FW_NLP_Final.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NLP on Food Waste Patent Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Data preparation and basic analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: 'dplyr'\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "The following objects are masked from 'package:base':\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "\n",
      "Attaching package: 'lubridate'\n",
      "\n",
      "The following object is masked from 'package:base':\n",
      "\n",
      "    date\n",
      "\n",
      "Loading required package: NLP\n",
      "-- Attaching packages --------------------------------------- tidyverse 1.2.1 --\n",
      "v ggplot2 2.2.1     v readr   1.1.1\n",
      "v tibble  1.4.1     v purrr   0.2.4\n",
      "v tidyr   0.7.2     v stringr 1.2.0\n",
      "v ggplot2 2.2.1     v forcats 0.2.0\n",
      "-- Conflicts ------------------------------------------ tidyverse_conflicts() --\n",
      "x ggplot2::annotate()      masks NLP::annotate()\n",
      "x lubridate::as.difftime() masks base::as.difftime()\n",
      "x lubridate::date()        masks base::date()\n",
      "x dplyr::filter()          masks stats::filter()\n",
      "x lubridate::intersect()   masks base::intersect()\n",
      "x dplyr::lag()             masks stats::lag()\n",
      "x lubridate::setdiff()     masks base::setdiff()\n",
      "x lubridate::union()       masks base::union()\n",
      "Loading required package: RColorBrewer\n",
      "\n",
      "Attaching package: 'igraph'\n",
      "\n",
      "The following objects are masked from 'package:purrr':\n",
      "\n",
      "    compose, simplify\n",
      "\n",
      "The following object is masked from 'package:tidyr':\n",
      "\n",
      "    crossing\n",
      "\n",
      "The following object is masked from 'package:tibble':\n",
      "\n",
      "    as_data_frame\n",
      "\n",
      "The following objects are masked from 'package:lubridate':\n",
      "\n",
      "    %--%, union\n",
      "\n",
      "The following objects are masked from 'package:dplyr':\n",
      "\n",
      "    as_data_frame, groups, union\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    decompose, spectrum\n",
      "\n",
      "The following object is masked from 'package:base':\n",
      "\n",
      "    union\n",
      "\n",
      "\n",
      "Attaching package: 'Matrix'\n",
      "\n",
      "The following object is masked from 'package:tidyr':\n",
      "\n",
      "    expand\n",
      "\n",
      "\n",
      "Attaching package: 'scales'\n",
      "\n",
      "The following object is masked from 'package:purrr':\n",
      "\n",
      "    discard\n",
      "\n",
      "The following object is masked from 'package:readr':\n",
      "\n",
      "    col_factor\n",
      "\n",
      "\n",
      "Attaching package: 'magrittr'\n",
      "\n",
      "The following object is masked from 'package:purrr':\n",
      "\n",
      "    set_names\n",
      "\n",
      "The following object is masked from 'package:tidyr':\n",
      "\n",
      "    extract\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Load packages\n",
    "library(dplyr)\n",
    "library(tidytext)\n",
    "library(lubridate)\n",
    "library(tm)\n",
    "library(tidyverse)\n",
    "library(stringr)\n",
    "library(ggplot2)\n",
    "library(wordcloud)\n",
    "library(RColorBrewer)\n",
    "library(readr)\n",
    "library(tidyr)\n",
    "library(igraph)\n",
    "library(ggraph)\n",
    "library(widyr)\n",
    "library(topicmodels)\n",
    "library(Matrix)\n",
    "library(janeaustenr)\n",
    "library(scales)\n",
    "library(magrittr)\n",
    "library(Matrix)\n",
    "library(textstem)\n",
    "library(DT)\n",
    "library(tools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set theme\n",
    "theme_set(theme_minimal())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load data on food waste patents\n",
    "df <- read.csv(\"fw1.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Keep text only\n",
    "df <- as.character(df$text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clean up text\n",
    "df <- removeNumbers(df) #remove the numbers from the text\n",
    "df <- removePunctuation(df) # remove the punctuation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tokenize text and remove stop words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Converting text vector into a dataframe\n",
    "text_df <- data_frame(line = 1:length(df), text = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Tokenize\n",
    "tokenized <- text_df %>%\n",
    "    unnest_tokens(word, text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Joining, by = \"word\"\n"
     ]
    }
   ],
   "source": [
    "#Remove common stop words\n",
    "data(\"stop_words\")\n",
    "\n",
    "# Custom stop words\n",
    "additional_stop_words <- data_frame(word=c(\"figref\", \"idrefdrawingsfig\", \"bb\", \"xb\", \"patent\", \"document\", \n",
    "                                           \"xbsubsub\", \"fig\"， \"invention\"),\n",
    "                                   lexicon = rep(\"custom\"))\n",
    "\n",
    "#Bind stop word data\n",
    "all_stops <- bind_rows(stop_words, additional_stop_words)\n",
    "\n",
    "# Remove stops\n",
    "clean_text_df <- tokenized %>% \n",
    "    anti_join(all_stops)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic word count visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get count of top words\n",
    "clean_text_df_count <- clean_text_df %>% \n",
    "    count(word, sort = TRUE)  %>% \n",
    "    filter(n > 2000)  %>% \n",
    "    mutate(word = reorder(word, n)) %>% \n",
    "    ggplot(aes(word,n)) +\n",
    "    geom_col() +\n",
    "    xlab(NULL) +\n",
    "    coord_flip()\n",
    "# clean_text_df_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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V6O24ASB7HKYmBCBynp2FM9lYa3w4Ec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\nEvD/ARtH39WxOYZAAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show wordcloud of top words\n",
    "set.seed(0)\n",
    "clean_text_df %>%\n",
    "    count(word) %>%\n",
    "    with(wordcloud(word, n, max.words = 100, colors=brewer.pal(8, \"Dark2\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. TF-IDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import data\n",
    "df_with_patent_id <- read.csv(\"fw1.csv\", stringsAsFactors = F)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_patent_id$country <- NULL\n",
    "df_with_patent_id$title <- NULL\n",
    "df_with_patent_id$abstract <- NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_patent_id$Abstract <- df_with_patent_id$text\n",
    "df_with_patent_id$text <- NULL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_patent_id$Abstract <- as.character(df_with_patent_id$Abstract)  %>% \n",
    "    removeNumbers() %>% \n",
    "    removePunctuation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "a <- mdy(df_with_patent_id$IssueDate)\n",
    "df_with_patent_id$IssueDate  <- as.factor(year(a))\n",
    "# head(df_with_patent_id, n=20)\n",
    "\n",
    "df_with_patent_id$PatentNo  <- NULL\n",
    "# df_with_patent_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Joining, by = \"word\"\n"
     ]
    }
   ],
   "source": [
    "abstract_words <- df_with_patent_id %>% \n",
    "    unnest_tokens(word, Abstract)  %>% \n",
    "    anti_join(all_stops) %>% \n",
    "    count(IssueDate, word, sort=TRUE) %>% \n",
    "    ungroup()\n",
    "\n",
    "total_words <- abstract_words %>% \n",
    "    group_by(IssueDate) %>% \n",
    "    summarize(total = sum(n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Joining, by = \"IssueDate\"\n"
     ]
    }
   ],
   "source": [
    "abstract_words <- left_join(abstract_words, total_words)\n",
    "# abstract_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in is.na(e1) | is.na(e2):\n",
      "\"longer object length is not a multiple of shorter object length\"Warning message in `==.default`(IssueDate, c(\"2010\", \"2011\", \"2012\", \"2013\", \"2014\", :\n",
      "\"longer object length is not a multiple of shorter object length\"`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.\n",
      "Warning message:\n",
      "\"Removed 172 rows containing non-finite values (stat_bin).\"Warning message:\n",
      "\"Removed 8 rows containing missing values (geom_bar).\""
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KoktZ3gMVxjke741eaVDTYma0Ra9RuyiU7NPd17u24Ff0t8gkhESoGvEGndnA2b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\n5P8Bjup/lkEKbpgAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(subset(abstract_words, IssueDate == c(\"2010\", \"2011\", \"2012\", \"2013\", \"2014\",\"2015\",\"2016\",\"2017\",\"2018\"), select=c(IssueDate:total)), \n",
    "       aes(n/total, fill = IssueDate)) +\n",
    "  geom_histogram(show.legend = FALSE) +\n",
    "  xlim(NA, 0.0009) +\n",
    "  facet_wrap(~IssueDate, ncol = 2, scales = \"free_y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_words <- df_with_patent_id %>% \n",
    "    count(IssueDate, sort=TRUE) \n",
    "# total_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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TaRIiOLeUTS/Jk9cdKfRDkR8h9xijcMkZzIVW3upLFFcs7+7m1LgoI9dkCuanMn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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(data=subset(total_words, IssueDate %in% c(\"1990\":\"2018\"))) +\n",
    "    geom_col(aes(IssueDate, n, fill=IssueDate)) +\n",
    "    coord_flip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "freq_by_rank <- abstract_words %>%\n",
    "  group_by(IssueDate) %>%\n",
    "  mutate(rank = row_number(),\n",
    "         `term frequency` = n/total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YDah+trH65vpzc2brAdEl21ODGtLmt3yRxPq/Gu6x/HwXZERNRnMdgl4tidg1zp\nA82n3p++hQe3q+3xt0aLdgAaq9D4ow2isEgUFo0KZjW8u3FUMEs3qs03NmkFEBYA9vTna231\nEmjSIv9fyfRHR88AkBUQANa95/FWjvNWjps35Svt+AyKcysPA2LV0AZVtFNO2i2rtOyQRc9k\nu47crKJlvGPdjoiIKGEMdom6f4zrt5eZz7yNB/DgdhXvYrMdgE251wJQ8e7vm7eOCmaNawoi\nMAHApGmDISWkAGCRBwFI4MadX2WF8eexEwwpswJC1yzr3vMAQCCv/+VOle2UCyrP+Kg4M/ai\npq55cuqaJ9GiNxYndsi2mu16VPt3no2Ld13MdlzTjoiI+iwGuwS5P9kGID7bAWa2S/9DNNuN\n3r5BZTsArgyLSngAdGnRJQKWQgCQ0p6+ps6mSm7yWzu/8keCj445DwjGZjvdEjSkCGpm0Q6B\nQO6zOb7s+6LxLj/TBUBlu5biBtspPTqRIm4WRasP8wAudEdERNRFDHaJmPXlfgDuT7a5P9nm\n+u1lC77+vtrfnO0e3A4gPT96/OjtGxqPRLeXvvkWgPMzc/1BN2CZOnUwRH5Jk3W4P2BNX2JO\nl9jrSAfwx3PGAMGsQMiAVNmueK6uDpBAf18QQCCQC8DMdko72U5tmEW7WKekQ7atbNcVrNgR\nEVHfxGDXVe5PtsFyvXtuRMW7aLYD8OB2yAwz2+0ouVZlO1eGRWU7XQv7g25Y9YkXDwGgyXRX\nU9CubVPZbtGmyr2OdL/h/OM5YwCkWQ9CO7b2vU26Jbg73TA/ffJRuwHb738fApB9X2ZsvFMz\nKlpecGyHrNo45YPt4kp3Cot2REREnSWklCc/ik700uvn/dx5X9zOQ5YsAJ5VFgCxUysgGhqr\nAGDHmEmjS19OLwAAb0NkwezLttQf09O2Afh4za6SxqOGaKxwGLJhVtAYKwEBMfaqv/9o30IA\nP/xsO4BKRx0AnzF5eL1uNwDgSEbey2fYACwqlsOLgp6p+nPvus1yneqZjSvmAdj+dLq5Peb2\nRrURG+lO1dg7FQHNSBcOh+fM25qcK+njqqqq8vPzT34cdQ3bOTnYztSXsWKXoEWh3y0K/S52\nz4BIXSTiP3924/mzG7fXfXmszqsekfIa3V8TifhHbnvfrNspuhb2+8YCmDhzJGw2zZpTFNBE\nxmqrDKgDLiu/ywjbXelDVN0uP5ADIE1bvzuz+Xaxsw+GANx3UOyusLvX+v9sXWMagvIAACAA\nSURBVLd25vdjL6xl3c4Mc4hZ1i7Jd5JV4op5KudxsB0REVFiGOy6RMU7M+ENQlBtuOdG+s+1\nlIsiAPWZDQDSQ03pAWPktvcjhr+uwj/AKP3rquUDIkckjIjRFDGaXDOK67XaRrsAoFl2CkBC\nLvJUlupZY2vOGNXofGfYeA2GynaaaFR3GCtoqM6IAIBxPNsBeNC3eNaFtth41062Mztk48xd\n705OvJs8z9PyThXdle042I6IiPoUBrtE7HM0P6651HPNpZ7d069X8c7MdgDcl1eVi6JyUaSy\nHbRAesD4uPgCAFrTUACvfVhqhy/onwDggC2v3FoMIN2AzHzHalFdkHKRp2LSiL/faCwB8M6w\n8WkG8gM5uti6N71JfUpI4PJDPg0hAAiHVLYD8KBv8Xljdnsbol3t7axyZ/bMrprsieuEPVWl\nuzi8LwUREVFHcIxdIhatOc9qtbb16rKMZ5qnUACu9IFLXwoCcNU3RCJ+GI5Gexb0nQDK9MhV\nF5WUi8wg0uz6xkGy4ePV2wDUaWEARu0Pw3AI4N7xhZ8WvKEbtnu/nDxv9yd+IQDk+42jmtsZ\nkQD25uS8dUaFCA/QpXhgoAVArnOb+vR+Wa4/vR3Nmj+41O6ZqsdeaquD7dBankvCqLvY8XYq\n51VVVW3ZNDv2mASmzXJZu47gmKTkYDsnB9uZ+jJW7LrfjQ23/Erenxf+S9jwhw3/Z/VfLrjO\nvuA6u98wQsIessiMUH1GQGYE5NBg+sr1ZRZNF9AsmvOQpeCya64HkBkRAITFK2AAWLSp8twj\nc/yW8KKz1j9y9lRAAKjStcLIJ+oTHRHtsq/6Seshv4iU1JeN8h05Ul8iw+G4C/vT20H3Wn/s\n4zujj36zYPU3C1bHHdlq6a6nq3etFu14XwoiIqKOY8UuEbH/HHzsgzajxuORQQAqtYUAChEE\nUPpC9F02w6I5ygHUOHQAg2ef7zeseto2V3r+317fNMJXdchSDUA2XhKMnAsIQJ57ZXlxuNIp\ndGeOa/kLXxqQhU0RixT1GAdgb04OEP6g+GBADn64sKxABgD8TLv8z9Z1AP68Nde8qh9cao+9\nyGC1NxKJTsVwFpxv7le1vSSX7syinVmxM9s5NtJ113J3ZGKFIznYzsnBdqa+jMEuEe3/1oiN\neirbAajUFqps9/rrWcNr7QAarfk54lMBSIhnhl5717kHoH8OwJWev/7lNwAcslT//rzFd6zd\nIYQGadwzvv+bxZvPitQBcOa4/vHCbgADfEaN5rYaxrr+6QP94q0zjuqRQEAOfqj/XgADIuGf\naZffVHkngCbf7QC8DTIu2AFoOrLF3I7NdqbdDV4AX8u5tSON05XkF9cbG9fOZrZjsOt2/EOY\nHGzn5GA7U1/GYJeITv3WcG/8WUVDdObpf1jKH5d3v/56FoDhtXY4ym2GprpWa+TYovkZNn1j\nIRpWvl9VGD4QQgSAbJhlGKMisAH4uTvtkwF/csrJOJ7tBvgMAA0YV5GR90VGoNhve+uMAIDf\n9qsMaxFICaC64p8AfPuuVrcyQ2sr2539ykdqQ1h0vcVtx5TdDa3Mn20r7SUc72KLdm0FOzDb\ndTf+IUwOtnNysJ2pL2OwS0Rnf2u4N/7M3PZM+A1+teGz+mq0ku3OG3Td5wDMbNckwgBkwyxL\n2BUStl+Mz/D0fwLAP+rfATDW++vAV2GLBIAGjNuVl2szAEiV7R4oAAAbDlkNS2XlazhetENr\nwa5smdtc90TdmuIa++KWX6TMEu201Sx6y1cVM+ollu3aCXZg0a7H8A9hcrCdk4PtTH0Zg10i\nEvit0TLbAfD6mhZcm7fub1uthgagRp4HoCyt4aorPgew8X2vL9IESNkwS0RcACKw/dyd9q/i\nPwJYted/ADi/fGL4sRx1F7IvM2Yds0ubId8fGADws9Ef4Gh0poU1bz2ANR+MN6/hB/OPxV2h\nOdjuf8u+g5g7j5laRr1Wa3u7G7xdyXYdDHbofLbj9Nh28A9hcrCdk4PtTH0Zg10iEvut0Wq2\nAwBHubexacRRICbbaRCRjI8Gojwu290zPhvAB8VPCIgf1zwK4MdrXnMYQgBC4pN+M/SIFhaG\nynZPlLxzqPYSAEICgKXf+vaznTnYTmW7OC2jHoBr7Itbxrsi6xRzu7PZLnaYXcmFb7ZsZ2a7\nnsA/hMnBdk4OtjP1ZVzuJHk8E35jbseGPAQGudKd1sFOALliK4DBvjQD0tJwYbU2pEkMs8I6\nUO61aDsBPLKpFsC0g3dKyMdz7/p97k+GfGMrAAlIAQn4LYZVapeW6yVNFf/+xUybNGzSUJ8T\nOTp55sz2br3qLDjfYtEtFv3GoS9mZbniHnoY6hGs9pqPV4O3Ljs8ZdnhKbEr5FWE15nbnV0k\npf2VisFOWCIioraxYpeIrvxz8IS63VtXNr/gKPc2RAobNcM/CgBglKc1ASiJfLwvVwMwSs77\n6tgWIzJSAveOz36/+AnzrZ+9cldB5BMAAvgkbwYAZ0R8UhSxWXYH+l8G4OHwG5WaUx381o6g\nK32I2m452M69abfaePWL69v/Iq3ei+zG/usA2PNcnql6bKTrVN3OLNq1WrFD26vZdSTzsWjX\nKlY4koPtnBxsZ+rLGOwS0cXfGq1nO0c5AG9DpKBRe7V4/jV7dkqgPK1pRORjAahsJxtm5YSc\nAH53Tg2A58/8XzW6rqbu331vfqZO47OKnVnTnRFNwPAUGX6b919DxwP4V93mSotDHfPmtoYi\nIQH889Lm+8kqjxv/BaAowwXAM3547Etly1qJU3Hxzlzr+H+PzAJwZ7HfnGaxem4jOuakwQ5d\ny3bUEv8QJgfbOTmS085CCACn6m+o+vRY8+bNu/HGG2fMmFFYWNjBk7z77ru///3vV6xY0d1X\nR6fSqQl28+fPT+wnaf78+eZ27Bna2t9Duv5bo61s522IADCznYAoS/OVRD4GsC9XG1Ij9tpm\nOgIOmwz+wS1l2L/yjJcypTMom1Yv/7Eq2gU0I6JZdmZNT4vAU2RI4N2SDHX6NQ2b6oQTwKrN\nBRbLvvazHYCvps876RdRac+Md7E3sTCznXqqWfQOZjsz2IXD4alXt9l3zGzXjRg4koPtnBx9\nM9iZtm7dOnbs2I6fhPWdFHMKgp0KYQnEr7g4aD5ta3/P6ZbfGma2W/qq25U+MLrXUe5tiPiN\n8KbcayWE0Hxf311WmekbHIzPdv/pzhkoKy4qWnCPdkmmdP7s4/suOlSjsp3PKgDsT5+pinax\n2W51w6Y64RTRbLcXQJGIz3ZmsPsP7b8B3DWtozmp9CU3gGvsi6WaXXtkltqfcLZrP9jFOend\nxhj42sHAkRxs5+ToO8Eu9tMrKyuXL19+2223zZs3b+nSpdnZ2QmchFJAsidPJCF1nS7MuRQL\nrvF4Gw9E9x5qdGVYdM06vuZlAQlgVcmwwvo0f2C63dBGHIXVECMC7+YGtSfX1006OCK0ZcPT\n2xZa+426eWy9gDxiuQCAxYgA+MrZCGjjKywOS9rM0gaHtDoMy9y0SdmySQKXjztihIca4aHV\nhvX2HbPU465pntgYpxLeYx+41eOk36jkOk/JdR49z+UsON9ZcP6Y2xvH3N6YleX6a0P0bhbG\n8XuX9YST5jbeZ5aIes7KlSvnz58vhLjjjjvefffdjrwkhIgrvMXtqa2tXbx4sdq5ePHi2tra\ndi6gsLDw1ltv/ctf/rJy5cq1a9ea+0tLSx999FF1kvnz57/44ovmZ8VtdPYTqXdKdrBrK9XN\nj9Fd5+z9Wsl2eSPNV8fXvAzD6TfCq0qGAagLTRNA0OkAkGlfZR5WHR7xm/fOeWqPtjevyC5R\nq11gN0TQos2o3ChhWA2RX2/YpDa6YhugAdrlaZOzZVO29EsBAIHIGZ+WXadO5XvqPt9T9301\nfZ4aYxeng/EuzuAbPYNvbI5cM1ZYOvX22NVPTqpT2Y5TKIiou7z44ovz589fuXIlgKeffnrm\nzJlmgGvnpZNasGDBbbfdprZvu+22++6776RvueyyywBs3LhRPd22bdvIkSPvvvtu9XTlypU3\n3HCDme265ROpt+kVY+w62Jea2GFxqqqqErzoHjOr9LdqY9mKiSWO/gDgKC9tQkBGvjZtwu+3\nF+jCMveLPeqYLNtaFcdrQnM0qa05cxAAn60OwMia3JKjlQByjE9qHJaMEADsS58ugP3Z1iPO\n4IzcSW84q9anVwKQVusbdete2HIGACHx44tu/GBf85iMqe7vqY2qptI75f0tr/nmsatb7ox+\nnU+b1z1ZfW5zie669dEbmmma48VJZSdtlh0fzmq5c/RFbX5u+zZ9FD3b+AujZ/jTn/70gx/8\nILGzEdHpouf6ZGP7MdV2RUVFYWFhaWnpyJEj582bp/4SnfSl2L/CsXtUne+FF164/vrrAbz4\n4os33HDDmjVrZsyY0ep7Wz3JHXfc8fTTT3/00UeTJk0CUFZWduaZZ8ZdtnmS9j+RThfWU30B\n3eykXb3d8n/y7h3AsTX/ETXeTkB8EahwpQ/EkYDI1CHxrw82Tpk20ZX33hNTRy99yQKgEuMH\nBz/WNVs/65uHjMtfGxyKRJq+fiDLZ6vbnhUpOSoAeUy7IDvgqXVYM0IY0vje/vTpZ9aGAfu7\n2DC3esRcFL0+CP9Kq7w8+yKL3BMRmhR4fN2yGdfcu3ZzNHut3/pXle36Z46+d/xWAHG1uiWf\nz1YbLUfgbZ0B99ponottpaf959+ubwFgGAHf27Njy3itslqt4XDYaj3hR7T0o9nowFp3rZ4t\n7pIeOK6zp0pJHPuVHGzn5Eh+O8+bN2/lypXLly+fMGHC2LFjY/NWOy+17/XXXwegMpbauOGG\nG7Zs2dKpmPXUU0899dRTlZWV27ZtKysrMyt5PfeJdMr1lgWKu9IVmwJUn+yCazwAvI0HkDdS\njbQDsO6Dj73V0z3jvrbguoh5vN+IABigvf7IpgqLxfnKwLo3CrHI/fKagfkhgaDAJ9lDy5z+\nHVn+oGac2fgegDNrw+7DWs2RzwFcXo6JDQDw1+nDLMeXL/7dq4uGlbxvfoRxJDrsT61sFzf8\nztTx/tmS6zzm0ie3ZHlbXTwlVjvprVP9s3E40o6Iut2vfvWrefPm3Xbbbeedd94dd9xRWVnZ\nkZfa9/TTT+P4qDtz7J3Zqdpxv/zlL4uKis4777z58+c/9NBDSfhEOrV6S7BbcSIkFPVO65kZ\n8dkuMMiV0Twczf3JYsgd/kgYQJl9ImDEZruBsgLAuAOXQhoABHBmY65fng1gd0YwpBlDGt9T\n5xGGXlO5PVj52uyt6//f53mTGvDcRcVmtquretbMduv2v2FmO1P78e6kCe/JRpfKdhHDD6Bs\nmbv9eDf6otWT53liH+ZLnc12rQ6/Y7mOiLrF2LFjV6xYsX///ttvv/3pp5/+3ve+V1paetKX\neoI6+e9+9zv1dPHixQ899NDtt9++Zs2arVu3VlRU9NxHUy/RG8fYJfauZKa6nqvzuzf+bOmr\n0cjiCjR4M3W/EQYwZdpEAK6895a+NMJvWAGMiHgkNAAa8Oi0O2vqvACeyiz82/bsqYeOAtiT\nUT9lTpnnzUbAGN5gdxjREL8/fZohAunYDQA2G4BQ+NhBOTIiNACXjzuSlnND6ZZ8ADPO/gkA\nYbW/d3BJy0vNuWVJW0lumWi+pVjsrcYAzFqVjuPTY83Zsm11y7bazh2MdC0Lfu3U6rgSCrsI\nk4PtnByndrmTd999d+bMmR15Ke4MlZWVRUVFOHF4XFt/o9v69EcfffTuu+9uayhebW1tTk5O\nWxfQ/ifS6aK3VOxiJdAbe1rX6mJ5JvxGFe0AeB0Zrnq/2SELwFs93T1rEKTTMNJ2ianqMAO4\n+/0/H7YWHBCZ8xuaAEMCEhjWmL7ujcEAAG13RuiILv0WADiz8YOhDRuOaqNKnXmltswvbNn7\nnGeO8MuzfDZ1Qt+xF0rOr3p18Cb1VIaD04sXtrzUY88svHn36Jt3jw5X7QtX7Yt96UY5paLe\nqx5x71Lr2Km63S1Z0VdPWrqL1cEBdutXuuMiYDvpjf2zRNQVajUTVS0bPnw4gHnz5p30JbWx\nYcMGALW1tX/84x9jzzlt2jQA5gzWDRs2CCF++ctftnUNlZWVixcvvvvuu+fNmxc3Kk59em1t\nrVnJa1VnP5F6p15RsUOHbx3R6mEtg+BpsUBxO06o2+VJdTsKAAtmX+ZtrFr3Vi0AQwoAJcZ6\n9dLCcbdKGHZxNBgpvOErTD1UA2HsSW+cMqcM4YGe1aWALAzaM0OaAADpiMCADGvhjflnAxhZ\nnQVAwgpg1NcOALg+bezkeudD/Z7NCaYBeL+yzenxpr/kvG5uP2GNLshyZ3iu2rDmDwFw1zRP\n6Uvu76dHI92ztSesqxJXumunnTvVFRubBVm3axUrScnBdk6O5Ffs1ATS2FdXrFihclvHX1qx\nYoX6c6bOWVtbu2DBArVOimn//v2DBw8G2rvzxK5du0pKStR2y09XYit25izd9j+RThe8V2wi\nkvBbw8x2Q33V+qBctdPbEFkw+zIAS1/br/aceSwUydgACRzPdtJw3PAVph46AqAiu8oXcUy5\nJJoLf7R/yE8+f8/MdgDK0w6d0ZgPYGP+2bHZbsSUxhudZwB41/ECgPSIFcAL/l/HXuGZ1aPb\nuvi/5LxuBju0yHYAnm/ckit1AI5c11P7TnhvbLZLuJ1bxr526nzvvOE+dOjggAHF6MPZjoEj\nOdjOyXFKumJffPHFZcuWrVy5ct68ebfeeqtZluvgSyrtteycVTeTAPCLX/xiwYIFZmJrGexu\nv/32adOmzZkzJ+6eE4sXL449w8iRI82PUF3DZrBr/xPpdMFgl4jk/Nbw3vdK8xNHefNtx+69\nFgAe3K4qeYPCH6rdh52Oe0d92yZD392bVmcxLjpUJYTckxaaMjMIS1gd89OvBgO4b8uHQgKA\n32Jkis+F1bbHkn1GQz89bDlsn6yO/NIZWTKlYHxQ/23mc2rPa/t+pBUcv4YWWua86bk/B3DE\nUmsGOxzPdv4a7yt2P4BcqTtyXasme2K7Ys1s18V2bquq1zLkLXm2mMGOgSMJ2M7JwXamvozB\nLhFJ+60Rm+2G+qoB6BY7AOSNxKGm6Ash2Zj5udo86NTvGbUQEeu/7dfOq6wUAocyIlNm+nyR\ndFirAPxw3whNhHXNMu2g0xCRKYfW+C1GdXrAle4EECr3CcNuQAAIaBAiZEF41FURHP8hubfm\npin2c9u/5rFXR7ORuZqdZ6p+7JmFON5Xq7Ld841b1Kv9c6JTKGJLdyrbdUs7txrvmO3i8A9h\ncrCdk4PtTH0Zg10ikvlbo2W2U3SLHYHj4x5CMpy2DUDAKjVDOygnFgSFMxQCELIAQMHXB5jZ\n7kdlxZCOi4+k2Yzof3p35TvV6QG1PbxBlwEDQEADEM12uzMjqut2QLgMwMrLXwTQVBM/MUL5\nmuYCMPZqT2ywA6CyHY5Pp/XXeAGoul3LbNeNwQ4dy3ZmsEOfzHb8Q5gcbOfkYDtTX8Zgl4ik\n/tb41Qaole0AnJjtAOjh4QAQktJmNeybpZRqBF0wMAlAWigkhAxqYn+ONmb6MMOiinbDNc0H\nYHZVv0g4OvyuNC/4/PjSpa/uG1RnN6SE1JwRaWY7CYsA9mY24ni2Wz7+0bhu2dicp7LdLf1O\nWPTEDHYAcm5ZAuDXr6XjxGwXrG4+iT3PFQ6H35q6NfGma01syIvLdrHzKvpatuMfwuRgOycH\n25n6Mga7RJyq3xrqzmMAlq7qrzaG1mTudQ501dvjst1BOTE/KMxgB0BlO1gOGbD9qCxamhpX\ng4FNWX5NA0RpXuD58aUAFr0+pMkIIpxx9Tmhtz4xxjesBSBh0SAkpN8ZzV7Lxz+qNlpNeHHZ\nrmXRTm2obAfgFbs/LtupYKduBbZqcnfGLDPbtbPWHYMd9QS2c3Kwnakv643r2FFbPBN+ox4L\n5h5We/bm1g9tOuDNDHrzQv6wHXlXCZtjTz8Y6dvXF01cPWjKUdtIG/zmGXSLNc0iDSNNPd2c\nIw8463TD0I3Iucec39p0wuwnTRhXjTM2ZUzdlDNuU47745wLtmeNy20sUY/vbvj1DdXfvqH6\n29/cNUs9vjvDA8CZ6wLwL8OLtrtrzYT386sa1cbXg/rhY1tij4mt3s1d353rzJl5riu3JiMi\nIuqFWLFLRC/556D3v/6gNobWZAKQ/tEAjIwNumYXxfbag9iQecu4ysq8UGlAkxrknszwuTNH\n2a0HANy2f5hA9D/9ebVGgT/PjgiA6qy951aF9ooBABDO+Pq5AYdhNBVtePOdC9TBGsRF9ZsR\nCqqndWkljuF/jb2qF/L+BsCPo8Jq+7N1HQBnrsu8/0TLDlnE1O0A/PyqRnOGbNqlb367dLb5\nUjfW7drqkO2zvbG95Ec65bGdk4PtTH0ZK3anMdd//0itgbI3tx6A0HcA2Gsb7zeC3sYDRx2Y\nVP/M5sLCGluJBkPNdfWs+VK99y9n7gFCavuOcf84qB8LwgIgr27ozsk3D5WHnNoxgYgujgmr\n01o5cfYln8yaWQ7AgNyUMw42u3pk+UoDu7+jHupsN1R/G4COfjIcUg/fkU/HvfKl76n7fE/d\nZ4a5WGbdDkDsbcrqXp8VG+a6sW7X1rJ2l8zxHDp0sLs+hYiIKMkY7E5z916r4p2u2QA4bLvO\nqrHstY0fUpNdawkCmFT/jAT2pZUAGFJvAyTCA9Rb7TDsshHAv3359TvHvWJmuwzPOukfEo40\n6fZDy7blQ1aMzez3g9pvWNEwa2b5rJnlX7u4fGPGaBn2y7AfNntWaJ8aZmcmPDPb/Xt4ivos\nP47usvwNgO+p+4wjB4wjB3Bi9c7Mdv4a78snLpbXQ9muLQMGFDPbERHRaYrBLiXcey2Knbpm\n02yame1025GIkADszpX9AhZHRDgi4qxGx8GV5X/deP5fN465oCJvTvnAq8pzrvwq+68fXZsV\nEEU+a67PketzHMiyD24cWdBQBGmoT/jI3viD+sutaAAgIWdessN9lR/OMhXv0svWRLQ69dAK\nBoZq//PiT5cD0NGv8fjayAB2Wf62y/I3PXs8ABXvYrPdtcHo7cX8MSPzVLdsj2Y7jrQjIqKU\nwWCXKu69FsVOABqE01Z6VtMXsmHWfmdIZbsc26vV9hIAaaGQRYrskFUiejsaKSGEKAxkAQiJ\nSEhEAOT6HBKwGvoZITyyp//3dwDAY1c25kUqVbbzy4Id9qzqsUvgLFOPnMZolSt01AsgP9N1\n8afLL/50uWZ1Nlojwmq7qSh6J9ldlr/tz9uxN3sTAFW6U0qua05vf0+Ln3XR7dmunZuMsWhH\nRESnKQa7FKJuNWYTAJwR7ezA/n+bdrvKdj6rLcf2qpb2CYC0UGhyxcc5IT07pAeEBSrbAQK+\nsrRjZenHVLazGQKA1dAnVmm+SPjfPvMvfRRPbx+TJ+oAAYiw0X/Q4IfunRpdgQXOshxjg3HO\n9xGT7QCs/ij0/IZhPgsAaAUD1UO9Q2W76odnmt8gdrCdyZxL0XN1u5ZFuwEDimMnUhAREZ0W\nOCs2Eb16ytWD21GxWW1Km3VHjk9tu7JgHAoj6AewX5t41zi3JgxDynMb7JowApYjowLaH4c9\nstPR9Mym/wZQ3JRT3GAACGnYnWM7bAsDgNDOy7HMG76yUkbDWaH1nwu1FXe+vnBQxigA4aM7\nq8cuAaB99qStnwtAVb33kHEmAKvFOemhrG3/aE5L4cOlAIbWjgeQd98atdOcIXtt0GX1R9ex\nQ8wNZNuKdInNmW11Tbs+uJpdr/6RTiFs5+RgO1Nfxopdyrl/DIrGmc+GVad9+6KbAXjrAEAI\nADjT+PjFzU8aUtOE+DQjKKVwRAoOibx5B+4Z1eS75cKHhGw6pB8yBAwBiwREpH/ICgDS8Prq\nFn06TQhNQkiIyvAVAJ64fEl5w87yhp3WfqPU5xrnfD9QPB3H63YAwpGmDb+oG7LrvbFXe9T9\nZK39S3C8bmcOttNzo8e/bPdmXb7a/CKt1u1idbGGx5F2RESUAhjsUlTROAAiFNY1LH3vVS2c\n8+2Lbt6VbpU2XWU7Q8i/b/nzIu+S3+1cKiGkFE2a5gjmzTv08Pz9P37xDGSFigxIA1IAo6qN\nPL8I2qyZhtXelKn705/7dJgmBAQkxCPBxUuMb7lnR6pl3qf1lcGdzfMhAsXTs+/LHKDtV0/D\nkSZvg6x9uL724fohu94DoFmi9TlzIsVd05pzW+Xbs8xCHXom27Uz0o6IiOi0w67YRJwGdf4H\nt8uDQWHZDkDarDsz7Gq3P3TROcY/VIdswIKdWTpEJDNoSzPEXwbfDECzVgHY5WjyCw3Ab7YV\nAbBAVKbZIMXWPNkvACHCAAS0b074VJ1WIFhoWf/2GwXq6d/n/j58NDr74b5aV+FCz3Pvuke8\nswqA1eJ0ZUTnbfiOeQEgHDp41hzVIasVDMy5ZcljH7jVxFgp5TdCo9HiHrItv+7305sPeLLx\nhANi52S0quVixbGj6/718RUPPPBA+2dIAafBj3RKYDsnB9uZ+jJW7FLU/WNEsV1Gxqhnrqzo\nbt32YTCQrYWiwWVknV/XtHp7KCzkLV/9z21lzxrh/F0OOwBdGgCOOEIAIpCFvhCA86pFtUNC\nWiAtUooXPj5//oGRACTsRyJfMz/8plU/tvaLpquHs713LU9fF/BePXnPgq8dVEU79VJajgsA\nrLbiL9+QhxfJw4sM7z0A7prmMTtkldgwFxvyTLFhLjbkASh96SRlvNii3fqV7vUr3X1naB0R\nEaUYVuwScXr8c/DB7fJg9MZf0HeKYrsaZndmXQiAHgn4I2ftz9F8+me6RQLIaIqm/CpH3W0T\nh+20R+8wu+KDC/3CGNLY/2iaXTNsEOLTXKNfIHpiCe3F/gaA19P8mpAbNn7ocDSEIv5L5xxZ\nqD1v1u0AHNP8K7EOwJnZ53um6rUP1yOmaAfAHtYBCKtdcz3y7PAdAJqqanbT3AAAIABJREFU\ndwghzPXtzEjXatEOMZEurmiHTtbtADRG52zgkjmeBx54IOWLdqfHj/Tpj+2cHCnWzkLE/6UW\nQpjb5kuxO9t56ZT/0e/g10lgf/J1+5W3bJxEruqU/zc+HZ02vzVisx0AfaffAAAJoUcCAHZl\njvBH5K3XDvvb28szm6wShnnssMvyIKVuhF5aO1MKAGiw2wc1ZUDaAEghD6ZFjzSzHYD7P38b\ngNPRsOCaDACecbPvWh4dRXdM86+QawEIoVks+sKsWxdN8QDY9g934cdPIhxSwQ4x2S4cbp4V\nC+Da42vexQ68i2MOs1Pj8Mxy3UmDHU7Mdo3NH9snemNPmx/p0xzbOTlSqZ1VFIgLB+08bbm/\ng8cnR8e/Tmf3J1+3X3nLxkkMu2JT2v1jRLG9+al/lB4c5YiEneGQkJqQclRdqSuwe/HLe759\n6ZXXXDlXQKoHgD1vVf/7l5fcsvfy/GB2QSC7IJCdEQyWOxsMzYAICYSH+AJ54nMAgLz+cPRf\nIdkRDUBTIEM9dW9+87ErG++rdd1X68ox9PliKgApDQBL6hbfuy4apConfr/yaz8qG31F81wK\n7z037x4d922WOaMFOXMWRTu6OJEivfl+GUj5VEdEvVPCqeXUpre29M6r6iW6sXHYyok4zf45\n+OB2ALGlO78B3bodgEBE7TGEZUfGhd+5Jv2H+4unb31a7ZSQAB496/pvfRmtpT1/ll8DrinL\n0mQEgAR2Zx8cFK6vhgvAsoHBxzavA1CrGQAumlfoyqwE4Bk3G0DlEvdyp/cj3b9CrrVCA7Aw\n74cAFk3xqMXtjCMHRka+Hdj9HSPSKKx2AMaI3zyb/7Y1f4h55cFq741NLnSsaAfg8fLm/R0p\n2iGmbhdbtIuTeoPwTrMf6dMW2zk5ktbOwSce6fpJ7Hfe0/4B7Vd6Wg0EsTs7lRjcH3+3g0e2\nwzPxuXZe7eDX6ZaK3YPLE/oCJ7r/yg4d1pUrb+uYxLBi1wfcPwb3jxFPjxPFdvXQNfjDY2IP\n0WRkdMNHG5esXvju5oH67IFBo6jJKPIZhT7jJ1++KGAAhoDxrS91A3h1cJ0hLBBCCDGitrjc\nmllra6i1NdxwwHH3uEkAsg0NgN8Ib6nN89YXuje/CaBwocfaz3WhX8+Qmi4BYEn1H8NHvXct\nTw8d9YaOeiNa3Q7xWKB4uhR+GQ4CEKX33Xbs8pt3j45dA0XV7dop2sUuhtLBMNeqdtIbb0pB\nRL1WW1FPOSWXRMnUdlGCUs/90TAnACfgu00ASLNujT1EWrZbKiAjk6wZGwABIN8fyMNiR8Tq\n918O4K4GCeD3Y3FNWZYGA0L0izgL6tM+y/XV2eq/eSAzNwwAWdCe2uSW1iYAwMglH9Y9cdF6\n5Dx01OL9z8pZ/8++un9EP2zxLxOrb5SzlhXgxiMAAKsNQHjQtdbyl2XYh+O/g449s/BmjH52\n+A57nitY7V3mjNbtTmruevfjibbW+pXuS+Z52spw77zBybNEdIp1MKglXMBLsra+Tu/Po11p\n1W7/L9J7/wP3ZinTn7LlpxUja0ulhLDv0Q0DsCCmiittVsN6zG8EAdgiVgANgUvr7EId8vS4\noiv2pgERANXp1QX1uZ/l+rJCmZceiN4cLAK8OmjW8WwHASy++MOj9dFxcgfrr7ZAZBkH1dO8\nMJZUz1Lbg2qzAFjLX1ZXYR3zF/OC/5LzesSoBXD94WwAQ39Y1dZXMztkAzXelpNk23fAH73I\ngboLMWU/NT02JW84ljI/0r0c2zk5Uqyd25lGKqVs9dUEJlskTce/Tqv7e9vXaXkZneqK7Ymv\nw67YPs2VKXZllwCQwWFb9FHbcu278m1+C2ATsAmBiKWwUJdBhxFd3STD8XZWUGqQAL6/uXJE\nVdmmAQFdsxU3FR3JrDmnJq3OVv/2wJnqYAsASECoyp8Ebn3/okpMU68WZ/5DWJ319rNg1WHV\nq3X92wXr1KP/Tw41X6LV7qt9PfaaLVo2gBf71yLmRmQtmR2yjtzOpbqWTroSHhFRMsnjWr7U\nS4JOp7T1ddr5mr1KF9tcxEB3lCcZ7Po0/ReFrszoT5EGGE1nLrh82t5cm9+Q0Ue5zzJg2BfZ\neshWJzSf0HwiY3Wu9Z/9tTcNyIDF+ObnlR8WNQAobirqV2S/2J5jN2qtBiwGLAZyAshtdGQH\ncG6N89wa5zk1zndWn3fQmKA+vdD5PIBqmaeeVonoynnutf4rxu/dbR8JAOGQ/avlObcsUS/d\nduzyuK/QTrYz/cegBNvngN9rVu9wvGL3/7P37vFRVGn+/+ecququ7s790pCEa4BAI3JtAREv\nKKB4nRldR2cWnZs7g3PZXWfG8YcO6xeVdZ0dd2fW1d119qKOzoyjzigqDoIKIiIGAgg0hHsC\nCXTunXR3dXfVOb8/TqfShBBCCE1IzvtVrxfVp05Xn/Ok0nzyPOd5jv1SrrSTSCTpp//HJc+K\nizf8KjhHVcdPBn1R7uTik/b9gYHk5zceDwKwqvcCqMxQGXDV1dN9QxpeeuPE6OgXos+hXM2w\n4pPCQYAD2JETLWvJVplm/9o1ubRj+t8AyMoHgKK9qwEwjo2FC1qpBYCrbcMjye0vqt1RgGuw\nAENVXMvnbzzaFkDbNdw0ABRwHYAr18fqjv37Zg+AcfED7rKV7iVPirc/vc4vKhVzM37X8exc\n940AbOXXiU5l7XqOyI2NNXXEZEVAdqBGYwfSI92fkXZODwPMzmcVWj3byGz6SWdW7PnmjCnJ\nOMuRywLFF4wB9q1ha7vKDBXAfTfOCoQTAMo/2S06jI5+cShXK26hblIFAOA7cqIFMa83wiDi\nrACAhOoEUDvqOyP2r05YAMA5PiqcZ1DC1bbhkUwg2b3aHQaggdna7trIIwCizYFX2RoARNUB\nvLq+SOMA8D1/lULzt94+RnxQqrYTkVkAD97exXq71NIn56jt5t0Tti+l+uoGhrYbYI90v0Xa\nOT0MMDv3fKuGLjt33z/99Hw6vd6/IT2c6lM8dXUgznLkUthdMAbYt4YQduzoXs4htJ2ukMXX\nzwTw0qrdUBKim/96s+atg+1vsvbn7iuIeYdELA6CdnkX9TgBfDb+O5dtXR13wLDw8JSFB/mJ\nbS4dhR/+uuIawJjU5K12R4Tzj4MSYmjcBPDelFJmJaOxVNH/ZK15feNocGg8KezEJSHvnvxT\nspSxre3UglGpVVFsTq1UfFYK78MXkx+UKuyQou2ksJP0HGnn9CDtLBnMyDV2EuiPeAHQYeMJ\nwfiwCcCw+Et/2fzSXzaDto1ubhZHeIOr+NbS9jcpY5vGfeFc9OClXz7B5p9g1yeoBcAVjrnC\nsWsrns2OxR1xZFm4shF3tQ559Hgm6uYBBNDDGbsijtA9s7beM2srAeNcT0BJQLl2+5E3PT8F\n5wCYZXxZmZ+DSoAnCP6jfIQ92umvH5j++oFX2Q7xkqgOkSdr1h9+el0Xi95OlXG92JRCIpFI\nJJKLAumx6w0D8s9B4/FgoM0c33zgSA4FYCSoriSdxqNbona3QDabHKm2X64qvGbNMA7g77Zb\nKkOB+hfRrnGDxcYDaFQncQ5G8H/jhj8xbc2/lM+eGjUA7NKt703bB+DFz6YDsfZ3xQEeHVUK\nVXXl+FYldv/w41UAii3XdTNhO+1s3jg6FwC3wn8sAVQHThOQxTn47WyPnTPXl7rnWKfMiYvd\nbzcgH+l+iLRzepB2lgxmpMdO0oEvQ6XDxhsYvfjWS3SNgSY3HDuU7ero00J36OOTO8pyLKr7\n6InPa3+8o0ohx7zxY1bUp/B4glqccBFszTN3coBw3FNZ9XDF/CXTP97mju/xmAqPg0fBoz+b\nseaeOW+JqigJ4qQgnsOHJu3adMmGdwCIGsU1SvT96P32GjubW4vfBEAUj0UiMOMAnnq962/z\nd+aUi+NsbSJK2SFlsZ3gk89uTn0pM2QlEolE0h+QHrveMFD/HBSL7QAE2kxxct+t7vI5OQD8\na9mGV9fZPQOZ+vh4pdNKPjyGNR5AoxMAcugmgOzJ1KeF2uLxcZTTKsfETFOxwAG8WDYiz4pQ\nYuokYrCsH07dKO5waQ5ftmZOlJngzMnjAEbHGpys0BMiTa49AIZO/DEA7z1JZTb99QPixGQN\nb9XcBuB3RXUAQMjXE1NSJ9VpV9lepFPYTjucvNLu0UcfvWLW26k9L16/3UB9pPsb0s7pQdpZ\nMpiRHjtJB2KxHQBfRnKvueffilQ8VGM8Hiy/jur/Oe9QZqE4dGQWzr9rR3ZS8ejKXgB5MQBo\nZrMJ4RPbYgD2ZqjH3M6fTh8ZUrkCAuCeyqpGxQ3A4G4Q81fb5iaQA6Ch6T/unvPHXyzcDEJj\nxAHgkDMZeM2NTgBwfPcvU4e69fYxtLCEFpY4hkymhSUdFzh/Wdue2rPTrrLn4rTDySIPwIJF\n5RevmJNIJBLJwEN67HrDwP5z8FS/HVKkns6SV7Fskv+zmv98c8PYSLKh0v0lzvklTVsdzs0A\nKBIAEBuzKf8mAN62GpeZdNoBGIYogKhF7Ofv+/41AHSqMesEgP/beIvO2IQYd7ckO3x6eemd\nd3U4zPzrDfv8jaNzWd2xpNMOuOuoWxlaljqpVL/dGZMnThV/la/67UrFnZx2A6Os3cB+pPsP\n0s7pQdpZMpiRwq43DJJvDZFOYb8U2s5xLLm7K31uqv+zGgDPv70WwNg2VWXq/szbDBaf2LjD\n4dxMkXwvMcZ8WnDTpPpjQZ3Y2o4SUswjSNF2lMQBLJmx3sGsOFEAOHjD7zfePOMEODiAPYVH\nsxidtWyaPSRb25VfpQP459eKmJVUXT9ovN+95EnbXddNQLZLTtV2p8uiQFcL7C46hTdIHukL\njrRzepB2lgxmpLDrDYPqW8O/sfn5t5JOOV+Gags7APGS4kA4bjBzcnRjZbY1tk3VqRo3+W7P\njQCmhn8jtB0xxhhkKACLD21wMpelAHhrzEgKkh9DULG4agDg7dqOg/zdtA+EttN5y+4/36Lw\nBAcXwo6oek6WD0DZDzoLOwBP/SG5v8V3Dl2mZ19Wn73GHm0fartONe1w8Wu7QfVIX0CkndOD\ntLNkMCOFXW8YbN8a/o3N4uT5tyKp2i5eUgzA1nYAXAqlRWogfBjA6FZGoSoWAxCLXSHeorJE\njV4itN3bY0btzwSAqGVd1UjrVUbAOCi0kJNb35u+Pk4UgKxdPbnQqsmKjgGwp/BoNnUDENpu\nTxtbPicu7iy03dPr/Gb9YZEh+4PG+wEE4y+IDl7Hvfa+ZN3QzS5kqU67Tpfm3FJ+URdAGWyP\n9IVC2jk9SDtLBjMyeUJyZkRiLID7bnXPvdaxN5PszezYF8XncQDY4ZoDIGoxVpuMwB7KpJTH\nCDVBTJ0fF40m1YqNo1ElWUhlbGvyJuvz2O4s7MpiBIwkMpDI+PXmWwEA/LqFO1rpkBZ9T4tr\nLwCxpWxzKABgQgZdttEhjspnACC5+YTqAPBs4QupswjGX4g899C52CE1i6ITG1f6ZSKFRCKR\nSC44UthJeoSt7Wz2ZpJDodq51zrmXuv44W05AHa45uxwzTEYG9lcbFiFAGIKgyhF597LCMSh\ncHhjVXmJIzccPKArmBQBIcnnkEPdnY0CS40TxcHNZ5O14niUKJwAnK+69KrfTPUf9S8G0BwK\nNIcCpmWIY2dLZPOKwOYVgdFxtNIWqA6x3s7ruDd12D3Xdl3Gak+n7Wpra8TeshKJRCKRXECk\nsJP0FFvbLf7SyFOvzp9vzr3WybhW4bx6u/Nq/9z5EbNkj7OUcYgD7o8t906nY3NUdQBIEOaN\nH1108PCig4f/5btEVdtUtU1T2zhn63Lj+abKCAj4s5/dzAGAt9AhFuVxFnVa/N1Yxb6x/n1j\n/Uf9i4eRI/YYjvKRR/nIkYc+vm7XZ0Lb/cfENe4lT4rCKGgPy3av7c5YD6VE9825pTz1sC8J\nv504lyWLJRKJRJJ+5Bq73iAXcGD5zkCbhZNFXkVrdP1aJs4pMPdaANj84bYpsS8AGAp1MhKh\nOW5TpGIwAvDo9Drn8CGFNBCOmZYBICeeQWAC8CScJuFvjhoBYFxLDYGp8VgmP/78zGsJtNnt\nm5y5Ci4F8GD8+ae2j+8YHud52Atgs2+hWjAKQLwxAICbCbsLUTX7/GvRpB9OJFicLq/C3nxC\nrLFLlYAbV/pra2uKiopTF9tdRJFZ+UinB2nn9CDtLBnMSI+dpJf4MhRfhlK+5mj5nBzhzNNp\neOGCKIVFYQHW+g+SfzNsd14KQLeYQQEgorojqttQCADi2loQq64N8ohJ4kSLQws6Yhwqh9qm\nWRontx+qvu1wVWVBJoAEcQIIq5wjscmFS1q9l7R6Sw+duHnPV/ffPG3FlXTFlVRVdFXRQUgj\nxtejbGZgtRiDI8+Hk8VcKq+4kopNlEc5ndPOzpkQCu+MebUSiUQikaQZKewkvWLZpE4N5XNy\nwgvGhheM/eFX/6Krrbra6lZbdPezV9200a3WqMSrEu/RjGE79OSKN0Y8UYVYhHL3tuQtmAqu\ngWtBR0w0tKqcABond1Q2FcZyQUgrHbrS87OIAp17/9ubLJW82/nr+K9/sXHbv5VfpS+fE18+\nJ64qOgAKUo+y6RueF92EtrNJ9d4hRdsJerFBRVFR8dm+RSKRSCSSvkW90AOQDDTKZ9xX8fou\ncb7m3Tvm3/iawTSDGTp1+DxaIPTWTv1eEa+dHX5WnLwwYRiAZeNqATDxTHL8sLqQWPTn26sB\nAKS0pQHIB/i6dx/87wk/tAg00JWovQW32R8d//Uvyn/0UwB+GFZ99c93D6cgjbzsinX/Pb7k\nlznfflF0S11j517y5NPr/GiP1QKoesUvArJdarvKV/0A7vckO9+00d8LCSiRSCQSyXlCeuwk\n58zynZ0apq24xOcuBKBTh2gJuHWDmcaxRij1z0xwUIAChBOTcgA/2f8sJUSnrmmZWRQmhQmS\n+Lfhdb8edeKxKSPEHSIqLW1pGBVq5MC39rgsKBZIvVq8Bm9tzAn+Zsgjv/X++rfeX//P74f/\n7wf+75tzf5Tz1w9M2im2rDhGx77vfrf5v+8Rt0qtZmeLvE7+vO55NnwWnSUSiUQiSRtS2El6\nyynR2E743IU+d+Gad++Yu2gfAAYOYHQzfSsnyAAGfJqxxMEAcADfOPq/j+/PgRLRqQtwgjsB\nCtDncq3ieV6TACARlVKO0pYmAPcFkpKxWi062Lrnn/JuN0gyMsuDJ3jwBIB/yPo+ARHabsS+\nte+73/3j7wreWO1/Y7X/3awX3s1KVrljdcfESadobK+RibESiaQPIYSc2mLTZWPqpdO1Xyh6\nOJ1u2k93n/RztiPvSfu5z0sKO8l5QX/EK06mZZQASNV25eVvPF2WfPBisZmmYgE8Lxo2mBmI\n1PuyEtNyrBm5yezaRHYDuDbiGq9JYFIechAApS1NpS1NP9zpujqYDyBBXH915ImDrXtSByC0\n3Y+nVhJCQcgxOnbEvrX2VVEARWi7++vutbWdoOoVf+qReqnszqRoszNkRQqFXfRk40r/o48+\nei6mk0gkEpsuZRBPwe7AT8buf7r2C0LPp3O69tPdJ/2c7ci7n1Ef/oyksJP0BadEY1PZsOo2\nn7PmSAal4AAb3UxX5zWKSxV5foepAAQg91S/bLSMCUTqxaUZuaw9wRbg2ohrit4cOQqA0HYA\nitvqbzhYdXUw/+pg/py6YXPrSva0fUzry8Xx18Ef8eCJZe77fjxlr/g9EdrOajhsD8zWdgBY\n3TFHnq9Lp10nbSdIjcbetNF/00b/UjUgjrcu/a/lJLCc9I3/TyKRDFqEFOjDN/b6hn1CX336\nhZ1F/0dapzfIIkkd2JKuq8is8XjQPp+74GcbXpklzvUhpXcPX/iDPXEAUxq36I7NFgGAp8d8\n//FRjb7iN8tn3Aegvr5+ZAUHkGjMAQDCrMKdn77jGhHVs+Idz21EpetHDAMAcAq+aWg9EokJ\ncRcAVuAHkLN/j8I1kKQX8Oqiv8n59otvrE7KNVZ37MbQvfb+Y3ec5LwDAFHcWGRUoD1/AsDf\nDzupW7glqeQ82b6Ghh2apgH4+IZwd9brN8hHOj1IO6eHtNn5HHcpFJxxD+tOOqb7l900dtNu\n49/8/515xGeifOY/dnO1h9M54zR7Iu9eePWsBt41997Zo25nHHkP288d6bGTnEfsgCyA8ln/\neyinTZwbJw7+rnr1MxMcALbnzeCAwgHgnmP/2+kO4QWFHS84RXzY3yzcUXrH/p054ThlccoA\nuE025+iRoLMRIAxk9vGC2Y0lexzRPY5oU/O7AJrHTljuqwVPPu3rav8LwFcWJoWa0G02r5XA\n67jXPpCyCK8TMh9WIpH0Q/qnu07SDX27AlIKO0kf0W00FoDxeND3/35ia7tA+MjvFmPtTIeu\nIBGfiXZtV/nJm4Ga21LfGF5Q6FaSD6rSnFdpXVHWlnn5/Jziuw4BRMi7KnfsSwfCQWdj0NkU\ndJ4AZ7MbS2Y3FJc2lQlt92nNq8t9tWj/Ugs8ehgp2u69MWvur+vYUvbZwhfEYbewumNdBmTf\nmVNuHytMnzgeboBw10kkEsl5pT8sNetDTjed/j/NcxTN3ay9681gpH7vBTKechLdRmOREpDV\nH/HiqdeMY/UADmUoABbfunHcgX94/uMaALrjcwAnXG4AlFg6Va2//5JtZ/3VOOMEgJXT6GTx\nMvMogH/9dDwj5vT6EIDKzDgI31qU3OJM47V58WSplB0Fu6uGzM4zvS8pbzzzxUQNSpl5HIDv\n0VF2QBbAVxaWi5p2qXxv93yxwyyAUX9bi5RQrJ1IIdi4suO9S9WACC4v476LYmMx+UinB2nn\n9DDA7NxlFFKcCB3QwxhlP/HY9Xw6vZvmBaHTsHsXXO6+vedIj50kfQiFp5cUABjdZgF46a05\n+8b8v/uuLAZgxC8DkB1HdhyUKQkL7J//HHzoN00P/+a9F/Fk0LH8hPLo8WRJ7Up1GICf3Ewp\nV7fm5wEoa3WAkyVT9y2ZWnn/1G0mGRp0GqLz5PqJI45vNEiQI/H9S7cnYMbQEkNL5TMdTjvB\nA1d3FmH/MXFNpxZbz9kKT2AnxgJYYfqYZQCQKRQSiaTP6SZ9sp+rui453XT6Kkv0fNPfbNu/\nRnOxMMD+HDxXUoOwZ3LaAdAd6wEYx+qF0w7A4ls3/vH33yw0VIDojs0ADMUd1k5yv3MOi+DF\n4m8xTohqgCuPjTkxMTsTwD+/zaY2JNNsKzPjs26MASAIA3h22xRvzEnAFVjb8/eC8yZSBmBO\nEGPNAwDcBVN2lp3ktLPPbe/dV7Yl19h5HfeKZc6dJF0qZXeWC9fdT2kFVXRcJPkT8pFOD9LO\n6WGA2fmskif6v7BLZ/JEGjjjwHqdVNH7IfUHu1x0DLBvjT7gTNFYpAZkHesBoDaEwpS00qUL\na3+8KWLxIcl9YqE7NjMCAM26R7RwDg78X8m3uBJzclM0EsV90/4IgJJQMEE5wPO/Vs2sXAAg\ncQDPVVzijTkIuAaLgsbg+Dg/cnONW+FGNipBiLtgSnMo6Vc76l+MdnmXGpa1tV2naGyX1LsA\n4Ke0AoDFlPz8yfalfptvIR/p9CDtnB4GmJ2lsDv1ZZct6acnKclnJez6ZFIyFCtJN6zWBICi\nLKihjtYVq4t+OXtMPtnniVvgFng0MT0Wn27GZma0XJIdC2fHwq0qAHzj2P/kmE6n6bHv985Y\n/Z2xbgAaIwBpeGW4W2sFbRKXl0zbBagcNAFV1Du5ssH9dnF0ffGeFpQ1qNbRpm1hZoa4EeLG\nsPKXAIiFd6eGZW06ra7rRGpMVtO0hoYd9ktRzVgikUh6jVhwZnPBxc05crrp9P9pipjSqQmt\nZzuj1Pa+GVg/NFb/Z4D9OdgH9CAaixSnnaPhA1qkAsCDd2DF6o4eSxd63joEoGZVLYhJQXSa\nXFSXsKA5NgMwKY66PKu93yLgAEj7HyfNmvWjbUcAJCjflp9306KdBrPAPAz8uYpJAAcJO3kU\nzJuT0AHszNsG4KqaCaa2h3BKiGIRE0AW0cUNc7J8wdYAgM1zFseCO+6uyUdKNPZUUpMqUqOx\niUSi/zvt5COdHqSd04O0s2Qwo17oAUgGBMsmnbHcCQD9Ea+t7VitmdR2Sxd2aLsVq8tD8M8Z\nl3f9iLe2mzrVrjpRJa5oCmDNhLJZZRgWDX/ryK9r4QcnS6dPJqoO4Kqg2uykOTGmMXJZXdPW\nP099o9TFOAfIkmlbAQAmAZ7dMiyoxQE0qXng/M3hJ3476hd3tv7RxYtu3P0uVDVkGULbNYcC\n3ixfsDUwc+NLGyb0xtP201YdgCd78ierb/584du9uINEIpFIJGeF9Nj1BvnnYBf0YJmdwHg8\n6Gj4AECH0w6wtV0gBIPFGQiAK2/aODFjVPmM+2qejhce3ALAsKA7NgMcgEnRxKcCMKARQgG8\nN3L2rfsP58SY/VnNTvqir0TUSXnkkq2A+dwWsfsF25PbrFPOzAiAt4c98sm2+hXjdwtt5+m4\nASLcAADO1ky8bFJEVUk+gDu+Xtvl1Do57YLhAABPtg/Av2Yn+0iP3WBG2jk9SDtLBjNyjZ2k\nr+mB6y6efy3sxXaCpQvFv74s6NRBwQF88t6451/TAg+/Umx8pBW3asWt5d4ZG3KWAACBypFN\nt3hxaAQqnTzGObvhyKa3xo5q0Tue6pwYuyeQzHt4fNf0FBc19YW4wQjEmgZCrphaAODdiTe+\nW7bwtasW/2aq/zdT/Uf9i93tkdn5uz+3b/vay0U9sYTX07GfbCgUEEdP3iiRSCQSSe+Qwk7S\nR6Q66rrVdqn7jLFaE0+9lnyxdKEt72xtB8Bg8YrWmorWGgBFxkcANuTc36a4w5oroWTEaGOM\nNjZrbToSnLPrD2/88eXDrv6Oy6I8QXmC8pwY+8aeo5RwgD2+a+qSGVvEbbmVrysaVbMB3Fz9\n2M1HHycNHycvBU+Ik/fMgMiTBaEAhh7+1OQN4lJqZePuEXvILuPPLpH6AAAgAElEQVRJkXfl\ne55uu0skEolE0nuksJP0HZ203enlnf6IVzjtALBak/397zsK3S1duHjB/MUL5uvUAeukYEpF\naw1X63Mja5bOdtD27KGEknEoK8E8O7PpFh0JAE9s3jx2b+Z3rx55MNurcMIIsuIsK6HlmI4c\n0/HMdn+Omayf9y8jdpqWwYij/RO4re2yjbycLF9Olm+TG9c8PE2lOgWloLMb8pPDPs0GsjYi\nNzbVaSeRSCQSyflGrrHrDXIBR3ecqudOX7VYLLYT2FJPf8TrX8sAmKap5nw3ECsW7RtWjQNA\nTO81s2cCeGN3fE7bOwZjx7KjALhpjA5pLWyG6PzA9BkAnt/QURj5eIZ39YgMAKPDJKTwZtUC\njS+Z9sUPD44lsJxMlBEmANaWPAPgmCO4OPQhgF98pXrDPwbEThIAdKZUjbkewI2hju1lOxUu\nFvVQUjcZm3NL+ZXveRKJhKZp/bBksXyk04O0c3qQdpYMZqSw6w3yW+MMnLO2C7RyAN+8Nnfb\n9Ul3mmf9w0LYcbOQglwze+Yr29y6o3mCpyDvxAsHMpNSaUwDb+TTxPlzk4fsU4fZ2q4yuzDL\nIra2AxBS2e9KDCC6cvhKjbf97b6bkkvuONaWPHPMEQSwOPThE0d/5PjRT9c/XiHu42QgSGq7\nVGhhSawpMIP4kFLoztZ2qcIuK6uzG++CZ1TIRzo9SDunB2lnyWBGCrveIL81ekQPsigAYNkk\nPPWanUghtJ0QdpzziVkU7cvy/J9986W35gCIxouvnT0LwBu74wAmeAr2RMJD8IK4g6+FsESW\nOG+c/u8ntv/viDadgDAQrT3ddd2oMeIkVdu5eOT7+xbZ2u7F0ctEH6HtnpnyB//HzwPIY3pE\nRdXIa0+dSkINAZhBfKcTdgA6lbWzubDaTj7S6UHaOT1IO0sGM3KNneS8sWzSGUufAMDynTAm\nUJ6gRSotUlMdeGhXeMbjQePx4Ib3/2lkc+HI5kIK/tGmTQAevPEdAHvC9RPcnntvvCz5lmxO\ntZCa7wOQt/X7Q6Z8syrDOJIRpeAJigQFgKsPH5h3+MC8wweyTAqmgWfeUn2LQdz/Pm7V6FjL\naCs6mkXvObycE5Mj8VLWPHHnjZfMBdBIDbeJEUc+oIUl4rBHq5lZALbwwKl7jm1c6bcjsDI3\nViKRSCTnCemx6w3yz8Gzo4euu8ZkrBPFLjx4R8XPToiNVnyZJ+2ywmo3cqYB+MI9mYGMMwBA\np2rr6Lxbr/n8hXc/B+BzZ6A2TLNmAQiO/AGArC2PAaCJsoiVvI+z3Xt3NNMbUvjyyfpb3moA\nFIkfV2WOZiEAj459DGIvP2hVuy99Zsof4o2BObs25DHdkecr+0HHqCLPPQTg3awX4mggqtal\n0w6AXdluwaLkVXuTMemxGwxIO6cHaWfJYEYKu94gvzX6jE6az9Z2QECddveCMlVVAWz4tN5u\nd5woN1hcaLvt7ilEqxvbWghAp+rnQ5wP3rj7dNpO4L2nvPm7BwA4RBFkAAADajK9AMquDwKg\nSPzgaI6ThwH8S+k/iT6Tjayvez6yhR2ASctOWioXee4hIewA+LWOYOsxo8M/10QNAFTVRdXi\nBYvKpbAbVEg7pwdpZ8lgRgq73iC/NfoeW+G1azuD4aA2lRCyeNFEAOXXdSwbYD98N2pytDvt\nxkQVkc1Kgc/zc7421fxg2ysAJoSjAKqUWRN+MTv4YofbzHtPuWdVK4C6N4JC29k7TdRken8y\nzQHwyW0OAivkaODgHJRw49nSJ7J5aKm63//x80LYdXLaAXjt5SIh7IiqpbbHeTKj1gLLMSlS\ntF0/2ZFCPtLpQdo5PUg7SwYzUtj1BvmtcR5ZvtPWdhw8xsghRzLL1ffP7Sv2VqwGsKcFBotf\nM2uSwbUPNvExUVGdjnyenw1gKF6c0BYV3Y+qs7957ew36zq03ejCDwH8y273HfurCYGeSAZo\nWVLbaQCmtCkAUrXdy6N/dmPk1Ymmy3baAcgau9i+Las7tim/wSImgdpJ29lEeSTHpP3NaScf\n6fQg7ZwepJ0lgxkp7HqD/NY47zz1GmqiHJyAGO3+NKHwkvKufW/ZbU1xALNnTkvRdhDyLlXb\nDZv7HQCV4WvEy4WZz+/TxwJ4bq8O4IZ91QzIjnMADHjhktGr82IaaZzY5gXQ4mgQYVvCDQVW\nFmu6NkgBdKPtADi8XaS+xpoCcW6MiOstDoQi2UVFxVLYDSqkndODtLNkMCOFXW+Q3xrp4KnX\nTNNUgwkAnbRdMjj72RrRGAgfAbD41o3/9qcflbbaPxcKwOP8AzgFUDDnGwB0qo7K+j2AytgN\nAGIkE+3aTlfYHTtrRGT2X6eOUHl8cxaKaBXMeFAZMjQOoe0UHs5mTTonc4IAIadqu9QdKUb9\nbW3qhN5Y7U8VdqKm3ZfuCkthN3iQdk4P0s6SwYwUdr1Bfmukh/r6+oL/+UicG0eTvjc7Mrt4\n0cSX3l/jy0p5w9KFYmuy1loDAINSoP4xolgACFeEtlOGruNWtCzRVhm7gai6YSUDpowj/GY9\nkMyoWDO6lIDXuuNfFBzKibl+WfqHbx/8BgACTnmEtudd3HS0xKUkSyhXjse9dwLA4V8ViRav\n416xI4XN7/7gARDnRjZ0AIlEoiRn8hP5nSeefoUnH+n0IO2cHqSdJYMZKex6g/zWSA8n2fmp\n19Au71K1HYCX3l9jv2XxgvkAnl9dN6wtJlry1DeiSgJc25Phmjv5qzhZ2wmnHQDGAXRou4iq\nAPhs2KjDHuZSaNSKtWhNjBAAQ4yc3Vk1IkwM4OajJWp79sWhifq9d6LqFb/w23kd96J9tzGB\ncNqhXdsJp92/ZkOst0slzdpOPtLpQdo5PQwwOxPS+X9qQjqKQNmXUhu7uXTB/9Pv4XR60Z5+\n+mrkfTsjKex6wwD71ui3dLbzU68BQE0UQEA9g7YD8M7rJwDkJ/YR91ZDiQc8mQCEs+1bV1aK\nPpXx+4miGywTAONY+wmfXd+ArrTdceUEAAaoPJIfK96VdYxAdMTNR4sVJNMvtsy7Kt4YAMDN\nBIC7a/KREpO1hR2AuIJsEwC8Ht8Fd9rJRzo9SDunh4FkZ/FfficR0M3LU9t72D899Hw6Z9ue\nfvpq5H0+I7nzhOTi4cE7AKDYhWKXz6zwZcGXhZdW7UaKmEvlptuHUBCAIDpDtxxTQwYF16kK\n4OXPvKJPmeNZn3fVtKGvWjdlU5JYMNfcVJAfp4hRuEwLwOyjh0eFadSyGPcw7qEAgZOruyZG\nmsdFm14cvfTF0UvvvPIbFpJ5GzM3vuTI86G94snvihsAVL2SXEX3lYVdyLVgOPB3LRBHKBQQ\nx/ur/O+v6rx9hUQiGVT0+v/4C6veTkf/HNXAQ1q5NwykPwf7M13bWfjtkHTdIW8aACybZOfJ\nAsDShf61yfDoqteDuYl9ACfurWHqAEAJrfTAoRz/6zkh0UfsPwbMrDhewri29hMOYHpjg6FQ\nBQTA2hEjQRhAmrVIieFM6HvEG1vURJ2SC+CpCUtf/fj/AGjgxHkIALOMT8bPEt3ursm3w7KV\nr/q38ABSPHap/DInebKMJ4Oz9h4V5xX5SKcHaef0kDY7N//3Ped+k5xvv9h9h+49Ol2qpdTG\ns3II+ct/0fORn45y/0+7udrD6ZytY7JL3juDaXvEDT37IfeVx+7ckR47ycWG8NsBKHYB7QWN\nl+/E0oUdfVasLr+OiprGi273QvzmRKa72ybtprcAKAtjYtawz9aR1cfXAzAbRHh087Shx9zZ\nOxfMrwM1t+Zn6xazwAFcV3VErIDISbhr9JjTmHTIMfyQY3gjLR0ba1NAfrpnxdvDagCYIMQY\n7c30Dc2ZduX+7faIgvEX0L7zmCAzy3fq0jpmGX1mKIlEMiiRjrGLEdLOud9KCjvJRUjPtB1W\nrBZr72bfdUVEVUXzjNBhEp7otAzrSJsZHRI8cA3MjZUq2d2yJxA+HAi/Cl7POAPnAE/Vdtce\nqRZ3yE64GzzxQsslXh5yDB8da1VBJoaK3x5Ww4E4IXV1SX3mTKlmF4y/EIy/EG8MzCBJPdeq\n4Et3hb0enxXK9np8Xo9Po3pWli8rq7Pgk0gkklPpiQ4Qm27b9GfNd7rpdNPeT6ZzjiMRbxec\nu7brL0a5uJDxlPRwZjunpFMkY7IAggcBoDhZYS4QSq7A+/RPnxksDoBaBIBD3wogrsSumP8n\nAJX6FQCIqgMw2BXMHLv2gzyAA0qG0SRu9cSUUQDuPk4ATkENPf5k2bsAvn1gXimrrUN0jztX\n9Lzt6BAAFPTzeXNFLsVdVcm6LK1KA4AvcuFAPoAbQ8kQ7ev/VVxUVAxAJFKEQgERjZWh2IGE\ntHN6GGB27iaNVOiAU6/2ItkibfR8Ot1Ps8tbXSh6EvuWyRMSSQ+wXXfo2GQW3lJ4S1FjJI/2\nnNnLvzwLcDCumVS13+SwnBvev+tQ6P/KjE8AcNMAoNNPKEIABwDSsQ7u4e2Hn9paNa3mCMB0\nSnLizod2LXho14IJLVmOtgnD2yZeGyx+ZdTPAYhcCg6Y+5O5FL8fEUodOEfytu9mJUO0X9T8\njWgJtwT60EISiWTgYXt3Tr3Uf7ROzznddLqZJvrTTPvPSARS2Ekuch68Q+TJotjVoe3QLu8A\nX1tS2730/hrQEFVatwzxf1Y0e4v6NdHRybBuc/Oh5o+0409odX+v1i7R6v5+Wm4FRHU6TiJu\nFSRZzaRFYQCm1RyNsITBEkC9QdkxVxsABqcC/sSOx347aqlYb8fBrqgaHd/7vCPP58jzvTG1\nxOu4N9PKBzC5SY2jIXUejz76aG1tjTgPtwQUnlR4MjdWIpGk0ifLsPoPZxt+ta/2Ey3Vf0Zi\n0+8GdFEwwPz8/ZazsLOdKot2N97yncmXwYMAAhnJyOywNg7g84J5D16pfvD2f7lYcjFcjJK9\nHheA7064EoCW76toja7aEudKnNLIdQsqPn17FABYmQCyLQqgongEgBYtxOEoMVwE3EUVgyUa\nnLU/mfKzZzevKIwPUTkFYBFWPu8qAA9cXV71ij8UCgD4IhfOXJ8oZSwCstuGrQGwVE167BLM\nAEAV/dQld31e5U4+0ulB2jk9DDA7n1Vo9Wwjs+nn3LNiL/gUbHoSIE5/KLa/WOfiYoB9a/Rb\nzs7OqdoOJ8s7seoOQLGeOMENCwDmfXkBgI/e+U/dionfgS8yMziYzuP3+q4DsNMxatWWOACu\nxgBcN6+eapUcbNObUwBkW/TB6SOgRN4rWZ3gIwA8FrhkSouDgDLwndltVwQzCExGLJVTizDq\nPLJ5zuJUYQfgi1wA4GZienOyQnFtZugf8pJa0wIDQEB1ogNw5p4k7/pW28lHOj1IO6eHAWbn\nnm/V0GXn7vunn3PceeJUT94FLFB8upFc2J0nZChWMlBIXW8H4KnX8NRrWDYJaA/LekthFqsx\nI8M0dAWfvvV++XU04+klhIASEGB8JOxEnBO8EFgLwMkbFs1wACCmk4J++KEX5gRiTgRNJD9h\naxWABMnnUDiUR3x7OCgACkxqyWhxQrccDks3CeOAFRs548P1T6/zv1bSMUZ+SnGTotas30Sm\nOYie2mhwA4C9ZYVEIhlUdLP4rMtLXd6h+/Vq6aTn0+mynZ9COgbdFd2M5Kxm1E1775Aeu94w\nwP4c7Lf0xs6d/HYCY0LqK15zAIDp1LUhBEsXGo8HHTWVAAzGuXvr4SzP2EQAQMv4deOcf46R\nfOG3I2py81kGTK9vPaFTAA9OHwEltKbkowgfKa6+vWkqAIbkr5XK48ddvDQlcWLLvKsALAwE\nAOzIMoiio33/MQFRtRnEd8wINFEDgIMmRV6Z6iu7s/ymjckld9JjdzEi7ZwepJ0lgxnpsZMM\nLB68o7PrDoC+B/oeNFYkDzVElDrNrEZNFVas1um2eHGZ6FilzhoVCmv5PgDZe6/eF/uSroS/\nPDNBwbjpFAcAgA8xWHGUCacdABCLIEIQWTb93xuc9TWucK3eBsAidGiURFXdbSYPc/9LAN4e\ngqws31xMc+b6nLk+vXCyA/ni0Mys96M18+4JD82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t7R78BdGABJhnhxIdRrgJ4Mra2o+LinIjTQdyDHQA8vUAACAASURBVHBe1pzMZl2x\nrX7pFO+NYfcbI/GVI63gCsDmV1trhmscxXdffuj3n5YW4kQzL766ZgIA4PMmftUbq/3xISEA\nEXAgkZMgH73gASD2Iptzi1xaJ5FIJIMF6bGTSM4vtGA0AGiUEMPSD4lGB6p8Wd4md+63Fq4B\nIbx9O7KRbaEV24OccABvjMwEoDEqits9t9X/3FY/Q94OZ1bQ2Sb6zzvmA1ARC+x0Gjudxn4n\n9jtRnsHXZRoA4o0BAGJHColEIpEMBqSwk0jOMw/e0aHtqAUidBqKKt+5sm7Lx38u0+n26rzy\nQ9mNqTHXz7KTbvmoAgDzq5lYvtHiBINmEJhwpH4IUfWTPpQntd0ZKbvzpIJ2EolEIrmokcJO\nIjn/2GFZjUKPQGkEAeGMqLqTm2WJRgBjIzUg3CJcOO0AZDOsHZ6pcHBQcHpdNQMUAF+7fMtd\nl28HYMJhgc7b0hA5sSU3y5eXN40Q4d4jDqY6LAVmgtUdY3XH5IZjEolEMkiQwk4iSQtDc8W/\nzHEcRIXSCLVRM6s02qDE3GWJxkNZYYe6S/QR2u6aqhMAVo/IBMAJwOn86sT8avbc1unPbfW/\nOTwKgEMFcPPRUdM+3HDzF+Vlpl4W63rhrNR2EolEMhiQwk4iSQf0ge90aDstCKKCqIAKrpnO\nbJVllCUaNVd1prLDRfe46R7RM1XbVTtE4WLMr2YAn9gC4ZzjUDgoAKv+cFlgw6nbxUokEolk\n8CCFnUSSRobmYmguNMrUIFODTAsytUaNGQmaqbIM0YXQGAcmRDY3q1azat16KKntikyYNLkp\nxfxqNr+akURN0NkKgIMw0DrubaNsvdM4oZLdroShWh/mWfXuUJ2j4S+ZT3/seeFCTlwikUgk\naUEKO4kkTdAHvpM8G5oLTYemAw5wB1NrqHXQQgMA5q4BEFfMGMXs0BYAVU4mKhKvHZ75xshM\nW9sBGBHJGtIWWTDvV28ObwRgEupI+MQncOCgxgAw0+Dc5Nw0ecP7q2R6hEQikQxwpLCTSNIH\nfeA7SXlX5AFEDRTYGx+aqqtxyov1lz/p5MkE2SnhCoBfUxUU2k6kU4Q0KJyKY0TEw7kfwJvD\nmzioBXrPltbUT6xwswoPr/DwzZmmqH4ikUgkkgFMv9td5KKgvr6+oKDgQo9i4DPw7fzYJtbw\nKRCHEG6EJhw5oUv+M2vLYzxhcK46GaIKVTipcSvvDbs+9a03HkkKuNIvbQHiPzww+7Zql7gN\n0754YYqfgk5M6DFugHOTJH/N12saUTVPti/1VrGmgNjrxpl7Uvs7c2Rl4z5m4D/S/QNpZ8lg\nRnrsJJILx89n0/zLaXwmNb0EAGcACuq/F5rxc6LphJgAXBazCC+OWDccXZ36VqX9L7Lnts58\nbuvsfxuzCUiGaJXEpPvKw6U1m3ndhjhFnEJsSmsRAOBmItzSI9fdTRtl6FYikUguMqSwk0gu\nKD+fLf6lCS8BHLFGfqQ1b+v3k9qOxtCu7ZoVa3btqmaFt1C0UKBd282vTgDqc1vnzr9qOwC0\nh3Yp4KJ6Yf3OCabL/rRvt6VxahKJRCJJOzIU2xuknz89DCI73/8h6GGmBu0GBi8Akw+lkWEx\n4nCTyqhC92ZQAP7Z85+o1rIZbjncapGOe5Teug+Irlk/E+AEXIG1rmRvFtFHjFhcHt4i+kww\ntNJoPi0sSd1AtvJVv2maqqrau1DYvjoZje1bBtEjfUGRdpYMZrquZSqRSNLKs/Pw2CZ6HExL\najtKglB1Pctn8UxndavFR7lweEIb35OhlG9a85eSGwCyclTm5TWtuYnkPQ6+Ne6Qpw04Mjqc\n/9mQlsJY8RXHLiHAMKN8e4mSADvjKOxdxWKeQKeW02FrQYlEIpH0B2QoViLpH/x8ds2YrxOz\nOOlC54BpsMZ1CjmuDM8EYLFRBHxCmzW+jX3z0PsiGvtpcaZJOtbbARTIBMisEzl1zhrRdLQ+\nfvMXSfm1VzcBsLpjfTVqucOsRCKR9CuksJNI+gvFDzhqS7/KEjdygANilQRrXEca/0DdHwFQ\nE6MIOAHPise/dXC1WGz3x1GZO72ZKdoOhzwxgMw6kVvWaIhbRdj4qpM3pIg895C9yZj0ukkk\nEsmAQa6x6w1yAUd6GJx2Tnz/CwAq2cbUGiLqlwAEYNwNwKCTaSzEQTinbQ71f0oXAGRqe0rE\nTZdvBbB2bYl46Y05s+O0Mk8n4OuLd+4v9o9IYGGjBmBUW77XcS8A95IncYqpe7LGzvbVSV3Y\ncwbnI51+pJ0lgxm5xk4i6V9oQwiAxImpSExVtHft7AhKIhxOHeXcScFZLD6hRsMN1e/PnrHg\nz23JXr/7fCqAX/mMZTsSAGIUbRopazT25Tmvqpm0vxgA3s9LOBj5NKsBeFoj+T/BkxdgkhKJ\npMcQ0tkFQ0hH2lTqpbNtvyCc+3S6uVWa6asfRN/+gGQoViLpZyybhHZ5ZyVuJOGZNOEVVwhi\nlJuEqQTc6dhTFkmAmpu2vJ/yZgLg7mPa8sna8skagIjC7L0t7isPL9xVvmBXOQiJUzNOzQhp\nWP6mZ+NK/+6P56d1jhKJpGek/pdvt/AU7A5n235BOPfpdHOrNNNXP4g+/wFJYSeR9D+WTcKy\nSdq/X6oNIWR4YQJ+mvDa8o6SCOd6Utu1cYBPD66+4vhqAFkmyTJplqktrO9YUscIxjXGOIgJ\nlZmX1FPXNbs3n/qZG1fKNAiJpH9xwT1SfUsfTmeAWaZvkaFYiaQfI7x3y3cmTvhVso0mvGLN\nHXfUceaOqtTl2FPGAIW0YdL04OrPvQsBgPAREWVmS2z5ZG3ZjkSd0/IaSlljrDLPyUHz4qUN\n2sHRcezVOWCCWweMAOecmOT4av9XFsoFcxJJT6l6pQ/+HBrxtdP+0qVfu/i3vnruNymffmeX\n7elXdZXP9MHHlf2g6/Z+qyylx04i6fcsm6QNIcQ7DXyUCKsq8UJKw26TRWlyf9gMZSeAHZlC\n9xEAk1vc3z3iFgHZfZktLQ5rSFsEAAcF4LBUwgmFShU99aPeWC39dhKJRHIRcxbCbsmSJStX\nrqysrDx/o5FIJF2zbBKWTcLQQlvb0bhXaDvddDmtpLZbVPX+MQc/5uDgpH29nb58MiVgQWcb\ngLeG1QDISZSOPPgpI9yCaZnRhBU1mZGwoqHGHa2hwPur/KFQQBwXcsoSieRMdFp0T1Lot/6k\nbjjd8rLU9v45tXMZVZ//4M7iFrZlb7nllltuuWXmzJlTpkw5x4+/SJG59OlB2rkLHtuE2ijo\nYXsjCSN+hepeTUhMlKyLx8f//+zdeXxV9Z0//tfnc+6elaysYakCURHEWJFadVCp2Am2FqnY\nUcdOtfiddqa1DLX+wKGWaTsWnI61hVFbW7HCWKdOw1RaF1qpVdCoRMQAKktkS0hC1ruecz6/\nP05yuSS5Se6Se2+S1/ORh577Oct9f07CzTuf7Tw15W/H6wCUBtFmU5vHB+7f47cO9hhafXa2\nKQIOZRr2Wiv5c5s4NnXeabsuYQMwIe/CB0RXSne/Kr92Ud/9RFzuJA78kU6NEXaf+5lGauUE\n1t4ehw1Yni6DrE6f5ZlWl7AeYcf0jUh6pWJosWtpaXn99dfXrVu3devWu+66a86cOUKI1atX\n79y5s6GhYeDziShxq+dhnBul5eF/uy4ctXnPE0oKQAIOx/65Jw7vyYaVtOXq4qt1rvq8/OKA\nVhzQPAayDCGVE4AIlYevOuHgzjTUhYjiEp5Bme5AkiNadfosj2zcQgbMjUUm5ZeWGBK7vLy8\nefPmfetb31JK7d69e/PmzZWVlWvXrr3ssstKS0vvvvvumpqaoQuUiLqsnofV8wBAAgJwHIHj\niPTOFjAFlIS6SP3PtYcO78mG0etUoVDS0Z5liICwhYTthFZ0QivskKJNUzYFqfRso/DaRdW5\nueW9TiWijJAJqUwSDab7NUydDRkwgyHTsjrEPXli9uzZCxYsuOWWW8IlGzdunDNnzurVq5MU\nGBH165E7YLNBnEnvROfF1kQKATVTPP/1wz+76PjhS48eNgBDqJrSbCUAwASOe9TvJp783cST\nt1z6fUA0aAWmwAs5ar9L7XbXP/RKRX0HR9cREQ0gA7M6xJfY1dXVrV+/vrS0dNmyZcuXL9+9\ne7dSav/+/atWrVq7du369euTHiUR9eHHt6IsB2U5mJwDAeE8AsB6mGyW2ekxAnmO5x2u3489\ndfgLn9DfzdV9Ulm53YUNHVc3TALwtYP33XLp962L3VZz1lC5TuVPdXWIaBCijbWPtTxDDNOw\n0d2m2KNrGBnwDYrtEjU1Nc8+++zatWsBLF++fPny5T3mT1gVy8BvQHKNsJG5GYv3ebAefBaA\nqusUyjRtjZF7DNj90lF46VfX1Eul6V846HOaAlASYndJljUOb5wXAFrcbzsUAAglvllxiVJm\ntvRw8kRy8Uc6NXifaTSLYYHiu+++e+PGjQDWrVt30003lZWV9XlYZWVlckIjoliIsix1pF3o\nRSKUC8B0HwQgoXtM3f+n373lnvvCJyb9zzT3rR/4DSEAzGno3F1iTbIQCmqM7yLD8Q6AgMC/\nvv3GmosqTMP/gFb749f6XtkukNXVXftSaqpHRESDEENX7MaNGzdv3nzkyJFvfetb0bI6pVRV\nVVWSYiOiwVm5xPq/kX00ZLO1ewKwn5Z6PgABBUC5Dl7se/v2fR8D2HSuS1Ndi6XMaeiY09BR\n0tEOQKHXUGWloIcGfPPPRsn8iIgo9WJb7uTmm2+OltIRUTqtXIKVS2yF5dJ12KkMAw6lnFIf\ng+5Rd8p1sMR4Txh2YdifmpYdkOojT6jJYTTZAwBKOtqPZoWum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97gL7V48eKqqqqYAg2fGN6OvEK0ciJKjZxxWuvxrGw0m3qBppSQTcI7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\nBDsAAICQINgBAACExP8HoX07GZ2Qh00AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "freq_by_rank %>%\n",
    "  ggplot(aes(rank, `term frequency`, color = IssueDate)) +\n",
    "  geom_abline(intercept = -0.62, slope = -1.1, color = \"gray50\", linetype = 2) +\n",
    "  geom_line(size = 1.1, alpha = 0.8, show.legend = TRUE) +\n",
    "  scale_x_log10() +\n",
    "  scale_y_log10()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF-IDF on unigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "abstract_tf_idf <- abstract_words %>% \n",
    "  bind_tf_idf(word, IssueDate,n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>IssueDate</th><th scope=col>word</th><th scope=col>n</th><th scope=col>tf</th><th scope=col>idf</th><th scope=col>tf_idf</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1981         </td><td>discs        </td><td> 20          </td><td>0.013812155  </td><td>1.9459101    </td><td>0.02687721   </td></tr>\n",
       "\t<tr><td>2001         </td><td>downcomer    </td><td>133          </td><td>0.006860621  </td><td>3.7376696    </td><td>0.02564273   </td></tr>\n",
       "\t<tr><td>2007         </td><td>beak         </td><td> 77          </td><td>0.006126183  </td><td>3.7376696    </td><td>0.02289765   </td></tr>\n",
       "\t<tr><td>2010         </td><td>platter      </td><td>191          </td><td>0.007463270  </td><td>3.0445224    </td><td>0.02272209   </td></tr>\n",
       "\t<tr><td>1983         </td><td>finfish      </td><td> 27          </td><td>0.005909389  </td><td>3.7376696    </td><td>0.02208735   </td></tr>\n",
       "\t<tr><td>1980         </td><td>restrictor   </td><td> 29          </td><td>0.005846774  </td><td>3.7376696    </td><td>0.02185331   </td></tr>\n",
       "\t<tr><td>1981         </td><td>hearth       </td><td> 16          </td><td>0.011049724  </td><td>1.9459101    </td><td>0.02150177   </td></tr>\n",
       "\t<tr><td>1987         </td><td>depositor    </td><td> 28          </td><td>0.005593288  </td><td>3.7376696    </td><td>0.02090586   </td></tr>\n",
       "\t<tr><td>1980         </td><td>embrittlement</td><td> 53          </td><td>0.010685484  </td><td>1.7917595    </td><td>0.01914582   </td></tr>\n",
       "\t<tr><td>2004         </td><td>asbestos     </td><td> 53          </td><td>0.006172121  </td><td>3.0445224    </td><td>0.01879116   </td></tr>\n",
       "\t<tr><td>1983         </td><td>collector    </td><td> 67          </td><td>0.014664040  </td><td>1.2527630    </td><td>0.01837057   </td></tr>\n",
       "\t<tr><td>1989         </td><td>float        </td><td> 43          </td><td>0.018663194  </td><td>0.9044563    </td><td>0.01688004   </td></tr>\n",
       "\t<tr><td>1989         </td><td>invalid      </td><td> 10          </td><td>0.004340278  </td><td>3.7376696    </td><td>0.01622252   </td></tr>\n",
       "\t<tr><td>1999         </td><td>banana       </td><td> 94          </td><td>0.005322763  </td><td>3.0445224    </td><td>0.01620527   </td></tr>\n",
       "\t<tr><td>1989         </td><td>handicapped  </td><td> 14          </td><td>0.006076389  </td><td>2.6390573    </td><td>0.01603594   </td></tr>\n",
       "\t<tr><td>1984         </td><td>warewashing  </td><td> 16          </td><td>0.006015038  </td><td>2.6390573    </td><td>0.01587403   </td></tr>\n",
       "\t<tr><td>1980         </td><td>embrittled   </td><td> 28          </td><td>0.005645161  </td><td>2.6390573    </td><td>0.01489790   </td></tr>\n",
       "\t<tr><td>1987         </td><td>polyamide    </td><td> 37          </td><td>0.007391131  </td><td>1.9459101    </td><td>0.01438248   </td></tr>\n",
       "\t<tr><td>2009         </td><td>septage      </td><td>110          </td><td>0.005291005  </td><td>2.6390573    </td><td>0.01396327   </td></tr>\n",
       "\t<tr><td>1984         </td><td>ware         </td><td> 19          </td><td>0.007142857  </td><td>1.9459101    </td><td>0.01389936   </td></tr>\n",
       "\t<tr><td>1992         </td><td>robot        </td><td> 49          </td><td>0.004461847  </td><td>3.0445224    </td><td>0.01358419   </td></tr>\n",
       "\t<tr><td>1977         </td><td>ruthenium    </td><td> 44          </td><td>0.006852515  </td><td>1.9459101    </td><td>0.01333438   </td></tr>\n",
       "\t<tr><td>2001         </td><td>coving       </td><td> 69          </td><td>0.003559270  </td><td>3.7376696    </td><td>0.01330337   </td></tr>\n",
       "\t<tr><td>1978         </td><td>kiln         </td><td> 68          </td><td>0.009219089  </td><td>1.4350845    </td><td>0.01323017   </td></tr>\n",
       "\t<tr><td>1981         </td><td>elliptical   </td><td>  9          </td><td>0.006215470  </td><td>2.1282317    </td><td>0.01322796   </td></tr>\n",
       "\t<tr><td>1991         </td><td>steamtable   </td><td> 33          </td><td>0.003510638  </td><td>3.7376696    </td><td>0.01312161   </td></tr>\n",
       "\t<tr><td>1981         </td><td>shafthearth  </td><td>  5          </td><td>0.003453039  </td><td>3.7376696    </td><td>0.01290632   </td></tr>\n",
       "\t<tr><td>1984         </td><td>wash         </td><td> 66          </td><td>0.024812030  </td><td>0.5187938    </td><td>0.01287233   </td></tr>\n",
       "\t<tr><td>1987         </td><td>fluidizing   </td><td> 33          </td><td>0.006592089  </td><td>1.9459101    </td><td>0.01282761   </td></tr>\n",
       "\t<tr><td>1984         </td><td>collector    </td><td> 27          </td><td>0.010150376  </td><td>1.2527630    </td><td>0.01271602   </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>1984         </td><td>natural      </td><td>1            </td><td>3.759398e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1984         </td><td>products     </td><td>1            </td><td>3.759398e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1984         </td><td>separation   </td><td>1            </td><td>3.759398e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1985         </td><td>andor        </td><td>1            </td><td>2.403268e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1985         </td><td>maximum      </td><td>1            </td><td>2.403268e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1985         </td><td>pressure     </td><td>1            </td><td>2.403268e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>bottom       </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>desirable    </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>liquid       </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>pressure     </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>reduce       </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>separation   </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1986         </td><td>step         </td><td>1            </td><td>3.148615e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1988         </td><td>resulting    </td><td>1            </td><td>2.262443e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>desirable    </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>including    </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>maximum      </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>objects      </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>pressure     </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>resulting    </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>separation   </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>1989         </td><td>type         </td><td>1            </td><td>4.340278e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2004         </td><td>maximum      </td><td>1            </td><td>1.164551e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2004         </td><td>objects      </td><td>1            </td><td>1.164551e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2005         </td><td>maximum      </td><td>1            </td><td>9.746589e-05 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2006         </td><td>maximum      </td><td>1            </td><td>5.912262e-05 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2008         </td><td>maximum      </td><td>1            </td><td>1.093613e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2008         </td><td>natural      </td><td>1            </td><td>1.093613e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2008         </td><td>objects      </td><td>1            </td><td>1.093613e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "\t<tr><td>2008         </td><td>substantially</td><td>1            </td><td>1.093613e-04 </td><td>0            </td><td>0            </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       " IssueDate & word & n & tf & idf & tf\\_idf\\\\\n",
       "\\hline\n",
       "\t 1981          & discs         &  20           & 0.013812155   & 1.9459101     & 0.02687721   \\\\\n",
       "\t 2001          & downcomer     & 133           & 0.006860621   & 3.7376696     & 0.02564273   \\\\\n",
       "\t 2007          & beak          &  77           & 0.006126183   & 3.7376696     & 0.02289765   \\\\\n",
       "\t 2010          & platter       & 191           & 0.007463270   & 3.0445224     & 0.02272209   \\\\\n",
       "\t 1983          & finfish       &  27           & 0.005909389   & 3.7376696     & 0.02208735   \\\\\n",
       "\t 1980          & restrictor    &  29           & 0.005846774   & 3.7376696     & 0.02185331   \\\\\n",
       "\t 1981          & hearth        &  16           & 0.011049724   & 1.9459101     & 0.02150177   \\\\\n",
       "\t 1987          & depositor     &  28           & 0.005593288   & 3.7376696     & 0.02090586   \\\\\n",
       "\t 1980          & embrittlement &  53           & 0.010685484   & 1.7917595     & 0.01914582   \\\\\n",
       "\t 2004          & asbestos      &  53           & 0.006172121   & 3.0445224     & 0.01879116   \\\\\n",
       "\t 1983          & collector     &  67           & 0.014664040   & 1.2527630     & 0.01837057   \\\\\n",
       "\t 1989          & float         &  43           & 0.018663194   & 0.9044563     & 0.01688004   \\\\\n",
       "\t 1989          & invalid       &  10           & 0.004340278   & 3.7376696     & 0.01622252   \\\\\n",
       "\t 1999          & banana        &  94           & 0.005322763   & 3.0445224     & 0.01620527   \\\\\n",
       "\t 1989          & handicapped   &  14           & 0.006076389   & 2.6390573     & 0.01603594   \\\\\n",
       "\t 1984          & warewashing   &  16           & 0.006015038   & 2.6390573     & 0.01587403   \\\\\n",
       "\t 1980          & embrittled    &  28           & 0.005645161   & 2.6390573     & 0.01489790   \\\\\n",
       "\t 1987          & polyamide     &  37           & 0.007391131   & 1.9459101     & 0.01438248   \\\\\n",
       "\t 2009          & septage       & 110           & 0.005291005   & 2.6390573     & 0.01396327   \\\\\n",
       "\t 1984          & ware          &  19           & 0.007142857   & 1.9459101     & 0.01389936   \\\\\n",
       "\t 1992          & robot         &  49           & 0.004461847   & 3.0445224     & 0.01358419   \\\\\n",
       "\t 1977          & ruthenium     &  44           & 0.006852515   & 1.9459101     & 0.01333438   \\\\\n",
       "\t 2001          & coving        &  69           & 0.003559270   & 3.7376696     & 0.01330337   \\\\\n",
       "\t 1978          & kiln          &  68           & 0.009219089   & 1.4350845     & 0.01323017   \\\\\n",
       "\t 1981          & elliptical    &   9           & 0.006215470   & 2.1282317     & 0.01322796   \\\\\n",
       "\t 1991          & steamtable    &  33           & 0.003510638   & 3.7376696     & 0.01312161   \\\\\n",
       "\t 1981          & shafthearth   &   5           & 0.003453039   & 3.7376696     & 0.01290632   \\\\\n",
       "\t 1984          & wash          &  66           & 0.024812030   & 0.5187938     & 0.01287233   \\\\\n",
       "\t 1987          & fluidizing    &  33           & 0.006592089   & 1.9459101     & 0.01282761   \\\\\n",
       "\t 1984          & collector     &  27           & 0.010150376   & 1.2527630     & 0.01271602   \\\\\n",
       "\t ... & ... & ... & ... & ... & ...\\\\\n",
       "\t 1984          & natural       & 1             & 3.759398e-04  & 0             & 0            \\\\\n",
       "\t 1984          & products      & 1             & 3.759398e-04  & 0             & 0            \\\\\n",
       "\t 1984          & separation    & 1             & 3.759398e-04  & 0             & 0            \\\\\n",
       "\t 1985          & andor         & 1             & 2.403268e-04  & 0             & 0            \\\\\n",
       "\t 1985          & maximum       & 1             & 2.403268e-04  & 0             & 0            \\\\\n",
       "\t 1985          & pressure      & 1             & 2.403268e-04  & 0             & 0            \\\\\n",
       "\t 1986          & bottom        & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & desirable     & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & liquid        & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & pressure      & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & reduce        & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & separation    & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1986          & step          & 1             & 3.148615e-04  & 0             & 0            \\\\\n",
       "\t 1988          & resulting     & 1             & 2.262443e-04  & 0             & 0            \\\\\n",
       "\t 1989          & desirable     & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & including     & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & maximum       & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & objects       & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & pressure      & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & resulting     & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & separation    & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 1989          & type          & 1             & 4.340278e-04  & 0             & 0            \\\\\n",
       "\t 2004          & maximum       & 1             & 1.164551e-04  & 0             & 0            \\\\\n",
       "\t 2004          & objects       & 1             & 1.164551e-04  & 0             & 0            \\\\\n",
       "\t 2005          & maximum       & 1             & 9.746589e-05  & 0             & 0            \\\\\n",
       "\t 2006          & maximum       & 1             & 5.912262e-05  & 0             & 0            \\\\\n",
       "\t 2008          & maximum       & 1             & 1.093613e-04  & 0             & 0            \\\\\n",
       "\t 2008          & natural       & 1             & 1.093613e-04  & 0             & 0            \\\\\n",
       "\t 2008          & objects       & 1             & 1.093613e-04  & 0             & 0            \\\\\n",
       "\t 2008          & substantially & 1             & 1.093613e-04  & 0             & 0            \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "IssueDate | word | n | tf | idf | tf_idf | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1981          | discs         |  20           | 0.013812155   | 1.9459101     | 0.02687721    | \n",
       "| 2001          | downcomer     | 133           | 0.006860621   | 3.7376696     | 0.02564273    | \n",
       "| 2007          | beak          |  77           | 0.006126183   | 3.7376696     | 0.02289765    | \n",
       "| 2010          | platter       | 191           | 0.007463270   | 3.0445224     | 0.02272209    | \n",
       "| 1983          | finfish       |  27           | 0.005909389   | 3.7376696     | 0.02208735    | \n",
       "| 1980          | restrictor    |  29           | 0.005846774   | 3.7376696     | 0.02185331    | \n",
       "| 1981          | hearth        |  16           | 0.011049724   | 1.9459101     | 0.02150177    | \n",
       "| 1987          | depositor     |  28           | 0.005593288   | 3.7376696     | 0.02090586    | \n",
       "| 1980          | embrittlement |  53           | 0.010685484   | 1.7917595     | 0.01914582    | \n",
       "| 2004          | asbestos      |  53           | 0.006172121   | 3.0445224     | 0.01879116    | \n",
       "| 1983          | collector     |  67           | 0.014664040   | 1.2527630     | 0.01837057    | \n",
       "| 1989          | float         |  43           | 0.018663194   | 0.9044563     | 0.01688004    | \n",
       "| 1989          | invalid       |  10           | 0.004340278   | 3.7376696     | 0.01622252    | \n",
       "| 1999          | banana        |  94           | 0.005322763   | 3.0445224     | 0.01620527    | \n",
       "| 1989          | handicapped   |  14           | 0.006076389   | 2.6390573     | 0.01603594    | \n",
       "| 1984          | warewashing   |  16           | 0.006015038   | 2.6390573     | 0.01587403    | \n",
       "| 1980          | embrittled    |  28           | 0.005645161   | 2.6390573     | 0.01489790    | \n",
       "| 1987          | polyamide     |  37           | 0.007391131   | 1.9459101     | 0.01438248    | \n",
       "| 2009          | septage       | 110           | 0.005291005   | 2.6390573     | 0.01396327    | \n",
       "| 1984          | ware          |  19           | 0.007142857   | 1.9459101     | 0.01389936    | \n",
       "| 1992          | robot         |  49           | 0.004461847   | 3.0445224     | 0.01358419    | \n",
       "| 1977          | ruthenium     |  44           | 0.006852515   | 1.9459101     | 0.01333438    | \n",
       "| 2001          | coving        |  69           | 0.003559270   | 3.7376696     | 0.01330337    | \n",
       "| 1978          | kiln          |  68           | 0.009219089   | 1.4350845     | 0.01323017    | \n",
       "| 1981          | elliptical    |   9           | 0.006215470   | 2.1282317     | 0.01322796    | \n",
       "| 1991          | steamtable    |  33           | 0.003510638   | 3.7376696     | 0.01312161    | \n",
       "| 1981          | shafthearth   |   5           | 0.003453039   | 3.7376696     | 0.01290632    | \n",
       "| 1984          | wash          |  66           | 0.024812030   | 0.5187938     | 0.01287233    | \n",
       "| 1987          | fluidizing    |  33           | 0.006592089   | 1.9459101     | 0.01282761    | \n",
       "| 1984          | collector     |  27           | 0.010150376   | 1.2527630     | 0.01271602    | \n",
       "| ... | ... | ... | ... | ... | ... | \n",
       "| 1984          | natural       | 1             | 3.759398e-04  | 0             | 0             | \n",
       "| 1984          | products      | 1             | 3.759398e-04  | 0             | 0             | \n",
       "| 1984          | separation    | 1             | 3.759398e-04  | 0             | 0             | \n",
       "| 1985          | andor         | 1             | 2.403268e-04  | 0             | 0             | \n",
       "| 1985          | maximum       | 1             | 2.403268e-04  | 0             | 0             | \n",
       "| 1985          | pressure      | 1             | 2.403268e-04  | 0             | 0             | \n",
       "| 1986          | bottom        | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | desirable     | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | liquid        | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | pressure      | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | reduce        | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | separation    | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1986          | step          | 1             | 3.148615e-04  | 0             | 0             | \n",
       "| 1988          | resulting     | 1             | 2.262443e-04  | 0             | 0             | \n",
       "| 1989          | desirable     | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | including     | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | maximum       | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | objects       | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | pressure      | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | resulting     | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | separation    | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 1989          | type          | 1             | 4.340278e-04  | 0             | 0             | \n",
       "| 2004          | maximum       | 1             | 1.164551e-04  | 0             | 0             | \n",
       "| 2004          | objects       | 1             | 1.164551e-04  | 0             | 0             | \n",
       "| 2005          | maximum       | 1             | 9.746589e-05  | 0             | 0             | \n",
       "| 2006          | maximum       | 1             | 5.912262e-05  | 0             | 0             | \n",
       "| 2008          | maximum       | 1             | 1.093613e-04  | 0             | 0             | \n",
       "| 2008          | natural       | 1             | 1.093613e-04  | 0             | 0             | \n",
       "| 2008          | objects       | 1             | 1.093613e-04  | 0             | 0             | \n",
       "| 2008          | substantially | 1             | 1.093613e-04  | 0             | 0             | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       IssueDate word          n   tf           idf       tf_idf    \n",
       "1      1981      discs          20 0.013812155  1.9459101 0.02687721\n",
       "2      2001      downcomer     133 0.006860621  3.7376696 0.02564273\n",
       "3      2007      beak           77 0.006126183  3.7376696 0.02289765\n",
       "4      2010      platter       191 0.007463270  3.0445224 0.02272209\n",
       "5      1983      finfish        27 0.005909389  3.7376696 0.02208735\n",
       "6      1980      restrictor     29 0.005846774  3.7376696 0.02185331\n",
       "7      1981      hearth         16 0.011049724  1.9459101 0.02150177\n",
       "8      1987      depositor      28 0.005593288  3.7376696 0.02090586\n",
       "9      1980      embrittlement  53 0.010685484  1.7917595 0.01914582\n",
       "10     2004      asbestos       53 0.006172121  3.0445224 0.01879116\n",
       "11     1983      collector      67 0.014664040  1.2527630 0.01837057\n",
       "12     1989      float          43 0.018663194  0.9044563 0.01688004\n",
       "13     1989      invalid        10 0.004340278  3.7376696 0.01622252\n",
       "14     1999      banana         94 0.005322763  3.0445224 0.01620527\n",
       "15     1989      handicapped    14 0.006076389  2.6390573 0.01603594\n",
       "16     1984      warewashing    16 0.006015038  2.6390573 0.01587403\n",
       "17     1980      embrittled     28 0.005645161  2.6390573 0.01489790\n",
       "18     1987      polyamide      37 0.007391131  1.9459101 0.01438248\n",
       "19     2009      septage       110 0.005291005  2.6390573 0.01396327\n",
       "20     1984      ware           19 0.007142857  1.9459101 0.01389936\n",
       "21     1992      robot          49 0.004461847  3.0445224 0.01358419\n",
       "22     1977      ruthenium      44 0.006852515  1.9459101 0.01333438\n",
       "23     2001      coving         69 0.003559270  3.7376696 0.01330337\n",
       "24     1978      kiln           68 0.009219089  1.4350845 0.01323017\n",
       "25     1981      elliptical      9 0.006215470  2.1282317 0.01322796\n",
       "26     1991      steamtable     33 0.003510638  3.7376696 0.01312161\n",
       "27     1981      shafthearth     5 0.003453039  3.7376696 0.01290632\n",
       "28     1984      wash           66 0.024812030  0.5187938 0.01287233\n",
       "29     1987      fluidizing     33 0.006592089  1.9459101 0.01282761\n",
       "30     1984      collector      27 0.010150376  1.2527630 0.01271602\n",
       "...    ...       ...           ... ...          ...       ...       \n",
       "130964 1984      natural       1   3.759398e-04 0         0         \n",
       "130965 1984      products      1   3.759398e-04 0         0         \n",
       "130966 1984      separation    1   3.759398e-04 0         0         \n",
       "130967 1985      andor         1   2.403268e-04 0         0         \n",
       "130968 1985      maximum       1   2.403268e-04 0         0         \n",
       "130969 1985      pressure      1   2.403268e-04 0         0         \n",
       "130970 1986      bottom        1   3.148615e-04 0         0         \n",
       "130971 1986      desirable     1   3.148615e-04 0         0         \n",
       "130972 1986      liquid        1   3.148615e-04 0         0         \n",
       "130973 1986      pressure      1   3.148615e-04 0         0         \n",
       "130974 1986      reduce        1   3.148615e-04 0         0         \n",
       "130975 1986      separation    1   3.148615e-04 0         0         \n",
       "130976 1986      step          1   3.148615e-04 0         0         \n",
       "130977 1988      resulting     1   2.262443e-04 0         0         \n",
       "130978 1989      desirable     1   4.340278e-04 0         0         \n",
       "130979 1989      including     1   4.340278e-04 0         0         \n",
       "130980 1989      maximum       1   4.340278e-04 0         0         \n",
       "130981 1989      objects       1   4.340278e-04 0         0         \n",
       "130982 1989      pressure      1   4.340278e-04 0         0         \n",
       "130983 1989      resulting     1   4.340278e-04 0         0         \n",
       "130984 1989      separation    1   4.340278e-04 0         0         \n",
       "130985 1989      type          1   4.340278e-04 0         0         \n",
       "130986 2004      maximum       1   1.164551e-04 0         0         \n",
       "130987 2004      objects       1   1.164551e-04 0         0         \n",
       "130988 2005      maximum       1   9.746589e-05 0         0         \n",
       "130989 2006      maximum       1   5.912262e-05 0         0         \n",
       "130990 2008      maximum       1   1.093613e-04 0         0         \n",
       "130991 2008      natural       1   1.093613e-04 0         0         \n",
       "130992 2008      objects       1   1.093613e-04 0         0         \n",
       "130993 2008      substantially 1   1.093613e-04 0         0         "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "abstract_tf_idf %>% \n",
    "  select(-total) %>% \n",
    "  arrange(desc(tf_idf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Selecting by tf_idf\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OZdN6B9LNoLUk10exDpUPGtgw3p6oRxnIjUuOsG9rO89ZaV9RWKIs1aIPJkC72h\nSPHw97ZVunbmECsinWH/aiH5GJQ1f/JCrQvB8HdL8Q1du4sgkgMQqVaMSDaI9A2fkZqK/Yvk\nr82GV3YlUuGbiXlN4K+y/2kU/tpseGVfItkgkuBfpHE9O7dpPUWkgd03r9EgEiL1B5EERLJB\npAqIJCCSDSJVQCQBkWwQqQIiCYhkg0gVEEmYJlJ4+Urx+yZEcgsiCbNEEoMKMyh+QCS3IJKA\nSDaIVAGRhEkiLfsFx6979y1+Euzaa1pTRAoXO1mUxwqIJMw8I8UTlcLTUri+RG+RZq2TcZ6b\nEpFIXhMs4sdKNF1EmtWqXZDmcyLS9pRCb5GCXXt925t0RlolgxtnyOpH4zUa72ek7SkFRLqH\nYKblok9lzkAkAZFsPlSktIu3F2YgkoBINp8pkrVVQCQBkWw+VyS6doeLHYi0ra2BSI27HkO6\n2En4mOHvajHX2tl8lkgnQCQBkWwQqQIiCYhkg0gVEEnwL5K/Nhte+SkizWsCf5URyWFlRHIb\nzYNFomvnlktdOn8uXKqMSDaIVAGRBESyQaQKiCQgkg0iVUAkAZFsEKkCIgmIZINIFRBJuFuk\nJX9oTjL/BZEuc/yPgrTVQCRhskjqMzGIdBlEGl8ZkWwQqQIiCVNEkmWDlm1eM6sIte/6ENmf\n7t3/amzyIPwrs/HEvjHTKPy5cKnyDJHiJWq0iX3hQi29RZq14Mx5Lrd3tjbQoj1YZZvXUKO5\nJtI7IA09QaTQHGbIntj1EaKWjea7Wg/ummru76RyqfL9IqXpbf0Oq/+ASFcIWjtaG0gRadFX\nD0KkpuLbRVrMM5IBIl1BJoyvLWckpRCRmopnfUZaV0Q6u+sj2FogUtfKjkSia9e46yOEQweV\nrl2wjWrY73SIJEwb/l5DkRj+PrLrQwTD3+UzUjr8LTUY/m4o5lo7m7cQ6TKFbjciCYhkg0jf\nIFJTMSLZINI3iNRU7F8kf202vLIrkQrMawJ/lRHJYWVEchvNg0Ua1K37xmtaTxGJrp2ASDaI\nVAGRBESyQaQKiCQgkg0iVUAkAZFsEKkCIgmIZINIFRBJ6C1SZUmgn5ccex6RzqE2Zz2dIyCS\n0FmklqAQCZEQqQIi9aiMSG6juUmk5ffS+3BdoHyG835dfvwSRGrddZVlXfRmTqdLlLbZ9Ioc\nRBIGnJGiGIL5R/ttPrkvmqL5fbQBPUWatdjMNY6nEMagTdgzm7+wVaK5JtI7IG0+QqR1VeNY\n9m0hsZyeIiW79vq2d/2MtDYKkr5utZ9X4IwkDBNpW5NG1qbJRMpfooFIh+kqUmEgFpGEoWek\naLv37orJ5VuTU2QAABLzSURBVCDSYfqKZKuESAIi2SBSJRtEEu76jLS9tylFfEY6uOsqpkhH\nBxviAdcMRBJGiZQPqsblS/4SRGrcdZVIpLPD39nrcxBJ4Fo7m8eKdBeIJCCSDSJVQCTBv0j+\n2mx45aeINK8J/FVGJIeVEcltNIj0pMqI5DYaRHpSZURyG82DRQJ4AIgE0AFEAugAIgF0AJEA\nOoBIAB1AJIAOIBJABxAJoAOIBNABRALoACIBdACRADqASAAdQCSADiASQAcQCaADiATQAUQC\n6AAiAXQAkQA6gEgRX38Tbv++t8aPYRJGNF9fPrJBpJCv182XPPgKn4dpWNFI4VwQKSRL62tF\nJB9Y0exlk0GkjOhtD4c8oUQT3ZkIImWoIrnoh388ukgukkGklK9VEWl/EiaiRbM6CQaRUlSR\n5DHMA5EeRCoOIrlBjcZLLogUk40wIJIX9Gi85IJIEdFXfcldH4F9LEY0XnJBpJD9a3KubPCG\nGQ0iAbwPiATQAUQC6AAiAXQAkQA6gEgAHUAkgA4gEkAH/Iv014XSh1au7NoN85rAX2VEclgZ\nkdxGg0hPqoxIbqNBpCdVRiS30TxYpP/zFOLD/gSR/mcUiDSA2X40Ex82IiGSL2b70Ux82IiE\nSL6Y7Ucz8WEjEiL5YrYfzcSHjUiINJCl8lhhth/NxIc9VqSGdjv0urzGsv1XAJEEP2ckK7PZ\nfjQTH/Z8kZbG15l7rlZGJAGRuhEfNiIhUk+Wvwm2P72Fn7v741fR9sKM2X40Ex/2aJF+G217\nsKbNvPygFsQJRFWi7da1M5NBpIDBIi2vm2D7G1OcVdod/ytgth/N/DUKrV1fv/OvRg6aM2jj\nuJ3TxjeqxMkEL1CiGSbSsKbsjSRyh0jxVoKJP8/StWssTdovezMK29gsMEviZMrjDcNE4oyU\nsWxvmuu2zWJMXpIy249m4sOeI9KySJcvEiktQKTOlccPNuzdjHXVRUpekjLbj2biw75HpFf3\nLu0e62ekNWl8ROpY+Y5RuzhIRaRiYLP9aCY+bERCpI7o8aiPEamxNGy/TaS0iyfFRkFeku8i\nzSsDkYQZw99rHONWxPB3W2nYfvtN1sy/DSpGhQXRTTb8vSYWMfzdUuznC1mL2X40Ex/2Xdfa\nFU4YhzizC0QSEKkb8WEjEiL5YrYfzcSHfY9Ila8ODoBI1yr7F8lfmw2vfOSMNJN5TeCvMiI5\nrIxIbqN5sEhuOmsJiDSua3eZ4mEjEiL5YrYuNsXDRiRE8sVsXWyKh41IiOSL2brYFA8bkRDJ\nF7N1sSkeNiIhki9m62JTPGxEQqQRWFfS1Zmti03xsBEJkQagadSo1mxdbIqHjUiINABEOlI6\nTaRghvMaL2oTXaJvX6qPSGOJ1nCS9YWy5zRm62JT/Cc/UaRttszrQTgnKVxCIL2EOVyoZaJI\ns9amSRgfkTa7L31OiWa2Ljb3R3PjKkKWOOXpzJyRBmNNpLXe5AJm62JT/Bc/8YwUXuevz3je\npseae0CksWw97LSHgEiHim9aRWhVFulYgv8LKiHSWMKeGyI5FmmLxepCxCnmINJYEOlI6eTB\nBk2kJdkiUuuu+8JnpCOlk4e/1+hj0RoNf0fD4AqINJboo+rriXj4e0WkevFtX8jmUZSG6gIQ\nyS2zdbEpHvYbiVTqyqUgkltm62JTPOwni5R23ApduRREcstsXWyKh/1kkS4w5J/tu/JTRJrX\nBP4qI5LDyojkNpoHizSvN4dIFWZ34FK240IkDURyy2xxUrbjQiQNRHLLbHFStuNCJA1Ecsts\ncVK240IkDURyy2xxUrbjQiQNRHLLbHFStuN6J5Eqs/UOgEg9OBhG28tni5OyHdebidRYWssM\nkXrQnscBZouTsh0XImkgUg8QSXiMSK+5Edo0iSVbpSZasUYDkVpJ50LoSzZF81mUDH6WqNGq\n58wWJ6Wx/Z4iUjBbL524Z00cS68GDxdquVeku5afOcKBdo8aeVm1EJbkNstj0asr0cwWJ2Vm\nNINEWpc1FSccf1iC11Ymj3FGaiVqXKvxt1ziMLQZselWYbY4KY3t96QzUirSEq8W9Lrduxp7\nuQIitZLMRc7PUHuDi0h5Boh0qvjGM9KrNDoDhe+GBojUTvIZSdmuae8uywCRThXfLpLalUCk\nI7suUe7SvV6yi6RlgEiniucONixhiHTtGndtEDXuslqDDXvHetUzULNCpFrxlOHvfZWaV9dd\nyhUQqZWgkV8fhIy/WLDut0oG2ZmI4e+W4huutSv12xpApJNcbPeGfc0WJ2U7rvcTqdRlawWR\nTtJJJD4jNRWPXmm1fbUgC0Q6Sa8zkp3hbHFStuN6Q5E6MO3X+ekijWdeE/irjEgOKyOS22ge\nLNKMTt0viFTBS1cuBZE0EMktiCQgEiKdBpEEREKk0yCSgEiIdBpEEoaItCRb/SUNr/oGkYaT\nJ9D2HRQiCUNFansJIh3cdXfOfnWLSAIiIRIidag8SCS5kDi57ju4xli7OlwBkbrwymS78ntZ\n4/VO5DXBLFrvi59Y/9b3EUlUKcxy0abKbEcbcJdI96+c0UrPTMSYNQwjmFmxTU56wOInswIR\npH3Hde0UkbKitFTjLpHyn/xmZ6RVvAjfupbw6eSF8SszZotk/Vvf54z0uomnhylFaakGInUB\nkRqLvYu0pr0JrVQDkbog71lrmENgUdK9Q6RDxTeKZHxGint9OYjUBURqLHYlkvQfrI5C0KEo\nh4VIfZBh1KJIrxCSxJwufmL9W99HJIa//Ym0jWbH/eklsSoc/l7jjHIQSeBau48RKb9nvKC5\nEJEEREKk4tN8RmorRqQPE8noQhe+f/C7+Il1xIikMe3X+b1EGsG8JvBXGZEcVkYkt9E8WKRp\nPTtEqjGv94ZIx0EktyCSgEiIdBpEEhAJkU6DSAIiIdJpEElAJEQ6DSIJ3UVSv7srXn5SAZHc\ngkgCIiGSSktkiCQgEiKpINKx4gEipfMlliV7Mrt+f/40CuUnv7tI0UpCyTa8fb0wB5GE/iIF\ns41+tov2pLHdjzbgJpFmrUPTQO+I0qjMSKIMlWhuEGlWmzci7TKmaxfMHs+mYu5b5XmNm0RS\nfvL7n5FWI681EcnYwQ0iGT/5E85IciMrEspbW/Ck8rwGIo0imhMb5bUi0tHicSIlvbn8TKQ8\nr4FIo4j7AWFeKyIdLR4mUt5rQ6ROu+5F2qtDpAuVhw42SNeuMNjgZBUh5Sd/jkhKFIh0rHjo\n8HfgjD787WgVIeUnf4RIVhTx8LcOIglca/e5Il0GkQREQqTTIJKASIh0GkQS/Ivkr82GV36K\nSPOawF9lRHJYGZHcRvNgkQZ257ym9RSRBvbhvEaDSIjUH0QSEMkGkSogkoBINohUAZEERLJB\npAqIJCCSDSJVQCThfpFKV3prIFJf0ivwL4BIwpQz0qEMEakvHQTaQCQBkWwQqQIiCTeKFCxJ\n81pYKJhOO2Uahde0BouU/aXsZZ80sa7qVBcjG0QS7hMpmCW2TSIzFz8JF2oZKdIz6JyDTLKU\nJTPi540pzlk0PUWa1bjXkGa9WSTJRp2CrjFSpPIRv+sZac1ECp9fwyfXYjY9RUp27TUaL2ek\nVRep9LeAEakvdZH2ObKvCmY2iCQ4EakQFyL1pSqSTC6vqYRIghuRzD4EIvWlJpKaiZ4NIgnz\nBhu25yauIuQ1rbEiKYMNr200EmQNBAUgkjBj+HtfsGZNl67RQKS+qMPfa/TOFmfC8HdLMdfa\n2bynSB1BJAGRbBCpAiIJiGSDSBUQSfAvkr82G175KSLNawJ/lRHJYWVEchvNg0Ua0ad77dpr\nWk8RqWfXLunieY0GkRCpP4gkIJINIlVAJAGRbBCpAiIJiGSDSBUQSUAkG0SqgEhCD5G0K7HS\n50pT98ogkgPGX7SKSFdFqimGSA5ApFoxItkg0g4i1Yr7iLTsE1iCWRLLGv0937A4uDw/vFVB\npMEkcylkmkXyV5pzEEnoIlJsyj4zLIknKE5nlaWTx8KFWkaINGvRmXN0iKiUXprHkmy3hPNo\nRog0q5HPIc3YrWsnSljzLsPioKomUsgIkbZfivK/6zPOSNFsciW+m2bIbrx27TWa8Z+RmkWS\nt7dl7xEui923Q6TBLHunG5HOV+4p0tatez1MRdq7d6/owq5DYe+INBx1sU5EOlQ8RST9M5IB\nIt1AQSBEaioeJNJiixQ9w2ekE7vuS5aH0kM3ut2IJHQV6eXCPvz9erBkxUv4Moa/D+66M2ke\na5IYw98txX2vtSt10erFOoh0LwdCQiQBkWwQqQIiCT1FKqyE31Bs4a/Nhld+ikjzmsBfZf/T\nKPy12fDKU0U6ACIJiOSwMiK5jebBIg36fPSN17SeItKYj0c/eI0GkRCpP4gkIJINIlVAJAGR\nbBCpAiIJiGSDSBUQSRgg0nLym1cDRJpLIUtEEsaI1BNEup/FuJ+ASAIi2SBSej8BkYRhXbtl\nv6z757l8QQ3tsQYi3c6yX/AdXA2ugEjCOJH2eSzh3JbK4/1oA3qLNGudjPP0j6hGNG8snnkZ\nHlhnkWa17wWkyQaekcIwGrcavUUKdu31bW/2GcmY6JzRWaRw116jmdG1WwviLLLwSfhYA5Hu\nB5EOF088I6XlBoh0P4h0uBiRbBAJkZqL+Yxkg0jxgrkZiCTcI1K2BIrxWAOR7mf/5uInSIa/\nG4q51s7mc0VqBJEERLJBpAqIJCCSDSJVQCTBv0j+2mx45aeINK8J/FVGJIeVEcltNA8WaVC3\n7huvaT1FpEHdum+8RoNIiNQfRBIQyQaRKiCSgEg2iFQBkQREskGkCogkIJINIlVAJGGESKVr\nuY+DSGMo/nGQtggRSeCMZPPWIvV4t0MkAZFsEKkCIgmdRIrWDIrmSchfiI1nKMlT8lAFkXoR\nhRH+6d6fgjTCcIWn8fORDjbB+4q07DfJ4gzr/mBJbreNPJSjDegp0qzFZq7RJ6I4jHgSrKQX\nRLgEL5RswgPrKNKstr2ING63M1KcUTqXXJ6PC4Ow7pghm+za69vesDPSaoikld471Tzdtddo\nxnft1oMiSd/u1cW4YxWhZNde0xoq0hK1PCJ1qnyvSGHvbk0eWSBSLyIlEKlv5Uki7c8j0vFd\nnwWRBlYeKVIW0bKG95Y8Pw1E6sX5z0hGtxuRhEEiRcsE7YPbS/DaJRqrY/j7wK7PEjX1kt0P\nb6JOA8PfDcV8IWvzbiJdAJFqxYhkg0jf8BmpqRiRbBDpB7vbjUiCf5H8tdnwyr5EspnXBP4q\nI5LDyojkNpoHi3SpH+evwTvs2g2j+nWr32gQScNrWojkNhpE0vCaFiK5jQaRNLymhUhuo0Ek\nDa9pIZLbaBBJw2taiOQ2Gk8ilS71VkCkcSxaGu35IJKASGeL30SkpicHX9mg7NprNIik4TUt\nRHIbzUyRlnXJl92QFWqirQIijUH+1vLvw2hSRbC80GKng0jCHSK90inM+0uvMA4Xajkt0qyV\nZbozJpVXMvlSTmEuYXR5NL1EmtWw15F2ueWMtKoipUUGnJGGkKQRJGK90eX0EknZtddo5nbt\nVmvu8r56UGEhakQagibSvr5QuNQQIjUVTxJJeg37q/iM1LrrLkRva8G88iM9BkQSpomUB2Sk\nhUhDyEU63vVGJOHmwYZlyZ1SBhtCEGkIQRrBTSmfHEQSbhz+lgHXleHvK7vuQ5DG3ttO85HR\nOzUdRBLu6tqdB5HcgkgCIp0tRiRECvAvkr82G175KSLNawJ/lf1Po/DXZsMrI5LbaBDpSZUR\nyW00iPSkyojkNpoHiwTwABAJoAOIBNABRALoACIBdACRADqASAAdQCSADiASQAcQCaAD/kQK\n5/gdmP83uPJau4r9yk++dNQ38oHRNFd2J1I46/zIjPSxlde1tNDRxZ986ahv5AOjaa+MSE2V\nv28Qab/5mGgQyah0uvJSrls/7Ct1312kNdwerjwyGkTylVa5I45IlyqPjAaR9EqX2ux85Urt\n8q+Jn8GGD4ymPRtEaqlc/cGXDvvSP/lGPjCa9sofJVL5F7KU1r5I+YjDRiS30SCSVqny+zjq\nPRORapX9RoNISqXaryMiVfjAaB4sknxtHN4/+j20UrnaBSj+5LWW9pXDvvRPvpEPjKa5sj+R\nAB4IIgF0AJEAOoBIAB1AJIAOIBJABxAJoAOIBNABRALoACIBdACRADqASG/Kf39fBfavf/z5\n8x+/j//sSX/fCwqgC4j0pvyIs/z5swkUixQUQBdozTflxxNVlu8nsag3NOh78nPG+ROcd37u\n/N2j++eaFEAXaM73RBXp3989un8i0ghozjcl7dp93/3PP/9Y//0PunYjoEHfFE2k//jzr7+7\nd4g0Ahr0TdlFenXjRB9EGgEN+qYg0r3QoG8KXbt7oUHfFE2k//rzj3+vDDYMgQZ9U/78WTKR\n9uFvROoODfqm/Lci0vqvf/5+IYtI3aFBATqASAAdQCSADiASQAcQCaADiATQAUQC6AAiAXQA\nkQA68P8BgOh1iuNGs04AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "abstract_tf_idf %>% \n",
    "  subset(IssueDate %in% c(\"2012\":\"2018\")) %>% \n",
    "  arrange(desc(tf_idf)) %>%\n",
    "  mutate(word = factor(word, levels = rev(unique(word)))) %>%\n",
    "  group_by(IssueDate) %>%\n",
    "  top_n(10) %>%\n",
    "  ungroup %>%\n",
    "  ggplot(aes(word, tf_idf, fill = IssueDate)) +\n",
    "  geom_col(show.legend = FALSE) +\n",
    "  labs(x = NULL, y = \"tf-idf\") +\n",
    "  facet_wrap(~IssueDate, ncol = 2, scales = \"free_y\") +\n",
    "  coord_flip()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF-IDF on bigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>bigram</th><th scope=col>n</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>of the           </td><td>22634            </td></tr>\n",
       "\t<tr><td>in the           </td><td> 9012            </td></tr>\n",
       "\t<tr><td>to the           </td><td> 7153            </td></tr>\n",
       "\t<tr><td>from the         </td><td> 4406            </td></tr>\n",
       "\t<tr><td>the present      </td><td> 4404            </td></tr>\n",
       "\t<tr><td>and the          </td><td> 4018            </td></tr>\n",
       "\t<tr><td>present invention</td><td> 3958            </td></tr>\n",
       "\t<tr><td>such as          </td><td> 3500            </td></tr>\n",
       "\t<tr><td>may be           </td><td> 3342            </td></tr>\n",
       "\t<tr><td>can be           </td><td> 3305            </td></tr>\n",
       "\t<tr><td>the invention    </td><td> 3302            </td></tr>\n",
       "\t<tr><td>in a             </td><td> 3270            </td></tr>\n",
       "\t<tr><td>food waste       </td><td> 3107            </td></tr>\n",
       "\t<tr><td>of a             </td><td> 3078            </td></tr>\n",
       "\t<tr><td>to a             </td><td> 3039            </td></tr>\n",
       "\t<tr><td>and a            </td><td> 2635            </td></tr>\n",
       "\t<tr><td>it is            </td><td> 2622            </td></tr>\n",
       "\t<tr><td>at least         </td><td> 2558            </td></tr>\n",
       "\t<tr><td>with the         </td><td> 2556            </td></tr>\n",
       "\t<tr><td>to be            </td><td> 2212            </td></tr>\n",
       "\t<tr><td>into the         </td><td> 2066            </td></tr>\n",
       "\t<tr><td>by the           </td><td> 1991            </td></tr>\n",
       "\t<tr><td>on the           </td><td> 1905            </td></tr>\n",
       "\t<tr><td>the food         </td><td> 1863            </td></tr>\n",
       "\t<tr><td>as a             </td><td> 1845            </td></tr>\n",
       "\t<tr><td>for the          </td><td> 1798            </td></tr>\n",
       "\t<tr><td>the first        </td><td> 1734            </td></tr>\n",
       "\t<tr><td>the waste        </td><td> 1731            </td></tr>\n",
       "\t<tr><td>that the         </td><td> 1727            </td></tr>\n",
       "\t<tr><td>is a             </td><td> 1642            </td></tr>\n",
       "\t<tr><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>zone without                        </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones adjacent                      </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones after                         </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones climatically                  </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones from                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones gas                           </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones including                     </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones intensive                     </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones into                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones more                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones not                           </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones one                           </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones serves                        </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones with                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zones would                         </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zoogloeal slime                     </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zoonoses into                       </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zoonoses such                       </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zoos the                            </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zopfiii in                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zr niobium                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zrfx ceo                            </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zrosubsub andor                     </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zrtm glycidoxypropyltrimethoxysilane</td><td>1                                   </td></tr>\n",
       "\t<tr><td>zshaped brackets                    </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zshaped or                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zsm in                              </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zu munster                          </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zuccarini xdc                       </td><td>1                                   </td></tr>\n",
       "\t<tr><td>zutell nov                          </td><td>1                                   </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " bigram & n\\\\\n",
       "\\hline\n",
       "\t of the            & 22634            \\\\\n",
       "\t in the            &  9012            \\\\\n",
       "\t to the            &  7153            \\\\\n",
       "\t from the          &  4406            \\\\\n",
       "\t the present       &  4404            \\\\\n",
       "\t and the           &  4018            \\\\\n",
       "\t present invention &  3958            \\\\\n",
       "\t such as           &  3500            \\\\\n",
       "\t may be            &  3342            \\\\\n",
       "\t can be            &  3305            \\\\\n",
       "\t the invention     &  3302            \\\\\n",
       "\t in a              &  3270            \\\\\n",
       "\t food waste        &  3107            \\\\\n",
       "\t of a              &  3078            \\\\\n",
       "\t to a              &  3039            \\\\\n",
       "\t and a             &  2635            \\\\\n",
       "\t it is             &  2622            \\\\\n",
       "\t at least          &  2558            \\\\\n",
       "\t with the          &  2556            \\\\\n",
       "\t to be             &  2212            \\\\\n",
       "\t into the          &  2066            \\\\\n",
       "\t by the            &  1991            \\\\\n",
       "\t on the            &  1905            \\\\\n",
       "\t the food          &  1863            \\\\\n",
       "\t as a              &  1845            \\\\\n",
       "\t for the           &  1798            \\\\\n",
       "\t the first         &  1734            \\\\\n",
       "\t the waste         &  1731            \\\\\n",
       "\t that the          &  1727            \\\\\n",
       "\t is a              &  1642            \\\\\n",
       "\t ... & ...\\\\\n",
       "\t zone without                         & 1                                   \\\\\n",
       "\t zones adjacent                       & 1                                   \\\\\n",
       "\t zones after                          & 1                                   \\\\\n",
       "\t zones climatically                   & 1                                   \\\\\n",
       "\t zones from                           & 1                                   \\\\\n",
       "\t zones gas                            & 1                                   \\\\\n",
       "\t zones including                      & 1                                   \\\\\n",
       "\t zones intensive                      & 1                                   \\\\\n",
       "\t zones into                           & 1                                   \\\\\n",
       "\t zones more                           & 1                                   \\\\\n",
       "\t zones not                            & 1                                   \\\\\n",
       "\t zones one                            & 1                                   \\\\\n",
       "\t zones serves                         & 1                                   \\\\\n",
       "\t zones with                           & 1                                   \\\\\n",
       "\t zones would                          & 1                                   \\\\\n",
       "\t zoogloeal slime                      & 1                                   \\\\\n",
       "\t zoonoses into                        & 1                                   \\\\\n",
       "\t zoonoses such                        & 1                                   \\\\\n",
       "\t zoos the                             & 1                                   \\\\\n",
       "\t zopfiii in                           & 1                                   \\\\\n",
       "\t zr niobium                           & 1                                   \\\\\n",
       "\t zrfx ceo                             & 1                                   \\\\\n",
       "\t zrosubsub andor                      & 1                                   \\\\\n",
       "\t zrtm glycidoxypropyltrimethoxysilane & 1                                   \\\\\n",
       "\t zshaped brackets                     & 1                                   \\\\\n",
       "\t zshaped or                           & 1                                   \\\\\n",
       "\t zsm in                               & 1                                   \\\\\n",
       "\t zu munster                           & 1                                   \\\\\n",
       "\t zuccarini xdc                        & 1                                   \\\\\n",
       "\t zutell nov                           & 1                                   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "bigram | n | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| of the            | 22634             | \n",
       "| in the            |  9012             | \n",
       "| to the            |  7153             | \n",
       "| from the          |  4406             | \n",
       "| the present       |  4404             | \n",
       "| and the           |  4018             | \n",
       "| present invention |  3958             | \n",
       "| such as           |  3500             | \n",
       "| may be            |  3342             | \n",
       "| can be            |  3305             | \n",
       "| the invention     |  3302             | \n",
       "| in a              |  3270             | \n",
       "| food waste        |  3107             | \n",
       "| of a              |  3078             | \n",
       "| to a              |  3039             | \n",
       "| and a             |  2635             | \n",
       "| it is             |  2622             | \n",
       "| at least          |  2558             | \n",
       "| with the          |  2556             | \n",
       "| to be             |  2212             | \n",
       "| into the          |  2066             | \n",
       "| by the            |  1991             | \n",
       "| on the            |  1905             | \n",
       "| the food          |  1863             | \n",
       "| as a              |  1845             | \n",
       "| for the           |  1798             | \n",
       "| the first         |  1734             | \n",
       "| the waste         |  1731             | \n",
       "| that the          |  1727             | \n",
       "| is a              |  1642             | \n",
       "| ... | ... | \n",
       "| zone without                         | 1                                    | \n",
       "| zones adjacent                       | 1                                    | \n",
       "| zones after                          | 1                                    | \n",
       "| zones climatically                   | 1                                    | \n",
       "| zones from                           | 1                                    | \n",
       "| zones gas                            | 1                                    | \n",
       "| zones including                      | 1                                    | \n",
       "| zones intensive                      | 1                                    | \n",
       "| zones into                           | 1                                    | \n",
       "| zones more                           | 1                                    | \n",
       "| zones not                            | 1                                    | \n",
       "| zones one                            | 1                                    | \n",
       "| zones serves                         | 1                                    | \n",
       "| zones with                           | 1                                    | \n",
       "| zones would                          | 1                                    | \n",
       "| zoogloeal slime                      | 1                                    | \n",
       "| zoonoses into                        | 1                                    | \n",
       "| zoonoses such                        | 1                                    | \n",
       "| zoos the                             | 1                                    | \n",
       "| zopfiii in                           | 1                                    | \n",
       "| zr niobium                           | 1                                    | \n",
       "| zrfx ceo                             | 1                                    | \n",
       "| zrosubsub andor                      | 1                                    | \n",
       "| zrtm glycidoxypropyltrimethoxysilane | 1                                    | \n",
       "| zshaped brackets                     | 1                                    | \n",
       "| zshaped or                           | 1                                    | \n",
       "| zsm in                               | 1                                    | \n",
       "| zu munster                           | 1                                    | \n",
       "| zuccarini xdc                        | 1                                    | \n",
       "| zutell nov                           | 1                                    | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       bigram                               n    \n",
       "1      of the                               22634\n",
       "2      in the                                9012\n",
       "3      to the                                7153\n",
       "4      from the                              4406\n",
       "5      the present                           4404\n",
       "6      and the                               4018\n",
       "7      present invention                     3958\n",
       "8      such as                               3500\n",
       "9      may be                                3342\n",
       "10     can be                                3305\n",
       "11     the invention                         3302\n",
       "12     in a                                  3270\n",
       "13     food waste                            3107\n",
       "14     of a                                  3078\n",
       "15     to a                                  3039\n",
       "16     and a                                 2635\n",
       "17     it is                                 2622\n",
       "18     at least                              2558\n",
       "19     with the                              2556\n",
       "20     to be                                 2212\n",
       "21     into the                              2066\n",
       "22     by the                                1991\n",
       "23     on the                                1905\n",
       "24     the food                              1863\n",
       "25     as a                                  1845\n",
       "26     for the                               1798\n",
       "27     the first                             1734\n",
       "28     the waste                             1731\n",
       "29     that the                              1727\n",
       "30     is a                                  1642\n",
       "...    ...                                  ...  \n",
       "290169 zone without                         1    \n",
       "290170 zones adjacent                       1    \n",
       "290171 zones after                          1    \n",
       "290172 zones climatically                   1    \n",
       "290173 zones from                           1    \n",
       "290174 zones gas                            1    \n",
       "290175 zones including                      1    \n",
       "290176 zones intensive                      1    \n",
       "290177 zones into                           1    \n",
       "290178 zones more                           1    \n",
       "290179 zones not                            1    \n",
       "290180 zones one                            1    \n",
       "290181 zones serves                         1    \n",
       "290182 zones with                           1    \n",
       "290183 zones would                          1    \n",
       "290184 zoogloeal slime                      1    \n",
       "290185 zoonoses into                        1    \n",
       "290186 zoonoses such                        1    \n",
       "290187 zoos the                             1    \n",
       "290188 zopfiii in                           1    \n",
       "290189 zr niobium                           1    \n",
       "290190 zrfx ceo                             1    \n",
       "290191 zrosubsub andor                      1    \n",
       "290192 zrtm glycidoxypropyltrimethoxysilane 1    \n",
       "290193 zshaped brackets                     1    \n",
       "290194 zshaped or                           1    \n",
       "290195 zsm in                               1    \n",
       "290196 zu munster                           1    \n",
       "290197 zuccarini xdc                        1    \n",
       "290198 zutell nov                           1    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "abstract_bigrams <- df_with_patent_id %>% \n",
    "  unnest_tokens(bigram, Abstract, token = \"ngrams\", n = 2)\n",
    "\n",
    "abstract_bigrams %>% \n",
    "  count(bigram, sort = TRUE)\n",
    "\n",
    "bigrams_separated <- abstract_bigrams %>% \n",
    "  separate(bigram, c(\"word1\", \"word2\"), sep = \" \")\n",
    "\n",
    "bigrams_filtered <- bigrams_separated %>%\n",
    "  filter(!word1 %in% all_stops$word) %>%\n",
    "  filter(!word2 %in% all_stops$word)\n",
    "\n",
    "bigram_counts <- bigrams_filtered %>%\n",
    "  count(word1, word2, sort = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>word1</th><th scope=col>word2</th><th scope=col>n</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>food      </td><td>waste     </td><td>3107      </td></tr>\n",
       "\t<tr><td>organic   </td><td>waste     </td><td>1105      </td></tr>\n",
       "\t<tr><td>solid     </td><td>waste     </td><td> 844      </td></tr>\n",
       "\t<tr><td>waste     </td><td>material  </td><td> 699      </td></tr>\n",
       "\t<tr><td>prior     </td><td>art       </td><td> 614      </td></tr>\n",
       "\t<tr><td>waste     </td><td>disposer  </td><td> 538      </td></tr>\n",
       "\t<tr><td>waste     </td><td>disposal  </td><td> 484      </td></tr>\n",
       "\t<tr><td>organic   </td><td>material  </td><td> 461      </td></tr>\n",
       "\t<tr><td>waste     </td><td>materials </td><td> 461      </td></tr>\n",
       "\t<tr><td>anaerobic </td><td>digestion </td><td> 449      </td></tr>\n",
       "\t<tr><td>food      </td><td>wastes    </td><td> 427      </td></tr>\n",
       "\t<tr><td>waste     </td><td>water     </td><td> 405      </td></tr>\n",
       "\t<tr><td>carbon    </td><td>dioxide   </td><td> 338      </td></tr>\n",
       "\t<tr><td>grinding  </td><td>mechanism </td><td> 335      </td></tr>\n",
       "\t<tr><td>preferred </td><td>embodiment</td><td> 326      </td></tr>\n",
       "\t<tr><td>moisture  </td><td>content   </td><td> 292      </td></tr>\n",
       "\t<tr><td>organic   </td><td>matter    </td><td> 291      </td></tr>\n",
       "\t<tr><td>municipal </td><td>solid     </td><td> 276      </td></tr>\n",
       "\t<tr><td>sewage    </td><td>sludge    </td><td> 259      </td></tr>\n",
       "\t<tr><td>organic   </td><td>materials </td><td> 247      </td></tr>\n",
       "\t<tr><td>garbage   </td><td>disposal  </td><td> 235      </td></tr>\n",
       "\t<tr><td>waste     </td><td>products  </td><td> 230      </td></tr>\n",
       "\t<tr><td>lactic    </td><td>acid      </td><td> 228      </td></tr>\n",
       "\t<tr><td>particle  </td><td>size      </td><td> 228      </td></tr>\n",
       "\t<tr><td>food      </td><td>conveying </td><td> 224      </td></tr>\n",
       "\t<tr><td>washing   </td><td>water     </td><td> 219      </td></tr>\n",
       "\t<tr><td>food      </td><td>processing</td><td> 218      </td></tr>\n",
       "\t<tr><td>conveying </td><td>section   </td><td> 217      </td></tr>\n",
       "\t<tr><td>waste     </td><td>treatment </td><td> 215      </td></tr>\n",
       "\t<tr><td>wastewater</td><td>treatment </td><td> 215      </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>zone                           </td><td>includes                       </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>indicator                      </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>inherent                       </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>liquid                         </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>macerating                     </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>mesophilic                     </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>pal                            </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>prior                          </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>ranges                         </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>results                        </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>similar                        </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>solids                         </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>steam                          </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>stops                          </td><td>1                              </td></tr>\n",
       "\t<tr><td>zone                           </td><td>substantially                  </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>adjacent                       </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>climatically                   </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>gas                            </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>including                      </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>intensive                      </td><td>1                              </td></tr>\n",
       "\t<tr><td>zones                          </td><td>serves                         </td><td>1                              </td></tr>\n",
       "\t<tr><td>zoogloeal                      </td><td>slime                          </td><td>1                              </td></tr>\n",
       "\t<tr><td>zr                             </td><td>niobium                        </td><td>1                              </td></tr>\n",
       "\t<tr><td>zrfx                           </td><td>ceo                            </td><td>1                              </td></tr>\n",
       "\t<tr><td>zrosubsub                      </td><td>andor                          </td><td>1                              </td></tr>\n",
       "\t<tr><td>zrtm                           </td><td>glycidoxypropyltrimethoxysilane</td><td>1                              </td></tr>\n",
       "\t<tr><td>zshaped                        </td><td>brackets                       </td><td>1                              </td></tr>\n",
       "\t<tr><td>zu                             </td><td>munster                        </td><td>1                              </td></tr>\n",
       "\t<tr><td>zuccarini                      </td><td>xdc                            </td><td>1                              </td></tr>\n",
       "\t<tr><td>zutell                         </td><td>nov                            </td><td>1                              </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       " word1 & word2 & n\\\\\n",
       "\\hline\n",
       "\t food       & waste      & 3107      \\\\\n",
       "\t organic    & waste      & 1105      \\\\\n",
       "\t solid      & waste      &  844      \\\\\n",
       "\t waste      & material   &  699      \\\\\n",
       "\t prior      & art        &  614      \\\\\n",
       "\t waste      & disposer   &  538      \\\\\n",
       "\t waste      & disposal   &  484      \\\\\n",
       "\t organic    & material   &  461      \\\\\n",
       "\t waste      & materials  &  461      \\\\\n",
       "\t anaerobic  & digestion  &  449      \\\\\n",
       "\t food       & wastes     &  427      \\\\\n",
       "\t waste      & water      &  405      \\\\\n",
       "\t carbon     & dioxide    &  338      \\\\\n",
       "\t grinding   & mechanism  &  335      \\\\\n",
       "\t preferred  & embodiment &  326      \\\\\n",
       "\t moisture   & content    &  292      \\\\\n",
       "\t organic    & matter     &  291      \\\\\n",
       "\t municipal  & solid      &  276      \\\\\n",
       "\t sewage     & sludge     &  259      \\\\\n",
       "\t organic    & materials  &  247      \\\\\n",
       "\t garbage    & disposal   &  235      \\\\\n",
       "\t waste      & products   &  230      \\\\\n",
       "\t lactic     & acid       &  228      \\\\\n",
       "\t particle   & size       &  228      \\\\\n",
       "\t food       & conveying  &  224      \\\\\n",
       "\t washing    & water      &  219      \\\\\n",
       "\t food       & processing &  218      \\\\\n",
       "\t conveying  & section    &  217      \\\\\n",
       "\t waste      & treatment  &  215      \\\\\n",
       "\t wastewater & treatment  &  215      \\\\\n",
       "\t ... & ... & ...\\\\\n",
       "\t zone                            & includes                        & 1                              \\\\\n",
       "\t zone                            & indicator                       & 1                              \\\\\n",
       "\t zone                            & inherent                        & 1                              \\\\\n",
       "\t zone                            & liquid                          & 1                              \\\\\n",
       "\t zone                            & macerating                      & 1                              \\\\\n",
       "\t zone                            & mesophilic                      & 1                              \\\\\n",
       "\t zone                            & pal                             & 1                              \\\\\n",
       "\t zone                            & prior                           & 1                              \\\\\n",
       "\t zone                            & ranges                          & 1                              \\\\\n",
       "\t zone                            & results                         & 1                              \\\\\n",
       "\t zone                            & similar                         & 1                              \\\\\n",
       "\t zone                            & solids                          & 1                              \\\\\n",
       "\t zone                            & steam                           & 1                              \\\\\n",
       "\t zone                            & stops                           & 1                              \\\\\n",
       "\t zone                            & substantially                   & 1                              \\\\\n",
       "\t zones                           & adjacent                        & 1                              \\\\\n",
       "\t zones                           & climatically                    & 1                              \\\\\n",
       "\t zones                           & gas                             & 1                              \\\\\n",
       "\t zones                           & including                       & 1                              \\\\\n",
       "\t zones                           & intensive                       & 1                              \\\\\n",
       "\t zones                           & serves                          & 1                              \\\\\n",
       "\t zoogloeal                       & slime                           & 1                              \\\\\n",
       "\t zr                              & niobium                         & 1                              \\\\\n",
       "\t zrfx                            & ceo                             & 1                              \\\\\n",
       "\t zrosubsub                       & andor                           & 1                              \\\\\n",
       "\t zrtm                            & glycidoxypropyltrimethoxysilane & 1                              \\\\\n",
       "\t zshaped                         & brackets                        & 1                              \\\\\n",
       "\t zu                              & munster                         & 1                              \\\\\n",
       "\t zuccarini                       & xdc                             & 1                              \\\\\n",
       "\t zutell                          & nov                             & 1                              \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "word1 | word2 | n | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| food       | waste      | 3107       | \n",
       "| organic    | waste      | 1105       | \n",
       "| solid      | waste      |  844       | \n",
       "| waste      | material   |  699       | \n",
       "| prior      | art        |  614       | \n",
       "| waste      | disposer   |  538       | \n",
       "| waste      | disposal   |  484       | \n",
       "| organic    | material   |  461       | \n",
       "| waste      | materials  |  461       | \n",
       "| anaerobic  | digestion  |  449       | \n",
       "| food       | wastes     |  427       | \n",
       "| waste      | water      |  405       | \n",
       "| carbon     | dioxide    |  338       | \n",
       "| grinding   | mechanism  |  335       | \n",
       "| preferred  | embodiment |  326       | \n",
       "| moisture   | content    |  292       | \n",
       "| organic    | matter     |  291       | \n",
       "| municipal  | solid      |  276       | \n",
       "| sewage     | sludge     |  259       | \n",
       "| organic    | materials  |  247       | \n",
       "| garbage    | disposal   |  235       | \n",
       "| waste      | products   |  230       | \n",
       "| lactic     | acid       |  228       | \n",
       "| particle   | size       |  228       | \n",
       "| food       | conveying  |  224       | \n",
       "| washing    | water      |  219       | \n",
       "| food       | processing |  218       | \n",
       "| conveying  | section    |  217       | \n",
       "| waste      | treatment  |  215       | \n",
       "| wastewater | treatment  |  215       | \n",
       "| ... | ... | ... | \n",
       "| zone                            | includes                        | 1                               | \n",
       "| zone                            | indicator                       | 1                               | \n",
       "| zone                            | inherent                        | 1                               | \n",
       "| zone                            | liquid                          | 1                               | \n",
       "| zone                            | macerating                      | 1                               | \n",
       "| zone                            | mesophilic                      | 1                               | \n",
       "| zone                            | pal                             | 1                               | \n",
       "| zone                            | prior                           | 1                               | \n",
       "| zone                            | ranges                          | 1                               | \n",
       "| zone                            | results                         | 1                               | \n",
       "| zone                            | similar                         | 1                               | \n",
       "| zone                            | solids                          | 1                               | \n",
       "| zone                            | steam                           | 1                               | \n",
       "| zone                            | stops                           | 1                               | \n",
       "| zone                            | substantially                   | 1                               | \n",
       "| zones                           | adjacent                        | 1                               | \n",
       "| zones                           | climatically                    | 1                               | \n",
       "| zones                           | gas                             | 1                               | \n",
       "| zones                           | including                       | 1                               | \n",
       "| zones                           | intensive                       | 1                               | \n",
       "| zones                           | serves                          | 1                               | \n",
       "| zoogloeal                       | slime                           | 1                               | \n",
       "| zr                              | niobium                         | 1                               | \n",
       "| zrfx                            | ceo                             | 1                               | \n",
       "| zrosubsub                       | andor                           | 1                               | \n",
       "| zrtm                            | glycidoxypropyltrimethoxysilane | 1                               | \n",
       "| zshaped                         | brackets                        | 1                               | \n",
       "| zu                              | munster                         | 1                               | \n",
       "| zuccarini                       | xdc                             | 1                               | \n",
       "| zutell                          | nov                             | 1                               | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       word1      word2                           n   \n",
       "1      food       waste                           3107\n",
       "2      organic    waste                           1105\n",
       "3      solid      waste                            844\n",
       "4      waste      material                         699\n",
       "5      prior      art                              614\n",
       "6      waste      disposer                         538\n",
       "7      waste      disposal                         484\n",
       "8      organic    material                         461\n",
       "9      waste      materials                        461\n",
       "10     anaerobic  digestion                        449\n",
       "11     food       wastes                           427\n",
       "12     waste      water                            405\n",
       "13     carbon     dioxide                          338\n",
       "14     grinding   mechanism                        335\n",
       "15     preferred  embodiment                       326\n",
       "16     moisture   content                          292\n",
       "17     organic    matter                           291\n",
       "18     municipal  solid                            276\n",
       "19     sewage     sludge                           259\n",
       "20     organic    materials                        247\n",
       "21     garbage    disposal                         235\n",
       "22     waste      products                         230\n",
       "23     lactic     acid                             228\n",
       "24     particle   size                             228\n",
       "25     food       conveying                        224\n",
       "26     washing    water                            219\n",
       "27     food       processing                       218\n",
       "28     conveying  section                          217\n",
       "29     waste      treatment                        215\n",
       "30     wastewater treatment                        215\n",
       "...    ...        ...                             ... \n",
       "110406 zone       includes                        1   \n",
       "110407 zone       indicator                       1   \n",
       "110408 zone       inherent                        1   \n",
       "110409 zone       liquid                          1   \n",
       "110410 zone       macerating                      1   \n",
       "110411 zone       mesophilic                      1   \n",
       "110412 zone       pal                             1   \n",
       "110413 zone       prior                           1   \n",
       "110414 zone       ranges                          1   \n",
       "110415 zone       results                         1   \n",
       "110416 zone       similar                         1   \n",
       "110417 zone       solids                          1   \n",
       "110418 zone       steam                           1   \n",
       "110419 zone       stops                           1   \n",
       "110420 zone       substantially                   1   \n",
       "110421 zones      adjacent                        1   \n",
       "110422 zones      climatically                    1   \n",
       "110423 zones      gas                             1   \n",
       "110424 zones      including                       1   \n",
       "110425 zones      intensive                       1   \n",
       "110426 zones      serves                          1   \n",
       "110427 zoogloeal  slime                           1   \n",
       "110428 zr         niobium                         1   \n",
       "110429 zrfx       ceo                             1   \n",
       "110430 zrosubsub  andor                           1   \n",
       "110431 zrtm       glycidoxypropyltrimethoxysilane 1   \n",
       "110432 zshaped    brackets                        1   \n",
       "110433 zu         munster                         1   \n",
       "110434 zuccarini  xdc                             1   \n",
       "110435 zutell     nov                             1   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bigrams_Query_filtered <- bigrams_separated %>%\n",
    "  filter(!word1 %in% all_stops$word) %>%\n",
    "  filter(!word2 %in% all_stops$word)\n",
    "\n",
    "bigrams_Query_filtered_counts <- bigrams_Query_filtered %>% \n",
    "  count(word1, word2, sort = TRUE)\n",
    "\n",
    "bigrams_Query_filtered_counts\n",
    "\n",
    "bigrams_united <- bigrams_Query_filtered %>%\n",
    "  unite(bigram, word1, word2, sep = \" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>IssueDate</th><th scope=col>bigram</th><th scope=col>n</th><th scope=col>tf</th><th scope=col>idf</th><th scope=col>tf_idf</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>1984              </td><td>soil collecting   </td><td> 42               </td><td>0.037135279       </td><td>2.639057          </td><td>0.09800213        </td></tr>\n",
       "\t<tr><td>1984              </td><td>collecting circuit</td><td> 31               </td><td>0.027409372       </td><td>2.639057          </td><td>0.07233490        </td></tr>\n",
       "\t<tr><td>1984              </td><td>food soil         </td><td> 34               </td><td>0.030061892       </td><td>2.351375          </td><td>0.07068679        </td></tr>\n",
       "\t<tr><td>1983              </td><td>collector body    </td><td> 55               </td><td>0.026278070       </td><td>2.639057          </td><td>0.06934933        </td></tr>\n",
       "\t<tr><td>1981              </td><td>pelletized refuse </td><td> 10               </td><td>0.018518519       </td><td>3.737670          </td><td>0.06921610        </td></tr>\n",
       "\t<tr><td>1989              </td><td>float sludge      </td><td> 31               </td><td>0.031958763       </td><td>2.128232          </td><td>0.06801565        </td></tr>\n",
       "\t<tr><td>1983              </td><td>soil collecting   </td><td> 50               </td><td>0.023889154       </td><td>2.639057          </td><td>0.06304485        </td></tr>\n",
       "\t<tr><td>1984              </td><td>wash chamber      </td><td> 30               </td><td>0.026525199       </td><td>2.351375          </td><td>0.06237070        </td></tr>\n",
       "\t<tr><td>1984              </td><td>soil collector    </td><td> 26               </td><td>0.022988506       </td><td>2.639057          </td><td>0.06066798        </td></tr>\n",
       "\t<tr><td>2001              </td><td>elongate vessel   </td><td>131               </td><td>0.016024465       </td><td>3.737670          </td><td>0.05989416        </td></tr>\n",
       "\t<tr><td>1987              </td><td>fluidizing oil    </td><td> 30               </td><td>0.014985015       </td><td>3.737670          </td><td>0.05600904        </td></tr>\n",
       "\t<tr><td>1986              </td><td>hot fats          </td><td> 18               </td><td>0.014610390       </td><td>3.737670          </td><td>0.05460881        </td></tr>\n",
       "\t<tr><td>1984              </td><td>soil debris       </td><td> 23               </td><td>0.020335986       </td><td>2.639057          </td><td>0.05366783        </td></tr>\n",
       "\t<tr><td>1983              </td><td>food soil         </td><td> 43               </td><td>0.020544673       </td><td>2.351375          </td><td>0.04830824        </td></tr>\n",
       "\t<tr><td>1983              </td><td>soil collector    </td><td> 38               </td><td>0.018155757       </td><td>2.639057          </td><td>0.04791408        </td></tr>\n",
       "\t<tr><td>1985              </td><td>nonionic organic  </td><td> 23               </td><td>0.012472885       </td><td>3.737670          </td><td>0.04661952        </td></tr>\n",
       "\t<tr><td>1999              </td><td>banana plant      </td><td> 93               </td><td>0.012174368       </td><td>3.737670          </td><td>0.04550377        </td></tr>\n",
       "\t<tr><td>1983              </td><td>collecting circuit</td><td> 36               </td><td>0.017200191       </td><td>2.639057          </td><td>0.04539229        </td></tr>\n",
       "\t<tr><td>2001              </td><td>downcomer zone    </td><td> 99               </td><td>0.012110092       </td><td>3.737670          </td><td>0.04526352        </td></tr>\n",
       "\t<tr><td>1983              </td><td>culture stage     </td><td> 24               </td><td>0.011466794       </td><td>3.737670          </td><td>0.04285909        </td></tr>\n",
       "\t<tr><td>1984              </td><td>ware items        </td><td> 18               </td><td>0.015915119       </td><td>2.639057          </td><td>0.04200091        </td></tr>\n",
       "\t<tr><td>1988              </td><td>float sludge      </td><td> 35               </td><td>0.019673974       </td><td>2.128232          </td><td>0.04187078        </td></tr>\n",
       "\t<tr><td>2001              </td><td>riser zone        </td><td> 91               </td><td>0.011131498       </td><td>3.737670          </td><td>0.04160586        </td></tr>\n",
       "\t<tr><td>1984              </td><td>primary spray     </td><td> 17               </td><td>0.015030946       </td><td>2.639057          </td><td>0.03966753        </td></tr>\n",
       "\t<tr><td>1984              </td><td>food ware         </td><td> 19               </td><td>0.016799293       </td><td>2.351375          </td><td>0.03950144        </td></tr>\n",
       "\t<tr><td>1981              </td><td>collecting vessel </td><td>  8               </td><td>0.014814815       </td><td>2.639057          </td><td>0.03909715        </td></tr>\n",
       "\t<tr><td>1982              </td><td>soil collecting   </td><td> 42               </td><td>0.013605442       </td><td>2.639057          </td><td>0.03590554        </td></tr>\n",
       "\t<tr><td>1983              </td><td>release agent     </td><td> 28               </td><td>0.013377926       </td><td>2.639057          </td><td>0.03530511        </td></tr>\n",
       "\t<tr><td>1989              </td><td>handicapped person</td><td>  9               </td><td>0.009278351       </td><td>3.737670          </td><td>0.03467941        </td></tr>\n",
       "\t<tr><td>1989              </td><td>infant invalid    </td><td>  9               </td><td>0.009278351       </td><td>3.737670          </td><td>0.03467941        </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>1988       </td><td>food waste </td><td>  3        </td><td>0.001686341</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1989       </td><td>food waste </td><td>  1        </td><td>0.001030928</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1990       </td><td>food waste </td><td>  5        </td><td>0.001585791</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1991       </td><td>food waste </td><td>  8        </td><td>0.001968988</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1992       </td><td>food waste </td><td> 16        </td><td>0.003355705</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1993       </td><td>food waste </td><td> 45        </td><td>0.007021376</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1994       </td><td>food waste </td><td> 18        </td><td>0.002575844</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1995       </td><td>food waste </td><td> 28        </td><td>0.003369029</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1996       </td><td>food waste </td><td> 19        </td><td>0.002880970</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1997       </td><td>food waste </td><td> 25        </td><td>0.003706449</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1998       </td><td>food waste </td><td> 24        </td><td>0.005598321</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>1999       </td><td>food waste </td><td> 76        </td><td>0.009948946</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2000       </td><td>food waste </td><td> 41        </td><td>0.004225062</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2001       </td><td>food waste </td><td> 43        </td><td>0.005259939</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2002       </td><td>food waste </td><td>239        </td><td>0.022475080</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2003       </td><td>food waste </td><td>179        </td><td>0.017625049</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2004       </td><td>food waste </td><td> 42        </td><td>0.010747185</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2005       </td><td>food waste </td><td> 65        </td><td>0.014142733</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2006       </td><td>food waste </td><td>155        </td><td>0.020402791</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2007       </td><td>food waste </td><td> 42        </td><td>0.007697947</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2008       </td><td>food waste </td><td> 77        </td><td>0.018984221</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2009       </td><td>food waste </td><td>170        </td><td>0.018581266</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2010       </td><td>food waste </td><td>179        </td><td>0.016358984</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2011       </td><td>food waste </td><td>301        </td><td>0.019048222</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2012       </td><td>food waste </td><td>270        </td><td>0.017584994</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2013       </td><td>food waste </td><td>191        </td><td>0.012751185</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2014       </td><td>food waste </td><td>160        </td><td>0.009129815</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2015       </td><td>food waste </td><td>224        </td><td>0.010935364</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2016       </td><td>food waste </td><td>228        </td><td>0.008855057</td><td>0          </td><td>0          </td></tr>\n",
       "\t<tr><td>2017       </td><td>food waste </td><td>118        </td><td>0.008035958</td><td>0          </td><td>0          </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllll}\n",
       " IssueDate & bigram & n & tf & idf & tf\\_idf\\\\\n",
       "\\hline\n",
       "\t 1984               & soil collecting    &  42                & 0.037135279        & 2.639057           & 0.09800213        \\\\\n",
       "\t 1984               & collecting circuit &  31                & 0.027409372        & 2.639057           & 0.07233490        \\\\\n",
       "\t 1984               & food soil          &  34                & 0.030061892        & 2.351375           & 0.07068679        \\\\\n",
       "\t 1983               & collector body     &  55                & 0.026278070        & 2.639057           & 0.06934933        \\\\\n",
       "\t 1981               & pelletized refuse  &  10                & 0.018518519        & 3.737670           & 0.06921610        \\\\\n",
       "\t 1989               & float sludge       &  31                & 0.031958763        & 2.128232           & 0.06801565        \\\\\n",
       "\t 1983               & soil collecting    &  50                & 0.023889154        & 2.639057           & 0.06304485        \\\\\n",
       "\t 1984               & wash chamber       &  30                & 0.026525199        & 2.351375           & 0.06237070        \\\\\n",
       "\t 1984               & soil collector     &  26                & 0.022988506        & 2.639057           & 0.06066798        \\\\\n",
       "\t 2001               & elongate vessel    & 131                & 0.016024465        & 3.737670           & 0.05989416        \\\\\n",
       "\t 1987               & fluidizing oil     &  30                & 0.014985015        & 3.737670           & 0.05600904        \\\\\n",
       "\t 1986               & hot fats           &  18                & 0.014610390        & 3.737670           & 0.05460881        \\\\\n",
       "\t 1984               & soil debris        &  23                & 0.020335986        & 2.639057           & 0.05366783        \\\\\n",
       "\t 1983               & food soil          &  43                & 0.020544673        & 2.351375           & 0.04830824        \\\\\n",
       "\t 1983               & soil collector     &  38                & 0.018155757        & 2.639057           & 0.04791408        \\\\\n",
       "\t 1985               & nonionic organic   &  23                & 0.012472885        & 3.737670           & 0.04661952        \\\\\n",
       "\t 1999               & banana plant       &  93                & 0.012174368        & 3.737670           & 0.04550377        \\\\\n",
       "\t 1983               & collecting circuit &  36                & 0.017200191        & 2.639057           & 0.04539229        \\\\\n",
       "\t 2001               & downcomer zone     &  99                & 0.012110092        & 3.737670           & 0.04526352        \\\\\n",
       "\t 1983               & culture stage      &  24                & 0.011466794        & 3.737670           & 0.04285909        \\\\\n",
       "\t 1984               & ware items         &  18                & 0.015915119        & 2.639057           & 0.04200091        \\\\\n",
       "\t 1988               & float sludge       &  35                & 0.019673974        & 2.128232           & 0.04187078        \\\\\n",
       "\t 2001               & riser zone         &  91                & 0.011131498        & 3.737670           & 0.04160586        \\\\\n",
       "\t 1984               & primary spray      &  17                & 0.015030946        & 2.639057           & 0.03966753        \\\\\n",
       "\t 1984               & food ware          &  19                & 0.016799293        & 2.351375           & 0.03950144        \\\\\n",
       "\t 1981               & collecting vessel  &   8                & 0.014814815        & 2.639057           & 0.03909715        \\\\\n",
       "\t 1982               & soil collecting    &  42                & 0.013605442        & 2.639057           & 0.03590554        \\\\\n",
       "\t 1983               & release agent      &  28                & 0.013377926        & 2.639057           & 0.03530511        \\\\\n",
       "\t 1989               & handicapped person &   9                & 0.009278351        & 3.737670           & 0.03467941        \\\\\n",
       "\t 1989               & infant invalid     &   9                & 0.009278351        & 3.737670           & 0.03467941        \\\\\n",
       "\t ... & ... & ... & ... & ... & ...\\\\\n",
       "\t 1988        & food waste  &   3         & 0.001686341 & 0           & 0          \\\\\n",
       "\t 1989        & food waste  &   1         & 0.001030928 & 0           & 0          \\\\\n",
       "\t 1990        & food waste  &   5         & 0.001585791 & 0           & 0          \\\\\n",
       "\t 1991        & food waste  &   8         & 0.001968988 & 0           & 0          \\\\\n",
       "\t 1992        & food waste  &  16         & 0.003355705 & 0           & 0          \\\\\n",
       "\t 1993        & food waste  &  45         & 0.007021376 & 0           & 0          \\\\\n",
       "\t 1994        & food waste  &  18         & 0.002575844 & 0           & 0          \\\\\n",
       "\t 1995        & food waste  &  28         & 0.003369029 & 0           & 0          \\\\\n",
       "\t 1996        & food waste  &  19         & 0.002880970 & 0           & 0          \\\\\n",
       "\t 1997        & food waste  &  25         & 0.003706449 & 0           & 0          \\\\\n",
       "\t 1998        & food waste  &  24         & 0.005598321 & 0           & 0          \\\\\n",
       "\t 1999        & food waste  &  76         & 0.009948946 & 0           & 0          \\\\\n",
       "\t 2000        & food waste  &  41         & 0.004225062 & 0           & 0          \\\\\n",
       "\t 2001        & food waste  &  43         & 0.005259939 & 0           & 0          \\\\\n",
       "\t 2002        & food waste  & 239         & 0.022475080 & 0           & 0          \\\\\n",
       "\t 2003        & food waste  & 179         & 0.017625049 & 0           & 0          \\\\\n",
       "\t 2004        & food waste  &  42         & 0.010747185 & 0           & 0          \\\\\n",
       "\t 2005        & food waste  &  65         & 0.014142733 & 0           & 0          \\\\\n",
       "\t 2006        & food waste  & 155         & 0.020402791 & 0           & 0          \\\\\n",
       "\t 2007        & food waste  &  42         & 0.007697947 & 0           & 0          \\\\\n",
       "\t 2008        & food waste  &  77         & 0.018984221 & 0           & 0          \\\\\n",
       "\t 2009        & food waste  & 170         & 0.018581266 & 0           & 0          \\\\\n",
       "\t 2010        & food waste  & 179         & 0.016358984 & 0           & 0          \\\\\n",
       "\t 2011        & food waste  & 301         & 0.019048222 & 0           & 0          \\\\\n",
       "\t 2012        & food waste  & 270         & 0.017584994 & 0           & 0          \\\\\n",
       "\t 2013        & food waste  & 191         & 0.012751185 & 0           & 0          \\\\\n",
       "\t 2014        & food waste  & 160         & 0.009129815 & 0           & 0          \\\\\n",
       "\t 2015        & food waste  & 224         & 0.010935364 & 0           & 0          \\\\\n",
       "\t 2016        & food waste  & 228         & 0.008855057 & 0           & 0          \\\\\n",
       "\t 2017        & food waste  & 118         & 0.008035958 & 0           & 0          \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "IssueDate | bigram | n | tf | idf | tf_idf | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1984               | soil collecting    |  42                | 0.037135279        | 2.639057           | 0.09800213         | \n",
       "| 1984               | collecting circuit |  31                | 0.027409372        | 2.639057           | 0.07233490         | \n",
       "| 1984               | food soil          |  34                | 0.030061892        | 2.351375           | 0.07068679         | \n",
       "| 1983               | collector body     |  55                | 0.026278070        | 2.639057           | 0.06934933         | \n",
       "| 1981               | pelletized refuse  |  10                | 0.018518519        | 3.737670           | 0.06921610         | \n",
       "| 1989               | float sludge       |  31                | 0.031958763        | 2.128232           | 0.06801565         | \n",
       "| 1983               | soil collecting    |  50                | 0.023889154        | 2.639057           | 0.06304485         | \n",
       "| 1984               | wash chamber       |  30                | 0.026525199        | 2.351375           | 0.06237070         | \n",
       "| 1984               | soil collector     |  26                | 0.022988506        | 2.639057           | 0.06066798         | \n",
       "| 2001               | elongate vessel    | 131                | 0.016024465        | 3.737670           | 0.05989416         | \n",
       "| 1987               | fluidizing oil     |  30                | 0.014985015        | 3.737670           | 0.05600904         | \n",
       "| 1986               | hot fats           |  18                | 0.014610390        | 3.737670           | 0.05460881         | \n",
       "| 1984               | soil debris        |  23                | 0.020335986        | 2.639057           | 0.05366783         | \n",
       "| 1983               | food soil          |  43                | 0.020544673        | 2.351375           | 0.04830824         | \n",
       "| 1983               | soil collector     |  38                | 0.018155757        | 2.639057           | 0.04791408         | \n",
       "| 1985               | nonionic organic   |  23                | 0.012472885        | 3.737670           | 0.04661952         | \n",
       "| 1999               | banana plant       |  93                | 0.012174368        | 3.737670           | 0.04550377         | \n",
       "| 1983               | collecting circuit |  36                | 0.017200191        | 2.639057           | 0.04539229         | \n",
       "| 2001               | downcomer zone     |  99                | 0.012110092        | 3.737670           | 0.04526352         | \n",
       "| 1983               | culture stage      |  24                | 0.011466794        | 3.737670           | 0.04285909         | \n",
       "| 1984               | ware items         |  18                | 0.015915119        | 2.639057           | 0.04200091         | \n",
       "| 1988               | float sludge       |  35                | 0.019673974        | 2.128232           | 0.04187078         | \n",
       "| 2001               | riser zone         |  91                | 0.011131498        | 3.737670           | 0.04160586         | \n",
       "| 1984               | primary spray      |  17                | 0.015030946        | 2.639057           | 0.03966753         | \n",
       "| 1984               | food ware          |  19                | 0.016799293        | 2.351375           | 0.03950144         | \n",
       "| 1981               | collecting vessel  |   8                | 0.014814815        | 2.639057           | 0.03909715         | \n",
       "| 1982               | soil collecting    |  42                | 0.013605442        | 2.639057           | 0.03590554         | \n",
       "| 1983               | release agent      |  28                | 0.013377926        | 2.639057           | 0.03530511         | \n",
       "| 1989               | handicapped person |   9                | 0.009278351        | 3.737670           | 0.03467941         | \n",
       "| 1989               | infant invalid     |   9                | 0.009278351        | 3.737670           | 0.03467941         | \n",
       "| ... | ... | ... | ... | ... | ... | \n",
       "| 1988        | food waste  |   3         | 0.001686341 | 0           | 0           | \n",
       "| 1989        | food waste  |   1         | 0.001030928 | 0           | 0           | \n",
       "| 1990        | food waste  |   5         | 0.001585791 | 0           | 0           | \n",
       "| 1991        | food waste  |   8         | 0.001968988 | 0           | 0           | \n",
       "| 1992        | food waste  |  16         | 0.003355705 | 0           | 0           | \n",
       "| 1993        | food waste  |  45         | 0.007021376 | 0           | 0           | \n",
       "| 1994        | food waste  |  18         | 0.002575844 | 0           | 0           | \n",
       "| 1995        | food waste  |  28         | 0.003369029 | 0           | 0           | \n",
       "| 1996        | food waste  |  19         | 0.002880970 | 0           | 0           | \n",
       "| 1997        | food waste  |  25         | 0.003706449 | 0           | 0           | \n",
       "| 1998        | food waste  |  24         | 0.005598321 | 0           | 0           | \n",
       "| 1999        | food waste  |  76         | 0.009948946 | 0           | 0           | \n",
       "| 2000        | food waste  |  41         | 0.004225062 | 0           | 0           | \n",
       "| 2001        | food waste  |  43         | 0.005259939 | 0           | 0           | \n",
       "| 2002        | food waste  | 239         | 0.022475080 | 0           | 0           | \n",
       "| 2003        | food waste  | 179         | 0.017625049 | 0           | 0           | \n",
       "| 2004        | food waste  |  42         | 0.010747185 | 0           | 0           | \n",
       "| 2005        | food waste  |  65         | 0.014142733 | 0           | 0           | \n",
       "| 2006        | food waste  | 155         | 0.020402791 | 0           | 0           | \n",
       "| 2007        | food waste  |  42         | 0.007697947 | 0           | 0           | \n",
       "| 2008        | food waste  |  77         | 0.018984221 | 0           | 0           | \n",
       "| 2009        | food waste  | 170         | 0.018581266 | 0           | 0           | \n",
       "| 2010        | food waste  | 179         | 0.016358984 | 0           | 0           | \n",
       "| 2011        | food waste  | 301         | 0.019048222 | 0           | 0           | \n",
       "| 2012        | food waste  | 270         | 0.017584994 | 0           | 0           | \n",
       "| 2013        | food waste  | 191         | 0.012751185 | 0           | 0           | \n",
       "| 2014        | food waste  | 160         | 0.009129815 | 0           | 0           | \n",
       "| 2015        | food waste  | 224         | 0.010935364 | 0           | 0           | \n",
       "| 2016        | food waste  | 228         | 0.008855057 | 0           | 0           | \n",
       "| 2017        | food waste  | 118         | 0.008035958 | 0           | 0           | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       IssueDate bigram             n   tf          idf      tf_idf    \n",
       "1      1984      soil collecting     42 0.037135279 2.639057 0.09800213\n",
       "2      1984      collecting circuit  31 0.027409372 2.639057 0.07233490\n",
       "3      1984      food soil           34 0.030061892 2.351375 0.07068679\n",
       "4      1983      collector body      55 0.026278070 2.639057 0.06934933\n",
       "5      1981      pelletized refuse   10 0.018518519 3.737670 0.06921610\n",
       "6      1989      float sludge        31 0.031958763 2.128232 0.06801565\n",
       "7      1983      soil collecting     50 0.023889154 2.639057 0.06304485\n",
       "8      1984      wash chamber        30 0.026525199 2.351375 0.06237070\n",
       "9      1984      soil collector      26 0.022988506 2.639057 0.06066798\n",
       "10     2001      elongate vessel    131 0.016024465 3.737670 0.05989416\n",
       "11     1987      fluidizing oil      30 0.014985015 3.737670 0.05600904\n",
       "12     1986      hot fats            18 0.014610390 3.737670 0.05460881\n",
       "13     1984      soil debris         23 0.020335986 2.639057 0.05366783\n",
       "14     1983      food soil           43 0.020544673 2.351375 0.04830824\n",
       "15     1983      soil collector      38 0.018155757 2.639057 0.04791408\n",
       "16     1985      nonionic organic    23 0.012472885 3.737670 0.04661952\n",
       "17     1999      banana plant        93 0.012174368 3.737670 0.04550377\n",
       "18     1983      collecting circuit  36 0.017200191 2.639057 0.04539229\n",
       "19     2001      downcomer zone      99 0.012110092 3.737670 0.04526352\n",
       "20     1983      culture stage       24 0.011466794 3.737670 0.04285909\n",
       "21     1984      ware items          18 0.015915119 2.639057 0.04200091\n",
       "22     1988      float sludge        35 0.019673974 2.128232 0.04187078\n",
       "23     2001      riser zone          91 0.011131498 3.737670 0.04160586\n",
       "24     1984      primary spray       17 0.015030946 2.639057 0.03966753\n",
       "25     1984      food ware           19 0.016799293 2.351375 0.03950144\n",
       "26     1981      collecting vessel    8 0.014814815 2.639057 0.03909715\n",
       "27     1982      soil collecting     42 0.013605442 2.639057 0.03590554\n",
       "28     1983      release agent       28 0.013377926 2.639057 0.03530511\n",
       "29     1989      handicapped person   9 0.009278351 3.737670 0.03467941\n",
       "30     1989      infant invalid       9 0.009278351 3.737670 0.03467941\n",
       "...    ...       ...                ... ...         ...      ...       \n",
       "174728 1988      food waste           3 0.001686341 0        0         \n",
       "174729 1989      food waste           1 0.001030928 0        0         \n",
       "174730 1990      food waste           5 0.001585791 0        0         \n",
       "174731 1991      food waste           8 0.001968988 0        0         \n",
       "174732 1992      food waste          16 0.003355705 0        0         \n",
       "174733 1993      food waste          45 0.007021376 0        0         \n",
       "174734 1994      food waste          18 0.002575844 0        0         \n",
       "174735 1995      food waste          28 0.003369029 0        0         \n",
       "174736 1996      food waste          19 0.002880970 0        0         \n",
       "174737 1997      food waste          25 0.003706449 0        0         \n",
       "174738 1998      food waste          24 0.005598321 0        0         \n",
       "174739 1999      food waste          76 0.009948946 0        0         \n",
       "174740 2000      food waste          41 0.004225062 0        0         \n",
       "174741 2001      food waste          43 0.005259939 0        0         \n",
       "174742 2002      food waste         239 0.022475080 0        0         \n",
       "174743 2003      food waste         179 0.017625049 0        0         \n",
       "174744 2004      food waste          42 0.010747185 0        0         \n",
       "174745 2005      food waste          65 0.014142733 0        0         \n",
       "174746 2006      food waste         155 0.020402791 0        0         \n",
       "174747 2007      food waste          42 0.007697947 0        0         \n",
       "174748 2008      food waste          77 0.018984221 0        0         \n",
       "174749 2009      food waste         170 0.018581266 0        0         \n",
       "174750 2010      food waste         179 0.016358984 0        0         \n",
       "174751 2011      food waste         301 0.019048222 0        0         \n",
       "174752 2012      food waste         270 0.017584994 0        0         \n",
       "174753 2013      food waste         191 0.012751185 0        0         \n",
       "174754 2014      food waste         160 0.009129815 0        0         \n",
       "174755 2015      food waste         224 0.010935364 0        0         \n",
       "174756 2016      food waste         228 0.008855057 0        0         \n",
       "174757 2017      food waste         118 0.008035958 0        0         "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bigram_tf_idf <- bigrams_united %>%\n",
    "  count(IssueDate, bigram) %>%\n",
    "  bind_tf_idf(bigram, IssueDate, n) %>%\n",
    "  arrange(desc(tf_idf))\n",
    "bigram_tf_idf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Selecting by tf_idf\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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OMgnfl9OgZD0kefJBdDq+yE5+pne1Q+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\nsuFApFbY+Q8OLYASETYxFIjUiioSfiNNRBfpooBApEZ+vCJSmAm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1UKSh/bhyPbtuDkSqgzewbu9k0rp5lzbOkkTJbYzkXTBQJPlVuCKV\nAZHqYPcXQv2MLDwUScnLRaKPCEKkuwCR6uDNn6L2VXxFEonTK5LymQKRlgMi1SFrZs0iid9V\nEGkkWhl2zgmR6kiOeVkLK/2NRPPiN9JgLB3aBUuASHV8i148qSef5ks6bcVFSV72BKCWG83f\n54FILUtf0NcOzyPV4cQ9OnoTz6fz/Ta0Z3pbkObhQKQ7ApHqOBiqM53vtExpg9HlYzZcemfv\nBSJdUafbeIZI24ts7mEieTHf+tGqc41IyhfjinQCiFQH+b1p3gDcptg9PJZp/4mrfwVEuiMQ\nqY6kBdR5/YokanNqIvxGeg4QqY7sbyJvzLcS6fU7iNRKpuk0/FQ9Sli74h2IVIf2cyep2sn5\n9m8kiNST/PHeeIeiMBtEqkPeo6M38bxX5muZHEspgUitQKT7iHQBEKkacoIyRhjehl//pv6e\n4URXCM/nkUzWo4EMiLQcEKkWUmW2atFk6SYSaQ1io37STMFOZd6XcNNshEgX3OvL3v67OScO\n2IEuLC8SfzdmRSvS36uZ37JGesoIkYzdxRWpDIhUC2/p2XurbvP2qxBEash0a+bU6/xDRKKN\nOT6+RwUyYkCkRwGRapFVOr1eB5HqM90aiFSLaGzQhmnPimQ2Nuwrh0h3BCJVw5u/93fHF4Uf\nS0KSXPN3ukKIdBsg0kgUB3jVrhE8j0Q5U5Ld1gORRiJDk/xGagQiUdRS7rOqciDSOJROCaSn\n1hmRULWjQKQMTxBpHC8XSQ4Pw39tsvEYjNEaxCmNdtLyyRDt/FfrvE6rTQUKkXK8W6SkkVRr\nG80sS25ExDSOfNQbZl3M5/21YzZc3WkLIr1BJG/IQZabyxx1Ib2hYa47c0MCV6TuNFWzKzO9\nWyTSE0veXIjzxegLQaS9Xz6poBWJ5Pj6EiBSb3qJlFvPy0VSql/BHk/FylytiErFVyQPkS4E\nImUX9Wq1s6pb8jcSffeiVB15g0gJA0SymnyUpqGtjiGaePZXbcxO+Xiz0vYkebdI9OD+FpJP\nDvqwzKfLpHxHImnrSYBIBRxFQz63R+czkRxPnw0Vj+mH0LIyQqRr2oTsNqKaeMhTkDivbacg\n5fSUvvNIxC5cZvM3i0gEIhWglHj6WZ6uWBT19LadPF/CCJGMr1rwinQ5VhgoEKmEvYJGm258\nTiTRxNMqkjWuJ0S6CvMKJIFIZbAbcYcikarep+ZhpD8WyVAJIl2GNfyW5MQBO9CF9UTSjvHj\n305bqjMiqedDiLQcEKmAImHc/qOWvzORnNdFSjLtn0NCDkRajoH1uOeIdNz87XcRHH2nP42+\nEyS91i60v+8f0fx9GyDSeHKVtDbwPNJyQKTxQKSyTLcGIo1G9o7sAap2ywGR7ghEWg6IdEcg\nkk3JZb+yajDjhixZNUQaBkSyOS9SUw0cIg1Hu8l6EohkA5EqFt9NJGWyJXvgrSIZo55of34q\nN0IKuV3H743rg6eo2SUQaTgQqTDTIUlPEifefWwkNdN61oHEiVfZpyT3Fb97E+gt0pynWv5Z\navCTtN8D7bjAl5hn1vBZ69vwZpG8TyUR7zVp3aYQSe8Kv4LRW6TiInvuFUkNVdnZ0unzd8JZ\nY4RIs89/RUXrrBJOj/KjtPGRGPIEYKjuycFOINL1KOfC9rOlHrURIhl7s9IVydNzy3F5Haf1\nXtTu+BUpkz0BIvUnPRfWni3Fe8J7Raorr6O0nolEF0GkBURKz4UtZ0uIlMCOdOfTqrD3avVZ\nplWeXg4XJCqSERK1Qz5EGgMv+5azJURKMUY9iVKkDTraCCl7WlK+LClr/vY8FGj+vgxFh9Kz\npXKGhUg2WtH0SNuyLojUn+Lm7/TMqj0wiOZviwkimec2iLQATrwfgueRPsy4IlmDoZw52se5\nAJHyQKTlgEgLAJHuD0QCAGhAJAA6AJEA6ABEAqADEAmADkAkADoAkQDoAEQCoAMQCYAOQCQA\nOvAwkWgvyYM/L9OQy9Vkcr7yqxzN1fNBhvmUFHBr3urM4amqo1I+ysxyP0sk2m+//AHAklxJ\n175cJjm/MJf1VbenqIAb8h6WlJZ5e5Lt8IuzmdOMEGkpkQ6je0vWEsmR2dUi7Y/JQaTGy0RS\ncIdf5Vu+6pEXpGEiHZaUcY46c0Wy8kGkQpGSn0i5rxJjGBR/1XfyeT+RwktnkQ5/IimZ2WSz\nSMk3Q6SKy4QrzNT8VWURvh3DRDrIO/iKxDJDpDKRvMx1lKldpOSrbs8okTx9L83MJlszp98M\nkRqP7hEiOZHwKUCkuzFCJFn213/V7Rkl0ikXOmeGSAdHN5lfnMnRDE0iPcqjoSJlS2qoSDzv\ns0RiI4LW92xQcrHuBmO/Kkbtaa12RWU1Iq+aORjRNfPDRAJgDhAJgA5AJAA6AJEA6ABEAqAD\nEAmADkAkADoAkQDoAEQCoAMQCYAOQCQAOgCR3st//PYW+89//fnzb9/Pf8LB8DtFFoBjINJ7\n+Yjj/vzZBeIikQXgGBTVe/l4osryOxMWVYHSei2fK84fct35TPyt0f27FwvAMSir16KK9F+/\nNbp/DjRCGgAAAJtJREFUh0jVoKzei6za/U7+7z//8v/1L1TtqkFpvRdNpH/7859/q3cQqRqU\n1nsJIm3VuKgPRKoGpfVeIFJHUFrvBVW7jqC03osm0v/586//8mhsqAel9V7+/HGJSKH5GyLV\ngdJ6L/+hiOT/89+/N2QhUh0oLQA6AJEA6ABEAqADEAmADkAkADoAkQDoAEQCoAMQCYAOQCQA\nOvD/AQWDSWtlFGbuAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bigram_tf_idf %>%\n",
    "  subset(IssueDate %in% c(\"2012\":\"2018\")) %>% \n",
    "  arrange(desc(tf_idf)) %>%\n",
    "  mutate(bigram = factor(bigram, levels = rev(unique(bigram)))) %>%\n",
    "  group_by(IssueDate) %>%\n",
    "  top_n(10) %>%\n",
    "  ungroup %>%\n",
    "  ggplot(aes(bigram, tf_idf, fill = IssueDate)) +\n",
    "  geom_col(show.legend = FALSE) +\n",
    "  labs(x = NULL, y = \"tf-idf\") +\n",
    "  facet_wrap(~IssueDate, ncol = 2, scales = \"free\") +\n",
    "  coord_flip()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TF-IDF on trigrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "abstract_trigrams <- df_with_patent_id %>%\n",
    "  unnest_tokens(trigram, Abstract, token = \"ngrams\", n = 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>trigram</th><th scope=col>n</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>the present invention    </td><td>3937                     </td></tr>\n",
       "\t<tr><td>of the invention         </td><td>2352                     </td></tr>\n",
       "\t<tr><td>of the present           </td><td>2040                     </td></tr>\n",
       "\t<tr><td>at least one             </td><td>1515                     </td></tr>\n",
       "\t<tr><td>us pat no                </td><td>1318                     </td></tr>\n",
       "\t<tr><td>to provide a             </td><td> 904                     </td></tr>\n",
       "\t<tr><td>portion of the           </td><td> 874                     </td></tr>\n",
       "\t<tr><td>one or more              </td><td> 829                     </td></tr>\n",
       "\t<tr><td>object of the            </td><td> 824                     </td></tr>\n",
       "\t<tr><td>the food waste           </td><td> 788                     </td></tr>\n",
       "\t<tr><td>present invention is     </td><td> 775                     </td></tr>\n",
       "\t<tr><td>the use of               </td><td> 734                     </td></tr>\n",
       "\t<tr><td>invention relates to     </td><td> 711                     </td></tr>\n",
       "\t<tr><td>a plurality of           </td><td> 676                     </td></tr>\n",
       "\t<tr><td>the invention the        </td><td> 643                     </td></tr>\n",
       "\t<tr><td>in order to              </td><td> 625                     </td></tr>\n",
       "\t<tr><td>according to the         </td><td> 576                     </td></tr>\n",
       "\t<tr><td>of this invention        </td><td> 551                     </td></tr>\n",
       "\t<tr><td>invention is to          </td><td> 540                     </td></tr>\n",
       "\t<tr><td>surface of the           </td><td> 507                     </td></tr>\n",
       "\t<tr><td>as well as               </td><td> 492                     </td></tr>\n",
       "\t<tr><td>invention to provide     </td><td> 490                     </td></tr>\n",
       "\t<tr><td>and the like             </td><td> 489                     </td></tr>\n",
       "\t<tr><td>is to provide            </td><td> 481                     </td></tr>\n",
       "\t<tr><td>present invention relates</td><td> 469                     </td></tr>\n",
       "\t<tr><td>end of the               </td><td> 465                     </td></tr>\n",
       "\t<tr><td>aspect of the            </td><td> 453                     </td></tr>\n",
       "\t<tr><td>relates to a             </td><td> 450                     </td></tr>\n",
       "\t<tr><td>food waste disposer      </td><td> 447                     </td></tr>\n",
       "\t<tr><td>the amount of            </td><td> 440                     </td></tr>\n",
       "\t<tr><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>zones more efficiently                  </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones not fully                         </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones of a                              </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones of other                          </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones one of                            </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones serves as                         </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones the lateral                       </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones the solid                         </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones the treated                       </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones to correspond                     </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones to remove                         </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones with neutral                      </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zones would also                        </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zoogloeal slime of                      </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zoonoses into rivers                    </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zoonoses such as                        </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zooplankton blooms in                   </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zooplankton blooms thereby              </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zoos the bedding                        </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zopfiii in some                         </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zr niobium nb                           </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zrfx ceo x                              </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zrosubsub andor titanium                </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zrtm glycidoxypropyltrimethoxysilane the</td><td>1                                       </td></tr>\n",
       "\t<tr><td>zshaped brackets attached               </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zshaped or cshaped                      </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zsm in some                             </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zu munster process                      </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zuccarini xdc of                        </td><td>1                                       </td></tr>\n",
       "\t<tr><td>zutell nov us                           </td><td>1                                       </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " trigram & n\\\\\n",
       "\\hline\n",
       "\t the present invention     & 3937                     \\\\\n",
       "\t of the invention          & 2352                     \\\\\n",
       "\t of the present            & 2040                     \\\\\n",
       "\t at least one              & 1515                     \\\\\n",
       "\t us pat no                 & 1318                     \\\\\n",
       "\t to provide a              &  904                     \\\\\n",
       "\t portion of the            &  874                     \\\\\n",
       "\t one or more               &  829                     \\\\\n",
       "\t object of the             &  824                     \\\\\n",
       "\t the food waste            &  788                     \\\\\n",
       "\t present invention is      &  775                     \\\\\n",
       "\t the use of                &  734                     \\\\\n",
       "\t invention relates to      &  711                     \\\\\n",
       "\t a plurality of            &  676                     \\\\\n",
       "\t the invention the         &  643                     \\\\\n",
       "\t in order to               &  625                     \\\\\n",
       "\t according to the          &  576                     \\\\\n",
       "\t of this invention         &  551                     \\\\\n",
       "\t invention is to           &  540                     \\\\\n",
       "\t surface of the            &  507                     \\\\\n",
       "\t as well as                &  492                     \\\\\n",
       "\t invention to provide      &  490                     \\\\\n",
       "\t and the like              &  489                     \\\\\n",
       "\t is to provide             &  481                     \\\\\n",
       "\t present invention relates &  469                     \\\\\n",
       "\t end of the                &  465                     \\\\\n",
       "\t aspect of the             &  453                     \\\\\n",
       "\t relates to a              &  450                     \\\\\n",
       "\t food waste disposer       &  447                     \\\\\n",
       "\t the amount of             &  440                     \\\\\n",
       "\t ... & ...\\\\\n",
       "\t zones more efficiently                   & 1                                       \\\\\n",
       "\t zones not fully                          & 1                                       \\\\\n",
       "\t zones of a                               & 1                                       \\\\\n",
       "\t zones of other                           & 1                                       \\\\\n",
       "\t zones one of                             & 1                                       \\\\\n",
       "\t zones serves as                          & 1                                       \\\\\n",
       "\t zones the lateral                        & 1                                       \\\\\n",
       "\t zones the solid                          & 1                                       \\\\\n",
       "\t zones the treated                        & 1                                       \\\\\n",
       "\t zones to correspond                      & 1                                       \\\\\n",
       "\t zones to remove                          & 1                                       \\\\\n",
       "\t zones with neutral                       & 1                                       \\\\\n",
       "\t zones would also                         & 1                                       \\\\\n",
       "\t zoogloeal slime of                       & 1                                       \\\\\n",
       "\t zoonoses into rivers                     & 1                                       \\\\\n",
       "\t zoonoses such as                         & 1                                       \\\\\n",
       "\t zooplankton blooms in                    & 1                                       \\\\\n",
       "\t zooplankton blooms thereby               & 1                                       \\\\\n",
       "\t zoos the bedding                         & 1                                       \\\\\n",
       "\t zopfiii in some                          & 1                                       \\\\\n",
       "\t zr niobium nb                            & 1                                       \\\\\n",
       "\t zrfx ceo x                               & 1                                       \\\\\n",
       "\t zrosubsub andor titanium                 & 1                                       \\\\\n",
       "\t zrtm glycidoxypropyltrimethoxysilane the & 1                                       \\\\\n",
       "\t zshaped brackets attached                & 1                                       \\\\\n",
       "\t zshaped or cshaped                       & 1                                       \\\\\n",
       "\t zsm in some                              & 1                                       \\\\\n",
       "\t zu munster process                       & 1                                       \\\\\n",
       "\t zuccarini xdc of                         & 1                                       \\\\\n",
       "\t zutell nov us                            & 1                                       \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "trigram | n | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| the present invention     | 3937                      | \n",
       "| of the invention          | 2352                      | \n",
       "| of the present            | 2040                      | \n",
       "| at least one              | 1515                      | \n",
       "| us pat no                 | 1318                      | \n",
       "| to provide a              |  904                      | \n",
       "| portion of the            |  874                      | \n",
       "| one or more               |  829                      | \n",
       "| object of the             |  824                      | \n",
       "| the food waste            |  788                      | \n",
       "| present invention is      |  775                      | \n",
       "| the use of                |  734                      | \n",
       "| invention relates to      |  711                      | \n",
       "| a plurality of            |  676                      | \n",
       "| the invention the         |  643                      | \n",
       "| in order to               |  625                      | \n",
       "| according to the          |  576                      | \n",
       "| of this invention         |  551                      | \n",
       "| invention is to           |  540                      | \n",
       "| surface of the            |  507                      | \n",
       "| as well as                |  492                      | \n",
       "| invention to provide      |  490                      | \n",
       "| and the like              |  489                      | \n",
       "| is to provide             |  481                      | \n",
       "| present invention relates |  469                      | \n",
       "| end of the                |  465                      | \n",
       "| aspect of the             |  453                      | \n",
       "| relates to a              |  450                      | \n",
       "| food waste disposer       |  447                      | \n",
       "| the amount of             |  440                      | \n",
       "| ... | ... | \n",
       "| zones more efficiently                   | 1                                        | \n",
       "| zones not fully                          | 1                                        | \n",
       "| zones of a                               | 1                                        | \n",
       "| zones of other                           | 1                                        | \n",
       "| zones one of                             | 1                                        | \n",
       "| zones serves as                          | 1                                        | \n",
       "| zones the lateral                        | 1                                        | \n",
       "| zones the solid                          | 1                                        | \n",
       "| zones the treated                        | 1                                        | \n",
       "| zones to correspond                      | 1                                        | \n",
       "| zones to remove                          | 1                                        | \n",
       "| zones with neutral                       | 1                                        | \n",
       "| zones would also                         | 1                                        | \n",
       "| zoogloeal slime of                       | 1                                        | \n",
       "| zoonoses into rivers                     | 1                                        | \n",
       "| zoonoses such as                         | 1                                        | \n",
       "| zooplankton blooms in                    | 1                                        | \n",
       "| zooplankton blooms thereby               | 1                                        | \n",
       "| zoos the bedding                         | 1                                        | \n",
       "| zopfiii in some                          | 1                                        | \n",
       "| zr niobium nb                            | 1                                        | \n",
       "| zrfx ceo x                               | 1                                        | \n",
       "| zrosubsub andor titanium                 | 1                                        | \n",
       "| zrtm glycidoxypropyltrimethoxysilane the | 1                                        | \n",
       "| zshaped brackets attached                | 1                                        | \n",
       "| zshaped or cshaped                       | 1                                        | \n",
       "| zsm in some                              | 1                                        | \n",
       "| zu munster process                       | 1                                        | \n",
       "| zuccarini xdc of                         | 1                                        | \n",
       "| zutell nov us                            | 1                                        | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       trigram                                  n   \n",
       "1      the present invention                    3937\n",
       "2      of the invention                         2352\n",
       "3      of the present                           2040\n",
       "4      at least one                             1515\n",
       "5      us pat no                                1318\n",
       "6      to provide a                              904\n",
       "7      portion of the                            874\n",
       "8      one or more                               829\n",
       "9      object of the                             824\n",
       "10     the food waste                            788\n",
       "11     present invention is                      775\n",
       "12     the use of                                734\n",
       "13     invention relates to                      711\n",
       "14     a plurality of                            676\n",
       "15     the invention the                         643\n",
       "16     in order to                               625\n",
       "17     according to the                          576\n",
       "18     of this invention                         551\n",
       "19     invention is to                           540\n",
       "20     surface of the                            507\n",
       "21     as well as                                492\n",
       "22     invention to provide                      490\n",
       "23     and the like                              489\n",
       "24     is to provide                             481\n",
       "25     present invention relates                 469\n",
       "26     end of the                                465\n",
       "27     aspect of the                             453\n",
       "28     relates to a                              450\n",
       "29     food waste disposer                       447\n",
       "30     the amount of                             440\n",
       "...    ...                                      ... \n",
       "658835 zones more efficiently                   1   \n",
       "658836 zones not fully                          1   \n",
       "658837 zones of a                               1   \n",
       "658838 zones of other                           1   \n",
       "658839 zones one of                             1   \n",
       "658840 zones serves as                          1   \n",
       "658841 zones the lateral                        1   \n",
       "658842 zones the solid                          1   \n",
       "658843 zones the treated                        1   \n",
       "658844 zones to correspond                      1   \n",
       "658845 zones to remove                          1   \n",
       "658846 zones with neutral                       1   \n",
       "658847 zones would also                         1   \n",
       "658848 zoogloeal slime of                       1   \n",
       "658849 zoonoses into rivers                     1   \n",
       "658850 zoonoses such as                         1   \n",
       "658851 zooplankton blooms in                    1   \n",
       "658852 zooplankton blooms thereby               1   \n",
       "658853 zoos the bedding                         1   \n",
       "658854 zopfiii in some                          1   \n",
       "658855 zr niobium nb                            1   \n",
       "658856 zrfx ceo x                               1   \n",
       "658857 zrosubsub andor titanium                 1   \n",
       "658858 zrtm glycidoxypropyltrimethoxysilane the 1   \n",
       "658859 zshaped brackets attached                1   \n",
       "658860 zshaped or cshaped                       1   \n",
       "658861 zsm in some                              1   \n",
       "658862 zu munster process                       1   \n",
       "658863 zuccarini xdc of                         1   \n",
       "658864 zutell nov us                            1   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "abstract_trigrams %>%\n",
    "    count(trigram, sort=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"Too few values at 1418173 locations: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...\""
     ]
    }
   ],
   "source": [
    "trigrams_separated <- abstract_trigrams %>% \n",
    "    separate(trigram, c(\"word1\",\"word2\",\"word3\", sep = \" \"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "trigrams_Query_filtered <- trigrams_separated %>% \n",
    "  filter(!word1 %in% all_stops$word) %>% \n",
    "  filter(!word2 %in% all_stops$word) %>%\n",
    "  filter(!word3 %in% all_stops$word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "trigrams_Query_filtered_counts <- trigrams_Query_filtered %>% \n",
    "  count(word1, word2, word3, sort = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "trigrams_united <- trigrams_Query_filtered %>%\n",
    "  unite(trigram, word1, word2, word3, sep = \" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "trigrams_tf_idf <- trigrams_united %>%\n",
    "  count(IssueDate, trigram, sort =TRUE) %>%\n",
    "  bind_tf_idf(trigram, IssueDate, n) %>%\n",
    "  arrange(desc(tf_idf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Selecting by tf_idf\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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QFNu1sCkWYDIt0SiDQbEOmWQKTZgEi3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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trigrams_tf_idf %>%\n",
    "  subset(IssueDate %in% c(\"2012\":\"2018\")) %>% \n",
    "  arrange(desc(tf_idf)) %>%\n",
    "  mutate(trigram = factor(trigram, levels = rev(unique(trigram)))) %>%\n",
    "  group_by(IssueDate) %>%\n",
    "  top_n(10) %>%\n",
    "  ungroup %>%\n",
    "  ggplot(aes(trigram, tf_idf, fill = IssueDate)) +\n",
    "  geom_col(show.legend = FALSE) +\n",
    "  labs(x = NULL, y = \"tf-idf\") +\n",
    "  facet_wrap(~IssueDate, ncol = 2, scales = \"free\") +\n",
    "  coord_flip()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing bigram networks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "bigram_graph <- bigrams_Query_filtered_counts %>%\n",
    "  filter(n > 100) %>%\n",
    "  graph_from_data_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AVK+hnQ6SLzyUDyT6PiCd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\nJAgQEgQICQKEBAFCggAhQYCQIOALAlnXG+s5YE4AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(2016)\n",
    "\n",
    "ggraph(bigram_graph, layout = \"fr\") +\n",
    "  geom_edge_link() +\n",
    "  geom_node_point() +\n",
    "  geom_node_text(aes(label = name), vjust = 1, hjust = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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eqUt+ma4w9FTwgCaTjJBpIrnZH2q07jrh3+UhpIeHpzs77FP1SNq6LsyaupAJIP\nbbImsy7LOGSOP8TN3zB2m0JE///bGaYdcqUzEqX9ADWMmTvIL6WBZE5vjutbsjGD7ce81Maz\nJy+NAkg+xBPzbfPBieb4w1mPdFVY2oSB9AT5SZFbe5gCkyudkTXbnvxf7yC/lAaS/GRLRn1L\nfqB1q/akKlMlIJH4UVnnCeS1OLuKIC2S7D6R0zyo+R7SvuRIZ2TNtqcAkDscHY16pHeUHSRr\ndvM4SFH07svv+rgFq666QGItSTKvxRpxxHK6bLEgIhDKqV3FzENHUs/sCsWIMqc3N+tb2LWL\n5J8vv/yy78tcRdUKko+o5CWT8MNm4s+qZ/DaFSCpf2N7mNObm/Ut/mFWyd6lFimQtFheQZLz\nRhAenwmrUAQnH42yXhxRb6wrosWYqp7B68gCKe7i4enNzfpWR3yYrSUUo3ffDc7dQvkESc0b\nIeIzgSQUwbmeIFlCszxUMhPerglSfAc9vbnolBL1LVb94nUw3Fry7rsMpEDSIvkECU0gweMz\noSHrD0ZTESaWNVpzpYUsUiXHNyxS3LFzu90pepmDFJy7RfIJkpo3As+KBzkAeZ/ENMoWrbna\nGspGu4qOv4stkmN7PpDelRYpmKQF8gkSmjciilzBK9miNVdbfI6H6qYKxxbJtT0fSC8rkAJJ\n6fLbaqfmjWCHRiBNdWPrmsvzrENx7UqQXI5dzmfwrrZIwblLl++ivWMGOndlmvRRAEkIpnio\nkKNIW6Tyx2IMvRxIyiC/dSQxBlKDtEUemk63yX0BJKXyc6Us0K4AqfyRuE8nfbvg3KXJf/P3\nNgbplCd3Ho6m0r1be4FrV+kJgKPdBMcun142QQokpchr0ZZjIDVI0ZsPQNbm0RRAmgaQagkC\n3fVrkBRIwblLUdVFm8/FJubBGVV8starnm405tl5OM7LGKSXQ8xdquoByZoGfk1V2yCS3V0f\njt27kp8Q2pBBdYCEpi5cZ5JqG47l6fCqWhQgyqAaQLLnN1xX1QSS/xMEkDKoepBUBWm9Maop\njVIVZwggZVDFIKmGhjWnKKoJpEpOEUDKoKpAEs9ROHYBo5qSVgSQmlI1IKknOeV1pEpOslyq\nBaRqThGa7DKoCpCMRxmMEdcSgxRMUgZVAFL1Dswyqg6QKjpHeIwZtBIgLcOTZtdY4eyx6hy+\n7354I2aSf5Cqf/EmnbDqE5UTXGHFaZQqAKnud2IVquXalx6kpXnSSwlSze/EKlTTxXsHqYK3\nYo7TVXkqLD05Ck44Nu70WILUWCYyti5l9thsYfHmXjud2KoAUky1XX4AqZD05Cg44ViPbIqs\ncH1zA1tMmT22CEg6o6NWxRwtH0n1Xf6Sg9TUk9aTo+B5KcEQQXpiligOb6A776TNHltkoJbr\nOwEkSwGkomer8FxYenIUPAkKuHowmyqTvQGlUcKXOYvNXa4z1io3kXuNYrQ+9ylRmns09ffJ\nebJxydvdqPdZVqAaL98HSPKJ0jJBurXe/MaedFLCMWQoXBvi+cgcc5frjLXKTeReIz+C8Cn1\noflefA6+De5DBpC4lhQk9kBrNRLLB5J9IPfc5SJjrXITudfIl/CEeyLBTC+Sq3q351fIhq97\nsewg1Xn9vkDS/64JSHJyFGsSFNu10xvcILnmLlcZa9WxsHNoTLjHvzhTq2ZiJio/dyKAlF0e\nLZJ4/55eJOTi7XpufYMgyclRrHkp2d9jbijMDW6QXKbNylgbxY9gzMMS31j8PlTdnF6vlhsk\n5uCdLXjp6c1Xsa1NgiQmRzEnQaGmQVZ17A1q7hTrQHqbBMnKWBvlBqnM7zL+XG6OlhUk/hSo\nqz+fXyJXil15TpAabLWbiclRrCljKQQ90YZmbYDPnRhIrrnLQTt8lXLt5Kc54V7MtdM7e1FL\nQFr4ixJ2WGqQWHmYk/PFrjtvIWgOJE8Hcs1drjLWKjcRg4Qn3Is1Niy4NtWuboRjdFlbITw6\ncTIVnDE7R86+0fxkPEVBWtZWO/FoiZpQzLUnzDA865I+PEXdc6I7TNRcfwd9Itehrca0gPRY\n85Oz5Pzt2p+0N5Bcc5erjLXKTTRAInLCPZEcGjd/p1+bale3wjH6rC0DjJrwP2Hrlrqk9oOU\npFUAKWFPmMpv0KUfMD2xepyow0TO9bfPD6IE16MAACAASURBVLOFHyx//4rCwHd97Sz9uLi8\nILnmLlcZa5WbaLh2wqfcUVnWUYds+rWpdnUrHGNfxGTsS1ZP+dGpuZzfPtfoLIsz2V8tIhnF\n63WflZ8DAq2bfbJvG9Ie6bJ10bMb5OyVOjiqyLVL3nOTei/0sQ1gX/04UYeJnOuvSwaR9Gvk\ng5WVBDEtIDvWpflrDTxpj/WQGk+M2tXZsXQ4Bpi4DrrDqPZ14q85Pb+0weZ90ur1yozyluxe\ncxtS+da9spQgaVffuSd7vZ7K58TW9Z0dJvS9sr/dMx8sbxTE0wLCsTx2nLRfpUBC7epmZ/EO\nrZUd6JnO5YnKN6eXle6v5n3S6vW6CT5wB3Aaq5gPZEjVl07m7/jroE6Td5C0q5+wp/6wH2eE\nHyLUwF2BAWYni/hYF4xKm0LVrm7e3FNaGLfk+81nc3pZ6UZN/jpVr9d9iv0B2aIvgB3lkRqG\ndCbfujW5/d5BQq6+e8+MIG2S7s7+zPVgcSeL+HjrLQ8/I0HtMnalS/WO9gXQ8TbJjA39MO+3\nLpFNyX726PXaA/SpmeoT+7L1En/r1vIE671JJkj6cTo7TCJ4UzruEJ4WUIL0dFVX3HSDlVcZ\n7eo46gIqqER2een7LRrWWwSSfr1uktNOP+p3RE0vyZDSt+6Zh2u50jpOos9mgKQfp7PD5EA5\nunqdPS0gfLwFFqkak1RT02ldUu3qdtQFvMpYX5J5v3WtvSlh105eFX+9Ut+O1pcG1LsbpBvS\nr8IUd9WrSZD043R0mGxZfp9cMqcFpB9vMZAqMUm1dULUJdWubodjUCM/iKLYC33WI91BkyDp\n/mp5VfL1ChWDGTAVr9ppQwpv3efJnaMarrRJkFB1Kt5hErFtDpttTAtIP54OIFWrWFhTjcLN\n3/C3fr2ClxeB9elFyYaU7/65OlL9Nvi28aOnqVsH/1fg29XYL95OsXrTFuv7bEqqv1q1iojX\nq+hF3maWNNGQbp0hZx4d1TFV5LKDBAgxkCowSWsPknj/z7wdsM67yAypmC9yVMPpqj9FlXpL\ngeTfJMU4Wj+Sdroi+MiL6rqN2pBO1cSrFZ9y6UFiCD3NP30fO4DkVa4b6e62LyttSNUMxqNK\nToS13CA9jQySd5MUQPIp550cDCo5lzSkI22RKjdJSw3SW28FkJZFbpDGg2qMEpOaubgOk7TM\nIL1lgrTItzNikZK0o9t6A0ge5b6VgzFVVaecYpAqN0nLDNLTlkVaYJIygYR3CBz5UwpItnvn\n61aPDI4CSIl6GoRBWmCSMvXQB5Aqkdu6j7kGzj3LnnJkGqRR2eMt0BKDxAQAfUESlWiSZj3c\nrTdTAyhjWYJFr7lYD8m63984FzgqrVSQUEXJ33trNLIsUsUmadlBAjF+0jgyA01QKGYsS7C5\nHkA6pwey1/RzVlHpIKmKkl8PAChSPFVtklYGpDThcZZ4AKUjSzDjSK2fe0ykvdZaCNLAtZuf\n0zKcKjdJKwDS4nZvMxg/NUswAwmnNDgJGC2Uq/a50zH3iIFE6Xl6gEgae6+U4sME126xFvcf\nmfHj+C/p5NkD2NEQDvYonhtW+hOWXC6QzHVxkGDtYDzgEu6dV5D82raFCiARNZQSDWC3x8AP\nh8NJVde//CoOkjRHoKdjHJUBwKtty6C1ACndtZPSA9hjKQ0oSJNJIClJRM+oK9N6iveTTu05\nvxSfAm0wNly7AFKDynSXzHGWegClI0swH8VipzSIhhNKUnDvEsRzdUKuV513jugGUlbXPA9L\nVsvNwKgheQXJI5LZtNwgZbxNSc3fjizBLBFwLKUBNUdgkgJJbunZz3Baz8hM/Hl7/qyVYU47\ndrz1O4DUkLLfKHOcpR5AGc8SzOeLsFMaAESMpODeuUTUfBg4rWdkJ/60M3kyirbucPfGliv+\nPpnMpiUGqdyNypWJYCJMUqgoOYVGefeMZhrV4iD3MB4Us0bVxGQFkHKo6I0qkIkAgRTcu7g0\nSFZazxhIxtdY1SiA1LQK36kCmQiGmKRglGwRc6qzUwTSWzCFhAxppK8wOVcPeNsf+KJu3eMT\nangLbgwgZVfxO5U/EwEGKbh3MeHZz4y0noT8DPmMmCaiq/vntnR7Hm716ZyWCG40rV0AKbNq\nvVUcJElS8O4s6eZvnNazI8n5aUJXb/GQYNmoh9rzIjTpYPHgRsttrJujAFImDSfaJAXXLibW\nIdtnNl7lnRMTWv0qNf6/wCYw4u2mslHPzPaOp8H1E9wYQMqqhkAKGOWRbGNQkVi/pA2Winno\ng+sXsWATsgnBjYTMz+sJUh1hE5Gcne+UN7mfqkk7m5v9NoCUQbJu9FzAKJ9skD6FPD8V82D2\njhPpKcoJUhldZthEpGbn22KTXw5o9Uy4k0YVbM1BSgqBbK46KZvrAkY5xR8ZDl0csNlDougD\n5POyjsQqSzOoXnVlHBeeINUdNiFm5xuz1N99chAZqxuY/XZpQarTC1ZVo0BSPvFHhkMXr+8/\ncQcH6WHJxClvbOgCOnpyPjTLxNgRNiGHvPRZIFcLZr9tIUguOeCqFSTh0wWQ8ok/NjukUbt2\nXSO4sYMnaFEfiWET7HNM3cN97gHi1c5Iimp/aj2nSdVMJiPhU8Db1UacuKSZ6qTy6YJzl0/i\n/adCF6G28z9cF16YnMhHBjcac267QHLNhgq2h1WU3CDV+FPrO1WScC2zp6aoNqqNfQ1Sc9VJ\nUACplHTgg2r+RgtGeAQCia3vxcIm+Oc+2erEmat/9tsWgLRtTQFvVhvNxCVNVidBAaRS0oEP\narJTtNDjnbIxkBLCJlRThmOusfpnv20BSPLtAfEhJ5Gz2jjTIDVXnWQKJJWRriOpyU7VgllP\nMkAi3P9zzYbKGsXjc43VP/ttC0DSFUOGRaK323R1kimAVEp6wj052aleEIGrDteuJ0IjHbOh\nRvjlilbP6p79tiUgcYg4FvlAqvliQ3ND3Vr0iA94y7jzqzXOftsCkKiTNp+fJIFku3bx9fVq\nUuv8jUELQeqRfdeX6p79tgUg0YrhfH4uCSQzcUmT1UmuelsJgxaARHhTgy3vs98uVAtA0g3Z\nEqS5XW3sx0GqvzoJqqkHOEgr/RF3IF7PIb+z32ZQC0BiXauvJYFkJi5psjoZ1Z8sLWhp1AaQ\nWKHUqZryFNE6q5NRACkoUS0AiZB35vNLeoBxtiJaf3UyzDwWlKwWgCQqhif5Smj91ckAUlCy\nWgBSdOUsIRdP8pZQqE7+QbMcBZKCpBoDycv04X9VzbUlKIAUlKjGQMLtbYXLZwApqCVaapD+\nKoAU1BJVDhJhqZpkShgVmSj6Ustl2KyeI407IQGkoGTVABJOCaNi5XHmmFiGzfHiwzLVDFJo\ntQtKVA0g4ZQw1uithAyb44wk1QkSKIAUlKQaQMIpYazxxEkZNlNJ+itVNcoBUiy3IF6nsrxH\nPGuEMTRGZCdk13tyPj5/Y1BQVE8dyRilFeEl409cNtNIoiC9+irAlIMjR25BtC6SozQjnjUC\nD9bsEz1s83QD1p8PIAXF1CKQTKWgRCliML2avdXOkVsQrdsGmiDLe8S5wg6ozE7IHdOL83fq\nThMRtBSqGaQU187+ok2S/vOvhF6VpimL4rkFI5TRnV1pX27Fl4UvEDLeBHMU5FLNICU1NrhG\nnZgkjQdqEYHETVMGlnqOvBlonSurRtJAd4bR6/nvRNAqq2aQcO0jlmEzJkzSAHElfTsJ1OKr\ncOUWxOvygMQUQAoyVDNIuj1MTx+uM8fEpOGhHNkmKQdH/PCncTRktkJjv1TXTiiAFGSoDdHf\nKZIksQmw1VrTs8tyHFduQTNboczyDluNxgaVnRAlMwwgBVlqOUiCpDGXWvuqBikTR87cgnqd\nzvLOtyY1f6tkhlEgKchU20HiKA3GDpP0anaO3LkFdbZCleVdeJhmh2xf+Z4qmWEAKchU+0Gi\nJHGOEEhgknJx5F8BpNVS2S6NJQApGgiQTN+OgdTgVVVIUuinqlvleweXAKSxwyT91QqDFLp8\n65aPQOQlAAkokkZJrXyVgdTgVVUFUogur11eQvrbD5JoaBhYIOWJtKtGlZAUxmnUr/UASVaP\nGEnIt2ucowDSimhuq9BR2g7SWGugTBL7uU1zVAlIfh5qUB6tB0gDTBKPt2tLIQsgrYRit7zY\nTW85SAMQImnQpsq4f5I8PdSgHFoPkJgEQxC3OmhTMQsgrYLWCCQpAKpNxUyB9LovpAJI9WsN\nQYraVocAfl5//StfCSC1UbMeId3FE2gFkJovZ19hEIGKfJtlP1+Q72s1QGrmh2Sd0tHPLV8u\nkNpU0F5XFL3+lUIHQOlflNrz8/ypqd/iur8uBZCaK2kCIklSCZAstePn+VRjv4abI3aTXUkN\nqePX3eeDpC8ScvF22YsMIOWXskSvy4XEXfVzkyOc1FPV4wzx4z1Hzr6hE341xpG3kzf3tDRI\nrqSGaC5vtnQ2gNSAXs8KEn9cfTzmVj1VDJL9eBsGyePpG3xaKAdcPKnhNs8hwJMawsyrV0pe\nYotBanFlXIH0lXTPDua4PTDTkOGnGkmQ0OOd3z7XcApKn7e3yceF6kjxpIYiv43MfDOX+XOL\nn83PRVehNlfGpS1aAJJKO6TzEuGnGinXLkKP90SCVMPvcMjrDW4HSI6khnhJewFlzubhiitS\nuyvjX0G+XeJO6ie401JGruR58NnkL/N5g2OPq86fpe6vK6lhHCT65+OHJc7m45JLaLtDfyUs\nqAkhZAUdlTaUi6Q980F8pRhI1lN1P97hpOKLT5bXkt8OkFxJDS3Xjunw2mFxkhoGiafEApJU\npitZQdcg4exYbD6ISw08lrgkSSmN3w7Xznqq7sc7HFZ/+QlaSZDiSQ1FpZXgpIaH10qQ1DBI\nUD044NVsOSGEqqCrG2Hka7w9v0I22sARb3JIB0lllMQ/wXiqjsd7L1ikpkyS36LfDpBcSQ11\n87dOangNTFJRkhoGqUM299mCnhBCvcVR86WRQXjebGUcSfh2yTuojJLaqOKn2rFBko93OGnK\nJBUq+iyqLfloqDm/EZCcSQ2hQ3ZgJjXkIBUkqWGQ9mnJ6fLaj/nWiBZWxktUDL2JcpQesaoy\nSuoOWfVUd+IgRfTxfugZZpEaMkmFQOokxrTFQKricot/neWfl6IMLS9ItKh1SecgL0j0g/qz\nDV2xoa98pVh8UKIoQuQMBSmrSfJcPAuBlEBRVDVIJY4KHjarRWhRiqCSdHit0LU0DhK8mY22\nk3TXTm44LNXE4lH/1Gf5oI93OHmQ3A8WKZNJKlGU4v3d8EcRkGRlQ7W7ohbYc+T8vKJIjZy0\nmxIe9gytuiZNUiGSGq8jHdDaeAe3nagKurOxIYoQSC0gyW8REY/3ewBSBpNUqijF+7vZH4UM\nEgNJzzBgtsCerwak3Jdpaqer0rhzHR5KkAqR1Irm723cdqIq6Koybk9HBp+lKobeVOpRuvTE\n3YTc/70Js0gLTVK5ohT3x4qCxL+o211xC2x1IU8lQYoJgVSEpKZdu60O6WzDgmo7URV0VRm3\npyPjILWAJN/PMoo4QRykhSYpy+kJTKfRM8LO6bpxp4f7u/tyfVRsUAH7Im531UuVhTwVAT5V\n3KsrTFLTIBWUfns0eRXeQcIcLTRJmYoSfQPZYefQG8fWGv3dfcFDkUEFwkvUzUV2v413jPyD\ndHiITVJ+kpYepAZJ8v5SFPxIkBaYpIwg9U7jYefK/vAqKOoBLzSoYCFI9OP54xw3YrFiP77s\n3TdBurYuIF1rA0neQRqaIKWbpGxFiVc77bBz5SbzRlHUTFpoUAFy7SJrSUa0He8deyXJO0jX\nFEjFAoVWAKSmSPL+LIdKkwwmKStI6rPnsBOxjjtpTXL9GnYEs92VL21ze0g371GQfJJUEUjX\nHl/aDtliMkBqiCTvz1LJq0WSn67BBMkg0T9vZb5e3kqh2l2tpT4HyS9Jvm/+obRERQ+1nCCZ\nFcOGSKoOpHx9sQtAYs5VT5Z2B0hx144rJ0io3RUt9Vkcf0QhApAKkmS21LOe5ApAiqIy3YLL\nDFLxJhYvaggkiUJWkFhugm0eFGMPJhCNDagHXLtlOUBarD2PIPG/qrj3ZY63nCDpmmGpMSRc\nhnuTpFoTSGQCKXOrHWE9247BBKKbDvWAY7dMgnTrlgeiJEh7hb5dE0ilDpgPJJ+lpYxUI6WP\nyNVMIMUDaioc974QpOynp65dzw4750fQ/d2yB1x1fnO3jAJ069bVqz5AOpauXR6SdF8yuzAz\njZmnbHSGagPJe4EpKmmP/Lh0CyFK2qlekOSgfIHCESHz8+TcyYKzZ/pxTt269WcAEWWp6BG0\n9oqQpPuS4UdYacw8ZaPDKvc4s9/nSopMMSmHrqw9om/rvrZIM518U4Uvi+KLA2qqTyDhAkkN\nyucXckRBou9ksnE7/fTFQOKWiHPkAaTjYw1SdpJ0XzJvBTHSmHnKRodVE0gVvXwLSdWKSoKk\nW2dR9UC97qATUxZfO6Cm2gQSFkhH8KEG5XNrxMrZ7fk5fXr3oQqAdPWqJIj/48ezUyBlJkn3\nJYtWQZzGzFM2OqQYR/kOu5QgKZUEaUul2+TRMSj5pghfxsVXNmv1Kk8gYYJ0dAQkqUH53BqJ\ncnYivZukQxWxSBIgbyDtGSBlJUk3Ljr6kwt1HKeqJpDK2b3KVI4kHcHCnQczQxPEcaLiGxl7\nVZpAwgRp92g3Mgbl4/aRSgJCDYvky7M73pO+XSGQYmnMuJ4pfXVSAaTiMh8V/ku+/YziG9uL\nL/m/GwZIR0fcJPFB+dIaGb1B3mWQVPpoyhJxmLJ+zexLtvqT+bvu6Gj3qPTlCdUDUsmzVKaq\nQUI5JaIkkOjHtNRl2LIN0hEzSREblH+ELleWswp01SdIwrPLAxEI9yXD/0Z/sug4vnd3t8SF\nGW8hM9lRACmP0l07qR3kT7gTSHgmyQBp94ibpA45OBrgvEO6nFWhqxIkL54dZyhnXIPuS+Z1\nU11H6qiWoad3j0qYJLujt0wJX3KQypGkg5NRMwLBcTIqp4SzsSGKKgfpSEoNykcgiXJWibyC\nJBbyfU/3JbN7bKYxY70Q917bVda6vJYYJA/HKQVSUvO3jpNBxTclgUSFIAmDROsC/1wMykeu\nXc9M3+FVyrXzeMx8z3tR9Y/flqMCJsns29Yj7efQNfVGsQKeWGM111UBkpcjlfPtZHBypDpk\nreSbKqdEagKJ6kCS9mg3XqmupplBi5PkIaxBKu/zXvADjyRIuU2S1bctZ3kDkC4V7hbMCJL/\nVjtPB/M+gqKgs+STJATSrsBoN15cqgYp8gtS/ue94AfuFgbJ6BzUs7xRkC6RZ4uWyaZA8nY0\nfyQ5km9mlz+Q8P3YlRg5PJjKQYqYb+fpWAWed/oP3FUWKbdvZ3QO6nH31CwV9esiBBJyVGYy\nAg2WvE79rNVCkBzJN7PLF0jGHcEYxcpL9SBFzYKUKlV1LGCSYn3butNjp9wIWfOAugrufepn\nJX8GzqNvF0u+mUN+QLJuyS7GyF/zVM7r8XYgjyTpqmMRk4Q7BzFI252Cr9HICdIWijnzPPWz\nkscb23S2VSEfJFn3RBcUp0mqXP7sh3eQdpFBKvSKUZ2DRgf7AMLCiskBEu6Y9Dz1s1TsvrbD\nJJVRBSA9Y3FUr0nyWe59Pm+Q7hQo8ooxOgfNSJUeDNYoJAdI7iUdbPtwwVMhBZBcit2TI1vl\nz1H0YrwerOwBd3eFy6uAyvX1WN+2XhqzHsIiygkS/fPy5cvFToUUQHLJ71vb78V4PZiX3wYA\nPbOb0KSZri2rbxstbRdstbVAijl08eizg4PLB6VJ8npjV4WkKkqbv4vxezRPP43x00Dt0SEF\nUod6h6qJ4VTGnPVi0WcHbpI03DFVnYAngFSBil6KuwzwQ/ifS7YFAEmhtjrwG5Oav3X02WUA\nKU5SCkgq3hPJZ5EJIPlX4WtJKAMxkPxcZhtBAsdxWzh4fdwha0WfcZDo/9ZxFoBkKYAU10qA\nlHY8vyA1e4NiytA9bkSfHQBEl6//Brnrs/CnEcHJQyD0/KF9lIfMDLSFuUXPvuFrSsR2kDTN\nTdKOGdY3j5W2toOEpi7Dk5URSEjXj2Zd0j+Ve10yf5q/Cyx9JE9KBckRfQYgHfzru4CO37DH\nFOgQCDV/KDNtGiQZaCt9xlUCKb9Jsk11Ba/tosoEEp66TIdQw/8UHTLo0o9NtdclnyD5M5Xe\nlAqSI/oM3LqD3yK/d/AiUGaOchMhEGr+UDR/lRVou+11btEAkhfhy8kEEk41p0Oo4f/NaABY\nDXiDL98L/7SSV7rYVtavdNcuHn3GQPq7ZI9ZpgNz3LVuJ+fzh6JJDqxAW3Nu0eeGmaZfSFY7\nSHKCpJ1Z7QRbPu+40xObT0yQ/M4otFAG1xk4ilxTl6m/CFFjH8Ve/hIuLR9IMXF+qDGSC+wY\nBP+vh9bLUxC0j7nEb8NwOCmHUntBUvOzYidYuEHyNvXoC/z078BfkDYVgcSy7ogkVnX/mEwg\n9cxnbYSv6Q+0l59inw3ymtUsSHwHPkVdiR/RDpBcJCn/1sgridygiNUsDj/PNxsViT2dUlEQ\nVc1lo4HX+ullGTbjmrosDpK9V3mtAkjMszv4eXDtLl9Odu1ALtdO/qlDJkBDNmlqCaPUXpDU\nTbDySuICNzs8PFSbkf+Dcirmncghj/DAaw1SlmEzvJV2EUj2XqUV46gVJBUC6bPkFy//uf2e\nlf26eCbRsXFf9e3WIROgoZh+uDhK7SDJAZJpll12mRDIZI5XqpKxZ5FUzVWbWZkjeC69bMNm\nXFOXuUAy9yqtVQCJO3SXr98l2rjjzd86BALNXxWLWEcjBiMO0nDxpKkpWmqQXJuZjES/lVWT\nzKzMnKNsw2biU5e5QLL3Kq3VAAkcuiga/5Jogop3yOoEPHL+qp04SNFMhUxEfO5hAVJBo9QO\nkCRJU90363Tt4G9xPw4P+Z/2Zq49RFJFjp2dlfmUcaR8vPRSak1dltDYYO1VWqsBkr1Q6tyi\nZx+BVBCl9oA0nY5GCCTl37rySjKvjv9pb+ZS7QwVchQZA6+pG7HJLw+7DNVp0Rn0dr20CiBp\nlQPJDJkQFSSpIgdsA0nT6WUGEWVJrVP+rSuvJNE1E3uzkJq/oeL2bznwml4u6/SykjZXpyIg\nrUSrnVI5kMyQCQ5SKeeuaZC4IeIYYZCUfxvPK3l4uIOq+NZmId34Xd2l44HXkiM8uXmlCiCV\n9O2MkInhRJmkog13jYI0EoZoKv/NECyUcSp2aZIq7JLFA6+VR4cmN69EqO9qS0a7sggPFPOM\nk8KJJbEVetve3zjXJo4Kg1TSJBlStqhEr2yzJE2lKcoIUkaMtEmCpZIXmSg08FpXjXSbUSWn\n1H1XfRXtChEeVsyzHhXHluRWAOkcuRhAsiRBeq5EdEOzvt3IAGlkboxfWo6L1QFC9YcJVSfU\nd9U7jbb5EtglHPMsU8FtxacknVcydW8ptQek4TJHCY0Mi2RsOrTNT2ZzBMIt36uDEuq70n0n\nsIRjnpMyh8BWQk5ahVEJkDySNBSNdWVIOmz4ro4SQbp2eA3/mQujCEySbmhYGZLMviujk9Hd\nxyuX0NZWYdQakHgjQ3GQmrfzmqSRsf7wEJukvBihabr4X2qpZeUor/CMosVAinLPXFapWgGS\naqsrSFIr2kJHbpCuUY6kScqPUWSXFoFV47+2vHZcuOCY57SkcCsFkjeSND7FnLuW9CqMpG+H\nV147VCYpVlkqJCCpFT+3jMwZRRFIuv9KJ4XD6eHk1lUCyWdzg9IygwQkjUamQTqUKmiOXDpu\ny+8tLiNpMAZJ91+5mr/11gDSIhUgqT0d3Sy4YYTXCIN0eM0bRlF7XhwlhJMGG1Hvuv8KJYXT\nS2zr3t4eITDS8fk9oRYQFUDyqRH4duhvaY+uXauOo+UkqZTkyBL1b9MXFJUCqRrfLjdJsXLV\nKEkmSNcERlYTeDm16Oc2pGMLpBYYpNaBlN8ktQqk6DK+gGsSo0M/DQ1M7fq9zWjPAKkNBql9\nIOUmqVUFy7gEjJE/klr1exuSZZGavhxQqXEn1ZiknCS1qGBZF3GNVY5UPamKk6wpSBEGqRUG\nqYUgLTZJ5iCW9hQs6yoMjPyZpPb83ia1hyxS09fCVA6kah7jIpKs0WCtKVfWZTxuYpTfJM16\nhHRjQ98CSCBtkdphkEqBVNWDLOvbeb6cwtdxaCvnAY1USynn8XT9y6U9ZZGavhKu4iCVf5aJ\nebEnp2xsFwRXjeWoSLEK/hFR95VMEVNC3gs4StdV6XmWU3scpJYYpOIglX+YyXmxH5z02egU\nlp9KjpncIjCEZSBmQ6tqipjiipXvslfCzZHq0advmn2WLuaAvEGPfZ59ri9HkbRITV+HUIMg\npeTFnuyz8ZLAjhoVOWapOPrkQIBUzRQxxVUhSOpNwxKYbRFz1i4vV7+EYrnR22KQCoPkodCk\n5cWedKHIdDp4VGSfRSuqZJPuKWIK/hwP8g6Sdu3Um2YTbkGHbMzn76uUBR4ufTlVQ5qyHGoQ\nJOX9O8ZwTXao5Tng8cGyyj2mNDHnxj3uq+lCVSFI6k2zT+/IAdkiB/MrwrPzceXLqmrTlOVU\nQZB8lJo0kKIfUGK2+FxVqu2KlidWUXKDdOvq1WK/pYis6V9BFYKEfmwP7gq1Tf3GXxwtUCvC\nvoUaBCk1L/Zkk8zAn8M5P2nFqRMvW3IA5dU6SXIlNvTNkQukTXLa6Uf9DvN1112tMskNgpSa\nFzt6mbC8xkbOzy4RGd7xnnKKmFu3rt66VezX5Fe9IOk3DfXtyIDeji2YmHW95e02+1GDIKXm\nxY4md5MuHPY2yvm5T1j5MUGSzd8MJL8k8XygqAdLZggVvqZKC0r/6pP+/OQsOX/b3wOONzaw\nM89g2i5pzddVXt9YPtQgSCl5seHzCfIaO+7JRZ3z05rtTnSy8CliGEhenTuZD1T3YMk1AiSV\nFpQnDH3tLP246O/xKpD0mwYmkozA78BXAgAAIABJREFURPVKH32p5dn2e1CDrXY5TiDWHYiA\nB4fIXdwi+SRJ5gPFPVh4djudFpS+Byho5NL8NZ/dOzqyQb1pon2RkHTNPbvqCl/R47UVJOfR\ne2Q/vierSn2OfJqD5NO5U/lAVQ+WObsdTvw5g4+rw3nz/VnroMpKX/EDsrIgpgaQPr+MRIEy\n06efB9RvEWFt1Iva59WDDLNel5HjRhHidGjEFDHflSD5I0nlA1U9WGaGUDNf4YSQ4aQF/Vnr\noIpAKnNIUdVgUwMon19EovDKLVTxrbC2KNus175+kjh+J6HJF6aI+bXv3pIg+XTuRD5Q1YNl\nZgjFIE2GEiSPpw9yK1Y6/JS/Uodkz104/srnF5EoHXgXb9JSNIh4O/U2nhdg8azX/n7TohNw\nUyQsktcGB5YPVPVgqTXItQNRkCYT+Agg1aHWgiQcf+Xzq0gUWmpg02x/u+dIHrto1uviynun\nrmKQvDl3Kh+o6sEyM4SqLq5JAKlWVQNSuWMK1044/spV0ZEoEevtjCc212MXKkh4mfNO3bpl\nguSJJJUPVPVgoQyhHeXp7g4DSPWqtSApx18SY0SibJLuzv7MDRI7hv8Q3Jx36qoFki/nTuYD\njWQPllrDBnCwVul7nxQMDQNI1amGNB0lDyoucEf5a0xGJApvpXO4dkoNg6T4UfJ9PYk9WHoy\ndj6ZtPcTBzHVkKbDB0jC8UdhbTgSBTpq9CSE9rwAoApAAq8RjXrNBFKFoXbOHiw1aaeaSzqA\nVI/aCpJw/NFU1jgSZUu5cbr525r12j9JNkiZvlUVSAk9WBGySOLfii5gjcVnO68hTYcPkGRV\nQE8FYESisLU4rM3YFeS9lsR+R2tASurBAk2GAaQqxWc7ryFNhw+Q8onEB7WVNUnbMrYCha8a\nIGU7TG2jKAxNhoqjAJJ3ERkXEFWdpqOcv5gLJBbWtsUCiCyVA0kGVRsDKpYGJNzk0NAFrLDs\nec+rS9NRI0iitjRzbCpFkgqqxkP8CiTKaQqkaBgsUlVy5SFYlKaDDQ/rceyghoWi51U1S40l\n0+7Qsxvk7JWCHOV07SCsbdPFUTmQVFC1MehcgTQaTRccQKgxi6SMUkMXsMJKAyn5O5vKsYEa\nlnZ0VC5FPZZMuUMPsoUrtYCUojIkmUHV6l7JVw7MJ5kJpYZA4vwwlJq5gFWWCx/dn5n0HTZ9\n85asYWlHR+VSxGPJwB06A9NpnszfgVRnhTzGVoBkBlUjkPhGmOI4E0oLQPLqUSNJfChKFRx9\nzeUCSfdnJn1nbCRK1I4OSrjDdqS26Qz55OMs9/Gd1C8q3g7oL6KlZMPdjpnlwwAJZmbNglIq\nSF7bSrECPVXKBdJpwvQCad8xi5SKcdvb++YZQu7ZP+YL3VnRItIKkFRQtZlPSIPESVqIUgpI\nxZtjFiqAVKWcUOj+zOzfcYME2cO/ew858xQYJTn8rNB1FvxeXCVAUkHVZj6hGEiLUEoGqUzD\n5iIFkJqRqz9TbOGOTU8WoQTXTs3lfPyvgCjI2rpTOOjYY7ByGZJwbMWmmSmIgaRISkWpEZAC\nR7UruT9TbmcDULdlEcKNDSqXIv3rEXLf8fEZ8srxc+QMLKjhZ0WuqeD3XDquqDY/NUiajpL3\nTCKpXF9bqgJH9SulP5MJGr3ZiDEBknZ0rFyK5LvHx7zV+xG5sF3wmjyCVFltfmqQVMQkBZBW\nS8n9mUyUsR5OlIg6ZI1cir0D8O4+fSc58wh4dmj4WX55A6nC2nzEG+0ESWk7JoAU48jfFQaO\nWqjFFR1VBvbY3DAeptD0BVKVtflopEzSgna72kEKXbBt1CKQcCmQHJWdIGaJQAKSFuxYP0ie\njhPkU+kgGeXgWNqjloBUYSUkUiBdHi3asW6QAketVCpIdkE49uLZLRVIkTJISacIIAUtUqwg\neDFInkCqzndiUrWjqXm22I41t9qtDUf+342NyVEU1gsktjC1z2XtWC9I68JRJc+0KbmKggfP\nbklAUo11U3QqNg4LVsrBWoS8AqO4VM5/Pb6r3JitJK0HSJU91UbkLqnlDdJygIQa66bqBJfM\n8elscpVfJpso578e37VVasxWgtaQo+UnqbKSWhQkc1rvikFynkmMw0KDtQj5XBShnP94fFeZ\nMVturUkXUgApmwoHu1af+tIpfYYNcvENdiIV0UvId9m/Mue/Ht/VKTVmy6215GjpSQogxc7z\nxgYhZ0/omdAYE9bY0JOjvvQwFBjL/tOFx2w5tR4cLTdIOzpuVapakKyqOaqko4r7GFfk7ZJa\nTW0+LuMOvH+WbLxjgATNdq6c/9H4+s8UH7Pl1HqAVFm5q0Xs0df0yhdlzaia6yVcce/hirwN\nUiW1eYesm3CFkDl27QAknfNfj+8ajMeDL3qdKGI9OFoFkCxVClKsai6XcMUd7BL+O8IgVVGb\ndwndgA3yzvx9eko9WEuCJHP+y/Fd48EHyJ8Pvl54zJZDa8JR8yDpdN9oyGef9KNZl/RPDe9J\nj5UQmer0277itOEghoJVNddLuOLOh3/ovyMMklGbL9G5BcfaSSnw6IHy5u9n53qwFgdJ5/wX\n47uoOfpiqTFbDgWQ6pHq2sBJCGj1ggy69GMTe096D5mpDoNUadpwkECBmOZFLtkVd+tvszYv\nM7BcfixjPkfX5eAEFS5hkjbIxrNwI+RgLQ6SzvnPxnd95vkx1e/eQT7wcOGrimmFOTIr6NyB\n3mgMJNW1gdPibEYDgGJg+lF4D5G4VxXSqtOGRwKk2HR8csmuuFt/4xwtOgPL6MWFwx3SLylH\n7K59J4wYITjQmGsAH2UuytAqdyFZFXS4xVnnqapAKFnJDKeqExN3Ye9J76ES9yKQqk0bHgmQ\nrKq5lYTl1LJSpyZIKuOlzMAyGt3ImBnVcTlEGGSdm9n0iRc0D9ogDaoBKX1zAwXOn9oFEm6R\njdBrHiESxZbMxL3uvbz/FFxH0qlX9JKuuPMLMP7ukIH4E00AHo2mLy4aEp58OQoklZvZ9IkX\nNA9aIBkceQMpnaOGilwhGUmb0N1HrzLgqIIqRUYVAslM3Ju8l98r5cfVVfMIL+GKO9xG/HdH\nbN7mLqyqzcOQhxczJUZ1XY78rTg3s+kTpzYPWiBJjhhIgwLX41QaSCluZ/tkphG0QeKvsmZB\ncrp2ke20Me9J7wHaMZjT+CxKG15Y7Ii6ai5eT3JJVdyleb8oK/J8Wu+tDoWHXZXOwALW6MXF\neUoSLkf+ap2b2fSJjebBeIk2x1EISyT+8QVSZo5aT5KZ2NZ64ctXWYF5qpKV9yAoD51xqbgZ\nQXhPeg/lHjlAWpQ2vLD0EfXBY6fJVThYdoUbmVIMOy5HP8p4+6D2f/mFDJ+LlWl7QBJnyCtI\nqY7dcoFkveZNkPCrzCdGuQ5k5aFTxhODJLwnu/l7W7hNJkiL0oYXVhaQ8pWOKTJJuY3SQpCU\n/0sPPaSyinV8ZB+lSNqlnNeSoBwGqe0kuaoOqIiabr0/jPIczMhDt2m0IEjXTnpPukNWukc7\ncZCiWXra8MLyDxJLsPDijUzJuuOXY7p26moQSLJ5kILEZ2/F33cNkR08LapKXlob8hiklQFp\nern8yaq5M8WQ8BnkIg+pl5JAylk6RqZJGuW7HPkoWW7mgWqCVx+oeXBKQYLJvYb4AA6Sxqqu\nlOtS3ErtQordqZaTZLl2ZgchfpVlnjMxRe0AaVHa8OIXsniXQiAVrCWpBkHhy45tkFDzYPRv\nJoIkVLidIMm6Ur5rcSqfQWo5SLh+PsD9GvxO61fZdDQqe66K7kxekBalDS9+IQv3yFs6BEjF\nWsB1gyDPzRzFXDuUoHm4NxFTt2qUHJUk8c8ggGTLqp9vq9cYqpazV9mZxbk5F6klIC1KG178\nQhbuUQwk6tt5cAfSxUAS84lLlGIgaXwq52jpQDLr59v6NcY9PfEqm36V3DnK6aLHtHS3Jq+8\ngyTrRpdflGvKpzpK0HCiTJJCKQ6SzzNO0l+Aq1laRmImkFIHSbw1VRWOulURSNQaTfktguTK\nfi41JgrSnjJJYkrxRkG6uaIc8fkLSh0lqRR5yCjXDiUUDDQmqABI3Km7Abdpz0fyvQRRhJBJ\nclskvxwJl/ymc+vNm8vW/J1FaG6qModJKkV7HlLKtUIJIOE3b77SoZsYbhz7mXkmUYCQNEkJ\ndaSCDQzQa7fP7oGRtOJeuC998rEnI7yF7c0q6tHpRUIu3l4ljsTcVFk6MkxrbQ3P5PcjFkde\nZfGoV0VAOjw8TD6genEdv/CCp0T/SWIg7Zm9sjZIhQ6s40jspBU8FP2uEd6Cok7Y0tlVAmmE\nLNICk2SC5OzVxyCxtXs+0m63QrxHG8ZB9emnmSRIjgmCG/D+xjl0B1JRArF50F7wM/NMopgp\nos7dc8n9SMVA2uaRkMRMUvHghOF0+tLHyCfxlgvkYzf53ttkC4bAX1kdjlR8SgaTVACkal+0\ntYqDJNJxWUmC5JgguAHnyEWzeKShJHy6Gy/UANJkbzhJBKlgDQnH2uskFd+LWGjXSzd3yT+4\nqbbcvPkP1N4sGGBOzq8KRqoJVs7fa2wUGdrwCEw7X5veCElHzmOQGD571RaQOsVB6sDLddNO\nEqTGBNEbcCnuriSZpWdk1ei4DpCGe9MoCaSiXbAoxrFnxM5GAM7Nm4S8pLbcNOLUuFYEI9Un\nKEEaGRu5s4tHYEZJr2Lh/57HAzIoSbKcrIJJYoVgixxEO8y/M5IE4UD6E5e34kbp2nVJ0o29\nqkGCytEUB8CZIBU8sEYjnm1SggRbtnftgM+KYvQb0giELZJhkniGNjwCM5avTW/cciQd2fM1\n7WQbxB76Kf29/fj71xjKkOCtxFk6PLwW7Rkmqaprl4MoEk1SUZC0a8f9E4zL7k3m2t0EpPiW\nrunarZpY77ogaoQ38Ig1/LaFpYRXsSvpyN6er5mQWyD+6Psd9mtjSYJMv8YtG6VrQJJRS6rq\n2iU+06nbJBXuQ9LDKFWSiokE6WM3Rx8jF27+iU5foffWcZ4rJmaJ4haJfxqFJOVVzP5Gr2NG\nkESpxh9TjTghA7IFNtl6/1pjghJloHTIJOuRlYKkhE2SBql4kKpu0FZJKjhILxHym9D8/cxL\nL/0zVUb03jrOc7Xkbvd2gbTgVWyUI9HSYLj/y9tKw38ZhYcnRTCSBFljgtKkUbomSWJG6YUb\ntbxtEEkIpOLHm4lhlCxJxbl3COExDcyh+03yi0++dPPmSyoPpdobhayvltJAMt+2ia/ieNIR\n1dKwp6Jflrn/TfyyLvNHrCRB1pigdEmUOEjXYJGRVIv/6xskJmInGIV2hpsvvfTSTS5rb/+D\nLtuhxJJNREMVftsmvoq3eUZUVI72EEksUGhu3e7lkvhl24RlNNg0kwSZY4IWidmhQyFGEjVK\nL+zVUpHUJCmQSnAkhlFetB7tSxgjDVJlgy7boJSSzQuF+bZNfBWzpT4qR8dYgNJ8vtQkeW1n\nAoAkSdxAAUk+z5CoqU+QRHE4MZ/sSzcRRZQpa+8KBos1rtSiLagw37ZJr2KYVqKPX8h7xyZK\nzweQsA6vWSQd/+leLTVIZZIkSKUcOxhGefHEerR/8ic3TeG9qxh02bgqLNvHtua2fJ6tBnkG\nCdq+r6FqUlRbDVKS5AUkkOPJGlUkbZJWVnUW7QASlqgfcZQYSfXdm6kBkn+O1OVrnMqeo+Wq\ns2wn3+6GlfVSqgBJsVTrO02YpOpB4gogVXuudoCU/WL8gqQrSBylWp2DKQKpfJ9oS59sjar1\nDrTydue5HN+tdljXHq/35gBJ4iwBpPJae5ByXY9XkK4ZGF2rH6TE8ywKGIyLH6fBObYaV/0g\nNTjHZuI1NQGS5OeabP2u+TWTcqL8ICWMjV4j1fv02vfayvfrvYOUeil11leNbQXGCK0ASMmv\njyz3I4DUFEiLL6UJkGY90aXOh5p1SHcning6oJ41HYjcyAdMX5p7nWOrAZUDqYZWO5yjaeOc\nHFzcjtuds/CuDkgJp9JBXjoWjE+oSXjaa3uCqh01YPrSKoCUdwtS5Q/PzNF0cWVB2kkPaNab\nkzJis7PXVYNM+NlbKiMQ/38WHfDs1iwaecucVFFshAHTu0/DUzXHRi+R3HYYIt6EBaC/m2fl\nMzL39XBOv8qz9OGB6VtRy15bHkFa8NpSm80ZirQmrBWtJsc36Xebw8ZhClpx8WMxNZCeJEht\njHaf/53+RwjZnZtjo5dHCXaYW182LLwvbIGdua/eLH16YDqfjE+c6WNXKzhXZvGuyPpBkmm3\nTbGVLQAJpyaRU9DGVpsbdx/+iB4MsIwYJdphGOwhZt6mBnlbWl9tFXBOvxqy9JkD0yVI0dWr\nn/1s9SglFO+dztVbKkmJF5DkTzSzl1mZywiZ/Db57cmsS/qwVew2mdBnB15EfZPLZwNJTUHr\nAoltvOPTD+/+FvmZf/47zxdoMm+NEuxwl5zy7dICwLJpFbo1ZumL52ji6xlIlaOU8GwJuXXr\nFmzLxVEWkMzsZVbmMkLuo/8+3KUfMLKN7Xb3BEZmd3h93QBpQX7WMkoCycoIFIkpaAlf3cOu\nHdiiX6cO3S79/+Hdl5YZpFQ7bGyPWwX9Ta7q3oDWwHQEEsXoatUopYEE3p03kPiZ7OxlVuYy\nQu6fPAP7DLg38OBk8iBvFaO+ww7pGK6d7K0t+MtBtCrMy7wtfoa4H6nHOPN3s5iClnAPZhs3\nNvwn5Ku7T5M7AKRP7770kdUBybLDxna3VcAgVXmVxsB0AyQgqVqU2NnQVAh95WhxixSdnCcb\nlzJylAUkM3uZlbmMkO+BH/cD/ufdZCJ2076DKtsQQnTNiA0voE7io42BxCeNdVW7t+GPjxM2\nGjrW/N3f3f09Yr6ll08Jdhi5dvLTtgp1Zunbsu4zEYkvrgqTVC1KzFarphbZDiNBuhWdbsDy\neX8g8UVl5s/hHz+kdSQAachqSxMSuzO6BhlZQ9EZToV+vVsxkCLIyDUeqzHO7KtyClpCbnxc\ndMOi+R/vIHdQjnZ3f4GQj3x1mUFKsMOQjGRsPx7TKtSapU8NTOfn3kEgSZKqQ4m/LKR/hdph\nWB3p1q3PkYvzdzL3f+QG6SI5e+UN+a4DdDhIk4npDdi+BdOhSZIaRJvnx7Ojq7I/1hTYWdrF\nNxJmMyfEuX6X6WH+T+6ra48S7PBMVnX147GtQhuy9HGAJElXP1vNWcymFmSsOUhXP0xOPY1H\nQiB1iVELuc1v/ASBFJnegBMkFh5+rQRHAiTtjX3rA3IpnqVdywETAymBJMHRMoMUue1wNO7x\n9w6qk1hWIZo1n6Xvai0mydXUEimQrvJ6kpcRsgikLehTeI2cA5DeYdnQFUjDIfPvItMbcIN0\niG1SAY5kuZDtA+Mvko9HMkDh47Es7Ug2NhwkJ0mSo6UGqaQaztL3WUxSVSdxNbVE0S3l2kE9\nKcfRUs8kZ4qXZv596KHTDJ+ZyDrSZBiZ3gAGST+UQ4Ok3D9dHFG3WA/uJs+Ltuu7HVnaLSFy\nxg6QxBcfFiA9XOTyll+tyNL3WeXcVdzYoJtapGvHGLoKHx8m38tBUhpIOxqkaMZy90JRE0l8\n59FD5CeHQ+zfRbGUkvC5g99u1xBJ+X62vF5cb4M29zHPWT6W61gz+43E7wt6BmOugdqAXMKH\n1xmkVmTpU012VTd/46kQeDsMMHT1Km9s+NytVzK3NmVulZrbek5OJy6U6Siqwa5oZ5IB0pgb\nFlhS6yb03xSQQPQrT49NkoxfJkgqdoFLrzZk6ZMgVdTMwGU2tYh2GPDofuIqM0vfvUu0zGQ7\nWsb9YhzN5yZICYGrtlQFqQxI0rUbjO8mN8bjG+Ru3f8xJJPoMEonKRoPqBBJ1i/jJBW7wCAP\nkrWjyi2SbmoR7TC3bv0p+QleR7r1yi8T8mvfzXq0jPs5QIK41OFwWAika9RsZDyzdb24sWEA\njQ3j8d+HxgbZcwLVtcUgMYQ4TIP4rwPvbk09u3ZIBQjB/1nbzcpIneMq9etuccFC9iOUAYlL\n4ZTpOKjBrnhjg2j+fms8fos1f99xqntOoLp2KH27JAdyoDw7kCuq6uEAUoP6rGysu3rVLm5V\nCJ3jKuOIfeQ7RnmQuLKCxLuS+GIRkkQvGuuGBRxufIaQz9wAqyJ6TshEmKSUmtgYazB4Ov2n\nBdUuNYqijqdinOPq1XyGSMkJkqOpgp3Fx2DXa6jBrlwwuOBgjNqxIcAC/Mxrh5vXUrqqxiZJ\ni14SQXVLVo3qeCrWOYpABMoKkrcxekbDdymSMEecJGCITF599Y+pLdpOAWmgIaKLrUxOGARq\nAKSih6kdpMhorytD0oBzgBrfhhQi8uSrVAKk1CoSgwgUQGqp6ngsvs6BkCEqQxUDCSXF8DrY\n9TDlrzwaY44YScMnKUQEOPp6KkgYIlAAqaVaWpBkhipzpIZ7sKuXXxElN6wlSJ/b4mgwpn7d\nqwKkV588BJKcnl087psds2XpcoPqecF5O4cBksxQZY7UcA529fMzmHKQhE8vu1T5vxFraZhI\nkP6YmyTXMRJaUtqV5TMoWmaQZIYqc6SGc7CrT2Ulyfi544FGiIn3DAuQhElyHSWAtCxaXpDk\np2ukhjXY1auykWT9Xss/k6FK9JJf/RXyjx6gIMmMh3rsn5E1kX9C/e/36kt2FJRdqwGSKylG\nZQOvM5GU/nuHGqTfoP//+DcPD3HGw86pPWw0QgM/zgeQWiNdyKoGiZijVT2CJDNUmSM1agAp\nC0npN3UoRYH42W+++o/IPwaQoNFRZwkysybK8N/N6KtmcuLAUaNChaxig8TOFAOp6MHwcWWG\nKnOkRh0gZSAp412lIO0++epz5KcOrxkZD7vx1DpiPNeu+J447PHzx95+VVApVQySPod3kAgf\nzupKimEPdvWtRSRltfPskq9RawQg8RXy0720K78njnm8t7cXUKpPuPsS6rRqgCit10IRf3/j\nnBeOYhnsxJncOXPy/wz8i2hlfFN1yFpJMWKDXX1rAUm5QIooRODa8RXyM3kpQgvHlKTjgFJt\nwt2XUKfVNdfOKYB0jlz0AVI8g50+U0LOnHw/A/+iMhdaXuldszlAYg7cL18TICW6dmzpZ8yU\niRGARDE6DijVJdx9Ke2EqtfO2SxVPgySM4MdO1NazpwcPwP/olJX6kFpKOUAiVX1/s/HmcHG\njQ06a2KH3lVWAdy1UiZGHCQgKaBUj3D3pXSH9MuPkBNf9SNHBjtxpvScORl/BlpsHKSkS4Ap\nzfKABG7BXFYhXc3frAK4DfUjlDJRuK3HiqSAUh1a6Hr7wciZwU6fqfQ52gZScjBCRo54Ve/i\niQJpfqI7ZGXWRMiYuM0bGmTKxB0M0jEHqY0oJfz0aZ6dW6WMddiyimews7vmy6l5eLDoD3KR\nlBOkzGNMnPlNjpFJgqVCP6QqJf6k0SiOkp/KRdUyuy/jrp2300RWBjt8pmUDyW7qzBC+o6Y0\ni57dIGevLKIjD0juPEHHBkmtMkkpP2o0nVooZXqVtEBm96XV2OATJDuDHTu2rjeXPb6Ha8xx\nNqupM0v4Tl+AxDu2riwoG0R51QvLUVK+rT3s3Pn41b6U9qMoSCZKGY1y8zK7L/GTlyN6vCiW\nwQ6dqb+EIJlNne7wncNIvpdQOyVrv3mHbCwoGdlBSsxbt6dMUu3mKP18C0GiKGXauVWyui+N\nDlmfFXc7g532evrLV0eymzoT+ngOpf+K+3hgIlRVLq4m5ahw1qZc5Sg5/+Oecu5K/trc2kut\nkKX+KAGSMkrZjHIb1II2Lh+qvY4UxVtL4u00PCrBjDrgE6HyQpGcMikrSCl5VBVIRX9lQVED\nWB4kiVIAqWa1EySr6VMsiIlQI57Gz22UMoKUlo9Y1o4qrCC5rmlRE2H6r9IgMZSyvEtaogBS\nkbNZTZ3p4TvdWPjOjlgCjNy5MLOBlJrXWwUIVUWS86r2/IFEUQog1a3aGxuMps608J1Da8ZT\nNRFqpEBSRkk/jEwgpefH31ONdZWA5Lwu1QOc8XtcCJ3LI0NLBNKKqHaQjKbOtPCd6NAM31ET\noUYA0i2R6lwe1/g9pTiKdCtDFSbJeWXHSu4vwZZVtUgrotpdO6OpE3fI2uE7UXRohu+oiVA5\nSJwku6aUAaRF87WgwlyWJMf3XVd2nACSsRZ/y0yeAaGII0KWtI60ImqiscG9QYU8wEguThib\nKkYOw4pOYRWrNW3/BPnwnwJIm3fRhUg2TcCe7ASzc+TsG0ljTHLNe1QapD2LDVf53rNBcmMV\nA0lugF+vQVq2VrsVUWtAEiEPYiTX7Q3m8+2jYViRdPSEk/dHMDkhXxAgdYyRW15AKkmSjJHQ\na+IF/FiH9e2JwCT3wdJBWtp+pBVRa0BibQ2X5mIk1yVCrVKPbB0eqvCGbR4AsQM7f/fWt8hd\nMEEhXxAg8TyWrOHCHKyFpx3LORFfSefOjtibv3OekA02Vu19Mcb5mBAgCD6P/+KT0ujirv3t\njgg2/C/ovyquXXUTsMAXbpHe/G31rZPz4jyBo1rUGpBYyMNZKB9QUs7CJ2sX/7BsA+/ygtMH\n0/Tpb7Dq0V2wALUk4dpFKKIXD9ZCIOWe0NILSCpO4g1uK2kJZzb3Er1IihDswD7PSKOLg824\nAd6R0WIbtxNBeuWM/taGOE8AqR61pBFflgrptbBPu1dWRh3u30XIh79LSfoGLOg0sBFeGmL3\nR5FUYGLYUiTh6g+wdJa8Rm0RXBrYXGY2jzVIj5BPC6OLw5/hDQHtloRNJ/8fcLONQJJ1pNEU\nf6t3e35lYWRikDe1CaS5BdJcxLAeil0kSNGtVz5M7voWtUVXX+HBDnGQIMGdPrwEqcgEy6Wc\nu2NDe8/P5ydvPMu8TmZzASl6uXsCpHsI9MiC0cUDciDIkHewkav0+9xs2793pEyxDmWcexhB\nHZRRrQGJeWPnJEKsmJ3wkIdTPtivqy/1Fsw9TW6xeUZ3ZFESIeK8PA0nLzpAKjZReU6QDPcV\ntyNAU8L8nGwHUS8M+AKtRAHt8pohAAAgAElEQVRI+l2BKdnvCENMWLChtEYmSFN3nFXAqC61\nBqReRB2dZ2UBA8eHFrotNAwLFqIBOC8d8q1br5CfuBXdJYMdTJC2yEcnk48aBZqRVIwjTlL2\nN7sFkiBINDlskrNX3jjBIIkvpIDEggwJs7tgf40XB/7lSaGMQXWoJbeahzxsKKeON39vnMph\nWB9WjdpjFOOgFkyQTn9SOYFS5UDSUQWZfor8Fuh55NhFwkbcVq7dCQ4uPN67h0g/0hprPZOW\ndkcPSdMxiQoke4R2AKk+teRWxzOWXISWXtjEwxsOeYtwj0V/f+4nRIzD50SwgwHSZPi9e8mH\nnjFBulGco0yDtnGP8vGD5MyDQAQk96RLVI+cIffssI3/OyH/NfzGZ8m52+Doodxg0YOEfo0Z\nXd1s0CF3kL0eNDbQF0lvTH5YDsDWX1Mg2SO0A0j1qSW3Gh55rA/RKLU4KYoKC4oFgBM5v8tw\nQs5M0IYbnjhKTjkOPcpn/gL8s77oGBbJPSlJD4oWbDXgmR4HbO45I7gQGV3d/C2/sS2X5ABs\n/TUivVt7hHYAqT5VdKuNhuuM+6eD5M4eGQeJzezy8nD4ILnfAKkwR1lAAnzu+wvV8nwabUPZ\nhuSex9/llZ9ZdMD7iik9/zcD6eQ8OcdcOx1ciIyuDkKkW/8291O3forgAdjqazsSJHuEdgCp\nPrUIpIVhLRlIImCN+PuffA+DtHsjKqj0q5Ixca58oZDc85H7AKQ7yeY+273Lm/nPyyOFor4q\nqhCk3PvHiuyXLP3ed2JfdIE0eeJuQu7/3mSo1+9GvkGywkqdDWY9TvTxMR8mH+nOMHmcANKq\nyP+DnBkJ6rY7pMtr2bIyjrwWuVEGdtuzePz6l75j6Etxm2TWkiZE1pDYp1oPfl1BkhwOpyuw\n1AUSS+75TQpSpIbJo15l9LWg5Zf3B2kmqJNxYpHOaGfXo4EkEdhtz+JB0TFRcnh3GKTh0ABp\nIn07Vj/yB5JrN1e+ULZ0TbKywxuo7a8Vu6qgtsn7gzTnl1S1bJ3RDrfRqiq4COy2Z/H4koHS\nlyJHPcn07chwGAeJtzPcKEZSZpDi+UJZcs/7eFO16DnWvcpBqyXvIJlZTDqylq0r47rXsGNU\nwSM+95MxiwfDR5MEq5wkEaJ9pgnMJDtBvp1sr6saJGLnC9XJPVXPsW7gDloteQfJ9GxQLRuv\njm1EoTFGWf0SRomvskm6dQuDpKRAUu3ebpDS2hfp+iPOzsJpr535QnVyTzVMXjdwB9WpxAfn\nSxWDhGrZ5mprIwLJFGcIUPqSXBUjKXKQJLw7I55BkmQ4eekgHWWdrTdUdtqs9GfnRRW7dqAd\nWVnilXHt2sEvu2JWwWPlUVaPKEpqndU16wQJIhwoS0Y8A+fnxmMxkFw6omILAaRl10K/3Ie8\nP3+doM6oZevKuGxsgCCZd+bvkw1cBY+XR1lD+vXvoE6khSTxDaZBYiABRm6LNNbN9gCRjgvN\nNO11AKm1ylDD9aBamr+3cWWc17dhwPQltvFZOTslVMHj5VG3NHwHoWSQFAdJbTIDgx7jGDlB\nYtewBRCZXmjGaa8DSK3VkoKkE9QZtWxdGWf1bRboPb+0QTaehQVVBXeUR9TS8J0E9y5Gktxg\ncHTjMYGREyTWbH8v1IpMkLxNex3UjDI1upZXXS9Si5AFv01UT7i+9B3d0uA2SjZIcr3h1wFF\nnKTH7Avj9bTR0RGa31yv9zTtdVAzWmmQUn/c0dGuARJq+o4wSokkybW4wU4glASS7dDpJflX\nwGg5FStqFT3GtoHEKDoyQKIm6UvoL02VJskJkuCIHkr7dI+5QDqK4xMHqegPXzO1zm6vNEiJ\nP05QZIGEDRL/Wyy4SRKrJEcsYDURpCNZK3LNK2OuD1qoit2nIlo1kAy5f9zRrsLIBCmKjZ6I\nRTkgkIxIVdkdJJvrHsNtDWybBCY+r4y9PmiBqi+tBbRuIBkUHS0ezipQko13tzRJRqSqhhKT\nFKH+VmWDoJm7p5rst43mbx/TXq+86iiuKZr1IMuS8ZzgL34xC0O8Sqs1IBnKMC7cMkoKpDhH\n4mAIJGzxtDMH46Vkk/22sd7LtNcrr4ZB6lhdiJF4fjGQqjm9/wKy01m4iwOkXaYcIGmjxP8S\nJEUcJMSROhgH6QvPP/988jEDMPklXl31eFDJYo/O8fyWFqQsZTF+03kzw67gKWOmEjyw4pY4\nKnusmCNtfm4ARI/dSBuYFEDKLTkQuWGQuDlytL9mC/Eqf37/RywEEi38yLPbjbU3JIihxEi6\nhY4lG+ywfWNHZJ2yjyUeLYCUX3L8pMPLqPU6kkBKCPGaej+/tyOJBAzcTyVk3OnhSfYgVyKb\neI9A8ob+/OQsOX/b/HG4tQH+drXfxSRJcjxB7CjK4wSQfGsohn01DZJ27TKEeKn52Dye3teB\nZAIGCVKPbKJJ9kSuRDa+HPInvnaWfly0brkFkrky8cSA0qHjEWqOqIFTe1OO0kAKyik57Ku1\nIJkhXoyfKUxv6P303g6kszOwv8D66En2IFdiJCLZNqMBpGZ4LR4I6u6PFduScaIoxR/hroRo\n1/raY59u4CmvqvSQ/raCZIZ4TQVGLQYJZWeIOFY4FwPkStwWnZwz+Dh1z96zu8D+uDd/J/4M\ndxVEdiNgQ895JfXEmaUBie80HcnJdr2f3teBzOwM8vJV235PLunNzkDQ3Syt3zGcYs/QaEzH\nuzb4pFdPE0JUuqZJwxxZICWEeE0lR+0FyczOYIPEciXObJBcR8ncjYR4crwNMUUIpGaf9dLL\numlDgvIItgak5BAvilH7LRJoxyTFzsVwmgUkqCjlS3h/dORyK45w0JE6YACpuGYX1Zzq8Cch\nQxZJMplc/SfOPLk1S5WppBAvbo1aD1IHz54nIMG5GA7syXySm5p3884c4QIJpGDaTdox/+9c\nW4m53/ic6hE8vgmsGA6HYi52O09uzdJlyhniJQmSJsn76X0dCGVnkDTFJtnLCFKUqS8WKQkk\ndqwj1G4XQCosORupmFOdgTQBjiaPkAdhBpB4ntw2SdWNhF3yfgJ/rp3MzqBn68HpEFWuxCwg\n5dBOJ3K459ZzPMKZtQJJhSTn6jyrQRryOtLdrKLkyJPbKimfjpmkkffjL3dP/oS1G2W2NAGk\nwkLTsPMlCtGQt9oR7G20+KYq524tQJos3kXuyZpduVkLIFWtGEjPcdfOBqnVGimTNPJ+7Jb9\n9OHQ+HMf4oyiAwJdvX36ySP2Ri+88MLv/Gfk5/54NIIHOBqN3oYGJR26Nx+5jx5AKqr53HLt\nYEJ2VkeSrh08uLaDpBvuRt4P3a6fPpyYIEUspSRr/IOnJGc3Hk0fYgtfncLndHSZNWqcRXiM\nRvz75uCoAFJRzeeosWGDvMbiQNkzgXaG3x9OniH3egSpukfDKBqtOkhDNDkY1yY0+XUApzHZ\npO++Z1jE3pQC9Ob0FXIGFuhteRQSIF8iVzAdI/Z969EGjgqK3ird/M0y5D7LQeqottldbyBV\n+3SApBUHSUUSa+2TberZbZGXJ0+Qy5GK2BudIQ98izm8FKTpqEuiqZ7i+BOf+MRTdNcRWKUA\nkh/BvTq5iDLkPsu6ZVkLbZSWJ7fYqSp9PtQiSYfFoxoDKX6f7IlfmUgvepD8gPp2fSNi74kz\nhNzz5rfIb1Pz9Iqs7ZJ3zhPy7/z73U889dSHfhwGR41EoJ8eFvXsBjl7JXCUqFmPD3uxVZ9T\nXMdZppdH3r3HhkCK36iJMcueXDm5n/yg04/6HRZDriP2ptPhPeQMde4oSH9ATP3InR/8VWNw\nlB4WxfuFr1RdGJZXHXHHYqrNlteMq7cjNgKS41ZNtCK9hvl2ZBANqHc3wBF74On+MSEPQFvD\nGfJDZLJN/smwS/7ZMPoZikyXkH/51BfJv/cU/cYID4uCHsN3yEbgKEmJzllDBqma81RxgiZA\nctyqiQES5onAACYKDznFEXsd8vXR8+TMt+j6r8NkLA8+QX6H3Bs98dj23yTkR7t/nfzwHz1F\n9QmoT6FhUTBoKpijSOUFMMbujDs94TirvAAQqMYXTq0OhqourA6QKjlDO0DSFLGJlPHOm8wn\n67KJwO3ZjR+F5u//iLxN/2ftRqIK9aN3/v2/Tj//JSWJkKd4TYl/jQ2a+t7aY6TyAhgg9cgm\nv006LwBvkIOBmbEOhmoU46iKM60KSPFbpRgaDmOtDfti0PoA/lARe9OtDjnz6HRKfbu/8al/\n89t33k/IvS/fT/7uQ/s/R8gH7+x27/xR8td+noH0CTy+EAZNnXly8vLLL9f+s9skMy+AAEl0\n1uG8AFtkMzrgo3riHQxVqA6QqjlDG0ASDLlaG9ziQfDQS/0t8ij5o8kz5EHyDPSzvziM/hsO\nUveD9B16J60sPfUUuHYj9d3JE4Rcf/fld9+t6uctg8y8AJFKAaCCjUVegC455V9g3rHqYKju\nwhaB5GMAxKqA5LhXkiGztSFJ8laKfiTyvckP6OcPAKQvD09pHemD3b9Gfv6Dd5IfglaHp3hk\nxOhRcA475OXJLjlzgYK01ibJzAsQy21g5gXg67mqxSgNJBYkN/IAUkVGrxUgTUyS0r+v7yTc\n1k+Su1kk/0fp5++Lp93t/gj796cBJN31/rysG/zh02CR1tokGXkBbJCsvAB8vfaOqxSKilWl\nXCPkZSTRKoMUQTeSYinVtzNeSKPpC4/DqLLJI+Rh+CatKX307wFI3R/5IfJD/yn99wO4630U\nTR48Q8780deuXweQ1psklBdgZoGkexlM164OxUC6rIfk+RnauuIgRQldspbM2zjd29vT2Teo\nXoyGd1+4QAHqQjXpx+68YH579MILdNfr168/DSCtsXOn8gKYiUIUSLKXAZzisVzgSQMqVgyk\nEbJG2iCVKP9tAqnU2JOUHyKBSPqq/ToaDvcmySD96IWnrO/TvV6YPC1BWmOTpPICmIlCZM4D\n5cfNZEyIThrgSe4BMhFP0mZk6h5NDZTgyw4CEooji/43t60MSOmtJowJ9/ccVn0qPEJpyzhI\nFz5IQbrzg1H0lEkS2+uFCxSk6197d71NkswLYCUKEZ+qlyEaU8O0Ca0SOmmAJzkHyGw5QBKD\n8XT2H2fZSSiOrpwGlXBUHKTiWvRDEkBycQSrgCUHSCz00gCJ7/T0Zx95RIC0xiapeRkDZIyU\n1hgk2HOKUBrl7E51ldR2gDTrifnr2CWiSBOY747tsCneYWqjDr4Wc1QUCcF2VjLluuFzFkh3\nfvCpC6x+hEgSsIFBeuT6hXcDSc1KDpA5iHbI/qxPfuoz0HXFSg+kvKf/naclbdYl/dPRlJDp\np8inRi/9HP3LHPR+0leTnKCAJukookZ8VS7pd86TjUueOcoLkk63pwN1WKQJRJd0TqUzDUtq\now6+5nNUFAnBdrbVqJUTWbv6MwbS3R/8BF3JQVIkCY6uQxXp+iNfu/7umjt3jYv0aEk4ZQNk\nRA0MCo74mLM5jcigS2DShREhn4K63D2ETWGCQdpQHiEKaFKOogZJl0vxHd+Jw3KCtEV/vm7l\nQZEmLC/sFt+BL6mNOPiavzzyhmC72zz1SuYLAkt/FkX/1d0XhB0ySJKBE19jIF1/4JFvBJPU\nrDYpP2KAzBa5h/w8LS+ETYcN3cGRmLRkCz4iapEemG4T8tB0oD0/vnTuts7/pgKasKMYyW09\nVS57t+dXvA8ByAmSTknOY7BVpMkYVnfVDl20UQdf8zCUvCHYCV0HUwsk+PfFKPottZa3fWub\nBJFI15/mIH3t6Xe/EUxSo0IDZLpEdl0BTDMOkpi0RLyx34QglldwFUq4drQIyeKoer3w3CeR\n3CbLJTuycyqUUsoJktkTnhppgjaaESd8Q3aMErrg4hxFEQUJ9UIJkvCXvvY0J+mhCy+//OUv\nr3vsarMiaoAMlA7edcUmrxT/IAwgTceUjS2zQZojkHTLghnjZJZLueQVo5IgpUea6I126JbY\nkEWJPdlofTpImKR336V1o+tglljTYAVD94MySw+QIWRLFZIEkEYA0jQjSI65T9wl1KNKuXag\nHVlZoqt72ISqjdacFHpDBiUGhGCOkkCKOXeRgu66+HeU6SqCqpAeIEN9MtF1hVy7yMQAmu4i\nBNJJHCTl2ukYJ6drp3bxqZzH07PN8DqSmoGCtUFs40qd2ojnpIBjqA0LlRxYJbYw/xB1OzlB\nwiZJQqcaGYJRal6sgW0smwR0K5wB0lSDBK1ufH5lEyQV0OSY+wQ3NkRR8yC5mr+3ebs2C7SO\nNX9v4/ASfvVqwwKlxScmRIoIkN6Wf8dIktCh1rqAUtMSrd5ds5E6shwzDZLMq6fT+fP/VUAT\nnvukE2/+jqLmQZKzzYgrkZEm1B73RDes7pBVYSh23jO1ActufEiN851G7kgRAdILLwiUZNDq\nU/YZjGbvgFLTMiKR9AhDs4ajQAKSnp3HQdKHUTFOemoU1CEbRS0AKeEoZQ8TMy6p4fIxjuT3\nKEhA0gtvv22SRKtJ5p5W/1FAqXoRHf1ihboIEMRWurQlM65YITEsYOHS3ArGa4daAVIMifRR\nJ9MsIAmjdMF9hlhH7KjUDwhaLB39Yoe6cJA2levVF9EK9n4iYOFSAClBMSYWDN5ycCRuKAJJ\nGKUL7jPEIxqCUapYOvolHuqCt7KlbVdIjAxYsKNaW6EWgrRoEOTU8R0nSGCUMoMUUKpYOPqF\n/a1CXThIYxx5EOl+E72fCljwH5dQXr7rXAXkZiJRbo74t0yQmFG64DyDO8YuoFShcJeo2UOf\nvGT15Pf03y3DaOVBokbpQnaQaq8qte21WqXKg+RIytIeNX9FCUwkaZr2pRhIVBecOyeSNPL5\n29KV8c2xIsLRL3qd/NRb9TrXfihgoV1q/orygTRN/BJA82X6/5Nvv2DoX9ybB6T6UMr86lgR\n4egXM9RFNDaIrXpdfD8jYKFdav6K3CAZt0r/MTVAMvOfRcIiDd82lROkmvy77O+OFZEd/aJD\nXQRIYqte5w6JCSAlaCFIUwyS8S0MElsLIEUmSC+8fSEvSLUYpTUEyYh+QaEuwrXrxSIP7JAY\nFbCw7iA570GCcdEajRQ+U/NbKSA9SUXI2y/A6VxnWDA0tnKUXC+P1VZ64W8hGvnUDEgsIESk\ntpA5AcWIx/Nkw0pmwQPoUYRJcqTIi5CL/3/5DJUAiR/HQd3CMeajyu4CUwApz9YlUO0giQUI\nAxGpLQyQHMksRmxspI4hSYgUeZTq1wGkR5/k+jV1uiIgUaM0quo+1Dkna2sUQMp1OGxq8CzI\nMyONFyDxuwDMvyI8aYwC6dztuZ3MgmVjGlH3+G0eQ5IQKbL9Y+RDvwIgfeEXCfnFL3/+yaE6\n3ewcOW+Zr0xZT0Z+bw5SACnX1iWQd5CQqUFRh+Y4plPR/HIqjAt27WIjHtloffh/qIbeuiJF\neJPOQ8Ph1R+DhR+/+qg6Djv5+QIgVUfSGoK04vIOEsqihKIOzTRetNCDqSERSx8zxiDh8SX8\nLaVAGkVilTNShJDZ8Enyk8Ph75Of/fyTHyW/P4z06XpzPqJSF9mMebiq8u8CSKsm7yDhLEo6\n6tDM9dCVLQ7wIY0LBymKEkGajnhDuDtSBJJ8PfoF6tl9iHx5OHyRfGiILNvsQnRiBjpmT2g3\n8nRjjD/ZlVzZCCCtjPzXkdBHUlAVUXsg4xIHyXLt3pxO31Td3LFIEZbk62MUJEIeZZ8mkBci\nM9AxR2ZIL1bJrgPAtaQ0+Qctm5oFCRriwLgMItduIpnFVDQ23Dd9+z4eQ+KOFBl3yd98Mg0k\n2En2ROVLsToqd1eiGEiTANKKqVKQdNRhgmvH8DlN4o0ns/g5Vj+i/99H/zhD3bvkSJEdQsC1\n+wK4dl1s2ejJHygDUnmSiB5AzbMHyGph4Gg1VClIOurQTOO1xZsYOEhgXDrusHqWzOIlCdKb\n95EH3oSKkjNSRCT5enT4++TvDYcflX1RvM1DnrwwSKX9Oz2A+vQMLHRuB5BWSpWCpKMOzeZv\nZ96kpEOyaXF4PQkWknaTSb4evfqThOjES+oy+rLpgu9eIHv+aOEKWyjjnhpAPXlQZFhrZeaB\noKKqFCQ0z5uZxiueNykVpBFvcBglYxTxJF//FIK/X/wIIR/RQ5jxySNlkopMQzGy/lxkpPAk\nnnIA9WSCc34GjFZGnkHyL26PRObnReLDKKCxwbGRp28oAZKFzuOjx9N3H6J5pRnGE9t9DRit\njJYAJD7nYbLJQmLR348+OnzUtZHP4adAKjbR/EgvjRaYJGNeaXr59C9HPTBoNdTeZyne1mCQ\nRlkLPQMJSHJu1SZpOv1G5mNaGsmFxylHqSYJZjZTFwJOHWpDROncg1ZCbX2Wqhq+oGZk6kX9\nXddmRtKImbhBakrkNAk79PhogUniU21Kk6TtkJ3OPWgl1M5nWTQI7cUoNaXIBekoAkij4pc3\nEo5dKkl8qk1ukrhTh5syeatilik5gpZCrQSpcDjni2kIUog+OZVtF6VAoiQJg5Ts3E2keOOd\nBkmnc98JIK2OVgyk5G8yS3Q/AqmgZ8f1+OOPp5skxdEQtYEHra7aCNLcVuZvpoAUMY/ufl8g\nUVuUapKGkiNnS3zQymm1QEr9pgIJSBqMylwhg+hxs73BOJ/CCDeBB62wWghSjIbsJKV/EWyR\nNEmlQJJenUDJODPfY6gxmgSTtA5aKZAWfnM0vf9+AVIZz07Vj0aiM8k+pXDqVHtD0MprvUAC\nksqDNEJirQ6xcw4nmqJgktZCawZSNBK+3TdKXODjo5HJkn1OA6NgktZCtYCUEli2o9M9S1UF\n0l+CImGSRoWiVplGtmInfc7iaG1MUp6HtWJqGiQ95ELLQcOOq+vS/Br9yw0S8PNNKg5SJHy7\n4iDFFDvpJCZ/J8t3VfWfcV1RagVIlhw0OL8dAyn+TQUQ1zdhx/tH0ADuD6R0O9iQ6r+Ult2A\nulUBSDxjd4RiYRRIKPMq3wkNj0V7QwLwS8ZTyRDf6QTpEYwRM0hUF6DJeqVBauBiWnYHapd/\nkETGbjM6U6BgZl5lw1aN8eDwV18kAP9/6eN45zz945LkTXNIyLjT44dkGfVl2v0Xn90gZ6/g\nx2mYpG/yK7wQXfb5sNsHUhNX0647UL/8gyQydtvjBXgWEp15VeyEEqWwvVmOkI/89/TjP57P\n3+BsbUmQFIcwLdUm+9q+3IX99ZvsjyvocfL6kQmSZ78ngBQ/ZeO3oHb5B4mndYzsEWw6PRfP\nvCp2Qqm7eMIu4INy8RqMwz5LXptDuiGxm+aQkSO+xjPqy5OczN8hG/hh/uVfIpbYKb087/+/\nvfN7jezI7ng95TGQh4ADu2Rg9bhqAiH2y5qAN0RNXsaBhcUJ6k1ICMuKrIOlfTBk7UmQHoKH\ngFftbGJ24gZ5tV5GYmQGrNlO0x4ZtO5YQQy41d1q6d6/JfX71/3R90dVd1frfBnd6dt9+/6s\nT9epU1XnaN6PFJBsu3FY9TCVtIhCDSC53yMyXpiRGhNBgyRIYusp2epWBDTg4fLZp4pDEUqE\nrOubvIT2zuxH+YlEiVVIbh643mhLKUQvqOQWp3MlaQGFOuXHxP9Bl0pLBxLdSnzQMrZPCyRp\nbvKAxC2eWs9RGnaf0BppDiAJbARMw+FpxcPkapD+9iIKNYC0ANPO2Chh2ukgWeHy00AyNzkk\ncYsbF+YJmW67cg/8jGanuUBneLmDl8K1YXo/SIi6r9c31R6HqgYiMH34tDhJxb2JBwfp7wNI\ni5APZ0ObNVqSzgYVeVVulHA26CCxwmqZdnFsV3ZqEzLV/CjhKtddDf9X8oHTSaxt0SSTrg3T\n+0EzpKFdfY9DjSX8+unTpy+KIXJyUmgzzNFgKUCaLOCYyyj3IMkwqkn3t4q8KjdCIj2fdH8b\nIBnh8hWHOkj6Ji+xuMX2KWmdSGWf+B452wbZ5RBXTqZrQ3k/IpqJ09yfIul0SGW1mzJ08qIY\nSQcDrNRPXBTqAv12XCw0jSeQAiLSPUgqjGqyQ1ZFXhUbyTyXbGsTJD2icUPnUIFkBj1+g8ct\ntvWJ9H2XfeJneG8XqI0BPaL2Xab345rv7eREsiJqJQYSN+5m0EQ+PcmjjRdxytEgbeTUYK4g\nTXg0Jh8cBVW5eQCpjpSfgS5kRGMWJ0RyqDkbjKDHhyRucZIjSlI1kGJcAbbRLa56dmZ4P/i+\nMAYWSkMurZmUTdOLtHpLP0126YyjA6u8D1gt5aVyyFCfk+T+mKl7G9ferS8tGUg1dZj1QXon\nUpFHvoduGzvxToNWPDO8H/HxcUwqFBOlU0GS5QNPpelFkqTkiQ4YRwZIA2XqOSjU7JrYOK5b\nlrgX179De2xJ3PkmevXnfbx+u4vQ7o0vjuT+er3aO/akOwJSTCsklDVAPEfYtsMNo1Ns3Z3O\n9H5cXh5fUpBeaA2d4WkWSUQ2NSeCJMTzw2+gbVI+r0lBvWZHGgwe3EMvvzcYCIgJQ+wVLd0O\nCjU3p5lnZYf22lH/qzW2hBnWhCT6wYZ/kMbLStJKgLQl9KfiRZIoUiGR4lH65xqR3t9b0Uuc\n6/0gID1hIKlKCWN0enpqGnfWgTWaNJBofvgNvNiNohs6/HD9hmHzE1p+36MgMYRE0Sel20Wh\n5nu7pTb1GXVatnEbMTm25IvJp2ht0u+gB1G0rwZnVTikqfTHNMbqLad5txIgxVuHTPL/7E1L\ng7RHf4GbBJdZ3o9jApIgiaPE20cMpVPzFIzjMJo0kGh++P2IDpbaR5tRtIn2GUgIPR38Et07\nwKbdwHRhktLdIbmXahZqbtrxV03SQG00kmNLGuitX9NQgX9MPojQtiOM8kDCStnUwSHrKXSQ\nmGcQs4PQv7/0ytbhB6+gbz+gRUsbFi4mdpD3u8k5Gvk646WTQpDv/cAgHT9RJFGUpKuBoTRj\nqN8JEQfp0Qu82xuWj2yDeAWvcTVDQbqH/uGnB1gD5ZbRin7TQaE2e72PcEV8wdL3mo3CX68h\n9OoXk35ffOCqTCc4Yrx5/0EAABy6SURBVLsdJ0mqU++6VOAgib6qLQzSK+j1rQ9fEk9aHxbe\nkK+63VtqJG37uP+XWASkJ7JawSipBhJrLOXXh+xLRAhRmiIGEiuieInZOTj4Kb7Kl5/yhpHd\nOx27KNQmSLe0OXSbBKk/6b6K1n5BEpOKD9woA6SeTVLur9JcFThIYvQEqZHewCbd36NXDj98\nhQ05Oo27HcPWJyDhb+xGX6mkky5P5liApJH0dKjr9PRRAZB4jURpskHCf8Rld/wyuvfLGSDV\nuRQTJFwRT4k9Z3tXaPDan5OkpK+iepFrbc0CqZe6mcszKKvAQZLj+bYQ+gCD9G2y/IAVgenZ\nX76m2/rdLgPs1pc5QEG6bOsknXxocnSaWj6UTjSQ9BpJmnYcpMHgPelnYN3Zqug3HTxTCyRs\nzSJiwVrelcka+nTyMVqbTB6gB332gRvNAomTBCC5kv5rTJwMZLnF3jX7TmltpNbofR9nDJ+u\nqEtq2h1TkNrcsBP8nArvdwmQTjSQhLOBrMWDl9AvB8foHgepgetezZWolfbqskDCcNK+JMu7\n0n9AVx9OJv+7Jj4op2kL8V4qKjpSgyxSQCL09DSSxss1CWoFQTqk63uo+f33D2WB6IpXusnz\nxClJl4wkChIjibsatG0yfmmlZE12wisbDpJwf1OQuPPwAQGpwdc66tpUaa8uG6Qj5msxvSvY\nrvvHb6K1h8TA++IthP7sInuHGWqYNqiqYVNvE0WJijWUACRn0qdqHDLTbkuYOd1u91jUQ10J\nkpzAgeW2SjrWQXrSTh0xlwMS+SEWHooXskxxkHiHbMRAIhnc7z04IPbdPbbW0X8k1IhGL5Jn\nLbO2UfXLpFYUslpyM0ES1RHVrF+luSpwkPSpGgSkN9Arh2Iyxo+7x7iN9JAipX5j5QSOmDwY\nhyRdmjVS+zJto5xnT86JVEWJ4UHKM2KVlAEZKuTuAopJO5M+54j9X2Vn3Pg2ZnmRxS1qkkPc\nqG5lurky7KgAJHfSp2psYZCU+1v0nZK6iEQ6FSDJCRxE/kC6PH4/baOZIKVsnwlSTFhydwFF\nZJw5DTNbORcvEXtW5iwvumij5/gAn6GPMkHC5h2A5FD6VI2tw63Dv2qh5ik15v4aodf+E0P0\nt5Z7WM7yiN2CdMxJehuht9+/vBRzXZXxgl9NRWewZqkZEf70UaH0A7KFRpK7060kq9jW93jT\na7ZmeZHFELXw/rfRV8Z19zSKkmcDILkSHSJEXpAm+MMu1cOH3YfZ33Bp2/Em0vHbAp0kSKz+\n3DZ9Bw3t19gYFUpf7psgOe2sKS/nxVa06vRZXnSxg4ZxJOJB8Y0xQQiJ0XaowgBkn1olkOKt\nLdrdQYLmCYwoT9nfGDuzjShEpCJ6ItGhJOkg4RNjncG6N1v1FsdmxDH2gWHa1Temasl9uWV3\nx+ypYHYD2sEm365xEApSjw9rIFstEUerBRJxNlBNWYXEMMqtkrJC8RRWp4GauNzHl7/ZYibj\npek6RmQ6RIsZn010y6Y46P2rxhTitIhjEiQyJIe17xeEkyeQErO8yCdNNG3TOclKpC4a698E\nkPyI3MrHTVqctepoVpVU75jMp3GUGqCZv9qR7+N1NsVBH/GjNoyTg9k0kMjqxPA4V3I415AH\nU0qRc2uBdIbaDSTGHbNQ8ZgiNoqjRYNd41eJCNWL0+qAZNzOh7I68lwlkYrjgnWLtqyYSeIV\nNtH4+6TflE5xkCDFhUBSh+tbfTe1zr2s/IFkzPLi19sU96KtxZMnn9GVHeWZfezsbGpdySIP\n7lDm4zUwyq2S6robGmiP2R/JKH5k+YKZaPz9JnqNdjaiP2CmXTPBS2bEMa6JUSf1a516afkC\nyZrlhVgYKOIUF948I1Q8+ckS3CUiVC9MKwKS9XwtjDxWSWc0tmtsF3wdJPW+KDFYm1Ekqy/t\nK+kRx9ThOECCpDpnXl6+QLJmeR3xeGr4J0h484x4oiqUaCMlQvWitKIgdW1lfrO2u4HHdk0H\nKX6hvz9tCI6MBpX4OCPiGNID9fX1Oin1fFC9R2p83dyXB5BydIGapjdPnJC6M2dpEaoXpNUA\nqcYDHtd33B1pv5O6accdUdr7w99PC/nHlpkRx450kCaqTuqnn40/kObrJWuhvzG9eeKE1J2J\n0yJUL0h3HqSaVVJDxHY1nQ361AZq0XeEfV93ikNfeuxqnHWO8jicI0iIBHKR3rwM044oGaF6\nMVqOs6ipWjbHODOtQxGxZk/Hdn/rUxt2tPfrT3EQzaNfKcMO8chdTbQjjEUVpYIG6JIVoD4E\nKfEl9XsvOsfYvvJykvpSg3q4hTfPCBXfYX5QpP2KLYEApJpVkoztqpW3S3NqAy6w0oqrP8VB\neb/FOzxyF/EX7+m8UncxCdClINeHINlfUiDJzjG1L/ZLsM5GLc3Dsot1b54WKj7p/u54Po1i\nApAISIwkO85TZZkzKNylfaZSjgZBEo/c1Y5PFQnSXcxC0rW42akPQbK/pLtKeOeY8DYLm7V1\nEz2eo7tZevPkSGNR3fIO2awI1QsQgCTcDfr4k5ryCpLWg8QrJerP4AEsRTNCtilYgC7h8LCG\nIBlfUq9k55jtRZmSTjA0J4zCUiggpeVdkA1j9mTz5u3kCvPzZNxLRh6sLGtOn/sqqc9fCpD0\nRcLLZWKSHB+aBMnoHLM7tNwFr1sphQJSqm9GvpkAqdS+x+PeEy3GU33Zk2PdkqQ3j+gr5yAZ\nnWNJkJxezaoolLuS//hqgTT+uDd2C5L3Kkm9JiQlmTAziyZMuzhOBcnosjlS+9I7yACkDC3b\nXTG9shk5W4Vbl75HN9k3QSp+PDLZkph1T3yC5LpKMlYmKUyYmUU1f4E1BEkuzJBe0q1sOxvi\nGEDK0LLdFdMrm5GzVbh1qT3PNtmvBBJrGdHlE3dNpCRIruskQ5MkSIa7WPdgW0OQ5MIM6SXd\nyrb7O44BpAwt210xvbJZOVtjkVVEbaKDVPBYKtxgzzVIfqskSylWmuEu1jtkzSFIamGG9BJu\nZWbxJYczgRJatrtiemVzcraqJ8s26VXwy2phOylJ7i5jrlVSLJ0P4JdemJYPJGPRspxM5nBg\nfZMx98uWmlrATTvaUHriMhdcMqjdHEia14gDUIqWG6QZOVvZJq/+yydnDCRcovolJ+n0lG0X\nMEjEAVG1PxrkRMsNEnPVWaad3IxvgjkYCJDKBwVRtt1/ObyMlNLsl6RJ9ZEdIBdadpByc7Zi\nfHoIfToefFcHqV/uiNK2cxfjLr04+yUJQFqslhukGTlbSW30LlJtpJhNeeuXOyStjhyClFWg\nvYIU2fJ5MFBSyw1Sbs5WUhvh4v9PCH33Uw5SP3fuaKZ6LkHKLtA+SQKQFqxlA6m4tJxTcsBp\nXwQGKbkvupNaE/yUcgq0P5ISHAFJc1a4IEnfNf8/5sGqKsXXIRl33ICUV6ABpNVVwCCJSonz\nFLM5b/1JJZLi3sduil9ugfZGEoC0aAUNEq2UehIkPehbv+yuHBXA/BINIK2swgaJVErCwLOi\nJ/ZL7cZZEZxRoh2RpM93oK8ApEUrdJDUyFMRzUDYdv0SO3FXBmeB5IakBEjgtVu0ggdpLNx3\neuxEGvitxE7mBpKjKskcgQ0gLYFCB4n4GHi8BQVSv+SIuwql0KwPcnblYKSQiDJnTmhgUxyW\nMcPJnVTgIPGpD4QkYdlVSBrkEKSZ+ypv3OWkYFrODCd3UqGDJP7vjSeiJqrPUYFymDm9beau\nSoOUk4JpOTOc3EmFDZI+FU/2HTkA6TmZ545LL4nutoOXFzJ1nBbMty2iAtOyviNyy22ijee5\ns97LkpSTgmk5M5zcSa0OSFIuaiQ6sq8t5rPL0BF6MN8d/hYfUsvX+LhalyDlpGBS7yxThpM7\nqaBBSp8b7gKkPTLEvEFwGuLKSQ8dIYP5tm7jjoi0o3KTd1Aru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eJBugCkTOWBREnSfqmDKGPCi96/uvoY/RFpIz0jZ379/KNNBlJEQeph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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(2016)\n",
    "a <- grid::arrow(type = \"closed\", length = unit(.15, \"inches\"))\n",
    "ggraph(bigram_graph, layout = \"fr\") +\n",
    "  geom_edge_link(aes(edge_alpha = n), show.legend = FALSE,\n",
    "                 arrow = a, end_cap = circle(.07, 'inches')) +\n",
    "  geom_node_point(color = \"gold\", size = 5) +\n",
    "  geom_node_text(aes(label = name), vjust = 1, hjust = 1) +\n",
    "  theme_void()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "trigram_graph <- trigrams_Query_filtered_counts %>%\n",
    "  filter(n > 40) %>%\n",
    "  graph_from_data_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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xyTMYeL6K8E7XQNpOPkhI3SQbrQt9w3rQRRWwBp6gWQSjATIPFSEHsc53Hf8S1I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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggraph(trigram_graph, layout = \"fr\") +\n",
    "  geom_edge_link() +\n",
    "  geom_node_point() +\n",
    "  geom_node_text(aes(label = name), vjust = 1, hjust = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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dKMTcYWQ5//D/T5588hSwIcUkwkFa8m2XNDO3iIR5pJV1dXTu5RrU+34XE7pEja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\nkQDAASASADjg/wd3yW/aItLbgAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a <- grid::arrow(type = \"closed\", length = unit(.15, \"inches\"))\n",
    "ggraph(trigram_graph, layout = \"fr\") +\n",
    "  geom_edge_link(aes(edge_alpha = n), show.legend = FALSE,\n",
    "                 arrow = a, end_cap = circle(.07, 'inches')) +\n",
    "  geom_node_point(color = \"lightblue\", size = 5) +\n",
    "  geom_node_text(aes(label = name), vjust = 1, hjust = 1) +\n",
    "  theme_void()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Word correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "abstract_section_words <- df_with_patent_id %>%\n",
    "  filter(IssueDate == \"2016\") %>%\n",
    "  mutate(section = row_number() %/%4) %>%\n",
    "  filter(section > 0) %>%\n",
    "  unnest_tokens(word, Abstract) %>%\n",
    "  filter(!word %in% all_stops$word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_pairs <- abstract_section_words %>%\n",
    "  pairwise_count(word, section, sort = TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>item1</th><th scope=col>item2</th><th scope=col>correlation</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>limonene   </td><td>citrus     </td><td>1          </td></tr>\n",
       "\t<tr><td>citrus     </td><td>limonene   </td><td>1          </td></tr>\n",
       "\t<tr><td>process    </td><td>methods    </td><td>1          </td></tr>\n",
       "\t<tr><td>processes  </td><td>methods    </td><td>1          </td></tr>\n",
       "\t<tr><td>liquid     </td><td>methods    </td><td>1          </td></tr>\n",
       "\t<tr><td>time       </td><td>include    </td><td>1          </td></tr>\n",
       "\t<tr><td>reference  </td><td>include    </td><td>1          </td></tr>\n",
       "\t<tr><td>capable    </td><td>include    </td><td>1          </td></tr>\n",
       "\t<tr><td>application</td><td>processing </td><td>1          </td></tr>\n",
       "\t<tr><td>include    </td><td>time       </td><td>1          </td></tr>\n",
       "\t<tr><td>reference  </td><td>time       </td><td>1          </td></tr>\n",
       "\t<tr><td>capable    </td><td>time       </td><td>1          </td></tr>\n",
       "\t<tr><td>methods    </td><td>process    </td><td>1          </td></tr>\n",
       "\t<tr><td>processes  </td><td>process    </td><td>1          </td></tr>\n",
       "\t<tr><td>liquid     </td><td>process    </td><td>1          </td></tr>\n",
       "\t<tr><td>andor      </td><td>production </td><td>1          </td></tr>\n",
       "\t<tr><td>comprising </td><td>production </td><td>1          </td></tr>\n",
       "\t<tr><td>addition   </td><td>production </td><td>1          </td></tr>\n",
       "\t<tr><td>production </td><td>andor      </td><td>1          </td></tr>\n",
       "\t<tr><td>comprising </td><td>andor      </td><td>1          </td></tr>\n",
       "\t<tr><td>addition   </td><td>andor      </td><td>1          </td></tr>\n",
       "\t<tr><td>production </td><td>comprising </td><td>1          </td></tr>\n",
       "\t<tr><td>andor      </td><td>comprising </td><td>1          </td></tr>\n",
       "\t<tr><td>addition   </td><td>comprising </td><td>1          </td></tr>\n",
       "\t<tr><td>methods    </td><td>processes  </td><td>1          </td></tr>\n",
       "\t<tr><td>process    </td><td>processes  </td><td>1          </td></tr>\n",
       "\t<tr><td>liquid     </td><td>processes  </td><td>1          </td></tr>\n",
       "\t<tr><td>production </td><td>addition   </td><td>1          </td></tr>\n",
       "\t<tr><td>andor      </td><td>addition   </td><td>1          </td></tr>\n",
       "\t<tr><td>comprising </td><td>addition   </td><td>1          </td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>relates    </td><td>limonene   </td><td>NaN        </td></tr>\n",
       "\t<tr><td>waste      </td><td>limonene   </td><td>NaN        </td></tr>\n",
       "\t<tr><td>provide    </td><td>limonene   </td><td>NaN        </td></tr>\n",
       "\t<tr><td>includes   </td><td>limonene   </td><td>NaN        </td></tr>\n",
       "\t<tr><td>background </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>field      </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>prior      </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>description</td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>food       </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>form       </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>water      </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>summary    </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>including  </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>relates    </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>waste      </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>provide    </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>includes   </td><td>hydrolysate</td><td>NaN        </td></tr>\n",
       "\t<tr><td>background </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>field      </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>prior      </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>description</td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>food       </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>form       </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>water      </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>summary    </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>including  </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>relates    </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>waste      </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>provide    </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "\t<tr><td>includes   </td><td>scimist    </td><td>NaN        </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       " item1 & item2 & correlation\\\\\n",
       "\\hline\n",
       "\t limonene    & citrus      & 1          \\\\\n",
       "\t citrus      & limonene    & 1          \\\\\n",
       "\t process     & methods     & 1          \\\\\n",
       "\t processes   & methods     & 1          \\\\\n",
       "\t liquid      & methods     & 1          \\\\\n",
       "\t time        & include     & 1          \\\\\n",
       "\t reference   & include     & 1          \\\\\n",
       "\t capable     & include     & 1          \\\\\n",
       "\t application & processing  & 1          \\\\\n",
       "\t include     & time        & 1          \\\\\n",
       "\t reference   & time        & 1          \\\\\n",
       "\t capable     & time        & 1          \\\\\n",
       "\t methods     & process     & 1          \\\\\n",
       "\t processes   & process     & 1          \\\\\n",
       "\t liquid      & process     & 1          \\\\\n",
       "\t andor       & production  & 1          \\\\\n",
       "\t comprising  & production  & 1          \\\\\n",
       "\t addition    & production  & 1          \\\\\n",
       "\t production  & andor       & 1          \\\\\n",
       "\t comprising  & andor       & 1          \\\\\n",
       "\t addition    & andor       & 1          \\\\\n",
       "\t production  & comprising  & 1          \\\\\n",
       "\t andor       & comprising  & 1          \\\\\n",
       "\t addition    & comprising  & 1          \\\\\n",
       "\t methods     & processes   & 1          \\\\\n",
       "\t process     & processes   & 1          \\\\\n",
       "\t liquid      & processes   & 1          \\\\\n",
       "\t production  & addition    & 1          \\\\\n",
       "\t andor       & addition    & 1          \\\\\n",
       "\t comprising  & addition    & 1          \\\\\n",
       "\t ... & ... & ...\\\\\n",
       "\t relates     & limonene    & NaN        \\\\\n",
       "\t waste       & limonene    & NaN        \\\\\n",
       "\t provide     & limonene    & NaN        \\\\\n",
       "\t includes    & limonene    & NaN        \\\\\n",
       "\t background  & hydrolysate & NaN        \\\\\n",
       "\t field       & hydrolysate & NaN        \\\\\n",
       "\t prior       & hydrolysate & NaN        \\\\\n",
       "\t description & hydrolysate & NaN        \\\\\n",
       "\t food        & hydrolysate & NaN        \\\\\n",
       "\t form        & hydrolysate & NaN        \\\\\n",
       "\t water       & hydrolysate & NaN        \\\\\n",
       "\t summary     & hydrolysate & NaN        \\\\\n",
       "\t including   & hydrolysate & NaN        \\\\\n",
       "\t relates     & hydrolysate & NaN        \\\\\n",
       "\t waste       & hydrolysate & NaN        \\\\\n",
       "\t provide     & hydrolysate & NaN        \\\\\n",
       "\t includes    & hydrolysate & NaN        \\\\\n",
       "\t background  & scimist     & NaN        \\\\\n",
       "\t field       & scimist     & NaN        \\\\\n",
       "\t prior       & scimist     & NaN        \\\\\n",
       "\t description & scimist     & NaN        \\\\\n",
       "\t food        & scimist     & NaN        \\\\\n",
       "\t form        & scimist     & NaN        \\\\\n",
       "\t water       & scimist     & NaN        \\\\\n",
       "\t summary     & scimist     & NaN        \\\\\n",
       "\t including   & scimist     & NaN        \\\\\n",
       "\t relates     & scimist     & NaN        \\\\\n",
       "\t waste       & scimist     & NaN        \\\\\n",
       "\t provide     & scimist     & NaN        \\\\\n",
       "\t includes    & scimist     & NaN        \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "item1 | item2 | correlation | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| limonene    | citrus      | 1           | \n",
       "| citrus      | limonene    | 1           | \n",
       "| process     | methods     | 1           | \n",
       "| processes   | methods     | 1           | \n",
       "| liquid      | methods     | 1           | \n",
       "| time        | include     | 1           | \n",
       "| reference   | include     | 1           | \n",
       "| capable     | include     | 1           | \n",
       "| application | processing  | 1           | \n",
       "| include     | time        | 1           | \n",
       "| reference   | time        | 1           | \n",
       "| capable     | time        | 1           | \n",
       "| methods     | process     | 1           | \n",
       "| processes   | process     | 1           | \n",
       "| liquid      | process     | 1           | \n",
       "| andor       | production  | 1           | \n",
       "| comprising  | production  | 1           | \n",
       "| addition    | production  | 1           | \n",
       "| production  | andor       | 1           | \n",
       "| comprising  | andor       | 1           | \n",
       "| addition    | andor       | 1           | \n",
       "| production  | comprising  | 1           | \n",
       "| andor       | comprising  | 1           | \n",
       "| addition    | comprising  | 1           | \n",
       "| methods     | processes   | 1           | \n",
       "| process     | processes   | 1           | \n",
       "| liquid      | processes   | 1           | \n",
       "| production  | addition    | 1           | \n",
       "| andor       | addition    | 1           | \n",
       "| comprising  | addition    | 1           | \n",
       "| ... | ... | ... | \n",
       "| relates     | limonene    | NaN         | \n",
       "| waste       | limonene    | NaN         | \n",
       "| provide     | limonene    | NaN         | \n",
       "| includes    | limonene    | NaN         | \n",
       "| background  | hydrolysate | NaN         | \n",
       "| field       | hydrolysate | NaN         | \n",
       "| prior       | hydrolysate | NaN         | \n",
       "| description | hydrolysate | NaN         | \n",
       "| food        | hydrolysate | NaN         | \n",
       "| form        | hydrolysate | NaN         | \n",
       "| water       | hydrolysate | NaN         | \n",
       "| summary     | hydrolysate | NaN         | \n",
       "| including   | hydrolysate | NaN         | \n",
       "| relates     | hydrolysate | NaN         | \n",
       "| waste       | hydrolysate | NaN         | \n",
       "| provide     | hydrolysate | NaN         | \n",
       "| includes    | hydrolysate | NaN         | \n",
       "| background  | scimist     | NaN         | \n",
       "| field       | scimist     | NaN         | \n",
       "| prior       | scimist     | NaN         | \n",
       "| description | scimist     | NaN         | \n",
       "| food        | scimist     | NaN         | \n",
       "| form        | scimist     | NaN         | \n",
       "| water       | scimist     | NaN         | \n",
       "| summary     | scimist     | NaN         | \n",
       "| including   | scimist     | NaN         | \n",
       "| relates     | scimist     | NaN         | \n",
       "| waste       | scimist     | NaN         | \n",
       "| provide     | scimist     | NaN         | \n",
       "| includes    | scimist     | NaN         | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "      item1       item2       correlation\n",
       "1     limonene    citrus      1          \n",
       "2     citrus      limonene    1          \n",
       "3     process     methods     1          \n",
       "4     processes   methods     1          \n",
       "5     liquid      methods     1          \n",
       "6     time        include     1          \n",
       "7     reference   include     1          \n",
       "8     capable     include     1          \n",
       "9     application processing  1          \n",
       "10    include     time        1          \n",
       "11    reference   time        1          \n",
       "12    capable     time        1          \n",
       "13    methods     process     1          \n",
       "14    processes   process     1          \n",
       "15    liquid      process     1          \n",
       "16    andor       production  1          \n",
       "17    comprising  production  1          \n",
       "18    addition    production  1          \n",
       "19    production  andor       1          \n",
       "20    comprising  andor       1          \n",
       "21    addition    andor       1          \n",
       "22    production  comprising  1          \n",
       "23    andor       comprising  1          \n",
       "24    addition    comprising  1          \n",
       "25    methods     processes   1          \n",
       "26    process     processes   1          \n",
       "27    liquid      processes   1          \n",
       "28    production  addition    1          \n",
       "29    andor       addition    1          \n",
       "30    comprising  addition    1          \n",
       "...   ...         ...         ...        \n",
       "45553 relates     limonene    NaN        \n",
       "45554 waste       limonene    NaN        \n",
       "45555 provide     limonene    NaN        \n",
       "45556 includes    limonene    NaN        \n",
       "45557 background  hydrolysate NaN        \n",
       "45558 field       hydrolysate NaN        \n",
       "45559 prior       hydrolysate NaN        \n",
       "45560 description hydrolysate NaN        \n",
       "45561 food        hydrolysate NaN        \n",
       "45562 form        hydrolysate NaN        \n",
       "45563 water       hydrolysate NaN        \n",
       "45564 summary     hydrolysate NaN        \n",
       "45565 including   hydrolysate NaN        \n",
       "45566 relates     hydrolysate NaN        \n",
       "45567 waste       hydrolysate NaN        \n",
       "45568 provide     hydrolysate NaN        \n",
       "45569 includes    hydrolysate NaN        \n",
       "45570 background  scimist     NaN        \n",
       "45571 field       scimist     NaN        \n",
       "45572 prior       scimist     NaN        \n",
       "45573 description scimist     NaN        \n",
       "45574 food        scimist     NaN        \n",
       "45575 form        scimist     NaN        \n",
       "45576 water       scimist     NaN        \n",
       "45577 summary     scimist     NaN        \n",
       "45578 including   scimist     NaN        \n",
       "45579 relates     scimist     NaN        \n",
       "45580 waste       scimist     NaN        \n",
       "45581 provide     scimist     NaN        \n",
       "45582 includes    scimist     NaN        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "word_cors <- abstract_section_words %>%\n",
    "  group_by(word) %>%\n",
    "  filter(n() >= 50) %>%\n",
    "  pairwise_cor(word, section, sort = TRUE)\n",
    "word_cors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Selecting by correlation\n",
      "ERROR while rich displaying an object: Error: Faceting variables must have at least one value\n",
      "\n",
      "Traceback:\n",
      "1. FUN(X[[i]], ...)\n",
      "2. tryCatch(withCallingHandlers({\n",
      " .     rpr <- mime2repr[[mime]](obj)\n",
      " .     if (is.null(rpr)) \n",
      " .         return(NULL)\n",
      " .     prepare_content(is.raw(rpr), rpr)\n",
      " . }, error = error_handler), error = outer_handler)\n",
      "3. tryCatchList(expr, classes, parentenv, handlers)\n",
      "4. tryCatchOne(expr, names, parentenv, handlers[[1L]])\n",
      "5. doTryCatch(return(expr), name, parentenv, handler)\n",
      "6. withCallingHandlers({\n",
      " .     rpr <- mime2repr[[mime]](obj)\n",
      " .     if (is.null(rpr)) \n",
      " .         return(NULL)\n",
      " .     prepare_content(is.raw(rpr), rpr)\n",
      " . }, error = error_handler)\n",
      "7. mime2repr[[mime]](obj)\n",
      "8. repr_text.default(obj)\n",
      "9. paste(capture.output(print(obj)), collapse = \"\\n\")\n",
      "10. capture.output(print(obj))\n",
      "11. evalVis(expr)\n",
      "12. withVisible(eval(expr, pf))\n",
      "13. eval(expr, pf)\n",
      "14. eval(expr, pf)\n",
      "15. print(obj)\n",
      "16. print.ggplot(obj)\n",
      "17. ggplot_build(x)\n",
      "18. layout$setup(layer_data, plot$data, plot$plot_env, plot$coordinates)\n",
      "19. f(..., self = self)\n",
      "20. self$facet$train(data)\n",
      "21. f(..., self = self)\n",
      "22. self$compute_layout(data, self$params)\n",
      "23. f(...)\n",
      "24. plyr::unrowname(combine_vars(data, params$plot_env, vars, drop = params$drop))\n",
      "25. combine_vars(data, params$plot_env, vars, drop = params$drop)\n",
      "26. stop(\"Faceting variables must have at least one value\", call. = FALSE)\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAAAA1BMVEX///+nxBvIAAAACXBI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\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMA3yB4AAXYzOhIAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "word_cors %>%\n",
    "  filter(item1 %in% c(\"food\", \"waste\")) %>%\n",
    "  group_by(item1) %>%\n",
    "  top_n(7) %>%\n",
    "  ungroup() %>%\n",
    "  mutate(item2 = reorder(item2, correlation)) %>%\n",
    "  ggplot(aes(item2, correlation)) +\n",
    "  geom_bar(stat = \"identity\") +\n",
    "  facet_wrap(~ item1, scales = \"free_x\") +\n",
    "  coord_flip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pJbJOIoNK5Xp37sne9TOM7qM2d4teFPBeFk+tlaaDMES/8Kw6TTF40g6s532t9+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\npKlwlfJsOx9rFcl/nu0RD9WKlK8sO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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "word_cors %>%\n",
    "  filter(correlation > .70) %>%\n",
    "  graph_from_data_frame() %>%\n",
    "  ggraph(layout = \"fr\") +\n",
    "  geom_edge_link(aes(edge_alpha = correlation), show.legend = FALSE) +\n",
    "  geom_node_point(color = \"lightblue\", size = 5) +\n",
    "  geom_node_text(aes(label = name), repel = TRUE) +\n",
    "  theme_void()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OADvnqnbuAIv7tx/E8ZpMG7c65RDkjk/SWflSklkJZLrf0n0dxW5LVTuBc40O0l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\nSwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(1)\n",
    "word_cors %>%\n",
    "  filter(correlation > .60) %>%\n",
    "  graph_from_data_frame() %>%\n",
    "  ggraph(layout = \"fr\") +\n",
    "  geom_edge_link(aes(edge_alpha = correlation, edge_width = correlation),\n",
    "                 edge_colour = 'darkred',\n",
    "                 show.legend = TRUE) +\n",
    "  geom_node_point(size = 3) +\n",
    "  geom_node_text(aes(label = name), repel = TRUE, size=3,\n",
    "                 point.padding = unit(0.2, \"lines\")) +\n",
    "  theme_void()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Latent dirichlet analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load data\n",
    "filename = \"fw1.csv\" # \"fw1.csv\" is our raw data which has been slightly pre-processed in Excel. \n",
    "df <- read.csv(filename)\n",
    "df$text <- as.character(df$text)\n",
    "df$IssueDate <- as.factor(df$IssueDate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t866 obs. of  6 variables:\n",
      " $ PatentNo : Factor w/ 866 levels \"3930799\",\"3937977\",..: 1 2 3 4 5 6 7 8 9 10 ...\n",
      " $ title    : Factor w/ 760 levels \"<i>Sphingomonas </i>sp. microorganism and method for decomposing methane or odor-producing compounds using the same\",..: 41 115 73 620 356 565 400 139 547 694 ...\n",
      " $ abstract : Factor w/ 785 levels \"\",\" A bag opener for opening bags containing recyclable materials includes a source of heat sufficient to melt the\"| __truncated__,..: 219 177 196 246 225 237 67 278 110 239 ...\n",
      " $ text     : chr  \"This invention relates to apparatus for making organic fertilizer, sometimes referred to as compost or humus, f\"| __truncated__ \"1. Field of the Invention This invention relates to an improvement in electrical circuitry employed to connect \"| __truncated__ \"Various methods and apparatus for cleaning and sorting culinary items have been proposed heretofore. See for ex\"| __truncated__ \"The present invention relates to the handling of soiled dishes preliminary to the washing thereof, especially f\"| __truncated__ ...\n",
      " $ IssueDate: Factor w/ 644 levels \"1/1/2013\",\"1/10/1995\",..: 42 196 207 253 283 361 373 373 462 482 ...\n",
      " $ country  : Factor w/ 1 level \"US\": 1 1 1 1 1 1 1 1 1 1 ...\n"
     ]
    }
   ],
   "source": [
    "str(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Remove common stop words\n",
    "data(\"stop_words\")\n",
    "\n",
    "# Custom stop words\n",
    "additional_stop_words <- data_frame(word=c(\"figref\", \"idrefdrawingsfig\", \"bb\", \"xb\", \"patent\", \"document\", \n",
    "                                           \"xbsubsub\", \"fig\"， \"invention\"),\n",
    "                                   lexicon = rep(\"custom\"))\n",
    "\n",
    "#Bind stop word data\n",
    "all_stops <- bind_rows(stop_words, additional_stop_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define a function to clean our text\n",
    "#Here we lemmatize words and remove punctiation, numbers, and stopwords. \n",
    "clean_patent <- function(df, column_name){\n",
    "    #clean the text of a patent : put to lowercase, lemmatize, remove punctuation and numbers\n",
    "    start.time <- Sys.time()\n",
    "    cleaned_text <- df[,c(column_name)]%>%\n",
    "        tolower() %>%\n",
    "        lemmatize_strings() %>%\n",
    "        removeWords(all_stops$word) %>%\n",
    "        removeNumbers() %>%\n",
    "        removePunctuation()\n",
    "    end.time <- Sys.time()\n",
    "    time.taken <- end.time - start.time\n",
    "    time.taken\n",
    "    return(cleaned_text)  \n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "df[,c(\"text\")] <- clean_patent(df, \"text\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define function to create a document-term matrix\n",
    "create_document_matrix <- function(df){\n",
    "    #create document matrix\n",
    "    text_lda <- df %>%\n",
    "        mutate(PatentNo = as.integer(PatentNo)) %>%\n",
    "        as_tibble() %>%\n",
    "        select_(\"text\",\"PatentNo\") %>% \n",
    "        unnest_tokens(word, text) %>%\n",
    "        count(PatentNo, word) %>% \n",
    "        cast_dtm(PatentNo, word, n)\n",
    "    text_lda\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Split the data between train and validation set : the validation set will be used to get the right number of topics\n",
    "n <- nrow(df)\n",
    "splitter <- sample(1:n, round(n * 0.7))\n",
    "train_set <- df[splitter, ]\n",
    "valid_set <- df[-splitter, ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t606 obs. of  6 variables:\n",
      " $ PatentNo : Factor w/ 866 levels \"3930799\",\"3937977\",..: 230 550 861 352 675 525 824 734 549 201 ...\n",
      " $ title    : Factor w/ 760 levels \"<i>Sphingomonas </i>sp. microorganism and method for decomposing methane or odor-producing compounds using the same\",..: 465 474 518 517 157 635 748 653 629 509 ...\n",
      " $ abstract : Factor w/ 785 levels \"\",\" A bag opener for opening bags containing recyclable materials includes a source of heat sufficient to melt the\"| __truncated__,..: 262 646 451 515 678 606 600 626 340 94 ...\n",
      " $ text     : chr  \"field     relate    apparatus  method  compact  pulverize waste  soil   specifically   mobile compactor  pulver\"| __truncated__ \"background     relate  compost device compost   purposeful biodegradation  organic matter   yard  food waste  y\"| __truncated__ \" technical field       refer   poultry feeder specifically refer   feeder   bird  initial stage   growth  poult\"| __truncated__ \"background    food waste disposer   commonplace  modern american kitchen  appliance mount beneath  kitchen sink\"| __truncated__ ...\n",
      " $ IssueDate: Factor w/ 644 levels \"1/1/2013\",\"1/10/1995\",..: 139 534 491 408 499 268 192 592 534 419 ...\n",
      " $ country  : Factor w/ 1 level \"US\": 1 1 1 1 1 1 1 1 1 1 ...\n"
     ]
    }
   ],
   "source": [
    "str(train_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Make a document term matrix for the training set and the validation set\n",
    "lda_document_matrix_train <- create_document_matrix(train_set)\n",
    "lda_document_matrix_valid <- create_document_matrix(valid_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Function to create LDA model based on different topics\n",
    "create_lda_model <- function(document_matrix, num_topics, seed=1234){\n",
    "    #create lda model\n",
    "    lda_model <- LDA(document_matrix, k=num_topics, control = list(seed=seed))\n",
    "    lda_model\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"k=2\"\n",
      "[1] \"k=4\"\n",
      "[1] \"k=8\"\n",
      "[1] \"k=10\"\n",
      "[1] \"k=20\"\n",
      "[1] \"k=30\"\n",
      "Time difference of 25.03346 mins\n",
      "$`2`\n",
      "[1] 1435.125\n",
      "\n",
      "$`4`\n",
      "[1] 1313.937\n",
      "\n",
      "$`8`\n",
      "[1] 1148.934\n",
      "\n",
      "$`10`\n",
      "[1] 1121.004\n",
      "\n",
      "$`20`\n",
      "[1] 984.6929\n",
      "\n",
      "$`30`\n",
      "[1] 930.5961\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Let's try out different values of K. CAREFUL, this takes a few hours to run. \n",
    "candidate_k <- c(2, 4, 8, 10, 20, 30) \n",
    "perplexities <- vector(mode=\"list\", length=length(candidate_k))\n",
    "names(perplexities) <- candidate_k\n",
    "index <- 1\n",
    "start.time <- Sys.time()\n",
    "for(k in candidate_k){\n",
    "    print(paste(\"k=\",k,sep=\"\"))\n",
    "    lda_model <- create_lda_model(lda_document_matrix_train, k)\n",
    "    perplexities[index] <- perplexity(lda_model, newdata = lda_document_matrix_valid)\n",
    "    index <- index + 1\n",
    "}\n",
    "end.time <- Sys.time()\n",
    "print(end.time - start.time)\n",
    "print(perplexities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "save(perplexities, file = \"perplexities.rda\")\n",
    "#load(\"perplexities.rda\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "Topics <- candidate_k\n",
    "Perplexity <- c(perplexities[[1]],perplexities[[2]],perplexities[[3]],perplexities[[4]],perplexities[[5]],perplexities[[6]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gjZhUiphYlsrxcypVNBpMlhpoKQEals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\nIf8DlSOZrVOinn0AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_topics_vs_perplexity <- data.frame(Topics, Perplexity)\n",
    "ggplot(num_topics_vs_perplexity, aes(Topics, Perplexity)) + \n",
    "    geom_line() + \n",
    "    geom_point() + \n",
    "    ggtitle(\"Perplexity on the validation set depending on the number of topics\") +\n",
    "    theme(plot.title = element_text(hjust = 0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_df <- as_tibble(text_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Joining, by = \"word\"\n"
     ]
    }
   ],
   "source": [
    "abstract_lda <- lda_df %>% \n",
    "  unnest_tokens(word, text) %>% \n",
    "  anti_join(all_stops) %>% \n",
    "  count(line, word) %>% \n",
    "  cast_dtm(line, word, n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<<DocumentTermMatrix (documents: 866, terms: 24684)>>\n",
       "Non-/sparse entries: 273082/21103262\n",
       "Sparsity           : 99%\n",
       "Maximal term length: 58\n",
       "Weighting          : term frequency (tf)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "abstract_lda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "ap_lda <- LDA(abstract_lda, k=20, control = list(seed=1234))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>topic</th><th scope=col>term</th><th scope=col>beta</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td> 1          </td><td>accept      </td><td>3.904112e-44</td></tr>\n",
       "\t<tr><td> 2          </td><td>accept      </td><td>5.281286e-05</td></tr>\n",
       "\t<tr><td> 3          </td><td>accept      </td><td>7.057033e-05</td></tr>\n",
       "\t<tr><td> 4          </td><td>accept      </td><td>2.639751e-70</td></tr>\n",
       "\t<tr><td> 5          </td><td>accept      </td><td>2.975061e-05</td></tr>\n",
       "\t<tr><td> 6          </td><td>accept      </td><td>5.322148e-04</td></tr>\n",
       "\t<tr><td> 7          </td><td>accept      </td><td>6.656161e-16</td></tr>\n",
       "\t<tr><td> 8          </td><td>accept      </td><td>3.648177e-05</td></tr>\n",
       "\t<tr><td> 9          </td><td>accept      </td><td>1.436543e-05</td></tr>\n",
       "\t<tr><td>10          </td><td>accept      </td><td>4.114650e-20</td></tr>\n",
       "\t<tr><td>11          </td><td>accept      </td><td>2.695373e-05</td></tr>\n",
       "\t<tr><td>12          </td><td>accept      </td><td>2.063673e-04</td></tr>\n",
       "\t<tr><td>13          </td><td>accept      </td><td>2.946278e-05</td></tr>\n",
       "\t<tr><td>14          </td><td>accept      </td><td>8.846002e-05</td></tr>\n",
       "\t<tr><td>15          </td><td>accept      </td><td>6.516893e-05</td></tr>\n",
       "\t<tr><td>16          </td><td>accept      </td><td>1.861850e-32</td></tr>\n",
       "\t<tr><td>17          </td><td>accept      </td><td>3.378814e-05</td></tr>\n",
       "\t<tr><td>18          </td><td>accept      </td><td>9.404091e-05</td></tr>\n",
       "\t<tr><td>19          </td><td>accept      </td><td>1.534031e-06</td></tr>\n",
       "\t<tr><td>20          </td><td>accept      </td><td>7.324756e-27</td></tr>\n",
       "\t<tr><td> 1          </td><td>action      </td><td>3.274591e-04</td></tr>\n",
       "\t<tr><td> 2          </td><td>action      </td><td>8.951273e-09</td></tr>\n",
       "\t<tr><td> 3          </td><td>action      </td><td>6.484695e-04</td></tr>\n",
       "\t<tr><td> 4          </td><td>action      </td><td>3.745856e-04</td></tr>\n",
       "\t<tr><td> 5          </td><td>action      </td><td>2.784730e-04</td></tr>\n",
       "\t<tr><td> 6          </td><td>action      </td><td>4.533960e-04</td></tr>\n",
       "\t<tr><td> 7          </td><td>action      </td><td>8.319541e-05</td></tr>\n",
       "\t<tr><td> 8          </td><td>action      </td><td>4.668374e-04</td></tr>\n",
       "\t<tr><td> 9          </td><td>action      </td><td>1.189793e-03</td></tr>\n",
       "\t<tr><td>10          </td><td>action      </td><td>8.254415e-04</td></tr>\n",
       "\t<tr><td>...</td><td>...</td><td>...</td></tr>\n",
       "\t<tr><td>11           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>12           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>13           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>14           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>15           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>16           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>17           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>18           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>19           </td><td>aiaddend     </td><td>1.482197e-323</td></tr>\n",
       "\t<tr><td>20           </td><td>aiaddend     </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td> 1           </td><td>iaddgb       </td><td>2.470328e-323</td></tr>\n",
       "\t<tr><td> 2           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td> 3           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td> 4           </td><td>iaddgb       </td><td> 3.101374e-05</td></tr>\n",
       "\t<tr><td> 5           </td><td>iaddgb       </td><td>4.940656e-324</td></tr>\n",
       "\t<tr><td> 6           </td><td>iaddgb       </td><td>4.940656e-324</td></tr>\n",
       "\t<tr><td> 7           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td> 8           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td> 9           </td><td>iaddgb       </td><td>1.185758e-322</td></tr>\n",
       "\t<tr><td>10           </td><td>iaddgb       </td><td>1.630417e-322</td></tr>\n",
       "\t<tr><td>11           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>12           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>13           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>14           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>15           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>16           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>17           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>18           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "\t<tr><td>19           </td><td>iaddgb       </td><td>1.482197e-323</td></tr>\n",
       "\t<tr><td>20           </td><td>iaddgb       </td><td> 0.000000e+00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       " topic & term & beta\\\\\n",
       "\\hline\n",
       "\t  1           & accept       & 3.904112e-44\\\\\n",
       "\t  2           & accept       & 5.281286e-05\\\\\n",
       "\t  3           & accept       & 7.057033e-05\\\\\n",
       "\t  4           & accept       & 2.639751e-70\\\\\n",
       "\t  5           & accept       & 2.975061e-05\\\\\n",
       "\t  6           & accept       & 5.322148e-04\\\\\n",
       "\t  7           & accept       & 6.656161e-16\\\\\n",
       "\t  8           & accept       & 3.648177e-05\\\\\n",
       "\t  9           & accept       & 1.436543e-05\\\\\n",
       "\t 10           & accept       & 4.114650e-20\\\\\n",
       "\t 11           & accept       & 2.695373e-05\\\\\n",
       "\t 12           & accept       & 2.063673e-04\\\\\n",
       "\t 13           & accept       & 2.946278e-05\\\\\n",
       "\t 14           & accept       & 8.846002e-05\\\\\n",
       "\t 15           & accept       & 6.516893e-05\\\\\n",
       "\t 16           & accept       & 1.861850e-32\\\\\n",
       "\t 17           & accept       & 3.378814e-05\\\\\n",
       "\t 18           & accept       & 9.404091e-05\\\\\n",
       "\t 19           & accept       & 1.534031e-06\\\\\n",
       "\t 20           & accept       & 7.324756e-27\\\\\n",
       "\t  1           & action       & 3.274591e-04\\\\\n",
       "\t  2           & action       & 8.951273e-09\\\\\n",
       "\t  3           & action       & 6.484695e-04\\\\\n",
       "\t  4           & action       & 3.745856e-04\\\\\n",
       "\t  5           & action       & 2.784730e-04\\\\\n",
       "\t  6           & action       & 4.533960e-04\\\\\n",
       "\t  7           & action       & 8.319541e-05\\\\\n",
       "\t  8           & action       & 4.668374e-04\\\\\n",
       "\t  9           & action       & 1.189793e-03\\\\\n",
       "\t 10           & action       & 8.254415e-04\\\\\n",
       "\t ... & ... & ...\\\\\n",
       "\t 11            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 12            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 13            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 14            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 15            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 16            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 17            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 18            & aiaddend      &  0.000000e+00\\\\\n",
       "\t 19            & aiaddend      & 1.482197e-323\\\\\n",
       "\t 20            & aiaddend      &  0.000000e+00\\\\\n",
       "\t  1            & iaddgb        & 2.470328e-323\\\\\n",
       "\t  2            & iaddgb        &  0.000000e+00\\\\\n",
       "\t  3            & iaddgb        &  0.000000e+00\\\\\n",
       "\t  4            & iaddgb        &  3.101374e-05\\\\\n",
       "\t  5            & iaddgb        & 4.940656e-324\\\\\n",
       "\t  6            & iaddgb        & 4.940656e-324\\\\\n",
       "\t  7            & iaddgb        &  0.000000e+00\\\\\n",
       "\t  8            & iaddgb        &  0.000000e+00\\\\\n",
       "\t  9            & iaddgb        & 1.185758e-322\\\\\n",
       "\t 10            & iaddgb        & 1.630417e-322\\\\\n",
       "\t 11            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 12            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 13            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 14            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 15            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 16            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 17            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 18            & iaddgb        &  0.000000e+00\\\\\n",
       "\t 19            & iaddgb        & 1.482197e-323\\\\\n",
       "\t 20            & iaddgb        &  0.000000e+00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "topic | term | beta | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "|  1           | accept       | 3.904112e-44 | \n",
       "|  2           | accept       | 5.281286e-05 | \n",
       "|  3           | accept       | 7.057033e-05 | \n",
       "|  4           | accept       | 2.639751e-70 | \n",
       "|  5           | accept       | 2.975061e-05 | \n",
       "|  6           | accept       | 5.322148e-04 | \n",
       "|  7           | accept       | 6.656161e-16 | \n",
       "|  8           | accept       | 3.648177e-05 | \n",
       "|  9           | accept       | 1.436543e-05 | \n",
       "| 10           | accept       | 4.114650e-20 | \n",
       "| 11           | accept       | 2.695373e-05 | \n",
       "| 12           | accept       | 2.063673e-04 | \n",
       "| 13           | accept       | 2.946278e-05 | \n",
       "| 14           | accept       | 8.846002e-05 | \n",
       "| 15           | accept       | 6.516893e-05 | \n",
       "| 16           | accept       | 1.861850e-32 | \n",
       "| 17           | accept       | 3.378814e-05 | \n",
       "| 18           | accept       | 9.404091e-05 | \n",
       "| 19           | accept       | 1.534031e-06 | \n",
       "| 20           | accept       | 7.324756e-27 | \n",
       "|  1           | action       | 3.274591e-04 | \n",
       "|  2           | action       | 8.951273e-09 | \n",
       "|  3           | action       | 6.484695e-04 | \n",
       "|  4           | action       | 3.745856e-04 | \n",
       "|  5           | action       | 2.784730e-04 | \n",
       "|  6           | action       | 4.533960e-04 | \n",
       "|  7           | action       | 8.319541e-05 | \n",
       "|  8           | action       | 4.668374e-04 | \n",
       "|  9           | action       | 1.189793e-03 | \n",
       "| 10           | action       | 8.254415e-04 | \n",
       "| ... | ... | ... | \n",
       "| 11            | aiaddend      |  0.000000e+00 | \n",
       "| 12            | aiaddend      |  0.000000e+00 | \n",
       "| 13            | aiaddend      |  0.000000e+00 | \n",
       "| 14            | aiaddend      |  0.000000e+00 | \n",
       "| 15            | aiaddend      |  0.000000e+00 | \n",
       "| 16            | aiaddend      |  0.000000e+00 | \n",
       "| 17            | aiaddend      |  0.000000e+00 | \n",
       "| 18            | aiaddend      |  0.000000e+00 | \n",
       "| 19            | aiaddend      | 1.482197e-323 | \n",
       "| 20            | aiaddend      |  0.000000e+00 | \n",
       "|  1            | iaddgb        | 2.470328e-323 | \n",
       "|  2            | iaddgb        |  0.000000e+00 | \n",
       "|  3            | iaddgb        |  0.000000e+00 | \n",
       "|  4            | iaddgb        |  3.101374e-05 | \n",
       "|  5            | iaddgb        | 4.940656e-324 | \n",
       "|  6            | iaddgb        | 4.940656e-324 | \n",
       "|  7            | iaddgb        |  0.000000e+00 | \n",
       "|  8            | iaddgb        |  0.000000e+00 | \n",
       "|  9            | iaddgb        | 1.185758e-322 | \n",
       "| 10            | iaddgb        | 1.630417e-322 | \n",
       "| 11            | iaddgb        |  0.000000e+00 | \n",
       "| 12            | iaddgb        |  0.000000e+00 | \n",
       "| 13            | iaddgb        |  0.000000e+00 | \n",
       "| 14            | iaddgb        |  0.000000e+00 | \n",
       "| 15            | iaddgb        |  0.000000e+00 | \n",
       "| 16            | iaddgb        |  0.000000e+00 | \n",
       "| 17            | iaddgb        |  0.000000e+00 | \n",
       "| 18            | iaddgb        |  0.000000e+00 | \n",
       "| 19            | iaddgb        | 1.482197e-323 | \n",
       "| 20            | iaddgb        |  0.000000e+00 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "       topic term     beta         \n",
       "1       1    accept   3.904112e-44 \n",
       "2       2    accept   5.281286e-05 \n",
       "3       3    accept   7.057033e-05 \n",
       "4       4    accept   2.639751e-70 \n",
       "5       5    accept   2.975061e-05 \n",
       "6       6    accept   5.322148e-04 \n",
       "7       7    accept   6.656161e-16 \n",
       "8       8    accept   3.648177e-05 \n",
       "9       9    accept   1.436543e-05 \n",
       "10     10    accept   4.114650e-20 \n",
       "11     11    accept   2.695373e-05 \n",
       "12     12    accept   2.063673e-04 \n",
       "13     13    accept   2.946278e-05 \n",
       "14     14    accept   8.846002e-05 \n",
       "15     15    accept   6.516893e-05 \n",
       "16     16    accept   1.861850e-32 \n",
       "17     17    accept   3.378814e-05 \n",
       "18     18    accept   9.404091e-05 \n",
       "19     19    accept   1.534031e-06 \n",
       "20     20    accept   7.324756e-27 \n",
       "21      1    action   3.274591e-04 \n",
       "22      2    action   8.951273e-09 \n",
       "23      3    action   6.484695e-04 \n",
       "24      4    action   3.745856e-04 \n",
       "25      5    action   2.784730e-04 \n",
       "26      6    action   4.533960e-04 \n",
       "27      7    action   8.319541e-05 \n",
       "28      8    action   4.668374e-04 \n",
       "29      9    action   1.189793e-03 \n",
       "30     10    action   8.254415e-04 \n",
       "...    ...   ...      ...          \n",
       "493651 11    aiaddend  0.000000e+00\n",
       "493652 12    aiaddend  0.000000e+00\n",
       "493653 13    aiaddend  0.000000e+00\n",
       "493654 14    aiaddend  0.000000e+00\n",
       "493655 15    aiaddend  0.000000e+00\n",
       "493656 16    aiaddend  0.000000e+00\n",
       "493657 17    aiaddend  0.000000e+00\n",
       "493658 18    aiaddend  0.000000e+00\n",
       "493659 19    aiaddend 1.482197e-323\n",
       "493660 20    aiaddend  0.000000e+00\n",
       "493661  1    iaddgb   2.470328e-323\n",
       "493662  2    iaddgb    0.000000e+00\n",
       "493663  3    iaddgb    0.000000e+00\n",
       "493664  4    iaddgb    3.101374e-05\n",
       "493665  5    iaddgb   4.940656e-324\n",
       "493666  6    iaddgb   4.940656e-324\n",
       "493667  7    iaddgb    0.000000e+00\n",
       "493668  8    iaddgb    0.000000e+00\n",
       "493669  9    iaddgb   1.185758e-322\n",
       "493670 10    iaddgb   1.630417e-322\n",
       "493671 11    iaddgb    0.000000e+00\n",
       "493672 12    iaddgb    0.000000e+00\n",
       "493673 13    iaddgb    0.000000e+00\n",
       "493674 14    iaddgb    0.000000e+00\n",
       "493675 15    iaddgb    0.000000e+00\n",
       "493676 16    iaddgb    0.000000e+00\n",
       "493677 17    iaddgb    0.000000e+00\n",
       "493678 18    iaddgb    0.000000e+00\n",
       "493679 19    iaddgb   1.482197e-323\n",
       "493680 20    iaddgb    0.000000e+00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ap_topics <- tidy(ap_lda, matrix = \"beta\")\n",
    "ap_topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "ap_top_terms <- ap_topics %>%\n",
    "  group_by(topic) %>%\n",
    "  top_n(10, beta) %>%\n",
    "  ungroup() %>%\n",
    "  arrange(topic, -beta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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SsxfsssSAG8Js9ovFK0FSTiDizfmvYZKcqm4Ha4AsJm9TOScAX7QKKh0xwm2Qfp\nNOVvBYm6Q8svTQKJnl9bSiBhg9ZAEiP7paUgsdBpDpOMgoTvqGLxbdFUkMrdR++jNXcTQXpP\nKB3nhXdQlKGCHMYsMyAJV9D5xb7BINFRsdjmSfZB0opvi+RGnzj9DV+Iu2XV36lOWpj+LndL\nUkyNjGKDp/QsyEhk2ptOf0vBqsTx7tCO16GzffCvVV42g9QjMSPpmtkbuMSENGjWLsqDtT7R\nXLQLJFFXMtJVkO5JzUhUDtI1OUgXdfkzkoN0VQ7SdwSJjUEdpNnaBVJT550M0n3tBymIb5kc\npCGqhNgaSGi7g1RVqK4iOUhD5CBNkoM0RCZBwjP6Shlu0T6QxMpvPLZfDpJQLJ+dvV1H1GGX\ngSQVqOfCdPibI8qDhB0gpeog9tUDas4uSFLxd2GrHKtVf1dAGkVStQI8uWMgTS6uZmZA4GBc\ns0EIUpuuOqPhyuQg1/QCstFWkEaXqbOex831/Pb30urvcDR4gOtiT/3SvowUeVSpvdUZiU7j\n4exO4vqlhRkp8jDBjok3s1HepqEdDaAIktGMhBtcKcMt2g5SwKORvZ+RYJF8BCEMdkAiA00C\nUhlN4b83BVKgYzurIOFRCMxIMZoDCW7YDhIczUXYDyKOa9J6kOjwSMhI4EKy9oAEbku1dGkf\nJGjdOEhilLfM2gmmjhUDILHhkQoSXnGQbtlPST6DZHBoB5bbh3b6aL7cipDBdSDBsYUEUlCM\nH9oCUgCLmjn7IKlluEVyo5+8jjL57haBWcXm8klrBE2a/kYbi3Fs8JSesdPfpTO2T39LwarE\ncdL0NzFJ3ZXT0g1sR5bdEqFFIDWJTn5H6GHW0K5HOR/NB+meWjPSKyvZfCD7OtJBuiQHKclB\ncpBuyEFKcpB2giR8F5FpPkjV89fNmQCpZnEZSHe1FaTTu4BxkMqkSeVKHKQ7cpBaJDQy3uQg\nddi4sNNBGiYH6bpCnintqv4eB5JS9It+Jlr+2e2kdSAJZd9ptjtgl/ID2XUgib+eLj1MQH11\nC0jV336H9myDBJ7XoQey8DmNUP09rHwZnTDQ9VDZmd1RkOYVV6fTAxsQJOASOATV34213wOK\nqnH4qG+yzEZ7QBpW/Q1cip0hu2sCSY7iRpDwQfMyUoBLsBLgRnGZtSwjUa/lDl/rn5sykuCT\nho8Z3ZSRmCu5nZ+VkRqrvyeCJHxDrtypJHcrh3YxORQqcB4DEr2OrP0g4cA+GSSwFWghSGQ4\not9Ks1ZONvCy7xioZfsgkevI2g6SFMksB+ns9HkpNropkAQbjwRJ6KdxP0hae7/1PJB4jCeD\nRGLHh3bVO9Xaz0jchnYJWZZAYiMnaHQPSKQHfgOQtlR/C1OzQkaS6q2xuXzSqZ+RJBusX9Lp\n70Z6poFEa+dNVRH3DQsAACAASURBVH9HMv2NyA88jOC0dAPbkeW1di0y+UB2c0a6pn1Duxap\nKchBGiNrIFn4jHRNDtJsOUg9oiMmB6kmB2k0SLWI1vaZA4l+TnaQhshBapQGy9kty0EaJQdp\nthykLjlIM2QSJDjnCCaYaVVz0jCQ5PppfFoyaxvIpC1ztxck8sBLqre0Uv2tVdpnLQLpmjmj\nINFHnAFuxM9qBlZ/s0eE0mnF54j0b4A7CtKC4mpyScKvqEOD5qq/yfZstAekG0avmFOrv5ui\nOP//jYIuxWsYl5ECXGqnRcvIQaLuNg/twoFQgOv7M1JUIiYEOGtZRrpizmhGOl4sg5SLlDWr\nhyyBlKuXTYEU8PCJBjhrC0it5hwkelrxTDIppXbEMkgBvJrNSGmDEOCsbRmpxZyDRE8rnkkj\nJTwJJGDRIkhagLN2gnRqzihIoHeqxdZFQ0FS+VU8GQcp3T4jcm4OJCWwNkBqMWcUJPJDHeTa\n6Myj3Ogjpr+l09L5bjr9HXGECSQbQQLR5AZP6ZkGEq3+ZtuxUbyoxHEISM3mdF62D+3ad+J0\nFK+DNEMkI73/zygWgnSqb/VAtlhd7VXOSF8z4McBDtI9OUij5CB1y0FaKAdpiEyC1CkHSVD1\nZgS1ByT2HCZtJ0ugJSA1h43KQTp0LYLnf2UAJDbNibQFJNXOA0CSD3GQDjlIDlLN2NkhNkEi\nc8ld1d/xEkiglls7H9iJjocu+bzoapD4j1WHkApd0BUkzQYpRCVuUkDh0cdfZ80FKdCwaQ88\nkPcikyCxx2HpeRh8Mpps0ervi+XLCFzpfHgncCjuyO4oSLOLq4FdahIZzQZnV3/zdqvFrdgn\nILVVf182CoxxK1F6BI8gr/z293kU58/aUaDIStKwoV31fGgZwYr4V1nrMxK2KYGE/mB+Ropy\nUNWAgg4NrU7NSBJIzDj3XmQyI8HK6qUgpSGQdD60M4JqYHxgIEl/K0jYJLmCQ2tBAhbUgG4B\nqZjRQeLei2yCFPlAYFlGisr50M50uOwSaidIgb0FV5C0PiOJdkJk0cY/ZLkgI3ELyDhtcySr\nIGn3BCMg0e5qEiSBqXJIlg2QpGgbA4m1OZJJkJBlBhK7kMmfkYR7JXImusxaDlKxy0zCK8ia\nDhKJn34DCiTay0Hi9x8WRuK9yCRIas3te2VK9TeekJXOB3dmZ2maPIAdyB2BpEbQoIyE5nGT\nSXZ5xOApPTcyEolbibAU0EibgBjFi0ocO71K098RhZG2ueiO87J9aKeJZ9V/EdUJUsf5ukTy\n0QKQOrVkaHdN+E9bMhL4JtKQaCpWBNnMSDU5SFU5SKNBEpKjIAep/3xdcpAu/M37D8lfbstI\nbBgn6Xkg8c/Lc0E6dcODrE82zAfpzBvT9q9RtJK2ASQ2M4MMP2Cy4VR2QJK6gRWQmrqog3TV\nmoM0zYmwzUE6k4M0wGmbwGw4fCiRtBMkVP8tzS+vAonM2YZS9IKDx0b8JkCCxUJwnh5a3Te0\nI09h4JR41hNAEp6QlWv4FH77+6Vp9dXcnGAwu8MgjS+uBjaQhfxQRPIGDc6u/m6xfphKIKGL\nyEbbQBpqtHQ2qQ4QudNBOo3iWpAiu5Cs7UM7HaRlGUmIEfAR+AFZJjISMKnEcWNG0m7kj8tI\nQjG4UZCE8up1Q7tsh7Q09sTqlm2AhOrU5TJ1B2mAaDG4UZDAtqR1kw16wbzm7SUTIJX/8kUw\nrw7SEAkXkuQglfMykGreXrIAEnDrIM2TdiFJJkCiX0ZOWvkZKXArsjdrQ7tkEoJka2hHyr+z\n4awngHQ2/S03+kKQyM9jIHcEkomfkbSCeexNKU8/pWfy0A4+RBDjKAerEsdxILHyb2iYuOO8\nWALpRCQTrQXpTDghzR3aXdL2jITERp5FrQlpTjNXjL30iIx0Igfpjhyku8ZecpAmy0HqULXI\n1kG67fPkIhykiljsaGe1BFJVq0E6QwfLQbqk9iBbA4l9iDcGkh7ZvRnpxJyDdE0O0iw5SFe9\nlULfwNf1neCfWAkSrKhms/LActY2kOTAhkBrhPaDdPKr4EnLQOK/g3JubjtI+dkbfECU10Nl\nZ7I16Le/O+2S98xydodAWlhcrQYW+bNQ/c1rm+R2bgJpgFHghDWxYs5A9XeAS7AS4EZxWbQw\nI0G7VctZuzJSLbDGhnasreV2XpWRNJBizZyNjBRRMEvhL7/nS1XBi4d22W4ZIwmWszYO7bJT\nGlgHqWqn9DLa4Z4EEhmJqDcGoLWTDfgrc8C2MZDIkAm6dJBO7USxwz0IJLq0BxLrjqLlrK2z\ndkJAHaQmO1HscNZBou3MQAr8IKDVn5GE5rY3tKsF1kFqsVO7C9kDSfuhZRJcVv4NJTf6rM9I\nIbmsFFwzc/FTXJ37GUkNLJr+bqRnNkhSZHE7S8GqxPG6V3X6u2KONjDfMBukASL5aPrQrkv/\njFPS2qFdi/ZnpEadp6NBIB0K54cAyekoOkij5CCNkoM0Ww7SHTlIolp+7RnKPEj4m4jivJ2D\npEmZ5kTrm0DCH9dbeu1IkDopaZB1kISPdZFucpDO5CDxsw+WgzRZDpJqyUF6awVIgUwtg3nc\nokUg4epuufS7bE+aDlL5P4sEBcppTyzhIpP1WatAYgET2lWKbNYokHBA4EML1ohiXX9P9Xe0\nAlIsMYexB5fwiau/J5Yv44L0SJZke3aHQZrgjpbIJ4COZTKNuywwuKj6mwVMaldpmY02gNRi\nlAQkwNdq49KdECOt+rspihtB2pSRotLMNPZQCzISdRRg2E7657KMFODyFKQoGB2UkUSi6xbE\nlict/cyMZAAkrfSbTpuaASnQocyh1SCB2mq5XVPZOvkCohmQ5K8gOEhdVvj9iBiMFKU9IMUg\nRI5cxaEdGSnSxhQiGOi/MA2kHK/2jMT9OUhdVhpiTdw5SOC8eFlpV37Hd5DuCXSHMiAgN/2d\nn5GAMRnz+SCxnMiMViYb1oLE0CHtKi2zBoKEB+MRvataEWg79BCQaO0yugq50eeCpJZ+00lb\nAsmMjASrkfPpoSHJMDF4Ss9dkOTpb9KuQTiQGI0SLZVdohF8vphepcZF2+FOApLKixGQWrQI\npGtaANI9rQLptkaBNEffAaRft+6C5NotB8mEHKSny0FyuQbIQXK5BshBcrkGyEFyuQbIQXK5\nBshBcrkGyEFyuQbIQXK5BmgzSLkS6/39kPwjmAGUbqWvtJD3x58tMsdWSz0cX8O/grrGIIpe\nfJfB0a3wu9ZzQydaLBVuyU1ek3cFtGuFQR4o4AQUQHJHe0ECxYQhlcKH9N9RT3z8jAF9X+rm\nF5iD50QuQVhD4IfOlRy9439B2spcLrRYwkT+l1EBUUx2p4eSNTIJVLYMKq9FV3ZBihmkCEDK\n79PuJeYkkAJaQ100xqnGBIMUGdhTRZDmhk6yqIEUyw0/5G8qw/DOTUiRNLIIEkzzECqgh4AE\n3pc7wuS71VlGUtfSltmqZSTcU1GeWpgzG0EK2i703wKDKkjkyHOQ/v77j0OznCO1gpTuBjgj\ngXHrZHMNIIGBXv7ryWoEKdDwzg+dZFEHKZRdxHeO4maQ6JHnIP3uwyRIx7HsM5KdjBTEQ+eq\nDaRAD1iIehtI9V1zozkrI318/HmWZVHqDFO5U4Wyjt4f/8Aic2w1jeaBZ3rodOnzc2UrnAZb\nFzrRYg4a8aTtysTPjCZvZByo0t+SDbmBCUi/9edKLtcFEXD+9ts//H2PEZfryaIZ6M9LPyO5\nXN9EeycbXK5vos2TDS7X9xDLSHtsuFzPFgXnd7//2xYfLtejxYZ2/hnJ5eqXg+RyDZAD43IN\nEAHpl9/vseFyPVsEpOAZyuW6IALOX3/5g8/auVzd8skGl2uAHCSXa4AcGJdrgBwkl2uAGEh/\n+t3PYd0vf93hxeV6rOiPn/z29fno4+Mve+y4XM8UAen3H3/4SVH888cve+y4XM8Um7Ur/7lc\nrlY5SC7XAMlDuz98WKi5+0GWtvR29eOnNhvRZN5g0g/2xpBKFOvu6GRDeD+ODQYKhZJzmx3h\n7aq8mJN5g0m5fS029OHp3Bkbwv3xtx8fJn6T60e6GZjsBz+i8X5q3mBSbl+LDV064ZksfxZ6\nwtAOvzMl8waTcl+16LP1TuQgXZX5fmreYNIDQDr/pCnM2n1pzW9Xn+ghINm0l309ZLLhR7QZ\nydYBMgQpfHyYqv52kG7pURnJ7Ge51ihCYP4EOPrTJF89egZINt3Fp4H0o2H4tENXQIrGHsTa\n7qo/0MKgHjJrZzy3XxnaWdMTQLLp7SUHaYRaP8A5SFdVpnNs+vPKhiFqjaJlkFyux8hBcrkG\nyEFyuQbIQXK5BshBcrkGyEFyuQbIQXK5BshBcrkGyEFyuQbIDEifZKlvKG+WSTWlu12r9uht\nMpj0SV/lt3DDQt0Io4PUIgdplByk2fqNJgsg/WOflvuL/6DIHEj/1KfF7v4nlYM0Vg7SKDlI\ns+Ug3ZGDNEQO0mStB4n+Zkbgm6BMgKT90AfcvA2kFnMPA0m+Iisgie72Z6STH6OxAJJq0QJI\nTeYcpNnuHKQ7Fh2k6wrwJYR3Xn0v4SvQSpC63a0B6eukryFcWQa0nW3KMgASjlxQjG4Cqc2c\nUZACeM1j/JD2pZe3rc9PHSRFK911gnTN3evM4RjNw2XazjdlgxpIWvBuha/mP0YeTWi0E6Rh\nRhvM/XTHQTpR+eNZQ7twdNIA1/k1FS0d2vW6W5KRpHYmS7opy0BGUvuqhYzUZs5gRsJd9Uil\nB/3h2IJHT/tAanDnIDX6d5BGC46c8kXkoQm2/9JikPrcOUiN/h2k0QJdFfkN1kBqcucgNfp3\nkIYLDJRiTB+WcVfdN7TrdbcMJOokO+IgobGnZZCQUWsg4c8XtkHKs4z5w0jI74vOLc8Bqcmd\nampoPy3T3PiGCae/8SZm8Dx6k58jnc0wf9JX+S3csM7cnTDaLxGStdbcef4Z1U/5mLfpUC0j\naYlqm1jCWQRSm1hGkiVZc5BatAQkPtxtP9RBGiIHabLWZCQ23G0/1EEaov0gBbLs13aQatbX\nDe0kY4ozz0iXFMS3b9kB6bq2gnRmfydIqjfrIInG94NUc+gg3ZSDNEEO0iVLodQFpLdpJjmW\njWyZNQwkcgZkI8h2Aqi7FudFN4LUVre8C6QAX1rq6DeClDsE6q0ojAZAyhZBWPF2cXmoVv0t\nS60KZmdCNip2yG5Us1wFaXJxNWxx5Bca7ARpcFF1eRWCitsZg3RWXD0yksAWaudyhFD9LWti\n9Td0Wd6SQAb0lmhURkJnoDbEZSwgsb85tHtod3If2ji0CwdCShszo/syEnUYkNm3DGQkYo2D\nhGus+VTUFpBQybeDdM1dVx391qFdcQycQz0ApJJFFZT2gFTSvIN00V0Ar1JQsbZONrCRPSXJ\nPkio5enypV0g5XUH6Zq7DJISVKzNs3a8iyKHBkAqXVHtwVJlc9FQkFQbCjHC5vYv9r2OWA9S\nU/X3dJBSCopRbGPWzps/I9kHSZr+hi+kxnpi9Teb/o4wcvIsPKm7VourmanzquDbkvwaqv4u\nIHXU0cv0LJz+xkvi7lIYH1drF+/El400Go9Vs9ECkJqkZh4rBpP+SVOcDlKDGjMSyExZDpJ2\nmIM0Qw7SbFkCiQ1IHKRRcpC4xF4Z+sZPRUtAuioHqSqlxaXNDhKXBtKlvzMHktmMJIbPHEha\nP7ACkuzPQRovB+mWJQdJOW9jKXWeqBcqvwOcEL1c/R0vxPdqQXjWapDIw6/zouo9IAkPPUg9\n/Un191yQuqM4H6TiJqYXsIxleTyQkyu/wTqZF+uo/r5QFUwfGzQXhGd3OkhzapYPwvOr+BQR\nhk8BaXJRdeUxPIlqNqqCNMFoZxTbq7+T+qu/qQ2964W243hmnZiRAlw2XQV1uHxoF47GD3C9\nGKNdYFtGYtaIS9bOS4d2vVFckJGOIt5rIJE/fi9piK2ABGuXs/aC1FBUbQAkwaUpkBqiuGho\nF0+6YDUj8fV1n5H6QIqldjlrA0gBvDJjrH/uB0l2uRukvig+EyRyIYZA4l1gJ0iSMXsgKS7N\ngNQUxYWTDWgl4I0pcZ511RDJdb00GySRGeUq9oOUbp4RhVUP3yaQSuwUl8zoUpB6o7hy+jtC\nL5Xpb3gw+WN55pE1tLphwPT3yVUcprk5ZmoBSB1F1S3Rmzj9TV2CVWKUwULfDgepKYp3wvi4\nWrvfDH5Ox/O7IJSFvjYs6acd4hPf1M+0oV2f1makXqlZx0E6lYN0XQ5SkYPUcpCDJMpBKtoB\nUiDLl3aBxKxIvcMESLVuuwekc62ftaPzRF16GEhJ+0CqhdokSGd9YzNIqr0tIF2Xg3TnzA37\nHKSL9hykoRKmn9NsZNYskKRCdFT7+3UAnaWn86LrQCKhUoqpQyQG94J02IMzyprRqSCV5y/s\n/HJcD9NZxkGCD8HI87tkq+O3vzurguVCdOiK7yNP6kj1d8sPVl/trkKooGHqORvkIE0yqNvG\nzwo1oypIA4wmF8L51bhCjMTq79YoLhvagQ+BvKvGmRkpktNRkPg+NjxYlpHQPAwOmdQPsgwM\n7QJco9eRNTMj0Vth5AHT4nvIeEbKA5S0thGk4kSoaAf78D+ycmgXkxUSsoeAxIusd4BEz599\nKPE9ZB0k2A2i3BMWgQScsJsmcrnrMxIZDT0OJPAOpv2sVSBFeagZlfgeMg6SkFc3gYTuWZI7\nmv0PrZ21E0w8BSRkTDK6DiQ9YEojx0eARCpv+fhpGUh5+Aa2kX2s+dd+RhI6wJNA4l/iBEfO\nBql3sgH/C8ZBYpW3YFPWecvzN03nRi9pghRNf5N9xSgzx0wtmv6WIojC1x69OSDl1mwzymCh\nb9dNfyPdCOODau2ugTRE/ygJWZnaT89FE9JikNql5KMxIHGF80OghIyEEpODdFMO0ig5SLPl\nIN2RgyTLQdoHkhR7B6lRpx13AUh8DuHk6CIHabKMgKT3j50gdd3114B09WgHabIcpEuuBDlI\nDY5gQa0y3ciWWUtACsSiNFMqTX+vB6mtaD1rCUhyZTdxxWacsdHJIN2cALcBUgokfH5wtky2\nWqq/75cv08d0+NlheXbH3IkgTS2ubitazwbZ89gJ1d+sDYE7sI+ZRkY1kMYYBW0quTx5JFv7\n7e+F1d+cEWBTXEdakZFEi5FsDIK7HRlJ8MtuUVkrMpLYltBJ4JuZ0bkZSWjDqh26biMjEcf4\ncgKuCmb11TtBwlXgDlLNkuIKBLGkAqnAehlIZ/XfqNmTHgASOE5GaR9IPPc7SKolxRUIYqXp\n40qQYr3+GzV70qNAUjZuA0lYOkiqpXNXdkCScZe2J9kAidzZtV7KL+ulLSDBL/IJfSHLQVLc\nQFd0aCcanQ9Sx2SD1aEdnE/snv4+b/mR09/HyhHOwCO8q/o7O0UvoAZcrltuj97I6e94dNUA\ng8hMC0YZLHumvxnnN8I4eGh3XdVk9DpiAEhMjabFjPSaAqeeBnrrEc1IVn4gkknORcNA4urq\nlmoucpB08dGlLgdplBykUz0NJD661OUgjZKDdNi6g0v1b/cM7SoWTycbRoPEPph3yBRIgSyh\nloNETWnrLy0Dqa+hg/Je1BaQaq52gHRZpkBKMg2SKAfpohykmXKQVDOs/FgqUo5CWXBQSq2L\nZoN06TfAk6aDdKVquVb9PR0kqdY/pD3lgtgH0S0g5egqdepZSzMSftJVXugecrR8SLJ1Uv09\noHy5rZya7EvudJDGFFcnb0oQxSXoAht++1uq9QcggQvCkeQgTTYagRnSIen9Uq7+bjR3A6QY\nyYu4BO+FQ4rmZ6RITiugTvclzc5IsHX5Jn171oaMFEnUUCOr7bwjI/GQBdnc4owEq3pxHMme\n4w6Vt1kCCbji18PKgheCdFa1LBdVmwUpkLGdAZBYnXrR+qFdJCGs3kwNZiTsKmr7klaCFOtV\ny8hulg2QYhDbGWo/SJz2IsMg8ZuVBZCYQ2Vf0lqQ9EjRIGc5SL1ejYDEQii1fb69mwQJuOKu\nN4B0/SvScQdIxF4lwMjqLpCQGRtDO1r8iwzqZcHC3DK6hvOWHzq0K66YJaEsWDW1c/obqj16\nw6e/oTcWRKWOXqZn/vQ3XrnTCW+CNFEn6SjeBemWcBqK8/upMCiqCmUj0c+Mod0FkXy0BqRm\nKfnIQRolB4nKQSJykFrkIFE5SERTQFKiXA2+g3TWN2v7l4MkqeWrATtAaof+ASCdXoyDdPUm\n/yULIDX5d5B65CBdkYMUyeuvBCT1x77R1OL96m96DZfie++XyReBJExw40cG8BDUPzaBhGq/\nsyc47X1S/T0cJKGfiU8SxLn5XSCl1kXPjiJ++IW2w0dM6W/etmrV32PqqzWztWV2R57CNqgz\nlsii7grV1UOD+GHsJIO6ZdjE9UjSx7GDjbLulyNF+6LwHEmq/m42dysjRRIsrRfEHGUlwHFB\nRtLMautQ64Z29RCq4duWkYhvLbJZkzMSOh9tbrqRd8JdQzvB7DNBSjXK6S5P55+2ggTqwW2C\nBOrRmeeT6u95IMlfUcDfTqDmHKQ7ZrERGaW9IEV11Je1PSNFAlKko/dDq0AiARM3MnMO0h2z\n1Ii0cTdIaf1JIMl9dRFIXX2zaPNkAzUbyDJv3wmSZra2zNoGEgkh3ZW1HaTSxOJcU9YCkHj3\nA20v9c2i3dPfb7dsajEtpVV2DectP2j6m5itLtVTzwRJm6UN+BAUvvbojQcJtymZWV5d/U26\n3xGwet+k7i6F8e7Qbpj0jPSb44j7Q7vLwukoruqndckZSfOzwaAkmpBGg/SlprYWD9r4GWmY\nHKQOsYTuIL3FRzpdBzlIp/peILFBiYN0iI3Wug7aA1K21bitrskgNQrM5SiTDdjCkn4auCEq\n0yDpkw1xOEitPmQ5SKMUxLc2QKrJHEhBeb8apL6O6CCNkoM0SA5Sv9Kvah8rZeZRKAq/Uv39\nG+1iRohM0+anDGEHSMosfJrDFSZyk3aC1PCr6kXTQGIxE33wCnvUDTeDdDh6r5THXfB5Ud6Y\n1nGAP6u//T2zfBn4Kw89k9vsDoDUVFp9zZ1gpthBYWMGO0u/R4XvbTu74Z7Rp87Iqr/HGWUx\ng5Eq+5hNiNGu6m/pGoRuoPYNnHb3ZKQAlwikDRlJMIPQroRvb0aSPee9KzJSJXbQh7r7rd1D\nu1hvbHQHoFW5SduGdvQaLIJ0eh+yAxJsYFhtfWgPSNmHbDPLBkgx/2DtSUaKQk/YBVJkQ1CD\nIMm/BGwTJLrRAkjFh2izyEG6ewG2QYpiPzAPEt32pR0g4cZ9FEjsO1V0oxWQhLgDt1kLQRKC\nJIOkVH9rfjZ8RkKNfmgqSHrsIh3awWWREZAOW7DwtlLJTK7ivOU3Tn+rppZPf8e6wfPoTQYJ\nVvvjngBPL9NzByQlZtQHs4n/kRthHPpzXOHGbjUfzQWpTf9IU9LCfqrKSkbq0j/RlDQKpCFi\n2cgcSDwDUTlIHWLhdJCGyAZI1bLb06pcB6lH36T620Hq18mw79cOkhAeuqkWwd0gnbVu1naQ\nqk6tghSU99KWXzlIgqyD1AwP1FaQTh07SJPlIAlykKDGgoTnIEnp7TEfTrYnLQJJKlWGHuWf\n7FgytBN++5tNd9MJ8qSpIN0prKZGV4EkuQnsGQz94G4FJO1p2BHn4xjhYdhnpfp7bPmyWqr8\nJhyvZ3cQpDnF1cLZaSAFw9ngzOrvWpSgV2of7s9GCUgTInmY1tyIDpM7DFKXuXnT3xCVACMf\npKPXZaQYWdeIZJ0NARZlpEjjI92ZRIMzMxJqL8kEh16A/dC6jKS4qTo0lZHe76QS4HxTCOTo\nL20BKZCxaNpJp+rNgJQMU4P7QDoprKZGHaRm94LjQtFxhFCesS0jSX5pBzADEvgDZHAbSCVy\ngn3BqIPU7D5ip/g97Lp2QBIjC+0ZBAmv7AIJvNdAwkYdpF73AYS6vKdoFe38jAQ9ihFeD1Lg\ngawZnA6SQjUwpnbdPSBp0DwCJFrrzUqAAzwKzz2eWx4PEvNLt6unngkSrEwGE7bUsGjwPHoX\nDN4prJaNyvSMzUiS6XFfQZgM0pmCvkvJR6NBuiaSjyaAdFP/ACX62WwwiSakqUO7bpF85CCN\nloM0Sg7SAFXrvx2kO3KQiL4JSHgqoemidoIkGpQnG4iFVf30LIQ7Qerqs6tAOqyFPncO0j09\nCiTR7OaM1N5bl4JU5jwa5SDdk4M0zt6JHKS6+AwpfeAg11sX7QWJu7MBEvx/7BRK6rP2Du1o\nmb9QX5+0EiS12ps+TMjaDpLwMI6t1Z6FfarV36OrgmX7wpO6AN311n4Pc6fdlmLE4UMgrTTI\nPYn19dkoBmmyUdqsYD1wc6T6uzOKA0GKqLErIEV+DbszUuQujWSkSOMmgLQ7I2GQJN9Z24Z2\n53fzaCUjxQgrf2WQcuV3oGnVBEiwcNkeSMUcC58FkFjwSGJ/aQ9I2Blt7iI7IJWlAlJJsEQm\nQCLrWSZACvgtkgWQiGXU3llbQKJDPLhEehRIyjU4SCfOKFNIhkHCbneApA3prILE0EmpvXIt\nRVtBEiKObqT7QCrOQDR5+KyARId2zOgukOjQThzB7wdJnv6GRdWn09/nlmdmpJPpb9XU/IzE\nKsHF6e/26M0BCU1/w5dd1d/JGe2HcP1OJ5wF0n3tBOlUG0Fq006QurQUpJrEyH4HkFySWkFy\ndYgP6QbIQTItB2mG2JBugBwkl2uAHCSXa4AcJJdrgBwkl2uAHCSXa4AcJJdrgBwkl2uAHCSX\na4B2gpQfi+VfXg3oe8p5Q/l/hArwz7b4Q3v4EWucNRoUHS91SF3mrwDhxs4FmvTtkrgOaeeN\nIKEKx5D/l0uej/8FcCiqft7mj9nJR6wtRTgzKDleXyuBKsOP/xs/3Ni5oUP+Dx4wO65j2vkB\nIIVsvdSSb/WX7ZAAx7jIWatB7nhD0dEpSKGwkwcgIC3sB6mpne2DVDbE3BNsgETvVKuMXTa4\nOmUylwpIP07m3AAAF1hJREFUqauit6XZd4PU1M4OUr8/PcBre2lLRsJHsB8pWOxSHdpxkGIJ\nrz2QBDcOUr8/NcCL++ipwUCOiHG5x5sZiZifbvB6O++ftQv5jTprlzaky1rUGUR/YAM9Yvn9\n/sRgEByvBwm5zNN2TbN2sRy8ymC82s7+HMnlGiAHyeUaIAfJ5RogB8nlGiAHyeUaIAfJ5Rog\nB8nlGiAHyeUaIAfJ5RogB8nlGiAHyeUaIAfJ5RogB8nlGiAHyeUaIAfJ5RogB8nlGiAHyeUa\nIAfJ5RogB8nlGiAHyeUaIAfJ5RogB8nlGiDLIP14v/7UZiOiXqZ+/LBqz3r4gAwbTabOzRkG\n6biE/GJLILAG3UXr4QMybDSZajBnF6Qf0W6As7v3W4uyHT4gy0a/BUhGY5tlHKRouH8SGTf6\nbUCyOHaOJa4mzX3JeP8sMm70u4D0I9oM8DNAsvkZHit3U5NOc/97Okj5xZieAZLZ8AFl4k0a\ndZAm6wdaGJTt8AGZnv9sjaKDdFUO0ihZNvqjvDpIc+QgjZJho7CRHw6S2U/LzwDJbPiA7BrN\nhSuPrmxwuZ4jB8nlGiAHyeUaIAfJ5RogB8nlGiAHyeUaIAfJ5RogB8nlGiAHyeUaIDMgfV56\ns0imzZ24+FT37NBn7UXdudQdehU2od1ZDlKLTJs7ceEgdbp7OEj/u09rzf27Lhsg/UefNjg8\n9J99WhzN/+oT/FMHqUUO0ig5SLPlIBGFnoO3gkSd1pw7SLfU0CmsgCRadZB6nD4BJNmjgzTZ\nqoPU49RBGmHwp5LNkFfB68+taQ394UqQAnw5bElWs1aAFCIy8rWetqOIgTCWP94DUrZSIvq1\nhSxRJFeC1N3MhkA6bJcuEHOcyxXF9JL/7PPzsxOkzzt3qtJPsUVqNburgSTrginSJ0EUg7Qb\ndIHPz06QLhnkjrNTHD2yRJHsBOmW0c5m/umuEyRobgZI+RroKr554fS6MiPlfhrgOreatSYj\nRdrU9HZPe0LRloxEo1dZZq3MSN3NbCgjpRtl8glXAxj2WQIpDVC41SxLIMEwZm0BCYRMBYlG\nch9IDc1sCaTkNA1MyiAO3gv2gwTTfnLCrGZtAgk4ZJnIAkhRGI8KS6jFIPU1sy2QYBdIq4ZB\nQk6CEmEHqWb7CSA1NbMhkLJf3AXo+90gpXtT+o/1X+JuCUjCzV0DiXXRLSABKzCKlcmG1dPf\nnc1sCKQyoxjgKp7+Fq9hF0h0otbQ9Lf8Andn7clIwIow7Q3dZu0CqamZLYFErqFdpgusV5gT\nA9YaRZPV35J5r/7uVS9IlbyzHyQ5GY01dwukStrZAhIfcRyqpp/tIAkJZzNIoZcjB0mIWHsU\nrYHER02HHKTZ+tWDdEvmQNLkIM2WAZD0+78lkESXxkDSI2kApEqad5CGyEEaJQdpmuh0KBtD\nLwYJP5uRa9TL0atBEtyJLrM2gtQXycUg9Zl7AEjS8zBwa9Cqv5XS6ov11cwQeGWPjUF8terv\n9e6UR4ly9XfN3pDq77pXOZI1kCYY7THHqr/rASTmFoKUWz7ATpC0emgXjtgSU6jbZi0f2inu\njrd8dnnn0K4rkquHdl3mHpKR8hPmlJ6QtoJUCqrl4uq9IDXULZsB6SySW0E6M/ckkPLtgKK0\nHiSY9vGtKtIIbwCJuYuxUre8F6SOSK4HqcPcg0CiQ7yijSCxwTP1thUkaVRsFaTzSG4E6dzc\nQ0CqVgWvn/4GAyVo7ti4GSTFHR3iZ22d/u6J5GqQusw9AKTTquCdICVTrEY9aydITXXLRkA6\nj+RGkM7NPQGkL7EBCVSlQ07qqx0ybe7ExXyQeqSy8lnbudQdJsUYSHwoRyVmJC1Nre4LckbC\n6WlrR5Uy0n9gOzZAqmaj7SD9lyYzIKnVwFkO0h05SEP0AJBOZQYkiXcHqVtBfGsHJPG2/iyQ\n5MxkBiRJRkDSc/p2kGrDDZMgiXKQJstBum7NQbqjAF9aypfXgIRqfum0ckQ/5YHcbQBJiGCl\nbnklSNJPkXNrKLJFS0C62sxGQeoqX+747e/rVcGlXyaLgW8MgrsGkEYXV2sRRHazQRGkSdXf\npfBPaVTxVyMPoxpII41ebObab3/vq/4ORwcIcL1cJ58OX5GRKNLcXiAtf2jH0E6JIO+dX1qb\nkaIcPR5ebnVFRrrczAYzEu4GDeXLO0EChcBWQTqrW94IkmKNRvbQRpDOm9kmSHBskkzr5csb\nQeIDESMgsQjCyFkBSbNGI3toH0gNzWwcJHUUgLQNJGFpDSRo0RhIqjUa2UPbQGppZosgpRSU\n/pNiji5kC0hSQTpF/0s7QFIiKPXOzSCJ1mhkD20BqbWZjYPU9rPLK0DC87GkIB03//bpbymC\net3yxqGdYo1G9tAKkC43s0mQesXbueXNXfHsLmqPuQ412NnqL0tlZSRITI3NLJGiIWQWpNZk\n9NKI6PLErkvKQNTK1o7Kc5FRkFgmipNB6mnmp3wfqarlIJ0XpBc5SKO0HKSeZn4iSOza1oN0\nYu9ksoFZmdtRg/g2yw5IIHKS0fUgKSaFt+ZBkgJqHKS4GaTaPdQ8SMLbrC0gNUfTQZogB+mS\nHKRpYpXB4oOkzSDhCvWVQ7tLxdQnP34i2ZkFkhw58sgjazZIt0rTjYOEH9bBYOcjWqu/h9ZX\nU4vkKQN0J4BULa3ucXelmJrchlj194m5keGTI5euiRmlII02eqM03f5vfwfwRuypX9qbkdDn\nY25vbkaKpMPRpuf72FhlX0aSIyd007fmZ6TYHc2iB2SknGCPDYHGePvQrljdClJbMTWd0d06\ntEOXQVImNboYpL7S9EeARDMqJWkzSCXn7wUJhIne61EISQ/dOtkgRA7c91d/RopXonnoASDR\nzAqv7aXtIFF7W0CSwiPtixEb3DxrxyJHB1BZS0HqieZLDwFJLAFP2guSEN5tIDUUU6N++qXN\nn5FEkITJhg0g9ZSmmwcJ/AYFvZ6szRlp5/Q3fGkspvbpb80NeuksTbcOUpMqHfJ2X70t0+ZO\nXKwY2rVLZWUQSAPcYVIeB1JTRmKpaZGEjFTTYndR+T7SOzfZAok+RsqGTID0HTKSg3RHDtIQ\nOUiT5SCNkoM0W2ZAkiZt94MkfDKG2gNSqK6KcpCGqBJqMyBJXreDFLgnpPUgsecXzwCp7tFB\nmuzVQRIdOUhF80DCj8aUevaifSDxByH5KUjSbpBCeeiBvyeQtBAk0IjJy3s7fG6Uvi1z9hxp\nCkhCzxN74NmvCMVy/t0gtf8KfMeP6H9p+vcAoL2mH9GHGugOmAwlbOSbNMqP6H9p+NcoaGVA\nat2In7fDp9rQKAVpxvc9tJ7HeiA2Z/ZrFAEGV7mMon0ZifgRIrw9I0GQsjdocF1G0nokdqf1\n1TVDO6XnJS9KD4xGMxK+HKWevWgjSNiPg1R3AppPAIl8WSGtZ60HKQ02U94EptjPC1kFCeZY\nfBuL0Q5IcBQC3jpIqhPgCA+kcONKN/1FILGeF8twE5p6wmckeDlsPBBZjLeBRNvcQTp1AhxZ\nBwlFivRAdD0v2QQp3QjSf8J4AGgrSOQLHiztO0jISSRNSUASlllrpr/lnkdtM3P2QTr/FXih\nnVveDLEp/kgP8rfPXPIY6yA12Bk7/V1ChF+ELyughlZZmQQSa93q9LdAigWQulRJPWv6ak2V\nrLPf3Jf0hDQcJFFsCKcJJ6RZIF0Vmvx+b3KQRspBOpGD5CC1yEGqik0j63KQbon9ZhCXg3Sm\nWgR3Z6RmOUh3JMwtMM0BST3r6T0UHbAdpDO7q0E68aPvdpDuyEG6KwdpiYyDFPAUpDyBOwWk\nXKNMpzxR8TIp/kYzpG+tA4nOzCK7yRyfn58BEmonvYhaOKxS5T8ZpPL/0SBNc2vLLOMgkad1\n6AneW3r1982q4PQ8TnxSiAqpS1cA68mdANLwmuXsV3uwScyh8nQNpDsGYTspfmhzCrtJlT95\nHttVYN0SPxIoNZjSA1lc/d3iDZjbANJxayUDgHlDO54Bg7BDXCYty0gBLrldrQvMGdrRdsJv\n1eakIKF/c3pGiiRAgQcVrSM9KyPtASmQwUmk0aZ1y/Cf2QgSsrsRJL2IWjiM7AbaChKt+q5W\nfz8CpPeG5RmJeGm6bb20DyRsdzVIAbymE7Ii6q4q/+0ZKZaLAMtDDtLJmWVOHgASsbsNJBpD\nBSQWXWLTDEjKxoeBlG5t6JhFn5FSZpdBosuktSDRHimDhG6mU0AC7QR9sPuQfJgYyOkg0a6m\nNq10O3oKSGXaMZbXpEqHvANSniYGH5FeQWTFy6RuGc2MzjGnGA5kCexCsyh+DXZugVQvomaH\n6VX+KiujMhI8aff0t0CKKZBapCek0X31goSM1JCaJmt+RpognJDmDO2uy3pGapGD1CE2KHGQ\n3nKQHKQu0UGJg/SWg7QfpFob7AMpiG+Z9oCkOKoZnQzSTT0GpEqIt4J0diPbA1KoriKZAqkm\nB2mIHKQbrhyk6bIEUq3utlIVPB2kU19oCpx8BFkHEnTAXOkTt3NBYr/kzR8VoMlv/BeIt2Ug\n0aZEve7tij+FMQUSexhHliX65Y8+tervcfXVLb6QtWKv/tvfQ9xll9QBNkl9Z4MaSGPCxyrk\nlbAdhwb8F6hMHYHUWWDdZTl50po2cJBsVX8H/AIuI+bIo22H5mekc19KP109tIMOAvfLYzc/\nI0UtbCGS91Xi12Wk2i2T39eTTGWk14tQa512bgWp7ssCSLgGnXZbWr+ctAokGrYgmTYBUiCe\nyPpTQIJrlkCq+zIAEnGi3f8pSotAoo4CN2oFJGKdrifTuBeaBUm6DAsgKb72g8QcqCDhlTUg\nNYbNQRohnjtJXLeDpPuyAZI4tDvpn5NBAk6UsAW8pIHOMvMZKc3hob8yBxKdEJWKhglIFVrG\ngVTzBVfLH6wxB2zCMu/26e8GO7cykhK29064mRAvl6lrLwNBYk2Jel12JXZCRMo2kK5KS0dx\neF+9oIWTDdekZaScl+4P7a4fuyMjNRolbv+LKDpIY+UgNR8W6ptMgIQ/KAE5SJPlILUdR78o\nxzeZAKmM6Mn2h4AUyBJpJ0inHWUlSD3jqKy5IDWqxbkRkJTO+DCQRDlIrWYkOUhXnTpIq4x9\nyUFqkYN0x5JcZMuKbeFBcB43axVIkkGpRBi5mwmScPK0PT8uoIabq78ngKT+vDad9hbn6TeB\nxMvWpbn5jSCVJwnFHloG+SAyZfIpVn9PrQpGnqj78sTh7a4G0l13PHQZpLo3aLAO0rjwQUOo\naY8dLLzUKAKps8D6ugRbwHRxR0HqMDdiaEcDJgaSXQbRoowUyIpmEB85NyOxkxN26t5eWpqR\nGtwFcnDWnoxE7Yh387j3MxIrqs3VC2KxrR2Q6gbtgQQj2lz9vR2kQMZ224Z21Ls1kGibw/Wo\nR3s/SF13/cUgRfD/eiPe4yNFySxI9K+3TTbQkagxkNpTuzGQmrpDlkGQsEEHqcm4bZBYPbDY\nJUOsTDbEtSAxoyQ9rQVJOLkGEo1o1kqQiF8WTrn9D238jCSChBP73ulvFDCpPrhp+rtCy6zp\nb2CczY7i5p9pTj85fpEi2mNwXEaSjJAC8HqZuvYy8zNS0/S3QMqyyYZRWvUc6ZIq6WgASK0b\nK1Lz0AyQ7ug/cUpaObRrEExGDtIEOUjXrWE5SLPlIIFN3Z3VQRqih4K0ZLJBavfuvjATJF0B\nLapaCFK/1MmG5SAJdyhtssEwSOwiHKRTtTo1B1JQ3m8F6bQvOEgdZ1W2VeUg9cpBGiChwDoc\na6QaHGgeSLCyBkx7C7XL/dXfzebUmMDTSQfJxlqqv4mdaSBJRerw1QxIOZr8ccIhWyCxp19o\n5p4e8HY1r/qbfTUhHggRI0FwnN2pILW6k2MSIgsQf2yohRIZlECaX1QNIyxcg9TOGKTT6uqh\nRrkpZA5Xf7dYm/rb38WaZDmwHUlTh3ZCl9QcCv10QEbSYqKfvuoaRe5LezOSdi2C2+1Du2oo\nDWYkxbJxkFjN+qG1IIFaZc11S/U3sbMIJFKkXt6/ZQekwM05SGdu3qeWbkhaKtgKUsTDYf2I\nLDsg0Y1mQYJGkxykEzePAymt6yBhgyZBktrZQeqzK7W+GZDEL/RVa5bHgCSeIcSeyQbNoC2Q\nQGObHNqxtk6yBZJQanv0lzx5Jsw8VjrkGJDKuUv81Olv4u6+OSUmR1tq09+qsY3V30w4wslp\nCCTW4OTaywqQ5O8nQHeYlJ0gXZKQkRpSU4/C9d1qRvr3e5Q3GWuRMPlN7UwDqUs4IS0G6VTG\nMtIl7QSJZSAqB2mUHKTZmg1StaKafc2QyEEaJQdptuZnJF1iT26abBgCUtUa+5Qhah1I1ErF\nmrRrIkjiPBw7pHrUTpBU26eNjw/YBRL7wCnZ2wZS4F5EWQKpanYBSG2HOEjozX05SJccqesO\n0jXxmm5Y+av+ejU4/NACkNQyZWn+2QRIoUwgi6HMmgESqvVB08XyU4PyROHoEXBmP2kqSKJD\n+kCB+QbanZF4TXeAOwLZAdcPt2L1d9agqmC9TFnbltzpIE2uWS7GRPPZoADS3aLq4xwJJBAb\nGia0TiKKE/7U3/4GwZH6YtlFfRd3O6u/IUPFVhB2iMusJRlJcaM5zNo6tAvEEwtdnJKRQFPC\nU1a6aQTFI3RX0uyhnQAS26VGcX9Ger0JZGwXYRxDOcAISIHbfAxIDdXfK0EqLQ/+wAJIoI5e\nAIk/ErEBEtkiZyRh/a0tGYn4fw5ItBNMBAnkmRjFMAX8N5ZAiuxjh7C3yBRIMIYO0k3pIGGD\nNkAyN7QTHAt7i+yAlABSQRJvZF+y9hkJ3ausgcT65yyQ3ufnN3XW0iCU20DiwRKWgu+irSDR\nmu5c8wt/aeIwz6rBiyodclRfld0IP4jBpr8XmNMtSxlpRfV3PgdqXilMeKIcRpT1VZWVERnp\n9vS3QMoykEZpW19tkWlzJy4ug5QVzg9p1kSQRrl7OEgusxoJ0reVg+Sqq14X7zrkILlcA+Qg\nuVwD5CC5XAPkILlcA+QguVwD5CC5XAPkILlcA+QguVwDtBmkXOyUC9/IFlgQBX7Dc5Mz6CCA\nTbAqbZE/1SPetSd4qstUgxmO1wgimCr2SlzLYUJd3CSDsJFL1aDU+vgf2QsSrGGNR6kr2lJq\nelkl8gZnR0NXvS7yp3qUHa0NnuIy33EAHqmBIVelxDQUz/Ns40Jq1Mil+/HWJ46sgxToMTHO\nDGrdGQep1D2nXaZACowscyC9yYn5/l9u/QikmQkplhhRkBDuuDs+DCTtzRZnEkiUdVMgKeFc\nqjOQ4E0pgxWOTfnmNDGsrRkJ3ygfN7Tjb5Z0hUaQyF3KPkjLOToDCUYX/X4b/F/5l6YaPAMJ\nB/HpGWlNV/imGWk9R1czUsg7cS+YafA0I0UQa1MgwTHoEWGyJUayBcxMrXdW5p2kLSn0y3pr\nW/Ti+uCpLlO2yQO4kD8jpW0gsFKIZxuE50uJUW59/I/4cySXa4AcJJdrgBwkl2uAHCSXa4Ac\nJJdrgBwkl2uAHCSXa4AcJJdrgBwkl2uAHCSXa4AcJJdrgBwkl2uAHKTvpg+hSf+0oer7VyYH\n6btJAkna5hoqj/B3k4O0RR7h76af0Pzu45e/fb39++8/Pn7/969NL5L+8ruPj/CHzfa+qxyk\n76aPj5+8fISf/MTwRdBvE0j/9vGSkzRFDtJ308fHL3+Pv3zx8sevlz98/OkY2v32488x/tVH\neXPkYf1u+vj4Oaz721ci+u2rcT9+lz8j/e3f/viLgzRHHtbvpjcpX68fh9K2X9Kqa7w8rN9N\nKki///jtn/7tbw7SHHlYv5vo0O69Lb383UGaIw/rd9PHxy/x7798/PFrnuEPMf7552oC6S9f\nO7zFp8jD+t1Upr///pr+/vjr17bwxZV/RponD+t30+uB7O9eD2T/9vuf6ekvP9/86Quk+Fpz\nkObIw+pyDZCD5HINkIPkcg2Qg+RyDZCD5HINkIPkcg2Qg+RyDZCD5HINkIPkcg3Q/wdaIUFb\nw+NWqAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ap_top_terms %>%\n",
    "  mutate(term = reorder(term, beta)) %>%\n",
    "  ggplot(aes(term, beta, fill = factor(topic))) +\n",
    "  geom_col(show.legend = FALSE) +\n",
    "  facet_wrap(~ topic, scales = \"free\") +\n",
    "  coord_flip() +\n",
    "  theme(axis.text.x=element_text(size=rel(0.7)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "#beta spread topics 1 and 2\n",
    "beta_spread <- ap_topics %>%\n",
    "  mutate(topic = paste0(\"topic\", topic)) %>%\n",
    "  spread(topic, beta) %>%\n",
    "  filter(topic1 > .001 | topic2 > .001) %>%\n",
    "  mutate(log_ratio = log2(topic2 / topic1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#beta spread topics 1 and 2 visualized\n",
    "beta_spread %>%\n",
    "  group_by(direction = log_ratio > 0) %>%\n",
    "  top_n(10, abs(log_ratio)) %>%\n",
    "  ungroup() %>%\n",
    "  mutate(term = reorder(term, log_ratio)) %>%\n",
    "  ggplot(aes(term, log_ratio)) +\n",
    "  geom_col() +\n",
    "  labs(y = \"Log2 ratio of beta in topic 2 / topic 1\") +\n",
    "  coord_flip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}