WD_RQ_NEWTON_TOV.ipynb

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      "name": "WD_RQ-NEWTON_TOV.ipynb",
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        "mKFnslgR-pYm"
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      "authorship_tag": "ABX9TyNO2zWC8nToG5ZkYsOiDxTA",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/taticorrea/monografia/blob/master/WD_RQ_NEWTON_TOV.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UQNlszZv7W4g"
      },
      "source": [
        "#Importando módulos\n",
        "import math as mt                         #funções matemáticas nativas do Python\n",
        "import numpy as np                        \n",
        "import csv\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt           #módulo para plotar gráficos\n",
        "from scipy.optimize import curve_fit      #modulo para fazer a regressao\n",
        "%matplotlib inline\n",
        "plt.style.use('seaborn-paper')"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tIz4RJH_76N_"
      },
      "source": [
        "#Constantes no SI\n",
        "c = 2.99792458E+8                                #m/s\n",
        "me = 9.109389E-31                                #kg\n",
        "mn = 1.674928E-27                                #kg\n",
        "A_Z_He = 4/2 #2He\n",
        "A_Z_C = 12/6 #12C\n",
        "G = 6.67408E-11 #N.m²/kg²\n",
        "Msol = 1.98892E+30 #kg\n",
        "Rsol = 696340  #m\n",
        "hbar = 1.054571726E-34                           #J.s\n",
        "e_zero = ((me**4)*(c**5))/((mt.pi**2)*(hbar**3)) #J/m³\n",
        "#e_zero = 1.42E+24     ARTIGO                    #erg/cm³"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kdm7Zn-cAM3o"
      },
      "source": [
        "#EoS exata"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O0bFfGMX-SpO"
      },
      "source": [
        "k = 1E-23\n",
        "delta = 1E-23\n",
        "while k < 9*me*c: \n",
        "  x = k/(me*c) \n",
        "  e_C = ((x**3*(A_Z_C)*me**3*mn*c**5)/(3*np.pi**2*hbar**3))\n",
        "  e_He =  (x**3*(A_Z_He)*me**3*mn*c**5)/(3*np.pi**2*hbar**3)\n",
        "  P = (e_zero/24)*((2*x**3 - 3*x)*(1 + x**2)**(1/2) + 3*mt.asinh(x))\n",
        "  with open('pressao_energia_C.csv', 'a', newline='') as file:\n",
        "    writter = csv.writer(file)\n",
        "    writter.writerow([k,x,e_C,P])\n",
        "  with open('pressao_energia_He.csv', 'a', newline='') as file:\n",
        "    writter = csv.writer(file)\n",
        "    writter.writerow([k,x,e_He,P])\n",
        "  #print(x,k)\n",
        "  k = k + delta\n",
        "\n",
        "pe_C = pd.read_csv('pressao_energia_C.csv', names=['k','x','dens. energia (J/m3)','pressao (N/m2)'])\n",
        "pe_He = pd.read_csv('pressao_energia_He.csv', names=['k','x','dens. energia (J/m3)','pressao (N/m2)'])"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VZ77v417LfB3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "bcffefaf-6e4f-45c2-bbe9-bcc2ff3454fb"
      },
      "source": [
        "pe_C"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>k</th>\n",
              "      <th>x</th>\n",
              "      <th>dens. energia (J/m3)</th>\n",
              "      <th>pressao (N/m2)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.000000e-23</td>\n",
              "      <td>0.036618</td>\n",
              "      <td>8.669982e+21</td>\n",
              "      <td>6.319512e+14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2.000000e-23</td>\n",
              "      <td>0.073235</td>\n",
              "      <td>6.935985e+22</td>\n",
              "      <td>2.019348e+16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.000000e-23</td>\n",
              "      <td>0.109853</td>\n",
              "      <td>2.340895e+23</td>\n",
              "      <td>1.529801e+17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.000000e-23</td>\n",
              "      <td>0.146470</td>\n",
              "      <td>5.548788e+23</td>\n",
              "      <td>6.425284e+17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.000000e-23</td>\n",
              "      <td>0.183088</td>\n",
              "      <td>1.083748e+24</td>\n",
              "      <td>1.952591e+18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>2.410000e-21</td>\n",
              "      <td>8.824845</td>\n",
              "      <td>1.213582e+29</td>\n",
              "      <td>7.191445e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>2.420000e-21</td>\n",
              "      <td>8.861463</td>\n",
              "      <td>1.228752e+29</td>\n",
              "      <td>7.312273e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>2.430000e-21</td>\n",
              "      <td>8.898080</td>\n",
              "      <td>1.244048e+29</td>\n",
              "      <td>7.434614e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>2.440000e-21</td>\n",
              "      <td>8.934698</td>\n",
              "      <td>1.259469e+29</td>\n",
              "      <td>7.558481e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>244</th>\n",
              "      <td>2.450000e-21</td>\n",
              "      <td>8.971316</td>\n",
              "      <td>1.275018e+29</td>\n",
              "      <td>7.683886e+25</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>245 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                k         x  dens. energia (J/m3)  pressao (N/m2)\n",
              "0    1.000000e-23  0.036618          8.669982e+21    6.319512e+14\n",
              "1    2.000000e-23  0.073235          6.935985e+22    2.019348e+16\n",
              "2    3.000000e-23  0.109853          2.340895e+23    1.529801e+17\n",
              "3    4.000000e-23  0.146470          5.548788e+23    6.425284e+17\n",
              "4    5.000000e-23  0.183088          1.083748e+24    1.952591e+18\n",
              "..            ...       ...                   ...             ...\n",
              "240  2.410000e-21  8.824845          1.213582e+29    7.191445e+25\n",
              "241  2.420000e-21  8.861463          1.228752e+29    7.312273e+25\n",
              "242  2.430000e-21  8.898080          1.244048e+29    7.434614e+25\n",
              "243  2.440000e-21  8.934698          1.259469e+29    7.558481e+25\n",
              "244  2.450000e-21  8.971316          1.275018e+29    7.683886e+25\n",
              "\n",
              "[245 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uhC8KLUQouC2"
      },
      "source": [
        "'''\n",
        "k = np.arange(0,2*me*c + 5.4e-22,1e-23)\n",
        "x = k/(2*me*c)\n",
        "\n",
        "\n",
        "df = pd.DataFrame(columns=['k','e_C','e_He','P'])\n",
        "\n",
        "df['k'] = k\n",
        "df['e_C'] = (e_zero/8)*((2*x**3 + x)*((1  + x**2)**(1/2)) - np.arcsinh(x)) + (x**3*(A_Z_C)*me**3*mn*c**5)/(3*np.pi**2*hbar**3)\n",
        "df['e_He'] = (e_zero/8)*((2*x**3 + x)*((1  + x**2)**(1/2)) - np.arcsinh(x)) + (x**3*(A_Z_He)*me**3*mn*c**5)/(3*np.pi**2*hbar**3)\n",
        "df['P'] = (e_zero/24)*((2*x**3 - 3*x)*(1 + x**2)**(1/2) + 3*np.arcsinh(x))\n",
        "'''"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IWKGKoZqzlOo"
      },
      "source": [
        "##fit"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YycZZQLGP-IE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "634ba1dd-a688-40d9-995f-fc342ac74cb6"
      },
      "source": [
        "###################### Regressao linear (EoS) ######################\n",
        "y_C = np.array(pe_C['dens. energia (J/m3)'])\n",
        "x_C = np.array(pe_C['pressao (N/m2)'])\n",
        "\n",
        "y_He = np.array(pe_He['dens. energia (J/m3)'])\n",
        "x_He= np.array(pe_He['pressao (N/m2)'])\n",
        "y_He = np.array(pe_He['dens. energia (J/m3)'])\n",
        "x_He = np.array(pe_He['pressao (N/m2)'])\n",
        "\n",
        "def fit_func(x, a, b):           #fit\n",
        "    return a*(x**(3/5)) + b*(x**(3/4))        #a-> caso nao-rel     b-> caso rel\n",
        "\n",
        "######### Ana branca C\n",
        "pars_C, cov_C = curve_fit(fit_func, x_C, y_C,p0=[1E+12,1E+9])\n",
        "stdevs_C = np.sqrt(np.diag(cov_C))   \n",
        "Anrel_C = pars_C[0]\n",
        "Arel_C = pars_C[1]\n",
        "\n",
        "\n",
        "pars_He, cov_He = curve_fit(fit_func, x_He, y_He,p0=[1E+12,1E+9])\n",
        "stdevs_He = np.sqrt(np.diag(cov_He))   \n",
        "Anrel_He = pars_He[0]\n",
        "Arel_He = pars_He[1]\n",
        "\n",
        "\n",
        "\n",
        "######### Ana branca He\n",
        "pars_He, cov_He = curve_fit(fit_func, x_He, y_He,p0=[1E+12,1E+9])\n",
        "######### desvpad dos parametros \n",
        "stdevs_He = np.sqrt(np.diag(cov_He))   \n",
        "\n",
        "\n",
        "Anrel_He = pars_He[0]\n",
        "Arel_He = pars_He[1]\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "######### Print dos resultados\n",
        "print('Ana Branca de C k[0,2mec]')\n",
        "print('Parametros',pars_C)\n",
        "print('Covariancia dos parametros',cov_C)\n",
        "print('Erros dos parametros',stdevs_C)\n",
        "print('\\n')\n",
        "\n",
        "\n",
        "print('Ana Branca de He')\n",
        "print('Parametros',pars_He)\n",
        "print('Covariancia dos parametros',cov_He)\n",
        "print('Erros dos parametros',stdevs_He)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Ana Branca de C k[0,2mec]\n",
            "Parametros [1.69209480e+12 4.68702176e+09]\n",
            "Covariancia dos parametros [[ 7.18251510e+20 -1.02748708e+17]\n",
            " [-1.02748708e+17  1.48284968e+13]]\n",
            "Erros dos parametros [2.68002147e+10 3.85077873e+06]\n",
            "\n",
            "\n",
            "Ana Branca de He\n",
            "Parametros [1.69209480e+12 4.68702176e+09]\n",
            "Covariancia dos parametros [[ 7.18251510e+20 -1.02748708e+17]\n",
            " [-1.02748708e+17  1.48284968e+13]]\n",
            "Erros dos parametros [2.68002147e+10 3.85077873e+06]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X8JX71Gr5aG_"
      },
      "source": [
        "##PxE"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8YcXvGxdKSau"
      },
      "source": [
        "###Regime qualquer"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QOK2Cip3Rtm4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "outputId": "35d92c36-b4ec-4075-cc92-7490c5fb79f5"
      },
      "source": [
        "######### Plot\n",
        "plt.figure(figsize=(8,6))\n",
        "plt.plot(pe_C['pressao (N/m2)'], pe_C['dens. energia (J/m3)'], color = 'green', label = r'Anã branca de $^{12}$C', linestyle = '-')\n",
        "plt.plot(x_C, fit_func(x_C, *pars_C), color = 'red', label = r'fit $^{12}$C', linestyle = '-.')\n",
        "\n",
        "plt.plot(pe_He['pressao (N/m2)'], pe_He['dens. energia (J/m3)'], color = 'blue', label = r'Anã branca de $^{4}$He', linestyle = '-')\n",
        "plt.plot(x_He, fit_func(x_He, *pars_He), color = 'violet', label = r'fit $^4$He', linestyle = '-.')\n",
        "\n",
        "plt.ylabel(r'Densidade de energia (J/m$^{3}$)',size = 13)\n",
        "plt.yscale('log')\n",
        "plt.yticks(size = 13)\n",
        "#plt.ylim(0,1.2e+28)\n",
        "\n",
        "plt.xlim(6e+14,1e+24)\n",
        "plt.xlabel(r'Pressao (N/m$^2$)',size = 13)\n",
        "plt.xticks(size = 13)\n",
        "plt.xscale('log')\n",
        "\n",
        "plt.legend(prop={'size': 12})\n",
        "\n",
        "plt.savefig('pxe_WD.png')\n",
        "plt.show()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1Mz1wmbBjQz9"
      },
      "source": [
        "#Politrópico"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hpIu8sgcjTvO"
      },
      "source": [
        "####$\\gamma$ = 4/3 (caso relativíístico)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Iz2Sms1ijkcA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "897d52d2-4daf-47f5-e6d1-7c2533864115"
      },
      "source": [
        "a = hbar*c/(12*np.pi**2)\n",
        "b = (3*np.pi**2*6/(12*mn*c**2))\n",
        "krel = a*b**(4/3)\n",
        "krel"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.2117706868491023e-13"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FNfW3zGpjcnM"
      },
      "source": [
        "####$\\gamma$ = 5/3 (caso não relativíístico)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K3M0xQRMjlSS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f72e12a3-7e75-427d-f550-ca8b7e5cebd9"
      },
      "source": [
        "a = hbar**2/(15*np.pi**2*me)\n",
        "b = (3*np.pi**2*6/(12*mn*c**2))\n",
        "knaorel = a*b**(5/3)\n",
        "knaorel"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.727936401002414e-22"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_km8GsdeWtqR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 515
        },
        "outputId": "72f4b9ea-b0b2-4046-8fa5-3593ecd36667"
      },
      "source": [
        "fig = plt.figure(figsize=(9,7))\n",
        "ax1 = fig.add_axes([0.1, 0.1, 0.85, 0.85])\n",
        "ax2 = fig.add_axes([0.63, 0.17, 0.3, 0.3])\n",
        "\n",
        "ax1.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2, pe_C['pressao (N/m2)']*10, color = 'red', label = r'EoS exata',ls='-')\n",
        "ax1.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2,knaorel*pe_C['dens. energia (J/m3)']**(5/3)*10, ls='-.',color='darkgreen', label='Politrópico não-relativístico $\\gamma = 5/3$')\n",
        "ax1.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2,krel*pe_C['dens. energia (J/m3)']**(4/3)*10, ls='-.',color='blue', label='Politrópico relativístico $\\gamma = 4/3$')\n",
        "\n",
        "ax1.set_xlabel(r'$\\rho (g/cm^3)$', size = 13)\n",
        "ax1.set_xscale('log')\n",
        "ax1.set_xlim([5e+4,1e+9])\n",
        "ax1.tick_params(axis = 'x', labelsize = 13)\n",
        "\n",
        "ax1.set_ylabel('p $(dyn/cm^2)$', size = 13)\n",
        "ax1.set_yscale('log')\n",
        "ax1.set_ylim([3e+20,1e+27])\n",
        "ax1.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "ax1.legend(loc=2,prop= {'size':12})\n",
        "\n",
        "\n",
        "ax2.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2, pe_C['pressao (N/m2)']*10, color = 'red', label = r'EoS exata')\n",
        "ax2.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2,knaorel*pe_C['dens. energia (J/m3)']**(5/3)*10, ls='-.',color='darkgreen')\n",
        "ax2.plot(pe_C['dens. energia (J/m3)']*1e-3/c**2,krel*pe_C['dens. energia (J/m3)']**(4/3)*10, ls='-.',color='blue')\n",
        "\n",
        "ax2.set_xscale('log')\n",
        "ax2.set_xlim([1e+6,1e+7])\n",
        "ax2.tick_params(axis = 'x', labelsize = 11)\n",
        "\n",
        "\n",
        "ax2.set_yscale('log')\n",
        "ax2.set_ylim([2.5e+22,1e+24])\n",
        "ax2.tick_params(axis = 'y', labelsize = 11)\n",
        "\n",
        "#ax2.grid(True)\n",
        "\n",
        "plt.savefig('pxe-politropico_exata_WD.png')"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 648x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c8wcD4K4-Fqf"
      },
      "source": [
        "##NEWTON"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdSEi8MZoAfD"
      },
      "source": [
        "h = 500 #m\n",
        "def f(R,P,M): #dp/dr\n",
        "    e_C = Anrel_C*(P**(3/5)) +  Arel_C*(P**(3/4)) #\n",
        "    #e_He = Anrel_He*(P**(3/5)) + Arel_He*(P**(3/4))\n",
        "    f = -G*M/(c**2*R**2)\n",
        "    return f*e_C\n",
        "def g(R,P,M): #dm/dr\n",
        "    e_C = Anrel_C*(P**(3/5)) +  Arel_C*(P**(3/4)) #\n",
        "    #e_He = Anrel_He*(P**(3/5)) + Arel_He*(P**(3/4))\n",
        "    f = (4*np.pi*R**2)/(c**2)\n",
        "    return f*e_C\n",
        "\n",
        "#Condicoes iniciais\n",
        "R = 1e-2\n",
        "M = 1e-2\n",
        "P = 1E+25\n",
        "\n",
        "with open('WD-NEWTON_regimequalquer-25.csv', 'a', newline='') as file:\n",
        "  writter = csv.writer(file)\n",
        "  writter.writerow(['p (N/m2)','m (Msol)','R (km)'])\n",
        "while P > 0:\n",
        "  k1P = h*f(R,       P,              M )    \n",
        "  k1M = h*g(R,       P,              M)\n",
        "  k2P = h*f(R + h/2, P + k1P/2, M + k1M/2)  \n",
        "  k2M = h*g(R + h/2, P + k1P/2, M + k1M/2)\n",
        "  k3P = h*f(R + h/2, P + k2P/2, M + k2M/2)\n",
        "  k3M = h*g(R + h/2, P + k2P/2, M + k2M/2)\n",
        "  k4P = h*f(R + h,   P + k3P, M + k3M)\n",
        "  k4M = h*g(R + h,   P + k3P, M + k3M)\n",
        "  with open('WD-NEWTON_regimequalquer-25.csv', 'a', newline='') as file:\n",
        "    writter = csv.writer(file)\n",
        "    writter.writerow([P,M/Msol,R*1E-3])      \n",
        "    #Calculando P+1, M+1 e R\n",
        "    P = P + (1/6)*(k1P + 2*k2P + 2*k3P + k4P)\n",
        "    M = M + (1/6)*(k1M + 2*k2M + 2*k3M + k4M)\n",
        "    R = R + h\n",
        "    print('P (N/m2):','{:e}'.format(P),' M (Msol):',M/Msol,'  R (km):',R*1E-3)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HCMUO6YXgwdT"
      },
      "source": [
        "WD_21_NEWTON = pd.read_csv('WD-NEWTON_regimequalquer-21.csv')\n",
        "WD_22_NEWTON = pd.read_csv('WD-NEWTON_regimequalquer-22.csv')\n",
        "WD_23_NEWTON = pd.read_csv('WD-NEWTON_regimequalquer-23.csv')\n",
        "WD_24_NEWTON = pd.read_csv('WD-NEWTON_regimequalquer-24.csv')\n",
        "WD_25_NEWTON = pd.read_csv('WD-NEWTON_regimequalquer-25.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kDe4jT0g-I-Y"
      },
      "source": [
        "##TOV"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6xhONFmqsEEN"
      },
      "source": [
        "h = 500 #m\n",
        "def f(R,P,M): #dp/dr = -GMe/c²r²[1 + p/e][1 + 4pir³/(Mc²)][1 - 2GM/(c²r²)] = -ABCD\n",
        "  e_C = Anrel_C*(P**(3/5)) + Arel_C*(P**(3/4))  #\n",
        "  #e_He = Anrel_He*(P**(3/5)) + Arel_He*(P**(3/4)) #\n",
        "  A_C = G*e_C*M/(c**2*R**2)\n",
        "  #A_He = G*e_He*M/(c**2*R**2)\n",
        "  B_C = 1 + P/e_C\n",
        "  #B_He = 1 + P/e_He\n",
        "  C = 1 + 4*np.pi*R**3*P/(M*c**2)\n",
        "  D = (1 - 2*G*M/(c**2*R))**(-1)\n",
        "  return -A_C*B_C*C*D\n",
        "def g(R,P,M): #dm/dr = 4pir²e/c²\n",
        "  e_C = Anrel_C*(P**(3/5)) + Arel_C*(P**(3/4))    #\n",
        "  #e_He = Anrel_He*(P**(3/5)) + Arel_He*(P**(3/4)) #\n",
        "  f = (4*np.pi*R**2)/(c**2)\n",
        "  return f*e_C\n",
        "\n",
        "#Condicoes iniciais\n",
        "R = 1e-2\n",
        "M = 1e-2\n",
        "P = 4E+33\n",
        "\n",
        "with open('WD-TOV_regimequalquer-4e33.csv', 'a', newline='') as file:\n",
        "  writter = csv.writer(file)\n",
        "  writter.writerow(['p (N/m2)','m (Msol)','R (km)'])\n",
        "while P > 0:\n",
        "  k1P = h*f(R,       P,              M )    \n",
        "  k1M = h*g(R,       P,              M)\n",
        "  k2P = h*f(R + h/2, P + k1P/2, M + k1M/2)  \n",
        "  k2M = h*g(R + h/2, P + k1P/2, M + k1M/2)\n",
        "  k3P = h*f(R + h/2, P + k2P/2, M + k2M/2)\n",
        "  k3M = h*g(R + h/2, P + k2P/2, M + k2M/2)\n",
        "  k4P = h*f(R + h,   P + k3P, M + k3M)\n",
        "  k4M = h*g(R + h,   P + k3P, M + k3M)\n",
        "  \n",
        "  with open('WD-TOV_regimequalquer-4e33.csv', 'a', newline='') as file:\n",
        "    writter = csv.writer(file)\n",
        "    writter.writerow([P,M/Msol,R*1E-3])      \n",
        "    #Calculando P+1, M+1 e R\n",
        "  \n",
        "\n",
        "  P = P + (1/6)*(k1P + 2*k2P + 2*k3P + k4P)\n",
        "  M = M + (1/6)*(k1M + 2*k2M + 2*k3M + k4M)\n",
        "  R = R + h\n",
        "\n",
        "  #print('k1P:','{:e}'.format(k1P),'k2P:','{:e}'.format(k2P),'k3P:','{:e}'.format(k3P),'k4P:','{:e}'.format(k4P))\n",
        "  #print('k1M:','{:e}'.format(k1M),'k2M:','{:e}'.format(k2M),'k3M:','{:e}'.format(k3M),'k4M:','{:e}'.format(k4M))\n",
        "  print('P (N/m2):','{:e}'.format(P),' M (Msol):',M/Msol,'  R (km):',R*1E-3)\n",
        "  print('\\n')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p_cJdsxN-I_h"
      },
      "source": [
        "#WD_18_TOV = pd.read_csv('WD-TOV_regimequalquer-18.csv')\n",
        "#WD_19_TOV = pd.read_csv('WD-TOV_regimequalquer-19.csv')\n",
        "#WD_20_TOV = pd.read_csv('WD-TOV_regimequalquer-20.csv')\n",
        "WD_21_TOV = pd.read_csv('WD-TOV_regimequalquer-21.csv')\n",
        "WD_2e21_TOV = pd.read_csv('WD-TOV_regimequalquer-2e21.csv')\n",
        "WD_4e21_TOV = pd.read_csv('WD-TOV_regimequalquer-4e21.csv')\n",
        "\n",
        "WD_22_TOV = pd.read_csv('WD-TOV_regimequalquer-22.csv')\n",
        "WD_2e22_TOV = pd.read_csv('WD-TOV_regimequalquer-2e22.csv')\n",
        "WD_4e22_TOV = pd.read_csv('WD-TOV_regimequalquer-4e22.csv')\n",
        "\n",
        "WD_23_TOV = pd.read_csv('WD-TOV_regimequalquer-23.csv')\n",
        "WD_2e23_TOV = pd.read_csv('WD-TOV_regimequalquer-2e23.csv')\n",
        "WD_4e23_TOV = pd.read_csv('WD-TOV_regimequalquer-4e23.csv')\n",
        "\n",
        "WD_24_TOV = pd.read_csv('WD-TOV_regimequalquer-24.csv')\n",
        "WD_2e24_TOV = pd.read_csv('WD-TOV_regimequalquer-2e24.csv')\n",
        "WD_4e24_TOV = pd.read_csv('WD-TOV_regimequalquer-4e24.csv')\n",
        "\n",
        "WD_25_TOV = pd.read_csv('WD-TOV_regimequalquer-25.csv')\n",
        "WD_2e25_TOV = pd.read_csv('WD-TOV_regimequalquer-2e25.csv')\n",
        "WD_4e25_TOV = pd.read_csv('WD-TOV_regimequalquer-4e25.csv')\n",
        "\n",
        "WD_26_TOV = pd.read_csv('WD-TOV_regimequalquer-26.csv')\n",
        "WD_2e26_TOV = pd.read_csv('WD-TOV_regimequalquer-2e26.csv')\n",
        "WD_4e26_TOV = pd.read_csv('WD-TOV_regimequalquer-4e26.csv')\n",
        "\n",
        "WD_27_TOV = pd.read_csv('WD-TOV_regimequalquer-27.csv')\n",
        "WD_2e27_TOV = pd.read_csv('WD-TOV_regimequalquer-2e27.csv')\n",
        "WD_4e27_TOV = pd.read_csv('WD-TOV_regimequalquer-4e27.csv')\n",
        "\n",
        "WD_28_TOV = pd.read_csv('WD-TOV_regimequalquer-28.csv')\n",
        "WD_2e28_TOV = pd.read_csv('WD-TOV_regimequalquer-2e28.csv')\n",
        "WD_4e28_TOV = pd.read_csv('WD-TOV_regimequalquer-4e28.csv')\n",
        "\n",
        "WD_29_TOV = pd.read_csv('WD-TOV_regimequalquer-29.csv')\n",
        "WD_2e29_TOV = pd.read_csv('WD-TOV_regimequalquer-2e29.csv')\n",
        "WD_4e29_TOV = pd.read_csv('WD-TOV_regimequalquer-4e29.csv')\n",
        "\n",
        "WD_30_TOV = pd.read_csv('WD-TOV_regimequalquer-30.csv')\n",
        "WD_2e30_TOV = pd.read_csv('WD-TOV_regimequalquer-2e30.csv')\n",
        "WD_4e30_TOV = pd.read_csv('WD-TOV_regimequalquer-4e30.csv')\n",
        "\n",
        "WD_31_TOV = pd.read_csv('WD-TOV_regimequalquer-31.csv')\n",
        "WD_2e31_TOV = pd.read_csv('WD-TOV_regimequalquer-2e31.csv')\n",
        "WD_4e31_TOV = pd.read_csv('WD-TOV_regimequalquer-4e31.csv')\n",
        "\n",
        "WD_32_TOV = pd.read_csv('WD-TOV_regimequalquer-32.csv')\n",
        "WD_2e32_TOV = pd.read_csv('WD-TOV_regimequalquer-2e32.csv')\n",
        "WD_4e32_TOV = pd.read_csv('WD-TOV_regimequalquer-4e32.csv')\n",
        "\n",
        "WD_33_TOV = pd.read_csv('WD-TOV_regimequalquer-33.csv')\n",
        "WD_2e33_TOV = pd.read_csv('WD-TOV_regimequalquer-2e33.csv')\n",
        "WD_4e33_TOV = pd.read_csv('WD-TOV_regimequalquer-4e33.csv')\n",
        "\n",
        "WD_34_TOV = pd.read_csv('WD-TOV_regimequalquer-34.csv')\n",
        "WD_2e34_TOV = pd.read_csv('WD-TOV_regimequalquer-2e34.csv')\n",
        "WD_4e34_TOV = pd.read_csv('WD-TOV_regimequalquer-4e34.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K7Qr9d11D3pS"
      },
      "source": [
        "#passo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o_-_gMq3SRAN"
      },
      "source": [
        "passo = [100e+3,50e+3,20e+3,10e+3,5e+3,2e+3,1e+3,50,20,10]\n",
        "massa = [1.3058027718590748,1.3057903428441846,1.3058174909391382,1.3058212512365333,1.3058220602568336,1.305822293188659,1.305822325324642,1.3058223360588526,1.3058223360812125,1.3058223360843726]\n",
        "raio = [3900.0000099999997,3950.0000099999997,4020.0000099999997,4050.0000099999997,4055.0000099999997,4062.0000099999997,4063.0000099999997,4064.90001,4064.96001,4064.9800099999998]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F4Z2DFGwi23Y",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "d8cb8d58-bfd5-4ace-902a-d60a48af2f89"
      },
      "source": [
        "%matplotlib inline\n",
        "\n",
        "plt.figure(figsize=(10,8))\n",
        "plt.plot(passo,raio,color='blue',ls='-')\n",
        "plt.xlabel('passo (m)')\n",
        "plt.ylabel('raio (km)')\n",
        "plt.yscale('log')\n",
        "#plt.yticks(np.arange(3.9,4.3,0.1))\n",
        "plt.xscale('log')\n",
        "#plt.xlim(1.305,1.306)\n",
        "plt.savefig('passoxraio.png')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3yW0pDq4hblM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "48d6cfee-c91e-4887-bb3a-cff485b3308a"
      },
      "source": [
        "%matplotlib inline\n",
        "\n",
        "plt.figure(figsize=(10,8))\n",
        "plt.plot(passo,massa, color='red')\n",
        "plt.xlabel('passo (m)')\n",
        "plt.ylabel(r'massa $(M_{\\odot})$')\n",
        "plt.yscale('log')\n",
        "plt.xscale('log')\n",
        "plt.savefig('passoxmassa.png')\n",
        "#plt.xlim(1.305,1.306)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mKFnslgR-pYm"
      },
      "source": [
        "#PLOTS"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ksn81n-eqB0M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "c6a889bd-8d58-445d-cd6a-b31562211337"
      },
      "source": [
        "fig = plt.figure(figsize = (8,6))\n",
        "ax = fig.add_subplot(111)\n",
        "\n",
        "ax.set_title(r'$p_0$ = 10$^{21} N/m^2$', size = 13)\n",
        "lns1 = ax.plot(WD_21_NEWTON['R (km)'],WD_21_NEWTON['p (N/m2)'],color ='red', linestyle=':', label = r'p (NEWTON)')\n",
        "lns2 = ax.plot(WD_21_TOV['R (km)'],WD_21_TOV['p (N/m2)'],color ='blue', linestyle='-.', label = r'p (TOV)')\n",
        "\n",
        "ax.tick_params(axis = 'y', labelsize = 13)\n",
        "ax.tick_params(axis = 'x', labelsize = 13)\n",
        "\n",
        "plt.ylim(0,1e+21)\n",
        "plt.xlim(0,15e+3)\n",
        "\n",
        "ax.set_ylabel(r'$p (N/m^2)$', size = 13)\n",
        "\n",
        "\n",
        "\n",
        "ax2 = ax.twinx()\n",
        "lns3 = ax2.plot(WD_21_NEWTON['R (km)'],WD_21_NEWTON['m (Msol)'],color ='blue',linestyle=':', label = r'M (NEWTON)')\n",
        "lns4 = ax2.plot(WD_21_TOV['R (km)'],WD_21_TOV['m (Msol)'],color ='red', linestyle='-.', label = r'M (TOV)')\n",
        "ax2.set_ylabel(r'M $(M_{\\odot})$', size = 13)\n",
        "ax.set_xlabel('Raio (km)', size = 13)\n",
        "lns = lns1+lns2+lns3+lns4\n",
        "labs = [l.get_label() for l in lns]\n",
        "plt.ylim(0,0.4)\n",
        "\n",
        "ax2.tick_params(axis = 'x', labelsize = 13)\n",
        "ax2.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "\n",
        "ax.legend(lns, labs, loc=5,prop={'size':12})\n",
        "\n",
        "fig.savefig('WD_regimequalquer-21.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9NygwneWj0yf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "4d9833fc-1208-4fbf-bae4-15b7392f0247"
      },
      "source": [
        "fig = plt.figure(figsize = (8,6))\n",
        "ax = fig.add_subplot(111)\n",
        "\n",
        "ax.set_title(r'$p_0$ = 10$^{22} N/m^2$', size = 13)\n",
        "lns1 = ax.plot(WD_22_NEWTON['R (km)'],WD_22_NEWTON['p (N/m2)'],color ='red', linestyle=':', label = r'p (NEWTON)')\n",
        "lns2 = ax.plot(WD_22_TOV['R (km)'],WD_22_TOV['p (N/m2)'],color ='blue', linestyle='-.', label = r'p (TOV)')\n",
        "plt.ylim(0,1e+22)\n",
        "plt.xlim(0,11e+3)\n",
        "ax.tick_params(axis = 'x', labelsize = 13)\n",
        "ax.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "\n",
        "ax.set_ylabel(r'$p (N/m^2)$', size = 13)\n",
        "\n",
        "ax2 = ax.twinx()\n",
        "lns3 = ax2.plot(WD_22_NEWTON['R (km)'],WD_22_NEWTON['m (Msol)'],color ='blue',linestyle=':', label = r'M (NEWTON)')\n",
        "lns4 = ax2.plot(WD_22_TOV['R (km)'],WD_22_TOV['m (Msol)'],color ='red', linestyle='-.', label = r'M (TOV)')\n",
        "ax2.set_ylabel(r'M $(M_{\\odot})$', size = 13)\n",
        "ax.set_xlabel('Raio (km)', size = 13)\n",
        "lns = lns1+lns2+lns3+lns4\n",
        "labs = [l.get_label() for l in lns]\n",
        "ax.legend(lns, labs, loc=5,prop={'size':12})\n",
        "plt.ylim(0,0.6)\n",
        "ax2.tick_params(axis = 'x', labelsize = 13)\n",
        "ax2.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "fig.savefig('WD_regimequalquer-22.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3fmMk88jtrQy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "b8349235-51df-40d6-c7b2-7b744f3bfbe0"
      },
      "source": [
        "fig = plt.figure(figsize = (8,6))\n",
        "ax = fig.add_subplot(111)\n",
        "\n",
        "ax.set_title(r'$p_0$ = 10$^{23} N/m^2$', size = 13)\n",
        "lns1 = ax.plot(WD_23_NEWTON['R (km)'],WD_23_NEWTON['p (N/m2)'],color ='red', linestyle=':', label = r'p (NEWTON)')\n",
        "lns2 = ax.plot(WD_23_TOV['R (km)'],WD_23_TOV['p (N/m2)'],color ='blue', linestyle='-.', label = r'p (TOV)')\n",
        "plt.ylim(0,1e+23)\n",
        "plt.xlim(0,8e+3)\n",
        "ax.set_ylabel(r'$p (N/m^2)$', size = 13)\n",
        "ax.tick_params(axis = 'x', labelsize = 13)\n",
        "ax.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "ax2 = ax.twinx()\n",
        "lns3 = ax2.plot(WD_23_NEWTON['R (km)'],WD_23_NEWTON['m (Msol)'],color ='blue',linestyle=':', label = r'M (NEWTON)')\n",
        "lns4 = ax2.plot(WD_23_TOV['R (km)'],WD_23_TOV['m (Msol)'],color ='red', linestyle='-.', label = r'M (TOV)')\n",
        "ax2.set_ylabel(r'M $(M_{\\odot})$', size = 13)\n",
        "ax.set_xlabel('Raio (km)', size = 13)\n",
        "lns = lns1+lns2+lns3+lns4\n",
        "labs = [l.get_label() for l in lns]\n",
        "ax.legend(lns, labs, loc=5,prop={'size':12})\n",
        "plt.ylim(0,0.9)\n",
        "ax2.tick_params(axis = 'x', labelsize = 13)\n",
        "ax2.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "fig.savefig('WD_regimequalquer-23.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ILBmh23MqGr9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "outputId": "6ebf89ae-6fa0-45e0-9ba1-8bb7029a2bcf"
      },
      "source": [
        "fig = plt.figure(figsize = (8,6))\n",
        "ax = fig.add_subplot(111)\n",
        "\n",
        "ax.set_title(r'$p_0$ = 10$^{24} N/m^2$', size = 13)\n",
        "lns1 = ax.plot(WD_24_NEWTON['R (km)'],WD_24_NEWTON['p (N/m2)'],color ='red', linestyle=':', label = r'p (NEWTON)')\n",
        "lns2 = ax.plot(WD_24_TOV['R (km)'],WD_24_TOV['p (N/m2)'],color ='blue', linestyle='-.', label = r'p (TOV)')\n",
        "plt.ylim(0,1e+24)\n",
        "plt.xlim(0,5e+3)\n",
        "ax.set_ylabel(r'$p (N/m^2)$', size = 13)\n",
        "ax.tick_params(axis = 'x', labelsize = 13)\n",
        "ax.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "ax2 = ax.twinx()\n",
        "lns3 = ax2.plot(WD_24_NEWTON['R (km)'],WD_24_NEWTON['m (Msol)'],color ='blue',linestyle=':', label = r'M (NEWTON)')\n",
        "lns4 = ax2.plot(WD_24_TOV['R (km)'],WD_24_TOV['m (Msol)'],color ='red', linestyle='-.', label = r'M (TOV)')\n",
        "ax2.set_ylabel(r'M $(M_{\\odot})$', size = 13)\n",
        "ax.set_xlabel('Raio (km)', size = 13)\n",
        "lns = lns1+lns2+lns3+lns4\n",
        "labs = [l.get_label() for l in lns]\n",
        "ax.legend(lns, labs, loc=5,prop={'size':12})\n",
        "plt.ylim(0,1.2)\n",
        "ax2.tick_params(axis = 'x', labelsize = 13)\n",
        "ax2.tick_params(axis = 'y', labelsize = 13)\n",
        "\n",
        "fig.savefig('WD_regimequalquer-24.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Hyi9cuP8X2LaNVAkg4cFnqfDWS84qdampUM4mRxQmS2hKKW9PaDKLiz5AWMPz3A7DGGMK7LfvjrL26Qn8M2IKMncOJCcTX7kuoTdcAVdcAT16OGNgTJHxhYTG9nLyYqvGr6be+QEsfH+126EYY0yepaXBmKF/sfTV2QBUCEzkvq2PkpqQDCNGwNq1hB7cAR98ANdea8mMKRTWQuPFUpPTeKXvHzz03zaEVw9yOxxjjDmrv/6CJd/s4qYh4RAWxg+17qd7ynQqHNjiLEYXF2eJi4t8oYXGEpoS4uhfsVSoZ5tYGmO8x6FDoEePUWXON+x9bTzVN80l6a0PKffQP9B9+5FywVDBZmt6A19IaKzLqQTYvmAPDeun8d0Tv7sdijHGQFoaaVOmMq/WLVRoUg0GD6ZaNUh592PKDboJAKlR3ZIZU6yshaYE0HTlmpbbWHygPmvW+lG9utsRGWN80W+TjxD98NvcLR8ju3YRX7c56f1vp/y9tzlTrI3X8oUWGktoSoi//4ZWrSCybRo/TxXE3xrXjDFFSxXmzEqj/MFo2t3amPXzYqjbqzH+N/Qj+MEh0KFDid2s0ddYQlNKlcSEBuDH/x3n2lvK8eGtcxjyRXe3wzHGlFKpqRAQ4Hz/ea1nue7QR4Qd3Q1ly0JysvPVlCi+kNDYf/NLkGtuLsfAyLU8/mM3du1yOxpjTGm0bso2PqvwEPtG/heAq6fcQ+hvP0JgoFPBkhnjpSyhKWHemNaSkDB/7r1H0XTfa10zxhS+bdtgwasL4brraH7t+dyaNp6yJ+IBqHxhPeSizta1ZLyeJTQlTKVK8N6byUz9RZh4zzy3wzHGlGSqMH066d0upuvTXdF165B33yXk0C4qDf+n29EZky+W0JRA/W4py52tlpEcXs3tUIwxJVBKCozu9jOHGnWEyy8nomo8SV98i2zYAPfdByGleqiFKaUC3A7AFMynqyPdDsEYU8Ls+iudOrWVwEB/uv49GQ0oA1OnEtC7NwHWpWRKOGuhKcFSj6fwaLNfmPzIfLdDMcZ4uQXTj3Mgoj3bX/ocgK6r36PKhgXO5pCWzJhSwBKaEsw/OJDdyVX5+6jt82SMOdP+/TDn9eWgSqce5fDrcxW1LmninAwKskTGlCq2Dk0Jp2q/k4wx2Vi9mk3XP0uTrT+T8t3PBPa90u2IjItsHRrj9UQg+Vgyz3edzbJPV7sdjjHGZV+/8zfRPYdAmzY0St1A/AcTCOxzudthGVPkrIWmFDiRmEq7KjsoU6UCS7dVxd/f7YiMMcUuORn+/W+ODxsBfn6UG/UCDB16akE849OshcaUCGWCA/jg1/r8ubMq777rdjTGmOJ07Bi83vVbEus3h2eeoezg2ym3ews8+qglM8anWAtNKTLkH8qXE06wYe5BanWo5XY4xpgilDF+Lj0dlte8mnrVUzhvwhvQsqXboRkvZC00pkQZPSyOoJRjPHLPcbdDMcYUoW2bU/m49nB2ffwrfn7QPvp/nLdimiUzplCIyC0iMl9EjolIah7qR4rIUhE5LiLRIjKgOOI8nSU0pUiliPK8/k5Zvl7ZiGnT3I7GGFPY0tOdr9Vr+ROZuhj/LZucgpAQm+5oCtMR4D3g4dwqikgF4BdgMlARuBf4QEQ6F2mE2cViXU6liypERcHBv46zeq0fgeVtjRpjSoPF3+3jyMCH6Tz+fsKvvdjJbvzs/6QmbwrS5SQi3YGZqnrWXQVE5E7gRSBCPQmFiIwHUlX1zoJHnH/2r6GUEYG3h+1ny66yfHDPCrfDMcacI01XGDeODnc2p0vKb3D0qHPCkhnjHS4AVmjW1pE/PeXFyv5FlEJteldn8mvbuPODjm6HYow5B7+N282iylfDwIH4XdGb8rvWE37HNW6HZUqmABFZluk1pJDuGwYcPa0sFihfSPfPM9ucspTq+0QjAI5t3k/5xtVdjsYYky+q8OmnXPzwo8SlBpMw/ltCBvRzOypTsqWqalHsahwHRJxWFg4cK4Jn5chaaEqxlRPWUqdJMIs+WOV2KMaYPJr2yW5WVu8Nd9+Nf79rCd+z3pIZ481WAW1OK2vrKS9WltCUYi1vas4TfTbSpE9jt0MxxuRReNwuasdtIOmbKTBuHFSq5HZIxseIiL+IBAGBnuMgzyu7qXTfASEi8oSIBIrIpcB1wNhiDBmwWU4+I/1EGn5lbE8EY7zR4unHODb6PS6b8QT4+0NKiq3yawpVfmY5icgg4L/ZnKoP1MGZpt1cVXd66rcH3gVaAfuAF1R1QmHEnR/WQuMDZry2ghYhO4jddtjtUIwx2Tg4fQVd5o0k8Y+1ToElM8ZFqvqZqko2rx2qOl9VQzOSGU/9P1S1g6oGq2oDN5IZsITGJzS7tCZ/aR1eed3WpDHGW+zYmsrv944DVa4eczFl9/1FcKdin+lqTKnhFQmNp79ujIgcFJE4EZksIlVyqP+4Z3nlOBHZIiL3F2e8JU3tdtV4/JlA/vNxObZtczsaYwz79qE9e9LxwztJmrcUEQioWtHtqIwp0bwioQGeBq4FOgK1PWXjs6soItcALwH9VTUMuAMYIyK9iiPQkurJJ6FSaDJP917pdijG+KwTJ2Drh7OgTRsikjaS8P1Mgi629aKMKQzektAMAV5V1W2qehR4EugtIvWyqXs+sEpVFwOo6iJgNS6sSliShIbCiOtW8PWWNvz+W5Lb4Rjje9LSWNDzRRrc24vUpi2QlSspf+0lbkdlTKnhekIjIuFAXWB5RpmqRuMsypNdkvIlUF5EuoiIn4h0AxoDvxZHvCXZoPc70rq18uizQfjg5DZjXHN8+99w+eV0n/8ye+56noDfZkB1W/DSmMLkekKDs2wy5H3p5APAN8BsIMXzdbiqrs3pISIyJGPJ59TUXHdDL5X8A4TXXxeWLIH/DVvtdjjG+IQfX/yTuEZtSV+1Gpk2jTqfvORMzTbGFCpvSGjiPF8rnFZ+tqWTnwduw1mZsAxOK84jIjI4p4eo6lhVjVTVyIAA393xoWdPuKr6ckb8O8xaaYwpBm2vqM7hxp3QP1dCLxvqZ0xRcT2hUdVYYCdwYUaZiDTAaZ3JrhmhHfCdqq5Xxzrge6BPccRbGrw7tT4z1tci2zUfjTHnLHpDClPaPE/yvsPU6ViTZuu/xb9OTbfDMqZUcz2h8RgLPCUi9UWkPPAqME1Vd2RTdyHQV0QaAYhIM6AvmcbgmJzVa1uJGvUCid92gNitMW6HY0ypE7thH53XfkTs1N/dDsUYn+EtCc1oYArwB7AH8AcGAIhIfxGJz1R3DM7eETM85dNwWmhGF2vEJVxaciqRTeIY1ned26EYUyqowoJ/L0fj4ml3XT0qHo6m2uCr3Q7LGJ9hezn5sCmj1tKiV00aRNrmd8acq00vf0m94YPY3/9xIiaMcDscY7LIz15OJZUlNIa05FT8y/ruQGljzsWJFKXMqyPghRc4fPmtVPr+UwiybUaMd/GFhMZbupyMS6Ln7qZx6B7++MhWEDYmvw7sSmbqeQPhhRfghReo9MtES2aMcYm10Pi41JR0Wtc4QPVGYcxaFGIzn4zJq5gY9LrrSFu4hAOjPqHmkwPcjsiYs7IWGlPqBQT6MfKT6sxeEsL06W5HY0zJMPXNTSRf2AlZv56AOTMtmTHGC1gLjUEVurRJ4PiuQ/y5vyZ+gTaexpizSU2FpZV6c37Ads5b+jOcf77bIRmTK2uhMT5BBF59YCerjtTlyw9P34HCGAOQng7HDiYTEADNl4+nyuZFlswY40WshcacdM01ypo1wsaNULas29EY410+v/J/XDL7eWrt+B3/alXcDseYfLEWGuNTRo4Udu5UPnzIFtsz5nRthnQgvmc//CuHux2KMSYb1kJjsrir2SJ+2dKQv+IqExhsOwIb33ZgXxprBv4fPb6+D6lQ3u1wjCkwa6ExPmfEN02Zs6ScJTPGJCeT0u9mus94lphv5rgdjTEmF9ZCY7KVejSBpKPJhNa1bRGM70k4eJyQAf1gzhwS//slwbf1czskY86JtdAYn6Rp6XSuvo1hV9nqwcb37NlwjDW1e5M6dwH89JMlM8aUELbgiDmD+Pvx6D9TadylsduhGFO8Dh2i5h29qSybif1yGlV6dXU7ImNMHlmXk8mZKrYfgvEFS3/cT6tHexEcuw+mTYN27dwOyZhCY11OxqdFz91Np7C1bPl5s9uhGFOkVCF2yBMk7o6BuXMtmTGmBLIWGnNWibHJNKyRQPfuwhe/VHQ7HGOKhKYr4icc2R5L2fhDlGvV0O2QjCl01kJjfFpweFmee70SX06ryJo1bkdjTOFbMG4bK8O7c3TVDirWD7dkxpgSzBIak6O774Z6NVN4/uZNbodiTKGrVNWfgJCylC1n6y4ZU9JZQmNyFBgIw/us4IcNTVg6PdbtcIwpFBt+2UH64ViaX1GPVvumE9SojtshGWPOkY2hMblKTUmnZSuoW8+P6dPdjsaYcxOzdBvHO11CYpvONPnzS7fDMaZY2BgaY4CAQD9e/pcfM2bA3HF/uR2OMQW3bRtVbryEKtUDqPe/MW5HY4wpRNZCY/IkPR0uDI8mVBKYH9valqYxJc7vE7fT+sHuhIYHwJw5UMe6mYzv8IUWGlsp2OSJnx+8974ffhVqWjJjSp7du2l8/6UcOxFAyIo5iCUzxpQ61kJj8k1PpIIIEmAzQ4z3S917gIAeUWhCAikz51O2SYTbIRlT7HyhhcbG0Jh8idt9lIvKr2HyowvdDsWYXG1ZeoQt9S/jxMEjyMyZlswYU4pZQmPyJax2BTq2SeG8C2q4HYoxuapazY+kanWJ/3YGNGnidjjGmCJkXU7GmFJn95ZEQhJjqNjaxsoYA9blZMxZrfsxmnuazCH1eIrboRiThSos6/YwCRf1hNRUt8MxxhQTS2hMgSTEpTN2c3cmvXfE7VCMyUIEmk18Ht57HwJsIqcxvsK6nEyB9emjbNwobNhgnxvGfUmJyuJb3qTrR4MIOK+S2+EY41Wsy8mYHLz0krB1K0x43jauNO7be89LdP/xMfb81/bnMMYXWQuNOSf96i5j1f5qbIqvTZlAW3HPuOT99+H++0l4+l+EjHrO7WiM8TrWQmNMLl78tB7bT9Th83GWzBh3fHPLN+gDD8ADDxAycpjb4RhjXGItNOac3XgjLF2ibFmbTGD5ILfDMT5Ef5tNWq/ebG52Lc1XTQJ/W73amOxYC40xeTD8qSR27VI+vWuB26EYH5L4+wqk77X4d+9Ks2XjLZkxppCIiL+IjBGRgyISJyKTRaRKDvUfF5FoT90tInJ/ccabwRIac85aRgYx7MqVNLiisduhGB/x5+TtxHW9guO1zke++w4JKut2SMaUJk8D1wIdgdqesvHZVRSRa4CXgP6qGgbcAYwRkV7FEWiWWKzLyRhT0hzdHcfmqx6h9ZRXKFu3mtvhGOP18tPlJCJ/AS+r6iee44bAViBCVf86re6jwA2qelGmskXAZFX9v0J7A3lgLTSm0Gz9eRN31p5B4oE4t0MxpdSBnUkcXrmTCrXDaL/qY0tmjMm7ABFZluk1JLtKIhIO1AWWZ5SpajRwDLggm0u+BMqLSBcR8RORbkBj4NfCfws5s+XQTKFJLxfKwkNN2PbHIVpcFeZ2OKYU+r37M3Tc+x0au8m6mYzJn1RVjcxDvYxf3kdPK48FymdT/wDwDTCbU40kD6vq2gJFeQ4soTGFpvEltdiYAH7W7meKSJtJTxO37ApqWDJjTFHJaGKvcFp5OE4rzemeB24F2gAbgObAjyKSmNFlVVzso8cUKj8/2PbbDn4dvsjtUEwpMv+x70jZfYCIjtVo/MBlbodjTKmlqrHATuDCjDIRaYDTOrM6m0vaAd+p6np1rAO+B/oUR7yZWUJjCt2of+7ljlcaE38s3e1QTCmwa+wvdH7jRqIfecftUIzxFWOBp0SkvoiUB14FpqnqjmzqLgT6ikgjABFpBvQl0xic4mIJjSl0wya15IhU4t337a+XOUcrV1LnsZtIjrqMZpNecDsaY3zFaGAK8AewB/AHBgCISH8Ric9UdwzwHTDDUz4Np4VmdLFGjE3bNkXk3nvh66/S2b46nvK1sxtHZkzOVv20i4YDOhFS/zxk3jwIs9apwcUAACAASURBVIHmxhSUrRRsTAE9+8QJ4o+c4O3+i90OxZRE8fFU/0cfEo77ceK7ny2ZMcbkyhIaUyTqNizD3b13838rexIb63Y0pkRJT4fbb6da3FYqzP+JwIiabkdkjCkBLKExReaZjxqSmOzHW2+5HYkpKVTh5wufh++/hwkTCOqY3TpexhhzJktoTJGpXRvuuT6GN0fEc3jjAbfDMSVAUkIaVfavYfWto6BvX7fDMcaUIDYo2BSpfesOc0nHBMZ9pnS4oa7b4RgvlnYiHf8yfmhqGuLvByJuh2RMqWGDgo05RzVaVGJDXB1LZkyOVv+8i61hbdj93R9IgL8lM8aYfLOExhQ5Edg5bQPfDZ3ldijGS4XXCOZQjVZUuqCO26EYY0oo63IyxeLpbguZtLg+W49WpUy5Mm6HY7xEYkI6fkePULZmZbdD8Snp6emkpaW5HYYpRP7+/vjlsJGeL3Q5WUJjisXR/YlImQDKV7ZkxpzyY+vn6LhlPOcdWIeEhbodjk9ISEjAz8+PgADbm7g0SU1NJT09nZCQ7HMWX0ho7G+0KRYVqgcDELMxBtF0Kjc7z+WIjOu+/ppr1rzC2ltHUM2SmWKRnp6On58fwcHBbodiClmZMmVITEw8+Wfsi3zzXRtXnEhKo03LE4y4ZY3boRiX7Z22Bh00CG64gZYTn3U7HJ+RlpZmLTOlmL+/v093JVpCY4pNmSB/7h6QzPuberB3r9vRGLfEbjtM8pV9iSnfAP77X5vRZEwhER//t+QVCY2I+IvIGBE5KCJxIjJZRKrkUP88EflcRA6JyDERWSkitj56CfDwWxEEBwujRvre2C0DpKURfv9t1Ao+TMCU7yHUupqMMYXDKxIa4GngWqAjUNtTNj67iiISBMwCUoAmQDjQH4jPrr7xLuHh8NjtfzP2vRPsmrfd7XBMMVKFfXc/B9OnE/jNJCpGNnQ7JFPCHTx4kKZNm5KYmOh2KEWqQ4cOrFu3zu0wvJ63JDRDgFdVdZuqHgWeBHqLSL1s6g7ESWLuV9UYVU1X1XWqeqw4AzYF9+Cw8oQGpvDK+5XcDsUUo7kvz6XGZ6P5+6GR0Lu32+GYUmD06NEMGjTo5CDn7t27ExQUxK5du07WmTlzJhERESePIyIiCA4OJjQ09ORr6NChpKamEhoaypIlS07WnThxIiJyRlnTpk259957T14fGBhImTJlTh5fccUVACQnJ/PMM89Qt25dgoODadSoEWPGjCHz7OK8xPz444/zwgsvFNrPrbRyPaERkXCgLrA8o0xVo4FjQHY7010CbAE+83Q5bRSRR/LwnCEiskxElqWmphZS9KYgylcL5okXQ/nkmwrs2OF2NKa4RA3rxqqnJ1HtjafcDsWUAsnJyXz++ecMGDAgS3lISAj/+te/crx2ypQpxMfHn3y98847BAQE0LlzZ+bNm3ey3rx582jatOkZZVFRUXzwwQcnr3/22We5+eabTx7/8ssvANx4443MmjWLqVOnEhcXx/jx4xk7diwPPfRQvmK+5pprmD17Nvv378/zz8cXuZ7QAGGer0dPK48FymdTvwpOUrMUqAEMAIaJSP+cHqKqY1U1UlUjbZS/+4YOhfDQE4y4caXboZgi9tfKI2z9bAF+AX5cMOoWGwRszioiIoJRo0bRvHlzKlasyJ133klSUlK2dZcsWUJ4eDi1a9fOUv7ggw8yadIkoqOj8/38qKioLMnL/Pnzeeqpp84oi4qKyvVes2bNYvr06UyePJmWLVsSEBBAp06dmDBhAu+++y5bt27Nc8xBQUG0a9eOadOm5fs9+RJvSGjiPF8rnFYejtNKk139Par6b1VNUdVlwAScMTimhAgNhacu+YMfVtQl/mDp7v/2dasGjKHi3deRHmeLWXqlvXth9epTxxs2cLLpNDUVli+HI0ec40OHnOP0dOd42zbYvPnUtStWwN9/O9/HxTl18zm+ZeLEiUybNo3o6Gg2b97MiBEjsq23Zs0amjRpckZ5rVq1+Mc//sHw4cPz9VxwEpqFCxeSnp5OTEwMCQkJ3HTTTSxduvRk2YYNG/KU0MyYMYOOHTtSp07W7Tw6duxI7dq1mTXr1FYweYm5WbNmrFq1Kt/vyZe4ntCoaiywE7gwo0xEGuC0zqzO5pKVQHZTZGzaTAnzwOcd2HIgnNCqtshXaXbpgpeI/34WfmGlepHSkmvs2KxjmgYOhIwkIjYWIiNh9mzn+KefnOOUFOf4mWfgvvtOXRsVBRMmON+vXOnUzWe/8tChQ6lTpw6VKlVi2LBhTJo0Kdt6sbGxhIWFZXvumWeeYcqUKWcdSNu3b1/Cw8NPvj766CPASTaOHz/OmjVrmD9/Pl27dqVcuXLUr1//ZFlERAR16+a+2W5MTAw1atTI9lyNGjWIiYnJV8xhYWHExsbm+lxf5i19L2OBp0RkNnAIeBWYpqo7sqn7mafuA8AHQEucWU5DiydUU1iCwwIIBo6s2UVSQjo1OmU3BtyUVItenEajzlWocnk7Qq5u5XY45myGDIHrrjt1/PnnkLGScHg4LFsGDRo4x1df7RwHBjrHo0Y5rTgZ5s2Dmp4VNNq0cepmGtyaF5lbNOrVq8fesyxaVbFiReLi4rI9V7VqVYYOHcoLL7zAfZkTLo/vv/+enj17nlEeFBREhw4dmDdvHtu2baNbt24AdO3a9WRZXlpnAKpUqcKWLVuyPbdv3z6qVMm6MkluMcfFxREeHp6nZ/sq11toPEYDU4A/gD2AP87YGESkv4icnJKtqn8BVwJ343RJfQO8qKr/K+6gzbnTdKVrZDJP37bT7VBMIUpeH03zl29m70Oj3Q7F5KZmTWjd+tRxs2ankpCAAGjXDipWdI4rV3aOM5bWb9AAGjc+dW3btlCtmvN9WJhTN5/bLGSe7bNz505q1sx+ibHWrVuzOXN312meeOIJZs+ezfLly89aJzsZ42jmz59/MqHp1q3bybK8JjQ9e/ZkyZIlWd4PcLKsR48e+Yp5w4YNXHBBdvNkTAavSGhUNU1VH1fVKqoapqrXqWqM59xEVQ09rf4cVW2rqiGq2khV33UncnOuxE94/30Y9Usbt0MxhSUxkbL9byCkTiUazx7rdjSmhHn33XfZvXs3hw8f5pVXXuHmm2/Otl6HDh2IjY1lz5492Z4PDw/nscce47XXXsvX86Oiopg9eza7du2iefPmAHTp0oU5c+awcuXKfCU0l156Kddffz3r1q0jLS2NxYsXM2DAAO677z4aNWqU55iTkpJYvnw5vXr1ytd78TVekdAY3xZ11/nUbBLGiYQUt0Mx5yg9HdZeMhTdsIGA7ycTVKOi2yGZEua2227jsssuo0GDBjRs2JDnnnsu23qBgYEMGjSICRljdrLx0EMP4e/vf0Z5nz59sqxD069fv5PnLrroIo4ePUrHjh1PbiVQpUoVqlatynnnnZdtInI2kydP5pJLLqF3796EhoYyYMAABg8ezNtvv52vmKdMmUL37t3P2lplHJJ5gR9fERISogkJNuPCm6ydsp3L+wbx67iDtOrfOvcLjFf6a/gn1Hv5bjY+/jFNxwx2OxxzmhMnTgDOzszeKCIigo8//jjb8S3ZOXjwIN26dWPFihWlegfxjh078sknn9CyZcsc6+X05ysix1W1VI/MtxYa4xUa96xLmdCyvDTBlsMvsVasoN6rD5B4212WzJhiUbVqVTZu3Fiqkxlwxt3klsyYfCQ0IlJWRAaJyPcislNE4j1ffxCRO0WkbFEGakq3wGB/nn+jEpN/DWGlrbVX4uxac4TYnjegzZoR/PE7bodjjPFBeepyEpG7gJE4Ww7MBNbgzDAqjzNtuhdwPvCsqv63yKItJNbl5J1OnICmEYm0CtrC99HW7VSS/Hb3RNp9OhT9Yxnh7ayVzVt5e5eTOTe+3uWU14RmEs7U6E051GkCDFfV2woxviJhCY33+vyffzDonfb8MSeByItL9b+9Uid+RwyhEVVyr2hcYwlN6WYJjQ0KNl4k9YTSvAU0aiT8/LPb0ZjczH5hNhV2r+PCTx6wPZpKAEtoSreSktB4hqjcCvTF2SWgEnAYWAF8D3yhqsn5va8NCjZeJaCMMHy4MHUqLB539kWzjHc4NmUOZX/+9tTePsYYkwPPEJa/gME4CczDOInNw8By4C5gh4jcme9759RCIyIXAm8BqcBoVZ3uKf9GVW/I78O8hbXQeLe0NGgZup0GFQ7z8/52bodjcqAKKXHJlC1vcwJKAmuhKd1KQgtNUQ5hyW0vp7eAe4AU4N8iEqGqY4HK+XmIMfnh7w/jJgVSvUULt0MxZzHz0lFEXFST8/810JIZY0yeqeqteaizCcj3eNzcupxUVTeoajRwDXCRiAzDdrY2Rax931rUaRREysGjTjOA8RrJU2fR47dhHPlzu9uhGB938OBBmjZtSmJiYrE8Lzk5maZNm3Lw4MFieZ7Jn1zH0IhIRQBVTVfVQUAN4KIijssYdizYTcNqccwZvdjtUEyG/fspe1d/6N6dyB+edzsa4+NGjx7NoEGDCA4OpkWLFie3MvD39ycoKOjk8ciRIwHYvXs3/fv3p3LlyoSEhNChQwd++uknAPbs2UNAQADR0dFnPKdfv348/vjjlC1blrvuuovRo23T1aIgIheLyBci8qWI5H/GtKqe9QU0ACpmU35xTtd5+6tcuXJqvF9aaro+0X2pbp6/3+1QjKomxqfquhqXamrl81T37nU7HFMAKSkpmpKS4nYYhSIpKUkrV66su3btOuPcxRdfrB999FGWskOHDmm9evV00KBBum/fPj1+/Lh+8cUXGhYWpl9//bWqql522WU6fPjwM64LDAzU1atXq6rqrl27tHLlypqUlFQ0b+wc5PTnCySoF3z+nu0FXAxMAoIBAUYA9+XnHjm20KjqNlU9kk353HxnTsbkk5+/8Nrs9jTqWs3tUAyQMGwkTff9RvRLE6BGDbfDMaVQREQEo0aNonnz5lSsWJE777yTpKSkbOsuWbKE8PBwateunad7v/nmm4SGhvLJJ59QvXp1goODufXWWxk2bBiPPfYYqsrAgQMZP358luu+/PJLmjdvTqtWrQCoXbs2FStWZPFiazkuZA8B9wLpQB9VfQ64MT83yPe0bRHpLCJTROQXEXlVRG4SkQb5vY8xeTXz/1ZyR705aJpNDXbNnDlUfvtFeOZZGj/Qy+1oTCHauxeWL8/5tX+/Uzc21jlOSXGOt23L/drY2PzFM3HiRKZNm0Z0dDSbN29mxIgR2dZbs2YNTZo0yfN9Z8yYwfXXX4+fX9aPvZtuuomdO3eyefNm+vXrR0xMDAsWLDh5fvz48QwcODDLNc2aNWPVqlX5eFcmD0JxdiAIBjK2P8/XAMqCrEMzAWcBnBnAecBzwCYROVyAexmTqzS/Mozf2Z2fvox3OxSftGPpAY5ceRupHbvg9/KLbodjCtnYsRAZmfNr3Din7vz5znFMjHP8zDO5Xzt/fv7iGTp0KHXq1KFSpUoMGzaMSZMmZVsvNjaWsLCwPN83JiaGGtm0LGaUxcTEEBwczI033sg4zxvesmULy5cv57bbsg7nCAsLIza/mZrJzSygv6rGquqdItIe2JWfG+Q2bTs7lYBBnj45AEQkGGhTgHsZk6vLHmlB1A8w7NXyXHUr+NlykMXq4Nz1+KWVw+/jSVQIKMivDOPNhgyBPn1yrlOrlvO1WzdYtgyqeHa4GDUKnnwy52sb5nNrrzp16pz8vl69euzduzfbehUrViQuLi7P961SpQr79u07ozyjrIrnTQ0cOJBrrrmG//znP4wfP57LL7+c8847L8s1cXFxhIeH5/nZJk9eB94XkZ5APFATuDs/NyjIb6epwAXAyT2RVTURWFSAexmTKxEYORK6doUvn17Jba9Z7lyc2j/RnfSHNuIXaMlMaVSzpvPKi/BwaJdprcsGRTDYYNeuU/8p37lzJzXPElzr1q15880383zfnj178u233zJ8+PAs3U5fffUVderUoXHjxgB07dqVSpUq8cMPPzBhwgRee+21M+61YcMGHnvssTw/2+ROVVOBf4hIeSBIVQ/k9x4F+b/uw8CrIhJVgGuNKZAuXeCqGn/ywjtV8SyGaYrYvJELWNp6MKlxiZbMmGLz7rvvsnv3bg4fPswrr7zCzTffnG29Dh06EBsby549e/J030ceeYSjR48yePBg9u/fT1JSEpMmTeKVV15hzJgxiGcvMhHhjjvu4KmnniI2NpY+pzVf7dmzh8OHD9OpU6dze6M+TETmi8gbInKriJyf+ZyqHitIMgMFS2ieBXoBc0TkiIjMFJHRIlJit0IwJcOIL88nOrEW//2v25H4hoQteyn79y78g2yZfFN8brvtNi677DIaNGhAw4YNee6557KtFxgYyKBBg5gwYUKe7lu5cmUWLFhAUlISzZs3p3LlyrzxxhuMHz/+jKTpjjvuYOfOndx8882ULZt1JewvvviCgQMHnlFu8qULcDUwBtgsIodFZLqIvCIifUUkb1PXTpPv3bZFJB64HKfLqQ3QDogELlTVlgUJorjZXk4l1y23wIJ5aWxZkUBwtfJuh1PqaboifraLdmnh7Xs5RURE8PHHH9OzZ8881T948CDdunVjxYoVBAcHF3F0zkrBF1xwAfPmzTtjXI03KAl7OQGIyP3AcOBzYCzQFGiPk0u0A6qqqn9+71uQFpp9wFJVTVDVhar6H1W9o6QkM6Zke/np4+zfp7w3cInboZRaM2/4gLWX/BPS0y2ZMV6tatWqbNy4sViSGYCyZcuyceNGr0xmShJVfQ9oCVTFmd0UpKrDVfUqVa0ORBTkvgVJaN7AWfzGmGLXuE05/nPfRi57voPboZRO69cT9f0jJBxOtulkxvgoEfEXkTEiclBE4kRksohUyaH+eSLyuYgcEpFjIrJSRHIcaq6qB1X1TqA/8Lyny6mR51y+pmufjKMAXU4HgTBgMvA98Ieq7ijIw91iXU6lRHq6fegWpuRk6NgREhPR5X8ioV7ROm0Kkbd3OZlzU1hdTp5NqAcCvYFDwKdAOVW9Ipu6QcAfwGLgGZx16poBu1T1WB6f548znuY+4CJVXZGX605XkE+Dm4BhnNprIdqTxf1akACMKYjVk9bRJWQFMauzX6PC5N+8rs+Svm49fPGFJTPG+LYhwKue7Y+OAk8CvUWkXjZ1BwLhwP2qGqPORtbrckpmRKS9iAwWkX+LyBzgb2AAMA84XtCg8zwXU0Taq+ofqjobmJ2pPAxnEM+FBQ3CmPyq3r4OFSpv58gROGs7qMmzlJ9nELXsDZZc9yodMy80YozxKSISDtQFlmeUqWq0iBzDWYPur9MuuQTYAnwmIr2Bg8CHqprTIkFLgLXAtzjDWFYUtJspS+x57XISkS1AEPADTlfTbFVNO9cA3GBdTsZkEhMDrVujTZvCjJmIv3XjlVbW5VS65dLllAKsyVQ0VlXHZlOvDrATaKCq2zOV/wUMU9UJp9WfCVyKs0bd+0Br4FfgIVWdmF2cIrIXqA7EAMs8r6XAclU9cznnPMrzby5VbQRcAewHXgUOiMh4EbleRMoVNABjzsWC91bz5pXT3Q6jxEpLVVZFDiY1IQkZN86SGWNKr1RVjcz0OiOZ8cjYT6LCaeXhOJtHZld/j6r+W1VTVHUZzp6P154tEFWtCdQG/gH8CXTEmcK9W0R2i8j3eX9bp+Trt5eqrlXVEaraDmcNmqXAA8B+EflRRO4SkUoFCcSYgvh9RgJP/tKDreuS3Q6lRIrZdIiQ/VtZ//BHULtAa1kZY0oRVY3FaaE5OYxERBoA5YHV2Vyykux3xc6x+0dV96rqD6r6nKperqqVgcbAE0B0QWLP9yynbG/iJDF9gL7AQlX9v3O+aRGyLqfS43hcGg0b+9GjhzAx28ZNk5u0pBO2GrCPKM1dTh9++CEbNmzgrbfecjuUIrN69Wruvfdefv/992zPF/Ispzs4NcvpEyBMVXtnU7cesAEnEfkAZ32ZmcBQVf1fXp5XWPLcQiMil4rI6U1QAKjqYVX9XFX7eXsyY0qXcmH+PP+8MGmSsmryVrfDKTHiDyWzsMldHFi4xZIZ4zUiIiIIDAwkJiYmS3nbtm0REXbs2JHtdSkpKYwYMYInnngCgB07diAiXHnllVnqDRgwgBdffBGAOXPm4OfnR2hoaJbXokWLmDRpEs2aNctyba9evbItGz16dJbr/fz8CA4OPnk80fM/rfXr13PNNddQoUIFwsLCuOSSS7IkJnmJuXXr1oSHhzNlypTcf5jnZjQwBWc69h7AH2cWEiLS37NjAACq+hdwJc7O2MeAb4AXz5bMiMhcEbk4p4eLSJRn9lO+5KfL6UfgsIhsFpEvROQREelm42eM2+4erDQI3M3T9+dpyQMD7Fy0h2rbF5Gw96jboRiTRf369Zk0adLJ4zVr1nD8eM4zeX/44QeaNm1KrVq1spQvWbLkrK0ZADVr1iQ+Pj7Lq3PnzkRFRbFx40YOHjwIQGpqKqtWrSIxMTFL2aJFi4iKispyfd26dZkyZcrJ4/79+xMdHU2XLl1o1aoV27dvZ+/evfTr14/LLruMRYsW5Svm/v378+GHH+b48zhXqpqmqo+rahVVDVPV61Q1xnNuoqqGnlZ/jqq2VdUQVW2kqu/mcPuRwHueXOI9ERkqInd4vr4nIptwBhePym/c+UloygNtcTK3o8BtwAzgqIisFRHbMtC4IrCsMHK0P78euJDffnM7mpKh+dUNiIhbS/0bI90OxZgsbr/9dsaNG3fy+PPPP+eOO+7I8ZpffvmFiy8+8z/9Tz75JMOGDct3DLVq1aJBgwbMmzcPgD///JMWLVpw8cUXZylLT0+nffv2ud7vxRdfpHPnzrzyyitUqlSJsLAwHnzwQW6//XaeeuqpfMXcvXt3Zs2aRXJyyRw3qKrTVLUF8E9P0QCcte0G4Kxv96CqtlDVafm9d35mOaWp6mpV/VRV71PV9jgrBt8GlMXpbzPGFTc8WJPISHjysTTSU1LdDsdr7VsTw4rGN3N8824CyuZ77zdTCu3dC6szDfXcsAEyenZSU2H5cjhyxDk+dMg5Tk93jrdtg82bT127YgX8/bfzfVycUzcxMX/xdOrUiWPHjrFhwwbS0tL48ssvGTBgQI7XrFmzhiZNmpxRfv/997N582ZmzpyZvyCAqKiok8nLvHnz6NatG127ds1S1qlTpzyNR5oxYwY33njjGeU33XQTCxcuJDHTDym3mGvVqkWZMmXYtGlTvt+TN/EkNveraidVbeL5el9BEpkMBZqjKSK1ROQRYD4wDtgM3FnQIIw5V35+8NrzcSxf6c9X989xOxzvpIr8427qR8/I94eMKb3GjoXemYZ6DhwII0Y438fGQmQkzPYspfrTT85xSopz/MwzcN99p66NioIJnlVKVq506p5l2EuOMlppZsyYQbNmzc7oSjpdbGwsYWFhZ5QHBwczbNgwnnvuuWyv27t3L+Hh4VleGRNGMrfGzJ8/n27dutGtW7csZdm1CmUnJiaGGjVqnFFeo0YN0tPTOXz4cJ5jBggLCyM2NjZPz/Yl+VkpuBpwI3ALzhbfs4EPge8807yMcdUl14TxRK+V1Lu6lduheKePPqL6kh848eU3lLnApmgbx5AhcN11p44//xwyNq8OD4dly6BBA+f46qud48BA53jUKKcVJ8O8eVDTsyVhmzZO3YiI/Md0++23ExUVxfbt23PtbgKoWLEicXFx2Z67++67GTNmTLYDaWvWrMnu3buzvS4qKorBgwdz5MgRFi9ezMSJEwkNDWXfvn0cOXKEBQsW8PDDD+fp/VSpUoV9+85cL27fvn34+flRsWJFDhw4kKeYAeLi4ggPD8/Ts31JnhMaYDdOS8zrQB9VPVI0IRlTcK9Nb+N2CF5p3eSNNB76MP53DabMzde7HY7xIjVrnkpCADJP5AkIgMw7YVSu7LwyZCQ6Gdq2PfV9WFjWa/OjXr161K9fn6lTp/LJJ5/kWr9169Zsztz3lUlgYCDDhw/n+eefp0WLFnmOoUGDBtSsWZOxY8dSt25dQkOdcbCdO3dm7NixxMfH06lTpzzdq2fPnnz99dfceWfWjoyvvvqKzp07U65c1rk1OcW8Z88eUlJSsu1i83X56XI6iLOD5mhgooi8LCJ9ROTMdjRjXLTpx030qzSXY9EH3Q7FO6SkUOWh29jrV5sTr5XeNTpM6fLJJ5/w22+/ERKS+9IpV155JXPnzj3r+dtvv52kpCR+/TV/eyh369aNN954g27dup0s69q1K2+88QaRkZEEZzRl5WL48OH8/vvvDBs2jMOHDxMXF8fbb7/NuHHjePXVV/MV89y5c+nRowdly5bN13vxBfkZFJzdUsWfcY5LFRtT2ILrVGFXWk12by7wpq2ly3PPUe3vNdSYNZGylUNzr2+MF2jYsCGRkXmbhdenTx82btzI3r17sz3v7+/Pyy+/nGWsCjhjaE5fh2by5Mknz1988cUcOHCArl27nizr1q0bBw4cICoqKs/vpVGjRixYsIBVq1YRERFBjRo1mDx5MtOmTaNLly75innixInce++9eX62LznnlYJFpCHQAYhU1ccKJaoiZisFl36qIOJ2FO5bNGIWnZ/v6Qx2ePppt8MxLivNKwWPHTuW9evXl/qVgu+5554z1q7JUFgrBRc1EdmWWx1VbZBbnTPuWxhbH5Q0ltD4hvU/bGHu5zu479tebofimtktHqDK3+touX8WEmDTtH1daU5oTIlKaNKB9cB/cTa8PsPZdurOSZ66nIpyqWJjisovEw4x9LsebPgjPvfKpVT3Ne9w/oafLJkxxniTTsAinAX1rgcOA194ViGeWJBkBvLYQiMilwNvAGVwNp1aj7NnQ3mgOXApkAo8ei6L4hQXa6HxDUnxqTRp7k/bC4XvfWyE19whE6nWJJymj13ldijGy3CacAAAIABJREFUi1gLTelWUlpoMohIKHArMASoirMJ5n9U/7+9+w6PqkofOP59Z9JIQgi9E0KQ3puAFBVsKIgiKqLYYVGsrOhaVlF0bbu6tlVWpCkqCjYUlfbDUKQjofdQQgKEhCSE1Dm/P2ZgQ0wgde6U9/M88yRzz7n3vnMIM++cc+49pkxrspRqyMmV2FyPc1nx6kAKsAH41hsSmTM0ofEfM2fCqFEQO3U3fe5qbnU4buHIN/xWdzgh9arRc/OFL3lV/kMTGt/mbQnNGSJiB54DngWuNMaUaREbnUOjfJrDAV2r7yEwP4vf09piK9O9sb1PbrYDR3YuwRF6aaf6H01ofJu3JTQi0hTnKt13AfHAf4HPjTFlWqiq1G/vIlJFRMaLyBQR+YeI9CjLiZVyB5sN/vV+CGtOtaXAAr4+K3bw6yR8toTAYJsmM0opjyQiN4nIL8BqIAy4yhhziTFmWlmTGShDD42IzAG6Aj8B9YErgK+B+4wxXrEqoPbQ+J+hQ2HdWsOODZmE1vaoLykVJuP7RYRfP5Dfh7xCz+/+ZnU4ygNpD41v85YemgJXOc0FsoqqY4x5pdTHLUNCkwa0McYccj2vC3wOxBpjni9tAFbQhMb/7NyWT9s2Dp6/ZCHPLrvG6nAqXnIydOhAXrOLsC/RS7RV0TSh8W1elND8H3C+5MMYYy4v7XFLs5bTGUeAs6toGWOSRORu4DfAKxIa5X9atLbz8q2baNmrjdWhVDhHvmFX//u56FQmAbNmgiYzyg999NFHbNu2zW031vvhhx/49NNP+fLLL91yPl9ijLm0Mo5blimSc/hz4nIE5yXcSnmsCZ935vqHo5y3EfYhSa9MoeWWb4gbNxkaN7Y6HKXKrGnTpgQFBXH8+PFztnfu3BkRYf/+/UXul5OTw6RJk3jiiSeIjY09u4xBWFgYInLO0gYHDhwAYN68efTo0YOwsDBq1qzJyJEjz668/eqrrxa5tMHx48cJCgpi8+bNDB48mC1btrBp06aKbQRVZmVJaB4AnhKRRSJyj+tS7inAxxUbmlIVL3lnMsPrLGXjlHVWh1Ixduyg/quPkD3ybjpOGm51NEqVW3R0NJ8XmMEfFxdHZub512X77rvvaNWqFQ0bNqRv375kZGSQkZHBli1bAEhNTT27rUmTJnz99dfcdtttPProoxw/fpwtW7YQHBxMnz59SElJ4fbbb2fFihXs27fvnPN88cUXtG/fnnbt2gEwYsQIJk+eXMEtoMqqLAnN1cA4YA8wFvgWuAXoKCL/FJG7RKRkK4op5WYRUdVJttUmKTXI6lDKLTM1h8SBIzH16hP8n39bHY5SFeKOO+5gxowZZ59Pnz6dUaNGnXef+fPn07//eW9mf5YxhvHjx/Pss89y2223UaVKFerVq8fHH39MeHg4b731Fo0aNeLyyy9n5syZ5+w7Y8aMc2K59NJL+fHHH0vx6lRlKvUcGmPM78DvZ567bojTFujsetwNdMB54z2lPEpgsI3FSW2tDqNCbP5wGe0PbWH/F0uJrlrV6nCUt0pIgCNHzl+nYUOoVw9SU2HPHmjfHoKCYO9eSEk5/74xMRAZWeJwevbsycyZM9m2bRstWrTgiy++YPny5Tz77LPF7hMXF8c115Rssv+OHTs4cOAAw4ef26Nps9kYNmwYv/76Ky+++CJ33nknL7zwAn//+9/P7rdx48ZzEpjWrVuzf/9+0tLSiIjQWRdWK8uk4HMYY/KBTa7H9HJHpJQbHNmYxNv3xfHSgl4EVfeIif+l1uOpyzlx/X6iW9e1OhTlzSZPhokTz1/ntddgwgSIjYUhQ+DwYWjQAP72N5g9+/z7fv89DB5cqpDO9NL079+f1q1b07Bhw/PWT01NpWoJk/oz83Pq16//p7L69eufLb/hhhsYO3YsK1asoHfv3syYMYNrrrmG2rVrn61/5pypqama0HiAcic0SnmjpAPZvLHuchq8dJBH/uVdCU3SthPsnzidHp8+TA1NZlR5jR594YTjTELRty+sXQu1ajmf/+MfzkTnfGJiSh3SHXfcQb9+/di3b98Fh5sAqlevTnp6eomOXcsV+5EjR4iOjj6n7MiRI2fLQ0NDGT58ODNmzKBXr1589tln/POf/zyn/plzRpaiB0pVHo9IaFzDVq/ivP1xCPArMMYYc/wC+40FPgCeM8ZMquw4le/oNKQJd9/l4IWpUYx8+n/vz95gw2u/0GP2JFKfvZnq7c7/zVWpC2rQwPkoichI6Nr1f8+bNauUkKKiooiOjuann35iypQLr0fWoUMHdu7cWaJjt2zZkkaNGvHVV18xoUAy5nA4mDNnDkOHDj277c4772To0KHceOONpKenM7hQ4rdt2zaaNm2qvTMewlNWtnkK56KXFwONXNtmFl8dRCQKGA/EVW5oyle9/A8b+fmGZ0fssTqUUrl62gjytu7SZEb5tClTprB48WLCwi7cgzpo0CCWLl1aouOKCG+++SaTJk1i1qxZZGVlkZiYyH333UdaWhqPPfbY2bp9+/YlMjKS0aNHc+uttxIUdO7FBEuXLi3x3B1V+TwloRkNvGaM2etaNnwCcLUraSnOFOAZ4IQ7AlS+p149eGHweiYvjGb9jxeYFOkBdvywk+0PvAMOB3Va1bA6HKUqVUxMDN26leyC2cGDB7N9+3YSEhJKVP+WW25h5syZvPXWW9SsWZM2bdpw+vRpli9fTs2aNc/WExFGjRpFfHx8kUNfn3/+OWPGjCnZC1KVzvLVtkUkEkgBOhtjNhbYfhK4wxjzfRH7jAEGGWOud91CeeGFhpxEZDTOxImgoKCu2dllXv9K+ZCcLAcd2+VRo24Qy5aBiNURFSMnh/hGvZGTqTQ89gf2CO+a96M8gy8vfTB58mS2bt3q1jsFz5w5k9kXmhTtRt6y9EFl8YSEpjFwAGhmjNlXYHs88Iwx5tNC9ZsAy4GexpjDJU1oCtK1nFRBCxbAlVfCp68nMPKJEs4lcLennsK8+SYnflhBzWt0gXtVNr6c0ChNaDxhyOnM1PRqhbZHAmlF1P8YmGSMOVypUSm/ccUVMLT1dp54UkhPKNmVEu608a0lmNdfRyZO1GRGKaWKYXkPDZztjZlojPnE9bwZzjsRRxtj9heqa3DOmzkTeDUgB1hvjOlbkvNpD40qbN/qY8yflcLoN1sQ4BHX/jmZ5BMcb9CBpKoxtEtaDHZdeFKVnfbQ+DZ/76HxlITmGWAUzmUVknFO+K1qjLm6iLqNCm36CogF/mmMSSrJ+TShUeeTn56JvWqo1WE4F9EcPhyzcCGpSzdRvWMTqyNSXk4TGt+Wk5ODiPhtQuMJQ07gvAfND8Aa4DBgB24HEJGRIpJxpqIx5lDBB5ANpJU0mVHqfCb1+5UbotZjHNYn+hsfmQpz5iAffaTJjKoQdrudvLw8q8NQlSQ/Px+7H/fiekQPjbtpD40qzncvb2bHH6f566yu2AKsy/ezM3JJimzJ0Vb96LZ5mmVxKN9z6tQpbDYbdrsd8djL+lRpGGPIz8/H4XAUe98ef+ih0YRGKQ91LC6R8DqhVKmrdyFVFcvhcJCfn291GKoC2e12bLbiv4T5Q0LjQdMflfIcf7/0N4LzTvHMMvffBfT3x76gw/grqd2+ntvPrfyDzWY774efUt5I/6KVKkK2rQov/n4Fu3a597wJW1K46O0HiXt8qntPrJRSXk6HnJQqwqlT0KYNtGgBv/7q3jsI71t2mKiL62EL9N/JfUqpiuUPQ07aQ6NUEcLC4N13YeFC+PKBki16Vx7GYVh/3wc4TqYT3aehJjNKKVVKmtAoVYwhQ+D6Jut5bEYnTp6s3HPtfmYqXaY8yLZ3F1TuiZRSykfpkJNS53FgXz6t29m55x5nj02l2LULOncmdeAwIr+dXkknUUr5Mx1yUsrPNYm288IL8MEHhnVTNlT48bPSc0m9biTUrUvkjMrKmJRSyvdpQqPUBTz6iKFNyF5efqniezN33Po84TvXk/jmpxCh95tRSqmy0vvQKHUBgUHCN0trUr9Vs4o98JIldJj/KknjXqTeDb0q9thKKeVndA6NUqUQ//M2giJCqN87ulzHObY9mWr9OhLUqhksWaKraCulKpXOoVFKnZWfk8+AIaE8e9fBch8rbtQbZB4/RdbHn2oyo5RSFUATGqVKyB5kZ9Zn8K/YHuU+Vp/FL5L81RJCWugq2kopzyIidhF5Q0SOiUi6iMwRkVol2G+siBgRedYdcf7p/DrkpFTpHdmYRHCQoUab0q23tPunnYSQRaNBHSopMqWU+rPSDDmJyDPAncDVQDLwCRBqjCl2cTsRiQIWAZnAbGPMpPJHXTraQ6NUKeVmO+jVPY/HB5d+oaeD900ka/jtmHxHJUSmlFIVYjTwmjFmrzHmJDABuNqVtBRnCvAMcMIdARZFExqlSikw2MbTj2cxfW9ffv21dPt2WvsxAd9/g9j1v55Syq0CRGRtgcfooiqJSCTQBFh3ZpsxZg+QBnQsZp8xwCljzJeVEHeJ6WXbSpXBff+IYdYqGDPaQdzydMIbVjtv/a2Tl9GoSx2qd2tB9QYxbopSKaXOyjPGdCtBvaqun4UXfEkF/nSzLBFpAjwL9CxfeOWnXxOVKgObDSZ/6ODIgVyeu2r1eevmJRyl9gM3sXfYX90UnVJKlVm662fhb2mROHtpCvsYmGSMOVypUZWAJjRKlVGLVjZeuGMv/946kFWriqlkDAGj76FGRB6Nvv+PW+NTSqnSMsakAgeALme2iUgznL0zm4rY5QrgFRE5LiLHgUuAv4lIrDviLUivclKqHHJz4eKLISvLsC72NFVqhp5Tvuex94h5+yH49lu4/nqLolRK+bsyXOU0iv9d5TQFqGqMubqIuo0KbfoKiAX+aYxJKl/UpaM9NEqVQ2AgTJ9m2L09j+cuPfcLyYmlcTR8+69s7D1WkxmllDd5FfgBWAMcBuzA7QAiMlJEMs5UNMYcKvgAsoE0dyczoD00SlWIt+/cQJVaYYz5ZwvnhtOnoXt3TmcabOvWEFw99PwHUEqpSuQPSx9oQqNUBTPZOSSMeJwGP32MrF4NHfQmekopa/lDQqOXbStVgZ7q/DOOxEReT3yfbWPeprUmM0op5Raa0ChVgZp0qU12Vi02dVtI+0cutzocpZTyG5rQKFVBcjLz6N/mGG3HOy8EcC5vINYGpZRSfkKvclKqgvz28Ne0+uu1JMXu5KUrfuMvFy0EP5yjppRSVtCERqkKctmHt7B56lrq9m1B7ehwJu+7km+/0YRGKaXcQa9yUqqcEjcdJTt2NVEPXnd2mzEwZAisXAmb/jA0aKhDT0op6/jDVU6a0ChVHg4HW5pcQ70jG6h2fA8B1aueLTp6FDq0yKK9bTO/JHTAFhJkYaBKKX/mDwmNDjkpVR5vvEHbw7+S9u70c5IZgDp1YNoL+1mY0o233rIoPqWU8hPaQ6NUGe2YtpIW9/VFHnsM3nij2HqPPgoffACrVxk6ddahJ6WU+/lDD40mNEqVgTmRwpH6nckIq0uLxFgIKn44KSsLLm5/ipxDx1i3uxqhDau7MVKllPKPhEaHnJQqLWOQ+++jXnAKVed9cd5kBiAkBGZ9cBJboI2De3PdFKRSSvkXvbGeUqW047EPaTl3LrbZs6nfO7pE+7S9ogFxqWCz4bwESnToSSmlKpL20ChVCqkH0qj776dZ330MDB9eqn1tNkhcd5ghNZax76dtlRShUkr5J+2hUaoUIptEsHvub7S9rHmZ9g+uV51kW22OpgRQsr4dpZRSJaGTgpUqAUe+Ye2DU+n29u3lvp/MmREnk+9AbKLDT0qpSqeTgpVSAGz4ZAOdPxrDtg+XlvtYInAqJYdr669jztiFFRCdUkop7aFRqoT2LI4n5vKoCjmWMTCsZRyLDrdi/aZAYmIq5LBKKVUk7aFRys8d3XqcuFGvQ35+hSUz4Oyl+WR1e2rUCeTmmyE7M7/Cjq2UUv5IExqliuNwkDH0dhp++hrpu5Mq/PCRkTB7NsRtzOORdouc3TZKKaXKRBMapYrz8ss02/ULeVM/pWrLBpVyiu7d4Z17N/HRviv5+ONKOYVSSvkFvWxbqSJseHMRnZ5/HnnmGerceU2lnmvMR11Y64AHxwntm2dy8WWhlXo+pZTyRTopWKnCEhJIie7Mgapt6Zi0AOz2Sj9lVhb075jC4d2nWbcqn7rdGlf6OZVS/kMnBSvlb3Jy4OabiaxhI2rZLLckM+Bc72nO19C3TTL2BnXdck6llPIl2kOjVAHr+zxE51UfIkuWQJ8+lsWRviuRqs3r6k33lFIVQntolPIjKXtOUOf371k5/C1Lk5nEuGO0aulg1v2LLYtBKaW8jU4KVsqlekwNAuLj6FW/qqVx1G1XmweGrqP/Y10tjUMppbyJ9tAov3d8RzKrWtxO+u4kqjaMcK6vZCEReGZuVxq2jeTEnhTiF+6yNB6llPIGmtAovxf/Wzw19q8nLTHT6lD+5LZL4hl0nY2Tqf43100ppUpDJwUr/+Za+jo320FgsOfl91sXHaHX0Dr0usTOvHkQoIPESqky0EnBSvmw5Y/PYVvzweSnZ3pkMgPQZkB9Zn9tZ+FCw2NXbdXlEZRSqhie+S6uVGXbto3uH9xFem4wtrAqVkdzXlddBe88sIP3Frfh3QkHrQ5HKaU8kg45Kb9jkk8gPS+GwEDM76uQCGuvaiqpR+9J451pEXz1FQwbZnU0SilvokNObiIidhF5Q0SOiUi6iMwRkVrF1B0kIotF5LiIpIhIrIj0dXfMyjvlns5jQ8tbyD6SDN9/7zXJDMA//xvBTTfByFvziH0l1upwlFLKo3hEQgM8BVwPXAw0cm2bWUzd6sC7QHOgNjALmC8iuviNuiDbXx+n44klbJv4FTRvbnU4pWK3w4zphp6R23l/ZoTV4SillEfxiCEnEYkHXjTGTHE9jwF2A02NMfEl2D8ReMAYM7ck59MhJ/+U8/5/CRo3Gt59F8aNszqcMks7kUeVcDuBQQL5+W5bb0op5b10yMkNRCQSaAKsO7PNGLMHSAM6lmD/9kAtIO4C9UaLyFoRWZuXl1e+oJXX2fjeMmTcA6TcPBoefNDqcMolokYAgUHCuo83MKDaGlK2HrE6JKWUspzlCQ1wZhLDyULbU4Hz9quLSB1gDvCmMea8t1M1xkw2xnQzxnQL0Jt5+J1GA1qyotsjhH/yrs8s+BjStB4BEWHkVfGeeUBKKVVZLB9ycvXQpACdjTEbC2w/CdxhjPm+mP0aAAuAJcBDphQvRIec/EdaQgaSecq5crUPS9x0lMi6wYTUrWZ1KEopD6RDTm5gjEkFDgBdzmwTkWY4e2c2FbWPiDQFYoH5xphxpUlmlH9Z1+8xjne4DJOXb3UolSY/zzCwZzo3d95Fbq7V0SillDUsT2hcJgNPiki0iEQArwG/GGP2F64oIq2AZcDnxpi/ujdM5W0afvgcyX9/Bwnw3Ymz9gDhtZdymX+sK6NGOecJK6WUv/GUhOZV4AdgDXAYsAO3A4jISBHJKFD3SaAh8KiIZBR4jHR30MpzbZ70LXnHU2kxsAndnhpodTiV7trxrfjsM2H2bMOY3nE4srWrRinlXyyfQ2MFnUPj245+Mo+a917P+hsm0X3u36wOx62mPbubu19uzoM3JfHu7Lq+Mv9ZKVVO/jCHRhMa5VvWr4d+/UjpfDkRi77BHuS7Q03F+fD1NMY+GcHYsfDeOw5sAZ7SEauUsoo/JDT6Tqd8xqGVB8kccB20bEn1+bP8MpkB+MuECCZPhv/8B/7SfCGOHL3vklKq5Lx1OSJNaJRvSEsj6MZrSUkP4NSX8yA83OqILHX//TDloQ0kV2lIPv6Z2CmlyswrlyPSISfl/XJyYPBgzMqVpM5bTvV+7a2OyGMY47yP4O5vNxN9RXPsYSFWh6SUskBphpzcvRxRRdEeGuXVHHkOVrW9G8fiJcjcuZrMFCICaYfT6XVjPV65drnV4SilrBNwZvkf12N0UZXctRxRZdA1AJRXO33iNIHJiax+cAY9B/r+5dllEdGwKtPfPEyvm3taHYpSyjp5xphuJajnluWIKoMOOSmvlXU8g5Ba4Zh8B2LXzsaSOLgmkfFDdvHhr82o0b6h1eEopdykpENOVixHVFH0U0B5pd8e+IKT9VuSsiVBk5lSOHogi0XHO9B/eG0SEqyORinlabx5OSL9JFBeqeFt/dncZyyRretbHYpX6TqsKbEbI0jJCOKS3g52/bjT6pCUUp7HK5cj0oRGeZXdX64lJ+E4MX3qM2DJs4hNb4VbWm3aCsuXQ1B6Mj0H12LZr5lWh6SU8ixeuRyRzqFRXuPU0rXkXzaA3R2G0WXjJ1aH4/WSD5zihsF5rNpejWlTDSNu0+RQKV+ldwpWylPExRF241XQqhUX/fi21dH4hJpNwliwuhrDh8NtI4VJveZhHP73BUcp5Rv0sm3l8fbO30G9WwYSGt2IiCXzocZ5rxxUpRAcDDNnQsyJNWw51BSDoP00SilvpENOyrPt20d6p74cywqn3o7fCG1ax+qIfJbDATYbxL62gov6N6Bez6ZWh6SUqiD+MOSkCY3yWI4Dh7Bd2g8DnJofS3hLvW9KZcvPyadtxAF6RyXwyY5LrA5HKVVB/CGh0SEn5ZGS/kgk6+LLqRuRS8iq3wiP1mTGHexBdhauiSS8Zl0Ajm06Qu329ZxrKCillAfTScHKI0U0rsahhj1JmrUYoqOtDsevNGpfncgGoSTHZ9CucwAP9VxDbq7VUSml1PnpkJPyKIeWx2PPzqT+5a2tDsXvGQPv3buBx2Z0ont34YtZDqKi9TuQUt7IH4ac9N1JeZQDQ8aRcuM9zk9TZSkReOiTzixdKhw6aOh8UQbfPakrdiulPJP20CiPsn/1UQLzTtOwd5TVoagCkg9mclefXcw70JFHH4XXXoOgIKujUkqVlPbQKOUGu3/YxuZGV5F98ChNe9TRZMYD1Wwcyvf7O/Lmm/Dee4Y+jePZ88NWq8NSSqmzNKFR1lqzhia396VK8iHST+jMU08mAuPHw7IfUjmWEsCP8/yvd1cp5bl0yElZJmHmIho8MBTatMEx7ydstWtaHZIqofSUPMKqBWCzwcyRP3PFQ630RnxKeTAdclKqkiS8/w01Rw0iMbonLFqkyYyXqVrdmcykHTzJhC+7MOPVBKtDUkr5OU1olPt98gkNHr6JpB6Dqb5sHoSHWx2RKqOIxtXYtCuUx2f3BGD2I8tJWh1vcVRKKX+kCY1yG+MwLOn3PNx7L9xzD01WfElwRLDVYalyqh0dTkCQjVMpOTz8fgta96/N1Kl65b1Syr00oVFuk5+TT/j2NSy7+iWYPBnsdqtDUhUorHoQm3aEcM2QIO65B67ofJw932+xOiyllJ/QScGq0qXuSyFt8wGaDO5Ifk4+9iBNZHzd/J8Mf7kxiaN5NXh2YhDjx0NIiNVRKeW/dFKwUhVgQ/9Hcdx8CyZPkxl/cc0gYUtCDcaOcfD889A25jTfP7IIk++wOjSllI/SHhpVaRyZWdhCQ4hfc5T8YydoNqiV1SEpC2zdCg8P2s3uxDC2n6hLSKh+j1LK3bSHRqmyMIaVI97hSK125CYmE9W9jiYzfqxNG1iwrzkrt1QjJNRG/OI9PNH+Z07uT7E6NKWUD9GERlWsrCy45x56ffEIe1pei1SLsDoi5QFEoH5MKABrF6Qwd2c7bGFVAHDk5lsZmlLKR+iQk6owCasPwbBh1D/2B/Lhh3DXXVaHpDxUXq4hIFBI2p5Cvw4pPDEui7teb0NAgNWRKeWbdMhJqZL66SdqDOiEJBzmxDe/aTKjzisgUADIzTF0apLC/W+1oV07+OzNBPIysiyOTinljTShUeWSm5nL/psnwLXXEtKnO1V3b6DmNT2sDkt5iUYdavDl7q6sXg3R0Ybbn2hAmwapTJ8OeXlWR6eU8iaa0KhyWTl6Ko2++hcn//Yq/Pgj4dG1rQ5JeaHu3WH+fGHVl/tp2TWcu+6Clk2zmHLzL+Rm6irsSqkL0zk0qtSMgYO/bKXJ1W3Iz8ln15xNtBrR2eqwlA9Zvx5eums3sVtrEp9SjbCqNnKS0wmqWdXq0JTySjqHRqkiLL7/c+pf05GkZbuwB9k1mVEVrksX+GZTc3YcCCWsqo0T25JoXPs0P/59ldWhKaU8lF5ToEosNe4gke0b0+O1YayuXoXevZtbHZLycTUbOBcvldAq3H/ZFrqOcN7PaPZjK4mMhIHP9cKmX8uUUuiQkyqJEyfYet0Emq38lJx1m4nooomMstYV9TaxMKkDzZrBmNEO7r7qCLU7NbQ6LKU8lg45Kb9mHIb0j2ZB69a02vwVq299i/AOzawOSyl+PdKB3xZk07MnPPccNOxcmxGDUlm8GBy6XJRSfkl7aFTR9u1j22VjaR3/C+aGG5F334GG+g1YeZ5j+zKY9vROPlrTmT17hEZhJ3j40jiemNff6tCU8hjaQ6P8TkZiBumPPQdt2hCTtYVVT3+HzJ2jyYzyWLWjw3ni8y7s2iXExsI1zXeTaXdeDXV0YwJvD/qVtIMnLY5SKVXZtIdGnWUMbI7oTavMdQROeByefhqq6mWyynt99/Qqbv1HBw7ty6Nm06osfnM9F3WPpHF/HTpV/sUfemg0oVFseOv/aHJZDDU7NeaP92Kp3q4hTS7VN3zlG9KPZ1O1VjDGQNPgBA7kNqBHD7hpaB5D2+zkoiGtnatnKuXDNKHxUZrQ/E9KwmlyGzZl7+X30XPRy1aHo1SlSk3I5Idv8pizIIKff8onO9dO8ybZDBoazDWdjtB/UBhV6uoK8cr3aELjo/w9oYmfu45j4/9Bx9j3CWxUl10/7yFmYDS2AJ1SpfxHRnI2C9/fwU8H2/PTfOHwYegUvpsN6c3BGHZ9v43m17ZEAuxWh6pUuWlC46P8MaExDkPGNwuo+p+dhYwkAAARvElEQVTXYdEi4gNjkM8/p8mw7laHppTljIG4nw5y9EAWA8dexKHYfTTuF83XT65h2Kvd2b0oHpN52png2HR4SnkfTWh8lF8lNDk58PXXxI97naiUP6BTJ5gwgfwbh2MP1htFK1WUrJPZLPlwBz1vbUr1qAjua7eSKVt60bChoX9/oVfAGnoOqkHHG2MIDLQ6WqUuTBMaH+UPCc3J+FQ23PoafXZ9QkDyUU50Hci+mybQ9cmBOgFSqVJKPXyK2G+Ps2RPFMtiDRvW5pFHICEh0K1tJr0cK3hoSicad65ldahKFUkTGh/lqwlNVmoWB77fSItRPck8nsmJem3IvvI6Yl4bA+3bWx2eUj7jdFou61fnsXJjFVZ+d5SVKw3L1ofRrEM4T/dYwNGTwXy8ox8AO+fvIebSxtirBFkctfJnmtD4KF9KaPKy8jBZ2QRGhjG//6v0/+1FglKPEVAtjPycfOxBOqFRqcp25m1UBKbcvYwTqTae+KY3yQczqdUklCqBuXToEkib+im0yVpH6/v60KZLCFFNDDa79piqyqcJjY/y9oTGnMpEFi0kZ+4PpM78gcTrx9Bh7kQOrT9KdkIyMde1tjpEpRSQnZHLbx9tY0NKUzbujWDbyhR27A/mNKEAVLFnc3XDOObGdwPgq4d+4+IRzWjSu5GVYSsfpAmNj/K2hMY4DGbbdmxLl7Drnfk02bWQYEcWxMSwtv5gqj8yipibOlsdplKqBBz5hvgDwrZtsG3WBoID8hk3rRunDqcS3iiSqWN+564Pe/LlE2t55d1wYq6IoVnLQJrl7SSqbhaNr+1Ao0ZQPdLoFVeqxDSh8VGentDkZuaSfiCFGq3qsH/BLkKv7ksdRxLY7Zxo1Yu4qMH0e2Mw0rqVTvBVyoekHj5FQJCN8NpVWPbfbcx85wR76vZm714hfl8+Dv43hFyFTCbetJknvurBrvm7mTrxAI9/2oVazSPZ99tB8nMd1OkeRdWq+jah/COh8Yg7qYmIXUTeEJFjIpIuInNEpNjLBUTkahHZIiKnRWSziFzpzngr1KlTJP60njXjpkN2NgCrGg/j4OV3AtCgVxRbe9xNwpT5kJJCjc2x9P9xAtJGb9eulK+JbBhGeO0qAPS5vzUfxV3CwoXC3r2QdRrit2SwfDl8+Vkek4auo9e1NQA4EHeSmWtbYcT5lj5hVCIXDYyiWjUIDYWo4CN0j0riuuvgnlsyeKrHYnYvTwJg9697iX1349kYMo+dwuQ73PzKlSfx1s9kj+ihEZFngDuBq4Fk4BMg1BhzTRF1mwGbgdHAbGA4MBloa4zZX5LzWdFDs/u7LQTs3UlT+0Gyt+4h7uvttLNvI+TowbN10n/bQNW+nVjz9nLCqtpoc28vt8aolPINu5ceZv+ObI6GN+PoUUias8z5e0ADkvae4ujOFD6d7qDPbU14rvcipqxuR0JeXQBigg8Sn9uA6jXtVI/Io3ridiLbNSS8UXWqnkqk6uHtvLysPxHVhJ8nrsKIjWv+3h2HA1b85w/CWzUiPKomofZsQvJPEVIvkpBQGzaP+Prsv0rTQ+Puz+SK4ikJTTzwojFmiut5DLAbaGqMiS9UdyJwuTGmb4FtscBCY8zEkpwvLDTMZKSmIsZBTpYDR56DkCAHOBycTHEQFBZIldrh5GTmkbLzGDWa1yAwPJijmxJJ23qI5vVPQWYmG1dkEhGYSbPaGWQeTGbNz8k0feR6ou68lKVPzafZv8bRKHUzElqFtbWuplvyLxAYiImKYm1Ga+pe1pomV7QiM6o1uTGtqBYVWWFtqpRSJXHyUDon4tOJvqQBAHP+tpYjubVIqdaUlMOZpCzeQGrj9mTYIsiIP076wZOsSIohIgJuqLeSXAKZl9iNtJR8qtUo/qrKIFseTYKOsOt0YwAG1VrFgD7ZjP+2HzsWH+bxWw8T0rEVIXUiCDx6iMCEAwRd2pvAQAjcspGW0dncN/liHNm5vDF0GYPGNKH90Bh2LDzIspn7COzXk8DQIAIP7CEwP4uAjm2x28EW9wdRnWvQcmBjMo6ks3HuXjreGEPV+uEcWpvI0T3p2FpehM0G9oSD2KoEY6tXBzv52BITqNWiBhH1wzidnMnJwxnUaVsbm11IO5RGbi4QEYEIyMlUCAlBqoRAXh6SeYqwuuEEBNvJTssm93Qe4XWd+UTm8UyMzY6EBIMxSHYWBAU5l9nIz0cc+QSFBSI2IT8nHwB7kB1jcPaeiZydP1XSjvpSJjRu/UyuMMYYSx9AJGCAToW2nwSGFFH/W+DtQtv+Dcwt6Tm7Oq+yLPaxsdu9xhhj1n++3Rgwuz9eYowxZsklzxS9j4jJr1HT7A1sYbY8Nd0YY8yG6X+YJV3Hm+yjqcYYYw7G7jPH4o4Yk59vlFLKV+Tl5J/9ufm73eb3X1LNggXGfD8t2cx+fIWZ/nG2+egjY94eu928P+r3s/tN7L/IfPP0amOMMVsXHDKD664yV/TOMH37GtMzJsl0Cd9h2rc3plUrY2LCj5iRrdYYY4zJOpZmIkg1nz7kPNZ/7191vrdzA8aM6+k8z4ZP4wwY8/v07cYYY8b3Wn7Bfd+/f4MxxphZf1lqwJiTSaeNMcYMqr/ugvsunrrfGGPMc70Xmgb2I2dfe3TgwQvue8RV/aYGy8yAmuudrz3r/PuAMZG21LPnaRe03YzrFGuMMQY4ZTz0M7miHpb30IhIY+AA0MwYs6/A9njgGWPMp4XqLwKWGWOeL7BtInCJMWbgec4zGmeXGEBXILPiXoUqQgCQZ3UQPk7buPJpG7uHtnPlCwXWFXg+2RgzuXAld30mVwZPWMwn3fWzWqHtkUBaMfVLWvcs1z/cZAARWWuM6Vb6UFVJaRtXPm3jyqdt7B7azpWvFG3sls/kymD5NC1jTCrObLDLmW2uSUYRwKYidvmjYF2Xzq7tSimllCojb/5MtjyhcZkMPCki0SISAbwG/GKKniE9A+gmIiNEJFBERuAcQpruvnCVUkopn+WVn8mektC8CvwArAEOA3bgdgARGSkiGWcqGmP2ADcCz+Ls0noWuKGYhi7On8YNVYXTNq582saVT9vYPbSdK19p2tjdn8kVwvJJwUoppZRS5eUpPTRKKaWUUmWmCY1SSimlvJ4mNEoppZTyeprQKKWUUsrr+U1CU9rVQxWIyK0iEisiaSLyp7t4XmiFVRFpLiILReSUiBwSkfGFykNF5BMRSXU9pohIlcp+XZ5ERF5ztWGaiCSIyH9FpEahOqNEZI+IZIrIKhHpWqi8m4isdpXvEZHbC5XXEZG5rr/7Y65z+s3/fQAReVlE9rna+aiIfC0iTQqUaxtXEBGxicgKETEi0qjAdm3jchKRaSKSKyIZBR4PFKrjv+3s7rUWrHoAzwA7gWY472o4B5hvdVye/ACuAkYA9wB5hcqa4Vw+4nYgCBgJnMK5eBk4L/PbBryL85bbXYCjwC0FjvFfYAVQF6jj+v0/Vr9uN7fxKzhvQhUI1AbmA98XKO/jatcrgWBgApAERLjKqwHHgCdd5VcAGUCvAsdYAMx11W3m+n/wpNWv3c3t3Aqo5vo9FPgXsELbuFLaejywEOd6QI20jSu0bacBH5+n3K/b2fIA3PiHEA/cW+B5jOs/XJTVsXn6A7iUPyc0E4HYQttigeddv1+GM+EJL1D+ErDE9XsV4DQwoED5ANc+IVa/Zgvb+mogrcDz6cDMAs8F510873Q9v9v1ty0F6swEprp+j3b9nccUKL8X2Gf1a7WwjcOAN4FkbeMKb9sWwB6gE+cmNNrGFdO+0zh/QuPX7ewd3UjlJCKRQBMKLMxlnDcDSgM6WhWXl+vIuQudAaznf+3ZEdhpjMkoprwlEFLoGOtxJjotKjxa7zGAc28Zfk47G+c7zAbObecNru1nFP53OOn6ey9Y3tR1B1C/ISK3ichJnN9IHwFecBVpG1cA17DEJ8BfgdRCxdrGFWeYiJwQkZ2uaRThBcr8up39IqEBqrp+niy0PRXn+hSq9Kpy/vYsSTmF6pz53S//TURkGPAXnB+2Z1REOxdVDn7WzsaYWcaYakB9nMlMnKtI27hiPAIkGmO+KaJM27hivItz+LQWcAPQH+fQ/Rl+3c7+ktCUdvVQdWEXWmG1JOUUqnPmd7/7NxGR4TjfmIYYY9YXKKqIdi6q/EyZ3zHGJOJs63muCdjaxuUkIs1xzp0ZV0wVbeMKYIxZZ4xJMsY4jDFbgMeAm0Qk2FXFr9vZLxIaU/rVQ9WFXWiF1T+AFiISVkz5DiCr0DE645xXs7PCo/VgInI38BEw2BizpFDxOe0sIoJzfkLBdu5UaJ/C/w7VXH/vBcv3G2MKfxPzJwE459I0QNu4IvTBOal9s4gcxzlMAbDJdRWOtnHlcLh+iuunf7ez1ZN43PXAeZXTDpyTniKAr4CfrY7Lkx84r1QKwTljPs/1ewjO/zwxOCfwjsB5hc4Iir7K6d8458V0wjnb/tYCx/8vsAznFU51XL9/aPXrdnMbPwwkA92LKe+Dc87HAJxXk/2Vc69aiMR51cITrvIBFH3Vwteuv/to1/+Dp6x+7W5sYxvOnoM6rueNgG+AfTgTG23j8rdxqKtdzzx64pxc2g0I1zausHa+FYh0/X4RzitD5xQo9+t2tjwAN/4h2HFe2XAcZ9fZXKCW1XF58gO4y/WmVPjR1FV+NbAFZ6/KFuDKQvs3BxbhTHwSgL8WKg/DOYkw1fWYAlSx+nW7uY0NkOt6Uzn7KFRnFLDX1c6rga6Fyru7tp921bu9UHkd1997uuvv/3XAZvVrd2Mb24CfcN424BTO1YM/49wrObSNK7bNm1LgKidt4wpr1/8DTrj+jvfhvP1ARKE6ftvOutq2UkoppbyeX8yhUUoppZRv04RGKaWUUl5PExqllFJKeT1NaJRSSinl9TShUUoppZTX04RGKaWUUl5PExqlVKmISBMRyRCRBuU4hojIChEZ4Hp+qYjkVVyUICIrzxxfKeX7NKFRys+IyP+JSLYrKTkpIhtda0mViDHmgDEm3BiTUI4wbgbyjDGLynGMC3kBeKsSj6+U8iCa0Cjln14yxoQDNYFpwCzXAoPu8ijnrhJcGRYA1UXk8ko+j1LKA2hCo5QfM8bk4UwsAiiwaJ2ITBWRgyKSLiJbReS2AmVNRcSISKMC28aKyA5Xj8/vItK3uHOKSF2ca/0sOE+dbq7z3+96/n8i8i8R+cYV0x4RGSAiA0Vks4ikucqqFnhtDpxLbwwtU+MopbyKJjRK+TERCQLGup4WXOV8Gc4EJxJ4EZgmIm2KOcYI4CWca8jUxJkg/SwiUcWctguQYoxJLOZ4Q4B5wP3GmIK9OHcAr7pi+hKYCYwG+uFcO6glzsU+C4rjz6vCK6V8kCY0SvmnZ0QkFecCdZOA+4wxm84UGmOmGGOSjTH5xpgvgE3ApcUc627gI2PMKmNMnjFmiqv+bcXUrw6kFVUgIg8D7wFXG2N+LlQ823WOfOBToD7whjHmhDHmBM4kqFuhfdKAGsXEoZTyIZrQKOWfXjbGRAK1cK5EfdmZAhGxiciLBYaQUoGOQO1ijtUY58q/Be1xbS9KChBRxHYb8Aww1RizsYjyIwV+zyxmW1XOFYFzdWKllI/ThEYpP2aMSQHuA64Vketdm0e4tg0DqrsSnz8AKeYwB3EO+RTUzLW9KBtwTtatV2i7A+gP3CMifyvN6ziPdq7zKaV8nCY0Svk513DNv4BXRMSGs1cjDzgG2ETkHpw9NMWZBowRkR4iEiAid+OcfzOrmPMlAquAgUWUbQf6AveJyD/K/qqcPU3AAODb8hxHKeUdNKFRSgH8G+eclFHAdJwJx27gMNAGiC1uR2PMLGAiznktyTgnGQ8yxsSf53xv4+wFKup4+3EmNUNE5AMRKa5n6EIGAicr+V43SikPIcYYq2NQSvkZV5KyAnjGGLO4ks6xAvi7MWZhZRxfKeVZNKFRSimllNfTISellFJKeT1NaJRSSinl9TShUUoppZTX04RGKaWUUl5PExqllFJKeT1NaJRSSinl9TShUUoppZTX04RGKaWUUl7v/wERZn0j5lcCtwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZBT_vODttdJI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        },
        "outputId": "e2f286de-16c8-4422-87a4-27ece637fa54"
      },
      "source": [
        "plt.figure(figsize = (8,6))\n",
        "plt.plot(WD_21_NEWTON['R (km)'],WD_21_NEWTON['m (Msol)'],color ='red',label =r'p(0) = $10^{21}$ (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_22_NEWTON['R (km)'],WD_22_NEWTON['m (Msol)'],color ='blue',label =r'p(0) = $10^{22}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_23_NEWTON['R (km)'],WD_23_NEWTON['m (Msol)'],color ='green',label =r'p(0) = $10^{23}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_24_NEWTON['R (km)'],WD_24_NEWTON['m (Msol)'],color ='brown',label =r'p(0) = $10^{24}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_25_NEWTON['R (km)'],WD_25_NEWTON['m (Msol)'],color ='grey',label =r'p(0) = $10^{25}$  (NEWTON)', linestyle='-')\n",
        "\n",
        "plt.plot(WD_21_TOV['R (km)'],WD_21_TOV['m (Msol)'],color ='red',label =r'p(0) = $10^{21}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_22_TOV['R (km)'],WD_22_TOV['m (Msol)'],color ='blue',label =r'p(0) = $10^{22}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_23_TOV['R (km)'],WD_23_TOV['m (Msol)'],color ='green',label =r'p(0) = $10^{23}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_24_TOV['R (km)'],WD_24_TOV['m (Msol)'],color ='brown',label =r'p(0) = $10^{24}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_25_TOV['R (km)'],WD_25_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{25}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_26_TOV['R (km)'],WD_26_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{26}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_27_TOV['R (km)'],WD_27_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{27}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_28_TOV['R (km)'],WD_28_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{28}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_29_TOV['R (km)'],WD_29_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{29}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_30_TOV['R (km)'],WD_30_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{30}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_31_TOV['R (km)'],WD_31_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{31}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_32_TOV['R (km)'],WD_32_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{32}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_33_TOV['R (km)'],WD_33_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{33}$ (TOV)', linestyle=':')\n",
        "#plt.plot(WD_34_TOV['R (km)'],WD_34_TOV['m (Msol)'],color ='grey',label =r'p(0) = $10^{34}$ (TOV)', linestyle=':')\n",
        "\n",
        "plt.yticks(size = 13)\n",
        "plt.xticks(size = 13)\n",
        "\n",
        "\n",
        "plt.ylabel(r'M (M$_{\\odot}$)', size = 13)\n",
        "plt.ylim(0,1.5)\n",
        "plt.xlim(0,15e+3)\n",
        "plt.xlabel('Raio (km)', size = 13)\n",
        "plt.legend(loc = 1, prop = {'size':10.5})\n",
        "plt.savefig('rM_regimequalquer-all-WD.png')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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qq+uao9PpLOpr4uzszOuvv87y5ctJTm48s7tGo2myvMjISLKyshBCEBERQWhoKKmpqeh0OkpKSggODrYqV2tay9fcMWkr2fB3MRqNhtra2kbfPCVJund5eRDaaPbz9pGTAyEhbd9PURQURaG6utq8ztfXl8uXL5uXL126ZNH7BqiqqsLV1bVReTExMZSWljZaHx0dzdq1a63OZU2Gu+Xq6mpR3/oSExNZtWoV4eHhVpcXERFBZmYmQgjWrFlDz5496d27Nzt27GDs2LGNvmA0NGzYMLRaLeXl5Rb/9h49epQRI0ZYna+5Y9JWsuHvYnJzcxk0aFCb/uglSbJOYKCxge6osq21fft2UlNT2b17N4MGDcLPzw8XFxeuX7+Op6cnKpWKgQMHsnfvXiZNmkR6ejrPPfeceX+DwUBhYSEBAQGNym6vHn9rGe6Fh4eHRX3rc3Z2ZvHixSxbtoxBgwZZVV5kZCSpqan069ePIUOGABAWFsbq1auZM2dOq/v7+/szZcoU5s2bx5YtW3B2dmbPnj0cPHiQdevWWZWvpWPSVrLh70J++OEHCgsLefbZZ+VNfZLUAdzc7q5X3t5KSkoICgrCycnJfENYXFwchw4dMt/wtmnTJhITE3nllVcYMmSI+S52gCNHjjBmzJh26V0CJCcns3//fsDY0584cSJbtmxpMcO9aljf+hISEli5cmWj9fVP2ffv39/8JUelUuHp6cljjz1m/r2p4W/t+r7J5s2bWbBgAQEBAXTv3p0BAwawb98++vXrZ1W+9jwmijXXehxdaGioyOmor+EOZMeOHZw6dYq5c+eiUqlsHUeSHJ5erwewq/tlFEVp8vp5Xl4e8+fPZ+/eva2WkZycTHx8POPHj++IiPdFW+rrCJo7Ji39DSqKckwI0ejik7yrv4sQQnDhwgUGDBjQ6LEaSZI6v8DAQOLj480D2jSnrq6O0NBQh270wfr6OoL2Piayx99FnD9/nt///vckJSXxyCOP2DqOJHUK9tjjl7oW2eOXmvX111/j6uoqR+qTJEnq4mTD3wUYDAYuXrxI9+7d6dZNHnJJkqSuTLYCXcCFCxeora2VI/VJkiRJsuHvCnJzc+nTp488zS9JkiTJhr+zMxgMnDhxAmdn50ZTYkqSJEldj2z4O7mLFy9iMBgYNWqUraNIkiRJdkA2/J3cmTNneOCBBxgzZoyto0iSJEl2QDb8nZgQgtzcXHx8fORpfkmSJAmQDX+ndvXqVaqqqujRo4eto0iSJEl2Qjb8nZhWq8XJyYmJEyfaOookSZJkJ+QUbZ3Y2bNn8ff3b7cZtiRJku6H7OxsMjIyMBgMBAQEsHjxYnJzc9mwYQPV1dUMGDCgydn1JOvIHn8ndfv2bQoLC+nZs6eto0iSZAdqa2sJCwszT1qTm5vLqFGjUKvVxMXFUVFRARgnhBk3bhxlZWXt9t6pqalN3mvUXIbw8HDS09PJyMggKysLgOHDh/PRRx+RkZFBXl5em+urKApJSUnm3x8+fJioqCjzsqIoBAcHm18zZ84E4LXXXmPp0qXm7ZYuXYqPj495uaCgAGdnZ0aOHElwcDB+fn54enqayzFN7VtZWUlaWhr+/v6o1WqioqI4fvy4xfs3l6+9j4ls+DsprVYLYDF/tCRJXVdmZibR0dG4u7sDkJKSwooVK9BqtQQGBrJ69WoAnJycSEhIYP369e323vHx8RaNnElzGUy2bt1KbGyseXnv3r08++yzPPHEE62+Z8P6AmRlZZn/bWyKRqMxv7Zv3w5AREQE2dnZFmV4e3tTUFBgXo6NjeXEiRNoNBqWL19OXFycuZyYmBgA5s6dS0VFBfn5+Wi1WhYuXMjEiRPR6XSt5mvvYyIb/k7q3Llz9O/fn6FDh9o6iiRJ95GiKCxZsoSgoCAef/xxTp48CUBGRgbTp08HoLS0lPPnzzNp0iQA5syZwxdffGEuY9q0aWzbtq3dMkVGRjaaDry1DBs3buTmzZu8/PLL5nWTJk1i586dfPXVV1RXV7f4nvXra7Jo0SLeeeedNmUPDw/n6NGj6PV69Ho9Op2OadOmmc9EZGdnExkZ2WIZ58+fZ+fOnaxfv948i97kyZOZMGECGzZssCpfex4TeY2/ExJCcPbsWUaMGGHrKJLUpdyuuU2ervXT0Hcj0CsQtx5uVm2rUqk4efIkX375JUlJSRw5cgSNRsPw4cMBuHz5Mr6+vubt/fz8KCwsNC97eXkhhKCwsLDRUN8xMTGUlpY2es/o6GjWrl1rdX1ayrBr1y7WrFlDTEwMaWlpbNy4kb/85S/s2rULvV7PqFGjWryMqdfrLeprMnv2bN577z3Onj3b5H7BwcHmnydPnsyvfvUrPDw88Pf359ixYwghCAkJITw8nIyMDBITE8nOziYlJaXFuubm5qJWq+nTp4/F+tGjR5u/QLSWr6Vj0lay4e+EioqKqKmpkTPxSdJ9lqfLI/R3jaY/bxc5L+YQ4h1i1bazZs0CIC4ujsTERIqLi3F3d8fJyQkwdg5ao1KpKCoqatTImK5Z36uWMkydOpWpU6darPvpT3/KT3/6U6vK1ul0FvU1cXZ25vXXX2f58uUkJyc32k+j0TRZXmRkJFlZWQghiIiIIDQ0lNTUVHQ6HSUlJRZfGO5Fa/maOyZtJRv+TujSpUt069aNiIgIW0eRpC4l0CuQnBdzOqzsu6EoCoqiWJwa9/X15fLly+blS5cuWfS+Aaqqqpp8Iqi9evzWZLhbrq6uzV4KSExMZNWqVYSHh1tdXkREBJmZmQghWLNmDT179qR3797s2LGDsWPHNvqC0dCwYcPQarWUl5db9PqPHj3a6MxsS/maOyZtJoS47y/g50AWcBOobWXbMcAeoBQoB44BU9vyfiEhIaIryczMFNu2bbN1DEnq9GpqakRNTY2tY1gAxIcffiiEEOL//u//xKhRo4QQQvj4+IgffvjBvN24cePEnj17hBBCLFy4UPzyl780/66urk54eXmJysrKds9WX0sZ7lXD+tZ/7/T0dOHn5yeefPLJZrPVV1JSIjw9PcWQIUPM6xYtWiQGDx4sVq5cabFtRkaGSExMbFTGjBkzREJCgvnvZffu3cLLy0tcvXrVqnzNHZOW/gaBHNFEm2irc8E3gA+BX1ixrSfwOTAM6Au8A/xBUZTRHRfPcdXW1nLu3Dl69epl6yiSJNlISUkJQUFBLFmyhIyMDMB42v/QoUPmbTZt2sQbb7yBWq3m9OnTLFq0yPy7I0eOMGbMmHYbAyQ5Odncm/f19TWfxm4pw71qWN/6EhISzDfZ1Vf/cT7T3fhgPMXu6elp8ZRUWFgY586da/XGPpPNmzfj6upKQEAAarWaVatWsW/fPvr162dVvvY8Joqw4lpPR1EUJQr4sxCiTZccFEX5O/BHIcT71mwfGhoqcnI65vSbvSkoKOCTTz5hwoQJjBs3ztZxJKlT0+v1AE02IraiKEqT18/z8vKYP38+e/fubbWM5ORk4uPjGT9+fEdEvC/aUl9H0NwxaelvUFGUY0KIRjedONzdX4qiqDD2/k/YOos9unDhAi4uLnI2PkmSLAQGBhIfH28e0KY5dXV1hIaGOnSjD9bX1xG09zFxqB6/oihuwEGgUAjx81a2fQl4CcDPzy/k4sWL95jWMWzatIm+ffvy85+3+PFIktQO7LHHL3UtnbrHryjKA8A+4CqQ0Nr2QojNQohQIURoU9dQOqMff/yRq1evUlNTY+sokiRJkp1yiIZfUZQHgUNAMTBdCCFbtiaYHo0ZO3asjZNIkiRJ9somDb+iKE6KorgAPe4su9x5KU1sqwL+BpwBZgohau9vWsdx6dIlXF1defTRR20dRZIkSbJTturxzwKqgAOA052fq4BHFEWJUBTllqIofne2nYvxZr5pQPmd391SFOWXtghuz77//ns8PDwazYAlSZIkSSY2GblPCLEV2NrMry8A7vW2XQYs6/BQDq62tpYbN27g5+fX+saSJElSl+UQ1/il1hUXFyOE4KmnnrJ1FEmSJMmOyYa/kzh//jzOzs54e3vbOookSZJkx2TD30kcP36c7t27yxn5JEmSpBbJVqITMBgMVFZWMnDgQFtHkSRJkuycbPg7gdLSUmpra/nJT35i6yiSJEn3LDs7mzlz5vDCCy/w7rvvmtfX1tby9NNPs2bNGhumc3yy4e8ETp8+jaIoDBgwwNZRJEmyU7W1tYSFhZnHrs/NzWXUqFGo1Wri4uKoqKgAjOPCjxs3jrKysnZ779TUVHx8fBo9atxchvDwcNLT08nIyCArK8u8/Xvvvcdzzz1n1Xs2rK+iKCQlJZl/f/jwYaKioszLiqJYzM43c+ZMAF577TWWLl1q3m7p0qX4+PiYlwsKCnB2dmbkyJEEBwfj5+eHp6enuZwDBw4AUFlZSVpaGv7+/qjVaqKiojh+/LjF+zeXr72PiWz4O4H8/HwURZHjhUuS1KzMzEyio6Nxdzc+LZ2SksKKFSvQarUEBgayevVqAJycnEhISGD9+vXt9t7x8fEWjZxJcxlMtm7dSmxsLAB/+9vf8PLyQq1WW/WeDesLkJWVhVarbXYfjUZjfm3fvh2AiIgIsrOzLcrw9vamoKDAvBwbG8uJEyfQaDQsX76cuLg4czmm6X3nzp1LRUUF+fn5aLVaFi5cyMSJE9HpdK3ma+9jIhv+TkCv1zNixAg5cI8kSSiKwpIlSwgKCuLxxx/n5MmTAGRkZDB9+nTAeHnw/PnzTJo0CYA5c+bwxRdfmMuYNm0a27Zta7dMkZGR9O/f32Jdaxk2btzIzZs3efnllwE4cOAA33//PRs2bODLL7+ktYnX6tfXZNGiRbzzzjttyh4eHs7Ro0fR6/Xo9Xp0Oh3Tpk0zn4nIzs4mMjKyxTLOnz/Pzp07Wb9+vbmDNnnyZCZMmMCGDRusyteex8QmA/hI7ef27duUlZURHR1t6yiS1OXVVlZy8/z5Dim796BBdO/Vy6ptVSoVJ0+e5MsvvyQpKYkjR46g0WgYPnw4YJzXw9fX17y9n58fhYWF5mUvLy+EEBQWFvLwww9blB0TE0NpaWmj94yOjmbt2rVW16elDLt27WLNmjXExMSQlpbGxo0bWblyJWA8BZ6Tk8MjjzzSbNl6vd6iviazZ8/mvffe4+zZs03uFxwcbP558uTJ/OpXv8LDwwN/f3+OHTuGEIKQkBDCw8PJyMggMTGR7OxsUlJSWqxrbm4uarWaPn36WKwfPXq0xaWMlvK1dEzaSjb8Du77778HwMPDw8ZJOg9hMFBz8ya1lZUY9Hrzq06vByEQQuDu44NrF5n1UbLezfPn2f+zn3VI2RP/+Ec8hw2zattZs2YBEBcXR2JiIsXFxbi7u+Pk5ASANdOxq1QqioqKGjUypmvW96qlDFOnTmXq1KlN/i4qKsri2nxTdDqdRX1NnJ2def3111m+fDnJycmN9tNoNE2WFxkZSVZWFkIIIiIiCA0NJTU1FZ1OR0lJicUXhnvRWr7mjklbyYbfwRUXF9OtW7dGp9Gk5gkhqCot5Yfvv6f87Fl0ubnob9/mx2vXqLp2jdrbt1stI+SXv2TInZt/JMmk96BBTPzjHzus7LuhKAqKolBdXW1e5+vra57NE4wTfNXvfQNUVVXh6uraqLz26vFbk+Fuubq6WtS3vsTERFatWkV4eLjV5UVERJCZmYkQgjVr1tCzZ0969+7Njh07GDt2bKMvGA0NGzYMrVZLeXm5Ra//6NGjjBgxwup8zR2TtpINv4OrqKhg8ODB9OzZ09ZR7FrFpUuUfP01V775hpJvv6WuqgoAJxcX6n78kX4hIXiHh3O7pITyc+cI+s//xNnNjYv79+Pi6cnDEyYgDAa0n32GT1QU/eWjk1ITuvfqZXWvvCNt376d1NRUdu/ezaBBg/Dz88PFxYXr16/j6emJSqVi4MCB7N27l0mTJpGenm5xt7zBYKCwsJCAgIBGZbdXj7+1DPfCw8PDor71OTs7s3jxYpYtW8YgK79MRUZGkpqaSr9+/RgyZAgAYWFhrF69mjlz5rS6v7+/P1OmTGHevHls2bIFZ2dn9uzZw8GDB1m3bp1V+Vo6Jm0lG34HZvpDCAsLs3UUu3SrqIgLu3ej/fxzqnMqjHMAACAASURBVEpLoVs3+gUH4zZgAJ7DhjFy3jx6enlRcf48vQcOxKmJL0/eEREWy/3a6ZSeJHWkkpISgoKCcHJyMt8QFhcXx6FDh8w3vG3atInExEReeeUVhgwZYr6LHeDIkSOMGTOmXXqXAMnJyezfvx8w9vQnTpzIli1bWsxwrxrWt76EhATzPQP11T9l379/f/OXHJVKhaenJ4899pj596aGv7Ub+0w2b97MggULCAgIoHv37gwYMIB9+/bRr4lLhk3la89jolhzrcfRhYaGipycHFvHaHeFhYV8/PHHhIeHM378eFvHsQtCCIr+9jc077/PzXPncHJx4cGRI6mrqiLigw/o9dBDto4odSJ6vR7Arh6lVRSlyevneXl5zJ8/n71797ZaRnJyMvHx8Q7970pb6usImjsmLf0NKopyTAgR2nC97PE7sCtXrgAwcuRIGyexPSEEl/bvJ/e//5tyrZZuPXrgFxPDT955B2c3N1vHkySbCwwMJD4+nlu3blk8295QXV0doaGhDt3og/X1dQTtfUxkj9+Bffnll1y+fNn8nGtXde34cY68/TY3z53Da9QogtLSeHDECNngSx3OHnv8Utcie/xdzD//+c8ufTd/TUUFx959l/P/+7/0UavxiYriJ8uX4/Lgg7aOJkmSZLdkw++g9Ho9FRUVXbbhL87K4uv/+i/0t28TvGABgYmJdGvlkRpJkiRJNvwOy3R939o7SjsLQ20tJ377W86kp/NgcDC+UVEMTUpC6SZHn5YkSbKGbPgdVElJCd26detSM/L9eP06B59/nlsXLzIiLY3hKSmywZckSWoj+a+mg/ruu+9wdname/eu8d3t5vnzHJwxg+obN/B7+mkeS06Wjb4kSdJd6BqtRidUWVnZaESqzqo4K4usV16h14ABPP3HP+J+j+NUS5IkdWWyy+SATDf2Pf7447aO0uFKjxzhq3nzMNTWMm7VKtnoS5Ik3SPZ8DugwsJChBCd/o7+4uxsDr/8Mv1GjWLqoUM82GCKTUmSJKnt5Kl+B5Sbmwvg8KNRtaTo8GH+9h//QZ9HH+XJjRvp7uJi60iSJEmdguzxO6Da2lo8PDw67TX+srNn+fq11+ilUjHu17+Wjb4kdTHZ2dnMmTOHF154gXfffReAw4cPM3bsWFJSUswTD0l3Rzb8Dujq1asMHDjQ1jE6RMXFixxKTsbd25tJO3bQNzDQ1pEkqVOora0lLCyMW7duAcYzh6NGjUKtVhMXF0dFRQVgHBd+3LhxlJWVtdt7p6am4uPjg6IoFuubyxAeHk56ejoZGRlkZWUBxsmHHnjgAW7fvs3gwYPbXF9FUUhKSjL//vDhw0RFRZmXFUUhODjY/Jo5cyYAr732GkuXLjVvt3TpUnx8fMzLBQUFODs7M3LkSIKDg/Hz88PT09NcjmmGv8rKStLS0vD390etVhMVFcXx48ct3r+5fO19TGTD72D0ej2lpaX06tXL1lHanf72bQ7OnEn1jRuEr11Lj969bR1JkjqNzMxMoqOjzZcIU1JSWLFiBVqtlsDAQFavXg2Ak5MTCQkJrF+/vt3eOz4+3qKRM2kug8nWrVuJjY0FICIigoMHD7J582beeuutVt+zYX0BsrKy0Gq1ze6j0WjML9MUwREREWRnZ1uU4e3tTUFBgXk5NjaWEydOoNFoWL58OXFxceZyYmJiAJg7dy4VFRXk5+ej1WpZuHAhEydORKfTtZqvvY+JbPgdzKVLlwA6XcMvhODvb7xBbVUVT7z1Fr076RkNSepoiqKwZMkSgoKCePzxxzl58iQAGRkZ5rnpS0tLOX/+PJMmTQJgzpw5fPHFF+Yypk2b1q6n0yMjIxvdjNxaho0bN3Lz5k3zJGTd7ozb4erqav65JfXra7Jo0SLeeeedNmUPDw/n6NGj6PV69Ho9Op2OadOmmc9EZGdntzqC6vnz59m5cyfr1683T6YzefJkJkyYwIYNG6zK157HRN7c52Bu3LiBoig88cQTto7SrnLeeYfCP/2J8Pffx+/ON2RJcjQ1NTUWPbj25OXlRY8ePazaVqVScfLkSb788kuSkpI4cuQIGo2G4XeejLl8+TK+vr7m7f38/CgsLLR4LyEEhYWFPNzgEdqYmBhKS0sbvWd0dDRr1661uj4tZdi1axdr1qwhJiaGtLQ0Nm7cyI4dO9i/fz+VlZXMmDGjxbL1er1FfU1mz57Ne++9x9mzZ5vcLzg42Pzz5MmT+dWvfoWHhwf+/v4cO3YMIQQhISGEh4eTkZFBYmIi2dnZpKSktJgnNzcXtVpNnz59LNaPHj3a/AWitXwtHZO2kg2/gykuLsbLy6tTTQNanJWF9vPP6RMQIBt9yaHpdDp+97vfdUjZL774It7e3lZtO2vWLADi4uJITEykuLgYd3d3nO5MZGXNdOwqlYqioqJGjYzpmvW9ainD1KlTmTp1qsW65557jueee86qsnU6nUV9TZydnXn99ddZvnw5ycnJjfbTaDRNlhcZGUlWVhZCCCIiIggNDSU1NRWdTkdJSYnFF4Z70Vq+5o5JW8mG38GcOXOmU53mr9Lp+Psbb+AVHEzEb39r6ziSdE+8vLx48cUXO6zsu6EoCoqiUF1dbV7n6+vL5cuXzcuXLl2y6H0DVFVV4erq2qi89urxW5Phbrm6ulrUt77ExERWrVpFeHi41eVFRESQmZmJEII1a9bQs2dPevfuzY4dOxg7dmyjLxgNDRs2DK1WS3l5uUWv/+jRo4wYMcLqfM0dk7aSDb8DEUKg1+ut/tZv74QQHH75ZQx1dUSsW4frgw/aOpIk3ZMePXrYxf+f27dvJzU1ld27dzNo0CD8/PxwcXHh+vXreHp6olKpGDhwIHv37mXSpEmkp6db9KYNBgOFhYUEBAQ0Kru9evytZbgXHh4eFvWtz9nZmcWLF7Ns2TIGDRpkVXmRkZGkpqbSr18/hgwZAkBYWBirV69mzpw5re7v7+/PlClTmDdvHlu2bMHZ2Zk9e/Zw8OBB1q1bZ1W+lo5JW8mb+xzI9evXqaurY+TIkbaO0i5yP/qIG99/j19MDK79+tk6jiR1GiUlJQQFBbFkyRIyMjIA42n/Q4cOmbfZtGkTb7zxBmq1mtOnT7No0SLz744cOcKYMWPapXcJkJycbO7N+/r6mk9jt5ThXjWsb30JCQlNXi6t/zhfTL3LjiqVCk9PTx577DHzurCwMM6dO2f11OibN2/G1dWVgIAA1Go1q1atYt++ffRr4t++pvK16zERQtz3F/BzIAu4CdRasX0o8A+gEjgHPN+W9wsJCRGdQU5Ojnj77bdFWVmZraPcszKtVvxh5EiRtWCBqKuttXUcSborNTU1oqamxtYxLBj/WW/szJkz4umnn7aqjDlz5og///nP7RnrvmtLfR1Bc8ekpb9BIEc00Sbaqsd/A/gQ+EVrGyqK0gfYB3wB9AVSgI8URRnboQnt0OnTpwFwc3OzcZJ7Y6irI3vBAlxVKsa88w7dWrk+JknSvQsMDCQ+Pt48oE1z6urqCA0NZfz48fcpWcewtr6OoL2PiU2u8QshDgAoihJlxebPYezpr77zDeZPiqLsBF4Cvu2wkHbIyckJHx8fund37FszTv72t5T/85+M+M//pHs7nUqUJMlItHC3vOlu/5Y4OTm1+niao7Cmvo6gvY+JI1zjHwl8Jyz/mo/fWd8sRVFeUhQlR1GUnGvXrnVowPvl2rVr9/wYh63dKiri7Pbt+Pz0pwx/6SVbx5EkSepyHKHhfwAob7CuDGhxPFchxGYhRKgQIrSpmyccze3btykrK6Nnz562jnLXhBB8u3gxPfr0Ydy776JYMfqWJEmS1L4c4V/eCqBPg3UeGG8M7DJMQ/U2HPnJkeRv3861Y8cYNGUKzp14SmFJkiR75ggN/wmg4bBIj99Z32VUVFTQrVu3RoM9OIraH38kb9s2+qjVDOsk1w8lSZIckU0afkVRnBRFcQF63Fl2ufNSmth8J+CmKMpCRVF6KIoyHuMNf5vvY2Sbu3LlCl5eXg57Y9/3W7ZQdfUq4e+/T3crxxuXJEmS2p+tevyzgCrgAOB05+cq4BFFUSIURbmlKIofgBCiDJgETMd4rf93QIoQokvd0X/69Gn0er2tY9yV8nPn+P6jj1CNHUsff39bx5EkSerSbPU431ZgazO/vgBYXAAWQhwFOtd0dG1gMBjQ6/X4+fnZOspdOblhA04uLgT/otVhGyRJkqQO5gjX+Lu8GzduYDAYGk0x6Qiuf/89hQcPMmrRIvoGBto6jiRJUpcnG34HcO7cOQAeeughGydpu6xXX8XFy4vBzz5r6yiSJEkSsuF3CPn5+QC4O9gjcCXffMPtoiIGjBtHtyYmxJAkSWpKdnY2c+bM4YUXXuDdd98FoKioiNmzZzN2bJcbrb3dyYbfAfTo0QMfHx+6OdCAN8Jg4MS6dXgOH85PfvUrW8eRpC6vtraWsLAw89j1ubm5jBo1CrVaTVxcHBUVFYBxXPhx48ZRVlbWbu+dmpqKj48PDR/cai5DeHg46enpZGRkkJWVBYCPjw8ff/wxD7YwfbepjhcvXjTPsufn54enp6d5+cCBA1RWVpKWloa/vz9qtZqoqCiOHz9uLmf8+PF8+umnFmWfPn0aHx+fDvl87jfHaUm6sGvXrtnFHN9tcSYjg+vff8/IX/zCob6wSFJnlZmZSXR0tPnMYUpKCitWrECr1RIYGMjq1asB47jwCQkJrF+/vt3eOz4+3qJhNWkug8nWrVuJjY21+n1MdXzkkUfQaDRoNBqWL19OXFyceTkmJoa5c+dSUVFBfn4+Wq2WhQsXMnHiRHQ6HWAc4z8zM9Oi7E8++YQZM2Z0yOdz3zU1ZV9neznytLw1NTXi7bffFvv377d1FKsZ6urE/xs7VnwWEiKn3JU6NXudlvfNN98UI0aMEMHBweLEiRNCCCEiIyOFRqMRQghx5coV4e3tbd4nLy9PDB061Lx87do1MXjw4A7JZtJahg0bNogPPvigURmTJ09utvz6dTTJyMgQiYmJ5uWCggLh5ubWaHrzGTNmiLfeeksIIURFRYXo3bu3KC0tFUIIYTAYhJ+fn/mz7KjP52440rS8kpVKSkoA6N27xakJ7Erhn/9MTXk541avllPuSl1PcTGcPPmv5TNn4MIF48+1tXDsGNy4YVz+4QfjssFgXC4ogLNn/7Xvd99BaWmbI6hUKk6ePMmyZctISkpCr9ej0WjMTwZdvnwZX19f8/Z+fn4UFhaal728vBBCWKwziYmJMZ82r/969dVX25SxpQy7du1izZo1nD59mrS0NACqqqpISUnh1KlTpKSkYDB9Znc0rGNzcnNzUavVjYY/Hz16NKdOnQKM91PFxsby2WefAfDVV1/Rt29fgoKCgJY/H0fgmMPAdSHl5cb5iUaObHEyQrshhODkhg08NHo0D//0p7aOI0n33+bNxldxsXE5MRGCgmDLFigrg9BQ+OILeO452L0bkpKgqgpcXGDxYtDp4NAh476RkfD227BgQZsimKajjYuLIzExkeLiYtzd3XG680VctDB1r4lKpaKoqKjRjKAHDhxoU5bmtJRh6tSpTJ061WKdq6srH330UbP76HQ6izreq4SEBJYsWcK8efPIzMxsNMVvc5+PI5ANv527cuUKbm5u9OrVy9ZRrJK3bRs3z53j0enTbR1FkmzjpZeMjbrJtm3g6mr82cMDcnLANIJlbKxx2TSM9bvvGs8KmHz1Fdzj/T2KoqAoCtXV1eZ1vr6+XL582bx86dIli943GHvYrqbc9cTExFDaxFmI6Oho1q5da3UuazK0haurq0UdmzNs2DC0Wi3l5eUWvf6jR49azIXy1FNP8cILL3Dq1Cl27txJbm6uRTnNfT6OQDb8di43N7fRKS17JYTgwu7duD/8MOqf/9zWcSTJNry9LRvroUP/9XP37hAS8q/lBx80vkwaDmn9+ON3FWH79u2kpqaye/duBg0ahJ+fHy4uLly/fh1PT09UKhUDBw5k7969TJo0ifT0dJ6r92XFYDBQWFhIQEBAo7Lbq8ffWoa28vDwsKhjc/z9/ZkyZQrz5s1jy5YtODs7s2fPHg4ePMi6devM2zk5OTFjxgwSExMJDQ1FpVKZf9fS5+MI5DV+OyeEwMfHx9YxrFKSnc2NM2cYvWQJTvK5fUmymZKSEoKCgliyZAkZGRmA8bT/IdMlBGDTpk288cYbqNVqTp8+zaJFi8y/O3LkCGPGjGm3Hm1ycrK5N+/r60tycnKrGe5Gwzo2Z/Pmzbi6uhIQEIBarWbVqlXs27ePfv36WWw3a9YsvvvuOxISEizWt/fnc78p1lzrcXShoaEiJyfH1jHaTK/Xs3LlSmJjYwmp30uwUzujo1GcnJjypz81el5Xkjoj08RZznb0RVdRlCavn+fl5TF//nz27t3bahnJycnEx8czfvz4jojYYdpSx3thT59PS3+DiqIcE0KENlwve/x2zHT9y8PDw8ZJWvdDbi5VV68yYNw42ehLkh0KDAwkPj7ePIBPc+rq6ggNDbWLRq2trK3jvXDkz8dE9vjt2P79+zly5Aipqal2P07/1wsXotNoeGbfPrp1l7eOSF2DPfb4pa5F9vg7GScnJ9zc3Bpdd7I3ZWfPcnH/fgJmzpSNviRJkp2TDb8d0+l0qFQquz91/t1vfgMGAz5RUbaOIkmSJLVCNvx27MKFC3bf6NdUVHDtu+8YPH06vQcOtHUcSZIkqRWy4bdTNTU11NTU2P1UvNrPPqOuupoRqam2jiJJkiRZQTb8duratWsAdv0YX11tLac2bqT3oEH06t/f1nEkSZIkK8iG305duXIFwK5v7CvJysKg16P+93+3dRRJkiTJSrLht1MnTpxAURR69uxp6yjN+ucf/0jfwEA5PK8kSZIDkQ2/HbPnZ/d/OHWK4q++YuAzz9j9DYiSJEnSv8iG307dunWLgXZ8l/yZjAxQFB6eMMHWUSRJkqQ2kKOt2KGamhpu3LiBm5ubraM0qfbHH7ny978TMGMG7g4ygZAkSY4jOzubjIwMDAYDAQEBLF68uMl10t2RPX47VFhYaOsILfrn559TU15OwIwZto4iSZKVamtrCQsLM49jn5uby6hRo1Cr1cTFxVFRUQEYx6IfN24cZWVl7fbeqamp+Pj4NLos2FyG8PBw0tPTycjIICsrq9l1zdXx4sWLBAcHExwcjJ+fH56enublAwcOUFlZSVpaGv7+/qjVaqKiojh+/Li5nPHjx/Ppp59alH369Gl8fHw65PO532TDb4dqamoAGDZsmI2TNO3Uhx/Sw8NDDtgjSQ4kMzOT6Oho89ggKSkprFixAq1WS2BgIKtXrwaMQ4UnJCSwfv36dnvv+Ph4i4bVpLkMJlu3biU2NrbVdSamOj7yyCNoNBo0Gg3Lly8nLi7OvBwTE8PcuXOpqKggPz8frVbLwoULmThxIjqdDjBOx5uZmWlR9ieffMKMGTM65PO574QQnf4VEhIiHElWVpZYuXKlMBgMto7SyI38fLH9scfEqU2bbB1FkmyupqZG1NTU2DqGBUC8+eabYsSIESI4OFicOHFCCCFEZGSk0Gg0Qgghrly5Iry9vc375OXliaFDh5qXr127JgYPHtwh2Uxay7BhwwbxwQcfWOzf1Lr66tfRJCMjQyQmJpqXCwoKhJubmygrK7PYbsaMGeKtt94SQghRUVEhevfuLUpLS4UQQhgMBuHn52f+LDvq87kbLf0NAjmiiTZR9vjt0JkzZ+jRo4dd3i1/7osv6Nm3L0Nnz7Z1FEmyS8XFcPLkv5bPnIELF4w/19bCsWNw44Zx+YcfjMsGg3G5oADOnv3Xvt99B6Wlbc+gUqk4efIky5YtIykpCb1ej0ajYfjw4YBxym9fX1/z9n5+fhaXGL28vBBCNHnZMSYmxnzavP7r1VdfbVPGljLs2rWLNWvWcPr0adLS0ppdV1/DOjYnNzcXtVpNnz59LNaPHj2aU6dOAeDu7k5sbCyfffYZAF999RV9+/YlKCgIaPnzcQSt3tynKEpPIB6YCowCPIHrwHfALuBTIUR1R4bsam7duoWLi4utYzSir6pC+/nn+D71FE49etg6jiTZpc2bja/iYuNyYiIEBcGWLVBWBqGh8MUX8NxzsHs3JCVBVRW4uMDixaDTwaFDxn0jI+Htt2HBgrZlmDVrFgBxcXEkJiZSXFyMu7s7Tk5OgPFMb2tUKhVFRUU8/PDDFusPHDjQtjDNaCnD1KlTmTp1aqvr6tPpdBZ1vFcJCQksWbKEefPmkZmZaf5MTZr7fBxBiw2/oiizgZWAFvgz8HvgJtAbGA7MBlYqivJLIURGB2ftMvR6PY8//ritYzRy4f/+D4Nej/eTT9o6iiTZrZdeMjbqJtu2gaur8WcPD8jJAX9/43JsrHHZ9D363XeNZwVMvvoKvL3vLY+iKCiKQnX1v/pnvr6+XL582bx86dIli943QFVVFa6m4PXExMRQ2sRpiOjoaNauXWt1LmsytIWrq6tFHZszbNgwtFot5eXlFr3+o0ePMmLECPPyU089xQsvvMCpU6fYuXMnubm5FuU09/k4gtZ6/BOAJ4UQ+U38bgewXFGUIcBbgGz428GtW7eoqqrCy8vL1lEaKfzTn3gwKAj/Z56xdRSpHVTpq7h6+ypFFUVU11Zz48cbHCs+RpW+igd7PcitmlvkFOegclfh0t2FklslXCi7wGP9HqOb0o0LZReoqathUN9BeLt7s36SA9/s1I68vS0b66FD//Vz9+5Qf/qNBx80vkxMXwhM7vb7//bt20lNTWX37t0MGjQIPz8/XFxcuH79Op6enqhUKgYOHMjevXuZNGkS6enpPFfv24rBYKCwsJCAgIBGZbdXj7+1DG3l4eFhUcfm+Pv7M2XKFObNm8eWLVtwdnZmz549HDx4kHXr1pm3c3JyYsaMGSQmJhIaGopKpTL/rqXPxxG02PALIeJbK+DOlwL5XFc7OXvnAp/BdNHPTpSdPcuVb77hibfftnUUyUq1hlrO3zjPwXMHuVR+ifLqcs7+cJZjJcfoRjfKqpt+HMlJccLDxYMeTj0ouVWC7wO+9Hfvz239bQpuFNDXpS/OTs4UVxRTU1eDVy8vqlyq7nPtpJaUlJQQFBSEk5MT27ZtA4yn/Q8dOsT06dMB2LRpE4mJibzyyisMGTKE7du3m/c/cuQIY8aMabcebXJyMvv37weMPf2JEyeyZcuWFjPcjYZ1bM7mzZtZsGABAQEBdO/enQEDBrBv375Gc6PMmjWL3/zmN41ytffnc78p1lzrcXShoaEiJyfH1jGs8u2333Lw4EHmz5/PAw88YOs4Zn9NSaEkK4spBw/iJgftsTs/1v7IdyXfkVOcwxdnvuBU6SkqairQG/QAdO/WnaFeQ+nn1o98XT5ThkxhtM9oKvWVXK+6zvTHpuPp6kmlvpI+Ln3wcPEwX4O1x5tM7YVeb/x8nZ2dbZzkXxRFafL6eV5eHvPnz2fv3r2tlpGcnEx8fDzjx4/viIgdpi11vBf29Pm09DeoKMoxIURow/V3PXKfoihPAnMxjgXwpRDi01Z2qb+vE/BrIAlwAQ4Cc4UQuma2/y8gFXgIuAKsFUJ8eLfZ7dmtW7fo3bu3XTX6wmCgXKtlQFiYbPTtRJW+isMXDvN14dfsPrubE6UnAGMD7/2ANw/0fIC3o94m0CsQRVEI6h/EQ25tm/tBNvidS2BgIPHx8dy6dcv8LH9T6urqCA0NtYtGra2sreO9cOTPx+Suevx3Gv0UjDf3/Qi8AxQJITZZuf8bQCIwEfgB+BjoJYR4uolt44A/AOOFEH9XFGUsxhsNpwoh/mTN+zlSjz89PR2DwcCLL75o6yhmV/7+d/4yZw5P/f73PFT/AqV0X12+eZk9Z/ewK38XB88dxCAMeLp6EukXSUVNBXND5vLMkGdw6W5/T4R0VvbY45e6lvvZ438FeAEwAM8IId5UFOUvgFUNP/ASsFwIUXAn3CLgn4qiPCKEuNhg20eBE0KIvwMIIb5VFOUkMBKwquF3JFeuXMHDw8PWMSx89957OPfuTb9Ro2wdpcu5evsqn576lM3HNnNGdwYFhchHInk+6HnG+IxhbuhcuilyOA5Jkqx3tw2/O8bH+voAzwJfAladOlAUxQPwA46Z1gkhzimKchNjY96w4f8MmK0oShjwLRAGBAD77zK73TIYDNTV1TFy5EhbRzGrraqi/Nw5vEaOlKd+7xN9nZ492j0sPLiQgrICuindePKRJ1F7qln11CoC+wXaOqIkSQ7sbhv+Q8BMIUQm8IKiKKMBa4cwMl28Lm+wvgzj+AANXQX+B/gr/5pb4BdCiNwmtjVTFOUljGcW8PPzszKabd24cQMhhMVjI7ZWdPgwBr2eJ5Yts3WUTu9y+WUW/GkBX134iiu3r+DVy4u4gDg2P7OZfm79Wi9AkiTJCnfb8P8G2KQoylPALcAbSLZy34o7/+3TYL0HxrMIDS3BOHJgMHAGeAz4UlGUKiFEenNvIoTYDGwG4zV+K7PZlOlRvo66KeVu5Gdm4jlsmJyQpwOduXaG33z7G35/4vfoDXriAuJ4O+ptHh9gf4M4SZLk+O6q4RdC1AIvKorSG3ARQlxtw75liqJcwjj8rwZAURR/jL39k03sEgLsFEKcvrP8vaIou4BngGYbfkd0/fp1ALsZvOdWcTE6jUaO1NdBzlw7w4wdM9Bc0TDAfQBLI5fylP9TjHl4jK2jSZLUid3143wAQoibNN1Lb81m4DVFUf6K8a7+VcABIcSFJrb9GkhSFGWLEEKrKMpQjPMGbL271PbLYDDw0EMP0b37PR2WdlP0179Ct24Ez59v6yidSk5RDqu+WcUXp7+gj0sf/m3wv7Hr33fh6uyYg4FIkuRYrJmkp6C1bYQQ/q1t08Cvgb7AUaAnxrvzn7/zfjOB/xZCmM53GndtYwAAIABJREFUv4fxssCfFEXxwjhB0P+7U0ancu3aNbvp7YNxbH7viAg8Hn3U1lE6hfIfy3n78NusO7IOd2d3fvv0b0kelSwfv5Mk6b6ypms5EDiNcSz+K+3xpkKIOuC/7rwa/m47sL3eci3w+p1Xp9ZwmkpbunrsGD+cOkXwwoW2juLwautqmX9wPp+e+pRKfSU/e+xnvDv+Xfw92/p9WZIk6d5Z0/CPAV4E3gAOA78D9ouuMNbvfVRdXY0QAv+Gs3TYyIXdu1G6dWPg043GVJLa4FTpKWbumMmpq6d48pEn+eTZT3i4j+NN4ylJUufRasMvhPgH8A9FUV7FeHf9cox39KcDvxVCNHwsT7oLOp1xtGK1Wm3jJMZ5sq98+y0DY2Pp1b+/reM4pNs1t5n9v7PZkbeDwX0H89+x/82Lo16UYyFIkhWys7PJyMjAYDAQEBDA4sWLyc3NZcOGDVRXVzNgwABWrlxp65gOy+ohv4QQt4QQv8N4BmArxql45fit7eTChQsALU4neb+UfP01twoLeWTSJFtHcUhHi44SsCGAP57+Iy8Ev4AmRcNLIS/JRl+yqdraWsLCwrh16xYAubm5jBo1CrVaTVxcHBUVxiet6+rqGDduHGVlTc/eeDdSU1Px8fFp9P9AcxnCw8NJT08nIyODrKwsAIYPH85HH31ERkYGeXl5Ldbx4sWLBAcHExwcjJ+fH56enublAwcOUFlZSVpaGv7+/qjVaqKiojh+/Li5nPHjx/Ppp5bTz5w+fRofH58O+XzuN6sbfkVRBiqKsgLjyHoTMD63/3VHBetqtFotAC4utr/R6/uPPgLAKzjYxkkcS21dLfP2zmPcx+N4qNdDfD7tczY/s1nevCfZhczMTKKjo83jhKSkpLBixQq0Wi2BgYGsXr0aMM5Dn5CQwPr169vtvePj4y0aVpPmMphs3bqV2NhY8/LevXt59tlneeKJJ5p8H1MdH3nkETQaDRqNhuXLlxMXF2dejomJYe7cuVRUVJCfn49Wq2XhwoVMnDjRfOZ11qxZZGZmWpT9ySefMGPGjA75fO47IUSLL2AacADjCHprgWGt7WNvr5CQEGHvPv/8c7FlyxZbxxAGg0HsHD9e/O0//sPWURzKxbKLInBDoOBtxIv/+6Korq22dSTpPqipqRE1NTW2jmEBEG+++aYYMWKECP7/2bvv8KiqrYHDv5NCEkIgCUEChNB7kRIE6QiIIAKiqLQEBAsXxYKgUtSPCwqKIja8CALSVQSl967SExJpoSQkkF5IbzP7+2OTSICElJk5Kft9nnlgJmfOWTOEWbPb2m3aCD8/PyGEEN27dxe+vr5CCCHCw8NFzZo1c55z4cIF0axZs5z7UVFRokGDBmaJLduDYvjmm2/EwoUL73ue/v37i7S0tHsev/M1Zlu2bJnw8fHJuX/16lXh6Ogo4uPjcx03YsQI8eGHHwohhEhMTBSVK1cWERERQgj5uejp6ZnzXprr/SmK/H4HgZPiPjmxIC3+n4FawPdAFDBY07Rpd97M8YWkvImNjeWhhwq3bao5xPj7kxIWRuMRI/QOpdTYdGETbb5vQ2J6Ih8/9jGLBy2mgnUFvcNSdHIz8SZnI/6tRXY+6jxB8UEAZBmzOHXzFHGpcQDEpMRw6uYpjMIIwNW4q1yKuZTz3DNhZ4hIiih0DO7u7pw9e5b/+7//Y8yYMWRmZuLr60vLli2Be1cQeXp6EhLyb9V1Nzc3hBC5HsvWr1+/nG7zO29vvfVWoWLML4ZNmzYxf/58zp07x8SJEwHYt28fkyZNYsKECbRr1w47O7tc57v7NeYlICCARo0aUaVK7uKxHTp0wN/fH5DVUwcOHMi6desAOHToEC4uLrRu3RrI//0pDQoyq/8QcgOebnn8XABqlkUxGI1GIiMjqVUC9rr3/fxzrO3teahDB71DKfGMwsiYTWNYeXYl3Ty7sfH5jVStWFXvsBSdLT61mMWnFnNz8k0AfDb50Lp6a5YMWkJ8WjxeP3ix4bkNDG02lC2XtjDm9zGkTk/F3sae9/e+T3RKNHu99wLQfXl3PurxEZM7Ty5UDKNHjwZg0KBB+Pj4cPPmTSpVqoS1tTVAdm9uvtzd3blx4wa1a+dehbJz585CxZKX/GIYMmQIQ4YMyfXYY489xmOPPZbnc6Kjo3O9xuLy9vZm5syZTJo0iVWrVuW8p9nyen9Kg4LM6u9pgTjKtZiYGIQQVK58vz2KLEcYjcRdvIhT3bpYlZDqgSVVfFo8ozeOZsulLXT17Mr2kdtxrOCod1hKCfBy+5cZ2mxozv0VQ1bkVGV0tnfm5Esnqe8il+0ObDyQky+dzOkh+qT3J2QZs3Kee2jMIWo61SxWPJqmoWka6enpOY95eHgQGhqac//69ev31BBJTU3FweHeapL9+vUjIuLeXohevXqxYMGCAsdVkBgKw8HBIddrzEuLFi0IDAzk1q1buVr9J06coFWrVjn3+/Tpw9ixY/H392fjxo0EBOTeFy6v96c0UJ/uJUBCgqx6/KAuKnOL9vMjMzGR9lOn6hpHSfd3yN88vupxADYP38zAxgMf8AylPKnpVDNXsm5WrVnO322sbGhf89/FUFUrVs3VS5T9hSBbUTdqWr16NRMmTGDLli3Uq1cPT09P7O3tiY2NxdXVFXd3d+rWrcu2bdsYMGAAS5cuZejQf7+sGI1GQkJCaNy48T3nNlWL/0ExFJazs3Ou15iX+vXrM3jwYCZNmsSSJUuwtbVl69at7Nq1iy+//DLnOGtra0aMGIGPjw9eXl65dk3N7/0pDfId49c07aCmafnu0KJpWg9N0w6YNKpyJiIiAk3TcHFx0TWOS2vXYufqSjUvL13jKMmOXj/KgDUDSMtKY9XTq1TSV0qksLAwWrduzcyZM1m2bBkgu/337t2bc8yiRYuYPn06jRo14ty5c0y94wv/sWPH6NSpk8latOPHj89pzXt4eDB+/PgHxlAUd7/GvCxevBgHBwcaN25Mo0aNmDdvHtu3b6datdzbX48ePZozZ87g7e2d63FTvz+WpuU3zqJpWj/gC8AW2IMs3ZuA3EmvOdAbyALeFkKY5mugGXh5eYmTJ0/qHUaevv/+e6Kjo5kxY4ZuMRgNBta3bYtTnToM3LxZtzhKslkHZzHn0Bw61OrAb8//xkOO+k/GVPSVmZkJgK2trc6R/EvTtPuOn1+4cIG3336bbdu2PfAc48ePZ/jw4fTu3dscIZpNYV5jcZSk9ye/30FN004JIe5pyeXb1X87mbe4/QVgMHIjHRcgDjgDTCrJCb+0sLa21n1Gf7SvL8JgoOWECbrGUVLN2DeDOYfn0Na9LXu896i1+Uqp07RpU4YPH05SUlLOWv77MRgMeHl5lYikVlgFfY3FUZrfn2z5tvjLipLe4l+wYAEtW7akb9++usVwYvZsQvfsYci+fWhWBa7rVOYJIZi2dxpzj85lVOtRLH1qKRVs1FI9RSqJLX6lfDF5i18xv9TUVBISEsz27bQgjAYDVzZsoEbXrirp38FgNNBxSUdOhZ1ibu+5vNv1Xb1DUhRFKTb1Ka+z4OBgAF3ruIf//TfGjAweUpP6cmQaMhm9cTSnwk4xuMlglfQVRSkzVItfZ1lZcs1us2bNHnCk+YT/+Sd2rq40GTVKtxhKkvSsdJ5a+xT7g/azZugahrcarndIiqIoJqMSv85iYmKwt7fXrXiPEILg7dup1bMnViaqeFWaZRmz6LS0E77hvvw46EeV9BVFKXNUV7/OLly4QIUKFXTr6g/dt4/UiAgcqlfX5folicFowHujN2fDz/Jul3cZ23as3iEpiqKY3ANb/JqmXX3QMUKI+g86Rrm/pKQkKlasqNv1YwICsLKzo+lddajLmyxDFh2WdMAv3I+1z6zl+ZbP6x2SoiiKWRSkq78usnDPMiDcrNGUM0IIMjIy8txb2hJuHjhA7ccew+6unarKEyEEY38fi2+4L6+2f1UlfUVRyrSCJP5OwEvAdOAA8AOwQ5SHAgBmlpCQQEZGBm5ubrpcP/LUKeIvXaLR8+U70c3cN5NV/qv4pv83THxkot7hKIqimNUDx/iFEMeFEC8BnsB2YBZwTdO0mZqmld9moglcuHAB0G8pX/DtspY1u3fX5folwejfRjPnyBxm9Zylkr6iKOVCgSf3CSGShBA/IHsAlgMfAu3zfZKSr+yKS3Xq1NHl+rHnz1OrZ08caxZv28/Sal3AOlb5r6LVQ62Y3m263uEoinLbkSNHGDduHGPHjuWTTz7JeTwrK4v+/fszf/58HaMr/Qqc+DVNq6tp2mwgGOgLjAeOmiuw8iA5ORkXFxdddnhKCA4mxs8Pjz59LH7tkmDDuQ14b/RmRKsR+L7qi5WqWKiUcVlZWXTp0oWkpCQAAgICaNeuHY0aNWLQoEEkJiYCshZ9586diY+PN9m1J0yYQK1ate7p3cwrhq5du7J06VKWLVvG4cOHc47/7LPP8t26N/s1BgcH06ZNG9q0aYOnpyeurq4593fu3ElKSgoTJ06kfv36NGrUiJ49e3L69Omc8/Tu3Zs1a9bkOve5c+eoVauWWd4fS3vgp52mac9qmrYTOA44Av2EEF2EEMuFEOlmj7AMu379um6legO++w6Aau3a6XJ9PR0MOsiwX4bR0LUhywYvw0pTSV8p+1atWkWvXr1yPnNeffVVZs+eTWBgIE2bNuXTTz8F5KZh3t7efP311ya79vDhw3Ml1mx5xZBt+fLlDBwot74+ePAgbm5uNGrUKM/rZL/GOnXq4Ovri6+vL7NmzWLQoEE59/v168crr7xCYmIiFy9eJDAwkClTpvDEE08QHR0NyO14V61alevcK1euZMSIEWZ5fyxOCJHvDTACAcix/Wn3uz3oHHrf2rdvL0qiWbNmie+++06Xa+8cNUpsfuopXa6tp4ikCFFnQR3hPt9dXI65rHc4SimXkZEhMjIy9A4jF0DMmDFDtGrVSrRp00b4+fkJIYTo3r278PX1FUIIER4eLmrWrJnznAsXLohmzZrl3I+KihINGjQwS2zZHhTDN998IxYuXJhz//333xdvvPGGeOaZZ0S3bt1EUFDQPee/8zVmW7ZsmfDx8cm5f/XqVeHo6Cji4+NzHTdixAjx4YcfCiGESExMFJUrVxYRERFCCCGMRqPw9PTMeS/N9f4URX6/g8BJcZ+cWJBZ/YcAAXTL67sD8HFxvnyUR1lZWRiNRtq0aWPxa6fHxxPj50e7d8tX/fnE9ET6/tSX1KxUjo0/Rl3nunqHpChm4e7uztmzZ/njjz8YM2YMx44dw9fXl5YtWwIQGhqKh4dHzvGenp6EhITk3Hdzc0MIQUhICLVr18517n79+hEREXHPNXv16sWCBQsKHGN+MWzatIn58+fTr18/Jk6cyLfffsvHH8s0c+DAAU6ePHnP3KjMzMxcrzEvAQEBNGrUiCp3LWHu0KFDzrBCpUqVGDhwIOvWrWPSpEkcOnQIFxcXWrduDeT//pQGD0z8QoieFoij3ImLiwPkf1BLO7d0KcJgwKNXL4tfWy9CCLov787ZyLNsG7FNJX3FbFIiI0mPi8OlSRMAbl25grW9PZVq1cKYlUX8xYtU8vCgQpUqpMfHk3zjBi7NmqFZWZEUEoLRYKBy3bqAnIDrUK0aDoVc8jv6dkGuQYMG4ePjw82bN6lUqRLWt8tyiwKsxnZ3d+fGjRv3JLadO3cWKpa85BfDkCFDGDJkyH1/1rNnT3r27HnP49HR0bleY3F5e3szc+ZMJk2axKpVq3Le02x5vT+lgRrc1Mn58+cBdKnRf/PIEawdHMrVbP5ZB2fhG+7L9G7T6d+ov97hKGXY5V9+4cArr+Tc/2vaNP753/8AyEhMZMdzzxFx/DgANw4cYMdzz2G8vcLH98svOTFrVs5z93h7E7RlS7Hi0TQNTdNIT/93SpaHhwehoaE5969fv56r9Q1yy/D7TTzu169fzkS5O29vvfVWoeIqSAyF4eDgkOs15qVFixYEBgZy69atXI+fOHGCVq1a5dzv06cPoaGh+Pv7s3HjRkaOHJnr+Lzen1Lhfv3/Ze1WEsf4N23aJP7v//5PGAwGi143Kz1drO/QQfh9841Fr6unOYfmCD5CfLT/I71DUcqY+42vJkdEiNgLF3Lux1++LBJDQ4UQQhgyM0VMQIBIvz2+nBYXJ2ICAoTx9udA4vXr4ta1aznPjTl3TqRERRUqJiBn7tDmzZtFu3bthBBC1KpVS8TExOQc17lzZ7F161YhhBBTpkwR06ZNy/mZwWAQbm5uIiUlpVDXLkhsd8ovhqK4+zUKce8YvxByPN/b2zvn327Lli3Czc1NREZG5jpu8uTJom3btqJfv365HjfX+1MURRnjVy1+Hbm7u1t8GVn4n3+SlZyMx326ysqi81Hnmbl/JrWcajGzx0y9w1HKgYoPPZTTzQ9QpUEDKtWqBYCVjQ2uLVpQ4fb4sp2zM64tWqDd/hyoVLt2Tjc/gGuzZoXu5gcICwujdevWzJw5k2XLlgGy23/v3r05xyxatIjp06fTqFEjzp07x9SpU3N+duzYMTp16mSyFu348eNzWvMeHh6MHz/+gTEUxd2vMS+LFy/GwcGBxo0b06hRI+bNm8f27dupVq1aruNGjx7NmTNn8Pb2zvW4qd8fS9NEOai86+XlJU6ePKl3GLksWbIEV1fXfNekmsP2YcOIv3SJF86cyfmwKasS0hPouKQjmYZM9njvUeP6isllF+GytbXVOZJ/aZp23/HzCxcu8Pbbb7PtdsXO/IwfP57hw4fTu3dvc4RoNoV5jcVRkt6f/H4HNU07JYTwuvvxsv3JX4LduHEjp5CGpQghSIuOplrbtmU+6RuMBrr92I2QWyFsHr5ZJX2l3GvatCnDhw9/4OeOwWDAy8urRCS1wiroayyO0vz+ZCvbn/4lVHJyMgD161t2N+OEq1dJjYyk6V3dVmXR1N1TORt5lokdJtKsWjO9w1EUi8mvF3f06NEPLBpmbW3Nq6++auqwLKYgr7E4Svv7Azolfk3TrDVN+0zTtChN0xI1TdugaVqeA1mapj2kadoKTdNiNE1L0DTNV9O0UjslPSYmBoCGDRta9LoXVqzAysYG90cfteh1LW33ld0s+HsBbzzyBvP6ztM7HEVRlBJFrxb/e8BgoCOQvX5j5f0O1DTNHtgLZABNAGdgJGDZfnITCgoKAsDFxcWi171x4AA2lSphU0onpBREQGQAQ9YPoWfdnnze73O9w1EURSlxClK5zxxeBmYJIa4CaJo2FbisaVodIUTwXcf6IJP9f4QQmbcf+8dyoZpeYGAgmqZhZ2dnsWumx8eTHhdH2ylTLHZNSzMYDbzw6wukZabxxeNfYG1lmkIeiqIoZYnFW/yapjkDnsCp7MeEEFeABODh+zylFxAILL/d1X9B07QHVorQNO1lTdNOapp2MioqykTRm0bFihUtXu3p5uHDCKOR2n37WvS6ljT70GzORZ1j4/MbaVPD8qWQFUVRSgM9uvqdbv95667H44H7lbFzQyb/40ANYBQwXdO0kfc5NocQYrEQwksI4XX32ky9xcbGUr16dYte0/+bb6hQpQqONWpY9LqW8u3xb/no4EfM6DaDQU0H6R2OoihKiaVH4k+8/WeVux53Rrb673f8DSHEQiFEhhDiJLAKOUeg1DEYDERHR9+zL7U5GTMzSY2Oxk2HDYEsITI5knf3vItTBSemd5+udziKoiglmsUTvxAiHrgO5GwEr2lafWRr/+x9nuKL3AHwnlOZJUAzy97VypI1+qN8fTGkpdGylC9BuR+jMDJ642gcbB04/cpp7GwsN29CURSlNNJrVv9i4F1N0+ppmlYZmAfsFEIE3efY5UBVTdMm3l4G+DByVv9vFovWhLILS7Ro0cJi17y0di22VapQ9QHbVZZGPht92HVlFz8N+YmGrpZdHqkoilIa6TWrfy7gApwA7IDdyLF7bo/d/08IUQlACBGsadoAYAHwKXAT+EgIsV6PwIsrMjISa2vre/aCNqcb+/dT8aGHyly1Pv8If9b4r6F5teZqxz1FF2lpYG0NmZmQng5WViAEpKZCRgbY2YHRCElJ8me2tmAwQHKy/JmVlTwuIwOyV9lmbzBXoYI8V1oa2NjI6xiN/57X3R2qVtXvtSully6JXwhhAN65fbv7Z6uB1Xc9dgBoa5HgzMzPzy9nm0xLSAgOxpiRQYuXX7bI9SwlPSudURtH0bhqY46MPaJ3OEoZkp4OoaHg5weHDskEGxUFf/4JsbFQpYq8HxwMrq6wY0fe57Kykgk7K0v+vUIF+XhmpnzcxgY0Td6y/56VJY/JXu2blSX/XqGC/NIgBFSsKL9ElFVHjhxh2bJlGI1GGjduzPvvv8+BAwd4//33efjhh3n00Ufx8fHRO8xSS68Wf7llbW2Nu7u7xa5388ABrGxt8XziCYtd0xKeWvsU5yLPcfyl47g4WLYQklK6GY0QEgKXL8Nvv8GNG/LxoCDw95c/v5Ojo0z+2S3vli3BzQ3OnYOOHaFOHZmEMzPlsdkJPDvplxRZWVn06NGDnTt3UqlSJQICAvD29iYxMZFmzZqxevVqnJycMBgMdOvWjW3btuHs7GySa0+YMIE//viDmzdv5iopnFcMXbt2pWvXrgAMGDCA999/H03TcHJyIjk5mQYNGuT7GtesWcPgwXL+d2xsLElJSXh6egIwb948unXrxpQpU9i+fTvW1tbUqlWLL774gnbt5NSz3r17M27cOEaMGJFz7nPnztG3b1+uX79u8vfH4u63V29Zu7Vv3z6vrYwt7rPPPhN79+612PU2dO8u/hgwwGLXs4TtgdsFHyH6rOijdyhKCZaVJYS/vxDTpgnx5ptCPP20ELVqCSHbzP/eKlYUok8fIV58UYiuXYWYOVOIHTuEOH5ciEuXhDAY8r5GfnuhlzTLli0T06dPz7nfpUsXsXXrViGEEFOmTBEzZszI+dmiRYvErFmzTHbtgwcPivDwcCFTzr/yiyE75m+//VYIIYTh9j9ESkqKeOyxx+57nbtfY/ZjPj4+uR4bNWqUGD16dM6/3ZYtW0S1atVEVFRUznP69++f6znvvfeeeOedd4QQpn9/iiO/30HgpLhPTtQ9KVviVlISf0JCgvjoo4/EsWPHLHK99IQEsbpFC3H03Xctcj1LiE2JFR5feIguS7uItMw0vcNRSoj0dCFOnhTiu++E8PKSCd7B4d/k7ugoRM+eQjz3nBD9+wvxyy9CnD8vRGJi8a5bEhM/IGbMmCFatWol2rRpI/z8/IQQQnTv3l34+voKIYQIDw8XNWvWzHnOhQsXRLNmzXLuR0VFiQYNGpgltmwPiuGbb74RCxcuvO95+vS5/5f+O19jtrsT/9WrV4Wjo6OIj4/PddyIESPEhx9+KIQQIjExUVSuXFlEREQIIYQwGo3C09Mz57001/tTFEVJ/Kqr34KuXbsGgI2NZd72sKNHQQhav/aaRa5nCX1X9iU+LZ4jY4+opXvl2JkzcOIEnD8P27fDxYvycWtrOeGtWjV4801o1UqOw7drV7K63c3N3d2ds2fP8scffzBmzBiOHTuGr68vLW+v7AkNDcXDwyPneE9PT0JCQnLuu7m5IYQgJCTkniqj/fr1y1mWfKdevXqxYMGCAseYXwybNm1i/vz59OvXj4kTJ/Ltt9/y22+/sWPHDlJSUnJ1wWfLzMzM9RrzEhAQQKNGje6ZYN2hQwcOHz4MQKVKlRg4cCDr1q1j0qRJHDp0CBcXF1q3bg3k//6UBirxW5Dx9uBhkyZNLHK9q7//TuX69al0x3+u0mzJ6SWcCjvFuLbjqONcR+9wFAs6fRp+/12Oze/fL8fjQY6vN28OdevCG29A9+5ynF1PiYmJpKSk5FTnjIqKwtbWFmdnZ4xGI+Hh4bi4uODg4EBKSgrx8fHUqFEDTdOIi4vDaDRS9fZ0/bCwMJycnAq9zezo0aMBGDRoED4+Pty8eZNKlSphffvbj2wM5s/d3Z0bN27ck9h27txZqFjykl8MQ4YMYciQIbkeGzp0KEOHDs3zOdHR0bleY3F5e3szc+ZMJk2axKpVq3Le02x5vT+lgUr8FhQbG4ujoyOOFvhkMmRmEnb4MK4WrBdgTlHJUUzbO43+DfuzeOBivcNRzCwyEhYulLPrDx+G251ltGgBTz4Jzs7w7LNQEotRnjp1ilOnTjF58mRAtl6rV6/OoEGDSEtL44cffuC5556jWbNmXLp0id9//53p06djY2PD3r17SUlJwdvbG4Dly5fTo0cPOnfuXOR4slcRpWevEwQ8PDwIDQ3NuX/9+vVcrW+A1NRUHO6zk6epWvwFiaEwHBwccr3GvLRo0YLAwEBu3bqVq9V/4sQJWrVqlXO/T58+jB07Fn9/fzZu3EhAQECu8+T1/pQGKvFb0IULF6iQvZ7HzGL9/UEImr/4okWuZ26D1g0i05DJ0kFLsSpj9QgUORK/Ywfs3CmX0R0+LJeu1agBQ4fKmfQdO0LbUrCot3379jRr1izn/pAhQ7C9vfbO3t6el156KWdL7saNG/PSSy/ltFJ79+6d0zMIMGbMGJycnCis1atXM2HCBLZs2UK9evXw9PTE3t6e2NhYXF1dcXd3p27dumzbto0BAwawdOnSXK1po9FISEgIjRs3vufcpmrxPyiGwnJ2ds71GvNSv359Bg8ezKRJk1iyZAm2trZs3bqVXbt28eWXX+YcZ21tzYgRI/Dx8cHLyyvXaqz83p/SQCV+C0pOTrZYqd4bBw9SoUoVPPr0scj1zOm7E9/xd+jfvOr1KjWcyuYmQ+WRwQBr18pu/I0bZfe9lRX06wcLFkCjRvLvFtzWwiScnJxyJes7NwmzsrKiZs2aOfcrVqxIxYoVc+5nfyHIVqOIm2qFhYXRunVrrK2tWbFiBSC7/ffu3cuwYcMAWLRoET4+PrzMg6/SAAAgAElEQVTxxhs0adKE1av/LZ9y7NgxOnXqZLIW7fjx49lxu+CBh4cHTzzxBEuWLMk3hqK4+zXmZfHixUyePJnGjRtjY2NDjRo12L59O3dv6DZ69Gg+//zze+Iy9ftjcfeb8VfWbiVhVr/RaBSzZ88WR48etcj1fu7USeweM8Yi1zKnqOQoUe3TaqL3it45y3mU0iszU4jt24V4/XUhqlaVM+5dXIR46SUhfvhBiLAwvSMsnJI6q/9+zp8/f88StbyMGzdO7Nmzx5RhWURhXmNxlKT3R83qL8Hi4uLIysrCzc3N7Ne6dfUqmQkJuDRtavZrmduzPz9LpiGTlU+vVF38pdjZs7ByJXz1lSw5W6MGDBsG9erBa6/JSnSKeTVt2pThw4eTlJSU72RBg8GAl5cXvXv3tmB0plHQ11gcpfn9yaYSv4WcO3cOsMxSvvC//kKzsaHVhAlmv5Y5ffHXFxwMPsgbHd9QXfylUFgYzJsHS5bI2vSurvDYY/DUU/Dqq7JbXzE9kc9s+btnpt+PtbU1r5binTwL8hqLo7S/P6ASv8VkZWWhaZpFln4E79hBtbZtqWDBrX9NLTolmnlH59HNsxtfPP6F3uEoBZSVBR9/DJs3y7F7a2uZ8L/4AsaM+bdWvaIo+lGJ30JSUlKoWrVqzuxec0mNjib69Gk8SnE3FIDPJh8yDBmse3ad6uIvBfz9YcMG2bq/cUMut/vmG3j+eZn4FUUpOVTit5CQkBCzjTndKfLUKQCa3F4HXBp9c+wbtgVu461Ob1HTqeaDn6DoQgjYs0e28A8ckDvIjRolbz16lL7Z+IpSGgkhCr3bq2pKWUhERESBiksUV9jhwzjVrUt1Ly+zX8sckjOSmf/XfFo+1JLP+n6mdzjKfaSnw6RJcoLe44/LYjvDhsnyuUuWQM+e5SfpW1tbk5W9j66i6MBgMBS6WqFq8VtARkYGQggefvhhs17HaDAQvH07tR9/3KzXMaepu6cSnhTOrtG7sLYqR8XVS4HLl2HFCvjhB4iIkPXwd++G3r3LT6K/m5WVFUajkdTUVKytrQvd8lKUohJCYDAYMBqNhR4OVYnfAmJiYgByFe4wh7AjRzCkpeFSSqtJ/fLPL3x38jvGPDyGxlVL52soi4KD4b//haVL5WS9F1+ULf4H7IVSbjg6OmI0GjEYDHqHopQjmqZhZ2dXpDlQKvFbQPZSvrt3gzK1aD8/bJycaDxypFmvYw5Zxiw+PvIx7pXcWdh/od7hKMChQ3KHu7NnoUoVeOYZ+OADuL1BmXIHKysrNQlVKTVU4reAuLg4rKysilRzuzBu7N9Pra5dsS6Fa6a++OsL/ML9OPriUSrbld5liGVBQADMnQtr1sj7U6fCjBlggbmpiqJYgEr8FuLh4WHW8b9of3/iL13CvWtXs13DXI5eP8p7e95jcJPBPFr7Ub3DKbcuXIDBg+HSJahVS9bLHzFCjuUrilJ2qL4pC4iOjs7ZX9tcok6dAk2j4TPPmPU6piaE4IMDH1DRtqLq4tfJyZPg7S23vI2Kkmvvr1yR+9urpK8oZY9q8ZuZ0WgkIiICZ2dns14n4vhxqrVrR+W6dc16HVNb67+Wfdf2sen5TXhW8dQ7nHIlKgpmzZKFdhwc4NNP4T//kX9XFKXsUonfzG7dugVAvXr1zHaN9Ph4wo4cofn48Wa7hjkExwfj87sPPer0YHDTwXqHU25ER4OPDxw8KJfhvfCCHNOvU0fvyBRFsQTV1W9msbGxADRs2NBs17i6aRPCYMC1RQuzXcMcZu6fiRCCeX3m6R1KuWA0yh3ymjWDbdvgySdll/7atSrpK0p5ohK/mV27dg1N03BxcTHbNRKDgnCsVYtavXqZ7RqmduLGCVadXcWnfT+lo0dHvcMp85YuBQ8POZbfrRscPQrr18NDD+kdmaIolqa6+s0sMDAQTdPMtsbXaDQSeuAAnv36lZp1xJmGTJ5c8yQNXRvy+iOv6x1OmRYUBO++Cz//DPb2cte8gQP1jkpRFD2VjkxRilWsWJH69eub7fzXd+wgLSqqVFXrm//nfKJSonj9kdextTbvboXlVVoa9OsHDRvKsfwffoD4eJX0FUVRid/sYmJiqF69utnOH+3ri2ZjU2rq80ckRTDv6Dy8H/bm9Y6qtW8O27fLcrp79kD79hAYCOPHy93zFEVRVOI3o6SkJBITEwu9c1JhRPv64vHYY1Qwc1VAUxmyfggA8/vO1zmSsic4GDw9YcAAOZ7v7w/HjkEp+dVQFMVCVOI3o7CwMACzreGPDwwk9p9/qNG5s1nOb2qbL27m79C/6d+wP9UcVWUYU0lLg/nzZQGemBiYMAH274fmzfWOTFGUkkhN7jOjtLQ0AJo2bWqW819cvRoANzNv92sKmYZM3tv7Hu1qtGPFkBV6h1Nm7N4NgwbJ5P+f/8CcOWDmWlGKopRyqsVvRpGRkTg6OuJgplJoadHRuDRvjnMpmNj3xo43OB91nsUDF1PBpvRtIlTSJCXBO+/ICXyVKsHy5fDttyrpK4ryYCrxm9HZs2fNtkd3Vloa4X/9hWcpmNQXGBPIopOLaOvelvY12+sdTqm3Zg24usJXX8kW/s2bshKfoihKQeiS+DVNs9Y07TNN06I0TUvUNG2DpmluBXjeBE3ThKZpMywRZ3FZWVlRs2ZNs5z7wooVGNLSqNa+5CfS9/a+h6uDK78+96veoZRq8fHwyiswcqRs2W/aBO+/D7ZqRaSiKIWgV4v/PWAw0BHwuP3YyvyeoGlaHWAy4G/e0ExDCEFSUhINGjQwy/lj/P2xdnDArU0bs5zfVH7y/Ynfzv/GwicWUs/FfPsVlHULF8qd8lauhK+/hvBwOXtfURSlsPRK/C8D84QQV4UQt4CpwBO3k3telgLTgVhLBFhcERERZGVlUblyZZOfWwhB3PnzNHj66RJdrS8pPYnxm8dT06kmI1uN1DucUikhAcaNgzffBDc32LULXnsNSvA/u6IoJZzFPz40TXMGPIFT2Y8JIa4ACcB9p6drmvYKkCyEWG+RIE0gMDAQwCwT+8L+/JOU8HBq9uhh8nOb0vy/5mMURhY9uQhN0/QOp9T54QeoXh3WrYP//U+O5XftqndUiqKUdnos58suJ3LrrsfjgXuax5qmeQIzgE6FuYimaS8jexbw9LT8Pu82NjZYWVlRxwzbnp1fuhQo2cv4/on6h7lH5jL50ckMajJI73BKlbQ0mDEDPv8cqlSR9fW7ddM7KkVRygo9OgwTb/9Z5a7HnZGt/rstAWYLIW4U5iJCiMVCCC8hhFe1apYvFhMTE0PVqlWxsTH9d6uMhASqP/JIia3WJ4TgsRWPYWNlw8weM/UOp1RZvx7c3eWY/ty5siCPSvqKopiSxRO/ECIeuA60y35M07T6yNb+2fs8pS/wsaZp0ZqmRQNdgPc1TTtsiXiLKjAw0CxJPyUykrjz56k3eLDJz20qf1z8g8jkSCZ4TaBShUp6h1MqZGXB7Nlyxn56OmzdKnfVM2O1Z0VRyim9KvctBt7VNG0/EAPMA3YKIYLuc2ztu+7/AhwGPjdrhMWUnJyMOXoaAr77DoAaJXSwNzUzlTd3vkmf+n34tO+neodTKhw7Bs8/L2vtv/sufPghmKnmk6Ioim6Jfy7gApwA7IDdwCgATdNGAv8TQlQCEEKE3vlETdPSgQQhRIRFIy6E5ORkDAYDbdu2Nfm5o8+epYKzMw5uDyx7oIuBawZyPf4620duVxP6CmDDBvD2luP6v/wCzz6rd0SKUoakp8sylwkJcteqChXkLSIC/PygSRMQAgIC5GMtWsj/jAcPQuXKctwtLg5OnZLHVqwIISHy1qqV7Kq7dAk0DWrUgMxMuHhRVthycIDkZIiOlj+zspLnysiQS3SEgMhIsLcHR0d5rthYObHHxgZSUiA1FYYNkzN8TUiXxC+EMADv3L7d/bPVwOp8ntvTfJGZRnh4OIDJW/xZaWkkBgfT8tVXTXpeU7kSe4WDwQfp6NGRpm7m2Z+grIiJgREj5PK8IUNgwQKoW1fvqBSlBDEaISxMdoXZ2sqkuW8fGAyygtWNG7B3r9yK0tpaHnf9Ojz0kEz2cXEyuRaUpsmEbW8vE7CTE9S+3eEcGytvIM9pZSVjsLGRlbVsbeHhh2UcBoPcIcvTU/5HDwiQy3Hs7OSXhMREeOQReb0//5RfCho2lF8Sjh+Xe2m7uMjXcv06PP20yd9atUmPGfj6+gJQpcrd8xeLJ2TXLgxpadTq1cuk5zUFIQSTdkyihlMNdo3epXc4JdrZs7LGfng4fPKJ7N5XnSNKmSeETHr+/nDtmmwRR0TAxo0y2drawtWrcO6c/FliYt6J29VVtowjImSC9vSEevVkIh4wQCblkBCZbLt2lcdcuwaNGkH2Sqv0dPmlwdFRPq8c/SdUid9MHB0dsbOzM+k5/1myBM3GhipmqgZYHP938P/YFriNdc+sUxP68mA0wgcfyC10GzSAxYvhqaf0jkpRTMBggKAg2coODpbLUypWlF3fAQEymVtby2R7JysreXNzg5YtoX59eb93b/mfJCVFdo337Stbwba2svtd1akuFpX4zSApKYnate+ek1g8QgjS4+Ko1aNHiRs7T81M5cu/v8TF3oVhzYfpHU6JFBMDvXrJxs7o0fD99/JzUVFKBYNB/vJGRMjb4cOwf79MwqGhskv67ta5qys0ayZb1ba2cv/oBg3kuSpXhs6doWpVtXRFByrxm0FYWBitW7c26Tnjzp0jPTaWRi+8YNLzmsLcI3NJyUzh5MsnS3QJYb0cOiST/a1bclOdjz/WOyJFuY+MDLnEJDFRTlD77Tf5jVUI2U1+Z2u9ShU5Ga1VK+jSRU5Cc3GBgQPluLibm+w+V0ok9S9jYnFxcaSnpyMKM6mkAAIWL8aqQgUe8vIy6XmL62DQQT4+8jFvd3qb1tVN+2WntBMCxo+HH3+ENm3kRGE1gU/RXWwsXL4Mvr7w009yHDwiAi5ckK1xkI85OsoE/+STsgs+Ohp69oROneSYuVJqqcRvYomJsjChqVv8UadPY+/qinWFCiY9b3GN3zweozDyTud7FmiUa7duyc11NmyAdu3gwAH1WalYWGqq7I7/4w85ruTvL7vo72y5W1nJ7vhu3eRaUisreOEFOctc9d6VWSrxm1hUVBSapuHu7m6ycybfvEl6bCyd5s412TlNYfPFzVyOvcy3A76lmqPlyyKXVL/8AmPHyknCP/8sl+EqitkYjXKpyLVrcPKkbMWD3NXJaJR/r11bdjsNHChnwA8fLtelm2H3UKXkU4nfxPz9/bGzs8PWhLNOg7ZtA2trPErQbnxxqXG8uvVVetfrzQSvCXqHUyIIIXfUe+01Oby5fTuUoH8ypSwwGuHECVnQxdoaTp+WrfisLPlzZ2f5jbNLF7nTU8OG0Ljxv+vRFQWV+E0uMTHR5Fvxnlu6FHsXFyqUoG/nwzcM52biTX5+9ucSt8pADxERcij01Ck5rr9woZq1rxSTEHIs/vhx+PJLuTTu2jVZhQ7kjPqOHWHUKJngx4yBmjXL1Xp0pWhU4jexzMxMk47vp8fHk5mYSP1Ro0x2zuK6EnuF/df283zz5+ni2UXvcHR37hz07y9XNP33v7KhpSiFFhEhx+GPHYNVq2Qxm4wM+bMKFWQ1uClTZFnZhg3ljHpFKQKV+E0oJSWFxMREk5bqvbF/PwhBs7FjTXbO4vrPtv9QzbEaSwYv0TsU3X3xhSzKU7u2nMCnuvaVAhFClps9cwauXJF/v3xZ/szJSVaXe/RRmDoVOnQAHbYWV8oulfhN6OLFiwAmXct+4aefqNygARWrVzfZOYvjw/0fsuvKLr7s92W5rtBnMICPD6xeLSdEb92qZu0r+TAYYNs2OfMzKUmOy0dHy581aSK77B95BF56Sf5CqaI2ihmpxG9CqampANSrV88k58tMSiI+MBD3Rx81yfmKKzUzleW+y2no2pDXH3ld73B0Exkph1V375Z/Ll+uPqeVu2Rmyg1YPvtMFsTx85NrPEG25F9+WY7HP/64rB+vKBakEr8JJSQk4OLiQqVKpmkJh//9NwhBu6lTTXK+4pp7ZC43k25y9tWz5bZC39atcrMse3vYuVN+bisKBoNcSvfZZ3Kc/sYNudsayHXyb70lu+w7dpRlahVFRyrxm9DVq1dNuiPf9d27qVy/Ps4loEVw4NoB/nvov3g/7E2zas30DkcXq1bJGftOTrKaqRrPL8eyZ9yvXAlLl/6757utrSxXO22a/AVp00ZWwFOUEkQlfhMRQhAVFWWypXxZqakEb91Kja5dTXK+4hBC8MGBD3CwdeCT3p/oHY7FpaTIz/CTJ2HkSLmrnlqqVw5FRcn94GfPlsVxYmNldbuKFeVmDMOHyxZ9CauuqSh3U4nfRJKSkgBo166dSc4XceIECEHdErBv66/nfuXw9cP89txv1HCqoXc4FhURIbv2T56Un+0rVqhl0uVGZib89Rd8/bUc17ldjhtnZ7mF7DvvyNr1JuzlUxRLUInfRCIiIgDw8PAwyfnCDh/GoXp16vbvb5LzFdWNhBuM3jiannV7MqTpEF1jsbTly+VuekajGs8vNyIiYPNmmDVL7kyXkiLL2rq4wNy5/5a8VZRSTCV+E/H19UXTNFxcXIp9LqPBwLXNm/F47DE0nSfRTds7jQxDBrN6zipXFfq+/homTYIaNWQ1PhN9n1NKmuxJeZ9+KpfYRUXJx52dYcAAmDxZTspTyzaUMkQlfhNJSEjAwcHBJLPdr+/cSWZiIs6NG5sgsqI7HXaaVf6rmPPYHLrV6aZrLJaSkCAnYP/4IwweLLv2VU9uGZOQIGvdz5snx+nj4+UyDTc3WLJE1l424SZbilLSqMRvIhkZGTQ2UaKO8fPDztWVRiNGmOR8RZFpyGTgmoE0cGnA5M6TdYvDkoKD5dBtSoqcwPfSS3pHpJjMzZvw4Ydw9KislJeRAQ4OMGgQTJgAnTvLGfmKUg6oxG8CmZmZREVF0aZNm2Kfy2gwELxrF559+2Kj4+zgOYfmEJYUxsInFlLBuuzPUj54EJ57Tu6q97//yWV7SikmhEzys2fLCnmnTsnH3dzgk09kd06DBvrGqCg6UYnfBK5evYrRaEQIUexzXdmwgbTISNxMtDqgKMKTwvny2JeMaj2KSR0n6RaHJRiNMGwYbNwoK6X+/DOUkOrISmEZDHJN/f79MtEHBsrHu3SBZctkF76qea8oKvGbQvZSPlN09UefPo21vT21+/Yt9rmK6tmfn8VKs+KLx7/QLQZLSEmRlVN/+w3atYM9e1Rvb6mTng6LFsGFC7Bpk5yVb2srayl/9hl07aoq5SnKXVTiN4G4uDgqVapE1WJ+wAijkfDjx6k/eDA2dnYmiq5w1vqv5WjIUca2GUs1x7LbOjp8GMaNg9BQOYHP21vviJQCS0uTG97s3Anr18sa+A89BCNGyHX1TzwBOv3/UZTSQCV+E7hy5YpJSvUGb99OakQEHjq19lMzU/ngwAe0r9GexU8t1iUGS9i1Sy7H1jT4+29o21bviJQHSk+XEzF++UUWWMjKkuvpx4yR+9S/+KKcoKEoygOp/ykmEBkZSXUTDAxfWrMGNI1qOo3vv7L5FYLigvCb4IeNVdn71TAa4YMP4OOPZQnexYvVxmglWmam3Kf+yy/ltzUh5D71gwbBU0/JfZHLUW0JRTGVsvfpbmHJyckYjUY6duxYrPMIo5HksDDqDRqkSzf/riu7WOm/kicbPUnzas0tfn1zS0yU4/iXL8OUKXJit6rJUgIZDHDggKyedO0apKbK6kleXvDf/8ryiSrZK0qxqMRfTGFhYUDxS/VGnTlDakQE9YdYvixuljGL9/e+Tz3neqx9Zq3Fr29uFy/CkCFyKffkybJIm1KCCAEbNsjJeMHBcoKek5OcmPfJJ/Ibm0r2imIyKvEX04kTJ7CyssLV1bVY5zk5ezbWdnZUa9/eRJEV3Af7P+BM2BmOvngUJzsni1/fnGbOlCXW69WDEyfkcLBSQmzeDFu3wu7dcPWqTO6jR8Mrr8Cjj6pkryhmohJ/MSUlJeHo6FisOvbGzEySQkNxa9MGKwv3Px+9fpRPjnxC73q9ebT2oxa9tjkZDPDRR7J+i7u77D2uWVPvqBTOnJHj9WvWwNmzcundyJHw7bdyRr69vd4RKkqZpxJ/MaWkpNC8mM3IsKNHyUpJoe2UKSaKqmCEEHyw/wOqOlTlpyE/WfTa5nTtmpy1f/68HBaeNk1um67oJDJSzsb/+ms57lKhgpycN368XG9vgo2tFEUpOJX4iyExMZH4+Hjci7mhxz8//ECl2rVxadrURJEVzKKTi9gXtI9tI7ZRs3LZaA6fPQt9+shN1tT6fB2lpMhyiJMny8RvZQXdu8vyiLNmyW0PFUXRhWoHFUNAQAAAdsWYhZ9+6xbRvr441qpl0W1vfcN9eW3ba3Su3Zn+jfpb7LrmtGCBHBquXl2uz1dJ38KMRvltq0ULWVBn1CjZuh8zRs6s3LcPfvhBJX1F0ZkuLX5N06yBucAYwB7YBbwihIi+z7EDgHeA1oA1EABME0IctljAecjIyMDKyoqGDRsW+Rw3DhwAoN3UqSaK6sGEEEzbO42KthVZOmipxa5rLllZ8Oyz8Pvvsmjbr7+Co6PeUZUjO3bI1v2OHXD9ulwn+Z//wOuvq0IJilIC6dXV/x4wGOgIxAA/AiuB+zU9XYCvgf1AEvASsF3TtGZCiBDLhHt/0dHR1KxZE9tiFHi/tnkz1dq2xaVJExNGlr8lp5ew/fJ2Nj6/kaZulh1eMLXwcBg+HA4dknPEfvpJjedbRHAwbNkCK1fCsWOyat6YMXJWfufOqoqeopRgen1EvgzME0JcFULcAqYCT2iaVufuA4UQq4UQG4UQ8UKILCHEIuQXgA4WjvkeV69excmp6Mvf4i5eJOKvv6jaurUJo8rfsdBjvLLlFfrU78OQppavGWBKq1ZB7drg5yc32Fm1SiV9s8rIkC37zp2hbl1ZZKdqVfjiC/kN7Icf5Di+SvqKUqJZ/H+opmnOgCdwKvsxIcQVTdMSgIeB4Ac8vxXgBvg/4LiXkV8w8PT0LGbU90pKSiIlJYUKFYq+V33I7t2gaTQYNsyEkeVNCMF7e9+jom1F/vfk/yxyTXMQAhYuhHfeAWdnuRS8mIUTlbwIAcePw4QJcge81FRo2VKWzZ03Dyw8IVVRlOLT46t5dhP51l2PxwOV83uipmkPARuA+UKIwPyOFUIsBhYDeHl5iaKFmreIiAgAOnfuXKTnCyEI2bWL2n36UKVePVOGlqdFJxdxIOgA20Zso75rfYtc09RCQ+Vy7ytX4I03ZBW+Ynz3UvJy8iTMmCEL6wQGykkTHTrIJXkW7KFSFMX09OgYTbz9593b2TkDCXk9SdO0mshx/l3A++YJreBCQ0Oxs7OjWrWibV0bvG0bt65coZ6FSvQeDDrIa9teY0iTIaV2Fr+/v1wNdvUqfPih3LtFJX0TunFDfpPq1Usm+Z07oUEDOWkvPl7ujqeSvqKUehZv8Qsh4jVNuw60A3wBNE2rj2ztn73fczRNqwvsBTYKId6xTKT5O3nyJPb29kVegndhxQqwssK9iD0GhWEwGnhn9zs42DjwVf+vzH49c3jzTfjf/6BhQzmm36qV3hGVEZmZcpndTz/BunVySV7PnrB0KfTrB7Vq6R2hoigmptcsnMXAu5qm7UfO6p8H7BRCBN19oKZpTYE9wHIhxAyLRpkHIQTp6enUr1+07vKslBQSrl2j6ejR2FigyTrn0BxO3TzFfp/91K5S2+zXM6W0NLn76s8/Q5custprxYp6R1UG+PvL1v2aNTLZN2oEL78sl0Z07ap3dIqimJFec6DnApuBE8AN5Pr8UQCapo3UNC3pjmPfBWoBb2qalnTHbaSlg84WFxdHZmYm7dq1K9Lzg7ZsISslhUYvvGDiyO71w6kf+PDgh7z+yOv0qNvD7NczpT//lAV5fv9d1t0/dEgl/WKJiIDnn5fb3LZuLZfjNW8uZ+pfvAiLFqmkryjlgC4tfiGEAVmU555ueyHEamD1HffHAmMtF92DXbhwAYBaRewGPfP55zhUr46TGVYb3CkhPYGPDnyEq4Mrn/T+xKzXMrXvvoOJE8HNTX4BKOJ3LCUuTpbIPX9ernkUAjw94bffYMAAKEbVSUVRSie14LYI/Pz8sLKywrEI5eHir1whMymJhs8/b4bIcvvP1v+QkJHAmVfOULFC6Wgq37oFb70Fy5bJ+WW//irzlFIIBgNs2wZ//AFr10JyMjRpItdAPvccFHFCqqIoZYNK/EVgZWVFgwYNivTcy+vXY+fsTOuJE00cVW6vbXuN1f6rWTxwMQ1di15S2JL27YP+txccLFkCL76otmQvlMuXZSW9zz+Xyb52bbnmsUcPePxxvaNTFKWEUIm/kDIyMoiMjKRt27aFfm5qVBSXf/6Z+s88g7UZu1gvRl9k6ZmlNHBpwLi248x2HVMRQg4vv/UWODnBjz/K+jBKAcTFyb3sP/0UEhOhUiW55rFvX7kUQpUyVBTlLirxF9Lp06cxGo3UKMIOYxdWrMCYmUmd/uZbR5+UkcSzvzxL7cq1OfnySaxK+Ad/cLCcTxYaCq++Kqu/OjjoHVUJl5kJn3wCmzfLfYgzM+VkiHfflcle7VCkKEo+VOIvpJCQEDRNK/TEPiEENw8fpmb37lT38jJLbEajkTbftyEoPojTr5ymsl2+hRB1t2+f3Do3PBzefx8+/ljviEowoxFWr5YzHX/9FaKjZYKfPRtGjFDr7RVFKTCV+AspOTmZxo0bF7olHbJnD7cuXzbr9rtLzyzlStwVxrUdR+vqJbfCWny8HHI+cUL2Sh8+DBaqWlz6XL0qixgsWSLrFFeuLCc/vPCCnP1Ywnt0FEUpeVTiL4SMjAxCQkLo04fchWwAABmNSURBVKdPoZ976uOPsbKzw/3RR80QGRy/cZzXt7/OuLbjWDJoiVmuYQq+vjJnXbwod3Bdtkxu367cISlJLrf74AM5FmJnB4MHw0svyT3uVTEDRVGKQSX+Qjhz5gxGo5HKlQvXhZ4YHExqVBSNhw9HM0ML7WL0Rbr82IWaTjX5uv/XJj+/KWRkyJVkW7fKDd2OHYNHHtE7qhIkIwPWr5cb40REQHo6tGghvx0tXAguLnpHqChKGaESfyHcunULa2trmjRpUqjnXVixArsqVWjz9tsmjynDkMH4zeOxtbJl5ZCVONiWvJlxV6/KgnEnT8rZ+uvXg7293lGVAEaj7MJfv152hcTGypmNw4fLLwBFXDKqKIqSH5X4CyEsLIz69etjY1Pwty3+8mUCf/6ZRi+8gI2Jp6sLIRj/+3j+Dv2bPaP30L1ud5Oev7gyMuRw9IYN8NBD8s+hQ/WOqgTYsAGOHJHd+devg42NXG8/ciS0aaOKFyiKYlYq8RdQUlISwcHB9OhRuHr3l1avBk2j8UjTby3gvdGbVf6rmNdnXomrw3/hguza9/eHp56CVavkvLRy6+JFmehXrJB/r1hRzsYfOhT69AFbW70jVBSlnFCJv4D8/PwQQlCzZs0CPyczOZnrO3bQ+IUXqGLiaeu7r+xmjf8autfpztQu5lspUFhpaTBunGzUenjIFWgjRugdlU4iI+UbMWeO3Ove3l5+Cxo1CiZNKuffhBRF0YtK/AV069YtKleuXKhSvSdmzyYjOZmmY8aYNJYN5zbgs8mHPg36sGX4FpOeuzh8feGZZ+SY/ujR8P335XACelQULF8Oc+fKqnqaBm3bylrE8+dDlSp6R6goSjmnEn8BXb58mYYNGxZ4/X5GYiLBW7ZQuW5dKpmwuMqV2Cu8sOEFnCo48euwX7G11r+LOLvq3vbt0Lix3OJ9+HC9o7Kg6Gi59G7PHvmtx2iEqlVh8mR45x2oXl3vCBVFUXKoxF8AQUFBxMXF0b59+wI/5+KqVWBlRZfPPzdZHNEp0QxYM4DqjtXZNnIbTnZOJjt3UQgha8u8/DIkJMiJ6DNnQoUKuoZlGcHB8NFHEBQkKxAZDDLZf/WVHLd3d9c7QkVRlPtSib8AgoKCAGjRokWBjk8OC+P88uU0eu45XBo3NkkMNxJu0GlpJ1IyUvhr/F80rmqa8xbVrl0wdSr4+cHAgbJMfNeuuoZkfufPw7p1cPw47N4tk33z5vDllzLZF2L+h6Ioil5U4i+A4OBg6tevj7Ozc4GOPzp5MllJSTTx8THJ9ZMyknh81eOEJoTyy7O/6Jr0ExJkTf3PPpMV9377DZ5+WrdwzO/IEZnof/8dDh2Sj3XpAgsWQK9e0LKlvvEpiqIUkkr8DxAdHU1QUBBPPPFEgY5PCg0l5p9/qP344zh5eBT7+kkZSQxaO4jg+GB2jNxBv4b9in3OosjKgrFj5YZw6enw9tswZYpcn1+mGI1yE4GdO+WShEuX5DecPn1g1iw5K79NG72jVBRFKTKV+B/g77//BsDT07NAx5+ePx97Fxc6zZ5d7GvfSrtFg68akJCewO7Ru3Vbq79nj0z0/v7QrBns2AEFfDtKh8xM2arfuBEWLYKUFLmv/RNPyNuUKXJtoqIoShmgEv8DJCYmUqNGDWrUqPHAYy+uWUPo7t20eecdbIu5J3pCegJPrX2K+LR45jw2R5ekv3+/3FAnMhI6dZI93d26WTwM84iJkRMVli2T32yEgGrVZDd+t24y2au6woqilEEq8ecjOTmZy5cv07dv3wcea8jI4OJPP2Hn4kLT0aOLdd3zUed5ev3ThCWFcWDMAbp6WnbW3N9/wxdfwC+/yHX406bJbd9LdSVZISAgQO4S9Nlnsi4+yC6MRx6RsxMHDVJbBSqKUuapxJ+Pbdu2YTQaad68+QOPPbdkCck3b9Jv/XqsClHL/27B8cE8uvRRkjKS+GvcX3So1aHI5yqsoCBZW3//frkabfFiGDOmFFeTTUyEAwfg229h3z7Zpe/gAHXrwrPPwvTpZWzMQlEU5cFU4s9HeHg4Li4uD9yGN/TAAfy/+45Gzz+Pa7NmRb7e0etHGfrzUJzsnFj/7HqLJf1t2+TOr/v2ycJyTz8NP/4IBVzEUHJkZcmJeTt2yCV2SUlysl6NGnIv4Jkz5dpDE2+WpCiKUpqoxJ+HqKgoYmNjefbZZ/M9zpCRge/nn2NdoQKtXn+9yNd7e+fbfPn3l3jV9GLz8M1Ur2T+am8nT8Inn8gleba2cpnehAlyXlupYDRCYKAco//+e7nO3mAAJyc5Xj9qFLz+OjRpUsrHKRRFUUxHJf487Ny5E3t7e5o0aZLvcWe/+orE69fpu3Il9kVoImcaMpm2dxoL/l5AQ9eG7Bq9C2d78zW1jUa5b8yrr8ph7nr15JD3+PGloIVvNMK5c7JVv3UrbNokE721tUzu3brBf/8LHTuW4vEJRVEU81KJ/z6Sk5O5cuUKtWvXxiaf8fqA77/n/LJltH7tNdxaty70df4K+YuhPw8lMimSeX3mMaXzFDQztUyDg+Uy9IMH4coVcHGB99+XjxVjSoJ5GY1y5n1wsAx840a5/R9Aq1byNn683BFI7XSnKIpSICX1I19Xvr6+aJrGoEGD8jwm4do1/lmyBDtXV5q/9FKhr/HruV958fcXSclMYe2za3muxXPFCfm+smvRrFgBS5dCRgYMHiw3j+vSpQT2fqekwMqVcP263LN+1y45QU/ToH17uaa+bVt47TVwddU7WkVRlFJJJf67JCcn8+eff9K6dWvc3Nzue0xqdDQHJ06kYvXqPL56daFm8f8T+Q8jfxuJX4Qfg5sMZtGTi6jh9OAaAYURFSXz58yZMpdWrw5vvgnDhoGXl0kvVXRCwLVr8hvJn39CcjKcOSMn6Flby+76sWPBzQ1eeaUMlghUFEXRh0r8d9m0aRMpKSl07tz5vj9Pi4lhc//+CIOB/hs3YlfAgXGD0cBy3+W8ueNNkjOT+eqJr3jtkddM1rWflATffCMLz924IRvJLVrIVWvvvqvzkHf2JLzz52HvXrmlX1bWv2vp7ezgmWdkl32NGrJlX2pmGCqKopQuKvHfITk5mevXr1OnTh0euk8LMzM5mUNvvIExM5MOH3xA5Tp1CnTe745/x8dHPuZG4g2ea/4cH/X8iGbVir7sL1tCglyK7ucnu/TT0uRKtenTYeJEnRrJBoMs8bdzp/z7mTNyLb3BIH/u4iK/lQwdKscdvLzUFraKoigWpBL/HXbs2IGVlRXDhg2752ex589z5O23SYuOpveyZVRr2/aB5/sz5E/mHJ7DtsBtVLStyH6f/fSs27PI8Qkhi+ssWSIrzh48KDfMqV5dbg3/zDPQsGGRT184GRlyhn1wsCz1t26dLHEbFPTvBLxataBdu38T/MiRULt2CZxcoCiKUn6oxH/brl27CAgI4PHHH8fxrjr70X5+7Bs3DkNGBn1Xr8atVas8z2MwGth5eSc+v/sQnRJNk6pNWDZ4GSNbjcTWuvD97UFBsnxuZCQcOybvA3TvDnPmyF7xFi0KfdqCi42VywB27ZJb1FatCv/8I7sZhJDHZL9fPXrAuHGyMl6LFrIcrqL8f3vnHt1VdeXxzzdgTAjyiAK2BYnge5wGBLUqTFEYZaij46O2FB+F+hi7uuys8VUXLh0f9VE7nXbs6ky1io6ta3QqzOgojqKiOCI4gCA4I/IwKvIKJEBCNITs+eOc4OWaHwSE/JLf3Z+17srvnn3uued7k/z2vefse7bjOB0Kd/zAunXreOuttygvL+fkk0/eUd5YX88799/P0scfp9dRR3HiLbfkdPoLVi/g1pm3smjtIqo2VdGvrB/XnnIt9465ly5FbVv/fdu28BA9ZQrMng3V1bBiRbCVl8NFF8EZZ4TX1ffZ6Hh9PaxdGyLpp06F2towLL9kCSxa9Llzh/CkPnx4iKwfOjTkor/wQn+KdxzH6UTkxfFL6gLcA3wfKAFeAK4ys+oc9ccCfw8MApYDf2tmL+yLvixbtoxp06ZRXl7OpEmTKCoqwpqb+fill5g9eTJN9fUcO3EiX7/mGroUF+84zsx47v3neK3qNV6tepU5q+YAMO6Icfzh/D9w6oBTcwbumYU4t2XLYPVqePFFmD49xLs1NoY6ZWVhnfyRI4N/3eOnerPgxOfODa/ENTcHZ/7MM2Hyf+PG0Im6up2PKykJw/PHHx+e7s8+G0aMCCv95HjLwXEcx+k85OuJ/yfAucDJwAbgYeAx4C/SFSUNAqYCVwJPAt8Gpkn6EzP7YG87YGbMmzePZ599ltLSUi655BK2VVfz5t13s/Hdd2lYu5aDKys55rLLGHjWWdQ11jF9yX/w9HtP00wzL698mTV1ayhSEeOOHMeUc6cwqmIUFb0qAKipCVPfZmGYfsaMkM++tDS8ol5bG/pRVBTm5fv1CylwzzoLKitTq+g1NcHq9WHuvLY2TPSXlEBxcRiGnzkTBg0KtoULw1CB2ed3ES0ceGC4AaisDI59yJAQJDB+PAwcGDrh78c7juMUNLLkUG57nVSqAm43s4fi/mBgGVBhZlWpurcBZ5jZyETZLGCGmd3WlvMNHTrUnv7jUxhQtXIFb89fQENjIw3bm+heW0uPpUvp2dxE04cfs7ULbOxTRsO3hvF22UZe+eg1SqyUdcUfUFTXg+1lmzms+escXTyShoXDKFl1MgO+9jU2bBDz5m6nrLiR9U29+XRLIw2U0Z0t1HEQAw/4GAEjTmjg6IOrOWTlXI7tvZoTh2ynW/364LwHDAjOedWq8I77oYeG0P2amtziSkuDgz/mmDC3/tlnYc7gvPOCI9+0CY48Mjj78nIfknccx8kIkuaZ2RdWb2n3J35JvYDDgHktZWa2XNJmoBKoSh1SmawbmR/L28S61av59Z23063icOpWrKH7wD5sfud9jq1ZzYKtjfTvso55vRtYclI9i5sHoe2iZu2TsKECtpzGYcv6staGUbniIObXn8OnTbW8yKGM5TnqWc9itnAwGzibKvrVr6GYbQzmffpSzVdYxUA+otu2htCZOYSX6s2Ck9/QPzjvmpqQWKZfv7DftSuMHh2G5aurw9P96aeHoYC6uvCE37+/r0nvOI7j7BHt/sQvaQDwITDIzFYmyquAyWb2+1T9l4DXzezWRNltwGlmNmYX57mSMD0AcDyweN+p6PAcArQaL1GAZEkrZEtvlrRCtvRmSSvkT+9AM+uTLszHHP+W+LNnqrwXsDlH/bbW3YGZPQA8ACDpf1ob7ihUsqQ3S1ohW3qzpBWypTdLWqHj6S1q7xOaWS3hif+ElrIYwNcDWNTKIQuTdSNDY7njOI7jOHtAuzv+yAPAjZIOl9QDuBf4rxxR+v8CDJc0XtIBksYDw4BH26+7juM4jlMY5Mvx3wM8A7wFrAK6ABcDSJogacfL5Wa2HDgfuJkwvH8zcN4evsr3wL7pdqchS3qzpBWypTdLWiFberOkFTqY3ry8zuc4juM4Tn7I1xO/4ziO4zh5wB2/4ziO42QId/yO4ziOkyHc8TuO4zhOhihoxy+pi6T7JK2XtEXSU5I6fIo5SfdKWiJps6RPJD0oqTxV51JJyyVtlTRH0rCUfbikudG+XNLFKXtfSVPjdVkfz5nXvwdJRZLekGSS+ifKC1HrGElvSqqTVC3pNwlbQemVdKikJ2JfaiS9LKkyYe+0eiV9V9Ks+L/a1Ip9bPxfbpC0WNKZKfsRkmZIqpf0saRrU/Zukh6WVBu3hySVpupcL2lVbGNGXBelXbVKGhd/r9XxdzxL0shUnU6jdXd6U/Wujt9ZN6fKO65eMyvYDZgMLCWk8+0JPAVMz3e/2tDvuwiLFB0A9AGmA08n7COAeuBM4EDgBmAt0CPaewLrgRuj/c+BOuCURBsvErIe9ozXZylwY551XwvMAAzoX6hagVFALXBh7HMJcEIB650a+9QbKAZ+BnwEIW9VZ9YLnAWMByYBTSnbIGAr4VXlYmBC1FoR7V2A/wXuB7oRFipbB3wn0caDwBtAP6Bv/PxPCfuEeMwJsY1/JCxP3qWdtU4AziOsqtoVuDr+ngZ0Rq2705uoM5CQYG4RcHOivEPrzcsXQXtthIQ/P0jsDyY4lYH57tse6hgLbE7sPwo8ltgXYTXEy+L+xKhdiTqPAVPi58PjdRicsP8AWJlHjUcBy4Eh7Oz4C1HrbOCeHLZC1LsIuDKxf3Ts4yGFopdwM5d2hrcBs1Jls4Bb4+fTCTcG3RP2O4BX4udSoAEYnbCPjseUxP1XgTsS9u7R/s321Jqj3hrg/M6sdXd6CQ8q3wFmsrPj79B6C3aoXzmyABIWAWpzZr8Owmh2XqJ4p4yFFv4qFvC5rkpgQSxvYX7Kvilej6S9QmElxXYlDss+DFxHeBJOUmhay4CTgK6S5seh0ZmSWtbxLii9kfuACyT1kVRCSJ71uplVU5h6W9hdZtFKYKmZ1eWwH00YDZqXspcSbpS/cI7Y1vvk+TtO0p8SbuzeiUUFp1XSVUC9mT3RirlD6y1Yxw8cFH9uSpXXEvICdAokXQD8NfDjRPFB7FrX3tohP9fmx8AaM5vWiq3QtPYm/N+NB74PfBV4AXgu3qwWml6A/yYMfa4jDP+eD1wRbYWot4V9oY1UnZbPbW2j3ZHUlzCt+nMzez8WF5RWSYcRVpH9YY4qHVpvITv+Pc0C2OGQ9G3CPNA5ZjY/YdpdxsK9tbfY2g1JRxDm9n+Uo0rBaE2dc4qZLTKzRuBuQjzHqRSY3jiaM4Mw796TMFf5U2CWpH4UmN4U+0IbqTotn9vaRrsi6avAK4Sb2ZsSpkLT+jvgTjNblcPeofUWrOO3Pc8C2KGQNBH4LfCXZvZKyrxTxkJJIsyNL0zYh6SOGZqy90xFiA4FPjCz9B3m/mYEIYBxsaRqwnAXwCJJP6SwtBLP+QFhXnonU9wKSi9QTpiHv9/MNptZo5n9jvDdcwqFpzfJ7jKLLgSOitM/rdnfAz5NtTGUMDe8tLVzSOoOHEkespdKqiDEMEw3sx+lpmcKSishyPSuOFVXDZwG3CRpVrR3bL37Mygi3xshqv89whdPD+DfgOfz3a829PsaYANwYg77CMKQ6WhCtPB17BwJ3YsQCX19tI+m9UjoP8brcni8Tj/Jg9ZuQP/E9g2CAxxOCGYpGK2J/lwPfAwcR4iAvgFYTbi7L0S97xGim8ui3klAIyHqvVPrJUxhlBDeSmiKn0sIQYqDCcFY4wkjOuNpPar/V4S53SFR+3cT7T8IvE6I+u4bP/9zwj4hHjM0tvFLYAn7J6p/V1qPiX/Td+7i2E6jtQ16+6e22YS3Vfp1Br15+SJory1e/J8D1YRhk6nAIfnuVxv6bcA2whfcji1V51JgBeEOcS4wLGU/MZY3xHoXp+x94/XYEq/Pz4CiDqC9gkRUfyFqjV8ctxOinmsJQ6NDCljvscB/xr5sIgQsnVsIeglxGtbKVhHtY+OXdUP8eWbq+COAlwg3CJ8A16XsZYTA19q4PQSUpurcEI/dGtsa3N5agSnxc11qm9AZtbbld5uqO5NEVH9H1+vZ+RzHcRwnQxTsHL/jOI7jOF/EHb/jOI7jZAh3/I7jOI6TIdzxO47jOE6GcMfvOI7jOBnCHb/jOI7jZAh3/I7j7BZJh0mqi0uy7m0bkvSGpNFxf9Su8pzv5Tlmt7TvOE7ruON3nAwQMwB+Fp33Jklvx1wQbcLMPjSz7mb2yZfoxkWE9KYvfYk2dsffAf+wH9t3nE6PO37HyQ53mFl34GDgEeDxmCSpvfgbwjKl+5MXgd6SztjP53GcTos7fsfJGGbWRHDAXUkkwJE0RdJHkrZIelfS9xK2CkkmqX+i7GpJ78URhDcljcx1zpiJ7xsEx5yrzvB4/ivi/kxJv5A0LfZpuaTRksZIWixpc7S1pDjFzJoJS5v+1V5dHMfJAO74HSdjSCoGro67SxOm1wk3Ar0IuQQekXRcjjbGA3cQ1tk/mHAj8bykgTlOewJQY2ZrcrR3DmE9/yvMLDkqcAlwT+zTE8BjwJXAnxHWiD+akNQqyTt8MSue4zgRd/yOkx0mS6olJIy5E7jczHakqDazh8xsg5ltN7N/JaSvHpWjrYnAb81sjpk1mdlDsf73ctTvTY484pKuAX4NjDWz51PmJ+M5tgO/B74C3GdmG81sI+FmYXjqmM2EdMCO47SCO37HyQ4/NbNewCHAc8DpLQZJRZJuTwzd1wKVQJ8cbQ0AVqbKlsfy1qghpM1NU0RInz3FzN5uxb468XlrjrKD2JkewMYc/XCczOOO33EyhpnVAJcD35J0biweH8suAHrHG4SFhBTCrfERYag9yaBY3hoLCEF3h6bKm4FvApMk3bQnOnbB8fF8juO0gjt+x8kgcZj8F8BdkooIT8lNwHqgSNIkwhN/Lh4BrpJ0kqSukiYS4gMez3G+NcAcYEwrtv8DRgKXS7p771WFkQtgNPDvX6Ydxylk3PE7Tnb5FWHO/FLgUYJjXgasAo4DZuU60MweB24jzLtvIAQLjjOzql2c75eEUYXW2vuA4PzPkfQbSblGGnbHGGDTfl4rwHE6NTKzfPfBcZwMEJ35G8BkM3t5P53jDeAWM5uxP9p3nELAHb/jOI7jZAgf6nccx3GcDOGO33Ecx3EyhDt+x3Ecx8kQ7vgdx3EcJ0O443ccx3GcDOGO33Ecx3EyhDt+x3Ecx8kQ7vgdx3EcJ0P8P0bZ72I6GO5FAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KGkbsqN6slFA",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 400
        },
        "outputId": "72c8cd40-5e01-4ab8-9c4b-fc768cf147c7"
      },
      "source": [
        "plt.figure(figsize = (8,6))\n",
        "plt.plot(WD_21_NEWTON['R (km)'],WD_21_NEWTON['p (N/m2)'],color ='red',label =r'p(0) = $10^{21}$ (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_22_NEWTON['R (km)'],WD_22_NEWTON['p (N/m2)'],color ='blue',label =r'p(0) = $10^{22}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_23_NEWTON['R (km)'],WD_23_NEWTON['p (N/m2)'],color ='green',label =r'p(0) = $10^{23}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_24_NEWTON['R (km)'],WD_24_NEWTON['p (N/m2)'],color ='brown',label =r'p(0) = $10^{24}$  (NEWTON)', linestyle='-')\n",
        "plt.plot(WD_25_NEWTON['R (km)'],WD_25_NEWTON['p (N/m2)'],color ='grey',label =r'p(0) = $10^{25}$  (NEWTON)', linestyle='-')\n",
        "\n",
        "plt.plot(WD_21_TOV['R (km)'],WD_21_TOV['p (N/m2)'],color ='red',label =r'p(0) = $10^{21}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_22_TOV['R (km)'],WD_22_TOV['p (N/m2)'],color ='blue',label =r'p(0) = $10^{22}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_23_TOV['R (km)'],WD_23_TOV['p (N/m2)'],color ='green',label =r'p(0) = $10^{23}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_24_TOV['R (km)'],WD_24_TOV['p (N/m2)'],color ='brown',label =r'p(0) = $10^{24}$ (TOV)', linestyle=':')\n",
        "plt.plot(WD_25_TOV['R (km)'],WD_25_TOV['p (N/m2)'],color ='grey',label =r'p(0) = $10^{25}$ (TOV)', linestyle=':')\n",
        "\n",
        "plt.yticks(size = 13)\n",
        "plt.xticks(size = 13)\n",
        "\n",
        "\n",
        "plt.ylabel(r'$p (N/m^2)$', size = 13)\n",
        "plt.axis([1E-3,1E+5,1E+7,1E+26])\n",
        "#plt.grid(True)\n",
        "plt.yscale('log')\n",
        "plt.xscale('log')\n",
        "plt.xlabel('Raio (km)', size = 13)\n",
        "plt.legend(loc = 3, prop = {'size':10.5})\n",
        "plt.savefig('rP_regimequalquer-all-WD.png')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gEe06Vxg16or"
      },
      "source": [
        "#Massa-Raio"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A0dPqHuH3DX9"
      },
      "source": [
        "WD_regimequalquer_TOV = pd.DataFrame(columns=['m (Msol)','R (km)','p (N/m2)'])\n",
        "WD_regimequalquer_TOV['m (Msol)'] = float(list(WD_21_TOV['m (Msol)'])[-1]),float(list(WD_2e21_TOV['m (Msol)'])[-1]),float(list(WD_4e21_TOV['m (Msol)'])[-1]),float(list(WD_22_TOV['m (Msol)'])[-1]),float(list(WD_2e22_TOV['m (Msol)'])[-1]),float(list(WD_4e22_TOV['m (Msol)'])[-1]),float(list(WD_23_TOV['m (Msol)'])[-1]),float(list(WD_2e23_TOV['m (Msol)'])[-1]),float(list(WD_4e23_TOV['m (Msol)'])[-1]),float(list(WD_24_TOV['m (Msol)'])[-1]),float(list(WD_2e24_TOV['m (Msol)'])[-1]),float(list(WD_4e24_TOV['m (Msol)'])[-1]),float(list(WD_25_TOV['m (Msol)'])[-1]),float(list(WD_2e25_TOV['m (Msol)'])[-1]),float(list(WD_4e25_TOV['m (Msol)'])[-1]),float(list(WD_26_TOV['m (Msol)'])[-1]),float(list(WD_2e26_TOV['m (Msol)'])[-1]),float(list(WD_4e26_TOV['m (Msol)'])[-1]),float(list(WD_27_TOV['m (Msol)'])[-1]),float(list(WD_2e27_TOV['m (Msol)'])[-1]),float(list(WD_4e27_TOV['m (Msol)'])[-1]),float(list(WD_28_TOV['m (Msol)'])[-1]),float(list(WD_2e28_TOV['m (Msol)'])[-1]),float(list(WD_4e28_TOV['m (Msol)'])[-1]),float(list(WD_29_TOV['m (Msol)'])[-1]),float(list(WD_2e29_TOV['m (Msol)'])[-1]),float(list(WD_4e29_TOV['m (Msol)'])[-1]),float(list(WD_30_TOV['m (Msol)'])[-1]),float(list(WD_2e30_TOV['m (Msol)'])[-1]),float(list(WD_4e30_TOV['m (Msol)'])[-1]),float(list(WD_31_TOV['m (Msol)'])[-1]),float(list(WD_2e31_TOV['m (Msol)'])[-1]),float(list(WD_4e31_TOV['m (Msol)'])[-1]),float(list(WD_32_TOV['m (Msol)'])[-1]),float(list(WD_2e32_TOV['m (Msol)'])[-1]),float(list(WD_4e32_TOV['m (Msol)'])[-1]),float(list(WD_33_TOV['m (Msol)'])[-1]),float(list(WD_2e33_TOV['m (Msol)'])[-1]),float(list(WD_4e33_TOV['m (Msol)'])[-1]),float(list(WD_34_TOV['m (Msol)'])[-1]),float(list(WD_2e34_TOV['m (Msol)'])[-1]),float(list(WD_4e34_TOV['m (Msol)'])[-1])\n",
        "#,float(list(WD_26_TOV['m (Msol)'])[-1]),float(list(WD_27_TOV['m (Msol)'])[-1]),float(list(WD_28_TOV['m (Msol)'])[-1]),float(list(WD_29_TOV['m (Msol)'])[-1]),float(list(WD_30_TOV['m (Msol)'])[-1]),float(list(WD_31_TOV['m (Msol)'])[-1]),float(list(WD_32_TOV['m (Msol)'])[-1]),float(list(WD_33_TOV['m (Msol)'])[-1]),float(list(WD_34_TOV['m (Msol)'])[-1])\n",
        "#float(list(WD_18_TOV['m (Msol)'])[-1]),float(list(WD_19_TOV['m (Msol)'])[-1]),float(list(WD_20_TOV['m (Msol)'])[-1]),\n",
        "#"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hN2nVSNF4E3i"
      },
      "source": [
        "WD_regimequalquer_TOV['R (km)'] = float(list(WD_21_TOV['R (km)'])[-1]),float(list(WD_2e21_TOV['R (km)'])[-1]),float(list(WD_4e21_TOV['R (km)'])[-1]),float(list(WD_22_TOV['R (km)'])[-1]),float(list(WD_2e22_TOV['R (km)'])[-1]),float(list(WD_4e22_TOV['R (km)'])[-1]),float(list(WD_23_TOV['R (km)'])[-1]),float(list(WD_2e23_TOV['R (km)'])[-1]),float(list(WD_4e23_TOV['R (km)'])[-1]),float(list(WD_24_TOV['R (km)'])[-1]),float(list(WD_2e24_TOV['R (km)'])[-1]),float(list(WD_4e24_TOV['R (km)'])[-1]),float(list(WD_25_TOV['R (km)'])[-1]),float(list(WD_2e25_TOV['R (km)'])[-1]),float(list(WD_4e25_TOV['R (km)'])[-1]),float(list(WD_26_TOV['R (km)'])[-1]),float(list(WD_2e26_TOV['R (km)'])[-1]),float(list(WD_4e26_TOV['R (km)'])[-1]),float(list(WD_27_TOV['R (km)'])[-1]),float(list(WD_2e27_TOV['R (km)'])[-1]),float(list(WD_4e27_TOV['R (km)'])[-1]),float(list(WD_28_TOV['R (km)'])[-1]),float(list(WD_2e28_TOV['R (km)'])[-1]),float(list(WD_4e28_TOV['R (km)'])[-1]),float(list(WD_29_TOV['R (km)'])[-1]),float(list(WD_2e29_TOV['R (km)'])[-1]),float(list(WD_4e29_TOV['R (km)'])[-1]),float(list(WD_30_TOV['R (km)'])[-1]),float(list(WD_2e30_TOV['R (km)'])[-1]),float(list(WD_4e30_TOV['R (km)'])[-1]),float(list(WD_31_TOV['R (km)'])[-1]),float(list(WD_2e31_TOV['R (km)'])[-1]),float(list(WD_4e31_TOV['R (km)'])[-1]),float(list(WD_32_TOV['R (km)'])[-1]),float(list(WD_2e32_TOV['R (km)'])[-1]),float(list(WD_4e32_TOV['R (km)'])[-1]),float(list(WD_33_TOV['R (km)'])[-1]),float(list(WD_2e33_TOV['R (km)'])[-1]),float(list(WD_4e33_TOV['R (km)'])[-1]),float(list(WD_34_TOV['R (km)'])[-1]),float(list(WD_2e34_TOV['R (km)'])[-1]),float(list(WD_4e34_TOV['R (km)'])[-1])\n",
        "#float(list(WD_18_TOV['R (km)'])[-1]),float(list(WD_19_TOV['R (km)'])[-1]),\n",
        "#\n",
        "#"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tuwqx2Tp4DNu"
      },
      "source": [
        "WD_regimequalquer_TOV['p (N/m2)'] = float(list(WD_21_TOV['p (N/m2)'])[0]),float(list(WD_2e21_TOV['p (N/m2)'])[0]),float(list(WD_4e21_TOV['p (N/m2)'])[0]),float(list(WD_22_TOV['p (N/m2)'])[0]),float(list(WD_2e22_TOV['p (N/m2)'])[0]),float(list(WD_4e22_TOV['p (N/m2)'])[0]),float(list(WD_23_TOV['p (N/m2)'])[0]),float(list(WD_2e23_TOV['p (N/m2)'])[0]),float(list(WD_4e23_TOV['p (N/m2)'])[0]),float(list(WD_24_TOV['p (N/m2)'])[0]),float(list(WD_2e24_TOV['p (N/m2)'])[0]),float(list(WD_4e24_TOV['p (N/m2)'])[0]),float(list(WD_25_TOV['p (N/m2)'])[0]),float(list(WD_2e25_TOV['p (N/m2)'])[0]),float(list(WD_4e25_TOV['p (N/m2)'])[0]),float(list(WD_26_TOV['p (N/m2)'])[0]),float(list(WD_2e26_TOV['p (N/m2)'])[0]),float(list(WD_4e26_TOV['p (N/m2)'])[0]),float(list(WD_27_TOV['p (N/m2)'])[0]),float(list(WD_2e27_TOV['p (N/m2)'])[0]),float(list(WD_4e27_TOV['p (N/m2)'])[0]),float(list(WD_28_TOV['p (N/m2)'])[0]),float(list(WD_2e28_TOV['p (N/m2)'])[0]),float(list(WD_4e28_TOV['p (N/m2)'])[0]),float(list(WD_29_TOV['p (N/m2)'])[0]),float(list(WD_2e29_TOV['p (N/m2)'])[0]),float(list(WD_4e29_TOV['p (N/m2)'])[0]),float(list(WD_30_TOV['p (N/m2)'])[0]),float(list(WD_2e30_TOV['p (N/m2)'])[0]),float(list(WD_4e30_TOV['p (N/m2)'])[0]),float(list(WD_31_TOV['p (N/m2)'])[0]),float(list(WD_2e31_TOV['p (N/m2)'])[0]),float(list(WD_4e31_TOV['p (N/m2)'])[0]),float(list(WD_32_TOV['p (N/m2)'])[0]),float(list(WD_2e32_TOV['p (N/m2)'])[0]),float(list(WD_4e32_TOV['p (N/m2)'])[0]),float(list(WD_33_TOV['p (N/m2)'])[0]),float(list(WD_2e33_TOV['p (N/m2)'])[0]),float(list(WD_4e33_TOV['p (N/m2)'])[0]),float(list(WD_34_TOV['p (N/m2)'])[0]),float(list(WD_2e34_TOV['p (N/m2)'])[0]),float(list(WD_4e34_TOV['p (N/m2)'])[0])\n",
        "#float(list(WD_18_TOV['p (N/m2)'])[0]),float(list(WD_19_TOV['p (N/m2)'])[0]),\n",
        "#"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hxjlhC4EE4BG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "00fb0c08-a2fa-4c6f-97a9-3cf67b8ba7f8"
      },
      "source": [
        "WD_regimequalquer_TOV"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>m (Msol)</th>\n",
              "      <th>R (km)</th>\n",
              "      <th>p (N/m2)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.376800</td>\n",
              "      <td>14511.50001</td>\n",
              "      <td>1.000000e+21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.430210</td>\n",
              "      <td>13157.50001</td>\n",
              "      <td>2.000000e+21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.488767</td>\n",
              "      <td>11907.00001</td>\n",
              "      <td>4.000000e+21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.574097</td>\n",
              "      <td>10402.50001</td>\n",
              "      <td>1.000000e+22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.644535</td>\n",
              "      <td>9370.00001</td>\n",
              "      <td>2.000000e+22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.719841</td>\n",
              "      <td>8422.50001</td>\n",
              "      <td>4.000000e+22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.826359</td>\n",
              "      <td>7291.50001</td>\n",
              "      <td>1.000000e+23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>0.911699</td>\n",
              "      <td>6522.00001</td>\n",
              "      <td>2.000000e+23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.000596</td>\n",
              "      <td>5821.00001</td>\n",
              "      <td>4.000000e+23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.122589</td>\n",
              "      <td>4992.00001</td>\n",
              "      <td>1.000000e+24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.217432</td>\n",
              "      <td>4433.50001</td>\n",
              "      <td>2.000000e+24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.313713</td>\n",
              "      <td>3928.50001</td>\n",
              "      <td>4.000000e+24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.441969</td>\n",
              "      <td>3337.50001</td>\n",
              "      <td>1.000000e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1.538791</td>\n",
              "      <td>2943.00001</td>\n",
              "      <td>2.000000e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1.634639</td>\n",
              "      <td>2590.00001</td>\n",
              "      <td>4.000000e+25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1.758659</td>\n",
              "      <td>2180.00001</td>\n",
              "      <td>1.000000e+26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1.849589</td>\n",
              "      <td>1909.50001</td>\n",
              "      <td>2.000000e+26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1.937342</td>\n",
              "      <td>1669.00001</td>\n",
              "      <td>4.000000e+26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2.287356</td>\n",
              "      <td>871.00001</td>\n",
              "      <td>1.000000e+28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2.125688</td>\n",
              "      <td>1211.50001</td>\n",
              "      <td>2.000000e+27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2.198931</td>\n",
              "      <td>1052.50001</td>\n",
              "      <td>4.000000e+27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2.287356</td>\n",
              "      <td>871.00001</td>\n",
              "      <td>1.000000e+28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2.347320</td>\n",
              "      <td>753.00001</td>\n",
              "      <td>2.000000e+28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2.400833</td>\n",
              "      <td>650.00001</td>\n",
              "      <td>4.000000e+28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2.460907</td>\n",
              "      <td>534.00001</td>\n",
              "      <td>1.000000e+29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2.497677</td>\n",
              "      <td>459.00001</td>\n",
              "      <td>2.000000e+29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2.526414</td>\n",
              "      <td>394.00001</td>\n",
              "      <td>4.000000e+29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2.551129</td>\n",
              "      <td>321.00001</td>\n",
              "      <td>1.000000e+30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2.559008</td>\n",
              "      <td>274.50001</td>\n",
              "      <td>2.000000e+30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2.556843</td>\n",
              "      <td>234.50001</td>\n",
              "      <td>4.000000e+30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>2.537398</td>\n",
              "      <td>189.50001</td>\n",
              "      <td>1.000000e+31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>2.509246</td>\n",
              "      <td>161.00001</td>\n",
              "      <td>2.000000e+31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>2.468785</td>\n",
              "      <td>137.00001</td>\n",
              "      <td>4.000000e+31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>2.395469</td>\n",
              "      <td>110.00001</td>\n",
              "      <td>1.000000e+32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>2.324536</td>\n",
              "      <td>93.00001</td>\n",
              "      <td>2.000000e+32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2.240190</td>\n",
              "      <td>78.50001</td>\n",
              "      <td>4.000000e+32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>2.108695</td>\n",
              "      <td>63.00001</td>\n",
              "      <td>1.000000e+33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>1.995192</td>\n",
              "      <td>53.00001</td>\n",
              "      <td>2.000000e+33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>1.871201</td>\n",
              "      <td>45.00001</td>\n",
              "      <td>4.000000e+33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>1.694760</td>\n",
              "      <td>36.00001</td>\n",
              "      <td>1.000000e+34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>1.555247</td>\n",
              "      <td>30.50001</td>\n",
              "      <td>2.000000e+34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>1.414021</td>\n",
              "      <td>26.50001</td>\n",
              "      <td>4.000000e+34</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    m (Msol)       R (km)      p (N/m2)\n",
              "0   0.376800  14511.50001  1.000000e+21\n",
              "1   0.430210  13157.50001  2.000000e+21\n",
              "2   0.488767  11907.00001  4.000000e+21\n",
              "3   0.574097  10402.50001  1.000000e+22\n",
              "4   0.644535   9370.00001  2.000000e+22\n",
              "5   0.719841   8422.50001  4.000000e+22\n",
              "6   0.826359   7291.50001  1.000000e+23\n",
              "7   0.911699   6522.00001  2.000000e+23\n",
              "8   1.000596   5821.00001  4.000000e+23\n",
              "9   1.122589   4992.00001  1.000000e+24\n",
              "10  1.217432   4433.50001  2.000000e+24\n",
              "11  1.313713   3928.50001  4.000000e+24\n",
              "12  1.441969   3337.50001  1.000000e+25\n",
              "13  1.538791   2943.00001  2.000000e+25\n",
              "14  1.634639   2590.00001  4.000000e+25\n",
              "15  1.758659   2180.00001  1.000000e+26\n",
              "16  1.849589   1909.50001  2.000000e+26\n",
              "17  1.937342   1669.00001  4.000000e+26\n",
              "18  2.287356    871.00001  1.000000e+28\n",
              "19  2.125688   1211.50001  2.000000e+27\n",
              "20  2.198931   1052.50001  4.000000e+27\n",
              "21  2.287356    871.00001  1.000000e+28\n",
              "22  2.347320    753.00001  2.000000e+28\n",
              "23  2.400833    650.00001  4.000000e+28\n",
              "24  2.460907    534.00001  1.000000e+29\n",
              "25  2.497677    459.00001  2.000000e+29\n",
              "26  2.526414    394.00001  4.000000e+29\n",
              "27  2.551129    321.00001  1.000000e+30\n",
              "28  2.559008    274.50001  2.000000e+30\n",
              "29  2.556843    234.50001  4.000000e+30\n",
              "30  2.537398    189.50001  1.000000e+31\n",
              "31  2.509246    161.00001  2.000000e+31\n",
              "32  2.468785    137.00001  4.000000e+31\n",
              "33  2.395469    110.00001  1.000000e+32\n",
              "34  2.324536     93.00001  2.000000e+32\n",
              "35  2.240190     78.50001  4.000000e+32\n",
              "36  2.108695     63.00001  1.000000e+33\n",
              "37  1.995192     53.00001  2.000000e+33\n",
              "38  1.871201     45.00001  4.000000e+33\n",
              "39  1.694760     36.00001  1.000000e+34\n",
              "40  1.555247     30.50001  2.000000e+34\n",
              "41  1.414021     26.50001  4.000000e+34"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CENdeCABuHmm"
      },
      "source": [
        "WD_regimequalquer_TOV['R (Rsol)'] = list(map(lambda x : x/Rsol,WD_regimequalquer_TOV['R (km)']))\n",
        "WD_regimequalquer_TOV = WD_regimequalquer_TOV.sort_values(by='R (Rsol)')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "exkCQM8H3FsX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8f1680ac-d38d-4669-a94c-963896a39b17"
      },
      "source": [
        "#WD_regimequalquer_TOV = WD_regimequalquer_TOV.sort_values(by='R (km)')\n",
        "WD_regimequalquer_TOV['R (Rsol)']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "41    0.000038\n",
              "40    0.000044\n",
              "39    0.000052\n",
              "38    0.000065\n",
              "37    0.000076\n",
              "36    0.000090\n",
              "35    0.000113\n",
              "34    0.000134\n",
              "33    0.000158\n",
              "32    0.000197\n",
              "31    0.000231\n",
              "30    0.000272\n",
              "29    0.000337\n",
              "28    0.000394\n",
              "27    0.000461\n",
              "26    0.000566\n",
              "25    0.000659\n",
              "24    0.000767\n",
              "23    0.000933\n",
              "22    0.001081\n",
              "21    0.001251\n",
              "18    0.001251\n",
              "20    0.001511\n",
              "19    0.001740\n",
              "17    0.002397\n",
              "16    0.002742\n",
              "15    0.003131\n",
              "14    0.003719\n",
              "13    0.004226\n",
              "12    0.004793\n",
              "11    0.005642\n",
              "10    0.006367\n",
              "9     0.007169\n",
              "8     0.008359\n",
              "7     0.009366\n",
              "6     0.010471\n",
              "5     0.012095\n",
              "4     0.013456\n",
              "3     0.014939\n",
              "2     0.017099\n",
              "1     0.018895\n",
              "0     0.020840\n",
              "Name: R (Rsol), dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "miXQMua7UFrM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "outputId": "f7220a30-9e36-4f08-8d56-4195b6bce153"
      },
      "source": [
        "plt.figure(figsize = (8,6))\n",
        "\n",
        "plt.plot(WD_regimequalquer_TOV['R (km)'], WD_regimequalquer_TOV['m (Msol)'], color='green', ls='-')\n",
        "\n",
        "#plt.axhline(y=1.4,color = 'black',linestyle='dashed') #Mch\n",
        "#plt.annotate(r'M$_{ch}$ ', xy=(0,1.44),size = 10)\n",
        "\n",
        "plt.xlabel(r\"R $(km)$\")\n",
        "plt.ylabel(r\"M ($M_\\odot$)\")\n",
        "#plt.xlim(0,1.5)\n",
        "#plt.ylim(0,25e+3)\n",
        "#plt.gca().invert_yaxis()\n",
        "#plt.xticks(np.arange(0,1.8,0.2),['0','0.2','0.4','0.6','0.8','1','1.2',r'M$_{Ch}$','1.6','1.8'])\n",
        "#plt.annotate(r'Sirius B', xy=(3500, 1.02))\n",
        "#plt.annotate(r'Procyon B', xy=(6570, 0.55))\n",
        "#plt.ylim(0,3)\n",
        "#plt.legend(loc=1,prop = {'size':10})\n",
        "plt.savefig('mass-radii_WD.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lOAM0-ielbXR"
      },
      "source": [
        "###Parsons et al. (2017)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ramARhvclu3k"
      },
      "source": [
        "dados_parsons = pd.DataFrame(columns=['massa (Msol)','raio (Rsol)','massa_erro','raio_erro'])\n",
        "dados_parsons['massa (Msol)'] = 0.4756,0.4164,0.6579,0.4817,0.4475,0.5340,0.4406,0.4656,0.5964,0.5338,0.4146,0.6050,0.6098,0.3916,0.3977,0.4356\n",
        "dados_parsons['massa_erro'] = 0.0036,0.0356,0.0097,0.0077,0.0015,0.0090,0.0144,0.0091,0.0088,0.0038,0.0036,0.0079,0.0031,0.0234,0.0220,0.0016\n",
        "dados_parsons['raio (Rsol)'] = 0.01749,0.02521,0.01221,0.01578,0.01568,0.01398,0.01747,0.01840,0.01594,0.01401,0.01768,0.01278,0.01207,0.01800,0.01975,0.01570\n",
        "dados_parsons['raio_erro'] = 0.00028, 0.00170,0.00046,0.00039,0.00009,0.00070,0.00083,0.00036,0.00022,0.00032,0.00020,0.00037,0.00061,0.00052,0.00050,0.00036"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rppBq9uqVkyi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        },
        "outputId": "83db5faa-7308-4a46-a5ec-b7c78024b68b"
      },
      "source": [
        "plt.figure(figsize = (8,6))\n",
        "\n",
        "plt.errorbar(dados_parsons['massa (Msol)'], dados_parsons['raio (Rsol)']*Rsol, color = 'red', \n",
        "             xerr = dados_parsons['massa_erro'], yerr = dados_parsons['raio_erro']*Rsol,\n",
        "             fmt = 'ok', elinewidth = 1.2, label = 'Parsons et al, 2017',ms=5)\n",
        "#plt.plot(WD_naorel['massa (Msol)'], WD_naorel['R (Rsol)'], color='blue', label = 'NEWTON - regime não-relativístico $^{12}C$',ls=':')\n",
        "#plt.plot(WD_regimequalquer_NEWTON['massa (Msol)'], WD_regimequalquer_NEWTON['R (Rsol)'], color='blue', ls = '-',lw = 1.2, label = 'NEWTON - regime qualquer $^{12}C$')\n",
        "#plt.plot(WD_regimequalquer_TOV_He['massa (Msol)'], WD_regimequalquer_TOV_He['R (Rsol)'], color='black', ls = '-',lw = 1.2, label = 'TOV - regime qualquer $^{4}He$')\n",
        "plt.plot(WD_regimequalquer_TOV['m (Msol)'], WD_regimequalquer_TOV['R (km)'], color='green', label = 'TOV - regime qualquer $^{12}C$')\n",
        "\n",
        "#plt.axvline(x=1.4,color = 'black',linestyle='dashed') #Mch\n",
        "#plt.annotate(r'M$_{ch}$ ', xy=(1.42,0.0072),size = 10)\n",
        "\n",
        "plt.xticks(size = 13)\n",
        "plt.yticks(size = 13)\n",
        "\n",
        "plt.ylabel(r\"R (km)\",size = 13)\n",
        "plt.xlabel(r\"M ($M_\\odot$)\",size = 13)\n",
        "plt.ylim(6e+3,19e+3)\n",
        "plt.xlim(0.365,0.7)\n",
        "#plt.gca().invert_yaxis()\n",
        "#plt.xticks(np.arange(0,1.8,0.2),['0','0.2','0.4','0.6','0.8','1','1.2',r'M$_{Ch}$','1.6','1.8'])\n",
        "#plt.annotate(r'Sirius B', xy=(3500, 1.02))\n",
        "#plt.annotate(r'Procyon B', xy=(6570, 0.55))\n",
        "\n",
        "plt.legend(loc=1,prop = {'size':12})\n",
        "plt.savefig('teorico-observacionais_WD.png')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}