2G_Correlation is not Causation_Regression Analysis in height Data.ipynb

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      "cell_type": "markdown",
      "source": "# Correlation is not Causation_Regression Analysis in height Data \n### We use *regression* when we want to investigate the relationship between one variable (we call it *dependent*) and one or more other variables (we call them *independent*). Specifically, we want to investigate whether the dependent variable actually depends on the independent variables. In the simplest case we have only two variables, one dependent and one independent, and we handle them with *linear regression*.",
      "metadata": {
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          "slide_type": "slide"
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    },
    {
      "cell_type": "markdown",
      "source": "* Linear regression starts with the *assumption* that the relationship between the dependent variable $y$ and the independent variable $x$ is of the form:\n\n$$y = \\alpha + \\beta x + \\epsilon$$\n\n* In practice, we have a set of observations $y_i$ and $x_i$ and we want to estimate $\\alpha$ and $\\beta$.",
      "metadata": {
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    {
      "cell_type": "markdown",
      "source": "### We will start with a historical example, which introduced the concept of regression.\n\n### This is a study published by Francis Galton, in 1886, in which he examined the height of children in relation to the height of their parents.",
      "metadata": {
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          "slide_type": "slide"
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    },
    {
      "cell_type": "markdown",
      "source": "* The main libraries we will use are SciPy and statsmodels.\n\n* [SciPy](https://www.scipy.org/) offers various statistical functions.\n\n* [statsmodels](https://www.statsmodels.org/stable/index.html) offers model implementations for statistical estimation.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "import pandas as pd\nimport statsmodels.api as sm\nimport statsmodels.formula.api as smf\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom plotnine import *\nimport seaborn as sns\nimport scipy.stats.stats as stats\n\nsns.set_theme()",
      "metadata": {
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          "slide_type": "slide"
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      "outputs": [],
      "execution_count": 1
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    {
      "cell_type": "code",
      "source": "galton_families = sm.datasets.get_rdataset(\"GaltonFamilies\", package=\"HistData\")\n\ngalton_families.data",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
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      },
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              "      <td>66.64</td>\n",
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            "text/plain": [
              "    family  father  mother  midparentHeight  children  childNum  gender  \\\n",
              "0      001    78.5    67.0            75.43         4         1    male   \n",
              "1      001    78.5    67.0            75.43         4         2  female   \n",
              "2      001    78.5    67.0            75.43         4         3  female   \n",
              "3      001    78.5    67.0            75.43         4         4  female   \n",
              "4      002    75.5    66.5            73.66         4         1    male   \n",
              "..     ...     ...     ...              ...       ...       ...     ...   \n",
              "929    203    62.0    66.0            66.64         3         1    male   \n",
              "930    203    62.0    66.0            66.64         3         2  female   \n",
              "931    203    62.0    66.0            66.64         3         3  female   \n",
              "932    204    62.5    63.0            65.27         2         1    male   \n",
              "933    204    62.5    63.0            65.27         2         2  female   \n",
              "\n",
              "     childHeight  \n",
              "0           73.2  \n",
              "1           69.2  \n",
              "2           69.0  \n",
              "3           69.0  \n",
              "4           73.5  \n",
              "..           ...  \n",
              "929         64.0  \n",
              "930         62.0  \n",
              "931         61.0  \n",
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              "933         57.0  \n",
              "\n",
              "[934 rows x 8 columns]"
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    {
      "cell_type": "markdown",
      "source": "* Let us take fathers and sons.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "fathers_sons = galton_families.data[galton_families.data['gender'] == 'male']\nfathers_sons",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
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            "text/plain": [
              "    family  father  mother  midparentHeight  children  childNum gender  \\\n",
              "0      001    78.5    67.0            75.43         4         1   male   \n",
              "4      002    75.5    66.5            73.66         4         1   male   \n",
              "5      002    75.5    66.5            73.66         4         2   male   \n",
              "8      003    75.0    64.0            72.06         2         1   male   \n",
              "10     004    75.0    64.0            72.06         5         1   male   \n",
              "..     ...     ...     ...              ...       ...       ...    ...   \n",
              "918    199    64.0    64.0            66.56         7         2   male   \n",
              "924    200    64.0    63.0            66.02         1         1   male   \n",
              "925    201    64.0    60.0            64.40         2         1   male   \n",
              "929    203    62.0    66.0            66.64         3         1   male   \n",
              "932    204    62.5    63.0            65.27         2         1   male   \n",
              "\n",
              "     childHeight  \n",
              "0           73.2  \n",
              "4           73.5  \n",
              "5           72.5  \n",
              "8           71.0  \n",
              "10          70.5  \n",
              "..           ...  \n",
              "918         68.0  \n",
              "924         64.5  \n",
              "925         66.0  \n",
              "929         64.0  \n",
              "932         66.5  \n",
              "\n",
              "[481 rows x 8 columns]"
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          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 3
    },
    {
      "cell_type": "markdown",
      "source": "* We can start with the Pearson coefficient to see if there is any indication of a linear correlation between the height of the sons and the fathers.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "pearsonr = stats.pearsonr(x=fathers_sons['father'], y=fathers_sons['childHeight'])\npearsonr",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(0.39238349666283556, 3.7371088561934017e-19)"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 4
    },
    {
      "cell_type": "markdown",
      "source": "* The simplest way to work with regression in Python is using *formulas* like in the R statistics program.\n\n* We define a model based on the appropriate mathematical formula.\n\n* We then fit the model to our data by calling the `fit()` method.\n\n* The `params' property of the results gives us the *ordinate* (intercept) and *slope* (slope) of the regression line.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "fathers_sons_mod = smf.ols(\"childHeight ~ father\", data=fathers_sons)\nfathers_sons_res = fathers_sons_mod.fit()\nfathers_sons_res.params",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Intercept    38.362581\n",
              "father        0.446523\n",
              "dtype: float64"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 5
    },
    {
      "cell_type": "markdown",
      "source": "* This means that the relation between the variable `childHeight` ($y$) of the height of the sons and the height of the fathers `father` ($x$) is:\n\n$$ y = 38{,}362581 + 0{,}446523 x $$",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": "* If the father was $0$ inches tall (impossible of course), the son's height is $38{,}362581$ inches.\n\n* For every inch the father's height increases, the son's height increases $0{.}446523$ of an inch.",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "* To see what the regression shows us, we will make a diagram.\n\n* The plot will include the observations and the line resulting from the linear regression.\n\n* We will also add the diagonal, in blue because it will help us understand the regression.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons) +\\\n    geom_point(mapping=aes(x='father', y='childHeight')) +\\\n    geom_abline(intercept=fathers_sons_res.params['Intercept'], \n                slope=fathers_sons_res.params['father']) +\\\n    geom_abline(intercept=0, slope=1, color='blue')",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332120760)>"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 6
    },
    {
      "cell_type": "markdown",
      "source": "* We can easily get the regression plot with seaborn's `lmplot()` function.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "sns.lmplot(x='father', y='childHeight', data=fathers_sons, aspect=1.5)",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x13cc3b970>"
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x360 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "execution_count": 7
    },
    {
      "cell_type": "markdown",
      "source": "* It may be useful to make a graph of our model predictions, i.e. the points on the regression line that correspond to the values ​​of the independent variable.\n\n* Predictions are available from our model via the `fittedvalues` property.\n\n* Predictors are generally *not equal to the values ​​of the dependent variable*.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "fathers_sons_res.fittedvalues",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0      73.414606\n",
              "4      72.075038\n",
              "5      72.075038\n",
              "8      71.851776\n",
              "10     71.851776\n",
              "         ...    \n",
              "918    66.940028\n",
              "924    66.940028\n",
              "925    66.940028\n",
              "929    66.046983\n",
              "932    66.270244\n",
              "Length: 481, dtype: float64"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 8
    },
    {
      "cell_type": "markdown",
      "source": "* In the diagram we will make we will use red for the model predictions and black for the actual observations.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons) +\\\n    geom_point(mapping=aes(x='father', y='childHeight')) +\\\n    geom_point(mapping=aes(x='father', y=fathers_sons_res.fittedvalues), color='red')",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332272080)>"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 9
    },
    {
      "cell_type": "markdown",
      "source": "* A summary of all regression parameters and results is available from the `summary()` method.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "fathers_sons_res.summary()",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>OLS Regression Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>       <td>childHeight</td>   <th>  R-squared:         </th> <td>   0.154</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.152</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   87.17</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>             <td>Thu, 09 Dec 2021</td> <th>  Prob (F-statistic):</th> <td>3.74e-19</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>                 <td>16:45:02</td>     <th>  Log-Likelihood:    </th> <td> -1105.8</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>No. Observations:</th>      <td>   481</td>      <th>  AIC:               </th> <td>   2216.</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Residuals:</th>          <td>   479</td>      <th>  BIC:               </th> <td>   2224.</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Intercept</th> <td>   38.3626</td> <td>    3.308</td> <td>   11.596</td> <td> 0.000</td> <td>   31.862</td> <td>   44.863</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>father</th>    <td>    0.4465</td> <td>    0.048</td> <td>    9.337</td> <td> 0.000</td> <td>    0.353</td> <td>    0.540</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "  <th>Omnibus:</th>       <td> 8.610</td> <th>  Durbin-Watson:     </th> <td>   1.468</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(Omnibus):</th> <td> 0.014</td> <th>  Jarque-Bera (JB):  </th> <td>  12.731</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Skew:</th>          <td>-0.110</td> <th>  Prob(JB):          </th> <td> 0.00172</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Kurtosis:</th>      <td> 3.766</td> <th>  Cond. No.          </th> <td>2.08e+03</td>\n",
              "</tr>\n",
              "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 2.08e+03. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
            ],
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                            OLS Regression Results                            \n",
              "==============================================================================\n",
              "Dep. Variable:            childHeight   R-squared:                       0.154\n",
              "Model:                            OLS   Adj. R-squared:                  0.152\n",
              "Method:                 Least Squares   F-statistic:                     87.17\n",
              "Date:                Thu, 09 Dec 2021   Prob (F-statistic):           3.74e-19\n",
              "Time:                        16:45:02   Log-Likelihood:                -1105.8\n",
              "No. Observations:                 481   AIC:                             2216.\n",
              "Df Residuals:                     479   BIC:                             2224.\n",
              "Df Model:                           1                                         \n",
              "Covariance Type:            nonrobust                                         \n",
              "==============================================================================\n",
              "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
              "------------------------------------------------------------------------------\n",
              "Intercept     38.3626      3.308     11.596      0.000      31.862      44.863\n",
              "father         0.4465      0.048      9.337      0.000       0.353       0.540\n",
              "==============================================================================\n",
              "Omnibus:                        8.610   Durbin-Watson:                   1.468\n",
              "Prob(Omnibus):                  0.014   Jarque-Bera (JB):               12.731\n",
              "Skew:                          -0.110   Prob(JB):                      0.00172\n",
              "Kurtosis:                       3.766   Cond. No.                     2.08e+03\n",
              "==============================================================================\n",
              "\n",
              "Notes:\n",
              "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
              "[2] The condition number is large, 2.08e+03. This might indicate that there are\n",
              "strong multicollinearity or other numerical problems.\n",
              "\"\"\""
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 10
    },
    {
      "cell_type": "markdown",
      "source": "* In the summary table of results, the *coefficient of determination* (coefficient of determination) R-squared is given in the first line.\n\n* This coefficient can also be obtained with the `rsquared' property.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "fathers_sons_res.rsquared",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.1539648084533538"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 11
    },
    {
      "cell_type": "markdown",
      "source": "* $R^2$ is a *goodness of fit* metric, i.e. it indicates how well the data fits our model.\n\n* $R^2$ ranges from 0 to 1.\n\n* $R^2 = 0$ means that our predictions are equivalent to always predicting as $y$ the mean of the observations, for any value of $x$ .\n\n* $R^2 = 1$ means that the observations lie on a straight line.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons) +\\\n    geom_point(mapping=aes(x='father', y='childHeight')) +\\\n    geom_abline(intercept=fathers_sons_res.params['Intercept'], \n                slope=fathers_sons_res.params['father']) +\\\n    geom_abline(intercept=fathers_sons.childHeight.mean(), slope=0, color='blue')",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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r9DhaKk0IIYSQUvPq1SsEBwcjKCgIV65cgUQigbe3N4YPH46OHTuq9RqUvBBSRshkMpw6dQo3b96ElZUVBg4cCCcnJ12HRUipePToEY4fPw6RSISOHTvCx8dH1yGVGSKRCOHh4UzCEh0dDUdHR3Ts2BE7duxA69atYWFhUaTXpOSFkDJiwYIF2Lx5M7hcLrhcLrZu3Ypz587Bzc1N16ERolVXrlxB//79weFwIJPJsHXrVqxcuRJDhgzRdWhGKzU1FSEhIQgKCsLly5eRk5ODli1bon///vD394eLi0uJ5pfRnJdSYojPIrWFnlcr0vb4ePHiBVq0aCHXxuPx4O3tjWPHjmmt3+KiMaKIriGfFXV8NG3aFK9evZIrpsfn8xEbGwtzc3NthlqqdDlGJBIJ7t27x8xdefjwIapUqQJ/f3/4+/ujXbt2ak9QV6dcAd15IaQMePnyJfOps4BEIkFCQoIOoyKkdKSkpChUARaLxXjz5g2cnZ11FJXhe/v2LS5duoTg4GCEhITgw4cP8PT0xLfffou1a9eiQYMGWlu9R8kLIWWAs7OzwsWbz+drbSNCQvRJ9erVkZCQIFfl2MTERCtFAo2ZVCrFw4cPmbsr9+7dQ8WKFeHn54dly5bB19dXK3WS2FDyQkgZUKNGDcyYMQPLly9nipeVK1cOS5Ys0XFkuiUUChEREQGhUIiGDRtqvX6NJiUmJuLFixeoVq0aVbMtxPr16xEYGMgk8CKRCGvWrIGZmZmOI9N/Hz58wKVLlxAUFISQkBC8ffsWdevWRdOmTTF79mx4e3trtaaPMjTnpZTQ8+rPaD6DotIaHyEhIbh16xYsLS3Rt29fVK1aVet9FkdpjJHXr1+jT58+ePr0KTgcDsqXL49Dhw6hSZMmWumvpL4cIxs3bsSCBQsA5K8iGzFiBJYsWaI3O31rW3HGR2xsLE6cOAGxWIwOHTrA09NTy1GWPk1cR2QyGaKiopi7K7dv34alpSU6dOiAZs2aYceOHUhISACHw0GlSpVw+PBhNGjQQEO/QT515rxQ8lJKKHn5jJIXRTQ+5JXGGOnXrx+uXr0KkUgEAMzFOCIiAiYmJlrpsyQKxsi1a9fQq1cvuceAPB4P69atQ//+/XUYYemhawi74l5HsrKycOXKFSZhSUlJQYMGDZjJts2aNQOfz8e3336Lu3fvMhuhcrlcVK1aFffv39fo3ReasEsIIUrcunWLSVyA/E+cb9++xcuXL/V6LlB4eDhMTEyQl5fHtMlkMty8ebPMJC+kZGQyGZ4/f84kKzdu3ICpqSnatWuHadOmwc/PD/b29grHfJm4APlzYJKTk/H69WuFn9c22piREA0oeIbes2dPDBkyBDdu3NB1SApEIhFWr16NHj16YMiQIbh586Zax61btw62trawtbWFnZ0djh8/rtZxFy9exMCBA9G7d29s375dbrKkMh8+fECzZs1ga2sLMzMzzJ49W62+ikNZUSxLS0uVxwmFQqxYsQI9evTA0KFDER4erlZ/J06cQI0aNVClShXUrVsX9+7dK3LMQP6n66/PJYfDkVuGKhQKsXz5cibGO3fuFKsvdS1cuBBubm6oW7cuRo0apdbfmpSu7OxsXLx4EdOnT0fz5s3h7e2Nf/75Bw0bNsShQ4fw9OlT7NmzB4MHD2ZNRDgcDsqVK8f62oX9m9EGemxUSuixwGfGdstXJpNh+PDhOH/+PEQiETgcDjgcDg4dOoR27dqp9RraHh8ymQxDhw7FxYsX5WI8cuSIykqjO3fuxMyZMxXajx8/jjZt2ig97vjx4xgzZgzzaIPP5+P777/H0qVLlR4jkUjg5OQEoVAo1z58+HAsW7assF+xyLy9vfHs2TO5NoFAgOTkZKXHyGQyDB48GJcuXZI7j8eOHUPr1q2VHnfhwgUMGjRIof3mzZtq3+UpGCMJCQnw8vJSSBBOnjyJVq1aQSaTYeDAgQgNDYVIJGJ2zj5+/DhatWqlVl9F8fPPP2Pv3r1ybY0bN0ZQUJDG+ypgbNcQTfn6OhIfH8/cXbl27Ro4HA58fHzg7+8PPz+/IlfYXrduHZYsWcKcc4FAgP79+2PNmjUa/T1ozoseoeTlM2O78Dx58kQhAeBwOPDw8MCFCxfUeg1tj4/Hjx/D19dXro3D4aBp06Y4d+6c0uMcHBzkHq0UKF++PJ4/f670OA8PDyQlJSm0R0dHK70wrV+/Hr///rtCO5fLxevXr5X2VVy2tras7WfPnlU6mTMiIgL+/v5ybRwOB15eXjh16pTSvho0aMD6OzRt2hTnz59XK96CMfLnn39i5syZcn8XPp+P8ePHY86cOXjw4IHC/jAcDgctW7bEyZMn1eqrKKpUqcJ6p+XevXuoXr26xvsDjO8aoikmJia4ePEik7A8f/4cNWrUQMeOHeHv7w9vb+8SrbCSyWTYvXs3/vzzT4jFYnTr1g2//PILs4JRU2jOCyGl4N27dwoF4ArmT+gLZTG+efNG5XHK3hhyc3NVHpeens7a/v79e6UXptjYWNb20n4EER0drTR5effuHbhcrlxM6pzHT58+sba/f/++yPG9fftWYXKkRCLBu3fvmO/zeDy5v506MRaXsr9PfHy81pIX8lnBJofBwcG4cuUKRCIRvL29MXToUPj7+2t0/haHw8GIESMwYsQIjb1mcVHyQkgJ1a1bFzweT24im0AgQNOmTXUYlTwXF5dixVi+fHnWRKSwqqQNGzZUmNxnaWmp8s2sR48e2Ldvn0K7sufsJfV1ElIgICBA6TFubm4KxwkEAjRr1kxlXzVr1kRkZKRCe3GW6zZq1Ejhbhifz0ejRo0AAO7u7grHCAQCrS0NNjc3R3Z2tkK7vi45N3TKNjn09/fH3r170axZsyJvcmiIaMIuISVkZ2eHTZs2MRsecjgcODg46FUBuKpVq2Ljxo3g8XgwMTEBj8eDs7NzoTHevn1boY3L5eLy5csqj9u0aRMqV64MPp8PExMTmJqaYteuXSoTkQ4dOrDOo9HW3ksbN25UaBs4cKDKqqsODg5Yu3YtuFwucx5r1qyJhQsXquzr9OnTCsuvK1WqhC1bthQ57o4dO2LkyJEA8h+fcDgc+Pv74/vvvwcAVKtWTSHGWrVqMXVhNG3Pnj0Kd4Lmz5+vk0mcxio1NRX79u3D8OHD4erqisDAQNy7dw/9+vVDWFgY7t27hxUrVqBr165lInEBaM5LqaE5L58Z4/PqCRMm4NChQ8zXXC4X58+fh4eHh1rHl9b4iI2Nxf3792FpaYl27dqpdVdDJBKhZ8+eiI+PR4MGDXDw4EG1+vr48SNCQ0MhFArh5eUFR0dHtY77559/cOzYMVStWhVz587Vagn3J0+eYNGiRcjNzcXQoUPRtWtXtY57/vw57t+/D2tra7Rr106teQQSiQQzZsxATEwMvLy88OuvvxYp1oIxIpPJMGnSJBw8eJB5PNS6dWscPHgQAoFAIcby5cujbdu2Wq0m+/LlS+zcuRNCoRD9+vXT+l0XY7yGfIltk0M7Ozu5TQ7ZqkEby/sMTdjVI8YyqDTB2C48Dx8+hJ+fn0K7nZ0dHj9+rNZr0PiQZ2xjRBMKxsjZs2cxbNgwufMiEAgwd+5cjB07VocRlh5jHB/v3r2TK8NfUDagIGFp2LBhoRWUjeU6QhN2CSkF165dY20vmEBJiCZFRUWBz+fLvWmLxWJER0frMCpSVFKpFJGRkczdlbt37zKbHC5duhS+vr6oWLGirsPUWzTnhZASqlOnDms7bfpWdOnp6Rg5ciRcXV1Rt25dHDhwQK3jbt++DT8/P7i6uuLbb7/F06dPtRyp7rAtTebz+bRDsgpSqRTr1q1DkyZN0KBBA0ybNq3QFXPa8OHDB5w4cQI//PADU37//PnzaN++Pc6dO4fHjx9j06ZN6N27NyUuhaDHRqXEWG7naYKx3fKVSqVo2bIl4uLi5NqXL1+OYcOGqfUaND7y59Z06tQJ0dHRzGoaLpeLzZs3o0+fPkqPi46Ohr+/P8RiMaRSKXg8HiwtLXH16lW93XiyOArGSHZ2NgICAvDixQuIRCIIBALY2NggNDRUae0aY1PUa8iKFSuwevVqZvWbQCBAp06dsHv3bq3GKZPJEB0dzdxdCQ8Ph6WlJdq3bw9/f3+0b98ednZ2GuvPWK4j9NiIkFLA5XJx/fp1jB49Grdv34a5uTl++eUXBAYG6jo0gxIREYGHDx/KtUmlUmzatEll8rJv3z5IpVLmboREIkFOTg7+/fdfo5wDYm5ujnPnzmHdunV48uQJnJ2d8cMPP5SZxKU4tm7dKrdsXyQS4b///sP79+81focjKysLYWFhTMKSnJyM+vXrw9/fH7NmzYKnp6fGi7qVRUZ7BguWZ+oLPp8vt/dIWVYw6czCwgLGdOPv8OHDxT6Wxke+rwvpAUBOTo7Kc1Nwx+VLXC4XEonEqM7pl2PEyspK5VYLxq6o15AvN7H8+nVKOkZkMhliYmJw/vx5nDt3DmFhYTA1NYWfnx9mz56NgIAAtVfalVRZuo4YbfIiFAoV9kjRJWO5nacJBbVGPn36ZBSPjTSBxgdQu3ZtWFhYICsri2kTCATo0KGDynPTsmVLhdv/eXl5aN68uVGdUxojnxX1GtKmTRum+mzB8Q4ODrC2ti7WOc3Ozsa1a9cQFBSE4OBgJCQkwMXFBf7+/pg4cSJatGghV9entP5uxjJG1LnxYLTJCyHEsFSoUAH//PMPvvvuO2RmZgIAfH19MWfOHJXH9ejRA9HR0Vi1ahWA/Lsuy5Ytg5eXl9ZjJoZh48aN6N+/P/NYskqVKjhw4AB4PJ7ar8G2yWGbNm0wfvx4+Pn5FVp1mmgWTdgtJcaSEWuCsU3Y1QQaH59lZWUhLi4Ojo6OqFSpktp7G6WmpiI5ORlOTk5qTfgzNDRGPivONUQikeDZs2cQiURwcXEp9NN9Xl4ebt68qbDJYUHdFW9vb61tXVFcxjJGaMIuIcTgWFpawsPDg3lzUlfVqlWNanUR0Swejwc3NzeVP5OUlMTsGRQaGgqxWAxvb298//336NixI2rVqlVooThSOih5IUZNIpEgMTERTk5ORbpFbAhyc3ORm5sLGxubIh2Xk5PD7HmjLpFIhAcPHsDDw0OuBL22Yrx9+zY8PT2L9EYhFovx9OlTuLq6Fmk1R0pKCrKyslC3bt0ixZidnQ1TU1O58yiRSJCXlwdzc3PWY6RSKd68eQNbW1uF/YC0gS1GYyCTyZTu1F0UIpEIt2/fZuauREVFoVq1aujYsSO2bduGNm3a0B5NeoqK1BGjNXDgQFStWhVeXl6oWrWq0SybzcrKQqtWrVC9enXUrVsXNWrUUFhizObFixdo27YtnJyc4OjoiPnz56v1SMbDwwMODg7o0qULHBwc0L59+0KPyczMRMuWLeViZNtV+Ws//vgjbG1t8c0336BSpUqoVKmS3AReZXx8fGBvbw9fX1/Y29ujX79+hR4TFxcHOzs7NGrUCN7e3rC1tcXevXsLPS42NhZt2rSBs7MzHB0dsXDhQojFYixevBiOjo5wdnZG69at8fz5c7njpk2bhipVqqBBgwaoWrUqNmzYUGhfxfX8+XO0bt2aiXHx4sVGs7Lv4MGDcHJygqWlJdzc3HD16tUiHf/69Wvs378fI0aMgJubG/r06YN79+6hb9++CAsLw/3797FixQp06tSJEhc9RnNeSomxPIvUhNKY8zJv3jxs2rRJoX3BggUYN26cVvosiaKMj/bt2+PRo0dybaampnjx4oXCzsUFsrOz4e3tjdTUVOac8/l8zJgxA5MmTVLaV/fu3XHjxg2F9iFDhjATZNm0bdtWoVy9mZkZ4uLilN4VuX37Nrp06aLQzufzkZKSorSv77//HmfOnFFo//nnnzFjxgylx7FVqgWAhIQEpXdOPn36hFatWiEtLU3uPPr7+yMoKIipJcLj8WBra4sbN27A0tISW7Zswdy5cxVe78CBA6z7YrFRd4wUJLdv3rxhYuTxeJg3b57BJ/ChoaHo27cvk4hxOByYmJjgypUrqFWrFusxEokE9+/fZ+auREREqLXJoSEylvcZdea80J0XYpS+3OH5S7t27SrlSDSPbbPHvLw81iSjQGRkJJKSkhT2wylsh+jw8HDW9sJq2jx58kShLTc3Fzdv3lR6zLRp01jbvywuxiY4OJi1fc+ePSqPU3bXiS3pLfDgwQO5BLAgvkuXLsnFKZFI8Pr1azx48ABAfiE9Ntqo8PrgwQO8fv1aLkaJRKL2buD67MSJE3KPEguSmIsXL8r93Pv373H06FGMGzcO9erVQ9euXXHlyhV06dIFwcHBiIyMxLp169CtWzejSVzKGprzQgghxKBJpVJEREQwc1fu3LmDihUrokOHDliyZAltcmiEinXnZfjw4Qr7uBRISEjA8OHDSxQUISWlbM6DunsN6TN3d3eFNlNTU7Rq1UrpMQ0bNkS1atXkJm7y+Xz0799fZV/KaqWoKtcPAK6urqwxtmzZUukxixYtYm0vbLJphw4dWNuHDBmi8jhlk4EnTJig9JjGjRujSpUqCuexXbt2co/DeDweqlSpAg8PDwDAgAEDWF9v6NChKmMsDg8PD9jZ2RX5b20IunfvrjB3RyQSYe3atfD398e5c+fQrl07nD17Fo8fP8bmzZtpk0MjVazkZc+ePXjz5g3r996+fYs///yzREERUlLz5s1TmEvQq1cvlW9MhuL06dNyS4JNTExw8uRJpfNdgPz9cI4ePcqsqOHxeBg9ejR++OEHlX2dPHlSYbdiNzc3rF69Gjt37kTPnj3Rr18/nDp1SiHGmjVrMl9bWFjgzJkzKlcBeXt7s77Bfj3x9Wt79+5VSJbatm2LWbNmqTzu1q1bCm3Lly9XOt8FyF/Gffz4cWZ+BZ/Px7hx4/Dnn39iwoQJzO9Xq1YtHDt2jJnwOX78eLlkisPhYPbs2ejYsaPKGIujIMaC88/n8zFhwgSMHj1a432VJplMhipVquDbb79lVmpxOBy0bNkS8+fPx+PHj3Hx4kVMnz4dzZo1M7oVVkResSbscrlc3Lp1C82bN1f43oEDB/Djjz8iLS1NIwEWF03Y1V+lWaROIpEgPj4eNWrU0OuLWVHGx/HjxzFmzBjmEyifz8egQYOwcuVKtY7/9OkTzMzM1DofKSkpaNu2LTIyMgDkv1lUq1YNAQEB+PPPP5m/H4fDwdq1azFw4EC547Ozs5GXl4cKFSqoFVuBW7duoVWrVuBwOGqPEbFYjKioKNSrV6/IS6UzMjJY72ipwnYeJRIJcnNzYWFhwXqMVCpFWloa7OzsirxUujjXkKL8rfVRwSaHBbVXkpKSmE0OO3fujCZNmpTKknNDYSzvM+pM2FU7edmyZQu2bNkCIH/CYK1atRSqC+bm5iI+Ph59+/bFP//8U4yQNYeSF/1FFXYVFWV8NGnSBK9evVJof/TokcJdkpJatGgRNm3axOwJA+TvN/Tl1wVsbW0RFRWlkX5pjCgqC9cQmUyG2NhYZmXQjRs3IBAI0K5dO/j7+8PPzw8ODg40PpQwljGi0Qq7Dg4OaNasGYD8i6Srq6vCFuwmJiZwd3fHiBEjihgq0aXs7Gw8e/YMlpaWVEGyBN68eYPQ0FDY2trCx8dHa58IC+6CfC09PV3jycv79+8V3hyUjQ9lcRVVVlYW4uPj4ejoqPW5ClKpFM+fP0deXh7q1q0LMzMzrfYXGRmJx48fw9PTE3Xq1NFqX1lZWYiNjYW1tTVq1Kiht/+uc3Jy5DY5jI+PR926deHv748ff/wRLVq0UGujPlK2qJ289OjRAz169GC+njt3rtwzbWKY7ty5gwEDBjBvPL6+vtizZ4/S296E3R9//CG31LdSpUq4ceNGkR+XqKNevXoKS5jLlSsHJycnjffl4eGBv/76S65NKBTCwsIC2dnZco+uGjRoUOL+bty4gcGDBzMbM37zzTfYuXOnVpKK9PR0DBgwAHfv3gWQv73AoUOHivz4SB1SqRTdu3eXm2fTt29fbN68WeN9AcC1a9cwePBgpsBf586dsWPHDr1JAhISEpi7KwVF5tq0aYOxY8fCz88PNWrU0G2ARO8V66PhH3/8QYmLEcjKysL//vc/fPjwgWm7du0aazEtolxSUpJCjZJ3797JJfuaxFaXwszMrEjzPNRlY2PDWpl19uzZKFeuHAQCAfh8PipVqsQ8Vi6u9PR0DBw4UO62d0hICBYuXFii11Vm8uTJcpWJ09LSMGDAANZHYiU1Z84chQnChw8f1srj9Xfv3mHQoEFylYmDgoKwdOlSjfelLqFQiCtXrmDu3Lnw9vaGp6cntm7dCmdnZ/zxxx+IiYlhqt5S4kLUUeyr3YULF3DkyBG8evUKubm5ct/jcDhKC0cR/REdHS2XuAD5yw5DQkJ0FJFhYqvuCgDPnj3TSn9shePS09ORkJBQ5P15ChMWFgYejyf36MjU1BQfPnzArVu3cOvWLQgEArRp06bExb4ePXqET58+ySVLIpEIQUFBWklgQkND5RIVqVSKpKQkvHz5Umm11uJS9m/qxIkTGDRokEb7evjwIXJycuTaRCIRLl68iN9++02jfamSnJwst8mhSCSCt7c3hgwZAn9/f9SuXVtvH2UR/Ves5GXFihWYPn06atSoAXd3d5QvX17TcZFSoGw7d33b5l3fKdt0UFsrPMzMzJjHKl/Sxt+tXLly4HK5csmLTCaDubk5qlatqtG7S+XKlWO9y6Nq6XJJmJqasm7up43+lD320kZfpX0eC4jFYrlNDh8/fgwHBwd07NgRW7dupU0OiUYV67HRpk2bMHHiRLx48QKnT5/G8ePHFf4j+s/d3R2enp5yuwRzuVyMHz9eh1EZnm7durEmDn379tVKf+PHj5d7RCQQCNC+fXtUq1ZN430NGDAAHA6HmXzM4/FgamqqlUdijRs3RsOGDUttPLKdx4CAAI1PegaAn376ibX9559/1nhfTZs2hbu7u8J51MaeXmlpaThw4ABGjhwJV1dX9OrVC3fu3EGfPn1w5coVPHjwACtXrqRNDonGFSt5ef/+PXr27KnhUEhp4/F4OHDgAL799ltUrlwZTk5OWLFiBQYPHqzr0AyKmZkZwsLC4ODgAA6Hw1QzXbNmjVb6Gzt2LGrXrs18bWpqimXLlmnlFrybmxsWL14MExMTcDgcmJmZYePGjXBwcNB4XwKBADt27EClSpWY8zhgwAAEBgZqvC8gfwfr2bNno1q1arC1tUX//v2xY8cOrZzH7t27Y/ny5TAzMwOHw4GlpSX++ecfNGzYUON9mZiY4NixY+jYsSMqVaqEmjVrYsOGDejVq1eJX1sikeDu3btYtmwZOnbsiPr162PBggUwNzfHmjVr8PTpU5w4cQI//PAD3N3d6bEQ0ZpiFakbNGgQXF1d9XpiJ9V50V9Uo0FRUcbHgAEDEBQUJNdWoUIFPHnyROPLs588eQI/Pz+IRCLIZDLweDyYm5vj6tWrGk9gRCIRAgIC8PTpU2YuCpfLxcaNG7V2F8uQ6Ooa8v79e1y6dAnBwcEICQnB+/fv4enpCT8/P/j7+6Nhw4alXiiOriHsjOV9RqN1Xu7du8f8/7BhwzBu3Djk5OSgY8eOrM/8mzZtqu5LE0KKgG0yfHp6Ou7evcta9bok9u/fD5lMxsyhkEgkyMvLw4kTJzT+GCIiIgKPHj2Sa5NKpdiyZQslL6VIKpUiMjKSmbty9+5d2NjYoEOHDli0aBF8fX1RqVIlXYdJyji1kxdPT0+FrciXLVumcLtaJpMVqaQ3IeoICwvDqVOnYGNjg7Fjx6pVP0Umk+HmzZvM6hFPT0+txnj48GEcPHgQFSpUwIIFC2Bvb69WjDdu3MDbt2/h4OCgVozKbpaqUyTuxYsXuH//PqysrODj44Ny5cohLy8PV65cwYcPH+Dh4SFXPC0nJ0dh6TCHw0F2dnahfSUnJ2PXrl3Izs5GYGAgU+RSmdzcXHA4HIXfT52+imv//v2YMWMGJBIJevfujfXr16t1XGxsLB48eAArKyu0bdsWZmZmyMvLQ2hoKD5+/AgPDw+5R3tA/t/t+vXrSEpKQt26ddGkSRO1+srMzGRWfTVq1EjtO16XLl3CuXPnULFiRYwbN07larDMzExcvnyZSVjS0tLQuHFj+Pv7Y8GCBWjSpInebDEgk8kQFhaGzMxMODg4oFGjRroOieiA2o+NQkNDi/TC7dq1K1ZAmkKPjfRXUW/5zpkzB1u3bmW+FggECAkJgZubm9JjpFIpxo0bh+PHj8PExARCoRDff/89li9frpXn8P3791dYDnvq1Cm0aNFCZYxjxozBiRMnmBiHDx+OJUuWqIzR3d2ddXzHxcWpnBR57NgxjB8/nln6XKtWLfzzzz8YOnQonj59Ch6PB7FYjDVr1jB7FB04cIB188Zjx47Bx8dHaV83b95Ejx49IJVKmbbZs2dj0qRJSo9JT0+Hm5ub3DEA0LVrV+zZs0fpccX13Xff4dy5c3JtFStWxNOnT1Ued/jwYfzwww/MeaxTpw7++usvDBkyBM+ePWPa169fz+xuLpFIMGLECJw9exYCgQBCoRBjx47FggULVPYVFxeHbt264d27d+ByueByudi3b5/Kcw8AU6ZMkSsuaGJiguvXr8PZ2RlAfgLw5MkTplBceHg4zM3N4evrC39/f3To0EErE5dLSiwWY+jQobh48SJzHidOnKjXUxhKk7G8z2h0byNDQ8mL/ipK8hITE4PWrVsrtFetWhWRkZFKj9u3bx9+/vlniMViuX537dqFrl27Fj94FlevXmWdDGlmZoaXL18qPe7vv//GL7/8Ihcjl8vFnj170LlzZ6XH1axZU64AWYEnT54ovZ2fmpqKJk2ayPUlEAjg4OCA5ORkubsrPB4P4eHhcHJyQrVq1SAUChVer7A3eWUxxsTEKL1rduTIEdZHUVwuF69fv1baV3F9vb1Jgf/++w8tW7Zk/V5KSgqaNm2q1nnk8/m4c+cOqlWrht27d+PXX39V+Fvv27dPYffzL3Xu3BkPHjyQO87KygrR0dFKq+XevXsXnTp1Umh3cnLCokWLmIQlKSkJ9erVY+auNG/eXG6Fkj7avn075s2bJ3eeuVwuDh06pPMPzPrAWN5n1EleaDtOoteU3fF78+aNyuMiIiIUHj/weDy5iqqa8t9//7G2f1288WsPHz5UuMsgEAgKjZEtKQDYi9cViImJUUgURSKRwhsukP9Y6MmTJwDAmrgA+XdJihPj7du3lR5z6NAh1vavz5G2LVu2TOn3oqOjFeJRdh4L7m4A+ePx6/MvEAgQERGhMpbIyEi5xAUAPn78yLoxZ4FLly6xticmJmLMmDF48+YNpkyZggcPHiA0NJSpeqvviQsAPHjwQOE8m5iYaOXfNdFvxSpSx+Vyld7W5nA4KF++PDw8PDB58mR069atRAGSsq3gNvfXTExMVB5XuXJlhcqwALSy0Z+yDfYKezxVqVIl8Pl8uQRBJpMVGiPb7wUoP1cFfX2dzBUsfRaLxXLfE4vFasVQnBhV7b9Up04dpW+8pcnb21vp9ypVqqSQvCg7jxKJhLkTVvC3/vKNVyaTFfoJs0KFCkhNTWWNg01OTo7ST97lypVDTEyM3uxvVBy2trYKu5pLJBKtb+BJ9E+x7rysWLECjo6OqFOnDn766ScsWbIEkydPRu3ateHg4IAJEyZAJBKhZ8+eOHDggKZjJgZOJBKxVjZl4+/vzzrxdcqUKSqPGzJkCKysrJgiZAKBAJUrV0b//v2LHnAhhg8fzvqGMGDAAJXHff/997CwsJCL0c7Ojpknoaq/r7m6uqJevXpKj6lXrx46d+7MfLrmcDjgcDiYMWMGM5eiIAZfX19mteDEiRNZX2/Dhg0qYxw2bJhCm7u7u8p5SgsWLGBN+L755huFttzcXOTl5amMoTDKEuBffvlF6TGNGjVCQEAA63ks+H8g/zz6+/ujcePGAICRI0fC3Nxc7m9tb2+P3r17q4xxzpw5cueEz+dj9OjRcis8ExISsHv3bgwcOBCurq7YvXs3612UuXPnGnTiAuSfxy/38RIIBKhevbrW9hEj+qtYc15+/fVXPHnyBEeOHFFYadSnTx/Url0bK1aswP/+9z88ffoU9+/f12jQ6qA5L/pHKBRi+vTp2LdvH6RSKTw8PLBnz55CK8Pm5uZi8ODBuH//PkxNTfHjjz9i7NixhfaXlJSEpUuXIi4uDi4uLpg5c6bSeQ4lFRERgU6dOjG3+OvXr4/g4OBC71C8evUKS5cuxcuXL1GnTh3MmDGj0Bjz8vLwzTff4PHjxwCA8uXL49KlS6hevbrK40QiEdatW4ewsDBYW1tj/PjxaNWqFe7evYv169cjPT0drVq1wpQpU+Te5L6e/Dl37lzWSbxfW7p0Kfbs2QOxWIzWrVtj165dhW4eeePGDfTo0YO5g1GnTh1cu3aNSa7S09MxevRoXL58GRwOB9988w02b94MKyurQuNh8+XcHA6Hg5iYGKXbPRQQCoVYu3Ytrl69ChsbG0yYMAEtWrRAeHg4Nm3ahPT0dLRp0waTJ0+WS5ASExOxbNkyJCQkwN3dHTNnzlTrjsG5c+eY8/jNN99gyJAhCA8PZ+auxMTEwNnZGf7+/vD390fr1q0hkUgwcOBAPHr0CObm5pg2bRqGDBlSrHOkb+Lj47F8+XIkJyfDzc0N06dP18ru7YbIWN5ntDZht2rVqtizZw/rpLBz585hyJAhSEtLw8mTJ9G/f3+FTcJKAyUv+mfu3LnYuXMnc8uXz+ejVq1aCA0N1cqOyKUlJycHrVq1QmpqKvOohM/n45dffin0DlGBooyPmTNn4s8//5Q7j3Xr1sWlS5f0ZjlrcXz69AmtWrVCWlqa3HmcMWMGs0opMDAQ169fZ373gpL+2liNpE9SUlJw9epVnD59GpcvX4ZQKIS3tzeTsJS1TQ6pSB07Y3mf0WiRui9lZ2cjMTGR9XsJCQnMREULC4tC5yaQsuPIkSNyz6rFYjFiYmIQFxen8d2QS9OjR4+QlJQk1yYWi3Ho0CG1k5eiOHr0qMJ5jI6ORkJCgsZ3Qy5NDx8+RGpqqsL8m8OHD2PSpEn49OmTwgRukUiEs2fPQiwWG3QC/DW2TQ6rVasGPz8/bNmyBT4+PrRXECnTivWvvXv37pgxYwYsLS3RrVs3Jts7ceIEZsyYwex7FBkZqXQyI9EfV65cwbVr12BpaYnAwEC1iqsZgszMTEyfPh3x8fGoW7cus7dMWXbp0iXcvHkTVlZWCAwMRNWqVQs95tmzZ+jSpQs+ffoEGxsb3LhxQ62d5I8cOYLly5dDJBKhe/fumD9/viZ+BY06fPgwli9fDrFYjB49emDevHnFfq2oqCgsXLgQmZmZ8PX1xdSpU+W+n5KSgu+++w6vX79GrVq1cODAAbkNPdPS0hASEoKgoCBcvnwZWVlZ8PLyQu/evbF582Z4eXkpXcXFZuXKlbh8+TKsra0xe/ZslXOiDEl2djYOHTqE9PR0ODk5oVevXqW+PQHRvWI9NsrMzMTQoUPx77//gsPhMLO/ZTIZevXqhT/++APW1tY4duwYLC0tERAQoI3YVaLHRurZuHEjFixYwEzwMzMzw7lz57RyJ2TevHnYvn273OOO2rVrIzQ0VOOPOzIyMtC4cWO56qzly5fHo0ePNJ7A5OTkoHXr1khJSWHmvPD5fEyfPh2TJ09W6zWKMj5Gjx6tsHO7vb097t+/r/I8rl69GsuWLWPuUJibm+P8+fMq79ZER0ejbdu2Cu3Pnz9XmcAsW7YMK1eulGtr3rw5zpw5o/SY7OxsNGjQQOE8/Pjjj5gzZw4AoF+/frh69arcY6NOnTph9+7dSl9XmSVLlmD16tVybS1atMCpU6eK/FrXr19Hz5495e4atWzZkllG/+rVKzRt2lTu+3w+H0ePHkVYWBiCgoLw4MED2NraMnVXfH195c5xUcZIt27dcPPmTeZrDoeDf//9V+VKKkOQlZWFzp0748WLFwDyl9H7+/vjzz//pAQG+vs+U1RaL1IXHR2N27dvIyUlBfb29vD09NSb7J6Sl8KlpKSgcePGchdUHo+HVq1aKbw5aoJIJMKsWbPw119/QSKRwNPTE7t379bKnZ4hQ4bg7NmzCu2DBg3C2rVrNd5fXFwchg0bhsePH4PP52Ps2LGYM2eO2hfUooyPdu3aISoqSq6Nx+MhJiZGaQn4hIQENG/eXOHN08fHR2l9FSB/+TVbef7CigTa2dmxbmNw7do1uLi4sB4TFxcHLy8vuTYOh4MOHTowqxY/fPiAcePGMRtTdu3aFRs2bCjWIxRlE6PDw8NRs2bNIr1WvXr1WGsPHTp0CO3bt4eXlxfi4uJYj/X09GTmrqja5FDdMXLp0iXWFWt2dnbMJG9DtWrVKqxatUqhqOKOHTuoLAf0832mOLQ256WAu7s73N3dS/ISRIfi4+MV3mAkEgliY2O10p9AIMCKFSuwYsUKWFpaIicnR2uT7ZS9UTx79kwr/dWsWROXL19GTk4OTExMtDpxNiEhQaFNIpEgKSlJafISHx+v0CYWiwv9WyubbP/+/XuVxyn7TBQWFqY0eYmPjweXy5WroyKTyeRiLF++PPbt28fUxtHGnLrQ0NAiJy/KivbduXMHlSpVUpgTVcDR0ZE1yS4JZYUACyssaAieP3+uUKROIBAo/fdOjFeRdpV2d3dHuXLl5HaYVoZ2ldZ/bEtreTyeykJimsDj8WBmZqbVVWiOjo5MddMvqSrkpglfzmHQlmrVquH58+dyb/JcLlflHSxHR0fWisOFnQ9TU1PWSsHqzHlh06pVK6Xfq169ukIBOGUxanMhQHEerZQvXx7v3r1TaN++fTuWL1+utHptjRo1itxXYZRtVKhqY0ZD4ezsrFCkTiwWF1omgBgftR8Senp6MreJPT090bx5c9b/Cr5H9J+joyOmTJkCLpcLPp8PgUAAExMTLFmyRNehldj69esV3uDMzc2xfPlyrfWZlZWFBw8e4Pnz50rvPGjCqlWrwOPxIBAIwOfzweFwMH/+fJX1SWrXro2JEyeCy+Uyx5qZmWHRokUq+zp8+DBre3BwsMrjRo0apdDm7u6u8rFynTp1MH78eCZGExMTtWIskJKSgjt37hS6dUSBESNGKLTVr19f6Z0hZWQyGaZPn67Qbm1tjfnz5yMyMhKXL19W+H7BPlaa1qlTJzRo0EChfdOmTRrvq7SNGzcODg4OzN1NgUCAFi1a0COjMqhIu0o3a9YMlpaWau0wretNsmjOi/pOnz6Na9euwcLCAgMGDND6ctvSqtHw5s0b/Pjjj0hKSkKNGjWwceNGrX36vHnzJgYPHowPHz4AANq3b489e/bA3NxcreOLOj6ePHmCQ4cOQSgUMjsBF0Ymk+G///7DzZs3YWlpiUGDBql1J+r27dsIDAxEbm4uLCwsEBoaqtYn3W3btmHDhg0Qi8Xw8/NT681TJpPh5MmTCA8Ph52dHQIDAwstYggAixcvxpo1awDkJwVLly5lrfL7tS1btmDTpk0Qi8Xw9/fHxo0bCz0GyK9Jc/XqVaZQ3KtXr1CjRg0IhUKmuu7ixYvl5q/ExMRgyJAheP/+PRwcHHDs2LEilbUvyhjZuHGj3OouGxsb3L59u9ACfIYgMzMTe/bswfv37+Hs7IzBgwcbxL5MpUGf32eKwiB2lf56YplQKISnpydmz54NIP/5/oYNGxAfH48qVapg9OjRTMltVSh50V/GVmDqw4cPaNKkCbKyspg7LgKBAIMHD1b7Tg+ND3lFGSMnTpzA6NGj5R45cTgcnDp1SmECcEnExsYyycr169fB5/PRrl07+Pv7w8/PT60kqyTUHSPKdmL38PDAxYsXtRFaqTO2a4imGMt1ROsTdqOjo3Hnzh28fPkSw4cPR9WqVfH8+XNUqVJF7XLdX650kEgkGDFiBPMPTywW4/fff0dAQACWLFmCmzdvYsmSJdi6datRfIIgxuHx48dyiQuQv7IqJCREh1GVHWFhYQptJiYmuHr1aomSl5ycHFy/fp1JWOLj41GnTh34+/tj4sSJaNmypV7uFaRsOfrXK9QIMWTFWhifnZ2NgQMHokGDBhg+fDjmzJmD5ORkAPmly3///fdiBXPv3j3k5uYyE+YiIyORl5eHwMBACAQC+Pj4wMnJCdeuXSvW6xPdu3nzJsaNG4fAwEDs3btXq3NDYmJi4Ofnh3r16uGbb77By5cv1Truxo0bGD9+PIYNG4a///670BgtLCxYf0adR0Zv3rzB7Nmz0bt3byxYsACZmZlqxThr1iw4OzvD0dERXbt2hUQiQVZWFhYvXozBgwdj5syZSElJkTtGKBRi6NChaNCgAby8vHDkyBG1+po/fz5sbW2Z/77c50iVbdu2oVmzZmjYsCF+/PFHhcm4bKKiomBra4uKFSuCw+GodTeD7TxLJBK1zn+9evWY38vBwQHPnj2T2+Rw6NChiIuLw5gxYxAeHo4bN25g3rx5iI6OxqhRozBp0iSVS8a/lJqailmzZmHQoEFYuHCh2gXntmzZgmbNmqFWrVqYMmVKoedR2WRqbVYgvnLlCsaNG4fhw4fj0KFDWv13TQhQzMdG48ePx7Fjx7B37174+PjAwsICd+7cQdOmTfHHH39gzZo1ePjwYZGDWbp0KaysrDBhwgQA+beD79y5I5cMbd26FVKpFOPHj1f5WvTYSP8EBwdj4MCBkMlkkMlk4PF4GDVqVLGTXVViY2Ph7e0td6Hn8/l48OABqlSpovS4ixcvYvDgwXIxjhkzRmV12Ly8PDg6Oiq0N2vWDOfOnVN63Lt37+Dr64t3795BJBJBIBDAyckJwcHBsLCwUHrcqFGj8O+//8q12dnZwdbWFjExMRCJRODz+bC2tkZoaCiqVq0KqVSK5s2bK2zrsWrVKpUb9i1duhSrVq1SaP/zzz/RpUsXpcd9OQelgKenp8plwZmZmahdu7ZCu0AgYD4csTl79izr73DlyhWVpRyU1bBxcnKS2+TwyyRIJpNhzJgx+O+//yAWi5nJxadOnVK5wjItLQ2+vr7IyMhg/ta1atXCxYsXVa5QmzdvnsJcoS+L37HJzs6Gi4uLwq7bY8eO1cq/tZMnT2LkyJEA8s8Pl8vFzz//jGnTpmm8rwL02IidsbzPaG3Oi52dHVasWIHvv/8eEokEAoGASV4uXbqEHj16qP0JskBB1d4lS5bA1dUVAHDgwAHEx8djxowZzM/99ddfSEtLw88//yx3fEpKitwnTVNTUzg4OBT1V9MaCwsLfPr0Sddh6FSLFi1Y66xERUWpVaa+KHr27IkrV64otPfo0QN//PGH0uOaN2/OWvvkyZMnsLOzYz1m6dKlSue2qKqHsnz5cqxevZqpWQLkP+5YtGgR60qYAsomefL5fKbCL5D/pj9mzBgsWLAAp0+fxnfffadwjKWlpdJ9ylT1xeVyVX5AsLW1ZX1TuX37NmuCAuQvG1Z23VB1Hrt06SJXTbZA3759sW3bNoX25ORkBAUFKa1+PH/+fKW7Zj969Eih4jCXy0XLli1VVuZduHAhNmzYILfEVyAQYOXKlax/lwLKzmNERITKSdOxsbHo3r07UlNTwefzMWTIEKxYsULpz5dE/fr1Fe7ycTgcxMXFaW2CPI/Hg7W1NTIzMyl5+YKxvM+os0t4se4jZmVlKa0pUdwTd/nyZdjb2zOJC5BfM+Pr1/v06RPrJ5Vt27bJfTqeNWuW2kssS0tZ36RS2RLWvLw8jW9pr+zN7u3btyr7Kk6MbPVkCqjqKyMjQy7ZAPIv+pmZmRo5HyKRCO/fv0eFChUU3lwK5ObmFqsvqVSq8jhlbyjJycnw9PRk/Z6qT4yq+lJWfK3gby0Wi3Hz5k2cOXMGZ86cQUREhMrHUSEhIZg7dy7r97Kzs8Hj8eR+P6lUirS0tEJj/PpvzePx8PHjx2Kdx9evXyut5wLk3+VSdbdKk9j+rclkMojFYo3/u/6aMdSu0bSy8j5TrOSlUaNGOHr0KOueRadPn1Z6cVIlODhYYbmnk5MTjh49CqlUyiw5jIuLY91rZcyYMejevTvztampqV5VlDSWjLgk3N3dcfv2bbmLuKmpKXP7V5Pc3Nzw6NEjhfb69eur7Mvd3R13795ViNHGxkbpcV27dsXJkycV2jkcjsq+6tSpAx6PJ/doSywWo2bNmiqP+7oKbYGv2wQCAVxcXJCeno4mTZqwvlalSpWK1Ve5cuVUHmdubs76SMbNzU3pca6urkoTQVV91a1bF0+fPlVo5/P56N27N0JCQphNDnv06IGNGzeiXr16qFSpEuvrTZgwQWl/9vb2CvM5BAIBGjRoUOjfms/ny915EYlEhf6ty5Urx1rMsU6dOnpzfXNxcUFUVJRcomVhYQELCwutxUh3XtgZy/uMOklvsR4bnT59Gj169MCAAQPQt29f9OrVC5s2bUJsbCzWr1+PM2fOwM/PT+3Xi42NxdSpU7F79265oMViMcaOHYtOnTqhR48euHXrFjZu3KjWaiOa86J/Xrx4ga5duyIzMxNcLhcikQjbtm1Djx49NN6XUChE48aN5caBo6Mj7t69q3K/odjYWHz77bfIzMwEh8OBWCxWa9+U5s2bK5Tg37RpE+seMwXEYjEGDx6My5cvM1VDe/fujU2bNoHD4Sg97p9//lF45NG5c2dUqVIFe/fuhYmJCcRiMZo3b44jR44wn8QmTJggt7qPx+Ph4sWLaNiwodK+4uPjWYtOvnz5UuUGl8HBwRgwYIDcG/2XGywqw7bf0NdzPF6/fo3r16+Dw+GgTZs2MDc3R+PGjZGRkSF3XOXKleU2Ofz6mvH15oVA/sWfbSuFL+3ZswfTpk2DqakpJBIJ7O3tcebMGZVzqUQiEfr374/r169DIBBAKBTif//7H9auXavyb33u3DkMGTJE7jxOmTIFM2fOVBljaXry5Am6deuG7OxscDgcSKVS7NmzR6sb8tKcF3bG8j6j1TovR44cwS+//CK3z4qjoyNWr16NwMDAIr3Wtm3b8PbtW/z6668K34uPj8fGjRsRHx8POzs7jBkzhuq8GLD3798jODgYHA4HHh4eqFOnjtb6EovFWLlyJWJiYtCgQQNMnjxZrY0S379/jwsXLiAvLw/e3t5q7bB97NgxjBkzhvnawcEBQUFBSjf/KyCVSnHx4kW8efMG1apVg6+vr8o3swJ37tzBggULkJubi4EDB2Lo0KEA8pcNP336FA4ODggICFBYYfLvv//izJkzsLGxweTJk9WaF5aRkYEmTZogOzsb5cuXx8OHDwvdmTs+Ph6dO3dmSubzeDz8888/6NChQ6H9fTmR9uuE5+7duwgMDEReXh5kMhkEAgHatGmDe/fu4d27d6hQoQIaNWqEWbNmwcPDo9C/99KlS7Fu3TpIpVK0adMGR48eLTQ+AHj48CHu3r0La2trfPPNN2ptDCmRSHDhwgUkJSWhbt26aNu2rVp/6ydPnmDr1q0Qi8Xo06cP2rdvr1aMpenNmzcICgqCSCRC69atlc5r0hRKXtgZy/tMqRSpi4mJwdu3b1GxYkW4ubmV5KU0ipIX/WVsF560tDQ0btxYYbJs586dsWvXLrVew9jGx7fffqvw+M3CwgLR0dFq7f/ENkakUinc3d0V5lhYWFhg5cqV8PX1VeuiZ6iMbYyUhLFdQzTFWMaI1ovUAfnPO4u6FwghxiQmJkbhAioSiXD//n0dRaR7kZGRChNUP336hJcvXxbpepGZmYmQkBCmUBzb5NBPnz6hW7duelkwjhCiHWonL8eOHSvSC/fu3bvIwRBiiCpXrqwwiZPD4aj16SEqKgq//vorXr58iTp16mDJkiWoWbOmVuLMysrC3LlzERYWBisrK/z0009qbWj3+PFjzJ49G4mJiXBxccGSJUsK3Q3ZxsaGdcJuYXv5fPz4ET/++COuXbsGkUiEnJwcmJubw9fXFzNnzsTUqVMVEkVzc3Ns27YNixcvZko3bNq0Cb169Sr0dytNkZGRmD17Nl69egVXV1csXbpU6zu4E2Ks1H5sxPbsmMPhsFZS5HA4Or+VR4+N9Jex3fKVyWQYMWIEzp07B5FIBA6HAw6Hg8OHD7OujCsQFxcHX19f5OXlQSKRgM/nw8rKCmFhYSonfxaHRCJBz549cffuXWbFC4fDwa5du1QmMC9evICvry+EQiETo7W1NcLCwpTWvQHy56rs379frq1mzZoIDw9X+NmCTQ4vXLiAAwcOyNW9AYCdO3cyk7rXrl2LJUuWMCuguFwuevbsyfrh6uTJk2jVqpXSGEvT8+fP0b59e4hEIuY82tjYICwsTO1HXXQN+czYriGaYixjRJ1/E2pvDxAXFyf337Nnz5hdar/+3osXL0oUOCGGhMPhYPv27Zg2bRratGmDLl264MSJEyoTFwD4+++/mTczIH+C8adPn4p8l1Mdjx49ws2bN+WW6spkMoUquGwxisViuRizsrIKjZFtX6e4uDikpqYCyF/VtW3bNvTt2xcuLi4YPXo0nj17ppC4AMCGDRuY/580aRLWrVuH9u3bw9/fH1u3bmXd2wiAXHFLXdu7d6/CeczMzMSJEyd0HBkhhkntx0bOzs5yXxf8I7S3t1f4HiFlDZ/Px+TJk5VWbWXz8eNHhRoqHA5H7T1viuLjx4+sd0oL+5T28eNHhU+2HA6n0FoSyr7/+++/4/bt24iLi0Pt2rXh7++PCRMmoFWrVrh16xYCAwNVxsjhcPC///0P//vf/5i2qVOnsvbF9thKV5SdR2P4lEyILhRrY0ZCSMmxPdIQCoVo0aKFxvtyd3dXWN5csMxYlZYtWyos51UnxhYtWrBuBJiWloZRo0bh1q1buHnzJhYuXAhfX1+YmpqiXr16CpNuTUxM4OPjo7IvZZVm1VmWXVpatmyp8OhdW39rQsoC7W0zSgiLhIQEZlNBLy8vvZmToAkhISG4ceMGrKys0LdvX6VbaBTo2bMn7t+/jy1btjAJwq+//lro46biqFSpEv78808MHjyYeTTTsGHDQjfq6927N+7fv49t27YxMc6ePZs16REKhQgPD0dQUBDi4+MVlknv27eP2TGeTeXKlbFnzx4MGzYMubm5kMlk8PT0xLx58+R+LiIiAufPnweXy0WXLl1w5MgR1K9fn6kpA+RXoF22bFmh56W09OvXD/fv38euXbuY8zhv3jytjv8LFy7g9u3bsLa2Rr9+/TQ+j4oQXSp2nZevN2TUNzRhV/9ERESge/fuEIvF4HA4EAqFWLJkicpNCA3FqlWrsHz5cuZug5mZGc6fP69WEb7Y2Fi8f/8eVapU0erqk5UrV2L58uXg8XgA8lfpXLhwQa2CYrGxsUhKSkKNGjXkYkxNTWWWMYeGhiIvLw+tWrWCn58ffH19kZ2dDaFQiAYNGqi9D827d+/w9OlTODo6wtnZWe4x0unTpzF8+HDmPEulUqb43T///IO7d++iffv2aq2i0oXnz58jOTkZNWvWVLmxIpuiXEMWL16MdevWMefJwsICFy5cKHSVmKGgCbvsjOV9RqNF6r6eoCeVStG/f38sX76cdWmnrpdKv3jxDpmZhVevLC3GsudESQwcOBBPnjyBTPZ5ngeHw8WlS5dQvnx5HUZWMklJSfj2265ybVwuD82bN8fWrVvVeg1tj49Xr16hW7dv5dp4PD68vLywefNmtV9HLBYjMjISV69exdWrVxET8xR2dlXQpk0btGnTBl5eXrCwsChxvDweF+XL2+DDhwxIJPnjRSqVwsfHB9nZ8uepQoWKrBOEjY26YyQ+Ph69evWUa+Px+GjTpg3Wrl2rneBKGdv4IMbzPuPhobqkAlDCpdJKX1QPlkpPm5aNFSvMdRoDIYQQQopGnaxE7eTlyz2M1KHrFUh050X/9OvXD8+exSi0h4RcUrmL6OvXrzFjxgw8fPgQJiYmGDp0KEaNGlWkhFqb2O5qAECzZp7YuXOnymM3b96MnTt3QiaTgsvlYcqUKRg0aJDKY/Ly8jB06FA8eRINAChfvjx27/4Dnz59wqxZs/Dq1StUqFABM2fORMeOHQEAiYmJ6NGju8JreXo2x44dO+TapFIpoqOjmbsrjx5Fyn2/Tp26OHz4cBFjtMGePXsKfWxx9OhRLFz4eR6OtXV5BAcHg8/nQyqVwtvbG3l5uXLHlC9vg+bNmyMo6CLTNmjQYKWrkAqw3TGbN2++VjYKBYCff/4ZISHBzNdDhnyPn376Se3j1b2GxMbGIjCwj1wbj8dHq1at5JadG6qgoCAsXrwY6enpqF69OhYuXKh00nZZYyzvMxq982JoaM6L/mnfvj0ePXok18bn8/Hy5UvWlSlA/iTQdu3ayU0A5fP5mDNnDsaPH6/1mNXx5s0b1KtXT6FdWVG2AgcOHMAPP/zA2q5qV/ZOnTrh7t27cm1mZmbgcrnIzc2VK+B27NgxtG7dGq9fv0aDBg0UXqt27dq4efMmMjIycOnSJQQFBSEkJATv3r1D06ZNkZKSguTkZIXjBgwYgPXr1yuNMSAgQGF7BAsLC7x48UJp0pmYmIhmzZoptNvb2+Phw4cA8h9fjxs3jpm3I5FI0LlzZ5w+fVrhuA0bNsgtqf6ask0zk5KSmJ24NWXevHnYtGmTQvvmzZvRt29ftV6jKNeQ2bNnY8eOHeByueByuTA1NcXFixe1vmGitl2/fh29evWSG+Ompqa4evUqVSuG8bzPaLRIHSElFRUVpdAmFouVFhkD8kvTP3/+XG7lilgsxt69e7USY3Fs376dtT0uLk7lccruymzbtk3lcffu3VNoy83NhUgkUqgbU7BLsrLXjI2NRdeuXeHq6opp06ZBLBZjwYIFiIqKwrlz55CSksJ63JEjR1TG+ODBA4W2T58+qUzmFi5cyNr+ZQy9e/fGf//9hzFjxmDs2LE4d+4cbty4wXqcquRKlaVLlxbrOFX27dvH2r5u3TqN9wXk19PZvn07RowYgcmTJyMsLMzgExeAfe6lRCLB+fPndRQR0RW1l0pzuVy1tm8voOs5L0T/KLvJl5eXp/SYrzf3K6BP44utKqw6lP1uytqLSiaTMa+l6hy3bt0av/32G5o2bapwB0zZ36ywG7bF+Vur+t6XvLy84OXlxXz9dcJWoLhjRBtFAjUdY2E4HA569OihtUdgusL2b0Mf5liS0qf2nZfVq1cz/y1fvhwODg6oUaMGJk+ejCVLlmDSpElwdnaGg4MDVqxYoc2YiYFi202Yz+errGtSv359VK1alXlMAOQXV9Oni/Lw4cNZ2wur8xIYGMjaPnDgQJXHsX2C5vP5CgmDTCZD48aNsWnTJoXHTAWqVauGWbNmwcvLi/XRXa1atViPK6wWDdsKRIFAoLKuyc8//8zaXtgS62+++Ya1ffDgwSqPU0Yb2woUzD362pAhQzTelzHr0qWLwjiXSCRo3769jiIiuqJ28jJ58mRMmjQJkyZNQlpaGpo0aYJnz55h1apVmDZtGlavXo3nz5/Dw8ND6a1mUradOnUK1apVY74WCAQ4dOgQzM2VrwozNzfHkSNH5I7r27cvpk+frrU4r127hjFjxuC7777D3r17C73L4OzsjMWLF8u1FWywqMrEiRPRr18/ubZx48YpTWoKnDlzBlWrVmW+NjExwdGjR/Hnn38yy5Q5HA5sbGwwY8YMHDhwAK1atVJ4ozQzM8PVq1dV9nXr1i2Fv4+trS0OHjyo8rizZ88qxHjs2DGVc0kaNWqEMWPGyLXxeDyliVeBjRs3okmTJnJtXbp0YZ1P9CW2fYXGjx9f6M7XxbFlyxY0btxYrq1r164YN26cxvsyZgEBAVi8eDGTaFtaWmLPnj1wdXXVcWSktBVrwm6VKlXw559/olOnTgrfO3v2LL7//nukpaVpJMDiogm7+qtgcz57e/tCE4MCMpkMaWlpsLCwgKWlpdZiu3DhAr777jvIZDLIZDLweDyMGjWq0Eq0QP4nwGvXrqF69eqsdx6UycrKQnJyMpycnBRK+KuSnJyMzMxMCAQCBAcHIygoCNevXweHw4GPjw8CAgLg5+eH6tWrQyqVwtPTEy9fvpR7jeXLl2PYsGGF9vXixQscPXoU3333nVxSUpikpCR8/PgRLi4uha4Ok0qlaNq0KZKSkuTaV61apdYdivfv3+PevXto2bJlkcbImTNnkJycjCFDhmh8ou7XihsjQNeQLxVscmliYlKk6QzGzljGiEaL1H3J2toay5cvx9ixYxW+t2XLFkyfPh2ZmZlFfVmNouRFf+lzdcwWLVqw7or++PFj2NnZaa3fooyP3Nxc3Lhxg6ls++LFC9SqVQv+/v7w9/dHq1atFJKgs2fPsiYAlpaWhU4sLi3//fcf6yM4fYpRl+ga8pk+X0N0yVjGiDrJS7H2NurZsyemT5+OcuXKoWfPnihfvjw+fPiA48ePY+bMmejZs2dxXpYQnXvz5o3S9sKSF5FIhJcvX8LS0rJIic7Hjx+RkpICa2trpdVpX758ydxdCQsLg0QigZubG5o1a4Y//viDdan2l2JjY1nbc3Jy1IoxJiYGt27dQtu2bbVWw4ktaQTykzV1JCcnIzo6Go0aNVK6DPprMpkMqampyMvLQ/Xq1eXmVqkiFArx6tUrWFlZqd0X0ZzMzEy8efMGFhYWCpt5krKhWEulN23ahI4dO2L48OGoWLEizMzMULFiRQwfPhx+fn7YuHGjpuMkpFSwPTs3MTEp9A07IiICHh4eaNGiBerXr4+RI0eqtXpm27ZtqFOnDho1aoS6desyc0lEIhGuXbuG+fPnw8fHB02bNsX69evh4OCA33//HWKxGBERETh8+DDatWuHv/76S2U/ynaPrlSpUqEx+vj4oHXr1pgyZQo8PT219uFEWYzqJAeDBw9G48aN8b///Q/16tXDtGnTCj3m48ePCAwMRKNGjdC8eXO0bNlSaZL3pXv37qFx48Zo0aIF6tWrh3HjxkEkEhV6HNGMdevWoVatWnB1dUXt2rWZjV5J2VKiInXR0dG4ffs2UlJSYG9vj+bNm8Pd3V2T8RUbPTbSX/p8y3fo0KEKBc8qVaqEyMhICAQC1mOysrLQrFkzZGRkMEtiBQIBRo0ahfnz5yvtKygoCAMHDlSY99OmTRs8ePAAubm5aNWqFfM4qG7duuBwOHB2dkZ2drbC6z1//lzpHlExMTFo3bq1QnuFChUQE6NY9bjA6NGjcfz4cYX2qVOnanzSdGZmJtzd3RWWng8cOFBlPZQlS5Zg9erVCu0bN25E//79lR43atQonD59mkk8eDweqlevjhs3bigtmvjhwwc0a9YMmZmZzN9NIBBg4sSJmDVrVqG/Y0nQNST/0eLIkSPllp7zeDwEBwejfv36OoxMPxjLGNF6kTp3d3cMGTIE06dPx5AhQ/QmcSGkuK5fv67Q9u7dO5VzLh49eoT09HS5C6pIJMKZM2dU9nXx4kXWyYYfP37Exo0bERMTg2PHjmH8+PFwcXFhfpYtcQGAkydPKu1rz549rO3p6ekqY7x8+TJre2FF6oojMjKS9Q6GqsJ2AJSe58JiDAoKkutPIpEgPj5eYVLzlx4+fCiXuAD5f2u2Cr9E84KCghSSfYFAgCtXrugoIqIras95YavqqUrTpk2LHAwhuqbs7oqqVSimpqasq6bYnsW/ffsWISEhCAoKwpkzZxSKlxXUsOnatavCsYVRVQ+lXLlyrO2FrdRQNgdE2XkqCYFAoPZ5/JKyuySFHafsd1B1XHGOIZpjamoKDocjN06kUqnWV4kR/aP2nRdPT080b9680P8Kfo4QQzR8+HC5N0OBQIAWLVqonPPSoEEDuLm5yb2x8Xg8jBgxAlKpFPfv38eKFSvwzTffoF69evjtt98gEAgwbdo08Hg8JoHgcrng8/no1q2byhirV6+u0MblcvHtt4qbQxaYMGECa/vX9VG+Nnr0aNb2X375ReVxxdG4cWO4uLiwnkdVlO1xVVidl2HDhin8rX18fFQWF2zSpAlq164td5w6MRLN+PoxII/Hg4mJCbp06aKjiIiuqD3nJTQ0tEgv3K5du2IFpCk050V/6fOcF6lUitWrV2PHjh3Iy8tD+/btsWbNGtjY2Kg8Li0tDRMnTsStW7dgZmYGf39/AGA2OWzSpAkzd6Vx48ZMzZOwsDD8/PPPSE1NhZOTE9avX1/oXUuhUIgWLVrg1atXAPKLzZ0/f77QFUfnz59natgA+dV17969W+gKmylTpjATgjkcDqZOnarWhNjiSE1NxcSJE3H79m1YWVnhp59+wvDhwwu9Q7RhwwYsXrwYYrEYpqamWLNmTaEbHkokEixfvhx//PEHRCIR/Pz8sHr16kIr+qampmLChAm4c+cOLCwsMGXKFIwYMULr9UboGpIvKCgIM2bMQFpaGmrXro3169ejYcOGug5LLxjLGNFanRdDQMmL/tLn5KU4ZDIZHj9+zNRduX37NqytrdG+fXv4+/ujffv2ha6Y0fb4kEgk6N69O+7fv8/M8+BwONixY4debbVQwNjGiCbQNeQzGh/sjGWMaK3OCyFlXVZWFkJDQ5mEJTU1FQ0aNIC/vz/mzJmDZs2aKZ2LoQuPHj1SmPgqk8mwbt06vUxeCCFEFbXnvFhbWzN7jFhZWcHa2lrlf8RwPHz4EEuWLMHWrVu1sqPul16/fo0pU6Zg4MCBhe6r86Xixrh+/XoMHToU27ZtU/uY3NxcXLlyBRcuXGCK1slkMsTExGDz5s3o3bs3XFxcMHHiRKSnp2P69Ol4+PAh1qxZAy6Xyyxz1qZbt26hcePGcHNzw9q1awv9+Y8fPypd2aSOadOmoVOnTli4cKHaMebk5DDnsSh3Qvfv34/OnTujd+/eah8nFouZGL/eZ0qV6OhoBAQEwMfHRysrqHQpKSkJ58+fx/Xr1zW2U7k+kMlkuH//Pk6cOKFymT8xbmo/Npo/fz5GjRoFBwcHzJs3r9Dnu7/99ptGAiwuemyknuXLl8vtAm5qaoqwsLAi7c2jritXrqBPnz5ybUOHDi10F/Jly5Zh5cqVzNdmZma4cuWKyhglEglcXV3x4cMHpq1KlSp49OiRyr5SU1PRq1cvptqrQCBAhw4d8PjxYyQmJsLNzQ3+/v7w8/ODl5cXs8rh61ojBZseqluNtijjY/78+QqFIGvUqIHbt28rPeb9+/dwd3dXWN3UqVMnlQXuxGIxqlevLvfmp065/pSUFPTo0QMJCQngcDgwMzPD/v37Ve4qXRDP1xsxnj17Fp6enkWK0crKSmnF3gKbN29WuE61bdsWR48eVXmcrhRljPz3338YM2YMZDIZJBIJmjRpgqNHj2p1X7DSIJVKMWHCBBw5cgQCgQAikQizZs3CTz/9pOvQ9IK+vs8UFc150SP6OKgSEhJY3xQcHR1x//59jffn4ODAWsfjzp07St/kY2Nj0bJlS4X26tWrq1y+36dPH9baD3369MHWrVuVHtetWzeEh4fLvcnz+XzMnz8fnTt3Zl3p8/z5c9Y3ZScnp0J3RC5QlPGhbP7MqVOn0KJFC9bvKdvbiMvl4vXr10r7UrbXU2Fv8r1798aNGzeYhILD4aB8+fKIjIxUuvnkqVOnWDeJ5PP5Kneq9/LyYk2m2rdvj0OHDik9Ttl5DA8P10ryXlLqjpHU1FQ0bdpU7t+aQCDAwIED5T4EGKI9e/Zg5syZcokqh8PBv//+C29vbx1Gph/08X2mOLRepI4YtpCQENb25ORkrfSnrIT6qVOnlB5z6dIl1vbCYoyMjGRtv3nzptzXubm5uHTpEn799Ve0aNECN2/eVLg7IRaL4ePjw5q4AEBwcDBr+9e7I2vbqlWrlH7v77//Zm3/+nf9WsGKpq9FRESoPO7evXtybzAymQwZGRkqC8Api7GwRx7KYixqbaoCu3btKtZx+uLx48cKk1hFIhFrAUZDc/v2bYXxYGpqWuy/NTFcxZpRKJVKsXPnThw5cgSvXr1ifb5f2C1bonvK6lloowCZKrVr11b6veLGaG5uzlo91srKCq9evWIm2hZscujt7Y0RI0Zgw4YNSE1NVThO1VJpfTmPjRo1Uvo9R0fHYr2mQCBQKNcPKC96V8DKygqfPn1SaFc1H05ZcliYgscHX1O2yWVhDH3ZrY2NDWtSWrFiRR1Eo1kVKlQAn8+XS2AkEonSbTGI8SrWnZfp06dj7NixEIlEaN++PXr06KHwH9F/AQEBrLfnlBUmKym2jffKlSuHTp06KT2mc+fOrJsHjhkzRmVfS5cuZW3Pzs5GkyZNsG7dOjg4OGDHjh14+vQpDh06hNGjR2P27NlMDRYg/42xT58+KguXdenSBRUqVFBoV1Y8raSUPXaZPXu20mOU7bFU8LirYG7E15TNXduwYYPKGDt06KDQVrNmTVSpUkXpMb///jtrO9ueTF+aO3cua3thMbK9mXM4HJX7IX1JIpGwVgTWNQ8PD7Ru3ZpJnjkcDrhcLqZOnarjyEpu+PDhEAgETG0igUAAOzs7es8pg4o158XBwQHjxo3DnDlztBGTRtCcF/VkZmaib9++iIqKgkAgwOjRozFjxgyt9CUWi9GyZUskJCQAyC+5f+XKFZV3XgAgIyMD/fr1Q3R0NAQCAcaMGVPopoCpqalYsmQJ9u/fz7zBuLu7o3///vD395fbK+hrJ06cwPbt25GTk4NvvvkGU6ZMKfQuSlRUFDp37szsO+Tt7Y3jx4/LJUKqFHV81KhRQ+7Oxv379wu9u3L9+nX07NmTOR9OTk64ffs2Nm/ejBUrViAnJwcNGjTArl275OZ8rFmzBkuWLIFMJgOXy8WGDRvQr18/lX01atSIdZ7K48ePYWdnp/S4uLg4tG3blrmb265dO7VWAa1atQrLli0rUoxfx2liYoKIiIhCn7cnJCRg5MiRiIiIQLly5TB58mRMnjxZr4rUZWdnY9GiRbh27RpsbGzw008/6bxwqKY8ffoUCxYsQHJyMtzc3DBv3jyVSXFZoq/vM0WltQm7FStWxOHDh+Hn51eswEoDJS/6Z/HixdiwYQNzy1cgEMDNzQ0XL14stMprYSQSCe7evcs8DoqMjESVKlWYqrbt2rWDlZWVJn4NBXl5efDx8cHLly+Z343P52Pu3LkYN26cWq+h7fGRm5sLHx8fvHr1Si7GLl264PTp08xdFz6fDzs7O1y7dq1EK1O+Tq4KXLt2DS4uLoUer69FyHJyctC6dWukpKQw55HH42HhwoUYOXKkVvuma8hn+jo+dM1YxojWJuwOGjQI//33X3EOJWXY33//LfesWiQSITIystBlt8q8ffsWhw8fxpgxY+Du7o5u3brh2rVr6NatG0JCQhAZGYm1a9fi22+/1VriAoD5Hb783cRiMfbu3au1Povq4cOHiI+PV4jx/Pnzchd/sViM1NRUtVdJKdOkSROFIn3W1tZwcnIq0evq2v379+USQCA/cVa13JwQonlqT9g9duwY8/+tWrXCr7/+itevX6Njx46skxl79+6tkQCJ8VB2k6+wFS9f/tzDhw+Zuyv37t1DxYoV4efnh2XLlsHX15d17om2KYtf3d+rOB4+fIj169cjJycHgYGB6NWrl8qfl0gkCrvxAur9TUQiEU6ePIlXr16hdu3a6NKlS6GPwzZu3IiuXbsiOTkZHA4HJiYm2Lt3r9L5Ol8KDw/H7du3UbVqVXTs2FGvil7q4m9NCFGkdvISGBio0JaQkICDBw8qtHM4HLqVRxR0794df/31F7MyhM/no3r16ipramRkZODy5csICgpCSEgI3rx5w2xyuHjxYnh4eKg9r0Rb6tevz3q7lm3SqiacPn0aQ4cOZb6+cOECbt68iWXLlik9pmHDhrC1tcW7d++Yf5sCgQAtW7aUq8DK5XJhY2PDbA4pFArRu3dvZgNHsViMzp07Y9euXSrP+4cPH/DhwwfmcWBeXp7KejIFtm7dirlz58LExAQymQwVKlTA+fPnUa1atUKPLQ2NGzdGpUqV5B5X8Pl89OzZU7eBEVLGqD3npWCSpbrUrSyqLTTnRf/k5uZi0qRJzF08V1dX/P3336hRowbzMzKZDFFRUXKbHFpaWsptcqhqwqcuJCcnw8PDQ+4uBofDQYcOHXDgwAG1XqMo48PJyQk5OTkK7ZGRkahatarS4548eYJBgwYhMTERHA4HQ4YMweLFi7FgwQJs374dMpkMDg4O+Ouvv5hl11u3bsWCBQvkliLz+Xxs3rxZ5d0ePz8/hXojJiYmePr0qdK5NImJifD09JQ7j3w+Hx07dtSrR3CPHz/G4MGD8erVK3A4HAwbNgyLFy8u8bytwtA15DOa88LOWMaIRjdm/DIZCQ4ORmJiIms1zD179sDZ2VnnyQvRP2ZmZti2bRvWrl2LcuXKgcvlQiqVym1yGBwcjJSUFNSvXx/+/v749ddf4enpqVebHH6NraaRTCbD06dPtdIfW+ICAHfv3kXXrl2VHufm5oY7d+7g3bt3MDc3h7m5OQBg4cKF+PXXX5GVlYXKlSvLrZp59uyZwpsDj8fDs2fPVMb4/PlzheOEQiGSkpLg6urKesyLFy8UHm2JxWJER0er7Ku01a9fH/fu3cPbt29haWlZaM0bQojmFesdYfbs2UrX1b958wY7duzAtWvXShRYSZmYmMDU1FSnMXyJz+drddKoISnYd+bkyZM4d+4crl27BjMzM/j5+WHu3LkICAjQm8cE6qhTp47C3BEulwsnJye1/+ZFGR/KirI1a9ZMrddgm0NiZWXFekfL2dkZfD5frlCdTCZDjRo1VPZlb2+P2NhYuTYOh4NatWopPa5OnToKc0d4PF6RzmNpKu25OHQN+awgwbawsNDLWju6UpbGSLGWSltbW+PYsWPw9/dX+F5wcDD69OmDjIwMTcRXbPTYSL9kZ2fj6tWrzN2VxMREuLq6MkuZv9zkUNdkMhmSk5ORm5sLJycntSrlTp8+HX/++SekUil4PB64XC5Onz4NDw8PtfosyvjYsGEDFixYINfWpk0bHD9+XK3jiyIjIwPt27fH69evIRKJIBAI4OrqirNnz6qcfHvp0iUMGDAAQP5kVg6Hg+nTp2PKlCkq+/v555/xzz//MOeRx+PhzJkzKqsHlxVl/RryJXpsxM5YxohGHxt9icPhyO3W+yUaTKRAXFwcM3fl2rVr4HK58PHxwY8//og+ffqgfPnyejdWsrKyMGzYMFy+fBkAUK1aNRw8eFDpo44CS5cuRePGjXHjxg1YWVlhyJAhcHNz00qMP/zwA+zs7LBx40YIhUIEBAQorU5bUjY2Nrh06RK2bNmCly9fok6dOhg7dmyhq4bat2+Ps2fPYv/+/cjLy4Ofnx+6d+9eaH8rV65EkyZNcOvWLVSpUgUDBgwotIghIaTsKdadl4CAAIjFYgQHB8s9H5fJZPDz8wOXy0VQUJBGAy0quvNS+vLy8nDjxg0mYYmNjUWNGjXQsWNH+Pv7w9vbG2ZmZnr9qWn8+PH4999/mccyPB4PVatWRXh4uFbvDJWF8VEU+jxGdIXGyGc0PtgZyxjR2p2X+fPno3379mjUqBGGDh0Ke3t7JCcnY+/evYiJiWE+tRLj9+rVKwQHByMoKAhXrlyBWCyGt7c3hg0bBn9/f4P71BwUFCQ3n0QikSApKQnx8fFqVYYlhBCifcVKXlq1aoXg4GBMmzYN06dPh1QqBZfLZdpbtmyp6TiJnhCJRAgPD2cSlujoaDg6OsLf3x/bt29HmzZtVO7mu3r1amzduhUSiQTNmzdXaymxVCrF1KlTcfXqVZibm2P69Ono3LlzocfdunULAwYMQHZ2NiwtLXHq1KlCH+Uom99S2F0XsViM1q1bIzExEXw+H+PGjcOsWbMKjbG4evTogevXrwPI/5QSHR2N3NxcbN++HTExMbC3t8fYsWNZN7UsqsjISAwePBgfPnyAra0tjh8/XuxdqgsjFArh6uqKrKwscDgc9O7dG1u3bi30uPT0dGzduhWvXr1CnTp1MGbMGGY1lSr37t3DgQMHkJeXh44dO+Lbb7/VxK/BKi4uDhMnTsTr169Rs2ZNbN++XWtFFWUyGf7++2+Eh4ejfPnyGDZsmMF9kCBElWI9NvpSTk4O0tPTYWNjo9bForTQYyPNSU1NRUhICIKCgnD58mXk5OSgRYsWzGRbV1dXtTalmz59Onbv3i3XVq1aNTx48EDlce3bt8ejR4/k2jZs2ID//e9/So+5c+cOa4ITHh6usije5MmT8c8//8i1OTo64t69eyp/x2rVqsmtyAGA7777DqtXr1Z6zJeKMj5atmypsJKHy+WiadOmiIiIYCbWVqpUCZcuXVLrFqwyUVFRChv6cTgcZu8oTbO1tVVoK2xzxoJJxWlpaRAKhTAxMYGbmxvOnDmjcsVhSEgIBg4cCOBzpeFZs2Zh0qRJJfwtFMXFxaFVq1ZyjzjKlSuHR48eqb1qqShjZPLkyTh48CAkEgl4PB74fD7OnTuH+vXrFyt+fUOPjdgZ8vvMl7S2t9GXypUrBwcHB71KXEjJSCQS3L59G0uWLIGfnx8aNmyIRYsWwcrKCuvWrcPTp0/x77//YuLEiXBzc1N7N92vExcASEpKwo0bN5QeExYWppC4AMDMmTNV9lXwpvS1wratCA8PZ43x3bt3So9Zu3atQuICQGv73XyduAD5d6fu3bvHPPISiUR49+4dtmzZUqK+vvvuO4U2mUwmV+FXU0aMGMHaHhoaqvK47du3M4kLkH/3Jjo6utDdqKdNmwaJRAKJRAKpVAqpVIpFixYpXYxQEj/++KPCm2xOTg5+++03jff1+PFj/PPPPxCLxZDJZBCLxRCJRJg/f77G+yJEV/S38hcpVe/evcOlS5eYMvwfPnxAs2bN0LVrV6xZswYNGzZUO0kpqtu3b6NVq1as34uKimJtz87OVvmabDsaAyh0CX9qaqpCm0wmw+vXr5V+Grhz547K1ywtX99EFYlESEpKKtFrKjtfbOeppCIjI4t1XHJyskLdGy6Xi5SUFJXHsW1XIJPJkJaWhvLlyxcrlqL0BRS9crk6kpOTwePx5JIliUSCxMREjfdFiK7odlMYojNSqRQRERFYtWoVOnfuDHd3d8yePRs8Hg9Lly5FdHQ0zpw5gylTpqBRo0YaSVyU7YXDVi+oQIsWLVjb2TYD/ZKyuR4ODg4qj6tTp45CmfeCPZiUUTb/RlvJnrpMTExKPMlY2fmqW7duiV6XTUBAQLGOc3FxUajALJFIUKdOHZXH1a5dW+FvbWJiUugYKQ5l800aNmyolb6+LvYnEAhQr149jfdFiK5Q8lKGfPjwASdOnMAPP/yABg0awN/fH+fPn0f79u1x7tw5PH78GJs2bULv3r1RsWJFjfe/cOFChbaWLVuqvKh6eHigW7ducm0cDge7du1S2deFCxcU2jgcDoKDg1Uet27dOlhYWDAVmrlcLtauXatyXsKgQYNY538sWrRIZV/F1alTJ4U2a2tr9OrVCzweD6amphAIBHB3d8e4ceNK1NexY8cUkk5TU1P8/fffJXpdNgsXLmTdBuKHH35QedyIESPg4eEBPp8PU1NT8Pl8dOrUqdC6Mhs2bEC5cuXk/tYbN25UOeG8uLZs2aLwuvb29lp5bFSrVi3Mnj0bHA4HZmZmMDExQcWKFVn//RFiqEo8YVdf0YRd/dzk8PLly8xGfz169MDUqVPVOm7v3r04c+YMrKys8Msvv6h1RyEjIwPdunXD69evUb16dZw+fbrQ4mpA/iORU6dOITc3Fz4+PmjcuLFaMY4ZMwahoaEwMzPDqlWr4Ofnp9ZxQNHGR0pKCtq2bcs80uFyuTh27Bi8vb1x9uxZZrVRz549NbJFxocPHzB8+HC8fPkSLi4u2L17t9Zq3pw6dUpuz7Rq1aohNDS00Mc4IpEI//77L5KSklCnTh106dJFrd3Gk5OTcfr0aQiFQrRt21Yrd0IKZGVlYd68eUhISED9+vUxd+7cIu2IXtRryPXr13Hnzh2UL18ePXr0KPRupSGhCbvsytKEXUpeSklpDaqsrCxcuXKFSVi+3OTQ399fLzY5pAuPoqKMj8DAQFy7dg1isZhps7a2xqNHjwx6k8DXr1+jadOmcpOfBQIB+vTpgw0bNugwMv1gLG9MmkDXEHbGMka0VqSO6A+ZTIbnz58zycqNGzdgYmICX19f/PLLL/Dz89PKM3yiO3fv3pVLXAAgMzOT2S/KUD158kRh4q1IJMKtW7d0FBEhRF9R8qJFeXl5WLFiBUJCQmBjY4OxY8cWe1Lil7Kzs3Ht2jVmk8OEhAS4uLjA398fkydPRosWLfRmk8Ov/ffff9ixYwfy8vKYeNXZ+LA4Xrx4gQULFiAuLg4uLi6YN2+eWrtVnzx5Etu3b0dOTg46deqEn376Sed3q75Uvnx5ZGVlsbaXFolEgo0bN+K///6Dqakphg4dir59+5boNW1sbFh3CNbG/CtCiGHTnyuykZHJZBg5ciSCg4OZT5NXr17F7t27i1XFMz4+Xm6TQw6HgzZt2mD8+PHw8/ODs7Ozpn8FjTty5AjGjx/PvEFFRkbi+fPn2LZtm8b7Sk5ORseOHZGdnQ2xWIyYmBhcu3YNYWFhKqvOHjp0CBMnTmRijI6OxosXL0pcL0WTnJycFJZAW1hYoGrVqqUWw4wZM/D3338zd4Du3LnDbGpZXO7u7uDz+Qp3lVQVFSSElE0050VLnj17Bm9vb4V2d3d3XLlypdDj8/LycPPmTSZhef78OWrUqMHMXfH29ja4+Q2enp6sdS0ePHig1h2Roli6dCk2bNggN3/CxMQEc+bMwdixY5Ue17RpU7x8+VKh/eHDh7C3t9dojF8qyrPqKlWqKCyFBfIrxmpzwmmBDx8+sC5DrlSpEp48eVLs1z18+DDGjx+v0G5hYYH4+Phiv66xMJb5DJpAc17YGcsYoTkvOqSsuFd6errSY5KSkpg9g0JDQ5lNDr///nt07NgRtWrV0nntkJJQdk4yMjI0nrwou6gVVqROWXXVjIwMrSYvRcGWuAD546c0khdl57CkF01lhe/y8vJK9LqEEONDdV60xMXFReHOiEAgkCu6JhKJcP36dSxYsADt2rWDh4cHVq9eDTs7O2zbtg1Pnz7F4cOHMXbsWNSuXdugExcAaN68ucL8FktLS9SoUUMrfX1NLBajadOmKo9r1qyZwvwWKysrvXosp2wzP2UF/TStWrVqqFSpktx45PP58PDwKNHrKltarqpAICGkbKLkRUvKly+P3bt3w8zMDHw+H1wuF7Vr18bUqVOxf/9+jBgxAm5ubujduzfu3r2LwMBAXLlyBffv38fKlSvRqVMnWFpa6vrX0Ki1a9fC2dkZXC4XfD4f5ubm2Lt3r1aKgvXp0weDBw8G8Hmn6AkTJhQ6YXr9+vUKMf711196tXfXkSNHFBKshQsXqrVD8c2bN7Fu3Trs3r1b5X5NqvD5fPz999+wsrICj8cDl8tF1apVSzwvqF69egoF6cqVK4fjx4+X6HUJIcaH5rxoWVJSEo4fP46YmBg8evQIkZGRsLOzg5+fH/z9/eHr66v2rrLGIDc3F3fu3AGPx4OLi4vKybOa8PDhQ7x8+RI1a9ZUuzx6Tk4OwsPDkZeXBw8Pj1Ip5FfUZ9Xp6en4+++/8enTJ/Ts2RNubm6FHrNlyxb89ttvMDExgUwmQ/ny5XH+/Pli39l49+4d7t69C4FAAC8vL40loffv38e5c+dQvXp19O3bVyOF9oyBscxn0ASa88LOWMYIFanTkS83Obx06RIyMjLg5eWF9u3bM7s0F6WyprGhC48ibV90Xr58iWbNmsktRebz+Wjfvj327duntX6Li8aIImN5Y9IEGh/sjGWM0ITdUiKVShEZGcmsDLp79y4qVKgAPz8/LFmyBL6+vnB2djaKQUUM04sXLxTaxGIxnj59qoNoCCGkZMrux/8SYtvk8Ny5c/D19cXZs2cRFRWFzZs3a22TQ015+/YtBg4ciBo1asDd3R1bt25lLRSmCdnZ2XB0dETFihXB4XBQsWJF1g0UNeX777+Hra0t89+PP/6otb5KU0ZGhtzvZWtri7/++kvlMdWqVWP9u6pTfXnq1KlMP3Z2dli1alWxYy/M48eP4erqiooVK4LH42H48OFKV1eVlFAoRPfu3WFnZwdbW1t4eHggOTlZK30RQjSLHhupSSaTITo6mrm7Eh4eDgsLC2aTww4dOqicG6GPt/PEYjECAgLkyrLzeDwsWrQII0aM0Hh/jo6OrMtek5OTNV5ld968edi0aZNC+4IFC0q807I2FGV82Nrasra/fPlS6caTWVlZqF27tkIi4O/vj/379yvta/369fj9998V2nfu3IkePXqoFa+6srKy4OrqKlebBwD69++PjRs3arQvAOjevTtu3Lgh12ZjY4OnT5/q5WNdfbyG6Ao9NmJnLGNEncdG+vcvVI9kZWXh7Nmz+Pnnn+Hh4YF27drh2LFjaN68OY4fP46nT59i586d+N///lfquzNrQlRUFCIjI+X2k5FIJNixY4dW+lNWr2Px4sUa7+uPP/5gbV+7dq3G+9IXEyZMUPq948ePs97BCAsLU/maylYQLVu2rGjBqeHIkSMKiQsA/PvvvxrvC8hfefW1jIwMREREaKU/Qojm0JyXL8hkMsTGxsptcsjn8+Hr64upU6ca3SaHbG8Uqtq1pbDCccWh7FHD16Xnjcn79++Vfi87O5u1vbBPrcrO19cbKGpCTk4Oa7u2Hhspu+nMtm8UIUS/lPk7Lzk5OQgKCsKMGTPg5eWFVq1aYe/evahXrx7279+PmJgY/Pnnn/juu++MKnEB8rcqqFy5stwtcoFAgG+++UYr/SkrsjdlyhSN98VWpA6ARjbG1FdLly5V+r1vv/2W9fwXVpHX19eXtb13795Fik0dxY2xuNj+PfP5fKVjhxCiP8pk8hIfH49du3ZhwIABcHFxwbBhw5CQkICxY8fi9u3bTNXbtm3bGnWNCQsLCxw8eFDu+WJAQAB+++03rfR3+vRphbYhQ4ZopYLqsWPHFOaG1KhRQ682WCwutt/B29sbrq6uSo+pVq0aNmzYIJccODg44NixYyr72rFjh8Lrent7Y+bMmUWMunDVq1fH2rVr5WJ0dHTE0aNHNd4XAJw9e1ZuJ24+n499+/YpnTdECNEfZWLC7pebHAYHB+PZs2eoUaMGUyiudevWWt/kUJ8nUolEIiQmJpbKzsQikQh79uxBRkYGRo4cqVZV2OLIzMxE+/btkZycDLFYDD6fjzp16uDChQt6uaFlUcdHbm4upk2bhrdv32Lx4sVqb7GQlZWF27dvw87ODvXr11e7vydPnuDmzZto166d1nd5zsrKwp07d+Di4oLq1atrdUKmVCpFREQEsrKy0Lx5c71OXPT5GlLaaMIuO2MZI2W6SF1ERATrJocFCUtp7xVkLINKE0rjwrN27VqsWLFCbv6OQCDAokWLMGzYMK30WRI0PuTRm5MiGiOf0fhgZyxjpEwXqfPw8ICDgwM6duyIbdu2oU2bNka3VxBRLjk5WeGixuFwkJKSorU+ZTIZ3rx5AwsLC63s1/S15ORkZGVloU6dOsy8JYlEgjdv3qBixYowMTHRegzaIJPJkJaWZrDxE0K0z2jnvISGhuLBgwdGu8khUY1t/odYLIaLi4tW+nv69Ck8PT1Rv3591KhRA1OmTNHayqb09HQ0atQIjRs3RuvWrVG9enXcvHkTFy9eRN26ddGwYUM4Oztj586dWulfm6KiotC0aVO4ubnB0tISU6dOpU/WhBAFRnvnRd1N+IhxqlOnjsKbnlQqRe3atTXe16dPn9CnTx+5eVYHDhyAra2tVia2dunSRe4OklAoRK9evcDhcJglzGKxGLNmzUL16tW1tnpM07KystCnTx+5Jd979+6Fra0tpk6dqsPICCH6xmjvvJCyLSgoCHy+fG5uYmKCkJAQjff1+PFjvH79Wi5ZEolEWiuuFhsbq9Cm7C7PmTNntBKDNkRERODdu3dydV3EYjGOHz+uw6gIIfqIkhdilHg8HuuEbG1M0ubxeKztui4xz+FwlMamj/T1PBJC9A9dFYhR6tmzp9wneA6HA5lMhm7dumm8rwYNGqBWrVpyd3r4fD6GDBmi8b4AoEmTJgptZmZmEAgECm/0ffr00UoM2uDh4QFnZ+dSO4+EEMNFyQsxSh4eHti7dy/s7OzA4XBgb2+PQ4cOoW7duhrvy9TUFMeOHUOTJk3A5XJhbm6OKVOmYOzYsRrvCwBOnDghV3W2QoUKCA4OxrFjx+Dk5AQOh4NKlSph+/btaN26tVZi0AYzMzMcO3YMjRs3BpfLhYWFBaZNm4aRI0cyPyOVSrF161b4+fkhICAAf/zxh9Z2QSeE6C+jrfOi6V2lS8pY1t9rQmnXaJBIJKX2+EQqlYLD4RT58VRxxodUKoVUKlWY21Oav682VapUCRkZGXJj5Pfff8fmzZuZOT48Hg/Tp0/HTz/9pKswSw1dQz6jOi/sjGWMGFSRuuvXr2Pfvn14/fo1rK2tMWLECHh7e2PkyJHIyMhgbofb2tpi06ZNhb4eJS/6iy48imh8yGMbI0KhENWrV1fYqNHMzAyJiYmlWnRSF2iMfEbXEHbGMkYMpkhdREQEdu7cialTp8LNzQ2ZmZnIzc1lvj9z5kw0a9ZMhxESTRGLxXj48CEEAgGcnJy0Xsxt6tSpuH79Ojp27Ij58+erHWNkZCRyc3NRv359WFtbq3Vceno6oqKiYGVlhfr162v17kd2djZOnjyJrKwsdOnSxag2Db18+TL27NmDmjVrYtasWRAIBADyf2e2HaZzc3MhFAqNeh8yQog8vUhe9u3bh/79+zO1WWxsbHQbENGK9+/fIzAwEJGRkeBwOLC2tsb+/fu1souvUChEtWrVmK+fPXuGbdu2ITU1VeVx7969Q2BgIB49esTEePDgwUKT59DQUAwZMgQ5OTmQyWRo2bIl9u/fr5XiiDExMejQoQPy8vIAALNmzcLatWsxcOBAjfdV2vr27YvLly8zX2/cuBFhYWFwc3ND+fLl4eTkhKSkJObTNo/Hg4uLCyUuhJQxOp+wK5FI8OzZM2RlZWHs2LEYOnQo1q1bh0+fPjE/s3btWgwePBizZs1CVFSUDqMlJTFlyhQ8efIEQH4J+MzMTAwaNAg5OTka76tx48YKbRKJBC1btlR53E8//YSnT5/KxThw4EC5O4FfS09Px5AhQ5Cdnc1MHr179y7mzJlTgt9AuZ49ezKJS0GckydPRmZmplb6Ky3BwcFyiUuBDh06AMhfMbZ3717Y2NiAy+WCy+XC1tYWu3fvLuVICSG6pvM7LxkZGRCLxbhy5QoWLlwIMzMzrFq1Cjt37sSkSZMwZcoUpipqcHAw5s+fjw0bNsDOzk7udVJSUuSqjpqamurVrXRDq7mhDdevX2cqwAL5b7rp6elITEzUeEXkd+/esbbHxcWp/Duwxfj+/XskJibC3d2d9ZiYmBiFBEwkEiEsLEztv3lRxsebN28U2mQyGcLDww2mmi4bZUmISCRizk2jRo1w584d3LlzB1wuF56enrCysirNMHWGriGfFZwHOh/yytIY0XnyUnC7t2vXrswknb59+2Lx4sUA5Mv8d+nSBWFhYbh79y46d+4s9zrbtm2Tm9Mwa9YsLFq0SNvhF0lZ32jOysoK6enpCu3VqlVDhQoVNNpXQV2Xr/H5fJV9WVlZ4cOHDwrtjo6OSo9zcHBg7cvGxqZIv5e644PL5bLO/ahdu7bGz2Npql69utLvffl7VahQATVq1CiFiPRPWb+GfE3d+WhlSVkZIzpPXiwtLVG5cmW1VwpwuVzWN4oxY8age/fuzNempqasb5S6YmFhIfcorCyaPHkypk6dyrzxCgQCdOjQAdbW1hr/Ww0bNgy7du1SaJ8xY4bKvn766Sf88ssvcjH6+/vD0tJS6XFOTk7w9vbG7du3mbs2HA4HP/74o9q/V1HGR48ePRRK5letWhV16tTRqzFfVL/99hvr36xJkyYG/XtpCl1DPuPxeLC2tkZmZiatNvqCsYwRdT6E6Tx5AYCAgACcPn0anp6eMDU1xdGjR+Hl5YU3b94gLS2N2Qk4JCQEz549w8SJExVew97eHvb29szXb9++1atBLZPJ9CoeXfjuu+/A4/Gwbds25OXlwd/fH7Nnz2a9i1BSS5cuRVJSEs6dO8e0DRgwAD/88IPKv8OXMebk5OCbb75RK8Z//vkHc+bMQVhYGKysrDBp0iR0795d7b95UcbH5s2b8fTpU2b+l7W1Nc6ePWvw46tcuXK4cOECunTpwtRx8fDwwIULFwz+d9MEuoYokkgkdE6+UJbGiF7UeZFIJNi1axcuX74MHo8HT09PjBo1Cm/fvsWqVauQkpICPp+P6tWrY/DgwXLVRZWhOi/6i2o0KCrK+Fi+fDnWrFnDvMELBAI0a9YMJ0+eNJpaJzRGFNE15DMaH+yMZYwYVJE6TaPkRX/RhUdRUcaHu7s76/i+c+cOnJ2dNR2aTtAYUUTXkM9ofLAzljFiMEXqiG5FRUUhPDwclpaWCAgIKPOT4N6/f4+LFy8iLy8PrVq10sp+SCXx5WooddoNzb///otz586hSpUqmDBhgsLKQkIIoeSljDt48CB+/PFHCAQCSKVS2NnZ4cyZM3q1zLw0vXjxAl27dsWHDx/A5XIhFouxc+dOfPvtt7oOjREQEIB///2XSVZ4PB6qVatmFHddxo8fj8OHDzNfb9u2DcHBwahfv74OoyKE6BudF6kjuvPmzRtMnjwZUqkUeXl5EIlESEtLw9SpU3Udms78+OOPyMjIgEgkQl5eHiQSCcaOHYusrCxdh8ZYvnw5fHx8mK8dHR1x6NAhpoy+obp7965c4gLkz4cbMGCAjiIihOgruvNShsXGxjKTPguIRCI8evRIRxHpXlRUlMI5ycvLQ0JCgt58+re0tMSBAwfw+vVrZhsEYyhMdfXqVdZ2tqJ8hJCyjZKXMoxtLgGHw0GVKlV0EI1+sLW1ZZ3wZmtrq4NolONwOKhataquw9CoWrVqsbabmZmVciSEEH1Hj43KsFq1amHQoEHg8/Nz2IL9YubNm6fbwHTo999/B5fLZZYc83g8jBs3jiaNloKuXbvC0dFRoV3d3cAJIWUH3Xkp41avXo0GDRogNDQU1tbWGDFiBJo2barrsHQmICAAx48fx969e5GdnY2OHTti8ODBug6rTOByubh16xZGjhyJO3fuwNraGtOmTUPv3r11HRohRM9QnZdSYizr7zWBajQoovEhj8aIIhojn9H4YGcsY0SdOi/02IgQQgghBoUeG6kpNjYWBw4cQE5ODtq2bYuAgABdh0TKsMWLF2P79u2QSCTw8vLC0aNHtdbX69evMXnyZCQnJ6NWrVrYsGEDLC0ttdZfaYqOjsaRI0cgFArh5+cHX19fXYdECFEDPTZSw/3795lN9mQyGaRSKWbNmoVJkyap/RrGcjtPE+iWr6KijI/Ro0cr7CptZ2eHx48fazyu1NRUNG3aVK56r6WlJR4/fgxzc3ON91egNMbI9evXERgYCODzhnaLFy/GyJEjtdJfSdE15DO6hrAzljFCj4005JdffoFQKIRIJIJYLIZUKsWiRYuQlpam69BIGfR14gIAaWlpuH79usb7mjhxosK2A1lZWZg1a5bG+yptU6ZMgVgsZv5dy2Qy/Prrr0Zx8SfE2FHyoobExERIpVK5NplMhuTkZB1FRIiioKAgjb9mUlISa3tcXJzG+yptSUlJ+PrGs1QqRWpqqo4iIoSoi5IXNdSqVUuhgimXy2WtSUGIrnTp0kXjr6lsvyR926yyOJycnMDlyl8C+Xw+7O3tdRQRIURdlLyoYeXKlTAzM4OJiQlMTEzA4XDw+++/q/VcjhBN++677xTanJyc4OnpqfG+tmzZolDh1sbGBosXL9Z4X6Vt/fr1zL9pU1NTcDgcrFy50mgmIxNizGi1kRoaNGiAsLAwHDt2DDk5OfDx8UHr1q11HRYpo1avXo26deti9erVkEgk8PX1xe7du7XSV4UKFRAZGYnp06cjMTERrq6uWLp0KUxMTLTSX2lq1qwZQkNDceLECQiFQvj6+qJFixa6DosQogZabVRKjGUWuCbQSgFFND7k0RhRRGPkMxof7IxljNBqI0IIIYQYHUpeCCGEEGJQKHkhhBBCiEGh5IUQQgghBoWSF0IIIYQYFEpeCCGEEGJQKHkhhBBCiEGh5IUQQgghBoWSF0IIIYQYFEpeCCGEEGJQKHkhpUYmk2HHjh3w8PCAvb09fvjhB2RlZek6LIMjlUoxZMgQVK1aFVWqVEHLli3x5s0brfX3119/wcnJCXZ2dqhZsybOnj2rtb4IIUQdlLyQUrN9+3bMmTMHiYmJSE1NxaFDhzB06FAY6fZaWvPdd9/h7NmzkEgkkEqliI2NhY+PD6RSqcb7OnfuHKZMmYKcnBzIZDJkZWVhyJAhePDggcb7IoQQdVHyQkrN5s2b5TZRE4lECA0NRUJCgg6jMjwXL15UaHv37h3u3r2r8b5WrlxZpHZCCCkNlLyQUpOTk8Panp2dXcqRGDZld6rS09M13ldeXh5rO/3NCCG6RMkLKTW+vr4QCATM11wuF7a2tqhVq5YOozI8VatWVWjjcrnw9vbWeF8dOnRgbe/atavG+yKEEHVR8kJKzcqVK9G0aVPm64oVK+LAgQMwMzPTYVSG59SpU7CwsGC+5nA42LZtGywtLTXe1/z58xWSol69emHEiBEa74sQQtTFkRnpbMm3b9/qOgQ5VlZW+Pjxo67D0DmpVIq4uDgIBAJUrVoVJiYmug5JLxR1fIjFYoSEhODjx4/o0KEDKlSooMXogMjISERGRsLT0xMuLi5a7QsAeDweKlSogPT0dLl5UmUZXUM+o/HBzljGSOXKlQv9GX4pxEEIg8vlwsXFhS48JcTn8xEQEFBq/TVs2BANGzYstf4IIUQVemxECCFGKjs7mz4gEKNEyQshhBiZ58+fo3Xr1nB2doajoyMWL15M9ZSIUaHkhRBCjEhWVhZ69eqF2NhYAPnzo9avX49t27bpODJCNIeSF0IIMSIPHjzA69ev5R4XSSQSHDx4UIdREaJZRjth18TEBKamproOg8Hn82FlZaXrMPQCh8MBAFhYWNCt7P9H40MejRFF6o6RcuXKsbZzuVyjGWM0PtiVpeuI0SYvQqEQQqFQ12EwjGUJmybweDyYmJjg06dPNJnw/9H4kEdjRJG6Y8TV1RV2dnZ4+/Ytc+74fD769u1rNGOMxgc7Y7mOqHPjgR4bEUKIEbG0tMTx48dRs2ZNAPmJy4QJEzB69GgdR0aI5hjtnRdCCCmr6tatixs3buDTp08wMzMDj8fTdUiEaBQlL4QQYqS+3EaCEGNCj40IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQeHrOoAC169fx759+/D69WtYW1tjxIgR8Pb2RkJCAjZs2ID4+HhUqVIFo0ePRuPGjXUdLiGEEEJ0RC+Sl4iICOzcuRNTp06Fm5sbMjMzkZubC7FYjN9//x0BAQFYsmQJbt68iSVLlmDr1q2wsbHRddiEEEII0QG9eGy0b98+9O/fH/Xq1QOXy4WNjQ2qVq2KyMhI5OXlITAwEAKBAD4+PnBycsK1a9d0HTIhRAWZTIa///4bbdu2RYsWLTBv3jzk5eXpOixCiJHQ+Z0XiUSCZ8+ewcvLC2PHjkVubi6aNGmCkSNHIjExETVq1ACX+znHqlWrFhISEnQYMSGkMLt378avv/4KiUQCANi+fTtevnyJXbt26TgyQogx0HnykpGRAbFYjCtXrmDhwoUwMzPDqlWrsHPnTlSpUgUWFhZyP29hYYG0tDSF10lJSUFKSgrztampKRwcHLQev7o4HA54PJ6uw9ALBeeBzsdnxjY+1qxZwyQuACASiXDy5EmkpaXB3t6+0ONpjCgytjFSEjQ+2JWlMaLz5MXU1BQA0LVrV1SuXBkA0LdvXyxevBh9+/bFp0+f5H7+06dPKFeunMLrbNu2DfPnz2e+njVrFhYtWqTFyIvOxMRE1yHoFWtra12HoFeMaXxkZ2eztvN4PFSoUEHt16ExIs+Yxogm0PhQVFbGiM6TF0tLS1SuXBkcDkfhe05OTjh69CikUinz6CguLg5t27ZV+NkxY8age/fuzNempqZIT0/XXuBFZGFhoZCIlVU8Hg/W1tbIzMyU+3Relhnb+GjRogVCQ0MhEokA5H8irFixIsqXL6/Wv0saI4qMbYyUBI0PdsYyRtT5gKPz5AUAAgICcPr0aXh6esLU1BRHjx6Fl5cXGjZsCBMTExw7dgw9evTArVu3kJCQgNatWyu8hr29vdzt6Ldv3+rVoJbJZHoVjz6QSCR0Tv6fsY2P9evXo3fv3njy5Ak4HA7Kly+Pffv2gc/nF+n3pDHymbGNEU2g8SGvLI0RvUhe+vbti8zMTEyYMAE8Hg+enp4YOXIk+Hw+Zs+ejY0bN+LAgQOws7PDzJkzaZk0IXrO1tYWISEhePjwIfLy8tCgQQO6xU8I0RiOTCaT6ToIbXj79q2uQ5BjZWWFjx8/6joMvVAw7yE9Pb3MfEooDI0PeTRGFNEY+YzGBztjGSMF819V0Ys6L4QQQggh6qLkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlAoeSGEEEKIQaHkhRBCCCEGhZIXQgghhBgUSl4IIYQQYlCMdmNGor9SUlKwbds2jBkzBvb29roOh+ghGiNEFRofhO68kFKXkpKC+fPnIyUlRdehED1FY4SoQuODUPJCCCGEEINCyQshhBBCDAolL6TU2dvb47fffqNn1UQpGiNEFRofhCbsEkIIIcSg0J0XQgghhBgUSl4IIYQQYlD4ug6AGL/r169j3759eP36NaytrTFixAh4e3tj5MiRyMjIAJebn0Pb2tpi06ZNOo6WlKZ+/frJfS0UCuHp6YnZs2cDABISErBhwwbEx8ejSpUqGD16NBo3bqyLUImOFDZG6DpSNlHyQrQqIiICO3fuxNSpU+Hm5obMzEzk5uYy3585cyaaNWumwwiJLh06dIj5f4lEghEjRqB169YAALFYjN9//x0BAQFYsmQJbt68iSVLlmDr1q2wsbHRUcSktKkaIwXoOlL20GMjolX79u1D//79Ua9ePXC5XNjY2KBq1aq6DovooXv37iE3Nxfe3t4AgMjISOTl5SEwMBACgQA+Pj5wcnLCtWvXdBwp0ZWvxwgpu+jOC9EaiUSCZ8+ewcvLC2PHjkVubi6aNGmCkSNHwsLCAgCwdu1ayGQyODk5YfDgwahXr56Ooya6EhwcDB8fH5iamgIAEhMTUaNGDeZxAADUqlULCQkJugqR6NjXY6QAXUfKHrrzQrQmIyMDYrEYV65cwcKFC7Fx40ZkZGRg586dAIApU6Zg586d2LVrF9q0aYP58+cjLS1Nx1ETXcjMzER4eDj8/f2ZtpycHCbJLWBhYYGcnJzSDo/oAbYxAtB1pKyi5IVoTcGno65du6Jy5cqwtLRE3759cfv2bQBAvXr1YGpqClNTU3Tp0gW1atXC3bt3dRky0ZHLly/D3t4erq6uTFu5cuXw6dMnuZ/79OkTypUrV9rhET3ANkYAuo6UVZS8EK2xtLRE5cqVweFw1Pp5LpcLqplYNgUHByt8onZyckJCQgKkUinTFhcXB2dn59IOj+gBtjHChq4jZQMlL0SrAgICcPr0aaSnpyM7OxtHjx6Fl5cX3rx5g8ePH0MkEkEkEuH8+fN49uwZmjRpouuQSSmLjY1FYmIifH195dobNmwIExMTHDt2DCKRCFevXkVCQoLCShNi/JSNEbqOlF00YZdoVd++fZGZmYkJEyaAx+PB09MTI0eOxNu3b7F9+3akpKSAz+ejevXqmDNnDu1VUgYFBQXB09MTFSpUkGvn8/mYPXs2Nm7ciAMHDsDOzg4zZ86kZdJlkLIxkpOTQ9eRMor2NiKEEEKIQaHHRoQQQggxKJS8EEIIIcSgUPJCCCGEEINCyQshhJD/a+9uQqLc4jiOfyfRgQjKTEx7GxsYUdAaIigaSCgTwsBqGUibXjBbxAStikDGoE1BDOEiKMqQooKCWRgZ0dJocldKULiISsJWhdl4F3EHvN6XwaZrj3w/MIvnmXP+58xZ/TjPYR4pUAwvkiQpUAwvkiQpUAwvkiQpUAwvkiQpUAwvkiQpUAwvkn7KhQsXWLt2LSUlJbS3txfU5+LFi2QymVn3I5EIXV1dRZ6hpIXG8CJpzkZHR0kmkxw4cICnT59y/vz5gvr9U3iRpEL4YkZJc/bq1Sump6c5dOgQ69evn+/p/Kvv37+Ty+UoLS2d76lI+knuvEiak4MHD7Jnzx4AotEooVCIdDpNV1cXdXV1LF68mEgkwtGjR/n8+XO+XyQS4e3bt6TTaUKhEKFQiKtXr86onU6nWbduHUuXLqW9vZ2PHz/O+H5iYoLOzk6qq6sJh8Ns2rSJgYGBGW2am5tpa2vj2rVr1NXVEQ6HGR4e/jWLIel/5VulJc3J69evuXPnDqdOneLu3btUV1cTjUY5c+YMO3bsoLKykrGxMVKpFCtXruTx48cAZLNZdu/eTSKRIJlMAj/CT2VlJZFIhFwuR319PcePH2d8fJwTJ07Q2tpKf38/AJOTk2zbto33799z9uxZVq1axY0bN+jv7+f58+c0NjYCP8LLy5cvWbFiBadPn6a8vJwNGzZQVVU1PwsmqWh8bCRpTqLRKLFYDIB4PE4kEgHg8uXL+TZTU1PU1taSSCQYGRkhFosRj8cJh8NUVVWxZcuWWXWnp6e5f/8+4XAYgDdv3tDT00Mul2PRokX09fXx4sULhoeHaWhoAKC1tZXR0VG6u7u5detWvtanT58YGhpizZo1v2oZJM0DHxtJKqrr168Tj8dZsmQJpaWlJBIJAEZGRgrqv3379nxwAWhoaODbt298+PABgIGBARobG4nFYkxNTeU/LS0tDA0NzajV1NRkcJEWIHdeJBXNvXv36Ojo4PDhw6RSKSoqKnj37h179+7l69evBdVYtmzZjOuysjKAfP/x8XGy2ezfHrwtKSmZce0jImlhMrxIKprbt2+zceNGent78/eePHlS1DGWL19OU1MTV65c+c+2oVCoqGNL+j0YXiQVzZcvX/I7JX/q6+ub1a6srKzgnZi/2rlzJ5lMhpqaGmpqauZUQ1KwGV4kFU1LSwvHjh2ju7ubrVu3kslkePTo0ax29fX1DA4O8vDhQ8rLy6mtraWioqKgMTo6Oujt7aW5uZmTJ08Si8WYmJggm80yOTnJuXPniv2zJP1mPLArqWiOHDlCMpnk0qVL7Nu3j7GxMW7evDmrXU9PD6tXr2b//v1s3ryZBw8eFDxGOBxmcHCQtrY2UqkUu3btorOzk2fPnuUPB0ta2PyfF0mSFCjuvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpEAxvEiSpED5A9cFTAdYPPuMAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332115725)>"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 12
    },
    {
      "cell_type": "markdown",
      "source": "* In linear regression it is true that $R^2 = r^2$.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "print(fathers_sons_res.rsquared, pearsonr[0]**2)\nnp.isclose(fathers_sons_res.rsquared, pearsonr[0]**2)",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "0.1539648084533538 0.15396480845335347\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 13
    },
    {
      "cell_type": "markdown",
      "source": "* The value $R^2 = 0{,}154$ that we observe means that our model explains 15.4% of the variation (variation) of the height of the son based on the height of the father.\n\n* Indeed, the values ​​are quite spread out around the regression line.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": "* The difference between the value of the dependent variable and the prediction is called the *residual*.\n\n* We can use the residuals of a model to construct a diagram.\n\n* In this diagram we put, for each value of the independent variable, the corresponding balance.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons) +\\\n    geom_hline(yintercept=0, color='black', linetype='dotted') +\\\n    geom_point(mapping=aes(x=fathers_sons['father'], y=fathers_sons_res.resid)) +\\\n    ylab('residual')",
      "metadata": {
        "scrolled": true,
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332354871)>"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 14
    },
    {
      "cell_type": "markdown",
      "source": "* The resulting chart should not show any regularity.\n\n* Then the rest are, we say, *homoscedastic*: they do not depend on the independent variable\n\n* Otherwise, they are *heteroscedastic*, heteroscedastic.\n\n* If the plot shows some regularity and the data is heteroscedastic, this is an indication that our assumption that a linear model can explain our data may be incorrect.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": "* Balance chart is very easily produced with seaborn.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "plt.figure(figsize=(8, 6))\nsns.residplot(x='father', y='childHeight', data=fathers_sons)",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:xlabel='father', ylabel='childHeight'>"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "execution_count": 15
    },
    {
      "cell_type": "markdown",
      "source": "* Another diagnostic chart that we can construct is the QQ chart (quantile-quantile plot).\n\n* This plot allows us to check an additional assumption of the linear regression model, that the residuals follow a normal distribution.\n\n* The QQ plot depicts the quantiles of the residuals and the quantiles of a corresponding normal distribution.\n\n* If the residuals follow a normal distribution, the plot points should fall on the diagonal.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons_res.resid.to_frame().rename(columns={0: 'resid'})) +\\\n    geom_qq(mapping=aes(sample='resid')) +\\\n    geom_qq_line(mapping=aes(sample='resid'))",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332408760)>"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 16
    },
    {
      "cell_type": "markdown",
      "source": "* The rest give us the key to understanding how linear regression works.\n\n* Linear regression finds the line that minimizes the sum of the squares of the residuals.\n\n* It does this with the *Ordinary Least Squares* method.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=fathers_sons) +\\\n    geom_point(mapping=aes(x='father', y='childHeight')) +\\\n    geom_abline(intercept=fathers_sons_res.params['Intercept'], \n                slope=fathers_sons_res.params['father'], color='red') +\\\n    geom_linerange(mapping=aes(x='father', \n                               ymin=fathers_sons_res.fittedvalues, \n                               ymax='childHeight'))",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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u3DgAitkTfcdYp04dDBw4EABQr149k+6gcnNzY/rq3bs3nJycTNYXj8fDoEGDsGzZMgBA6dKlTdYXAAwdOhSLFy8GAPTq1UvjpSRC1KSkQHDhAhwmTYJLzZpw/OsvvQ6jrdKEEEIIyTTcDx8gDA2FICQEwkuXAKkUYh8fJPfuDZGvL2z1uA8KXgjJJuRyOY4dO4br16/DyckJAQEB8PDwMPewCMkUjx49wsGDByEWi+Hr64u6deuae0jZh1gM/s2bEIaGQhgSAv7Tp5AWLAiRry9i//0X4tq1gXReiqbghZBsYvr06Vi9ejW4XC64XC7WrFmDU6dOmfySAiHmdunSJfj7+4PD4UAul2PNmjVYuHAhAgMDzT20LIvz5QuE585BGBICwYUL4CQlQVyzJlL8/RHXpAmknp5ABi7TUvBCSDbw+vVrrFy5EgCYfCNSqRQTJ07EgQMHzDk0QkxuxIgRkEqlKsn0xo0bh44dO5pk0XS2JJWCf/cuhCEhitmVhw8hzZcP4iZNEL98OcT160NuxHVeFLwQkg28f/+e+dapJJVK8e7dOzOOipDM8fnzZ7UswBKJBN+/f0fhwoXNNCrrx/nxA8Lz5yEIDYXw3DlwYmIg8fZGyh9/IG7pUkjLlcvQ7Io2FLwQkg0ULlxY7c2bx+OhePHiZhoRIZmnUKFCePfunUqWY6FQaJIkgVmaTAb+w4eKhbYhIeDfvQt5zpwQNW6M+HnzIG7QAHIT5EliQ/vZCMkGihQpgvHjx4PL5UIgEAAA7O3tMWfOHDOPzLxEIhFevnwJQFEawJpERkbiwoULePHihbmHYvGWL18OgUDAnPsAsGTJEtja6rOvJXvjxMRAeOgQHIcMQc5y5ZCjaVP82LcPI5OT8fy///DzyRPEr1oFUfv2mRa4ABS8EJJtjB49Gjt37kSPHj0AAPv378/WMy9fv35Fo0aNMHPmTACK58da6vGsXLkS3t7e6Ny5M3x8fJhCjIRdzZo1cfHiRfTt2xeAouBo586dzTwqCyWXg/f4MeyWLUOO1q2Rs1QpOI4ZA45IhA/Dh6OGhweKvHqFVY8fw2foUDwyU50zCl4IyUYaNWqEwYMHA1Bkps3Ohg4ditevXzO3ExMTERAQAJFIZMZR6RYWFobp06dDLpczAcvmzZuxZ88eM4/MshUvXpwJXipUqGDm0VgWTnw8hCdOwHHUKLhWrAjXBg1gc+gQxDVrIubwYfx89gxx69ah89GjuJeqcOmvX7/QrVs3taKjmYHWvBBCsqUbN25ALBartP348QPv37+36BmpmzdvQigUIiVVGnW5XI7r16/D39/fjCMjVkMuB+/lS2btiuDaNchtbCCuXx+JY8dC3LgxZPnzpzlEjjt37qhUcJfL5fj06RO+fv2K/Gl+39Ro5oUQIxCLxViyZAnatWuHwMBAXLt2zdxDUiMWi7F48WIEBQUBAO7evavXccuWLUPPnj0BAD179sTBgwf1Ou7s2bMICAiAn58f1q1bp9e3s5iYGFStWhV//vknAGD79u169WUITfWZHB0dtR4nEomwYMECtG3bFj179sTNmzf16u/w4cNo3749AEWZBX2f/7ScnJxYn8vU5QZEIhHmz5/PvNYPHz40qC99zZw5E0OGDAEArFq1yizfxIkOiYkQnD0Lh3Hj4FqtGlx9fGC7fTsk5csjds8e/Hz+HHGbNyOle3e1wAVQ1Myys7NjvWtdfzOmwJFn0QulP378MPcQVDg5OSEuLs7cw7AIPB4Prq6uiI6OhlQqNfdwMkwul6N37944ffo0xGIxOBwOOBwO9uzZg/r16+t1H6Y+P+RyOXr27ImzZ88ysw0cDgf79+/Xmml0/fr1mDBhglr7wYMHUadOHY3HHTx4EP3792cua/D5fPTo0QNz587VeIxUKoWHh4faZZvevXtj3rx5Wh8fAHz48AGVK1fGvXv3ULBgQZ2/7+Pjo7bYVSAQ4NOnTxqPkcvl6N69O86fP6/yWh84cAC1a9fWeNyZM2fQrVs3tfbr16/rPcujPEfevXuH6tWrqwUIR44cQa1atSCXyxEQEICLFy8yrzWXy8WhQ4dQq1YtvfpKj9GjR2Pr1q0qbRUrVkRISIjR+1Iy9D0kveeItUn7PsJ9+5bJuyIICwM4HIjr1oWoSROIGjeGLJ0ZtpctW4Y5c+Ywz7lAIIC/vz+WLFli1MeRO3dunb9DMy+EZNDz589x7Ngx5oNCuRZh1qxZZh7Z/z158gQnTpxQuUyizxinTJnC2q6cidEkODhYZQGpRCLBhg0btH6pWLVqFet6k82bN2vty1Bsu3TEYjFu376t8ZiHDx/izJkzaq+1rl1bo0aNYm0fNGhQOkascOHCBfB4PJU2Ho/HBAsPHjxASEiIymstk8lMtrNs27Ztam0PHjzA+/fvTdIf0SIlBYKLF+EweTJcatVCzmrVYLd2LaTFiiF2yxZERUQgdvt2JPfqle7ABQCGDRuGWbNmwcvLCyVLlsTQoUOxYMECEzwQ3WjNCyEZFBUVpZYATi6XW9TsH9sYAeD79+9aj9P0rTY5OVnrcdHR0aztP3/+1Pit6tWrV6ztmX0J4unTp/D29mb9WVRUFLhcrsqY5HK5zucxISGBtf3nz5/pHt+PHz/UqjZLpVJERUUxP+fxeGqvna4xGkrT6/P27VsUKlTIJH2S/2OKHIaGQnjpEoRisaLIYc+eEDVpApkR129xOBz06dMHffr0Mdp9GopmXgjJoJIlS6p9E+bz+ahSpYqZRqTO09OT9du6rjHmyJGDtV1XVtLy5cuDz1f9buTo6Kj1w6xt27as7Zqus2dU2gBAqWnTphqPKV26tNpxfD4fVatW1dpX0aJFWds1BUnaVKhQQW2hMY/HY3bQeHl5qR3D4/EM6ksfmtLrV65c2ST9ZXtiMfhhYbCfPh0u9eohZ+XKsFu6FLJ8+SDZulUxu7J3L5L79zdq4GJpKHghJIPy5s2LVatWgcvlgvM7FXa+fPksKgGcm5sbVq5cCR6PxwQVbm5uOsd469YttTYul4sLFy5oPW7VqlXInTs3EzAJhUJs2LBBayDSqFEj1nU0pqq9pKz1lFpAQIDWrKvu7u5YunSpSrK/QoUKMbliNDl+/DiEQqFKW65cufDPP/+ke9y+vr7MQlzl+VatWjUmf0+BAgWYMSpf6wIFCmD69Onp7ksfmzdvVgvogoODzbKIM6vifPkCmx074NS7N3KWKoUcHTuCf/cuUjp3RvTly4i+excJCxZA1qpVuqszWysKXggxgtDQUMhkMuayzKdPn/AxVT4ES9ChQweEhYVh5MiRABQf3roWxuXIkQOfPn2C6+/MmXnz5sXXr19VMpWyKVy4MK5evcostD106BAaNWqkc4wHDx7E0qVLUaBAAQCKxbqmmjHo1KkTLl++zCzcbNiwIZYtW6bzOH9/f4SFhWHq1KkAgJ07dyJnzpxaj7Gzs0NkZCQz0+Xj44Nnz54ZNG65XI64uDimOjigyFGT+vJNly5dEBYWhhEjRgBQZJh1NVH204YNG+L27duoUaMGAMVrZshaHpKKVAr+rVuwnzMHLo0bI1f58nCYNQtyJyfEL1uGn8+fI/bQISQNGQJp6dImqx9kySh4ISSDHj58qJYgTC6Xs+4uMbfixYujYcOGAAAbGxu9jhEIBGjcuDEAoF69enr35eTkxByXnhwQ3bp1Q8eOHZn7MKXSpUujSZMmAHRfCkutRIkSaNWqFQD9n0cej4eWLVsCgF6BnCanTp3Cnj17IJPJmHUtjx8/xoYNG9TGqOwn7ayPsRUqVAi+vr4AFLNTJP04UVGw2bcPjgMGIKeXF3L88QcEly8jpVUrRIeG4uejR4hftgyi1q0hd3Y293DNjhbsEpJBYWFhrO3KBZSEGNOTJ0/A5/NVFuRKpVI8ffrUjKMi6SaTgRcezmxl5t+58/8ih3PnKooc6pjRy85o5oWQDCpRogRrOxV9S7/o6GgEBQVhzZo1ABQf1Pq4desWunbtCgDo1asXnj9/brIxmlu+fPnUdvhwuVyqkKyFTCbDsmXL0KJFCwDA7Nmzde6YMwVOTAyEhw/DcehQ5CxXDq5NmkB4+jTEDRsi5tQp/Hz8WFHk0M+PAhcdaOaFkAxq3LgxihYtijdv3qi0K9dEEP2IxWJ07NgRT58+ZXbTnD17Fvv370eHDh00Hvf06VO0a9eOOebhw4do1aoVrly5Ajc3t0wZe2by8/PDmjVr8Pr1a+YxOzg4MHV7iLpFixZh8eLFTGr7gwcPIjk5GRs3bjRtx3I5eE+f/n925eZNyB0dIW7YEAlTp0LUsCHkefOadgxZFM28EJJBXC4XV69eRevWrZmtxf3790evXr3MPDLr8uDBAzx8+FBtG/CqVau0Hrdjxw6VxdIymQxJSUk4dOiQqYZqVvb29jh16hQGDx6MSpUqAVCk58/uhTa1WbNmjUpNHolEgqNHjxqUZ0en+HgIT56Ew+jRcK1UCa7168PmwAGIq1dHzKFDiiKH//6LFH9/ClwyIMvOvAiFQr0X0mUGPp9v8sWH1kK5vdPBwUEtaZo127t3Lw4fPgx/f380atQoXa93Zp4fyrwc9vb2evep3F0kEAjSNU5l/SAHBwe9jmNLpJeUlKT1WIlEwnoZRSqV6tVnZj024P+Le21sbNL9eqc+R5ycnDB37lzmfHNzc2O9P0Nea0Nl5LGlV3rfQ1IXsUx7Pxkeq1wOTkQEuKdPg3vqFDiXLwM2NpA1bgzZpEmQNG0KFCwIHgDTZCz6v+z0OZNlgxeRSGRRpe2pttH/8Xg8CIVCJCQkZInaRqklJSUx/03P652Z50diYiLzX337VM6GiMXidI1TmVk2ISFB53HFixeHg4MD4uPjVdobNWqk9diaNWuqTf+npKSgWrVqeo01Mx5b6nEp/5ve15vtHNF1vhnyWhsqI48tvdL7HlKnTh1cunRJpa5XwYIF4ezsbNhYExMhCAtTXA4KDQXv3TtIPD2R3KQJxEOGQFyjBpB6h1cm/W1nlc8ZfSYesmzwQgixLq6urti+fTv+/PNPxMbGAlBsu508ebLW49q2bYunT59i0aJFTNv8+fNRvXp1k46XWI+VK1fC39+fqa6dM2dO7Nq1Sy3rtDasRQ7r1EHSoEGKIofp2GpPMo6CF0KIxfDx8cGDBw8wdOhQHDt2DM2aNdNr19b48eNRuXJldO/eHTt27GByjhACKKoUnzlzBgcPHsTAgQOxceNGeHp6aj8oJQWC69cVwUpICPgvX0JapAhETZogqW9fiH18ABOVriC6UfBCCLEojo6OBi0+VWa5dXFxMfKISFbA4/GYRISaMkRzP35UFDgMCYHw4kVAIlEUOezRAyJfX8iKFcuW2WwtEQUvJEuTSqWIjIyEh4dHuqaIrUFycjKSk5PT/WGtafGiNsoFsemt8GxIXwDw7du3dB+jXPuQ3nVUmio+66Jcb5J2DCkpKRqLFRr6PBrKHLlMMoNcLjf4dVMhFoN/6xazdoX/5AmkBQpA5OuLuLVrIapTB6AaTRaJtkqTLCsgIABubm6oXr063NzcMGDAAHMPySji4+NRq1YtFCpUCCVLlkSRIkWYa/navH79GvXq1UP79u0BABs2bNDrQ7RSpUpMccQDBw4w5QW0iY2NRc2aNVGzZk0AistB4eHhOo8bNmwY8uTJg+PHjwMANm3apLaAl03dunXRunVrAEDr1q3RuXNnnce8efMGefPmxd69ewEoCgxu3bpV53GvXr1CnTp14OPjA0BRN0gikWD27NkoWLAgChcujNq1a+Ply5cqx40dOxazZ88GoEiStmLFCp19Gerly5eoXbs2/Pz8AABbtmzJMjv7du/eDQ8PDzg6OqJ06dK4cuVKuu9DcOYMnPr0Qc7SpZGjQwdFkcNOnRRFDu/dQ8KCBRA1b06BiwWj4IVkSdOmTcPZs2dV2vbv329QFV9L07p1a5UPxoSEBLRs2VLr7rrExET4+fkhIiKCaTt48KDOD9A2bdqoFZh89OgRRo8erfW4P/74A69evWJuJyUloWXLliq5NtK6desWdu7cqdZesmRJrX316NFDrcjh+fPnMXfuXK3H1axZU+0DffTo0cwOHTYJCQlo3769yvO/detW9OrVCytWrGAe36tXr9C+fXsm8Prnn3+wadMmlfuaPn06QkNDtY7REPHx8Wjfvr3K879nzx6sXbvW6H1ltosXL2Lo0KHMrMv379/RpUsXvH79WvNBUin4t2/Dfu5cOA4bBgCw27wZckdHxC9dSkUOrRQFLyRLSlsoUSlt8Tpr9PjxY7W2lJQUXLt2TeMx4eHh+Pjxo8olFZlMht27d2vt6+bNm6ztytkKTdgqJicnJ+P69esajxk7dixru7aAB4DGAGDz5s1aj9M066QtKd79+/fx5csXtbpC58+fVxmnVCrF169fcf/+fQCKRHpsTJHh9f79+/j69avKGOVyuc7X2hocPnyYyfECgAk+035R4fz8CZv9++E4cCBylimDHK1aQXDpEvI0bQqfChXgeO4cFTm0crTmhRBCiHWTycB78OD/a1du31YUOWzUCPFz5jBFDnMDOGzusRKjMGjmpXfv3mp1XJTevXuH3r17Z2hQhGSUpjUPWSFlv5eXl1qbjY0NatWqpfGY8uXLo0CBAiqLljkcDvz9/bX2pSlXirZaQwBQqlQp1jEq18CwmTVrFmu7roXWjRo1Ym0PDAzUehxHw+WBwYMHazymYsWKyJcvn8qYuFwu6tevDz6fr9KWL18+Jn2/smhkWj179tQ6RkNUqlQJefPmTfdrbQ3atGmjcqmvFYC1YjH+WrpUUeTw1CmI69dHzMmTiiKHq1dTkcMsyqDgZfPmzfj+/Tvrz378+IEtW7ZkaFCEZNS0adPQuHFjlbb27dtr/WCyFsePH1cpOMjn83HkyBEIU2f0TMPe3h779+9XWT/SrFkzDB06VGtfR44cUatWXLp0aSxevBjr169Hu3bt0LlzZxw7dkxtjEWLFmVuC4VCnDhxQuUDPi0fHx/WD9i0C1/T2rp1q1qwVK9ePUycOFHrcTdu3FBrmz9/vsadQoBiG/fBgwdRrFgxps3Pzw9btmzB4MGDmYDBw8MDBw4cgOPvBZ+DBg1SC6YmTZpkknw0yjGmfv5btmyJfv36Gb2vTCWXo3G+fLj8xx/Y+zvwnAugcc2aSAkORtTjx4g5exaJ48ZBUrUqkMV2FxJVBq950fSt5cWLF8iVK5fBAyLEWHbt2sWsKdi4cSPWrVtn5hEZx9mzZ/H161fmtkwm07imIrXixYvj8uXLWLNmDQCgS5cu4HK1vwV8/vxZbbtzfHw8xo8fj0mTJiEsLAznz59H7969Vcbg7OyMmzdvMotE161bhwoVKugc48qVK/H9+3cUKVIEgGLGyFGPHR9XrlzBoEGDACgChf379+s8pmjRovj+/TvKly8PAKhSpYpeM3MlSpTA1atXmT569+4NPp+PSZMmMQHRwYMH1RYaL1q0iAlgAgMDMXz4cJ19GapkyZK4du0a81p36tRJ52ttkZRFDseMgWvlynCtVw81Xr+GrGVLcDkc3Nu8GbaHDyOlSxcqcpjN6L3m5Z9//mF2anA4HAQEBMAuTXbB5ORkvH37Fp06dTLuKAkxkPIN2yrfuDWYPn26ytS5TCbDli1b8Ndff6nNkrDRJ2Ot0saNG9XyaXz9+lVtoalcLsfMmTMREBCg0m5ocVRDisspZz3Sm89HU8IyXdK+/+nTd2afj+l5rS2CXA7eq1cQKNPwX7sGuUAAcf36SBw9GuLGjSFzd8fjFSsgO34cL7XtMiJZmt7Bi7u7O6pWrQpAsVWyVKlSalkwhUIhvLy80KdPH+OOkphUYmIiXrx4AUdHRxQrVkzjrBrR7vv378yOH1MmIfv16xdre3R0tF7BS3r8/PlTLembpvND07jSKz4+3jgJyPQgk8mYrdGZUST0x48fAICYmBiT9xUfH8+sTbToHC9JSapFDt++haRkSYibNEHSsGGKIocGBsEk69I7eGnbti3atm3L3J4yZYrKNVVinW7fvo2uXbsyHzwNGjTA5s2b4eDgYN6BWZlNmzapbPUdNmwY6tSpA1dXV6P3VaZMGbUtzHZ2dvDw8DB6X5UqVcJ///2n0iYSieDg4IDExETmQ5HH46FcuXIZ7u/atWvo3r07U5jx9evXSE5ONskMQnR0NLp27cps6w4PD8fTp09ZF0RnlEwmQ5s2bVQuK/H5fKxevdrofQFAWFgYunfvzuSZWb58OXx9fQ2eCTM27rt3/y9y+DvJnLhOHSQNGKAocvj7siEhmhg0d7lp0yYKXLKA+Ph4dOnSReVbYFhYGKZMmWLGUVmfjx8/quUoiY+PVwn2jcmZJS+Fra2t1sWwhnJxcWH91j5p0iTY2dkxfbq6umY4AWB0dDQCAgIQFxfHtCUkJGDmzJkZul9NRowYoZKZWCaToWvXrhCLxUbva/LkyWoLhPfu3Yvt27cbva+oqCh069ZNJTPxgwcPdCbtMymRCIJLl+AwZQpcfHyQ09sbdmvWQFq4MGI3bUJURARid+5Ecp8+FLgQvRj8bnfmzBns27cPHz58UKufweFwTJI5khjX06dP1aavxWIxzp07Z6YRWacTJ06wtr948cIk/bEljouOjsa7d+90ZqNNr8uXL4PH46lcUrGxsUFMTAxu3LiBEydOYNy4cTh48CCKFy+eob4ePXqEhIQEtWApJCTEJAHMxYsX1QKVjx8/4v379yq7iYxB09/U4cOH0a1bN6P29fDhQ7W6SzKZDGfPnsXUqVON2pc23E+fmCKHgosXwRGLFUUOAwMhbtIE0uLFKZstMZhBwcuCBQswbtw4FClSBF5eXsiRI4exx0UyAduCQ23thJ2mwoimKgRpa2vLXFZJzRSvm52dHbhcrlq2Vnt7e7i5uaFp06YYN26cXjuC9OmLbZZH29bljLCxsWFdW2OK/jRd9jJFX5n9PDJ+nyOCc+fgcvAg+I8fQ+ruDpGvL+LXrKEih8SoDLpstGrVKgwZMgSvX7/G8ePHcfDgQbV/xPJ5eXnB29tbZbcFh8NhtpwS/bRu3Zo1cDDVrrtBgwapXCLicDho2LAhChQoYPS+unbtqrZA18bGxiSXxCpWrIjy5cur7f4x1fmY9nkEgKZNmxp90TMAjBw5krVdV40oQ1SpUgVeXl5qz+PAgQON3hfn2zfY7NoFp6Ag2C1aBADgffiAlA4dEH3pEqLv30fCwoVU5JAYnUHBy8+fP9GuXTsjD4VkNh6Ph127duGPP/5gFpb+/fff6N69u5lHZl1sbW1x+fJluLu7M23ly5fHkiVLTNLfgAEDVC7RCAQCzJs3zyS7xEqXLs1UQlZauXKlymM1FoFAgH///VclT5SjoyM6duxo9L4AxaLqSZMmMduWc+TIgX///dckz2ObNm0wf/585jaHw8H27duZHDPGJBQKceDAAfj6+jKzLV27dmWqiWeIVAr+nTuwnzcPOXx9katsWThMnw65vT2KBAWBy+Wi0IwZSBo6FFIvL7osREzGoOCldevWBpUhJ5YnR44cWLduHXNNXlfad8KucOHCePDgASZNmgQAJlusCwDdu3fH8+fPmdsikQjNmjUzyfbsZ8+eqWWqHTJkCD59+mT0vsRiMYKCghAVFcW0xcfH6ywCaSgOh4PBgwejTJkyAIBChQqZ9NJKr1690LJlSwBAixYt0LRpU5P1lStXLmzZsgUzZswAAHh7ext8X0yRw0GDkLNsWeRo0QKCixchat4c0SEh+PnoEeKXL0eZvn0hk8n0SkZISEbpvebl7t27zP/36tULAwcORFJSEnx9fVmv+VepUsUoAySEqGJbDB8dHY07d+6gWrVqRu1r586dausnUlJScPjwYaNfhnjw4AEePXqk1v7PP/9Q4svMJJOBFx7+/yKHd+5A7uICUaNGSJg1C6IGDSCnLOrEzPQOXry9vdVKkc+bN09tuloul4PD4WRKwieSfVy+fBnHjh2Di4sLBgwYoFf+FLlczsxQvHr1ytRDxN69e7Ft2zYAUNnuq41cLse1a9fw48cPuLu76/UNWVPCMX2SxL1+/RrXr18HoJixARTByKVLlxATE4NKlSqhRIkSzO8nJSWp7cjhcDhMYjdtPn36xMya6PP8Jycng8PhqD0+ffoy1M6dO5mAKTIyUu/jXr16hQsXLgBQfx4BRYHaggULqhwjl8uZJHXpSegXGxvL7PqqUKGC3pfszp8/z5QwSLsjNC1ObCwEFy4wAQv32zeIK1aEuEkTJEyfDknlyhZTK0gul+P178y6Hz58MPNoiLnoHbycP3/elOMgRKPJkyczNVoAYMWKFTh37hxKly6t8RiZTIaBAwfiwIEDAIAZM2bg/fv3mD9/vknWNPj7+6tsh122bBl8fX1Ro0YNrWPs378/Dh8+DKFQCJFIhN69e2POnDlax5g7d27mQzA1bVWlAeDAgQMqi1+nTJmCSpUqoWfPnnj+/Dl4PB4kEgmWLFnCpPmvUqUKNm3apHI/KSkpGqtNK12/fh1t27ZlLmXNmDEDcrlcaz2fsmXLsgYv2l7njPjzzz9x6tQp5nZsbCxKlSqlckmOzd69ezF06FDmNRo2bBj27duHwMBAREREAFAUa1yxYgVT3VwqlaJPnz7MNverV69iypQpmD59uta+3rx5g9atWyMqKgpcLhdcLhc7duxA3bp1tR43atQoleSCkydPRrNmzVC4cGFFg1wO3rNnTKI4/s2bkNvbQ9ygARImTYKoUSPITbBwOaMkEgl69uyJ06dPA1CUr3BwcKDcVNmQ3sFL/fr1TTkOQlhFRESoBC6AYm1Ep06dEB4ervG4Xbt24ciRIypt//33Hxo0aIBWrVoZdYxXrlxhzePRsWNHvH//XuNxO3bswLFjxyCXy5nih5s2bUL9+vXRokULjcdp+hadkpKiccvyly9fMHjwYJUZ0W/fvqFTp0749OkTpFIp87NRo0ahTp068PDw0LgbJigoSOuHfNeuXdXW4MycOROBgYEaZ81CQ0NZ1+2cPHlSYz8ZkTpwUfr58yeuX7+OmjVrsh7z+fNnDBs2TOV5/PjxI/M8Kscvk8kwfPhw1K5dGwUKFMCWLVuYD1yltWvXon79+mrVz1MbNGgQoqKiIJFImLYePXrg6dOnGrPl3rlzRy0rskwmQ6CfH67NmsXUDeJ9/AhJmTIQNW6MhHHjIKlWDTCwzlNm2bhxo9rf2qpVq1C/fn36jMpmsk61OpIlXbx4kbX9+/fvWo978OCB2jd4Ho+nklHVWI4ePcrarmuq/uHDh2of1gKBQOcYU2dOTY0teZ1SRESE2qVcmUyGT58+sV4WUqbMV14SSSs6OtqgMd66dUvjMXv27GFtN2WdKDbz5s3T+LOnT5+qjUcqlbI+j3K5nHkeHzx4oPb8CwQCPHjwQOtYwsPDVQIXQHFJUtvlktSz5Mrqc8MB3I2MhFP//uB+/47EUaPw8/59/Lp4EYlTpkDi42PxgQsA3L9/X+15FgqFJvm7JpbNoOCFy+WCx+Ox/uPz+ciVKxcaN26s8U2dEH0x09xpCIVCrcflzp2bNUlczpw5jTKu1FKvEUlN1+WpXLlyqeUZkcvlOseoKfmdpudK2RfbWhlbW1u1cUokEoPHoOvn2uovaXoeM5uPj4/Gn+XKlYs1mGJ7HqVSKbPtW9NrnTt3bq1j0TRLlUvTgtmkJNSOi8MyAC8A9P7d/ABARzs7REVEIG7LFqQEBkJmgrxAppYnTx61/DVSqdQkf9fEshkUvCxYsAAFCxZEiRIlMHLkSMyZMwcjRoxA8eLF4e7ujsGDB0MsFqNdu3bYtWuXscdMrJxYLNa7anCTJk2QP39+tfZRo0ZpPS4wMBBOTk7MbQ6Hg9y5c8Pf3z99g9VD7969Wafwu3btqvW4Hj16wMHBgfmg5/P5yJs3L7NOQlt/aZUqVYrZ8sumTJkyaNGihdob//jx48HlcpkPXj6fjwYNGjC7BYcMGcJ6fytWrNA6xl69eqm1eXl5aV2/Mn36dNaAr1mzZmptycnJzKU2Q2kKgP/66y+Nx1SoUAFNmzZlfR5Tj53H46FJkyaoWLEiAMVltrTbsPPnzw8/Pz+tY5w8ebLa/fbr109th6cgJATOAQHIVaoU/ti4EV4CAZYAUL5KFwDUnjLF6qszBwUFqWQr5nA4KFSokElTExDLZHCSOm9vbzx79gwLFy7E2LFjsWjRIjx//hze3t5ISkrCpUuX0KlTJ61TsCR7EYlEGDlyJPLnzw9HR0c0atQIHz9+1HoMl8vFzZs3Ub9+febNv2/fvhgxYoTW4/Lly4fQ0FBm90716tUREhKiMZV/RvB4PBw/flzlm7WTkxMWL16s9Tg3NzecO3eOWd/Spk0bnDlzRme5jalTp6Js2bIq/e/cuVPrMRwOBxs2bMCoUaOYuj2DBg1Cv379cPz4cTRo0AAA0LNnT2zbto1J3DZ16lT8+eefKvc1ZcoUnYnj5syZg9GjRzMfNJ6enjprZvH5fBw+fFgtgNm6dSvz/9HR0ejUqRMKFSqEQoUK4c8//9R7Z1daHz9+VFsjpKseFYfDwaZNmzBixAh4enoCACZOnIh+/frh6NGjzKJpf39/bNmyhXks7u7uOHfuHPLmzQtAEbicOXNGZ1mFzp07Y+vWrahduzYARUbemVOmQHD5MuynToXjhAkAAJtTpyD18EDsxo2IiohAyYgI3KtVC8m/X8cqVaogKCgoPU+PRSpUqBDOnTuHqlWrAlDMkp06dcoo5SmIdTEoeNmwYQP69u2r9ibD4XDQr18/bNmyBQAQEBDAXPMlZObMmdi9ezcz7f7o0SN07txZ7Zp+Wra2tti3bx/27dsHAHpnCi1QoAAz+9G5c2fkyZNHxxGGSUpKQo8ePVQuy8TFxWHZsmU6jy1YsCCTSGzy5Ml6jXHatGnMrhZAMW3erVs3nekJBAIBxowZg8GDBwMAk6W3atWqTKA1ePBgtVmkxYsXM4Gjvb09hg4dqnOMgGI2YsyYMQAUz7+uqtcJCQno378/EzgppZ7l6du3L8LCwgAoLruEhobqPR42b968Yap0Ozs76xXcCoVCjB07lknepwxiqlevjsmTJwNQJBJMO7Pj4eHBBJ2lS5fW+1JH8+bNsfr3bpqg27eRq1QpOPv7g//4MQp16ICCbm7Id+AAEubOhbhJE8DODo6Ojjhy5Agzs2PsQpPmVKRIESYLeMeOHfVKm0CyHoOCl8TERI05Ed69e8csVHRwcNC5NoFkH/v27VNZbCeRSBAREYE3b96YcVQZ9+jRI3z8+FEteNC0ADWj9u/fr7Zo8enTp3j37p1J+sssDx8+xJcvX9SeR2WumISEBLVK0GKxGCdPntQZAFsdiQT8a9dgP2MGXBo0ALdZM3hwuYh1cED8P//gZ0QEYvftQ7GpU3EvPBylvbzMPWJCMpVBwUubNm0wfvx47Nixg5myjYuLw7Zt2zB+/Him7lF4eLjFLMIjml26dAmrVq0CoNg+m1XExsZi+/btABTJyHTt/skOzp8/jxMnTgAAa2VqNi9evGASxSUmJiImJkav4/bt24eVK1cCAM6ePWvAaE1v7969zPOQ0WR4T548YfKN7NixQ+3nnz9/ZnaE3blzB0lJSSo/T13kMGfp0sjRvj0Et24hxc8Pn1avRqRMhm8DB0LUogXkelwmWbhwIXOpTt/XzBokJibi8uXLAIDbt29n+m40YhkMCl5Wr16NBg0aoHv37nBxcYGtrS1cXFwQGBiIRo0aMW9YHh4emDNnjlEHTIxr5cqV6NixI3Opr0OHDjqv+xuqc+fOKgsdeTweSpUqZZIp7V+/fqF8+fJMWYvbt2+jXLlyJglgypUrh0KFCqldFunSpYvR+wLArE9JLX/+/Fp3GwGKyz9dunRhttLOmzePyVSqydOnT9V235QoUULnh+G8efMwcOBAJpPsjRs3mLo+mlSsWJF17YJywa6DgwMaNmyocg7x+Xy0atVK5yUpNnPmzFFJ2ieRSPDHH3+k+34ARdK5Bg0a4Pbt2wCAbdu2oXXr1szPP3z4gIoVKzIL1WNjY1GyWDFIr15VL3JoZ4f4RYvw8/lzxBw5gqRhwyAtUiRd42ndujXmzZuHnz9/AlAEj1evXjXosVmS+Ph4NGvWDIcOHQIAbN++HT169KAAJhsyKHhxdnbGgQMH8PjxY2zatAnBwcHYtGkTHj16hP379zPXkP38/ExafIxkzOfPnzF9+nTI5XJmKj4xMRFjx441SX9///03unXrxqxpKFOmDPbu3atz260hhg0bpvZNOiYmBuPHjzd6X3Z2dti/fz9KlSrFtBUpUgTDhg0zel8AWJPDffv2TesOrnfv3mHu3LmQyWTMG31ycrLO56N58+as7XXq1NF63KJFi9Tabt26pbJWJ62vX7+yLr59/Pgx8////vuvSvBWv359LF++XOtYNGFbUH3jxg2DLmMGBQWpbUW/fv06Eyj6+flBLpczb7jlAbyXSJCnbVsILlxQLXK4YgVEbdtCrmPhtibnz59nSkCk1rdvX4Puz5KsXbsWr169UglWzp49i+PHj5txVMQc0v91JRUvLy940bVWq/X27Vu1N1yZTGayOkACgQALFizA8OHDUblyZWzfvp11G7QxaPoAMtWsUtGiRXHhwgV0794dp0+fRpkyZdQWnhoL29oWqVSKjx8/Ml8c0nr79i1ru67XOu2lDSXlN3pNNNVfunz5MrPANa23b9+Cy+WqfYtOPcYcOXJgx44dePPmDapXr46FCxcafafJxYsXUbRo0XQdoylp353bt9EkVy70+PgRTQBMB3AGgAzACABPChbEWSNnENaUCFBXYkFr8PLlS7X1XgKBwOrXzZH0S1dVaS8vL9jZ2alUmNaEqkpbvkKFCqm1cTgcrYnEjMEUMy1pFSxYkHWnm65LKxmVGY+tQIECePnypcqHPJfL1RoIFixYkDWg0PV82NjYsF5q07WdWxNt9ZcKFSrEOv3PNsa0eVaMSVuSOk1y5MiBqKgo5nYNAH0BdF23Dvbz58NPIMAhAMocyI9//6uTzstB+qhQoQJru6bA1poULlwYAoFAbeE/23sZydr0/mro7e3N1JLx9vZGtWrVWP8pf0YsX8GCBTFq1Cim4Bug+FDICuuUli9frrbTzd7eHvPnzzdZn/Hx8cwaD00zD8awaNEitSApODhY6zbf4sWLY8iQISqzQXw+H7NmzdLal3KnT1qhoaFaj2O7ROHl5aU1kV6JEiUwaNAgtRkrXWNUUpYk0DcBYp8+fdTaypYtq3FmSCO5HFvGjcMYACN/N3UFUMjZGdLgYESFhyPuwgVMAfAr1WFcLhebN29OX196aN68OcqVK6fWrlyUb80GDhwId3d35vzncrmoUaOGyvoikj3oHbycP3+eeeM5f/48zp07x/pP+TNiHSZMmICNGzcyCxVXr16N8uXLm3lUGZcnTx7cv3+fmUUqUqQIwsPDTZbM6vr166hUqRKzKPLmzZsZ3r2iSc2aNXHu3Dnm22b58uUxYMAAncdNmTIF//77L5O4r3///jov+9asWZPZnaR09+5dnZf7Zs+ejZkzZzIBpIeHBy5duqRzjNOmTcO6deuYBbiOjo4qa4m09aesfr1x40a1Sths5s6dq1bV+cKFCzqPAwAkJEBw/75ijKNHo9XYsZhcpAgcc+YEn8PBhT/+QKUXL5ASEAC5mxs8PT0RFhbGnH85cuTA06dPDZ7B0qVDhw4qt4VCIZPYzZrlyJED586dY/LXdOvWDXv37jVowTaxbgZVlTZm9c60qdBFIhG8vb0xadIkAIrr+ytWrMDbt2+RL18+9OvXj0m5TYyjVatWyJs3L44cOQJ3d3dzD8do8uTJg7Zt22LFihVo3bq1yabNY2JiEBAQoFKMMCoqCtOmTTPZTE/p0qVRokQJvH//Xmd9HCUOh4M2bdrgzZs3uH37tt7JvapVqwY+nw+JRAI+n6/3FH3//v1x//597Nu3D9WrV9d7jG3btsWoUaMQGxur17qhw4cPqyUEHDduHMqWLauz34EDB2L27NlITk5WSTvPhvvqFYS/KzILrl6FnUwGLoCUNm3wc8QIyAoUwDAAmpZpe3p6omPHjti8eTPat29vsno8ERERCA4OVmkTiUTo1KmTxW5ZTw9nZ2e0adMGe/fuZS3VQLKHDIWrT58+xe3bt/H+/Xv07t0bbm5uePnyJfLly6dSV0ab1Im8pFIp+vTpw6TClkgkmDFjBpo2bYo5c+bg+vXrmDNnDtasWWOSNO+EGOLx48eIj49Xu1REM5CZQ5nzIzWhUIgrV67oHTSxSkqC4OpVJmDhvX0LSYkSEDdpgqQhQxD76xdkQUEQN2hgUUUO086UKT158iSTR0KI6RicYTcgIADlypVD7969MXnyZHz69AmA4jKEMt15et29exfJycnMgrnw8HCkpKSgY8eOEAgEqFu3Ljw8PJj04MT6XL9+nUmrvn//fpOuDYmIiGCShe3evRvv37/X67hr165h0KBB6NWrF7Zt26ZzjA4ODqy/k7YQH5vv379jwYIFAIBly5bpnThu4sSJzDbc27dvQyqVIj4+HrNnz0b37t0xYcIEfP78WeUYkUiEnj17YsmSJQDArGHTJTg4mMlgK5FI8N9//+l13Nq1a3Hs2DEAisto+uTiePLkCfLkycM8D/o8H2zPs1Qq1ev5L1OmDLMgOTk5GeIXL2C7cSNT5NC5Z0/w3rxBUv/++HnzJn5du4bYadOw4ulTLPu9hkTfzMZfvnzBtWvXACiS1KWeqdPmn3/+Qc+ePQEo1nLpeh41XYoy5aWVS5cu4e+//wYAHDt2zKR/14QABs68jBkzBufOncPJkydRt25dODg4MD9r2bIllixZYtB0eWhoKOrWrcvUVomMjESRIkVUpo6LFStm9WnQs6vQ0FAEBAQwb74zZszA169fDQ52tXn16hXq1q3L9PXt2zdUr14d9+/fR758+TQed/bsWXTv3h1yuRxyuRwnT57Eixcv1KbhU9NUKVnXh2dUVBQaNWqEHz9+AFAkNrt8+TJCQ0NV/qbS6tu3L5OkC1Bkt65QoQLy5MmDiIgIiMVi8Pl8HDhwABcvXoSbmxtkMhlq1aqlUtbj8OHDqFevHgIDAzX2NXfuXCbppNKoUaOQK1curUnnZs+ezQRJgOJvuVWrVjipZVtwbGws6yVpd3d35ssRm1q1auGff/5RaZNIJDovbxcuXBjiVOuSbADk9/GB1MMDoiZNkLRhA8S1awOpXke5XI6BAwfi6NGjTEAXHByMmjVrat1h+e3bNzRq1Ajfv38HoAgcmzdvjrNnz8LOzk7jcdOmTVNZaHvq1Cm0bdsWR48e1XiMv78/Jk+erFZ1W9vrnBFHjhxRyXMzZcoUxMbGmixfFCGAgTMv+/btw7x589C0aVO1HR1FihTRmFNCm9jYWNy8eRNNmjRh2pKSktTexB0cHFhzT3z+/Bl3795l/n39+hU8Hs9i/nE4HLOPQdc/ACa9/8mTJ6t8a5TJZFizZg2+f/9u9DGOHTtW7RuqRCLB33//rdcYlW/EUqkUq1evRlRUlMZjNCVJu3Pnjta+Nm/ejJ8/f6rMarx//55J3KfpX+rARenbt294/vw5s4VUIpEgLi4Oa9euBY/Hw5kzZ1jrkU2dOlXrc8uWbA4AevXqpfU4tufk9u3bePv2rcbHVblyZda+xGKx1nNh9erVrMetWLGC9Tj+16+w274d/yUmIgqKoAUAUgCUBjC7Tx8kL1wIWfPm4Dk5qRz77NkzHDx4UKWWkkwmQ3BwsNbXbMOGDcxONKXXr1/j4MGDWo9bs2aN2uO6fv06Pn36pPEYJycnXLlyRWVRde3atTF79myT/F1PmjRJZaZFLpdj4cKFSEhIMEl/PB6P+ULL5XJN1oc1/rOGzxl9/unDoJmX+Ph4jbsN9N2mmNaFCxeQP39+lZ0FdnZ2aveXkJDA+k1l7dq1Kt+OJ06cqPcWy8xiyUUqlWuUnJycTFalVfmtM62UlBS9+kzPGDUlUfvx44fWYw0Zo7bK6dr6+vXrl1pBQQ6Hg9jYWKO8BmKxGD9//oSrq6vaJSSl5ORkuLq6Mpltc+TIoVffMplM63GaKlx/+vSJ2e2UFlt2XaW0Y0rdr6bka8xrLZEA168DJ04o/j14ABQogB8A/oQiaFF6DiD03DlM/l2jKK3ExETweDy1x/ft2zetz1t0dLTaa83j8RAXF6f1OE3P49evXzXmcwEU6Sw+ffqEdevWoX///ggMDDTZ3zXb35pcLodEIjFZn8rPADs7O6oqnYYlf84Yk0HBS4UKFbB//37W1P/Hjx/X+OakTWhoqMqsC6DYXrl//37IZDIm0n7z5g3q1aundnz//v3Rpk0b5raNjY1FZZR0cHAwOLDLDKkLbJrqefPy8sKtW7dU3sRtbGzg6uqqV5/pGWPp0qXx6NEjtfayZctqPdbLywt37txRG6OLi4vG41q1aoUjR46otXM4HK19lShRAjweT2WGSCKRoGjRolqPY8tCC0Ctjc/nw9PTE9HR0RpnNXLlyoXo6GimVlFMTIxK35r6srOz03qcvb0961bx0qVLa3xspUqV0hgIpj0mdb8lS5ZUK5mQB0BvPh8iPz/wz50DJz4ekurVIW7bFpKVKyEtUwb9c+Vi7Wvw4MEax5g/f3619Rw8Hg/lypXT+Vrz+Xy1iti6Xms7OzvWmeYSJUro9TeTuqCmqf6uPT098eTJE5VAy8HBAQ4ODibrU/mcJCUlWdT7vLlZ+ueMvvQJSA0KXiZPnoy2bdsiMTERnTp1AofDwc2bN7Fz505s3LhR42p3TV69eoXIyEi1gnPly5eHUCjEgQMH0LZtW9y4cQPv3r1jdiOllj9/fpXZoB8/fmj81mIOcrncosaTlnJsUqnUZONcunQpWrVqxcw4cDgcrFq1Cg4ODnr1mZ4xLlu2DBcuXGDWkwCKpHwzZszQeuyyZcvwxx9/ICYmBmKxGFwuF//88w/s7e01Hufn54c5c+aoXS5duXKl1r66deuGkydP4ty5c5DL5eBwOPDz88Mff/yh9bjFixdjxIgRKm0tWrRAvnz5sHXrVggEAqSkpKBChQro27cvpFIpKlWqhM6dO6vs7gMU1bZTP59pn9sbN26wJp2MiIjQetzGjRvRtWtXlQ/6YcOGIWfOnBof2+XLl5EnTx619po1a6oc8/XrV6aWzffv37Fq1SpcvXIFkl+/EAugHoCLAGT37kHUuDHiFy6EuEEDyFPvUJTJULNmTbUaQMrij5rG6O7ujnnz5mHs2LEQCAQQiUTIlSsXZs6cqfU169WrF06dOoXUO6P8/f3h6+ur9bh169YhMDBQ5XkcNWoUnJyc9PqbUQaeMpnMZH/Xq1evRuvWrZGYmAgOhwOZTMbk6jFVn5nxuKyRpX/OGJNBa15atWqFXbt24cqVK2jXrh3kcjkGDRqE3bt3Y/v27WjcuHG67i8kJATe3t5q0Rafz8ekSZNw/fp1dO3aFTt27MCECRNom7SVKlasGMLCwpgP3rVr16Jt27Ym6UsoFCI8PJy5DFmmTBncuXNHZ96Q4sWLIywsjMkztG/fPr2yd06YMEHlNofDQcOGDbUew+fzsWPHDkz5fYlixowZWLVqFTgcjtbjlEGPMi+Jm5sbtm7digULFmDfvn0qz2/qKeRVq1bh33//ZdLtd+rUSWdCwiJFiqjVg3r//r3OnCjFixdHrjQzG2xfOtL6/v272kLn1ItT79y5g5o1a2Ly5MkAgDUtW0IYFIRvPB6U2Z+iHB3x8/Rp/Hz8GPErV0LUrp1q4JLqfkePHs3cFggEeq3X69mzJ0JCQhAUFARA8eGtbRG48r737t2LVq1aAQDatm2LpUuX6nytmzdvjkuXLqFbt27w9/fHnj171M41cytdujSuXr2KhQsXYvbs2bh8+TIV5CUmZ3DluI4dO+LNmzd49uwZrly5gidPniAyMhIdO3ZM933179+f2WaXVpEiRbBw4ULs27cPq1evpgR1Vi5nzpzw9fUFYPo6Q3w+n/lwTk+hxJw5czKXIPUp0Pft2zcMHjxYpU0ul+tVwVqZ3hxQ1APT9WGm5O3tjRIlSgCASpK6unXrokuXLgDYt8a2a9eOCaq07WhKLe2XBV2BCwAMGTJEbYFq7969NRZ6TE3TbkK5TIb5AQEYFh+PXb8v6/2dkoIbV68iceZM/PodqHKKFIGsShVAj9d7/PjxTNI9Nzc3nb+vVKFCBSYrtT5bsgHF5aVixYoBUFwS1/e1Ll26NJYuXYotW7boDIjNJU+ePOjatSsCAwNRvHhxcw+HZAMZLnvr6ekJHx8fjdtFCcnqlJdQ0rp3754ZRmMZwsPD1RaoJiQk6J1rJzXh0aNwHD4cruXLI/TnT/gBOAXFm1clAO0SEhDbujXklGmVkGxD7zUvBw4cSNcdK2tPEJLV5c6dmzUplz5p+588eYJx48YBUOTHWL16tV6zPYaIj4/HlClTmL/lN2/e6HXc48ePVW6/ffsWRXRUQ3ZxcWFdsKsrJX58XBzWDFNNsO84fDjEDRogYcIElBszBh/SBIr29vZYu3Yts0D70aNHOHjwINq3b6+1r8wWHh6O/fv3A1Dk2OnZs6fJK7gTklXpHbywXQ7icDisb9ocDifbLBoipFSpUmjdujVOnTqlsptEuW5Gkzdv3qBFixbMpZS7d++iWbNmuHz5ss41FOkllUrRtWtX3LlzhxnjxYsXcfToUa1rel6/fo0WLVqotCnHmDdvXo3H1a9fHzt37lRpK1q0KHtAl5AA4ZUr4J85A/GuXZgrEmFeqh9vW7IELX+vjerx4wfmzJmjsgOqefPmaokO+/XrBzc3N9SqVUvjGDPTy5cv0bJlSyabb2RkJPM86lubihDyf3pfNnrz5o3KvxcvXkAul+Po0aNqP3v9+rUpx0yIReFwOFi3bh3Gjh3LLJB1c3Nj3dKf2rZt2yAWi5kvADKZDAkJCeme5dTHo0ePcP36dZXgCoBKFlxNY0x7+Sc+Pl7nGNnqOr158wZfvnwBoChyaLt2LZw7dUIuT0849euH+BcvME0kQtq5iMUrVjD/P3z4cCxbtozJZjtu3Diw1TYCoNeao8yydetWtecxNjYWhw8fNtOICLFues+8pF1cqZxZyZ8/v8kXXhJi6fh8PkaMGIEdO3bgzZs3WlO+K8XFxanlUOFwOHrXvEmPuLg41plSbYnhlD9PO4vK4XB05pJg+3lTALlmzIDrrVvgvXkDSfHiiiKHgwdDXKsWrty4gX87dtQ6Rg6Hgy5duqB48eJo2bIl6tevr1YaQIntspW5aHoedT3/hBB2GV6wSwgxDNslDZFIxOw+MiYvLy/WXUJ16tTRelzNmjXVdsXoM8YaNWqgOJ8P5WbpqgAOA3D99g1Jffvi540b+HX9OhJmzoS4QQPAxgZlypRh6pqlVrduXa19aco026hRI63HZaaaNWuq7XYz1WtNSHZAwQvJVO/evWPWQjx48MDMozGuc+fOISoqCoDmtO6ptWvXDv369VNp+/vvv3VebjJErly5sGXLFpW8Ly4uLjqLYvr5+TH5TJQmTZrEHvSIRBBcuQL7adNw/O1bvJRIoCxV+BHAlcOHEb93L5L79oXs95bh1HLnzo3NmzerzVpNmzZN5faDBw+wbds2AIrFw/v27VPLKVOiRAnMmzcPlqJz585MZWiladOmmXRNzpkzZ5hkfvpWKyfEWlDwQjLNgwcPUK9ePeaDZ+zYsdiwYYOZR2UcixYtQteuXZkPicjISLx8+VLrMRwOB9OnT8fcuXMBAAsWLMDw4cNNNsbUi3UBxaWMr1+/6hzjzJkzVdqGpdoNxP1dC8ph9GjkLFUKzp07gx8eDklgIL5fvAiXTp0AAG3790clHx+dY2zcuLHKFnMulwtHR0fm9vHjx9G0aVMmU/CQIUNw8eJFPHv2TCUh4bVr13T2lZk4HA7mzp2LgQMHAlCMe9CgQSbrb/bs2fjzzz9x4cIFAMD8+fMNKphLiKUyeKu0TCYDh8PB+fPnWf8oaKs0SWv06NFITk5WWecxceJE+Pn5WXVxtcjISCYASW38+PHYt2+fzuOVydHYUuMby9u3b9VmIqRSKSZMmKBWMkAX/o0bEIaEQBgSgsRHj1BPIABy5ED8qlUQ16sH+e9gg4P/P7b0FIvLlSsXa00lmUyGIUOGQCaTqaSHHzx4MJ4+fQp3d3c8f/7c6Du1jEk5Q2TKLOEvX75UW4idlJSEyZMn47///jNZv4RkpgxtlQaAv/76S62NtkoTNm/evGH9QPrw4YPelYwtUWRkJOti2FevXpm0X03PB1v7u3fvDB4jJ02l7Rxt20JSrRpS2rVDzOTJuOTvj4QpUyAqWFDvMerCloLh169frIuZf/z4gZSUFLX2jPRlzd68ecNa+TptmQdCrJnBW6W1/aOt0oRNQZYPN0BR7E6bT58+4Y8//mDykWzfvt2iApmCBQuyfgDqk4Bs7ty5zFqInj17Yu3atTqPSU5ORuPGjfHkyRMAim3QERERuHPnDqpVq4aqVasCAM6ePcscU6hQIf3HKJOBf+8e7BYsQI5mzeBapozKj+t4eiLm6FEkDR8Oqaen1jGuWrUKgKLOkq7LaIBiS3GePHlUto8rtxi7uLiw7uLKmTMnBg0ahPPnzwMAzp8/z9Q+0iYyMhJ58uTBhw8fAChqNqXNTWNMPXv2ZC7BzZw5U20tj7F4eHiwfnksxrLOyBodPXqUueQ2evRo3L5928wjIuagd/BSuHDhdP0jJC222kJ8Ph85cuTQeIxIJEKHDh1w584d5gNt586dWLNmjcnGmV6aagR9/vxZ63G7du3CokWLVNomTZqE0NBQrce1a9cODx8+VGlr3Lgx/Pz8EBkZybSNGzcOYWFheo2R83utjv2kSchZtixyNGsGYWgoNn75guppjrn69KnKuhc2bdq0URmjSCRCkyZNtAadkZGRKoUSlZQ5XbhcLpYuXQoul8vUbeJwOKhVqxaOHDmicsyaNWuwa9curWNUBnmpDRs2DCKRSOtxhpg2bRqzeFZp1apV2Lt3r9H7KlWqFPr37w8ul8vsFLOxsdG5ONsaXL16FUFBQcwW82/fvqmd9yR7oAW7JNMoZwpSk0gkGpOMAYrU9C9fvlRJ8CWTybB161aTjNEQ69atY23XlX5//fr1rO26Zl/u3r2r1pacnAyxWKwWHCjT0bPdpxOAzq9eIUerVnCpXx/1eDxwpFIkTJ+On0+eIObUKQz8/Bl3WMagay3P/fv31doSEhJw8+ZNjcekXRislDoI9PPzw9GjR9GtWzcAwH///adxce7y5cu1jlETtvVLGbVjxw7W9mXLlhm9L0BRoXzdunVo0qQJAGDOnDlZomAiW3JEqVSK06dPm2E0xJz0XvOSOorXB615IWlpWlugbb1C2qykSpZ0fhn6TV3TY9PUnl5yuZy5r5SUFDgBaALgMYAIANUAdAQgrl0bsQMH4lKvXkiYMwcpqS7vaXrNdK0TMeS11nfdSvXq1eHu7o4tW7agbNmyGmdzDD1HTJEk0Nhj1IXD4aBt27bg8/k4e/aszppS1oLtb4PWWGZPes+8LF68mPk3f/58uLu7o0iRIhgxYgTmzJmD4cOHo3DhwnB3d8eCBQtMOWZipTxZ1kfw+XyteU3Kli0LNzc38Hg8po3L5aLt71o3lqB3796s7fnz59d6nKZF8AEBAVqPY/sGzefzWQOGrhUrwm7VKiy4cwdRADYDSPr9s3MA2hQogMSJEyGtVIm1L03rJHTlomErLikQCLTmNWG7ZAQAzs7OWvtq1qwZa3v37t21HqeJKcoK+Pr6srYHBgYava+srGXLlmrnuVQqRcOGDc00ImIuegcvI0aMwPDhwzF8+HB8+/YNlStXxosXL7Bo0SKMHTsWixcvxsuXL1GpUiWd1/pJ9nTs2DEUKFBApW3Pnj2wt7fXeIy9vT327duncpyPjw9TidkUwsLCMGHCBACKyy66ZhkKFy6M2bNnq7VruxwGKHJ9dO7cWaVt4MCBGoMapRMnTjBbkJX279+PLVu2IK+DA5TZVE47OqL1+PGw2bUL/Fq1sC0wELkBvE913JUrV7T2dePGDbXXJ0+ePNi9e7fW406ePKkyRi6XiwMHDmjdMl2hQgX0799frf3OHbYLV/+3cuVKVK5cWaWtZcuWGDp0qNbj2OoKDRo0yCSzFP/88w8qVqyo0taqVSsm7wvRT9OmTTF79mxm/ZytrS02b97M5Pgh2YdBa142b96MQYMGqS3A5HK5GDRoELZs2WKUwZGsxcXFBffv38eIESMAAJMnT9aZ+h1QLEC8ffs2sz4gKCgIAoHAJGM8c+YM/Pz8cOrUKQCKZF9TpkzReVzfvn3x5csXJqFarly5tC5EVlq1ahWTbmD8+PGYPn26zmNcXV0RHh7O7BQqVqAAGj16hI7r1+OLRIIFfD6ceTzwe/TAz7t38evyZcRPnoyp589DnOa+9Fkw+u7dO2Yre65cuVjXLqWVK1cuhIeHM7t+5s2bh5o1a2o9RiaT4dixY2rtaRfjsjlz5gy6dOkCQDFzpc97kI+PD75//47y5csDUFTCDg4O1nmcoUJCQphFxPv27cPmzZtN1ldWFhQUxASe+/fv1zjzRrI2g4KXpKQkjdka3759y5R9J4SN8jJAetZQcTgcvYKBjJo8ebLK+gSZTIY1a9bg27dvOo/l8XistXl0UR6j3EGjU3IyBOfPg//zJwCA+/Ej7DZsgLRkScT+9x9i9u1DrFSKlFatICtUCABw+vRpvH//Xu2u9AmWADDBYurLd/pQJmNj22mW1vHjx/Hx40e19qlTp+rVl7J2U3oS4gGKsgSAfmPMKOW5r222keimfI31/pshWY5Br3y7du0wbtw42NnZoV27dsiRIwdiYmJw8OBBTJgwAe3atTPyMAnJHN/TJGRL3Z43b16tx4rFYoMW2yoXqmpb+Mt9/x7C0FAIQkIgvHwZkErx+vdxLwFE37jx/1++dUvteE3J6JKSkljb01KOzViLidloyg+l75chZSXr9FSTlsvlzPOfntxBIpEInz590vv3iXEpF1XTF+Xsy6CvGqtWrYKvry969+6NnDlzwtbWFjlz5kTv3r3RuHFjrFy50tjjJCRTsF07FwqFOnMXPXjwAJUqVUJMTAwAICYmRq/dM2vXrmUWuM+fP///a0nEYgjCwmAfHAyXunWRs0oV2C1fDpm7O17MmAGXNEGErrTvmqpHpy1oyKZu3br49esXAODnz58m+3KiaYz6lE3o3r07cwlsz549GDt2rM5j4uLi0LFjR1y9ehUAcO3aNb0yDt+9excVK1ZkClYuWLBApWYUMa1ly5ahQ4cOABSL3g8dOmTeARGzMCh4cXJywr59+/Do0SNs2rQJwcHB2LRpEx4/foz9+/fr3B1AiKViq4vj5OSk9XJQfHw8OnfujB8/fjBtEomEdRFvaiEhISqZYB0B3B0yBJL27ZHT0xPOHTuC/+ABUrp2RXRYGKLv3EHC/PmoPHkyYtNsDR01ahQTOLHRdJlC14duv3798OzZM5W2sLAwk1RsLlmyJOslH107SebMmaOW52PTpk06FxWPGjVKJUeMSCRCly5dtM4uxcTEoHPnzkz1cAC4dOkS7bDMJEePHlX5uxKLxRgwYAAeP35sxlERc8jQRV4vLy8EBgZi3LhxCAwMhJeXl7HGRYhZKL+FpxYVFaU14dyjR48QHR2tdtnhxIkTWvs6f/Ys6nA4UG6i/RvAdACRcXGIX7kSPyMiEHvgAJIGDVKk4f+9RkjTZRFtC1s1LQ6Njo7WOkZlVeK09Ck4mV7h4eGswZS2xHaA5udZ1xhDQkLU+nv79i3r2iClhw8fIjY2VmUHmlQqVcueS0wjJCREbfefQCDApUuXzDQiYi56r3lhy+qpjTKlNyHWRNMuJm2LQG1sbFi3U7PN1nB+/IDw3DkIQ0Kw+MQJ2MpkWAYgFMBaAFMFAoxv2xbFWrVK99i1zXiy1QQCdC+a1rRA1xS7vQQCgd7PY2qaFm3qOk7TY9B2nCHHEOOxsbFRKzAqk8nSvUibWD+9Z168vb1RrVo1nf+Uv0eINerdu7fKhyGXy0WNGjW0rnkpV64cSpcurfbB1qdPH7UihznLlIHD1KmQCwR4O3Ys8vN4GMPhQAYgkssFj89nClBqUuj3DqLUuFwu/vjjD43HDB48mLU9bX6UtPr168fazlZNPqMqVqwIT09P9udRC2WRvrR05Xnp1auXWuBTt25drckFK1eujOLFi6udI7rGSIzD399f5TaXy4VQKETLli3NNCJiLnrPvCgrthKSlY0cORJyuRwrV65EQkICqlSpgm3btmmdoRAIBNi/fz+GDBnC/J3Y8/kYevs2hPPngxMVBUnlyhA1aYKEuXMhqVgR4HKRD8DaypUxevRofPnyBR4eHli+fDmKFCmidYzXr19HjRo1mGrIgOLvU9s25pw5c2Lbtm34888/mW+tQqFQ56WtkSNH4v379yoLgv/66y+0b99e63GGsLGxYZ7HixcvAlDMqujKlNupUyd8+fKF2fbN5XKxcuVK1KhRQ+txykW9y5Ytg1QqRd68ebF582atr7WNjQ0OHjyIwYMH4+bNm0hOTsZff/2lMysyMY6qVati+/btGDNmDD5+/IgSJUpgzZo1OrNZk6xH7+Clfv36phwHIRaBy+VizJgx8PLyQs+ePTFkyBAmV4lGcjnyf/uGoz4+KHj+PH4BEEok4IjFSAgOhqhhQ8g17JipW7cubt68CScnJ6ZSri5CoRD37t1T2YVTpkwZrcdIpVIsX74cfD6fWechEolw7NgxnaUWFi9ejCtXruDNmzcoWrSoXjt5DOXm5oZ9+/ahcOHCSExMhFAo1Csf0NChQyGTyTBz5kxMnDgRnTp10nkMj8fDhAkT8OzZM5w4cQLe3t56bTZwc3PD/v378eHDB1SuXBldunRJV84ikjFNmjTByZMnUaFCBezbt48Cl2yKMvwQYgBOfDwEFy9CGBICQUgIeF++QFKuHFwdHfErPh45ChdGnIZq0+bw6NEj1oWvy5Yts6g6UYQQog+917w4OzszNUacnJzg7Oys9R+xHg8fPsTWrVsBpC/BlyG+fv3KpIDXtoMnrYcPH2L//v0A9E+sBgDPnz9X+a8+kpOTmRT4zPZjuRy8iAjYrV4NZz8/5PT0hOOQIeBERyNx3Dj8fPgQF5YsgfR3XRy2dSnGdCN1Ujo9xMXFsc4O6Dvbo0zel3qLsC5JSUl48eJFuvoBgJ07dzLnob6J4yQSCU6ePAkgfZe4nz59ytSg0rbLyBp9/PgR9+/fB2BZVdgzSi6X49GjRwA0JzYkWZ/eMy+jR49mpudGjx5N06RZxPz581VyVHTt2hVhYWGsVYEz6tKlS0xyKUCRWI3H4+nMkTFv3jwsXLiQuT1s2DBUrVpV6xilUilKlSrFBB/h4eEoV64c86anyZcvX9C+fXu8fPkSALBj9Gi0PnUKHo8fgxcZCUnp0hA1aYKkUaMgrl4d+L3LYc6cOVi8eDFzP1euXMG7d+90JrczRHBwsFoiyGrVquEWS2ZdpTJlyqjt0gCA0qVLa+1LIpGgUKFCTO6T2NhYFC1aVGfg+fnzZ7Rt25b5vVmzZqFKlSpaq0oDQPPmzVUKMSYnJ+P27dvw9vbWe4xhYWEoVqyYzg+21atXq5QeCA8PR4cOHZgg2ZodPXoU/fv3Z56TmTNnolGjRkztLWslk8kwePBgZht8u3btMHHiRIwcOdLMIyOZjSPXVTLXSqVOGGYJ0rOmIbO8e/eO9UOhYMGCuHfvntH7c3d3Z83jcfv2bY0f8q9evWIt6FeoUCGt2/c7dOjAmvuhQ4cOWLNmjcbjRrZujVw3b8JJJsNMADsA5ODzUTM4GGjRgqkVlNrLly9ZP5Q9PDx0VkRWSs/5oSnj7LFjx1CjRg3cunULLVu2xIkTJ5idfydPnkRgYKDaMVwuF1+/fmXWb9y7dw8FCxZkfl6jRg3WIKBevXoq6z7SHufn54dr166pJHxzcXFBeHg4U4OIbfy9evVSa+fz+WqV6lP36+fnxxpMNWzYEHv27GHtC9D8PN68eVOv4F3TY9eG7bXRl77nyJcvX1ClShWVvzUul4s///xT5UuANdq8eTMmTJigcl5xOBwcOnQIPj4+Wo7MHizxc8YQynpj2pi+EhmxWOfOnWNtN1XNFk3ZXNkqCStpugSga4zh4eGs7devX1dt+F3k0OHvv+Faowb+u34dg2QyKOdnAgC0kkjwuG5d1sAFAEJDQ1nb2YoMmtKiRYs0/mzbtm2s7bouy6Te0ZTagwcPtB539+5dtUy1v3790nppRtMYddVT0jTG9OamUtqwYYNBx1mKx48fq10mkslkrAkYrc2tW7fUzgcbGxuDX2tivQxasCuTybB+/Xrs27cPHz58YC2ORdciLZ+mVfqmSECmTfHixTX+zNAx2tvbs2aPdXJyAvfDB2ahrbLIodjHB0l9+qDlihW4/OWL2nHadhxZyvNYoUIFjT/Td2YgLYFAwFowUlPSOyUnJyemUGJq2tbDGbpOSCAQsAbGDg4OBt1f+fLlDTrOUri4uLAGpTl/r8eyZq6uruDz+SoBjFQqzZSK88SyGDTzMm7cOAwYMABisRgNGzZE27Zt1f4Ry9e0aVPW6TlNickyiq3wnp2dHZo3b67xmBYtWrAWD+zfv7/WvubOnaty2wnAPAA3ExORs3Jl2C1bBpm7O2L//RdRz58jds8eJPfrB/9Jk8Dlqv5ZdOjQQet2zJYtW8LV1VWtXVPytIzSdNll0qRJGo8JDg5mbVde7tJ09Tj1mpDUVqxYoW2IaNSokVpb0aJFWWtHKc2YMYO1vXbt2lr7mjJlCmu7rjGyfZhzOBy1RGiaWOoi2EqVKqF27dpqwfOYMWPMNCLj6d27NwQCAZPTSCAQIG/evPSZkw0ZFLxs374dwcHBOH/+PFatWoUlS5ao/SOWj8vl4saNG6hSpQqTMbRJkyYaPwwyau/evWprW3TtDOFyubh+/ToqV67MvGHVqVNH6wc1ALSoVAkhAQFQLketCCDQywvc3r0RfeUKou/eRcL8+RA3bQqk+obu7++PdevWoUCBAkxfuj4E+Xw+Dh06pFL8MFeuXBg3bpzW4wz1/v17tVkFXWuUbG1tcfjwYZWF9i4uLjh06BBWrlzJrBfo0qWLyvqRXr16YeLEiSr3tWrVKjRo0EBrf2yv65s3b/Dt2zetY7x586ZKcMblcnVWDe7Tpw/Gjx/P3OZwOFi1ahXq1aun9bjnz5+rBKVcLpfZZabNu3fv4Ovry6wXW79+vcbgzxx4PB527NiBXr16MQkPZ82apfM1swbFihXD2bNn0bhxY5QrVw5t27bF6dOnaYdrNmRQ8JKcnEyLo7IIZ2dnnD59mqkS3KJFC5P1NX/+fLV1IH379tX5DdbFxQVnzpzBhAkTAID9TVgqBf/mTdjPng2XRo2Qq3x5NAgNhfz3h/yXokXBv3QJSYMHQ1qqFFPkkE3btm2ZhaMNGjTQefknJSUFPXv2VLm8EhUVhbVr12o9LiPevn3LzBBxuVydl4WSk5MxfPhwlSy8v379Qt++fTFz5kzm0u/Lly/Rrl07xMfHM783cuRIZoamVq1a6Ny5s87xxcbGsrb/+vVL63FFixbF+/fvmdk2thktNqNHj2YCuLt37+o1RkCxBV+5VmjBggU6FwomJSWhffv2KrvW/vnnH4tbJ2Nvb49Zs2Zh9erVAHSXgbAmpUqVwq5duxAeHo5169Zpnc0jWZdBwUu3bt1w9OhRY4+FZHHbtm1TW2wXHh6ernwvqXF+/IDN3r1w7N8fOb28kKN1awjCwpDSujWiz51DdHg4Yn9/I0tgWZdlLMrHkPaxKXPnWIKHDx/i7du3amM8ffq0SvAolUrx5csXvXdJaVK5cmW1ukHOzs7w8PDI0P2a27179/DhwweV51Emk6mUTyCEmJ7eC3YPHDjA/H+tWrXw999/4+vXr/D19WVdzOjn52eUAZKsQ9PUur6JyPD79/iXLiHHyZPg370Lec6cEDVujPh58yBu0AByPb+pG5Om8ev9uAzw8OFD5v716UcqlbLmedHnNRGLxczlnh8/fkAmk6mtC0pr5cqVaNWqFTPTJhQKsXXrVo3rdVK7efMms9jX0taVmOO1JoSo0zt46dixo1rbu3fvsHv3brV2DodjcW86xPzatGmD//77T2VnSNGiRbXm1OD8+gXBhQsQhoTA7sgRAAA/IgLiP/9EwuzZkFSqBOj4IDW1smXLsuZXYFu0agzHjx9Hz549VdrGjRvHXPpjU758eeTJkwdRUVHM3yaXy0XNmjVx9epVZiaBy+XCxcUFVapUAaCof+Tn54dXr14BAF68eIE+ffpgw4YNWgOYmJgYxMTEgMvlQiaTQSQS4evXrzof25o1azBlyhQmqPr16xc+fvzIrEEyt4oVKyJXrlyIjo5mnkc+n4927dqZd2CEZDN6v+u/efNG73+0TZqwCQ4ORuvWrZnb9vb22LNnj+qaErkcvMePYbdsGXK0bo2cpUvDccwYcFJSkPd3sb1cU6cicexYSKpUMXvgAig+qFOvEVEy9HKYLgMHDlRr27hxI76wbPFWcnR0xP79+1WCgHr16mHnzp3o06cPs5DXzc0Ne/fuZbaebty4US2HxqlTp3D48GGtYxw6dCiSkpJUZiSGDh3K+jwpRUZGqgQuSsq1TpbAyclJpRggh8NBYGAgRowYYd6BEZLN6D3zknqXSGhoKCIjI1mzYW7evBmFCxc2SVp0Yt1sbW2xdu1aJCQk4PTp02jYsCGKFCmiWuQwNBS8z58hKVsWoiZNkPD335B4ewN8PgrcugVs3Wpx55amYD099ZTSQ1Ntpzt37qBVq1YajytdujRu376NXbt2YdiwYejZsyeEQiFmzpyJv//+G/Hx8cidO7fKjqQXL16ozaLyeDymZpEmL1++VDtOJBLh48ePKFWqFOsxr1+/Zr209fTpU619ZbayZcvi7t27+PHjBxwdHXXmvCGEGJ9BSeomTZqkcV/99+/f8e+//yIsLCxDA8sooVAIGxsbs44hNT6fDycnJ3MPQyPlWgRbW1uTj9P29+vCf/0aOTt1AicsDLC1haxxY8imTIGkaVOgQAHwAKT+WFBuRba3t9d7jMoPYg6Hk67HpTx3bGxsdB5XokQJ1rUjHh4eeveZnvNDU1K2qlWrwsnJSefzpNydYWdnx/zcyckJefPmVfvdwoULg8/nq+ykksvlKFKkCJycnJgt2w4ODip95c+fn7nUpMThcFCsWDGNj7NEiRKsa0fYnke2fjWNRRdDz31Dtucacg4rGfIekpH+LJny79rBwcGitqmbm6V/zhiTQcHL48ePNSaUqlKlCmbNmpWhQRmDSCRizQxqLpZec0K5VTY5Odk040xMhODKFQhDQoDTpxVt794huVEjiIcPVylyCABgGYOy0nBiYqLeY1S+scnl8nQdo6yirE9fbm5u6N27N7Zs2aIy2xAcHKx3n+k5PyZMmIDp06ertNWpUwdubm6Ii4vT+TwpZ26SkpJ09hkYGIhNmzappOD39PREmzZtEBcXxyysTUhIULmvOXPmoGvXrpDL5ZDJZOBwOBg/fjwEAoHGPgsWLIjAwEBs375d5XmcOnWq2jFs/Woaiy4mP/dTMeQcVjLkPSQj/VkyHo8HoVCIhIQEWl+ZiqV/zuhLn4kHgxYMcDgcplpvWqkXspHsjfvmDWz//RfO/v7I5ekJ56Ag8D5+RNzvNPCxNWogcdo0iOvUUQ1czCg+Ph6dO3fG8uXLASh2zehz+Wfu3LlYvHgxc0kkICAAlSpVMskYhw4dqlZV+uDBgybpy8XFBefPn2e2OBcpUgTHjx/XuWuoYcOGOHnyJFNFfN68eRg1apTO/hYuXIiFCxdC+Pt8cHV11Vr2gBCSPRkUvNSoUQOrVq1i3Xa5evVq1KhRwyiDI1YmJQWCCxfgMGkSXGrWRM7q1WG3bh2kxYsjdutWREVEIHb7diT/vjyRkpJi5gGrGzt2rMolz7i4OPj7++ucxeNwOAgICEDTpk0BgLWkgTH5+/szeVTS5lMxNhcXF6b+VNGiRVUyCWtTuXJlJjuvr6+vXsdwOBx0796dSb+Q2fWhCCHWwaB3veDgYDRs2BAVKlRAz549kT9/fnz69Albt25FREQELly4YORhEkvF/fABwtBQRZHDS5cAiQRiHx8k9+oFUZMmkGkpumiJQkJC1NaTfPz4EW/fvoWnp6eZRkUIISQ1g4KXWrVqITQ0FGPHjsW4ceOYpFXK9po1axp7nMRSiMXg37wJYWgohCEh4D99CmnBghA1aYK4desgqlNHpVZQWosXL8a1a9cAQCXFujYymQxjxoxBSEgIAODatWuoVq2azuNu3LiBz58/AwA+f/6MZ8+eoXTp0lqP0fRNX6jjspZEIkHt2rWZnUfKx2gqbdu2ZXKzKP+bnJyMdevW4erVqwCg8dJueoWHh+PKlSsAgLCwMHz48MHgKtW6iEQilCpVitlSzVYZnE10dDRWrVoFQFFraOzYsXrNEN29exf79+8HoEj8Z0pv3rzB6NGjAQB///03du/erXf5g/SSy+XYtm0bjh8/DkARgOvzN0OItTB4vrl27doICwtDUlISoqOj4eLiovd0MrEunC9fIDx3TrGV+cIFcJKSIK5RAymdOyOuSROdtYKUxo0bh40bNzK3Y2NjUalSJdy/f1/rcY0bN1YJdGbMmIG8efOiS5cuGo+5ffs2/vjjD5W2unXr4ubNm1qT4vn6+mL79u0qbQULFtS5Pbtw4cIql5Zu376NUaNGYfHixVqPM0TNmjXVdvLky5cPVapUwYMHD5iZo8GDByMsLExnvR5tnjx5opJsTyQSoUqVKggPDzdJTZm0yejEYjE6duyIffv2aTzm169faNSoEZMEb926dbh8+TJOnDihdeHfuXPnEBAQwKzR27JlCwoVKoThw4cb4ZGoevPmDWrVqsX0de/ePVSsWBGPHj0ySVHBkSNHYvfu3UxgO3jwYJQsWRJly5Y1el+EmEOGM3zZ2dnB3d2dApesRCoF/9Yt2M+ZA5fGjZGrfHk4zJoFuZMT4pctw8/nzxF76BCShgyBtHRpvQIXACqBi9LHjx+1zlJcvnyZdYZGV+KygIAA1nZdZStu3rzJOsaoqCiNxyxdupR1TYyp6t2kDVwAxezU3bt3VS55xcTE4J9//slQX3/++adam1wuV8vwawx9+vRhbb948aLW49atW4dv374xj10sFuPp06daAx5Asb4p7eaCWbNmGW3GKrVhw4ap9ZWUlISpU6cava/Hjx9j+/btKvWXxGIxgoODjd4XIeZi2pV+xGpwfk/T22zbhpwzZ4ITEwNJ1apIadUKcUuWQFq+vN5BSnrdunWLqVqc1pMnT1jblVtANVFum01LV1Vjtiy1crkcX79+1TiDcfv2ba33mVnSLqCXSqVqVbzTS9PzpS2br6HCw8MNOu7Tp09q65S4XC5zyVATtnIFcrkc3759YzIMG4um0gjv3r0zaj+A4vng8XgqwZJcLkdkZKTR+yLEXMyfW52Yh0wG3oMHsFu0CDlatECRqVPBBZDH1hbxc+fi59OniDlxAkmjRkFaoYJRAhdNtXCaNGmi8RhNO9fYioGmpmm3j7u7u9bjSpQoAR6Pp9LG5/NR6Pf2bjYtWrRgbeeYKNjTl0AgyPAiY03PV8mSJTN0v2yUO7XSy9PTU23HlVQqRYkSJbQeV7x4cbXXWigU6jxHDFFcw8L18uXLm6SvtMn++Hw+ypQpY/S+CDEXCl6yEU5MDISHD8Nx6FDkLFcOrk2aQHj6NMQNG8JhyRLIADhNngyRnx/kOXMavf+ZM2eqtdWsWVPrm2qlSpVU6iEBiqBgw4YNWvs6c+aMWhuHw0FoaKjW45YtWwYHBweVD7WlS5dqXZfQrVs31vUfpkrW2Lx5c7U2Z2dntG/fnkneBSgCMbY6SOlx4MABtaDTxsYG27Zty9D9spk5cybrtu+hQ4dqPa5Pnz6oVKkS+Hw+bGxswOfz0bx5c7Rp00brcStWrICdnZ3Ka71y5UomU68x/fPPP2r3mz9/fpNcNipWrBgmTZoEDofDrPlxcXFh/fsjxFpR8JKVpS1yWKoUHEePBic5GQlTpyLq8WPEnDmDxLFjFYtuTaxv377Yu3cvEwh4eXnh6NGjOo/buHEjFi1ahMaNG6Ndu3a4cuUK6tSpo/UYNzc3vHjxgtk9JBQKERkZqTO5mpeXF8LCwtC1a1cAiuyu/v7+Osf46NEj+Pn5MY9t+vTp6Nu3r87jDDF//ny1maetW7dizZo12LhxI/r16wdAUWcso3V38uTJg4iICCY4K1CgAF6/fq1z95Wh/v33X5XbPB5P5wJaGxsbHD58GMuXL8eYMWPw77//6qx6DShmPcLCwpiF38HBwWjfvn3GHoAGLi4uePToEXr06IEGDRpg8ODBuH//vs4xGmrYsGE4dOgQ+vfvDwDYv3+/SWaUCDEXWvOSxXDi4yG4dEmxMygkRGORQ3Np0KABmjVrhr1796JcuXJ6HxcYGIjAwMB09eXi4oJSpUrh0aNH8PT01Bm4KLm5uaFJkybYtm2b1p1Jaa1duxa3bt1Cy5Yt4e3tna6xpgdbdebAwEA8evQILVu2RIUKFbBy5UqjBRg5cuRAixYtsHnzZvj6+poscPn69SvzYasklUoxadIkrFixQuuxAoEAnX5XHU8Pd3d3ZoeZqQt+Ojo6YuHChSbtIzUfHx94eHhg+fLlJtnRRIg5UfBi7eRy8F6+VCSJCwmB4No1yIVCiBs0QOJff0HcuDFk9I0rS7lz547KThJAse08MjJSY8Vma/Ds2TPWgpM3btwww2gIIZaMLhuZUEpKCmbOnIlGjRrB19eXdR2GQRITITh7Fg7jxsG1WjW4+vjAdts2SMqVQ+zu3fgZEYG4zZuR8uefFhe4HD16FOfOnQOg2F3C9mFlLK9fv8bbt28BAG/fvtV7582RI0eY9SqHDh1SCxTMTdNOGGPvkNFGKpVi2bJlzJZ0ZTK0jHBxcWGtEJzTBOuvCCHWjWZeTEQulyMoKAihoaHMB/SVK1ewceNGteRp+uC+fQuhcnYlLAzgcCCuUwdJgwZB1LgxZCae8jaGffv2YdCgQcwH1LNnzzBkyBCsXbvW6H19+vQJvr6+zOWV+Ph4+Pr64vLly1rrDu3ZswdDhgxhxnjkyBHw+fwM50sxJg8PD7VAzMHBAW5ubpk2hvHjx2Pbtm1MYDd58mQIhUL06tXL4Pv08vICn89XCxbTc+mOEJI90MyLibx8+RKnTp1SmVmQy+WYP3++fneQkgLBxYtwmDwZLrVqIWe1arBbuxbSokURu3kzop4/R+yOHUju3dsqAhdAUXk57TfrAwcOZDgXCZutW7ciOTlZpS0mJgZ79+5N1xhlMhn27dunM2dIZmK7jJKQkGBwnpT0iomJwebNm1WCDLlcjnnz5mXofg8fPsw6y3Xy5MkM3S8hJOuhmRcT0ZTcS1utFu7HjxD8rhkkvHjx/0UOe/SAyNcXsmLFTJYoLjNoek5+/fqllhY+o6Kjo9Uymmobg5Km7Kq/fv1C/vz5jTG0DEubw0Pp48ePJskbkpam5zAuLi5D96sp8Z0lVh8nhJgXzbyYiKenp9o2VT6fr5p0TSwG/+pV2E+fDpf69ZGzUiXYL14MWd68iFu7VjG7sncvkgcMUFRntuLABQCqVaumVvjQ0dERRYoUMUlfaUkkElSpUkXrcVWrVlXLNeLk5GTynSjpoamYn6aEfsZWoEAB5MqVSyUJH5/PR6VKlTJ0v40bN2Zt15YgkBCSPVHwYiI5cuTAxo0bYWtryyTBKly4MBaOGQObnTvh1KcPcpYujRx+fhDcuYOUjh0RfekSou/dQ8LChRA1bw44Opr5URjX0qVLVYIALpeLrVu3miQpWIcOHdC9e3eVtsGDB+vM4rp8+XKVMdrY2OC///6zqNpd+/btUwuwZs6cqVeF4uvXr+PYsWMADJ8p4fP52LZtG5ycnMDj8cDlcuHm5pbhdUFlypRhTUh38ODBDN0vISTroeDFhJo0aYJb169j0+835FN8PkrUrQuHmTMhd3BA/JIl+BkRgZjDh5E0dCikXl5WP7uiTb58+XD+/Hk0a9YMANCpUyfUrVvXJH1xOBwsXLiQ2TpcqlQpTJkyRedxbm5uOH/+PLPbaOPGjahdu7ZJxmioChUq4MmTJ0zeGmdnZ7X8KGz++ecftGnTBocOHQIATJw4Ee/fvzdoDN7e3rh58ya2bt2KXbt24cqVK/Dw8DDovlKbMmUKzpw5g2LFigEAmjVrZvRLioQQ60drXkyAExUF4fnzEISEoMz58ygYHY0pBQrAvmVLRK9apShyaKLMmpbO1taWyfSZGbMZylmd9Mzu2NnZoXLlygA0X6IxN1dXVzg4OCA5OVntUhyb9+/fY+rUqZDL5cyi2Pj4eIwbNw47duwwaAy5cuUyuB6RNpUrV4aXlxdev37NWi6AEELoncEYZDLwwsOZrcz8O3cgd3WFqHFjxM+ZA2mDBphYuDDi4uKgvoSUENN7/fq1WptcLsfz58/NMBpCCMmY7Pn13whYixyeOgVxgwaIOXkSP588Qfzq1SYrcmgsP378QEBAAFPT5eDBg6yJwowhMTERBQsWxKZNmwAAmzZtMl7iPhY9evTA3bt3AQB3797FsGHDTNZXZvr16xfy5MmDqKgoAEBUVBT+++8/rccUKFCA9XXVp97NmDFjsHnzZgCKekmLFi1K/6D19PjxY5QqVYpJenfr1i2Nu6sySiQSoU2bNujZsycAYOTIkfj06ZNJ+iKEGBcFL/qSy8F78gR2y5cjR5s2iiKHo0aBk5SEhClTFEUOz55F4rhxkFStCqSqVGupJBIJOnfujAsXLjDbUdevX4+NGzeapD9PT0+1ba/dunUzSZbdadOm4cSJEyptO3futKhkc4YqWbKkWtuoUaPU8tqk5ubmxloE0FHHovDly5djy5YtKm1z587F4cOH9Ryt/uLj49G0aVP8/PmTafv27ZvJgs6OHTvi2rVrzO3o6GjUr1/fZMESIcR4KHjRJj4ewpMn4TB6NFwrVQK3fn3MW7MGPypUQMzBg/j5/Dni1q9HSpcukOfNa+7RptuTJ0/UUvTL5XK1yr7Goilfx+zZs43el3J2J62lS5cavS9LMXjwYI0/O3jwIOuH8uXLl7Xep6ZgL6MJ6djs27cPIpFIrV25wNjYrl+/rtb269cvPHjwwCT9EUKMh9a8pCaXg/fqlUqRQ/D5EDVogMQxY/CuTBnMaN4cfgMGoGDBguYebYaxfVBoazcVXYnjDKHp27Ol1SkyptQzFmklJiaytrMl8ktN0/NlitmypKQk1nZTzYRoujyatmI3IcTy0MxLUhIEISFwGD8ertWrw7VWLdhu3QppmTKI3bkTURERiNuyRVHkMF8+c4/WqLy8vJA7d26Vywl8Pp/ZymxsHA3bwEeNGmX0vtiS1AEwye4YSzF37lyNP/vjjz9Yn39dGXkbNGjA2u7n55eusenD0DEaim29D5/P13juEEIsR7YMXrhv38J2wwY4d+2KXJ6ecO7VC7x375A0YAB+3rqFX1evImH6dIjr1QNsbMw9XJNxcHDA7t27kTt3bqatXr16mDp1qkn6Y6s8HBgYaJIMqgcOHECePHlU2ooUKZIl1rywPQYfHx8mpw2bAgUKYMWKFSrBgbu7Ow4cOKC1r3///Vftfn18fDBhwoR0jlq3QoUKYenSpSpjtLOzw/79+43eF6ComZS6EjePx8OOHTuY/DmEEMuVPYKX1EUOfXwURQ7XrIG0cGHEbtqEqIgIxO7cieQ+fSAzQap6S1ahQgXcv3+fWVewaNEik715V6tWDZ8+fcKAAQMAALt37zbZzpXY2Fi18gy2trYaL01Yk44dO+L9+/dMdexKlSrptYDW398fr1+/xp49e3DhwgU8ePBA54JdQFEN/a+//gIATJgwwSSLdZUCAgLw+vVr+Pr6AgC6dOmi1xgN4e7ujoiICGzbtg0AEBYWhoYNG5qkL0KIcWXZNS8aixwGBkLcpAmkWaBWkLEIBIJMq90jEAjQvn17rFmzBi4uLibrZ+PGjWqF/l69eoVdu3ahV69eJus3s9ja2sLT0xPXrl1TC9K0cXR0NOgD2s3NDQBUZulMxdHRMdPWlHG5XJQtWxaAohQEIcQ6ZNngJWelSpC6u0Pk64u4tWshqlMny9UKIpp9+vRJbTEqh8PB58+fTdanXC7XWjXc2JQLq1MvaJVKpfj+/XumjcEU5HK5xgXGhBACZOHgJfrixSxfK4hoxrb+QyKRwNPT0yT9PX/+HAEBAYiMjASgyI+yadMmk6S3V+YjUQZiN27cwPXr1xEXF4f+/fszBRd37dqFMWPGGL1/U3ry5Am6deuGDx8+AACuXr0KqVTKFDclhBAgC695kZYpQ4FLNlaiRAm1mReZTIbixYsbva+EhAR06NABHz9+ZNrOnj2LBQsWGL0vAGjZsqXaDFL79u3Ro0cPlUrR8+bNw+nTp00yBlOIj49Hhw4dVLLcPn/+HEuWLDHjqAghlijLBi8kewsJCVGb9RAKhTh37pzR+3r8+DG+fv2qEixJpVKTJVd79eqVWpumfCxpswxbsgcPHiAqKkotr8vBgwfNNCJCiKWi4IVkSTwejzVniKZcMxntiw1bOv7MxOFwrOpyi6U+j4QQy0PvCiRLateundo3eLlcjtatWxu9r3LlyqFYsWIqMz08Hg+BgYFG7wsAKleurNZma2sLgUCg8kHP4XDQoUMHk4zBFCpVqoTChQurzZiZ6nkkhFgvCl5IllSpUiVs3bqVyVljb2+PPXv2sBY1zCgbGxscOHAAlStXZmZ2+vbty+SzMbbDhw+rZJ3l8XgIDQ3FgQMH4OHhAQ6Hg1y5cmHdunWoXbu2ScZgCra2tjhw4AAqVqzItNWoUQNBQUHMbZlMhjVr1qBr164AgD179pisCjohxHJR8EKyrKZNm6Jv374AgD59+qBOnTom66tAgQI4ceIEbt++DQDo37+/SS5RAYoP+XPnzqF58+YAgGbNmsHT0xNVq1bFrVu38PnzZzx79gxt27Y1Sf+mVKhQIZw6dQpDhw4FANSsWVPleZw1axaCg4Px7NkzAIpFyVm52CYhhJ3FbJW+evUqduzYga9fv8LZ2Rl9+vSBj48PgoKC8OvXL2Y6PE+ePFi1apWZR0sIu8xcn6GpL2ta56IJ22MTiURYuXKlyuVAmUyGxYsXY8SIESYLFgkhlscigpcHDx5g/fr1GDNmDEqXLo3Y2FgkJyczP58wYQKqVq1qxhESY5FIJHj+/DmAzKneq9xddPnyZb2PkUgkiIiIAKC5GjOb6OhoZuZFV7XmjEpMTMT79+8BQOVvJSu4cOECjh49CkC1enViYiJrhenk5GSIRCLKkEtINmIRl4127NgBf39/lClTBlwuFy4uLkw6cpJ1/Pz5E02bNsWwYcMAKBZi3rp1yyR9iUQi5MmTB48fPwYA3L9/X69zKioqCr6+vhgxYgQAoEePHrhz547O4y5evIhKlSoxl6n69u1rsuAsIiICnp6eCA8PB6AI0Hbs2GGSvjJbp06d0KlTJ7x+/RoAsHr1auYSUY4cOeDh4aEys8Tj8eDl5UWBCyHZjNmDF6lUihcvXiA+Ph4DBgxAz549sWzZMiQkJDC/s3TpUnTv3h0TJ07EkydPzDhakhGjRo1iPogARXK3bt26maRYYupFn0pSqRQ1a9bUetzIkSOZmSHlGAMCArTObkRHRyMwMFBlliY8PByTJ082YOS6tWvXDikpKSptI0aMQGxsrEn6yyyhoaG4cOGCWnujRo0AKHZPbd26FS4uLuByueByuciTJw82btyYySMlhJib2S8b/fr1CxKJBJcuXcLMmTNha2uLRYsWYf369Rg+fDhGjRrFZEUNDQ1FcHAwVqxYgbx586rcz+fPn1WyjtrY2MDd3d2oY1V+4+PxeOleV2DpOTcy8tj0dfXqVZXLAIDigz8yMhJlypQxal9RUVGs7W/evNH6+NjG+PPnT0RGRsLLy4v1mIiICLUATCKR4PLly3o/l+k5P9hqF8nlcty8eRPNmjXT6z7SS7kGhcvlpuv8SM95pSkIEYvFzLEVKlTA7du3cfv2bXC5XHh7e8PJyUnv8WR0jOZkyHuItTy29Er9uMj/WfrnjDGZPXhRTve2atWKqVjbqVMnzJ49GwBUPtRatmyJy5cv486dO2jRooXK/axduxbBwcHM7YkTJ2LWrFlGHasy9XqOHDng6uqa7uOFQqFRx2NMGX1s+nBycmItXFigQAGj98nhcFi30PL5fK19OTk5ISYmRq29YMGCGo9zd3dn7cvFxSVdj0vf84PL5bKu/ShevLjJXjt7e3vmv+npIz3nVaFChTT+LPWxrq6uKFKkiN5j0CUzzn1jSe97iDU9NkM4OzubewgWx5I/Z4zJ7MGLo6MjcufOrfdOAS6Xy/pB0b9/f7Rp04a5bWNjY/QKv8oPtZiYmHTft4ODg8qlMEuTkcemrxEjRmDMmDHMBy+fz0fjxo3h7Oxs9D579eqFDRs2qLWPHz9ea18jR47EX3/9pTJGX19fODo6ajzOw8MDPj4+uHXrFjNrw+FwMGzYML0fV3rOj7Zt26qlzHdzc0OJEiVM9topL4klJiamq4/0nFdTp05lfc0qV65s0mrdmXHuG4Mh7yHW8tjSi8fjwdnZGbGxsSZfHG9NLP1zRl/6BNpmD14ART6O48ePw9vbGzY2Nti/fz+qV6+O79+/49u3b0wl4HPnzuHFixcYMmSI2n3kz58f+fPnZ27/+PHD6Ce18v6kUmm671sul1v0H1lGHpu+/vzzT/B4PKxcuRIvXrxA586dMW/ePNZZhIyaO3cuPn78iFOnTjFtXbt2xdChQ7U+vtRjfPnypd5j3L59OyZPnozLly/DyckJw4cPR5s2bfR+LtNzfqxevRrPnz9n1n/x+XycPHnSpOeX8vHLZLJ09ZOe88rOzg5nzpxBy5YtmVpNJUuWxJkzZ0z62DLj3DcGQ95DrOWxGSqrPi5DWfrnjDFZRPDSqVMnxMbGYvDgweDxePD29kZQUBB+/PiBdevW4fPnz+Dz+ShUqBAmT56sEqQQ6xIQEICGDRuiQoUKGD9+PJMB1xT++++/dB/D4XDQrVs31K9fH5UrV8Zff/2l1xgdHR0zrfrx4sWLma3cgGJ9zcCBA3HkyBGrz3VSuXJlfP78GXfv3kWzZs2wcuVKcw+JEGKBLCJ44fF46NevH/r166fS7uHhgWXLlplpVIRYpk2bNqlVkb5+/ToiIyNRuHBhM42KEEIyj0UEL8S8njx5gtOnTwPInMRxlu7nz59MkrQ3b96gYMGCZh6RqrS7oXS1W5tDhw5h+/btABSXfwkhJC2z53kh5rV79240bNgQCxcuBAB07NgRnz59MvOozOf169eoXbs2pk+fDkDxfBw7dszMo1LVtGlTCAQClTYPD48sMesyaNAg9O3bl8n30r17dybRICGEKFHwko19//4dI0aMgEwmg0gkAqDIjzJmzBgzj8x8hg0bxuQeAhQLVAcMGGBRM1Lz589H3bp1mdtOTk7Ys2ePWkBjbe7cuYO9e/eqtMnlcqaCNCGEKFHwko29evVKbe2ERCLBo0ePzDQi83vy5Inac5KSkoJ3796ZaUTqHB0dsWvXLvTu3RuAosyCMpGjNbty5QprO1tSPkJI9kbBSzaWNkuxUr58+TJ5JJYjT5486Wo3Fw6HAwcHBwCZW8nalIoVK8babsodaYQQ65Q13vWIQYoVK4Zu3bqBz1es21amfp82bZp5B2ZGM2bMAJfLZbYc83g8DBw4UGOgR4ynVatWrIujU2fOJoQQgHYbZXuLFy9GuXLlcPHiRTg7O6NPnz6oUqWKuYdlNk2bNsXBgwexdetWJCYmwtfXF927dzf3sLIFLpeLGzduICgoCLdv34azszPGjh0LPz8/cw+NEGJhKHjJ5rhcLoKCghAUFGTuoVgMHx8f+Pj4mHsY2ZJQKMTWrVvB4/Hg6uqK6OjobJMxlBCiP7psRAghhBCrQsGLnl69eoUVK1YAAC5dumTm0ZDsbvbs2Vi9ejUA4MCBAybt6+vXr1i3bh0AYPPmzRa1bTyjnj59iuXLlwMArl27ZubREEL0RZeN9HDv3j20adOG2UI7YsQIfP/+HcOHDzfzyEh21K9fP5Wq0h8/fkTZsmVNkszty5cvqFKlCpO9Nzw8HOXLl8fjx49hb29v9P4y09WrV9GxY0emSv2gQYMQExNDl1AJsQI086KHv/76CyKRiAle5HI5Zs2ahW/fvpl5ZCQ7Sh24KH379g1Xr141el9DhgxRKzsQHx+PiRMnGr2vzDZq1ChIJBKVvD5///034uLizDgqQog+KHjRQ2RkJGQymUqbXC7P1mn0ieUJCQkx+n1+/PiRtf3NmzdG7yuzffz4kZl1UZLJZPjy5YuZRkQI0RcFL3ooVqwYeDyeShuXy7W4gn0ke2vZsqXR71NTvaSSJUsava/M5uHhoZbgj8/nI3/+/GYaESFEXxS86GHhwoWwtbWFUCiEUCgEh8PBjBkzkDt3bnMPjWRDf/75p1qbh4cHvL29jd7XP//8o5bh1sXFBbNnzzZ6X5lt+fLlzN+0jY0NOBwOFi5cCEdHR3MPjRCiAy3Y1UO5cuVw+fJlHDhwAElJSahbty5q165t7mGRbGrx4sUoWbIk5s+fj/j4eNSuXRuHDh0ySV+urq4IDw9HUFAQLl68iKZNm2LDhg0QCoUm6S8zVa1aFRcvXsThw4chEonQoEED1KhRw9zDIoTogYIXPRUqVIh2FxGLMXDgQHh7e6Nly5b4+++/TdqXi4sLxo0bh4sXL2LEiBFZqtZQsWLFMHLkSHMPgxCSTnTZiBBCCCFWhYIXQgghhFgVCl4IIYQQYlUoeCGEEEKIVaHghRBCCCFWhYIXQgghhFgVCl4IIYQQYlUoeCGEEEKIVaHghRBCCCFWhYIXQgghhFgVCl5IppHL5fj333/RvHlzAMCUKVMQHx9v5lFZH5lMhsDAQLRq1QoAEBQUhO/fv5usv//++w/t2rUDAPj5+eHkyZMm64sQQvRBwQvJNOvWrcPkyZPx6dMnAMCxY8fQs2dPyOVyM4/Muvz55584efIk87x9+vQJdevWhUwmM3pfp06dwqhRoyASiQAAycnJCAwMxP37943eFyGE6IuCF5JpVq9eDalUytyWSCS4ePEi3r17Z8ZRWZ+zZ8+qtUVFReHOnTtG72vhwoXpaieEkMxAwQvJNElJSaztiYmJmTwS66Zppio6OtrofaWkpLC202tGCDEnCl5IpmnQoAEEAgFzm8vlIk+ePChWrJgZR2V93Nzc1Nq4XC58fHyM3lejRo1Y25XrbQghxBwoeCGZZuHChahSpQpzO2fOnNi1axdsbW3NOCrrc+zYMTg4ODC3ORwO1q5dC0dHR6P3FRwcrBYUtW/fHn369DF6X4QQoi++uQdAsg9nZ2ccOXIEb968gUAggJubG4RCobmHZXUKFy6Mly9f4ty5c4iLi0OjRo3g6upqsv4OHz6M8PBwhIeHw9vbG56enibrixBC9EHBC8lUXC4Xnp6ecHV1RXR0tMoCXqI/Pp+Ppk2bZlp/5cuXR/ny5TOtP0II0YYuGxFCSBalaZE8IdaOghdCCMliXr58idq1azPrlVauXEn5lEiWQsELIYRkIfHx8Wjfvj1evXrFtG3atAlr164146gIMS4KXgghJAu5f/8+vn79qrKeTCaTYffu3WYcFSHGlWUX7AqFQtjY2Jh7GAw+nw8nJydzD8MicDgcAICDgwNNZf+WVc8P5ZZuBweHdD0+OkfU6XuO2NnZsbZzudwsc47R+cEuq76PsMmywYtIJGLqsVgCJycnxMXFmXsYFoHH40EoFCIhIYF2G/2WVc+PhIQE5r/peXx0jqjT9xwpVaoU8ubNix8/fjDPHZ/PR6dOnbLMOUbnB7us8j6iz8QDXTYihJAsxNHREQcPHkTRokUBKAKXwYMHo1+/fmYeGSHGk2VnXgghJLsqWbIkrl27hoSEBNja2oLH45l7SIQYFQUvhBCSRaUuI0FIVkKXjQghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohVoeCFEEIIIVaFghdCCCGEWBUKXgghhBBiVSh4IYQQQohV4Zt7AEpXr17Fjh078PXrVzg7O6NPnz7w8fHBu3fvsGLFCrx9+xb58uVDv379ULFiRXMPlxBCCCFmYhHBy4MHD7B+/XqMGTMGpUuXRmxsLJKTkyGRSDBjxgw0bdoUc+bMwfXr1zFnzhysWbMGLi4u5h42IYQQQszAIi4b7dixA/7+/ihTpgy4XC5cXFzg5uaG8PBwpKSkoGPHjhAIBKhbty48PDwQFhZm7iETQrSQy+XYtm0bOnXqBABYsmQJUlJSzDwqQkhWYfaZF6lUihcvXqB69eoYMGAAkpOTUblyZQQFBSEyMhJFihQBl/v/GKtYsWJ49+6dGUdMCNFl48aN+PvvvyGVSgEovqD8+vULGzZsMPPICCFZgdmDl1+/fkEikeDSpUuYOXMmbG1tsWjRIqxfvx758uWDg4ODyu87ODjg27dvavfz+fNnfP78mbltY2MDd3d3k49fXxwOBzwez9zDsAjK54Gej//LaufHkiVLmMAFACQSCY4cOYJv374hf/78Oo+nc0RdVjtHMoLOD3bZ6Rwxe/BiY2MDAGjVqhVy584NAOjUqRNmz56NTp06ISEhQeX3ExISYGdnp3Y/a9euRXBwMHN74sSJmDVrlglHnn5CodDcQ7Aozs7O5h6CRclK50diYiJrO4/Hg6urq973Q+eIqqx0jhgDnR/qsss5YvbgxdHREblz5waHw1H7mYeHB/bv3w+ZTMZcOnrz5g3q1aun9rv9+/dHmzZtmNs2NjaIjo423cDTycHBQS0Qy654PB6cnZ0RGxur8u08O8tq50eNGjVw8eJFiMViAIpvhDlz5kSOHDn0+rukc0RdVjtHMoLOD3ZZ5RzR5wuO2YMXAGjatCmOHz8Ob29v2NjYYP/+/ahevTrKly8PoVCIAwcOoG3btrhx4wbevXuH2rVrq91H/vz5Vaajf/z4YVEntVwut6jxWAKpVErPyW9Z7fxYvnw5/Pz88OzZM3A4HOTIkQM7duwAn89P1+Okc+T/sto5Ygx0fqjKTueIRQQvnTp1QmxsLAYPHgwejwdvb28EBQWBz+dj0qRJWLlyJXbt2oW8efNiwoQJtE2aEAuXJ08enDt3Dg8fPkRKSgrKlStHU/yEEKPhyOVyubkHYQo/fvww9xBUODk5IS4uztzDsAjKdQ/R0dHZ5luCLnR+qKJzRB2dI/9H5we7rHKOKNe/amMReV4IIYQQQvRFwQshhBBCrAoFL4QQQgixKhS8EEIIIcSqUPBCCCGEEKtCwQshhBBCrAoFL4QQQgixKhS8EEIIIcSqUPBCCCGEEKtCwQshhBBCrAoFL4QQQgixKhS8EEIIIcSqZNnCjMRyff78GWvXrkX//v2RP39+cw+HWCA6R4g2dH4Qmnkhme7z588IDg7G58+fzT0UYqHoHCHa0PlBKHghhBBCiFWh4IUQQgghVoWCF5Lp8ufPj6lTp9K1aqIRnSNEGzo/CC3YJYQQQohVoZkXQgghhFgVCl4IIYQQYlX45h4AyfquXr2KHTt24OvXr3B2dkafPn3g4+ODoKAg/Pr1C1yuIobOkycPVq1aZebRkszUuXNnldsikQje3t6YNGkSAODdu3dYsWIF3r59i3z58qFfv36oWLGiOYZKzETXOULvI9kTBS/EpB48eID169djzJgxKF26NGJjY5GcnMz8fMKECahataoZR0jMac+ePcz/S6VS9OnTB7Vr1wYASCQSzJgxA02bNsWcOXNw/fp1zJkzB2vWrIGLi4uZRkwym7ZzRIneR7IfumxETGrHjh3w9/dHmTJlwOVy4eLiAjc3N3MPi1igu3fvIjk5GT4+PgCA8PBwpKSkoGPHjhAIBKhbty48PDwQFhZm5pESc0l7jpDsi2ZeiMlIpVK8ePEC1atXx4ABA5CcnIzKlSsjKCgIDg4OAIClS5dCLpfDw8MD3bv/r727C4lqa8A4/h+/NpZQpmZa6qgw4oDWkEXRREJ+gBlY4VUv0kVfqF2UQQQZhWnQTUFKGApFGVJoUCRkaZ9XWZkXQSlSoxeSSk2CTTg2vheHBjzWOeLRpsnnB17Mcu2112wWi2fW2jP7f1itVh/3Wnylra2NjRs3YhgGAH19fZjNZu92AEBSUhIOh8NXXRQf+/sY+U7zyPyjlReZM06nk/HxcR4/fsypU6eorq7G6XRSV1cHwKFDh6irq6O+vh673c7JkycZHBz0ca/FF0ZGRnj27BlZWVneMpfL5Q253y1cuBCXy/Wruye/gR+NEdA8Ml8pvMic+f7paMuWLURGRhIWFkZhYSEdHR0AWK1WDMPAMAzy8vJISkrixYsXvuyy+MjDhw+JiYkhJSXFWxYaGsro6OikeqOjo4SGhv7q7slv4EdjBDSPzFcKLzJnwsLCiIyMxGQyTat+QEAA+s3E+amtrW3KJ+r4+HgcDgcej8db9u7dOxISEn519+Q38KMx8iOaR+YHhReZUzk5Ody5c4dPnz7x5csXmpqaWLt2LUNDQ7x+/Rq3243b7ebu3bv09PRgs9l83WX5xXp7e+nr6yMzM3NSeVpaGiEhITQ3N+N2u3n69CkOh2PKN03kz/ezMaJ5ZP7SDbsypwoLCxkZGaGkpITAwEAyMjLYvXs3w8PDXLx4kYGBAYKCgoiLi6O8vFzPKpmH7t+/T0ZGBuHh4ZPKg4KCOHbsGNXV1TQ2NrJ06VKOHj2qr0nPQz8bIy6XS/PIPKVnG4mIiIhf0baRiIiI+BWFFxEREfErCi8iIiLiVxReRERExK8ovIiIiIhfUXgRERERv6LwIiIiIn5F4UVERET8isKLiIiI+BWFFxH5T86ePUt8fDyBgYEUFBRM65hz587R0tIypdxsNlNaWjrLPRSRP43Ci4jMWE9PD2VlZezcuZMnT55w5syZaR33s/AiIjIdejCjiMzY27dvmZiYYM+ePSQlJfm6O//o27dveDwegoODfd0VEfmPtPIiIjOya9cutm7dCkBycjImk4mamhpKS0tJSUlhwYIFmM1m9u/fz+fPn73Hmc1mHA4HNTU1mEwmTCYTly5dmtR2TU0NCQkJLFq0iIKCAoaGhib93+l0UlxcTExMDIZhsHr1alpbWyfVyczMJD8/n8uXL5OSkoJhGHR1dc3NxRCRX0pPlRaRGent7aWpqYkjR47Q3NxMTEwMycnJHD9+nM2bNxMVFUV/fz+VlZUsW7aMBw8eANDZ2UleXh52u52ysjLgr/ATFRWF2WzG4/GQmprKgQMHGB4e5uDBg+Tm5tLY2AjA2NgYGzZs4MOHD5w4cYLly5dz9epVGhsbefnyJWlpacBf4eXNmzdERkZSXl5OeHg4K1euJDo62jcXTERmjbaNRGRGkpOTsVgsANhsNsxmMwAXLlzw1hkfHycxMRG73U53dzcWiwWbzYZhGERHR7Nu3bop7U5MTHDr1i0MwwDg/fv3VFVV4fF4CAgIoKGhgVevXtHV1YXVagUgNzeXnp4eKioquH79uretjx8/0tHRQVxc3FxdBhHxAW0bicisunLlCjabjbCwMIKDg7Hb7QB0d3dP6/hNmzZ5gwuA1WrF7XYzODgIQGtrK2lpaVgsFsbHx71/2dnZdHR0TGorPT1dwUXkD6SVFxGZNTdv3qSoqIi9e/dSWVlJREQEAwMDbNu2ja9fv06rjcWLF096HRISAuA9fnh4mM7Ozh/eeBsYGDjptbaIRP5MCi8iMmtu3LjBqlWrqK2t9ZY9evRoVs+xZMkS0tPTqa+v/9e6JpNpVs8tIr8HhRcRmTUul8u7UvJdQ0PDlHohISHTXon5u6ysLFpaWoiNjSU2NnZGbYiIf1N4EZFZk52dTUlJCRUVFaxfv56Wlhba2tqm1EtNTaW9vZ179+4RHh5OYmIiERER0zpHUVERtbW1ZGZmcvjwYSwWC06nk87OTsbGxjh9+vRsvy0R+c3ohl0RmTX79u2jrKyM8+fPs337dvr7+7l27dqUelVVVaxYsYIdO3awZs0abt++Pe1zGIZBe3s7+fn5VFZWkpOTQ3FxMc+fP/feHCwifzb9zouIiIj4Fa28iIiIiF9ReBERERG/ovAiIiIifkXhRURERPyKwouIiIj4FYUXERER8SsKLyIiIuJXFF5ERETEryi8iIiIiF9ReBERERG/ovAiIiIifuX/nqorOcJWgEYAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332462279)>"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 17
    },
    {
      "cell_type": "markdown",
      "source": "* Now let's consider another data set.\n\n* The data includes the values ​​of two variables `c` and `d` for the years from 1999 to 2019.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "cd = pd.read_csv('correlation_regression.csv')\nprint(cd.shape)\ncd.iloc[[0, -1]]",
      "metadata": {
        "scrolled": true,
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(21, 3)\n"
          ]
        },
        {
          "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>year</th>\n",
              "      <th>c</th>\n",
              "      <th>d</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1999</td>\n",
              "      <td>7.588764</td>\n",
              "      <td>330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2019</td>\n",
              "      <td>8.587049</td>\n",
              "      <td>1070</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    year         c     d\n",
              "0   1999  7.588764   330\n",
              "20  2019  8.587049  1070"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 18
    },
    {
      "cell_type": "markdown",
      "source": "* As we can see in the next diagram, the two variables `c` and `d` seem to follow similar paths.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "plt.style.use('ggplot')\nfig, ax1 = plt.subplots(figsize=(12, 10))\nd_line, = ax1.plot(cd.year, cd.d, 'bo-', label='d')\nax1.set_ylabel('d scale')\n\nax2 = ax1.twinx()\nc_line, = ax2.plot(cd.year, cd.c, 'ro-', label='c')\nax2.set_ylabel('c scale')\n\nplt.xticks(np.arange(cd.year.min(), cd.year.max()+1, step=5))\nplt.legend(handles=[c_line, d_line], loc='right', fontsize=12)",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        },
        "tags": [
          "remove_input"
        ]
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x13d23ca60>"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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sxCuvvILOzk5kZGTg4YcfhkwmQ3NzM9atW4e2tjbo9Xr88Ic/hFqt9mbIRERERH7rYm+B2RMH11vgSuZMjsFHX9Vg5+F6pOrTBvw5a1k5AEDtwc3D+cUGqBRSTE+N8tgx6cq8NjNw9uxZ/PKXv0RtbS0AwG6346WXXsKTTz6JZ599FmVlZThy5AgAYN26dXjggQfw17/+FYIgYOfOnQCA1157DUuXLsVzzz2HlJQUbNy40VvhEhEREfm9i70F5nhgidBFaqUM86bG4shZIwzttgF/zlpWBllkBOQxntno63C6UXTWgBlpWig9lOjQ1XktGdi5cycefPBB6HRd0zylpaVITExEXFwcZDIZ5s+fjwMHDqCpqQl2ux0TJkwAACxcuBAHDhyA0+lEcXExcnNzu8cPHjzorXCJiIiI/N5wegtcyaLMOADAF0caB/wZW2k51KmpQy5ternTlW3otLqQncElQr7ktWVCjzzySI+vDQYDoqKiur+OioqCwWCA0WjsMa7VamEwGGAymRASEgKZTNY93tLS0ue5zGYzzGZzr/G4uLjh/0aIiIiI/MDF3gIr5yZ57Ab8Il2ECpnjtdh3ogk3zdFDrbzyk3mnwQinwYCIJYs8FkN+iQHhIXJkjInw2DHp6kTdpi2RSCAIwoDHpdK+JzI++eSTPpcQbdiwAXq9fviBDpGY56bgx+uLvInXF3kTr6+h2XPqawDAqkWTEKcL9fjx77xBjZ/+bS9On3fgpnmjr/jeptKu/QKj5+QizAN/n51WB46XF+H67DEYPXrUsI7F62twfJYM6HQ6tLW1dX/d2toKrVYLnU6H1tbW7nGj0QitVouIiAhYLBa43W5IpdLu8b6sWLECCxcu7PO1i3sWfE2v14t2bgp+vL7Im3h9kTfx+hoaQRDw2YEKTBwTDqe1FbW1rR4/R4QCGJeowYe7zmDGOBWkV5h9aC4shESlQptSgXYP/H0ePN0Mu8OFyaNVw7o+xLy+AjUJ8Vlp0bS0NNTW1qK+vh5utxv79u1DZmYmYmNjoVQqUVJSAgDYvXs3MjMzIZfLkZ6ejv379wMA9uzZgxkzZvR5bI1Gg7i4uF6/iIiIiIKBJ3sLXMmSmfFobLXhRHnbFd9nKyuHKmUcJDLPbPQtKDEgOkKJFL1n90LQ1flsZkCpVOLRRx/FX/7yF9jtdmRmZnZvDn7sscfwyiuvwGq1Ijk5GcuXLwcAPPTQQ3jhhRfw/vvvIyYmBo8//rivwiUiIiLyG57sLXAlMyfooN1zHjsP1/db3tNtscBeU4uoFcs9cs72TgdOV7ZhaVaix/dC0NV5PRl44YUXuv9/6tSpWLt2ba/3JCcn45lnnuk1Hhsbi6efftqb4RERERH5NW/0FuiPTCrBohlx+GDveZxr7MTouN57E6zlFYAgQO2hZmOHvzbALYBVhETCDsREREREfswbvQWuZN60WCjlUuwsaujzdWtpOSCVQjUu2SPnKygxICkmBEkxnt8UTVfHZICIiIjIj3mrt0B/NGo55k6JQUFJC9rMjl6v28rKoBw9ClKVatjnam6zoay2A9npnmlcRoPHZICIiIjIT13sLTB3coxP19MvzoyH0yVgz7GeTcgEpxO2yiqo01I9cp6Ckq4eUllcIiQaJgNEREREfurgqa6b5dzJvn1yHq9TY2pKJHYfbYTD6e4et1Wfg+BweGy/QH6JAWlJYYiOGP4sAw0NkwEiIiIiPyQIAvafasbEMeGi3CxfNysBJosT+cUt3WO2sq5mY55IBmqaOlHbbOESIZExGSAiIiLyQ77qLdCfiaPDMSo2BDuLGiAIAgDAWlYGeVwsZBERwz5+fkkLpFIJZk3wbrlUf7Rnzx78+Mc/xo9//GO89dZb/b6voqICd999t1dj8VmfASIiIiIxHCpuxqa9NTCY7NCFK5E3Pwk5GeLcYA+Gr3oL9EcikWDxzHi89VklSqpNSB8TDmtpOUKnTR32sd2CgIISAyaNjUBYqMID0QYOm82GN954A3/961+h0Wjwi1/8AsePH8e0adN6ve/111+H0+n0ajycGSAiIqKgdai4Geu3V8FgsgMADCY71m+vwqHiZpEjuzJf9ha4kuz0aISHyrGzqB6Ohga4zWao04a/RKi8pgMt7XZkZwTXEqHGxsZev8xmc4/3uN1uCIIAm80Gl8sFl8sFpVLZ61hvvfUWVqxY4fWYJcLFeR8iIiIion7Ub9+BshdewswX1yEkSS92OH5pzZo1vcZWr17da3zr1q1Yv349lEolJk+ejCeeeKJHtajCwkIcPHgQP/jBD7BmzRps2LDBazEH/TKh2tpaUc6r1+tFOzcFP15f5E28vsibfH19fe8vBf2+9soTWT6LY7D+998laGmz47cPTvVpSdG+tJsd+Nnfj+F+ayESwsJggADJMP4OXS43fvryMUwaG4GHbvJMidKLxPz5pdfr8fzzz/ca12g0Pb6uqqrCrl278OKLLyI0NBTr1q3Dli1bsHLlSgBAa2sr3n//ffziF7/wSdxcJkRERERBS6Pue4mNLrz3sgx/IVZvgf5EaBTISo+GsrYainHjhh3T6ap2mK1OZAXZEiEAiIuL6/Xr8mTg2LFjmDJlCiIjI6FQKLBw4UKcOnWq+/XDhw+jo6MDv/rVr/DTn/4UAPDTn/4UFovFKzEH/cwAERERjUxNrVZY7S5IJMCli6KlEmDVvCTxArsKsXoLXMni8SFwOUw4p47DcBcI5Ze0QKOWYXLy8CsSBaKxY8di7969sFqtUKlUKCwsRGrqNzMkS5YswZIlS7q/XrNmDdauXeu1eDgzQEREREHH7Rbwj20VUMhlWL1wdPdMQIhKBrcAdFi8W6FlqMTuLdCf6LY6AMC+Vg1cLvdV3t0/m8OFY6WtmDVBB7lsZN6GTp8+Hddccw2eeuop/OQnP4HL5UJeXh5efvllFBYW+jwezgwQERFR0NleWI/Smg58+4ZxmDM5BtfNTADQVdLy1S1l2Lj7HJJiQpEx1r+eTl/sLXDzXP/aoGstLYcgV6DUHYGis0ZkDbFR2PGyVtgc7qBcIjQYeXl5yMvL6zH2yCOP9Pleb24eBjgzQEREREHmXGMnPvqqBjPHa5E7qedNp1QiwbdvGIcEnRp//7gMzW02kaLsm9i9BfpjLSuDOiUZMbquJmRDlV9sgDZMgbSkMA9GR8PBZICIiIiChsPpxutby6FRy3DPdWP73OyqVsrw6KrxEAQBL20+C7vDJUKkvflLb4HLua1W2M+dR0haKhZnxqOizoyy2o5BH6fD4sTJyjZkpUdD6gcbo6kLkwEiIiIKGpu/qkFtswX3Lxt3xc62cVo1HlyRipomC976rBL+0HbpyFkjbA435kz2r+7ItopKQBCgSk3BnMkxCFXJsPNw/aCPU3TGALdbCLpGY4GOyQAREREFhTPn2rGjsB4LpsViakrUVd8/ZVwk8uaNQsHXBmwvHPzNraftP9WMmEiV3y2hsZaVAxIJ1OOSoVbKMG9qLIrOGtHSPrglVvklBiTq1BgVG+KlSGkomAwQERFRwLPYnHhjawVio1S47drRA/7csuwEzJqgxYd7z+N0ZZsXI7wyf+stcClraRmUo5IgDem6iV+UGQcJgF1HGgd8DEO7DWfPm5CVEe13v7+RjskAERERBbz3dlXD2GHHA8tToFYOfL29RCLB/cvGQR8dgr9/UoamVqsXo+yfP/YWAADB5YKtshLqS+rg6yJUyByvxb4TTbDaB7bfouBrAwAgO13nlThp6JgMEBERUUArOmvAgVMtWJ6TiBT94JfYqJUyfH9VGgDgpc2lA77B9RR/7S0AAPbzNRBsdqjSUnqMXzcrARabCwdONQ/oOAXFBoxL1CA2Su2NMGkYmAwQERFRwGozO7B+exXGxIXiptyh1+aPjVLj4RWpqG2x4M3PKny6ofhib4G5frZxGOhaIgQA6tSeyUCKPgzjEjX4oqgB7qv8WdW2WHCuqRPZQ+xNQN7FZICIiIgCkiAI+Of2CtidLjxwYwpkw+xoOyk5ErfMH4WiM0Z8lu+7DcX+2lsA6No8LI+OhjwqqtdrS2bGo7HVhhPlV95rUVDSAokEmD2RS4T8EZMBIiIiCkh7TzThRHkbbpk/Cvpoz1SoWTo7AVkTddi07zxOVrR65JhX4q+9BYCuZMtWVgb1ZUuELpo5QQdtuPKKZUYFQUB+sQEZYyIQoem/1CuJh8kAERERBZymVis2fnkO6WMisCgz3mPH7dpQnIyk2BD83yflaDB6d0Oxv/YWAABnUzNc7SaoLtk8fCmZVIJFmXH4+pwJ5xo7+3xPZb0ZzW029hbwY0wGiIiIKKC43AJe/7QcUqkE31qW7PFutkqFDN9fNR4SiQQvbT7r1Q3F+081IzbK/3oLAIC17MJ+gX5mBgBg3tRYKOVS7Cxq6PP1Q8UtkMskmJHmf0ugqAuTASIiIgoonxXUobzOjLuXjIXOS9V3YiJVePimVNQbrHhja/lVN8kOxcXeAnP8sLcAAFhLyyHVhEIR3//Mi0Ytx9wpMSgoaUGb2dHjNZdbQOHXBkxLjUKIyr+WQNE3mAwQERFRwKhuMGPL/lrMmqBFlpdr1meMjcDqa0fjaGkrth6q8/jxD55qgQTAnEn+uYTGVlYGdUoKJNIr3y4unhkPp0vA7qM9m5B9Xd0OU6eTVYT8HJMBIiIiCggOpxuvby1HeIgc91yX7JOn6UtmxiM7Q4ctX9XgeFmrx477TW+BCK/NbgyHy2SCo6ERqrS+9wtcKl6rxtSUSOw51giH0909nl/SghCVDFPGRXozVBomJgNEREQUED7cdx51LVZ864Zx0ITIfXJOiUSC+64fh9Fxofi/T8tRb7B45LhnL/QWmONnHYcvspaVA+jdX6A/181KgMniRH5xVydlu8ONI2eNmDleC4Wct5v+jH87RERE5PdKqtux83ADFs6Iw+Rk3z5pViqk+P6qNMhlEry0uRQW2/A3FB842Qy10j97CwBdyYBELodqzOgBvX/i6HCMig3BzqIGCIKAExWtsNrdrCIUAJgMEBERkV/rtDrxj20ViNeqcduCUaLEoItQ4bs3p6LROPwNxVa7C4fPGDBrgv/1FrjIVloOZfJYSBQD6w0gkUiweGY8apotKKk2Ib+4BZEaBSaMCvdypDRcTAaIiIjIr737RTXaOux4YPk4KEW8eZ44OgK3LxyDY2Wt+ORA7ZCPc7G3wFw/7C0AAG67Hbbq6gEvEbooOz0aKoUEz394BkdLW2FzuFDwdYuXoiRPYTJAREREfuvw1wYcKm7Bjbl6jEsUvxb/osw4zJkcjY8P1OJoqXFIxzhwobdAqh/2FgAAW2UV4HZDPYDNw5cqOmuA0wU4XV2zJla7G+u3V+FQcbM3wiQPYTJAREREfqmtw463d1QiOUGDG3MSxQ4HQNdymHuuS8bY+FC8/mk56loGt6G4uc2Gr8/5b28BALCWlgESCVTjxg3qc5v21sDl7rl8yu50Y9PeGk+GRx7GZICIiIj8jiAIePOzStidAh5YPg4ymf/csijkUjyyMg1KhRQvbj6LTqtzwJ89eLrZr3sLAICtrBwKfSJkmtBBfc5gsg9qnPyD/3xnEREREV2w51gTTlW24bYFo5CgCxE7nF50ESp87+Y0NLfZ8foANxS7BQEHTrX4bW8BABDcbljLKwa9XwAAdOHKQY2Tf2AyQERERH6lwWDFxt3nMGlsBBbOiBM7nH6NHxWOOxaNwYnyNmzZf/WlMKV+3lsAAOw1tRCsVqhTB7dfAADy5idBeVlPAaVcirz5SZ4Kj7zANx07iIiIiAbA5Rbw+tZyyOUS3L9snN+uq7/o2umxqG4w49ODdRgdF4qZ43X9vtffewsAgK2sDACgThv8zEBORld1pE17a2Aw2aELVyJvflL3OPknJgNERETkN7YdqkNlvRkPrUiBNgCWl0gkEty1ZCxqWyz4x9auXghJMb3X2l/sLTB7ov/2FgAAa2k5ZFot5Lr+k5orycmI4c1/gOEyISIiIvILlfVmfHygBtnpOmSl++9Smssp5FJ87+Y0qJQyvLS5FOY+NhT7e28BoGvTtrW0bEj7BShwMRkgIiIi0dkdLryxtRwRGgXuXDJW7HAGTRuuxPduToWh3Y7/+6Qc7stKbPp7bwEAcBoMcLW1DWmJEAUuJgNEREQkug/2nke9wYpv3zAOGnVgrmJOSwrHnYvH4FRlGzZ/db57PBB6CwCArbQcAIa0eZgCV2B+txEREVHQOF3Zhl1HGrE4Mw4ZYyPFDmdYFkyPQ3VjJ7bl12N0nAazJ+oCorcAAFjLyiANCYFC7x8N3sg3mAwQERGRaMxWJ978rAIJOjVumT9a7HA84o5FY1DT1InXPynDhl3VaDM7IJdJcLbGhBw/7S8AdG0eVqWMg0TKhSMjCf+2iYiISDTv7KxCe6cT37kxBUpFcNyWKORSZGfo4BKANrMDAOB0CVi/vQqHiptFjq5vLrMZjro6bh4egYLju46IiIgCTkFJCwpKDLhpjh5j4zVih+NR2wsaeo3ZnW5s2nv15mRisJVXAABUadwvMNIwGSAiIiKfM5rs+NeOKoxL1OCG7OBbo24w2Qc1LjZraRkgk0E1dozYoZCPMRkgIiIin3ILAt78rAJOl4DvLE+BTOq/FXaGStdPw7T+xsVmLSuHauwYSJX+GR95D5MBIiIi8qndRxtRXNWO2xeORpxWLXY4XpE3PwlKec/bLKVcirz5SSJF1D+3wwFbVTX3C4xQrCZEREREXneouBmb9tbAYCoAAIyKCcH8abEiR+U9ORldnYa7fs926MKVyJuf1D3uT+xV1YDTCRX7C4xITAaIiIjIqw4VN2P99irYne7usYZWK/JLWvzy5thTcjJiAuL3Zy0rAwCoU8eJHAmJgcuEiIiIyCsEQUBTqxXvfXGuRyIAAA6n4LeVdUYaa2k5FAkJkIWFiR0KiYAzA0REROQRVrsLlfVmlNd1oKLWjIq6Dpgszn7f76+VdUYSwe2GrawcmlmZYodCImEyQERERIPmFgTUG6yoqO1AeV3XjX9tswXChdcTdGpMSYlCSqIGHx+o7W6+dSl/rawzkjjq6uG2WKDi5uERi8kAERERXVVHpwMVlz71rzfDancBAELVMoxLCEPmeC1S9GFITtBAo/7mFkOllPbaM+CvlXVGGmtZOQBAzc3DIxaTASIiohHkm6o+/Ve4cbncON9sQXltByouPPVvbLUBAKQSICk2FDkZOoxLDMO4RA3itGpIJf33Cri0so7RZIfWjyvrjDTWsjLIIiMgj4kWOxQSCZMBIiKiEeLyqj4Gkx3rt1fBbHEiMkzZfeNf1WCGw9m14CdCo0BKogbzpsZinD4MY+NDoVLIBn3ui5V19Ho9amtrPfr7oqGzlZZDnZoKyRWSOQpuoiQDmzZtwq5du6BQKDB37lzceuutqKysxCuvvILOzk5kZGTg4YcfhkwmQ3NzM9atW4e2tjbo9Xr88Ic/hFodnA1KiIiIvGnT3ppeVX3sTjfe23UOACCXSTAmLhQLpschJTEMKYkaaMOVvFEMUk6DEU6DARFLFokdConI58nA8ePHsW/fPjzzzDNQq9VYu3YtDh06hA0bNuB73/seJkyYgJdeegk7d+7E0qVL8dprr2Hp0qW45pprsHHjRmzcuBH33nuvr8MmIiIKeFeq3vOzezIwKjYUchmrjo8U3fsF0rhfYCTz+Xd8ZWUlpk+fjtDQUEilUsyYMQPbtm2D3W7HhAkTAAALFy7EgQMH4HQ6UVxcjNzc3O7xgwcP9jqm2WxGY2Njr19ERET0jf6q9+jClUhOCGMiMMJYy8ogUamgTNKLHQqJyOczA+PGjcObb76JW265BUqlEoWFhZBKpYiKiup+j1arhcFggMlkQkhICGQyWfd4S0tLr2N+8skn2LhxY6/xDRs2QK8X7wIX89wU/Hh9kTfx+gpO997owN/eO9pjTKWQ4YGbp/j075zXl39orD6HyIx0JI0eLXYoHsXra3B8ngxMnToVCxcuxNNPP42wsDBMnToVJ0+e7PU+iUQCQRB6jUulvZ9arFixAgsXLuzzfGJtUuIGKfImXl/kTby+gpfR0AoACA+Vw9Tp7K4mNCFR5rO/c15f/sFtscBcWYWoFcuD6u9DzOsrUJMQnycDFosF2dnZuOmmmwAAH3/8MWJjY1FcXNz9HqPRCK1Wi4iICFgsFrjdbkil0u7xy2k0Gmg0Gp/9HoiIiAKNIAjYeaQBo2JD8PP7JnNT8AhnLa8ABAFqNhsb8Xy+OLCxsRFr166Fy+VCZ2cndu7cicWLF0OpVKKkpAQAsHv3bmRmZkIulyM9PR379+8HAOzZswczZszwdchEREQBr6TahNpmC5bMTGAiQLCWlgNSKVTjksUOhUTm85mBsWPHIicnBz/5yU/gdruxYsUKpKen47HHHsMrr7wCq9WK5ORkLF++HADw0EMP4YUXXsD777+PmJgYPP74474OmYiIKOB9UdSA8BA5stJ1YodCfsBWVgbl6FGQqlRih0IiE6XPwOrVq7F69eoeY8nJyXjmmWd6vTc2NhZPP/20jyIjIiIKPg1GK06Ut+LGXD0UclYMGukEpxO2yiqEL5gndijkB/gTgYiIKMjtOtIAqVSCa2fEiR0K+QFb9TkIDgf3CxAAJgNERERBzWJzYv/JZmSl6xCpUYgdDvkB28VmY0wGCCItEyIiIiLf+OpkM2wONxbPjBc7FPIT1rIyyONiIYuIEDuUEWvPnj3YtGkTAGDGjBm4//77e7xeUlKCN998E06nE+Hh4fj+97+P2NhYr8TCmQEiIqIg5XYL2HWkEWlJYRgbzxLc1FVi1lpaDnVqqtihjFg2mw1vvPEGnn76aaxduxYlJSU4fvx4j/esW7cOjzzyCNauXYt58+bhjTfe8Fo8nBkgIiIKUsfLWtHcZsNtC0aJHQr5CUdDA9xmM9RpXCLkDY2Njb3GLu+H5Xa7IQgCbDYb1Go1XC4XlEpl9+sOhwN33HEHxo4dC6CrEue2bdu8FrNE6KvNLxEREREFnfrtO1D2wkuY+eI6hCQFZsdcf7ZmzZpeY6tXr+41vnXrVqxfvx5KpRKTJ0/GE0880Wf/D7fbjT/96U9ITU3F7bff7pWYg35mQMyW1MHU3pv8C68v8iZeX8HhXGMnfvvPU7htwSgszUoUO5xuvL7E1XT4MKRhYTBAgCQI/x7EvL70ej2ef/75XuOXzgoAQFVVFXbt2oUXX3wRoaGhWLduHbZs2YKVK1f2eJ/T6cTzzz8Pl8uFW265xWtxc88AERFRENpZ1AClXIprpnpn0yEFJmtZOdRpKexC7SVxcXG9fl2eDBw7dgxTpkxBZGQkFAoFFi5ciFOnTvV4j9Vqxe9+9zu43W48+eSTkMu99/yeyQAREVGQae90oKCkBXMmx0CjDvpFADRAzrY2OJuauXlYZGPHjsWJEydgtVohCAIKCwuRetnfyd/+9jckJCTgRz/6ERQK75YE5k8IIiKiILPnWCOcLgGLZ7LJGH2ju78ANw+Lavr06aioqMBTTz0FmUyGtLQ05OXl4eWXX8bs2bMRHR2NwsJCjBo1Ck8++SQAQKfT4Wc/+5lX4mEyQEREFEQcTjd2H2vClHGRSNCFiB0O+RFraTkkCgWUo0eLHcqIl5eXh7y8vB5jjzzySPf/b9iwwWexcJkQERFREDl8xoB2swNL2GSMLmMtK4NqXDIkMpnYoZAfYTJAREQUJARBwM7DDUjUqZExlt1l6RtuqxX2c+ehTuN+AeqJyQAREVGQKKvpQHVjJxbPjGe1GOrBVlEJCAJUqdwvQD0xGSAiIgoSO4saEKqWIXdStNihkJ+xlpUDEgnU45LFDoX8DJMBIiKiINDSbsORUiPmT42FUsE14dSTtbQMylFJkIZwUzn1xGSAiIgoCOw60ggJgIUzWE6UehJcLtgqK9lfgPrEZICIiCjAWe0ufHWiCZnjtdBFqMQOh/yM/XwNBJsdKvYXoD4wGSAiIgpwB0+3oNPmwpJZCWKHQn7IWloGAFBz8zD1gckAERFRAHMLAr4oakByggYpiRqxwyE/ZC0rhzxaB3lUlNihkB9iMkBERBTATle2ocFoxRKWE6U+CIIAW1kZVNwvQP1gMkBERBTAdh5uQKRGgZkTtGKHQn7I2dQMV7sJau4XoH4wGSAiIgpQtS0WnK5qx8IZcZDL+E869WYtu7hfgDMD1Df+5CAiIgpQu4oaIJdJMH9arNihkJ+ylpZDGhoKRUK82KGQn2IyQEREFIDMFicOnG5BTkY0wkMVYodDfqprv0AKJFLe8lHf5GIHQERERIO390QTHE43lszkE19/ZcovgHHzFrgMRsh0WmhX3Yzw7Cyfnd9lMsHR0IiwObk+OycFHiYDREREAcblcuPLIw2YOCYcSbGhYodDfTDlF6Dl7Xcg2B0AAJfBiJa33wEAnyUE1rJyAIA6jfsFqH9MBoiIiALMkdJWGDscuOu6ZLFDoX4YN2/pTgQuEuwOtLzzHlytbZBFhEMWEQFZeHjX/4eFQSKTeTQGa1k5JHI5VGNGe/S4FFyYDBAREQWYnYfrERulwtSUSLFDoX64DMY+xwWrDcYPN/d+QSKBVKP5Jjm4+N+IcMjCI3qOhYdDIu//Fu7S5UmQy9Fx5KhPlydRYGEyQEREFEAq6jpQXmfGHYvGQMomY37H1WFGy3v/7vd1mU6LUT//GVwmE1ztF36ZTN98bWqHq90EW1UVXO0mCDZbn8eRhoZeliB0JQyO5hZ05BcATmfXG51Ony9PosDCZICIiCiAfFHUALVSijmTY8QOhS5jPnIUze9sgNtsRsiM6bCeOg3B8c1SIYlSAe2qmyENCYE0JASKuLirHtNtt8PV3v5N0tD93/bur+3nauAylcBtsfR5DMHugHHzFiYD1CcmA0RERAGitcOOwjNGLJoRhxCVZ9eX09C5TCa0vLcR5sNFUI4ehZgfPgrVqFEeqSYkVSohjYmBIubqyZ/b4UDVD3/cd4z9LFsiYjJAREQUIL482gjBLWBR5tWfKJNvmIuOdM0GWCyIunkFopZd370RODw7y6dP46UKBWQ6bZ83/jKd1mdxUGBhMkBERBQA7A439h5vwrTUKMRGqcUOZ8RztZvQ8t6/YS46AuWY0Yi9/zEok/RihwXtqpt7lDQFvlmeRNQXJgNEREQBIL+kBR0WJ5bMYpMxMQmCAPPhIrS8txFuqxXaVTcj8volHi8LOlQXZyLEbHZGgYXJABERkZ8TBAE7ixowKjYEE0aFix3OiOVqb0fzOxvQefQYlGPHIPb+e6HUJ4odVi++Xp5EgY3JABERkZ/7+pwJtc0W3L8sGRKWE/U5QRBgLjzcNRtgs0GbtxKR1y32m9kAouFgMkBEROTndh5uQHiIHNnp0WKHMuI429rR8s576Dx2HKrkZMTcfzeUif43G0A0VEwGiIiI/Fij0YoT5a24MVcPhVwqdjgjhiAIMBcUouW9jRDsduhuzUPEkkWQSPl3QMGFyQAREZEf23WkAVKpBNdOjxU7lBHD2dqGln+9i84TJ6FKGYeY++6GMiFB7LCIvILJABERkZ+y2FzYf6oZsyfqEBmmFDucoCcIAjoO5cOw4X0ITid0t92CiMULORtAQY3JABERkZ/66mQTrHY3y4n6gLO1Fc1vvwvLyVNQpaYg9r57oIhnczcKfkwGiIiI/JDbLWDXkUak6sMwNl4jdjhBSxAEdBw8BMO/P+iaDbj9NkQsXMDZABoxmAwQERH5oePlrWhus+HWBaPEDiVoOY3GrtmAU6ehSkvtmg2I494MGlmYDBAREfmhnUUN0IUrMSNNK3YoQUcQBHTsP4iWjR8Abjei71iN8AXzORtAIxKTASIiIj9zrrETZ86ZcOuCUZBJ2WRsuEz5BTBu3gKXwQhZVCSkoaFw1NZBPWE8Yu69G4rYGLFDJBINkwEiIiI/80VRA5RyKeZN5ZKV4TLlF6Dl7Xcg2B0AAFdrG1ytbdDkZiP2vns4G0AjHr8DiIiI/Eh7pwP5JS2YMzkaGjWf2Q2XcfOW7kTgUtYzZ5kIEIHJABERkV/Ze6wJTpeAxZksJ+oJLoNxUONEIw2TASIiIj/hdLnx5bFGTE6OREJ0iNjhBAWZru8N2P2NE400TAaIiIj8ROHXBrSbHWwy5kGRNyztNSZRKqBddbMI0RD5HyYDREREfkAQBOwsakCCTo1JYyPEDidoSGUyAIAsIrzrvzotou+5C+HZWWKGReQ3uDOJiMjPHCpuxqa9NTCY7NCFK5E3Pwk5GSx9GOzKajtQ3dCJu68bC4mE5UQ9pSO/EPLYGIz69S/550rUB84MEBH5kUPFzVi/vQoGkx0AYDDZsX57FQ4VN4scGXnbzqIGhKplyJ0ULXYoQcPZ1gbrmbMIy5rNRICoH0wGiIj8yKa9NbA73T3G7E43Nu2tESki8oWWdhuOnDVi3tRYqBQyscMJGubCw4AgQJM1S+xQiPwWkwEiIj9ycUZgoOMUHL480ggJgEUz4sQOJah0FByGcvRoKBMSxA6FyG8xGSAi8iP9NZnShSt9HAn5is3hwr4TTcgcr4UuQiV2OEHD0dAIe1U1wrJnix0KkV8TZQPxnj17sGnTJgDAjBkzcP/996OyshKvvPIKOjs7kZGRgYcffhgymQzNzc1Yt24d2traoNfr8cMf/hBqtVqMsImIvKqtww670wUJAOGScaVcirz5SWKFRV528FQLOm0uLJnJcqKe1FFQCEgk0MyeKXYoRH7N5zMDNpsNb7zxBp5++mmsXbsWJSUlOH78ONatW4cHHngAf/3rX7vKq+3cCQB47bXXsHTpUjz33HNISUnBxo0bfR0yEZHXCYKA9Z9XAQBuWTCqx0zATXP1rCYUpNwXyomOjQ9Fij5M7HCChiAI6CgohHp8GuRRUWKHQ+TXfJ4MuN1uCIIAm80Gl8sFl8sFuVwOu92OCRMmAAAWLlyIAwcOwOl0ori4GLm5ud3jBw8e9HXIRERed/B0C46XtyJv3igsy0rEM9+djrXfnwGlXIqaJovY4ZGHHSpuxs9ePYbv/28hGoxWJCdoWO3Gg+zV5+BsbEIYewkQXZXPlwmFhITgjjvuwH/+539CqVRi8uTJkMvliLokc9dqtTAYDDCZTAgJCYHsQsMQrVaLlpaWXsc0m80wm829xuPiuBGLiPyf0WTHe7uqkZYUhsWXLBWJCFXg2umx2FHUgBW5esTruEQyGFwsH3tp1aj9p5qRmhTGGSAP6SgoBORyhM6YLnYoRH7P58lAVVUVdu3ahRdffBGhoaFYt24djh071ut9EokEgiD0GpdKe09mfPLJJ30uH9qwYQP0er1nAh8CMc9NwY/XV3AQBAGvfHIQbgH46f050Mf0XCpy38067D6+A1+eaMWP7vLd2mdeX96z5fWTvcrHOpwCthyoxy1LpokUlW958/oSXC6cLzoK3ayZGD0+zWvnIf/Fn1+D4/Nk4NixY5gyZQoiIyMBdC392bJlC1pbW7vfYzQaodVqERERAYvFArfbDalU2j1+uRUrVmDhwoV9nq+2ttYbv42r0uv1op2bgh+vr+Cx70QTikoacefiMYC9HbW17b3es2BaDHYePoeF06IQr/X+7ACvL+9qMva97KvJaBkRf+7evr4sJV/DYTRCPnXKiPjzpJ7E/PkVqEmIz/cMjB07FidOnIDVaoUgCCgsLERGRgaUSiVKSkoAALt370ZmZibkcjnS09Oxf/9+AF1ViGbMmNHrmBqNBnFxcb1+ERH5M0O7Df/+shoTR4fj2ivUl1+alQi5TIKth3hjEwz6KxPL8rGe0VFQCIlajZCpk8UOhSgg+HxmYPr06aioqMBTTz0FmUyGtLQ05OXlITs7G6+88gqsViuSk5OxfPlyAMBDDz2EF154Ae+//z5iYmLw+OOP+zpkIiKPEwQBb31WCUEA7l82DtIrbB6N1CiwYHocdhU14MYcPeJ8MDtA3pM3PwlvbquEy/3NUliWj/UMt8MBc9FRaGZMg1TJ5IpoIETpM5CXl4e8vLweY8nJyXjmmWd6vTc2NhZPP/20bwIjIvKRPcebUFzdjnuuG4uYyKs3mlqWlYg9xxrx6aE6fPuGcT6IkLwla2I03vuiGjaHG06XAF24Ennzk7h52AMsJ09BsFqhyWKjMaKBEiUZICIayZrbbHh/9zlkjI3A/GmxA/pMpEaB+dPi8OWRBqzITURsFGcHAtWxslaYrS58b2UqZo7XiR1OUOkoOAxZRDhCJk4QOxSiK+qrAe+lfNl01+d7BoiIRjK3IODNbRWQSCS4f2nyoGrL35CVAJlMgq2H6rwYIXnbF0caoAtXYnpq74IYNHRuiwWWEyehmTUTkgslyYn8UX8NeC/ly6a7TAaIiHzoyyONOHPehDULR0MXcfXlQZeKDFNi/tRYHDjVjKZWq5ciJG8639SJM+dMWJgZB5mUTcY8yXzkGASnk0uESFSNjY29fl3eC6uvBrzKS/a4+LrprkToq5g/ERERUQA5+ctfw9bQiJkvP89uziSaNWvW9BpbvXp1r/GtW7di/fr13Q14n3jiie7r1mg04mc/+xlefvllAIDL5cK9996Ld955xysxB/2eAfYZoGDE6yvwuN0C/vxeCepaLPjlt6ZAO4wyku9+UYXdx5rwm+9MHdDm48Hi9eUdHZ0OPPX3Y5gzKQb3XJ8sdjii8cb15WxrQ9vxE4havgx1dVxGN5KJ3Wfg+eef7zWu0Wh6fN1XA94tW7Zg5cqVADDgpruewmVCREQ+sLOoAWW1Hbhj8ZhhJQJAV2UhqQTsOxBg9p5ogsMpYFFmvNihBB1zYREgCNDMniV2KDTC9dX36vJk4NIGvAqFAgsXLsSpU6e6X7+06S6AfpvuegqTASIiL6tvsWDzV+cxPTUKORnRwz6eNlyJeVNjsf9UC5rbbB6IkLzN5XLjy6ONyBgTAX1MiNjhBJ2OgkIoR4+CMjFB7FCIrqqvBrypqandrw+06a6nMBkgIvIit1vAPz6rgFIuxT3XD6560JXckN01O7Atn0siAsGR0la0djiwaCZnBTzN0dgIe1U1wrK5cZgCw/Tp03HNNdfgqaeewk9+8hO4XC7k5eXh5ZdfRmFhIYCuprs7duzAj370IxQXF+POO+/0WjxBv2eAiEhM2wvrUVFnxoM3piBSo/DYcbXhSlwzJRZ7TzRheU4iogdZmYh864uiBsRGqTA1JVLsUIJOR34hIJFAM2um2KEQDVhfDXgfeeSR7v/3ZdNdzgwQEXlJbbMFW/bXYOZ4LbLSPd9c6obshK7ZAfYd8GuV9WaU1XZgUWYcpKxy41GCIMBccBjq8WmQe3FNNVEwYzJAROQFLpcbb2wrh1opw13XjfVKqUNdhArXTInBVyebYWjn3gF/tetIA1QKKeZOjhE7lKBjrz4HR2MjNFncOEw0VEwGiIi84LOCelQ3dOLuJWMREeq55UGXuyE7EQCwlXsH/FKb2YGCEgPmTolBiIorcz2to6AQkMmgycwUOxSigMVkgIjIw841duLjA7WYPVGHWRM9vzzoUroIFa6ZGoOvTnB2wB/tOdYIl1vAohncOOxpgtsNc+FhhE6ZBJkmVOxwiAIWkwEiIg9yutx4c1sFNGoZ7loy1ifnXH5hdoCVhfyL0+XGnmONmDIuEvE6tdjhBB3rmbNwtbVDk8UqQkTDwWSAiMiDth6qw7mmTtxzfTLCQnyzLEQXocLcC3sHjCa7T85JV1f4tQHtnU4sZjlRr+goOAyJSoXQqVPEDoUooDEZICLykOoGMz49VIecjGjMSPNtZZPlOYlwC5wd8BeCIOCLogYk6NSYNDZC7HCCjtvhQOeRo9DMmA6pcngdvYlGOiYDREQe4HC68ca2CoSHyHHH4jE+P390hApzJ8dg34kmzg74gfI6M6oaOrEoM94rlaRGOsup03BbLNCw0RjRsDEZICLygE8O1qK22YL7liZDoxanagxnB/zHrqIGhKhkyJ0ULXYoQamjoBDS8HCETJwgdihEAY/JABHRMFXWd2Bbfh3mTo7B1JQo0eKIiVRh7uRozg6IzGiy4/BZI66ZEgO1UiZ2OEHHbbHAcvwkwmbNhETGP1+i4WIyQEQ0DA6nG//YWoEojQJrFo0WOxwsz9HDLQCfFXB2QCy7jzVCcAtYlMmNw95gPnoMgtPJRmNEHsJkgIhoGD76qgZ1BivuXzbOL5pKxUSqMGdSNPYeb0JrB2cHfM3ucGPPsSZMS41CTKRK7HCCUkfBYchjYqAalyx2KERBgckAEdEQldWY8HlhPeZPi8Wk5Eixw+m2PCcRbreAzwrqxQ5lxCkoaYHZ6sQSlhP1CmdbO6wlXyMsaxY3ZhN5iPiPsYiIApDd4cI/PquALkKJ1deKvzzoUrFRauROisHe4424ISsBkWEsvegLgiDgiyMN0MeEYMLo8Cu+15RfAOPmLXAZjJDptNCuuhnh2Vk+ijRwmQ8XAYLARmNEHsSZASKiIdi0rwaNRhvuXzbOLzeJ3pibCJeLswO+dPa8CeebLFhylXKipvwCtLz9DlwGIwDAZTCi5e13YMov8FWoActcUAjlqFFQJiaIHQpR0GAyQEQ0SGfOm/BFUQMWzohD+hj/bCgVG6VGzqQY7DneiDazQ+xwRoQvjjRCo5YhO0N3xfcZN2+BYO/5dyLYHTBu3uLN8AKeo7EJtsoqhLG3AJFHMRkgIhoEm8OFN7dVIDpShVvmjxI7nCu6Mefi7AArC3lbc5sNR0uNmD8tFkrFlWeKLs4IDHScunQUFAISCTSzZ4odClFQYTJARDQIH+w5j+Y2G751g38uD7pUnFaN7Ixo7DnWhHbODnjV7qONkAC4dnrcFd8nuN2QqPquMiTTab0QWXAQBAHmgkKo01Ih1/LPiciTmAwQEQ1QSXU7vjzaiMUz4zFh1JU3iPqLG3P1cLrc2M7ZAa+xOVzYd6IJmeO10EX0X05UcLnQ9MZbEGw2QNr7n1/tihu9GWZAs587D0dDIzcOE3kBkwEiogGw2l1467MKxGlVuGVektjhDFi8Vo2cjGh8ydkBrzl0ugWdNhcWX6HJmNtuR8PLr8JceBjavJWI+da93TMB0vAwAIDTYPBJvIGoI78AkMmgmTlD7FCIgg5LixIRDcDG3edgaLfjp3emX3VNuL+5MUePQ8Ut2F5Y73dlUAPdxXKiY+JCkZoU1ud73BYL6l98BbayckTfcyci5l0DAD1KiTb+3z/Q+tnn0MyeCWUCK+VcSnC7YS4sQujkSZBpNGKHQxR0ODNARHQVpyvbsPd4E66bnYDUpMBYHnSpeJ0a2enR2H20Ee2dnB3wpJLqdtS1WLF4Zt/lRF3tJtQ9+zfYKioR++C3uxOBy0XffiukCgVa/vUeBEHwdtgBxXq2FK62NmiyZokdClFQ4swAEVEfDhU3Y9PeGhhMdkglQIRGjpVzA2d50OVuzE1EfkkLPi+ox22cHfCYnUUNCA+VY/bE3uVEnQYD6v/6ApxGI+K//12ETp7U73FkERHQ3roKLW+/i44DhxA+N9ebYQeUjvxCSFQqhE6bKnYoREGJMwNERJc5VNyM9durYDDZAQBuAei0unCkNHDXdCfoQpA1UYcvjzbCxNkBj2g0WnGyvA0LpsVBIe/5z6m9vgG1f34OLpMJCY//4IqJwEXhc+dAlZoCwwcfwmUyeSvsgCI4HOg8chSaGdMgVbKTNpE3MBkgIrrMpr01sDvdPcacLgGb9taIFJFnrMjVw+F04/NCdiX2hF1HGyGRSnDt9Nge47bqc6j7y3MQnE4k/OiHUKemDOh4EqkUMffcCbfVBsP7m7wQceDpPHUabouFVYSIvIjJABHRZS7OCAx0PFAkRIdgdnrX7EAHZweGxWp3Yf/JJsyeoEVk2DdPrC1nS1H37N8gUSqgf+I/oRo9uMZ0ysRERF5/HToO5cNS8rWnww445oLDkIaFISR9otihEAUtJgNERJfRhfe9HKG/8UCyIlcPu8ONzw9zdmA49p9shtXuxuKZ35QT7TxxEg3rXoQ8KhL6n/wIivgrNyDrT9TypZDHxqL5X+/B7Ri5SZvbYkHniZMImz0TEllgVfAiCiRMBoiILrM0u3dpR6Vcirz5gbuB+KLE6BDMnqjDriOcHRgqtyBg19EGjEvUYFxiVznRjoJCNLz8dygSE5D448eH1SVXqlQi5q41cDY1oW3bdk+FHXDMR49DcDi4RIjIy5gMEBFd5lxDJyQAIjUKAF0zAvcuHYucjBhxA/OQG+dcnB1oEDuUgHSqog2NRlt3k7H23XvR9MZbUKemIPE/H4MsfPjlZ0My0qHJzkLrZ5/DXjcyu0ebCwohj46Galyy2KEQBTWWFiUiukR1gxn7TzZjyax43L5wjNjheIU+OgQzJ2ix60gDrp+dgLAQ/lMwGF8caUCkRoHM8VFo3foZjB99jNCpUxD70AMerXgTfdstsJw6hea330Xijx+HRDpynt8529phKfkakcuW9tm/gYg8Z+T8ZCEiugpBELDhy3PQhMixIlcvdjheteLC7MAO7h0YlPoWC05XtuPa6bEwbd4C40cfQ5OdhbjvPeTx0peyiHDobs2DrawcHQcOefTY/s58uAgQBIRls9EYkbcxGSAiuqDorBFnz5uw8pokhKqD+2l5Ukxo9+yA2eIUO5yA8cWRBiikAjJLdqFtx06EXzsfsd+612sbXMPm5EI9Pg2GDzbB1T5yeg+YCw5DOSoJysREsUMhCnpMBoiIADicbry/+xySYkIwb2rs1T8QBFbk6mG1u7GjiLMDA9FpdSL/RCPu7zgIW/4hRN14A6LvuN2ry3ckEgmi77oDbpsNLe9/4LXz+BNHUxNslZXcOEzkI0wGiIgA7DzcgJZ2O25fOAYy6chYo5wU2zU78EURZwcGYv+RWtx8bgdia89Ct/oWaG9e4ZP17MrEBEQtux7m/EJYiku8fj6xdRQcBgCEzeYSISJfYDJARCNeW4cdnx6qxfTUKGSMjRA7HJ+66cLswM4iVha6EkeHGWHvv4lxlnrE3HcPIpcs9un5I29YCnlcLJrfeQ9ue2A3v7sSQRBgzi+Aenwa5Lqhl2clooEL7kWxREQDsPmrGjhdAm67drTYofhcUmwoMsdrsbOoAUtmxUMT5HslhsLZ1o6qP/8N0eZmdNy0Bilzc30eg1ShQMxdd6D+r8+jdetn0K262ecx+IL9/Hk4GhoRsWSR2KGQl1itVrhcLq/NqtXU1MBisXj8uIIgAADUajVkQdYEb0A/9UtLS1FRUYFFixahvLwcEyZM8HZcREQ+cbGU6HWz4hGvVYsdjihW5Opx5KwROw83YOU1gd9YzZMcLS2o/+vzEIyt2Ja6DI8uv0a0WELSJyIsNxtt23cgLGs2lPrg21zbkV8IyGTQZGaKHQp5geNCR22NRuO1cygUCq8lGoIgwGw2IyQkJKgSgqsuE/ryyy/x4osv4qOPPoLZbMaf/vQn7NixwxexERF5lSAIeG9XNcJC5FgxJ7hLiV7J6LhQzEiLwhdHGtBp5d6Bi+x1dahb+yycHWb8K/F6jF+QKfp+Et1tt0AaEoLmt9+B4HaLGounCW43zAWHETopA7Iw790sknjsdjtUKpXYYQyZRCKBRqOB1WoVO5QerFYrXnvtNfzP//wPOjo68Oqrrw4qxqsmA1u3bsVvf/tbhISEIDIyEn/4wx/w6aefDitoIiJ/UHTGiNKaDqy8JgkhqpG9POamOUmw2Fz4778fx8onNuNnrx7DoeJmscMSja2yCnV/eQ4QBBTNWY2msHjM94MqU7KwMOhuy4OtvAKmrw6IHY5HWUvL4GprYxWhIBfoTeT8Mf7XX38dGo0GbW1tUCgU6OzsxCuvvDLgz181GZBKpQgNDe3+OiYmJqimRohoZHI43Xh/zzmMih05pUSvpLalExIJYLG7IAAwmOxYv71qRCYElq/PoO65dZCqQxD5g8ewq1aKnIxoaPykU3NYbg7UE8bD+OFmONvaxQ7HYzryCyBRKRE6farYoZCX+OON9FD42++jsrISd911F2QyGVQqFX74wx+isrJywJ+/ajIQFhaGysrK7t/43r17ERYWNuSAiYj8wY7D9d2lRKUjpJTolWzaW4ML++O62Z1ubNpbI05AIjEfO46G51+CPFqHxJ/8CAdqBTicAhbPjBM7tG7dvQccDhg2vi92OB4hOBzoLDqK0OnTPd7JmSjYSS/rdeJ2u3uNXclVH3N861vfwrPPPov6+np873vfg0KhwJNPPjn4SImI/ERbhx1bD9VhRloU0seMrFKi/TGY+i5X2d94sDDlF8C4eQtcBiOkGg3cZjNUycmI/8EjgDoEXx6twMQx4UiKCb36wXxImRCPqGXXo/WTrejMzUHo5ElihzQsnaeL4bZYEJbF3gLUt0u/V2U6LbSrbkZ4dpbYYfmFjIwMrF+/Hna7HUePHsW2bdswefLkAX/+qsnAqFGjsHbtWtTW1sLtdkOv10Mu94+pUiKiodi070Ip0QUjr5Rof3Thyj5v/CNCg/fnvSm/AC1vvwPB3lXhxG02AxIJwq6ZA5lGg8NfG2DscOCuJWNFjrRvUcuuh7nwMFre2QD1L/87oJ+omwsKIQ0LQ0hGutihkB+6/HvVZTCi5e13AIAJAYB77rkHmzZtQmhoKN59911Mnz4dt91224A/3+9P+Y8//rjP8ePHjwMAbrrppkGGSkQkvqoGMw6casZ1sxMQN0JLifYlb34S1m+vgt3Zs0JNe6cTnxyoxfKcxKBbTmXcvKX75qKbIKB16zZEzJuLnUUNiIlUYWpKlCjxXY1EoUD03Xei/tm/ofWTrdDdskrskIbEbbGg8/hJhM3NhYR7EkcU08FD6Nh/8Krvs1ZUAs6elc4EuwPN//wXOvbt7zEukUi6ewIAQNjcXITn5gwonk8//RQbNmyATCZDZGQknnrqKcTF+c8Swf7I5XKsXr0aq1evHtrn+3uhurp6yEEREfkjQRCw4WIp0dzgq9E+HDkZMQC69g4YTXZow5W4MTcRZ86Z8NH+GhRXt+M7y8dBFxG4ZQEv5zIY+x2vajCjrLYDty8c7ddJUMiE8Qibk4u2HV8gLDsLyqTAK5FrPnYcgsOBMFYRov44+yl53N/4EJSWluLVV1/Fq6++iri4OGzcuBHr16/Hj3/8Y4+dw9OeeOKJK25m/vOf/zyg4/SbDDz66KODj4qIyI8dvlBK9J7rx474UqJ9ycmIQU5GDPR6PWprawEA86bGYlJyJN7ZWYXf/PMU7luajJnjdSJH6hkynbbPhECm6+rIrFJIMXdyjAiRDY7u1jx0njiJ5rffQeJPfgTJIDYO+gNzwWHIo3VQpYwTOxTysfDcnAE9ta/+f7/s93s18ceP9xhTKBTdzc0Go6ioCFlZWd0zAUN9yu5LDz74oEeOc9V/Dc+cOYNNmzbBarVCEAS43W40NjbipZde8kgARES+YHe48cHFUqJTWEp0oCQSCeZMjkGqPgz/92k5XvmoDPOmtmPNotFQKQJ7SYd21c1ofuttwOXqHpMoFVAvuxGFRQbMmxqLULX/J42yMA10q29B8z/+CdPerxBx7XyxQxowV3s7LMUliFx2vd+VayT/oV11c489A0DX96p21c0eO4dMJutxDdpsNjQ0NGDMmDEeO4enTZr0TeGAjo6O7kZjbrcb9fX1Az7OVR8fvPzyy5gwYQIsFgvmz5+PkJAQ5OQMbO0VEZG/2FHUVUp0DUuJDkmcVo2f3pmOG7IT8NWJJvx+/Wmca+wUO6xhCc/OgiJJD1x4ki7TaRF9z13IV4yG0yVgUab/rxW+KCw7C+qJE2DY9BGcbW1ihzNgHYePAILAJUJ0ReHZWYi+5y7IdFoA33yvenLzcGZmJg4fPoyWlhYAwJYtWwbVuEtM7733Hh5++GE89thjePzxx/HYY4/hzTffHPDnr/rIQyKRIC8vDyaTCXq9Hj/+8Y/xi1/8YlhBExH5UmuHHdsulBKdyFKiQyaXSXHL/NFIHxOJN7aW4w//Oo1b5o/CkpnxAflUVxAEuAxGhGXNRuy37wMAOF1u7P77cUxOjkSCLkTkCAdOIpEg5u47UPObZ2DY8D7iHv6O2CENiLmgEMokPZR67uGhKwvPzvJq5aCUlBQ88sgj3eXzo6OjA6aU/p49e/Diiy/izTffxH333YdTp06hqKhowJ+/ajKgVndV24iPj8e5c+eQnp4Ot9t9lU/1b+fOndi2bVv3142NjViwYAGysrLw1ltvwW63Y+7cubjzzjsBdHVVe+WVV9DZ2YmMjAw8/PDD7IBMRIOyaV8NXG4Bq69lKVFPyBgbgV/ePxlvflaJf395DsVV7fjWsnGI0CjEDm1QnI1NcHd0QJWW0j12+IwR7WYHFi+LFzGyoVHExSFy+TK0bvkEnSdOInTqFLFDuiJHUxNsFZXQ5q0UOxQiAMD111+P66+/XuwwBi0iIgJarRajRo1CVVUVFixYgE8//XTAn7/qMqG0tDQ8++yzmDJlCrZs2YK33nprUF3NLrdkyRKsXbsWa9euxQ9/+ENERkZi1apVeOmll/Dkk0/i2WefRVlZGY4cOQIAWLduHR544AH89a9/hSAI2Llz55DPTUQjT2V9VynRxTPjERvFUqKeEhaqwKN5abhz8RiUVLfjN2+dxKnKwFmeAgDWsjIAgDo1FUDXTMEXRQ2I16oxKTkwZ5Cill4HRUICWt79N9w2m9jhXFFHwWEAYKMxomGSy+Wor6+HXq9HcXExXC4XzGbzgD9/1bv6b3/721ixYgX0ej2+/e1vQxAEPP7441f72IC89tpruOuuu9DY2IjExETExcVBJpNh/vz5OHDgAJqammC32zFhwgQAwMKFC3HgwAGPnJuIgt/FUqLhoXLcmBN4JRf9nUQiwaLMePz3vZMQFqLA394/g39/WQ2Hc+izx75kLS2HVKOBIqFrFqCizozKejMWZcZBGoDLngBAIpcj5u474DQY0PrxVrHD6ZcgCDAXFEKVlgq5LjiqUxGJJS8vD6+++ipmzpyJ/Px8fP/73/dsB2Kj0Yg9e/ZgwoQJSEhIwI4dOxAaOvy27MePH4fdbsecOXOwb98+REVFdb8WFRUFg8EAo9HYY1yr1cJgMPQ6ltls7jMDCoRGEUTkPYVfG1BW24H7rk9GiIrLC70lKSYUP7tnEt7fcw47Djfg63MmPLQixe/X3FvLyqBOTene7/BFUQPUShnmBEA50StRj09D2DVz0PbFLmiyZ0M1epTYIfViP18DR30Dou9aKHYoRAFv1qxZmDRpEtRqNf70pz+huroaaWlpA/78VZOBF154AbNmdU3hxcTEYPLkyXjppZfws5/9bOhRA9ixYwdWrFjR7+uXd5C7dPxyn3zyCTZu3NhrfMOGDdDrxXsaKOa5Kfjx+roym8OFza+fxDh9BG5bOg0yVhAalKFcX0/cNwrzMuvw1/eO4vdvF+PhVVOxNGeMX24utre2oqKxCaNuXA69Xo+WNguKzhpx07wUpCQH/t6S2O9/D0dOnkb7vz/AtD/+zv86+54uhkQmQ+qNy6GICBc7GvKRmpoaKBTe31vk7XOEhIT41b/B+/fvx7vvvou//e1vaGlpwR//+Ec88sgjmD17YFW6rpoMtLe348YbbwQAKJVKrFixArt37x5W0E6nE6dPn+5ubKbT6dB2SSm01tZWaLVa6HQ6tLa2do8bjUZotdpex1uxYgUWLlzY57kuNs7xtUub9hB5Gq+vq/vkYC2ajBbcd/0YNNTXiR1OQBnO9TVaB/y/ezPwxrZyPP/vo9h/rAr3Xp8MjZ/V6zcfOQoAsMXGoLa2Fpv2nYfbLSBrfGjQfG9F3ZqHpjfexNfvbUDEwmvFDqdbYkICGr7cA/WkDDR1mIAOk9ghkY9YLBavPxwYatOxwbBYLH3+nBArQfjwww/xq1/9qjuGP/zhD1i7dq3nkgG32w2DwQDdhTV9ra2tfT6xH4yqqiokJiZ2VypKS0tDbW0t6uvrERcXh3379mHRokWIjY2FUqlESUkJ0tPTsXv3bmRmZvY6nkajgUajGVZMRBQ8LpYSzRyvxcTRgbkRNJBpw5X4z9UTsb2gHpu/qkFF3Sk8eGMKxo/ynyfA1tIySBQKHOsMxYevHoPRZIdCLkF5XUfQbDTXZM1Cx8FDMGz+GKEzpkN+ybJbMbWfLoartRVht64SOxQiUfRXWfPSjsLl5eX4+9//DqfTiejoaDz22GP93uu63W5ER0d3fx0TEzOoyp9XTQZWrFiBJ598EjNmzAAAnDhxAvfdd9+AT9CXhoaGHkErlUo8+uij+Mtf/gK73Y7MzEzk5uYCAB577DG88sorsFqtSE5OxvLly4d1biIKfpv2nYdbEHDbAv9bKz1SSCUS3JCdiPQx4Xjtk3L8ZUMJbszRY8UcvV8s2bKWlcMWp8f6nedhv7Dh2eEUsH57FQAgJyOw9w0AXctqo+9ag5rfPIOWDe8j/rsPXv1DXmTKL4Bx8xa4DEYAgNtuFzUeIrEsWbIES5YsAQCcO3cOa9euxe23397jPf/4xz+wZs0aZGZm4q233sKWLVu6y+5fLiIiAp9//jkWL14MiUSCL7/8ssee26u5ajKwePFipKam4sSJE5DJZFi5cuWwWzPPnTsXc+fO7TE2depUrF27ttd7k5OT8cwzzwzrfEQ0clTWd+DAqRYsy0oImie8gSw5IQw/v28y3tlZhU8O1qKkuh3fuTEFMZEqUeJxutyoq2uDo/ocjkRPhT2k59Mzu9ONTXtrgiIZAABFbCyibrwBxs1b0Hn8BEKnTRUlDlN+AVrefgeC/ZvlG4YNGyFRKLzaSIpoqHbv3o0PP/wQzz333KA+19jY2GvsSitYLlbWjIjoOYvtdrthsVgAADabDWFhYf2e87vf/S6ee+45vP766wC6Gqg99thjA45ZIgxgzU9DQwPi4+Nx8OBBnD9/HjfeeKNHKgoRERH5Wuux4zj1y19j0q9+Du3M3ktPg43b4cCxH/8Uzk4LZj7/HGQhvq/yVPjQ92Brau41roqNwezXXvF5PCSOmpoaKJXKIX32wKkmfLC7Gi3tNkRHqHDrtWMwZ3KshyP8xq5du/D+++/j+eef7/Wa3W5HUlJSn59bs2ZNr7HVq1f3OX78+HG88847fT70PnPmDH77299CrVZDpVLh97//PcLDr7zUsqOjAzKZDCGD/B6/ajLw6quvAgBuvPFG/OY3v8H06dNhsVjwxBNPDOpEYuEGYgpGvL76VlDSgtc+Kcd9S5Mxb6r3/pEIdt68vprbbHjtkzJU1JkxZ3IM7lw8Bmrl8CrdmDodqG22oKbZgprmTtQ0W1DbbIHN8c1T/+gIJfQxIUiKCcX4skPQ5O/GG1PvQ0Nn7+PpwpV45rvThxWTv7GWlaPuz88iYskiRK++1WvnEQQBrtZW2Ovq4airu/DfetjKK/r9zLiX1nktHvIvnZ2dQ3qYfKi4Geu3V3Uv6QMApVyKe5eO7TWLN5wNxK+//jp27tyJiIgIJCUlobm5uc+Zgf5+H3q9flAzA//7v/+L7OxszJs3r8e43W7HU089hUcffRRpaWn4+OOPceLEiX4redbU1KCkpASLFy/Gn//8Z1RVVeGRRx7BlCkD60J+1WVC5eXl+P3vf49Nmzbh2muvxd133z3ssqJERJ5md7jx/p7zGB0birkBXic+mMVEqvDTO9Lx8cFabD1Yh7JaE3IzorHvRDMMJjt04UrkzU/qc5mO3eFCbcvFm34Lapu6bv7bO53d79Go5UiKDcHcKTHdN//66JAefSbqijbBnaTHioXj+rzByJvf9xO/QKZOTUH4/GvQ/sWXCMvOgmrM8MqnCoIAl9EIe20dHPX1XTf9tfWw19dDsFq73ycNC4MyMQESlQpCHx2RZbreFQJp5Dhwqhn7T/aeMbpceV0HnK6ez67tTjfe+qwS+473/PzlpennTokZUO+Qffv2Yc+ePfj73/8OlUqFn//85wP8XfQ00B5Xl1fWvFR1dTWUSmV3r4DrrrsO7733Xr/HevXVV3Hdddfh8OHDaG9vx/e//33861//wu9+97sBxXLVZEAQBEilUpw4cQK33HILAMB6yTc6EZE/+LywHkaTHd9ZPg5SP9igSv2TyaRYdc0oZIyJwEubz+Kj/d/MQhhMdqzfXoVWkwMxkarup/21zRY0tdpw8Z94hVyCxOgQTB4XhaSYkO5fERrFFUsXCi4XbBUVCMvN6U44Nu2tuWoiEgy0q1ai89hxNLzyGnDhZl6m00K76uZ+1+0LbjecRiMctRee8tfXX0gAGnrc3MsiwqFISEB4bjYUCQlQJCZAmZgA2YVlDX3tGZAoFdCuutm7v2kKCpcnAlcbH4qioiIsWLCg+4n/8uXL8cEHH3js+Je7vLLmpRISEtDS0oLa2lro9XoUFhYiNTW132M5HA7Mnz8fr7/+OubMmYPJkyfD5XINOJarJgPx8fF45pln0NDQgEmTJuFvf/sbxo4dO+ATEBF5m9Fkx7b8Oswcr8UElhINGBNGR0ClkKHT1nsT7wd7zwMAJBIgLkqNUXGhyM6IRlJs19P+2EjVkJI++/kaCDY71Bf+Yc3JiAnam//LyTShCM2cAdPuvd1jLoMRLW+/A7gFqFNTeiztsddduOm/pOqPLDICisREhM/NvXDDnwhFQgJkYVcu730x2TBu3gKXsRUybdQVkxAaGeZMHthT+5+9egwGU+/qU7pwJZ64I73H2HCWCV06oyDzcqO+yytrAsAzzzyDNWvWIDU1FY8++iieffZZCIKAyMjIPmcQLnI4HGhtbUVRURGeeuoptLa2wj6Ial1XTQYeffRR5OfnIz09HXK5HOnp6bj2Wv9pXkJEdLGU6K0sJRpwjB39/6P9/+6dhARdCJQKqcfOZy0rBwCo01I8dsxA0nniZK8xwe5A85v/7DEmi4qCMjEB6nlze970a4ZePCQ8Owvh2Vnc80SDljc/yetL+rKzs/Hiiy/ijjvuQGhoKD7//HOPHbsvfVXWvHQZfmZmZp+9tfpy/fXX4z/+4z8wZ84cjBo1Ct///vdx2223DTiWqyYDarUaCxYs6P566dKlAz44EZG3VdR14ODpFtyQzVKigUgXruz3id+YeM83k7SWlUGu00HeRzf7keBijf++xNx3NxQJXct7pCJUHCLqjy+W9OXm5qKiogLf+973EB4ejtTUVLS2tnrs+N60dOlSXHfddZBKux6c/OlPf7pq5aFL+Vd/eCKiQRAEARt2VSMiVI7lOeK0gafh8cUTv4sEQYCttBzq9IkeP3agkOm0fSYEMp0W4XPniBAR0cD4YknfXXfdhbvuusur5/CWi4kAgEElAgDgublXIiIfKygxoLzOjLx5o4ZdnpLEkZMRg3uXjoUuvKv2uC5c2We5QE9wNjfD1d4+YpcIAYB21c2QKBU9xriRl2hk48wAEQUku8OFD/aex+i40AFtQCP/5atNvNbSMgDo3jw8EvXYyGu4ejUhIgp+/SYDv/71r6/4wV/96lceD4aIaKC2XywlemMKS4nSgFhLyyENDYUiIV7sUER1cSMvEQWHlpYWfPjhh3jooYdQW1uL9evX47vf/S6ioqIG9Pl+lwktW7YMy5Ytg1arhUqlwvLly7FixQqEh4cjISHBU/ETEQ2a0WTHZ/n1mDlBiwmjBrc2kkYuW1kZVKkpkEi5QpZIDJeW7gxk/vb7ePHFF6HXd+2bi4mJweTJk/HSSy8N+PP9zgzk5uYCALZs2YLf/OY33RsTZs6cOeSubEREnnCxlOhtC4bXRZVGDpfJBEdDI8Lm5IodCtGIJgjCFRsD+jt/SwQAoL29HTfeeCMAQKlUYsWKFdi9e/eAP3/VxyPt7e09mjdYrVZ0dHQMIVQiouG7WEr0ulkJiIlUiR0OBYhv+guM3P0CRGJTKpWwXdK5OtAIggCz2dxn12Axud1uGAyG7q9bW1sHlbRcdQPxvHnz8N///d/IycmBIAg4ePAgrrvuuqFFS0Q0DIIg4L1d1YjQKLA8J1HscCiAWMvKIZHLoRrD2SQisSgUCrhcLpjNZq/NDoSEhMBisXj8uBdvrkNCQrzenXiwVqxYgSeffBIzZswAAJw4cQL33XffgD9/1WTgjjvuQEpKCk6cOAGJRIL7779/wB3RiIg8qaDEgIo6M+5flsxSojQottJyKMeOgUShuPqbichrvP1UfSR2uF68eDFSU1Nx4sQJyGQyrFy5EmPGjBnw5wdUWjQrKwtZWaw8QETisTtc+GDPOYxhKVEaJLfdDlt1NSKvXyJ2KEREXjF27FiMHTt2SJ9lnwEi8muHipu7W9ADwJwpMZAG8OYz8j1bZRXgdkOdOnKbjRER9Yf11YjIbx0qbsb67VXdiQAA7ChswKHiZhGjokBjLS0DJBKoUpgMEBFdjskAEfmtTXtrYHe6e4zZnW5s2lsjUkQUiGxl5VDoEyHThIodChGR32EyQER+69IZgYGME11OcLthLa/gEiEion4wGSAiv6ULVw5qnOhy9poaCFYr1KnsL0BE1BcmA0Tkt+ZMju41ppRLkTc/SYRoKBBZSy82G+PMABFRX1hNiIj8kiAIOHu+A2qFBCFqOYwmB3ThSuTNT0JOBkuL0sDYysog02oh1+nEDoWIyC8xGSAiv1Rc1Y4z5024Y9EYLJ4ZL3Y4FIAEQYC1tBzq8Wlih0JE5Le4TIiI/I4gCNj8VQ104UrMnxYrdjgUoJwtLXC1tXGJEBHRFTAZICK/c6ysFZX1Ztw0Rw+FnD+maGisZRf2C3DzMBFRv/ivLBH5FfeFWYF4rRq5k7k3gIbOVloOaUgIFPpEsUMhIvJbTAaIyK8UlhhQ22zBzXP1kEklYodDAcxaVgZVyjhIpPynjoioP/wJSUR+w+VyY8v+GoyKDcGsiaz+QkPn6jDDUVfPZmNERFfBZICI/MaBUy1obLVh5dwkSCWcFaChs5Vf7C/A/QJERFfCZICI/ILD6cbHB2uRnKDBtNQoscOhAGctKwfkciiTx4odChGRX2MyQER+Ye/xJhhNduTNS4KEswI0TNbSMqjGjIZUoRA7FCIiv8ZkgIhEZ3O48OmhWkwYHY70MRFih0MBzm23w1ZVzSVCREQDwGSAiES3q6gRpk4n8q7hrAANn62qGnC5uHmYiGgAmAwQkag6rU58VliHqSmRSE0KFzscCgK20jIAgCqFyQAR0dUwGSAiUX1+uB6dVhdWXTNK7FAoSFjLyqFITIAsTCN2KEREfo/JABGJxtTpwM7DDZg1QYvRcaFih0NBQHC7YSuvgDqV+wWIiAaCyQARiWZbfh3sTjdWzk0SOxQKEo7aOrgtFqjSuESIiGggmAwQkSiMJju+PNqI3EnRSIgOETscChLWsq79Atw8TEQ0MEwGiEgUnx6qhSAAN83hrAB5jrW0HLLISMijo8UOhYgoIDAZICKfa2q1Yt+JZsybGoOYSJXY4VAQsZaVQ52WwhK1REQDxGSAiHzu4wO1kEmBG3P1YodCQcRpMMBlNLLZGBHRIDAZICKfqm2x4FBxCxbOiEdUmFLscCiIWEvLAQAqVhIiIhowJgNE5FNbvqqBSiHFDVkJYodCQcZaVgaJWg1lEmeciIgGiskAEflMdYMZRWeNWDIzAWGhCrHDoSBjLS2DOmUcJFL+00ZENFD8iUlEPrP5qxqEqmW4fna82KFQkHGZO+GorYOKJUWJiAaFyQAR+URpjQknK9qwLCsRISq52OFQkLGVd+0X4OZhIqLBYTJARF4nCAI276tBRKgcizLjxA6HgpC1rByQSqFKHit2KEREAYXJABF5XXFVO86cN2F5jh4qhUzscCgIWUvLoBozBlIlK1QREQ0GkwEi8ipBELD5qxrowpWYPy1W7HAoCLkdDtiqqqFK434BIqLBYjJARF51rKwVlfVmrJijh0LOHznkefbqc4DTCTU3DxMRDRr/ZSYir3FfmBWI06owZ3KM2OFQkLKWlgEAkwEioiFgMkBEXlNYYkBtswUr5yZBJpWIHQ4FKWtZORTxcZCFh4sdChFRwGEyQERe4XK5sWV/DUbFhmDWRJ3Y4VCQEtxu2MrKoWJJUSKiIWEyQEReceBUCxpbbVg5NwlSCWcFyDsc9Q1wd3ZCncpkgIhoKJgMEJHHOZxufHywFskJGkxLjRI7HApi1rIL+wVYSYiIaEiYDBCRx+093gSjyY68eUmQcFaAvMhaWgZZRATkMdygTkQ0FHIxTlpYWIh///vfsNlsmD59Oh544AEcP34cb731Fux2O+bOnYs777wTAFBZWYlXXnkFnZ2dyMjIwMMPPwyZjE2LiPyVzeHCp4dqMWF0ONLHRIgdDgU5W2k5VGkpTDqJiIbI5zMDDQ0N+Pvf/44nn3wSf/7zn1FRUYEjR47gpZdewpNPPolnn30WZWVlOHLkCABg3bp1eOCBB/DXv/4VgiBg586dvg6ZiAZhV1EjTJ1O5F3DWQHyLqfBCKfBwP0CRETD4PNkID8/H3PnzkV0dDTkcjn+8z//EyqVComJiYiLi4NMJsP8+fNx4MABNDU1wW63Y8KECQCAhQsX4sCBA72OaTab0djY2OsXEflWp9WJzwrrMGVcJFKTWOaRvMtaVg6A/QWIiIbD58uE6uvrIZfL8bvf/Q6tra2YNWsWRo0ahaioqO73REVFwWAwwGg09hjXarUwGAy9jvnJJ59g48aNvcY3bNgAvV7vjd/GgIh5bgpOXx4+h7e2FqPZWIAYbQjuX56BhbNGix1Wt/Vbi9FpdeGhvBnQ66PEDoeGIRB+fpXVfwKpWo3k7CxIuHw0oATC9UWBy9+vr507d2Lbtm3dXzc2NmLBggV48MEHu8dqa2vx6quvwmw2IyoqCo8//jjCwsK8Eo/PkwGXy4Xi4mI8/fTTUKvV+NOf/gSlUtnrfRKJBIIg9Dl+uRUrVmDhwoV9nq+2tnbYMQ+FXq8X7dwUnA4VN2P99irYnW4AQJPRgnUbjsLYakROhvibJ02dDmzaXYpZE7QIkXaitrZT7JBoiALl55fh+Akok8eirqFB7FBoEALl+qLAJOb1NdAkZMmSJViyZAkA4Ny5c1i7di1uv/327tcFQcAf//hHPPDAA5gxYwbefvttbNq0Cffee69X4vZ5MhAVFYWpU6ciIqJrY2FWVhYOHjwIqfSbFUutra3QarXQ6XRobW3tHjcajdBqtb2OqdFooNFovB47kZg27a3pTgQusjvd2LS3xi+SgW35dbA73Vg5N0nsUGgEcFsssNfUIurGG8QOhYioW1/L1K90n/raa6/hrrvu6r4vBoCKigqo1WrMmDEDAHDLLbegs9N7D9h8ngzMmjULL7zwAsxmM0JCQnDkyBHk5ORg8+bNqK+vR1xcHPbt24dFixYhNjYWSqUSJSUlSE9Px+7du5GZmTmo83GZEAWLN5/27+vp8bv1ePxusaMgT/H3n1/GoiOAICApJxtRfh4r9ebv1xcFNjGvrx/84Ae9xlavXo01a9b0Gj9+/DjsdjvmzJnTY7y+vh5RUVF4/vnnUVlZiTFjxuA73/mO12L2eTIwfvx4rFy5Er/85S/hdDoxbdo0LF26FElJSfjLX/4Cu92OzMxM5ObmAgAee+wxvPLKK7BarUhOTsby5csHdT5fTxWZ8gtg3LwFLmMrZNooaFfdjPDsLJ/GQMHpZ68eg8Fk7/O10bGhuGmOHtPTokSp4PP2jkp8daIZ//OdqYiJVPn8/ORZgbCMw3CoAJBK0RERjk4/j5V6CoTriwKX2MuEnn/++V7j/c0K7NixAytWrOg17nK5cOrUKfz6179Gamoq3n33Xbz55pv4j//4D4/HDIjUZ2Dx4sVYvHhxj7GpU6di7dq1vd6bnJyMZ555xlehDYspvwAtb78Dwe4AALgMRrS8/Q4AMCGgYcscH4WdRT2nH5VyKXIn6VBSbcJLH5VidNyFpCDVd0lBU6sV+040Y/7UGCYC5DO2sjIoR4+CVMVrjoj8R1xc3IDe53Q6cfr0aTz66KO9XouKikJiYiJSL5RNnjdvHv7yl794NM5LiZIMBCvj5i3dicBFgt0B4+YtTAZoWARBQHmdGWEhMijlMhhNdmjDlcibn4ScjBi43ALyi1vwycFavLS5FGPiQnHT3CRMS4n0elLw8YFayKTAjbmc9g90F2c2K/x8ZlNwOmGrrEL4gnlih0JENCRVVVVITEyEWq3u9drEiRPR3t6OyspKJCcno7CwECkp3iuhzGTAg1wG46DGiQbqbE0HKurMuHvJWFw7I67XNKhMKsGcyTHIzojGodNdScGLm85iTHwobp6ThKleSgpqWyw4VNyC62bGIyqsd1UwChyBNLNpqz4HweFgfwEiClgNDQ2Ijo7uMfbMM89gzZo1SE1NxU9+8hO88sorsNlsiI6O7nMvgqcwGfAgmU7b542/TNe7AhLRYGwvqEN4iBxzJl+5apBMKsHcKTHIydDhYHELPj1Yhxc2ncXY+FDcPDcJU8Z5NinY8lUNlHIpbshO9NgxSRyBNLNpLS0DwGZjRBS45s6di7lz5/YY+9nPftb9/+PHj/fZMnmfdyAOZtpVN0OiVPQYkygV0K66WaSIKBjUNHfiRHkbFs2Mh1IxsG9ZmUyKa6bE4n8emIL7lyajw+LE8x+exR/+VYyTFa199vAYrOoGM4rOGnHdrASEhSqu/gHya4E0s2krK4c8LhayS0rxERHR0HBmwIMuPj0zbt7S9Q+oTIboe+7yu6dqFFi2F9RDKZdi4fSBbUq6lEwmxTVTY5E7KRoHTrXg00O1WPfBWYxL1OCmOUmYnBwx5JmCzV/VIFQtw/Wz44f0efIvgTKzKbjdsJaVI3TaVLFDISIKCpwZ8LDw7CyM+d3/YNxD3wFcLqiS2ICJhs7QbkN+iQHzpsVCEzL03F0mk2LetFj8z3em4t7rk9HW4cC6D87gj+8U41Rl26BnCkprTDhZ0YZlWYkIUfGZQjCIXLK496BM5nczm46GRrjNZqjTuESIiMgTmAx4Sey18wGZDKaDh8QOhQLYjqIGQBBw/SzPPH2Xy6SYPy0Wv3lwKu65fizaOhz42/tn8Kd3inF6gEmBIAjYvK8GEaFyLMoc/GwF+SdbVTUgkUAWGQlIJIBcBkilCJk4QezQerCWXdwvkCpyJEREwYHJgJcoIiIQOmUyzPkFEFwuscOhAGS2OrHveBOy0qOhi/BsLXW5TIoF0+LwP9+ZiruvGwtjhwN/ff8M1r5bguKqKycFxVXtOHPehOU5eqgUMo/GReKwVVXDnF+AyKXXYcwffotrNm1E0v/7GSQAWv71nkf2mHiKrbQc0rAwyONixQ6FiCgoMBnworA5OXC1m2A5XSx2KBSAdh9rhM3hxtKsBK+dQyGX4trpcfjNd6bi7iVjYWi34bmNZ/Dn90pQXNXe6yZQEARs/qoGunAl5k/jzVgwEAQBhvc/hDQsDFHLru8eVybEQ7tyBTqPn4A5v1DECHuylpVDnZYiSqdtIqJgxMW+XhQ6ZTKkYWEwHTyE0KlTxA6HAojd4cYXRQ2YMi4So2JDvX4+hVyKa2fEYe6UGOw70YRt+XV4buPXSEsKw8q5SWg127Fpbw0MJjsA4JopMVDI+SwhGHQeOw7r2VJE37kG0pCQHq9FLF4E85FjaNmwEer0CZBHRooUZRdnaxuczc2IuHa+qHEQEQUT/mvuRRKZDGFZs9F5/CRcZrPY4VAAOXi6GaZOp1dnBfqikEuxKDMev31wGu5cPAbNbTb877+/xhtbK7oTAQAoKDHgUHGzT2MjzxOcThg+2AxFQgLC583t9bpEKkXs/fdCcDjQ8va7oi8XspWVAwDUadwvQETkKUwGvCxsTg7gdMJceFjsUChAuN0CPi+sR3KCBhNGhYsSw6VJQahKhsvvAe1ONzbtrRElNvKc9j374Gxqgu7WVZDI+t7/oYiPg3bVTeg8cRId+QU+jrAna1kZJEollKNHiRoHEVEwYTLgZarRo6BM0sN0gFWFaGCOlBrR2GrDsqwE0ddFK+RSdNr63gB/6UwBBR6XuROtn26FOn0iQqZMvuJ7IxYthCo1BYb3NsLZ2uabAPtgLS2Halxyv4kLERENHpMBHwibkwN7VTXsdXVih0J+ThAEbC+oR1yUCjPS/KPZky5cOahxCgytW7fB3WmB7ra8qyadXcuF7oHgdKL57XdEWS7ktlhgP38e6lT2FyAi8iQmAz4QljUbkErRcTBf7FDIz505b0JlvRnXz06AVOof1VLy5idBedlmYaVcirz5bKgXqBxNTWj/cg/C5uRANWpgS24UcXHQrroZlpOnRPlZZq2oBASB+wWIiDyMyYAPyCIiEDp5EjoOFUBwu8UOh/zY9oJ6hIfKkTspRuxQuuVkxODepWO7ZwJ04Urcu3QscjL8J0YaHMOHH0Eik0F7802D+lzEomu7lgv9+304W1u9E1w/bGXlgEQC1bhkn56XiCjYsbSoj4Tl5qDzxElYiksQOnmS2OGQHzrf1ImTFW1YNS8JSoV/5ek5GTG8+Q8S1tIydB45iqgVyyGPGlyp0IvVhWp++wya334H8Y8+4rN9LdbSMihHjYJUrfbJ+YiIRgr/uuMIYqFTJ0OqCUXHQW4kpr5tL6iHStHVBIzIGwS3G4b3P4QsMhKR1y8Z0jEUcbHQ5q2E5eRpn/08E1wu2CoqoU7jfgEiIk9jMuAjEoUCmtmz0Hn0OFydnWKHQ36mpd2GgpIWzJsWC42aE3bkHebDRbBVVkG76iZIVaohHydi4QKo0lJh+PcHcBqNHoywb/Zz5yA4HFCncr8AEZGnMRnwofA5uRCcTpgPHxE7FPIzOw43ABIJrpsZL3YoFKTcdjsMmz6CctQohOVkD+tY3dWFXC40r/d+dSFraVezMRUrCREReRyTAR9SjhkNRWIClwpRDx0WJ/Ydb0J2ug66iKE/rSW6kvZdX8JlMHaVEpUO/0e/IvbCcqHTxeg4cNADEfbPWlYGeUzMoPc4EBHR1TEZ8CGJRIKw3BzYyivgaGgUOxzyE7uPNcLudGNpVoLYoVCQcrWb0Lrtc4RMnYKQ9IkeO27EtfOhHp+Gln9/AKfBO8uFBEGAtbSc/QWIiLyEyYCPheVkARIJTJwdIAB2hxu7ihowNSUSSTGhYodDQcr4yacQ7Hbobl3l0eNKpFLE3HcP4HZ7rRmZs7EJ7o4O9hcgIvISJgM+Jo+MRMikDHQcymfPAcKBU80wWZxYmpUodigUpOx19TDt24/w+ddAmeD52SdFbAx0t1xYLrTf88uFrGVlAAAVKwkREXkFkwERhOVmw2VshfXrM2KHQiJyuwVsL6zHuEQNxieFiR0OBSnDB5sgUSqhXbHca+cIXzAf6gnj0bLxAzgNBo8e21paDqlGA0U8N9cTEXkDkwERhE6fBmlICEwH88UOhURUdNaI5jYblmUl+qxxE40sluISWE6eQtTyZZCFh3vtPBKpFDH33g0IbjR5uLqQtbQM6rQUfo8QEXkJkwERSBUKaGbPROeRo3BbLGKHQyIQBAGfFdQhXqvG9NQoscOhIHSxwZhcp0PEomu9fr6u5UKrYC0ugemr/R45prOtHc6mJvYXICLyIiYDIgnLzYHgcMBcdFTsUEgEX58zobqhE9fPToBUyiee5HkdBw/BXlMLbd5KSBUKn5wzfP48qCeMh+H9TR5ZLmQrY38BIiJvYzIgEtW4ZCji4lhVaIT6LL8OERoFcidFix0KBSG31QbjRx9DNS4ZmtkzfXberupCnlsuZC0rg0ShgGrMaA9FSEREl2MyIBKJRIKwOTmwlZbB0dQkdjjkQ+caO3G6qh1LMuOhkPNbkDyvbcdOuNraobvtFp+vtVfExEB3S17XcqF9w1suZC0rhyp5LCRyuYeiIyKiy/FOREQXew50cCPxiLK9oA5qpRQLpseKHQoFIWdrG9o+3wnNzEzRGnWFz78G6okTYHj/QzhahrZcyG21wX7uPFTcL0BE5FVMBkQk12qhTp+IjoPsOTBSNLfZUPi1AfOnxSFUzaed5HnGjz6G4HZDm7dStBi6lwsBaP7n20NaLmSrrATcbqjZX4CIyKuYDIgsPDcHToMB1tIysUMhH9hxuB4SiQRLZrJmOnme7dx5dBw8hIiFC6CIjRE1FkV0NHS35sH69RmY9n416M9bS8sAiQTqlHFeiI6IiC5iMiCy0BnTIFGr0XHA8507yb90dDqw70QzsjOioQ1Xih0OBRlBEGB4/0NIQ0MRtXyZ2OEAuLBcKH0iDB9sgqOlZVCftZaVQ5mkhzQkxEvRERERwGRAdFKlEppZmTAfOQq31SZ2OORFu442wuF0Y2lWgtihUBCynDwF69dnELViOWShoWKHA6CrUELMvXcDEgma//mvAS+HFFwu2CoqoE7jfgEiIm9jMuAHwnNzINjsMB85KnYo5CV2hwu7jjRiWkoU9NF80kmeJbhcMHywCYq4OEQsmCd2OD0oonWDXi5kP18DwWZnfwEiIh9gMuAHVKkpkMfGoIM9B4LWVyebYbY6sYyzAuQFpn1fwVHfAO2tqyCRycQOp5fweXOhzkiH4cNNcDQ3X/X91gvNxsSqhkRENJIwGfADEokEYbk5sJ45O+h1teT/XG4BnxfWI1UfhrRR4WKHQ0HGbbHA+PFWqMenIXTaVLHD6ZNEIkHsvXcBEumAlgtZS8sgj9ZBrtX6KEIiopGLyYCfCMvJBgB0HCoQORLytKIzBrS027lXgLyiddt2uM1m6Fbf6vMGY4Mh1+mguy0P1jNnYdq7r9/3CYIAW1kZ+wsQEfkIkwE/oYjWQT1hPDoOHhpSTW7yT4Ig4LOCeiTo1JiWGiV2OBRkHC0taPviS4RlZ0E1ZrTY4VxV+DVzEZKRDsMHm+Fo6nu5kLOpGa52E/sLEBH5CJMBPxI2JwfOpmbYLqyXpcBXXNWOc42dWDo7AVI/fmpLgcm46SNIJBJoV90kdigD0l1dSCrtakbWx3Iha1lXzxU1ZwaIiHyCyYAf0cyYAYlKCdMBbiQOFtsL6hGpUSA7I1rsUCjIWCsqYS4sQuR1iwNqbb1cp0X06lthPVsK0569vV63lpZDGhoKRQIb8xER+QKTAT8iVaugmZkJc9ERuO12scOhYapuMKO4uh1LZsZDIee3GnmOIAgwbPwAsohwRC69TuxwBi1sbi5CJmXA8OFHcDQ19Xita79ACiRSfs8QEfkCf9r6mbDcHAhWKzqPHhM7FBqmzwrqoVbKsGB6rNihUJDpLDoKW3kFtDffBKlaLXY4g9a1XOiuC8uFvqku5DKZ4GhoZElRIiIfYjLgZ9RpqZBH67hUKMA1tVpx+IwBC6bHIkQlFzscCiKCwwHDh5uhSNIjbG6u2OEMmVyrRfTtXcuF2nd3LRfq7i/AzsNERD7DZMDPSKRShOVkw/r1GTgNRrHDoSHacbgBUokES2Zy3TN5VvvuPXC2tEB3a17AL6UJm5OLkMmTYPxwMxyNTbCWlUMilwdEZSQiomAR2P+SBKmw3GxAENBxKF/sUGgITJ0OfHWyGbmTohEVphQ7HAoirg4zWj/9DCGTMhA6KUPscIZNIpEg5p47IQA4/5vfo33HFxAAdBw5KnJkREQjB5MBP6SIjYUqLRUdB/PZcyAA7TrSCIfTjaWz2WSMPKv1061wW63Q3XaL2KF4jOVsKeB2A05n14DTiZa334Epnw0YiYh8gcmAnwqfkwNHYyNsFZVih0KDYHO48OXRBkxPjUJCdIjY4VAQcTQ0on33XoTPmwulPlHscDzGuHkL4HL1GBPsjq5xIiLyOiYDfkqTOQMShQIdB7mROJB8daIZZqsLy7I4K0CeZfhwEyQKBbQ33Sh2KB7l6mdvVH/jRETkWUwG/JQ0JAShmTNgLixiz4EA4XK58XlhPdKSwpCaFC52OBRELGfOovPYCUQtux6yiAixw/Eoma7vhmn9jRMRkWcxGfBj4bnZcFss6Dx+QuxQaAAOnzHCYLJjaVbwLOEg8QluNwwbP4RMq0XEkkVih+Nx2lU3Q6JU9BiTKBXQrrpZpIiIiEYWFkD3Y+qJEyDTatFx4BDCZs8SOxy/c6i4GZv21sBgskMXrkTe/CTkZMSIEosgCPisoA6J0WpMTYkUJQYKTh0FhbCfO4fYb98PqTL4qlOFZ2cB6No74DIYIdNpoV11c/c4ERF5F5MBP3ax50DbZ9vhbG2DPIo3mRcdKm7G+u1VsDu7OpcaTHas314FAKIkBKer2nG+yYJvLRsHqUTi8/NTcHLb7TBu3gLl2DHQZAXvA4Hw7Cze/BMRiYTLhPxc+MWeAyyz18OmvTXdicBFdqcbG3adg8Xm9Hk8nxXUISpMgewMnc/PTcGrbccXcBlbEX3bLQHfYIyIiPwTZwb8nCI+DqqUceg4eAiR1y+BhE+dAXTNBPSlw+LEj144grHxGmSMjUD6mAik6sOgkHvvRqqy3oyvq024bcEoyGW8YQsWpvwC0ZaumPILYPzwI7haWyFRKOAwGqH2yZmJiGikYTIQAMJyc9Dyr3dhr6qGKnms2OGIzuVyQy6TwOnq3ZAtPFSOBdPiUFLdjs/y67D1UB0UcglS9eFIHxOO9DERGBuvgVTquaRqe0EdQlQyzJ8W57FjkrhM+QVoefsdCHYHgK4yly3r34HbakPYrJldb5Kgd3IukXS9gG/+g0vfc+H/JZeOX/Z6R34hWv71LgRH17kFhwMtb78DAFxKQ0REHidKMvDrX/8abW1tkMlkAIDvfve7aGhowPvvvw+n04kVK1bghhtuAAAcP34cb731Fux2O+bOnYs777xTjJBFpZmVCcO/34fp4KERnwwIgoB/7ayG0yVAJpXA5f4mIVDKpbh94WjkZMRg5TVJsNhcOHvehJLqdpRUt2PTvhoANQhVyTBhdFdikD4mAgk69ZBnXBqNVhSdNWJZVgJCVDIP/S5JTIIgwPj+h92JQPe4wwHDO+/B8M57vo/pQhMuJgNERORpPk8GBEFAbW0tXnzxxe5kwGAw4LnnnsMf//hHyOVy/OIXv8CUKVMQFxeHl156Cb/+9a8RHR2NP/zhDzhy5AgyMzN9HbaoZKGhCJ0+FeaCw11rhxWKq38oSH1WUI99J5qwPCcRidHqK1YTClHJMC01CtNSowAA7WYHvj7XfiE5MOFoaSsAICpMgYmjIy4kB+HQRagGHM/nh+shk0qwODPek79N8jFBEOCoqUVH4WGYC4vgajf1+17d7bcBggDgQiLanY9+87UgXDZr1df7L3nPpe9v3fJJn+dlEy4iouCwc+dObNu2rfvrxsZGLFiwAA8++GCv9xYVFeH//u//8MILL3gtHp8nA7W1tQCA3//+92hvb8eSJUugVqsxZcoUhIWFAQBycnJw8OBBTJo0CYmJiYiL61p+MX/+fBw4cGDEJQMAEDYnF+bCInSeOAXNzBlihyOKgpIWfLj3PLLSdVh1TRIkEsmgKgdFaBTISo9GVno0AKCp1YqS6q6Zg9OVbThU3AIAiNequ5cUTRwdAU1I398m7WYH9p9sRu6kGESGBV/Jx5HA0diIjsIimAsPw1FXD0ilCEmfCLfVAre5s9f7ZTotIhcv9GpMpq/293njzyZcRETBYcmSJViyZAkA4Ny5c1i7di1uv/32Xu9rbW3FP//5T6/H4/NkwGw2Y+rUqXjooYdgt9vx61//GnPmzIFW+80/dFqtFqWlpTAYDIiKiuoej4qKgsFg6POYZrO51/jFJCIYhKRPhCwyEqaDh0ZkMlBaY8I/tlUgLSkM31o2ziMbqWOj1IiNUmP+tFi4BQG1zZbuJUUHT7dg97EmSACMjgtF+pgIZIyNQFpSGI6UGrtnJAAgTjvwmQQSn9NggPnwEXQUHIb93DlAIoE6LRURd66BZuYMyMLDe+0ZAHzXCEu76mbRzk1ERMPT2NjYa0yj0UCj0fT5/tdeew133XUXIvroLv/yyy9j9erV+Ne//uXxOC/l82RgwoQJmDBhAgBArVZj0aJFeOutt3Drrbf2eF9/N3t9jX/yySfYuHFjr/ENGzZAr9d7IOqh8fS5HUsWoWbTR4gJDYXykiRpJNDrgQVZE716jlFJQPb0q78veexo3LJkmldjGQgxr+1AY29tRctXB9C0dx9MxSUAgLDxadB/59uIuWYuVDHRPT+QtwqNWi2q//k2bM0tUMVEY8x99yDu2gXeD1bMc1+C1xd5E68v8iYxr68f/OAHvcZWr16NNWvW9Bo/fvw47HY75syZ0+u1Tz/9FCkpKRg/frxX4ryUz5OBkpISOBwOTJ06tXssNjYWra2t3V8bjUbodDrodDq0tbV1j7e2tvaYQbhoxYoVWLhwYZ/nu7gsydf0er3nzz1lMvDBJpR99DEir1vs2WP7qQ6LE3985zTMFheeujsDcVpxCizaHC6U1nTg1S2lsNrdvV7XhSvxzHcHkEl4iFeuryDjMnei8+gxdBQehvXrM4AgQJGkh3blTdDMnglFbCwAoMVuA/r6sxyfBv3//Kr7Syd8+PNEzHOD1xd5F68v8iYxry+9Xo/nn3++13h/swI7duzAihUreo1XV1fj0KFD+OUvf4mWlhaPx3k5UZYJbdiwAb/5zW/gcrmwe/duPPbYY1i3bh3a29uhUqlw6NAhfO9738OYMWNQW1uL+vp6xMXFYd++ff+/vTuPjqrM0wf+VN1KZamqpKqyQMKSsIVEgaQChLDZCMpiRKAVBJe2HduBZnT6zNhq97HbVqf7YDftmePR0aGlfz0isqMgY6utjCBrwpKwJYEETYCEbLWQSlVS272/PwLRmAQTUlU3qXo+5+RI3qq691v6Wtyn3ve+L+68885Ox7zZ8EsoUScPRmRaKuxHCxA7586Q33PA4xXx9u5yWJrc+LelY2ULAgAQGSHg9rS4LoMA0P2+BxRcYqsLztNn4Dh+As6SUsDngyoxAfr5c6GZNBHqlGS5SyQiohDW0ynqXq8XJSUlWL16dafHjh49CpvNhl/96lfwer2wWCx48cUX8corr/i7XAAyhIGJEyeivLwczz//PERRxLx585CRkYEVK1bg5ZdfhtfrxezZszF69GgAwOrVq/Haa6/B7XbDZDIhLy8v2CX3K9q8XJi3bIf7yhVEDhsmdzkBI0kSNnz2DSqqm/Gz/JEYPUQnd0kA2kYAurrwN+p4A7FcRI8HLedK2gLA6bOQPB4IBj1i7/wRtJMmQj18WMgHZyIiGliqqqqQnJyMqKjOX3QuW7asfVpRfX09Xn755YAFAUCmfQaWL1/eab+AGTNmYMaMGZ2eO378eKxduzZYpfV7mkkTYd7xIZqPFIR0GPjocDUKyyxYPGNI++o//cHimUOw8R9VcHu/HSFQq5RYPHOIjFWFtq52AtZOzEFL2Xk4jp+Ao/g0pNZWKLVaaKfmQTt5IiJHjoBCyd2giYiof6qrq0N8fMfrmzVr1mDZsmUYNWpUUGtRSJ0WxA4tIXXPwHV17/wVrRcqMHzNf0ChCr1NpA+dbcCGzyoxfVwCHp2b1u++1S0obbzp/gbBEC5zbrta1QdKJRARAbhcUEZHIyY7C9rJExGVPgYKgRu/+UO49C+SB/sXBZLc9wwMRKF3JRkGdHlT4DxZDOfZc9BkB++m1WAorWrCxs+rkJkai4fvSu13QQAApmQmBP3iP1xZd+/ptBMwRBEKSUTiqn9GzG0ZYb0JHxERUV9xHH0Air4tE0KsDs1HC+Uuxa9qzC1Yt6cCg41RWLlwFASB3TPcdbfrruT2QJM1nkGAiIioj3i1NQApBAGa3MlwnjkLn90udzl+cc3hwZsfXECESomnl4xBdCQHrcKZz+FEw4aN3T7O3XiJiIj8g2FggNLlTQFEEc3HTshdSp+5PT68tascdqcXTy0ZA2Msd/QNZ87TZ1D9H39Ac8ExRE8Y1+nbf+7GS0RE5D/8+nWAUg9JgXrYMDQfLUDc7Flyl3PLRFHCX//+NapqHfj5otFIHRT6+0VQ13wOB8zbdsJReAwRQ1Iw6OcrEZk6vMvVhHS5k+Uul4iIKCQwDAxg2rxcWLbvhPtKNdRDB+bSlju+uoziChsevHM4skZz6ke4chSfgnnzVviaHdDfMx/6BfPaV8rS5U7mxT8REVGAcJrQAKbNnQQIAuxHC+Qu5ZZ8WVSHvSfqMNuUhNk5g+Quh2Tgs9tRv/5vqF+3HkJsHFJ+9SwMC/NDcslcIiKi/oh/4w5gglaLmPG3w3HsOIxLFg2oNdZPX7Rh65eXkDVKj6WzhstdDsnAcaIIjVu2QWxpgX5hPvTz7h5QfZiIiCgUMAwMcNq8KXAWn0ZLSSlixo+Tu5weuVTnwPqPL2JYUgyeyB8JpbL/7SVAgeNrsqNx6zY4TxZDPXwYEn/yNNRDBuZGLURERAMdw8AAFzPudii1WtiPFgyIMGBpcuHND8uhiVLhqcVjEBnBb4LDhSRJcBw/AfPWHRBdLhgWL0TcXXM4GkBERCQjhoEBTiEI0E6ehKYDB+FzOCBo+u9qPC0uH978sBwuj4jnVmQgTquWuyQKEu+1Jpg3b4Xz1GlEpqUh4ScPQZ2cLHdZREREYY9hIARop05B05f74Dh+ArE/ukPucrrk84n4y/9W4KqlFU8vGYMhCTFyl0RBIEkSmguPwbJtJyS3G8YfL0bsnDuhUHLtAiIiov6AYSAERA4bCkGvh3n7BzBv2d7v1mKXJAmb9l5CSWUTHp2bhtvS4uQuiYLAa7OhcdNWtJw5i8iRI5Dw6MNQD+aqUURERP0Jw0AIsBceg89uB3w+AIDPYoX5/c0A0C8CwWfHanHwTAPm5yZjxvhEucuhAJMkCc1HCmDZ8QEkrxfGB36M2Dt/xNEAIiKifohhIARYd+9pDwI3SG4PrLv3yB4Gjp+34MMDVzBprBGLZgzMjdGo57wWKxrf34yWklJEjh6FxEcfRkQSAyAREVF/xTAQAnwWa6/ag+VitR1/++RrjErR4qfzR0Cp4BKioUqSJNgPHYZl5y5AEhH/4APQ3TGTowFERET9HMNACBCMhi4v/AWjQYZq2jTYWvHW7goYdWqsXjQaESpeFIYqj9mMxo2b0Vp2HlHpY5Dw6EOISEiQuywiIiLqAYaBEGBYtBDm9zdDcnva2xTqCBgWLZSlnuYWL974oBySBDz143RoYyJkqYMCSxJF2A8cguXD3QCA+BUPQjdjGkcDiIiIBhCGgRBw474A6+49bSMESiXiH1ouy/0CHq+It3eXw9zkwr89MBaDDFFBr4H8z154rL1/CUYDYu+8Ey1nzqD1QjmiMjOQ8PAKRMQb5S6TiIiIeolhIETocidDlzsZ9sNH0PjeJqgHDw56DZIkYcNn36Ciuhk/yx+J0UN1Qa+B/M9eeKzDyJPPYoV15weASoWEh1dAO30qFLwfhIiIaEBiGAgxMRMmAMotcBQVIzJ1eFDOWVDaiF0HqmGxuwEAOel6TM6ID8q5KfCsu/d0mIJ2g6DVQDdjmgwVERERkb9wcm+IEbQaRKWPgeNkMSRJCvj5CkobsfEfVe1BAADOft2EgtLGgJ+bAsfndMJ55izMOz/sfrUq27UgV0VERET+xpGBEKTJyYZ501Z4qmugHhrYtf13HaiG2yt2aHN7Rew6UI0pmVxRZqDwOZxorbiI1vJytF6ogPvKFUCSAJWq7cfr7fQaOVerIiIiIv9gGAhBmqwJMG/eBkdRccDDwHdHBHrSTv2Dz+FAa3lF28+FCrirqwFJgkKlQuTIEdDfMx9R6WMQmZYKR/GpfrVaFREREfkPw0AIEmJjETV6FBxFxTAszA/ouYw6dZcX/kadOqDnpd7xNTd/5+K/HO6aq20X/xERbRf/+QvaL/6VER2Xgv3+alWC0QDDooWy725NREREfccwEKI0Odkwb90B99VaqJMDt7LQlEwjPims7dCmVimxeGZgRyTo5nx2e/vFf8uFcnhqrgJA28X/qJHQ32tCdPoYRKYOhyLih/eBuLFaFREREYUWhoEQFZOdBfPWHW1ThZLnB+w8TU4vBCUQq4mA1e6BUafG4plDeL9AgNxY7/8bqw2CQd/+Db2vqQkt16f8tJaXw3O1LaAp1GpEjRoJ7aSJbd/8pw6HQsX/7YmIiKgNrwpClEqvR+TIEXAWFcNwT2DCgMcr4mS5FZMz4vH4gpEBOQd9q6v1/hvf3QjLzl0Qm5oAAIrIyLaL/ymTETXm+sW/IMhZNhEREfVjDAMhTJOTDcuOD+Gpb0BEUqLfj3/2m2tocfmQmxleewp8fzdef82fl3w++Jod8NmbINqb4bPbr/80w9dkh+P4CUie7633L4qQWpwwLFmE6PTRUA8bxot/IiIi6jGGgRAWk90WBhxFxdDPu9vvxy8sNUMXo0LG8Fi/H7u/6urbefP7mwGgUyCQJAlSa2vbxXz7hX3bxb34vQt9n90O0eHo+qSCAEGn6xwEbpzH44V+7l3+e5NEREQUNhgGQlhEvBHq1OEBCQMtLi9Of23DzAmJEJQKvx67P+tqN17J7YF58za0lp3/9gLfbodob+72Al4ZEwNBp4VSp0NE8mBEpY+BoNNC0Omu/2ghxMZCqdNCGR0NhUKBSy+82OUGYFzvn4iIiG4Vw0CI05iyYd31ETxmCyLijX477skLVnh9EqaE2RSh7nbjlVpb0VJ2vv1iXp08uP3PytjvXODrdBC02lu6idewaCHX+yciIiK/YhgIcTfCgLOoGHF3zfbbcQvLLEjURyJtsMZvxxwIBIMBPmvX384P/8MrAT13h/X+v7eaEBEREdGtYBgIcRFJiVAPHQqHH8OArdmN85eacE9eChSK8JkiJPl8EGJjO4WBYH47f2O9/5SUFNTU1ATlnERERBS6lHIXQIEXY8qC6+tv4LXZ/HK8Y2UWSAByM/037ai/k3w+NPy/d+GuqoImd1L7PH3BaED8wyv47TwRERENSBwZCAOanGzY9nwMR9EpxN35oz4fr7DUjOGDYjDYGO2H6vo/yedDw9/eheNkEYz3L/HrdCsiIiIiOXFkIAyoBw9GRHIynEXFfT5WrbkFl+qdYXPjcFsQ2ADHiSIY71/MIEBEREQhhWEgTGhMWWituAjf9Z1qb1VBmRkKBTB5bOhPEZJ8PjT8zwY4TpyE8ceLEXfXHLlLIiIiIvIrhoEwockxAZIER/HpWz6GJEkoLLUgY1gs4rRqP1bX/7QFgffgOH4ShiWLEHc3gwARERGFHoaBMBGRkgxVUiIcfZgq9M1VBxqvuTA5xG8clnw+NLy7EY7jJ2BYsoi7+xIREVHIYhgIEwqFAhpTNlovlMPX7LilYxSUmqESFMgZE7o73rYHgWPHYVh8H4MAERERhTSGgTCiyTEBogjn6d5PFfL5RJw4b8GEUXpER4bmIlSSKH4nCCyEft7dcpdEREREFFAMA2FEPWwoVPFGOE4W9/q1pZeaYG/xYkpGaK4i1BYE3msLAosWQj9vrtwlEREREQUcw0AYaZsqZEJL2Xn4nM5evbaw1IKYSAG3j4gLUHXyaR8RKLweBOYzCBAREVF4YBgIMzE52YDPB+eZsz1+jcvjQ3GFFTnpRkSoQqvLSKKIxg0b4Sg8BsN99zIIEBERUVgJrSs7+kGRqcMhGPRw9mKq0KkKG1weEbkhtopQWxB4H80F14PAgnlyl0REREQUVAwDYUahVEKTnY2WklKIra09ek1hmRkGbQTGDNUFuLrgkUQRje+9j+aCQugX5jMIEBERUVhiGAhDGlMWJK8XzjPnfvC5zU4PzlU2YXJGPJQKRRCqCzxJFNG4cROaj7YFAcM98+UuiYiIiEgWDANhKHLUSAixsT3agOzEBStEUUJuZmisItQWBDaj+UgB9PfewyBAREREYY1hIAwplErEZGeh5VwJRJfrps8tKDUjJT4aQxOjg1Rd4HwbBI5Cn78AhvwFcpdEREREJCuGgTClMWVBcrvRcq602+c0XnPhYk0zJmcaoRjgU4Q6BYF775G7JCIiIiLZMQyEqagxo6HUauEoKur2OYVlZgBA7gDfaEwSRTS+fz0I3DOfQYCIiIjoOoaBMKUQBMRkjYfzzDmIHk+nxyVJQmGpGaNStEiIi5ShQv9oCwJb0Hy4LQjoGQSIiIiI2jEMhDFNjgmSy4WWkrJOj11paMFVcyumDOAbhyVRROOmLWg+fAT6BfOgv/eeAT/diYiIiMifGAbCWPTYdChjYuDsYqpQYakZSqUCE9MNMlTWd5Iowrx5K5oPHUHc/HnQL8xnECAiIiL6HpXcBZB8FIKAmAnj4Dx1BpLXC4WqrTuIkoRjZWbcnhYLbUyEzFX2XlsQ2Ab7wcOImz8PhvsYBIiIiKh/2Lt3Lz799NP23+vr63HHHXfgiSeeaG87duwYtm3bBgBITEzE6tWrodVqA1IPw0CY0+SY0Hy0EC1l5xEz7nYAQPkVO6zNHvz4joE3RUgSRZi3bIP94CHEzZ/LIEBERET9ypw5czBnzhwAwOXLl7F27VosXbq0/XGn04n169djzZo1MBqN2Lp1K7Zv347HH388IPXIFgbee+89NDU14V/+5V9QWVmJdevWwel0IjMzE08++SQEQUBjYyPeeOMNXLt2DSkpKfjXf/1XREVFyVVySIrOGAtFVBQcRafaw0BhqRmREUpkjdbLW1wvtQWB7bAfOIS4eXfDcN+9DAJEREQUNPX19Z3aNBoNNBpNl89fv349VqxYgdjY2PY2n8+HJ554AkajEQCQmpqKAwcOBKZgyBQGzpw5g3379iEnJwcA8MYbb2DlypVIT0/H22+/jb1792Lu3LlYv3495s6di+nTp2PHjh3YsWMHHnnkkV6dKyUlJRBvod+fuzeacyfDVlSEwUlJUKpUeP6nA6Pu75JEEV+vewf2Awcx5P4lSH304ZAPAgOlf9HAxP5FgcT+RYEkZ/966qmnOrU98MADWLZsWaf206dPw+12Y+rUqR3adTodcnNzAQButxu7du3C/PnzA1MwZAgDzc3N2LJlC5YsWYKqqio0NDTA7XYjPT0dADBr1ixs27YNs2fPRmlpKZ599tn29pdeeqnLMOBwOOBwODq1JyUloaamJrBvqBspKSmynbu3lJlj4f3qAL7Z/xXOqwbh7Y8q8PSP0zFuRJzcpd2UvfAYrLv3wGexQhEZCcnlQtzcuxAx505cvXpV7vICaiD1Lxp42L8okNi/KJDk7F8pKSl48803O7V3NyrwxRdfID8/v9vjOZ1OrF27FqmpqZg1a5a/yuwk6GHgL3/5C5YvXw6zuW1DK6vVCr1e3/64wWCAxWKB3W5HdHQ0BEFob7/xmu/7+OOPsWPHjk7t27Zt48hAD/ji49H4P+8BF8pxOkaHOK0ac/LGQhD672JT9fu/gmXTVoguFwBAcrmgEAQk3X4bkoYMkbm64Bgo/YsGJvYvCiT2LwokOftXUlJSj57n9XpRUlKC1atXd/m41WrFH/7wB4wbNw6PPfaYP0vsJKhhYO/evYiPj8f48eOxb98+AG2bW32fQqHosl2p7PriND8/v9vExJGBnom+/TbUHzyMwpRBmD5hEOrqauUu6aYu/c+G9iBwg+Tz4et334M3fYxMVQXPQOtfNLCwf1EgsX9RIMk9MtBTVVVVSE5O7vJeWFEU8eqrr2Lq1Km4//77/Vlil4IaBg4fPgybzYZnn30Wzc3NaG1thUKhgM1ma3+O1WqFwWBAbGwsWlpaIIoilEple3tXbnZjBvVMTE42HCeLMNhRjymZt8ldzg/yWay9aiciIiLqL+rq6hAf33HVxjVr1mDZsmUwm82orKyEKIo4evQoAGDUqFFYtWpVQGoJahj47W9/2/7nffv24dy5c1i9ejWeeeYZlJWVISMjA/v374fJZIJKpUJGRgYOHz6MGTNm4KuvvkJ2dnYwyw0rMbffDp9SQLbnCkYk9/9gJRj08FltnduNA3OTNCIiIgof06ZNw7Rp0zq0/frXvwbQduG/devWoNXSL/YZePrpp7Fu3Tq0trYiLS0NCxYsAAD87Gc/w3/9139h586dSEhIwC9+8QuZKw1ddq8CF6NTkG6vAiQJ6Ocr8UQMTu4UBhTqCBgWLZSnICIiIqIBSLYwMGvWrPZ5/mlpaVizZk2n5yQmJuKll14KbmFh6th5C8q0qUivuwxXZRWiRo6Qu6RutV78Gq1lZYjMGAtvfT18FisEowGGRQuhy50sd3lEREREA0a/GBkg+RWUmhGROgZoPALHyaJ+GwZEjweN770PlcGAwSt/BiU3oSMiIiK6Zf137UgKmlpLCy7VOWEan4LozAw4i051uZpTf2D7+BN46uoR//ByBgEiIiKiPmIYIBSWWqAAMDnDCI0pG16LBe5Ll+UuqxPXpcu49vleaKfmIea2TLnLISIiIhrwGAbCnCRJKCwzY+zwWOi1asRkjQeUSjhOFsldWgeS14vGDRsh6LQw3r9E7nKIiIiIQgLDQJirrHWgweZCbqYRACBoNIgemw5HP5sqZPvHF3BX1yB+xYMQNDFyl0NEREQUEhgGwlxBqRkqQYGcMd+uzx9jyoa3oQHu6moZK/uWu+YqbH//FJpJOdBkTZC7HCIiIqKQwTAQxnyihOPnLZgwUo/oyG8XltJkTQAUCjhPFstX3HWSKKLxvfehjI5G/LIH5C6HiIiIKKQwDISx0qom2J1e5GZ23A5biNUhasxoOIpOyVTZt5r+70u4KqsQv+x+CDqd3OUQERERhRSGgTB2rMyMmEgB40bEdXpMY8qGp7YW7qtXZaisjae+AdaPPkbMhPHQTJooWx1EREREoYphIEy5PT4UlVuRk25AhKpzN4jJzgIUCjhkmiokiSIaN26CQqVC/IoHoVAoZKmDiIiIKJQxDISpUxdtcHlE5GbEd/m4Sh+HyJEj4CwqDm5h19kPHEJreQWM9y+BSt955IKIiIiI+o5hIEwVlJqh10ZgzLDu5+FrTNlwV9fAU18fxMoAr8UCy4e7EZUxFtppeUE9NxEREVE4YRgIQ81OD85VNmFyRjyUN5l+ozFlAQAcQRwdkCQJje9vASAh4ZEVnB5EREREFEAMA2HoxAUrRFHClMyupwjdoDIaEZmWGtT7BpqPFqKlpBTGxfchIv7m9RERERFR3zAMhKHCMjOS46MwNDH6B58bY8qG+9JleBobA16X99o1WLbvROSokdDdMTPg5yMiIiIKdwwDYcbc5EJFdTNyM+J7NAVHY8oGADiLA7vngCRJMG/ZBsnjQcIjD0GhZNckIiIiCjRecYWZwlIzAHTaaKw7EYkJUA8bGvCpQs6TxXAWn4Z+YT7UgwcF9FxERERE1IZhIIxIkoTCUgtGpWiREBfZ49dpTNlwfVMJr9UakLp8zc1o3Lod6uHDEDfnzoCcg4iIiIg6YxgII1caWlBjbunxqMANMdenCjmKAjNVyLx9J0SHA4mPPgyFIATkHERERETUGcNAGCksM0OpVGBSuqFXr1MPHoSIlOSALDHqPHMWjsLj0C+YB/XQIX4/PhERERF1j2EgTIiShGNlFtyWGgttTESvX68xZcN18Wt4rzX5r6aWFjRu2oqIlGTo58/123GJiIiIqGcYBsJExRU7rHb3D+4t0B2NKRuQJL+uKmT5YBd81661TQ9Sqfx2XCIiIiLqGYaBMFFQakFkhBJZo/W39PqIlGREDEry21ShlrLzsB88jLi7ZiMyLdUvxyQiIiKi3mEYCAMer4iTFyzIGq1HZMSt3aCrUCgQY8pGa3kFfHZ7n+oRXS40btwMVVIi9Pfe06djEREREdGtYxgIA+cqr8Hp8t3yFKEbNDnZgCjCeepMn45j3f2/8JrNSHzkISjV6j4di4iIiIhuHcNAGCgsNUMbrULm8Ng+HUc9dChUCQl9mirUevFrNO3bD92PZiJqzOg+1UNEREREfcMwEOJaXD6c/tqGSWONEIS+/edWKBTQmLLQUnYePoez168XPR40vvc+BIMexsX39akWIiIiIuo7hoEQV1Ruhccr9Xqjse60TxU63fupQraPP4Gnrh4JD6+AMirKL/UQERER0a1jGAhxhaVmJMRFYmSyxi/HU6emQjAY4OzlVCHXpcu49vleaKfmIea2TL/UQkRERER9wzAQwq41u1F2uQm5mUYoFAq/HPPGVCFnaRnElpYevUby+dqmB+m0MN6/xC91EBEREVHfMQyEsGPnLZAkIDfDP1OEbtDkmACvF86z53r0fNtnn8N9pRrxKx6EoInxay1EREREdOsYBkJYYakZw5JikBwf7dfjRo5IgxAXC8fJ4h98rrvmKmyffAbNxBxosib4tQ4iIiIi6huGgRBVZ2lFVZ2zz3sLdEWhVCImOwst50ogulzdPk8SRTS+twnKqCjEP/iA3+sgIiIior5hGAhRBaVmKABMGmsMyPE1OSZIHg9azpV0+5ym/9sHV2Ul4pfdD0GnC0gdRERERHTrGAZCkCRJKCwzI324DgZdYHb4jRo9CkqtttupQp76Blg/+l/EjB8HzaSJAamBiIiIiPqGYSAEVdY60GBzYYqfbxz+LoVSCU12Fpxnz0J0uzs8JokiGjdugkKlQvxDD/ptJSMiIiIi8i+GgRBUWGqGSlDANMYQ0PPEmLIgudxoKS3r0G4/eBit5RUw3r8EKr0+oDUQERER0a1jGAgxPlHCsfMWjB+pR0yUKqDnih6bDmVMTIepQl6LBZYPdiEqYyy00/ICen4iIiIi6pvAXi2GoYLSRuw6UA2r/RgMOjUWzxyCKZkJQTt/2aUm2J1e5GYG5sbh71IIAmKyJsBZfAqSxwOoVGh8fwsACQmPrOD0ICIiIqJ+jmHAjwpKG7HxH1Vwe0UAgMXuxsZ/VAFA0AJBYakZ0ZECxo/QB+V8GlMWmo8cRcv5C/A1N6OlpBTGZQ8gIj5w9ysQERERkX8wDPjRrgPV7UHgBrdXxN8++QZ/P3oVMZECYqJU3/4zSkBMZBe/X/9nlFrZ42/XC0ob8eGBK7DaPYiMUOJkuSUoASQ6YyygUqH+L39tHx1QRvt3kzMiIiIiCgyGAT+y2N1dtksSMCQhGs5WH5qcHtRaWuF0edHS6oN0k+MpFUB0pAqaKAHR3wkSmijVt79HCahpaMGBMw3w+tqO5vKIQRuRaC4qBkQRkng9BHm9MG/eAigV0OVODui5iYiIiKhvGAb8yKhTdxkIjDo1/nnh6E7toiTB5fbB0eqDs9ULp8sHp8sL53d/b/1Om8sLS5O7/Xef2H2UcHtF7DpQHfAwYN29BxA7joZIbg+su/cwDBARERH1cwwDfrR45pAO9wwAgFqlxOKZQ7p8vlKhQHSkCtGRKiAuslfnkiQJbq8IZ6sPv/rLqS6f091IhT/5LNZetRMRERFR/8GlRf1oSmYCHpmbCqNODQXaRgQemZsakG/nFQoFIiMEGHRqGLvZZbi7dn8SjF3vZdBdOxERERH1HxwZ8LMpmQmYkpmAlJQU1NTUBOWcvR2R8CfDooUwv78ZktvT3qZQR8CwaGHAz01EREREfcMwEAJujDzsOlANi90NYxD3N7hxX4B19x74LFYIRgMMixbyfgEiIiKiAYBhIETcGJGQgy53Mi/+iYiIiAYg3jNARERERBSmGAaIiIiIiMIUwwARERERUZhiGCAiIiIiClMMA0REREREYYqrCRERERERBcnevXvx6aeftv9eX1+PO+64A0888UR7W2VlJdatWwen04nMzEw8+eSTEAQhIPUwDBARERERBcmcOXMwZ84cAMDly5exdu1aLF26tMNz3njjDaxcuRLp6el4++23sXfvXsydOzcg9XCaEBERERGRH9TX13f6cTgc3T5//fr1WLFiBWJjY9vbGhoa4Ha7kZ6eDgCYNWsWjhw5ErCaQ35kICUlJSzPTaGP/YsCif2LAon9iwJJzv711FNPdWp74IEHsGzZsk7tp0+fhtvtxtSpUzu0W61W6PX69t8NBgMsFovfa71BljCwdetWHD16FAqFArNnz8a9996L06dPY8OGDXC73Zg2bRqWL18OoO9zpmpqagL1Nm4qJSVFtnNT6GP/okBi/6JAYv+iQJKzf6WkpODNN9/s1K7RaLp8/hdffIH8/PxO7ZIkdWpTKBR9L7AbQZ8mVFJSgrNnz+LPf/4zXn31VXzyySeorKzE22+/jeeeew7/+Z//iYsXL6KoqAhA25ypxx9/HK+//jokScLevXuDXTIRERER0Q9KSkrq9NNVGPB6vSgpKcGkSZM6PWY0GmGz2dp/t1qtMBgMAas56GHgtttuw+9+9zsIgoBr165BFEU4nU4kJycjKSkJgiBg5syZOHLkSNDnTBERERERBVpVVRWSk5MRFRXV6bHExESo1WqUlZUBAPbv3w+TyRSwWmSZJqRSqbBt2zbs2bMHeXl5sFgsHeZG6fV6WCyWHs+ZcjgcXd6ckZSUFIjyiYiIiIhuWV1dHeLj4zu0rVmzBsuWLcOoUaPw9NNPY926dWhtbUVaWhoWLFgQsFpku4F42bJlWLRoEf74xz+itra20+MKhaLHc6Y+/vhj7Nixo1P7tm3beAMxhSz2Lwok9i8KJPYvCqSB0L+mTZuGadOmdWj79a9/3f7ntLQ0rFmzJii1BD0MVFdXw+PxIC0tDZGRkcjNzUVBQQGUym9nLNlsNhgMhh7PmcrPz8esWbO6PB9vIKZQxP5FgcT+RYHE/kWBJPcNxANR0O8ZqKurw7p16+DxeOD1enH8+HHcddddqKmpQW1tLURRxMGDB2EymXo8Z0qj0XR5wwYREREREXUv6CMDOTk5qKiowHPPPQelUokpU6Zg+vTpiI2NxWuvvQa32w2TyYS8vDwACOqcKSIiIiKicKKQupqYH0I4TYhCEfsXBRL7FwUS+xcFEqcJ9V7QpwkREREREVH/EPIjA0RERERE1DWODBARERERhSmGASIiIiKiMMUwQEREREQUphgGiIiIiIjCFMMAEREREVGYYhggIiIiIgpTDANERERERGGKYYCIiIiIKEwxDBARERERhSmV3AUMJE6nE7/97W/x/PPPIykpCfv27cPu3buhVCoxbtw4/OQnP4EgCKioqMBf//pXeDweJCQkYNWqVdDr9bDZbPjv//5vNDQ0ICoqCo899hjS09PlflvUT2zfvh1HjhwBAOTk5OCRRx7B6dOnsWHDBrjdbkybNg3Lly8HAFRWVmLdunVwOp3IzMzEk08+CUEQ2o/1zTff4IUXXsCmTZtkeS/U//ijf3X32UbUm/51w5tvvolx48Zh1qxZHdr5+UXf54/+xc+vm5CoRy5cuCA988wz0vLly6W6ujqpurpaWrlypWSxWCRJkqR33nlH2rNnjySKorRq1SrpzJkzkiRJ0qFDh6RXX31VkiRJev3116WtW7dKkiRJtbW10lNPPSW5XC553hD1K6dOnZJ+85vfSB6PR/J4PNLLL78sHThwQFq1apVUV1cneb1e6fe//7108uRJSZIk6d///d+l8+fPS5IkSW+99Zb02WeftR+rtbVV+s1vfiMtXbpUlvdC/Y8/+tfNPtsovPW2f5nNZmnNmjXSww8/LH355ZcdjsXPL/o+f/Qvfn7dHKcJ9dDevXvxxBNPwGg0AgCqqqqQnp4Og8EAoC2pHjt2DHa7HW63G+PGjQMATJw4EcXFxfB4PKisrMTUqVMBAIMGDYJWq8WFCxfkeUPUrxgMBjz66KNQqVRQqVQYMmQIrl69iuTkZCQlJUEQBMycORNHjhxBQ0MD3G53+6jSrFmz2r8xAYANGzYgPz9frrdC/ZA/+tfNPtsovPWmfwHAwYMHMXny5Pa/D7+Ln1/0ff7oX/z8ujmGgR5atWoVMjMz239PTU1FeXk5GhsbIYoijh49CpvNBp1Oh6ioKJw6dQoAcOjQIfh8PtjtdowYMQKHDh0CAFy6dAlXrlyBzWaT4+1QPzNs2LD2i6+rV6/i8OHDUCgUHYYw9Xo9LBYLrFZrh3aDwQCLxQIAOH78OFwuF/Ly8oJZPvVz/uhfN/tso/DWm/4FAPfddx/mzJnT6Tj8/KKu+KN/8fPr5hgGblFKSgoeeugh/OlPf8KLL76I1NRUqFQqKBQKPPPMM/jwww/x3HPPwel0QqfTQaVS4bHHHkNtbS2eeeYZ/P3vf8ftt98OlYq3bdC3Ll++jN///vd49NFHMXjw4E6PKxQKSJLUZbvNZsPOnTvxT//0T8EolQagvvSvm322EQE961/d4ecX/ZC+9C9+ft0c/y3cIrfbjdGjR+NPf/oTAKCgoACDBg0CAAiCgJdeegkA0NzcjJ07d0Kr1aKxsRErV65EdHQ0AOCXv/xl+2uIysrK8Nprr+GnP/0ppk+fjpKSEly7dq39cZvNBoPBAKPR2GFEyWq1wmAw4MSJE2hubsbvfve79seeffZZvPLKK+19jsJXX/sX0P1nG1FP+1d3+PlFN9PX/gXw8+tmODJwi1wuF1555RW0tLTA6/Xik08+wbRp0wAAb731FioqKgAAH330EfLy8qBUKvHpp5/i888/BwCcOnUKXq8Xqampsr0H6j8aGxuxdu1a/OIXv8D06dMBAKNHj0ZNTQ1qa2shiiIOHjwIk8mExMREqNVqlJWVAQD2798Pk8mEOXPm4I033sDatWuxdu1aAMDatWv5Fyn5pX8B3X+2UXjrTf/qDj+/qDv+6F8AP79uhiMDt0in02Hp0qV44YUX4PP5MH36dMyYMQMA8OSTT+Kdd96By+XC8OHD8fOf/xwAsHjxYrz++uvYv38/oqOj8ctf/pIdkQAAe/bsgcfjwbvvvtvedvfdd2P16tV47bXX4Ha7YTKZ2ufSPv3001i3bh1aW1uRlpaGBQsWyFU6DQD+6l/dfbZReOtt/yLqDX/1L35+dU8hdTVBlIiIiIiIQh6/liYiIiIiClMMA0REREREYYphgIiIiIgoTDEMEBERERGFKYYBIiIiIqIwxTBARERERBSmGAaIiIiIiMIUwwARERERUZj6/z0uiv1b2p2BAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x720 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "execution_count": 19
    },
    {
      "cell_type": "markdown",
      "source": "* The Pearson correlation coefficient indeed confirms this.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "stats.pearsonr(cd.c, cd.d)",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(0.7980824438518808, 1.457161889155522e-05)"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 20
    },
    {
      "cell_type": "markdown",
      "source": "* We can proceed to create a linear regression model.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "cd_mod = smf.ols(\"d ~ c\", data=cd)\ncd_res = cd_mod.fit()\ncd_res.params",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Intercept   -2423.778839\n",
              "c             410.191120\n",
              "dtype: float64"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 21
    },
    {
      "cell_type": "code",
      "source": "ggplot(data=cd) +\\\n    geom_point(mapping=aes(x='c', y='d')) +\\\n    geom_abline(intercept=cd_res.params['Intercept'], \n                slope=cd_res.params['c'])",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "<ggplot: (332575254)>"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 22
    },
    {
      "cell_type": "code",
      "source": "sns.lmplot(x='c', y='d', data=cd, aspect=1.5)",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x13d2dfb50>"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 540x360 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "execution_count": 23
    },
    {
      "cell_type": "markdown",
      "source": "* And let's see the summary.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "cd_res.summary()",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>OLS Regression Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>            <td>d</td>        <th>  R-squared:         </th> <td>   0.637</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.618</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   33.33</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>             <td>Thu, 09 Dec 2021</td> <th>  Prob (F-statistic):</th> <td>1.46e-05</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>                 <td>16:45:04</td>     <th>  Log-Likelihood:    </th> <td> -132.06</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>No. Observations:</th>      <td>    21</td>      <th>  AIC:               </th> <td>   268.1</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Residuals:</th>          <td>    19</td>      <th>  BIC:               </th> <td>   270.2</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Intercept</th> <td>-2423.7788</td> <td>  545.684</td> <td>   -4.442</td> <td> 0.000</td> <td>-3565.909</td> <td>-1281.649</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>c</th>         <td>  410.1911</td> <td>   71.048</td> <td>    5.773</td> <td> 0.000</td> <td>  261.485</td> <td>  558.897</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "  <th>Omnibus:</th>       <td> 7.240</td> <th>  Durbin-Watson:     </th> <td>   0.817</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(Omnibus):</th> <td> 0.027</td> <th>  Jarque-Bera (JB):  </th> <td>   4.796</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Skew:</th>          <td>-1.057</td> <th>  Prob(JB):          </th> <td>  0.0909</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Kurtosis:</th>      <td> 4.007</td> <th>  Cond. No.          </th> <td>    143.</td>\n",
              "</tr>\n",
              "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
            ],
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                            OLS Regression Results                            \n",
              "==============================================================================\n",
              "Dep. Variable:                      d   R-squared:                       0.637\n",
              "Model:                            OLS   Adj. R-squared:                  0.618\n",
              "Method:                 Least Squares   F-statistic:                     33.33\n",
              "Date:                Thu, 09 Dec 2021   Prob (F-statistic):           1.46e-05\n",
              "Time:                        16:45:04   Log-Likelihood:                -132.06\n",
              "No. Observations:                  21   AIC:                             268.1\n",
              "Df Residuals:                      19   BIC:                             270.2\n",
              "Df Model:                           1                                         \n",
              "Covariance Type:            nonrobust                                         \n",
              "==============================================================================\n",
              "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
              "------------------------------------------------------------------------------\n",
              "Intercept  -2423.7788    545.684     -4.442      0.000   -3565.909   -1281.649\n",
              "c            410.1911     71.048      5.773      0.000     261.485     558.897\n",
              "==============================================================================\n",
              "Omnibus:                        7.240   Durbin-Watson:                   0.817\n",
              "Prob(Omnibus):                  0.027   Jarque-Bera (JB):                4.796\n",
              "Skew:                          -1.057   Prob(JB):                       0.0909\n",
              "Kurtosis:                       4.007   Cond. No.                         143.\n",
              "==============================================================================\n",
              "\n",
              "Notes:\n",
              "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
              "\"\"\""
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 24
    },
    {
      "cell_type": "markdown",
      "source": "* So we have seen that the model of the second example fits the data quite well, since it explains more than 60% of its variation:",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "cd_res.rsquared",
      "metadata": {
        "slideshow": {
          "slide_type": "fragment"
        }
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0.6369355871845903"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "execution_count": 25
    },
    {
      "cell_type": "markdown",
      "source": "* But what really was our data?\n\n* What were the variables `c` and `d`?\n\n* The `c' variable is actually US per capita cheese consumption in the years 1999-2019.\n\n* The variable `d` is the number of deaths in the US from suffocation and strangulation accidents in bed.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "code",
      "source": "plt.style.use('ggplot')\nfig, ax1 = plt.subplots(figsize=(12, 10))\nd_line, = ax1.plot(cd.year, cd.d, 'bo-', label='deaths by accidental suffocation and strangulation in bed')\nax1.set_ylabel('Deaths by Accidental Suffocation and Strangulation in Bed')\n\nax2 = ax1.twinx()\nc_line, = ax2.plot(cd.year, cd.c, 'ro-', label='per capita cheese consumption')\nax2.set_ylabel('Per Capita Cheese Consumption')\n\nplt.xticks(np.arange(cd.year.min(), cd.year.max()+1, step=5))\nplt.legend(handles=[c_line, d_line], loc='upper left', fontsize=12)",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        },
        "tags": [
          "remove_input"
        ]
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x13d429970>"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x720 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "execution_count": 26
    },
    {
      "cell_type": "markdown",
      "source": "* Should we really think there is a connection between the two?",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "### Attention: correlation does not imply causation!\n### Just because we observe a statistical relationship in our data does not mean that our data are not unrelated.",
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      }
    },
    {
      "cell_type": "markdown",
      "source": "\n* The above example example can be found on Tyler Vigen's website (and book) [Spurious Correlations](https://www.tylervigen.com/spurious-correlations).",
      "metadata": {}
    }
  ]
}