reproducibility.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "── Attaching packages ─────────────────────────────────────── tidyverse 1.2.1 ──\n",
      "✔ ggplot2 2.2.1     ✔ purrr   0.2.4\n",
      "✔ tibble  1.4.2     ✔ dplyr   0.7.4\n",
      "✔ tidyr   0.8.0     ✔ stringr 1.2.0\n",
      "✔ readr   1.1.1     ✔ forcats 0.2.0\n",
      "── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n",
      "✖ dplyr::filter() masks stats::filter()\n",
      "✖ dplyr::lag()    masks stats::lag()\n"
     ]
    }
   ],
   "source": [
    "#load libraries\n",
    "library(tidyverse)\n",
    "library(stringr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#define helper functions\n",
    "find_library_prep <- function(entry) {\n",
    "  sapply(entry, function(x) {\n",
    "    if (grepl(\"(N)\", as.character(x), fixed = TRUE)) {\n",
    "      \"Nextera\"\n",
    "    } else if (grepl(\"(LA)\", as.character(x), fixed = TRUE)) {\n",
    "      \"Linker amplification\"\n",
    "    } else {\n",
    "      \"Standard\"\n",
    "    }\n",
    "  })\n",
    "}\n",
    "\n",
    "convert_sci_to_label <- function(sci_num) {\n",
    "  format(sci_num, scientific = FALSE)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Parsed with column specification:\n",
      "cols(\n",
      "  Experiment = col_character(),\n",
      "  `DNA source` = col_character(),\n",
      "  Technology = col_character(),\n",
      "  `Starting DNA (ng)` = col_number(),\n",
      "  `Library amplification (# cycles)` = col_character(),\n",
      "  Replicates = col_integer(),\n",
      "  `Raw reads (millions)` = col_character(),\n",
      "  `Raw quality +/-SD (PHRED)` = col_character(),\n",
      "  `Raw length (bp)` = col_character(),\n",
      "  `Failed QC +/- SD (%)` = col_character()\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "#load data\n",
    "article_data <- read_csv(\"article_data.csv\") %>%\n",
    "  mutate(prep = find_library_prep(`Library amplification (# cycles)`)) %>%\n",
    "  within({\n",
    "  `Library amplification (# cycles)` <- as.numeric(stringr::str_replace(`Library amplification (# cycles)`, \"\\\\(.*\\\\)\", \"\"))\n",
    "  `DNA source` <- stringr::str_replace(`DNA source`, \"Tara Oceans \", \"\")\n",
    "  })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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HIDkZiASHIDkZiASHIDkZiASHIDkZhw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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#graph experiment 1\n",
    "ggplot(data = filter(article_data, Experiment == \"Experiment 1\"), aes(x = `Starting DNA (ng)`, y = `Library amplification (# cycles)`)) +\n",
    "  geom_point(aes(shape = Technology), size = 3) +\n",
    "  scale_x_continuous(limits = c(0.001, 10000), labels = convert_sci_to_label, trans = \"log10\") +\n",
    "  geom_text(aes(label = Replicates), hjust = -1, vjust = -1) +\n",
    "  labs(x = \"Starting DNA amount (ng)\",\n",
    "       y = \"Library amplification cycles\",\n",
    "       shape = \"Sequencing technology\") +\n",
    "  ggtitle(\"Experiment 1\") +\n",
    "  theme_bw(base_size = 14) +\n",
    "  theme(plot.title = element_text(size = 18, face = \"bold\"),\n",
    "        panel.grid.major = element_blank(), \n",
    "        panel.grid.minor = element_blank(),\n",
    "        panel.background = element_blank(), \n",
    "        axis.line = element_line(colour = \"black\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YpFtR+QGkn+3JRNnjz56tWrtra2u3bt\nUm5X8ycJoDAQ7MqQxMTEr7/++unTp5UqVWrTpo2RkdHTp0/Dw8NPnTql+EujQ9WrV1+5cmWl\nSpV0PrOKX3/99cOHD7a2tuXLl3/79m2OY86cOTNnzpxy5cp5eHikpqaeOnVq3LhxK1asULyl\nMS0tbdq0aTdu3HB2du7cufPr16+PHz9+8eLFX3/91cHBobB3AdIj1Z+bQnBw8I0bN/T19bN3\nqfOTBFBICHZlyM6dO58+fdq9e/eJEyfq6f3vWfgPHz6EhoYWxubMzMzq169fGDOr8PPzq1Gj\nhrW19dy5c0+ePJl9wMePH5ctW2Zqaurv7y//yyf/EpYtW7ZmzRr5mKCgoBs3brRs2XLevHny\nv1Xnz5+fMWPGqlWrFi5cWAR7AYmR6s9NLj4+fu3atQMGDNizZ0/23nx/kgAKD8GuDLlz544Q\nwsvLS/FnRghhYmLi4eEh/7x58+YtW7YIIVauXLly5UohRMWKFQMDA1NTU/fu3RsWFvb48eO3\nb9/a2tq2aNHC29u7fPnyeax1/fr1CRMm+Pr69unTRz5/WlraH3/8ceTIkdjYWFNT00aNGnl7\nezs5Ocl7z5079/3330+fPt3a2nrTpk1RUVHm5uZffPGFj49PjkcFFJo1a5b3joeHh8fHx/fp\n00dxPOPTTz91d3cPDQ19+PChs7OzECIsLEwIMWTIEMW2mjdvXr9+/bCwsNevX1tbW6v9NQNC\nSPfnJrds2TIrK6vBgwfnGOzy/UkCKDwEuzLE0tJSCPH8+fPcrndp1apVampqYGBghw4dmjRp\nIoQoV66cEOLNmzcbNmxo0qRJ+/btjY2NHzx4sHfv3qtXr/r7+xsaGua2lorMzMxZs2ZduHCh\ndu3a/fr1e/Xq1dGjRy9evLhs2TLF+VAhRFhY2JkzZ5o3b16rVq2LFy8GBgamp6f7+voWZMev\nXbsmhHB1dVVudHV1DQ0NvXbtmjzYvXnzRgihcibLwcHh+vXr169fb9u2bUEKQBkk4Z/b8ePH\nz5w5s3z5ckNDQ22/HgCFhWBXhrRr1+6ff/6ZP3++p6dns2bNPvnkE5X/Nf/kk0/evn0bGBhY\np06djh07KtptbGz27Nljbm6uaDlw4MDixYv/+eefjh075raWiqNHj164cKFt27Y//PCDTCYT\nQnh4eEybNm3p0qVr165VDAsNDV2+fHm9evWEEMnJyd7e3sHBwaNGjSrIn5CnT58KIVT+vsoz\n3JMnT+SLFSpUEELExcV98sknijHPnz8XQsTExGi9aZRZUv25JSYm/s///E+nTp0aNmyo1RcD\noHDxuJMypFWrVqNHj05NTd2wYcOYMWO6dOkyefLk/fv3p6en572ioaGh/M9MRkbG27dvX79+\n3bRpU319/atXr6q/9aNHjwohRowYIf8zI4Ro2rRpkyZN7t69q5ycPDw85H9mhBBmZmZt27b9\n8OGDIn5pJzk5WWQ7sCFflHeJ/5482rp1a0ZGhrzl8uXL8kN9ijGA+qT6c1u1apUQYuzYseoX\nA6AoccSubOnfv3/37t0vXrx4/fr1W7duXbt27erVqwcPHlyxYkXeh8TCwsK2bdt2584dRe4R\nQrx+/Vr9TUdGRlpZWVWtWlW5sUGDBpcvX46KilK016xZU3mAra2tECIpKUn9DWWXlZWV75ge\nPXocPnz41KlTo0ePbtSoUXx8/OnTp52cnB4+fKh8jRSgPun93C5cuHDkyJGZM2fKL/gDUAIR\n7MqccuXKtWnTpk2bNkKIuLg4Pz+/27dv79y5c9CgQbmtcv78+e+//75KlSo+Pj6VKlUyMTER\nQsyZMyctLU397aakpGR/boiVlZX4/w+JmZmZKQ+Qn71SJ5nlQX78IyUlRfkeiJSUFOXNmZiY\nrFy5cvPmzadPn967d++//vUvb29vc3Pz5cuXyy+WArQgpZ9bWlra0qVLmzVrprj/A0AJRLAr\n0+zt7ceNG+fr6xsREZHHX5pdu3YZGhquXLlSEXHev3+fmpqq0bbKlSsnv0FBmbxF5a+Lzsmv\nrnv69GmVKlUUjfIL75RbzMzMfH19la8c/+mnn0S2oxqAdkr7zy0pKen58+fPnz9v3769cnty\ncnL79u2dnZ03btyo3cwAdIhgV9bJ/x/9/fv3youZmZnKY168eGFvb6984Ep+8ZnKJCprqahR\no0Z4eHhMTIzy6aHr168LIapXr17AvchbgwYNdu7cefHixebNmysaL126JO/Kba3ExMTTp09b\nW1sX5ePBIG2l+udmbGzcuXNnlcbDhw8bGBh8/vnn8tO4AIodFw+VIYGBgVevXlU+z/Lx48et\nW7cKIerWrStvsbCwEEK8fPlSeUV7e/vY2Fj5LaJCiPfv369bt055QI5rqZCfvtmwYYOigMuX\nL1+6dMnFxUXlSiCda9asmY2NzYEDB549eyZvuXnz5rlz52rXri1/1omc/Bie3Lt37+bPn5+c\nnKz8ZDtAfdL7uZmZmX2TjbGxsbm5+TfffOPt7a3dtAB0iyN2Zcjly5f9/f1tbGzq1q1raWn5\n9u3biIiIt2/f2tvb9+/fXz7G0dHRysoqKCgoLS3N0tLS3Ny8V69ePXr0CA8P//rrrz///HM9\nPb2TJ09WrlxZ+YROjmupbN3Dw+Off/45efLkmDFjXF1dX716dezYMVNT0ylTphRwv/7888/7\n9++L/z4S9rfffjM1NRVCjBo1Sn5RnZGR0aRJk+bMmTNmzJh27dqlpaWdOHHCwMBg8uTJyvOM\nHDnS3t6+cuXKaWlpN27cSE5O7tixY2G8/QllgVR/burI9ycJoPAQ7MqQSZMmnT59+sKFC/fu\n3YuPjzc0NKxcuXL37t29vLwUD83S19efO3euv79/SEhIampqxYoVe/Xq1bJly5kzZ/7+++/7\n9++3sLBo167diBEjFA+4z20tla3r6ektWLAgMDDw8OHDO3fuNDU1bdmy5dChQ5WPmWnnypUr\nZ86cUSyeOnVK/mHgwIGKvyKtWrVasmRJQEDAkSNH9PT0GjZs6OPjo/zIOiFEjx49wsLCLl68\nqKenV7169e7du3fo0KGAtaHMkurPTR3q/CQBFBJZAe83LF2++OIL+UOYAKhp3LhxBgYGf//9\ndx5j9u/ff/369b59+xZZVUBpd+nSpV9++cXX15ez2NAtrrEDAACQCIIdAACARBDsAAAAJIJg\nBwAAIBEEOwAAAIkg2AEAAEgEwQ4AAEAiCHYAAAASQbADAACQiLL1SrEPHz78+OOPxV0FUJok\nJSVZWVnlOyw0NFT+elAA6khKSiruEiBNZSjYeXh4XLp0KSUlpbgLAUqZfH81t27devny5cuX\nL4umHkAaZDJZbGxscVcBqSlDwS4mJiYtLW3fvn3FXQhQmgwfPlxfXz/vMS4uLl5eXoMGDSqa\nkgAJuHDhwsKFCx0cHIq7EEhNGQp2cpUrVy7uEoDSJN9UJx9jYWHBjwtQn7W1dXGXAGni5gkA\nAACJINgBAABIBMEOAABAIgh2AAAAEkGwAwAAkAiCHQAAgEQQ7AAAACSCYAcAACARBDsAAACJ\nINgBAABIBMEOAABAIgh2AAAAEkGwAwAAkAiCHQAAgEQQ7AAAACSCYAcAACARBDsAAACJINgB\nAABIBMEOAABAIgh2AAAAEkGwAwAAkAiD4i7g/yQlJZ09e/bcuXOPHz9+8+aNlZVVkyZN+vfv\nb2trqzysZ8+emZmZKusuXLiwfv36RVgsAABAiVOCgt2uXbv27t1rbm5eq1YtFxeXqKiow4cP\nh4WFLVmyxMHBQXmkjY2NSoyztLQs2mIBAABKnBIU7KpVqzZ9+nQ3Nzd9fX0hRGZm5oYNG4KC\nggICAqZPn6480tnZecqUKcVUJgAAQAlVgq6x8/DwaNmypTzVCSH09PSGDh2qr69/+/bt4i0M\nAACgVChBR+yyM/gvlfb4+PiAgICkpCRra+umTZvWqlWrWMoDAAAoUUp0sDt37lxqamqTJk1U\n2h8+fPjw4UP55x07drRr127ixImKQ30AAABlU8kNdm/evFm3bp25ubmXl5dyu6enp7u7e6VK\nldLT02/fvr1x48YTJ07Y2toOGTJEZYZffvklMjJSsWhqaiqTyYqidAAAgOJQQoNdSkrKvHnz\n3r59O3PmTJXHnQwePFjxuXnz5k5OTuPHjw8KChowYIChoaHyyFu3bkVERCgWDQwMCHYAAEDC\nSmKwe//+/Q8//PDw4cMpU6a4urrmPbhixYp169a9fPlyTExM9erVlbs2bNigvOji4pL9AXgA\nAACSUYLuipX78OHDvHnz7t27N378+LZt26qzipmZmRAiLS2tkEsDAAAo0UpWsEtNTfXz87t1\n69aYMWM8PDzUWSUjI+P+/ftCCDs7u0KuDgAAoEQrQcHu48ePCxYsuHHjxsiRIzt16pTjmJs3\nb7548UJ5ld9++y0uLq5evXpWVlZFVSkAAEBJVIKusdu6dWtERISlpWVkZOTy5cuVuyZOnCi/\n7+Hs2bPBwcGOjo52dnbp6elRUVEJCQkVKlTw9fUtpqoBAABKihIU7JKSkoQQCQkJx44dU+ka\nP368/DF1bm5uiYmJ9+7du3btWkZGhp2dXZs2bTw9PTlcBwAAUIKC3aRJkyZNmpT3mPr169ev\nX79o6gEAAChdStA1dgAAACgIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAA\nQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCII\ndgAAABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAA\nABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJB\nsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMA\nAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAI\ngh0AAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0A\nAIBEEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBE\nEOwAAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwA\nAAAkgmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwAAAAk\ngmAHAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAH\nAAAgEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAg\nEQQ7AAAAiSDYAQAASATBDgAAQCIIdgAAABJBsAMAAJAIgh0AAIBEEOwAAAAkgmAHAAAgEQQ7\nAAAAiTAo7gL+T1JS0tmzZ8+dO/f48eM3b95YWVk1adKkf//+tra2KiMjIiICAwMjIyP19PTq\n1q07ePBgZ2fnYqkZAACg5ChBR+x27dq1evXqe/fuVatWzc3NzdDQ8PDhw5MmTYqNjVUedv78\n+Tlz5kRHR7dt29bNze369evffvvtgwcPiqtsAACAEqIEHbGrVq3a9OnT3dzc9PX1hRCZmZkb\nNmwICgoKCAiYPn26fMzHjx/XrFljamq6dOlSe3t7IUTHjh1nzJixZs2aX375pTirBwAAKG4l\n6Iidh4dHy5Yt5alOCKGnpzd06FB9ff3bt28rxly5cuX169cdOnSQpzohRO3atT/77LP79+9H\nR0cXQ9EAAAAlRgkKdtkZ/Jei5ebNm0KIhg0bKg9r1KiRogsAAKDMKtHB7ty5c6mpqU2aNFG0\nyK+3c3BwUB4mP3qncikeAABAWVOCrrFT8ebNm3Xr1pmbm3t5eSkaU1JShBDlypVTHilfTE5O\nVpnBz8/v/v37ikUzMzM9vRIdZAEAAAqihAa7lJSUefPmvX37dubMmdkfdyKTyRd6vn0AACAA\nSURBVNSZJDo6Wvn6PFIdAACQtpIY7N6/f//DDz88fPhwypQprq6uyl2Kg3OWlpaKRvlhPDMz\nM5V5NmzYoLzo4uKSmZlZWEUDAAAUtxJ3EOvDhw/z5s27d+/e+PHj27Ztq9Irv7pO5XK6HC+8\nAwAAKGtKVrBLTU318/O7devWmDFjPDw8sg/49NNPhRARERHKjfJFeRcAAECZVYKC3cePHxcs\nWHDjxo2RI0d26tQpxzGNGze2trY+cuRIXFycvOXOnTsXLlyoWbOmo6NjERYLAABQ4pSga+y2\nbt0aERFhaWkZGRm5fPly5a6JEyfKb5gwMjIaM2bMf/7zn6lTp7Zs2TItLS00NNTAwGDs2LHF\nVDUAAEBJUYKCXVJSkhAiISHh2LFjKl3jx49XvJHCzc3Nz88vMDDwxIkTMpmsXr16gwcPrl69\nelGXCwAAUMKUoGA3adKkSZMmqTOyYcOGKi+fAAAAQAm6xg4AAAAFQbADAACQCIIdAACARBDs\nAAAAJIJgBwAAIBEEOwAAAIkg2AEAAEgEwQ4AAEAiCHYAAAASQbADAACQCIIdAACARBDsAAAA\nJIJgBwAAIBEEOwAAAIkg2AEAAEgEwQ4AAEAiCHYAAAASQbADAACQCIIdAACARBDsAAAAJELj\nYPf48ePdu3dHREQoWjIzM3/88UcnJycjI6OWLVteuXJFpxUCAABALRoHu1WrVvXt2/f+/fuK\nliVLlsycOTM6OjotLe3s2bP//ve/nz17ptMiAQAAkD+Ng93x48eNjY27du0qX0xPT//ll1+E\nEEuWLAkPD+/bt++bN2/kLQAAAChKGge7J0+eVKlSxcTERL54/vz5ly9ftmvXbtq0aa6uruvW\nrTMxMTl8+LCu6wQAAEA+NA528fHxdnZ2isUzZ84IIbp37y5frFChQq1ataKionRVHwAAANSk\ncbAzNDR8+/atYvH06dNCiFatWilazMzMMjIydFIcAAAA1KdxsKtRo8bdu3flt0ckJCQcO3bM\n3Ny8cePGigFxcXEVK1bUZY0AAABQg8bBrnv37hkZGZ07d166dGn37t1TUlJ69OhhYGAg7331\n6tWjR4+cnJx0XCYAAADyY6DpClOnTt21a1dERMTUqVOFEFZWVnPnzlX07t+/Pysrq02bNjos\nEQAAAOrQONhZWVlduHBh3bp1d+7cqVatmo+PT6VKlRS9t27d+ve//614GAoAAACKjMbBTghR\noUKFadOm5dj1888/F6weAAAAaKlA74rNzMx8/fr1kydPdFUNAAAAtKZlsDt16lTXrl0tLCxs\nbGyqVq2qaF+0aNGwYcNevXqlo/IAAACgLm2C3c8//9yuXbuQkJDk5GSVLgsLiy1btgQFBemi\nNgAAAGhA42B38uTJb775xtjYeN68eQ8ePBgyZIhyb69evYQQBDsAAICip/HNE0uXLhVCrFmz\nZtiwYUIImUym3Ovg4FC5cuW7d+/qqDwAAACoS+MjdmfPnrW2tpanuhw5ODjI30sBAACAoqRx\nsHv79q2jo2MeAzIzMz98+FCAkgAAAKANjYOdlZXV48ePc+tNT0+/d++evb19waoCAACAxjQO\nds2aNYuPjz98+HCOvdu3b3/37l2LFi0KXBgAAAA0o3Gw8/HxEUKMGjXq8uXLKl1HjhyZMGGC\nEGLkyJE6KQ4AAADq0/iu2J49e/bt23fXrl3Nmzd3c3N7+fKlEGL69OmhoaFnz54VQgwfPrxd\nu3Y6LxQAAAB50+Zdsdu2bbO3t//1119DQ0PlLYsXLxZC6Onp+fr6yp+HAgAAgCKmTbAzMjJa\nuXLl5MmT9+zZExER8ebNG3Nz8/r16/fp06dWrVo6LxEAAADq0CbYyTk7O0+dOlWHpQAAAKAg\ntHlXLAAAAEqg/I/YBQcHazFv165dtVgLAAAAWss/2HXr1k2LebOysrRYCwAAAFrLP9g1bdq0\nCOoAAABAAeUf7C5evFgEdQAAAKCAuHkCAABAIgh2AAAAEqFxsIuNjd28ebPinRMqQkNDN2/e\nHBcXV+DCAAAAoBmNg93atWu9vb2jo6Nz7H306JG3t/eGDRsKXBgAAAA0o3GwCw4ONjQ09PT0\nzLG3T58+hoaG2j36DgAAAAWhcbCLjo52dHQ0MTHJsdfExKRatWqPHj0qaF0AAADQkMbBLjEx\n0crKKo8BVlZW8fHxBSgJAAAA2tA42NnY2ERFRWVmZubYm5mZGRUVZW1tXeDCAAAAoBmNg13z\n5s3j4+P//PPPHHt37dr1+vXrzz77rMCFAQAAQDMaB7vhw4cLIUaNGnXo0CGVrgMHDowaNUoI\nMWLECJ0UBwAAAPXl/0oxFd27d+/Tp8/u3bs7duzYuHHjFi1aWFpaJiQknDlz5urVq0IILy+v\nHj16FEKpAAAAyIvGwU4IsW3bNhsbm3Xr1l25cuXKlSuKdj09vbFjxy5dulR35QEAAEBd2gQ7\nY2PjtWvXTp48+a+//rp+/XpiYqKFhUWDBg169+5ds2ZNnZcIAAAAdWgT7ORcXFxmzJihw1IA\nAABQEBrfPJGRkVEYdQAAAKCANA521apVmzVr1sOHDwujGgAAAGhN42D37NmzhQsX1qhR44sv\nvti5c+fHjx8LoywAAABoSuNgt2/fvm7duunp6R05cqRfv36VK1eeNm3anTt3CqM4AAAAqE/j\nYNe9e/f9+/fHxMTIj9u9evXql19+qVOnTuvWrQMCAt6/f18YVQIAACBfGgc7OQcHh++///7+\n/fvHjh0bOHCgiYlJaGjo0KFDK1WqNG7cuIiICN1WCQAAgHxpGezkZDJZ+/btt2/f/uzZs5Ur\nVzZs2DAhIWH16tWNGjVq1qzZunXrkpOTdVUoAAAA8lagYKdgZWXVuHHjRo0aGRj874PxLl68\nOGrUKEdHx9WrV+tkEwAAAMib9g8olnvx4kVAQMCGDRvk90/o6+v36NFj5MiRz58/X7NmzcWL\nF8eNG5eRkTFhwgRdVAsAAIBcaRnsMjMzDx06tH79+qCgoLS0NCFE1apVfXx8fHx8KlWqJB8z\nfPjwbdu2DR48eNWqVQQ7AACAwqZxsIuOjt64ceOmTZtiYmKEEPr6+l27dh09enTnzp319FRP\n7H711Vc///zzzZs3dVMsAAAAcqdxsHN2ds7KyhJCVK5cecSIET4+PlWrVs1jvKWlZXp6uvYF\nAgAAQD0aBzuZTNaxY8fRo0d37dpVX18/3/EBAQEpKSla1QYAAAANaBzsHj58WK1aNfXHazQY\nAAAAWtP4cScENQAAgJJJ42AXGxu7efPm0NDQHHtDQ0M3b94cFxdX4MIAAACgGY2D3dq1a729\nvaOjo3PsffTokbe394YNGwpcGAAAADSjcbALDg42NDT09PTMsbdPnz6GhobBwcEFLgwAAACa\n0TjYRUdHOzo6mpiY5NhrYmJSrVq1R48eFbQuAAAAaEjjYJeYmGhlZZXHACsrq/j4+AKUBAAA\nAG1oHOxsbGyioqIyMzNz7M3MzIyKirK2ti5wYQAAANCMxsGuefPm8fHxf/75Z469u3btev36\n9WeffVbgwgAAAKAZjYPd8OHDhRCjRo06dOiQSteBAwdGjRolhBgxYoROigMAAID6NH7zRPfu\n3fv06bN79+6OHTs2bty4RYsWlpaWCQkJZ86cuXr1qhDCy8urR48ehVAqAAAA8qJxsBNCbNu2\nzcbGZt26dVeuXLly5YqiXU9Pb+zYsUuXLtVdeQAAAFCXNsHO2Nh47dq1kydP/uuvv65fv56Y\nmGhhYdGgQYPevXvXrFlT5yUCAABAHdoEOzkXF5cZM2bosBSUFo8ePdqxY8eBAwfu3bv37t07\nJyenzp07T58+3cbGprhLA0q3xYsXX7p06fLly5GRkVlZWUlJSebm5sVdFIDSROObJ4Dly5fP\nnDkzIyNj4MCB48ePt7W1XbJkSYMGDWJiYoq7NKB0+/777w8fPly1atWKFSsWdy0ASiXtj9ih\nzOratevEiROdnZ0VLT/88IOfn9/ChQvXrl1bjIUBpd29e/ecnZ1lMlm7du3i4uKKuxwApQ9H\n7KAxDw8P5VQnhBg7dqwQ4saNG8VUESAR1atXl8lkxV0FgFKMYAcdePHihRDCwcGhuAsBAKBM\nI9hBB+bMmSOEGD16dHEXAgBAmUawQ0HNmTNn3759vr6+Hh4exV0LAABlGsEOBbJgwYL58+cP\nGjRoxYoVxV0LAABlHcEO2ps1a9bs2bOHDRsWEBCgr69f3OUAAFDW8bgTaGny5MnLly8fNWrU\n2rVruY8PAICSQJtgl5WVtW/fvpCQkAcPHrx79y4rKyv7mIsXLxa4NpRQWVlZY8eO9ff3Hz9+\n/IoVK0h1AACUEBoHu5SUlG7duh07dqwwqkGpMHv2bH9//8qVK9vZ2S1cuFDRbmlpOW7cuGIs\nDCjtduzYERkZKYSIjo4WQixevNjIyEgIMXPmTP4PCoA6NA52fn5+x44dMzQ07N+/f6tWrezt\n7fX0uFCvbHnw4IEQ4unTp7Nnz1Zud3R0JNgBBbFly5ZDhw4pFufPny//MGPGDAMDrpwBkD+N\n/0uxc+dOIcSOHTs8PT0LoR6UAoGBgYGBgcVdBSBBBw8eLO4SAJRuGh9se/LkiY2NDakOAACg\npNH4iJ2NjU2FChUKoxQAAAAUhMZH7L744ovIyMj4+PjCqAYAAABa0zjYzZ0719zcfNKkSenp\n6YVREAAAALSj8anY58+fL1q0aNKkSVeuXBk7dqyLi4u5uXn2YW5ubrooDwAAAOrSONi5u7vL\nP9y8eTOPZ1vk+NTifB08ePDOnTsPHjyIiYnJysry9/d3cHBQGdOzZ8/MzEyVxoULF9avX1+L\nLQIAAEiGxsHO0dGxMOqQ27hx44cPH2xsbMqXL5+YmJjbMBsbG5UYZ2lpWXhVSZXsxJl8x2S1\na1kElQASk++Pi18WgEKicbB79OhRIZTxv2bMmOHs7GxlZbVo0aKzZ8/mNszZ2XnKlCmFVwYA\nAEBpVLIeZd6kSZPiLgEAAKC0KlnBTk3x8fEBAQFJSUnW1tZNmzatVatWcVcEAABQ/LQMdvHx\n8WvXrg0JCblz505SUlL58uXr1KnTpUuXMWPGWFtb67bE7B4+fPjw4UP55x07drRr127ixIn6\n+vqFvV0AAICSTJtgFxoa6unp+eLFC0XLmzdvzp49e/bs2f/5n//Zs2eP4s7ZwuDp6enu7l6p\nUqX09PTbt29v3LjxxIkTtra2Q4YMURnp5+d3//59xaKZmZmensbP7QMAACgtNA52T5486dat\nW0JCgo2NzahRo+rXr+/g4BAbG3vjxg1/f/+4uLguXbrcuHGjUqVKhVGuEGLw4MGKz82bN3dy\ncho/fnxQUNCAAQMMDQ2VR7569erp06eKRVIdAACQNo2D3eLFixMSEjp37vzHH3+oPJr4u+++\n8/LyOnDgwOLFi5cvX667IvNSsWLFunXrXr58OSYmpnr16spdK1euVF50cXHJ/gA8AAAAydD4\nINaBAweMjIy2bNmS/YUT5ubmAQEBRkZGf//9t47KU4uZmZkQIi0trSg3CgAAUNJoHOxiYmLq\n1atna2ubY6+tre2nn34aExNT4MLUlZGRIb+Qzs7Orsg2CgAAUAJpHOwMDQ1TUlLyGJCSkmJk\nZFSAkvJy8+ZN5Zs2Pn78+Ntvv8XFxdWrV8/KyqqQNgoAAFAqaHyNnYuLy6VLlyIiIho2bJi9\nNyIi4u7du82aNdOumqCgoMjISCHEgwcPhBCbN282NTUVQgwdOlSe286ePRscHOzo6GhnZ5ee\nnh4VFZWQkFChQgVfX1/ttggAACAZGge7fv36Xbp0qVevXlu2bGndurVy1+nTp4cOHSofo101\n165dO3/+vGLx3Llz8g99+vSRBzs3N7fExMR79+5du3YtIyPDzs6uTZs2np6eHK7TAm+rBAoJ\nPy4AxUXjYOfr67tt27Zr1661adPG1dW1Xr169vb2cXFxN27cuHjxohCicePGWh8/mzlzZt4D\n6tevX79+fe0mBwAAkDaNg125cuUOHz48dOjQQ4cOXbx4UR7mFDp37rx582YTExPdVQgAAAC1\naPPmiYoVKx48eDA8PDwkJOTu3bvyV4rVrl27S5curq6uOi8RAAAA6tDyXbFCiGbNmml9kwQA\nAAB0jrdsAQAASET+R+yCg4OFEFWqVGnUqJFiMV9du3YtYGUAAADQSP7Brlu3bkKIQYMGbdu2\nTbGYr6ysrAJWBgAAAI3kH+yaNm0qhKhevbryIgAAAEqa/IOdygNNVBYBAABQQnDzBAAAgERo\nHOzGjBmzZcuWPAYsXbp0zJgxBSgJAAAA2tA42Pn7+x8/fjyPAfv37/f39y9ASQAAANCG7k/F\nZmZmymQynU8LAACAvOk+2D158qR8+fI6nxYAAOiWq6urTCZTfkKtk5OTTCYLCwsrxqpQEGq9\nUiwqKioqKkqxGBsbe/To0ezDUlJS/vnnn4cPH7Zo0UJnBQIAAA117do1JCRk9OjRa9euLe5a\nipn8q1As6unpWVhY1K5du0ePHuPGjTM3Ny/G2gqDWsEuICBg3rx5isXDhw8fPnw4j/Hjxo0r\naF0AAKCQde7cuXbt2lWqVCnuQgqdubm5jY2NECI9PT02NjYsLCwsLGz9+vUnTpyQ2O6rFezs\n7Ow+/fRT+eebN29aWlpWrlxZZYxMJitXrlzNmjUHDx785Zdf6rhMAACga35+fsVdQhEZNGiQ\n4uBlamrq+vXrJ0+eHBkZOXr0aOXjeRKgVrD7+uuvv/76a/lnmUzWo0ePzZs3F2JRAAAAhcPY\n2NjX1zc2NnbhwoUHDhx4+fLlv/71r+IuSmc0vnli06ZNPj4+hVEKAAAoStlvnlC4evWqp6en\nnZ2dqanpp59++tNPP338+FFljOJOizt37gwePLhy5coGBgaKy7Hu3bv3008/ff75505OTiYm\nJhUqVHB3d1+2bFlqaqqa80RHR+vr6+vr60dHR2evcP/+/TKZrHLlyhkZGVrse8eOHYUQWVlZ\nDx48UGd3hBD79u3r1q2bvb29kZGRnZ1dz549T506ldu+qPMFFgaNg92wYcNatWpVGKUAAICS\n4NSpU25ubgcPHnR2dnZ0dLx169aMGTM6duz44cOH7IMvXLjg6uq6bds2IYSlpWVmZqa8/fvv\nv58xY8a5c+f09fUbNGhgZWV1/vz5KVOmeHh4ZM92Oc7j6Oj45ZdfZmZmbty4Mfv49evXCyG8\nvb319fW12EdFnerszsePH/v169ezZ8/g4OC0tLR69eqlp6fv27evXbt2P//8c/ZJNPoCdSyr\nAF6+fHnnzp3rOSnItIWkVq1ahoaGxV0FUMp06tSpU6dOeY/Zt2/fmjVriqYeQBpOnDjRtGnT\njRs3FtL8Xbp0EUKMHj0672FNmzYVQgQFBSlaHB0dhRAGBgZ9+vR5+/atvPHMmTO2trZCiOnT\npyuvLh9sbGzctWvX6OhoeePLly/lHwIDA0+cOJGenq4Yf/fu3datWwshfvjhBzXn2bt3rxCi\natWqGRkZyqs8e/ZMX19fJpNFRUVp91V89913QgiZTKYoOI8yJkyYIISoVq3agQMHFDNs3LjR\nxMREJpOdPHlSuy+wMGgT7N6/fz9nzpxq1aoVUl4sJAQ7QAsEO6AwlPBgV7Fixffv3yuP3Lp1\nqxDCzMwsISFBZbCLi0tqaqqahcXGxsoTknJjHvOkp6fL79f8+++/ldsXLlwohOjQoUO+W8z+\nVSQnJ69YscLQ0FAIofzft9zKiIqK0tfXNzAwCA8PV5lc/syQLl26qEyi5hdYGDQ+FZuamtq+\nfXs/P7/Hjx/LvxQrKyvFUVADAwMbGxv5HcUAAKA0Gj16tImJiXJL//797ezskpOTs19V5uPj\nY2RklOM8Hz9+DA4Onj179siRIwcPHvzVV19NmzbN0NDw8ePHr169UmcefX39ESNGiP+eeJXL\nysqSn5xV/6L/bdu2ValSpUqVKvb29ubm5hMnTkxLS3N2ds7+nL/sZezZsycjI8PNzc3V1VVl\n8KBBg4QQJ06cUDmxq9EXqFtq3RWrbNWqVWFhYe3atduxY8e0adO2b9/++vXrtLS0CxcuLF68\nOCQkZM6cOfIjlgAAoDRSPONMwcDAoFatWi9evLh9+3a3bt2Uuxo2bJjjJGFhYf3798/xvgch\nRHx8vPzsZL7z+Pj4LFy4MCgo6MWLF3Z2dkKIEydOREZG2tra9uzZU809Sk5OTk5OFkLIZDL5\nA4q7des2fvx4CwsLlZHZy4iIiBBCvHz5ctiwYSpdWVlZ8skTEhKsra0V7Rp9gbqlcbDbuXOn\nTCZbv369vb29otHQ0LBly5b79u2bMGHCpEmT6tSp06FDB53WCQAAikjFihVza0xKSlJpz/E9\novHx8V26dHn9+rWXl9e4cePq1KljaWlpYGAghLC2tn7z5k1aWpo68wghqlat2qlTp+Dg4ICA\ngGnTpon/Hr0bOnRobkcKs1P/JRzZy3jz5o0Q4u7du3fv3s1trZSUFOVgp9EXqFsan4q9ffu2\no6NjjRo1hBAymUwIoXyb8U8//WRubr5s2TIdlggAAIrS8+fPc2tU83XwO3fufP369WeffbZj\nx47WrVvb2trKU11aWlpiYqKm9YwePVoIsWHDBiHEmzdv9uzZIzQ5D1tA8teOffvtt3lc2aby\n+oqCf4Fa0+YaO8Vz/IyNjYUQCQkJil5TU9O6detevHhRV/UBAIAiduvWLZWWjIyMe/fuCSHq\n1Kmjzgzyg1utWrXS0/v/ksaFCxe0eOxc586dq1ateufOndDQ0G3btn348KFVq1a1a9fWdB7t\n1K9fXwgRGhqq/ioF/wK1pnGws7e3lx+TFEI4ODgIIW7fvq084OXLl2/fvtVJcQAAoOj5+/ur\nPGouMDDwxYsX5cqVa9OmjTozyA/9PHv2TKV98eLFWtSjp6cnPz63fv16+XG7kSNHajGPdjw9\nPfX09M6ePfvPP/+ouUrBv0CtaRzsatSoERsbK7/7o3nz5kKIVatWKW4GCQoKioqKyvtJKAAA\noCR79erV0KFDFVeDhYWFTZ48WQjh6+tboUIFdWaQx5fdu3cHBQXJW96/fz9x4sSQkBD5OVlN\njRgxQl9ff/v27RERERUqVOjbt68Wk2jHxcXF19dXCNGnT59t27alp6crumJjY3/99ddFixap\nrKLmF7h8+XInJyd3d3cdVqtxsPviiy+Sk5PPnTsn/+zo6PjHH3+4u7tPnTp1wIABvXv3Fv+9\n+xcAABSjLVu22OakSZMmea+4cOHCvXv3Ojg4uLm51alTx93d/eXLl23atJE/tk0dnTt37tCh\nQ3p6evfu3WvUqOHu7l6xYsWVK1f+8ssvakZDFZUrV+7atas8VH311VempqZaTKK1pUuXent7\nJyQkDB482Nra2tXV9bPPPqtSpUqlSpV8fX3v3LmjMl7NLzAhISE6OjomJkaHpWoc7Hr37u3p\n6fn06VMhhJGRUWBgoJWV1YULF5YuXRoYGJient6xY8fvv/9ehyUCAAAtfPjwIT4nr1+/znvF\nNm3ahIWFffHFF1FRUQ8fPqxdu/aPP/54+PBh9eOUTCbbv3//rFmzatSoERMTc//+fXd39wMH\nDkycOFHr3VGcfi36d9YbGBhs3Ljx2LFjAwYMsLKyunHjxr179ywsLHr16rVhw4bsbxUr+Beo\nNZn8ESwFER8fv3Pnzrt37xobG7dt27ZTp07yu2VLGhcXl4cPHxbNK3gByejcubMQ4u+//85j\nzP79+589ezZmzJiiKgoo9U6ePDl16lRfX19vb+/irqXU2Lhx44gRI1xdXcPDw4u7llw5OTlF\nR0efO3fOzc2tWArQ5jy3Chsbm7FjxxZ8HgAAgNzIH0Q3atSo4i6kRNP4VCwAAEAR2759e3h4\nuI2NzcCBA4u7lhJN4yN2sbGxhw4d+uSTT1q1apW9NzQ09MGDBx07dlR+LwUAAIAWHj9+PGTI\nkISEBPl7vebNm2dmZlbcRZVoGh+xW7t2rbe3d26vfnv06JG3t7f8GTMAAAAFkZKScvLkyZs3\nb37yySfLly+XP3YEedA42AUHBxsaGnp6eubY26dPH0NDw+Dg4AIXBgAAyrratWtnZWWlpaXd\nv3+/IHfUFplHjx5lZWUV150TQotgFx0d7ejoaGJikmOviYlJtWrVHj16VNC6AAAAoCGNg11i\nYqKVlVUeA6ysrOLj4wtQEgAAALShcbCzsbGJiopSvENMRWZmZlRUlLW1dYELAwAAgGY0DnbN\nmzePj4//888/c+zdtWvX69evP/vsswIXBgAAAM1oHOyGDx8uhBg1atShQ4dUug4cOCB/bOCI\nESN0UhxKrMWLF/fr169mzZp6enoymezdu3fFXVERKbM7jiLw6NGj//znP23atLG3tzc3N69X\nr963335bdq5s4ccF6ITGz7Hr3r17nz59du/e3bFjx8aNG7do0cLS0jIhIeHMmTNXr14VQnh5\nefXo0aMQSkUJ8v3335cvX75x48bv3r2Li4sr7nKKTpndcRSB5cuXr1y50t3dfeDAgcbGxufO\nnVuyZMn27dvDwsKqVq1a3NUVOn5cgE5o80qxbdu22djYrFu37sqVK1euXFG06+npjR07dunS\npborDyXUvXv3nJ2dZTJZu3btytR/gsvsjqMIdO3adeLEic7OzoqWH374wc/Pb+HChfI3KUkb\nPy5AJ7QJdsbGxmvXrp08efJff/11/fr1xMRECwuLBg0a9O7du2bNmjovESVQ9erVi7uE4lFm\ndxxFwMPDQ6Vl7Nixfn5+N27cKJZ6ihg/LkAntAl2ci4uLjNmzNBhKQAAZS9evBBCODg4FHch\nAEoNjW+eAAAUjTlz5gghRo8eXdyFAP+fGzduyGQymUyW/VUQ/fv3l8lkDx480NW2jh49KpPJ\nVq1apasJJU/7I3YAgMIzZ86cffv2+fr6Zj9FC2ghdfqEfMcY/7RSozn93LVhQgAAIABJREFU\n/f2/+eabKlWqaFsUdC//YDd37lwhRN26db28vBSLaq4FANDCggUL5s+fP2jQoBUrVhR3LUDO\nnJ2dHz58OH/+fH9//+KuBf8n/2A3b948IYSnp6c82MkX80WwAwDtzJo1a+HChcOGDduwYYOe\nHhfMoIRq06aNo6Pjpk2bpk+fnve9L9u3b1+9evX169czMjLq1as3YcKEr776SgiRkZHRpk2b\n8+fPnzlzpnnz5vLBDx8+bNCgQcWKFSMiIpYsWSJPHePHjx8/frwQwtHRUfE++tymFUIEBwd3\n69Zt06ZN5cuXX7Ro0Y0bN7p06bJ79+7379+vXr06ODj47t278fHxlSpV6tat27x586T0xqz8\ng5388o4mTZooWmrVqtW+fftCLAoAyqrJkycvX7581KhRa9eulclkxV0OkJf58+e3bt3az89v\n8+bNuY2R/yvt6uo6cuRImUx26NChwYMH379/f968efr6+gEBAQ0bNhwyZMiVK1fKlSuXmZk5\ndOjQlJSUgIAAMzOznj17pqSkLFmy5Kuvvvr3v/8thDA3N893WsWm9+zZ8/fff3/++eeDBw+2\ns7MTQjx//nzWrFmff/65l5dXuXLlrl69unr16pMnT4aHhxsbGxful1VU8g922Z+f5O7uXhYe\nqgQARSkrK2vs2LH+/v7jx49fsWIFqQ4lX6tWrb788stt27Z99913Li4u2QccOXJk+fLl8+bN\nk98JJIRYvHixp6fnwoULvb29nZycatSosXTp0tGjR3/77berVq365ZdfTp8+PWPGjBYtWggh\nGjVq9OrVqyVLljRv3nzYsGHqTytvDA4ODgkJ6dSpk2JFBweH2NhYKysrRcumTZuGDx++Y8cO\n5flLtfyDXf/+/evXrz9z5swiqAalxY4dOyIjI4UQ0dHRQojFixcbGRkJIWbOnCntv0ZldsdR\nBGbPnu3v71+5cmU7O7uFCxcq2i0tLceNG1eMhRUNflyl1Pz58w8dOvTDDz8EBgZm7/X39zc3\nNx8+fLjyQ6f79++/b9++o0eP+vj4CCFGjRq1f//+X3/9tUaNGrNnz27QoEG+F32pM60Qonv3\n7sqpTghhbGwsPzKXnp6ekJCQnp7u4eFhYGBw4sSJMhTs/vjjj1evXhHsoGzLli3KLwueP3++\n/MOMGTMMDKR8q3WZ3XEUAfkTIp4+fTp79mzldkdHx7IQ7PhxlVLNmjXr3r37zp07Z86cWb9+\nfZXeCxcuvHv3Lsd34sXGxio+r1+/vl69elOmTDEyMtq6das80+dBzWkV1+0pCwkJWbhwYXh4\neHp6eo5rlXb5/1r09PQ+fvxYBKWgFDl48GBxl1A8yuyOowgEBgbmeMyjjODHVXrNnz8/KCho\nzpw5f/31l0rXmzdvqlSpsm7duuxrffLJJ4rP9vb2zZo1O3jwYIsWLRo0aJDvFtWfVqX377//\n7tatW61atX788ccaNWqUK1dOCNG7d+/U1NR8N1pa5B/s7Ozsbt68mZSUVL58+SIoCAAAlCIN\nGjTo27fvzp07L168qNJVvnz5Fy9eyE935jHD1q1bDx48aG1tfeLEicDAwP79++e9RTWnzX4S\nf9myZcbGxqdPn/7Xv/4lb3n37t379+/z3lzpkn+w69Sp06ZNm2rXrt28eXN5tj19+rTijuLc\nbNu2TTcFAgCAkm3evHl//vnn7NmzK1SooNzerFmz/fv379+/v3fv3rmtGxMTM378+OrVq588\nedLd3d3X17dNmzaVKlWS9+rr6wshMjIyNJ02t205OTkpUp0Q4tSpUxrNUPLlH+wWLVp09erV\nK1euKA6xRkVFRUVF5b0WwQ4AgDKidu3aAwcO3Lp1q8oD7caOHbt///5vvvnG3d1d+a3HISEh\nLVu2tLS0zMrK8vb2TkpKCgoKqlKlyqZNm7744osRI0YcOHBAPtLGxkYI8eTJE42mza1OR0fH\nkydPPn78uFq1akKId+/eff/997r4AkoQtU7FXrx48fTp0zdv3nz//v20adNcXV379etXBMUB\nAIBSYe7cuTt27FA57tOxY8dvvvlmyZIlderU6d27d6VKlZ4/f378+PHIyMiYmBhLS8uVK1f+\n888/06ZNa926tRDCw8Pj66+/Xr169dq1a8eMGSOEqFu3rp2dnb+/f2pqqp2dnfwm8Xynza3I\nr7/++vDhw82bNx8wYICent7u3bs/+X/t3XlcFXXf//HvgcMui6IsbkdQAbfAJYHcK7zd9VZv\nvQ2Jy8pc0jbLy8stc8ml1C5zrS41tTSzUrE0rVT0SkTSy9QHiijiwqJACsoO5/fH3L9znYv1\nzOEcDgyv51/Md75n5sOZGXk7M9+Zdu1cXFzM/eXUKq1MQojIyEi5n6oL/Pz8bGxsLF0FUM8M\nHjx48ODBVfc5cODApk2baqceQBlOnDjRvXv3rVu3WroQY1y6dKnCMDB58mQpWly/fl2/ff/+\n/c8//7ybm5udnZ1Goxk6dOjWrVsLCwvj4+MdHBw6deqUn5+v6/zkyRM/Pz8nJ6fExESpJTo6\nOiQkxMHBQQih0WiqXaxWq42KihJCbNu2rXzxX375ZZcuXezt7Vu0aPHWW289fvzY1dW1X79+\npvhi6gSVVquVFQRXrFjRpUuXoUOHmjhgmp+/v39SUhIjfAFZhgwZIoT48ccfq+hz8ODBlJQU\n6b/XAAxx8uTJWbNmvfbaa5MmTbJ0LVAU2Q8HmjNnjjnqAAAAQA1VH+wOHTokhGjZsmVQUJBu\nslrDhg2rYWUwN9WJf1bbR9u/Vy1UUssa7C+OWlPtPqbUHYyDC7C46oPd8OHDhRDh4eHSQFdp\nslpyr/ACAACghqoPdt27dxdC6AYwS5MAAACoa6oPdmUeJF3+udIAAACoC6wsXQAAAABMg2AH\nAACgEIaOipWLUbEAAAC1zNBRsXIxKhYAAKCWGToqFgAAAHWc7FGxAAAAqJsYPAEAAKAQst8V\nC8VosC/2abC/OGpNg93HGuwvDoubP3/+smXL4uPjAwIC6tfCTc74YPfo0aPo6Oj4+PicnBxn\nZ+cOHTr07dvX1dXVhMUBAIA66OHDhytWrDhw4MCtW7fUarW3t3dgYOBzzz03depUqcPPP/8c\nFhb2ySefzJgxw7KlNjTGBLu8vLz33ntvw4YNubm5+u1OTk4zZsxYtGiRvb29icoDAAAmoDrx\nz2r7GHjONTMzMyQkJDEx0dfXd8yYMfb29jdu3Dhy5Mi+fft0wQ6WIjvYFRQUDBo0KDo6Wgjh\n4eHh5+fn6emZnp6ekJBw//79lStXxsbGHjlyxNbW1gzVAgAAC1u9enViYuK0adPWr19vZfV/\nN+vn5uZ+//33li0MwojBE2vWrImOjm7WrNmuXbtSUlJOnTq1b9++U6dO3bt3b+fOnU2bNj1+\n/PjatWvNUSsAALC4c+fOCSHeeustXaoTQjg6OoaHh0s/L1q0KCwsTAgxc+ZMlUqlUqnatGkj\nhMjLy/voo4/69+/v7e1ta2vbpk2bmTNnZmVl6RZy6NAhlUq1ffv2I0eO9OzZ08HBoXnz5rNn\nzy4uLtYv4PHjx2+++aaXl5ejo+Mzzzzz66+/lqnQ8BV9++23Tz/9tIODw9ixYw1ceB0n+4zd\njh07hBAHDx4MCQn5jwWp1RMnTvT19e3Vq9eOHTv++te/mqxGAABQZzRr1kwIcfv27fbt21fY\nYdSoUbm5uR9++OHEiROfe+45IUSjRo2EEOnp6fPnz3/22WfHjRvn6Oj4r3/9a8OGDSdPnjx3\n7pydnZ3u44cOHYqKiho8eHCPHj2OHj364YcfFhcXr1mzRppbWlo6fPjwEydOPPvss3379r1+\n/fqQIUN69+6tX4CBK/ruu+9+/PHHZ599NiIiwsPDw8CF13Gyg11SUlJAQECZVKfzzDPP+Pv7\n37x5s8aFAQCAumjcuHG7d++eMGHCm2++OXDgwKCgILX6P+JEUFBQRkbGhx9+GBwc/Je//EXX\n7u3tnZqa2rhxY13Ltm3bXnrppd27d+t3O3DgwIkTJ3r16iWEyM7O7tSp06effrp8+XIpk+3c\nufPEiROTJ0/+9NNPpf5hYWH6Hzd8RYcOHfrhhx8GDx6sazFk4XWc7EuxLi4uVQ99dXV1dXZ2\nrkFJAACg7ho1atSqVavy8vLmzZv39NNPu7i49O/ff/PmzYWFhVV/0M7OTgpbxcXFGRkZaWlp\nzz//vFqtPnHihH638PBwKdUJIVxcXMaOHfvkyZOEhASpZffu3dbW1gsXLtT1f/HFF/38/IxY\n0YgRI/RTnYELr+NkB7vevXtfvnw5JyenwrnZ2dmXL1/u06dPjQsDAAB11LvvvpuSkvLNN9+8\n9dZbgYGBp06dmjZtWt++fQsKCqr+4A8//PDMM884ODg0a9bM29u7devWxcXFqamp+n26deum\nP9miRQshxMOHD6XJP/74o2XLli1bttR1UKlU5S8kGrKi4ODgMp8ycOF1mexgt3DhwuLi4smT\nJ5ffePn5+S+//HJJScmCBQtMVB4AAKiLnJ2dx44du2bNmjNnzty4cSM4OPjs2bO6O+Eq9OOP\nPw4fPjwrK+uDDz749ttvDx8+fPjwYQcHhzKJwsXFRX9Sus5bUlIiTWZnZ0s3+emT7pCTuyIv\nL68yyzFk4XWc7Hvs8vPzFy9ePG/evJMnT06ZMqVjx47S406uXLmyZcuWzMzMZcuW5efnx8TE\n6H+qfqVdAABguDZt2nz88cehoaEnT57829/+Vlm3tWvX2tnZnTp1SheeHj9+nJeXJ2tdLi4u\nDx48KNN4//59I1akUqmMWHgdJzvYhYaGSj+kpaW9//775TtUOB5Wq9XKXREAAKgvpPNqjx8/\nliatra2F3mk2yZ07d9q0aaN/Skx6LK4sTz311M8//3z37l3dBVOtVlvmdJLRKzJk4XWc7GCn\n0WjMUQcAAKgXPvzww549e/bt21d3xis/P3/p0qVC7wKdu7u7EOLu3bv6H9RoNCdPnrx9+3br\n1q2FEI8fP547d67ctU+YMOGnn35avHixbuDqjh07dEMrargiQxZex8kOdrdu3TJDGQAAoH74\n5ZdfZs+e3bx58+Dg4GbNmmVkZERHR2dkZLRp02b27NlSn44dO3p4eGzZsqWgoMDDw8PNzW3G\njBnTp08/evRocHDwhAkTrKys9u3b165duzJ31FUrIiJi27Ztn3322fXr1/v06XP9+vXvv//+\n+eef//nnn3V9jF6RIQuv44x5VywAAKhfDHwPrCE2btz43XffHTly5Pz586mpqba2tu3atZs6\nderbb7+te3ScWq3et2/f7NmzP//887y8PI1GM2PGjJEjR3755ZcrVqzYtGmTu7v7uHHjlixZ\nIg16NZyVldWhQ4fmzZu3Z8+es2fPBgYGHj58+JdfftHPXkavyJCF13GqhnP3m7+/f1JSUrVP\n2QGgb8iQIUKIH3/8sYo+Bw8eTElJ4eXfgOFOnjw5a9as1157bdKkSZauBYoi+3EnAAAAqJuM\nvBR7/PjxqKioxMTEx48fl5aWlu9Q5uHOAAAAMDfZwS4vL2/8+PFRUVHmqAYAAABGkx3sFi5c\nGBUVpVarR40aFRwc7OHhYWXF9VwAAADLkx3sdu/eLYT49ttvR4wYYYZ6AAAAYCTZJ9sePHjg\n5eVFqgMAAKhrZJ+xa9myJddeAQAA6iDZEW306NE3bty4ceOGOaoBAACA0WQHu3nz5vn5+U2c\nOPH27dvmKAgAAADGkX0p1s3NLTo6Ojw83N/ff+jQoe3atWvUqFH5bvPnzzdFeQAAADCUMQ8o\n3rNnz7lz5/Lz87/99tvK+hDsAAAAapnsYLdz58433nhDCOHl5RUYGMhz7AAAAOoI2cFu9erV\nQoh33nnngw8+sLGxMUNJAAAAMIbsYJeQkNCoUaOVK1dyog4AAKBOkR3snJ2dmzRpQqoDAACo\na2Tns/79+yclJeXk5JijGgAAABhNdrBbtGiRWq1+9913S0tLzVEQAAAAjCP7UuyjR49WrFjx\nzjvvnD17dsqUKZU9xy4kJMQU5QEAAMBQsoNdaGio9MO//vWvadOmVdZNq9UaXxQAAADkkx3s\nNBqNOeoAAABADckOdrdu3TJDGQAAAKgpY14pZj5Hjhy5evVqYmLinTt3tFrtli1bvL29y3e7\nePHinj17bty4YWVl1bFjx4iICB8fn9qvFgAAoE6pW4+j27p166+//vrkyRNnZ+fK+pw9e3bh\nwoXJycn9+vULCQm5dOnS7NmzExMTa7NOAACAOqhGZ+wyMjIyMzOLiorKz+rcubMRC5wzZ46P\nj0/jxo1XrFjx22+/le9QWFi4adMmBweHNWvWeHl5CSEGDRo0Z86cTZs2Se86AwAAaLCMCXb5\n+fnLly/fvn377du3K+tj3KjYbt26Vd3hwoULWVlZI0eOlFKdECIgIKBnz54xMTHJyckM7AAA\nAA2Z7GBXUFAwYMCAmJgYIYSNjU1RUVHjxo2zs7NLSkqEEGq12tXV1fRl/n9XrlwRQgQGBuo3\nBgUFxcTEXLlyhWAHAAAaMtn32K1fvz4mJqZ///6pqanjxo0TQmRlZeXl5Z0+fXrEiBFarXbh\nwoUZGRlmKFUIIVJTU4UQZUZUSGfvpFkAAAANluwzdnv37lWpVJ9//rnuYqgQwsbGplevXgcO\nHHj99dfffPPNDh06hIWFmbTO/5ObmyuEcHR01G+UJp88eVKm85w5c+Lj43WTTk5OVlZ1a7BI\n/bVq1arff//9/PnzN27c0Gq1OTk5Fb6ABIAsHFkAakh20ImPj9doNG3bthVCqFQqIYR0EVay\ncuXKRo0arV271oQlliett1q5ubk5ekh1JjR37tyjR4+2atXK09PT0rUAysGRBaCGjLnHrlmz\nZtLPdnZ2QoiHDx+6u7tLLQ4ODh07doyLizNhifp0J+fc3Nx0jdJpPCcnpzKd161bpz/p7+9f\nWlpqpsIamoSEBB8fH5VK1b9//7S0NEuXAygERxaAGpJ9EsvLy+vPP/+UfpbuddO/3CmEePDg\nwaNHj0xSXHnSGsvcTlfhjXcwK19fXwPPmwIwHEcWgBqSHezatm2bmpoqnfoKDg4WQqxfv153\nJiwqKurmzZutW7c2bZU6nTp1EkJcvHhRv1GalGYBAAA0WLKD3cCBA588eXLmzBnpZ41G8/XX\nX4eGhs6aNWvChAmjR48WQoSHh5u+UiGEEF27dm3SpMmxY8d0FymuXr0aGxvbvn17nnUCAAAa\nONn32I0ePTouLu7evXtCCFtb2z179gwZMiQ2NjY2NlbqMGjQoLlz5xpXTVRU1I0bN4QQ0ivC\ntm/f7uDgIISIjIxs3LixtMapU6cuX7581qxZvXr1KioqOn36tFqtnjZtmnFrBAAAUAzZwc7P\nz2/fvn26yZCQkOvXr+/du/fatWt2dnb9+vUbPHiw0feI/PHHH2fPntVNSucFhRBjx46Vgp20\nxsWLF+/Zs+fEiRMqlapz584RERG+vr7GrREAAEAxavSuWIm7u7upTpjNmzfPkG6BgYFlXj4B\nAAAAHu0GAACgEAQ7AAAAhTDBpVg0QLt375aGuSQnJwshVq1aZWtrK4SYN28eT+ECjMaRBaCG\nCHYwxhdffPHTTz/pJpcsWSL9MGfOHLWanQowEkcWgBriXwoY48iRI5YuAVAgjiwANcQ9dgAA\nAApBsAMAAFAI2cGupKTEHHUAAACghmQHu9atW8+fPz8pKckc1QAAAMBosoNdSkrKsmXL2rZt\nO3DgwL179xYWFpqjLAAAAMglO9gdOHBg+PDhVlZWx44dGz9+fIsWLd55552rV6+aozgAAAAY\nTvbjTkaMGDFixIjU1NRt27Zt3br1xo0bq1evXr16de/evSdPnvw///M/Dg4O5igUJlfw19er\n7WO3cl0tVAIoTLUHF0cWADMxclSst7f33Llzr1+//uuvv77wwgv29vanT5+OjIxs3rz5jBkz\nLl68aNoqAQAAUK0aPe5EpVINGDDgyy+/TElJWbduXWBg4MOHDzds2BAUFPT0009/9tlnT548\nMVWhAAAAqJppnmPXuHHjrl27BgUF6V56ExcX9+qrr2o0mg0bNphkFQAAAKhaTV8pdv/+/R07\ndvzjH/+Qxk9YW1uPHDly8uTJ6enpmzZtiouLmzFjRklJyeuvV387FwAAAGrCyGBXWlr6008/\nff7551FRUUVFRUKIVq1avfLKK6+88krz5s2lPi+99NKuXbsiIiLWr19PsAMAADA32cEuOTl5\n69at27Ztu3PnjhDC2tp62LBhU6ZMGTJkiJVV2Qu7EydO/Oijj65cuWKaYgEAAFA52cHOx8dH\nq9UKIVq0aPHyyy+/8sorrVq1qqK/m5tbcXGx8QUCAADAMLKDnUqlGjRo0JQpU4YNG2ZtbV1t\n/x07duTm5hpVGwAAAGSQHeySkpJat25teH9ZnQEAAGA02Y87WbVq1fTp0zMyMsxRDQAAAIwm\nO9ht3rx57969TZs2NUc1AAAAMJrsS7Genp4qlcocpaCW8bZKwEw4uABYiuwzdgMGDEhJSZGe\ndQIAAIC6Q3awmz9/vqOj48yZMwsKCsxREAAAAIwj+1Lsw4cPP/jgg9mzZ7dr12769OkBAQFe\nXl7lL86GhISYqEIAAAAYRHawCw0NlX64e/fu3LlzK+smPcQYAAAAtUZ2sNNoNOaoAwAAADUk\nO9jdunXLDGUAAACgpmQPngAAAEDdRLADAABQCNmXYvVlZGRkZmYWFRWVn9W5c+eaLBkAAABy\nGRPs8vPzly9fvn379tu3b1fWh1GxAAAAtUx2sCsoKBgwYEBMTIwQwsbGpqioqHHjxtnZ2SUl\nJUIItVrt6upq+jIBAABQHdn32K1fvz4mJqZ///6pqanjxo0TQmRlZeXl5Z0+fXrEiBFarXbh\nwoUZGRlmKBUAAABVkR3s9u7dq1KpPv/8cy8vL12jjY1Nr169Dhw4MH369DfffPPYsWMmLRIA\nAADVkx3s4uPjNRpN27ZthRDSm8Ski7CSlStXNmrUaO3atSYsEQAAAIaQHewKCgqaNWsm/Wxn\nZyeEePjwoW6ug4NDx44d4+LiTFUfAAAADCQ72Hl5ef3555/Sz97e3kKI+Ph4/Q4PHjx49OiR\nSYoDAACA4WQHu7Zt26amppaWlgohgoODhRDr16+XJoUQUVFRN2/ebN26tWmrBAAAQLVkP+5k\n4MCBx48fP3PmTK9evQYOHKjRaL7++uukpKTevXunpKTs27dPCBEeHm6GUgEAAFAV2cFu9OjR\ncXFx9+7dE0LY2tru2bNnyJAhsbGxsbGxUodBgwbNnTvXxGUCAACgOrKDnZ+fn3RaThISEnL9\n+vW9e/deu3bNzs6uX79+gwcPlkbLAgAAoDbV6F2xEnd392nTptV8OQAAAKgJ2YMnZsyYMX36\ndN4tAQAAUNfIDnabN2/eu3dv06ZNzVENAAAAjCb7Uqynpye30AEAANRBss/YDRgwICUl5c6d\nO+aoBgAAAEaTHezmz5/v6Og4c+bMgoICcxQEAAAA48i+FPvw4cMPPvhg9uzZ7dq1mz59ekBA\ngJeXV/mLsyEhISaqEAAAAAaRHexCQ0OlH+7evVvFg4i1Wq3xRQEAAEA+2cFOo9GYow4AAADU\nkOxgd+vWLTOUAQAAgJqSPXgCAAAAdRPBDgAAQCGMf1fso0ePoqOj4+Pjc3JynJ2dO3To0Ldv\nX1dXVxMWBwAAAMMZE+zy8vLee++9DRs25Obm6rc7OTnNmDFj0aJF9vb2JioPAAAAhpId7AoK\nCgYNGhQdHS2E8PDw8PPz8/T0TE9PT0hIuH///sqVK2NjY48cOWJra2uGagEAAFAp2ffYrVmz\nJjo6ulmzZrt27UpJSTl16tS+fftOnTp17969nTt3Nm3a9Pjx42vXrjVHrQAAAKiC7GC3Y8cO\nIcTBgwfDw8Otra117Wq1euLEiQcOHND1AQAAQG2SHeySkpICAgIqe2PYM8884+/vf/PmzRoX\nBgAAAHlkBzsXF5eqh766uro6OzvXoCQAAAAYQ3aw69279+XLl3Nyciqcm52dffny5T59+tS4\nMAAAAMgjO9gtXLiwuLh48uTJBQUFZWbl5+e//PLLJSUlCxYsMFF5AAAAMFT1jzuJiYkp07J4\n8eJ58+adPHlyypQpHTt2lB53cuXKlS1btmRmZi5btiw/P9881QIAAKBS1Qe70NDQCtvT0tLe\nf//98u1//etfhRBarbaGlQEAAECW6oOdRqOphToAAABQQ9UHu1u3bpm/DAAAANSU7METAAAA\nqJsIdgAAAApR/aXYQ4cOCSFatmwZFBSkm6zWsGHDalgZAAAAZKk+2A0fPlwIER4evmvXLt1k\ntRgVCwAAUMuqD3bdu3cXQvj6+upPAgAAoK6pPtjFxcVVMQkAAIA6gsETAAAACmH6YNetW7c2\nbdqYfLEAAACoWvWXYuW6fft2ZmamyRcLAACAqnEpFgAAQCEIdgAAAApBsAMAAFAIgh0AAIBC\nEOwAAAAUgmAHAACgEAY97mTq1KmGL/HJkyfGFgMAAADjGRTstmzZYu46AAAAUEMGBbuhQ4ea\nuw4AAADUkEHB7tChQ+auAwAAADXE4AkAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiC\nHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiCHQAA\ngEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAi1pQuQbdSo\nUaWlpWUaly1b1qVLF4vUAwAAUEfUv2AnhHB3dy8T49zc3CxVDAAAQB1RL4Odj4/P22+/bekq\nAAAA6hbusQMAAFCIennGLjMzc8eOHTk5OU2aNOnevbufn5+lKwIAALC8ehnskpKSkpKSpJ93\n797dv3//N954w9ra2rJVAQAAWFb9C3ZjxowJDQ1t3rx5cXFxfHzILHBvAAAbO0lEQVT81q1b\nT5w40bRp0xdffLFMzzlz5sTHx+smnZycrKy49AwAABSr/gWdiIiIdu3aOTo6uri4BAcHL168\n2N7ePioqqqioyNKlAQAAWFL9O2NXhqenZ8eOHc+fP3/nzh1fX1/9WStWrNCf9Pf3L/8APAAA\nAMWof2fsynNychJCcMYOAAA0cPU+2JWUlFy/fl0I4eHhYelaAAAALKmeBbsrV67cv39fN1lY\nWPjpp5+mpaV17ty5cePGFiwMAADA4urZPXa//fbboUOHNBqNh4dHcXHxzZs3Hz586Orq+tpr\nr1m6NAAAAAurZ8EuJCQkOzs7ISHhjz/+KCkp8fDw6Nu375gxYzhdBwAAUM+CXZcuXbp06WLp\nKgAAAOqienaPHQAAACpDsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATB\nDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAA\nQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEI\ndgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAA\nAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApB\nsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMA\nAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAI\ngh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0A\nAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBC\nEOwAAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwA\nAAAUgmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAU\ngmAHAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAH\nAACgEAQ7AAAAhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACg\nEGpLF2CMixcv7tmz58aNG1ZWVh07doyIiPDx8bF0UQAAABZW/87YnT17duHChcnJyf369QsJ\nCbl06dLs2bMTExMtXRcAAICF1bMzdoWFhZs2bXJwcFizZo2Xl5cQYtCgQXPmzNm0adPq1ast\nXR0AAIAl1bMzdhcuXMjKygoLC5NSnRAiICCgZ8+e169fT05OtmxtAAAAllXPgt2VK1eEEIGB\ngfqNQUFBulkAAAANVj0LdqmpqUIIb29v/Ubp7J00CwAAoMGqZ/fY5ebmCiEcHR31G6XJJ0+e\nlOn8+uuvX758WTfp7OxsZVXPgiwAAIDh6lmwk6hUKkO6OTo6Ojs76yYfPnxotooAAAAsr54F\nO93JOTc3N12jdBrPycmpTOcVK1boT/r7+5eWlpq/RgAAAMuoZ5cmpbvrytxOV+GNdwAAAA1N\nPQt2nTp1EkJcvHhRv1GalGYBAAA0WPUs2HXt2rVJkybHjh1LS0uTWq5evRobG9u+fXuNRmPZ\n2gAAACyrnt1jZ2trO3Xq1OXLl8+aNatXr15FRUWnT59Wq9XTpk2zdGkAAAAWVs+CnRAiJCRk\n8eLFe/bsOXHihEql6ty5c0REhK+vr6XrAgAAsLD6F+yEEIGBgWVePgEAAIB6do8dAAAAKkOw\nAwAAUAiCHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAA\nUAiCHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFINgBAAAoBMEOAABAIQh2AAAACkGwAwAAUAiC\nHQAAgEIQ7AAAABSCYAcAAKAQBDsAAACFUFu6gNrj4uJSXFxsY2Nj6ULqKGtrayFESUmJpQtB\nLVGpVFZWVqWlpVqttuqeYWFhVXeIjo7++9//PnPmTNNVpxxWVlYqlcqQ7xmKYeA/p+7u7rVS\nDhqWBhTszp075+rqWlxcbOlC6iIrKyt/f//c3Nzk5GRL14Ja4ubm5u3tnZqa+vDhwyq6qVSq\n559/vupFOTk52dramrQ65WjSpImnp+e9e/eys7MtXQtqiY+Pj52d3dWrV6vu1rRp027dutVO\nSWg4VPwnEkKIwsLCZ555pnv37lu2bLF0Lagl+/fvX7p06fz580eNGmXpWpRs165dH3/88YoV\nK6rNx1CM8PDwpKSk3377zdKFoCHiHjsAAACFINgBAAAoBMEOAABAIRrQ4AlUQaVSdejQQaPR\nWLoQ1B43N7cOHTq4ublZuhCFa9KkSYcOHVxcXCxdCGqPNHjC0lWggWLwBAAAgEJwKRYAAEAh\nCHYAAAAKQbADAABQCAZPNHRHjhy5evVqYmLinTt3tFrtli1bvL29y3e7ePHinj17bty4YWVl\n1bFjx4iICB8fn9qvFmWYcPOZqg8kHFn1GkcW6i8GTzR048aNy8/Pd3d3Lyoqys7OrvDfr7Nn\nz37wwQdOTk69evUqKir65z//KYRYvnx5u3btLFEy/s1Um89UfaDDkVWvcWShHtOiYfv999+z\nsrK0Wu3y5cuHDx+ekpJSpkNBQUFkZOT48eNTU1Ollvj4+JEjR7799tu1XSvKMcnmM1Uf6OPI\nqtc4slB/cY9dQ9etW7fGjRtX0eHChQtZWVlhYWFeXl5SS0BAQM+ePa9fv56cnFwrNaJSJtl8\npuoDfRxZ9RpHFuovgh2qceXKFSFEYGCgfmNQUJBuFuoyQzafqfpAFr7Seo0jC3UWwQ7VSE1N\nFUKUub9E+s+lNAt1mSGbz1R9IAtfab3GkYU6i2CHauTm5gohHB0d9RulySdPnlimJhjMkM1n\nqj6Qha+0XuPIQp1FsINBVCqVpUuA8QzZfKbqA1n4Sus1jizUQQQ7VKPC/ztK/8t0cnKyTE0w\nmCGbz1R9IAtfab3GkYU6i2CHakg3f5S526PC+0JQBxmy+UzVB7LwldZrHFmoswh2qEanTp2E\nEBcvXtRvlCalWajLDNl8puoDWfhK6zWOLNRZBDtUo2vXrk2aNDl27FhaWprUcvXq1djY2Pbt\n22s0GsvWhmoZsvlM1Qey8JXWaxxZqLN4pVhDFxUVdePGDSHE5cuX79+/Hxoa6uDgIISIjIzU\nPZ8zJiZm+fLljRo1kt54c/r0aa1Wu2LFCt54Y3Gm2nym6gMdjqx6jSML9RfBrqFbtmzZ2bNn\ny7dv3LixZcuWukndO6pVKpX0jmpfX99aLBMVM+HmM1UfSDiy6jWOLNRfBDsAAACF4B47AAAA\nhSDYAQAAKATBDgAAQCEIdgAAAApBsAMAAFAIgh0AAIBCEOwAAAAUgmAHAACgEAQ7AAAAhSDY\nAVXp0aOHSqU6dOiQpQuBohQWFrZv375Zs2Y5OTnmXldxcbGfn5+np2d2dra51wXA4gh2sIys\nrKwlS5aEhIQ0btzY1tbWy8srMDAwIiLiH//4R1pamn7PjRs3Llq06ObNm+YrphZWYbRhw4ap\n9Njb23t4eHTp0iUiIuKzzz6r7E+17lMTJkwoPzcjI0Oae/Xq1Qo/Pm/ePKnDihUrTPnLKJFx\nO8+6desSExPnzJnj7OxspsJ01Gr1e++9d//+/SVLlph7XQAsTwvUuri4OA8PD2kPVKvVLVq0\n0E0KIZYsWaLfuVOnTkKIY8eOma+eKlaxYMGC8PDwCxcumG/tVRs6dKgQolGjRhqNRqPRtGzZ\nUj8KODo6rlq1qqSkpMJPCSFUKlX54h88eCDNjY+PL7/GkpIS3WvO/fz8zPWLKYUR+2dmZqar\nq6uHh0dubq75CtNXUlLi7+9va2ublJRUO2sEYCmcsUNty8vLGz169P379zt37nzo0KH8/Py7\nd++mp6f/+eef+/fvnzBhgp2dnaVr/LfFixfv2rUrKCjIsmWEh4ffunXr1q1bd+7cyc7Ovn//\n/jfffNO7d+/c3NzZs2dHRkZW+Clra2utVjt37lxZ6zp69Ojdu3ednJxsbGwSEhL++c9/muI3\nwL9t3br10aNHERERDg4OtbNGKyurSZMmFRYWbtiwoXbWCMBSCHaobUePHr19+7ZarT58+PDQ\noUOtra2ldjc3t5EjR3711VfvvvuuZSus+5o1azZ27Njo6Oh58+YJIXbt2vXpp5+W7zZ+/Hhb\nW9vDhw9HR0cbvvCtW7cKIcaOHTtkyBDdJExFq9Vu2bJFCFFZHDeTiRMnWllZbdu2LT8/vzbX\nC6CWEexQ26S7kVq0aKG73leZ7du3q1SqK1euCCHCwsJ095lNnTpV6pCQkLBy5cpnn322TZs2\n9vb2rq6uoaGha9euLSgoKLOoNm3aqFSqmJiYq1evRkREtGjRQq1Wz5gxo9pVlB88oVvUrVu3\nIiMjvb297ezs2rVrN3fu3Ly8vPK/RUZGxuuvv67RaOzs7Fq1ajV16tS0tLTNmzerVKpRo0YZ\n+SUKIYRQqVRLly597rnnhBDLli0rLS0t08HHx+fVV18VQvztb38zcJlZWVkHDx4UQrz44otS\n8ti7d++TJ08M/LgRW+TatWsvvPCCl5eXo6Nj165dd+3aJXV49OjRnDlz2rVrZ29v37p169mz\nZ1f49ebl5X300UdPP/20q6urg4ODn5/fG2+8cffuXf0+xcXF0mbNyMgo8/H169erVKqxY8dW\nWFvVm7janadCZ86cSUxM9PHx6dKlS2XfiTl2rRYtWnTv3j0zM/PHH3+sojwA9Z6lrwWjwZHO\nAKnV6tTU1Kp7njp1KjIy0s3NTQgxcODAyP9v+/btUocxY8YIIezt7X19fZ9++mmNRqNSqYQQ\nvXv3zs/P11+URqMRQvz97393cnISQjRv3tzd3X3atGnVrqJ79+5CiKioqDKL2rx5s5ubm1qt\n9vPza9KkiXQ0hYWFlZaW6q/39u3bUn9ra+uuXbt269ZNrVZ7e3tLZ9pGjhxZ7dcl3S03ZcqU\nyjro/k7HxcWV+dS8efPS09MbNWokhDh48KBubhX32K1bt04I0bp169LS0sLCwqZNmwohtm3b\nVm2dErlb5JNPPmnUqJGdnZ2/v79UpxBi3bp16enpAQEBKpXK19fX09NTah8xYkSZ1aWnpwcG\nBkpz/f39u3btamtrK4Rwc3M7deqUrltRUZHU58GDB2WW8MknnwghxowZU762ajdxtTtPhaQR\nDBMmTCg/y9y71syZM4UQM2bMqKI8APUdwQ617d69e9JddF26dPnmm28ePXpUdf8qbk7fs2fP\niRMniouLdS3Xrl3r06ePEOK9997T7yn9CbSzsxs2bFhycrLUqPszX8UqKgt29vb24eHhGRkZ\nUuPXX3+tVquFEPv379f/+IABA4QQXbt2vXXrltRy9+7d0NBQGxsbUwW7nJwc6XL2+vXry3xq\n3rx5Wq12/vz50retG2NRRbCT7iacO3euNClFgT59+lRbp8SILfLqq69K+0BJScmsWbOEEK6u\nrs8//3xwcHBiYqLU+fvvv5d+x19//VV/IYMGDRJC+Pj46AaI3L9//7/+67+EEB4eHrqtY1yw\nM3ATyx08ERYWJoRYs2ZN+Vnm3rWks6FPPfWUgaUCqI8IdrCAHTt2SGdWhBBWVlYBAQEvvPDC\n5s2b09LSyneW+4czNTVVOuek3yj9yfT39y8oKJC1isqCXceOHYuKivR7Tpw4UQjxyiuv6Fpi\nYmKEEOWHIqakpDg6Opoq2Gm1Wumc1oIFC8p8Sgp2jx49cnd3F0Ls3LlTmltZsLtw4YLUfvXq\nVanl999/l1oSEhKqLbUyVWyRoKAg/SG9BQUF0u9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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#graph experiment 2\n",
    "ggplot(data = filter(article_data, Experiment == \"Experiment 2\"), aes(x = `Starting DNA (ng)`, y = `Library amplification (# cycles)`)) +\n",
    "  geom_point(aes(color = prep), shape = 15, size = 3) +\n",
    "  geom_text(aes(label = Replicates), hjust = -1, vjust = -1) +\n",
    "  scale_y_continuous(limits = c(0, 25)) +\n",
    "  scale_x_continuous(limits = c(1, 1000), labels = convert_sci_to_label, trans = \"log10\") +\n",
    "  facet_wrap(~`DNA source`) +\n",
    "  labs(x = \"Starting DNA amount (ng)\",\n",
    "       y = \"Library amplification cycles\",\n",
    "       color = \"Library Prep.\") +\n",
    "  ggtitle(\"Experiment 2\") +\n",
    "  theme_bw(base_size = 14) +\n",
    "  theme(plot.title = element_text(size = 18, face = \"bold\"),\n",
    "        panel.grid.major = element_blank(), \n",
    "        panel.grid.minor = element_blank(),\n",
    "        panel.background = element_blank(), \n",
    "        axis.line = element_line(colour = \"black\"))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}