0c4rZrB70GkZruePXsq5x15SsnT/cFahA7aiCBG0O50IY5XmMBBerONq/g94/HHV2+zBDairuWTYJIT4fOIoY56vUxyO06ptOpJoGa7srLGnKOOHMQIBG0hghid+PDDD/U24YowhN4coI6F7GAIJ5jIYVayk830J4SgDqNDW7iDDpZaPpeqLtHZPPpyniinPsMddHCE0zRW/u6BpNnu7bffVs478jJrT/cHaxE6aCOCGJ1ISUnR24R2pxdJfEs+UcjVjhvwUq5dw498Rk+GDh6ql3kuhTv4g+WPacPPjauRzhPq1Ge4gw6OcFpVwbonlZrtunbtSm1tLdCxR2I83R+sReigjQhidGLAgAF6m9CueAFvEU6E+ZvndwwiDiPjGESJuZrvBA4z6XTL5So6Gu7gD5Yg5tKZxtGEczheR0yNO+jgCIWUUGYO/Hq0Uvl7wIAByt5VUVFRTqnX5o54uj9Yi9BBGxHE6ERNTY3eJrQr/vjzE50AOE0S15FJIcXs4gjT6UItfrzANZybGKSzpa6Bq/tDYGAgRqMRgIqiUs6QSD0+nG9lSsQeXF0HZ3AaeVoumWx8VEUh1dTU1JCVlaW87qijMR3BH6xB6NA6ui/DctXjCq1x9+hjIoOlcS3sIxJHx1026o5Hz549lSW/d9xxhwRIBpD88NHdNnc7NjBSWWbdnSTNdhMnTlQ0nzRpku52i0Mcth5iibUH8+STT+ptwhVhOz/yHUeavZ9nTgztKDq0havroE4utYwQNAB1mJz6HFfXwRmcxl8576lRd+rJJ5/k3LlzyuukpKR2t8sV6Qj+YA1CB21sLjsgcA4+PkJ6EDpYcHUdWgpi2gNX18EZbKOSYCaRDqRzosU2Pj4+ZGVl0dDQgMFgoGvXrlfWSBehI/iDNQgdtBHK6MShQ4f0NqFdmMRgjATwCWmYuNRm+8xvf+IFxjOHMwyjnFLVEtSOhKv7gyWIkSSJ7OzsdnuOq+vgDL5kP1+20ebQoUOYTCZycnJITEykc+fO+Pr6Ul/fsfbk6Qj+YA1CB23EdJJOHD9+XG8T2oU/ARv5nvNE0oX4tpozdn8Zz7CTbmRxD1e1u32uiiv7g7e3txLEFOQX8GVdf9YxhseY5PRnubIOVxKLDpYpJS8vrw65X4zwBxmhgzYiiNEJdRVvT6Ef3ZnIjwCUEsLP5LZ5T8FNw5Tz3/Fzu9nm6riyP3Tu3FkZzs45lMUkDnE7u5lGudOf5co6XEksOpw/f155ryNOKQl/kBE6aCOCGIHT+A2N3xRXY923xku9vNnKEAD6cJYJHXg0xlVJTk5WzuuPlSrnpxDL4x0hhk5MZgBhrWwYePbsWeVc/f8gEAhkRBCjE+vXr9fbBKdiwIvbyACgFj/WmEdk2mL9+vW8qaohc6d5b5mOhiv7g/qPZ1Bu4y6zJ1U7MDsLV9bBmTzHePIp4xvSGU2fZtctOmRlZWEyySvAunXrdkVtdAU6ij+0hdBBGxHE6ETv3r31NsGpTGCQUk9nM0OaJOh6e3vTrVs3RowYQUpKCnFxjbv09u7dm00cooJgAG7hKH4dMN/clf3B8sezoaGB+PJq5f2TrWybby+urIMzOa1amj7Q7PtqLDpcunSJn3+Wp1ljY2MJCupYo18dxR/aQuigjQhidMLTamHcTphy/m/zLqT+/v7MnDmTV155hSeffJL77ruPefPm8ac//Yk//vGPjBw5kpSUFKqo5r8MBsDIBa41Ty91JFzVH/z8/JTq1dnZ2fSkcefQUxQ5/XmuqoOzOarSbmALe+2odcjMzFTOO9poTEfxh7YQOmgjghidaGho0NsEp+GDN7dwFIBKgviUQ/Tq1Ys//elPXHvttQQHN/+mmZCQwNy5cxk1ahShoaGspVa5NgffK2a7q+Cq/tC1a1e8vORpo7Nnz9ITOSfGhDdncf5+Ma6qg7P5iXOYzMF+CgXNrqt1UAcxPXr0aH/jXIiO4g9tIXTQxgt5615BCwQFBfHJJ58wffp0qqqq9DbHZbmeYXzOfgDWMZrlIy5xzz334O0tf0ibTCYOHTrE2bNn8fPzY8CAAU0+jIuKinh9+escLqolihKqCCQWAxXtMF0hsI3rr7+eGTNmAPDeu+/x1fdHCaWC03ShZwdeTeYM0ujLMH6iAS/CCaacihbbRURE8NJLLwHyUtsVK1ZcSTMFAru5En9DxUiMTjz++ON6m+A0bldto74tPob77rtPCWB++uknnn32Wd566y22bNnC559/ztKlS/n73//OhQsXuOqqq4iKiuLRhY+y0SCvTKrDj4F0rGFzV/UH9Vx8yU/FhJr/0J4kpl2e56o6tAd7zSUHDEhcTc8m19Q6lJaWcuHCBUCeTrKMjHUEOpI/tIbQQRsRxOhEYGBg243chGUU8QoTOezVh6v+MEV5f8eOHaxYsYKSkpJm96Snp/PSSy9RWSmPtoSFhVF02wRm+0wgjhr2mqenOgqu6A8Gg0EZMSstLSX6YoBy7WQLyajOwBV1aC/2qna0HqXKKYPmOlimlAICAjrUpncdyR9aQ+igjQhidOLYsWN6m+A0fuQEr0Qe5ZtX5+ETLOez7Nixg7Vr1yJJ2rOVFy9e5O233yY3V94UL2piZxIeHkqdV90VsduVcEV/6Nq1K35+fgCcPHmScxTwGON4g3F8Q3Ubd9uHK+rQXuxV5RSNoulQ++U6nDjRWGOpI61U6Uj+0BpCB21EEKMTaWlpepvgNHx8fJg/f76y/PPHH39k3bp1Vt27a9cuVqxYQVlZGQB9+/Zl+vTp7Warq+KK/tCrVy/l/MSJE2SRz3K+4yG+YxM/tMszXVGH9uIU5ykmAoBRZDa5drkOGRkZynlHCmI6kj+0htBBGxHE6MTdd9+ttwlO46abblKGuPPz83nnnXdaHYFRc/fdd3PhwgVWr16tZOBfd911dO/enUBVro2n44r+0KdP4yZsJ0+evCLPdEUd2pO99KAOX34kmVDVzr2X65Cbm6tMvaqDS0+no/mDFkIHbUQQI7CbaxnKs8G/ZGKP8YC8Cmn16tXU1ta2cWdzTp8+zSeffCK/+KqA1YXdKcJAAnGt3yhoF/z8/JQgprS0lPz8fJ0t8kwepYQoQpjKfsrbqEVlmVIKCgoiISHhSpgnELg8IojRiY8//lhvExxmAQb+XPk5D//1EUz7y/j444/JycmxqQ+1Dl9++SWZmZmEHstmSvkWgqjmNjrG0Lmr+UOfPn2Uoo9HjhwhmCDGM4Rw8/RHe+FqOrQ3p8iknNJm77ekgzovpm/fvk2uXUUSM0hhOkOII9z5hupER/MHLYQO2oggRifcfYVBJBFM5RAAWV6JnAnJ59tvv7W5H7UOkiTx7rvvUji5cQ+ZOV7FjhvrBriaPwwaNEg5P3LkCMPpxQ4OUUopLzCp3Z7rajroRUs6/PTTT8p5//79AbiHqzlGMj9ynv9ykE0cIpcL/B8Trpit7YnwBxmhgzYiiNGJESNG6G2CQ/w6cAS+5u3Sdyddw4drP7Srn8t1KCws5L/HPueIr7xnzDApnX4+nr9Lqav5gyWIMZlMZGRkcJVqCfBZ6tvtua6mw5XEAIQTArSsQ25uLqWl8qhNr/BkvmAI7/ED/TjbpF09PmzAthFRV6Uj+4MaoYM2IogR2IyXlxezGy4or7+MqHdqzsT27dvZmThMef27CFE35ErStWtXIiLkaaOMjAzq6uq4isZtzw+3MP0hsJ8oInifUeQTwYf0bbVteno6DZmV/HLJG1xrHgkF2E4Kz/ALXuYa/sxETnCqvc0WCFwGSRwtH0FBQdKWLVukoKAgp/dtMBh0//nsPaYP/5V0CS9JAumkobtk8LL/Z9HS4arwAZIEkgTScZ++UpcuXXT/udvzcCV/uPXWW6XU1FQpNTVVGjt2rARIe+kvSSBdwksKxvm/D66ow5U6vDFIZ0lQ/L03XTV1mN7tGinHK15pm0OMdB2j23zGAJJ1/zmFP3Q8Hdrzb6iiDQJdePDBB/U2wS6MRiMzq7pgQALgY99eNEj2FyfT0uHwhXT2essjMH1NPzF3+B0evd26q/iDl5cXV199NSBPJR04cAB/fBli/mZ/iq5U0n51xFxFhyvJJRr4u6rswCN00dTB7+d6YqU8AE4YejGKAL5gj2bfBuB1RnOQLEa0McrjinREf2gJoYM2IojRibCwsLYbuSB33H4Ho080JvD+s/a4Q/21psOHlxr3zej3YxGTJ0926FmujKv4Q58+fejUqRMgJ/RWV1czlD74I++ivJv2XdrrKjpcad7mIBXmUg4P8D3R51veZv4/pu9Y3vu3HPQdypf/9yj18a3nJ93PGB5kD76Y+DcVhNHJ6ba3J67qD/740p/uDKYnndqpBIcaV9XBFRBBjE5cqc3DnMmwYcPoV9WFPiZ599DvuIrTnHeoz9Z0+IhjXDK76Miz3zL9xukYjUaHnuequIo/TJjQuKpl3759AIylUfNdtO9omKvocKW5QBkrGA6AH/X8+tP1DKArCYQTS2STtp92zmDP0gfw6+zN0KFDW+33Xb5nNwMB6EYWKxjUantXw9X84Wr6soGRlCORTiaHOMVFKtlCCjea///aA1fTwZUQQYxO7NixQ28TbCIwMJDbbruN+K8PK++954Rvda3pUEAR3zAEgCpDCN7FXtx5550OP9MVcQV/MBqNpKTIU3hlZWUcPiz/X4+hRmmzu51XvbiCDnrxJ3axlwEAdJPOc5RzZHGB5+nXpN2hQ4fwDpA/ui3/X1qYuMTtFFNqXl12D7uYxrBW73ElXM0fHiSMW/leWZlp4Rcc5BPS+H+MIArnf9FyNR1cCRHE6MT999+vtwk2MXPmTDp16kTew2NY2ud+tpDCR/zocL9t6fAU1Qz26cv/XrgLnwQ/BgwYwPDh7feNRy9cwR+uueYaJe9o27ZtXLokV1key2kASgnj+GU1fpyNK+igFyZM3MZFTtG1yfv38j1diFVeX7hwgTNnzgDy/iHR0dGt9vszufxBNQLzT/IIvgJTIM7A1fzhUY6QTSz5RPEvxvAO4zip+v+6iX3sJZhel/0fOoqr6eBKiCBG0Cbdu3dXphlMQZd4qeBjpnKQsja2SXcGBznOYdNPTQpK3nbbbUqxSYFzCA0Nbfw/NpmUb34RdOJnojDhzR56mdO5Be3FebIYRAGp3e5nO0P4lqG8xniqaZo8f+DAAeV81KhRbfb7Dt/xDfKoTVeyedGNRmNciYtUMQFvkrjIXezmfr6jD+eYzWgKzNN+PfiZl+mss6UdBxHE6MSnn36qtwlW4e3tzV133aW83rRpk7LhljOwVocff/yRgwcPAvIf3FtuucVpNrgCevvDjTfeiL+/XHDzu+++o6KiAoBSyhhOBuH4Mp+sdrdDbx1cgRqqWRX6A5M4xC84wFN8SxGFTdrs27dPKbI6evRoq/r9LYVUIScM/56djDLnyrgyevpDMIGkMgEjUU3ezySHOtWGjxLwEXsYii+H6cXXDOfXHHWqLeL3QhsRxOiEuySoTp06lc6d5W8V586dY+vWrU7t3xYd1q1dR812+cN8zJgxTaosuzt6+kNiYiLjx8tFPGtqavjf//7XrE0lNZwnr91tcZffi/amLR0uXrxIenq60taa34VMsnjWnHxqQOJNavDF13Fj2xE9/eE9rmIeO9hOBHHmkRWDwUBCQgLDhg1j4sSJTJo0iREjRpCcnEyBbzHjyedG0qly8ii1+L3QxkdvAzoqY8eOZdu2bXqb0SoJCQn86le/AiB42QEGn/6J4VI/fuCY055hrQ43cTV/KS9h4Lo/8g//v+I7Kow777yT559/HpPJ1Ob9ro5e/uDn58dvfvMbJRfmiy++UEZh9MAdfi+uBNbosGfPHgYOlEdTxo0bR0ZGRpv9Luc7bqcvw/mJSgKIIopccp1hcruglz88zURuYTsAXcjn6uSRdL72Rvr160dAQECL95hMJk6dOsUPP/xAWtr/b++8w6Oq0j/+mZIp6Y2QADGAEEIRgiCQ0FyaFKWIgOAiCAiKu8pvXZEFFV2wl11jBUUQVlEEgSAdBEQIYBADKdJJII30PjOZmfP7Y5KBSZ1AKrmf57kP5N73nnPv977n3ndOjUSv1wOgwQE9xbfVFCuVi8qRamIkKkSpVDJ79myUSiXmQjMPnNvEFNMvHOEcLcoM+awPvFHTraSDqf9my8vFx8eHMWPG1Pu1NCQyYDg9+YiBHKEbl2hDNHeznd74UHUHz3JpyWTMnDmTli0tnUYTEhLYu3ev9bgrLsjqeEi1xK0TFRVFQUEBYJn+wJ65REwI5mDiWYYQSmyjDmAaitH0ZjmWPmFmZKwa8jRjFk2kZ8+elQYwYHlnBgUFMX36dN58801GjRpFB1VrjtCOVxlcX5ff7JCB1FevMhwdHQkPD2fs2LEUFtbuLKUqlQqDwVCradYmjzzyCMOGDQNA98lpnjvzKQDfEsJjVcwQWlPs1UGLhqto8SILAw58/uLbqNs5IoTg/fff58KFpr1WjD06TCWEpSTTqcyCfwA5uOJFASZMduc3c+ZM6zwjer2e5cuXk5Z2o+/FGvrzAOf4iSAWE0ca6fbf0C3S2MtFfWGvDmPHjmX06NGApRZty5YtdX1p9Up9+0MgbTlBJm7kAvC/oKcoWBBsPZ6fn8+ff/7J1atXycnJQQiBs7MzrVq1IigoCC+vGz/wRJ6RcQtfx09YAsVJ9GMjx27puppquajLb2gpUk1MA/HEE0809CVUSlBQkDWAMRQaGHNmu/VYGDm1mpe9OhShYyWWla1VFOP0maVvjkwm48knn8TZ2blWr6u+qUqHtrTmAD34lohyAUwGHhTgyCGCygUwHfBHUUFNSnBwMC+99JI1gDEajaxYscImgHHHlcmcxJc0JhFFXj2MRIPGXS7qE3t1uHko/KBBg6yds+8U6tMfXHFhKzJrALPPfST5z/YALLVeH374IS+88AJffvklu3fv5tixYxw/fpz9+/ezbt06lixZwhtvvEFERARmsxmZi5I999wYgLCG09xz0/ISNUEqF5Uj9YlpILy9vas3agC8vLx48sknrX9fe+8wHYgHYB89Oc6pWs2vJjr8lxieQ4sjRUzL3cvLhzvQcWAn3NzcmD17NmFhYdYRG02NynToQUcOkYobidZ9B+nBJ2iJcEnAuZULjlpHPBycGeY2DLnc8rvEsUDNp0eOE68I5r+921PoY8DHx8dmWQGw1MCsXLmS2Fjbfk5PEIy2pEp9DcHoqJ/Jthpruahv7NUhNzeXEydOEBISgqOjI8OHD6+wY3ZVhBDIO6iYxHVSuH4rl1tn1Jc/yIDvHLoTVHwEgDhlZ87960EunD/Hhg0bSExMrDqBEhISEvj666/Zvn07o0ePpt+8fuxYOo7R6VtxopCtMgP95C24bkqrPrGbkMpF5UhBTANx5cqVhr6EcqjVaubPn4+Tk2UirJhTMfwt6Tfr8X/b2VRRE2qiw3XS+ZxB/INf0KIjYP0pcnv44erqSufOnXnwwQeb7FDEynSI5gIR9GQkv3OZNvzn7gEox/oR6u/PsCrmygl8cRN+XMfPdJ0Vxy+yfvhzyO6zXffo0qVLrF692qYGBkCOjKdLAleAz25zaYma0BjLRUNQEx22b99O3759kcvlDB8+nIMHD9rdOfsx+rCW35AjWEEfxjWyIKY+/MHNzY33nEYzKskyF1UmHmyZ8Sjff/sFUVG3NqFneno6a9eu5dChQzw2/TFafxJPD8MftBMJbFL1Z6aPKxfjL9qdnlQuKkcBvNrQF9FYcXBwYOrUqaxfv57i4qoXWqspSUlJFBUV1Wqat8uTTz5JYGAgAKmpqZg+OMFU8QcABwhmWS3M0FuWmupwmkLmI3DAyL3iGq/G5NNlUHdkMhmBgYFkZ2eTkFB/H93aojIdPL28yAztjqm4F2f+NZWWQ9vj7e2Ng0PVQ2NTVH60jD2Pu8hBg57el37h8mlPsnv6EBMXw4YNG9iyZUuF7dTzGMjjWJYc2E9P/sOftXOTdtAYy0VDUBMdCgsLcXNzIyAgAKVSiVar5cyZM/blQwFP4IQTRXQikVQGEXlTANvQ1LU/9O7dm7898zfa/3qRjgV/YkLOv4On8fbPn9hd+1IVOTk5/Hr8V9J69eX+pEycKOQu41X83B7EOORuLly4gNlsrjadplou6vIbWorUJ6aBeOqppxr6EmyYNGkSwcGWDmxFRUV89+G3vGQ+CVh66D9P3RSgmuqQQhrvcB8ADhj5Z5KejT9stB5/7LHHrPfRlCjVoRUt6UYgnTt35rnnnuP1119n+KSR5L40EIXHjYrT7OxsYmJi2LdvHxs3bmTt2rWsXLmSzz//nM8//5wvY79jSqAvGx1ujIqYlLCWnv9cxfbPtpZrPiqlBV68wY31sV6lfoevN7Zy0VDUVIeffvrJOqR34MCBdOhgX9+LDLKZRVvr3//hOPeWWaupIakrf3BxcWHu3LnMmTMHJ2cn4pc+wDcdZrDMZRTv/LHKqmVtIIRg04mtzHQKpLik8WNSwjpGJ93NkiVLuOuuu6pNQyoXlSM1J0kwYcIEhg4dClgK3BdffMFrmR64YZl3YhX9OcWvDXmJNrzDCWbjhz/JDCSO5372Ya/HXoYPH45MJmPOnDl8/PHH/Pln/dUg1AZ96cqPpCNk+fw4fhGqAJX1mBCCuLg4Tp8+TXR0NOnp9o0UmgQ8w0A+4BgqihnIaU7jyr8YyEqOYLppOnsXnPmJlniUzAP0Nf35lSO1eo8SdUNubi6bN2/m0UcfBWDGjBm88cYbdv16385JPmIAf+dXNOj5kVzuw7teRqM1BH369GHKlCnWZnOAyJORrE/6oc5G0ADszD/C3xnI5xwGYNbx9/m40zssWrSInTt3smPHDmsnbQn7kZqTqqAuq8KKiopISqrbFYGrQyaTMW3aNGsAA7B27VpOnTrFWbT0xwsZMiaSRmEd1cTcig5GjFykM/548wAKLnKFuLg4vL29adOmDXK5nN69e5OcnExKSt3PMnu7qFQqHkjpwIr0A3iQiyt55ETLyB7WifT0dHbv3s2aNWv45ZdfuHLlSo1ftL+RwB6CGI4Kd/LQoGcMCbRmAOEl/V0UyPgNf3pyDoAUWjCRdAqou5d6RTSGctEYuBUd4uPj6dKlCx4eHjg5OeHn50dkZKRd5+4niaF0wZ/ruJPH/bTlWwoppm6aAOylNv2hdADAyJEjkZ0tpjhWh65FsbUjbl01d9zMSRJwYRChxLPabwZiWnvkCjmBgYF0796dS5cukZdXfiRgUy0XUnPSHUxDD4V0dHTk2WeftS76B/DNN98QEWGZA+Y057mPKwzFg3Qy6+w6blWHcH5jEKe5dFP7/dq1a60d8ZRKJfPmzWvUk+G5ubkx4YHxrPccz6I/v0SNZR6IE9p+HHykOytWrODll19m9+7d5OTc3tD2E8TSg1xW09+6b9tNTUUmBDtLplZPx5NhuHK9AX6JN3S5aCzcig5CCFatWmUNcnv06MGUKVPsOteAkUdI4Rq+ANxHLNvoiDMNO3VBbfiDUqnkgQce4LXXXqN79+4UH8th0qdv88T3ywhfvJGTJ0/WwpXazz/5hVH0ZU7KOnbs3G7tE+Pv78+SJUt49NFHbWqJQCoXVSEFMQ3E/fff32B5BwUF8corr9C5s6Xt22w2s2rVKg4fPmxjZ6CYaOp2Ernb0aHsYGqtWcW6z9ZZAzGwLGy4YMECPDw8bjmf2qZdu3bMnj2bZWMX8fa+GB5O2WA99p3neGa0yubNL9/i1KlTtTpkPJc8ZnGEULqxgRB+4jeb42/yB9u4j0F4EIP9Iydqk4YsF42JW9UhIyODVatWWf3mL3/5C1OmTLEuK1EVyaTzAFoycbecyx98zT23dB21xe34g1wup2/fvrz22mtMmDABjUaD2HiNJ9a8RktxHVfyeNWgq72LrQG7OI4QZn766SfefPNNkpKSMB/OALPlnpctW8aI7JMa8wAAHxZJREFUESOswYtULipH6hPTjPDy8mLChAn07t3bui8vL48VK1YQcMGF3dzLI5wjj4ZbO+dWUePAVoJwxsDEr3eTkpLC+PHjkclkBAUF8dprr7Fr1y4OHDjQIL38nZ2d6d27NyEhIbR28MP3q2OMu/YSypJh64VoWaQdwEeZW6jDii8AIoiucM7lLPIYWyawkWh6xMTE8PXXXzNz5kzAEsj4+vqyZs2aamv0YrnMSILYBThRyNv13JxYG6jVakJCQhgxYoR14URTppHWYYcYl/KD1e5X7mEilxvqMq1cvXqVI8t+ZI+I4ciWgUQ9/TCOHRx5+OGHGTlyJAcPHqxyuYPmzi0tO/D000/zwgsv4OfnR0xMDAsWLODXXyvv+Dlo0CA++OADunbtSlJSEu+88w4rVqywsXn44YdZtmwZd999NxcvXmTJkiXlptC2J9+lS5cyd+5cPDw8OH78OM8884zNSAyVSsV7773H1KlT0Wq17N+/n/nz51c4nK4up0x2dnaut4X2OnXqRP/+/endu7d1MjSAuLg4Nn61kQV5HfgHvyBHcIgejOIsRdTsF4pcraX1A7Nw7xKK0skVmVIFAmTW/ATCbEYYDZj0RQhTMdmxEeSdCMelz1ib84SxGGNhDtkxR0nc/RVmffVBx1pCmF7yaU7HkwUEEdkxg5mzZtrUwuh0Og4fPszBgwfJyMio0T3WFC8vL7p160b37t3p3LmzVfuQZz+ju+HGcPXf6MKTGkGULs6udOVqLW1Gz8Wz51AUDpaXm6lYR+ap/VzbsdIuvW6VG8+5Pw6unsgUSkqfbVFqPLqUy3h0H1yyHxACIczI5Aq70tfIBTqzba2BMJswGw0gBDKZHLmq/Au91LeMhbkYC/NQOjojkyuRq7UAlvMc1GCtkRBQ0bpQQmAu1iNTKC3XfFMNhjCbMRXlodA43bi/ytISgqLr8RQkxOHaoddNWpUcNhnJ/ONnzMV63Drdh0yhRJhMGIvyUTo64+igoNBgJDs2wloGbmgfUmJve7wsISEhTJ8+HYWDCqc2nRAu3hw5n8qJC8kU5eeWaKSoMJ1u3E13WvEttrWzKpQY6nHEmr3vSaVSSWBgIP369aNnz57WKQjMhWbU35xn9Mlv8SXVav8NocwmkmK1wi5Na6p9VZRNS5mvY9uHL9Kq5PoKcCT87qlkzgxG2cLBen9RUVFEREQQHR2NTtcwNUg1pT6WHahxEDN58mTWrVvH/PnzOXLkCPPmzWPOnDl06dKFq1evlrNv27Yt0dHRfPHFF6xYsYL+/fvz6aefMnXqVH788UcA+vXrx+HDh3n55ZfZvHkzEyZM4N///jcDBgzgxIkTdue7cOFClixZwsyZMzl37hwvvfQSgwYNolOnTtaC8Omnn/LQQw8xc+ZMMjIyeP/99/H09KRXr17lxuvX5QOYNWsWX331Va2mWYqjoyOBgYF06tSJ7t2726znAVBQUMCRL3/m3rh85nEG75t++m+nN5OJqVFHXrlaS+dnPkLT4i5kCvs+VgBmk4kHWhrYk6qq8DxhMqFLSyDuk79X+6LoTge2Uchd3Oj8dpqOfKpoTeGINoSO7V+uSv3atWtERUVx/vx5EhISbusZOzo64uvri7+/P+3bt6d9+/Z4e3ljvKhH5q5E2eLGByxvdTT/PP4xBTjyNvfxJr/y+KwZdvmDXK2l898+RuMTUO5+hBDorscT9/Hf6iSQqe45lzZhVHRd9jRnAIzw0bPn+u21/9ckv7pMuzI9qjpemn6pDmaTCX1aAme/WEinJ98pp33p8crKSKeu9/DiR//Dzd0T5JZ89MVmYlJyuJReSHxmIQaTudp0ADQoiaMlkfjzPbCfOLJqeRmSslT2ntRqtfj7+xMQEEBQUBCBgYHl5k5y/s/vjDi7iRbc+LFSgCP/x718wa+V+nNZLey1s4fK0uq6P4439iynlbgxEKEQLQe8H+BqcDfazgklPtvSCd9sNnP58mViY2O5cuUKCQkJFXYGbgw0yiDm2LFj/P7778yfP9+6LzY2li1btrB48eJy9m+99RZjx46lS5cu1n2fffYZPXr0IDQ0FIDvvvsOV1dX60JmADt37iQrK4tp06bZnW9SUhL//e9/eeeddwBLrUtqaiovvvgiK1euxNXVlbS0NKZPn86GDZZ+CH5+fly9epXRo0ezZ88em2uvywewZMkSXn/9devfMpkMuVxueaEJkMss/5cpZMhkMhQKBSqVCkcHR7QqDWqVBo1ajZOjM66uLri6uNLCuwU+LVri5uoKclC43/hwmrKNuK44iUtyPN1152jHNZvr0aHmFfryHr/UuGrOf+wz+ISMq1EAU8qU1jq+T6y8qtRsMpF2dAtXt31abVoeuPEFQUzkuM1+E3JiuZtzzu25Nm4wmoGeN9LPN2HOMiFzlJOtyyEjM4Pc3Fxy83LQ6fQYDAaMJiMKhQK5Wo5cLkelUuHq6oqH0R1X4YizQoujToEiW4cqMx/X62l45aQQmBdHa5HIF30XkjHeUjN4/PhxkpOTWcRA1vAnKVhmyy3rD5XhP/YZfELH31TDZYswm7l+ZLNdetWU23nO9lKdPzQXbtbBbDJRlHIJR9/2FWpfVRnxH/sMdw2awLDOftzTyo2y8ZRZCK7n6cksMJCep+PayQNc3L2OgoICCgsL0el0mEwmjEYj8wp78p75Rs2MGRm/E8QZPDmHkssYyERPCvmcKRnlVooGNQKBCTNCJpArLWVJoVAgQ4aDwgGFXIHCQYHGUYNGY9memvcUm//3I64urnh6eOHh5o6H2g1noYV8I7L8YpTphWjTc8h94h4cnCw/0k6cOMGDGxP5q+lGTf0m+vJ/JHC1ZOXuqvz5Zk3ttbOHqtJSZxTw2GermZ37E6oyo8KMKIhVdePA83PRBNw415Sow5xlotCkI0efR1ZhNhkFGaTnZFCkK6KgsICioiIKiwoxmS3P0Wg0Wp+pyWTCZDJhNpvrZMmW+ghiatQnxsHBgV69evHWW2/Z7N+zZ481IClLSEhIueBg9+7dzJ49G6VSidFoJCQkhP/85z/lbBYsWGB3vu3atcPPz88mL4PBwKFDhwgNDWXlypX06tULlUplY5OcnEx0dDShoaHlrrMUZ2dnFDc5nV6vv+UVRZ9//nkCI+TMev0tXkWBDIEMgVwIKDNHQLLMl/CPXrXZ1+5f4YxI3VFtPptbPcr1V+5HCEFsbCzHDh3j2OVI5GVClGKUfEcfXiae+FtcH8dSLXprH7YMQ9V9y+UKBe5dQu16SWSRwyMcZzg9+TcG+hEDgAIz93Cee/LPM/aHfIozXAgODqZt27Yof7rGkwffrDbtZJkv4Z+9arOv44s/MiSnYp+5GU3kCf51/KDNvrfKVNPbOzuoe5eQSgMYsDTf2atXTbmd52wv1flDc+FmHeQKBVrfdpVqX1UZce8Sgt4sY3tMCseuZNKvrSddfF1RKizRjFwmw9dVg6+rBvxcMd31EJntnMqlA6D5PIbUqLO0FJalCeQIehNH7zJ2UQ49OPbR5zb7+j/7Cd0MJbMICzAXm8u9iwC+DnoG3YIbnYnbOfqxJ2JfhddTlrk7nuJEuqW5xWQyoSOYSaj4kV68Rya/l/lxU5U/36ypvXb2UFVaei8nPnt6Im+/fYJ/cDcz+MO6GKUSE0GGWJbFHeEeTSdatmwJQKuvjzM+YX21+e5yf5D4tx602Td2/mv4mFMRyLA8TRlf3b+Qsz2Lyn2PGzM1CmK8vb1RKpWkpqba7E9NTcXX17fCc3x9fSu0d3BwwNvbm5SUlEptStO0J9/SfyuyCQgIsNro9Xqys7Ptvn6wfGCUyhtS/fzzz6xZs4bt27fz9NNPA5aASqlUMmTIEADCwsKYOHEirVu3Jjk5mQ0bNvDcc88xYMAAMk5FWDt0VoUcaNWqFXq93noP2TL71gbSFuvZtGkTnp6edOjQgYHDBnLtdCJ3kUQRGiKV97Bb7Y3s0WCErxzF+vWM6TyG4OBgjEYjb7/9Ns8//zwajYaYmBhOnTrFX//6VwA2bdpEQECAtYPwNpSM9dWjVQiuFcmJy1My3McS5B3LcsBNaaazi+V+NyapecDHgItSkKKXczpXwZTWlvbdyGwlajnc42ppc9+SrGawtwE3H0diZ8xg69atPPPMMwDs22d5sZWutv3JJ58wbtw42rRpQ2pqKkO//ZYXhy6k/ckEeqScorP5AkpM3PP4/azcssI6l4Z3foFdeoKMbt26ER0dbV39OVe9s8ozCnDklKYHOe2CGNPeibi4OKZOnQrA999/T2BgID179sRsNvPxxx/zj3/8A61WS2xsLJGRkTz++OMA/Pjjj7Rp04Y+ffrgGujIxlTBGF8DTgpBkk5OdK6SESV6n8hyQKNUM3bJEgDeffddnnjiCby9vbly5Qq7du2yzv65e/du1Gq1deTDhx9+yOTJk/Hz8yMxMZFNmzbx7LPPAhafb+Olpk8ry7Panqqij7uRFmozOUYZP6epmOBnmeU0OldJkQnu87A8x13XVfRwNeKnMZNvlLEzVcWk1hbbP/MVZBnkhHhafnn+muFAqKcBf60ZnVnG1mQ1k1vrkAEXChSk6OQM8LLYHkx3oK2jmbaOJowCNiVpmNhKh1IGVwoVXCmUc7/3jXR9NWY6OJkQwIZEDeP89GjkgqtFcs7mKxnWwqJhRKYDHiozQc4Wn/0hUc2olgaclYJknZyoXCUjS/T+LUuJVgHdSnx2c7KaIS0MuCkFaXo5J7KVjGlpsT2Vo0QO9HCz2IanqOnvWYyXykxWsYxf0lWM87uhS0cnI/e6W2y3Jyvp7WmgpdpMrlHG3usqJray2MbmKckyq6zPfNWqVQwaNIiOHTuiaOfIzkzB5NZ6QMfZawXExSsZHaDC082ZXKUbAa5KXJRgAi7p5fTs2ROZTEZ6ejo5OTncfffdAFxY6Mpv6uGY9qbicDCSdhcO09lYfubnIrUH7u7uuLi40KJFCwDk2DbVVxTAALg4u2CQywkKCkKj0ZB1NrlCuwrPzbbMlbNo0SIADuzazyhjKKEP9mcUcKnMOyJKpWRyybvnTK4SvRl6l+i9M1VF9wCtRdO2WvZlCx4p0TsuT0GOUU4/D4tv7dA58Mgjj9CpUyfy8vIICwtjScmziIyMJD4+nokTJwJwQutAJ89iArQmDGbYnKzhkVY6FDK4VKjgksGBsUtmch0I+SaNYaoxhGYbuTfjD3QmOXe198VgMHDkyBEyMzP5vyL7mjZlMrn1vRUfH49arUaBGUWZ5+Lh7o6jo8x6/TV9RxiNRkaMGAFYWlzGjx9v9/O7VWrUnOTn50dSUhIhISEcO3bMun/x4sVMnz7dOmT3Zs6ePcvq1attalFCQ0M5cuSINXjR6/XMmDGD7777zmozbdo0Vq1ahVartSvfkJAQjh49ip+fn80EZytXrsTf359Ro0YxdepUVq9eXa6n9549e7h48aI1ICmltCps2rRpNiNabqcmZvr06XS96Mnok4cwmSwOJGSl9TEWLJGxjBylC1vndEcIgdlsxmAw0HNbHj0yL1rsBZixtKObhcBsFpa/gQO48DaHbPIOoSs5FHGeeIprcTHHexb9D7Wn3y2da0/zgT4zmTNv/fWW0i9FjYoutONUySzEpQwnmPmo0GJEU6KJTCZDhgyZ7EZ3zUy5Ey91ycVkMlFcXExeXh6PpAbSx1yMDjlZyMlARhomLpHHBVJJJMXuwmVvc5I9WteGXrea9+0iNSdZKKuD2WRErqj8N2dlz9yeZ6aQyXB3dMDTUYWDLpuUze/j5OSEs7MzKpUKhUKBUqlEoVBY/1/aj0eWL1AlmHFOMeCaVYBGbyDL1ZXUh1xs8uj3ZRy+BddRCCNyYUYpTAhkmEvefeaS99+etvcS2ysfnU6HTqdj4tCH6LBoDWYhMAkwCUEhSvJRkIeCfOSkI0jAwAEukob9q0NXp02ppvba1WaeZVmyZAlvvf6mzQzbAM/Sn3sBDSbUmNHIBFqZCRVm6/tLJoNI9yCOj1ahVCqtz3LKmijcii19RUu/Pj/1G8qZ1sl8//33dt1PdTS65qT09HSMRmO5WgsfH59yNSCllNa0lLUvLi62jg6pzKY0TXvyLQ1cfH19bYKYsjZqtRp3d3eb2hgfHx+OHj1a6X3n5+fX2gNYt24dAHn2fLSKgY8OVW1TAyJKmldqm+zYCFqEjENeB00NZpOJ7JjKn4296DGUC2AA9vIHe8vuFGX+BUu0eNrW7CPs/5VYW2THRlTbJ6Y29Kos77p6zhKVY+kTcxmtb/sKta+qjNjzzExCkFFgIC23iLSjW7laSbO63SQC9g20K8/53+H8jT979erFk6a6GfZflTY3a2qvXW3mWRFlAxiAsLLLgggqrpZI/wPW2u76rKJMfrVv4dDGRI0aoIuLizl58iTDhw+32T98+PBKg4CIiIhy9iNGjCAyMhKj0VilTWma9uR7+fJlkpOTbWwcHBwYPHiw1ebkyZMYDAYbG19fX7p161ZlEFMX/Pzzz/WaX12SuPsr9GkJmGu47ofZZOKPTMsopIoQJb3/E/esro3LbNTY6w+Ju79Cl5ZQYSc8IQS6OtSruucshKj0uuwlKuf2p66qiw6Kt5J2ZXpUdbz071IdSkfAnP9qcYXam6spI5U9s7L5VpdOQ1GX78nKtCmrhb12tZlnWe6k70VtU+O1k3Jzc1m+fDmJiYnodDoWL17MkCFDmDVrFjk5Obzxxhs8/vjj1jleLly4wOLFi/Hy8iIhIYGHHnqIV155heeff564OEu4npiYyPLly9Hr9aSnpzN79mzmzJnD3LlzrR0eq8sXQKFQsHjxYs6ePYtCoeD999+ndevWzJs3D4PBgF6vp1WrVvz9738nKioKNzc3Pv/8c/Ly8li0aFG5gl2X6z6UNpHdCQiTkYzf96JQaXFw9kSmkINMhjCbABkIAcKMMJkwG3QYC3IxFuSQ+ftejL9vIyUt3eY8c7GO4rwMMk7u5dJ3b9TpvCeNBXv9oVRrpcYZtbe/ZS4TITDpi8j4bSeXvl1eZ3rZPmcv5Co1yORY5omx1Bbknf8djc9dJfuxzhNTblhMJXiqzOU69wqzCZOhCHNxMcJsKjNHS6mNucRvMtFnJiNMxZj1OktTq7HkvJvnqqksuBACs3UW1/Lz1ZgKc5HJlTfuz3KkwnSKUq+QExuBUut2k1Ylh01GMn/fS0F8LEpHt5JykYc+KwVhKsZDYSQ1I5vM3y1lwFSYd5P2HtZyVHq8smdu+8w8yuVj1hfZlU5DUZfvyYq1Ka+FvXa1mWdZmur3oj7WToIbFVB2b08//bS4fPmy0Ol0IjIyUgwcONB6bPXq1eLAgQM29oMGDRInT54UOp1OXLp0ScybN69cmhMnThRxcXFCr9eL2NhYMWHChBrlW7otXbpUJCUliaKiInHw4EHRtWtXm+NqtVqEhYWJ9PR0UVBQIMLDw0WbNm0qvE9HR0exb98+4ejoWGONqtuWLFlS62k2xU3SQdJB0kHSQdLhztShLr+hN20Nf6ONdZOCmLrfJB0kHSQdJB0kHe5MHaQg5g5+AJ6eng1+f41hk3SQdJB0kHSQdLgzdaiPIEaaWaqBGDNmTENfQqNA0sGCpIMFSQcLkg4WJB0sSDpUjhTENAAqlYqZM2eiUqka+lIaFEkHC5IOFiQdLEg6WJB0sCDpUD0NXuXUWLe6qgpzcXERQgjh4uLS4PfYkJukg6SDpIOkg6TDnauD1JwkISEhISEhIVEJUhAjISEhISEh0SS5/ekxmwFarbbW0zMajWi1Wkw1nOX2TkLSwYKkgwVJBwuSDhYkHSw0ZR1q+9tZETVaALK54eXlVWsLYUlISEhISDRHpkyZYl0rsbaRgphq8PLyslnBWkJCQkJCQsI+tFptnQUwIAUxEhISEhISEk0UqWOvhISEhISERJNECmIkJCQkJCQkmiRSECMhISEhISHRJJGCmFtg6dKlCCFstuTk5HI2iYmJFBYWcuDAAbp06WJzXKVSERYWRlpaGvn5+WzdupXWrVvb2Li7u7N27Vqys7PJzs5m7dq1uLm51fn9VcbAgQMJDw8nMTERIQTjxo0rZ1Nf9+3v7094eDj5+fmkpaXx4Ycf4uDgUPs3XQHV6bB69epy/hEREWFjcyfosGjRIk6cOEFubi6pqals3ryZwMDAcnZ3uk/Yo0Nz8ImnnnqKqKgocnJyyMnJ4ejRo4wcOdLG5k73Baheh+bgC/VNg09N3NS2pUuXijNnzoiWLVtaN29vb+vxhQsXipycHDFhwgTRtWtXsX79epGYmCicnZ2tNp9++qm4evWqGDp0qAgODhb79+8Xp06dEnK53GqzY8cOcfr0adGvXz/Rr18/cfr0aREeHt5g9z1y5EixbNkyMWHCBCGEEOPGjbM5Xl/3LZfLxenTp8X+/ftFcHCwGDp0qLh27ZoICwtrFDqsXr1a7Nixw8Y/PDw8bGzuBB127twpZsyYIbp06SK6d+8utm3bJq5cuWIzxXhz8Al7dGgOPvHggw+KUaNGiY4dO4qOHTuK5cuXC71eL7p06dJsfMEeHZqDL9Tz1uAX0OS2pUuXilOnTlV6PCkpSSxcuND6t0qlEllZWWLu3LkCEK6urkKv14vJkydbbfz8/ITRaBQjRowQgAgKChJCCNGnTx+rTd++fYUQQgQGBja4BhV9vOvrvkeOHCmMRqPw8/Oz2kyZMkUUFRXV+/oilQUxmzdvrvScO1EHQHh7ewshhBg4cGCz9omKdGiuPpGRkSFmzZrVbH2hIh2aqy/U1SY1J90iHTt2JDExkUuXLrF+/XratWsHQLt27fDz82PPnj1WW4PBwKFDhwgNDQWgV69eqFQqG5vk5GSio6OtNiEhIWRnZ3PixAmrzfHjx8nOzrbaNCbq875DQkKIjo62acLbvXs3Go2GXr161el92sv9999PamoqZ8+eZeXKlbRo0cJ67E7VobQqOzMzE2i+PlFWh1Kak0/I5XKmTJmCk5MTERERzdYXyupQSnPyhbpGWnbgFjh+/DiPP/44586do2XLlrz00kscPXqUrl274uvrC0BqaqrNOampqQQEBADg6+uLXq8nOzu7nE3p+b6+vly/fr1c3tevX7faNCbq8759fX3L5ZOdnY1er28U2uzcuZMffviB+Ph42rVrx7Jly/j555/p1asXBoPhjtXhgw8+4PDhw8TExFivD5qfT5TVAZqPT3Tr1o2IiAg0Gg35+flMmDCBuLg4QkJCgObjC5XpAM3HF+oLKYi5BXbt2mX9f3R0NBEREVy8eJEZM2Zw7NgxAIQQNufIZLJy+8pS1qYie3vSaUjq674bszYbNmyw/j8mJobIyEji4+MZM2YMmzdvrvS8pqzDxx9/TPfu3RkwYEC5Y83JJyrTobn4xNmzZwkODsbd3Z2JEyfy9ddfM3jw4Eqv7U71hcp0iIuLaza+UF9IzUm1QGFhIWfOnKFjx46kpKQAlIt0fXx8rFFxSkoKarUad3f3Km1atmxZLq8WLVqUi64bA/V53ykpKeXycXd3R6VSNVpt4uPj6dixo/XvO0mHsLAwxo4dy1/+8hcSExOt+5ubT1SmQ0XcqT5RXFzMxYsXOXnyJIsXLyYqKornnnuu2flCZTpUxJ3qC/VJg3fMaeqbSqUSV69eFS+//LIASwe2F154wXrcwcGhwg5skyZNstr4+vpW2HHrvvvus9r06dOn0XfsrY/7Lu2w5uvra7WZPHlyo+nYW3bz9PQURUVFYvr06XecDh999JG4du2a6NChQ4XHm4tPVKdDc/KJm7d9+/aJ1atXNytfqE6H5uoLdbg1+AU0ue3dd98VgwYNEm3bthV9+vQR4eHhIicnR9x1110CLEMJs7KyxPjx40XXrl3FN998U+FQwoSEBDFkyBARHBws9u3bV+EQuj/++EP07dtX9O3bV0RFRTXoEGsnJyfRo0cP0aNHDyGEEAsWLBA9evQQ/v7+9XrfpUMH9+7dK4KDg8WQIUNEQkJCvQ0drEoHJycn8e6774p+/fqJgIAAMXjwYHHkyBFx9erVO06HTz75RGRlZYlBgwbZDBfVaDRWm+bgE9Xp0Fx84vXXXxcDBgwQAQEBolu3bmL58uXCaDSKYcOGNRtfqE6H5uIL9bw1+AU0ua10fgO9Xi+uXbsmNm7cKDp37mxjs3TpUpGUlCSKiorEwYMHRdeuXW2Oq9VqERYWJtLT00VBQYEIDw8Xbdq0sbHx8PAQ69atEzk5OSInJ0esW7dOuLm5Ndh9Dx48WFTEzb8w6uu+/f39xbZt20RBQYFIT08XYWFhQqVSNbgOGo1G7Nq1S6Smpgq9Xi+uXLkiVq9eXe4e7wQdKmPGjBkNUhYaSovqdGguPvHll1+Ky5cvC51OJ1JTU8XevXutAUxz8YXqdGguvlCfm7SKtYSEhISEhESTROrYKyEhISEhIdEkkYIYCQkJCQkJiSaJFMRISEhISEhINEmkIEZCQkJCQkKiSSIFMRISEhISEhJNEimIkZCQkJCQkGiSSEGMhISEhISERJNECmIkJCQkJCQkmiRSECMhISEhISHRJJGCGAkJCQkJCYkmiRTESEhISEhISDRJpCBGQkJCQkJCokny/7HUyMt6vFpXAAAAAElFTkSuQmCC\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        " ## Comparing density estimates for K = 6, 7 and 8\n",
+        " ## Plot the final result distribution for various samples\n",
+        "fig, ax = plt.subplots(1, 1)\n",
+        "# Bayesian plot (K = 6)\n",
+        "ax.plot(xx, mdeKK6, color = 'white',  lw=2, alpha=0.6, label='$K = 6$') # Trace plot of data\n",
+        "# EM algorithm K = 7\n",
+        "ax.plot(xx, mdeKK7, '--', color = 'blue', label = '$K = 7$')\n",
+        "# EM algorithm K = 8\n",
+        "ax.plot(xx, mdeKK8, '--', color = 'red', label = '$K = 8$')\n",
+        "# Plotting original data\n",
+        "ax.scatter(np.array(x), np.zeros((x.shape[0])), label = 'Original data')\n",
+        "ax.legend(loc='best', frameon=False)\n",
+        "# plot density estimate of the posterior\n",
+        "plt.title('Estimated distribution with different components')\n",
+        "plt.show()"
+      ]
+    }
+  ]
+}
\ No newline at end of file