C3/L5A_bayesian_expectation_maximization.ipynb

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        },
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      "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": []
    },
    {
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      "source": [
        "### Bayesian EM for Mixture of two gaussians\n",
        "\n",
        "Implementation of the markup chain Monte Carlo algorithm for\n",
        "fitting a location mixture of two univariate Gaussian  distributions."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1EF48VnKjPkY",
        "outputId": "a43e2a86-54d4-4e4a-9f11-ccefb9c6d742"
      },
      "source": [
        "### Example of an EM algorithm for fitting a location mixture of 2 Gaussian components\n",
        "### The algorithm is tested using simulated data\n",
        "\n",
        "from scipy.stats import norm\n",
        "\n",
        "## Clear the environment and load required libraries\n",
        "np.random.seed(1)\n",
        "\n",
        "## Generate data from a mixture with 2 components\n",
        "KK         = 2 # Number of componentes\n",
        "w_true     = [0.6, 0.4]  # True weights associated with the components\n",
        "mu_true    = [0, 5]   # True mean for the first and secondcomponent\n",
        "sigma_true = [1, 1]   # True standard deviation of all components\n",
        "n          = 120         # Number of observations to be generated\n",
        "### Step 1 ### Sample component indicators\n",
        "cc_true    = np.random.choice([0, 1], n, p = w_true) # C_i sample \n",
        "x     = []\n",
        "### Step 2 ### Sample from normal distribution\n",
        "for i in range(n):\n",
        "  x.append(norm.rvs(loc = mu_true[cc_true[i]], scale = sigma_true[cc_true[i]], size = 1)[0])\n",
        "\n",
        "x = np.array(x)\n",
        "print('The first five samples of C_i are: {}'.format(cc_true[:5]))\n",
        "print('The first five samples of the mixture are: {}'.format(x[:5]))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The first five samples of C_i are: [0 1 0 0 0]\nThe first five samples of the mixture are: [ 0.12182127  6.12948391  1.19891788  0.18515642 -0.37528495]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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          "height": 474
        },
        "id": "4iNDl1JDTe53",
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      "source": [
        "### Plotting the true distributions\n",
        "\n",
        "# Plot f(x) along with the observations just sampled\n",
        "\n",
        "# Values to sample\n",
        "xx_true = np.linspace(-8, 11.0, num = 200)\n",
        "\n",
        "yy_true = w_true[0] * norm.pdf(loc = mu_true[0], scale = sigma_true[0], x = xx_true) + w_true[1] * norm.pdf(loc = mu_true[1], scale = sigma_true[1], x = xx_true)\n",
        "\n",
        "# Plotting the mixture models\n",
        "fig, ax = plt.subplots(1, 1)\n",
        "sns.lineplot(xx_true, yy_true)\n",
        "sns.scatterplot(np.array(x), np.zeros(len(x)), hue = cc_true)\n",
        "plt.xlabel('xx')\n",
        "plt.ylabel('Density')\n",
        "plt.legend(['Density', 'Points sampled 1'])\n",
        "plt.show()"
      ],
      "execution_count": 3,
      "outputs": [
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "id": "mHkwF2au-2Dp",
        "outputId": "7ce63da3-b1fa-497d-b239-1ee0aa573239"
      },
      "source": [
        "# Density estimation of X\n",
        "fig, ax = plt.subplots(1, 1)\n",
        "sns.histplot(x, stat= 'density', bins = 18)\n",
        "sns.kdeplot(x, bw_adjust = 1.0, label = 'Density estimate $x$')\n",
        "plt.title('Histogram of $x$')\n",
        "plt.show()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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EInEIchp0rJvCNTAwkMzMTAdHpj4iehnV6X6PqDeZSlCUsr8T6tVrQETEGZuOqYdp0I1aX/dCRCeQXkbDUV5yGnQV6Nu3r9YhqIKIXkZ1uv2I+orKpk255b7v5OSqdehVwqj1dS9EdALpZTT06CWTDisJDQ3VOgRVENFLRCeA0NASrUNQBRHrS0QnkF5GQ49eMumwkitXrmgdgiqI6CWiE8CVK2L+uYpYXyI6gfQyGnr0EvMspgIxMTFah6AKInqJ6AQQE+OmdQiqIGJ9iegE0sto6NFLJh1WMmHCBK1DUAURvUR0ApgwIU/rEFRBxPoS0Qmkl9HQo5dMOiQSiUQikTgEmXRYSUJCgtYhqIKIXiI6ASQkuGgdgiqIWF8iOoH0Mhp69JJJh5VkZ2drHYIqiOglohNAdrZJ6xBUQcT6EtEJpJfR0KOXTDqsRI/3O9sDEb1EdALo27dQ6xBUQcT6EtEJpJfR0KOXTDokEolEIpE4BF0kHWPGjCElJYXc3FwSExPp2LFjhes+++yzxMfHc/nyZbKysti7d2+Zh9q8/PLLKIpSpri7u9sc49KlS23eVs+I6CWiE8DSpba3Xz0jYn2J6ATSy2jo0UvzpGPgwIHMmzePadOm0apVKxISEti0aRP16tUrd/2IiAi2bt1Knz59aN26NTt27GDDhg20bNmy1HpZWVmEhISUKvn5+TbH2bVrV5u31TMieonoBNC1q/4eU20PRKwvEZ1AehkNPXppPhx+woQJLFu2jGXLlgHw1ltv0atXL8aMGcPUqVPLrP/WW2+Veh0VFUX//v3p168fSUlJlvcVRSE9Pd1ucTZs2NBu+9ITInqJ6ATQsGGx1iGogoj1JaITSC+joUcvTXs6XF1dad26NfHx8aXej4+Pp3379lbtw2Qy4evrW+ZJej4+Ppw7d44LFy6U2xNSWa5du1al7fWKiF4iOgFcuybm3Ssi1peITiC9jIYevTRNOoKCgnBxcSnTI5Genk5ISIhV+5g4cSLe3t7ExsZa3jtx4gTDhw/n6aef5oUXXiAvL489e/bcN+vz8fHB19fXUtzc7kw7vWTJkkqYGQcRvUR0AliyRMwxHSLWl4hOIL2Mhh69NL+8AuZLIXdjMpnKvFcegwcP5oMPPqB///6lHmxz4MABDhw4YHm9Z88eDh8+zN///nfGjx9f4f5SU1NxcbnzlWzfvp3o6Gg2btzI3LlzOXXqFPHx8bi4uPDEE08AsGDBAp577jnq1KlDWloasbGxlmPs3LmT/Px8evXqBcDixYvp3bs3DRo0ICMjg+XLlzNp0iRLjJmZmfTr1w+AZcuWERERQaNGjcjKymLhwoVMmTIFgIMHD3Lx4kUGDBgAwIoVK2jTpg1NmzYlNzeXOXPmMGXKFJycnDhy5AinTp1i0KBBAHzxxReEh4fTsmVLioqKcHFxIS8vDw8PD44dO8aRI0d48cUXAYiLi6N+/fq0adMGgGnTpjFu3Dh8fX05efIke/bs4ZVXXgFg/fr1BAcHW3qoPvzwQ1599VUCAwNJSUlh69atjBo1CoBNmzbh5eVF586dAZg7dy5DhgyhZs2aXLx4kfXr1/PGG28AsG3bNgC6d+8OwCeffEL//v2pW7cu6enprF692nLJ7YcffiAnJ4fx48dz6tQplixZQo8ePQgLCyMzM5PPPvuMd955B4C9e/dy5coV+vfvD8Dnn39Ohw4daNKkCdevX2fBggVERUUBkJiYyG+//cZzzz0HwMqVK2nVqhUPP/wweXl5fPTRR0yePBkXFxeSkpJITk7mhRdeAGDNmjU0btyYVq1aUVJSwowZM5gwYQKenp4cP36cxMREXnrpJQCcnYvo0aOQtm3NYzdmzPBg7Nh8/P0VTp92plmzIvLzzb0dGza4Ehio0KFDEdevn8bNTWHEiAKCgko4d86JzZtdGT3aPIZpyxZX3N2hSxfzLbfz53swcGABtWqV4O7ugq+vL+PGjbO0+aKiIsvg7EWLFtG3b19CQ0O5cuUKMTExlqmVExISyM7OttyWt3TpUrp27UrDhg25du0aS5Ys4d133wVg//79XLp0iWeeeQaA6OhoHnvsMcLDwwkLC2PkyJFMnToVk8nEoUOHSElJ4fnnnwdg9erVNG/enObNm1NQUMDs2bOZNGkSbm5uHD16lKNHjzJkyBAA1q5dS1hYGK1bt0ZRFKZPn05kZCTe3t4kJydz4MABhg8fDsDXX39NSEgI7dq1A2DmzJmMGjWKgIAAzpw5w44dO3jttdcA2LhxI35+fnTq1AmAOXPmMGzYMIKDgzl//jwbN25kzJgxgLmndtCgQZZfmUY/R8yaNYuJEyfi4eFBSEgI//rXvwx/jnjyyScBLOeI3r17s3//ft2fI9atW0fdunVp27btrXPEDMaOHYu/vz+nT59m165djBw58tY5YgPDhw/n6tWrAMyePZsRI0YQFBTEuXPn2Lx5M6NHjwZgy5YtuLu706VLFwDmz5/PwIEDqVWrFqmpqcTFxd3zHHH779paFK2Kq6urUlhYqDzzzDOl3p83b56yc+fOe247cOBA5ebNm0qfPn2sOtann36qfPfdd+V+5uXlpWzbtk2pUaOG4uvraylubm6WdaKiojT7ntQsInoZ1WnVql0KbK+wREVtLPf93bvT7rndvYr5mLK+pJP00joGI3vd/h/q5eV133U1vbxSWFjIoUOH6NGjR6n3e/Towd69eyvcbvDgwURHRzNkyBC+++47q47VsmVL0tLS7rnOjRs3uH79uqUUFBRYPtu/f79VxzEaInqJ6ASwf78uOibtjoj1JaITSC+joUcvzc9ic+bMISYmhsTERPbt28frr79OaGgoixcvBmD69OnUqVOHl19+GTAnHCtWrGD8+PHs37+fmjVrApCbm2uZ8vW9995j//79nD59Gj8/P8aNG0fLli0t3XG2cOnSpSqa6hMRvUR0Arh0SfM73FVBxPoS0Qmkl9HQo5fmZ7HY2FgiIyN57733SEpKIiIigj59+nD+/HkAatWqRWhoqGX9UaNG4erqysKFC7l06ZKlzJ8/37JOtWrV+PTTT0lOTiY+Pp46deoQERHBjz/+aHOclb1mZRRE9BLRCeCZZwruv5IBEbG+RHQC6WU09OileU8HmAeiLFq0qNzPRowYUeq1NZOdTJgwwTLYTSKRSCQSiT7QvKfDKERHR2sdgiqI6CWiE0B0tJi3zIpYXyI6gfQyGnr0kkmHlTz22GNah6AKInqJ6ATw2GNiToMuYn2J6ATSy2jo0UsmHVYSHh6udQiqIKKXiE4A4eFiToMuYn2J6ATSy2jo0UsmHVZy8+ZNrUNQBRG9RHQCuHlTzGnQRawvEZ1AehkNPXqZME/Y8ZfGy8uLb775hqeffpqcnBytw5H8RVm1ahdDh1b+Esru3eF07Jhs4zFdGDo0wqZtJRKJBCr3P1T2dFhJeU+8FQERvUR0Apg6NVfrEFRBxPoS0Qmkl9HQo5dMOqzEZBKza1tELxGdAATVErK+RHQC6WU09Oglkw4rOXTokNYhqIKIXiI6ARw6pItpdeyOiPUlohNIL6OhRy+ZdFhJSkqK1iGogoheIjoBpKSI+ecqYn2J6ATSy2jo0UvMs5gK3H7MtmiI6CWiE8Dzz4s5DbqI9SWiE0gvo6FHL5l0SCQSiUQicQgy6bCS1atXax2CKojoJaITwOrVblqHoAoi1peITiC9jIYevWTSYSXNmzfXOgRVENFLRCeA5s3FnJFUxPoS0Qmkl9HQo5dMOqxEj5VnD0T0EtEJZNJhJER0AullNPToJZMOKykoEHMQn4heIjoBFBTo7557eyBifYnoBNLLaOjRS06DjpwGXaIP5DToEonEiMhp0FVg0qRJWoegCiJ6iegEMGlSntYhqIKI9SWiE0gvo6FHL5l0WImbm5h3DojoJaITgJubmJ2SItaXiE4gvYyGHr1k0mElR48e1ToEVRDRS0QngKNHnbUOQRVErC8RnUB6GQ09esmkw0r0WHn2QEQvEZ1AJh1GQkQnkF5GQ49eMumwkiFDhmgdgiqI6CWiE8CQIfobiW4PRKwvEZ1AehkNPXrJpEMikUgkEolDkEmHlaxdu1brEFRBRC8RnQDWrtXfoDB7IGJ9iegE0sto6NFLJh1WEhYWpnUIqiCil4hOAGFhJVqHoAoi1peITiC9jIYevWTSYSWtW7fWOgRVENFLRCeA1q0rP3GYERCxvkR0AullNPToJZMOK1EUMedIENFLRCcAQbWErC8RnUB6GQ09eslp0JHToEv0gZwGXSKRGBE5DboKREZGah2CKojoJaITQGSkmNOgi1hfIjqB9DIaevSSSYeVeHt7ax2CKojoJaITgLe3mJ2SItaXiE4gvYyGHr1k0mElycm2dV/rHRG9RHQCSE4Wc0ZSEetLRCeQXkZDj14y6bCSAwcOaB2CKojoJaITwIEDLlqHoAoi1peITiC9jIYevWTSYSXDhw/XOgRVENFLRCeA4cPztQ5BFUSsLxGdQHoZDT16yaRDIpFIJBKJQ5BJh5V8/fXXWoegCiJ6iegE8PXXYk6DLmJ9iegE0sto6NFLJh1WEhISonUIqiCil4hOACEhYk6DLmJ9iegE0sto6NFLJh1W0q5dO61DUAURvUR0AmjXTsxp0EWsLxGdQHoZDT16yaRDIpFIJBKJQ5DToGPdFK7Ozs4UFxc7ODL1EdHLqE73mwbd2VmhuNhU5n2jT4Nu1Pq6FyI6gfQyGo7yktOgq8CoUaO0DkEVRPQS0Qlg1Cgxb5kVsb5EdALpZTT06CWTDisJCAjQOgRVENFLRCeAgAAxOyVFrC8RnUB6GQ09esmkw0rOnDmjdQiqIKKXiE4AZ86IOQ26iPUlohNIL6OhRy9dJB1jxowhJSWF3NxcEhMT6dixY4XrPvvss8THx3P58mWysrLYu3cvPXv2LLPegAEDOHbsGHl5eRw7doxnnnmmSjHu2LGjStvrFRG9RHQC2LFDzGnQRawvEZ1AehkNPXppnnQMHDiQefPmMW3aNFq1akVCQgKbNm2iXr165a4fERHB1q1b6dOnD61bt2bHjh1s2LCBli1bWtZp164da9asISYmhhYtWhATE0NsbCxt27a1Oc7XXnvN5m31jIheIjoBvPaamGM6RKwvW50WLfqSVat22VQWLfrSzhZlEbGuQHo5Es1/Ok2YMIFly5axbNkyAN566y169erFmDFjmDp1apn133rrrVKvo6Ki6N+/P/369SMpKQmAyMhItm7dysyZMwGYOXMmnTt3JjIykiFDhqhsJJFIJLbh51f7nncw3YtVq2rbORqJxP5o2tPh6upK69atiY+PL/V+fHw87du3t2ofJpMJX19fMjMzLe89/vjjZfa5ZcuW++7Tx8cHX19fS3FzuzPt9MaNG62Kx2iI6CWiE8DGja5ah6AKItaXiE4gvYyGHr007ekICgrCxcWF9PT0Uu+np6dbPX3rxIkT8fb2JjY21vJeSEiITftMTU3FxeXOV7J9+3aio6PZuHEjL730En379iU+Ph4XFxeeeOIJABYsWMBzzz1HnTp1SEtLIzY2lvHjxwOwc+dO8vPz6dWrFwCLFy+md+/eNGjQgIyMDJYvX86kSZMA2LNnD5mZmfTr1w+AZcuWERERQaNGjcjKymLhwoVMmTIFgIMHD3Lx4kUGDBgAwIoVK2jTpg1NmzYlNzeXOXPmMGXKFJycnDhy5AinTp1i0KBBAHzxxReEh4fTsmVLioqK2LdvHxMnTsTDw4Njx45x5MgRXnzxRQDi4uKoX78+bdq0AWDatGmMGzcOX19fTp48yZ49e3jllVcAWL9+PcHBwZbE7sMPP+TVV18lMDCQlJQUtm7darl9a9OmTXh5edG5c2cA5s6dy5AhQ6hZsyYXL15k/fr1vPHGGwBs27YNgO7duwPwySef0L9/f+rWrUt6ejqrV6+29H798MMP5OTk8OKLL9K3b1+WLFlCjx49CAsLIzMzk88++4x33nkHgL1793LlyhX69+8PwOeff06HDh1o0qQJ169fZ8GCBURFRQGQmJjIb7/9xnPPPQfAypUradWqFQ8//DB5eXl89NFHTJ48GRcXF5KSkkhOTuaFF14AYM2aNWixxsEAACAASURBVDRu3JhWrVpRUlLCjBkzmDBhAp6enhw/fpzExEReeuklAJydi+jRo5C2bc2/dGfM8GDs2Hz8/RVOn3YmNxf69s0FYMMGVwIDFTp0KOL69dO4uSmMGFFAUFAJ5845sXmzK6NHmy/HbNniirs7dOlSCMD8+R4MHFhArVoluLu74Ovry7hx4yxtvqioyDJOatGiRfTt25fQ0FCuXLlCTEwMEyZMACAhIYHs7Gz69u0LwNKlS+natSsNGzbk2rVrLFmyhHfffReA/fv3c+nSJcvYqujoaB577DHCw8Px8fEhKSmJqVOnYjKZOHToECkpKTz//PMArF69mubNm9O8eXMKCgqYPXs2kyZNws3NjaNHj3L06FFLD+batWsJCwujdevWKIrC9OnTiYyMxNvbm+TkZA4cOGB58ubXX39NSEiIZdbGmTNnMmrUKAICAjhz5gw7duywdE9v3LgRPz8/OnXqBMCcOXMYNmwYwcHBnD9/no0bNzJmzBjA/KPpkUcesXwvlTlHmEwlDB2aT4MGJWRkOLF8uRuTJuXdOke4kJlpol+/wlvnCHciIopo1KiYrCwT4G1ps/Y8R8yaNctyjsjNzeXatWuGP0c8+eSTAJZzxN/+9jcef/xx3Z8j1q1bR926dS1DBWbMmMHYsWPx9/fn9OnT7Nq1i5EjR946R2zgscces7TD2bNnM2LECIKCgjh37hybN29m9OjRgPlHubu7O126dAFg/vz5DBw4kFq1apGamkpcXNw9zxGVHTOpaFVq1aqlKIqitGvXrtT7U6dOVZKTk++7/eDBg5UbN24o3bp1K/V+fn6+Mnjw4FLvDRkyRMnNzS13P15eXsq2bduUGjVqKL6+vpbi5uZmWScqKkqz70nNIqKXUZ1WrdqlwPYKS1TUxnLf37077Z7b3auYjynrSy9O92sDWteliHUlvapebv8P9fLyuu+6mvZ0ZGRkUFRUVKYHokaNGmV6Kv7MwIEDWbZsGc8//zzff/99qc8uXbpk0z5v3Lhx39nUJBKJRCKR2IamYzoKCws5dOgQPXr0KPV+jx492Lt3b4XbDR48mOjoaIYMGcJ3331X5vN9+/aV2WfPnj3vuc/7MWfOHJu31TMieonoBDBnjofWIaiCiPUlohNIL6OhRy/Nb5mdM2cOr776KiNGjOChhx5izpw5hIaGsnjxYgCmT5/Of/7zH8v6gwcPZsWKFUycOJH9+/dTs2ZNatasiZ+fn2Wd+fPn07NnT9555x2aNGnCO++8Q/fu3Zk3b57NcQ4bNsx2SR0jopeITgDDhhVoHYIqiFhfIjqB9DIaevTSPOmIjY0lMjKS9957j6SkJCIiIujTpw/nz58HoFatWoSGhlrWHzVqFK6urixcuJBLly5Zyvz58y3r7Nu3j8GDBzNixAh+/vlnhg8fzqBBgzh48KDNcQYHB9suqWNE9BLRCSA4uETrEFRBxPoS0Qmkl9HQo5fm83SAefTrokWLyv1sxIgRpV537drVqn3GxcURFxdX5dhuczsJEg0RvUR0Ajh/XvPfCKogYn2J6ATSy2jo0UvMs5gK6PF+Z3sgopeITiDn6TASIjqB9DIaevSSSYeV3L4HXzRE9BLRCWDMGDGnQRexvkR0AullNPToJZMOiUQikUgkDkEmHVby52nVRUFELxGdAOLjxby8ImJ9iegE0sto6NFLJh1Wcvf06CIhopeITgCCaglZXyI6gfQyGnr0kkmHldx+1opoiOglohPAE08Uah2CKohYXyI6gfQyGnr0kkmHRCKRSCQShyCTDitZsGCB1iGogoheIjoBLFgg5jToItaXiE4gvYyGHr1k0mEltx9ZLBoieonoBPDcc2JOgy5ifYnoBNLLaOjRSyYdVlKnTh2tQ1AFEb1EdAKoU0fMadBFrC8RnUB6GQ09esmkw0rS0tK0DkEVRPQS0QkgLU3MP1cR60tEJ5BeRkOPXmKexVQgNjZW6xBUQUQvEZ0AYmPdtA5BFUSsLxGdQHoZDT16yaTDSsaPH691CKogopeITgDjx+dpHYIqiFhfIjqB9DIaevSSSYdEIpFIJBKHIJMOK9m5c6fWIaiCiF4iOgHs3CnmNOgi1peITiC9jIYevWTSYSX5+WI+4VNELxGdAATVErK+RHQC6WU09Oglkw4r6dWrl9YhqIKIXiI6AfTqJeY06CLWl4hOIL2Mhh69ZNIhkRgSResAJBKJpNLY/Ag6V1dXCgvF/OVVHosXL9Y6BFUQ0UtEJxcvhS9/dqfJaAWPYHDxhvxMhdx0SLySBU4KlJi0DtMmRKwvEZ1AehkNPXrZ3NORmprK9OnTqVevnj3j0S29e/fWOgRVENFLJCeTi0LdpxSaT4WATiZ8w8DVF0xO4BEEAQ/DytOpNH8HAlsas/dDpPq6jYhOIL2Mhh69bE46NmzYwLhx4zh79izr1q3T5SN07UmDBg20DkEVRPQSxck9SCH8TQiJAOe75gUryIac36H4rjFi7oEQNgTqP6dgcjFW8iFKfd2NiE4gvYyGHr1sTjpGjhxJ3bp1iYqKokWLFsTHx3P8+HHeeOMNfHx87BmjLsjIyNA6BFUQ0UsEJ+9QhfC/g1dt8+uSQqjxRzE/T4ef/9fE8XkmjrwHJxbDQ9W8LdsFPwZNRoOzh3ESDxHq68+I6ATSy2jo0cuEnUak9evXjzfffJNu3bpx8+ZNVqxYwccff8zJkyftsXtV8fLy4ptvvuHpp58mJyen3HXc3NwoKBDvKZ8iemnttGjRl/j51a70dvXqNSAi4gyetRSajAIXL/P7uelwdiWUXIOCgrLjNnbvDqf/uOOEDrjTI3L9Vzj9GZQU3nucx6pVLgwdGlHpWO2J1vWlBrY6rVq1i6FDi2w6piPqUsS6AulVVaz5H3obu929smHDBiZPnswPP/yAj48PY8eO5dixY3z11VcEBwfb6zCaMWnSJK1DUAURvbR28vOrzdChRZUuTk6uuFdXaPzanYQj+zQk/xvy0k1MmlTxNOhXD5s48QkU3jC/9n0AHhwGJif993hoXV9qIKITSC+joUevKicdzs7ODB48mISEBBITEwkLC2Py5Mk0aNCAyMhIOnXqxIoVK+wRq0QiNIUlJTw4DFxvXZ28cQ7O/AdKyundKI/cNBOnl0FRrvm1/0NQu6c6sUokEokt2HzLbO3atRk1ahSvvfYaNWvWJCEhgYEDB/J///d/KIr519XHH39MamoqK1eutFvAWrFnzx6tQ1AFEb2M6vT1r+mWMRy56XD689IJx5499/9zzUk1cSZaofHr4OQMtZ6A6ykK2af0ezutUevrXojoBNLLaOjRy+ak49y5cxQVFfHll18yf/58fvrpp3LXS0lJIT093eYA9UJmZqbWIaiCiF5GdAporrAn/RpgHjSasgqK80onCpmZ1iUON341kbpJod5T5tcPDIZjcxSKbugz8TBifd0PEZ1AehkNPXrZfHnlv//7vwkNDeWVV16pMOEA+OmnnwgLC7P1MLqhX79+WoegCiJ6Gc3J2UMh9Jk7r8+vh9xLZROEfv2sn4wvPQH+SDYvu/pA6NNVjVI9jFZf1iCiE0gvo6FHL5uTjvPnz1NSUlLuZwEBAQwbNszmoCSSvxJ1njRP+AVw7RfIOGiHnSomzsVC4U3zy8CW4NdY/4NKJRKJ2NicdCxfvpwHH3yw3M8eeOABli9fbnNQemTZsmVah6AKInoZyck7VKHG4+Zldycnzq8H853sZVm2zL1S+y66aeLit3dehz6LLicOM1J9WYuITiC9jIYevWxOOkymiq8Pe3h4UFxcbOuudUlEhLZzGaiFiF6GcTKVvqzyZGgwhVkV/11FRFR+/oarh+D6WfOyR3UI6VLpXaiOYeqrEojoBNLLaOjRq1IDSevVq1dqWtVWrVrh4eFRah1PT09ef/11zp8/b5cA9UKjRo20DkEVRPQyilPAI+Bd17yc8zt0ejwQuFzh+o0a2ZLIm/htnULTCea7WUI6w5X9+hpUapT6qgwiOoH0Mhp69KpU0jFixAjef/99FEVBURQWLlxYZp3bPSDjx4+3T4Q6ISsrS+sQVEFELyM4mZwV6vS68/rid+D8X/dOBLLu0QtyL/KumMg4oFCjPTi7Q+1u3LqMow+MUF+VRUQnkF5GQ49elUo6YmNj+eWXXzCZTMTGxjJ16lROnz5dap38/Hx++eUXfvvtN7sGqjXlJVgiIKKXEZyCHjM/JRbMs45mn7r/NgsXVm5Mx938vg2qtzYnHUHtIH2PQn6GPno7jFBflUVEJ5BeRkOPXpUa03HixAnWrVtHXFwcI0aMYOnSpaxbt65U2bhxo3AJB8CUKVO0DkEVRPTSu5PJRaF2tzuvL26CigaP3s2UKRVPg34/im6YSN9lXnZyhto9bN6V3dF7fdmCiE4gvYyGHr1sHki6YsUKXU48IpHonaC/3blFNvNnyLnomB6HS7vuuoW2BbhX19+dLBKJRGwqdXnln//8J5999hlpaWn885//vOe6iqLwv//7v1UKTk8cPGiPyRP0h4heenYyOSul7iBJ+976bQ8etHkCYQBK8k2k71Ko+ySYnCCka5V2Zzf0XF+2IqITSC+joUevSp3FPvjgAzZv3kxaWhoffPDBPdcVLem4ePGi1iGogoheenYKbAXuAeblP5LND2mzlosXq/5Q6Cv7zLfNuniax3hkF2nf26Hn+rIVEZ1AehkNPXpVKulwdnYud/mvwIABA5g2bZrWYdgdEb1062RSqHVX70JlejkABgwoYNo0zyqFUJxn4vIehdrdzWM7Dt0of1ZhR6Lb+qoCRnJatOhL/PxqW7Wup+cNcnPNj0HOzv6dMWMGqxmawzBSfVUGPXpVrb9WIpFYjX84eASbl7PPws3z2tw9kr4banYy38nyS04Jzp6+FOde1yQWifb4+dVm6FDrJp6LilKYNs287qpV1iUqEsnd2Nxf6+7ujq+vb6n3nn/+eWbMmEG3bt0q2Kp8xowZQ0pKCrm5uSQmJtKxY8cK1w0JCWHVqlWcOHGC4uJi5s6dW2adl19+2TKXyN3F3d32Ww5XrFhh87Z6RkQvvTrVvKtZp/9Q+e1XrLC9/d5NcY6JjB/Ny0UKBD/W1y77tRW91ldVENEJ7NcG9Ya49aU/L5uTjpiYGBYsWGB5/fe//50vv/ySd955hy1btvDkk09atZ+BAwcyb948pk2bRqtWrUhISGDTpk3Uq1ev3PXd3d25cuUK06ZNu+fTbbOysggJCSlV8vPzKyd5F23atLF5Wz0jopcenTxrKfg1NC/nXYGsk5XfR5s2lZ8GvSIu7wbl1pWVGh2exeSsXaenHuurqojoBPZtg3pC3PrSn5fNSUfbtm3ZvHmz5fW4ceNYuXIl1apVY926dbz99ttW7WfChAksW7aMZcuWceLECd566y0uXLjAmDFjyl3/t99+IzIykpiYmHvOtqYoCunp6aVKVWjatGmVttcrInrp0alUL8duQKn8pZWmTe33PKP8TBN/HDcvu/kHEfBIZ7vtu7Losb6qiohOYN82qCfErS/9edmcdAQHB5OamgpAgwYNCAsL49///jfXr19n2bJlNGvW7L77cHV1pXXr1sTHx5d6Pz4+nvbt29saGgA+Pj6cO3eOCxcusGHDBlq2bGnVNr6+vpbi5uZm+Sw3N7dK8egVEb305uTirRDYyrxclGN+CJst5ObadwxIesKd5ZodB9h135VBb/VlD0R0Avu3Qb0gbn3pz8vmPtWcnBz8/f0B6NSpEzdu3CAxMRGAvLw8fHx87ruPoKAgXFxcyvRCpKenExISYmtonDhxguHDh3P06FH8/PwYP348e/bsoUWLFpw5c6bC7VJTU3FxufOVbN++nejoaDZu3IinpydRUVHEx8fj4uLCE088AcCCBQt47rnnqFOnDmlpacTGxlqeO7Nz507y8/Pp1cv8kI3FixfTu3dvGjRoQEZGBsuXL2fSpEkA7Nmzh8zMTPr16weYH0kcERFBo0aNyMrKYuHChZbZ5Q4ePMjFixcZMMD8j2LFihW0adOGpk2bkpuby5w5c5gyZQpOTk4cOXKEU6dOMWjQIAC++OILwsPDadmyJUVFRcyaNYuJEyfi4eHBsWPHOHLkCC+++CIAcXFx1K9f39JFN23aNMaNG4evry8nT55kz549vPLKKwCsX7+e4OBgS7L44Ycf8uqrrxIYGEhKSgpbt25l1KhRAGzatAkvLy86dzb/up47dy5DhgyhZs2aXLx4kfXr1/PGG28AsG3bNgC6d+8OwCeffEL//v2pW7cu6enprF69mrfeeguAH374gZycHEtdLVmyhB49ehAWFkZmZiafffYZ77zzDgB79+7lypUr9O/fH4DPP/+cDh060KRJE65fv86CBQuIiooCIDExkd9++43nnnsOgJUrV9KqVSsefvhh8vLy+Oijj5g8eTIuLi4kJSXh5FREVJT5j33NGjfqdFO46WK+2yvjR4h8Mx9PT4Xjx51JTHThpZfMl/0KC6/To0chbduau7BnzPBg7Nh8/P0VTp92ZvVqN8t+N2xwJTBQoUOHIq5fP42bm8KIEQUEBZVw7pwTmze7Mnq0eb9btrji7g5duhQCMH++BwMHFhBSq4Sf3NxJLzDhXe8h3vznTA5tW09RURE9e/YEYNGiRfTt25fQ0FCuXLlCTEwMEyZMACAhIYHs7Gz69jWPCVm6dCldu3alYcOGXLt2jSVLlvDuu+8CsH//fi5dusQzz5gfqxsdHc1jjz1GeHg4N2+aZyybOnUqJpOJQ4cOkZKSwvPPPw/A6tWrad68Oc2bN6egoIDZs2czadIk3NzcOHr0KEePHmXIkCEArF27lrCwMFq3bo2iKEyfPp3IyEi8vb1JTk7mwIEDDB8+HICvv/6akJAQ2rVrB8DMmTMZNWoUAQEBnDlzhh07dvDaa68BsHHjRvz8/OjUqRMAc+bMYdiwYQQHB3P+/Hk2btxo6Z2Nj49n3759lvZTmXOEyVTC0KH5NGhQQkaGE8uXuzFpUt6tc4QLmZkm+vUrvHWOcCcioohGjYpvPZfH23LMypwjXF3zadgQBg0quHWOcCM8vJiWLYspKoJZszyZODEPDw+FY8ecqV+/mBdfLMDT08RDDz1kyHPE7cv/t88Rnp6ejBkzxmHniOTkZF544YVb54g1NG7cmFatWlFSUsKMGTOYMGECnp6eHD9+nMTERF566SUA1q1bR926dWnbtu2tc8QMxo4di7+/P6dPn2bXrl2MHDny1jliA4cPH7bEOHv2bEaMGEFQUBDnzp1j8+bNjB49+tY5Ygvu7u506dIFgPnz5zNw4EBq1apFamoqcXFxjBs3DjD/X/zzOeL237W1KLaU7du3K999953SrFkzZd++fcrXX39t+WzYsGHK2bNn77uPWrVqKYqiKO3atSv1/tSpU5Xk5OT7br9jxw5l7ty5913PZDIpR44cUebPn1/u515eXsq2bduUGjVqKL6+vpbi5uZmWWfKlCk2fU96LyJ6ae20atUuBbabi+l7pdk73yttPjQX9+rf3/nsT2X37rQKP4PtypQpG23a7l5l8qc7LbHVH/DWX7K+9ORUqu1Uspi3VfeYd7dBW4+nxyJiG3Sk1+3/oV5eXvdd1+aejv/3//4f3377LUlJSRQUFFiyTIC+ffty+PDh++4jIyODoqKiMr0aNWrUqPIYjLtRFIUff/zxvo/5vXHjBjk5OeV+5uRU9YmZ9IiIXnpy8mt458FuWacg/6rt3dNqaD3kaSI+PQdndy8CWz3BhY2LKcl3bJesnurLXojoBOq0QT0gbn3pz8vmiHbs2EF4eDjPP/88Dz/8MHv37rV8tn37dmbPnn3ffRQWFnLo0CF69Cj99KkePXqU2p89aNmyJWlpaTZvf+TIETtGox9E9NKTU9Bjd5av7K/avo4csf+EfG5OJq4eMc9S5uzuRWDLyt3ubg/0VF/2QkQnUKcN6gFx60t/XlW6T+78+fOcP3++zPuffvqp1fuYM2cOMTExJCYmsm/fPl5//XVCQ0NZvHgxANOnT6dOnTq8/PLLlm1atGgBmAd+BgcH06JFCwoKCkhOTgbgvffeY//+/Zw+fRo/Pz/GjRtHy5YtLdcAbeHUKSuePW5ARPTSi5Orr0LAw+blgmzIOl61/Z06pc4J/8r+b6nRzjyWKLjdU2Qc+FaV41SEXurLnojoBOq1Qa0Rt77051Xlvpfg4GDatGlDp06dyhRriI2NJTIykvfee4+kpCQiIiLo06ePJZmpVasWoaGhpbZJSkoiKSmJNm3aMHToUJKSkvjuu+8sn1erVo1PP/2U5ORk4uPjqVOnDhEREfz44482e94eiCkaInrpxSnwUTDdOkdn/AhKSdVG/t8e6Gdvcn8/w80LJwDwrtMIr7qNVTlOReilvuyJiE6gXhvUGnHrS39eNvd0hISEEBMTQ9euZR9VaTKZUBSl1J0g92LRokUsWrSo3M9GjBhR7v7vxYQJEywj7CUSbVAIan3n1VXb812HcOXARrzrPQRA8GNP8dvFORpHJJFIRMTmpOPjjz+mVatWTJ48mZ9//rlKs30agS+++ELrEFRBRC89OHnVBc9b46Ov/2qejKuqfPGF2/1XspHMpO3Ue2o0zh7eBLZ8ggvfLqYkv/xB1fZGD/Vlb0R0AnXboJaIW1/687I56ejcuTNvv/020dHRdgxHv4SHh5OSkqJ1GHZHRC89OFW/u5fDxsnA/kx4eDEpKepcUy8pyOPq4W3UaN8fZ3dPqrfqxpX9G1Q51p/RQ33ZGxGdQN02qCXi1pf+vGwe06EoChcuXLBnLLrGmhlNjYiIXlo7FSkK1W+FUFII1362z35btlR3CuorBzZaloPbPaXqse5G6/pSAxGdQP02qBXi1pf+vGzu6Vi7di1PPfUU33//vT3j0S1FRWI+6EhEL62dfs1TcPE2L1/7BYrz7DN1tBpaYWENWLVql+X1F5eLuFSo4FW7IXOW/0BNt/Jjz87+nTFjBtslBq3rSw1EdAJ12qAeELe+9Odlc9IRGxvL0qVLcXJyYsOGDVy9erXMOnq8R9hWZs2apXUIqiCil9ZOx3NKLMtXE+2331mzPO23s1sUF7sydOidE1PQYwoNzDM5M/f/irjwTflJx6pVte0Wg9b1pQYiOoE6bVAPiFtf+vOy+fLK9u3befDBB3nzzTfZvHkzP/74o6UkJiZW6fZUPTJx4kStQ1AFEb20dHLxrsa5PAWAgj8gu+JH/VSaiRPz7LezCrj2k/mSEEBgKzA5K6ofU7ZB4+CINqgF4taX/rxs7uko71ZWkfHw8NA6BFUQ0UtLp8BWT3C7n+PqEbDlEfYV4eGhfgJQnGfij2MKgS3B1Rv8H4I/jql7TNkGjYMj2qAWiFtf+vOyOelYsWKFPePQPceOqXzm1QgRvbR0Cmrd07Jsr7tWbnPsmGPuGsg4BIG3xp9Vf1T9pEO2QePgqDboaMStL/152eVpMI0bN6Z9+/Z4eXnZY3e6RKTxKXcjopdWTp61wvCqY36o4I3zkHfZfr0c4LjnXmSfNk/bDuAfDs5e6v66lW3QOMhnrxgLPXpVKekYNmwYFy5c4Pjx4+zatYsmTZoAsGbNGl599VW7BKgXXnzxRa1DUAURvbRyqt7qzpOW7d3LAfDiiw6agrrEROatc5WTy51eD7WQbdA4OKwNOhhx60t/XjYnHf/1X/9FdHQ0hw8f5s033yw1Nfnhw4cZOHCgXQKUSIxCwCOdATBhHpBpZDLuuuvm7uncJRKJpCrYnHRMmTKF5cuX079//zJPlU1OTqZp06ZVDk5PxMXFaR2CKojopYWTd70muAea5z0PdTdRlGPfSysAcXGOm4I6L93EzYvmZe964FFDvUsssg0aB0e2QUcibn3pz8vmpCM8PJwvv/yy3M8yMzOpXr26zUHpkfr162sdgiqI6KWFU8AjXSzLjT3tMlSqDPXrl9x/JTty9yWi6ir2dsg2aBwc3QYdhbj1pT8vm8+OOTk5+Pv7l/tZnTp1uHbtms1B6ZE2bdpoHYIqiOilhdPtSyslxUU09LR/LwdAmzaOnV0wMwlKbs16Xf1RwKROb4dsg8bB0W3QUYhbX/rzsjnp2LNnD2+++Wa5nw0fPpydO3faumuJxFB4h4bjHlATgOunD+PhpE7S4WiKbprISjYvu/mDX0Nt45FIJMbH5qTjf/7nf2jXrh0HDx5k3LhxKIrCgAED+Oabb4iIiGDatGn2jFNzRPO5jYhejna6+9JK5s87VTvOtGmOn4K61CWWR9U5hmyDxkGLNugIxK0v/XnZnHQcOnSIJ598Eh8fHz766CNMJhNTp06lcePG9OnTR5eTklSFcePGaR2CKojo5VAnk4nARyIAKCkq5I9je1Q71Lhxjp+COusEFOWYl6s1Byc3+19ikW3QOGjRBh2BuPWlPy+bZyQF2LlzJ02bNiUsLIyaNWuSkZHB6dOn7RWbrvD19dU6BFUQ0cuRTt6h4bhVqwFA9ulDFOfeUO1Yvr6On4JaKTaR+bNCjXbg7AbVHsYyh4e9kG3QOGjRBh2BuPWlPy+bko6goCBGjRpFREQEtWubnzb5+++/s2PHDj799FMyMzPtGqQeOHnypNYhqIKIXo50Crw1gBTg2s8/qHqskye1mQ0y8xDUaGderv6o/ZMO2QaNg1ZtUG3ErS/9eVU66XjiiSeIi4vDz8+P4uJiMjIyMJlMNGnShO7du/P222/z7LPPkpCQoEa8mrFnj3rd5loiopc9nBYt+hI/v3s/vl1RFD67VMSNEvN1yg8jo/Bw+gf16jUA7Ph42Vvs2VOljkmbufEb5F8F9+rg1whc7fxrV7ZB46BVG1QbcetLf16VGtMRFBTEmjVryMrKYuDAgfj7+1O7dm1q1aqFv78/gwcP5ubNm3z11VcEBgaqFbMmvPLKK1qHoAoietnDB+Mg6gAAIABJREFUyc+vNkOHFt2zjI4yJxwAmcdh5LBihg4twsnJtcrHL49XXslXZb/3x2R+Yi5gcrL/tOiyDRoH7dqguohbX/rzqlTSMXLkSJydnenQoQNxcXHk5uZaPsvNzWXt2rV07NgRV1dXRo4cafdgJRI9EdDiznLmz9rF4QiuHr6zrNZdLBKJRHwqlXT07NmTzz//nNTU1ArXuXDhAsuXL6d3795VDk5PrF+/XusQVEFEL4c4mRQCHjEvlhRB1nH1D7l+vTo9KNaQn2HixnnzslcdyCi03yUW2QaNg5ZtUE3ErS/9eVUq6QgPD2f37t33XS8hIYHw8HCbg9IjwcHBWoegCiJ6OcLJpz64+ZmXs05CcZ76E4IFB2t758DdvR3JOfabDlu2QeOgdRtUC3HrS39elUo6qlWrxuXLl++73uXLl6lWrZrNQemR9u3bax2CKojo5Qinuy+tXHPQpZX27bWdgvraT3emRT+RWwIm+yRasg0aB63boFqIW1/686rUUGR3d3cKCwvvu15RURFubmI+jVAiwaQQ0Ny8WFIIfzjg0ooeKLppIvukQrWmcKMYfMNacP1sktZhSf6Es4c37kF1cHLzwOTkQmF2BvmZl1CKCrQOTSKp/C2zTZo0oajo3tnuQw89ZHNAeuXDDz/UOgRVENFLbSefB0pfWinJd8yzVj780MMhx7kXV49Atabm5eqPdrdL0iHbYFVR8K4P3/9RTLNJ/8EjuG7ZNUpKyLl4ij+S95GZtJ38q7/bdCQ9tEE1ELENgj69Kj0NenR0ND/++OM9y/Lly9WIVVNeffVVrUNQBRG91HYKfOTOsqMurQC8+qr2tyv+cQyKbt20FtA8ApNL1Xs0ZRu0EZNCQAuFhydC+Bvw882SchMOAJOTE96hD1Gn1wiaTYombMg/8Ax5oNKH1EMbVAMR2yDo06tSPR0jRoxQKw7dI9q8I7cR0UtVpz9fWklW71B/JjBQ+0F8SpGJa0cVgtuau/GrPdyeaz/trNI+ZRusPN71FOoPMN9JdDclhQXk/H6GnLSz5in5FQW3gBp4hoThVSsMAJOTM4EtuxLQPIJLu2IpUqxvV3pog2ogYhsEfXpVKulYsWKFWnHonpSUFK1DUAURvdR08n0AXG89ziDrhOMurQCkpNj8fEa7knkEgtual6s/2qPKSYdsg9Zjclao3RNCOpsnarvN9V/hvx51ZsYbz1JSUP5D2dyq1SCwVTdqdnoOV58ATM7O1Or6AisvF+FRE/LS79+W9dIG7Y2IbRD06SVmC1KBrVu3ah2CKojopaZTwF2XVhw9IdjWrfqYI+F6CvjcegSHf+O/4eLtX6X9yTZoHa5+Ck1GQ62udxKOnFQ4tRROLoKmXk4VJhwABX9c5tKOLzg6YyipW5ZTcmtg6bUiCH8T/JvevxdDL23Q3ojYBkGfXjLpsJJRo0ZpHYIqiOilmpNT6UsrWQ68tAIwapROrqcrJh7yNJ86TM7OBLboWqXdyTZ4f7zrKYSPM88PA+YJ6S5uguR/Q/ZpE2B9j1tJYT5p36/k+LzR5KSanwru7A4NX4LgdvdOPHTTBu2MiG0Q9Oklkw6JxEruvrTyRzKUFDju0oreCPe6c+oIfLS7hpGIj19jhcaj7twxlX8NTnwCl3aYUEpsb4N5l3/jxMLxNPY078PkBPUHQI32Yo7bkOgDmXRYyaZNm7QOQRVE9FLLSYsJwe5m0yb9dG0HuZq4eetXsk9oOO4V3DVhDbINVkxAC4WGI8D51k1C2WcheT7kpNon4S0pzKdPgDNpO+68F/pMxT0eemqD9kTENgj69JJJh5V4eXlpHYIqiOilipOTQkAz82JxgeMvrQB4eenrF2jm4W2W5eqtbO/tkG2wfAKaK4QNBqdb42cyf4bTn0FRjn172EwmE6mb4Pc71UnoM1CtnDEeemuD9kLENgj69Kr05GB/VTp37mzVc2eMhoheajj5hoGrj3k5KxlKCh1/aaVz5yJ279bPL83MpO3U7fs6Jidnqj/and/jo23aj2yDZfFvqvDAEDDdSjiuHITf4gCl4nYXFtaAVat2VfpY9eo1AM7we7z57pjbA1UfGAKnPlW4ef7OMfXWBu2FiG0Q9Oklkw6JxAoCNb60okcKr2eSffow/k3+hntgLXwaNOPGuV+0Dsvw+DRQeHDonR6OjB/vn3AAFBe7MnRo5Z+NcncSkboZ3Pyh+qPmSzoPDoPj8xWKbvx1xy9J7Iu8vGIlc+fO1ToEVRDRy95OJieFandfWjlh191bzdy5+puC+urdl1ge7WHTPmQbvMPVQoWGw8HpVh5w9Qic+4r7Jhx2QzFxbi1cP2t+6eYPD75o/hsAfbZBeyBiGwR9esmkw0qGDBmidQiqIKKXvZ18HwRXb/OyVpdWAIYM0d8Du/74ZTfF+eZ50QNadLFpWnTZBs24eFfj/64W4XLrMnzWSTi3BsclHLdQik2cXQUFf5hf+4ZBnSfNy3psg/ZAxDYI+vSSSYeV1KxZU+sQVEFEL3s7lZoQ7Ce77rpS1KxZot3BK6CkMI9rR83jCFw8fQho1rHS+5Bt0Dw1+YPD3uN6sfn1zYtwdiVVuiW2KhTdMHF2pXk+EDDPgOrbUNFlG7QHIrZB0KeXLpKOMWPGkJKSQm5uLomJiXTsWPGJKyQkhFWrVnHixAmKi4sr7D4aMGAAx44dIy8vj2PHjvHMM89UKcaLFy9WaXu9IqKXPZ1Md9+1kg/ZJ+2260pz8aIu/lzLkHHwzm15QX/rXentZRuEek+/gW+YeeBQQTaciXbsFPvlcfO8iYvf3Xn9wCA4l6bPNlhVRGyDoE8vzVvQwIEDmTdvHtOmTaNVq1YkJCSwadMm6tWrV+767u7uXLlyhWnTpvHTT+X/7GzXrh1r1qwhJiaGFi1aEBMTQ2xsLG3btrU5zvXr19u8rZ4R0cueTr4NweXWpZU/NLy0ArB+vT7vGrhx7ih5GeaTm1+j1rgFhFRq+796Gwxq24ca7fsD4Ayc/Q8UZutj4OblPZB1yrzs5g+HFH22waoiYhsEfXppnnRMmDCBZcuWsWzZMk6cOMFbb73FhQsXGDNmTLnr//bbb0RGRhITE0NWVla560RGRrJ161ZmzpzJyZMnmTlzJt9//z2RkZE2x/nGG2/YvK2eEdHLnk53X1q5puGlFYA33tDvFNQZP262LAe16VWpbf/KbdC7flNCnxlned2tmjM3L+gj4QDMA0tjofCm+aVPuIlqzcSbq0PENgj69NI06XB1daV169bEx8eXej8+Pp727dvbvN/HH3+8zD63bNlSpX1K/nqYnEtfWsnS8NKK3rl6KB6lxDwgoXqbXqUfgSopF1ffQB4c9gFOLubeg/Td63jYW3/fW2G2ifP/d+d1/WfB2VO8xEPiGDRt4f+/vTOPb6pK+/g3ado0pS0UWmhLoaWyV5YCgyBYGKSooCIwgiwKiK8CM4OAAkJd5vM6LCMvoMywDZuioODAiMgiIpuyiAU6Mpa9tqUtrd2ge9Ik5/0jJVAokLZJ7831fj+f82lyc+/N88t5cvL0LM8JDAxEp9ORlZVV6XhWVhbBwdXror2V4ODgGt3T19cXPz8/e/HyujkTf9++ffe40n1Roi5nafJriX0lwbVEEGZp/wPdt0++XdvlBblcP/8jAPqAJvi3jHb42t+kD2o0tBjxBl7+jQAouHSatK9W1oFlNSP/J8ivSMHi6QfNnpLWHmejRB8EeeqSRXIwISpHzRqN5o5jdXHP9PR0dLqbH8n+/fv58MMP2blzJ88++yz9+/dn79696HQ6+vXrB8DSpUsZNmwYTZs25erVq2zZsoVXX30VgIMHD2I0GnnsMVt388qVK3n88ceJiIggJyeH9evXM2PGDACOHDlCXl4eTz1l+zavXbuWmJgYWrVqxfXr11m+fDmzZ88G4MSJE6SlpTF06FAANmzYQLdu3Wjfvj2lpaUsXryY2bNno9VqOX36NBcuXGDEiBEAfPrpp7Rr147OnTtjNps5ePAgr732Gt7e3vz888+cPn2aMWPGALB161bCw8Pp1q0bAHPnzmXKlCn4+flx/vx5jhw5wosvvgjYxg6DgoLsvUnvvfceL730Eg0bNiQpKYlvvvnGvuPh7t278fHxoU+fPoBtLfmoUaNo0qQJaWlpbN++3d4teONL07+/Lc32smXLGDx4MGFhYWRlZbFp0yamTZsGwKFDhygpKbHX1apVq4iNjSUyMpK8vDzWrFnDzJkzATh69CjZ2dkMHmwbS1+3bh29evWiTZs2FBYWAtD3eTMZFV8Rn1wrcXG25YKffOJFdLSFqCgLZWUaFi3yZtasUnQ6SEjwwGwuJi7Otox082YvWre2EB1twWqF+fMNTJ9ehsEgSEz0ID5exwsv2IZNyssLiY0tp3t325KB+fO9mTzZSP36gosXPbh+Hft9d+zwpGFDQa9eZgoLL+LlJRg/3kRgoJXkZC179ngycaLtvl9/7YleD337lgPwwQfeDB9uIiTESknJFfz8BFOmlFX4vCdmMwwYYDt3xQo9gwaV07y5lexsLR9/7FVhv4aYmBgKCgoYNGiQ7XM5cATa9QCgx6g/8+1fJ/DGG28AcPz4cTIzM+0Tuj/88EMeeugh2rVrh8Fg4IcffmDOnDloNBpOnjxJUlISzz77LACbNm2iQ4cOdOjQAZPJxMKFC5kxYwZeXl6cOXOGM2fO2JcGfv7550RGRtK1a1eEEMybN4+pU6dSr149zp49yw8//MC4ceMA+OKLLwgODqZHD5vNCxYs4JVXXiEgIIBLly5x4MAB/ud//geAnTt34u/vzyOPPALA4sWLef755wkKCiI1NZWdO3fah4T37t1LmzZt7D5bVRvx9IxFXDC0BIDSAgY3LsJr9htoNFZGjzYSEWElJ0fL+vVezJhRVtFG6MjL0/DUU+UVbYSemBgzrVpZuH7d1r7d8I8TJ3SkpWkZOtRU0Ubo6dbNTPv2FkpLNSxe7M3s2aVotVBWlkXLlhZGjDBVtBFetGtnoXNnC2Yz/O1vBl57zQgGwfdWPRathsBu8CvFtG3b1i3biCeesK0BvtFGdO3alS5dulSrjVi6dClxcXEAxMfHk5KSwrBhwyraiE+Ijo4mKiqKsrIyFi1axKxZs9DpdCQkJHD27FlGjhxZ0UZspnXr1kRHR2O1Wpk/fz7Tp0/HYDCQmJhIfHw8L7zwAgDbtm0jLCzMPj9x/vz5TJ48mfr163Px4kUOHz7MhAkTKtqIHTz44IP2z2XhwoWMHz+ewMBAkpOT2bNnDxMnTqxoI75Gr9fTt2/fijbiA4YPH05ISAjp6els3bqVKVOmVLQR+zGbzQwYMKCijVhRrYUaGkCyfjJPT0/7j8QXX3xhP/7+++/TuXNn+wdwNw4cOEBCQoLdoW6QkpLCkiVLeP/99+3Hpk6dytSpU4mIiLjjPj4+Pnz55ZeMGjWK0tJS+3Gj0YjJZPsixsXFMXfu3BqolDdK1OUMTRs+OcTiy2Z0BrCUQcL/Ot7T8f337ejdu/qbs9zvuri4UubONTjt/Wpz7caNOkaPjql0TOOho2PcZ3j6BmA1m/jPu8OxlBbe916/NR/0CWtD2z8uReuhQ1itXFgzk8JLpwHYuPFwjbKKguv87lZe+IuJRB9bj1ugDva8HgtW919Gq0QfhLrTdeM39Omnn6akpOSe50o6vFJeXs7JkyeJja2cyTA2NpajR4/W+L7Hjh27454DBgy47z2LioooLCy0lxsBh8pvjxSjQFfx+y6HoRV3QFjM9gylWp0XjaIfldgi+aHVG4gcFYfWw9aDlnnwM3vA4Q6ElVsorliFmWOGoB4KG2dRcTmSz1pavHgxL730EuPHj6dt27YsXryY5s2bs3KlbXxz3rx5fPTRR5Wu6dSpE506dcLX15egoCA6depEu3bt7K9/8MEHDBgwgJkzZ9KmTRtmzpxJ//79K/V8VJdly5bV+Fo5o0RdztB0sfTmf295MtlrZdkyvdQm3JecH6ufs+O35IPNn5mCd2BTAIpSz9Z4kzypWL5MT+rNTmmaDhiPrl596QxyEkr0QZCnLsmDji1btjB16lTefvttEhISiImJYeDAgaSmpgIQEhJC8+bNK12TkJBAQkIC3bp1Y/To0SQkJLBr180sNseOHeO5555j/Pjx/PTTT4wbN44RI0Zw4sSJGtt5Y1xPaShRV201aTw8uVxqG3U0l0LBBWdYVXsGDy6X2oT7UpaVQlFKIgA+TVtRr1nb+17zW/HBhtH9CexqGwe3lBWTtGmufcWPuzB4cDnFqRpy4m3PdT5+NH38RWmNcgJK9EGQpy5ZTCRdsWIFK1asqPK18ePH33FMo7l/V/fWrVvZunVrrW27QVhYmNPuJSeUqKu2mvxbd8VYMdNJTkMrYWHuMXae/cNX+Ia3ByDo4cEUb773Dnm/BR/UNwwhfOir9ucp297HlHe1rs2qNTd8MG0XhP4OTAICfzeQ7ONfUZJ+UWLrao4SfRDkqUsWQYc7cPsSXKWgRF211RTQsY/9sZy2sc/Kkrxj0iHyEg7QbNBEdPX8adipL2lfrcJcfO2u57vaB1es+Ax//9AaXVtQkMGkSc9V+7pbNWk8dESOehMPvW39dU78XvIS9tfIHqm54YPmIg2DIhrx719y0Gi1PDpjFSMCPRz6hxBq/rm6CiW2gyBPXWrQ4SCbNm2S2gSXoERdtdGk0XnSoL1tSZ+chlYANm2q/g6uUiDMJrJP7CLk98+h1XkR2H0gmQfuXieu9kF//9AarwjZuLFmwcqtmkIHjKNec9swU1lOGqnbl9bonnLgVh/s3SSITcdzMDSBqybBlP8zk5fgWNBR08/VVSixHQR56nKPf51kwO3LcpWCEnXVRpN/627oDL4AXPvZts23XJg2rUxqExwm+/iXiIqllI17PgXauzc1SvZBv5ZdCO5jy5FjNZeTtGkuVmPpvS6VNbf6oIdWw5Uvb77W9DFbFl93RIk+CPLUpQYdKiq30LDT7+2P5TS04m6Y8rO4dvYYAF4NGtOgfS+JLap7dPXq0+K5N9BUBFzpe9ZSkiajrjMnUHBRY98QTt8Igh6S1h4V+aMGHQ5y6NAhqU1wCUrUVVNNWk9vGkTZhla8NVAgs3lxhw6512ho9tGbO1w27nX3jIVK9MGDhw4RMXymPc359fM/kvXdvyS2qvZU5YPpN1dJE9IftHr36+1Qog+CPHWpQYeD3C/LmruiRF011VS/3UN4eNkygrU0aGQ1tAJQUiIve+5HwaVTlP5qW/ru/0BnvJtEVHmeEn2wtGk0DSpSwpcX5fPL5r9BLbd2kANV+WBJuobcBNtjT18IjrnjFNmjRB8EeepSgw4HuZGrX2koUVdNNTXs3M/+uK2P/L4aTzwh/zwdlRCCX4/ezCTV+OGqcwYozQcNIZF4dHna/vyXze9hLsqX0CLncTcfzNgDN1KONIkBna97BVhK88EbyFGX/FpWFRUJ8PCuR/22tk2UTAW5NPVyr14FuZJ78hssRtt/W426xuLhXU9ii1yL1tObyFFvIjS2pjXz8L8oOF/zpITugjFPQ/Zx22MPPYSqGfBV7oIadDjIqlWrpDbBJShRV000NYjqhVZnWw6Y/9MhtA7mG6hLVq2Sfxr027EaS8iN3wuAh5eBwIcG3XGOknyw2dOTMTQJB6A4/SLpu9dIbJFzuZcPXv0WLLaNjQnsAfpG7tPboSQfvBU56lKDDge5fQM5paBEXTXRdOuqlbyEA840x2nExrrZ8EoFWUf/bV8+2+SRYWg8PCu9rhQfDOgQQ1BFUKWxlJO06a8Ii3vW2d24lw+aizRkHbY91npA6IA6MsoJKMUHb0eOutSgw0EiIyOlNsElKFFXdTXpfPzxb9UVAGNeJsWpia4wq9ZERrpHGvTbMWance3nIwB4+QfSqGvlhlAJPugV0ITwP7xmfx5lvIQxO01Ci1zD/Xww8zCUF9keN+wE3o3do7dDCT5YFXLUpQYdDpKXlye1CS5BibqqqymgYwwaDw/btf+RZy8HQF6e/IZ8HCXz4Gf2x8F9hoPmZtPj7j6o0XoQOepNe1K5vIQDeGf9LLFVruF+Pmg1asiqWKWp0dqW0LoD7u6Dd0OOutSgw0HWrFHW2OwNlKiruprcYWgFYM0a95vTcYPiK+couGxbV+kd1IyAB3vbX3N3H2z6+AT7BndluRmkbFvCWjfXdDcc8cFfj97S29ERvJvIv7fD3X3wbshRlxp0OMjMmTOlNsElKFFXdTR5+gfi26IjAKW/plJ69bKrzKo1M2e6Txr0qsg88Kn9cUj/56Fisq47+6B/m+4E970lzfnGv2IpK3ZrTffCER+0lmvIPGh7rNFCqBv0dii3vuSnSw06VH7TBHSMsaepzpfx0IoSKLgQT1HqWQB8QiIJePARiS2qHZ7+jWgxYpb9efru1ZSknZfQIvmQfQzKC22PG3YCQ7D8eztU6gY16HCQo0ePSm2CS1CirupoatTl5r9hch5aATh61L3SoFdFxt6P7I9DY18AjcY9fVCjpcXIOXj6NgDgWuIxsr7ban/ZLTU5gKM+aC3XcPWWr1Oo/BZRVEK59SU/XWrQ4SDZ2dlSm+ASlKjLUU3ejcOpF9YGgOK085RlX3GlWbUmO9t9J5LeoODCjxSl2FYHGYJbENCxr1v6YNPHxuP/QGcATNeySd7yXqXX3VGTI1THB7OPg6nA9jigAxhC5dvbodz6kp8uNehwkMGDq07h7O4oUZejmm7t5cg9+Y2rzHEagwcrI+dDxt4P7Y+bPv4iTw2++2ZwcqTBg48Q0m8UAMJiIWnTXMwlBZXOUeL3Cqrng8Ks4er+m8/l3Nuh3PqSny416FD5baLR2IMOYbHIfmhFSRRcPEnBpdMAeDcKJdWrqcQWOY5343BajLg5Oe/KVyspSj4joUXyJucEmK7ZHgdEgU+YfHs7VOoGNehwkHXr1kltgktQoi5HNPlFdsKrQWMArp8/gbn4mqvNqjXr1rnvktnbSdu5yp6l9KwmFI+KHBdyxsO7Hi3H/i8eeh8Ack/t49cj26o8V4nfK6i+D7pLb4dy60t+utSgw0F69eoltQkuQYm6HNHUqMvN1i/3lPyHVgB69TJLbYLTKEm/SO6pfQBovX0J7f+8xBbdB42GiBGz8A4KA6Ak4xIpWxff9XQlfq+gZj6Y8yMYKzbZbdAO6jWTX2+HcutLfrrUoMNB2rRpI7UJLkGJuu6nSeupJ6BjDADm0iKuJR6rC7NqTZs2FqlNcCrpX6/DWm7bIazxw0MwhMgvZfMNmg4YT0CUrQE3lxRwacNf7LZXhRK/V1AzHxSW23o7ZLgni3LrS3661KDDQQoLC6U2wSUoUdf9NDWI6mXvIs//6RDCbKoLs2pNYaH7r165lfLr2Vz9diMAGg8PwodOsycMkxOBDz1JyKOjARBWK0mb5mLKu3rPa5T4vYKa+2BuPBgrMnLXbwMZRnntI6Tc+pKfLjXocJClS5dKbYJLUKKu+2m6dcMxdxlaAVi61FtqE5xO5qEtlGalAOAb3t6+S6tcSCq1Ej5kiv156pf/oOBC/H2vU+L3Cmrug8Ki4eq3N58fK5RX0KHc+pKfLjXocJC4uDipTXAJStR1L02efg1v2VH2KkXJ/60rs2pNXFyp1CY4HWEpJ6Zerv152MCX8QoIltCim9RrJtiZb0GjtW0GmHlwM9lHtzt0rRK/V1A7H8w9CcaKqk41CnzDo5xkVe1Rbn3JT5cadKj8pmgY/aj9RyT31D4Q8pvU9lujoeUa2Sd2A7YVIi2ee6PSLrRSoG8oaDkezBXukZuwn7TdqyW1yd0RVg0Zt/R2hA4YK50xKpKhBh0OEh9//y5Vd0SJuu6lqVHXm7PYbqyecBfi490/DXpVxMfHc2XHcowV8yT8WnQguO9zktnj1UDQ+mXwrFjFW3g5geTN71UrQFXi9wpq74N5p6CsorfDv1VXfCM6OMGq2qPc+pKfLjXocJCUlBSpTXAJStR1N031mrXBp2KFRFFKIsactLo0q9akpCjz65qSkoLVWMIvny1AWG2rI5oOGIdfyy51botnfUHrV0Df0Pa8oQ4ubXgHYaleNlglfq+g9j4orBqu3hLry6W3Q7n1JT9dymzFXMCwYcOkNsElKFHX3TQFPvSk/XH2DzvryhynMWyYe6yyqS436qso+b+VVrM8MOYt9A1D6swOfSNB24ng3cj2vCwbhgXqsJQWVfteSvxegXN8MPc0NLCNcOLfMhrfyI61vmdtUW59yU+XGnSo/CbQ6g007PR7ACxlxeT/56C0BqlUSca+Dfa8KToff1qO+ysePv4uf19DiKDtZNDfCDhy4Pwq8PWQ3xJet8eq4SF/D/vTprHy6O1QqRvUoMNBPvnkE6lNcAlK1FWVpoad++GhNwC2SYHW8rK6NqvWfPKJl9QmuIRK9SUEv3w2n9JfUwEwBEfQesJ8PLzruez967ezBRyefrbnpZlwfiWUF9Q84FDi9wqc54NtDRrKsm3Dm34PdMavYsdeqVBufclPlxp0OEh0dLTUJrgEJeqqSlNQ94H2xzluOLQCEB2trIykN7i9vixlxVxaH4epwDbjsF6ztrR6cR4eBj/nvrFGEPx7Qcux4FGxpUhRCpxbUbuAA5T5vQLn+aBWoyFj38f256ES93Yot77kp0uZ0+FdQFRUFF988YXUZjgdJeq6XZMhtCX1mrUFoDjtAiXpF6UyrVZERVlQWFUBVfugMTeDC6tn0GbiEjzr1cc34kHa/envXFw3B2NuRq3f09Nf0GIE+Le6eSzvP5C8BazltR9SGTnyBZ59dnq1r2vWLAK4VOv3dxXO9MG8hP2EPDoaQ+Pm+EV2xK9lNIUVuw/XNUpsB0GeutSgw0HKytyvO94RlKjrdk2VejlOuGcvB0BZmTLnF9zNB8uyUriweiatJyzA0y/asgjdAAAgAElEQVQA76BmtPvzMlL+vZT8/xyo2ZtpBUEPQdPHQGfLhI+wQsZeKvYHcc5nrNMZGDGi+pujff+9p1Pe31U41QeFlav7PiZylC2BVWjsWM5LFHQosR0EeepSh1ccZNGiRVKb4BKUqOtWTVpPbxpGPwqAxVRK7un9d7tM9ixapLw06HBvHyzNuMTZf/yR0sxfANvk0gdGv8kDL/wv3o2bO/4mGkFAR0H7KRA+5GbAYboGF1bD1f0anBVwAJSVuW4OipQ42wfz/nPQngbfr0UHe7bgukaJ7SDIU5cadDjIrFmzpDbBJShR162aAjr2QWewZXnKSziI1VgilVm1ZtYs5aVBh/v7oCk/i3PLXyXvp0P2YwEP9iJq+loeeP4vBHSIQVuxgd+taLQe+DRtxZECCx1mwgNjwCf05us58fDzEii87PweJG/vYqffUw443QeFVRZzO5TYDoI8danDKw6i0ynzo1Kirls1BT2kjKEVAAVWFeCYD1rKikn65H/J7xBD8yFT8PQNQKPVEtDhEQI6PIKwWjBd+xXTtWzQaPDQ++Ad1AytpxcnCq32pbAAxVcg9UsoTnHdcJVGo8z0+q7wwfyfDlH66BgMwRH4RkTh37qbQ5vqORMltoMgT13ys0imJCQkSG2CS1CirhuaDCGR+EY8CEDJ1SSKU89KaVatSUjwuP9Jbkh1fDD/zGGuX/iRoIeepEnMs3j526IJjdYDfcOQuyYTE1YouAiZh6DwEjhzKKUqzGZ5z82oKS7xQWElY98GHhjzNmDr7ajroEOJ7SDIU5cadDjI2bPu/YN1N5So64amJr2H2o9lH98hlTlO4+xZZQYd1fVBq7GUrMOf8+uRf+MX2Yn67XviGx6FvlGofShNWCyU5aRRejWJP/R5lMWvWTEX1d1EXItFqXXlGl35Zw5TcjUJn5BIfMPb49+mOwXnT7jkvapCie0gyFOXOqfDQUaOHCm1CS5BibpGjhyJrl4D+wRSc0khuSf3SmxV7Rk5Uplp0Gvqg8JipuDiSa5s/wdnl04i4Z3BnJzzBPFvxHJy9gB+XvQiSZv+SidfjzoNOAD0evmtGnAGLvNBIbh6y9yOsMdfBE3d1ZkS20GQpy416FBRJEE9n0Krs2VPzDmxC6tJmT8CKpURZhNYrVKboVID8v/7HcVpFwDwadqKgI59pTVIxSXIIuiYNGkSSUlJlJaWEh8fT+/eve95fkxMDPHx8ZSWlnL58mVeeeWVSq+PHTsWIcQdRa/X19jGzZs31/haOaNEXZs/30rjnk8Dtm72X4/KKzlOTdm8WZlp0JXog0ajMpc3u9QHhSB99xr706aPjUejrZthKiX6IMhTl+RBx/Dhw3n//feZO3cu0dHRfPfdd+zevZtmzZpVeX5ERAS7du3iu+++Izo6mnnz5rF06VKGDh1a6bzr168THBxcqRiNxhrb2bp16xpfK2eUqKtZryfx9LPtTZ7/3+8wXftVYoucQ+vWykyDrkQf9PBQal25VlfBxZMUVCQI8w5sSmD3J1z6fjdQog+CPHVJHnRMnz6dtWvXsnbtWs6dO8e0adO4cuUKkyZNqvL8iRMnkpqayrRp0zh37hxr165l3bp1vP7665XOE0KQlZVVqdQGOeawdwaK1NX6Zk9Z1vdbJTTEufxW9l5RAjpdudQmuIS68MH03avtj0P6v4DWs+Y91I6iRB8EeeqSNOjw9PSka9eu7N1beZLf3r17efjhh6u8pmfPnnec//XXX9OtW7dKa5J9fX1JTk7mypUr7Nixg86d77+Loa+vL35+fvbi5XWzK9Gq0HFipenybdGBQg/bxmDFqecoTkmU2CLnobCqsqM0HwQQQpkp6+uiqoqvnCf/zGEAvPwb0bjXEJe/pxJ9EOSpS9Ils4GBgeh0ujt6IbKysggODq7ymuDg4CrP9/T0JDAwkMzMTM6dO8e4ceM4c+YM/v7+vPrqqxw5coROnTpx6dLdN1NKT0+vFLjs37+fDz/8kJ07d6LVaomLi2Pv3r3odDr69esHwNKlSxk2bBhNmzbl6tWrbNmyhVdffRWAgwcPYjQaeeyxxwBYuXIljz/+OBEREeTk5LB+/XpmzJgBwJEjR8jLy+Opp54CYO3atcTExNCqVSuuX7/O8uXLmT17NgAnTpwgLS3NPqS0YcMGunXrRvv27SktLWXx4sXMnj0brVbL6dOnuXDhAiNGjADg008/pV27dnTu3Bmz2cz8+fN57bXX8Pb25ueff+b06dOMGTMGgK1btxIeHk63bt0AmDt3LlOmTMHPz4/z589z5MgRXnzxRQC2b99OUFCQPVh87733eOmll2jYsCFJSUl888039rk3u3fvxsfHhz59+gCwZMkSRo0aRZMmTUhLS2P79u388Y9/BGDfvn0A9O/fH4Bly5YxePBgwsLCyMrKYtOmTUybNg2AQ4cOURr9B3v9lfxnLyNHjiQyMpK8vDzWrFnDzJkzATh69CjZ2dkMHjwYgHXr1tGrVy/atGlDYWEhAHFxtuyL8fE6UlK0DBtmm7n/ySdeREdbiIqyUFamYdEib2bNKkWns+UxMJuL7ddu3uxF69YWoqMtWK0wf76B6dPLMBgEiYkexMfreOEF27BfeXkhsbHldO9u27Nj/nxvJk82Ur++4OJFD9av19vvu2OHJw0bCnr1MlNYeBEvL8H48SYCA60kJ2vZs8eTiRNt9/36a0/0eujb1/bf9wcfeDN8uImQECslJVfw8xNMmVJW4fOemM0wYIDt3BUr9AwaVE7z5lays7V8/LFXhf0aYmJiKCgoYNCgQQCsXr2a3//+97Rs2ZL8/HxWrVrFG2+8AcDx48fJzMzkmWeeAeDDDz/koYceol27dhQX27J3zpkzB41Gw8mTJ0lKSuLZZ58FYNOmTXTo0IEOHTpgMplYuHAhM2bMwMvLizNnznDmzBlGjRoFwOeff05kZCRdu3ZFCMG8efPw9i4mLs7K2bMe/PCDjnHjbJ/LF194ERxspUcP2+e9YIE3r7xiJCBAcOmSBwcO6DAYioiLi2Pnzp34+/vzyCOPALB48WKef/55goKCSE1NZefOnfbe2b1792I2e9rraulSb4YNM9G0qZWrV7Vs2eLFq6/aPu+DBz0xGuGxx2yft9VqYvRoIxERVnJytKxf78WMGbZzjxzRkZen4amnbOeuXasnJsZMq1YWrl/XIISwv+eJEzrS0rQMHWrz2Q0b9HTrZqZ9ewulpRoWL/Zm9uxStFooK8uiZUsLI0bYzv30Uy/atbPQubMFsxn+9jcDr71Whre34OefPQgPtzBmjInCwou0bWshPNxKt27mijbCwJQpZfj5Cc6f9+DIER0vvmisaCM8CQoSPPywGYNBg6en593biCM/wIO9QaMl4olxFJ3Zz3NDnnZKG1FSUsITT9iGbVatWkVsbCxarZZJkyZVq41YunQpcXFxFW1EPCkpKQwbNqyijfiE6OhooqKiKCsrY9GiRcyaNQudTkdCQgJnz561ryzZvHkzrVu3Jjo6GqvVyvz585k+fToGg4HExETi4+N54YUXANi2bRthYWF07969oo2Yz+TJk6lfvz4XL17k8OHDTJgwoaKN2MGxY8fsNi5cuJDx48cTGBhIcnIye/bsYeLEiRVtxNfo9Xr69u1b0UZ8wPDhwwkJCSE9PZ2tW7cyZcqUijZiP2azmQEDBlS0ESvs32tH0ACSpc4LCQkhIyODnj17cvz4cfvxOXPm8Pzzz9OuXbs7rjl//jzr169nwYIF9mMPP/wwR44cqTIgAdBoNJw6dYrDhw/bA4Jb8fHx4csvv2TUqFGUlt5M82s0GjGZbF/E6dOns3jx4lrplSNK0uUVEEyHWR+j0WoxXc/hzILRCEv1N90C2LjxMKNH1+za779vR+/e1V8ff7/rpk8vY/HiOyco1vT9anPtxo06Ro+OqdF73o6rfbA2dVlTnVu37mbYsOoPC0hRl9W57lYfrI2tjnyu4X94naCKOR2ZhzaTtvOfNXovR1BSO3grdaXrxm/o008/TUnJvbeakHR4JScnB7PZfEevRuPGje86ByMzM7PK88vLy8nNza3yGiEEP/74I61atary9RsUFRVRWFhoLzcCDgCDweCIJLdDSbqC+wxHo7W5dPax7TUOOOSKwaDM1NpK8sEbKDUNel36YMY3H2Ett7XBjXsNwesu2WadgRJ9EOSpS9LhlfLyck6ePElsbCxffHFzWWNsbCzbt2+v8ppjx47ZhyBuMGDAAOLj4zGb7/4j07lzZ86cOVNjWxMTlTM34FaUokvnG0Dg72z/FWksJn495v4ZSG8nMVGZWS6V4oO3YjYrM9mzs3wwMjKCjRsP3/e8769b+LHIilbnxdC/bKSP569MmvScU2y4FSX6IMhTl+TfjMWLF/Pxxx8THx/PsWPHePnll2nevDkrV64EYN68eTRt2pSxY227D65cuZI//elPLFq0iNWrV9OzZ08mTJhQKfPa22+/zfHjx7l48SL+/v5MmTKFzp0728cAa0J8fN3uBVBXKEVXk0f+gNbTNvG3KGEfltJCiS1yPvHxkn9dXYJSfPBWLBZPJBy5dhnO8kGLxdOhIS+tXtBhJnj6waUyQbRv1XP9aosSfRDkqUvyJbNbtmxh6tSpvP322yQkJBATE8PAgQNJTU0FbPM+mjdvbj8/OTmZgQMH0rdvXxISEnjrrbeYMmUK27Zts5/ToEED/vnPf3L27Fn27t1L06ZNiYmJ4ccff6yxnTcm8igNJejyMPjR+GFbMjBruYlBrfwltsg13JhwqjSU4IO3o9c7eQt4mVDXPmg1akjfc/P5oesW0Dj/Z0uJPgjy1CWLf51WrFjBihUrqnxt/Pjxdxw7fPgwXbt2vev9pk+fzvTp051mn4q8adJ7KB56HwByftyNPspPYotUVFScRU48NH4YfJrCr+XQqGssufFfS22WSg2RvKfDXbi1J0VJuLsuD4MfTR6xLVOzWsxkHtri9pruxrZtykyDrsT6MpmUmQZdEh8UGq58dfNp08cnoNU7d4KkEn0Q5KlLDTocJCwsTGoTXIK76wruMxwP73oA5P64B1N+pttruhthYfJL9OMMlFhfWq0ys8dK5YOFlzXk/9f22Mu/ESF9nbt7qhJ9EOSpSw06HORGMhal4c66dPXq27MVWs0mru7fCLi3pntxI2mY0lBifSk1DbqUPpi28+YPVpM+z6IPdN4PqhJ9EOSpSw06VNyW4N+PxKOimzXnh12K2dhNRUXlToy5Grr42n6ytDovwofcmehRRf6oQYeDzJ8/X2oTXIK76vIKaELjh23pia3lRq4e+NT+mrtquh/z5ytznoAS66u0tJ7UJrgEqX2wh58WY14mAP6tutAwur9T7qtEHwR56lKDDgeZPHmy1Ca4BHfV1fSxF9HqbJPasr7bSnlBjv01d9V0PyZPVuaSWSXWl1KXzErtg55aDanb/25/3uypiXgYar9aTYk+CPLUpQYdDlK/fn2pTXAJ7qjLENqSRl1s/+GUF18n8+BnlV53R02OUL++8pJNgTLrS6tV5qRfOfjg9bPH7bvQevoGEDbwpVrfU4k+CPLUpQYdDnLx4kWpTXAJ7qir2ZMT7Y+v7vsES1lxpdfdUZMjXLyozDToSqwvi0UWKZCcjlx8MPXLZViMto3Fgh56Et/wqFrdT4k+CPLUpQYdDnL48P33CXBH3E1XQIcY/FtGA1CWm0H28Tv3WHE3TY5y+LAyf8iUWF/l5Z5Sm+AS5OKD5ddzSN+z3v48fNg0NB41t02JPgjy1KUGHQ4yYcIEqU1wCe6kS+upJ+yWXo4rO5YjLHcuTXQnTdVhwgRlzulQYn15eytzToecfPDXo19QnHYBAENwC0Jjx9b4Xkr0QZCnLjXoUHEbgn8/En1AEwCunzvB9cRjElukoqIiGcJK8r8WYTXb/vEI7juCeuHtJTZK5X6oQYeD7NihvK3SwX10eTduTnDfEQBYzeWk7lh213PdRVN12bFDmV32Sqwvk0kvtQkuQW4+WJpxiYxvNgCg0XrQ4rnZaL2qv6xXiT4I8tQljwE6N6Bhw4ZSm+AS3EKXRkP40Gk3l8ge/hxjdtpdT3cLTTWgYUPpVw44gxUrPsPfP9T+XKczYTbff0+PgoIMJk16zpWm3UFkZAQbN1Z/XDww0B/Ic75BEiNHH8w89BkN2vXANyIK70ahNHtqEilbl1TrHsptM+SnSw06HKRXr14cPHhQajOcjjvoCuw+EL/IjgCU5aSTse/je57vDppqQq9eZg4elNd/mjXB3z+U0aNvptOOizMyd+79O103bgy97znOxmLxrGSro+zeXeACa6RHlj5otfLL5gW0n/pPPPQGgh56kmuJx7h+9rjDt1BumyE/Xerwioqs8WrQmLCBL9ufp2xbgjCbJLRIRUVFbhhzM7jy1Qr784g/vIaunvxyVKioQYfDLFy4UGoTXIKsdWk0RAyfic7gC0DOj3sovHT6vpfJWlMtWLhQmWnQlajL1zdSahNcgpzrKueHnVyr6N3w9GtIi+feAI3GoWuV22bIT5cadDjI+PHjpTbBJchZV+NeQ+w5OYz5WVzZsdyh6+SsqTaMH6/MHh4l6iopufucI3dG7nWV/Pn/UV6YD0D9Nt0J6TfaoeuU22bIT5cadDhIYGCg1Ca4BLnqMoQ8QNgT/2N/nrzlvTsyj94NuWqqLYGBykytrURdVqu8f5xritzrylyUT9KmvyKsFgBCY8fi36rrfa9TbpshP11q0OEgycnJUpvgEuSoS6v34YExb6P1vLmhW+HlBIevl6MmZ5CcrMyvqxJ1eXgYpDbBJbhDXRVeTiBj70cAaLRaIke/ib5hyD2vUW6bkSy1CXcgfw+SCXv27JHaBJcgR13hw6bhHRQGQHHaedJ2ra7W9XLU5Az27JHZqgEnoURd3t6NpTbBJbhLXV09sIlrFckDdT7+tBz3Llr93QNB5bYZ8tOlBh0OMnHixPuf5IbITVeTmGdp1LkfAObSIi5/8m6Vqc7vhdw0OYuJE+WTgtqZKFFXcXGK1Ca4BLepKyFI+nQepVm2ejAEtyBy1JugrfonT7lthvx0qUGHimzwb9OdsIG3zOP4fCGmvKsSWqSiouKuWI0lXProLcwlhQA0aNeD8GdeldgqFTXocJCvv/5aahNcglx0eTeJIHJUHBqtbevsjG82cO2/39foXnLR5Gy+/to9urarixJ16fVBUpvgEtytrow56Vze8A7Witw+QT2eJOTRMXecp9w2Q3661KDDQfR6Ze6lIAddXg0a03rCAns+jvwz35Gxb0ON7ycHTa5AobIUqkveqzxqijvWVWHSf0jecjNfRdPHxtO419BK5yi3zZCfLjXocJC+fftKbYJLkFqXzsefVhMW4NXA9p9h8ZVz/LJ5AYia7/EgtSZX0bdv9ea2uAtK1GU05kptgktw17rKS9jPla9W2p83H/xHArsPtD9XbpvRV2oT7kANOlQkw8PHn9YvL8TQJByAsuw0Lq6bg9VUJrFlKioqSiPr8Of2HWnBlio9qMeTElr020Td8M1BPvjgA6lNcAlS6dJVBBw+oS0BMBXkcGHNLMzF12t9b+XWlXxTUNcGJeqqV68FcFFqM5yOu9dVxjcfofXyJrjPcADb7tWeegW3GfLTpfZ0OMjw4cOlNsElSKHLq0Fj2kx6v1LAcX7la5jyM51yf+XWlTKzXCpRV2lphtQmuAQl1FXazlVcPfCp/XmzpybzyB/nO7xPizshx7ZQ7elwkJCQe2e0c1fqWpchOJJWL86zz+EwFeRwftVrGHPuvVfFihWf4e/v2NbmBkMRjz46DoDmzYNJTa1+MNOsWQRwqdrXuZKQEPlMToyMjGDjxsM1uvb2z9ZRXTV9Tynq0mp1k3wW1UROPlgb0nevwVpupOmAcQBkN2pPi+dmk/z5/ylqF2s5/m6pQYeDpKenS22CS6hLXQ2ietHiudl4VGQGLMtO48KaWQ71cPj7hzJ6tNmh9xk3TsOHH9rO/f57P0aPrv7mW99/L7+lgenp8umYtFg8Ha6P27n9s3VUV03fU4q69PDwBorq/H1djZx8sLZc3fcx5qJ8mj8zBY3Wg0bRj+Id2JRLG96h/HqO1OY5BTn+binHg1zM1q1bpTbBJdSJLq2W0AHjaDn2f+0BR3HqOc4tn+K0IZVb2brVy+n3lAOqLvfB2ztYahNcgtLqKvv4V1ze8Bf75PV6zdrSfspKhzaJcwfk+LulBh0OMmXKFKlNcAmu1uXVoDFtXllMaP/n7cdyT+/j3MppTpk0WhVTpihz9Yuqy30oLk6W2gSXoMS6upZ4lN7G/2DMtc3D8fQLoNWEBTR94iU0Hu49GCDH3y016FBxDRoNgQ89SdT0Nfi16ACAsFi4snMVv3w6X1HjpioqKu6Nn7WYxL//kevnTgC23WlDfj+Sdn9ejqFiwruKc1CDDgfZv3+/1Ca4BFfoMgRH0uaVRUQMm4aHdz0AjHmZnFsxlaxDW5z+frezf7/85mM4A1WX+6DXN5LaBJegxLoCWztoKSng4vo5XPlqJVaLbe6QT+gDtP/zcsKenIhW7yOxldVHjr9b7t13VIeYzTWbNCd3nKnL078RIf2fJ6j7QPseKgDZJ3aT9tUKLGXFTnuve6HQqlJ1uRXK/H9OmXV1SzsoBFmHP6fg0mlaDJ+BT2hLNB4eBMc8S8PO/bi6bwM5P+5BWNzjg5Dj75YyvxkuYMCAAVKb4BKcocuzfiBhT06kw6yPadzjKXvAUZaTzoXVM0n51//VWcABMGCAe6Zqvh+qLvfBaMyW2gSXoMS6gjvbwdKMS5z9+x9J/3o91nLb8mcv/0aED53GgzM3EHjbP1ZyRY6/W2pPh0qN8Y14kMDug2gY3Q/tLROuLMYSrn67kazvtiIsymykVFRUlI2wmLn67SfkntpHsycnEtDhEQD0AU2I+MNrhPQbRdbhf5F7eh+WUuUtj3YVatDhICtWrJDaBJdQXV2e/oE06hpLYLfH8Q4Kq/SatdzIr0e3k3nwM5etTHGEFSvkt7OiM1B1uQ/16oUDl6U2w+kosa7g3u2gKT+Tyx//BZ+wNoTGvkCDdj0A0DcMofkzfyZs0Mvk/ecQOT98RVHKz3VlskPI8XdLHV5xkEGDBkltgktwRJch5AFC+o2i7eSldJzzKWFPvFQp4DCXFJDx7Sf8NH80aTtXSRpwAAwapMzeFVWX+1BW9qvUJrgEJdYVONYOlqSd59L6OM7+409cP/+j/bjWU09gtwG0/eNSHpy5gbAnJ+LbogNopf95lePvlvSfihvg5eXFuHHj8PJSVmKcKnVptRhCWxLU82laPDebjnM+I2raP2n6+AR8I6LQ3PJFKrh4iqRP5/PT3OfI+Ho95qJ8CVRUxstLw7hxD+Dlpax9FFRd7oOXl4YWLYIUpQmUWVdQ/fa9OPUsF9e+wX8XTSDr+22YSwrtr3kHNiU45lnaTnqfTm/9ixbPzSbwoUF4Nw6v871d5Pq7JYvhlUmTJjFjxgxCQkL4+eefmTp1Kt9///1dz4+JiWHx4sVERUWRkZHBe++9x6pVqyqdM3ToUN59910eeOABLl++TFxcHF988UWN7NPr9fTr1w+9Xo/JpJz8Ej6NgvFvGU2T3kPRNAjG0CQCn9CW9qyhVVGa+Qv5Zw6TE7/XJdlEa4ter6Vfv1bo9VcxmSxSm+M0VF3ug16vpWXLcPT6FMVoAmXWFdS8fS/LSubKl8tI27WagI4xBHZ7HL8WHdF42CaYetarT6Mu/WnUpT9g6xEuSkmkNOMypVm/UJqZTFn2FZethJHr75bkQcfw4cN5//33mTx5MkeOHOGVV15h9+7dtG/fnitXrtxxfkREBLt27WL16tWMGTOGXr16sXz5crKzs9m2bRsAPXr0YPPmzbz11lv8+9//ZsiQIWzZsoXevXtz4sSJupZYt2i0eHjXw9O3ATrfBnj6BqDzDbA99wtA36AJXgFN0DcMRuupZ9Lm0zR5/H/uejtruZHCywlcO/sD188dx5SfVYdiVFRUVOSNMJvIO7WPvFP78PDxp37b7jRo/zD12/wOj1tye+h8/GnQrod9TgiA1WLGdO1XTHmZGPMzMeVlYirIxVx8DXPRNcqLr2MuyrenaVcCkgcd06dPZ+3ataxduxaAadOm8dhjjzFp0iTmzJlzx/kTJ04kNTWVadOmAXDu3Dm6devG66+/bg86pk6dyjfffMOCBQsAWLBgAX369GHq1KmMGjWqTnT5tuhgS4yl0aDRaG3Lq7RaNBoNaDxswxQabaW/Go224hzb+RqdJ1qdV9V/Pb3Qenrj4e2Dh3c9tHoDHvp69+ylcARjfhbFKYkUpSRSnPozJRmX3WZNuoqKioqUWEoK7AGIxsMTn6at8I2IwjeiA74tHsSzXv1K52s9dHg3CsW70b130LaWGzEXF2AxlmA1lWIxllb8LcFqLMNqNiGsFoS5HGExIyxmvHQebIpPpUG3J9AXFyEsFoTVjLBawWrBdD2b4tSzrvw4qkTSoMPT05OuXbvag4Mb7N27l4cffrjKa3r27MnevXsrHfv666+ZMGECOp0Os9lMz549WbJkyR3nTJ069Z72BAUFUVpaan9uNBopLy/HYDBgNpsxGAxYLI51K7Ye/hqG21Z31A3ivmdYyo2Y8rOwFubywrAnWb7gL1xLvYgxOxWLsaTSuQa9FyD9mKBGI/Dxub82g0FU1JXAYhEIYXHoutup6XW1ufZe192uS862Vufae+mSm62OUh1Nzni/2l7r6HXO+m5V5z1vx9YOODczaE3ad0cROckU5iRTGL8TAM8GTTA0CcfQuDneTcIxNG6GZ4Mm6CoyN98VvRfoA6v9/ssPXaT5oJerfO1a4lF++WxBla9VF4PB8X92NTjyK+UiQkJCyMjI4OGHH+bYsWP247Nnz2bs2LG0bRfxVzYAAAnaSURBVNv2jmvOnz/Phx9+yPz58+3HevbsydGjRwkJCSEzMxOj0ci4ceP49NNP7eeMHDmS9evX4+3tfcc9GzVqxObNm52sTkVFRUVF5bfDiBEjyM3Nvec5kg+vAAhROe7RaDR3HLvf+bcfr849c3NzGTNmDFartdLxGz0dKioqKioqKnfHYDDcN+AAiYOOnJwczGYzwcHBlY43btyYrKyqJyxmZmZWeX55ebld8N3Ouds9b1yjoqKioqKiUn1KSkrufxIS5+koLy/n5MmTxMbGVjoeGxvL0aNHq7zm2LFjd5w/YMAA4uPj7Zvb3O2cu91TRUVFRUVFpW4QUpbhw4cLo9Eoxo8fL9q2bSsWL14sCgsLRfPmzQUg5s2bJz766CP7+REREaKoqEgsWrRItG3bVowfP14YjUYxdOhQ+zk9e/YU5eXlYubMmaJNmzZi5syZwmQyie7du0uqVS1qUYta1KKW33iR3AAxadIk8csvv4iysjIRHx8vHnnkEftr69evFwcOHKh0fkxMjDh58qQoKysTSUlJ4pVXXrnjnsOGDRNnz54VRqNRJCYmiiFDhkiuUy1qUYta1KKW33iR3AC3KwMHDhTHjx8XJSUlIjs7W2zdulVym5xVvLy8xOnTp4UQQnTq1Elye2pTwsPDxZo1a0RSUpIoKSkRly5dEn/5y1+Ep6en5LZVp0yaNEkkJSWJ0tJSER8fL3r37i25TbUpb7zxhjhx4oQoKCgQWVlZ4t///rdo3bq15Ha5QqcQQixZskRyW2pbQkNDxccffyxycnJEcXGxOH36tOjSpYvkdtWmeHh4iHfffdfePly+fFm89dZbQqPRSG6bo+WRRx4RX375pUhPTxdCCDF48OA7znnnnXdEenq6KCkpEQcOHBDt27eX2m7pPzh3KkOHDhW5ubnilVdeEa1atRKtW7cWw4YNk9wuZ5X3339f7Ny5UxFBx2OPPSbWrVsnYmNjRYsWLcRTTz0lMjMzxcKFCyW3zdFyY/hxwoQJom3btmLJkiWisLBQNGvWTHLbalp2794txo4dK9q3by8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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FqZi45dOUNKC"
      },
      "source": [
        "### Initial guess of data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 505
        },
        "id": "PW_61-jwUMNX",
        "outputId": "00a35365-80d9-4517-d7b1-0a069a01ef3d"
      },
      "source": [
        "## Initialize the parameters\n",
        "w     = 0.5                         # 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)                   # Initial standard deviation\n",
        "\n",
        "print('The initial guess for mu are: {}'.format(mu))\n",
        "print('The initial guess for sigma are: {}'.format(sigma))\n",
        "\n",
        "# Values to sample\n",
        "xx = np.linspace(-8, 11.0, num = 200)\n",
        "yy = w * norm.pdf(loc = mu[0], scale = sigma, x = xx) + w * norm.pdf(loc = mu[1], scale = sigma, x = xx)\n",
        "\n",
        "# Plot the initial guess for the density\n",
        "fig, ax = plt.subplots(1, 1)\n",
        "sns.lineplot(xx, yy)\n",
        "sns.scatterplot(np.array(x), np.zeros(len(x)), hue = cc_true)\n",
        "plt.xlabel('xx')\n",
        "plt.ylabel('Density')\n",
        "plt.legend(['Density guess'])\n",
        "plt.show()"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The initial guess for mu are: [6.52666313 0.62053546]\nThe initial guess for sigma are: 2.6412606675636803\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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OnDlzGDdunFBFR+X373b49hhKwKM3i/G8hJMkrPs/2SeQuhuN/P0pSkmgKCWBlN1rDUNNQyNxC4nAqVmHKvej6Fw80bl44hbS1bhPKi+nNOcaJVmplF6/RnlxARUlRZSXFlFRWoxKrUGl1aG2MWxaR3d0bt7oXL2xcfVCo7O7Y3wV+jLyL540FBp/HKIkI7lWfjXJnbkoSIoj/oPnafa3mbiFdEWl0dB0yCR0zp4k76z/l6mcbg2BiH4WUXRMmDCBadOm4e/vz+nTp5kyZYrxS6Q6oqKiWLhwIW3btuXq1au8++67LF++vEqbyZMnM2HCBAIDA8nIyOCbb75hxowZlJSUmFunzvy1J8EU2Nra4uvrW2XI7IwZM9i6dStr1qwBYPfu3Rw4cIDNmzfz6quvcubMGRo1asTAgQPZvHkzR4/e/b/ULl268OCDD7Jr1y6uXbtGREQE3t7exMfHA4behspcunSJiIgImjZtSn5+PllZWUiSREVFBatXr2bu3LmcP3+egwcP3vG8H374ITNmzOD8+fP88ccfvPjii7i7u1fp/bgxUmfr1q1kZ2fz9ttvVxkqfDf/06dPM3/+fL755hsuXrxIkyZN6Ny5Mxs3bgTg/fffZ//+/cTGxuLu7k6fPn2M3qKQnHznLzr/B0fR+KGbi1NlxO4kceNC47BUS+avbmU56aQf2EL6gS2o1BocmrT+czjofTg2aYXWoeqMnSqNBlsPf2w9TPMFUV5aTEFiHHkXT5KfcJL8pHgkfd2n2b9b7sxNeXEB51e/TuOHovHvMxIA/wf/jtbJlcRNi+p1f4/cbuZGRD/Zi47hw4ezaNEiJk6cyP79+xk/fjzbt28nNDSUy5dvncwnKCiI77//nk8++YRRo0bRvXt3li5dSnp6Ops2bQJg5MiRzJs3jzFjxhATE0OrVq1YvXo1AC+99FJD6tWKG6NETMmAAQNITU2lrKyM7OxsTpw4waRJk/jss8+qfDEPHDiQ2bNn8+mnnxpn19y7d2+VGz3vRG5uLlFRUUyZMgUXFxcSExN5+eWXjdP4lpaWYm9/8z/G9957j88++4y4uDgcHBwICgoy9jKsXLmSWbNm1ahb8Z133sHPz481a9ZQXl7Of//7X3bu3FmlqJg7dy7BwcH873//Iycnh9dff71KT8fd/MvLy/H09GTNmjX4+vqSkZHBpk2beOONNwDDsN25c+fSpEkTcnNz2bFjh3CTnt0osKqj0UPRNHpwlPFx8q7VpOxe2xBhmYQ7uUkV5Ya5Q5LiSN2zDgCdux+OTVrh0Lgldt5N0Hn4Y+vud9tRJLejvLiA0uvplGSnUpSSQGHKBYquXqA4M9mkIz3u5NdgSBUk71hJaU4GgYP/iUqtxjviEYB6FR4W4WZGRPW77br3DbEdPHhQWrp0aZV9cXFx0pw5c6ptP2/ePCkuLq7KvmXLlkkxMTHGxx9++KG0e/fuKm3ee+89ae/evdUe08HBQdq9e7fk4OBQ7fNTp05tkPfCz89P1lxYiltkZKRUWloq+fj41Po8KpVK+uOPP6S33nrLYv0a6vfJlNusWbOq9+71lBT+7o/GzbfHUNljNZVbbTeNnaNk59NUcgxoIzm3uF9ya9td8gh7UHLv0FNyDe0mubTsJDkFd5DsfJtKatvqP2ss2c9Um/t9vaVOc3cZf2cCh0wSxk303N1uu9t3aOVN1p4OGxsbOnXqxLx586rs37VrF5GRkdW+plu3buzatavKvp07dzJ27Fi0Wi16vZ5ff/2VUaNGGYdeNmvWjIEDB/LZZ5/dMR4nJ6cq9xmUlJQIv3qoJaHT6QgICODtt99mw4YNVaZNvx2BgYH079+fX375BVtbW/75z3/SrFkz1q1b1wAR39t4d32UJgPHGR8nfruY9AOmuUHQGikvLqjRWi/3Otkn9pAABP9tBiq1Bp/IwZTlZ1tV75hC3ZG16PDy8kKr1d7ShZ+WloafX/Uz6/n5+VXb3sbGBi8vL1JTU1m/fj3e3t78+uuvqFQqbGxsWLp0Ke+8884d40lOTkarvfmW/PTTT6xevRqtVmuMJzc3F5VKhbOzoSv12rVruLu7Y2NjY7yEcWMYaV5eHpIk4eJiuAacnp6Oq6srOp0OvV5PZmYmvr6Gu9Tz8/MpKSkxnicjIwNnZ2dsbW0pLy8nPT3d+FxBQQFlZWW4ubkBkJmZiaOjI3Z2dkiSVOX9KywspKSkBHd3dwCysrKwt7c3XupITU3F19cXlUpFcXExhYWFeHgYJj27fv06Op0OBwcHY1sfHx/UajUlJSXk5+fj6elpbGtjY4Ojo6MxJ15eXmg0GuOcHJXfQ7VajZOTk/E99PDwYOTIkSxcuJDjx4/z8ssv4+fnR15eHoDx/U5PT8fNzQ0bGxv0esP9AuPGjTNOKBYXF8eIESO4fv06Wq0WFxcXdDod5eXlZGRkGN/v6t5DJycnbG1tqaio4Nq1a1Xew9LSUmPbrKwsHBwcqrzfGo0GPz8/ioqKKCoqMr6H2dnZ2NraVnkPAwMDmTVrFnFxccTGxvL0008DsGnTJpo0aUKXLoYFtebOncvEiRNxdXXl3Llz7N27l7FjxwKwdetWPDw86N69OwDz588nOjoaLy8vLl26xI4dO3j++ecBQ1Fua2trHJ3zwQcfMHz4cPz9/UlOTmbjxo1MmjTJ+Duv1+vp378/AMuWLWPQoEF4eHjw3HPPsXbtWl566SWuaT055tDB+LfSsug8SRcOMGLECFq0aEF2djbLly9n+vTpABw8eJDU1FSGDBkCwOrVq4mIiCAkJISCggIWLVrEzJkzUalUHD16lISEBIYNGwbAunXraN++Pe3bt6e0tJT58+czbdo0dDodp06d4tSpU4wcabhX4OuvvyY4OJhOnTohSRJz5sxhypQpODo6Eh8fz6FDh4zrEW3evBk/Pz88PDyYNWsW8+bNY/z48bi7u3P+/Hn27NnDuHGGomrbtm24uLjQo0cPwDCEevTo0Xh7e5OUlMS2bduYMGECYPinSavV0qdPH8AwpHro0KE0btyYlJQUNmzYwOTJkwH4+eefKSkp4aGHHgLg448/5uGHHyYoKIiMjAxWrVplnKdm//79ZGVl8eijjwKGy5BRUVG0bNmSnJwcli5dyowZMwA4fPgwV65c4YknnsDDw4OAgADCw8MJDQ2lqKiIhQsXMmPGDNRqNceOHePs2bOMGDECgC+//JKQkBA6duyIXq/nnXfe4eWXX8bOzo7Tp09z7NgxRo0yXE7buHEjTZs2JTw8HIDZs2czadIknJ2dOXPmDPv372fMmDEAbNmyBW9vb+M/lP/9ZgFNh78CQOP+z2BbUcLfuxmmbt++fTsODg707NkTMNw3NXLkSHx9fbly5QpbtmzhhRdewMPDg4gIw1wwffsaRhgtWbKEwYMH06RJE9LS0li3bp3xcucvv/xCYWEhAwYMAGD58uX069eP4OBgsrKyWLFiBa+8YogpJiaG9PR0Bg8eDMCnn35K9+7dad26NXl5eSxevJhZswxzoMTGxpKYmMjQoUMB+PzzzwkLC6Nt27YUFxezYMECXn31VbRaLcePHyc+Pp6//e1vAKxfv55WrVoRFhZGRUUFc+fO5aWXXsLe3p6CggICAgIs/jPixt91TZGtS8bf31+SJEnq2rVrlf0zZ86U4uPjq33NmTNnpOnTp1fZFxkZKUmSJPn6+kqA1LNnTyklJUUaO3as1K5dO2nIkCFSYmKi9Nprr92xa8jHx0dydnY2bjqdToKG6w6vSdeUtW4iu9XWzxovr3Tu3Nn4s32jFlLY2/8zdo83HjBO9vhM5SbiZsl+vj2GGn+POs3bJbm07CSMm+i5q7zV5vJKzWdQMgMZGRno9fpbejV8fHxuewNjampqte3LysqMc1y8/fbbrF27lpUrV/L777+zefNmZs6cyYwZM+64vkl+fj55eXnGraEvrdzoERERkd1AfL8b/9Vondxp+cz/GYeRZh3fQ/KOFXKGVm9uuImKJful7dtI6l7D5H8qtYbgv79224nQqsOS3UyBiH6yFh1lZWUcPXqUfv36Vdnfr18/YmJiqn3NgQMHbmnfv39/YmNjjd3tDg4OtwzRLC8vR6VS1WlRNXMsxKZw72Ktv08qtYbmo/5tnP4//9JpLm54B2UZc4X6cGXbcq7HGT7vtQ4utPjH26grzY2iIB6ydssMHz5cKikpkaKjo6U2bdpICxculPLy8qTAwEAJkObMmSN99tlnxvZBQUFSfn6+tGDBAqlNmzZSdHS0VFJSIj3xxBPGNm+88YaUk5MjjRgxQgoKCpL69u0rnTt3Tvrqq6/q1DU0ZcoUydHR0ezvhUajkb2bTHEzr5+jo6M0ZcoU2eOt7ebh4SEFPDrB2BXeYeZXktbJXfa4TOUmdwz3up/a1kFq+/Knxt+v4JHVXwq3RjfRcwe1u7yC3MEC0oQJE6SLFy9KxcXFUmxsrNSjRw/jc6tWrZL27NlTpX1UVJR09OhRqbi4WEpISJDGjx9f5XmNRiP9+9//ls6dOycVFhZKiYmJ0kcffSS5urrW6Q1r2rSp9Morr5i98LCWXzDFrW5+jo6O0iuvvCI1bdpU9nhruw1+YZbxC+H+OTskx8AQ2WMy1TZ69GjZY1D8kGy9Gksd39xi/D3zinhEGDfRc2c1Q2ZvsGzZMpYtW1btc9HR0bfs27t3L506dbrt8crLy3nrrbd46623TBJfYmIi69ev59lnn0Wj0dyy1oepCAoK4tKlS2Y5ttyI7AZ391OpVFRUVLB+/fp6TzXf0Ni4epMW0MP4+PLWpRQkiTPjamBgoNwhmBVr8SvJSCbxmwU0H/0GAIGPvUBBUjxFKRdu+xprcasrIvpZRNFhDSQmJpp9xb/nnnuO//73v2Y9h1yI7AYC+6nUBP9tBnq1YV2grJN7ST/wncxBmZb09HS5QzAr1uSXfWovafu/xbf746htdAT/bSZxi59H0le/RIQ1udUFEf1qsJi6+Dg4OPDdd9/x2GOPUVgo39Lb9vb2d11R1VoR2Q3E9fPr9ZRxArCS7DTiFj1HeVG+zFGZFlFzdwNr81NpbAj554c4NDbM2ZG69xuu/K/6nnBrc6st1uJXm+9QWUevKFTFkteFqS8iu4GYfna+QTTq/w/DA0ni4pdzhSs4QMzcVcba/KTyMhK+mkdFmWHKAr+oJ3FuEVZtW2tzqy0i+ilFh4KCwi2o1BqajXgFtVYHQFBpEvmXTskclcK9QnHapSrzvwQ9+TJqnZ2MESmYCqXosCD27dsndwhmQ2Q3EM/Pt+dwHJu0BqAoLZG0H8VdF0O03P0Va/VL+3UTeReOA2Dr4U/jh8bc0sZa3WqKiH5K0WFB5Obmyh2C2RDZDcTys/VsRKO+hrUepIpyLm14h7zr2TJHZT5Eyl11WK2fJHHpmwVUlJUA4NP9cRwDQ6s0sVq3GiKin1J0WBCDBg2SOwSzIbIbiOXX9IkpqG0Ml1XSft1EweUzQvn9FZHdwLr9SjKvkrxzFQAqtZqmQ6eC+ubXljW71QQR/ZSiQ0FBwYhHWF9cWhrmwCnJSuXqrtXyBqRwz5P260YKrpwBwME/GJ9ug2WOSKG+yD6bmdxbLadwNdvm4+Mj+3uhuN27fmpbe6nDaxuMM0K6tukilJ/IuRPdzzGgjfH3suObWySto5swbiLkzmpWmVWoSu/eveUOwWyI7AZi+Pn3HonOxROA7FP7yPnjsPE5Efxuh8huIIZfweU/yDiyHQCtvRONBzwLiOF2J0T0U4oOC6JFixZyh2A2RHYD6/fTefjjG/UkABX6Ui5vW17leWv3uxMiu4E4fle2r0T/5zwx3l0G4BjQWhi32yGin1J0WBDZ2eKOEBDZDazfL2DQeOOcHGl7v6E0K6XK89budydEdgNx/PT52Vzd9ZnxceCQSWQJ4nY7RMldZZRp0LGcadA1Gg3l5eWynd+ciOwG1u3n3CKM1s+9B0Bpbia/z/8HFSVVp162Zr+7IbIbCOanVhM6eTkO/sEAJG1cyLVD22QOynxYS+6UadCtlOnTp8sdgtkQ2Q2s2E+tJuDRicaHydtX3FJwgBX71QCR3UAwv4oKLm/5yPiw+eP/RG3rIGNA5kWo3P2JUky3ltoAACAASURBVHQoKNzDeEc8YvyvsSDpDzJ/+0HmiBQU7kxewgmyTuwBoEytwy9qmMwRKdQGpeiwIA4ePCh3CGZDZDewTj+1rT2N+v3D+DjpuyUgVX+11Rr9aorIbiCmX/L2lVSU6wHwjRqG1tFN5ojMg4i5U4oOCyI1NVXuEMyGyG5gnX6+DwzFxsnwYZ15/CcKkuJu29Ya/WqKyG4gpl9JVgoZB/8HgMbWHv8H/y5zROZBxNwpRYcFMWTIELlDMBsiu4H1+WnsnfH9s1taKi+/68yj1uZXG0R2A3H9rv74ORrJcJOld9dH0bn7yRyR6RExd0rRoaBwD+LXawRaeycAMmJ3UJKRLHNECgq1Q5+fTdOSywCotTY06v+Pu7xCwRJQig4LYvXq1XKHYDZEdgPr8tM6uePT/XHAMBHY1d13X7bemvxqi8huILZfzKq56AsMK7F6hvXF3q+ZzBGZFhFzpxQdFkRERITcIZgNkd3Auvz8H/w7Gp0dAOkHtlKWk37X11iTX20R2Q3E9usS1oGUPesAwyq0jR8eI3NEpkXE3ClFhwUREhIidwhmQ2Q3sB4/nZsP3hGPAFBeUkTKni9r9Dpr8asLIruB2H4hISFci9lM6fVrALiFRuLYNFTmqEyHiLlTig4LoqCgQO4QzIbIbmA9fo36PY1aawPAtV83oc+v2TTL1uJXF0R2A7H9CgoKkPRlXP1hjXFfowdHyRiRaRExd8o06FjONOgKCubE1rMR7aatRqXWoC/M49Q7oyj/cwEtBQVrRqXW0O6VNdh6GEawxC2eQOGVszJHde+gTINupcycOVPuEMyGyG5gHX5+vZ5CpdYAkLZ3Q60KDmvwqysiu4HYfjfcpIpyUn++eanQv48YvR0i5k4pOiwIlUoldwhmQ2Q3sHw/G1dvPDv1B0BflM+1mC21er2l+9UHkd1AbL/KbhlHdlJ63XBTtHu77tj7BcsVlskQMXdK0WFBHD16VO4QzIbIbmD5fn49hxvv5UiP2UJ5ce2uFVu6X30Q2Q3E9qvsJpWXkfrLeuNjEWYpFTF3StFhQSQkJMgdgtkQ2Q0s20/r6IZXl4EAlJcWkfbrxlofw5L96ovIbiC231/dMg5/T1me4eZo9/ZR2PkEyhGWyRAxd0rRYUEMGybuaokiu4Fl+/n2GGqclyPj0Db0BTm1PoYl+9UXkd1AbL+/ulWUlZC6dwNgmLfDv/dIOcIyGSLmTik6FBQERmPniHe3xwCo0JeRuvdrmSNSUDAv6Qe+M85S6hHWB1vPRjJHpFAZpeiwINatWyd3CGZDZDewXD+fyCHGNVYyj+6kLCejTsexVD9TILIbiO1XnVtFaTFp+74BDENp/XqNaOiwTIaIuVOKDguiffv2codgNkR2A8v0U9vY4dNjKHBjSOH6u7zi9liin6kQ2Q3E9rud27WYzcabpT3v74/W0a0hwzIZIuZOKTosCBF/wW4gshtYpp9XlwHYOLoCkHViDyWZV+t8LEv0MxUiu4HYfrdzKy8uIP3QNgDUNjp8Igc3ZFgmQ8TcKUWHBVFaWip3CGZDZDewQD+VGt8HnjA+TN3zVb0OZ3F+JkRkNxDb705uab9uoqJcD4B35GDUNrYNFZbJEDF3yjToKNOgK4iHW7setHj6PwDknDnCuZXT5Q1IQUEGmj01A8/7+wKQuGkR6Qe3yhyRmCjToFsp06ZNkzsEsyGyG1ien1/Uk8afb9xUVx8szc+UiOwGYvvdza3yaC3fqCdBZV1feSLmzroyIDg6nU7uEMyGyG5gWX6OgSE4BbUDoCj1IrlnY+t9TEvyMzUiu4HYfndzK7p6ntxzhlk97bya4BbarSHCMhki5k4pOiyIU6dOyR2C2RDZDSzLz7fHzV6O1L317+UAy/IzNSK7gdh+NXFL/eVmb4dfz+HmDMfkiJg7peiwIET8BbuByG5gOX46dz/c2/cAoCwvm6zjP5rkuJbiZw5EdgOx/Wrilnv2CIUphunEnYLa4dg01NxhmQwRc6cUHRbEyJHWPWXvnRDZDSzHz/eBx43L11+L2YykLzPJcS3FzxyI7AZi+9XULa1Sj59flPX0doiYO6XoUFAQBI2do3Fht4qyEuVOfQWFP8k6/hOluYbZeN3aRqJz85E5onsXpeiwIL7+Wtx1MUR2A8vw8+oyEI2tAwAZR3fVaWG322EJfuZCZDcQ26+mblJ5GekHDEW4Sq3Bu5t1TBYmYu6UosOCCA4OljsEsyGyG1iAn0pdZdbFa/tqv3z9nZDdz4yI7AZi+9XGLf3QNir0hsm2vLsMtIrJwkTMnVJ0WBCdOnWSOwSzIbIbyO/n2iYCWw9/AHLOHKY4/bJJjy+3nzkR2Q3E9quNmz4/m6wTPwOgdXTBI+xBM0VlOkTMnVJ0WBCSJO7ksCK7gfx+Pt2HGH++tn+zyY8vt585EdkNxParrVvlvw2fyCF3aGkZiJg7ZRp0lGnQFawbO+8A2k1bDUBx5lV+f/cfIFXIG5SCgoXS5oUPcfpz2OwfH08lP+GkzBFZP8o06FbKlClT5A7BbIjsBvL6eXd7zPhz+oHvzFJwiJw/kd1AbL+6uF3b/63xZ5/Ix00ZjskRMXdK0WFBODo6yh2C2RDZDeTzU9va4xX+EADlpcVkHNlulvOInD+R3UBsv7q4ZZ/aS2luJgDu7bpb9PBZEXOnFB0WRHx8vNwhmA2R3UA+P8/7+6OxM3wwZR3bTXlRvlnOI3L+RHYDsf3q4iaV641z2KjUGry7PmrqsEyGiLlTig4L4tChQ3KHYDZEdgP5/KoMk92/xWznETl/IruB2H51dUs/+D8q/pyt1ytiECqtjSnDMhki5k4pOiyIZ555Ru4QzIbIbiCPn3OLMOx9mwKQl3CCotQEs51L5PyJ7AZi+9XVTZ+fTfbJXwCwcXTFvUNPE0ZlOkTMnVJ0KChYKZWH/JljmKyCgsikH/jO+LNP18fu0FLBlChFhwWxebO4Xxwiu0HD+9m4euEW2g2A0pwMrp/eb9bziZw/kd1AbL/6uOUnnq60+mxb7P0tb/ZPEXOnFB0WhJ+fn9whmA2R3aDh/by7DDSuJptxeBtSRblZzydy/kR2A7H96utWeVFES7yhVMTcWUTRMWHCBBISEigqKiI2NpYHHnjgju2joqKIjY2lqKiICxcuMH78+FvauLq68tFHH3H16lWKioqIi4tjwIAB5lIwCV27dpU7BLMhshs0sJ9ajVdnw2qyUkU56Ye/N/spRc6fyG4gtl993TJ/2015SREAnvf3RW1rb4qwTIaIuZO96Bg+fDiLFi1i9uzZhIWFsW/fPrZv305AQEC17YOCgvj+++/Zt28fYWFhzJkzh8WLF/PEE08Y29jY2PDDDz8QFBTEk08+SevWrRk3bhzJyckNpaWgYDbc2nRF5+YNwPW4g5TlZMgckYKCdVJRUkjWsR8B0Ng64GkF67GIgCTndvDgQWnp0qVV9sXFxUlz5syptv28efOkuLi4KvuWLVsmxcTEGB+PHz9eOn/+vKTVamsUg4ODg7R7927JwcFB1vdCo9HIen7FzTr8Wo6ZK4W/+6MU/u6PkkvrLsL5iZw7xc/y3Oz9mxv/nkKnLJfdyRpzV5vvUFl7OmxsbOjUqRO7du2qsn/Xrl1ERkZW+5pu3brd0n7nzp2Eh4ej1WoBeOyxxzhw4ABLliwhNTWVU6dOMWPGDNTqO+s6OTnh7Oxs3HQ6XT3sak91l4lEQWQ3aDg/nbsfLq3CASjJSiH3bGyDnFfk/InsBmL7mcKtKOUC+YlxADg0aoFjYGi9j2kqRMydVs6Te3l5odVqSUtLq7I/LS3ttjfQ+Pn5VdvexsYGLy8vUlNTCQ4Opk+fPnzxxRcMHDiQli1bsmTJErRaLW+//fZt40lOTjYWLgA//fQTq1evZtu2bUyYMAEwFERarZY+ffoAsHjxYoYOHUrjxo1JSUlhw4YNTJ48GYCff/6ZkpISHnrIME31xx9/zMMPP0xQUBAZGRmsWrWKadOmAbB//36aNm3KrFmzAFi5ciVRUVG0bNmSnJwcli5dyowZMwA4fPgwV65cMV5SWrNmDeHh4YSGhlJUVMTChQuNRdaxY8c4e/YsI0aMAODLL78kJCSEjh07otfreeedd3j55Zexs7Pj9OnTHDt2jFGjRgGwceNGmjZtSni44Utu9uzZTJo0CWdnZ86cOcP+/fsZM2YMAFu2bMHb29tYLL777rs8++yzeHh4kJCQgK+vr9Ft+/btODg40LNnTwDef/99Ro4cia+vL1euXGHLli288MILAOzevRuAvn37ArBkyRIGDx5MkyZNSEtLY926dUydOhWAX375hcLCQuO9O8uXL6dfv34EBweTlZXFihUreOWVVwCIiYkhPT2dwYMNk2t9+umndO/endatW5OXl8fixYuN8cbGxpKYmMjQoUMB+PzzzwkLC6Nt27YUFxezYMECOnfuzKxZszh+/Djx8fH87W9/A2D9+vW0atWKsLAwKioqmDt3Li+99BL29vbExcURGxvL008/DcCmTZto0qQJXbp0AWDu3LlMnDgRV1dXzp07x969e+kxcTYX/yyendPjmTXT8Dsxf/58oqOj8fLy4tKlS+zYsYPnn38eMBTltra29OrVC4APPviA4cOH4+/vT3JyMhs3bmTSpEnG33m9Xk///v0BWLZsGYMGDSIiIgK9Xs/atWt56aWXANi3bx+5ubkMGjQIgE8++YTevXvTokULsrOzWb58OdOnTwfg4MGDpKamMmSIYZjv6tWriYiIICQkhIKCAhYtWsTMmTNRqVQcPXqUhIQEhg0bBsC6deto37497du3p7S0lPnz5zNt2jR0Oh2nTp3i1KlTjBw5EoCvv/6a4OBgOnXqhCRJzJkzhylTpuDo6Eh8fDyHDh0yzn2wefNm/Pz8iIiIwN3dnXnz5jF+/Hjc3d05f/48e/bsYdy4cQBs27YNFxcXevToAcDChQsZPXo03t7eJCUlNdhnRFZWFo8++mitPiNatWrF1q1bLf4z4ocffjB+ydb0M6JVq1YcPXq03p8Rtt7wOwYefG4m7YviTf4Z8eqrr6LVamv1GeHv709AQECtPiPGjh0LwNatW/Hw8KB79+5m/4y48XddU2TrkvH395ckSZK6du1aZf/MmTOl+Pj4al9z5swZafr06VX2RUZGSpIkSb6+vsY2iYmJklqtNraZOnWqdPXq1Tt2Dfn4+EjOzs7GTafTNej7MWLECNm7yRQ3y/VTabTSfa9/I4W/+6N0/9ydktbJXSg/kXOn+Fm2m0qrkzr+51vD39bs7ZLGwUV2N2vKndVcXsnIyECv19/Sq+Hj43NLb8YNUlNTq21fVlZGZqZhEZ+UlBTOnj1LRcXN1Tbj4+Px9/fHxub2093m5+eTl5dn3EpLS+uqVif27NnToOdrSER2g4bxcwuNxMbZHYDrv/+KPj/b7Oe8gcj5E9kNxPYzlZukLyUj1nDZXm2jw/P+viY5bn0RMXeyFh1lZWUcPXqUfv36Vdnfr18/YmJiqn3NgQMHbmnfv39/YmNj0ev1gKEbskWLFqhUKmObVq1acfXqVcrKykxsYTpudOWKiMhu0DB+lecRqDy/QEMgcv5EdgOx/UzplnHof8afvbsMMtlx64OIuZN9yOzChQt59tlniY6Opk2bNixcuJDAwEA+/vhjAObMmcNnn31mbP/xxx/TtGlTFixYQJs2bYiOjmbs2LG89957xjbLli3D09OTDz74gJYtWzJw4EBmzpzJkiVLGtxPQcEU2Ho1xqXl/QAUp18h78JxmSNSUBCL4vTL5F08BYC9XxCOTS3nhlLRkP160IQJE6SLFy9KxcXFUmxsrNSjRw/jc6tWrZL27NlTpX1UVJR09OhRqbi4WEpISJDGjx9/yzG7du0qHThwQCoqKpLOnz8vzZgxo8o9HpU3Sxky27FjR9lzobhZpl/jh8cah/X59hwunJ/IuZN7E9nP1G6e9/cz/p0FDfuXcH7m2mrzHSrr6JUbLFu2jGXLllX7XHR09C379u7dS6dOne54zIMHD9KtWzeTxNdQuLi4yB2C2RDZDczsp1bjGW4Y3VBRriczdtddXmB6RM6fyG4gtp+p3bJP7SVg8D/R2jvhfl8vkr5bSkVJoUnPURtEzJ3sl1cUbnJjOJ6IiOwG5vVzbROBzsUTgJy4GPQF1812rtshcv5EdgOx/UztVlFWcnOGUp09Hh37mPT4tUXE3ClFh4KChePdZaDx54wj22WMREFBfCqvZeQdMfAOLRXqggrDdZZ7GgcHB7777jsee+wxCgvl60qzt7enqKhItvObE5HdwHx+Ni6edJjxJSqNhtLr6ZycOxKkiru/0MSInD+R3UBsP3O5hUxaimOT1gCcXjSeoqvnTX6OmmAtuavNd6jS02FBjB49Wu4QzIbIbmA+P89O/VFp/lzCPnaHLAUHiJ0/kd1AbD9zuWVU7u3oIl9vh4i5U4oOC8Lb21vuEMyGyG5gPj+vzgOMP2cc2WGWc9QEkfMnshuI7Wcut8xjP1Feauhh8Ah7ELWNrVnOczdEzJ1SdFgQSUlJcodgNkR2A/P4OQffh51XYwByzx2lNDvV5OeoKSLnT2Q3ENvPXG4VJYVkn/gFwDCSpX2UWc5zN0TMnVJ0WBDbtm2TOwSzIbIbmMevci9H+mF5byAVOX8iu4HYfuZ0Sz9889heMl1iETF3StFhQdxYpVJERHYD0/tp7Bxx72D470pfmMv107+a9Pi1ReT8iewGYvuZ060gMY6itEQAnIM7YOcdYLZz3Q4Rc6cUHQoKFkjl68iZv+1G0lvumkEKCqKSUaW3Y8AdWirUFKXosCB27Wr4mSYbCpHdwPR+lbtzM2S+tAJi509kNxDbz9xumUd/oOLPgt8wkqxhJ/EWMXdK0WFBaLUWMSu9WRDZDUzr59C4JY6NWwJQkPQHRakJJjt2XRE5fyK7gdh+5narfGnTxskdt9BIs57vr4iYO6XosCD69JF3yl1zIrIbmNavyg2kFjIDqcj5E9kNxPZrCLf0Qzfn7GjoSywi5k4pOhQULAiVVodH2IMAlJcWkXX8J5kjUlC4t8m7cIySzKsAuLQMR+fmI3NE1o/sy+LKvVnK0vbOzs6yvxeKm7x+HmF9by6tPfwV2b3uhfyJ7Ca6X0O5+T84yvh36d93tHB+9d1q8x2q9HRYEEOHDpU7BLMhshuYzq9y923lqZjlRuT8iewGYvs1lFvm0V1IFYYlCLzCHwKVqkHOK2LulKLDgmjcuLHcIZgNkd3ANH62no1wad4RgKJrSeRf+r3exzQVIudPZDcQ26+h3EqvXyP3XCwAth7+ODcPa5Dzipg7peiwIFJSUuQOwWyI7Aam8au6zopl3EB6A5HzJ7IbiO3XkG6Vh657dX64Qc4pYu6UosOC2LBhg9whmA2R3cAEfmo1nuEPAVBRrifz6A8miMp0iJw/kd1AbL+GdLsed4CyghwA3Nv1QGPvZPZzipg7peiwICZPnix3CGZDZDeov59rmwh0Lp4A5MQdQJ+fbYqwTIbI+RPZDcT2a0g3qbyMrN8M/wyobW6OMjMnIuZOKToUFCwAr3DLvbSioKBgIOPIDuPP3p2VadHrglJ0WBA///yz3CGYDZHdoH5+Wid33EK6AlCak0HO2SMmisp0iJw/kd1AbL+GditKvUhB0h+AYeZghz9nDjYXIuZOKTosiJKSErlDMBsiu0H9/Dzv74tKowEMQ/P4c2ieJSFy/kR2A7H95HCrPEuwV7h5bygVMXdK0WFBPPTQQ3KHYDZEdoP6+VX+4MqI3WmKcEyOyPkT2Q3E9pPDLfvEHspLiwHDatAqrc5s5xIxd0rRoaAgI44BbbD3CwIg7+IpSjKuyBuQgoLCHSkvLiD75F4AtA7OuLd7QOaIrIs6Fx02NjamjEMB+Pjjj+UOwWyI7AZ197PkuTkqI3L+RHYDsf3kcss4UmkRODPeUCpi7upcdCQnJzNnzhwCAgJMGc89zcMPN8yEM3IgshvUzU9tY4v7fb0AKC8pIvvkLyaOynSInD+R3UBsP7nc8i+eovjPXkmXlvej8/A3y3lEzF2di46tW7cyadIkLly4wKZNm4RcgrehCQoKkjsEsyGyG9TNz61dD7R/TjCUffJnKv68TmyJiJw/kd1AbD853SoPn/UKN8+9FyLmrs5Fx9ixY2nSpAmzZs3ivvvuY9euXcTFxfHCCy/g5GT+mdpEJCMjQ+4QzIbIblA3v8pTKVf+ALNERM6fyG4gtp+cboZF4MqBG4vAmf4WSVFzZ5KlbR999FFp586dkl6vl3JycqQPP/xQat26texL7tZks5Sl7XU6nezvheLWMH46D3/jUtntpn0me/z3cv5EdhPdT263Fs/8n/Hv2KVVZ+H8arrJsrT91q1befXVV/nll19wcnJi4sSJnD59mm+++QZvb29TnUZopk2bJncIZkNkN6i9n1en/safM2Itu5cDxM6fyG4gtp/cbpVv/vbqYvobSuX2Mwf1Ljo0Gg1PPfUU+/btIzY2luDgYF599VWCgoKYMmUKPXr0YM2aNaaIVUFBDFQ3F3eTKsotbnE3BQWFmpETf5CyPMM6SW6hkWgdXWWOyPKpc9HRqFEj3nzzTS5fvswXX3xBeXk5w4cPJzg4mPfee4/Lly/z0Ucf8fzzzxMVFWXKmIVl//79codgNkR2g9r5ubQIw9bdF4CcM0coy7X867Yi509kNxDbT243qaKczN92AaDW2uB5f1+THl9uP3OgresLL126hF6v56uvvuKDDz7gxIkT1bZLSEggLS2tzgHeS2RlZckdgtkQ2Q1q5+dZ6U53S7+B9AYi509kNxDbzxLcMg5vx6/nCMAwZ0favo0mO7Yl+JmaOvd0vPnmmwQGBjJmzJjbFhwAJ06cIDg4uK6nuad49NFH5Q7BbIjsBjX309g74d6uBwBlBTnkxB8wZ1gmQ+T8iewGYvtZgltx+mXyL/0OgL1fMxwDWpvs2JbgZ2rqXHQkJSVRcZuFqdzd3Rk9enSdg1JQEBWPjn1Q2xjWasj6bTdSuV7miBQUFOpL+uFKN5R2HihjJNZBnYbI6PV6qXPn6ocI3X///ZJer5d9GE9NN0sZMuvn5yf7e6G4mdcv5MUlxiF29v7Bsset5E9sN9H9LMVNrbOTwt7+nxT+7o9S2FvfSWobO6H87rY1yJBZlUp12+fs7OwoLy+v66HvWUS+4VZkN6iZn71fMI4BbQAouHKWopQEc4dlMkTOn8huILafpbhVlBaTdeJnADR2jrh3ME1cluJnSmp1I2lAQECVaVnDwsKws7Or0sbe3p7nnnuOpKQkkwR4L9GyZUu5QzAbIrtBzfy8OlvfDaQ3EDl/IruB2H6W5JZx5Hu8/5yrw6vzw2Qe3VXvY1qSn6moVdERHR3NG2+8gSRJSJLE0qVLb2lzowdk8uTJponwHiInJ0fuEMyGyG5wdz+VRotHmGE4XUVZKVnHf2qIsEyGyPkT2Q3E9rMkt4LEOIrSErH3bYpz8H3YejWmJCO5Xse0JD9TocJwnaVGtGnThtDQUFQqFRs2bGDmzJmcO3euSpuSkhJ+//13EhMTTR2r2XBwcOC7777jscceo7CwULY41Gr1bW/OtXZEdoO7+7m1e4AWT78JQNbxPSSs+7+GCs0kiJw/kd1AbD9Lc/ONGkbAI88DkPLTOpJ3rKzX8SzN73bU9ju0TjeOPP3005KHh4fsN7CYYrOUG0lnzZol+3uhuJnHr0X07JtrNLTsJHu8Sv7uDTfR/SzNTevoJt0/d6cU/u6PUofX1kuo1UL53W5rkBtJ16xZI+TEJQoKpsbGxRPX1p0BKMlOI/f8MZkjUlBQMAf6guvkxBnm3tG5eOHaOkLmiCyPWt3T8frrr7NixQpSUlJ4/fXX79hWkiT+7/+sqwtZbg4fPix3CGZDZDe4s5/n/f1QqTWAYTlsJMvvLv0rIudPZDcQ288S3TJid+De3jABoFfnh+s1AaAl+tWXWhUd//nPf9ixYwcpKSn85z//uWNbpeioPVeuXJE7BLMhshvc2c+r88PGnzNidzZEOCZH5PyJ7AZi+1miW86Zw5TmZhh6OkK6onVyR5+fXadjWaJffanV5RWNRsORI0eMP99p02rrvKzLPcsTTzwhdwhmQ2Q3uL2fU9O22HkHAJB74TilWSkNGZbJEDl/IruB2H4W6VZRQWbsn4vAabR4dupX50NZpF89qffS9goKCrfHs3Ivx5Htd2ipoKAgCpX/1r06D5AxEsujzkWHra0tzs7OVfYNGzaMuXPn8uCDD9Y7sHuRNWvWyB2C2RDZDar3U+vs8LivFwDlxQVcP7WvgaMyHSLnT2Q3ENvPUt1KMq+Sd+E4APY+gTg1bVun41iqX32oc9Gxdu1aFi9ebHz84osv8tVXX/HKK6+wc+dOBgxQqrvaEh4eLncIZkNkN6jez719TzS2DgBkndhDRVlJQ4dlMkTOn8huILafJbulV+7t6FK370NL9qsrdS46unTpwo4dN6dynjRpEp9//jlubm5s2rSJf/3rXyYJ8F4iNDRU7hDMhshuUL2fNU97/ldEzp/IbiC2nyW7XT+1D31RPgDuHXqhtrWv9TEs2a+u1Lno8Pb2JjnZMMVrUFAQwcHBfPjhh+Tl5bFy5UratWtnsiDvFYqKiuQOwWyI7Aa3+tl6NcY5+D7Dc2mJFCTFyxGWyRA5fyK7gdh+luxWUVZC1ok9AGhs7fHo0KvWx7Bkv/pQpxnI0tPTpUGDBkmANHr0aCknJ8f4XM+ePaWCggLZZ0mr6WYpM5Iqmzhb44fGGGcg9e05XPZ4lE3ZlK3hN4cmrY2fA20mLpY9HrN5NsSMpKdOneKFF16gXbt2TJw4kT179hifCwwMJDU1ta6HvmeZMWOG3CGYDZHd4C9+KjWenfoDIJWXk3n0B5miMh0iJpJRbQAAIABJREFU509kNxDbz9LdCq+coTAlAQCnoLbY+QTW6vWW7lcX6lx0vP322/Ts2ZPjx49z33338e677xqfGzRoEL/99ptJAryXUKvFHcEsshtU9XNp2QmdmzcA1/84WOeJgSwJkfMnshuI7WcNbhmH6z581hr8akudjfbs2UNISAjDhg2jbdu2xMTEGJ/76aefmD9/vkkCvJc4dkzcNTlEdoOqft4RA40/Z1rpDKR/ReT8iewGYvtZg1vWsd1U6MsA8Ox0c0mEmmANfrWlXtOGJiUlkZSUdMv+//73v/U57D3L2bNn5Q7BbIjsBjf9tE7uuIZGAlCam0lO/EE5wzIZIudPZDcQ288a3PSFuVw/vR+P+3ph4+SOa0hXrp/eX6PXWoNfbal33423tzfh4eH06NHjlq2mTJgwgYSEBIqKioiNjeWBBx64Y/uoqChiY2MpKiriwoULjB8//rZtR4wYgSRJfPvttzWORy5GjBghdwhmQ2Q3uOnn1ak/ao2hls+M3YlUUS5nWCZD5PyJ7AZi+1mLW5UZSrsMvEPLqliLX22oc0+Hn58fa9eupXfv3rc8p1KpkCSpRuuvDB8+nEWLFjFx4kT279/P+PHj2b59O6GhoVy+fPmW9kFBQXz//fd88sknjBo1iu7du7N06VLS09PZtGlTlbaBgYG899577N27t66aCgq1ovIHSsbh72WMREFBwVLIPfcbJdlp2Lr74tq6MzYuXpTlZsgdlmzUaYjMN998I2VkZEgvv/yy1K9fPykqKuqWrSbHOXjwoLR06dIq++Li4qQ5c+ZU237evHlSXFxclX3Lli2TYmJiqg7LUaulffv2SWPGjJFWrVolffvttyYZ7mPOLTg4WPahT4pb3f2cgjsYh8e1Gjdf9piU/CluovtZk1ujfv8wfj749R4plF+DDJnt2bMn//rXv1iwYAE//PADe/fuvWW7GzY2NnTq1Ildu3ZV2b9r1y4iIyOrfU23bt1uab9z507Cw8Or9Kz8+9//Jj09nU8//bTGTk5OTjg7Oxs3nU5X49eagpCQkAY9X0MishsY/Ly7DDI+zjgiVi+HyPkT2Q3E9rMmt4zYm7MSe1VaCPJOWJNfTanz5RVJkqq9/FEbvLy80Gq1pKWlVdmflpaGn59fta/x8/Ortr2NjQ1eXl6kpqYSGRnJ2LFj6dixY63iSU5OrlK4/PTTT6xevZpt27YxYcIEwFAQabVa+vTpA8DixYsZOnQojRs3JiUlhQ0bNjB58mQAfv75Z0pKSnjoIcN02B9//DEPP/wwQUFBZGRksGrVKqZNmwbA/v37iYqKMsa8cuVKoqKiaNmyJTk5OSxdutQ4Zvvw4cNcuXLFuOzxmjVrCA8PJzQ0lKKiIhYuXMiMGTNQq9UcO3aMs2fPGq8Nfvnll4SEhNCxY0f0ej3vvPMOL7/8MnZ2dpw+fZpjx44xatQoADZu3EjTpk2N8//Pnj2bSZMm4ezszJkzZ9i/fz9jxowBYMuWLXh7exuLxXfffZdnn30WDw8PEhISaNOmjdFt+/btODg40LNnTwDef/99Ro4cia+vL1euXGHLli288MILAOzevRuAvn37ArBkyRIGDx5MkyZNSEtLY926dUydOhWAX375hcLCQuO6P8uXL6dfv34EBweTlZXFihUreOWVVwCIiYkhPT2dwYMHA/Dpp5/SvXt3WrduTV5eHosXL2bWrFkAxMbGkpiYyNChQwH4/PPPCQsLo23bthQXF7NgwQIeeWI46Rn+VAAVxfk8N+gBNIMiWb9+Pa1atSIsLIyKigrmzp3LSy+9hL29PXFxccTGxvL0008DsGnTJpo0aUKXLl0AmDt3LhMnTsTV1ZVz586xd+9exo4dC8DWrVvx8PCge/fuAMyfP5/o6Gi8vLy4dOkSO3bs4PnnnwcMRbmtrS29evUC4IMPPmD48OH4+/uTnJzMxo0bmTRpkvF3Xq/X07+/YZ6RZcuWMWjQIPr27Uvjxo1Zu3YtL730EgD79u0jNzeXQYMMxdYnn3xC7969adGiBdnZ2Sxfvpzp06cDcPDgQVJTUxkyZAgAq1evJiIigpCQEAoKCli0aBEzZ85EpVJx9OhREhISGDZsGADr1q2jffv2tG/fntLSUubPn8+0adPQ6XScOnWKU6dOMXLkSAC+/vprgoOD6dSpE5IkMWfOHKZMmYKjoyPx8fEcOnSIZ555BoDNmzfj5+fH8OHD6dixI/PmzWP8+PG4u7tz/vx59uzZw7hx4wDYtm0bLi4uxnvVFi5cyOjRo/H29iYpKanBPiOysrJ49NFHa/UZ0apVK06ePGnxnxE//PCD8f68mn5GtGrVioyMDKv4jJj63DMc02eRpfXAzqsxE/49H4/y63f8jPD39+fkyZMW/xlx4++6ptSpO2XJkiXS+++/X68uGX9/f0mSJKlr165V9s+cOVOKj4+v9jVnzpyRpk+fXmVfZGSkJEmS5OvrKzk5OUkJCQnSww8/bHy+ppdXfHx8JGdnZ+Om0+katIvq1Vdflb2bTHGr2zbyjY+MXacBj06QPR4lf4rbveBnbW4eHXsbPyeCRtw9dmvxq83llTr3dGzYsIFPPvkEtVrN1q1byczMvKXN3cYYZ2RkoNfrb+nV8PHxuaU34wapqanVti8rKyMzM5O2bdvSrFkztm7danz+xgQrZWVltG79/+ydd3gU1f64363ZbHqyaQQIPRBACITeqxQVgSsq1wKCAupFQVGBr/q7Koh4ReVepUkRvQoqKChVOgQQEqkBQiAESEjvPdnd+f2Ry0JMaEk2u3uY93nmebIzZ8583j3Z2c+emTknhLi4uCrrzs/Pp7Cw8LYxW5OPPvrIZse2NiK7ARzPdULvUv53moA3kIrcfiK7gdh+juaWdfoAxsJc1Hp3vNr25uqG/2AqLrhleUfzuxuqfU/Hrl27aNq0KS+//DJbt27l6NGjliUyMpKjR4/esY6ysjKioqIYNGhQhfWDBg2qMNjYzRw6dKhS+cGDBxMZGYnRaOTcuXO0adOG9u3bW5aNGzeye/du2rdvX+NLQtbktddes3UIVkNkN5cGIegDmwCQHx9NccplG0dU+4jcfiK7gdh+juYmGcvIOLYTAJVWh3f7yk9/3oyj+d0N1e7pGD9+fK0EsGDBAr755hsiIyM5dOgQL7zwAg0bNmTx4sUAzJ07l6CgIJ599lmg/Jrnyy+/zCeffMKyZcvo1q0bEyZM4MknnwSgpKSE6OjoCsfIzs4GqLTe3tDpdLYOwWqI7Ga46QZSEXs5QOz2E9kNxPZzRLf0I1vw7zESKB8WPe3wb7cs64h+d6LaScfq1atrJYAffvgBHx8f3nnnHQIDAzl9+jTDhg2zjHQaGBhIw4Y3JsmJj49n2LBhfPrpp7z00ktcu3aNqVOnVhqjwxGx96SoJojqpnRyxrt9+Q2DpuICsk7ssW1AVkLU9gOx3UBsP0d0K0q6SEHCeVzqt8ClQUucA5pQlFz1JX9H9LsbanwTSYsWLaTu3bvbfJyL6i72Mk5HcHCwzd8L2e3eFkPnYZYbwxqOetXm8cjtJ7vdT36O6ubbbcRNN56/6PB+dTJOB8DTTz/N1atXOXPmDPv27SMkJASAtWvXMnHixJpUfV9y/TE0ERHV7X4ZgVTU9gOx3UBsP0d1yzy+E3NZKQA+HQahUGmqLOeofrej2knH3/72N1atWsWff/7Jyy+/jEKhsGz7888/GTNmTK0EKCNjrzgHNMG1YfngPW6mPAoTxJucSUZGpvYxFeWTdbp8AE21izueraseDFNEqp10zJw5k5UrVzJixIhKs8qePXuW0NDQGgd3v7Fu3Tpbh2A1RHQzdLk/ejlAzPa7jshuILafI7ulH7lpErhOQ6ss48h+t6LaSUerVq1Ys2ZNldsyMzPx8fGpdlD3K8HBwbYOwWqI5qbU6PDpUP7otrmshIDSZBtHZF1Ea7+bEdkNxPZzZLe8uBOUZFwDwL15R7SefpXKOLLfrah20lFYWIiHh0eV24KCgsjKyqp2UPcr14cSFhHR3LzD+qN2dgUg8/guOrdva+OIrIto7XczIruB2H4O7SZJpEduA0ChVOIT/mClIg7tdwuqnXRERETw8ssvV7lt3Lhx7Nmzp7pVy8jYPb5dH7b8nXro19uUlJGRkama9MhtSGYzAIbwIXDTvZEiU61HZDp27CgVFRVJR44ckV599VXJaDRK77//vrRx40apoKBAat26tc0f47nbxV4emZUXx1hcGoRYHndr9Y8vbB6PvMiLvDju0vy5uZbziUfLzjaPpzpLnTwyGxUVxdChQ3F1deWTTz5BoVAwa9YsWrRowbBhw4Qd1MSaXJ/FT0REcvPt+ojl7+u9HCL5VYXIfiK7gdh+IrilHr7RU+rbbUSFbSL4/ZVqj0gK5dMyh4aG0qRJE/z9/UlPTyc2Nra2YrvvcHNzs3UIVkMUN5Wzm2W+BGNhHlkndgPi+N0Kkf1EdgOx/URwyzn7ByVZKTh5+eMR0hmtVwClWeU3povg91eqlXQYDAYmTZpE7969qVevHgDXrl1j9+7dLF26lMzMzFoN8n4hJibG1iFYDVHcDOEPotQ4AZARtR1zWQkgjt+tENlPZDcQ208IN8lM2uFfqT90IgqlEt+uD5O4ZRkgiN9fuOfLK/379yc2Npb33nuPfv364ePjg8FgoF+/fsyZM4fz58/Tq1cva8QqPBEREbYOwWoI4aZQVLyB9PBGy99C+N0Gkf1EdgOx/URxSz+yBbOxDABD56Eo1OUjlIridzP3lHQYDAbWrl1LTk4OY8aMwcPDg3r16hEYGIiHhwdPPPEEBQUF/PTTT3h7e1srZmF57rnnbB2C1RDBza1pGDrf+gDkxv5JSVqCZZsIfrdDZD+R3UBsP1HcjAXZZJ3aC4DGxQPvB/oC4vjdzD0lHRMmTEClUtGjRw/WrVtHUVGRZVtRURE//vgjPXv2RKPRMGHChFoPVkbGlvh1u3EDadph+TFZGRmZ2iP14AbL3743nWtE456SjsGDB7NixQoSExNvWebq1ausXLmSIUOG1Di4+40NGzbcuZCD4uhuGncDnqHl8yOU5qaTHV2x29PR/e6EyH4iu4HYfiK5FVw+Q+G1CwC4BoeiD2oulN917inpaNWqFQcOHLhjuf3799OqVatqB3W/4uvra+sQrIaju/l2GYZCpQIg/Y/NSGZTxe0O7ncnRPYT2Q3E9hPNrWJvxwjh/OAekw5PT09SU1PvWC41NRVPT89qB3W/0r27uDMNOrKbQqnC0Hk4AJLJRNqRTZXKOLLf3SCyn8huILafaG6Zx3ZhLMoHwCesP52697ZxRLXPPSUdTk5OlJWV3bGc0WhEq9VWOygZGXvCI7QbWg8DANlnD1GWk27jiGRkZETEXFZMRtR2AJQaJxK1gTaOqPa553E6QkJCMBqNty3TsmXLagd0PzN//nxbh2A1HNmtwg2khzZWWcaR/e4Gkf1EdgOx/UR0Sz20Af+eowA4WaAvn49FkmwcVe1xz+N0rFq1iqNHj952WblypTViFZ6JEyfaOgSr4ahuOt8GuDfvCEBxegK5F/6sspyj+t0tIvuJ7AZi+4noVpKWQG5sFABOhiDcm3WwcUS1yz31dIwfP95acciA0GObOKqbX4+Rlr/TDv16y18cjup3t4jsJ7IbiO0nqlvqoY2WHzu+3UdYkhARuKekY/Xq1daKQwaIi4uzdQhWwxHdVDoXfDoOBsBUUkT60S23LOuIfveCyH4iu4HYfqK6ZZ85SGl2GlpPXzxbdUXr6Udp9p0f4nAEqj3LrEzt8/vvv9s6BKvhiG6GzsNQOTkDkBG5DVNxwS3LOqLfvSCyn8huILafsG5mM2l//AaUPz3319lnHRk56bAjJk2aZOsQrIbDuSmU+HW/8UFPOfjzbYs7nN89IrKfyG4gtp/Ibml/bEIhmYHycYKUGp2NI6od5KRDRqYKPEO74eRd/rhazrkjFeZZkZGRkbE2xvwsAstSAFDr3fHpOMjGEdUOctJhR2zZcut7BhwdR3Pz+98jawApB9bfsbyj+d0rIvuJ7AZi+4nsBpCwa43lb7+eo8ofn3Vw5KTDjtDr9bYOwWo4kptzQBPcm7YHoDjtKrmxkXfcx5H8qoPIfiK7gdh+IrsB6Euzybt4HABnv4a4t+hk44hqjpx02BF9+vSxdQhWw5Hc/HreeEw25cDPdzUwjyP5VQeR/UR2A7H9RHaDcr+U/essr/1v6oF1VOSkQ0bmJtR6d3zCBgBgLMonI2qbjSOSkZG5n8k+e5jijGsAeIR0QucfbOOIao50vy96vV7asWOHpNfrbR6Hrd+L+90tsP/fpfD5O6Xw+Tul+g9NEc5P9PaT3e4vP5Hdbvbz6zHKcl4KHj3N5nFVFefdfofKPR12xNixY20dgtVwBDeFWmMZgVQym0iNuP1jsjfjCH41QWQ/kd1AbD+R3eCGX3rkVss4QT4dBqHWu9syrBohJx12hL+/v61DsBqO4ObTYRAaNy8Ask7uozQr+a73dQS/miCyn8huILafyG5ww89cUmgZEVmpccK360O2DKtGyEmHHZGQIO5YEHbvplDg3/sxy8vkfT/c0+5271dDRPYT2Q3E9hPZDSr6pUT8gmQ2AeVzQinUGluFVSPkpMOO2LBhg61DsBr27ubRqivOfg0ByL14nMKE8/e0v7371RSR/UR2A7H9RHaDin6lmUlkndoPgMbNG58OjjlYmJx02BEvvfSSrUOwGvbuFtB7jOXvlL331ssB9u9XU0T2E9kNxPYT2Q0q+yXfdG4K6PM4KBzvK9zxIpaRqWVcGrTErckDABQlx5MTc8TGEcnIyMhUpjAhhtwLxwDQ+dbHs3V3G0d078hJhx2xY8cOW4dgNezZzb/PjV6O5H0/cjeDgf0Ve/arDUT2E9kNxPYT2Q2q9kves9byd0DfJ+oynFpBTjpk7mucvAPxatMTgNLcDDKP7bRxRDIyMjK3Jvf8UQqvXQTAtWErXBu3tXFE94acdNgRAwcOtHUIVsNe3fx7P4ZCqQIgNeJnJFNZteqxV7/aQmQ/kd1AbD+R3eDWfsl7Hbe3Q046ZO5bNG7eGDoNBcBUUkja4d9sHJGMjIzMnck6sYeSrPJp7z1bdUXn38i2Ad0jNh9C1daLvQyD7unpafP34n5yqz980o0hz4e9IJyf6O0nu8l+Irvdye/modEbjXnTpnHKw6A7KCNGjLB1CFbD3txUend8uz4MgLmstPwG0hpgb361jch+IruB2H4iu8Ht/dKPbsZYmAuAd1h/tF4BdRVWjZCTDjuifv36tg7Batibm3/PUaicnAFIP7IZY35WjeqzN7/aRmQ/kd1AbD+R3eD2fubSYsv8UEqVmsB+T9ZVWDVCTjrsiJSUFFuHYDXsyU2lc7FM7GY2GSvclFVd7MnPGojsJ7IbiO0nshvc2S/lwPobE8GFP4jGw7cuwqoRctJhR3z33Xe2DsFq2JObb7dHUDu7ApAR9Tul2ak1rtOe/KyByH4iu4HYfiK7wZ39TEX5pEb8AoBSrSGg7+N1EVaNkJMOO2LatGm2DsFq2IubUuOEf6/RAEhmE8l7vq+Veu3Fz1qI7CeyG4jtJ7Ib3J1fyv6fMJUUAeDbeTgaN29rh1Uj5KRD5r7C0Hk4Gtfy6eszT+6lJD3RxhHJyMjIVB9jYS5phzYCoNRo8e9j370dctJhR+zdu9fWIVgNe3BTqLUVuh+Td9Ve16w9+FkTkf1EdgOx/UR2g7v3S973I6bSYgB8uz6E2sXTmmHVCDnpsCMKCwttHYLVsAc3v24Po/UwAJB1+gBFyZdqrW578LMmIvuJ7AZi+4nsBnfvZ8zPIv2PTQCotDr8ez9mzbBqhJx02BFDhw61dQhWw9ZuSq2OgL43Him7tv3rWq3f1n7WRmQ/kd1AbD+R3eDe/JL3rsVcVgqAX/cRqF08rBVWjZCTDpn7Ar/uj6Jx+9+9HCd2U5QcZ+OIZGRkZGqPstwM0o9uAUDl5GzXc7LYfKhXWy/2Mgy6wWCw+XshopvSSS+1f/dnKXz+TqnjvO2Szq+hUH6it5/sJvvdj27V8dO4G6QOczZL4fN3Sh3mbJE0HnXz/sjDoDsogwYNsnUIVsOWbv69RqN2cQcg49hOilOv1PoxRG47ENtPZDcQ209kN7h3v7LcdFIP/m/cDo2WwAFPWSOsGiEnHXZEkyZNbB2C1bCVm8rZDf9efwNAMplI+n21VY4jctuB2H4iu4HYfiK7QfX8knevsYxSaug0FCeferUdVo2Qkw47IjMz09YhWA1buQX0fswy+mh65FZKMpOschyR2w7E9hPZDcT2E9kNqudnLMy1TGCpVKmpN+jZ2g6rxtj8utWUKVOkuLg4qaioSIqMjJR69ux52/K9e/eWIiMjpaKiIunixYvSpEmTKmyfOHGitG/fPikzM1PKzMyUfv/9d6lTp061cj3KmotGo7F5W4jkpnb1ksLe/638+ubcrZLW008oP9HbT3aT/e5nt5r4KZ30Urt31//vPrbfJeeAxlaN06Hu6RgzZgyfffYZc+bMISwsjP3797NlyxYaNGhQZflGjRqxefNm9u/fT1hYGHPnzmXhwoWMGjXKUqZv3758//339OvXj27dunHlyhW2b99OvXr21c30V9544w1bh2A1bOFWb9AzN2aS/WNTrcyxcitEbjsQ209kNxDbT2Q3qL6fuaSQ5N3lUzwolErqDR5fm2HVCJsnHdOnT2f58uUsX76cc+fOMW3aNK5evcqUKVOqLD958mSuXLnCtGnTOHfuHMuXL2fFihW8/vrrljJPPfUUixYt4sSJE8TExPD888+jVCoZMGBAXWnJ2BidbwN8Ow8HwFRSyLWd39o4IhkZGZm6I/XgBkqz0wDwatMDl4atbBxROTZNOjQaDR07dmT79u0V1m/fvp3u3btXuU+3bt0qld+2bRvh4eGo1eoq99Hr9Wg0mjteH3N1dcXNzc2yaLXae7CpOQcPHqzT49Ulde0WNOx5FCoVUH5jlTE/y6rHE7ntQGw/kd1AbD+R3aBmfpKxlGs7v7G8bvDQ5NoIqcZU/S1dRxgMBtRqNSkpKRXWp6SkEBAQUOU+AQEBVZbXaDQYDAaSk5Mr7TNv3jwSExPZsWPHbeNJTEyskLjs2rWLVatWsWnTJkvPy/bt21Gr1fTv3x+AhQsXMnr0aIKCgkhKSuKHH37glVdeAWDPnj2UlJTw4IMPArB48WKGDBlCo0aNSE9PZ+XKlcyYMQOAiIgI3N3dmT17NgDLly+nd+/eNG/enJycHL788ktmzpwJwJEjR0hISLBcUlq9ejXh4eGEhoZSVFTEggULmDlzJkqlkmPHjnH+/Hkef7x8zpHvv/+eVq1a0b59e4xGIx999BGvvfYaOp2O6Ohojh07xlNPlT9mtW7dOoKDgwkPDwdgzpw5TJ06FTc3N2JiYoiIiOC5554DYMOGDfj6+lqSxfnz5zNx4kS8vb2Ji4vjypUrFrctW7ag1+vp06cPAJ9++iljx47F39+fhIQENmzYwEsvvQRgabOBAwcC8MUXXzBixAjq169PSkoK3333nWUmxr1791JYWEiXh57kqGsHAFSlBTzbrQk5IVP46quvLN2VBw8eJC0tjREjRgCwYsUKevToQUhICHl5eSxcuNASb2RkJJcvX2b06PLZab/99lvCwsJo3bo1xcXFfPLJJwwcOJDu3btz/Phxzp49y5NPlo9+unbtWlq0aEFYWBhms5kPP/yQ6dOn4+zszJkzZ4iMjOSZZ54BYP369dSvX5/OnTsD8OGHH/Liiy/i4eFBbGws+/btY8KECQD8+uuveHt706NHDwA+/vhjxo8fj8FgID4+nq1btzJ5cvlJZtu2bTg5OdG3b18APv/8c8aMGUNgYCCJiYmsW7eOqVOnWv7njUYjgwcPBmDRokUMHz6cNm3a0Lx5c7755humT58OwP79+8nNzWX48PIepWXLltGvXz+aNWtGVlYWS5Ys4a233gLg8OHDJCcn8+ijjwKwatUqunTpQqtWrSgoKOCzzz5j1qxZKBQKoqKiiIuL47HHyody/u6772jbti1t27altLSUjz/+mBkzZqDVajl16hSnTp1i7NixAPz44480adKEjh07IkkSc+fO5dVXX8XFxYWzZ8/yxx9/MG7cOAB++eUXAgICGDx4MN27d2fevHlMmjQJLy8vLly4wO7du3n++ecB2LRpE+7u7vTq1QuABQsW8PTTT+Pr68uVK1fq7ByRmZnJww8/fE/nCHd3dy5cuGD354jff/+dSZMm3dM5wt3d3TJU+L2cI66P9LlkyRIGDRpEkyZNyMzMtOo54s0330StVt/TOSIzM5MLFy5U+xzhpS8EUwEFKhdcG7Xhsenv08K5uNbPEdc/13eLzW6SCQwMlCRJkrp27Vph/axZs6SzZ89WuU9MTIz01ltvVVjXvXt3SZIkyd/fv1L5GTNmSBkZGVLbtm3veBOMn5+f5ObmZlm0Wm2dvh+zZ8+2WVsI46ZQSK3+8YUUPn+nFD5/p+QT/qBYfqK3n+wm+8lutern0bKz5XzY9q1vJYW69m++dZgbSdPT0zEajZV6Nfz8/Cr1ZlwnOTm5yvJlZWVkZGRUWP/aa68xa9YsBg8ezKlTp+4YT35+Pnl5eZaltLT0Ho1kbI13u764NGgJQGFSHBlRv9s4IhkZGRnbkXPuCDnnIwFw8g7Ev8eoO+xhXWyadJSVlREVFVVp1LVBgwbd8lrWoUOHKpUfPHgwkZGRGI1Gy7rXX3+dt99+myFDhhAVFVX7wVuBFStW2DoEq1EXbgqVhqAhEyyvEzYtAcls9eOC2G0HYvuJ7AZi+4nsBrXnl/DbYiSzCYCA/mNRu3jWSr3VweZPryxYsICJEycyfvx4WrZsyYIFC2jYsCGLFy8GYO7cuXz99Y0ZQRcscqrxAAAgAElEQVQvXkxwcDCffPIJLVu2ZPz48UyYMIF//etfljIzZszggw8+4LnnniM+Ph5/f3/8/f1xcXGpc7974fr1eRGpCzf/3n/DyTsQgJzzkeT+L7uvC0RuOxDbT2Q3ENtPZDeoPb+i5EuWyeDUzq7UG/xsrdRbHWyedPzwww+8+uqrvPPOOxw/fpzevXszbNgwrlwpnx8jMDCQhg0bWsrHx8czbNgw+vbty/Hjx3n77beZOnUq69evt5R58cUXcXJyYt26dSQnJ1uWmx+rtUdCQkJsHYLVsLabxsOXwAF/B0Aym8p7OeoQkdsOxPYT2Q3E9hPZDWrXL3HbKkwl5Tfd+nYZjs4/uNbqvhds+vTKdRYtWsSiRYuq3DZ+fOVBTfbt20fHjh1vWV/jxo1rLba6JC8vz9YhWA1ruzV4aDIqbflAYKmHNlKUVLdT14vcdiC2n8huILafyG5Qu37G/CySdn1P/aETUChVNBg+mdgVM2ut/rtFQfkdpfc1er2ejRs38sgjj1gev5JxHNyahRHyQvnltbL8LE7Pf9Yy4ZGMjIyMTDkKtZY2M1bh5OVP1ukI4r77AMlY8wcm7uU71OaXV2RucP2ZbxGxlptCpabhiH9YXidsXmaThEPktgOx/UR2A7H9RHaD2veTjKVcXvcpMUte4+Lqd2ol4bhX7OLyioxMdfHrMRLn/12bzL98hoyo7XfYQ0ZGRub+Jff8UZseX+7psCMiI+vuaYu6xhpuGncf6g0qH6lPMpu58stCkGxztVDktgOx/UR2A7H9RHYDMf3kpMOOuHz5sq1DsBrWcGvw8IuonPQApP3xG4WJsbV+jLtF5LYDsf1EdgOx/UR2AzH95KTDjrg+br+I1LabZ+seeLfrC0BZfjaJ21bWav33ishtB2L7iewGYvuJ7AZi+slJh4zDoXJ2peHIVyyvr278D6bCXBtGJCMjIyNzN8hJhx3x7bff2joEq1GbbvWHT0br7gNA9pmDZB7fXWt1VxeR2w7E9hPZDcT2E9kNxPSTkw47IiwszNYhWI3acnNv3hHfzuXTUhuL8rn88+e1Um9NEbntQGw/kd1AbD+R3UBMPznpsCNat25t6xCsRm24KbU6gkdPs7xO2LyUspz0GtdbG4jcdiC2n8huILafyG4gpp+cdNgRxcXFtg7BatSGW9CQCZYJ3XIvHif9yOYa11lbiNx2ILafyG4gtp/IbiCmnzwMOvIw6I6Ae4twWkz8CABTaTFnPn2ekoxrNo5KRkZGRkYeBt1BefPNN20dgtWoiZvaxYNGY96wvE7c8pXdJRwitx2I7SeyG4jtJ7IbiOknJx12hFot7qj0NXFr9NjrlqdVcs4dITXi59oKq9YQue1AbD+R3UBsP5HdQEw/OemwI44fP27rEKxGdd18uz6EZ2h3oHwG2Us/zK/NsGoNkdsOxPYT2Q3E9hPZDcT0k5MOO+Ls2bO2DsFqVMdN59eQ+g9NsbyO//FfGPOzajOsWkPktgOx/UR2A7H9RHYDMf3kpMOOePLJJ20dgtW4VzeFWkuTJ2eh0uoASI34hZyzh60RWq0gctuB2H4iu4HYfiK7gZh+ctIhY5cEj5yKPqg5AEUpl7m6aYmNI5KRkZGRqSly0mFHrF271tYhWI17cTN0eQhDp/JRR02lRcT9930kY6m1QqsVRG47ENtPZDcQ209kNxDTT0467IgWLVrYOgSrcbduLg1b0XDEy5bXl3/6hKLkS9YKq9YQue1AbD+R3UBsP5HdQEw/OemwI0QcZ/86d+OmdvWi6VPvolRrAEjZ/5NdTOZ2N4jcdiC2n8huILafyG4gpp+cdNgRZrPZ1iFYjTu5KZQqmvz9/9B6+gKQF3eChE1L6yK0WkHktgOx/UR2A7H9RHYDMf3kYdCRh0G3B4JHT8e3y3AASnPSOfP5ZLt9PFZGRkZG5gbyMOgOyvTp020dgtW4nVtAv7GWhMNsLOXit/90uIRD5LYDsf1EdgOx/UR2AzH95KTDjnB2drZ1CFbjVm7eYQOpP3SC5fWltfMpuHymrsKqNURuOxDbT2Q3ENtPZDcQ009OOuyIM2cc78v2bqnKza1pexo99rrldcLmZWSdcIwbR/+KyG0HYvuJ7AZi+4nsBmL6yUmHHREZGWnrEKzGX910/o1o+sw/LU+qpB7aSPKeNbYIrVYQue1AbD+R3UBsP5HdQEw/OemwI5555hlbh2A1bnbT+TYg5IWPUTu7ApB99jBXNvzbVqHVCiK3HYjtJ7IbiO0nshuI6ScnHTJ1ipMhiBaT/oXGzRuAgivniPvv+yDgo2EyMjIyMhWRkw47Yv369bYOwWqsX78erVcAIS/8C627AYDCxFjOL38Tc2mxjaOrOSK3HYjtJ7IbiO0nshuI6ScnHXZE/fr1bR2C1ajXLJSQSZ+g9fQDoDApjphlb2AqyrdxZLWDyG0HYvuJ7AZi+4nsBmL6yUmHHdG5c2dbh2AVdL4NKOnxHE7eAQAUJcdzfukMTIW5No6s9hC17a4jsp/IbiC2n8huIKafnHTIWBWXBi0JefFzipU6AIrTrhKz9HWMBdk2jkxGRkZGpq6Rh0HHfoZBVyqVQo21796iE02feReVtnyAm4LEWGKXz3S40UbvBtHa7q+I7CeyG4jtJ7IbOI6fPAy6g/Liiy/aOoRawztsIM3Gf2BJONyL04hZPF3IhAPEaruqENlPZDcQ209kNxDTT23rAGRu4OHhYesQao5CSdCQ5wjs96RlVebJfQwMNrOrRNzJ9IRou9sgsp/IbiC2n8huIKafnHTYEbGxsbYOoUaonN1oMnYWHiE3bn5KPbSRK7/8m7jH/mbDyKyPo7fdnRDZT2Q3ENtPZDcQ009OOuyIffv22TqEauMc0Jimz76HzqceAJLJxNVfvyT14C+AY7vdDbKf4yKyG4jtJ7IbiOkn39NhR0yYMOHOhewQQ+dhtHz535aEoyw/m/PLZlgSDnBct7tF9nNcRHYDsf1EdgMx/eSeDplqo9a7E/y31/Bq09OyriDhPBdXv0tpdqoNI5ORkZGRsUfkpMOO+PXXX20dwl3j3qITjcbMQOvuY1mX9sdvXNnwBZKxtFJ5R3KrDrKf4yKyG4jtJ7IbiOknJx12hLe3t61DuCNqFw/qD3seQ6ehlnVl+dlc/ukTss8cvOV+juBWE2Q/x0VkNxDbT2Q3ENNPvqfDjujRo4etQ7g1CgWGzsNo8/qqCglHzrk/iF4w8bYJB9i5Wy0g+zkuIruB2H4iu4GYfnJPh8wd0Qc1p+GIf+DaqLVlnbEon8Qty0g7/JsNI5ORkZGRcSTkYdCxn2HQtVotpaWV74ewFU6GIIIeHI93u34V1mf8uYOrvy2+p9FF7c2ttpH9HBeR3UBsP5HdwHH85GHQHZTx48fbOgQANO4GGo56lTavrayQcFyfrO3Smg/veThze3GzFrKf4yKyG4jtJ7IbiOknX16xIwwGg02Pr/MLJqDPY3iHDUSp1ljWl+VnkbTjW9L++A3JZKxW3bZ2szayn+MishuI7SeyG4jpJycddkR8fLxNjuva5AECeo/BM7RbhfWm4gKS9/1Iyv6fMJcU1egYtnKrK2Q/x0VkNxDbT2Q3ENNPTjrsiK1bt9bZsdQunvh0HISh8zCc/RpW2GYsyift0EZS9v+EsSCnVo5Xl262QPZzXER2A7H9RHYDMf3kezrsiMmTJ1u1fqXGCc82vWjy1Ls8MHsNDR6aXCHhKM1O5eqvizg59wkSty6vtYQDrO9ma2Q/x0VkNxDbT2Q3ENNP7ukQHKVWh3uLcLwf6ItHq66onJwrlcm9eJz0PzaRdXIvktlkgyhlZGRkZO4H5KTDjti2bVut1KPzb4RHSCc8Qjrj2rhthZtCr1OWl0l65DbSj26hJD2xVo57O2rLzV6R/RwXkd1AbD+R3UBMPznpsCOcnJzufSeFEn29prg2aotr47a4NW6Dxq3qoXONBblkRR8g68Qe8i4er9NejWq5ORCyn+MishuI7SeyG4jpJycddkTfvn2JiIi45XaFWoPO0AB9UDP0Qc1xqd8C53pNUWkrXzK5TklmEjkxR8mOjiDvwjGbXT65k5ujI/s5LiK7gdh+IruBmH5y0mFvKBSoXTxx8glE59sQZ/+G6HwbovNriJN3AAql6ra7G4vyKbgcTU5MJDnnj1CSllBHgd+/tGvXjjbt2vP9L5uIPnmcr778N8nJybVSt0ajYfRjY3hq3ESaNG+OWuuEWQLJWIJKpUWp0VBaUsyRvTuQNDpatgrFjJLkawlIxjJKTWZMxQX07DsArc6ZMrOEsayUkoICSkqLcXbW4+yso6jURH52Bt4+Pmid9CiVCkxmkCQzaqXE+ejTTHptFlqVAgUSRjMYzWaUCgWSVD6wsbNGQZkJSk0SWhUUlZSiUKnRqdWAmVKjGbMkUVpUyIXzMThpNQQ2bIxKraY0P4f8klKMRYWUGM1kZWdx7MgffLXo36SnpwPg6enJ+Ocn06l7T3Jzcvh2+WIO7N9vea86derEuMkv4+Xtw4mooyxf/AVt2j7A2PEv4OLqwuH9e1j11VLy8vIAcHd3Z9zEF+jYqQtLV6/hu5VL2LN7923bIygoiHdem0HfLt1Qa53IzsslMy0NJzcXmtRrgE6roaisjDlfLmTJ0qUADB44kHGjx6DXOXMtKx0/Dy9UKNi8bw879+9l4pNP0aZ5CzJzcig0llLfx5fUzAy++GYVpaWlvPvq67QPbU2Zycj2/Xv5fNkShg0YxMMDBhIa0gpPL0+kMiNKnRNFpSWU5BUgmU0onJxwcXLizJV4pjz+dxZ9/y0dWoXSoWUoOicdSp0WCZBKylAqFJgUEoVlZXjonFFKUKaAq8nX8HB1x9vFFZVKSYkkcSz6NMaCQkwKqF8viIb+Aai1GpQqFQqNitL8QpJSUvh9/14WLFlEYuKtL98qFAoGDhjA61Neomm9+uTlF7Bx53Y+X7oYd3d3po6fSPNGjYm/lsDCFV8RGxtbo8+TjO2xi2HQp0yZwowZMwgMDCQ6OppXX32VAwcO3LJ87969WbBgAa1bt+batWvMnz+fJUuWVCgzatQo3n//fZo2bcrFixeZPXs2v/zyS5X11ckw6AoFKp0rGldP1C6eqF09ULt4onX3Qevlj9bTD513AGp3H5Rq7V1XW5JxjYKEGPIunSL/0mmKki+BZLaOQw1wdXUlPz/f1mHUKgqFgi+Wf41zo3Zsi8sjIa+MFgYXHgtx5fsln7J6+bIa1R8cHMzKHzag8wnEQ6/j6OUsfjyeQG6xkY4NPHmyYwO+jbxMSm4pr/Ztht5JxbKD8ZxIzMbLWcsjbQPpFOyFXqOioNTE5uhkdp1PxSzBgBBfRj4QhItWxddHriBJEn2a+7L7fCrDWgfy2+kk9l9MR6NSMrilP90auvPtn9eY2C0YVycNO8+nEVbfk7V/JnAsIRt3nZrHwurTPsiDnOIyTl3LZXN0Mn2aG+jU0ItvjlwhNj2fQHcdz/doRICbMysPXybyShZuTmpGta/HoBA//ojP4r9RV8koKKG1vxujm+tZPP+f5ObkMPPDBfwcW8iJpHzcdWqGNHElsCyFZ8aMZPHKbynybsLmuAIyCksJq+fOP3o3ZvuZJDbFZJJfYqJDkCuPNtPzzrQpKBRK/vnJF/xysZAzSXloNBoGN3ahkTKLsSMfqvI88PKE55k+eiyx85bg0bo59Qb3Im71eppPGsu1zbu58tNWzGVGgob3I+SVcRRqlcRfjEOx/zipa7dgzC8gYHAvmk8cw6kPFxE0ajAeIU2Jfu/fZJ+MQd8ggBYvPoVkMnP+i28IW/weJZevcfbjZRReTcbrgRDavDsVJ4MXZ+YvJWnrPtR6Z4LHDCPwwV5o3N3IOnGWc5+tpCgpDZ9ObQmZ+izxG3cQ2CMcQ6cHiFv9M/Hf/4pCpaT76n+RvCOCiyt+wlhYRL0hfQj5x9Ocev8/pB86RtDDA2gzawpxq9dz6eufMRYVE/RQf5pNGEPW6Rh0Bi/OfvwVuecv4da8ESH/eBqXRvXJj7tK1LQ5eD4QQtArT7N060YWLltS6f10c3Pj19Xf0cLHj4wDUcSt/InitCx8e3Sg2ZsvUFxQwMX/9x9yYy7h1qQBflMeZ3fCRWb88x1LHSKeV27GUfzu5TvU5knHmDFj+Oabb3jxxReJiIhg0qRJTJw4kdDQUK5evVqpfKNGjTh9+jTLli1jyZIl9OjRgy+//JInn3yS9evXA9C1a1f279/P22+/zc8//8zIkSN577336NmzJ0eOHKlUpzWSjuC/vYaTdyBqF4/yREPvgUJ1+16K22EqKaI47QrFqVcpSr5EQcJ5ChNjMRXl1Uq81ua5555jxYoVtg6jVpn+5mxcuo5iS2w2g/1K2J564/rrWz0CmPPyUxw7dqza9f8eEUk83jTzdeX7qKv8eTW7wna1UsH8EW1ZdvAS47sGM3NjNCap4se5ZxMfJvVowowNp0jOLa6wzVuv4b3hrflsdyxPdW7InK3nWDC6HbM2niavpOLIs6MbmOjSoR2uTmre23qWGQNa8OaG0xjNFY839+HWrP3zKicSc2kX5MHglv58vPO8ZbuXXsPbQ1rx5oZTlJkq7ts+yINBfymvVMC7fYPw0Kl5fduVSsfrUM+Vv4c48UtcGfsv51rWvzUohE3RSZy6lluhvFal5KMB9TBKErN3JVFqMldouzYBLvTgEs8/82SF/bp368bSF6ZzctLbeIe3pelzf+Poi+/Sc+1Cjr01n4JLFXsUtT6eDNixmsMTZ5IVFV1hm0rvTJ9fFpN/6SpHJv0ff6XphMcw9OhI5pGTxC7+7sZ+zjp6/fhvDjzxCsb8iucpj9bNaT/vDfY+/HzFyhQKGq35mBb1G3Jk8ttkn4oBoOuKjzi3YDnZp89XKK521dNz7UL2P/YPOn/5T6I/Wkru2QsVy7i50H/rSnYOeBpTcUmFbW1mv4jW4E3uuYtcWPI9ACGfz2LqN4uJOFhxJup1K76mrUlH4sYdJG3bX2GbQqWix38XlL+38Td6Shq9MZEvYo7y3x/XAmKeV27GUfwcau6V6dOns3z5cpYvX865c+eYNm0aV69eZcqUKVWWnzx5MleuXGHatGmcO3eO5cuXs2LFCl5//XVLmVdffZXff/+defPmERMTw7x589i5cyevvvpqXWnh1uQB3JuFoQ9sgsbN+64SDrVURuG1i2SfOUTqwQ1c2fAfzi97gxNznuDY2w9xduGLXFrzIcl71pB34U+HSTgAAgMDbR1CraJUKhk+agxbYssTAS9NxS/DlSezeOWtt6tdf/8BAzmdqyI00B2TWaqUcAAYzRLfHL3CpJ6NWX4ovlLCAXAgLoO80jKyiypPGpVZWEZEXDqTezVh2cF4+jT3ZfvZlEoJB4DaXEZmYSlbzybzUOtAvj5SOQHwcNZgMkucSCz/oh/dPoivDl2qUGZE23p8e/RKpYQD4HhiDp7OGtx1N676miVYeSKLHIW+0vEA/ryWj94QxJ9JBZZ1ns4a9FpVpYQDoNRkJsmk48dzBZSaynsEb26708kF+DVrjY+PT4X9Zk5+mfNvfwZA8xee4PT7/8GrfSh55y9VSjgASjOyubjiJ/RBAZW2mQqLOL/4v+Sei6u0DeDiynV4tQ0h9n9f2tcJfnw4F1euq5RwAOREx1JwOQGXRkEVN0gSWZcTyL901ZJwuATXw1RUVCnhADDmF3Jx+Y+0ePlpSnPyKiUcAMa8AmIWfk3Dvw2ptO3sghW41PcnaHhfy7r4DxYzc/LLFcoFBQXRSK1H5+tdKeEAkEwmouctodnExyusv/LZ17z09LOW16KdV/6KiH42TTo0Gg0dO3Zk+/btFdZv376d7t27V7lPt27dKpXftm0b4eHhqNXq25a5VZ3XcXV1xc3NzbJotXd/meOvGPPLB9Yyl5VSkpVCQcJ5cmKOkB61neR9P5KweRmXfviY2BWzOP3JBI698wgtz67hzGcvcGHV/3Hll4WkRvxMbmwUZTlp1Y7DXrjddV1HJCAggMTCG5exMkorfpRS8kow1GtQ7fp7DRhEfAHkFZdx8lrlhOM6xxKy8dZriUm9dRds5OUsmvi4VLntcHwm3s5aErOLaFvPnSOXM6ssl1GqZG9sOkqFkqa+rpxMrDxwXIifK38m3IhVq1KSVVhWoUxLf7cqE6jrHE/MpoWfW4V18ZmF6DS3TtoPx2fRzNf1Rhz+bhy7zTG8XHQcvWn7X9vuZIaJDh06VFjn5+JGcWoGUP5LvygpDZ8u7UjeWfHX+81c27QbQ5f2VW5L2rofz9bNq9zm5O1B7rmL8Jck0qfz7Y+XsvMQPp3aVVqvLi4jYcMOy2vv8AdI3nX4lvUk74ggoH83UnYeumWZpB0RGLqFVVpvKirGbDRRcOUaWh9PAErSMvHVu1YoFx4ejuJiIplRp295jKzjZ3BrFlxhnbm0DF2xEaWyvM1EO6/8FRH9bHojqcFgQK1Wk5KSUmF9SkoKAQGVfyFA+cm+qvIajQaDwUBycvIty9yqzuskJiZaEheAXbt2sWrVKjZt2mTpedm+fTtqtZr+/fsDsHDhQkaPHk1QUBBJSUn88MMPvPLKK5QoMjm46QNKC/J45MEHwQ0W/3cxQ4YMoVG7RqSnS6xcuZ4ZM2YAEBERwblz55g9ezYAy5cvp3fv3jRv3pycnBy+/PJLZs6cCcCRI0dISEhg1KhRAKxevZrw8HBCQ0MpKipiwYIFzJw5E6VSybFjxzh//jyPP17+i+H777+nVatWtG/fHqPRyEcffcRrr72GTqcjOjqaY8eO8dRTTwGwbt06goODCQ8PB2DOnDlMnToVNzc3YmJiiIiI4LnnngNgw4YN+Pr6WhK7+fPnM3HiRLy9vYmLi2PPnj0Wty1btqDX6+nTpw8An376KWPHjsXf35+EhAQ2bNjASy+9BMCOHeUny4EDBwLwxRdfMGLECOrXr09KSgrfffcd06ZNA2Dv3r0UFhYydOhQAJYsWcKgQYNo0qQJmZmZfPXVV7zxxhsAHDx4kLS0NEaMGAHAihUr6NGjByEhIeTl5bFw4UJLvJGRkVy+fJnRo0cD8O2339KjRw/citIZGVjKz0k6fLRmHg8qJq5QxdVCJX0MZUj5Rpo1a0aLFi0ICwvDbDbz4YcfMn36dJydnTlz5gyRkZE888wzAKxfv5769evTuXNnGgcFclKpwJwaT1BxMb18Sjmdq2awX3mPxZEsDa5qiTbuRpJiT+OkhP6+JbirJVJKlERlqxnmX17WQyrEX1VI26DyyysbkpzobSgt/4WvkTCbyng8qBinjDhauCrwkIyEeZT3dmxK0dLZ04ifkxm9UzZpJgMliTE8Wb+YkzlqikzQyau87FVzGfWkYh4PKibfqECpkHj8f8c8l68iq1RJcUIMTzYoZnuKlhBXIw2czRSbFWxIcmJMUDENyq5RolQRpDPR06c8YdmbrsGYlczjQcUYJVh3TcfoesWoFRBfqMJNVUYnpwxaBhk5kKEhkDwam7IYE1TMD4k6RgSWoFNKXC1SEpOvpiQxhicaFBORrsFLa8bPqbztfkx0Yqh/KU1JIy8sjBMnTvD88+WXK0pUStQ92qPu2Z5LaiPonMhpFkhZSD209bwo23IQpxfKP49lO/4AtQrFI31ICnQHNz3aR/uhrOeLOTmd0nU7cZr+FPHOoOrWFkrK0AzqWn6cZT+jGN6Dy84KtBMfpXT1JnTT/g5AllpCHRaCqnPr8rKrNqLu2R5Vs4ZIOfmo8svI7tgcXRM/jEejMV9LQzuiL0Z3PYp6BjSP9EHVqjH53p54Rl9GN+NpUKownYjBFHsV7d/KP2OKXUdJLsqncGBHdM0DKP7kW5xeeRKFzgnTmThMJ86jeW4EV9w0KEOCUTYIQN2xFQDFH63iqtpEmY8exaAuKPZE4fTsQ2RroE2bNpZzhJ+fH+Y8JTn1DejeHIf5UiJlu47iNOHR8vdw20EUrnrilGXo3hxH8b/XoB0zCKW/DzlaBe7u7rz00kuo1Wq6dOlil+eIsLAwWrduTXFxMZ988glvvvkmarWa48ePc/bsWZ58svwS3tq1a295jrh48SINGjSo8hwB8OGHH/Liiy/i4eFBbGws+/btY8KECQD8+uuveHt706NHDwA+/vhjxo8fj8FgID4+nq1bt1pGPN22bRtOTk707dsXgM8//5wxY8YQGBhIYmIi69atY+rUqUD596LRaGTw4MEALFq0iEcfLW+3u8Gm93QEBgZy7do1unXrxuHDNzLvWbNm8fTTT9OqVatK+8TExLBy5UrmzZtnWde9e3ciIiIsyUZJSQnPPvssa9assZQZO3Ysy5cvx9m58uOl169HjR07lqKiGxOblZSUUFpauVvaWsyePZs5c+bU2fHqEhHdNu89xJyoYkqM5V9aaxN1lm1tAtxomrSft998rVp1N2/enHeX/UTDoHqolApeWXeiynJDQwMIq+/BwUsZ7IlNr7RdAXz9dDjPfhNZ5Qd9Wr9mKIA9semUmsx0b+LD0ohLlco9HlRMx/BOHEvIJre4DKNZYtvZion99XtMpv98EoBX+jbjt9NJXEy/celjSCt/VEoFm6Krfrrn01EP8PovpzDddCmla7AnA1r4Muf3qp9cWP33MCZ8f5yy/+2jUSn46JEbcfyVGX0bcz41nw1n0ixuN7fdvL5+DO3RgbKyG700i+b/i+AfDpB98hwP/PMVEjbsoPBaKu0/mM7hiTOrPE74wne4uOInso6fqbSt1WsTKSso5MJN92xcR+2iZ+Ce/7Kj798xFty4lOLfvxte7VtxbkHV1/h7fP8Zf7wwG2NeQYX1ngteI6xVa3YPLf+BoHbV0/WrDznwxCtV1tNy2njyL14h+PHhRPx9epVlQt98gfRDx0jdd7TCeud6frR7fzpqVz0HHi//kvJsG8LlJ7iAFq4AABX1SURBVHozZcaNz4KzszMHv1+Pn5OevY9OrtSrAxA0YiDO/gYuLL1xHtf5+aCd+xIPPTMWEPO8cjOO4ucw93Skp6djNBor9UD4+flV6qm4zvWejL+WLysrIyMj47ZlblXndfLz88nLy7MsdZlwyDgen859j1e6+KJUVFzv4azhmVA9/1kwv9p1x8bGYkyO5cTVDEBics/GlcoEeTozNNSfL/bFMbpdEP5ulQcSemNgC3KLyujVrPIU2V2Cvajv6czyw5cZ1zWYxJwiGnnraVvPvVJZPzcnrmYV0qeZgXPJeQxvHUCQh65CGaNZosxsZkK38i7xNVFXebl3U1ydbvQe7jyfyoOt/KnvWTn5n9yzMfsvpldIOHxctIxuqsXHlE29vxwPYEKYgZ2//czkcF/LujKTxOH4TJ7p3LBS+WAvPQZTJt29S2noVTmGv7f1ZuPabyokHABzFn5Gk3nT0Xi6E7v4O9q+OxVzSSklmdk0GPVgpXp8e3TEr28XfHqHV9rm2aYFfn07EzS0D1ovjwrbFCoVHT+dzcWV6+j0xT8r3AuWsvswfj3D8QoLrVRnsxeeQOvtUel+D52/AdfGDdB4utF04hig/L6NrBPnLK8rxPZAS3x7dCTh113knIujyfjRlcp4hYUS/MRDZBw9VWG9SudEh09moXZzIeY/3wCg8XAj6L2XmfP5pxXKFhUVsfHgXrITkmj3QeXERl8/gOYvPEH8dxst65ROWpoueJO3a/C5krE9Nn965fDhw0RFRVm60wGio6PZsGEDs2bNqlR+3rx5PPzww7Ru3dqy7ssvv6R9+/aWrv01a9bg5ubG8OHDLWU2b95MdnY2Y8eOrVRnnTwyexd069aNQ4dufR3VkRHVbdRjj/PSjNnEpOZz2ehKUxczDZyKmfbCOM6dO1ejurVaLZ9+uYz23Xrj4+NDidHEtrMpZBWW0aeZgXqezmw4eQ2DixNDWvtTVGriTFIuUVezMbhq6dPMQFp+Ka0C3MgrNpJRUMqu2DTMZonBrfzxddGiVilJySvmyOUs+jYzcDmrEB+9llKTmT2x6WjVSgaF+JGZlkJimY7BLf1BAXEZhbhqVSTmFHMkPhNvFy1DQwMwSxLxGQX4uenYeyENJ5WSIaH+HEvI4XhCNg299PRs6oNGpeRKViF7YtPx0Kl5qE0gaqUCFLD1TArJucW09ABfKZeXn3uK4uJiFq36jjwnH6JzwE0t0dlXyYbvVvHF5wt4evxEnpkylcg0M1mlClq6SzxQz5WcwlIiksooMEI7L1DnJfPiuPLLFYu+/o4yV3+uZhVSqtbT2VfBtp/XsmBe1b8s27Rpw5p/L0Z56gKF8YkEjxlG5rEzOHl7ovFwLX9ktrSUBiMfxL1VU7Yd3E/s+ViGde5OwZYIKCyi/sjBaD3cufzDJtyG9sS7cUOubNmD8WQsLs0bEfRQP1J3HSInJQ3/xx7ESa0h47e95MfG4x3eFr/+XTFp1KSeOEPu1gNoXF2o/+hATEUluDZtCJLE5TW/kX8pgYCB3fFo1ZSYPQdp3K4tbiGNKUxI4vKaTRjzCwiZOg7JbObS6p8py82jwcjBuIc04dLqnylITCFoeF8MXdpTmJBM/H83YCwqJviJh3D2N3Bt+wECB/ckdc8fZEadxiO0KYEP9kbj4Ub64eMkbd2HV9f2FLYIYsKbr3Hq1Kkq39N/vjGTpx8ZibNRIuGX7RSnZuA7oDsFDQ2oVCoK90ZhirmMskkQTr3CeGPeB+zau9eyv6jnles4ip9DPjI7efJkDh06xAsvvMDzzz9P69atuXLlCnPnziUoKIhnny2/Y/n6I7NLlixh2bJldOvWjcWLF1d4ZLZbt27s27eP2bNns2HDBkaMGMEHH3xQp4/MVodOnTpx9OjROxd0QER2U6lUjBs3jrz8fM7HxHD8+PFard9gMNC3b1/atWuHl5c3znpnzp09i6+vL82aNyfu4kWWLl1KcHAwbdq0QalUWhIeFxcXzp07x7hx4+jbrz+S2cSBiAhysrNJTkmhflAQ3j4+SJLEgf376dChA2EdOhJUL5DS0jIuXYojOTmZ5s1bEBAQQGFhIcUlxZiMRkwmMyazCS9PLzQaNfHx8bi5uVOvXiAnTp7kWmIioa3b4ObqQkFBAQUFhZSWlnApPp7du3ah0Wjo268femdnjh49iqenJ4mJieh0OgqLiog+fZro6IqPm7Zo0YJ27dqRn5/Prl27KCm58cimWq2mX79+eHl5ER0dTXR0NM7OzvTv3x+9Xk9UVBRxcRWfGGnatCmPPPIIMTEx7Nq1i+Liio8VV0V4eDjDhw1DqVJx8eJFSoqLKSwqonv37rRp3ZqTp04xd+5cCgoKLG3Qv39/dDodZ86coWnTpmi1Wg4dOkRiYiIdOnSgebNmpKSmkpWVRcuQEDIyM9mzZw9ms5l+/frRt08f8gsK2LJlCydPnqRBgwZ06dKF0NBQenTrTpOmTUhOSWHfvn0oFArUKhUpqanl9x65uhIZFcX7779P586dGTZ0KE5OTiiUSoxlZUiAl4cHOXl5nDx5kn79+uHt5UXM+fNEHj2Kh6cnffr0ISgwkCORkaxfv56goCDy8vLQ6/WMGjUKZ50Ok9mMVqMhIzOTqMgo/jjyB1FRUXd8P/V6PYMHDyY8PJyka0ns2r2Ls2fPAuXDHwQ3bEjitWtEREQg/eUyjMjnFXAcv3v9DpVsvUyZMkW6dOmSVFxcLEVGRkq9evWybFu5cqW0e/fuCuV79+4tRUVFScXFxVJcXJw0adKkSnWOHj1aOnv2rFRSUiKdOXNGGjly5C2Pr9frpR07dkh6vd6m78Ps2bNt3haym+x3v/mJ7Ca6n8hujuR3L9+hdjEM+qJFi1i0aFGV28aPH19p3b59++jYseNt61y3bh3r1q2rlfhkZGRkZGRkagebZ0m2Xuylp8Pb29vm74XsJvvdb34iu4nuJ7KbI/ndy3eozUcklbnBzTe+iobIbiD7OTIiu4HYfiK7gZh+ctJhJ2i1WsaNG1ejUVDtFZHdQPZzZER2A7H9RHYDsf1s3jVj68UeLq+4ublJkiRJbm5uNn8/ZDfZ737xE9lNdD+R3RzNT768IiMjIyMjI2N3yEmHjIyMjIyMTJ1gF4/M2gtVzctSl8c2Go04OztjMplsFoc1ENkNZD9HRmQ3ENtPZDdwLL97+e60+Yik9oCPjw9r1661dRgyMjIyMjIOy+OPP26ZA+1WyEnH//Dx8akww6yMjIyMjIzM3eHs7HzHhAPkpENGRkZGRkamjpBvJJWRkZGRkZGpE+SkQ0ZGRkZGRqZOkJMOGRkZGRkZmTpBTjpsQJ8+fZAkqcolPDz8lvutXLmyUvlDhw7VYeR3z6VLlyrF+uGHH95xv3fffZfExEQKCwvZvXs3oaGhdRDtvREcHMxXX31FXFwchYWFXLhwgf/3//4fGo3mtvvZa/tNmTKFuLg4ioqKiIyMpGfPnrct37t3byIjIykqKuLixYtMmjSpjiK9N9566y2OHDlCbm4uKSkp/Pzzz7Ro0eK2+9zqsxkSElJHUd897777bqU4k5KSbruPo7RdVecPSZL4z3/+U2V5e2+3Xr16sXHjRhITE5EkiREjRlQqU51z36hRo4iOjqa4uJjo6GgeffRRa4Rf69h8CNX7bdFoNJK/v3+FZenSpVJcXNxt91u5cqW0efPmCvt5eXnZ3Keq5dKlS9L//d//VYjVxcXltvu88cYbUk5OjjRy5EipdevW0vfffy8lJiZKrq6uNve5eXnwwQelFStWSIMGDZIaN24sPfzww1JycrL08ccfO1z7jRkzRiopKZEmTJggtWzZUvr000+lvLw8qUGDBlWWb9SokZSfny99+umnUsuWLaUJEyZIJSUl0qhRo2zeLn9dtmzZIj377LNSaGio9MADD0i//vqrFB8ff9uhmvv06SNJkiQ1b968QjsplUqb+/x1effdd6VTp05ViNNgMNyyvCO1ncFgqOA1YMAASZIkqU+fPg7ZbkOGDJHef/99aeTI/9/e/YdEff9xAH/VV60M5ia3PGszG0ZagYgVKqQmnWN/lL8WxJLJFRX9UdkvkwguCtwgdMtZi4LdEmr+ESyN0sK6laW2cgaVYpJamXeOVGJlnh48v3/09b47u/O8W34+d+35gCfo+/P+cO+3L/v00vNzlwUAyMjIcDjuzbUvISEBIyMjKCwsxIIFC1BYWIjh4WEsW7ZM9f26ieoL+NcnICAAFosF+/fvH3ee0WjEr7/+qvp6J5LOzk5s377do3N6enpQUFBg/zwoKAgDAwPYtGmT6vtxl927d+PRo0d+V7/GxkYcO3bMYaylpQVFRUVO53/77bdoaWlxGPvxxx9RX1+v+l7cRaPRAACWL1/ucs7of14hISGqr9ddDAYDmpubJzzfn2v33Xffob29/b2om7Omw5trX0VFBS5evOgwVl1djTNnzqi+x/HCp1d8wOrVq0Wj0cjPP//sdm5qaqr09vZKW1ubnDhxQj7++OPJX6CX9u7dK8+fP5fm5mbZt2/fuE8/zJs3T8LDw+Xy5cv2seHhYbl27ZokJSUpsdx/JCQkRPr7+93O86X6BQYGSnx8vMPXXETk8uXLLr/miYmJb82/dOmSLFmyRAICfPsFjkNCQkREJlSn5uZm6enpkdraWklNTZ3klXlv/vz58uzZM+no6JBffvlF5s2b53Kuv9YuMDBQcnNz5aeffnI711/q9nfeXvtc1dPXr5dsOnzAhg0b5NKlS9Ld3T3uvOrqalm3bp2kpaXJrl27ZOnSpXL16lWffOvjI0eOyNq1a2XFihVSVlYm+fn5cuzYMZfztVqtiIj09vY6jPf29tqP+arPPvtMtm7dKsePHx93nq/VT6PRSEBAgEdfc61W63R+YGCgaDSaSVvru1BSUiJ1dXXy4MEDl3PMZrNs3LhRcnJyJDs7W9ra2uTKlSuyfPlyBVc6Mbdu3ZKvv/5aPv/8c9m4caNotVqpr6+X0NBQp/P9tXaZmZny4YcfjvtDmT/VbSxvr32u6unr10sRH/h1y/sSg8EAd+Lj4x3OmTNnDmw2m1fPq2q1WlitVmRlZfns/kaTnZ0NAAgNDXV6PDExEQCg1Wodxk+cOIHq6mqf3V94eDgePnyIkydP+nz9xiY8PBwAkJCQ4DC+b98+tLa2Oj2nra0NhYWFDmNJSUkAgLCwMFX2MZGUlZWhs7MTc+bM8fjcqqoqVFZWqr4HdwkODobZbMaOHTveq9rV1NSgqqrqvanb2KdXvL32Wa1WrF271mHsq6++wuvXr1Xf43jx3d+p+aGysjKpqKgYd05XV5fD53q9Xvr6+qSqqsrjx7NYLPL48WOZP3++x+d6w5v9jWpsbBQRkaioKPn999/fOm6xWETkTfc++rGIyKxZs97q5ieLp/sLDw8Xk8kkDQ0NsmnTJo8fT+n6jfX8+XOx2Wxv/WQ03tfcYrE4nT8yMjKhl0BWQ2lpqaxevVqSk5Pl2bNnHp/f2Ngoubm5k7Cyd2twcFDu3bvn8vvJH2sXEREhK1eulOzsbI/P9Ze6eXvtc1VPpa6X3mLT8Q719fV5/I9Xr9dLeXm52Gw2jx8vNDRUPv30U7e3yb0r3uxvVFxcnIiIy7V2dnaK2WwWnU4nd+/eFZE3z+WmpKTI3r17vVuwhzzZ3+zZs8VkMklTU5Po9XoB4PHjKV2/sUZGRqSpqUl0Op2cO3fOPq7T6aSystLpOQ0NDbJq1SqHsfT0dLlz545X38OT7YcffpCsrCxJTU112RC7ExcXp1qNPBEUFCQxMTFSV1fn9Li/1U7kzfXxzz//lAsXLnh8rr/UzdtrX0NDg+h0Ovn+++/tY+np6VJfXz/pa/6nVP91y781aWlpAIDo6Ginx1tbW5GZmQkRwcyZM3H48GEkJCRg7ty5SElJwc2bN/H06VOfu6U0ISEB+fn5iI2NRWRkJNasWYPu7m6cO3fO5f5E3tw2NjAwgMzMTCxatAinT5/2yVtmR59Sqa2txezZsx1u0fO3+o3eMqvX6xEdHY2SkhL89ddfiIiIgIi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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fiPpDWfqBaMI"
      },
      "source": [
        "### Initializing priors"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GbeDlrILBcNz"
      },
      "source": [
        "## The actual MCMC algorithm starts here\n",
        "# Priors\n",
        "aa  = np.ones(KK)  # Uniform prior on w\n",
        "eta = 0          # Mean 0 for the prior on mu_k\n",
        "tau = 5          # Standard deviation 5 on the prior for mu_l\n",
        "dd  = 2          # Inverse gamma prior for sigma_2, parameter d\n",
        "qq  = 1          # Inverse gamma prior for sigma_2, parameter q"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 589
        },
        "id": "eH5GGs5RAl4o",
        "outputId": "a0bb6ccd-578b-46b3-864e-98ac5b634a34"
      },
      "source": [
        "from scipy.stats import beta\n",
        "from scipy.stats import invgamma\n",
        "from scipy.stats import beta\n",
        "\n",
        "# Number of iterations of the sampler\n",
        "rrr   = 6000 # Number of iterations\n",
        "burn  = 1000 # Burning period\n",
        "\n",
        "# Storing the samples\n",
        "cc_out    = np.zeros((rrr, n))    # Store indicators\n",
        "w_out     = np.zeros(rrr)         # Sample of the weights\n",
        "mu_out    = np.zeros((rrr, KK))   # Sample of mus\n",
        "sigma_out = np.zeros(rrr)         # Sample of sigmas\n",
        "logpost   = np.zeros(rrr)         # Used to monitor convergence\n",
        "\n",
        "for s in range(rrr):\n",
        "  # Sample the indicators\n",
        "  cc = np.zeros(n)\n",
        "  for i in range(n):\n",
        "    v = np.zeros(KK)\n",
        "    v[0]  = np.log(w) + norm.logpdf(loc = mu[0], scale = sigma, x = x[i])    # Compute the log of the weights\n",
        "    v[1]  = np.log(1 - w) + norm.logpdf(loc = mu[1], scale = sigma, x = x[i])  # Compute the log of the weights\n",
        "    v     = np.exp(v - max(v)) / np.sum(np.exp(v - max(v)))  # Go from logs to actual weights in a numerically stable manner\n",
        "    cc[i] = np.random.choice([0, 1], 1, p = v) # C_i sample \n",
        "\n",
        "  # Sample the weights\n",
        "  w = beta.rvs(a = aa[0] + np.sum(cc == 0), b = aa[1] + np.sum(cc == 1), size = 1)\n",
        "\n",
        "  # Sample the means\n",
        "  for k in range(KK):\n",
        "    nk    = np.sum(cc == k)\n",
        "    xsumk = np.sum(x[cc == k])\n",
        "    tau2_hat = 1 / (nk / sigma**2 + 1 / tau**2)\n",
        "    mu_hat  = tau2_hat * (xsumk / sigma**2 + eta / tau**2)\n",
        "    mu[k]   = norm.rvs(loc = mu_hat, scale = np.sqrt(tau2_hat), size = 1)\n",
        "\n",
        "  # Sample the variances\n",
        "  dd_star = dd + n / 2\n",
        "  mu_temp = [mu[int(c_i)] for c_i in cc] # Create vector of mus\n",
        "  qq_star = qq + np.sum((x - mu_temp)**2) / 2\n",
        "  sigma = np.sqrt(invgamma.rvs(a = dd_star, scale = qq_star, size = 1)) \n",
        "\n",
        "  # Store samples\n",
        "  cc_out[s, :]   = cc\n",
        "  w_out[s]       = w\n",
        "  mu_out[s, :]   = mu\n",
        "  sigma_out[s]   = sigma\n",
        "\n",
        "  for i in range(n):\n",
        "    # Computing logposterior likelihood term\n",
        "    if cc[i] == 0:\n",
        "      logpost[s] = logpost[s] + np.log(w) + norm.logpdf(loc = mu[0], scale = sigma, x = x[i])\n",
        "    else: \n",
        "      logpost[s] = logpost[s] + np.log(1 - w) + norm.logpdf(loc = mu[1], scale = sigma, x = x[i])\n",
        "\n",
        "  # W term\n",
        "  logpost[s] = logpost[s] + beta.logpdf(a = aa[0], b = aa[1], x = w)\n",
        "  # Mu term\n",
        "  for k in range(KK):\n",
        "    logpost[s] = logpost[s] + norm.logpdf(loc = eta, scale = tau, x = mu[k])\n",
        "  # Sigma term\n",
        "  logpost[s] = logpost[s] + invgamma.logpdf(a = dd, scale = 1 / qq, x = sigma**2)\n",
        "  if s / 500 == np.floor(s / 500):\n",
        "    print('Current iteration is: {}'.format(s))\n",
        "\n",
        "## Plot the logposterior distribution for various samples\n",
        "fig, ax = plt.subplots(1, 1)\n",
        "ax.plot(np.arange(len(logpost)), logpost, 'r-', lw=1, alpha=0.6, label='Trace plot') # Trace plot of data\n",
        "ax.legend(loc='best', frameon=False)\n",
        "# plot density estimate of the posterior\n",
        "plt.title('Trace plot of Logposterior')\n",
        "plt.show()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Current iteration is: 0\n",
            "Current iteration is: 500\n",
            "Current iteration is: 1000\n",
            "Current iteration is: 1500\n",
            "Current iteration is: 2000\n",
            "Current iteration is: 2500\n",
            "Current iteration is: 3000\n",
            "Current iteration is: 3500\n",
            "Current iteration is: 4000\n",
            "Current iteration is: 4500\n",
            "Current iteration is: 5000\n",
            "Current iteration is: 5500\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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38.653977 \nL 88.443758 38.938128 \nL 88.595965 35.544688 \nL 88.798908 40.817645 \nL 88.849644 35.933461 \nL 88.900379 39.372246 \nL 89.103322 62.329817 \nL 89.204794 39.915254 \nL 89.255529 40.205143 \nL 89.306265 41.987081 \nL 89.357001 34.86924 \nL 89.407737 36.782114 \nL 89.458472 51.55402 \nL 89.509208 43.122671 \nL 89.712151 37.077814 \nL 89.762887 38.808717 \nL 89.864358 34.549537 \nL 90.016565 58.136949 \nL 90.219508 38.315953 \nL 90.270244 45.072445 \nL 90.32098 34.920062 \nL 90.371716 40.382439 \nL 90.473187 61.612598 \nL 90.523923 36.123409 \nL 90.625394 37.38533 \nL 90.67613 64.564754 \nL 90.726866 35.418296 \nL 90.828337 36.061856 \nL 90.879073 45.215256 \nL 90.929809 41.6277 \nL 90.980544 38.681565 \nL 91.03128 41.115558 \nL 91.082016 46.487758 \nL 91.132751 35.573184 \nL 91.183487 47.614039 \nL 91.234223 36.254596 \nL 91.335694 35.797164 \nL 91.38643 35.113068 \nL 91.538637 48.303288 \nL 91.589373 46.512729 \nL 91.640109 42.489686 \nL 91.690844 43.307032 \nL 91.74158 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54.594255 \nL 97.728396 39.507209 \nL 97.779132 39.714653 \nL 97.829868 57.974257 \nL 97.880603 40.6158 \nL 98.032811 59.443604 \nL 98.083546 37.079557 \nL 98.185018 38.187302 \nL 98.286489 57.871627 \nL 98.337225 53.635182 \nL 98.387961 36.181525 \nL 98.438696 41.005068 \nL 98.489432 43.716587 \nL 98.540168 37.876315 \nL 98.590904 43.163843 \nL 98.641639 43.046984 \nL 98.692375 38.178498 \nL 98.743111 48.924927 \nL 98.844582 48.688038 \nL 98.895318 37.162778 \nL 98.946054 42.669657 \nL 98.996789 40.225472 \nL 99.047525 42.044382 \nL 99.148997 45.077632 \nL 99.199732 54.750815 \nL 99.250468 43.418545 \nL 99.35194 37.263589 \nL 99.453411 48.514923 \nL 99.504147 36.423477 \nL 99.554882 45.130934 \nL 99.605618 49.777561 \nL 99.656354 37.916129 \nL 99.70709 49.938696 \nL 99.757825 40.228252 \nL 99.808561 49.062209 \nL 99.859297 68.040246 \nL 99.910033 49.294292 \nL 99.960768 61.679678 \nL 100.011504 39.435671 \nL 100.06224 39.901565 \nL 100.112975 45.332294 \nL 100.163711 38.642622 \nL 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44.53321 \nL 103.004912 34.547093 \nL 103.055648 42.205132 \nL 103.106383 42.002367 \nL 103.157119 48.974914 \nL 103.309326 37.722975 \nL 103.360062 38.447412 \nL 103.410798 49.912764 \nL 103.461534 39.081335 \nL 103.563005 37.654546 \nL 103.613741 49.223748 \nL 103.664476 51.173287 \nL 103.765948 37.968068 \nL 103.816684 45.170505 \nL 103.867419 41.44039 \nL 103.918155 37.40405 \nL 103.968891 41.415089 \nL 104.019627 41.279311 \nL 104.070362 37.650049 \nL 104.222569 62.995603 \nL 104.324041 44.453318 \nL 104.374777 47.380691 \nL 104.476248 36.185072 \nL 104.526984 37.54418 \nL 104.628455 44.475308 \nL 104.679191 37.589555 \nL 104.729927 44.868043 \nL 104.882134 37.268564 \nL 104.93287 41.427229 \nL 104.983605 36.375603 \nL 105.034341 44.792314 \nL 105.135813 43.38766 \nL 105.237284 38.710924 \nL 105.338755 38.0325 \nL 105.389491 45.430318 \nL 105.440227 36.879432 \nL 105.490963 53.565284 \nL 105.541698 43.187036 \nL 105.592434 44.827445 \nL 105.744641 37.095676 \nL 105.99832 58.998501 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108.890256 36.05183 \nL 108.940992 40.519248 \nL 108.991728 34.725652 \nL 109.042464 43.163171 \nL 109.143935 42.884736 \nL 109.194671 36.76257 \nL 109.245407 54.218875 \nL 109.296142 48.295201 \nL 109.44835 39.344333 \nL 109.499085 44.055284 \nL 109.549821 36.767332 \nL 109.600557 46.661467 \nL 109.651292 38.99912 \nL 109.752764 49.576655 \nL 109.854235 34.680627 \nL 110.057178 52.787639 \nL 110.107914 37.000303 \nL 110.15865 44.445091 \nL 110.260121 38.076981 \nL 110.463064 91.351296 \nL 110.615271 45.703272 \nL 110.716743 40.539217 \nL 110.767478 41.593995 \nL 110.818214 56.61375 \nL 110.86895 39.200703 \nL 110.919686 49.144602 \nL 110.970421 35.216248 \nL 111.071893 35.897607 \nL 111.122629 44.235507 \nL 111.173364 37.318457 \nL 111.274836 36.664335 \nL 111.325571 52.250554 \nL 111.376307 44.264971 \nL 111.427043 55.071658 \nL 111.477779 37.488727 \nL 111.57925 37.961778 \nL 111.629986 53.738076 \nL 111.680722 47.235209 \nL 111.883664 35.010369 \nL 111.9344 58.919233 \nL 111.985136 38.980869 \nL 112.035872 38.706116 \nL 112.086607 36.274848 \nL 112.188079 52.402427 \nL 112.238815 50.740034 \nL 112.28955 42.208421 \nL 112.340286 43.607353 \nL 112.391022 65.757147 \nL 112.441758 35.320312 \nL 112.492493 49.878496 \nL 112.543229 56.236637 \nL 112.593965 40.536691 \nL 112.695436 42.460555 \nL 112.796908 42.932339 \nL 112.949115 37.031078 \nL 112.999851 39.026102 \nL 113.050586 36.632048 \nL 113.101322 50.814058 \nL 113.152058 45.616721 \nL 113.304265 35.114199 \nL 113.456472 44.907412 \nL 113.557944 37.68548 \nL 113.608679 48.265149 \nL 113.659415 43.247782 \nL 113.710151 41.187324 \nL 113.760886 42.169932 \nL 113.862358 47.483643 \nL 113.913094 37.129354 \nL 113.963829 43.985615 \nL 114.065301 44.180705 \nL 114.116037 41.429866 \nL 114.166772 41.557532 \nL 114.217508 56.654367 \nL 114.268244 40.22137 \nL 114.369715 36.331565 \nL 114.521922 48.244446 \nL 114.572658 36.409951 \nL 114.623394 43.973549 \nL 114.826337 48.017726 \nL 114.877072 38.059834 \nL 114.927808 61.537877 \nL 114.978544 49.282149 \nL 115.02928 54.364682 \nL 115.080015 44.565828 \nL 115.130751 62.720426 \nL 115.181487 37.607729 \nL 115.282958 39.363255 \nL 115.38443 50.338242 \nL 115.435165 37.973275 \nL 115.485901 43.719514 \nL 115.536637 42.444888 \nL 115.587373 35.027334 \nL 115.638108 43.520014 \nL 115.688844 39.319537 \nL 115.73958 41.008381 \nL 115.790316 42.334546 \nL 115.841051 36.508326 \nL 115.891787 48.671389 \nL 115.993259 46.440674 \nL 116.246937 37.604263 \nL 116.399144 40.482684 \nL 116.44988 48.283176 \nL 116.500616 48.280168 \nL 116.602087 38.634287 \nL 116.652823 39.234209 \nL 116.703559 56.041027 \nL 116.754294 42.369306 \nL 116.855766 50.654493 \nL 117.007973 36.530679 \nL 117.109445 39.867501 \nL 117.16018 47.869957 \nL 117.210916 47.591619 \nL 117.261652 36.19575 \nL 117.312387 39.830966 \nL 117.363123 46.053084 \nL 117.413859 45.678634 \nL 117.464595 43.918225 \nL 117.51533 34.791777 \nL 117.616802 55.019911 \nL 117.718273 39.025119 \nL 117.769009 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123.349939 38.550655 \nL 123.400675 46.017455 \nL 123.451411 35.29956 \nL 123.502146 38.514409 \nL 123.705089 45.413942 \nL 123.806561 43.775573 \nL 123.857296 37.407264 \nL 123.908032 42.208866 \nL 123.958768 41.259856 \nL 124.009504 42.767504 \nL 124.060239 38.37354 \nL 124.110975 50.851532 \nL 124.161711 38.401238 \nL 124.212447 39.794542 \nL 124.263182 38.55192 \nL 124.313918 51.993692 \nL 124.364654 38.51943 \nL 124.415389 37.765867 \nL 124.466125 52.981358 \nL 124.516861 34.554447 \nL 124.567597 36.02386 \nL 124.618332 44.153843 \nL 124.669068 42.034399 \nL 124.719804 38.501649 \nL 124.77054 43.320227 \nL 124.821275 36.618624 \nL 124.872011 37.896699 \nL 124.973482 43.894362 \nL 125.024218 41.430996 \nL 125.074954 36.195399 \nL 125.176425 53.239049 \nL 125.328633 35.345216 \nL 125.430104 51.479822 \nL 125.48084 46.328662 \nL 125.633047 34.713302 \nL 125.683783 37.336833 \nL 125.734518 53.070309 \nL 125.785254 38.120564 \nL 125.886726 51.277441 \nL 125.937461 43.020857 \nL 126.089669 34.881795 \nL 126.140404 46.927127 \nL 126.19114 36.715481 \nL 126.241876 34.516656 \nL 126.394083 45.88458 \nL 126.54629 36.315628 \nL 126.597026 38.488647 \nL 126.647762 37.839508 \nL 126.698497 36.430019 \nL 126.749233 45.56396 \nL 126.799969 38.285686 \nL 126.850704 36.239486 \nL 126.90144 45.484397 \nL 126.952176 36.692924 \nL 127.002912 36.26725 \nL 127.053647 41.159919 \nL 127.104383 36.035463 \nL 127.408797 58.525886 \nL 127.510269 43.21593 \nL 127.561005 54.789547 \nL 127.662476 37.538872 \nL 127.713212 58.553173 \nL 127.763948 42.456783 \nL 127.865419 39.121385 \nL 127.96689 43.753842 \nL 128.068362 42.354158 \nL 128.119098 34.959755 \nL 128.169833 37.094524 \nL 128.220569 37.398584 \nL 128.271305 42.135724 \nL 128.322041 39.492071 \nL 128.372776 36.002595 \nL 128.423512 41.872367 \nL 128.474248 38.387476 \nL 128.524983 37.857547 \nL 128.575719 47.991694 \nL 128.626455 43.995523 \nL 128.778662 35.646531 \nL 128.829398 39.69249 \nL 128.880134 38.121763 \nL 128.930869 35.934622 \nL 129.032341 48.236656 \nL 129.083077 44.863173 \nL 129.133812 57.276435 \nL 129.235284 37.837601 \nL 129.286019 42.72318 \nL 129.387491 55.168588 \nL 129.438227 38.34257 \nL 129.539698 39.671516 \nL 129.590434 36.706941 \nL 129.64117 48.153262 \nL 129.691905 44.485001 \nL 129.742641 37.774951 \nL 129.793377 42.089862 \nL 129.844112 49.277191 \nL 129.894848 37.278882 \nL 129.945584 38.908804 \nL 129.99632 54.348507 \nL 130.047055 45.689052 \nL 130.097791 34.449881 \nL 130.148527 60.338906 \nL 130.199263 34.762436 \nL 130.249998 35.537666 \nL 130.35147 45.54997 \nL 130.402205 42.890565 \nL 130.452941 39.632836 \nL 130.605148 54.806121 \nL 130.655884 37.444987 \nL 130.70662 59.287111 \nL 130.757356 36.987406 \nL 130.808091 35.205938 \nL 130.858827 45.206231 \nL 130.909563 42.812335 \nL 130.960298 37.478904 \nL 131.06177 54.122757 \nL 131.163241 35.211726 \nL 131.213977 43.582366 \nL 131.264713 42.408021 \nL 131.315449 45.425841 \nL 131.41692 46.516582 \nL 131.467656 38.935385 \nL 131.569127 42.35115 \nL 131.77207 36.803749 \nL 131.873542 39.885433 \nL 131.924277 39.665215 \nL 131.975013 37.148242 \nL 132.076485 37.598311 \nL 132.12722 46.237282 \nL 132.177956 36.662096 \nL 132.228692 39.771919 \nL 132.279427 53.570678 \nL 132.330163 50.797667 \nL 132.431635 36.358838 \nL 132.533106 51.285112 \nL 132.583842 39.675333 \nL 132.634578 43.499024 \nL 132.685313 52.270678 \nL 132.736049 46.901422 \nL 132.888256 39.424288 \nL 132.989728 40.429184 \nL 133.040463 43.902852 \nL 133.091199 38.88902 \nL 133.141935 44.58082 \nL 133.243406 39.473033 \nL 133.294142 46.307423 \nL 133.344878 36.153429 \nL 133.446349 36.854679 \nL 133.497085 52.460271 \nL 133.547821 36.453312 \nL 133.598556 34.333679 \nL 133.750764 45.125294 \nL 133.801499 35.074707 \nL 133.852235 36.919054 \nL 133.902971 53.224122 \nL 133.953706 42.788815 \nL 134.004442 39.290226 \nL 134.156649 49.494305 \nL 134.258121 38.391244 \nL 134.359592 60.022111 \nL 134.410328 53.740353 \nL 134.613271 36.960712 \nL 134.816214 45.967443 \nL 134.86695 35.936204 \nL 134.917685 42.230993 \nL 134.968421 42.311747 \nL 135.019157 34.824567 \nL 135.069892 44.654283 \nL 135.120628 38.935646 \nL 135.171364 36.914619 \nL 135.272835 50.401635 \nL 135.323571 38.328339 \nL 135.374307 52.811635 \nL 135.475778 51.011999 \nL 135.526514 35.71116 \nL 135.627986 36.94802 \nL 135.678721 41.230314 \nL 135.729457 37.818543 \nL 135.780193 38.558266 \nL 135.9324 57.117603 \nL 136.033871 36.732083 \nL 136.084607 42.625265 \nL 136.135343 42.625146 \nL 136.236814 36.556358 \nL 136.389021 52.264121 \nL 136.591964 35.494005 \nL 136.6427 37.191918 \nL 136.744172 52.00883 \nL 136.896379 36.564287 \nL 136.99785 37.560878 \nL 137.099322 63.565319 \nL 137.150057 38.392897 \nL 137.200793 62.965083 \nL 137.403736 36.3985 \nL 137.454472 41.388359 \nL 137.555943 41.162274 \nL 137.606679 42.022076 \nL 137.657415 37.616529 \nL 137.70815 40.71178 \nL 137.809622 52.271353 \nL 137.911093 38.62813 \nL 138.0633 47.576969 \nL 138.114036 40.287501 \nL 138.164772 53.702942 \nL 138.215508 52.279896 \nL 138.367715 35.216683 \nL 138.469186 61.918794 \nL 138.621394 36.705835 \nL 138.672129 36.146615 \nL 138.722865 36.891092 \nL 138.824336 48.088127 \nL 138.875072 38.007052 \nL 138.925808 50.523548 \nL 138.976544 38.738882 \nL 139.027279 41.994007 \nL 139.078015 38.707604 \nL 139.128751 37.83075 \nL 139.179487 49.053073 \nL 139.230222 37.164321 \nL 139.433165 54.215757 \nL 139.534637 38.285655 \nL 139.585372 58.957436 \nL 139.636108 51.954767 \nL 139.73758 41.683109 \nL 139.788315 48.665261 \nL 139.839051 39.030226 \nL 139.889787 45.257822 \nL 139.940522 42.283384 \nL 139.991258 60.04618 \nL 140.041994 41.562093 \nL 140.09273 46.102327 \nL 140.143465 36.955285 \nL 140.194201 38.436518 \nL 140.244937 40.567102 \nL 140.295673 53.552137 \nL 140.346408 41.488868 \nL 140.44788 35.656221 \nL 140.498615 38.130427 \nL 140.549351 36.538176 \nL 140.600087 36.76923 \nL 140.701558 43.923377 \nL 140.80303 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37.088848 \nL 143.796438 34.849241 \nL 143.847174 41.963359 \nL 143.897909 37.881524 \nL 143.948645 39.785135 \nL 143.999381 36.119298 \nL 144.100852 44.615348 \nL 144.151588 35.535988 \nL 144.253059 37.068698 \nL 144.354531 46.225661 \nL 144.405267 37.999751 \nL 144.456002 48.175978 \nL 144.506738 42.521535 \nL 144.557474 46.016383 \nL 144.709681 36.534627 \nL 144.760417 51.39034 \nL 144.811152 42.044379 \nL 144.912624 35.30165 \nL 145.064831 46.127272 \nL 145.115567 42.891422 \nL 145.166303 54.133187 \nL 145.217038 51.818963 \nL 145.369245 40.271548 \nL 145.572188 53.501385 \nL 145.67366 34.690453 \nL 145.724396 45.749902 \nL 145.775131 52.098781 \nL 145.825867 45.761474 \nL 145.876603 42.954362 \nL 145.927338 67.466999 \nL 145.978074 43.368128 \nL 146.02881 41.114663 \nL 146.079546 50.338284 \nL 146.181017 51.424188 \nL 146.231753 36.6725 \nL 146.282489 36.673292 \nL 146.333224 39.755115 \nL 146.38396 36.896101 \nL 146.434696 35.786789 \nL 146.485431 37.153963 \nL 146.688374 52.613729 \nL 146.73911 37.432817 \nL 146.789846 41.480847 \nL 146.840582 44.20253 \nL 146.891317 64.117778 \nL 146.942053 49.467802 \nL 146.992789 42.687448 \nL 147.043524 45.967226 \nL 147.09426 66.608116 \nL 147.144996 48.193524 \nL 147.195732 48.439482 \nL 147.347939 38.746254 \nL 147.44941 45.226173 \nL 147.500146 44.959463 \nL 147.550882 39.843592 \nL 147.601617 46.86147 \nL 147.652353 38.552941 \nL 147.703089 44.960925 \nL 147.753825 38.939891 \nL 147.80456 37.936076 \nL 147.855296 52.727993 \nL 147.906032 47.281778 \nL 147.956768 39.661377 \nL 148.007503 58.441122 \nL 148.058239 42.96056 \nL 148.108975 35.964384 \nL 148.15971 36.944734 \nL 148.311918 49.060091 \nL 148.413389 37.551737 \nL 148.464125 49.932625 \nL 148.514861 36.561565 \nL 148.565596 45.989025 \nL 148.616332 45.176584 \nL 148.667068 39.326206 \nL 148.717804 52.680363 \nL 148.768539 42.501847 \nL 148.870011 39.54562 \nL 148.920746 35.926792 \nL 148.971482 39.953104 \nL 149.022218 50.597248 \nL 149.072954 44.860611 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152.117097 55.180791 \nL 152.32004 36.99713 \nL 152.370776 38.111945 \nL 152.472247 44.758491 \nL 152.725926 36.388769 \nL 152.776662 46.467016 \nL 152.827398 37.168669 \nL 152.878133 43.978037 \nL 152.928869 42.872388 \nL 152.979605 42.555194 \nL 153.03034 39.408671 \nL 153.081076 40.405422 \nL 153.182548 54.028388 \nL 153.233283 41.293279 \nL 153.334755 43.290918 \nL 153.385491 36.116436 \nL 153.436226 56.270857 \nL 153.537698 54.349862 \nL 153.689905 36.619638 \nL 153.740641 37.713381 \nL 153.842112 49.896808 \nL 153.892848 48.523141 \nL 153.943584 35.787623 \nL 153.994319 37.316328 \nL 154.197262 55.884657 \nL 154.298734 40.908883 \nL 154.349469 43.679062 \nL 154.450941 39.525884 \nL 154.501677 40.988092 \nL 154.552412 51.24773 \nL 154.603148 35.919153 \nL 154.653884 44.723514 \nL 154.704619 47.601212 \nL 154.755355 36.451368 \nL 154.806091 36.455995 \nL 154.958298 46.838657 \nL 155.009034 39.576709 \nL 155.05977 52.332543 \nL 155.110505 51.353767 \nL 155.262713 35.026538 \nL 155.364184 60.534563 \nL 155.41492 37.073033 \nL 155.516391 40.308422 \nL 155.567127 37.645741 \nL 155.617863 48.924424 \nL 155.668598 37.90948 \nL 155.719334 39.235756 \nL 155.922277 58.748397 \nL 156.074484 35.627444 \nL 156.175956 48.756895 \nL 156.277427 35.35794 \nL 156.328163 38.614683 \nL 156.378899 39.219946 \nL 156.429634 46.410629 \nL 156.48037 41.328159 \nL 156.531106 41.851872 \nL 156.581841 39.065616 \nL 156.632577 39.260646 \nL 156.683313 50.097391 \nL 156.734049 48.091028 \nL 156.886256 34.568703 \nL 156.936992 59.312548 \nL 157.038463 54.643484 \nL 157.139934 36.042809 \nL 157.19067 44.498509 \nL 157.241406 44.794303 \nL 157.292142 41.009496 \nL 157.342877 51.675244 \nL 157.444349 36.532256 \nL 157.495085 51.696302 \nL 157.54582 46.258026 \nL 157.596556 39.533229 \nL 157.647292 52.302044 \nL 157.698027 47.138278 \nL 157.748763 36.217245 \nL 157.850235 58.981037 \nL 157.951706 35.799194 \nL 158.002442 47.464841 \nL 158.053178 42.50248 \nL 158.103913 40.799638 \nL 158.205385 68.145496 \nL 158.306856 36.380722 \nL 158.357592 38.190332 \nL 158.459063 37.997379 \nL 158.509799 35.900457 \nL 158.560535 48.792099 \nL 158.611271 45.067491 \nL 158.662006 35.946112 \nL 158.712742 43.52824 \nL 158.763478 51.954823 \nL 158.864949 34.585448 \nL 158.915685 38.53552 \nL 158.966421 42.91149 \nL 159.118628 37.152454 \nL 159.169364 39.718517 \nL 159.220099 35.57461 \nL 159.270835 59.672717 \nL 159.321571 53.212481 \nL 159.372307 35.566286 \nL 159.473778 38.804931 \nL 159.524514 36.106176 \nL 159.575249 36.591478 \nL 159.625985 55.482878 \nL 159.676721 52.302254 \nL 159.727457 41.577515 \nL 159.778192 50.361429 \nL 159.879664 47.613368 \nL 159.981135 38.558826 \nL 160.031871 39.186247 \nL 160.082607 61.96295 \nL 160.133342 43.955431 \nL 160.184078 55.649178 \nL 160.234814 44.581359 \nL 160.28555 40.117797 \nL 160.336285 43.519452 \nL 160.437757 61.353532 \nL 160.488493 55.822562 \nL 160.589964 38.025802 \nL 160.6407 53.390888 \nL 160.691435 42.759052 \nL 160.742171 36.804571 \nL 160.792907 38.400937 \nL 160.843643 43.62464 \nL 160.894378 60.346845 \nL 161.046586 35.259293 \nL 161.148057 43.826046 \nL 161.249528 38.28676 \nL 161.300264 42.981447 \nL 161.351 36.596583 \nL 161.401736 44.124402 \nL 161.503207 56.915771 \nL 161.553943 35.851653 \nL 161.604679 37.631075 \nL 161.655414 43.027664 \nL 161.70615 35.070573 \nL 161.756886 35.798689 \nL 161.909093 53.738428 \nL 162.0613 35.04274 \nL 162.112036 42.625348 \nL 162.162772 39.793737 \nL 162.213507 39.753228 \nL 162.264243 37.853488 \nL 162.314979 42.009219 \nL 162.41645 36.124219 \nL 162.467186 37.392675 \nL 162.517922 37.003299 \nL 162.568657 64.247589 \nL 162.619393 38.520272 \nL 162.670129 39.510141 \nL 162.7716 51.189967 \nL 162.822336 36.090573 \nL 162.873072 38.321405 \nL 162.923808 42.252982 \nL 162.974543 57.546386 \nL 163.025279 38.341105 \nL 163.076015 46.537833 \nL 163.12675 51.968558 \nL 163.177486 47.11272 \nL 163.278958 34.937392 \nL 163.380429 39.980313 \nL 163.431165 51.290638 \nL 163.481901 43.108994 \nL 163.583372 38.38489 \nL 163.634108 41.837529 \nL 163.684843 41.14938 \nL 163.735579 65.98336 \nL 163.786315 43.624228 \nL 163.887786 52.529182 \nL 163.989258 35.379152 \nL 164.090729 38.455291 \nL 164.141465 35.984567 \nL 164.242936 36.169302 \nL 164.293672 62.74537 \nL 164.344408 38.832176 \nL 164.395144 36.699038 \nL 164.445879 39.488786 \nL 164.496615 78.463329 \nL 164.547351 52.625444 \nL 164.648822 35.317861 \nL 164.699558 39.554997 \nL 164.750294 56.521896 \nL 164.80103 41.099654 \nL 164.851765 40.310034 \nL 165.054708 49.566426 \nL 165.105444 50.266854 \nL 165.15618 47.269757 \nL 165.206915 55.777694 \nL 165.257651 44.992115 \nL 165.308387 64.251458 \nL 165.359123 42.060024 \nL 165.409858 45.761223 \nL 165.460594 38.075491 \nL 165.562065 47.768378 \nL 165.663537 36.858991 \nL 165.714273 54.630603 \nL 165.765008 53.127881 \nL 165.86648 38.372544 \nL 165.967951 56.462745 \nL 166.018687 47.031282 \nL 166.069423 55.549639 \nL 166.120158 38.980073 \nL 166.170894 42.578375 \nL 166.22163 47.786139 \nL 166.272366 41.469277 \nL 166.373837 41.966103 \nL 166.424573 43.416262 \nL 166.526044 34.841405 \nL 166.57678 37.4617 \nL 166.627516 36.490555 \nL 166.678251 45.236794 \nL 166.728987 42.297206 \nL 166.830459 35.668645 \nL 166.881194 39.513889 \nL 166.93193 52.616896 \nL 166.982666 37.59186 \nL 167.033402 43.426396 \nL 167.084137 35.914598 \nL 167.134873 38.944911 \nL 167.236344 55.89794 \nL 167.337816 53.372042 \nL 167.388552 54.615275 \nL 167.439287 34.843217 \nL 167.490023 37.424141 \nL 167.591495 52.709243 \nL 167.743702 38.868539 \nL 167.794437 57.103243 \nL 167.845173 48.968524 \nL 167.895909 47.829534 \nL 167.946645 41.740827 \nL 167.99738 55.267863 \nL 168.048116 36.160541 \nL 168.149588 36.992794 \nL 168.200323 56.578846 \nL 168.251059 38.601328 \nL 168.352531 36.740537 \nL 168.454002 57.359844 \nL 168.555473 38.621189 \nL 168.606209 42.066557 \nL 168.656945 63.893511 \nL 168.707681 41.423538 \nL 168.809152 35.437735 \nL 168.859888 37.722703 \nL 168.961359 36.791697 \nL 169.012095 48.293718 \nL 169.062831 43.023459 \nL 169.113566 42.66999 \nL 169.265774 35.497058 \nL 169.417981 55.514953 \nL 169.519452 43.732172 \nL 169.570188 47.713772 \nL 169.620924 53.729787 \nL 169.773131 39.48274 \nL 169.874602 46.740664 \nL 169.925338 43.202293 \nL 170.02681 37.691444 \nL 170.128281 52.792272 \nL 170.179017 41.471113 \nL 170.229752 41.221248 \nL 170.331224 35.727857 \nL 170.38196 39.705104 \nL 170.432695 36.784574 \nL 170.483431 38.467491 \nL 170.534167 35.715669 \nL 170.584903 39.90853 \nL 170.635638 67.2844 \nL 170.686374 40.393902 \nL 170.73711 44.997962 \nL 170.787845 39.240056 \nL 170.838581 41.250555 \nL 170.889317 57.00438 \nL 170.940053 38.641921 \nL 170.990788 41.583735 \nL 171.041524 35.905057 \nL 171.09226 38.10548 \nL 171.345939 47.76187 \nL 171.498146 36.798982 \nL 171.548881 35.52206 \nL 171.751824 59.073833 \nL 171.80256 63.104444 \nL 171.853296 41.466854 \nL 171.904032 45.276882 \nL 171.954767 52.931128 \nL 172.005503 44.579548 \nL 172.056239 41.795153 \nL 172.106974 45.339673 \nL 172.15771 40.459194 \nL 172.208446 44.262893 \nL 172.259182 43.296995 \nL 172.360653 35.37826 \nL 172.563596 43.739515 \nL 172.715803 36.470359 \nL 172.817275 34.821804 \nL 173.020218 54.373049 \nL 173.070953 34.62288 \nL 173.121689 41.332705 \nL 173.22316 46.231373 \nL 173.273896 66.530561 \nL 173.375368 66.166119 \nL 173.527575 36.446192 \nL 173.679782 42.886001 \nL 173.730518 42.256105 \nL 173.781253 42.278403 \nL 173.831989 36.650868 \nL 173.882725 48.575649 \nL 173.933461 45.668636 \nL 173.984196 35.772729 \nL 174.034932 53.648206 \nL 174.085668 47.868265 \nL 174.187139 39.623839 \nL 174.339346 53.090983 \nL 174.440818 35.469691 \nL 174.542289 51.226823 \nL 174.643761 35.722993 \nL 174.694497 40.988183 \nL 174.745232 37.616987 \nL 174.795968 45.031968 \nL 174.846704 36.381155 \nL 174.948175 35.405254 \nL 175.100382 50.695798 \nL 175.151118 50.47098 \nL 175.354061 34.233025 \nL 175.506268 41.976777 \nL 175.658475 34.448222 \nL 175.709211 47.547464 \nL 175.759947 40.565709 \nL 175.861418 35.141417 \nL 175.912154 35.855422 \nL 175.96289 49.826972 \nL 176.013626 37.91409 \nL 176.064361 35.359721 \nL 176.115097 35.742057 \nL 176.267304 65.551771 \nL 176.419511 36.216338 \nL 176.470247 52.964802 \nL 176.520983 36.386118 \nL 176.571719 36.573502 \nL 176.622454 42.488392 \nL 176.723926 41.58786 \nL 176.774661 38.851923 \nL 176.825397 47.646372 \nL 176.876133 37.133288 \nL 176.926869 45.439019 \nL 177.02834 39.430871 \nL 177.079076 41.501371 \nL 177.129812 40.858256 \nL 177.180547 38.106106 \nL 177.231283 48.963212 \nL 177.282019 35.536891 \nL 177.332754 38.567815 \nL 177.38349 42.791461 \nL 177.434226 56.32604 \nL 177.586433 38.289592 \nL 177.637169 47.767889 \nL 177.687905 45.206614 \nL 177.73864 38.112633 \nL 177.789376 64.713629 \nL 177.840112 37.269557 \nL 177.890848 44.955322 \nL 177.941583 40.858848 \nL 178.043055 36.070317 \nL 178.09379 37.299127 \nL 178.195262 50.271472 \nL 178.245998 43.92908 \nL 178.296733 42.952019 \nL 178.347469 59.932929 \nL 178.499676 37.814253 \nL 178.550412 39.639705 \nL 178.601148 36.483432 \nL 178.651883 47.171875 \nL 178.702619 37.806774 \nL 178.753355 36.877966 \nL 178.804091 37.798538 \nL 178.905562 64.823762 \nL 178.956298 36.91207 \nL 179.007034 46.42854 \nL 179.108505 36.634391 \nL 179.159241 36.931635 \nL 179.260712 50.416874 \nL 179.311448 44.734514 \nL 179.362184 45.840364 \nL 179.412919 50.715225 \nL 179.463655 47.024639 \nL 179.514391 42.062641 \nL 179.565127 56.509412 \nL 179.615862 52.970603 \nL 179.666598 51.543306 \nL 179.818805 37.485009 \nL 179.869541 51.847001 \nL 179.920277 41.201505 \nL 179.971012 48.133058 \nL 180.021748 37.405536 \nL 180.072484 43.073438 \nL 180.173955 58.586236 \nL 180.224691 43.482851 \nL 180.326162 44.29583 \nL 180.376898 51.024784 \nL 180.427634 37.87025 \nL 180.47837 39.687724 \nL 180.529105 49.805948 \nL 180.630577 48.130593 \nL 180.782784 37.964001 \nL 180.884255 35.164144 \nL 180.934991 37.473183 \nL 180.985727 53.985818 \nL 181.036463 44.09187 \nL 181.18867 34.982308 \nL 181.290141 50.16397 \nL 181.442349 47.871689 \nL 181.493084 42.460462 \nL 181.594556 42.536299 \nL 181.746763 51.00285 \nL 181.848234 41.737031 \nL 181.89897 54.450939 \nL 181.949706 52.582188 \nL 182.101913 40.830259 \nL 182.203384 39.277996 \nL 182.25412 50.294487 \nL 182.355592 48.516698 \nL 182.507799 35.399158 \nL 182.60927 42.803035 \nL 182.660006 36.276666 \nL 182.862949 62.023142 \nL 183.116628 37.185443 \nL 183.167363 46.097475 \nL 183.268835 45.93734 \nL 183.31957 49.814498 \nL 183.370306 39.023243 \nL 183.471778 39.489456 \nL 183.522513 37.939463 \nL 183.573249 46.862246 \nL 183.623985 34.732456 \nL 183.674721 37.640087 \nL 183.826928 45.666682 \nL 183.877663 39.633792 \nL 183.928399 44.76755 \nL 184.080606 39.037571 \nL 184.232814 52.973064 \nL 184.435757 39.655451 \nL 184.537228 49.792884 \nL 184.638699 34.510601 \nL 184.689435 38.880417 \nL 184.740171 51.363126 \nL 184.790907 41.811934 \nL 184.841642 46.248819 \nL 184.892378 63.300388 \nL 184.943114 48.949308 \nL 185.044585 37.357109 \nL 185.095321 40.165443 \nL 185.146057 36.0948 \nL 185.196792 36.998359 \nL 185.298264 46.961475 \nL 185.399735 36.372471 \nL 185.450471 41.311062 \nL 185.501207 37.08873 \nL 185.551943 36.546265 \nL 185.754885 49.474053 \nL 185.907093 35.536684 \nL 185.957828 38.321354 \nL 186.008564 49.867981 \nL 186.0593 36.43028 \nL 186.110036 35.91061 \nL 186.160771 41.029339 \nL 186.211507 36.108544 \nL 186.262243 38.715993 \nL 186.312978 35.727011 \nL 186.41445 58.100875 \nL 186.465186 37.398802 \nL 186.515921 42.370817 \nL 186.566657 54.992586 \nL 186.617393 43.825471 \nL 186.668129 45.060472 \nL 186.718864 38.238054 \nL 186.7696 56.332963 \nL 186.820336 43.514708 \nL 186.871071 42.207986 \nL 186.921807 35.747011 \nL 186.972543 49.38881 \nL 187.023279 42.099919 \nL 187.074014 43.980147 \nL 187.12475 39.354521 \nL 187.226222 48.547354 \nL 187.276957 48.330888 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38.644124 \nL 192.959359 46.750757 \nL 193.010095 42.121976 \nL 193.06083 36.503435 \nL 193.111566 41.257744 \nL 193.263773 43.965561 \nL 193.41598 36.304462 \nL 193.466716 39.086819 \nL 193.517452 50.272647 \nL 193.568188 48.270156 \nL 193.669659 38.94462 \nL 193.720395 52.044176 \nL 193.771131 38.92756 \nL 194.024809 54.266382 \nL 194.177016 36.436513 \nL 194.227752 56.339551 \nL 194.278488 48.475313 \nL 194.379959 35.012545 \nL 194.582902 58.980804 \nL 194.684374 44.486916 \nL 194.785845 59.300465 \nL 194.887317 38.019222 \nL 194.938052 40.159319 \nL 195.039524 39.624189 \nL 195.09026 49.161397 \nL 195.140995 47.724849 \nL 195.191731 54.864206 \nL 195.242467 47.00458 \nL 195.293202 48.040408 \nL 195.343938 36.545396 \nL 195.394674 39.649037 \nL 195.496145 45.75178 \nL 195.546881 36.11794 \nL 195.648353 50.232039 \nL 195.80056 36.269516 \nL 195.952767 46.057378 \nL 196.003503 40.703744 \nL 196.054238 49.452499 \nL 196.104974 39.383823 \nL 196.15571 38.109967 \nL 196.206446 49.200013 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207.723456 42.088257 \nL 207.774192 36.646489 \nL 207.875663 46.858007 \nL 207.926399 44.206599 \nL 208.02787 39.818875 \nL 208.078606 40.625193 \nL 208.129342 43.924807 \nL 208.180078 37.424191 \nL 208.230813 41.011791 \nL 208.281549 48.005327 \nL 208.433756 37.793083 \nL 208.585963 52.704326 \nL 208.687435 35.005898 \nL 208.788906 45.330301 \nL 208.839642 42.282842 \nL 208.890378 35.926692 \nL 208.941113 40.151758 \nL 208.991849 39.519526 \nL 209.042585 46.425404 \nL 209.093321 37.141048 \nL 209.144056 60.277327 \nL 209.194792 40.157986 \nL 209.245528 45.791514 \nL 209.296264 45.755358 \nL 209.346999 41.90175 \nL 209.397735 49.604735 \nL 209.549942 35.278907 \nL 209.651414 66.239007 \nL 209.702149 61.632643 \nL 209.854357 41.265656 \nL 209.905092 49.13033 \nL 209.955828 37.647927 \nL 210.006564 51.926587 \nL 210.057299 37.428459 \nL 210.158771 34.513432 \nL 210.260242 46.553202 \nL 210.310978 36.907013 \nL 210.361714 39.310094 \nL 210.41245 54.876784 \nL 210.463185 39.117099 \nL 210.513921 35.802146 \nL 210.564657 38.836169 \nL 210.615393 40.793562 \nL 210.716864 55.458996 \nL 210.7676 51.631172 \nL 210.818335 52.755553 \nL 210.869071 37.378185 \nL 210.970543 38.373803 \nL 211.021278 35.805979 \nL 211.072014 39.811951 \nL 211.12275 34.780965 \nL 211.173486 34.912972 \nL 211.224221 53.156632 \nL 211.325693 50.628306 \nL 211.427164 37.090305 \nL 211.4779 52.385043 \nL 211.528636 43.01925 \nL 211.579371 37.472263 \nL 211.630107 41.277547 \nL 211.680843 40.42725 \nL 211.731579 53.532302 \nL 211.83305 36.587572 \nL 212.035993 47.878567 \nL 212.1882 39.745913 \nL 212.238936 40.801324 \nL 212.289672 38.920876 \nL 212.340407 40.978538 \nL 212.441879 48.392365 \nL 212.492614 36.720454 \nL 212.54335 39.275221 \nL 212.594086 43.411837 \nL 212.644822 35.564609 \nL 212.695557 40.100465 \nL 212.797029 56.436599 \nL 212.847765 36.406767 \nL 212.949236 37.32042 \nL 213.050707 45.878784 \nL 213.101443 36.210494 \nL 213.152179 45.875138 \nL 213.202915 48.411866 \nL 213.355122 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233.09132 38.187301 \nL 233.142056 43.459254 \nL 233.192792 37.294854 \nL 233.344999 44.692932 \nL 233.395735 58.859653 \nL 233.44647 34.403301 \nL 233.497206 35.800932 \nL 233.547942 53.625204 \nL 233.598678 41.829243 \nL 233.649413 43.552163 \nL 233.700149 40.907116 \nL 233.750885 45.561697 \nL 233.801621 38.93449 \nL 233.852356 39.200541 \nL 233.953828 42.367039 \nL 234.004563 38.334375 \nL 234.055299 42.468093 \nL 234.106035 49.035391 \nL 234.207506 37.923999 \nL 234.258242 52.301144 \nL 234.308978 40.319583 \nL 234.359714 40.970084 \nL 234.410449 36.416466 \nL 234.511921 47.490194 \nL 234.562656 43.02998 \nL 234.613392 40.132739 \nL 234.664128 48.767361 \nL 234.714864 38.365414 \nL 234.765599 39.315732 \nL 234.816335 50.740249 \nL 234.867071 38.215482 \nL 234.917807 38.108861 \nL 235.070014 52.211264 \nL 235.222221 37.955165 \nL 235.272957 36.607194 \nL 235.323692 64.049353 \nL 235.374428 41.053349 \nL 235.425164 41.858132 \nL 235.4759 35.694959 \nL 235.628107 48.813948 \nL 235.678842 52.486356 \nL 235.881785 36.172126 \nL 235.932521 44.346367 \nL 235.983257 35.179249 \nL 236.1862 61.540354 \nL 236.287671 38.469823 \nL 236.338407 41.150795 \nL 236.389143 46.170328 \nL 236.439878 39.773819 \nL 236.592086 61.639191 \nL 236.744293 38.403843 \nL 236.795029 40.533429 \nL 236.845764 64.577272 \nL 236.8965 62.534515 \nL 236.947236 41.856158 \nL 236.997971 42.537285 \nL 237.200914 60.651369 \nL 237.25165 36.65095 \nL 237.353122 39.465283 \nL 237.454593 60.684518 \nL 237.6068 37.816574 \nL 237.657536 37.170047 \nL 237.708272 38.204045 \nL 237.759007 37.877671 \nL 237.96195 58.944882 \nL 238.114157 35.894898 \nL 238.164893 44.787971 \nL 238.266365 52.949709 \nL 238.3171 36.899051 \nL 238.418572 36.953265 \nL 238.520043 55.826636 \nL 238.67225 36.941128 \nL 238.722986 45.794064 \nL 238.773722 37.123309 \nL 238.875193 51.069182 \nL 238.976665 51.634335 \nL 239.027401 35.090139 \nL 239.078136 37.545704 \nL 239.128872 36.872246 \nL 239.179608 55.056015 \nL 239.230343 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49.917739 \nL 241.817866 45.877157 \nL 241.868601 45.06512 \nL 241.970073 37.44521 \nL 242.020809 40.236418 \nL 242.071544 58.152121 \nL 242.12228 39.837173 \nL 242.223751 48.192932 \nL 242.274487 39.233351 \nL 242.325223 47.803513 \nL 242.47743 39.620641 \nL 242.629637 56.404121 \nL 242.680373 40.382215 \nL 242.731109 47.426239 \nL 242.781844 60.559437 \nL 242.934052 34.242366 \nL 243.136995 46.326908 \nL 243.18773 39.468604 \nL 243.238466 43.887611 \nL 243.289202 45.745656 \nL 243.339938 44.07593 \nL 243.390673 55.341214 \nL 243.441409 35.96257 \nL 243.492145 41.265031 \nL 243.54288 40.519849 \nL 243.593616 45.132438 \nL 243.644352 35.345719 \nL 243.695088 43.240611 \nL 243.796559 40.394605 \nL 243.847295 45.270165 \nL 243.898031 41.301065 \nL 243.999502 36.390366 \nL 244.050238 57.922541 \nL 244.100973 38.506977 \nL 244.151709 36.354431 \nL 244.303916 45.867103 \nL 244.354652 39.358398 \nL 244.405388 46.84871 \nL 244.456124 49.456877 \nL 244.506859 48.355174 \nL 244.557595 39.068492 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247.195853 51.153292 \nL 247.297324 36.644303 \nL 247.34806 42.926505 \nL 247.398796 57.837057 \nL 247.449532 45.338822 \nL 247.500267 40.108539 \nL 247.551003 41.227852 \nL 247.601739 41.788433 \nL 247.652474 35.818593 \nL 247.70321 36.400852 \nL 247.753946 50.601949 \nL 247.804682 35.761367 \nL 247.855417 40.206992 \nL 247.906153 64.963486 \nL 247.956889 52.304038 \nL 248.007625 51.616358 \nL 248.05836 40.317455 \nL 248.109096 41.434031 \nL 248.210567 57.320861 \nL 248.261303 48.331191 \nL 248.312039 45.529713 \nL 248.362775 36.021541 \nL 248.41351 39.075822 \nL 248.514982 70.879211 \nL 248.616453 37.737635 \nL 248.667189 47.476482 \nL 248.717925 38.610762 \nL 248.76866 39.491792 \nL 248.819396 46.172009 \nL 248.870132 40.344018 \nL 248.971603 49.470384 \nL 249.022339 43.428194 \nL 249.073075 42.356297 \nL 249.174546 54.50816 \nL 249.225282 38.340161 \nL 249.326753 40.413875 \nL 249.377489 36.767494 \nL 249.428225 37.380719 \nL 249.478961 50.608992 \nL 249.529696 46.426995 \nL 249.580432 44.947363 \nL 249.631168 50.309672 \nL 249.681904 68.093929 \nL 249.732639 43.163615 \nL 249.783375 48.508442 \nL 249.834111 53.199339 \nL 249.884847 44.100023 \nL 249.986318 45.310706 \nL 250.037054 42.379028 \nL 250.087789 49.971372 \nL 250.138525 35.072122 \nL 250.189261 51.544369 \nL 250.239997 54.5147 \nL 250.341468 45.070453 \nL 250.392204 50.295133 \nL 250.544411 40.62439 \nL 250.595147 38.710766 \nL 250.645882 40.71799 \nL 250.696618 45.535973 \nL 250.747354 35.346457 \nL 250.79809 61.756004 \nL 250.848825 40.411021 \nL 250.899561 53.863193 \nL 250.950297 37.009145 \nL 251.051768 37.807714 \nL 251.102504 35.584018 \nL 251.15324 46.035562 \nL 251.203975 37.096935 \nL 251.305447 47.258507 \nL 251.406918 47.879754 \nL 251.457654 40.844529 \nL 251.559126 48.079677 \nL 251.609861 37.298868 \nL 251.660597 38.152139 \nL 251.711333 46.84197 \nL 251.762068 35.505584 \nL 251.812804 36.063004 \nL 251.86354 47.465558 \nL 251.914276 34.509076 \nL 251.965011 37.993342 \nL 252.066483 36.514513 \nL 252.117219 52.115134 \nL 252.167954 35.571694 \nL 252.21869 59.411072 \nL 252.269426 56.851738 \nL 252.421633 39.024386 \nL 252.472369 42.437055 \nL 252.57384 35.336547 \nL 252.624576 51.206808 \nL 252.675312 43.228286 \nL 252.726047 38.323087 \nL 252.776783 43.419999 \nL 252.92899 57.573854 \nL 252.979726 52.962688 \nL 253.030462 35.12014 \nL 253.182669 60.060343 \nL 253.28414 36.740964 \nL 253.334876 43.96808 \nL 253.385612 38.284969 \nL 253.436348 34.503771 \nL 253.487083 55.659456 \nL 253.537819 36.793017 \nL 253.690026 58.190411 \nL 253.791498 91.800783 \nL 253.943705 40.785454 \nL 253.994441 43.052095 \nL 254.095912 37.008684 \nL 254.146648 38.974931 \nL 254.197383 47.535144 \nL 254.248119 42.866738 \nL 254.298855 37.391524 \nL 254.400326 59.588323 \nL 254.451062 52.830998 \nL 254.501798 57.732101 \nL 254.654005 35.712466 \nL 254.704741 54.243941 \nL 254.755476 50.895239 \nL 254.856948 39.119372 \nL 254.907684 43.919422 \nL 254.958419 37.424651 \nL 255.161362 64.870441 \nL 255.262834 35.135671 \nL 255.313569 40.124302 \nL 255.415041 44.633333 \nL 255.465777 39.089376 \nL 255.516512 48.232095 \nL 255.567248 44.340318 \nL 255.617984 40.578538 \nL 255.66872 58.033308 \nL 255.719455 35.538103 \nL 255.820927 38.301377 \nL 255.871662 34.677354 \nL 255.973134 45.691385 \nL 256.02387 36.051393 \nL 256.125341 36.636009 \nL 256.176077 53.922564 \nL 256.226813 51.457896 \nL 256.328284 36.910777 \nL 256.37902 38.724867 \nL 256.429756 39.066494 \nL 256.531227 45.512993 \nL 256.581963 56.706885 \nL 256.73417 35.404592 \nL 256.784906 35.46569 \nL 256.835641 35.844736 \nL 256.987849 56.203675 \nL 257.038584 35.493383 \nL 257.08932 43.277846 \nL 257.140056 45.513635 \nL 257.190791 41.513057 \nL 257.241527 47.828519 \nL 257.292263 38.681969 \nL 257.393734 38.816168 \nL 257.44447 41.259571 \nL 257.545942 34.293708 \nL 257.698149 54.530602 \nL 257.748884 51.44571 \nL 257.79962 36.574606 \nL 257.850356 45.076087 \nL 257.901092 65.92049 \nL 257.951827 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282.710863 35.300243 \nL 282.812334 37.150634 \nL 282.964542 40.211299 \nL 283.015277 58.452568 \nL 283.066013 37.341213 \nL 283.116749 47.557829 \nL 283.167485 37.29506 \nL 283.21822 38.87628 \nL 283.268956 36.677296 \nL 283.370427 55.420894 \nL 283.471899 34.70192 \nL 283.522635 39.348627 \nL 283.57337 52.016488 \nL 283.624106 36.838699 \nL 283.674842 49.07839 \nL 283.725578 54.608222 \nL 283.776313 52.808021 \nL 283.877785 36.597202 \nL 283.979256 38.703761 \nL 284.029992 37.900747 \nL 284.080728 46.378809 \nL 284.131463 39.843872 \nL 284.232935 36.926278 \nL 284.283671 44.192492 \nL 284.334406 37.892968 \nL 284.385142 41.852778 \nL 284.537349 36.632994 \nL 284.638821 38.682605 \nL 284.740292 43.959915 \nL 284.791028 52.32271 \nL 284.841764 43.345858 \nL 284.892499 35.237356 \nL 284.943235 37.355624 \nL 285.044706 47.213412 \nL 285.095442 46.792301 \nL 285.146178 36.284938 \nL 285.196914 52.443112 \nL 285.247649 46.713986 \nL 285.349121 42.060209 \nL 285.399857 45.19829 \nL 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39.262666 \nL 288.291793 54.55863 \nL 288.342529 42.1401 \nL 288.393265 48.31563 \nL 288.444 46.21133 \nL 288.545472 37.738633 \nL 288.596207 43.813708 \nL 288.646943 39.603065 \nL 288.697679 40.622005 \nL 288.748415 54.131912 \nL 288.79915 46.506899 \nL 288.849886 48.372908 \nL 288.951358 36.389738 \nL 289.002093 38.817977 \nL 289.052829 53.365775 \nL 289.103565 44.894956 \nL 289.205036 34.564849 \nL 289.255772 47.343649 \nL 289.357243 47.297058 \nL 289.407979 45.268234 \nL 289.458715 36.674847 \nL 289.560186 37.063439 \nL 289.712394 42.92582 \nL 289.763129 34.720484 \nL 289.915336 52.891475 \nL 290.067544 34.874481 \nL 290.219751 50.602448 \nL 290.371958 37.96475 \nL 290.422694 48.863385 \nL 290.473429 44.383005 \nL 290.524165 40.762632 \nL 290.574901 41.034092 \nL 290.625637 46.415762 \nL 290.676372 37.005498 \nL 290.727108 39.997729 \nL 290.777844 43.615393 \nL 290.82858 55.190693 \nL 290.879315 34.635638 \nL 290.930051 37.461898 \nL 291.031522 56.20488 \nL 291.082258 43.319878 \nL 291.132994 38.456354 \nL 291.335937 51.752319 \nL 291.386673 57.018508 \nL 291.488144 37.493381 \nL 291.53888 37.703712 \nL 291.589615 38.59385 \nL 291.640351 44.491716 \nL 291.691087 40.9724 \nL 291.741823 42.634623 \nL 291.792558 35.511594 \nL 291.89403 57.918009 \nL 291.944766 49.447517 \nL 291.995501 49.290876 \nL 292.046237 39.523946 \nL 292.096973 46.800416 \nL 292.147708 44.847253 \nL 292.198444 45.000617 \nL 292.24918 55.829173 \nL 292.299916 45.841645 \nL 292.401387 37.931504 \nL 292.452123 42.646595 \nL 292.502859 41.259133 \nL 292.553594 35.504385 \nL 292.60433 41.695049 \nL 292.655066 48.816139 \nL 292.705802 43.133101 \nL 292.756537 34.882441 \nL 292.807273 42.411424 \nL 292.908744 38.928725 \nL 292.95948 42.596812 \nL 293.010216 36.776165 \nL 293.060952 37.198097 \nL 293.162423 49.187004 \nL 293.213159 44.861606 \nL 293.31463 37.809591 \nL 293.365366 39.586047 \nL 293.466837 42.003317 \nL 293.568309 40.777202 \nL 293.66978 56.914104 \nL 293.720516 61.814914 \nL 293.872723 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59.522109 \nL 297.170546 37.74489 \nL 297.221281 37.910134 \nL 297.272017 44.713021 \nL 297.322753 41.256099 \nL 297.373489 41.780981 \nL 297.424224 34.428347 \nL 297.47496 41.851825 \nL 297.525696 44.849201 \nL 297.576431 54.86872 \nL 297.728639 38.444145 \nL 297.83011 41.585525 \nL 297.880846 52.890611 \nL 297.931582 47.574471 \nL 298.033053 35.223112 \nL 298.083789 38.729282 \nL 298.134524 37.411566 \nL 298.286732 64.342543 \nL 298.337467 34.623681 \nL 298.438939 37.720131 \nL 298.489675 39.436985 \nL 298.54041 56.543927 \nL 298.591146 52.049897 \nL 298.692617 39.326887 \nL 298.743353 41.881258 \nL 298.89556 35.274048 \nL 298.946296 36.17353 \nL 299.098503 74.359076 \nL 299.250711 40.831844 \nL 299.301446 48.001728 \nL 299.402918 47.171059 \nL 299.453653 50.205127 \nL 299.707332 35.500546 \nL 299.758068 36.090163 \nL 299.910275 53.146491 \nL 300.011746 38.468153 \nL 300.062482 50.421231 \nL 300.113218 41.589947 \nL 300.214689 37.787133 \nL 300.265425 47.534508 \nL 300.316161 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EVz2hcsLSntF",
        "outputId": "ebb2e34b-e9cb-492a-b386-09c148db07b6"
      },
      "source": [
        "print('The final Mu_hat values are: {}'.format(mu))\n",
        "print('The true mu values are: {}\\n'.format(mu_true))\n",
        "\n",
        "print('The final sigma_hat values are: {}'.format(sigma))\n",
        "print('The true sigma values are: {}\\n'.format(sigma_true))\n",
        "\n",
        "print('The final w_hat values are: {}'.format(w))\n",
        "print('The true w values are: {}\\n'.format(w_true))\n",
        "\n",
        "print('The final c_hat values are: {}'.format(cc[:10]))\n",
        "print('The true c values are: {}\\n'.format(cc_true[:10]))"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The final Mu_hat values are: [5.1900598  0.29016343]\nThe true mu values are: [0, 5]\n\nThe final sigma_hat values are: [0.9182188]\nThe true sigma values are: [1, 1]\n\nThe final w_hat values are: [0.49238716]\nThe true w values are: [0.6, 0.4]\n\nThe final c_hat values are: [1. 0. 1. 1. 1. 1. 1. 1. 1. 1.]\nThe true c values are: [0 1 0 0 0 0 0 0 0 0]\n\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gCwq9CbEXjSd"
      },
      "source": [
        "# Values to sample\n",
        "xx = np.linspace(-8, 11.0, num = 200)\n",
        "density_posterior = np.zeros((rrr-burn, len(xx)))\n",
        "for s in range(rrr-burn):\n",
        "  density_posterior[s, :] = density_posterior[s, :] + \\\n",
        "                             w_out[s + burn] * norm.pdf(loc = mu_out[s + burn, 0], scale = sigma_out[s + burn], x = xx) + \\\n",
        "                             (1 - w_out[s + burn]) * norm.pdf(loc = mu_out[s + burn, 1], scale = sigma_out[s + burn], x = xx)\n",
        "\n",
        "density_posterior_m = np.mean(density_posterior, axis = 0)\n",
        "density_posterior_lq = np.quantile(density_posterior, 0.025, axis = 0)\n",
        "density_posterior_uq = np.quantile(density_posterior, 0.975, axis = 0)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        },
        "id": "gti5P1ALYCMq",
        "outputId": "510f7a41-6a40-414e-8237-64de307e3159"
      },
      "source": [
        "## Plot the final result distribution for various samples\n",
        "fig, ax = plt.subplots(1, 1)\n",
        "# Mean value\n",
        "ax.plot(xx, density_posterior_m,  lw=2, alpha=0.6, label='Mean value') # Trace plot of data\n",
        "# Plotting original data\n",
        "for k in range(KK):\n",
        "  ax.scatter(np.array(x[cc_true == k]), np.zeros((x[cc_true == k].shape[0])), label = 'Component {}'.format(k + 1))\n",
        "# Plotting uncertainty\n",
        "plt.fill_between(xx, density_posterior_uq, density_posterior_lq, alpha=0.2,\n",
        "                 label='Uncertainty Interval')\n",
        "ax.legend(loc='best', frameon=False)\n",
        "# plot density estimate of the posterior\n",
        "plt.title('Trace plot of Logposterior')\n",
        "plt.show()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}