fractinalfactorymodel.ipynb

fractinalfactorymodel.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyOvoeOM+UJg9KaRnCb3S1Tc",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "ir",
      "display_name": "R"
    },
    "language_info": {
      "name": "R"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/Curlyhub/edea3b5a0c5e2b94ee2edf781ca77d53/fractinalfactorymodel.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Obtain catapult the data source:We skip all the comments lines  "
      ],
      "metadata": {
        "id": "Uu-31hK_3X8s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "m = read.table(\"https://www.itl.nist.gov/div898/handbook/datasets/CATAPULT.DAT\", header=FALSE, skip=50)\n",
        "print(m)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1GVg9cqfxX65",
        "outputId": "64e9c8cc-b74d-41bd-daeb-344c6d424c6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "       V1   V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13   V14\n",
            "1   28.00 3.25  0  1  0 80 -1 -1 -1  -1   1   1   0 ----+\n",
            "2   35.00 4.75  0  1  0 45  1 -1 -1  -1  -1   6   0 +----\n",
            "3    8.00 3.25 20  1  0 45 -1  1 -1  -1  -1  10   0 -+---\n",
            "4   28.25 4.75 20  1  0 80  1  1 -1  -1   1   8   0 ++--+\n",
            "5   33.50 3.25  0  2  0 45 -1 -1  1  -1  -1  15   0 --+--\n",
            "6   84.00 4.75  0  2  0 80  1 -1  1  -1   1  17   0 +-+-+\n",
            "7   36.00 3.25 20  2  0 80 -1  1  1  -1   1  16   0 -++-+\n",
            "8   28.50 4.75 20  2  0 45  1  1  1  -1  -1  14   0 +++--\n",
            "9   33.00 3.25  0  1  4 45 -1 -1 -1   1  -1  12   0 ---+-\n",
            "10  85.00 4.75  0  1  4 80  1 -1 -1   1   1   9   0 +--++\n",
            "11  45.00 3.25 20  1  4 80 -1  1 -1   1   1  18   0 -+-++\n",
            "12  36.50 4.75 20  1  4 45  1  1 -1   1  -1  11   0 ++-+-\n",
            "13 106.00 3.25  0  2  4 80 -1 -1  1   1   1  20   0 --+++\n",
            "14 126.50 4.75  0  2  4 45  1 -1  1   1  -1   4   0 +-++-\n",
            "15  45.00 3.25 20  2  4 45 -1  1  1   1  -1   5   0 -+++-\n",
            "16 126.50 4.75 20  2  4 80  1  1  1   1   1   3   0 +++++\n",
            "17  99.00 4.00 10  2  2 62  0  0  1   0   0   2   2 00+00\n",
            "18  45.00 4.00 10  1  2 62  0  0 -1   0   0   7   1 00-00\n",
            "19  84.50 4.00 10  2  2 62  0  0  1   0   0  13   2 00+00\n",
            "20  37.50 4.00 10  1  2 62  0  0 -1   0   0  19   1 00-00\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now we going to create a dataset, where\n",
        "  1. Dependent variable V1 = Distance (inches) ball travels\n",
        "  2. Factor Variable V2   = Band Height (height in inches of pivot point for rubber bands), 2.25, 3.5, 4.75\n",
        "  3. Factor Variable V3   = Start Angle (location of arm when operator releases), 0, 10, 20 degrees\n",
        "  4. Factor Variable V4   = Number of Rubber Bands, 1 or 2\n",
        "  5. Factor Variable V5   = Arm Length (distance the arm is extended in inches), 0, 2, 4\n",
        "  6. Factor Variable V6   = Stop Angle (location of the arm when arm is stopped) 45, 62, 80 degrees\n",
        "\n",
        "The design matrix appears below in (randomized) run order, column V12 from data source"
      ],
      "metadata": {
        "id": "SVgScdzT1ZF6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "distance = as.vector(m[[1]])\n",
        "order = as.vector(m[[12]])\n",
        "\n",
        "## Save variables as factors.\n",
        "height = as.factor(as.vector(m[[2]]))\n",
        "start = as.factor(as.vector(m[[3]]))\n",
        "bands = as.factor(as.vector(m[[4]]))\n",
        "length = as.factor(as.vector(m[[5]]))\n",
        "stop = as.factor(as.vector(m[[6]]))\n",
        "\n",
        "\n",
        "## Save numeric variables and interactions.\n",
        "h = as.vector(m[[7]])\n",
        "s = as.vector(m[[8]])\n",
        "b = as.vector(m[[9]])\n",
        "l = as.vector(m[[10]])\n",
        "e = as.vector(m[[11]])\n",
        "hs = h*s\n",
        "hb = h*b\n",
        "hl = h*l\n",
        "he = h*e\n",
        "sb = s*b\n",
        "sl = s*l\n",
        "se = s*e\n",
        "bl = b*l\n",
        "be = b*e\n",
        "le = l*e\n",
        "\n",
        "df = data.frame(distance,height,start,bands,length,stop,order,\n",
        "     h,s,b,l,e,hs,hb,hl,he,sb,sl,se,bl,be,le)\n",
        "df[order(df$order),1:7]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 725
        },
        "id": "1DY8UYh-2MjJ",
        "outputId": "359c4c12-0ea9-492c-9752-60ca05da3065"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A data.frame: 20 × 7</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>distance</th><th scope=col>height</th><th scope=col>start</th><th scope=col>bands</th><th scope=col>length</th><th scope=col>stop</th><th scope=col>order</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>1</th><td> 28.00</td><td>3.25</td><td>0 </td><td>1</td><td>0</td><td>80</td><td> 1</td></tr>\n",
              "\t<tr><th scope=row>17</th><td> 99.00</td><td>4   </td><td>10</td><td>2</td><td>2</td><td>62</td><td> 2</td></tr>\n",
              "\t<tr><th scope=row>16</th><td>126.50</td><td>4.75</td><td>20</td><td>2</td><td>4</td><td>80</td><td> 3</td></tr>\n",
              "\t<tr><th scope=row>14</th><td>126.50</td><td>4.75</td><td>0 </td><td>2</td><td>4</td><td>45</td><td> 4</td></tr>\n",
              "\t<tr><th scope=row>15</th><td> 45.00</td><td>3.25</td><td>20</td><td>2</td><td>4</td><td>45</td><td> 5</td></tr>\n",
              "\t<tr><th scope=row>2</th><td> 35.00</td><td>4.75</td><td>0 </td><td>1</td><td>0</td><td>45</td><td> 6</td></tr>\n",
              "\t<tr><th scope=row>18</th><td> 45.00</td><td>4   </td><td>10</td><td>1</td><td>2</td><td>62</td><td> 7</td></tr>\n",
              "\t<tr><th scope=row>4</th><td> 28.25</td><td>4.75</td><td>20</td><td>1</td><td>0</td><td>80</td><td> 8</td></tr>\n",
              "\t<tr><th scope=row>10</th><td> 85.00</td><td>4.75</td><td>0 </td><td>1</td><td>4</td><td>80</td><td> 9</td></tr>\n",
              "\t<tr><th scope=row>3</th><td>  8.00</td><td>3.25</td><td>20</td><td>1</td><td>0</td><td>45</td><td>10</td></tr>\n",
              "\t<tr><th scope=row>12</th><td> 36.50</td><td>4.75</td><td>20</td><td>1</td><td>4</td><td>45</td><td>11</td></tr>\n",
              "\t<tr><th scope=row>9</th><td> 33.00</td><td>3.25</td><td>0 </td><td>1</td><td>4</td><td>45</td><td>12</td></tr>\n",
              "\t<tr><th scope=row>19</th><td> 84.50</td><td>4   </td><td>10</td><td>2</td><td>2</td><td>62</td><td>13</td></tr>\n",
              "\t<tr><th scope=row>8</th><td> 28.50</td><td>4.75</td><td>20</td><td>2</td><td>0</td><td>45</td><td>14</td></tr>\n",
              "\t<tr><th scope=row>5</th><td> 33.50</td><td>3.25</td><td>0 </td><td>2</td><td>0</td><td>45</td><td>15</td></tr>\n",
              "\t<tr><th scope=row>7</th><td> 36.00</td><td>3.25</td><td>20</td><td>2</td><td>0</td><td>80</td><td>16</td></tr>\n",
              "\t<tr><th scope=row>6</th><td> 84.00</td><td>4.75</td><td>0 </td><td>2</td><td>0</td><td>80</td><td>17</td></tr>\n",
              "\t<tr><th scope=row>11</th><td> 45.00</td><td>3.25</td><td>20</td><td>1</td><td>4</td><td>80</td><td>18</td></tr>\n",
              "\t<tr><th scope=row>20</th><td> 37.50</td><td>4   </td><td>10</td><td>1</td><td>2</td><td>62</td><td>19</td></tr>\n",
              "\t<tr><th scope=row>13</th><td>106.00</td><td>3.25</td><td>0 </td><td>2</td><td>4</td><td>80</td><td>20</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA data.frame: 20 × 7\n\n| <!--/--> | distance &lt;dbl&gt; | height &lt;fct&gt; | start &lt;fct&gt; | bands &lt;fct&gt; | length &lt;fct&gt; | stop &lt;fct&gt; | order &lt;int&gt; |\n|---|---|---|---|---|---|---|---|\n| 1 |  28.00 | 3.25 | 0  | 1 | 0 | 80 |  1 |\n| 17 |  99.00 | 4    | 10 | 2 | 2 | 62 |  2 |\n| 16 | 126.50 | 4.75 | 20 | 2 | 4 | 80 |  3 |\n| 14 | 126.50 | 4.75 | 0  | 2 | 4 | 45 |  4 |\n| 15 |  45.00 | 3.25 | 20 | 2 | 4 | 45 |  5 |\n| 2 |  35.00 | 4.75 | 0  | 1 | 0 | 45 |  6 |\n| 18 |  45.00 | 4    | 10 | 1 | 2 | 62 |  7 |\n| 4 |  28.25 | 4.75 | 20 | 1 | 0 | 80 |  8 |\n| 10 |  85.00 | 4.75 | 0  | 1 | 4 | 80 |  9 |\n| 3 |   8.00 | 3.25 | 20 | 1 | 0 | 45 | 10 |\n| 12 |  36.50 | 4.75 | 20 | 1 | 4 | 45 | 11 |\n| 9 |  33.00 | 3.25 | 0  | 1 | 4 | 45 | 12 |\n| 19 |  84.50 | 4    | 10 | 2 | 2 | 62 | 13 |\n| 8 |  28.50 | 4.75 | 20 | 2 | 0 | 45 | 14 |\n| 5 |  33.50 | 3.25 | 0  | 2 | 0 | 45 | 15 |\n| 7 |  36.00 | 3.25 | 20 | 2 | 0 | 80 | 16 |\n| 6 |  84.00 | 4.75 | 0  | 2 | 0 | 80 | 17 |\n| 11 |  45.00 | 3.25 | 20 | 1 | 4 | 80 | 18 |\n| 20 |  37.50 | 4    | 10 | 1 | 2 | 62 | 19 |\n| 13 | 106.00 | 3.25 | 0  | 2 | 4 | 80 | 20 |\n\n",
            "text/latex": "A data.frame: 20 × 7\n\\begin{tabular}{r|lllllll}\n  & distance & height & start & bands & length & stop & order\\\\\n  & <dbl> & <fct> & <fct> & <fct> & <fct> & <fct> & <int>\\\\\n\\hline\n\t1 &  28.00 & 3.25 & 0  & 1 & 0 & 80 &  1\\\\\n\t17 &  99.00 & 4    & 10 & 2 & 2 & 62 &  2\\\\\n\t16 & 126.50 & 4.75 & 20 & 2 & 4 & 80 &  3\\\\\n\t14 & 126.50 & 4.75 & 0  & 2 & 4 & 45 &  4\\\\\n\t15 &  45.00 & 3.25 & 20 & 2 & 4 & 45 &  5\\\\\n\t2 &  35.00 & 4.75 & 0  & 1 & 0 & 45 &  6\\\\\n\t18 &  45.00 & 4    & 10 & 1 & 2 & 62 &  7\\\\\n\t4 &  28.25 & 4.75 & 20 & 1 & 0 & 80 &  8\\\\\n\t10 &  85.00 & 4.75 & 0  & 1 & 4 & 80 &  9\\\\\n\t3 &   8.00 & 3.25 & 20 & 1 & 0 & 45 & 10\\\\\n\t12 &  36.50 & 4.75 & 20 & 1 & 4 & 45 & 11\\\\\n\t9 &  33.00 & 3.25 & 0  & 1 & 4 & 45 & 12\\\\\n\t19 &  84.50 & 4    & 10 & 2 & 2 & 62 & 13\\\\\n\t8 &  28.50 & 4.75 & 20 & 2 & 0 & 45 & 14\\\\\n\t5 &  33.50 & 3.25 & 0  & 2 & 0 & 45 & 15\\\\\n\t7 &  36.00 & 3.25 & 20 & 2 & 0 & 80 & 16\\\\\n\t6 &  84.00 & 4.75 & 0  & 2 & 0 & 80 & 17\\\\\n\t11 &  45.00 & 3.25 & 20 & 1 & 4 & 80 & 18\\\\\n\t20 &  37.50 & 4    & 10 & 1 & 2 & 62 & 19\\\\\n\t13 & 106.00 & 3.25 & 0  & 2 & 4 & 80 & 20\\\\\n\\end{tabular}\n",
            "text/plain": [
              "   distance height start bands length stop order\n",
              "1   28.00   3.25   0     1     0      80    1   \n",
              "17  99.00   4      10    2     2      62    2   \n",
              "16 126.50   4.75   20    2     4      80    3   \n",
              "14 126.50   4.75   0     2     4      45    4   \n",
              "15  45.00   3.25   20    2     4      45    5   \n",
              "2   35.00   4.75   0     1     0      45    6   \n",
              "18  45.00   4      10    1     2      62    7   \n",
              "4   28.25   4.75   20    1     0      80    8   \n",
              "10  85.00   4.75   0     1     4      80    9   \n",
              "3    8.00   3.25   20    1     0      45   10   \n",
              "12  36.50   4.75   20    1     4      45   11   \n",
              "9   33.00   3.25   0     1     4      45   12   \n",
              "19  84.50   4      10    2     2      62   13   \n",
              "8   28.50   4.75   20    2     0      45   14   \n",
              "5   33.50   3.25   0     2     0      45   15   \n",
              "7   36.00   3.25   20    2     0      80   16   \n",
              "6   84.00   4.75   0     2     0      80   17   \n",
              "11  45.00   3.25   20    1     4      80   18   \n",
              "20  37.50   4      10    1     2      62   19   \n",
              "13 106.00   3.25   0     2     4      80   20   "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Note that four of the factors are continuous, and one, number of rubber bands, is discrete. Due to the presence of this discrete factor, we actually have two different centerpoints, each with two runs. Runs 7 and 19 are with one rubber band, and the center of the other factors, while runs 2 and 13 are with two rubber bands and the center of the other factors.\n",
        "\n",
        "**Analysis of the Experiment**\n",
        "\n",
        "After analyzing the 20 runs and determining factor settings needed to achieve predicted distances of 30, 60 and 90 inches, the team was asked to conduct five confirmatory runs at each of the derived settings.\n",
        "\n",
        "***Data Analysis***\n",
        "\n",
        ">  We start by plotting the data several ways to see if any trends or anomalies appear that would not be accounted for by the models\n"
      ],
      "metadata": {
        "id": "w0iXRPyivLZb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate four plots.\n",
        "options(repr.plot.width=12, repr.plot.height=12)\n",
        "center = which(height[]==4)\n",
        "par(mfrow=c(2,2),bg=rgb(1,1,1))\n",
        "qqnorm(distance)\n",
        "qqline(distance, col = 2)\n",
        "boxplot(distance, horizontal=TRUE, main=\"Box Plot\", xlab=\"Distance\")\n",
        "hist(distance, main=\"Histogram\", xlab=\"Distance\")\n",
        "plot(order, distance, xlab=\"Actual Run Order\", ylab=\"Distance\",\n",
        "     main=\"Run Order Plot\")\n",
        "points(df$order[center],df$distance[center],pch=19)\n",
        "par(mfrow=c(1,1))\n",
        "  \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "prH-u88kvO4Q",
        "outputId": "b619842b-9489-4d44-ded9-c656ca79f795"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Run Order Plot”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\nlRfSHTtTAAAAAElFTkSuQmCC"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "> We can see the large spread of the data and a pattern to the data that should be explained by the analysis. The run order plot does not indicate an obvious time sequence. The four highlighted points in the run order plot are the center points in the design. Recall that runs 2 and 13 had two rubber bands and runs 7 and 19 had one rubber band. There may be a slight aging of the rubber bands in that the second center point resulted in a distance that was a little shorter than the first for each pair.\n",
        "\n"
      ],
      "metadata": {
        "id": "wRIVFKLc5atJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Plots of responses versus factor columns\n",
        "par(mfrow=c(2,3),bg=rgb(1,1,1))\n",
        "boxplot(distance~height, data=df, main=\"Distance by Band Height\",\n",
        "        xlab=\"Height\",ylab=\"Distance\")\n",
        "\n",
        "boxplot(distance~start, data=df, main=\"Distance by Start Angle\",\n",
        "        xlab=\"Start Angle\",ylab=\"Distance\")\n",
        "\n",
        "boxplot(distance~bands, data=df, main=\"Distance by Number of Bands\",\n",
        "        xlab=\"Number of Bands\",ylab=\"Distance\")\n",
        "\n",
        "boxplot(distance~length, data=df, main=\"Distance by Arm Length\",\n",
        "        xlab=\"Arm Length\",ylab=\"Distance\")\n",
        "\n",
        "boxplot(distance~stop, data=df, main=\"Distance by Stop Angle\",\n",
        "        xlab=\"Stop Angle\",ylab=\"Distance\")\n",
        "par(mfrow=c(1,1))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "7PB_IbUF5YOx",
        "outputId": "2ac13b4f-c92c-47de-9791-e42a5e3ffbad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Distance by Stop Angle”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAMAAACffhT6AAADAFBMVEUAAAABAQECAgIDAwME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\n"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Several factors appear to change the average response level and most have large spread at each of the levels.\n",
        "\n",
        "**Analytical model**\n",
        "\n",
        "> With a predifined positive domain/interval of $R$, where the distance are defined , we are able to estimate all the main effects and all two-factor interactions without worrying about confounding. Therefore, the initial model will have 16 terms: the intercept term, the 5 main effects, and the 10 two-factor interactions. The $n$-factor interactions with $n\\ge3$ are not consider in base of the data source. Therefore we have:\n",
        "\n",
        ">$Y = \\beta_{0} + \\beta_{1}h + \\beta_{2}s + \\beta_{3}b + \\beta_{5}l + \\beta_{5}e + \\beta_{6}hs + \\beta_{7}hb + \\beta_{8}hl + \\beta_{9}he + \\beta_{10}sb + \\beta_{11}sl + \\beta_{12}se + \\beta_{13}bl + \\beta_{14}be + \\beta_{15}le $\n",
        "\n",
        "where $Y$ is the distance, therefore:\n"
      ],
      "metadata": {
        "id": "xovvvBnKx08v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "\n",
        "## Analytical model:Fit a model with up to second order interactions.\n",
        "q = lm(distance~h+s+b+l+e+hs+hb+hl+he+sb+sl+se+bl+be+le,data=df)\n",
        "qq = summary(q)\n",
        "qq"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 625
        },
        "id": "iGaSJXOo588z",
        "outputId": "122c51f4-62cc-422d-f001-8b06816dbd03"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "Call:\n",
              "lm(formula = distance ~ h + s + b + l + e + hs + hb + hl + he + \n",
              "    sb + sl + se + bl + be + le, data = df)\n",
              "\n",
              "Residuals:\n",
              "      1       2       3       4       5       6       7       8       9      10 \n",
              "-0.7813 -0.7812 -0.7813 -0.7813 -3.7000 -3.7000 -3.7000 -3.7000 -0.7813 -0.7812 \n",
              "     11      12      13      14      15      16      17      18      19      20 \n",
              "-0.7813 -0.7812 -3.7000 -3.7000 -3.7000 -3.7000 22.0500  6.8750  7.5500 -0.6250 \n",
              "\n",
              "Coefficients:\n",
              "            Estimate Std. Error t value Pr(>|t|)    \n",
              "(Intercept)  57.5375     2.9691  19.378 4.18e-05 ***\n",
              "h            13.4844     3.3196   4.062  0.01532 *  \n",
              "s           -11.0781     3.3196  -3.337  0.02891 *  \n",
              "b            19.4125     2.9691   6.538  0.00283 ** \n",
              "l            20.1406     3.3196   6.067  0.00373 ** \n",
              "e            12.0469     3.3196   3.629  0.02218 *  \n",
              "hs           -2.7656     3.3196  -0.833  0.45163    \n",
              "hb            4.6406     3.3196   1.398  0.23467    \n",
              "hl            4.7031     3.3196   1.417  0.22950    \n",
              "he            0.1094     3.3196   0.033  0.97529    \n",
              "sb           -3.1719     3.3196  -0.955  0.39343    \n",
              "sl           -1.1094     3.3196  -0.334  0.75502    \n",
              "se            2.6719     3.3196   0.805  0.46601    \n",
              "bl            7.6094     3.3196   2.292  0.08365 .  \n",
              "be            2.8281     3.3196   0.852  0.44225    \n",
              "le            3.1406     3.3196   0.946  0.39768    \n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
              "\n",
              "Residual standard error: 13.28 on 4 degrees of freedom\n",
              "Multiple R-squared:  0.9709,\tAdjusted R-squared:  0.8619 \n",
              "F-statistic: 8.905 on 15 and 4 DF,  p-value: 0.02375\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "> Note we have used the orthogonally coded columns for the analysis, and have abbreviated the factor names as follows:\n",
        "\n",
        "\n",
        "*   Height (h) = band height\n",
        "*   Start (s) = start angle\n",
        "*   Bands (b) = number of rubber bands\n",
        "*   Stop (e) = stop angle\n",
        "*   Length (l) = arm length.\n",
        "\n",
        ">The results of fitting the trial model that includes all main factors and two-factor interactions are shown above.\n",
        "\n",
        "> The model has a good R$^2$ value, but the fact that R$^2$ adjusted is considerably smaller indicates that we undoubtedly have some terms in our model that are not significant. Scanning the column of p-values (labeled $Pr(>|t|)$) for small values shows five significant effects at the 0.05 level and another one at the 0.10 level.\n",
        "\n",
        ">A normal probability plot of effects is a useful graphical tool to determine significant effects. The graph below shows that there are nine terms in the model that can be assumed to be noise. That would leave six terms to be included in the model. Whereas the output above shows a $p$-value of 0.0836 for the interaction of Bands (b) and Length (l), the normal plot suggests we treat this interaction as significant.\n",
        "\n"
      ],
      "metadata": {
        "id": "TaQl6iE9Em6y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate normal probability plot of the effects.\n",
        "## Save parameters in a vector, but remove intercept and the two largest\n",
        "## parameters (b & l).\n",
        "qef = q$coef\n",
        "ex = c(1,4,5)\n",
        "qef = qef[-ex]\n",
        "\n",
        "## Sort effects and save labels.\n",
        "sef = qef[order(qef)]\n",
        "qlab = names(sef)\n",
        "\n",
        "## Leave off the two largest effects, b & l.\n",
        "#large = c(1,2)\n",
        "#sef = sef[-large]\n",
        "#qlab = qlab[-large]\n",
        "\n",
        "## Generate theoretical quantiles.\n",
        "ip = ppoints(length(sef))\n",
        "zp = qnorm(ip)\n",
        "\n",
        "## Generate normal probability plot of all effects (excluding the\n",
        "## intercept).  Bands and length are not shown.\n",
        "par(bg=rgb(1,1,1))\n",
        "plot(zp,sef, \n",
        "     ylab=\"Parameter Estimate\", xlab=\"Theoretical Quantiles\",\n",
        "     main=\"Normal Probability Plot of Saturated Model Effects\")\n",
        "qqline(sef, col=2)\n",
        "abline(h=0, col=4)\n",
        "text(-1.5,12,\"b & l not shown\",pos=4)\n",
        "\n",
        "## Add labels for largest 4 effects (two are not shown).\n",
        "small2 = c(1:(length(sef)-3))\n",
        "text(zp[1],sef[1],label=qlab[1],pos=4,cex=1, font=2)\n",
        "text(zp[-small2],sef[-small2],label=qlab[-small2],pos=2,cex=1, font=2)\n",
        "par(mfrow=c(1,1))\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "Py1j0cHSx2ic",
        "outputId": "17a833cb-7643-46f8-ecdf-0caf2656ca73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Normal Probability Plot of Saturated Model Effects”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94\nAAAgAElEQVR4nOzdeWAV5b038DnZE5awCAgILkARcMECbghYBFEBwaWKtdorImL1qnXHitaK\nSy9ytbdW6wquZZWlAu5aFFSgioIoLiibCEgSdhKSnPePc3ve3BBCAoSTgc/nr8kzz5nze2Ym\ngfM9M89EotFoAAAAABBmSYkuAAAAAGBPCTgAAACA0BNwAAAAAKEn4AAAAABCT8ABAAAAhJ6A\nAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABCT8ABAAAA\nhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABCT8AB\nAAAAhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABC\nT8ABAAAAhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAA\nAABCT8ABAAAAhJ6AAwAAAAg9AQcAAAAQegIOACptwoQJkUgkEolkZGQkupayVUWFldpmmZ0r\n3lgdVNvC4saPH9+hQ4fMzMysrKwWLVps3bo10RXtPyZPnhw7+ikpKYmuZRf2pNSqPsl3doo6\ndQGqiIADYO976qmnIv929NFHFxUVlerwwgsvxNaeccYZCalwnym5K0rKzMw89NBDL7jggtdf\nfz3RNR4o9rNj8dFHH11wwQUff/zxtm3btm7dumTJkh1/0UrKzc0dMWJEjx49mjRpkp6enpaW\nVr9+/eOPP/6WW25ZunTpPit7/1PqvHr66ad37PPss8+W7PPUU0/t+zr30M5+fUoZMmRI/CU7\nO0Ure+oCUHHVPZUHCLuFCxeOHj368ssvT3Qh1cu2bduWLVu2bNmy8ePHDxw4MPbhIdFF7U3t\n27d/6KGHgiDY5bfKO+u5evXqpk2bFhUVffHFF0ceeWTVlVqlx6LqRjFq1KjYQnZ29h/+8If6\n9eunp6fvrPPMmTPPPffcdevWlWzMycnJycmZO3fuX/7ylzFjxvTr16+yNeyzYxSKMmImT568\n45+7qVOnJqSYxNrZKVqpU3e3VauzAmCfEXAAVLlhw4YNGDCgRo0aiS4kwXr16hX7DF9cXLxy\n5cqFCxcWFxcHQfDMM8+0a9fuhhtuSHSBe1PLli2vv/76Pek5bty4qvted58di6obxbJly2IL\nAwYMKH9X5+bmxtONjIyMc889t3Xr1tu2bZs/f/5rr71WXFy8bdu2Sy655Ntvv23QoEGlaqjS\nYxS6MmLefPPNzZs3l/xzl5+fH66Lg3bprLPOSk1NLXNV+/bt48s7O0UrfuruiWp1VgDsMwIO\ngCq3atWqkSNH3nnnnYkuJMHGjBlTp06d+I8LFiw47bTT1q5dGwTBQw89tJ8FHHtu7NixVbfx\nfXYsqm4UBQUFsYWaNWuW33Py5MmxdCMlJeWjjz465phjSq4655xzgiDYuHHjc889d+ONN1aq\nhio9RhVXTco45JBDVqxYsW3bttdee+3cc8+Nt7/99tubNm0KgqBp06YrV65MXIF7zYsvvljy\n12dndnaKVvzU3RPV5KwA2MfMwQFQhbp37x672n/EiBE//vjjLvtv2LDhvvvuO/HEE+vVq5eW\nltaoUaNevXqNGjWq1BdxzzzzTOx+727duhUWFl533XUNGjRo1KhRyVVdu3YNgmDChAnHHXdc\nVlbWYYcddscdd2zfvj0Igi+++OLss8+uW7duzZo1Tz/99M8//7zkxqPR6JgxY3r16tWwYcPU\n1NTatWufcMIJf/nLX/b6l4FHH310/PPkihUrVqxYUf7QKrWL4pKSkoIgmDRpUteuXbOzs2vX\nrv2LX/zi3XffLdWtUqOuyDYrPnnhjj379OkTiURmzZoV+7FNmzaRSOT6668fOHBgrOdRRx1V\naiPPPfdcfCN5eXnlv+OOyjwW5ajIUdjZKPZ8y0OGDIlEIm+99Vbsx5EjR8bGHvsUvaP4FBvN\nmjUrmW4EQdC/f//hw4ePHDly0qRJ5513Xrx9l+dDOaO74447YvWceOKJJd+rzLkwyz/h96SM\nmMWLFw8ZMqRVq1YZGRm1a9fu1KnT//zP/xQWFpbaRaNHj+7YsWONGjXq1avXu3fvefPm7cZt\nSscff3xycnIQBFOmTCnZHrs/JTk5uUOHDmW+sFK/1JUqtYLD3+t2dor++te/Lv/UrWDBK1eu\nvOGGG9q2bVujRo3MzMx27drddtttsYAy2NVZUVhY+MQTT/To0SN2UjVs2LBTp07333//Tz/9\nVKX7BGAfiQKwtz355JOxv7GXX375hRdeGFsePHhwvMPzzz8fa+zVq1e8cf78+U2bNi3zb/VJ\nJ530008/xXu+9NJLsfZjjjlm5MiRseXk5ORoNDpmzJjYj0cdddS4ceNK/df/6quvXrJkyUEH\nHVSysUGDBnl5efGNX3zxxWXW0KdPn+Li4lif8ePHxxrT09MruCuCIMjNzS21tuR3jJ9//nn5\nQ6vULopXWLNmzccee6xU56SkpFdeeaVkJZUadUW2WeYuqmBj7969d6zkuuuui39iCYJg8eLF\nJev/5S9/GWv/5S9/ubeOxc6OcgWPws5GsbPyKr7lK6+8ssw+GzduLHOzjz76aKxDUlLSjBkz\nyikgbpfnQzmj+/3vfx/78YQTTii5zUmTJsXa4+dzdFcn/J6UEY1GJ06cWGa+1r17961bt8Zr\n2PG6lfT09DvuuGPHassUP69+/etfxzKdevXqFRYWxjsccsghQRCcdNJJ559/fqznk08+GV9b\n8V/qypZakeHvrT9lpezsFN3ZAY2duhU8Xm+//XZ2dvaO3Ro1avTZZ59Fyz0rCgoKTj311DJr\nOOKII7755pvyxwVQ/Qk4APa++H+FL7zwwm+//TYtLS0IguTk5NjnxmhZAUdOTk78f/mHH374\nY489Nnny5FtvvTX+ZW/v3r3j24//p/ywww5r1qxZampq+/btW7duXXJV48aNDznkkLPPPvua\na66J/284PT39zDPPbNKkyXXXXXfCCSfE/2v70EMPxbb8j3/8I9aSlJT06KOPLliw4Omnn47X\nMG7cuFIF7OGngj/+8Y+xVZFIZN26deUPbfd2UXp6eq1atQYNGvT3v//9v/7rv+K7olmzZvn5\n+bs96l1uc08Cjs8//7zkd+Avvvjie++9t2TJkmg02rZt21jj/fffH99CQUFBvIZSwc1eORYl\nq634UShnFGWq+Ja/+eab9957r2PHjrH2AQMGvPfee++9915RUVGZW168eHHsyoIgCJKTk886\n66zHH3/8888/j0dXpVTkfChndJUKOMo54fewjCVLlmRmZsbab7755sWLF8+dO7dbt26xlqFD\nh8YK+Oijj+Iv7969+8svvzx16tQzzjgj/kYVDzguuOCCu+66K7b89ttvx9b+61//irXcdddd\n/fv3jy3HA45K/VJXqtQKDr+KAo6dnaJfffXVzk7dCha8atWqevXqxRq7des2YcKEF154IT7x\nR+vWrbdv317OWRFPZo888si///3vs2fPfvXVV+PXLnXr1q38cQFUfwIOgL0v/l/h8847LxqN\nxq8Njv9nfceA4+6774611K5de+XKlfFNxXsGQTBv3rxYY/w/5UEQtGrVavny5fH+JVfFv8yf\nOHFivDEjI+Pbb7+NRqP5+fmtW7eONfbt2zfW85FHHundu3fv3r1LftN+9tlnx7pdeumlpd5l\nTz4VfPrpp/Xr14+t6tChwy6Httu7aMiQIfHOEyZMiLdPnz5990ZdkW3uScARjUZXrVoV3+YX\nX3wRb49/yd+pU6d4Y/yK94YNG27fvn2vH4uShVXqKOxsFGWq1Jaj0ehpp50Wa7zxxhvL33I0\nGr3vvvuCHdStW7dv375PPPHEhg0bSnau4Pmws9HtXsAR7HDC72EZ11xzTazx1FNPjTeuXbs2\nNu9DrVq1YhcFXHHFFbFuDRo02LRpU6zb9u3b48/dqHjAcd55582ZMye2HK85HnnMmTMn/pya\neMBRqYNeqVIrOPzd+1N21lln9SvLFVdcUfIlOztFy2yvYMFDhw6NdTvooIM2b94c67ZmzZp4\nODJhwoTozs+K//iP/4g1jhw5Mt5YUFBw0UUXXXPNNQ888MDOUkKAsDAHB0CVGzZsWGxGumnT\npr399ttl9nn55ZdjC+eee26TJk3i7RdddFHdunVjy9OnT9/xhXfffXfsCvAd3XzzzbGFvn37\nxh9DeM455xxxxBFBEKSlpfXt2zfWuHz58tjC1Vdf/corr7zyyisPP/xwfDuHHnpobKEi04iU\n4+KLL+7fv3///v379evXoUOHDh06xB/bGb/IvJyh7fYuuvrqq+PL/fv3r127dmz5ww8/jHeo\n7Kh3uc0qcumll8YuCJo7d278qL3yyiuxhYsvvniXT6WN96zUsYjb7aOwS1W35SAIhg4dOmPG\njC5dupS8aSs3N/cf//jH4MGDmzdvPnr06Hh7lf4WlKPUCb+HZcyYMSO20Llz523/VrNmzZ//\n/OdBEGzcuDF2x9P7778f69a3b9/4o09SUlJ2djNF+Tp27Bi7IiN+BUFsAo6mTZvGL1soqVIH\nvVKlVnD4u2f69OlTyrInD4upYMHx63r69++flZUVW27QoMGbb745Y8aMGTNmHHvsseW8S/wv\n1Z///Ofnn39+9erVQRCkpqa+9NJLf/nLX2699dbYBEMA4eWvGECVq1evXvxrt5tuuikajZbq\nEI1G4zN9Hn300SVXJScnx7+f/OKLL3bcePfu3Xf2vvGpKFNTU+PPvyw5yWLjxo1jCxs3bow3\nvvnmm/3792/RokVGRkZsAry//OUvsVV7OM9o/FPB1KlTP/7449jMeZFI5N57741fu76zoe32\nLkpNTY3f1hHr3LJly9hy/GGNQSVHXcFtVoWDDjoovq/iVwTEA45LL720gtup7LGI2ZMTtXxV\nt+W4M844Y+bMmcuXL3/uueeuvPLKY445Jh525OXlXXbZZfEP20FV/haUY8ff5d0uIxqNfvfd\nd7Hle++9N7OEmTNnxtpjO/z777+P/diqVauSW2jXrt1uDCESicQu0/j+++8/++yzFStWfPLJ\nJ0EQ9O/ff8epQCt70CteasWHX01UsOBoNBrfGy1atCi5hZNPPvmMM84444wz4n+LynTZZZfF\nYpFly5ZdeumlBx98cMuWLQcNGvTyyy97piywfxBwAOwL1157bfPmzYMg+OSTT1544YVSX7Nv\n2bIlPk/+jg8OjH9XWTKGiElOTo4nF6Wkp6fHL1qO/RhbKPl0w9i1ACU99thjPXv2nDJlypIl\nS1JSUtq0aXPssceWmpR0r0hLS2vWrNnFF1/84Ycf3n777Tt2KDW03d5FNWrUKPWdZPxrz61b\nt8YWKjvqimyz6gwaNCi2EPtA/vXXX3/99ddBEBxzzDHxW/ErZZfHIm63j8IuVd2WS2natOkl\nl1zyt7/97dNPP122bNntt98en55j2LBhsYV99ltQ0o6/y3tSxpYtW4qLi8vvk5OTE41G42ds\n/Bwu88eKiwdkb7zxRsnLDcossuIHvVKlVnD45Xcox87m4IhHMJVVwYK3bNkSjyHiV7hUSvv2\n7adNm1YyEvr222+ffvrp8847r2XLlh988MFubBOgWhFwAOwLGRkZw4cPjy3//ve/LxVwZGVl\nxVs2bNhQ6rXxD3U7zpyfkpKyF68o3rRp00033RRb/tWvfrV27dpFixbNnz//ggsu2CvbL/mp\nID8/f9myZS+88MLxxx9fZudSQ9vtXRS7cb1ky+bNm2MLsU9QuzHqXW6zSvXo0eOwww4LguD9\n999fu3Zt/DNkxS/fCCp5LOJ2+yjsUtVtOS42O0nJlkMOOeTee++Nz666aNGirVu37sXfgvz8\n/JI/rlmzppzOpU74PSwjKysrHtw8/PDDZX4a/8Mf/lDy4cTxczhmx6NQQaeeemosRX377bdj\ns8PUqVMnPllmqSIrftArVWoFh797A6wKFSw4MzMzfpKU2gkVd+qppy5YsGD27Nl//OMfzzjj\njPjv1Pfff9+vX7/d3ixANSHgANhHfv3rX8e+YF++fHn82ZAxkUgkfjvJ/PnzS67avn37okWL\nYssl7y6pCp988smWLVtiyzfffHP8ApDFixdX6ftWxG7vovz8/JL1FxYWfvPNN7HlWEywG6Pe\n5TarVCQSGThwYBAERUVFU6ZMid2fkpycvHuTJlT2ravoRK26LS9ZsuS8885r06ZNVlZWfDbW\nkuI3asXK2PPfgvjFCD/88EPJSOXjjz+ueNl7WEYkEonfwhC/96FMsSvLgiD48ssvSxVQ8WpL\nSk1NPeuss4IgeO+99955550gCHr37p2amlpmkZU66BUvteLDryYqWHBSUlL89pxSt2u99NJL\nw4cPHz58+KuvvlqRtzvppJOGDRs2Y8aMdevWTZkyJXY9yNq1a+N3xACElIADYB+JRCIjRoyI\nLZd8hl/MueeeG1uYPHnyihUr4u2jR4+OfZMZiUTKmRxhryj5hfP27dtjC4sWLYp9SinZmBC7\nvYueeOKJ+PLLL78c/2b4lFNOCXZ31OVvc8+VnLDgp59+KrV24MCBse97R48eHZt58fTTTz/4\n4IP3yluXr1JHofxR7MmWK65Jkybvvvvul19+WVhYOGjQoIULF5Zcu2bNmvisFm3atMnIyKj4\n+bCz0cUnCl2zZs20adNiy19++WXJJ4Ps0p6X0atXr9jC+PHj41lJUVHRxRdfPHDgwKFDh65c\nuTIIgpNOOim2aurUqbm5ubHlTZs2VaraUmKHaePGjbHbQMo5apU66JUqtYLDrz4qWHAsPAqC\nYPLkyevXr48t5+bmXnPNNcOGDRs2bFhsN5Z5VmzduvX++++/7LLL+vXrF78jJjk5+eyzz+7U\nqVPsx1KXHQGEz84erwLAbiv1mNiS4v+LjYk/JjY3Nzf+uahly5Z//etfJ06cePPNN8fnzhg0\naFB8I+U82nBnq+JfDz722GPxxvhHuxYtWkSj0ZUrV8avf+7bt++CBQumTp3atGnT+NNka9eu\n/cEHH6xevXqvPCa2TOVsuVK7aOzYsbHG5OTktLS03/3ud1OmTBk5cmT8IQKtW7cuLCys1Kgr\nvs2dDaTijYWFhfEvvbt06TJu3LjXXnut5N7o3bt3yRNpzJgxu9y3e+VYVOoo7HIUJVVqy9HK\nPCb20UcfjQ889t31r3/964svvvjUU08tOQ3NU089Fa3M+bCz0X377bfxj5c1atS48sorb7rp\npnr16p188snx86f8nby3yohf99G5c+dp06a99tpr8UChXbt2sXP13Xffje+BDh06jBkz5tln\nn+3UqVP8OpSkpKTyd++Of+42btwYP2oZGRkbN26Mte/4mNhKHfRKlVrB4e/dx8TGxJ86XKnH\nxFaw4KVLl9aqVSvWeMIJJ4wdO/bFF1/s0KFDrKV58+axB+ju7KyIT9Nz3nnnTZ8+fd68eTNn\nzrz77rtjndPT01evXl3+fgCo5gQcAHtfOQHHZ599VvJO+3jAEY1G58+fH3vC4o7OPffc2LwP\nMVUUcESj0f/8z/8s9dZNmjT57rvvSj7B8a677kpIwFGpXfTCCy/E2hs2bHjvvfeW6pyRkTFr\n1qx45wqOulLb3MOAIxqNnnnmmSW337t375Jr449QCYIgOzu75Nh3Zm8di4ofhV2OopRKbbni\nAUc0Gr3vvvvKeYBucnLynXfeGe9cwfOhnNENGTKk1BZatWoVf8ppJBIpLi4ufyfvlTLGjx8f\nTwpKatq06RdffBF/o8suu6xUhxo1ajzyyCPxH4uKisrZt2X+uYtfaFDyiO8YcEQredArVWpF\nhr97f8rKt3bt2thLKhVwVPx4vfLKK2VOAXvwwQfPnz8/3q3Ms2LBggU7e6x4UlLS008/Xf5O\nAKj+3KICsE8dffTRv/nNb8pcdeyxxy5atGj48OGdOnXKzs5OTU1t3LjxOeecM3Xq1IkTJ8Yn\n2KtSI0eO/NOf/tS2bdvMzMymTZsOGjRo7ty5hx122LPPPtu6deuUlJRDDjmkTZs2+6CSMlV8\nF23bti22UK9evdtvv33UqFHt27fPyMioW7fu2Wef/eGHH8a/Tg8qPOpKbXPPPfnkk/37969T\np05GRsbhhx9eauN9+vSJP3Tjl7/85b45PWIqdaKWP4o92XKlDB06dPHixb///e9PPvnkBg0a\npKampqWlNWjQoHPnzrfddtvnn39+9913xztX/LdgZ6N75JFH7r///latWqWlpTVt2nTw4MHv\nv/9+fH6WaIkHgpRjz8s4//zzP/nkk4EDBx5++OHp6elZWVlHHXXU73//+wULFsQfwhoEwVNP\nPTVy5MjWrVunpaU1bNjw/PPP/+ijj37xi1/EO+zGxJPnnHNObGGXdxVV6qBXqtQKDr/6qGDB\nvXv3Xrhw4VVXXdWqVavYo2TbtWs3dOjQBQsWHHvssfFuZZ4VRx111Lx58+65556OHTs2atQo\nNTU1KyvryCOPHDx4cOytEzBsgL0qEv2/M4oDANXf6tWrmzdvXlBQEATB+++/37lz50RXBACQ\nYK7gAIDwGTZsWCzd6NChg3QDACAIgp3ejwoAVDcvvPDC6tWrZ82aFZ+DY/jw4YktCQCgmnCL\nCgCExqmnnvrPf/4z/uPgwYMff/zxBNYDAFB9uIIDAEKjQYMG6enpRUVFLVq0GDx48PXXX5/o\nigAAqgtXcAAAAAChZ5JRAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABCT8ABAAAA\nhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABCT8AB\nAAAAhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAAAABC\nT8ABAAAAhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPQEHAAAAEDoCTgAAACA0BNwAAAAAKEn4AAA\nAABCT8ABAAAAhJ6AAwAAAAg9AQcAAAAQegIOAAAAIPRSEl1AOHz66aeFhYWJrgIAAAASLCUl\n5dhjj010FWUQcOzavHnzOnXqlOgqAAAAoFqYO3dux44dE11FaQKOXSsoKAiCID8/Py0tLdG1\nAAAAQMIUFBSkp6fHPiZXN+bgAAAAAEJPwAEAAACEnoADAAAACD0BBwAAABB6Ag4AAAAg9AQc\nAAAAQOgJOAAAAIDQE3AAAAAAoSfgAAAAAEJPwAEAAACEnoADAAAACD0BBwAAABB6Ag4AAAAg\n9AQcAAAAQOgJOAAAAIDQE3AAAAAAoSfgAAAAAEJPwAEAAACEnoADAAAACD0BBwAAABB6Ag4A\nAAAg9AQcAAAAQOgJOAAAAIDQE3AAAAAAoSfgAAAAAEJPwAEAAACEnoADAAAACD0BBwAAABB6\nAg4AAAAg9AQcAAAAQOgJOAAAAIDQE3AAAAAAoSfgAAAAAEJPwAEAAABVZdCgQZFIJBKJfPPN\nN4muZT8n4AAAAABCT8ABAAAAhJ6AAwAAAAg9AQcAAABUuaSkpNGjR7dt2zYjI6NVq1Z/+9vf\nEl3R/iYl0QUAAADA/m/s2LG33357bPmbb7656qqrGjdu3K9fv3Jesnr16rfeeuvLL7/Mzs7+\n+c9/3q1bt6QklynslF0DAAAAVe6hhx56/PHHP/vss4EDB8Za/vznP5ff/7DDDrvxxhtnz579\n0ksvnXHGGR06dPjqq6/2SbGhJOAAAACAKnfllVcOHjz46KOP/utf/1q7du0gCBYtWrSzzk88\n8cTQoUMff/zxlStXvvnmm//617+WLVvWtGnTHj165OXl7cOqw0TAAQAAAFXuzDPPjC1kZGT8\n7Gc/C4Jg3bp1ZfYsKCi4/fbbH3jggUsvvTR+T0qjRo0mTpyYkZHx8MMP75uCQ0fAAQAAAFWu\nYcOG8eUaNWoEQRCNRsvsOWfOnLy8vPidLHHp6emXXHLJq6++WnVFhpqAAwAAAKqR1atX16lT\nJ3YbSynNmzf/8ccf931JoSDgAAAAgGqkfv3669ev37p1646rfvzxx/r16+/7kkJBwAEAAADV\nyAknnJCRkTF27NhS7cXFxX//+99PO+20hFRV/Qk4AAAAoBrJzMy8/fbbr7/++rfeeiveuHXr\n1iuuuGL58uW/+93vElhbdZaS6AIAAACA/+O222776aefevbsedxxxx199NG5ubmzZ8/OyMiY\nPn1648aNE11dNRXZ2aytxM2ePbtz5875+flpaWmJrgUAAIADxcKFC6dPn75o0aJ69eq1b9/+\n/PPPz8rKSmxJBQUF6enps2bNOvnkkxNbyY5cwQEAAADV0VFHHXXUUUcluorQMAcHAAAAEHoC\nDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEHAAAA\nEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEH\nAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAI\nPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMA\nAAAIPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISe\ngAMAAAAIPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAA\nAISegAMAAAAIPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4OIAMGDAgEomsWLFiP3uv3TNo0KBI\nJPLNN98kuhAAAIC9QMABFTJ69Ohjjz22Zs2ahx566I033rhly5ZEVxQ88MAD4s33kwsAACAA\nSURBVAkAAIAYAQfs2pQpUy677LIuXbpMmzbt1ltvfeyxx2644YbElrRq1aqhQ4cKOAAA9o2c\nnJwbbrihZcuW6enp9evX79ev32effZboooD/IyXRBUAIjBs3rkWLFo888kgQBN26dfvss8+m\nTp36t7/9LYElzZ07N4HvDgBwQPnpp59OPPHEb7/9Njk5uW3btitWrJg6deqbb7757rvvdurU\nqZwXFhYWzpo16/PPPw+CoF27dp07d05J8REMqoorODjgFBQU3HjjjU2bNk1PTz/yyCMfffTR\nXb5k/fr1NWvWjP+4ePHi2rVr70kNv/rVryKRyKZNm2699dbDDjssPT29WbNmDz30UDQajfdZ\nunTpZZdd1rRp07S0tIMOOujss8+eM2dObFWfPn369esXBMGZZ54ZiUTef//9Mt8lPz9/xIgR\nxx57bHZ2dq1atY455pgRI0YUFxeX7JOUlPSnP/3piCOOSE9Pb968+T333FPBGpo2bXrMMceU\n3FS7du0ikcj06dPjLX//+98jkcgLL7xQkfECAFRbt91227fffhsEwfTp0z/77LOlS5f+/Oc/\n37JlyzXXXFPOq2bNmtW6deuePXs++uijjz76aM+ePY888sjZs2fvq6rhgCPg4IBz7bXXzp07\n95prrrntttu2b99+9dVXP/XUU+W/5Jhjjlm8ePHGjRtzc3MHDhw4c+bMESNG7EkNaWlpQRCc\nf/75GzZsGDNmzDvvvNO2bdsbbrhh9OjRsQ7Lly8//vjjJ0yYcPHFFz/55JM33HDDxx9/3LVr\n11iWcccdd1xyySVBENx5552TJk1q27Ztme9y1VVX3XLLLUcdddSf/vSnBx98sGXLlrfccsu1\n115bss/w4cPHjh07ePDg4cOHxzY4ZsyYitTQs2fPhQsX5ubmxjqvWbNm0aJFNWvW/Oc//xnf\n+LvvvhuJRHr27LnL8QIAVFvbt28fO3ZsEATt27c//fTTgyCoVavWddddFwTBnDlzlixZUuar\nFixY0KtXrx49eqxevXrhwoULFy5cvXr1L37xi169esUu6AD2vii7MmvWrCAI8vPzE10Ie+rC\nCy8MgqBLly5FRUWxlu+//z4tLe3www8v/4Xz588PgqB79+61atVq1qzZ9OnTK/hey5cvL3Pt\n5ZdfHgTBRRddFG+JfSfQp0+f2I+/+c1vgiB4+eWX4x0WLVqUnJx84oknxn68//77gyCYMWNG\nOTVkZWWddNJJJVt+97vfnXfeeYWFhfEaTjnllIKCgtjaf/3rX0EQnH322RWp4YUXXgiCYOrU\nqbFVY8aMSUlJueyyy+IVRqPRn/3sZ+3bt6/IeAEAqq3FixfHPjo1bNiw97+ddNJJscYJEyaU\n+ao+ffrE/1sVV1xc3Lt37379+lV91VBV8vPzgyCYNWtWogspgxvAOOAMGTIkKel/r1069NBD\nO3fu/M477yxfvrxZs2Zl9l+6dGksTXj77bf//Oc/X3nllenp6UEQfPnllw0aNKhfv/5uVxJL\nEGKOOOKIrKys2GNlo9Ho5MmTGzVq1L9//3iHNm3anHTSSe+///66desq+KapqalLly5ds2ZN\nw4YNYy3//d//XarPjTfemJqaGls+7rjjkpOTf/jhh4rU0KNHj0gkMnPmzL59+wZB8M477xx9\n9NG/+MUvnn/++c2bN9eoUWPVqlVfffXVrbfeusvxAgBUZxs3bowtrFmzZtq0aaXWrlmzZseX\n5Ofnv/7661OnTi3VHolEfvvb35577rnbt2+P/x8M2FvcosIBp9TMEUcccUQQBEuXLi2z88cf\nf9yxY8cPP/zwnnvuSUpK+uGHH2LpRhAEV1xxxTnnnLMnlTRv3rzkj6mpqdu3bw+C4Mcff1y/\nfn1sSouSHVq3bh0EwVdffVXB7f/xj3/84YcfWrVqdemll44aNWrlypU79mnVqlV8ORKJ1KxZ\nc+vWrRWpoVGjRkcfffR7770Xa3/nnXe6du3atWvXwsLCDz74INYSBEHsMs7yxwsAUJ3FJ1/r\n27fvjt8YX3XVVTu+5KeffiooKIj9P7OUFi1a5Ofnr1u3rmqLhgOSgIMDTqn5QbOysoIg2LZt\n2449i4qKLr300tq1a8+bN++OO+649tprR44c+emnnwZB8OOPP86ePftXv/rVnlSys9h+8+bN\nQRDUqFGjVHtmZmZ8bUVce+21b731Vvfu3V9++eWBAwc2a9asd+/epaKceF6zGzX07NnzX//6\n1+bNm3/44YevvvqqW7duhx56aLNmzWLTcLz77rs1atQ45ZRTdjleAIDq7IgjjojNN79gwYLo\nv6dI37p164YNG3b2kuzs7Egk8tNPP+24au3atZFIJDs7u4qqhQOZgIMDTuwKhbgtW7YE/445\nSvniiy8+//zz3/72twcddFAQBMOHDz/88MPPP//8vLy8//qv/8rMzLzggguqosLYv6A7Bhmx\nllq1alV8U927d580adK6deveeOONSy+9dMaMGT169CgoKNgrNfTs2TN2vcY777wTiUS6dOkS\nBMEpp5wyc+bMIAjefffdbt26xaYXBQAIr+Tk5Nj0at9///2DDz5YXFy8bdu2iy++ODs7u27d\numWmGDVr1uzYseO4ceN2XDVu3Ljjjz8+9qURsHcJODjgfPHFFyV/jM12WeYFhLFHhMSzjxo1\nakyePPnHH3/s16/fo48+esstt9SrV68qKjz44IPr1av3xRdfRP/vU1QXLVoUiURiN4lUSnp6\neo8ePUaPHj1kyJBvvvkmNmfqntfQtWvX9PT0999//5133mnXrl0sBurSpctHH3303Xffff31\n17169apsqQAA1dB999136KGHBkFwyy23ZGdn169ff9KkSUEQPPjgg7H/Au1o2LBhjzzyyIsv\nvliy8fnnn3/ssceGDRu2D2qGA5CAgwPOM888E19esWLF7Nmz27Zte/DBB+/Ys23btklJSc8/\n/3xhYWG85bbbbps5c2Y0Gi3/sed76Nxzz121atWUKVPiLfPnz58zZ0737t3r1KkTBEFycnKw\nw9UoJX344YdNmzZ97rnnSjbGZlet4K0iu6whMzOzc+fOH3744TvvvNOtW7dYny5duuTn5z/0\n0EPB/52AAwAgvBo2bDhnzpyrr776sMMOy8/PT0lJOe2001599dXYo+LK1Ldv35EjR1522WUd\nO3a86qqrrrrqqg4dOlx++eUPPfRQ796992XxcODwFBUOOPn5+eecc86ZZ565ZcuWJ554oqCg\nYGchev369a+55pr/+Z//ad++/XnnnVe3bt0PPvhg4sSJDRs2XLNmTbdu3S688MK0tLQbbrgh\nJWUv/yrdfffdr7zyyiWXXHLttde2bt36+++//+tf/1qzZs34Y1Bil5w88MAD3333XZcuXTp1\n6lRqCx07dqxXr94VV1zx/vvvt2/fPhKJzJs3b/To0aecckr79u33Sg1BEPTs2fPee+/dtGlT\nPOBo165dvXr1Ro0a1bx58yOPPHIv7AsAgGqgYcOGjzzyyCOPPFLxl1x77bVnnnnmmDFjFi5c\nGARB//79x44d27JlyyqrEQ54+/KZtCE1a9asIAjy8/MTXQh7ql+/fkEQ5OTkXH/99Y0bN05L\nS2vTps2oUaPKeUlxcfHjjz/esWPHrKyszMzMY445Zvjw4Zs2bXrppZeOPvro1NTURo0alXlu\nxG7UXL58eZmbjYX9X3/9dcnG7Ozsdu3axX9ctmzZZZdd1rhx45SUlIYNGw4YMGDRokXxtQUF\nBeedd15mZmbdunXHjx9f5rusW7fu+uuvb9GiRVZWVnZ29rHHHnvfffdt3Lhxb9UQjUbnzZsX\n+0vy448/xhtjD44dNGhQpcYLAABUf/n5+UEQzJo1K9GFlCES/b832LOj2bNnd+7cOT8/33SJ\nAAAAHMgKCgrS09NnzZp18sknJ7qW0szBAQAAAISegAMAAAAIPQEHAAAAEHoCDgAAACD0BBwA\nAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEHAAAAEHoCDgAAACD0\nBBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEHAAAAEHoCDgAA\nACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEHAAAAEHoC\nDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEHAAAA\nEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAIPQEH\nAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMAAAAI\nPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISegAMA\nAAAIPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAAAISe\ngAMAAAAIPQEHAAAAEHoCDgAAACD0BBwAAABA6Ak4AAAAgNATcAAAAAChJ+AAAAAAQk/AAQAA\nAISegAMAAAAIPQEHAAAAEHoCDgAAACD0UhJdQKVFo9HvvvtuyZIlGzduDIIgOzu7VatWzZo1\nS3RdAAAAQMKEKeDIzc299957n3/++TVr1pRa1bx580GDBt10002ZmZkJqQ0AAABIoNAEHKtW\nrercufN3333XqlWrs84669BDD61Ro0YQBBs2bPj222//+c9/3nnnnRMnTnznnXfq1q2b6GIB\nAACAfSo0AcewYcNWrFgxbty4X/7ylzuuLSoqevzxx6+55pq777774Ycf3vflAQAAAAkUmklG\np02bdskll5SZbgRBkJyc/Nvf/vaCCy54+eWX93FhAAAAQMKFJuBYt25dixYtyu/Tpk2b1atX\n75t6AAAAgOojNAFHkyZNPv300/L7fPLJJ02aNNk39QAAAADVR2gCjv79+48fP/7BBx/Mz8/f\nce3mzZvvuuuuKVOmXHjhhfu+NgAAACCxItFoNNE1VEheXt5pp5328ccf16pV6/jjj2/WrFnN\nmjWj0eimTZuWLl06Z86cLVu2dOnSZfr06TVr1ty7bz179uzOnTvn5+enpaXt3S0DAABAiBQU\nFDSqlT3tnbdOPvnkRNdSWmieolKnTp0PPvjgr3/963PPPffuu+8WFRXFV6Wmpnbo0GHgwIED\nBw5MTk5OYJEAAACwvypcsy5n9MSb252Y6ELKFporOEratm3b8uXLN27cGARB7dq1mzdvvtvX\nVnz//fcnnnhiQUFBOX22b9++adOmLVu2ZGZm7t67AAAAQHhF8wvWT35j/ZQ3Uw8/5LS/3v/0\n9KnV8AqOUAYcO7Nu3brc3NyWLVtW/CVFRUXTpk0rc16PuDfeeOPJJ5/cuHHjXr/5BQAAAKq5\nLfMW5DwzIbq9sO6vz047sX16RsasWbOqYcARmltUKmLEiBF/+tOfKhXZJCcnn3322eX3ycnJ\nefLJJ/esNAAAAAiZ7StX54yasG3BV7V6dalzUZ+kzIzyb4BIrP0q4AAAAAD2XPHmrXljp214\nbWZmu1ZNRg5NPeTgRFe0awIOAAAA4N+i0U0z5+Q+NzkpK6PhLYOzOhyV6IIqKjQBR8eOHXfZ\nZ+XKlfugEgAAANgv5X+zNOfp8QXLfsju1yP7nNMjqaEJDYIQBRyffPJJEASpqanl9CksLNxX\n5QAAAMD+oyhnfe6LUzbNnFvjxPYNbrw85aC6ia6o0pISXUBF3XzzzTVq1Fi4cOG2nbvpppsS\nXSYAAACESbSoaMO0d1ded0/B8lWN7/ldSNONIERXcNxzzz2vv/76RRddNHv27PKv4wAAAAAq\nYutni3OeGV+Ut6HOgD61z+waJIXmMogdhab01NTUF1988fPPP7/99tsTXQsAAACE2/ZVa1ff\n/7fV9/41o02LQ/5yV+3ep4Y63QhCdAVHEARt2rT58ccfy5lo48wzz6xTp86+LAkAAADCJZpf\nsH7Km+snvZ7e+ogmI25La94k0RXtHWEKOIIgqF27djlru3Xr1q1bt31WDAAAAIRJNLr5w/m5\nz74cRKP1h1xUs9sJiS5obwpZwAEAAADshoIly9c9M75gyfLs/j2z+/eMpO1vs1sKOAAAAGB/\nVrxxc974GRtenZl1XNumD9+R0rB+oiuqEgIOAAAA2D9Fi4o3vjozb+y05Lq1G91+VWb7Nomu\nqAoJOAAAAGA/tG3BVzmjJhSuy6tzYe9aZ3SNJIf7ISm7JOAAAACA/Urhury8l6Zumjm3ZtdO\nje76z+TsWomuaF8QcAAAAMB+4t+PgH0j7dAmje+7Mb3VYYmuaN8RcAAAAMD+YMu8BTnPTIgW\nFtYfMqBm1+ODSCTRFe1TAg4AAAAIt+0rV+c8M2Hbwq9q9epS56I+SZkZia4oAQQcAAAAEFbF\nm7fkjZ2+4bWZme1aNRk5NPWQgxNdUcIIOAAAACCEotFNM+fkPjspqUZmo1sGZ3Y4KtEFJZiA\nAwAAAEIm/5ulOU+NK1i+Krtfj+xzTo+k+nQv4AAAAIDwKMpZn/vilNgjYBvedmVyndqJrqi6\nEHAAAABACEQLiza+9l7emFdSGjdsPPx36a2PSHRF1YuAAwAAAKq7LfMW5IyaWLxla50BfWqf\n2TVISkp0RdWOgAMAAACqr+2r1uaMmrD10y9q9+paZ0DvpKzMRFdUTQk4AAAAoDqK5hesn/Lm\n+kmvpx95RJMRt6U1b5Loiqo1AQcAAABUM7FHwD4/JZKSXH/IRTW7nZDogkJAwAEAAADVSMGS\nZeuenlDw/Yrsfj2yz+kZSU1NdEXhIOAAAACAaqF44+a88TM2zPhn1s/bNX34jpQG9RJdUZgI\nOAAAACDBokVFG199L2/stOR62Y3u+G3msW0SXVH4CDgAAAAgkbYt+GrdM+OLctbXubC3R8Du\nNgEHAAAAJEbhT7l5f//Hpplza3btVPfu65Jr10x0RSEm4AAAAIB97d+PgH0jvdWhTUbclnZY\n00RXFHoCDgAAANintsxbkPP0+GhRUf0hA2p2PT6IRBJd0f5AwAEAAAD7SMH3K3KemZD/1Xe1\nTu9S56I+SZkZia5o/yHgAAAAgCpXvHlL3tjpG16dmXVc26Z/HpbS6KBEV7S/EXAAAABAVYpG\nN82ck/vspKSaWY1uuzLz5+0SXdD+ScABAAAAVWXboq9znpmwfdXa7H49ss85PZLqY3hVsWcB\nAABg7yvKyct9cWrsEbCN7rgmuU6tRFe0nxNwAAAAwN4ULSza+Np7eWNeSWncsPG9N6T/7PBE\nV3RAEHAAAADAXrNl3oKcUROLt2ytM6BP7bO6eQTsPiPgAAAAgL1g+w9rckZP3Pbpl7V6dakz\noHdSVmaiKzqwCDgAAABgjxRvy98w9a31L7+W3qZlkwdvS23WONEVHYgEHAAAALC7Yo+AfX5y\nJCP9oOv+o8ZJxyW6oAOXgAMAAAB2R/63y3KeHl+wdGV2vx7Z5/SMpKYmuqIDmoADAAAAKqco\nb0Pe2Gkb35yd9fN2TR++I6VBvURXhIADAAAAKixaVLTx1ffyxryS0uigg/94fUabFomuiP8l\n4AAAAIAK2bZg8bpnJhTlrK8zoE/tM7sGSUmJroj/T8ABAAAAu1D440+5L07Z/OH8ml071b37\nuuTaNRNdEaUJOAAAAGCnovkF66e8uX7SG+mtDmvy4G1phzZNdEWUTcABAAAAZdsyb0HO0+Oj\nRcX1hwyo2fX4IBJJdEXslIADAAAASiv4fkXO0+Pzv/6+1uld6vyqb1JGeqIrYhcEHAAAAPD/\nFW/akjdu+oZXZ2Yd17bpn4elNDoo0RVRIQIOAAAACIIgCKLRTTPn5I6elFQrq9HQIZnHtU10\nQVSCgAMAAACCbYu+znl6QuFPOdnnnF67T/dISnKiK6JyBBwAAAAc0Ipy8nJfnLpp5tyaXTs1\nGnZNcp1aia6I3SHgAAAA4AAVLdi+Yfq76ye8mtq0UeN7b0j/2eGJrojdJ+AAAADgQLRl3oKc\nZyZEtxfW/c25tXqc7BGwYSfgAAAA4MCy/YfVOaMmbvtsca1eXepc1CcpMyPRFbEXCDgAAAA4\nUBRv3rp+0usbXnk7vU3LJg/eltqscaIrYq8RcAAAAHAAiD0C9vnJSRkZB133HzVOOi7RBbGX\nCTgAAADYz+V/uyzn6XEFS3/I7tcj+5yekdTURFfE3ifgAAAAYL9VlLs+b9z0jW/Ozvp5u6Z/\nHpZyUN1EV0RVEXAAAACwH4oWFW189b28Ma+kHHzQwfdcn3Fki0RXRNUScAAAALC/2frZ4pxn\nxhflbagzoE/tM7sGSUmJrogqJ+AAAABg/7H9x7V5L07dPOfTWt1PqvOrvsm1aia6IvYRAQcA\nAAD7g2h+wfopb66f9Eb6zw5r8l+3ph3aNNEVsU8JOAAAAAi5aHTzh/Nzn305WhytP2RAza7H\nB5FIomtiXxNwAAAAEGIF363IeXp8/pJltc86Nfv8M5Iy0hNdEYkh4AAAACCUijdtyRs3fcOr\nM7OOa9v04TtSGtZPdEUkkoADAACAkIkWFW96+4O8l/6RVKtGo6FDMo9rm+iKSDwBBwAAAGGy\n7fOvc54eX7guN/uc02v36R5JSU50RVQLAg4AAADCoXBdXt5LUzfNnFuza6dGd/5ncp1aia6I\nakTAAQAAQHUXLdi+Yfq76ye8mnrIwY3vvSH9Z4cnuiKqHQEHAAAA1dqWeQtynpkQ3V5Y9zfn\n1upxskfAUiYBBwAAANXU9h9W54yauO2zxbV6dalzUZ+kzIxEV0T1JeAAAACg2inevHX9pNc3\nvPJ2RtuWTUYOTT3k4ERXRHUn4AAAAKA6iUY3zZyT+9zkpMyMBjdfkdXhqEQXRDgIOAAAAKgu\n8r9ZmvPM+IKlP2T365F9zumRVB9aqSjnCgAAAIlXlLs+94Upm2bOrXFi+wY3XJ5yUN1EV0TI\nCDgAAABIpGhR0cZX38sb80rKwQcdfM/1GUe2SHRFhJKAAwAAgITZ+tninGfGF+VtqDOgT+0z\nuwZJSYmuiLAScAAAAJAA239cmztq4pb5i2p1P6nOr/om16qZ6IoINwEHAAAA+1Q0v2D9lDfX\nT3o9vfURTUbclta8SaIrYn8g4AAAAGBfiUY3fzg/99mXg2i0/pCLanY7IdEFsf8QcAAAALAv\nFCxZvu6Z8QVLltc+69Ts889IykhPdEXsVwQcAAAAVK3iTVvyxk3f8OrMrOPaNn34jpSG9RNd\nEfshAQcAAABVJVpUvOntD3Jfmppcq2aj26/KbN8m0RWx3xJwAAAAUCW2Lfwq55kJhety61zQ\nu9YZXSPJHgFLFRJwAAAAsJcVrsvLe2nqpplza3bt1Oiu/0zOrpXoitj/CTgAAADYa6IF29dP\nfmP95DfSmjdpfN+N6a0OS3RFHCgEHAAAAOwdW+YtyHlmQrSwsP6VA2p2PT6IRBJdEQcQAQcA\nAAB7avvK1TmjJmxb8FWtXl3qXNQnKTMj0RVxwBFwAAAAsPuKN2/JGzt9w2szM9u1ajJyaOoh\nBye6Ig5QAg4AAAB2SzS6aeac3OcmJ2VlNLplcGaHoxJdEAc0AQcAAACVlv/N0pynxxcs+yG7\nX4/sc06PpPp0SYI5BQEAAKiEopz1uS9O2TRzbo0T2ze48fKUg+omuiIIAgEHAAAAFRQtKtr4\n6nt5Y15Jadyg8T2/Sz/yiERXBP9fUqILAAAA9sigQYMikUgkEvnmm2/2pA+Ub+tni3+48f68\nCTPqDOjT5IGbpRtUN67gAAAAoDzbV63NGT1x6/xFtXt1rTOgd1JWZqIrgjIIOAAAAChbNL9g\n/ZQ31096Pb31EU1G3JbWvEmiK4KdEnAAAACwg2h084fzc599OYhG6w+5qGa3ExJdEOyCOTgA\nAGA/EYlERowY0apVq4yMjJ/97Gd/+9vfEl0RYVWwZPmqOx766ZHna3Y/qekjd0k3CAVXcAAA\nwH7i3nvvHTVqVFJSUnFx8ddff33VVVclJSUNHjy4UhvJycl5++23Fy1aVLt27WOPPbZbt25J\nSb4WPYAUb9ycN37GhldnZh3XtulDv09pWD/RFUFF+VMFAAD7iTfeeOPTTz/dtm3bs88+G4lE\ngiC48847i4qKKr6Fp59++tBDD73yyivfeuut55577owzzmjfvv2iRYuqrGSqkWhR8YZp7664\n+g9bP/2i0e1XNRw6RLpBuAg4AABgP3H77bcfc8wxqampl156adeuXYMgWL169cKFCyv48rFj\nxw4ZMuSBBx5YvXr1P//5z48//njFihVHHHFEjx491q5dW5WFk3jbFny16uYH8sZNr3Nh7yb/\n/fvM9m0SXRFUmoADAAD2E507d44vd+jQIbawcuXKiry2uLj45ptvHjZs2NVXX52S8r93sjdo\n0GD8+P/H3r2HRVkn/B+/5wDDwAwzCgIDng+ZaAUaVhbYYwqJJGGuorXZto+Fltlpn8DDVlpt\nv9V2bbf1WreErDwBpigqqbk5ZiJgoliuh/WIiiLDDAyngeH+/UFrrmkDNsPNDO/XX+M94/De\na3cVP8zMNysgIGDRokVOr0UH0XSl8spfPylb8FfvPt3D/jLff9yDMgX/ToRb4n+4AAAAgIfQ\n6/VXb3fp0qXlhslkas3vLSkpOXfu3E8/sMPLy+s3v/nNli1bnBWJjkNssJkzt5yftaDx/CXD\nH14NnPWkQqeVOgq4dXzIKAAAAOAhqqqqrt62Wq0tN7p169aa31tWVqZSqUJCQn56V69evcrK\nypxSiI6jtqjElJ4tNjUFpCRrYoYLMpnURcAvxcABAAAAeIj8/PwhQ4a03N6/f3/LjR49erTm\n93bt2rWhocFsNl/7MpAWly5d6tq1qxM7Ia3G85dM6dn1h49p46L1UxLkpRJ0bQAAIABJREFU\nah+piwDn4C0qAAAAgIdYsGDBd99919zc/Mknn3z55ZeCIPTq1WvQoFZ9WmRERERAQMCqVauu\nuy6K4urVqx966CHn56LdNdfUmtKzz7/8tiA2h/5pTtenJ7JuwJPwCg4AAADAvTU2NrbcuPvu\nu4cMGaJSqRoaGlqu/PGPf5S17q0HXl5e8+bNe+211/r16xcXF3f1mX/3u98VFxevWLHCFeVo\nP6JoNRZUrlgv91MHv/aseuhgqYMA52PgAAAAANxbfX19y42PP/44PDw8IyPjypUrAwcOnDt3\n7qRJk1r/PLNnz758+fLYsWMjIyMjIiKqqqq++eabpqamjRs39u3b1zXtaA8NJ86YPsq0nbuo\nSxytS4qVefHPQHgmmSiKUjd0dMuWLUtJSamurtZoNFK3AAAAAK713Xffbdq06ciRIxqNJiIi\nYvLkyf7+/lJH4RbZTZbKlTlWY6EmJqrLrx9V6PmvEr+UzWZTqVR79uwZMWKE1C3XY7oDAAAA\n8KPBgwcPHsz7F9ye2GSv/mK3eU2u0hBkeOsl1UBegwPPx8ABAAAAAB6ltqjElLGuubZOn5zg\nPzZGkHO4BDoFBg4AAAAA8BCNFy6bPl5Xf/Bf2rhoffI4ua9a6iKg/TBwAAAAAIDbExtslpwd\nlvXbVLf3NSx6zbtnqNRFQHtj4AAAAAAAd9ZyBOynOTKlIiBlimbkPVIHAdJg4AAAAAAAd2U7\nebZiebbtdKkucbQuaYzMy0vqIkAyDBwAAAAA4H6aq2vMWVurtu7yHTo4bMk8ZbeuUhcBEmPg\nAAAAAAB3Itrt1Xm7zWs3K7rqgufNVN81SOoioENg4AAAAAAAt1FfcqwiPctusugnj+MIWOBa\nDBwAAAAA4AaarlSaV2+yGgs1MVFd3pyt8NdIXQR0LAwcAAAAANCh/ecI2O2qAb1CF6V69w6T\nugjoiBg4AAAAAKDjqi0qMS3PEu3NASnJmpjhgkwmdRHQQTFwAAAAAEBHZDtdalqe1XD8tDY2\nWj8lQa72kboI6NAYOAAAAACgY2muqTWv3VKVZ/SNDA97f74yOFDqIsANMHAAAAAAQIchilZj\nQeWK9XKNb3Dqs+qhg6UOAtwGAwcAAAAAdAj13x83pWc3XizXJY7WJcXKvPj3GtAG/B8GAAAA\nACRmN5krV25sOQI2eN7zCr1W6iLA/TBwAAAAAIBkxCZ79Re7zWtylYYgw9svq27rI3UR4K4Y\nOAAAAABAGrVFJaaMdc21dfrkBP/4kRwBC/wSDBwAAAAA0N4aL1w2ZWTXHzqqjYvWJ4+T+6ql\nLgLcHgMHAAAAALSf5vqGqo1fWj7/QjWof+jiVK8eBqmLAA/BwAEAAAAA7aLlCNhPN8h8VIGz\nn/K7L1LqIMCjMHAAAAAAgMs1/PusaXmW7cx5XeJoXdIYmZeX1EWAp2HgAAAAAAAXspurzGs3\nV+/4xnfo4LAl85TdukpdBHgmBg4AAAAAcAnRbq/O221ek6sMDgxZ8KLPoH5SFwGejIEDAAAA\nAJyvvuRoRXq2vdKiT07wHxsjyOVSFwEejoEDAAAAAJypqexK5cqcmvxiTUxUl2mzFf4aqYuA\nToGBAwAAAACcQ2ywWXJ2WNZvVw3oHbo41btXmNRFQCfCwAEAAAAATlBbVGL6KFNsFgNSkjUx\nwwWZTOoioHNh4AAAAACAX8R2qtSUntVw/LQ2Nlo/9RG5j0rqIqAzYuAAAAAAgFvUbK01Z26p\nyjP6RoaH/eX3yqAAqYuAzouBAwAAAADaThStxoLKj9fLtb7BaSnqyHCpg4DOjoEDAAAAANqm\n/vvjpuXZTVdMuqRY/4RRMqVC6iIADBwAAAAA0Gp2k7ly5UarsVATExU8/3mFXit1EYAfMHAA\nAAAAgGOirbFqy1eW7DyvsGDD2y+rbusjdRGA/8LAAQAAAAAO1BaVmNKzxcamLtMmaEeP4AhY\noANi4AAAAACAm2q8cMmUsa7+0FFtXLR+SoJc7SN1EYAbY+AAAAAAgBtorqmzrN9WlbvTJ7x/\n6HtpXt1DpC4C8HMYOAAAAADgv7UcAfvpBrmPT+Dsp/zui5Q6CIBjDBwAAAAA8KOGf581Lc+0\nnbmgSxytSxoj8/KSughAqzBwAAAAAIAgCIK90mLO3FK94xvfoYPD3p+vDOwidRGANmDgAAAA\nANDZiXZ7dd5u85pcZUhgyMIXfW7vJ3URgDZj4AAAAADQqdUdOmpKz7Kbq/TJCf5jYwS5XOoi\nALeCgQMAAABAJ9VYVm5eubGm4KB21H36qY8otBqpiwDcOgYOAAAAAJ2O2GCz5OywrN+muq1P\n6B9f8+4VJnURgF+KgQMAAABAZyKKNfnFlSs+F0QxIGWKZuQ9UgcBcA4GDgAAAACdhe1UqWl5\nVsPJs/7xD+omPiz3UUldBMBpGDgAAAAAeL5ma605c0tVntE3MjxsyTxlUIDURQCcjIEDAAAA\ngCcT7c3WnXvNqzbJtX7BaSnqyHCpiwC4BAMHAAAAAI9V/91x0/KspopKXVKsf8IomVIhdREA\nV2HgAAAAAOCBmirM5lUbrcZCTUxU8OuzFDqt1EUAXIuBAwAAAIBHEW2NVVu+smTneXUPMbz9\nsuq2PlIXAWgPDBwAAAAAPEdtUYkpPVtsbOoybYJ29AhBJpO6CEA7YeAAAAAA4AkaL1wypWfX\nlxzTxkXrpyTI1T5SFwFoVwwcAAAAANxbc02dZf22qtydPuH9Q99L8+oeInURAAkwcAAAAABw\nW6JoNRZUfrJBrvbp9rvpvsOGSB0EQDIMHAAAAADcUsOJM6b0LNuZC7rE0bqkWJkX/7oBOjX+\nCAAAAADgZuyVlsrPcqzGQr97I7q9/FtlYBepiwBIj4EDAAAAgNsQ7fbqvN3mNblKQ7eQhS/6\n3N5P6iIAHQUDBwAAAAD3UHfoqCk9y26u0icn+I+NEeRyqYsAdCAMHAAAAAA6usaL5ZUfr6st\n/l476j791EcUWo3URQA6HAYOAAAAAB2X2GCz5OywrN+mGtg3dFGqd89QqYsAdFAMHAAAAAA6\nJFGsyS+uXPG5IIoBKVM0I++ROghAh8bAAQAAAKDDsZ08V5GeZTt5zj/+Qd3Eh+U+KqmLAHR0\nDBwAAAAAOpBma605c0tVntE3MjxsyTxlUIDURQDcAwMHAAAAgA5BtDdbd+6tXLVR4a8JnjND\nHTFI6iIA7oSBAwAAAID06g8fM6VnN1VU6ieN0z4cI1NwBCyAtmHgAAAAACClpgqzedVGq7FQ\nExMV/PoshU4rdREAt8TAAQAAAEAaoq3RsmG7ZcN2756hhndeUQ3oLXURADfGwAEAAABAArVF\nJab0bLGpKeDZZE3McEEmk7oIgHtj4AAAAADQrhrPXzJlZNeXHNPGReunJMjVPlIXAfAEDBwA\nAAAA2klzTa157ZaqL4zqwQNC30vz6h4idREAz8HAAQAAAMD1RNFqLKj8ZIPc1yf4/55RDxsi\ndRAAT8PAAQAAAMC1Gk6cMS3Psp29oEscrUuKlXnxzxAAzsefLAAAAABcxW6yVK7MsRoL/e6N\n6PbKb5WBXaQuAuCxGDgAAAAAOJ9ot1fn7TavyVUauhkWvqS6va/URQA8HAMHAAAAACerO3TU\nlJ5lt1TrkxP8x8YIcrnURQA8HwMHAAAAAKdpvFhu+nhdXfH3/nEx+uRxcl+11EUAOgsGDgAA\nAABOIDbYLDk7LOu3qQb2DV2U6t0zVOoiAJ0LAwcAAACAX6blCNhPc2QKeUDKFM3Ie6QOAtAZ\nMXAAAAAAuHW2k+cqlmfZTpfqEkfrksbIvLykLgLQSTFwAAAAALgVzdU15qytVXlG38jwsD/P\nVQYFSF0EoFNj4AAAAADQNqK9uTrPaF67WdHFP3juDPVdg6QuAgAGDgAAAABtUV9yzJSR3VRh\n1k8ep304RqbgCFgAHQIDBwAAAIBWabpSaV69yWos1MREBb/xgsJfI3URAPyIgQMAAACAA/85\nAna7d69Qwx9eVfXvJXURAFyPgQMAAADAz6ktKjEtzxLt9oCUZE3McEEmk7oIAG6AgQMAAADA\njTWev2RKz64/fEwbF62fkiBX+0hdBAA3xcABAAAA4HrNNbXmtVuqvjD6RoSHvT9fGRIodREA\nOMDAAQAAAOAaomg1FlSuWC/3Uwe/9qx66GCpgwCgVRg4AAAAAPyg/vsTpvSsxovlusTRuqRY\nmRf/XgDgNvgDCwAAAIBgN1kqV+b8cATsvOcUen+piwCgbRg4AAAAgE5NbLJXf7HbvCZXaQgy\nvPWSamBfqYsA4FYwcAAAAACdV21RiSljXXNtnT45wT9+JEfAAnBfDBwAAABAZ9R44bLp43X1\nB/+ljYvWJ4+T+6qlLgKAX4SBAwAAAOhcxAabJWeHZf021e19DYte8+4ZKnURADgBAwcAAADQ\nabQcAftpjkypCEiZohl5j9RBAOA0DBwAAABAp2A7ebZiebbtdKkucbQuaYzMy0vqIgBwJgYO\nAAAAwMM1V9eYs7ZWbd3lO3Rw2JJ5ym5dpS4CAOdj4AAAAAA8lmi3V+ftNq/drAwKCHlztk94\nf6mLAMBVGDgAAAAAz1RfcrQiPdtusugnj/MfGyPI5VIXAYALMXAAAAAAnqap7Erlypya/GJN\nTFSXN2cr/DVSFwGAyzFwAAAAAJ7jP0fAblcN6BW6KNW7d5jURQDQThg4AAAAAA9RW1RiWp4l\n2psDUpI1McMFmUzqIgBoPwwcAAAAgNuznS41Lc9qOH5aGxutn5IgV/tIXQQA7Y2BAwAAAHBj\nzTW15rVbqvKMvpHhYe/PVwYHSl0EANJg4AAAAADckyhajQWVK9bLNb7Bqc+qhw6WOggApMTA\nAQAAALif+u+Pm5ZnN1264j/+Id2EOJlSIXURAEiMgQMAAABwJ3aTuXLlRquxUBMTFTz/eYVe\nK3URAHQI7j1w2Gy2gwcPWq3W3r179+nTR+ocAAAAwIXEJnv1F7vNqzd5hQUb3n5ZdRvfAAPA\nj9xm4Hjrrbfuv//+//mf/7l6ZdmyZWlpaZWVlS2/HDZs2EcffRQRESFRIAAAAOBCtUUlpox1\nYoOty7QJ2tEjOAIWAK7jNgPH/PnzX3vttasDx+bNm1NSUlQqVVJSUlBQ0OHDh/fs2fPggw/u\n37+/X79+0qYCAAAATtR44bIpI7v+0FFtXLQ+eZzcVy11EQB0RG4zcFznpZde0ul0e/fuHTRo\nUMuVzz//fOLEiW+//XZ6erq0bQAAAIBTNNfUWdZvq8rdqRrUP3RxqlcPg9RFANBxueXAUV5e\nfvz48Tlz5lxdNwRBmDBhQmJi4rZt29r6bKWlpTab7WcecOXKlVupBAAAAG5ZyxGwn26Q+agC\nZz/ld1+k1EEA0NG55cBRX18vCMK160aLIUOGbN68uU1P9e9//7t///6teaQoim16ZgAAAODW\nNPz7rGl5lu3MeV3iaF3SGJmXl9RFAOAG3HLgCA0N1el0paWl112/cOGCVtu2U7L69etXWlra\n0NDwM49ZvXr1vHnzZHyMEwAAAFzMXmkxZ26p3vGN79DBYUvmKbt1lboIANyGOw0cZ8+eLSoq\n0uv1er1+5syZy5cvf+GFF3x9fVvu/de//rV27dpRo0a19WnDwsJ+/gGBgYG3kgsAAAC0mmi3\nV+ftNq/JVQYHhix40WcQH5wPAG3jTgPH6tWrV69efe2VrVu3PvbYY4IgrFq16plnnqmrq5s/\nf75EdQAAAMAtqi85WpGeba+06JMT/MfGCHK51EUA4H7cZuDIyMgwX8NisZjN5i5durTcazab\n9Xr9mjVroqKipO0EAAAAWq+p7Erlypya/GJNTFSXp2YrtBqpiwDAXbnNwPHUU0/9zL1PPvlk\nSkqKnKkbAAAAbkJssFlydljWb1cN6B26ONW7l4P3TQMAfp7bDBw/T6Nh6gYAAIDbqC0qMX2U\nKTaLASnJmpjhAp9nDwC/mIcMHAAAAIBbsJ0qNaVnNfz7rH/8g7qJD8t9VFIXAYCHYOAAAAAA\n2kOztdacuaUqz+gbGR62ZJ4yKEDqIgDwKAwcAAAAwA+ampqWLVu2bt26kpISPz+/O+6449ln\nn01ISPiFTyvam60795pXbZJr/YLTUtSR4U6pBQBci4EDAAAAEARBqK2tHTduXElJyfTp02fM\nmFFbW7tnz54JEyY8//zzf/rTn275aeu/O25Kz266YtIlxfonjJIpFU5sBgBcxcABAACAW2Gx\nWPz8/JRKz/l+ct68eadOnSouLu7evXvLlWnTpj3xxBOxsbEjRoyYOHFiW5/QbjJXrtxoNRZq\nYqKC5z+v0GudnQwA+BHnqgIAAKANzp8///TTTxsMBr1er9Fo7rnnnszMTKmjnKC+vv7DDz98\n9913r64bLWJiYp555pkPPvigTc8m2hotG7aff2FhY2mZ4e2XA2c9yboBAK7mOYs7AAAAXO3o\n0aMxMTF9+vRZtGjRkCFDrly5sm3btieffHL//v3/7//9P6nrfpFjx45ZrdYxY8b89K7Ro0d/\n/PHHrX+q2qISU3q22NjUZdoE7egRHAELAO2DgQMAAACt9Zvf/CYqKmrDhg1X35kyevTouLi4\nuLi4+Pj4kSNHSpv3S9hsNkEQVKobHNrq4+PTcq9DjRcumTLW1R86qo2L1k9JkKt9nFwJALg5\nBg4AAAC0yuHDh/fu3Xv8+PHrPnfjoYceSkpK+uijj9x64Ojbt69CoSguLn7ggQeuu6u4uLh/\n//4//9uba+os67dV5e70Ce8f+l6aV/cQl5UCAG6Mz+AAAABAqxw+fDgkJOSG/9S///77Dx8+\n3P5JTtS1a9exY8e+8cYbTU1N114vLy9///33H3/88Zv+TlG07tp3fvaC2vziwNlPBf9+FusG\nAEiCgQMAAAAQBEFYsmTJoUOH4uLidu3aVVVVdfny5XXr1t1///3du3d/8cUXb/hbGk6cuTj3\nvYp/rNXGRof+eY7ffZHt3AwAuIqBAwAAAK0yePDgS5cunTx58qd37d27Nzw8vP2TnKtfv377\n9u3z9fUdNWqUTqcLDg5+4okn4uLiduzYoVarr3uwvdJSsWz1xTnvKQO6hL0/Xz8pXublJUk2\nAKAFn8EBAACAVrnjjjuioqJefvnldevWKRSKq9d37dq1bt26bdu2SdjmLH369Nm0aVNtbe2R\nI0d8fX0HDBhw3QeOCIIg2u3VebvNa3KVIYEhC2b73N5PklQAwHUYOAAAANBaGRkZMTExDz74\n4KxZs4YMGVJeXr5jx47Fixe/8MILo0aNkrrOaXx9fYcNG3bDu+oOHTWlZ9nNVfrkBP+xMYKc\nF0QDQEfBwAEAAIDWCg8P//bbb+fMmTNjxgyTyeTl5RUeHv7hhx8+8cQTUqe5XGNZeWXGutri\n77Wj7tNPfUSh1UhdBAD4LwwcAAAAaIOePXt+9tlngiBcvnxZr9d7e3tLXeRyYoPNkrPDsn6b\n6rY+oX98zbtXmNRFAIAbYOAAAADArQgKCpI6wfVEsSa/uHLF54IoBqRM0Yy8R+ogAMBNMXAA\nAAAAN2A7VWpantVw8qx//IO6iQ/LfVRSFwEAfg4DBwAAAPBfmq215swtVXlG38jwsCXzlEEB\nUhcBABxj4AAAAAB+INqbrTv3mldtkmv9gtNS1JHhUhcBAFqLgQMAAAAQBEGoP3zMlJ7dVFGp\nS4r1TxglUyqkLgIAtAEDBwAAADq7pgqzedVGq7FQExMV/PoshU4rdREAoM0YOAAAANB5ibbG\nqi1fWbLzvLqHGN5+WXVbH6mLAAC3iIEDAAAAnVRtUYkpPVtsbOo6fZImZrggk0ldBAC4dQwc\nAAAA6HQaL1wypWfXlxzTxkXrpyTI1T5SFwEAfikGDgAAAHQizTV1lvXbqnJ3+oT3D30vzat7\niNRFAADnYOAAAABA5yCKVmNB5Scb5Gqfbr+b7jtsiNRBAABnYuAAAACA52s4cca0PMt29oIu\ncbQuKVbmxbfBAOBp+JMdAAAAnsxuslSuzLEaC/3ujej2ym+VgV2kLgIAuAQDBwAAADyTaLdX\n5+02r8lVGroZFr6kur2v1EUAABdi4AAAAIAHqjt01JSeZTdX6ZMT/MfGCHK51EUAANdi4AAA\nAIBHabxYXvnxutri77Wj7tNPfUSh1UhdBABoDwwcAAAA8BBig82Ss8OyfptqYN/QRanePUOl\nLgIAtB8GDgAAALg/UazJL65c8bkgigEpUzQj75E6CADQ3hg4AAAA4N5sJ89VpGfZTp7zj39Q\nN/FhuY9K6iIAgAQYOAAAAOCumqtrzFlbq/KMvpHhYUvmKYMCpC4CAEiGgQMAAADuR7Q3W3fu\nrVy1UeGvCZ4zQx0xSOoiAIDEGDgAAADgZuoPHzOlZzdVmPWT4rUPx8gUHAELAGDgAAAAgPto\nqjCbV220Ggs1MVHBr89S6LRSFwEAOgoGDgAAALgB0dZo2bDdsmG7d89QwzuvqAb0lroIANCx\nMHAAAACgo6stKjGlZ4tNTQHPJmtihgsymdRFAIAOh4EDAAAAHVfj+UumjOz6kmPauGj9lAS5\n2kfqIgBAB8XAAQAAgI6ouabWvHZL1RdG9eABoe+leXUPkboIANChMXAAAACggxFFq7Gg8pMN\ncl+f4P97Rj1siNRBAAA3wMABAACADqThxBnTR5m2cxd1iaN1SbEyL75fBQC0Cn9hAAAAoEOw\nmyyVK3OsxkK/eyO6vfq/ysAuUhcBANwJAwcAAAAkJtrt1Xm7zWtylYZuhrdeUg3sK3URAMD9\nMHAAAABASnWHjprSs+yWan1ygv/YGEEul7oIAOCWGDgAAAAgjcaL5aaP19UVf+8fF6NPHif3\nVUtdBABwYwwcAAAAaG9ig82Ss8Oyfpvq9r6hi1K9e4ZKXQQAcHsMHAAAAGhHLUfAfpojUyoC\nUqZoRt4jdRAAwEMwcAAAAKCd2E6erViebTtdqkscrUsaI/PykroIAOA5GDgAAADgcs3VNeas\nrVV5Rt/I8LA/z1UGBUhdBADwNAwcAAAAcKEfjoBdu1nRxT947gz1XYOkLgIAeCYGDgAAALhK\nfckxU0Z2U4VZP3mc9uEYmYIjYAEArsLAAQAAAOdrulJpXr3JaizUxEQFv/GCwl8jdREAwMMx\ncAAAAMCZ/nME7HbvXqGGP7yq6t9L6iIAQKfAwAEAAACnqS0qMS3PEu32gJRkTcxwQSaTuggA\n0FkwcAAAAMAJGkvLTBnr6r87po2N1k9JkKt9pC4CAHQuDBwAAAD4RZpras1rt/xwBOz785XB\ngVIXAQA6IwYOAAAA3CpRtBoLKlesl2t8g1OfVQ8dLHUQAKDzYuAAAADAraj//oQpPavxYrku\ncbQuKVbmxTeWAAAp8fcQAAAA2sZuslSuzPnhCNh5zyn0/lIXAQDAwAEAAIBWE5vs1V/sNq/J\nVRqCDG+9pBrYV+oiAAB+wMABAACAVqktKjFlrGuurdMnJ/jHj+QIWABAh8LAAQAAAAcaL1w2\nfbyu/uC/tHHR+uRxcl+11EUAAFyPgQMAAAA3JTbYLDk7LOu3qW7vG7o41auHQeoiAABujIED\nAAAAN9JyBOynG2RKZUDKFM3Ie6QOAgDg5zBwAAAA4Hq2k2crPsqynTmvSxytSxoj8/KSuggA\nAAcYOAAAAPCj5uoac9bWqq27fIcODlsyT9mtq9RFAAC0CgMHAAAABEEQRLu9Om+3ee1mZVBA\nyIIXfQb1k7oIAIA2YOAAAACAUF9ytCI9226y6CeP8x8bI8jlUhcBANA2DBwAAACdWlPZlcqV\nOTX5xZqYqC5vzlb4a6QuAgDgVjBwAAAAtJOmpqbS0lKDwaBSqaRuEYQfj4DdrhrQO3RRqnfv\nMKmLAAC4dbz4EAAAwOXy8/NHjRrl5+fXp08fjUYTFRWVm5srbVJtUcn5F9+q3vFNQEpyyJsv\nsG4AANwdAwcAAIBrbdy4MTo6OiwsbMuWLWfOnPnnP/95//33JyUl/fWvf5Wkx3a6tGz+n8sX\nf+QbdWfY+/M0I+8RZDJJSgAAcCLeogIAAOBCVVVV//u//ztnzpw333yz5UrPnj0feOCBoUOH\nTp8+PT4+vl+/9juspNlaa87cUpVn9I0MD3t/vjI4sN2+NAAArsYrOAAAAFwoNzfXbrfPnTv3\nuutPPvlkeHj4qlWr2qlDFK279p1/YUFd8ffBaSlBaSmsGwAAD8MrOAAAAFzoyJEjkZGR3t7e\nP71r+PDhR44caYeG+u+Pm5ZnN1264j/+Id2EOJlS0Q5fFACAdtaGgaO6uvrs2bNhYWF6vd51\nQQAAAJ5EoVA0Nzff8K7m5ma53LUvp7WbzJUrN1qNhZqYqOD5zyv0Wpd+OQAAJNSqv1N37dp1\n9913+/v7DxkyJD8/v+Xi+PHjv/zyS1e2AQAAuL077rhj//79NTU1110XRfHrr7++8847XfR1\nxSZ71eavzr+wsLG0zPD2y4GznmTdAAB4NscDR0FBQWxs7LFjx+Li4q5eLC8vLywsjI+P379/\nvyvzAAAA3Ft8fLy/v/9rr70miuK11//85z+fO3fu8ccfd8UXrS0qOT97oWX9ti7TJhje/Z3q\ntj6u+CoAAHQojt+ismDBgpCQkD179iiVSoPB0HKxW7duBw8ejIqKWrhw4YYNG1wcCQAA4K7U\navXKlSvj4+OPHj361FNP9evXr7S0dN26ddnZ2StWrAgLC3Pul2u8cNmUkV1/6Kg2Llo/JUGu\n9nHu8wMA0GE5fgVHfn7+jBkzunfvft31oKCglJQUo9HomjAAAAAPERMT8+233wYGBr722mv3\n3XffjBkzrFbr119/PXXqVCd+leaausrPci68/LbYZA9dnNr16YmsGwCATsXxKzgsFkuPHj1u\neJfBYLBarc5OAgAA8DS33Xbb6tWrBUGoq6tTq9VOfnZRtBoLKj/dIPNRBc5+yu++SCc/PwAA\n7sDxwBESEnKzA8yMRmNoaKizkwAAADyW09eNhn+fNS3Psp05r0sc+IlvAAAgAElEQVQcrUsa\nI/Pycu7zAwDgLhy/RSU+Pn7p0qXffvvttRcrKyvnzp2bkZExbtw4l7UBAADgpuyVloplqy+m\nLlJo/cLen6+fFM+6AQDozGTXfaD3T5WVlQ0fPvzixYt33nnnt99+GxERIQjCkSNHGhoaevbs\nWVBQEBwc3C6pklm2bFlKSkp1dbVGo5G6BQAAQBDt9uq83eY1ucrgwK6//ZXPoH5SFwEAOgub\nzaZSqfbs2TNixAipW67XqreoFBUVvfHGG5mZmYIgFBcXC4IQGBj49NNPv/HGG0FBQS5vBAAA\nnduBAwdWrlxZUlIiCMIdd9zx+OOPR0Z23o+ZqC85WpGeba+06JMT/MfGCHLHL8gFAKAzaNXf\niEFBQUuXLi0vLy8rKzt+/HhZWVl5efnSpUtZNwAAgKu99dZbUVFRBw4cGDp06NChQw8cOBAV\nFfXWW29J3SWBxrLy8veWly34QNW3R9hff+8/7kHWDQAArnL8Co6vv/46PDy8a9euMpksODj4\n2jekFBQUnDt37rHHHnNlIQAA6LwyMzMXLly4fv36Rx555OrFTZs2TZw4ceDAgb/61a8kbGtP\nYoPNkrPDsn67akDv0MWp3r3CpC4CAKDDcbz6R0dHG43GG961e/fu6dOnOzsJAADgB3/4wx9e\nfPHFa9cNQRAeeeSRF1988Z133pGqqp3VFpWcn72wesc3ASnJIW++wLoBAMAN3fQVHCdOnDhx\n4kTL7QMHDvj4+Fz3gLq6uszMzIaGBhfWAQCATsxqtRYXF//973//6V1JSUl//OMfrVarZ38E\nuO1UqWl5VsPJs/7xD+omPiz3UUldBABAx3XTgSM7OzstLa3l9oIFC272sIkTJzo/CgAAQBCq\nq6sFQdDr9T+9q0uXLi0P8NSBo9laa87cUpVn9I0MD1syTxkUIHURAAAd3U0HjtTU1GnTphUW\nFiYmJv76178ODw+/7gEKhaJv377jx493cSEAAOikAgMD1Wr18ePHBw4ceN1dx48fV6vVgYGB\nkoS5lGhvtu7ca161Sa71C05LUUde/z0YAAC4oZ/7kFGDwTB+/Phx48bNnDnz3nvv/ekDampq\nKioqQkJCXJYHAAB+EVEUv/rqq3379pWWlvbp0+fBBx8cNmyY1FGt5eXlNW7cuPfffz8+Pl5+\nzXEhzc3NS5YsSUhI8PLykjDPFeq/O25Kz266YtIlxfonjJIpFVIXAQDgNhx/yGhubu4N1w1B\nEHJycoYOHersJAAA4ByXL18eNWpUXFxcTk5OeXn5ypUrhw8fnpycXFdXJ3Vaa73zzjv79++f\nOnVqaWlpy5XS0tKpU6d+++23HvYho3aT+cpfPyl74y/evcPC3v+97tExrBsAALSJ42NiBUG4\ncuXKmjVrTp8+3dTUdPVifX19bm6u1Wp1WRsAALh1zc3NiYmJjY2Nx44d6927d8vFAwcOTJgw\nYfr06Z999pmkda01YMCAf/7zn9OmTevRo0dYWJggCOfPn4+IiPjnP//Zv39/qeucQ7Q1Vm35\nypKd5xUWbHj7ZdVtfaQuAgDALTkeOE6fPj18+PDy8vIb/Galcv78+S6oAgAAv1ROTk5JScnx\n48cNBsPVi5GRkdnZ2VFRUa+99todd9whYV7r3XXXXQcOHDh06NB3330nCMLgwYPvvPNOmUwm\ndZdz1BaVmNKzxcamLtMmaEePEDzlPxcAAO3P8cAxb968+vr6Dz74YNCgQQ899NBHH33UvXv3\nr7766tNPP12+fHlcXFw7VAIAgLbatm1bbGzstetGi2HDhg0ePHj79u3uMnAIgiCTye666667\n7rpL6hBnarxwyZSxrv7QUW1ctH5KglztI3URAADuzfHAsXv37ueee+65556rr68XBGHw4MH3\n3ntvXFzc5MmTH3rooY0bN95///2u7wQAAG1z5cqVlvd0/FT37t1v+NpMtI/mmjrL+m1VuTt9\nwvuHvpfm1Z3PawcAwAkcDxwXL17s27evIAgtn15us9larkdERDz33HOvv/76jh07XJoIAABu\nQbdu3c6fP3/Du0pLS8eMGdPOPRAEQRBFq7Gg8pMNcrVP4Oyn/O6LlDoIAADP4fgUFa1We+nS\nJUEQvL29NRrNyZMnr94VHh5eVFTkwjoAAHCrYmNjt23bduHCheuuFxUVfffdd7GxsZJUdWYN\nJ85cnPtexT/WauOiQ/88l3UDAADncjxwREdH//3vf//qq68EQbjjjjv+9re/XT05ZefOnSqV\nyqV9AADg1owfP/7OO+985JFHTp06dfXit99+O3HixMcff3zIkCEStnU29kpLxbLVF+e8pwzo\nEvb+fP2keJlXq06yAwAAref4L9c5c+aMHDny1VdfLSoqmj59+tNPPx0eHn733XefOnWquLj4\n8ccfb4dKAADQVnK5PCcnZ/LkyQMHDoyMjOzRo8eJEycOHTqUnJz8j3/8Q+q6zkK026vzdpvX\n5CpDAkMWzPa5vZ/URQAAeCzHA8fw4cO//vrrgoICQRCeeuqp48ePL1myZP369TKZbPz48UuW\nLHF9JAAAuBXdunXbuXPnrl279u3bd+7cuQceeCAmJmbo0KFSd3UWdYeOmtKz7OYqfXKC/9gY\nQe74lbMAAOCWyURRbOvvqa+vLysrCw4OVqvVrmjqaJYtW5aSklJdXa3RaKRuAQAAbqCxrLwy\nY11t8ffaUffppz6i0PItBADAQ9hsNpVKtWfPnhEjRkjdcr1bef+nj49P7969nV0CAADg9sQG\nmyVnh2X9NtVtfUIXpXr3DJW6CACAzqJVA4fdbt+3b9/FixcbGxt/em9ycrKzqwAAANyNKNbk\nF1eu+FwQxYCUKZqR90gdBABA5+J44Ni/f//EiRNPnz59swcwcAAAgE7OdvJcRXqW7eQ5//gH\ndRMflvtwzBwAAO3N8cDx/PPPm83m2bNnDxw40MvLqx2aAAAA3EWztdacuaUqz+gbGR62ZJ4y\nKEDqIgAAOinHA0dJSclnn3326KOPtkMNAACAuxDtzdade82rNsm1fsFpKerIcKmLAADo1BwP\nHBqNpmfPnu2QAgAA4C7qDx8zpWc3VVTqkmL9E0bJlAqpiwAA6OwcDxyTJk3Kzs4eOnRoO9QA\nAAB0cE0VZvOqjVZjoSYmKvj1WQqdVuoiAAAgCK0ZON59993k5ORJkyYlJiaGhob+9GM4Hnjg\nAde0AQAAdCCirbFqy1eW7Dyv7iGGt19W3dZH6iIAAPAjxwPH4cOHi4uLz507l5WVdcMHiKLo\n7CoAAICOpbaoxJSeLTY2dZ0+SRMzXJDJpC4CAAD/xfHAMWvWrPLy8kmTJg0YMECpdPx4AAAA\nT9J4/pIpI7u+5Jg2Llo/JUGu9pG6CAAA3IDjweLQoUMffvjhE0880Q41AAAAHUdzTZ157eaq\nL4zqwQNC30vz6h4idREAALgpxwOHn5/fkCFD2iEFAACgoxBFq7Gg8pMNcl+foP97xncY3wsB\nANDROR44kpKScnNzIyIi2qEGAABAcg0nzpiWZ9nOXtAljtYlxcq8eIsuAABuwPFf2IsWLfrV\nr3518eLFpKSksLCwn56i0r9/f9e0AQAAtCu7yVK5MsdqLPS7N6LbK79VBnaRuggAALSW44Gj\nS5cugiDs2LFj6dKlN3wAp6gAAAB3J9rt1Xm7zWtylYZuhoUvqW7vK3URAABoG8cDx5QpU7y9\nvTk/BQAAeKq6Q0dN6Vl2c5U+OcF/bIwgl0tdBAAA2szxbLFq1ap26AAAAGh/jRfLTR+vqyv+\nXjvqvi5Tx8u1flIXAQCAW3TjgaOsrEylUrW8OaWsrOznnyIkhCPTAACAmxEbbJacHZb121QD\n+4YuSvXuGSp1EQAA+EVuPHAYDIa4uLi8vLyW2z//FHwGBwAAcCeiWJNfXLnic0EUA1KmaEbe\nI3UQAABwghsPHJMnT756LuzkyZPbsQcAAMCFbCfPVaRn2U6e0z06RvfoGJn39cfDAQAAN3Xj\ngWPNmjU3vA0AAOCmmqtrzFlbq/KMvpHhYUvmKYMCpC4CAADO5PhDRr/++uvw8PCuXbv+9K6C\ngoJz58499thjLggDAABwDtHeXJ1nNK/drOjiHzxnhjpikNRFAADA+RyfghYdHW00Gm941+7d\nu6dPn+7sJAAAAKepP3zs4u/eNWdu0U8eF/qnuawbAAB4qpu+guPEiRMnTpxouX3gwAEfH5/r\nHlBXV5eZmdnQ0ODCOgAAgFvVVGE2r9poNRZqYqKCX5+l0GmlLgIAAC5004EjOzs7LS2t5faC\nBQtu9rCJEyc6PwoAAOAX+M8RsNu9e4Ua3nlFNaC31EUAAMDlbjpwpKamTps2rbCwMDEx8de/\n/nV4ePh1D1AoFH379h0/fryLCwEAANqgtqjElJ4tNjUFpCRrYoYLMpnURQAAoD383IeMGgyG\n8ePHjxs3bubMmffee2+7NQEAANyCxvOXTOnZ9YePaeOi9VMS5Orr32ALAAA8mONTVHJzcwVB\nsNvtCoWi5UpDQ0NxcbG3t3dERISMn4oAAACpNdfUmtduqfrCqB48IPS9NK/uIVIXAQCA9uZ4\n4LDb7S+88MLly5ezsrIEQTh9+vRDDz108uRJQRAeeOCBrVu3ajQal2cCAADckChajQWVK9bL\n/dTB//eMetgQqYMAAIA0HB8Tu2jRoqVLl/bs2bPll88999ypU6dmzJgxc+bMb7755oMPPnBx\nIQAAwI01nDhzMW1xxT/Wah+OCf3TXNYNAAA6M8ev4Fi5cuWECRPee+89QRDOnz+/devWp59+\neunSpYIg1NfXr127NjU11eWZAAAA17CbLJUrc1qOgA1KfVah95e6CAAASMzxwHH69Onnn3++\n5fYXX3whiuKUKVNafjls2LDPP//chXUAAAD/TbTbq/N2m9fkKg3dDG+9pBrYV+oiAADQITge\nOK79GNEdO3b4+flFR0e3/FIUxcbGRlelAQAA/LfaohLTx+uaa+r0yQn+Y2MEueM32wIAgE7C\n8cDRq1cvo9H47LPPXrp0adOmTbGxsd7e3i13HTx4sHv37i4uBAAAEBovlpsysusOHvGPi9En\nj5P7qqUuAgAAHYvjgWPq1Klz5sw5derUmTNnrFbr7NmzW65/8sknK1asuPpLAAAAVxAbbJac\nHZb121S39w1dlOrdM1TqIgAA0BE5HjheeumlY8eOrV271tvb+y9/+cvIkSNbrqempg4cODAt\nLc3FhQAAoLNqOQL20xyZUhGQMkUz8h6pgwAAQMfleODw8fHJyMjIyMi47vrnn39+9913K5WO\nnwEAAKCtbCfPVizPtp0u1SWO1iWNkXl5SV0EAAA6tJvOE1euXFGr1X5+fjd7wL333rt9+/Z9\n+/bNmzfPNW0AAKAzaq6uMWdtrcoz+kaGh/15rjIoQOoiAADgBm762ePdunWbO3futVfeeOON\nbdu2XXtl8+bN8+fPd1UaAADoZES7vWrzV6XPvVF38Ejw3BlBaSmsGwAAoJXa8AaTN99885VX\nXomNjXVdDQAA6LTqS46ZMrKbKsz6yeO0D8fIFBwBCwAA2oBP0AAAABJrulJpXr3JaizUxEQF\nv/GCwl8jdREAAHA/DBwAAEAy/zkCdrtqQK/QRanevcOkLgIAAO6KgQMAAEijtqjEtDxLtNsD\nUpI1McMFmUzqIgAA4MYYOAAAQHuznS41pWc3HDuljY3WT0mQq32kLgIAAG6PgQMAALSf5ppa\n89otPxwB+/58ZXCg1EUAAMBDMHAAAIB2IYpWY0HlivVyjW9w6rPqoYOlDgIAAB7l5waO/Pz8\nN95449or33zzzbVX8vPzXVMFAAA8Sv33J0zpWY0Xy3WJo3VJsTIvfsQCAACc7Oe+vdi3b9++\nffuuvbJ37969e/e6OAkAAHgOu8lcuXLjD0fAzntOofeXuggAAHimmw4cn376aXt2AAAADyM2\n2au/2G1ek6s0BBneekk1sK/URQAAwJPddOB44okn2rMDAAB4ktqiElPGuubaOn1ygn/8SI6A\nBQAArsY7YAEAgDM1Xrhs+nhd/cF/aeOi9cnj5L5qqYsAAECnwMABAACco7m+oWrjl5bPv1AN\n6h+6ONWrh0HqIgAA0IkwcAAAgF+s5QjYTzfIfFSBs5/yuy9S6iAAANDpMHAAAIBfxHbybMVH\nWbYz53WJo3VJY2ReXlIXAQCAzoiBAwAA3CK7ucq8dnP1jm98hw4OWzJP2a2r1EUAAKDzYuAA\nAABtJtrt1Xm7zWs3K4MCQha86DOon9RFAACgs3M8cGzcuLFfv36DBw9uhxoAANDx1ZccrUjP\ntpss+snj/MfGCHK51EUAAACC4+9IJk+enJub2w4pAACgg2squ1L+3vKyBR+o+vYI++vv/cc9\nyLoBAAA6CMfflDzwwAO7du1qbm5uhxoAANAxiQ02c+aW8y+9bbdYQxenBs56UuGvkToKAADg\nR47fovLZZ5+99NJL48aNe/LJJ2+77TadTnfdA/r37++aNgAA0CHUFpWYlmeJ9uaAlGRNzHBB\nJpO6CAAA4HqOB46QkJCWG3l5eTd8gCiKziwCAAAdhu10qWl5VsPx09rYaP3UR+Q+KqmLAAAA\nbszxwDF58mRvb28vLy8ZP64BAKDTaLbWmjO3VOUZfSPDw96frwwOlLoIAADg5zgeONasWdMO\nHQAAoKMQRauxoHLFernGNzgtRR0ZLnUQAACAY44Hjquqq6vPnj0bFham1+tdFwQAACRU//1x\n0/LspismXVKsf8IomVIhdREAAECrtOpot127dt19993+/v5DhgzJz89vuTh+/Pgvv/zSlW0A\nAKD92E3mK3/9pOz1v3j3Dgt7//e6R8ewbgAAADfieOAoKCiIjY09duxYXFzc1Yvl5eWFhYXx\n8fH79+93ZR4AAHA5scletfmr8y8sbCwtM7z9cuCsJxV6rdRRAAAAbeP4LSoLFiwICQnZs2eP\nUqk0GAwtF7t163bw4MGoqKiFCxdu2LDBxZEAAMBVaotKTOnZYmNTl2kTtKNHcAQsAABwU44H\njvz8/FdffbV79+5lZWXXXg8KCkpJSVm0aJHL2gAAgAs1XrhkylhXf+ioNi5aPyVBrvaRuggA\nAODWOR44LBZLjx49bniXwWCwWq3OTgIAAK7VXFNnWb+tKnenalD/0MWpXj0MUhcBAAD8Uo4H\njpCQkCNHjtzwLqPRGBoa6uwkAADgMi1HwH66QeajCpz9lN99kVIHAQAAOIfjgSM+Pn7p0qUT\nJky4dsuorKxcvHhxRkbGzJkzXZkHAACcpuHfZ03Ls2xnzusSR+uSxsi8vKQuAgAAcBqZKIo/\n/4iysrLhw4dfvHjxzjvv/PbbbyMiIgRBOHLkSENDQ8+ePQsKCoKDg9slVTLLli1LSUmprq7W\naDRStwAAcCvslRZz5pbqHd/4Dh3cdfpkZWAXqYsAAIBbstlsKpVqz549I0aMkLrleo6PiQ0J\nCSkqKpo+ffqZM2cEQSguLi4uLtZqtTNmzCgsLPT4dQMAALcm2n84ArbhxJmQBS8GpaWwbgAA\nAI/k+C0qgiAEBQUtXbr0b3/72+XLl6urq7VaLbsGAAAdX92ho6b0LLu5Sp+c4D82RpA7/sEG\nAACAm3I8cHz99dfh4eFdu3aVyWTBwcHXThsFBQXnzp177LHHXFkIAADarLGs3LxyY01+sSYm\nqstTExRa3mUJAAA8nOOf5ERHRxuNxhvetXv37unTpzs7CQAA3DqxwWbO3HLhpXfsVdbQxamB\ns55k3QAAAJ3BTV/BceLEiRMnTrTcPnDggI+Pz3UPqKury8zMbGhocGEdAABoi9qiEtNHmWKz\nGJCSrIkZLshkUhcBAAC0k5sOHNnZ2WlpaS23FyxYcLOHTZw40flRAACgjWynSk3LsxpOnvWP\nf1A38WG5j0rqIgAAgHZ104EjNTV12rRphYWFiYmJv/71r8PDw697gEKh6Nu37/jx411cCAAA\nfk6ztdacuaUqz+gbGR62ZJ4yKEDqIgAAAAn83IeMGgyG8ePHjxs3bubMmffee2+7NQEAgNYQ\n7c3WnXvNqzbJtX7BaSnqyOt/GgEAANB5OD5FJTc3t+VGdXX12bNnw8LC9Hq9i6sAAIAD9d8d\nN6VnN10x6ZJi/RNGyZQKqYsAAACk5PgUFUEQdu3adffdd/v7+w8ZMiQ/P7/l4vjx47/88ktX\ntgEAgBtoqjBf+esnZW/8xbt3WNj7v9c9OoZ1AwAAwPHAUVBQEBsbe+zYsbi4uKsXy8vLCwsL\n4+Pj9+/f78o8AADwI9HWaNmw/cLshY3nLxnefjlw1pMKvVbqKAAAgA7B8VtUFixYEBISsmfP\nHqVSaTAYWi5269bt4MGDUVFRCxcu3LBhg4sjAQCAUFtUYkrPFhubukyboB09giNgAQAAruV4\n4MjPz3/11Ve7d+9eVlZ27fWgoKCUlJRFixa5rA0AAAiCIDReuGTKWFd/6Kg2Llo/JUGu9pG6\nCAAAoMNxPHBYLJYePXrc8C6DwWC1Wp2dBAAAftBcU2dZv60qd6dPeP/Q99K8uodIXQQAANBB\nOR44QkJCjhw5csO7jEZjaGios5MAAIAgiKLVWFD5yQa52idw9lN+90VKHQQAANChOR444uPj\nly5dOmHChGu3jMrKysWLF2dkZMycOdOVeQAAdEYNJ86Y0rNsZy7oEkfrkmJlXo7/vgYAAOjk\nHH/D9Oabb27duvWee+658847BUFIS0tLS0s7cuRIQ0NDz549f//737s+EgCAzsJeaTFnbqn+\ncq/fPXd1e/m3ysAuUhcBAAC4B8fHxIaEhBQVFU2fPv3MmTOCIBQXFxcXF2u12hkzZhQWFgYH\nB7s+EgAAzyfa7VWbvzr/wsKGE2dCFszu9grrBgAAQBu06iWvQUFBS5cu/dvf/nb58uXq6mqt\nVsuuAQCAE9UdOmpKz7Kbq/TJCf5jYwS5459AAAAA4FpteE+vTCYLDg5m2gAAwIkay8orM9bV\nFn+vHXWffuojCq1G6iIAAAC31KqBw26379u37+LFi42NjT+9Nzk52dlVAAB4PrHBZsnZYVm/\nTXVbn9BFqd49OZgMAADg1jkeOPbv3z9x4sTTp0/f7AEMHAAAtI0o1uQXV674XBDFgJQpmpH3\nSB0EAADg9hwPHM8//7zZbJ49e/bAgQO9vLzaoQkAAA9mO3muIj3LdvKcf/yDuokPy31UUhcB\nAAB4AscDR0lJyWefffboo4+2Qw0AAB6s2VprztxSlWf0jQwPWzJPGRQgdREAAIDncDxwaDSa\nnj17tkMKAACeSrQ3W3fuNa/aJNf6Bc+ZoY4YJHURAACAp3E8cEyaNCk7O3vo0KHtUAMAgOep\nP3zMlJ7dVFGpS4r1TxglUyqkLgIAAPBAjgeOd999Nzk5edKkSYmJiaGhoT/9GI4HHnjANW0A\nALi3pgqzedVGq7FQExMV/PoshU4rdREAAIDHcjxwHD58uLi4+Ny5c1lZWTd8gCiKzq4CAMC9\nibbGqi1fWbLzvLqHGN55RTWgt9RFAAAAHs7xwDFr1qzy8vJJkyYNGDBAqXT8eAAAOrnaohJT\nerbY2NR1+iRNzHBBJpO6CAAAwPM5HiwOHTr04YcfPvHEE+1QAwCAW2s8f8mUkV1fckwbF62f\nkiBX+0hdBAAA0Fk4Hjj8/PyGDBnSDikAALiv5po689rNVV8Y1YMHhL6X5tU9ROoiAACAzsXx\nwJGUlJSbmxsREdEONQAAuB9RtBoLKj/ZIPf1Cfq/Z3yH8VMBAAAACTgeOBYtWvSrX/3q4sWL\nSUlJYWFhPz1FpX///q5pA/D/2bv3+KjqA///M5OEJJAbBggJKopiBdzvigoqLsFVBC+siGvX\nUGsv9karrpfaFRWsveDuetmlbrtbHr8SqlRFE4pQRFRWMdRqle2CuLZ4QUTFCzCZXEkmmczv\nD1rbWpSLSU5O8nz+JWcm4/uhwiN5eWY+QE/X+uob8YVVyW3bC6dPLpwxJZrlw6oAAIKx7+/D\nBg4cGIlE1qxZ85//+Z97fYJTVADog1Lxutp7lzfWPD/glOMHf/NLmYMGBr0IAKBP23fgmDlz\nZr9+/ZyfAkDfsXXr1gULFvzmN7/ZuXPnsccee84558ycOTMjI2PPo+lUqmH1usSSlZmlg0u/\nd032sSOCXQsAQGR/Asd99933UQ81NTU1NDR06h4ACNjy5csvueSS0aNHT548efDgwS+++OLl\nl1++cOHCX/ziF3l5ebtf2ByvrErVNRRVTCs4pzwSiwW9FwCASGR/AsfHWL58+XXXXbd9+/bO\nWgMAwdqyZUtFRcWNN944Z86caDS65+Itt9wyefLkuV+/cvbok3dveCn/jFMHfub8WP6AYKcC\nAPCn9itw7Ny5c8mSJVu3bm1vb//gYktLy8qVKxsbG7tsGwB0t7vuumvs2LFz587904uHDil5\n4EtX9X92U2tDY9nts/sdXhbUPAAAPsq+A8fWrVvHjx+/Y8eOvXxxZuaHvgUEgFB75plnLrjg\ngj/+Op1uenZD7d0/H5ROz/7ts39/6ZQZ6gYAQI+078AxZ86clpaWH/7wh6NGjTrzzDN/8pOf\nHHrooWvXrl28ePHChQunTp3aDSv/VDqdfv3117ds2bLn4z8KCwtHjhx52GGHdfMMAHqlpqam\ngoKCPX+d3PLmrsqq5JY3Cy84q/CCs5466u6zm5qCnQcAwEfZd+BYt27d5Zdffvnll7e0tEQi\nkTFjxpxyyilTp069+OKLzzzzzBUrVpx22mldvzMSiURqa2vnzZu3ePHi999//0MPHX744V/+\n8pevu+663Nzc7hkDQK80fPjwzZs3dzQ0JaoeqV9d03/s6GHz52QOKU4kEu++++7w4cODHggA\nwN7tO3C88847I0aMiEQisVgsEokkk8k9148//vjLL7/829/+9po1a7p04gczTjvttNdff33k\nyJHnnnvu8OHDBwwYEIlE6uvrX3vttaeeeurmm29eunTpk4Sk17QAACAASURBVE8+OXDgwG7Y\nA0CvdNGFf7/+B//ftq/fnFVcVHLj13OPH7Xn+r/9278NGTLk1FNPDXYeAAAfZd+BIz8//733\n3otEIv369cvLy9uyZUt5efmeh0aPHn3XXXd17cA/mDt37ltvvfXggw9++tOf/stHU6nUggUL\nrrjiiu985zvz58/vnkkA9DItm16e8uI7448+/r+2vHD2F2+YeNzISCSyc+fOf//3f7/tttuq\nqqoyMz/R6WMAAHSdaDqd/vhnXHDBBevXr//Zz352+umnT5gwoa2t7cknn8zLy4tEIl/96leX\nL1++J390tdLS0nPPPXfhwoUf85yKiopf/epX27Zt2/+XTaVSK1eu/OC2lL16/PHH73n01/et\neionJ2f/XxmAEEk1NDX/cn3Lb1/LGXVUbPz/u+fBJU899VRGRkZeXl5tbe2gQYMuu+yyk046\nKeiZAAABa29v/4cppz1x/39NmDAh6C0ftu//E3XjjTdOmjTpuuuuW79+/Ve+8pXLLrts9OjR\nJ5100uuvv75hw4ZLLrmkG1ZGIpFdu3YdddRRH/+cUaNGLVu27IBe9s0335w1a1Zra+vHPKe1\ntTXvvOu/9+uWaPTjngZASKWTbem2tkjs2NgJ/y8Si0X+LxIZ85mjRs9sb29Pp9OHZGRkZGQ8\n1Bx5qKYu6KUAAMHLG39h0BP2bt+BY/z48b/85S+fe+65SCTyhS984ZVXXpk/f/6yZcui0ej5\n55/fbe8HKSsr27hx48c/53//93/Lyg7s9L4jjjjinXfe+fjnLFiwYNasWVsrr91z3woAvUbz\n+k3xyup0e/vAS87PKx8fiUaDXgQA0KMlk8nsy26JXHNW0EP2Yr/eS3ziiSeeeOKJkUgkGo3e\neuutN99887vvvltSUtKdR5ZccMEFd91117hx46688srs7OwPPdrU1HTbbbctX778+uuv77ZJ\nAIRX29vvxSurW158OX/qxKKZ02K53oQIABBu+/4MjhUrVhx11FFjxozpnkEfJZFInHnmmb/5\nzW/y8/PHjx9/2GGH5eXlpdPpxsbGN95447nnnmtubp44ceKqVas6/T6LPXdwNDQ0uIMDoBfo\naGpOPLCq/tGa3DEjD7ns01mHDg16EQBAaCSTyezs7KeffjqUn8Fx8cUX33LLLYEHjqKiomee\neeZHP/rRPffcs3bt2lQq9cFDWVlZJ5544mWXXXbZZZdlZGQEOBKAHi2dbqx5rvbuZbEBuSX/\n9NXcE48LehAAAJ1m34Hjb/7mb5566qlvfetbsVisGwZ9jH79+l1zzTXXXHNNS0vLm2++2dDQ\nEIlECgoKDj/88H79+gW7DYAervXVN+I/eTD55juF0ycXzpgSzXLgKwBAr7Lvb+9+9rOfXXPN\nNeedd97nPve5Y445prCw8ENPOProo7tm20fKyckZOXJkN/9NAQipVLyu9t7ljTXP55WPGzL7\naxlFBUEvAgCg8+07cAwd+vs3J69evXqvT9jnp3gAQCDS7amGR9cllqzMLB1S+v1rsj81IuhF\nAAB0lf36DI5+/fplZWVFHZ4HQHg0r98UX7S0o3l3UcW0gnPKI0G/0RIAgC6178CxZMmSj3qo\nqalpzwdhAEDP0fbOjvii6t0bf1swtbyo4rxY/+471BwAgKB8ov+dtXz58hNOOKGzpgDAJ5Ru\nTSYeXLX92nnptray22cfctlF6gYAQB+xX58hv3PnziVLlmzdurW9vf2Diy0tLStXrmxsbOyy\nbQCw3/YcAbt4eTQzo3jWzLxJJwc9CACAbrXvwLF169bx48fv2LFjL1+cmTl37twuWAUAByC5\nZduuhdXJrW8VTp9cOOOsaFZW0IsAAOhu+w4cc+bMaWlp+eEPfzhq1KgzzzzzJz/5yaGHHrp2\n7drFixcvXLhw6tSp3bASAPaqo6EpUfVI/SNP9T9hzLD5czIHHxL0IgAAgrHvwLFu3brLL7/8\n8ssvb2lpiUQiY8aMOeWUU6ZOnXrxxRefeeaZK1asOO2007p+JwD8mXQq1bB6XeKBhzMOKSyZ\n843cvx4V9CIAAIK078DxzjvvjBgxIhKJxGKxSCSSTCb3XD/++OMvv/zyb3/722vWrOnSiQDw\nIS2bXt5VWZWK1xVdfJ4jYAEAiOzPKSr5+fnvvfdeJBLp169fXl7eli1bPnho9OjR69ev78J1\nAPDn2nfW7vyPe9797n9kjzhs2H/cXHDe6eoGAACR/QkcEydO/PGPf7x27dpIJPJXf/VXP/rR\njz44OeWJJ57Izs7u0n0AsMeeI2DfvvK77TviZbfPHnTl5zIK8oIeBQBAT7Hvt6jceOONkyZN\nuu6669avX/+Vr3zlsssuGz169EknnfT6669v2LDhkksu6YaVAPRxzes3xRdWpVOp4lkVeeXj\nI9Fo0IsAAOhZ9h04xo8f/8tf/vK5556LRCJf+MIXXnnllfnz5y9btiwajZ5//vnz58/v+pEA\n9F3JrW/FK6tbX349f8rEopnTYrk5QS8CAKAniqbT6QP9mpaWlnfffbekpCQ3N7crNvU0CxYs\nmDVrVkNDQ16ee6EBuk9HU3PigVX1q2v6jx19yGUXZZYMCnoRAEBfl0wms7Ozn3766QkTJgS9\n5cP2cQdHa2vrxo0bm5ubjz322KFDh+65mJOTc8QRR3T5NAD6rHS6sea52ruXxfL6l8z+Wu4J\nY4IeBABAT/dxgePuu++++uqrE4lEJBKJRqMVFRULFizIz8/vrm0A9EUtL70Sr6xue2dH4fTJ\nhTOmRLP2/W5KAAD4yO8aa2pqvvjFL2ZkZEydOrW4uPjZZ5+9//77d+/evWzZsu7cB0DfkYon\nau9d0VjzfF75uJI5V2QUSeoAAOyvjwwcd9xxRzQafeKJJyZOnBiJRJLJZEVFxbJly1588cXj\njjuuGxcC0Pul21MNj65LLFmZWTqkdN612cccGfQiAABC5iMDx7PPPjtlypQ9dSMSifTr1++W\nW25ZtmxZTU2NwAFAJ2pevym+aGlH8+6iimkF505yBCwAAAfhIwPHrl27jjnmmD+9sueXu3bt\n6vJRAPQNbdvfj/90acvG3+VPnVhUcV6sf584nAsAgK7wkYGjo6PjQ6fA5uTkRCKRVCrV5aMA\n6O06WlrrV/x33c8fzR51dNkds7MOKw16EQAA4eaj6QHoXnuOgF38UDQne9BVXxhw6tigBwEA\n0BsIHAB0n9bXtsUXViXfeLtw+uTCGWdFs7KCXgQAQC/xcYHjl7/85S233PKhi2vXrv3Qxb98\nDgB8SCpRn3jg4YY1v+p/wphh8+dkDj4k6EUAAPQq0XQ6vfcH9vtD7D/qFXqNBQsWzJo1q6Gh\nIS8vL+gtAOGTTqUaVq9LLFmZWTLokC99OmfUUUEvAgDgICWTyezs7KeffnrChAlBb/mwj7yD\nY/Hixd25A4BeqWXT5l2V1anauqKKaQXnlEdisaAXAQDQO31k4PjsZz/bnTsA6GXa391Ze+/y\npmc35JWPG/j5qzIK3AQHAEAX8iGjAHSydGuybvmaumWPZ488ouyO2f2GDwt6EQAAvZ/AAUBn\nal6/Kb6wKp3qKJ5VkVc+PrLfn+gEAACfhMABQOdIbn0rvrCq9ZWt+VMmFn3m72I52UEvAgCg\nDxE4APikOhqbEw+uql9d03/s6GE/mJtZMijoRQAA9DkCBwCfQDrdWPNc7U+XxfL7l9wwK3fs\n6KAHAQDQRwkcAByklpdeiS+sbt8ZL5wxpWDaGdHMjKAXAQDQdwkcABywVDxRe++Kxprn88rH\nlcy9IqMoP+hFAAD0dQIHAAcgnWyrX7W2rnp11rCS0nnXZh9zZNCLAAAgEhE4ANh/zes3xSur\n023tAz9/Yf7kCY6ABQCg5xA4ANi3tu3vxRctbXlhc/7UiUUzp8Vyc4JeBAAAf0bgAODjdDTt\nrlv2WP3KJ7JHHV12x+ysw0qDXgQAAHshcADwEfYcAbv4oVhOzqCrvjDg1LFBDwIAgI8kcACw\nF62vbYsvfDD5xvbC6ZMLZ5wVzcr60BM2bdpUWVm5adOm5ubmMWPGXHTRRVOnTg1kKgAARCKR\nWNADAOhZUrV1uxbc/87s2zPy84b9YG7RP5z7l3Xjhz/84QknnLBx48ZTTz31/PPPr62tPf/8\n87/4xS92dHQEshkAANzBAcDvpVOphtXrEktWZg4dNPR7V+cce9Ren7Z27dqrr776pz/96Wc/\n+9kPLv7P//zPlClTbrvtttmzZ3fXXgAA+COBA4BIJBLZ/cLmeGVVKlFfVDGt4JzySOwjb/G7\n/fbbL7nkkj+tG5FI5MQTT5w3b97cuXO/9a1vZWRkdP1eAAD4M96iAtDXtb27Y8edC9+b96Oc\nUUcN+4+bC847/WPqRiQS+dWvfnX++ef/5fXzzz9/586dL7/8cpctBQCAj+QODoC+K92arFu+\npm7Z49nHHFF22/X9hg/bn69qbGwsLCz8y+tFRUWRSKShoaGTVwIAwH4QOAD6pHS66dkNtXf/\nPN2RLp5VkVc+PhKN7ueXDh8+fPPmzZMnT/7Q9d/97nfRaPTwww/v7K0AALBvAgdAn5N8/a34\nwqrWLdsKzj298KKzYznZB/TlF1544Y9+9KMvfvGL/fv3/9Prt99++2mnnTZ06NBOHQsAAPvF\nZ3AA9CEdjc3xyurt198WG5A7bP6cgZ+dfqB1IxKJzJ49u7W19eyzz964ceOeK2+//faXvvSl\nFStWzJ8/v7MnAwDAfnEHB0CfkE51ND7xTOK+X8TyB5TcMCt37OiDfqlDDjlk7dq1X/nKV44/\n/viCgoKcnJz3339/9OjRa9asOfHEEztxMwAA7D+BA6D3a/m/V+ILq9p31RbOmFIw7Yxo5ic9\nxvWwww5bvXr1G2+88cILL+zevXv06NGjR4+OfezZKwAA0KUEDoDerH1XInHfisaa5/PKx5V8\n+8qMwvxOfPHhw4cPHz68E18QAAAOmsAB0Dulk231q9bWVa/OOnRo6bxrs485MuhFAADQhQQO\ngF6oef2meGV1uq194OcvzJ88Yf+PgAUAgJASOAB6lbbt78UXLW15YXP+1IlFM6fFcnOCXgQA\nAN1B4ADoJTqadtcte6x+5RM5o48uu/OGrEOHBr0IAAC6j8ABEH7pdGPNc7X3PBTLzRn8ra/0\nP/G4oAcBAEB3EzgAwq311TfilVXJN7YXTp9cOGNKNMsf7AAA9EW+DwYIq1RtXe3PljfWPD/g\nlOMHX/ulzEEDg14EAACBETgAwiedSjWsXpdYsjJz6KCh37s659ijgl4EAAABEzgAQmb3C5vj\nlVWpRH1RxbSCc8ojsVjQiwAAIHgCB0BotL27o3bR0uYNL+WfcWrRZ/4uIz8v6EUAANBTCBwA\nIZBuTdYtX1O37LHsT40ou312v8PLgl4EAAA9i8AB0LOl003Pbqi9++eRdLp41sy8SScHPQgA\nAHoigQOg50pueXNXZVVyy5sF555eeNHZsZzsoBcBAEAPJXAA9EQdjc2JB1fVr67pP3b0sPlz\nMocUB70IAAB6NIEDoGdJpzoan3im9r4VGQV5JTd+Pff4UUEvAgCAEBA4AHqQlhdfjldWt++q\nLfqH8/LPLo9mOAIWAAD2i8AB0CO070ok7lvRWPN8Xvm4km9fmVGYH/QiAAAIE4EDIGDpZFvd\nQ4/XPfR4v8PLSm/9ZvbII4JeBAAA4SNwAASpef2meGV1ur29+GsVeeXjI9Fo0IsAACCUBA6A\nYLS9/V58UXXLppfzp04smjktlpsT9CIAAAgxgQOgu3U0NSceWFX/aE3umJFld96QdejQoBcB\nAEDoCRwA3Sidbqx5rvaeh2L9c0r+6au5Jx4X9CAAAOglBA6AbtL66hvxhVXJbdsLp08unDEl\nmuVPYAAA6DS+vQbocql4Xe29yxtrnh9wyvGDv/mlzEEDg14EAAC9jcAB0IXSqVTD6nWJJSsz\nSweXfu+a7GNHBL0IAAB6J4EDoKvsfmFzvLIqVddQVDGt4JzySCwW9CIAAOi1BA6Aztf2zo74\nT5fu3vBSwdTyoorzYv1zg14EAAC9nMAB0JnSrcm65Wvqlj2W/akRZbfP7nd4WdCLAACgTxA4\nADrJniNgFy+PZsSKZ83Mm3Ry0IMAAKAPETgAOkFyy5u7FlYlt75VOH1y4YyzollZQS8CAIC+\nReAA+EQ6GpoSVY/Ur67pP3b0sH+/KXNIcdCLAACgLxI4AA5SOtXRsLom8cDDGQMLSm76eu5f\njwp6EQAA9F0CB8DBaNn0cnxRdfuuRNHF5+WfXR7NcAQsAAAESeAAODDtO2sT9/+iseb5vPJx\nJd++MqMwP+hFAACAwAGw3/5wBOzj/YaXlf7zddlHDw96EQAA8HsCB8B+aV6/KV5ZnW5vL55V\nkVc+PhKNBr0IAAD4I4EDYB/a3n4vXlnd8uLL+VMnFs2cFsvNCXoRAADwYQIHwEfqaGpOPLCq\n/tGa/sePHvaDuZlDBwW9CAAA2DuBA2Bv0unGmudq714WG5Bbcv3Xck8YE/QgAADg4wgcAB/W\n+uob8Z88mHzzncLpkwtnTIlm+aMSAAB6Ot+1A/xRKl5Xe+/yPUfADpn9tYyigqAXAQAA+0Xg\nAIhEIpF0e6rh0XWJJSszS4eUfv+a7E+NCHoRAABwAAQOgEjz+k3xRUs7mncXVUwrOKc8EosF\nvQgAADgwAgfQp7Vtfz/+06UtG3+XP3ViUcV5sf65QS8CAAAOhsAB9FHp1mTd8jV1yx7LPnZE\n6e3X9zu8LOhFAADAwRM4gL5nzxGwi5dHMzOKZ83Mm3Ry0IMAAIBPSuAA+pbklm27FlYnt75V\nOH1y4YyzollZQS8CAAA6gcAB9BUdDU2JqkfqH3mq/wljhs2fkzn4kKAXAQAAnUbgAHq/dCrV\nsHpd4oGHMw4pLJnzjdy/HhX0IgAAoJMJHEAv17Lp5V2VVal4XdHF5zkCFgAAeiuBA+i12nfW\nJu7/RWPN83nl4wZ+56qMgrygFwEAAF1F4AB6oT8cAft49sjhZbfP7nfEsKAXAQAAXUvgAHqb\n5vWb4gur0qmO4lkVeeXjI9Fo0IsAAIAuJ3AAvUdy61vxhVWtr2zNnzKxaOa0WG5O0IsAAIBu\nInAAvUFHU3PigVX1q2v6jx097AdzM0sGBb0IAADoVgIHEHLpdGPNc7V3L4vl9S+Z/bXcE8YE\nPQgAAAiAwAGEWMtLr8QXVre9u6Nw+uTCC6dGMzOCXgQAAARD4ABCKRVP1N67Ys8RsCVzr8go\nyg96EQAAECSBAwiZdHuq4dF1iSUrM0uHlM67NvuYI4NeBAAABE/gAMKkef2m+KKlHc27iyqm\nFZw7yRGwAADAHgIHEA5t29+PL6pueWFz/tSJRRXnxfrnBr0IAADoQQQOoKfraGmtX/HfdT9/\nNHvU0WV3zM46rDToRQAAQI8jcAA92J4jYBc/FM3JHnTVFwacOjboQQAAQA8lcAA9VOtr2+IL\nq5JvvF04fXLhjLOiWVlBLwIAAHougQPocVKJ+sQDDzes+VX/E8YMmz8nc/AhQS/ai127dt1/\n//0bN26sr68fPXr0+eefP3asG0wAACAwsaAHAPxROpWqf3jt21d+t/WVN4Z+9+ohN8zqmXXj\nscceO+aYY+68887du3cXFxc/9thjJ5100je/+c10Oh30NAAA6KPcwQH0FC2bNu+qrE7V1hVV\nTCs4pzwS66EF9pVXXpkxY8YVV1xx6623ZmRk7Ln45JNPXnDBBaWlpdddd12w8wAAoG/qoT8/\nAH1K+7s7d9y58N3v/jB7xGHD7rq54LzTe2zdiEQit91227hx4/71X//1g7oRiUT+9m//9rbb\nbrv11luTyWSA2wAAoM/quT9CAH1BujWZeHDV29fMS9U1lt0xe9CVn8soyAt61D6sXbu2oqLi\nL69ffPHFtbW1Gzdu7P5JAACAt6gAgWlevyn+kwfTHeniWRV55eMj0WjQi/ZLbW3t4MGD//J6\nUVFRdnZ2bW1t908CAAAEDiAAydffildWtb6yNX/KxKLP/F0sJzvoRQegtLR069atf3l9+/bt\nra2tpaWl3b4IAADwFhWge3U0Nscrq7dff1usf+6wu24+5LKLwlU3IpHItGnTKisr//KzNv7r\nv/7riCOOOO644wJZBQAAfZzAAXSXdLrxqV+/feV3d294qeSGWUNumJU5pDjoTQfjuuuuq6ur\nmzFjxvbt2/dcSSaT//Zv//Yv//Ivd955ZzQkb7QBAIBexltUgO7Q8tIr8YXV7TvjhTOmFEw7\nI5qZse+v6amKi4ufeOKJmTNnDh8+fOTIkQUFBb/97W9jsVhlZeWFF14Y9DoAAOijBA6ga6Xi\nidp7VzTWPJ9XPq5k7hUZRflBL+oExxxzzPr165955pkXXnghkUjcdNNNkyZNKigoCHoXAAD0\nXQIH0FXSybb6VWvrqldnDSspnXdt9jFHBr2oM0Wj0QkTJkyYMCHoIQAAQCQicABdpHn9pnhl\ndbqtfeDnL8yfPCEsR8ACAAAhJXAAnaxt+3vxRUtbXticP3Vi0cxpsdycoBcBAAC9n8ABdJqO\npt11yx6rX/lEzuijy+68IevQoUEvAgAA+gqBA+gM6XRjzXO1ix+K5eQMuuoLA04dG/QgAACg\nbxE4gE+q9bVt8YUPJt/YXjh9cuGMs6JZWUEvAgAA+hyBAzh4qdq6xIOrGtb8qv8JY4b9YG7m\noIFBLwIAAPoogQP6nI6OjkgkEovFPsmLpFOphtXrEktWZg4dNPR7V+cce1QnrQMAADgYAgf0\nFalU6j//8z8XL1780ksvpdPpMWPGXHrppd/4xjcyMjIO9KV2v7A5XlmVStQXVUwrOKc88sla\nCQAAwCcncECfkEwmL7jggl//+tdXXnnld7/73Ugk8utf//qWW255+OGHV6xY0a9fv/18nbZ3\ndyTuXdH03Mb8M04t+szfZeTndeVqAACA/SVwQJ9w5513/uY3v1m/fv2RRx6558rZZ5/9uc99\n7tRTT7399ttvuummfb5CujVZt3xN3bLHso85suy26/sNH9bFkwEAAA6AG8uh90un0z/+8Y9v\nuOGGD+rGHkceeeRNN9304x//OJ1Of/zXNz3zv29f9b3G//5V8ayZQ79zlboBAAD0NO7ggN4v\nkUhs27bt9NNP/8uHJk2a9I//+I/xeLy4uHivX5t8/a34wqrWLdsKzj298KKzYznZXbsVAADg\noAgc0Pu1t7dHIpHMzL38ft9zMZVK/eVDHY3NiQdX1a+u6T929LD5czKH7L2AAAAA9AQCB/R+\ngwYNGjx48PPPPz9mzJgPPbR+/fri4uJBgwb96cV0qqPxiWcS9/0ilj+g5IZZuWNHd+NYAACA\ngyFwQO8XjUYvvfTSW2+99YILLigqKvrgeiKRmDdv3qWXXhr7k3NeW/7vlfjCqvZdtYUzphRM\nOyOaecCHyAIAAHQ/HzIKfcLNN9+cm5t7yimn3Hfffa+99tqWLVvuv//+U045JTs7+5Zbbtnz\nnPZdiZ3/cc+7t9zV78hDh911c+EFZ6kbAABAWLiDA/qEwsLCdevWzZkz5/LLL08kEnuuXHrp\npfPmzSsoKEgn2+pXra2rXp116NDSeddmH3PkPl8QAACgRxE4oK8oKCi466677rrrrm3btkUi\nkcMPP3zP9eb1m+KV1em29oGfvzB/8oRINBroTAAAgIMhcECf80HaaNv+XryyumXTy/lTJxbN\nnBbLzQl2GAAAwEETOKAv6mjaXbfssfqVT+SMPrrszhuyDh0a9CIAAIBPROCAPiadbqx5rvae\nh2K5OYO/9ZX+Jx4X9CAAAIBOIHBAH9L66hvxyqrkG9sLp08unDElmuVPAAAAoJfw4w30Cana\nutqfLW+seX7AKccPvvZLmYMGBr0IAACgMwkc0MulU6mG1esSS1Zmlg4e+r2rc449KuhFAAAA\nnU/ggN5s9wub45VVqUR9UcW0gnPKI7FY0IsAAAC6hMABvVPbOztqf7q0ecNL+WecWvSZv8vI\nzwt6EQAAQBcSOKC3Sbcm65avqVv2WPanRpTdPrvf4WVBLwIAAOhyAgf0Iul007Mbau/+eSSd\nLp41M2/SyUEPAgAA6CYCB/QSyS1v7qqsSm55s+Dc0wsvOjuWkx30IgAAgO4jcEDodTQ2Jx5c\nVb+6pv/Y0cPmz8kcUhz0IgAAgO4mcECIpVMdjU88U3vfioyCvJIbv557/KigFwEAAARD4ICw\nannx5Xhldfuu2qJ/OC//7PJohiNgAQCAvkvggPBp35VI3Leiseb5vPJxJd++MqMwP+hFAAAA\nARM4IEzSyba6hx6ve+jxfoeXld76zeyRRwS9CAAAoEcQOCA0mtdvildWp9vbi79WkVc+PhKN\nBr0IAACgpxA4IATa3n4vvqi6ZdPL+VMnFs2cFsvNCXoRAABAzyJwQI/W0dSceGBV/aM1uWNG\nlt15Q9ahQ4NeBAAA0BMJHNBTpdONNc/V3vNQrH9OyT99NffE44IeBAAA0HMJHNATtb76Rnxh\nVXLb9sLpkwtnTIlm+a0KAADwcfzUBD1LKl5Xe+/yxprnB5xy/OBvfilz0MCgFwEAAISAwAE9\nRTqVali9LrFkZWbp4NLvXZN97IigFwEAAISGwAE9wu4XNscrq1J1DUUV0wrOKY/EYkEvAgAA\nCBOBAwLW9s6O+E+X7t7wUsHU8qKK82L9c4NeBAAAED4CBwQm3ZqsW76mbtlj2ceOKLt9dr/D\ny4JeBAAAEFYCBwRhzxGwi5dHM2LFs2bmTTo56EEAAADhJnBAd0tueXPXwqrk1rcKp08unHFW\nNCsr6EUAAAChJ3BA9+loaEpUPVK/uqb/2NHD/v2mzCHFQS8CAADoJQQO6A7pVEfD6prEAw9n\nDCwouenruX89KuhFAAAAvYrAAV2uZdPL8UXV7bsSRRefl392eTTDEbAAAACdTOCALtS+szZx\n/y8aa57PKx9Xcss/ZhTkBb0IAACgdxI4oEv84QjYdHojTQAAIABJREFUx/sNLyv95+uyjx4e\n9CIAAIDeTOCAzte8flN8YVU6lSqeVZFXPj4SjQa9CAAAoJcTOKAztb39XryyuuXFl/OnTiya\nOS2WmxP0IgAAgD5B4IDO0dHUnHhgVf2jNf2PHz3sB3Mzhw4KehEAAEAfInDAJ5ZON9Y8V3v3\nstiA3JLrv5Z7wpigBwEAAPQ5Agd8Ii0vvRqvrGp7Z0fh9MmFM6ZEs/yeAgAACIAfxuAgpeJ1\ntfcu//0RsHMuzygqCHoRAABA3yVwwAFLt6caHl2XWLIys3RI6fevyf7UiKAXAQAA9HUCBxyY\n5vWb4ouWdjTvLqqYVnDuJEfAAgAA9AQCB+yvtu3vx3+6tGXj7/KnTiyqOC/WPzfoRQAAAPye\nwAH7lm5N1i1fU7fssexjR5TdMTvrsNKgFwEAAPBnBA74WHuOgF28PJqZUTxrZt6kk4MeBAAA\nwF4IHPCRklu27VpYndz6VuH0yYUzzopmZQW9CAAAgL0TOGAvOhqaElWP1D/yVP8TxgybPydz\n8CFBLwIAAODjCBzwZ9KpVMPqdYkHHs4cUjz0O1fljD466EUAAADsm8ABf9SyafOuyupUvK7o\n4vMKzimPxGJBLwIAAGC/CBwQiUQi7e/urL13edOzG/LKxw38zlUZBXlBLwIAAOAACBz0dX84\nAvbx7JFHlN0+u98Rw4JeBAAAwAETOOjTmtdvii+sSqc6imdV5JWPj0SjQS8CAADgYAgc9FHJ\nrW/FF1a1vrI1f8rEopnTYrk5QS8CAADg4Akc9DkdTc2JB1bVr67pP3b0sB/MzSwZFPQiAAAA\nPimBg74knW6sea727mWxvP4ls7+We8KYoAcBAADQOQQO+oqWl16JL6xuf29nwflnFl44NZqZ\nEfQiAAAAOo3AQe+Xiidq713RWPN8Xvm4krlXZBTlB70IAACATiZw0Jul21MNj65L3P+LrGEl\npfOuzT7myKAXAQAA0CUEDnqt5vWb4ouWpluTAz9/Yf7kCY6ABQAA6MUEDnqhtu3vxxdVt7yw\nOX+qI2ABAAD6BIGDXqWjaXfdssfqVz6RPerosjtmZx1WGvQiAAAAuoPAQW+x5wjYxQ9Fc7IH\nXfWFAaeODXoQAAAA3UfgoDdofW1bfGFV8o23C6dPLpxxVjQrK+hFAAAAdCuBg3BL1dYlHlzV\nsOZX/U8YM2z+nMzBhwS9CAAAgAAIHIRVOpVqWL0usWRlZsmgod+9OmfUUUEvAgAAIDACB6HU\nsmnzrsrqVG1dUcW0gnPKI7FY0IsAAAAIksBByLS9uyNx74qmZzfklY8b+IWrMvLzgl4EAABA\n8AQOQiPdmqxbvqZu2ePZI48ou2N2v+HDgl4EAABATyFwEA7N6zfFf/JguiNdPKsir3x8JBoN\nehEAAAA9iMBBT5d8/a14ZVXra9sKzj298KKzYznZQS8CAACgxwl34Egmkxs3bmxsbDziiCOO\nPPLIoOfQyToamxMPrqpfXdN/7Ohh8+dkDikOehEAAAA9VGjOnvj+97//5JNP/umVBQsWDB06\ndPz48WecccaIESNOOumkDRs2BDWPzpVOdTQ8/vTbV35394bfltwwa8gNs9QNAAAAPkZo7uCY\nO3fu9ddf/7d/+7d7fvnwww/PmjUrOzt7xowZQ4YMefHFF59++unTTz/9f/7nf4466qhgp/IJ\ntfzfK/HK6vad8cIZUwqmnRHNzAh6EQAAAD1daALHh1xzzTWFhYXPPPPMqFGj9lz5+c9/ftFF\nF82bN6+ysjLYbRy0VDxRe++Kxprn88rHlcy9IqMoP+hFAAAAhEMoA8eOHTteeeWVG2+88YO6\nEYlELrzwwunTpz/22GMBDuOgpZNt9avW1lWvzhpWUjrv2uxjfKIKAAAAByCUgaOlpSUSifxp\n3djjuOOOe/jhh4NYxCfSvH5TvLI63dY+8PMX5k+e4AhYAAAADlQoA0dZWVlhYeFbb731oevb\nt2/Pz/emhjBp2/5efNHSlhc250+dWDRzWiw3J+hFAAAAhFJoTlGJRCLbtm1bv379q6++Wltb\n+41vfGPhwoXNzc0fPPq73/3ugQceOO200wJcyP7raNpd+7Pl26+9NZJKld15wyGXXaRuAAAA\ncNDCdAfH/ffff//99//plUceeeTv//7vI5HIfffd99WvfnX37t1z5849oNdsbGy87bbbksnk\nxzzH6bOdLJ1urHmudvFDsZycQVd9YcCpY4MeBAAAQOiFJnAsWrQo8Sfq6uoSicTAgQP3PJpI\nJIqKipYsWTJu3LgDetmmpqbf/OY3ra2tH/Oct99+OxKJpNPpgx7PB1pffSNeWZV8Y3vh9MmF\nM86KZmUFvQgAAIDeINo7fm5vbGzs379/LNYl77hZsGDBrFmzGhoa8vLyuuL1+4hUbV3iwVUN\n//3MgJP/euDnL8wcNDDoRQAAAByYZDKZnZ399NNPT5gwIegtHxaaOzg+nvTQk6VTqYbV6xJL\nVmYOHTT0u1flHHtU0IsAAADobcIdOO64446HHnrol7/8ZdBD+Ei7X9gcr6xKJeqLKqYVnFMe\n6Zq7bAAAAOjjwh04Xn311aeffjroFexd27s7ahctbd7wUv4ZpxZ95u8y8t1lAwAAQFcJd+Cg\nZ0q3JuuWr6lb9lj2MUeW3T673+FlQS8CAACglxM46FTpdNOzG2rv/nkknS6eNTNv0slBDwIA\nAKBPEDjoNMnX34ovrGrdsq3g3NMLLzo7lpMd9CIAAAD6inB/4uO//Mu/vPnmm0GvINLR2Byv\nrN5+/W2xAbnD5s8Z+Nnp6gYAAADdKdx3cBQVFRUVFQW9ok9Lpzoan3gmcd8vYvkDSm6YlTt2\ndNCLAAAA6IvCHTgIVsuLL8crq9t31RbOmFIw7YxoZkbQiwAAAOijBA4ORvuuROK+FY01z+eV\njyv59pUZhflBLwIAAKBPEzg4MOlkW/2qtXXVq7MOHVo679rsY44MehEAAAAIHByI5vWb4pXV\n6bb2Q77yD3nl4yPRaNCLAAAAIBIRONhPbdvfi1dWt2x6OX/qxKKZ02K5OUEvAgAAgD8SONiH\njqbdiQcern+0JnfMyLI7b8g6dGjQiwAAAODDBA4+WjrdWPNc7T0PxXJzhvzTV/ufeFzQgwAA\nAGDvBA72rvXVN+ILq5LbthdOn1w4Y0o0y38qAAAA9Fx+auXDUvG62nuXN9Y8P+CU4wd/80uZ\ngwYGvQgAAAD2QeDgj9KpVMPqdYklKzNLB5d+75rsY0cEvQgAAAD2i8DB7+1+YXO8siqVqC+q\nmFZwTnkkFgt6EQAAAOwvgYNI2zs74j9dunvDS/lnnDrwM+fH8gcEvQgAAAAOjMDRp6Vbk3XL\n19Qteyz7UyPKbp/d7/CyoBcBAADAwRA4+qp0uunZDbV3/zySThfPmpk36eSgBwEAAMDBEzj6\nouSWN3dVViW3vFl4wVmFF5wV7ZcV9CIAAAD4RASOvqWjoSlR9Uj96pr+Y0cPmz8nc0hx0IsA\nAACgEwgcfUU61dH4xDO1963IKMgrufHrucePCnoRAAAAdBqBo09oefHleGV1+65E0T+cm392\neTTDEbAAAAD0KgJHL9e+K5G4b0VjzfN55eNKvn1lRmF+0IsAAACg8wkcvVY62Vb30ON1yx7v\nN7ys9NZvZo88IuhFAAAA0FUEjt6pef2meGV1ur29eFZFXvn4SDQa9CIAAADoQgJHb9P29nvx\nRdUtm17OnzqxaOa0WG5O0IsAAACgywkcvUdHU3PigVX1j9bkjhlZducNWYcODXoRAAAAdBOB\no1dIpxtrnqu956FY/5ySf/pq7onHBT0IAAAAupXAEXqtr74R/8mDyTffKZw+uXDGlGiWf6cA\nAAD0OX4YDrFUvK723uWNNc8POOX4wdd9OXPQwKAXAQAAQDAEjlBKp1INq9cllqzMLB1c+v1r\nsj81IuhFAAAAECSBI3x2v7A5vvDBVH1jUcW0gnPKI7FY0IsAAAAgYAJHmLS9syP+06W7N7xU\nMLW8qOK8WP/coBcBAABAjyBwhEO6NVm3fE3dsseyjx1RdvvsfoeXBb0IAAAAehCBo8fbcwTs\n4uXRzIziWTPzJp0c9CAAAADocQSOHi25ZduuhdXJrW8VTp9cOOOsaFZW0IsAAACgJxI4eqiO\nhqZE1SP1q2v6jx097N9vyhxSHPQiAAAA6LkEjh7n90fAPvBwxsCCkpu+nvvXo4JeBAAAAD2d\nwNGztGx6Ob6oun1Xouji8/LPLo9mOAIWAAAA9k3g6Cnad9Ym7v9FY83zeeXjSm75x4yCvKAX\nAQAAQGgIHMH7wxGwj/cbXlb6z9dlHz086EUAAAAQMgJHwJrXb4ovrEqnUsWzKvLKx0ei0aAX\nAQAAQPgIHIFpe+vd+KKlLf/3cv6UiUUzp8Vyc4JeBAAAAGElcASgo6k58cCq3x8B+4O5mSWD\ngl4EAAAA4SZwdK90urHmudq7l8Xy+pfM/lruCWOCHgQAAAC9gcDRfVpeejVeWdX2zo7C6ZML\nZ0yJZvmHDwAAAJ3Dz9jdIRVP1N674vdHwM65PKOoIOhFAAAA0KsIHF0r3Z5qeHRdYsnKzNIh\npd+/JvtTI4JeBAAAAL2QwNGFmtdvii9a2tG8u6hiWsG5kxwBCwAAAF1E4OgSbdvfj/90acvG\n3+VPnVhUcV6sf27QiwAAAKA3Ezg6Wbo1Wbd8Td2yx7KPHVF2x+ysw0qDXgQAAAC9n8DRefYc\nAbv4oWhmZvGsmXmTTg56EAAAAPQVAkfnSG7ZtusnVck33i6cPrlwxlnRrKygFwEAAEAfInB8\nUh0NTYmqR+ofear/CWOGzZ+TOfiQoBcBAABAnyNwHLx0KtWwel3igYczhxQP/e7VOaOOCnoR\nAAAA9FECx0Fq2bR5V2V1Kl5XdPF5BeeUR2KxoBcBAABA3yVwHLD2d3fW3ru86dkNeeXjBn7n\nqoyCvKAXAQAAQF8ncByAPxwB+3j2yCPKbp/d74hhQS8CAAAAIhGBY/8lN/w2ce8v0qmO4lkV\neeXjI9Fo0IsAAACA3xM49ss/HXdqw4/uK5x+ZuGMKdHsfkHPAQAAAP6MwLFfNtW+P/Cfry04\n4rCghwAAAAB74eyP/fLI26/FBg0MegUAAACwdwIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAA\nEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcA\nAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoC\nBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQ\negIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAA\nABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIH\nAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6\nAgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAA\nEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcA\nAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoC\nBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQ\negIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAA\nABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIH\nAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6\nAgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAA\nEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcA\nAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoC\nBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQ\negIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQegIHAAAAEHoCBwAA\nABB6AgcAAAAQegIHAAAAEHoCBwAAABB6AgcAAAAQeplBDzhg6XT69ddf37JlS0NDQyQSKSws\nHDly5GGHHRb0LgAAACAwYQoctbW18+bNW7x48fvvv/+hhw4//PAvf/nL1113XW5ubiDbAAAA\ngACFJnC88847p5122uuvvz5y5Mhzzz13+PDhAwYMiEQi9fX1r7322lNPPXXzzTcvXbr0ySef\nHDhwYNBjAQAAgG4VmsAxd+7ct95668EHH/z0pz/9l4+mUqkFCxZcccUV3/nOd+bPn9/98wAA\nAIAAheZDRh9++OFLL710r3UjEon8/+3deXSV9Z0/8G/MRlgk7DQsAQrHBUYRUqyIZQCXYilL\nmSo4FIqiI9NWpKJDPa1LrVtxqYI6rT2VotZaWi09Mg4eqXJAW3G0OAq0A1Qx1bAFQ4mQhCT3\n98f9TU4mQgiR5PJNXq8/PPd+n+V+7vP1w728eZ7npqen/+u//usll1zyzDPPNHNhAAAAQMpF\nE3AUFxd/9rOfrX+d0047befOnc1TDwAAAHDiiCbgyMvLe+utt+pf509/+lNeXl7z1AMAAACc\nOKIJOCZPnrx8+fJ77rmnvLz8k0s//vjjm2++ecWKFZdeemnz1wYAAACkVjQ3Gb3lllvWrl17\n/fXXf//73x8xYkSfPn3at2+fSCRKS0u3b9++fv36AwcOnHfeed/97ndTXSkAAADQ3KIJOHJz\nc//whz889NBDy5Yte/nll6uqqmoWZWZmDh8+/PLLL7/88svT09NTWCQAAACQEtEEHCGErKys\n+fPnz58/v6ysrLCwcP/+/SGEk08+uW/fvllZWamuDgAAAEiZmAKOGm3atBk0aNAnx4uLiz/6\n6KOBAwc2f0kAAABACkVzk9GGWLRo0WGDDwAAAKBla1EBBwAAANA6RXmJynG0c+fOyy+/vKKi\nop51PvjggxBCIpForqIAAACAYxNNwFFQUHDUdZJJxDFp165dQUFBeXl5Pet06dJl8+bN2dnZ\nx7pzAAAAoHmkxXJiQvL3XzMzM+tZp7Kysqqq6ri/o1dfffXcc88tLy/3Wy0AAAC0ZhUVFdnZ\n2a+88srIkSNTXUtd0dyD4/rrr2/Xrt0777xTdmQLFixIdZkAAABACkQTcNx2220DBw6cPn36\noUOHUl0LAAAAcGKJJuDIzMx88sknN27ceOONN6a6FgAAAODEEs1NRkMIp5122o4dOyorK4+0\nwvjx43Nzc5uzJAAAAOBEEFPAEUI4+eST61k6evTo0aNHN1sxAAAAwAkimktUAAAAAI4k7oDj\nnnvuGTVqVKqrAAAAAFIs7oBj69atr7zySqqrAAAAAFIs7oADAAAAIAg4AAAAgBZAwAEAAABE\nL+6A46677iosLEx1FQAAAECKZaS6gE8lNzc3Nzc31VUAAAAAKRb3GRwAAAAAQcABAAAAtAAC\nDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAg\negIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAA\nACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIO\nAAAAIHoCDgAAACB6Ag4AAAAgegKOFm7NmjVTpkzp379/mzZt8vLyJkyYsGrVqlQXBQAAAMdZ\nRqoL4BgcOHDg17/+9YYNG/bu3Xv66adffPHFQ4YMqWf9X/3qV9OmTUskEm3atOnRo8eePXtW\nrlz5H//xH4899tisWbOarWwAAABoas7giMZrr712yimnLFiwYNu2bSGEX/7yl2ecccaCBQsS\nicSRNrn//vsTicSwYcOKi4u3b9++d+/eCRMmJBKJe++9t56tAAAAIDrO4IhDUVHR+PHjp0yZ\nsmTJkpycnOTg6tWrv/KVr3Tt2nXhwoWH3Wrfvn3J/+7atatfv37Z2dlPPfVUWlpau3btmq90\nAAAAaHrO4IjDfffdl5+f/+ijj9akGyGEcePGPfDAA7fffvvBgwcPu9WXv/zlEMK2bdv69+8/\nZMiQq666auXKlenp6c1UNAAAADQXAUccVq9ePX369JNOqjtfl156aVlZ2fr16w+71e23337N\nNde0adMmhLBx48ZHH3102rRp/fr1W716dZNXDAAAAM1IwBGHvXv39ujR45PjOTk5HTt2LC4u\nPuxWGRkZDzzwwM6dO5999tnrr79+xIgRIYSdO3dOnjz5SJsAAABAjAQccejRo0dhYeEnx//+\n97+XlJQcNvsIIVRWVv7lL3/JyMiYPHnyD3/4w9dee+3BBx8MIZSWlm7YsKFpKwYAAIBmJOCI\nw/jx45ctW1ZeXl5n/Gc/+1mnTp2Sp2bU8eGHH3bo0OHUU0/93ve+V1VVFUJIJBIlJSXJpUfK\nRAAAACBGAo44XHvttQcPHpw6derOnTuTI9XV1T//+c8XLlx4xx13ZGZmfnKTvLy8OXPmhBDu\nu+++Tp069e/fv3PnzjfddFMIYerUqUOGDGnO+gEAAKBJ+ZnYOOTm5q5evfqSSy7Jz88fPHhw\np06dNm7cWFJSctddd1155ZVH2mrx4sVnnXXW0qVLN2/e/MEHH3Tp0mXkyJHTp0+/+uqrm7N4\nAAAAaGppiUQi1TWc6F599dVzzz23vLw8KysrtZVUV1evWbPmzTff3Ldv36mnnjpu3DhXmgAA\nANBsKioqsrOzX3nllZEjR6a6lrqcwRGTk046acyYMWPGjEl1IQAAAHBicQ8OAAAAIHoCDgAA\nACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIO\nAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6\nAg4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAA\nIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6Ag4A\nAAAgegIOAAAAIHoCDgAAACB6Ag4AAAAgegIOAAAAIHoCDgAAACB6GakuIAJZWVkhhOzs7FQX\nAgAAAKmX/GvyiSYtkUikuoYIvPXWW5WVlamugsP74Q9/uHXr1vnz56e6EJrbsmXL9u3b961v\nfSvVhdDcHnvssbKysrlz56a6EJrbo48+GkK48sorU10Ize2RRx5p06bN7NmzU10IzW3x4sUd\nO3acOXNmqguhud1///0DBw684YYbUl0Ih5eRkXHmmWemuorDcAZHg5yYk0dS7969y8rKZsyY\nkepCaG6vvfbajh07TH0rtHbt2tLSUlPfCq1evTqEYOpboeeff759+/amvhVasWJFz549TX0r\ntHz58t69ew8fPjzVhRAZ9+AAAAAAoifgAAAAAKIn4AAAAACiJ+AAAAAAoifgAAAAAKIn4AAA\nAACiJ+AAAAAAoifgAAAAAKIn4AAAAACil5HqAuDTysrKysrKSnUVpICpb7VMfatl3lstXd9q\nmfpWy9TTOGmJRCLVNcCnsn///rKysm7duqW6EJrbvn37Kisru3TpkupCaG4lJSXV1dWdO3dO\ndSE0t48++iiE0KlTp1QXQnPbu3fvSSedlJubm+pCaG7FxcUZGRkdO3ZMdSE0t927d7dp06ZD\nhw6pLoTICDgAAACA6LkHBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAA\nED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcA\nAAAQPQEHAAAAED0BB5E5dOjQd77znfT09IKCgqOuvHTp0rTD+cEPftAMpXJ8HdPUhxBKSkqu\nvfbafv36ZWVl5eXlzZkzp6ioqKmL5Lg71nnU9VFrRNvq9JZBp7dmPt9bLd/qaQoZqS4AjsHm\nzZtnzJixZcuWBq5fUlISQpg+fXrfvn1rj5977rnHvzia0rFOfUVFxbhx4958882pU6cOGzZs\n27Zty5Yt+/3vf//GG2906tSpSUvlOGrEPOr6eDViunV6y6DTWzOf762Wb/U0lQREYt++fTk5\nOQUFBVu2bMnOzh4+fPhRN7n55ptDCK+//nozlEfTacTU33fffSGEu+++u2bk6aefDiFcd911\nTVkpx1kj5lHXx6sR063TWwad3mr5fG+1fKun6Qg4iEZxcfF1111XUVGRSCQa+EfhvHnzQghb\ntmxp+upoQo2Y+qFDh3bo0KGsrKz24MCBA7t3715dXd1UhXK8NWIedX28GjHdOr1l0Omtls/3\nVsu3epqOe3AQjc6dO99zzz2ZmZkN3yR5Mltubm5VVdXf/va3PXv2NFl1NKFjnfqysrK33357\nxIgR2dnZtcdHjRq1a9eud999twlq5Phr3Dx2TlZ9AAARI0lEQVTq+kg1Yrp1esug01szn++t\nlm/1NB0BBy3Zvn37Qgg/+tGPunXr1qdPn27dup1yyim/+MUvUl0XTauwsLCqqqpPnz51xvPz\n80MIf/3rX1NRFMescfOo6yPViOnW6S2DTqfhdH1rputpIDcZpSVLZr1PPfXUDTfc0KtXr82b\nNz/00EP//M//vH///n/5l39JdXU0lf3794cQ2rVrV2e8ffv2NUs58TVuHnV9pBox3Tq9ZdDp\nNJyub810PQ0k4OCEU1JSsnDhwpqnAwcOXLBgQeN29b3vfe+b3/zmF7/4xZrPwhkzZgwbNuzG\nG2+cPXt2VlbWcSiX4+c4Tn0IIS0trc5IIpE47DgpV8/UH+s86vqoNaJtdXrLoNNpOF3fOul6\nGkjAwQmntLT0xz/+cc3Tc889t9F/yx07dmydkdNPP/3iiy9+9tln33rrrc997nONr5ImcLym\n/uSTTw6H+5ecv//97yGEDh06fIoaaRKHnfrGzaOuj1Qjpluntww6nYbT9a2ZrqeBBByccHr3\n7p1M4ptI9+7dQwilpaVN9xI0zvGa+r59+2ZkZGzfvr3O+LZt20IIgwYN+vQvwfF12Kk/jvOo\n6098jZhund4y6HQaTtdTh67nk9xklBartLT0kUceeeqpp+qMb9y4Mfzv/ahokbKysoYPH75+\n/foDBw7UDFZXV69Zs6ZPnz59+/ZNYW00XCPmUdfHqxHTrdNbBp1Ow+n6VkvX03ACDlqOsrKy\nDRs2JFP8EELbtm1vv/32q6666s9//nPNOitWrFi3bt1ZZ501YMCAFJXJ8Vdn6kMIV1xxxYED\nBxYtWlQz8pOf/OTDDz+cM2dOKgqkkY46j7q+JTnW6W7IJkRBp3Mkur7V0vU0WlqTXgsAx9Ga\nNWuef/755ON77rmnW7dus2bNSj69/vrru3Tp8s477/zDP/zDuHHjXnzxxeT47373u8mTJ7dt\n23batGl5eXnvvPPOb3/72w4dOrz00kvDhg1Lzdvg2DVi6quqqsaMGbN27dpJkyYNGzZs8+bN\nTz/99JAhQ/74xz+2bds2NW+DY3fUedT1LUkjpluntww6vdXy+d5q+VZPE0pAJO68884j/W+8\nZcuWRCLx9ttvhxDGjRtXe6tXX311/Pjxubm5GRkZeXl5M2fOTK5MRBo39fv371+wYEF+fn5m\nZmavXr2+8Y1vFBcXp+gd0Hj1z6Oub2EaMd06vWXQ6a2Tz/dWy7d6mo4zOAAAAIDouQcHAAAA\nED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcA\nAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0B\nBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQ\nPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAA\nABA9AQcAxGrOnDlpaWlbt25NdSFHN23atLS0tB07dhyvXf3tb3/79LtKldpHowW8HQA4QQg4\nAOCEs2DBgrR6jRo1KtU1HsVdd91VO3kZOnToRRddlJ2d3Tyvnkgkfv3rX0+ZMqV3797Z2dm5\nublDhw694YYbCgsLm6eAOlJ7NACglchIdQEAQF1f+MIXKisra54+8cQTxcXF3/zmN9PT05Mj\nAwYMSFFpDVJUVPSd73xn6NChAwcOTI4sXLhw4cKFzfPqe/funTp16ssvv9y+ffsxY8bk5+cf\nPHjw9ddfX7Ro0YMPPviTn/xk5syZzVNJUmqPBgC0HgIOADjhTJw4ceLEiTVPX3zxxeLi4kWL\nFrVp0yaFVTXc66+/nqqXrq6u/upXv/ryyy9Pnz59yZIlnTt3rln0wgsvXHbZZV//+te7des2\nfvz4ZisphUcDAFoVl6gAQNxOOumku+++e8CAAdnZ2X379r3tttsSiUTN0p07d37jG9/Iz8/P\nysrq1q3b5MmT6/x9e/v27bNnz+7Vq1dWVlbXrl0nTpy4fv36mqXJO0Ts2rXrggsuyMnJ+d3v\nfnfU3U6YMGHSpEkhhPHjx6elpa1bty584h4cO3bsmDNnTq9evdq1a3fmmWc+8MADtc9YWb9+\n/ZQpU7p27ZqVldWvX7+vfe1r7733XgOPxm9+85vf//73o0ePfvLJJ2unGyGECy+88De/+U0I\nYd68edXV1TXVpqWllZSU1KxWWVmZlpZ2/vnnN7Ceyy67LC0trbS09N/+7d/69euXnZ3dp0+f\n+++/PzkLDTkatdU/X+Xl5YsWLTrzzDM7duzYoUOHM844Y9GiRTXvBQBaOWdwAEDcfvCDH2zY\nsOGqq65KT09fvHjxTTfdNHDgwOnTp4cQdu/effbZZ5eUlFx99dVDhgwpLCx8+OGHzzvvvFWr\nVo0ePTqEUFhYOGLEiAMHDsydO3fw4MEffPDBww8//IUvfOHFF19M3uYjKysrhDB//vzMzMyb\nbropeWlM/bv97ne/27lz58cff/ymm24666yzTj/99DoF7969u6CgoLS0dObMmfn5+S+//PK1\n11779ttv//SnPw0hvPHGG6NHj+7cufO8efN69uz517/+9aGHHnrhhRc2bdrUpUuXox6NZcuW\nhRBuueWWtLS0Ty4dPXr02LFjV69e/eqrrzbwPiZHrSd5iP7pn/6pf//+v/zlL6urq2+99dZv\nf/vbubm5s2fPPurRqHNk6p+vuXPnPvbYY5dddtncuXPT0tJWrVp1ww03bN++fcmSJQ15LwDQ\nwiUAgBPb4MGDQwgHDx6sM37FFVeEEEaNGlVRUZEceeONN0IIEydOTD6dO3duRkbG66+/XrPJ\n+++/36FDh4KCguTTWbNmhRCeeeaZmhU2bdqUnp7++c9/Pvn08ssvDyFceOGFVVVVNescdbd3\n3nlnCOH555+vWeHSSy8NIRQVFSU3DyGsWrWqZumXvvSlEMI777yTSCQefvjhYcOGvfTSSzVL\nFy9eHEJYvHhx7V0VFhYe9lh17dq1TZs2hw4dOvyhTCQWLVoUQrj77rtrv/RHH31Us8KhQ4dC\nCOPGjUs+PWo9yVmYPn16zQrbtm0LIUyYMKEhR6P22znqgW3btu0555xT++3Mnz9/6tSplZWV\nR3q/ANB6OIMDAOJ23XXXZWZmJh+fddZZ6enpH374YQghkUgsX778jDPO6N27d83VEJmZmSNH\njly1alVpaWm7du1++9vf9ujRY/LkyTV7O+20084555x169YVFxd36dIleR7ErFmzTjrp/1/W\netTdtm/fvp5qE4nEr371qz59+lxwwQU1gw8++OB1113Xo0ePEMLcuXOTCUgI4dChQ1VVVcmz\nHhpylUpVVVVxcXF+fn5GxhG/4fTr1y+E0PAfrG1gPcmoKGnAgAFt27Y91l9+bciBzczM3L59\n+65du7p3755c4b777jumVwGAFkzAAQBxGzRoUM3jtLS09u3bHzx4MISwa9euPXv27Nmz5zOf\n+cwnt3r//fc7deq0b9++4cOH17ma45RTTlm3bt3//M//nHPOOTUjNUuPutv6r8IoKioqLi4e\nNmxY7RcdMGBA7d+Fefzxx3/605/+93//d51bY9Sz26Saf8Cpf52j7qeOhtTTt2/f2k8zMzOT\nZ4I0XEMO7Pe///158+YNGjRo0qRJY8aMufDCC3v16nVMrwIALZiAAwDilp2dfdjx/fv3hxCG\nDh2avESijry8vD179oQQ2rVrV2dRTk5OCOHjjz+uGenYsWPDd1t/tcnw5Ug1hxBuvPHGO++8\ns6Cg4P777+/fv392dvbGjRvnzJlT/26TMjIyunbtWlRUVFFRkbw1xie9//77IYTDhgifpp6a\nk2garSEH9pprrhkyZMjixYufeeaZxx9/PC0tbfz48Q8//HB+fv6nfHUAaAEEHADQMnXo0CH5\n4Itf/OJhVygrKwv/N8hISo7UbH6su61fz549Qwi1T4WoU9KPfvSjPn36vPTSSzWXuuzbt6/h\n+z/77LNXrlz50ksvXXTRRYddYfXq1SGEkSNHHmkPFRUVx7GehmvggR07duzYsWPLy8vXrl37\nxBNPLFu27Pzzz9+4ceORAh0AaD38TCwAtEw9evTo2rXrn//85zppwu7du5MPevbs2blz582b\nN9e5amPTpk1paWm1L0s5pt3Wr127dt26ddu8eXPtKzj+8pe/LFmyZOPGjTt27Dh48GBBQUHt\nG3msWbOmIXtOmjFjRgjhtttuO+yPp7755psvvPDCoEGDagKO5JkXtYt59913ax5/+noa7pgO\nbHZ29vnnn7906dKrr75669atGzZsaIqSACAuAg4AaLG++tWvlpWVJX83JGn37t1nnHHGl7/8\n5eTTr3zlK0VFRStWrKhZYcOGDevXrx87dmxubm6jd5uenh7+92qUT5o0aVJxcfHPf/7zmpFb\nbrnlW9/6Vnl5eY8ePdLS0mrfv3PDhg3JX35Nnm/SkLd89tlnv/LKK7NmzUpe9FHjT3/606RJ\nk6qrqx988MGaO4Akr1XZvHlzzWrJl0v69PWEox2NOsXXc2D/+Mc/9urVq3Z5IYTkzV8//QUy\nANACuEQFAFqsW265ZeXKlXfccUdRUdHo0aM//PDDf//3fy8uLr7mmmuSK9x6663PPffc1772\ntWuuueaUU0557733Hnroofbt29f/2xxH3W3yjqF33XXXu+++e955533uc5+rvfnNN9/83HPP\nzZ0796233srPz1+zZs1zzz03c+bMYcOGhRC+9KUvPffcc1dfffU//uM/btq0acmSJU8++eTE\niRNXrlz51FNPTZw4sf63nJ6e/uyzz1500UVPPPHEf/7nf06YMKFfv35lZWVvvPHG6tWrs7Ky\nfvazn9W+BmTmzJmPPPLIt7/97UWLFrVt23bFihV/+MMfaq4WycnJ+ZT1HPVoNPzAFhQUdO7c\n+corr1y3bt3QoUPT0tL+67/+a+nSpaNGjRo6dOhRywCAli8lP04LADTc4MGDQwgHDx6sM37F\nFVeEELZs2VJ7sGPHjoMHD655WlRUNHfu3D59+mRkZOTm5k6cOPG1116rvf77778/e/bsz3zm\nMxkZGd27d582bdqmTZvqf4mj7raiomLq1Kk5OTmdOnVavnx5IpG49NJLQwhFRUXJFd57770Z\nM2Z07949MzNzwIAB9957b2VlZXLRrl27Lrvssm7dunXs2HHs2LFr165NJBK33npr+/bte/bs\nWVRUlNxVYWFhPUesvLz83nvvHTFixMknn5z8wnPqqafOmzdv69atn1x56dKlp59+ek5OTo8e\nPa666qqSkpK8vLxRo0Y1sJ6jzkL9R6PO26n/wBYXF1977bWf/exn27Zt27FjxzPPPPOOO+7Y\nv39/PYcCAFqPtMSx/1gaAEAsLrnkkuXLl7/wwgsXXHBBqmsBAJqQe3AAAC3Z17/+9RDCbbfd\nVlVVlepaAIAm5AwOAKCFu/jii59//vmzzz57ypQpOTk5NfcKAQBaEgEHANDCffzxxwsWLHj6\n6ac//vjjz3/+8030O68AQGoJOAAAAIDouQcHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0B\nBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQ\nPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAA\nABA9AQcAAAAQPQEHAAAAED0BBwAAABA9AQcAAAAQPQEHAAAAED0BBwAAABC9/weeXDXsoPTk\nHQAAAABJRU5ErkJggg=="
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Remove the non-significant terms from the model and refit to produce the following analysis of variance table. Here we obtain the parameter estimates, where also we can verify that R$^2$ and R$^2$ adjusted values are acceptable."
      ],
      "metadata": {
        "id": "Pgt7fKeiHYsx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate effect estimates.\n",
        "q = lm(distance~h+s+b+l+e+bl,data=df)\n",
        "summary(q)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "qltFsuewGUQv",
        "outputId": "2fc4fafd-d7dc-4cea-944c-b9af685fc30f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "Call:\n",
              "lm(formula = distance ~ h + s + b + l + e + bl, data = df)\n",
              "\n",
              "Residuals:\n",
              "    Min      1Q  Median      3Q     Max \n",
              "-23.091  -5.195  -1.528   6.993  22.050 \n",
              "\n",
              "Coefficients:\n",
              "            Estimate Std. Error t value Pr(>|t|)    \n",
              "(Intercept)   57.537      2.847  20.212 3.33e-11 ***\n",
              "h             13.484      3.183   4.237 0.000971 ***\n",
              "s            -11.078      3.183  -3.481 0.004062 ** \n",
              "b             19.412      2.847   6.819 1.23e-05 ***\n",
              "l             20.141      3.183   6.328 2.62e-05 ***\n",
              "e             12.047      3.183   3.785 0.002271 ** \n",
              "bl             7.609      3.183   2.391 0.032640 *  \n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
              "\n",
              "Residual standard error: 12.73 on 13 degrees of freedom\n",
              "Multiple R-squared:  0.9131,\tAdjusted R-squared:  0.873 \n",
              "F-statistic: 22.78 on 6 and 13 DF,  p-value: 3.452e-06\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">The ANOVA table shows us that the model is significant, and the lack-of-fit test is not significant"
      ],
      "metadata": {
        "id": "IhFKELKzyIy9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate anova table.\n",
        "anova(q)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 318
        },
        "id": "AQbDFQecyLVt",
        "outputId": "44f5e7d9-3a75-482b-843d-af3695acec96"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A anova: 7 × 5</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>h</th><td> 1</td><td>2909.2539</td><td>2909.2539</td><td>17.949947</td><td>9.708404e-04</td></tr>\n",
              "\t<tr><th scope=row>s</th><td> 1</td><td>1963.5977</td><td>1963.5977</td><td>12.115297</td><td>4.061618e-03</td></tr>\n",
              "\t<tr><th scope=row>b</th><td> 1</td><td>7536.9031</td><td>7536.9031</td><td>46.502306</td><td>1.226099e-05</td></tr>\n",
              "\t<tr><th scope=row>l</th><td> 1</td><td>6490.3164</td><td>6490.3164</td><td>40.044919</td><td>2.624976e-05</td></tr>\n",
              "\t<tr><th scope=row>e</th><td> 1</td><td>2322.0352</td><td>2322.0352</td><td>14.326838</td><td>2.270802e-03</td></tr>\n",
              "\t<tr><th scope=row>bl</th><td> 1</td><td> 926.4414</td><td> 926.4414</td><td> 5.716096</td><td>3.263993e-02</td></tr>\n",
              "\t<tr><th scope=row>Residuals</th><td>13</td><td>2106.9867</td><td> 162.0759</td><td>       NA</td><td>          NA</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA anova: 7 × 5\n\n| <!--/--> | Df &lt;int&gt; | Sum Sq &lt;dbl&gt; | Mean Sq &lt;dbl&gt; | F value &lt;dbl&gt; | Pr(&gt;F) &lt;dbl&gt; |\n|---|---|---|---|---|---|\n| h |  1 | 2909.2539 | 2909.2539 | 17.949947 | 9.708404e-04 |\n| s |  1 | 1963.5977 | 1963.5977 | 12.115297 | 4.061618e-03 |\n| b |  1 | 7536.9031 | 7536.9031 | 46.502306 | 1.226099e-05 |\n| l |  1 | 6490.3164 | 6490.3164 | 40.044919 | 2.624976e-05 |\n| e |  1 | 2322.0352 | 2322.0352 | 14.326838 | 2.270802e-03 |\n| bl |  1 |  926.4414 |  926.4414 |  5.716096 | 3.263993e-02 |\n| Residuals | 13 | 2106.9867 |  162.0759 |        NA |           NA |\n\n",
            "text/latex": "A anova: 7 × 5\n\\begin{tabular}{r|lllll}\n  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n  & <int> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n\\hline\n\th &  1 & 2909.2539 & 2909.2539 & 17.949947 & 9.708404e-04\\\\\n\ts &  1 & 1963.5977 & 1963.5977 & 12.115297 & 4.061618e-03\\\\\n\tb &  1 & 7536.9031 & 7536.9031 & 46.502306 & 1.226099e-05\\\\\n\tl &  1 & 6490.3164 & 6490.3164 & 40.044919 & 2.624976e-05\\\\\n\te &  1 & 2322.0352 & 2322.0352 & 14.326838 & 2.270802e-03\\\\\n\tbl &  1 &  926.4414 &  926.4414 &  5.716096 & 3.263993e-02\\\\\n\tResiduals & 13 & 2106.9867 &  162.0759 &        NA &           NA\\\\\n\\end{tabular}\n",
            "text/plain": [
              "          Df Sum Sq    Mean Sq   F value   Pr(>F)      \n",
              "h          1 2909.2539 2909.2539 17.949947 9.708404e-04\n",
              "s          1 1963.5977 1963.5977 12.115297 4.061618e-03\n",
              "b          1 7536.9031 7536.9031 46.502306 1.226099e-05\n",
              "l          1 6490.3164 6490.3164 40.044919 2.624976e-05\n",
              "e          1 2322.0352 2322.0352 14.326838 2.270802e-03\n",
              "bl         1  926.4414  926.4414  5.716096 3.263993e-02\n",
              "Residuals 13 2106.9867  162.0759        NA           NA"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Test the model assumptions using residual graphs (adjust and simplify as needed)**\n",
        "\n",
        ">To examine the assumption that the residuals are approximately normally distributed, are independent, and have equal variances, we generate four plots of the residuals: a normal probability plot, box plot, histogram, and a run-order plot of the residuals. In the run-order plot, the highlighted points are the centerpoint values. Recall that run numbers 2 and 13 had two rubber bands while run numbers 7 and 19 had only one rubber band.\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "-KvG5ecuyN3m"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate four plots.\n",
        "center = which(height[]==4)\n",
        "par(mfrow=c(2,2),bg=rgb(1,1,1))\n",
        "qqnorm(q$residuals)\n",
        "qqline(q$residuals, col = 2)\n",
        "abline(h=0)\n",
        "boxplot(q$residuals, horizontal=TRUE, main=\"Box Plot\", xlab=\"Residual\")\n",
        "hist(q$residuals, main=\"Histogram\", xlab=\"Residual\")\n",
        "plot(order, q$residuals, xlab=\"Actual Run Order\", ylab=\"Residual\",\n",
        "     main=\"Run Order Plot\")\n",
        "points(df$order[center],q$residuals[center],pch=19)\n",
        "par(mfrow=c(1,1))\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "YpPMPPGgypNy",
        "outputId": "7f9e1e80-2366-41f5-f8e6-2848b8c978cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Run Order Plot”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\ngg=="
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">The residuals do appear to have, at least approximately, a normal distributed .Next we plot the residuals versus the predicted values."
      ],
      "metadata": {
        "id": "WE2OFSVhymd9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Plot residuals versus predicted response.\n",
        "par(mfrow=c(1,1),bg=rgb(1,1,1))\n",
        "plot(predict(q),q$residuals,ylab=\"Residual\",\n",
        "     xlab=\"Predicted Distance\", col=4)\n",
        "abline(h=0, col=2)\n",
        "par(mfrow=c(1,1))\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "-05wES3ZLKTi",
        "outputId": "999fa46c-dbe0-4dd4-86a0-d488b60df947"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\nD4wXaVS8oMpKAAAAAElFTkSuQmCC"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">There does not appear to be a pattern to the residuals. One observation about the graph, from a single point, is that the model performs poorly in predicting a short distance. In fact, run number 10 had a measured distance of 8 meters, but the model predicts -11 meters, giving a residual of 19 meters. The fact that the model predicts an impossible negative distance is an obvious shortcoming of the model. We may not be successful at predicting the catapult settings required to hit a distance less than 25 meters. This is not surprising since there is only one data value less than 28 meters. Recall that the objective is to achieve distances of 30, 60, and 90 meters.\n",
        "\n",
        ">Next we look at the residual values versus each of the factors."
      ],
      "metadata": {
        "id": "RmHAcRAQLUzh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Plots of residuals versus the factor variables\n",
        "par(mfrow=c(2,3),bg=rgb(1,1,1))\n",
        "plot(q$residuals~h, data=df, main=\"Residuals by Band Height\",\n",
        "        xlab=\"Height\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(q$residuals~s, data=df, main=\"Residuals by Start Angle\",\n",
        "        xlab=\"Start Angle\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(q$residuals~b, data=df, main=\"Residuals by Number of Bands\",\n",
        "        xlab=\"Number of Bands\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(q$residuals~l, data=df, main=\"Residuals by Arm Length\",\n",
        "        xlab=\"Arm Length\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(q$residuals~e, data=df, main=\"Residuals by Stop Angle\",\n",
        "        xlab=\"Stop Angle\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "par(mfrow=c(1,1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "WIh1F6EuLWYu",
        "outputId": "27ad4ad7-3eb6-47fb-cdf6-0ecc63824e93"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Residuals by Stop Angle”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\nAJAeBQcAAAAAAJDev8cVkkxJJzqAAAAAAElFTkSuQmCC"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## Perform lack-of-fit test.\n",
        "lof = factor(paste(height,start,bands,length,stop,bands))\n",
        "inner.model = lm(distance ~ h+s+b+l+e+bl, data = df)\n",
        "outer.model = lm(distance ~ lof)\n",
        "anova(inner.model, outer.model)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 161
        },
        "id": "0vau7NLpycct",
        "outputId": "1f9e4783-7c36-4194-fb6b-68515380636a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A anova: 2 × 6</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>Res.Df</th><th scope=col>RSS</th><th scope=col>Df</th><th scope=col>Sum of Sq</th><th scope=col>F</th><th scope=col>Pr(&gt;F)</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>1</th><td>13</td><td>2106.987</td><td>NA</td><td>      NA</td><td>      NA</td><td>       NA</td></tr>\n",
              "\t<tr><th scope=row>2</th><td> 2</td><td> 133.250</td><td>11</td><td>1973.737</td><td>2.693142</td><td>0.3018467</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA anova: 2 × 6\n\n| <!--/--> | Res.Df &lt;dbl&gt; | RSS &lt;dbl&gt; | Df &lt;dbl&gt; | Sum of Sq &lt;dbl&gt; | F &lt;dbl&gt; | Pr(&gt;F) &lt;dbl&gt; |\n|---|---|---|---|---|---|---|\n| 1 | 13 | 2106.987 | NA |       NA |       NA |        NA |\n| 2 |  2 |  133.250 | 11 | 1973.737 | 2.693142 | 0.3018467 |\n\n",
            "text/latex": "A anova: 2 × 6\n\\begin{tabular}{r|llllll}\n  & Res.Df & RSS & Df & Sum of Sq & F & Pr(>F)\\\\\n  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n\\hline\n\t1 & 13 & 2106.987 & NA &       NA &       NA &        NA\\\\\n\t2 &  2 &  133.250 & 11 & 1973.737 & 2.693142 & 0.3018467\\\\\n\\end{tabular}\n",
            "text/plain": [
              "  Res.Df RSS      Df Sum of Sq F        Pr(>F)   \n",
              "1 13     2106.987 NA       NA        NA        NA\n",
              "2  2      133.250 11 1973.737  2.693142 0.3018467"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The above model can be expressed in analytical terms as:\n",
        ">$Y = \\beta_{0} + \\beta_{1}h + \\beta_{2}s + \\beta_{3}b + \\beta_{4}l +  \\beta_{5}e + \\beta_{6}bl$\n",
        "\n",
        "\n",
        ">At this point, since there are several unsatisfactory features of the model we have fit and the resultant residuals, we should consider whether a simple transformation of the response variable ($Y$ = \"Distance\") might improve the situation.\n",
        "There are at least two good reasons to suspect that using the logarithm of distance as the response might lead to a better model.\n",
        " \n",
        "*   A linear model fit to $ln(Y)$ will always predict a positive distance when converted back to the original scale for any possible combination of X factor values.\n",
        "*   Physical considerations suggest that a realistic model for distance might require quadratic terms since gravity plays a key role - taking logarithms often reduces the impact of non-linear terms.\n",
        "\n",
        "\n",
        "So,using $ln(Y)$ as the response leads to a more satisfactory model.With this change of variable ($logdist = log(distance)$) we implementing again our analytical model.\n",
        "\n",
        ">$ln(Y) = \\beta_{0} + \\beta_{1}h + \\beta_{2}s + \\beta_{3}b + \\beta_{5}l + \\beta_{5}e + \\beta_{6}hs + \\beta_{7}hb + \\beta_{8}hl + \\beta_{9}he + \\beta_{10}sb + \\beta_{11}sl + \\beta_{12}se + \\beta_{13}bl + \\beta_{14}be + \\beta_{15}le$\n",
        "\n",
        "\n",
        ">Proceeding as before, using the coded values of the factor levels and the natural logarithm of distance as the response, we obtain the following parameter estimates."
      ],
      "metadata": {
        "id": "d01_FF95y8EG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Add log(distance) to the data frame.\n",
        "logdist = log(distance)\n",
        "df = data.frame(df,logdist)\n",
        "\n",
        "## Fit a model with up to second order interactions.\n",
        "z = lm(logdist~h+s+b+l+e+hs+hb+hl+he+sb+sl+se+bl+be+le,data=df)\n",
        "summary(z)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "id": "GE-VWVgby_kF",
        "outputId": "60e67831-81a4-41fd-d55a-4f7a43bb596e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "Call:\n",
              "lm(formula = logdist ~ h + s + b + l + e + hs + hb + hl + he + \n",
              "    sb + sl + se + bl + be + le, data = df)\n",
              "\n",
              "Residuals:\n",
              "       1        2        3        4        5        6        7        8 \n",
              "-0.05182 -0.05182 -0.05182 -0.05182 -0.07753 -0.07753 -0.07753 -0.07753 \n",
              "       9       10       11       12       13       14       15       16 \n",
              "-0.05182 -0.05182 -0.05182 -0.05182 -0.07753 -0.07753 -0.07753 -0.07753 \n",
              "      17       18       19       20 \n",
              " 0.38930  0.29844  0.23093  0.11612 \n",
              "\n",
              "Coefficients:\n",
              "            Estimate Std. Error t value Pr(>|t|)    \n",
              "(Intercept)  3.85702    0.06865  56.186 6.01e-07 ***\n",
              "h            0.25735    0.07675   3.353  0.02849 *  \n",
              "s           -0.24174    0.07675  -3.150  0.03452 *  \n",
              "b            0.34880    0.06865   5.081  0.00708 ** \n",
              "l            0.39437    0.07675   5.138  0.00680 ** \n",
              "e            0.26273    0.07675   3.423  0.02670 *  \n",
              "hs          -0.02582    0.07675  -0.336  0.75348    \n",
              "hb          -0.02035    0.07675  -0.265  0.80403    \n",
              "hl          -0.01396    0.07675  -0.182  0.86457    \n",
              "he          -0.04873    0.07675  -0.635  0.55999    \n",
              "sb           0.00853    0.07675   0.111  0.91686    \n",
              "sl           0.06775    0.07675   0.883  0.42724    \n",
              "se           0.07955    0.07675   1.036  0.35855    \n",
              "bl           0.01499    0.07675   0.195  0.85472    \n",
              "be          -0.01152    0.07675  -0.150  0.88794    \n",
              "le          -0.01120    0.07675  -0.146  0.89108    \n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
              "\n",
              "Residual standard error: 0.307 on 4 degrees of freedom\n",
              "Multiple R-squared:  0.9564,\tAdjusted R-squared:  0.7927 \n",
              "F-statistic: 5.845 on 15 and 4 DF,  p-value: 0.0502\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Examining the p-values of the 16 model coefficients, only the intercept and the 5 main effect terms appear significant. Refitting the model with just these terms \n",
        "\n",
        ">$ln(Y) = \\beta_{0} + \\beta_{1}h + \\beta_{2}s + \\beta_{3}b + \\beta_{5}l + \\beta_{5}e$\n",
        "\n",
        "yields the following results.\n",
        "\n"
      ],
      "metadata": {
        "id": "oS0oT37_zNCO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Fit model with significant effects.\n",
        "z = lm(logdist~h+s+b+l+e,data=df)\n",
        "summary(z)\n",
        "\n",
        "## Generate anova table \n",
        "anova(z)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 668
        },
        "id": "d0G3cHEozO0L",
        "outputId": "090ea981-99d7-4c6d-d4b4-13296bde021e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "Call:\n",
              "lm(formula = logdist ~ h + s + b + l + e, data = df)\n",
              "\n",
              "Residuals:\n",
              "     Min       1Q   Median       3Q      Max \n",
              "-0.27259 -0.13143 -0.03024  0.12220  0.38930 \n",
              "\n",
              "Coefficients:\n",
              "            Estimate Std. Error t value Pr(>|t|)    \n",
              "(Intercept)  3.85702    0.04702  82.035  < 2e-16 ***\n",
              "h            0.25735    0.05257   4.896 0.000236 ***\n",
              "s           -0.24174    0.05257  -4.599 0.000413 ***\n",
              "b            0.34880    0.04702   7.419 3.26e-06 ***\n",
              "l            0.39437    0.05257   7.502 2.87e-06 ***\n",
              "e            0.26273    0.05257   4.998 0.000195 ***\n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
              "\n",
              "Residual standard error: 0.2103 on 14 degrees of freedom\n",
              "Multiple R-squared:  0.9284,\tAdjusted R-squared:  0.9028 \n",
              "F-statistic: 36.28 on 5 and 14 DF,  p-value: 1.565e-07\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<table class=\"dataframe\">\n",
              "<caption>A anova: 6 × 5</caption>\n",
              "<thead>\n",
              "\t<tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr>\n",
              "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
              "</thead>\n",
              "<tbody>\n",
              "\t<tr><th scope=row>h</th><td> 1</td><td>1.0596790</td><td>1.05967902</td><td>23.96845</td><td>2.361594e-04</td></tr>\n",
              "\t<tr><th scope=row>s</th><td> 1</td><td>0.9350491</td><td>0.93504909</td><td>21.14950</td><td>4.133609e-04</td></tr>\n",
              "\t<tr><th scope=row>b</th><td> 1</td><td>2.4332416</td><td>2.43324156</td><td>55.03651</td><td>3.258409e-06</td></tr>\n",
              "\t<tr><th scope=row>l</th><td> 1</td><td>2.4883855</td><td>2.48838552</td><td>56.28379</td><td>2.869040e-06</td></tr>\n",
              "\t<tr><th scope=row>e</th><td> 1</td><td>1.1044250</td><td>1.10442502</td><td>24.98054</td><td>1.952186e-04</td></tr>\n",
              "\t<tr><th scope=row>Residuals</th><td>14</td><td>0.6189597</td><td>0.04421141</td><td>      NA</td><td>          NA</td></tr>\n",
              "</tbody>\n",
              "</table>\n"
            ],
            "text/markdown": "\nA anova: 6 × 5\n\n| <!--/--> | Df &lt;int&gt; | Sum Sq &lt;dbl&gt; | Mean Sq &lt;dbl&gt; | F value &lt;dbl&gt; | Pr(&gt;F) &lt;dbl&gt; |\n|---|---|---|---|---|---|\n| h |  1 | 1.0596790 | 1.05967902 | 23.96845 | 2.361594e-04 |\n| s |  1 | 0.9350491 | 0.93504909 | 21.14950 | 4.133609e-04 |\n| b |  1 | 2.4332416 | 2.43324156 | 55.03651 | 3.258409e-06 |\n| l |  1 | 2.4883855 | 2.48838552 | 56.28379 | 2.869040e-06 |\n| e |  1 | 1.1044250 | 1.10442502 | 24.98054 | 1.952186e-04 |\n| Residuals | 14 | 0.6189597 | 0.04421141 |       NA |           NA |\n\n",
            "text/latex": "A anova: 6 × 5\n\\begin{tabular}{r|lllll}\n  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n  & <int> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n\\hline\n\th &  1 & 1.0596790 & 1.05967902 & 23.96845 & 2.361594e-04\\\\\n\ts &  1 & 0.9350491 & 0.93504909 & 21.14950 & 4.133609e-04\\\\\n\tb &  1 & 2.4332416 & 2.43324156 & 55.03651 & 3.258409e-06\\\\\n\tl &  1 & 2.4883855 & 2.48838552 & 56.28379 & 2.869040e-06\\\\\n\te &  1 & 1.1044250 & 1.10442502 & 24.98054 & 1.952186e-04\\\\\n\tResiduals & 14 & 0.6189597 & 0.04421141 &       NA &           NA\\\\\n\\end{tabular}\n",
            "text/plain": [
              "          Df Sum Sq    Mean Sq    F value  Pr(>F)      \n",
              "h          1 1.0596790 1.05967902 23.96845 2.361594e-04\n",
              "s          1 0.9350491 0.93504909 21.14950 4.133609e-04\n",
              "b          1 2.4332416 2.43324156 55.03651 3.258409e-06\n",
              "l          1 2.4883855 2.48838552 56.28379 2.869040e-06\n",
              "e          1 1.1044250 1.10442502 24.98054 1.952186e-04\n",
              "Residuals 14 0.6189597 0.04421141       NA           NA"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">This is a simpler model than our first model. All the terms are highly significant and there is no indication of a significant lack of fit. We next look at the residuals for this new model fit.\n",
        "\n",
        ">The following normal plot, box plot, histogram and run-order plot of the residuals shows no problems."
      ],
      "metadata": {
        "id": "vTBQsdbip_ww"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Generate four plots.\n",
        "center = which(height[]==4)\n",
        "par(mfrow=c(2,2),bg=rgb(1,1,1))\n",
        "qqnorm(z$residuals)\n",
        "qqline(z$residuals, col = 2)\n",
        "abline(h=0)\n",
        "boxplot(z$residuals, horizontal=TRUE, main=\"Box Plot\", xlab=\"Residual\")\n",
        "hist(z$residuals, main=\"Histogram\", xlab=\"Residual\")\n",
        "plot(order, z$residuals, xlab=\"Actual Run Order\", ylab=\"Residual\",\n",
        "     main=\"Run Order Plot\")\n",
        "points(df$order[center],z$residuals[center],pch=19)\n",
        "par(mfrow=c(1,1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "XCnJScoRzesz",
        "outputId": "bc1234a7-4940-4975-be05-04b5faa735e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Run Order Plot”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\nYII="
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">Residuals plotted versus run order again show a possible slight decreasing trend\n",
        "\n",
        ">A plot of the residuals versus the predicted ln(Y) values looks reasonable, although there might be a tendency for the model to overestimate slightly for high predicted values."
      ],
      "metadata": {
        "id": "W5gVw0FWlbZ5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Plot residuals versus predicted response.\n",
        "par(mfrow=c(1,1),bg=rgb(1,1,1))\n",
        "plot(predict(z),z$residuals,ylab=\"Residual\",\n",
        "     xlab=\"Predicted log(Distance)\", col=4)\n",
        "abline(h=0,col=2)\n",
        "par(mfrow=c(1,1))\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "t-SIfgW6lpWZ",
        "outputId": "a9d1d5e0-532a-492e-86c0-36350d5ecf19"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Next we look at the residual values versus each of the factors."
      ],
      "metadata": {
        "id": "b1wWTfFyzv5j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Plot of residuals versus the factor variables\n",
        "par(mfrow=c(2,3),bg=rgb(1,1,1))\n",
        "plot(z$residuals~h, data=df, main=\"Residuals by Band Height\",\n",
        "        xlab=\"Height\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(z$residuals~s, data=df, main=\"Residuals by Start Angle\",\n",
        "        xlab=\"Start Angle\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(z$residuals~b, data=df, main=\"Residuals by Number of Bands\",\n",
        "        xlab=\"Number of Bands\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(z$residuals~l, data=df, main=\"Residuals by Arm Length\",\n",
        "        xlab=\"Arm Length\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "\n",
        "plot(z$residuals~e, data=df, main=\"Residuals by Stop Angle\",\n",
        "        xlab=\"Stop Angle\",ylab=\"Residual\", xlim=c(-1.5,1.5), col=4)\n",
        "par(mfrow=c(1,1))\n",
        "\n",
        "\n",
        "## Rearrange data so that factors and levels are in single columns.\n",
        "group = rep(1:5,each=length(df$logdist))\n",
        "newd = rep(logdist,5)\n",
        "level = c(m[,7],m[,8],m[,9],m[,10],m[,11])\n",
        "dflong = data.frame(group,level,newd)\n",
        "dflong = dflong[order(group,level),]\n",
        "\n",
        "## Generate means by factor and level.\n",
        "gmn = aggregate(x=dflong$newd,by=list(dflong$group,dflong$level),FUN=\"mean\")\n",
        "cgroup = rep(c(\"Height\",\"Start\",\"Bands\",\"Length\",\"Stop\"),3)\n",
        "cgroup = cgroup[-8]\n",
        "dfp = data.frame(cgroup,gmn)\n",
        "names(dfp)=c(\"cgroup\",\"group\",\"level\",\"tmean\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "iNmocU3nmcEP",
        "outputId": "910af0a5-e423-4961-8b5b-458c8fe8aa95"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Plot with title “Residuals by Stop Angle”"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94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\n4AAAAACC978vnkbVXqVFLAAAAABJRU5ErkJggg=="
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        ">These plots still appear to have a slight \"frown\" on the graph (higher residuals in the center). However, the model is generally an improvement over the previous model and will be accepted as possibly the best that can be done without conducting a new experiment designed to fit a quadratic model.\n",
        "\n",
        "**Final results**\n",
        "\n",
        "Based on the analyses and plots, we can select factor settings that maximize the log-transaformed distance. Translating from \"-1\", \"0\", and \"+1\" back to the actual factor settings, we have: band height at \"0\" or 3.5 meters; start angle at \"0\" or 10 degrees; number of rubber bands at \"1\" or 2 bands; arm length at \"1\" or 4 meters , and stop angle at \"0\" or 80 degrees."
      ],
      "metadata": {
        "id": "Hk9we1SQqqVY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Attach lattice library and generate main effects plot.\n",
        "library(lattice)\n",
        "xyplot(tmean~level|cgroup,data=dfp,layout=c(5,1),xlim=c(-2,2),\n",
        "       ylab=\"log(Distance)\",xlab=\"Factor Levels\", type=\"b\",\n",
        "panel = function(x, y, ...){\n",
        "panel.xyplot(x, y, ...)\n",
        "panel.abline(h = mean(logdist), lty = 2, col = 2)})\n",
        "par(mfrow=c(1,1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 737
        },
        "id": "SuBxv899zxkY",
        "outputId": "88f404a3-b84f-4194-c8d3-7662abf3bf58"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABaAAAAWgCAIAAAAnwnOfAAAACXBIWXMAABJ0AAASdAHeZh94\nAAAgAElEQVR4nOzdd3wUVdvG8WvTCEnoEEB6LyqiIr1IEUFBpKjYAAUVRFCwggXFhoLoY0HF\nR0QQH+m9VynSFFAEaaFLDSmQTrL7/rG8MYYAKZs9O7u/78c/kslk5lrcyezee59zbA6HQwAA\nAAAAAFbmZzoAAAAAAABAXlHgAAAAAAAAlkeBAwAAAAAAWB4FDgAAAAAAYHkUOAAAAAAAgOVR\n4AAAAAAAAJZHgQMAAAAAAFgeBQ4AAAAAAGB5FDgAAAAAAIDlUeAAAAAAAACWR4EDAAAAAABY\nHgUOAAAAAABgeRQ4AAAAAACA5VHgAAAAAAAAlkeBAwAAAAAAWB4FDgAAAAAAYHkUOAAAAAAA\ngOVR4AAAAAAAAJZHgQMAAAAAAFgeBQ4AAAAAAGB5FDgAAAAAAIDlUeAAAAAAAACWR4EDAAAA\nAABYHgUOAAAAAABgeRQ4AAAAAACA5VHgAAAAAAAAlkeBAwAAAAAAWB4FDgAAAAAAYHkUOAAA\nAAAAgOVR4AAAAAAAAJZHgQMAAAAAAFgeBQ4AAAAAAGB5FDgAAAAAAIDlUeAAAAAAAACWR4ED\nAAAAAABYHgUOAAAAAABgeRQ4AAAAAACA5VHgAAAAAAAAlkeBA4D3S0tLe+211/z8/D755BPT\nWXLm008/rVatWoECBWrXrj158mTTcXLDuv/4ALyVdf8ucVMAgKsLMB0AAPLXyZMnH3zwwTNn\nzvj7+5vOkjPjx49/4YUX3n333UaNGq1atap3795FihS55557TOfKAev+4wPwVtb9u8RNAQCu\niQIHAC83ZcqUUqVKLViwoGTJkqaz5IDD4XjvvfcGDhz44osvSmrZsuVff/317rvvWuu1rEX/\n8QF4MYv+XeKmAADZwRAVAF6uZ8+e06dPDwsLMx0kZ/bv33/kyJEuXbqkb+ncufOWLVvOnz9v\nMFVOWfQfH4AXs+jfJW4KAJAdFDgAeLny5cubjpAb+/btk1StWrX0Lc6v9+/fbyxTzln0Hx+A\nF7Po3yVuCgCQHRQ4AMATOT+UK1y4cPqWQoUKpW8HAPgUbgoAkB3MwQHAq6SmpsbFxTm/DgoK\nCgkJMZsHAGAQNwUA8Cl0cADwKitWrCj2/55++mnTcXKvaNGikmJjY9O3xMTEpG8HAGQHNwUA\n8Cl0cADwKo0bN163bp3z69KlS5sNkxe1atWStH///ooVKzq37N2719/f37kdAJAd3BQAwKdQ\n4ADgVYoWLdq8eXPTKVygWrVqNWrUmD17dtu2bZ1b5syZ06pVK/qrASD7uCkAgE+hwAHAy23b\nts05B5vdbj9w4MCaNWskNW7cODg42HCya3nttdf69u1bvnz5Jk2aLFiwYNGiRStXrjQdKmes\n+48PwFtZ9+8SNwUAuCabw+EwnQEA8lHjxo03b96caeOhQ4cqV65sIk7OjBs3bsyYMcePH69R\no8bIkSO7d+9uOlHOWPofH4BXsvTfJW4KAHB1FDgAAAAAAIDlsYoKAAAAAACwPAocAAAAAADA\n8ihwAAAAAAAAy6PAAQAAAAAALI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAA\nACyPAkfWjhw50r9/f9Mp8mTLli0jRowwnSJP5s+fP27cONMp8mT8+PFz5swxnSJP2rRp8803\n35hOkScDBw48ePCg6RS5l5KS0qtXr9jYWNNBcu/06dOPPfaYw+EwHST35syZ07BhQ9Mp8mTl\nypVjxowxnSJPpkyZMmXKFNMp8mTMmDErV640nSJPGjZsaOn7msPheOyxx06fPm06SO7Fxsb2\n6tUrJSXFdJDcO3jw4MCBA02nyJNvvvmmTZs2plPkyZw5c8aPH286RZ6MGzdu/vz5plPkyYgR\nI7Zs2WI6RZ7079//yJEjplP8CwWOrO3Zs2fixImmU+TJr7/+OmPGDNMp8mTt2rWLFy82nSJP\nlixZsmbNGtMp8mTTpk1W/78wadKk3bt3m06RezExMZMnT/77779NB8m9gwcPTpw40dIvx5ct\nW7Zt2zbTKfJkw4YNVn8huGLFihUrVphOkSfz58/fsGGD6RR5sm3btmXLlplOkXspKSkTJ060\ndNX777//njx5ckxMjOkgubd79+5JkyaZTpEnixcv3rRpk+kUebJmzZolS5aYTpEnixcvXrt2\nrekUeTJjxoxff/3VdIo8mThx4p49e0yn+BcKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyP\nAgcAAAAAALA8ChwAAAAAAMDyKHAAAAAAAADLo8ABAAAAAAAsL8B0AA9lt9vtdvuKFStMB8m9\nPXv2xMfHW/ohHDlyJDIy0tIP4cyZM5Is/RBSU1NPnTpl6YeQlpa2Y8eO4OBg00FyKSYmRtLG\njRtPnDhhOksu7d69W9KqVasCAwNNZ8mlo0ePWv2mcPDgwejoaEs/BOclYOmHEB0dffDgQUs/\nBIfDcfToUes+hIsXL0raunVrfHy86Sy5dOTIEUlr164tWrSo6Sy5tGPHjrS0NOs+iySdOnUq\nNTXV0g/h6NGjZ86csfRDiIyMPHLkiKUfQnx8/J49eyz9EJzvmk2n+DcHsvL111+b/j8DeIQC\nQVZ9RwoAcLmgQD4bAwD84+uvvzb93v1fuEtlrVKlSgWCgpIO/WI6CGBYsbqtP3h18LP9HjQd\nBDDp6eGj5ixec2L7EtNBAMNCqjX/YeyIh7t1NB0EMKlbvxf3Hzq2c+VPpoMAhgVXaVqpUiXT\nKf6FOTgAAAAAAIDlUeAAAAAAAACWR4ED3iOgYsPGnfqYTgG4Us8Bw23lGpw6cy47O/d74W1b\nuQYHDh/L71SARXGNAADg3ShwwJV+mLnIVq5B+n9+5W8rdWO7+nc89NI7n56LjjWdDnAT54Xw\n5kfjL/9RXHyCrVyD+nc8lM1D1b++5p23NylQwGVTvY76fCLv7uAGV7kK3IknPDyZ3W6fsXBl\np17PVWl8T8GqTQtWbVqtaZdHB7/x++59GXdz1dOYywEey83XArwbk4zC9ZrddlPzhvUlORyO\nc9Gxq3/5dfSXk+YuXbNt6ZTQkIKm0wFW8sozfV55po+rjnbyTOSw9z+vf33N6pUruOqYgMfi\nCQ8P9+DTr06bv7xS+bI97m5bJrxE7Pm433b+9b85S2YvXr34h09bNLpZrnsacznAk7nzWoDX\no8AB12vXotGbzz+Z/m1amv3Oh55ZuX7L7MWrH+l+l8FggI/bumO36QiA+/CEhydb/cuv0+Yv\nb9XklhU/fRkQ4J++ff7ytff0GTr49dHbl/0o1z2NuRzgsdx8LcDrMUQF+c7f369Tu+aSzkbF\npG/csmNX174vlLyhbVClxpUbdX508BuHj51I/+lDA1+1lWsQF5/w8rufVm7UuUDlJhUa3PXx\nNz86HI70fRat2nBrh0cKVm0aXu+Ofi+8HXP+QsaTJqekjP5y0k3tHixSu1Whmi3rte05+stJ\ndrs9/x8ukDOnz0YNHP5BpYadgio1LnVju3sffz7jLTzTHBwLV65veHevkGrNytRv/+wbYxKT\nkis0uOuWOx/OeEA/m98HX3xftck9BSo3qXjb3W9/8l/nhdOp13NdHhsqqeMjg23lGqzfssON\njxLIwtWf/Nm5EVzlirjKE/5K1wjgTrv3HZR0X6d2Gd/RSep8R8vJn44c/fpzdrv9Sk/jq7+I\nct44zkRG3dHz6YJVm85btpa///BkebkWjhw/+diQt8rd0jGoUuOSN7S9p8/QLTt2pR+ha98X\nbOUanDwT2e+Ft0vf1L5A5Sa1W3b/ctIMNz44GEAHB9xh9/5Dkm69sbbz29/++KtVtyeKFy3y\nbL8Hy5QqcfDo319MnLbs502710wvUayIpKDAQEk9nny5SoXrfvryPbvd8dbY8UPfHFu0cNhj\nD9wjaf2WHff0GVK6ZIk3hjxRqkSxnzdtu6fPUD/bPwW7Aa+M+m7qvIe6dhjQu4fNZlu6ZuNL\n73x65Pipz999ycDjB67g7LnoRp16x8Re6N+r+w21qh07cXrc99NbdO239MfPWzW5JdPOazdt\n6/LY0FIlir3yTJ+SxYtOn7+i54BhF+ISypUJz7jbO//5dseuvU8+3M3f3++zCVPfGP1V9coV\nHrz3ztee61u8WOHJMxa9MeSJm2+oVbdmVTc+UCCzaz75r3kjuPoVcZUn/JWuEUP/EvBRFa4r\nI2n52s1PPdI90/u69HbXLJ/G134RFRQgacibYwMDA94Y8kTViuX4+w9Plutr4diJ0w3v7p2Q\nmDSgV4/ra1X9++SZcd/PaNn1iRVTxzkHyxcICpJ072PPt27WYPa3Y+x2+8iPv3l62KjAgIB+\nD93r7scJd6HAAdeLiolNnwEoOubCzEUrv/3f3D73d27Z+NIbti07dtWtWfWjEUNub3Krc0u5\nMuGDXvvwf3OWPvPY/ZKcf92KFy385ahhzh2+fH9YtaZdZi1a7Xxd++6nE9LS7HMmfHRb/bqS\n+j1078DhH6zbvD09w9R5y5rcWm/K5+84v33qkW5D3xx79MSptDS7vz+NS/AUI8Z8/fepMxvn\nfdfgprrOLY90v+v61ve98PYnWxdNyrTzO//5Ni3NPn/ix86dn3qk+x09n469EJdpt/2Hjm5e\n+H1gQICkts0b3trhkZ/mLn3w3jsb33Ljml9+k9Tk1hs7tG6a748NuKprPvmveSO4+hVxlSf8\nla4R9zxwwKljm6Y331Br7tKfb7vr0cd7dmnb/LY6NarYbLaM+2T5NL7miyjnczsyKmbxD5/6\n+V16zcPff3isXF8Lr3/45ZnIqFn/Hd21Y2vnlq4dW9/Y9oEX3/7Pxvnfpf9utcrlRw0f5Px6\n+vgPStdr/+6nEyhweDEKHHC9zyZM/WzC1PRvbTZb/0e7p/9lkTSgV48BvXo4v76YmpqWZq9b\ns4qkjA2Wknrf1yn966qVyoUUDD5+8rQku93+88bfqlUq76xuOD3xcNdx309P/zYwIODI8ZNn\nIqPCSxZ3bhn75lAXPkbgmt4aO/6tsVdbQsLhcExfsKJenRrly5ZOH4QSGBDQtMFNS9dsjItP\nCAsNybj/us3ba1evnP5u0N/f7+WBvVf/8mumwz7/1CPOV7eSbr6hlr+/34nTka55SICLZP/J\nf6UbgbJ9RVyOawSeIDAgYM2M8cNHfTHhp7mDXx8tqUSxIi0a3dz5jpY9u7QPKRh8pV+85oso\n5zvD3vd1Sq9uAJ4sd9eCw+GYs2RN6VLF7+1we/rGOjWqNLm13votO85FxzobmiT17PJP/bpI\nobAWjeqvWLfl5JnIsuEl8/FRwRwKHHC9+zq1u/+eO5xfn78Qv+fA4YnT5s9esnraV6Oc0yBL\nmjxj0X//N+eP3fszzp2RmpaW8TgVy5XJ+G1gQMDF1FRJJ89EJiYlV61ULuNPa1evnPHbkS/2\nf/aNMTWad+1yZ6vWTRu0b9U4Uxs/kN9urVenQb06mTampqV9+7+5zq/PREZHRsVERsWUvTmL\nj46P/n0qYxdxzPkLSckpmWYOb9rgpst/sUaViulf22y2sJCQxKSkXD8KID9k/8l/pRtB9q+I\ny3GNwEMULhT6+bsvffDqoFUbtm7Y+vu6zdsXrlg/Z8maV9777Mcv3m3XouGVfjE7L6JqVauU\nj9EBl8rFtXDq7LnYC3G31rstU69HrWqV1m/Zse/gkSa31nNuqVm1YsYdnO8ITp05R4HDW1Hg\ngOvVrVm1x91tM24Z2Oe+m9s//PAzr+3fMLtAUNDwUV+8/9l3DW6q+/FbQ6tUKFegQOCuvQf7\nvfB2puMEBmb9/ExITJIUXKBAxo3BBYIy/oEb3LfnDbWrfTZh6qxFqyfPWGSz2Tq2bjru/Vcq\nlS/rmgcJXEundi0yLifkFBefkF7guBAfL6n+9TXfH/bM5b9+XZlSGb89Fx0rKdPnGIXCQi4f\nclWgQGDeggP5LvtP/ivdCLJ/RVyOawQeJTSkYOc7Wna+o6Wk6NjzP8xc/OLb/+nxxEsHfplT\nsnjRy/fP5ouoIoXD3JEecJ0cXQvxCYnOX8m0vWBwAUnxCf+UrTPdKZy/kml1AngTChxwh0rl\ny7Zp3mDmwlW79h6sW7PqJ9/8WOG60qunf5XehBx7PvM8AldRMDhYUlJycsaNcfEJmabBb9Ps\ntjbNbktOSVm3eccPMxdNmrGw3QNP71ozzTlxHWBcodBQ5xfZGRHt7KjP9LRPSExKS2NtIFhP\njp78WeKKgFcqVqTwoMcfOHL85Edf//Dzxm3d726TaYek5JQ8vogCLOGa10JYSIj+v8yRkbO0\nUSgsJMOWf+3jnKopfQALvA9j8+AmF+ISJCUlp5w6E5mYlNzgproZ5xf4edO27B+qTKkSQYGB\nh47+a8KOP/46kOXOBYKC2rVoOPGTN/s/2v3A4WM7du3LVXzA9UqXKl6yeNE9Bw5n+hjh7Lno\ny3cuE17Cz8/vyPFTGTdu3v5n/kYE8keOnvxZ4oqApaWl2Qe88n7n3kOyXMC+aJFCkuISEi7/\nUd5fRAEeJdfXQpnwEsWLFv5r/6FMH3Du3nfQZrNlHKL11/5DGXfYf/CoJManeDEKHHCHX3/f\nvW7z9rDQkJvq1ihdqoTNZss4n+iOXfsmTV8oKSkp+crH+EdAgH/TBvUOHD62dcfu9I1fTJyW\n/vWmbTvL3dJx0oyFGX/LOdVW+sRygCe4r1O7pOSU0V9OTt9y9lx0vXY9O/cekmnPoMDABvXq\n/PHX/j0HDju3pKXZP/ji+xydztm9n5i9Cw3IV9l/8mcpO1cET3h4LH9/v0PHTixYsW7Y+59n\najuKOHL868kzAwL8nYukZHoa5/pFFJcDPFOurwVJ3e5qc/JM5NylP6dv2bFr35Ydu9o0u61o\n4ULpGyf8NC/9630Hj279fXetapVKlSiWfw8KZvFmD663Yt3m9Lbh5JSLEYePL1n9S5rdPmHs\nMOewt7vbNl+wYl3/l9+7vWmD3fsOfv7dtCmfv3PPY0MWrlz/vzlL72nf8pqneOnp3j9v2tap\n93OP97ynRLEiP2/clpCYVKTQpeGmDerVLV6s8BMvvLN+y47619e02Wy//r574rQFzRvWr399\nzfx74EBOvfn8kwtXrn/v0wknT0e2anLLiVNnv5o881xU7OC+PS/f+cWne9335Mt3PTr46d73\nFQ4L/WHW4qoVyznXeM+mqhXLSxr1+cRDx060aHhzxnWIgPywZPUvl49zds79nKMnf5aueUXw\nhIcn+2b0a7f3ePLDcZP+N2fp3W2bly5VIi4+YW/EkWU/b7qYmjp2xBDnrGGXP41z9yKKywEe\nK9fXwlsvPLVgxbpHB78xuG/PWtUqHT524ouJ08NCC45981+F8uSUlM69h3S6o4Xdbv9w3CSH\nw/HGkCfMPFS4BQUOuN6Grb9v2Pq78+vgAkHly5a+t8Ptzz3xUNMGl2YznjD2jedGfDRr8eqf\n5i67tV6deRPHNm9Y//Xn+o3+cvLQt8a2btrgmqfo2Kbp/8a9++5/Joz9ekqRwmGd72jx0Ygh\n9dr2TLl4UVJAgP/PM795+5P/zl+2dsqsxYEBAZUrXPfOSwMGPf5AppmWAbPCSxbfvOD7kR9/\ns2DFuskzF4aFhLRsfPP08R80rH/95Tv3uLvttx+98eG4718dNa5s6ZKPdOs44vkn/zdnaXZm\nVXS6586W3e9us2jlhv2Hjo0f/SovcJHfNm//8/JhI+XLhrdu2iBHT/4sXfOK4AkPT1bhutI7\nlv1v3PfT5y37edr85bEX4oICAytcV/qR7h0H9OqRvv7x5U/j3L2I4nKAx8r1tXBd6VJbFk4a\nMebr736adzYqunjRIm2aNXhjyBN1alTJePwvRw37YuL0kWO/iYyKqV6lwsRP3nyoawcTDxRu\nYss0bAlOS5cu7XLPPUmHfjEdBDCsWN3Wbw598tl+D5oOgiycvxBfpHare9q3nPvdWNNZvNzT\nw0fNWbzmxPYlpoPgargi3CCkWvNvRr/6cLeOpoMAJnXr9+L+Q8d2rvzJdBBcTc8Bw6fOW3bs\n10Xly4abzuK1gqs0nTtv3p13ZrHouynMwQEA1vDd1Hm393jytz/+St8ycdp8Sc0b1jcXCjCG\nKwIAAGTCEBUAsIa6Natu+u3PTr2fG9Crx3WlS23/c+/4KbMqlivzxMNdTUcDDOCKAAAAmVDg\nAABraHTzDSunffnup99+MXF6dMz58JLFe/W4++2XBmScKhzwHVwRAAAgEwocWbPb7Xa7fcW6\nLaaDAIalpdn3HTzKteA5hj75SMZvd+87tHvfoSvtDFc59vep5JSLXAgeiCvC7Ry79h3kWoCP\nO3XmXFx8AheCh+v30L39Hrp3z4HD6QuKw+Wc75pNp/g3B7Ly9ddf+7HcBiAFBlAGBSSJNZgA\nSYGB3BQAiZsCIEnys9m+/vpr0+/d/4W7VNYqVaoUGBSUlJRkOghgWEhISKfOnWfNmmU6CGDS\n008/PX78+NTUVNNBAMMCAgIGDBgwbtw400EAk7p167ZkyZKEhATTQQDDgoODK1WqZDrFv7CK\nCgAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcAAAAAALA8ChwAAAAAAMDy\nKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8ihwAAAAAAAAy6PAAQAAAAAA\nLI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcAAAAAALA8ChwAAAAA\nAMDyKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8ihwAAAAAAAAy6PAAQAA\nAAAALI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcAAAAAALA8ChwA\nAAAAAMDyKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8ihwAAAAAAAAy6PA\nAQAAAAAALI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcAAAAAALA8\nChwAAAAAAMDyKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8ihwAAAAAAAA\ny6PAAQAAAAAALI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcAAAAA\nALA8ChwAAAAAAMDyKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8ihwAAAA\nAAAAy6PAAQAAAAAALI8CBwAAAAAAsDwKHAAAAAAAwPIocAAAAAAAAMujwAEAAAAAACyPAgcA\nAAAAALA8ChwAAAAAAMDyKHAAAAAAAADLo8ABAAAAAAAsjwIHAAAAAACwPAocAAAAAADA8gJM\nBwC81o5T+v20gvxVv4zqlDSdBgAAAAC8GgUOwPWOxuqpBVpyQJWLKiVNJy/owRv1WUcVL2g6\nGQAAAAB4KQocgIslpar9ZJUO075BqlFckn47qcfnqutUrektm810PgAAAADwRszBAbjYjzt1\nLlHzH7xU3ZB0a1nNf1CbjmvFIaPJAAAAAMB7UeAAXGzDMbWvpsIFJGnL3/orUpIqFlGjctpw\n1Gw0AAAAAPBaFDgAF0u8qLCgS1+/uko//HHp69AgJaWaCgUAAAAAXo4CB+BitUtq8/FLXx+I\nUpWikpSSpm0nVZu1VAAAAAAgf1ipwJGYmFi1atXy5ctn+dO0tLSxY8def/31oaGhtWvX/vDD\nD9PS0tycEJD06E3ae06jf1FKmo7Fqlpxpdr10nLZHbq3tulwAAAAAOClrLSKyptvvnn8+PHw\n8PAsf/r6669/9NFHb7/9dqNGjdauXTts2DA/P78XXnjBzSGBKkX1XRf1m6cfdirNoal/6plF\nOh2nafepaLDpcAAAAADgpSzTwbFz585PP/20d+/eWf704sWLn3322ZAhQ1566aVWrVq9/vrr\n3bp1mzp1qptDAk49b9CeZ1SzmPyko+fVo672DVKbKqZjAQAAAID3skYHh91uf/LJJwcMGFCx\nYsXFixdfvoO/v//27dtLlCiRvqVixYrbtm1zY0bgX8oX1u1VtPOMFj1kOgoAAAAA+ABrdHB8\n9dVXx48fHzly5JV28PPzq169erFixZzfpqamLl++vHnz5u4KCGQhIkrVipsOAQAAAAC+wQId\nHCdPnhw+fPh3330XFhaWzV8ZNmzYoUOHZs6cefXdFi1atHbt2ix/dOjQIeYoRR5FRKtaMdMh\nAAAAACAfpKWlTZgwYfXq1Vn+tGXLlnfddZebI1mgwDF48OAWLVp07do1m/u/8sorn3322axZ\ns2rUqHH1PSMiIn777bcsf3Tu3DmHw5GzoMC/HYhi3g0AAAAA3snhcOzfvz8qKirLn5YrV87N\neeT5BY5FixYtXbp0586d2dnZbrc/9dRTU6dOXbRoUZs2ba65/6BBgwYNGpTlj5YuXdqlS5ec\nZQUycDh0OEbVGaICAAAAwBsFBAS8//77d955p+kg//D0Asf06dPj4uKqVavm/NbhcNjt9oCA\ngLFjxw4ePDjTzoMGDZo9e/aqVasaNGjg9qTAv5yIU8JFhqgAAAAAgJt4eoHjnXfeef7559O/\n/eGHHyZOnLhixYqyZctm2nPSpEnffffd2rVrqW7AE0REyc+mykVN5wAAAAAA3+DpBY5y5cpl\nHLpTpkyZgICAG264wfntuHHjfvzxx/Xr1ycmJr766qsdO3aMi4tbs2ZN+v5NmzYNCgpyc2ZA\nUkS0yhVSsKdfYQAAAADgJaz99uvo0aObNm2StHfv3uPHjx8/fnzWrFkZdzh58mSZMmUMpYNP\nY41YAAAAAHAnP9MBcua55547fvx4+rejRo1KTU2VVL9+fUdWqG7AFNaIBQAAAAB3sliBA7AK\nOjgAAAAAwJ0ocAD5gg4OAAAAAHAnChyA68UkKSqRDg4AAAAAcB8KHIDrRURLUksXdpIAACAA\nSURBVFU6OAAAAADAXShwAK4XEaXiBVUs2HQOAAAAAPAZFDgA12MCDgAAAABwswDTAQAvxBIq\nAICM7A6tP6o/zygkUA3LqW4p04EAAPBGFDgA14uIVrMKpkMAADzDn2fUd562n1T14kpM1dFY\nPXSjPr9LRQqYTgYAgHdhiArgenRwAACcohLVbpLKFdLRIdo9UIee1eZ++u2EHpxhOhkAAF6H\nAgfgYslp+vsCc3AAACRp/G8KC9LU+1Qm7NKWBtdpdk8tjdDWE0aTAQDgdShwAC52KFp2Bx0c\nAABJ2nhcnWoq0E+SlkVof5Qk1SqhOiW18ZjZaAAAeBsKHICLRUQrOEBlw669JwDA6yWnqmCg\nJO2JVJeftOPUpe0FA5WSZjAXAABeiAIH4GIRUapaTH420zkAAB6gbin9ckxpDvWZo7ZVdF9d\nSYpN1q4zqsNaKgAAuBQFDsDFIqKZgAMAcEnfW/TLMXWdqr3n9FUnSUq4qP4LdF0h3VHVdDgA\nALwLy8QCLhYRpRolTIcAAHiG60tpZBsNX6GqRfXpZl1I0aL9kjS3p4L8TYcDAMC7UOAAXCwi\nWh2qmw4BAPAMqXbN3q12VXRbOf15RgUD9VxjPXWrQgJNJwMAwOtQ4ABcye7Q4RiWUAEAXPLe\nOh2M1p9P/7NMLAAAyCcUOABX+vuCklKZgwMAIEm/n9a76/T9vVQ3AABwByYZBVzpQJT8bKpU\n1HQOAIBpqXb1nauO1dXzBtNRAADwDXRwAK4UEaWKRVSAeeMAwOe9vVZHYrXwYdM5AADwGRQ4\nAFdijVgAgKQdp/T+Ov3YXaVDTUcBAMBnMEQFcKWIKGYYBQBfl5ymXrPVo6561DUdBQAAX0KB\nA3AlOjgAAG+t0ak4fdLBdA4AAHwMQ1QAVzoYTQcHAPi0bSc15hf91EPhDE4BAMC96OAAXOZc\nomKS6OAAAN/lHJzS8wZ1q2M6CgAAvocCB+AyEVGSVJUCBwD4qtdXKSqRwSkAAJjBEBXAZSKi\nVSpEhQuYzgEAMGHTcY3dqBn3q3hB01EAAPBJdHAALsMSKgDgs5JS1XeeetfXvbVNRwEAwFdR\n4ABchiVUAMBnDVup2CSNaW86BwAAPowCB+AydHAAgG/65Zg+26xv7lGxYNNRAADwYRQ4AJeh\ngwMAfFDCRfWZo763qGN101EAAPBtFDgA10hM1ckLdHAAgM95eYVS0jT6DtM5AADweayiArjG\nwWg5RAcHAPiW1Yc1bqsWPcwSWgAAmEcHB+AaEVEKCVTpUNM5AADuEn9RT8xT/wa6s5rpKAAA\ngAIH4CrOCThsNtM5AADu8sIy2R0a1c50DgAAIIkhKoCrsIQKAPiUlYf0zW9a2VuFgkxHAQAA\nkujgAFyFJVQAwHecT9bjc/VMQ7WqZDoKAAD4fxQ4ANeggwMAfMfQpQrw0zttTOcAAAAZMEQF\ncIE0h47E0sEBAD5h+UFN3KFVvRXG4BQAADwJHRyACxyLVUoaHRwA4P1ik9V3rp5rrJYMTgEA\nwMNQ4ABcICJaAX6qWMR0DgBAPnt2sUIC9TaDUwAA8DwMUQFcICJKFYsokIIhAHi1Bfv0wx9a\n00cFeQEFAIDn4Q0Z4AIsoQIAXi8mSQMW6sVmal7RdBQAAJAVChyAC7CECgB4vYGLVChII1qZ\nzgEAAK6AAgfgAnRwAIB3m7dX03bp+64KZnAKAACeigIH4AIHo+ngAACvFZmgJ+frlea67TrT\nUQAAwJVR4ADy6ky8zierOgUOAPBSAxepRIhebWE6BwAAuCr6LIG8ioiWpCpFTecAAOSDOXs0\n6y9t6sfgFAAAPB0dHEBeRUSpTJjCgkznAAC42tkEPbVAr7XUrWVNRwEAANdCgQPIK2YYBQBv\nNWCBriuk4QxOAQDACui2BPKKNWIBwCtN2an5+7T1CQXyeRAAAFbAHRvIKzo4AMD7nIzT4MV6\no5XqlTYdBQAAZA8FDiCv6OAAAO8zcKEqFdFLzUznAAAA2cYQFSBP4lJ0Jp4ODgDwKt//rkX7\n9euTDE4BAMBKuG8DeXIwWg7RwQEA3uPEBQ1ZopGtdUO46SgAACAnKHAAeRIRrUJBKhViOgcA\nwEWemK9aJfV8U9M5AABADjFEBcgTJuAAAG/y321aeVDbnpK/zXQUAACQQ3RwAHnCEioA4DX+\nvqAXl+u9tqpbynQUAACQcxQ4gDyhgwMAvIPDoX7zVKeknm1sOgoAAMgVChxAntDBAQDe4evf\ntPaIvu/K4BQAAKyKAgeQe6l2HYulgwMALO9wjF5arlHtVIM/6QAAWBYFDiD3jsTqop0ODgCw\nNodDTy1QvdIaeJvpKAAAIA9YRQXIvYgoBfqpQhHTOQAAefDFVm04qh395cfgFAAArIwODiD3\nIqJVuSijtQHAwg7FaNhKjW6v6gxOAQDA4ihwALnHEioAYGl2hx6bo4bl1P9W01EAAECeMUQF\nyD2WUAEAS/vPZv16Qn8MkI1ePAAArI8ODiD36OAAAOs6GK3XV+njDqpKqRoAAK9AgQPIvUMx\ndHAAgCXZHeozR00qqN/NpqMAAAAXYYgKkEun4hSXQgcHAFjSRxv1x2ntfJrBKQAAeA8KHEAu\nRUTLJlUpajoHACCH9kRqxGqNu1sVCpuOAgAAXIchKkAuRUSpbCGFBJrOAQDIiVS7es9Rmyrq\nU990FAAA4FJ0cAC5FBGt6oxPAQCr+XCD9p3TzPtN5wAAAK5GgQPIpQNRzDAKABbzV6TeXqtv\nOqs8g1MAAPA6DFEBcok1YgHAWlLt6j1bd1TVI/VMRwEAAPmADg4glyKi6eAAACt5b50ORmve\ng6ZzAACA/EGBA8iN88mKTKCDAwAs4/fTenedJnVVmTDTUQAAQP5giAqQGxHRkujgAABrSLWr\n71x1rK4HrjcdBQAA5Bs6OIDciIhS0WAVL2g6BwAgG0b+rCOxWviw6RwAACA/UeAAcoMJOADA\nKraf0qj1+rG7SoeajgIAAPITQ1SA3GAJFQCwhOQ09Z6tHnXVo67pKAAAIJ9R4ABygw4OALCE\nt9boVJw+6WA6BwAAyH8UOIDcoIMDADzftpMa84u+6qRwBqcAAOADKHAAOZaSpuPn6eAAAI+W\nnKZes/XgjepWx3QUAADgFhQ4gBw7HKM0Bx0cAODRXlulqER9fKfpHAAAwF1YRQXIsYhoFfBX\nuUKmcwAArmDjcX28UfMeZD1vAAB8CB0cQI5FRKlKMfnZTOcAAGQl4aL6zFHv+rqrhukoAADA\njShwADnGEioA4MleXaX4FI1pbzoHAABwL4aoADnGEioA4LF+OabPNmv+QyoWbDoKAABwLzo4\ngByjgwMAPJNzcErfW9SxuukoAADA7ShwADnjcOhQNB0cAOCJXl6hlDQGpwAA4KMYogLkzIk4\nJabSwQEAHmf1YY3bqsUPq1CQ6SgAAMAEOjiAnImIkp9NlYuazgEAyCD+op6YpwEN1L6a6SgA\nAMAQChxAzkREq1whBdP8BACe5Pmlsjv0fjvTOQAAgDm8SwNyhiVUAMDTrDyk/27Tyt4MTgEA\nwKfRwQHkDEuoAIBHOZ+sx+fqmYZqVcl0FAAAYBQFDiBn6OAAAI8ydKkC/PROG9M5AACAaQxR\nAXKGDg4A8BzLD2riDq3uozAGpwAA4PPo4AByICZJUYl0cACAR4hNVt+5GtJELSqajgIAADwA\nBQ4gBw5ESVJVOjgAwAMMXqyQQI1sbToHAADwDAxRAXIgIlolCqpYsOkcAODzFuzTlD+0po8K\n8loGAABIooMDyBFmGAUATxCTpP4L9GIzNWdwCgAA+H8UOIAcYIZRAPAEAxepcAGNaGU6BwAA\n8CQUOIAcoIMDAIybt1fTdun7rgpmcAoAAMiAlwZADkREq0990yHgM+Iv6v11mvmXDkWrQhF1\nrqk3WqkoU8DA96w+rHfWavtJSbohXH+e0bDmuu0607EA94pJ0siftWCfjsaqSjF1r6NhLRQa\naDoW4HYL9umDDdp5WoH+anCd3rpdDcuZzgSPQYEDyK7kNJ24QAcH3ORMvJpPUJpDQxqrenEd\nidWnmzVtl9Y/rspFTYcD3OjddRqxWv1u0cDbJOnF5YpJUgAdqPAxh2PUfIKKBOv5pqpURAei\n9PGmSzeF8FDT4QA3GrJU47bq6dv0QlOlpGneXjX9Vp/fpf4NTCeDZ6DAAWTXwWjZHczBATcZ\nvlKhQVr/+D+fzj1WX+0n67klmtPTaDLAjf6K1IjVmnG/7q0tSVN36WisRrfXy8t13/WqU9J0\nPsBdnlui6sW17FEF+V/a8vjNajZBw1fqv/cYTQa40S/H9NlmreqtlpUubbmvrlpV0qDF6lxL\n5QoZDQfPwCcgQHZFRKlggMqGmc4BH+BwaPpuvdL8X73HQf56vZUW7Vf8RXPJAPeauVv1y1yq\nbpxN0ODFeq2lnm+i+mU0c7fpcIC7xF/Uov16vdU/1Q1JIYF6pbmm75bDYS4Z4F7Tdqld1X+q\nG059b1aZMM3faygTPAwFDiC7IqJVtZhsNtM54APOp+h8smqVkKTzySr5odYekaRaJXTRrlNx\nZtMB7nPsvGqWuPT1u2tVJkzDW0hSzRI6dt5gLsCtTsXpov3STeHXEyo1WueTJalWCZ1P1vkU\ns+kA98l4U3hsrh6fK0k2m2oU56aASyhwANnFEipwm7AgBfnrZJwk/X1B5xL18CydS9TJONmk\nYswzCp9RouClC0HS4Ri1rqxAP0k6GacSBc3FAtyrWLBs0sk4ORwatFiRCfr7giSdjFOQv8KC\nTOcD3CXjTWFPpL7boS+2StwUkAEFDiC7IqKZgANu4m9T+2oat1UOh87Gy8+mwgX05Hx9sUWN\nyqs4t3D4jA7Vtf6o/jgtSdFJKlZQkv44rfVH1aG62WiA+xQvqEbl9cUWTf5Df5yWn01n4uVw\naNxWta8mf3pL4TM6VNei/TocI0mRCWpVSUOX6out2n1Wd3JTgCQKHED20cEBdxrVTj8fVpef\ntPG4ihbQW601d4+m7NTYO00nA9yoZSX1qKs7Juvb7ToTLz+bvt2uOyare53MY7AB7zb2Tv30\np/ovVO/6KhasjcfU5Sf9fFij2plOBrhR19pqVkEtv9OPO3U6To/epAbXafBi9bpJ15cyHQ6e\ngQIHkC12hw7H0MEB97m+lDY/oaRUvbJCUUm6b5oqFZWfjVZk+Jzv79XzTTR0qfZE6o3VGrpU\nzzfRpK6mYwHu1aS8HrhBdru+3KpziRq2Ukmp2tSPN3XwLTab5j6oPvX1xHxdSFa/edobqcpF\ntSdSKWmmw8EzUOAAsuX4eSWn0cEBt6pTUsse1bDmuqWMol7WgUHqWF0PzVRiqulkgBsF+eul\nZop6WQUD9HUnRb2sl5r9ay0JwBcciNLUP/Vjd0W9rFvL6pXmWvao6lLdgO8pGKCRrbV7oGTT\nyl4686LWP64jMXpxuelk8AwUOIBsiYiWv02VipjOAd9zIUWVi6lYsGw2fXevzifrlRWmMwFu\nl2ZXYqquD2e6AfioZ5eoWUV1q6Niwapa7NIqKoDPikmSpFvKys+msmGafr++3KqJO0zHggeg\nwAFkS0SUKhThM0MYcDZepUIufV0sWJO66ostmsdi7/Ax0UkSSwjBVy3Yp2UR+qTDpW/DQ3U2\n3mggwLSz8Qr0U5ECl75tVkHvt9OAhdp20mgseAAKHEC2sIQKTDmboPDQf75tVUkvNlPfeTpx\nwVwmwO2iEyVdWkUF8CkpaXp+mQbephvDL20pFaozFDjg284mqGSIbBl6+p5voi611H2aziWa\niwUPQIEDyBaWUIEpZ+NVKvRfW95urRrF9dBMpTkMZQLcjg4O+KyPN+lcgl5v9c+WUiEUOODr\nLn91JOnbLgoL0oMzeIHk0yhwANlCBwdMOZvwzxAVpwA//dBN20/po18MZQLcLjpRwQEKDjCd\nA3Cv0/F6b53eb6cSGdqXwkN1NsFcJsADXP7qSFJooGY9oK0nNPJnE5ngGShwANlyMJoODhjg\ncOhcQhafUVQtpm8669VV2nTcRCzA7aKTaN+AL3pxmaoV0+M3/2tjeKiiEpVqN5QJ8ABZdnBI\nqlFck7rqnbWa9ZfbM8EzUOAAru1comKS6OCAATHJumjP4jMKSfdfr5436JFZzKUPnxCdyAQc\n8Dkbj2vKTn3SIfPiQaVCZXcw0QB8WmSCSmb16khS55oa3kJ95mhPpHszwTNQ4ACuLSJKkqpS\n4IDbOefJz/IzCklf3i1/Pw1a7M5EgBl0cMDX2B16bokevEEtK2X+kXPmaabhgC/LcohKurdu\nV4tK6jpVF1LcmAmegQIHcG0R0SoVosIFrr0n4FpnE2TTv4ZeZxQWpCnd9NOfmrLTvbEAt6OD\nA75mwnb9eUbvtc3iR8WDFeDHSrHwaVcaouLkZ9MP3XQxTU/Od2MmeAYKHMC1sYQKTDkbryLB\nCvK/4g4NrtPI1uq/QPvOuTEW4HZ0cMCnnE/W66v1WktVLJLFT202lWQhFfi2q3dwSCoWrFkP\naN5efbzJXZngGShwANfGEiow5Zr3b0kvNlXj8np4llLS3JIJMIEODviUEWsUGqghja+4AyvF\nwpelORSdeLUODqd6pfVNZ720XD8fcUsseAYKHMC1HYhSdTo4YMLVOzCdnH2Yx2L15hp3RAKM\noIMDvuOvSH2xRR93uNq6yKwUC18Wlag0x7U/AZL00I3q30APTNfx8/kfC56BAgdwbQxRgSnZ\n6eCQVDpU392rDzdo5aH8zwSYQAcHfMfQpWpVWZ1rXm2f8FDm4IDvcj75r7SKSiZj71Stkuox\nTck0uvoGChzANSRc1Kk4hqjAjOx0cDh1rK4Bt6n3bEXymR68ER0c8BGz92jlQX3W8Rq7lQpl\niAp819kE+dlUPHtV70A/TbtPx89ryJJ8jgXPQIEDuIaD0XKIDg6Ykc0ODqcx7VUyRL3nyOHI\nz0yACXRwwBckp+nl5Xq2sWqXvMaepUIYogLfFZmgYsEKyPYb2dKhmn6/vt2ub7fnZyx4Bgoc\nwDVERCssSOHZfpMJuFD2OzgkFfDXj9215rC+/DU/MwFud9Gu+It0cMD7jd6g2GS91vLae4bT\nwQEflqNXR05NymtMez2zSL+eyJ9M8BgUOIBriIhS1WKy2UzngE/KUQeHpLql9FF7Pb9Mv5/O\nt0yA20UnSspuNzJgUcfPa9R6jWqnIgWuvTMFDviynL46chrUUD1vUPdpdD95OQocwDWwRiwM\nikzI8WcU/RuoSy09NFMJF/MnE+B20UmSGKICL/fictUuqd43ZWvnUqGKTWJ1cPioXHRwOH15\nt0qG6MEZSmMwr/eiwAFcA0uowJQLKUpKzc1nFF91UnyKXliWD5kAE5wdHAxRgRfbcEzTdumL\nu+WXvY7R8FA5xAfR8FG56+CQFBygWQ/o99N6fZWrM8FjUOAAroEODpjiXAUtF59RFA3W5G76\nZpvm7HF5KMCA6CQFByg4wHQOIH/YHXpuiXrdpEblsvsrznd3rBQL35SL/tZ0lYrox+4a/Ytm\n7HZpJngMChzA1aQ5dDSWDg6Y4fxoLpvLvGfSoqJeaa7H5+porGtDAQZEJ9K+AW/29W/aG6n3\n2ubgV4oGq4A/03DAR52Nz+WrI6c7qur1lnpsrnafdV0meAwKHMDVHI1VShodHDDjTLzCglQw\nt59aj2ilOqX06GwGmsLyopOYgANeKzpJb6zWG61UNixnv1iSlWLhq3I9RCXd6y3Vvpq6TdX5\nZBdlgsegwAFcTUSUAvxUoYjpHPBJZ+PzdP8O8NNPPbTztD5Y77pMgAl0cMCLvbFaRYM1qFGO\nf5GFVOCz8jJExclm08R75WdTr9ly8DmQd6HAAVxNRLQqFVEgFwpMOJvn+3eFwhrfWSPWaONx\nF2UCTKCDA95q11l99av+00EF/HP8u+GhzMEBXxSbrJS0vHZwSCoUpFkPaPVhjf7FFbHgMXjf\nBlwNS6jAoLPxCs9bgUNSj7p6pJ4enqlYmjBhWXRwwFsNWqSO1XVXjdz8bik6OOCTcj0F++Vq\nl9TEezV8pZZGuOBo8BAUOICrYQkVGJT3IaZOn9+lAgF6Yp4LDgUYQQcHvNL03dpwTGPa5/LX\nw0OZgwO+KC9TsF+ua20921gPzdShGNccEMZR4ACuhg4OGHQ23jUfUIQGako3zd2r7393wdEA\n96ODA94nMVUvLdfQJqpZIpdHKBVCBwd80dl4FQrKzaiuK/mgneqVVrepSkx12TFhEAUO4GoO\nxdDBAWNc1cEh6Zayeq+tBi7U3nOuOSDgTnRwwPt8sF5JqRrWPPdHYIgKfFPeZxjNJMBPU3so\nMkFPzXflYWEKBQ7gis7E63wyHRwwxlUdHE5DG+v2ynp4plLSXHZMwD3o4ICXOXZeo3/R6DtU\nuEDuD8Iko/BNLvz4J114qGbcr2m7NP43Fx8Z7keBA7iiiGhJqlLUdA74Ktfewm02Teiivy/o\ntVUuOybgHnRwwMsMXaqbSuvhG/N0kPBQXUihqR4+x7Uf/6RrVE6fdNAzi7ThmOsPDneiwAFc\nUUSUyoQpLMh0DvikhItKuOjiW3h4qCbeq482atF+Vx4WyFcX7YpPoYMD3mPVIc36S590kM2W\np+M4K+A0ccDX5EcHh1P/Bup1k+6bppNx+XJ8uAcFDuCKWEIFBjknCXf5LfzOahrcSI/N1Slu\n3rCImCQ5RAcHvESaQ0OWqu/Nalgur4dyriPONBzwNfnUweH0+V0qX1gPz1SqPb9OgfxGgQO4\nIpZQgUEuXOY9k1HtVK6QHpsrh8P1BwdcLjpREh0c8BLjtupwjEa2dsGhwoIUEshKsfA5ZxNc\ntkbs5YIDNON+/XlGr6zIr1Mgv1HgAK6IDg4YdDZBBQMUGuj6Ixfw17T7tOGoPtvi+oMDLhed\nJNHBAa8Qlai31mhka5UJc80BWSkWPigy34aoOFUsov/10H82a+qufDwL8g8FDuCK6OCAQfna\ngVm9uMbeqZeWa/up/DoF4CpRiSrgr4IBpnMAeTZ8pcJD9fRtLjsgK8XCB+XrCySntlX0dmv1\nnas/z+TviZAfKHAAWYtL0Zl4OjhgTP7NoeXU7xZ1q6MHpisuJR/PAuRddCLtG/AGO07pv9v0\ncQcFuu7VNyvFwtckpir+Yv6+QHJ6uZnuqqFuUxWTlO/ngmtR4ACydjBaDtHBAWPc8AHFuLt1\n0a6hS/P3LEAeRScxAQe8wXNLdE8t3VnNlccMD2UODviW/JuhLBObTRO6KNBfvWbLzpxllkKB\nA8jagSgVLuCOCjGQpfzu4JBUNFg/dNN3O/TTn/l7IiAv6OCAF/hxpzYd1wd3uPiwzMEBX5NP\na8xlKSxIsx/Q2iN6b507TgdXocABZI0ZRmGWGzo4JDWroNdaasBCHYnN93MBuUMHB6wu4aKG\nrdRLzVTD1W2hzMEBX3M2XsEBCgty0+lqltD3XfXmGi3a76YzIu8ocABZY4ZRmOWGDg6n11vq\n5jJ6ZJbS6MCER6KDA1b37jrZHXq5ueuPzBwc8DVue3WUrkstvdBUj8xSRLRbz4tco8ABZI0O\nDpjlng4OSX42Teqq3Wf17lp3nA7IKTo4YGkHozV2o8a0z5dlv8Pp4ICPORuvkm4fP/5eWzUq\nr25TlXDR3adGLlDgALJGBwfMcudnFOUL65vOGvmz1hx20xmB7KODA5Y2dKluLav76+bLwUuF\nKDGVxbDgQyIT3PTxT0Z+Nk3ppgvJemK+u0+NXKDAAWQh1a5j5+nggDHJaTqf7NZbeLc6evxm\n9ZqtqET3nRTIDjo4YF0rD2nBPn1xt2y2fDl+eKgkmjjgQ9w/RMWpeEHNekCz/9LnWwycHTlC\ngQPIwuEYpdrp4IAxl1ZBc+8t/JMOCgvSk3w6AQ9DBwcsKtWu55boyVt1U+n8OoWzDs5KsfAd\nbhvAe7n6ZfR1Zw1dqnVHzQRANlHgALIQEa0gf5UvbDoHfNWlVdDcewsPCdS0+7Rov77d7tbz\nAldHBwcs6tPN+vu8RrbOx1MUDFChIDo44ENMdXA4PVpPj9+s+6fr7wvGMuCaKHAAWYiIUuWi\n8s+fhlLgms7GK8hfhd21Clq6G8L1fjs9u1h7It19aiBLqXbFp9DBAes5E6+31+rtNvk+ISIr\nxcKnGOzgcPrsLlUrpvumKSXNZAxcBQUOIAssoQKznB9Q5NOY7asb3FBtquj+6UpKNXB2IJPo\nJDlEBwesZ9hKlSukp27N9xOxUix8SmSCgVVUMgr00/T7dThGLy43GQNXQYEDyAJLqMAsgx9Q\n2Gz6tosiEzR8pZkAQEbRiZLo4IDFbDup73fo87sUkP8vtMNDmYMDviLVrpgkk0NUnMqGafr9\n+nKrJu4wnARZosABZIEODphldohpqRD92F2fbtaCfcYyAE7RSRIdHLAUh0PPLlH3urq9sjtO\nVyqEISrwFZEJcrh9hrIsNaugUe00YKG2nTQdBZehwAFk5nDoUDQdHDDJ+BDT2ytrSBM9Plcn\n40zGAKITFeSvkEDTOYBsm/SHfjuhD9q56XQMUYHvuDQFu+kODqehTXT/9eo2VZG0UHkYChxA\nZqfiFX+RDg6YZLaDw+m9tqpaTH3myOEwnAS+jCVUYC0XUjR8pV5prspF3XRGJhmF7zgbL3+b\ninrMTWHc3SpUQA/NVBqvlDwJBQ4gs4go2aQqFDhgjvEODkmBfprSXZuOa+wmw0ngy6ITVZwJ\nOGAd76yVv00vNHXfGRmiAt9xNkElQ+TnMaschgZq1gPaekIjfzYdBRlQ4AAyi4jWdYVUMMB0\nDvgwT+jgkFStmD7tqGErtPlv01Hgq6KTmGEUlnEgSv/ZpI87uHVQlXOSUVrt4As84eOfTGoU\n1+SuemetZv1lOgr+HwUOIDOWUIFxnnML732T7r9ej8zShRTTUeCTohMZogLLeHaJmlVU9zpu\nPWl4qFLSFJvs1pMCRhhfIzZLnWrq1RbqM0d/RZqOAkkUOIDLsYQKzPKQ/KaQxwAAIABJREFU\nVdDSfdVJNunZxaZzwCfRwQGrWBahpQf0SQd3n9dZDWelWPgCD+lvvdybt6tFJXWbyqdBHoEC\nB5AZHRwwy3NWQXMKC9KU7vrhD/2403QU+B46OGAJKWkavFgDG+rGcHefOjxUNjENB3yC5/S3\nZuJn0w/ddDFNT843HQUUOIDL0cEBszxqFTSn267TiNv19EIdijEdBT6GDg5YwsebdDZBb7Qy\ncOpAPxUJZqVY+ASP7eCQVCxYsx7QvP9j797j5C7ru/+/Z2ePM9ns5jCThEMSkiDnKsEKaAH5\ncZPYpGJF7gJ6CxRuEIgUKtByEi0i2iKWIqaKRc6oFA8oNwfRiEAROQhWwAKZkEA4ZTbz3dMc\n9jDz/f0xm81mD5jd/c5c1/Wd1/OvZCfufNpHwnz3c72vz+cl/Suj2U2jwQHsoLtPHTkSHDDJ\nti1oZRf/hQ7aRSfcrYGS6VJQS0hwwH7vZHXVo/rKUZpjqBmXZFMsaoO1CY6yP5un73xU//CQ\nHt5oupTaRoMD2EHKk0SCAybZtgWtrC6iWz+uVEZfYhcaqogEB+z3Dw9p6SydttxYAWyKRY2w\nOcFR9skDdNb7dfzd2txtupQaRoMD2EEqo/ZmzeZ5GuZYe0Cxa6tu+biuelTrXjVdCmoGCQ5Y\n7jebdft/69qPKGquK13eFAuEm+8rk7dxi8oo16zU3nN13F3qK5oupVbR4AB2wAAOGGfzAcXq\nPXXGQTr5J9qaN10KasBgSb39JDhgr5Kv8x7Qifvr8EUmy0jGmcGB8MsUNFiy9ARopIY63fW/\ntblb5z1gupRaRYMD2AErVGCctQmOsq+v1OwWnf5T03WgBnQW5IsEB+x103N6fouuOspwGQlm\ncKAGdNg3gn0i8+L6z7/Rd5/Vjc+aLqUm0eAAdkCCA8bZnOCQ1FyvOz+hB9br28+YLgVh5xUk\nkeCApbr79Pl1uvQwLWwzXAkzOFAL0llFpDkWPyCNdOhu+toKffY+PfWm6VJqDw0OYAckOGCc\n5QkOSfsldPUKnfeA/vsd06Ug1Ly8RIIDtvriw2pp0OcONV0HMzhQG9I5tTerwZ0fXs/5gE7Y\nX8fdxT/PanPn7whQeX1Fbe4mwQHDLE9wlK35c61cqk/+UPlB06UgvLyCGqOKNZiuAxjjjx26\n/kn960o115suZdsMjpJvug6gkuw//hnr31crEdOJd6vIP88qosEBbLexU0Vfy0hwwChXPsJv\n+mv19OsfHzJdB8KLFSqw1uce1BGLdcxepuuQJCXiKvpDV7qAsHLi+GeU5nr98Hj9/h1dts50\nKbWEBgewXSqjpqh2aTVdB2pY0Vcm78ZH+Kxm3fpxrX1KP33JdCkIKa/AAA7Y6Cf/o19s0L+u\nNF3HNsm4JMZwIORcOf4ZZVGb7vyEvva4/vNF06XUDBocwHYpT0tmqc7cKnsgk1fRd+Yj/IhF\n+ocP6bSf6s0e06UgjEhwwEL9Rf3DQzr3YO2fNF3KNnNjqouwKRYh15HTXBeOf8Y6eokuP0Kn\n3qMX06ZLqQ00OIDtmDAK48pPqE4kOMquOFJ7ztYnf8j9UgSPBAcsdPXj6urT548wXccI0Yhm\nt5DgQMi5eEVl2GWHacVSHfsDdfWZLqUG0OAAtmNHLIxL51QXcWYLmqT6Ot1+rJ59W1973HQp\nCB0SHLDNGz366mP6ylFqazJdyo7YFIvQc/SKSlkkopv/WnURnfxj+RwIVRgNDmA7EhwwLp3V\n7BZFnbontWSWvvNRXbZOT2w2XQrChQQHbHPhz7XXHJ3yPtN1jMGmWISe0wkOSa2N+tHx+tVG\n/QsHQhVGgwMY4vva2EmCA4Y5+vn9N/vpxP31qR+pm+wlgpMhwQGbPP66fvCCrl9l46yu8qZY\nIMQ6cg4nOMr2nqub/1qX/lIPpkyXEmo0OIAhb/QoP0iCA4a5m8Bcu1r1dfrsfabrQIh4eRIc\nsEXJ17kP6NN/pkN2M13KeBJxrqggzHr6VRh0dcjoSB/fW+ceok/+UL9/Rzc8o/Me0Bcf1s/p\ndwSKBgcwJOWpLqLF7abrQG1zNMEhaUaj7vyEfvCCbv9v06UgLLwCCQ7Y4oZn9FKHrjrKdB0T\nSMS4ooIwc24E+7v45/+lXVr1/hv0pUe0qUuPbNIx39OK29TBP+GA0OAAhqQy2m2mmqKm60Bt\nczfBIemgBbriSJ31//TyVtOlIBRIcMASXkGf/5U+f4R2aTVdygSSJDgQauUf/kOQ4JD00la9\n1KFYg45YpB8fr3Un68U1yuT1yR+ariwsaHAAQ1ihAhu4m+Aou/CDOmQ3fepH6i+aLgWOGyyp\nt58EB6xw+a/U3qy/O9h0HROjwYFwS+cUb1CswXQdQfjGb3X4Iv3807r7RX37GUlaMku3HauH\nNugPW0wXFwo0OIAhrFCBDZxOcEiqi+j2Y/V6l774sOlS4LjOgnyR4IB5L6b17af1bx+xOuOZ\niCuT12DJdB1AZXTkQhLfkPTs2zp6qQ7eVf/2lzr3fj33tiTtM1e7zxz6NaaJBgcwhAQHbOB6\ngkPSvLhu+mv9y3/pFxtMlwKXeQVJJDhg3t8/qJXLtGpP03W8q2RcJV9b86brACrD9eOfcX3m\nIH35KDVY3Dl1FA0OYAgJDhjn+9rq/hY0SX+5TGf/uU7+CROzMHVeXiLBAdPuflEPb9Q1K0zX\n8aeUO+NsikVYbckq6f7TUdmB87evTTn/UO2XkKQX03q9WwfON1hXeNDgACSpsyCvQIIDhnX2\naaDkfIKj7OoVSsZ10o/VX9SLaf08pQ2efN90WXCHV1BjVPFQ3LiGo/KDuvAh/f0hes8c06X8\nKXNaVF/HGA6EVgjyrcPOOViPvaZ/+rUGtt0pS3n69I+1cqn2TxqtLCzqTRcAWGF9RpKW0OCA\nUUNb0EJxRtEU1R3Havm3tcvXtTWnpqj6ijp4V61dreULTBcHF3h5tXM/BUb982PKD+iSw0zX\nsRMiEc1pYVMsQqsjp72s7zPupP0S+sFx+sy9uvF3OmgXdRX0+Os6fJFuP9Z0ZWFBggOQpJSn\nOS08TMOwdE6RsGxBk/RiWgMldea17mQVLtPL52jpbB1+E0PCsVO8AgM4YNLr3fra47p6hWY2\nmS5l57BIBSEWshkcf723XvqsLjtci9p0+CL97JP6+afD8/hnHAkOQGIAB+yQzqqtWQ2h6Dz7\nvi58SJcdrpc69Nn79NTp2nO27jhWH/2evvAr/eh40/XBel6eARww6XMP6s/m6f8cYLqOnZaM\nM4MDoRWmKypl7c064yDTRYRUKJ6jgWljhQps0BGiz+8NndrYqVPep7Wr1dOn838+9PVT3qdf\nvmq0MjiCBAcMeuw1/eiPuvYjikRMl7LTEiQ4EF4hS3CgomhwABIJDtghHYoVKmVdBUma06LZ\nLbrjE/qv14YmjM5pUW+/SkwbxZ9CggOmFH2tuU+nHqgP7Gq6lMlIxpnBgXDqK6qnPzwnQKg0\nGhyARIIDdtiSDc/n96J21UWGxm0ctlD/fdbQQegftmhxu+rcORSFKSQ4YMq/P6WNnfrSkabr\nmKREjAQHwilMI9hRBTQ4ABUG9WYPCQ6YF6YE5pwWrdpTF/9C+cHtX3yzR//yX/qUO3faYZCX\n12wSHKi6TF5ffFj/9GHNn2G6lEniigrCqhxNYgYndhJDRgG92qmST4ID5qVzOihEK1TXrtYR\nN2nfb+r05VrYpue36NvP6M/m6aK/MF0ZXOAVuKICAy5dp2Rcaz5guo7JY8gowiqdVWNUMxtN\n1wFH0OAAlMqopV4LXDurQfhsCVGCQ9LuM/X82br6cf3sZW3u1nvm6J//l/7vcu6nYKd4ea6o\noNqee1vfeUb3ftLJbVbJuDoL6i+qMWq6FCBQHTnNjbk08Rdm0eAAtD6jJbP47ybMS4doBkdZ\nrEFfOEJfOMJ0HXAQCQ5U33kP6Ji99JFlpuuYkkRMvtSR0y6tpksBAhW+HbGoKAcb1EDQUp6W\nMYADFugI0RYVYDqKvnr6SHCgqr73vJ7YrH8+2nQdU5WMS2IMB0IoTBPKUAU0OAB2xMIK3X3q\nKw49oQI1rrMgXyQ4UD25AV38C134Ie3p7PNAe7Mao2yKRQiR4MCk0OAA2BELK5SfSvkIByR5\neUkkOFA9Vz2qou/8CGQ2xSKUSHBgUmhwoNaVfG3qJMEB88rT79mCBkjyChIJDlTLBk/X/EZX\nH614g+lSpodNsQil8pBRYCfR4ECte71bfUUSHDAvnVNro5oZ/QxIXl4Ndc7/tAlXnP9zHbRA\nx+9nuo5pY1MsQokrKpgUHqVR61IZRSNa2Ga6DtQ8EpjAMFaooGp++ap++pJ++3/DsEwtGWcG\nB0KIByRMCgkO1LqUp4VtLI2HeRxQAMO8PAM4UA2DJZ33gD5zkN6/i+lSgsAMDoRP0ZdX4AEJ\nk0CDA7WOFSqwBAcUwDASHKiObzypN7p1xZGm6whIgisqCJ2tOZV8HpAwCVxRQa1jhQosQYID\nGEaCA1WwJasrfq0vHRme+YVJhowidNgxh8kiwYFaR4IDliDBAQwjwYEquOSX2rVVZ77fdB3B\nocGB8ElnVRfhEwGTQIMDtW4DCQ7YgQQHMIwEByqnsyDf1+/e0s3P6RurVB+iZ+FETD39yg+a\nrgMITjqn2S2Kuj8DGFXDFRXUtI6cuvpIcMAKJDiAYV5B+yRMF4FwyeR1+a/0/ee1Na8ZDWqq\n14qlOnKx6bIClYxLUjrLbjiERwfHP5ikEHWtgclLeZK0R7vpOgASHMAIJDgQrHeyWv5t/XqT\nvrFKvz9TZ7xfXkG/3qin3jRdWaDKXXI2xSJMOP7BZJHgQE1LZZSMa2aT6TpQ83IDyg3wEQ4M\nYQYHgvWFX2l2ix4/Tc316u3X95/X5Ufola1a8//05OmmiwtOa6Na6hnDgVDh+AeTRYIDNY0V\nKrAEQ8KBkUhwIFg/+R+de4ia6yXpykcUjejCD+of/0JPvak3e0wXF6gEc0YRLiQ4MFk0OFDT\nWKECS6SzkvgIBySp6KunnwQHAlPytSWrxe2S5Pv61tP6148o1jD0lbd6zVYXsGR86AMFCAcS\nHJgsrqigpqU8HbWH6SIAKZ1TS73iDabrACzQWVDJJ8GBwNRFlIhrU6e0SJGIXj1v6G/Xpk5J\nmj/DbHUBS8aZwYFQSWc1lwYHJoMEB2oaCQ5YggQmMMzLSyLBgSB9bC9d91v1FSVt7539y3/p\noAXatdVgXcFLxLiiglDpyPGAhMmhwYHalRvQ273M4IAVtmRJYAJDvIIkEhwI0hVHaktWh/yH\n7n5Rf+zQz1NafafuflHfXG26sqBxRQVh4vusicWkcUUFtWuDJ18kOGCFNAcUwDZeXg113NhC\nkObP0O8+o0vX6bSfqrtPzfU6eomePVN7zTFdWdAScW3ZaLoIICBdfRoo8YCEyaHBgdqV8jSj\nUUm6wrBAmgQHsI1XUHuzIhHTdSBc5sb07b/St/9Kb/cqEVc0pH/BuKKCMGHHHKaAKyqoXamM\nlsziGRpWSOeU5IACkFTeEcsADlTM/Bmh7W6IIaMIl/J9K4aMYlJocKB2pTwGcMAWDBkFhnkF\nBnAAU5SMKzeg3n7TdQBBSOfU1qTGqOk64BQaHKhdrFCBPVjzDgwjwQFMWblXTogD4cDxD6aA\nBgdqFwkO2IOPcGAYCQ5gysq3HRnDgXBI57ifgkmjwYEaVfT1WhcJDlihr6iefhIcwBASHMCU\ntdRrRiObYhES7IjFFNDgQI3a1Kn+IgkOWKH8JEqCAygjwQFMRzJOggMhQb4VU0CDAzUq5am+\nTgvbTNcBsAUN2BEJDmA62BSL0GBCGaaABgdqVCqjxe2q518ALJDOqjGq1kbTdQB2IMEBTAeb\nYhEaJDgwBfx4hxrFhFHYo3xAEYmYrgOwAwkOYDqScWZwICRIcGAKaHCgRrEjFvbggAIYVvTV\n00+CA5i6BDM4EBYdbFHB5NHgQI0iwQF7cEABDOsqqOST4ACmjhkcCIfcgHIDnABh0mhwoEa9\n6pHggC1IcADDvIIkEhzA1DGDA+HACHZMDQ0O1KJ3surpJ8EBW5DgAIZ5eUmaTYIDmKrymljf\nN10HMD3lUTKcAGGyaHCgFqUyikh70OCAHUhwAMO8gurrFG8wXQfgrERc/UV195uuA5iedE4t\n9XwcYNJocKAWpTzNn8F/MWELEhzAMC+vWc0sFQKmLhmXxBgOOI/jH0wNDQ7UIlaowCp8hAPD\nvAITRoFpScQUEZti4TyOfzA1NDhQi1ihAnsMltRZ4CMcGFJOcACYssao2ppJcMB57IjF1NDg\nQC0iwQF7dOTkM0ML2IYEBzB9bIpFCJBvxdTQ4EAtIsEBe7AFDRiJBAcwfWyKRQhwRQVTQ4MD\nNae3X1uyJDhgiy1Z1depnZ/oAEkkOIAgJOPM4IDzSHBgamhwoOakPEkkOGCLdFZzWlTHzghA\nEgkOIAiJOFdU4DwSHJgaGhyoOamMZjYxtQi2SOc4oAC2I8EBTB9XVBACJDgwNTQ4UHMYwAGr\npLNK8vkNbEOCA5g+hozCdQMldfdxHompoMGBmsMKFViFBCYwEgkOYPq4ogLXpbPyGcGOKaHB\ngZpDggNWIYEJDCv56u4jwQFMVzKujpxKvuk6gKnqKO+Y4wEJk0eDAzWHBAesQoIDGNbVp5JP\nggOYrmRcgyV5BdN1AFOVzqm+Tu1NpuuAg2hwoLYMlPR6NwkOWIQEBzDMy0siwQFMV7lvzqZY\nuCud1dyYIuyYw+TR4EBt2dSpwRIJDliEBAcwrHzgTIIDmKZEXHURxnDAYTwdYcpocKC2pDw1\nRrXbTNN1AJKkoi8vT4IDGOLlVV+nGQ2m6wAcF41oVjObYuEw8q2YMhocqC2pjBa3K0rgDXbI\n5FX0OaMAhngFtTeTSQYCkGSRClxGggNTRoMDtYUVKrBK+YI0ZxRAWSbPAA4gGDQ44LSOnObS\n4MCU0OBAbUlltIwBHLBGOqe6iGYzcQCQJHl5BnAAwUjEGTIKh3FFBVNGgwO1ZT07YmGTdFaz\nW7gzBQzxCiQ4gGAk48zggMO4ooIpo8GBGuL7erWTKyqwCJ/fwEgkOICgJGJcUYHDSHBgymhw\noIa81avcAAkOWITPb2AkEhxAUBLM4ICzSr4yeU6AMEUuNTjy+fySJUt22223if7Addddt3Tp\n0qampr333vu2226rZm1wQspTRFrcbroOYBsSHMBIJDiAoCSZwQFnlXfMMWQUU+NSg+OLX/zi\n5s2bJ3r1hhtuuOCCC84888yHHnrohBNOOPnkk3/6059WszzYL5XRrjPVUm+6DmAbEhzASCQ4\ngKAk49qaV9E3XQcweeXxMTwgYWqc+VHvD3/4w3XXXXfyySfff//9Y1/1ff+qq65as2bNhRde\nKOnwww//4x//+OUvf/mYY46peqWwFztiYZt0Tu+ZY7oIwBokOICgJGIq+dqaU5KfEuGajpwi\n0hw+DjAlbiQ4SqXSGWeccdZZZ+23337j/oFXXnll06ZNH/vYx4a/8tGPfvTJJ5/s7u6uVo1w\nQIoVKrAMCQ5gJBIcQFDKfQ3GcMBF6axmtajejZ9TYR03/uJ861vf2rx58xVXXDHRH3j55Zcl\nLV26dPgr5V+/8sorVSgPriDBAdswgwMYVvLV3UeCAwjG7BbV17EpFk7i6QjT4cAVlbfeeuuS\nSy656aabZsyYMdGfKSc1Zs6cOfyV1tbW4a9P5Ctf+coPf/jDib7hwMDAFCuGrUhwwCq+r605\nEhzAkK4+lXwSHEAw6iKa00KCA04i3+qQgYGBc845Z+SP4SN94hOfuPjii6tckgMNjr/7u787\n7LDDPv7xjwf+nT/0oQ/V1Y2fYXn55ZdfffXVwN8RBnX3aWueBAcs4hU0UOKMAhji5SWR4AAC\nw6ZYOIoEh0Pq6uoOO+yw97znPeO+euihh1a5Htnf4LjvvvsefPDBP/zhD+/+x9rb2yV1dXW1\ntbWVv9LZ2Tn89Ykcfvjhhx9++LgvPfjgg3fcccdUKoat1mckkeCARRgSDozkFSSR4AACw6ZY\nOIoEh0Oi0ejf/M3frFy50nQh29k+g+M///M/e3t7ly5dWl9fX19ff/7557/xxhv19fXXXXfd\nyD+21157aceJGy+99FI0Gi1/HZCU8tTezKMzLJLOKiLWvANDvLyiEbU2mq4DCItknBkccFJH\njqcjTJ3tCY4rr7zy/PPPH/7t7bfffvPNN//iF79YsGDByD+2dOnSPffc88c//vFRRx1V/spP\nfvKTI444IhbjHweGpDJaRnwDNknn1N6sBtv7zECVeAW1NysSMV0HEBaJmN7oMV0EMHlcUcF0\n2N7g2HXXXXfdddfh386fP7++vn7//fcv/3bt2rV33nnnY489Jumyyy477bTTdtttt0MPPfTe\ne++97777fvnLX5opGlZihQpsQwITGMnLM4ADCFIirufeNl0EMHk8IGE6bG9wvLvXXnvtiSee\nKP/6pJNO6u3t/drXvnb55Zfvueeed91114c//GGj1cEuqYwO3d10EcAIHFAAI3kFzabBAQQn\nyZBRuKmDByRMg2PZ6PPOO2/z5s3Dv/3qV786ODg4/Nuzzz57w4YN/f39L7zwwic+8QkTBcJe\nJDhgGw4ogJG8PGOSgCDR4ICLuvvUV+QBCVPnWIMDmJq+ot7oZoUK7EKCAxjJK3BFBQhSIqbO\nggZKpusAJmNoxxwPSJgqGhyoCRs7VfRJcMAuJDiAkUhwAMFKxuWLTbFwTPlvLFtUMGU0OFAT\nUhk112uXVtN1ACOQ4ABGIsEBBKvcQ2dTLNySzmlGo5rdHhQJk2hwoCakPO3Rrjq2D8ImJDiA\nkUhwAMFqb1JjlDEccAwTRjFNNDhQE1IZBnDAOnyEAyOR4ACCFYlobowrKnAMxz+YJhocqAms\nUIFtGBIOjEKCAwgci1TgHC7wYppocKAmkOCAbRgSDoxU8tXdR4IDCFgyzgwOOIYEB6aJBgfC\nz/e1sZMEB+zCkHBgpO4+FX0SHEDAEjESHHAMCQ5MEw0OhN8bPcoPkuCAXdI5tTIkHNjGK0gi\nwQEELBlnBgcc05Hj+AfTQoMD4bc+o7qIFrebrgMYgQQmMJKXl0SCAwhYghkccA0PSJgmGhwI\nv5Sn3WeqKWq6DmAEEpjASF5B0YhaG03XAYQLV1TgHB6QME00OBB+TBiFhTigAEby8mpvViRi\nug4gXBgyCrcUBtXbzwMSpoUGB8KPHbGwEAcUwEhegQEcQPCScXX3KT9oug5g57BjDtNHgwPh\nR4IDFiLBAYzk5RnAAQSv/EHTQYgDjijPxOUBCdNBgwPht4EEB+xDggMYiQQHUAnJuCTGcMAZ\n6ZyaosxjwrTQ4EDIZfLyCiQ4YB0SHMBIJDiASmhtVEs9m2LhjHSWHbGYLhocCLmUJ0l7sCMW\nliHBAYxEggOoEDbFwiEdOY5/MF00OBByqYzmxtTOwSBskh1QboCPcGA7EhxAhbApFg7h+AfT\nR4MDIccKFVhoaIYWH+HANiQ4gAphUywcwgVeTB8NDoQcK1RgofKzZpKPcGCbDAkOoDKScWZw\nwBkkODB9NDgQciQ4YKF0VrEGxRpM1wFYw8uT4AAqghkccAgJDkwfDQ6EHAkOWIgDCmCkkq/u\nPhIcQEUwgwMOSefYooLposGBMCsM6q1eEhywDgcUwEjdfSr6JDiAimAGBxzSwQkQpo0GB8Js\ng6eST4ID1iHBAYzkFSSR4AAqIskVFThisKTOAidAmC4aHAizlKdYg+bzH0pYhgQHMJKXl0SC\nA6iIRFy5AWUHTNcB/Clb8yr5nABhumhwIMxSGS2ZpUjEdB3AjkhwACN5BUUjam00XQcQRuWN\nXYQ4YL/yuh9OgDBNNDgQZqxQgZ1IcAAjeXm1NauOZjRQAeUGB5tiYb90TtEI1xUxXTQ4EGas\nUIGdSHAAI3kFnmiBSmmp14xGEhxwQDqrOTGa3ZguGhwIMxIcsBMJDmAkL88ADqCC2BQLJ3D8\ng0DQ4EBolXxt6iTBAev0FdXTz0c4sB0JDqCi2BQLJ6SzmsvTEaaNBgdC6/Vu9RVJcMA6zNAC\nRiHBAVRUMs4MDjigI8fTEQJAgwOhlcooGtHCNtN1ADsqH6OR4ACGkeAAKioR54oKHMAVFQSC\nBgdCK+VpYZsao6brAHaUzqoxykZMYDsSHEBFcUUFTmBCGQJBgwOhxQoV2Kl8QBFhSDiwDQkO\noKIYMgonkOBAIGhwILRYoQI7cUABjEKCA6gorqjACTwgIRA0OBBaJDhgJw4ogFG8gmbT4AAq\npjxk1PdN1wFMzPe1Nc8WFQSABgdCiwQH7MQBBTCS76uLKypAJSXj6iuqu990HcDEOvs0WOIE\nCAGgwYFwSufU3adlJDhgHxIcwEjd/Sr6XFEBKqj8ocOmWNis/PeTEyBMHw0OhFMqI0l7kOCA\nfbaQ4ABG8PKSSHAAFZSMKyLGcMBq6Zwi0hya3Zg2GhwIp5SneXE2ccJG6SwJDmA7ryCJBAdQ\nQY1RzWxiUyysls6qrVmNUdN1wH00OBBOTBiFtdI5EhzAdl5e0Qj9aKCykixSgd24wIug0OBA\nODFhFHYaKKmroCQNDmAbr6C2ZtVFTNcBhBqbYmE5RrAjKDQ4EE4kOGCnjpx8cUYBbOflGcAB\nVFx5UyxgrY4cO2IRDBocCCcSHLATQ8KBUbwCAziAikvGmcEBq3FFBUGhwYEQyg3onV4SHLBR\nOqf6OrU3ma4DsAYJDqAKEjGuqMBqXFFBUGhwIIRSnnyR4ICN0lnNjSnCuAFgGxIcQBUwgwOW\nI8GBoNDgQAilMprRyBxH2IjPb2AUEhxAFTCDA5YjwYGg0OBACDGAA9bi8xsYhQQHUAXlGRy+\nb7oOYAIdnAAhIDQ4EEKsUIG1SHAAo5DgAKogEdNgSV7BdB3AeHr7lR9kiwqCQYMDIUSCA9Yi\nwQGMQoIDqILyvV3GcMBO5RU/PCAhEDQ4EEIkOGAtEhzAKCQ4gCp0RysqAAAgAElEQVSYG1Nd\nhE2xsFRHucHBAxKCQIMDYTNY0mtdJDhgKRIcwEi+r64+EhxAxdXXaVYzCQ5YKp1VrEGxBtN1\nIBRocCBsXuvSQIkEByxFggMYqadfgyUSHEA1sCkW1uLpCAGiwYGwSXmqr9PuM03XAYxR9OXl\nSXAA22XykkhwANXAplhYi3wrAkSDA2GTymhxu+r5qw37ZPIq+pxRANuVdzqQ4ACqoLwpFrAQ\nCQ4EiJ8CETasUIG1ykdnnFEAw7y86iKa2WS6DqAGJGJcUYGlOnI8HSEwNDgQNqxQgbXSOdVF\nNJs0PrCNV1Bbk+oipusAagBXVGCtdFZzSXAgIDQ4EDYkOGCtdFazWxTlZzlgGy/PAA6gShgy\nCmtxRQUBosGBsHnVI8EBS/H5DYziFRjAAVRJkgYHbMWQUQSIBgdC5Z2sevpJcMBSW/j8BnZE\nggOomkRsaNY1YBtOgBAgGhwIlVRGEWkPGhywUjrL5zewAxIcQNUk4yr62soiFVimv6iePk6A\nEBgaHAiVlKf5MxRvMF0HMJ40Q8KBHZHgAKqm/AHEpljYJp2TL4aMIjA0OBAqqYyWMYADtkpn\nlaTBAYxAggOomjktqq9jDAesU17uQ8QVQaHBgVBZz45YWIwrpsAoJDiAqinvKWdTLGzTkVND\nndqaTNeBsKDBgVBhRyxsxpBwYBQSHEA1sUgFFkrnNDemSMR0HQgLGhwIlRQJDtjK97U1T4ID\n2AEJDqCaknFmcMA6HP8gWDQ4EB69/UrnSHDAUl5BgyU+woHtfF9dfSQ4gOpJxEhwwDpc4EWw\naHAgPNZnJJHggKXKh2Z8hAPDevo1WCLBAVRPMs4MDliHBAeCRYMD4ZHyNLNJc3hWhpXSWUWk\nOTQ4gG28giQSHED1JJjBAfuQ4ECwaHAgPNgRC5ulc2pvVgP/0QW28fKSSHAA1cMVFVioI6e5\nNDgQHJ61ER6sUIHNSGACo3gF1UVYDQhUD0NGYSEekBAsGhwID1aowGYkMIFRvLzamlTHakCg\nWpJxeXkNlEzXAYzAAxKCRYMD4UGCAzbjgAIYxStwPwWoqkRcvtRBiAPWKPry8jwgIUg0OBAS\nAyW93kWCA/bigAIYxcszYRSoqmRcEmM4YJFMXkWfByQEiQYHQmJjp4o+CQ7YiwQHMAoJDqDK\n2pvUUMemWFik/LeRByQEiAYHQiKVUVNUu840XQcwARIcwCgkOIAqi0TYFAu7pHOqi2g2zW4E\nhwYHQiLlaXG7ogyrg61IcACjkOAAqo9NsbBKOqtZzTzAI0g0OBASrFCB5TpIcAA7IsEBVB+b\nYmGVjhzHPwgYDQ6EBCtUYLPuPvUV+QgHdkCCA6i+ZJwZHLAIF3gROBocCAkSHLBZ+biMj3Bg\nJBIcQPUxgwNW4QIvAkeDA2Hg+3q1kwQH7FU+LptLgwMYgQQHUH3M4IBVSHAgcDQ4EAZv9So3\nQIID9tqSVWujmutN1wFYw/fVWSDBAVQbMzhgFRIcCBwNDoRBylNEWtxuug5gAmlmaAE76h3Q\nYIkEB1BtSa6owCYdOfKtCBgNDoRBKqNdZ6qF43HYKp0lgQnswMtLIsEBVFsiru4+FQZN1wFI\n4ooKKoAGB8KAFSqwXDqnJAkOYASvIIkEB1Bt5Q8jbqnAEqyJReBocCAMWKECy3HFFBjFy6su\noplNpusAakz5tJxNsbBBV5/6iyQ4EDAaHAgDEhywHAlMYBSvoJlNikZM1wHUmJlNaqlnDAes\nUG60cQKEYNHgQBiQ4IDlSHAAo3h5BnAAZsxlUyzsUL4qxZBRBIsGB5zXWdDWPAkOWI0EBzCK\nV2AAB2AGm2JhiXRWM5vUFDVdB8KFBgecl/IkkeCA1ZihBYxCggMwJRlnBgeskGZHLCqABgec\nl8podgsPyrBXdkC5ARIcwA4yeRIcgBmJOFdUYIUO8q2oABoccB4TRmE5ZmgBY3kFGtOAGVxR\ngSWYUIZKoMEB5zFhFJYrP0dyRgGM5JHgAAxJMGQUdmBCGSqBBgecR4IDlktnFWtQrMF0HYBN\nSHAApnBFBZYgwYFKoMEB55HggOU4oADGIsEBmJKkwQE78ICESqDBAbf1FfVGDwkOWI0DCmAs\nEhyAKcm4cgPKDpiuAzUvnWWLCoJHgwNue9VTySfBAatxQAGM1VUgwQGYUf5IYlMsjOvIcQKE\n4NHggNtSnprrtWCG6TqAiZHgAEbp6ddAiQQHYEYyLolbKjAsP6jsACdACB4NDrgtldGSWaqL\nmK4DmBgJDmAULy+JBAdgRqxB8QY2xcKwcoaIEyAEjgYH3MYKFdiPBAcwileQRIIDMIY5ozCu\n3GLjBAiBo8EBt7FCBfYjwQGM4uUVkdpocACGsCkWxqWzaq7XjEbTdSB0aHDAbSQ4YD8SHMAo\nXkEzmxTldiFgSDLOkFEYxvEPKoQGBxxW8rWxkwQHrFYYVE8/H+HADrw8AzgAk5JxZnDAMI5/\nUCE0OOCwN3pUGCTBAasNXTHlIxwYwSswgAMwKRHjigoM68hpLsc/qAAaHHBYKqO6iBa1m64D\nmNjQkHA+woERSHAAZjGDA8ZxRQUVQoMDDkt52n2mmqKm6wAmls6pKaqZTabrAGziFTSbBgdg\nDjM4YBxXVFAhNDjgMFaowH58fgNjeXmuqAAmsSYWxpHgQIXQ4IDDWKEC+/H5DYzlFbiiApiU\niKmvqO4+03WghnEChAqhwQGHkeCA/fj8BsYiwQGYlYxLIsQBkzgBQoXQ4IDDNpDggPX4/AbG\nIsEBmJWIKyI2xcKYgZK6CmxRQUXQ4ICrMnl5BRIcsB0JDmAsEhyAWeXp1yQ4YMrWnHzxgISK\noMEBV6U8SVpCggN2I8EBjNVJggMwjU2xMKicHuIBCZVAgwOuSmU0N6Y2tm/CbiQ4gFF6+zVQ\nIsEBGMamWBiUzioaUTsfBKgAGhxwFStU4AQSHMAoXkESCQ7AsGScGRwwJp3T3JjqIqbrQBjR\n4ICrWKEC+5VnaJHgAEby8pJIcACGJWJcUYEx5FtROTQ44Kr1GS2jwQG7dZRnaJHgAEbwCopI\nbTQ4AKO4ogKDyLeicmhwwFVcUYH9ys+OnFEAI3l5zWxSlGQyYBRDRmFQR44dsagUGhxwUn5Q\nb/VwRQW2S+dUX6d2RuECI3isUAEskKTBAXO4ooLKocEBJ23w5IsEB2yXzmpuTBFOqoERvDwD\nOADzEjGlc/J903WgJnFFBZVDgwNOSmUUa9A8Wr+wG5/fwFgkOAAbJOMaLA1tNQKqjAQHKocG\nB5xUHsDBwTgsx+c3MBYJDsAG5Y8nNsXCCE6AUDk0OOAkdsTCCXx+A2OR4ABskIipLsIYDhjg\n+8rkOQFCpdDggJNYoQInkOAAxiLBAdigvk7tzWyKhQGZggZLbFFBpdDggJNIcMAJJDiAsUhw\nAJZgkQqMKLfVeEBChdDggHuKvjZ1keCAA0hwAGOR4AAsQYMDRnTkFJHm0OBAZdDggHte71J/\nkQQHHLAlywEFMFomT4IDsEJ5UyxQZemc2pvVwI+hqAz+ZsE9KU/1dVrYZroO4F0VfXkFEhzA\naF19JDgAKyTjzOCAAeRbUVE0OOCeVEYL2+j7wnZbcyr5JDiAHfT2q79IggOwQoIrKjCBCWWo\nKH5GhHtYoQInlHO/Sc4ogBG8giQSHIAVEjEaHDCABAcqigYH3MMKFTghnVU0wkk1sAMvL4l/\nF4AVknFmcMCADhIcqCQaHHAPCQ44IZ3T7BZFI6brAGziFRSR2ppM1wFASsa1Naeib7oO1Jh0\nTnNpcKBiaHDAPRs8EhxwAAlMYCwvr9Ym1fP0AVggEVfRVyZvug7UGB6QUFE8YsAx6Zy6+0hw\nwAHM0ALG8goM4ABsUZ4SxRgOVBkPSKgoGhxwTCojSXvQ4ID1OKAAxvLyDOAAbDGnRdEIm2JR\nbR05HpBQQTQ44JiUp3lxtTaargP4UzigAMYiwQHYoy6iOSxSQXX19KswyAMSKogGBxzDChW4\nggQHMBYJDsAqbIpFlZUTQwwZReXQ4IBjWKECV5DgAMYiwQFYhU2xqLLy3zcaHKgcGhxwDAkO\nuIIEBzAWCQ7AKsk4MzhQVR05xRsUazBdB8KLBgccQ4IDTvB9bc2T4ABGI8EBWCUR54oKqorj\nH1QaDQ64JDegd3pJcMABXkGDJT7CgdFIcABWScS4ooKq4gIvKo0GB1yS8uSLBAccUH5e5CMc\nGIUEB2CVJAkOVBcJDlQaDQ64ZH1GMxqV5D+LsF46q4g0hwYHsKPOAgkOwCI0OFBlJDhQaTQ4\n4JJURsu4nwIXpHNqb1YD/4kFRsgOqL+o2TQ4AGsk4vLyGiiZrgM1gwQHKo2nb7iECaNwBZ/f\nwFheXhJXVACLJOPypQ7GcKBaOnLsiEVl0eCAS9gRC1eQwATG8gqSuKICWKT8UcWmWFQND0io\nNBoccAkJDriCBAcwlpdXRGprMl0HgG1mNauhjjEcqB4ekFBpNDjgjMGSXu8iwQE3cEABjOUV\n1Nqkeh49AGtEIpobo8GBKukrqqefByRUFk8ZcMamLg2USHDADVs4oADG8PIM4ACsk4wPrTYH\nKq18GYoHJFQUDQ44I5VRQ512bzNdB7AT0lkOKIDRPHbEAvZJxpnBgSopt9J4QEJF0eCAM1Ke\nFrcrGjFdB7AT0jkOKIDRSHAAFkrEuaKCKkln1RhVa6PpOhBqNDjgDFaowCFbc0rS4AB2RIID\nsBBXVFA16ZzmxhThtBKVRIMDzmCFClzR1ae+IglMYDQSHICFEgwZRbV0MIIdlUeDA84gwQFX\nMEMLGBcJDsBCXFFB1bAjFlVAgwPOeLWTBAfcUM76zuWMAtgRCQ7AQgwZRdWkSXCg8mhwwA1v\n96q3nwQH3JDOamaTmqKm6wAsQ4IDsFAyrq4+FQZN14EaQIIDVUCDA25IeYpIe7SbrgPYCRxQ\nAOMiwQFYqPyB1cGcUVQeD0ioAhoccEMqowWtijWYrgPYCRxQAOPqJMEB2Ke884sxHKiCjhwX\neFFxNDjgBlaowCEcUABj5QbUVyTBAVhnZpOa69kUi2rgBAhVQIMDbmCFChzC5zcwlleQRIID\nsBGbYlEFRV9egRMgVBwNDriBBAccQoIDGMvLSyLBAdiITbGogq05lXxOgFBxNDjgBhIccAgJ\nDmCsTF4RqZ0GB2AfNsWiCsrXoDgBQqXR4IADevqVzpHggDNIcABjeQXNaFQ9zx2AfZJxZnCg\n4tJZRSNcVETF8aABB6QykkhwwBkdORIcwGhenudawFLM4EAVpHOa3aJoxHQdCDsaHHBAylNb\nk+bwZAwXZAeUGyDBAYzmFRjAAViKGRyognSWHbGoBhoccAADOOCQ8jVmEhzAKCQ4AGsxgwNV\nQL4V1UGDAw5ghQocwgwtYFwkOABrJUlwoPKYUIbqoMEBB5DggEPSWcUaFGswXQdgGRIcgLUS\nsaH7lUDlsGMO1UGDAw4gwQGHcEABjIsEB2CtZFwSIQ5UFg9IqA4aHLBdf1Gvd2kZCQ44YgsH\nFMB4SHAA1io3ONgUi4oiwYHqoMEB223sVNHnigqckc5yQAGMgwQHYK1Yg+INJDhQWekcW1RQ\nDTQ4YLuUp6aodm01XQewc9IMCQfGQ4IDsBmbYlFRvq+tXFFBVdDggO1SGe0xS3UR03UAOyed\nHcr6AhipkwQHYDE2xaKiuvo0UOIECNVAgwO2Y8Io3MIMLWCs3ID6iiQ4AHsl48zgQAWV/3bx\ngIQqoMEB27EjFm5hhhYwlleQRIIDsFcixhUVVFA5H8QMDlQBDQ7YjgQH3EKCAxjLy0siwQHY\niysqqKh0Tm1NaoyargM1gAYHrOb72thJggPOKAyqt58EBzBaOcHRToIDsBVDRlFR5FtRNTQ4\nYLU3e5UbIMEBZ3DFFBiXl1droxp46ABsxRUVVBT5VlQNzxqwWiqjuogWt5uuA9g55XwvZxTA\nKF6B+ymA1RgyiorqyDGAA1VCgwNWS3natVXN9abrAHZOOqemqFobTdcBWMbLM2EUsFoyrsKg\nuvtM14GQ4ooKqoYGB6zGChW4hc9vYFwkOADLlT+8CHGgQriigqqhwQGrsUIFbuHzGxgXCQ7A\ncsm4JMZwoFI4AULV0OCA1UhwwC18fgPjIsEBWK4pqplNbIpFpXAChKqhwQGrkeCAW/j8BsZF\nggOwX5JNsaiYjhwnQKgSGhywV2dBmTwJDriEBAcwLhIcgP1ocKBCsgPKDbBFBVVCgwP2SnmS\ntIQEB9xBggMYFwkOwH6JGENGUREdOUk8IKFKaHDAXqmMZrfwTAyXkOAAxkWCA7BfMs4MDlRE\n+e8VD0iojnrTBVis5Hu33zP8u/rE7NaVhw29ks13/2ydPzjIqxV99fW385d0rPNut6uqWns1\nVhedn8lu/7dQF2k96oP18+aWf5f9zbP9qdeG/4e8euJLr723JO9Fu6ri1UBeba6LjvxQaNht\n/owPH1z+ddHr6n7gERVLvDrRq52Fg8vdaquq4tUpvNpcF028sXX7v4Vo3cyPHB6d1Vb+Xe/D\nvx3Y/Pbw/5BX3Xo1EVf9E7/1brerKmtfnRmtH/mh0Lh0YfzQA8u/Hnyno+eXj6vk82r5Vf34\n8Uu3+P0/UL9NVfFqIK9aiAbHu/D7N2x/0i1297Zu+3Upl+9LbVKxyKsVffXNd/IrC5v6N9hV\nVa292hipa+kb3P5vIRIpvv+A4R/5Bl5/a+Q/kxp/te+1t97T+1rbO+rvsqgqXg3q1WgkMvJV\nf3BQ2vYDYU+2f/1r8ku8Ou6rA/2DhcGDywkOe6ri1am9Wh+pa84VRnwo1BV7ssM/8vVv3Dzw\n2pvD/0NedevVREzRjs39g3ZVZe2rDZG6kR8KkcYGbfuRr9jV0596Tb7Pq+VX6ze9dmCf37/B\nrqp4NZBXLRTxR9SKYQ8++ODHPvaxQqFgupCaduQt+tDuuvL/M11HbYvFYh/5yEd+9KMfmS7E\nAW/1apdr9NJn9Z45pktB0M4+++wbbrhhcETQCTvvzR7t+nX+aYREfX39GWecsXbtWtOFIHh3\n/kEXPqQ3Pme6Dhcce+yxDzzwQC7HzJKdcs1v9L0/6OkzTNeBCmhubr7nnntWrlxpupDtmMEB\ne6UyrFCBS7hiCozLK0hiBgdgu/IMDo4+ETgmlKGaaHDAUn1FvdGjpaxQgTu2ZFVfp/Ym03UA\nlvHyktTGPw3Abom4Bkrq7DNdB0KnI8eOWFQPDQ5Y6lVPJZ8EB1ySzmluTJGI6ToAy3gFzWhU\nY9R0HQDeVTIuSVtYpIKgpXPsiEX10OCApVKemuu1YIbpOoCdls7y+Q2Mw8uz8BtwQCKmiNgU\ni+BxRQXVRIMDllqf0ZJZquMwHO5I54aOvwCM5BUYwAE4oL5Os1pIcCB4JDhQTTQ4YKlURsu4\nnwKncEABjIsEB+CKRIwGB4LHAxKqiQYHLJXymDAKx3BAAYyLBAfgimRcaTafIlADJXX38YCE\n6qHBAUuxIxbO4YACGFeGBAfgiPKmWCBA6ax8sUUF1UODAzYq+drYSYIDjiHBAYzLy5PgANyQ\niHNFBQErZ4I4AULV0OCAjTZ3q69IggOOIcEBjMsrkOAA3MAVFQSuI6f6OrU3ma4DNYMGB2yU\n8hSNaFGb6TqAnVb05RVIcADjIMEBuIIhowhcOqu5MUVYjIhqocEBG6Uy2r1NjVHTdQA7bWtO\nJZ8EBzAOEhyAK5JcUUHQuMCLKqPBARuxQgXOGbpiykc4MEYnW1QARyTi2ppT0TddB0KEC7yo\nMhocsBErVOCcdFbRCD/FAaPlB1UYJMEBuCEZV9FXJm+6DoQICQ5UGQ0O2IgEB5yTzml2i6Jc\nMQV25OUl0fsD3FD+QZRNsQhQR44EB6qKBgdstMEjwQHHkMAExuUVJJHgANwwJ6ZohDEcCFJ5\nyChQNfUBfq+NGzeuX7++o6Ojq6urra1t7ty5y5YtW7x4cYBvgVqwNa/OAgkOOIYEJjCucoKj\nnQYH4IJoRLNbaHAgSDwgocoCaHBs2LDh2muvvf/++9evXz/21WXLlq1ateq8887bY489pv9e\nqAWpjCQtocEBp5DgAMblFRRvYCsW4IxkfGhsNhAIHpBQZdNqcKTT6YsuuujWW28dHBxMJpPH\nH3/8nnvumUwm29vbOzs7t2zZ8sorr6xbt+66665bu3btSSed9NWvfjWRSARVOsIq5SkR08wm\n03UAk8EBBTAuL88ADsAlyTgzOBCYkq9MngckVNXUGxwPP/zw8ccfv3Xr1hNOOOFzn/vcgQce\nGImMM17P9/1nn33261//+i233HLvvffeddddRxxxxDQKRvixQgUuSme191zTRQD28QoM4ABc\nkohzRQWByeRV9ElwoKqmPmR0xYoVe++990svvXT77bcvX7583O6GpEgksnz58ttvv/1//ud/\n9t5776OPPnrK74gawQoVuIgEBzAuEhyAW7iiggCV/y4xZBTVNPUGx0UXXbRu3bqlS5fu5J9f\ntmzZunXrLrrooim/I2oECQ64iCumwLhIcABuScRIcCAw6awi0hza3KiiqTc4rrjiimh09NCw\nnp6eF154obOzc9z/STQaveKKK6b8jqgRJDjgHN/XVq6YAuMhwQG4hSsqCFBHTrNaVD/1nziB\nSQvsr9uvf/3r97///TNnztx///2feOKJ8hePOeaYX/7yl0G9BWpBflBv9ZDggGMyBQ2WSHAA\n4/AKmk2DA3AHQ0YRIC7wovqCaXA8+eSTK1asePnll1euXDn8xXQ6/dRTT61ateqZZ54J5F1Q\nCzZ48kWCA44pPwvyEQ6M5eW5ogK4JBlXJq+Bkuk6EApc4EX1BdPguOKKK+bPn//iiy/efPPN\nw19MJBK///3v58+f/6UvfSmQd0EtSGUUa9A8/lMIp6RzikhzaHAAY3gFrqgALknE5EtbmTOK\nIJDgQPUF0+B44oknzjrrrN12223U15PJ5JlnnvnII48E8i6oBeUBHBPs5AEslc5qVosauGIK\njEGCA3BLMi6JMRwIBgkOVF8wz+NdXV277777uC8tWLCgt7c3kHdBLWCFClzEAQUwERIcgFtm\nNauhjk2xCAYPSKi+YBoc8+fP/+Mf/zjuS4888sguu+wSyLugFrBCBS7igAIYV2FQhUESHIBL\nIhHNZVMsAtKR01waHKiuYBocq1atWrt27e9+97uRX/Q879JLL73ppptWr14dyLugFpDggIs4\noADG5RUkkeAAHMOmWASFEyBUXzANjn/6p3+aMWPGwQcfXO5lXHzxxQceeOCCBQuuuuqqhQsX\nXn755YG8C0Kv6GtTFwkOuIfPb2BcXl4SCQ7AMWyKRVA6OAFC1QV2ReXpp58+/fTTN23aJOm5\n55577rnnWltbzzrrrKeeemrevHmBvAtC77Uu9RdJcMA9JDiAcZUTHG00OACnJOPM4EAAuvvU\nV+QECNVWH9Q3SiaTa9eu/eY3v7lly5aenp7W1lb6GpisVEb1dVrYZroOYJJIcADj8vKKN6gp\naroOAJORiGlTl+ki4L5ym4wTIFRZYA0OSS+88MK8bcq/7e/vP/DAAwN8C4RbytOiNnZtwj0k\nOIBxsUIFcFEirqfeNF0E3Fe+6MSQUVRZMD9KDgwMnHbaafvvv//zzz8//MVf/epXy5cv/9u/\n/dtisRjIuyD0mDAKR3XkSHAA4/DyDOAA3MMMDgQinVNro5qDPE8H/rRgGhzf+MY3vvvd765e\nvXrRokXDXzz66KOPP/74m2+++frrrw/kXRB67IiFi7r61F8kwQGMgwQH4KIkW1QQhHSW+AYM\nCKbBcfPNN//VX/3Vvffeu8ceewx/ca+99vr+97+/atUqGhzYSSQ44KLyMRcJDmAsEhyAixIx\ndfWpjwQ2pod8K4wIpsGxfv36I488ctyXPvzhD5dXqwB/0qudJDjgnvIMLc4ogLFIcAAuSsYl\ncUsF08WEMhgRTINj5syZGzduHPeljRs3zp7NoTz+tC1ZdfeR4IB70lnNbGJPBDAOEhyAi8qn\n7myKxTSxYw5GBNPgWL169Y033njfffeN/OLAwMB3vvOdG264YcWKFYG8C8It5UnSHu2m6wAm\niQMKYCIkOAAXtTWpuZ4xHJguHpBgRDBjba+88sr7779/9erVCxcu3GuvvZqamjo7O1988cVM\nJrNgwYIrr7wykHdBuKUymj9DMxpN1wFMEgcUwERIcACOmhujwYHpSmeVWGy6CNSeYBIcCxYs\nePbZZ88888xsNvvQQw/de++9jz32WDQaPf3005966qmFCxcG8i4IN1aowFEcUAATIcEBOIpN\nsZi+jhwTymBAYIuJ582b9+///u9r165966238vn8/Pnz43HONDEJrFCBo0hwABMhwQE4Khln\nBgemixMgGBFYg6MsEonssssuwX5P1IiUp5VLTRcBTF46p/fOM10EYJ/CoPKDJDgAJyW4ooLp\nKQyqt58TIBgQTIPD9/2777771ltv3bx588DAwNg/8PzzzwfyRgixVEZL/9x0EcDkkeAAxuUV\nJJHgAJyUjOvlraaLgMvKCSASHKi+YBoc11xzzYUXXigpFos1NDQE8j1RU3r7tSXLDA44iQQm\nMC4vL4kEB+CkRFyPvWa6CLisPMOFEyBUXzANjn/7t39buXLl2rVrlyxZEsg3RK3Z4MkXMzjg\nJBIcwLjKCY52EhyAg7iigmlK59QUVSvrEVF1wTQ43nnnnbvvvpvuBqYs5am1kWNwuKe3X/lB\n/uoC4/DyijWoKWq6DgCTx5BRTBPHPzAlmDWx8+bN830/kG+F2sQKFThq6IopH+HAGF6BARyA\nq5Jx9fYrN85gPWCnpNkRC0OCaXCceOKJt912WyDfCrUp5TGAA04aumLKRzgwhpdnAAfgqnLj\nnhAHpqyDCWUwJJgrKpdffvlxxx33qU996qSTTlq4cOHYOaPLli0L5I0QVqmMDlxgughg8tI5\nxRsUY7YyMAYJDsBd8+KStCWrRW2mS4GbuKICU4JpcLS2tuy54ecAACAASURBVJZ/ceedd477\nB7jAgneX8nTcvqaLACaPz29gIiQ4AHfFGhRrGEopAlOQztEdgxnBNDhOPPHExsbG+vpgvhtq\nzWBJr3cxgwNOYkcsMBESHIDTknEWqWDq0lm9fxfTRaAmBdOSmCi4ISmbzfb09ATyLgirTV0a\nKDGDA04iwQFMxMvTuQYcRoMD08EJEEwJZsjou7jnnnuWL19e6XeB01IZNdRpd2JscBCf38BE\nSHAATkvEGDKKqUtn2aICMwK7VNLR0fH9739/48aNg4ODw18sFAr33ntvb29vUO+CUEp5Wtyu\naMR0HcDkpbPaJ2G6CMBKzOAAnJaMM4MDUzRYUmeBiCvMCKbBsXHjxg984APpdHqcN6iv//zn\nPx/IuyCsUhlizHBVOqfDOaAAxkOCA3BaIq4/vGO6CLhpa16+iLjCjGAaHJdddlmhULj++uv3\n2Wefo4466j/+4z922223hx9++LbbbrvxxhtXrlwZyLsgrFKeltHggJuYwQFMhAQH4LREjBkc\nmKJy9ocHJBgRTIPj0UcfXbNmzZo1awqFgqT99tvvkEMOWbly5fHHH3/UUUf99Kc//dCHPhTI\nGyGU1md0xCLTRQBTwgwOYFx9ReUHSXAADkvGmcGBKUrnFI3wEQAzghky+tZbby1ZskRSXV2d\npP7+/vLX3/e+961Zs+YLX/hCIO+CUPJ9vepxRQVOKgyqt58DCmAcXl6SZpPgAJzFFhVMWTqr\nOTHVMV8PJgTT4GhtbX3nnXckNTY2zpgxY8OGDcMv7bvvvk8//XQg74JQejur7AA7YuGk8tEW\nCQ5gLK8giSsqgMMScRUG1dNvug44iHwrDAqmwXHYYYd961vfevjhhyUdcMAB3/zmN4c3p6xb\nt66pqSmQd0EopTKKSIvbTdcBTB5XTIGJlBMc7eSTAWcl45IIcWAqmFAGg4JpcFxyySVbt269\n4IILJJ1++ulPP/30vvvue+yxxx544IHf+c53jj766EDeBaGU8rRLq2INpusAJi+dU1NUrY2m\n6wDs4xUUa1BT1HQdAKaq3OBgUyymoCOnuSQ4YEgwQ0Y/8IEPPPbYY08++aSkU0455ZVXXrn2\n2mt//OMfRyKRY4455tprrw3kXRBK7IiFuzigACbi5RkvB7itKaqZTSQ4MBVcUYFBwTQ4JB10\n0EEHHXSQpEgkctVVV11++eVvv/32vHnzWlq4gIt3k/IYwAFX8fkNTMQrMIADcB6bYjE16az2\nnmu6CNSqYK6oPPbYY5lMZuRXmpubFy9e3NLS8uSTT/7whz8M5F0QSiQ44C4SHMBESHAAIcCm\nWEwNJ0AwKLAho4888si4Lz366KOnn356IO+CUCLBAXfx+Q1MhAQHEALJODM4MBWcAMGgaV1R\nWb9+/fr168u/fvbZZ5ubRx/W5PP5u+66q6+vbzrvghDr7lNHjgQHXLUlqyW054DxkOAAQiAR\n54oKJs33tTXPCRCMmVaD4+6777744ovLv77iiism+mPHHXfcdN4FIZbyJJHggKvSWR28q+ki\nACt5Bdp/gPOScT39puki4BqvoMESW1RgzLQaHBdddNHJJ5/81FNPfexjH/v0pz+97777jvoD\n0Wh0yZIlxxxzzHTeBSGWyqi9WbOJMcNN6RwJTGB8Xl6zFpguAsD0MGQUU9CRk8QDEoyZ7haV\nBQsWHHPMMatXrz777LMPOeSQQGoaJZ/Pf/GLX/z+97//9ttvL1iw4Mwzz7zgggvq60dXns/n\nv/zlL//gBz948803Fy1adMopp3zuc58b+8dgFQZwwGnprJJ8fgPjYQYHEAJJrqhg8tI5RaQ5\nfATAkGB+/r/33nslFYvFaDRa/kpfX99zzz3X2Nj4vve9LxKJTOebn3rqqevWrfvKV76y5557\nPvroo5deeunAwMDnP//5UX/s3HPP/dnPfnbjjTfus88+v/3tb0877bRCoXD55ZdP561RaaxQ\ngbsGSuru44opMD5mcAAhkIgrnZXva3rP8qgt6azamtUYNV0HalUwW1SKxeKaNWtOOOGE8m83\nbty47777HnLIIcuXLz/88MN7e3un/J07OzsfeOCBq6+++tRTTz3ssMMuueSSY4899kc/+tGo\nP1Yqle68885zzjln1apVe+yxxwknnHD88cffcccdU/8/CVVBggPuSmflk8AEJkCCAwiBZFwD\nJXWyLQCTwY45mBVMg+Pqq69eu3btwoULy79ds2bNq6++etZZZ5199tmPP/749ddfP+Xv3N7e\n7nneSSedNPyV+vr6sRdPIpGI7/sNDQ3DX2lubp5mcgRVQIID7kqXr5jyEQ6M0V9UboAEB+C8\n8mccm2IxKeyIhVnBXFG54447jj322GuuuUbSG2+8cf/995966qlr166VVCgUfvCDH1x00UXT\nfIt8Pt/V1XXPPffcc8893/3ud0e9GolEzjjjjG9961urVq3ab7/9nnnmmZEbXiZSKpW6urrG\nfWk6qRPspP6iNneT4ICr0lk11KmtyXQdgH28giQSHIDzEnFFpC1ZvWeO6VLgDhIctaa3t9fz\nvHFfamtrq6sLJlGx84JpcGzcuPGzn/1s+dcPPvig7/snnnhi+bcHHXTQ2BslU/CXf/mXv/71\nr2fNmnXjjTcO34UZ6Wtf+9qWLVv233//hoaGgYGB888//+///u/f/Xueeuqpt9xyy0SvEgCp\ntI2dKvokOOCqdE5zY1xLBsbh5SWR4ACc11Cn9uahxCKwkzpy7IitIf39/ccdd9xEr5588sk3\n33xzFcuRgmpwjOwF/OIXv4jH44cddlj5t77vDwwMTP8tvvGNb7z11lvr1q075ZRTOjs7zzrr\nrFF/4NJLL123bt33vve9ffbZ59lnn73wwgsTicQ//uM/vsv3vPrqq88555xxX/rNb35z/vnn\nT79svIuUp6aodm01XQcwJSQwgYmUExztNDgA97FIBZOVzupA1oTXjIaGhmuuuebQQw8d99Xh\nERbVFEyDY9GiRY888shnPvOZd95552c/+9mKFSsaGxvLL/3+97/fbbfdpv8WBxxwwAEHHLBi\nxYrW1tbzzz//pJNOise3/2zx2muvXX311bfddls53PHe9763t7f3ggsuWLNmzYwZMyb6nolE\nIpFIjPtSR0cHCY5KS2W0xyzV8f9muIkEJjARL6+WejWzqB1wHw0OTBYPSDUlEonsueeeBx10\nkOlCtgvmSswnP/nJO++884Mf/ODy5ct7e3vPPffc8tdvvfXWW2655Zhjjpnyd37jjTduu+22\nkRMx3vve9+bz+ddff33kH/v/2bv7MMnPsk70d3X3dM90zVsm05WEJOSFYYNwWJAAiwHhgCER\nvcCX9aioG9AsngtRPJhLhOOKoHII1+HKEgngvnBwZU8WDytcUREQibgGFnMCWcGjQVIhJIS8\nVKd+0zPTVdWvdf6oMYSku6qmu3p+9Xt+n89fTc+Qei4yzPP0/Xyf+77zzjvX19ef+tSnPvKd\nI0eOLC0tPea3MVaMUKHQJDhgM822BhyQiN6kWBieAxL5Gk2B4w1veMOrX/3q//E//sfi4uLv\n/u7vvuhFL+p9/01vetMll1wysNlnHw888MBVV1110003PfKdL33pSxMTExdccMGjf9v5558f\nEXfccccj3+l9PZLwCDvECBUKzQUFbCbraMABiahV9eDg1Mw7IJGr0eRHd+/e/cEPfvCDH/zg\nY77/0Y9+9NnPfvbjp7oO79JLL73iiite//rXHz9+/GlPe9ptt932zne+8+qrr96zZ09EvO99\n77vxxhtvueWWJz/5yVdeeeWb3vSm/fv3P+UpT/nyl7/8jne846qrrtq3T4OH8VXP4vKL814E\nbFVjMZ55dt6LgLGUSXBAKuZm4x8fznsRFMeJ5WivSnCQp62XHh544IGZmZkzzjij9/WGv+fC\nCy+cn5+PiLPP3vrPAX/0R3/0lre85W1ve1uz2bzggguuueaaRyIh99xzzxe+8IXe13/4h3/4\nlre85ed+7ucefvjhs84666d+6qd+53d+Z8sfyk7rduPrmQQHBSbBAZuR4IBkzOnBwano5X1M\nUSFHWy9wnHPOOVdeeeUnP/nJ3tf9f3O3293yB+3du/e666677rrrHv9L11577bXXXtv7+sCB\nA9dff/3111+/5Q/idPrWiWiv6sFBgXliCpuR4IBk1PTg4FT0/rS4ASJHWy9w/MRP/MQzn/nM\nR74e0XooizubMVGJCw/mvQ7YkrVuZB37N2ws68RF/nqHJNSqMd+K9a6xdwxlvhWzu2J2V97r\noMS2XuD48Ic/vOHXMIx6M87bb4ggRfVwK9a7EhywsawdzxqQ7ASKYW421rrRbHt0wFA84CV3\nI/v58mtf+9oXvvCFhx56aGpq6txzz33hC19Yq9VG9Q8nPWbEUmi9J6a2cNiQHhyQjFo1IuKh\nRQUOhuIBL7kbQYHj1ltv/eVf/uVHmn32VCqVV7ziFe9617uOHDmy/Y8gPWbEUmiNxZis6DIA\nG9ODA5Jx5mxMVkyKZVgSHORuuwWOT33qUz/8wz/c6XSe9axnXXnlleeee+7Kysqdd9758Y9/\n/KabbvrsZz/7iU984nu+53tGslZSUs/iX35X3ouArWq04tCemPQgGTYiwQHJmKzEoT0GqTAs\nCQ5yt60Cx9GjR6+66qqJiYmPfOQjP/ZjP/boX7r++ut/7/d+7w1veMOP/MiPfPWrXz1w4MD2\n1klqJDgotIfs37CJ5bVorUhwQDpMimV48634Z2fmvQjKbWI7/+Xf//3ff+ihh2644YbHVDci\nYnJy8nWve92//bf/9sEHH3zf+963nU8hPUc7kXX04KDAGosSmLCxrBMREhyQDpNiGV6jpV0L\nOdtWgePjH//4eeed96pXvWqz3/Da1772iU984k033bSdTyE9dzYjIi5W4KCwGi0JDthY1o4I\nCQ5IR62qBwfD8kSF3G2rwPGVr3zle7/3eycmNv2HTExMvPjFL77jjju28ymkp57FmXvioPs9\nCquxeLKxPPAYEhyQmLlZT1QYliaj5G5bBY5ms3nOOQMm3ddqtYWFhe18CunRgIOis3/DZrJ2\n7J6K3SMbQw/kTA8OhrS8FseXJDjI2bYKHCsrK7t27RrwAZvnOyiteqYBB8UmgQmbMUIFEqMH\nB0NqtKIbboDImeoDOZDgoOgkOGAzWTsOacABCalJcDCcXiFMk1Hytd0I6S233PLWt761/2/Y\n5keQnnoWr35m3ouArep2o9mW4ICNZR0dRiEpc7PRbMfqeky5GKWvRit2TcSBmbzXQbltt8Dx\nuc997nOf+9xIlkJJdFbjW8clOCiwZidW1yU4YGNZ2xMVSEqtGt2I+VacvTfvpTDe5ltxeDYq\nlbzXQbltq8DxoQ99aFTroDy+fjTWu3pwUGC9BKYEB2xIggMS09vvGgocDKJDGeNgWwWOn/mZ\nnxnVOiiPejP2TMU59kgKq9GKSsSZfoSDjWTtuPBg3osARufQ7tg1oQ0Hg+lQxjjY+lu6L37x\ni6ftv0VK6llcfIb0GgXWWIwz9niKDBuT4IDEVCpx5qwCB4NJcDAOtn5Cv+yyy97znvec0n/l\nPe95z2WXXbblTyQNRqhQdC4ooA89OCA9JsUyDAckxsHWCxw///M///rXv/6yyy77xCc+MfA3\nf+ITn7jssste//rXv+Y1r9nyJ5KGeqYBB8XmggL6kOCA9NSq0WjlvQjGXmPRjFjyt/UeHL04\nxi/90i/9wA/8wHd913ddccUVL37xi48cOXL48OEDBw4sLCzMz8/feeedf/mXf/nnf/7n//AP\n/3DmmWfeeOONr3zlK0e4eoqo3owfeHLei4BtcEEBfUhwQHrmPFFhCPMtN0Dkb1tNRl/5yle+\n/OUvv+GGG9797ndff/31119//Ya/7eyzz7722mtf97rX7d2rsWTZrXfj7qMSHBSbBAdsZnkt\nFlckOCA1tWrcs5D3Ihh7boAYB9sqcETE3r173/SmN73xjW/84he/+JnPfOZrX/va/Pz8sWPH\n9u/ff/jw4Sc/+cmXX375s571rIkJ7fiIiPjmsVha04ODYmu04mJFOtjI0U5ESHBAauaqcdu3\n8l4E422tG1nbDRD5226Bo2diYuI5z3nOc57znJH800hYPYvJSlxwIO91wDZIcMBmsl6BQ4ID\n0uKJCgM127HWleAgf4IVnFb1Zpx/IKYn814HbIMEJmwma0dIcEByNBlloN6cHTdA5G40CY5n\nPetZ09PTm/3q5OTk4cOHX/CCF7zmNa85ePDgSD6RgjJChQTooQWbyTqxeyp2j+ZwAYyLWjWO\ndmJpLWbcUbGJRismKnFIgo+8jeYM0mg0jh8/vrBwsvvQ5OTk2tpa7+uZmZlut7u8vPzHf/zH\n733vez//+c8/4QlPGMmHUkT1pgYcFNvCUiyvSXDAxoxQgST1yvrzrTh3X95LYVw1FuPQnpis\n5L0OSm80T1S++tWvvvCFL3zJS17yyU9+8tixY6urq4uLi5/5zGeuuOKKn/zJn1xcXFxYWLju\nuuu++c1vvuUtbxnJJ1JQEhwUnQQm9JF1NOCABNWqEaENB/00WnHY9Q9jYDQFjje+8Y0nTpz4\n9Kc/feWVV+7bty8iZmdnX/KSl3ziE5+49957f/u3f3v//v1veMMbrr766k996lMj+UQK6q5M\ngoNi6x3vbOGwIQkOSNKBmZiZPFnihw3N61DGeBhNgeMjH/nIj/3Yjz1+FuzExMSP//iP/8Ef\n/EHvPz772c9+8MEHR/KJFNF8K4524ogCB0XWaMX+GY+QYWMSHJCquaoEB/2YMceYGE2B49ix\nY/Pz8xv+0sLCwv3339/7+r777jt8+PBIPpEiqmcRERfpM0uRNRZdUMCmJDggVSbF0p8Zc4yJ\n0RQ4nvrUp77//e//0pe+9Jjv33HHHe9///svuuiiiLjtttve//73X3rppSP5RIqo3oxaNfbP\n5L0O2IZG6+RTZODxJDggVSbF0p8EB2NiNFNU3vrWt/7Ij/zIpZde+pSnPOXIkSOzs7OdTufu\nu+/+yle+0u12P/CBD0TENddcs7Cw8OY3v3kkn0gR6TBKAuzf0EezHc84K+9FADugVtWDg34k\nOBgToylwvPzlL//MZz7z9re//a//+q/vuOOO3jcnJyef+9znvvGNb/zRH/3RiHj1q1/9rne9\n6znPec5IPpEiMiOWBNi/oY+sLcEBaZqrxtceznsRjLF5U1QYD6MpcETEi170ohe96EURkWVZ\ns9nctWvX2WefPT09/chv+Nmf/dlRfRYFVc/i+y7KexGwPY3F+O5z8l4EjKusowcHpGluNj53\nT96LYIzNt0RcGQuj6cHxiPn5+TvuuOPrX//6/fff32p5qMd3kOAgARIc0IcEB6RKDw76WFiK\n5TUHJMbCyAoct9xyy/Oe97y5ubnLLrvspS996fOe97xDhw5dfvnlf/d3fzeqj6DQWivxwAk9\nOCg8PThgMyvrsbgiwQFpqhkTy+Z6/VkckBgHo3micuutt15++eWrq6sveMELLrnkkj179iwu\nLv793//9zTff/PznP//WW2+95JJLRvJBFNddWXRDgoPCm5fggE1k7YiQ4IA0zVXjxHK0VmJ2\nV95LYfz00j16cDAORlPg+J3f+Z25ublPf/rTT3nKUx79/dtvv/37v//73/a2t914440j+SCK\nq57F3umo+YuPIjuxHO1VFxSwsawTERIckKbeiPRGKy44kPdSGD+Nxdg/EzOTea8DRvVE5fOf\n//wv/MIvPKa6ERHf/d3f/Qu/8As333zzSD6FQqs34+IzolLJex2wDb0LCgkO2JAEByTsZIHD\nKxU2okMZ42M0BY6FhYXzzjtvw1+68MILm83mSD6FQqtnGnBQeL2DnQQmbCjrxMxk7BnZfDZg\njFR3xewubTjYWGPR6YhxMZoCR61W+4d/+IcNf+nv//7va7XaSD6FQjNChQQ0WidPeMDjGaEC\naZubVeBgY2bEMj5GU+C44oor3vOe99x0003dbveRb3a73Y997GPvfe97X/ayl43kUyg0CQ4S\nYIQK9JF1NOCAlJkUy2Y8UWF8jCZI+pu/+Zt/9md/9sM//MNnn332U5/61Gq12pui8sADD5xz\nzjm/+Zu/OZJPobjWunHPggQHhWf/hj4kOCBttaoeHGyssRhPPyvvRUBEjCrBceGFF952222v\netWr2u32zTff/Cd/8ic333zz8vLyv/7X//qLX/ziZu05KI97FmJ5TYKDwpPggD4kOCBtc1VP\nVNiYGyDGx8hagZ1//vm///u/3+12H3jggcXFxb1795599tmj+odTdPVmTE3E+eaKUXD2b+hD\nggPSVqvG3z2U9yIYS26AGB9bL3B885vf3OyXdu/evbq6+ujfIMRRcvUsLjgQu0YTGILcNBbj\nu+byXgSMq6wT5+/PexHAjtFklM00WqaoMC62XuA4//zzh//Nj24+SgkZoUIaGq14of0bNpG1\n4597gw3pqnmiwkbaq9FaEXFlXGy9wPETP/ETI1wHaTNChTRIYEIfenBA2uY0GWUjvT8VDkiM\nia0XOD784Q+PcB2krd6My04h8QNjSg8O6CNrxyE9OCBdtWq0V+P4cuybznspjJPe8GAHJMaE\npgicDndJcFB87dU4seyCAjaVdTQZhZT1foIV4uAxGouxeyr2KnsxHhQ42HEPLcbxZT04KLyT\nCUwXFLCRlfVYXPZEBVJWq0aENhw8lnwrY0WBgx1XzyIiLjqY9zpge04mMCU4YCNHO9ENCQ5I\n2e6p2Dd9cjeER+hQxlhR4GDH1Ztx9l65NQqvl8D08Bg2lLUjQoIDEmeQCo8nwcFYUeBgx93Z\njCPep1B89m/oI+tESHBA6hQ4eLz5Vhx2QGJsKHCw48yIJQ0SmNBH1o6Zydiz9eFsQAGYFMvj\nOSAxVhQ42HH1pg6jpECCA/owQgXKoFbVg4PHckBirChwsOMkOEiDCwroI2trwAHpm5v1RIXH\nckBirChwsLNOLMdDixIcpMAFBfQhwQFlMKcHB4/jgMRYUeBgZ/VmxEpwkAAXFNCHBAeUQU0P\nDr7TynosdByQGCMKHOysejP2z2itTApcUEAfEhxQBr0pKt1u3utgbMy3ohuO+owRBQ52lgYc\nJEOCA/qQ4IAymJuNlfVYWMp7HYyN+VZEuAFijChwsLOMUCENy2txbMn+DZuS4IAyqFUjQhsO\nvq2xGFMTcVCBm7GhwMHOkuAgDb0EpgQHbEaCA8pgrhqVMCmWb2u04sw9MVHJex3wTxQ42FkS\nHKShIYEJfUlwQBnsmoiDuyU4+DYPeBk3ChzsoNX1uPeYBAcpaCzGrok4MJP3OmBcSXBASZgU\ny6Npwc64UeBgB919NFbXJThIQaMVh2ejIoEJG1ldjxPLEhxQCibF8mgSHIwbBQ52UD2L6ck4\nb3/e64Bts39DH1knuiHBAaVQq+rBwbfNt8yIZbwocLCD6s248GBMuvSm+CQwoY+sHRESHFAK\nc7OeqPBtDkiMGwUOdpARKiRDggP6yDoREhxQDjU9OHgUByTGjQIHO8gIFZLhggL6yNoxPRmz\nu/JeB7Dz5vTg4FEckBg3ChzsIAkOkuGCAvrIOuIbUBYSHDyi241m2wGJ8aLAwU7pduPrmQQH\niXBBAX1kbQ04oCzmZmO+FevdvNfBGGh2YnXdAYnxosDBTnlgMRZXJDhIxEMSHLA5CQ4oj1o1\n1rrRbOe9DsZA77GSKSqMFQUOdkq9GZWIixQ4KL61bhztuKCATUlwQHn0yv0mxRIRjVZUIs50\nQGKcKHCwU+pZPGFf7JnKex2wbb0srgQHbEaCA8rj8GxMVrThICJivhUHd8cuP1AyTvx5ZKcY\noUIyegnMmgIHbEKCA8pjshJn7FHgIEILdsaSAgc7xQgVktFoxWTFBTVsSoIDSqVmUiwRoQU7\nY0mBg50iwUEyGotx5mxMVPJeB4wrCQ4oFZNi6ZHgYAwpcLBTJDhIhgsK6E+CA0plblaTUSIc\nkBhLChzsiGNLMd+S4CARLiigPwkOKBVPVOiZbzkgMXYUONgRdzYjIo4ocJAEFxTQx+p6nFiW\n4IASmfNEhYiIaCzGYQckxowCBzuinsXB3c67JEKCA/o42oluSHBAiczNKnAQ4QaIsaTAwY6o\nN8U3SIf9G/rIOhGhog0lUqvqwUGEJyqMJQUOdoQOo6REggP6yNoREYckOKA0atV4uBWr63mv\ng1wdX47Oqhsgxo4CBzvCjFhSIsEBfWSdmJ6M2V15rwM4Xeaq0Y14uJ33OshVr9GsGyDGjQIH\nO0KCg2Ssd6PZtn/DprK29ylQLrVqRGjDUXa9Z0qajDJuFDgYvaW1uO+YBAeJyDqxui7BAZvK\nOjqMQrkc2h1TEybFll1jMaq7Ys9U3uuA76TAwejdfTTWuhIcJEICE/qT4ICyqVTisEEqpafD\nKONJgYPRqzdjZjKesC/vdcAoNFpRiTjTBTVsQoIDSsikWHQoYzwpcDB69SwuPiMmKnmvA0ah\nsRhn7Ikpf1nCJiQ4oIRMisWMOcaTMzujZ4QKKXFBAf1JcEAJ1ap6cJSdAxLjSYGD0TNChZS4\noID+JDighOaqnqiUnQMS40mBg9GT4CAlLiigPwkOKCE9OGi0zIhlHClwMGLdbtx9VIKDdLig\ngP4kOKCE9OBg3g0QY0mBgxG773i0VyU4SMdDi/Zv6EeCA0qo5olK6bkBYjwpcDBi9SwmKnHh\nwbzXASPSMOYdNrfWjeNLEhxQOnPVWOjE8lre6yAnS2txfNkNEONIgYMRqzfjvP0xM5n3OmBE\nGhIcsLmjneiGBAeUTq0a3fBKpbx6M3TcADGGFDgYMSNUSEm3Gw+3o2b/hk1k7YiQ4IDS6ZX+\nTYotrV5tyw0QY0iBgxEzQoWULCzF8poLCthU1omQ4IDyObg7Zia14SivxmJMT8a+6bzXAY+j\nwMGISXCQEhcU0F/Wjl0TUd2V9zqA0+6wSbEl1mjFR7a0rAAAIABJREFU3GxUKnmvAx5HgYMR\nk+AgJb3wrTHvsBkjVKC0TIots8ai0xFjSoGDUTraiawjwUE6Gq04MBPTmubCJpptDTigpGpV\nPTjKa96MOcaVAgejdGczIuJiBQ5SYcY79Je1JTigpOaqnqiUV++JCowhBQ5GqZ7FmXvioNs8\nUmH/hv6yjgQHlJQnKmXmBoixpcDBKGnAQWLs39CfBAeU1pwmoyXmBoixpcDBKBmhQmLs39Cf\nBAeUVs0TlRJzA8TYUuBglO5sxhEJDhJi/4b+JDigtOY0GS2x+ZYpKowpBQ5GyRMVEiPBAf1J\ncEBp1apxfDnaq3mvg9NurRtZxwGJMaXAwch0VuP+E56okBQJDuhPggNKq/fzrRBHCT3civWu\nAxJjSoGDkbkri/WuBAdJmZfggL4kOKC0atWI0IajjHrTcxyQGE8KHIxMPYvZXXG2ai6pOLEc\n7VUXFLCptW4cX5LggJLaOx2zu0yKLaPGYkxW/OXPmFLgYGTqzbj4jKhU8l4HjIgLCujvaCe6\nIcEB5WVSbDk1WnFoT0w68zOWFDgYGTNiSUzvXbEm4bCZrB0RLvGgvEyKLScdyhhnChyMjBEq\nJKbRiuqumN2V9zpgXGWdCAkOKDGTYsupYUYsY0yBg5GR4CAxLiigv6wduyaiqggIZVWr6sFR\nRlqwM84UOBiN9W5846gEB0l5aNH+Df1knTi4W+slKC89OMrJDRDjTIGD0bj3WCytSXCQlEbL\n/g39ZG0NOKDU5vTgKKWGBAdjTIGD0ag3Y7ISTzyQ9zpgdBoSHNBX1tGAA0qtpgdHKUlwMM4U\nOBiNehZPPBDTk3mvA0an0Yqa/Rs2l7XjkAQHlJgpKuUkwcE4U+BgNIxQIT0uKKC/rOOJCpTa\n3Gy0V+PEct7r4DTqduNhU1QYYwocjIYRKqTHBQX0l7U9UYFS6+UchThK5ehSrKy7AWJ8KXAw\nGhIcpEeCA/qT4ICS6xU4TIotlflWRLgBYnwpcDAad0lwkJb2aiyu2L+hHwkOKLndU7FvWoKj\nXHptZT1RYWwpcDAC861YWJLgICm9/VuCA/qQ4ABMii2bRisOzBgswPhS4GAE6llExMUSHCSk\nIYEJg0hwACbFlo0HvIw5BQ5GoN6MWjX2Tee9DhidxmLsnoq9/lTDJta6cXxZggPKrlbVg6Nc\ntGBnzClwMAJGqJAe+zf0t9CJ9a4EB5Td3KwnKuUiwcGYU+BgBIxQIT32b+gv60SEBAeUnScq\nZTPf0mGUsabAwQhIcJAeCQ7oL2tHhAQHlJ0mo2XjgMSYU+BgBCQ4SI8EB/SXdWJqIqq78l4H\nkKuaAkfJOCAx5hQ42K7WSjxwQoKD1LiggP56I1QqlbzXAeRqbjYareh2814Hp4sDEmNOgYPt\nqmfRDQkOUuOCAvrLOhpwAFGrxvJaLCzlvQ5Ol/mWAxJjTYGD7ao3Y+901JRySYsLCuivl+AA\nSq73s65JsSWxuBKtFQckxpoCB9vV6zAqpUxiJDigPwkOICJq1aiENhxl0ZuYY4oK40yBg+3S\nYZT0LK/FsSUXFNCPBAcQEbsm4sBuBY6ymG9FhBsgxpoCB9tlRizpmW9F1/4NfUlwAD216smL\nfZLXaMWeKfOzGGsKHGyXBAfp6d1ESXBAHxIcQI9JseXhAS/jT4GDbVnrxj0LEhykptGKXRNx\nYCbvdcAYk+AAenqTYikDLdgZfwocbMs3jsbKugQHqWksxuFZrXOhn6YEBxARnqiUiQQH40+B\ng22pZzE1Eefvz3sdMFKNVtTs39BX1pbgACIi5jxRKQ0JDsafAgfbUm/GhQdjyp8j0uKCAvpb\n68bxZQkOICJiblaBoyzmW2bEMu78YMq2GKFCklxQQH8LnVjvSnAAEb0nKnpwlIMbIMafAgfb\nYoQKSbJ/Q39ZJyIkOICIf+rBsd7Nex3sPDdAjD8FDrZFgoMk2b+hv6wdERIcQETEXDXWuifr\nnqTNDRDjT4GDbfl6JsFBguzf0F/WiamJ2Lsr73UAY6DXllsbjuQtr8WxJTdAjDsFDrbuwcU4\nvizBQYIkOKC/rB0HdxulDEREHJ6NiYpJsembb0U33AAx7hQ42Lp6MyoRFylwkJa1bhzt2L+h\nn6yjAQdw0mQlDu2R4Ehfr5WsKSqMOQUOtq6exdl7oyqiTFrmW7HeleCAfrK2BhzAt5kUWwaN\nxZiaiIMzea8D+lLgYOuMUCFJvZCtBAf0IcEBPJpJsWUw34rDsx4nMu4UONg6I1RIUqMVkxU/\nvEE/EhzAo/UmxZI2HcooBAUOtk6CgyQ1FuPM2ZhwQQGbk+AAHm2u6olK+syYoxAUONg6CQ6S\n5IICBpLgAB5ND44ycECiEBQ42KITy/HQogQHCXJBAQNJcACPpgdHGTggUQgKHGxRPYsICQ4S\n5IICBpLgAB6t5olKCfSajMKYU+Bgi+rN2D/jrzkS5IICBso6cUiBA/gnc9VotmN1Pe91sJPc\nAFEIChxskQYcpMr+Df2td+PYkicqwLfVqrHejYfbea+DneQGiEJQ4GCLjFAhVfZv6G9hKda7\nnqgA39a7GDApNmHr3Wi23QBRAAocbJEEB6mS4ID+snZESHAA33bmnpia0IYjZc12rHXdAFEA\nChxskQQHSTp5QWH/hs1lnYiQ4AC+rVKJM/cocKSsNyXHDRDjT4GDrVhZj3sW4ogCB8np9Uiz\nf0MfWTumJmLvrrzXAYwTk2LT1liMSmgvTQEocLAVdx+Nta4nKiTo5AWFBAdsLuvEwd1RqeS9\nDmCc1Kp6cKSs0Yoz9sSUnx0Ze/6QshX1ZsxMxrn7814HjFrvguJMFxSwuaytAQfwWHNVT1RS\nNq9DGQWhwMFW1LO48GBMur4jOY1WHHJBAX1lHQ04gMfyRCVtZsxRFE7xbIUOo6TK/g0DSXAA\njzc3K8GRMjPmKAoFDrbCjFhSZf+GgSQ4gMfzRCVtboAoCgUOtkKCg1TZv2EgCQ7g8TQZTZsb\nIIpCgYNT1u3G149KcJAm+zcMJMEBPF6tGkc7sbyW9zrYGY3FOOyARBEocHDK7j8RrRUJDtIk\nwQEDSXAAjzc3G92IeX1GEzXfckCiGBQ4OGX1LCoRFx7Mex2wAyQ4YCAJDuDxatWI0IYjWcbE\nUhQKHJyyejPO3R97pvJeB+wACQ4YSIIDeLyDu2N60qTYNB1biqU1BySKQYGDU2aECqnqduPh\ntgsK6Ge9GwtLEhzABkyKTVWvbuWARCEocHDKjFAhVQtLseyCAvo6thTrXQkOYAM1k2IT1ZuP\no8kohaDAwSmT4CBVLihgoGY7IiQ4gA3MmRSbqEYr9k3Hbu/TKQIFDk6ZBAepckEBA2WdiJDg\nADZQq+rBkSYdyigQBQ5OzbGleLgtwUGaGq04MBPTk3mvA8ZY1o7JSuybznsdwPjRgyNVjZbr\nHwpDgYNTc2czIiQ4SJMLChgo68TB3VGp5L0OYPzM6cGRKDNiKRAFDk5NPYuDu4WTSVPD/g2D\nZG0NOICN1fTgSJQbIApEgYNTU2/GEfENEmX/hoGyjho3sDFTVFLlBogCUeDg1BihQsLs3zCQ\nBAewmbnZOL4c7dW818GouQGiQBQ4ODVGqJAw+zcMJMEBbKZWjQivVBLkBogCUeDg1EhwkDD7\nNwwkwQFs5mSBw6TY5MybokJxKHBwCpbW4r5jEhwk6yEJDhhEggPYzN7pmN2lDUdqOqtxYtkB\nicJQ4OAU3H001roSHCTLFDQYSIID6OPwrAJHanqRHAckikKBg1NQb8buqXjCvrzXATvg+HJ0\nVl1QwAASHEAfJsWmp/cv1AGJolDg4BTc2YyLDsZEJe91wA7o7d81+zf0JcEB9FGr6sGRmkYr\nZiZj33Te64DhKHBwCupZHNGAg0T1DmR6aEEf6904tiTBAWxqzhOV5JgxR7EocHAKzIglYY3F\n2Dsde6byXgeMsWNLsdaV4AA25YlKesyYo1gUODgFZsSSMPs3DJR1IkKCA9jUXFWCIzVmxFIs\nChwMa70bdx+V4CBZEpgwUNaOCAkOYFM1BY7kOCBRLAocDOu+49FZleAgWRIcMFDWicmKVnPA\npvTgSI8DEsWiwMGw6s2YqMQFB/NeB+wMFxQwUNaOg7vN0gI2VatGezVOLOe9DkbHAYliUeBg\nWPUszt8fM5N5rwN2hgsKGCjreJ8C9NP7Sdik2JQ4IFEsChwMywgV0uaCAgbK2jqMAv3UqhHh\nlUpSHJAoFgUOhmWECmlzQQEDSXAA/e2Zir3TJsWmY3U9jnZMUaFIFDgYlgQHaXNBAQNJcAAD\nGaSSkvlWdMMNEEWiwMGw7pLgIF3t1VhcsX/DABIcwEAKHCmZb0WEGyCKRIGDoTTbkXUkOEhW\nL0xr/4b+JDiAgeZmNRlNR6MVkxV/81MkChwMpZ5FRFwswUGiekcxCQ7oT4IDGKhW1YMjHY3F\nOHPWdHCKRIGDodSbcXg2DszkvQ7YGY3F2D0Ve6fzXgeMNwkOYKA5T1QSogU7haPAwVCMUCFt\n9m8YhgQHMNDcrAJHOrRgp3AUOBiKESqkzf4NA3W7sdCR4AAGqFX14EiHGyAKR4GDoUhwkDb7\nNwx0bDnWuhIcwAC9KSrdbt7rYBTmW3HYAYlCUeBgKBIcpE2CAwbK2hEhwQEMMFeN5bU4tpz3\nOhgFByQKR4GDwTqrcf8JCQ5S9tCiBAcMkHUiQoIDGKBWjQhtOBIh4krhKHAw2F1ZrHclOEhZ\no+WCAgbI2jFZiX2GDQF9zc1GJUyKTYQEB4WjwMFg9Sxmd8XZ/nYjXQ0JDhgk68SB3TFRyXsd\nwHibnowDuyU4UtDtxsNtByQKRoGDwerNuPiMqDjUkq5G62SkFthM1taAAxiKSbFpyDqxui7B\nQcEocDCYESqkbXktji/Zv2GArKMBBzAUk2LT0PuXaIoKxaLAwWBGqJC2Riu6IYEJA0hwAEOq\nVfXgSMF8KyoKHBSNAgeDSXCQtt4hTIID+mu2JTiAocxVPVFJQWMxDuyOXX5epFD8gWWA9W58\n46gEBylrtGLXROw3GwL6yjoSHMBQagocSTAjliJS4GCAexZiaU2Cg5T1RqBpowv9ZRIcwHDm\nZvXgSIEZsRSRAgcD1LOYrMQFB/NeB+wYFxQwDAkOYEgSHGlwQKKIFDgYoN6MCw56fUfKXFDA\nMCQ4gCHNVWO+FevdvNfB9jggUUR+bGUAHUZJngsKGIYEBzCkWjVW1yPr5L0Otme+ZYQKxaPA\nwQBmxJI8FxQwULcbCx0JDmAovWsDk2KLzg0QRaTAwQASHCTP/g0DHVuOta4EBzCUuWpMVLTh\nKDw3QBSRAgcD3JVJcJA4+zcMlLUjQoIDGMpkJc7YrcBRePNugCggBQ76abTi2JIEB4mT4ICB\nem/pJTiAIdWqJsUW24nlaK+6AaJ4FDjop96MiLhIgYN0ra7H0Y79GwbI2jFRif0zea8DKAiT\nYouuV59yA0ThKHDQTz2Ls6qxbzrvdcCOebgd6137NwyQdeLATExU8l4HUBBzVU1Gi633r88U\nFQpHgYN+jFAheb39W4ID+svaGnAAp8ATlaJrtGJ2V8zuynsdcIoUOOjHCBWS12id7IUG9JF1\n/N8EOAVzs56oFJsOoxSUAgf9SHCQvMZinDkreA8DSHAAp2ROD46CM2OOglLgoB8JDpL30KIL\nChgs68QhBQ5gaDU9OArOjDkKSoGDTbVW4sETEhwkrtFyQQGDZW1PVIBTUKvGw+1YXc97HWyV\nBAcFpcDBpupZdEOCg8Q1JDhgCFnHExXgFMzNxno3mu2818FWSXBQUAocbKrejL3TUVO7JWmN\nlj/kMJgEB3BKenurNhzFNd8yI5ZCUuBgUxpwUAYSmDAMCQ7glBzaE1MTJsUWmAMSBaXAwaaM\nUKEMJDBhGBIcwCmZqMSZeyQ4CswBiYJS4GBTEhyUgQsKGKjbjYUlCQ7g1JgUW1zLa3F8yQGJ\nQlLgYFMSHCSv1//MBQX0d3w5VtclOIBTY1JscTVa0Q0HJApJgYONra7HPQsSHCSu2Y61rgsK\nGCDrRIQEB3BqalU9OIqqV5lyQKKIFDjY2D0LsbIuwUHiegcvFxTQX9aOCAkO4NTMzXqiUlSN\nVuyaiP3Tea8DTp0CBxurZ7FrIs7fn/c6YCc1FqMScci9NPSVdWKiEvtn8l4HUCh6cBRXYzEO\nz0alkvc64NQpcLCxejMuOBhT/oCQtEbr5Bw7oI+sHQdmYsJJFzgVenAU13zL+xSKyrmejRmh\nQhkYoQLDyDoacACnrCbBUVhmxFJcChxsrN6MIxpwkDr7Nwwja2vAAZyyudk42omV9bzXwalz\nA0RxKXCwsTvNiKUE7N8wDAkOYAtq1eiGVyqF5AaI4lLgYGNfP+qJCumzf8MwJDiALahVI8Kk\n2EJyA0RxKXCwgQdOxIllCQ7SZ/+GYUhwAFtwYCamJ7XhKKRGKw67AaKYFDjYQD2LSsRFB/Ne\nB+wwCQ4YhgQHsAWVShyeVeAopHkHJApLgYMN1Jtxzr6Y3ZX3OmCHSXDAMCQ4gK0xKbaI1rqR\ntR2QKCoFDjZgRixl0O26oIChSHAAW1Or6sFRPM12rHUdkCgqBQ42UDdChRJYWIqVdRcUMJgE\nB7A1c56oFFAvdOOAREEpcLABCQ7KoHen5IIC+ut242hHggPYCk9UiqjRiolKHFLXppgUONiA\nBAdl0LtT0iQc+ju+HKvrEhzAVsxVJTiKp7EYh/bEZCXvdcCWKHDwWMeXo9GS4CB9jcWTE+yA\nPrJOREhwAFtRU+AoIDPmKDQFDh6r3owICQ7S12h5XwqDZe2IkOAAtmJuVpPR4mksyrdSYAoc\nPFY9i/0zcaazLKlrLEZNgQMGyToxUYn9M3mvAyigWjWOLUV7Ne91cCrm3QBRZAocPFa9GUfE\nNygBCUwYRtaO/TMeYwNb0fs5eV6Io1AckCg0BQ4eywgVSqKx6IICBsuMUAG2qpeU1IajWByQ\nKDQFDh7LCBVKwgUFDCNra8ABbNG+6dgzZVJswTggUWgKHDyWBAcl4YIChiHBAWyHSbGF44BE\noSlw8B1W1uPeBQkOSsEFBQxDggPYDpNiC+fhtikqFJgCB9/h7qOx1pXgoBQ0CYdhSHAA22FS\nbLEsLMXymhsgCkyBg+9Qb8bMZJy7P+91wA47vhydVfs3DCbBAWxHraoHR5H0/mW5AaK4FDj4\nDvUsLjxoHCDps3/DkCQ4gO3Qg6NYenEbT1QorgIUONrt9q/92q9dcMEFMzMzF1544bXXXru6\nurrh7/zbv/3bF7/4xbOzs+ecc86v/MqvrKysnOalJsAIFUrC/g1DkuAAtmNuVoGjSBqLsX8m\nZibzXgds1VTeCxjs537u526++eZ3vOMdT37yk//6r//613/911dWVn7jN37jMb/t3nvvffGL\nX/wDP/ADn/70p++6665f+qVf2rVr1zvf+c5c1lxcRqhQEo3F2DsdewrwVyDkTIID2I5aVQ+O\nItGCnaIb99P90aNHP/nJT15//fVXXXVVRHzv937v7bff/tGPfvTxBY53vvOdT3rSkz70oQ9V\nKpXnP//555xzzvLych5LLrZ6M15yUd6LgJ1n/4YhLXQkOICtM0WlWMyIpejGvcBx8ODBLMse\n/Z2pqampqQ2W/bGPfexXf/VXK5WT3SMuv/zy07G+tHS78fWjEhyUgv0bhnF8OVbW45ACB7BV\nc9VorcTiSlR35b0UhjDf8oCXYitAD46edrv9wAMP/Lt/9+9uuumma6655jG/2mw2v/Wtb83N\nzf30T//04cOHzzvvvLe+9a1ra2u5LLW47j8RrRU9OCgFCQ4YRtaOCE9UgK2rVSNCiKMwHJAo\nunFPcDziZS972V/91V+dccYZH/jAB37yJ3/yMb/aaDQi4s1vfvNrX/vaN7zhDZ/73Ofe9KY3\nraysvP3tb+/zz7z77rvvvPPODX/p9ttv73a7o1p8UdzZjIlKXHgw73XAzpPggGFknYjwRAXY\nul6Bo7EYFzlhFkFjMZ5+Vt6LoDi63e7tt98+OblxW9ojR45ceOGFp3dFxSlwvOc977n//vtv\nvvnmV7/61UePHn3ta1/76F/tDUz5wR/8wTe/+c0R8exnP/vBBx9897vf/Vu/9Vub/c8dEe96\n17tuvPHGDX9pZWWlhENY6lmcu0/bRUqh0YqnzeW9CBh7WTsmKrF/Ju91AIW1Zyr2TktwFIYE\nB6ekFynYtWvjF2g/9VM/dcMNN5zmJRXmZ9mnP/3pT3/606+44op9+/Zdc801V111VbX67evX\nffv2RcSznvWsR77zghe84B3veMfdd9/9pCc9abN/5g033LDZ/+Kf+tSnfuiHfmh0yy8GM2Ip\nj8ZizF2Y9yJg7GWd2D8Tk5W81wEUmUmxBSLiyimZnp7+r//1v1555ZV5L+Tbxr0Hx3333feh\nD33oxIkTj3znGc94Rrvdvvfeex/9284777zdu3fPz88/8p3V1dWImJ6ePm1LTYAZsZSHCwoY\nRtbWgAPYLpNiC8QBiaIb9wLHAw88cNVVV910002PfOdLX/rSxMTEBRdc8OjfNjk5+dKXvvRj\nH/vYI9/57Gc/e+jQofPOO+/0rbX4JDgoDxcUMIzMjFhg22rVaEhwFEFrJVorpqhQbOP+ROXS\nSy+94oorXv/61x8/fvxpT3vabbfd9s53vvPqq6/es2dPRLzvfe+78cYbb7nlloj4N//m37zg\nBS+4+uqrf/Znf/bWW29973vf+9u//duPTI1lGBIclERvXp0LChhIggPYvrmqJyrF0AvauAGi\n0Ma9wBERf/RHf/SWt7zlbW97W7PZvOCCC6655ppeJ9GIuOeee77whS/0vn7uc5/7p3/6p29+\n85u/7/u+r1arveMd7/iVX/mV/FZdPEc70WxLcFAK9m8YkgQHsH21atx+f96LYAjzvQOSGyCK\nrAAFjr1791533XXXXXfd43/p2muvvfbaax/5j1dcccUVV1xxGpeWlHoWEXGxBAcl0AvK2r9h\nIAkOYPvmZvXgKIbGYuyeir16GFJk496Dg9Om3oxDexxkKYVG6+TUOqA/CQ5g+2qeqBSEDqMk\nQIGDkzTgoDx0GIUhSXAA2zdXjcZidLt5r4NBHJBIgAIHJxmhQnm4oIAhSXAA21erxtJaHFvO\nex0M4oBEAhQ4OEmCg/JwQQFDkuAAtq/3M7NJsePPAYkEKHBwkgQH5eGCAoZ0VIID2LZaNSqh\nDUcBzLfisAMSBafAQUTE0lrcd1yCg7JwQQHDOLEcK+sSHMB2TU/G/hkFjgJwA0QCFDiIiPh6\nFutdCQ7Kwv4Nw8g6ESHBAYxArWpSbAG4ASIBChxERNSz2D0V5+zNex1wWti/YRhZOyIkOIAR\nMCm2ENwAkQAFDiIi6s24+IyYqOS9Djgt7N8wjGY7KhEHFDiAbetNimWcrazHQscNEIWnwEGE\nESqUyfJaHF+yf8NgWSf2z8Sk2jewbZ6ojL/5VnRDk1EKT4GDCCNUKJNGK7ohwQGDZW0NOIDR\nmJv1RGXc9SI2DkgUnQIHERIclMnJ/VuCAwbJOhpwAKMxpwfH2JtvxdREHPTXPgWnwEGsd+Pu\noxIclEWjFdOTsX8673XA2JPgAEalpgfH2Gu04sw9WvJReAocxH3Ho7MqwUFZNBbj8GxU7N8w\niAQHMCq9Hhzr3bzXwebMmCMNChxEvRkTlbjgYN7rgNPCCBUYkgQHMCpzs7G6Hkc7ea+DzTkg\nkQYFDqKexfn7Y2Yy73XAaeGCAoYkwQGMSq0aEdpwjDUHJNKgwIERKpSLCwoYkgQHMCpz1Zio\nmBQ71hyQSIMCB0aoUC4uKGBIEhzAqExW4ozdEhxjbb4VhxU4KD4FDiQ4KBcXFDAkCQ5ghEyK\nHXNugEiDAgcSHJTLQ/ZvGM7CkgQHMDImxY45N0CkQYGj7B5ux9FOHJHgoDQai/ZvGOzEciyv\nSXAAI9ObFMt4Wu9Gs+0GiBQocJRdvRkRcbEEB+XQm1Fn/4aBsk5ESHAAIzM364nK+Mo6sbru\nBogUKHCUXT2LudnYP5P3OuC0mG9F95+G1QF9ZO2IkOAARqamB8cY670ecgNEAhQ4yk6HUUql\nF451QQEDZZ2oRBxQ/gZGZE4PjjHWaEUl4pCiNsWnwFF2OoxSKo3FmKzEQal7GCRrx76ZmHJM\nAEZEgmOcNRbj4O7Y5e98is+f4rKT4KBUGq04PBsTlbzXAWMv67jKA0ZpbjYebsdaN+91sJH5\nlvcpJEKBo+wkOCgVM95hSFlbh1FglGrVWO/GwwapjCUzYkmGAkeptVfj/uMSHJSI/RuGlHV0\nGAVGqXfBYFLseHIDRDIUOErtriy6IcFBidi/YUgSHMBonbknpia04RhTboBIhgJHqdWbMbsr\nzvLzHqVh/4YhSXAAozVRiUN7FDjGlBsgkqHAUWq9BhwVDRcpDfs3DEmCAxi5mkmx42q+FYfd\nAJEEBY5SM0KFspHggCFJcAAjV6vqwTGmHJBIhgJHqRmhQtlIcMCQJDiAkZub9URlTBkTSzIU\nOEpNgoNSWe9Gs+2CAoYiwQGMnCcq4+n4cnRWHZBIhAJHea114xsLEhyUSLMda10XFDCUox0J\nDmDE5qoSHOOoV3VyQCINChzlde9CLK9JcFAivXe/LihgoMWVWF6T4ABGrKbAMZZ6ByRNRkmD\nAkd51bOYmognHsh7HXC6NBZPzqgD+svaESHBAYzY3Kwmo+OosRh7p2PPVN7rgFFQ4CivejOe\neCB2+SNAaTRaccbumPJnHgbJOhEhwQGMWK0aWTtW1vNeB9+pYUYsCXHSLy8jVCgbI1RgSFk7\nKhEHZvJeB5CWuWp0I+aFOMbMvBmxJESBo7yMUKFszHiHIWWd2Dcj7gSMWK0aEdpwjB03QKTE\n4aW8JDgoG/s3DClra8ABjN7Bmdg1YVLs2HEDREoUOMrrrkyCg3J5aNH+DUPJOhpwAKNXqZgU\nO47cAJESBY6SarTi2JIEB+XSaNm/YSgSHMAyFB9EAAAgAElEQVQOMSl2DElwkBIFjpKqNyMi\nLlLgoEwaEhwwHAkOYIeYFDuGGoumqJAOBY6SurMZZ1Vj33Te64DTqNE62d4M6E+CA9ghtaoe\nHGNnXsSVhChwlFQ9iyMacFAm3W48bP+G4TTbEhzAjtCDY9wsrcXxZRFX0qHAUVJmxFI2R5di\nZd3+DUPJOhIcwI6Ym1XgGC+9QI0bIJKhwFFSZsRSNvZvGF4mwQHsjFpVD47x0vvX4QaIZChw\nlJQEB2XTaEUl4kw/s8EQJDiAHWKKyrhpLMb0pMZ8pEOBo4xOLMdDixIclEtjMQ7sjunJvNcB\nRbBgigqwM+aqcWwpOqt5r4N/0psRW6nkvQ4YEQWOMrori25IcFAuZrzDkBZXYmlNggPYEb1x\nZl6pjI/Goge8JEWBo4zqWeyd9sMe5WL/hiFl7YiQ4AB2xMkCh1cqY2O+FYf9UEBCFDjKqN40\nI5bSkeCAIWWdiJDgAHbEvunYM6UNxxhxQCIxChxlZIQKJSTBAUPK2lGJOKjAAeyMwybFjhMH\nJBKjwFFGRqhQQi4oYEhZJ/ZOx5QDArAzTIodKw5IJMb5pYwkOCghFxQwpKytAQewg87cE3c2\nY62b9zqICAckkqPAUTqr63HvggQHpeOCAoaUdTTgAHbEf/9mPO8/xp/fFb93W1TfHq/5E1GO\n/DkgkRgFjtL5xkKsrEtwUDrzLRcUMBQJDmAn/Mk/xgs/GE+rxc/883jJRfGRH48vfiv+xX+I\neTWO/Kx142jHFBWSosBROvVm7JqI8w/kvQ44jY4vR2fVBQUMRYIDGLn1brzu4/Grl8UHXhFP\nr8WJ5Xj5P4vPXR2zu+LaW/JeXIk93Ir1rhsgkqLAUTr1LC48GJOVvNcBp1FjMSLs3zAUCQ5g\n5L78YNx7LP6350VE1Konp6jsmYqfvzT+9B/zXVqp9Z4IuQEiJQocpWOECiXU278lMGEYWScO\nKXAAI/XQYkxPRq0aEXHRGbG2fvL75+3XhiNPjcWYrChqkxQFjtIxQoUSaizG3unYM5X3OqAI\nsrYnKsCInbs/ltfi3mMRES+6IOq/fPL79SzO3Zfjusqu0YpDeyS7SYoCR+lIcFBCDy2KX8Kw\nso7bPGDEnno4vutw/NZfnfyPuyYiIprteO+t8S+fmuO6ys6MWNLjQrN0vn5UgoPSaRihAkOT\n4ABGrlKJ//CKeOkfxDeOxv/67Dhnb9z+QFx7S9Sqcc335L24EjMjlvQocJTLAyfixLIEB6XT\nkOCAoR2V4AB2wPPPj6/8Qrz5L+Ln/ySydlx0RrzmWfGrz/eANE/zLR3KSI2/UcqlnkUl4qKD\nea8DTq9G62RjM6C/1kosrUlwADviSWfE//O/REQsrcXMZN6rwRMVUqQHR7nUm3HOvpjdlfc6\n4PSyf8OQsk5ESHAAO0t1Y0x4okJ6FDjKxQgVysn+DUPK2hEhwQFQCm6ASI8CR7kYoUI52b9h\nSL0ExwEFDoAScANEehQ4ykWCg3Kyf8OQsnbsmz45wRGAhHW78bAxcyTHEaZcJDgoodZKtFbs\n3zCUzAgVgHI4uhQr66aokBoFjhI5thSNlgQHpdNoRYQEBwwla2vAAVAKjcUIBySSo8BRIvUs\nIuKIBAclc3L/luCAIUhwAJTEfCsiJDhIjQJHidSbcXB3HHJypWQardgzFVXTkWEIEhwAJdFo\nxYGZmDayl7QocJSIDqOUkxEqMDwJDoCScEAiSQocJaLDKOVkhAoMT4IDoCQckEiSAkeJSHBQ\nTi4oYHgSHAAl4YBEkhQ4SkSCg1JZ78a//2Jc9oG4/m/iv98bv/hnJ8epAH1IcACUhAQHSVLg\nKIvltfjmMQkOymJpLV76ofi1v4iXPin+p1o8+wnx+Xvju26Iv30w75XBeJPgACiJ+ZYRKiRI\ngaMs7j4aa10JDsrid/8m/r+H4suvjbf9zzE1EZdfHP/vz8dLLoqrb8p7ZTDejnYkOABKwRMV\nkqTAURb1LGYm49x9ea8DTosP/1384nPj/P0R/7R/T1bi//i++OL98Y8P5704GFetleisSnAA\nlIInKiRJgaMs6s246IyYqOS9DjgtvnE0njp38uuFpTirGhFx5FBMT8Y3FnJcF4y1rBMREhwA\npTDfkuAgQVN5L4DTxAgVSuXg7nhw8eTXn311XHJmRETWieU1P7zBprJ2REhwAKRvcSVaKxIc\nJEiCoyyMUKFUrnhSfPD2WF2PiHjaXExNRET8+y9GrRrPPDvfpcH46iU4DioCAqSusRgRmoyS\nIAWOspDgoFR+/YVxz0J8/3+OW++L5bW4ZyH+98/Eb9wc77riZLEDeLysHXunY5f/jwCka2U9\n/tPfxq/9RUTETV+NxZW8FwQj5YlKKXS78fVMgoMSOXdffP7q+N8+Gf/iP578zkUH4yM/Hj90\nSa7LgvGWGaECkLSvPBQ//pGYb8Ulh2OyEv/n5+Jdn4///KPxogvyXhmMiAJHKXzrRLRXJTgo\nl4vPiD9+ZTzcjjvm45y9ceFBTXZhgKytAQdAstqr8Yr/Es9+QvzHV8RNd8S9C/HVX4xf/XT8\n8Ifjq78YNQ1HSYIcainUmzFRiQsP5r0OOO3O3BPPPz8uNkIIhiDBAZCwP/5qZO34v34oDsyc\nnBG7eyre/f1xeDb+09/mvTgYEQWOUqhnce6+2C2vA8DmJDgAEvblB+O558a+6YiI+dbJDqOT\nlXjRBfHlB/NdGoyMH3lLwQgVAAaS4ABI2EQl1ronv/7BJ8f3nHfy67WuoCvpkOAoBSNUABhI\nggMgYZeeE3/zzXi4HRHxgifGKy6JiFhai8/cFZeek+/SYGQUOEpBggOAgSQ4ABL2g/8sLjoj\nfuIjcd/xk99ptuNVH4uV9XjVM3NdGYyOJyqlIMEBwEASHAAJ2zURf/zK+JmPxpN/Ny59QkxP\nxm3fivP3xyd+Og7M5L04GBEFjvQd7USzLcEBwAASHABpu+hg3PKz8cl6fOn+WF6L1z0nXnFJ\nTMn0kxAFjvTVs4iIiyU4AOjraEeCAyBxlUq87Ei87Eje64CdoV6XvnozDu1xKQdAP+3V6Kza\nLACAAlPgSJ8GHAAMlLUjQoIDACgwBY70GaECwEBZJyLikAIHAFBYChzpu7MZRxQ4AOirl+DQ\nSB8AKC4FjvR5ogLAQFkn9k7H9GTe6wAA2CoFjsQtrcW3jnuiAsAAWVuHUQCg2BQ4EndXFutd\nCQ4ABsjMiAUACk6BI3H1ZuyZinP25r0OAMabBAcAUHQKHImrZ3HxGVGp5L0OAMabBAcAUHQK\nHIkzIxaAYUhwAABFp8CROCNUABiGBAcAUHQKHImT4ABgGBIcAEDRKXCkbL0bdx+V4ABgMAkO\nAKDoFDhS9s1jsbQmwQHAYBIcAEDRKXCkrJ7FZCUuOJD3OgAYexIcAEDRKXCkrN6M8w/E9GTe\n6wBgvHVWo7MqwQEAFJsCR8qMUAFgGFknIiQ4AIBiU+BImREqAAwja0eEBAcAUGxTeS+AHfHf\nvhGfvzf+2z3xogvi+HLsm857QQCMsV6C46ACBwBQZBIcqck68fL/Epf/Qdz01Wi24s/r8ZQb\n4s++lveyABhjWTuqu/RsAgCKTYEjNf/qo3HPQnz5tfGnPxUr6/GpfxWvfmb86B/GHfN5rwyA\ncdVsa8ABABSeAkdS/r4RH/9a/OcfjaccjnozIuIpZ8bbXxLPOy9+92/yXhwA4yrraMABABSe\nAkdSvnh/nLsvnl6LiKhnMTcb+2ciIr7/SHzp/nyXBsD4yiQ4AIDiU+BISrcbk//0r/Spc/Fr\nLzj59UQl1rt5LQqAcSfBAQAkwBSVpDzj7Lh3Ib76cFxyZjzjrHjGWSe//xd3xTPPznVlAIwx\nCQ4AIAESHEl5xlnx4oviqo/FvcdOfmetG+/8XPzl3fGLz811ZQCMMQkOACABEhypufFfxo9/\nJJ5yQ3zvE+PQnrj1vmi24//+0fjnZw3+7wJQThIcAEACFDhSc1Y1Pvuq+JN/jM/fG1knfulf\nxE8/PQ7P5r0sAMaYBAcAkAAFjgRVKvGKS+IVl+S9DgAKQoIDAEiAHhwAUHYSHABAAhQ4AKDU\nOqvRWZXgAAAKT4EDAEot60SEBAcAUHgKHABQalk7IiQ4AIDCU+AAgFLrJTgOSnAAAAWnwAEA\npZa1Y3ZXzEzmvQ4AgO1R4ACAUjNCBQBIgwIHAJRa1o5DGnAAAMWnwAEApZZ1dBgFAFKgwAEA\npZa1PVEBAFKgwAEApSbBAQCkQYEDAEpNggMASIMCBwCUmgQHAJAGBQ4AKDUJDgAgDQocAFBq\nEhwAQBoUOACg1CQ4AIA0KHAAQHktrUV7VYIDAEiBAgcAlFfWjggJDgAgBQocAFBeWSciJDgA\ngBQocABAefUSHAclOACA4lPgAIDyyjoxuytmJvNeBwDAtilwAEB5GaECACRDgQMAyivraMAB\nACRCgQMAykuCAwBIhgIHAJSXBAcAkAwFDgAoLwkOACAZChwAUF4SHABAMhQ4AKC8mhIcAEAq\nFDgAoLyytgQHAJAIBQ4AKK+sI8EBACRCgQMAykuCAwBIhgIHAJTU0lq0VyU4AIBEKHAAQEll\n7YiQ4AAAEqHAAQAllXUiQoIDAEiEAgcAlFQvwXFQgQMASIICBwCUVNaJPVOxeyrvdQAAjIIC\nBwCUlBEqAEBKFDgAoKSyjgYcAEA6FDgAoKQkOACAlChwAEBJSXAAAClR4ACAkpLgAABSosAB\nACUlwQEApESBAwBKSoIDAEiJAgcAlJQEBwCQEgUOACiprB2HJDgAgFQocABASWUdT1QAgHQo\ncABAGS2vRWvFExUAIB0KHABQRlknIiQ4AIB0KHAAQBll7YiQ4AAA0qHAAQBl1EtwHFTgAABS\nocABAGWUtWPPVOyeynsdAAAjosABAGVkhAoAkBgFDgAoo6ytAQcAkBQFDoD/v717D86ivvcH\n/g2ERG4lIDfLJRrKSPEC2qhQuSgiChYQL0ekclHRIdoilmpHjhekFejQWgHNUcdWK9iekUqR\nIor1esAOIjL2Z0UFp8jN0CgmKjZBAs/vj6cnhyoqBPTJd5/X66+wz+7mvauzC+/57D6QjUxw\nAAAJo+AAgGxkggMASBgFBwBkIxMcAEDCKDgAIBuZ4AAAEkbBAQDZyAQHAJAwCg4AyEYmOACA\nhFFwAEA2MsEBACSMggMAspEJDgAgYRQcAJB1PtkdPt5lggMASBQFBwBknYrqEIIJDgAgURQc\nAJB1KqpCCCY4AIBEUXAAQNYxwQEAJI+CAwCyTkVVOCw3HJab6RwAAIeOggMAsk5FtfENACBp\nFBwAkHUqqryAAwBIGgUHAGQdExwAQPIoOAAg65jgAACSR8EBAFnHBAcAkDwKDgDIOiY4AIDk\nUXAAQNYxwQEAJI+CAwCyjgkOACB5FBwAkHVMcAAAyaPgAICsY4IDAEgeBQcAZJdde8LHu0xw\nAABJo+AAgOxSURVCMMEBACSNggMAsktFdQjBBAcAkDQKDgDILukJjlYmOACAZFFwAEB2qagO\nh+WGw3IznQMA4JBScABAdqmo8nwKAJBACg4AyC4V1d4wCgAkkIIDALKLCQ4AIJEUHACQXUxw\nAACJpOAAgOxiggMASCQFBwBkFxMcAEAiKTgAILuY4AAAEknBAQDZxQQHAJBICg4AyC4mOACA\nRFJwAEB2McEBACSSggMAssiuPeHjT0xwAAAJpOAAgCxSWR1SwQQHAJBACg4AyCIVVSEEExwA\nQAIpOAAgi1RUh2CCAwBIIgUHAGSRiqqQ3zA0zs10DgCAQ03BAQBZxFeoAABJpeAAgCxSUeUF\nHABAMik4ACCLvF9lggMASCYFBwBkkYpqExwAQDIpOAAgi1SY4AAAEkrBAQBZxAQHAJBUCg4A\nyCImOACApFJwAEAWMcEBACSVggMAsogJDgAgqRQcAJBFTHAAAEml4ACAbFGzJ3z8iQkOACCZ\nFBwAkC0qqkMqmOAAAJJJwQEA2aKiKoRgggMASCYFBwBki4rqEExwAAAJpeAAgGxRURXyGoYm\njTKdAwDgK6DgAIBs4StUAIAEU3AAQLaoqPICDgAgsRQcAJAtTHAAAAmm4ACAbFFRFVqZ4AAA\nEkrBAQDZoqLaIyoAQGIpOAAgW1RUeUQFAEgsBQcAZAsTHABAgik4ACBbmOAAABJMwQEA2cIE\nBwCQYAoOAMgWJjgAgARTcABAVqjZE3Z8YoIDAEgsBQcAZIXK6pAKJjgAgMRScABAVqioDiGY\n4AAAEkvBAQBZoaIqBBMcAEByKTgAICtUVIe8hqFJo0znAAD4aig4ACAr+AoVACDZFBwAkBUq\nqr2AAwBIMgUHAGQFExwAQLIpOAAgK5jgAACSTcEBAFnBBAcAkGwKDgDICiY4AIBkU3AAQFYw\nwQEAJJuCAwCyggkOACDZFBwAkBXeN8EBACRaBAVHVVXVT37yk8LCwvz8/COPPHLmzJk1NTVf\nvH5RUVHHjh2/toQAUP9VVJngAACSLDfTAb7cZZdd9swzz8yYMaNr167Lly//z//8z127dt10\n002ft/7UqVO3bNnStm3brzMkANRnNXvCjk9McAAASVbfJzgqKyufeOKJWbNmXXbZZX379p0y\nZcp55523cOHCz1v/1VdfnTNnztixY7/OkABQz1VWh1QwwQEAJFl9n+AoKCioqKjYe0lubm5u\n7r5j79mz58orrywpKencufPjjz/+tQQEgAhUVIcQTHAAAElW3yc4alVVVW3btu2ee+559NFH\nJ0+evM917r777i1btkybNu1rzgYA9daHO8NP/ydc9mgIIdy2PKx/P9OBAAC+GvV9gqPW4MGD\nn3/++ZYtW/76178eOXLkZ1coKyubMmXK/fff36xZs/3c55/+9KcXXnhhnx9t2LBh9+7ddY8L\nAPXAi1vDuf8dmueFHu1Dw5zwxnvh2NJwx9mhpDjTyQCAyO3evfs3v/nNs88+u89PTz311KFD\nh37NkaIpOObOnVtWVvbMM8+MGzeusrKypKTkUytMnDixb9++I0aM2P99bt68+eWXX97nR9u3\nb0+lUnWPCwCZVl0T/mNBGPytcPf3wsLXw/9sDM+ODQ+8EsYvDr07hp7tM50PAIhZKpVav379\n++/vezq0c+fOX3OeEFHBcdxxxx133HGDBg1q3rz55MmTx4wZ07Rp09pPly5dumzZsldfffWA\n9nnVVVddddVV+/xo2bJlw4cPP6jEAJBRf/572P7PMGdwyGsYKqr/9QKOcT3DvP8X7n8lzD47\n0/kAgJjl5ubOmDHjrLPOynSQ/1Pf38GxdevWefPm7dixo3ZJjx49qqqqNm/evPdqCxYs2LFj\nR5cuXdKvIJ08efLWrVtzc3PnzJnztUcGgHrhjfdC9zahWV4IIXy48/++QuWUDuGN9zKYCwDg\nK1HfJzi2bds2ZsyY+fPnf//7308vWbNmTYMGDQoLC/de7Wc/+9nebx6dP3/+Aw888NRTTx1x\nxBFfa1wAqDca54Ydn/zr5/84JvTu+K+fd3wSGtf3+z8AwAGr73/B+c53vjNo0KCJEyd+9NFH\nxxxzzOrVq3/+859ffvnljRs3DiGUlpb+7ne/W7FiRYcOHTp06FC7Vfv27XNzc4899tjMBQeA\nDDu1c5j4eHi1PBzXNhxVEI4qCCGE6pqw+M3wg5MzHQ4A4FCr7wVHCOGRRx65+eabb7311vff\nf7+wsHDy5Mk33HBD+qNNmzatXLkys/EAoH46oX0479vh3P8Ovxke+heGEMLblWHCkrAnFa78\nTqbDAQAcavX9HRwhhGbNmt1+++1lZWU7d+5ct27dtGnT0uMbIYSZM2fW1NR8dpNJkyZt2bLl\n640JAPXOb0eEQV3CGb8NbWaFotmhaHbYuTs8PTZ8Iz/TyQAADrUIJjgAgLpp2ij81znh+lPD\n6nfCP3eFY9uG73g5FQCQUAoOAEi42hdwAAAkWASPqAAAAAB8MQUHAAAAED0FBwAAABA9BQcA\nAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0F\nBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQ\nPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAA\nABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUH\nAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9\nBQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAA\nED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcA\nAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0F\nBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQvxT7cs8992T6vwwAAADUX/fcc0+m\n/+3+b3IzfULqqU6dOjVq1Gjp0qWZDlJ3ixcvXrx48X333ZfpIHV37733bt68+ac//Wmmg9Td\n1KlT27Zte9VVV2U6SN0NGTKkuLh42rRpmQ5Sd8OGDZsyZUqvXr0yHaSOKisrL7zwwvvuu6+w\nsDDTWepo7dq111xzzdKlSxs1apTpLHV0xx13LF269Mknn8x0kLqbP3/+mjVrbr/99kwHqbtZ\ns2aFEK677rpMB6m7H/3oRyeeeOIll1yS6SB1d9ZZZw0ePHjSpEmZDlJHu3btGjJkyOzZs7t3\n757pLHW0cePG8ePHL1iwoKCgINNZ6mjlypXTp09fvHhxpoPU3c0337x69eqo/6VQWlpaXl4+\nderUTAepu5tuuqlTp05XXnllpoPU3fjx44cNGzZs2LBMB6m7IUOGdOrUKdMp/o2CY98aNGjQ\noEGDgQMHZjpI3a1bt+7pp5+O+hCWLVtWVVUV9SGUlpZ27tw56kPIzc1t37591IfQsGHDnj17\nxnsI5eXlIYTevXvH+9fxpk2bhhAGDBiQn5+f6Sx1tHDhwthvCn/5y182bNgQ9SE89NBDIYSo\nD6Fly5ZFRUVRH0JOTk7U97WdO3eGEE466aTevXtnOksdrV27NoTQr1+/tm3bZjpLHVVXVzds\n2DDe/4tCCKWlpbm5uVEfwpIlS0LkV9TZs2cXFhZGfQhNmzbt1q1b1IeQ/ldzplP8m/qVBgAA\nAKAOFBwAAABA9BQcAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0cjMdoJ7q1q3b\nuHHjMp3ioBQXF19wwQWZTnFQ+vXrd9RRR2U6xUE5++yz4/2a+rRevXoNHjw40ykOypgxY7p3\n757pFHVXUFAwevToDh06ZDpI3RUVFY0bNy4vLy/TQepu0KBBq1evznSKg3Lqqac2adIk0ykO\nysCBAzMd4WANHTr0hBNOyHSKg3LiiScOGjQo0ynqLi8vb9y4cUVFRZkOUncdOnQYPXp0QUFB\npoPUXffu3ceMGZPpFAdl8ODBlZWVmU5xUE477bTy8vJMpzgogwcP7tSpU6ZTHJQLLriguLg4\n0ykOyrhx47p165bpFP8mJ5VKZToDAAAAwEHxiAoAAAAQPQUHAAAAED0FBwAAABA9BQcAAAAQ\nPQUHAAAAED0FBwAAABA9BQcAAAAQPQUHAAAAED0FR5Lt3r37xhtvbNCgwR133JHpLAdszpw5\nXbp0yc/P79at27x58zId54BFffKBRIr6uuSmAHBoxXtdiv2OEGI++fVfbqYD8FUpKyu7+OKL\ny8vLGzZsmOksB+zee+/98Y9/fNttt51yyinPPPPM2LFjW7RoMWzYsEzn2l9Rn3wgkaK+Lrkp\nABxa8V6XYr8jhJhPfhQUHIn10EMPtWnTZsmSJa1bt850lgOTSqWmT59+9dVXX3fddSGEfv36\nvf7667fddltEV654Tz6QVPFel9wUAA65SK9LCbgjhGhPfiw8opJYI0eOXLBgQbNmzTId5ICt\nX79+48aNw4cPr10ydOjQVatWffjhhxlMdUDiPflAUsV7XXJTADjkIr0uJeCOEKI9+bFQcCRW\nx44dMx2hjtatWxdC6NKlS+2S9M/r16/PWKYDFO/JB5Iq3uuSmwLAIRfpdSkBd4QQ7cmPhYKD\neiddwX7jG9+oXdK8efPa5QBkFTcFANLcEfhS3sGREDU1NTt27Ej/nJeX16RJk8zmASCD3BQA\nqOWmQPYwwZEQTz31VMv/ddVVV2U6zkEpKCgIIXzwwQe1SyorK2uXA/Cl3BQAqJWYm4I7Al/K\nBEdC9OrVa/ny5emf27Vrl9kwB+noo48OIaxfv75z587pJW+++WbDhg3TywH4Um4KANRKzE3B\nHYEvpeBIiIKCgj59+mQ6xaHRpUuXrl27/vGPfzzjjDPSSxYtWtS/f3/TdAD7yU0BgFqJuSm4\nI/ClFByJtWbNmvTrdvbs2fPWW28999xzIYRevXoddthhGU62H2688cbLL7+8Y8eOvXv3XrJk\nydKlS59++ulMhzoAUZ98IJGivi65KQAcWvFel2K/I4SYT34UclKpVKYz8JXo1avXiy+++KmF\nGzZsOPLIIzMR54CVlpb+4he/2LJlS9euXadNm3b++ednOtEBiP3kA8kT+3XJTQHgEIr6uhT1\nHSFEfvLrPwUHAAAAED3fogIAAABET8EBAAAARE/BAQAAAERPwQEAAABET8EBAAAARE/BAQAA\nAERPwQEAAABET8EBAAAARE/BAQAAAERPwQEAAABET8EBAAAARE/BAQAAAERPwQEAAABET8EB\nAAAARE/BAQAAAERPwQEAAABET8EBAAjPh4kAAAmsSURBVAAARE/BAQBwwEaOHJmTk7Nly5ZM\nBwEA/kXBAQBZav78+Tmf78477zwkv2XmzJlvvfXWIdnV3tLhp06desj3DABEKjfTAQCATDrl\nlFN69er12eU9e/Y8+J2XlZXdcMMNPXv2/Na3vnXwewMA+AIKDgDIamefffZXNwfx0ksvfUV7\nBgD4FI+oAABfZNWqVSNGjGjdunVeXt6RRx45evTot99+e+8Vtm3bNn78+A4dOjRt2rRHjx6z\nZ8+uqakJIXzve98bPnx4CGHw4ME5OTkrVqxIr79x48ZLL720Q4cOeXl5rVu3HjZs2KpVq2r3\nln63RXl5+Zlnntm4cePFixfXOfk//vGPq6++urCwMC8vr02bNueee25t4dKnT58GDRq88847\ne6+/ZcuWBg0a9O/f/0s3/5SdO3fOmjWrR48eLVq0aN68+fHHHz9r1qw9e/bUOTkAUAcmOACA\nz/Xyyy/379+/VatW11xzTfv27f/+97/fddddTz755Nq1aw8//PAQwrvvvltcXLxjx44xY8YU\nFhY+99xzkyZNevXVV++7774bb7yxVatW8+bNu/nmm0844YTu3buHEDZv3nzyySf/85//LCkp\nOeaYY7Zu3VpaWtqvX7+nnnqqT58+IYS8vLwQwrXXXtuoUaObb765qKiobsnffffdU045pbKy\ncsKECccee+zmzZtLS0v79u27bNmy/v37jxo16oUXXli4cOEPfvCD2k3+8Ic/pFKpSy655Es3\n/9TvKikpuf/++0eNGlVSUpKTk7Ns2bLrr79+48aNh+o9JgDAfkkBAFlp3rx5IYRbbrnlC9Yp\nLS098cQTn3322dolc+fODSHMnTs3/ceSkpIQwrJly2pXOOecc0IIf/vb31Kp1IwZM0IIjz/+\neO2nY8eODSEsXLiwdsnatWsbNmzYq1ev9B8vu+yyEMKgQYN27959MOFLSkpyc3Nfeuml2iWb\nNm1q3rx5cXFxKpUqLy/Pzc097bTT9t6kd+/e+fn5FRUVX7p5KpW66KKLQgibN29OpVJNmjTp\n3bv33ru69tprzz///Jqami84BADg0DLBAQB8rpKSknSFEULYtWvX7t2704MY6adUUqnUww8/\n3KlTpzPPPLN2kzlz5kyePLldu3af3VsqlVq0aFG7du3OPffc2oXf/va3e/fuvWLFiu3btx9+\n+OE5OTkhhLFjxzZoUPcHaVOp1IIFC44//viOHTtu27YtvbBRo0bf/e53ly1btmPHjjZt2gwc\nOPDPf/5zeXl527ZtQwhbtmxZuXLliBEjCgoKvnTzZs2a7f3rGjVqtHHjxtpdhRBuv/32OocH\nAOrGOzgAIKvdeuut+/ya2FdeeSW9wrx58/r379+yZcu8vLzGjRufccYZIYT0WzbKysq2b9/e\nrVu3dCuRVlRUdPrpp7du3fqzv2vbtm0ffPDBMcccs/f6IYSjjz46hLBu3bpPLamz8vLy9957\nb82aNUf8u2XLloUQNm3aFEK4+OKLd+/evWjRovQmez+fsj+b723atGnvvPNO165dx4wZc//9\n92/duvVgwgMAdWOCAwCy2kknnXTyySd/dnmbNm1CCFOmTJkxY0ZxcfGvfvWro446Kj8//7XX\nXhs/fnx6naqqqhBCfn7+fv6ujz/+OITQtGnTTy1v3Lhx7adpLVq0OOAj2ctHH30UQujZs2f6\nGZlP+eY3vxlCGDFixIQJEx555JErr7wyhPDwww+3bNky/XzN/my+t4kTJx577LFz585duHDh\nvHnzcnJyBg8eXFpaWlhYeDBHAQAcEAUHAGS1IUOGfN7XxFZXV99xxx2dOnV69tlnax/K+OCD\nD2pXaN++fQihsrJyP39Xeid7Fxlp6SXNmzc/sOifr3ZXZ5999hesc8455yxatKiiouLjjz9e\nuXLlFVdckX7F6f5s/ikDBgwYMGDAzp07ly9fPn/+/AcffHDgwIGvvfZaeocAwNfAIyoAwL5t\n27atqqqquLh471dOPP/887U/N23atE2bNq+//vquXbtqF7755pt33nnna6+99tkdtm/fvlWr\nVq+//noqldp7+dq1a3Nycg7ysZS9tWvXrnXr1m+88canypd333137z+OGjWqpqbmscce2/v5\nlP3f/LPy8/MHDhz4wAMPTJgw4a233qp9zAcA+BooOACAfWvXrl1OTk76faJpr7zyyoMPPhhC\nqK6uTi8ZPnz49u3bf/vb39auM3Xq1B/+8Ic7d+4MITRs2DD875Msaeedd15ZWdmjjz669z5X\nrVo1YMCAgoKCQxj+wgsvrK6unjVrVu2Sd9999/jjjx86dGjtkiFDhrRo0eLxxx9ftGhRYWFh\n+ntq93/ztJUrV3bo0CF9Wmql35DaqFGjQ3hEAMAX84gKALBvjRs3Puecc5YsWTJhwoTTTjtt\n7dq1d95550MPPTRs2LDHHnvs97///bBhw2655ZYlS5aUlJT89a9/LSwsfP7555csWTJmzJgT\nTzwxhFBUVBRCmDlz5oYNG/r27XvSSSfdeuutS5YsGT169MSJE48++ui33377rrvuatasWd2+\nduSJJ5747AMyw4cPP/3006dOnfrYY49Nnz69rKysf//+77zzzt133719+/aJEyfWrpmfn3/e\neec9+uijH3744fXXX7/3q0/3Z/O04uLiVq1aXXHFFStWrOjZs2dOTs7q1asfeOCBPn369OzZ\nsw4HBQDUUQa/ohYAyKB58+aFEG655ZYvWKe8vHzUqFFt2rRp0aLFgAEDli9fnkqlbr311mbN\nmrVv376srCyVSr399tuXXHJJ27ZtGzVqVFRU9Mtf/rKmpia9+SeffHL++ec3bty4ZcuWCxYs\nSC/ctGnTpZdeesQRR+Tm5rZt23bkyJFr166t/Y2XX355CGH9+vX7E36fZs2alV6nrKyspKSk\nU6dOubm5BQUFw4YNe/HFFz+1nyeffDK91d4Z9mfziy66KISwefPmVCq1ffv2SZMmdenSpUmT\nJi1atOjRo8f06dM/+uijLz4EAODQykn9+0OwAAAAANHxDg4AAAAgegoOAAAAIHoKDgAAACB6\nCg4AAAAgegoOAAAAIHoKDgAAACB6Cg4AAAAgegoOAAAAIHoKDgAAACB6Cg4AAAAgegoOAAAA\nIHoKDgAAACB6Cg4AAAAgegoOAAAAIHoKDgAAACB6Cg4AAAAgegoOAAAAIHoKDgAAACB6Cg4A\nAAAgegoOAAAAIHoKDgAAACB6Cg4AAAAgegoOAAAAIHoKDgAAACB6Cg4AAAAgegoOAAAAIHoK\nDgAAACB6Cg4AAAAgegoOAAAAIHr/HxWvMwjnKFjCAAAAAElFTkSuQmCC"
          },
          "metadata": {
            "image/png": {
              "width": 720,
              "height": 720
            }
          }
        }
      ]
    }
  ]
}