{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "
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Enter Password:
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Enter Password:
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\n", "\n", "show code\n", "\"\"\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Exploring Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data Description" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Data and information are so prevalent in our lives today, that it is known as the \"Information Age\". Being literate today means not just being able to read, but being able to understand the massive amount of information thrown at us every day – much of it on the computer. Statistics is the science of making effective use of numerical data. It deals with all aspects of data, including the collection, analysis and interpretation of data. However, it can be easily misinterpreted and manipulated if we don't do it carefully. As **Mark Twain** said\n", "\n", "\\begin{equation}\n", "\\text{\"There are lies, damned lies, and statistics.\"} \\nonumber\n", "\\end{equation}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Percentage\n", "\n", "Percentage is the most frequently used concept in business analytics because of many uncertainties in today's complex business environment. But many times people use it without really understanding its meaning.\n", "\n", "![pct](https://github.com/ming-zhao/Business-Analytics/raw/master/images/pct.png)\n", "\n", "\n", "Percentage is a relative terminology. It is always important to ask \"percentage of what\" as shown in this simple example. \n", "\n", "... of what?\n", "\n", "* Pay: $10,000 per month.\n", "\n", "* \"Sorry guys. You have to have a 10% pay cut.\"\n", "\n", "* Pay: $9,000 per month.\n", "\n", "* \"Now I can give you a 10% pay rise.\"\n", "\n", "* Pay: $9,900 per month.\n", "\n", "**What does \"60% sure or confidence\" mean?**\n", "\n", "This is about probability. If we flip a coin 100 times and see the head 60 times, then we could say that we are 60% sure that next toss will show a head. \n", "\n", "If someone says \"I have 60% confidence that this campaign will increase sales\", the statistical meaning is that if a decision maker can try 100 times under current business environment, s/he may see a sales increase for 60 times." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Question 1:**\n", "\n", "There are 3 sequences (each of them has 10 symbols with 6 Xs and 4 Os):\n", "\n", "1) OXXOXOXOXX\n", "\n", "2) XXOXOOXXXO\n", "\n", "3) XOXXOXOXOX\n", "\n", "Predict the next symbol for those 3 sequences\n", "\n", "* A) 1-O, 2-X, 3-O\n", "* B) 1-X, 2-X, 3-X\n", "* C) 1-O, 2-O, 3-O\n", "* D) 1-X, 2-O, 3-X" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "B is correct. \n", "\n", "A psychology experiment gives subjects a random series of $X$s and $O$s and asks them to predict what the next one will be. For instance, they may see: \n", "\n", "\\begin{equation}\n", "OXXOXOXOXOXXOOXXOXOXXXOXX \\nonumber\n", "\\end{equation}\n", "\n", "Most people realize that there are slightly more $X$s than $O$s — if you count, you'll see it's 60 percent $X$s, 40 percent $O$s — so they guess $X$ most of the time, but throw in some $O$s to reflect that balance. \n", "\n", "However, if you want to maximize your chances of a correct prediction, you would always choose $X$. Then you would be right 60 percent of the time. \n", "\n", "If you randomize 60/40, as most participants do, your prediction ends up being correct **52** percent of the time only slightly better than if you had not bothered to assess relative frequencies of $X$s and $O$s and instead just guessed one or the other (50/50).\n", "\n", "Why 52%?\n", "\n", "Sixty percent of the time you choose X and are correct 60 percent of the time, while 40 percent of the time you choose O and are correct only 40 percent of the time. On average, this is $0.6^2 + 0.4^2 = 0.52$ \n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Question 2:**\n", "\n", "The chance a baby will be a boy (or girl) is 50%. There are two hospitals:\n", "\n", "- A - 45 births per day\n", "- B - 15 births per day\n", "\n", "Which hospital would have more days when 60% or more of the babies born are boys?\n", "\n", "* A) Hospital A\n", "* B) Hospital B\n", "* C) Equal chance\n", "* D) Uncertain" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, B is correct. \n", "\n", "The smaller hospital is correct because the larger the number of events (in this case, births), the likelier each daily outcome will be close to the average (in this case, 50 percent). \n", "\n", "To see how this works, imagine you are flipping coins. You are more likely to get heads every time if you flip 5 coins than if you flip 50 coins. \n", "\n", "Thus, the smaller hospital — precisely because it has fewer births — is more likely to have more extreme outcomes away from the average.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you were a real-estate agent and trying to convince people to move into a particular neighborhood. You could, with perfect honesty and \"truthfulness\" tell different people that the average income in the neighborhood is: a), b) or c). \n", "\n", "![house](https://github.com/ming-zhao/Business-Analytics/raw/master/images/house.png)\n", "\n", "because we have mean, median and mode to characterize the central tendency.\n", "\n", "![avg](https://github.com/ming-zhao/Business-Analytics/raw/master/images/avg.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Data Visualization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If your goal is to lie, cheat, manipulate, or mislead, **Graphical Displays** are your friend...\n", "\n", "![pie](https://github.com/ming-zhao/Business-Analytics/raw/master/images/pie.png)\n", "\n", "**Example 1:**\n", "\n", "![chart1](https://github.com/ming-zhao/Business-Analytics/raw/master/images/chart1.png)\n", "\n", "**Example 2:**\n", "\n", "![chart2](https://github.com/ming-zhao/Business-Analytics/raw/master/images/chart2.png)\n", "\n", "**Example 3:**\n", "\n", "![chart3](https://github.com/ming-zhao/Business-Analytics/raw/master/images/chart3.png)\n", "\n", "**Example 4:**\n", "\n", "![chart4](https://github.com/ming-zhao/Business-Analytics/raw/master/images/chart4.png)\n", "\n", "As \"Statistics is the art of never having to say you’re wrong\", I would like to recommend a book\n", "\n", "![book_lie](https://github.com/ming-zhao/Business-Analytics/raw/master/images/book_lie.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [Case](https://github.com/ming-zhao/Business-Analytics/blob/master/notebooks/parking_violation.ipynb): NYC Parking Violation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We consider packing violation data in NYC from August 2013 to June 2014. The [dataset](https://data.cityofnewyork.us/City-Government/Parking-Violations-Issued-Fiscal-Year-2014-August-/jt7v-77mi\n", ") is available in [NYC Open Data](https://opendata.cityofnewyork.us/). The website NYC Open Data is a collection of 750 New York City public datasets made available by city agencies and organizations.\n", "\n", "The original dataset has 9.1M rows and 43 columns with size more than 1G. The dataset used in this note is already filtered with only hydrant paking violations. The excel file can be downloaded from this [link](https://github.com/ming-zhao/Business-Analytics/raw/master/data/regression/Parking_Violations.xlsx)." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show code\n", " " ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_park = pd.read_csv(dataurl+'Parking_Violations.csv', parse_dates=['Time'])\n", "\n", "# run pivot table\n", "df_pivot = df_park[(df_park['Street Code1']!=0) &\\\n", " (df_park['Street Code2']!=0) &\\\n", " (df_park['Street Code2']!=0)].pivot_table(values='Summons Number',\n", " index='Address',\n", " margins=False,\n", " aggfunc='count').sort_values(by='Summons Number',\n", " ascending=False).head(10)\n", "df_pivot['ticket'] = df_pivot['Summons Number']\n", "df_pivot['fine'] = df_pivot['ticket']*115\n", "df_pivot = df_pivot.drop(['Summons Number'], axis=1)\n", "\n", "toggle()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Show the first 5 rows of the dataset" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Summons NumberRegistration StateIssue DateVehicle Body TypeStreet Code1Street Code2Street Code3Vehicle MakeViolation TimeViolation CountyVehicle ColorVehicle YearTimeAddress
01356906515NY9/18/1971SDN136103727037290MAZDA0914PNYBLK20109:14 PM4165 BROADWAY
11365454538NY2/12/1976VAN372901074010940TOYOT0458AQBLK20074:58 AM49-11 BROADWAY
21355329360NY12/9/1990SUBN352903124031290FORD0902AQBK20039:02 AM4402 BEACH CHANNEL DR
31364794688NY1/12/1991SUBN2710693409540ME/BE0223PQSILVE20052:23 PM40-30 235 ST
41357592103NY1/4/2000SDN04040440404NISSA1045PRSILVE200810:45 PM140 LUDWIGE LANE
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" ], "text/plain": [ " Summons Number Registration State Issue Date Vehicle Body Type \\\n", "0 1356906515 NY 9/18/1971 SDN \n", "1 1365454538 NY 2/12/1976 VAN \n", "2 1355329360 NY 12/9/1990 SUBN \n", "3 1364794688 NY 1/12/1991 SUBN \n", "4 1357592103 NY 1/4/2000 SDN \n", "\n", " Street Code1 Street Code2 Street Code3 Vehicle Make Violation Time \\\n", "0 13610 37270 37290 MAZDA 0914P \n", "1 37290 10740 10940 TOYOT 0458A \n", "2 35290 31240 31290 FORD 0902A \n", "3 27106 9340 9540 ME/BE 0223P \n", "4 0 40404 40404 NISSA 1045P \n", "\n", " Violation County Vehicle Color Vehicle Year Time \\\n", "0 NY BLK 2010 9:14 PM \n", "1 Q BLK 2007 4:58 AM \n", "2 Q BK 2003 9:02 AM \n", "3 Q SILVE 2005 2:23 PM \n", "4 R SILVE 2008 10:45 PM \n", "\n", " Address \n", "0 4165 BROADWAY \n", "1 49-11 BROADWAY \n", "2 4402 BEACH CHANNEL DR \n", "3 40-30 235 ST \n", "4 140 LUDWIGE LANE " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_park.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The top 10 hydrants that collect most of the tickets. Note that the fine for hydrant parking violation is $115. So the column \"fine\" is the revenue generated by each hydrant and the total fine of the top 10 hydrants is $144,440." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total annual revenue of top 10 hydrants 144440\n" ] }, { "data": { "text/html": [ "
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ticketfine
Address
152 Forsyth St17920585
104 Forsyth St13715755
100 Overlook Ter13515525
720 Lenox Ave12714605
122 Montague St12614490
21 W 58th St12514375
2960 Fredrick Douglas Blv11913685
44 Court St11413110
1498 3rd Ave9911385
41-28 Main St9510925
\n", "
" ], "text/plain": [ " ticket fine\n", "Address \n", "152 Forsyth St 179 20585\n", "104 Forsyth St 137 15755\n", "100 Overlook Ter 135 15525\n", "720 Lenox Ave 127 14605\n", "122 Montague St 126 14490\n", "21 W 58th St 125 14375\n", "2960 Fredrick Douglas Blv 119 13685\n", "44 Court St 114 13110\n", "1498 3rd Ave 99 11385\n", "41-28 Main St 95 10925" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Total annual revenue of top 10 hydrants', df_pivot.fine.sum())\n", "df_pivot" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "axes = df_pivot.plot.pie(y='ticket', autopct='%1.1f%%', figsize=(5, 5))\n", "axes.legend(loc='best', bbox_to_anchor=(2,.8))\n", "axes.set_ylabel('')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The most \"valuable\" hydrant is shown in [google street view](https://www.google.com/maps/@40.7206121,-73.9917312,3a,75y,288.92h,55.77t/data=!3m6!1e1!3m4!1s_SBRnIVor2FDGiszffialA!2e0!7i13312!8i6656\n", ")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "IFrame('https://www.google.com/maps/embed?pb=!4v1557893815788!6m8!1m7!1s_SBRnIVor2FDGiszffialA!2m2!1d40.\\\n", "72061441911959!2d-73.99172978854598!3f288.92!4f0!5f0.7820865974627469', width=700, height=400)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "However, according to NYC department of transportation (DOT), this may not be considered as a parking violation. \n", "\n", "![hydrant](https://github.com/ming-zhao/Business-Analytics/raw/master/images/hydrant.png)\n", "\n", "The issue is first spotted by Ben Wellington who is the author of blog [I Quant NY](https://iquantny.tumblr.com/). It certainly has impacts on NYC DOT. Today, the google street map shows" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "IFrame('https://www.google.com/maps/embed?pb=!4v1557932957501!6m8!1m7!1s04LptdatMEwvnW3J_tjGvw!2m2!1d40.\\\n", "72061130331954!2d-73.99171284164994!3f264.0115330665066!4f-27.9676492146982!5f0.7820865974627469', width=700, height=400)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Statistical Inferences" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generally, statistical inferences are of two types: *confidence interval estimation* and *hypothesis testing*." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interval Estimation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In confidence interval estimation, data are used to obtain a point estimate and a confidence interval takes the form\n", "\n", "
\n", "Point Estimate $\\pm$ Multiple $\\times$ Standard Error\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Hypothesis Testing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Statistical Significance" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When you run an experiment, conduct a survey, take a poll, or analyze a set of data, you're taking a sample of some population of interest, not looking at every single data point that you possibly can. Statistical significance helps quantify whether a result is likely due to chance or to some factor of interest. When a finding is (statistically) significant, it simply means you can feel confident that's it real, not that you just got lucky (or unlucky) in choosing the sample. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The Process of Evaluating" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "No matter what you're studying, the process for evaluating significance is the same.\n", "\n", "1. **Establish a null hypothesis** \n", "\n", " Establish a straw man that you're trying to disprove. For example, in an experiment of a marketing campaign, the null hypothesis might be \"on average, customers don't prefer our new campaign to the old one\". In an experiment of introducing new surgical intervention, the null hypothesis might be \"the new surgical intervention cannot reduce the number of patient deaths\".\n", "\n", "
\n", "\n", "2. **Set a target and interpret p-value.** \n", "\n", " The significance level is an expression of how rare your results are, under the assumption that the null hypothesis is true. It is usually expressed as a p-value, and the lower the p-value, the less likely the results are due purely to chance. Setting a target can be dauntingly complex and depends on what we are analyzing. For the surgical intervention, we may want an every low p-value (such as 0.001) to be conservative. But if we are testing for whether the new marketing concept is better, we probably willing to take a higher value (such as 0.2).\n", " \n", "
\n", "\n", "3. **Collect data.**\n", "\n", "
\n", "\n", "4. **Plot the results.** \n", "\n", " The graph will help us to understand the variation, sampling error and statistical significance.\n", "\n", "
\n", "\n", "5. **Calculate statistics.**\n", "\n", "
\n", "\n", "After the process, we want to know if the findings are \"significant\". However, a statistically significant result is not necessarily of practical importance because \n", "\n", "- Practical significance is business relevance\n", "\n", "- Statistical significance is the confidence that a result isn't due purely to chance\n", "\n", "Give an example that statistical significance is not practical significance." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Example: Weight-Loss Program** \n", "\n", "Researchers are studying a new weight-loss program. Using a large sample they construct a $95%$ confidence interval for the mean amount of weight loss after six months on the program to be $[0.12, 0.20]$. \n", "\n", "All measurements were taken in pounds. Note that this confidence interval does not contain $0$, so we know that their results were statistically significant at a $0.05$ alpha level. \n", "\n", "However, most people would say that the results are not practically significant because after six months on a weight-loss program we would want to lose more than $0.12$ to $0.20$ pounds.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Case: Surgical Intervention" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need to decide whether a new surgical intervention is more appropriate for a cancer patient with a brain tumor compared to the standard chemotherapy treatment:" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Hypothetical result 1:**
\n", "The new surgical intervention **significantly** reduced the number of patient deaths compared to the current standard chemotherapy treatment (p=0.04)\n", "\n", "Evaluate the result?" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What is significant? \n", "\n", "Do the analysts mean considerably fewer deaths or just statistically significant fewer deaths? \n", "\n", "It is not clear, but possibly just the latter, since the p-value is reported. Here, we don't have any information on exactly how superior the new surgical intervention was compared to chemotherapy.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Hypothetical result 2:**
\n", "The new surgical intervention **significantly** reduced the number of patient deaths compared to the current standard chemotherapy treatment (p=0.04). After five years, there were two fewer deaths in the intervention group.\n", "\n", "Evaluate the result?" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now the exact difference in number of deaths is provided and it is clear the word \"significantly\" refers to statistical significance in this case, since two is not a large difference. \n", "\n", "As a manager, it is now important to contextualize these results. \n", "\n", "In an exploratory study in which each group had only 10 participants, two fewer deaths in the intervention group would be meaningful and warrant further investigation. \n", "\n", "In a large clinical trial with 1000 participants in each group, two fewer deaths, even if statistically significant, is less impressive. In this case, we would consider the two interventions more or less equal and base our treatment decision on other factors.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Hypothetical result 3:**
\n", "The new surgical intervention **did not statistically significantly** reduce the number of patient deaths compared to the current standard chemotherapy treatment (p=0.07). After five years, there was 1 death in the surgical intervention group and 9 deaths in the standard chemotherapy group.\n", "\n", "Evaluate the result?" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This time we have a statistically **non–significant** result that corresponds to a seemingly large point estimate (8 fewer deaths). \n", "\n", "In this case, it appears the treatment has an important effect but perhaps the study lacks sufficient power for this difference to be statistically **significant**. \n", "\n", "Again, we need more information about the size of the trial to contextualize the results. To simply conclude by virtue of statistical hypothesis testing that this study shows no difference between groups would seem inappropriate.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Case: Market Campaign" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The marketing department comes up with a new concept and you want to see if it works better than the current one. You can't show it to every single target customer, of course, so you choose a sample group. When you run the results, you find that those who saw the new campaign spent $10.17 on average, more than the $8.41 those who saw the old one spent. \n", "\n", "This $1.76 might seem like a big — and perhaps important — difference. But in reality you may have been unlucky, drawing a sample of people who do not represent the larger population; in fact, maybe there was no difference between the two campaigns and their influence on consumers' purchasing behaviors. This is called a sampling error, something you must contend with in any test that does not include the entire population of interest.\n", "\n", "What causes sampling error?" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are two main contributors to sampling error **the size of the sample** and **the variation in the underlying population**.\n", "\n", "**sample size** follows our intuition: \n", " \n", "- All else being equal, we will feel more comfortable in the accuracy of the campaigns' $1.76 difference if you showed the new one to 1,000 people rather than just 25. Of course, showing the campaign to more people costs more, so you have to balance the need for a larger sample size with your budget.\n", " \n", "- The same is true of statistical significance: with bigger sample sizes, you're less likely to get results that reflect randomness. Thus, a small difference, which may not be practical significance, can be statistical significance.\n", " \n", "**variation** is a little trickier to understand.\n", " ![](https://hbr.org/resources/images/article_assets/2016/02/W160214_GALLO_GREATERVARIATION1-1200x589.png)\n", " \n", "- In the graph, each plot expresses a different possible distribution of customer purchases under the campaign. The plot with less variation: most people spend roughly the same amount of dollars. Some people spend a few dollars more or less, but if you pick a customer at random, chances are pretty good that they'll be pretty close to the average. So it's less likely that you'll select a sample that looks vastly different from the total population, which means you can be relatively confident in your results.\n", " \n", "- The plot with more variation: people vary more widely in how much they spend. The average is still the same, but quite a few people spend more or less. If you pick a customer at random, chances are higher that they are pretty far from the average. So if you select a sample from a more varied population, you can't be as confident in your results. \n", " \n", "To summarize, the important thing to understand is that the greater the variation in the underlying population, the larger the sampling error.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Should we adopt the new campaign? Evaluate the new campaign in different scenarios." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The new marketing campaign shows a $1.76 increase (more than 20\\%) in average sales. If the p-values is 0.02, then the result is also statistically significant, and we should adopt the new campaign. \n", "\n", "If the p-value comes in at 0.2 the result is not statistically significant, but since the boost is so large we'll likely still proceed, though perhaps with a bit more caution.\n", "\n", "But what if the difference were only a few cents? If the p-value comes in at 0.2, we'll stick with your current campaign or explore other options. But even if it had a significance level of 0.01, the result is likely real, though quite small. In this case, our decision probably will be based on other factors, such as the cost of implementing the new campaign.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Advice to Managers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**How to evaluate?**" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Although software will report statistical significance, it's still helpful to know the process described above in order to understand and interpret the results because **Managers should not trust a model they don't understand**.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**How do managers use it?**" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Companies use statistical significance to understand how strongly the results of an experiment they've conducted should influence the decisions they make. \n", "\n", "Managers want to know what findings say about what they should do in the real world. But confidence intervals and hypothesis tests were designed to support science, where the idea is to learn something that will stand the test of time. \n", "\n", "So rather than obsessing about whether your findings are precisely right, think about the implication of each finding for the decision you're hoping to make. What would you do differently if the finding were different?\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**What mistakes do managers make?**" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The word \"significant\" is often used in businesses to mean whether a finding is strategically important. When you look at results of a survey or experiment, ask about the statistical significance if the analyst hasn't reported it.\n", "\n", "Statistical significance tests help you account for potential sampling errors, but what is often more worrisome is the *non-sampling error*. Non-sampling error involves things where the experimental and/or measurement protocols didn't happen according to plan, such as people lying on the survey, data getting lost, or mistakes being made in the analysis.\n", "\n", "Keep in mind the practical application of the findings.\n", "\n", "Be all for using statistics, but always wed it with good judgment.\n", "\n", " $\\blacksquare$ " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimating Relationships" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The relationship between circumference and diameter is known to follow the exact equation \n", "\n", "\\begin{equation}\n", "\\text{circumference $= \\pi$ $\\times$ diameter}\n", "\\end{equation}\n", "\n", "However, such a deterministic (or functional) relationship is not our interests. We are interested in statistical relationships, in which the relationship between the variables is not perfect. For example, we might be interested in the relationship between rainfall and product sales, or between the mortality due to skin cancer and state latitude. \n", "\n", "Scatterplots provide graphical indications of relationships, whether they are linear, non-linear or even nonexistent. Correlation $\\rho$ is a numerical summary measures that indicate the strength of **linear relationships** between pairs of variables.\n", "\n", "- If $\\rho$ = -1, then there is a perfect negative linear relationship between $X$ and $Y$.\n", "- If $\\rho$ = 1, then there is a perfect positive linear relationship between $X$ and $Y$.\n", "- If $\\rho$ = 0, then there is no linear relationship between $X$ and $Y$.\n", "\n", "Scatterplots are useful for indicating linear relationships and demonstrate its strength visually. However, they do not quantify the relationship. For example, a scatterplot could show a strong positive relationship between rainfall and product sales. But a scatterplot does not specify exactly what this relationship is. For example, what is the sales amount if the rainfall is, says, 4 inches?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Scatterplots" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here are some typical scatterplots" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " show code\n", " " ], "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "size=100\n", "nrows=2\n", "ncols=3\n", "\n", "np.random.seed(123)\n", "\n", "plt.subplots(nrows, ncols, figsize = (16,8))\n", "plt.subplot(nrows, ncols, 1)\n", "x = np.linspace(0, 10, size)\n", "y = 100 + 4*x+ 4*np.random.normal(size=size)\n", "plt.title(\"Linear relationship (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.subplot(nrows, ncols, 2)\n", "x = np.linspace(0, 10, size)\n", "y = 100 + 100*np.log(3*x+1)+ 30*np.random.normal(size=size)\n", "plt.title(\"Nonlinear relationship (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.subplot(nrows, ncols, 3)\n", "x = np.linspace(0, 10, size)\n", "y = 100*np.sin(x) + 30*np.random.normal(size=size)\n", "plt.title(\"Nonlinear relationship (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.subplot(nrows, ncols, 4)\n", "x = np.linspace(0, 10, size)\n", "y = 100 + 10*np.random.normal(size=size)\n", "plt.title(\"No relationship (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.subplot(nrows, ncols, 5)\n", "x = np.linspace(0, 10, size)\n", "y = 100 + 3*x+ abs(50*x*np.random.normal(size=size))\n", "plt.title(\"Heteroscedasticity (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.subplot(nrows, ncols, 6)\n", "x = np.linspace(0, 10, size)\n", "y = 100 + 4*x+ 5*np.random.normal(size=size)\n", "plt.title(\"Outlier (correlation = {:.3f})\".format(np.corrcoef(x,y)[0,1]))\n", "plt.plot(x, y, 'o');\n", "plt.plot(8, 180, 'o', c='red')\n", "\n", "plt.show()\n", "\n", "toggle()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correlation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- correlation only quantifies the strength of a linear relationship (see example in section of R-squared).\n", "- correlation can be greatly affected by just one data point (see example in section of R-squared).\n", "- correlation can be greatly affected after aggregation." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Data:\n", " age score\n", "0 10 15\n", "1 10 39\n", "2 20 20\n", "3 20 43\n", "4 30 35\n", "correlation: 0.27831712743147 \n", "\n", "Aggregated Data:\n", " age score\n", "0 10 27.0\n", "1 20 31.5\n", "2 30 35.0\n", "correlation: 0.9974059619080593\n" ] }, { "data": { "text/html": [ "\n", " show code\n", " " ], "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "age = [10, 10, 20, 20, 30]\n", "score = [15, 39, 20, 43, 35]\n", "df = pd.DataFrame({'age':age,'score':score})\n", "print('Data:\\n',df)\n", "print('correlation:',np.corrcoef(df.age, df.score)[0,1], '\\n')\n", "\n", "df = df.groupby('age').mean().reset_index()\n", "print('Aggregated Data:\\n',df)\n", "print('correlation:',np.corrcoef(df.age, df.score)[0,1])\n", "toggle()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Freedman, Pisani and Purves (1997) investigated data from the 1988 Current Population Survey and considered the relationship between a man's level of education and his income. They calculated the correlation between education and income in two ways:\n", "\n", "- First, they treated individual men, aged 25-64, as the experimental units. That is, each data point represented a man's income and education level. Using these data, they determined that the correlation between income and education level for men aged 25-64 was about 0.4, not a convincingly strong relationship.\n", "\n", "- The statisticians analyzed the data again, but in the second go-around they treated nine geographical regions as the units. That is, they first computed the average income and average education for men aged 25-64 in each of the nine regions. They determined that the correlation between the average income and average education for the sample of n = 9 regions was about 0.7, obtaining a much larger correlation than that obtained on the individual data.\n", "\n", "The correlation calculated on the region data tends to overstate the strength of an association. How do you know what kind of data to use — aggregate data (such as the regional data) or individual data? It depends on the conclusion you'd like to make.\n", "\n", "If you want to learn about the strength of the association between an individual's education level and his/her income, then by all means you should use individual data. On the other hand, if you want to learn about the strength of the association between a school's average salary level and the schools graduation rate, you should use aggregate data in which the units are the schools." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Case: Sales Prediction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Suppose we are trying to predict next month's sales. We probably know a lots of factors from the weather to a competitor's promotion to the rumor of a new and improved model can impact the sales. Perhaps your colleagues even have theories: \"Trust me. The more rain we have, the more we sell\" or \"Six weeks after the competitor's promotion, sales jump\".\n", "\n", "To perform a regression analysis, the first step is to gather the data on the variables in question. Suppose we have all of monthly sales number for the past three years and some independent variables we are interested in. Let's say we consider the average monthly rainfall for the past three years as one of the independent variables.\n", "\n", "Glancing at this data, the sales are higher on days when it rains a lot, but by how much? The regression line can answer this question. In addition to the line, we also have a formula in the form of\n", "\\begin{equation}\n", "Y = a + b X \\nonumber\n", "\\end{equation}\n", "\n", "The formula shows\n", "- Historically, when it didn't rain, we made an average of $a$ sales, and\n", "- in the past, for every additional inch of rain, we made an average of $b$ more sales.\n", "\n", "However, regression is not perfectly precise to model the real world so the formula we need keep in mind is\n", "\n", "\\begin{equation}\n", "Y = a + b X + \\text{residual}\\nonumber\n", "\\end{equation}\n", "\n", "where residual is the vertical distance from a point to the line." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "scrolled": false }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9d5a6445523b4d5cbc6b519a325d9273", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(IntSlider(value=30, description='Number of points:', max=30, min=5, step=5, style=SliderStyle(d…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "LinRegressDisplay().container" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Case: Skin Cancer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data includes the mortality due to skin cancer (number of deaths per 10 million people) and the latitude (degrees North) at the center of each of 49 states in the U.S. (The data were compiled in the 1950s, so Alaska and Hawaii were not yet states, and Washington, D.C. is included in the data set even though it is not technically a state.)\n", "\n", "The scatterplot suggests that if you lived in the higher latitudes of the northern U.S., the less exposed you'd be to the harmful rays of the sun, and therefore, the less risk you'd have of death due to skin cancer. There appears to be a negative linear relationship between latitude and mortality due to skin cancer, but the relationship is not perfect. Indeed, the plot exhibits some \"trend,\" but it also exhibits some \"scatter.\" Therefore, it is a statistical relationship, not a deterministic one." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " show code\n", " " ], "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv(dataurl+'skincancer.txt', sep='\\s+', header=0)\n", "slope, intercept, r_value, p_value, std_err = stats.linregress(df.Lat,df.Mort)\n", "sns.regplot(x=df.Lat, y=df.Mort, data=df, marker='o',\n", " line_kws={'color':'maroon', \n", " 'label':\"$Y$\"+\"$={:.2f}X+{:.2f}$\".format(slope, intercept)},\n", " scatter_kws={'s':20})\n", " \n", "plt.legend()\n", "plt.title('Skin Cancer Mortality vs State Latitude')\n", "plt.show()\n", "toggle()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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Hj1GiRCkAzpw5zYUL52jZMmmoe9euHcyaNZ3IyBuMG/ctN2/epH79hsybt/ChP6NGJW2BGhFxnXz5/vtYK18+L65du/bQ/S5dukBioomhQwfQqVM7li//HXd3D1xdc9G1aw/atWvF22+/TsGChalUqXK6rimyliV77INImiw3UVEe1DBeDBQABiqKMjD52CpVVUcA7YFZiqJ4APuBKRaM7bnld83Pl7W/pleVfkw/9ANzw2Zx+/4txgZ9y4xDU+leuScf+n6Ep9Pz760rkjQNKMaCTce5Dzga9cQlJNWmbhpQzNahCWET9+/Hcv78OX76aSrTpk3m2rVrTJgwhTx58gBQp0496tSp99BrntVjN5lM6HS6B8fNZjN6ve6hcxMTEzl48AA//DATV1cXhg79mHXrVlO2bDnWrFnFsmV/kiuXG6NGfc6iRfPTdU2RtSw5ea4f0O8JT41+yvmHgBqWisdSvF29GVFrFD2r9GXGwR+Zc/gn7sTdZlzQaGYemkY33x509+1Jbuc8tg4120uZICez4oVIcuLECdzd3QkM/B2jUc+kSeOZO/cnfvhh5lNfU79+Q+rXb/jE5/LnL8ChQwcePI6MvIGXl/dD5+TNmw8/vxoPfnl46aWG/PvvEW7dukn16jXIkycvAK+99iYrVvxOo0ZN0rymyFr2NTPBhrxcvBhe60uCO4TRv9ogcjm4cSfuNhOCv6N6YCXG7Puam7GRtg4z2/Mt5cWQdtUY+1FthrSrJkld5GjHjx+jfPkKDx63bduR0NCD3Lx5M1PX8/OrQUhIEDdv3iQ2NpZt27YQEFDroXNq167Hvn27uXv3LomJiezZ8w/lypWjdOmyBAfvIyYmBrPZzK5df1Ou3IvpuqbIWjm2pKyl5HPJx6c1R9CjSi9mHprKrNCZ3I27w8Tgsfx0aDrdfLvTvXIv8jrns3WoQohs7sQJ9aHE7uXlTYUKldi1aztvvNEiw9fz9s5Pt2496du3O/HxCbz5ZnNefLEiAJ06tWP8+MlUqFCRdu3ep2fPLiQkJODvH8Brr72FXq/n+PFjdOnSAaPRSPnyFejQoRNOTk5PvaawjByzbWsKa8/svRkbyczQacwKncHduDsA5HJwo2ul7vSo3Jt8LplP8DlxlnJ2KlCTE9+f7ES2bdU2ac9/ZNtWjcnjnJdhNYYT0iGMgX5D8XD05F58FJP3T6D6/Ip8tfsLImIibB1mtpBSoObWvbiHCtSEnpKvnxBCpJDEbiW5nfMwtMZnhHQMY7D/J3g4ehKdcI8fDkzCb34lRv7zOdejr9s6TE1bv/c8BoMeJwcDOp0OJwcDBoOe9XvP2zo0IYTQDEnsVubplJvB/p8Q0jGMIf6f4umUm+iEe0w9OBn/wEp8+c9wrkXLGs8nibgdi+MjlZscjXoibsfaKCIhhNAeSew24umUm0H+w9jf8TCf1Pic3E65iU6IZtrBKfgHVmLErk8Jjw63dZiaIgVqhBAibZLYbczd0YMBfoMJ6XiYTwNGkMcpDzEJMcw49CP+8yvx+c5hhN+7auswNaFpQDESE03cj0/EbDZzPz5RCtQIK9JhNtvPZC6RPWRmgrskdo1wd/Sgf/VBhHQ8zPCaX5LXOS+xibHMDJ2Gf6Avn+0YwtV7V9K+kB3zLeVF+yZlyZ3LkejYBHLncqR9k7KanRUv7IujozO3bkWQkBCfqR+2QmSU2Wzm3r07GI2OGXqdLHfTqKj4KH4+PJtpByZzI/YGAE4GJzq8+AF9q35MIbfC2aYt6SXt0bac3h6z2UxU1G1iYqIwmRItGFnm6PV6TCb7GVGQ9iQxGh3Jk8cbg+G/sjNpLXeTxK5x9+LvMe/wHKYenExETNKseUe9I+1ffJ+RL4/AOc5+atFnt/cmLdIebZP2aJu05+lkHXs2l8shF72q9iWoQygja3+Lt0t+4kxx/Hx4NqV/KM3g7QO4ePeCrcMUQgihEZLYs4lcDrn4qEpvgjqEMqrOt+R3LUBcYhy/HJlDwIIqDNrWnwt3ZT23EELkdJLYsxlXB1d6VE5K8JObTqaAa0HiTfH8+u9cai6oysBtfTl/55ytwxRCCGEjktizKRejC30Dkobov607loK5ChFvimf+v/OoubAqA7b25uztM7YO87mFnopg7ML9DJn+D2MX7pfysUIIkQZJ7Nmcs9GZrr492Nf+EKPrjadQrsIkmBJYcPRXai2sRr8tPTlz+7Stw8wUqQ0vhBAZJ4ndTjgbnelS6UP2dTjEdy9NpIhbURLNiSw6FkjthdXps7kHp2+fsnWYGSK14YUQIuMksdsZJ4MT/6vYlT3tDzCu/vcUdXuBRHMii9WF1FnoR+/N3Tl966Stw0wXqQ0vhBAZJ4ndTjkZnPigQmf2tD/AhAZTeMG9GInmRJaoi6i9yI9ef33IqVsnbB3mM0lteCGEyDhJ7HbO0eBIxxc7sbvdfiY1+JFiHj6YzCZ+P/4bdRb589Gmrpy4edzWYT6R1IYXQoiMk8SeQzgakqrV7W4bwuSG0yienOCXnVhC3UX+9NjUmeORqq3DfIjUhhdCiIwzpn2KsCcOBgfalu9Aq7LvsezEEiYGj+XsnTMsP7GUFSeW0bz023zsN5RyecvbOlQgKblLIhdCiPSTHnsO5WBwoE259vzTLoQpjaZTwrMkZsysPLmc+r/VpOuGDzh6419bhymEECKDJLHncEa9kTbl2rOrbTA/Np5JqdylMWNm1akV1F9ck87rO3Ik4rCtwxRCCJFOktgFkJTg31XasrNNENNenkXp3GUAWH36DxouqU2nde0Jiwi1cZRCCCHSIoldPMSgN9Cq7HvsaLOPGU3mUDaPAsDaM3/SeEldPljXjrDrh2wcpRBCiKex6OQ5RVG+AN5NfrhGVdUhiqK8DEwEXIDFqqoOTz63CjAb8AD+BnqoqppgyfjE0xn0BlqWaU3zUi3589RKJgR/h3rzGOvOrGbdmdU09XmNgX5DqZy/qq1DFXYs9FQE6/eeJ+J2LF6ezjQNKCaTKYVIg8V67MkJ/BWgKlAFqK4oSltgLtAcKA/4K4rSLPklgUBvVVXLAjqgm6ViE+ln0BtoUeYdtrfZw+xXfnkwW3792bU0WVqfDmve5eC1/TaOUtgj2StAiMyx5FD8FWCgqqpxqqrGA0eBssAJVVXPJPfGA4HWiqIUB1xUVd2T/Np5QGsLxiYySK/T81bpt9n23m7mvPor5fNWAGDjufW8srQB7Va3Yn94sI2jzH5k97qnk70ChMgciw3Fq6p6JOXfiqKUIWlI/geSEn6KK0BRoPBTjqdbvnxu6T7X29s9I5fWNFu0pXP+jnQKaM/KYysZtX0Uh8IP8df5jfx1fiNNSzfli/pfULNozUxd257eG3h2e4KPhvPb5pMYjTo83RyJio3nt80n8fR0xa98AStGmX7WfH8io+JwdzGi0+keHDMadNyMisuyOHLS91t2JO3JHIsXqFEUpQKwBhgMJJDUa0+hA0wkjRyYn3A83W7ciMJkMqd5nre3O9ev383IpTXL1m2p59WEDS0bs/7MWiYEf0dYxCHWn1zP+pPrafhCYwb5D8O/YEC6r2fr9mS1tNqzeOMx0IFBrych0Zz0ty6RxRuPUdzL1YqRpo+135+8bo7cuheHk4PhwbH78YnkcXPMkjhy2vdbdiPteTq9XvfMzqxFZ8UrilIH2AwMU1X1F+AiUCjVKQWBy884bnUyNJoxep2e10q+wV+t/+bXZr/h610FgK0XNvP68ia0XtWcvVf2pHGVnEl2r3s22StAiMyx5OS5F4CVQDtVVX9LPrw36SmltKIoBqAdsE5V1XNAbPIvAgAdgXWWiu1pZLJO5ul0OpqWeI1NrbYT+NpiqngnzZbffnErb654hXdWvcWey//YOEptkd3rnk32ChAicyw5FD8IcAYmKoqScmwG0AlYlvzcWmBp8nPtgVmKongA+4EpFoztiVJP1gFwcjBwP/m4/DBJH51Oxys+zWhSvCl/ndvA+OAxHLi2nx0Xt7Hj4jbqFanPIP9h1CpcJ+2L2bmmAcVYsOk490nqqcclmKRH+gjZK0CIjLPk5Ll+QL+nPF35CecfAmpYKp70iLgdi6vzw18SGRrNHJ1ORxOfprxc/FW2nN/E+OAxhIQHs+PSdnZc2k6dwvUY5D+MOkXq2TpUm0lJWLJOWwiRlWR3t1S8PJ0fm6wjQ6PPR6fT0bj4KzQq1oStFzYzPmgMweH72HV5B7v+2EGtwnUY5DeMukVesnWoNiE9UiFEVpOSsqnIZB3L0el0NCr2MmtabmLJmyupUTBpOdzuy7t4Z9WbvLWyKX+d/guzOe2VDUIIIZ5OEnsqMlnH8nQ6HQ1eaMSfb29g6VurCChUC4C9V3bTZH4T3ljxCtsubJEEL4QQmSRD8Y+QoVHr0Ol0vFS0AfWK1GfX5R2MCxrN7su7CLq6l3f/bIFfgRoM8h9GwxcaP1SgRAghxLNJj13YlE6no26Rl/ijxTq2frCVOoWTJtMFh++jzeqWvLa8MVvOb5IevBBCpJMkdqEZDXwasKLFGlY2X0u9IvUBCAkPps3qd2i2rBF/ndsgCV4IIdIgiV1oTu0idVnW/E9WtVhPvaINANh/LYR2a1rz6tIGbDy7ThK8EEI8hXzGLjSrZuHaLHtrFXuv7GF80Gi2X9zKwesH6LD2PXy9qzDIbxiv+jSTz+DtmOzHLkTGSWIXT6SlH6gBhWry+1t/EHR1L+ODxrD1wmZCrx/k/XVtqORVmYF+Q2lW4nVJ8HYmpcSzwaB/qMQzIMldiGeQoXjxGK3WzPcvGMDiN1ewtuVfNC7WBICwiEN0Wt+ORkvqsvrUKkzmDG0KKDRM9mMXInMksYvHaP0Hql/BGix6Yxnr39nCy8VeAeDIjTA6b+hAw8V1+PPUSknwdkB2vxMicySxi8dklx+o1Qr4sfCNpWx4ZyuvFG8KwNHII3TZ8D4NF9dm1ckVkuCzMdn9TojMkcQuHpPdfqBWLVCdwNeXsKnVdpr6vAbA0ch/6brxAxosrsXKE8tINCXaOEqRUVLiWYjMkcQuHpNdf6BWzl+VX1/7jc2td9CsxBsAHIs8yoeb/kf9xTVZfuJ3SfDZiJR4FiJzZFa8eEx23060kndlfmm2kLCIUCYGj2XN6VUcv6nSY1MXxgeN4WO/IbxduhUGvSHtiwmbkhLPQmScJHbxRPbwA7WSly8/Nw3kSMRhJgR/x+rTf3Dy1gl6/tWNCcHfMaD6YFqWaY1Rr/3/BlpafiiE0DYZihd2r4JXReY2nc+293bzVqm30aHj1K2T9N7cnbqL/Fl8bCEJpgRbh/lUWl1+KITQJknsIsd4MV8FZr/6C9vb7KFF6Zbo0HH69in6bOlBnUV+/HZsgSYTvNaXHwohtEUSu8hxyuUtz0+vzOPvNntpWaYVOnScuX2avls+otbCaiw8Op/4xHhbh/lAdll+KITQBknsIsdS8pZjRpO57GwbxDtl3kWv03Puzln6b+1FrUXVCfz3F00k+Oy2/FAIYVuS2EWOVyZPWaY3mc3ONkG0Kvseep2e83fO8vG2PtRcWJX5/84jLjHOZvFl1+WHQgjbkMQuRLLSecow7eVZ7GobxLtKW/Q6PRfunmfgtr7UXFCVX47MtUmCl/XcQoiM0NnBvtY+wJkbN6IwmdJui7e3O9ev37V4UNZgT20B7bXn9O1TfB8ynt/V30g0JxW2KeJWlL7VPqZd+Y44GZye+fr0tCc7LGNLiTEyKo68bo6ajDEztPb99rykPdqWle3R63Xky+cGUAI4+9jzWXIXIexQSc9STGk0nX/ahdCuXEcMOgOXoi4y9O+PCQiswpywn4hNyPwEtuywjC11jO4u2oxRCPEwSexCpKGEZ0m+bzSV3e320778+xj1Ri7fu8QnOwZRY0FlZofOyFSCzw7L2LJDjEKIh1k0sSuK4qEoymFFUXySH7+iKMqh5GO/KorimHy8iqIowYqiHFcUZbaiKNovBSZyHB/PEkxq+CN72h2g44udMOqNXL13hU93DsE/0JefDk0jJiEm3dfLDsvYskOMQoiHWSyxK4oSAOwEyqY6PAdoo6pqRcAVeD/5eCDQW1XVsoAO6GapuIR4XsU8ijOhwRT2thlNwn4AACAASURBVD/I+y92xkHvQHj0VYbvGoZ/oC8zDv1IdHx0mtfJDsvYskOMQoiHWbLH3g3oBVxOdcwAeCiKYgCcgRhFUYoDLqqq7kk+Zx7Q2oJxCZElXnAvxvgG37O3/UE6VeiCo96Ra9HhjNj1Kf6BvkzcPfGZCT47LGPLDjEKIR5mscSuqmpXVVV3PHK4J7CNpGTvBSwFCgNXUp1zBShqqbiEyGpF3V9gbP1J7G1/kM4Vu+God+R6zDUGbhyIX2Alph6Ywr34e4+9LjssY0sdY1SMNmMUQjzM4svdFEU5CzQAYklK6q8DZ4CJgAOwEBijqmq95PPLAH+qqlounbfwSb6eEGkKPhrO8m0nCY+MpkBeV1o2KI1f+QJZeo+Ldy7y3c7vmLV/FvcT7wPg7erNoNqD6OnfEzdHtyy9nxAix3ricjdrJnZ/4D1VVVslH68ALAFeAzarqlo6+Xg9YKSqqo3SeQsfZB27XbB0e1KWbhkMehyNeuISTCQmmizWA413vsuXm75i/r/ziE1MmmyW1zkvPav0pXPFbrg5umf5PS1Jvt+0Tdqjbfa6jv0wUENRlJTuUXMgSFXVc0Csoih1ko93BNZZMS6RQ1h76VZh98J8U28sQR1C6e7bE2eDM5GxkXy950uqz6/I5JAJRMXZzw8uSwg9FcHYhfsZMv0fxi7cL+vnhUgHqyV2VVWPAp8DWxVFCQX8gEHJT7cHJimKcgxwA6ZYKy6Rc9hq6VaBXAX5qu4YgjqG8VHlPrgYXbh5/ybf7B1J9fkVmRQ8jrtxdywaQ3aUHQr4CKFFFl8vrqqqT6p//wL88oRzDgE1LB2LyNm8PJ25dS8OJwfDg2PWXLpVwLUAI+t8Q6+q/Zh2cArzDs/m5v2bjN73FdMP/UD3yr3oVqkHHk6eVolH61KPsAA4ORi4n3xcJu8J8XRSeU7kGFpZupXfNT9f1v6aoA5h9K7aH1djLm7dv8V3+76hemAlxgWN5vb9W1aNSYukOI4QmSOJXeQYWlte5u3qzYhaowjuGEafqgNwNebi9v1bjAsaTfX5lRi771tuxd60SWxaIMVxhMgcKd0qchTfUl6aG8b1cvHi81oj6VmlLzMO/cjssJncibvN+OAxzAydRrdK3eleuRd5nPPaOlSrahpQjAWbjnMfHlrFIMVxhHg26bELoRH5XPLxWc0vCOkYxoDqg3BzcOdu3B0mhoyj+vxKjN47isjYG7YO02q0NsIiRHYh+7FnY/bUFpD2POpmbCQzQ6cxK3TGg1nzuRzc6FqpOz0q9yafS76sCjVd5P3RNmmPttnrOnYhRAbkcc7LsBrDCekQxkC/oXg4enIvPorJ+yfgF1iJr3Z/QUSMLP0SQjxMErsQGpfbOQ9Da3xGSMcwBvt/gqdTbu7FR/HDgUn4za/EqN0juB593dZhCiE0QhK7ENmEp1NuBvt/QkiHMIbW+IzcTrmJTrjHjwe+xz+wEl/+M5xr0ddsHaYQwsYksQuRzXg4eTLQbyghHQ/zSY3PyeOUh+iEaKYdnIJ/YCVG7PqU8OhwW4cphLARSexCZLGU+uZdvtlk0frm7o4eDPAbTEjHw3wW8AV5nfMSkxDDjEM/4j+/Ep/vHEb4vasWubcQQrsksQuRhVLXN3d3sU59czdHd/pVH0hwhzCG1xxJPud8xCbGMjN0Gv6Bvny2YwhX712x2P2FENoiiV2ILGTtHeRSc3N0p2+1AQR1DOPzWqMeJPhZYTPwD/Tlkx2DuBJ12eJxCCFsSxK7EFlIC/XN3Rzc6FO1P8EdD/NFra/xcvHmfuJ95oT9hH+gL8P+HsjlqEtWi0cIYV2S2IXIQlqqb57LIRe9qvYlqEMoX9b+Bi8Xb+JMccw9PIsagZUZsn0AF+9esHpcQgjLksQuRBbSyg5yqeVyyEXPKn0I7hDGqDrfkt+1AHGmOOYdmUPAgioM2tafC3ct/1GBEMI6JLELkYVS1zePitFWfXNXB1d6VO5NUIdQvq4zhgKuBYk3xfPrv3OpuaAqA7f15fydc7YOUwjxnKRWfDZmT20BaY+1xSbEsuDoL0zeP/HBrHmj3kgbpT39qg+kuIcPkDTTf/3e80RGxZHXzZGmAcWe+xeVlGtG3I7Fy9M5S66ZUVp/fzJK2qNtUiteCGFxzkZnulTqzr72hxhdbzyFchUmwZRA4NFfqLWwGv239GJ92P4sX76Xekmgq7N1lgQKkZNIYhcih0tK8B+yr8Mhxrw0gcK5ipBgSmDhsfl8sKMRO80TiTFczbLle7ZcEihETiCJXQgBgJPBic4Vu7G3w0HGvjSJIm5FMWPihHkjC2M7sSFmDLdMF597+Z4WlgQKYc8ksQshHuJkcKJTxS7sbX+QJi4DcaMAZkwcjd/Awtj/sTF2DHq3zO8mp6UlgULYI0nsQogncjQ4MvSlXrTUzaauYQAeuoKYMXHS/Bfz7n7AR5u6cuLm8QxfV4tLAoWwJ5LYhRBP5VvKi/dfqUBN9+a8o5/Lqy6DKejyAiZMLDuxhLqL/OmxqTPHI9UMXTNlSWB0rLaWBAphD4y2DkAIoW2+pbzwLeWVvFynLvGJw1h6fDGTQsZx9s4Zlp9YyooTy2he+m0+9htKubzl033NtGhhWZwQ2U26euyKosx5wrGlWR+OEELrHAwOtC3fgX/ahTCl0XRKeJbEjJmVJ5dT/7eadN3wAUdv/Pvc95FlcUJkzjN77IqiTAeKAPUURfFO9ZQDUNKSgQkhtM2oN9KmXHtalX2P5Sd+Z1LIOE7dOsmqUytYdWoFb5RszkC/oVTwqpip66deFgfg5GDgfvJx6bUL8XRpDcXPASoClYFlqY4nAHvSuriiKB7AP8AbqqqeVRSlFjAJcAdCgQ9UVY1TFKUKMBvwAP4GeqiqmpDRxghhSTIs/GRGvZF3lba8U+ZdVpxcysTgsZy8dYLVp/9g9ek/eL3kWwz0G0pFr0oZum7E7VhcnR/+ESXL4oRI2zOH4lVVDVZVdR6wUVXVX1L9WaCq6qlnvVZRlABgJ1A2+bEHsBz4UFXVCsmndUn+OxDorapqWUAHdMt0i4SwABkWTptBb6BV2ffY0WYfM5rMoWweBYA1p1fRaEkdPljXjrDrh9J9PVkWJ0TmpHdWfM1MXLsb0Au4nPy4CbBbVdXQ5Md9gBWKohQHXFRVTRkBmAe0zsT9hLAYqZaWfga9gZZlWrP9vT381ORnlDzlAFh3ZjWNf6/H+2vbcOjagTSvY61lcaGnIhi7cD9Dpv/D2IX7bfLLmhZiEPYjXZvAKIryB+BCUg88KuW4qqoT0/Has0AD4D2gAuAIlAN2AQOBqsA4VVXrJp9fGlib3HtPDx/gTDrPFSJTunyzCXcXIzqd7sExs9lMVEwCsz9rYsPItM9kNrH036WM2j6KI9ePPDj+Rtk3+KL+F/gV9nvqa4OPhrN820muRUaTP68rLRuUxq98gSyLLfhoODOXh2I0Jv2ydj8+kYQEM91b+mbpfbQeg8i2nrgJTHqXu0WmukiKjG4LZwReJan3f56kz++HAZseuZYOMD326jTI7m7Zn5bbk9fNkVv34h5M5AK4H59IHjfHp8as5fZkxvO0p2H+ZtRv9SprTq9ifNB3HI08wurjq1l9fDUvF3uFQf7DqFbg8QRf3MuVAa18HzqWVV9Tb293Fm88Bjow6PUkJJqT/tYlsnjjMYp7uWbJfdKSVTHI95u2WWh3tyc/n56LqKr6P1VV/wd8CXyT/LhzBmO5CuxRVfWMqqqJwBKgBnARKJTqvIL8N3wvhCZItbTnp9fpebNUC7a+t4u5rwZSIV/SZLq/zm+k6bJGtF39DiHhQVaNSQt167UQg7Av6V3HXlpRlCPAQSBEUZRTiqKUy+C9NgLVFUV5IfnxG0CIqqrngFhFUeokH+8IrMvgtYWwKKmWlnX0Oj1vlHqLze/uYF7ThVT0SuqRbz6/iWbLGvPen28TdHWvVWLRwgQ9LcQg7Et6J8/9CIxVVTWPqqqewNfAtIzcSFXVC0B34E9FUY4BeYHRyU+3ByYlH3cDpmTk2kJYg28pL4a0q8bYj2ozpF01SerPSa/T81rJN9jcege/NvsNX+8qAGy9sJnXlzfh3T9bsO+KZRO8FkZitBCDsC/pnTx3QFXVqo8cC1NVNWMLUy3DBzgjn7Fnf9IebbN0e8xmM5vOrWd80BgOXv9v1vxLRRsyyH8YNQvVytL7pbRHC/UJsiIG+X7TNgt9xv5ck+eMiqLkVVU1EkBRFC8yPnlOCCGeSqfT8YpPM5oUb8pf5zYwPngMB67t5++LW/n74lbqFanPIP9h1CpcJ+2LZUB669ZbkhZiEPYjvUPxPwB7FEX5SlGUUSRVk5tuubCEEDmVTqejiU9T1r+zlYWv/061/NUB2HFpO81XNuPtla+z69IOG0cphHY9M7EripJXUZS8wFLgM5JmrxcCPgEWWz48IUROpdPpeLn4q6x7Zwu/vbGM6gX8Adh1eQdv//E6zVc2Y8fF7aTn40QhcpK0huIj+G/IXZfqeJfk44bHXiGEEFlIp9PRqFgTGr7wMtsubGFc0GiCw/ex+/Iu3ln1JgGFajHY/xPqFan/UAEhYXlamJ8gHpfWUPyvwClgIlBRVVV9qj+S1IUQVqPT6WhYrDFrWm7i9zf/ICB5Mt3eK7tpteot3lzxKtsubJEevJXI/gnaldYmMJ2AKsAhYLKiKLsVRempKEpuawQnhBCP0ul01H+hIatarGfZW38+mEy37+oe3v2zBa8vb8KW839Jgn9EVtejl/0TtCvNyXOqqkarqhqoqmoTkjZn8QS2Kooin7ELIWxGp9NRr2h9/mixjhXN11C7cF0AgsP30WZ1S15b3pjN5zZKgscyvWupmKdd6Z0Vn8I7+Y8XIL12IYQm1ClSj5Ut1rKy+VrqFnkJgJDwYNquaUWzZY3YdHZ9jk7wluhdS8U87UozsSuK8oKiKJ8oivIvSZ+5XwUCVFV91eLRCSFEBtQuUpflzVezqsV66hVtAMD+ayG0X/sury5twIaz63JkgrdE71oq5mlXWsvdtgJ7gfxAe1VVK6mqOlZVVdmkRQihWTUL12bZW6v48+2N1C/aEICD1w/Qce17NFlan3Vn1uSoBG+J3rXsn6BdzywpqyiKCYgFEnl8a1Wzqqoelg0vXXyQkrJ2QdqjbbZoT1Ytp9p3ZS8Tgsew9cLmB8eqFKxC/ypDaFbidbtYJves9yflM3aDQY+jUU9cgonERJOmE7H8/3m65y0pWyKN54UQwiJSJ6PUE76ADCejGoUCWPzmCoKv7mN88Bi2nP+Lg1cP0ml9Oyrkq8RAv6G8VvIN9LqMTjvKHlK+XrLmPGd4ZmJP3lJVCCGsLvWELwAnBwP3k49nNiH5FazBb28sZ394MFNCx7P2xFqO3Aij84YOlM9bgUH+Q3m95Ft2meClHn3OYX/fvUIIq8jqddGPsuRyqmoF/FjTbg0b3tnKK8WbAnA08ghdNrxPw8W1WXVyBSazKY2rCKFNktiFEBlmjapj1lhOVbVAdQJfX8KmVttp6vMaAEcj/6Xrxg9osLgWK08sI9GUmGX3E8IaJLELITLMGlXHrLmcqnL+qvz62m9sbr2DZiXeAOBY5FE+3PQ/6i+uyfITv0uCF9mGJHYhRIZZo+qYLZZTVfKuzC/NFrL53Z28VuJNAI7fVOmxqQsv/RbA0uOLJcELzUtrVrwQQjzGy9OZW/fiHkxsA8tUHbPVhK9KXr7Ma7aAwxFhTAwey+rTf3Di1nF6/tWNCcHf8XH1IbxdphVGvfwIFdojPXYhRIbllKpjFb0qMbfpfLa9t5u3Sr2NDh2nbp2k1+YPqbvIn8XHFpJgSrB1mEI8RBK7ECLDclrVsRfzVWD2q7+w7b3dtCjdEh06Tt8+RZ8tPaizyI/fji2QBC8045mV57IJH6TynF2Q9mibtOc/auQxJgZ/x8qTyzEnF+Us7uHDgOqDaV22DQ4Gh6wMFUi7Cp+8P9pmzcpz0mMXQogMUvKWY+YrP7OjzT5almmNXqfn3J2z9N/ai1qLqhP47y/EJcZl2f2ssbxQ2A9J7EIIu2DpgjlPUjavwowmc9jZJohWZd9Dr9Nz/s5ZPt7Wh1oLq/HrkZ+zJMFbY3mhsB+S2IUQ2Z6te7Sl85Rh2suz2NU2iHeVtuh1ei7cPc+g7f2ouaAq8w7P4X7i/Uxf3xrLC4X9kMQuRBZL6Tl2+WaT1XqOOZ1WerSlcpfhx8Yz+addCG3KtcegM3Ax6gJD/h5AzQVV+fnw7EwleGtU4RP2w6KJXVEUD0VRDiuK4vPI8d6KomxL9biKoijBiqIcVxRltqIosjhUZEupe47uLvJZqLVorUdb0rMUUxpN5592IbQr1xGDzsClqIsM/ftjAgKrMCfsJ2IT0h9bTlleKLKGxRK7oigBwE6g7CPHXwSGPXJ6INBbVdWyJO313s1ScQlhSVrpOeY0Wu3RlvAsyfeNprKn/QE6lP8Ao97I5XuX+GTHIGosqMzs0BnpSvA5bXmheD6W7LF3A3oBl1MOKIriBMwERqQ6VhxwUVV1T/KheUBrC8YlhMVoreeYU2i9R1vcw4eJDX9gT7sDdHyxE0a9kav3rvDpziH4B/ry06FpxCTEPPMavqW8GNKuGmM/qs2QdtUkqYunslhiV1W1q6qqOx45PBqYC5xOdawwcCXV4ytAUUvFJYQlabXnaO+yS4+2mEdxJjSYwt72B3n/xc446B0Ij77K8F3D8A/0ZcahH4mOj7Z1mCKbs3iBGkVRzgINgDJAd1VVWymK0gD4UlXVBoqi1AHGqKpaL/n8MsCfqqqWS+ctfIAzWRy2EJkSfDScmctDMRqThuHvxyeSkGCme0tf/MoXsHV4QmPO3z7PmJ1jmHNgzoNlcQVyFWBInSH08OuBq4OrjSMUGvfEAjXWTOwjgFrAfcANKAisAYYAm1VVLZ18fj1gpKqqjdJ5Cx+k8pxdsJf2pFQIuxkVRx43x8cqhGVX9vL+pNBSey7dvcgPByYlFbYxJSV4LxdvelXpR6eKXcjlkCvNa2ipPVlB2vN0aVWes9rsc1VVO6f8O1WP/b3kx7GKotRRVXUX0BFYZ624hMhqKTuS2dsPJmE5N645k/die5qb6nPScTmHE1YTEXOdkbuHM/Xg9/Ss0o//VeyargQvhFaWlbUHZimK4gHsB6bYOB4hhA2kVQ/dHqUskTQY9Hi7FMQzoQdlze8QX2wTay/9RkRMBKN2f87UA9/zUZW+dK7UDTcHN1uHDeTM9ys7kE1gsjF7agtIe7TO0u1JneAcjXriEkwkJposNglOK+/P2IX7H9vb/n58IrlzOfJB88L8eOB7fjkyl9jEpJUVeZ3z8lHlPnSp9CFuju4PXmPt9lj6/dLK+5NVZBMYIUSOk1NrADxriWSBXAX5qu4YgjqG0aNyb1yMLkTGRvLN3pFUn1+RScHjuBt3xyZx59T3KzuQxC6E0IScWgMgPUskC7gWYFSdbwnqEMZHlfvgYnTh5v2bjN73FdXnV2RC8Hfcjr1t1bhz6vuVHUhiF0JoQk6tAZCR4jr5XfMzss43BHc4TK8q/XA1unLr/i2+2/cNPpN9GBc0mtv3bz3xPlm9+11Ofb+yA0nsQghN0Hr1OEvJTHEdb1dvvqj9FcEdD9On6gBcjbm4FXuLcUGjqT6/Et/t+4ZbsTcfnG+J3e9y6vuVHcjkuWzMntoC0h6ts0Z7rDnL2p7enxsxN/j1xE9M2fsD9+KjAHB39KCbbw+6+/Zk1vKzT52gN6RdtUzf15Lvlz29P2Cn69iFECItKTUAtE5ry7zyueTj28bf8kHZD5l5aCqzQmdyN+4OE4PH8tOh6ZSMfx0/59ZA7gevyYrPw7PL+5XTyFC8EEJkgCWGtbNKXud8fBIwgpCOYXzsNwR3Rw+i4u8Sym/Mj+3A7rjZxJiTJtnJ5+H2S3rsQgir01KPN6OxpF7mBSTtCZB8XCu91zzOeRlWYzg9fHvxU+h0ph+cyr2Eu+xPWERowgpe1Dengvlt2gTUsHWowgKkxy6EsCot9XgzE0t2WuaV2zkPQ2p8ysEPjvB+qX446dxIIJZQ02JW6DuzInwy16Ov2zpMkcUksQshrEpLhU0yE0t2XObl6ZSb8a9+xZHORxla4zM8nXITmxjN1IOT8Q+sxBe7PuNa9DVbhymyiCR2IYRVaanHm5lYsvMyLw8nTwb6DWV/x8N8UuNz8jjlITohmumHfsA/sBKf7/qE8OhwW4cpnpMkdiGEVWmpx5uZWDKz7lxr3B09GOA3mOCOYXwaMII8TnmISYhh5qGp+M+vxOc7hxF+7+pjr8vqIjfCMmTynBDCqpoGFGPBpuPch4c2D7FFj7dpQDHmrj1G5O1YEk0mDHo9zk5G2jQq/czX2WKZlyUmHLo7etC/+iC6VurO3MOzmX5wCjdibzAzdBq/HJlLxxc70afaAArmKvTQpi+p5yMA2eqXmpxAeuxCCKvSXI/3QZEu3SOPtcPSEw7dHN3pW20AQR3D+LzWKPI55yM2MZZZYTPwD/Tl0x2D+X13iGbmRohnkx67EMLqtFLYZP3e87i6OJDH47+h9/vxiZpaugbWW2Ln5uBGn6r96VyxG/MOz2HqwclExFxndthM9MzlRcNrVDe1xU3vDWh3NUBOJz12IUSOpaWJfM9i7ThzOeSiV9W+BHUI5cva3+Dl4o2JeA4n/sH82I5sj5vMXdM1za8GyKkksQshciwtTeR7FlvFmcshFz2r9CG4Qxg9lM9wIU9Sgk9YRWBsR3bET6aqryHtCwmrksQuhMixssvSNVvH6ergyqjGQ/n95Z00dO6VnOATUFlDp52NGLitH+fvnLNKLCJtktiFEDmW5ibyPYVW4qxR9gUWdx7NsQ+P8W3dsRTMVYh4Uzzz//2Zmgur8vHWPpy7c9aqMYnHybat2Zg9tQWkPVpnL+1JWTYWGRVHXjdHm+/MllVs8f7EJsSy4OgvTNk/iSv3LgNg1Bt5t2xb+lcfhI9niUxf216+31JYc9tW6bELIXKM1MvG3F20tTNbduRsdKZLpe7s63CIMS9NoHCuIiSYElh4bD61Flaj75aPOH37lK3DzHEksQshcgwt1am3J04GJzpX7MbeDgcZ+9IkirgVJdGcyG/HFlBnoR99Nvfg9K2Ttg4zx5DELoTIMbLL8rbsysngRKeKXdjb/iDj60+mqNsLJJoTWawupPYiP3r99SGnbp2wdZh2TxK7ECLHsPXytpxSa93R4Mj7Ff7HnvYHmNBgCsXci2Mym/j9+G/UWeTPR5u6cuLmcVuHabcksQshcgxbLhvT0j701uJocKTji53Y3W4/kxr8SDEPH0xmE8tOLKHuIn96bOrM8UjV1mHaHUnsQogcI/WysagY6y4by8mf7zsYHGj/4vvsbhvC5IbT8PEogRkzy08spd5vNfhwYyeORR61dZh2w6K14hVF8QD+Ad5QVfWsoigfAn0BMxAMdFdVNU5RlCrAbMAD+BvooapqgiVjE0LkTCl16q29nCridiyuzg//yM1pn+87GBxoW74DrZU2LD2+mEkh4zhz+zQrTy7nj5MreLNUCwb6DaV8vhdtHWq2ZrEeu6IoAcBOoGzy47LAYKA24Jt8717JpwcCvVVVLUvSFkvdLBWXEELYgq0/39cSo95Im3Lt2dU2mB8bz6RU7tKYMbPq1ArqL65J5/UdCQ0PtXWY2ZYlh+K7kZS4Lyc/vg/0VFX1jqqqZiAMKKYoSnHARVXVPcnnzQNaWzAuIYSwOluXhdUio97Iu0pbdrYJYtrLsyiduwwAq0//QeUZlfnf+g4cjgizcZTZj8UrzymKchZooKrq2VTHvIEgoBNJCX+cqqp1k58rDaxN7r2nhw9wJssCFkIICwk+Gs7ybSe5FhlN/ryutGxQGr/yBWwdlmYkmhJZcmQJo/4exbGIYw+OtyjXghEvjaBqoao2jE6Tnlh5zur7sSuKUgRYB8xRVXWboih1SPrMPYUOMD3xxc8gJWWzP2mPtkl7nl9xL1cGtPJ96FhWxWAv78/LBd+gYatmbL++gS+2fIl68xgrj61k5bGVNC3xOoP8huLrXcXWYWaYhUrKPpFVE7uiKOWADcAUVVUnJB++CBRKdVpB/hu+F0IIYWUp9fQjbsfi5els9Xr6Br2B9yq+R4P8Tfnxn/nMCJtIhOkM68+sYf2ZNbzq04xBfsOonF/7PXhb7E1gteVuiqK4AxuB4amSOqqqngNik3vuAB1J6tELIYSwMi2ttz98OpJLYWVorp/Oq44jyEPSpjIbzq6jydL6tF/TmgPhIVaPK71stTeBNXvsXYECwEBFUQYmH1ulquoIoD0wK3l53H5gihXjEkIIkSz1ensAJwcD95OPZ7anmdkRgNSxlKY+pQz1UON2EGpewHXTKTad28CmcxtoXKwJg/yHUb2Af5bdOys8qXbB834t08PiiV1VVZ/kf05K/vOkcw4BNSwdixBCiGfL6vX2Kb1Wg0H/0AgAkGZyezQWnU6P4vgSRWNq0qDpTSYEf8fhiFA2n9/E5vObaPhCYwb5D8O/YMBz3zsr2Kp2gVSeE0II8UBWr7d/nop7T4vFO7crr5d8k82td/BLs0VU8qoMwNYLm3l9eRNar2rO3it7bF7tz8vTmbvR8YRHRnP2yl3CI6O5Gx1v8doFktiFEEI8kNXr7Z9nR720YtHpdDQr8Tp/tf6b+a8tprJ30mS67Re38uaKV1hwqz8RuiOZundWKFcsN7fv3Sc+wYReZyY+wcTte/cpVyy3Re8riV0IIcQDqevpR8c+fz395xkBSG8sOp2OV32asbHVNha8toSq+asBcIWDrIwbwMrYQVxODM3QvbPCsfO38HB1xGjUYzKD0ajHw9WRY+dvWfS+Vl/HLoQQQttS6ulnhaYBxViw6Tj3SeotxyWYMjQCkJFYdDodTXya8nLxT0N5jwAAD3dJREFUV9lyfhMjd37NsdsHuWQ6wIr7Byikq0xl2tEmwDrFTSNux+KRyxFPNx0ORj3xCSbMZrN8xi6EECL7yuoRgPTQ6XQ0Lv4K29ttZ3T1eRQyJG0qc8V8iPXmoXwe1pGdl/7G0pVXbbU/gPTYhRBCWFRWjgBkhE6no0tASzrXeJttF7YwPngMQVf3svvyLlr+8QY1C9VmkP8w6hWpj06ny/L7px6tMBp0VtsfQHrsQggh7JpOp6Nhscasfnsjv7/5BwGFagGw58o/tFr1Fm+ueJVtF7ZkeQ8+9WhFVIx1RitAeuxCCCFyCJ1OR/0XGvJS0QbsvPQ344PHsPvyLvZd3cO7f7bAr0ANBvkPo+ELjbOsB58yWmHNWv6S2IUQQliUrWvPP0qn01GvaH3qFa3Prks7GB80hl2XdxAcvo82q1tSvYAfg/yG0ahYE4sM0VuaDMULIYSwGC3Vnn+SOkXqsaLFGlY2X0vdIi8BEBIeTNs1rWi6rCGbzq63+CS7rCaJXQghhMXYuvpbetUuUpflzVezqsV66hVtAMCBa/tpv/ZdXl3agA1n1z1I8KGnIhi7cD9Dpv/D2IX7NfNLSgoZihdCCGExtqqXnlk1C9dm2Vv/b+/eo6UqzzuOf+cMKCiEoAcLMeCFy4NLQkgEDxRvVVRIRAwqGohVK1K8pQYV2ppAJK2m8ZbQxMQqCIarJtLYxWWFohKRcALWI0TgAbmKIQ03QbBczqV/7H3aYZjDOeCZ2bN3fp+1WMu9532H9/Gdh2f2Zfb7KuXblvLEssdYtPV1Kra/wy1zb6J7mx7c8Pm72VDRniZN0pE8f74hdMQuIiJ5E9VvuT+tsna9efnaXzFncLC4DMCK7RWMfWcE/1FzHx+mlgIU5RkIFXYREcmbxn72fKH1alvGrIGzmTv4P7m8Qz8AdvI+8w6N5aUDI9lQuZimaYrqDIQKu4iI5E0UT57Lh55tL2TmNa8wrMUztE8Fq4zvqHmfeYfGMevASHY1L6e6prqedykMXWMXEZG8iurJc/lwe9/+nLTgXHaVrKOiZhqbq5eyiw28+sk41s2axQM9x3BNx0GUpKI7blZhFxERaaDaLyjzy5vRes93qWyxifXNX+a32xeyetcqhv/6Vrqedh6jLhjNwI7XkS5JF3yMKuwiIiLH4cgzEH8JDGXF9gqeWP4vzN84hzW7VjNiwe10Wf59RvUczaCOgws6Pl1jFxER+ZS6t+nBiwNmsHDIYr5yzkAA1u52Ri64g0tmljF95XSqqqsKMhYVdhERkUbyhdLuTB4wjdeGvMU15w4CYN1Haxn2yjAunnkhL/tMKqsr8zoGFXYREZFG1q30C0zq/3NeH7KEgR2vA+D9j9Zxz8IRXDSjF7PWTM9bgVdhFxERyZPzS7sx8eoXWXnXSgZ1HEyKFBv2rOe+10bSd0ZPZq6Z1ugFXoVdREQkz7qd0Y3nrp7Mb24u52udridFio17NvDN1+6iz/QvM331zzlcdbhR/i4VdhERkQKx07ry7FUv8ObNv2Nw5xspSZWwee8m7n/9HvrMuICpq6Z86gKvwi4iIlJgXU4zfnblRBbfvIwbutxESaqELXs3MeqN++gz/cu8+N4LHKo6dELvndfCbmafMbPfm9nZ4XY/M1thZuvM7J8y2vUws+VmttbMnjcz/b5eREQSr1PrzjzT7zne+voyhtjXgwL/8WYeXPR39J72Jaa8N+m4C3zeCruZlQGLgS7hdnNgEjAIOA/oZWYDwuZTgXvdvQuQAu7M17hERESKTcfPdubHVzzLkqFvc3PXYaRTabbu+4CHFt1P2bQevPD75zlYdbBB75XPI/Y7gXuAP4TbFwLr3H2ju1cSFPMbzewsoLm7Lw3bTQZuzOO4REREitK5rToy4fKfsmTo2wztegvpVJoP921lzG9GUTa1BxNX/lu9BT5VU1OT10Ga2SbgMqAP8FV3/0a4vx8wGhgHPO7uF4X7OwFzw6P3hjgb2NiogxYRESkCG3Zv4NE3H2XKu1P+72dxZWeWsXT4UoBzgE3ZfQp5LbsEyPwWkQKqj7H/uOzcuY/q6vq/pLRp05Lt2z8+3rcvSkmKBRRPsVM8xU3xFLcTjaclbXisz9Pcdf79/Oi/nmTGmqn8cd8fj9mnkHfFbwXaZWy3JThNX9d+ERERATp85iyevGwC5cMquL7zkGO2LWRhLwfMzDqZWRoYCsxz983AATPrG7a7BZhXwHGJiIjEQvuWHfjH3mOP2aZghd3dDwC3Ab8EVgFrgF+ELw8DnjazNUALYEKhxiUiIpIkeb/G7u5nZ/z3QuCLOdq8S3DXvIiIiHwKevKciIhIgqiwi4iIJIgKu4iISIKosIuIiCSICruIiEiCqLCLiIgkiAq7iIhIgqiwi4iIJIgKu4iISIKosIuIiCSICruIiEiCqLCLiIgkiAq7iIhIgqiwi4iIJIgKu4iISIKosIuIiCRIk6gHICIif75WrN/B/PIt7NhzgNJWzehf1oHuHUujHlasqbCLiEgkVqzfwbQFa0mnSzilWRM+2n+IaQvWAnBFm5YRjy6+dCpeREQiMb98C+l0CSc3TZNKpTi5aZp0uoT55VuiHlqsqbCLiEgkduw5wElNjixDJzUpYceeAxGNKBlU2EVEJBKlrZpxqLL6iH2HKqspbdUsohElgwq7iIhEon9ZB6qqqjl4uIqamhoOHq6iqqqa/mUdoh5arOnmORERiUTt3e+6K75xqbCLiEhkuncsVSFvZDoVLyIikiAq7CIiIgkSyal4M/sG8A/h5jx3f9DM+gFPAc2BWe7+7SjGJiIiEmcFP2I3s1OACcClwBeBi81sIDAJGAScB/QyswGFHpuIiEjcRXEqPh3+vacCTcM/e4F17r7R3SuBqcCNEYxNREQk1gp+Kt7dPzaz7wBrgE+ARcDngG0ZzbYBnz+e9z399BYNbtsmQc8gTlIsoHiKneIpboqnuBUqnoIXdjPrDvwNcBawh+DovAtQk9EsBVQf3TunNMDu3fuprq6pry2nn96CnTv3Hc+Qi1aSYgHFU+wUT3FTPMWtMeMpKUnRuvWpENa/bFHcPHc1sNDd/wRgZpOBB4GqjDZtgT808P3aAbVBNsjxHN0XuyTFAoqn2Cme4qZ4ilse4mkHrM/eGUVhfxf4gZmdSnAqfiBQDgwzs07ARmAowc10DbEMuJjg9H1VPW1FRETiLk1Q1JflejFVU1P/6evGZmZjgNuBw8DvgHuAvgQ/d2sGzAVGuXvhByciIhJjkRR2ERERyQ89eU5ERCRBVNhFREQSRIVdREQkQVTYRUREEkSFXUREJEFU2EVERBJEhV1ERCRBIlmPPR/MbBwwJNycA7wBPJrR5Eyg3N2vyep3K/B94L9r+7r7w/kdbf3MbDxwA8Ez9Ce6+1MNWbPezDoQPH//DMCBYe4e+QOX64hnBPDNcN9y4G/d/VBWvzjNzwvARcD+sNkj7j47q18s5odgkabY5g+AmT0BlLr7bXHOnVpZ8cQ2d2plxRPb3KlVGw/wEhHnTiIKe5i0VwFfIvigzwd+6+49wtfbAm8B38rRvSfBU+5mFGi49TKzS4HLge4Ey9quMrOFBI/ZvRT4AJhjZgPcfV5W92eAZ9x9ZriK3neAMYUb/dHqiGcO8BBwAfAxMJngCYRPZ3WPy/zMIRjrJe6+7RjdYzE/QP+45g+AmV0B3EqQJ82Jae7UyoqnCzHNnVqZ8YS7Ypk7tTLjcfe5BE9PjSx3knIqfhvwgLsfcvfDwGqgQ8brjwM/c/d1Ofr2Am41s5VmNtXMWhdgvMfk7ouAvwrXpj+D4AvYZ6lnzXozawpcAvwi3DU5u00U6ojnAHC3u+8NHx28kiPnrFZc5ud/CMY/ycxWmNkjZnZEfsVsfvZnNIlV/pjZacA/8/9HTRcS09yBnPEcJKa5A0fHY2anENPcgZzzkymS3ElEYXf399x9KYCZdSY4JT83Y/syYEId3bcB3yM4WvkA+HG+x9sQ7n7YzB4hOHpaSMPWrC8F9ob/eNXVJhI54tni7gsAzKwNcC/wqxxd4zI/TYHXCJYk7k2wMNEdWd3iND8fQmzz51ngYWB3uB3r3CErHnffHOfc4ej5aUuMc4ej4wGizZ1EFPZaZnY+sAB4KOMb0giC0zcHc/Vx96+5+1vhN98fAAMKM9r6ufs4oA3QnoatWV+S1YYcbSKTFc+dAGZ2JkEhmejub+ToE5f5uSIc6zZ3/wT4V+ArWV1iNz/ELH/MbDjwgbsvzNid/f89NrlTRzy1r8Uud3LF4+4b4po7x5ofIsydxBR2M+tL8CH/e3efkvHSdcDMOvq0MrPMax8poDJX20Iys65m1gMg/KC/QvDNr11Gs1xr1v8JaGVm6XC7XY42BVdHPN3NrCuwBJji7t/L0S9O83OTmV2f0SxFsHphpljNT/hy3PLnJuAqM6sAxgPXAsOJae6QIx4zezquuUPueGbHNXeoY37C1yLLnUQUdjNrD/w7MNTdZ2bsLwWau/vGOrruA0abWVm4fS8wu462hXQu8JyZnWxmJwGDCE73mJl1Cj/cQ4Ejbv4J7y94k+DDBvDX2W0ikiuecuDXwLfd/ck6+sVpfhYBPzSz1uH1wBFkjTVm87M4jvnj7le6e7fwxr+xwKsER0KxzJ064hlLTHOnjnjGEdPcyRWPu38r6txJRGEHHiRYx/0pM6sI/4wk+Adra3ZjM3vezK519yqC6/E/NbPVBHeZji7kwHMJ76qcA7wDvA0sCb+w3Ab8kuA66BrCG0lq4wm73w2MMLNVBNeqjvpZT6HliofgmtlfAA9kzNl4iO38jAceI7gDdhVQUXu3axznJ/y8xTJ/srn7AWKaO3UYTkxzJxd3X0FMc+cYIs0drccuIiKSIEk5YhcRERFU2EVERBJFhV1ERCRBVNhFREQSRIVdREQkQVTYReSYzOxsMzuuVbTMbKyZDcrXmESkbirsIpIPlxM8P19ECiwRy7aKSOFZsHzoT4CWBI/4rCB4MtgdBEtSPm5mVZ61rraI5JeO2EXkRN1J8Kzy3kAn4Bzgq+7+E2A5wWJMKuoiBaYjdhE5UWOAK81sNMHqg58DWkQ7JBFRYReREzWD4N+QlwieNd+BYJUqEYmQTsWLyIm6Ghjv7rPC7TKgdlnNSnTznEgkdMQuIg1xao6fvD0MzDaz/cAegqVrO4WvvQo8ZmYnufuUAo5T5M+eVncTERFJEJ2KFxERSRAVdhERkQRRYRcREUkQFXYREZEEUWEXERFJEBV2ERGRBFFhFxERSZD/BZ+iRoYuMYUxAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df = pd.read_csv(dataurl+'skincancer.txt', sep='\\s+', header=0)\n", "result = analysis(df, 'Mort', ['Lat'], printlvl=1)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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hw849Ypu+ffvz7bdfU1ZWhtfr5YsvPmXAgIHs3Lmdxx77C5WVlVRVVfH55/8hISGJ8867kK+//oqDBw/idrtZtuxLBgw4/ScCiohI4Kin3wisW2cdUfRjY+MYNGgIX3zxH6677saTPl5cXHsmTpzMr36VTFVVNSNH3sDAgYMBGDduFI8//m+GDh3O2rVrGD/+LoKCgoiPH8Rdd40jNDSUVatWcu+9o3E6nVx88WVcccVVAIwaNZbJk8dTXV3NOecM45prrq+fBhARkYDQo3UbQFNbO96UNbW21qN1pS7U1oHT3Npaj9YVERERQEVfRESkxVDRFxERaSFU9EVERFqIFlv0m/EERmmkvF4PvgdFiojYo0UW/aCgEEpKDqjwS0B4vV6qq6soKsonJCTM7nREpAVrkev027aNo7Awj+LiogY5vtPpxONpOsvImrKm0tZOp4vw8EgiI1vbnYqItGAtsui7XEHExnZqsOM3t3WfjZnaWkSk7lrk5X0REZGWSEVfRESkhVDRFxERaSFU9EVERFoIFX0REZEWQkVfRESkhVDRFxERaSFU9EVERFoIFX0REZEWQkVfRESkhVDRFxERaSFU9EVERFoIFX0REZEWwpan7BljPgbaA1U1oWQgCngCCAdesCzroZptk4BZQDTwKZBiWVZ1wJMWERFp4gLe0zfGOID+QKJlWUmWZSUBucAc4AYgHjjHGHN1zS4LgTTLsvoDDmBioHMWERFp7CrcFfxn28e1bmNHT9/U/P2eMSYGyAJWAOssy9oEYIxZCNxqjFkFhFuWtaxmn3nAw0BGYFMWERFpnPaVFzB/5Vxmr5hJWHAov0waedxt7Sj6bYEPgalAMPAJ8Biw67BtdgFdgc7HiddZTEzkaaR66uLiomw5b0uktg4ctXXgqK0Dp6m29dqCtfxr2b+Ylz2PsuoyAHq36V3rPgEv+pZlfQV89dNrY8xs4BHg88M2cwAefMMP3mPE66ygoBiPx3viDetRXFwUeXkHA3rOlkptHThq68BRWwdOU2trr9fLVzu/ICPnad7bvBRvTYmMDmnNmIHjmHxGWq37B7zoG2MuAEIty/qwJuQANgOdDtusI7AT2H6cuIiISItR5a7i9Q2vkJkzjdy8bH+8e1QPJiWkMip+DJEhUTidjlqPY8fl/TbAI8aY8/Bd3r8bSAFeNMb0BTYBo4A5lmVtMcaUG2POtyzrC2AM8I4NOYuIiARcUXkhC1Y/w6zcTHaVHOrzntNxGCmJaVzd61qCnHUv5XZc3n/LGDMM+AFwAdMsy/rKGDMOeBkIA5YAi2t2GQ1kGWOige+BpwKds4iISCBt2r+RrNwMnl29kNLqEgCcDifX9r6e1MQ0zu449JSO6/B6AzveHUA9gU0a02/e1NaBo7YOHLV14DSmtvZ6vXy9ezkZ2U/zzqa3/OP1kcFRjB44lolDUuge3aPWYzidjp8msPfCN3R+BFtuziMiIiI+1Z5q3trwOpk56Xy/9zt/vEtkVyYmpHJX/FiiQ1vXy7lU9EVERGxwoGI/i1YvICs3g+3F2/zxM9qfSWriVK7rc8NJjdfXhYq+iIhIAG07uJWs3EwWrnqG4irf0IIDByN6XUtq0lSGdRyOw1H7LPxTpaIvIiISAN/t+YbM7Gm8tfF13F43ABFBEdwZfxeTEibTq3XtN9apDyr6IiIiDcTtcfPOprfJzEnn693L/PGOrToxYUgyYwfeQ5uwtgHLR0VfRESknhVXHuS5NQuZkZvB1gOb/fHBsQmkJqZxQ99fEuIKCXheKvoiIiL1ZGfxDmatmMH8lXM5ULnfH7+yx1WkJk3l/M4XNth4fV2o6IuIiJymnL0/kJGTzhsbXqXaUw1AmCuM2weMJjlhMn3b9rM5Qx8VfRERkVPg8Xp4b/NSMnPS+XLnoWfGxYW3Z/yQSdw9aDwx4TE2ZvhzKvoiIiInoaSqhBesZ5mZM52N+zf44/HtBpGalMZN/W4h1BVqY4bHp6IvIiJSB7tLdjFnRRbPrJxNYUWhP35Z9ytITZzKRV0vsXW8vi5U9EVERGrxY/4KMnPSeXXdYqo8VQCEukK5tf8dTEqczIB28TZnWHcq+iIiIkfxeD18tPV9MnKm8dn2T/zx2PBYxg2awD2DJxIXEWdfgqdIRV9ERKRGWXUZL1nPMyNnGuuK1vrj/dsaUhLTuLn/bYQHhduY4elR0RcRkRZvb+le5v6YxbwfZ1FQXuCPX9j1EiYnpnFp9ytwOpw2Zlg/VPRFRKTF+nHvjzz68d9ZvPYFKj2VAAQ7g7m5/20kJ0xhUOxgmzOsXyr6IiLSoni9Xj7Z9hGZOel8vO1Df7xtaFvuGewbr+/QqqONGTYcFX0REWkRKtwVvLz2RTJz0lmzb7U/3qdNX5ITpnCbuZOI4AgbM2x4KvoiItKsFZQVMG/lLOasyCKvbK8/fn7nC3nw4t9zTpsLm8V4fV2o6IuISLO0rnAtM3Km86L1LOXucgCCnEHc2PdmUhKnkBCXRFxcFHl5B23ONHBU9EVEpNnwer18sfMzMrPTeW/LUn88OqQ1dw+6l/FDJtE5souNGdpLRV9ERJq8Snclr61/mcycafyYn+uP94juSXLCZO6Iv4vI4EgbM2wcVPRFRKTJKizfx/yVc5m1YgZ7Snf740M7Dic1aSojel6Dy+myMcPGRUVfRESanI1F65mZm8HzaxZRWl0KgMvhYmSfG0hJTOPMDmfbnGHjpKIvIiJNgtfrZfmur5ie8zTvblqCFy8AkcFRjBk4jgkJyXSL6m5zlo2brUXfGPM4EGtZ1jhjzBXAE0A48IJlWQ/VbJMEzAKigU+BFMuyqu3KWUREAqvKXcWbG18jMzud7Lwf/PFuUd2ZmJDC6PixRIVE25hh02Fb0TfGXA7cDbxtjAkH5gAXA9tqYldblvUOsBCYYFnWMmPMbGAikGFX3iIiEhj7K4pYuGo+s1ZksqN4uz9+VoezSU2cyjW9RxLk1AXrk2FLaxlj2gF/Af4KJAJDgXWWZW2qeX8hcKsxZhUQblnWsppd5wEPo6IvItJsbTmwmazcDBatXkBJVTEAToeTa3qNJCUxjaGdhtmcYdNl11ekGcD/AN1qXncGdh32/i6gay3xOouJsWeJRlxclC3nbYnU1oGjtg6cltjWX277kie+eoJX17yKx+sBIDIkkvFnjOdXw35F77a9G+S8LamtA170jTETgG2WZX1ojBlXE3ZCzYwMHwfgqSVeZwUFxXg83hNvWI9a2h2e7KS2Dhy1deC0pLau9lSzZOObZOSk892eb/zxzq26MDEhlbsGjqV1aBuopkHapLm1tdPpqLWza0dP/3agkzEmG2gHRAI9APdh23QEdgLbgU7HiIuISBN2sPIAz65eQFZuJlsPbvHHE+POIDUpjZG9byTYFWxjhs1TwIu+ZVlX/vTvmp7+JUAKsM4Y0xfYBIwC5liWtcUYU26MOd+yrC+AMcA7gc5ZRETqx/aD28jKzWTh6mc4WHkAAAcOrup1DamJaQzvdB4Oh8PmLJuvRjHt0bKs8povAC8DYcASYHHN26OBLGNMNPA98JQtSYqIyCn7Yc93ZOak88aG13B7fRd2w4PCuWPAaCYlpNKnTT+bM2wZbC36lmXNwzcjH8uyPsQ3k//obXLwze4XEZEmxO1xs3TzEjJz0lm+6yt/vENERyYMSWbMoHG0C4uxMcOWp1H09EVEpPkorirmhTWLmJEznc0HNvnjg2KGkJI4hZv63UKIK8TGDFsuFX0REakXu4p3MmvFDOavmsv+iiJ//MoeV5GcOIULu1ys8XqbqeiLiMhpWZGXQ0ZOOq+tf5lqj+8u6WGuMG41d5KcMJn+7YzNGcpPVPRFROS4cjfks3T5VvL3lxPbOowRw7qT0CcWj9fDB1veJSM7nS92fubfPjY8jvFDJnH3oPHEhsfamLkci4q+iIgcU+6GfBa9vxaXy0lEWBBFJZU8814u7eJX8NbOZ9hQtN6/7YB28aQkpvHLfrcSFhRmY9ZSGxV9ERE5pqXLt+JyOQkNdlHi3ceP3tdZ4X2DilUH/Ntc2u1yUhLTuKTbZRqvbwJU9EVE5Jjy95dTGrKV3IqXWev+CA9VADgJ5o4Bd5CcOIX4mIE2ZyknQ0VfRESO4PV6+XjbB3zs+itbKr7zx8NoTbxzJMMjf8nDl11hY4ZyqlT0RUQEgPLqchavfYEZOdOwCtf4463pRlLwzfTyXo7DE8zN5/a3MUs5HSr6IiItXF5pHnN/zGLeylnkl+X74xd2vYQR7cewb0MvCg5UHjF7X5omFX0RkRbK2reGGTnTeGnt81S4KwAIdgZzU79bSE6cwpDYBN+Gw21MUuqVir6ISAvi9Xr5dPsnZOQ8zUdbP/DH24S2YdygCdw7ZCIdW3Wq5QjSlKnoi4i0ABXuCl5dt5iM7HRW71vpj/du3YfkxCncZu6kVXArGzOUQFDRFxFpxvaVFzDvx9nMXjGTvLK9/vh5nS8gJTGNX/QcgdPhtDFDCSQVfRGRZmhD0Toyc6bzovUsZdVlAAQ5g7i+z02kJqaR2P4MmzMUO6joi4g0E16vl692fkFGztO8t3kpXrwARIe0ZszAcUwYkkyXqK42Zyl2UtEXEWniqtxVvL7hFTJzppGbl+2Pd4/uSXJCKncOuIvIkCgbM5TGQkVfRKSJKiovZMHqZ5iVm8mukp3++Dkdh5GSmMbVva4lyKlf83KIfhpERJqYTfs3kpWbwbOrF1JaXQKA0+Hkut43kJI4hbM7DrU5Q2msVPRFRJoAr9fL8t3LyMxO551Nb/nH6yODoxg9cCwTh6TQPbqHzVlKY3fCom+MucGyrNePio2xLGtBw6UlIiIA1Z5q3trwOpk56Xy/99DDb7pEdmViQip3xY8lOrS1jRlKU3Lcom+MGQkEA/8wxrgOeysYeBhQ0RcRaSAHKvazcPV8ZuVmsr14mz9+RvszSU2cyrW9ryfYFWxjhtIU1dbTTwIuA9oDUw+LVwNPNmRSIiIt1dYDW3j0+zlkfTeL4qqDADhwcHWv60hNmsrQjsNwOBw2ZylN1XGLvmVZfwL+ZIyZbFnW9ADmJCLS4ny35xsystN5a+PreLweACKCWjEq/i4mJqTSq3VvmzOU5qAuE/nmGmNG4+vx+79eWpb1RINlJSLSArg9bpZseovMnHS+2b3cH+8S1YV7ByczJv5u2oS1tTFDaW7qUvSfBboBP0LNdNFDf4uIyEkqrjzIs6sXMHNFJlsPbPbHE+KSSEmcwvjhY9m/r8K+BKXZqkvRHwL0tyzLU18nNcY8AtyC78vDbMuynjDGXAE8AYQDL1iW9VDNtknALCAa+BRIsSyrur5yEREJlB0HtzNrxQwWrJrHgcr9/vhVPa8mNXEq53Y+H4fDQYgrBFDRl/pXl6K/B9+M/Xr5CTTGXIxvgmBCzXFXGWM+BOYAFwPbgLeNMVdblvUOsBCYYFnWMmPMbGAikFEfuYiIBEL23u/JzEnn9fWv4va6AQgPCud2M4pJCZPp27afzRlKS1Hbkr37av65G/jEGPMaUPXT+6c6pm9Z1n+MMZdallVtjOlSk0MbYJ1lWZtqzr0QuNUYswoItyxrWc3u8/AtF1TRF5FGzeP18O7md8jMSeernV/44+0jOjBhSDJjB91Du7AYGzOUlqi2nv6Qmr8P1PwZUF8ntSyryhjzMPA74CWgM7DrsE12AV1riddZTEzk6SV7iuLi9HCLQFFbB47a+sRKKkt4JucZ/rXsX6zbt84fH9J+CL8997fcMfgOQoNCT3gctXXgtKS2rm3J3j0NeWLLsv5ojHkMeBPoz5GTAx2AB3AeJ15nBQXFeDyBnXcYFxdFXt7BgJ6zpVJbB47auna7S3YxZ0UWz6ycTWFFoT9+efcrSUlM46Kul+BwODhQWAlU1nostXXgNLe2djodtXZ263Ib3k0cWXi9QCm+2fz3WZa165g7Hv94A4Awy7KyLcsqNca8gm9Sn/uwzToCO4HtQKdjxEVEGoUV+bnMyJnGq+sWU+XxjYCGukK5tf8dTEqczIB28TZnKHJIXSbyvQZEAdPw9bLH17zOBWYCI0/ynL2Bh40xF+D7AnEDMAPf7X77ApuAUcAcy7K2GGPKjQNLfSUAACAASURBVDHnW5b1BTAGeOckzyciUq88Xg8fbnmPzJxpfLbjP/54bHgs9wyeyLhBE4iLiLMxQ5Fjq0vRv9CyrLMPe/0rY8zXlmXdY4w56SEAy7KWGGOGAj/g692/bFnW88aYPOBlIAxYAiyu2WU0kGWMiQa+B5462XOKiNSHsuoyXrKeZ0bONNYVrfXH+7c1pCSmcXP/2wgPCrcxQ5Ha1aXoRxtjoizLOghQU3wjat47pRtAW5b1f8D/HRX7EEg8xrY5gB4OLSK22Vu6l7k/ZjHvx1kUlBf44xd3vZTUpDQu7XaF7ocvTUJdiv4cYLkx5iV8Rf5mYJYxZiqwuiGTExGx0+qCVczImcbitS9Q6fFNvgt2BnNz/9tITpjCoNjBNmcocnJOWPQty/qbMeZ74Bp8T9hLsyzrY2PMWfjWzYuINBter5ePt31IZk46n2z7yB9vG9qWewZP4J7BE+nQqqONGYqcutpuzjPAsqw1xpgzgXxg/mHvnWlZ1neBSFBEJBDKq8t5Zd1LZOaks2bfoYuYfdr0JTlhCreZO4kIjqjlCCKNX209/ceB6/BNrjuaF98sfBGRJi2/LJ9nVs5mzoos8sr2+uMXdLmIlMQpXNHjKpwOp40ZitSf2m7Oc13N370Cl46ISGCsK1xLZs40XrKeo9xdDkCQM4gb+95MSuIUEuKSbM5QpP7V5eY8kcDfgHjgVuBR4LeWZRU3cG4iIvXK6/Xy+Y5PycxJ5/0t7/rjrUPbMHbgPUwYkkynyM42ZijSsOoye/8pfPe87wCU43vE7Ux8N9AREWn0Kt2VvLpuMZk501hZsMIf7xndi+TEydw+YDSRwfY8p0MkkOpS9M+wLOteY8w1NbfNHY3vFrwiIo3avvIC5q+cy+wVM9lTutsfH9bpXFIS0xjR8xpcTpeNGYoEVl2Kvvuo1y5O8qE3IiKBtLFoPTNyp/P8mkWUVZcB4HK4uL7PjSQnTuHMDmef4AgizVNdiv6nNU/DCzfGXAWkAR83bFoiIifH6/WybNeXZGQ/zbub38Fb85ywqJBoxgwcx4QhyXSN6mZzliL2qkvR34xvHH8/8GfgPeBPDZiTiEidVbmreHPja2Rmp5Od94M/3i2qO5MSUhkdP5bIkJbzvHSR2tSl6A/Bdze+DcBLwCuWZZU3aFYiIiewv6KIBaueYVZuJjtLdvjjZ3U4m9TEqVzTeyRBzrr8ihNpOepyG96JAMaY4fgeo/uFMWanZVnnNXRyIiJH23JgM1m5GSxavYCSKt/KYafDyTW9RpKSmMbQTsNszlCk8arLOv1Q4ELgFzV/vGj2vogE2De7l5ORnc6STW/i8frmErcKjmR0/BgmDEmhZ2vdR0zkROpy7asI2Ac8AdxmWdbaE2wvIlIvqj3VLNn4Jhk56Xy35xt/vHOrLoxPSGbswHG0Dm1jY4YiTUtdiv69wAhgMnCFMeZd4H3LslY2aGYi0mIdrDzAotXzycrNZNvBrf54YtwZpCalMbL3jQS7gm3MUKRpqsuY/nPAcwDGmOvx3ZL3n/jW64uI1JvtB7eRlZvJwtXPcLDyAAAOHIzodS0piVMY3uk8HA6HzVmKNF11GdO/FLi65k8I8Bq+3r+ISL34Yc93ZOak88aG13B7ffcDiwiK4I4Bo5mUkErvNn1tzlCkeajL5f0n8D1e907LsjSBT0TqhdvjZunmJWTmpLN811f+eMdWnRg/eBJjB91D27B2NmYo0vzU5fL+GYFIRERahuKqYl5Ys4gZOdPZfGCTPz44NoGUxCnc2PdmQlwhNmYo0nzpzhUiEhA7i3cwe8VM5q+ay/6KIn/8yh5XkZo0lfM7X6jxepEGpqIvIg0qNy+bjOx0Xt/wCtWeagDCXGHcZkaRnDiZfm3725yhSMuhoi8i9c7j9fD+lnfJzE7ni52f+eOx4XGMHzKJcYMmEBMeY2OGIi2Tir6I1JvSqlJetJ5jRu40NhSt98fj2w0kOXEKv+x3K2FBYTZmKNKyqeiLyGnbU7qHuStmMm/lbPaV7/PHL+12OSmJaVzS7TKN14s0ArYUfWPMH4Hbal6+bVnW740xV+BbHhgOvGBZ1kM12yYBs/A93vdTIMWyrGob0haRo6zM/5EZudN4Ze1LVHoqAQhxhnBL/9tJTpxCfMxAmzMUkcMFvOjXFPdfAGfge3jPUmPMncBjwMXANuBtY8zVlmW9AywEJliWtcwYMxuYCGQEOm8R8fF4PXy89QMycqbx6faP/fGYsBjuHjyeewdPon1EexszrF+5G/JZunwr+fvLiW0dxohh3UnoE2t3WiKnxI6e/i7gt5ZlVQIYY1YD/YF1lmVtqoktBG41xqwCwi3LWlaz7zzgYVT0RQKurKqMBavmMSNnGmsLLX+8X5v+pCSlcUv/2wkPCrcxw/qXuyGfRe+vxeVyEhEWRFFJJYve9z1zTIVfmqKAF/3DH9RjjOmH7zL/0/i+DPxkF9AV6HyceJ3FxESecq6nIy4uypbztkRq64a1t2Qv07+ZzvRvppNXmuePX97rcu479z5G9B2B0+G0McOG8+HiXEJDXISF+H5VhgS7KK+s5sMfdnL58IZ9lK9+rgOnJbW1bRP5jDGDgLeB+4FqfL39nzgAD+DENwRwdLzOCgqK8Xi8J96wHsXFRZGXdzCg52yp1NYNx9q3hhk503hp7fNUuCsACHYG88t+t5KcOIXBsUMAKMgvsTPNBrUrr5iIsCCqqg/92nE6HOzKK27Qnzv9XAdOc2trp9NRa2fXrol85+O7n/+vLct63hhzMdDpsE06AjuB7ceJi0gD8Hq9fLr9EzJynuajrR/4421D2zJ56GTu6H03HVp1tDHDwIptHUZRSSWhwYceKlpZ7SG2tZYdStNkx0S+bvie1He7ZVkf1YSX+94yfYFNwChgjmVZW4wx5caY8y3L+gIYA7wT6JxFmrsKdwWvrltMRnY6q/f5R+Do3boPkxInc7sZRc/OHZtVj6guRgzrzqL311IBhAQ5qaz24HZ7GDGsu92piZwSO3r6vwPCgCeMMT/FMoFx+Hr/YcASYHHNe6OBLGNMNPA98FQgkxVpzgrKCpi/cg6zf5zJ3tI9/vh5nS8gOXEKV/W8utmO19fFT5P1NHtfmguH1xvY8e4A6gls0ph+86a2PjXrC9cxI3c6L1rPUlZdBkCQM4jr+9xEamIaie1//nBNtXXgqK0Dp7m19WFj+r2AzUe/rzvyibQQXq+XL3Z+RmZ2Ou9tWeqPR4e0ZszAcUwYkkyXqJNaHCMiTYyKvkgzV+mu5PX1r5CZM40V+Tn+eI/oniQnTOaO+LuIDLZnaauIBJaKvkgzVVReyPxVc5m1Yga7Sw7d7mJox+EkJ07hml7X4XK6ajmCiDQ3KvoizczG/RvIys3gudULKa0uBcDpcDKy942kJE3hrA7n2JyhiNhFRV+kGfB6vSzfvYyM7KdZuultvDX3tIoMjmL0wLFMHJJC9+geNmcpInZT0Rdpwqo91by54TUyc9L5Ye/3/ni3qO5MTEhhdPxYokKibcxQRBoTFX2RJuhAxX4Wrp7PrNxMthdv88fPbH8WKYlpXNfnBoKc+t9bRI6k3woiTcjWA1vIWpHJolXzKa7yrS124OCa3iNJSUxjaMdhOBwOm7MUkcZKRV+kCfh299dk5kzjrY2v4/H6Hv4SEdSKO+NHMylhMr1a97Y5QxFpClT0RRqpak8172x6i4zsdL7d87U/3qlVZyYkpDAm/m7ahLW1MUMRaWpU9EUameLKgyxaPZ+s3Ey2HtzijyfEJZGcMJkb+v6SEFeIjRmKSFOloi/SSGw/uI1ZK2awYNU8DlYeAHzj9Vf1vJqUxDTO7Xy+xutF5LSo6IvYLHvv92TmpPP6+ldxe90AhAeFc8eA0UxKSKVPm342ZygizYWKvogN3B43725+h8ycdJbt+tIfbx/RgQlDkhk76B7ahcXYmKGINEcq+iIBVFJVwvNrFjEzdzqb9m/0xwfGDCYlcQo39buFUFeojRmKSHOmoi8SALtLdjF7xUyeWTmboooif/zy7leSkpjGRV0vOanx+twN+SxdvpX8/eXEtg5jxLDuJPSJbYjURaQZUdEXaUAr8nPJzE7ntfUvU+WpAiDUFcqt/e8gOXEKpt2Akz5m7oZ8Fr2/FpfLSURYEEUllSx6fy2ACr+I1EpFX6SeebwePtzyHhk56Xy+41N/PDY8jnsHT+TuQeOJi4g75eMvXb4Vl8tJaLDvsbihwS4qauIq+iJSGxV9kXpSWlXKS2ufZ0bONNYXrfPHTdsBpCSmcXP/2wgLCjvt8+TvLyci7Mj/dUOCnOTvLz/tY4tI86aiL3Ka9pTuYe6PWcz7cRb7yvf54xd3vZTUpKlc2u3yel1fH9s6jKKSSn9PH6Cy2kNs69P/QiEizZuKvsgpWl2wisycdF5e+yKVnkoAQpwh3Nz/NpITpzAwZlCDnHfEsO4sen8tFfh6+JXVHtxuDyOGdW+Q84lI86GiL3ISvF4vH2/7kMycdD7Z9pE/3i6sHeMGjeeeIZPoENGhQXP4adxes/dF5GSp6IvUQXl1Oa+se4nMnHTW7Fvtj/dt04/kxCnc2v8OIoIjbMxQROTEVPRFapFfls+8H2cx58cs8svy/PELulxESuIUruhxFU6HM6A5acmeiJwqFX2RY1i7z2JG7nResp6j3O2bFR/kDOLGvjeTmpjGkLjEUzpufdxUR0v2RORUqeiL1PB6vXy24z9kZqfzwdb3/PHWoW24e+C9jB8yiU6RnU/5+Lkb8pnz9mrKK924PV4OlFQy5+3V3Htt/EkVay3ZE5FTZVvRN8ZEA18C11mWtdkYcwXwBBAOvGBZ1kM12yUBs4Bo4FMgxbKsapvSlmao0l3Jq+sWk5kzjZUFK/zxntG9SE6czO0DRhMZHHna51n88XpKyqtxOMDpAI/XS0l5NYs/Xn9SRV9L9kTkVAV2MLKGMWYY8DnQv+Z1ODAHuAGIB84xxlxds/lCIM2yrP6AA5gY+IylOSos38e/vnucsxYMZupHKf6CP7zTecwb8Sxfjfqe8UOS66XgA+wpLK8p+A4cDkfN3774yRgxrDtut4eKKjder5eKKreW7IlIndjV058ITAEW1LweCqyzLGsTgDFmIXCrMWYVEG5Z1rKa7eYBDwMZgU1XmpONReuZkTudF9Y8S2l1KQAuh4uRfW4gNXEqZ3Q4q4HO7MXrxffV9aeIFxwO70kdRUv2RORU2VL0LcuaAGCM+SnUGdh12Ca7gK61xOssJqZ+emknKy4uypbztkR1aWuv18unWz7liWVP8Kb1Jl58hTY6NJpJZ05i6rCpdG99/J7yt6v38Mon69mzr5QO7SL45SV9OTv+5Nbjd2kfxbY9B/Hy0+X9Q/GT/Xm5PC6Ky4f3Oql96oN+rgNHbR04LamtG8tEPidweHfHAXhqiddZQUExHs/J9aROV1xcFHl5BwN6zpbqRG1d5a7ijQ2vkpkzjZy8H/zx7lE9mJiQwuj4sUSGREElxz3O4UvkwoKd5BWWMn1xNqOv7H9SvesbL+jJnCVrKK+optrtweV00io8mBsv6Nkkfl70cx04auvAaW5t7XQ6au3sNpaivx3odNjrjsDOWuIitSoqL2TB6meYlZvJrpJDPzJndxhKalIaV/e6jiDnsX/8j15WV1xaeUpL5I61PO/eawbosryI2KaxFP3lgDHG9AU2AaOAOZZlbTHGlBtjzrcs6wtgDPCOnYlK47Z5/yaycjNYtHoBpdUlADgdTq7tfT0piVM4p+OwWvc/1o1v9u4rpVV4EIUHvVRXewgKchIVHlTrErnj3UBn9JX9+f2oM+v1M4uI1FWjKPqWZZUbY8YBLwNhwBJgcc3bo4GsmiV+3wNP2ZKkNFper5evdy8nMyedJRsPjdeHu1oxMOhqelZcR6+CnoSWnHh2+7FufONwwMHSQ6tE3ZVuqqrcdI45/m13dQMdEWmMbC36lmX1POzfHwI/u82ZZVk5+Gb3ixyh2lPNiytf5O+f/YPv9nzrj3eJ7Mq1ncdQsu5swj1RhIQ763yr2mPd+MY3lcR7xL88XiivOv70Et1AR0Qao0bR0xc5GQcrD7Bw1XyycjPYXrzNH0+KO4PUpKlc1/sGnnxhBZ6gypPuaR/rxjfumomgDsdPS+x8xX9/ccVJHUc30BERu6noS5Ox7eBWsnIzWbjqGYqrfLNtHTgY0etaUpOmMqzjcBwO3yL4U+1pH+tZ9QAuJ7ich+5l5Tl6wT1HTtwLC3ZSWl7tP6+eeS8ijYGKvjR63+/5lsycdN7c8DpurxuAiKAI7oy/iwcvuZ/W7p+vlz/VnvaxbnxTVVlNUUkVHq/Xf3nf64WO7Q4d6+iJe5XVHvB6CXI6KC2v1kx9EWkUVPSlUXJ73CzdvISM7Kf5evcyf7xjq06MHzyJsYPuoW1YO+LaHXuN7bF67HXtaSf0iT2iOB/9oByX00FYqItbLu3r3+ZYE/cAIsODeWR87SsGREQCRUVf6qQ+HglbF8VVxTy/eiEzcqez5cBmf3xwbAIpiVO4se/NhLhCTnic+rxVbUKfWO69Nr7WY2ninog0BSr6ckLHW3MOtc+EPxk7i3cwe8VM5q+ay/6KIn/8yh5XkZo0lfM7X+gfr6+ro3vsp+NEx9LEPRFpClT05YQacs15bl42GdnpvL7hFao9NRPfnKHEB/2CXpXX03d/P6LLu590wQ+00xlOEBEJFBV9OaG6Xrqu6xCAx+vhvc1LycxJ58udn/vjceHtubbLaCo2DKeVt+1Jra+3m558JyJNgYq+nFBdLl3nbsj3P0zG7fFwoKSSOUvWcO81A/yFr7SqlBesZ5mRM42N+zf4941vN4jUpDRu6ncL/35hJUWnsL6+MajP4QQRkYagoi8nVJdL14s/2UBJWSUOhxOX04nHCyVllSz+ZAMdOlYze8VMnlk5m8KKQv8+l3a7nNSkqVzc9dLTXl8vIiInpqLfwAI1670h1eXS9Z59pYADZ83Qu9MB+xyb+aH4DWYv+IwqTxUAoa5Qbul/O8mJUxjQLv5n59KEOBGRhqOi34ACMes9UE586dqBw+HFi4c9zh9YF/waea4c31seiAmLYdzgCQyP/CXLs8uYs6aQ2Nbf/+zLgybEiYg0HBX9BtQYnrRWX1caTnScmDYOvjn4LhtDXuegc7s/3pbu/OGS+7m5/22s21Jywi9BmhAnItJwVPQbkN3j08e60jBnyRqiw4Mor/LUuaDWdsWiYycPc3/M4iWy2B+2z79PnDuRQfyS/756NEl92wOwdPnqOn0J0oQ4EZGGoaLfgOo6Pt1Q4/5HX2nweLyUlFVSXlFNx5iIOg83HOuKxW7vZn7z8VOsdX9Ihdv3tLkgRzAm+HL6VF5P/5iBumudiEgjo6LfgOoyPt2Q4/5HF9kDJZWAA7fHi8PhqPNww0/H8Xq9bPd8R3bVYrZ6vvG/3za0LXcPGs/4IZPo0KrjcY+jSXoiIvZS0a+jU+mN12V8uiHH/Y8ustVuDw4HuFyHHhFbl552m2gn3xcvZaXnZQq8m/zxts6uPHjBfdxuRhERHHHCfDRJT0TEXir6dXA6vfETjU835CXvo4us0+Hr5UdHBPu3qa2nXVBWwDMrZ/NMWSaF7nx/vKNjCIP4JQ9cMcY/Xl8XmqQnImIvFf06CGRvHOrvkvfRRbZ923AOlFTicjnxer3H7WmvL1zHjNzpvGg9S1l1GQAuRxD9gy6hT9UNDGg95LSeWKciLyJiDxX9Oghkb7y+L3kf69nwx+ppe71evtj5GZnZ6by3Zal/++iQ1owddA8ThiTTObJLveQkIiL2UNGvg0D2xhv6kvfRXwIq3ZW8ZD1PZs40VuTn+OM9onuSnDCZO+LvIjI4skFyERGRwFLRr4NA98YDobB8HwtWzWPWihnsLtnlj5/TcRipiVO5ute1uJyuWo4gIiJNjYp+HTSnCWgb928gKzeD51YvpLS6FACnw8nI3jeSkjSFszqcY3OGIiLSUFT066gpT0Dzer0s3/UVGTnpLN30Nl68AEQGRzF64FgmDkmhe3QPm7MUEZGGpqLfjFW5q3hr4+tkZD9Ndt4P/ni3qO5MTEhhdPxYokKibcxQREQCqUkUfWPMKOAhIBj4l2VZ02xOqVHbX1HEwlXzmbUikx3Fhx5+c2b7s0hNmsq1va8nyNkk/tOLiEg9avS/+Y0xXYC/AGcBFcCXxpiPLctaZW9mjc+WA5vJys1g0eoFlFQVA77x+mt6jSQlMY1zOg7F4XDYnKWIiNil0Rd94ArgI8uy9gEYYxYDtwCP2JpVI/LN7uVk5kzj7Y1v4PF6AIgIasWo+LuYlDCZnq172ZyhiIg0Bk2h6HcGdh32ehcwtK47x8TYs8Y8Li6qQY9f7anmtTWv8c+v/smy7cv88a7RXfnV0F8x8ayJtAlr06A5NBYN3dZyiNo6cNTWgdOS2ropFH0n1Ew393EAnrruXFBQjMfjPfGG9SguLoq8vIMNcuziyoMsWj2frNxMth7c4o8nxCWRmpjG9X1uItgVTNVByDvYMDk0Jg3Z1nIktXXgqK0Dp7m1tdPpqLWz2xSK/nbgwsNedwR22pSLbbYf3MasFTNYsGoeBysPAODAwVW9riE1MY3hnc7TeL2IiNSqKRT9D4D/M8bEASXAzcAke1MKnOy935OZk87r61/F7XUDEB4Uzh0DRpOcMJnebfranKGIiDQVjb7oW5a1wxjzP8DHQAgwy7Ksr21Oq0G5PW7e3fwOmTnpLNv1pT/eIaIjE4YkM3bQPbQNa2djhiIi0hQ1+qIPYFnWs8CzdufR0EqqSnh+zSJm5k5n0/6N/vjAmMGkJqZxU79bCHGF2JihiIg0ZU2i6Dd3u4p3MnvFTOavmkNRRZE/fkX3X5CSlMaFXS7WeL2IiJw2FX0brcjPJTM7nVfXL6baUw1AqCuU28ydJCdMoX87Y3OGIiLSnKjoB5jH6+GDLe+SmTONz3d86o/Hhsdx7+CJjBs8gdjwpvlgHxERadxU9AOktKqUl9Y+z4ycaawvWuePm7YDSElM4+b+txEWFGZjhiIi0typ6DewPaV7mLtiJvNWzmZf+T5//JJul5GSmMal3S7XeL2IiASEin4DWVWwkhk503h57YtUeioBCHGGcHP/20hOnMLAmEE2ZygiIi2Nin498nq9fLztA2YvzeT9je/74+3C2jFu8ATuGTyRDhEdbMxQRERaMhX9elBeXc7La18kMycdq3CNP963TT+SE6dwm7mT8KBwGzMUERFR0T8teaV5zFs5i7k/ZpFflu+PX9brMsbHp3B5j1/gdDhtzFBEROQQFf1TYO1bw8zc6bxoPUeFuwKAIGcQN/W9hZSkNC6LP79ZPbVJRESaBxX9OvJ6vXy6/RMyc9L5cOuh8fo2oW24e9B47h08kU6RnW3MUEREpHYq+idQ6a7klXUvkZkzjVUFP/rjvVr3JjlxCrebUbQKbmVjhiIiInWjon8c+8oLmL9yLrNXzGRP6W5/fHin80hNmsoveozA5XTZmKGIiMjJUdE/yoaidczImc4L1rOUVZcB4HK4uL7PjaQkpnFGh7NszlBEROTUqOjjG6//aucXZOak8+7md/DiBSA6pDVjBo5j/JBJdI3qZnOWIiIip6dFF/0qdxWvb3iFzJxp5OZl++Pdo3owMSGF0fFjiQyJsjFDERGR+tMii35ReSELVj/DrNxMdpXs9MfP6TiMlMQ0rul1ncbrRUSk2WlRRX/z/k3MzJ3Os6sXUlpdAoDT4eTa3teTmpjG2R2H2pyhiIhIw2n2Rd/r9bJ81zIyc9JZsvFN/3h9q+BI7oofy8SEVLpH97A5SxERkYbX7Iv+uKWjeHvDW/7XXSK7MjEhlbvixxId2trGzERERAKr2Rf9H/NXAJAUdwapSVO5rvcNBLuCbc5KREQk8Jp90b+k2+XcfNntDOs4HIfDYXc6IiIitmn2Rf+fl/wbj8drdxoiIiK203NfRUREWggVfRERkRbCtsv7xpg/AW7Lsv6v5nUbYBHQG8gDbrMsa7cxJgSYDZwNlAGjLMtaY0/WIiIiTVfAe/rGmNbGmNnAb49668/AZ5ZlxQNZwL9r4r8CSmrivwbmBSpXERGR5sSOy/s3AOuAfx4VvxZfTx/gOeBqY0zw4XHLsj4F4owx3QOUq4iISLMR8KJvWdZ8y7L+BriPeqszsKtmm2rgABB3eLzGLqBrAFIVERFpVhpsTN8Ycyvw5FHhNZZlXXGcXY5eRO8APPi+mHiPEa+TmJjIum5ar+Li9HS+QFFbB47aOnDU1oHTktq6wYq+ZVkvAS+dxC47gI7AdmNMEBAFFADbgU7AhprtOgI7j3mEYygoKA74Ov24uCjy8g4G9Jwtldo6cNTWgaO2Dpzm1tZOp6PWzm5jWrK3BBhb8+/b8U3qqzo8boy5ACi3LGurPSmKiIg0XY3pjnx/AOYZY1YCRcDomvjTwIyaeAUwpo7Hc4HvW48d7DpvS6S2Dhy1deCorQOnObX1/2/v3kPsqu4ojn+T8RWTmFJQqw0Rg2QlBlTUGIwGA0aCEjGlSrCt4COJokGhKk3BF/qHbaENiKWKbxFE1JRKJBiMtKbVBFNM64MsRYwaadF/SgQTn9M/9hm4Xu5k1HNvbnLP+sBl5uxzzp09i5n5ncees1u+l6FO68cNDw/sI2rPBDb2uxMRERF9MB/4e3vjIBf9g4E5lNH+7f8pEBERMYiGKOPgXqFcHf+GQS76ERER0WJfGsgXERERPZSiHxER0RAp+hEREQ2Roh8REdEQKfoRERENkaIfERHRECn6ERERDbEvPYZ3vyTpfOBWYCKw3vZ1khYCfwAmAE/YvqmffRwkkn4B/LpaXGf7huTdPZIOA14CFtvePlq2kk4C7gcOA14ErqqmxI5vqUPWK4BrKbOKbgGutP15sq6vPeuW/3DgSQAABFxJREFU9pXAhbYXVMsDn3XO9GuQNB24B1gCnACcLOlc4EHgAmAWMKdqi5okHQrcBZwFnAjMrw66kncXSJpLeWznjGp5AqNn+xiw0vYMynTXy/d+j/dfHbKeAdwIzKP8LRkPXFNtnqxraM+6pf14YFXb5gOfdYp+PT+hnP3sqGYEXAp8Crxt+93qCPEx4KJ+dnKADFF+ZicCB1avnSTvbllOKTQjU1efRodsJR0DTLC9qdruYZL5d9We9WfA1bZ32h4GXgOmJeuuaM8aSQcD9wK3tLQ1Iutc3q/nOOBzSc8A04C1wBuU5/2P+A8wtQ99Gzi2P5F0M7CNcnD1N+BokndX2F4GIGmkabRsk3lN7Vnbfg94r2o7HFgJXEqyrq3DzzXAnZSrWO+2tDUi65zp13MAsBC4AjgdmAtMp9yTGzEO+Hrvd23wSDoBuBw4hvIL+hXlkl3y7o3xdM52tPaoSdKPgQ3AA7b/SrLuOknnANNsP9S2qhFZp+jX81/gedsf294F/JlyEHBUyzY/ouWyUtSyCNhg+yPbn1Euvy0geffKDjpnO1p71CBpJmWw2SO276iak3X3XQzMlrSVMmjvVElP0JCsU/TrWQsskvQDSUPAucBTgCQdV7X9DFjXz04OkH8BCyVNlDQOOB/YTPLulY7ZVpeid0s6o9ruEpJ5LZImA+uBm2z/fqQ9WXef7cttz7J9ErAM2GJ7aVOyTtGvwfZm4HeUkaFvUu7J/YlyL+7pqm0b5UAgarK9Hngc+Cfwb8pAvttI3j1hezejZ/tzYLWkbcAkyn9VxPe3DDgSuF7S1up1e7UuWe89A5/1uOHh4bG3ioiIiP1ezvQjIiIaIkU/IiKiIVL0IyIiGiJFPyIioiFS9CMiIhoiRT8iIqIhUvQjoiNJCyS93oP3nSPpnl5+jYjoLEU/Iva22QzgRCYR+4M8nCciOpK0ALgbOBn4LXAWZXrjV4Frbe+UtJ0yB8LZlJkmH7V9c7X/KspkVJ8ALwJLgPnAP4ApwBrgkWr/TcBM4BBgue2Nvf8OI5onZ/oRMZZVwJfAKbZPpExC8puW9ZNszwfmATdIOlbSIsojfOcApwCTAWx/QJnDfKPty6r9pwKrq2eh30t5tHJE9ECKfkSMZTFwAfBqNTPZEuD4lvV/AbD9IfAR8EPgPOBJ2/+zPQz8cQ/v/041jwXAVuCILvc/IioH9LsDEbHPGwKus70OQNIkymX4EbtaPh+mzEP+ZfVxxFd7eP8vOuwfET2QM/2IGMtzwEpJB0kaD9wH3DnGPs8CP5U0pVq+glLQoRwQHNiTnkbEHqXoR8RY7gC2UwbwvUk5E79+TzvYfoFycPCypC2UgXufVqs3AdMlrelVhyOis4zej4iuk3QqMM/2XdXyL4G5tpf2t2cRzZZ7+hHRC28Bv5K0gnJZ/31gRX+7FBE504+IiGiI3NOPiIhoiBT9iIiIhkjRj4iIaIgU/YiIiIZI0Y+IiGiI/wOQYo65SJ1WegAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df = pd.read_csv(dataurl+'alligator.txt', sep='\\s+', header=0)\n", "result = analysis(df, 'weight', ['length'], printlvl=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Consider the above two plots where one is about skin cancer mortality, and the other is about the weight and length of alligators. What is your assessment?" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", " show answer\n", " " ], "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hide_answer()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It appears as if the relationship between latitude and skin cancer mortality is indeed linear, and therefore it would be best if we summarized the trend in the data using a linear function.\n", "\n", "However, for the dataset of alligators, a a curved function would more adequately describe the trend. The scatter plot gives us a pretty good indication that a linear model is inadequate in this case.\n", "\n", " $\\blacksquare$ " ] } ], "metadata": { "hide_input": false, "kernelspec": { "display_name": "Python 3", "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": "3.7.3" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", "width": "355px" }, "toc_section_display": true, "toc_window_display": true }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { "002db71f226f4f4dbc42859db8a7b90f": { "model_module": "@jupyter-widgets/base", 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\n", 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\n", 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\n", 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58pVkZ3d/Kj5WuRYW5uJw2MuAA3raLzlHMYiIiEhIKuwiIiIpJPHvYxcREUkSPp+fLzZW0lJWRabNz9hh+XGfflaFXUREJApWmOUsLF0XsH67O8/JnDivAqdT8SIi0i2fz8+aTVW8//lO1myqar/lUgKtMMtZsGR1QFEHqKptYsGS1awwy+MWi3rsIiISUqL0QBOdz+dnYem6HvdZVLqOw0qK4nJaXj12EREJkkg90ES3dkt10M+pq8raJtZuqY5LPCrsIiISINweqE7Lt6qu7yjqXk8TK5+5gpXPXIHX09TtfrGkwi4iIgESrQea6ApynVHdr79U2JPErbfeyJVXXtbt9pUr/8OMGUewY8f2uB1TRFJTovVAE934kQW483ou2oV5TsaPLOhxn2jR4Lkkcc011+Lzea0OQ0TSQKL1QBOd3W5jzswSFixZ3e0+F8wsidv97OqxJ4mBAwficuVbHYaIpIFE64EmgynGEObOnoh7YODPrTDPydzZE+N6F0FS9NgbG4OXee2PtiU+w9HTRP/dmTHjCC688BJeffWftLS08OCDDzN06HAeffQh/vWvpdTX1zFmzFh++MMfc9RRRwPg9Xp5+OEFlJa+SlVVJUOHDuPccy/gzDPPBlpPi+/YsZ0HH3wEgFWrPubBB+9j/fovGTVqFN/4xhkBMVx55WUMHTqMG274bXtb19f45JP/8qc/PcIXX3xGc3MzI0aM5MILL2HWrFMizllEUkei9UCTxRRjCBNGTOWYJ1sfX3v+oRx8wP6aeS6UthV1rPDf/67p0/Neeulv3H33/Xg8XoqLR3Pjjb+irGwDv/nNzRQVDeHdd9/iZz/7CbfddjfTp89gyZLFvPHGa9x0023t2++++3eMGTOOyZMPDXjt7du3MW/elZx66mlcf/1NlJWt5847b4sovoqKcubNm8vs2edw7bW/wOPxsHDhU9x++2+ZMuVICgsH9SlvEUkNbT3Qp5cGFvfCPCcX6D72bnUu4kax25IvP0lR2JPRySd/gwkTDgJg69YtlJa+ymOPPdXedv753+XLL9excOFTTJ8+g23btpGdPYBhw4YzaNBgvv3t8yguHk1xcXHQa7/00hIGDRrE//zPz3E4HIwaNZry8q+4//57w46vubmZSy65jAsu+B52e+sVme9972L++c+X2bJlswq7iAT1QOedM5lJJUPVU09wSVHYly9fGdXXi+RUfF+NGNFRkNeuNQG46qofBezj8XgYODAPgLPOOoe33nqD2bO/gWEcyFFHHc0JJ8zC7S4Meu0NG76kpMTA4XC0t02cOCmi+IYPH8Fpp32LF154jo0bN7Bly+b2OL1eDdITkVaBPdACFfUkkBSFvS/XuXuSkWHH44ltYXc6OwZQ+P2tx1qw4FFycnID9mvrLY8cWcyzz77Ixx//h48++oC3336Tp576E7/85Q2ceuo3g17f7w+cGCIjI/it7LqPx+Np//emTRv58Y8vYfz4CRx11FRmzDiOggI3l176/QgzFRGRRKJR8XEwZsxYAHbt2sWIESPb//vHP17iH/94CYDFi5/hzTdf48gjj+aKK67hqaeeZcqUI3nttX8FvV5JicGaNZ/T0tLS3vbFF58H7JOZmUl9fV1A29atW9r/vWTJYgoLC/n97//Ad77zfaZNm8Hu3bujlrOIiFhDhT0ODjhgLNOnH8vdd9/OO+/8m23btrJw4dP85S9PMmzYcAAqK3czf/6dvPPOv9m5cwfvv/8e69aZIU+xz559No2Njdx++2/ZuLGMd999myeeeDRgn0MOmbyv5996vMcff5gNG75s3z5kyH6Ul3/F8uXvsnPnDv7979e5557fAa3X30VEJDklxan4VPDb397OI48s4K67bqe2toZhw4bzs5/9itNOa71N7Qc/+BFer5d7772TqqpKCgsHMXv2OXzvexcHvdbgwUXcf/9D3H//vVxyyXfZb7/9+P73f9BemAHOP/87bN++jRtv/DU2G5xwwizOPXcOn366CoCzzz6fTZs2cvPNv6GlpYWRI0dy2WVX8Kc/PcLnn6/m6KOnx+cHIyIiUWXreh02xjZ4vb4xlZX1QRtaWprZvXsHgwYNJTMzK6ZBxOMae6JIl1zTIc+2v5GSknE0NnpTOt+MDDtudy5VVfUpnSckfq6NjQ3ttxwvX76yz2OeEj3P3oT7c2hsbOCiMw+hodnGC6+uJitrQNRiKCzMxeGwlwEH9LSfeuwiIiJRkFn5b4pWnM7r10KzByr81nyBUWEXERHpB0ftpxS+f0xAW1beMHJycvF447+0rQq7iIhIH9gbNzPonYlB7fUH30/u5Kugqh5QYRcREUlo9pZKBn1wEPaWyoD2+gN+TsPYX5GRYSe3m+fGQ8IV9jgP5hNJIvrbELHSgEwff5+7ixEfHBTQ3jjsu9QdtABsiTErX8IUdru9dXpUrTkuEprX2zpzYOtUwvo7EYkbn4fBn1/I+tt2BjQ3F36dPYctBnts7+SKVAIVdjt2u4O9exsYMCC6U8iKJDu/309DQz2ZmVlkZmYCmkRIJOb8fgaa15K9JXACME/OOKqn/ht/Rp5FgfUsYQq7zWZj4MACamp2U1eXSVbWAGwxOq3h89nwWjBS0Qrpkmvq5unH6/XQ0FBPc3MjhYVaKlMkHrLL5jPwyxsC2vz2HHbP+AS/M7H/DhOmsANkZ+fS0tJEXd0eoDpmx7Hb7fh8yTdBQl+kS66pnmdGRhb5+YODFhESkehybl+E67MfBbVXTl+JN3ecBRFFLqEKu81mIz9/EHl5BTFbOtThsJGfn8OePQ0p2sPrkC65pnqedrsdhyOh/lRFUk7m7tcoWDk7qL3qqNfx5B9hQUR9Z8mnRUZGb2vP2IHMmBzb4bAzYMAAmpv9MV+T3Wrpkmu65AmtuXb+f6pKlzwh8XPtHJfDYQ/j87vn10m0PB17Psb13rFB7bsmLsQxsnUtj0gLpdW5xn2ueL/fPyZW185FRCS6GhoaKCkpAWDdunXk5KTI4Oa6DfDS2KDmec8W8Nx/chI518SbK97n81NT0xDvw7ZzOOy4XNnU1DSmRe8uHXJNlzwhcXL1+fyYm6uormumYGAWRrEbuz16X9gTJc94SPRcGxo6Pq+rquppaupbZzBR8rQ1lZP/70nYvHUB7Y0lv6Zy2FU8d92hQGLm6nJlh3UWwJJT8Ymwso/X60uIOOIhXXJNlzzB2lxXmOUsLF1HVW1Te5s7z8mcmSVMMaI7WljvqfU6F6ZoxGhZnp463B9+nYx6M6C5ccQPqJtwL9hseBs7vsQkc66JdbFDRBLaCrOcBUtWBxR1gKraJhYsWc0Ks9yiyES64Wshf+Vsit4YFlDUmwafRMWJldQdOD9hZoyLFg21FZGw+Hx+Fpau63GfRaXrOKykKKqn5UX6xO9n4BfXkL3tyYBmz8CDqTqqFBype+uoCruIhGXtluqgnnpXlbVNrN1SzYRR7jhFJRIsZ8Md5K6/NaDNl1FA5TEr8WcNtiiq+FFhF5GwVNd3FHWvp4lVz88DYPLZ83FkOEPuJxJPA7Y9Rd7nVwa17z5mFb6cMRZEZA0VdhEJS0Gus/edIthPJFqyKv6P/P+eG9ReNfUtPK5DLYjIWirsIhKW8SMLcOc5ezwdX5jnZPzIgjhGJeksY89HuD88Mai9+vAXaRl0ggURJQaNiheRsNjtNubMLOlxnwtmlmjgnMSco34dRctcQUW9ZuIjVMyqSeuiDuqxi0gEphhDmDt7Ik8vXR3QXpjn5IIY3Mcu0pmt6SsGvX0wNn/gssV1JTfTOPoai6JKPCrsIhKRKcYQJoyYyjFPtj6ed85kJpUMVU9dYsbmqcX9/gwcjWUB7Q0jf0y9cUfK3YfeXyrsIhKxzkXcKC5QUZfY8DWTv/IssqreCmhuGnI6NZOeApvDosASmwq7iIgkFr+PvM8uZ8CORQHNLXmHUX3k/4Ej26LAkoMKu4iIJIycL28mt+yugDZfVhGV0z/Cn1loUVTJRYVdREQsN2DL4+StmRfUvnvGanzZxRZElLxU2EVExDJZ5a+Qv2pOUHvl0e/hzZtoQUTJT4VdRETiLqP6fdwfnRTUXj3lFVoKj7MgotShwi4iInFjr/2ConeODGqvOeRJmvY/y4KIUo8Ku4iIxJxt73ZYOJ78Lu11xu9oLL7CkphSlQq7iIjEjK1lD+73p+PYuyWgvWHU1dSX3KzJZWJAhV1ERKLP10TBf75J5p4PApqbh36bPQc/DjYtVRIrKuwiIhI9fh95n/6AAV+9ENDsKTiajJPfoL7GCx6fRcGlBxV2kQTj8/lZu6Wa6vomCnJbl0HVlK2S8Px+cr+8gZyN9wU0e53DqZq2HEd2IW7HAKDemvjSiAq7SAJZYZazsHRdwJrn7jwnc7RymiSw7M0PMdD8eVD77mPX4BswzIKI0psucogkiBVmOQuWrA4o6gBVtU0sWLKaFWa5RZGJhJb11RKKlrmCinrltA+pmFWjom4R9dhFEoDP52dh6boe91lUuo4jD9wvThGJdC+z8m0KVpwW1F51xKt43NMsiEg6U2EXSQBrt1QH9dS7qqxtwtxcxfRBA+MUlUigzPovKHrn60Hteyb/leYhp1sQkYSiwi6SAKrrO4q619PEqudbF8OYfPZ8HBnOjv3qmuMem4ixXwuvX1sBHwcW9doJ97B35KUWRSXdUWEXSQAFuc7edwIKBmbFOBKRDva92yl+ZwKvXxvYXj/mWhrG/caaoKRXKuwiCWD8yALcec4eT8cX5jkxit1xjErSla15F4P/fUBQe7P7OPZMeUmTyyQ4FXaRBGC325gzs4QFS1Z3u88FM0t0P7tF0mZuAV8TRa8VhdxUccJX4MiOc0DSFyrsIgliijGEubMn8vTSwOJemOfkAt3Hbpm0mFvA76eotOvyLK22Tv0Mp2tknAOS/lBhF0kgU4whTBgxlWOebH0875zJTCoZmpq9wyTQNrdAV21zC8ydPTHpi3vRMlfI9tl/GMSHZU6WLx8U54ikv3ShRCTBdC7iRnGKnvJNAuHOLeDz+eMUUXQVvn1wyKJec/BDbJ6xkw/LwhvQKYnHkh57RoZ13yccDnvA/1NZuuSaanl2zsPhsAf8vSRKrj3FGM3XtzLPLzZWhjW3wPrtezhwdGGfjxPvXPNLi7G3VAa17x1zNY0TbmuNpaEhIL5ovL+J8J72Jlq/11bnGvfCbrfbcLtz433YIC5X+gwCSZdcUyVPp7Ojh+5255KTkxO0j9W5hhNjNFiZZ0tZVfu/e5pboMUfnc+0mOf6znmw+bng9v2+Die+zgBgwL6mWL6/Vv/u9iTaeVuVa9wLu8/np6amofcdY8ThsONyZVNT04jXm9pLB6ZLrqmWZ0On3lJVVT1NTR2nehMl155ijIZEyDPTFl5OmTY/VVV9X7Es1rk6yx4gZ80vQm7bdnx5a/HqEn8s3t9EeE97E628Y5Wry5Ud1lkAS07FexJgLV6v15cQccRDuuSaKnl2/iDoLiercw0nxmgdx6o8xw7LD2tugbHD8qMSY7Rzzdz9GgUrZ4fcNvy61sVZli/v/vcrVnFZ/bvbk2jnbVWuiXuxQ0TEQm1zC/QkEecWsDesp2iZK2RRr5hZxeYZOy2ISuJJt7uJiHQjmeYWsHlqGfzG8JDbdn1tM/7MgjhHJFZRYRcR6UHCzy3g91FUGrpoV077CO9AI84BidVU2EVEepGocwt0N7nMnkOfpbno1DhHI4lChV1EJMkMeqMYu6c6qL1+7K9pOOA6CyKSRKLCLiKSJFwfn41z17+C2hvdJ1B3xIsWRCSJSKPiRUQSXM6XN1O0zBVU1Jd97mT4dcOoOHihRZFJIlKPXUQkQTl3LMa1+gdB7b7MQrZO/ZyLrjvcgqgk0amwi0hYOq9JPsCRmBOMpIqM6g9xfzQz5LaKWTWt/2i0bgZPSWwq7CLSq65rkns9PS+OIn1jb9zCoHcODrmtYuYesCXGaHxJbCrsItKj7tYkb/Px2gqmTx4Vx4hSUEsd7qV5ITdVnPAVOBJ34RRJPCrsItKtcNYkX/zGeo4+pDhh7u1OKn4v7qWh70XffdxafM794xyQpAIVdhHp1tot1b2vSV7XxNot1UwY5Y5TVGijKu8AACAASURBVKmhu8llqqa+jcc1Oc7RSCpRYReRblXXdxT1zmuSTzzzd93uJz0bXOrG5vcGtdcdvojGQadZEJGkGt3HLiLdKsh1RnW/dJb/n29QtMwVVNQbxt8Ec/y07He6RZFJqlGPXUS6NX5kQe9rkg90Mn6kVg7rTq75S3I2PxjUvne/s6id9CQZGXZyLIhLUpd67CLSrXDWJD/n62M1cC4E57a/ULTMFVTUvQOKqZhVQ+2kJ60JTFKeCruI9KhtTXL3wNCn2w8bXxTniBJbZtW7FC1z4fr8iqBtFbNqqDy2+1sHxVo+n7/93+bm6oDHyUSn4kWkV13XJL9q9iH8SGuOBLA3bGDQu4eG3KbJZRLfCrOcp5d2fOmav3gVg91lzJlZwhRjiIWRRU49dhEJS+fT7SW6pt7O1lJN0TJXyKJecWJF6xSwMSjqqdK7TARtkzBV1QWOJamqbWLBktWsMMstiqxvIuqxG4ZhA75pmubLhmEMA+4CKoDrTdOsi0WAIiIJyeeh6LXCkJt2Hb8Bf9bgmB06lXqXVgtnEqZFpes4rKQoacaSRNpjvwv4475//wEoBiYDD0QzKBGRRFa0zBWyqFdO+4CKWTUxL+qp1Lu0WliTMNW2TsKULCK9xn46cIxhGLnAqcBEoBz4MtqBiYgkmm13bYd3gqd53XPY8zQPPinmx0/F3qXVOk+u5Mhwcvj5f+h1v0QXaY+9yDTNjcDxwE7TNNcBtUBmtAMTEUkU+Zvuai3qXVSNuZmKWTVxKeqQmr1Lq6XiJEyR9tg3GIYxBzgPeHXfNfefAF9EPTIREYs5dzyLa/WlQe2LPszh2sUFLF9+KfFcdy0Ve5dWC2sSprzkmoQp0h77dcCdwATgRuBE4FfAT6Mblkh8+Hx+1myq4v3Pd7JmU5VGFgsAmZVvt96L3qWoN7uPY/OMnVy72JoP+VTsXVotnEmYLphZklSXNiLqsZum+QYwou2xYRiVwHDTNPdGOzCRWFthlrOwdF3AN3V3nlMji9OYo24NhcuPCmp/YWU2R15dRnZ2DjQ2WBBZq1TsXSaCtkmYun4eFOY5uSAJPw8inqDGMIzxwI+AkcCPgXPpGCkvkhTaRhZ31TayeO7siUn3xyx9Z2v6isFvBffamnMnMeaKCsDG8qvjH1dXbb3LUL+7bZKtd5kophhDOKykiLVbqqmub6Igt/ULUjL+LCM6FW8YxonAf2jttZ8CDARuMQzj2hjEJhIT4Y4s1mn5NOCpo2iZK6io+21ZVMysYudh/wICP9itnhimfYrfvMDT7YV5Tn0h7Se73caEUW6OPmh/JoxyJ2VRh8h77LcDc0zTfMUwjCrTNDcbhvENYBFwd/TDE4m+SEYWTxjljlNUElc9TC5TccIOcOSG3JYoE8OkUu9Soi/Swj4e+Me+f/sBTNP80DCM2M3GIBJlnUcMez1NrHp+HgCTz56PI8MZcj9JEX4/7uVHk1EffCPPruO+xO/svjh/vLaCx5aux+sJPTFMvHvLbb1Lka4iLeybganA+20NhmEcDmyJZlAisaSRxanN5/OH7MnmfXIRA776W9D+ldP/gzd3fK+v+9wb63vcrolhJFFEWtjvAP5hGMaDQJZhGP9D633sN0R00Azr1p5xOOwB/09l6ZJrpHkeNKaQwjwnlT2NLHY5OWhMoSUf0p3zcDjsAX8vVr6nXePq/O9o/033Nc+P1pTz11fNgPf2B6Of5cxBi4L2rZ36Kp7CY7DR/Qdh5+NX1TUFnNHpqrK2ifXb93Dg6NCn+LsT7/c0nPcuFu9vunwegfW5Rnq7218Nw6gF5gLbgNOA60zTfDbc17Dbbbjdoa9fxZPLFc9pJayVLrlGkuePzprE7X/+qPvtsycxaNDAaIQVMaez48uE251LTk5O0D5WvKed4yoo6IipuxijIZI83/tkOw88/0n745mDSrlm9IPBO05fBKPPJy+M1+ycc5ueJoZp8ff98y1e72k4v1/h7NNX6fJ5BNblGvHtbqZpvgS81NcD+nx+amqsuw/U4bDjcmVTU9OI1+uzLI54SJdc+5LngSPzuersSTz1yicB7YUuJ985yeDAkflUVdXHItxeNTR0/H1UVdXT1NQx6trK97RzXNXV3ccYDZHm6fP5efhvre/lmUNe5Acjnwza59ldFzPzO/e3noUJ873tnHM4Mm3+iH9v4v2e9vT7Fck+kUqXzyOIXa4uV3ZYZwHCKuyGYTzS2z6maV4WzmsBeDzWv6lery8h4oiHdMk10jwPGzeY8ZdO5ZgnWx/PO2cyk0qGYrfbLP15df4g6C4nK97TrnHFI5ZwX3vNpirG2t/hz1NuDdr2asUsHtw8F4BhZZURDTjrnKd7oJOaHqbiKsxzMnZYfp9/FvF6T8P9/YpVXOnyeQTW5Rpujz19zp1IWul8Dd0o1u1CychRu5pj107n2HHB205f8WLA40jvdOh8j/qMQ/bnnx/t7HZfTQwjiSKswm6a5vdiHYiISDjaRr031Gzj5J3TQ+7zrRUv4MMR1B7JnQ5d71l/efkmXANbr5/X7/W0tyfrtKOSuiK6xm4YRhatK7sNp2PWuizgENM0vx3l2EREAqwwy1n82mc8XvKtkNvP/XgRjb7QJxgjmUO9bcrhrvestxX0M2eMYUhhtiaGkYQU6eC5x4BvArtpXYO9gdaV3v4a5bhERAKsWPMVp2wp4ZQQC3H94NOHOfzQI2j0dT+lRrinysOZcvitVdu58/LpKuiSkCK9ye4bwDHAxcB7pmkeBPwvfRhdLyISrqJlLk7ZElzRr/3sJk5f8SLlzfvx4RflXH5m/+dQj2TKYZFEFGlBdpim+cW+KWQP3df2ANDzlEwiIn2Q//pY7E1fBbVfvaiAF1bmMPnsCTj2fYpV1jaRl53JXZdP79cc6p0H2PV0z7qmHJZEFWlh32oYxhjTNMsMw9jPMIwcwEfrKm8iIlGRu/IC+OrloFOKi3d8m6e2fw/Gw+EhZoGtrm/q9xzqmnI4eAW7SSXZuuyQRCIt7IuAtwzDOAr4J/AisBf4ONqBiUj6ydlwB7nrg+9Fr8o5lgvf/mmvz49GsR0/sgB3nrPH0/GRDMRLNomygp30XUTX2E3TvA34GVADXAlsAhqBS6Ifmoiki6yvllC0zBVU1P2OHCpm1dA87ZWga+ddRavY2u025swMMUKvk1S9Z73tboCqutAr2K0wyy2KTCIR8Qz1pmkuMk2z3jTNPcCdwNWmaeoau4hELGPPSoqWucj/5PvBG+f4qT6ptZDEu9hOMYYwd3b/B+Ilk3DuBlhUui7gNL0kpkjvY58KPGia5pGGYfwQeARoNgzjbNM0X4lJhCKScux7tzPo7Qkht1XMrCYjM4OuV8nbiu3C0nUBp8ljNUHMFGMIh5UU9WsgXjKJ5G4ArQOf2PqybOsywzBswPW0noKvAm4DVNhFpGfeeopeHxpyU8UJO8DR88po8S62/R2Il0x0N0DqiLSwHwh8HTCA/YFnTNPcaxjGX6IemYikDr+PotLQ1793H/sFvgHDw36pdCq28aS7AVJHpIXdB+QCpwAf7CvqxUBt1CMTkX5pm1Pd6tPIRctcIdurjnoTT/7hcY5GupPudwOkkkgL+4vAG8ABwDzDMA4E/gY8G+3ARKTvVpjlQdei3XnOuN6y1F1B3zPpzzTvNzsuMUj42gYoLliyutt9UvVugFQT6aj4q4CHaR0J/xTgBZ4Aer/BVETiov2WpVprblkqWuYKWdTrx/6q9dY1FfWElY53A6SiiHrspml6aF0Ipu3xWlpveRORBBDuLUuHlRRFveeVv+IMsirfDGpvLPgadUe+FNVjSeyk290AqUiLt0jCSJRrwsnMiluW8jfdQf6W+SG3Db9uGMuXP0PohVQlUWmAYnJTYZeEkAjXhFNB51uRvJ4mVj0/D4DJZ8/HkeEMuV9fnTKxkce/XwUhivrmGTuZNk0D40SsEPHMcyLRZvU14VQSj1uWjP1aMFaMaS3qXVTM3EPFrJo+v7aI9J967GIpK68Jp6JY3rJk89Sx7a7tIbeFM7mMiMRHWIXdMIwWoMcJgk3TzIpKRJJWNI1ldMXkliW/l6LS0D/73TM+wZc9OsIoRSSWwu2xnxLTKCRtxfOacLpou2Wp89Kb0Lc51bu7F716yiu0FB7XrzhFJDbCKuymab7W03bDMAqjE46kG01jGRtTjCFMGDGVY55sfTzvnMlMKhkadk+928llDn2W5qJToxSliMRCpKu7TaH1vvXhdAy8ywKGAvrklYhpGsvY6VzEjeLwbh0s+OgkMqvfD2qvK7mFxtFXRzU+EYmNSEfFLwAqgTeBMlonq3EAv4puWJIu4r3OtoSWu+ZnFC1zBRX1vfufS8WsGhV1kSQSaWGfBHwfuB+wmaZ5J3AecG60A5P00T6N5UBNYxlvA7Y+SdEyFzlb/hjQ7skZS8WsGmoPeaybZ4pIoor0drcq0zQbDMMoAw4GME3zPcMwxkY/NEkn/b0mLJHJrHyLghXfDLlN96GLJLdIC7tpGMYPTdN8zDCMRsMwJgFNtC7nKtIvfbkmLJGxN6xn0LuHhdxWMXMP2PQzF0l2kRb2G4C/G4bxBnAP8AEQsDCMiCQem6eaomX7h9xWceIusGsaCpFUEenqbm8bhjEC2Gua5kOGYawC8k3TXBqb8ESkO10XzRk3PJ8vt+1pfzxycBYZdj+b7tgB708Iev6u48vwZw2yIHIRiaVIb3f7yDTNI9sem6b53r72L03THBft4EQktI/WlPOXV82A2wRtNvC3zw/p5+Ups9l0R/BzK6d9hHegEZc4RST+ei3s+wbG/Xzfw0mGYTzSZZf8ff+Ff9AM69aecTjsAf9PZcmWa+c4HQ572L8n/cmzr8eMpZ5icjjsvPfJdh54/pOg57UV9ZennBnydWuP+DueohOxEftFIvr7c022393+iHeuVv3O6z2Nn17/vk3TXG8YRh1QBNggaGnlGuD8cA9ot9twu61fLMLlSp8VopMlV6ezY+CW251LTk5ORM/vS579PWYs9BST1+fnkRc/Dfm8+w/8CWNyNga1/6XiCi646kHy4jgYMVo/12T53Y2GeOWakdnx7+2VjRw+dDCOOP5u6D2NvXCnlP0fAMMw1pumeWN/Dujz+ampaejPS/SLw2HH5cqmpqYRrze1B/MnW64NDR2/F1VV9TQ19bjuULv+5NnXY8ZSTzGZW6rZvWdvwP5XFi/g5KJlQa+ztOJk/rD5cgAOWLWVA0fHb+bn/v5ck+13tz/imetHa8p56pWOsz03PPY+Re7P+c7JBkdOiO18EXpP+8/lyg7rLECkg+duNAzjUOASYDSwA3jSNM3lkbyOx2P9m+r1+hIijnhIllw7/wH0Jea+Pqe353cdpDZ+ZGxvxesppspORf2KkQ9w6pDgZRzWNxzAT764N6Btd83euP4O9Pe9jMZzk02sc11hlrNgyWq8nsDpmytrm3jg+U/iNhmU3tPYi3Tw3InAK8A/gbXAWOBNwzC+bZrmKzGIT8RSK8xyFpauCxik5s5zMifCVdKipWBgFicN/hdXjfpDyO2nr3gx9PO0iE5a8/n8LCxd1+M+i0rXcVhJkeaPSAGRjqG5BbjINM1n2xoMwzgfuJHWgi+SMtp6OF1V1TaxYMnquE93m1G1nOlfnMz0UcHbuivooEV0BNZuqe5xoSVo7bmv3VLNhFHuOEUlsRJpYZ8ALO7SthjoOlJeJKklUg/Hvncrg94+KOS22SsX4/FnhtzWRovoSHV9R1F3ZDg5/PzQZ3w67yfJK9LCXknrHPGdh+VOBMqjFpFIArCyh+PztQ40G5Dhp/id0LPFvVn8IX8q3Y3H39197K099QssumQgiSXcSzG6ZJMaIi3sjwMvGYZxC63Lto4Ffgn8scdniSSZzj0Xr6eJVc/PA2Dy2fNxZDhD7hcNK8xynl76Kdvu2h5ye830d3GNns7kqnruKvH2OPNcrAf5SfIYP7IAd56zxy+rumSTOiIt7L8DcoDfAkOATcDDwF1RjkvEUlb0cFaY5ZyyeRynHBy87c4NP2XS1y5nan5HD95utwWdLdD1UQnFbrcxZ2ZJyDEjbXTJJnWEVdgNwzjGNM13TdP0Adfv+08kZcW7h1P49kRO2bs5qP357afz5x0/AOCz0nUceeB+UTmepJ8pxhDmzp4YdJeHLtmknnB77EsBVywDEUkk8erh5H1yEQO++ltQ+2Nv53LDS/lMPvu7OPb9lVbWNmFurmL6oIH9OqakrynGEA4rKYrrvAwSf+EWdr3rknbaejhPLw0s7tHo4WSX3cvAL28Mal9dexC/WHsb5MDhISZqrq5r7vMxRSD0JRxJLeEWduvn2RSxwBRjCBNGTOWYJ1sfzztnMpNKhva5h5NV/gr5q+YEtfuxccaKJb0+v2Cg1k0XkZ6FW9hzDcPY0NMOpmkeEIV4RBJO5yJuFPfttGVGzSrcHxwbclvFrBp8Pj/ute/1ek3fKFZPS0R6Fm5hbwZuimUgIqnI3rSTQW+ND7mtYmYV2Byt+2nUsohESbiFvcU0zT/HNBKRVOJtpOj10CPYd319G/6MvKB2jVoWkWjQ4DmRaPL7KSrND7lp94zV+LKLe3y6Ri2LSH+FW9j/EtMoRFJA0bLQd4RWHbkMT8HUsF9Ho5ZFpD/CKuymaV4e60BEktWgN0djb6kMaq+Z+ChNQ8+zICIRSWeRTikrIvu4Pj4P566lQe31Y66lYdxvLIhIRESFXSRiOV/eQm7ZnUHtzYNmsufw4FnkRETiSYVdJExnTG4MuYyqL8PF7q9vtSAiEZFgKuwivXDu+aDbZVQrZtXEORoRkZ6psIt0w1FnUrj8yJDbKmZWg80e54hERHqnwi7Sha2lmsFvhr7fvOKEneDIiXNEycfn61hewtxczaSSbN2LLxInKuwibfzebu9Fn3HHEBa+/AnZKuq9WmGWB6yIN3/xKga7y5ij2fNE4kLnEkWAbXdtp/jd4UHt5Qc/w/DrhlG2S9+Bw7HCLGfBktVU1QUuZlNV28SCJatZYZZbFJlI+lBhl7RW/M7+IQfG1ZXcSsWsGva6vxb/oJKUz+dnYem6HvdZVLou4DS9iESfuiGSlvL/802yqt4Kam8aciY1k5+yIKLkt3ZLdY/LzgJU1jaxdku1pswViSEVdkkruWuvJ2fT/UHtvowCdn99swURpY7q+o6i7shwcvj5f+h1PxGJPhV2SQvO7X/F9Vnwkgde53Aqj/vCgohST0GuM6r7iUjfqLBL0vL5/KzdUk1tYwsjh+YzzD0gaJ/Mqvco+M8pIZ+/ecZOsrM1yj1axo8swJ3n7PF0fGFe6zK0IhI7KuySlFaY5SwsXRdQRArznFyw75Yqe0MZg96dHPK5w68bCthYvjxOwaYJu93GnJklLFiyutt9LphZovvZRWJMo+Il6bTfUtWlZ1hZ28QTf/+AomWukEW94oRyNs/YCaiwxMoUYwhzZ0/EnRd4ur0wz8nc2RN1H7tIHKjHLkmlu1uq7Hj5+5Rvh3zOruPX488q2veoIYbRCbQW98NKili7pZrq+iYKcltPv6unLhIflhT2jAzrThQ4HPaA/6eyZMu1c5wOhz3k78kXGyuDeuovTzkz5OvtmfEBvryDcUR4jEhjiqdkek8njh3U5+cmU579lS65pkueYH2ucS/sdrsNtzs33ocN4nJlWx1C3CRLrk5nR4/O7c4lJyd4YFtLWVX7v7sr6Detu56vnf4jji8e0adj9Gf/eEmW97S/0iVPSJ9c0yVPsC7XuBd2n89PTY11p0MdDjsuVzY1NY14vT7L4oiHZMu1oaHj96Kqqp6mpuAZyjJtfu6dcC0luV8GbXtsy8X8vfxbAMyy+amqqu/TMfqzf6wl23vaV+mSJ6RPrumSJ8QuV5crO6yzAJacivd4rH9TvV5fQsQRD8mSa+c/gFAxD/xiHtO3Pg5dTviU7jqB32+6uv1xYZ6TscPyQ+bc2zH6u3+8JFIssZQueUL65JoueYJ1uWrwnCS8AVseI2/N/wS1b24cydzPHwhq1y1VIpLOVNglYWXufoOCld8Kue3/ir/cNzq+033sLicXnKilQUUkvamwS8IZW+Sh+J39Q26rmLkHbDamQPstVZ1nntPKYSKS7lTYJWHYvPUhl1AFqDhxN9gzA9rsdhsTRrnJyLDjdudSVVWvwi4iaU+FXazn8zD4tUHYCC7Ku762EX9moQVBiYgkJxV2sY7fj/v96WTUfRa0qXL6Cry5JRYEJSKS3FTYxRJ5n1zMgK9eCGqvnPYR3oGGBRGJiKQGFXaJq5z1t5K74Y6g9uop/6SlcIYFEYmIpBYVdokL57a/4Pr8iqD2momP0zT0HAsiEhFJTSrsElOZu1+nYGXwnO51426gccxPLYhIRCS1qbBLTDhqV1P4/vSg9sZh36Xu4D9YEFGrzrfDmZurmVSSrVnqRCSlqLBLVNn3bmfQ2xOC2lvyj6T6qNcsiKjDCrOcp5eubn88f/EqBrvLmDNTs9WJSOpQYZeosHlqGPxG8DKpPkceu7++BWzWrsG8wixnwZLVeD2Ba7lX1TaxYMlq5s6eqOIuIilBhV36x9dC0WuDQm6qOOErcFi/9rLP5983r3z3FpWu47CSIp2WF5Gkp8IufeP34373MDIaNwRt2nV8Gf6s0MXeCmu3VFNV29TjPpW1TazdUs2EUe44RSUiEhsq7BIx5/a/4vrs8qD2GXcMYeHLn5CdlWNBVN2rru8o6o4MJ4efH3rwXuf9RESSlQq7hC137a/J2fT7oPZNxvNMP+NqCyIKT0GuM6r7iYgkMhV26dWALY+Tt2ZeUPu024ewuTKD11+fYkFU4Rs/sgB3nrPH0/GFeU7GjyyIY1QiIrFh7VBlSWhZFa9StMwVVNRvetnF8OuGsbkyOb4X2u025szseUGZC2aWaOCciKQEFXYJklHzX4qWucj/b+BUr40jfsjmGTt55K2BFkXWd1OMIcydPRF3XuDp9sI8p251E5GUkhxdLokLe+NmBr0zMai92X0ce454pfVBY0Oco4qeKcYQDispYu2WaqrrmyjIbT39rp66iKQSFXbB1lLN4DeLg9p9WUXsPm6d5ZPLRJPdbovoljZNQSsiyUaFPZ35mil6bXDITRUnVoA9vFHiqVr8NAWtiCSj1OmKSfj8fgrfmhCyqO/62kYqZtWEXdQBbnrio/Z/z1+8iuseeo8VZnlUQrVK2xS0VXWhp6BN9vxEJHWpsKcAn8/Pmk1VvP/5TtZsqgroQXeVv3I2RaX5OJq2B7TvnvEJFbNq8GcWRnz8qvrUKn7hTkHb089ZRMQqOhWf5FaY5SwsXRdwj7Y7z8mcmSVMPXj/9rbcNT8jZ8sfg55fddQbePJjcx96ss6/riloRSSZqbAnsbbTxV219ZjtDjsnFb6Me8U1QfvsOfRZmotOjfiYH6+tCHvfZC1+moJWRJKZCnuS6u108dH573NS2ZlQFtheO+Fu9o68rE/HXGGW8/DLnwe1p1rx0xS0IpLMVNiTVHeni8fnrOWeA38W1N5QfCX1xm19Pl44151DScbipyloRSSZqbAnqc49Ya+niarXr2L5L4IHq+3OPQH7cS/h8fj6dbxwrjt3lazFr20K2lCXOdpoCloRSVQaFZ+k2nrCeY4a/jn1vKCi/lXTEE5fsYTtBz8bleP15ZR6Mhc/TUErIslKPfYkNX7YAF6ecmbIbbNXLsbjz6TQ5eSgAwZRs6f/08BGckq9MM/JBSkwiYumoBWRZGRJYc/IsO5EgcNhD/h/0vH7yH9tFPaWqqBNp3/4V3Dktj++8JQJOOy2qOR60JhCCvOcVFT13HM/89gxnHnsAXEtfrF+TyeOHRST1+2LpP/9DVO65Anpk2u65AnW5xr3wm6323C7c3vfMcZcrmyrQ4jczlJ4fVZQ85G37Mf2PQ4mn52BAxhckM2l35rI9EnDgOjleunsQ7jtT+/2uM87n+7kojMOwWFBrzYp39M+Spdc0yVPSJ9c0yVPsC7XuBd2n89PTY11K4Q5HHZcrmxqahrxevs3oCxeHHs+JnvtjWTuei2gveaY96jNGMf26w4F4NJvHsR+g/Mxit3Y7TZqahqjmqvd1/tr7Kpu5INVWzlwdOQz2PVVMr6nfZUuuaZLnpA+uaZLnhC7XF2u7LDOAlhyKr6/I7Sjwev1JUQcPXHUryP3y5txlr8IgN+WycsfO5hfmsefX/yU7OwcvJ2WUZ1iFJGdnYPP5w+Y7jRaue6u2RvwePLZ83FkBF97312z15KfbTK8p9GSLrmmS56QPrmmS55gXa4aPJeA7Hu3krP+dwzY8Vdsfi9+bDQNPY/dw+dx+bWzLYtLE7eIiCQ+FfYEYmveTU7ZPWRvfRSbr3WQWlPRN6gf+2u8eQcH9M6tMH5kAe6BPRftZL13XUQkVaiwJwCbp5bsTQ+SvelB7N5aAJrdM6gfdwOegqkWR9fBbrdx7tfH8uaT3e+TzPeui4ikAhV2K3n3kr31cXLK7sbeshuAlrxDqR/3G1oGnQi2xCuQh40vCtmeKveui4gkOxV2K/g8DNixiJwNt+PYuxUAT8446sf9muYh3wJbctznOe+cyez12jVxi4hIAlFhjye/n6zyl8hdfzMZ9WsB8DqH0XDAL9g77DtgT663wyguIDs7x+owRESkk+SqJEksc/cb5H55E5k1KwHwZRbSMPqnNI78ITjSZ8IGERGJrZQo7D6fP2Hn885bfRkDdjzT/tjvyKVh1JU0jroKf4bLwshERCQVJX1hX2GWs7B0XcCSou48J3MsHsiVs+EOctffGtDW6D6B+kmP4s8KPQBNRESkv5JjlFY3VpjlLFiyOmid8KraJhYsWc0KM3h98lhz7niGomWuoKJ+9aICKg5eqKIuIiIxlbSF3efzs7B0XY/7LCpdFzC1aixlVr5F0TIXrtWXBbRXn0gD4gAAC1RJREFUF/+M4dcN44WVsRlk1jk/c3N13PIVEZHElLSn4tduqQ7qqXdVWdvE2i3VTBjljlkcjrovKFwePInM3qHnUzvxERobG4C/xOTYK8xynl66uv3x/MWrGOwus/wyhIiIWCdpC3t1fUdR93qaWPX8PCB4YZLO+0WTvWkng94aH9Te4jqM6qn/jskxO/t4bQWPLV2P1xP6MsTc2ROZevD+MY9DREQSS9IWdssWJPHUUfTGsKBmvz2bXSdsB5sjusfrpPNp9r8uW0dPV1IWla7jyAP3i1ksIiKSmJK2sI8fWYA7z9nj6fioLkji81D0Wug1xitO2AmO2E7U0vW0e93elpBLpraprG3C3FzF9EEDYxqXiIgklqQt7Ha7jTkzS1iwZHW3+0RlQRK/H/fyI9tniuts1/Hr4zLKvW30f9fT7gCODCeHn/+HkM+rrmuOdWgiIpJgknZUPMAUYwhzZ08MWkq0MM/J3NkT+z2AzLXqQopK84OKeuX0FVTMqolLUQ9n9H93CgZmRTkaERFJdEnbY28zxRjChBFTOebJ1sfzzpnMpJKh/eqp53z5W3LL7g5qrzriVTzuaX1+3b4IZ/R/KIV5Tozi2N0NICIiiSnpCzsQUMSN4r5PJztg65/J++KqoPaaQ56gaf9v9zm+/ug8qr+n0+5daV10EZH0lBKFvb8yd5VS8PFZQe11Jb+lcfRPLIioQ6Sj+mO9LnrXCXEmlWTrC4SISAJJ68LuqP2EwvdnBLU3Dr+YuoN+b0FEwcIZ/Z+Xk8l5J46jcOCAmC6AowlxREQSX1IPnuuz+i24lw4MKuotBdOomFWTMEUdOkb/9+TCkw2mHzyUCaPcMS3qC5aspqouceblFxGRYGlV2G0te3AvHQh/Lw5o92W6qZhZTfWRr1oUWc/aR//nxWb0f28SbV5+ERHpXnqcivc1U/Ta4JCbKk4oB8eAOAcUuSnGEA4rKbJk3flEmZdfRER6l9qF3e+n8J1DcOzdHLSp+sRNtNiTqwjZ7TZLCme4I/NjNS+/iIiEL2ULu+vjc3Hu+r+g9j3HfUL+iEPwV9WDx2dBZMnHsnn5RUQkYilX2As23IBr+8NB7VVHvYYn/0gyMtJqWEFUxH1efhER6bOUqXInHdzItru2BxX1PZP/SsWsGjz5R1oUWfILZ2S+JsQREUkMSV/YbU1f4f7yZzxxUVVAe51xBxWzamgecrpFkaUWq0fmi4hIeJL+VHz+x98ms/aT9scNI39M/YQ7LYwodVk5Ml9ERMKT1IW9sbGB519ez/j9nEw89xns+59odUgpz6qR+SIiEp6kLuwAt/wjH4Dll04j2+JYRERErGZJYY/WyHSHwx7w73Bet+05nZ8bS32JMdrHjleuVkmXPCF9ck2XPCF9ck2XPMH6XONe2O12G253blRey+nsuLbrdueSk5MT9nNdrvj07/sTY7TEK1erpUuekD65pkuekD65pkueYF2ucS/sPp+fmpqGqLxWQ0PH61RV1dPU1Ptc5Q6HHZcrm5qaRrze2E9Q05cYoyXeuVolXfKE9Mk1XfKE9Mk1XfKE2OXqcmWHdRbAklPxnijN+Nb5B+b1+iJ63Uj376uWFm/7vz8vq2RSiTPuo8jjlavV0iVPSJ9c0yVPSJ9c0yVPsC7XpB88l8i0frmIiMRb6o9isIjWLxcRESuosMeA1i8XERGrJHVh71wYzc3VCVMoI1m/XEREJJqS9hp7Il+/1vrlIiJilaTssSf69WutXy4iIlZJusKeDNev29Yv74nWLxcRkVhIusKeDNevtX65iIhYJemusSfL9eu29csXlq4L+CJSmOfkggQYByAiIqkp6Qp7Ml2/1vrlIiISb0lX2NuuX/d0Oj6Rrl9r/XIREYmnpLvGruvXIiIi3Uu6wg4d16+7jjwvzHMyd/ZEXb8WEZG0lXSn4tvo+rWIiEiwpC3soOvXIiIiXSXlqXgREREJTYVdREQkhaiwi4iIpBAVdhERkRSiwi4iIpJCVNhFRERSiM3vj+vypo1+v3+AlUuqAjgcdrxen6UxxEu65JoueUL65JoueUL65JoueUJscrXbbdhstr1Adk/7xbuwVwNOYEc8DyoiIpIChgJNQI+LocS7sIuIiEgM6Rq7iIhIClFhFxERSSEq7CIiIilEhV1ERCSFqLCLxJlhGOOsjkFEUldSL9sqEk+GYfwR+O6+hxlAFtDQaZdTTdN8u5fXmA/kAT8M43gzgf8zTTMqf6eGYZjAb0zTfDaMfb8OPAXkA9eapvlIOHHu+9KyDhhpmubWbvYfu++1jwd+ARxlmubpEScU+Jrv7Ivhlm62/x/wK9M0V/TnOCLJQIVdJEymaf4Y+DGAYRgXATeapjk6wpcpAvZGN7LwmKZpRLD7hcCHpml+OwahPA1cb5qmB7g5Bq8fyk+B5wzDONQ0zZY4HVPEEirsIlFkGIYD+DmtPfJBwBpae4qlhmHcBJy3b7/DTNOcYhjGscBvAQMoBD4B5pqm+VEvx5kJPAa8D5wC3AI8CtxLa094KFAFPGCa5h37nrMV+F/TNP+yr4f77337HgpsBn5tmuYLhmEsAb657zl1tPbap/clzhBxfwvIM03z9X2PbwGONk1zpmEYPwS+t++1LwC8wN+BK0zT9BiGkQncAFwEuICPgStN0/x038uXGIaxDDgS2A1cZ5rm3wBM0/zMMIztwMVAt2cfRFKBrrGLRNdNwI+As2gt7POBVwzDONw0zRuAZ4E/7yvqucBLwDPACGAwrQX2zjCPNYrWIlgEPAzcte91pgADae2l3m4Yxuhunn8ZMJfWQv134BHDMLJM05zdKc6BwIB+xtnZFcDCHrYfB2wF9ge+ReuljzP3bbsBOBeYCbiBd4GXDcNo+xw7GbhuXz5/AZ4wDKNz52XRvuOLpDQVdpHougS41TTN/5qm6TFN8xngn/vau9pL6/Xlh2ktnqNo7WkOj+B4j5um2WKaZi3wa1p7urXAyH2vbwOGdfPcZ03TXGWaZjOt17wLaS3asYiTfUX2OOC9HnarM03zjn0/u/eBT4Hx+7Z9H/idaZprTNP00noG4Xw6PscW7fu5+2j9YuLqks97wGTDMAZFErdIstGpeJHoGgJs6NJWRusp7ACmaXoNw5i5b2BXDvAZ4CP8L9xe0zS/6vR4P+A+4LB9MbQNFOvu9XZ2+nfbdeegfaMQZ5siWr8YbOthn6+6PG7pdJz9gU2d4tpL66UIDMOA1i8bbZr3/b/zZ1zbYL6RXfYVSSnqsYtE1yZgbJe2sYRY+MgwjOm0nqo/2zTNoaZpzgRe68exXwCWA0WmaU6htQffb1GMs22pq75+7mwFijvFlWUYxnzDMPYL8/ltRd7bx+OLJAX12EWi6zHgl4ZhfACshv9v7w59KQrDOI5/k6rZ8Ac8CVW45QZJEWT+As0oCkW4TRJsRFET7rRbTNNegaCZjQkodoX3YDMbzq5j9933E8/ZPc970m/PfZ9zDovAPNCuzj+Th9Egf6HpBXiC9wBd4SMAf2u0utZLRIwBO9XxkZrXezOodd6Q738SuKixjn1gvRr8uwI2yPvwqz/8/QTQB65r1JaGhh27NFgdYJfcPd8Da+ROt1edPwTaEXEJHJMn2XsRcUcO4h1gPCK+2uv+zjJ52OwBOCOH3zkwVf92YFDrTCn1gS7QqrmObfLeeRe4BWbJ7w74aQfeAk5TSvc160tDwc+2SmpMRCwAWyml6X+ofUIesNtrurbUJDt2SY1JKR0BjxEx12TdiJghbwEcNFlX+g8Gu6SmLQGbn54x/2sdYKl6251UNP+KlySpIHbskiQVxGCXJKkgBrskSQUx2CVJKojBLklSQQx2SZIKYrBLklQQg12SpIK8AiGqZmdXbs+LAAAAAElFTkSuQmCC\n", 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58pVkZ3d/Kj5WuRYW5uJw2MuAA3raLzlHMYiIiEhIKuwiIiIpJPHvYxcREUkSPp+fLzZW0lJWRabNz9hh+XGfflaFXUREJApWmOUsLF0XsH67O8/JnDivAqdT8SIi0i2fz8+aTVW8//lO1myqar/lUgKtMMtZsGR1QFEHqKptYsGS1awwy+MWi3rsIiISUqL0QBOdz+dnYem6HvdZVLqOw0qK4nJaXj12EREJkkg90ES3dkt10M+pq8raJtZuqY5LPCrsIiISINweqE7Lt6qu7yjqXk8TK5+5gpXPXIHX09TtfrGkwi4iIgESrQea6ApynVHdr79U2JPErbfeyJVXXtbt9pUr/8OMGUewY8f2uB1TRFJTovVAE934kQW483ou2oV5TsaPLOhxn2jR4Lkkcc011+Lzea0OQ0TSQKL1QBOd3W5jzswSFixZ3e0+F8wsidv97OqxJ4mBAwficuVbHYaIpIFE64EmgynGEObOnoh7YODPrTDPydzZE+N6F0FS9NgbG4OXee2PtiU+w9HTRP/dmTHjCC688BJeffWftLS08OCDDzN06HAeffQh/vWvpdTX1zFmzFh++MMfc9RRRwPg9Xp5+OEFlJa+SlVVJUOHDuPccy/gzDPPBlpPi+/YsZ0HH3wEgFWrPubBB+9j/fovGTVqFN/4xhkBMVx55WUMHTqMG274bXtb19f45JP/8qc/PcIXX3xGc3MzI0aM5MILL2HWrFMizllEUkei9UCTxRRjCBNGTOWYJ1sfX3v+oRx8wP6aeS6UthV1rPDf/67p0/Neeulv3H33/Xg8XoqLR3Pjjb+irGwDv/nNzRQVDeHdd9/iZz/7CbfddjfTp89gyZLFvPHGa9x0023t2++++3eMGTOOyZMPDXjt7du3MW/elZx66mlcf/1NlJWt5847b4sovoqKcubNm8vs2edw7bW/wOPxsHDhU9x++2+ZMuVICgsH9SlvEUkNbT3Qp5cGFvfCPCcX6D72bnUu4kax25IvP0lR2JPRySd/gwkTDgJg69YtlJa+ymOPPdXedv753+XLL9excOFTTJ8+g23btpGdPYBhw4YzaNBgvv3t8yguHk1xcXHQa7/00hIGDRrE//zPz3E4HIwaNZry8q+4//57w46vubmZSy65jAsu+B52e+sVme9972L++c+X2bJlswq7iAT1QOedM5lJJUPVU09wSVHYly9fGdXXi+RUfF+NGNFRkNeuNQG46qofBezj8XgYODAPgLPOOoe33nqD2bO/gWEcyFFHHc0JJ8zC7S4Meu0NG76kpMTA4XC0t02cOCmi+IYPH8Fpp32LF154jo0bN7Bly+b2OL1eDdITkVaBPdACFfUkkBSFvS/XuXuSkWHH44ltYXc6OwZQ+P2tx1qw4FFycnID9mvrLY8cWcyzz77Ixx//h48++oC3336Tp576E7/85Q2ceuo3g17f7w+cGCIjI/it7LqPx+Np//emTRv58Y8vYfz4CRx11FRmzDiOggI3l176/QgzFRGRRKJR8XEwZsxYAHbt2sWIESPb//vHP17iH/94CYDFi5/hzTdf48gjj+aKK67hqaeeZcqUI3nttX8FvV5JicGaNZ/T0tLS3vbFF58H7JOZmUl9fV1A29atW9r/vWTJYgoLC/n97//Ad77zfaZNm8Hu3bujlrOIiFhDhT0ODjhgLNOnH8vdd9/OO+/8m23btrJw4dP85S9PMmzYcAAqK3czf/6dvPPOv9m5cwfvv/8e69aZIU+xz559No2Njdx++2/ZuLGMd999myeeeDRgn0MOmbyv5996vMcff5gNG75s3z5kyH6Ul3/F8uXvsnPnDv7979e5557fAa3X30VEJDklxan4VPDb397OI48s4K67bqe2toZhw4bzs5/9itNOa71N7Qc/+BFer5d7772TqqpKCgsHMXv2OXzvexcHvdbgwUXcf/9D3H//vVxyyXfZb7/9+P73f9BemAHOP/87bN++jRtv/DU2G5xwwizOPXcOn366CoCzzz6fTZs2cvPNv6GlpYWRI0dy2WVX8Kc/PcLnn6/m6KOnx+cHIyIiUWXreh02xjZ4vb4xlZX1QRtaWprZvXsHgwYNJTMzK6ZBxOMae6JIl1zTIc+2v5GSknE0NnpTOt+MDDtudy5VVfUpnSckfq6NjQ3ttxwvX76yz2OeEj3P3oT7c2hsbOCiMw+hodnGC6+uJitrQNRiKCzMxeGwlwEH9LSfeuwiIiJRkFn5b4pWnM7r10KzByr81nyBUWEXERHpB0ftpxS+f0xAW1beMHJycvF447+0rQq7iIhIH9gbNzPonYlB7fUH30/u5Kugqh5QYRcREUlo9pZKBn1wEPaWyoD2+gN+TsPYX5GRYSe3m+fGQ8IV9jgP5hNJIvrbELHSgEwff5+7ixEfHBTQ3jjsu9QdtABsiTErX8IUdru9dXpUrTkuEprX2zpzYOtUwvo7EYkbn4fBn1/I+tt2BjQ3F36dPYctBnts7+SKVAIVdjt2u4O9exsYMCC6U8iKJDu/309DQz2ZmVlkZmYCmkRIJOb8fgaa15K9JXACME/OOKqn/ht/Rp5FgfUsYQq7zWZj4MACamp2U1eXSVbWAGwxOq3h89nwWjBS0Qrpkmvq5unH6/XQ0FBPc3MjhYVaKlMkHrLL5jPwyxsC2vz2HHbP+AS/M7H/DhOmsANkZ+fS0tJEXd0eoDpmx7Hb7fh8yTdBQl+kS66pnmdGRhb5+YODFhESkehybl+E67MfBbVXTl+JN3ecBRFFLqEKu81mIz9/EHl5BTFbOtThsJGfn8OePQ0p2sPrkC65pnqedrsdhyOh/lRFUk7m7tcoWDk7qL3qqNfx5B9hQUR9Z8mnRUZGb2vP2IHMmBzb4bAzYMAAmpv9MV+T3Wrpkmu65AmtuXb+f6pKlzwh8XPtHJfDYQ/j87vn10m0PB17Psb13rFB7bsmLsQxsnUtj0gLpdW5xn2ueL/fPyZW185FRCS6GhoaKCkpAWDdunXk5KTI4Oa6DfDS2KDmec8W8Nx/chI518SbK97n81NT0xDvw7ZzOOy4XNnU1DSmRe8uHXJNlzwhcXL1+fyYm6uormumYGAWRrEbuz16X9gTJc94SPRcGxo6Pq+rquppaupbZzBR8rQ1lZP/70nYvHUB7Y0lv6Zy2FU8d92hQGLm6nJlh3UWwJJT8Ymwso/X60uIOOIhXXJNlzzB2lxXmOUsLF1HVW1Te5s7z8mcmSVMMaI7WljvqfU6F6ZoxGhZnp463B9+nYx6M6C5ccQPqJtwL9hseBs7vsQkc66JdbFDRBLaCrOcBUtWBxR1gKraJhYsWc0Ks9yiyES64Wshf+Vsit4YFlDUmwafRMWJldQdOD9hZoyLFg21FZGw+Hx+Fpau63GfRaXrOKykKKqn5UX6xO9n4BfXkL3tyYBmz8CDqTqqFBype+uoCruIhGXtluqgnnpXlbVNrN1SzYRR7jhFJRIsZ8Md5K6/NaDNl1FA5TEr8WcNtiiq+FFhF5GwVNd3FHWvp4lVz88DYPLZ83FkOEPuJxJPA7Y9Rd7nVwa17z5mFb6cMRZEZA0VdhEJS0Gus/edIthPJFqyKv6P/P+eG9ReNfUtPK5DLYjIWirsIhKW8SMLcOc5ezwdX5jnZPzIgjhGJeksY89HuD88Mai9+vAXaRl0ggURJQaNiheRsNjtNubMLOlxnwtmlmjgnMSco34dRctcQUW9ZuIjVMyqSeuiDuqxi0gEphhDmDt7Ik8vXR3QXpjn5IIY3Mcu0pmt6SsGvX0wNn/gssV1JTfTOPoai6JKPCrsIhKRKcYQJoyYyjFPtj6ed85kJpUMVU9dYsbmqcX9/gwcjWUB7Q0jf0y9cUfK3YfeXyrsIhKxzkXcKC5QUZfY8DWTv/IssqreCmhuGnI6NZOeApvDosASmwq7iIgkFr+PvM8uZ8CORQHNLXmHUX3k/4Ej26LAkoMKu4iIJIycL28mt+yugDZfVhGV0z/Cn1loUVTJRYVdREQsN2DL4+StmRfUvnvGanzZxRZElLxU2EVExDJZ5a+Qv2pOUHvl0e/hzZtoQUTJT4VdRETiLqP6fdwfnRTUXj3lFVoKj7MgotShwi4iInFjr/2ConeODGqvOeRJmvY/y4KIUo8Ku4iIxJxt73ZYOJ78Lu11xu9oLL7CkphSlQq7iIjEjK1lD+73p+PYuyWgvWHU1dSX3KzJZWJAhV1ERKLP10TBf75J5p4PApqbh36bPQc/DjYtVRIrKuwiIhI9fh95n/6AAV+9ENDsKTiajJPfoL7GCx6fRcGlBxV2kQTj8/lZu6Wa6vomCnJbl0HVlK2S8Px+cr+8gZyN9wU0e53DqZq2HEd2IW7HAKDemvjSiAq7SAJZYZazsHRdwJrn7jwnc7RymiSw7M0PMdD8eVD77mPX4BswzIKI0psucogkiBVmOQuWrA4o6gBVtU0sWLKaFWa5RZGJhJb11RKKlrmCinrltA+pmFWjom4R9dhFEoDP52dh6boe91lUuo4jD9wvThGJdC+z8m0KVpwW1F51xKt43NMsiEg6U2EXSQBrt1QH9dS7qqxtwtxcxfRBA+MUlUigzPovKHrn60Hteyb/leYhp1sQkYSiwi6SAKrrO4q619PEqudbF8OYfPZ8HBnOjv3qmuMem4ixXwuvX1sBHwcW9doJ97B35KUWRSXdUWEXSQAFuc7edwIKBmbFOBKRDva92yl+ZwKvXxvYXj/mWhrG/caaoKRXKuwiCWD8yALcec4eT8cX5jkxit1xjErSla15F4P/fUBQe7P7OPZMeUmTyyQ4FXaRBGC325gzs4QFS1Z3u88FM0t0P7tF0mZuAV8TRa8VhdxUccJX4MiOc0DSFyrsIgliijGEubMn8vTSwOJemOfkAt3Hbpm0mFvA76eotOvyLK22Tv0Mp2tknAOS/lBhF0kgU4whTBgxlWOebH0875zJTCoZmpq9wyTQNrdAV21zC8ydPTHpi3vRMlfI9tl/GMSHZU6WLx8U54ikv3ShRCTBdC7iRnGKnvJNAuHOLeDz+eMUUXQVvn1wyKJec/BDbJ6xkw/LwhvQKYnHkh57RoZ13yccDnvA/1NZuuSaanl2zsPhsAf8vSRKrj3FGM3XtzLPLzZWhjW3wPrtezhwdGGfjxPvXPNLi7G3VAa17x1zNY0TbmuNpaEhIL5ovL+J8J72Jlq/11bnGvfCbrfbcLtz433YIC5X+gwCSZdcUyVPp7Ojh+5255KTkxO0j9W5hhNjNFiZZ0tZVfu/e5pboMUfnc+0mOf6znmw+bng9v2+Die+zgBgwL6mWL6/Vv/u9iTaeVuVa9wLu8/np6amofcdY8ThsONyZVNT04jXm9pLB6ZLrqmWZ0On3lJVVT1NTR2nehMl155ijIZEyDPTFl5OmTY/VVV9X7Es1rk6yx4gZ80vQm7bdnx5a/HqEn8s3t9EeE97E628Y5Wry5Ud1lkAS07FexJgLV6v15cQccRDuuSaKnl2/iDoLiercw0nxmgdx6o8xw7LD2tugbHD8qMSY7Rzzdz9GgUrZ4fcNvy61sVZli/v/vcrVnFZ/bvbk2jnbVWuiXuxQ0TEQm1zC/QkEecWsDesp2iZK2RRr5hZxeYZOy2ISuJJt7uJiHQjmeYWsHlqGfzG8JDbdn1tM/7MgjhHJFZRYRcR6UHCzy3g91FUGrpoV077CO9AI84BidVU2EVEepGocwt0N7nMnkOfpbno1DhHI4lChV1EJMkMeqMYu6c6qL1+7K9pOOA6CyKSRKLCLiKSJFwfn41z17+C2hvdJ1B3xIsWRCSJSKPiRUQSXM6XN1O0zBVU1Jd97mT4dcOoOHihRZFJIlKPXUQkQTl3LMa1+gdB7b7MQrZO/ZyLrjvcgqgk0amwi0hYOq9JPsCRmBOMpIqM6g9xfzQz5LaKWTWt/2i0bgZPSWwq7CLSq65rkns9PS+OIn1jb9zCoHcODrmtYuYesCXGaHxJbCrsItKj7tYkb/Px2gqmTx4Vx4hSUEsd7qV5ITdVnPAVOBJ34RRJPCrsItKtcNYkX/zGeo4+pDhh7u1OKn4v7qWh70XffdxafM794xyQpAIVdhHp1tot1b2vSV7XxNot1UwY5Y5TVGijKu8AACAASURBVKmhu8llqqa+jcc1Oc7RSCpRYReRblXXdxT1zmuSTzzzd93uJz0bXOrG5vcGtdcdvojGQadZEJGkGt3HLiLdKsh1RnW/dJb/n29QtMwVVNQbxt8Ec/y07He6RZFJqlGPXUS6NX5kQe9rkg90Mn6kVg7rTq75S3I2PxjUvne/s6id9CQZGXZyLIhLUpd67CLSrXDWJD/n62M1cC4E57a/ULTMFVTUvQOKqZhVQ+2kJ60JTFKeCruI9KhtTXL3wNCn2w8bXxTniBJbZtW7FC1z4fr8iqBtFbNqqDy2+1sHxVo+n7/93+bm6oDHyUSn4kWkV13XJL9q9iH8SGuOBLA3bGDQu4eG3KbJZRLfCrOcp5d2fOmav3gVg91lzJlZwhRjiIWRRU49dhEJS+fT7SW6pt7O1lJN0TJXyKJecWJF6xSwMSjqqdK7TARtkzBV1QWOJamqbWLBktWsMMstiqxvIuqxG4ZhA75pmubLhmEMA+4CKoDrTdOsi0WAIiIJyeeh6LXCkJt2Hb8Bf9bgmB06lXqXVgtnEqZFpes4rKQoacaSRNpjvwv4475//wEoBiYDD0QzKBGRRFa0zBWyqFdO+4CKWTUxL+qp1Lu0WliTMNW2TsKULCK9xn46cIxhGLnAqcBEoBz4MtqBiYgkmm13bYd3gqd53XPY8zQPPinmx0/F3qXVOk+u5Mhwcvj5f+h1v0QXaY+9yDTNjcDxwE7TNNcBtUBmtAMTEUkU+Zvuai3qXVSNuZmKWTVxKeqQmr1Lq6XiJEyR9tg3GIYxBzgPeHXfNfefAF9EPTIREYs5dzyLa/WlQe2LPszh2sUFLF9+KfFcdy0Ve5dWC2sSprzkmoQp0h77dcCdwATgRuBE4FfAT6Mblkh8+Hx+1myq4v3Pd7JmU5VGFgsAmZVvt96L3qWoN7uPY/OMnVy72JoP+VTsXVotnEmYLphZklSXNiLqsZum+QYwou2xYRiVwHDTNPdGOzCRWFthlrOwdF3AN3V3nlMji9OYo24NhcuPCmp/YWU2R15dRnZ2DjQ2WBBZq1TsXSaCtkmYun4eFOY5uSAJPw8inqDGMIzxwI+AkcCPgXPpGCkvkhTaRhZ31TayeO7siUn3xyx9Z2v6isFvBffamnMnMeaKCsDG8qvjH1dXbb3LUL+7bZKtd5kophhDOKykiLVbqqmub6Igt/ULUjL+LCM6FW8YxonAf2jttZ8CDARuMQzj2hjEJhIT4Y4s1mn5NOCpo2iZK6io+21ZVMysYudh/wICP9itnhimfYrfvMDT7YV5Tn0h7Se73caEUW6OPmh/JoxyJ2VRh8h77LcDc0zTfMUwjCrTNDcbhvENYBFwd/TDE4m+SEYWTxjljlNUElc9TC5TccIOcOSG3JYoE8OkUu9Soi/Swj4e+Me+f/sBTNP80DCM2M3GIBJlnUcMez1NrHp+HgCTz56PI8MZcj9JEX4/7uVHk1EffCPPruO+xO/svjh/vLaCx5aux+sJPTFMvHvLbb1Lka4iLeybganA+20NhmEcDmyJZlAisaSRxanN5/OH7MnmfXIRA776W9D+ldP/gzd3fK+v+9wb63vcrolhJFFEWtjvAP5hGMaDQJZhGP9D633sN0R00Azr1p5xOOwB/09l6ZJrpHkeNKaQwjwnlT2NLHY5OWhMoSUf0p3zcDjsAX8vVr6nXePq/O9o/033Nc+P1pTz11fNgPf2B6Of5cxBi4L2rZ36Kp7CY7DR/Qdh5+NX1TUFnNHpqrK2ifXb93Dg6NCn+LsT7/c0nPcuFu9vunwegfW5Rnq7218Nw6gF5gLbgNOA60zTfDbc17Dbbbjdoa9fxZPLFc9pJayVLrlGkuePzprE7X/+qPvtsycxaNDAaIQVMaez48uE251LTk5O0D5WvKed4yoo6IipuxijIZI83/tkOw88/0n745mDSrlm9IPBO05fBKPPJy+M1+ycc5ueJoZp8ff98y1e72k4v1/h7NNX6fJ5BNblGvHtbqZpvgS81NcD+nx+amqsuw/U4bDjcmVTU9OI1+uzLI54SJdc+5LngSPzuersSTz1yicB7YUuJ985yeDAkflUVdXHItxeNTR0/H1UVdXT1NQx6trK97RzXNXV3ccYDZHm6fP5efhvre/lmUNe5Acjnwza59ldFzPzO/e3noUJ873tnHM4Mm3+iH9v4v2e9vT7Fck+kUqXzyOIXa4uV3ZYZwHCKuyGYTzS2z6maV4WzmsBeDzWv6lery8h4oiHdMk10jwPGzeY8ZdO5ZgnWx/PO2cyk0qGYrfbLP15df4g6C4nK97TrnHFI5ZwX3vNpirG2t/hz1NuDdr2asUsHtw8F4BhZZURDTjrnKd7oJOaHqbiKsxzMnZYfp9/FvF6T8P9/YpVXOnyeQTW5Rpujz19zp1IWul8Dd0o1u1CychRu5pj107n2HHB205f8WLA40jvdOh8j/qMQ/bnnx/t7HZfTQwjiSKswm6a5vdiHYiISDjaRr031Gzj5J3TQ+7zrRUv4MMR1B7JnQ5d71l/efkmXANbr5/X7/W0tyfrtKOSuiK6xm4YRhatK7sNp2PWuizgENM0vx3l2EREAqwwy1n82mc8XvKtkNvP/XgRjb7QJxgjmUO9bcrhrvestxX0M2eMYUhhtiaGkYQU6eC5x4BvArtpXYO9gdaV3v4a5bhERAKsWPMVp2wp4ZQQC3H94NOHOfzQI2j0dT+lRrinysOZcvitVdu58/LpKuiSkCK9ye4bwDHAxcB7pmkeBPwvfRhdLyISrqJlLk7ZElzRr/3sJk5f8SLlzfvx4RflXH5m/+dQj2TKYZFEFGlBdpim+cW+KWQP3df2ANDzlEwiIn2Q//pY7E1fBbVfvaiAF1bmMPnsCTj2fYpV1jaRl53JXZdP79cc6p0H2PV0z7qmHJZEFWlh32oYxhjTNMsMw9jPMIwcwEfrKm8iIlGRu/IC+OrloFOKi3d8m6e2fw/Gw+EhZoGtrm/q9xzqmnI4eAW7SSXZuuyQRCIt7IuAtwzDOAr4J/AisBf4ONqBiUj6ydlwB7nrg+9Fr8o5lgvf/mmvz49GsR0/sgB3nrPH0/GRDMRLNomygp30XUTX2E3TvA34GVADXAlsAhqBS6Ifmoiki6yvllC0zBVU1P2OHCpm1dA87ZWga+ddRavY2u025swMMUKvk1S9Z73tboCqutAr2K0wyy2KTCIR8Qz1pmkuMk2z3jTNPcCdwNWmaeoau4hELGPPSoqWucj/5PvBG+f4qT6ptZDEu9hOMYYwd3b/B+Ilk3DuBlhUui7gNL0kpkjvY58KPGia5pGGYfwQeARoNgzjbNM0X4lJhCKScux7tzPo7Qkht1XMrCYjM4OuV8nbiu3C0nUBp8ljNUHMFGMIh5UU9WsgXjKJ5G4ArQOf2PqybOsywzBswPW0noKvAm4DVNhFpGfeeopeHxpyU8UJO8DR88po8S62/R2Il0x0N0DqiLSwHwh8HTCA/YFnTNPcaxjGX6IemYikDr+PotLQ1793H/sFvgHDw36pdCq28aS7AVJHpIXdB+QCpwAf7CvqxUBt1CMTkX5pm1Pd6tPIRctcIdurjnoTT/7hcY5GupPudwOkkkgL+4vAG8ABwDzDMA4E/gY8G+3ARKTvVpjlQdei3XnOuN6y1F1B3zPpzzTvNzsuMUj42gYoLliyutt9UvVugFQT6aj4q4CHaR0J/xTgBZ4Aer/BVETiov2WpVprblkqWuYKWdTrx/6q9dY1FfWElY53A6SiiHrspml6aF0Ipu3xWlpveRORBBDuLUuHlRRFveeVv+IMsirfDGpvLPgadUe+FNVjSeyk290AqUiLt0jCSJRrwsnMiluW8jfdQf6W+SG3Db9uGMuXP0PohVQlUWmAYnJTYZeEkAjXhFNB51uRvJ4mVj0/D4DJZ8/HkeEMuV9fnTKxkce/XwUhivrmGTuZNk0D40SsEPHMcyLRZvU14VQSj1uWjP1aMFaMaS3qXVTM3EPFrJo+v7aI9J967GIpK68Jp6JY3rJk89Sx7a7tIbeFM7mMiMRHWIXdMIwWoMcJgk3TzIpKRJJWNI1ldMXkliW/l6LS0D/73TM+wZc9OsIoRSSWwu2xnxLTKCRtxfOacLpou2Wp89Kb0Lc51bu7F716yiu0FB7XrzhFJDbCKuymab7W03bDMAqjE46kG01jGRtTjCFMGDGVY55sfTzvnMlMKhkadk+928llDn2W5qJToxSliMRCpKu7TaH1vvXhdAy8ywKGAvrklYhpGsvY6VzEjeLwbh0s+OgkMqvfD2qvK7mFxtFXRzU+EYmNSEfFLwAqgTeBMlonq3EAv4puWJIu4r3OtoSWu+ZnFC1zBRX1vfufS8WsGhV1kSQSaWGfBHwfuB+wmaZ5J3AecG60A5P00T6N5UBNYxlvA7Y+SdEyFzlb/hjQ7skZS8WsGmoPeaybZ4pIoor0drcq0zQbDMMoAw4GME3zPcMwxkY/NEkn/b0mLJHJrHyLghXfDLlN96GLJLdIC7tpGMYPTdN8zDCMRsMwJgFNtC7nKtIvfbkmLJGxN6xn0LuHhdxWMXMP2PQzF0l2kRb2G4C/G4bxBnAP8AEQsDCMiCQem6eaomX7h9xWceIusGsaCpFUEenqbm8bhjEC2Gua5kOGYawC8k3TXBqb8ESkO10XzRk3PJ8vt+1pfzxycBYZdj+b7tgB708Iev6u48vwZw2yIHIRiaVIb3f7yDTNI9sem6b53r72L03THBft4EQktI/WlPOXV82A2wRtNvC3zw/p5+Ups9l0R/BzK6d9hHegEZc4RST+ei3s+wbG/Xzfw0mGYTzSZZf8ff+Ff9AM69aecTjsAf9PZcmWa+c4HQ572L8n/cmzr8eMpZ5icjjsvPfJdh54/pOg57UV9ZennBnydWuP+DueohOxEftFIvr7c022393+iHeuVv3O6z2Nn17/vk3TXG8YRh1QBNggaGnlGuD8cA9ot9twu61fLMLlSp8VopMlV6ezY+CW251LTk5ORM/vS579PWYs9BST1+fnkRc/Dfm8+w/8CWNyNga1/6XiCi646kHy4jgYMVo/12T53Y2GeOWakdnx7+2VjRw+dDCOOP5u6D2NvXCnlP0fAMMw1pumeWN/Dujz+ampaejPS/SLw2HH5cqmpqYRrze1B/MnW64NDR2/F1VV9TQ19bjuULv+5NnXY8ZSTzGZW6rZvWdvwP5XFi/g5KJlQa+ztOJk/rD5cgAOWLWVA0fHb+bn/v5ck+13tz/imetHa8p56pWOsz03PPY+Re7P+c7JBkdOiO18EXpP+8/lyg7rLECkg+duNAzjUOASYDSwA3jSNM3lkbyOx2P9m+r1+hIijnhIllw7/wH0Jea+Pqe353cdpDZ+ZGxvxesppspORf2KkQ9w6pDgZRzWNxzAT764N6Btd83euP4O9Pe9jMZzk02sc11hlrNgyWq8nsDpmytrm3jg+U/iNhmU3tPYi3Tw3InAK8A/gbXAWOBNwzC+bZrmKzGIT8RSK8xyFpauCxik5s5zMifCVdKipWBgFicN/hdXjfpDyO2nr3gx9PO0iE5a8/n8LCxd1+M+i0rXcVhJkeaPSAGRjqG5BbjINM1n2xoMwzgfuJHWgi+SMtp6OF1V1TaxYMnquE93m1G1nOlfnMz0UcHbuivooEV0BNZuqe5xoSVo7bmv3VLNhFHuOEUlsRJpYZ8ALO7SthjoOlJeJKklUg/Hvncrg94+KOS22SsX4/FnhtzWRovoSHV9R1F3ZDg5/PzQZ3w67yfJK9LCXknrHPGdh+VOBMqjFpFIArCyh+PztQ40G5Dhp/id0LPFvVn8IX8q3Y3H39197K099QssumQgiSXcSzG6ZJMaIi3sjwMvGYZxC63Lto4Ffgn8scdniSSZzj0Xr6eJVc/PA2Dy2fNxZDhD7hcNK8xynl76Kdvu2h5ye830d3GNns7kqnruKvH2OPNcrAf5SfIYP7IAd56zxy+rumSTOiIt7L8DcoDfAkOATcDDwF1RjkvEUlb0cFaY5ZyyeRynHBy87c4NP2XS1y5nan5HD95utwWdLdD1UQnFbrcxZ2ZJyDEjbXTJJnWEVdgNwzjGNM13TdP0Adfv+08kZcW7h1P49kRO2bs5qP357afz5x0/AOCz0nUceeB+UTmepJ8pxhDmzp4YdJeHLtmknnB77EsBVywDEUkk8erh5H1yEQO++ltQ+2Nv53LDS/lMPvu7OPb9lVbWNmFurmL6oIH9OqakrynGEA4rKYrrvAwSf+EWdr3rknbaejhPLw0s7tHo4WSX3cvAL28Mal9dexC/WHsb5MDhISZqrq5r7vMxRSD0JRxJLeEWduvn2RSxwBRjCBNGTOWYJ1sfzztnMpNKhva5h5NV/gr5q+YEtfuxccaKJb0+v2Cg1k0XkZ6FW9hzDcPY0NMOpmkeEIV4RBJO5yJuFPfttGVGzSrcHxwbclvFrBp8Pj/ute/1ek3fKFZPS0R6Fm5hbwZuimUgIqnI3rSTQW+ND7mtYmYV2Byt+2nUsohESbiFvcU0zT/HNBKRVOJtpOj10CPYd319G/6MvKB2jVoWkWjQ4DmRaPL7KSrND7lp94zV+LKLe3y6Ri2LSH+FW9j/EtMoRFJA0bLQd4RWHbkMT8HUsF9Ho5ZFpD/CKuymaV4e60BEktWgN0djb6kMaq+Z+ChNQ8+zICIRSWeRTikrIvu4Pj4P566lQe31Y66lYdxvLIhIRESFXSRiOV/eQm7ZnUHtzYNmsufw4FnkRETiSYVdJExnTG4MuYyqL8PF7q9vtSAiEZFgKuwivXDu+aDbZVQrZtXEORoRkZ6psIt0w1FnUrj8yJDbKmZWg80e54hERHqnwi7Sha2lmsFvhr7fvOKEneDIiXNEycfn61hewtxczaSSbN2LLxInKuwibfzebu9Fn3HHEBa+/AnZKuq9WmGWB6yIN3/xKga7y5ij2fNE4kLnEkWAbXdtp/jd4UHt5Qc/w/DrhlG2S9+Bw7HCLGfBktVU1QUuZlNV28SCJatZYZZbFJlI+lBhl7RW/M7+IQfG1ZXcSsWsGva6vxb/oJKUz+dnYem6HvdZVLou4DS9iESfuiGSlvL/802yqt4Kam8aciY1k5+yIKLkt3ZLdY/LzgJU1jaxdku1pswViSEVdkkruWuvJ2fT/UHtvowCdn99swURpY7q+o6i7shwcvj5f+h1PxGJPhV2SQvO7X/F9Vnwkgde53Aqj/vCgohST0GuM6r7iUjfqLBL0vL5/KzdUk1tYwsjh+YzzD0gaJ/Mqvco+M8pIZ+/ecZOsrM1yj1axo8swJ3n7PF0fGFe6zK0IhI7KuySlFaY5SwsXRdQRArznFyw75Yqe0MZg96dHPK5w68bCthYvjxOwaYJu93GnJklLFiyutt9LphZovvZRWJMo+Il6bTfUtWlZ1hZ28QTf/+AomWukEW94oRyNs/YCaiwxMoUYwhzZ0/EnRd4ur0wz8nc2RN1H7tIHKjHLkmlu1uq7Hj5+5Rvh3zOruPX488q2veoIYbRCbQW98NKili7pZrq+iYKcltPv6unLhIflhT2jAzrThQ4HPaA/6eyZMu1c5wOhz3k78kXGyuDeuovTzkz5OvtmfEBvryDcUR4jEhjiqdkek8njh3U5+cmU579lS65pkueYH2ucS/sdrsNtzs33ocN4nJlWx1C3CRLrk5nR4/O7c4lJyd4YFtLWVX7v7sr6Detu56vnf4jji8e0adj9Gf/eEmW97S/0iVPSJ9c0yVPsC7XuBd2n89PTY11p0MdDjsuVzY1NY14vT7L4oiHZMu1oaHj96Kqqp6mpuAZyjJtfu6dcC0luV8GbXtsy8X8vfxbAMyy+amqqu/TMfqzf6wl23vaV+mSJ6RPrumSJ8QuV5crO6yzAJacivd4rH9TvV5fQsQRD8mSa+c/gFAxD/xiHtO3Pg5dTviU7jqB32+6uv1xYZ6TscPyQ+bc2zH6u3+8JFIssZQueUL65JoueYJ1uWrwnCS8AVseI2/N/wS1b24cydzPHwhq1y1VIpLOVNglYWXufoOCld8Kue3/ir/cNzq+033sLicXnKilQUUkvamwS8IZW+Sh+J39Q26rmLkHbDamQPstVZ1nntPKYSKS7lTYJWHYvPUhl1AFqDhxN9gzA9rsdhsTRrnJyLDjdudSVVWvwi4iaU+FXazn8zD4tUHYCC7Ku762EX9moQVBiYgkJxV2sY7fj/v96WTUfRa0qXL6Cry5JRYEJSKS3FTYxRJ5n1zMgK9eCGqvnPYR3oGGBRGJiKQGFXaJq5z1t5K74Y6g9uop/6SlcIYFEYmIpBYVdokL57a/4Pr8iqD2momP0zT0HAsiEhFJTSrsElOZu1+nYGXwnO51426gccxPLYhIRCS1qbBLTDhqV1P4/vSg9sZh36Xu4D9YEFGrzrfDmZurmVSSrVnqRCSlqLBLVNn3bmfQ2xOC2lvyj6T6qNcsiKjDCrOcp5eubn88f/EqBrvLmDNTs9WJSOpQYZeosHlqGPxG8DKpPkceu7++BWzWrsG8wixnwZLVeD2Ba7lX1TaxYMlq5s6eqOIuIilBhV36x9dC0WuDQm6qOOErcFi/9rLP5983r3z3FpWu47CSIp2WF5Gkp8IufeP34373MDIaNwRt2nV8Gf6s0MXeCmu3VFNV29TjPpW1TazdUs2EUe44RSUiEhsq7BIx5/a/4vrs8qD2GXcMYeHLn5CdlWNBVN2rru8o6o4MJ4efH3rwXuf9RESSlQq7hC137a/J2fT7oPZNxvNMP+NqCyIKT0GuM6r7iYgkMhV26dWALY+Tt2ZeUPu024ewuTKD11+fYkFU4Rs/sgB3nrPH0/GFeU7GjyyIY1QiIrFh7VBlSWhZFa9StMwVVNRvetnF8OuGsbkyOb4X2u025szseUGZC2aWaOCciKQEFXYJklHzX4qWucj/b+BUr40jfsjmGTt55K2BFkXWd1OMIcydPRF3XuDp9sI8p251E5GUkhxdLokLe+NmBr0zMai92X0ce454pfVBY0Oco4qeKcYQDispYu2WaqrrmyjIbT39rp66iKQSFXbB1lLN4DeLg9p9WUXsPm6d5ZPLRJPdbovoljZNQSsiyUaFPZ35mil6bXDITRUnVoA9vFHiqVr8NAWtiCSj1OmKSfj8fgrfmhCyqO/62kYqZtWEXdQBbnrio/Z/z1+8iuseeo8VZnlUQrVK2xS0VXWhp6BN9vxEJHWpsKcAn8/Pmk1VvP/5TtZsqgroQXeVv3I2RaX5OJq2B7TvnvEJFbNq8GcWRnz8qvrUKn7hTkHb089ZRMQqOhWf5FaY5SwsXRdwj7Y7z8mcmSVMPXj/9rbcNT8jZ8sfg55fddQbePJjcx96ss6/riloRSSZqbAnsbbTxV219ZjtDjsnFb6Me8U1QfvsOfRZmotOjfiYH6+tCHvfZC1+moJWRJKZCnuS6u108dH573NS2ZlQFtheO+Fu9o68rE/HXGGW8/DLnwe1p1rx0xS0IpLMVNiTVHeni8fnrOWeA38W1N5QfCX1xm19Pl44151DScbipyloRSSZqbAnqc49Ya+niarXr2L5L4IHq+3OPQH7cS/h8fj6dbxwrjt3lazFr20K2lCXOdpoCloRSVQaFZ+k2nrCeY4a/jn1vKCi/lXTEE5fsYTtBz8bleP15ZR6Mhc/TUErIslKPfYkNX7YAF6ecmbIbbNXLsbjz6TQ5eSgAwZRs6f/08BGckq9MM/JBSkwiYumoBWRZGRJYc/IsO5EgcNhD/h/0vH7yH9tFPaWqqBNp3/4V3Dktj++8JQJOOy2qOR60JhCCvOcVFT13HM/89gxnHnsAXEtfrF+TyeOHRST1+2LpP/9DVO65Anpk2u65AnW5xr3wm6323C7c3vfMcZcrmyrQ4jczlJ4fVZQ85G37Mf2PQ4mn52BAxhckM2l35rI9EnDgOjleunsQ7jtT+/2uM87n+7kojMOwWFBrzYp39M+Spdc0yVPSJ9c0yVPsC7XuBd2n89PTY11K4Q5HHZcrmxqahrxevs3oCxeHHs+JnvtjWTuei2gveaY96jNGMf26w4F4NJvHsR+g/Mxit3Y7TZqahqjmqvd1/tr7Kpu5INVWzlwdOQz2PVVMr6nfZUuuaZLnpA+uaZLnhC7XF2u7LDOAlhyKr6/I7Sjwev1JUQcPXHUryP3y5txlr8IgN+WycsfO5hfmsefX/yU7OwcvJ2WUZ1iFJGdnYPP5w+Y7jRaue6u2RvwePLZ83FkBF97312z15KfbTK8p9GSLrmmS56QPrmmS55gXa4aPJeA7Hu3krP+dwzY8Vdsfi9+bDQNPY/dw+dx+bWzLYtLE7eIiCQ+FfYEYmveTU7ZPWRvfRSbr3WQWlPRN6gf+2u8eQcH9M6tMH5kAe6BPRftZL13XUQkVaiwJwCbp5bsTQ+SvelB7N5aAJrdM6gfdwOegqkWR9fBbrdx7tfH8uaT3e+TzPeui4ikAhV2K3n3kr31cXLK7sbeshuAlrxDqR/3G1oGnQi2xCuQh40vCtmeKveui4gkOxV2K/g8DNixiJwNt+PYuxUAT8446sf9muYh3wJbctznOe+cyez12jVxi4hIAlFhjye/n6zyl8hdfzMZ9WsB8DqH0XDAL9g77DtgT663wyguIDs7x+owRESkk+SqJEksc/cb5H55E5k1KwHwZRbSMPqnNI78ITjSZ8IGERGJrZQo7D6fP2Hn885bfRkDdjzT/tjvyKVh1JU0jroKf4bLwshERCQVJX1hX2GWs7B0XcCSou48J3MsHsiVs+EOctffGtDW6D6B+kmP4s8KPQBNRESkv5JjlFY3VpjlLFiyOmid8KraJhYsWc0KM3h98lhz7niGomWuoKJ+9aICKg5eqKIuIiIxlbSF3efzs7B0XY/7LCpdFzC1aixlVr5F0TIXrtWXBbRXn0gD4gAAC1RJREFUF/+M4dcN44WVsRlk1jk/c3N13PIVEZHElLSn4tduqQ7qqXdVWdvE2i3VTBjljlkcjrovKFwePInM3qHnUzvxERobG4C/xOTYK8xynl66uv3x/MWrGOwus/wyhIiIWCdpC3t1fUdR93qaWPX8PCB4YZLO+0WTvWkng94aH9Te4jqM6qn/jskxO/t4bQWPLV2P1xP6MsTc2ROZevD+MY9DREQSS9IWdssWJPHUUfTGsKBmvz2bXSdsB5sjusfrpPNp9r8uW0dPV1IWla7jyAP3i1ksIiKSmJK2sI8fWYA7z9nj6fioLkji81D0Wug1xitO2AmO2E7U0vW0e93elpBLpraprG3C3FzF9EEDYxqXiIgklqQt7Ha7jTkzS1iwZHW3+0RlQRK/H/fyI9tniuts1/Hr4zLKvW30f9fT7gCODCeHn/+HkM+rrmuOdWgiIpJgknZUPMAUYwhzZ08MWkq0MM/J3NkT+z2AzLXqQopK84OKeuX0FVTMqolLUQ9n9H93CgZmRTkaERFJdEnbY28zxRjChBFTOebJ1sfzzpnMpJKh/eqp53z5W3LL7g5qrzriVTzuaX1+3b4IZ/R/KIV5Tozi2N0NICIiiSnpCzsQUMSN4r5PJztg65/J++KqoPaaQ56gaf9v9zm+/ug8qr+n0+5daV10EZH0lBKFvb8yd5VS8PFZQe11Jb+lcfRPLIioQ6Sj+mO9LnrXCXEmlWTrC4SISAJJ68LuqP2EwvdnBLU3Dr+YuoN+b0FEwcIZ/Z+Xk8l5J46jcOCAmC6AowlxREQSX1IPnuuz+i24lw4MKuotBdOomFWTMEUdOkb/9+TCkw2mHzyUCaPcMS3qC5aspqouceblFxGRYGlV2G0te3AvHQh/Lw5o92W6qZhZTfWRr1oUWc/aR//nxWb0f28SbV5+ERHpXnqcivc1U/Ta4JCbKk4oB8eAOAcUuSnGEA4rKbJk3flEmZdfRER6l9qF3e+n8J1DcOzdHLSp+sRNtNiTqwjZ7TZLCme4I/NjNS+/iIiEL2ULu+vjc3Hu+r+g9j3HfUL+iEPwV9WDx2dBZMnHsnn5RUQkYilX2As23IBr+8NB7VVHvYYn/0gyMtJqWEFUxH1efhER6bOUqXInHdzItru2BxX1PZP/SsWsGjz5R1oUWfILZ2S+JsQREUkMSV/YbU1f4f7yZzxxUVVAe51xBxWzamgecrpFkaUWq0fmi4hIeJL+VHz+x98ms/aT9scNI39M/YQ7LYwodVk5Ml9ERMKT1IW9sbGB519ez/j9nEw89xns+59odUgpz6qR+SIiEp6kLuwAt/wjH4Dll04j2+JYRERErGZJYY/WyHSHwx7w73Bet+05nZ8bS32JMdrHjleuVkmXPCF9ck2XPCF9ck2XPMH6XONe2O12G253blRey+nsuLbrdueSk5MT9nNdrvj07/sTY7TEK1erpUuekD65pkuekD65pkueYF2ucS/sPp+fmpqGqLxWQ0PH61RV1dPU1Ptc5Q6HHZcrm5qaRrze2E9Q05cYoyXeuVolXfKE9Mk1XfKE9Mk1XfKE2OXqcmWHdRbAklPxnijN+Nb5B+b1+iJ63Uj376uWFm/7vz8vq2RSiTPuo8jjlavV0iVPSJ9c0yVPSJ9c0yVPsC7XpB88l8i0frmIiMRb6o9isIjWLxcRESuosMeA1i8XERGrJHVh71wYzc3VCVMoI1m/XEREJJqS9hp7Il+/1vrlIiJilaTssSf69WutXy4iIlZJusKeDNev29Yv74nWLxcRkVhIusKeDNevtX65iIhYJemusSfL9eu29csXlq4L+CJSmOfkggQYByAiIqkp6Qp7Ml2/1vrlIiISb0lX2NuuX/d0Oj6Rrl9r/XIREYmnpLvGruvXIiIi3Uu6wg4d16+7jjwvzHMyd/ZEXb8WEZG0lXSn4tvo+rWIiEiwpC3soOvXIiIiXSXlqXgREREJTYVdREQkhaiwi4iIpBAVdhERkRSiwi4iIpJCVNhFRERSiM3vj+vypo1+v3+AlUuqAjgcdrxen6UxxEu65JoueUL65JoueUL65JoueUJscrXbbdhstr1Adk/7xbuwVwNOYEc8DyoiIpIChgJNQI+LocS7sIuIiEgM6Rq7iIhIClFhFxERSSEq7CIiIilEhV1ERCSFqLCLxJlhGOOsjkFEUldSL9sqEk+GYfwR+O6+hxlAFtDQaZdTTdN8u5fXmA/kAT8M43gzgf8zTTMqf6eGYZjAb0zTfDaMfb8OPAXkA9eapvlIOHHu+9KyDhhpmubWbvYfu++1jwd+ARxlmubpEScU+Jrv7Ivhlm62/x/wK9M0V/TnOCLJQIVdJEymaf4Y+DGAYRgXATeapjk6wpcpAvZGN7LwmKZpRLD7hcCHpml+OwahPA1cb5qmB7g5Bq8fyk+B5wzDONQ0zZY4HVPEEirsIlFkGIYD+DmtPfJBwBpae4qlhmHcBJy3b7/DTNOcYhjGscBvAQMoBD4B5pqm+VEvx5kJPAa8D5wC3AI8CtxLa094KFAFPGCa5h37nrMV+F/TNP+yr4f77337HgpsBn5tmuYLhmEsAb657zl1tPbap/clzhBxfwvIM03z9X2PbwGONk1zpmEYPwS+t++1LwC8wN+BK0zT9BiGkQncAFwEuICPgStN0/x038uXGIaxDDgS2A1cZ5rm3wBM0/zMMIztwMVAt2cfRFKBrrGLRNdNwI+As2gt7POBVwzDONw0zRuAZ4E/7yvqucBLwDPACGAwrQX2zjCPNYrWIlgEPAzcte91pgADae2l3m4Yxuhunn8ZMJfWQv134BHDMLJM05zdKc6BwIB+xtnZFcDCHrYfB2wF9ge+ReuljzP3bbsBOBeYCbiBd4GXDcNo+xw7GbhuXz5/AZ4wDKNz52XRvuOLpDQVdpHougS41TTN/5qm6TFN8xn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