{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Progress report 2\n",
    "\n",
    "*Asura Enkhbayar, 15.06.2020*\n",
    "\n",
    "This report contains a brief summary of the methodology and a few descriptives to assess it. Furthermore, some statistics and plots are generated for the citationa and altmetrics gathered for the current data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "from IPython.display import Markdown as md\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "from matplotlib_venn import venn3\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "from tracking_grants import references_f, articles_f, wos_f, altmetric_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Seaborn styles\n",
    "sns.set_style(\"darkgrid\")\n",
    "\n",
    "# Matplotlib figure configuration fonts and figsizes\n",
    "plt.rcParams.update({\n",
    "    'font.family':'sans-serif',\n",
    "    'font.size': 16.0,\n",
    "    'text.usetex': False,\n",
    "    'figure.figsize': (11.69,8.27)\n",
    "})\n",
    "\n",
    "# Color palette\n",
    "cm = \"Paired\"\n",
    "cp3 = sns.color_palette(cm, 3)\n",
    "cp10 = sns.color_palette(cm, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Methodology"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Input data\n",
    "\n",
    "The input data always comes from the CDMRP database (https://cdmrp.army.mil/search.aspx). The data contains unstructured references and grant IDs for each article in the selected research program."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load references\n",
    "refs = pd.read_csv(references_f, index_col=\"reference_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "**Data from CDMRP database**\n",
       "\n",
       "- Selected research programs: TSCRP, NFRP, PCRP, PRORP\n",
       "- Total number of references found: 9078\n",
       "- Unique references: 8620 => Several articles are in multiple research programs and multiple grants affiliated\n",
       "    - Unique grant IDs: 2227\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keywords = refs.program.unique().tolist()\n",
    "mds = f\"\"\"\n",
    "**Data from CDMRP database**\n",
    "\n",
    "- Selected research programs: { \", \".join(keywords) }\n",
    "- Total number of references found: { len(refs) }\n",
    "- Unique references: { refs.reference.nunique() } => Several articles are in multiple research programs and multiple grants affiliated\n",
    "    - Unique grant IDs: { refs.grant_id.nunique() }\n",
    "\"\"\"\n",
    "md(mds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Matching references to articles\n",
    "\n",
    "From here on, we are using a [reference matcher](https://gitlab.com/crossref/search_based_reference_matcher) developed by Dominika Tkaczyk at Crossref. The algorithm is described to some degree in a blog series: https://www.crossref.org/blog/matchmaker-matchmaker-make-me-a-match/\n",
    "\n",
    "The algorithm is implemented in Java and no longer very well maintained. However, it seems to be working fine. Dominika recommends up to 20 threads (already implemented) and with some workarounds we could also implement progress reports for larger datasets which are not supported at the moment.\n",
    "\n",
    "In our case, I used the 8620 unique references from our dataset and matched 6711 articles. Each matched article also comes with the matching score. In this case, the implementation takes care of thresholds and simply returns Nulls for those references that are not matching (enough)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load matched articles\n",
    "articles = pd.read_csv(articles_f)\n",
    "\n",
    "articles.DOI = articles.DOI.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "**Matching references with Crossref**\n",
       "\n",
       "- Matched articles: 6711\n",
       "- Articles in multiple research programs: 198\n",
       "- Articles funded by multiple grants: 829\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mds = f\"\"\"\n",
    "**Matching references with Crossref**\n",
    "\n",
    "- Matched articles: { articles.DOI.nunique() }\n",
    "- Articles in multiple research programs: { (articles.groupby(\"DOI\").program.nunique()>1).sum() }\n",
    "- Articles funded by multiple grants: { (articles.groupby(\"DOI\").grant_id.nunique()>1).sum() }\n",
    "\"\"\"\n",
    "md(mds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Retrieving metrics\n",
    "\n",
    "Once the the references have been matched to articles in Crossref, we are using the DOIs to retrieve metrics from the Web of Science and Altmetric."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load metrics from WoS\n",
    "wos = pd.read_csv(wos_f,  low_memory=False, index_col=\"DOI\")\n",
    "wos.columns = [x.lower() for x in wos.columns.tolist()]\n",
    "wos.index = wos.index.str.lower()\n",
    "\n",
    "wos = wos.rename(columns={'relative citation score':'citation_score'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load metrics from Altmetric\n",
    "altmetrics = pd.read_json(altmetric_f).T\n",
    "\n",
    "# Filter out all articles had not altmetrics\n",
    "altmetrics = altmetrics[altmetrics.altmetric_id.notna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = [\"last_updated\", \"published_on\", \"added_on\"]\n",
    "for d in dates:\n",
    "    altmetrics[d] = pd.to_datetime(altmetrics[d], unit=\"s\")\n",
    "\n",
    "str_cols = [\"pmid\", \"pmc\", \"altmetric_id\", \"doi\", 'hollis_id', \"arxiv_id\"]\n",
    "for _ in str_cols:\n",
    "    altmetrics[_] = altmetrics[_].astype(str)\n",
    "    \n",
    "metric_cols = {\n",
    "    'cited_by_posts_count': 'posts_count',\n",
    "    'cited_by_rh_count': 'research_highlight',\n",
    "    'cited_by_tweeters_count': 'twitter_accounts',\n",
    "    'cited_by_patents_count': 'patents',\n",
    "    'cited_by_msm_count': 'news_outlets',\n",
    "    'cited_by_feeds_count': 'blogs',\n",
    "    'cited_by_fbwalls_count': 'fb_pages',\n",
    "    'cited_by_qna_count': 'qna_count',\n",
    "    'cited_by_videos_count': 'videos',\n",
    "    'cited_by_peer_review_sites_count': 'peer_reviews',\n",
    "    'cited_by_weibo_count': 'weibo',\n",
    "    'cited_by_gplus_count': 'gplus',\n",
    "    'cited_by_rdts_count': 'reddit_threads',\n",
    "    'cited_by_policies_count': 'policies',\n",
    "    'cited_by_syllabi_count': 'syllabi',\n",
    "    'cited_by_linkedin_count': 'linkedin',\n",
    "    'cited_by_wikipedia_count': 'wikipedia',\n",
    "}\n",
    "altmetrics = altmetrics.rename(columns=metric_cols)\n",
    "metric_cols = list(metric_cols.values())\n",
    "\n",
    "altmetrics[metric_cols] = altmetrics[metric_cols].astype(float)\n",
    "\n",
    "cols_to_keep = metric_cols + dates + str_cols + ['subjects', 'scopus_subjects']\n",
    "altmetrics = altmetrics[cols_to_keep]\n",
    "\n",
    "# Transform all DOIs to lowercase\n",
    "altmetrics.index = altmetrics.index.str.lower()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results in detail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics = articles.drop_duplicates().merge(altmetrics[metric_cols], left_on=\"DOI\", right_index=True, how=\"left\")\n",
    "metrics = metrics.merge(wos[[\"citations\", \"citation_score\"]], left_on=\"DOI\", right_index=True, how=\"left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace articles with 0 citations as NaN\n",
    "metrics = metrics.replace(0.0, np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "\n",
       "**Metrics from the Web of Science and Altmetric.com**\n",
       "\n",
       "- Articles found in WoS: 2688\n",
       "    - Articles with at least 1 citation: 3298\n",
       "- Articles found in Altmetric.com: 3372\n",
       "    - Articles with tweets: 1488\n",
       "    - Articles with FB mentions: 432\n"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mds = f\"\"\"\n",
    "**Metrics from the Web of Science and Altmetric.com**\n",
    "\n",
    "- Articles found in WoS: { len(wos) }\n",
    "    - Articles with at least 1 citation: { metrics.citations.count() }\n",
    "- Articles found in Altmetric.com: { len(altmetrics) }\n",
    "    - Articles with tweets: { altmetrics.twitter_accounts.notna().sum() }\n",
    "    - Articles with FB mentions: { altmetrics.fb_pages.notna().sum() }\n",
    "\"\"\"\n",
    "md(mds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Coverage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_articles = set(articles.DOI.unique().tolist())\n",
    "articles_w_altm = set(altmetrics.index.tolist())\n",
    "articles_w_cit = set(wos.index.tolist())\n",
    "\n",
    "total = len(all_articles)\n",
    "\n",
    "v = venn3([all_articles, articles_w_altm, articles_w_cit],\n",
    "      set_labels=('', '', ''),\n",
    "      subset_label_formatter=lambda x: \"{:,} ({:.1f})\".format(x, 100*x/total));\n",
    "\n",
    "v.get_patch_by_id('100').set_color(cp3[0])\n",
    "v.get_patch_by_id('110').set_color(np.add(cp3[0], cp3[1])/2)\n",
    "v.get_patch_by_id('101').set_color(np.add(cp3[0], cp3[2])/2)\n",
    "v.get_patch_by_id('111').set_color(np.add(np.add(cp3[1], cp3[0]), cp3[2]) / 3)\n",
    "\n",
    "for text in v.set_labels:\n",
    "    text.set_fontsize(10)\n",
    "# for text in v.subset_labels:\n",
    "#     text.set_fontsize(12)\n",
    "\n",
    "handles = []\n",
    "labels=[\"All articles\", \"Altmetric\", \"WoS\"]\n",
    "for l, c in zip(labels, [cp3[0], np.add(cp3[0], cp3[1])/2, np.add(cp3[0], cp3[2])/2]):\n",
    "    handles.append(mpatches.Patch(color=c, label=l))\n",
    "plt.legend(handles=handles);\n",
    "\n",
    "# plt.gca().legend(handles=[v.get_patch_by_id('100'), v.get_patch_by_id('010'), v.get_patch_by_id('001')],\n",
    "#                  , prop={'size': 12});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Disciplines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wos.groupby(\"discipline\").size().div(len(wos)/100).sort_values().plot(kind=\"barh\", color=cp3[0])\n",
    "plt.title(f\"Relative number of articles in WoS disciplines (n={len(wos)})\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = pd.get_dummies(altmetrics['scopus_subjects'].apply(pd.Series).stack()).sum(level=0).melt()\n",
    "pdf.groupby(\"variable\")['value'].sum().div(len(altmetrics)/100).sort_values().plot(kind=\"barh\", color=cp3[0])\n",
    "plt.title(f\"Relative number of articles in Scopus subjects (n={len(altmetrics)})\")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = metrics[metrics.columns.drop('citation_score')].count().div(len(metrics)/100).sort_values()\n",
    "pdf.plot(kind=\"barh\", color=cp3[0])\n",
    "plt.xlabel(\"Coverage [%]\")\n",
    "count_order = pdf.index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TsGFDli1bRpcuXdi4cSOrV6/mj3/8I927d2fbtm0cP34ch8NBcXExcLaefurUqQwbNoyGDRuycePGi/YbGxvL1KlTyc7OxuVy8eqrr9KlSxe6du3K8uXLSU5OJjc3l40bNzJ79myys7M5fPgwpmly7Ngx9u/fX+m+ORwOysrKzrvIEBH5pe5tm1kdgkd4ewItcjkCHQ6aOxuUl/XYbTaaO0MICbzigstV5iO1yeszzoiICMaPH09mZia33HILDz30EPXr1ycpKYnS0lLat2/P1KlTCQoKYsOGDdx9990EBQVx++23ExMTw6lTp3juuedo0qQJTz/9NBMmTCAgIICgoCCmTp160X4jIyN54YUXGD58OIZhcMMNNzBgwADOnDnDlClTSExMxO12M2rUKNq3b09JSQkrVqzgzjvvpGXLlnTq1KnSfUtISKBv376kpKScc1dAROSXNHorUrdEhdbneMEZisrcBDrsRIXWr3C5SG2xmV5cd5KamsqcOXP0rPtfyMkpwDBq9ytzuUJZufNQrfbpD77etgWA67v1sDgS79C/U7Se438Bd8S2UOIvl0SlPt5Bz/GveTq3K2e322jc+OLzTr1+xN+TioqKuP/++y+47oknniAhIaGWIxLxb3pZ1fncv5rXJCJ1gzM4kLioJue9ofdiy0Vqg1cn/l26dKFLly4eaz84OJjVq1d7rH0RuTS1OZKjkSMR8bSLJfdK+sUqPv/mXhERERERUeIvIiIiIuIXvLrUR7yDYZr07xRtdRg+J9Z59s/oaB1bALdbtewiIiKepMRfKmW32Xy2FtrKOm+nM9Lr68y9PT4RERGpOpX6iIiIiIj4ASX+IiIiIiJ+QKU+IhY5ciSNvLwQnM5Iq0MRERERP6DEXyplmCYuV6jVYXiMVfu2Y8e/OHEC+vTx7sm9l3t83G6D3NzTNRyNiIiIXC4l/lIpu83Gyp2HrA7D53yd9iMAxT56bPUkKBEREe+iGn8RERERET+gxF9ERERExA8o8RcRERER8QOq8RcRj/H2SeFWxuc2DHJzNPlZ/EtxmZugAEeNb+uJ/kV8kRJ/EfGYf+xNtzoEr3X7dc2tDkGkVuUVlbAn6ySxEeE4gwNrbFtP9C/iq2os8c/Pz+e5555j3rx5FW6XmZlJcnIy77zzDps2bSI9PZ1HHnmE3bt3s2HDBsaNG1dTIXmNN998k5tvvpmbbrrJ6lBExIt4+x2RX9IdCqkO0zQ5kHMKgIO5p+h0ZWNsNlu1t/VE/yK+rMYS/7y8PL777rtKt4uMjOSdd94B4JtvvilffujQIXJycmoqHK+yY8cOunTpYnUYIuJlth7KsDqEKrs5OqpOXahUlWEY5OiCxuMy8gspNdwAlLgNMvILaRYWUu1tPdG/iC+rscT/lVdeISsri6SkJB599FF69uzJG2+8wTfffMOf/vQnsrKy+H//7/+xYMEChg4dyttvv83SpUsBCA0N5S9/+QuFhYXMnz+fkSNHMmPGDLZv347b7WbAgAEMGzaM1NRUZs6ciWEYtGnThtdee+2CsRQUFPD888+TmZlJVlYWN910EzNmzABg1qxZfPTRRzgcDu6//34efvhh9u3bx6RJkygqKsLpdDJr1iyaNm3KggUL+Pvf/47D4eCWW25h3LhxHD9+nKFDh7Jp0yYAZs+eDcDYsWO59dZbueOOO9i5cycOh4M//OEP7Ny5k71795KcnMycOXPYunUrK1euxG6306FDB1566aWa+gpERDxq99Fsq0OocR2ucnn1BY1pmpc1Mn0p+3S5fVzK512uUNq7DT7YlYZhmqTnFeAKCSbQcW69fYnbTXpeAYZ59ueKtq0qT7QpUlfV2FN9kpOTiYiIoE+fPnzxxRfA2ZHutLQ03G43n376KT169CjfPjo6msGDBzN48GCGDRvGE088Qe/evXnsscdYtmwZACtXrmT58uVs3LiRf/7znwB8//33LFq06KJJP8Ann3xCu3bt+Nvf/saGDRvYtWsX33zzDR9++CFffvkla9as4f333yclJYXs7GyeffZZRo8ezZo1a+jTpw+LFi1i8+bNbNq0iZSUFFauXEl6enr5hcrFZGdn061bN1atWkVcXBzvvvsu/fr147rrruOVV16hdevWvPXWW6xYsYKUlBRsNhuZmZnVPfQiIiJ1imlC9umi85Znny7CNKu2bVV5ok2RuqrGJ/f26tWLxx57jIKCAgBiYmL45ptv2LJlCw899FCV2ti2bRv79u0rv4AoLCxk//79REdH07JlS0JDKx7JuOeee9i9ezd/+ctfSEtL46effqKwsJAdO3Zw1113ERgYSGBgIKtXryY3N5fs7Gzi4+MBGDJkCACvvfYad999N8HBwQAMHDiQVatW0bNnzwr77t69OwBt2rQpv1j5WUBAAB07duR3v/sdCQkJPPjgg0RGRlbpmIiIWK3DVS6rQ6hxvljq43KFkp2db3UY5Urcbv6ZcaJ8xB3AZgNXSPB527pCgknPKzgnUb/YtlXliTZF6qoaT/yvvPJKDMPgH//4BzfeeCNNmjThiy++4JtvvuHGG2/k+PHjlbbhdrsZN24ct99+OwC5ubnUr1+fr7/+ujwRr8iSJUvYsGEDgwYN4uabb+bAgQOYpklAwLm7e+zYMZxO5znLiouLycrKwjCM89otKyvDZrNh/uK3R1lZ2TntBgUFAZy33c/mzZvHrl272LJlC48++iizZs2ic+fOle6TiPiem6OjrA6hyjS5Vy5XoMNBc2eD8nIbu81Gc2fIBctsLmVbT/Qv4utqLPEPCAigrKwMgB49ejB//nxefPFFIiIiGDFiBJ07d8bxq//JHA4HxcXF5X//+fNdu3Zl2bJlxMfHU1JSwpAhQ5g6dWqVY/n888+5//77SUxM5ODBg3z33XcYhkFcXByLFy/mgQceoKysjEcffZT58+fTtGlTPv/8c2655RZWr17N9u3bufvuu5k/fz73338/AQEBrFixgq5duxIWFkZeXh65ubk0aNCATz/9tPxuwcU4HA7cbje5ubkMGTKEFStW0LFjR3788Uf279+vxF/ET3nTqKyIJ0WF1ud4wRmKytwEOuxEhdavkW090b+IL6uxxL9x48ZERUWRlJTEk08+ycKFC+nUqRP169entLSUXr16nfeZuLg4nnvuOZo0acKtt97KnDlzmDVrFk8++STp6en079+fsrIyBgwYQJcuXUhNTa1SLA8//DBTpkzhf/7nfwgJCaFjx44cO3aM++67j7179zJgwAAMw2Do0KG0bNmSmTNnMmXKFGbMmEF4eDgzZswgIiKCffv2MXDgQMrKyujevTsPPfQQAQEBDB8+nN/97nc0bdqU2NjYSuPp3r07kydP5rXXXmPw4MH87ne/o169elx55ZX079//Ug+1SJ2hZ9VfnPsCdxVFfJXNZqNNozD2ZJ2kTaOwCicDX8q2nuhfxJfZzAvVo4jXyskpwDBq9ytzuUJZufNQrfbpD77etgWA67v1qGTLuql/p2ivHtH2tjpokZrizee23twr1eHN57a3sNttNG7c4KLr6+ybe9etW8dbb711wXWrV6+u5WhERESkMpeSdHsiQVfSL/6uzib+ffr0oU+fPlaHISIiIiJSJ9TYc/xFRERERMR71dkRf6k9hmnSv1O01WH4nNh/P0k2Oto3j63brcmrIiIi3kSJv1TKbrP57GQaKycKOZ2RXj9RydvjExERkapTqY+IiIiIiB9Q4i8iIiIi4gdU6iN+68iRNPLyQnA6I60ORURERMTjlPhLpQzTxOUKtTqMGrdjx784cQL69LFucq2h9+eJiIhILVHiL5Wy22w++eber9N+BKDYwn3T05JERESktqjGX0RERETEDyjxFxERERHxAyr1EbGYt8+fuNz43IZBbs7pGo5GPK24zE1QgMPqMKrNV/ZDRKQmKfEXsdhH3/xgdQgecVv7q60OQS5RXlEJe7JOEhsRjjM40OpwLpuv7IeISE1TqU8VTZw4kX/961+X9dlNmzaxcOHCGo5IRKTmmKbJgZxTABzMPYVZR5845Sv7ISLiCRrxr6LU1FQef/zxy/rsN998U8PRiNQNVpYxqdTo0mTkF1JquAEocRtk5BfSLCzE4qguna/sh4iIJ/ht4p+amsrs2bMJCAjg+PHjdOjQgWnTpjF37ly2bdtGXl4e4eHhzJ49m5UrV5KVlcXIkSN59913OXr0KNOnT6eoqIjw8HCmTp3KVVddRVJSErGxsezcuZPc3FySk5Np1qwZS5cuBSAqKoqoqChmzpwJgNPp5PXXX6dRo0ZWHgoRj9n+70emWqFzq6aVXnhc7oWJYRjk+NBFRYnbTXpeAca/B8cN0yQ9rwBXSDCBjrpTJ+8r+yEi4il+m/gD7N69m1WrVtGyZUuefPJJFi1aRFpaGkuXLsVutzN+/HjWrFnDyJEjWbp0KW+//TYhISEkJyezYMECoqKi+PTTT3nxxRf5y1/+AkBpaSl/+9vf2LRpE3/84x9JSUlh8ODBAAwcOJCkpCSmTJlChw4dWLx4Md9++y233nqrhUdBxHfty8j1SLvtohrV6t0M0zSx2Ww19vnTp4spLCwp/zn7dBG/rogxzbPL69Joua/sh4iIp/h14h8XF0erVq0A6Nu3L8uWLePFF1/k/fff58iRI+zatYurrz53guL333/P0aNHeeyxx8qXFRQUlP+9e/fuALRp04affvrpvD4TEhIYM2YMt912GwkJCdxyyy2e2DUR4WyC7gnVTcRrm2nCiRP5F13vCgkmPa/gnKTZZju7vC7xlf0QEfEUv078Hb+49fvzP+TDhw9n2LBh3HHHHdjt9vMmhhmGwW9+8xtWr14NgNvt5sSJE+Xrg4KCAC6aFAwbNoz4+Hg+/vhjZs6cye7du8+5iBCRmpOdXUGy6wqtcL0/CXQ4aO5sUF4mY7fZaO4MqXPlMb6yHyIinuLXif/OnTvJzMzE5XKxatUqbrzxRlwuFw888AD5+flMmTKF+Ph44OxFgtvtplWrVuTl5fHPf/6Tm266iRUrVrBmzRqWLFly0X4cDgfFxcUA3HfffUydOpVhw4bRsGFDNm7cWCv7KmKFzq2aWta32zAs67suigqtz/GCMxSVuQl02IkKrW91SJfFV/ZDRMQT/Drxj4iIYPz48WRmZnLLLbfQt29fxowZQ2JiIldccQUxMTEcO3YMgF69ejFy5Ej+9Kc/8cc//pFp06ZRXFxMgwYNeO211yrsJy4ujueee44mTZrw9NNPM2HCBAICAggKCmLq1Km1sasiltCIet1hs9lo0yiMPVknadMorE6VMv2Sr+yHiIgn2Ew/fchxamoqc+bMqXCk3hvl5BRgGLX7lblcoazceahW+6wNX2/bAsD13XpYFkP/TtGW9e1p3v44TZX6XJivvPHWV/bjcujcFl+lc7tydruNxo0bXHS9X4/4i3gDb/4lpl+y/sdXkmVf2Q8RkZrkt4l/ly5d6NKli9VhiIiIiIjUCrvVAYiIiIiIiOcp8RcRERER8QN+W+ojVWeYpk9OQo11nv0zOtq6fTP8c269iIiIWECJv1TKbrP55ARPpzPS8smrLleoZX2LiIiIf1Gpj4iIiIiIH9CIv1ToyJE08vJCcDojrQ5FRERERKpBib9UKC3tEFnZwdxzt+/V+INq7EVERMR/KPGXStltNp98cy/49ptzRURERH5JNf4iIiIiIn5Aib+IiIiIiB9Q4i8iIiIi4gdU4y9+z8pn6WtysVituMxNUIDD6jDqJB07qYjOD/FGPpn4T5w4kTVr1gCwd+9ei6MRb/fxvqOW9R3f7irL+hbJKyphT9ZJYiPCcQYHWh1OnaJjJxXR+SHeyidLfVauXMmaNWuIiIiwOhQREa9kmiYHck4BcDD3FKbuPlWZjp1UROeHeDOfG/EfNWoUpmly3333UVBQwJNPPsmRI0e4+uqrmTZtGk6n86KfTUpKolWrVuzevZvi4mKef/55br31Vg4cOMDLL79MYWEhubm5PPLIIwwdOpT8/HzGjx/PDz/8wFVXXcWPP/7InDlzuPLKK5kxYwbbt2/H7XYzYMAAhg0bxo8//sizzz5LYWEhdrud5ORkbrjhhlo8OuKNrCw1qsbckU0AACAASURBVIpGjUPIzTltdRhSwzLyCyk13ACUuA0y8gtpFhZicVR1g46dVETnh3gzn0v8FyxYQExMDKtWreK2224jKSmJm266iRkzZjB37lyef/75Cj9fUlLCypUr2bdvHyNGjGDTpk28//77jB49mm7dunH06FHuvfdehg4dyty5c2nZsiXz589nz549DBo0CIBly5YBZ+88lJSUMHz4cK677jq++OILevXqxaOPPkpqaio7d+5U4i98lZ5ldQgV6tg8wusvTi7XpeyXaZrYbDYPRnNxhmGSk1NQY+2VuN2k5xVg/Hsg0jBN0vMKcIUEE+hQTXJFdOykIjo/xNv5XOL/Sy1btuSmm24C4N5772XChAmVfubn5L1du3a4XC7279/PhAkT+PTTT3nrrbfYv38/hYWFAHz++efMmjULgNjYWGJiYgDYtm0b+/bt44svvgCgsLCQ/fv3061bN8aOHcu+ffvo2bMnDz30UI3vs4gnfH/ilNUhWK5FkzDL+rbZav7OUL5hsO94bvnPpgnZp4s0MlmJ7NNF/LpyQ8dOfqbzQ7ydTyf+AQEBFf58IY5fXJEbhkFAQABPPfUUYWFhxMfH06dPH9auXVu+7YVq99xuN+PGjeP2228HIDc3l/r16xMcHMzatWv55JNPWLduHStXrmThwoXV2UWRWmFl0ustanrU3Uolbjf7f8w9Z5nNBq6QYIsiqjtcIcGk5xWck9zp2MnPdH6It/PpxP/w4cN8++23XHvttSxfvpybb7650s+sW7eODh06sGfPHk6dOkXbtm35/PPPWb9+PZGRkaSkpABnk/ubb76ZNWvWcM0117B//34OHjyIzWaja9euLFu2jPj4eEpKShgyZAhTp05l8+bNREREMGzYMLp06UL//v09fQikDujY3LsnobsNwydr/F2uULKz860OwxKBDgfNnQ3KSxLsNhvNnSEqRagCHTupiM4P8XY+nfhfffXVzJ07lx9++IG2bdvyX//1X5V+5ujRo+UJ+RtvvIHD4WDs2LEMGTKEsLAwWrZsSbNmzTh27BijR49m4sSJJCYmcvXVV9OkSROCg4MZPHgw6enp9O/fn7KyMgYMGECXLl24+uqreeaZZ1i5ciUOh4PJkyd7+hBIHeDNyafLFeqTSb9AVGh9jhecoajMTaDDTlRofatDqjN07KQiOj/Em9lMPWeqXFJSEmPGjKFLly5V2n716tX85je/oVOnTmRkZPDQQw/x0UcfYbd77impOTkFGEbtfWUbN/6DsLB6FEe2rbU+a1P/TtGWP8ff2xN/b46vOnx536pKzxq/fN587HRuW8+bz4+6TOd25ex2G40bN7joep8e8b+QZ555hkOHDp23vHfv3pfcVqtWrZg8eTKGYWC323nppZc8mvSLZ1j5Ei29uVes5AwOJC6qid4uehl07KQiOj/EW/ld4v/666/XWFuxsbHlNf9Sd1k5euCrj8mUukOJyeXTsZOK6PwQb6ThaRERERERP6DEX0RERETED/hdqY9cmlatomkYXp+2baKtDsUjVGMvIiIi/kKJv1SoZctWPj2LXjX2IiIi4i9U6iMiIiIi4geU+IuIiIiI+AGV+ojfOnIkjby8EJzOSKtDEREREfE4Jf5SKcM0fbIWfseOf3HiBPTpY+3EZW8/tr+Mz+02yM09bWE0IiIicrmU+Eul7DYbK3ee/7bjuu7rtB8BKPbBffOU/p188+lOIiIi/kA1/iIiIiIifkCJv4iIiIiIH1DiLyIiIiLiB1TjLyKXxNsnI1+KX++L2zDIzdHkZX9TXOYmKMDh0XZqqg8RkepQ4i8il+TjfUetDsFj4ttdZXUIUsvyikrYk3WS2IhwnMGBHmmnpvoQEakuJf6XIT8/n+eee4558+Zx7Ngxhg4dyqZNmy66/e7du9mwYQPjxo2rxShF5HJ46x0N3Y2oeaZpciDnFAAHc0/R6crG2Gy2Gm2npvoQEakJSvwvQ15eHt99912Vtz906BA5OTkejEhEaspX6VlWh3BBHZtHeO1FyaUwDJOcnAKrwwAgI7+QUsMNQInbICO/kGZhITXaTk31ISJSE7wm8U9NTeWtt94iODiYw4cPExMTw6xZs1i3bh2LFi3CMAzat2/P5MmTmTFjBq1bt2bIkCEsW7aMhQsXsn79ekpLS7ntttv46KOPeP755zl48CAAQ4YMYdCgQRft+8yZMyQnJ7N//35sNhvDhw+nX79+pKSksH37dn7/+98DkJSUxJgxY1i4cCFZWVk8/vjjTJw4sbydEydOMGnSJH788UdsNhvPPPMM1113HW+++SaFhYXMnz+f+Ph4Jk2aRFlZGUFBQUyfPp0WLVp49NiKiG/4/sQpq0OothZNwiy5gDFN87yRdpcrlBuAUrfBB7vSSM8rwBUSTKCj6rX4JW436XkFGObZnw3TLG8HuOi6S+lDRKSmeNVTfb766ismTZrE+vXrycjI4L333mPZsmUsXbqU1atX07hxY/785z/Ts2dPvvjiCwC2bdtGXl4eJ06cYOfOndxwww189dVX5OXlsWrVKhYuXMiXX35ZYb+zZ88mPDycDz74gEWLFjF79uwKR/STk5OJiIhg7ty55yyfNm0aAwcOJCUlhfnz5zNp0iTsdjtPPPEEvXv35rHHHmPRokU88sgjpKSkkJSUxK5du6p/4EREpNpME7JPF13SZ7JPF2GaF26nonUiIlbwmhF/gDZt2tC0aVMAWrduTX5+Punp6eWj9aWlpVx77bUMHz6cSZMm4Xa7SUtLo0+fPuzYsYM9e/YQHx9PmzZtOHLkCMOHD6dHjx48++yzFfb7xRdf8OqrrwLQqFEjEhIS2L59Ow0aNLik+Ldu3UpaWhpvvvkmAGVlZRw9eu5EyJ49e/LSSy/x6aefEh8fzx133HFJfYiI/2rRJMzqEKrNW0p9Stxu/plxonw0HsBmo3ykvqpcIcGk5xWck+D/sp2K1omI1DavSvyDgoLK/26z2QgNDeWuu+4iOTkZgNOnT+N2uwkKCuKaa65hzZo1tGrVii5durBt2zZ27tzJo48+Snh4OGvXruXzzz9n8+bN9O/fn7Vr1xIWduF/NM1fDcmYponb7cZms52zrrS0tML4DcNg0aJFNGzYEIDMzEyaNGnCvn37yre588476dixIx9//DGLFi1i8+bNvPLKK5d2oETEYzo2j7A6hAvS5N6aFehw0NzZoLwUx26z0dwZcsklOJW1UxN9iIjUFK8q9bmQ//u//yMnJwfTNJkyZQqLFi0Czo6cz507l86dO9O5c2c2btxIvXr1aNSoERs3buTZZ5+lV69eJCcnU79+fY4fP37RPrp27cry5csByM3NZePGjXTu3Jnw8HAOHz6MaZocPXqU/fv3AxAQEEBZWdkF2/nrX/8KnJ3Qe++993LmzBkcDkf59k899RS7d+9m8ODBPPnkk3z77bc1erxEpHqys/O98j8l/TUvKrR+eRIe6LATFVq/xtupqT5ERGqCV434/1poaChjxozh4YcfxjAM2rVrx8iRIwHo1asXU6ZMoXPnzjidTho3bkyvXr0A6NGjBxs2bODuu+8mKCiI22+/nZiYmIv28/jjjzNlyhQSExNxu92MGjWK9u3bU1JSwooVK7jzzjtp2bIlnTp1AqBx48ZERUWRlJTE9OnTy9tJTk5m0qRJJCYmAjBjxgwaNGhAhw4dmDNnDrNmzWLUqFG88MILzJs3D4fDwYQJEzx09EQ8w5efde82DKtDkFpks9lo0yiMPVknadMo7LIfs1lROzXVh4hITbCZv65zEa+Wk1OAYdTuV+ZyhbJy56Fa7bM2fL1tCwDXd+thcSR1R/9O0WRn51sdRo1wuUJ9Zl+kenztzb06t8VX6dyunN1uo3Hji89R9eoR/5r0l7/8hZUrV563PCIignfeeceCiERExBvUVEJeUTu1lfSLiFTEbxL/YcOGMWzYMKvDEBERERGxhNdP7hURERERkerzmxF/uXyGadK/U7TVYdS4WOfZP6OjfW/fPMXt1uRXERGRukqJv1TKbrP55GQapzPS8olCVvdfGW+PT0RERKpOpT4iIiIiIn5Aib+IiIiIiB9QqY9U6MiRNPLyQnA6I60ORURERESqQYm/VCgt7RBZ2cHcc7dvToA19P46ERER8RNK/KVSdpvNJ9/cC/jk04pERERELkQ1/iIiIiIifkCJv4iIiIiIH1Cpj/g9lyvUsr41x0CkZhWXuQkKcFgdhoiIV1LiL37v431HLes7vt1VlvUt4mvyikrYk3WS2IhwnMGBVocjIuJ1VOpTidTUVJKSks5bHhMTY0E0IiJyIaZpciDnFAAHc09h6m6aiMh5NOIvYjFPlRq5DYPcnNMeaVvE22TkF1JquAEocRtk5BfSLCzE4qhERLyLEv8qOHnyJMOHDycrK4sOHTowefLk8nVnzpwhOTmZ/fv3Y7PZGD58OP369aO0tJTJkyezc+dOIiMjsdlsjB49mubNm/Pss89SWFiI3W4nOTmZG264wcK9E6t9lZ7lkXY7No+okYuKS23DMExycgqq3a9IVZW43aTnFWD8e5DfME3S8wpwhQQT6FC9v4jIz5T4V8GxY8eYM2cOzZs357/+67947733ytfNnj2b8PBwPvjgA3Jzc7nvvvu45ppr2LFjB2fOnOHDDz8kIyODxMREAJYvX06vXr149NFHSU1NZefOnUr8xWO+P3Gq1vts0SQMlysU0zSx2Wy13v+luNwLo9OniyksLKnhaORyZZ8u4teVPaZ5drlG/UVE/kOJfxXcdNNNtGjRAoDExERSUlLK133xxRe8+uqrADRq1IiEhAS2b9/O1q1bGTRoEDabjWbNmtGtWzcAunXrxtixY9m3bx89e/bkoYceqvX9Ef/RoklYrff5c8JvmnDiRH6t919VLlco2dneG59UnSskmPS8gnOSf5vt7HIREfkPJf5VEBDwn8NkmuZ5P/+SaZq43W4cDgeGYZzXVqdOnVi7di2ffPIJ69atY+XKlSxcuNBzwYtfq25iq+RY6oJAh4Pmzgbl5T52m43mzhCV+YiI/IoS/yrYuXMnGRkZNG3alFWrVtG9e3c+/PBDALp27cry5ctJTk4mNzeXjRs3Mnv2bAIDA1m3bh0JCQlkZWWxfft2Hn74YWbMmEFERATDhg2jS5cu9O/f3+K9E6t1bB7hkXbdF7jwFPFVUaH1OV5whqIyN4EOO1Gh9a0OSUTE6yjxr4Lo6Gief/55srOz6dq1K7/73e+YNGkSAI8//jhTpkwhMTERt9vNqFGjaN++PW3btuW7774jMTERl8tFVFQUwcHBJCUl8cwzz7By5UocDsc5E4XFP2lEXaT6bDYbbRqFsSfrJG0ahXn9/BIRESvYTD3s2CM++eQTTNMkPj6e/Px8+vXrx4oVK2jYsGG12s3JKcAwau8r27jxH4SF1aM4sm2t9Vmb+neKtrR/wzTJOeG9T8Dx5VIfX943f6Y39+rcFt+lc7tydruNxo0bXHS9Rvw9pHXr1owfP54//OEPADzxxBPVTvrFM6z8JeKpZ/iL+Ct/T/pFRCqixN9DrrrqqnMe+ykiIiIiYiW71QGIiIiIiIjnKfEXEREREfEDKvWRCrVqFU3D8Pq0bWPtJFhPMTS3XURERPyEEn+pUMuWrXx6Fr0m14qIiIi/UKmPiIiIiIgf0Ii/VOjIkTTy8kJwOiOtDkVEREREqkEj/lKhtLRDHDhwwOowRERERKSalPiLiIiIiPgBJf4iIiIiIn5Aib+IiIiIiB9Q4i8iIiIi4gf0VB+pEl993r1e4FWxMyVlVodw2YrL3AQFOKwOQ0RExGv4VeK/Z88eli5dyrRp00hKSmLMmDF06dLlguurq3fv3ixevJj9+/ezd+9ennzyyWq3aaVPD/zL6hA8onvbZlaH4LXyikr47IdMYiPCcQYHWh3OJckrKmFP1sk6GbuIiIin+FXiHxsbS2xs7GWvvxwJCQkkJCTUaJsinmaaJgdyTgFwMPcUna5sjM1msziqqqnLsYuIiHiSz9X4JyYmcvjwYQCeeeYZJk+eDMCuXbu4/vrrSUpKOmf7nJwc7rnnHj766CNSU1PL1yclJTF58mT69+9Pnz59+OyzzwA4ceIEo0ePZsCAAQwcOJCtW7cC8NNPPzFixAgSExN56qmnKC4uBiAlJYUJEyYAsH79egYNGsS9997LHXfcwY4dOzx/QEQuQ0Z+IaWGG4ASt0FGfqHFEVVdXY5dRETEk3xuxL9nz55s27aN1q1bn/PiqS1btjB+/Hg+/PDD8mX5+fmMHDmSMWPGcNttt5GamnpOWyUlJaxcuZJ9+/YxYsQINm3axLRp0xg4cCAJCQlkZWUxZMgQVq1axZtvvsm1117LO++8w44dO1i/fv05bRmGwdKlS1mwYAGNGjVi+fLl/PnPfyYuLs6zB0QqZeX8BdM0Pda/YZjk5BRc8udK3G7S8wow/j39wTBN0vMKcIUEE+jw7pr5uhy7iIiIp/lc4t+rVy8WLlxI165diY6OJi0tjZycHLZs2cJDDz10zraTJ0+mSZMm3H777Rdsa9CgQQC0a9cOl8vF/v372bp1K2lpabz55psAlJWVcfToUbZv387rr78OQFxcHFddddU5bdntdubOncumTZs4cuQI27dvx273uRsuddKJ/DOW9d0ktJ5lfV9M9ukifj3n2TTPLm8WFmJNUFVUl2MXERHxNJ9L/Dt27Mj48ePZunUrnTt3pnHjxnz44YeUlpZy5ZVXnrPtiBEj2Lx5M++99x4PPvjgeW05fjFCaBgGAQEBGIbBokWLaNiwIQCZmZk0adIEm82G+YuMw/Gr0cXTp08zcOBA+vbtS1xcHDExMbz77rs1uetymaxMvk3T5MSJSx+V9yRXSDDpeQXnJNA229nl3q4uxy4iIuJpPpf4OxwOrr/+epYsWcKCBQtwuVxMnTqV/v37n7dtu3bt6NWrFw888AC33XbbeevXrVtHhw4d2LNnD6dOnaJt27Z07dqVv/71r4wePZpDhw7x4IMPsnHjRrp168bq1au55ppr2L17Nz/88MM5bX3//ffY7XZGjRoFQHJyMm632zMHQS5Jdna+ZX1742NSAx0OmjsblJfM2G02mjtD6kSpTF2OXURExNN8LvGHs3X+O3bsoHXr1rhcLnJycujVqxelpaXnbduiRQsefPBBXnrpJYYOHXrOuqNHj5ZfMLzxxhs4HA6Sk5OZNGkSiYmJAMyYMYMGDRrwxBNPMGHCBO6++25atWp1XqnPNddcQ7t27bjrrrsIDg4mLi6OjIwMDx0BkeqJCq3P8YIzFJW5CXTYiQqtb3VIVVaXYxcREfEkm2nqDUYXcqHn/HuDnJwCDKP2vrKNG/9BWFg9QqOvr7U+a1P3ts0sH/G3sv+K1OVn4Vcldm8+9iLVoXNbfJXO7crZ7TYaN25w0fU+OeIvNc9XX3SlN/denDM4kDtjW1CQZ93k58vlDA4kLqqJ3twrIiLyC0r8L2LJkiVWh+BVfPUK2xtr7L1JvcAAvGvqcdUp6RcRETmXnicpIiIiIuIHlPiLiIiIiPgBlfpIhVq1iqZRI734SERERKSu04i/VKhly1ZER0dbHYaIiIiIVJMSfxERERERP6DEX0RERETED6jGXyp05EgaeXkhOJ2RVociIiIiItWgEX+pUFraIQ4cOGB1GCIiIiJSTUr8RURERET8gBJ/ERERERE/oMRfRERERMQPKPEXEREREfEDSvxFLPTjT6etDkFERET8RJ1L/GfPns3s2bOrvH1qaipJSUnnLc/MzGTEiBGX1VdKSgoTJkwAYMSIEWRmZl5y/8BFl4t/OJx7im2Hj5OWe8rqUERERMQP+O1z/CMjI3nnnXeq3U512ti+fXu1+68tLleo1SF4hGmalvTrdrs5XnAGgIyCMzR3huBwOCyJRURERPxDpYl/amoqM2fOxDAMmjVrRv369Tl48CBut5sRI0Zwzz338N133zFp0iTKysoICgpi+vTptGjRgi1btvDmm29SVlbGb37zG15++WXCw8NZv349CxcupKioiOLiYl555RXi4uJISkrC6XRy8OBB/vCHP3Do0CHmz5+PzWYjNjaWl19+GYDdu3czePBgMjMzGTBgAGPHjq1wH3JzcxkxYgQ//PADLVu25M033yQrK4uhQ4eyadMmfvzxR5599lny8vJo27YtO3bsYMuWLVXqq3fv3ixevJjIyEgmT57Mzp07iYyMxGazMXr06Iv2P2PGDADuu+8+3n///Uv/5mrZvoxcq0PwiHZRjSzpd9eP5x7PXZm5dIpyWRKLiIiI+Icqjfh///33fPzxx7z11ltERETw2muvUVBQwODBg7n++utZtGgRjzzyCHfddRfr1q1j165dhIWF8frrr7N48WKcTidLly5l1qxZvPzyyyxdupQFCxbQqFEjli9fzp///Gfi4uIAiImJYc6cOWRmZjJ9+nRSUlJo2rQp48aNY/PmzQDk5OSwdOlSCgoK6N27N4888ggNGjS4aPwZGRksWLCAZs2aMWjQILZu3Up0dHT5+mnTpnHXXXfx4IMP8n//93988MEH5esu1NeFLF26lDNnzvDhhx+SkZFBYmJihf0nJyezZMmSOpH0+zpP3s0wDJOcnIJzlp08U8wZt3HOsjNlBj+dKaZhvSCPxSIiIiL+rUqJf8uWLQkNDWXr1q0UFRWxYsUKAAoLCzl48CA9e/bkpZde4tNPPyU+Pp477riDLVu2cPz4cYYOHQqAYRg4nU7sdjtz585l06ZNHDlyhO3bt2O3/2eqQYcOHQD46quvuPHGG2natCkAM2fOBGDfvn10796dwMBAGjVqRHh4OHl5eRUm/tdccw1XXXUVAK1bt+bkyZPnrP/888+ZPn06AL/97W8JCwsrX3ehvi7k888/Z9CgQdhsNpo1a0a3bt2q3L/4lyMn8y+4PO1kPjcq8RcREREPqVLiHxwcDJxN3mfOnEn79u0BOHHiBE6nkyuuuIKOHTvy8ccfs2jRIjZv3kyvXr248cYbWbBgAQDFxcWcPn2a06dPM3DgQPr27UtcXBwxMTG8++675/UVEHBuaLm5/ymN+OU6m81WaZ12Zds7HI6LtlHVvhwOB4ZhXHDdpcYrtSs7+8KJuKe0Cg9lb/ZPF1wuIiIi4imXNLm3a9euvPfee7zyyitkZWXRr18/li5dyn//939z9913M3jwYFq3bs306dN58sknSU5O5siRI7Rs2ZJ58+aRmZlJUlISdrudUaNGAZCcnIzb7T6vr9jYWKZOnUp2djYul4tXX32VLl261Mxe/8rNN9/MmjVrGDJkCJs3b+bUqUt/ysrNN9/MunXrSEhIICsri+3bt/Pwww9XmOQ7HA7KysrOu8jxRlbVwnuaFRdhDesFUc9hP6fcp16AXWU+IiIi4lGXlHGOGTOGKVOmcM899+B2uxk3bhxXX301o0aN4oUXXmDevHk4HA4mTJhQnqw/9dRTGIZBZGQkM2fOJCwsjHbt2nHXXXcRHBxMXFwcGRkZ5/UVGRnJCy+8wPDhwzEMgxtuuIEBAwYwb968Gtv5nz3//PM899xzLFu2jGuuueacUp+qGjRoEN999x2JiYm4XC6ioqIIDg7mzJkzF/1MQkICffv2JSUlhaAg7076antUvLZY9bSiG5o2Ytu/Tvzn50jfvLASERER72EzVXfC4sWLufnmm4mOjuabb77hxRdfJCUl5ZLa+OSTTzBNk/j4ePLz8+nXrx8rVqygYcOGNRprTk4BhlF7X9nGjf8gLKwecXHda63P2uRyhVp2UXM49xTHC84Q1aAerRpd+sVmbbDy+HiaL++b+Ded2+KrdG5Xzm630bjxxee9en+NSRX885//LH/U56+9/fbbREZGVvj55s2b8/TTT2O32wkKCrpoWxVp3bo148eP5w9/+AMATzzxRI0n/eJbWjcKo0VkQxylF54bIiIiIlKTNOJfx2jEv2ZZPXpgdf+V8fb4qsOX9038m85t8VU6tytX2Yi//aJrRERERETEZyjxFxERERHxAz5R4y+e06pVNI0ahVgdhoiIiIhUk0b8pUItW7YiOjra6jBEREREpJqU+IuIiIiI+AEl/iIiIiIifkA1/lKhI0fSyMsLwems+F0IIiIiIuLdNOIvFUpLO8SBAwesDkNEREREqkmJv4iIiIiIH1DiLyIiIiLiB5T4i4iIiIj4AU3ulSpxuUKtDsEjTNO0OgSfVVzmJijAYXUYcgH6bkRE/JMSf6mS7Wk/Wh2CR3Ru1dTqEHxSXlEJe7JOEhsRjjM40Opw5Bf03YiI+C+V+tSwmJgYq0MQsZRpmhzIOQXAwdxTuqviRfTdiIj4N434i9+zuoypqv0bhklOToGHo6m+jPxCSg03ACVug4z8QpqFhVgclYC+GxERf6fEvwpef/11NmzYQHh4OC6Xi969e7Nw4UKuuuoq0tPTiYqKYubMmTRs2LD8M7NnzwZg7NixAPTu3ZvFixdTUFDApEmTKCsrIygoiOnTp9OiRQsrdkv+7V8nvT+ZBmgW3qBGL1I8cSFR4naTnleA8e+BZMM0Sc8rwBUSTKBDNeVW0ncjIiIq9anEpk2b2LlzJx988AFvv/023377LQAHDhzg4YcfZu3atbRu3Zo5c+ZUqb1FixbxyCOPkJKSQlJSErt27fJk+CIXZbfbarzN7NNF/Lp6xDTPLhdr6bsREREl/pXYunUrd911F4GBgTidTm677TYAWrRoQZcuXQDo168fX3zxRZXa69mzJy+//DLPP/88V1xxBYmJiR6LXaQihlHz9d2ukGBsv7qesNnOLhdr6bsRERGV+lTCbrdjGMZ5ywMC/nPoTNPE8atb5Tab7ZzPlZaWAnDnnXfSsWNHPv74YxYtWsTmzZt55ZVXPBS9+Jrs7HyrQ6hQoMNBc2eD8pISu81Gc2eIZG+zfQAAIABJREFUSkm8gL4bERFR4l+JW265hbfffpsHHniAkpISPvnkE8LCwjhy5Aj79u2jXbt2rFixgh49epzzufDwcFJTUwHYvXs32dnZADz11FPcfffdDB48mNatWzN9+vRa3yc5V7PwBlaHUCWeGKH3hKjQ+hwvOENRmZtAh52o0PpWhyT/pu9GRMS/KfGvRM+ePfnyyy/p378/TqeTiIgIgoKCcDqdvPnmm/zwww/ExMScN2rfp08fNmzYQJ8+fWjfvj3XXnstAKNGjeKFF15g3rx5OBwOJkyYYMVuyS9YOYrucoV6/Sj+pfr/7d17VNVlvsfxzwYERAUBAdOa4mJmltfwkuKthkxEAh0l81Jjts6ZtDpHLUdNrbQU9TReKqtRM6c08wLeUhtMrSR0zGtaYqCJEiIYgspt733+aGJCuajA3sDv/Vqrtdi/328/z/fZ+3GtD0/P74fJZFILL3cdOX9RLbzcZbp2fwnshu8GAIyN4F+BAwcO6K677tLmzZtVWFioIUOGKCQkRCtXrtQ777xz3fU//PCDpF9X/D/88MNS21y7dm211lwd6uofuuI55tXDw9VZwc2a8NdhayC+GwAwLoJ/Bfz9/bVo0SItW7ZMVqtVjz32mBo2rB1bQ6pSXVuV/o29n+FflxEsay6+GwAwJoJ/BRo3bqwlS5Zcd3zHjh12qAYAAAC4NTzOEwAAADAAgj8AAABgAGz1QbkCAoLk5dXA3mUAAACgkljxR7n8/QMUFBRk7zIAAABQSQR/AAAAwADY6oNypaQkKzu7gTw8/OxdCgAAACqBFX+UKzn5pE6cOGHvMgAAAFBJBH8AAADAAAj+AAAAgAEQ/AEAAAADIPgDAAAABkDwh6H9/Mtle5cAAABgEwT/G9CyZUtJ0sqVK7Vy5coyr6voPGqWH7MuKeHHNCVnXbJ3KQAAANWO5/jfhMcff7xS52szH59G9i6hylgsVp0/n6203KuSpHO5V3WnRwM5OjrauTIAAIDqY8jgn5iYqIULF8rJyUlpaWlq06aNZs6cqY0bN2rZsmUymUxq3bq1Xn75ZTVo0KD4fQsXLpQkjR07Vhs3btQ777wjk8mk+++/X6+99poWL15cfH737t1asGCBioqKdPvtt+u1116Tp6enZs+era+//lqOjo566KGHNGbMGLt8Bkbm4GDSwZ+zShw7mJ6ljs187FQRAABA9TPsVp/Dhw9r6tSp2rp1q/Lz8/Xee+9p8eLFWrFihTZu3Kj69etr0aJFpb43PT1db7zxhpYuXarNmzfLbDZr165dxeezsrI0b948LVmyRLGxserevbvmzp2rs2fPavfu3dqwYYNWrVqlU6dOKT8/31ZDxu9cNVtKvi6y6JerfBcAAKDuMuSKvyQFBwcrICBAkhQREaGxY8dq2LBh8vT0lCQNGTJEf/3rX0t974EDB9ShQwc1bdpUkjRnzhxJ0vHjxyVJhw4dUlpamkaMGCFJslgs8vDwkJ+fn1xcXBQdHa3evXvrhRdekIuLS7WOEzcu+WKOOtTn+wAAAHWTYYP/7/dzW61WWSwlV4CtVquKiopKfa+TU8mPLSur5LYRs9msDh06FG/9yc/P1+XLl+Xk5KRPP/1Ue/fu1e7duxUdHa0VK1bI39+/KoaESgrwrDv3MQAAAFzLsFt99u/fr/T0dFksFsXGxuqvf/2rduzYoV9++UWStHr1anXu3LnU995///06dOiQMjIyJEmvv/664uPji8+3bdtWBw8eVEpKiiTp7bffVkxMjI4dO6Zhw4YpODhYL730kgIDA4uvge1YLFbVdyw59es7Oagxq/0AAKAOM+yKv6+vr1588UWlp6erW7duGjZsmNzc3DR8+HAVFhaqdevWeuWVV0p9r5+fnyZPnqxRo0bJYrGoXbt2ioqK0ttvvy1J8vHx0euvv64XXnhBFotFfn5+mjNnjjw9PdWuXTv1799f9evXV6tWrdSjRw9bDvuWZWTk2LuEKtWuqZcSzl74z2s/LztWAwAAUP1MVqvVau8ibC0xMVGLFi3SihUr7F3KTcvMzJXFYruvLD5+u9zd6ys4OMRmfdrKj1mXlJZ7Vc0a1leAl7tdavDxaVSjf6mq6fVVRl0eG4yNuY26irldMQcHk7y9G5Z53rAr/kCgl7vu8mssx0JLxRcDAADUcoYM/p07dy5z/z6MpWnjBqweAAAAQzDszb0AAACAkRD8AQAAAAMw5FYf3LiAgCB5eTWwdxkAAACoJFb8US5//wAFBQXZuwwAAABUEsEfAAAAMACCPwAAAGAA7PFHuVJSkpWd3UAeHn72LgUAAACVQPBHuZKTT+p8hqv6h9XNff4W4/3hagAAYFAEf1TIwWTS+v0n7V1GtYjsWDd/oQEAALgWe/wBAAAAAyD4AwAAAAZA8AcAAAAMgOAPAKXILzLXyLYAALhVBP9yTJ48WUeOHLnu+MSJE7Vu3To7VATAFrLzCrTv3AVl5xXUqLYAAKgMnupTjpkzZ9q7BNiAj0+jWtO/xWJVZmZuNVYDq9WqE5mXJElJWZfU8TZvmUwmu7cFAEBlseL/b2PGjNHWrVuLX0dFRalDhw5KTEyU1WrVG2+8oUceeUTDhw/XTz/9VHxdbGysIiMjFRERoUmTJik/P1+S9MUXXygiIkLh4eH6y1/+ogsXLkiSZs+erQEDBigyMlKLFi2y7SBR6zk4EBqr27mcKyq0/Lo1p8Bs0bmcKzWiLQAAKovg/28RERHasmWLJOnUqVPKz89X69atJUnbtm3TsWPHtGnTJs2fP784+CclJWn16tVatWqV4uLi5O3trSVLligzM1NTp07VW2+9pY0bN6pDhw569dVXdfbsWe3evVsbNmzQqlWrivsBUDMUmM06nZ0ry7//rpvFatXp7FwVmG9+j35VtgUAQFUg+P9bz549dfDgQeXm5mrTpk0KDw8vPrd3716FhoaqXr168vLyUo8ePSRJiYmJOn36tAYPHqyIiAjFx8crOTlZhw8fVps2bXT77bdLkoYMGaJvvvlGfn5+cnFxUXR0tD744AO98MILcnFxsct4AVwv43Kerv1jzlbrr8ft2RYAAFWB4P9vzs7O6tWrl3bs2KGtW7eWCP4mk0kWi6X4tZPTr7dGmM1mPfroo4qLi1NcXJw+/fRTTZ06tcS10q/7fIuKiuTk5KRPP/1Uzz//vH755RdFR0crJSXFNgMEUCGfBq66dgu+yfTrcXu2BQBAVSD4/05ERISWLVsmDw8PNW/evPh4165dtXXrVhUUFCg7O1tffvmlJKlz5876/PPPlZmZKavVqunTp2v58uVq27atDh06pNTUVEnSJ598os6dO+vYsWMaNmyYgoOD9dJLLykwMJDgj5tisVgrvgi3zNnRUXd6NNRvt1I4mEy606OhnB0d7doWAABVgaf6/E7Hjh2Vk5Oj6OjoEscffvhhHTlyRP3791eTJk0UGBgoSbrnnns0ZswYjRw5UhaLRa1atdIzzzwjFxcXvfrqqxozZowKCwvVrFkzzZw5U76+vmrXrp369++v+vXrq1WrVsXbhmA/GRk5duvbx6eRXfvH9Zo1clNa7lXlFZnl7OigZo3cakRbAABUlslqvXYXKmqyzMxcm676xsdvl7t7feX73W2zPm0psmMQwb8cNb2+yihvbNl5BTpy/qLu9/WUh6tzpfqpyraAG1GX/93C2JjbFXNwMMnbu2GZ51nxB4BreLg6K7hZE7k4VX5bTlW2BQBAZbDHHwBKUZVBndAPAKgJCP4AAACAARD8AQAAAANgjz/KFRAQpMaebrq7RZC9S6kWFu5tBwAABkHwR7n8/QPq9F30Pj6N7F0CAACATbDVBwAAADAAgj8AAABgAGz1QblSUpKVnd1AHh5+9i4FAAAAlcCKP8qVnHxSJ06csHcZAAAAqCSCPwAAAGAABH8AAADAAAj+AAAAgAEQ/AEAAAADIPgDAAAABkDwv0nz589XfHy8vcsAAAAAbgrP8b9Jzz//vL1LAAAAAG5ajQj+iYmJWrhwoZycnJSWlqY2bdpo5syZ2rJli5YvXy6LxaLWrVtr2rRpcnFx0e7du7VgwQIVFRXp9ttv12uvvSZPT0/16dNHbdq00fHjx/Xxxx/L29u71P66dOmi1q1b68KFC1qzZo2WLVumzz77TGazWd27d9eECRM0a9Ys+fr6atSoUZKk5557Tv3799eOHTvUqVMnRUVFKTY29rr6YmJiFBgYqKFDh2r16tXFbRcWFurhhx/WP//5T02aNElJSUmSpKFDh2rw4ME2+6wBAABgTDVmq8/hw4c1depUbd26Vfn5+VqyZIlWr16tVatWKS4uTt7e3lqyZImysrI0b948LVmyRLGxserevbvmzp1b3E6PHj20bdu2MkO/JF28eFHPPPOM4uLilJCQoKNHj2rNmjWKjY1Venq6NmzYoIiICG3evFmSlJubq2+//Va9evUqbiMpKanU+nr27KlvvvlGkpSQkKDs7GxduHBB+/fvV7t27XTgwAFlZ2crNjZWy5Yt07fffls9HygAAADwOzVixV+SgoODFRAQIEmKiIjQ2LFj5enpWbwaXlhYqHvvvVeHDh1SWlqaRowYIUmyWCzy8PAobqdt27Y31N9v1yUkJOjw4cOKioqSJOXl5alZs2aKiIhQQUGBTp8+rQMHDqh3795ydnYufn9iYqJOnz59XX2jRo3S1KlTZTablZycrH79+mnfvn06cuSIevfurRYtWiglJUWjRo1Sjx49NH78+Ep+cgAAAEDFakzwd3R0LP7ZarXKbDbr0Ucf1ZQpUyRJly9fltls1t69e9WhQwctXrxYkpSfn6/Lly8Xv9fFxeWG+nN1dZUkmc1mjRw5Uk899ZQk6dKlS8W1DBgwQFu2bNGBAwc0evToEu8vqz4XFxfdc8892rhxowICAtS5c2clJCRo//79evrpp+Xp6anNmzfr66+/1q5duxQZGanNmzfL3d39Vj42AAAA4IbUmK0++/fvV3p6uiwWi2JjYzVp0iR9/vnnyszMlNVq1fTp07V8+XK1bdtWBw8eVEpKiiTp7bffVkxMzC3326VLF8XFxeny5csqKirSs88+q23btkmSwsPDtWXLFp0+fVoPPPBAifd17ty51PokqWfPnnrrrbfUqVMnderUSfHx8apfv768vLwUHx+v8ePHq1evXpoyZYrc3NyUlpZ2y/UDAAAAN6LGrPj7+vrqxRdfVHp6urp166Zhw4bJzc1NI0eOlMViUatWrfTMM8/IxcVFr7/+ul544QVZLBb5+flpzpw5t9xvnz599P3332vw4MEym80KCQlRZGSkJOm2226Tp6en2rVrJ5PJVOJ999xzj8aMGXNdfZLUq1cvTZ8+XZ06dZKHh4e8vb2L7w/47R6EsLAwubi4KDQ0VC1btrzl+gEAAIAbYbJarVZ7F5GYmKhFixZpxYoV9i6lxsvMzJXFYruvLD5+u9zd6ys4OMRmfdqSj08jZWTkGLb/itT0+iqjLo8NxsbcRl3F3K6Yg4NJ3t4NyzxfY1b8q1JeXp6GDBlS6rnnnntODz30kI0rAgAAAOyrRgT/zp07q3PnzlXWnqurq+Li4qqsPQAAAKC2qzE39wIAAACoPgR/AAAAwABqxFYf1FwBAUHy8mpg7zIAAABQSaz4o1z+/gEKCgqydxkAAACoJII/AAAAYABs9UG5UlKSlZ3dQB4efvYuBQAAAJVA8Ee5kpNP6nyGq/qH1d3tPj4+jWp1/2azRVlZl6uoGgAAUFcR/FEhB5NJ6/eftHcZKENkx7r7SxkAAKg67PEHAAAADIDgDwAAABgAwR8AAAAwAPb4A3VAdd6gbI+bny0WqzIzc8s8n19klouTY7lt3Mg1AAAYCSv+VSA9PV2jR4+WJE2cOFHr1q2zc0VA7ebgYCrzXHZegfadu6DsvIJKXQMAgNEQ/KuAn5+f3n//fXuXAdR5VqtVJzIvSZKSsi7JarXe0jUAABgRwf8a4eHh+vHHHyVJ48aN07Rp0yRJBw8e1OjRo/Xee+8pMjJSAwYMUExMjKxWq1JTU9WnT5/iNnbu3KmoqCiFh4dry5YtkiSLxaIZM2YoLCxM/fv313vvvWf7wQG13LmcKyq0mCVJBWaLzuVcuaVrAAAwIvb4X6Nnz55KSEhQYGCgTpw4UXx89+7d6tWrlxITE7VmzRqZTCZNmDBBGzZsUMeOHUu0cfXqVa1evVqZmZkaOHCggoODtX37dqWlpWnDhg0qKCjQ8OHDdffdd6tXr142HiFQOxWYzTqdnSvLvxfwLVarTmfnyqeBq5wdHW/4GgAAjIoV/2v06tVLCQkJOnnypIKCguTg4KDMzEzt3r1bR48e1eHDhxUVFaXIyEgdPXpUJ09e/4etIiMj5eTkJD8/P7Vr106HDh1SYmKiIiMj5ejoqPr16ys8PFwJCQl2GCFQO2VcztO1u3as1l+P38w1AAAYFSv+12jfvr1efPFF7dmzR506dZK3t7e2bt2qwsJCNWrUSCNHjtRTTz0lSbp06ZIcHR118eLFEm04/m5l0Wq1ql69erJYLCWusVqtMpvN1T8goI7waeCq09m5JYK9yfTr8Zu5BgAAo2LF/xqOjo5q27atVqxYoU6dOqlLly5avHixevbsqS5duiguLk6XL19WUVGRnn32WW3btu26NjZv3iyr1aqzZ8/qyJEjuv/++9WlSxfFxsbKbDbr6tWr2rhxozp37myHEQK1k7Ojo+70aKjfHvjjYDLpTo+GJbbw3Mg1AAAYFSv+pejZs6f27dunwMBA+fj4KDMzU7169VKHDh30/fffa/DgwTKbzQoJCVFkZKTOnj1b4v1ubm6KiopSUVGRXn31VXl5eWnIkCE6deqUIiIiVFhYqAEDBuiPf/yjnUYI1E7NGrkpLfeq8orMcnZ0ULNGbrd0DQAARmSy8qy7WiUzM1cWi+2+svj47XJ3r698v7tt1iduTmTHIHuXUC0yMnJKPZ6dV6Aj5y/qfl9Pebg63/I1Pj6NyuwDqM2Y26irmNsVc3Awydu7YZnnWfEHUOOU98uth6uzgps1Kfev8t7INQAAGA3BH6gDqmsFpKaurtxIoCf0AwBQEjf3AgAAAAZA8AcAAAAMgK0+KFdAQJAae7rp7hZ18wbSusBstlR8EQAAMDyCP8rl7x9QY/d5VwV7j83e/QMAAONgqw8AAABgAAR/AAAAwADY6oNypaQkKzu7gTw8/OxdCgAAACqBFX+UKzn5pE6cOGHvMgAAAFBJBH8AAADAAAj+AAAAgAEQ/AEAAAADIPgDAAAABkDwBwAAAAyA4A8AAAAYQK0I/sOHD1diYuJ1xydOnKh169YpPT1do0ePliTt2LFDy5YtK7e9M2fOaNKkSZKkxMREDR8+vOqLvsbChQu1cOHCau8HAAAAKE2d+ANefn5+ev/99yVJ3333XYXXnzt3TmfOnKnusgAAAIAaw+bBPzExUXPmzJHFYlHz5s3l5uampKQkmc1mjR49Wv3791dBQYEmT56so0ePqnnz5rp48aIkyWq1atasWdq5c6d8fX1lNpvVqVMnpaamasSIEXrvvfe0atUqSVKzZs00cODAUmuYMWOGUlNT9corr6hv377KysrS6NGj9dNPP8nf318LFizQ+fPn9fTTT8vT01MuLi5asmSJYmJitHfvXpnNZkVFRenJJ59UUVGRpk+frqSkJF24cEH+/v5atGiRXF1d9fe//12rV6+Wp6en3N3d1aZNGxUWFmrSpElKSkqSJA0dOlSDBw+2zYcPAAAAw7LLiv+pU6f0xRdf6N1335Wvr69mz56t3NxcRUdHq23bttq+fbsk6bPPPtOpU6c0YMAASdK2bdt07Ngxbdq0STk5OcXHfxMUFKTo6GhJKjP0S9KUKVO0aNEiTZs2TYmJiTp37pwWL16s5s2ba/DgwdqzZ4+CgoKUkpKiv//977r99tu1cuVKSdL69etVUFCgUaNG6b777pPValW9evX0ySefyGKxaOTIkdq1a5eaNWumtWvXav369TKZTBoyZIjatGmjAwcOKDs7W7Gxsbp48aJmz55N8AcAAEC1s0vw9/f3V6NGjbRnzx7l5eVp7dq1kqQrV64oKSlJe/fu1ZAhQyRJd911l9q3by9J2rt3r0JDQ1WvXj15eXmpR48eVVLPPffcozvuuEOSFBgYWPx/GLy9vXX77bdLkhISEnT8+HF98803xbX+8MMPeuKJJ9S4cWN99NFHSk5O1qlTp3TlyhXt3btXPXv2VIMGDSRJffv2lcViUYsWLZSSkqJRo0apR48eGj9+fJWMAQAAACiPXYK/q6urJMlisWjOnDlq3bq1JOnChQvy8PDQ6tWrZbFY/lOk069lmkymUo9X1u/bMZlMslqtJeqUJLPZrAkTJig0NFSSlJWVJTc3N8XHx2vBggUaMWKEoqKidPHiRVmt1lJrLSgokKenpzZv3qyvv/5au3btUmRkpDZv3ix3d/cqGQsAAABQGrs+1adLly7FW2jOnz+vAQMGKC0tTV27dtWmTZtksVh09uxZffvtt5Kkrl27auvWrSooKFB2dra+/PLL69p0dHRUUVFRuf3eyDWl1bp69WoVFhbq8uXLGjp0qA4dOqSEhAQ9+uijGjhwoJo0aaJ9+/bJbDara9eu2rlzp3JycpSfn6/PP/9ckhQfH6/x48erV69emjJlitzc3JSWlnZTtQAAAAA3y65P9RkzZoymT5+u/v37F6+o/+EPf9DQoUOVlJSkRx99VM2bN9fdd98tSXr44Yd15MgR9e/fX02aNFFgYOB1bQYHB+ull15SkyZNynxMZ2BgoHJycjRhwgQNGjTohmqNjo7W6dOnFRkZqaKiIkVFRalz585q3Lixxo8fr61bt8rZ2Vnt2rVTamqq/vSnP2nkyJEaNGiQ3N3d1axZM0lSjx49tG3bNoWFhcnFxUWhoaFq2bLlLX6CAAAAwI0xWX/b14JaITMzVxaL7b6y+Pjtcnevr+DgEJv1aUs+Po2UkZFj2P4rUtPrq4y6PDYYG3MbdRVzu2IODiZ5ezcs83ydeI5/abZs2aJ333231HNxcXE2rgYAAACwrzob/Pv166d+/frZuwwAAACgRrDrzb0AAAAAbKPOrvijagQEBMnLq4G9ywAAAEAlseKPcvn7BygoKMjeZQAAAKCSCP4AAACAARD8AQAAAANgjz/KlZKSrOzsBvLw8LN3KQAAAKgEgj/KlZx8UuczXNU/zH77/M1mi7KyLtutfwAAgLqA4I8KOZhMWr//pN36j+zIzcUAAACVxR5/AAAAwAAI/gAAAIABsNUHtYKPT6MbvtZisSozM/eGrr1aUHSrJQEAANQqrPijznFwMN3Qddl5Bdp65JSy8wqquSIAAAD7I/jbyYIFC/Svf/3L3mUYltVq1YnMS5KkpKxLslqtdq4IAACgehH87WTfvn0ym832LsOwzuVcUaHl18+/wGzRuZwrdq4IAACgetXaPf5Wq1WzZs3Szp075evrKy8vL/Xs2VMffvihWrRooePHj8vb21vz589X48aN9Y9//ENxcXG6evWqTCaT/va3vykwMLDM9o8fP66pU6cqLy9PHh4emjt3rpo2barFixdrw4YNcnR0VLdu3TRhwgSlpaVpxIgR2rFjhyRp4cKFkqSxY8eqe/fueuSRR7R//345Ojrqb3/7m/bv36+jR49qypQpWrRokVq2bGmTzwy/KjCbdTo7V5Z/L/JbrFadzs6VTwNXOTs62rc4AACAalJrV/w/++wzfffdd9q0aZPefPPN4m0z33//vZ566ilt2rRJ7u7u2rhxo3Jzc/XPf/5TK1as0KZNm/Twww/r448/Lrf98ePH6y9/+Ys2btyofv36afny5dq1a5d27NihdevWaf369Tp9+rRWrVpVbjsZGRnq2rWrYmNjFRwcrI8++kiPPfaY7rvvPs2YMYPQbwcZl/N07c4eq/XX4wAAAHVVrQ3++/btU2hoqOrVq6cmTZqoT58+kiRvb2/de++9kqQWLVooOztbDRs21Lx587R582bNmzdPX3zxha5cKXtrR1ZWljIyMtS7d29J0tChQ/XSSy/pm2++UVhYmFxdXeXk5KSBAwcqISGhwlpDQkJK1AP78mngKtM19/+aTL8eBwAAqKtqbfB3dXUtcUOmk9Ovu5ZcXFyKj5lMJlmtVqWlpWnIkCHKyclRjx49FBkZWe7NnPXq1SvxOj8/X2fOnJHFYrnu2qKiouJ+fn/s936r6drrYB/Ojo6606Ohfnv4j4PJpDs9GrLNBwAA1Gm1Nvh369ZNn332mQoKCpSTk6Ndu3aVee2RI0d055136sknn1Tbtm21e/fucm+sbdSokZo2baqvv/5akhQXF6f58+erS5cu2rx5s/Ly8lRUVKS1a9eqS5cucnd3V3Z2trKyslRQUKAvv/yywvodHR25udeOmjVyKw76zo4OatbIzc4VAQAAVK9ae3Nv9+7ddezYMUVGRsrd3V0+Pj5lXtutWzetXLlS/fr1k7Ozs9q0aaOkpKRy258zZ46mT5+umJgYeXp6KiYmRr6+vjp+/LgGDhyooqIihYSEaNiwYXJyctKoUaM0aNAgNW3aVPfff3+F9YeEhGjatGmaPXu2OnTocNPjR+WYTCa18HLXkfMX1cLLXaZr9/4AAADUMSZrHdl7MnHiRHXq1ElRUVH2LqVaZWbmymKx3VcWH79d7u71le93t836vFZkx6Cbuv5m/nJvQ4/6ys2+eitlVQkfn0bKyMixW/8Vqen1VUZdHhuMjbmNuoq5XTEHB5O8vRuWeb7WrvhXhXHjxunkyZPXHe/Tp4+ef/55O1SEslTXP/T6zk66sV8RAAAAarc6E/xnzZp10++ZN29eNVQCAAAA1Dy19uZeAAAAADeO4A8AAAAYQJ3Z6oPqERAQpMaebrq7xc3dYFuVzOaRa8OHAAAN3UlEQVTr/34CAAAAbg7BH+Xy9w/gLnoAAIA6gK0+AAAAgAGw4o9ypaQkKzu7gTw8/OxdCgAAACqBFX+UKzn5pE6cOGHvMgAAAFBJBH8AAADAAAj+AAAAgAEQ/AEAAAADIPgDAAAABkDwBwAAAAzAkME/MTFRw4cP1+TJk3XkyJEyr0tNTVWfPn1uuZ8+ffooNTVV8fHxmj9//i23AwAAAFSWoZ/jP3PmTJv089BDD+mhhx6ySV8AAABAaQwd/IcPH64xY8ZIkt599125urrqxx9/VMuWLTV37twS127btk1vvfWWPvjgA1ksFk2dOlU///yzTCaTxo0bpwcffFC//PKLJkyYoJ9//lmBgYHKz8+XJK1bt0579+7VrFmz1KdPHw0YMEBfffWVrl69qtmzZ+u+++6z+dgBAABgLIbc6lOaAwcOaOrUqfrss8907tw5ffXVV8XnvvrqK7311ltaunSpvLy8NHPmTA0cOFDr1q3TO++8o6lTpyo3N1cLFizQvffeq40bN+qJJ57QhQsXSu2rcePGWrNmjaKjo/Xuu+/aaogAAAAwMEOv+P9eixYt1LRpU0lSYGCgsrOzJUkXL17U2LFjNXbsWDVp0kSStGfPHiUnJ2vBggWSpKKiIp05c0Z79+7VvHnzJEnBwcG64447Su0rJCSkuM/t27dX67gAAAAAieBfzMXFpfhnk8kkq9Va/PNbb72l8ePHKywsTH5+frJYLFq+fLkaN24sSUpPT1eTJk1KvE+SHB0dy+3LZDJV13AAAACAEtjqU4HGjRura9euevzxxzVjxgxJUpcuXfTxxx9Lkk6ePKkBAwbo6tWr6tq1q+Li4iRJhw8f1k8//WS3ugEAAIDfI/jfoGeeeUZJSUmKj4/XlClTdOjQIYWHh+t//ud/FBMTo4YNG+q5557TmTNnFBYWpvfff7/MrT4AAACArZmsv9+bghovMzNXFovtvrL4+O1yd6+v4OAQm/VpSz4+jZSRkWPY/itS0+urjLo8Nhgbcxt1FXO7Yg4OJnl7Nyz7vA1rAQAAAGAnBH8AAADAAAj+AAAAgAEQ/AEAAAAD4Dn+KFdAQJC8vBrYuwwAAABUEiv+KJe/f4CCgoLsXQYAAAAqieAPAAAAGADBHwAAADAAgj8AAABgAAR/AAAAwAAI/gAAAIABEPwBAAAAAyD4AwAAAAZA8AcAAAAMgOAPAAAAGADB/xasW7dOEydOlCT16dNHqampZV6bmJio4cOHl3ouIiKiWuoDAAAArkXwt6O4uDh7lwAAAACDcLJ3ATXJzz//rPHjx+vKlStycHDQQw89pF27dmnVqlWSpPXr1+vgwYNq27btde/Nzc3VpEmTlJ6ervPnz+uBBx5QTEyMJOnixYsaNWqUzp8/rzZt2mjatGlydnZWy5Yt9cMPP9h0jAAAADAmVvx/Z82aNerVq5fWrVunCRMmqF69esrIyNBPP/0k6dfgHxUVVep7d+7cqVatWumTTz7Rtm3bdPDgQX333XeSpNTUVL388svasGGDLl++rJUrV9psTAAAAIBE8C+ha9euWrp0qcaNG6f09HQNHz5ckZGR2rBhg86dO6fMzMxSV/slqX///urWrZs++OADzZgxQ7/88ouuXLkiSXrggQd01113yWQyKTw8XHv37rXlsAAAAAC2+vxex44dtXnzZu3cuVNbtmzR+vXrNWPGDD399NNydnYu92bcFStWaNu2bRo8eLAefPBBnThxQlarVZLk5PSfj9lqtZZ4DQAAANgCCfR3YmJi5OvrqyeffFKdO3dWZGSkmjdvrqZNm2rVqlXlbtH5+uuvNWTIEIWHhyspKUnff/+9LBaLHBwctH//fp07d05NmzZVbGysQkJCbDgqAAAAgOBfwvDhwzVu3DitX79ejo6OmjZtmiSpX79+2r59u/z8/Mp878iRIzV9+nQtXbpUDRo0UPv27ZWamqo//OEPCgoK0qRJk5SRkaEuXbpo0KBBthoSAAAAIEkyWX/bj4JSFRUV6cUXX1Tfvn0VGhpq73KUmZkri8W2X5mPTyNlZOTYtE9bsffY7N1/RWp6fZVRl8cGY2Nuo65iblfMwcEkb++GZZ+3YS21jtVqVUhIiEwmkx5++GF7lwMAAADcMrb6lMNkMikhIcHeZQAAAACVxoo/AAAAYAAEfwAAAMAACP4AAACAAbDHv5ZxcDAZql9bsPfY7N1/RWp6fZVRl8cGY2Nuo65ibpevos+Hx3kCAAAABsBWHwAAAMAACP4AAACAARD8AQAAAAMg+AMAAAAGQPAHAAAADIDgDwAAABgAwR8AAAAwAII/AAAAYAAEfwAAAMAACP4oV25urvr376/U1FR7l1KlFi1apLCwMIWFhSkmJsbm/c+fP1/9+vVTWFiYli1bZvP+b8SIESMUFhamiIgIRURE6NChQ/YuqVKunct79uxReHi4QkND9eabb9q5OuDm3Oh8Pn78uAYOHKhHHnlEkydPVlFRkb1KBspU2fl87tw5PfHEE+rbt6/++7//W5cvX7bLOGoDgj/KdOjQIT3++OM6deqUvUupUnv27NFXX32l9evXKzY2Vt99950+//xzm/W/d+9effPNN9qwYYPWrl2rFStWKDk52Wb93wir1ark5GTFxcUV/9e2bVt7l3XLrp3LeXl5mjRpkt5++21t2bJFR48e1a5du+xbJHCDbmY+T5gwQS+//LK2bdsmq9Wq1atX27Fy4HpVMZ9feeUVDR06VFu3btV9992nt99+217DqfEI/ijT6tWrNW3aNPn6+tq7lCrl4+OjiRMnytnZWfXq1VNgYKDOnTtns/47deqkDz/8UE5OTsrMzJTZbJabm5vN+r8RycnJMplMGj16tAYMGKB//OMf9i6pUq6dy4cPH9add96pO+64Q05OTgoPD9fWrVvtXCVwY250Pp89e1Z5eXlq166dJCkqKop5jhqnsvO5sLBQ+/bt0yOPPFLiOErnZO8CUHPNnDnT3iVUixYtWhT/fOrUKW3ZskWrVq2yaQ316tXTggULtHTpUvXt21d+fn427b8ily5dUteuXTV9+nTl5eVpxIgR8vf3V7du3exd2i25di6fP39ePj4+xa99fX2Vnp5u67KAW3Kj8/na4z4+Psxz1DiVnc8XL15Uw4YN5eTkVOI4SseKPwwrKSlJf/7zn/XSSy/prrvusnn/zz33nBISEpSWllbj/vd7+/btFRMTIzc3N3l5eWnQoEF1aiuM1Wq97pjJZLJDJUDllTWfmeeojW52PjPPbw7BH4a0f/9+Pfnkkxo3bpwiIyNt2vePP/6o48ePS5Lq16+v0NBQ/fDDDzatoSL/+te/lJCQUPzaarUWr6bUBX5+frpw4ULx6/Pnz9e5LW0wjrLm87XHMzIymOeo8W52Pnt5eSk3N1dms7nEcZSO4A/DSUtL07PPPqu5c+cqLCzM5v2npqZqypQpKigoUEFBgeLj49WxY0eb11GenJwcxcTEKD8/X7m5uVq/fr3++Mc/2rusKtO2bVulpKTo9OnTMpvN2rRpk3r06GHvsoBbUtZ8bt68uVxcXLR//35JUmxsLPMcNd7Nzud69erpgQce0JYtW0ocR+nqzhIecIOWLFmi/Px8zZo1q/hYdHS0Hn/8cZv037NnTx06dEiPPfaYHB0dFRoaapdfQMrTu3fv4hotFouGDh2q9u3b27usKuPi4qJZs2Zp7Nixys/PV8+ePdW3b197lwXckvLm89y5czVlyhRdvnxZ9957r0aMGGHnaoHy3cp8njZtmiZOnKh33nlHt912m/7v//7PnkOo0UzW0jZHAQAAAKhT2OoDAAAAGADBHwAAADAAgj8AAABgAAR/AAAAwAAI/gAAAIAB8DhPAIDdmc1mffjhh9q4caPMZrMKCwvVu3dvPf/883J2dq7Svg4fPqw1a9bo1VdfrdJ2AaCmY8UfAGB306dP14EDB7R8+XLFxcVpzZo1SklJ0eTJk6u8r5MnTyo9Pb3K2wWAmo7n+AMA7OrMmTMKDw/XV199pYYNGxYfz8jI0IEDB9S1a1e98sor+v7772UymRQSEqL//d//lZOTk1q2bKmEhAR5eXlJUvHrpKQkvfnmm7rjjjuUlJSkgoICTZ06VXfeeacef/xx5eTkKDQ0VG+88Ya9hg0ANseKPwDAro4dO6agoKASoV+SfHx8FBoaqhkzZqhx48bauHGj1q5dqx9++EFLly6tsN3Dhw/rz3/+s2JjYzVo0CAtWrRIt912m5577jk98MADhH4AhkPwBwDYlYODgywWS5nnd+/erWHDhslkMsnZ2VnR0dHavXt3he02a9ZMrVq1kiTde++9ys7OrrKaAaA2IvgDAOyqTZs2Sk5OVm5ubonj6enpeuaZZ677pcBisaioqOi6dgoKCkq8dnV1Lf7ZZDKJna0AjI7gDwCwKz8/P4WHh2vSpEnF4T83N1fTp09X48aN1b17d3300UeyWq0qKCjQ6tWr9eCDD0qSvLy8dOTIEUnS559/fkP9OTo6lvqLAwDUdQR/AIDdTZs2TUFBQYqOjlZERIT+9Kc/KSgoSDNmzNCUKVOUlZWl8PBwhYeHy9/fX//1X/8lSZoyZYpeffVVRUZG6tixY/Lx8amwr/bt2ys5OVnPPvtsdQ8LAGoUnuoDAAAAGAAr/gAAAIABEPwBAAAAAyD4AwAAAAZA8AcAAAAMgOAPAAAAGADBHwAAADAAgj8AAABgAAR/AAAAwAD+HyXBf26SvL+2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = metrics[metrics.columns].reset_index().melt(id_vars=\"DOI\")\n",
    "sns.boxenplot(y=\"variable\", x=\"value\", data=pdf, order=count_order[::-1], k_depth=\"trustworthy\", color=cp3[0])\n",
    "plt.ylabel(\"\")\n",
    "plt.xlabel(\"Count\")\n",
    "plt.xscale(\"log\")\n",
    "ticks = [1,2,3,5,10,100,1000]\n",
    "plt.xticks(ticks, ticks);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>avg_citation_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>discipline</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Biology</th>\n",
       "      <td>2.366737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Biomedical Research</th>\n",
       "      <td>2.236923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chemistry</th>\n",
       "      <td>1.434047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clinical Medicine</th>\n",
       "      <td>2.030200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Earth and Space</th>\n",
       "      <td>0.982333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Engineering and Technology</th>\n",
       "      <td>2.124703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Health</th>\n",
       "      <td>0.787700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mathematics</th>\n",
       "      <td>1.490500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Physics</th>\n",
       "      <td>1.435974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Professional Fields</th>\n",
       "      <td>1.083000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Psychology</th>\n",
       "      <td>0.115000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            avg_citation_score\n",
       "discipline                                    \n",
       "Biology                               2.366737\n",
       "Biomedical Research                   2.236923\n",
       "Chemistry                             1.434047\n",
       "Clinical Medicine                     2.030200\n",
       "Earth and Space                       0.982333\n",
       "Engineering and Technology            2.124703\n",
       "Health                                0.787700\n",
       "Mathematics                           1.490500\n",
       "Physics                               1.435974\n",
       "Professional Fields                   1.083000\n",
       "Psychology                            0.115000"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wos.groupby(\"discipline\").citation_score.mean().to_frame(\"avg_citation_score\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = wos.melt(id_vars=\"discipline\", value_vars=\"citation_score\")\n",
    "sns.boxenplot(y=\"discipline\", x=\"value\", data=pdf)\n",
    "plt.xlim(0,15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Web of Science in detail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = pd.DataFrame(index=range(2000,2020))\n",
    "pdf['count'] = wos.groupby(\"year\").size()\n",
    "pdf['count'].plot(kind=\"bar\", color=cp3[0]);\n",
    "sns.despine()\n",
    "plt.title(\"Articles indexed in WoS by years\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = wos.replace(0, np.nan).melt(id_vars=\"year\", value_vars=\"citations\")\n",
    "for y in range(pdf.year.min(),pdf.year.max()+1):\n",
    "    if str(y) not in pdf.year:\n",
    "        pdf.loc[len(pdf)+1] = [y, 'citations', np.nan]\n",
    "sns.boxenplot(x=\"year\", y=\"value\", data=pdf, color=cp3[0])\n",
    "plt.title(\"Letter-value plot of citation counts by year\")\n",
    "plt.ylim(1,2000)\n",
    "plt.yscale(\"log\")\n",
    "plt.ylabel(\"\")\n",
    "ticks = [1,2,3,5,10,20,30,50,100,200,300,500,1000]\n",
    "plt.yticks(ticks, ticks);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = pd.DataFrame(index=range(2000,2020))\n",
    "pdf['mean'] = wos.groupby(\"year\").citations.mean()\n",
    "pdf['mean'].plot(kind=\"bar\", color=cp3[0])\n",
    "sns.despine()\n",
    "plt.title(\"Average citations for articles by year\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Altmetrics in detail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "altmetrics['year'] = altmetrics.published_on.map(lambda x: str(x.year))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdf = altmetrics.groupby(\"year\").size().to_frame(\"count\")\n",
    "pdf.index = pdf.index.astype(float)\n",
    "for y in range(int(pdf.index.min()), int(pdf.index.max()+1)):\n",
    "    if y not in pdf.index:\n",
    "        pdf.loc[y] = [np.nan]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = altmetrics.groupby(\"year\").size().to_frame(\"count\")\n",
    "pdf = pdf[pdf.index.astype(float)>1996]\n",
    "pdf.plot(kind=\"bar\", color=cp3[0]);\n",
    "plt.title(\"Articles indexed in Altmetric.com by year\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_metrics = ['twitter_accounts', 'fb_pages']\n",
    "pdf = altmetrics.melt(id_vars=\"year\", value_vars=plt_metrics, value_name=\"counts\")\n",
    "pdf = pdf[pdf.year.astype(float)>1996]\n",
    "pdf = pdf.dropna()\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(20, 10)\n",
    "sns.boxenplot(x=\"year\", y=\"counts\", hue=\"variable\", data=pdf, ax=ax, palette=\"Paired\")\n",
    "plt.yscale(\"log\")\n",
    "ticks = [1,2,3,5,10,20,30,50,100,200,300,500,1000]\n",
    "plt.yticks(ticks, ticks);\n",
    "plt.title(\"Altmetrics counts by year for select metrics\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_metrics = ['news_outlets', 'wikipedia']\n",
    "pdf = altmetrics.melt(id_vars=\"year\", value_vars=plt_metrics, value_name=\"counts\")\n",
    "pdf = pdf[pdf.year.astype(float)>1996]\n",
    "pdf = pdf.dropna()\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(20, 10)\n",
    "sns.boxenplot(x=\"year\", y=\"counts\", hue=\"variable\", data=pdf, ax=ax, palette=\"Paired\")\n",
    "plt.yscale(\"log\")\n",
    "ticks = [1,2,3,5,10,20,30,50,100,200,300,500,1000]\n",
    "plt.yticks(ticks, ticks);\n",
    "plt.title(\"Altmetrics counts by year for select metrics\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### By Research Programs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>References</th>\n",
       "      <th>Found DOI</th>\n",
       "      <th>Found (%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>program</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NFRP</th>\n",
       "      <td>208</td>\n",
       "      <td>197</td>\n",
       "      <td>94.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSCRP</th>\n",
       "      <td>208</td>\n",
       "      <td>197</td>\n",
       "      <td>94.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRORP</th>\n",
       "      <td>354</td>\n",
       "      <td>271</td>\n",
       "      <td>76.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCRP</th>\n",
       "      <td>8308</td>\n",
       "      <td>6246</td>\n",
       "      <td>75.18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         References  Found DOI  Found (%)\n",
       "program                                  \n",
       "NFRP            208        197      94.71\n",
       "TSCRP           208        197      94.71\n",
       "PRORP           354        271      76.55\n",
       "PCRP           8308       6246      75.18"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = refs.groupby(\"program\").size().to_frame(\"total references\")\n",
    "df['found in crossref'] = articles.groupby(\"program\").DOI.nunique()\n",
    "df[\"found (%)\"] = 100 * df['found in crossref'] / refs.groupby(\"program\").size()\n",
    "df.columns = [\"References\", \"Found DOI\", \"Found (%)\"]\n",
    "df = df.sort_values(\"References\")\n",
    "df.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COCI (Cov in %)</th>\n",
       "      <th>WoS (Cov in %)</th>\n",
       "      <th>Altmetric (Cov in %)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>program</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NFRP</th>\n",
       "      <td>97.97</td>\n",
       "      <td>66.50</td>\n",
       "      <td>59.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSCRP</th>\n",
       "      <td>97.97</td>\n",
       "      <td>66.50</td>\n",
       "      <td>59.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRORP</th>\n",
       "      <td>96.68</td>\n",
       "      <td>71.96</td>\n",
       "      <td>56.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCRP</th>\n",
       "      <td>96.13</td>\n",
       "      <td>36.60</td>\n",
       "      <td>49.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         COCI (Cov in %)  WoS (Cov in %)  Altmetric (Cov in %)\n",
       "program                                                       \n",
       "NFRP               97.97           66.50                 59.39\n",
       "TSCRP              97.97           66.50                 59.39\n",
       "PRORP              96.68           71.96                 56.09\n",
       "PCRP               96.13           36.60                 49.70"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cs = ['coci_citations', 'citations', 'posts_count']\n",
    "\n",
    "x = metrics.groupby([\"DOI\", \"program\"])[cs].mean().reset_index().groupby(\"program\").count()[cs]\n",
    "x[cs] = x[cs].apply(lambda x: 100 * x / articles.groupby(\"program\").DOI.nunique())\n",
    "x.columns = [\"COCI (Cov in %)\", \"WoS (Cov in %)\", \"Altmetric (Cov in %)\"]\n",
    "x.reindex(df.index).round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>grant_id</th>\n",
       "      <th>program</th>\n",
       "      <th>coci_citations</th>\n",
       "      <th>citations</th>\n",
       "      <th>twitter_accounts</th>\n",
       "      <th>citation_score</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MP980015</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PC081249P1</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>176.000000</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PC081249</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>176.000000</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PC081246</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.575000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PC081176</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.672000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2239</th>\n",
       "      <td>PC100473</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>89.487805</td>\n",
       "      <td>71.633333</td>\n",
       "      <td>2.153846</td>\n",
       "      <td>3.444767</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2240</th>\n",
       "      <td>PC010267</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>23.527273</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.779500</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2241</th>\n",
       "      <td>PC051369</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>43.629630</td>\n",
       "      <td>30.780000</td>\n",
       "      <td>11.272727</td>\n",
       "      <td>1.319580</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2242</th>\n",
       "      <td>PC081610</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>73.276316</td>\n",
       "      <td>101.909091</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>3.421500</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2243</th>\n",
       "      <td>PC021004</td>\n",
       "      <td>PCRP</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>1.388000</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        grant_id program  coci_citations   citations  twitter_accounts  \\\n",
       "0       MP980015    PCRP        1.000000         NaN               NaN   \n",
       "1     PC081249P1    PCRP      176.000000  163.000000               NaN   \n",
       "2       PC081249    PCRP      176.000000  163.000000               NaN   \n",
       "3       PC081246    PCRP       36.000000   30.000000               NaN   \n",
       "4       PC081176    PCRP       19.000000   12.000000          1.000000   \n",
       "...          ...     ...             ...         ...               ...   \n",
       "2239    PC100473    PCRP       89.487805   71.633333          2.153846   \n",
       "2240    PC010267    PCRP       23.527273   20.500000               NaN   \n",
       "2241    PC051369    PCRP       43.629630   30.780000         11.272727   \n",
       "2242    PC081610    PCRP       73.276316  101.909091          4.750000   \n",
       "2243    PC021004    PCRP      133.000000   83.000000          1.200000   \n",
       "\n",
       "      citation_score  count  \n",
       "0                NaN      1  \n",
       "1           4.770000      1  \n",
       "2           4.770000      1  \n",
       "3           0.575000      1  \n",
       "4           0.672000      1  \n",
       "...              ...    ...  \n",
       "2239        3.444767     41  \n",
       "2240        0.779500     57  \n",
       "2241        1.319580     83  \n",
       "2242        3.421500     97  \n",
       "2243        1.388000    136  \n",
       "\n",
       "[2244 rows x 7 columns]"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = metrics.groupby([\"grant_id\", \"program\"])[['coci_citations', 'citations', 'twitter_accounts', 'citation_score']].mean()\n",
    "df['count'] = metrics.groupby([\"grant_id\", \"program\"]).size()\n",
    "df = df.sort_values(\"count\").reset_index()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f17dac92358>"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 841.68x595.44 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df['citation_score'] = 100*df['citation_score']\n",
    "sns.scatterplot(x=\"citation_score\", y=\"twitter_accounts\", hue=\"program\", size=\"count\", data=df, sizes=(50,300), alpha=.5)\n",
    "# plt.xlim(0, 500)\n",
    "# plt.ylim(0, 100)\n",
    "# plt.yscale(\"log\")\n",
    "# plt.xscale(\"log\")"
   ]
  },
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   "metadata": {},
   "source": [
    "## To-Do\n",
    "\n",
    "New data to get\n",
    "\n",
    "- Get Metadata from Crossref\n",
    "- Get OA status from unpaywall\n",
    "- clinicaltrials.gov\n",
    "\n",
    "Available data from DoD\n",
    "\n",
    "- Patents\n",
    "- Drugs to market\n",
    "\n",
    "Notes\n",
    "\n",
    "- Do analysis for \n",
    "\n",
    "For grants\n",
    "\n",
    "- award size\n",
    "- and some measures\n",
    "\n",
    "Next Thing To Do:\n",
    "- Get some plots going to present the gist of this"
   ]
  }
 ],
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