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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Science Programs\n",
+    "\n",
+    "[Data Science Brochure](./DataScienceatUW.pdf)\n",
+    "\n",
+    "Consider Data Science at UW!\n",
+    "\n",
+    "The Statistics Department offers two undergraduate programs for students interested in Data Science.\n",
+    "\n",
+    "The [Data Science major](https://stat.wisc.edu/undergraduate-data-science-studies/) is a great fit for students who like advanced math and programming and want to be a developer of Data Science tools. If you’re ready/interested in declaring, register for a [group declaration session](https://stat.wisc.edu/undergraduate-data-science-studies/).\n",
+    "\n",
+    "The [Data Science certificate](https://stat.wisc.edu/data-science-certificate/) is a great fit for students who are high end users of data science tools. If you’re ready/interested in declaring, visit [our website](https://stat.wisc.edu/data-science-certificate/) to self-enroll in our canvas course."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Warmup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#A function to load a csv file\n",
+    "\n",
+    "import csv\n",
+    "\n",
+    "# source:  Automate the Boring Stuff with Python Ch 12\n",
+    "def process_csv(filename):\n",
+    "    exampleFile = open(filename, encoding=\"utf-8\")  \n",
+    "    exampleReader = csv.reader(exampleFile) \n",
+    "    exampleData = list(exampleReader)        \n",
+    "    exampleFile.close()  \n",
+    "    return exampleData"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 0\n",
+    "# Load the survey data and split into cs220_header and cs220_data\n",
+    "# (this will be used later in the lecture)\n",
+    "\n",
+    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
+    "cs220_header = ...\n",
+    "cs220_data = ...\n",
+    "\n",
+    "print(len(cs220_csv))\n",
+    "print(len(cs220_data))\n",
+    "print(len(cs220_header)) # TODO: Explain why this is 17?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# these lists hold parallel information about the island names in the Caribbean, the type of pie that is sold on the island,\n",
+    "# and the price of a slice of the pie\n",
+    "# Caribbean Pie Rates data\n",
+    "\n",
+    "island_list = [\"Aruba\", \"Jamaica\", \"Antigua\", \"Saint Martin\", \"Saint Kitts\", \"Grand Cayman\", \"Cuba\", \"Grenada\", \"Tobago\", \"Trinidad\"]\n",
+    "pie_list = [\"Apple\", \"Apple\", \"Blueberry\", \"Pecan\", \"Tart\", \"Blueberry\", \"Chocolate Cream\", \"Key Lime\", \"Banana Cream\", \"Apple\" ]\n",
+    "rate_list = [5.99, 3.99, 7.49, 4.99, 2.99, 4.99, 5.00, 2.00, 3.99, 4.49]\n",
+    "len(rate_list)\n",
+    "\n",
+    "for i in range(len(island_list)):\n",
+    "    print(island_list[i],pie_list[i],rate_list[i])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# warmup 1\n",
+    "# TODO: this code attempts to find the island that sells the cheapest pie and then print out\n",
+    "# the type of pie, the price, and the island it is sold on.\n",
+    "# **this code is broken in several ways**\n",
+    "# fix all of the bugs and get it working correctly\n",
+    "# Caribbean Pie Rates program\n",
+    "\n",
+    "best_rate = 0\n",
+    "best_pie = None\n",
+    "rate_list.sort()\n",
+    "for rate in rate_list:\n",
+    "    if best_pie == None or best_rate > rate:\n",
+    "        best_rate = rate_list.index(rate)\n",
+    "        best_price = rate\n",
+    "        best_island = island_list[best_rate]\n",
+    "    else:\n",
+    "        best_rate = rate_list.index(rate)\n",
+    "        best_price = rate\n",
+    "        best_island = island_list[best_rate]\n",
+    "print(\"The cheapest pie is on {}\".format(best_island))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2: Write code to answer the following questions about english_dict\n",
+    "english_dict = {\n",
+    "    \"shenanigans\": \"silly or high-spirited behavior; mischief.\",\n",
+    "    \"bamboozle\": \"fool or cheat (someone).\",\n",
+    "    \"gubbins\": \"(objects) of little to no value.\",\n",
+    "    \"malarkey\": \"nonsense, rubbish.\",\n",
+    "    \"gnarly\": \"gnarled.\"\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2a: What is the definition of \"gubbins\"?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2b: How many words are in our dictionary?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2c: Is \"badger\" in our dictionary?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2d: Is \"bamboozle\" in our dictionary?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2d: Is \"nonsense, rubbish.\" a value in our dictionary?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2e: How many definitions have the word \"or\" appear in them?\n",
+    "count = 0\n",
+    "for english_word in english_dict:\n",
+    "    pass\n",
+    "count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup #3: answer these Q's about dictionaries\n",
+    "\n",
+    "# Keys can be what type?\n",
+    "# Values can be what type?\n",
+    "# Are dictionaries mutable?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup #4: answer these Q's about how to do each of the following with dictionaries:\n",
+    "\n",
+    "# How do you lookup an item in a dictionary?\n",
+    "# How do you insert a new item into a dictionary?\n",
+    "# How do you update/change an item in a dictionary?\n",
+    "# How do you remove an item from a dictionary? "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Dictionaries 2\n",
+    "\n",
+    "## Readings\n",
+    "\n",
+    "- [Downey Ch 11 (\"Dictionaries and Lists\" and \"Global Variables\" to end)](https://greenteapress.com/thinkpython2/html/thinkpython2012.html)\n",
+    "\n",
+    "## Learning Objectives\n",
+    "After this lecture you will be able to...\n",
+    " - Handle key errors with get and pop using default values\n",
+    " - Understand the idea of nesting data structures\n",
+    " - Use a dictionary of lists to put rows of data into \"buckets\"\n",
+    " - Use a list of dictionaries to represent a table of data.\n",
+    " - Create a dictionary of dictionaries\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Errors That Occur with Dictionaries\n",
+    "### (and how to fix them)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "suffix = {1:\"st\", 2:'nd', 3:\"rd\"}\n",
+    "\n",
+    "# what happens when you try to access a key that is not there? \n",
+    "print(suffix[5])  # key errors\n",
+    "\n",
+    "# what happens when you try to pop a key that is not there?\n",
+    "suffix.pop(4)\n",
+    "\n",
+    "# One way to protect from getting an error is to use a conditional\n",
+    "if 4 in suffix: # safe programming\n",
+    "    suffix.pop(4) # key errors\n",
+    "else:\n",
+    "    print(\"Skipped!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# There is a better way to access and pop from a dictionary.\n",
+    "# Take a look at the help for these methods:\n",
+    "x={}\n",
+    "help(x.get)\n",
+    "help(x.pop)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Make sure the calls to `get()` and `pop()` in the cell below will not cause a key error."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# TODO: make sure the call does not cause a key error\n",
+    "print(suffix.get(5))\n",
+    "\n",
+    "# TODO: make sure the call does not cause a key error\n",
+    "print(suffix.pop(5))\n",
+    "\n",
+    "## Notice that the suffix dictionary is not changed by calling pop() to remove an item that isn't already in it\n",
+    "print(suffix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Nesting\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Putting one data structure inside of another.\n",
+    "\n",
+    "We've done this with control structures...\n",
+    " - a conditional inside a conditional\n",
+    " - a loop inside a loop\n",
+    " - a conditional inside a loop\n",
+    " - ... and so on...\n",
+    "\n",
+    " \n",
+    "We can also do...\n",
+    " - a list inside a list\n",
+    " - a dict inside a dict\n",
+    " - a list inside a dict\n",
+    " - ... and so on..."
+   ]
+  },
+  {
+   "attachments": {
+    "buckets.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![buckets.png](attachment:buckets.png)"
+   ]
+  },
+  {
+   "attachments": {
+    "bins.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "![bins.png](attachment:bins.png)\n",
+    "\n",
+    "What is it?\n",
+    " - Start with an empty Dictionary\n",
+    " - Read a row\n",
+    "  - Keys are entries from one of the colums of the data\n",
+    "  - Each key's associated value is a list of lists\n",
+    " - Each row of data ends up in some bin\n",
+    "\n",
+    "Why bucket data?\n",
+    " - A way to organize our data, without losing information in the process\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rows = [\n",
+    "    [2014, \"A\", 123],\n",
+    "    [2015, \"B\", 120],\n",
+    "    [2015, \"C\", 140],\n",
+    "    [2016, \"D\", 100],\n",
+    "    [2015, \"E\", 130],\n",
+    "    [2016, \"F\", 200]\n",
+    "]\n",
+    "\n",
+    "bins = {}\n",
+    "for row in rows:\n",
+    "    year = row[0]\n",
+    "    if year not in bins:\n",
+    "        bins[year]=[]\n",
+    "    bins[year].append(row)\n",
+    "\n",
+    "bins"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in the cell below to calculate the average of the last column for the year 2015"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#TODO: calculate the average of the of the last column for the year 2015\n",
+    "\n",
+    "total=0\n",
+    "\n",
+    "print(total)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Applications of Nested Data Structures\n",
+    "\n",
+    "Let's bucket-ize data from the CS220 Survey.\n",
+    "\n",
+    "As a refresher, run the below cells to see some of the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cs220_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The cell function will also be useful!\n",
+    "\n",
+    "def cell(row_idx, col_name):\n",
+    "    col_idx = cs220_header.index(col_name)\n",
+    "    val = cs220_data[row_idx][col_idx]\n",
+    "    if val == \"\":\n",
+    "        return None\n",
+    "    elif col_name == \"Age\":\n",
+    "        if \".\" in val:\n",
+    "            return None\n",
+    "        return int(val)\n",
+    "    elif col_name == 'Latitude' or col_name == 'Longitude':\n",
+    "        return float(val)\n",
+    "    else:\n",
+    "        return val"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in the cell below to bucket-ize the survey data by lecture.  When you are done the `lecture_sections` variable should be a dictionary where the keys are the different lecture values and the values are the rows of data that are in that lecture."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Example 1: Place the data into buckets by lecture\n",
+    "# Key:   name of lecture (\"LEC001\", \"LEC002\", etc.)\n",
+    "# Value: a list of all the rows that go with that lecture (list of lists)\n",
+    "\n",
+    "#TODO complete the code below to populate the lecture_sections dictionary\n",
+    "\n",
+    "lecture_sections = {}\n",
+    "\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_student = cs220_data[i]\n",
+    "    current_lecture = cell(i, 'Lecture')\n",
+    "    pass\n",
+    "    \n",
+    "print(sorted(list(lecture_sections.keys()))) # print all the lecture sections\n",
+    "print(len(lecture_sections['LEC002'])) # print how many LEC002 students completed the survey\n",
+    "print(cs220_header)\n",
+    "print(lecture_sections['LEC002'][2]) # print the third student to complete the survey for LEC002"
+   ]
+  },
+  {
+   "attachments": {
+    "table_rep.png": {
+     "image/png": 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IZpdWo3a5Tq5uvJ6PvoWBgiGnEcLovfEzkyum+WbR5k4WKpZslitWb6zv2dTa5tsl2Qc6ODrqO8k7C7iQXLGuy24f3Uc8uj3veNXvPOt9bNchn2Rfqh+F7OvvEeAUaB9kE2xJsQwxC9UMkw0XiGDZTROJiFyN+kH9Gb0Wi44jxgslaOxxSoxOKkxu2TuVQrOfL1UmTfuATbrfwfiMw4cqM9uyhrO/5zIfVjhinxdx9HB+XcGjY++OrxdyFikX250MLTlYeuZU8+nespkzv84xl0uc166wu0CujK06VF0M73PddXOXiJcV6x2vRF3Nu1bX0Hl95MaXJkwzx03JWxq3LVrc7gS2xrSl3E1tP9Bx8F5G56H7mQ+yH+Y+Otx1+PHhJ4e7c5/mPMvqOdSb3pfav/d53F9RA7sHI1/EDCW9PDh87FX5SMPrB6Mv33waB2+JE4Lv5Cd1psyn/WbOvv/0UXk26VPr51/zmgtxXy5/fbfIvmT5PeVHw8/pFe5Vh7XsX53b82+M0EfuQH5GtaMPYRyx4tgF3E18BsGBhptmlPY8XTi9OgOCoZ0xncmCyEDsJR1ltmVhYHnKms1mwg6xN3NEcApxDnHlcOtwf+Ip5TXj/cZXxm/G/1nguKCG4IjQXmF+4VYRb5FV0WIxJbFu8QDxVYljklKSbVKOUlPSqTIiMkOyuTsMdnyTq5L3VKBTaFOMVBJQ6ldOU1FQGVfNU9NW+6ReqmGusah5Xste65d2nY67Llb3hh5Zn6h/1yDSkN+w1yjNWMl42qTE1Ba+d9w2j7KQsnhnWWblYc1q/dymwNbBjmQ3aH/SwdtR2PGD01XnRBdjVwbXYbdK92gPA09az0GvMzuDvRW8V3bd98n39fKT8Fsid/ofC/ANVAxCBQ0G11JSQpxCpcPQYW/Cb0UU746PdI3SoPJGo6JnYwZi2+Pq48sS8vakJsYnhSb77925zy3Fab9Dqn2a/QGHdKeD7hk7DwVkhmZFZ6fkZOYWHC47UpPXePRefl/B6LHPJ1CFEkVexUdP3i9ZOSV72q/sxJnHZ1fLFc4HVJRc6KlCVWvVxNfW1328JHk5pL72ytw1lYb917sbOZrCmjtv8d1OaXnbatXW0i7fcbFT6v7VhwaPhh8ndPM97e053Of0XHQADH4cejf84TV4IzK+a6J2Cj2T+BF8qpgnf9VdUvvpvFq8Mf9b3/s2CkYFgBOHANj4nuNQA0DuRQDE9gDABueednQAOKkDhIApgBY7AGSh/ef8gODEkwBIgAdIAjVgBueXYXBOWQTqQReYAGsQO6QMOULR0AmoGXoN53zSCBdEKqIeMYpkQBog45GXkFNwluaFKkW9gjMxH/QF9CeMCiYV8wzLgw3HtuFIOAquHc+Jj8X3ExQJRYRVGjLNU1p12mo6drpcegR9Ev13hliGJcZEJogpm8hKrCCpkXqZQ1iwLBdYjVmn2DLZpdh7OWI4OThbufy5abiv8XjwInkv8XnCGUGfQJ6grRCT0HPhIhFPUQHRKbGL4tESGpKQZJdUvrQnHJ3zsv07WuQq5QsU9ilSlByVNVT4VCHVMbUW9eMaIZraWvRaI9o1OjG6uno4vT79BoPrhk1Gt4xbTe6Zdpn1mA9ajFpOWy1Yr9ji7FjtRR3UHK2cyM7JLsWurW4zHiRPfa/IneXeAz4EX32/JHKz//dAtaCk4PYQQqhzWEX44m6zyLKouWitmJzY0XilhKN7FpJckx/s005pTbVMm0jPytDOBFl9OVcOn8oryDc7hjx+vzC/OKDE8JR0meBZkXKlCpvKqOrS2ieXQL3qVZsG9xvBTck3T9y+dqe/bamDt9PsQcyjs4+fda/1yPTtfH5k4O4QaZg8cml0dpx7Qm1Sb1r+Pf2HF7NHPu+Ya18w+9L5TWGxZGn5h/3PC8sLqxprKb/ubu4fW/NPhOdfAqgCE+AKQsA+cBzUgU4wCn5AJEgOsoEioKNQA/QSARAScJafhriKeAvn8VbIdGQbcgWljTqA6kazowPRjRg8xhvTiGXEhmGf4KRxebhFvBf+AUGWUESDpImiGad1pn1MZ0jXSq9FfwfOYh8x2jOOwnnqOvE4SZb0lDkCzjybWX3ZaNia2QM5WDkecu7hkuYa5y7iseXF8Xbw7ec3EMAIPBUsFPIVlhVeFekWLROLEjeW4JL4IvlY6rx0ioynrOYOCTl2ebz8qsKc4oTSC+XHKrdVL6qVqB/SoGp6ahlqS+ow6izqDuu16tcbXDVsMGoyvm3SZtpp9ti81+KF5RuraesFmxU7nD2rg5ijupO1s7/LXtcSt5vuwx5rXoI7Lbxjdp316fGDyCr+EQE1gVPBopSQkKuhy+GmEYW7Z6K0qHuj22JRcVbxRQlTiepJR5Kn9xmnVKfSp+05MA3vJ72ZFlkPc8xyu4845I3lpxzjPX63MLCY/mRzqf9pUtmDs3vLVc5/uXC1KrZGqw5zceDyhSvJ17yuqzTSN03cvH77wB2bNva74x01ndQHWo+wXYNPap7u7/Hq03kuMsA0+GjI+eXkq8TXzKPXxpzGVyeqJ92nGWa6PmTOWn5mnHuxcPZryKLKd8SPnuXS1aBfitvzjwQYQLu5A4gDFTgC3EA4OAjOgNtgGF7/gpAFFAtVQIMIGoQRvPI7kDikPfIM8gvKAlWFxqOp6DcYJ3i122AHcGTcT3whQZ0wSXOSVo92hC6Jnp++iyGeUZJxgukM0Y8kQfrO/JCljDWJzZNdj0OKk52LhhvBvcqzzLvKDwSw8A2UR1hWRFvUQSxIfL/ESckbcN49L8u4Q0HOVX6fQoVij9KKioSqu1qBer8ms5a7doXOnJ62/mGDN0aKxjkm42Za5oUWX6zsrC/Z0tqF2T92lHTKcf7gauFW64H3pHg99BbdddBn0s+QXBmADPQPukcRDckInQm3iqiPZIlKoI7FGMVejmdP2LfnY5IbvE5VUqpSOdKOpKMOJmd8yfTIupq9nut0uOrI8lHH/MvHCMcpJx4USRXnnpwrdT11p0z0TD689/uf776gWVlVzVSTWDt10fFSS73olbyrSw3e1x80yjQdbZ6/ZX/78h1Ca2BbazuxI+Be433UA7uHpY8mHks8oXRXPh3v4ey17zvYf/352wHCoNwLhyHqyyPDNa/ujQy8nhpdeLM6Dr3FTmDeYSbB5PLUp+nRmafvmz+Uf8ycjfhk/VlqDjv3Zr55IeuLx1eJr1++tSymLRl9x3zv/JHyU/PnwvKFFY9VwmrjGvkX3a9r6+4b8x8dqKiweXxAtAYAoEfX17+KAoAtAGAtf319pXx9fe08nGyMAHA3bOs/pM2zhhGAs1wbqO/K4r/+y/kfiazUoRVG4s8AAAGdaVRYdFhNTDpjb20uYWRvYmUueG1wAAAAAAA8eDp4bXBtZXRhIHhtbG5zOng9ImFkb2JlOm5zOm1ldGEvIiB4OnhtcHRrPSJYTVAgQ29yZSA1LjQuMCI+CiAgIDxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+CiAgICAgIDxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSIiCiAgICAgICAgICAgIHhtbG5zOmV4aWY9Imh0dHA6Ly9ucy5hZG9iZS5jb20vZXhpZi8xLjAvIj4KICAgICAgICAgPGV4aWY6UGl4ZWxYRGltZW5zaW9uPjY2NTwvZXhpZjpQaXhlbFhEaW1lbnNpb24+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj40OTE8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICA8L3JkZjpEZXNjcmlwdGlvbj4KICAgPC9yZGY6UkRGPgo8L3g6eG1wbWV0YT4K+/VJzQAAQABJREFUeAHsnQncTNUbx58XUdotUSFtkhRJ2ogoJMmSFklo0/IvCqn+bSoVStoTpSSlJJUUkRAtQmXL3xZlCSFLCOf//M64M3fmnXnfeeed5c7M7/l8Zu5yzj3nOd9z79xnzvKcHKMiFBIgARIgARIgARIgARKII4EicUyLSZEACZAACZAACZAACZCAJUAjkzcCCZAACZAACZAACZBA3AnQyIw7UiZIAiRAAiRAAiRAAiRAI5P3AAmQAAmQAAmQAAmQQNwJ0MiMO1ImSAIkQAIkQAIkQAIkQCOT9wAJkAAJkAAJkAAJkEDcCdDIjDtSJkgCJEACJEACJEACJEAjk/cACZAACZAACZAACZBA3AnQyIw7UiZIAiRAAiRAAiRAAiRAI5P3AAmQAAmQAAmQAAmQQNwJ0MiMO1ImSAIkQAIkQAIkQAIkQCOT9wAJkAAJkAAJkAAJkEDcCdDIjDtSJkgCJEACJEACJEACJEAjk/cACZAACZAACZAACZBA3AnQyIw7UiZIAiRAAiRAAiRAAiRAI5P3AAmQAAmQAAmQAAmQQNwJ0MiMO1ImSAIkQAIkQAIkQAIkQCOT9wAJkAAJkAAJkAAJkEDcCdDIjDtSJkgCJEACJEACJEACJEAjk/cACZAACZAACZAACZBA3AnQyIw7UiZIAiRAAiRAAiRAAiRAI5P3AAmQAAmQAAmQAAmQQNwJ0MiMO1ImSAIkQAIkQAIkQAIkUCydESxYsEC2b98etyKceuqpUrx48UKl988//8j8+fP9aZQoUUKqV6/uP452Z+/evTJnzhwxxthLihQpIjVr1pScnJxok4hLvCVLlsimTZsipgVexx13nBx44IER4zCABEiABEiABEgg+wjkqBHjs2LSsOwVK1aU33//PW6af/fdd1KnTp1CpTdx4kS58MIL/WnA+Nq6dav/ONodGHcnnHBCUPR169ZJmTJlgs4l+uCcc86Rb7/9Ns9sYPgeffTR0rhxY3n00UflqKOOyjM+A0kg3gR27Nghw4cPlwkTJkjz5s3lyiuvlP322y/e2TA9EiABEiCBAhBgd3kBYDFqeAL4nwJj//XXX5cqVarI4MGDw0fkWRJIEIF+/frJDTfcIO+9955ce+218sorryQoJyZLAiRAAiQQLQEamdGSYryoCGzbtk1uueUWmT59elTxGYkE4kEArZhueeedd9yH3CcBEiABEkgBgbQek/nAAw/Ixo0bw2Jbu3atDBgwICjsoosukkaNGgWdcx9gbCElbwLlypWTRx55xEb67bff5IsvvpDZs2f7x44iYPfu3XLNNdfIsmXL8k6MoWlLAOOh77zzThk/fnzCyxBNXueff778+uuvfl3OO+88/z53SIAESIAEUkMgrY3Mm266KSK1pUuXhjUye/ToEfEaBuRPoHz58nLzzTf7I/bp00dgbGLs5urVq/3nly9fbo3MY4891n+OO5lBAH8e8IcN4yATLdHmdf/998tff/0lY8eOlVatWsldd92VaNWYPgmQAAmQQD4E2F2eDyAG50/gmGOOkdtuuy1XxFmzZuU6xxPpTWDVqlV2Ytsff/yR8IIUJC/cgx988IH1NoGuck4+S3j1MAMSIAESyJdAWrdk5lu6OEXYuXOnLF68WOCeCC15eIHBpVBBBS9mtPqVKlVKKleuLPvvv39Bk8gzPlqW/ve//9mu66pVqxbaHVOemYUEHnrooSFnRP7+++9c58KdiJfemMWPWfmom5NPPlmKFYv99kYLGlw3IZ386gn1ig8MHQwniFbAB/n8+++/cuSRR9pPtPdVvJhBVwwtWbFihXVFVbp06Yjqb9iwwXoQQC9BLOLkg2sxQSzcPeOkG2teBXHxBYaot/Xr11sXXBUqVJDDDjvMUSGmrVNGDL3Ji2VMifMiEiABEkg3AnBhlImixgZcMwV9+vbtG3VRtevNaNe6Of74403RokWD0lHfkKZjx45GDbpc6X355ZdBcaFD7969jb5wgs6rexXTrl07s3Dhwlxp4IQatUHxkY66MMoVVw0Um74aQ0F6In31z2leffXVXNcU5MTZZ58dpEeNGjXCXt6kSZOgeNB38uTJYePiZGH0Rl5q+Pk/4FivXr2g/FFHp59+uhk5cmRYHaZOneq/HmnpnwcbTw0oo+P5/Gkhne7duxv9gxGUzk8//WTUZZPRPwz+uChz2bJlTevWrY0abUHxnQP1f2reffddWzeI7/6ULFnSdOjQwUC3cBIrs3BlhR461MHocIYgHdQ4MuPGjcuV/ebNm03t2rWD4kJ3dz1gXw3toGt1zKZp0KCBUYMy17Xqosu89tpr9l5wXxRLXjp0JkgXPLuRZNSoUaZZs2ZG/4Tk0qlatWrmiSeeMPoHI+zl8WAZNmGeJAESIIEMJIBWr4yUwhiZQ4cONYcffniuF5DbIMD+IYccYhYtWhTEL5yRGXqd+1hbvqxBGZSIHkRjZKrTd3PGGWfkq+ell15qtGUoNIuojvMzMleuXGmuv/76XDrA2NKZ5mHzKKzedevWzZWfm2no/nXXXWe0lTNIl9B6Un+mRlu0zIknnhg27c6dO9vrYZw9/vjjBsZnaD7uY20RM+pOJyhPHOhkmTyvQxow9EKlMMxCy6qtfaZt27Z56uH+c6ILHhidWJNnfKfsMLohYKnjNqO6Rr0R+IsbS164uH379kF56fANf5rODv6kXXbZZUHxHL1Dt5UqVTJff/21c6l/W1iW/oS4QwIkQAJZQIBGZphKbtmyZVQvIryY8PJ1S+hLKPTlFe4YRoVOmnEnk6+RiZcxrgtNDy9HtBBpt2tQGFrIYpFQIxP5abei/YRrnXL0GThwYNjs4qF3QY1M6NStW7cgfULrCUYmGDn6h26dFlH1v5grDlogTznllFytdWhN1hnP/nx1Fn6ua5EvWlHd+YUamYVlFlpWd16R9mEk//nnn1b3//73v0H6RboG5x0jU1erivoaXDdp0qSY88KF+RmZOuTF6OS0Aul0wAEHmB9//NHq5XwVlqWTDrckQAIkkA0ECj6wUN8I2SIHHXSQ3H777TJixAjR7lHrbBxj9NyCVYIwpi4vwfjIjz76SDCRYebMmXLVVVcFRccYN21ZCjqX3wHcCLnHxmnLq3UngzGfGJcJvdzjA4cNGyY//PBDfslGFQ7H6/hot2bY+Pfee6/ccccdYcMSoTfGMcIRN1wpYezsm2++ace9uhV4/vnnZd68ee5TQfvw7wlGjqix7h93i3G4+sdD1qxZI/fcc48TxW61q97W69y5c0WNMusj1ImA+8I9y/mzzz5zguxWhx7YcZ+YlY+xfEOGDBFtSQ2Kg4NEMEO6DRs2lE8//VR0yIZoSy1O+QXjUeHYHAJ3VLh/77vvPn84dtQIs+cR5nx0KEBQHByce+65okNVZNq0aaJDKKRr16654iAMUti8ciW878SDDz4oM2bMCArGMq3QB/cxloJFXbnHdGIM9uWXX25dcgVdGOYgWpZhLuUpEiABEshcAplqSRemuxwtmbqOedjxkhhPp3dD0Add246EtnSgNUQnGDjB/m24Lmb1B+gPz6u7HOPFQseT6Wo7/mudHX2xBul5xRVXOEFRb8O1ZIaW330cbjyfk1m89A5tyVQjzMnCvwVLtCS6dXO35obWkxMPrV3omoZgfOYll1xi1B+rPcY4Pycetjp5JVfd6mQeg9ZJdzwnvYcffjjovP6JMWrYGnTBO6I+Ro3+GXAO7djAwtZ1uLJefPHFQbrjHoU+br1Du5w///zzoHCMM44kaMnEWObHHnssqHxOfIwhdueFlki3FCQvXJdXSyaGSqBl1p0fnu/QcbZI55lnngmKh2vef/99BFmJF0snPW5JgARIIJMJxD79Vn99M1XQ0oI1zNFS4xasHY4WnlBRIyH0lP8YrWwlSpTwHzs7Oq7Ptpzt2rXLOWVbItHqmZ+gRQ4Oz92CtcO/+eYb9yk7g9d9Ak6tCys6FlF0Qo2dxY1ZuaGC1iC0xumEqdAg25KYCL21uzpXXuCIVka0ajqC1sa8BDO8P/zwQ+tBAPHg4xMtfY6o4eTs2u1JJ51kW6aDTuqBTh4JajUGd7SAo+XSLZgNjyUQn376adHJJtK0aVNRw0x0go0/WiLqWifoyOjRo4PuS9yjWHse5XcEreKxCrwn6CQZ6z/VnQaele+//150zK6478e8niH39bHsT5w4MddzC97gECrouXj22WftbHsnDK6R0KIZTpLBMly+PEcCJEAC6UCARmaYWqpfv77/LFycvP322/aljO7meL0M0ZUNQ8z9okUXdDQSrttXZ1zneym6kvUfU1CXYL4XhUSAsfTtt99aDuh+1NZR213sREN5tPXPdl2HGunJ1hurwLiNTKwIk1f5taXRb2A65XFvQ/X/5JNPBJ/8BMMXIC1atLB/XmBkuQXGq7YsSvPmzeWNN96QMmXK+IND80RAYesahmy4Pz4wgt1GZmHudbgngoN+yJ49e+wfKAw70ZZu6zLIBiTpa5m6iQoVnfEeesoea+u3NfLh0smRcNc7Yclg6eTFLQmQAAmkGwGOyYxQY3ix6Kxswdi8Xr162TGOhXnphsvGbUwgPFq/ku4XYLh0I53DGDOM/YuHoIUWS/dp92GQUYS0YczBYAuVZOuNsZRuwbjLSMuQIp77z4X7OuyjBRZjamMRx0gBMyzDGclIRKspxgm6W6STzSyW8kW6Bga9TpQS+J9Ul0G25T5c63ek6+N1Hj0QboEhqUMa3KeC9t1jmREQen1QZB6QAAmQAAlEJMCWzDBopk+fbrsOYZQ4gi5ZHfdlu2AjtYI4caPdhrZc6qzwqC4Nt1Qjuv/yE0xqULdL+UUrUDhaNnU8qG2lc1+os8ulS5cutsvZOZ9svTFRxy1wzh7J2Ta6PdH9HUlwbcWKFUVdNvmjwMhG62N+om6m/FGQv443tC3jmEiDSTduQcs5JhmhRRh/QpLNzK1LYffbtGljy+lOB0b0rbfeaocTqI9Md1DC9o844oigtDEhC892JEMz9M9E6PVBifGABEiABEggIgEamWHQ6KQc+xJygtCNqC5s7BjHaFsbnWsjbbEyTWgrFcbyRSM6aSFXNLQUnXbaabnOJ+MEWnzRFfzxxx/7s8MqSVhPGkv8OZJsvTFz2C15rdSEbs/8BPq7jUwYH2jljkWwvrb6bBTMxlYXQXblHycdtPZhHCCM9GQzc3SIZhs6vtZ9DcqFcZ+OoBUX45AxOx9/dtzDRJw4eW3zyiuv6xCG8aGhgnsDwzpCBWOk4QHCLepg3n3IfRIgARIggSgJsLs8BBTcyYS2Lj333HO5JtGEXFbgQxgWGKvmCF684QwKJ9y9VZ+Mgi4/t2Dt8LxexHhxRnIr5E4n1v1+/frlWsYRhsYvv/ziTzKZeqt/Qxk+fLg/b+yEMyqCIuRzgFY4t8BtD8YYRhIMT0ALM4YUQDCMwO1GB4YXJieBkXuyD+I64ziTyQz55iWhLX9w/YNWf7c496D6vXSfFvVSYA1yt4ugoAghBwXJK+TSXIeNGjWSgw8+OOi8egwQ96Q7J/CFF16wS006x9jiDwGFBEiABEig4ARoZIYwc7dUOUHuMVm6JJ1z2r9F19vPP/9sZ836T+7bQdccWkHhwxHrMWPyELoRYYC5RZfFs92x7nOR9tF1DyPVLfAzCF99GM/nGK8Yf6irllhDBrPlw+nuTqMw+1iLGr4q3YIxeW49E6U3JpRgPKM6LbeTSnTFJrnggguCJmmhuztUP7eu0ezD64C76xTlw8QntNDpMqQ2CbDHnxRdMcf+MUGXuDMmE61n8BmJbnbUP2ZvY5wvWrRDxypifXtIopjZxAv4haERoYKub/gXxX2my6faexiGZ+hz5PapimEM7nGnSBPPEJ4VZ6JWQfIK1Sn0GAZrqB9QPI+YGIZJWGh1Rx3Bv6u6qQq6HF4bdJnQoHM8IAESIAESiJKAvigzUmL1k6mGmdHWliBfefqSMurCxJx11llB5xWxPYa/QG2VMlgbPZwfPSdepK2O9TPwr+iWvPxkIp6+kCMuKQn/kFjWMTQ/7S52ZxHVfqifTB06EPE6rFoEVqH5auud/5p46B3qJzM0v9Bj1I22avp1wE5oPUHvaERnX+cqn5MfliLVsZ25wgcNGmSTDrdaEHRzrndvsTqQI4VlFm1Z4W/UrQPW9w4VrAfvjhNuf8qUKUYN8lzxcO/AV2u4JVt1uIJdLUiNan+W0eaFC/Lyk4lwrJqkLdG5dAqnv3MOS4eqwYzL/RJPlv5EuUMCJEACGUqALZn6RnELJmboWtfuU7aVBWPksIpOOEELZawzz9FNila40O68cPm4z6FlDu5m4NswVNAi5G59RTi6ZuEmJ5GC2dzuFW6cvHS9bus6CMep0Pvll1+2rbmOPoXZousUM6bhoidU0HKsTs2DTmM8X/Xq1YPOuQ/C3Tf/+c9/7CxzJ14qmDl5h24HDx6ca1hEaBwco2UerbBuwapZaNUPN8MfLcBOa7BzTbR5OfHz2sKdFoY26HrqeUXzh2H87tixY/1umPwB3CEBEiABEoieQIYaz0a7InO1WgwYMCCq4mrXnbnxxhuDWjTR0qIGnV2NBS2WStj/QcsMVtdRY9PoOC8zYcIEu1a2zlb2x3HHRwsJ1rrW8V9GX65hdVq+fHnQtWhd1Zdw2Lg6uca20qjvw6BrkCfWxdauwqA1tMMmEuFkvXr1gtLUmdIRYvpOb9myxa5r7i4v9tWQznVdrHqHtmSqIWdbwULzxOo9+ucgV744od27QeXCijAFEZ2BbNSRulEH7kHpQAe0ZtaqVcuoz0t7Pzjpape4XVEGLWrhWjCx7rwuLRnxnkA6sTCLtqx9+vQJKotO5nJUD9qilTXcOuB4DrCSFVq0IWj1Q92460XdA5knn3zS6Cx6g5Z1d5h6bbDPjjuzaPPq1KlTUFpoSQ0natQb9XtrdDhF0PPt6KG+aw1adPEsh5N4swyXB8+RAAmQQKYQyEFB9AeWEoYAxsnBGTZarTBGzO3AGutUYwUZjNmC66FIs5Mx3gu+KTEODTPTMdMVbmkixQ+jRtSn0BqE9cwx1g+r1yCf0NakqBNLYsSC6q2Gr10H21ERk47QWoqywy0U6gucQ/2QOvHjvUXLHGZLo1XyuOOOs+zzm+CCSSfQFWMXMYkL14X69cxLz4IyyyutWMMwznLRokWClYvgTxattmh1dQsmAmHCE54XuIhCC6EjmBiFMcpoZccEJzVSnaBc22jyynVRPifwPII/JvvhnoGLqoLUQT7JM5gESIAEsp4AjcysvwXSD0A4I7N79+7pVxBqTAIkQAIkQAIZTIBjMjO4clk0EiABEiABEiABEkgVARqZqSLPfEmABEiABEiABEgggwnQyMzgymXRSIAESIAESIAESCBVBGhkpoo88yUBEiABEiABEiCBDCZAIzODK5dFIwESIAESIAESIIFUEeDs8lSRZ74xE/jqq69E/VT6r8eSmSeeeKL/mDskQAIkQAIkQAKpJ0AjM/V1QA1IgARIgARIgARIIOMIsLs846qUBSIBEiABEiABEiCB1BOgkZn6OqAGJEACJEACJEACJJBxBGhkZlyVskAkQAIkQAIkQAIkkHoCNDJTXwfUgARIgARIgARIgAQyjgCNzIyrUhaIBEiABEiABEiABFJPgEZm6uuAGpAACZAACZAACZBAxhGgkZlxVcoCkQAJkAAJkAAJkEDqCdDITH0dUAMSIAESIAESIAESyDgCNDIzrkpZIBIgARIgARIgARJIPQEamamvA2pAAiRAAiRAAiRAAhlHgEZmxlUpC0QCJEACJEACJEACqSdAIzP1dUANSIAESIAESIAESCDjCNDIzLgqZYFIgARIgARIgARIIPUEaGSmvg6oAQmQAAmQAAmQAAlkHAEamRlXpSwQCZAACZAACZAACaSeAI3M1NcBNSABEiABEiABEiCBjCNAIzPjqpQFIgESIAESIAESIIHUE6CRmfo6oAYkQAIkQAIkQAIkkHEEaGRmXJWyQCRAAiRAAiRAAiSQegI0MlNfB9SABEiABEiABEiABDKOAI3MjKtSFogESIAESIAESIAEUk+ARmbq64AakAAJkAAJkAAJkEDGEaCRmXFVygKRAAmQAAmQAAmQQOoJ0MhMfR1QAxIgARIgARIgARLIOAI0MjOuSlkgEiABEiABEiABEkg9ARqZqa8DakACJEACJEACJEACGUeARmbGVSkLRAIkQAIkQAIkQAKpJ0AjM/V1QA1IgARIgARIgARIIOMI0MjMuCplgUiABEiABEiABEgg9QRoZKa+DqgBCZAACZAACZAACWQcARqZGVelLBAJkAAJkAAJkAAJpJ4AjczU1wE1IAESIAESIAESIIGMI0AjM+OqlAUiARIgARIgARIggdQToJGZ+jqgBiRAAiRAAiRAAiSQcQRoZGZclbJAJEACJEACJEACJJB6AjQyU18H1IAESIAESIAESIAEMo4AjcyMq1IWiARIgARIgARIgARST4BGZurrgBqQAAmQAAmQAAmQQMYRoJGZcVXKApEACZAACZAACZBA6gnQyEx9HVADEiABEiABEiABEsg4AjQyM65KWSASIAESIAESIAESSD0BGpmprwNqQAIkQAIkQAIkQAIZR4BGZsZVKQtEAiRAAiRAAiRAAqknQCMz9XVADUiABEiABEiABEgg4wjQyMy4KmWBSIAESIAESIAESCD1BGhkpr4OqAEJkAAJkAAJkAAJZBwBGpkZV6UsEAmQAAmQAAmQAAmkngCNzNTXATUgARIgARIgARIggYwjQCMz46qUBSIBEiABEiABEiCB1BOgkZn6OqAGJEACJEACJEACJJBxBGhkZlyVskAkQAIkQAIkQAIkkHoCNDJTXwfUgARIgARIgARIgAQyjgCNzIyrUhaIBEiABEiABEiABFJPgEZm6uuAGpAACZAACZAACZBAxhGgkZlxVcoCkQAJkAAJkAAJkEDqCdDITH0dUAMSIAESIAESIAESyDgCNDIzrkpZIBIgARIgARIgARJIPQEamamvA2pAAllLwBgj+FCSR4DMk8eaOZFAthOgkZntdwDLTwIpJNCyZUv5+OOPU6hB9mU9ZswYadWqVfYVnCUmARJIOoFiSc+RGZIACZDAPgI9e/aUypUrk0cSCZx55plStmzZJObIrEiABLKVAFsys7XmWW4S8AABdpWnphLIPTXcmSsJZBsBGpnZVuMsLwl4iEC/fv1k5syZHtIo81X54YcfpH///plfUJaQBEgg5QRy9B8tR92nvBqoAAmQAAmQAAmQAAlkFgG2ZGZWfbI0JJBWBJ566ilByxoleQS+//576du3b/IyZE4kQAJZS4BGZtZWPQtOAqknkJOTk3olslADcs/CSmeRSSAFBNhdngLozJIESIAESIAESIAEMp0AWzIzvYZZPhLwMIHLLrtM4LeRkjwCH330kcA/KYUESIAEEk2AfjITTZjpkwAJRCRAP5kR0SQsgH4yE4aWCZMACYQQoJEZAoSHJJAMAi+//LJs3brVOsVu1KiRvP/++7Jx40a55pprpGrVqn4V5s6dK+PHj5cVK1ZI8eLFpWnTplK/fn0pWrSo/PHHH/LOO+/YuHXr1pV///1XvvrqK9m+fbu0adNG6tSpI7/++quMHTvWpn3++efLRRdd5E977969dtINJoL89ttvUqtWLbnkkkvk0EMP9cdJ9E66OLf4/fffZcSIEX4c119/vZQqVUrGjRsnqCNIgwYNBAZcOki6cJ8xY4ZMmzbNIq1Xr56cffbZdh/Py/LlywVjS++++267TQfu1JEEso4AXBhRSIAEkktADRS4DjMHHnigcfZxjM8LL7xglXnggQfssXPe2Xbr1s2GT5w40R9+9NFH+/cRT41Q0717d7P//vsHnX/zzTfttWqQmnbt2gWF4brq1asbNV6TBqNFixZGu2+Tll+sGe3Zs8c0btzYz+vqq682CxYs8PPVPwZm8+bNsSaf1OtGjx5tdJhCUvOMNTP1oepnrgamTWb16tWmRIkS9ny6lCPW8vM6Ekh3ApLuBaD+JJCOBNyG5THHHGMuuOAC/8u0YcOGtkhXXnmlqVGjhnn22WfNyJEjTcWKFW0cGKYwaNxGJgxEbeE0xx9/vD8dnMMxXs7Yd+Ig8ccff9x/DsaottKZMmXK2HMdOnRIR6QJ13n9+vWmUqVKfm5HHnmk3T/kkEOswZlwBbI0A/ezMWfOHNOrVy9/HWhLZ5ZSYbFJID0IcOKPvnkpJJAqAuhy/e6772TSpEmirYhWDXQPasuZ3HjjjYKubHSRL1y4UHbs2GHDt23bJhs2bAhSGRNoJk+eLNpK5T+vBqbMnj1bpk6dKiVLlrTnFy9ebLdffvmlP95hhx1mu8ud9awRP1mSTn4yS5cuLR988IFoK5rFoy1qtpv2rbfeChrikCx2seaTbn4ye/To4S8q7hcMNYFg+IfTfe6PwB0SIAFPEeCYTE9VB5XJNgLazS3lypWzxcY+xvft2rVLdu/eLSeeeKI0adLEGo/aeikHH3xwRDxnnHGGDatcubI/TrVq1fzXaCuoHZ+JdCGrVq3yx3vkkUf8+/vtt59g/CEMWeSZaEk3f40Yc3nWWWfJlClTLJpixYqJtkQnGlPc008n7viThT9geDbc42K1RTPuXJggCZBAfAmwJTO+PJkaCcSNQJcuXayBecABB4iO/5OLL77Yn7ZjLPpP5LMTalSce+65/it0DKg1bGHcLlu2TD7++OOkGJhQALPL02WyDPR9+umn/QYmjjHZ6vLLLxcdvoDDtBBMCHO3DnpdaWdyj1tPHUYS9Dy4w7hPAiTgHQI0Mr1TF9SEBIIILF261B6j63zgwIHW+HMiNG/eXNauXescFnh78803+1s5sX/yySdLlSpVpEKFCnLrrbcWOL1YL0gnP5mYuX/PPffYoqKFuXXr1nZ/yZIl0qlTp1gRJP26dPSTqZPURMfA+lnhzwmFBEjA+wRoZHq/jqhhlhAoUiT4cbz//vvtWEq0MA4ePFh0QpA4cXTIt6Bru6DitGiiy3fChAk2TXTDY8wnjCV00SfTyISxULt27YIWI+nx16xZIzoRy46VxRjWIUOGyKuvvipHHHGE1QVjYZ977rmk6xVLhmg5TqeWTJQRLfd4DiDHHnusrQt7wC8SIAFPE+Cykp6uHiqX7QTQHQv/mY4xg25ZGJgwdOIl8JepM6et30eMMUymYJITjAaMR6UkhwD8q2JYBHyrpougJb9r165WXQzvuO2229JFdepJAllNgEZmVlc/C08CqSWA7vLOnTsLtpTkEEB3+dChQwXbdBD80YKnhJUrV9o/W3DCjnHKFBIgAe8ToJHp/TqihiRAAiSQtQR0AQHp2LGjLf9jjz0mGEZCIQESSA8CNDLTo56oJQlkJAH4PcRY03SaYZ7uFQE/mfCpmi6TZ+DrFcueQnCvqPP7dK8C6k8CWUMguQOwsgYrC0oCJBANAWciUjRxGSd+BNKJ++mnny74UEiABNKPAFsy06/OqHGCCAwbNszOuE5Q8kyWBEggiwk0btxY2rdvn8UEWPRsJMCWzGysdZY5LIGTTjrJztwOG8iTCSGg67Lb5QFr1aqVkPSZaG4CP/74o11q1JmtnTsGzySCAPzQUkgg2wiwJTPbapzlJQEPEfjmm28ES2HShVHyKgUujDBD+7zzzktepsyJBEggKwkEe3/OSgQsNAmQQKoIwOcnJfkEyD35zJkjCWQjARqZ2VjrLDMJeIRAv379ZObMmR7RJjvU+OGHH6R///7ZUViWkgRIIKUE2F2eUvzMnARIgARIgARIgAQykwBbMjOzXlkqEkgLAvCTiZY1SvIIwE9m3759k5chcyIBEshaAjQys7bqWXCvE4AT6lWrVuVSc/fu3TJ37lzBOubpLungrxG8MSM7r2591AfqK13GOqYD96VLl1qXYlhOMpysXbtWpkyZItu3bw8XzHMkQAJeIKA/ihQSIAGPEVixYoUpWrSoadKkSS7N9OWL2TLm3XffNTt37jRPP/200RnDueLxRHwIHHfccZY3mB9zzDFG1/z2J6wGjtFVaPzh5557rtm6das/nDsFJ6BrlZtWrVr5mapBbHQpyaCEcM/jPOpEVwAy2hoeFM4DEiABbxBgS6YXLH3qQAIhBF5++WXZs2ePfPHFFzJv3ryQ0MDhkiVL5O6775bx48cHTqbR3mWXXSZjxozxtMbt2rWTDz/8UAYPHixqQErv3r39+j700EMyadIke+7JJ5+U6dOne35tbTWSpWXLlv4yeG1nx44d8umnn9r7Gn5Ujz/+eHn88cetb0/oiu5+3PP6B0zefvttOeigg6RNmzb2efFaWagPCWQ9AW/YutSCBEjAIfDPP/+YMmXKmGrVqpkiRYqY66+/3gmyW3dLJk6kcyvmtGnTzO+//x5UPi8f3HLLLbb1DDqjFblUqVKmfv36fpUbNGhgDj30UIM69KpAd3D3qoDd2LFj/ephX1/U5rHHHrPnOnXqZI///PNPe/zSSy/ZY/2z4r+GOyRAAt4gwJbMrP+bQQBeIzBixAhZv369PPHEE9K8eXMZPny46As1rJqrV6+Wq666yo5NQwS0fmIyzVlnnSUnnHCCDdu0aZO99vPPPxft2hWsbNShQwdZt25d2DSTeVJ/BpOZXcx5geuMGTMEDMuWLStHHXWULFu2TP766y9xr1ZUs2ZNO1Z28eLFMeeVjAu9zH3//feXZs2a+THoEAW7f8ABB9gtxsbCeT/qAVKjRg27xbhZCgmQgLcI0Mj0Vn1QGxKQ559/XipVqiSXXHKJ3HXXXYLuQ22tCUsGYVOnThUYm5Du3btLr1695O+//7aGJowiGKxYWQcvbsSH4Yru9dtvvz1smsk8mS5+Ml988UXR8ZbWsBwyZIhg4oy2CFpU1atX9yPT1me774T5Azy0k25+MjFUAaKtxHaLFYtOPfVUu4+vdGDuV5Y7JJBlBLh2eZZVOIvrbQLajWlnKZ9//vny2muv2dnKGHOGMZowHtHKE0lgQL7wwgvSqFEjOysXhpB26Urx4sXlv//9r5QoUcKOK0SL0OGHH25bPBGO86kSr4/HdLicccYZopNR7PjRW2+9VS688EIpVsz38wmGjuzatcvugrlXBeMxvTwm080NM8sx1rVx48b+FmOdEGfvayeeThSyu/vtt59zilsSIAGPEGBLpkcqgmqQAAigFRMC1yw6/k9g0GCyCbrL0W2el6D7Fu52MJkGBiYEBiT2l+ta1RB0rSN85MiRcuyxx8ovv/xiz6fqK138ZGKdb7So3XbbbbYF0+myBTf3xCy4MoJUqFDBbr34lS5+Mvfu3Ss6Htn+SXrllVf8KNFV7nDGSece9jJzv/LcIYEsI0AjM8sqnMX1LgF0A8KQ6dixo/X9B/9/+MDIxLi0AQMG5Kl8+fLlbTi6z0OlatWqghYghP3888/289NPPwla6FIpjjGcSh3yyhstk+DviNNCqROyrJEOg+e7776zwRjn+O2331oDEzOivSxe5w52jz76qG2Rf/311y1rh2fdunXteGL8qYJgrCzE6U63B/wiARLwBAF2l3uiGqgECYjtEkdL5B133CHOJAeHS9euXaVbt27WpVGVKlWc00FbdIE3bdpURo8eLVdffbXtNl+wYIG0b99eLr/8cnnrrbdsN6/OzrUtnnh5wwWMe0xhUIJJOOjZs2cScok9i99++01OO+0021172GGHyfvvv2+NSEz2gdGOlmb14SjXXnutnXQ1Z84cOwwBYV6VOnXqCD5elokTJ1q3UOXKlRMMIcEHAt5o4X/11VeldevWdtwy/nzVrl1bYHxSSIAEPEbAG5PcqQUJZDcBOKDW2bJGu2XDgtCJPNY1zsUXX2y0Bce6bIEzdvc+LlyzZo11ZK3j02ycI4880qjvRpumjtc02sJmzyMcDq83bNgQNr9knWzRokWQc/Nk5RttPnCTo+MBzYEHHmi5qcFpZs2a5b9cZ50bNXyM/ikwJUuWNPoHwWg3rz/cizv6J8TokAkvqmZ10lWurAsvfVVa5u7t5MmTbZxRo0YZ3Ntw8XXOOecYXEMhARLwHoEcqOQxu5fqkAAJFJIAJkNs2bJF1I9jrpQw8xyTidDlm2rBrPfKlStblzSp1iWv/METQxfUB2bYaJj8gy5opzs9bCSPnMSwDIzRxTjTdBfUiRr36V4M6k8CGUuA3eUZW7UsWDYTwEzbcAYmmOgyfJ5Bky7/ccEzkoEJmKmcoR9LZaYL9/zKRgMzP0IMJ4HUEkh9U0Zqy8/cSYAEUkggXfxkphBR3LNONz+ZcQfABEmABJJGgN3lSUPNjEiABEiABEiABEggewiwJTN76polJQHPEUgXP5meA1cIhdLFT2YhishLSYAEPEKARqZHKoJqkEA2EkgHf42ZWC/knom1yjKRgPcI0Mj0Xp1QoxQRePbZZ60PPmSPVXHgExGOy+F/D+t/h4Zj1RwnfN26dTJw4EDp0qWL1R7L9r333nt2NRJcjxV7nnvuObn55pttOJYoVBdEduUShK9du9au9nPTTTfZcPgAHDFihF1NxgnHkpGRwtV1kV1S8sYbb7TXt2nTRt555x2ZP3++1R9rm2P97RtuuMGGw28mVhCCH02kry5g7ProWGEF0rZtW+tDc+HChTYcM5KxtKUTfsUVV4QN79y5s70e4cOGDZNff/3VXo+1vLFqC3x0Qq688krrtxOc4P8TywfC92HHjh1tOFYmevPNN+V///ufvX7FihUyaNAgue6662w4/IAifPHixRHDhw4d6g+Hv0ss09mhQwd7fbt27eSNN96QJUuW2Osx23rw4MHW3yUiXHPNNQI/okuXLrXh6ipKsGY5fI5CsEU4zoMftjh2hyO+E450EI50IfCrifyQL66HHtAHekGgJ/SF3ghHOVEelBsCDuABLk44eEQKB0eEgyt8ZGKVIvAGd1y/aNEiWx+oFwjqCfWFekM46hH1iXqFoJ5xP+C+QDjuE/hcdcJxn4QLx30FQfhLL71k7ztcj/sQ9yPuSwjuU9yvuG8RjvsY9zPuawjuczwPuO8RjvLgecFzA8FzgnA8V5HCsbqWE44VhPA84rmE4DnF84rnFtdjVSE8z85ynHjO8bzjuUc4fgfwe4DfDQh8eeL3Ar8bTrgN4BcJZBsBuDCikAAJGKMvcqOr4FgUunKL0Res2bRpk9FVcoyuC27UEDDqbNuG6yovNnzz5s1JCf/nn3+C8tcuT6MGgoH/TOiHcDVkzOzZs61+iQp3fEQifTVwjLpJsvmrKxmjBpXfh6ROLokqvFmzZqZPnz4mluvVAPPnv23bNqMGm/nxxx9t+XXZR4NwXa3H6pfocOSD/JAvBHpAH+SL+kl0OOoB+YM7BPWE+gBX5I9w1BfC4Sezfv36EcPzuz6vcNwXTjjuR9yXyB/3Ke5XJxz3aaLD8bw6+eM5xfOM5xaC5xjheK6hX6LD8TtCIYFsJMCJP9n2r4LlJQEPEUgXP5keQlZoVTLJT2ahYTABEiCBhBJgd3lC8TJxEiCBvAjoP/u8ghmWIALkniCwTJYESCCIAI3MIBw8IAESSCYB+slMJm1fXvSTmXzmzJEEspUAu8uzteZZbhIgARIgARIgARJIIAG2ZCYQLpMmARLImwD9ZObNJxGhOvlG+vbtm4ikmSYJkAAJBBHg2uVBOHhAAt4hALcwu3fvtgoddNBBUrly5QIpB7c1Bx54oBx11FEFui6ZkdPRX6O7XsAKa8FXqlQpmdgKnVe6cNcZ8rJnzx454YQTcpX5r7/+si6QqlSpIsWLF88VzhMkQAKpJ8Du8tTXATUggbAE9ttvP7+RiQgVK1a0vvrOOeecsPFDT8Lwad68ufVHGBrG49gJHH744aIuafwJwDfjqFGj/MfciR+Bs846S9TNkKhrsVyJPv3009K9e3frwxOGJoUESMB7BNhd7r06oUYk4CfQuHFjGTdunDz22GPWsIEz6EyaGQzn1WPGjPGXN112YFiOHz/efnr37p0uals9P/roI79T8bRSnMqSAAmkHQF2l6ddlVHhbCKAru6mTZvaj7PqClZpSbfu2Uh11rNnzwIPA4iUVjLPo/v2oosuSmaWccvrzDPPlLJly8YtPSZEAiRAApEIsCUzEhmeJwGPEEDLJboLv/76a6latWqQgTlp0iS7xCAMHixlB0PULVgOD0sNojsRS/Xpyibu4JTvp2urLJYR/OKLL0RX0kk5w1gUSFfusZSV15AACaSOAI3M1LFnziSQLwGsh1yqVCmpWbOmXSca61k7grWlGzVqZLvTixYtatfGrlGjhujSeU4UmTZtml1fuVy5cnbt7V69evnDvLCTrn4yP//8c9u6fNJJJ8mMGTO8gDJqHegnM2pUjEgCJFBIApz4U0iAvJwEEkUAE39gxGBc5rp166zxuHbtWhk6dKhccsklggkoMConT55sZ9euWbPGzsKtVauWTJkyxbZ4ooVzyJAhVsX27dvLhAkTZPXq1VKkCP9fxlpvmLX/77//CsY2PvDAA5YzZkFT4k+AE3/iz5QpkkAyCfBNk0zazIsECkgA4+eeeeYZGTZsmKCL9uijj7aTgNAtvn37dmnXrp3ffUv58uXl0ksvlVmzZvlzKVGihH+/SZMm8ueff4adqeuPlOSddPSTeeKJJ0q1atXkvvvuk1atWsny5cvtJ8noYs6OfjJjRscLSYAECkiARmYBgTE6CaSKAAxG+L1ES9qRRx5p1XB31WKcHQyII444IqyK3377rT3vXBs2UpJPpou/RgfL1q1bnV27hYEJQb2kk6Qb93RiS11JgAQCBDi7PMCCeyTgOQLz5s2zLZlwPA0jcebMmXaiT5kyZaRt27aCMZswGM4++2wZPXq0LF26VJ588kl/OTBhCK2guPb1118XtGaixdMrgtnl6STXXnut/P7771K/fn3BpKvZs2fbcbHpNFu7Tp06gg+FBEiABBJNgEZmogkzfRIoBAFM0sAH4zNPPvlkueeee+TRRx+1KQ4ePNiuNjN8+HDBBxOEnnjiCenRo4cNr127tnzyyScyffp026XeokULefHFFwuhTfwvhZ/Mzp07C7bpIBgfi8lXAwYMkGLFikmbNm08xzQ/jhhLinG92Hpd8mpxdcI4vtjrtUj9spkAJ/5kc+2z7BlBAMvubdy4UdC6GSoIW79+vZQuXdoaRaHhqT7+5ptvrJ9MjDVNJ8F4WCxlCEMz3eSPP/6wY0jPO++8dFOd+pIACaQZgfT7hUwzwFSXBBJNAO6LwhmYyBdhcF/kVUlXf40lS5b0KtKo9EpX7lEVjpFIgAQ8Q4ATfzxTFVSEBLKPQLr6yUznmqKfzHSuPepOAulFgN3l6VVf1JYESIAESIAESIAE0oIAWzLTopqoJAlkJoF09JOZ7jVBP5npXoPUnwTShwCNzPSpK2pKAhlHwJkhnHEF83iByN3jFUT1SCBDCNDIzJCKZDEKTwBLBLZs2dImdPrppwtcBKHVBzOfsWTjgw8+6He1g6Ub4coG49sQjqUaH3roIYGbIMgZZ5whgwYNsn4tEb5q1Sp5+OGH7Yo8CId7IYT/+OOP9vpw4a+++qo/HDOCH3nkEf/1WAkIa5djdR+kD9+NvXv3tstNIn34QXz55ZetH0eEr1y50ro+atasGYIFy/W99NJLMmfOHHv9ihUr7EpCF198sQ2H3024O4KfTVz/22+/yeOPP27X60aEc845R1544QX/KkRwSt6nTx/rhxPh5557rjz//PPyyy+/2Oux7CLcK8EFEAQzm5977jmBPmDu+PfEMpiQunXrysCBAwV+QpE/wtHqGSl8yZIlNvzCCy+019erV0+effZZmT9/vr1+8eLF0rdvX+vTEhHOP/9864ZowYIFNhwO7jE+tGHDhvZ6+MHESksLFy604YsWLZL+/fvLBRdcYMMbNGggTz/9tGDlJeiHLY5xHoJ4iI/rEI50kB7ShSAf5Id8EQ494BYJekGwJj30hd4IRzlQHpQLgnKCB8qNcHACL3CDgBPCwS00HPfG+PHjrT9VJ3zu3Lm2PpwZ56gn1BfqDdejHlGfqFcI/K2ivlHvCMdqVLgfcF9AmjZtau8X3DcIx32E+wn3FQT32WOPPSa47xCO+xD3Y906Z4rM+1H6nXuKTL7yIjEPdZEP1A+sXHqybKmRI4uw3+xoWV40R9afpPttTpMxem5b16tldufL5KFq6gN2zgxp2+xi+7zguUH6eM7wPOG5g2BlLDyPeO6ccDyPkcLhnxbheK4heM7xvOO5x/X4HcDvAX4XIHDJhd8L/G4gHL8jFBLIRgIck5mNtc4yhyWwefNmuyY1Zmrj5XDQQQdZ/5QbNmywM7Sx2suuXbsEjredcLixgYsgzOBOZDhW8dm2bZs/f6xhjlVmnPwTEY4Z1FhlCOVD+nDbs3PnTlt+5B9L+I4dO2xazvVYFrN169YCJ+dIPzR8//33t+u2O/nHGo46++eff/zpY3nNAw44QJz04xEO3ZAHdEX6SBt5YN15pB+PcDDCveakjzrAvpN+NOFYJQoG13vvvWfrMJrr8Uyg7p30USbcG07+sYQXV9+vh65YJHs//0CKLPlF5NvPRX4O+2jGdvJYvQxG/XGnqdXdUradfIZs0frBYgTQH88OnnHci9Afzzae4USEw4WYe4nX2ArEq0gg/QjQyEy/OqPGJJAxBNLVT2Y6V0BK/WSqISdTxop8PlLk+XdF9DCXVNEztbTFsXxlkSMqiJQ7SqS0LqN68CEixfYTKVJUxOwV2b1bZNsWkfVrRNatEln7u36Wi8zV5VPn5ErVd+KWS7QZ9iptKlbn/wcdHCEST5MACcSLQLF4JcR0SIAESKCgBOivsaDE4hM/6dw3rBMZ9qxItz65C/AfHaJy5gUip2hXdNWaIiXjsA78rp0ii7R1dN4skVlTRd5+W0TtUHlZDVx8INoVLzfosqYV0ORJIQESSAQBtmQmgirTJAESiIpAui0rGVWhPB4pqctKbt4o0ucOkb5q5DlSTXc6qXHXuI1IdW2xLJKEqQHGiCyeL/LlhyLvPSjytaOMbq9vJPLoGyJHVnSd5C4JkEA8CNDIjAdFpkECJEACJBBMYNz7OknnisC5K3VSzG3aklm3sQgm8KRS5miX+iuPiLyq40AdeVNbWtv/JzlGr5MntySQ4QSS8BcywwmyeCRAAjEToJ/MmNHFfGHC/WTu1fGSd+u4R8fAbKijshbqjJ53fxSp1yT1BibI1Txbjcxx2oW+Qg1L3Ydc11XkitNEdvzjO+Y3CZBAoQnQyCw0QiZAAvEjsFdf0HB788UXX1i3L5itHA/ZuHGjwE0N0veSpLO/xn///de6xpkyZYps2aITUNJIEsYd3dI9rxF55j0fjdf7iUzQ8ZEnnVogOpjFjvvV/YH3B7dgVjjYI27Mgi7yt6aLfPKOL4lR80SuPUsnJKnOFBIggcIT0AHgFBIggRQT2LNnj1E/iubggw/Wt7T4P+qmyFxxxRVG3asYdSFj1Bej0dnBBdZWfVLaNP/+++8CX8sLchNQv5DmxBNP9NeTusAxkyZNyh0x2870vwdmpu8z9YuYSz9hwgQ/W+d5GDFihD89PAdqKNs4hxxyiFE/lf6wmHcW/hzQvUuzmJPhhSRAAgECbMksvJ3OFEig0ATatGkjd911lxx77LHWqfW4ceNkyJAh0qpVK8FEDbSawfH23XffbR1pFzpDjySAiT9jxozxiDbRqwHn27vVhQ4crHfv3t36MIWvT/2zEH0iKYqJ+8lZdCCuKmzcINL9KV+S40f5xl4WMgM4oIfjeHwcR/vo7sdzAIfwb+uscfi6xPNTaPZobZ0706fxK5/p7PS5hdSel5MACehfTgoJkEAqCejKPbZFRh2TGzUmc6mizrL952JpxcTFXm3JnDZtmtHVivzlS5ed6dOnG10txq9ux44dbR3qyj/+c17dAW9wj7s8c6+vJfDSEwqdtNOSGa6FslOnTpa181zoSkH2WP+sFDpfm0CPdr5y3NoiPukxFRLIYgJsyeQfDRJIMYG33npLSpUqZZeJLFYst+tarOYCwRJ2V111lR2HhlZNLEGIpQyxBGGNGjXssoBOUfQ3zS4DiOUjq1SpYpf0QxhaRLGk35133ulEFTWYbFqffaatN0kW6JmOguUTjzxSHYTvk2OOOcbuYYWfdJCEcJ+0b1zjzY/GDQHuye+++y4oPSzxiKUanecC9z4ES0fGReBeCfLOx74tv0mABGImQCMzZnS8kAQKTwBdfHg5Yi1yHY+ZZ4JYlnDq1KnW2MREE+xj/WSsN42lDGE4fv21zwEg1oW+44477FKAV199tei4NZv2frqU3ymnnGINUEyqgGCNaqwt7axbbU8m6Qvrd8NoSGfBZCp0QR9//PFSsaL3fS2iqx/rqsddNv3mS7Lc0XFLGvc31jvHWvBY8hGCFYtOPVW7tvdJtWpwvCmiLbT7zhRyc4SuMATZ5NvwmwRIIHYCNDJjZ8crSaDQBIoWLSqHHXaYHd8XS2JYg7p3794ydOhQe/ns2bPtFi2ctWrVkjlz5sgjjzxi1wZ30u/Ro4ddVxvG5fz582Xs2LFyyy23yKGHHupESdoW4zExLtPLgrGXK1eu9H9CZ5IPGjTIGum9evXycjH8umE8JoziuEt5X4uizJ9V6KRhWC5dulR0MpUdlzx58mR7HyNhPDNYR90RtM5D8AcqLjJ/X4vocXFJjYmQQFYToJGZ1dXPwnuBACY0oHVp3Tpdeq+AorPP7RXoPsS+jlOT9evXC9y9NG/ePGxq5cqVk5tuuknee+89ue2226R48eLStav6CEyBpIOfTLiUqlSpkv9z//33+0nBEIJx2bhxY+ncubP/vJd3EuYn8+o7fcV+VO+lQk6AwmQeTIJDCyb+QKGV32mlx73utMIjw19+0eUjVSpU0HXO4yED7vKlcus98UiNaZBAVhOgkZnV1c/Ce4EAZsaqayHp0KGD3YbqNHHiRNm0Kf++uyL7lucrXbq0lCxZUubNU59/EaRnz56C8Z9oIerYsaOUL18+QszEnk6Yv8Y4qo2xl+hedj7OzGy0prVt29Ya95jl7PCPY9YJSyoh3FtcK1JOVV6snyfU4CzEeFu3f1j4w9y2bZvlDCB169a1f8iWLVuGQ5kxY4bdNmjQwG4L9TX8RZHRC3xJdOpeqKR4MQmQgEjuWQakQgIkkFQCcFOE7m24Zalataqd3INWHHTRwghEK6fOWo66OxAGBAzHwYMHC8ZmVq9e3XaLuwt11FFHyUUXXSRwlYTu81QJjF2vy+GHH27rJlTPbt26yaxZs6RevXry5JNP2mC0JmP4gpelTp06gk/cBZPW3ta1wS9qLfKAGmsHHCRy1xMFXuEH3d+YCNe0aVPBfTpq1Ci7iAAmvUEwtAPDRFq3bi2XXHKJDBgwQGrXrm2Nz0KV6YMhuvrP7b4k4ES+VJlCJceLSYAElEAWz6xn0UnAUwTeeecdoy9Oo5N4rEsWbRmzDr918oPRlhyjLTf2/Lvvvmt07KXdHz16tL8McOR+773qRkZFV0ExOhHI6EvaxsOjjo+OJ7ThcP+irZ3myiuvtMep+mrRooXR8YGpyj7mfLXlMoirwxdO2b0uuGd0HGzi1PzoTbRh+j5X1jJm1YoC5YWFCa655hqj3d+WsRr5pk+fPkFpqOFptIXZ4BnRmf5B7qSCIkZzsOkvY+5sE9B54IPRXMU4JEACURDIQRz9gaSQAAl4iMCGDRvsRJxwLo3ioeYDDzxgWzkxUahmzZrxSDKmNL755hupXLmydUkTUwK8qMAEMDt7+fLlifUm8PFwkcvaB3R7VVs0290mclDeHky5MS4AAEAASURBVBQCFyRhb9cukY+HibS9IZDZy4+LdLkvcMw9EiCBQhHgmMxC4ePFJJAYAhhXmSgDE7OjX3zxRbtiSioNTJDjf9zE3D/5pZpw7i10/fLV6lKona4DDrn5XpGD1Y1W71vVB9FyeyplXxt0gt2zOnmrRImAgdlQu/qxwg8NzJRVCzPOTAI0MjOzXlkqEohIAOPZNm7caGdFR4yUpIBM8JOZJFRxyyZhfjJDNSx/tI7RnCHyxQcijfY5qX/oZZ0GfqzIBTkiAx8Q6+4oGZ1pyxeJDNJxsy1OFClzhEi3Pj5tq+tmxCsiE9Ql0omnhJaAxyRAAoUkwO7yQgLk5SSQbgS++uor6+YIM6MpJJA0AnO+FXnlEZFXPw/OUu1NueZckRp1RU6pLVL9DJ8hqhPYCiwwWP9cLTJPfV1iHfKfvxH5cqLIbyEpXa4+Pe9Qo7NukwJPTApJiYckQAJ5EKCRmQccBpEACSSWAPxkNmzY0K54lNicmLpDAH4y4bUgZTP7t/wtMk0NzS9GamvmKEet3NviekrtTTlaDcIjjxU5pJR6Yt9PfaIUVT+ce/Xzr8jWzSJrlutyP2pQLtS46/UTSa6/UKRZO5EGl3LmeCRGPE8CcSagA1EoJEACJJAaAgnx15iaoqRVrinljrGZF1/h+zyjxiLGQmKVnZ+/F5kzSWSMdm1DdulHe9tFftr3wX6U0risSO3m2ip6praOqqV68ulYEijKixmNBEggXgTYkhkvkkyHBEiABEggPgT+2a6tkmt8n3Xa/Y3P1i2+1svde3ytmWjV3F/HepY9ct+nvEhp/WAGeyxd7fHRnKmQAAm4CNDIdMHgLgmQAAmQAAmQAAmQQHwIcHZ5fDgyFRIgARIgARIgARIgARcBGpkuGNwlARIgARIgARIgARKIDwEamfHhyFRIgARIgARIgARIgARcBGhkumBwlwRIgARIgARIgARIID4EaGTGhyNTIQESIAESIAESIAEScBGgkemCwV0SIAESIAESIAESIIH4EKCRGR+OTIUESIAESIAESIAESMBFgEamCwZ3SYAESIAESIAESIAE4kOARmZ8ODIVEiABEiABEiABEiABFwEamS4Y3CUBEiABEiABEiABEogPARqZ8eHIVEiABEiABEiABEiABFwEaGS6YHCXBEiABEiABEiABEggPgRoZMaHI1MhgcQT2LVLZMInic+HOZAACZAACZBAHAjQyIwDRCZBAkkh8OT9Io1biNzcVmTLpqRkyUxIgARIgARIIFYCNDJjJcfrSCCZBL79WuSh/r4cB30gckObZObOvEggNQQ2bhC55UqRDetSkz9zJQESKBSBHKNSqBR4MQmQQGIJoNXy+MNF3O/ZBb+IVK2e2HyZOgmkkgAMzKYni3yvN/7pJXWoyHKR0mVTqRHzJgESKCABtmQWEBijk0DSCXS/MdjAfOUZGphJrwRmmHQCj/bwGZjIePZ2kYsqs0Uz6ZXADEmgcATYklk4fryaBBJL4KMRIq3aBfJocbaYj6ZLTk5O4Bz3SCATCfy9We/9s0UmLQyUji2aARbcI4E0IEAjMw0qiSpmKYE/VopUqBRc+NV/iJQ/Kvgcj0ggUwnQ0MzUmmW5soQAu8uzpKJZzPQiYIdK39QyWOlP3qeBGUyER5lO4JBDRUZ/K9KwaqCk7DoPsOAeCXicAI1Mj1cQ1ctOAjkv9RP5bFag8LdcLdL88sAx90ggWwjQ0MyWmmY5M5AAu8szsFJZpDQnMP9nkVNqBApxtO4u0PFpBx8SOMc9Esg2Auw6z7YaZ3kzgABbMjOgElmEDCKwc6fI1bWCCzR6Kg3MYCI8ykYCbNHMxlpnmdOcAI3MNK9Aqp9hBHp3F/l5T6BQj98jcmbdwDH3SCCbCdDQzObaZ9nTkAC7y9Ow0qhyhhKY8qVI/YsChTungsjXS0X22y9wjnskQAIi4brOaxQXmfg7Hbbz/iABDxFIn5bMTX+JYKzatq2pxbf0V1154hMRuJdxidm7V8fN6Sosa1e7znKXBKIkgNVNmrkMTFw2bAINzCjxMVqWEQjXovnTLpFG+sfMC0tQrlwugndFKgW/KZM+F/lpZnRaLJwnAr0pJBBHAuljZH7wtm8yxKzvfMX/borI5x/FEUUUSb06QJf3U1cajVuIDB4YdEEOftiqnSby1AO+8zA2h72SeqM4SMssOUjFvVFYtF076b3iSuSNF3z3musUd0mABFwEvGxodtZ3BN4VkFS8C9AgU6qMGt0Xi1xypk+P/L5P1mVq7+rsi5UKnfPTL5vC0/EdFqF+0sfIDC3ATQ1FLm4lskv/vSZD/t4o0uUuX0597tMlzprnnSsMzA63iHz5Wd7xGBp/Asm+NwpbgpFDRd7S1nFHLr9ApONtzhG3JEACkQh42dB0dE7Fu+BRHdsNueUqkWeG2t0CfaVC5wIpmOGR0+0dlkd1pK+ROXiy+hH8UKS4jsPJS9b/qf/ObsgrRnRhi/d1fdxzs8i9j4uc2yDv62BgDn1RjdFL8o6H0AfuEFmzKv942RBj8niRIc9HX9Jw9RvtvRF9LomLuWKZyJXaiumWl991H3GfBEggLwJeNzRT8S6YoENtIC/psrRXXOfbL8h3QXQO9xtckLwyLW62vcPyqb9i+YR7N3iVGmWbdcyJitmzR3KmT9ZB39pqeNwJIg2ailQ6VmTdWpELy+tsXY10fBXRBZ9FrleDrkQJPRFGMCZl1rfaOrrD1zXvzOpdtijQPf77cs1nrHZD5GM8Iu+tOn4U42JKHiiyZKHIWDWKd6mLmguaiqlZR6RIEcm5p4tIv0F2X444Sid+NBapXjNIOYz3zHn1GZEqJ4scq+UbPsRuTbsbJEfTEBgqn4z0jROtcYZIm2tFimnVQoeRb/rSKqaTRyodI1LrHJFyR9pzMaeLq8OUJ6doUV9eUyeKTN33I9eomchZ5/vOY2zQtEm2/DL5C5E/14g0bSFydn1f+CStP3BtrfF3/KNlPF7HKbYR+WKMyHfTfAP6L23rq1tcEal+XfeGL2H9jlS3iJCfXv5E4rtj71t0q7kFZS1zhPsM90mABPIj4Bia7rXOnTGaqZ4MFPouQK/Y5x+LzJvt++07r6EY9YEbzbvAwWB/O775SuR/C0RQ9rPqBX4XMawLr8ay+nm5v7Zm7mvVdC52thjihWFo+C0/Rn9r3RKqM8K+n6oTEfV3/S9NvNqpIi2v0t9pfZ9F8Y6N+V3Dd1igVjz4Dgsol8eeLl+XHvLaQGPUnjRTvvTpe+GpvmMcvfCUbx/hzmfrFmOquo6d8+v/DF/eXl0C1zpxW9czBul8Nio4rH2z3Gn8ucYXp9v1vjC3vk6Yky62n39kzH//E5wuzg99MXfaO3b44p1TITj+e28Y8/3U4HNI49Kz9Jnea8yPM3KHIXzwc748Yk03UnmQap/7cufplKn/Q7nDoM+40cZM+yp32MU1jRn4eO7zEz7x1Uuk+nXfG9Apr7pFeF56ITxR8vQjwWXr1ilROTFdEsgOAps3GdOwavBzVaO4MZF+9xNFxf0b5HoX2N/lescH63fT5dG/C6DvHyuNOfeY4DTwO4r3IAT7rs/ePXt8593fC34JiuOPf/kFvlgune2Jvg/kjo/f9Ui/we68sB/ru4bvMB9Jr77DQus5zLHejWkioTe9+yG+7FzfA/DDN8bgc9/tPiNr7WpjcrSI1fWDfRhH4eTNl3zX1ylrzKi3fUZls9q+cz1uMmbXLmPef8t3/PwTxmz+K3cqjuEVzsiEMYiHXvWyPxAwnH6ZbczGDcZ07egLmzndpx8exlBxHlCk8Uh3Y776wpjbrjFm505japfyXT/+Y59et7bzHcNwcx7QnlqGn340ZuSbvjCk89PMwINf0HQjlWfxAl/6pxU1Zuki/fxqTEXNC+lv3xYw5u7o4NN94jhf2PWtjflnuzFffuo7RhlRX3+tVwPxVmPuvc2Y5UuMeesVX/h/rs27ft33Rn51C9aOkRlOr9C6iNcx+IOL8zlO97dtjVfqTIcEspfA35vDG5rr1iaPifs3yP3uwrsDz/zR+vl7ozEfDjfmvaHRvwtQAufd1OUKY6ZONGbQAGMO1fSQ7tRJxqCc2IcOkcrcuIYvzsN3+947a1b5jsMZmW6D9N3XjVk415gBjxozY7LvdzqadyzfYZn3DovyadI7MU3E/aBCZfdDPOxV3wOCB0v/Xdl/i06xSuk5GI95SbNavuvx4ncEBg7SwweC1jPsw9AJJ3kZmc4DjOvVQDL4t+3Ig3f60l222DmTe+s8oPowB5UNP6aOjt1vNAYftL7i3OP3BIzMpx4IpIkfNYQ/+1jAyCxoupHKM2KIL20YmY4+lTUv5Dd3TsCYQ+urii0LwtBCC3GMYujmCH6IIfixxI8p4t/QxncO3+Hq131vRFO3jpEZSa9AbvHZg8FdZR8XlAefWd/FJ22mQgIkoAZcBEMzWS2a7t+g0HeX0yiC99Ls7wO1Fc27APrj96JyyLvA+eOP310I4rQ427cf+o3GCYTrZ+/u3YFQnAtnZL7+vC+++z0SuCr8b7A7HPt8h2XWOyy0fvM4Tt+JP+4hAO1vCkwW0Vm5OTe00qdFH6FoZfEsX8yT1IWDI4eXFjlt3xjD7ducs7FtMQZy9veanl7+/DBdweUwkVW/Fzyt9pfosFIdV+rIP9udPV12UMfl4FPjLJFHdAxOrbMDYe69MuV8RxgP6UhB041Unq1bfCmW1bGjjj6dVBfoc9DBTm7+rS1LZT3cttp/LtdOseIiD3XV8UWq96i3fMF7d+eKFvFEDHUblV4RM4wi4EEtjw7z9Uu/B0VO1zG6FBIggfgQ0DGO8tF3Ig2rBtJzxmim2o/mWzr2/PrWOsZRx0Tiuf9IJ+dEK87v9vmXBr8Lztj3ex+Nb06Md4dcXFP84+h9Z8J/O7xOOCl8eEHOFvRdEy5tvsNE8rFPEv4OC1cvEc7p7JAMkN+WinS+XaSJTqJoow/t62Mkp8s3vuX4dM6NrNaHOS+po5NTFumDP+bdwEy8X2b7lvcrrxdi4k5h5I8VIifrQOmZu9Rg6ibyxIuq4/Mi/31KpKhOyIFgBYv8xJlY48Q7QpVTW9gO8r5Z3Svtm9Bj0/pzVfg0Rw/3XX1SNScV1WGfMe2cyS/dSOVp1sqXQon9xTzQN/AjuGh+QDcnj3BbGJQQN4shz4n0Higy+l0xl13hm+jki+X7zq9+E123bl2i2ceksf6vBWI20CbNbg+K669DIIx7JEACsRNwDM2W+sd70kJfOo6hmarJQLv1D/IW/a0fPEqknb5z7ETHdiJ7r47uXXBcFV854PJswHqfL0ycGfGG7/xpZ/q2eX1johB+cMbN8f3W4jgvOX6fcTl8kJhW7QK/6841+f0GO/GwLei7xv0ucNLhO0wknvaJwzVB28xoybxcH6xmp+tMOW0l3KwzqiGOwYJZ5Sv1uMdNaoDWF3l7kA0O+rr7Yd/hlR3Vce0ZIu2baqtjLd+5vi/7toX5hl5HH6DGxcNq8EIZFefBLneU77jnDSJ3XufL23cmuu97H/LFK6/pdLlC5Fb9wTpUW0o/1R8xR95RY7a/xkPZBryhbp80oJX+qOUleaUbqTynavpnlVPXUjMlp6LeWnD31LahyEmnaLmjaLlFayXkoX4+t05nqxE95wffuU3rJef5J3z7P0/V8n3g28+vfhNdtz4tovuGq48LmwfHHTouutaE4Kt4RAIkEA0Bx9D0SovmymUiFY7x/db/+K2vBGX2FSSadwE8ozza03dB6bIiN16uM9T1d1L/1FtBY0s08lJ/X6x6+q5AT9GARyJf1eQy30z1D6dITjn9Xcd7qqm+H5/r47smv9/gyCn7QvJ61zjX8h2mru46JsY+cRgnaptHV7q3gpxxIRhsDGlyum+cCPYf7enb3zfOxDxxP8765OsJgckxCB/7gRMSvMWsdUwQctIorfsYY+iIMyYTA5/DiTPY2hkT49YXOmCgt5M2xr044zI3rDPm6saBMGfikDsPZzxL58vcZwP7KD/GJjrpYzwQJvo4Yxyd89jWP9GYBTpwGxJrunmVB2NTr2gY0AV53nmdbza4M/bRPf6wsoZjDKcj7lmMmBU6+YtA2TCr3xnrhJn5kHD16743ECe/uo1GL6RTWLnqomAuwwcXNkVeTwIkEA2BZI/RdP8Gud8FGOvvTNzBb2OtQ3wTOVGGaN4FiPfvv76JN7je+TSq7hv3jnAIzrc6z7cf5tuOh3/t2dyzw69p4ovt1hlnMKkT3j6c/LBFHEi432BfSOA71ncN32E+hl55hwVqNOq9HMRMlAGbzHSt37DNG8UcVip3lyoUgW+yQw7PXyU0z+/dI6LpxF0cn5nanZxLkC/OR/LhmeuCMCfQUga94SMTAp+fZ5zjW+oSvtLQVRFL139our7UAz5Aw5UH3UJaH4J/2wUVXLv1b38d6AwhycH40wMP0l82IzlbNuWuy2jqN5F1m18ZnRU0nHjtm+myo2OdI25JgAQSTWCL/qa4u86RXw3t1klF1znGRWIMezifuAV5F2z6S+QA7a8uzHujINx37tQx9Ko3lqwMlWh+g0OvCT0OfdfwHRZMKJXvsGBNoj7KGCMz6hJnU0T3A9qzdzaV3FtlhTP/4/aNa4JmGA+1fl34H2pvaU5tSCCzCHjJ0MwssokpDd9hieGaxFR1gAWFBEggYQTQKtuhaXDyk76ggRlMhEckkBwCXhujmZxSMxcSSBkBGpkpQ5+EjEsfIdJJZ9xXr5GEzJhFWAL9H9alNJcFgnp10WVPGweOuUcCJJBcAnkZmuiupXiHAN9h3qmLGDVhd3mM4HgZCeRLYOZ0daN1XiBadd2dqWOxwo1hDcTiHgmQQDIIROo6/1I9gIQbK5kMnZgHCWQYARqZGVahLI5HCGzbqr5R1QH9Po9VViv4Nqte0yMKUg0SIAGhocmbgAQSSoDd5QnFy8SzlsC9twYbmPDxSQMza28HFtyjBPxd59UCCsJh+4UVdXIeu84DULhHArERYEtmbNx4FQlEJjDuQ10coE0gvMnpYuCgvgj/0wWgcI8EPETAtmiqu7dJ8wNKwb0Ru84DPLhHAjEQoJEZAzReQgIRCaxdLYLVl9zy+2+64lMl9xnukwAJeI0ADU2v1Qj1yQACbFrJgEpkEbxBwK5rcEvbYGXsEpw0MIOh8IgEPEjAdp3PEGnIrnMP1g5VSlMCNDLTtOKotvcI5Ax5XmT0NwHFrm8t0qZ94Jh7JEAC3iZAQ9Pb9UPt0o4Au8vTrsqosCcJ/DpPpCp8FO2T0rpdqku+RbOUqXMNtyRAAt4gEK7r/DRdlnfiKro38kYNUYs0IcCWzDSpKKrpYQK7dDZqhwuCFRzzFQ3MYCI8IoH0IRCuRfPnPSKNdLw1Z52nTz1S05QToJGZ8iqgAmlP4In7RL7XtcgdeairyHkNnCNuSYAE0pEADc10rDXq7DEC7C73WIVQnTQjMH2yGpSuVsxah4jMUIOzuLo/oZAACaQ/AXadp38dsgQpI0AjM2XomXHaE9iySaTy4SI69NIvC+bq2MxT/IfcIQESyAACNDQzoBJZhFQQYHd5Kqgzz8wg0P3GYANz0AAamJlRsywFCQQTcLrOG7km93GMZjAjHpFAGAJsyQwDhadIIF8CH40QadUuEK3F2WI+mi45OTmBc9wjARLILAJo0Wx1ns4y1x4LRzjr3CHBLQnkIkAjMxcSniCBfAj8sVKkQoiD9dV/5F7pJ59kGEwCJJCGBGhopmGlUeVUEWB3earIM9+0JGBX9bmpZbDun7xPAzOYCI9IIHMJoOsciy6w6zxz65glixsBGplxQ8mEsoFAzkv9RD6bFSjqLVeLNL88cMw9EiCBzCdAQzPz65gljAsBdpfHBSMTyQoC838WOaVGoKhH6+6CzSJ44VBIgASyjwC7zrOvzlniAhFgS2aBcDFy1hLYuUPk6lrBxR89lQZmMBEekUB2EYjYolmOKwNl153A0kYgQCMzAhieJoEgAr17iMBliSN9eomcWdc54pYESCBbCYQ1NBVGIxqa2XpLsNwBAuwuD7DgHgmEJzDlS5H6FwXCzqkgMmWZSLFigXPcIwESyG4CYbvOFcnEtSJljshuNix91hKgkZm1Vc+CR0Vg4waRimVEtrliL14gcnxV1wnukgAJkIAS2LZV5LJzQvxo6nkamrw9spQAu8uztOJZ7CgJdO0UbGC+8QINzCjRMRoJZB2BAw8SGTMjxL2RUmDXedbdCiywjwBbMnknkEAkAiOHilypRqYjl18g8v4k54hbEiABEghPgC2a4bnwbNYRoJGZdVXOAkdFYIWOuTzmuOCo6zi2KhgIj0iABCISCGdoYunzr/g7EpEZAzKOALvLM65KWaDCEjB7dBZ55xbByXwxhoP3g4nwiARIIC8C4brO5+oFF3DWeV7YGJZZBGhkZlZ9sjRxIJDz/BPBA/e7aZd54xCjMw75MAkSIIEMJ0BDM8MrmMXLjwC7y/MjxPDsIvDzjyI1agfKjB7zX3TGaMkDA+e4RwIkQAIFIYCu85bninz5S+Aqdp0HWHAvYwmwJTNjq5YFKzCBf7aLtHUZmEjgg+9oYBYYJC8gARIIIoAWzY+mi1x4auD0XN1F1znGelNIIEMJ0MjM0IplsWIg8GBXkUWu6/o9KHJ6HdcJ7pIACZBAjAQiGZoNy+c2NP/9V4wxMWbEy0jAOwRoZHqnLqhJKglMHCvS/7WABg2qiOmmRiaFBEiABOJFIBpDc9cukU6XSc7cOfHKlemQQMoI0MhMGXpmnFICPW8WgZsiyPo/tRuruW/f+R46TnKKFnWOuCUBEiCB+BDIy9Bc9bt6tmgpMnycOnV/Nz75MRUSSCEBTvxJIXxmnRoC6IbKKbLv/9W7r4uMHi7y3sSAMsMHi7S7PnDMPRIgARKIN4Fwk4HceVQWMUv3Sk5Ojvss90kgrQjQyEyr6qKycSHwxwqRCseET6p9M5Fh2nVOIQESIIFEE8jP0Px5lsippydaC6ZPAgkjwO7yhKFlwp4lsMQ9uydEy4FvhpzgIQmQAAkkiAC6zt+fHDlxdplHZsOQtCBAIzMtqolKxpXAkoWRk+v3kMjOHZHDGUICJEAC8SKAST63t4+c2pC+nGUemQ5D0oAAjcw0qCSqGGcCixZETvDJl0TqHCCCLnUKCZAACSSIgNm7V+T6Vr5JPpHyWC6cZR6JDc+nBQEamWlRTVQyrgQWuVbdCE34ND3RT9cpP7pSaAiPSYAESCBuBOzkwydfEXm5v4i6TIso7DKPiIYB3ifAiT/eryNqGG8CFXS25h8hiZbW4xeGiLmiY2DmeUgUHpIACZBAwgj8sVLkk5Hq6WKQyGTXuPHKnGWeMOZMOOEEaGQmHDEz8BSBnTtF9t8/WKUXnhS54U6REiHng2PxiARIgASSQyDU4OQs8+RwZy5xJ0AjM+5ImaCnCSycJ3JydZ+KD98t0u1+kUMO97TKVI4ESCCLCcDg3Lld5LiTshgCi56uBGhkpmvNUe/YCIz/WOTTD0R69RE5qkJsafAqEiABEiABEiCBfAnQyMwXESNkEgHM6PSv9pNJBWNZSIAESIAESMBjBGhkeqxCqA4JkAAJkAAJkAAJZAIBujDKhFpkGUiABEiABEiABEjAYwRoZHqsQqgOCZAACZAACZAACWQCARqZmVCLLAMJkAAJkAAJkAAJeIwAjUyPVQjVIQESIAESIAESIIFMIEAjMxNqkWUgARIgARIgARIgAY8RoJHpsQqhOiRAAiRAAiRAAiSQCQRoZGZCLbIMJEACJEACJEACJOAxAjQyPVYhVIcESIAESIAESIAEMoEAjcxMqEWWgQRIgARIgARIgAQ8RoBGpscqhOqQAAmQAAmQAAmQQCYQoJGZCbXIMpAACZAACZAACZCAxwjQyPRYhVAdEiABEiABEiABEsgEAjQyM6EWWQYSIAESIAESIAES8BgBGpkeqxCqQwIkQAIkQAIkQAKZQIBGZibUIstAAiRAAiRAAiRAAh4jQCPTYxVCdUiABEiABEiABEggEwjQyMyEWmQZSIAESIAESIAESMBjBGhkeqxCqA4JkAAJkAAJkAAJZAIBGpmZUIssAwmQAAmQAAmQAAl4jACNTI9VCNUhARIgARIgARIggUwgUCwTCsEykAAJkICXCfTt21d+/PFHycnJkSeeeEKOPfZYL6tL3UiABEggLgTYkhkXjEyEBEiABCITGDlypKxatUqaNGkipUuXjhyRISRAAiSQQQTYkplBlcmikAAJeJfAySefLJ06dfKugtSMBEiABOJMwFNG5pgxY2TatGnStGlTadSoUZyLGjm5PXv2SO/evWX79u22peHCCy+MHJkhJEACJEACJEACJEAC+RLwVHf5X3/9JcOHD5fx48fnq3g8I+zdu1dWr14tb7/9tkyYMCGeSSc9ra1bt0qHDh3kyiuvlDvvvDNs/ps2bZLq1avLkiVL5Oeff5ZTTz1VwMCr8s4779jyfPXVV/Lkk0/a/d9++y0h6o4ePVqaNWtm03788cflnnvuKXA+S5cutTr26dNHvv76a7v/7rvvFjidaC6IV13ecccdVs/169dLu3btwt47KA/uK4SvWLEiGvUYhwRIgARIIIsJeMrIRFdSzZo1k14d++23nwwaNCglece7sH/++acMGzZMjjrqKGnYsGHY5F944QX53//+Z+M89thj1sAsUsRTt0KQ3i+//LJ8+umngu7Gp556yhrGFStWDIoTjwNjjDz88MNywAEHyObNm6Vfv352v6BpQ1eMwUMdvPXWW3YfuidC4lGX+IP1/PPPy5YtW2TmzJkyYsQIOfjgg3Ope84550itWrVs+K+//pornCdIgARIgARIwE3Ak5YFDKBLLrlEypcvL507dxa0DLnls88+k3r16kmpUqXsLM1bbrlFNmzY4I4iaHU577zzpFy5coKXI17GbkEX+YABA+Tiiy+2XeTYD23N27lzpzz66KO21e/QQw+VGjVqyKuvviowRiBz5syxaZ911lkyatQoee+996RBgwY2z//+97/u7PLch1H40ksvhf0sXrw4z2sjBaI17rLLLssVjJbOZ599VqDz8uXLrd5uYxSGFcJ69OghLVq0sGW57rrrrFHqTgytihjWcNxxx0nlypXlrrvukrVr19oovXr1smmgDsuUKWOZILxs2bK2FQytb47kV5cYwvD999/LTTfdJCtXrhRce++990oijOJPPvnEGrCoQxhdMDTdbJo3b27Ldf7558uyZcvkmWeescfg9dprrzlFErA55phj5JprrpFJkybZexn3Trwlv7pE/UC3s88+2+oBligbzqEMOIZMnjzZbnHPQt+SJUtK165d7Tn31wUXXCBXXHGF+xT3SYAESIAESCAyATWYPCVq9MGCM+3btzf6EjfaYmXUwPDr+P7779twfdmZDz/80Dz99NNGjVFz5plnml27dtl4aiwapNO9e3cbp2fPnvaahQsX+tNp06aNUUPFqDFmOnbsaA488EAbB3EdQR44/8ADD5ixY8ea22+/3cbR1j8bZePGjeaNN94wamSZatWqGTWobJ5dunQxt956q5NMnlvoqi98c/rpp4f9oLwFEe0CtzrqkIOwl2mroClatKhBGdQ4t/sff/yxP+7s2bONtibbNLRr1KjxbcunXfD+ONjB9dptaoYOHWrU8LZ1oAa5jfPNN9+Y448/3pxwwglm4MCBZv/99zdqpBuEH3LIIUa7pG28aOpSDTZTokQJ8/vvv9v7Aaz//fdfe328v3QcsClWrJiZO3eu0T8n5rDDDjP6R8OfjXbbmyOPPNLo7GCjBqj56KOPLKcbbrjBLFiwwB9PjWmjfxqszriXp0+f7g+L505+dal/Xmz9Nm7c2OgfAJu1DjewOj/yyCNG/2jZc7hX1YC0+/qHzHTr1i2imvqHL8/7K+KFWR5wxhlnmBtvvDHLKbD4JEAC2UYArXKeEhiH5557rl+n/v37WwPGOaHjB412PdoX+B9//GHwUb9z9sX35ZdfOtHMjh07jLbQ2DAYoto6Y7Sr1YbDCMLLX1ur/PF1bKI95xiZMBoQ5+6777Z5OHnhJawtqP7rsFOnTh1riC1atCjofLQHeNnDcAr3iTYNJ15+RqYTL69ty5YtDV6KjoDT4Ycf7hz6t/Pnzzcvvvii0bGLRluWTe3atf1hqENtTbbHdevWtX8acIB9bTGz56Opy927dxvtmrXxteXNaAui3U/VF+q4QoUKRlsJrSEd7s+EtsT7//CAUSoFf6C0294+D9AD+p522mkGf24c0bHQRrvM7SGM+b///tsJyrWlkZkLSVQnaGRGhYmRSIAEMoyAp2aXq1FnBd3cjpx00kmiLz17iO5sfWkLurr1Re9EsVtt7bJjynAAp8foDkR3OroG4QAZHycddHND3F1/mPxStWpVex5f2ppl99VAFXzcgi5gNWJFW+j8p7WVU0488UT/cbQ7ej+Jtpj5dQ+9To04UcMg9HTCj0PrAF3HjmAYgRqRogaXaAuyYHykGuGiLaROlKAtOGkLpD2HOvnnn3/s0IRo6hJpVqlSxV6LsZJOOkEZJPEAdYxhEeCDMZfoMg8VbcH1n0rUWEx/BvnsaCu8nUw3ePBgO/wBW0xCwvPgiP6BcHbl6KOP9u9zhwRIgARIgAQKQ8CTRqb7BeguHMbhaXelnXygXZXuoKCX5v333y940cPY1O5P0W500e5sf3wYiRCM9cM4OwgmzGC2tSOOEYvxkhhb55Zw+oU7574m0j6umzFjhmzbti1sFLfhGzZCCk5iFj4MdXxgnEO0xVcwpjFaibYuo00P8TC2EJNuYDThHkiE4D7R7nFp3bq16NACu9VhG4I/OQWVZOiLMbPammknTEHfU045RbSluqCqMn4cCOhwHRkyZIhcfvnlgjHeFBIgARLIdAKeMjIxqQMtZuvWrRNMasAEBO2+s0YitjD8dKymYIk2TNTByxITfiZOnGhn8KLFEZMT8GLF7FcYb0gPk3VgQMJAQHz4wYShickNmEyCfR07KNpd7c8bs2jRCoWJPzAg0HIFowoTVaZMmWL3MRsXrnQwgQL6wR0QjEa0vhYvXjzqewcvfq8IeKEedCyqbV3FFmVDKzLc1lSqVMnyxfF3331ny67jVe1kIvwBQFzUG5hgIpAzuQR1ihZQCNzkoCU4mrosCBfUP4xMTBJKhOgQCuvCB3WL1kzturd/eC699FLbWoiJTQWRROvr6IIJPW+++aY1cHT8bdAfMicOt4klcNVVV9mZ+/itgg9gGpmJ5c3USYAEPELAS93/mEChWOwHk35mzZpl1Gizx2rcWFUx1vI///mPnaDhxMWYM/VnaNTos3Ewhk+NRHsdJvfoLGmjM63tsTOBZerUqUZnANtzyEMNBaOthvZYZ1/708EYQicfbDH+UlvybLjOmA4KQzjS0hY9G56Kr8KOybztttv8ZcIkEYxVxUQhlA2TXhzBpB9MyMF57UI2OuPblh0Te7Slxp+Gds8aTKBCPDUA7SQu7H/wwQd2nGB+denkl98WYzeRN3QFg3iLLglo1NWVLQfKrbP+jXos8JcTE9UKIonWN1QX/WMVNGY2NDzaY47JjJYU45EACZAACeQAgb70007QBY5WRLQIHHHEEWH1RyslxgCiNS6coOhIA3HUQAkXxZ5D696aNWtsS2qktCJenOQAuHvSmd3Wof1FF12U0NzBBS2VaMEsjERTl/ml/8MPP4j+AbCtoxji4HVJpr5wg4VWeayo5Tiaj5UPWm/RU4AFExJ9f8WqI68jARIgARLwBgFPdZcXBAm6LPObaJOfw250bVfeNyElr7xhyKZb99a4cePskINWrVrlVbRChcWLSzR1mZ+i3377re0Gvu+++/KL6onwZOiL4Qz4EwWjG3+i4DO2MKLeG+w45sKkwWtJgARIgASyh0DatmRmTxUVrKSYQKRd3nbMI1oYMXY1GwQz1n/66SfreDwdypsMfTHmFYamIzr0Q9Svq3NY4C2W9MS4ZMz4x2IHOtykwGnwAhIgARIggewhQCMze+qaJSUBEsgAAhjmg8mHGK6CVbkohSegY6TtJE9nouLVV19tJ/VFShlDkuACT300R4rC8zESwARdnTNhJ9xi1TJ4iAkVDIXDJDr80a1fv35CVoALzTPVx3ju1ce3wEsFVqLDsKVwkh8brE6Hyclw85gMKZKMTJgHCZAACZBAfAhgaVB4yMDypaECzxDVq1e33jTg7QIuxuAJwquiq2hZjw0oC1rKdZUxO8SjoPrqKmL+8ca6OIToRNCgJOBiDWnjA7/D8LXsFjDSyX3W28igQYOsZxJ3eOi+rvYWeirux3fccYfVF944dKKl3HnnnXHPw0mwU6dO8sorr9h7BUs2T1Z3cAWVeNQlelrQAwe/0ygzfBHDaHILXA/CIwvc1MEIvf76693Bcd2P1/NU2LqEHqgXeKbAstAYKgg+oZIfG/yZGj58uDXM8UwkRdQ6ppAACZAACaQBAazGpC8Go60RYbXF0q06xtloi5xp27atXe42bESPnIT3DqzGhhWnsIwrPHw4y51Gq6IaiHYVK/Vda/RlbJewfeihh4Iux/K4WEoY7PBxL6UbFFEPsEQwPEfkJcgzkQJvFtATK+Dp+Hq7r0ZVQrLEqmTwwjJixAgzcuRIm9e8efMKnFc86lKNW6MtlHZFMtzrOqnX9OjRI0gXLMPcpEkTG2fSpElWX3VXGBQnXgfxeJ7iUZc6FMwudQyPO/9v7zzg5qiq/n/y8lJU5FVQQIoBlPpHmjQjSFNKQpGmWELviBQB6SGAisQCBIL0SJESaujSpAXpTRRpoWkABRSpUu7/973z3N3ZfbbvPs9unpzz+ezOzJ07t/xm5s6555x7DsTzy/NBGOg8NYoNoa8lzcxfOmD7PRdWcsB66gU7Ao6AIzCdI5BcSEld3q8nuHCba665YojXxDhIIlTIJ//C0QXbfvvtF1228QHHpVt5OFw+3HzEF1544ejmjVj28q4Ry8FVHG7c5KUg1iVVZYx1L1/DQSrmIAlfoT75z41hZAlJqwWWgQ+bpHKF87Ifjwyx/BUHSWDiR1P+XAvn8zuSdAaYLEViyyfHfXlNiNeecMIJAaaAj++tt97aLx/9gGnjN2rUqH7nU0ItJhOGh/7zk+QuXVLY4mJPUbYio0q/CUMsH6mFULpkJM+RRx4ZJI2LbtcI8yopYkmoV8qmH4RApk4YcfkaLtTTyR3cr1EXzNCyyy4bmZlUvrxgxHtIfxWUJCaDHcf0LT07jd5LQieffPLJYdy4cUHmHqmaqltcEcrvceG8fC/HtioYSyGNMNPc205TvfeJMNXpWdCC01j9gQceWEi7/vrrY1qj97IeNjw3iXgWuGc884mawYZw3byzg0HOZA4Gyl6HI+AIOAIdQCAxY0mikS+Sjzd+Yo8++uiw2267xf28xA6px3LLLRc/TlIbB6R7MH/Jd3Aqi+vxgztx4sSgQBZh3nnnjcwb52F6ZI8YFFEtKIBFUMjYKDmEucNPrdTWsZhJkybFevCRq4hYQYEHYjkKQxvksizmgXHE56wCOAT8ItMWPrTlpEVykcnio7riiiuWnw5SIUa/yTCg8qAQJaIK/FCSjzoVLCFK62BQkNwpuERJnnRQi8nEvzKYyB6ugEm6jq0ChER/uvhdhgGAGafdUusWsoGJXOFFZhRGnIkAecA9kVT6QYFF4iHM3EAwURTO5IF7AHOJBJHnJ/88MClQMIfYPiYREFuF+A3jx48v+KZu9F7iH5m+8oNJq0bgsu6668b7ed999xWysc+1ibnlBBJqfp2meu+TIgpGCbq8rAR5C4nVT5kyJT5n+CVWqOWY1ui9bBQbCkVSj99mNACJmsGGSQ33vfw9SWV1cutMZifR9LIcAUfAERggBPjgE+iAgA9IjlohmKAvf/nLhUthFJC4lROS0JNOOinIvjFKRvPM3YgRI4K8C8RLUJGmQATsw5BAsgUNSJhgIPnY8tMimcggyBVWzENAAgJnQKj35YM17lf6U8S1eC3S0FYI5hcmmHqoV9HjwuGHH16xqFpMZroAxi/PFJIO0wEDlC8X1b/cyBWYIEUNi3lkD1fABWwoT/6aU/HhtddeKzAQYIjquJt05plnRkZ+p512igzyddddV9KcRu8l/ec+MDmBkaxGTFqYdBAAJD0v5GUfjBMDRxpMMRONbhB9oD0w6BDMNhOYvLlBo/eyUWyYwFEH71OemsEGTQjtPuKII6JkPV9Op/edyew0om2Ux8yOWS5SBtRiTo6AI+AIgACSOD7MfBgSI9cKMjCZWoRQuFRO9eMHKyWgkkNFOfvss0dJGh9wpHZE9UqUZzKR2KT2EFkN5gnGCokYbS3/IT1J0s5UXqPbdtTFRHzDVhXGlx/q5/nnnz8ynOX1t8pkouqnvzDoecJ+M0lok4S3HBeOUV8ite1V4rmhnbvssktbTaSPKTpfrYJ45pEEL7/88oVs2CbShjwTx3OHSUK3aNVVVw2YjUBsk8Q3JjT5Vw8bVPA8x5XuQTPY8Exi9gCWqPwHknx1uVDuFZLRdVzhKHsok21VrzTL2+EIOAJdRkCqMWN80AfNtCjFWCU6EKSQudEXqtR+JtvMGPNejGlTVUnKElcI415JH7OSn5hYa7Y8Kie4BL5ZZSbQVFvIjEuca665xqSSN6nt40+SuTjWShLVdHnVLpDkLZ664447SrKIcYh1kSgJajxHgIRybMREmyYSJdc2ciC1vMnO1hTOuJHsLeWR5NIUIjiu+gY7qZJbKkeMo0lCHu9BvRX6PPOa8JgYyoI3gOFyWUS6VMOF+iVBtsUWW6xwnHZeffVVO+CAAyI2Mo1IyR3fyr7WZANsY8eONe69VNkt1VEPG94BTZaixwEwLKdmsAFTnn2ZJMT7UV4Wx3gY4LnCW0NbNJAcbLNlYzPErADOGvuECy64IM4MMFDPr6xjJswqKuxvmHUS/1oPVKxu9OjR8XrKYaVaImY6lEs6KhpsUbgOtQ4zSGbnzNgxfm6UsL9ApVTpV65OaKRM1FioI5wcAUfAEaiEgD5iUfpQLi2rlLc8jZXXcn8UF3CgfkXiiBpUH5CgyFAxe1qty+p17MxYxIJqDqmfXMnEcRa7TrnTiSp7JJlIVZCAIlHaZpttojSOBRBchy3m008/HRf2oN5DKkUdzRDSnSTFzUu1GimDdtEHVLRIv5DgQNhjUha2knw7sE179NFHA9IgbE4POuiguI+dZ7oG6Rvn+WHDiK0d+3IVFSXNlAE2qOIxQ+A7g3QT7NBQQeRBkiqmKK7kRu2LylUBNOK3qNmV9dxH+ZGM9/CGG26IdXTyD/wuueSSKJlONpR873hmWLyDtLEZSqvXub5c3fvmm2/GBWkTJkwI8gUZsJ2VC6OShT/Uhf0l321NHiLOmI/kbTRTe5JkGZU7/RhIknuhiEkyHWmlrlrYYIvNO4AtNLhga42WIb/whzqbwYb3M/FNldq74YYbxj7lF15VylcvrafU5axMlJ+saIsB8wjzx0pI7HB4oSGMcXlAMQrWbDCuvCMfK/UYjDBo5TyGsTCM2OBAvMi83KwsZLCA6eQY2wTcHyTRcV4MHy+s8aeZSxyoGKzKf63cGGcya4DtpxwBRyAybIxvLEBplmBkuJaffFJG5iiptfkQJ2LRD2pt8qEmh+HiQw6jhk1oKkOSrcg8cXzVVVdFZoB9BAR81JnEJwaIdBgGVqc3oipNbUnbb3zjG5FpbXYBjCSzse3UT58SM0J/SePHNyb/gU/pbGk/TDKEfWr+XNoHm2STB7NOW9M5GMwdd9yxZFU9zCf2qykPWwQgtLVZkoQ2lrPKKqs0e2lD+WH4UjuxG4XWkEqYNLCBAW2GwJ8FWDxLlZhiGCcWFVE+Jg0w5+ULtLBR5bkkD4yS/EZWbMK2224b87CSeqCJxWC8S+n5aqW+Wthg/5vuQ35b3vdGsWHyl7cBLm8vNrbcI/qUnv/yPI0e9xSTmRrNC4fRb6UbhvSy/IVCsgnwzMqZCZJHDnUDMyOAAlBAw8AddxcQDzOzTlxdYHCLvQ+zdxjVRokZLrY2lX5p9ttoWeRzJrMZtDyvIzDjIcDiH8a6Vu0aG0UMqWczWp1q5SK5YxzHvUq7xHg+vRDueaZOnVqzuWCMxK6dfuHeiOch70WgZqU9cDJ9L6s1hfNIiGtNRvjOI0FmUU01Gj58eHSz1Q6+1couT8drAkxtu1QPm0bKbwQbNA1obqtR8mLRjmQ2ld2zNpl4/MerfZ6wWdFgZXIynE82iXVNsx+TCimGl8IWCPsFzS5ND2q0ZZK/L8M2hkgZkFYAxmPNykwSTdPsyiZOnAjTXVJ2rQMiDWAfUulH2CcnR8ARcAQ6iYCkD4btHxFEsJEbKJJblmhX2W75WqQQx3GZPLVblMntT9tlDFYBEm7E+1SrPjAmvF87/ZIWzuRnM34Da9XVS+ckAa0YKjK1kfP0SYvPUlK/rSSYMZqVBEf9zpEgc7gYOYooSe3gW7HwvkRNwiJvga0w/IVMKJriHyqVXQ+bSteUp9XCBv5GPj2jHSb2rtVIpjImCX3MWy1Po+n9g4I2euUA56OD5SS1eHzwiNubD4mUGMhkVI1hudThxotOPsIwnX322TEkk0TwsVgM229RKDOMbTEQljTTtt9++8hoysdcedUVjzGIlSq/4rlODKoVC/ZER8ARmGERYFxkkQEh/GTPN8Pi4B3PEOA5kOQqMgSOSREB+Xa1u+++O4afLKZ2dg8hFot+INlKxkmfJH8Gn9KrBJMpbYjJhMBkilC1mTLxMElnowCuaqYGTwxDpNlg3gHPJhVDnH0osoDJrsUkfo4vD7M9ZsTQvvvua6ymk9sMI5+MteOqQ7n8ifuygTGpaKJkEikmqxFlz2lw5sRmlZF6LEc2lHHLSjlmTeQjNijSAR6UbpB80cXVdMTOdXIEHAFHwBFwBBwBR2B6RqCn1OXMChA5a0WfKRpF3OdYvtwKGGtFmsn422S4Ht0WaDVVnMnhYgEGE5KBtynigsk202R3aajPESGjVk+Eeh3GVHaQMT9qdMW+Nfm4Sll86wg4Ao6AI+AIOAKOgCPQIgI9Jclspg/4iXv22WejP8lKdhn44EINjhhbKx3tqaeesqWXXrpQBec++clPRqkndp4Lyc4Je4hukksyu4m+1+0IOAKOgCPgCDgCnURgumUyOwlCr5QFk4nNqHzNmVyFGIbhTo6AI+AIOAKOgCPgCEyPCPSUunx6BLCTbWaxknzJxVXx9aIhdLJeL8sRcAQcAUfAEXAEHIFOI+CSzE4j6uU5Ao6AIzCACLBWEw8bLJTE3txp4BEgNCXrBLD3P+KIIwa+whm0BtwUYgaXCG8KCrQSXRSmtBl5i+kfoStZb6KoRxWhqJdH/sCj6yxFTax4facTXZLZaUS9PEfAEXAEBhABhYaM/n5xwVZOcvAdbc8VpcPkrDp+iBQYojxbzxzjgufb3/52dCfHYk72FTWn6fbJOb2NHDkyXodrOUUWKpRBzHLKTT+8khB7G1v8RklOsqMvRNpYjzrVp3r1dPL8dtttF72v8KzgZUUhmZsuvhP9VlQqUzCWwg83OoqE1HRbOnVBp94n/Nry/OE+SBG1DP+dzRLuGFl/gucdPOVUonp5WMty3nnnGf7B824gK5XVsTRcGDk5Ao6AI+AI9D4CxKrW4B+jk1Vq7VFHHRXk7i2G01XQikB43l4mwisSPnDatGnhU5/6VFhiiSVi1LZm2kx0NbmhC/IOEoiiI1v2GFY4lXHBBRcEucGLWBxwwAFB/pADYSWJf90MKcBHDE1Z75pO9KleHZ08ryAmMTzj+eefXwiv2Ux45dSWTvSbsKWEkCYCH79asbVTvQO57cT7ROQs3llCWvMMsX/IIYc03Wyi8BACW4FeCmG2ywtpJA/XEKqbd2IwyCWZHWPXvSBHwBFwBAYWASQhEL6Dy0nh82LgCYXdjSpHxZW2fOSxcePGGecUijCq2VG5scjwySefLCkKCen6669vCjsXvW7gmzhJ/RSOLpYxatSo6HQaqSrniZiGhAbJTyLF1Y5SMaIULbzwwkaQC7x6JHr77bdNH0Xbeeed7YUXXojXKk56dDeX8qQtkjV8I4v5SUmF7ZVXXhmltrRl/Pjx0Ywg328kSKgWkYr9/Oc/tzPOOMMuvPDC6Fc5Lw2+/PLLo4QHR96oaJE+KWxhoZ60QzQ57OepAyzzeZrpUyqv21si1iDBRLqFFJjnQpOT2Kz77rsv3kOem+Q/GleAHI8YMaLw7DTabyRpSOFwBq4JU8WuE+kHs4TZZpvNeHa6RfXep2OPPTbiABZiGmMzeX455pdcLyapMM/vzTffHBf37r333v26VQ8bnt9VV1214DO8XwFKaCQP1+F1J/8uViqrU2nOZHYKSS/HEXAEHIEBRiAxmZVC7qFWhMlbb731IrOFPdu6665baBFqNiKc8YHHiwUfRGw7jz766EIedoiGNtdcc9mYMWNiWDlJuAw7LggbUD5OikceQ/MSVYWAFqj/rr766oKa9eKLLzYYURYywtTtueeeBhMnaY6heoZgMGnjfvvtF+3MFpIbORjVcsLGjLJggAjQUU4E58D9HEzfiSeeaJKIxo9xeb50DEN7xRVXxLphjiEYn0033TQyNuBDffQbuzXqT0SgDzCAAVFs7Kh2x9dyYpga7VMqr9tbJg+TJk2KPqmJeoePap6fREwOYN7pVzK7IJIeQVC4V5IIx6yN9hvcmWzAnFdT+XIPqYMf97Rbka3qvU/41ubZ+Otf/1qwjebZUMz62PbkMhEbyrXWWisy5ewTEKZSVKBGsEn3pd0t4wfBahgPBpwGQ1zqddRGQINuUCz1oME2/u6///6aFxDYngD3Q4FQdaGa0YcqyIasapdQEygaU3j88cer5unECUl1gkKQBoUMC7StEj3//PPhrLPOCpqVNq3aq1SepzkCjSAgBjOgThRjFt56661GLumXRyF3g5iiQrokf0F2XoXjtIMK9aSTTgpi7IJs9ILcq6VTQRKsIOlXPEZFKglXYV/SmriPKnrJJZcML774YhCTEH8KpBFVhTfeeGPMI8lN0Ac67ksSFvRxjvuV/r761a/Ga1HztULgpo9pyU+xm4M+tLE4Se+CpE8lRcvOM+ZnbIKSqnPChAmFfGK2Yh5wgprpU6GQ6WAHDMTIh5122ikoFnhQ8JOSVjfabzGyQcxjkJQyaFJSUgYHYjyDJO7xWzBx4sSg8MxBE6V++XolgT7wXPG9gCQZj6YHeXMDSbqjOQjneR8wealE9bBJ10jLUFVd3mgeTS5ju7WILYhRTpcNyJaA7k41EGAQGj16dFCczyD1ScWcl156abS34KSkAgG7nzxJnRSvpwzN4uJAlD+v2XFQrNAgtU58ATWTy5/ut89HYaCZTEkeYpuxi1EUpKp979e4JhOkeokP+xe+8IX48VSkpn4lKBJUfHE///nPx4FOM75+eTqRcNhhh4WZZpopLLbYYkEzvaBZfJDUo6RoSW6CnPgHSWii7ZskKyXn0wEfHe432GkhQ0r2rSPQEgKSOMQPMx+0xMi1UhBMZn4ck0ovvlupLD44MF88/5K+hK233jowqV100UVTlhImU9KcQnskxQlaTBAnXrxH5Uwdx1KDBpi3VoixqFWCyeRd5AMPM8sYwjgqaVzQyvHYVkkwS4pn8q/IcHHiz4nEZMLs5wm7V8buoU48N9xDSeLa6uo777xTYO7rFcSzrmh90ca4Xt5unZcKO8jUIFbPluesVWoEm04wmQhQJK2P91MLrVptbkPXubpcb00twnXFOeecE9U+eTufdI1Qji4tCFOJSxHsntip7v5cAABAAElEQVTP04ILLhhDX1500UVRvYKtUp6Iy446SgbqtsACC+RPVdxHXUV4zYEiGeFHdRvidGxyUBsRHWkgCBWVBv0YkWny5MmGfdW9995bqEpG0zZ27Fg75ZRT4qpTzaSj6i2pbgoZO7CDio/7h/oDFY2kRfF+5YtGzYMtkmakRihTzbbtj3/8Yz5L3P/KV74S49CDHeU5OQLtIDDzzDMb4wc2WagTsd8aCEJF+NBDD0WVOfZjv/3tb02MaVNVEcIXNSqqQ97T/A/1YrPlUTl2kNgOPvDAA021JZ+ZcZZxDLU8bVtnnXXiu4vqEvUhpgN5YhzSR7/fmIzKMxHmC9i0ppDGKb2RLbZ6mApgBtDrxFgnTZL94Ac/iOYRrM5vhVDPSkJuv/zlL60RX9A8S1D5eM83UMKciJ80S600pWPXEA771ltvjd8png3MTFqhZrFppY50DbbNmLdgTsP9qEQdez4bYkVn4ExyBRK5fWb8lYgZsW5QkF1QYCUa+3rg+mVVvPUo7WSFGTOIasSsuJokUwxOYNbBT+4i+hWBFAJpHGUwSxejE2SgXpA0cAF5kAzKsD1KTVmViYpCL3GhPMqmH3feeWegTlZ/tiNFKBRcZydhfcMNNxRyggVSFaS9UFJPoT7vNIFNnmSLFKU5KU32SxEX2ZalpKgS5N5WomeeeSbmr/bsVLrG0xyBWgjoIxafKdTZzRIrr3mm5cInSvQ+/PDDaKbCu56k7ZiAcKxJb9DkKY4nSJLEREWpvj7uYbnllguywYwqeySZSLZ4d5BkaiFRQBqDpoXrxEwE3mvZ7AXU5csvv3w0M2mm7ZSHepV2cX2zhKRS9qgBrcnDDz8cUNfLrVEsE0ktxDuM9FUMQpC9adCiqWhWwDiKihOsZFsa24BGheslfIhSXVbzMy41S0mLo4VPzV46aPm5r2ABNlo0FevFjIJ7gVobCXszpIlSvJbreR7yhNYQaTLfHTGgsV68AGgykM8W9zX5ieVwvnzc7pd5EBIwKaFPyXSklSprYUN5L730UjQjwHQEyTnmZbyPeWokD/nBj/ez/Pp8WZ16Pl1dnke1wn5ifKoxCrwA2KrIYDpg14MbjsQQpeJ4EWVgHiTVCjAo3Fzs+ipRLSbz9ttvD5LoRfUVDG05oQqTxCOgcobpld+4+OAjXk+EChebGphR7Ek0M415UPMnwoUEqjIIRrUaE5Xyt7vFnocBjMGbPuTxw/Rg2WWXLVRBXmzScEsykMQLTD2asReqkVQ3YsVHKNHmm28e+FUiZzIroeJp7SCQxiPGgmZJPgjj88vHUP4e40cqqbX5WCdChYxam3yoybVAKL4L2NLlbRuxkWY8Id9VV10VYJbYl0YgfvgxuWFsJI0fJibyX9mwqjS1hy1MIuNmK2MRY1lqQ9ri5ogPdbLJhFHBJj71m3ww05jHQJLuxvpJhzGFsWQfkxrU6M0S4xh4gj/3tFcJ+9OEGd8CCJUwadxbGNBmiLGTbyF9zwsTKANTBiYRqT622P9W+lZipsT5chOHZtrSybx8l7mX+W9Ds+XXwoayyrGh/7jjylMjecjP5E8r9/OXlux38vl0JrME2v4HaVCvxmT2v6J/CjZIvFQYt3PzpBKPC3365wxRCllNkpny87LnmULSWSzEQ8cCokTMvqWOLjBBGBaTB7upZIzPlvLyD1yjhsqpnna3MjOIPu6QViAZYTaWiA8XM7c8YSeF9HWgCMnF8OHDA4sa8rNkJCDgB2aJ+OBUmmlz3pnMhJJvO4UA9oA8g63aNTbaDqSe+Pdrl5gw8vFEC9AuaUV3u0XUvR47TBb/MQbWIvrVjnYHyS73sR3JV6329fI5MOZXjWA2mdAn6XqlfIzP8oAQBuOZqFR/eZpcB4Vq9vnleWsd18Om1rXNnEPTgK11Nerk8+k2mXrTB5qw2xOzYri6wF8bftVw6yEmsGNV43oCwn9bIs38DV952HpCKQ/2MNgQpZ9Uz9E3HW2EpCIyfMVB5Bkoe8xYgf7EgMd2PvXUU0ZbcImSSKsLS3zvYbeCnRTpA0HYWGGngp82XEqwTZTcneR9AbKf0lM+3zoCA4UAfgOxKcSHIzZyA0WS9BXc07RTB3aQkoZ25H2VBqadpjR0raRz0YcgY2Atol+V3NDUuiZ/Djtu3DcdfPDB+eQZYh+M+VUjvjd8K6XZqphFQohon4/brMF4Jio2QomsF8BOGlth7HelcUNoVy17Q+n1sGmokBqZaB/PHHaYWuBXNWcnn8/qd7pq9X6iGQRYOMRCH+Le4twY0kzNtAItGt5igN4J4sMDYXgs1yFxnz8YMhgnXti0qIiFTIRWyxMDXiuEjzoMr6VCManpWymicA0MLW0kHF4inMZKEhIxgxllIRLEh6ucMFSW2i4yyck5bnmeWsfcK/yZSUphcknRzxGwZs/GAgzaILOGWJQkyLbDDjvUKrbquXbbW7VgPzFkEeA9ZZEBIfxYnOY0fSIgbyLRcXZ+rJ4+ezL4rUYAgn9WHOZ3k/hGsOgH4jvFpA+H9e1MPga6PzCZ8AP4gpWpS9XqOvp8VhOXenqGQDvqclSt2D6iKsdvVlpcg40JthPYSmJ4i+oFw3GM0nHlgw0U+9h5pmuwHSKNHzaK2E2yj+0gNp+UgQ0Rqnh83+F/DuNeMW7RborekAffdbjowcgYtS92mdhq4dcO9XozhFpDM6+o9im3r2mkHK7B3QN2qqiocPujp77EVoc6sCFFxY8KC8zArhK1Y6gMNuCKHSaqeK10D8cff3xU3+frwv4SrFhMAM7kr2aHU09d3k57823yfUfAEXAEHAFHoBcRcJvMOnelHSZT7kAiEwLjhEF5YkYwsieNH8bm+VVlKZ0tDFwyCk8MWP48+zA5yREsNiwYyKc8MJj438SOKxHMJ7aGKQ9bVqvT1mZJEtpYTrkT40bLoW/45KMPtEOunkpWwqdyMC5PhvY454WxLqd2DZVh6Fk0lceF/XJ7UOw1WQzBORYiHHfcceVNKRzXYjLbbW+hEt9xBBwBR8ARcAR6FIFhtEsfTKcqCIhRMEkXYxxSwrJND4Q6HrvPpEKv1GZ8emLbgnq6VbsW/JThVxL/lu2oymmLGORoryqGs1Jzo89K/NERqquSPQ82MWKWo7oCc4CBJHy24WcM7GrZbuH/ExMJLRqz8mdnMNs7kFh42Y6AI+AIOAKOQDUE3CazGjJl6TgDJl4tzsN7nbBd5FeLMOzn1w6xSEd+Nk1q33aKie2gnFoEIyxzgKpZOmmoXLWSvhMsqGIBVy3SSvQY77dansFsb7U2eLoj4Ag4Ao6AIzCQCLgksw66RH2RzWJcHS41d1zAU+eSGea0Qi7GFfK1JKaDBQYLnGSjGiOiDFadteqRH8IYOUW+0+LqQxYN5anX2ptvm+/3NgIon4hOgwagUwsHe7vHg9s6NFcsimg3qhreQ1gYItd1tt5665ncsw1uR4ZobTz/cthujz/+uBGFLy2oHaLdzbr12j/NHr5fRlpliucvLm72+YULXQebYbffZPbQPWbzzm+25npmc2eeYlImogsuvvji9rWvfS0lDexWjXJyBBwBR8ARqIbAS/IXeZMcbj90b9Aqu2q5Bi1dH4dor7333nv3q5NIKUTzkjuwuDBQ5iVNL+jrV+gAJpx33nlxYSKRhogAg3P3Z599tukaL7300hhRjQvxIUwQhzyxqFEePoKYkri4kgWEOJZngV85EeUHP4LtEgsyFQY3aDV0v/Y0UjbO7MEDf5wskMzHnG/k+mby4OORwBPghM3+Lbfc0szlMW+n7mWtinm+sZPHRp/nHLv4dmKF16qLc516n9q+l2eMh73s/9ts9UIXPpIP7rDDZv3zMG71EX441+hzpr/vvvum5AHd+sKfAYXXC3cEHIHpFYGP9MENe29bOmgvM1MIU5/qWpfwtiCxQwz7WKkRRALjA0zghy233DIGd6iUr1fSYGgIWztt2rQYLW2JJZZominGAwfhcTfbbLOAE3mi+YxReMg8EQUNLx9EOsLrRlogKR+H+WxxP3n06HeixQQY2nKmt15ROMLnPhOGmIhC7MstW73LWjpPiFKYNSLSpUWoeENpljpxL+vViUcVIusphn3MyiQBbB588MF6l7Z0vhPvU0fu5WnHZ+PQyp8N4aA9ir/rryj267LfFceqcQrKsvYSxWuKueLerrvuGiTNLEsdmENnMgcGVy/VEXAEpncE3n0nG6QX0TC521bFAXy9yi60BqO7yWOB1OX9qsPNGVFQiKOcGAfCxiY69thjoycJPFrAdOGpgYhVyetFyodUUerdGDKRyCqEckxRuAgLiTcKQtZSF1IRzss3YJQoIflJhHs0GA8kgzKpCXzY8p4uZIoUGWIksinCCAxgJUKyBpOFF4hyUtCEyGgQShemAKZDvkQL2YgxTlpeakndeLPIM5n7779/7Bv9kx/SwvVpB0zwpAGjirs4QkoeccQRJWFw8RpBXHMYSwV1iPtsE5NJ+FzK5yen2LFopKYp7frrr49p1E+bieNNu2DE24kwlPpQaUvUIeqCGcKNG0xcIi1QjPeQ9hHzHho1alRsL5Hi0rPT6L1EkobElLjnRHprhfJR2MCEtnPvO0313qdO38ua2CQmc/fvhnDHLQrxd1cIjE952mRENkYxMYaee6Y4Zj18f5bW9084Tt7ZwSBnMgcDZa/DEXAEpj8E3nsvhO021mD+btb21+QKTB+0+HvzP53rz8STQnirsZCJiRlLkpx8I/h4Ez8ZdfFuu+0W9/OMFdIemCM+ysTtRn0M8wejmSeuJ365IpUFYjKj7oV5g2B68OUr59PRjyyhYJEcch5JYQp3OWnSpFgP6l5U2cRKphzC76FGhmAcce2GWzAYM9rCh7acZL8cmSzaveKKK5afjmFdcfcGAwqD9KlPfaqE8UPCqSgyJSFiKYR45HmJHfHg6S/h9lJ/85UlKR/9heGFOQTvK6+8spANP7pIBWHCUUHj45d2JyaT8L9IXSlDi//idVOmTInxvAmpm0LW4geZmOsQzFwrMdvjxXX+mDxwD2AucYVHf/LPA5OCQw89NPYhqaXZEtoXP8Ep9nuj95K49uDBDyatXUJijes5JOGdpnrvU6fvZU1sEpMp3ARe9ptfWxjJRAv1pZ99ckop5p18UTFNe/iC5r7jH3qgSa1y6nUEiPvLgMYLNdRIxttRisHHkx9O6btN+OHEQXw14qOHI/lK/jqrXePpQwSB1RbOBu5pxfj1FXuGDeflFzb2Sx+NE/XRrcFs8sHHjhC/skiOWqFvfvObQSH7CpfCKCBpLCckoQo9FwMkIBnNM3cjRowoSACRVKb42+zDkEAELCDwAwwkjBM/bC5hLuR5IeZB6offXgj1vlx+xf1Kf9jhcS3S0GYJu1SkiY0STB2MdjnBANMGJJmJsI/deeed4yEMOOfBNBFjBGmJySQdCS9pyb8xDBqMaZ7hJfBEYpzAEDOJbpJC/UY7YGxMYZyvu+66kuY0ei//8pe/xMkIkxNwyBPjKuN/pV+l/jORATeeq25RJ+9lLWyiTbiembCFJh4HSzvBPr+jcrbHKe3Gq4pwLDtLlu+3E4pp2kMTwjOIJD4vGS7J1KEDZzLrAMlMbfTo0dEAu5rhdS2jc2bwzObTDwnBhAkTCuqnOtXH0wwy66yzTpx51Ms/GMbX9drQzPnkiJ0Hnh8z6bxKrZmy2s2L7RPSFtqheOQVi8NYmgGSPEgbqhHO87nnzPpxku80BBBAoqn7Hn/1urN0X76Uv9Ht2P0KUb7yVSD9S89dYuTy5xvdh8nMj2Py4Ro/1Ol6PjgESJh99tmjJA2pFpI9AhAkyjOZSN9Se7TSPUbmYvEI73F6p/NbpCdJ2pnKa3TbqrqYxT68z7SrEarHZCp0b6EYmK6tttoqHsOU01eEAnnCzjTPZHJu1VVXjaYG7K+xxhoDuniFOjpBPDf0b5dddmmrOJjJJAHNF8RzkX9W8vuod/OEWQG2x+22JV9mq/udvJfVsKFtJbbCF56VjUPz5lg47MUZZ5isQpoUxWPSfj85S+v7pyzMHsAYU4iBpP9RJU41ECCeNc6955tvvuguoTyrbo5pNmBSH0SXIjgnZz8R8bhxrSNVjkkdZPpQmFQx/Zxzp/yVtpQhO6pKp/qlScQf43cTE1fqiBgHXLZH/fL1SgL4acAwfUDiT4b7JluvrjQPP5yasUcH89UaoA+KSfJQ8VnIX6MPleljbTKmN0lr8qd8f3pFYMIxWcvH7Fu/B48WhneG+No/Stvje2ZTnzI7fJxVCkgglaBJXRtddJ144okmyVH9NrSQQ5G/oustqXBNtpkmG0kTY9pUSZIuGe7ecK+kj1nJT0xs0+VROX6KZT9pMhNoqi1k1kc0ji24vckTGNKeTlGKWS2NTKFIvh+KbFY4Tju4NiIG/dixY01Mq0lLlU41vZU9Yvw+SG3f9LWNXiDJZYzNLRvfOEbynWmFNFkyMeMm4YvJfrekCDFrdsYZZ1T85Z9BnoVNNtnEZPIRyyopJHegkM0m5j5io1DOuTOd3e3UvayFDS0uGRfe+HfWiZdyfVlpk+zglmuy7X25532JUr/OBBORFNYk4a+K4R/+8IeInQQmuUpa2B1IDnYolF0vrGQ9o3MwQMW1zTbbFOBIomoM7BMxi0P1gk3RUkstFXB5QFzzREjZkAIQyhF7Kux1MODP52nU+DqV2QtbPbJRTY6UopI9VjfaqIGuqiQztQfD/lqSTPKlRRpIi5ymcwTyRvQvd9j+68XnGwYHKRrvDOrsZomV12uuuWZcwIH6EckealDKS9J2xiSO5Usv2gwedthhUdJJiFr5xY3jDXade+21V1TZI8lEmoQEFEkm4xzSGMx7UGWiyWEMxRQGtebyyy8f8uNeI32gvCTF5fpmCdUzkkxsSa+66qq4WIUwutiVIomEkKyxcpkf9om82+yj7k42pOl95lokQVyDDSZjAeMwPxZTUA/aKmw4k5p/u+226ye9wwwBrJO5QbP9Ij/3EXtUysGEp9PEfSWsL5LpZEOZJLYs3knYNFpvsmulva2ouXmOeBa4d5g0YXOMtL3Swh8WkVEPYZzpx0BSJ+5lTWwOkEmG+hJGrhDCxqsWp60n/LTYrQfuLqanleVcM3pUMU/fHtjwfub5h/JMCrIS8UvmIOXnGz1WC5xqIVCPyUSNXcvonLLzTKZmVFGlhJo42R9iYMzLgN0QKyFZTchghR8wBlgIJpM81IWYOxmVYyyfVulJwhYZ0XqG9LHAHvhjoKZPyTiewQO1EundJGcyu4l+D9aNcfyI4dkAfvE5XW1gGo9YpNIsKahEfN9457ArhIFKam0+xIkw6WFCSz7U5AcddFC0A2VhD2MZ6fxOP/30aBLCPswbHyP2WcDAR52JcmKASJc2KLA6vZKqNNVdbYvLIT6KrS6AwfYTtSbt4MdiEcbQpILHvCWdy28Zp5PtJKvxOYeaFltySR8L16R2cV+GDx8e07mWVfyoy7nuuOOOK+kei4zAP63QLjnZ4AFCB8pm1ftAEMxywgMzAgj1PmncWxjQZoi+wvDzLLXCFGMrm9qT35ZjS5u4v+QpV7U3095G83biXtbE5hdjsvFH/VGnst/3R4ZQvgDx/DOK58m3kZ6L14vCqtQfJn9zzjlnOuy3xcaWe8TzyZjTDjmTWQe9NKi3I43KD8zpxcDuKQ22SC/LB4lkn4KkAUpMJi99IphUymOAhBo1vk7X98KWD9MFF1wQGW6Ya/qDFKWb5ExmN9HvwboP1GITBuwft2eL1omeYa/MO9KqXWOjbUDqiUubdonVq3w8y+0UWylXYX1buazkGiQ3MNdp7C052aEDJslTtYgpTf6rFctKexihdiiNmXkvAu2UNxjXorEaDK0VzD5utjrx3NTDpRP3kjpqYvPKS1lAiEfkI7QC41hoI5Ni8tTQuKBpwNa6GiExZpxpR8qeyvbY5UJyMEgLQEyzHdMgF+0kNbiY1EymGZhpADYNFiXNIB44tp1Si5WkazFJ4VirJk2q9VgeiZp12GKLLRbPcy02oL1OYJJIfvxMg6VhW7TjjjumZN86At1DYPIks2N+k9V/+3VmaymMGzSnQrVdcmu2P4j/kj7E91qLMEwM54C9J3KxY/zaJUn9TNLQdouJ10vj0XY54MdvIAnbuYWqjL1i3KMNpiIymXxQmqTGCHpK7e2aaNxdd91lcolkfC+mF5IEdMCbKtdMJhOQGNazE89NpQZ3+l5SR01sPjuPGb96pHfOvrR8xVw8a3K/Fe0wCXVajeReKz6T8uVaLUvD6QN/txtuytDOyGArX23xxwAkNbtxIzEW10rOGIv4Rz/6UQEEBiCpym2BBRYopLGDkThGzxAfmSeffNJkExSPm/nDqFcqLpP7kvjQNXPtQOZlgYMkAf2q6NX29mtoEwlDsU9NdL/3sz4/1WyT4qTOpjyXa/MTuf3B24WBYcGInHWb3AINXsVeU0cQkOo9Mj4UJrvCuJhG0qL4HWilAp4D2da2zKS2Uuf0cI28hNjdd99tMjkbsOZ2+l4OWENzBcNkwjfIhMDyAqtclriLkEfSWWMBcbvkTGa7CNa5nlXTUpvEVYxS08RVjmxh8LjJfDRkfG6sEGSVuqIqmNTgcSUlDKBU7ZHpYtYEIcGQAbrJrsVY4cf1Miqv04r+p1ndRxukru5/cpBS7rvvvjib1yImk/1HXFXIKnxWMJbTYLRXvvpMai6TTWtcvct9ol0L5aQSSJ1ZMSp1W5RKc69Y/d+KdGQw+lSOox83gcDnF0ZJ3sQFg5P185//vEndNTiVeS0dRUDu8Ixfp6iXPYd0qo+tloNXgYGkTt/LgWxrKhvPD6eeemo6rLpFE8pq/45Q0pv7tjIC7dpksgpcN6rkR7QHVognuyCM5Fkpnoztyc8KTs3EYqOITIHRO+mspMPwnH3CmmGr2Sx10qi32brz+TH8FnNWwCYZ9pcv/Bms9hJirtK9ov5ErG4tz7P99tun0yXbtBq1kj3vYPWppEF+4Ag4Ao6AI+AIDCICw6hLH02nKgggNZRLChOj0JRvyyrF1UwW42HPPvts9BOJFLMa4U9LritaVrGgimeWh5oGH6DdJB4/7JPwmYY9qULC9WtOL7W3X+NqJCAVlXF1xWdneu1Tje76KUfAEXAEHAFHoAQBV5eXwFH9QBJD0yo123TTTatnavMMRr/Y6dQj7DuT4996eSud76RRb6Xym0lD3V9vYUAvtbfRvil0nuWdMpdfNz32qbwPfuwIOAKOgCPgCNRCwCWZtdDROTk4N/mXizaVRLH49a9/XeeK3j/NgiKiEHXM5mKAuzy9tRc45IcwRk5hxT+RSuROowSl6bFPJR3wA0fAEXAEHIHuI/CrI832PMhMi2Z7kZzJ7MW74m1yBBwBR8ARcAQcAUegFgJ4wBi+iNk5cgX4/e4t4q3VRGcya6Hj5xwBR8AR6AACSLPRHiDZRsrNCnEnR8ARcATaQuCHW5uN17qK+VXK1P/2pDTzf9rqoF/sCDgCjoAjUBcBheQzRfmy888/3xTisG5+z+AIOAKOQE0EkGLCYEK4zL3ot3G31/6cyey1O+LtcQQcgSGHAL5gazk/HnId9g45Ao7AwCKAH993383quPYys+/tOLD1tVh6T64uD4r4MuwJhVN88VmzRZfKbA5a7KBf5gg4Ao6AI+AIOAKOgCMw+Aj0HpM59Ukb9r21ze56sYjGHt+zcMLZNkze6oc64ZMTicfPfvaztrpKqLEjjzzSiGJDjNKvf/3rbZXXzYuJmEQoPaLsEFKTMJwDQrffZPb++6VFz/UZs2VXLKTh13MY+R66x2xeGcKsqfivcyuOtZMj4Ag4Ao6AI+AIlCDQe0zmfXdlDObIFcw+rWDw511rdtJ5NmwFhTjavn+4wZLeDMABvjF33313e++994x4qMcff3y/Wi677DI77bTT7JprrrGf/OQn0VH6z3/+80I+YnETNvLKK6+05557LvqFhFFS9B7baKONCvnYwSl5J4g6p02bFusklFSzTCbhKwmheNJJJ8VQloSxrNT3TrS1VhnE91Z0pBha8xOf+ITtuuuuMZwmjuQ7Sv98xexrVRjxf//LbI7/s0CM4F0Uy/qMS0urfujeEkaUk77QoxQiP3IEHAFHwBGY8RDoPdHgrB8zO/tks6vvNzv3GrPzz8juytWTOnd3Xp7WX2JVpXTiVBMVZ7755rO115aEtYyQbBFznFifSNzGjRsX9/PZvvnNb9qYMWNs3XXXtcMPP9yQMl588cVGnO5yevXVV9uWYlLmzPKZRYxShacsr6LuMczp+PHjo+SQ+OIsVvjkJz9Z97qByHDTTTfFBRNEz+G3+eab21FHHaWQ0h0OVCWmvEAH7WGWfr8YExlMzg278qIigznucLO1l8gu2Xlk4dK04ws9EhK+dQQcAUfAEZhREeg9JnPjLc1G71q8H6v3SZf+JUlTp+g6GckuPIvZ78TAlqtHq9QxcuTIqKotP4108pFHHrE111wzMmYwmnlm9Nxzz43SRLY//vGPo/Ty8ssvtwUXXLCkqAMOOMBWWWWV6CAdpq6c1l9//XgOCaniZ8dwhWPHjjVCTCaCecVZ/AYbbBBV5Owj0Ux07LHHxjqo55BDDonJBx10UCGN0JkQ0kPo0EMPtZtvvtk+/vGP29577x3TBvsP5vyqq66KKnKiA9H2J5980v75z38OTFOGqdhvbWM2cnOzfcVI/uiIYj0TT8z2997WbL+xZmdpEgTd8w+zRx7I9vv+faFHCRx+4Ag4Ao6AIzADItB7TGb5Tfjzw1nKMlKX16LrLpeoSRxCI79tJaliyT+rsWA2//xIrZJrnkMNTjhIGMsTTzwxxt7OR9JBlY4UEClmIpg2mFPsCxNtvPHGtsMOO0Tm6emnn07JhS3n7r777ijlHDVqVFQhI9FLjCEZUSvvt99+hnocyethhx1Wch6V+btajYYLFeqD2CIhnGOOOWzppZeOaXfccYfBJI0YMcLY32WXXdoKYxkLbfEPbPEtCL2vCcEpp5wS24b6fkAIAenyK5utLqn1Z2Wuccm5xWoenpLtr7BKtmV1X6Ln+t+zdMq3joAj4Ag4Ao7AjIjA//Zyp+Mq80N3yJq4ze61m7rsSmZXSJ3ZCJ1yrNk195lt9jWzQ2Q7udQyjVxVMQ8xqhO99NJLabewfeKJJwzV6ayzzlpIY2fZZZctOV5ttdWM38SJE8UnI04rpRQzHckjElFoypQpkVndcMMN4/4ll1wSpak/+EFmu7rvvvvaMssU+4afPhYUwaQSLhPC1hQVPfaWMKbQ0UcfHdPZnzRpUmRA2e80YfP5j39IClhGMMlLLrlkCQ6ox7fddlt75pln7Oyzzy67ogOHn54rK2TFOc02kL3nLVea3THV7IDRZpv32X8+21fPfDkp9LKapDwsafLrAyRZ7UDXvAhHwBFwBBwBR6AbCPQ0kznsrJMyVeS3JFVaTkxkLfqcVvqiam+EFIPcjlLXWUw0wDT33HPbgw8+GNXWME/tEoxoosUXXzwuMuL4oYceisl5X3xf+tKXbIkl+uwG+y5C7Y+klZXnSF+xJ0UCutRSS/Xl0HqrT3+6sD///MJ1gAgm+He/+13F0lkglY+Ksueee9pFF11kV199dQnjXPHiVhKJ+5q38/yP1OFzCIdnVBgLe3j+lpFE9ZEPzR5/zGydUWYffJAxmNT3uQVaqdWvmUEQYDJ6zz33zCC99W46Ao7AoCCA8Cr/3RqUSpurpHeZTFTYO/4w683x5zTXq3q5VyoyavWytnt+5ZVXjnaNd955p62++uqF4j4Qg8JvttlmK6S1s/OZz8jVjogPGZJNiEVLlVTvMJio77HpRB3+2GNimlokzAWef/55W2ONNfqtlK9XJBLXddZZp1821OOfYyLQR3vssUdcvQ9Dmjc7SOfTFltS7DdhkpPNaTrX9PbNt4qXvPt2tr+SzBseuVRSTtli7nGA2X13FvMs8aXifoN7HW1vg3V6tu4gwAI6bLe/+93v2mKLLdadRnitjoAj4AgMNgJSQ/YevfHvEBaJ/HkIt9/c1faJScNKL8j2saV2vPbaa0H2g0H+L4MYoCD1edAioPDFL34x7LTTTrFM+X8Mimscf1KjB7lMivv6KAUt7Il5pCaO7eBaLeYJXKOV1kELgoLU3fEnRjPWM2HChCCpX/jqV78ar9luu+1i/nwHxPDGc3IFlE9uav+NN94IspmM5dxwww1NXdtoZq3Gj+WD1eTJk+NPEtrw1FNP9StCzHXMu/POO/c7VzfhluuZD4aw4pwhfG+DbJ/jr8xXvPSBu4vpay9R3B89qpgnt5fuWbVnp6325urxXUfAEXAEHAFHoBcR0Fe0B2m7jYsf8DUXCyH9Jowb9Ma2y2TSYC20CVJRRwYIhlXuhYLsC4PsEWN/5FuzcI7z6SfbzCAXPjGP1O4xfZZZZgmPP/540KrrQr599tkn5rn99tvD8OHDYzrXygdnkLo8Hh933HExT/rTApogiWFkelNas1v5BY1la8V3s5c2nB+mO+GRtrRb6vSSMiQVDlq8FPvEPWuaHnmg+MzBXPJbSr/77yot6vwzSvNtpL6//mppnr6jWkxm2+2tWKMnOgKOgCPgCDgCvYNA7zGZZ51Y+hFPH3y2B7QgoWoT604wmakJSByRTiKFHChCyjl16tQgV0o1q1hppZUio1szU52T+++/f2QAkTB2m2QmENvSjmQ2vP1WCI89HMJ9U0L42wtRYlyxX++9FwJM6cvTKp5OibWYzI60N1XkW0fAEXAEHIGhh8Bbb4aw6VdDOPgHIVxzSbZ/09W1+3nzdVm+yReFcODuIWy2eojfttpXDdjZ3rPJxL0Qvx6ja6+91oj+k1Z5t9K8Oeec0/gNJLEyfaGFFqpYxd///vdogylVs917773RPkxPVskq7ooXVkm866674iKcZANaJdugJP/xj3+M/Tj44INbr+9jHy/xNNB/jX9f0bNoRfmXlq9ZT72FHh1pb80W+ElHwBFwBByB6RqBD+S55DLZ/v/9KbN5tE6B/U1fqN2lF5/N8q05UusHLjG7+2X5/3vPjO9bF6j95c5daPRgVjnPPPPYNttsYzBot91222BW3fG6iJ7DgpizzjrLZBNqp59+enRf1GpFLMS54oorWmZSW6230nU77rhjdOOE66NeoHoLPXqtvb2AmbfBEXAEHAFHIIfAzH2uDz/2f2ZEQ4RmrbNYOJ2fRdd+os9TTConK2FQ/4chIx3UGr0yR8ARcAQcAUfAEXAEHIH6CMwtndoWW5ltua1CGa9vdv9dtd0v4nKPgCI3yNfz5IsU2VDeef7ZPTav99Tl9SH3HI7AoCMQzQqIY77/kYNet1foCDgCjoAjMIMiMHac2SKLZiZaP9zabPgXzE461uxTMr0jamGiC88SM/kPs622MyPf0iuYwv+ZLb50ytGVrUsyuwK7VzrdIXCNbFtGbWH26IN6eZeb7prvDXYEHAFHwBEYIgh8dSGF/HvO7MF7skAhf5Wv6yXETC4vu8sHcj6ee6C7bpPZAzfBm9DbCESLksO2zxp5zIG93VhvnSPgCDgCjsDQRmDMCVn/fnFYtj1J4bGhQ0/Ntj3075LMHroZ3pQeReBaRfkZuXmxcS7NLGLhe46AI+AIOAKDj8Aqc2dht2+9wWyNb5gpAnR47gMbpoh5vUQ9Kcm85ZZbYjxtYmpffPHFvYSXt2VGRGCDzeQG4ras59P+5uryGfEZ8D47Ao6AI9BLCBzxm6w1MJjQUeN7jsGkWT3JZC688MIxRvXdd99t119/Pe10cgQcAUfAEXAEHAFHwBEQAmH9TTMbzITGd3OLgFJaD2x7ksnEmfgOO+xgisXdAxB5ExwBR8ARcAQcAUfAEegdBAi8YqN2yBr066Pq+8/sUtN7ksnsEhZerSPgCDgCjoAj4Ag4Ar2PwDtvmx09Pmvn9r0XJTEB6ExmQsK3joAj4Ag4Ao6AI+AITA8InNu3knzMvmZz9EX26cF2O5PZgzfFm+QIOAKOgCPgCDgCjkBFBN5/3+ygfbJTu+1XMUuvJDqT2St3wtvhCDgCjoAj4Ag4Ao5APQQuO8/sVWXae1uzeT5XL3dXzzuT2VX4vXJHwBFwBBwBR8ARcASaQABXetttrPCRBzdxUXeyeuzy7uDutU5vCKy8unxGhOmt1d5eR8ARcAQcgaGGwF6HTDc9cknmdHOrvKGOgCPgCDgCjoAj4AhMPwj0pCRz6tSpdtNNN9krr7wy/SDpLXUEHAFHwBFwBBwBR8ARKCDQk5LM5557zm688UYbMWKErbfeeoXG+o4j4Ag4Ao6AI+AIOAKOwPSBwLAgmj6a6q10BLqEwMvTzB572GwuRaBaalmzmWfuUkO8WkfAEXAEHAFHYPpBoCclmdMPfN7SoYxA+Ogjs322M5t3PrN1NjBbbiWzFT9m9uzTQ7nb3jdHwBFwBBwBR6AjCLgksyMweiFDEoH33jWbTUzlIurdeluZnXxB1s31lje77oEh2WXvlCPgCDgCjoAj0CkEnMnsFJJeztBD4L//Ndt1SzGXF5nNOqvZ6/J+O6dU5tCb/zH7xOzZvv87Ao6AI+AIOAKOQD8EnMnsB4knOAI1EFhdYs07pprhDBc1upMj4Ag4Ao6AI+AIVETAmcyKsHiiI1ABgffek/p8tuyEr5erAJAnOQKOgCPgCDgCRQR84U8RC99zBGojMOGY7PyYfWvn87OOgCPgCDgCjoAjYC7J9IfAEWgEgeelIh/OCiARLo3mnjfb939HwBFwBBwBR8ARqIiASzIrwuKJjkAOARYAfWetLOHic5zBzEHju46AI+AIOAKOQDUEnMmshoynOwIJgTF7mU15zuzHu5ht/v2U6ltHwBFwBBwBR8ARqIGAq8trgOOnHAGbPMlsk29lQIwYbjaLXBlBc0pdfsmt2b7/OwKOgCPgCDgCjkA/BJzJ7AeJJzgCfQjk7TArgeIrzCuh4mmOgCPgCDgCjkBEwJlMfxAcAUfAEXAEHAFHwBFwBDqOgNtkdhxSL9ARcAQcAUfAEXAEHAFHwJlMfwYcAUfAEXAEHAFHwBFwBDqOgDOZHYfUC3QEHAFHwBFwBBwBR8ARcCbTnwFHwBFwBBwBR8ARcAQcgY4j4ExmxyH1Ah0BR8ARcAQcAUfAEXAEnMn0Z8ARcAQcAUfAEXAEHAFHoOMIOJPZcUi9QEfAEXAEHAFHwBFwBBwBZzL9GXAEHAFHwBFwBBwBR8AR6DgCzmR2HFIv0BFwBBwBR8ARcAQcAUfAmUx/BhwBR8ARcAQcAUfAEXAEOo6AM5kdh9QLdAQcAUfAEXAEHAFHwBFwJtOfAUfAEXAEHAFHwBFwBByBjiPgTGbHIfUCHQFHwBFwBBwBR8ARcAScyfRnwBFwBBwBR8ARcAQcAUeg4wg4k9lxSL1AR8ARcAQcAUfAEXAEHIH/dQiaQOCN180eut/s9dfMVl/bbM7PNHFx41lDCDbsnN+YvfKS2cdnN9t9/8Yv7lTO228yu+d2M7XFZtJcZPRuZp+Zu1Olt17OOkua3fy42Rv/NvvkHK2XoyvDhx9mOP/zlawc+rftHm2V6Rc7Ao6AI9ANBMJHH9mwB+82e+FZsyWW0e//daMZXqcjUILAMDE04iKc7KLfmj3+pwyIBYabbf+DUlDG/8zshweXpm32NbMzLjP71JzF9CsnmT14T3Y8l5jQPX5cPJff+88bZif/wuzdd7LUdTc0W3WNbP+Zv5p9YYlC7jh4DBtWOB6UnSVVn3i5At12oxjrdQqHXdtJODz1lxKMWmrPYw+bLb1c6aWD8Tq8957Z2B+ZffazZvuMKa2fo8P3Mpt5VrPDjjX7hc7/Q5ONn5/SP1+9lEceMLvqIrOPgtmWW5tdco7Zhx+Z7XeE2cc+Hq+Oz9aGX9ZE5hCzDbeoXuLTehh+d2Y26fjfmcy22d1s/s9Xz+9nHAFHoHMIPCLhxhUXZu/fzJIN7aLxIy/kuPcOs61WN3smV6X4TBt/g9nXvl5IjBPrXx9p9vbbWdpqa5mtPbJwvmSnXp1kZrK/1ZoaU/R9XE2Cl2+pvB33qT2WlFSSO2hkvEIw0Gj7c0X7bhcRgMl0EgILRpkdLEYIK8xRCsk7b2fpnPvKAiGssWjx+PC9SvNu/83iOfK//Vbp+XT08P2l+Y49LJ3Rd/+jEMbsXTgfjwtnB2nnlutDOObQQhvCbTcOUsV1qjlw9xB2/24I775bJ2P90x998EEIJx0bwj7bFftZ/7K2csR7+Z11s/ouObd/WY//KTv3/ZEhvPhctr/Bcv3zNZKy23ey60euEMJhP8z29Wz3e55GrZSdu+yC6qVyLvvEZdsLzqye1884Ao5AZxEYu1/p+/fIA6Xlf2vt4vnN1yjuz6VvUJ7+/a/iOd5n8lajenVy3S/GZOVd9rsQTj8h2z9zfLUSa6c3Ml410/7atfnZQUJAU6JBICQ3551m9u9Xzf53FrNd9zO761az6y43e+s/Zt/fyWyl1bKGvKMZ1qTfmj32kBnXfWFxs02/a4Z0EWnafVPMhulzN8ecFiRtHIZk67//Vfmnmv1L5Qcdr6yymFU9p2ndrderrj+YzTKb2fAvSMoodcJPTzJbcKHKHb/7Nl2vGWGOwiyz2rD5lbD51haOm5jV+eX/M3tA0sj77szl1C6SzV++ZvbpuUrTax3xauYo9mmz0ZJ2HRdTh111sdn1V5gtKlXxt7Y1+xyNyRFq9YslpXryz8J3ZrNlJJki36yShiWiX/f90QyJFOrhL6qs0cJ94cVSjmz7wrNmU24xe01YrrWu2SJHl86OU27uw03Xmj37hNm8C2o2vEGppHOq0q+6xOwD3ZsvLmW27kYWpcXci88p/256BppRv//5EbMbrjSbWyrtz85jNu1Fs4V0PxO99HdJ6s7VsyDJ8FfW1H2+1+wR/daRhHijb5ViwTWa+Q97+H6z2Wc3W28Ts1+flUoqbj/4wOzy880eVjmv/lP9WEK4bpM9i+RC4nz1pVkfP6Zyvru9+ni22X/+lT3nW+mYtuZo2KXnmZ3/e92jmSzoudbTWkrHHJwdgxdSTGi9nISRZ+HJx7L0T37KwnZ6By5Q21/5W5a25LJm638z2/+N2g6N0XO001rZ/k/Pzp7f7Cj7P+ZU9WN5vWdbyRTkG6WS+ZTvm9/Wu6Xfhisrr/BwcgSGEgI3XyNTqPuyb8tIvW+zfSwbT/78cDauIblPRN4pt5r9/QV9R4brW/P1LA/jxbmn6B3SWMF3aMURRSnis09rPJxk9r6+aTPNLM3CNhbm+ZwNu/8ufaM0HvxF49vc82X18k08VuVUogN3NfvZyf3PLCmx5TI3m13zXKZhOE7j9j6HadxS1tf1l75Hc+i7xfcGc6ytd+tfTqWUanViPrbf2OwKvt8L9mk21tK3AELKedHEbDwEj+VXMVtK7WScfu9tYT2TxmZhnbR2jYxXrbQ/Nsb/uobAoDCz996ZzXCyxzuEXbYsPUaKCP35kRCYeaV8+e2FE0NYpOzcc89k191/V+k1I4aH8NRfStPyZU2+KLsu/58kmXfflk+tuB8lQV/sa8s+O/TP8/qrxbobkWT2LyGEcklnvv3M5hJdf0WxrnwesHrlpSzXXX+onIf8f3shlRTCOadUz5eXZO67Y+V8P9y6WNahexbzLKR6Vlu4eEy9zJKboR02K71+0tmlV4//Wen5PBZbrFXM+9//hjB6VPW8KefL00JYZqbK+a65JMuVl4BS34k/L81/RtmMnmfh/5SPvBNPSjUVt489XLwevFMfeBZEH334YTEtnbvp2tK0T6hsKJW1yYgQpv0ty8M9qEZJmomkuBalfC7JrIWSn5veEMh/d5DupfcrbXkH33svBMaSlJbfbr9JCEgX82lfma+IAhqv/LkTjwmBb1o+Lb9fvDLbS1LFA3ctP1P5+KgDCmX301xwxdknZ+fpazWqV+fPDsnK4HuLRoj2p285ZTJO5vu0lM5PGFeaxncCana8aqT9Wcn+32UE/mdQuNtlVjSbMK5Y1Sma0Y1cwexAzQ4lHLLt987ObaFZDjMv6KA9zH51hGZl8cjs29ua/eSMvgNtDtjZ7GVJr3bcXDMidWO372TnZtHml7/VTO20Yt5pkvL8VdKfw36Ypc37ueK5FvaGjRtj9lTfhRtt2UIJTV6yxqJmp0kaleimq7M9JJJI4SBw+OOtZkjKPqFjbHPACJp/uNn31hMumnUiEfzLo1k6/3fclO0/8WdJNncpplNeJZokSd2vTs/OnHZ8JllOErcTdG6y7i20re7tbpKMQc/qd8dUs313VPrGZovpGFugZmivQ4uSvUrXbT5az5Ses0T7bCc7w+9mRxffIgnC+9n+hGP1bPThN0K4bFGlHXt+T5LQD7O2XnNpJkVPeUcKG2bpexwgaYHqSTSTZuaJxh2uWXrZs3HbDZLm92XYYuuUs7hFKr7e8mY7a3aPHSb731nXwpe0FQ37Hz3nl19YzP/9kRbW+EYRZ85cfmV2fpqkLNDhvzR78dm4az85NdtW+v++JCTQMROyrf87AjMSAhdpTFhhjqzHl9xqNpd2j/iRNDT6QPFbeBFpO46SxkhjCfSttc1O/bXecUnnoDOv0Bh3o9mR+2fH/I/TWMy4vfe22djKuAcxjjBe/erH2TG2/Wjwbr7ObLPVZWuZJbf8jy0l9tzQD7fur7nIzrT/j0aFMWq3gzMtGvsHjSuWi4QXKWiicdLCbP794jcd7LbfMzvb7HiVyvRt7yMwqExumtVoNtZvdvXkn4sznJ8eXGzWH28tpjN72Wz17BhJUNrfbuOiFGnnLbJrb7iyeB31LqYf9pJIYJBmlVOjkszjf1Is96cHlpeSHXdakvnog1m52ObRF+w1oasvLrZlW2Gw67ey30LKk7Am37vvhHDRb0PYc3QIzCaXzp1H+gblJYHcC+ieO4rlJEnm9zYopqX62Kb6kHImykvZ/vD7lNredpm+tpdLMimV54Z2IMWFXv1HsV3JhgnpAnmQUiY6aI9iPtKQOKb+UF/qZ16KcftN6WrVq+cg5Wd75aTiufzeL8dm+bgH7dABO2flfP1LWSlIK6n3uKNLSo2Sz76U/H5JpnSQJAmU8+LzKbX/1iWZ/THxlKGBAOMjzz/vfNIC5Xu27CzZ+SV0vo+iXTfaA67j3cjbDE59KkvnHNqzEcOz42svy65ONoic58f5/fVuo/krp3pSxZT/oXuLda782RDeejOdKd02IglstM7SkkuP+NYmfE47PoR/vFxs39OPl+TNj1H5/ZJM6aCR9qe8vu0qAhKNdIE2+nb/2RWSoUR51wuLLpVSzf72ouxcNNODHrpXUrvbs/2zJmc2nBwtv2pMC+uMki1an4SUlCf0O/NyrYTbXnaTJ8Q8Tf/9/DCzvQ7JLpOkNRz406aLaOWC8P+WzS773ELZltcU+sfL2Zb/24TB7y/KftzVL+q3fZ+U87C9MlvC8efIflJ4riRpYjklaZfSwyKLZ2eX1sy0nF7P1ZnqY7uIMi6j35eWK78iO0biVo9kg6u3oV6u+udXWTfLk199iS0UdNffs+2IzbMt/8utVNxnD6lCoke0k/r5wC1ZP5GAfmaelEPPVE6aSSr2rpUo2VIuOqLS2cbTdpWEBbrx0cy+6Yop2fF2u2fbvv8o+aywX5IpHcw9b9qT3e5fi/u+5wjMaAisv3M/W+oIwYv/zZD48gYFRIahvVhjhez4aX2TsBlk7IVO+VW25Z/1B1Oey47R7EEH/iTTQGVH2flxp2p8/qq0D31507lGtvfeWRzLVv6s2ZUavD7+iUauHLg8M8+sNRDqJzRO36Ezxmf7o/V9Tt+ZLCXT1FTY70vyzXSKQHeYzEpgLb50MfV0qfj+9Vqm4vzNL4rpy+nl5AcdNzFuCirZk8/Pjln0Ihp27aVm155nxoIX1MPnnCIGK8tip0qV2SyN3U+DwtHZVScdK1XKr2zY1htmqpBmy+pU/qWWLZaEKcHTYtD43TVNaly1cY31svMMXNAeUgHfJBXHqZdoQUwOb87lGKNhky8kxeyCM7Nt/n+5HIN0+wuxvvDUR1LTPmC2yQ+lcvpKPnfj+788Qkbvs9mwT+qRRKU/UJT6/RsxxiwWgqG8sKyfMKez9DXg2+vI1OL9DNc/v2N2orD7mgbIhb+QZcCgf/k+phyzBmhJYYuLpXKaT8wp9NrL2bbVfxZrSY0eaYvR2ZYJ1RyfbrXEbNFcunq++dOebx0BRyAhsJbU3NB51xZNjli4c43GPmi1zbPtmn3bZHqCCnzC77Jz/M+3QLb/q7HZ+POyxmt8Eh97WDEPCzmboSl/yBa8cs3GErRcp/HnejG2q+qjl/wAc64btHWfyvwJVZ6+ofuO6UZLvM5uIDAoctRqBs4LSXD1/vvFJiTxfFIf5LeoOXFbw0KVfHr5cVoUky+LBRq/PiqE+fvUEqiWy6mWurzcgDlfPwuAyqlddXn+eurCZdJvflXa70vPy0wOkskA+egfZgGpfat/IWtZPg+q1c/m8pAXd0V5NUa6vnyLGvWFZ4vlc36VeUqPMeyGtt6oND2VlQy9s1zF/2G5NmFQnqdy9zmpLLZS/UfTC1TU+XTuN+rkfNo/XwnhCqmt8mnl+2mR0LmnlebDdVU+L1hggpBPY9FY/viEn+Z7UVJ3XXVQ6ZX9j+68pbQuFve0Q7+fXCivZttcXd4Oyn5tLyLA2DdLbvzJv8O8Z4num1J4R+J7LgcnJe97MsnJL25hweJZJxbzMRYnSt8cysHUJ79YkrElT+l7Vmnhz5v/KZafb3va/9ND+ZKy/UbUzbXq7F9i7ZRk4kObcKnWLjXS/nbr8Os7gsAgSTL1KlYjXo9EB//M7Pg+0XpKY8uinskPZm5omAVKkBNph82yWSGG0xBqTNQV0CdyagLc0+DO4W9KRzJVyQVEvKjK3/sfVjmh5EVy0sTqudo7g1seXAHlSe4yoqujiZOLC3zoH7NFCOPyU6/I9lHrJ6N2VKv/UHJalEOO/76buRPCBCEv4ATCZciQI1xJPap7kSSCd/dJ5VARYeS9zW5ZZlxUNEPH9M3ih+mi8gUzyQF7tfLyz1DKo+gXFWnjLYsqm5QBSUOiD/tw/t6OcjV0hkTifSfuejHbWV0STCS88y+o4bJKHYWyPkx72fbLkjD00bApf0i7rW1HrJmp7rlaxv0273ytlZOuuvTcbE/G+Hk1ezrtW0dgSCNQNrwW+pr7PNmXpaXBjV4aE1/ry7XKPJkksm+Bnn3tG4XLbXNpj1gomGjtUWlPboVmyvYp52CN0UePzxbFHLqnBRbINErvV2t8XwFzSXXebSJiXKL91FenGQeBjrCqHS4kSqZwRI0bokqLdN54PQQ5rY5G19SNhBP3RyxwScTs7q+PZWksZNH5Qv6UJ79Ns8oGXBjlL6u4n5dEturCqGLBNRKRCD/zRKlLovLsSN/067foqjwfUjEZrdfNB8Z/+VMIb/y7vITWjlVOTSlaa6VWvCo+CzxfSDfrEe6MeIbyUvd611Q7n6QDLEJrh5KjdiQD9KMdyi+QqiT1yJftksw8Gr4/oyLAGP+XR7OFPpUwQOPDeJsIaekzfy0dU9HCscCI94+Fd89PTbn7b9O4UUmS2T93/ZRGJIGdrPPUX2fS1hXnrN+2RnI00v5GyvE8A46AvlBOEYHEZKIuZRVwq8Tq9fxq60aYzL23DeHm61qt0a+bnhAgelTy99rn/7Kp5l98TvH6pA5bd9n2mPMUXYqPSjXiI4jZSVIrup/Makh5uiPQeQQSw8fK9/12qrz6vZFamSgf/INi1LrN16h+VSfqZAX9vGpzGqvYlnnBqN6ACmeaaX+Fyz1p8BEYJHX5D7B0/AAAA2VJREFUdCAZXm3dbLHH5FsU0eTC1ht8p64/U4tKZlERiupiM7NTgYhrzvoKTk+YaPanBypk8qQhhwCRRK7+k1avqmenH9d89555on8Ept8/bMPqqcyq1YT/UCJLYXry46Or5VL0rKfMTjorO49FCr5XnRwBR2BwECDyHd+Kx/U767RSzyLNtICFjr87UYtDn8zK+3/LVb+6E3Xeeb4WWJZV8SeZW7VKzbS/1Tr8uo4iMAy+tqMlemGOgCNQHwFC0L3zpplCQzZDvK7DCC6Qf22ZsMC8tkqvyki3F+y2Wm2/X+cIOAK9iQBMISGKEymgRJD9eFxPkNJ8O6QRcCZzSN9e75wj4Ag4Ao6AI+AIOALdQcDV5d3B3Wt1BBwBR8ARcAQcAUdgSCPgTOaQvr3eOUfAEXAEHAFHwBFwBLqDgDOZ3cHda3UEHAFHwBFwBBwBR2BII+BM5pC+vd45R8ARcAQcAUfAEXAEuoOAM5ndwd1rdQQcAUfAEXAEHAFHYEgj4EzmkL693jlHwBFwBBwBR8ARcAS6g4Azmd3B3Wt1BBwBR8ARcAQcAUdgSCPgTOaQvr3eOUfAEXAEHAFHwBFwBLqDgDOZ3cHda3UEHAFHwBFwBBwBR2BII+BM5pC+vd45R8ARcAQcAUfAEXAEuoOAM5ndwd1rdQQcAUfAEXAEHAFHYEgj4EzmkL693jlHwBFwBBwBR8ARcAS6g4Azmd3B3Wt1BBwBR8ARcAQcAUdgSCPgTOaQvr3eOUfAEXAEHAFHwBFwBLqDgDOZ3cHda3UEHAFHwBFwBBwBR2BII+BM5pC+vd45R8ARcAQcAUfAEXAEuoOAM5ndwd1rdQQcAUfAEXAEHAFHYEgj4EzmkL693jlHwBFwBBwBR8ARcAS6g4Azmd3B3Wt1BBwBR8ARcAQcAUdgSCPgTOaQvr3eOUfAEXAEHAFHwBFwBLqDgDOZ3cHda3UEHAFHwBFwBBwBR2BII+BM5pC+vd45R8ARcAQcAUfAEXAEuoOAM5ndwd1rdQQcAUfAEXAEHAFHYEgj4EzmkL693jlHwBFwBBwBR8ARcAS6g4Azmd3B3Wt1BBwBR8ARcAQcAUdgSCPgTOaQvr3eOUfAEXAEHAFHwBFwBLqDgDOZ3cHda3UEHAFHwBFwBBwBR2BII/D/ARqmyJUlK7+KAAAAAElFTkSuQmCC"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![table_rep.png](attachment:table_rep.png)\n",
+    "What is it?\n",
+    " - Start with an empty list\n",
+    " - Each row of data is one dictionary\n",
+    "  - keys are the column names\n",
+    "  - values are the data in each cell\n",
+    " - Makes a list of dictionaries\n",
+    "\n",
+    "Why put data in table form?\n",
+    " - It seems redundant, but is used often in computer apps for storing info\n",
+    " - Its a little easier to access subsets of the data without worrying about the header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Let's put the student survey data into a list of dictionaries\n",
+    "students_info = [] # list of dictionaries\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_row = cs220_data[i]\n",
+    "    current_student = {}\n",
+    "    for col_name in cs220_header:\n",
+    "        current_student[col_name] = cell(i, col_name)\n",
+    "    students_info.append(current_student)\n",
+    "\n",
+    "print(list(students_info[278].keys())) # print all the keys for a particular student\n",
+    "print()\n",
+    "print(len(students_info)) # print how many students completed the survey\n",
+    "print()\n",
+    "print(students_info[3]) # print the fourth student to complete the survey\n",
+    "print()\n",
+    "print(students_info[3]['Age']) # print the student's age"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Nesting: Dictionary of Dictionaries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nested_english_dict = {\n",
+    "    \"shenanigans\": {\n",
+    "        \"definition\": \"silly or high-spirited behavior; mischief.\",\n",
+    "        \"usage\": \"widespread financial shenanigans had ruined the fortunes of many\",\n",
+    "        \"fun_to_say\": 7 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"bamboozle\": {\n",
+    "        \"definition\": \"fool or cheat (someone).\",\n",
+    "        \"usage\": \"Tom Sawyer bamboozled the neighborhood boys into painting for him\",\n",
+    "        \"fun_to_say\": 8 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"gubbins\": {\n",
+    "        \"definition\": \"(objects) of little to no value.\",\n",
+    "        \"usage\": \"I cleared all the gubbins off my desk before I started working\",\n",
+    "        \"fun_to_say\": 10 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"malarkey\": {\n",
+    "        \"definition\": \"meaningless talk; nonsense.\",\n",
+    "        \"usage\": \"don't give me that malarkey\",\n",
+    "        \"fun_to_say\": 5 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"gnarly\": {\n",
+    "        \"definition\": \"gnarled.\",\n",
+    "        \"usage\": \"twisted trees and gnarly roots\",\n",
+    "        \"fun_to_say\": 2 # on a scale of 1-10\n",
+    "    }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get the definition, usage, and score of 'malarkey'\n",
+    "nested_english_dict['malarkey']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get the definition of 'shenanigans'\n",
+    "nested_english_dict['shenanigans']['definition']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get the usage of 'gubbins'\n",
+    "nested_english_dict['gubbins']['usage']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in each of the cells below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Print out each word and its corresponding definition\n",
+    "# TODO: finish this code\n",
+    "for word in nested_english_dict:\n",
+    "    pass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# average of fun_to_say for all words in dictionary\n",
+    "total = 0\n",
+    "for word in nested_english_dict:\n",
+    "   pass\n",
+    "    \n",
+    "print(total/len(nested_english_dict)) # be safer, check if count is 0 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Let the user enter a word.\n",
+    "# If it has a fun_to_say of more than 6, print :)\n",
+    "#                           more than 3, print :|\n",
+    "#                           otherwise    print :(\n",
+    "choosen_word = input(\"Enter a word to lookup: \")\n",
+    "\n",
+    "???\n",
+    "    \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## More Examples Of Dictionary Usage\n",
+    "\n",
+    "If you want to see more Examples of ways to use dictionaries check out [w3schools](https://www.w3schools.com/python/python_dictionaries_nested.asp).  Below is one final example.  Look to see how the `scores` dictionary is used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#KEY: player name VALUE: player score\n",
+    "scores = { \"bob\" : 0,\n",
+    "           \"alice\": 0 }\n",
+    "\n",
+    "def do_set(cmd):\n",
+    "    # why do we need this?\n",
+    "    global scores   \n",
+    "    name = cmd[1]\n",
+    "    score = int(cmd[2])\n",
+    "    scores[name] = score\n",
+    "    \n",
+    "def do_get(cmd):\n",
+    "    name = cmd[1]\n",
+    "    if name in scores:\n",
+    "        print(scores[name])\n",
+    "    else:\n",
+    "        print(\"unknown name\")\n",
+    "    \n",
+    "def do_print():\n",
+    "    for person in scores:\n",
+    "        print(person, ':', scores[person])\n",
+    "        \n",
+    "def do_high():\n",
+    "    # PASS 1: find the best score\n",
+    "    best_player = None\n",
+    "    for player in scores:\n",
+    "        if best_player == None or scores[player] > scores[best_player]:\n",
+    "            best_player = player\n",
+    "\n",
+    "    # PASS 2: find all players with the best score\n",
+    "    winners = []\n",
+    "    for player in scores:\n",
+    "        if scores[player] == scores[best_player]:\n",
+    "            winners.append(player)\n",
+    "\n",
+    "    if len(winners) == 1:\n",
+    "        print (\"Only winner is:\", winners[0])\n",
+    "    else:\n",
+    "        tie = \", \".join(winners)\n",
+    "        print(\"Tie for win between:\", tie)\n",
+    "\n",
+    "def do_help():\n",
+    "    print('Commands:')\n",
+    "    print('help')\n",
+    "    print('  print list of commands')\n",
+    "    print('set <name> <score>')\n",
+    "    print('  updates score of player with given name')\n",
+    "    print('get <name>')\n",
+    "    print('  gets the score of player with given name')  \n",
+    "    print('print')\n",
+    "    print('  prints all the scores')\n",
+    "    print('high')\n",
+    "    print('  print high score')\n",
+    "    print('quit')\n",
+    "    print('  quit program')\n",
+    "\n",
+    "while True:\n",
+    "    cmd = input('enter a cmd (type \"help\" for descriptions): ')\n",
+    "    cmd = cmd.strip().lower().split(' ')\n",
+    "\n",
+    "    if cmd[0] == 'quit':\n",
+    "        break\n",
+    "    elif cmd[0] == 'help':\n",
+    "        do_help()\n",
+    "    elif cmd[0] == 'print':\n",
+    "        do_print()\n",
+    "    elif cmd[0] == 'set':\n",
+    "        do_set(cmd) # why do we pass cmd here?\n",
+    "    elif cmd[0] == 'get':\n",
+    "        do_get(cmd) # why do we pass cmd here?\n",
+    "    elif cmd[0] == 'high':\n",
+    "        do_high()\n",
+    "\n",
+    "print('exiting')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n",
+    "\n",
+    "We have practiced working with dictionaries, specificially working nested data structures: list of dictionaries, dictionary of dictionaries, and a dictionary of lists.  We have also practiced working with `get()` and `pop()` and passing in a default so they will not cause a key error."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/s25/Louis_Lecture_Notes/18_Dictionaries2/Lec_18_Dictionaries2_Solution.ipynb b/s25/Louis_Lecture_Notes/18_Dictionaries2/Lec_18_Dictionaries2_Solution.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f24fbe0973ca51a6351894b661a18c92bffa272b
--- /dev/null
+++ b/s25/Louis_Lecture_Notes/18_Dictionaries2/Lec_18_Dictionaries2_Solution.ipynb
@@ -0,0 +1,1291 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Data Science Programs\n",
+    "\n",
+    "[Data Science Brochure](./DataScienceatUW.pdf)\n",
+    "\n",
+    "Consider Data Science at UW!\n",
+    "\n",
+    "The Statistics Department offers two undergraduate programs for students interested in Data Science.\n",
+    "\n",
+    "The [Data Science major](https://stat.wisc.edu/undergraduate-data-science-studies/) is a great fit for students who like advanced math and programming and want to be a developer of Data Science tools. If you’re ready/interested in declaring, register for a [group declaration session](https://stat.wisc.edu/undergraduate-data-science-studies/).\n",
+    "\n",
+    "The [Data Science certificate](https://stat.wisc.edu/data-science-certificate/) is a great fit for students who are high end users of data science tools. If you’re ready/interested in declaring, visit [our website](https://stat.wisc.edu/data-science-certificate/) to self-enroll in our canvas course.\n",
+    "\n",
+    "Interested in learning about our Data Science courses? A Stats Dept Advisor is available at the Multicultural Student Center ([Red Gym 2nd Floor](https://maps.app.goo.gl/xLFy5yRbd1SGxGB68)) on these dates from 3-5 PM – Oct 22, Nov 5, and Nov 19."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Warmup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#A function to load a csv file\n",
+    "\n",
+    "import csv\n",
+    "\n",
+    "# source:  Automate the Boring Stuff with Python Ch 12\n",
+    "def process_csv(filename):\n",
+    "    exampleFile = open(filename, encoding=\"utf-8\")  \n",
+    "    exampleReader = csv.reader(exampleFile) \n",
+    "    exampleData = list(exampleReader)        \n",
+    "    exampleFile.close()  \n",
+    "    return exampleData"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "936\n",
+      "935\n",
+      "17\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Warmup 0\n",
+    "# Load the survey data and split into cs220_header and cs220_data\n",
+    "# (this will be used later in the lecture)\n",
+    "\n",
+    "cs220_csv = process_csv('cs220_survey_data.csv')\n",
+    "cs220_header = ...\n",
+    "cs220_data = ...\n",
+    "\n",
+    "print(len(cs220_csv))\n",
+    "print(len(cs220_data))\n",
+    "print(len(cs220_header)) # TODO: Explain why this is 17?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Section',\n",
+       " 'Lecture',\n",
+       " 'Printed Copy',\n",
+       " 'Age',\n",
+       " 'Primary Major',\n",
+       " 'Other Majors',\n",
+       " 'Secondary Majors',\n",
+       " 'Zip Code',\n",
+       " 'Latitude',\n",
+       " 'Longitude',\n",
+       " 'Data Science Major',\n",
+       " 'Pizza Topping',\n",
+       " 'Cats or Dogs',\n",
+       " 'Runner',\n",
+       " 'Sleep Habit',\n",
+       " 'Procrastinator',\n",
+       " 'Song']"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Aruba Apple 5.99\n",
+      "Jamaica Apple 3.99\n",
+      "Antigua Blueberry 7.49\n",
+      "Saint Martin Pecan 4.99\n",
+      "Saint Kitts Tart 2.99\n",
+      "Grand Cayman Blueberry 4.99\n",
+      "Cuba Chocolate Cream 5.0\n",
+      "Grenada Key Lime 2.0\n",
+      "Tobago Banana Cream 3.99\n",
+      "Trinidad Apple 4.49\n"
+     ]
+    }
+   ],
+   "source": [
+    "# these lists hold parallel information about the island names in the Caribbean, the type of pie that is sold on the island,\n",
+    "# and the price of a slice of the pie\n",
+    "# Caribbean Pie Rates data\n",
+    "\n",
+    "island_list = [\"Aruba\", \"Jamaica\", \"Antigua\", \"Saint Martin\", \"Saint Kitts\", \"Grand Cayman\", \"Cuba\", \"Grenada\", \"Tobago\", \"Trinidad\"]\n",
+    "pie_list = [\"Apple\", \"Apple\", \"Blueberry\", \"Pecan\", \"Tart\", \"Blueberry\", \"Chocolate Cream\", \"Key Lime\", \"Banana Cream\", \"Apple\" ]\n",
+    "rate_list = [5.99, 3.99, 7.49, 4.99, 2.99, 4.99, 5.00, 2.00, 3.99, 4.49]\n",
+    "len(rate_list)\n",
+    "\n",
+    "for i in range(len(island_list)):\n",
+    "    print(island_list[i],pie_list[i],rate_list[i])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The cheapest pie is on Trinidad\n"
+     ]
+    }
+   ],
+   "source": [
+    "# warmup 1\n",
+    "# TODO: this code attempts to find the island that sells the cheapest pie and then print out\n",
+    "# the type of pie, the price, and the island it is sold on.\n",
+    "# **this code is broken in several ways**\n",
+    "# fix all of the bugs and get it working correctly\n",
+    "# Caribbean Pie Rates program\n",
+    "\n",
+    "best_rate = 0\n",
+    "best_pie = None\n",
+    "rate_list.sort()\n",
+    "for rate in rate_list:\n",
+    "    if best_pie == None or best_rate > rate:\n",
+    "        best_rate = rate_list.index(rate)\n",
+    "        best_price = rate\n",
+    "        best_island = island_list[best_rate]\n",
+    "    else:\n",
+    "        best_rate = rate_list.index(rate)\n",
+    "        best_price = rate\n",
+    "        best_island = island_list[best_rate]\n",
+    "print(\"The cheapest pie is on {}\".format(best_island))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup 2: Write code to answer the following questions about english_dict\n",
+    "english_dict = {\n",
+    "    \"shenanigans\": \"silly or high-spirited behavior; mischief.\",\n",
+    "    \"bamboozle\": \"fool or cheat (someone).\",\n",
+    "    \"gubbins\": \"(objects) of little to no value.\",\n",
+    "    \"malarkey\": \"nonsense, rubbish.\",\n",
+    "    \"gnarly\": \"gnarled.\"\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'(objects) of little to no value.'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2a: What is the definition of \"gubbins\"?\n",
+    "english_dict[\"gubbins\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2b: How many words are in our dictionary?\n",
+    "len(english_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2c: Is \"badger\" in our dictionary?\n",
+    "\"badger\" in english_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2d: Is \"bamboozle\" in our dictionary?\n",
+    "\"bamboozle\" in english_dict"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2d: Is \"nonsense, rubbish.\" a value in our dictionary?\n",
+    "\"nonsense, rubbish.\" in english_dict.values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Warmup 2e: How many definitions have the word \"or\" appear in them?\n",
+    "count = 0\n",
+    "for english_word in english_dict:\n",
+    "    if 'or' in english_dict[english_word]:\n",
+    "        count+=1\n",
+    "count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup #3: answer these Q's about dictionaries\n",
+    "\n",
+    "# Keys can be what type?    any immutable type (e.g. string, int, float, boolean)\n",
+    "# Values can be what type?   any type (including lists and dictionaries)\n",
+    "# Are dictionaries mutable? Yes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Warmup #4: answer these Q's about how to do each of the following with dictionaries:\n",
+    "\n",
+    "# How do you lookup an item in a dictionary? Using the key: dict[key] (to look at the value) or (XXX in dict) to see if a key is in a dict\n",
+    "# How do you insert a new item into a dictionary?  dict[key] = new_value (for a key that isn't there yet)\n",
+    "# How do you update/change an item in a dictionary? dict[key] = new_value (to modify an existing key's value)\n",
+    "# How do you remove an item from a dictionary? dict.pop(key) (but the key better be in there)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Dictionaries 2\n",
+    "\n",
+    "## Readings\n",
+    "\n",
+    "- [Downey Ch 11 (\"Dictionaries and Lists\" and \"Global Variables\" to end)](https://greenteapress.com/thinkpython2/html/thinkpython2012.html)\n",
+    "\n",
+    "## Learning Objectives\n",
+    "After this lecture you will be able to...\n",
+    " - Handle key errors with get and pop using default values\n",
+    " - Understand the idea of nesting data structures\n",
+    " - Use a dictionary of lists to put rows of data into \"buckets\"\n",
+    " - Use a list of dictionaries to represent a table of data.\n",
+    " - Create a dictionary of dictionaries\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Errors That Occur with Dictionaries\n",
+    "### (and how to fix them)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "5",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "\u001b[0;32m/tmp/ipykernel_636734/191372038.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# what happens when you try to access a key that is not there?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msuffix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# key errors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;31m# what happens when you try to pop a key that is not there?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mKeyError\u001b[0m: 5"
+     ]
+    }
+   ],
+   "source": [
+    "suffix = {1:\"st\", 2:'nd', 3:\"rd\"}\n",
+    "\n",
+    "# what happens when you try to access a key that is not there? \n",
+    "print(suffix[5])  # key errors\n",
+    "\n",
+    "# what happens when you try to pop a key that is not there?\n",
+    "suffix.pop(4)\n",
+    "\n",
+    "# One way to protect from getting an error is to use a conditional\n",
+    "if 4 in suffix: # safe programming\n",
+    "    suffix.pop(4) # key errors\n",
+    "else:\n",
+    "    print(\"Skipped!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on built-in function get:\n",
+      "\n",
+      "get(key, default=None, /) method of builtins.dict instance\n",
+      "    Return the value for key if key is in the dictionary, else default.\n",
+      "\n",
+      "Help on built-in function pop:\n",
+      "\n",
+      "pop(...) method of builtins.dict instance\n",
+      "    D.pop(k[,d]) -> v, remove specified key and return the corresponding value.\n",
+      "    \n",
+      "    If the key is not found, return the default if given; otherwise,\n",
+      "    raise a KeyError.\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# There is a better way to access and pop from a dictionary.\n",
+    "# Take a look at the help for these methods:\n",
+    "x={}\n",
+    "help(x.get)\n",
+    "help(x.pop)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Make sure the calls to `get()` and `pop()` in the cell below will not cause a key error."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "None\n",
+      "None\n",
+      "{1: 'st', 2: 'nd', 3: 'rd'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# TODO: make sure the call does not cause a key error\n",
+    "print(suffix.get(5,None))\n",
+    "\n",
+    "# TODO: make sure the call does not cause a key error\n",
+    "print(suffix.pop(5,None))\n",
+    "\n",
+    "## Notice that the suffix dictionary is not changed by calling pop() to remove an item that isn't already in it\n",
+    "print(suffix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Nesting\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Putting one data structure inside of another.\n",
+    "\n",
+    "We've done this with control structures...\n",
+    " - a conditional inside a conditional\n",
+    " - a loop inside a loop\n",
+    " - a conditional inside a loop\n",
+    " - ... and so on...\n",
+    "\n",
+    " \n",
+    "We can also do...\n",
+    " - a list inside a list\n",
+    " - a dict inside a dict\n",
+    " - a list inside a dict\n",
+    " - ... and so on..."
+   ]
+  },
+  {
+   "attachments": {
+    "buckets.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![buckets.png](attachment:buckets.png)"
+   ]
+  },
+  {
+   "attachments": {
+    "bins.png": {
+     "image/png": 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IZpdWo3a5Tq5uvJ6PvoWBgiGnEcLovfEzkyum+WbR5k4WKpZslitWb6zv2dTa5tsl2Qc6ODrqO8k7C7iQXLGuy24f3Uc8uj3veNXvPOt9bNchn2Rfqh+F7OvvEeAUaB9kE2xJsQwxC9UMkw0XiGDZTROJiFyN+kH9Gb0Wi44jxgslaOxxSoxOKkxu2TuVQrOfL1UmTfuATbrfwfiMw4cqM9uyhrO/5zIfVjhinxdx9HB+XcGjY++OrxdyFikX250MLTlYeuZU8+nespkzv84xl0uc166wu0CujK06VF0M73PddXOXiJcV6x2vRF3Nu1bX0Hl95MaXJkwzx03JWxq3LVrc7gS2xrSl3E1tP9Bx8F5G56H7mQ+yH+Y+Otx1+PHhJ4e7c5/mPMvqOdSb3pfav/d53F9RA7sHI1/EDCW9PDh87FX5SMPrB6Mv33waB2+JE4Lv5Cd1psyn/WbOvv/0UXk26VPr51/zmgtxXy5/fbfIvmT5PeVHw8/pFe5Vh7XsX53b82+M0EfuQH5GtaMPYRyx4tgF3E18BsGBhptmlPY8XTi9OgOCoZ0xncmCyEDsJR1ltmVhYHnKms1mwg6xN3NEcApxDnHlcOtwf+Ip5TXj/cZXxm/G/1nguKCG4IjQXmF+4VYRb5FV0WIxJbFu8QDxVYljklKSbVKOUlPSqTIiMkOyuTsMdnyTq5L3VKBTaFOMVBJQ6ldOU1FQGVfNU9NW+6ReqmGusah5Xste65d2nY67Llb3hh5Zn6h/1yDSkN+w1yjNWMl42qTE1Ba+d9w2j7KQsnhnWWblYc1q/dymwNbBjmQ3aH/SwdtR2PGD01XnRBdjVwbXYbdK92gPA09az0GvMzuDvRW8V3bd98n39fKT8Fsid/ofC/ANVAxCBQ0G11JSQpxCpcPQYW/Cb0UU746PdI3SoPJGo6JnYwZi2+Pq48sS8vakJsYnhSb77925zy3Fab9Dqn2a/QGHdKeD7hk7DwVkhmZFZ6fkZOYWHC47UpPXePRefl/B6LHPJ1CFEkVexUdP3i9ZOSV72q/sxJnHZ1fLFc4HVJRc6KlCVWvVxNfW1328JHk5pL72ytw1lYb917sbOZrCmjtv8d1OaXnbatXW0i7fcbFT6v7VhwaPhh8ndPM97e053Of0XHQADH4cejf84TV4IzK+a6J2Cj2T+BF8qpgnf9VdUvvpvFq8Mf9b3/s2CkYFgBOHANj4nuNQA0DuRQDE9gDABueednQAOKkDhIApgBY7AGSh/ef8gODEkwBIgAdIAjVgBueXYXBOWQTqQReYAGsQO6QMOULR0AmoGXoN53zSCBdEKqIeMYpkQBog45GXkFNwluaFKkW9gjMxH/QF9CeMCiYV8wzLgw3HtuFIOAquHc+Jj8X3ExQJRYRVGjLNU1p12mo6drpcegR9Ev13hliGJcZEJogpm8hKrCCpkXqZQ1iwLBdYjVmn2DLZpdh7OWI4OThbufy5abiv8XjwInkv8XnCGUGfQJ6grRCT0HPhIhFPUQHRKbGL4tESGpKQZJdUvrQnHJ3zsv07WuQq5QsU9ilSlByVNVT4VCHVMbUW9eMaIZraWvRaI9o1OjG6uno4vT79BoPrhk1Gt4xbTe6Zdpn1mA9ajFpOWy1Yr9ji7FjtRR3UHK2cyM7JLsWurW4zHiRPfa/IneXeAz4EX32/JHKz//dAtaCk4PYQQqhzWEX44m6zyLKouWitmJzY0XilhKN7FpJckx/s005pTbVMm0jPytDOBFl9OVcOn8oryDc7hjx+vzC/OKDE8JR0meBZkXKlCpvKqOrS2ieXQL3qVZsG9xvBTck3T9y+dqe/bamDt9PsQcyjs4+fda/1yPTtfH5k4O4QaZg8cml0dpx7Qm1Sb1r+Pf2HF7NHPu+Ya18w+9L5TWGxZGn5h/3PC8sLqxprKb/ubu4fW/NPhOdfAqgCE+AKQsA+cBzUgU4wCn5AJEgOsoEioKNQA/QSARAScJafhriKeAvn8VbIdGQbcgWljTqA6kazowPRjRg8xhvTiGXEhmGf4KRxebhFvBf+AUGWUESDpImiGad1pn1MZ0jXSq9FfwfOYh8x2jOOwnnqOvE4SZb0lDkCzjybWX3ZaNia2QM5WDkecu7hkuYa5y7iseXF8Xbw7ec3EMAIPBUsFPIVlhVeFekWLROLEjeW4JL4IvlY6rx0ioynrOYOCTl2ebz8qsKc4oTSC+XHKrdVL6qVqB/SoGp6ahlqS+ow6izqDuu16tcbXDVsMGoyvm3SZtpp9ti81+KF5RuraesFmxU7nD2rg5ijupO1s7/LXtcSt5vuwx5rXoI7Lbxjdp316fGDyCr+EQE1gVPBopSQkKuhy+GmEYW7Z6K0qHuj22JRcVbxRQlTiepJR5Kn9xmnVKfSp+05MA3vJ72ZFlkPc8xyu4845I3lpxzjPX63MLCY/mRzqf9pUtmDs3vLVc5/uXC1KrZGqw5zceDyhSvJ17yuqzTSN03cvH77wB2bNva74x01ndQHWo+wXYNPap7u7/Hq03kuMsA0+GjI+eXkq8TXzKPXxpzGVyeqJ92nGWa6PmTOWn5mnHuxcPZryKLKd8SPnuXS1aBfitvzjwQYQLu5A4gDFTgC3EA4OAjOgNtgGF7/gpAFFAtVQIMIGoQRvPI7kDikPfIM8gvKAlWFxqOp6DcYJ3i122AHcGTcT3whQZ0wSXOSVo92hC6Jnp++iyGeUZJxgukM0Y8kQfrO/JCljDWJzZNdj0OKk52LhhvBvcqzzLvKDwSw8A2UR1hWRFvUQSxIfL/ESckbcN49L8u4Q0HOVX6fQoVij9KKioSqu1qBer8ms5a7doXOnJ62/mGDN0aKxjkm42Za5oUWX6zsrC/Z0tqF2T92lHTKcf7gauFW64H3pHg99BbdddBn0s+QXBmADPQPukcRDckInQm3iqiPZIlKoI7FGMVejmdP2LfnY5IbvE5VUqpSOdKOpKMOJmd8yfTIupq9nut0uOrI8lHH/MvHCMcpJx4USRXnnpwrdT11p0z0TD689/uf776gWVlVzVSTWDt10fFSS73olbyrSw3e1x80yjQdbZ6/ZX/78h1Ca2BbazuxI+Be433UA7uHpY8mHks8oXRXPh3v4ey17zvYf/352wHCoNwLhyHqyyPDNa/ujQy8nhpdeLM6Dr3FTmDeYSbB5PLUp+nRmafvmz+Uf8ycjfhk/VlqDjv3Zr55IeuLx1eJr1++tSymLRl9x3zv/JHyU/PnwvKFFY9VwmrjGvkX3a9r6+4b8x8dqKiweXxAtAYAoEfX17+KAoAtAGAtf319pXx9fe08nGyMAHA3bOs/pM2zhhGAs1wbqO/K4r/+y/kfiazUoRVG4s8AAAGdaVRYdFhNTDpjb20uYWRvYmUueG1wAAAAAAA8eDp4bXBtZXRhIHhtbG5zOng9ImFkb2JlOm5zOm1ldGEvIiB4OnhtcHRrPSJYTVAgQ29yZSA1LjQuMCI+CiAgIDxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+CiAgICAgIDxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSIiCiAgICAgICAgICAgIHhtbG5zOmV4aWY9Imh0dHA6Ly9ucy5hZG9iZS5jb20vZXhpZi8xLjAvIj4KICAgICAgICAgPGV4aWY6UGl4ZWxYRGltZW5zaW9uPjY1MDwvZXhpZjpQaXhlbFhEaW1lbnNpb24+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj40Nzg8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICA8L3JkZjpEZXNjcmlwdGlvbj4KICAgPC9yZGY6UkRGPgo8L3g6eG1wbWV0YT4KsOVqQQAAQABJREFUeAHsnQmcTeUbx5+xb9n3sS9ZsvxVUlIJaUVRFMmWJCWENhRabEkloagIoRSipEgq2bPv+76vg7Gd//O8d86555x7Z+beM/fO3Dnze3zunHdfvuc497nv8rxRGgtBQAAEQAAEQAAEQAAEQMBGIJ3NDy8IgAAIgAAIgAAIgAAIKAJQFPEggAAIgAAIgAAIgAAI+CUARdEvFgSCAAiAAAiAAAiAAAhAUcQzAAIgAAIgAAIgAAIg4JcAFEW/WBAIAiAAAiAAAiAAAiAARRHPAAiAAAiAAAiAAAiAgF8CUBT9YkEgCIAACIAACIAACIAAFEU8AyAAAiAAAiAAAiAAAn4JQFH0iwWBIAACIAACIAACIAACUBTxDIAACIAACIAACIAACPglAEXRLxYEggAIgAAIgAAIgAAIQFHEMwACIAACIAACIAACIOCXABRFv1gQCAIgAAIgAAIgAAIgAEURzwAIgAAIgAAIgAAIgIBfAlAU/WJBIAiAAAiAAAiAAAiAABRFPAMgAAIgAAIgAAIgAAJ+CUBR9IsFgSAAAiAAAiAAAiAAAhkiDcH58+dp1apVCTYrV65cVK5cOcqePXuC6RCZvAQ2bNhAJ06cMCqtUKECFSpUyPCHynH16lVasmQJaZqmikyXLh3deeedFBUVFaoqUE4SCRw/fpw2btxolJInTx6qWrWq4Q+lY+XKlRQTE2MU+b///Y9y5sxp+OEAARAAARBwTiCKv2w937bOywhpznnz5tEDDzwQUJnR0dHUuXNn6t69O2XLls1vHvkCGT9+PC1cuJDuv/9+atOmDWXJksVv2rQYuGLFChozZgylT5+eXnjhBapWrZpjDHfddRf99ddfRv6hQ4dSz549DX+oHDt27FA/FMzlHTt2jPLnz28EhbJfRqFwBExg7Nix1KlTJyP9zTffTKLQhUOKFi1Khw4dMoqeNWsWNWrUyPDjWTBQwAECIAACQROIuBHFYHpw4MAB6tOnD3366ackCqa/EYvBgwfTwIEDVbE//PCDGnno0aNHMNW4Nu25c+eofv36dPbsWdXHGTNm0L59+yhz5sypus9u7Veqvikp1Hg8CykEHtWCAAi4hoAr1ijKaMKjjz5KJ0+e9LkxU6dOtYRNmzbN4k/Lnrlz5xpKonCQUTkZeU3t4tZ+pfb7khLtx7OQEtRRJwiAgJsIpApFUaaLP/roI/V57rnn/K5727lzJ33yySc+90ZGzMxyzz33mL1p2l2nTh3KkME7qJw1a1a67bbb/DKRFQoyNT158mS/8ZEUGEy/nLR77dq1JNPskMgnEO5nQSeAZ0IngSsIgIDbCKQKRVFGC7t27ao+sp7u4MGDJFPKdpENDnZ544036OmnnybZANOuXTvCtLOXkKzx/Pzzz+nGG2+km266Sa3lzJs3rzeByfXKK6/QZ5995nfU1pQsIpzB9CvYBm/bto0aNmxImzZtCjYr0qcAgXA+C3p38EzoJHAFARBwIwHvcFIq6p3scu3du7dSFs3TzTKqaJdixYrRxIkT7cHwxxFo27YtySchGTBgAH344YcJJYm4uED6FWyjZf1mgwYN6MiRI5QvX75gsyN9ChEIx7OgdwXPhE4CVxAAAbcSSJWKon4z7OZQQj0deOnSJdq8ebMyw1K5cuWANnnExsbSnj17lJkY2RRSsmTJVK1UyJT/W2+9pSN3fBUuYvZIpreFZaZMmRyXFcqMsi5z165d6h4XKFCA5IeFv7YdPXpUKYl79+4NuvpA6wi2YFkOIO2REfZr166pkeGCBQsGW4xK7+RZ1ysSywK7d+9WCnSZMmWoVKlSelRIr9Jf6avUJUsmqlSpEjYTWadPnybZXS/PbeHChUl2VtutJUTiMxFS4CgMBEAABIQAv3wjSn755Rcx12P58G5lnzbyWjlLGsnDu3Z90rVv315jhdL4dOvWzZKmXr16RpykGzFihMb2ADW2y6dlzJjRqIO/mLSnnnpKO3XqlCW/7uHRTI2ntjVJZ28/T+1qgwYN0tjGoJ48wau00dxm/uLVWBHwySPlseJlpF28eLFPGglgc0NGGin3vvvuU+n4C9cSziO1Go/QGmWwWSEVb++PuW3i5ilplYfXg1n6zuZxtK1bt2rCmL9kjThh1Lp1a42/jI26gnFs377dKEtvGytjRhGJ9UtYfvXVV1r58uV9ymHlXmvRooX2+++/G+XJPWfbfD5p7RxYoTDyBFuHkTEAx+zZs7Xbb79d3Xu9//qVFV1t5MiR2uXLl31KCtWzrhe8evVqrXnz5pb/J9IOXuahPnqb5MrmcfRsQV+vXLmiybNUtmxZyz2Q55VtdVrCpC42j2PUkdizYCRkx+HDh7VnnnlG4+lqnzL5x4P28MMPa8JeJNKeCdUo/AEBEACBMBBIFYri8OHDNTbeq/33339KkeMNKj4KGW9S0XhkwwcRr0+0vPS7dOliSWNXbqQcNtZryWP+witdurTGJjcsZciXERuWjjePnn/ChAmWfPF5eOTNpyzevemT/IMPPrCka9WqlU8aUWDlC1Vvg1z1diSkcE2fPl1j24qWfOYyzO6PP/5Y1WtnybbsNF7zGG8Z8sXPBtZ92pxYQELtlryJxbPtzXjbpPeLR8ZUM6R9tWvXTjS95JO+6hJMHXqexK6iDMvzqbcxoeuzzz7rU5z9/jh51vVC5UdJjhw5AmqLtNOpoihK4uOPPx5wPVKXWVFM7FnQ+yM/HNgoeKL18PpU9cxGyjOhtx9XEAABEAgXgVShKCb0hShxvF5R49M6/DIKVlFMrC6Jf/XVVy11NWnSxPIFIyNNomjwyTGWcF1Bs2SOx2NXCKQOs1y/ft1nRExGw/hEDHMyjTfzWNogo148nabSxPclKsqRjKAEwkLSxKcoBpLfztLS+Hg88bVbT55QPBt99umXjICVKFHCEq4rinZ+CfVJVxSDrUNvd2JX+aGUUP32uN9++81SpF1RtKf35/d3f/744w+fZ9tfXnOYE0VRRkWbNm0aVJ+lzmAVxTlz5gRchyiKkfRMWG4wPCAAAiAQBgKpYtczv/wTlJkzZxKPrhF/sSSYLtBIOeVFNm/wtKky5F2kSBFLVtkpbJa///7b7KXvv/9erW8SQ9ZiNkNM+vhb92bJZPPIaTNm+emnn0gMjOvCU6Mkuy3NIuupvvzySyOIR2PUTmYjgB1i4iaxtsg6QmHKX6DEo37m7MQjVSpc4vQPf5lb0pg9PH1PPJWu0g4ZMsRnnaedpTlvONw///yzpVg57k02RMm6UrnKxidZQ6mLbISQfvbr108PUldhpPdfv8p9Fwm2DpUpyD/8Q4J4mQQtW7aM/vnnH7W5y16E+ZQce5zuD/ZZ59FzeuihhyxH5sla3Pfee4+2bNmi1imKYXtJk1SR50aMwJtFzDctWLCA5IhAWfMq/0+TcpSn/B81nyCj11W9enWS02VYKabvvvtOnTCkWwSI1GdCbzuuIAACIBBSAmFQPpNUpL81itzhgH7xy4iJea2aNCTYEUVZ82denyZl8JegT/16PTKSaV+XyEcFajIdbRbeHanx4ndzUIJuWeNmX5PVv39/I098Iy2y7k5GG0X4C87SbhlxNLchoZE3vSJZC2fmz7Yq9Sifq33EStZ42teXspkdS3lSNu8i9ikroYDE2p1QvDA090dGfWUtpnkNqPCT0Tuz2J9L3vVsjra4ndZhKcSPR9okzxqbhjLusTkZmziy9E2efbPY70+wz7qU9dprr1nqkNHzhQsXmqtRbjZjZUkX7IiirJWV9pnvlSw58TdzwD/kLOmCGVG03yupr0OHDppMedtFRtplWYgukfBM6G3BFQRAAATCRSBVjCg+9thj6qg+Oa5PPjIqxgvzib+k+L3uFRlB6dixozfAgYu/CFXZ5qyNGzc2e5VbRqBE5Ixk2X1pFjlOUGwTvvzyy4bdQdlNK7tqAxUxAST5zfLFF18QKzFq5yd/GZqjDLeMMsqIi4jYnDRLy5Ytg2qDOa8Tt7AUG5hmeeSRR8xe5Xayk9inkAADZKTILLJjlzc8kYTzRgUVJc+VPZ05T2Jue95Q1cHrY43RQ/Ozz0ou8ZpB4jV2lqbJs5KQBPusS1k6I71c3sxCdevW1b0hu8qI+cWLFy3l8SYd9f/NEphEj4xKmkV2bPNSCoshej1eRi5r1Kihe4O6huuZCKoRSAwCIAACDgikCkWRdyKq85rlzGb5yNnO8kWyZs0ask8L//jjj+rL1AELlUWm4uwixqjNX8wSb/4Sfuedd0gUO7PINLh84fAIH40aNcocFbBbDISLoXBdxGabHEkmCiOPrOjBPtfRo0erqW9eo2aJsyuelsgweHhTkE+pPKrlw5J/BfmkC1cAb7ChO+64w6f49evXk/wgePDBB0nMniRFwlWH8KxZs6Zqmtx/Udp05f/uu++mQKaazf1y8qzL1LNZQm2SSi/bXk/+/PmpYsWKenTIrnLfzcI7m8kfF3MaJ+5wPRNO2oI8IAACIBAMAat2E0zOCEhbtWpVpYzZmyKjK8kp8uUiZ0jnzp3bp1pZ98Y7rYlN6wS9hpJ3lao1geZCRem0r+uTdYnmdYeyvlAUarMCdu+99yZplMzchqS4eeo0KdmTnFcUep4yJLln/kTiZN3in3/+6S86oLBw1iH3VH4oiV0/UWynTJlCbKoloHYlNZEop/ZRPn8/BpJaj+RnywKWYsJRj/RHbGiaRUYUwyHhfCbC0V6UCQIgAAI6gVStKEonZMTOLvZNHvb4cPibNWumNpeIUmhW2vS6vv32W5KRx2DlpZdesky3yUaJ/fv3G8XIaKcsrmfbf0aYbGL5+uuvDb84kns00VJ5hHlE6ZDNQaJQCz+7HDp0iGSDDq9DtUcF7A9XHTKV/+KLL1raxuv/aNy4cX43ZQTc4AASipIvBrXN4u80JHO8U7cs3TCLLE9IaBTdnDZQt/THvhwknMsgwvVMBNpfpAMBEAABJwRSvaLob/TQ38ieEzjB5pHpMVlHxZsp1EigfTpadlEGK3KyS0K7imVnqIh+9Ve+fLnL1FcoRJRQt4iMyMmudFHi7bu72Zi52r0eX18DVVqSUoe9bhk9NK9NledLdpKvWLFCrbMMx5SpvQ12xVpG0gNlYS8rIb+9HqlD6gq1VKtWzVKkLO2QU2qcSKAcQvlMOGkn8oAACIBAMARSraIoC/jli1POfLZLpUqV7EFh9Yv5jDNnzhh1FC9eXE0P27/Y5Ixg3jlppAvUEZ8SKIop72xVxciokqxT8yddu3b1WUPpL52/MLvpEfkitUtqUh7lSEazOSNRtmQ0VhRGff2f3j/zyLSdg9xvczmSR1cUnNah1xvfVd+kpMfzjnTq1auXz5pPPT4cVzFPYxY2hE9sa5FC/QzIesQbbrjBXJXq67p16yxhSfXIMgOzyLF9PXv2tKxBNsdfuHDB8EbCM2E0Bg4QAAEQCBOBVKEovvvuu8SnM6iP7IDm4/XUGi1ZyG9fMyWjibITMzlFpodFOWTTL/Tvv/8qG3OiSGzatMnSDFHsZN1hsMKnQJD9C1rKeP755y3nz9ptL0oa+bKVTTFOxa50i7LSo0cPWrRokRqJk80f/nYyO60v3Pmk3bKhRja08DGQJJsmZGOSrFWzb2LR7eZJm+wcJEx238sUv9jae/vtt9U50aI8Oq1DykxIzEsOJJ35x4lMl9sVV9ltLQqc2bZmQuUHEic/Wuyjr3xyklr/yoaole1B2VC2fPnyQIqLN42cq8zH9lni5Zxn+UEkm9uGDRumfihKXU5+fOkFy48o+25xWQMq/+dkpJlNEtGSJUuUBQE2z2NJGwnPhN4PXEEABEAgbATCZXfHabl222TccYuNtIT8cqSYfharXn+wdhTlTFl/wrueLe1gQ8dGMjntxNwue1o9jteXGXmCdfDoqaUOXgepsXJgKcaf7UVem2hJY/YkZG9QT8fr+Cz16n0xX+UMYRG7nT4nLPV6E7om1u6E4nlHuE9/eFTRJ0z6J2cZm4VNo/hNZ2bBm2C0pNRhrs/uZiXNp36eOtWeeOIJjX8g+cTJEYxyLB1PSauiQnV/xG5ifM+4mYXZHawdRWkwK/DqnHBzOYG4g7GjKPWwQujDLr565FkxS0o/E+a2wA0CIAAC4SCQKkYU+aWdqMhaPjmhIhJGt/hG+bRXRhPZWLVPeKABMqIqthh1efLJJ4kVVN2rrjKNKiMkuohfRjuTIrKeKqE1kkkpO1Lymk0d6W0SbvZpSTFL5HTXdqB16PX7u8oJP/Z1iDJlzudy0+nTp32yyPKMcOyIrlu3LrGy6HeU1acRSQgQk1Sy4UhGsMVeabhElh7I/00nO6tT+pkIFxOUCwIgAAI6gYhTFOXIt0BEplRlClp2GcsmEZnqEnM5drGXF6xfL8+ez6wwyBRVmzZtLDYP9XyirMkUuUxJmxU9PT7Qq9Qnu111iW/dotn2oijN9mlCPb9czX0Qv3wx+/tClrWgsmPbviZL8tSqVUttpBC3nZHdL2lE7OH2dnhSxf/Xnt7e7oTiefSNZKpUDCfLvbELn/msdhDL8Xh2kWlPec782WGU6Us+0UPtwk9KHfY6zX6Z6pTNLPKjyCyFChWiQYMGKUPsYjbHLKLU6Rtg7Nztfj2fPdzOU9LJEYIyLSu2QsX0kyjVcqxhfOKvjPjSmsNlqYYcz8nnZ6sfPQ0aNKDo6GhzEh+3uS6zWxLanxU9s/zfkiMI5f+PnaGeRp6Zvn376l51TelnwtIYeEAABEAgDASiZJgyDOWm2SJlt6yY2JCrfKHJaRqy3ioUIrblZB2anK0rdhHjE/lSFdMusnNU1k6GSmRUTNb0yXo+WQsqfTOv4wtVPclVjhhFl3V/YshclCPZHW4fpY2vLbI+UBQLWQcoyqUob3alRPImpY746pZNM1K3rKmsUKGCRbGRNbuizIoSLPffvv4uvjIRbiUgZ0DLpiRZ/yjPhCiPiVlTSMlnwtp6+EAABEAgdASgKIaOJUoCARAAARAAARAAAVcR8J17c1X30BkQAAEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRAAARAAARAAARBwSgCKolNyyAcCIAACIAACIAACLicARdHlNxjdAwEQAAEQAAEQAAGnBKAoOiWHfCAAAiAAAiAAAiDgcgJQFF1+g9E9EAABEAABEAABEHBKAIqiU3LIBwIgAAIgAAIgAAIuJwBF0eU3GN0DARAAARAAARAAAacEoCg6JYd8IAACIAACIAACIOByAlAUXX6D0T0QAAEQAAEQAAEQcEoAiqJTcsgHAiAAAiAAAiAAAi4nAEXR5TcY3QMBEAABEAABEAABpwSgKDolh3wgAAIgAAIgAAIg4HICUBRdfoPRPRBICwQ0TaOLFy+qz+XLlxPt8v79+xNNE2kJDh8+TGvXro20ZqE9IAACLicARdHlNxjdA4G0QGDFihWULVs29bnrrrsS7HLnzp2pePHi9M477ySYLlIiZ8yYQXnz5qUiRYpQ9erV6erVq5HSNLQDBEAgDRCAopgGbjK6CAJpiYCMLiYkO3fuVNGHDh1KKFlExF2/fp2ef/55OnXqVES0B40AARBIewQypL0uo8cgAAJuJ3DkyBHauHEj5c+fnypXrkzp06dXXRYlsk+fPlSvXj164IEHVJhMVe/atUu5s2bNSiVKlKB9+/bR1q1bqWTJklSuXDkLLlHetm3bRrt376bo6GhVfrp0/n9zL1u2jBYtWmTJb/fICOjtt99uD1b+Y8eOkXxEatasSR988AFlyIDXtgKCPyAAAslCAG+cZMGMSkAABJKLwOrVq5UCd+3aNVVlwYIFafLkyVS/fn06f/483X333Sp84MCByr9hwwa6+eabVViZMmWU+7vvvjOa27FjRxo7dqzyL1myhJ544gk6cOCAES/T2MuXL6dChQoZYbpj/vz5SjHV/f6uAwYMiFdRvHDhgpHlkUceocSm1Y3EcIAACIBAiAhAUQwRSBQDAiAQGQTsa/iOHj1KomRt376dcubMmWAjZVpan5rWE37++efUoUMHqlWrlrrqSqIolzIauX79eoqJidGTW66VKlVSiqUl0Oa56aabbCFer2xg0SVfvny6E1cQAAEQSDYCUBSTDTUqAgEQSA4CpUuXpp9++klNN993331qGvnSpUs0ZswY6tWrV6JNeO211+ixxx6jNm3a0ObNm1X6VatW0W233UbHjx838j/99NPUpUsXko00MmrpT5o2bUrycSKi8H777bdG1qJFixpuOEAABEAguQhAUUwu0qgHBEAgWQjo6xKlskaNGtGoUaNUvbrSl1AjKlasSO+//75K8uCDDxqK4okTJygqKopkx7RMFYv06NGDhg8fToMGDaLatWurMPufH3/8kSZNmmQPtviffPJJatasmSVMPPfffz8tWLBAhYsi2rBhQ580CAABEACBcBOAohhuwigfBEAgxQicPXvWqFvM5yQmsplFlxw5cuhO49q/f3+SdYxvvvmmWqco9hhbt26t1ic2aNDASKc7ZP2jeb2jHm6+VqtWza+iaJ5CF2Uye/bs5mxwgwAIgECyEICimCyYUQkIgEByEZC1iCNGjFA7nmfNmmVUe+eddxpupw4ZPXzmmWeoZcuW1KRJE/r5559JdlL/+eef5E9RlDCz8umv3vja1bhxY9q0aZPa9fzxxx+rOmWdJAQEQAAEkpMAFMXkpI26QAAEwk5AbA52797dUo+s73v44YctYU48I0eOpNdff50KFy5smK2Rcu69916/xYli51S5e+WVV5Sy27ZtW1X2mjVrHJflt3EIBAEQAIEACPg3/hVARiTxQ2DXVqLNGzwRJ3nR+9qVROe8U19+cliD9u8hWrfaGgYfCIBAogRk/aAusp5PdhuLiP1EsVEotgxFWTSn0936VdIn5pZRvjx58pDsRhbzO3JSynvvvRevoihlJkXEBqQup0+f1p24ggAIgECyEYjiaZOEjzFItqa4oKL7qhH9to54Loroi4+JOr5M9OdvRHfVD6xzHR4lGj+T6CLbTsviXSsVWGakAgEQMBMQQ9WZM2dO1CSOOU+gbjG5I0plgQIFAs3iKJ2Y6ilbtqzKKyOMw4YNc1QOMoEACICAUwKYenZKDvlAAAQimkA4lbj4zOGEGkju3LmNIkePHk1y7ODEiRMpvpNgjMRwgAAIgECICGDqOUQgk72YBXN51PKjZK8WFYIACCQfgbx589Idd9yhKhSj3nLCjBwhCAEBEACB5CKAEcVgSW/iqeU53/HawzNEDR8l7fa7KCruHNlgi9L4hR/1w2SiFUs8U80rf7YWMfd7oqWLifKxMd9GjxOVvtETP382192Y6DHexSnT1CXLETV+gii+9NZS4QMBEEhFBObOnUtDhw5VZ1fr9hxTUfPRVBAAgVROAGsUg7mBslGlUhVrjuebE3021RMWzBpFPnWBmrCpi7mrrOWJT5S/McOJuvWxxs3j9YvZcviueXzwf2ydlxVJf+lFoYSAAAiAAAiAAAiAgAMCmHoOBtrZk6yk8cLyNSuItm/y5Bw9LZgSvGm/GuVREkXJW8vK4qWLRE3v8sYfPkjUtyvRvt1Ek77whP/EI5k1eRRxwS8e/8DeRMeOEE1dSBRfem+JcIEACIAACIAACIBAUAQw9RwMrio3E82PM3+zkKeJS3Hm3cEUYEr7568ezxsfEFWt4XHnzutN8Pp7RDlzeRRB3cSOjDTyLk7KxeEiN+Qkyl/Q444vvScWf0EABEAABEAABEAgaAIYUQwGWTY+QmvaV7yeMAtRu8ecK4lS59lTnporV/Nc7X8zZvSMKBYsTDTrG0/sdZ6ujk+CTR9fOQgHARAAARAAARAAgTgCUBSDeRT27CR65nmiZ5sR7Yklap2Ekx4qx40i/j7XfwvGsR3Gdz4h+nEqaT/xVLdZMmTy+M6c9oYmlN6bCi4QAIEgCMjmkc2bN9OVK1cSzCU2G/ft25dgmsuXL9PFixfVJ7Gdy3LOs542wUL9RZ7j98IBbov9E8vvLAgIgAAIBEkAimIwwHZs9qTmF77aYfzLHI//s2FEEhaMPNfdk7p5G6JXOhIN7Uf0z0xvCZvXe9wn2bDvxzwNLbL5PyJZp1igkMf/Ntf75ktEtXj6+b/lnjB/6T0x+AsCIBAggTlz5lDNmjXVEXpyyksuXu7RqlUrunTpkqWE5cuXk5yeInYVS5QoQUWKFKEZM2ZY0uieW265hbJly6Y+P/74ox7sc5U6brvtNiPt8ePHfdIkGDByMFGxEr4fsaAAAQEQAIEgCUBRDAbY3Q2JHrqVaAKbpxnSk6hZc0/uIb08p7GkNy35TBeHNqMpzFxXKd4Us5LN4jSoSjScN6v0HsiKoCnBsy8TyZLF9qwIrvjHk+4fPuJv6Z9ERaK5/r5cJ8e/N5Io9gyPbnaKP72pWDhBAAQSJiCK2SOPPEIrVqwwEsrontgwbNOGf9jFyZYtW6hOnTq0aVPcxjYOl6P9mjVrRjNnmn706RkCvL744ou0evXqAFMHkSxDPO+iIIpAUhAAgbRHAOZxnNxzmdq5Ibcn5/GjpOXNT1G6YuikvHjyKDuLsoElew4+FVCjKDk/Ol8Bb2oxsSP2HPPkU2GJpvfmhAsEQCAeAjKNLCOEMgJYt25dktFFmX4WkRHBU6dOUaZMmah58+Y0ffp0FV67dm266aab6PPPP1d+GWVct26d5QSVqlWr0vr1npmC77//npo2barSmv+MHz+eOnToYA4iaU/+/PlV2JkzZ1QZtWrVogzxKX7vv070xiBPGeN4+Ur7Fy3lwQMCIAACwRDAiGIwtPS0upIoft51HA4lUYpW5bKSqNx8rqxFSZRA+aKIUxJVGlFWE0oviSAgAAIJEsjIG8P69+9PMq0sZyv//DNbOIiTCxcuqGP05IfbTz/9pAfT4MGDafjw4YZ/48aNtH37dsMfiOO///6jLl26kJzG4k+kvKJFi6pRzCeffNJfEoSBQOgIrF1J9NeC0JWHklItASiKqfbWoeEgAALhICDnK/fr14+i5McZS3R0tDF6lz17dipevLhSFmU6WpcKFSpQjhw5SOJ12bFjh+5M9CojhY8//jjF8oaTb775xjISqWeeNWsWiaIqMm/ePD0YVxAID4EL5z2HO8hxsZA0TQCKYpq+/eg8CIBAYgTkCD3ZhSzSunVrpcQdPHjQkk1GIUVuuOEGI/zIETaGH4DI6KSsfRTFsk+fPvTggw/6zdWoUSOjfGkHBASShUB9tu7xs/8NWslSPypJcQJQFFP8FqABIAACkUpARvB69+6tmlegQAEaMGCAcssUsFlOnjypvOfOnTOCCxcubLgTcsh6Rdn8kjNnTipWrBiNGzdOrUnW80yaNIl27txJ5cuXpwMHDtDatWtp1KhRejSuIBB+Ag81I/phcvjrQQ0RSQDb4CLytqBRIAACKU1ARvratm1LW7duVdPQEydOJFEWRcQMjmxs0aeCjx49SoUKFaKYmBij2WXLsmWDAOT0ad4cx3L27Fnq1ImtF9ikW7dulC9fPipTpgxJPbIhRkzxiMkeCAgkG4Gmrfg4WV5u0dK62SrZ6kdFKUYAimKKoUfFIAACkUzgzTffNHY158mTh6ZOnao+stt47Nix1KRJE5oyZYrqgqxplLWMulSpUoUCVRRFAWzRooWeVV2lLl0aN25MpUuXViZzZCe2KLBilmfx4sV6ElxBIHkItHqW6BIri9hJnzy8I6QWKIoRciPQDBAAgcghIIrg+++/bzRIppa//PJL5Zf1iBI/cOBAEsPZsqll/vz5RlrZBDNo0CC/G1KMRCZHvXr1SD5mEbM7+uktMhUt5nFGjBhhTEnLDmlRGPUNN+a8cINAWAl0YNu+Yrati2dJRljrQuERQQBrFCPiNqARIAACkUJAlL7OnTvH2xxdOZMRw6VLl6oTXNLF2VEtV66csrv48MO8AcAmej4JNrttyZRXL0886dOnV2Ey6ijrFGVEs3v37omWoTLhDwiEg8CLrxINe8v44RKOKlBm5BDAiGLk3Au0BARAIAII3HfffXTt2rWAWiJGtJctW0bnz5/nUzwvx2sDUQqTTSiBir+zpWVdpJwGI2saZSocAgIpSqDXAIri0XStz2D8aEnRGxH+yqEohp8xagABEHA5AbGhmBwiI5FBKYli1uQUn+gk0qIdn/9c0uPGXxAIBYF+QynqQgxpfJRsYqPkoagOZaQMASiKKcMdtYIACIBA+Al8t5BIPiI160BR9JDA31ASGDSKoi5dIG3YFxQVt0wilMWjrJQnAEUx5e8BWgACIAACoSNw8+1EL7T0La+od1e2byRCQCAJBEZ8xdPQbBpqJNtajO8M8iQUj6wpSyCKd85pKdsE1A4CIAACIAACIBBRBP5dRHRH3eCa1Jo3cX3Byx0yZQouH1JHNAGMKEb07UHjQAAEQAAEQMAPgXNnic6c8hMRoqAAj6C01DZxDlEsH0E5ga+Zs1ii4Em9BDCimHrvHVoOAiAAAiCQVgmMH0kkNg0jURrVIvr2d6Js2SOxdWhTkAQwohgkMCQHARAAgaAIHD/Koyyx1iyyjqtQERWmDGdv20R08hjRjTcR5c1vTWv2HT5ItHcHUfnKRHnymWO87mNHiG31ePz5CyQ8snPlCtHRw560OflIwBtyessJ1HX1KtH2zUQVq3hz7NvN04+ZjT4aEadOEJ97aHgpH/c1S1avX3ft2kYkbbuR+ylyms/S3rmVqNqtztbAmfvJO8epaDFPufa/Rw4R7dlOlL8gUZkK9liP/yTvIt+zkyhjJtIqVbVu4JBTS07E7TI3507sPpjTusE9eylRkzuIvufTg+S5ikCJ5f+Thw8fpoIFC1LWrH6ewRC3+Sr/P5Gz2nPnzu1z/KaY49q8eTO/JmLppptuosyZ+f+OScT4/saNG0mM/VeoEM9zaUofcqesUYSAAAiAAAiEiUA5tktMvh9++WvahNGals8W9+D/NO3kcWtj9u/VtHoVreW0fljTzp6yphNfcVN50yf4xptDuj7jLfPTIeaYwNxzvvPkz8V1XojRtJ1bvO1cvMBSxvVr1zStlKltwqRvV0sa5Zn2tbdNL7fRtL27vP4ynOfMad88iYWsWektQ+q9dMma47/lmtawujWNpFvyhzfdlSua1qCqb5qBvb1pPv/IN17KSew+eEsI3DXuE/91SX2R8qlTWtNOnQi8T8mYcu7cubI/Q+NTkFStM2fO1Hbv3h22FqxevVrVx8byLXX88ssvGp/druKkPay4avPmzTPSsHKpsXJpxPPxoNr48eON+ORw4GSWkKveKBAEQAAEEicQtX8P0TPP8wiULe3P/xG1auANlNGwO0oQLeBRO7PIerBWD5hDgnN/O57o4wnB5TGnnj+b6OHHPSFreYRNRtNkFE7aOfZDojr3mlNT1K+ziHZbgogGfkwUc94aOGuq1//R10Q/TvH6uRr6kXfWhlpe4H78usa31DvqEh3c7wkXI+y/rfNN03cI0egPfMMRQvTXLqL7yhPJqHoEi4z0ydnt/fv3D3srWbGz1MFKnzLY37ZtW3WG+9GjR+nJJ5+k48c9I9My2litWjV65513qFOnTrRjxw7q2LEjbd/OI9/JJFAUkwk0qgEBEAABkmlhfbxHpkBFbs1L9HoXVrI8XvVXlMVzpz0Bk8YS7TPFDerj9cgU318LvP5AXRtYKXqqQ6Cp/acbMcAbfoWn1r+b6PWn56l1u5jTm+OmjDP7eMrySatfn37WQ0+EUeno1pao6d16TZ7rn7+qqybLBbq3I1rFzDetJ6qRzZtu+hce97Ndvfe393Pe+LTsWsHLBu4tRCTT+hEq0dHRNHnyZHrzzTeTvYVy7OeKFSvUWfKLFy+mJ554gk6dOkWLFi1SbSlevLhyS9tGjx5NHTp0UCdHSZ7kEiiKyUUa9YAACICAmYCszXv3VdL+ZcWHT7aguax8mOXgAY/vNx650+XlNkSvDiRqWF0P4RG8n73uQFyigD7yv0BSJpzmwFpvfLlKVkVANlms+Mcbv3YV0bzVXn+19F73u91I4zVYhjzemqjrM4aX7r6P8870+mWdYqilCdd3iHl/+CWvq+Mv6CqmCvbtVh5lTHr4eFYQb+P1mLyWtPI93kT5i3rdcPkSkEe7NjM6sNc3zk/IunXraNy4cSSja19++SUNGzbMGEFbsmSJGl2TozPt8t9//9EHH3xAw4cPpw0bNtijVRkjR45UI4cLFiww4mX94EU+jvDECc/wvhyhOXXqVBo4cCD99ttvJPG6zJ49m2bMmKFG9qSezz//3Minpwnm+u6771Lp0qWNLA0aNFBuURb9ybFjvJaZRRTIZJPkmN9GHSAAAiCQZgmY1ygeOxI/Bll75x2P8q6jq57JGz5ykCd/u8besGcaWctMYI2iWhfZ6n5P3vaPalrzet5ygl2j2O9lb15p9+Lfrf75s73ter65N07WGW5e7/VL3p9/8KaV9Zh548Zdv+W1WJcva1rbuP7a++rNlbArsTWK9tyP3elt3w/fWmPnfq9p5nsq7V/2lzWN+Ho/5y0jra5RND/P4u7FTAIQnmbl/wqkFS1aVMuePbtyyzq9F154QeOjAnlwN4MK69Kli1EaK4Ba+vTpVbykyZQpk/bdd7yGNk6+/fZbLUuWLCqfxEn58pE1imfPnlVuff1gw4YNjXhJU7FiRV7W6lnXWqtWLVU/H9upZcuWTaXjDSiqDL0uf1d9jWK3bt38RRthXbt2VWX+888/Rpg4vv/+e61GjRqqf6xM8n8L/n+RTIIRRX4KICAAAiCQ4gRmT/c2oTNPv+o7H9dc9obrU7pZc3jDjseNPHpD4nVFfTqYaNI8z4jZJ98QH9Abb9pEI158najHs0TRnHLcJ6TVrutZm1iG/Z2eILqLRwJFZMpx9DSPW/72GERUgUfkzKOi5mnpD94ievxxomV/ec6nnvMdr+M8QjRxDGlfmUYWvSWG1iXr6X7421vm/Y28bnHt2cW7vE1B0t/i3hEhUwycZgLtGvMI+khzSKJuVgTp3LlzNGnSJDp9+jTxBhTatGkTHTx4kKpWraqmYmWnsKwx7NmzJ918883EG1Jo586dJFO6rHSpaVoZKZT1fbly5aIffviBYmJi1EhlfA2QuljJVLuin376abUjefny5UZyVkhVPCuY1KNHDzV66W+E08gQoGPfvn30xRdfEG9Yodtvv92S699//yVWNlnb1qhIkSIkbUgugaKYXKRRDwiAAAjER0CUk6c7emP7mTZHyBpGXU7xei+RC+c9V/lbuITXnZBLTNO8xMqdyF1P8QkaHxEt/93jl78LeHPMLJOy6o3x7yrA684++JxoPw+AtH+RotLx10nHbkQ72C+Koa7ojucNK2YRszkzJvG506W8oTItvS5ualqmd8dwO2re6Yl/lNs661/m8xzrtUlQbL21Jex61bS2cOqXRFmzWdM3bkH0JSs82eOCd/L1zResaeCzEuj8FGmfz2CTQhmt4Yn4WrZsqe75I488oq633XabMg9ToEABkjDZ6LF//36S6Wge8aOcOXOqqWCZtuYRP6VQ7tmzh0SJO3PmDLVq1YoeffRRPmUwAxUqxM9vPPLrr79Ss2bN1JTzDTfcoFLJ1LQuMu17//33K2VNyhPZsmWLHu34KkrnBTYfJZtq7M/6G2+8QbxDmm688UaaOHEi8S5tx/UEmxGKYrDEkB4EQAAEQklAbB62augtcS5/oRY2rXmrHKcwSYrD+z3p9ol2EidlK+iuhK+6bUVJ9dkUopffZNuEpiyyNu+LOAVV1gTyKCGJ3cakiOyEfoNHEM3yXHeiZk8Tjbd90X02xJwqcXeo2miu6bNh3nY924yoeVtvrCja8hEbjG27MMPR3jh7X7wxVtcWXjc3aijR6mXWcDf7enYkbeQ3VnuTQfZXFECe5rXkypcvn/LL+kFRAkXE/qAoj/KpX78+vf7668r2oIwQitxyyy3qmtifkydP0mOPPUaVKlWi9evXq+TmdYrm/GKHUUQUvKSI7H6WUUxRjps2bepTlNhfFOVUlEmRVatW+aQJV0CGcBWMckEABEAABAIg0K2N1TTLVzxaJZ906Umb9AtFNW7OR6LN9hQk5mzEOPDvni8vFfig75eK31qzZuGRvybWqG9YWdNntqtxVP1GntE+UeREorvyUMk5Hj0zTXV7YgL7O/1razrZKZwltzdsCyuiJ+O8n31L9PaHRAULe+Pjc8mIZKjaqNfxy49EL/TSfbzxYgdPfdf3+Hu8xe08TvRQM6Kh/YhKlCEaxsqiLpl0RwJXUTIrVvEmWMyjuXXqef1udPV5ibQBH/mMjoW6q7xuUBUpo4jvvfeeUfyhQ4cof/78xGsMVZiMFIoilpg8//zzauOLjBKuXLmSZDdyOEU277z44otqOn3s2LGWqmREVJTUsmXLqnAxvC2S0IioShDCP1AUQwgTRYEACIBAUATe51E9UZDMMm2B4YuacI20x3j6rVZPoqW8Tk9k8BjPVf7Kui/ZhRuI5MzDo4SsDJklpgHR1Ljp5048oieKkrRJlwPsWPonUb2H9JCAr7KWKmpQZ2960ZFWxXj94trKX3qyXlEXGcV8/V3dF/91i+fLUiVIQhuNClYuIXrwMcOrHGKiSJcW7T0Kuvh7DdBDvdeeL3rd8blkV7VZxI6lmxXF914j7bX3wq4kCtLKlStT7dq1adq0aSSK1UMPPaTWKvIGFqXw8SYQkt3E33zzjRp1lPTbtm0z3w2Le82aNZQnTx4SRVNG+URkjaJM+4ZaZA2mmMTRp7afeoqXWsSJ7PZeuHAhieJavXp11XaZRpcRVn3KW08bzmu6cBaOskEABEAABOIhMHMaT8t6Rz/8puI1eWrt3/zNRDIVapa+PNo3xvMlZg6mjCafrBsMVPT1Yy2e4ZEvUyYx+O1Aov7hqWyTPkcvf+RbithING9qYR6iYCYqwbZRbCCaxbzW8cQxtmVZ2xzr6xaON9Ugkk1Gdun3MlF/HglNROS4P+pgGv29qg/lJpIxvujcrPjLfQrXJ298FQcQ/uFAVvjfT7KSmC6B51ePk6t8Zs2apZQnOQrvrbfeIt7NTGLEOm9eT0dE4Wvfvj3NmTOHeOcxffrpp6ojshZQXw+oX8VmoWwsadSokVrrWLhwYRo6dKja3KLXq1PQ/YltLtHL1vPpV2mTvr5RRhbF/I7+kSl12dhSt25dlUaURJkOlz4UK8ZLIJJJomR3dTLVhWpAAARAIO0RKM8bMLbHdVsMbss5wk5F7Lnx2cxakWjjy81pUQnmG8ZTrfrIWVLbnGBFSYhMyTaePcMG0c+SxmtJlX1Ff914tRPRkLhpxOkTeCd3a+sIqmyUad7WX87ICPuXFf076gbfltHDedd79+DzhSiHrE+UNYn6GkanxcqaQzano5TQ8+fPq40ryXEmdHztlc06MuooI53JLbafWcldPeoDARAAgTREYORgItlFmS0Hj07xdHKwIiNjvJmCVc/wyeYNRIMGeMqXUc+kKLbhamVKtzFnLiL++NwH2bn960xPrxfFXXUGFy8QDYi7511akfZEG9/8etrUev16FB9LaVpukAL9kJG9pCqJ0mzz5hlZ+5jSIkqrfFJCoCimBHXUCQIgkDYJ9OfRFl2cKIp63nBe163kqdRBnqP0ipUMZ03Oy47UNsp6zp79/fdr7y6iIjxd+MevRPfc5z4lMdJHSP3fFYQGQACKYgCQkAQEQAAEHBNo9yrvoN1nzc6L0SNWnuA1ipEukdrG8rzm8oWWvvTKlPds2hkaNxXtmyJ1h/w4lX9YNE/dfUDr4yWANYrxokEECIAACIAACKRRAoGuURSzQvc3SaOQ0ka3MaKYNu4zegkCIAACIAACoSWwcB5R3YahLROlRRwBKIoRd0vQIBAAARAAARCIcAJ/LySqXTfCG4nmhYIAFMVQUAygDN2YpjlpRrZbJmdOQkAABCKIgNjVY1MUFhG7e3J0GwQEQIBoxT98Ht4dIJFGCKRLI/1M0W7u2LFDbbWX7fbmz6uv8iJ3CAiAQGQRaF6XqFgJ6ye6OB91dzmy2onWgEBKEFjDu+KhJKYE+RSrE8NZyYDebtNct+SeDFWjChAAgWAJZM4UbA6kB4G0QWDTOut51Wmj12m+lymiKMbGxqpzGIW+WDovUaIEnTp1iuR8xZo1a1L27NmNG7N//351JqOcbVihQgV1nI4euX37dhIr7CLlypVTltMv86/+Xbt2qSld/RBtOQbn8OHDKl3u3LmNw7SPHDlC69evV6N81apVs9SrEpv+fP3113T06FFTiK/z2WefTdRq+oMPPkhz5871zYwQEACByCAwl40m62I+6k0PwxUE0hoBti9Oq/gYyTIV0lrP0V8hIEf4JbfweYWaVC0fVgy1IUOGaDwlq/x86LZqzp9//qnxwd1GOknLZyVqHTt21E6ePKnS3HrrrUY8n32owr766isVxqN2Gh8OrsJeeOEFI93777+v8j/wwANGmJTNCqs2ZcoUld7fHz6Q25Jeb7/5umnTJn9ZNT583MjLiqLfNAgEARCIQAL8buD/vJ5PbGwENhBNAoEwEVjyh+e5j+bnf8/OMFWCYlMDgRQZUWTlyhAZ0Vu5ciVdv35dhd1zzz3q8OuGDRvyenLrgnIGSp9//jkdOHBAHYr9/PPPk4ziiUycOJEeeughGjdunPJLeePHj6c+ffqow8ElUDaOyCHhH330Ef3yyy8qXdGiRUlGHpcuXUqsWKowf39YsSRWYv1FGWG5csnPLggIgAAIgAAIuIBAOe7DIjYWj41cLriZzruQ4oqi7AbmkUKqUqUKbdiwgZ555hkaNGiQoSTefPPN9OWXX9Lq1auVkiddlanbFStW0JNPPkk9evSgs/9frRgAAEAASURBVGfP0syZM1XY4sWLDRqS77bbbqNjx3gXI0ujRo2ocOHCJFPOutxyyy302WefKSVSprnjE2kTBARAAARAAATSBIEivIHr70NEBQunie6ik/ETSHFFUZo2ZswY4illNZIo6xC7du1qtLhNmzYk6wfl884775CsSxSRkUieeqbWrVvTp59+SqJwNmvWzMgnjr1791Lnzt4DyqUOERmFFCVS1krOnj2bfv31V1X/sGHDVLy/P7169TLWVfqLlzAZqZQRSggIgAAIgAAIpGoCJcuk6uaj8aEjkOKKYunSpalDhw6qR6IkisiGE11iYmJ0pzHKKAE33HCDCu/UqZNSFMUjiqGIKJe8xlFtatHDZMPM/fffr+JlFFFGJLt06aLSicI4cuRIunLlCo0ePVqlsf+ZP3++2mxjDzf7Bw4cCEXRDARuEHAhAV5jrZapyHIU/T3kwm6iSyAAAiCgCKS4opg/f36ym4u5++67aeHChaqBY8eOpTJlytB///1H5qlhSSNStWpVuuOOO2jJkiXKL3948wpVrFiRXn/9dSOsffv2Rj0zZsxQO58XLVpEUr4omyLij09kRNE8Ze0vXaFChfwFIwwEQMAlBGT2QRREWS8ty2L+/fdfEsP5EBAAARBwK4EUVxT9gZUpYt6BTFu3blXTvbIW0SxiqLpAgQJGkGxq0RXFGjVqqHWJpUqVorfeeott5F5WCqIoirrIOsYRI0YoUzYSr8u9996rO32urVq18glDAAiAQNoisGrVKqUkSq/FvXz5cqpdu3bagoDeggAIpCkCKXIyi2xe0cXs1sOio6PVlLAoiMWL84JaFvnVLjYWRcGzbyxp3ry5Yb9QlEaRggULUtOmTZVbRgD0ciRARiBlmltsN8rUtmxwkd3QolhCQAAEQCA+AvJOkvXSupw/f1534goCIAACriQQJTZ8Ir1nYuhaTM9kzpw5pE2Vl/yJEyeUwW9/CmuoKpMNOOXLl1fFweB2qKiiHBBIBgKmH7W8+40oUya1aa1bt27qx+nOnTsta6qToUWoAgRAAASSlUBETj3bCcjoYDgkR44clpNewlGHvUw5NUbfMMNGvNXopj0N/CAAAilIYPoE3hm3028DxIar2HKVTSxyWpN5453fDAgEARAAgVROIFWMKKZyxsqkjz6iaO6LjEp8+OGH5iC4QQAEUppA/ZuIFmz0bQWPKE794Qdl8F+WuxQrVsw3DUJAAARAwGUEUsWIYmpnLqMPsgbSLrVq1bIHwQ8CIJDSBJrwxrWKG6yt4CloLX16atGihTUcPhAAARBwOQGMKLr8BqN7IAACIAACIAACIOCUQIrsenbaWOQDARAAARAAARAAARBIPgJQFJOPNWoCARAAARAAARAAgVRFwB1rFI8fJWW6wow+A3etUBEVIhaAorZtIjp5jOhGXqieN785pdV9+CDveNxBVL4yUZ581jjdd+wIsSVvjy8/G/7OnEWP8b3ysYB09LAnPGcuPnswp2+axEKuXiXavpnXTVXxpty3m011sLmguD4aEadOEF24YHgpH/c1S1avX3ft2kZ8ZiHz4H6KnD5JtHMrUbVbiYRdsGLup5gUKeq70D/g+3DyONEe3nWaMRNplapSFK8NM+QE38NLlwyvcsRTnzURfCAQPAExn3Xs2DEqW7ZsgiewSJpL/Fya7bXaaxPj/teuXVPBYurLfCKV/N+Q/P7EntZfGnPY6aun6ey1s+Yg5S6YoRBlSR9aE2M+lSAABEDAfQT4BZX6pRwflkC+n+vXr2vahNGals8W9+D/NO3kcWu/9+/VtHoVreW0fljTzp6yphNfcVN50yf4xptDuj7jLfPTIeaYwNxzvvPkz8V1XojRtJ1bvO1cvMBSxvVr1zStlKltwqRvV0sa5Zn2tbdNL7fRtL27vP4ynOfMad88iYWsWektQ+q9dMnIEfB9uHJF0xpUtZYjZQ3sbZSl1avsGy9pYmO9aeACgSQS+Omnn7Rbb71VbMyqT9asWbWWLVtqFy9etJTM5z5rlSpVMtKx8X7t+++/t6TRPVWqVDHS2dNs2rTJiNPr1K+zZ8/Wiwjo2nXnKxrN43bbPvNO/hJQfiQCARAAATMBV089R+3fQ/QMn9TCg2wW+fk/olYNvEEyGnZHCTaJwaN2Zpk4h9M9YA4Jzv3teKKP2SabU5k/m+jhxz251/II26WLRGUqeNo5ls3q1LEeORj16yyi3bbKBn5MFHPeGjhrqtf/0ddEP07x+rka+nGy1x8CV8D3QUZbflvnW2PfIUSjP/CEZ87kG48QEAghgePHj9MjjzxCK1asMEplBZEmT55Mbdq0McK2bNlCderUIVbyjLDDhw9Ts2bNaObMmUZYUh38QyupRaj8GaJwJnVIQKIQEEhjBNynKMq0sD7mpJ+qcGteote7sJJluruiLJ477QmYNJZonyluUB+vZ/ZSor8WeP2BujasIXqqQ6Cp/acbMcAbfoVPhfhuotef3s/0sDm9NyXRlHFmH1GTJ61+ffpZDz3BU/mhlADvgyZT3t3b8SG6zHzTeqIa2bytmP6Fxz13tff+emPhAoGQEeBf0qqsW265hV555RWqWLGiUTaPNKrz4yWgb9++hlvOe5Yz6nV54403yKmC9+ijj6qjSuW4UvnwSKReLJ05c4b+/vtvuirLUQKQYTcNJ62hpj71ctcLIAeSgAAIgICNgHl4MdW6zVPPx454uyHud1/Vrl+96gnbvF5XIT1X8Yu0ut8bLlOxIg2re8P69/SE6X8Tm3qW6epShrrqLSfYqefqmbx5RT2SKVivmqRpy//WW6Rp9qnfaum9abktalram1rTzFPiMqU9b6Y3/W8/mVMG5rbXb5p61gK9D/aaWj3obVPzevZYb5wwwdSzLx+EOCLAZ8Br/fv319SSCS6BT1OyTAvv3r1bxcl0NL9O1Wfx4sXauXPnDL+E84ijpf5Ap54//vhjSz7ds23bNi1btmyqDh611IN9ruap52H7h/vEIwAEQAAEgiHgvhFFsyKcn4/+e2OQdzNEEdsGi1LlPKnXL/TmKl/J444u6Q3bscXrTsTF8Ik684jdbk7Y/lGi5kn4Fd+ks7W2uvdb/bIBRZfPBusuz8jpNB7R1GU3kZqW1v0HePj0mwken0yPZ+ApKX3U8ZlGRPUf1lOG5hrofdBr+3kGbyaKIpr0sx5C1HOA1w0XCISRgBzL169fP9LPf4+Ojub9XZ4R/OzZs6sNK4cOHSKZjtalQoUK6jhQiddlxw7eFOdAXnvtNapcuTJ16tSJ5CxpXWbNmsX71Dwb1ebNm6cH4woCIAACYSXgbkXRjm72dG+IKHO881DJmrgdzOLRp3Sz5vDEyd/jB7zuRFxRn7LCNolf4jJb9Mk3rKGxwuNUXnydqMezRNFcwLhPSKtdl0jWJpZhf6cniO66z1PykUO8hm+axy1/ewwiqnATUcPq3jDztPQHbxE9zmsfl/1F1IKneud8x+s4jxBNHEPaV6FbW+Wt3OaK7z7oyfbs4l3euoev0t/ipU0BcIJA8hGYO3euMdXbunVrtVv54EG2jmCSjBn5xxaLnMKky5Ej/H/KgYgyKOsex44dS3fffTfJ+fAijRo1MsqXdkBAAARAIDkIpB1FUUzoPN3Ry7Rf3OYICZE1jLqcihulu2DaAFK4hB6b8FVM07zEyp3IXU8RffER0fLfPX75u4A3x8wyKaveGP+uAoWIPvicaD+PUrZ/kaLS8e3q2I1oB/tFMdQV3fG8YcUsYjZnxiSiYqW8ofN4bd86/ogM51HEMdyOmnd6/I9yW2f9y3yeM0ZRPBFh+JvQfdCra9yC6MuRRNnjAmRQ5c0X9FhcQSDZCIjS1rt3b1VfgQIFaMCAAcpdtGhRSxtOnvS8N3j62QjnHdCGOzGHlDdu3Di1/vDrr7+m/PnzqywHDhygr776SrnlvHjxr127lkaNGpVYkYgHARAAgZAQ8MynhKSoCC5EbB62auht4Fye2ixsetFXZoVpBe8wFjm833Pd553yobIVPGGJ/dVtK0q6z6b4pv5+EdtfvETUmEcD5/HI3f69vKu5mbUtvrkSDpGd0Dy9bpHnulu8huezIUSj/LTLSGBzhKqNerGJ3QdRtEXEBmPbLp7RXdm1LjKeeY3zOBP8u2UD0e9zeRf7PbwZ5rYEkyISBBIiIMtI5Iz2rVu3qh9QEydOJFEWRYoUKUK8XtCYCj569CgVKlSIYmJijCLF9mKgsnr1amrfvr1KLhtjZMf1J598ovyrVq0yipF61q9fTyVKlKBcuXIZ4XCAAAiAQLgIpA1FsVsbol/XeBl+xaNV8kmXnrRJv1BU4+ZEE+IURTFnkzUrKxvrvekfbOp1J+TKmoVH/ppYU3zDCo4+s12No+o38oz2NXvaky66K9GWczx6ZprqtpaQsG/619Z42SmcJbc3bAtPkZ2M8372LdHbHxIVDGCkQ0YkQ9VGvTWJ3Yd/WZF+iBXnof2ISpQhGsbKoi6BWMURRdNslHwxj+bWqaeXgCsIBEXgzTffpOnTeeSdJU+ePDR16lT1kfWKMi3cpEkTmjLF88NL1jTKWkZdZKdyMIpiq1atVH7Z8ZwlSxaaNo1nDOJE3/UsyqTsxBYFVszy8AYaPQmuIAACIBA+AsHsfInYtPHtepYGv/eGbC+J/3P5smdHcK1C/tO0a+zb7cR2PZtztKjvLVff9Wxv0+9zzDkCdqtdmZVNfasi3yE22bLBW79wkLoDkWDbmNCuZ6nPXp79nvB90OayoWJ7uO5/40XfVutxcpVdzxvWWPN3aeWbxw0hbHRd35Hrhu5EYh/GjBnDj6JnR7P9yusRVZO3b9+umXc+6+l4E4wmBrvtktCuZ1Yy/daXM2dObd26daqoDz/80EiTI0eOeJ8B7Hq2k4cfBEAgKQTShU8FjYCSZ/Kv8jfeS7ghvNlErf2bv5noWR7NMktfHu0bwxs97JLRFCDrBgOVuAXv1OIZHvkyZRKD3w4k6h8egdtoyvjyRyZPnFNsJJo3tTAPfmB809lDgm2j/dg/8yaeAO8D3VTDs2Pc3pZ+LxP155HQRESO+6MOptHfq/pQbiIZU1v0159RVAfeUW83pJ7a+hGh7Z0/fz517tw53tbpu6FlxHDp0qVUs2ZN4zi+cuXK0Zw5c+jhhx/2ya/nkwizW/zjx4+nevXq8bLjzOJVV5mClt3N+ohiixYtSNYpyohm9+7dfcpQGfEHBEAABEJMIEq0zBCXmfzFiSkVfZesGNwWcyxORQzZ8tnMWpHo8L6Ih71F1GuAp5VJbbPTviaWLyXbePYMG0Q/SxqvJbWc9Wxus1kZjY3ls695fnora86y41tk6pdsnqitcrrqz9vdWXEeQcS/AWjWJqKy5l8druppqunM+fPnlfHtvHlNG+MctF6MdIvpHdnMoiuN5mLkdX369Gk1FW4ON7tf3tWTPt72gQoSg9uvRPPzAgEBEAABhwTct0Zx5GCxUUGUjdf8de4ZPBYZGePNFKx6hk8284aLQXFKooy2JUWxDVcrU7qNOXMR8cfnPkyfQLTXtNHI3P+LF4gGxN3zLq1Ie6KNb35z+tTultHkcpU85o1kbSckxQjwVHBI6k7HMxTmtY72QmUkUtZLBiofHp9Ox64cV8mfL9yRSmUpFWhWpAMBEAABRcB9imL/4d5b60RR9OYOn2vdSh4RGuQ5Sq9YyfDVk5SSI7WNo/mHwALRkPzI3l28HZV3TP/xK9E997lbSTR3X84D788K8hvvs/F09/2XNncV7uAIHDiyhAbzR6RerruhKAaHD6lBAASYgDu+Vdq9SiSnjZglZ06zL7LcT/AaxUiXSG1jk1a8vpNHZM3Coyxa+vQUJVPOQ8eaY9KO+61hREv/IPp6TmSOUKedO5HiPb3nhtq0tdgen3YUy1zcJwwBIAACIJAYAXesUUysl4gHATcR0Nco+usTz9jTwqWwIemPDcJAAARAAASCJhDElt2gy0YGEACB5CbAe4Do5lpsF/SzwHa3J3f7UB8IgAAIgECqIgBFMVXdLjQWBAIk0OYFinqRjbrLyT0QEAABEAABEHBIAIqiQ3DIBgIRT2DUZN7Uw5ulZJMPBARAAARAAAQcEHDFZpYjV45Q7HW2o2eS9FEZKDpTURUitsc2XtxIRy8fparZq1L+jPlNKa3Og7EHaPul7VQlWxXKmzGfNTLOd/jyYbqseYw5F8hYkLKmy2JJd+DyQbqmsT1Gm2SNykoFMhWwhSbuvXr9Km3i9lfNXs1IvPPSLsqcLjMVzliIDlw+YITrjoxRGakQx6WLsv4WkLJWxKygclnKGRw2X9yspikrZWNTKw7k3LXzdOrqSZUzR7rsfrnFXIuhDRc20HX+979sNShLeo9hYXt117XrtJHTXdQuUbVs1bmP3rP79sbutSen+OrzSZhWA5YdIypZho+k/Jm3vT6QVimkaL/xfor891Og3xEJvZ+OXT7G7y3rCD4f50DFsYkoRf//ofKkE3CFolh4GZ9dHGODwaenXK97nT499Bm9tL0LT8GZ4vNVphPV/rQoNKKElFx7D9Gp3UbCGkUa0IJK0yl3BtPZyRxbZFkRIjbZJzKu+nhqX6idxxP3t9gyPvM1Lt4cUa1IfVpT9TdzUKLuqcem0ZMbW/BRDtzFO2No/+V9VGE9f+Gf3k3zb51PWrbrVHIRjxr5EzFCmKc0/VF+PN2Tq65KUX7dvbT7yF+qvJm3zKR9rBi/uO4FFfdUqXY0+cbxyh3Mn9f39KVPt7MBaJZSherQrureM2hPXjlBnXf2oGn7JvANiSuVddfuZXvR8NJD4gI8lx9O/EhN1z3mPRub0w2uOJR6F+tJopz762eZwnfRDr6XkEQI1H+Qz85+i7Tu/TwnESWSHNGhI4D3U+S+n0RBDPQ7IqH3kzwtBdfWIjrpO3p/qUGs5Qdv6J4slAQCyUOAv4pdKqwk7YrdTS+ttymJ0t0TGynf2ruNjl++foVKLueXmUlJlMjVh36jPKxYpZTIi+nJ1awk8mDp9po76NL1i1RhaUXVzsGVhlCDPA0SbprG0fziqrviXpJfu7HXL3uURMnFcU1YgXv/6ESjjCm7vyRR7IIVjUcB45NPWFGftmeCV0mUhJz8w21DacTBj4xsf539i5quNCmJcele3diLRh4cRdcMLdPIAkewBHr2p6gW/Myc9oz+Bpsd6UNIAO8nz0naKfx+CvQ7IrH3k3oyeMYIAgJuJOA6RfHwvXz8XkONtLoapdNNLufMRM+U7kiU3XQLWVk8ffW0Chh1eJR3BJDHWHvc2FuNuKnIY//R/NPzTRmDcGbhEbHKQ4zP+8V6BJGZqOmefp706XmQTYulL46MN0bbZGrdnwy5aRgdrXuUXruxjzf6Giu9MavUr1oZ1TTk8g7qW7Ct4RXHkStHLf5QeSoVrkuPlWhJxH3R5Z2jU3Qn3bX9ecNNufPRfdGPGn4ZEc6XPp/nvvK9/f223404OIIk8N1Comq8pGLDmiAzInkoCOD9FFnvp0C/IxJ7P126FkvaLRuMdxR5V8yE4rFJmTLOniLtGn95QNI8AdcpiuY7mjV9VnqpXA+6WusCfV1+LK373zpzNO2P3a/8Y4//aIQ3KfIUfVBqMFHeG42wH0/8ZLiDcmS+gXpF9+Sp017q81Ceh4LKTrFx7eX/q5WXV6a9vPZRl54bepD8yvUnsg6yTs7bLVEVsvJIJMt/VVjpjdMxa+d6iDoVeY7qFWviScvT9WWylPW4Q/S3ROZiNKfmHNpYbSHNqDiJepZ5zSj5xMWlyi0vWTq+wQifW34iTbxxtOGXZQPrLq71+uFKGoF9nL3K/4i+m5i0cpA7SQTwfvLiS6n3UyD3IM2+nzaupajn+NSnK1e8NwquNEnA1YqibOb4uMwHlD7KM4xlWVTMUz/lspRXN31TzB/Gza+RvbJy35a5jBG29OImwx2U48w5Svcb/2ZdXpo+PvhJUFkl8bMFXvDm4f+rTfJaFc0TfqaJe+/pSVHL8tMjqx8x8nYr35NKZuGpdZZvj00lkn02vJdkQplPSDbFLDg+U42gjq/8ZcjX0rQr1JbMCnLpuHZIW2rkaCAX2hm7Q131P/KlUSCDddPPtovb9GhcQ0VATt95tROPUns2ZoWqWJQTGAG8nzycUvL9FMg9SNPvp/E8iNKuES9/sm4WDewJRyq3EHC1omi/SZOOeac6GxR7zLvz1vR/IBPvFhbJmy6HkX2laSTPCAzUIesET+2ml9d3pbf3Dgw0l0o3sERferxka6JsvA+h0nCqn6u+msaWKXQZBbw/9wO+5Z3noNO8ztA0YzDxzGLetLKPLly7QC23P0WyaeVI7SNUNmsZar/jZaqUuy79VesvEqUu3NL98Dijir5Fef0oi2xUMUtGnlZXu7U9+r2KOnrlmDkJ3KEiMGQs0f1ViQ4dCFWJKMchAbyfUv795O8epPn306R5RC3vg01Wh/+v3ZAtbhLSDV1JuA9Hee1dl62dPYm411/zaJohWXhBSdyoytGrx1XwyetnjejamT2jcUZAIo6JFb6h/BnyKRM6TVgR0zfJ9N/Vj95m5S9QKZypME2vMIFIPnGiT2PrfjU6aHiIakc/RI/mrke/nv2bftv/g1owfuLoUno8w7O0tMo80mqL5uqVP26a5fWE2SWjmZePrVC1RBe6gx7L51mHWJynp80iI6XRmaItym6RjEXMSeAOJYE/thIV5Xvw10KiO+uGsmSUFSABvJ9S/v0U3z3A+4kf4hmLiZrVIZq2iNf6ewdRAny8kSyVE0gTI4qy27fQ2rvU7mG5X9OrTaeimVkRiZNbctyjO2nHpX3KvezSDiPslrj1fUZAAo5FZ/6ge3PdSw/keYAa521MP5YZ4U3NI5f6ruIZx2fQsAPDSew2hlJESewV/QrNrzSDsheoaRS97MivJDbAApEzV8+oHclTeARW2IVC1seso6fWPekpKgvRqso8pREnJTOX1p3qevDKQTp0xTrKeGPW8pY0/jzhYuqvLleG1bmXaNRQHP2XzDcX7yeilH4/JXQP8H6K+w8xdxVRY/5OOXc6mf+HoLqUJpAmFMVHtrCCcoJHTeKk14ERVHpNHSrLJnJEeepSoKUeRbMPTaWnt3Zgjc6rKLYs8IQRn5jjk0NfULHF0VR3Q2N6fXdfenSrZ9RM5eN1gWLE+6ujX1OzVc2o14ZXKHp5MRKD1aGSE1dO0p5Le0jsL8acWu4tNqMMLlpHE72RVtcdGx+l7uu7UcvVLantNl7DlkSRqZuqq9hYuKyNjJNaG5uqe9B3z9uUKV1GEnuIujy8tRVV53hDeKq9ajaeHk1Awsk0gWrdF9WlN0W152f2nHdE3X2djKwe4f3E9yMF30/yNCR0DzLwGne8n+L+zyzYzEtVbuLvR8/MW1woLi4n4HpFsfuuXvTbPp6CNcnuI3+zPcG/aefhxXRVu0ZtCvKi/lw3eFKwMjNpN5uhiZPbij5At99wu+4N7HqNaNGB2TRo6zv8hevN0rvE68qzJma9N5ANc/9xhqf8QiSDt75Hpf4s5bG/yBtgdBlSdpixqUcPi++66dwfRtS3B75K0gjT2avnqMh/VYguGkUq4+f6Pfj+DE9lsMws+ymxPSOPnDlNMl2uy+TyUyhDuoRXSYSTqd6ONHP9ipcj3J6LjXc63MSVZkAlvaN4P3kYptT7SWoP5B7g/WR61pew9Y16PCN37IgpEE43E9C/ml3Zx8nHJtOIbcMS7JvY0ZKNE6du2Uv3RDfyKiusl7Qv05kWV/azhi/KW6T9iLz3S/ajRsVbGCZoVEoeEXuzQj8aXPo95e1UmEcsTcs8rrDBb6eSkUfj4hVpJ9f96o1vUNciL8WbzB7xRdkvvPYOA5utNorIarPvWHtTE8/mGiOF1ZExbkd6FT5acdnty1hhz+pNwJt4pt88nZ4qGDdl7Y3xcYWSqU/haTFgI3e6fGWin75Li71Plj7j/cSYU/j9FOg9wPvJ9l9iDS9JqlMYm+BsWNzqjeIjjAKbj4xgAlF/s0YU42mgGLQVkwdORc5CPnTlEBXLVIyiokwaoYMCZT3iNZ7a9ne+86u73qAh295XCtnhu5PWZgdNSzRL1BLuO4+GyqaT/dX/STR9KBPIGsnLvDbSHzepZ8HpBVR/WX1VpfkIv0hnGjJGb3cn6j8iZMUlWtBbPYj6DOYfPwmP6iZaThpNgPdT6G98JL+fpLdRf/D7M255t36EX6p7P/27iOiOugnfvOIc/fcuouKlEk6H2FRNwHVv/rf2vkO50+eknOlz0BvFPVO9wdwhmeK02FsMJrMtraxH9CeysWPIPo+SOLna5CQptv7KT2qYHJmnpsx5Nv7PCpOSWlzQ+XNl4GlPm1y8fokG7H2XV1lep/UXt9tiiSKK6RcfE00Z49PGkAX8JcN9ySj9hxMt/4NNBfxMlL9gMlbsvqrwfkr6PY3E95P0ahyfnLXtYtzadl7CZJaIej+ZG5ZU9z4uoEZpfj9sISp9Y1JLQ/4IJeC6EUWDsyyOvjcyB0vlhbI/9iCvjXyaSmUpZTQ5Uhwtt7an23PUoI6Fn6Ws6UxTwSnYwANsy7LYH7wuxib6iGJEMe3blegdk/klW5tTrVf09wVLiG4Ocs1uqu1waBpuHlE0SsT7yUARrCMS30/Sh6gVZXiTB4+u2URGFL859k1Ev/NtTfZ4AxlRNGfcxGvvK/JGF4jrCLhiRPGlIj1o26W9lpuT38+olCVBCno6FGqfgrUnXvXkG72beRJPnTwpsqfLRg8Ue9ynsvq57lBhkc7Up+GpMeAMN/oW5v3Vp6Q90znJSzNSIwInbcb7yQm1+PNE4vtJWtuvQBtals20UZHDZPmS7JpOE++nSrxpcS2b0KlaI/6bh5hUScAVI4qpkjwa7V4Cbh1RNN+xzk8RDR9HlCUyRpzNTYMbBEAgBASCHVHUq1yJWQcdhVuurhhRdMvNQD9AINUQ+GwKr0uaR/TdcqKSPOUGAQEQSF4CS/9ku2LTwlfn/t3OypZZhyV/sImte5zlR66II+AKRfHIlSN8gkisBW56NtMSnamoCpON3RsvbqSjl49SVTbDkj9jfktas0dOStl+aTtVyVZFGcc2x+luMSB9WfNsaSuQsSCv4+OjRkwi6+muabbVzByfNSprvDt5Tdl9nLITexO3v2p2NlodJzsv7aLM6TIbfdTDJe2u2J18tvN+KsD9LJ65BOXOkFuPJolfEbOCymUpZ3DYfHGzspVYKVslI10wDjEYfurqSZUlR7rs8XKTBJfZFNBh3lUukjt9HsqZgXfMmEQMoG+8sIEuapeoWrbq3MdMRuzeWOvyAolIrD4jMxyhJ7CC73mpskS/z2G7ag+FvnyUCAIgED+BDWuJ3mf7s5Eoslt60XyiuxtEYutUm2JjY+nw4cNUsCB/h2cN/8zI1atX6cCBA5Q7d27Klcu6YfP6df7e27iRMmbMSBUqVPDL7Nq1a7R27VoqUaIE5cvnf6Os34yhCBTzOKld6C/eDMvHGFs+C0hj+NonBz7VaJEtbkVl7cTl45Zu82kmGi0rZSmjxtoG2qkrpyzpxEOLveWNOzw+wXhzm6qtre+TNrGAb49O1egPro/7EHM1RttyYbOnnb+SNv/kfCP7hpgN2m3rHtCIw811Kve/WbWBe99VaUv9V8cTz+lmnpip8Q5CI/1TW9oZ5QXj6LKjm1GGlJ+QNNrYwkirt0lPP+P4DxotNLV/PmmD9w1V0YdiDxn5zP0rs+YuPXvkXPu8JDan0tZnSF/t+rVrkXMPIqgl/MNSk/eL+bM/9oDRQnlPrY9Zry04tUA7dvmYEe7PceDSfm3R6T983l/mtPJ/Ra/rwrWL5ijllrr1ePP1aOxRn7SBBFy5dkVbe36NJemOizs1cx/1SEm79cIW7fdTv6s89verxC85u8TCYdOFTdrGmI16EUFf2ei/0V/7e99eWOy1y0baM1fO2qO1a9evaevOr9WWnVumXboWa4k3s9TdidVnKSBYz7hPIv8d8+usYHuVbOnnzp0ru1216dOnqzpnzpyp7d69O2z1r169WtXXvXt3Sx2sPGqsPKo4aU+VKlW08eOtesW///6rsXKo0qRLl0577bXXLGWE2+OKEUW/CjObsdoVu5teWt/FN/rERsrHx/dpt2xQcTLKVXJ5SaIL1qSrD/1Gea7eS1qN1daIZPL9cOJHzwkrXN/2u3bQpesXqcLSiso+1+DKQ6hBHs+vtdknZ1PjFY3jb9WZi9RX68dnQPfkE2n+8qTjR67Jzh4UzSOiukzZ/SWNLD00wRFBPa35qvEoYCAy5tBYmr1vqt+kf539i5qufMwax8W+urEXZeONLI/lNx2FaE0FXyQQ6D2QomQq7IsZPFScNxJaFDFtKLyMDRPH2Xk1GsW7nq/XvU6fHvqMXtrO76hLRgxRvsp0otqflv+HMppecu09RKd2GwlrFGlACypNt8wYSGSRZUWMd9m46uOpfaF2Rh5xFFvG1gNs7zoJr1akPq2p+ps4AxY5KvTJjXzAAL9vY+6Mof2X91GF9Q+wkf3dNP/W+caMx8YLG6ndzldo2aFf+KvQVjwb2R9YtA/1Kf4GlV93r+cdxeXNvGUmz4wcoBfXvaAyPFWqHTnZyPL6nr706XaP3dFSherQruqLbQ3weh/f0tp4Rw2s9K5qkx4r7+Om6/gdFWcfUU6SGlxxKPUu1pNklqnkIv4OsYlulcEWnHa8Dfl7SabHGz8R0X2Wkb4mTZpQu3btiJW0sLaVlTpL+TJSWK1aNWrYsCHt27ePJkyYQB07dqS77rqLypUrR6dP/7+984CPqtj++AmB0HsCCQkkdAgEBAQECyCIyANBLCgoouBDQVEQeH9FUAQVG09FxGcDRboCgqgUpSq9d0IJJSSEXgMJkP/vzN179+5mN9lNdpPN5hw+u3fuzNwp3xvunntm5sx56tChA7FFctiwYbRkyRIaO3YsQaGknj172pTlrRP8qfuXsMPttPbY1bh1Gv4f42nDUiqIelV9Tu0CoEXgG8ri+Rvn1ekXiV9YH5xQnQfXGqYefCrx1FZach4m9KwIRqRZodM/70XAcbEb0u3ISC13IJ5NadfpG7jV0R9SPLTOgjdXenCbnZLISSFNtFXCZUJUPv7iYVz+MTAk5SCNqNDbOOXAydQkm3NPnWy5vIWe39XPaXF3H3jemlamPN0XblUM+Ye0fGB57b7i3v7Z7E9rXgn5DoGfV0DbwJDIzq2+0yZfbQkeTcaLrFlJ5PZaXmT1phsvsiYlkdPUiywUq9wS40UWs34ONDW9yKKd79e1fZGtt7oerT/hQEnkxvOLbPxITB9KSfci+17SFKN7/CLLmxi4Kx59kdWVRG6E5UWW/Tre5BMRxwS6PIa5zNb76DhT7saGh4fTtGnTaPjw4TnekMqVK9OKFStU3V9++SX16dOHWHncuHGjasvkyZOVsvj+++8Tf2AJVUPUn376aY61VdM2cqy6nK2oaGBReqnGYPpv1Q/UPsdDKw2kmL9jjEYcxzw+nr/31el5RlyXsCfo46j3aRzeHunMfhU/78yvdF+Z+4w8LgcKl1RWvCzv8HJ9h1bVTaLoDdE0oPIrRtVDdg2m5iWb0jLeKznViCYqG0bxDTZQpcLhRiSGtehn7g9ka/0lVOAU3g8whbJl6Y7UL+zfNOvcb/TX8V+IYOWoVqS6cZ2nAqyQN97aWD1YHZWJIRyi07uMpN9qTqHGJRpTaLzlvuCHdEfydmpaoqmRRwI+SuAY2sXuMWZOJnrsaR9tZO41y7xzVNy1OK0h/CJb/mn6Ielrq+XR8iLLz6d0L7LVhtG42A80y5zlRTZLzyd+ka2GcixSv7h7PvCy9SJbFi+yhavSH5fx/Dp/SrVAf5HdnmB5EeQX2fBh9PzJNXoT1Yuss40MjExZCLj9Ilv8blpieT7xi2zfin3UiyxXbd45KgtN8c9LHu1F9APM2E85NxaYO75jxw5av349de7cmRYuXEhnzpyhrl27KgvbmjVr6M8//1QWuGbNmpkvo61bt6o0/s29//77qV4927/pAwcO0B9//KHKu3z5snEtW+uSk5NVfPXq1Sk1NZXmzJlD+/fvpxYtWlDr1q2xMZWmLi1YsEClN2zYkDBcTSVLlqRu3bp5bN7gqVPa/wdWIFlYMWRp00Z7KQwNDaVatWrRhg0biPOGhFiNQSqjF778WlHkrfw+q/axgc1mx5UAwoKOmiptz5XlRp5GxaNVuFnharSeNEVxXfIeI92twIVLVGAplLIyUfRp+GAaWOklty7vG9Kfvrn0hXYNlMEu5TrSBPrEKOMM3q4XX7Q+RDnhQP3VNkoix9UvXl99ODzjFIZ+eZ1NYfy/rTaeeFHMX6ehJILHd9GTbBaPcP7sCpvZW+5+SFlsW4Z3pBPYni/u5N82xR66ftDmvHbROhRS0PaPPzY5VhRFG0o+ftK9N9FGbP347gTZ+s/JrZIXWQ2MvMg6+QPxt+heGDXCAhLqOzDTns2fP5/eeOMNqlSpEl24cIGuXLlC77zzDvXo0YMmTpxIgYGBNGLECBowYAB9/vnnqrwJEybQyy+/TLwwhOW1115TVsKHH35Ync+cOZN69+5N165do6CgIEpJsZqHWUlkSx7mDxIrn506daLFixer6/irTp06SgktXLiwasemTZuoSJEiqq6rV68SW/dYgWWlMavCiumYMWNUPe3atVPt4LJ4OJrrrVlT01c4jhXgXbt2qbScUBT9buiZITqTqaemG0ntIh6iIoHQlljwt6tLUADMapByBUroUbQJq5izLDwdAUMxL+8cSG8dHe1WMaOrjKBHIp8iKkb0Ud1x1LZ0WzWMTcWxyDSiC91fpgOtvrrZWia6U71oNeu5XejqzavU48ATxHN9TrY8qfI+e/BlqlumNa1uvpqeqdjb7orsn446Nob2JC4nwv+fxXVmoUBopHbC83vMUgjD6gUC8KcZaI1NStXesqwxEvJ5ArXqURoe6CKOCegvsoFwyMzi7ousXmp2X2QDNlSlz06M14tz+cgvsoZYXmSNcwTceZF9s8ob6tLcfpGNqninuQsq7OqLbLoLJSI9gSjnv0/pM5NSBC9dukRTp05Vw69sXduzZw+dOHGCYmJiiIdqefUyzzEcMmQINW7cmLAghQ4dOqSsjwMHDlTDuGyR7Nevn1ptPHfuXKV4Tpo0yVGVKo7nBf70009qVfSTTz5Je/fuVRY8/QJWVDn94sWLNHjwYKW0sQU0O4IFK4QFL8oDSVhYmFKGuTxue2RkpGHR5Dhe+cxy9uxZdfT2V75RFJMw927A/hc0nrCjfg9rmiFFrC5Ykm6cVtFnb100klsWjjTCrgSm1P6Rfm/6O/1yOyx1ZaOMS0YdHmmEXQmEBoXS7No/UBoWKr8aPkgpT8MihlLanZinFz1PKbr3FjeZ3qHwYrWh06KLBRajtJZpakJ4BcsiluX15tPuBsvozlLpH5BOC3IxgecTjdqr9bl96Yfpg+MfUdzl1cbVE84soOlQ3isXjjDiOMA/MOwmBxN/DAkrFGaEJeDjBPhdYP0qZTnI8rQLH++iN5onL7LyIuuNvyufKXPlUqJ2ndxqDlsQ+RnCFj4+srWP3cewFY3jeC7f8ePHlTWPLYWlSpWir7/+mr799lsqUaKEUiiPHDmihrHZMsmLP3gIm4eRK1as6LQtbE1kSyQPSetWQrY66sLDwjy0zQojl8eyb98+PTlLx9dff10Ni/Ow8pQpU9SwNhfEfWWLqlkOHtRG4TLqgzl/dsP5QlHkSdIVt99tWA5nN5htMzzbpEQrg+PBa8dUeP017UbwSRMMhboqKy4spzal21CHsh3owXIP0rxq1qFitlzqk7HnnJ5DH8WPI/bbmB1pW7K5zeU1tlZXC1z0SB765Tkzj+x9So/K9HgBw8OfnPhUKXHMLquSjAU4uiw+/jO9ve8t6xwsJCQmraUexz+gSMxVMsuJ1BOUkGprZaxV1Gp2N+c1hz3F1FymhN0k0L4hbmwCUdO73Lwwf2eXF1kMnMiLrP/+J+BdXu5um+X+sQJYrBiG1kyi+xJkZY6VQBYeomXlkT9t27ZVw8/sm5AthCxNmjRRx8y+2FL30EMPUd26dWnnzp0qO9fjSNgPIwsPQWdH2L8iK59soWTZvFkbLWSlNCEhQVkW9fJ5DieLPo9Rj/fW0a/nKOrQOu173FiYwnFD4z9RHx7ejI1ZTgNCetCzJ5ao7AsSZtKTgRjbPWtVFHuEPKoXlelxfMI39HP8VGoV2plaFG9IYxPGWK/B0DBPxJ6c9D09s7W3ih9a7FW62OISlQy0DnVbL8g89GLYizT8yOvWVduXiKJWRmGldyD+18QQXdqqud5Q/8emZF4gcrTY3VUbLkb48cjeNL22cxN9RgUWK1CU7qj0gE2WtWd/t7oCwXD0G+W6UFCBQsRuJA4lrlJ5/7W/J5UvXNt6HW5HTDH0JQPxJNMMqpGkjAjw1oUjPsKiKG36RkZZJc1KwJUX2U0XteeTp15k9c0I5uFFsusmzSKiv8jyM4pfug5dj6Mewd1tXqqtrXYtxC+yfxFGVizCL7JxjeIosog2SsMvsssuLMOCnUn0Ux3Xnk/8IjspaTJVxKhIt/IPZ3letf2L7GL6WW+mOqoXWTj+v97QdkiRX2RDUjXlQL/A1RdZTzDV68wzx83riBo182pzmzfXDCZsRXz33XeNuljBCg4OVnMMOZIthWylzEyef/554oUvbCXk+YirVmm/TZldl5V0tniyEsqLaFjY8TaLbi1ktz2LFi1SbnN4DiUvsOGhdVaEWbnMCfF7RXHQ4aG09NhcG5bmxRQ36t+kpyv0omdL40cOi094ocfUuO+M/M0qdaA7St5hnLsUuAmn9PELaAUtsMk+rMpr6nwbViEbcpVoOR6Unct1NqLcCfDOJivhc+2ezfcYrnPU9RfRCIKSmAXZc2m5cdWM+MlqqDorQ4hlC5alNfV/M8riQNVtd1PcNW34eXSE1U/ZL9UnUExSA21l9IXzdIbwcLHItJrTqWCBjP9UPclUr1eObhCYO4Ooa3c3LpCsOgF5kQUJeZHV/xz867hjC1ZT3ub1PkVHR1PLli1p1qxZxIpXx44d1VzFGTNmKIWvUaNGxAtEfvzxR2V15PyxsbFO27Vt2zYqW7assuTxXEQWXmXMw8KeFl6FzYopr6JmiyjPdWQLqj6kzXMk3377bWUdZaV15cqVqglDhw71dFOclufXQ8/TTk2jT2Jh4chA2NciWxbPNTlKrcKhrOlEoJc8W+0FWhU9P/3VpvUYatGFKcd7kSOpc2X8YJr1GljEhtceSe9X1d50+oX2wd5z1otS4fA7O3J3qbvp7J1n6MkolGtrnVftCAq5HW/r2h+7K/V8U/0b60ISTBV0R4pa/Du6co2+cIjz1sfWiuvvwJs7nO8agr7MbjybnqgAi3Am4mmmmVQnyTqBGgjswYuPKIk6EbeOzl5k+WWWLew30rQXWSpdUivXgy+yY/ePwYiDtbkZvchac7kX0l9kyToNXCuAX2Th2sfG0biLRdu/yNo7MHaxGNJfZPllVv9Elb7LuJxfZEdHvqXO+UXW+G3gF9mk7L/IGhX5Y4B/I/fiuZBNJRG7kDilo6fxkT+8UpqVK1548uabbxJ2XKHevXtTuXLlVBms8D377LPK3c4rr7xCvEqahY0guiFEP7I/RV5tzO552ErJLmk+/PBDtbhFr1ddjC/9nOcrZiR62fZ52HF269atlfWSlUQe7maXQBERESorz5Fkd0C88poX9bDrHp6HycPUOSUB+E+WllOVeauegL/xV3lFK93spywr9fFeyAnYizgiKML448lKOXwNz0e8iUUZIUEh6Yr4z+HX6YPY95RClnhPIoZRKqbLk9UI9kvIwyMlMIQeXDBYW0HsZmEBa8AUPyLhFVvQ8Yb/uHl19rLz0FIK5kY64sYlm/2UmXc+8CZTt3rEQ7Bjxrt1SZ7M3PMBoi+mY5pD6TzZ/JxqtLPnE7/I9tzSM8NmpLZLVdZ09kXadV8vWpGAUQp+eeMX2Sov0MRqn6qpG+ZCzPVNum0y9a7wtJEcm7yfXo0bSTzFhkdPlPCLbMRIGhM5Sp3y3u91t9Qluqwl/9z4Z+oW3E07yeL3udSzNPDwMPox6VvrNBkuC/0IKns7Tav8f/Rw8MMulf5t4rfUd1dfbbEb9IhbbW9l+KweAM8OXxz8TJVdN7S1WrznrCI14mHZvYo3SuDFg7psuLyBmu1qpRyEqzh+ka0zmx4JfkTPoo6Onk/eYKoUMV405i05sJdotMbNrSpYL9u4n6hq5vPK3SrXxcw8P5HnJOpzGF28LF02nnPILnBYEWSfi6wIenNPaF6Mwwtm2JLpTHgupv0+0c7yejLe7xTFftVfpDKBpTBFrwS9Xlkb6vUkME+UtfPKDorZhGFWGBKnNZhGT4Q84YliPVYG7zSgtj6EEeNgo0Nwwl3VY2VntaDkW9fo7aPvYPevW7Qz+QAtPDZLFaUrij7FND8oip+9S2kv/l+GP9BZvdf+dp1ZcZMXWRgR5UWWPG0c8Mr/GV6A0qK1e0VXRvZ/4rBPpDYH1b2LJbevEsD7nH/J/w5+rnUI8+l9VVFchzfTt6JGY27kkxRVJMrnbsA/lzfSp/U/o+dC+1JRLEjxBTl74yypoTInjfF1pk6anTej2c0FVjAG5M3W52qr3zw6JlsvsjxX18bfYjZ642yHE37p+uCYNtrBL7KeHO3g5rL/2mqBWX/55BdZNWSOF9mVtadmg0DWLi1dML0F3f5F1r5kbzO1ry9Xztk5yF/Hsdl4eK5UL5V6j4BfKIovhQ2m2GtHbSgFO/jPbJMhF0/6VHw2F2vPvOpptayLeTLPnTM5ihcopu1dbVdd29ItVIyvM7Vrdt48bQkrwayVmI9QJW+23wdaLS+y2b8J8iKbfYYeL6ERxuEXHyYKruDxoqXA3CfgF0PPuY9RWiAETAR+wbD4MtvV3qbU7AeXY17gtpTsl+NOCYOwUOq9CeyozJ2rJC8IDDz0qsMX2Sm1vhE+fkKA55A+sf+5dL3hF9kh2L41T4qrQ88tsOhiIRYmlS2fJ7spjc6cgCiKmTOSHELAtwi8NYho1Cc516bpWIDwuG9bwXMOhtQkBPIJAVcUxXujieb9jS1ay+QTKPmzm34x9Jw/b530Wgh4mUAoyl+0iahBYy9XJMULASGQ5wh0vB3LvpfDJRuWzYv4NYECft076ZwQEAJZI/DQnUS7TomSmDV6cpUQ8G8CD8NN0M+YryxKon/fZ0vv/MKimJgMlwt2jqELYklmBObXsrCnyB0XiU5eI7oNFvKQDKZZHbtKtB/+wxpiYVuwk3wJqO+6pb6KRYiKZuBnc+0ZbD+Hsopng/QN1LUDW1k2MrlXOoA2FoGaH4b6j6E9ZuHVqCWx6rsMPgWcLE3dCx4p4NLAsoDvzHVsHYS4FphmUjALrw+X4OrnjGXaXAn01Rm7y8i38bzW7tpYtehIbqFd29HfZPjkbYL7FWTim4R7eBXxZuEuRspLrRlJ9sJj36C0IW9RQCYOZLNXSf65+mTqSTwv8B/MJIFwTK9vo8eubHcn76aklCSKgeP54ELBppy2Qd4b/sC1A1S/WH21HahtqnaWmJKI/9vaf8YQbHNXtAAeEiaJTzkB/666E0VrQtGAok59l1pzpQ+x79k9aH9Mcbj8ssiha4extV5hCoV/2PiUeD3a4TG0UJjyBck+HlPSUqlesXoqH/te3Ju8j5qWaJrpzkyOCk7BRgaJ8InLApfKDleLM3tu6/GUo1S1SDWqUtj5Qi1n7JNvJdOpVLxU2Ykj9nZZ8ubpkx2Jvp2LB7O9F/W82R1pdeYEsqG+ZF54TuUIW4iaoFjYCJS8Wz2Jxh0gGrIZKVCsDKmETQHutVVm4q7AP+hy5Eg0clHtakRrYVgpY/f/odKvyAOlimViG6Lnkc9eWDnti3q/24oUKDrRkURzbidyphzZX6+fTzlK1Gu1VsZl+KM9CkU2ehXOTxL9hv+vrK9WnaHntjuyggU/3l/VIXquqjVt4iGi/su08/ZIm9CQqOY8nPNvGRTH8w/iYNdn69WOQ4N24NmxRUurGAWMbW3zsbLbG6OYU5EPzhA1KUX0N+5DSyinusw6TtR9Bc6gECopgOl4zYlGYioMS8U/8WW6RyoSX9d72yqUerwc3SSweD7RfZ3F9Y2b2DLKHroeY/h4vtgIXuJutb5FExIm0ksHBlj/3jlT+Wg6g205ze5rjl4/SpHbWxGdizOKaRTWjv6qO5vKFMTblEnC1ocZTq2/bfgdPVvxGVMqXqDXhxvp5oQGYW1pW8xSc1Sm4ZmnZtHju7uzJkZX7rwChesY1d7ZAQ+ROFpy+xJKK3aLIlfg4ZeBbGyxkbZe3UZ9t/VRubpUfoLGVX2Hqq/BgxUvloSXwPPNz5MjtzQZFEvbUGazf5oaWZLbXlOuefSIlRdWUitmmqzH4AhvYItjFtN9Ze4zIjNj/3nCFzRs1xAjvx5wxF5Py7PHvvgRmjgD1gS/UB3y7G3I6YbjZ9hPBQ+ug3g4D1mJ/pmVRO7uCVgV/7L2OxVKTFVepGqngOyDQlXWlM96ReahB/6xKImcFRawMPww1MADzx1hpanXElyBB1kslEK2sEUvwDna+dYdRA/g9ydDYcsb+vpv9KElOLDyyvJJnDqor8V7ib4+jKBu8IDC/RWfuyk3LWU7u+xpVhK3I9WcD8r2negPW3FZluOlvPsiBK6pU+0L9+bNNUQfx1ri/Pcv1tTpXAiye4vDeKuCkiiSAwTwfDp8PU5zbG/+e+eqz+ym8tvvMRrBlrHIDZE2SiInbklYSmV3tDHy5XRg7pl59PiW7urZcaDpQYzqJFPtdXVUO9+v+wG1K9vO5SZ9ljTNyPvLsen0Q9IUTUnkWDzHv0/6wUj3VODAtYO2SiIXjGdt+43tia2bLL7KXjUup78G9qK0L2eKkpjT3H2gPr/72U3oAV0EL6ZpPa1bcxIsVo/FgDasZYZgROJ8inb2MT8TLBZC3pO0f2Oc40GuBKMmvyGvOzIWytcifHRpW5toyZ0wLLpJu/tOSwmBeBZDYZqA55quRBXS26dXYjlyXd/cS/QyrJfmfZ/XQNEavkvLNCgKR9P1jdggYfKrfcL+h0u7LMvfR/Cgn6b3BaXcj98SKmcpDsps/61auM1GSxwfQqBE1rSeD0HaNeRNe8Byf9n4YGqzNaeE3CbQ71GYdqGlR1V3+1K5wD0CvDNLWvs0Smudhq2DLf8JSwVRr6rPKcuZURqURXa5wvJF4hdWCyAMOYNrDbP+/8V+yUvOLzEucytQhIi3qdM/70UMduvybkdGavnxfEpJu07fnPwOAUuUkz3f/1X5MZreaIbNp06xOvRyBTywTc+kBhhaN+8PnYBheU9Ldew49UbtNyn2nv00p8kca/F41v4MJZjFFfZDw1/V7inu6xNRz1jL8afQf/pR2n8nyXQUf7qnbvTFTdXFjZJ9IGsxPMD6NsKWphhKndmMaKv5BReWrSMWS9b/YHXTpX01KGS4hkL1GCzsMqVbYx2HTsEy99p627Q6JYiW4jnHc+/cErzdKoGCVH8hLG8mBW74P5oFzr68VlCK+1SF1RDDyce6IBXDu7q8tx0v6XgI8lB5OyiUSqAYd8ZI1cy79VxEdwVbw54ILeJnPOpVUhiKd0uid1hZtMivUMZZCWTrpy7zoOj+1FQ/wxH3aov2u2mKlGC2CXw7ntImwkpQtFi2i5IC3CNQNLAovVRjMN1ofpW+r/kV7bhth00Bx69jSAHy1WlNaeFwl7An6OOo9/GiVYtPlcw786sedO9YuCQNDR+i9jPmPY07lu3o3vXC9ZM8AABAAElEQVTXLe3F/93oDdF0FHMfdRmyazCtvrhaPzWOrUo1o8dDutt8imNPeh4e7xwB6yQLlOEOZTvQnBir8tailPlhoGXL7ner0q1pdORbVKNITbq7FB6AqFeXkIJ4kEK8xl6vKC8c3xxMae9NpADseSySPwn49Z0PhcXpa1gHdUtelPm3EG+v+nzBONP8xiYWq2OMKe/6i67/cYzag7yptvknYNi1PZ7lzVZiFFpXmGyzODzrGWGKhgLaDQqdWU4jLiPhxTyPYMTKECie+y4R8XzMpfwbBAaftcCLO/4K3j6o5YquRvRwuHGFRwK8SMYQ8OUFNuEmvrwd1x5zHmSuBwW3AiweZivDXuQT8RABvCDQhr+Jnn1R9mv2EFJ3i+Gt8T6r9jEFBuCNFmKzNR/+j7ACw7LnynJ15K9GxaNVuFlh/Ee1yLpkfuhkQS5cogJLYdfcUJU+OzHe7QL6hvS3XoNnXpdyHa3nCJ1JPWNzzic8ly/gTywt0T/L0FEIzwNccBovLJD/RX9FBQMK0diEL9V5k0r30YPl8LbvJekd249CVofAomCpAC/2PdjCCfEae0tVPn94fwSlvfmRPCN8/kZ5t4FQEfKPTIqz9vUuPIOLaM9n67AOkvUh3XKmt8vdJkuetQTHoQnWl2otg0kh2oQpYONiHV/nKPZDjL50qosUKE3v3IG37FDMTYRix0PoLdD+TnaKo6My7ixjG8srpF/YRtQc1/7ViWDRIPrhCDyhoI8f30O0s7Vtfk+cxaFOQ7TfBeKV0YbA0rrvsnGmAnwf1Ipt018or1oX8QCB+2EyP55IdDtMuyI+Q2DqqelGW9pFPGRdeHHdiKYgKFAs5QpAm7HIJpMlT49z+cijHOfi6OWdA+mto6Ndvowzjq4yAi+iT6kpLh/VHUdtS7dVw9i8+OTeiC50f5kOjsuDBZLnbauPRTkbfPh1al3+QVp5x0r6d+hzNBNK4/rUJPo85gvaUG+R43I8FPv9+T9sXu4fKPsoFQ7gNymIN9lrNfjud6M7oNm/LUqi796hHGuZ+ec6xyrNjYpYyRi00VIzngHTmphawYtMLErIScscm9P62yWSeJ6/y2IaHn2zBRS7aCzQWI8tcndoJUyGIjlUH/bNpNAwWEQX2P2Wv4ny+OOqJFn6o+evjr7+blcmD1Xzx1tSs5ipZMuD95KJL1sNY6AMm+U02l2Zr+MfFIvYWCH1SDm6R2Dky0QjPpIJ6e5R83ruJChFA/a/oNWDp/L31UwWviJ4YKVo/5GTbpxWec7esprgWxY2Dxtk3tQptX+kYAytsgudLgfx9wBFkWXU4ZH0FpQ/VyU0KJRm1/4BQzP4WISHsPljiPn/OSLLV2hOz5RuYyQXs7ju+anOj0YcB56q8KT62ER66WR5re+hmM6hiQc15r8fm02zgx+h7iGPwZrgWfZe6oJ3ipXtOr3DNQ+Wmi8UxRQoG6F/4e5YLFtTW1mUEMsNi4aFbrdllOSgZd7iLgzP6tKkpB5y4cgKj6Ue9rHIEmE5cni3RXGbcQyrsmFF64VnvFKIONHDwv4e39ttKhSKZy03+uKpNkablUDw5dXXR0182WKq2gWFUV8VzZbPipjPaJa6ViOKOdom7Kk22xTqLye8B/WDj/pLb/ymH9dvpVDF7Xcb1qvZDWZTpcLW+R9NSrSiTReXqP4evIYHB2Q9r9i1SJOidfRgpscVF5ZTGyhqug/HefjP2HVTV+06vMSdxXAxu+WZA8Xp0PU46hHc3aYtmVaQSYb/hDyKeZGvZpLLebIn27Xjynb4o4whnqvIn4kXV8Fv2lZV+ZyzC5Wi6An2O6/spHln51O7MvfSHSVhpRMRAnmMQL5QFNv+g7uSYL0zr+wn4k8QFJOj9xINhLL2/CEtfSmev92YSqI1/9NVrOHMQj0qwlp5UsvVfzWsfyj3lPZsV5F9QzT3M/3+0vK8sRMLrvGcZgfZnpCRR4gOQAn7gdvAHyhlunSppocyP7KLHE+18V+hqI/7l4oPFOUWeB6vM/HtFYXkApi3iPsQH4c8kIdg/S1sUrB5uJ2dpWcknmxzRvXkubRaaPGCXdDG3TBF57lO5t0Gd9r3OCb04YFkkaHxnxB/CgQUoNiY5TQgpAc9e0JTFBckzKQnsfiDzloVxR5QvlyV8Qnf0M/xU6lVaGdqUbwh5gGOsV6KFzNWEicnfU/PbO2t4ocWe5UutrhEJQNdeEuzluQ09MXpuemcjz+O9uvzMZ1eiARPt6t/3Ou0+uouGhf+Ml25iTfYM5qSyG0oAmfhLNllz4p3zLoYNf9xBMpb3MzWR6OqRL6EgI8TwM+zf8vzW4hWW5/BqrOnoEzxh5US9v+nnFFDgVMCZWYulDddYqq7twr4o/q4EkqNEpTF9RgrfjGUOrYe0ebzlnQ+YARpSZLpPLvBeCiJmIOoFF30zZBKGP5uapxlGvBkG3lRypDbrFWui0X4kuUcz+OP8Rxl+bUJvvS/yFMwsJgU7Mloe2Y7xniyzapB/vD11L+waAV/cKIk+uTdHHR4KC09NtembXEn/yb+HEpcRTfSbtLTFXrhmVJSy4Oh3Klx3xn5m1Xq4L6V6ibRivgFNHY/lET9/yFKHFblNVXuNljADIH+tPzCMuM0uwHu14g9w20+Gy9tdqlYr7TrXBwN3jlItcd4TqM1z1boodqUXfZH+SFmGn7/b8LXLvVVMgkBXyKg/yz7Ups81pZJcVhBl8kzKAC18aKJcx2wKrkGTgIt1WNqSo8GRJvusZybD3yRRdSCC/0ER55XGIuy6kHBJChISkC5ShQc7D6IOTpQjAZyWhktib9TblnD7obYKupU0Af2Iflac/wetHNv55LstLGogzZ9CJZjWqI94KOE84SDVVfrDjlsMfwHjLjNhpTCD+N9RE9HGjFOA9lps9NC83LC52Mp7fsFWAylv7nk5c74X9unnZpGn8R+lGHH2NciWxbPNTlKrcI7W1+kCkKZqfYCrYqen/560/8/vtYs70WOpM6Vu9u4guHFJ8Nrj6T3q76rsvYL7UNkMiCmwuF3VqVQgcyHSgKNt8OMa3G3XYXM/m5QdECACQzOB3M/g/GWakaEl3n288hD0Sxus1dXWb8awmp7Vzhe1ixy3bK1on4uRyGQFwgEYK9Ls90pL7Q5XRsDfkKUxcUNO9xmtzhZFd5qLj4Zih0eGHbPFbeLVHPx8EYegfboLnr0QgbC6jd+I87wHE3AyFF22qyX6emjt9p4HExYYc5oj+wLKZqTceUix0nHAqYhAfeK5XpvTRH2VptVJb7y9dYgrDz4JOPWrPoTpvB7M84jqTlCIOBvKChXtKrY4Ta7xcmq8L7KCdi/OCIoIp3i426ZPCx6M+2Ww/2d/4NVyB/EvqdenBPvyV6b3W1XRvm90S7+CUxMTVRuiipgb2xn4gr7Hvufpelxk1QR+hZ+uzC8XX91fRX3dYOvqW9oX2dVSLwQ8EkCeC/1L/nPLmy7B+WrJHo2up77fePhzUi8YXtCWNF0VNbW81AS96IGtHNSK99UEr3ZRvbvmJk422ua96lmX5BKoEyaxZttNtfj0+G7Ya6esZyoUoRPNzO/Nu7No2OoTGApKoU5f69X1oZ63WFRsEBBW3+L7lxsl9e8l7Q5aeeVHfTBMU1JnNZgWrYUW3O52Q17q11saQwLCsu0ec7Yb7q0iWafmaOun36OrRZWuYq5j90PvqQiHqj8KPWpCCumiBDIYwT8TlFU8/P4JsBilRVFMSfu35qzGA6GEts3iqhaiZyo0f06fLWN/fegL4mO++OrbXbcWi/EDnkO4/vj8bePP34RnyTwv4Ofa+3CS2JWFMWc6NS6yxvorajRmBv5JEUVicqJKl2qw1fb9SfmcL6/Xxu2t+/IoWuHqF5QZfqo6e9qtxn7dDkXAnmBgF8oin2rYa4bhjPNEowHsa/KC2ivr4uvtnFoFbgGsZtyByMwho3gSDwPcPXafZ+J4a7HenuteCk46wReChtMsdeO2hQQXNDuj9gmNXdP+lR8Nncb4KR2X21Xg+L1qUPEI+laXRdui+ojbWbt79OlSYQQyEsE/GKOYl4CLm0VAtkmYJ6jiAVB9PtmeCxvlO1ipQAhIASEgBAQAvYE2BgjIgSEQF4k0O0eoh2nRUnMi/dO2iwEhIAQyCMERFHMIzdKmikEDAIBgUQfjKC02cuwcsvsS8jIIQEhIASEgBAQAh4h4BdDzydTT6bz9h8YUNDYpordH+xO3k1JKUkUUzyGggsFO4V34no8Hbh2AFs71Ve7FDjKmJiSqPZJ5bQQuFMoatmvVM8bn3ICbidMXlYtCUUDijp0RaFf5+zIbhn2oP0xxRsYWQ5dO0yFsXtAKFxtxKfEG/GOAqGFwigI/sxik/ej3alUr5i2HPxc6lnam7yPmpZoCmfW7k9XTYF/tUS46mAJwL/KhSunqz751jU6mBxLZ2+cpduKN6ZSBUumy6NHOGN/KuUUJadZ/OBYMjurTy/Lr4/nsRqqTDm/7mJudk7+3nKTvtQtBISArxHwC0XR7KfMAIzFLLda36IJCRPppQMDiK4ZKXDiF01nGqy0UQSPXj9Kkdvhq+ZcnJGxUVg7+qvubCpTEJ6gTRKwGisnLItndF9ZpmQyp5vjG4S1pW0xS81RmYZnnppFj+/uzpoYXbnzCh1POUa1d8Kj9/k4WnL7EqpTrA5VXpFeQTMXvLHFRtp6dRv13aa5ZuhS+QkaV/Udqr6mmratHtwBnW9+nkq7OcF+w+WN1OyfpkZVyW2vUZFA64rb1+JG0NiDY7D9jZEFDm7rUVL9ZTYKc2bsAzainWcPmwrRgtfaXYeyzF7FRYSA5wjI35vnWEpJQkAI5H0C/jv0DMXq8PU4emmnnZLI9+zMbiq/HfO7LMKWscgNkTZKIidtSVhKZXe00bPl+HHumXn0+BYoidexf3PTg3TtVjLVXldHtfP9uh9Qu7LtXG7TZ0nsnVqTX45Npx+SpmhKIkfBGfD3ST9YUj13mHVxha2SyEWf3kUVtjU2KnGJPSyxIkIgxwjI31uOoZaKhIAQ8H0C7o83+nifzDsfxF2L01pbKoh6lX8ayhH22YRSpATK4vkb55W18IvELwwLIe/6NLjaMBoX+wFRGnKe2kpLzi+h+8rcZ7nQjUMRoveroRyL1C+uDfnq55kdux0ZqWXBlLSUtOv0zcnvELBEYWjdkfyr8mP0ZHA3myS2Or5coSf1ScRuHdwnSAMMrRMb4yzlJWBY3tPSo/S9VC9sAPaibU5vHB1t3aP23HE6fv04RRSOIFfYpzXZZTQtYDneAOwcbRuJEhACHiAgf28egChFCAEh4DcE/NeiiFtUNLAovVRjMN1ofpW+r/kV7bhth82NY2WF5avT84z4LmFP0MdR7xOVq2XEzTvzqxF2K1C4JA0NH0LDIoaqT8eyHd26nK5b2ouh2+gN0XQUcx91GbJrMK2+uFo/NY6tSjWjx0O623yKBxanZys+Q50jYJ1kgY7ZoWwHmhMzRzvHd4tS1iFkIzKbgdGRb6l2sNPe9mVa2ZRW2jKc7zX2NrXJiRAQAkJACAgBIZAVAn6tKPKeqp9V+1jt4clwbBZbwDBVo0hNxWzPleXqyF+NikercLPC1Yy4dcl7jLBbgQuXqMDSAhSwoSp9dmK8W5dy5r4h/a3XpBJ1KWeraJ7BXq32MmzXEAr4E0s99M8ydBTC8wAXnJ6pwv+L/ooKBhSisQlfqvMmle6jB8s9qMKe/uIFMwEbKtPT2542iu5X/UUqiS3MWLzG3qhNAkJACAgBISAEhEBWCfi1omgPZeqp6UZUu4iHrAsvMAdQlyAoUCzlClj31ttksuTp+Vw+8lAvFsi8vHMgvYXhV3dkdJUR9EjkU0TFiD6qO47alm5L70d/QITFJ/dGdKH7y2BRiyPhxSP6x7L4evDh16l1+Qdp5R0r6d+hz9FMKI3rU5Po85gvaEO9RY5K8UjclVtY9YOhZn3ImwvtWNY0jO9N9h7pgRQiBISAEBACQiD/EsAgZP6QJChFA/a/oHUWvf6+msnCVwST9VK0iW9JN+DAGHL21kUtL75bFo40wq4EptT+kYILllcudLocfNlYJDPq8Eh6C8qfqxIaFEqza/9AxB+L6MPY+jnZeeEpX6E5PVO6jZFczOK656c6PxpxHHgK+7jyx9tSAVbdH26bQn3jP6WUUxtVdV22dKGrbZI1t0IeZu/t/kj5QkAICAEhIATyE4F8oShev5VCFbffrVYP882d3WA2VSrMe59p0qREK9p0cYk6OXjtmDquv3bQkkrUBHt2uiorLiynNlDUwoMqqUvmwYdj101dtcthPTuL4eJyhcrTnNNz6BBWZfcI7m7TFlfrcZbvPyGPYl7kq86SM433ZLt2Xtmp9jplhbRzuU5U9q+yWv2wdv59YbVate0J9lzPvLPzqV2Ze7Fw5o5M+ygZhEB2CKxfv56OHDlCHTp0oJIlnfsFzU4dcq0QEAJCwFcI5AtFsdO+x+ESZ7/BfGj8J8SfAgEFKDZmOQ0I6UHPntAUxQUJM+lJLP6gs1ZFsQeUL1dlfMI39HP8VGoV2plaFG+IeYBjrJfCxSAriZOTvqdntvZW8UOLvUoXW1wy5uxZM2ct9MXpuemcjz+O9uvzMTMq1dPtilkTQ/8Kf4weKnc/zThruyCosMXfYnbZs+Idsy6G2LI6Ap1b3Gxx1laoZwRG0oSAhcDixYuVgshO/Bs3bkxr166lQoW06SoCSQgIASHgjwT8XlEcdHgoLT021+bexZ382zi/Uf8mPV2hFz1beiARFp+wwjE1Dm5oLNKsUgf3rVSwmK2IX0AraIFejDoOq/KaOm6DBcwQTOFbfmEZLG6djajsBLhvI0z947JqFKnukqLo8XZhfubCY7PUx6ZPmHPZtHgzFZVd9kevwwJsGn7/b8LXoijawJYTTxLYvHkzsZLIwuENGzZQy5YtPVmFlCUEhIAQ8CkCfr2YZdqpafRJ7EcZAseaZGVZPNfkKLUKh7KmE4EK/Wy1F2hV9Pz012sLiVU8WyXN8l7kSOpcGW5ozCo4DJTDa4+k96u+q7L2C+1DZF0rQ6lw+J1VKYSt+TKTQKNTGed0t12FbDqJzWMCTGBQ1Ss1htj0k2svXqEpxd6+31hIxPzcYm/XhYaw2t4V/i8j9nqaNtfUiJCAEPAggccff5waNGhglHj58mUjLAEhIASEgD8S8Lst/MwOt7Nyw3hf5QTsXxwRFJFO8XG3PB4WvZl2y2a7Or2M/2AV8gex7xEFEiXek0jsyscXxBvt4jmiCVg5XgH7YhcLhDnRibjC3uxwW9/Cb9fVXVR/dX1V6tcNvqa+oX2d1CDRQsA9Ao7+3j799FN65ZVXqGzZsnTo0CEqU8Z2i0/3apDcQkAICAHfJmC2e/l2S11s3ZtHx1CZwFJUCn76Xq+sDfW6eKnKVrBAQVt/i+5cbJeX5yM6kp1XdtAHxzQlcVqDaT6jJHqrXbwfMzvdzkycsf8WO9LEJlvmjJqGmbm8qzevUveDL6miH6j8KPWpCGutiBDIBoGM/t7i4+Pp66+/VotYvv/+e1ESs8FZLhUCQiBvEPA7i6KBHSOyaW20uURGnI8E+Ifo+PUTmBv5pEsKVE4121fbFbCxGhYXHU6HgS2Kscn7afTxD+mZCk+o3WbSZZIIIeAmgYz+3ubNnkusLD722GMUERHhZsmSXQgIASGQ9wj4haI48NCrFHvtqA394IKlaUqtb2zi5CRvEnjzyChab14AhG7wfMgFdaYbu+7kzZ5Jq32RgPy9+eJdkTYJASGQWwT8QlHMLXhSrxAQAkJACAgBISAE/JmA7ZJdf+6p9E0ICAEhIASEgBAQAkLALQKiKLqFSzILASEgBISAEBACQiD/EPC7Vc/559ZJT4WAEPA2gTNnztCpU6eoevXqGe7AwnmuXbtGlStXdtqkFOwnf/MmvPFDChcuTAUKOH5Pv3XrFp04cSLLi2XOw5XoeQeuWUOLEPyXOm2eJAgBISAEHBJw/KRymNV3IxOTieKu2H6OY8cTXXgjhe0XiJacJDqF/ZYzkmO47s8kotMZ5Esw1ZesPfedFrn2DNEVO5cuTjM7Sbhxi2jLOdvEA/Dzy328iTT7vpvPj1o4cBmrT9v2f/dFol3gklXh+pkVl5ORuML0Fu7R1vNEa8ArxY6puT96OKP7k1FbJE0IuEJg4cKF1LRpUwoODqa6detS6dKlqWfPnkoZNF/PO7NER0dThQoVqEqVKhQWFkZz5swxZzHCTZo0oWLFiqnPvHnzjHhz4MqVK9StWzelcHL9//3vf83JLoX/g42fqs5I/1mK/6siQkAICAF3CfiFRTFsIbptr/BgX+VbPYnGHSAashnp5g0UKkFhupcoGHl0YQWk6nKcJeoxRLWrEa29k6hMkDWOQ5V+xZdFOZrYhuh55LMXVk77ot7vtiIFb/HRkURzbkeZJe1zZnw+5ShRr9VaGZcfJmLFL3oVzqH0/tYRfUSQfxScCqwIaeAQsQyXxCEXNk/56X6iIyjn1ZXaVV3hq3puc6clpEv4B8rcnesQnWBKKop9ltsS3WfyG+4q01nHibqvQFnXLOUVIBqF9oyMRhVQyh31LzwKijLqExECniZw+vRp6tSpk02xycnJNG3aNLpx4wbNnDlTpe3bt4/uuusuYkuhLomJifTwww8TK4JdunTRo106ch333nsvrV+/XuXfvXs31apVy6VrXclUCP+vRISAEBAC7hLw30cHFKKDUP6GsDJkVhKZ0AmikL+sqFKhbVX9DecmJZFT9x0iKmvKZ70i89AD/1iURM4KC1kY/DrWwFZ+7ggrUL2W4AooS7FQCtl6Gc3bR6Odb91B9ECoa6WxhU4piZwdCuwjUF5HH7FeO29nxhZUa04tdCf6ZqMkcjTa2B4Mj4A5i6tMl5+CkrgIF+hKIl+M+/HmGqKPY4EO7RURAjlJQN/LmS2Ar776KtWpU8eo/tdffzUUwxEjRhhh3u/5ueeeM/K9/vrrxEPI7ghfryuJQUFBStn817+s21NyWRcuXKC///5bKayulP1OS/yX76N97q/oyhWSRwgIASFgS8DvFMWEHpYHI6xoRuewQcpjMeh4aVPnYQ3juTwsH+/Hlz58GkTUvzHOoWgqiYflzmw5s0RndBi7l2gRPrq0rY1h7zthWDQapKdkfOwOBU5JINF1/OZMOIgzi0JVSG+fJYt+4Lq+b2f9zGlNFITra1XVc+CIMkZF4Wgq46SlXMS6JrBU3o/fz8KVTdnRxl8srFxl2maj6foQWCprWs+HII2tvvoP3R+2Rh5rRgkJAQ8SKFSoEI0aNYp4WPmjjz6i33//3Sj96tWrlJCQQKxMstKoy/vvv0/jxo3TT4mtgQcOYDjDRfnjjz9o6tSpRm4e7uZ9pHmOpC5cXqVKlZQVk/ecFhECQkAI5AQBN1WXnGiS5+ooBgWpbyOiGw8SzWyGOXBQoAyBpYqHX1n+BwujLu2rQSHDNRSqxxDNNqVbYx2HeA7ka9rIkZGhTgkinh/E8/DcEljplMAiWH8h0TGTMjccVj22xtlLKyjFvSKtn4fCtRx72+AIJZilUTDRwBpELfBRAmWsJtroqgyAcnj0IaI/oPxea4+rylqvjL2shV1heg39YuuuLvNux7B4U/0MR9yfLZi3KCIEcpIA7908cuRIYqfuLOHh4VSwYEEVLl68uJo/yMoiDxXrUrt2bSpRogRxui4HDx7Ug5ke33nnHZs827ZtU3MVIyMjadmyZSpt/vz5xIoqy6JFbIYXEQJCQAh4n4BfK4qhmDf3NayDuiUvqpgJKH4D9PmCcRes8U0sVscYU971urXRms1paNQeJKXaJk/YhGFZGB+ardQWn9imOj/rGWFKgwLaLcx0jqCjBR0jUVfAz6YPFEyWH47iiy2o6NcsMOHFMGtgLWWr4pctNasjzlySz28jqmziQ9bfRmpURivCFabcBrPUK0VUAZZKs6Vz7yVzDgkLgZwn8NtvvxlDvU899ZRarcyrks3CVkiWkiVLGtEnT540whkFWPnj4WRdihQpohbH8DkvbuH5kpync+fORvncDhEhIASEQE4Q8GtF0R7gpDhrzF01Ta4iLJZFTtWHdMtpBgR1wW6TJc9aguPQBNvfD6WY6Tk3YSRqXKx+lvnxw/pEneoiHxSod+4g6hCKuYktcA5ltgXa38lOcVQlQqEktsKZPrzquvdGIl60kghLYA38lvWEQhlVEVbJzkT9qqkrs/TFK84NqyAsk9115dYFpvF2XJl9ATbimP4q3R4Sz1Iv5CIh4JgAK2jDhg1TiSEhIfT222+rMA8Bm+Xs2bPq9NIl65tNaCj+w7og+/fvV0PZnJWVxEOHDin3OPrcSG7D6tWrqWbNmmqf6e3bt9MXX3zhQsmSRQgIASGQfQImdSj7hflyCaxwDIKypCSIaFoTU2vZImZRWk6y1Q1yGsqVLo3M1jM90tmRFTSLvAml7q1oKE/rYcXboUVOhiI5tLaeI+NjGCyiC2DtM8ubKI8/TgXKX3vTUHAw+locdzntYdsr1rWyPc/q2QPrcKVlzv549JfrUuIC00j0zyynwV5ZKnlI2iLhxfSQHIVAzhLgeYi9e/cmVuR4GHrKlCnEyiILu8FhVzesxLEkJSVRxYoVlQVQReCLfS+6IhER+tuVpiiWL1+eAgMDlR/FvXv3qiLYTyML17Nz507liodd9ogIASEgBLxNQP9Z93Y9uVo+r/oN/QtNYOsXZCqUJPPQaTSet7vPaGkHLZawXVe0c/5uAgucywLrn15PRR5GhURYjhzebVFEZxzDqmwMvfJ8QnNbOE925G38No1gK2QW5ALaNvEQWEGB64HfLl4Ek5GM2IV5n5ZpWM1qEL1o+l10hWn1EiidLYhpWi3HcH8qwipplrqcJxPxFstMqpVkPycwfPhwmj17tupl2bJllVscdo3D8xW/+uor5f5m+vTpKp3nNPJcRl3q16/vsqLIvhp5jiO72zl//jy1atWKeG7i0qVL9eLo9ttvpy1bthCvxGYFlt3yrFq1ykiXgBAQAkLAWwRMg3zeqiL3y237D9qQYG3HK/sxFw7P4Ig/tQUmA6Gs6bIUik83tpIl6jFET1exhjML9YBFT5f+q7V6xmGYV5e+MEh8dZjoicVEb6BdVRYSXbKb06jnzenjbWjva5gq9QzYPLYh49qnHyMas9aaZz0UbGbKn6UnsVjGBabs1y3clO8hWHxroA2GQIG/zTLn0YizC/gqS7tmymkeI8CK4HvvvWe0moeWJ02apD6TJ09W8aNHj6aiRfFWBVmyZAnp8Wx9HDt2rNOdV9QFdl+ff/45sUsclrVr1xq+Gvn8+eefV4rkihUrjCHqrVu3GmHOIyIEhIAQ8BYBv1cUn9+CHUmgGJrl1BE43MYnPk7z0/dcVaRCgVMCpW3uTksYhxhYye4Ktp5nFvqoPnLoI0Ioi+vRh2Z5IcnYekSbTcPT7JZnSVJmpeZMepw2zUpV9guYsdNwR7ICo2A9oGTbyAmtr9zfQ1AaXWX6K08B0P8KUe51KKC6TG5KVFBP0yPtjr7K0q6ZcpqHCLDS98ILLzhtsb4amoeW161bp3Zw0bfjq1GjBvGuLvb+D7kw/Tr7MJ+3a9dO7ehyLxxu8zxFFt7thZXV8ePHq/Pu3bureYps0Rw0aJBNeSqDfAkBISAEvECgoBfK9JkiJ8XB9c3mjJsTgGReQHGuA/wCriFaD2sfO8hmVzI96hBNZkXGXvgii6jFF/oJjjyvMBZldYV1bFc8InjuI5Qd7O5FK+4gKl8Y1jYon//DEK9acIJDyi18ZVGCTG3JYhHGZewWaMAqnHL/+eNAktCf1n8gwUk6XxKIj6tM2WL4z4NELbley/A/L96Z2hz8XbDkepIlt11ECNx3333GnsyZ0YiJiVFOstnnIe/QUq5cOaeX8CKUjISVS/7wntEXL140Vj7r1/C8SH14mofCRYSAEBACOUEgAPNdnNiNcqJ6z9QR8BPKuaCVxQ63eY5dVoX3RI7HXLkqsP5Z3KhltShlkeMt9yLQHt1Fj17YwG1E46FMUiGMij+avTbrZXriGDAXpcCyWAZDwufaeaJE+LF0kSnPkWTH4spFjoOqF53Eyu9ftYTwKOsWfr7K0kEXJEoIeJ1AP7wcf4WRFBb+f/y0ZbSEX6qqldDi5VsICAEh4CoBv7Mo/mcX/D9D+SqJno3GMK+7wkOdkcXdvcpxflY0HZW1FUPP4/fiGrRzUivfURJ5yzxWEtmB9gZYPz0lrjItrU3RsqmWty18HVMB+G1m5yWbJHXiqyzTt1RihEDOEzh/hOhTfFjaVRBFUSMh3y4RSMCQWAms5CyJIR6RfE3A7xTFH2CpU4Ih3qwoijnx17AGythrUGL7RvnWg3s12vXBXRh+huWhmI/8ZZyBX8hP2PLqRHyVpZPmSrQQ8DqBNrAg7qudvhqbDQfSJ0uMELAlcOQA0f89RzR/HXz5wnogkm8J+MXQ83ObMS8QQ7xmCYa17ifMcxPJ2wR4P+6u69P34b7yRMPrpo+XGCEgBISAEPAAgbUrsLNDa2wphjeP3zBUVx5HkXxJwC8UxXx556TTQkAICAEhIAS8RUBXFLn8BvgsScAE8lBv1Sbl+jCBTJyP+HDLpWlCQAgIASEgBISA9wnwgv0WYVjpecz7dUkNPkdAFEWfuyXSICEgBISAEBACPkbgENpzexWio4d9rGHSHG8TyJUlC6mpqXTjxg2bvrEzWt3RrE2CnAgBISAE8jCBRLjbuga3T2YpCI8IEXDBxcIOynbA8T7vR89+RUOwEM+ZHMNc7P2XiRrCqX+wk3wJqI/dTLHwNqJFA7Wwo++18F0ag7KMPdodZcokjt1f7bhA1Mi03uEA2lgEZogw1M9bc5oFXaeSmENeBh97P7R6vr3gkQIuDdA2Fl7UthtxLTA3OTMn/NoVtt+paCO7PWPh+h15o+C0y9gkYSO8UnC7a2PBrzNxdh/Yz+xVOx+zGdXnrHyfjU9Ey6KrEW3fi5WYDlZM+WzDpWHZIZArimKnTp1o8eLFNu0ODAxMpzzaZJATISAEhEAeJBC2EI2GImUjUPJu9SQah4WlQ7AYj6BYGVIJuxzda6sIxl0hqrocOfiH2iK18Xu99k4oXHZupSr9igxQqlgmtsEWgMhnL6yc9kW9321FChTJ6EiiObdnrBzZl8HnU45iv/rVWhmXH4axCYps9Cqcw+fpbx21TamqzuCcDoQV2Irw+VjHspOTJQvvN99/mXbSHmkTGhLVnIdzKIu869X5B3Gw67PlUqeHTeegZHIZFknuDUXWpECzstt7Exz970AGsFFSiuhv3IeWUE51yew+VPwTOU33SL/uem/s4WCqT4/Pk0f8LVJ13Jg9gFWnfp7sgjTaPQIF3MvumdysFPKWV/q2V54pVUoRAkJACOQRAjAzHcQP7pCVaK9ZSeTmn4BV8S9rP9gaVvU3nNspIPugUJU15bNekXnogX8sSiJnhQUsDNa9Gm76j511HEriElwPS10slEL2eRq9AOdo51t3ED0QyoVnIGx5Q1//jT60BAd964dP4qzXLIbh6uvDOGclkQUKN+/v7ml5mpXE7ShVVxK5Aijbd6I/bD1kcek+5Movqta+HP+uGwPLIr/liPg7gVz5s/7tt9/UFlk3b96kqKgof2cs/RMCQkAIKAK8c1RaH3xgTTQevrBYPYbfXGOPeM6ZAMtZirqEPt6Po8VCyFuL9m+Mcx7PZImH5Q553ZGxUL4W4aNL29pY0ArLpP3uUXq6s2P3nZYUWMp4qHvCQZxf0+IK6e2zu5jr+uZeopdhvSTL0DtnWRMLd1e7tMyDonA0Xd+oDM6Lamn8fcJShzUme6EjUNin6X1BUffDWEblLGVCme2/VQu7ch/SHrDcX9xjc5stpfnfoWETjNXjrUPErwkYzyq/7qV0TggIASHgYwSKQcHq2whbXGIodWYzoq3tTA2EZeuIxZL1P1jddGlfDQoZrqFQPYZotindGus4dAqWudfW26bVwbZ+S5MwTGy2ptlmcXxmmfPHFsn6C2F5Mylww6E7LD+V/rJWUIr7VIUTfQwnH+uCdAzv6vLeds1qx0Pl7aBQKgki6hwGPnfruYjuCraGPRFahL4TFF0lhaF4tyR6h5VFi/wKZZzFk/dBK9FPvpviLePv5X7SGemGIwKiKDqiInFCQAgIAS8T4D3pv4Z1ULfk2eycAouavpgizjS/sQnm6LHEmKxx6y9qca58j9qDXKm2OSdg2LX9r/CrvBKj0LrCZJvF4VnPCFM0FNBuUOjMchpxGQkv5nkk0pQDiue+S0Q8D3AphrXZqvhZC8ztw6/U22ythPA6iofDtbCnvnmRjCHgywtswk18CW3iOYyevA9Gff4SuKsN0bJF/tIb6YcdAVEU7YDIqRAQAkIgNwhMirPWeldN02ILi2WRU/Uh3XIFrXl3myx51ljHoQn21keTQrQJC2vGYQjYVfkQ6xg61UVuWAXfuYOoQyjmJkKx4yH0Fmh/p7DMS7qTh5VNwiukX9hG1BzX/tWJ6KUaRD8cIdqFPn58D/Z7b23K7KFgnG4Z5fKgJLKUMPHleYvnWLn24H1Qlfjb170dMKfhF3/rlfQHBMz/HQSIEBACQkAI5AIBdo0zaKOlYgy3TsPUL0N4kQnSWU5a5i2eNnkXa2RS9rRcGXyft6a9CaXurWii7uuJZu3Q4idDkRyqD/taszoMhcEiugDDtGZ5E+Xxx1VJsvRHz18dff3drkwequaPt6RmMVPJ17XwJRNfVh7LFUK8J++DqUq/CnboSjR3BvZd7e5X3crvnRFFMb//BUj/hYAQyFUCKZjjF/oXmmCxbE1tRVTZpLxEw0K3+4zWxIMWq9YuDM/q0qSkHnLhyHMCLfWwj0WWCMuRw7stituMY1iVfRmrmjE0bG4L5/GUsL/H93abSoPiWcuNvniqjdGmeZJsNeTV10dNfNliytMDPHEftkFRn405jx0qemCuJVvvvhhrAujh4KnjWSvwoccxqRQ397HeWbtervI5AqIo+twtkQYJASGQnwi0/Qe9TbD2+JX9RPwJgiXr6L1EA6GsPX9IS1+KuXrd+KmdaM3/dBVrOLNQDygo005qufqvhvUP5Z6CUqhL3xDN/Uw/Vlwhb2A18EUYidhBtidk5BGiA1DCfuA28AdKmS5dMP/QVWEXOZ5q479CUSv3j4eXoSi3WEW0zsS3VxTiIdm9Dzxn87b5KAj1vIPDwo5EHTHEnmXh7fTmr83y5V69sPszeCGB1v10f69Wk53Cr1+/TomJiVShQgUqWhRvKV4W3mQkPj6eypQpQ6VLWyYbW+rkdnB7zFKpUiUqVMj6H4+9xGzfvp2qVKlC5cuXN2f1eljmKHodsVQgBISAEHBM4PktRKuhFJrlFJQp/sTHYXEJFKnnqiIVCpwSKBlzobzpElPdPcvUR5hXaLjhQVlcj7HiF1bMsfWINpuGp9ktz5IkvTYPHOOhJGIOolJ0TUoiVcLwd1PXy/dkGysUgT/L26x1r4tFGAtYlGAV9McxWjC790GtYgdzXT6yLNDRz/3u2HsAlor/12e79ddffyn3fAsXLlRtnD9/Ph05wv8hvCM7d+5U9Y0aNSpdBR07dlRp7C5Q/2zatMnIt27dOqpYsSI1btxYKbavvfaakZYTAVEUc4Ky1CEEhIAQsCMwKQ6/o5vtIu1OA3DOq3DPdcCq5Bo4CbRkwDzGHg2INt1jdwGf8kUW4WvNwvMKY1FWPSiYBAVJCX4FqkQRHX6QqDwUo4GcVkZL4u+UW9awuyG2ijoV9IFgGHmtOfSydu7tXOJuGwvZ/dLZndKHYDmmJdqjG5a43eFgBWuqvlWi2/fBruONwbQJ30OL2G/rqMf71fH5wfCFNMbnu8SWvi5dupAjJc7TjU/TPcvbFRwWFkYffPCB8WHLIcv58+epQ4cOyuI4bNgwatiwIY0dO5amTp1qV4L3Tgt6r2gpWQgIASEgBJwReCaK6Jk+zlJt43mbvnWt4Kblbm3P4iqw/gU4UcLSHrG91v6sRglt9bCai4fRwQgoR7qLHs7Lc/Z4tfF4XlyDka/WwfYluH7OLoDYwbinxd02NimbeTuG14XTb3yOgwkrzI72yHbnPtj3me/Xd7BcNsTqcpYeUETzhQwagWHoK5T2f+/ib9bJH20ugwgPD6dp06ZRs2bNcq0lPNQ8dOjQdPVPnjxZKYsTJkyg/v3706BBg9Tw86effko9e/ZMl98bEbmiKPLOLEePHlX9uXjR7MTKG12UMoWAEBACvkHgP7uw7R6Ur5J48o7GMK+7UhCmsEhefesB4d9sR2VtPQ8lcS8qQDsnQTllZc/XxJttZP+OmYmz+8D7VLMvSCWY72iWK1hJ3c0ymtimNtGAauZUPw+/PpYCrkJZfPtTl5TFHTt20Pr166lz587EQ8Nnzpyhrl27Uo0aNWjNmjX0559/Uvv27dMpdlu3blVprJDef//9VK+e7X+yAwcO0B9//KHKu3z5sgGd5w8mJyer+OrVq1NqairNmTOH9u/fTy1atKDWrVtTwYKaurRgwQKVzpa9X375hUqWLEndunXz2rxB1pdY2rRpo46hoaFUq1Yt2rBhA506dYpCQkJUvFe/YAbNccEN5tkpNh/s/5zj7ZAKhYAQEALeJkCzYbv7xu4zxdu1Zr38Lw6mpb22Iy3t4KWsl+HtK321jfSr3X223PfrN9LStp5LS+u8Ji1tfryH6Hw7no3Ceevz1qsudX7MmDFKP4CVLa148eIqjEUgabCopUEJTIPSpuIGDBhglPf555+nsR7B6fwJCgpK++mnn4z0GTNmpBUpUkRdx2m6DjJ79uw0GKzUOax1Kr+9jlKnTp20a9euqbTmzZur+kuUKJFWrFgxdR0UUlWGUZmDwJYtW1TeV155JV1qo0aNVFpwcHDaAw88kAaF18jDdRcuXDgNyqsR99hjj6n8mMdoxHkzgPfTnBfW9Hv37p3uk/MtkRqFgBAQAt4l0BeWo1awIJk/D9f0bp3ZKf0FtPddLHqphiFqXxVfbeNQTCsz32cOs/UwENbbhpijOP8ObEmIhTv5Vh7t5VbXoQjSpUuX1Hw8nqvH1rU9e/bQiRMnKCYmhr788ks1d4/nGA4ZMkQt9oiLi6NDhw4p6+PAgQOJVwuzRbJfv35qtfHcuXPpypUrNGnSJKdt4bqgZKpV0U8++STt3btXWfD0C6CQqnQeER08eDDt2rVLWUD1dHePLVu2pEce0eaM/P7778TnsbGxqhhue2RkpGHR5Eh9/uLZs2fdrSpL+XNl6JnBiggBISAE8gMB3qZPJH8Q+MCyQjp/9NaNXvLCpV27iWpgEqgb0qNHDzVU3alTJ3XkOYS1a0PzhnAcD1EfP36cYK0jWPyoVKlS9PXXX6t0WPxo9+7daiXzvn376MKFC9SnTx81hM0ZeBWxM1m8eLFSKlkB5aFlFh6a1qVy5cpqaJvPeUh83LhxxHW0bdtWz+LWEdZQlZ+VWp6H+NVXX6kyJ06cqIaWue1mOXhQWzKfUR/M+bMbzhWLYnYbLdcLASEgBISAEBACeYAAT6HbhxU8biqJ5p6xAohhXnOUMSeQ5xfqihSGaJUFkRUuVtrYjQz7ImQLIUuTJk1synB2wpa6hx56iOrWrUvs1oaF63Ek7IeR5erVq46S3YpjS+VLL72krmErJgsrpQkJCcoqqiLwxQoyC6flhOSKRTEnOiZ1CAEhIASEgBAQArlIANMYaOURuBrSXL14qyWYN6iKZiviu+++a1TDChbm/RHm+ak4thSylTIzef7554kXvrCVkP0Zrlq1KrNLspzOCmFERARx21mmT5+ujlWrVlVHdtuzaNEi+uGHH9SKZ15gw0PrrAiz8+6cEFEUc4Ky1CEEhEC+JZCIESt7n3kFMWdNX13LqxF2wPkD7/d8G577IYWdozoGo8V+LNZsiI0ddP9+9rl5a7zrt7RY3qbPkZsX/Zq1Z4hiUFbxbPwS3EBdOzAy1gguaHQ5gDYWwXhVGOo/Zh2x05ONI/smZFc/XMZaTLeqjVE+vf+7wYTZ1EP7siLs5mYf2sFtYHc6zsQVprfQju3oY/JNWKVwj4ICraXFXbGG9VAJ8HR2f/Q8fn/EPFdaegJjvNnZfsY1StHR0Wpe36xZs9RQMzuw5rmKWMCiFD4sFqF27drRjz/+SGx15Pz6HEBHNWzbto3Kli2rLHk8V5GFVxnzamNPy3vvvUfcblb8uE2sCLJl8d///reqiudIvv3228o6ykrrypUrVbwjVzqebpteXjYeD3oRchQCQkAICAFnBMIWIsV2ihERlMFbcIE2DiNyQzYjHQqNIVjscOpeW0WDlZGqy5Ej0chFtWGtWXsnfGMHWeM4VOlXfEHJYpnYBtv/IZ+9sALWF/V+txUpUHqiI4nm3K4pavZ5MzqfchT7Qa/Wyrj8MLYchHIWzcaXk0S/ddQ2fak6I4MSoMSlgUPEMlwSh3xQHH+6n4h3MXl1pXZdVygcczWDUQYFWZP+gfJ75zqcJ1jj2JH24rZE91W0xrnKdNZxou4rcB0UeSUFiEahPSOjUQWUYEf9C4+CP0bUl2+lMTTzRbH4I66QLQQFCgC2E9HT+Mgf3lmlb9++tGzZMuKdTNhC17t3bypXrpwqgRU+Vq7Y3Q7PAdSFXenwh0U/Dh8+XClm7J6Hh6DZJc2HH36olDm9Xv16/ZyVu4xEL9s+Dyu17C6QXf7wPEueg/nxxx/THXdg5ROE50hyGltC2ck2t4XnYfKi4JySAF5SnVOVST1CQAgIgfxGIIANEvaKIhSk2C5ENWc6oQFlMe0BLS0V1ragnxG2KH82V4QjXwebGAqYbc3rTFHs8Dd+x7UpUOritrVx3tLW8bZtqenPlAK1SIuPfUxTWEO4r1Co3mqBfaShSLHiGDk9/bVGDDhcfxx682QjBo4bUVZh7EhxxBp36klbxdmakj4UsABxSenjCTpHHNrJviNdZbr8FFYtz3dQFqI+ugcKJPhXdtC/HFEUE2GtO4I3DW/JDrxFPPey+6XfVZVowUbcRE1Bc7+A7F3B8xN5TmJ290PmOYdwp6OUUPa5yIqgN/eE5r2eU1JSjMUzjijwXEz7faId5fN0nFgUPU1UyhMCQkAIOCGQ0MPqwPqQbkUsT/QYFMNZR3GRrlAmQFFK0ZSvj/cjXlcSYT3sDwvbF1sQx6/48bDcIW9HN0b3xkJBtFcSl9zpfKcX1OJQuu+0RMOQwkPdE3ghJpRElkKagUY7MX2zQtrLNP+eHY/zMG4t6Bb7D1syooxRyPcy87CYMXhY3q2hXCig90cRLYcl9voxS7lo4y9gNbAG9m92kWkb6DuGhMBSiWHnv2EoYxmCNHaare88s+gkUQe25uaUhOKPhj/ekqzYkNrFEP28iqhUFucLeKAvrNBlV0nkZpgXz+jzBz3QPKdF8JA4fzKS3FASuT14xxIRAkJACAiBnCZQDApS30aYn/cg0cxmRFvbmVoABYmHX1n+B8ORLu2hmEzANWx102W2KV2Pc3Y8dR17K6+3Ta1TAlPJYIHjeXhuCYZdlWDeXn0Mrx+zKIkcN/wfKGmwxtlLKyjFvSKtn4dgkWPZ2wZfQSpIjYI1Za4FFDol+O2siTa6KgOgiB59iOgPKL/X2uOqstYrYy3KuStMr6FfZGI773YMize1lkW4P1vOm87ze7AzxuN/WZOrSmJ+vwXe6r8oit4iK+UKASEgBDIgwFvjsY9FfZ/lqGKmzLDI8cIOlrgL2pG/m1gMNTGmvOt1a6M1m9PQqD1ISrVNnrCJqD0sYc1WEt2E1c1V6RlhygkFtJudVfM04uxlJOoK+Nn0gYLJ8sNRfKXgg37NAhNeDLMG1lKes/hlS9vFI4jNUD6/DcPBJj6EoWZdGsEiyOIKU26DWeph2l0FWCq5TbrsvaSH8vnxEWj6s5fj/plg53Mk/tR9URT96W5KX4SAEMizBCbFWZt+F3ZuKQKLoxKLZZHD+pBuOQzZ6rLbZMnT45wdJ5gsZCqPSaHahOlu4yzDqs6uN8d/WB9Oj+siBgrUO3dg2DVUm5tIUGZboP2d7BRHdS0rj2yFM314D+TeGMblRSuJsATWKEnUEwplVEVYJTsT9aumrszSF684N6yCsEx215VbF5jG23Fl9rxK2zwOx0Pi+V564SZN/QMTTVmLFvFHAqbHjT92T/okBISAEPB9AqxwDIKypARDsNOamNrMRhqLQnKSrW6Q01CudGlkUvb0OKdHVtAs8mYLKHbRUJ7Ww4q3Q4ucDEVyaG09R8bHMFhEF8DaZxZewMIfpwLlr71pKDgYfWXXPGkP216xrpXteVbPHliHKy1W0vHor+EGyAWmkeifWU6DvbJU8pC0RcKL6aF8euz3KNHn0wj7y+VTAPmj23J388d9ll4KASHgowRSoHiE/oXGsfULMhVKknnoNBoWut1ntLSDFkvYrivaOX83KWkNZxqC9U+vh30sskSYDEG7LYroDCwAOYihV55PaG6LdkXWv9+uTjSCrZBZkAto28RD2mKgHrAMmn0ZOipuxC7M+zyopTSrQfQi6tbFFabVSyA3WxDTtKvYH2RFWCXNUpfzZCLeYplJtd5PfqU3pX38LQVk4MLG+42QGnKCgAw95wRlqUMICAEh4IRA23+QkGBNfGU/5sIthQL3p7bAZCCUNV2WQvHpxlayRD2G6Okq1nBmoR6w6OnSf7VWz7hNegwW14QQfXWY6InFRG+gXVUWEl2ym9NozZ2zodvQ3tf+JnoGbB7bkHHd06HojllrzbMeCjYz5c/Sk1gs4wLTQvh1DDflewgW3xpogyFQ4NlBekbiqywzarNLaf/Xn9LGfSdKokuw8n4mURTz/j2UHggBIZBHCTy/hWg1FEOznDoCh9v4xMdhcUkaXNlVRSoUOCVQ2ubutIRxiIGV7K5g63lmoY/qIwcUHCUoi+vRh2Z5IcnYekSbTcPT7JZnSZIlfy4f4s5aG/ALmDnz3rLiFFEPKNk2ckLrK/f3EJRGV5n+ylMA9F9JlGu42kH05KYYcdXTbCqznvgqS2sLsxB6eyilvfu54Zw6CyXIJXmMQCZ/5nmsN9JcISAEhEAeITApDq5vNmfc2AAk8wKKcx2wKhnDp7yLipIgKEMNiDbdYzk3H/gii6jFF/oJjjyvMBZl1eNh2CJ6JlgOo4gOP0hUHkOrAznNZClLuWXJl4VDkKktWbjc5hLlFkjv/02bJOMkCXM5W/+BUyfpnJGLcJUpWwz/ARcqz1dapBSmB9wHS67J2qgn2R89ydK+7Fw5/+hNSnvjfVEScwV+7lUqO7PkHnupWQgIgXxAwLwzi9nhdla6znsix2OuHO+PbNl1LCvFqGvYIsc7p0RAedRd9OiFDdxGNB5DrVQIo+KPavMC9bTcPAbMRe1nocdCSTvXzjMtcZUpz5Fkx+LKRY6Dqs0Ot8OjrFv4+SpLB12wjVq7AsvXW1vjPn8fHsaHWc8llG8IFMw3PZWOCgEhIARymcB/dsH/M5Qv3pFkNIZ53RUe6uQt6DwhrGg6Kmsrhp7H70UNaOekVr6jJH4cizZBSWQH2hvu8AQBrQxXmZaGFddekmG5fB1TAaBz085L9qlYTOOjLNO3NJOYb8cTPftiJpkk2V8JiKLor3dW+iUEhIDPEfgBljolGOLNiqKYEx1aA2XsNSixfaOIqpXIiRpdq2M12vXBXTBqYWi8mI/8cp2BX8hP2PLqRHyVpZPmOo6e+g3mOfRxnCax+YKADD3ni9ssnRQCQiC3CDy3GfMCMcRrlmBY635qbo6RcF4kwPtxd12fvuX3YU7j8Lrp4/NUzIa/MX5+hOihZvoYkgAAB8ZJREFUHnmq2dJYzxMQRdHzTKVEISAEhIAQEAJ5mkAaJrEGZHcibJ4mII3XCciqZ52EHIWAEBACQkAICAFFQJRE+UPQCYiiqJOQoxAQAkJACAgBISAEhIANAVEUbXDIiRAQAkJACAgBISAEhIBOwEfWjunNkaMQEAJCIHcJsNPmq3YOm9lvtCNXMrnbUqldCAgBIeB9ArKYxfuMpQYhIATyEIGAhWhsYvoGX+9NFKTvDJI+WWKEgBAQAn5JQIae/fK2SqeEgBDIMgF5KmYZnVwoBISA/xGQoWf/u6fSIyEgBLJBIO0B68UB0xDGlnkiQkAICIH8SkDenfPrnZd+CwEhIASEgBAQAkIgEwKiKGYCSJKFgBAQAkJACAgBIZBfCYiimF/vvPRbCAgBISAEhIAQEAKZEBBFMRNAkiwEhIAQEAJCQAgIgfxKQBTF/Hrnpd9CQAgIASEgBISAEMiEgCiKmQCSZCEgBISAEBACQkAI5FcCoijm1zsv/RYCQkAICAEhIASEQCYERFHMBJAkCwEhIASEgBAQAkIgvxIQRTG/3nnptxAQAkJACAgBISAEMiEgO7NkAkiShYAQyF8EJh4i2nfJ0ueU/NV36a0QEAJCwJ6AKIr2RORcCAiBfE2g/x50PzFfI5DOCwEhIAQMAqIoGigkIASEgBAgGlqFaH1pWxI8RycwwDZOzoSAEBAC+YFAQBokP3RU+igEhIAQEAJCQAgIASHgHgFZzOIeL8ktBISAEBACQkAICIF8Q0AUxXxzq6WjQsB/Cezbt48SEhL8t4PSMyEgBIRALhEQRTGXwEu1QkAIeI7Agw8+SJUqVaIKFSrQ+PHjPVewlCQEhIAQyOcEZI5iPv8DkO4LAX8gULt2bdq/f7/qSmBgIB0+fJgqV67sD12TPggBISAEcpWAWBRzFb9ULgSEgCcITJ06lbp27aqKunnzJh05csQTxUoZQkAICIF8T0AUxXz/JyAAhEDeJ3D77bdT9+7djY4kJSUZYQkIASEgBIRA1gmIoph1dnKlEBACPkSgbNmyRmvOnDljhCUgBISAEBACWScgimLW2cmVQkAI+BCB8uXLG6356aefKDU11TiXgBAQAkJACGSNgCxmyRo3uUoICAEfI3Dr1i1q0KAB7dq1S7WMV0HHx8f7WCulOUJACAiBvEVALIp5635Ja4WAEHBCoECBAjR06FAjVSyKBgoJCAEhIASyTEAUxSyjkwuFgBDwJQLJycn04osvqiYVLVqUnnzySV9qnrRFCAgBIZAnCYiimCdvmzRaCAgBewLbtm2jy5cvq+hXX32Vxo0bZ59FzoWAEBACQsBNAqIouglMsgsBIeCbBM6fP280rH79+kZYAkJACAgBIZB1AqIoZp2dXCkEhIAPETAvXClTpowPtUyaIgSEgBDIuwQK5t2mS8uFgBAQAhoBXsQyZcoUA0epUqWMsASEgBAQAkIg6wTEPU7W2cmVQkAI+AgB817PoaGhdPToUSpUqJCPtE6aIQSEgBDIuwTEoph37520XAgIAQsB3sKvVq1aVLNmTXrllVdESZS/DCEgBISAhwiIRdFDIKUYISAEhIAQEAJCQAj4GwFZzOJvd1T6IwSEgBAQAkJACAgBDxEQRdFDIKUYISAEhIAQEAJCQAj4GwFRFP3tjkp/hIAQEAJCQAgIASHgIQKiKHoIpBQjBISAEBACQkAICAF/IyCKor/dUemPEBACQkAICAEhIAQ8REAURQ+BlGKEgBAQAkJACAgBIeBvBERR9Lc7Kv0RAkJACAgBISAEhICHCIii6CGQUowQEAJCQAgIASEgBPyNgCiK/nZHpT9CQAgIASEgBISAEPAQAVEUPQRSihECQkAICAEhIASEgL8REEXR3+6o9EcICAEhIASEgBAQAh4iIIqih0BKMUJACAgBISAEhIAQ8DcCoij62x2V/ggBISAEhIAQEAJCwEMERFH0EEgpRggIASEgBISAEBAC/kZAFEV/u6PSHyEgBISAEBACQkAIeIiAKIoeAinFCAEhIASEgBAQAkLA3wiIouhvd1T6IwSEgBAQAkJACAgBDxEQRdFDIKUYISAEhIAQEAJCQAj4GwFRFP3tjkp/hIAQEAJCQAgIASHgIQKiKHoIpBQjBISAEBACQkAICAF/IyCKor/dUemPEBACQkAICAEhIAQ8REAURQ+BlGKEgBAQAkJACAgBIeBvBERR9Lc7Kv0RAkJACAgBISAEhICHCIii6CGQUowQEAJCQAgIASEgBPyNgCiK/nZHpT9CQAgIASEgBISAEPAQAVEUPQRSihECQkAICAEhIASEgL8REEXR3+6o9EcICAEhIASEgBAQAh4iIIqih0BKMUJACAgBISAEhIAQ8DcCoij62x2V/ggBISAEhIAQEAJCwEMERFH0EEgpRggIASEgBISAEBAC/kZAFEV/u6PSHyEgBISAEBACQkAIeIiAKIoeAinFCAEhIASEgBAQAkLA3wiIouhvd1T6IwSEgBAQAkJACAgBDxEQRdFDIKUYISAEhIAQEAJCQAj4GwFRFP3tjkp/hIAQEAJCQAgIASHgIQKiKHoIpBQjBISAEBACQkAICAF/IyCKor/dUemPEBACQkAICAEhIAQ8REAURQ+BlGKEgBAQAkJACAgBIeBvBP4fC/b5K0yMzsMAAAAASUVORK5CYII="
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "![bins.png](attachment:bins.png)\n",
+    "\n",
+    "What is it?\n",
+    " - Start with an empty Dictionary\n",
+    " - Read a row\n",
+    "  - Keys are entries from one of the colums of the data\n",
+    "  - Each key's associated value is a list of lists\n",
+    " - Each row of data ends up in some bin\n",
+    "\n",
+    "Why bucket data?\n",
+    " - A way to organize our data, without losing information in the process\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{2014: [[2014, 'A', 123]],\n",
+       " 2015: [[2015, 'B', 120], [2015, 'C', 140], [2015, 'E', 130]],\n",
+       " 2016: [[2016, 'D', 100], [2016, 'F', 200]]}"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows = [\n",
+    "    [2014, \"A\", 123],\n",
+    "    [2015, \"B\", 120],\n",
+    "    [2015, \"C\", 140],\n",
+    "    [2016, \"D\", 100],\n",
+    "    [2015, \"E\", 130],\n",
+    "    [2016, \"F\", 200]\n",
+    "]\n",
+    "\n",
+    "bins = {}\n",
+    "for row in rows:\n",
+    "    year = row[0]\n",
+    "    if year not in bins:\n",
+    "        bins[year]=[]\n",
+    "    bins[year].append(row)\n",
+    "\n",
+    "bins"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in the cell below to calculate the average of the last column for the year 2015"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "390\n"
+     ]
+    }
+   ],
+   "source": [
+    "#TODO: calculate the average of the of the last column for the year 2015\n",
+    "\n",
+    "total=0\n",
+    "for row in bins[2015]:\n",
+    "    total+=row[2]\n",
+    "print(total)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Applications of Nested Data Structures\n",
+    "\n",
+    "Let's bucket-ize data from the CS220 Survey.\n",
+    "\n",
+    "As a refresher, run the below cells to see some of the data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Section',\n",
+       " 'Lecture',\n",
+       " 'Printed Copy',\n",
+       " 'Age',\n",
+       " 'Primary Major',\n",
+       " 'Other Majors',\n",
+       " 'Secondary Majors',\n",
+       " 'Zip Code',\n",
+       " 'Latitude',\n",
+       " 'Longitude',\n",
+       " 'Data Science Major',\n",
+       " 'Pizza Topping',\n",
+       " 'Cats or Dogs',\n",
+       " 'Runner',\n",
+       " 'Sleep Habit',\n",
+       " 'Procrastinator',\n",
+       " 'Song']"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['COMP SCI 220:LEC004, COMP SCI 220:LAB344',\n",
+       " 'LEC004',\n",
+       " 'No',\n",
+       " '19',\n",
+       " 'Engineering: Other',\n",
+       " 'Engineering Mechanics',\n",
+       " '',\n",
+       " '53726',\n",
+       " '44.39',\n",
+       " '-89.83',\n",
+       " 'No',\n",
+       " 'none (just cheese)',\n",
+       " 'dog',\n",
+       " 'No',\n",
+       " 'night owl',\n",
+       " 'Maybe',\n",
+       " 'Family Ties-Baby Keem']"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cs220_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The cell function will also be useful!\n",
+    "\n",
+    "def cell(row_idx, col_name):\n",
+    "    col_idx = cs220_header.index(col_name)\n",
+    "    val = cs220_data[row_idx][col_idx]\n",
+    "    if val == \"\":\n",
+    "        return None\n",
+    "    elif col_name == \"Age\":\n",
+    "        if \".\" in val:\n",
+    "            return None\n",
+    "        return int(val)\n",
+    "    elif col_name == 'Latitude' or col_name == 'Longitude':\n",
+    "        return float(val)\n",
+    "    else:\n",
+    "        return val"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in the cell below to bucket-ize the survey data by lecture.  When you are done the `lecture_sections` variable should be a dictionary where the keys are the different lecture values and the values are the rows of data that are in that lecture."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['LEC001', 'LEC002', 'LEC003', 'LEC004']\n",
+      "234\n",
+      "['Section', 'Lecture', 'Printed Copy', 'Age', 'Primary Major', 'Other Majors', 'Secondary Majors', 'Zip Code', 'Latitude', 'Longitude', 'Data Science Major', 'Pizza Topping', 'Cats or Dogs', 'Runner', 'Sleep Habit', 'Procrastinator', 'Song']\n",
+      "['COMP SCI 220:LAB324, COMP SCI 220:LEC002', 'LEC002', 'Yes', '18', 'Computer Science', '', '', '53706', '34', '108', 'Maybe', 'sausage', 'cat', 'Yes', 'night owl', 'Maybe', 'Bohemian Rhapsody by Queen']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Example 1: Place the data into buckets by lecture\n",
+    "# Key:   name of lecture (\"LEC001\", \"LEC002\", etc.)\n",
+    "# Value: a list of all the rows that go with that lecture (list of lists)\n",
+    "\n",
+    "#TODO complete the code below to populate the lecture_sections dictionary\n",
+    "\n",
+    "lecture_sections = {}\n",
+    "\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_student = cs220_data[i]\n",
+    "    current_lecture = cell(i, 'Lecture')\n",
+    "    if current_lecture not in lecture_sections:\n",
+    "        lecture_sections[current_lecture]=[]\n",
+    "    lecture_sections[current_lecture].append(current_student)\n",
+    "    \n",
+    "print(sorted(list(lecture_sections.keys()))) # print all the lecture sections\n",
+    "print(len(lecture_sections['LEC002'])) # print how many LEC002 students completed the survey\n",
+    "print(cs220_header)\n",
+    "print(lecture_sections['LEC002'][2]) # print the third student to complete the survey for LEC002"
+   ]
+  },
+  {
+   "attachments": {
+    "table_rep.png": {
+     "image/png": 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"
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![table_rep.png](attachment:table_rep.png)\n",
+    "What is it?\n",
+    " - Start with an empty list\n",
+    " - Each row of data is one dictionary\n",
+    "  - keys are the column names\n",
+    "  - values are the data in each cell\n",
+    " - Makes a list of dictionaries\n",
+    "\n",
+    "Why put data in table form?\n",
+    " - It seems redundant, but is used often in computer apps for storing info\n",
+    " - Its a little easier to access subsets of the data without worrying about the header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Section',\n",
+       " 'Lecture',\n",
+       " 'Printed Copy',\n",
+       " 'Age',\n",
+       " 'Primary Major',\n",
+       " 'Other Majors',\n",
+       " 'Secondary Majors',\n",
+       " 'Zip Code',\n",
+       " 'Latitude',\n",
+       " 'Longitude',\n",
+       " 'Data Science Major',\n",
+       " 'Pizza Topping',\n",
+       " 'Cats or Dogs',\n",
+       " 'Runner',\n",
+       " 'Sleep Habit',\n",
+       " 'Procrastinator',\n",
+       " 'Song']"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cs220_header"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['Section', 'Lecture', 'Printed Copy', 'Age', 'Primary Major', 'Other Majors', 'Secondary Majors', 'Zip Code', 'Latitude', 'Longitude', 'Data Science Major', 'Pizza Topping', 'Cats or Dogs', 'Runner', 'Sleep Habit', 'Procrastinator', 'Song']\n",
+      "\n",
+      "935\n",
+      "\n",
+      "{'Section': 'COMP SCI 220:LEC001, COMP SCI 220:LAB313', 'Lecture': 'LEC001', 'Printed Copy': 'No', 'Age': 19, 'Primary Major': 'Data Science', 'Other Majors': None, 'Secondary Majors': None, 'Zip Code': '53703', 'Latitude': 37.2788, 'Longitude': 127.154, 'Data Science Major': 'Yes', 'Pizza Topping': 'Other', 'Cats or Dogs': 'dog', 'Runner': 'Yes', 'Sleep Habit': 'no preference', 'Procrastinator': 'Yes', 'Song': 'im fine with any song'}\n",
+      "\n",
+      "19\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Let's put the student survey data into a list of dictionaries\n",
+    "students_info = [] # list of dictionaries\n",
+    "for i in range(len(cs220_data)):\n",
+    "    current_row = cs220_data[i]\n",
+    "    current_student = {}\n",
+    "    for col_name in cs220_header:\n",
+    "        current_student[col_name] = cell(i, col_name)\n",
+    "    students_info.append(current_student)\n",
+    "\n",
+    "print(list(students_info[278].keys())) # print all the keys for a particular student\n",
+    "print()\n",
+    "print(len(students_info)) # print how many students completed the survey\n",
+    "print()\n",
+    "print(students_info[3]) # print the fourth student to complete the survey\n",
+    "print()\n",
+    "print(students_info[3]['Age']) # print the student's age"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Nesting: Dictionary of Dictionaries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nested_english_dict = {\n",
+    "    \"shenanigans\": {\n",
+    "        \"definition\": \"silly or high-spirited behavior; mischief.\",\n",
+    "        \"usage\": \"widespread financial shenanigans had ruined the fortunes of many\",\n",
+    "        \"fun_to_say\": 7 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"bamboozle\": {\n",
+    "        \"definition\": \"fool or cheat (someone).\",\n",
+    "        \"usage\": \"Tom Sawyer bamboozled the neighborhood boys into painting for him\",\n",
+    "        \"fun_to_say\": 8 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"gubbins\": {\n",
+    "        \"definition\": \"(objects) of little to no value.\",\n",
+    "        \"usage\": \"I cleared all the gubbins off my desk before I started working\",\n",
+    "        \"fun_to_say\": 10 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"malarkey\": {\n",
+    "        \"definition\": \"meaningless talk; nonsense.\",\n",
+    "        \"usage\": \"don't give me that malarkey\",\n",
+    "        \"fun_to_say\": 5 # on a scale of 1-10\n",
+    "    },\n",
+    "    \"gnarly\": {\n",
+    "        \"definition\": \"gnarled.\",\n",
+    "        \"usage\": \"twisted trees and gnarly roots\",\n",
+    "        \"fun_to_say\": 2 # on a scale of 1-10\n",
+    "    }\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'definition': 'meaningless talk; nonsense.',\n",
+       " 'usage': \"don't give me that malarkey\",\n",
+       " 'fun_to_say': 5}"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Get the definition, usage, and score of 'malarkey'\n",
+    "nested_english_dict['malarkey']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'silly or high-spirited behavior; mischief.'"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Get the definition of 'shenanigans'\n",
+    "nested_english_dict['shenanigans']['definition']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'I cleared all the gubbins off my desk before I started working'"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Get the usage of 'gubbins'\n",
+    "nested_english_dict['gubbins']['usage']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### You Try It\n",
+    "\n",
+    "Finish the code in each of the cells below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "shenanigans : silly or high-spirited behavior; mischief.\n",
+      "bamboozle : fool or cheat (someone).\n",
+      "gubbins : (objects) of little to no value.\n",
+      "malarkey : meaningless talk; nonsense.\n",
+      "gnarly : gnarled.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Print out each word and its corresponding definition\n",
+    "# TODO: finish this code\n",
+    "for word in nested_english_dict:\n",
+    "    print(word,\":\",nested_english_dict[word]['definition'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6.4\n"
+     ]
+    }
+   ],
+   "source": [
+    "# average of fun_to_say for all words in dictionary\n",
+    "total = 0\n",
+    "for word in nested_english_dict:\n",
+    "    total+=nested_english_dict[word]['fun_to_say']\n",
+    "    \n",
+    "print(total/len(nested_english_dict)) # be safer, check if count is 0 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter a word to lookup:  blunderbuss\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ":(\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Let the user enter a word.\n",
+    "# If it has a fun_to_say of more than 6, print :)\n",
+    "#                           more than 3, print :|\n",
+    "#                           otherwise    print :(\n",
+    "choosen_word = input(\"Enter a word to lookup: \")\n",
+    "\n",
+    "if choosen_word in nested_english_dict:\n",
+    "    if nested_english_dict[choosen_word]['fun_to_say'] > 6:\n",
+    "        print(\":)\")\n",
+    "    else:\n",
+    "        print(\":|\")\n",
+    "else:\n",
+    "    print(\":(\")\n",
+    "    \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## More Examples Of Dictionary Usage\n",
+    "\n",
+    "If you want to see more Examples of ways to use dictionaries check out [w3schools](https://www.w3schools.com/python/python_dictionaries_nested.asp).  Below is one final example.  Look to see how the `scores` dictionary is used."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  help\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Commands:\n",
+      "help\n",
+      "  print list of commands\n",
+      "set <name> <score>\n",
+      "  updates score of player with given name\n",
+      "get <name>\n",
+      "  gets the score of player with given name\n",
+      "print\n",
+      "  prints all the scores\n",
+      "high\n",
+      "  print high score\n",
+      "quit\n",
+      "  quit program\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  get bob\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  set alice 5\n",
+      "enter a cmd (type \"help\" for descriptions):  get alice\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  get george\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "unknown name\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  set george 4\n",
+      "enter a cmd (type \"help\" for descriptions):  get george\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4\n"
+     ]
+    },
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "enter a cmd (type \"help\" for descriptions):  quit\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "exiting\n"
+     ]
+    }
+   ],
+   "source": [
+    "#KEY: player name VALUE: player score\n",
+    "scores = { \"bob\" : 0,\n",
+    "           \"alice\": 0 }\n",
+    "\n",
+    "def do_set(cmd):\n",
+    "    # why do we need this?\n",
+    "    global scores   \n",
+    "    name = cmd[1]\n",
+    "    score = int(cmd[2])\n",
+    "    scores[name] = score\n",
+    "    \n",
+    "def do_get(cmd):\n",
+    "    name = cmd[1]\n",
+    "    if name in scores:\n",
+    "        print(scores[name])\n",
+    "    else:\n",
+    "        print(\"unknown name\")\n",
+    "    \n",
+    "def do_print():\n",
+    "    for person in scores:\n",
+    "        print(person, ':', scores[person])\n",
+    "        \n",
+    "def do_high():\n",
+    "    # PASS 1: find the best score\n",
+    "    best_player = None\n",
+    "    for player in scores:\n",
+    "        if best_player == None or scores[player] > scores[best_player]:\n",
+    "            best_player = player\n",
+    "\n",
+    "    # PASS 2: find all players with the best score\n",
+    "    winners = []\n",
+    "    for player in scores:\n",
+    "        if scores[player] == scores[best_player]:\n",
+    "            winners.append(player)\n",
+    "\n",
+    "    if len(winners) == 1:\n",
+    "        print (\"Only winner is:\", winners[0])\n",
+    "    else:\n",
+    "        tie = \", \".join(winners)\n",
+    "        print(\"Tie for win between:\", tie)\n",
+    "\n",
+    "def do_help():\n",
+    "    print('Commands:')\n",
+    "    print('help')\n",
+    "    print('  print list of commands')\n",
+    "    print('set <name> <score>')\n",
+    "    print('  updates score of player with given name')\n",
+    "    print('get <name>')\n",
+    "    print('  gets the score of player with given name')  \n",
+    "    print('print')\n",
+    "    print('  prints all the scores')\n",
+    "    print('high')\n",
+    "    print('  print high score')\n",
+    "    print('quit')\n",
+    "    print('  quit program')\n",
+    "\n",
+    "while True:\n",
+    "    cmd = input('enter a cmd (type \"help\" for descriptions): ')\n",
+    "    cmd = cmd.strip().lower().split(' ')\n",
+    "\n",
+    "    if cmd[0] == 'quit':\n",
+    "        break\n",
+    "    elif cmd[0] == 'help':\n",
+    "        do_help()\n",
+    "    elif cmd[0] == 'print':\n",
+    "        do_print()\n",
+    "    elif cmd[0] == 'set':\n",
+    "        do_set(cmd) # why do we pass cmd here?\n",
+    "    elif cmd[0] == 'get':\n",
+    "        do_get(cmd) # why do we pass cmd here?\n",
+    "    elif cmd[0] == 'high':\n",
+    "        do_high()\n",
+    "\n",
+    "print('exiting')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n",
+    "\n",
+    "We have practiced working with dictionaries, specificially working nested data structures: list of dictionaries, dictionary of dictionaries, and a dictionary of lists.  We have also practiced working with `get()` and `pop()` and passing in a default so they will not cause a key error."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/s25/Louis_Lecture_Notes/18_Dictionaries2/cs220_survey_data.csv b/s25/Louis_Lecture_Notes/18_Dictionaries2/cs220_survey_data.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5a0eb3c095988961ecdaba302d3afc56ac5704d5
--- /dev/null
+++ b/s25/Louis_Lecture_Notes/18_Dictionaries2/cs220_survey_data.csv
@@ -0,0 +1,979 @@
+Section,Lecture,Printed Copy,Age,Primary Major,Other Majors,Secondary Majors,Zip Code,Latitude,Longitude,Data Science Major,Pizza Topping,Cats or Dogs,Runner,Sleep Habit,Procrastinator,Song
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",,,,,,,,,,,,,,,,
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,20,Science: Physics,,,53726,43.0762,-89.409,No,sausage,cat,No,night owl,Maybe,The 
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,18,Science: Chemistry,,Physics,53703,,,Maybe,mushroom,dog,No,no preference,Yes,
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,20,Science: Other,,,53717,40.7128,-74.006,Maybe,sausage,cat,No,night owl,Yes,The Score - Money Run Low
+COMP SCI 319:LEC003,LEC003,Yes,24,Other (please provide details below).,Economics,,53703,30.5728,104.0668,No,pineapple,dog,Yes,early bird,Yes,Piano man Billy Joel
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Industrial,,,53706,40.71,-74,No,mushroom,dog,No,night owl,Yes,L.A. by Brent Faiyaz
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Biomedical,,,53706,38.9022,-77.0381,No,none (just cheese),dog,Yes,night owl,Yes,Risk - Gracie Abrams
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,22,Mathematics/AMEP,,,53703,43.2965,5.3698,No,mushroom,cat,No,night owl,Yes,false self - willow 
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,20,Computer Science,,,53718,43.0734,89.3865,Yes,sausage,dog,Yes,no preference,Yes,Fly Me to the Moon by Frank Sinatra
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Other (please provide details below).,Undecided,,53706,38.5849,-90.3762,No,none (just cheese),dog,No,night owl,Yes,Tequila Sunrise - The Eagles
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical,,,53706,44.5133,-88.0133,No,sausage,dog,No,early bird,Maybe,"Pursuit of Happiness, Kid Cudi"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,19,Statistics,,,,,,Yes,mushroom,,No,night owl,No,
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,18,Data Science,.,.,53703,40.7128,-74.006,Yes,basil/spinach,cat,No,night owl,Yes,justin bieber or ken carson
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Business: Finance,,Operations and Technology Management ,53706,41.8781,-87.6298,No,pepperoni,dog,Yes,night owl,Yes,Don’t have one
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",,,,,,,,,,,,,,,,
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,Yes,20,Business: Finance,,,53703,39.9042,116.4074,Maybe,mushroom,cat,Yes,early bird,Maybe,Country road
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,20,Computer Science,,,53726,37.5667,126.9783,Maybe,pepperoni,cat,No,night owl,Yes,Air - Ce matin-là
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,19,Data Science,,,53703,22.3964,114.1095,Yes,mushroom,neither,Yes,no preference,Maybe,just Friend
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,,Science: Physics,,,53715,43.0739,-89.3852,No,pepperoni,cat,Yes,night owl,Yes,"People Change, by Little Hurt"
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,Yes,20,Data Science,,,53703,42.359,-71.0586,Maybe,pineapple,dog,No,night owl,Yes,"tyler, the creator"
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Science: Biology/Life,Neurobiology,Psychology,53715,40.7128,-74.006,Yes,sausage,dog,No,night owl,No,"Cold Summer, Fabulous "
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,19,Engineering: Biomedical,N/A,considering neurobiology,53706,43.3178,88.379,No,sausage,dog,No,night owl,Yes,Big iron by Marty Robbins
+COMP SCI 319:LEC001,LEC001,Yes,24,Computer Science,,,53726,40.7128,-74.006,No,macaroni/pasta,cat,No,early bird,Yes,Yellow Submarine by the Beatles
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Engineering: Biomedical,,,53705,21.1619,-86.8515,No,sausage,dog,Yes,night owl,Yes,dreams by fleetwood mac
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,,Engineering: Mechanical,,,53715,28.5383,-81.3792,No,sausage,cat,Yes,night owl,Yes,Ain't It Fun - Paramore
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,21,Data Science,economics,,,,,Yes,sausage,dog,Yes,night owl,Maybe,
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Data Science,Psychology,Data science,53715,41,120,Yes,pepperoni,dog,No,night owl,Yes,I like you ---Doja Cat
+COMP SCI 319:LEC004,LEC004,No,26,Data Science,,,53715,40.7128,-74.006,Yes,mushroom,dog,Yes,night owl,Yes,Young and Beautiful-- Lana Del Rey song
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Other,,,53706,13.7563,100.5018,No,pepperoni,cat,No,night owl,Yes,Again - Fetty Wap (clean version)
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,18,Engineering: Mechanical,,,53715,34.0126,-118.4371,No,none (just cheese),dog,No,night owl,Yes,Young Free and Single - Frank Jade
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,19,Statistics,,Economics,53706,40.7128,-74.006,No,none (just cheese),cat,No,no preference,Yes,"Song: Fly Me To The Moon
+
+By: Frank Sinatra"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,22,Other (please provide details below).,information science,I have a certificate from the university in computer science,53175,26.642,409.9576,No,none (just cheese),cat,No,night owl,Yes,She Burns away - Briscoe EP
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,Yes,19,Data Science,,,,43.0945,-87.8975,Yes,green pepper,dog,No,night owl,Yes,No Pole by Don Toliver
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,20,Other (please provide details below).,Information Systems,,53726,46.5935,7.9091,Yes,green pepper,cat,No,night owl,Maybe,Feel Good Inc. by Gorillaz
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,21,Other (please provide details below).,Information Science,,53703,43.0389,-87.9065,No,sausage,neither,No,night owl,Yes,D4VD
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Biomedical,,,53706,42.3314,-83.0458,No,pepperoni,dog,Yes,night owl,Maybe,fortnite lobby music
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,20,Science: Biology/Life,,Statistics,53703,31,121,No,sausage,neither,No,night owl,Yes,love story taylor swift
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,20,Data Science,,Pre-Business planning on doing Operation and Technology Management.,53715,38.9072,-77.0369,Yes,sausage,dog,No,no preference,Maybe,Taste by Sabrina Carpenter
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,19,Data Science,,,53706,23.3,113.8,Yes,pineapple,cat,Yes,night owl,Maybe,"----------------------
+Kehlani, “After Hours”
+----------------------"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,19,Engineering: Mechanical,,,53706,37.1,25.4,No,sausage,cat,Yes,night owl,Yes,"We Major
+
+Kanye West"
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,pepperoni,cat,No,early bird,Yes,Will I See You Again? - Thee Sacred Souls
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,21,Science: Other,N/A,I intend to declare a Data Sciences major as my second major. ,53706,39.9042,116.4074,Yes,pineapple,dog,No,night owl,Yes,I Love You - Riopy
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,18,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,pepperoni,dog,No,night owl,Yes,Learning to Flt - Tom Petty
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,20,Computer Science,,Data Science,53706,-1.2921,36.8219,Yes,pepperoni,cat,Yes,no preference,Yes,"Verdansk, Dave"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,Yes,21,Other (please provide details below).,Economics,Data Science Certificate,53703,37.2489,-121.9452,No,pepperoni,dog,Yes,night owl,Yes,One of my favorite songs of all time is Hotel California by The Eagles.
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,18,Engineering: Mechanical,,,53706,43.0712,-89.3981,Maybe,basil/spinach,dog,No,night owl,Yes,
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,20,Other (please provide details below).,,"Economics, data science",53703,40.7128,-74.006,Maybe,green pepper,dog,No,early bird,No,lil tjay
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,,Other (please provide details below).,,,53703,39,116,Yes,pineapple,dog,Yes,no preference,Yes,Taylor Swift
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,19,Engineering: Other,N/A,N/A,53706,41.3851,2.1734,No,sausage,dog,No,night owl,Yes,Broken Window Serenade
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,19,Business: Information Systems,,,53703,,,No,basil/spinach,dog,Yes,night owl,Yes,Weston estate -water
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Mechanical,,,53706,40.7,74,No,sausage,cat,No,night owl,Yes,She Will lil wayne
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,20,Data Science,,,53703,-34.6037,-58.3816,Yes,mushroom,dog,No,night owl,Yes,Christ Is Enough - Hillsong Worship
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,19,Engineering: Biomedical,,,,,,,,,,,,Any SZA song or country song ever
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,Yes,21,Mathematics/AMEP,,I do have data science and stats in minors.,53703,48.8566,2.3522,Yes,pepperoni,dog,Yes,night owl,Yes,"Recently, it would be 'Always' by Yoon Mi-rae. It's a Korean song."
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,18,Other (please provide details below).,,,,53706,-89.3852,Yes,pineapple,cat,Yes,night owl,Yes,love story
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC002,Yes,18,Engineering: Mechanical,,Philosophy,53706,,-89.4012,No,macaroni/pasta,dog,Yes,no preference,Yes,Bob Marley!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,19,Engineering: Mechanical,,,53726,41.8781,-87.6298,No,pepperoni,dog,Yes,early bird,Yes,Can't Tell Me Nothing by Kanye West
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,No,20,Data Science,,Possibly neurobiology,53715,41.8781,-87.6298,Yes,sausage,cat,No,night owl,Yes,Walk This Way by Aerosmith
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,18,Data Science,didn't select,I'm also majoring in Economics. ,53706,41.881,-87.623,Yes,none (just cheese),dog,Yes,night owl,Maybe,Hey Driver By Zach Bryan 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Engineering: Biomedical,n/a,n/a,53706,41.4979,-88.2313,No,sausage,dog,Yes,early bird,Maybe,NISSAN ALTIMA by Doechii
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,21,Science: Other,,,53702,43.0722,89.4008,No,pepperoni,dog,Yes,early bird,Yes,Some Nights by FUN
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,21,Statistics,,,53706,30.0023,120.5681,Maybe,pepperoni,neither,Yes,night owl,Yes,"The First Snow
+
+by EXO"
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Other,Materials Science and Engineering,no,53703,59.321,18.072,No,pepperoni,dog,Yes,night owl,Yes,Kingslayer (Feat. BABYMETAL) this ain't never getting played
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,21,Business: Finance,,,53715,51.5074,-0.1278,No,basil/spinach,cat,Yes,night owl,Yes,Hotel California by the Eagles
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,19,Engineering: Mechanical,,,57303,10,20,No,pepperoni,cat,No,night owl,No,Born in the USA - Bruce Springsteen
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,20,Computer Science,,,53705,37.5,121.4737,Maybe,pepperoni,cat,Yes,early bird,Yes,"Der Hexenkönig
+
+HyperGryph · 2023"
+COMP SCI 319:LEC003,LEC003,No,23,Other (please provide details below).,Agricultural and Applied Economics.,,53713,39.9042,116.4074,No,pepperoni,cat,No,night owl,Yes,"Hotel California
+
+Eagles"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,21,Computer Science,,Data Science,53703,37.7749,-122.4194,Yes,pineapple,cat,Yes,night owl,Yes,rookie by knock2
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,43.0798,-89.5482,No,sausage,dog,Yes,early bird,No,Welcome to the Jungle by Guns n' Roses
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,21,Other (please provide details below).,Personal Finance,,53703,40.7536,-73.9992,Yes,pepperoni,dog,No,night owl,Yes,That's so True by Gracie Abrams 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC001,Yes,20,Other (please provide details below).,Information Science,Data Science (possibly),53706,25.7617,-80.1918,Yes,macaroni/pasta,dog,Yes,night owl,Yes,august by Taylor Swift
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,19,Other (please provide details below).,I am majoring in Economics and Statistics.,"Economics, Statistics",53715,59.3293,18.0686,Maybe,pepperoni,cat,No,night owl,Yes,Snowman by Sia
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,20,Other (please provide details below).,Information Science ,,53703,41.8781,-87.6298,No,none (just cheese),dog,No,no preference,Yes,"Cold Damn Vampires, Zach Bryan "
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,21,Other (please provide details below).,Information Science,N/A,53713,41.8781,-87.6298,Maybe,pepperoni,dog,Yes,early bird,Yes,"I do not have a favorite song, but favorite artist would probably be Travis Scott"
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,19,Computer Science,,,53715,31.14,121.29,Maybe,mushroom,cat,Yes,night owl,Yes,if looks could kill by chrissy costanza
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,22,Computer Science,"My primary major is Information Science, however, I am doing a Computer Science Certificate. ",,53711,25.2048,55.2708,No,pineapple,dog,No,early bird,Yes,Til Further Notice - Travis Scott & 21 Savage
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,21,Business: Other,,,53715,40.9807,-73.6838,No,pepperoni,dog,No,early bird,No,Everywhere Fleetwood Mac
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,22,Computer Science,.,.,53715,35.8687,128.605,Maybe,none (just cheese),neither,No,night owl,Maybe,Hello - Luther Vandross
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,18,Engineering: Industrial,,,53706,56.3217,-2.716,No,none (just cheese),dog,Yes,night owl,Yes,Guy for That by Post Malone and Luke Combs
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Other,,,53706,44.7316,-73.3937,No,pineapple,dog,No,night owl,Yes,Maine - Noah Kahan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,22,Data Science,,,53706,37.5665,126.978,Maybe,pepperoni,dog,No,night owl,Yes,Smells like teen spirit - nirvana
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,18,Engineering: Biomedical,,,53706,43.3209,-1.9845,Maybe,basil/spinach,dog,No,night owl,Yes,Stick Season by Noah Kahan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,18,Other (please provide details below).,undecided,,53706,48.8566,2.3522,Yes,none (just cheese),neither,No,night owl,Maybe,"Typa girl, by BLACKPINK"
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,-43.5321,172.6362,No,pepperoni,cat,No,night owl,Yes,You Got Me by The Roots & Erykah Badu 
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,No,20,Business: Finance,N/A,"Mathematics, Finance",53703,44.8511,-93.4773,No,sausage,dog,Yes,night owl,Maybe,SUPERPOSITION - Daniel Caesar
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,20,Other (please provide details below).,Econ,,53703,36.7783,-119.4179,Maybe,pepperoni,cat,No,night owl,Yes,Gracie Abrams - That's so True
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Mathematics/AMEP,,,53703,-2.9001,-79.0059,Yes,green pepper,dog,Yes,night owl,Yes,I will Survive Gloria Gainor
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,20,Business: Finance,N/A,Data Science Certificate,53706,32.7765,-79.9311,No,sausage,dog,Yes,early bird,Yes,Race My Mind-Drake
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,,Computer Science,,,63706,0,0,Maybe,mushroom,dog,Yes,night owl,Yes,jump around
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,18,Data Science,,"Math, Stats",53706,38.6083,-90.1813,Yes,pepperoni,dog,Yes,night owl,Yes,"Search & Rescue
+
+By:Drake"
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,21,Business: Finance,,,53703,27.6233,-80.3893,No,pepperoni,dog,No,night owl,Yes,"FourFiveSeconds, Rihanna, Kanye West"
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,21,Other (please provide details below).,Information Science ,,53703,35.0116,135.768,Maybe,Other,cat,Yes,early bird,No,"Say It Right, Nelly Furtado "
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,19,Engineering: Mechanical,,,53703,21.4055,-157.7402,No,pepperoni,dog,Yes,early bird,Yes,"More - Bobby Darin
+
+ "
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,Yes,21,Computer Science,,,53715,34.0522,-118.2437,No,sausage,dog,No,night owl,No,Dehors
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,21,Mathematics/AMEP,,,53715,30,120,Yes,none (just cheese),cat,No,night owl,Yes,Clean by Taylor Swift
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,18,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,pineapple,cat,No,no preference,Maybe,dtmf by Bad Bunny
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,18,Engineering: Other,,"Data science, computer science",53706,44.3154,-89.902,Maybe,pepperoni,dog,No,night owl,Yes,Hozier -> From Eden
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,19,Other (please provide details below).,Political Science,,53706,41.8818,87.6298,No,none (just cheese),neither,No,night owl,Yes,"Sprinter, Dave & Central Cee"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,25,Data Science,,,53703,41.8781,-87.6298,Yes,pepperoni,neither,No,early bird,No,REBEL HEART - IVE
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,21,Data Science,,,53703,18.4562,-67.1221,Yes,pepperoni,cat,No,night owl,Yes,NuevaYol - Bad Bunny
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Mechanical,,,53706,20.6296,-87.0739,No,pepperoni,cat,Yes,night owl,Yes,Yellow by coldplay
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,18,Engineering: Biomedical,,,53706,40.7128,-74.006,Maybe,sausage,cat,No,night owl,Yes,Art House by Malcolm Todd
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,19,Engineering: Mechanical,,,53589,31.7684,35.2137,No,pepperoni,dog,Yes,night owl,Yes,"Rompe la Piñata, Voces Infantiles"
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,20,Mathematics/AMEP,,,53703,30.2741,120.1551,No,pineapple,cat,No,night owl,Maybe,"Coming Home
+
+Peter Jeremias"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,18,Business: Finance,,,63117,51.1785,-115.5743,Yes,pepperoni,dog,No,night owl,Yes,Iris - The Goo Goo Dolls
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,19,Engineering: Mechanical,,,53706,43.7401,7.4266,No,none (just cheese),dog,No,night owl,Yes,Crooked Smile - J Cole
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,18,Other (please provide details below).,I am not sure. ,,53706,22.1987,113.5439,Maybe,sausage,cat,No,night owl,Yes,Happiness is a butterfly - Lana Del Rey
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,20,Other (please provide details below).,Economics,,53703,39.4698,-106.0492,Yes,sausage,dog,No,night owl,Yes,Sundream by Rufus Du Sol
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,Yes,21,Data Science,Data Science,,53703,30,,Yes,sausage,dog,No,early bird,Yes,Justin Biber
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,19,Computer Science,,,53715,40.0384,-76.1078,No,mushroom,cat,No,night owl,Yes,エータ・ベータ・イータ - ルゼ （Eta Beta Eta - LUZE)
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,20,Science: Biology/Life,,Data Science,53706,43.0775,-89.4122,Maybe,pineapple,cat,No,night owl,Yes,Redbone - Childish Gambino
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,21,Data Science,,,53703,18.3381,-64.8941,Yes,pepperoni,dog,No,no preference,Yes,"I like It, by Debarge"
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Other,,,53718,45.9409,89.4957,No,pepperoni,dog,No,night owl,Yes,
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,21,Other (please provide details below).,Personal finance ,,53703,43.0722,89.4008,No,pineapple,dog,No,night owl,Yes,"Fast car, Luke combs"
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,Yes,21,Science: Other,,Classical humanities,53703,44.9291,-87.1967,No,none (just cheese),cat,No,no preference,No,Avalyn I by Slowdive
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC004,No,19,Computer Science,,,53703,26.2146,78.1827,Maybe,mushroom,dog,No,night owl,Yes,"MOCKINGBIRD , eminem"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,20,Data Science,,I am also an Economics major. ,53703,41.8781,-87.6298,Yes,pepperoni,cat,Yes,night owl,Yes,"""Me and Your Mamma"" by Childish Gambino "
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,21,Data Science,,,53715,23.1291,113.2644,Yes,pepperoni,dog,No,night owl,Yes,luther - Kendrick Lamar & SZA
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,Yes,20,Business: Finance,,Information systems,53711,-6.1751,106,No,pineapple,dog,Yes,night owl,Yes,Kelis
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,18,Engineering: Biomedical,,no,53706,43.0731,-89.4012,No,pineapple,cat,Yes,no preference,Yes,Any bonjovi music
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,20,Engineering: Mechanical,,,53715,41.8781,-87.6298,No,sausage,dog,No,night owl,Yes,"Hypnotize, System of a Down"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,17,Data Science,None,Data Sciemce,53715,35.4532,-82.2871,Yes,green pepper,dog,Yes,night owl,Yes,Astronomy
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,20,Engineering: Mechanical,,,53715,110.7624,43.4799,No,pineapple,dog,Yes,night owl,No,
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,Yes,18,Engineering: Biomedical,,,53706,44.9778,-93.265,No,sausage,dog,Yes,no preference,Yes,Linger by The Cranberries
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,18,Science: Chemistry,,Possibly data science?,53706,32.7157,-117.1611,Yes,basil/spinach,dog,Yes,early bird,Yes,Vienna by Billy Joel
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,18,Business: Finance,,Data Science Certificate,53706,34.0736,-118.4004,Maybe,pepperoni,dog,Yes,night owl,Yes,We are young - by fun.
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,20,Computer Science,,"I am double majoring, and Data Science is my other major",53715,36.3932,25.4615,Yes,sausage,cat,Yes,early bird,No,Lovesick by Laufey
+COMP SCI 319:LEC003,LEC003,No,26,Data Science,,,53703,30.5728,104.0668,No,basil/spinach,dog,Yes,early bird,Maybe,"Billy Joe
+
+Piano man"
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Biomedical,,,53706,45.4408,12.3155,No,pepperoni,dog,Yes,no preference,No,Luther by SZA and Kendrick Lamar
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,18,Other (please provide details below).,Computer Science,Data Science ,53706,35.6762,139.7636,Yes,pepperoni,dog,Yes,night owl,Yes,Who Knows Who Cares - Local Natives
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,19,Engineering: Mechanical,,,53706,48.8566,2.3522,Maybe,pepperoni,dog,No,no preference,Yes,"""That's What I Like"" - Bruno Mars"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,18,Science: Physics,,Astrophysics,53706,42.9665,-88.0032,No,sausage,dog,Yes,early bird,No,Where the Wild Things Are by Luke Combs
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,22,Statistics,Statistics ,Economics,53715,31.299,120.5853,Maybe,tater tots,cat,No,night owl,Maybe,Someone like you - Adele
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,41.9028,12.4964,Maybe,pepperoni,cat,No,night owl,Yes,"The Marías-Cariño
+
+The Killers-Jenny was a friend of mine"
+COMP SCI 319:LEC004,LEC004,Yes,24,Business: Information Systems,,,53705,22.9995,120.2293,Yes,macaroni/pasta,dog,No,night owl,Yes,None
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Data Science,,Economic,53703,22.3964,114.1095,Yes,pineapple,neither,No,night owl,Yes,Love yourself- Justin Bieber
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,19,Mathematics/AMEP,,,53715,44.7439,-93.2171,No,sausage,dog,Yes,night owl,Yes,Viva La Vida by Coldplay
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,20,Other (please provide details below).,Undecided major,N/A,53703,37.5665,126.978,Maybe,Other,dog,No,early bird,No,Luther by Kendrick Lamar
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,20,Business: Finance,N/A,Data Science,53703,37.5665,37.5665,Maybe,pepperoni,cat,No,night owl,Yes,I had some help - Post Malone
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,Yes,18,Computer Science,,,53706,48.8566,2.3522,Yes,pepperoni,cat,Yes,early bird,Maybe,The Unforgiven by Metallica
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,Yes,19,Business: Finance,,Statistics,53703,32.0853,34.7818,Maybe,none (just cheese),dog,Yes,night owl,Yes,Phoenix by A$AP Rocky
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Biomedical,,,53706,36.1699,-115.1398,No,sausage,dog,No,no preference,Maybe,My favorite song is What I've Done by Linkin Park.
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,18,Engineering: Biomedical,,,53706,48.8566,2.3522,No,sausage,dog,No,no preference,Maybe,Sunday Morning - Maroon 5
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,20,Other (please provide details below).,"Design, Innovation, and Society",,53706,40.7128,-74.006,Maybe,none (just cheese),dog,No,no preference,Maybe,You Are Enough - Sleeping At Last
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Biomedical,,,53706,41.8988,12.5024,No,sausage,dog,No,no preference,No,Nine Ball by Zach Bryan
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Business: Finance,,,53703,37.9838,23.7275,Maybe,pepperoni,neither,No,early bird,Yes,Redbone- Childish Gambino
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,Yes,18,Engineering: Biomedical,,,53706,39.6635,-106.6218,No,pepperoni,dog,No,night owl,No,One of These Mornings - Zeds Dead
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,18,Business: Actuarial,,,53706,48.8647,2.349,Maybe,none (just cheese),dog,Yes,night owl,Maybe,I remember everything by Zach Bryan
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,,Engineering: Mechanical,,,53706,44.86,-92.63,No,pepperoni,dog,Yes,night owl,Yes,"still standing, Elton john"
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,20,Other (please provide details below).,Economics,Personal Finance,53715,60.8608,7.1118,No,pineapple,dog,No,night owl,No,"""Sultans of Swing"" - Dire Straits"
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,19,Statistics,,,53715,42.3601,-71.0589,No,pepperoni,dog,No,no preference,Maybe,Colder Weather - Zac Brown Band 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,19,Other (please provide details below).,My primary major is Economics. ,data sciences,53703,33,107,Yes,pineapple,neither,No,night owl,Yes,《BYE BYE BYE》lovestoned
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,19,Engineering: Industrial,,,53703,51.5074,-0.1278,No,pineapple,dog,Yes,early bird,Yes,Julia - SZA
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Mechanical,,,53706,44.1874,-89.8742,No,sausage,dog,No,night owl,Yes,"We Are Young (feat. Janelle Monae), by Fun."
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,18,Engineering: Mechanical,,,53706,-25.4075,-49.2825,No,Other,dog,No,no preference,No,Xtal by Aphex Twin
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Industrial,,,53715,43.3328,-88.0074,No,sausage,cat,Yes,early bird,No,Any song by the eagles
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,19,Engineering: Mechanical,,,53703,38.5394,-0.1912,Maybe,pepperoni,dog,No,night owl,Yes,Beautiful Things Benson Boone 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,20,Data Science,,,53703,41.8781,87.6298,Yes,pepperoni,dog,No,night owl,Yes,More Than My Hometown by Morgan Wallen
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,19,Statistics,,Music,53715,44.9778,-93.265,Maybe,pepperoni,cat,No,night owl,Yes,"Texas Blue, Quadeca"
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,19,Other (please provide details below).,Economics,N/A,53703,44.8897,93.3499,Maybe,none (just cheese),dog,No,night owl,Maybe,Erase Me - Kid Cudi
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,21,Engineering: Other,Materials Science and Engineering ,none,53703,-23.01,-44.31,No,basil/spinach,dog,No,early bird,Maybe,halo - beyonce 
+COMP SCI 319:LEC001,LEC001,No,25,Engineering: Biomedical,no,no,53705,30,30,Maybe,pineapple,dog,Yes,no preference,Yes,SULONG WANG
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,Yes,18,Other (please provide details below).,Economics ,Data Science,53706,12.9716,77.5946,Yes,pepperoni,dog,No,night owl,Maybe,Where is my mind-pixies
+COMP SCI 319:LEC002,LEC002,Yes,26,Data Science,INTERNATIONAL PUBLIC AFFAIRS,,53593,43.7696,11.2558,Maybe,mushroom,dog,Yes,night owl,Yes,"Sam Smith Say it first
+
+Sam Smith  Too Good At GoodByes"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Computer Science,,,53703,43.0718,-89.3949,No,Other,dog,Yes,night owl,Yes,DragonForce - Ashes of the Dawn
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,19,Business: Finance,Don‘t make sure,nope,53707,1,1,Maybe,macaroni/pasta,dog,No,no preference,No,Girls Want Girls
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,18,Engineering: Biomedical,,,53706,42.3601,-71.0589,No,pepperoni,cat,Yes,early bird,Yes,"Walking on Sunshine, katrina and the waves "
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,24,Computer Science,,Psychology,53715,42.3601,-71.0589,Maybe,pepperoni,cat,No,night owl,Yes,"Pink Pony Club, Chappel Roan (but specifically the Plankton version)"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,18,Science: Physics,,,53706,41.9028,12.4964,Maybe,sausage,cat,No,no preference,Yes,Don't Stop Believin' - Journey
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,19,Engineering: Mechanical,,,53703,53.23,-9.71,No,pepperoni,dog,No,night owl,Yes,"Here Today, The Chameleons"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,35,Other (please provide details below).,Genetics and Genomics,Data Science,53706,8.815,108.4755,Yes,Other,neither,No,night owl,Yes,The Final Countdown
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,21,Other (please provide details below).,其实我到现在还没决定我的专业。但我可能会选择信息科学。,,53706,-37.8136,144.9631,Maybe,pineapple,cat,Yes,no preference,Maybe,Anyone Crystal_Bats
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,22,Computer Science,,Data Science,53703,40.7128,151.2093,Yes,Other,dog,No,early bird,No,"Mozart, Don Giovanni.
+
+ "
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,,Data Science,,,53706,37,126,Yes,pineapple,dog,No,night owl,Yes,"I like K-pop. And Enhypen is my favorite group. My favorite song is ""No Doubt"" from Enhypen. I will be so excited if this song is played before class starts!"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,22,Engineering: Mechanical,,,53726,45.6927,-90.4011,No,sausage,cat,No,night owl,Yes,Ten Years Gone - Led Zeppelin 
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Other,,,53706,41.0082,28.9784,No,basil/spinach,cat,Yes,early bird,Yes,5 dollar pony rides - Mac Miller
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,,Other (please provide details below).,Economics,Data Science,53706,10.8231,106.6297,Yes,sausage,dog,No,night owl,Yes,Girl with the tattoo enter - Miguel
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,22,Other (please provide details below).,Economics,Data science,53703,37.5665,126.978,Yes,mushroom,cat,No,early bird,Maybe,Sting - shape of my heart
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical,,,53706,39.0742,21.8243,No,mushroom,dog,No,night owl,Yes,CHIHIRO - Billie Eilish
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,19,Other (please provide details below).,Astronomy-Physics,,53706,48.1771,16.3806,Maybe,green pepper,dog,No,night owl,Yes,Speed the Collapse - Metric
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,,Science: Other,,,53715,48.8566,2.3522,No,basil/spinach,dog,No,no preference,Maybe,Delicate by Taylor Swift
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,24,Computer Science,,,53703,41.8,-87.6298,No,pepperoni,neither,No,no preference,No,Babymonster - Drip
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,18,Other (please provide details below).,Economics,,53706,34.6937,135.5022,No,basil/spinach,cat,No,night owl,Yes,Brazil by Declan McKenna 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,19,Engineering: Mechanical,,,53706,41.3851,2.1734,No,pepperoni,dog,No,night owl,Yes,Summertime Sadness (Lana Del Rey Vs. Cedric Gervais) - Cedric Gervais Remix
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,21,Statistics,Statistics ,Mathematics,53703,30,121,Maybe,sausage,neither,No,night owl,Yes,"Risk It All, Jason Zhang"
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,18,Other (please provide details below).,Currently a pre business student but looking to apply to the engineering school,,53706,51.1802,-115.5657,Maybe,macaroni/pasta,dog,Yes,no preference,Yes,"Younger Years Zach Bryan
+
+Chase Her Baily Zimmerman
+
+Big Country music guy"
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,18,Science: Physics,,,53706,46.7828,-92.1055,Maybe,none (just cheese),cat,No,night owl,No,"Love’s Train 
+
+Bruno Mars, Anderson .Paak, Silk Sonic"
+COMP SCI 319:LEC002,LEC002,Yes,22,Science: Other,,,53726,47.6062,-122.3321,No,Other,dog,Yes,no preference,Maybe,"Fast Car - Luke Combs cover
+
+Blinding Lights - The Weeknd
+
+Alley Rose - Conan Grey
+
+Iris - Goo Goo Dolls, preferably Live Buffalo version
+
+Highwayman - the Highwaymen (Johnny Cash, Willie Nelson, Kris Kristoferson, Waylon Jennings)
+
+Dream Lantern - RADWIMPS <English version, not Japanese
+
+Help! - The Beatles
+
+Crimson and Clover - Joan Jett
+
+Tiny Dancer - Elton John"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC001,Yes,19,Science: Physics,physics ,,53717,28.2199,112.9175,No,sausage,neither,Yes,night owl,Yes,春雷  Yonezu Kenshi
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,21,Engineering: Industrial,,,53703,40.7128,-74.006,No,basil/spinach,dog,No,night owl,Yes,Favourite by Fontaines D.C.
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,19,Other (please provide details below).,Economics,Nope,53706,39.93,116.38,Maybe,sausage,dog,No,no preference,Maybe,Blank Space by Taylor Swift
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,19,Business: Actuarial,,,53711,43.0389,-87.9065,No,pepperoni,cat,Yes,early bird,Yes,Counting Stars- One Republic
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,,Other (please provide details below).,neurobiology,,53715,23.1291,113.2644,No,none (just cheese),dog,Yes,no preference,Maybe,head in the clound by hayd
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,20,Other (please provide details below).,History,Biology,53706,39.9524,-75.1636,No,pepperoni,dog,No,night owl,Yes,"""Man on the Moon"" - Zella Day"
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,20,Computer Science,,,53715,45.4408,12.3155,No,Other,cat,No,night owl,Yes,The Fine Print by The Stupendium
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,19,Data Science,,,53706,39.3377,-83.3528,Yes,none (just cheese),dog,No,no preference,Yes,You're So Vain by Carly Simon
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,18,Other (please provide details below).,Undecided major - just exploring some areas of possible interest. ,n/a,53706,39.0699,-77.1847,Maybe,pepperoni,dog,Yes,night owl,Yes,Something in the way you move - Ellie Goulding
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,18,Engineering: Biomedical,,,53706,39.0742,21.8243,No,pepperoni,dog,No,night owl,Yes,Shirt by SZA
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,19,Business: Actuarial,,Risk Management & Insurance,53703,34.8697,-111.7609,No,pepperoni,dog,Yes,no preference,Yes,"All Star, Smash Mouth"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,20,Business: Finance,,,53703,42.3601,-71.0589,No,Other,dog,No,no preference,Maybe,(Don't Fear) The Reaper - Blue Oyster Cult
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,20,Engineering: Mechanical,n/a,n/a,53726,43.6275,89.7661,Yes,Other,cat,No,early bird,No,Why Georgia - John Mayer
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,22,Business: Other,,Political science,53715,25.033,121.5654,Maybe,none (just cheese),cat,Yes,early bird,Maybe,Everything Sucks / Vaultboy
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,Yes,19,Other (please provide details below).,Political Science ,,53706,41.8781,87.6298,Maybe,none (just cheese),dog,Yes,night owl,Yes,Pyramids by Frank Ocean
+COMP SCI 319:LEC003,LEC003,No,24,Computer Science,,,53705,-3.846,-32.412,Yes,pepperoni,dog,No,early bird,No,
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,No,20,Data Science,,,53715,31.2304,121.4737,Yes,mushroom,cat,No,night owl,Yes,Exhale
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,20,Engineering: Industrial,,,53703,41.8781,-87.6298,No,pepperoni,dog,Yes,early bird,Yes,Sunflower - Post Malone (feat. Swae Lee)
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,18,Data Science,,,53706,44.8653,-93.367,Yes,pineapple,dog,No,night owl,Yes,When the sun goes down - Arctic Monkeys
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,19,Computer Science,,,53706,28.7041,77.1025,Maybe,Other,dog,No,no preference,Yes,Sailor Song by Gigi Perez
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,Yes,20,Computer Science,,,53703,57.697,11.9865,No,mushroom,cat,No,no preference,No,Julia - Yellow Ostrich
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,19,Computer Science,,Information Systems,53703,41.8781,-87.6298,No,Other,dog,No,no preference,Maybe,"Hey Jude, The Beatles"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,22,Other (please provide details below).,Psychology,Information Science,53703,32.0603,118.7969,No,mushroom,neither,No,night owl,Yes,Wasteland - Royal & The Serpent
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,23,Science: Physics,Not applicable,Not applicable,53706,43.07,-89.4,No,pepperoni,dog,No,night owl,Yes,"Deference for Darkness, Marty O'Donnell"
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,20,Computer Science,,,53715,46.1129,-89.6445,Maybe,pepperoni,dog,No,night owl,Yes,Mr.Brightside by The Killers
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,19,Business: Actuarial,,,53715,3.1279,101.5945,Maybe,none (just cheese),cat,Yes,early bird,Yes,'lock/unlock' by jhope (ft. benny blanco)
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Science: Physics,Physics,Astronomy,2420,42,71,Maybe,basil/spinach,dog,No,night owl,Maybe,Somebody Else by 1975
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Engineering: Mechanical,,,53706,23.032,113.1181,No,none (just cheese),dog,Yes,no preference,Maybe,富士山下-陈奕迅
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical,N/A (I can't submit the quiz unless there is an answer in this field),N/A (I can't submit the quiz unless there is an answer in this field),53706,40.7128,-74.006,No,Other,dog,No,night owl,No,"""Biking"" - Frank Ocean, JAY-Z, Tyler, The Creator"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,20,Other (please provide details below).,Global Health,,53715,50.5486,-4.586,No,green pepper,cat,No,no preference,Yes,Jackie and Wilson by Hozier
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,21,Other (please provide details below).,Economics,Political Science,53703,3.1409,101.6932,Maybe,sausage,cat,No,early bird,Yes,Selfless by The Strokes
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,Yes,21,Other (please provide details below).,Consumer Behavior and Marketplace Studies,,53703,41.8781,-87.6298,No,pepperoni,dog,No,early bird,No,This is the life by Amy Macdonald
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,19,Statistics,,psychology,53706,48.8566,2.3522,No,sausage,neither,No,night owl,Yes,"The other side of paradise
+
+Glass animals"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC002,Yes,20,Data Science,,"Math,Computer science,Statistic",53706,30.2741,120.1551,Yes,sausage,dog,No,early bird,Maybe,Divina Commedia by GD
+COMP SCI 319:LEC003,LEC003,Yes,24,Engineering: Biomedical,,,53705,44.8113,-91.4985,No,sausage,dog,No,early bird,Yes,"Summer, Highland Falls - Billy Joel"
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,20,Business: Other,,,53716,49.0835,19.2818,No,pepperoni,cat,No,no preference,Yes,Ides of March by Silverstein
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,18,Other (please provide details below).,information science,Fashion Design,53706,35.0077,135.7471,Maybe,pepperoni,dog,No,night owl,Maybe,Apple Cider by Beabadoobee
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,20,Engineering: Other,Civil Engineering,N/A,53218,35.2271,-80.8431,No,mushroom,dog,No,early bird,Maybe,One of my favorite songs at the moment is Oscar winning tears by Raye.
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,20,Business: Finance,,Risk Managment and Insurance,53703,46.4676,10.3782,No,pineapple,dog,Yes,night owl,Yes,"Title: Stargazing 
+
+Artist: Myles Smith
+
+ "
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,19,Engineering: Biomedical,N/A,N/A,53715,39.7392,-104.9903,No,pineapple,dog,No,night owl,Yes,Why Why Why - Shawn Mendes
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,Yes,19,Engineering: Mechanical,,,53562,35.7242,139.7976,No,mushroom,neither,No,night owl,Maybe,Flashback by Miyavi
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,Yes,19,Science: Other,Pharmacy -toxicology ,,53706,48.1351,11.582,No,pepperoni,dog,No,night owl,Yes,toosii - favorite song
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,19,Other (please provide details below).,Undecided now,,53703,31.299,120.5853,Yes,pineapple,cat,No,night owl,Yes,Love story
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,19,Science: Physics,,,53706,24.8801,102.8329,No,pineapple,neither,Yes,early bird,Yes,Cello Concerto in E Minor by Jacqueline du Pre
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,20,Science: Other,Astrophysics,,53715,36.3932,25.4615,Maybe,pepperoni,dog,Yes,night owl,Maybe,Da Fonk (feat. Joni) - Mochakk
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,19,Engineering: Biomedical,,,53703,39.0968,120.0324,No,pepperoni,dog,No,no preference,No,Blood Bank - Bon Iver
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,21,Engineering: Other,,,53711,25,55,No,pepperoni,dog,No,night owl,Yes,Freebird - Lynyrd Skynyrd
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,18,Engineering: Biomedical,,,53706,43.0731,-89.4012,No,pepperoni,dog,Yes,no preference,No,Love Lost by Mac Miller
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,Yes,20,Data Science,,,53703,30.25,120.16,Yes,pineapple,dog,No,night owl,Yes,Regular Friends By David Tao
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,44.9355,-88.1572,No,pepperoni,dog,Yes,night owl,Yes,River - Leon Bridges
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Other,,,53706,45,92,No,pineapple,dog,Yes,night owl,Yes,"Misty mountains by The Wellerman
+
+or 
+
+I See Fire vinny marchi and bobby bass"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,Yes,18,Engineering: Other,,,53703,41.9028,12.4964,No,sausage,cat,Yes,night owl,Yes,Jupiter from The Planets by Gustav Holst
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,20,Engineering: Industrial,,Computer Science,53706,26.8206,30.8025,Maybe,basil/spinach,dog,Yes,no preference,Maybe,"""In the stars"" : Benson Boone"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,,Data Science,,Cartography & GIS,53706,59.9138,10.7387,Yes,pepperoni,dog,No,night owl,Yes,"No Woman No Cry (live at the Lyceum, London, 1975), Bob Marley & The Wailers"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Engineering: Mechanical,,,53706,47.6062,-122.3321,Maybe,pepperoni,cat,No,night owl,Yes,O Valencia! by The Decemberists
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,20,Other (please provide details below).,Economics,,53703,43.07,-89.4,Yes,pepperoni,dog,No,night owl,Yes,Otherside - Red Hot Chilli Peppers
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,19,Business: Other,,,53706,43.0666,-89.3993,No,pepperoni,neither,Yes,night owl,Yes,"Don't Stop Me Now
+
+Queen"
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,22,Business: Finance,,,53703,43.7696,11.2558,No,sausage,cat,No,night owl,Yes,Hungersite by Goose
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,40.7608,111.891,No,pepperoni,dog,Yes,early bird,Maybe,One Thing at a Time Morgan Wallen
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Mechanical,,,53706,44.9537,-93.09,No,sausage,dog,No,night owl,No,Tweaker - Gelo
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC001,Yes,19,Other (please provide details below).,Physics,Data Science,53706,55.7558,37.6173,Maybe,mushroom,cat,Yes,no preference,Yes,Tweaker by Gelo
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,Yes,19,Other (please provide details below).,我的主要专业是新闻学。,我的第二个专业是数据科学。,53706,30.5728,104.0668,Yes,pineapple,dog,Yes,night owl,Yes,My favorite song is Getaway Car from Taylor Swift.
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,18,Statistics,,Data Science,53706,55.6761,12.5683,Yes,sausage,cat,No,night owl,No,Kyoto - Phoebe Bridgers
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,20,Engineering: Other,,,53715,35.6895,139.6917,No,pepperoni,dog,No,no preference,Yes,Money Trees by Kendrick Lamar
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,18,Data Science,,Econ,53706,16.0544,108.2022,Yes,sausage,dog,Yes,night owl,Yes,Sunroof (Nicky Youre & Dazy) 
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Statistics,,,53706,20.6028,-105.2337,No,sausage,dog,No,night owl,Yes,Best Love Song by T-Pain
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,,Computer Science,,,53706,30,120,No,sausage,cat,No,night owl,Yes,Ashes from fireworks(Chenyu Hua)
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC001,No,19,Engineering: Industrial,,,53706,39.9172,-105.7895,Maybe,pepperoni,dog,Yes,night owl,Yes,Silver Lining Mt. Joy
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Mechanical,,,53706,41.9924,-87.6971,No,green pepper,dog,Yes,no preference,Maybe,"New Person, Same Old Mistakes by Tame Impala "
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,21,Computer Science,,,53706,40,120,Yes,pineapple,cat,Yes,no preference,No,Twenty-one pilot: <line>
+COMP SCI 319:LEC004,LEC004,Yes,23,Engineering: Industrial,,,53703,34,-119,No,mushroom,dog,No,night owl,Maybe,
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Other (please provide details below).,Economics,Political Science,53703,41.8781,-87.6298,No,sausage,dog,No,no preference,Maybe,Piano Man by Billy Joel
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,,Other (please provide details below).,Economics,,53706,,113.2644,No,mushroom,dog,No,night owl,Yes,Young Cai Xukun
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,19,Other (please provide details below).,Linguistics,,53706,43.0981,-89.4986,Yes,pepperoni,dog,No,night owl,Yes,Steppa Pig by JPEGMAFIA
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,21,Engineering: Mechanical,,,53706,45.4015,-92.6522,No,pepperoni,dog,No,night owl,Yes,"Dear Maria, count me in by all time low
+
+only the good die young by billy joel
+
+aint no rest for the wicked by cage the elephant
+
+ "
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,18,Other (please provide details below).,经济的,数据科学,53706,30.5928,114.3055,Yes,none (just cheese),cat,No,night owl,Maybe,"Had I Not Seen the Sun
+
+by HOYO-Mix/Chevy"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,18,Business: Information Systems,,,53706,33.597,130.4081,Maybe,mushroom,dog,Yes,early bird,Maybe,Strategy - TWICE
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,Yes,19,Business: Other,Supply Chain Management & Operations and Technology Management,Data Science Certificate,53707,52.3702,4.8952,No,pepperoni,dog,No,no preference,Yes,Rhymes Like Dimes- MF DOOM
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,18,Data Science,,Molecular and cell biology,53706,41.9028,12.4964,Yes,Other,cat,No,night owl,Yes,Fake tales of San francisco by arctic monkeys 
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Mechanical,,,53706,44.4932,11.3275,No,sausage,dog,Yes,night owl,Yes,"Wisconsin, On, Wisconsin. EA Sports College Football Marching Band"
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC002,Yes,20,Statistics,,,53715,31.2304,121.4737,No,Other,dog,No,night owl,Yes,You'll be back (theme of Alexander Hamilton)
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,19,Science: Biology/Life,,,53703,43038902,-87.9064,No,pepperoni,cat,No,night owl,Yes,dangerous - big data
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Science: Other,,,53703,30.25,120.1667,Maybe,pepperoni,neither,No,early bird,Maybe,Isahini-Lucy
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,20,Statistics,,,53706,45.6378,-89.4113,No,pepperoni,cat,No,night owl,No,Lose yourself-Eminem 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,21,Other (please provide details below).,Accounting,Information Systems,53703,45.4642,9.19,No,basil/spinach,dog,Yes,night owl,Yes,Starting Over- Chris Stapleton 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,19,Engineering: Mechanical,,,53706,44.3113,-93.928,No,Other,dog,No,no preference,Yes,Different 'Round Here by Riley Green Ft. Luke Combs
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,21,Business: Finance,,Risk Management and Insurance,53726,31.542,-82.4687,No,mushroom,dog,Yes,early bird,Yes,"Colder Weather, Zach Brown Band"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,20,Business: Information Systems,,,53726,41.8781,-87.6298,Maybe,Other,dog,Yes,no preference,Yes,Way I Are by Timbaland
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,20,Business: Actuarial,,Risk Management & Insurance,53715,19.0414,-98.2063,No,none (just cheese),cat,No,night owl,No,Return of the Mack by Mark Morrison
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,,Business: Information Systems,,,53703,41.8967,12.4822,No,pineapple,neither,No,no preference,Yes,"No scrubs, by tlc"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Other (please provide details below).,Economics ,Psychology,53703,43.0389,-87.9065,No,pepperoni,dog,Yes,night owl,Maybe,alabama pines -Jason isbell
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Other,Currently Engineering Undecided,,53706,45.6495,13.7768,No,sausage,dog,Yes,no preference,Maybe,"The Veldt , deadmau5"
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,48.5015,-113.9848,No,sausage,dog,Yes,night owl,Yes,through the wire- kanye west 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,18,Engineering: Other,I am undecided between different types of engineering. Im trying to decide between chemical and mechanical.,I might get a math certificate,53706,21.5808,-158.1053,No,pepperoni,dog,Yes,early bird,No,One of these nights by the egales
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Biomedical,,,53706,55.6755,12.5539,No,pepperoni,dog,No,no preference,No,OCT 33 by the Black Pumas 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,20,Engineering: Mechanical,,,53703,41.8781,-87.6298,Yes,pepperoni,cat,No,night owl,Maybe,Bad Romance - Lady Gaga
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Industrial,,German,53703,36.1627,-86.7816,No,sausage,dog,No,night owl,Maybe,Good Looking by Suki Waterhouse
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,18,Data Science,,,53706,17.385,78.4867,Yes,sausage,dog,Yes,night owl,Yes,Feather - Sabrina Carpenter
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC001,No,24,Mathematics/AMEP,,,53704,26.0745,119.2965,No,pepperoni,dog,No,night owl,Yes,"Just the Two of US - Grover Washington, Jr., Bill Withers"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Mechanical,,,53706,43.4138,-89.7148,No,pepperoni,dog,No,no preference,No,NOW WHAT? by Connor Price
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,Yes,20,Other (please provide details below).,Economics,,53572,42.3659,21.1545,No,none (just cheese),cat,Yes,early bird,Maybe,Tahir Meha - Ilir Shaqiri
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,19,Business: Information Systems,,Operations and Technology Management (OTM),53703,33.5458,-117.7817,No,sausage,dog,No,no preference,Yes,"""Say Something"" - Zac Samuel Remix"
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,19,Computer Science,,,53702,51.5074,-0.1278,Yes,Other,dog,No,night owl,No,No One Like You - Scorpions
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Biomedical,,,53706,40.7128,-74.006,No,sausage,dog,No,early bird,No,"Mr. Brightside, The Killers"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,20,Business: Finance,,,53703,36.0566,-112.1251,Yes,pepperoni,dog,Yes,no preference,Yes,All Falls Down - Kanye West
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Statistics,,,53706,40.7128,-74.006,Yes,pineapple,dog,No,night owl,Yes,One Headlight - The Wallflowers
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Engineering: Industrial,,,53706,45.7852,-88.0987,Maybe,sausage,dog,No,night owl,No,"The Prodigal, Josiah Queen "
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,18,Engineering: Other,,,53706,40.6299,14.4863,No,sausage,dog,No,night owl,Yes,Everlong by Foofighters
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Mechanical,,,53719,35.6895,139.6917,No,pepperoni,dog,Yes,night owl,Yes,From The Start - Laufey
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,18,Engineering: Mechanical,NA,NA,53706,39.1447,8.3037,No,Other,dog,No,night owl,Maybe,hooked on a feeling
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Mechanical,NA,NA,53706,45.1821,-93.6522,No,sausage,dog,No,night owl,Maybe,Ghost Town by Kanye West
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,22,Computer Science,,,53715,43.0731,89.4012,No,pepperoni,cat,No,night owl,Yes,The Great Mermaid - Lesserafim
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,19,Engineering: Mechanical,,,53711,31.23,121.47,No,pepperoni,cat,No,night owl,Maybe,When you say nothing at all-Ronan Keating
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,18,Engineering: Mechanical,,,53706,41.8468,3.1286,No,basil/spinach,dog,Yes,early bird,Yes,MUSSEGU - Figa Flawas
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,19,Science: Physics,,"Mathematics, Astrophysics",53703,43.4256,-88.1321,No,green pepper,dog,No,early bird,Yes,"2112, Rush"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,18,Engineering: Mechanical,,,53706,35.6764,139.65,No,pepperoni,neither,Yes,night owl,Yes,my favorite song is Lost in Space by Derivakat
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,19,Business: Finance,,Accounting,53703,41.8781,-87.6298,No,sausage,dog,No,night owl,No,"""Saturday Mornings"" by Cordae"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,18,Other (please provide details below).,Economics,"Data Science, Computer Science",53706,42.4545,-83.502,Yes,sausage,cat,Yes,night owl,No,Upside Down
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Mechanical,,,53706,44.98,-93.26,No,basil/spinach,dog,Yes,night owl,Maybe,Surfin' USA - Beach Boys
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,18,Engineering: Biomedical,,,53706,23.4814,120.4539,Maybe,pepperoni,dog,Yes,night owl,Yes,"Photograph, Ed Sheeran"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,19,Engineering: Mechanical,,,53706,41.9956,-87.7029,Maybe,pineapple,dog,Yes,early bird,Yes,Virgen - Adolescent's Orquesta
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Biomedical,N/A,N/A,53706,35.6895,139.6917,No,mushroom,dog,No,no preference,Yes,Unwritten by Natasha Bedingfield
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,22,Other (please provide details below).,Economics,Political Science,53703,55.6564,12.5983,No,pepperoni,cat,No,early bird,No,Good days by SZA
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,,Data Science,,,53703,40.767,-73.962,Yes,pepperoni,dog,Yes,night owl,Maybe,Saturn by SZA
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,No,22,Engineering: Industrial,,"Economics, Data Science",53703,-33.8688,151.2093,Yes,mushroom,dog,Yes,night owl,Maybe,"This month, my favorite song has been Burn, Burn, Burn by Zach Bryan. However, I'd say my 3 lifetime favorite songs are:
+
+* this is me trying, Taylor Swift
+
+* Somebody That I Used To Know, Gotye 
+
+* For Emma, Bon Iver"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,20,Computer Science,,,53715,39.9042,116.4074,Maybe,mushroom,neither,No,night owl,Yes,"Chasing Pavements, Adele"
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Data Science,,,537152236,19.3785,-81.4007,Yes,pepperoni,dog,No,night owl,Yes,Coffee Bean - Travis Scott
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,18,Engineering: Mechanical,,,53706,11.5888,37.3881,No,none (just cheese),cat,No,night owl,Yes,
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,19,Engineering: Mechanical,,,53706,38.627,-90.1994,No,none (just cheese),dog,No,night owl,Yes,Young Metro by Future and Metro Boomin
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,20,Engineering: Industrial,,,53703,43.77,11.2577,Maybe,pepperoni,dog,Yes,night owl,Yes,Sheep by Mt.Joy
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,Yes,20,Business: Other,Economics ,"data science, Risk Management and insurance ",53703,40.6281,14.485,Yes,sausage,cat,No,no preference,Maybe,new perspective - noah kahn 
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,20,Business: Finance,.,.,53706,37.5665,126.978,No,pineapple,dog,No,early bird,Yes,Sunflower - Post Malone
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,20,Engineering: Mechanical,,,53703,45.514,-122.6733,No,pepperoni,dog,Yes,night owl,Maybe,Cigarette Daydreams - Cage the Elephant 
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,19,Data Science,,Psychology,53726,52.52,13.405,Yes,pepperoni,dog,No,no preference,Yes,"El Muchacho de los Ojos Tristes, Jeanette"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,19,Engineering: Mechanical,,,53706,41.4944,-87.8748,No,pepperoni,dog,Yes,night owl,Yes,Brazil- Declan Mckenna
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,19,Data Science,,Information Sciences,53706,40.7128,-74.006,Yes,Other,dog,No,night owl,Yes,One More Love Song - Marc DeMarco
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,19,Computer Science,,,53703,34.0522,-118.2437,Maybe,pepperoni,dog,No,night owl,Maybe,where you are - john summit
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,20,Engineering: Biomedical,N/A,Pre-Med (Not a major),53703,40.7293,-73.9964,No,sausage,cat,No,night owl,Yes,I Lived by OneRepublic
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,18,Science: Physics,,,53706,47,122,No,pepperoni,neither,Yes,early bird,No,Clocks Coldplay
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,19,Business: Finance,,,53706,41.8318,-88.1098,Maybe,pepperoni,dog,No,no preference,Yes,No Pasa Nada by Fuerza Regida and Clave Especial 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,19,Data Science,,Computer science,53706,43.8064,-87.7706,Yes,pepperoni,cat,Yes,night owl,Yes,holy land - wave to earth
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,18,Engineering: Mechanical,,,53706,52.52,13.405,No,macaroni/pasta,dog,Yes,night owl,Yes,"1812 Overture
+
+ by Pyotr Ilyich Tchaikovsky"
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,19,Data Science,,,53703,34.5218,69.1807,Yes,green pepper,cat,No,night owl,Maybe,I don't listen to music!
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC003,Yes,21,Business: Finance,Economics,computer science,53703,22,66,Yes,mushroom,cat,No,night owl,Yes,Bahamus
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Engineering: Mechanical,,,53703,42.3314,-83.0458,No,sausage,dog,Yes,night owl,Yes,Higher by Creed
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,19,Science: Other,,Environmental Studies,53703,45.0124,-92.9921,No,basil/spinach,dog,Yes,early bird,Yes,Sunlight by Hozier
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Industrial,,,53706,32,117,No,sausage,dog,No,early bird,Maybe,knockin on heavens door bob Dylan
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,Yes,19,Engineering: Mechanical,,,53706,40.7131,-74.0072,No,none (just cheese),dog,Yes,no preference,Yes,Brazil by Declan McKenna
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,Yes,19,Engineering: Other,Engineering Mechanics,"Might do Econ, Physics, or DS",53706,35.6895,139.6917,Maybe,basil/spinach,dog,No,night owl,Yes,Outside today - NBA Youngboy
+COMP SCI 319:LEC002,LEC002,Yes,32,Science: Physics,,,53714,13.45,-16.57,Maybe,pineapple,neither,Yes,early bird,No,"Bob Marley
+
+No Woman, No Cry"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,No,19,Engineering: Biomedical,,,53706,50.1185,-122.9604,No,pepperoni,dog,Yes,night owl,Maybe,Free Now by Gracie Abrams
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,21,Engineering: Mechanical,,,53590,34.0522,-118.2437,No,pepperoni,dog,No,night owl,Yes,popular by the weeknd
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,22,Statistics,,Data Science,42,-76,106.53,Yes,mushroom,neither,Yes,no preference,No,"Here There And Everywhere, Paul McCartney"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,18,Data Science,,,53706,46.024,-123.92,Yes,basil/spinach,dog,No,night owl,Yes,Musta been a ghost by Proxima Prada
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,18,Engineering: Mechanical,,,53706,45.83,-89.27,No,sausage,dog,No,night owl,Yes,"Run This Town - JAY-Z, Rihanna, Kanye West"
+COMP SCI 319:LEC004,LEC004,Yes,26,Business: Information Systems,,,53705,23.5,121,Maybe,mushroom,dog,No,night owl,Maybe,Someone You Loved - Lewis Capaldi
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,19,Science: Other,,,53715,33.4484,-112.074,No,sausage,cat,No,night owl,Yes,Follow You by Imagine Dragons
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Mechanical,,I do not have a secondary major.,53703,49.2269,17.669,No,pepperoni,dog,No,early bird,No,One of my favorite songs is Circadian Rhythm by Drake.
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,18,Mathematics/AMEP,,I'm gonna learning data science in the future.,53706,30.5728,104.0668,Yes,pepperoni,dog,Yes,night owl,Yes,"Take me to Church, Hozier"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,19,Engineering: Mechanical,,,57306,40.7128,-74.006,No,pepperoni,dog,Yes,night owl,Maybe,Mr. Jones by Counting Crows
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,20,Business: Actuarial,,,53703,43.1566,-77.6088,Maybe,sausage,cat,Yes,night owl,Maybe,Obsession - Joywave
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Mechanical,N/A,N/A,53706,41.8781,-87.6298,No,macaroni/pasta,cat,No,no preference,Yes,Maine by Noah Kahan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,19,Engineering: Industrial,,,53706,41.8781,-87.6298,No,pepperoni,cat,No,no preference,Yes,Something Just Like This - Chainsmokers 
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,Yes,20,Data Science,,Economics,53703,20,-156,Yes,pepperoni,dog,Yes,no preference,No,Tweaker by Gelo
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,19,Engineering: Biomedical,,,53706,44.0668,-92.7538,No,pepperoni,dog,Yes,night owl,Maybe,Borderline - Tame Impala
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,Yes,19,Engineering: Other,,,53706,50.0755,14.4378,Maybe,none (just cheese),dog,No,no preference,Yes,Smoke a little smoke - Eric Church
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,19,Engineering: Biomedical,,,53715,43.732,7.4196,No,pepperoni,dog,No,night owl,No,"Cello Suite No. 1 in G Major; Johann Sebastian Bach, Yo-Yo Ma"
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,20,Science: Biology/Life,,,53715,43.4799,-110.7624,Yes,Other,dog,No,night owl,No,Paul Revere by Noah Kahan
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,18,Engineering: Biomedical,,,53706,40.7128,-74.006,Maybe,pepperoni,dog,Yes,early bird,Maybe,Unwritten by Natasha Bedingfield
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC001,No,21,Engineering: Industrial,,,53715,45.8157,-94.6374,No,pepperoni,dog,No,night owl,Yes,"Unwritten, by Natasha Bedingfield"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,Yes,19,Business: Finance,,Economics,53726,43.07,-89.39,No,Other,neither,Yes,no preference,No,Down Under -Men At Work
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,19,Business: Finance,Data Science,,53706,87.6298,41.8781,Yes,pepperoni,dog,Yes,night owl,Maybe,Back to Black by Amy Winehouse
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,18,Data Science,,,53706,40.374,-105.509,Yes,pepperoni,dog,No,night owl,Maybe,eenie meenie - Sean Kingston and Justice Bieber
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,18,Engineering: Biomedical,,,53706,47.8095,13.055,No,sausage,cat,Yes,night owl,Yes,"On Wisconsin! - Finale
+
+University of Wisconsin Marching Band"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,19,Data Science,,,53715,25.2854,51.531,Yes,mushroom,cat,Yes,early bird,Yes,"Borderline by Tame Impala
+
+ "
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,19,Data Science,,,53706,45.0697,92.9516,Maybe,pineapple,dog,No,night owl,Yes,Strange to hear - By Sports
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,18,Business: Information Systems,,Business: Operations and Technology Management,53716,43.0731,-89.4012,No,mushroom,dog,No,night owl,Yes,You Give Love a Bad Name by Bon Jovi
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,19,Business: Other,,,53703,37.7749,-122.4194,Yes,basil/spinach,dog,Yes,night owl,Yes,What I got - Sublime 
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Other,,,53706,43.0779,-89.4134,No,pineapple,dog,No,no preference,No,Next to You by Flavors
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,19,Business: Other,Economics.,Data science,53706,28.6107,-244.1199,Maybe,Other,dog,No,night owl,Yes,Sometimes-Goth Babe
+COMP SCI 319:LEC001,LEC001,No,22,Engineering: Other,ECE,,53715,31.2304,121.4737,Maybe,pineapple,cat,No,no preference,Yes,"Never Gonna Give You Up, by Rick Astley"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,19,Data Science,Nothing,Economics ,53706,35.689,139691,Yes,green pepper,neither,No,night owl,Yes,Sun flower by Post Malone
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,20,Business: Information Systems,,,53706,3.139,101.6869,Maybe,Other,dog,Yes,no preference,Maybe,Livin' on a Prayer by Bon Jovi
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,19,Engineering: Mechanical,,,53706,34.4208,-119.6982,No,pepperoni,dog,Yes,no preference,No,甜蜜蜜 鄧麗君
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,20,Other (please provide details below).,Environmental Science,n/a,53703,39.9526,-75.1652,No,pepperoni,dog,No,no preference,Maybe,Anything from kendrick lamar
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,19,Other (please provide details below).,Geography,,53726,47.6032,-122.3303,Maybe,Other,dog,No,night owl,No,Beef Stew by Nicki Minaj
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,20,Engineering: Other,,,53706,31.298,120.585,No,none (just cheese),cat,No,no preference,Maybe,Subhuman by Garbage
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,21,Statistics,,,53703,43.0389,-87.9065,No,pepperoni,dog,Yes,night owl,Yes,Dirty Water by Foo Fighters
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,18,Engineering: Biomedical,N/A,N/A,53706,43.7696,11.2558,No,pepperoni,dog,No,night owl,Yes,Stick Season by Noah Kahan 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,20,Engineering: Mechanical,,,53715,49.4435,1.098,No,sausage,dog,Yes,night owl,Maybe,Sleep on the Floor - The Lumineers
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,18,Science: Other,Biochemistry,,53706,46.595,7.9075,No,pineapple,dog,No,night owl,Maybe,Flower Shops by ERNEST and Morgan Wallen
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,18,Business: Information Systems,,,53703,41.8781,-87.6298,Maybe,pepperoni,dog,Yes,no preference,Yes,All falls Down- Kanye West 
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,20,Other (please provide details below).,Journalism,,53706,-22.9068,-43.1729,No,pepperoni,dog,Yes,no preference,Maybe,"Cool Blue by The Japanese House
+
+or
+
+My Love by Until the Ribbon Breaks"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,19,Engineering: Other,,,53706,48.1118,-1.6803,Maybe,none (just cheese),dog,No,night owl,Yes,A Troubled Mind-Noah Kahan
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Industrial,,Naval Science,53703,-18.1248,178.4501,No,sausage,dog,Yes,early bird,No,"Angela, The Lumineers"
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Mechanical,,,57303,43.0731,-89.4012,No,pepperoni,dog,No,night owl,Yes,YMCA 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,18,Engineering: Mechanical,,,53706,32,34.8,No,basil/spinach,dog,Yes,night owl,Maybe,Lovestick by asap rocky
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,19,Business: Finance,I am also a Data Science major,,53706,25.1,55.2,Yes,mushroom,dog,No,night owl,Yes,Fein (Feat. playboi carti) by Travis Scott
+COMP SCI 319:LEC001,LEC001,Yes,,Business: Finance,,,53715,30.5,104,No,pineapple,dog,Yes,night owl,Yes,"I love you baby
+
+Paul Anka"
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,20,Science: Other,,,53575,43.07,-89.4,Maybe,Other,cat,Yes,night owl,Yes,Sexy Villain - Remi Wolf
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,21,Statistics,,,53703,40.7128,-74.006,No,mushroom,dog,No,early bird,No,my heart will go on
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,20,Business: Information Systems,,Business: Operations & Technology Management ,53703,48.8566,2.3522,Maybe,sausage,dog,Yes,early bird,Yes,30 for 30 by SZA
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical," 
+
+ ",Neurobiology,53706,53.5745,10.0778,No,basil/spinach,cat,No,night owl,Yes,"Maine by Noah kahan
+
+ "
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,19,Business: Actuarial,,RMI,53715,43.0389,-87.9065,No,pepperoni,cat,Yes,night owl,No,Congratulations by Mac Miller
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC002,No,19,Business: Information Systems,,I am also a Marketing major with a certificate in Digital Studies!,53706,39.1434,-77.2014,Maybe,basil/spinach,dog,Yes,night owl,Maybe,"Gracie Abrams: ""Risk"""
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,18,Business: Other,,Data Science,53706,42.3601,-71.0589,Yes,mushroom,dog,No,no preference,Yes,Luther by Kendrick Lamar and SZA
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,19,Other (please provide details below).,Economics,,53703,40.7128,74.006,No,mushroom,dog,Yes,early bird,Yes,Pursuit of Happiness- Kid Cudi
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,18,Engineering: Biomedical,,,53706,39.0742,21.8243,No,sausage,cat,No,early bird,Yes,Weight of Love - The Black Keys
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Biomedical,,,53706,45,-93,No,sausage,dog,No,night owl,No,Die with a Smile - Bruno Mars
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Biomedical,,,53706,19.076,72.8777,No,pineapple,dog,Yes,early bird,Yes,Luther by Kendrick Lamar and SZA.
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Mechanical,,,53706,-45.0327,168.658,No,sausage,dog,Yes,night owl,Yes,Night Changes - One Direction
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,18,Science: Physics,,,53706,40.7,70,No,none (just cheese),neither,No,night owl,Yes,My Eyes by Travis Scott
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,20,Computer Science,,,53703,3.139,101.6869,No,macaroni/pasta,cat,No,early bird,No,GOT7 PYTHON 
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Industrial,,,53706,41.8781,-87.6298,No,mushroom,dog,No,night owl,Yes,Coyote Joni Mitchell
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,20,Science: Biology/Life,,,53706,37.8715,112.5512,No,sausage,cat,Yes,early bird,Maybe,Soledad y el Mar by Natalia Lafourcade
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,20,Computer Science,,,53715,37.5665,126.978,No,sausage,neither,Yes,night owl,No,"Echo, The Marias"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,20,Engineering: Mechanical,,,53703,43.7696,11.2558,No,mushroom,neither,No,no preference,No,"When it rains it pours
+
+Luke combs"
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53715,45.4408,12.3155,No,sausage,dog,No,night owl,Yes,Put Me Thru by Anderson .Paak
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,17,Computer Science,,,53706,35.6528,139.8395,No,pepperoni,cat,Yes,early bird,Maybe,"40oz, polyphia"
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Mechanical,,,53706,42.3009,-71.0684,No,sausage,dog,Yes,night owl,No,Breakdown by Jack Johnson
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Biomedical,,,53706,42.3601,-71.0589,No,pepperoni,dog,No,night owl,Yes,Sweet Child O' Mine by Guns and Roses
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,18,Science: Physics,,Mathematics,53706,37.9838,23.7275,No,none (just cheese),dog,No,no preference,Yes,Bohemian Rhapsody-Queen
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical,Above,None,53706,-29.94,-50.99,No,none (just cheese),dog,No,night owl,No,That's So True by Gracie Abrams
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,19,Computer Science,,data science,53703,43.0731,-89.4012,Yes,sausage,neither,No,night owl,Maybe,doja
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,21,Other (please provide details below).,Geography and Cartography/Geographic Information Systems,"Data Science Certificate, Environmental Studies Certificate",53715,36.1699,-115.1398,No,sausage,dog,Yes,night owl,Yes,"Rain, The Beatles"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,18,Engineering: Biomedical,,,53706,41.16,-8.63,Maybe,sausage,cat,No,night owl,Yes,This Must Be the Place - Talking Heads
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,19,Science: Physics,,Astronomy,53726,36.9741,122.0308,No,pepperoni,dog,No,night owl,Yes,Californication Red Hot Chili Peppers
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC003,No,20,Computer Science,,"Data Science, Economics, Accounting",53706,-1.2921,36.8219,Yes,pepperoni,cat,No,no preference,Yes,"Verdansk, Dave"
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Other,,,53706,41.1184,20.8,No,mushroom,dog,No,early bird,Yes,November Air - Zach Bryan
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,18,Engineering: Biomedical,n/a,n/a,53706,53.3498,-6.2603,No,green pepper,dog,Yes,night owl,Maybe,Moon River by Frank Ocean
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Biomedical,,,53706,22.0964,-159.5261,No,pineapple,dog,Yes,night owl,No,Maine by Noah Kahan
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,19,Computer Science,,Data Science,53711,43.0731,-89.4012,No,none (just cheese),cat,No,night owl,Yes,I'm A Believer - The Monkees
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,19,Engineering: Mechanical,,,53706,44,-88,No,sausage,cat,Yes,night owl,Yes,Triggers - Royal Blood
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,,Engineering: Other,,,53703,36.0671,120.3826,Maybe,mushroom,dog,No,night owl,Yes,《Glad You Came》by Boyce Avenue
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,18,Mathematics/AMEP,,,53715,37.5407,-77.436,No,mushroom,cat,Yes,no preference,Yes,Posthumous forgiveness - Tame Impala
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,19,Engineering: Mechanical,,,53706,21.28,-157.83,No,sausage,cat,Yes,early bird,No,Yellow by Coldplay
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,20,Engineering: Mechanical,,,53715,43.0739,-89.3852,No,macaroni/pasta,cat,No,night owl,Yes,Africa by Toto
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,Yes,24,Statistics,,,53713,30.4515,-91.1871,Yes,mushroom,dog,No,no preference,Yes,Liberation - Outkast ft. Cee-Lo Green
+COMP SCI 319:LEC002,LEC002,No,22,Engineering: Other,,,53703,36.1699,-115.1398,No,pineapple,dog,No,night owl,Yes,dancinwithsomebawdy - ericdoa
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Biomedical,,,53706,45.0033,-93.484,Maybe,sausage,cat,No,night owl,No,Second Nature by Clairo
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,22,Computer Science,,"German, Data Science",53703,45.4404,12.316,No,sausage,dog,No,night owl,Yes,Modern Day Cowboy (Tesla)
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,18,Engineering: Industrial,,,53706,25.0772,55.3093,No,pepperoni,dog,No,night owl,Maybe,Drake - Gods Plan
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Biomedical,,,53706,47.0543,8.3094,Maybe,none (just cheese),cat,Yes,early bird,Maybe,Shes always a woman (billy joel)
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,18,Engineering: Mechanical,,,53706,43.6775,-70.299,No,pepperoni,dog,Yes,early bird,Yes,The Cave by NEEDTOBREATHE
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Industrial,,,57303,34.0549,118.2426,No,sausage,cat,No,night owl,Yes,Feather - Sabrina Carpenter
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Engineering: Other,Material Science and Engineering,,53715,35.8617,104.1954,No,sausage,cat,Yes,night owl,Maybe,"patrick Brasca
+
+BRB
+
+Ryan.B"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,23,Science: Biology/Life,Biochemistry,N/A,53703,33,120,Maybe,pepperoni,cat,No,night owl,Yes,"Piano Concerto No.23 in A major, K.488 - 1. Allegro
+
+Mozart"
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,20,Engineering: Industrial,Industrial Engineering,,53706,,,Maybe,pineapple,dog,No,early bird,No,Ride the Lightning by Warren Zeiders
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,17,Engineering: Mechanical,,,53703,33.1042,-96.6717,No,none (just cheese),dog,Yes,night owl,Yes,Stick Season by Noah Kahan
+COMP SCI 319:LEC004,LEC004,Yes,27,Engineering: Other,Environmental Engineering,,53719,30.98,121.5,Maybe,none (just cheese),dog,No,night owl,No,"Salt
+
+Ava Max"
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,Yes,19,Data Science,,,53706,44,91,Yes,Other,cat,Yes,early bird,No,"Oak Island, Zach Bryan "
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,18,Business: Finance,,,53706,40.0169,-105.2796,Maybe,pineapple,dog,Yes,early bird,No,Back in Black by ACDC
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Other,Material Science and Engineering,,53706,46.5378,12.1359,No,basil/spinach,dog,Yes,early bird,No,Sweet Dreams by Eurythmics
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,18,Computer Science,,"Data Science, Graphic Design (certificate)",53715,42.6403,18.1083,Yes,basil/spinach,cat,No,night owl,Maybe,South Side - Moby
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,Yes,18,Engineering: Biomedical,,Accounting,53715,41.9028,12.4964,No,pepperoni,dog,Yes,no preference,No,"She Had ME At Heads Carolina, Cole Swindell"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Other (please provide details below).,Currently undecided but intend to have a business major and double major in something along these lines. Wanted to try out this class to see if I would enjoy it ! ,None.,53706,35.5405,-79.3692,Maybe,sausage,dog,No,night owl,Maybe,I have too many liked songs to choose just one! If I were to choose a genre of music thought it would have to be R&B :)
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,19,Engineering: Industrial,N/A.,N/A.,53706,41.9408,-87.7532,No,Other,cat,No,night owl,No,Sunday morning Maroon 5
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Engineering: Mechanical,,,53175,32.7765,-79.931,No,sausage,dog,No,night owl,Maybe,God Gave Me Style - 50 Cent
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,Yes,19,Engineering: Biomedical,,,53726,47.0455,8.308,No,pepperoni,dog,No,early bird,Maybe,Black and White by Niall Horan
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Industrial,,,60010,48.8566,2.3522,Maybe,green pepper,cat,Yes,night owl,Yes,Learning To Fly - Tom Petty and the Heartbreakers
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,18,Data Science,,,53706,121.4365,31.1886,Maybe,pineapple,cat,Yes,night owl,Maybe,"Song Title: I Like Me Better
+
+Artist: Lauv "
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,19,Data Science,na,Economics,53715,1.3521,103.8198,Yes,pepperoni,dog,No,early bird,Yes,Toxic Till The End - Rose
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,19,Engineering: Biomedical,,,53706,45.5017,-73.5673,No,pepperoni,dog,No,night owl,Yes,She's always a woman - Billy Joel
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,Yes,22,Other (please provide details below).,Economics,,53703,31.2304,121.4737,No,pineapple,dog,No,early bird,Yes,Kammy - Fred again..
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Biomedical,,,53706,-3.6225,-79.2388,No,macaroni/pasta,cat,No,night owl,Yes,"DtMF, by Bad Bunny"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,18,Other (please provide details below).,Molecular and Cell Biology,Statistics,53706,35.0844,-106.6504,No,Other,dog,Yes,early bird,No,Run by One Republic
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,No,18,Engineering: Mechanical,,,53706,43.0731,-89.4012,Maybe,Other,cat,No,night owl,Maybe,Lovers Rock - TV Girl
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,Yes,19,Engineering: Other,Engineering Mechanics: Aerospace,Applied Mathematics,53715,41.3851,2.1734,No,pepperoni,cat,Yes,early bird,Yes,Set Sail by The Movement
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Mechanical,,,53706,43.0747,89.3842,No,pineapple,dog,Yes,night owl,Yes,"The Man who sold the world, David Bowie"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,19,Other (please provide details below).,Economics,,53703,35.994,-78.8986,Yes,none (just cheese),dog,Yes,night owl,Yes,Any song by Drake
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,20,Science: Other,Biochemistry,Chinese,53703,41.8781,87.6298,No,sausage,cat,No,night owl,Yes,Empire of the Sun-We the People
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,21,Business: Information Systems,,,53703,43.0731,-89.4012,Maybe,sausage,cat,Yes,night owl,Yes,"Scott Mescudi Vs. The World, By Kid Cudi"
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,19,Other (please provide details below).,Music ,Data science,53706,41.8781,-87.6298,Yes,macaroni/pasta,cat,No,night owl,Yes,Oompa Loompa song from Wonka
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Mechanical,,,53706,37.5641,126.9756,No,pepperoni,dog,No,night owl,Yes,toxic till the end by ROSE
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Business: Other,,certificate in data science,53706,43.7696,11.2558,No,mushroom,dog,No,night owl,No,"Vienna, Billy Joel"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,18,Engineering: Biomedical,,,53715,45.1034,-93.7295,No,pepperoni,dog,No,early bird,Maybe,"See You Again, Tyler the Creator"
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,Yes,19,Business: Actuarial,,Business: Risk Management and Insurance,53703,43.0752,-89.3964,No,pepperoni,cat,No,no preference,Yes,Prison Song - System of a Down
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,20,Engineering: Biomedical,,,53703,52.37,4.9,No,sausage,dog,No,night owl,Yes,Fast Forward - Floating Points
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,No,19,Engineering: Biomedical,,,53706,41,12,No,pepperoni,dog,Yes,night owl,No,Locked out of Heaven - Bruno Mars
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,18,Engineering: Mechanical,,,53715,43.8464,-91.2398,No,pepperoni,dog,Yes,night owl,Maybe,Missed Call by Treaty Oak Revival
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,No,19,Engineering: Biomedical,,,53706,55.9533,-3.1883,No,pepperoni,dog,No,night owl,Yes,Work Song - Hozier
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,20,Computer Science,,,53703,25.033,121.5654,No,tater tots,cat,No,night owl,Yes,Dive - Olivia Dean
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,Yes,21,Other (please provide details below).,My primary major is Classical Humanities. ,,53703,36.5983,-121.8964,No,green pepper,cat,No,night owl,Yes,"My Father's House, Eidola"
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Science: Physics,,Astronomy,53706,43.0731,-89.4012,Maybe,sausage,dog,No,night owl,Yes,Judaiyaan- Darshan Raval
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Industrial,,,53706,43.0495,88.0076,No,pepperoni,dog,No,night owl,Maybe,Holy Ghost Asap Rocky
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,19,Engineering: Mechanical,,,53706,43.0728,-89.3835,No,pepperoni,dog,No,night owl,Yes,Something in the Orange: Zach Bryan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,19,Engineering: Other,Chemical Engineering ,,53706,43.0739,-89.3852,No,macaroni/pasta,dog,No,night owl,Yes,Dancing Queen by Abba
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,19,Business: Actuarial,,,53706,52.3732,4.8907,No,pepperoni,dog,Yes,night owl,No,Popular Weeknd
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,23,Other (please provide details below).,Consumer Behavior and Marketplace Studies,Economics,53703,42.3555,71.0565,No,Other,dog,Yes,early bird,No,Jackie and Wilson by Hoizer
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,18,Science: Biology/Life,,,53706,43.0731,43.0731,Maybe,mushroom,dog,Yes,early bird,Maybe,Live Well - Palace
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,18,Business: Finance,,,53706,-34.9276,-57.9578,Yes,mushroom,cat,Yes,early bird,Yes,Cafe con ron Bad Bunny
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,19,Engineering: Industrial,,,53715,52.6638,8.6267,No,pepperoni,cat,No,early bird,Maybe,Do for love - Tupac
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,40.6958,-73.8666,No,pineapple,cat,Yes,no preference,Yes,Hell on the heart Eric Church  
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,Yes,19,Other (please provide details below).,Undecided,,53715,40.7128,-74.006,Maybe,pepperoni,dog,Yes,night owl,Yes,"New Drop, Don Toliver"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,18,Engineering: Mechanical,,,53706,41.88,87.62,No,sausage,dog,No,night owl,Maybe,Buy dirt by Jordan Davis
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,21,Other (please provide details below).,economics,n/a,53073,415204.8,873954,No,green pepper,dog,Yes,night owl,Yes,"you're not the only one - the sundays
+
+blue Sunday - the doors
+
+dazed and confused - led zeppelin"
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,19,Data Science,,Economics,53706,6.5244,3.3792,Yes,Other,dog,No,early bird,Maybe,Jealousy - Khalil Harrison & Tyler ICU
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,No,20,Data Science,,,53703,41.8781,-87.6298,Yes,none (just cheese),dog,Yes,early bird,No,charlie brown - coldplay
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,42.3601,-71.0589,No,mushroom,cat,No,no preference,No,"My My, Hey Hey - Neil Young"
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Mechanical,,,53706,41.9028,12.4964,No,pepperoni,cat,No,no preference,Yes,Replay by Iyaz
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,No,19,Business: Finance,,,53066,25.2048,55.2708,No,pepperoni,neither,No,night owl,Yes,Duvet Boa
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,18,Statistics,,,53706,43.0731,-89.4012,Maybe,none (just cheese),dog,No,early bird,Yes,RIOT! - Earl Sweatshirt
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,19,Other (please provide details below).,Economics with Math Emphasis,Data Science,53715,41.8781,-87.6298,Yes,sausage,dog,No,night owl,Yes,Everybody Wants To Rule The World by Tears For Fears
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,20,Engineering: Industrial,,,53703,40.7128,-74.006,No,pepperoni,dog,No,night owl,Yes,Stairway to Heaven by Led Zepplin
+COMP SCI 319:LEC004,LEC004,No,27,Other (please provide details below).,Information,,53715,48.8566,2.3522,No,Other,cat,No,night owl,Yes,Instant Crush (feat. Julian Casablancas) - Daft Punk
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,18,Data Science,Planning on to be Data Science.,Global Health or communications possibly.,53715,36.1975,-79.7935,Yes,basil/spinach,neither,Yes,no preference,Maybe,"Give Me Everything by Pitbull
+
+Me Like Yuh Jay Park "
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,19,Business: Actuarial,,Risk Management and Insurance,53715,41.3851,2.1734,Maybe,sausage,dog,No,night owl,Yes,Like a Boy by Ciara
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,20,Statistics,,,53703,23.1291,113.2644,Maybe,none (just cheese),dog,Yes,night owl,Maybe,Flashing light by kanye west
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,19,Science: Biology/Life,,,53715,53715,-106.3468,Maybe,pepperoni,cat,No,night owl,Yes,When I was your man - Bruno Mars
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Data Science,,,53706,43.1049,-89.3512,Yes,tater tots,cat,Yes,night owl,Yes,A Love Supreme Pt I - John Coltrane
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,No,20,Statistics,,,53711,34.6887,-82.8349,No,sausage,dog,Yes,night owl,Yes,Go Your Own Way - Fleetwood Mac
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,18,Data Science,,,53715,30,114,Maybe,mushroom,cat,No,night owl,Yes,Standing Before Mt. Fuji  by Eason Chan
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Industrial,,,53703,43.4796,-110.7624,No,sausage,dog,No,night owl,No,Miss You - The Rolling Stones
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,20,Engineering: Mechanical,,,53702,45.4408,12.3155,No,pepperoni,dog,No,night owl,Maybe,"Escape, by RupertHolmes"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,No,19,Engineering: Other,,,53705,43.08,-89.383,No,basil/spinach,cat,No,no preference,No,"I'm too embarrassed to open Youtube in the middle of class- also, I'm in Louis's section. I'm so sorry."
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,22,Computer Science,,DS and Stat,53715,37.5326,127.0246,Maybe,pepperoni,dog,No,night owl,No,Marigold - Aimyon
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Other,N/A,N/A,53706,43.1686,-89.2784,No,none (just cheese),cat,No,early bird,Yes,California Dreaming' - The Mamas and The Papas
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,,Other (please provide details below).,Economics,,53703,51.5074,-0.1278,No,none (just cheese),dog,No,night owl,Yes,The only exception by Paramore
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Biomedical,,,53715,32.7157,117.1611,No,pineapple,dog,No,night owl,Yes,Jingle BOOM! - A.J. & Big Justice 
+"COMP SCI 220:LAB344, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Biomedical,,,53706,52.3062,10.4835,No,basil/spinach,dog,No,night owl,Yes,Black Magic Woman by Santana
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,,Engineering: Biomedical,,,53706,1.3521,103.8198,Yes,pepperoni,dog,No,night owl,Yes,Come Together by The Beatles
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,sausage,dog,Yes,night owl,Yes,Houston Old Head by A$AP Rocky
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,Yes,19,Computer Science,computer science ,,53703,35.6764,139.65,Yes,basil/spinach,neither,No,night owl,Yes,"green room ken carson 
+
+summer sixteen osamason 
+
+congrats osamason 
+
+pose for the pic che 
+
+swag overlord ken carson 
+
+intro ken carson 
+
+ "
+"COMP SCI 220:LEC004, COMP SCI 220:LAB345",LEC004,Yes,19,Science: Biology/Life,,,53706,30.2741,120.1551,Yes,sausage,cat,No,night owl,Yes,no favorite songs
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,No,18,Computer Science,n/a,Physics?,53706,34.8927,127.9688,Maybe,mushroom,neither,Yes,no preference,Maybe,"Tender Surrender, Steve Vai"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC004,No,21,Data Science,,,53711,37.5665,126.978,Yes,pineapple,dog,No,night owl,Yes,pink + white - frank ocean
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,20,Engineering: Industrial,,,53715,34,-118,No,sausage,dog,No,night owl,Yes,Payphone - Maroon 5
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,20,Engineering: Mechanical,,,53711,33.63,-111.85,No,pepperoni,dog,Yes,night owl,Yes,"While My Guitar Gently Weeps - Prince, Tom Petty, Jeff Lynne"
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Statistics,,,53706,45.9213,89.2035,Maybe,tater tots,dog,No,no preference,Maybe,Agnes by Glass Animals
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,19,Other (please provide details below).,"I am currently a pre-business student choosing between the fields of finance, real estate, data science, and economics.",,53706,45.8711,89.7093,Maybe,sausage,dog,Yes,night owl,Yes,Banana Pancakes - Jack Johnson
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,20,Science: Other,Biochemistry,,53703,43.4799,110.7624,No,sausage,dog,No,night owl,Yes,Wish you were here - Pink Floyd
+COMP SCI 319:LEC004,LEC004,Yes,24,Engineering: Other,ECE,N/A,53711,39.9042,116.4074,No,mushroom,dog,No,night owl,Yes,"song:爱我还是他
+
+singer:陶喆"
+COMP SCI 319:LEC004,LEC004,Yes,26,Other (please provide details below).,Electrical and computer Engineering,,53711,38.9248,121.6279,Maybe,pepperoni,dog,No,night owl,No,EMINEM
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,19,Engineering: Mechanical,,,53706,41.3874,2.1686,Maybe,mushroom,dog,Yes,night owl,Yes,Many Men (Wish Death) by 50 Cent
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Biomedical,,,53706,48.8566,2.3522,No,pepperoni,cat,Yes,no preference,Maybe,"Whitney Houston: I Wanna Dance with Somebody
+--------------------------------------------
+
+Bob Marley and The Wailers: Could You Be Loved"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,18,Engineering: Biomedical,N/A,N/A,53706,41.3851,2.1734,No,pepperoni,dog,No,night owl,Maybe,Rolling Stone - Brent Faiyaz
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,18,Engineering: Mechanical,,,53706,37.7749,-122.419,No,pineapple,dog,Yes,night owl,Yes,Roll the Dice by Arden Jones
+COMP SCI 319:LEC002,LEC002,Yes,24,Other (please provide details below).,International Public Affairs,N/A,53715,41.795,140.74,No,pepperoni,cat,No,night owl,Yes,Astronaut - Simple Plan
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,19,Science: Other,,Data Science,53703,35.6895,139.6917,Yes,sausage,dog,Yes,no preference,Maybe,Cant Feel My Face - The Weeknd
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,18,Statistics,,Political Science,53706,42.2499,-71.0409,No,basil/spinach,dog,Yes,no preference,Yes,Waiting Room by Phoebe Bridgers
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,21,Science: Biology/Life,,,53715,48.8575,2.3514,No,mushroom,dog,No,night owl,Yes,Take On Me by A-ha
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,Yes,18,Engineering: Biomedical,,,53706,44.932,-93.2853,No,pepperoni,dog,Yes,night owl,Yes,Operator (That's Not the Way It Feels) by Jim Croce
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,19,Engineering: Mechanical,,,53706,41.8789,-87.6355,No,pepperoni,cat,Yes,no preference,Maybe,someday by the strokes
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,Yes,18,Engineering: Biomedical,,,53706,43.7696,11.2558,Maybe,basil/spinach,dog,No,night owl,Maybe,Boy - Lee Brice
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,19,Engineering: Biomedical,,,53715,35.6895,139.6917,No,mushroom,dog,No,night owl,Maybe,Button by Lyn Lapid
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,18,Engineering: Mechanical,,,53706,24.1477,120.6736,No,Other,dog,No,night owl,Yes,Remember the Time - Michael Jackson
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,20,Science: Biology/Life,,Life Science Communication,53706,43.0844,-89.3812,No,Other,dog,Yes,no preference,Yes,"Reach Out, Four Tops"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,Yes,19,Science: Physics,,Astronomy-Physics,53706,44.2165,-114.93,Maybe,pepperoni,dog,No,early bird,Yes,"Bad Kids to the Back, Snarky Puppy"
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,18,Other (please provide details below).,Undecided planning on Biomedical Engineering,,53706,37.3925,-5.9941,No,none (just cheese),cat,No,night owl,No,Much too Much - Rex Orange County
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,18,Science: Biology/Life,,,53706,39.9042,116.4074,No,sausage,cat,No,night owl,Maybe,"A Heart Like Hers, Mac DeMarco"
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Biomedical,,,53706,25.0338,121.527,No,green pepper,dog,Yes,early bird,Maybe,Alaska - Maggie Rogers
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,No,18,Engineering: Mechanical,,,53706,43.8307,-91.2395,No,macaroni/pasta,dog,Yes,night owl,Maybe,"New York, Lucki"
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,No,22,Engineering: Other,,,53703,12.3715,-1.5197,No,sausage,neither,No,no preference,Yes,Flowers by Samantha Ebert
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,20,Science: Biology/Life,,Spanish,53715,39.4822,-106.0435,No,pepperoni,dog,No,no preference,No,"Title ""Rockin' in the Free World""
+
+Artist: Neil Young"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,19,Science: Biology/Life,,,53715,43.05,-89.45,No,pepperoni,dog,No,early bird,Maybe,Pictures of You by The Cure
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,,,Engineering: Mechanical,,,54944,44,-89,No,sausage,dog,No,night owl,Yes,Apple Pie by Travis Scott
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,20,Data Science,,Maybe stats,53703,43.0731,-89.4012,Yes,sausage,dog,No,night owl,Maybe,Jay Chou
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,N/A,N/A,53706,40.7128,-74.006,No,basil/spinach,dog,No,night owl,Maybe,"Two Princes - Spin Doctors
+
+ "
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,20,Engineering: Biomedical,,,53715,41.8781,-87.6298,No,mushroom,dog,No,early bird,Maybe,Maria by Justin Bieber 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,20,Other (please provide details below).,Economics ,Statistics ,53703,37.5,127.02,No,pepperoni,dog,No,night owl,Maybe,Rewrite the Stars (Zac Efron and Zendaya) 
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,19,Other (please provide details below).,Political Science,Business: Finance,53703,40.7128,-74.006,Maybe,none (just cheese),dog,No,early bird,Yes,America by Simon and Garfunkel 
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,19,Data Science,,"Legal Studies, International Studies",53706,53.9045,27.5615,Yes,sausage,cat,No,no preference,Yes,Spanish Eyes - Ricky Martin
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Engineering: Industrial,,,53706,43.18,-89.21,Maybe,sausage,dog,No,night owl,No,Telescope cage the elephant
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,20,Other (please provide details below).,Economics,Mathematics,53590,71,42,No,mushroom,dog,Yes,night owl,No,You're The One by The Vogues 
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,Yes,19,Other (please provide details below).,Undecided but scouting out Information Science as a major.,Also considering a Comm Arts major. ,53711,43.0731,-89.4012,Yes,sausage,dog,Yes,no preference,Yes,Kick Your Game -> TLC
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,19,Science: Other,Genetics and Genomics,,53706,42.3601,-71.0589,Maybe,pepperoni,dog,No,night owl,No,Champagne Problems Taylor Swift
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,18,Engineering: Biomedical,,,53706,37.8136,144.9631,Maybe,basil/spinach,cat,Yes,night owl,Yes,"sunday morning views
+
+by: Drod"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,Yes,20,Data Science,,,53703,43.0731,-89.4012,Yes,pepperoni,dog,No,night owl,Yes,Let Go - Aaron May
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,19,Engineering: Biomedical,,,53706,29.9012,-81.3124,No,pepperoni,dog,No,early bird,Yes,Dreams by Fleetwood Mac
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,19,Data Science,,Economics,53706,51.5074,-0.1278,Yes,pepperoni,dog,Yes,no preference,No,Good Life by Kanye West
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,20,Engineering: Biomedical,,,53715,43.6123,-110.7054,No,pepperoni,dog,Yes,early bird,No,When It Rains It Pours by Luke Combs
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,18,Engineering: Mechanical,,,53706,62.8126,-150.2252,No,pepperoni,dog,No,no preference,Maybe,Forever - Noah Kahan
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,18,Engineering: Industrial,,,53706,27.2679,-82.5555,No,macaroni/pasta,dog,No,night owl,No,Unwritten by Natasha Bedingfield
+"COMP SCI 220:LEC004, COMP SCI 220:LAB342",LEC004,Yes,20,Business: Other,Accounting,Information Systems,53703,44.8977,-85.9916,No,pepperoni,dog,Yes,night owl,Yes,Vienna Billy Joel
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,Yes,20,Science: Other,,Computer Science,53715,70.221,-148.39,No,sausage,cat,No,night owl,No,"I Miss You, Blink-182"
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,20,Science: Biology/Life,,,53726,42.3,-711,No,green pepper,cat,Yes,early bird,No,Silver Lining by Mt. Joy
+"COMP SCI 220:LEC004, COMP SCI 220:LAB344",LEC004,No,19,Data Science,,,53715,36.154,-99.952,Yes,basil/spinach,neither,No,night owl,Yes,Jealous - Eyedress
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,Yes,18,Statistics,,,53706,42.3555,71.0565,Maybe,basil/spinach,dog,No,night owl,Maybe,Dreams by Fleetwood Mac
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,pepperoni,dog,Yes,early bird,Maybe,Restless Mind by Sam Barber
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,20,Engineering: Other,Engineering: Aerospace,"Aerospace Engineering, Data Science ",53703,74.006,40.7128,Yes,pepperoni,dog,Yes,night owl,Yes,"American Pie, Don McLean "
+"COMP SCI 220:LAB342, COMP SCI 220:LEC004",LEC004,No,21,Statistics,,Mathematics,53703,39.9042,116.4074,No,mushroom,cat,No,no preference,Maybe,Mind over Matter by PVRIS
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,19,Engineering: Mechanical,non,non,,33.5138,33.5138,No,mushroom,neither,No,early bird,Maybe,"1) Hobbak Metl Beirut- elissa
+
+2) Mararti Bisadri - Kadim Al Sahir 
+
+3) Betew7ashini- Weal Jassar
+
+ "
+"COMP SCI 220:LAB336, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Mechanical,,,53706,34.2121,-119.0341,No,macaroni/pasta,cat,Yes,no preference,Maybe,7 Summers - Morgan Wallen
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,No,19,Other (please provide details below).,Economics,none,53706,41.8781,-87.6298,No,mushroom,neither,Yes,night owl,Yes,mind over matter by Young the Giant.
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC002,Yes,18,Engineering: Mechanical,,,53706,20.7754,-156.4534,No,sausage,dog,No,night owl,Yes,Take Me Out - Franz Ferdinand
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,19,Engineering: Mechanical,,"AMEP -  Applied Mathematics, Engineering and Physics Program",53703,9.3183,76.6135,No,sausage,dog,No,night owl,Yes,TobyMac help is on the way
+COMP SCI 319:LEC002,LEC002,Yes,27,Data Science,N/A,N/A,53705,25.033,121.5654,Maybe,mushroom,cat,Yes,early bird,Maybe,I drink wine - Adele
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,19,Data Science,,,53706,20.6752,-103.3473,Yes,pepperoni,dog,Yes,night owl,Yes,El hijo major- junior H 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,Yes,18,Engineering: Mechanical,/,/,53706,30.5728,104.0668,No,pepperoni,neither,No,night owl,Maybe,Call of silence / gemie
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,18,Engineering: Mechanical,,,53151,42.9955,-88.0957,No,pepperoni,dog,No,night owl,Yes,none
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,Yes,18,Engineering: Mechanical,,,53706,41.8781,-87.6298,No,pepperoni,dog,Yes,no preference,Maybe,Under the Bridge by Red Hot Chili Peppers 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,No,20,Science: Biology/Life,,,53703,51.5074,-0.1278,No,pineapple,cat,No,night owl,Yes,When Am I Gonna Lose You by Local Natives
+COMP SCI 319:LEC003,LEC003,No,33,Data Science,,,53704,43.7102,7.262,No,pepperoni,dog,Yes,night owl,Yes,Cruel Summer - Taylor Swift
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,19,Other (please provide details below).,Economics,,53715,22.5726,88.3639,Maybe,Other,dog,No,night owl,Yes,Norwegian Wood by The Beatles
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,19,Engineering: Industrial,,,53703,44.0221,-92.4666,No,pepperoni,dog,No,night owl,Yes,UK rap- central cee/dave
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,19,Science: Physics,,,53706,35.676,139.65,No,basil/spinach,dog,Yes,night owl,Yes,My favorite song is Stayin Alive from the Bee Gees 
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Other (please provide details below).,economics,data science,53715,32.72,-117.16,No,sausage,dog,Yes,early bird,Yes,"You're the one kaytranada, syd"
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,20,Business: Finance,,Business: Management,53703,21.1619,-86.8515,Maybe,pepperoni,dog,No,night owl,Maybe,Kryptonite by The Better Life
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,19,Business: Finance,N/A,Real Estate,53706,42.355,-71.057,No,pepperoni,dog,Yes,night owl,Yes,"Crazy Story Pt 3
+
+King Von"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,18,Data Science,,Economics,53706,32.69,-117.18,Yes,pepperoni,dog,Yes,no preference,Maybe,Tin Man - America
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,Yes,19,Other (please provide details below).,Astrophysics,"Data science, physics",53706,43.06,88.4042,Yes,mushroom,dog,Yes,night owl,Yes,Tear in Space- Glass Animals
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,20,Computer Science,,,53175,51.5074,-0.1278,No,pepperoni,cat,No,night owl,Yes,Sex [EP Version] - The 1975
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,19,Engineering: Other,EE,Spanish,53715,40.4168,-3.7038,Maybe,basil/spinach,dog,No,no preference,No,Lune by Moya
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,19,Science: Biology/Life,,,53715,10.012,76.2901,No,pineapple,dog,Yes,night owl,No,good things fall apart by Jon Bellion
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,20,Engineering: Mechanical,n/a,n/a,53715,49.9712,10.4182,No,pepperoni,dog,No,night owl,Yes,Homecoming- Kanye
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,19,Engineering: Mechanical,,,53706,37.0475,112.5263,No,sausage,dog,Yes,early bird,No,Stick Season - Noah Kahan 
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,18,Computer Science,n/a,Mathematics,53706,45.4408,12.3155,Maybe,mushroom,neither,No,night owl,Maybe,Instant Crush - Daft Punk
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,21,Science: Chemistry,n/a,n/a,53703,40.62,14.48,No,macaroni/pasta,cat,No,night owl,No,Club can't handle me - Flo Rida
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,19,Business: Actuarial,N/A,N/A,53703,40.7128,-74.006,Maybe,pepperoni,dog,Yes,night owl,Maybe,Sunshine by Steve Lacy 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,19,Engineering: Mechanical,,,53706,35.8819,-106.3077,No,pepperoni,dog,Yes,early bird,Yes,All my love - Noah Kahan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,Yes,21,Statistics,,,53715,35.9078,127.7669,Yes,mushroom,cat,Yes,no preference,No,Take On Me by a-ha
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,20,Other (please provide details below).,Economics,Chinese,53703,20.7815,-156.4627,No,pepperoni,cat,No,night owl,Yes,She will be loved by Maroon5
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,18,Business: Information Systems,,,53706,40.7128,-74.006,No,pepperoni,dog,No,early bird,No,"24/7, 365 by Elijah Woods"
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,19,Business: Information Systems,,,53715,53.9006,27.559,Yes,sausage,dog,No,night owl,Yes,Breaking Dishes - Rihanna
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,18,Science: Biology/Life,NA,NA,53715,31.2304,121.4737,Yes,pepperoni,dog,No,night owl,Yes,Like Me Better -Lauv
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Engineering: Mechanical,,,53706,-33.8688,151.2093,No,pepperoni,dog,No,night owl,Maybe,"Bones, Imagine Dragons"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,20,Data Science,,"Data Science, Molecular and Cell Biology",53715,39.9,116.36,Yes,sausage,dog,No,night owl,Yes,Last Dance - Bigbang
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,20,Business: Finance,,Real Estate,53703,40.718,-74.3587,No,none (just cheese),dog,No,early bird,Maybe,One of these Nights - Eagles
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,21,Data Science,N/A,Economics,53711,40,116,Yes,pineapple,cat,No,no preference,Yes,Hastune Miku
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,20,Computer Science,,,53706,40.7128,-74.006,No,Other,dog,Yes,night owl,Maybe,Blackjack ---> Gunna
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,Yes,19,Engineering: Biomedical,na,Looking possibly for a different field of engineering ,53715,43.7382,11.2299,No,sausage,dog,No,night owl,Yes,"Echo by Incubus (So good, live for the guitar riff at the beginning and the chorus vocals)"
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC001,Yes,19,Engineering: Industrial,N/A,N/A,53703,43.7684,11.2562,No,pepperoni,dog,Yes,night owl,Yes,Disorder by Joy Division
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,20,Engineering: Biomedical,,,53715,51.5074,-0.1278,No,pepperoni,cat,No,no preference,Maybe,"We Are Young
+
+fun."
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,20,Data Science,,,53726,39.9042,116.4074,Yes,pepperoni,dog,No,night owl,Yes,Toxic by Meovv 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,18,Data Science,,"Economics, Consulting Certificate",53706,41.8818,-87.6232,Yes,pepperoni,dog,Yes,early bird,Maybe,"Cigarettes and Coffee, Otis Retting"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC002,No,19,Business: Information Systems,,Business: Operations Technology Management,53703,43.3216,-87.9518,No,sausage,dog,Yes,early bird,Yes,Biggest Part of Me - Ambrosia 
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,20,Engineering: Mechanical,,,53703,43.0309,-87.9047,No,mushroom,cat,No,no preference,No,I can't get no satisfaction - Rolling stones 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,20,Engineering: Mechanical,,,53715,44.9778,-93.265,No,pineapple,cat,No,night owl,Yes,Total Eclipse of the Heart by Bonnie Tyler
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,18,Data Science,,Economics,53706,,,Yes,pepperoni,dog,No,night owl,Yes,
+"COMP SCI 220:LEC002, COMP SCI 220:LAB324",LEC002,No,19,Science: Biology/Life,,Psychology,53715,43.0758,-89.4001,No,mushroom,dog,No,night owl,Yes,Redbone by Childish Gambino
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,Yes,18,Data Science,Data Science,Risk Management,53706,41,2.17,Yes,sausage,dog,No,early bird,Yes,See you again-Tyler the Creator
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,18,Data Science,,,53706,22.8948,-109.9152,Yes,none (just cheese),dog,Yes,early bird,No,miami- will smith
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,Yes,21,Other (please provide details below).,economics,n/a,53715,74.006,40.7128,Yes,pepperoni,dog,No,night owl,Yes,riptide 
+COMP SCI 319:LEC002,LEC002,Yes,29,Science: Other,Geosciences Graduate Student,,53715,41.3851,2.1734,No,pineapple,dog,No,night owl,Yes,Xtal Aphex Twin
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,Yes,18,Other (please provide details below).,Cartography & Geographic Information Systems,,53703,41.88,-87.6,No,sausage,cat,No,night owl,Yes,The Other Side of Paradise - Glass Animals
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,19,Other (please provide details below).,My primary major is Biochemistry,,53726,43.0703,-89.422,No,pepperoni,cat,No,night owl,Maybe,My favorite singer is SZA
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,18,Engineering: Biomedical,,,53706,37.9838,23.7275,No,sausage,dog,No,night owl,No,Forever by Noah Kahan
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,20,Other (please provide details below).,"Environmental Sciences, but planning on transferring to the industrial engineering major",,53703,-12.0464,-77.0428,No,pepperoni,cat,No,night owl,Yes,circles - mac miller
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,20,Engineering: Biomedical,,,53726,33.8847,-118.4109,No,pepperoni,dog,No,night owl,Yes,"Title: Self Esteem
+
+Artist: The Offspring"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,Yes,18,Engineering: Other,Civil Engineering,,53706,43.0645,-88.1192,No,pepperoni,dog,Yes,no preference,No,"Mother Natures Song, By the Beatles"
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,20,Science: Physics,,Currently working my way into the mechanical engineering major,53703,23.725,-100.5469,No,sausage,dog,Yes,night owl,No,Loco - Neton Vega
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,Yes,20,Data Science,,,53706,71,42,Yes,pepperoni,cat,No,night owl,,Threat of Joy - The Strokes
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,18,Engineering: Biomedical,,,53706,18.4663,-66.1052,No,sausage,dog,No,night owl,Yes,Close to you by Gracie Abrams 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,No,18,Business: Other,Business: Accounting,Business: Information Systems,54942,51.51,0.12,No,Other,dog,Yes,night owl,Yes,Laser-Shooting Dinosaur by Angus McSix
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,20,Engineering: Biomedical,N/A,N/A,55449,35.6895,139.6917,No,pepperoni,dog,Yes,night owl,Yes,"Mystery Lady - Masego, Don Toliver"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB325",LEC002,Yes,18,Statistics,,Cell Biology,53075,,,No,basil/spinach,cat,Yes,early bird,No,Be Sweet by Japanese Breakfast
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,Yes,18,Data Science,,Economics,53706,37.3859,-5.9906,Yes,none (just cheese),dog,Yes,night owl,Yes,"Assassin, John Mayer"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,19,Engineering: Mechanical,,,53715,25,-80,No,pepperoni,dog,No,night owl,Yes,All Your'n- Tyler Childers
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,Yes,19,Engineering: Biomedical,,,53704,44.5133,-88.0133,No,sausage,dog,No,night owl,No,Under Pressure - Queen
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Biomedical,,,53706,19.64,-155.9969,No,green pepper,dog,Yes,early bird,Maybe,Dreams Fleetwood Mac
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,No,20,Engineering: Other,,,53528,40.7128,-74.006,No,pepperoni,dog,No,no preference,Maybe,Amazonia by Gorjira
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,19,Other (please provide details below).,Economics,,53706,37.3414,-122.0284,No,pineapple,dog,No,night owl,Yes,"One of These Nights, Eagles"
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,Yes,18,Computer Science,,"Data Science, Economics",53706,51.5074,-0.1278,Yes,pepperoni,dog,Yes,night owl,Yes,16 by Baby Keep
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,No,18,Other (please provide details below).,"Music: Performance
+
+Engineering/Science/Undecided?",,53706,49.8,-63.3,No,pepperoni,dog,No,early bird,Yes,"Just the Way You Are, Billy Joel"
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,19,Engineering: Biomedical,,,53706,46.4761,-93.9014,No,sausage,cat,Yes,night owl,Maybe,"One of my favorite songs is ""New Perspective"" by Noah Kahan."
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Mechanical,,,53706,38.9072,-77.0369,No,pepperoni,cat,No,night owl,Yes,Weird Fishes - Radiohead
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,No,18,Statistics,,,53706,33.4484,-112.074,Maybe,pepperoni,dog,No,night owl,Maybe,Springsteen by Eric Church
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Biomedical,,,53706,47,87,No,pepperoni,dog,Yes,early bird,Maybe,Upside down Jack Johnson 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,No,18,Other (please provide details below).,Economics,Data Science,53706,41.8781,-87.6298,Yes,macaroni/pasta,cat,Yes,early bird,Yes,Bad Boy - Red Velvet
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,Yes,19,Data Science,,,53706,46.8182,8.2275,Yes,none (just cheese),dog,Yes,early bird,Maybe,Classic music
+"COMP SCI 220:LAB322, COMP SCI 220:LEC002",LEC002,No,20,Engineering: Biomedical,,,53703,41.9028,12.4964,No,mushroom,dog,No,night owl,Maybe,"Dancing queen, ABBA"
+"COMP SCI 220:LEC002, COMP SCI 220:LAB323",LEC002,Yes,19,Mathematics/AMEP,,Economics,53706,31,121,Maybe,pineapple,neither,No,night owl,Yes,ma meilleure ennemie
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC002,No,19,Engineering: Mechanical,,,53706,30.246,87.7,No,sausage,dog,Yes,night owl,Yes,A Cold Sunday - Lil Yachty
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Science: Biology/Life,,data science,53715,32.0603,118.7969,Maybe,mushroom,cat,No,night owl,No,counting star
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,19,Science: Other,,Data science,53706,32.8328,-117.2713,Maybe,sausage,cat,Yes,night owl,Maybe,Please Please Please - Sabrina Carpenter
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,18,Other (please provide details below).,education policy,,53706,48.8566,2.3522,No,sausage,dog,No,night owl,Yes,Better Than - Lake Street Dive
+"COMP SCI 220:LAB324, COMP SCI 220:LEC002",LEC002,No,18,Business: Actuarial,N/A,Risk Management & Insurance,53706,39.9526,-75.1652,No,macaroni/pasta,cat,No,no preference,Maybe,See you again - Tyler the Creator
+COMP SCI 319:LEC001,LEC001,Yes,22,Engineering: Biomedical,,,53705,31.2304,121.4737,Maybe,mushroom,dog,No,no preference,Yes,"city of stars, ryan gosling & emma stone"
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Mechanical,,,53715,48.86,2.3488,No,pepperoni,dog,No,night owl,Maybe,Silver Springs- 2004 remastered By: Fleetwood Mac
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,19,Science: Other,,Data science,53706,32.8328,-117.2713,Maybe,sausage,cat,Yes,night owl,Maybe,Good Graces - Sabrina Carpenter
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,18,Engineering: Biomedical,,,53715,26.1267,-81.7863,No,none (just cheese),cat,Yes,early bird,No,Ground Khalid
+"COMP SCI 220:LAB323, COMP SCI 220:LEC002",LEC002,No,19,Business: Actuarial,,Risk Management & Insurance,53706,-87.6298,41.8781,Maybe,pineapple,cat,Yes,night owl,No,Electric Relaxation by a Tribe Called Quest
+"COMP SCI 220:LAB326, COMP SCI 220:LEC002",LEC002,No,18,Business: Actuarial,,,53703,45.1602,-87.1719,No,pepperoni,dog,No,no preference,No,Les by Childish Gambino
+COMP SCI 319:LEC002,LEC002,Yes,23,Other (please provide details below).,Agricultural and Applied Economics,N/A,53703,37.87,112.55,Maybe,pepperoni,cat,No,early bird,Yes,Unconditional by Eason Chan
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC001,Yes,19,Data Science,N/.A,Economics,53706,43.8,123.5,Maybe,mushroom,dog,No,early bird,No,lie BTS
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Data Science,,,57303,43.8514,-89.1338,Yes,pineapple,cat,No,night owl,Yes,Better Off Alone - Alice Deejay
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,22,Science: Biology/Life,,Neurobiology,53715,44.0121,-92.4802,No,sausage,dog,Yes,early bird,Yes,"Five Leaf Clover, Luke Combs"
+"COMP SCI 220:LAB325, COMP SCI 220:LEC002",LEC002,Yes,18,Engineering: Biomedical,,,53706,39.9526,-75.1652,No,pepperoni,dog,Yes,night owl,No,Any colour you like - Pink Floyd 
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,19,Data Science,,,53715,32.0853,34.7818,No,pepperoni,dog,No,night owl,Maybe,New Years Day by Charlie Robison
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Mechanical,,Business: Other,53726,41.8781,-87.6298,Yes,pepperoni,dog,Yes,no preference,Yes,Billy Joel- Vienna
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Biomedical,,,53706,20.8771,-156.6813,No,basil/spinach,dog,No,no preference,Yes,If We Were Vampires by Jason Isbell and the 400 Unit
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,Yes,18,Engineering: Other,Undecided,,53706,32,118,No,sausage,neither,No,night owl,Yes,
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,19,Engineering: Biomedical,,,53715,51.5074,-0.1278,No,none (just cheese),cat,No,night owl,Yes,Take  it  easy by the eagles
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,19,Engineering: Mechanical,,,53706,36.1946,139.043,No,Other,dog,No,no preference,Maybe,Killer Queen Queen
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,Yes,18,Engineering: Biomedical,,,53706,44.9778,-93.265,No,basil/spinach,dog,Yes,night owl,Yes,She Lit a Fire by Lord Huron
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,29.4316,106.9123,No,pepperoni,neither,Yes,no preference,Yes,
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53089,-17.7134,178.065,No,sausage,dog,No,night owl,Yes,"A Bar Song, Shaboozey"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,Yes,21,Other (please provide details below).,Economics,,53703,44.7785,-81.2872,Maybe,sausage,dog,No,night owl,No,seasons-wave to earth
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,18,Engineering: Mechanical,,,53706,35.6764,139.65,No,sausage,dog,No,night owl,Maybe,4 Your Eyez Only - J Cole
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,No,19,Engineering: Mechanical,,,53706,17.1584,-89.0691,No,pepperoni,dog,No,night owl,Yes,Thinkin Bout You - Frank Ocean
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Other,,"Geology & Geophysics, Mathematics",53705,43.0731,-89.4012,No,pepperoni,cat,Yes,night owl,No,Uptown Girl (Billy Joel)
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Engineering: Biomedical,,,53706,44.6366,-124.0545,No,basil/spinach,cat,No,night owl,Yes,Paul Revere by Noah Kahan
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,No,19,Engineering: Biomedical,,,53706,42.3555,71.0565,No,sausage,dog,No,early bird,No,Second Hand News by Fleetwood Mac
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,18,Engineering: Biomedical,,,53706,38.9072,-77.0369,No,none (just cheese),dog,No,no preference,No,III. Telegraph Ave - Childish Gambino
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,19,Business: Actuarial,,"Data Science, Risk Management & Insurance",53711,32.2154,-80.7476,Yes,basil/spinach,dog,Yes,early bird,No,
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,18.3463,-65.8137,No,pepperoni,dog,No,night owl,Yes,Alive! by Bakar
+"COMP SCI 220:LAB341, COMP SCI 220:LEC004",LEC004,Yes,19,Business: Actuarial,,Risk Management and Insurance,53703,41.9028,12.4964,No,pepperoni,dog,Yes,early bird,No,Timeless-The Weeknd
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53703,45.0981,-93.4445,No,basil/spinach,dog,Yes,early bird,Yes,"st elmos fire, john parr"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC004,Yes,24,Engineering: Mechanical,,,52719,43.0747,89.3842,No,Other,cat,No,night owl,Yes,"""Through Me"" - Hozier"
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,Yes,20,Other (please provide details below).,I am still undecided but maybe data science or economics,,53715,31.4912,120.3119,Maybe,mushroom,cat,No,no preference,Yes,The songs of Jay Chou!
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,18,Engineering: Mechanical,,,53706,28.06,-80.56,No,sausage,dog,No,night owl,Maybe,Wish You Were Here- Pink Floyd
+"COMP SCI 220:LEC003, COMP SCI 220:LAB335",LEC003,Yes,19,Data Science,,,53715,41.885,-87.6215,Yes,none (just cheese),dog,Yes,night owl,Yes,Starman - David Bowie
+COMP SCI 319:LEC001,LEC001,No,23,Other (please provide details below).,Economics,,53711,43.0731,-89.4012,No,pineapple,dog,No,early bird,No,Any Taylor Swift
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,18,Data Science,Psychology,,53703,33.3875,120.1233,Yes,none (just cheese),dog,No,night owl,No,Whiplash from aespa.
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,21,Science: Other,,I have a minor in Data Science. ,53726,35.6895,139.6917,No,sausage,cat,No,no preference,Yes,Lit Up by Buckcherry.
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,20,Engineering: Mechanical,,,53706,40.7,74,No,pepperoni,dog,Yes,early bird,No,Ms. Jackson - Outkast
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,21,Engineering: Mechanical,,,53703,44.9886,93.268,No,pepperoni,dog,No,night owl,Yes,Land of the Snakes - J Cole
+"COMP SCI 220:LEC002, COMP SCI 220:LAB321",LEC002,No,18,Statistics,,,53715,-28.0015,153.4285,Maybe,pepperoni,cat,No,no preference,Yes,"1:37
+
+OMORI OST - 005 By Your Side.
+
+by OMOCAT"
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Statistics,,,53715,43,11,No,pineapple,dog,Yes,early bird,No,called on me
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,19,Other (please provide details below).,Legal Studies,Information Science,53715,48.3707,-114.1866,No,sausage,cat,No,night owl,Maybe,When the Sun Hits by Slowdive
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,No,19,Engineering: Biomedical,,,53072,40.4111,-105.6413,No,pepperoni,neither,No,no preference,Maybe,"I have a wide range of music variety that I like, from Noah Khan to Pitbull I really don't have a preference. But recently I have been listening to brown eye girl by van morrison."
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,19,Engineering: Other,,,53706,26.142,81.7948,No,pepperoni,dog,Yes,early bird,Yes,Champagne Supernova by Oasis
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,Yes,19,Engineering: Mechanical,,,53706,42.4627,2.455,No,pepperoni,dog,No,night owl,Yes,Dreamer - Laufey
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,22,Business: Other,Business: Marketing. ,,53703,36.1993,117.0643,No,pepperoni,cat,No,night owl,Yes,Title: 雑踏、僕らの街 (Wrong World). Artist: TOGENASHI TOGEARI
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Other (please provide details below).,Economics with Math Emphasis,certificates in data science and asian American studies,53706,25.033,121.5654,Maybe,basil/spinach,dog,Yes,night owl,Yes,Bolo by Penomeco 
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,19,Business: Information Systems,,,53703,41.8781,-87.6298,Maybe,pepperoni,dog,No,night owl,No,My Eyes - Travis Scott
+"COMP SCI 220:LAB343, COMP SCI 220:LEC004",LEC004,No,21,Other (please provide details below).,电子信息工程,,53703,31.2304,121.4737,Yes,sausage,cat,No,no preference,Yes,Without You -- Avicii
+"COMP SCI 220:LAB333, COMP SCI 220:LEC003",LEC003,No,18,Other (please provide details below).,Biochemistry,Neurobiology,53706,-13.532,-71.9675,No,mushroom,dog,No,night owl,Yes,"Drugs, Sex and Hella Melodies by Don Toliver"
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,41.8781,87.6298,No,none (just cheese),dog,Yes,early bird,Yes,Vienna Billy Joel
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,18,Other (please provide details below).,"Right now I’m undecided in the college of Letters and Science, but I’m thinking about applying to the school of engineering potentially.",,53706,58.4566,16.8331,Maybe,pepperoni,dog,Yes,night owl,Yes,get away from you— Jason Aldean
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,No,19,Engineering: Biomedical,,,53706,45.4384,10.9917,No,pepperoni,dog,No,night owl,Maybe,Si antes te hubiera conocido Karol G
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,19,Other (please provide details below).,Astronomy-Physics,,53706,46.0105,-95.6817,No,pineapple,cat,No,early bird,No,Let it Die - Foo Fighters
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,21,Data Science,,,53715,41.8781,-87.6298,Yes,sausage,cat,No,night owl,Maybe,Southern Nights by Glen Campbell
+"COMP SCI 220:LAB334, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Biomedical,,,53706,40.7128,-74.006,No,pineapple,dog,No,night owl,Yes,Babydoll by Dominic Fike
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,Yes,19,Engineering: Biomedical,,Material Science and Engineering ,53706,40.416,-3.7,No,pepperoni,neither,No,early bird,Maybe,indigo- Sam Barber
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,Yes,19,Other (please provide details below).,Astronomy-Physics,Data Science,53711,31,121,Yes,pepperoni,neither,No,no preference,Maybe,"Shoulder of Giants, Various Artists (2009)"
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,20,Data Science,Data science,,53703,40.7128,-74.006,Yes,basil/spinach,neither,Yes,early bird,Yes,Love Song
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,18,Business: Information Systems,,Management ,53703,41.5933,-74.5039,No,basil/spinach,dog,No,night owl,No,One of my favorite songs is Umbrella by Rihanna. 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,Yes,19,Other (please provide details below).,Atmospheric & Oceanic Sciences,,53711,35,139,Yes,pepperoni,cat,No,night owl,Maybe,
+"COMP SCI 220:LAB335, COMP SCI 220:LEC003",LEC003,Yes,19,Engineering: Mechanical,,,53706,40.015,105.2705,Maybe,sausage,dog,No,night owl,Yes,"Laramee
+
+Ritchy Mitch and the coal miners"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,,Business: Other,,,53706,31.23,121.47,Yes,sausage,cat,No,night owl,Yes,The race by Chris James 
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,20,Other (please provide details below).,Psychology ,none,53703,55.6761,12.5683,No,Other,dog,No,no preference,Yes,Precious by Depeche Mode is my absolute favorite song of all time
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,21,Science: Biology/Life,,Zoology & Conservation Biology,53703,35.6895,139.6917,No,pepperoni,cat,Yes,early bird,Maybe,"Give Me My Heart Back, Masked Wolf"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,,18,Mathematics/AMEP,,,53706,54.3722,18.6383,No,pepperoni,cat,No,no preference,Yes,"Toutes les machines ont un cœur
+
+Maëlle"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,Yes,19,Data Science,,Math based Economics,53705,34.6937,135.5022,Yes,Other,cat,No,night owl,Yes,"Higher, Creed"
+"COMP SCI 220:LAB331, COMP SCI 220:LEC003",LEC003,No,19,Data Science,,,53715,43.7102,7.262,Maybe,pepperoni,cat,No,early bird,Yes,Silver Lining - In Guards We Trust
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,19,Engineering: Mechanical,,,53706,43.0731,-89.4012,Maybe,sausage,dog,No,night owl,Yes,
+COMP SCI 319:LEC001,LEC001,,24,Science: Biology/Life,,,53711,33.9331,-83.3389,No,none (just cheese),cat,Yes,early bird,Maybe,"""Linger"" by The Cranberries"
+"COMP SCI 220:LEC003, COMP SCI 220:LAB336",LEC003,No,19,Science: Biology/Life,Global Health ,Conservation Biology with certificates in Data Science and Environmental Studies and Health Policy ,53715,40.7128,-74.006,Maybe,green pepper,dog,No,night owl,No,Where You Are by John Summit 
+"COMP SCI 220:LEC003, COMP SCI 220:LAB333",LEC003,No,19,Business: Finance,,other major: Risk Management ,53706,45.6793,-111.0466,Maybe,sausage,dog,Yes,night owl,Maybe,devil in a new dress- kanye west
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,20,Other (please provide details below).,Data Science.,Probably economics.,53706,56.4104,-5.4697,Maybe,basil/spinach,dog,No,night owl,Maybe,Surrender by Cheap Trick.
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,18,Engineering: Mechanical,,,53706,43.0686,-89.3988,No,pepperoni,dog,No,night owl,Maybe,"Hanging by a moment, Lifehouse"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Other (please provide details below).,undecided,,53703,28.9704,118.8707,Yes,pineapple,dog,No,night owl,Yes,What She Hasn't Seen - The 1999
+"COMP SCI 220:LEC003, COMP SCI 220:LAB331",LEC003,Yes,18,Business: Information Systems,,I am doing a data science certificate.,53706,39444164,,Maybe,pepperoni,dog,No,night owl,Maybe,Blowing in the wind - Bob Dylan
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,18,Science: Other,Information Science,"English, language & linguistics",53703,43.0731,-89.4012,No,pepperoni,cat,No,night owl,No,La Seine - Vanessa Paradis
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,18,Science: Physics,,,53706,18.4655,-66.1057,No,none (just cheese),cat,No,night owl,Maybe,Rim Tim Tagi Dim by Baby Lasagna
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,Yes,19,Engineering: Biomedical,,,53715,12.9716,77.5946,No,green pepper,cat,No,no preference,Yes,In cold blood 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB326",LEC002,Yes,18,Other (please provide details below).,"Art History, trying to get into business school ",,53706,46.2044,6.1432,No,pepperoni,dog,No,early bird,Yes,"Halo by Beyonce 
+
+someday from the movie Zombies 
+
+mojo so dope by kid kudi 
+
+hotline bling by drake 
+
+scar tissue by Red Hot Chili Peppers "
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,18,Engineering: Industrial,,,53706,-6.2615,106.8106,No,sausage,cat,Yes,early bird,Maybe,luther
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,18,Engineering: Biomedical,,,53706,42.2934,-83.5241,No,none (just cheese),dog,Yes,no preference,Maybe,linger by the cranberries
+"COMP SCI 220:LEC004, COMP SCI 220:LAB341",LEC004,No,20,Engineering: Biomedical,,,53715,46.8721,-113.994,No,pepperoni,dog,Yes,early bird,No,Sara by Fleetwood Mac
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,18,Data Science,,,53706,37.45,25.35,Yes,pepperoni,dog,Yes,night owl,Yes,"Luther, Sza & Kendrick Lamar"
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,19,Other (please provide details below).,Atmospheric and Oceanic Sciences ,,53149,40.3761,-105.5237,No,sausage,dog,Yes,early bird,Maybe,Silver Springs -Fleetwood Mac
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC004,No,19,Engineering: Biomedical,,,94022,41.8781,-87.6298,No,sausage,dog,No,early bird,Yes,Babel - Mumford and Sons 
+"COMP SCI 220:LEC002, COMP SCI 220:LAB322",LEC002,No,19,Business: Finance,,,53706,20.7984,-156.3319,No,mushroom,dog,Yes,early bird,No,"Burn, Burn, Burn - Zach Bryan"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,26,Engineering: Mechanical,,,53703,26.1219,-80.3975,No,none (just cheese),dog,Yes,early bird,Yes,Pitorro de Coco - Bad Bunny
+"COMP SCI 220:LEC001, COMP SCI 220:LAB314",LEC001,Yes,18,Other (please provide details below).,Information Science ,Journalism,53706,40.7306,-73.9352,No,pepperoni,dog,No,night owl,Yes,Push 2 Start by Tyla 
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Biomedical,,,53706,34.1347,-118.0516,Maybe,pepperoni,dog,No,night owl,Yes,Sweet Disposition - The Temper Trap
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,18,Business: Finance,,"Math, potentially data science as well",53706,40.6344,14.6026,Yes,Other,dog,No,night owl,No,Arms wide open by Creed
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,19,Data Science,,,53703,35.6895,139.6917,Yes,pineapple,cat,No,night owl,Maybe,Hiding In The Blue-TheFatRat
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,21,Data Science,,,53726,43.0722,89.4008,Yes,pepperoni,dog,No,no preference,Yes,BON VOYAGE! by Mika Ogawa
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,20,Engineering: Mechanical,,,53706,43.0338,-87.9208,No,pepperoni,cat,No,no preference,Maybe,"Come on, Come Over (Jaco Pastorius)"
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Biomedical,,,53706,25.761,-80.192,No,macaroni/pasta,dog,No,night owl,Yes,Seabird by the Alessi Brothers
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,20,Science: Other,"Economics, Data Science cert",ds cert,53703,41.8781,-87.6298,No,none (just cheese),cat,No,early bird,Maybe,jackie down the line - fontaines d.c.
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,19,Engineering: Mechanical,,,53706,78,15,No,pepperoni,dog,No,night owl,Yes,Seimeisei Syndrome by Camellia ft. Hatsune Miku
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,19,Business: Other,My primary major is Business: Operations and Technology Management,,53715,41.8781,87.6298,No,pepperoni,cat,No,night owl,Yes,"Give You the World - Steve Lacy
+
+Homecoming - Kanye West "
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,Yes,19,Engineering: Industrial,,,53715,38.5382,75.0587,No,pepperoni,neither,Yes,early bird,No,"After Hours, The Weekend"
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,Yes,18,Science: Physics,,,53706,40.7128,-74.006,No,none (just cheese),cat,No,night owl,Yes, benzi box by dangerdoom
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,18,Engineering: Mechanical,Mechanical Engineering,,53706,25.2048,55.2708,No,pepperoni,cat,Yes,night owl,Maybe,Travis Scott: K-pop
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,19,Science: Biology/Life,,,53715,23.6978,120.9605,Yes,mushroom,cat,No,night owl,Yes,Hazel Eyes - BoyWithUke
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,Yes,19,Science: Other,Biology & Environmental Science,Minor: French Language,53706,41.8781,87.6298,No,basil/spinach,dog,No,night owl,Yes,Stir Fry - Migos
+"COMP SCI 220:LAB312, COMP SCI 220:LEC001",LEC001,No,19,Other (please provide details below).,Economics,NA,53706,51.0543,3.7174,Maybe,pepperoni,dog,Yes,early bird,No,Chocolate by The 1975
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,18,Engineering: Mechanical,,,53706,46.0207,7.7491,No,none (just cheese),dog,Yes,no preference,Yes,nangs - tame impala 
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,21,Engineering: Other,Material Science and Engineering,Nuclear Engineering,53715,45.197,-89.647,No,sausage,dog,Yes,early bird,No,"Snow, Zach Bryan
+
+ "
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,18,Engineering: Biomedical,,,53706,46.3489,10.9072,No,mushroom,cat,No,early bird,No,Hysteria - Muse
+"COMP SCI 220:LAB321, COMP SCI 220:LEC002",LEC002,No,,Engineering: Industrial,,,53715,42.3611,-71.0571,Maybe,pineapple,dog,No,early bird,Yes,Burning Man by Dierks Bentley
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,18,Engineering: Mechanical,,,53706,36.5116,-104.9154,No,pepperoni,dog,Yes,no preference,Yes,Doolin-Dalton by the Eagles
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,20,Science: Biology/Life,,,53703,35.6895,139.6917,No,pepperoni,neither,No,night owl,Yes,SPECIALZ by King Gnu
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,19,Engineering: Biomedical,,,53706,44.2832,-88.3132,No,pepperoni,dog,No,night owl,Yes,Nobody Gets Me - SZA
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC002,No,18,Engineering: Mechanical,,,53706,31.2304,121.4737,No,sausage,dog,Yes,no preference,Yes,Room for You - grentperez and Lyn Lapid
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,,Science: Other,,,53705,31.9522,35.2332,No,basil/spinach,cat,No,no preference,Maybe,I don't know that's a tough question
+"COMP SCI 220:LAB346, COMP SCI 220:LEC004",LEC004,Yes,18,Data Science,,,53706,25,55,Yes,pepperoni,dog,Yes,no preference,No,no church in the wild by kanye
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,Yes,19,Data Science,,Accounting,53706,34.0522,-118.2437,Yes,pepperoni,dog,Yes,night owl,Yes,Use Somebody - Kings of Leon
+"COMP SCI 220:LAB314, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Mechanical,,,53706,51.5074,-0.1278,No,mushroom,dog,No,night owl,Yes,Exit Music (For A Film) by Radiohead
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,19,Engineering: Industrial,,French,53715,48.2082,16.3738,No,pepperoni,cat,Yes,night owl,Maybe,Somebody to Love- Queen
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,19,Engineering: Mechanical,,,53715,21.1619,-86.8515,No,sausage,dog,No,night owl,Maybe,Sunflower - post malone
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,No,19,Engineering: Other,,,53706,30.1726,107.8857,No,Other,cat,No,night owl,Yes,Tango-ABIR
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,18,Engineering: Industrial,,,53706,41.8781,-87.6298,No,pineapple,dog,No,early bird,Maybe,Put Your Records On - Corrine Bailey Rae 
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,18,Data Science,,Mathematics,53706,49.4825,20.0318,Yes,green pepper,cat,No,early bird,No,Black by Pearl Jam
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,Yes,19,Engineering: Mechanical,,,53706,41.9028,12.4964,No,sausage,dog,Yes,no preference,Yes,One of these nights or After the Thrill is gone by the Eagles
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,20,Engineering: Mechanical,Mechanical Engineer,,53965,-1.1435,13.9002,No,sausage,dog,No,night owl,Yes,Burn burn burn by Zach bryan
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,21,Science: Biology/Life,,Music Performance ,53703,14.4423,121.044,No,mushroom,cat,Yes,early bird,Maybe,Strawberry Fields Forever - The Beatles
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,Yes,18,Engineering: Mechanical,,,53706,33.7501,84.3885,No,pepperoni,dog,Yes,no preference,Yes,Gasolina - Daddy Yanke
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,No,18,Data Science,,,53706,41.3851,2.1734,Yes,Other,dog,No,early bird,No,Runaway - Kanye West
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,No,19,Engineering: Mechanical,,,53706,45.78,88.5368,No,Other,dog,No,no preference,Yes,"Rockstar, Nickleback"
+COMP SCI 319:LEC001,LEC001,No,25,Other (please provide details below).,PhD student in Animal Sciences studying primarily rumen microbiology,none,53705,45.374,-84.9556,Maybe,mushroom,dog,Yes,early bird,No,Apple Charli xcx
+"COMP SCI 220:LEC001, COMP SCI 220:LAB316",LEC001,No,19,Data Science,,,53715,43.0731,-89.4012,Yes,basil/spinach,cat,No,early bird,No,let down - radiohead
+"COMP SCI 220:LAB313, COMP SCI 220:LEC001",LEC001,No,18,Engineering: Mechanical,,,53703,41.8781,-87.6298,Maybe,none (just cheese),dog,Yes,early bird,No,The Promise by When in Rome
+"COMP SCI 220:LEC001, COMP SCI 220:LAB315",LEC001,No,19,Engineering: Industrial,,,53706,59.9139,10.7522,Maybe,basil/spinach,dog,Yes,early bird,Maybe,wannabe spice girls
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,18,Data Science,,,53706,43.0731,-89.4012,Yes,Other,cat,Yes,early bird,Maybe,penny lane- the beatles
+"COMP SCI 220:LEC003, COMP SCI 220:LAB332",LEC003,Yes,19,Science: Other,"Social science, sociology",Data science,53703,41.8781,-87.6298,Maybe,basil/spinach,cat,No,night owl,Maybe,Lovely Day by Bill Withers
+"COMP SCI 220:LEC001, COMP SCI 220:LAB313",LEC001,No,19,Engineering: Mechanical,,,53706,46,7.7,No,pineapple,dog,Yes,no preference,No,"brandy 
+
+The looking glass"
+"COMP SCI 220:LEC004, COMP SCI 220:LAB346",LEC003,No,19,Other (please provide details below).,Integrative Animal Biology,"Atmospheric and Oceanic Sciences, Folklore certificate",53703,47.75,90.33,No,macaroni/pasta,cat,Yes,night owl,Yes,"Damage Gets Done by Hozier and Brandi Carlile, or Everybody Wants to Rule the World by Tears for Fears"
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,Yes,22,Statistics,,,53715,43.0731,-89.4012,No,pineapple,dog,Yes,early bird,Maybe,Counting Stars
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,21,Engineering: Biomedical,,,53703,6.2476,75.5658,No,pineapple,dog,No,early bird,No,isnt she lovely - Stevie Wonder
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,Yes,18,Science: Physics,,,53706,43.0731,-89.4012,No,sausage,cat,No,no preference,Maybe,Move Along - All American Rejects
+"COMP SCI 220:LEC001, COMP SCI 220:LAB311",LEC001,Yes,22,Engineering: Other,Electronic Computer Engineering,no,53703,24.9893,121.6583,Maybe,macaroni/pasta,dog,Yes,early bird,No,Alexander Hamilton——my shot
+"COMP SCI 220:LAB316, COMP SCI 220:LEC001",LEC001,No,19,Other (please provide details below).,Economics,n/a,53562,41.3851,2.1734,No,mushroom,dog,No,night owl,Maybe,Beer for my horses - Toby Keith
+"COMP SCI 220:LEC001, COMP SCI 220:LAB312",LEC001,No,18,Science: Physics,,,53706,47.5928,-120.6676,Maybe,pepperoni,cat,No,no preference,Yes,Work Song by Hozier
+"COMP SCI 220:LAB332, COMP SCI 220:LEC003",LEC003,No,18,Engineering: Biomedical,,,53706,18.582,-68.4055,No,pepperoni,dog,No,night owl,Yes,Vienna by billy joel 
+COMP SCI 319:LEC004,LEC004,Yes,27,Other (please provide details below).,Financial Economics,,53572,37.9838,23.7275,No,basil/spinach,dog,No,no preference,No,Mr Blue Sky by ELO
+"COMP SCI 220:LEC003, COMP SCI 220:LAB334",LEC003,Yes,18,Engineering: Biomedical,,,53706,41.3851,2.1734,No,mushroom,dog,Yes,early bird,Maybe,Homemade Dynamite by Lorde
+COMP SCI 319:LEC001,LEC001,Yes,35,Engineering: Other,Electrical and Computer Engineering,,53715,36.1839,113.1053,Maybe,sausage,neither,No,early bird,No,An‘he Bridge - Dongye Song
+"COMP SCI 220:LAB315, COMP SCI 220:LEC001",LEC001,No,18,Mathematics/AMEP,,,53706,48.8566,2.3522,Maybe,pineapple,dog,Yes,early bird,No,"FLY ME TO THE MOON
+
+Song by Claire Littley, Kotono Mitsuishi, and Yūko Miyamura"
+"COMP SCI 220:LAB311, COMP SCI 220:LEC001",LEC001,Yes,20,Engineering: Mechanical,,,53706,59.9139,10.7522,No,pepperoni,dog,Yes,early bird,No,Seven Nation Army by White Stripes
+"COMP SCI 220:LEC004, COMP SCI 220:LAB343",LEC001,Yes,19,Data Science,N/A,Economics,54706,43.8,125.3,Maybe,mushroom,dog,No,early bird,No,"wait for it 
+
+Leslie Odom Jr."
+"COMP SCI 220:LAB345, COMP SCI 220:LEC004",LEC004,Yes,20,Data Science,,,53715,34.2544,108.9418,Yes,pepperoni,dog,No,early bird,Maybe,Love Transfer by Eason Chan